diff --git a/.DS_Store b/.DS_Store new file mode 100644 index 0000000..660a29e Binary files /dev/null and b/.DS_Store differ diff --git "a/2.1 An\303\241lise de Dados em Python/DataVisualizationAnswers.ipynb" "b/2.1 An\303\241lise de Dados em Python/DataVisualizationAnswers.ipynb" new file mode 100644 index 0000000..4d7fd83 --- /dev/null +++ "b/2.1 An\303\241lise de Dados em Python/DataVisualizationAnswers.ipynb" @@ -0,0 +1,1736 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Visualização de dados para tomada de decisão" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![](https://media.giphy.com/media/zw69pUViBZCZW/giphy.gif)" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "import re\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/bahbbc/anaconda3/lib/python3.6/site-packages/IPython/core/interactiveshell.py:2698: DtypeWarning: Columns (31,83,86,87,98,99,109,116,123,124,127,129,130,164) have mixed types. Specify dtype option on import or set low_memory=False.\n", + " interactivity=interactivity, compiler=compiler, result=result)\n" + ] + } + ], + "source": [ + "df = pd.read_csv('kaggle-survey-2017/multipleChoiceResponses.csv', encoding=\"ISO-8859-1\")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "exchange = pd.read_csv('kaggle-survey-2017/conversionRates.csv', encoding=\"ISO-8859-1\", low_memory=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "df = pd.merge(left=df, right=exchange, how='left', \n", + " left_on='CompensationCurrency', right_on='originCountry')" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['GenderSelect', 'Country', 'Age', 'EmploymentStatus', 'StudentStatus',\n", + " 'LearningDataScience', 'CodeWriter', 'CareerSwitcher',\n", + " 'CurrentJobTitleSelect', 'TitleFit',\n", + " ...\n", + " 'JobFactorCompanyFunding', 'JobFactorImpact', 'JobFactorRemote',\n", + " 'JobFactorIndustry', 'JobFactorLeaderReputation', 'JobFactorDiversity',\n", + " 'JobFactorPublishingOpportunity', 'Unnamed: 0', 'originCountry',\n", + " 'exchangeRate'],\n", + " dtype='object', length=231)" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(16716, 231)" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Histogramas" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Vamos analisar a idade dos cientistas de dados dessa pesquisa. Qual a idade média? Quantos anos tem a pessoa mais velha dessa pesquisa? " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Para conseguir usar o `countplot` vamos transformar `Age` para inteiro para poder enxergar os numeros melhor" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "df['Age'] = df['Age'].fillna(0).astype(int)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Vamos ver um histograma da idade dos participantes" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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WivL1SaL77Kfuvh3RRbNhztM1l29PtI43IlppW+c2byOu9Y2JwL43UW6KY3sc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\nQmCC\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "_ = sns.countplot(x = 'Age', data=df)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Ficou horrível...\n", + "\n", + "Vamos adicionar o titulo e aumentar o gráfico" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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AfwMnVdX6iZ41NDRUIyMjuzCtJEmSJEnSniXJiqoammzctDbC9Kuqa4CM0/2r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\n7bLHNm7jjo/dN+q+w1Yd0HIaSZIkSZKkPUfrTaUkS4DL+kpHAB+g9+b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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.subplots(figsize=(20,15))\n", + "plot = sns.countplot(y=\"Age\", data=df).set_title(\"Count of respondents by age\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "E se eu não quiser um eixo x mais limpo? Só para ver a distribuição em si?" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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ZTjO738yuX2C9wIJFx+Maj0/n3Rg1V0fmPtmF+AAA5Cuf0DXbiJXL85xeSV3Oucsk/aWk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\nVdDBXOk6D9jg7hsBzOxpYD7QP+iaD3wrXH4W+LE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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.subplots(figsize=(10,8))\n", + "_ = sns.distplot(df['Age']).set_title(\"Count of respondents by age\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "E para remover a curva de tendencia?" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "_ = sns.distplot(df['Age'], kde=False).set_title(\"Count of respondents by age\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Nota**: Distplot não aceita Nulos. O grande número de pessoas que ficaram com idade zero na verdade são pessoas que não preencheram. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Desafio 1\n", + "\n", + "Ao invés de substituir os valores nulos pelo número zero, substitua-os pelo valor médio da idade no dataset. Plot a idade novamente. Além disso, troque as cores do gráfico. Para isso use [o guia de paletas do seaborn](https://seaborn.pydata.org/tutorial/color_palettes.html#palette-tutorial).\n", + "\n", + "![monstros_sa](https://media.giphy.com/media/zxxXYJqTlpBnO/giphy.gif)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Como seria o mesmo histograma usando apenas matplotlib?" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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HLRn21CS3dvfRSc5Ncs60/ANJju/uhyQ5KcnvVNWmlZo8AMB6scierhOS7Ojua7r7s0ku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\n6AIAGEB0AQAMILoAAAb4/xC1h9zadYS/AAAAAElFTkSuQmCC\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.subplots(figsize=(10,8))\n", + "_ = plt.hist(df['Age'], normed=True, alpha=0.5)\n", + "_ = plt.title(\"Count of respondents by age\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Quais são as áreas de graduação dos cientistas de dados?" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5,1,'Count of respondents by major')" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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UtHreZ4l8XloUj5mZtT0nq9ZhRMS/IuIPFTadSxpBGw10qqOdCcDTwDOkBHh0Lv8C+E/g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\nraTtJN1T0u6R9O6S7ypJI2vKvVI+h0uaLGm8pMclXVd2zTo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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.countplot(y=\"MajorSelect\", data=df, palette=\"Greens_d\").set_title(\"Count of respondents by major\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Para ficar mais facil de ver podemos ordenar as barras" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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0E2nGehhwe63Ma6+6poMmM7M24mDVzNpVRGzX0X2oJyJOqJ/LzMzag9esmpmZ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\nA33HDl0FuCFRAAAAAElFTkSuQmCC\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "_ = sns.countplot(y=\"MajorSelect\", data=df, palette=\"Greens_d\", order=df['MajorSelect'].value_counts().index) \\\n", + ".set_title(\"Count of respondents by major\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Agora ficou bem mais fácil de tirar conclusões sobre os cursos.\n", + "\n", + "A maioria dos cientistas de dados estudou ciência da computação, matemática ou engenharia." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "E se trocarmos os y por um x?" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Qual o maior grau de educação dos cientistas de dados?" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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k6QtqLLc68EpEvAcQEa9ExPMAknaRNE3STEmXSeqWy+dI+rWkiZIekrSFpJGS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\n7VRhP/SUdE+OeaakPQv753FJl0h6VNI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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "_ = sns.countplot(y=\"FormalEducation\", data=df, palette=\"Greens_d\", order=df['FormalEducation'].value_counts().index) \\\n", + ".set_title(\"Count of respondents by formal education\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Desafio 2\n", + "##### Quais os empregos anteriores dos cientistas de dados?\n", + "\n", + "Para fazer esse desafio você vai consultar a coluna `PastJobTitlesSelect`. Veja que essa coluna possui varios valores. Você precisará criar um método para reduzir a granularidade dessa coluna." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Dica: A solução fica mais fácil se você usar [expressões regulares](https://pt.wikipedia.org/wiki/Express%C3%A3o_regular). Para testá-las use [esse site](https://regexr.com/)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![finn_mathematical](https://media.giphy.com/media/ccQ8MSKkjHE2c/giphy.gif)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "I haven't started working yet 1454\n", + "Other 1043\n", + "Researcher 786\n", + "Software Developer/Software Engineer 784\n", + "Engineer 497\n", + "Programmer,Software Developer/Software Engineer 379\n", + "Programmer 372\n", + "Data Analyst 353\n", + "Business Analyst 340\n", + "Data Scientist 210\n", + "Business Analyst,Data Analyst 194\n", + "Engineer,Programmer,Software Developer/Software Engineer 143\n", + "Engineer,Researcher 138\n", + "Researcher,Other 131\n", + "Statistician 125\n", + "Computer Scientist 121\n", + "Business Analyst,Other 119\n", + "Data Scientist,Researcher 109\n", + "Researcher,Software Developer/Software Engineer 105\n", + 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+ }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['PastJobTitlesSelect'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "df['PastJobTitlesSelect'] = df['PastJobTitlesSelect'].fillna('NULL')" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "past_job_category = []\n", + "for s in df['PastJobTitlesSelect']:\n", + " past_job_category.append(re.sub(r'(?=,).*', '', s))\n", + " \n", + "df['new_job_category'] = past_job_category" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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xkvbM259WR8hmreOdKmmcpAckLS1pM2BX4IxcfuX8nvfK+5yWR8TGS/p1pfJN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\nQD9JYyT9SNIU4ApJ+0t6RClw8xFJuxZq/WHet/M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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "_ = sns.countplot(y=\"new_job_category\", data=df, palette=\"Greens_d\", order=df['new_job_category'].value_counts().index) \\\n", + ".set_title(\"Count of respondents by previous job category\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Será que o trabalho remoto impacta no tempo que um cientista passa coletando dados?" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Sometimes 2440\n", + "Rarely 1772\n", + "Never 823\n", + "Most of the time 684\n", + "Always 352\n", + "Don't know 26\n", + "Name: RemoteWork, dtype: int64" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['RemoteWork'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "30.0 1070\n", + "50.0 1054\n", + "20.0 985\n", + "40.0 967\n", + "10.0 610\n", + "60.0 603\n", + "0.0 464\n", + "70.0 347\n", + "25.0 258\n", + "80.0 187\n", + "35.0 174\n", + "15.0 153\n", + "5.0 144\n", + "45.0 96\n", + "65.0 82\n", + "55.0 65\n", + "75.0 63\n", + "90.0 61\n", + "100.0 34\n", + "85.0 16\n", + "1.0 7\n", + "95.0 6\n", + "2.0 6\n", + "33.0 5\n", + "3.0 4\n", + "8.0 4\n", + "7.0 4\n", + "12.0 3\n", + "28.0 3\n", + "34.0 3\n", + " ... \n", + "53.0 2\n", + "78.0 2\n", + "22.0 2\n", + "72.0 2\n", + "6.0 2\n", + "49.0 2\n", + "66.0 2\n", + "56.0 1\n", + "64.0 1\n", + "16.0 1\n", + "4.0 1\n", + "59.0 1\n", + "42.0 1\n", + "24.0 1\n", + "77.0 1\n", + "92.0 1\n", + "13.0 1\n", + "39.0 1\n", + "36.0 1\n", + "17.0 1\n", + "9.0 1\n", + "94.0 1\n", + "47.0 1\n", + "87.0 1\n", + "23.0 1\n", + "44.0 1\n", + "73.0 1\n", + "29.0 1\n", + "31.0 1\n", + "11.0 1\n", + "Name: TimeGatheringData, Length: 67, dtype: int64" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['TimeGatheringData'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "df['TimeGatheringData'] = df['TimeGatheringData'].fillna(-1)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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jR+M7+0HSp0xF1EvpJdRhYUT973vSJ92JITsbAMHZmahl31G4+NMW1wRwGziQ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\n4s/qKavPeM5rstfwzbFv0Kg1zImfQ5x33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" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### E se eu quiser saber se o tempo que a pessoa passa gerando visualizações impacta no tempo que ela gasta em visualização em um projeto?" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Python,R 125\n", + "R 123\n", + "Python 118\n", + "Python,R,SQL 64\n", + "R,SQL 61\n", + "Python,TensorFlow 49\n", + "Jupyter notebooks,Python,R 38\n", + "MATLAB/Octave 37\n", + "C/C++,Python 37\n", + "Jupyter notebooks,Python,TensorFlow 37\n", + "Python,SQL 35\n", + "Other 35\n", + "Jupyter notebooks,Python 34\n", + "Jupyter notebooks,Python,R,SQL 33\n", + "MATLAB/Octave,Python 31\n", + "SQL 30\n", + "Jupyter notebooks,Python,SQL 24\n", + "R,SAS Base,SQL 23\n", + "MATLAB/Octave,Python,TensorFlow 22\n", + "Amazon Web services,Python,R 22\n", + "MATLAB/Octave,Python,R 21\n", + "Jupyter notebooks,Python,R,SQL,Tableau 19\n", 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Excel Data Mining,Minitab,SQL 1\n", + "Hadoop/Hive/Pig,Microsoft Excel Data Mining,Oracle Data Mining/ Oracle R Enterprise,Python,R,RapidMiner (commercial version),Spark / MLlib,SQL 1\n", + "C/C++,Microsoft Azure Machine Learning,Microsoft Excel Data Mining,Microsoft R Server (Formerly Revolution Analytics),Microsoft SQL Server Data Mining,Python,R,SQL 1\n", + "IBM Cognos,IBM SPSS Modeler,IBM SPSS Statistics,IBM Watson / Waton Analytics,KNIME (free version),NoSQL,Python,R 1\n", + "Amazon Web services,Python,QlikView,R,Spark / MLlib,SQL 1\n", + "Java,MATLAB/Octave,Microsoft Excel Data Mining,Python,R 1\n", + "Python,R,SAP BusinessObjects Predictive Analytics,SQL 1\n", + "Jupyter notebooks,Python,R,SAS JMP,SQL 1\n", + "Java,R,SQL,Other 1\n", + "Name: WorkToolsSelect, Length: 5248, dtype: int64" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['WorkToolsSelect'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "df['WorkDataVisualizations'] = df['WorkDataVisualizations'].fillna('NULL')\n", + "work_visualization = []\n", + "for s in df['WorkDataVisualizations']:\n", + " work_visualization.append(re.sub(' of projects', '', s))\n", + " \n", + "df['work_visualization'] = work_visualization" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "NULL 9837\n", + "10-25% 1265\n", + "76-99% 1255\n", + "100% 1253\n", + "51-75% 1160\n", + "26-50% 918\n", + "Less than 10% 868\n", + "None 160\n", + "Name: work_visualization, dtype: int64" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['work_visualization'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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r7QZjzAIgfv+H9ra5ISDNWnvLwfp09JozERERka4S6jVnofxaM9Fae2Kb5VeM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\nNz7vNNbafwP/3v/vrcCUcM4jIiIiEm5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FW7lSMx844LNnY6s8N3p41rXCs2VgBmA5eNBD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\nWk3gCN89zxVRnZXbn0XEBxKTrNRUaomk7p79THxmGDqD8rcR3TnId88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Qa9R8sqXQpRmt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\nHome5l/iVMOPz4y1lULJ4ATg5dNe5vy3z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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.subplots(figsize=(10,8))\n", + "sns.swarmplot(x=\"work_visualization\", y=\"TimeVisualizing\", data=df, \n", + " order=['100%', '51-75%', '26-50%', '10-25%', 'Less than 10%', 'None', 'NULL'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Desafio 3\n", + "\n", + "Fazer um Heatmap mostrando a [correlação](https://pt.wikipedia.org/wiki/Coeficiente_de_correla%C3%A7%C3%A3o_de_Pearson) dos tempos das etapas de um projeto de Data Science. \n", + "\n", + "São elas:\n", + "\n", + " - TimeGatheringData\n", + " - TimeVisualizing\n", + " - TimeModelBuilding\n", + " - TimeFindingInsights\n", + " - TimeProduction\n", + "\n", + "Siga os passos [desse tutorial](https://seaborn.pydata.org/examples/many_pairwise_correlations.html). Atenção! Use apenas essas variáveis." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![crazy_finn](https://media.giphy.com/media/KI9oNS4JBemyI/giphy.gif)" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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ggX0a749fAwAAuMrqPT3KcZGaNm2amTkAAICP8IkRqVatWjl8UGpqqlvCAAAA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\n5swZDR8+XAUFBYqIiNC2bdv0+eefu/0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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from string import ascii_letters\n", + "import numpy as np\n", + "import pandas as pd\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "\n", + "sns.set(style=\"white\")\n", + "\n", + "# Generate a large random dataset\n", + "rs = np.random.RandomState(33)\n", + "d = df[['TimeGatheringData', 'TimeVisualizing', 'TimeModelBuilding', 'TimeFindingInsights', 'TimeProduction']]\n", + "# Compute the correlation matrix\n", + "corr = d.corr()\n", + "\n", + "# Generate a mask for the upper triangle\n", + "mask = np.zeros_like(corr, dtype=np.bool)\n", + "mask[np.triu_indices_from(mask)] = True\n", + "\n", + "# Set up the matplotlib figure\n", + "f, ax = plt.subplots(figsize=(11, 9))\n", + "\n", + "# Generate a custom diverging colormap\n", + "cmap = sns.diverging_palette(220, 10, as_cmap=True)\n", + "\n", + "# Draw the heatmap with the mask and correct aspect ratio\n", + "sns.heatmap(corr, mask=mask, cmap=cmap, vmax=.3, center=0,\n", + " square=True, linewidths=.5, cbar_kws={\"shrink\": .5})" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### E se eu quiser ter uma ideia do tempo que é investido criando-se modelos?" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Boxplot" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "_ = sns.boxplot(df['TimeModelBuilding']).set_title(\"Time spent by building models\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Eu também posso usar boxplots com variáveis categóricas..." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### E Se eu quiser verificar o salário das pessoas por gênero?" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Primeiramente, vamos usar apenas as pessoas que tenham valores de salário que é representado pela variável `CompensationAmount`" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "money_index = df['CompensationAmount'].notnull()\n", + "compensation_check = df[money_index]" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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AgeLearningCategorySelftTaughtLearningCategoryOnlineCoursesLearningCategoryWorkLearningCategoryUniversityLearningCategoryKaggleLearningCategoryOtherTimeGatheringDataTimeModelBuildingTimeProductionTimeVisualizingTimeFindingInsightsTimeOtherSelectUnnamed: 0exchangeRate
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std11.30769125.78718126.86084018.99677823.67691711.0726809.35788623.50933516.16595812.25793211.72294512.97484612.15713711.3333610.486712
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75%37.00000050.00000040.00000025.00000030.00000010.0000000.00000030.00000030.00000015.00000020.00000020.0000000.0000007.0000001.000000
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"\n", + " LearningCategoryOther TimeGatheringData TimeModelBuilding \\\n", + "count 13094.000000 16716.000000 7528.000000 \n", + "mean 1.795940 15.732472 21.268066 \n", + "std 9.357886 23.509335 16.165958 \n", + "min 0.000000 -1.000000 0.000000 \n", + "25% 0.000000 -1.000000 10.000000 \n", + "50% 0.000000 -1.000000 20.000000 \n", + "75% 0.000000 30.000000 30.000000 \n", + "max 100.000000 100.000000 100.000000 \n", + "\n", + " TimeProduction TimeVisualizing TimeFindingInsights TimeOtherSelect \\\n", + "count 7517.000000 7529.000000 7523.000000 7513.000000 \n", + "mean 10.806372 13.869372 13.094776 2.396247 \n", + "std 12.257932 11.722945 12.974846 12.157137 \n", + "min 0.000000 0.000000 0.000000 0.000000 \n", + "25% 0.000000 5.000000 5.000000 0.000000 \n", + "50% 10.000000 10.000000 10.000000 0.000000 \n", + "75% 15.000000 20.000000 20.000000 0.000000 \n", + "max 100.000000 100.000000 303.000000 100.000000 \n", + "\n", + " Unnamed: 0 exchangeRate \n", + "count 4529.000000 4529.000000 \n", + "mean 7.075293 0.703953 \n", + "std 11.333361 0.486712 \n", + "min 1.000000 0.000030 \n", + "25% 1.000000 0.058444 \n", + "50% 2.000000 1.000000 \n", + "75% 7.000000 1.000000 \n", + "max 86.000000 2.652053 " + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Male 4432\n", + "Female 725\n", + "A different identity 32\n", + "Non-binary, genderqueer, or gender non-conforming 29\n", + "Name: GenderSelect, dtype: int64" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "compensation_check['GenderSelect'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "df['exchangeRate'] = df['exchangeRate'].fillna(0)\n", + "df['CompensationAmount'] = df['CompensationAmount'].fillna(0)" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "df['CompensationAmount'] = df.CompensationAmount.apply(lambda x: 0 if (pd.isnull(x) or (x=='-') or (x==0))\n", + " else float(x.replace(',',''))) \n", + "df['CompensationAmount'] = df['CompensationAmount']*df['exchangeRate']\n", + "df = df[df['CompensationAmount']>0]" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "count 4.333000e+03\n", + "mean 6.651893e+06\n", + "std 4.298948e+08\n", + "min 6.000000e-02\n", + "25% 2.152487e+04\n", + "50% 5.390140e+04\n", + "75% 9.627720e+04\n", + "max 2.829740e+10\n", + "Name: CompensationAmount, dtype: float64" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['CompensationAmount'].describe()" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.boxplot(x=\"GenderSelect\", y=\"CompensationAmount\",\n", + " data=df)\n", + "sns.despine(offset=10, trim=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Tem um outlier nesse conj. de dados que está atrapalhando a nossa visualização... Podemos removê-lo usando boolean indexes. Vamos usar pessoas que ganham até 2000000." + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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0yNllSRlUh52gmrIDJI7liM/mihUr2LFjhwOqqbhevXrx1FNPObsM+QM1OrS/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\nSZMmERAQYKslOzubUaNGlXn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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.boxplot(x=\"GenderSelect\", y=\"CompensationAmount\",\n", + " data=df[df['CompensationAmount'] < 2000000])\n", + "sns.despine(offset=10, trim=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Agora vamos colocar os titulos em 45º" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([0, 1, 2, 3]), )" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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C0aNHq7s2uUFamUxEpO6oUFB7eHgA0LZtW2JjY2ncuHG1FiWV07VrV1xcXHBxcdH9aRGR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\nG1VVVcyePRuAEydOUFVVhd/vJzk5mRdffDH0M5g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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.boxplot(x=\"GenderSelect\", y=\"CompensationAmount\",\n", + " data=df[df['CompensationAmount'] < 2000000])\n", + "sns.despine(offset=10, trim=True)\n", + "plt.xticks(rotation=15)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Scatterplots (Dispersão)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### E se eu quiser ver a distribuição da probabilidade das pessoas que aprenderam algo (da profissão) no Trabalho e que foram auto didatas? " + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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/0JnTV199hePHj6OwsBCvvPIKunXrhjlz5kCj0aBFixZYtGgR7Fi5fGD4ev/E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\n9e3kyZNwdXVFSEgIZsyYgYEDB5pV/zp37gy1Wg2NRoOSkhJYWlqaRf8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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.jointplot(x=\"LearningCategorySelftTaught\", y=\"LearningCategoryWork\", data=df);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "E o que eu posso fazer se eu quiser ver as probabilidades de todas as categorias `LearningCategory(...)` todas juntas?" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/bahbbc/anaconda3/lib/python3.6/site-packages/statsmodels/nonparametric/kde.py:454: RuntimeWarning: invalid value encountered in greater\n", + " X = X[np.logical_and(X>clip[0], Xclip[0], X" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.kdeplot(df['LearningCategorySelftTaught'])\n", + "sns.kdeplot(df['LearningCategoryWork'])\n", + "sns.kdeplot(df['LearningCategoryOnlineCourses'])\n", + "sns.kdeplot(df['LearningCategoryUniversity'])\n", + "#sns.kdeplot(df['LearningCategoryKaggle'])\n", + "sns.kdeplot(df['LearningCategoryOther'])\n", + "plt.legend();" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Desafio 4\n", + "\n", + "Existem ainda várias perguntas que ficaram sem resposta, do tipo:\n", + "\n", + " 1. Quais os maiores desafios de um cientista de dados? (`WorkChallengesSelect`)\n", + " - Quais os algoritmos mais utilizados em data science? (`WorkAlgorithmsSelect`)\n", + " - Quais os setores que mais empregam cientistas de dados? (`EmployerIndustry`)\n", + " - Qual o tamanho das empresas que contratam cientistas de dados? (`EmployerSize`)\n", + " \n", + "Organizem-se em duplas para resolver esses desafios." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![challenge](https://media.giphy.com/media/d4zHnLjdy48Cc/giphy.gif)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Gráficos mais complexos" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " - Uma das análises desse dataset no blog do kaggle -> http://blog.kaggle.com/2017/10/30/introducing-kaggles-state-of-data-science-machine-learning-report-2017/\n", + " - Joyplots -> http://blog.kaggle.com/2017/07/20/joyplots-tutorial-with-insect-data/\n", + " - Plots de mapas -> http://blog.kaggle.com/2016/11/30/seventeen-ways-to-map-data-in-kaggle-kernels/" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.4" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/2.1 An\303\241lise de Dados em Python/PandasStructuredData-Answers.ipynb" "b/2.1 An\303\241lise de Dados em Python/PandasStructuredData-Answers.ipynb" new file mode 100644 index 0000000..b526d7e --- /dev/null +++ "b/2.1 An\303\241lise de Dados em Python/PandasStructuredData-Answers.ipynb" @@ -0,0 +1,8051 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Análise de dados estruturados" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import pandas as pd" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![panda](https://media.giphy.com/media/HDR31jsQUPqQo/giphy.gif)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Criar um dataframe a partir de um dicionário" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "dict = {\"country\": [\"Brazil\", \"Russia\", \"India\", \"China\", \"South Africa\"],\n", + " \"capital\": [\"Brasilia\", \"Moscow\", \"New Dehli\", \"Beijing\", \"Pretoria\"],\n", + " \"area\": [8.516, 17.10, 3.286, 9.597, 1.221],\n", + " \"population\": [200.4, 143.5, 1252, 1357, 52.98] }" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Transformar o dicionário em um dataframe\n", + "brics = pd.DataFrame(dict)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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areacapitalcountrypopulation
08.516BrasiliaBrazil200.40
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" + ], + "text/plain": [ + " area capital country population\n", + "0 8.516 Brasilia Brazil 200.40\n", + "1 17.100 Moscow Russia 143.50\n", + "2 3.286 New Dehli India 1252.00\n", + "3 9.597 Beijing China 1357.00\n", + "4 1.221 Pretoria South Africa 52.98" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Ver os primeiros registros desse dataframe\n", + "brics.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Importar um csv com o pandas" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Vamos utilizar os dados que o Kaggle lançou no ano de 2017 sobre Cientistas de Dados e Data Science. São 5 datasets diferentes:\n", + "\n", + " - **schema.csv**: a CSV file with survey schema. This schema includes the questions that correspond to each column name in both the multipleChoiceResponses.csv and freeformResponses.csv.\n", + " - **multipleChoiceResponses.csv**: Respondents' answers to multiple choice and ranking questions. These are non-randomized and thus a single row does correspond to all of a single user's answers. \n", + " -**freeformResponses.csv:** Respondents' freeform answers to Kaggle's survey questions. These responses are randomized within a column, so that reading across a single row does not give a single user's answers.\n", + " - **conversionRates.csv**: Currency conversion rates (to USD) as accessed from the R package \"quantmod\" on September 14, 2017\n", + " - **RespondentTypeREADME.txt**: This is a schema for decoding the responses in the \"Asked\" column of the schema.csv file." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# Carregue o dataset multipleChoiceResponses com o pandas \n", + "multiple_choice = pd.read_csv('kaggle-survey-2017/multipleChoiceResponses.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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GenderSelectCountryAgeEmploymentStatusStudentStatusLearningDataScienceCodeWriterCareerSwitcherCurrentJobTitleSelectTitleFit...JobFactorExperienceLevelJobFactorDepartmentJobFactorTitleJobFactorCompanyFundingJobFactorImpactJobFactorRemoteJobFactorIndustryJobFactorLeaderReputationJobFactorDiversityJobFactorPublishingOpportunity
0Non-binary, genderqueer, or gender non-conformingNaNNaNEmployed full-timeNaNNaNYesNaNDBA/Database EngineerFine...NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1FemaleUnited States30.0Not employed, but looking for workNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNSomewhat importantNaNNaN
2MaleCanada28.0Not employed, but looking for workNaNNaNNaNNaNNaNNaN...Very ImportantVery ImportantVery ImportantVery ImportantVery ImportantVery ImportantVery ImportantVery ImportantVery ImportantVery Important
3MaleUnited States56.0Independent contractor, freelancer, or self-em...NaNNaNYesNaNOperations Research PractitionerPoorly...NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
4MaleTaiwan38.0Employed full-timeNaNNaNYesNaNComputer ScientistFine...NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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" + ], + "text/plain": [ + " GenderSelect Country Age \\\n", + "0 Non-binary, genderqueer, or gender non-conforming NaN NaN \n", + "1 Female United States 30.0 \n", + "2 Male Canada 28.0 \n", + "3 Male United States 56.0 \n", + "4 Male Taiwan 38.0 \n", + "\n", + " EmploymentStatus StudentStatus \\\n", + "0 Employed full-time NaN \n", + "1 Not employed, but looking for work NaN \n", + "2 Not employed, but looking for work NaN \n", + "3 Independent contractor, freelancer, or self-em... NaN \n", + "4 Employed full-time NaN \n", + "\n", + " LearningDataScience CodeWriter CareerSwitcher \\\n", + "0 NaN Yes NaN \n", + "1 NaN NaN NaN \n", + "2 NaN NaN NaN \n", + "3 NaN Yes NaN \n", + "4 NaN Yes NaN \n", + "\n", + " CurrentJobTitleSelect TitleFit ... \\\n", + "0 DBA/Database Engineer Fine ... \n", + "1 NaN NaN ... \n", + "2 NaN NaN ... \n", + "3 Operations Research Practitioner Poorly ... \n", + "4 Computer Scientist Fine ... \n", + "\n", + " JobFactorExperienceLevel JobFactorDepartment JobFactorTitle \\\n", + "0 NaN NaN NaN \n", + "1 NaN NaN NaN \n", + "2 Very Important Very Important Very Important \n", + "3 NaN NaN NaN \n", + "4 NaN NaN NaN \n", + "\n", + " JobFactorCompanyFunding JobFactorImpact JobFactorRemote JobFactorIndustry \\\n", + "0 NaN NaN NaN NaN \n", + "1 NaN NaN NaN NaN \n", + "2 Very Important Very Important Very Important Very Important \n", + "3 NaN NaN NaN NaN \n", + "4 NaN NaN NaN NaN \n", + "\n", + " JobFactorLeaderReputation JobFactorDiversity JobFactorPublishingOpportunity \n", + "0 NaN NaN NaN \n", + "1 Somewhat important NaN NaN \n", + "2 Very Important Very Important Very Important \n", + "3 NaN NaN NaN \n", + "4 NaN NaN NaN \n", + "\n", + "[5 rows x 228 columns]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Veja as primeiras linhas do dataset\n", + "multiple_choice.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(16716, 228)" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Veja a quantidade de linhas e de colunas do dataset\n", + "multiple_choice.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Existem 228 colunas!!!\n", + "![panda](https://media.giphy.com/media/14aUO0Mf7dWDXW/giphy.gif)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Vamos ver do que se tratam essas colunas. Como são MUITAS colunas precisamos alterar a configuração padrão do pandas para visualização de linhas e colunas" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "pd.set_option('max_rows', 200)\n", + "pd.set_option('max_columns', 1000)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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WorkMethodsFrequencyGBM WorkMethodsFrequencyHMMs WorkMethodsFrequencyKNN \\\n", + "0 NaN NaN NaN \n", + "1 NaN NaN NaN \n", + "2 NaN NaN NaN \n", + "3 NaN NaN NaN \n", + "4 NaN NaN Most of the time \n", + "\n", + " WorkMethodsFrequencyLiftAnalysis WorkMethodsFrequencyLogisticRegression \\\n", + "0 NaN NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 NaN Sometimes \n", + "4 NaN Sometimes \n", + "\n", + " WorkMethodsFrequencyMLN WorkMethodsFrequencyNaiveBayes \\\n", + "0 NaN NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 Often Sometimes \n", + "4 NaN Sometimes \n", + "\n", + " WorkMethodsFrequencyNLP WorkMethodsFrequencyNeuralNetworks \\\n", + "0 NaN Sometimes \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 NaN Sometimes \n", + "4 NaN Most of the time \n", + "\n", + " WorkMethodsFrequencyPCA WorkMethodsFrequencyPrescriptiveModeling \\\n", + "0 Often NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 NaN NaN \n", + "4 Sometimes NaN \n", + "\n", + " WorkMethodsFrequencyRandomForests WorkMethodsFrequencyRecommenderSystems \\\n", + "0 Most of the time NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 Sometimes NaN \n", + "4 NaN NaN \n", + "\n", + " WorkMethodsFrequencyRNNs WorkMethodsFrequencySegmentation \\\n", + "0 NaN NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 NaN NaN \n", + "4 Sometimes Often \n", + "\n", + " WorkMethodsFrequencySimulation WorkMethodsFrequencySVMs \\\n", + "0 NaN NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 Often NaN \n", + "4 NaN Most of the time \n", + "\n", + " WorkMethodsFrequencyTextAnalysis WorkMethodsFrequencyTimeSeriesAnalysis \\\n", + "0 NaN NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 NaN Often \n", + "4 NaN Sometimes \n", + "\n", + " WorkMethodsFrequencySelect1 WorkMethodsFrequencySelect2 \\\n", + "0 NaN NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 NaN NaN \n", + "4 NaN NaN \n", + "\n", + " WorkMethodsFrequencySelect3 TimeGatheringData TimeModelBuilding \\\n", + "0 NaN 0.0 100.0 \n", + "1 NaN NaN NaN \n", + "2 NaN NaN NaN \n", + "3 NaN 50.0 20.0 \n", + "4 NaN 30.0 20.0 \n", + "\n", + " TimeProduction TimeVisualizing TimeFindingInsights TimeOtherSelect \\\n", + "0 0.0 0.0 0.0 0.0 \n", + "1 NaN NaN NaN NaN \n", + "2 NaN NaN NaN NaN \n", + "3 0.0 10.0 20.0 0.0 \n", + "4 15.0 15.0 20.0 0.0 \n", + "\n", + " AlgorithmUnderstandingLevel \\\n", + "0 Enough to explain the algorithm to someone non... \n", + "1 NaN \n", + "2 NaN \n", + "3 Enough to refine and innovate on the algorithm \n", + "4 Enough to refine and innovate on the algorithm \n", + "\n", + " WorkChallengesSelect \\\n", + "0 Company politics / Lack of management/financia... \n", + "1 NaN \n", + "2 NaN \n", + "3 Company politics / Lack of management/financia... \n", + "4 Company politics / Lack of management/financia... \n", + "\n", + " WorkChallengeFrequencyPolitics WorkChallengeFrequencyUnusedResults \\\n", + "0 Rarely NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 Often Often \n", + "4 Often Sometimes \n", + "\n", + " WorkChallengeFrequencyUnusefulInstrumenting \\\n", + "0 NaN \n", + "1 NaN \n", + "2 NaN \n", + "3 Often \n", + "4 NaN \n", + "\n", + " WorkChallengeFrequencyDeployment WorkChallengeFrequencyDirtyData \\\n", + "0 NaN NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 Often Often \n", + "4 NaN NaN \n", + "\n", + " WorkChallengeFrequencyExplaining WorkChallengeFrequencyPass \\\n", + "0 NaN NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 Often NaN \n", + "4 NaN NaN \n", + "\n", + " WorkChallengeFrequencyIntegration WorkChallengeFrequencyTalent \\\n", + "0 NaN NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 Often Often \n", + "4 NaN Sometimes \n", + "\n", + " WorkChallengeFrequencyDataFunds WorkChallengeFrequencyDomainExpertise \\\n", + "0 NaN NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 Often Most of the time \n", + "4 Sometimes Sometimes \n", + "\n", + " WorkChallengeFrequencyML WorkChallengeFrequencyTools \\\n", + "0 NaN NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 Often Often \n", + "4 NaN NaN \n", + "\n", + " WorkChallengeFrequencyExpectations WorkChallengeFrequencyITCoordination \\\n", + "0 NaN NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 Often NaN \n", + "4 NaN Sometimes \n", + "\n", + " WorkChallengeFrequencyHiringFunds WorkChallengeFrequencyPrivacy \\\n", + "0 NaN Often \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 Often Often \n", + "4 NaN Most of the time \n", + "\n", + " WorkChallengeFrequencyScaling WorkChallengeFrequencyEnvironments \\\n", + "0 Most of the time NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 Often Often \n", + "4 NaN Sometimes \n", + "\n", + " WorkChallengeFrequencyClarity WorkChallengeFrequencyDataAccess \\\n", + "0 NaN NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 Often Often \n", + "4 NaN NaN \n", + "\n", + " WorkChallengeFrequencyOtherSelect WorkDataVisualizations \\\n", + "0 NaN 26-50% of projects \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 NaN 100% of projects \n", + "4 NaN 10-25% of projects \n", + "\n", + " WorkInternalVsExternalTools WorkMLTeamSeatSelect \\\n", + "0 Do not know Standalone Team \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 Entirely internal Standalone Team \n", + "4 Approximately half internal and half external Business Department \n", + "\n", + " WorkDatasets \\\n", + "0 NaN \n", + "1 NaN \n", + "2 NaN \n", + "3 Electricity data sets from government and states \n", + "4 NaN \n", + "\n", + " WorkDatasetsChallenge \\\n", + "0 NaN \n", + "1 NaN \n", + "2 NaN \n", + "3 Everything is custom, there is never a tool th... \n", + "4 NaN \n", + "\n", + " WorkDataStorage \\\n", + "0 Document-oriented (e.g. MongoDB/Elasticsearch)... \n", + "1 NaN \n", + "2 NaN \n", + "3 Column-oriented relational (e.g. KDB/MariaDB),... \n", + "4 Flat files not in a database or cache (e.g. CS... \n", + "\n", + " WorkDataSharing WorkDataSourcing \\\n", + "0 Company Developed Platform,I don't typically s... NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 Company Developed Platform,Email NaN \n", + "4 Company Developed Platform NaN \n", + "\n", + " WorkCodeSharing RemoteWork \\\n", + "0 Mercurial,Subversion,Other Always \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 Generic cloud file sharing software (Dropbox/B... NaN \n", + "4 Git Rarely \n", + "\n", + " CompensationAmount CompensationCurrency \\\n", + "0 NaN NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 250,000 USD \n", + "4 NaN NaN \n", + "\n", + " SalaryChange JobSatisfaction \\\n", + "0 I am not currently employed 5 \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 Has increased 20% or more 10 - Highly Satisfied \n", + "4 I do not want to share information about my sa... 2 \n", + "\n", + " JobSearchResource JobHuntTime \\\n", + "0 NaN NaN \n", + "1 NaN NaN \n", + "2 Asking friends, family members, or former coll... 1-2 \n", + "3 NaN NaN \n", + "4 NaN NaN \n", + "\n", + " JobFactorLearning JobFactorSalary JobFactorOffice JobFactorLanguages \\\n", + "0 NaN NaN NaN NaN \n", + "1 NaN NaN NaN NaN \n", + "2 Very Important Very Important Very Important Very Important \n", + "3 NaN NaN NaN NaN \n", + "4 NaN NaN NaN NaN \n", + "\n", + " JobFactorCommute JobFactorManagement JobFactorExperienceLevel \\\n", + "0 NaN NaN NaN \n", + "1 NaN NaN NaN \n", + "2 Very Important Very Important Very Important \n", + "3 NaN NaN NaN \n", + "4 NaN NaN NaN \n", + "\n", + " JobFactorDepartment JobFactorTitle JobFactorCompanyFunding JobFactorImpact \\\n", + "0 NaN NaN NaN NaN \n", + "1 NaN NaN NaN NaN \n", + "2 Very Important Very Important Very Important Very Important \n", + "3 NaN NaN NaN NaN \n", + "4 NaN NaN NaN NaN \n", + "\n", + " JobFactorRemote JobFactorIndustry JobFactorLeaderReputation \\\n", + "0 NaN NaN NaN \n", + "1 NaN NaN Somewhat important \n", + "2 Very Important Very Important Very Important \n", + "3 NaN NaN NaN \n", + "4 NaN NaN NaN \n", + "\n", + " JobFactorDiversity JobFactorPublishingOpportunity \n", + "0 NaN NaN \n", + "1 NaN NaN \n", + "2 Very Important Very Important \n", + "3 NaN NaN \n", + "4 NaN NaN " + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "multiple_choice.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Podemos ver só o nome das colunas também utilizando o `columns`. Para ficar mais fácil de visualizar, ao invés de retornar o array, podemos transformar esse dado em uma Series." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0 GenderSelect\n", + "1 Country\n", + "2 Age\n", + "3 EmploymentStatus\n", + "4 StudentStatus\n", + "5 LearningDataScience\n", + "6 CodeWriter\n", + "7 CareerSwitcher\n", + "8 CurrentJobTitleSelect\n", + "9 TitleFit\n", + "10 CurrentEmployerType\n", + "11 MLToolNextYearSelect\n", + "12 MLMethodNextYearSelect\n", + "13 LanguageRecommendationSelect\n", + "14 PublicDatasetsSelect\n", + "15 LearningPlatformSelect\n", + "16 LearningPlatformUsefulnessArxiv\n", + "17 LearningPlatformUsefulnessBlogs\n", + "18 LearningPlatformUsefulnessCollege\n", + "19 LearningPlatformUsefulnessCompany\n", + "20 LearningPlatformUsefulnessConferences\n", + "21 LearningPlatformUsefulnessFriends\n", + "22 LearningPlatformUsefulnessKaggle\n", + "23 LearningPlatformUsefulnessNewsletters\n", + "24 LearningPlatformUsefulnessCommunities\n", + "25 LearningPlatformUsefulnessDocumentation\n", + "26 LearningPlatformUsefulnessCourses\n", + "27 LearningPlatformUsefulnessProjects\n", + "28 LearningPlatformUsefulnessPodcasts\n", + "29 LearningPlatformUsefulnessSO\n", + "30 LearningPlatformUsefulnessTextbook\n", + "31 LearningPlatformUsefulnessTradeBook\n", + "32 LearningPlatformUsefulnessTutoring\n", + "33 LearningPlatformUsefulnessYouTube\n", + "34 BlogsPodcastsNewslettersSelect\n", + "35 LearningDataScienceTime\n", + "36 JobSkillImportanceBigData\n", + "37 JobSkillImportanceDegree\n", + "38 JobSkillImportanceStats\n", + "39 JobSkillImportanceEnterpriseTools\n", + "40 JobSkillImportancePython\n", + "41 JobSkillImportanceR\n", + "42 JobSkillImportanceSQL\n", + "43 JobSkillImportanceKaggleRanking\n", + "44 JobSkillImportanceMOOC\n", + "45 JobSkillImportanceVisualizations\n", + "46 JobSkillImportanceOtherSelect1\n", + "47 JobSkillImportanceOtherSelect2\n", + "48 JobSkillImportanceOtherSelect3\n", + "49 CoursePlatformSelect\n", + "50 HardwarePersonalProjectsSelect\n", + "51 TimeSpentStudying\n", + "52 ProveKnowledgeSelect\n", + "53 DataScienceIdentitySelect\n", + "54 FormalEducation\n", + "55 MajorSelect\n", + "56 Tenure\n", + "57 PastJobTitlesSelect\n", + "58 FirstTrainingSelect\n", + "59 LearningCategorySelftTaught\n", + "60 LearningCategoryOnlineCourses\n", + "61 LearningCategoryWork\n", + "62 LearningCategoryUniversity\n", + "63 LearningCategoryKaggle\n", + "64 LearningCategoryOther\n", + "65 MLSkillsSelect\n", + "66 MLTechniquesSelect\n", + "67 ParentsEducation\n", + "68 EmployerIndustry\n", + "69 EmployerSize\n", + "70 EmployerSizeChange\n", + "71 EmployerMLTime\n", + "72 EmployerSearchMethod\n", + "73 UniversityImportance\n", + "74 JobFunctionSelect\n", + "75 WorkHardwareSelect\n", + "76 WorkDataTypeSelect\n", + "77 WorkProductionFrequency\n", + "78 WorkDatasetSize\n", + "79 WorkAlgorithmsSelect\n", + "80 WorkToolsSelect\n", + "81 WorkToolsFrequencyAmazonML\n", + "82 WorkToolsFrequencyAWS\n", + "83 WorkToolsFrequencyAngoss\n", + "84 WorkToolsFrequencyC\n", + "85 WorkToolsFrequencyCloudera\n", + "86 WorkToolsFrequencyDataRobot\n", + "87 WorkToolsFrequencyFlume\n", + "88 WorkToolsFrequencyGCP\n", + "89 WorkToolsFrequencyHadoop\n", + "90 WorkToolsFrequencyIBMCognos\n", + "91 WorkToolsFrequencyIBMSPSSModeler\n", + "92 WorkToolsFrequencyIBMSPSSStatistics\n", + "93 WorkToolsFrequencyIBMWatson\n", + "94 WorkToolsFrequencyImpala\n", + "95 WorkToolsFrequencyJava\n", + "96 WorkToolsFrequencyJulia\n", + "97 WorkToolsFrequencyJupyter\n", + "98 WorkToolsFrequencyKNIMECommercial\n", + "99 WorkToolsFrequencyKNIMEFree\n", + " ... \n", + "128 WorkToolsFrequencyUnix\n", + "129 WorkToolsFrequencySelect1\n", + "130 WorkToolsFrequencySelect2\n", + "131 WorkFrequencySelect3\n", + "132 WorkMethodsSelect\n", + "133 WorkMethodsFrequencyA/B\n", + "134 WorkMethodsFrequencyAssociationRules\n", + "135 WorkMethodsFrequencyBayesian\n", + "136 WorkMethodsFrequencyCNNs\n", + "137 WorkMethodsFrequencyCollaborativeFiltering\n", + "138 WorkMethodsFrequencyCross-Validation\n", + "139 WorkMethodsFrequencyDataVisualization\n", + "140 WorkMethodsFrequencyDecisionTrees\n", + "141 WorkMethodsFrequencyEnsembleMethods\n", + "142 WorkMethodsFrequencyEvolutionaryApproaches\n", + "143 WorkMethodsFrequencyGANs\n", + "144 WorkMethodsFrequencyGBM\n", + "145 WorkMethodsFrequencyHMMs\n", + "146 WorkMethodsFrequencyKNN\n", + "147 WorkMethodsFrequencyLiftAnalysis\n", + "148 WorkMethodsFrequencyLogisticRegression\n", + "149 WorkMethodsFrequencyMLN\n", + "150 WorkMethodsFrequencyNaiveBayes\n", + "151 WorkMethodsFrequencyNLP\n", + "152 WorkMethodsFrequencyNeuralNetworks\n", + "153 WorkMethodsFrequencyPCA\n", + "154 WorkMethodsFrequencyPrescriptiveModeling\n", + "155 WorkMethodsFrequencyRandomForests\n", + "156 WorkMethodsFrequencyRecommenderSystems\n", + "157 WorkMethodsFrequencyRNNs\n", + "158 WorkMethodsFrequencySegmentation\n", + "159 WorkMethodsFrequencySimulation\n", + "160 WorkMethodsFrequencySVMs\n", + "161 WorkMethodsFrequencyTextAnalysis\n", + "162 WorkMethodsFrequencyTimeSeriesAnalysis\n", + "163 WorkMethodsFrequencySelect1\n", + "164 WorkMethodsFrequencySelect2\n", + "165 WorkMethodsFrequencySelect3\n", + "166 TimeGatheringData\n", + "167 TimeModelBuilding\n", + "168 TimeProduction\n", + "169 TimeVisualizing\n", + "170 TimeFindingInsights\n", + "171 TimeOtherSelect\n", + "172 AlgorithmUnderstandingLevel\n", + "173 WorkChallengesSelect\n", + "174 WorkChallengeFrequencyPolitics\n", + "175 WorkChallengeFrequencyUnusedResults\n", + "176 WorkChallengeFrequencyUnusefulInstrumenting\n", + "177 WorkChallengeFrequencyDeployment\n", + "178 WorkChallengeFrequencyDirtyData\n", + "179 WorkChallengeFrequencyExplaining\n", + "180 WorkChallengeFrequencyPass\n", + "181 WorkChallengeFrequencyIntegration\n", + "182 WorkChallengeFrequencyTalent\n", + "183 WorkChallengeFrequencyDataFunds\n", + "184 WorkChallengeFrequencyDomainExpertise\n", + "185 WorkChallengeFrequencyML\n", + "186 WorkChallengeFrequencyTools\n", + "187 WorkChallengeFrequencyExpectations\n", + "188 WorkChallengeFrequencyITCoordination\n", + "189 WorkChallengeFrequencyHiringFunds\n", + "190 WorkChallengeFrequencyPrivacy\n", + "191 WorkChallengeFrequencyScaling\n", + "192 WorkChallengeFrequencyEnvironments\n", + "193 WorkChallengeFrequencyClarity\n", + "194 WorkChallengeFrequencyDataAccess\n", + "195 WorkChallengeFrequencyOtherSelect\n", + "196 WorkDataVisualizations\n", + "197 WorkInternalVsExternalTools\n", + "198 WorkMLTeamSeatSelect\n", + "199 WorkDatasets\n", + "200 WorkDatasetsChallenge\n", + "201 WorkDataStorage\n", + "202 WorkDataSharing\n", + "203 WorkDataSourcing\n", + "204 WorkCodeSharing\n", + "205 RemoteWork\n", + "206 CompensationAmount\n", + "207 CompensationCurrency\n", + "208 SalaryChange\n", + "209 JobSatisfaction\n", + "210 JobSearchResource\n", + "211 JobHuntTime\n", + "212 JobFactorLearning\n", + "213 JobFactorSalary\n", + "214 JobFactorOffice\n", + "215 JobFactorLanguages\n", + "216 JobFactorCommute\n", + "217 JobFactorManagement\n", + "218 JobFactorExperienceLevel\n", + "219 JobFactorDepartment\n", + "220 JobFactorTitle\n", + "221 JobFactorCompanyFunding\n", + "222 JobFactorImpact\n", + "223 JobFactorRemote\n", + "224 JobFactorIndustry\n", + "225 JobFactorLeaderReputation\n", + "226 JobFactorDiversity\n", + "227 JobFactorPublishingOpportunity\n", + "Length: 228, dtype: object" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Use o columns no dataframe e coloque-o em uma Series para facilitar a visualização\n", + "pd.Series(multiple_choice.columns)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Podemos ver mais detalhes do dataset com o `info()`" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 16716 entries, 0 to 16715\n", + "Columns: 228 entries, GenderSelect to JobFactorPublishingOpportunity\n", + "dtypes: float64(13), object(215)\n", + "memory usage: 29.1+ MB\n" + ] + } + ], + "source": [ + "multiple_choice.info()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Podemos dar uma olhada nos tipos de campos que vem em cada uma das colunas númericas com um único comando" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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"execute_result" + } + ], + "source": [ + "multiple_choice.describe()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "E se eu quiser ver a quantidade de nulos no dataset todo?" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "GenderSelect 95\n", + "Country 121\n", + "Age 331\n", + "EmploymentStatus 0\n", + "StudentStatus 15436\n", + "LearningDataScience 15432\n", + "CodeWriter 3530\n", + "CareerSwitcher 13704\n", + "CurrentJobTitleSelect 4886\n", + "TitleFit 5212\n", + "CurrentEmployerType 5115\n", + "MLToolNextYearSelect 5718\n", + "MLMethodNextYearSelect 5883\n", + "LanguageRecommendationSelect 5718\n", + "PublicDatasetsSelect 5920\n", + "LearningPlatformSelect 5445\n", + "LearningPlatformUsefulnessArxiv 14325\n", + "LearningPlatformUsefulnessBlogs 11951\n", + "LearningPlatformUsefulnessCollege 13357\n", + "LearningPlatformUsefulnessCompany 15735\n", + "LearningPlatformUsefulnessConferences 14534\n", + "LearningPlatformUsefulnessFriends 15135\n", + "LearningPlatformUsefulnessKaggle 10133\n", + "LearningPlatformUsefulnessNewsletters 15627\n", + "LearningPlatformUsefulnessCommunities 15574\n", + "LearningPlatformUsefulnessDocumentation 14395\n", + "LearningPlatformUsefulnessCourses 10724\n", + "LearningPlatformUsefulnessProjects 11922\n", + "LearningPlatformUsefulnessPodcasts 15502\n", + "LearningPlatformUsefulnessSO 11076\n", + "LearningPlatformUsefulnessTextbook 12535\n", + "LearningPlatformUsefulnessTradeBook 16383\n", + "LearningPlatformUsefulnessTutoring 15290\n", + "LearningPlatformUsefulnessYouTube 11487\n", + "BlogsPodcastsNewslettersSelect 8576\n", + "LearningDataScienceTime 12367\n", + "JobSkillImportanceBigData 12760\n", + "JobSkillImportanceDegree 12807\n", + "JobSkillImportanceStats 12756\n", + "JobSkillImportanceEnterpriseTools 13022\n", + "JobSkillImportancePython 12685\n", + "JobSkillImportanceR 12772\n", + "JobSkillImportanceSQL 12824\n", + "JobSkillImportanceKaggleRanking 12846\n", + "JobSkillImportanceMOOC 12884\n", + "JobSkillImportanceVisualizations 12849\n", + "JobSkillImportanceOtherSelect1 16358\n", + "JobSkillImportanceOtherSelect2 16544\n", + "JobSkillImportanceOtherSelect3 16603\n", + "CoursePlatformSelect 14420\n", + "HardwarePersonalProjectsSelect 12510\n", + "TimeSpentStudying 12688\n", + "ProveKnowledgeSelect 12555\n", + "DataScienceIdentitySelect 4045\n", + "FormalEducation 1701\n", + "MajorSelect 3435\n", + "Tenure 3184\n", + "PastJobTitlesSelect 2524\n", + "FirstTrainingSelect 2004\n", + "LearningCategorySelftTaught 3607\n", + "LearningCategoryOnlineCourses 3590\n", + "LearningCategoryWork 3605\n", + "LearningCategoryUniversity 3594\n", + "LearningCategoryKaggle 3590\n", + "LearningCategoryOther 3622\n", + "MLSkillsSelect 3963\n", + "MLTechniquesSelect 4132\n", + "ParentsEducation 4048\n", + "EmployerIndustry 5970\n", + "EmployerSize 8945\n", + "EmployerSizeChange 9159\n", + "EmployerMLTime 9065\n", + "EmployerSearchMethod 8988\n", + "UniversityImportance 8618\n", + "JobFunctionSelect 8735\n", + "WorkHardwareSelect 8698\n", + "WorkDataTypeSelect 8692\n", + "WorkProductionFrequency 9594\n", + "WorkDatasetSize 9628\n", + "WorkAlgorithmsSelect 9415\n", + "WorkToolsSelect 8761\n", + "WorkToolsFrequencyAmazonML 16317\n", + "WorkToolsFrequencyAWS 14896\n", + "WorkToolsFrequencyAngoss 16694\n", + "WorkToolsFrequencyC 15215\n", + "WorkToolsFrequencyCloudera 16277\n", + "WorkToolsFrequencyDataRobot 16653\n", + "WorkToolsFrequencyFlume 16575\n", + "WorkToolsFrequencyGCP 16192\n", + "WorkToolsFrequencyHadoop 15379\n", + "WorkToolsFrequencyIBMCognos 16561\n", + "WorkToolsFrequencyIBMSPSSModeler 16450\n", + "WorkToolsFrequencyIBMSPSSStatistics 16258\n", + "WorkToolsFrequencyIBMWatson 16473\n", + "WorkToolsFrequencyImpala 16464\n", + "WorkToolsFrequencyJava 15311\n", + "WorkToolsFrequencyJulia 16536\n", + "WorkToolsFrequencyJupyter 13547\n", + "WorkToolsFrequencyKNIMECommercial 16680\n", + "WorkToolsFrequencyKNIMEFree 16449\n", + " ... \n", + "WorkToolsFrequencyUnix 14888\n", + "WorkToolsFrequencySelect1 16030\n", + "WorkToolsFrequencySelect2 16581\n", + "WorkFrequencySelect3 16635\n", + "WorkMethodsSelect 8943\n", + "WorkMethodsFrequencyA/B 14846\n", + "WorkMethodsFrequencyAssociationRules 15620\n", + "WorkMethodsFrequencyBayesian 14871\n", + "WorkMethodsFrequencyCNNs 15363\n", + "WorkMethodsFrequencyCollaborativeFiltering 15955\n", + "WorkMethodsFrequencyCross-Validation 12956\n", + "WorkMethodsFrequencyDataVisualization 11810\n", + "WorkMethodsFrequencyDecisionTrees 13134\n", + "WorkMethodsFrequencyEnsembleMethods 14733\n", + "WorkMethodsFrequencyEvolutionaryApproaches 16302\n", + "WorkMethodsFrequencyGANs 16486\n", + "WorkMethodsFrequencyGBM 15211\n", + "WorkMethodsFrequencyHMMs 16317\n", + "WorkMethodsFrequencyKNN 14171\n", + "WorkMethodsFrequencyLiftAnalysis 16093\n", + "WorkMethodsFrequencyLogisticRegression 12544\n", + "WorkMethodsFrequencyMLN 16474\n", + "WorkMethodsFrequencyNaiveBayes 14910\n", + "WorkMethodsFrequencyNLP 14840\n", + "WorkMethodsFrequencyNeuralNetworks 14006\n", + "WorkMethodsFrequencyPCA 14014\n", + "WorkMethodsFrequencyPrescriptiveModeling 15899\n", + "WorkMethodsFrequencyRandomForests 13360\n", + "WorkMethodsFrequencyRecommenderSystems 15604\n", + "WorkMethodsFrequencyRNNs 15868\n", + "WorkMethodsFrequencySegmentation 14739\n", + "WorkMethodsFrequencySimulation 15365\n", + "WorkMethodsFrequencySVMs 14813\n", + "WorkMethodsFrequencyTextAnalysis 14385\n", + "WorkMethodsFrequencyTimeSeriesAnalysis 13644\n", + "WorkMethodsFrequencySelect1 16483\n", + "WorkMethodsFrequencySelect2 16677\n", + "WorkMethodsFrequencySelect3 16623\n", + "TimeGatheringData 9186\n", + "TimeModelBuilding 9188\n", + "TimeProduction 9199\n", + "TimeVisualizing 9187\n", + "TimeFindingInsights 9193\n", + "TimeOtherSelect 9203\n", + "AlgorithmUnderstandingLevel 9306\n", + "WorkChallengesSelect 9340\n", + "WorkChallengeFrequencyPolitics 14036\n", + "WorkChallengeFrequencyUnusedResults 14972\n", + "WorkChallengeFrequencyUnusefulInstrumenting 16077\n", + "WorkChallengeFrequencyDeployment 15869\n", + "WorkChallengeFrequencyDirtyData 13165\n", + "WorkChallengeFrequencyExplaining 15131\n", + "WorkChallengeFrequencyPass 16292\n", + "WorkChallengeFrequencyIntegration 15744\n", + "WorkChallengeFrequencyTalent 13720\n", + "WorkChallengeFrequencyDataFunds 15764\n", + "WorkChallengeFrequencyDomainExpertise 15308\n", + "WorkChallengeFrequencyML 15951\n", + "WorkChallengeFrequencyTools 15537\n", + "WorkChallengeFrequencyExpectations 15582\n", + "WorkChallengeFrequencyITCoordination 15547\n", + "WorkChallengeFrequencyHiringFunds 15429\n", + "WorkChallengeFrequencyPrivacy 15294\n", + "WorkChallengeFrequencyScaling 15883\n", + "WorkChallengeFrequencyEnvironments 15463\n", + "WorkChallengeFrequencyClarity 14537\n", + "WorkChallengeFrequencyDataAccess 14526\n", + "WorkChallengeFrequencyOtherSelect 16439\n", + "WorkDataVisualizations 9837\n", + "WorkInternalVsExternalTools 9959\n", + "WorkMLTeamSeatSelect 10028\n", + "WorkDatasets 14530\n", + "WorkDatasetsChallenge 14150\n", + "WorkDataStorage 10201\n", + "WorkDataSharing 10214\n", + "WorkDataSourcing 16337\n", + "WorkCodeSharing 10513\n", + "RemoteWork 10619\n", + "CompensationAmount 11492\n", + "CompensationCurrency 12186\n", + "SalaryChange 10327\n", + "JobSatisfaction 10039\n", + "JobSearchResource 12977\n", + "JobHuntTime 12985\n", + "JobFactorLearning 13165\n", + "JobFactorSalary 13231\n", + "JobFactorOffice 13248\n", + "JobFactorLanguages 13241\n", + "JobFactorCommute 13269\n", + "JobFactorManagement 13282\n", + "JobFactorExperienceLevel 13279\n", + "JobFactorDepartment 13300\n", + "JobFactorTitle 13302\n", + "JobFactorCompanyFunding 13305\n", + "JobFactorImpact 13322\n", + "JobFactorRemote 13292\n", + "JobFactorIndustry 13307\n", + "JobFactorLeaderReputation 13315\n", + "JobFactorDiversity 13306\n", + "JobFactorPublishingOpportunity 13292\n", + "Length: 228, dtype: int64" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "multiple_choice.isnull().sum()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "E se eu quiser fazer a porcentagem de nulos?" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "GenderSelect 0.005683\n", + "Country 0.007239\n", + "Age 0.019801\n", + "EmploymentStatus 0.000000\n", + "StudentStatus 0.923427\n", + "LearningDataScience 0.923187\n", + "CodeWriter 0.211175\n", + "CareerSwitcher 0.819813\n", + "CurrentJobTitleSelect 0.292295\n", + "TitleFit 0.311797\n", + "CurrentEmployerType 0.305994\n", + "MLToolNextYearSelect 0.342067\n", + "MLMethodNextYearSelect 0.351938\n", + "LanguageRecommendationSelect 0.342067\n", + "PublicDatasetsSelect 0.354152\n", + "LearningPlatformSelect 0.325736\n", + "LearningPlatformUsefulnessArxiv 0.856963\n", + "LearningPlatformUsefulnessBlogs 0.714944\n", + "LearningPlatformUsefulnessCollege 0.799055\n", + "LearningPlatformUsefulnessCompany 0.941314\n", + "LearningPlatformUsefulnessConferences 0.869466\n", + "LearningPlatformUsefulnessFriends 0.905420\n", + "LearningPlatformUsefulnessKaggle 0.606186\n", + "LearningPlatformUsefulnessNewsletters 0.934853\n", + "LearningPlatformUsefulnessCommunities 0.931682\n", + "LearningPlatformUsefulnessDocumentation 0.861151\n", + "LearningPlatformUsefulnessCourses 0.641541\n", + "LearningPlatformUsefulnessProjects 0.713209\n", + "LearningPlatformUsefulnessPodcasts 0.927375\n", + "LearningPlatformUsefulnessSO 0.662599\n", + "LearningPlatformUsefulnessTextbook 0.749880\n", + "LearningPlatformUsefulnessTradeBook 0.980079\n", + "LearningPlatformUsefulnessTutoring 0.914693\n", + "LearningPlatformUsefulnessYouTube 0.687186\n", + "BlogsPodcastsNewslettersSelect 0.513041\n", + "LearningDataScienceTime 0.739830\n", + "JobSkillImportanceBigData 0.763341\n", + "JobSkillImportanceDegree 0.766152\n", + "JobSkillImportanceStats 0.763101\n", + "JobSkillImportanceEnterpriseTools 0.779014\n", + "JobSkillImportancePython 0.758854\n", + "JobSkillImportanceR 0.764058\n", + "JobSkillImportanceSQL 0.767169\n", + "JobSkillImportanceKaggleRanking 0.768485\n", + "JobSkillImportanceMOOC 0.770759\n", + "JobSkillImportanceVisualizations 0.768665\n", + "JobSkillImportanceOtherSelect1 0.978583\n", + "JobSkillImportanceOtherSelect2 0.989710\n", + "JobSkillImportanceOtherSelect3 0.993240\n", + "CoursePlatformSelect 0.862647\n", + "HardwarePersonalProjectsSelect 0.748385\n", + "TimeSpentStudying 0.759033\n", + "ProveKnowledgeSelect 0.751077\n", + "DataScienceIdentitySelect 0.241984\n", + "FormalEducation 0.101759\n", + "MajorSelect 0.205492\n", + "Tenure 0.190476\n", + "PastJobTitlesSelect 0.150993\n", + "FirstTrainingSelect 0.119885\n", + "LearningCategorySelftTaught 0.215781\n", + "LearningCategoryOnlineCourses 0.214764\n", + "LearningCategoryWork 0.215662\n", + "LearningCategoryUniversity 0.215004\n", + "LearningCategoryKaggle 0.214764\n", + "LearningCategoryOther 0.216679\n", + "MLSkillsSelect 0.237078\n", + "MLTechniquesSelect 0.247188\n", + "ParentsEducation 0.242163\n", + "EmployerIndustry 0.357143\n", + "EmployerSize 0.535116\n", + "EmployerSizeChange 0.547918\n", + "EmployerMLTime 0.542295\n", + "EmployerSearchMethod 0.537688\n", + "UniversityImportance 0.515554\n", + "JobFunctionSelect 0.522553\n", + "WorkHardwareSelect 0.520340\n", + "WorkDataTypeSelect 0.519981\n", + "WorkProductionFrequency 0.573941\n", + "WorkDatasetSize 0.575975\n", + "WorkAlgorithmsSelect 0.563233\n", + "WorkToolsSelect 0.524109\n", + "WorkToolsFrequencyAmazonML 0.976131\n", + "WorkToolsFrequencyAWS 0.891122\n", + "WorkToolsFrequencyAngoss 0.998684\n", + "WorkToolsFrequencyC 0.910206\n", + "WorkToolsFrequencyCloudera 0.973738\n", + "WorkToolsFrequencyDataRobot 0.996231\n", + "WorkToolsFrequencyFlume 0.991565\n", + "WorkToolsFrequencyGCP 0.968653\n", + "WorkToolsFrequencyHadoop 0.920017\n", + "WorkToolsFrequencyIBMCognos 0.990727\n", + "WorkToolsFrequencyIBMSPSSModeler 0.984087\n", + "WorkToolsFrequencyIBMSPSSStatistics 0.972601\n", + "WorkToolsFrequencyIBMWatson 0.985463\n", + "WorkToolsFrequencyImpala 0.984925\n", + "WorkToolsFrequencyJava 0.915949\n", + "WorkToolsFrequencyJulia 0.989232\n", + "WorkToolsFrequencyJupyter 0.810421\n", + "WorkToolsFrequencyKNIMECommercial 0.997846\n", + "WorkToolsFrequencyKNIMEFree 0.984027\n", + " ... \n", + "WorkToolsFrequencyUnix 0.890644\n", + "WorkToolsFrequencySelect1 0.958961\n", + "WorkToolsFrequencySelect2 0.991924\n", + "WorkFrequencySelect3 0.995154\n", + "WorkMethodsSelect 0.534996\n", + "WorkMethodsFrequencyA/B 0.888131\n", + "WorkMethodsFrequencyAssociationRules 0.934434\n", + "WorkMethodsFrequencyBayesian 0.889627\n", + "WorkMethodsFrequencyCNNs 0.919060\n", + "WorkMethodsFrequencyCollaborativeFiltering 0.954475\n", + "WorkMethodsFrequencyCross-Validation 0.775066\n", + "WorkMethodsFrequencyDataVisualization 0.706509\n", + "WorkMethodsFrequencyDecisionTrees 0.785714\n", + "WorkMethodsFrequencyEnsembleMethods 0.881371\n", + "WorkMethodsFrequencyEvolutionaryApproaches 0.975233\n", + "WorkMethodsFrequencyGANs 0.986241\n", + "WorkMethodsFrequencyGBM 0.909966\n", + "WorkMethodsFrequencyHMMs 0.976131\n", + "WorkMethodsFrequencyKNN 0.847751\n", + "WorkMethodsFrequencyLiftAnalysis 0.962730\n", + "WorkMethodsFrequencyLogisticRegression 0.750419\n", + "WorkMethodsFrequencyMLN 0.985523\n", + "WorkMethodsFrequencyNaiveBayes 0.891960\n", + "WorkMethodsFrequencyNLP 0.887772\n", + "WorkMethodsFrequencyNeuralNetworks 0.837880\n", + "WorkMethodsFrequencyPCA 0.838358\n", + "WorkMethodsFrequencyPrescriptiveModeling 0.951125\n", + "WorkMethodsFrequencyRandomForests 0.799234\n", + "WorkMethodsFrequencyRecommenderSystems 0.933477\n", + "WorkMethodsFrequencyRNNs 0.949270\n", + "WorkMethodsFrequencySegmentation 0.881730\n", + "WorkMethodsFrequencySimulation 0.919179\n", + "WorkMethodsFrequencySVMs 0.886157\n", + "WorkMethodsFrequencyTextAnalysis 0.860553\n", + "WorkMethodsFrequencyTimeSeriesAnalysis 0.816224\n", + "WorkMethodsFrequencySelect1 0.986061\n", + "WorkMethodsFrequencySelect2 0.997667\n", + "WorkMethodsFrequencySelect3 0.994436\n", + "TimeGatheringData 0.549533\n", + "TimeModelBuilding 0.549653\n", + "TimeProduction 0.550311\n", + "TimeVisualizing 0.549593\n", + "TimeFindingInsights 0.549952\n", + "TimeOtherSelect 0.550550\n", + "AlgorithmUnderstandingLevel 0.556712\n", + "WorkChallengesSelect 0.558746\n", + "WorkChallengeFrequencyPolitics 0.839675\n", + "WorkChallengeFrequencyUnusedResults 0.895669\n", + "WorkChallengeFrequencyUnusefulInstrumenting 0.961773\n", + "WorkChallengeFrequencyDeployment 0.949330\n", + "WorkChallengeFrequencyDirtyData 0.787569\n", + "WorkChallengeFrequencyExplaining 0.905181\n", + "WorkChallengeFrequencyPass 0.974635\n", + "WorkChallengeFrequencyIntegration 0.941852\n", + "WorkChallengeFrequencyTalent 0.820771\n", + "WorkChallengeFrequencyDataFunds 0.943049\n", + "WorkChallengeFrequencyDomainExpertise 0.915769\n", + "WorkChallengeFrequencyML 0.954235\n", + "WorkChallengeFrequencyTools 0.929469\n", + "WorkChallengeFrequencyExpectations 0.932161\n", + "WorkChallengeFrequencyITCoordination 0.930067\n", + "WorkChallengeFrequencyHiringFunds 0.923008\n", + "WorkChallengeFrequencyPrivacy 0.914932\n", + "WorkChallengeFrequencyScaling 0.950168\n", + "WorkChallengeFrequencyEnvironments 0.925042\n", + "WorkChallengeFrequencyClarity 0.869646\n", + "WorkChallengeFrequencyDataAccess 0.868988\n", + "WorkChallengeFrequencyOtherSelect 0.983429\n", + "WorkDataVisualizations 0.588478\n", + "WorkInternalVsExternalTools 0.595777\n", + "WorkMLTeamSeatSelect 0.599904\n", + "WorkDatasets 0.869227\n", + "WorkDatasetsChallenge 0.846494\n", + "WorkDataStorage 0.610254\n", + "WorkDataSharing 0.611031\n", + "WorkDataSourcing 0.977327\n", + "WorkCodeSharing 0.628918\n", + "RemoteWork 0.635260\n", + "CompensationAmount 0.687485\n", + "CompensationCurrency 0.729002\n", + "SalaryChange 0.617791\n", + "JobSatisfaction 0.600562\n", + "JobSearchResource 0.776322\n", + "JobHuntTime 0.776801\n", + "JobFactorLearning 0.787569\n", + "JobFactorSalary 0.791517\n", + "JobFactorOffice 0.792534\n", + "JobFactorLanguages 0.792115\n", + "JobFactorCommute 0.793790\n", + "JobFactorManagement 0.794568\n", + "JobFactorExperienceLevel 0.794389\n", + "JobFactorDepartment 0.795645\n", + "JobFactorTitle 0.795765\n", + "JobFactorCompanyFunding 0.795944\n", + "JobFactorImpact 0.796961\n", + "JobFactorRemote 0.795166\n", + "JobFactorIndustry 0.796064\n", + "JobFactorLeaderReputation 0.796542\n", + "JobFactorDiversity 0.796004\n", + "JobFactorPublishingOpportunity 0.795166\n", + "Length: 228, dtype: float64" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "multiple_choice.isnull().sum() / len(multiple_choice)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Nossa quanto nulo!\n", + "![sad_panda](https://media.giphy.com/media/3e18NPUVzoxzO/giphy.gif)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "O que eu devo fazer se eu quiser ver apenas coluna `JobFactorSalary`?" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "0 NaN\n", + "1 NaN\n", + "2 Very Important\n", + "3 NaN\n", + "4 NaN\n", + "5 NaN\n", + "6 NaN\n", + "7 Very Important\n", + "8 NaN\n", + "9 NaN\n", + "10 Somewhat important\n", + "11 NaN\n", + "12 Somewhat important\n", + "13 NaN\n", + "14 NaN\n", + "15 NaN\n", + "16 NaN\n", + "17 NaN\n", + "18 Somewhat important\n", + "19 Not important\n", + "20 Somewhat important\n", + "21 NaN\n", + "22 NaN\n", + "23 NaN\n", + "24 NaN\n", + "25 NaN\n", + "26 NaN\n", + "27 NaN\n", + 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] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "multiple_choice['JobFactorSalary']" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Vamos fazer algumas operações com o pandas para contar o número de nulos que existem nessa coluna" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "13231" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "multiple_choice['JobFactorSalary'].isnull().sum()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Como eu faço se eu só quiser ver os 10 primeiros registros?" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0 NaN\n", + "1 NaN\n", + "2 Very Important\n", + "3 NaN\n", + "4 NaN\n", + "5 NaN\n", + "6 NaN\n", + "7 Very Important\n", + "8 NaN\n", + "9 NaN\n", + "Name: JobFactorSalary, dtype: object" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "multiple_choice['JobFactorSalary'][:10]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "E se eu quiser ver 2 colunas ao mesmo tempo? (E apenas essas 2 colunas)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " JobFactorSalary JobFactorLearning\n", + "0 NaN NaN\n", + "1 NaN NaN\n", + "2 Very Important Very Important\n", + "3 NaN NaN\n", + "4 NaN NaN\n", + "5 NaN NaN\n", + "6 NaN NaN\n", + "7 Very Important Very Important\n", + "8 NaN NaN\n", + "9 NaN NaN" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "multiple_choice[['JobFactorSalary', 'JobFactorLearning']][:10]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "O quanto que as pessoas dessa pesquisa estão satisfeitas com o trabalhos? Conseguimos saber isso usando só o pandas?" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "7 1448\n", + "8 1427\n", + "6 765\n", + "9 677\n", + "5 627\n", + "10 - Highly Satisfied 589\n", + "3 358\n", + "4 354\n", + "1 - Highly Dissatisfied 167\n", + "I prefer not to share 148\n", + "2 117\n", + "Name: JobSatisfaction, dtype: int64" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "multiple_choice['JobSatisfaction'].value_counts()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Percebemos com esse comando que as pessoas até que estão bastante satisfeitas." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Agora vamos olhar só as pessoas que estão Super Satisfeitas (Highly Satisfied) com o seu trabalho. Como que eu posso fazer isso?" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Filtre só quem está com o JobSatisfaction de 10. Guarde isso em uma variável pq é bastante dado\n", + "highly_satisfied = multiple_choice[multiple_choice['JobSatisfaction'] == '10 - Highly Satisfied']" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(589, 228)" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# veja o tamanho do dataset. Ele bateu com a quantidade de pessoas que estão altamente satisfeitas?\n", + "highly_satisfied.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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77MaleIsrael29.0Independent contractor, freelancer, or self-em...NaNNaNYesNaNData ScientistPerfectlySelf-employedNaNDeep learningPythonDataset aggregator/platform (i.e. Socrata/Kagg...Arxiv,Kaggle,Official documentation,Online cou...Somewhat usefulNaNNaNNaNNaNNaNVery usefulNaNNaNVery usefulVery usefulNaNNaNVery usefulNaNNaNNaNVery usefulFastML Blog,KDnuggets Blog,No Free Hunch BlogNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNMaster's degreeComputer Science3 to 5 yearsData Scientist,Software Developer/Software Eng...University courses80.00.00.00.020.00.0Recommendation Engines,Supervised Machine Lear...Bayesian Techniques,Ensemble MethodsA master's degreeFinancialNaNNaNNaNNaNVery importantAnalyze and understand data to influence produ...Laptop or Workstation and private datacentersRelational dataAlways1GBDecision Trees,Ensemble Methods,Random ForestsJava,Python,TableauNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNMost of the timeNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNMost of the timeNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNRarelyNaNNaNNaNNaNNaNNaNA/B Testing,Bayesian Techniques,Cross-Validati...SometimesNaNOftenNaNNaNMost of the timeMost of the timeMost of the timeMost of the timeNaNNaNNaNNaNNaNNaNMost of the timeNaNNaNNaNNaNNaNNaNMost of the timeNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN30.030.010.020.010.00.0Enough to code it again from scratch, albeit i...Dirty data,Explaining data science to others,L...NaNNaNNaNNaNSometimesOftenNaNNaNNaNMost of the timeNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN76-99% of projectsEntirely externalStandalone TeamNaNNaNFlat files not in a database or cache (e.g. CS...I don't typically share dataNaNBitbucketMost of the timeNaNNaNI do not want to share information about my sa...10 - Highly SatisfiedNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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Relational data \n", + "60 Basic laptop (Macbook) Text data \n", + "77 Laptop or Workstation and private datacenters Relational data \n", + "\n", + " WorkProductionFrequency WorkDatasetSize \\\n", + "3 Always 1GB \n", + "60 NaN NaN \n", + "77 Always 1GB \n", + "\n", + " WorkAlgorithmsSelect \\\n", + "3 Bayesian Techniques,Decision Trees,Random Fore... \n", + "60 Bayesian Techniques,Regression/Logistic Regres... \n", + "77 Decision Trees,Ensemble Methods,Random Forests \n", + "\n", + " WorkToolsSelect \\\n", + "3 Amazon Machine Learning,Amazon Web services,Cl... \n", + "60 C/C++,Jupyter notebooks,MATLAB/Octave,NoSQL,Py... \n", + "77 Java,Python,Tableau \n", + "\n", + " WorkToolsFrequencyAmazonML WorkToolsFrequencyAWS WorkToolsFrequencyAngoss \\\n", + "3 Rarely Often NaN \n", + "60 NaN NaN NaN \n", + "77 NaN NaN NaN \n", + "\n", + " WorkToolsFrequencyC WorkToolsFrequencyCloudera WorkToolsFrequencyDataRobot \\\n", + "3 NaN Rarely NaN \n", + "60 Sometimes NaN NaN \n", + "77 NaN NaN NaN \n", + "\n", + " WorkToolsFrequencyFlume WorkToolsFrequencyGCP WorkToolsFrequencyHadoop \\\n", + "3 NaN NaN Rarely \n", + "60 NaN NaN NaN \n", + "77 NaN NaN NaN \n", + "\n", + " WorkToolsFrequencyIBMCognos WorkToolsFrequencyIBMSPSSModeler \\\n", + "3 NaN NaN \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkToolsFrequencyIBMSPSSStatistics WorkToolsFrequencyIBMWatson \\\n", + "3 NaN NaN \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkToolsFrequencyImpala WorkToolsFrequencyJava WorkToolsFrequencyJulia \\\n", + "3 Rarely Rarely NaN \n", + "60 NaN NaN NaN \n", + "77 NaN Most of the time NaN \n", + "\n", + " WorkToolsFrequencyJupyter WorkToolsFrequencyKNIMECommercial \\\n", + "3 NaN NaN \n", + "60 Sometimes NaN \n", + "77 NaN NaN \n", + "\n", + " WorkToolsFrequencyKNIMEFree WorkToolsFrequencyMathematica \\\n", + "3 NaN Rarely \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkToolsFrequencyMATLAB WorkToolsFrequencyAzure WorkToolsFrequencyExcel \\\n", + "3 Rarely NaN Sometimes \n", + "60 Most of the time NaN NaN \n", + "77 NaN NaN NaN \n", + "\n", + " WorkToolsFrequencyMicrosoftRServer WorkToolsFrequencyMicrosoftSQL \\\n", + "3 NaN Rarely \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkToolsFrequencyMinitab WorkToolsFrequencyNoSQL WorkToolsFrequencyOracle \\\n", + "3 NaN Rarely NaN \n", + "60 NaN Sometimes NaN \n", + "77 NaN NaN NaN \n", + "\n", + " WorkToolsFrequencyOrange WorkToolsFrequencyPerl WorkToolsFrequencyPython \\\n", + "3 NaN NaN Rarely \n", + "60 NaN NaN Sometimes \n", + "77 NaN NaN Most of the time \n", + "\n", + " WorkToolsFrequencyQlik WorkToolsFrequencyR \\\n", + "3 NaN Rarely \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkToolsFrequencyRapidMinerCommercial WorkToolsFrequencyRapidMinerFree \\\n", + "3 NaN NaN \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkToolsFrequencySalfrod WorkToolsFrequencySAPBusinessObjects \\\n", + "3 NaN NaN \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkToolsFrequencySASBase WorkToolsFrequencySASEnterprise \\\n", + "3 Sometimes NaN \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkToolsFrequencySASJMP WorkToolsFrequencySpark WorkToolsFrequencySQL \\\n", + "3 Rarely NaN Often \n", + "60 NaN NaN Sometimes \n", + "77 NaN NaN NaN \n", + "\n", + " WorkToolsFrequencyStan WorkToolsFrequencyStatistica \\\n", + "3 NaN NaN \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkToolsFrequencyTableau WorkToolsFrequencyTensorFlow \\\n", + "3 Rarely NaN \n", + "60 NaN NaN \n", + "77 Rarely NaN \n", + "\n", + " WorkToolsFrequencyTIBCO WorkToolsFrequencyUnix WorkToolsFrequencySelect1 \\\n", + "3 NaN NaN NaN \n", + "60 NaN NaN NaN \n", + "77 NaN NaN NaN \n", + "\n", + " WorkToolsFrequencySelect2 WorkFrequencySelect3 \\\n", + "3 NaN NaN \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkMethodsSelect WorkMethodsFrequencyA/B \\\n", + "3 A/B Testing,Bayesian Techniques,Data Visualiza... Sometimes \n", + "60 Data Visualization,kNN and Other Clustering,Ti... NaN \n", + "77 A/B Testing,Bayesian Techniques,Cross-Validati... Sometimes \n", + "\n", + " WorkMethodsFrequencyAssociationRules WorkMethodsFrequencyBayesian \\\n", + "3 NaN Sometimes \n", + "60 NaN NaN \n", + "77 NaN Often \n", + "\n", + " WorkMethodsFrequencyCNNs WorkMethodsFrequencyCollaborativeFiltering \\\n", + "3 NaN NaN \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkMethodsFrequencyCross-Validation WorkMethodsFrequencyDataVisualization \\\n", + "3 NaN Sometimes \n", + "60 NaN Most of the time \n", + "77 Most of the time Most of the time \n", + "\n", + " WorkMethodsFrequencyDecisionTrees WorkMethodsFrequencyEnsembleMethods \\\n", + "3 Often Sometimes \n", + "60 NaN NaN \n", + "77 Most of the time Most of the time \n", + "\n", + " WorkMethodsFrequencyEvolutionaryApproaches WorkMethodsFrequencyGANs \\\n", + "3 NaN NaN \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkMethodsFrequencyGBM WorkMethodsFrequencyHMMs WorkMethodsFrequencyKNN \\\n", + "3 NaN NaN NaN \n", + "60 NaN NaN Sometimes \n", + "77 NaN NaN NaN \n", + "\n", + " WorkMethodsFrequencyLiftAnalysis WorkMethodsFrequencyLogisticRegression \\\n", + "3 NaN Sometimes \n", + "60 NaN NaN \n", + "77 NaN Most of the time \n", + "\n", + " WorkMethodsFrequencyMLN WorkMethodsFrequencyNaiveBayes \\\n", + "3 Often Sometimes \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkMethodsFrequencyNLP WorkMethodsFrequencyNeuralNetworks \\\n", + "3 NaN Sometimes \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkMethodsFrequencyPCA WorkMethodsFrequencyPrescriptiveModeling \\\n", + "3 NaN NaN \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkMethodsFrequencyRandomForests WorkMethodsFrequencyRecommenderSystems \\\n", + "3 Sometimes NaN \n", + "60 NaN NaN \n", + "77 Most of the time NaN \n", + "\n", + " WorkMethodsFrequencyRNNs WorkMethodsFrequencySegmentation \\\n", + "3 NaN NaN \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkMethodsFrequencySimulation WorkMethodsFrequencySVMs \\\n", + "3 Often NaN \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkMethodsFrequencyTextAnalysis WorkMethodsFrequencyTimeSeriesAnalysis \\\n", + "3 NaN Often \n", + "60 NaN Often \n", + "77 NaN NaN \n", + "\n", + " WorkMethodsFrequencySelect1 WorkMethodsFrequencySelect2 \\\n", + "3 NaN NaN \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkMethodsFrequencySelect3 TimeGatheringData TimeModelBuilding \\\n", + "3 NaN 50.0 20.0 \n", + "60 NaN 0.0 0.0 \n", + "77 NaN 30.0 30.0 \n", + "\n", + " TimeProduction TimeVisualizing TimeFindingInsights TimeOtherSelect \\\n", + "3 0.0 10.0 20.0 0.0 \n", + "60 0.0 0.0 0.0 0.0 \n", + "77 10.0 20.0 10.0 0.0 \n", + "\n", + " AlgorithmUnderstandingLevel \\\n", + "3 Enough to refine and innovate on the algorithm \n", + "60 Enough to code it again from scratch, albeit i... \n", + "77 Enough to code it again from scratch, albeit i... \n", + "\n", + " WorkChallengesSelect \\\n", + "3 Company politics / Lack of management/financia... \n", + "60 Dirty data,Explaining data science to others,L... \n", + "77 Dirty data,Explaining data science to others,L... \n", + "\n", + " WorkChallengeFrequencyPolitics WorkChallengeFrequencyUnusedResults \\\n", + "3 Often Often \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkChallengeFrequencyUnusefulInstrumenting \\\n", + "3 Often \n", + "60 NaN \n", + "77 NaN \n", + "\n", + " WorkChallengeFrequencyDeployment WorkChallengeFrequencyDirtyData \\\n", + "3 Often Often \n", + "60 NaN Most of the time \n", + "77 NaN Sometimes \n", + "\n", + " WorkChallengeFrequencyExplaining WorkChallengeFrequencyPass \\\n", + "3 Often NaN \n", + "60 Sometimes NaN \n", + "77 Often NaN \n", + "\n", + " WorkChallengeFrequencyIntegration WorkChallengeFrequencyTalent \\\n", + "3 Often Often \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkChallengeFrequencyDataFunds WorkChallengeFrequencyDomainExpertise \\\n", + "3 Often Most of the time \n", + "60 NaN NaN \n", + "77 Most of the time NaN \n", + "\n", + " WorkChallengeFrequencyML WorkChallengeFrequencyTools \\\n", + "3 Often Often \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkChallengeFrequencyExpectations WorkChallengeFrequencyITCoordination \\\n", + "3 Often NaN \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkChallengeFrequencyHiringFunds WorkChallengeFrequencyPrivacy \\\n", + "3 Often Often \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkChallengeFrequencyScaling WorkChallengeFrequencyEnvironments \\\n", + "3 Often Often \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkChallengeFrequencyClarity WorkChallengeFrequencyDataAccess \\\n", + "3 Often Often \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " WorkChallengeFrequencyOtherSelect WorkDataVisualizations \\\n", + "3 NaN 100% of projects \n", + "60 NaN 76-99% of projects \n", + "77 NaN 76-99% of projects \n", + "\n", + " WorkInternalVsExternalTools WorkMLTeamSeatSelect \\\n", + "3 Entirely internal Standalone Team \n", + "60 NaN NaN \n", + "77 Entirely external Standalone Team \n", + "\n", + " WorkDatasets \\\n", + "3 Electricity data sets from government and states \n", + "60 NaN \n", + "77 NaN \n", + "\n", + " WorkDatasetsChallenge \\\n", + "3 Everything is custom, there is never a tool th... \n", + "60 NaN \n", + "77 NaN \n", + "\n", + " WorkDataStorage \\\n", + "3 Column-oriented relational (e.g. KDB/MariaDB),... \n", + "60 NaN \n", + "77 Flat files not in a database or cache (e.g. CS... \n", + "\n", + " WorkDataSharing WorkDataSourcing \\\n", + "3 Company Developed Platform,Email NaN \n", + "60 NaN NaN \n", + "77 I don't typically share data NaN \n", + "\n", + " WorkCodeSharing RemoteWork \\\n", + "3 Generic cloud file sharing software (Dropbox/B... NaN \n", + "60 NaN NaN \n", + "77 Bitbucket Most of the time \n", + "\n", + " CompensationAmount CompensationCurrency \\\n", + "3 250,000 USD \n", + "60 NaN NaN \n", + "77 NaN NaN \n", + "\n", + " SalaryChange JobSatisfaction \\\n", + "3 Has increased 20% or more 10 - Highly Satisfied \n", + "60 NaN 10 - Highly Satisfied \n", + "77 I do not want to share information about my sa... 10 - Highly Satisfied \n", + "\n", + " JobSearchResource JobHuntTime JobFactorLearning JobFactorSalary \\\n", + "3 NaN NaN NaN NaN \n", + "60 NaN NaN NaN NaN \n", + "77 NaN NaN NaN NaN \n", + "\n", + " JobFactorOffice JobFactorLanguages JobFactorCommute JobFactorManagement \\\n", + "3 NaN NaN NaN NaN \n", + "60 NaN NaN NaN NaN \n", + "77 NaN NaN NaN NaN \n", + "\n", + " JobFactorExperienceLevel JobFactorDepartment JobFactorTitle \\\n", + "3 NaN NaN NaN \n", + "60 NaN NaN NaN \n", + "77 NaN NaN NaN \n", + "\n", + " JobFactorCompanyFunding JobFactorImpact JobFactorRemote JobFactorIndustry \\\n", + "3 NaN NaN NaN NaN \n", + "60 NaN NaN NaN NaN \n", + "77 NaN NaN NaN NaN \n", + "\n", + " JobFactorLeaderReputation JobFactorDiversity JobFactorPublishingOpportunity \n", + "3 NaN NaN NaN \n", + "60 NaN NaN NaN \n", + "77 NaN NaN NaN " + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Veja os primeiros 3 registros (todas as colunas) das pessoas altamentes satisfeitas\n", + "highly_satisfied[:3]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "E se eu quiser ver as pessoas altamente satisfeitas e que trabalham com python?" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "highly_satisfied = multiple_choice['JobSatisfaction'] == '10 - Highly Satisfied'\n", + "pythonist = multiple_choice['LanguageRecommendationSelect'] == 'Python'\n", + "highly_satisfied_and_pythonist = multiple_choice[highly_satisfied & pythonist]" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(319, 228)" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "highly_satisfied_and_pythonist.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "E se tentassemos com a idade? Ver só que está abaixo de 30 anos" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "highly_satisfied = multiple_choice['JobSatisfaction'] == '10 - Highly Satisfied'\n", + "age = multiple_choice['Age'] < 30.0\n", + "highly_satisfied_and_age = multiple_choice[highly_satisfied & age]" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(171, 228)" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "highly_satisfied_and_age.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Quais são as linguagens que a galera altamente satisfeita recomenda?" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Python 319\n", + "R 151\n", + "SQL 28\n", + "C/C++/C# 20\n", + "Matlab 11\n", + "Other 9\n", + "Scala 9\n", + "Java 7\n", + "Julia 5\n", + "SAS 4\n", + "Stata 3\n", + "Haskell 2\n", + "Name: LanguageRecommendationSelect, dtype: int64" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "multiple_choice[highly_satisfied]['LanguageRecommendationSelect'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "highly_satisfied_languages = multiple_choice[highly_satisfied]['LanguageRecommendationSelect'].value_counts()\n", + "language_counts = multiple_choice['JobSatisfaction'][highly_satisfied].notnull().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "589" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "language_counts" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Python 54.159593\n", + "R 25.636672\n", + "SQL 4.753820\n", + "C/C++/C# 3.395586\n", + "Matlab 1.867572\n", + "Other 1.528014\n", + "Scala 1.528014\n", + "Java 1.188455\n", + "Julia 0.848896\n", + "SAS 0.679117\n", + "Stata 0.509338\n", + "Haskell 0.339559\n", + "Name: LanguageRecommendationSelect, dtype: float64" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(highly_satisfied_languages / language_counts) * 100" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "E se eu quiser ordenar esses valores? Do menor para o maior?" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Haskell 0.339559\n", + "Stata 0.509338\n", + "SAS 0.679117\n", + "Julia 0.848896\n", + "Java 1.188455\n", + "Other 1.528014\n", + "Scala 1.528014\n", + "Matlab 1.867572\n", + "C/C++/C# 3.395586\n", + "SQL 4.753820\n", + "R 25.636672\n", + "Python 54.159593\n", + "Name: LanguageRecommendationSelect, dtype: float64" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pd.Series((highly_satisfied_languages / language_counts) * 100).sort_values()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Desafio 1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Qual o país que tem a maior quantidade de dados onde as pessoas preencheram a coluna que tem o menor número dos dados?\n", + "\n", + "Dica: Você precisará ordenar os campos pela quantidade de nulos (ou não nulos) e depois ver o país dessa galera." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![arrested_panda](https://media.giphy.com/media/N6funLtVsHW0g/giphy.gif)" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "WorkToolsFrequencyAngoss 16694\n", + "WorkToolsFrequencySalfrod 16684\n", + "WorkToolsFrequencyKNIMECommercial 16680\n", + "WorkMethodsFrequencySelect2 16677\n", + "WorkToolsFrequencyStatistica 16674\n", + "WorkToolsFrequencyDataRobot 16653\n", + "WorkToolsFrequencyRapidMinerCommercial 16642\n", + "WorkFrequencySelect3 16635\n", + "WorkToolsFrequencySAPBusinessObjects 16625\n", + "WorkMethodsFrequencySelect3 16623\n", + "JobSkillImportanceOtherSelect3 16603\n", + "WorkToolsFrequencySASJMP 16601\n", + "WorkToolsFrequencyOrange 16594\n", + "WorkToolsFrequencySelect2 16581\n", + "WorkToolsFrequencyTIBCO 16577\n", + "WorkToolsFrequencyFlume 16575\n", + "WorkToolsFrequencyMinitab 16572\n", + "WorkToolsFrequencyStan 16564\n", + "WorkToolsFrequencyIBMCognos 16561\n", + "JobSkillImportanceOtherSelect2 16544\n", + "WorkToolsFrequencyJulia 16536\n", + "WorkToolsFrequencyOracle 16508\n", + "WorkMethodsFrequencyGANs 16486\n", + "WorkMethodsFrequencySelect1 16483\n", + "WorkMethodsFrequencyMLN 16474\n", + "WorkToolsFrequencyIBMWatson 16473\n", + "WorkToolsFrequencyImpala 16464\n", + "WorkToolsFrequencyIBMSPSSModeler 16450\n", + "WorkToolsFrequencyKNIMEFree 16449\n", + "WorkChallengeFrequencyOtherSelect 16439\n", + "WorkToolsFrequencyMathematica 16424\n", + "WorkToolsFrequencyPerl 16414\n", + "WorkToolsFrequencyRapidMinerFree 16389\n", + "LearningPlatformUsefulnessTradeBook 16383\n", + "JobSkillImportanceOtherSelect1 16358\n", + "WorkToolsFrequencyQlik 16352\n", + "WorkToolsFrequencyMicrosoftRServer 16344\n", + "WorkDataSourcing 16337\n", + "WorkToolsFrequencySASEnterprise 16329\n", + "WorkMethodsFrequencyHMMs 16317\n", + "WorkToolsFrequencyAmazonML 16317\n", + "WorkMethodsFrequencyEvolutionaryApproaches 16302\n", + "WorkChallengeFrequencyPass 16292\n", + "WorkToolsFrequencyMicrosoftSQL 16277\n", + "WorkToolsFrequencyCloudera 16277\n", + "WorkToolsFrequencyIBMSPSSStatistics 16258\n", + "WorkToolsFrequencyGCP 16192\n", + "WorkToolsFrequencyAzure 16141\n", + "WorkMethodsFrequencyLiftAnalysis 16093\n", + "WorkChallengeFrequencyUnusefulInstrumenting 16077\n", + "WorkToolsFrequencySelect1 16030\n", + "WorkToolsFrequencySASBase 16001\n", + "WorkMethodsFrequencyCollaborativeFiltering 15955\n", + "WorkChallengeFrequencyML 15951\n", + "WorkMethodsFrequencyPrescriptiveModeling 15899\n", + "WorkChallengeFrequencyScaling 15883\n", + "WorkChallengeFrequencyDeployment 15869\n", + "WorkMethodsFrequencyRNNs 15868\n", + "WorkChallengeFrequencyDataFunds 15764\n", + "WorkChallengeFrequencyIntegration 15744\n", + "LearningPlatformUsefulnessCompany 15735\n", + "WorkToolsFrequencyExcel 15668\n", + "LearningPlatformUsefulnessNewsletters 15627\n", + "WorkMethodsFrequencyAssociationRules 15620\n", + "WorkMethodsFrequencyRecommenderSystems 15604\n", + "WorkChallengeFrequencyExpectations 15582\n", + "LearningPlatformUsefulnessCommunities 15574\n", + "WorkChallengeFrequencyITCoordination 15547\n", + "WorkChallengeFrequencyTools 15537\n", + "LearningPlatformUsefulnessPodcasts 15502\n", + "WorkChallengeFrequencyEnvironments 15463\n", + "StudentStatus 15436\n", + "LearningDataScience 15432\n", + "WorkChallengeFrequencyHiringFunds 15429\n", + "WorkToolsFrequencySpark 15391\n", + "WorkToolsFrequencyHadoop 15379\n", + "WorkMethodsFrequencySimulation 15365\n", + "WorkMethodsFrequencyCNNs 15363\n", + "WorkToolsFrequencyJava 15311\n", + "WorkChallengeFrequencyDomainExpertise 15308\n", + "WorkChallengeFrequencyPrivacy 15294\n", + "WorkToolsFrequencyMATLAB 15292\n", + "LearningPlatformUsefulnessTutoring 15290\n", + "WorkToolsFrequencyNoSQL 15238\n", + "WorkToolsFrequencyC 15215\n", + "WorkMethodsFrequencyGBM 15211\n", + "LearningPlatformUsefulnessFriends 15135\n", + "WorkToolsFrequencyTableau 15132\n", + "WorkChallengeFrequencyExplaining 15131\n", + "WorkChallengeFrequencyUnusedResults 14972\n", + "WorkMethodsFrequencyNaiveBayes 14910\n", + "WorkToolsFrequencyAWS 14896\n", + "WorkToolsFrequencyUnix 14888\n", + "WorkMethodsFrequencyBayesian 14871\n", + "WorkMethodsFrequencyA/B 14846\n", + "WorkMethodsFrequencyNLP 14840\n", + "WorkMethodsFrequencySVMs 14813\n", + "WorkMethodsFrequencySegmentation 14739\n", + "WorkMethodsFrequencyEnsembleMethods 14733\n", + "WorkChallengeFrequencyClarity 14537\n", + " ... \n", + "JobFactorManagement 13282\n", + "JobFactorExperienceLevel 13279\n", + "JobFactorCommute 13269\n", + "JobFactorOffice 13248\n", + "JobFactorLanguages 13241\n", + "JobFactorSalary 13231\n", + "WorkChallengeFrequencyDirtyData 13165\n", + "JobFactorLearning 13165\n", + "WorkMethodsFrequencyDecisionTrees 13134\n", + "JobSkillImportanceEnterpriseTools 13022\n", + "JobHuntTime 12985\n", + "JobSearchResource 12977\n", + "WorkMethodsFrequencyCross-Validation 12956\n", + "JobSkillImportanceMOOC 12884\n", + "JobSkillImportanceVisualizations 12849\n", + "JobSkillImportanceKaggleRanking 12846\n", + "JobSkillImportanceSQL 12824\n", + "JobSkillImportanceDegree 12807\n", + "JobSkillImportanceR 12772\n", + "JobSkillImportanceBigData 12760\n", + "JobSkillImportanceStats 12756\n", + "TimeSpentStudying 12688\n", + "JobSkillImportancePython 12685\n", + "ProveKnowledgeSelect 12555\n", + "WorkMethodsFrequencyLogisticRegression 12544\n", + "LearningPlatformUsefulnessTextbook 12535\n", + "WorkToolsFrequencySQL 12528\n", + "HardwarePersonalProjectsSelect 12510\n", + "LearningDataScienceTime 12367\n", + "CompensationCurrency 12186\n", + "WorkToolsFrequencyR 12078\n", + "LearningPlatformUsefulnessBlogs 11951\n", + "LearningPlatformUsefulnessProjects 11922\n", + "WorkMethodsFrequencyDataVisualization 11810\n", + "CompensationAmount 11492\n", + "LearningPlatformUsefulnessYouTube 11487\n", + "LearningPlatformUsefulnessSO 11076\n", + "WorkToolsFrequencyPython 10726\n", + "LearningPlatformUsefulnessCourses 10724\n", + "RemoteWork 10619\n", + "WorkCodeSharing 10513\n", + "SalaryChange 10327\n", + "WorkDataSharing 10214\n", + "WorkDataStorage 10201\n", + "LearningPlatformUsefulnessKaggle 10133\n", + "JobSatisfaction 10039\n", + "WorkMLTeamSeatSelect 10028\n", + "WorkInternalVsExternalTools 9959\n", + "WorkDataVisualizations 9837\n", + "WorkDatasetSize 9628\n", + "WorkProductionFrequency 9594\n", + "WorkAlgorithmsSelect 9415\n", + "WorkChallengesSelect 9340\n", + "AlgorithmUnderstandingLevel 9306\n", + "TimeOtherSelect 9203\n", + "TimeProduction 9199\n", + "TimeFindingInsights 9193\n", + "TimeModelBuilding 9188\n", + "TimeVisualizing 9187\n", + "TimeGatheringData 9186\n", + "EmployerSizeChange 9159\n", + "EmployerMLTime 9065\n", + "EmployerSearchMethod 8988\n", + "EmployerSize 8945\n", + "WorkMethodsSelect 8943\n", + "WorkToolsSelect 8761\n", + "JobFunctionSelect 8735\n", + "WorkHardwareSelect 8698\n", + "WorkDataTypeSelect 8692\n", + "UniversityImportance 8618\n", + "BlogsPodcastsNewslettersSelect 8576\n", + "EmployerIndustry 5970\n", + "PublicDatasetsSelect 5920\n", + "MLMethodNextYearSelect 5883\n", + "LanguageRecommendationSelect 5718\n", + "MLToolNextYearSelect 5718\n", + "LearningPlatformSelect 5445\n", + "TitleFit 5212\n", + "CurrentEmployerType 5115\n", + "CurrentJobTitleSelect 4886\n", + "MLTechniquesSelect 4132\n", + "ParentsEducation 4048\n", + "DataScienceIdentitySelect 4045\n", + "MLSkillsSelect 3963\n", + "LearningCategoryOther 3622\n", + "LearningCategorySelftTaught 3607\n", + "LearningCategoryWork 3605\n", + "LearningCategoryUniversity 3594\n", + "LearningCategoryKaggle 3590\n", + "LearningCategoryOnlineCourses 3590\n", + "CodeWriter 3530\n", + "MajorSelect 3435\n", + "Tenure 3184\n", + "PastJobTitlesSelect 2524\n", + "FirstTrainingSelect 2004\n", + "FormalEducation 1701\n", + "Age 331\n", + "Country 121\n", + "GenderSelect 95\n", + "EmploymentStatus 0\n", + "Length: 228, dtype: int64" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "multiple_choice.isnull().sum().sort_values(ascending=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "United States 8\n", + "India 3\n", + "Mexico 2\n", + "Italy 2\n", + "Canada 2\n", + "Singapore 1\n", + "Australia 1\n", + "Egypt 1\n", + "Other 1\n", + "United Kingdom 1\n", + "Name: Country, dtype: int64" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "multiple_choice[multiple_choice['WorkToolsFrequencyAngoss'].notnull()]['Country'].value_counts()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Selecionando por index" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "E se eu quiser pegar os valores de uma linha específica do dataframe?" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "GenderSelect Female\n", + "Country Russia\n", + "Age 20\n", + "EmploymentStatus Not employed, and not looking for work\n", + "StudentStatus Yes\n", + "LearningDataScience Yes, I'm focused on learning mostly data scien...\n", + "CodeWriter NaN\n", + "CareerSwitcher NaN\n", + "CurrentJobTitleSelect NaN\n", + "TitleFit NaN\n", + "CurrentEmployerType NaN\n", + "MLToolNextYearSelect Python\n", + "MLMethodNextYearSelect Neural Nets\n", + "LanguageRecommendationSelect Python\n", + "PublicDatasetsSelect Dataset aggregator/platform (i.e. Socrata/Kagg...\n", + "LearningPlatformSelect Kaggle,Online courses\n", + "LearningPlatformUsefulnessArxiv NaN\n", + "LearningPlatformUsefulnessBlogs NaN\n", + "LearningPlatformUsefulnessCollege NaN\n", + "LearningPlatformUsefulnessCompany NaN\n", + "LearningPlatformUsefulnessConferences NaN\n", + "LearningPlatformUsefulnessFriends NaN\n", + "LearningPlatformUsefulnessKaggle Very useful\n", + "LearningPlatformUsefulnessNewsletters NaN\n", + "LearningPlatformUsefulnessCommunities NaN\n", + "LearningPlatformUsefulnessDocumentation NaN\n", + "LearningPlatformUsefulnessCourses Very useful\n", + "LearningPlatformUsefulnessProjects NaN\n", + "LearningPlatformUsefulnessPodcasts NaN\n", + "LearningPlatformUsefulnessSO NaN\n", + "LearningPlatformUsefulnessTextbook NaN\n", + "LearningPlatformUsefulnessTradeBook NaN\n", + "LearningPlatformUsefulnessTutoring NaN\n", + "LearningPlatformUsefulnessYouTube NaN\n", + "BlogsPodcastsNewslettersSelect NaN\n", + "LearningDataScienceTime < 1 year\n", + "JobSkillImportanceBigData Nice to have\n", + "JobSkillImportanceDegree Nice to have\n", + "JobSkillImportanceStats Nice to have\n", + "JobSkillImportanceEnterpriseTools Unnecessary\n", + "JobSkillImportancePython Necessary\n", + "JobSkillImportanceR Unnecessary\n", + "JobSkillImportanceSQL Unnecessary\n", + "JobSkillImportanceKaggleRanking Nice to have\n", + "JobSkillImportanceMOOC Unnecessary\n", + "JobSkillImportanceVisualizations Nice to have\n", + "JobSkillImportanceOtherSelect1 NaN\n", + "JobSkillImportanceOtherSelect2 NaN\n", + "JobSkillImportanceOtherSelect3 NaN\n", + "CoursePlatformSelect Coursera\n", + "HardwarePersonalProjectsSelect Laptop or Workstation and local IT supported s...\n", + "TimeSpentStudying 11 - 39 hours\n", + "ProveKnowledgeSelect Kaggle Competitions\n", + "DataScienceIdentitySelect No\n", + "FormalEducation Bachelor's degree\n", + "MajorSelect Computer Science\n", + "Tenure NaN\n", + "PastJobTitlesSelect I haven't started working yet\n", + "FirstTrainingSelect Online courses (coursera, udemy, edx, etc.)\n", + "LearningCategorySelftTaught NaN\n", + "LearningCategoryOnlineCourses NaN\n", + "LearningCategoryWork NaN\n", + "LearningCategoryUniversity NaN\n", + "LearningCategoryKaggle NaN\n", + "LearningCategoryOther NaN\n", + "MLSkillsSelect Computer Vision,Outlier detection (e.g. Fraud ...\n", + "MLTechniquesSelect Gradient Boosting,Logistic Regression\n", + "ParentsEducation A bachelor's degree\n", + "EmployerIndustry NaN\n", + "EmployerSize NaN\n", + "EmployerSizeChange NaN\n", + "EmployerMLTime NaN\n", + "EmployerSearchMethod NaN\n", + "UniversityImportance NaN\n", + "JobFunctionSelect NaN\n", + "WorkHardwareSelect NaN\n", + "WorkDataTypeSelect NaN\n", + "WorkProductionFrequency NaN\n", + "WorkDatasetSize NaN\n", + "WorkAlgorithmsSelect NaN\n", + "WorkToolsSelect NaN\n", + "WorkToolsFrequencyAmazonML NaN\n", + "WorkToolsFrequencyAWS NaN\n", + "WorkToolsFrequencyAngoss NaN\n", + "WorkToolsFrequencyC NaN\n", + "WorkToolsFrequencyCloudera NaN\n", + "WorkToolsFrequencyDataRobot NaN\n", + "WorkToolsFrequencyFlume NaN\n", + "WorkToolsFrequencyGCP NaN\n", + "WorkToolsFrequencyHadoop NaN\n", + "WorkToolsFrequencyIBMCognos NaN\n", + "WorkToolsFrequencyIBMSPSSModeler NaN\n", + "WorkToolsFrequencyIBMSPSSStatistics NaN\n", + "WorkToolsFrequencyIBMWatson NaN\n", + "WorkToolsFrequencyImpala NaN\n", + "WorkToolsFrequencyJava NaN\n", + "WorkToolsFrequencyJulia NaN\n", + "WorkToolsFrequencyJupyter NaN\n", + "WorkToolsFrequencyKNIMECommercial NaN\n", + "WorkToolsFrequencyKNIMEFree NaN\n", + " ... \n", + "WorkToolsFrequencyUnix NaN\n", + "WorkToolsFrequencySelect1 NaN\n", + "WorkToolsFrequencySelect2 NaN\n", + "WorkFrequencySelect3 NaN\n", + "WorkMethodsSelect NaN\n", + "WorkMethodsFrequencyA/B NaN\n", + "WorkMethodsFrequencyAssociationRules NaN\n", + "WorkMethodsFrequencyBayesian NaN\n", + "WorkMethodsFrequencyCNNs NaN\n", + "WorkMethodsFrequencyCollaborativeFiltering NaN\n", + "WorkMethodsFrequencyCross-Validation NaN\n", + "WorkMethodsFrequencyDataVisualization NaN\n", + "WorkMethodsFrequencyDecisionTrees NaN\n", + "WorkMethodsFrequencyEnsembleMethods NaN\n", + "WorkMethodsFrequencyEvolutionaryApproaches NaN\n", + "WorkMethodsFrequencyGANs NaN\n", + "WorkMethodsFrequencyGBM NaN\n", + "WorkMethodsFrequencyHMMs NaN\n", + "WorkMethodsFrequencyKNN NaN\n", + "WorkMethodsFrequencyLiftAnalysis NaN\n", + "WorkMethodsFrequencyLogisticRegression NaN\n", + "WorkMethodsFrequencyMLN NaN\n", + "WorkMethodsFrequencyNaiveBayes NaN\n", + "WorkMethodsFrequencyNLP NaN\n", + "WorkMethodsFrequencyNeuralNetworks NaN\n", + "WorkMethodsFrequencyPCA NaN\n", + "WorkMethodsFrequencyPrescriptiveModeling NaN\n", + "WorkMethodsFrequencyRandomForests NaN\n", + "WorkMethodsFrequencyRecommenderSystems NaN\n", + "WorkMethodsFrequencyRNNs NaN\n", + "WorkMethodsFrequencySegmentation NaN\n", + "WorkMethodsFrequencySimulation NaN\n", + "WorkMethodsFrequencySVMs NaN\n", + "WorkMethodsFrequencyTextAnalysis NaN\n", + "WorkMethodsFrequencyTimeSeriesAnalysis NaN\n", + "WorkMethodsFrequencySelect1 NaN\n", + "WorkMethodsFrequencySelect2 NaN\n", + "WorkMethodsFrequencySelect3 NaN\n", + "TimeGatheringData NaN\n", + "TimeModelBuilding NaN\n", + "TimeProduction NaN\n", + "TimeVisualizing NaN\n", + "TimeFindingInsights NaN\n", + "TimeOtherSelect NaN\n", + "AlgorithmUnderstandingLevel NaN\n", + "WorkChallengesSelect NaN\n", + "WorkChallengeFrequencyPolitics NaN\n", + "WorkChallengeFrequencyUnusedResults NaN\n", + "WorkChallengeFrequencyUnusefulInstrumenting NaN\n", + "WorkChallengeFrequencyDeployment NaN\n", + "WorkChallengeFrequencyDirtyData NaN\n", + "WorkChallengeFrequencyExplaining NaN\n", + "WorkChallengeFrequencyPass NaN\n", + "WorkChallengeFrequencyIntegration NaN\n", + "WorkChallengeFrequencyTalent NaN\n", + "WorkChallengeFrequencyDataFunds NaN\n", + "WorkChallengeFrequencyDomainExpertise NaN\n", + "WorkChallengeFrequencyML NaN\n", + "WorkChallengeFrequencyTools NaN\n", + "WorkChallengeFrequencyExpectations NaN\n", + "WorkChallengeFrequencyITCoordination NaN\n", + "WorkChallengeFrequencyHiringFunds NaN\n", + "WorkChallengeFrequencyPrivacy NaN\n", + "WorkChallengeFrequencyScaling NaN\n", + "WorkChallengeFrequencyEnvironments NaN\n", + "WorkChallengeFrequencyClarity NaN\n", + "WorkChallengeFrequencyDataAccess NaN\n", + "WorkChallengeFrequencyOtherSelect NaN\n", + "WorkDataVisualizations NaN\n", + "WorkInternalVsExternalTools NaN\n", + "WorkMLTeamSeatSelect NaN\n", + "WorkDatasets NaN\n", + "WorkDatasetsChallenge NaN\n", + "WorkDataStorage NaN\n", + "WorkDataSharing NaN\n", + "WorkDataSourcing NaN\n", + "WorkCodeSharing NaN\n", + "RemoteWork NaN\n", + "CompensationAmount NaN\n", + "CompensationCurrency NaN\n", + "SalaryChange NaN\n", + "JobSatisfaction NaN\n", + "JobSearchResource Tech-specific job board\n", + "JobHuntTime 0\n", + "JobFactorLearning Very Important\n", + "JobFactorSalary Somewhat important\n", + "JobFactorOffice Somewhat important\n", + "JobFactorLanguages Somewhat important\n", + "JobFactorCommute Somewhat important\n", + "JobFactorManagement Somewhat important\n", + "JobFactorExperienceLevel Somewhat important\n", + "JobFactorDepartment Very Important\n", + "JobFactorTitle Very Important\n", + "JobFactorCompanyFunding Somewhat important\n", + "JobFactorImpact Very Important\n", + "JobFactorRemote Somewhat important\n", + "JobFactorIndustry Very Important\n", + "JobFactorLeaderReputation Very Important\n", + "JobFactorDiversity Somewhat important\n", + "JobFactorPublishingOpportunity Somewhat important\n", + "Name: 10, Length: 228, dtype: object" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "multiple_choice.iloc[10,]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Também posso ver só o valor de uma coluna, sem escrever o nome, somente pela sua posição" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "0 Non-binary, genderqueer, or gender non-conforming\n", + "1 Female\n", + "2 Male\n", + "3 Male\n", + "4 Male\n", + "5 Male\n", + "6 Male\n", + "7 Female\n", + "8 Female\n", + "9 Male\n", + "10 Female\n", + "11 Male\n", + "12 Male\n", + "13 Male\n", + "14 Male\n", + "15 Male\n", + "16 Male\n", + "17 Male\n", + "18 Male\n", + "19 Male\n", + "20 Male\n", + "21 Male\n", + "22 Male\n", + "23 Male\n", + "24 Male\n", + "25 Male\n", + "26 Male\n", + "27 Male\n", + "28 Male\n", + "29 Female\n", + "30 Male\n", + "31 Male\n", + "32 Male\n", + "33 Male\n", + "34 Male\n", + "35 Female\n", + "36 Male\n", + "37 Male\n", + "38 Female\n", + "39 Male\n", + "40 Male\n", + "41 Male\n", + "42 Male\n", + "43 Female\n", + "44 Male\n", + "45 Male\n", + "46 Male\n", + "47 Female\n", + "48 Male\n", + "49 Male\n", + "50 Male\n", + "51 Male\n", + "52 Male\n", + "53 Male\n", + "54 Female\n", + "55 Male\n", + "56 Female\n", + "57 Male\n", + "58 Male\n", + "59 Male\n", + "60 Male\n", + "61 Male\n", + "62 Male\n", + "63 Male\n", + "64 Male\n", + "65 Male\n", + "66 Female\n", + "67 Male\n", + "68 Male\n", + "69 Female\n", + "70 Male\n", + "71 Female\n", + "72 Male\n", + "73 Male\n", + "74 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"16647 Male\n", + "16648 Male\n", + "16649 Male\n", + "16650 Male\n", + "16651 Male\n", + "16652 NaN\n", + "16653 Male\n", + "16654 Male\n", + "16655 Male\n", + "16656 Female\n", + "16657 Male\n", + "16658 Male\n", + "16659 Male\n", + "16660 Male\n", + "16661 Male\n", + "16662 Male\n", + "16663 Female\n", + "16664 Male\n", + "16665 Male\n", + "16666 Female\n", + "16667 Male\n", + "16668 Male\n", + "16669 Male\n", + "16670 Female\n", + "16671 Male\n", + "16672 Male\n", + "16673 Male\n", + "16674 Male\n", + "16675 Male\n", + "16676 Male\n", + "16677 Male\n", + "16678 Female\n", + "16679 Male\n", + "16680 Male\n", + "16681 Male\n", + "16682 Male\n", + "16683 Male\n", + "16684 Male\n", + "16685 Male\n", + "16686 Male\n", + "16687 Male\n", + "16688 Female\n", + "16689 Female\n", + "16690 Male\n", + "16691 Male\n", + "16692 Male\n", + "16693 Male\n", + "16694 Male\n", + "16695 Male\n", + "16696 Male\n", + "16697 Male\n", + "16698 Male\n", + "16699 Male\n", + "16700 Male\n", + "16701 Male\n", + "16702 Male\n", + "16703 Male\n", + "16704 Male\n", + "16705 Male\n", + "16706 Male\n", + "16707 Female\n", + "16708 Male\n", + "16709 Male\n", + "16710 Male\n", + "16711 Female\n", + "16712 Male\n", + "16713 Female\n", + "16714 Female\n", + "16715 Male\n", + "Name: GenderSelect, Length: 16716, dtype: object" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "multiple_choice.iloc[:,0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Mais detalhes sobre `loc`, `iloc` e `ix` podem ser vistas nesse [link](https://www.shanelynn.ie/select-pandas-dataframe-rows-and-columns-using-iloc-loc-and-ix/)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Desafio 2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Será que temos uma quantidade gigante de nulos nesse dataset porque as pessoas não preencheram essas perguntas por multipla escolha, por que responderam no modo livre? \n", + "\n", + "Para validar essa hipótese teremos que carregar o outro dataset, que contém as perguntas em forma livre. e juntar (Pelo menos uma das variáveis) dos dois os datasets. Eu escolhi `DataScienceIdentity`" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![challenge_panda](https://media.giphy.com/media/K9z3im98oo9Ve/giphy.gif)" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/usr/lib/python2.7/site-packages/IPython/core/interactiveshell.py:2718: DtypeWarning: Columns (5,17,21,38,50) have mixed types. Specify dtype option on import or set low_memory=False.\n", + " interactivity=interactivity, compiler=compiler, result=result)\n" + ] + } + ], + "source": [ + "free_responses = pd.read_csv('kaggle-survey-2017/freeformResponses.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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"WorkLibrariesFreeForm 12221\n", + "InterestingProblemFreeForm 12261\n", + "ImpactfulAlgorithmFreeForm 12369\n", + "PersonalProjectsChallengeFreeForm 13209\n", + "DataScienceIdentityFreeForm 14299\n", + "PastJobTitlesFreeForm 14622\n", + "CurrentJobTitleFreeForm 15573\n", + "BlogsPodcastsNewslettersFreeForm 15603\n", + "WorkMLTeamSeatFreeForm 15788\n", + "EmployerIndustryOtherFreeForm 15790\n", + "MajorFreeForm 15907\n", + "MLTechniquesFreeform 15963\n", + "KaggleMotivationFreeForm 15970\n", + "MLSkillsFreeForm 16050\n", + "WorkToolsFreeForm1 16052\n", + "WorkDataTypeFreeForm 16055\n", + "EmployerSearchMethodOtherFreeForm 16076\n", + "JobFunctionFreeForm 16212\n", + "LearningCategoryOtherFreeForm 16240\n", + "WorkAlgorithmsFreeForm 16303\n", + "MLToolNextYearFreeForm 16331\n", + "WorkCodeSharingFreeForm 16342\n", + "LearningPlatformUsefulnessFreeForm1Select 16347\n", + "TimeOtherSelectFreeForm 16358\n", + "CoursePlatformFreeForm 16384\n", + "LearningPlatformFreeForm1 16386\n", + "PublicDatasetsFreeForm 16454\n", + "WorkDataStorageFreeForm 16461\n", + "FirstTrainingFreeForm 16472\n", + "MLMethodNextYearFreeForm 16489\n", + "WorkChallengesFreeForm 16502\n", + "JobSkillImportanceOtherSelect1FreeForm 16515\n", + "JobSearchResourceFreeForm 16519\n", + "WorkMethodsFreeForm1 16528\n", + "LearningPlatformCommunityFreeForm 16537\n", + "GenderFreeForm 16582\n", + "WorkToolsFreeForm2 16583\n", + "WorkHardwareFreeForm 16595\n", + "ProveKnowledgeFreeForm 16595\n", + "HardwarePersonalProjectsFreeForm 16596\n", + "SalaryChangeFreeForm 16615\n", + "JobSkillImportanceOtherSelect2FreeForm 16629\n", + "LanguageRecommendationFreeForm 16635\n", + "WorkToolsFreeForm3 16636\n", + "LearningPlatformUsefulnessFreeForm2Select 16652\n", + "WorkMethodsFreeForm3 16657\n", + "LearningPlatformFreeForm2 16662\n", + "LearningPlatformUsefulnessFreeForm3Select 16662\n", + "LearningPlatformFreeForm3 16671\n", + "JobSkillImportanceOtherSelect3FreeForm 16681\n", + "WorkMethodsFreeForm2 16683\n", + "LearningPlatformUsefulnessFreeForm3SelectFreeForm 16716\n", + "WorkMethodsFrequencySelect1FreeForm 16716\n", + "WorkMethodsFrequencySelect2FreeForm 16716\n", + "WorkMethodsFrequencySelect3FreeForm 16716\n", + "LearningPlatformUsefulnessCommunitiesFreeForm 16716\n", + "WorkChallengeFrequencyOtherFreeForm 16716\n", + "WorkToolsFrequencySelect1FreeForm 16716\n", + "LearningPlatformUsefulnessFreeForm1SelectFreeForm 16716\n", + "LearningPlatformUsefulnessFreeForm2SelectFreeForm 16716\n", + "WorkFrequencySelect2FreeForm 16716\n", + "WorkFrequencySelect3FreeForm 16716\n", + "dtype: int64" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "free_responses.isnull().sum().sort_values()" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "free_index = free_responses['DataScienceIdentityFreeForm'].notnull()" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "identity_check = pd.DataFrame({'IdentityFree': free_responses[free_index]['DataScienceIdentityFreeForm'], \n", + " 'IdentitySelect': multiple_choice[free_index]['DataScienceIdentitySelect']})" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(2417, 2)" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "identity_check.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "IdentityFree 0\n", + "IdentitySelect 583\n", + "dtype: int64" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "identity_check.isnull().sum()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Aparentemente não foi isso que aconteceu..." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Alterando o dataset original" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "df = multiple_choice.copy()" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Yes, I'm focused on learning mostly data science skills 800\n", + "Yes, but data science is a small part of what I'm focused on learning 429\n", + "No, I am not focused on learning data science skills 55\n", + "Name: LearningDataScience, dtype: int64" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['LearningDataScience'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def replace_value(row):\n", + " if row == \"Yes, I'm focused on learning mostly data science skills\":\n", + " return \"yes\"\n", + " elif row == \"Yes, but data science is a small part of what I'm focused on learning\":\n", + " return \"so so\"\n", + " elif row == \"No, I am not focused on learning data science skills\":\n", + " return \"no\"" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "df['LearningDataScienceSimple'] = df['LearningDataScience'].apply(replace_value)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Agora podemos ver os novos valores desses campos" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "yes 800\n", + "so so 429\n", + "no 55\n", + "Name: LearningDataScienceSimple, dtype: int64" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['LearningDataScienceSimple'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(16716, 229)" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "E agora que a outra coluna muito complexa não serve mais, podemos descartá-la" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "df.drop(['LearningDataScience'], axis=1, inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(16716, 228)" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Pela quantidade de linhas no dataset percebemos que o `value_counts()` não retorna os valores nulos - e nós temos MUITOS valores nulos nessa coluna. Podemos utilizar um método do pandas para trocar os NAs por uma categoria nossa." + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "df['LearningDataScienceSimple'].fillna(\"did not answer the question\", inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "did not answer the question 15432\n", + "yes 800\n", + "so so 429\n", + "no 55\n", + "Name: LearningDataScienceSimple, dtype: int64" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['LearningDataScienceSimple'].value_counts()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Outra forma de alterar o dataset é utilizando funções _in place_ para isso utilizaremos o `lambda`" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Por exemplo: E se eu quiser atualizar a idade dos participantes? O dataset foi coletado em 2017 e já estamos em 2018" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "df['NewAge'] = df['Age'].apply(lambda x: x + 1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Vamos ver se funcionou? Vamos dar uma olhada nos primeiros 5 registros, com a coluna 'Age' e a 'NewAge' lado a lado" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " Column Question Asked\n", + "0 GenderSelect Select your gender identity. - Selected Choice All\n", + "1 GenderFreeForm Select your gender identity. - A different ide... All\n", + "2 Country Select the country you currently live in. All\n", + "3 Age What's your age? All\n", + "4 EmploymentStatus What's your current employment status? All" + ] + }, + "execution_count": 57, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "schema.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "CodingWorker 161\n", + "All 70\n", + "Learners 41\n", + "Worker1 6\n", + "CodingWorker-NC 5\n", + "Worker 2\n", + "OnlineLearners 2\n", + "Non-worker 2\n", + "Non-switcher 1\n", + "Name: Asked, dtype: int64" + ] + }, + "execution_count": 58, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "schema.Asked.value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "coding_worker_column = schema[schema['Asked'] == 'CodingWorker']['Column']\n", + "all_column = schema[schema['Asked'] == 'All']['Column']\n", + "learners_column = schema[schema['Asked'] == 'Learners']['Column']\n", + "others_columns = schema[(~ schema['Asked'].isin(['CodingWorker', 'All', 'Learners']))]['Column']" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "all_multiple_selection_cols = [c for c in all_column.values if 'freeform' not in c.lower()]\n", + "coding_worker_multiple_selection_cols = [c for c in coding_worker_column.values if 'freeform' not in c.lower()]\n", + "learners_multiple_selection_cols = [c for c in learners_column.values if 'freeform' not in c.lower()]\n", + "others_multiple_selection_cols = [c for c in others_columns.values if 'freeform' not in c.lower()]" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['StudentStatus',\n", + " 'LearningDataScience',\n", + " 'CodeWriter',\n", + " 'CareerSwitcher',\n", + " 'CurrentJobTitleSelect',\n", + " 'TitleFit',\n", + " 'CurrentEmployerType',\n", + " 'CoursePlatformSelect',\n", + " 'EmployerIndustry',\n", + " 'EmployerSize',\n", + " 'EmployerSizeChange',\n", + " 'EmployerMLTime',\n", + " 'EmployerSearchMethod']" + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "others_multiple_selection_cols" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "all_multiple_selection = multiple_choice[all_multiple_selection_cols]\n", + "coding_worker_multiple_selection = multiple_choice[coding_worker_multiple_selection_cols]\n", + "learners_multiple_selection = multiple_choice[learners_multiple_selection_cols]\n", + "others_multiple_selection = multiple_choice[others_multiple_selection_cols]" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(16716, 43)\n", + "(16716, 137)\n", + "(16716, 35)\n", + "(16716, 13)\n" + ] + } + ], + "source": [ + "print(all_multiple_selection.shape)\n", + "print(coding_worker_multiple_selection.shape)\n", + "print(learners_multiple_selection.shape)\n", + "print(others_multiple_selection.shape)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Lembrando que nós jogamos fora quem era 'free_form' - Logo, haverão sempre menos colunas do que vimos antes na quantidade por tipo de pessoa que respondeu." + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "all_multiple_selection.to_csv('all_multiple_selection.csv')\n", + "coding_worker_multiple_selection.to_csv('coding_worker_multiple_selection.csv')\n", + "learners_multiple_selection.to_csv('learners_multiple_selection.csv')\n", + "others_multiple_selection.to_csv('others_multiple_selection.csv')" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.15" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/3. Modelos regressivos/.DS_Store b/3. Modelos regressivos/.DS_Store new file mode 100644 index 0000000..5de4b30 Binary files /dev/null and b/3. Modelos regressivos/.DS_Store differ diff --git a/3. Modelos regressivos/.ipynb_checkpoints/Exemplo Regressao Polinomial com Split Test-checkpoint.ipynb b/3. Modelos regressivos/.ipynb_checkpoints/Exemplo Regressao Polinomial com Split Test-checkpoint.ipynb new file mode 100644 index 0000000..528f112 --- /dev/null +++ b/3. Modelos regressivos/.ipynb_checkpoints/Exemplo Regressao Polinomial com Split Test-checkpoint.ipynb @@ -0,0 +1,180 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Regressão Polinomial\n", + "\n", + "Um exemplo de split teste e predict na Regressao Polinomial" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "#Importe as bibliotecas que irá usar\n", + "\n", + "import numpy as np\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.linear_model import LinearRegression\n", + "from sklearn.preprocessing import PolynomialFeatures\n", + "from sklearn.model_selection import train_test_split" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# TODO: Crie a vaíavel do preditor e de saída. Carregue os dados\n", + "train_data = pd.read_csv('https://raw.githubusercontent.com/WoMakersCode/data-science-bootcamp/master/3.%20Modelos%20regressivos/Exercicio_3/position_salaries.csv')\n", + "X = train_data.iloc[:, 1:2].values\n", + "y = train_data.iloc[:, 2].values" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "#Split test\n", + "xtrain, xtest, ytrain, ytest = train_test_split(X, y, test_size = 0.2)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#Criando Regressao Linear\n", + "\n", + "lin_reg = LinearRegression()\n", + "lin_reg.fit(X, y)\n", + "\n", + "# Visualizando resultados\n", + "def viz_linear():\n", + " plt.scatter(X, y, color='red')\n", + " plt.plot(X, lin_reg.predict(X), color='blue')\n", + " plt.title('Truth or Bluff (Linear Regression)')\n", + " plt.xlabel('Position level')\n", + " plt.ylabel('Salary')\n", + " plt.show()\n", + " return\n", + "viz_linear()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Criando a regressao Polinomial\n", + "\n", + "poly_reg = PolynomialFeatures(degree=4)\n", + "X_poly = poly_reg.fit_transform(X)\n", + "pol_reg = LinearRegression()\n", + "pol_reg.fit(X_poly, y)\n", + "\n", + "# Visualizando resultados\n", + "def viz_polymonial():\n", + " plt.scatter(X, y, color='red')\n", + " plt.plot(X, pol_reg.predict(poly_reg.fit_transform(X)), color='blue')\n", + " plt.title('Truth or Bluff (Linear Regression)')\n", + " plt.xlabel('Position level')\n", + " plt.ylabel('Salary')\n", + " plt.show()\n", + " return\n", + "viz_polymonial()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([132148.43750002])" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Fazendo previsao\n", + "\n", + "# Fazendo previsão\n", + "lin_reg.predict([[5.5]])\n", + "\n", + "\n", + "# Fazendo previsao com Polymonial Regression\n", + "pol_reg.predict(poly_reg.fit_transform([[5.5]]))\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/3. Modelos regressivos/Exemplo Regressao Polinomial com Split Test.ipynb b/3. Modelos regressivos/Exemplo Regressao Polinomial com Split Test.ipynb new file mode 100644 index 0000000..528f112 --- /dev/null +++ b/3. Modelos regressivos/Exemplo Regressao Polinomial com Split Test.ipynb @@ -0,0 +1,180 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Regressão Polinomial\n", + "\n", + "Um exemplo de split teste e predict na Regressao Polinomial" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "#Importe as bibliotecas que irá usar\n", + "\n", + "import numpy as np\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.linear_model import LinearRegression\n", + "from sklearn.preprocessing import PolynomialFeatures\n", + "from sklearn.model_selection import train_test_split" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# TODO: Crie a vaíavel do preditor e de saída. Carregue os dados\n", + "train_data = pd.read_csv('https://raw.githubusercontent.com/WoMakersCode/data-science-bootcamp/master/3.%20Modelos%20regressivos/Exercicio_3/position_salaries.csv')\n", + "X = train_data.iloc[:, 1:2].values\n", + "y = train_data.iloc[:, 2].values" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "#Split test\n", + "xtrain, xtest, ytrain, ytest = train_test_split(X, y, test_size = 0.2)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#Criando Regressao Linear\n", + "\n", + "lin_reg = LinearRegression()\n", + "lin_reg.fit(X, y)\n", + "\n", + "# Visualizando resultados\n", + "def viz_linear():\n", + " plt.scatter(X, y, color='red')\n", + " plt.plot(X, lin_reg.predict(X), color='blue')\n", + " plt.title('Truth or Bluff (Linear Regression)')\n", + " plt.xlabel('Position level')\n", + " plt.ylabel('Salary')\n", + " plt.show()\n", + " return\n", + "viz_linear()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Criando a regressao Polinomial\n", + "\n", + "poly_reg = PolynomialFeatures(degree=4)\n", + "X_poly = poly_reg.fit_transform(X)\n", + "pol_reg = LinearRegression()\n", + "pol_reg.fit(X_poly, y)\n", + "\n", + "# Visualizando resultados\n", + "def viz_polymonial():\n", + " plt.scatter(X, y, color='red')\n", + " plt.plot(X, pol_reg.predict(poly_reg.fit_transform(X)), color='blue')\n", + " plt.title('Truth or Bluff (Linear Regression)')\n", + " plt.xlabel('Position level')\n", + " plt.ylabel('Salary')\n", + " plt.show()\n", + " return\n", + "viz_polymonial()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([132148.43750002])" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Fazendo previsao\n", + "\n", + "# Fazendo previsão\n", + "lin_reg.predict([[5.5]])\n", + "\n", + "\n", + "# Fazendo previsao com Polymonial Regression\n", + "pol_reg.predict(poly_reg.fit_transform([[5.5]]))\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/3. Modelos regressivos/Exercicio Diferencia\303\247\303\243o/tb-sales.xlsx" "b/3. Modelos regressivos/Exercicio Diferencia\303\247\303\243o/tb-sales.xlsx" new file mode 100644 index 0000000..d860e58 Binary files /dev/null and "b/3. Modelos regressivos/Exercicio Diferencia\303\247\303\243o/tb-sales.xlsx" differ diff --git "a/3. Modelos regressivos/Exercicio_1/.ipynb_checkpoints/[Solu\303\247\303\243o] Prevendo Expectativa de Vida-checkpoint.ipynb" "b/3. Modelos regressivos/Exercicio_1/.ipynb_checkpoints/[Solu\303\247\303\243o] Prevendo Expectativa de Vida-checkpoint.ipynb" new file mode 100644 index 0000000..3065849 --- /dev/null +++ "b/3. Modelos regressivos/Exercicio_1/.ipynb_checkpoints/[Solu\303\247\303\243o] Prevendo Expectativa de Vida-checkpoint.ipynb" @@ -0,0 +1,99 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# #Importe as bibliotecas que você irá usar\n", + "import pandas as pd\n", + "from sklearn.linear_model import LinearRegression\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "#Carregue os dados\n", + "#Insira o data frame nessa váriavel\n", + "bmi_life_data = pd.read_csv(\"bmi_and_life_expectancy.csv\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,\n", + " normalize=False)" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Execute o .fit do modelo e insira na variavel bmi_life_model\n", + "bmi_life_model = LinearRegression()\n", + "bmi_life_model.fit(bmi_life_data[['BMI']], bmi_life_data[['Life expectancy']])" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "#Faça predições usando o modelo para uma expectativa de vida de 21,07931\n", + "laos_life_exp = bmi_life_model.predict([[21.07931]])" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[60.31564716]]\n" + ] + } + ], + "source": [ + "print(laos_life_exp)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/3. Modelos regressivos/Prevendo Expectativa de Vida.ipynb b/3. Modelos regressivos/Exercicio_1/Prevendo Expectativa de Vida.ipynb similarity index 100% rename from 3. Modelos regressivos/Prevendo Expectativa de Vida.ipynb rename to 3. Modelos regressivos/Exercicio_1/Prevendo Expectativa de Vida.ipynb diff --git "a/3. Modelos regressivos/[Soluc\314\247a\314\203o] Prevendo Expectativa de Vida.ipynb" "b/3. Modelos regressivos/Exercicio_1/[Soluc\314\247a\314\203o] Prevendo Expectativa de Vida.ipynb" similarity index 65% rename from "3. Modelos regressivos/[Soluc\314\247a\314\203o] Prevendo Expectativa de Vida.ipynb" rename to "3. Modelos regressivos/Exercicio_1/[Soluc\314\247a\314\203o] Prevendo Expectativa de Vida.ipynb" index 1b646b7..3065849 100644 --- "a/3. Modelos regressivos/[Soluc\314\247a\314\203o] Prevendo Expectativa de Vida.ipynb" +++ "b/3. Modelos regressivos/Exercicio_1/[Soluc\314\247a\314\203o] Prevendo Expectativa de Vida.ipynb" @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -15,7 +15,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -26,24 +26,52 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,\n", + " normalize=False)" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "#Execute o .fit do modelo e insira na variavel bmi_life_model\n", "bmi_life_model = LinearRegression()\n", - "bmi_life_model.fit(bmi_life_data[['BMI']], bmi_life_data[['Life expectancy']])\n", - "\n" + "bmi_life_model.fit(bmi_life_data[['BMI']], bmi_life_data[['Life expectancy']])" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "#Faça predições usando o modelo para uma expectativa de vida de 21,07931\n", - "laos_life_exp = bmi_life_model.predict(21.07931)" + "laos_life_exp = bmi_life_model.predict([[21.07931]])" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[60.31564716]]\n" + ] + } + ], + "source": [ + "print(laos_life_exp)" ] } ], diff --git "a/3. Modelos regressivos/Exercicio_1/[Solu\303\247\303\243o] Prevendo Expectativa de Vida.ipynb" "b/3. Modelos regressivos/Exercicio_1/[Solu\303\247\303\243o] Prevendo Expectativa de Vida.ipynb" new file mode 100644 index 0000000..3065849 --- /dev/null +++ "b/3. Modelos regressivos/Exercicio_1/[Solu\303\247\303\243o] Prevendo Expectativa de Vida.ipynb" @@ -0,0 +1,99 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# #Importe as bibliotecas que você irá usar\n", + "import pandas as pd\n", + "from sklearn.linear_model import LinearRegression\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "#Carregue os dados\n", + "#Insira o data frame nessa váriavel\n", + "bmi_life_data = pd.read_csv(\"bmi_and_life_expectancy.csv\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,\n", + " normalize=False)" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Execute o .fit do modelo e insira na variavel bmi_life_model\n", + "bmi_life_model = LinearRegression()\n", + "bmi_life_model.fit(bmi_life_data[['BMI']], bmi_life_data[['Life expectancy']])" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "#Faça predições usando o modelo para uma expectativa de vida de 21,07931\n", + "laos_life_exp = bmi_life_model.predict([[21.07931]])" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[60.31564716]]\n" + ] + } + ], + "source": [ + "print(laos_life_exp)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/3. Modelos regressivos/bmi_and_life_expectancy.csv b/3. Modelos regressivos/Exercicio_1/bmi_and_life_expectancy.csv similarity index 100% rename from 3. Modelos regressivos/bmi_and_life_expectancy.csv rename to 3. Modelos regressivos/Exercicio_1/bmi_and_life_expectancy.csv diff --git "a/3. Modelos regressivos/Exercicio_2/.ipynb_checkpoints/[Solu\303\247\303\243o]Boston Houses Prices-checkpoint.ipynb" "b/3. Modelos regressivos/Exercicio_2/.ipynb_checkpoints/[Solu\303\247\303\243o]Boston Houses Prices-checkpoint.ipynb" new file mode 100644 index 0000000..f2754ff --- /dev/null +++ "b/3. Modelos regressivos/Exercicio_2/.ipynb_checkpoints/[Solu\303\247\303\243o]Boston Houses Prices-checkpoint.ipynb" @@ -0,0 +1,127 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Preços das Casas de Boston\n", + "\n", + "Agora vamos tentar prever o preço de casas? No próximo exercício, você usará o conjunto de dados de preços de casas em Boston. \n", + "\n", + "O conjunto de dados consiste em 13 features de 506 casas e o valor médio da casa em US $ 1000. \n", + "Você ajustará um modelo com 13 recursos para prever o valor das casas.\n", + "\n", + "Para concluir, siga as etapas abaixo:\n", + "\n", + "1. Construa um modelo de regressão linear\n", + "\n", + " Crie um modelo de regressão usando o LinearRegression do scikit-learn e atribua-o ao modelo.\n", + " Ajuste o modelo aos dados.\n", + " \n", + "2. Faça previsões usando o modelo\n", + "\n", + " Preveja o valor de sample_house." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.linear_model import LinearRegression\n", + "from sklearn.datasets import load_boston\n", + "\n", + "# Carregue os dados do boston dataset\n", + "boston_data = load_boston()\n", + "x = boston_data['data']\n", + "y = boston_data['target']\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,\n", + " normalize=False)" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# TODO: Faça o fit no modelo e insira na variável model\n", + "model = LinearRegression()\n", + "model.fit(x, y)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# Faça predições usando o modelo\n", + "\n", + "sample_house = [[2.29690000e-01, 0.00000000e+00, 1.05900000e+01, 0.00000000e+00, 4.89000000e-01,\n", + " 6.32600000e+00, 5.25000000e+01, 4.35490000e+00, 4.00000000e+00, 2.77000000e+02,\n", + " 1.86000000e+01, 3.94870000e+02, 1.09700000e+01]]\n", + "\n", + "# Insira suas predições na variável prediction\n", + "\n", + "prediction = model.predict(sample_house)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[23.68284712]\n" + ] + } + ], + "source": [ + "print(prediction)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/3. Modelos regressivos/Exercicio_2/Boston Houses Prices.ipynb b/3. Modelos regressivos/Exercicio_2/Boston Houses Prices.ipynb new file mode 100644 index 0000000..c5e51d7 --- /dev/null +++ b/3. Modelos regressivos/Exercicio_2/Boston Houses Prices.ipynb @@ -0,0 +1,90 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Preços das Casas de Boston\n", + "\n", + "Agora vamos tentar prever o preço de casas? No próximo exercício, você usará o conjunto de dados de preços de casas em Boston. \n", + "\n", + "O conjunto de dados consiste em 13 features de 506 casas e o valor médio da casa em US $ 1000. \n", + "Você ajustará um modelo com 13 recursos para prever o valor das casas.\n", + "\n", + "Para concluir, siga as etapas abaixo:\n", + "\n", + "1. Construa um modelo de regressão linear\n", + "\n", + " Crie um modelo de regressão usando o LinearRegression do scikit-learn e atribua-o ao modelo.\n", + " Ajuste o modelo aos dados.\n", + " \n", + "2. Faça previsões usando o modelo\n", + "\n", + " Preveja o valor de sample_house." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.linear_model import LinearRegression\n", + "from sklearn.datasets import load_boston\n", + "\n", + "# Carregue os dados do boston dataset\n", + "boston_data = load_boston()\n", + "x = boston_data['data']\n", + "y = boston_data['target']\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# TODO: Faça o fit no modelo e insira na variável model\n", + "model = None\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Faça predições usando o modelo\n", + "\n", + "sample_house = [[2.29690000e-01, 0.00000000e+00, 1.05900000e+01, 0.00000000e+00, 4.89000000e-01,\n", + " 6.32600000e+00, 5.25000000e+01, 4.35490000e+00, 4.00000000e+00, 2.77000000e+02,\n", + " 1.86000000e+01, 3.94870000e+02, 1.09700000e+01]]\n", + "\n", + "# Insira suas predições na variável prediction\n", + "\n", + "prediction = None" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/3. Modelos regressivos/Exercicio_2/[Soluc\314\247a\314\203o]Boston Houses Prices.ipynb" "b/3. Modelos regressivos/Exercicio_2/[Soluc\314\247a\314\203o]Boston Houses Prices.ipynb" new file mode 100644 index 0000000..f2754ff --- /dev/null +++ "b/3. Modelos regressivos/Exercicio_2/[Soluc\314\247a\314\203o]Boston Houses Prices.ipynb" @@ -0,0 +1,127 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Preços das Casas de Boston\n", + "\n", + "Agora vamos tentar prever o preço de casas? No próximo exercício, você usará o conjunto de dados de preços de casas em Boston. \n", + "\n", + "O conjunto de dados consiste em 13 features de 506 casas e o valor médio da casa em US $ 1000. \n", + "Você ajustará um modelo com 13 recursos para prever o valor das casas.\n", + "\n", + "Para concluir, siga as etapas abaixo:\n", + "\n", + "1. Construa um modelo de regressão linear\n", + "\n", + " Crie um modelo de regressão usando o LinearRegression do scikit-learn e atribua-o ao modelo.\n", + " Ajuste o modelo aos dados.\n", + " \n", + "2. Faça previsões usando o modelo\n", + "\n", + " Preveja o valor de sample_house." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.linear_model import LinearRegression\n", + "from sklearn.datasets import load_boston\n", + "\n", + "# Carregue os dados do boston dataset\n", + "boston_data = load_boston()\n", + "x = boston_data['data']\n", + "y = boston_data['target']\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,\n", + " normalize=False)" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# TODO: Faça o fit no modelo e insira na variável model\n", + "model = LinearRegression()\n", + "model.fit(x, y)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# Faça predições usando o modelo\n", + "\n", + "sample_house = [[2.29690000e-01, 0.00000000e+00, 1.05900000e+01, 0.00000000e+00, 4.89000000e-01,\n", + " 6.32600000e+00, 5.25000000e+01, 4.35490000e+00, 4.00000000e+00, 2.77000000e+02,\n", + " 1.86000000e+01, 3.94870000e+02, 1.09700000e+01]]\n", + "\n", + "# Insira suas predições na variável prediction\n", + "\n", + "prediction = model.predict(sample_house)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[23.68284712]\n" + ] + } + ], + "source": [ + "print(prediction)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/3. Modelos regressivos/Exercicio_2/[Solu\303\247\303\243o]Boston Houses Prices.ipynb" "b/3. Modelos regressivos/Exercicio_2/[Solu\303\247\303\243o]Boston Houses Prices.ipynb" new file mode 100644 index 0000000..f2754ff --- /dev/null +++ "b/3. Modelos regressivos/Exercicio_2/[Solu\303\247\303\243o]Boston Houses Prices.ipynb" @@ -0,0 +1,127 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Preços das Casas de Boston\n", + "\n", + "Agora vamos tentar prever o preço de casas? No próximo exercício, você usará o conjunto de dados de preços de casas em Boston. \n", + "\n", + "O conjunto de dados consiste em 13 features de 506 casas e o valor médio da casa em US $ 1000. \n", + "Você ajustará um modelo com 13 recursos para prever o valor das casas.\n", + "\n", + "Para concluir, siga as etapas abaixo:\n", + "\n", + "1. Construa um modelo de regressão linear\n", + "\n", + " Crie um modelo de regressão usando o LinearRegression do scikit-learn e atribua-o ao modelo.\n", + " Ajuste o modelo aos dados.\n", + " \n", + "2. Faça previsões usando o modelo\n", + "\n", + " Preveja o valor de sample_house." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.linear_model import LinearRegression\n", + "from sklearn.datasets import load_boston\n", + "\n", + "# Carregue os dados do boston dataset\n", + "boston_data = load_boston()\n", + "x = boston_data['data']\n", + "y = boston_data['target']\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,\n", + " normalize=False)" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# TODO: Faça o fit no modelo e insira na variável model\n", + "model = LinearRegression()\n", + "model.fit(x, y)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# Faça predições usando o modelo\n", + "\n", + "sample_house = [[2.29690000e-01, 0.00000000e+00, 1.05900000e+01, 0.00000000e+00, 4.89000000e-01,\n", + " 6.32600000e+00, 5.25000000e+01, 4.35490000e+00, 4.00000000e+00, 2.77000000e+02,\n", + " 1.86000000e+01, 3.94870000e+02, 1.09700000e+01]]\n", + "\n", + "# Insira suas predições na variável prediction\n", + "\n", + "prediction = model.predict(sample_house)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[23.68284712]\n" + ] + } + ], + "source": [ + "print(prediction)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/3. Modelos regressivos/Exercicio_3/.ipynb_checkpoints/[Solu\303\247\303\243o]Regress\303\243o Polinomial-checkpoint.ipynb" "b/3. Modelos regressivos/Exercicio_3/.ipynb_checkpoints/[Solu\303\247\303\243o]Regress\303\243o Polinomial-checkpoint.ipynb" new file mode 100644 index 0000000..9b21cde --- /dev/null +++ "b/3. Modelos regressivos/Exercicio_3/.ipynb_checkpoints/[Solu\303\247\303\243o]Regress\303\243o Polinomial-checkpoint.ipynb" @@ -0,0 +1,172 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Regressão Polinomial\n", + "\n", + "Agora vamos tentar praticar um pouco sobre como implementar regressão polinomial. No arquivo data.csv você poderá encontrar dados gerados para um feature preditora ('Var_X') e a feature de saída ('Var_Y'), seguindo um padrão não-linear.\n", + "\n", + "User a classe PolynomialFeatures do sklearn's para estender a coluna de feature de previsão em várias colunas com recursos polinomiais. Brinque com diferentes graus de polinômio e use o botão Test Run para ver o que melhor se encaixa.\n", + "\n", + "\n", + "Para concluir, siga as etapas abaixo:\n", + "\n", + "1. Carregue os dados\n", + "\n", + " Os dados estão no arquivo chamado 'data.csv'. Observe que esses dados têm uma linha de cabeçalho.\n", + " Certifique-se de dividir os dados na feature de previsão em X e na feature de resultado em y.\n", + " Para X, verifique se ele está em uma matriz bidimensional de 20 linhas por 1 coluna. Pode ser necessário usar a função de remodelação do NumPy para fazer isso.\n", + " \n", + "\n", + "2. Crie recursos polinomiais\n", + "\n", + " Crie uma instância da classe PolynomialFeatures do sklearn e atribua-a à variável poly_feat. Preste atenção em como definir o grau de recursos, pois será assim que o exercício será avaliado.\n", + " Crie os recursos polinomiais usando o método .fit_transform () do objeto PolynomialFeatures. O lado \"apto\" do método considera quantos recursos são necessários na saída e o lado \"transformação\" aplica essas considerações aos dados fornecidos ao método como argumento. Atribua a nova matriz de recurso à variável X_poly.\n", + "\n", + "3. Construa um modelo de regressão polinomial\n", + "\n", + " Crie um modelo de regressão polinomial combinando a classe LinearRegression do sklearn com os recursos polinomiais. Atribua o modelo de ajuste ao poly_model." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Importe as bibliotecas que irá usar\n", + "\n", + "import numpy as np\n", + "import pandas as pd\n", + "from sklearn.linear_model import LinearRegression\n", + "from sklearn.preprocessing import PolynomialFeatures\n", + "from sklearn.cross_validation import train_test_split" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# TODO: Crie a vaíavel do preditor e de saída. Carregue os dados\n", + "train_data = pd.read_csv('data.csv')\n", + "X = train_data['Var_X'].values.reshape(-1, 1)\n", + "y = train_data['Var_Y'].values\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Split test\n", + "xtrain, xtest, ytrain, ytest = train_test_split(X, y, test_size = 0.2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie as features polinomiais e depois faça um fit e transform na feature preditora\n", + "poly_feat = PolynomialFeatures(degree = 4)\n", + "X_poly = poly_feat.fit_transform(xtrain)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie e dê fit no modelo de regressão polinomial\n", + "ploy_reg = LinearRegression()\n", + "poly_model = ploy_reg.fit(X_poly, ytrain)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Visualizando resultados da regressao linear\n", + "def viz_linear():\n", + " plt.scatter(X, y, color='red')\n", + " plt.plot(X, lin_reg.predict(X), color='blue')\n", + " plt.title('Regressao Polinomial')\n", + " plt.xlabel('X')\n", + " plt.ylabel('Y)\n", + " plt.show()\n", + " return\n", + "viz_linear()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Fit Regressao Polinomial\n", + "\n", + "\n", + "y_predict = poly_model.predict(poly_reg.fit_transform(xtest))\n", + "\n", + " \n", + "# Visualizando resultados\n", + "def viz_polymonial():\n", + " plt.scatter(X, y, color='red')\n", + " plt.plot(X, pol_reg.predict(poly_reg.fit_transform(X)), color='blue')\n", + " plt.title('Truth or Bluff (Linear Regression)')\n", + " plt.xlabel('Position level')\n", + " plt.ylabel('Salary')\n", + " plt.show()\n", + " return\n", + "viz_polymonial()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Fazendo previsao\n", + "\n", + "# Fazendo previsão\n", + "lin_reg.predict([[5.5]])\n", + "\n", + "\n", + "# Fazendo previsao com Polymonial Regression\n", + "pol_reg.predict(poly_reg.fit_transform([[5.5]]))\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/3. Modelos regressivos/Exercicio_3/Regressa\314\203o Polinomial.ipynb" "b/3. Modelos regressivos/Exercicio_3/Regressa\314\203o Polinomial.ipynb" new file mode 100644 index 0000000..bf82746 --- /dev/null +++ "b/3. Modelos regressivos/Exercicio_3/Regressa\314\203o Polinomial.ipynb" @@ -0,0 +1,97 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Regressão Polinomial\n", + "\n", + "Agora vamos tentar praticar um pouco sobre como implementar regressão polinomial. No arquivo data.csv você poderá encontrar dados gerados para um feature preditora ('Var_X') e a feature de saída ('Var_Y'), seguindo um padrão não-linear.\n", + "\n", + "User a classe PolynomialFeatures do sklearn's para estender a coluna de feature de previsão em várias colunas com recursos polinomiais. Brinque com diferentes graus de polinômio e use o botão Test Run para ver o que melhor se encaixa.\n", + "\n", + "\n", + "Para concluir, siga as etapas abaixo:\n", + "\n", + "1. Carregue os dados\n", + "\n", + " Os dados estão no arquivo chamado 'data.csv'. Observe que esses dados têm uma linha de cabeçalho.\n", + " Certifique-se de dividir os dados na feature de previsão em X e na feature de resultado em y.\n", + " Para X, verifique se ele está em uma matriz bidimensional de 20 linhas por 1 coluna. Pode ser necessário usar a função de remodelação do NumPy para fazer isso.\n", + " \n", + "\n", + "2. Crie recursos polinomiais\n", + "\n", + " Crie uma instância da classe PolynomialFeatures do sklearn e atribua-a à variável poly_feat. Preste atenção em como definir o grau de recursos, pois será assim que o exercício será avaliado.\n", + " Crie os recursos polinomiais usando o método .fit_transform () do objeto PolynomialFeatures. O lado \"apto\" do método considera quantos recursos são necessários na saída e o lado \"transformação\" aplica essas considerações aos dados fornecidos ao método como argumento. Atribua a nova matriz de recurso à variável X_poly.\n", + "\n", + "3. Construa um modelo de regressão polinomial\n", + "\n", + " Crie um modelo de regressão polinomial combinando a classe LinearRegression do sklearn com os recursos polinomiais. Atribua o modelo de ajuste ao poly_model." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Importe as bibliotecas que irá usar" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# TODO: Crie a vaíavel do preditor e de saída. Carregue os dados\n", + "train_data = None\n", + "X = None\n", + "y = None\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie as features polinomiais e depois faça um fit e transform na feature preditora\n", + "poly_feat = None\n", + "X_poly = None" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie e de fit no modelo de regressão polinomial\n", + "poly_model = None" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/3. Modelos regressivos/Exercicio_3/Regress\303\243o Polinomial.ipynb" "b/3. Modelos regressivos/Exercicio_3/Regress\303\243o Polinomial.ipynb" new file mode 100644 index 0000000..bf82746 --- /dev/null +++ "b/3. Modelos regressivos/Exercicio_3/Regress\303\243o Polinomial.ipynb" @@ -0,0 +1,97 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Regressão Polinomial\n", + "\n", + "Agora vamos tentar praticar um pouco sobre como implementar regressão polinomial. No arquivo data.csv você poderá encontrar dados gerados para um feature preditora ('Var_X') e a feature de saída ('Var_Y'), seguindo um padrão não-linear.\n", + "\n", + "User a classe PolynomialFeatures do sklearn's para estender a coluna de feature de previsão em várias colunas com recursos polinomiais. Brinque com diferentes graus de polinômio e use o botão Test Run para ver o que melhor se encaixa.\n", + "\n", + "\n", + "Para concluir, siga as etapas abaixo:\n", + "\n", + "1. Carregue os dados\n", + "\n", + " Os dados estão no arquivo chamado 'data.csv'. Observe que esses dados têm uma linha de cabeçalho.\n", + " Certifique-se de dividir os dados na feature de previsão em X e na feature de resultado em y.\n", + " Para X, verifique se ele está em uma matriz bidimensional de 20 linhas por 1 coluna. Pode ser necessário usar a função de remodelação do NumPy para fazer isso.\n", + " \n", + "\n", + "2. Crie recursos polinomiais\n", + "\n", + " Crie uma instância da classe PolynomialFeatures do sklearn e atribua-a à variável poly_feat. Preste atenção em como definir o grau de recursos, pois será assim que o exercício será avaliado.\n", + " Crie os recursos polinomiais usando o método .fit_transform () do objeto PolynomialFeatures. O lado \"apto\" do método considera quantos recursos são necessários na saída e o lado \"transformação\" aplica essas considerações aos dados fornecidos ao método como argumento. Atribua a nova matriz de recurso à variável X_poly.\n", + "\n", + "3. Construa um modelo de regressão polinomial\n", + "\n", + " Crie um modelo de regressão polinomial combinando a classe LinearRegression do sklearn com os recursos polinomiais. Atribua o modelo de ajuste ao poly_model." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Importe as bibliotecas que irá usar" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# TODO: Crie a vaíavel do preditor e de saída. Carregue os dados\n", + "train_data = None\n", + "X = None\n", + "y = None\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie as features polinomiais e depois faça um fit e transform na feature preditora\n", + "poly_feat = None\n", + "X_poly = None" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie e de fit no modelo de regressão polinomial\n", + "poly_model = None" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/3. Modelos regressivos/Exercicio_3/[Soluc\314\247a\314\203o]Regressa\314\203o Polinomial.ipynb" "b/3. Modelos regressivos/Exercicio_3/[Soluc\314\247a\314\203o]Regressa\314\203o Polinomial.ipynb" new file mode 100644 index 0000000..9b21cde --- /dev/null +++ "b/3. Modelos regressivos/Exercicio_3/[Soluc\314\247a\314\203o]Regressa\314\203o Polinomial.ipynb" @@ -0,0 +1,172 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Regressão Polinomial\n", + "\n", + "Agora vamos tentar praticar um pouco sobre como implementar regressão polinomial. No arquivo data.csv você poderá encontrar dados gerados para um feature preditora ('Var_X') e a feature de saída ('Var_Y'), seguindo um padrão não-linear.\n", + "\n", + "User a classe PolynomialFeatures do sklearn's para estender a coluna de feature de previsão em várias colunas com recursos polinomiais. Brinque com diferentes graus de polinômio e use o botão Test Run para ver o que melhor se encaixa.\n", + "\n", + "\n", + "Para concluir, siga as etapas abaixo:\n", + "\n", + "1. Carregue os dados\n", + "\n", + " Os dados estão no arquivo chamado 'data.csv'. Observe que esses dados têm uma linha de cabeçalho.\n", + " Certifique-se de dividir os dados na feature de previsão em X e na feature de resultado em y.\n", + " Para X, verifique se ele está em uma matriz bidimensional de 20 linhas por 1 coluna. Pode ser necessário usar a função de remodelação do NumPy para fazer isso.\n", + " \n", + "\n", + "2. Crie recursos polinomiais\n", + "\n", + " Crie uma instância da classe PolynomialFeatures do sklearn e atribua-a à variável poly_feat. Preste atenção em como definir o grau de recursos, pois será assim que o exercício será avaliado.\n", + " Crie os recursos polinomiais usando o método .fit_transform () do objeto PolynomialFeatures. O lado \"apto\" do método considera quantos recursos são necessários na saída e o lado \"transformação\" aplica essas considerações aos dados fornecidos ao método como argumento. Atribua a nova matriz de recurso à variável X_poly.\n", + "\n", + "3. Construa um modelo de regressão polinomial\n", + "\n", + " Crie um modelo de regressão polinomial combinando a classe LinearRegression do sklearn com os recursos polinomiais. Atribua o modelo de ajuste ao poly_model." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Importe as bibliotecas que irá usar\n", + "\n", + "import numpy as np\n", + "import pandas as pd\n", + "from sklearn.linear_model import LinearRegression\n", + "from sklearn.preprocessing import PolynomialFeatures\n", + "from sklearn.cross_validation import train_test_split" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# TODO: Crie a vaíavel do preditor e de saída. Carregue os dados\n", + "train_data = pd.read_csv('data.csv')\n", + "X = train_data['Var_X'].values.reshape(-1, 1)\n", + "y = train_data['Var_Y'].values\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Split test\n", + "xtrain, xtest, ytrain, ytest = train_test_split(X, y, test_size = 0.2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie as features polinomiais e depois faça um fit e transform na feature preditora\n", + "poly_feat = PolynomialFeatures(degree = 4)\n", + "X_poly = poly_feat.fit_transform(xtrain)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie e dê fit no modelo de regressão polinomial\n", + "ploy_reg = LinearRegression()\n", + "poly_model = ploy_reg.fit(X_poly, ytrain)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Visualizando resultados da regressao linear\n", + "def viz_linear():\n", + " plt.scatter(X, y, color='red')\n", + " plt.plot(X, lin_reg.predict(X), color='blue')\n", + " plt.title('Regressao Polinomial')\n", + " plt.xlabel('X')\n", + " plt.ylabel('Y)\n", + " plt.show()\n", + " return\n", + "viz_linear()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Fit Regressao Polinomial\n", + "\n", + "\n", + "y_predict = poly_model.predict(poly_reg.fit_transform(xtest))\n", + "\n", + " \n", + "# Visualizando resultados\n", + "def viz_polymonial():\n", + " plt.scatter(X, y, color='red')\n", + " plt.plot(X, pol_reg.predict(poly_reg.fit_transform(X)), color='blue')\n", + " plt.title('Truth or Bluff (Linear Regression)')\n", + " plt.xlabel('Position level')\n", + " plt.ylabel('Salary')\n", + " plt.show()\n", + " return\n", + "viz_polymonial()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Fazendo previsao\n", + "\n", + "# Fazendo previsão\n", + "lin_reg.predict([[5.5]])\n", + "\n", + "\n", + "# Fazendo previsao com Polymonial Regression\n", + "pol_reg.predict(poly_reg.fit_transform([[5.5]]))\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/3. Modelos regressivos/Exercicio_3/[Solu\303\247\303\243o]Regress\303\243o Polinomial.ipynb" "b/3. Modelos regressivos/Exercicio_3/[Solu\303\247\303\243o]Regress\303\243o Polinomial.ipynb" new file mode 100644 index 0000000..9b21cde --- /dev/null +++ "b/3. Modelos regressivos/Exercicio_3/[Solu\303\247\303\243o]Regress\303\243o Polinomial.ipynb" @@ -0,0 +1,172 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Regressão Polinomial\n", + "\n", + "Agora vamos tentar praticar um pouco sobre como implementar regressão polinomial. No arquivo data.csv você poderá encontrar dados gerados para um feature preditora ('Var_X') e a feature de saída ('Var_Y'), seguindo um padrão não-linear.\n", + "\n", + "User a classe PolynomialFeatures do sklearn's para estender a coluna de feature de previsão em várias colunas com recursos polinomiais. Brinque com diferentes graus de polinômio e use o botão Test Run para ver o que melhor se encaixa.\n", + "\n", + "\n", + "Para concluir, siga as etapas abaixo:\n", + "\n", + "1. Carregue os dados\n", + "\n", + " Os dados estão no arquivo chamado 'data.csv'. Observe que esses dados têm uma linha de cabeçalho.\n", + " Certifique-se de dividir os dados na feature de previsão em X e na feature de resultado em y.\n", + " Para X, verifique se ele está em uma matriz bidimensional de 20 linhas por 1 coluna. Pode ser necessário usar a função de remodelação do NumPy para fazer isso.\n", + " \n", + "\n", + "2. Crie recursos polinomiais\n", + "\n", + " Crie uma instância da classe PolynomialFeatures do sklearn e atribua-a à variável poly_feat. Preste atenção em como definir o grau de recursos, pois será assim que o exercício será avaliado.\n", + " Crie os recursos polinomiais usando o método .fit_transform () do objeto PolynomialFeatures. O lado \"apto\" do método considera quantos recursos são necessários na saída e o lado \"transformação\" aplica essas considerações aos dados fornecidos ao método como argumento. Atribua a nova matriz de recurso à variável X_poly.\n", + "\n", + "3. Construa um modelo de regressão polinomial\n", + "\n", + " Crie um modelo de regressão polinomial combinando a classe LinearRegression do sklearn com os recursos polinomiais. Atribua o modelo de ajuste ao poly_model." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Importe as bibliotecas que irá usar\n", + "\n", + "import numpy as np\n", + "import pandas as pd\n", + "from sklearn.linear_model import LinearRegression\n", + "from sklearn.preprocessing import PolynomialFeatures\n", + "from sklearn.cross_validation import train_test_split" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# TODO: Crie a vaíavel do preditor e de saída. Carregue os dados\n", + "train_data = pd.read_csv('data.csv')\n", + "X = train_data['Var_X'].values.reshape(-1, 1)\n", + "y = train_data['Var_Y'].values\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Split test\n", + "xtrain, xtest, ytrain, ytest = train_test_split(X, y, test_size = 0.2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie as features polinomiais e depois faça um fit e transform na feature preditora\n", + "poly_feat = PolynomialFeatures(degree = 4)\n", + "X_poly = poly_feat.fit_transform(xtrain)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie e dê fit no modelo de regressão polinomial\n", + "ploy_reg = LinearRegression()\n", + "poly_model = ploy_reg.fit(X_poly, ytrain)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Visualizando resultados da regressao linear\n", + "def viz_linear():\n", + " plt.scatter(X, y, color='red')\n", + " plt.plot(X, lin_reg.predict(X), color='blue')\n", + " plt.title('Regressao Polinomial')\n", + " plt.xlabel('X')\n", + " plt.ylabel('Y)\n", + " plt.show()\n", + " return\n", + "viz_linear()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Fit Regressao Polinomial\n", + "\n", + "\n", + "y_predict = poly_model.predict(poly_reg.fit_transform(xtest))\n", + "\n", + " \n", + "# Visualizando resultados\n", + "def viz_polymonial():\n", + " plt.scatter(X, y, color='red')\n", + " plt.plot(X, pol_reg.predict(poly_reg.fit_transform(X)), color='blue')\n", + " plt.title('Truth or Bluff (Linear Regression)')\n", + " plt.xlabel('Position level')\n", + " plt.ylabel('Salary')\n", + " plt.show()\n", + " return\n", + "viz_polymonial()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Fazendo previsao\n", + "\n", + "# Fazendo previsão\n", + "lin_reg.predict([[5.5]])\n", + "\n", + "\n", + "# Fazendo previsao com Polymonial Regression\n", + "pol_reg.predict(poly_reg.fit_transform([[5.5]]))\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/3. Modelos regressivos/Exercicio_3/data.csv b/3. Modelos regressivos/Exercicio_3/data.csv new file mode 100644 index 0000000..4f43d46 --- /dev/null +++ b/3. Modelos regressivos/Exercicio_3/data.csv @@ -0,0 +1,21 @@ +Var_X,Var_Y +-0.33532,6.66854 +0.02160,3.86398 +-1.19438,5.16161 +-0.65046,8.43823 +-0.28001,5.57201 +1.93258,-11.13270 +1.22620,-5.31226 +0.74727,-4.63725 +3.32853,3.80650 +2.87457,-6.06084 +-1.48662,7.22328 +0.37629,2.38887 +1.43918,-7.13415 +0.24183,2.00412 +-2.79140,4.29794 +1.08176,-5.86553 +2.81555,-5.20711 +0.54924,-3.52863 +2.36449,-10.16202 +-1.01925,5.31123 \ No newline at end of file diff --git a/3. Modelos regressivos/Exercicio_3/position_salaries.csv b/3. Modelos regressivos/Exercicio_3/position_salaries.csv new file mode 100644 index 0000000..76d9d3e --- /dev/null +++ b/3. Modelos regressivos/Exercicio_3/position_salaries.csv @@ -0,0 +1,11 @@ +Position,Level,Salary +Business Analyst,1,45000 +Junior Consultant,2,50000 +Senior Consultant,3,60000 +Manager,4,80000 +Country Manager,5,110000 +Region Manager,6,150000 +Partner,7,200000 +Senior Partner,8,300000 +C-level,9,500000 +CEO,10,1000000 \ No newline at end of file diff --git a/3. Modelos regressivos/Exercicio_4/.ipynb_checkpoints/Feature Scaling-checkpoint.ipynb b/3. Modelos regressivos/Exercicio_4/.ipynb_checkpoints/Feature Scaling-checkpoint.ipynb new file mode 100644 index 0000000..c1a7570 --- /dev/null +++ b/3. Modelos regressivos/Exercicio_4/.ipynb_checkpoints/Feature Scaling-checkpoint.ipynb @@ -0,0 +1,131 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Feature Scaling\n", + "\n", + "Agora vamos tentar praticar um pouco sobre como normalizar nossos dados.\n", + "User a classe StanderScaler do Sklearn para estandatizar antes de uma regressão linear. \n", + "\n", + "\n", + "Para concluir, siga as etapas abaixo:\n", + "\n", + "1. Carregue os dados\n", + "\n", + " Os dados estão no arquivo chamado 'data.csv'. Observe que não há linha de cabeçalho neste arquivo.\n", + " Divida os dados para que os seis features preditoras (primeiras seis colunas) sejam armazenados em X e o resultado (última coluna) seja armazenado em y.\n", + "\n", + "\n", + "2. Execute o dimensionamento de recursos nos dados via padronização\n", + "\n", + " Crie uma instância do StandardScaler do sklearn e atribua a variavel scaler.\n", + " Calcule os parâmetros de dimensionamento usando o método .fit_transform () na matriz de recursos do preditor, que também retorna as variáveis do preditor em seus valores padronizados. Armazene esses valores padronizados em X_scaled.\n", + "\n", + "\n", + "3. Ajustar dados usando regressão linear \n", + "\n", + " Crie uma instância da classe Lasso do sklearn e atribua-a à variável Lonear_Regression(). Você não precisa definir nenhum valor de parâmetro: use os valores padrão para o questionário.\n", + " Use o método .fit () do objeto Regresao para ajustar o modelo de regressão aos dados. Certifique-se de aplicar o ajuste aos dados padronizados da etapa anterior (X_scaled), não aos dados originais.\n", + "\n", + "\n", + "4. Inspecione os coeficientes do modelo de regressão\n", + "\n", + " Obtenha os coeficientes do modelo de regressão de ajuste usando o atributo .coef_ do objeto Rregressao. Armazene isso na variável reg_coef: os coeficientes serão impressos." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Importe as bibliotecas que irá usar" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# TODO: Crie a vaíavel do preditor e de saída. Carregue os dados\n", + "train_data = None\n", + "X = None\n", + "y = None\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie o objeto de normalização\n", + "scaler = None" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie e de fit do objeto de normalização\n", + "x_scaled = None" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie um modelo de regressão linear\n", + "linear_reg = None" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#dê um fit no seu modelo" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Pegue e imprima os coeficientes do seu modelo de regressão.\n", + "reg_coef = None\n", + "print(reg_coef)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/3. Modelos regressivos/Exercicio_4/.ipynb_checkpoints/[Solu\303\247\303\243o]Feature Scaling-checkpoint.ipynb" "b/3. Modelos regressivos/Exercicio_4/.ipynb_checkpoints/[Solu\303\247\303\243o]Feature Scaling-checkpoint.ipynb" new file mode 100644 index 0000000..148f80b --- /dev/null +++ "b/3. Modelos regressivos/Exercicio_4/.ipynb_checkpoints/[Solu\303\247\303\243o]Feature Scaling-checkpoint.ipynb" @@ -0,0 +1,301 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Feature Scaling\n", + "\n", + "Agora vamos tentar praticar um pouco sobre como normalizar nossos dados.\n", + "User a classe StanderScaler do Sklearn para estandatizar antes de uma regressão linear. \n", + "\n", + "\n", + "Para concluir, siga as etapas abaixo:\n", + "\n", + "1. Carregue os dados\n", + "\n", + " Os dados estão no arquivo chamado 'data.csv'. Observe que não há linha de cabeçalho neste arquivo.\n", + " Divida os dados para que os seis features preditoras (primeiras seis colunas) sejam armazenados em X e o resultado (última coluna) seja armazenado em y.\n", + "\n", + "\n", + "2. Execute o dimensionamento de recursos nos dados via padronização\n", + "\n", + " Crie uma instância do StandardScaler do sklearn e atribua a variavel scaler.\n", + " Calcule os parâmetros de dimensionamento usando o método .fit_transform () na matriz de recursos do preditor, que também retorna as variáveis do preditor em seus valores padronizados. Armazene esses valores padronizados em X_scaled.\n", + "\n", + "\n", + "3. Ajustar dados usando regressão linear com regularização de Lasso\n", + "\n", + " Crie uma instância da classe Lasso do sklearn e atribua-a à variável lasso_reg. Você não precisa definir nenhum valor de parâmetro: use os valores padrão para o questionário.\n", + " Use o método .fit () do objeto Lasso para ajustar o modelo de regressão aos dados. Certifique-se de aplicar o ajuste aos dados padronizados da etapa anterior (X_scaled), não aos dados originais.\n", + "\n", + "\n", + "4. Inspecione os coeficientes do modelo de regressão\n", + "\n", + " Obtenha os coeficientes do modelo de regressão de ajuste usando o atributo .coef_ do objeto Lasso. Armazene isso na variável reg_coef: os coeficientes serão impressos" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [], + "source": [ + "#Importe as bibliotecas que irá usar\n", + "import numpy as np\n", + "import pandas as pd\n", + "from sklearn.linear_model import LinearRegression\n", + "from sklearn.preprocessing import StandardScaler\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import r2_score, mean_squared_error, mean_absolute_error" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [], + "source": [ + "# TODO: Crie a vaíavel do preditor e de saída. Carregue os dados\n", + "train_data = pd.read_csv('data.csv', header = None)\n", + "X = train_data.iloc[:,:-1]\n", + "y = train_data.iloc[:,-1]\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [], + "source": [ + "X_treino, X_teste, y_treino, y_teste = train_test_split(train_data.iloc[:,:-1], train_data.iloc[:,-1], test_size=0.3)" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie o objeto de normalização\n", + "scaler = StandardScaler()" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie e de fit do objeto de normalização\n", + "X_scaled = scaler.fit_transform(X_treino)" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie um modelo de regressão linear\n", + "lr = LinearRegression()" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,\n", + " normalize=False)" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#dê um fit no seu modelo\n", + "lr.fit(X_scaled, y_treino)" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[-9.85856608e-03 5.27612213e+00 1.04133561e+01 -6.18704694e-01\n", + " -1.22565933e+01 1.68774522e+00]\n" + ] + } + ], + "source": [ + "#Pegue e imprima os coeficientes do seu modelo de regressão.\n", + "reg_coef = lr.coef_\n", + "print(reg_coef)" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [], + "source": [ + "predito = lr.predict(X_teste)" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([65.82979866, 44.83985993, 13.62366917, 73.75651577, 42.56105671])" + ] + }, + "execution_count": 67, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "predito[:5]" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R²: -6.786127686388584\n" + ] + } + ], + "source": [ + "print('R²: ', lr.score(X_teste, y_teste))" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MSE: 1940.2265356923494\n" + ] + } + ], + "source": [ + "print('MSE: ', mean_squared_error(y_teste, predito))" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MAE: 37.125111509216744\n" + ] + } + ], + "source": [ + "print('MAE: ', mean_absolute_error(y_teste, predito))" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-9.85856608e-03, 5.27612213e+00, 1.04133561e+01, -6.18704694e-01,\n", + " -1.22565933e+01, 1.68774522e+00])" + ] + }, + "execution_count": 71, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lr.coef_" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0 : -0.009858566079575694\n", + "1 : 5.276122130446721\n", + "2 : 10.413356065166655\n", + "3 : -0.6187046944903595\n", + "4 : -12.256593300714483\n", + "5 : 1.6877452179873818\n" + ] + } + ], + "source": [ + "for i,coef in enumerate(lr.coef_):\n", + " print(train_data.columns[i],' : ', coef)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/3. Modelos regressivos/Exercicio_4/Feature Scaling.ipynb b/3. Modelos regressivos/Exercicio_4/Feature Scaling.ipynb new file mode 100644 index 0000000..c1a7570 --- /dev/null +++ b/3. Modelos regressivos/Exercicio_4/Feature Scaling.ipynb @@ -0,0 +1,131 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Feature Scaling\n", + "\n", + "Agora vamos tentar praticar um pouco sobre como normalizar nossos dados.\n", + "User a classe StanderScaler do Sklearn para estandatizar antes de uma regressão linear. \n", + "\n", + "\n", + "Para concluir, siga as etapas abaixo:\n", + "\n", + "1. Carregue os dados\n", + "\n", + " Os dados estão no arquivo chamado 'data.csv'. Observe que não há linha de cabeçalho neste arquivo.\n", + " Divida os dados para que os seis features preditoras (primeiras seis colunas) sejam armazenados em X e o resultado (última coluna) seja armazenado em y.\n", + "\n", + "\n", + "2. Execute o dimensionamento de recursos nos dados via padronização\n", + "\n", + " Crie uma instância do StandardScaler do sklearn e atribua a variavel scaler.\n", + " Calcule os parâmetros de dimensionamento usando o método .fit_transform () na matriz de recursos do preditor, que também retorna as variáveis do preditor em seus valores padronizados. Armazene esses valores padronizados em X_scaled.\n", + "\n", + "\n", + "3. Ajustar dados usando regressão linear \n", + "\n", + " Crie uma instância da classe Lasso do sklearn e atribua-a à variável Lonear_Regression(). Você não precisa definir nenhum valor de parâmetro: use os valores padrão para o questionário.\n", + " Use o método .fit () do objeto Regresao para ajustar o modelo de regressão aos dados. Certifique-se de aplicar o ajuste aos dados padronizados da etapa anterior (X_scaled), não aos dados originais.\n", + "\n", + "\n", + "4. Inspecione os coeficientes do modelo de regressão\n", + "\n", + " Obtenha os coeficientes do modelo de regressão de ajuste usando o atributo .coef_ do objeto Rregressao. Armazene isso na variável reg_coef: os coeficientes serão impressos." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Importe as bibliotecas que irá usar" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# TODO: Crie a vaíavel do preditor e de saída. Carregue os dados\n", + "train_data = None\n", + "X = None\n", + "y = None\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie o objeto de normalização\n", + "scaler = None" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie e de fit do objeto de normalização\n", + "x_scaled = None" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie um modelo de regressão linear\n", + "linear_reg = None" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#dê um fit no seu modelo" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Pegue e imprima os coeficientes do seu modelo de regressão.\n", + "reg_coef = None\n", + "print(reg_coef)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/3. Modelos regressivos/Exercicio_4/[Soluc\314\247a\314\203o]Feature Scaling.ipynb" "b/3. Modelos regressivos/Exercicio_4/[Soluc\314\247a\314\203o]Feature Scaling.ipynb" new file mode 100644 index 0000000..148f80b --- /dev/null +++ "b/3. Modelos regressivos/Exercicio_4/[Soluc\314\247a\314\203o]Feature Scaling.ipynb" @@ -0,0 +1,301 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Feature Scaling\n", + "\n", + "Agora vamos tentar praticar um pouco sobre como normalizar nossos dados.\n", + "User a classe StanderScaler do Sklearn para estandatizar antes de uma regressão linear. \n", + "\n", + "\n", + "Para concluir, siga as etapas abaixo:\n", + "\n", + "1. Carregue os dados\n", + "\n", + " Os dados estão no arquivo chamado 'data.csv'. Observe que não há linha de cabeçalho neste arquivo.\n", + " Divida os dados para que os seis features preditoras (primeiras seis colunas) sejam armazenados em X e o resultado (última coluna) seja armazenado em y.\n", + "\n", + "\n", + "2. Execute o dimensionamento de recursos nos dados via padronização\n", + "\n", + " Crie uma instância do StandardScaler do sklearn e atribua a variavel scaler.\n", + " Calcule os parâmetros de dimensionamento usando o método .fit_transform () na matriz de recursos do preditor, que também retorna as variáveis do preditor em seus valores padronizados. Armazene esses valores padronizados em X_scaled.\n", + "\n", + "\n", + "3. Ajustar dados usando regressão linear com regularização de Lasso\n", + "\n", + " Crie uma instância da classe Lasso do sklearn e atribua-a à variável lasso_reg. Você não precisa definir nenhum valor de parâmetro: use os valores padrão para o questionário.\n", + " Use o método .fit () do objeto Lasso para ajustar o modelo de regressão aos dados. Certifique-se de aplicar o ajuste aos dados padronizados da etapa anterior (X_scaled), não aos dados originais.\n", + "\n", + "\n", + "4. Inspecione os coeficientes do modelo de regressão\n", + "\n", + " Obtenha os coeficientes do modelo de regressão de ajuste usando o atributo .coef_ do objeto Lasso. Armazene isso na variável reg_coef: os coeficientes serão impressos" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [], + "source": [ + "#Importe as bibliotecas que irá usar\n", + "import numpy as np\n", + "import pandas as pd\n", + "from sklearn.linear_model import LinearRegression\n", + "from sklearn.preprocessing import StandardScaler\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import r2_score, mean_squared_error, mean_absolute_error" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [], + "source": [ + "# TODO: Crie a vaíavel do preditor e de saída. Carregue os dados\n", + "train_data = pd.read_csv('data.csv', header = None)\n", + "X = train_data.iloc[:,:-1]\n", + "y = train_data.iloc[:,-1]\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [], + "source": [ + "X_treino, X_teste, y_treino, y_teste = train_test_split(train_data.iloc[:,:-1], train_data.iloc[:,-1], test_size=0.3)" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie o objeto de normalização\n", + "scaler = StandardScaler()" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie e de fit do objeto de normalização\n", + "X_scaled = scaler.fit_transform(X_treino)" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie um modelo de regressão linear\n", + "lr = LinearRegression()" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,\n", + " normalize=False)" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#dê um fit no seu modelo\n", + "lr.fit(X_scaled, y_treino)" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[-9.85856608e-03 5.27612213e+00 1.04133561e+01 -6.18704694e-01\n", + " -1.22565933e+01 1.68774522e+00]\n" + ] + } + ], + "source": [ + "#Pegue e imprima os coeficientes do seu modelo de regressão.\n", + "reg_coef = lr.coef_\n", + "print(reg_coef)" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [], + "source": [ + "predito = lr.predict(X_teste)" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([65.82979866, 44.83985993, 13.62366917, 73.75651577, 42.56105671])" + ] + }, + "execution_count": 67, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "predito[:5]" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R²: -6.786127686388584\n" + ] + } + ], + "source": [ + "print('R²: ', lr.score(X_teste, y_teste))" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MSE: 1940.2265356923494\n" + ] + } + ], + "source": [ + "print('MSE: ', mean_squared_error(y_teste, predito))" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MAE: 37.125111509216744\n" + ] + } + ], + "source": [ + "print('MAE: ', mean_absolute_error(y_teste, predito))" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-9.85856608e-03, 5.27612213e+00, 1.04133561e+01, -6.18704694e-01,\n", + " -1.22565933e+01, 1.68774522e+00])" + ] + }, + "execution_count": 71, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lr.coef_" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0 : -0.009858566079575694\n", + "1 : 5.276122130446721\n", + "2 : 10.413356065166655\n", + "3 : -0.6187046944903595\n", + "4 : -12.256593300714483\n", + "5 : 1.6877452179873818\n" + ] + } + ], + "source": [ + "for i,coef in enumerate(lr.coef_):\n", + " print(train_data.columns[i],' : ', coef)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/3. Modelos regressivos/Exercicio_4/[Solu\303\247\303\243o]Feature Scaling.ipynb" "b/3. Modelos regressivos/Exercicio_4/[Solu\303\247\303\243o]Feature Scaling.ipynb" new file mode 100644 index 0000000..148f80b --- /dev/null +++ "b/3. Modelos regressivos/Exercicio_4/[Solu\303\247\303\243o]Feature Scaling.ipynb" @@ -0,0 +1,301 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Feature Scaling\n", + "\n", + "Agora vamos tentar praticar um pouco sobre como normalizar nossos dados.\n", + "User a classe StanderScaler do Sklearn para estandatizar antes de uma regressão linear. \n", + "\n", + "\n", + "Para concluir, siga as etapas abaixo:\n", + "\n", + "1. Carregue os dados\n", + "\n", + " Os dados estão no arquivo chamado 'data.csv'. Observe que não há linha de cabeçalho neste arquivo.\n", + " Divida os dados para que os seis features preditoras (primeiras seis colunas) sejam armazenados em X e o resultado (última coluna) seja armazenado em y.\n", + "\n", + "\n", + "2. Execute o dimensionamento de recursos nos dados via padronização\n", + "\n", + " Crie uma instância do StandardScaler do sklearn e atribua a variavel scaler.\n", + " Calcule os parâmetros de dimensionamento usando o método .fit_transform () na matriz de recursos do preditor, que também retorna as variáveis do preditor em seus valores padronizados. Armazene esses valores padronizados em X_scaled.\n", + "\n", + "\n", + "3. Ajustar dados usando regressão linear com regularização de Lasso\n", + "\n", + " Crie uma instância da classe Lasso do sklearn e atribua-a à variável lasso_reg. Você não precisa definir nenhum valor de parâmetro: use os valores padrão para o questionário.\n", + " Use o método .fit () do objeto Lasso para ajustar o modelo de regressão aos dados. Certifique-se de aplicar o ajuste aos dados padronizados da etapa anterior (X_scaled), não aos dados originais.\n", + "\n", + "\n", + "4. Inspecione os coeficientes do modelo de regressão\n", + "\n", + " Obtenha os coeficientes do modelo de regressão de ajuste usando o atributo .coef_ do objeto Lasso. Armazene isso na variável reg_coef: os coeficientes serão impressos" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [], + "source": [ + "#Importe as bibliotecas que irá usar\n", + "import numpy as np\n", + "import pandas as pd\n", + "from sklearn.linear_model import LinearRegression\n", + "from sklearn.preprocessing import StandardScaler\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import r2_score, mean_squared_error, mean_absolute_error" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [], + "source": [ + "# TODO: Crie a vaíavel do preditor e de saída. Carregue os dados\n", + "train_data = pd.read_csv('data.csv', header = None)\n", + "X = train_data.iloc[:,:-1]\n", + "y = train_data.iloc[:,-1]\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [], + "source": [ + "X_treino, X_teste, y_treino, y_teste = train_test_split(train_data.iloc[:,:-1], train_data.iloc[:,-1], test_size=0.3)" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie o objeto de normalização\n", + "scaler = StandardScaler()" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie e de fit do objeto de normalização\n", + "X_scaled = scaler.fit_transform(X_treino)" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie um modelo de regressão linear\n", + "lr = LinearRegression()" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,\n", + " normalize=False)" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#dê um fit no seu modelo\n", + "lr.fit(X_scaled, y_treino)" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[-9.85856608e-03 5.27612213e+00 1.04133561e+01 -6.18704694e-01\n", + " -1.22565933e+01 1.68774522e+00]\n" + ] + } + ], + "source": [ + "#Pegue e imprima os coeficientes do seu modelo de regressão.\n", + "reg_coef = lr.coef_\n", + "print(reg_coef)" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [], + "source": [ + "predito = lr.predict(X_teste)" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([65.82979866, 44.83985993, 13.62366917, 73.75651577, 42.56105671])" + ] + }, + "execution_count": 67, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "predito[:5]" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R²: -6.786127686388584\n" + ] + } + ], + "source": [ + "print('R²: ', lr.score(X_teste, y_teste))" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MSE: 1940.2265356923494\n" + ] + } + ], + "source": [ + "print('MSE: ', mean_squared_error(y_teste, predito))" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MAE: 37.125111509216744\n" + ] + } + ], + "source": [ + "print('MAE: ', mean_absolute_error(y_teste, predito))" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-9.85856608e-03, 5.27612213e+00, 1.04133561e+01, -6.18704694e-01,\n", + " -1.22565933e+01, 1.68774522e+00])" + ] + }, + "execution_count": 71, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lr.coef_" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0 : -0.009858566079575694\n", + "1 : 5.276122130446721\n", + "2 : 10.413356065166655\n", + "3 : -0.6187046944903595\n", + "4 : -12.256593300714483\n", + "5 : 1.6877452179873818\n" + ] + } + ], + "source": [ + "for i,coef in enumerate(lr.coef_):\n", + " print(train_data.columns[i],' : ', coef)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/3. 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Modelos regressivos/Exercicio_ARIMA/.DS_Store b/3. Modelos regressivos/Exercicio_ARIMA/.DS_Store new file mode 100644 index 0000000..5008ddf Binary files /dev/null and b/3. Modelos regressivos/Exercicio_ARIMA/.DS_Store differ diff --git a/3. Modelos regressivos/Exercicio_ARIMA/.ipynb_checkpoints/Prevendo Vendas Shampoo-checkpoint.ipynb b/3. Modelos regressivos/Exercicio_ARIMA/.ipynb_checkpoints/Prevendo Vendas Shampoo-checkpoint.ipynb new file mode 100644 index 0000000..dd7a1c1 --- /dev/null +++ b/3. Modelos regressivos/Exercicio_ARIMA/.ipynb_checkpoints/Prevendo Vendas Shampoo-checkpoint.ipynb @@ -0,0 +1,272 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Prevendo vendas de shampoo\n", + "\n", + "\n", + "Agora vamos praticar em python como criar um modelo ARIMA.\n", + "\n", + "Vamos analisar um dataset que contém vendas de shampoo durante um período de 3 anos. As unidades são vendas e ele possui 36 observações.\n", + "\n", + "Para concluir esse exercicio siga os passos abaixo:\n", + "\n", + "1. Importe as bibliotecas que irá usar\n", + "2. Importe o dataser shampoo-sales.csv\n", + "3. Gere o gráfico de autocorrelaçã0\n", + "4. Dê o fit no modelo\n", + "5. Faça previsão usando o modelo" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "#Primeiramente vamos importar as bibliotecas que iremos utilizar\n", + "\n", + "\n", + "import pandas as pd\n", + "import matplotlib as mtpl\n", + "from statsmodels.graphics.tsaplots import plot_acf, plot_pacf\n", + "from statsmodels.tsa.arima_model import ARIMA\n", + "\n", + "from sklearn.metrics import mean_squared_error\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Month\n", + "1901-01-01 266.0\n", + "1901-02-01 145.9\n", + "1901-03-01 183.1\n", + "1901-04-01 119.3\n", + "1901-05-01 180.3\n", + "Name: Sales, dtype: float64\n" + ] + }, + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#função para tratar campo data\n", + "def parser(x):\n", + " return pd.datetime.strptime('190'+x, '%Y-%m')\n", + "\n", + "#Importe o arquivo e insira na variável serie\n", + "series = \n", + "print(series.head())\n", + "series.plot()\n", + "mtpl.pyplot.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#plote o gráfico de autocorrelação\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/talitabarcelos/anaconda3/lib/python3.7/site-packages/statsmodels/tsa/base/tsa_model.py:171: ValueWarning: No frequency information was provided, so inferred frequency MS will be used.\n", + " % freq, ValueWarning)\n", + "/Users/talitabarcelos/anaconda3/lib/python3.7/site-packages/statsmodels/tsa/base/tsa_model.py:191: FutureWarning: Creating a DatetimeIndex by passing range endpoints is deprecated. Use `pandas.date_range` instead.\n", + " start=index[0], end=index[-1], freq=freq)\n", + "/Users/talitabarcelos/anaconda3/lib/python3.7/site-packages/statsmodels/tsa/base/tsa_model.py:171: ValueWarning: No frequency information was provided, so inferred frequency MS will be used.\n", + " % freq, ValueWarning)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " ARIMA Model Results \n", + "==============================================================================\n", + "Dep. Variable: D.Sales No. Observations: 35\n", + "Model: ARIMA(5, 1, 0) Log Likelihood -196.170\n", + "Method: css-mle S.D. of innovations 64.241\n", + "Date: Thu, 24 Oct 2019 AIC 406.340\n", + "Time: 23:51:56 BIC 417.227\n", + "Sample: 02-01-1901 HQIC 410.098\n", + " - 12-01-1903 \n", + "=================================================================================\n", + " coef std err z P>|z| [0.025 0.975]\n", + "---------------------------------------------------------------------------------\n", + "const 12.0649 3.652 3.304 0.003 4.908 19.222\n", + "ar.L1.D.Sales -1.1082 0.183 -6.063 0.000 -1.466 -0.750\n", + "ar.L2.D.Sales -0.6203 0.282 -2.203 0.036 -1.172 -0.068\n", + "ar.L3.D.Sales -0.3606 0.295 -1.222 0.231 -0.939 0.218\n", + "ar.L4.D.Sales -0.1252 0.280 -0.447 0.658 -0.674 0.424\n", + "ar.L5.D.Sales 0.1289 0.191 0.673 0.506 -0.246 0.504\n", + " Roots \n", + "=============================================================================\n", + " Real Imaginary Modulus Frequency\n", + "-----------------------------------------------------------------------------\n", + "AR.1 -1.0617 -0.5064j 1.1763 -0.4292\n", + "AR.2 -1.0617 +0.5064j 1.1763 0.4292\n", + "AR.3 0.0816 -1.3804j 1.3828 -0.2406\n", + "AR.4 0.0816 +1.3804j 1.3828 0.2406\n", + "AR.5 2.9315 -0.0000j 2.9315 -0.0000\n", + "-----------------------------------------------------------------------------\n" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 0\n", + "count 35.000000\n", + "mean -5.495218\n", + "std 68.132882\n", + "min -133.296637\n", + "25% -42.477890\n", + "50% -7.186512\n", + "75% 24.748330\n", + "max 133.237936\n" + ] + } + ], + "source": [ + "# fit modelo\n", + "model = \n", + "model_fit = " + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'fc' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m#faça a previsao\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mfc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconf\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;31m#plote o resultado\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'fc' is not defined" + ] + } + ], + "source": [ + "#faz split do modelo e a previsão\n", + "X = series.values\n", + "size = int(len(X) * 0.66)\n", + "train, test = X[0:size], X[size:len(X)]\n", + "history = [x for x in train]\n", + "predictions = list()\n", + "for t in range(len(test)):\n", + "\tmodel = ARIMA(history, order=(5,1,0))\n", + "\tmodel_fit = model.fit(disp=0)\n", + "\toutput = model_fit.forecast()\n", + "\tyhat = output[0]\n", + "\tpredictions.append(yhat)\n", + "\tobs = test[t]\n", + "\thistory.append(obs)\n", + "\tprint('predicted=%f, expected=%f' % (yhat, obs))\n", + "error = mean_squared_error(test, predictions)\n", + "print('Test MSE: %.3f' % error)\n", + "# plot\n", + "mtpl.pyplot.plot(test)\n", + "mtpl.pyplot.plot(predictions, color='red')\n", + "mtpl.pyplot.show()\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/3. Modelos regressivos/Exercicio_ARIMA/.ipynb_checkpoints/Prevendo com ARIMA-checkpoint.ipynb b/3. Modelos regressivos/Exercicio_ARIMA/.ipynb_checkpoints/Prevendo com ARIMA-checkpoint.ipynb new file mode 100644 index 0000000..04a80af --- /dev/null +++ b/3. Modelos regressivos/Exercicio_ARIMA/.ipynb_checkpoints/Prevendo com ARIMA-checkpoint.ipynb @@ -0,0 +1,785 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Prevendo com ARIMA\n", + "\n", + "\n", + "Agora vamos praticar em python como criar um modelo ARIMA.\n", + "\n", + "Vamos analisar um dataset que contém vendas de shampoo durante um período de 3 anos. As unidades são vendas e ele possui 36 observações." + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [], + "source": [ + "#Primeiramente vamos importar as bibliotecas que iremos utilizar\n", + "\n", + "\n", + "import pandas as pd\n", + "import matplotlib as plt\n", + "import numpy as np\n", + "from statsmodels.graphics.tsaplots import plot_acf, plot_pacf\n", + "from statsmodels.tsa.arima_model import ARIMA\n", + "from statsmodels.tsa.stattools import adfuller\n", + "from numpy import log\n", + "from sklearn.metrics import mean_squared_error\n", + "from statsmodels.tsa.stattools import acf\n" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " value\n", + "0 88\n", + "1 84\n", + "2 85\n", + "3 85\n", + "4 84\n" + ] + } + ], + "source": [ + "#função para tratar campo data\n", + "def parser(x):\n", + " return pd.datetime.strptime('190'+x, '%Y-%m')\n", + "\n", + "#Agora vamos importar nosso arquivo \n", + "df = pd.read_csv('dataset.csv',names=['value'], header=0)\n", + "print(series.head())\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.plot()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Podemos ver que o conjunto de dados tem uma tendência clara.\n", + "\n", + "Vamos também dar uma olhada rápida em um gráfico de autocorrelação da série temporal. Isso pode ser feito usando o Pandas. O exemplo abaixo plota a autocorrelação para um grande número de lags na série temporal." + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "pd.plotting.autocorrelation_plot(df)\n", + "plt.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Isso sugere que a série temporal não é estacionária e exigirá diferenciação para torná-la estacionária.\n", + "\n", + "Para torná-la estacionária precisaremos diferencia-la. \n", + "\n", + "O objetivo de diferenciá-lo para tornar a série temporal estacionária.\n", + "\n", + "Mas você precisa ter cuidado para não superestimar a série. Por isso, uma série super diferenciada ainda pode ser estacionária, o que, por sua vez, afetará os parâmetros do modelo.\n", + "\n", + "Então, como determinar a ordem correta de diferenciação?\n", + "\n", + "A ordem correta da diferenciação é a diferenciação mínima necessária para obter uma série quase estacionária que circula em torno de uma média definida e o gráfico do ACF chega a zero razoavelmente rápido.\n", + "\n", + "Se as autocorrelações forem positivas para muitos atrasos (10 ou mais), a série precisará ser diferenciada. Por outro lado, se a autocorrelação lag 1 em si for muito negativa, a série provavelmente será super diferenciada.\n", + "\n", + "No caso, você não pode realmente decidir entre duas ordens de diferenciação e seguir a ordem que apresenta o menor desvio padrão na série diferenciada.\n", + "\n", + "Vamos ver como fazer isso com um exemplo.\n", + "\n", + "Primeiro, vou verificar se a série está estacionária usando o teste Augmented Dickey Fuller (adfuller ()), do pacote statsmodels.\n", + "\n", + "Por quê?\n", + "\n", + "Porque você precisa diferenciar apenas se a série não for estacionária. Senão, nenhuma diferenciação é necessária, ou seja, d = 0.\n", + "\n", + "A hipótese nula do teste ADF é que a série temporal não é estacionária. Portanto, se o valor p do teste for menor que o nível de significância (0,05), você rejeita a hipótese nula e deduz que a série temporal é realmente estacionária.\n", + "\n", + "Portanto, no nosso caso, se P Value> 0,05, prosseguimos em busca da ordem da diferenciação.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ADF Statistic: -2.464240\n", + "p-value: 0.124419\n" + ] + } + ], + "source": [ + "result = adfuller(df.value.dropna())\n", + "print('ADF Statistic: %f' % result[0])\n", + "print('p-value: %f' % result[1])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Como o valor p é maior que o nível de significância, vamos diferenciar as séries e ver como fica o gráfico de autocorrelação." + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.rcParams.update({'figure.figsize':(9,7), 'figure.dpi':120})\n", + "\n", + "# Importando dados\n", + "df = pd.read_csv('https://raw.githubusercontent.com/selva86/datasets/master/wwwusage.csv', names=['value'], header=0)\n", + "\n", + "# Série Original\n", + "fig, axes = plt.pyplot.subplots(3, 2, sharex=True)\n", + "axes[0, 0].plot(df.value); axes[0, 0].set_title('Original Series')\n", + "plot_acf(df.value, ax=axes[0, 1])\n", + "\n", + "# 1st Diferenciação\n", + "axes[1, 0].plot(df.value.diff()); axes[1, 0].set_title('1st Order Differencing')\n", + "plot_acf(df.value.diff().dropna(), ax=axes[1, 1])\n", + "\n", + "# 2nd Diferenciação\n", + "axes[2, 0].plot(df.value.diff().diff()); axes[2, 0].set_title('2nd Order Differencing')\n", + "plot_acf(df.value.diff().diff().dropna(), ax=axes[2, 1])\n", + "\n", + "plt.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Para as séries acima, a série temporal atinge a estacionariedade com duas ordens de diferenciação.\n", + "Mas, olhando para o gráfico de autocorrelação para a segunda diferenciação do lag, entra na zona negativa muito rápido, o que indica que a série pode ter sido super diferenciada.\n", + "\n", + "Então, tentarei fixar provisoriamente a ordem da diferenção como 1, mesmo que a série não seja perfeitamente estacionária (fraca estacionariedade).\n", + "\n", + "\n", + "# Como encontrar a ordem do termo AR (p)\n", + "\n", + "A próxima etapa é identificar se o modelo precisa de termos de AR. Você pode descobrir o número necessário de termos de AR, inspecionando o gráfico PACF (Plot de correlação parcial).\n", + "\n", + "Mas o que é PACF?\n", + "\n", + "A autocorrelação parcial pode ser imaginada como a correlação entre a série e seu lag, após excluir as contribuições dos atrasos intermediários. Portanto, o PACF meio que transmite a correlação pura entre um lag e a série. Dessa forma, você saberá se esse lag é necessário no termo AR ou não.\n", + "\n", + "\n", + "Agora, como encontrar o número de termos de AR?\n", + "\n", + "Qualquer autocorrelação em uma série estacionarizada pode ser retificada adicionando termos de AR suficientes. Portanto, inicialmente consideramos a ordem do termo AR igual a tantos lags que ultrapassam o limite de significância no gráfico PACF." + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# PACF plot da serie diferenciada 1x\n", + "\n", + "fig, axes = plt.pyplot.subplots(1, 2, sharex=True)\n", + "axes[0].plot(df.value.diff()); axes[0].set_title('1st Differencing')\n", + "axes[1].set(ylim=(0,5))\n", + "plot_pacf(df.value.diff().dropna(), ax=axes[1])\n", + "\n", + "plt.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Você pode observar que o lag 1 do PACF é bastante significativo, pois está bem acima da linha de significância. O lag 2 também é significativo, conseguindo ultrapassar um pouco o limite de significância (região azul). Mas vou ser conservadora e, provisoriamente, corrigir o p como 1.\n", + "\n", + "\n", + "# Como encontrar a ordem do termo MA (q)\n", + "\n", + "Assim como observamos o gráfico do PACF para o número de termos de AR, você pode ver o gráfico do ACF para o número de termos de MA. Um termo MA é tecnicamente o erro da previsão atrasada.\n", + "\n", + "O ACF informa quantos termos de MA são necessários para remover qualquer autocorrelação na série estacionarizada.\n", + "\n", + "Vamos ver o gráfico de autocorrelação das séries diferenciadas." + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.pyplot.subplots(1, 2, sharex=True)\n", + "axes[0].plot(df.value.diff()); axes[0].set_title('1st Differencing')\n", + "axes[1].set(ylim=(0,1.2))\n", + "plot_acf(df.value.diff().dropna(), ax=axes[1])\n", + "\n", + "plt.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Algumas defasagens estão bem acima da linha de significância. Então, vamos tentar usar provisoriamente q como 2. Em caso de dúvida, siga o modelo mais simples que explica suficientemente o Y.\n", + "\n", + "\n", + "# Como lidar se uma série temporal é um pouco abaixo ou acima da diferença\n", + "\n", + "Pode acontecer que sua série esteja ligeiramente menos diferenciada, aonde diferenciá-la mais uma vez a torne um pouco super diferenciada.\n", + "\n", + "Como lidar com este caso?\n", + "\n", + "Se sua série estiver um pouco menos diferenciada, a adição de um ou mais termos adicionais de AR geralmente o fará. Da mesma forma, se houver um pouco de diferença excessiva, tente adicionar um termo MA adicional.\n", + "\n", + "\n", + "# Como construir o modelo ARIMA\n", + "\n", + "Agora que você determinou os valores de p, d e q, você tem tudo o que é necessário para se ajustar ao modelo ARIMA. Vamos usar a implementação ARIMA () no pacote statsmodels." + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " ARIMA Model Results \n", + "==============================================================================\n", + "Dep. Variable: D.value No. Observations: 99\n", + "Model: ARIMA(1, 1, 2) Log Likelihood -253.790\n", + "Method: css-mle S.D. of innovations 3.119\n", + "Date: Fri, 25 Oct 2019 AIC 517.579\n", + "Time: 21:57:36 BIC 530.555\n", + "Sample: 1 HQIC 522.829\n", + " \n", + "=================================================================================\n", + " coef std err z P>|z| [0.025 0.975]\n", + "---------------------------------------------------------------------------------\n", + "const 1.1202 1.290 0.868 0.387 -1.409 3.649\n", + "ar.L1.D.value 0.6351 0.257 2.469 0.015 0.131 1.139\n", + "ma.L1.D.value 0.5287 0.355 1.489 0.140 -0.167 1.224\n", + "ma.L2.D.value -0.0010 0.321 -0.003 0.998 -0.631 0.629\n", + " Roots \n", + "=============================================================================\n", + " Real Imaginary Modulus Frequency\n", + "-----------------------------------------------------------------------------\n", + "AR.1 1.5746 +0.0000j 1.5746 0.0000\n", + "MA.1 -1.8850 +0.0000j 1.8850 0.5000\n", + "MA.2 544.7269 +0.0000j 544.7269 0.0000\n", + "-----------------------------------------------------------------------------\n" + ] + } + ], + "source": [ + "# 1,1,2 ARIMA Model\n", + "model = ARIMA(df.value, order=(1,1,2))\n", + "model_fit = model.fit(disp=0)\n", + "print(model_fit.summary())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "O resumo do modelo revela muitas informações. A tabela no meio é a tabela de coeficientes em que os valores em \"coef\" são os pesos dos respectivos termos.\n", + "\n", + "Observe aqui que o coeficiente do termo MA2 é próximo de zero e o valor P na coluna 'P> | z |' é altamente insignificante. Idealmente, deveria ser menor que 0,05 para o respectivo X ser significativo.\n", + "\n", + "Então, vamos reconstruir o modelo sem o termo MA2." + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " ARIMA Model Results \n", + "==============================================================================\n", + "Dep. Variable: D.value No. Observations: 99\n", + "Model: ARIMA(1, 1, 1) Log Likelihood -253.790\n", + "Method: css-mle S.D. of innovations 3.119\n", + "Date: Fri, 25 Oct 2019 AIC 515.579\n", + "Time: 21:58:38 BIC 525.960\n", + "Sample: 1 HQIC 519.779\n", + " \n", + "=================================================================================\n", + " coef std err z P>|z| [0.025 0.975]\n", + "---------------------------------------------------------------------------------\n", + "const 1.1205 1.286 0.871 0.386 -1.400 3.641\n", + "ar.L1.D.value 0.6344 0.087 7.317 0.000 0.464 0.804\n", + "ma.L1.D.value 0.5297 0.089 5.932 0.000 0.355 0.705\n", + " Roots \n", + "=============================================================================\n", + " Real Imaginary Modulus Frequency\n", + "-----------------------------------------------------------------------------\n", + "AR.1 1.5764 +0.0000j 1.5764 0.0000\n", + "MA.1 -1.8879 +0.0000j 1.8879 0.5000\n", + "-----------------------------------------------------------------------------\n" + ] + } + ], + "source": [ + "# 1,1,1 ARIMA Model\n", + "model = ARIMA(df.value, order=(1,1,1))\n", + "model_fit = model.fit(disp=0)\n", + "print(model_fit.summary())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "O modelo AIC reduziu, o que é bom. Os valores P dos termos AR1 e MA1 melhoraram e são altamente significativos (<< 0,05).\n", + "\n", + "Vamos traçar os resíduos para garantir que não haja padrões (ou seja, procure média e variação constantes)." + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Plot erro residual\n", + "residuals = pd.DataFrame(model_fit.resid)\n", + "fig, ax = plt.pyplot.subplots(1,2)\n", + "residuals.plot(title=\"Residuals\", ax=ax[0])\n", + "residuals.plot(kind='kde', title='Density', ax=ax[1])\n", + "plt.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Os erros residuais parecem bons com média próxima de zero e variância uniforme. Vamos plotar os valores reais em relação aos valores ajustados usando plot_predict ()." + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Atual vs Previsto\n", + "model_fit.plot_predict(dynamic=False)\n", + "plt.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Quando você define dynamic = False, os valores lag na amostra são usados para previsão.\n", + "\n", + "Ou seja, o modelo é treinado até o valor anterior para fazer a próxima previsão. Isso pode fazer com que a previsão e os dados reais pareçam artificialmente bons.\n", + "\n", + "Portanto, parece que temos um modelo ARIMA decente. Mas esse é o melhor?\n", + "\n", + "Não posso dizer isso neste momento, porque ainda não previmos o futuro e comparamos a previsão com o desempenho real.\n", + "\n", + "Portanto, a validação real de que você precisa agora é a validação cruzada de Out-Time.\n", + "\n", + "# Como encontrar o modelo ARIMA ideal manualmente usando a validação cruzada Out-Time\n", + "\n", + "Na validação cruzada Out_Time, você dá alguns passos para trás no tempo e projeta no futuro quantos passos você deu. Em seguida, você compara a previsão com os dados reais.\n", + "\n", + "Para realizar a validação cruzada fora do tempo, você precisa criar o conjunto de dados de treinamento e teste dividindo a série temporal em duas partes contíguas em uma proporção de aproximadamente 75:25 ou uma proporção razoável com base na frequência temporal das séries.\n", + "\n", + "Por que não estou amostrando os dados de treinamento aleatoriamente, você pergunta?\n", + "\n", + "Isso ocorre porque a sequência de pedidos da série temporal deve estar intacta para usá-la na previsão." + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Cria Training and Test set\n", + "train = df.value[:85]\n", + "test = df.value[85:]\n", + "\n", + "# Cria Modelo\n", + "# modelo = ARIMA(train, order=(3,2,1)) \n", + "model = ARIMA(train, order=(1, 1, 1)) \n", + "fitted = model.fit(disp=-1) \n", + "\n", + "# Previsao\n", + "fc, se, conf = fitted.forecast(15, alpha=0.05) # 95% conf\n", + "\n", + "# Cria como um pandas dataframe\n", + "fc_series = pd.Series(fc, index=test.index)\n", + "lower_series = pd.Series(conf[:, 0], index=test.index)\n", + "upper_series = pd.Series(conf[:, 1], index=test.index)\n", + "\n", + "# Plota\n", + "plt.pyplot.figure(figsize=(12,5), dpi=100)\n", + "plt.pyplot.plot(train, label='training')\n", + "plt.pyplot.plot(test, label='actual')\n", + "plt.pyplot.plot(fc_series, label='forecast')\n", + "plt.pyplot.fill_between(lower_series.index, lower_series, upper_series, \n", + " color='k', alpha=.15)\n", + "plt.pyplot.title('Forecast vs Actuals')\n", + "plt.pyplot.legend(loc='upper left', fontsize=8)\n", + "plt.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A partir do gráfico, o modelo ARIMA (1,1,1) parece fornecer uma previsão direcional correta. E os valores reais observados estão dentro da faixa de confiança de 95%. Isso parece bom.\n", + "\n", + "Mas cada uma das previsões previstas é consistentemente abaixo dos valores reais. Isso significa que, ao adicionar uma pequena constante à nossa previsão, a precisão certamente aumentará. Portanto, definitivamente há margem para melhorias.\n", + "\n", + "Então, o que vou fazer é aumentar a ordem de diferenciação para dois, que é definido d = 2 e aumentar iterativamente p para até 5 e depois q até 5 para ver qual modelo oferece menor AIC e também procurar um gráfico que fornece dados reais e previsões mais próximos.\n", + "\n", + "Enquanto isso, fico de olho nos valores P dos termos AR e MA no resumo do modelo. Eles devem estar o mais próximo de zero, idealmente, menores que 0,05." + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " ARIMA Model Results \n", + "==============================================================================\n", + "Dep. Variable: D2.value No. Observations: 83\n", + "Model: ARIMA(3, 2, 1) Log Likelihood -214.248\n", + "Method: css-mle S.D. of innovations 3.153\n", + "Date: Fri, 25 Oct 2019 AIC 440.497\n", + "Time: 22:07:14 BIC 455.010\n", + "Sample: 2 HQIC 446.327\n", + " \n", + "==================================================================================\n", + " coef std err z P>|z| [0.025 0.975]\n", + "----------------------------------------------------------------------------------\n", + "const 0.0483 0.084 0.577 0.565 -0.116 0.212\n", + "ar.L1.D2.value 1.1386 0.109 10.399 0.000 0.924 1.353\n", + "ar.L2.D2.value -0.5923 0.155 -3.827 0.000 -0.896 -0.289\n", + "ar.L3.D2.value 0.3079 0.111 2.778 0.007 0.091 0.525\n", + "ma.L1.D2.value -1.0000 0.035 -28.799 0.000 -1.068 -0.932\n", + " Roots \n", + "=============================================================================\n", + " Real Imaginary Modulus Frequency\n", + "-----------------------------------------------------------------------------\n", + "AR.1 1.1557 -0.0000j 1.1557 -0.0000\n", + "AR.2 0.3839 -1.6318j 1.6763 -0.2132\n", + "AR.3 0.3839 +1.6318j 1.6763 0.2132\n", + "MA.1 1.0000 +0.0000j 1.0000 0.0000\n", + "-----------------------------------------------------------------------------\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Constroi Modelo\n", + "model = ARIMA(train, order=(3, 2, 1)) \n", + "fitted = model.fit(disp=-1) \n", + "print(fitted.summary())\n", + "\n", + "# Faz previsao\n", + "fc, se, conf = fitted.forecast(15, alpha=0.05) # 95% conf\n", + "\n", + "# Cria pandas dataframa\n", + "fc_series = pd.Series(fc, index=test.index)\n", + "lower_series = pd.Series(conf[:, 0], index=test.index)\n", + "upper_series = pd.Series(conf[:, 1], index=test.index)\n", + "\n", + "# Plota\n", + "plt.pyplot.figure(figsize=(12,5), dpi=100)\n", + "plt.pyplot.plot(train, label='training')\n", + "plt.pyplot.plot(test, label='actual')\n", + "plt.pyplot.plot(fc_series, label='forecast')\n", + "plt.pyplot.fill_between(lower_series.index, lower_series, upper_series, \n", + " color='k', alpha=.15)\n", + "plt.pyplot.title('Forecast vs Actuals')\n", + "plt.pyplot.legend(loc='upper left', fontsize=8)\n", + "plt.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A AIC reduziu de 515 para 440. Bom. Os valores P dos termos X são menores que <0,05, o que é ótimo.\n", + "\n", + "Então, no geral, é muito melhor.\n", + "\n", + "Idealmente, você deve voltar vários pontos no tempo, como 1, 2, 3 e 4 trimestres e ver como suas previsões estão se saindo em vários pontos do ano.\n", + "\n", + "Aqui está um ótimo exercício: tente retroceder 27, 30, 33, 36 pontos de dados e ver o desempenho das proibições. O desempenho da previsão pode ser avaliado usando várias métricas de precisão discutidas a seguir.\n", + "\n", + "\n", + "# Métricas de precisão para previsão de séries temporais\n", + "\n", + "As métricas de precisão comumente usadas para avaliar previsões são:\n", + "\n", + "Erro percentual absoluto médio (MAPE)\n", + "Erro médio (ME)\n", + "Erro Absoluto Médio (MAE)\n", + "Erro percentual médio (MPE)\n", + "Erro médio quadrático da raiz (RMSE)\n", + "Lag 1 Autocorrelação de Erro (ACF1)\n", + "Correlação entre o atual e o previsto (corr)\n", + "Min-Max Error (minmax)\n", + "\n", + "Normalmente, se você estiver comparando previsões de duas séries diferentes, o MAPE, Correlação e Erro Mín. Máx. Podem ser usados.\n", + "\n", + "Por que não usar as outras métricas?\n", + "\n", + "Como apenas os três acima são erros percentuais que variam entre 0 e 1. Dessa forma, você pode julgar o quão boa é a previsão, independentemente da escala da série.\n", + "\n", + "As outras métricas de erro são quantidades. Isso implica que um RMSE de 100 para uma série cuja média é de 1000 é melhor que um RMSE de 5 para séries de 10. Portanto, você não pode usá-los para comparar as previsões de duas séries temporais em escala diferentes." + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'mape': 0.022501305114356305,\n", + " 'me': 3.2307774659756165,\n", + " 'mae': 4.548320385364536,\n", + " 'mpe': 0.016420975902695575,\n", + " 'rmse': 6.373234889679405,\n", + " 'acf1': 0.5105507587572337,\n", + " 'corr': 0.9674576520337695,\n", + " 'minmax': 0.02163154042918869}" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Metricas\n", + "def forecast_accuracy(forecast, actual):\n", + " mape = np.mean(np.abs(forecast - actual)/np.abs(actual)) # MAPE\n", + " me = np.mean(forecast - actual) # ME\n", + " mae = np.mean(np.abs(forecast - actual)) # MAE\n", + " mpe = np.mean((forecast - actual)/actual) # MPE\n", + " rmse = np.mean((forecast - actual)**2)**.5 # RMSE\n", + " corr = np.corrcoef(forecast, actual)[0,1] # corr\n", + " mins = np.amin(np.hstack([forecast[:,None], \n", + " actual[:,None]]), axis=1)\n", + " maxs = np.amax(np.hstack([forecast[:,None], \n", + " actual[:,None]]), axis=1)\n", + " minmax = 1 - np.mean(mins/maxs) # minmax\n", + " acf1 = acf(fc-test)[1] # ACF1\n", + " return({'mape':mape, 'me':me, 'mae': mae, \n", + " 'mpe': mpe, 'rmse':rmse, 'acf1':acf1, \n", + " 'corr':corr, 'minmax':minmax})\n", + "\n", + "forecast_accuracy(fc, test.values)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Cerca de 2,2% do MAPE implica que o modelo é cerca de 97,8% preciso na previsão das próximas 15 observações." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/3. Modelos regressivos/Exercicio_ARIMA/.ipynb_checkpoints/Untitled-checkpoint.ipynb b/3. Modelos regressivos/Exercicio_ARIMA/.ipynb_checkpoints/Untitled-checkpoint.ipynb new file mode 100644 index 0000000..2fd6442 --- /dev/null +++ b/3. Modelos regressivos/Exercicio_ARIMA/.ipynb_checkpoints/Untitled-checkpoint.ipynb @@ -0,0 +1,6 @@ +{ + "cells": [], + "metadata": {}, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/3. Modelos regressivos/Exercicio_ARIMA/.ipynb_checkpoints/[Solu\303\247\303\243o] Prevendo Vendas Shampoo-checkpoint.ipynb" "b/3. Modelos regressivos/Exercicio_ARIMA/.ipynb_checkpoints/[Solu\303\247\303\243o] Prevendo Vendas Shampoo-checkpoint.ipynb" new file mode 100644 index 0000000..26e3048 --- /dev/null +++ "b/3. Modelos regressivos/Exercicio_ARIMA/.ipynb_checkpoints/[Solu\303\247\303\243o] Prevendo Vendas Shampoo-checkpoint.ipynb" @@ -0,0 +1,336 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Prevendo vendas de shampoo\n", + "\n", + "\n", + "Agora vamos praticar em python como criar um modelo ARIMA.\n", + "\n", + "Vamos analisar um dataset que contém vendas de shampoo durante um período de 3 anos. As unidades são vendas e ele possui 36 observações." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "#Primeiramente vamos importar as bibliotecas que iremos utilizar\n", + "\n", + "\n", + "import pandas as pd\n", + "import matplotlib as mtpl\n", + "from statsmodels.graphics.tsaplots import plot_acf, plot_pacf\n", + "from statsmodels.tsa.arima_model import ARIMA\n", + "\n", + "from sklearn.metrics import mean_squared_error" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Month\n", + "1901-01-01 266.0\n", + "1901-02-01 145.9\n", + "1901-03-01 183.1\n", + "1901-04-01 119.3\n", + "1901-05-01 180.3\n", + "Name: Sales, dtype: float64\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#função para tratar campo data\n", + "def parser(x):\n", + " return pd.datetime.strptime('190'+x, '%Y-%m')\n", + "\n", + "#Agora vamos importar nosso arquivo \n", + "series = pd.read_csv('shampoo-sales.csv', header=0, parse_dates=[0], index_col=0, squeeze=True, date_parser=parser)\n", + "print(series.head())\n", + "series.plot()\n", + "mtpl.pyplot.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Podemos ver que o conjunto de dados de vendas de shampoo tem uma tendência clara.\n", + "\n", + "Isso sugere que a série temporal não é estacionária e exigirá diferenciação para torná-la estacionária, pelo menos na ordem de 1.\n", + "\n", + "Vamos também dar uma olhada rápida em um gráfico de autocorrelação da série temporal. Isso pode ser feito usando o Pandas. O exemplo abaixo plota a autocorrelação para um grande número de lags na série temporal." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "pd.plotting.autocorrelation_plot(series)\n", + "mtpl.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Executando o exemplo, podemos ver que há uma correlação positiva com os primeiros 10 a 12 lags que talvez seja significativa apenas para os 5 primeiros.\n", + "\n", + "Um bom ponto de partida para o parâmetro AR do modelo pode ser 5\n", + "\n", + "\n", + "# ARIMA com Python\n", + "\n", + "A biblioteca statsmodels fornece a capacidade de ajustar um modelo ARIMA.\n", + "\n", + "Um modelo ARIMA pode ser criado usando a biblioteca statsmodels da seguinte maneira:\n", + "\n", + "Defina o modelo chamando ARIMA () e passando os parâmetros p, d e q.\n", + "O modelo é preparado nos dados de treinamento chamando a função fit ().\n", + "As previsões podem ser feitas chamando a função predict () e especificando o índice da hora ou horas a serem previstas.\n", + "Vamos começar com algo simples. Ajustaremos um modelo ARIMA a todo o conjunto de dados de vendas de shampoo e revisaremos os erros residuais.\n", + "\n", + "Primeiro, ajustamos um modelo ARIMA (5,1,0). Isso define o valor do atraso como 5 para regressão automática, usa uma ordem de diferença de 1 para tornar a série temporal estacionária e usa um modelo de média móvel de 0.\n", + "\n", + "Ao ajustar o modelo, são fornecidas muitas informações de depuração sobre o ajuste do modelo de regressão linear. Podemos desativar isso definindo o argumento disp como 0" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " ARIMA Model Results \n", + "==============================================================================\n", + "Dep. Variable: D.Sales No. Observations: 35\n", + "Model: ARIMA(5, 1, 0) Log Likelihood -196.170\n", + "Method: css-mle S.D. of innovations 64.241\n", + "Date: Sat, 26 Oct 2019 AIC 406.340\n", + "Time: 10:34:41 BIC 417.227\n", + "Sample: 02-01-1901 HQIC 410.098\n", + " - 12-01-1903 \n", + "=================================================================================\n", + " coef std err z P>|z| [0.025 0.975]\n", + "---------------------------------------------------------------------------------\n", + "const 12.0649 3.652 3.304 0.003 4.908 19.222\n", + "ar.L1.D.Sales -1.1082 0.183 -6.063 0.000 -1.466 -0.750\n", + "ar.L2.D.Sales -0.6203 0.282 -2.203 0.036 -1.172 -0.068\n", + "ar.L3.D.Sales -0.3606 0.295 -1.222 0.231 -0.939 0.218\n", + "ar.L4.D.Sales -0.1252 0.280 -0.447 0.658 -0.674 0.424\n", + "ar.L5.D.Sales 0.1289 0.191 0.673 0.506 -0.246 0.504\n", + " Roots \n", + "=============================================================================\n", + " Real Imaginary Modulus Frequency\n", + "-----------------------------------------------------------------------------\n", + "AR.1 -1.0617 -0.5064j 1.1763 -0.4292\n", + "AR.2 -1.0617 +0.5064j 1.1763 0.4292\n", + "AR.3 0.0816 -1.3804j 1.3828 -0.2406\n", + "AR.4 0.0816 +1.3804j 1.3828 0.2406\n", + "AR.5 2.9315 -0.0000j 2.9315 -0.0000\n", + "-----------------------------------------------------------------------------\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/talitabarcelos/anaconda3/lib/python3.7/site-packages/statsmodels/tsa/base/tsa_model.py:171: ValueWarning: No frequency information was provided, so inferred frequency MS will be used.\n", + " # Now, if no frequency information is available from the index\n", + "/Users/talitabarcelos/anaconda3/lib/python3.7/site-packages/statsmodels/tsa/base/tsa_model.py:171: ValueWarning: No frequency information was provided, so inferred frequency MS will be used.\n", + " # Now, if no frequency information is available from the index\n" + ] + } + ], + "source": [ + "# fit modelo\n", + "model = ARIMA(series, order=(5,1,0))\n", + "model_fit = model.fit(disp=0)\n", + "print(model_fit.summary())\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A execução do exemplo imprime um resumo do modelo de ajuste. Isso resume os valores do coeficiente usados, bem como a habilidade do ajuste nas observações na amostra.\n", + "\n", + "Primeiro, obtemos um gráfico de linha dos erros residuais, sugerindo que ainda pode haver algumas informações de tendência não capturadas pelo modelo.\n", + "\n", + "Em seguida, obtemos um gráfico de densidade dos valores de erro residual, sugerindo que os erros são gaussianos, mas podem não estar centrados no zero.\n", + "\n", + "A distribuição dos erros residuais é exibida. Os resultados mostram que, de fato, existe um viés na predição (média não zerada no residual)\n", + "\n", + "Observe que, embora acima tenhamos usado todo o conjunto de dados para análise de séries temporais, o ideal seria realizar essa análise apenas no conjunto de dados de treinamento ao desenvolver um modelo preditivo.\n", + "\n", + "A seguir, veremos como podemos usar o modelo ARIMA para fazer previsões.\n", + "\n", + "# Modelo ARIMA de previsão contínua\n", + "\n", + "O modelo ARIMA pode ser usado para prever futuro\n", + "\n", + "Podemos usar a função predict () no objeto ARIMAResults para fazer previsões. Ele aceita o índice das etapas de tempo para fazer previsões como argumentos. Esses índices são relativos ao início do conjunto de dados de treinamento usado para fazer previsões.\n", + "\n", + "Se usamos 100 observações no conjunto de dados de treinamento para ajustar-se ao modelo, o índice da próxima etapa para fazer uma previsão será especificado para a função de previsão como start = 101, end = 101. Isso retornaria uma matriz com um elemento contendo a previsão.\n", + "\n", + "Também preferimos que os valores previstos estejam na escala original, caso realizemos alguma diferença (d> 0 ao configurar o modelo). Isso pode ser especificado configurando o argumento de tipo com o valor 'levels': typ = 'levels'.\n", + "\n", + "Como alternativa, podemos evitar todas essas especificações usando a função forecast (), que executa uma previsão em uma etapa usando o modelo.\n", + "\n", + "Podemos dividir o conjunto de dados de treinamento em conjuntos de treinamento e teste, usar o conjunto de treinamento para ajustar-se ao modelo e gerar uma previsão para cada elemento no conjunto de teste.\n", + "\n", + "É necessária uma previsão contínua, dada a dependência das observações em etapas anteriores para diferenciar e o modelo de AR. Uma maneira grosseira de executar essa previsão contínua é recriar o modelo ARIMA após cada nova observação ser recebida.\n", + "\n", + "Nós mantemos o controle manual de todas as observações em uma lista chamada histórico que é semeada com os dados de treinamento e à qual novas observações são anexadas a cada iteração.\n", + "\n", + "Juntando tudo isso, abaixo está um exemplo de uma previsão contínua com o modelo ARIMA em Python." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "predicted=349.117636, expected=342.300000\n", + "predicted=306.513010, expected=339.700000\n", + "predicted=387.376466, expected=440.400000\n", + "predicted=348.154255, expected=315.900000\n", + "predicted=386.308811, expected=439.300000\n", + "predicted=356.082028, expected=401.300000\n", + "predicted=446.379518, expected=437.400000\n", + "predicted=394.737242, expected=575.500000\n", + "predicted=434.915541, expected=407.600000\n", + "predicted=507.923456, expected=682.000000\n", + "predicted=435.482818, expected=475.300000\n", + "predicted=652.743768, expected=581.300000\n", + "predicted=546.343465, expected=646.900000\n", + "Test MSE: 6958.327\n" + ] + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "X = series.values\n", + "size = int(len(X) * 0.66)\n", + "train, test = X[0:size], X[size:len(X)]\n", + "history = [x for x in train]\n", + "predictions = list()\n", + "for t in range(len(test)):\n", + "\tmodel = ARIMA(history, order=(5,1,0))\n", + "\tmodel_fit = model.fit(disp=0)\n", + "\toutput = model_fit.forecast()\n", + "\tyhat = output[0]\n", + "\tpredictions.append(yhat)\n", + "\tobs = test[t]\n", + "\thistory.append(obs)\n", + "\tprint('predicted=%f, expected=%f' % (yhat, obs))\n", + "error = mean_squared_error(test, predictions)\n", + "print('Test MSE: %.3f' % error)\n", + "# plot\n", + "mtpl.pyplot.plot(test)\n", + "mtpl.pyplot.plot(predictions, color='red')\n", + "mtpl.pyplot.show()\n", + "\n", + "\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A execução do exemplo imprime a previsão e o valor esperado a cada iteração.\n", + "\n", + "Também podemos calcular uma pontuação média de erro quadrático final (MSE) para as previsões, fornecendo um ponto de comparação para outras configurações do ARIMA.\n", + "\n", + "É criado um gráfico de linhas mostrando os valores esperados (azul) em comparação com as previsões de previsão sem interrupção (vermelho). Podemos ver que os valores mostram alguma tendência e estão na escala correta.\n", + "\n", + "Neste exercicio,aprendemos como desenvolver um modelo ARIMA para previsão de séries temporais no Python.\n", + "\n", + "Você aprendeu especificamente:\n", + "\n", + "Sobre o modelo ARIMA, como ele pode ser configurado e suposições feitas pelo modelo.\n", + "Como executar uma análise rápida de séries temporais usando o modelo ARIMA.\n", + "Como usar um modelo ARIMA para prever previsões fora da amostra." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/3. Modelos regressivos/Exercicio_ARIMA/Prevendo Vendas Shampoo.ipynb b/3. Modelos regressivos/Exercicio_ARIMA/Prevendo Vendas Shampoo.ipynb new file mode 100644 index 0000000..e796b9b --- /dev/null +++ b/3. Modelos regressivos/Exercicio_ARIMA/Prevendo Vendas Shampoo.ipynb @@ -0,0 +1,274 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Prevendo vendas de shampoo\n", + "\n", + "\n", + "Agora vamos praticar em python como criar um modelo ARIMA.\n", + "\n", + "Vamos analisar um dataset que contém vendas de shampoo durante um período de 3 anos. As unidades são vendas e ele possui 36 observações.\n", + "\n", + "Para concluir esse exercicio siga os passos abaixo:\n", + "\n", + "1. Importe as bibliotecas que irá usar\n", + "2. Importe o dataser shampoo-sales.csv\n", + "3. Gere o gráfico de autocorrelaçã0\n", + "4. Dê o fit no modelo\n", + "5. Faça previsão usando o modelo" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "#Primeiramente vamos importar as bibliotecas que iremos utilizar\n", + "\n", + "\n", + "import pandas as pd\n", + "import matplotlib as mtpl\n", + "from statsmodels.graphics.tsaplots import plot_acf, plot_pacf\n", + "from statsmodels.tsa.arima_model import ARIMA\n", + "\n", + "from sklearn.metrics import mean_squared_error\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Month\n", + "1901-01-01 266.0\n", + "1901-02-01 145.9\n", + "1901-03-01 183.1\n", + "1901-04-01 119.3\n", + "1901-05-01 180.3\n", + "Name: Sales, dtype: float64\n" + ] + }, + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#função para tratar campo data\n", + "def parser(x):\n", + " return pd.datetime.strptime('190'+x, '%Y-%m')\n", + "\n", + "#Importe o arquivo e insira na variável serie\n", + "series = \n", + "print(series.head())\n", + "series.plot()\n", + "mtpl.pyplot.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#plote o gráfico de autocorrelação\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/talitabarcelos/anaconda3/lib/python3.7/site-packages/statsmodels/tsa/base/tsa_model.py:171: ValueWarning: No frequency information was provided, so inferred frequency MS will be used.\n", + " % freq, ValueWarning)\n", + "/Users/talitabarcelos/anaconda3/lib/python3.7/site-packages/statsmodels/tsa/base/tsa_model.py:191: FutureWarning: Creating a DatetimeIndex by passing range endpoints is deprecated. Use `pandas.date_range` instead.\n", + " start=index[0], end=index[-1], freq=freq)\n", + "/Users/talitabarcelos/anaconda3/lib/python3.7/site-packages/statsmodels/tsa/base/tsa_model.py:171: ValueWarning: No frequency information was provided, so inferred frequency MS will be used.\n", + " % freq, ValueWarning)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " ARIMA Model Results \n", + "==============================================================================\n", + "Dep. Variable: D.Sales No. Observations: 35\n", + "Model: ARIMA(5, 1, 0) Log Likelihood -196.170\n", + "Method: css-mle S.D. of innovations 64.241\n", + "Date: Thu, 24 Oct 2019 AIC 406.340\n", + "Time: 23:51:56 BIC 417.227\n", + "Sample: 02-01-1901 HQIC 410.098\n", + " - 12-01-1903 \n", + "=================================================================================\n", + " coef std err z P>|z| [0.025 0.975]\n", + "---------------------------------------------------------------------------------\n", + "const 12.0649 3.652 3.304 0.003 4.908 19.222\n", + "ar.L1.D.Sales -1.1082 0.183 -6.063 0.000 -1.466 -0.750\n", + "ar.L2.D.Sales -0.6203 0.282 -2.203 0.036 -1.172 -0.068\n", + "ar.L3.D.Sales -0.3606 0.295 -1.222 0.231 -0.939 0.218\n", + "ar.L4.D.Sales -0.1252 0.280 -0.447 0.658 -0.674 0.424\n", + "ar.L5.D.Sales 0.1289 0.191 0.673 0.506 -0.246 0.504\n", + " Roots \n", + "=============================================================================\n", + " Real Imaginary Modulus Frequency\n", + "-----------------------------------------------------------------------------\n", + "AR.1 -1.0617 -0.5064j 1.1763 -0.4292\n", + "AR.2 -1.0617 +0.5064j 1.1763 0.4292\n", + "AR.3 0.0816 -1.3804j 1.3828 -0.2406\n", + "AR.4 0.0816 +1.3804j 1.3828 0.2406\n", + "AR.5 2.9315 -0.0000j 2.9315 -0.0000\n", + "-----------------------------------------------------------------------------\n" + ] + }, + { + "data": { + "image/png": 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qISVhGb1EZUKIdH8q9ggYhWzOEQDcjrpWkBOJO/KIyWSkmQTxqsfk5UTxjfVkCGQxWZHELpBWFyuqGiqsKpbpabWBCJjVOGHsCcYQTaSK/t1kw4agwfFHEmhJGwKXw4xmqwkzq1xCWgsUGkiTjcthQSyRQjiufdJRDXKi+MaRDgDrD9laRomYTKaz2YrlIj9TNJGENxRXZAjMRgO6nTbVpZ7FkNvEcGiIUUQyJbAWTcBpk0JDUgmpgz2CGmHOFwZR8YeUO91motoJ47GlNTitJgy02dFqN9eFRyDnMdR4BIU8r5W04EyJIQDScwk0Thavq9E5NMQoYC3dXqLFvi5WGmQtQc0w5w2js9kKi6nw29SdbjxX7YTxpaUgRjqbQETobrHWiSGQBHtNRUo9AamENJZIIVCgqk6pqlhmhw5agmJtSXKhuyEgogkiepGIThHR8fSxNiL6MRG9nP7frfc6mK3I7SVkjwCQKoemPKGqx5sZKUeg5M1cK20mLi2tYVdnMwDJi6mHqqHFQASdRUpHZZSIypSKyWTkkZVavt/mfRFYTNIwHaVUyiN4jRDiOiHE/vTnnwLwUyHEbgA/TX/OVBjZELRktS8YbHcgmkipGsLB6MOcAjEZsB4aqqa6OBhNYN4Xwa4uyRB0OW2ZipxaZtEfRbdC4VVGVFbIEBQYWp+L3lYbYokUVjQM6816w9jRaiuqY8imWqGhuwA8kP74AQBvrdI6Ghq582jLJo8AYC1BtVkvASzuEbgyHUir5xGML0sVQyMdTQCA7hYrFgPRmh+hKfUZUvbQ7nBKv+dCjefkZnvtzcp243qUkM77Ior+brKphCEQAH5ERCeI6HD6WLcQYh4A0v93bX4RER0mouNEdHxpaakCy2w85FkE2TmCAS4hrQm8oTgi8ZSi0JAr4xFUzxDIFUOyR9DdYkMiJeCpAX1DPiRVcfH2EjJy3H+pQB+lpbUIXA4zrCajomvqYghUqoqByhiCm4QQ1wO4HcA9RHSrkhcJIe4TQuwXQuzv7OzUd4U6E0uk8L4vH8XPzy1WeykbkD2C7BxBv1v6w5xa4RLSajKrovLDbDTAaTNVNVl8aSkIAwE726WNhLzLruWEsS8cRyyRUiQmA6RcjNFABT0Cpapimb6MIdDm95RIpnDZX4MegRBiLv3/IoBvAzgAYIGIdgBA+v/aekJqzMRKEE9dXMYf/+vzNdMcDMidI7CZjehusXJoqMqorfyQRGXV9QgG2hyZnbD8cK3luQRqxGSA1Om1vclSNFlcaNLZZlwOM+xmo2YewWIgipRQVzEE6GwIiKiJiJzyxwBeD+A0gEcBvD992vsBfFfPdVQbOX66vBbDX33/pSqvZh3ZI2i2bSydG2QtQdVRKwpyO6rbivrS4nrFELCufahlj0CNmEym2BD7pTV1HgERYYeGWgK5LUmthYa6ATxFRM8DeBbAD4QQTwD4PIDXEdHLAF6X/nzbMpE2BL97407823Mz+MX52nCA/OE4HBYjzMaNfwYD3I666sx5w6pKAF0OS9WSxamUwPhyMJMoBtbj6bVcQiqvTWmyGAA6nPkNgRBCCg0p9DBkpBJSbQzmbJEZ1/nQ1RAIIcaEENem/10phPhc+viKEOK1Qojd6f89eq6j2kyshOB2mPFnb3oFruhqxp99+7Si2ad6E4gkNuQHZAbcDlz2RxBNVLdlQSMzm24aprQEsK2peqGhWW8Y0UQqkygGkDFitTygRvYI1PTt72y25g0NrUWlTqZqDUFvq12z0NB8CapigJXFFWFiOYihjiZYTUb893dcgzlfGH/3xLlqLwv+SHxDfkBmsM0BIYBZ7jlUNdS2EZaG01QnNJSpGMoKDQFSLX0tawkW/RE4bSbYLcoqfACphHR5LZZTAKZWTCbT67JjKRDVZOM17ys82jQfbAgqwMRKEMPtktt8w043PvDqIXzjyCSOTVTXEcrnEQy2cwlptZnzhlV1j3Q7LFiLJhBLpHRcVW7GltIags6mDce1UBcvBaL4xEMnFc0BUIuSyWSb6Wy2IpZMwR/e6tGvt5dQd015977gK/9nLDbaNB9sCHQmHEti3hfBzvb1N8knXz+KPpcd/+XfXkCkih0j/ZH4Bg2BzLqojD2CapBIprDgj6BPhXsvq4urUZV2aWkNrXbzlnyGFv2Gnrm0jEefn8NXnxov6zq5UDKZbDOZNhM5DJNaVbGMXEI6q0F4aN6nXkMAsCHQnUmPtFsa6nBkjjVZTfibt1+NsaUg/vfPXq7W0tIewVZD0OWUGp1xwrg6LKRLAIuNqMxGbjxXjcohqcdQ05Z8RneLDctrUSSSpXsp8pCkB49OaT5CdUFFewmZjub8/YbkUlm1hmCHhqKyOW9ElScpw4ZAZ+SKoeGOjW7zLbs78c4b+vGlX47h9KyvGkuDPxzf0F5CxmAgDLjtPKmsSpTSPbKajefGloIY2ZQfACQtQUqgrD46U54QzEaCLxzHt45Pl7PMDWQqfEr0CHKFqpbWojAZCK4cXnYhdqQniZVrCCJxebQpewQ1x/iy9DAd2mQIAODP37QPbU0W/Mm/voB4GbumUhBC5PUIgHQJKYvKqsL6QBrlb2hXlUJDgUgci4HolkQxAHQ7y1cXT3lCuG7AhesHXfjq0xNIatS7yBuKI5ZMlewR5DQEgSg6mq0wGJQ3ewMkEWdHs6VsLYGsPWGPoAaZWA6ivcmSszqn1WHGX911Fc7O+3H/r8Yquq5oIoVYMpWZV7wZFpVVD6UjKrNZ9wgqGxqSE8W7OrdudNZFZaUnQac9IQy0OfCRW0Yw5QnhR2cul3ytbOSyVrXJYpfdDJOBcoaG1KqKs+nVQEsgbyA4R1CDjK8Ec3oDMm+8qgd3XN2D//mTlzNleJVgfRZBbo9gsM2BQCQBX5WHnTQic94wWu1mRcNSZGRDUOkpZfLfbK7QULnq4mgiiXl/BANuB15/ZQ8G2xy4T6MNUyliMiDdZqLZktcjUKMqzkYLLYHS0aa5YEOgMxPLQQy15zcEAPDZO6+E3WzEp/7thYq17ZXL33LlCACg380lpNVi3qe+BNBuMcJmNlQ8NHRpaQ0mA2WazWXT0WwBEUrWEsyuhiGEtCkxGggfvnkYJ6e8ODFZftl1Ke0lZDqduUVlSofW56LXZcd8mQNq5NBQTyt7BDVFKJbAYiCK4Y6tb5Jsupw2/MWb9+HYxCoePDpZkbUFcjScy2aQ21FXjVlvBL0lvJmlxnOVDw0Ntju2tCkBAJPRgI5ma8mhIflvT9a1vHN/P1rtZtz/ZPmlpLJxKuXBLfUb2mhwkymBlbIMgQ3BWDKnPkEpc94wOpqtiltgZ8OGQEcmCiSKN/OO6/twy+4OfP7xc7js01+N6c/MK87tEQy0STtSThhXnrkSRUEuh6UqHsFIx9awkEx3i7XkNhNy+bK8KXFYTHjfoUH88OzlTDVeqSwGomi1m2Ezq39o5mo85wnGkBKlGRZgvUKsHC3BnC+iurWEDBsCHZlYSWsIioSGAKkL4WfeciWCsSR+dFabhFghAkVyBE6bGW6HmT2CChOMJuALx0syBG6HuaI5gmRKYGI5hF1d+f++u52lq4unPCFYTYYNcff33zgEs8GArz5dnldQiphMpjPdeC47jKN2aP1mtBhQM5ceUVkKbAh0RG4/rcQjAKTKi95WG46O6d96Yj1HkL/meZC7kFYcuY1wKTs7d5Olov2GZlZDiCVTOUtHZbpaSp9dPJWuGMoux+xqseHO63rxreMzZXVbVTOZbDMdzVbEkwK+8PrvejFQeqgJWL/fpZaQCiEwX6InCbAh0JWJ5SA6mq1oVlj9QUQ4ONKOo+MrZSWNlLDuEeRfWz8bgoqTaSNcokdQSUHZerO5Ah5BixUrwVhJPZCmPOFMWCibj9wygnA8WVY+bdEfKfmhnWkzkZUwLrXhnExHkxUWo6Hk0JA/kkAwllTdflqGDYGOTKwEiyaKN3NwuA3LazHdS0n9kTiMBoKjQOfFwTYHZlbDmol49GTaE8L9T45pVnX105cW8JOzC5pcSw3zJaiKZdwOC3zheMUqzy4tygPrC+UIpJ1urt48hRBCYNoTymkIRnucuHVPJx749WRJHTtTKYGltXI8AqlUN/tnkj/uKDE0ZDBIA2rmS9QSlKMhANgQ6Mr4ckhRfiCbQyPtAIAjOoeH5M6jhfrdD7Y5kEiJTLiilvnm0Ul87rGX8MsLS2Vfay2awH/6l1P4T4+cqvjciDlvGAZaV+WqweWwICXWNSJ6M7a8hrYmS6bPUS5KnV28GopjLZrAQA5DAAAfuWUYS4EovntqTtV1pWvHEE+Kkn7HQPYQ+40eQZPFqEr7sZlytATrIUX2CGqKQCSO5bWo4vyAzM52B7pbrDg6rq8hkPoMFe6JkulC6ql9Q3ByygsAuO/J8gVHjxybhj+SQCCSwMPPTpV9PTXM+SLobrHBlKMcsxhtTdL9rFTC+NJisGBYCFgf+qI2TzC1qWJoMzdf0YG9PU58+VdjqsOo62Ky0nbP6/2G1n/Pkqq4tOvJ7HDZSjYEcyVOJpNhQ6ATk+mGbZubzRWDiHBwuB1HxvTNE+SbRZCN/Cas9TxBIpnCizM+tNrN+PXYCl6cKb2JXyKZwleeGserhtw4NNKGrzw1XtE+UOVUfrgq3GZC6jqaPywElN5mopghICJ85JYRXFhYU+0FyuWspT64W+1mmI20oYS0HFWxTJ/Ljsv+SEndWue8YZgMVHKOgg2BTmQqhlSGhgApPLQUiGauoQf5ppNls8Nlg9FANV9CemFhDeF4Ep98wyicVlNZbQgeO30Zs94wDt+6Cx+9dRfmfRF873n14YdSKVVDAKy3maiElsAbimElGNsyjGYz7U0WGA2kOjQkbz5kPUsu3nJtL7pbrPjyr9SVki5mRlSW9tAkInRsGllZjqpYptdlR0pIbcjVMp/2JI0qG97JsCHQicmVrXMIlHJwpA0AdA0PKfEIzEYDdrTaal5UdmpaCgvdckUH3nNwEI+9OF+SFyOEwH1PXsJIZxNeu7cLt412YrTbifueVB9+KAUhBOZ8kZJ6xQDrw2kq4RFcyjSbK+wRGAyELqd6dfG0J4SOZisclvx/oxaTAR949TCeuriMM3PKvUB5bkCpDeKAraKyUobWb6YcLYG0gSg9NMWGQCfGl0Pobin8h5yPkY4mdDRbcWRsRYeVSfjDuaeTbaYeupCeml6F22HGznYHPnDTEAjAV0qYaPXrSys4PevHR24ZgcFAUvjh1hGcuxzQJAldDLnMsuzQUAVyBPnmFOeiq8WWqbNXypQnhMEC3oDMew4MwmEx4isqvIKFQARuh7mkVgwyHc2WjEcQiScRiCTKNgQj6TDyuXm/6tfOldCfKhs2BDoxsVK82Vw+iAiHRtpwdMyj205UiUcA1Ieo7OSUF9cOuEBE2NFqx53X9eKR49OqQyT3/WoMHc0WvO2VfZljd17bi54WmyZJ6EIkUwL/9ItLALBhrKkaWmwmGA1UES3B2FIQZiOh31384dPtVD+ycipP6ehmWh1mvGv/AB59fk5xdVs5YjIZWV0MlK8qlul327Gj1YYjKiMBqZTAZV9pk8lk2BDoxMRyUHWiOJuDI+247I/oshtPpgQC0fxDabIZaHNgeS2GUKyyZZRKCUTiuLi0husGXJljH7llBKFYEg8eVV7xc/5yAL84v4T33zi0of+MxWTAh24ewjOXVvDCjFfTtct4QzF84GvP4itPjeN9hwZx657Okq5DRGlRWSVCQ2sYam9SVN2kdoh9PJnCnDe3mCwXH755GCkh8PVnJhSdX46YTKaj2YqVtRhSKYHFMsVkMtIGsB1HVRaKLK9FEU8KDg3VGv5IHCvBmOrS0WwODUt5Aj3CQ3JtfL4W1NkMtNV2CekLMz4IAbxy0J059oodLbh1Tye+9vSEYsHR/b8ag91sxPsO7dzytXcfGITTasL/0cErOHfZjzu/+DSOjnnw+bdfjf/21qtLTvgBlWs8N6agYkimu8UKXziOSFzZvZjzhpESyKsh2MxAmwO3X7UD//fIFJ56ebno+YsBbTyCRErAG46XrSrO5tCIekHpnK+80lGADYEuTGQqhtQnimWu6GpGe5NFl75D/nDHf4/RAAAgAElEQVThFtTZ1HoJqZwovq7fteH44VtGsLwWxXdOzha9xmVfBN89NYt37e/PKY5y2sx4z6FBPP7ivKZznB97cR5v/8dnEIkn8fBHD+HuA4NlX7MSbSbiyRQmV0JFK4Zk5DLNXD38c1GsdDQXf/yGUXS2WPG+rxzFn337xbxCQHkHX2rDOZnskZWyqlgbQyAJSn+t4n0/X6aqGGBDoAtqm83lQuo71KaLniBQpAV1NgPpGHCtJoxPTnkx0tGEVsdGo3bTFe3Yt6MF9/9qvGjLha8/I83C/fDNI3nP+dBNwzAaCF9+qnyvIJkS+NsnzuH3HnwOe3uc+P7Hb8b1WR5NObgdFqwG9Q0NTXlCSKSECo9A3aSyzXMIlDDU0YTHPnELPnLLMP7vs1N44/98Es9c2uodrARjSKaEJh4BIBm3pUAURFKpbLkMtjmkPIGKSIDcn4g9ghpDnkOws610QwAAB4fbMeeLYGZV27BMsTGV2bQ1WdBkMdakIRBC4NS0d0N+QIaIcPjWEVxcXMPPzy/mvcZaNIEHj07i9qt2FHzwdLfY8Nbr+vDI8emylLu+UBwffuAY/vEXl/DuAwN46PChshWp2UjDafT1CDJziruUh4YA5aKyKU8IFqNB9WB5m9mIP3vTPnzrozfCbDTgPfcfxV985zSCWd7BQkZDUN7vfINHEIiivclSkhp8M5KgtE1VnmDeF4HdbITLUfz9nA82BDowsRLEjlYb7AUauilhve+QtnmCjEegwBAQEQbaHJipQS3BzGoYy2tRXDe41RAAwJuu2YHe1sIVPw8/O4VAJIHDt+b3BmQO3zqCSDyFb/x6oqT1XlgI4K57n8LTF5fxubddhb95+zVllTDmwtVkhjcU11X3sD6nWNlGR36gK/UIpj0h9LfZN7SfVsP+oTY89olb8OGbh/HNo5N44xeezLyHFjOq4vLCONn9hpYC0ZKbzeXi0Ei7qjzBvC+MHS5bwb5hxaiaISCiNxLReSK6SESfqtY69GBcwZxiJezuaobbYda8AZ2cI1BSPgpIybha9Ajk/MArB3KHVcxGAz508zCOjnvw/PTWip94MoWvPjWOA8NtuDaHV7GZ3d1OvHZvFx54ZgLhmLqul0+cnsfb7n0aa9EkHvrIIbz34NaktBa4HRbEkimEVK5PDZcW19DptCraSACAy2GGxWhQPKlMaeloIewWI/7izfvwL4dvhIEId993BJ999EzGWy83NNRiN8FiNGApnSPQIj8go7bx5Ky3dBGiTFUMAREZAdwL4HYA+wC8m4j2VWMtejC5EiwrPyBjMBAODLfh6LjWHkE6WaxAUAbIWoLyBmvrwalpL6wmA/bucOY95+4Dg3DacredeOzFecz5IvioAm9A5qO/sQuroTj+9cS0ovMj8SQ+++gZfOybz+GKbikfsH+oTfH3U0tbWlSmZ+O5seXizeayISJ0tVgzit5iTK2UbwhkDgy34fE/uAUfePUQvv7MBP7bD84CKL/mX2ozYcFyIIZlDVTF2exsd6CnRXmeYL6M/lQy1fIIDgC4KIQYE0LEADwM4K4qrUVTfKE4VkNx1XMI8nFopB0zq2FNQzPyvGLFHoHbjnA8uWVgd7U5Ne3FVX2tOQenyzRbTXjPwa0VP0II/J9fjmFXZxNeM9ql+Hu+asiN6wZcuP9X40XnNLy8EMBb730aX39mAh+8aQj/cvgQesp8wxZDjhPrNalMCIGLi2sYUZgolpG0BMU9Al8oDn8koZkhAKRZx5+980o8fPgQ+t0ODHc0wWIq/9HX6bRiMRDRpL1ENrKg9IgCQWkskcLSWrQsMRlQPUPQByB7SzWTPpaBiA4T0XEiOr60pL+8XyvGVcwpVsLBYclN1LKMNBCJw242FnyAZiMnUWspPBRLpHB61pczUbyZD75aqvj5SlbFz9MXV3B23o/Dt46oikUTET72GyOY8oTwxOncs6WFEPjmkUm8+X8/haVAFF/7wKvwmbdcWdKgdLXI5a96JYw9wRh84bjiiiGZ7hZl6uKpTLM57QyBzKGRdvz4j27Fd+65SZPrdTRbMbYURCyZKtvD2IyUJ4hmejrlY8EfgRCoz9AQgFzvvA2mTwhxnxBivxBif2dnaUrLaiBrCMpRFWezt8eJVrtZ0/CQP6ysvYRMLWoJzl32I5pIKTIEPa023HltHx7JmnMrtZOw4q7r+oq8eiuv29eDoXYHvvTLS1t2bKvBGD76zyfw5985LYUl/vAWvGavco+jXNYbz+ljCMaW5WZz6v6+u5w2RaGhUjQEarCajGhVGBItRkezNVO6qaVHACgvFCl3MplMtQzBDICBrM/7AVSu16+OjC8HQaTdjmY9T6ChRxBV1nBOpt9de4YgkyjOUzG0mcO3SnNuv3lkEi/N+/HkhSV88KahknbpRoPUjO7FWR9+nfVGfebSMm7/wq/w8/OL+PM3vQIPfPBA2WWKanFlWlHrExq6tKi82Vw23S02BKKJDaWcudDTI9Ca7Ie/1oZAaZ5AHnZfr6GhYwB2E9EwEVkA3A3g0SqtRVMmVoLobbVrGgY4ONyGyZWQZiMj1XoENrMRXU5rTYWGTk150dFsVewSj/Y4cdtoJx749QS++POLcFiMeO/B0pW877i+Hx3NFtz35BjiyRT+7ofn8N4vH4XDYsS3f+8m/Idb1IWctMJl13dK2aWlNVhNBtWdLmUtwWIRdfGUJ4T2Jguayxj5WCnk2cVA6bMN8qE0T5CZTFaPHoEQIgHg9wH8EMBLAB4RQpypxlq0ZmI5WNIMgkLIbqJWeYKAgqE0m6m1dtSykExN7bTUdiKGH7wwj3ftH8jsnkvBZjbi/TcO4Rfnl3DnF5/GvT+/hHfdMIDvffxmXNXXWvJ1y8VkNKDFZtKt39DYktRMUW0/JKXq4mlPqC68AQDozPL2OnXw/A6m8wRjBQZUzfvCcDnMJbW7z6ZqOgIhxGNCiD1CiF1CiM9Vax1aIoTQTEOQzSt2tMBpM2mWJ/ArbEGdjSQqq43Gc75QHGPLQcVhIZkbd7Xjqr4WGEjqWFkuv3PjTjgsRsyshvDF97wS//23rylreLlWuJssunUgVTKeMhdKh9hP1ZEhkD0Ci8mgqIGjWpTkCea8kbJaS8hU/692G7GaLn3TKlEsYzQQDgy1aSYsC0TU5QgAyRB859QsYomUJqV35XBqRhaSqTMERIS/fce1GF8OavKwcTks+O49N6HVbta0TUS5uHRqMxFNJDHlCeHOa3tVv1b+/RRKGCeSKcx6w3jLtTtKXmMl6UiHgzqbrWWpevMx1O5Ad4sVR8Y8eQWIc96wopkQxeAWExpSzpziYhwcacP4cjAzb7Uc1OYIACk0JMR6g6tqcnJqFUTA1f3qQzD7elvwpmu0e9Ds7nbWlBEAgDadOpBOrYSQElCtIQAAp9UEu9lY0COY90WQTAndKoa0Rk4Qa50olpHnExRqPDlf5kAaGTYEGrI+p1h7Q5BxE8usHorEk4glU6pzBHIX0lqoHDo17cXurmZFTfMaEb06kKoZT7kZIpK0BAWSxfVUMQRIxs1iMuhmCADpfb8UyJ0nCEYT8IXjZY2olGFDoCETy0EYSJ8a6H07WtBsNZXdgE7uPKo2plkrojIhBJ7P03GUkdBrOI0sblLabG4zXUXUxXprCLRG7hSqVQvxXBTKE8hVhOVWDAFsCDRlfCWEPrddlxi6yWjA/iE3jpZpCNZnEajbTXc7bbAYDZiuchfSyZUQVkNxXJen0RwjicqCsaTi6WxKubS0hp4WW8kJ8e4WW8HQ5pQnBJOBNAl1VIp//vBB/Mfbdul2/ew8wWZm06WjHBqqMSZ0qBjK5tBIOy4tBRVPesqF2s6jMgYDob/Njsnl6hoCtUKyRkRuM6GlqEwIgTOz/pK9AUAeYh/NG++e8oTQ77aXNapzu1EoTyBPJmOPoIYQQpQ9sL4YB9NzjMspI1Uzi2Azu7uacWExUPL31oKTU6twWIzY052/42ij43Zo32/oh2cu4/xCAG++Rn3FkEx3iw3heBKBPOrietIQVBI5TzC+KU8w54uAqPyW2gAbAs1YCcYQiCZ09Qiu6muFw2IsS1imZjrZZka7nZhYDioeQq4Hp6a9uLqvlXeNBcj0G9IoYRxLpPD5x89hd1cz3rW/v+TryMNg8oWHtJhDsB2RN4Cbw0Nz3jC6nFbFzSMLwYZAI7RuNpcLs9GA/UPlzSdQM694M3t6nEgJ4OKisslJWhOJJ3F23p93Ihkjsd5vSBuP4MGjk5hYCeHTd7yirHGM6+riraFNXzgObyjOhiAHwx1N6HJatySM531hTSqGADYEmiG7bTtVDNwuhYPDbbiwsIaVtdLyBOs5AvUewd4eKRxzYaE64aGz837Ek0K1kKzRcDfJHUjL9wh8oTi+8NOXcdMV7bhttLwuwIXaTEzXWcVQJcmXJ5jXSFUMsCHQjImVIIwG0j3GeWhEchOfLVFPEIgkYCCgqYR5yjvbm2AxGnD+cnUMwakpOVHMFUOF0DJHcO8vLsIXjuPTd7yibPWs3Jgtl0cwXWcagkpzaKQdi1l5AiEEZr1hTRLFABsCzZhYlioetIjXFeLqPhfsZmPJban9kTicNnNJb2qz0YBdXc04XyWP4NS0FztabZokx7YzNrMRdrMxM3uhVKY9IXz96Qm84/p+XNlbfiO9JqsJTqspt0eQLkse1NmjrlfkDaCcJ1gNxRFNpDQrtWVDoBETK/qWjspYTAbcsNNdsrAsEEmUlB+QGe1urppHcHJ6lYVkCnE7zGWHhv72h+dhMAD/+fV7NFqVlDBezDHEfsoTgsthLqmarRHYnCeY07B0FGBDoAmVKB3N5uBwG85dDpSUDPSH43BaS3+zjfa0YN4XgS+sT3fLfKysRTHtCbMhUEi56uKTU6v43vNz+MgtI5oKvKTZxVtDQ1OeMOcHCiDnCY6OS3mCdUPAHkHNsLQWRTCWxFCF3Np9vS0AsKWuWAllewQ9Up+ZSieMZSEZGwJltDVZ4CnREAgh8NePvYSOZis++hvaqmbzDbFnDUFxDo20Y8EfxcRKCPM+7VTFABsCTZhIq231aDaXi750A7hS5gPIOYJSGe2RjFClw0Onpr0wGqikjqONiMthLllZ/MMzl3FsYhV/9Lo9mk8K62qxYnGTujiZEphZZQ1BMdbzBCuY84ZhMRrQ3lT6cKVseB6BBlRCQ5CNPJ6xFEMQiCTKisP2ttrQbDVVxRCMdjvLnsTUKLhLnEmglXgsH91OG2LJFLyheKYVxmV/BPFk/bSfrhbDHU3oTOcJUkIaWK/VOFT2CDRgfCUIk4EUz88tF6fNDJfDjFmv+r4//nBcdZ+hbIgIe7orWzmUSgmcmvKykEwFbocZvnAcyVT+ebe50Eo8lo+MliArYTy1whoCJWTrCea8Yexo1a56jg2BBkwsBzHY5tDljZOPfrddtUeQSgmsxRKqO49uZrSnBRcWAgWHamvJ2PIaAtEE5wdU4G6yQIh1AaESfGFJPHbzFR1li8fysT6ycj1hzGIy5RwaacOCP4oXZ32aJYoBNgSaML4crFh+QKbPpd4QBKIJCKF+FsFmRrub4Q3FsVhGF1Q1nJwqbTRlIyOLytQkjP/x55J47E/v2KvL6EUgt7p4yhOC0UCa7nC3K/J8glgipZmqGGBDUDZCCEyuhHRvLbGZfrcDM6shVbvyQGYoTfkeAVC5hPGpaS+cVlNJk7EaFVe68ZzSEtJpTwhf01A8lg95mtfiJkPQ57JX1KOuV0bSeQJAyhFoBf/my2TBH0U4nqxYolim321HJJ6CR4V61B+WGs6VkyMAgNF0z6FKGoJrB1yaJcYagUybCYUdSGXx2CdfP6rnsmAzG9FqN28IDXHXUeXIeQJAOw0BwIagbCZW9BtYX4hSKocyHkGZOYK2Jgs6ndaKJIzDsSTOXQ5wfkAlavoNyeKxw7eMoKcC4ZnuFuuG0BBrCNTx6l2SIdDSeHItXplUunRUpt8t/RHMrIZxrcKHpD+ijUcASLMJKuERvDjrQzIl2BCoZL0DaWFD8PTFZfzhv5xCR7MVhzUWj+Wju8WWGWK/Fk1gJRhjj0AF77yhH0PtTZqGStkQ5OGT33oev7ywhAPDbTg03IZDI+24oqt5SxJtfCUIi9GgqZumBFlUpqaEVKscASCFhx48OolkSug6JObYhNRk6/qd3HFUDc1WE0wGyttvKJ5M4X/8+AK+9MtL2NXZjC++55Wai8fy0eW04eLiMgCuGCoFk9GAG9NegWbX1PRq24RkSuCJ05fR0WzBc5Or+MEL8wCA9iYLDo604eBwOw6NtGN3VzMmloMYaKv8nNVWuxktNpOq0FCp84pzMdrtRCSewpQnpKs3dGRsBaPdTrRppKBsFIgob7+haU8IH3/oJE5Ne/HuA4P4r2/eB3sJbclLpbvFisVAFKmUwBQbgpqADUEOLiwEsBZN4K/eeiXeel0fpj1hHBlbwZHxFRwd8+CxFy8DkEQ7sURKc+uslD63Q2WOQA4Nle8R7MlKGOtlCOLJFE5MruK3b9Be4doIuB3mLcniR5+fw5/9+4sAAfe+53q86ZodFV9Xd4sNyZTASjDGHkGNwIYgBycmVwEA1w+6QUQYbHdgsN2Bd71qAIC0ozoytoKj4x48N7mK39zbXZV19rvtmFxR3njOH4nDZjbAYiq/RmBPtxSfPH85gDde1VP29XJxZs6PUCyJA+mZrYw63E3rbSZCsQQ+++gZPHJ8BjfsdOMLd1+XyTNVmnVRWQRTnhBabCa0Orj9dDXRzRAQ0WcBfATAUvrQp4UQj6W/9qcAPgwgCeATQogf6rWOUnhuchUdzZa8u5SBNgcG2hx45/6BCq9sI/1uO565uAwhhCIBULl9hrJxWEwYbHPo2oX0aLr3OhuC0nA7zBhfDuLMnA8ff+gkxpeD+PhvXoE/eO3uqtbsd6VFZYsByRBwxVD10dsj+P+FEH+ffYCI9gG4G8CVAHoB/ISI9gghkjqvRTEnplYz3kAt0+eyIxhLbmjgVQip86h2t3y0x6lrCenRcQ9GOpvQ5WTFaSm4HRb8fGUJb7v3GbibzHjwPxzEq3d1VHtZG4bYT3lCGO12VnlFTDW2BXcBeFgIERVCjAO4COBAFdaRk+W1KCZXQrihDqpUsktIlSDNItDOBR/tdmJ8OYhoQnsbnkwJHBv34OBwdfIv24FOpxWxRAq37unA439wa00YAQDobJZCQ/O+CGZ4IE1NoLch+H0ieoGIvkpE8pO1D8B01jkz6WM1wXPp/EB9GAJ1JaRS51ENDUGPE8mUwKVF9QNyivHSvB+BaAIHOSxUMh+8aRhf++CrcP/v7q+pqiuLSeqj/+KMF7FkikNDNUBZhoCIfkJEp3P8uwvAPwHYBeA6APMA/kF+WY5LbWmYQ0SHieg4ER1fWlrK8RJ9ODG1CrORcFVf7Q9AGSjFI9A4NAQA5xf8ml1T5ui4pB84OMKGoFTamix4zWhXTYY4u1psmaIM9giqT1lPBSHEbyk5j4juB/D99KczALKzrP0A5nJc+z4A9wHA/v37K9PvGJJHcFVfK2zmytVVl0qL3YRmq3ItQbnTyTYz3NEEs5Fw/vKaZteUOTq2gsE2h6bzcpnaobvFipfmpQ0EG4Lqo1toiIiyC5TfBuB0+uNHAdxNRFYiGgawG8Czeq1DDbFECs/P+HDDYO2HhQBJNCTNJVAYGtLYIzAbDdjV2Yzzl7X1CFIpgWcnPBwW2sZ0pwsADKRt8zSmNPSsGvpbIroOUthnAsBHAUAIcYaIHgFwFkACwD21UjF0Zs6HWCJVV+0MlA6oicSTiCVSmiaLAWBPtzPj4mvFy4tr8IbiXDa6jZG1BDta7ZroWpjy0M0QCCF+p8DXPgfgc3p971J5Lj0ApR4SxTJ9LjuOjnmKagkCGjacy2a0x4lHn5+DPxLXTKNwdFzSD8jtdpnth6wl4LBQbcCmOIvnJlfR57Jn6pzrgX63A4FoIjNrIB9aNpzLRq4Bf1lDPcHRMQ96W22Zqihm+9HNhqCmYEOQRgiB45OeuvIGgPUS0pkiJaRatqDOZn1IjTYJYyEEjo6v4OBIe01WuzDaIIeGBis82Y/JDRuCNHO+CBb80To0BMpKSLUaSrOZPpcdTRajZgnjseUgltdinB/Y5ox0NmNvj7NqDRuZjXDTuTQn6khIlo08l6CYIdBqTOVmDAbCHg1bTRwdS+sH2BBsa5qtJjzxh7dWexlMGvYI0jw3uQq72Yi9PfXV98TtMMNhMRYtIdUrRwCsTysTony5x9HxFXQ6rRWf+MYwjQwbgjQnJldx3YCrql0ZS0HWEswW8wgi2g2l2cyebidWQ3EsrUWLn1wAIQSOjkn6Ac4PMEzlqK+nnk6EYgmcnffj+p31ORe3z1VcSxCIJGAgoMmivSHYmzWkphymPWFc9kc4LMQwFYYNAYAXZqQB6fWWH5DpdzuKhob84TiarSYYdBipuUcjQ3AkrR84yPoBhqkobAiwnih+5UC9GgI7/JFEJvyTC61bUGfT0WxFR7OlbENwdMyDtiYLdnc1a7QyhmGUwIYAUqJ4V2eTouEutYhcQlooT6B1w7nN7Ol2lj2t7NmJFRwY4vwAw1SahjcEQgicmFqt27AQoKyEVOuGc5sZ7XHiwsIaUqnSKofmvGFMe8KsH2CYKtDwhmBsOQhvKF7XhiCjLi6QJ9B6KM1mRrudCMeTmFbYCXUzRzP5ATYEDFNpto0h8ARjeOL0ZdWvq1chWTbtTRbYzIaCoSEpR6CvRwCUnjA+OuZBi82EvT0tWi6LYRgFbBtD8JWnxvCxb57Ar15WN83s5NQqWu1mjHTUb4KSiIqWkGrZHTQXu7vLMwTPjntwYLgNRh2qmhiGKcy2MQTHxqWd/d88dk5VnPrE5CquH3TpUlZZSfrdjryN51IpgbWovjmCZqsJ/W57Sa0mFv0RjC0HOT/AMFViWxiCaCKJUzNejHQ04ey8H999flbR63zhOC4srOH6OplIVohC6uK1WAJCQNccASAJy0rxCDLziYdZP8Aw1WBbGILTs9JksT9+wyiu6mvB3//wAiLx4kPPTk7Vf35Apt/twGoojrXo1rkE8lAaPXMEgFRCOr4cRDShbuDc0fEVNFtNuLKX8wMMUw22hSE4PiE90PcPteHTt78Cs94wvvHriaKve25yFQYCrh2oz9YS2cglpLm8An9Y7jOkr0cw2uNEIiUwthRU9bpnx6U5EPXW54lhtgvb4p13bGIVwx1N6HRa8eorOnDbaCe++LOL8IZiBV93YmoVr9jRgiZr/XfjLlRCmvEIKmAIAKgSlnmCMVxYWOP8AMNUkbo3BKmUwIlJD/ZnhXc+dfteBKIJ3Pvzi3lfl0wJnJrybouwELBuCGa9hTwCfQ3eSEczTAbCORV5gmcz84nZEDBMtah7QzC2vIbVUByvGlp/kOztacFvX9+PB56ZxLQndyXN+csBBGPJbWMIOpqssJgMOUtIA1F9ppNtxmIyYKSzCRdUGIIjYx7YzAZc3Vf/4TmGqVfq3hDI+YEbhjY+0P/o9XtABPzDj87nfN2JdKJ4O1QMAdKksH6XPWdoSK/pZLkY7WlRVUIq5wcsprr/U2SYuqXu333HJlbR1mTByKaJVjta7fjwzcP4zqk5nJ71bXndc5Or6HJaMyGV7UBfnhLSgI5DaTYz2t2MmdVwzuqlzfhCcbx02Y8DQ1w2yjDVpO4NwfF0fiBXx8qP3bYLbocZf/3YS1vGKEpCstyvq1ekuQQ5cgSRBKwmA6wmo+5r2NOtPGF8bMIDIbi/EMNUm7o2BIuBCCZXQhvyA9m02Mz4+G/uxjOXVvDLC0sbXjflCW2b/IBMv9uOlWAModjG3XggEtc9PyAj9wp69NQcXpr3F9QUHB1fgcVowHXboHyXYeqZuq6bPJEnP5DN+w7txNefmcDnHz+HW3Z3wmggPDfpBQBcvw0NASBpCeTeP4CUI6hEWEhew0CbHV9/ZgJff2YCJgNhuKMJoz1O7O1xYrSnBXt7nOhz2fHsuAfXDbhgM+vvqTAMk5+6NgTHJlZhNRlwVW9r3nMsJgP++A2j+PhDJ/Hvz83gnfsHcHJqFRajAVf1bS8la0ZL4N1kCHRuOJeNwUD42X++DWNLQZxfCOD8ZT/OXw7g1LQX339hPnNek8WIUDyJ33/NFRVZF8Mw+alrQ3B8UtpRFqs4edPVO/DlX43hH350AW+5thcnJldxdX9rRWLmlaTPJU0q25wn0HsozWbMRgNGe5ySwOza3szxtWgCFxYCOH9Z+jezGsJbX9lXsXUxDJObujUEwWgCZ+b8+I+/savouQYD4VO3vwLvvv8IvvTLS3hh1ocPvHpI/0VWmC6nFWYjbSkhDUTiNVEd1Ww14fpB97Yp2WWY7UJZyWIieicRnSGiFBHt3/S1PyWii0R0nojekHX8jeljF4noU6V+7+envUimRMH8QDY37mrHa/d24X/99GXEEqlt+TAyGKS5BJtLSP3hynoEDMPUF+VWDZ0G8HYAT2YfJKJ9AO4GcCWANwL4RyIyEpERwL0AbgewD8C70+eq5tjEKojUCcL+y+17Mx9fv3N7VqrkKiENVDBHwDBM/VGWIRBCvCSEyCXdvQvAw0KIqBBiHMBFAAfS/y4KIcaEEDEAD6fPVc3xSQ9Gu51oVVEWuafbife/egjX9reiy2kr5dvWPJsnlUUTSUQTqYpVDTEMU3/o9XToA3Ak6/OZ9DEAmN50/GCuCxDRYQCHAWBwcHDD1xLJFJ6bXMXbr+9XvbD/+uaSHJC6od9tx/JaFJF4EjazMWsWAXsEDMPkpqhHQEQ/IaLTOf4V2snnkuuKAse3HhTiPiHEfiHE/s7Ozg1fO5duGLdfYX5gw8KItpWaeDP9bRu7kFaq8yjDMPVL0aeDEOK3SrjuDICBrM/7AcylP853XDHHJ6TRhmoA9uAAAAlcSURBVPvzKIobmewS0l2dzRWbRcAwTP2iV4uJRwHcTURWIhoGsBvAswCOAdhNRMNEZIGUUH5U7cWPTa6it9WGPlf1SyJrjc0DavyRykwnYximfim3fPRtRDQD4EYAPyCiHwKAEOIMgEcAnAXwBIB7hBBJIUQCwO8D+CGAlwA8kj5XMUIIHJ/wsDeQh+4WG0wGypSQVmpeMcMw9UtZTwchxLcBfDvP1z4H4HM5jj8G4LFSv+fMahgL/mhJ+YFGwGgg9GZVDlVqXjHDMPVL3XUfPT6Zzg/sZI8gH31ZA2rWcwTsETAMk5u6MwTHJlbhtJoyg9KZrfS7szyCSBxEQJOFDQHDMLmpO0NwfMKD63e6YTRs3xLQcul3O7AYiCKaSCIQScBpNcHAvy+GYfJQV4bAF4rjwsIa9m+zOQJa05euHJrzRuAPxzk/wDBMQerKEJyYYv2AErJLSP2RBKuKGYYpSF0ZgmMTqzAZiEcbFiF7Upk/EmdVMcMwBakrQ3B8woOr+lpht2yvgTJa09Nig9FAmFkNI1DhoTQMw9QfdWMIookknp/xcX5AASajAT0tNik0FOYW1AzDFKZuDMHpWR9iiRTnBxTS77Zj1htGgENDDMMUoW4MwbGJVQBgRbFC+t0OTHlCCEQ5WcwwTGHqZqt4fMKDkY4mdDRbq72UuqDPbceCPwqAW1AzDFOYuvEITkyu4gbODygme1g95wgYhilEXWwVo4kUAqE4XsX5AcVkGwIWlDEMU4i68AiCUalxGucHlDPgdmQ+5hbUDMMUoj4MQSyB9iYLhjuaqr2UuqGn1Qa5vRB7BAzDFKIuDEEomsQNO93betaw1pjTWgKAW1AzDFOYujAEsWSK8wMl0J8OD7FHwDBMIerCEACcHygFuQspl48yDFOIujAEwx1NuLK3tdrLqDtu2OnGrs4m2Mzcm4lhmPzUxVax2WqCxVQXNqumeN+hnXjfoZ3VXgbDMDUOP10ZhmEaHDYEDMMwDQ4bAoZhmAaHDQHDMEyDw4aAYRimwWFDwDAM0+CwIWAYhmlw2BAwDMM0OCSEqPYaikJEPgAvKzi1FYCvQc6r5bUBwCCAKY2uV+s/ayPdfy3vq9Lzavk+VOs8pdfaLYQo3pZBCFHz/wDcx+dV/3uqPG+pgX7WRrr/mt3XOvhZa/Y8rb9nvYSGvsfn1cT3VHOeV8Pr1frP2kj3X8v7qvS8Wr4P1TpP0+9ZF6Ehpv4gouNCiP3VXgejLXxftyf14hEw9cd91V4Aowt8X7ch7BEwDMM0OOwRMAzDNDhsCHSCiNaKfP0XRMSx1jqD7+v2pNHvKxsCpiyKvYGY+oTva2PBhkBHiOg2Ivp+1udfJKIPVHFJjAbwfd2eNPJ9ZUPAlA0RNRPRT4noOSJ6kYjuSh8fIqKXiOh+IjpDRD8iInu118sog+9r48CGgNGCCIC3CSGuB/AaAP9ARJT+2m4A9wohroQkRnpHldbIqIfva4NQF8Pr65gENhpbW7UWojME4K+J6FYAKQB9ALrTXxsXQpxKf3wCwFDll6c5fF/5vm4r2CPQl0kA+4jISkStAF5b7QXpxHsBdAK4QQhxHYAFrL+JolnnJbE9Nh98X/m+biu2w82rOYjIBCAqhJgmokcAvACpe+rJ6q5MN1oBLAoh4kT0GgA7q70gPeD7yvd1u8KGQB+uBHAJAIQQfwLgTzafIIS4rcJr0hz5DQTgQQDfI6LjAE4BOFfVhekH39ftSUPc10JwiwmNIaKPAfgEgD8UQvyo2uvREyK6FsD9QogD1V6L3vB93Z400n0tBBsCpiT4DbQ94fvamLAhYBiGaXC4aohhGKbBYUPAKIKIvkpEi0R0OuvYtUT067Tq9HtE1JL1tT8lootEdJ6I3pA+NkBEP0+rUs8Q0R9U42dh1tHovtqI6Fkiej59X/+yGj8LUzocGmIUkRYVrQH4hhDiqvSxYwA+KYT4JRF9CMCwEOIviGgfgIcAHADQC+AnAPYA6AKwQwjxHBE5IQmR3iqEOFuFH4mBZvc1BaBJCLFGRGYATwH4AyHEkSr8SEwJsEfAKEII8SQAz6bDowCeTH/8Y6y3GbgLwMNCiKgQYhzARQAHhBDzQojn0tcLAHgJklqVqRIa3VchhJC7lZrT/3iHWUewIWDK4TSAO9MfvxPAQPrjPgDTWefNYNMDn4iGALwSwFFdV8iUgur7SkRGIjoFYBHAj4UQfF/rCDYETDl8CMA9RHQCgBNALH2ccpyb2SESUTOAf4NUoujXfZWMWlTfVyFEMt2Goh/AASK6qiIrZTSBlcVMyQghzgF4PQAQ0R4Ab0p/aQbru0hAejjMpc8zQzICDwoh/r1yq2WUUsp9zXqtl4h+AeCNkDwLpg5gj4ApGSLqSv9vAPDnAL6U/tKjAO5ON+8ahtSy+Nl0C+OvAHhJCPE/qrFmpjgl3NdOInKlX2MH8FvYvu0otiXsETCKIKKHANwGoIOIZgB8BkAzEd2TPuXfAXwNAIQQZ9LNu85Cau17jxAiSUQ3A/gdAC+m48kA8GkhxGMV/FGYLDS6rzsAPEBERkiby0eEEN8HUzdw+SjDMEyDw6EhhmGYBocNAcMwTIPDhoBhGKbBYUPAMAzT4LAhYBiGaXDYEDAMACISRPTPWZ+biGiJiEoqgyQiFxH9Xtbnt5V6LYbRGzYEDCMRBHBVWhAFAK8DMFvG9VwAfq/oWQxTA7AhYJh1Hsd6O4V3Q2q5DAAgojYi+g4RvUBER4jomvTxz6Z7+v+CiMaI6BPpl3wewC4iOkVEf5c+1kxE/0pE54jowbTSmmGqDhsChlnnYUgtFGwArsHGzqh/CeCkEOIaAJ8G8I2sr+0F8AZIffo/k+6n9CkAl4QQ1wkh/jh93isB/CGAfQBGANyk5w/DMEphQ8AwaYQQLwAYguQNbG57cTOAf06f9zMA7UTUmv7aD9I9+pchtWHuzvMtnhVCzAghUgBOpb8Xw1Qd7jXEMBt5FMDfQ+q/0551vFBr7WjWsSTyv6+UnscwFYU9AobZyFcB/H9CiBc3HX8SwHsBqQIIwHKRWQoBSL38Gabm4R0Jw2QhhJgB8IUcX/osgK8R0QsAQgDeX+Q6K0T0dHoo/OMAfqD1WhlGK7j7KMMwTIPDoSGGYZgGhw0BwzBMg8OGgGEYpsFhQ8AwDNPgsCFgGIZpcNgQMAzDNDhsCBiGYRqc/wcANV+MDRO2FwAAAABJRU5ErkJggg==\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 0\n", + "count 35.000000\n", + "mean -5.495218\n", + "std 68.132882\n", + "min -133.296637\n", + "25% -42.477890\n", + "50% -7.186512\n", + "75% 24.748330\n", + "max 133.237936\n" + ] + } + ], + "source": [ + "# fit modelo\n", + "model = \n", + "model_fit = " + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'fc' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m#faça a previsao\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mfc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconf\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;31m#plote o resultado\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'fc' is not defined" + ] + } + ], + "source": [ + "#faz split do modelo e a previsão\n", + "X = series.values\n", + "size = int(len(X) * 0.66)\n", + "train, test = X[0:size], X[size:len(X)]\n", + "history = [x for x in train]\n", + "predictions = list()\n", + "for t in range(len(test)):\n", + " model = ARIMA(history, order=(5,1,0))\n", + " model_fit = model.fit(disp=0)\n", + " output = model_fit.forecast()\n", + " yhat = output[0]\n", + " predictions.append(yhat)\n", + " obs = test[t]\n", + " history.append(obs)\n", + " print('predicted=%f, expected=%f' % (yhat, obs))\n", + "\n", + " error = mean_squared_error(test, predictions)\n", + "print('Test MSE: %.3f' % error)\n", + "\n", + "# plot\n", + "mtpl.pyplot.plot(test)\n", + "mtpl.pyplot.plot(predictions, color='red')\n", + "mtpl.pyplot.show()\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/3. Modelos regressivos/Exercicio_ARIMA/Prevendo com ARIMA.ipynb b/3. Modelos regressivos/Exercicio_ARIMA/Prevendo com ARIMA.ipynb new file mode 100644 index 0000000..04a80af --- /dev/null +++ b/3. Modelos regressivos/Exercicio_ARIMA/Prevendo com ARIMA.ipynb @@ -0,0 +1,785 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Prevendo com ARIMA\n", + "\n", + "\n", + "Agora vamos praticar em python como criar um modelo ARIMA.\n", + "\n", + "Vamos analisar um dataset que contém vendas de shampoo durante um período de 3 anos. As unidades são vendas e ele possui 36 observações." + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [], + "source": [ + "#Primeiramente vamos importar as bibliotecas que iremos utilizar\n", + "\n", + "\n", + "import pandas as pd\n", + "import matplotlib as plt\n", + "import numpy as np\n", + "from statsmodels.graphics.tsaplots import plot_acf, plot_pacf\n", + "from statsmodels.tsa.arima_model import ARIMA\n", + "from statsmodels.tsa.stattools import adfuller\n", + "from numpy import log\n", + "from sklearn.metrics import mean_squared_error\n", + "from statsmodels.tsa.stattools import acf\n" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " value\n", + "0 88\n", + "1 84\n", + "2 85\n", + "3 85\n", + "4 84\n" + ] + } + ], + "source": [ + "#função para tratar campo data\n", + "def parser(x):\n", + " return pd.datetime.strptime('190'+x, '%Y-%m')\n", + "\n", + "#Agora vamos importar nosso arquivo \n", + "df = pd.read_csv('dataset.csv',names=['value'], header=0)\n", + "print(series.head())\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.plot()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Podemos ver que o conjunto de dados tem uma tendência clara.\n", + "\n", + "Vamos também dar uma olhada rápida em um gráfico de autocorrelação da série temporal. Isso pode ser feito usando o Pandas. O exemplo abaixo plota a autocorrelação para um grande número de lags na série temporal." + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "pd.plotting.autocorrelation_plot(df)\n", + "plt.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Isso sugere que a série temporal não é estacionária e exigirá diferenciação para torná-la estacionária.\n", + "\n", + "Para torná-la estacionária precisaremos diferencia-la. \n", + "\n", + "O objetivo de diferenciá-lo para tornar a série temporal estacionária.\n", + "\n", + "Mas você precisa ter cuidado para não superestimar a série. Por isso, uma série super diferenciada ainda pode ser estacionária, o que, por sua vez, afetará os parâmetros do modelo.\n", + "\n", + "Então, como determinar a ordem correta de diferenciação?\n", + "\n", + "A ordem correta da diferenciação é a diferenciação mínima necessária para obter uma série quase estacionária que circula em torno de uma média definida e o gráfico do ACF chega a zero razoavelmente rápido.\n", + "\n", + "Se as autocorrelações forem positivas para muitos atrasos (10 ou mais), a série precisará ser diferenciada. Por outro lado, se a autocorrelação lag 1 em si for muito negativa, a série provavelmente será super diferenciada.\n", + "\n", + "No caso, você não pode realmente decidir entre duas ordens de diferenciação e seguir a ordem que apresenta o menor desvio padrão na série diferenciada.\n", + "\n", + "Vamos ver como fazer isso com um exemplo.\n", + "\n", + "Primeiro, vou verificar se a série está estacionária usando o teste Augmented Dickey Fuller (adfuller ()), do pacote statsmodels.\n", + "\n", + "Por quê?\n", + "\n", + "Porque você precisa diferenciar apenas se a série não for estacionária. Senão, nenhuma diferenciação é necessária, ou seja, d = 0.\n", + "\n", + "A hipótese nula do teste ADF é que a série temporal não é estacionária. Portanto, se o valor p do teste for menor que o nível de significância (0,05), você rejeita a hipótese nula e deduz que a série temporal é realmente estacionária.\n", + "\n", + "Portanto, no nosso caso, se P Value> 0,05, prosseguimos em busca da ordem da diferenciação.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ADF Statistic: -2.464240\n", + "p-value: 0.124419\n" + ] + } + ], + "source": [ + "result = adfuller(df.value.dropna())\n", + "print('ADF Statistic: %f' % result[0])\n", + "print('p-value: %f' % result[1])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Como o valor p é maior que o nível de significância, vamos diferenciar as séries e ver como fica o gráfico de autocorrelação." + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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n8ECoAm0kVd0kIt/HJaSLReS/uN7m6biCc6twFWKNaRRLHk2b4PUk3iwi/wGux1USOxnX07gJVx78z95Vy0Q95y4RmYrr9ZyBS1BX4xae349LHutc7L4Jfok7GXwbdxIuwV2N/QUNW/Yilp/gehVPAY7GzdNIx524XgYeU9X/hT/Aqwx7Lm4u5FW4tSI7eXFu9GJ+MgGxoap3i8hc3NDTY3EfckpwyerfcVUFQx7CJYlTcAlsOrDN236vqm5OREzGGJNkoZ7Dh+tq5CUXb+EqaX9FVZ8XkZNxlVhPxSVCK3C9eEVETx4fxl2suwR3vkjHTQf5t/ccL4rINOBWXPKXi0sa/wb8WlUPSpS8KqBTcb2JX8XNyQzgLlw+SthFR1Xd4M0f/AXu3HsC7lw7G/itqn5c56vUCKpaKiLTvbguwxUdysadE9cCP8Cdg+s6RkBEzsYt7zUDd/4qwL2WvyHKhVXvdbkAVyDuG7iL5OB6F2POWVTVh0RkHfAjL9Yc3Gt5D25d5VgF+oypl6g2tFaFMaY+IvJb3EnzDFV9PdnxGGOMMcYY01SWPBrTBCLSN/IKqjdPZB5uyE0/bxFhY4wxxhhjUpoNWzWmaT7xhoaswA1VHQGchStGda0ljsYYY4wxpq2wnkdjmsArNnAurvJbZ9xyFQuAP6jqe8mLzBhjjDHGmMSy5NEYY4wxxhhjTL1snUdjjDHGGGOMMfWy5NEYY4wxxhhjTL0seTTGGGOMMcYYU692U21VRHKB6bhFUquTHI4xxpjmkwkMAN5X1ZgLaRvHzo/GGNOuNOkc2W6SR9yJ8cVkB2GMMabFnAO8lOwgUoCdH40xpv1p1DmyPSWPWwFeeOEFhg8fnuxYjDHGNJN169Zx7rnngve+b+pl50djjGknmnqObE/JYzXA8OHDGTNmTLJjMcYY0/xsCGZ87PxojDHtT6POkVYwxxhjjGlhItJZRH4vIm+ISKGIqIjc3oDH9xKRx0Vkj4iUi8h8ETm5GUM2xhhj2lXPozHGGNNadAeuAZYCLwDfjveBIpIFvA3kATcBu4Hrgdkicoqqvp/4cOtWUl7Dqyt2ULivip6ds5gxNp/cnIyWDsMYY0wzs+TRGGOMaXmbga6qqiLSgwYkj8C3gLHAVFWdDyAi7+IS0d8DUxIdbCyqygPvrOPBd9dR5Q/Wbr/9pZVcf+JwbjxpOCLSUuEYY4xpZjZs1RhjjGlh6mnkw88DVocSR+94fuAJYLKI9EtEjPF44J11/PHNNQcljgBV/iB/fHMND7yzrqVCMcYY0wIseTTGGNOs9pRV8fvZq5iztjDZobQVY4FlUbaHtrVI1ZuS8hr+8m7dyeH9b69l697ylgjHGGNMC7Dk0RhjTLO64anFPPTeer72yEf8eNZSSipqkh1SqusOFEXZXhS2Pyqv0M6Y8BswrDFBvLpiB9URPY6R/EHlxHvf4/6319L4jlZjjDGthc15NMYY02wWbNjLgg0H8pxZi7YxZ+0efnfBOE4Y1SuJkaW8ujKxuvZdB9yWiAAK91XF1c4fVP745hoAvnfyiEQ8tTHGmCSxnkdjjDHN5r631gKQneHj2OE9ANhZWslVj33M7BU7kxlaKttL9N7Fbt59tF7JkIdww17Db+c0JoienbMa1P7Bd9dRUm69zsYYk8oseTTGGNMsFm7Yy/wNewG4fMog/v2tyfzu/HHkZKYB8ONnlrK1yObDNcJyYFyU7aFtK2I9UFV3q+rK8BuwvjFBzBibT1Z6/B8jqvxBXluxozFPZYwxppWw5NEYY0yzuO9t1+uYle7jO9OHIiJcMnkgf7x4AgD7Kv3c8NTieufNmUM8D4wWkdolOUQkHbgCWKiq21siiNycDK4/cXiDHhPvUFdjjDGtkyWPxhhjEu6jjUXMW3+g17FX5+zafWeM7cNVUwcDsHRbCXfPXpWMEJNORM4UkQuBr3ibDheRC71bjtfmERHxi8igsIc+CqwEZonIZSJyCvBfYBRwS0v+DDeeNJwfnjqSdF98azlu3LPfhq4aY0wKs+TRGGNMwt33tiuQkpXu49rpQw/Z/7MZoxnXLxeARz7cyMvLWqSzrLX5KzALlwwCXOR9PwsIVRNK82612ZmqVgEnA+8CDwD/A/KBM1X1/RaJ3CMifO/kEbx78wkQDNRbUfW5TwuYfNdbVn3VGGNSlCWPxhhjEmrZtmLmrnO9jpdNGUivLtmHtMlKT+PBy46kc5Yr+n3DU59y6/PLKavyt2isyaSqg1VVYtw2eW2uCv8+7LG7VPVKVe2uqh1U9RhVfSsZPwfAgO455BXMR0SgnqSwyh/kj2+u4YF36l4j0hhjTOtjyaMxxpiEenzeJgDSfMI1xx/a6xgysHsO9106obaAzlMLt3D6nz5g7ro9LRGmSbDcgvkUz3kC0UBc7a36qjHGpB5LHo0xxiTMnrIqXl7qKmqeMaYP+bkd6mx/0ujevP794zlmqFt5oqC4gssfXshf3lnb7LGaxBKgZN5M+i96iI67YxZ8rWXVV40xJvVY8miMMSZhnl64heqAq5561bTBcT1mQLccnvz2FH59zhg6ZKQhAlOGRlvG0KSCtEAVGVXFcbW16qvGGJNa0pMdgDHGmLahJhDkiYWbATg8vwtHDeoa92N9PuFrxwxm+shezFlXyJcGd6v/QabVSqvZH1e7np2zmjkSY4wxiWQ9j8YYYxJi9oqd7Cp1PUlXTR3siqc00MDuOVw+ZVD9DU2rlrN3NcGaqjqL56T7hGnDerRgVMYYY5rKkkdjjDEJ8U+vUE7XnAzOntA3ucGYpEoLVFG6YBbUcQHBH1RO+dP7tmyHMcakEEsejTHGNNmKghI+2fwFAJdMHkh2RlqSIzLJVjJvJnlbPyQrPfZHDVu2wxhjUoslj8YYY5rsoffch3+fwBVH27BT4+QVzOetH0yHYKDO3kVbtsMYY1KDJY/GGGOa5MO1e3h1+U4AvjK+L/3y6l6ew7QvH67fA760OufA2rIdxhiTGix5NMYY02jV/iC3veTW9MvJTOOnZ45OckSmtYl3OQ5btsMYY1o/W6rDGGNMoz0+byPrC92yDN87eQT5udbraA4W73IctmyHMaYtCQSVQFAJqrsPqKJBCKp6N9DQPYoqKG5b5Cj/0Pcds9Lo3im575WWPBpjjGmUXaWV3PfWWgCG9ezIN6cNSXJEpjWaMTafW5/5lKDEHrqa5hPKqwOUlNeQm5PRwhEaY0zd/IEgNQGlJhikxh/EH1SqvXt/IHSv+INBAkHFHzw0AUyEnp2zLHk0xhiTeoJB5c7/fcb+6gAAd5w9lsw6qmqa9is3J4PcggUUDzjWXT6PkkAGgsqdL3/G3bNXcf2Jw7nxpOGNWifUGGPipapUh5JCf5CaQJDqQJBqv7fN+77GHyRoqwnVsuTRGGNMg2zeu58fP7OMjzYWATBjXB+OHWGLvZvYcgvms2nTJrpOuwSV2B89Qkt3gBsGbYwx0QSDinJgCKgqtUNDg17PX+g+1CPoD7qEsCagtT2JpuEseTTGGBOXYFD51/xN3D17NRU1rsdxUPccfvXlMckNzLR6glv3cVx2EWU9Dqdo0ImI+KL2QoJbuuPKYwbbEFZjmlkowXJDLYO18/RCiVggqASD1H6tGkrQXOIG1CZvtfP1IGzIpvsi3iGc0ZqFHnvosU0yWPJojDEmLr999XMe+XBj7fdfP2YQt5wxmo5Zdiox8UkLVOHTAOJLq7NdaOmOSyYPbKHIjElN4UVZ/EElEHDJXe3cu8CBxNAf+X1AbTimaTA74xtjjKnX7BU7axPHfnkduOeiI5g6zIaqmoYLZHSMq50t3WFag/DKl6GetQNfH6iSScT3wbBestAxIreFqmwG1RuGqYdW4gzv5QtV7QztDzRTURZj6mLJozHGmDptLSrnJ88sBaBzdjozrzmaAd1ykhyVSVVpNfvjamdLdzQfVXXzvoKHVokMH6YY9OaP1SY5wejJUuhrOHjYoSYos6lrKGNdLaO10Rj7w5PC2Mc3xljyaIwxJqZqf5AbnlpMaaUfgHsuHG+Jo2mSnL2rKRxwAr70zJhzHrPSfZw5Nr+FI2s7agJBKmsCVNYEqfIHqPaHV5F0hUIsOTLGNIYlj8YYY2K6e/Yqlm4rAeCqqYM5Y2yfJEdkUl1aoIrSBbPIO+6KmG2uP3G4FcuJQyColFX5Ka/2U14doKI6QEVNAL9VkTTGNJOELMolIieJyKMiskpE9otIgYi8KCKTorQ9UkTeEpEyESkWkedEZGiM497oHbNKRDaKyG0iYmcTY4xpAQXFFTw6181zHNcvl5/NGJ3kiExbUTJvJnlbPyQrYm3QdJ8wdVh3enTKpKS8JknRtV7l1X52lVaybvc+lmwt5qONRXy2vZRNe8rZXVrFvkq/JY7GmGaVqBWdvwsMBu4DZgA3Ab2ABSJyUqiRiIwG3gMygYuBbwIjgTki0jP8gCLyc+94zwGnAw8BtwIPJihmY4wxdfhgTWHt0LY7zxlDVnrdFTKNaYi8gvl8dOspdFs/m4pNSyAYwB9U5q3fy63Pr2DyXW9x/9trEzZvLhWVV/vZUVLB6p37+HhTEUu3lrChcD+F+6qpqA4kOzxjTDuUqGGr16vq7vANIjIbWIdL+N7xNt8JVAFfVtVSr90iYC3wI+AWb1t34BfAP1T1Vu+x73m9jr8RkT+r6mcJit0YY0wUH67dA0DXnAzG989LcjSmLcrNySCY2YkOAyYcUqGkyh/kj2+uAeB7J49IRngtriYQpKSihuLyGkoqqqn2t9/E2RjTOiWk5zEycfS2lQGfAQMARCQd+DLwbChx9NptBt4Fzgt7+BlANvBYxGEfw601fG4i4jbGGBNdIKh8uM4lj9OG98Dni17YxJimKCmvobjf0a53MUbxnAffXdemh7BWVAcoKK5gRUEJizZ/wdpdZRTuq7LE0RjTKjVbwRwRyQWO5ECv4zCgA7AsSvNlwKkikq2qlcBYb/vy8EaqukNE9oTtj/XcvYCeEZuHNewnMMaY9mtFQQklFe4D+3EjbD1H0zxeXbEDfOnUdWmiyh/ktRU7uGTywBaLqzmpKvuq/Hyxv5qi/dVU1gSTHZIxxsStOautPgh0BH7rfd/duy+K0rYI16PYFdjhta1S1WiLQRWFHSuW64DbGhqwMcYYZ87awtqvjx0ReS3OmMQo3FeV0HatVTColFTUUFReTXG5DUc1xqSuZkkeReTXwOXAjaq6KGJ3Xe+YGuPrutpF8xAwK2LbMODFeh5njDEGmOPNdxzasyP98jokORrTVvXsnJXQdq1JtT9IcUU1JeU1fFFeQyBoCaMxJvUlPHkUkdtwxW5+rqp/Cdu117uP1mvYDZcQFoe1zRaRHFUtj9I2MiE9iDcHM7KAT3w/gDHGtHP7q/ws3vIFAMdbr6NpRjPG5nPrM58SlLSY5+msdB9njs1v4cgaLhhU9lX6Ka2soaSihrIqf2QNIGOMSXkJTR69xPF24HZVvSti93qgAhgX5aHjgHXefEc4MNdxHLAw7Ph9gB7AigSGbYwxJszCjXup8daKs/mOpjnl5mSQW7CA4gHHumqrURLISYO68uqKHcwYm09uTutY6llVqfIH2VfpZ3+Vn7Iqd2+di8aYti5hyaOI/BKXOP5GVe+I3K+qfhH5H3C+iPxEVfd5jxsInAj8Kaz5bKASuIqw5NH7XoEXEhW3McaYg32wxg1ZTfcJU4bWN8XcmKbJLZjPpk2b6DrtElQO/Vgyb/1e5q3fy+0vreT6E4dz40nDEz6aSFVRdR8wgqoEgkpQFX9QqfYHqQkEqfErlf4AFdUBKmsCligaY9qlhCSPInIzbg3H2cArInJ0+H5VXeB9eRvwMfCyiPwOtxzHncAe4N6w9kUi8hvg1yJSBLwBfAmXnD5sazwaY0zzCS3RceSgrnTKas66asa4ankl82YyLruI8m4j2ZbWhw6DJxzSrq51HytrAuyv8lPpD1JVE6DKH8QfUPzBoJcMegkihywnaYwxpgES9angK979Gd4tkgCo6ioROQG4G3gG8OOW8viRqhaGP0BVfysi+4DrgR8BO4HfcaB6qzHGmATbUVLBut1lABw33IasmpaTFqgip2gN2RNPijmEFdwGqNNLAAAgAElEQVS6j1ccPQh/MEhJeQ2llX6q/bbchTHGtISEJI+qekID2i4CTomz7f3A/Y0MyxhjTAOFqqwCHDfSiuWYllXefRSSnllnmyp/kL9/sJ7pI3u1UFTGGGNCfMkOwBhjTOsRSh5zO2Qwrl9ukqMx7U0go2Nc7faWVTdzJMYYY6Kx5NEYYwzglhqY6813nDa8O2k+W+KoOYlIJxH5s4hsF5FKEVkiIpfE8birRERj3Pq0ROzNJa1mf1zt8nLq7p00xhjTPKwSgjHGGAA+21FK0X7Xo3PscBuy2gKewxWD+ymwBrgMeFpEfKr6VByP/wawKmLb3mgNU0XO3tUUDjgBX3pmzDmPGWnC5CHdWjgyY4wxYMmjMcYYz0HzHW19x2YlIjOAU4HLVPVpb/O7IjIIuEdE/qOqgXoOs0JVP2nWQFtYWqCK0gWzyDvuiphtzp3Qz6oAG2NMktiwVWOMMQDMWeuKXg/unsOAbjlJjqbNOw8oA2ZFbH8M6AtMafGIWomSeTPpsPF9MtIO7nlMExjTtwu5HTIoq/InKTpjjGnfLHk0xhhDRXWATzZ9AcBxI2zIagsYC3yuqpFZ0LKw/fV5WUQCIlIkIs+JSL2PEZFeIjIm/AYMa2DszcYfcIswdtg0l4cun0SHVa9QsWkJBAMEFFZuL+XhDzdy3ZOLeG7xNtQWbTTGmBZl4z6MMcawcONeqgNurbxjbchqS+gObIiyvShsfyw7cWseLwBKgXG4eZMLRGSaqi6t47HXAbc1PNzmFwgqFTUHRup2ykqHzE50GDzBrfsYpiagzFq0DYDzj+zfonEaY0x7ZsmjMcYYPvTmO6b5hGOG1ZW3mASqq9ss5j5VnQ3MDtv0gYi8AiwH7gTOqeO4D3HoUNlhwIt1h9r8yqsDB/UkllX5qRg8DVVFYhTPeWFJAaeN6WNzII0xpoXYu60xxpjaYjkTBuTRJTsjydG0C3uJ3rsYKiNaFGVfTKq6SUQ+BI6up91uYHf4tliJWUsJ5YuRQ1AXbtwLvnTqiq4moHy0sYiTRvdqvgCNMcbUsjmPxhjTzu0urWT1rn2AVVltQcuBw0Qk8iLuOO9+RSOOKUCwSVElQaU/elHZkvKauB5fXF6dyHCMMcbUwZJHY4xp52yJjqR4HugEXBCx/UpgO7CwIQcTkSHANNw8yJRRUlFDjT96vpubE18PeF5OZiJDMsYYUwcbtmqMMe3ch+tc8tg5K53x/fOSHE37oKqvicibwF9FpAuwDrgUOAO4IrTGo4g8gksoh6nqZm/bW8AHuMqsoYI5P8HNk/xlS/8sTbFxz/6Y+6YM6c7D761Bfekxh9ZmpAmTh3SLus8YY0ziWfJojDHtWDCotT2PxwzrTnqaDUhpQefjqqbeiZvruAq4VFVnhrVJ827h2dNy4KvAj4AOuDmM7wC/VtU1LRB3QlT5g1RURx+yCq7aaofN86gYOt1NjIySQJ47oZ8VyzHGmBZk77jGGNOOPbt4G3vKqgA4fqSt79iSVLUMuMm7xWpzFXBVxLYfNGtgLaQqxlzHcNmb57KjYCt5U78KaQeGsWakCedO6Md5E/s1Z4jGGGMiWPJojDHtVElFDb97bRUAvbtkca59EDctqa6FSjwClMybyWB2U91zFNt3F9G3Vzfuuu3nrNhewvOfFpCbk8GUId2tB9IYY1qAvdMaY0w79ac317B3v6tUeeuMw+zDt2kRgWAcWWMEn7+S7B1LKfloHvkX/ZgfP7OUmsCB4/xz3qbanshkLz1ijDFtmX1SMMaYduiz7aX8a/4mAKYM6cbZ4/smNR7TflTHqK4aj9ypl7g5kIGDE9CagDJr0TYAzj+yf5PiM8YYE5tVRjDGmHZGVbntpRUEFdJ8wp3njLXeGtMigqrUBBuXPAbTs8k95mJXPCeGF5YUUFblb2x4xhhj6mHJozHGtCM1gSD3vL6ajzd9AcBVUwczqk/nJEdl2otqfzCuuY5RH9tzNJKeGbXqakhNQPloY1EjozPGGFMfG7ZqjDHtxOqd+7h51hJWFJQC0LNzFt8/ZUSSozLtSU2gkZkjoJkd42pXXF7d6OcwxhhTN0sejWljdpVW8uryHawvLONbxw5lSI/4PnCZtu3hORu4e/aq2g/vI3p14r5LJtI5O6OeRxqTOFrHkNP6SPX+uNrl5WQ2+jmMMcbUzZJHY9oAfyDIfz/ZxgufFvDx5qLaKUGzV+xi5jVTGN4r+rDEmkCQl5Zsp6C4onZbx6x0vvqlAVZ5sw3539Lt/OaVzwHwCVw7fRg3nTKCrPS0JEdmTPwyC1dRNuxkfHUMXc1IEyYP6dbCkRljTPthnw6NSXFrd+3j5llLWbat5JB9e8qquOTvC6MmkJ/vKOVHs5aycnvpIY9btLmIhy6f1Gwxm5azac9+fvbccgDycjJ4/BuTmTAgL8lRmfbG34jlOSL5/JWULphF3nFXxGxz7oR+duHLGGOakb3DGpNCisurKdp/YD7P6yt38ac311AdcNUL83Oz+cr4vswYl8/cdXu45/XVtQnkX684ku4d3XCuV5bt4P531sacf/Tq8p3MWVvIcSN6Nv8PZZpNZU2A659aXFt98o8Xj7fE0SSFP9D45TnClcybSX6/AfhHnHDQ+1eawOj8LuR2yKCsym8JpDHGNBN7dzWmlSvcV8XsFTt4ZfkOFm4silql3idw9fFD+cEpI8nOcEMRQ0lCKIG86G/zD3lcmk+4dvpQbjxpBBlpPnbvq+SUe99nf3WA215ayeybjicz3Yoyp6q7Xv28tmf5muOHctLo3kmOyLRXieh5DOmweS53334z37v1Doqy+9Fh4DgCvjRWbi9l5fZS/jl/E+dO6Md5E/vZEjTGGJNgljwa0wrtKati9oqdvLJsBws37qWuz11De3bkDxeN58iBXQ/Zd/2Jw1FV/vDGmkP2jejViXsvHs8R/Q/0ROXnduD7p4zkt69+zobC/Tzy4Ua+e8KwhPxMpmW9sXIn/5q/GYCJA/P48emjkhyRaa8qawIEE5g8Aq5nMbMTHQZPOGTdx5qAMmvRNgDOP7J/Qp/XGGPaO0sejWlF9pZVccuzy3hn1e5DEsb83GzOHJvPEf1za2tFdMxM59gRPWp7G6O54aQRnDCqF+sLy2q3dcpyj4tWMOWqaYP5zydbWbe7jAfeWcu5E/uSn9shIT+faRmBoPK72asA6JKdzgOXTiQjzXqQTXKUVNQk/JhlVX4qBk9DVWP2Lr6wpIDTxvSxIazGGJNA9o5qTCuxt6yKyx9eyKqd+2q39emSzZnj+vDlI/KZOKArPl/jhmCN7ZfL2H65cbXNSPNx59ljuOzhhZRXB/jNK5/z4GVHNup5TXK8vGw7GwrdsgbfO3kE/bvmJDki054Vlyc+eVy4cS/40qnrHbEmoHy0sYiTRvdK+PMbY0x7ZcmjMa1A0f7qgxLH08f05tvHDWXSwMYnjE0xdXgPzjoin1eW7eCVZTs4fcx2zh7ft8XjMA0XCCr3v70WgB6dMrl8yqAkR2Tau9LKxCePJXEmpMXl1fU3MqYNKavys3DjXkrKa8jO8AFCZU2A3JwMxvbNZcX2kqj7pgzpbr30Ji72V2JMkhXtr+ayfyyoTRzPn9iPey4aT1oSksZwvzzrcOau20NxeQ0/e3YZ4/rlMqRHx6TGZOr38rLtrPd6Hb9z/DA6ZNpajiZ5AkHFH6Oqc1Pk5mTE1S4vJzPhz21MaxJKFov3V7Nx736WbSuJWUm9Lo/P3cj4/nkM6dmJPEsmTR3sr8KYJPvJM0trE8fzWkniCNAnN5s/Xjyebz7+CfurA1z/5GKeu25qnfMrTXIFgsoD76wDvF7HowcmOSLT3iWyymq4KUO68/B7a1Bfesw5jxlpwuQh3Zrl+Y1JprIqPws27GHBhiJW7dxHIAH/Z/4gLNpSzKItxQD8c55VLTbRWQUFY5KooLiCt1ftBuC0w3vzh1aSOIacNLo31xw/FIDPdpTy21c+T3JEpi6vLN/But2uMNI1xw8lJ9OuD5rkStT6jpE6ZaXTYfM896E22vpFwMjenVm4cW/tOqfGpDpV5bnF27juyUU88uEmVm4vTUjiGE2oavG9b6y2/yFzEEsejUmi5xdvq/3c872TR7SqxDHkx6ePYuJAt5zHvxds5o2VO5MckYkmGFQe8OY6du+YyRVH21xHk3yBGIldImRvnkvxnCcgGP2D7crtpTw8ZyPXPbmI5xZvQ5sxFmOaU1mVn7dX7eK3r37OrEXbGjUstbEWbSm2/yFzELssbUySqCrPLi4AYHSfzozp2yXJEUWXkebjgUsnMuO+OZRW+nl07kZOG9Mn2WGZCJ9uLWat1+t4tfU6mtaiGT9rClAybyaD2U11z1Hsze7n1n2MYOs+mlTUHENTGyv0P/TZjlKOGdbd5kO2c/abNyZJFm/5go17XGGTCyf1b9VzCvp3zeGCSf15bO4mPtpYROG+Knp2zkp2WCbMq8t3ACAC5x/ZL8nRGNNyfP5KMgtXk33MqW4Iq637aFJQogrfNKeV20tZub3U5kO2c/YOakySPONdCU/zCedMaP0f9s8al89jczcRVJi9cidfs2GRrUYwqLzmJY+TB3ejV+fsJEdkTMuq7jkaSa+7sqqt+2ham9bUu9gQoZ7IDYVlXHvCcLsg087Yb9uYJKisCfDyUvdh/8RRPVOiF+/IgV3p0yWbnaWVvLpshyWPrciSbcVsL6kE4Kwj8pMcjTEtTzPjW0bI1n00LS3auosV1f5W27vYEKH5kNYL2b5Y8mhMEry+cif7vOplF05KjTk4Pp9wxtg+PD5vEws37mVPWRU9OrX+pLc9eHXZgSGrZ4y1+aim/ZHq/XG1s3UfTXNLheGniWRzitsfSx6NSYLQkNW8nAxOTKEhVGcdkc/j87yhqyt2WkXPVkBVeW2Fq4D7JRuyatqpzMJVlA07GV96Zsw5j7buo0mU8N7E3JwMxvbNZXlBcasYfpruA9m1msLPPyK/Ty9A2LFzF317deOu237OrXf8lu27iw7a1/OwyWjvUfibsLLOs4u3kZ2RxvEje9ow1jbOfrvGtLCdJZXMXbcHgHPG9yUrPS3JEcVv0sCu9O6Sxa7SKl5dvsOSx1ZgydZiCoorADcv1Zj2yOevpHTBLPKOuyJmm3Mn9LMPtabRWvX8xKCfii0r6F5ZwH133cYt37iLdR/NY+jkqQCUeF/37pJN9o6ltd/X7gts5e6bn+O6e5+kpueoOgtPxQxB3XJeMz/eYsNY2zh7FzWmhb28bDuhc06qDfHw+YQzx7rexwUbbOhqaxBeZfVMG7Jq2rGSeTPJ7zcA/4gTDhommCYwOr8LuR0yKKvyWwJp4pIKw08rNi2he2UBmYWr2TzvHfpNntrov+9OWel0WvEsG9MHkjf1q5CW0ajj2DDWts/eQY1pYa94H/YHdsvhiP65SY6m4WaMOzB09fWVO7l8ivU+Jouq8upyb8jqoG706mJDVk371mHzXO6+/Wa+d+sdFGX3o8PAcQR8aQeWGJhvSwyY2Fp172KYjDQhfe17bJ51D/28HsREiHft1Hg8t3gb04b3oLedl9ocSx6NaUHbiyv4dEsx4JKwVPzwctSgrvTqnMXufW7oqiWPybN0W0ntkNUZ46zX0RhwPShkdnIfevXgD//WK2JStvrpIUNTf9tsT+XzV5K9Yym7P/oroy/6MTXDpzd4PmRA4eZZSzl/ol2saWsseTSmBYWGGELqzk/z+aS293H++gMFA0zLe2nJdsAbspqif0/GJFpZlZ+KwdNQ1ZgfWF9YUsBpY/rYENY2KmUTxDDhhW/69uqWkKGpjdFh81zuv/3mRs2HDATdxZrPdpRyzLDuTBnS3f7n2gD7DRrTgkLJ44BuHRjbr0uSo2m86aN61g5dXbKtmOkjeyY7pHZnf5WfWYu2AnDM0O42NMgYz8KNe8GXTl0fb2sCykcbizgphapdt0fRksDKmkBthdMV20tSOkE8RD2Fb5KlqfMha4eNz7Nh422BJY/GtJDtxRUsTvEhqyET+ufVfr10qyWPyfD8pwXsq3RrhV45dXBygzGmFSkpr4mrXXF5dTNHYhoqFYrUJFJr6V2MR/h8yKreYygfdjLiS2tQVdbQsPENhWVce8LwVvczmvgk5LcmIp2BXwITgIlAD+AOVb09ot3jwJVRDrFaVUdHtM0AbgW+AeQDG4EHVfWBRMRsTEub7a3FB6k7ZDWka8dMBnfPYdPecpZsLU52OO2OqvLPeZsA6JfXgVMO653cgIxpReIdRp+Xk9nMkZh4pEqRmsaqa93F1tS7GC+fv5IOBYvYsauwzqVx6rJoSzHXPbnIeiFTVKJS/u7ANcBS4AXg23W0rQBOirIt0kPA13BJ6cfA6cB9ItJZVe9qcsTGtLDQkNX+XTswrl/qVVmNNGFAXm3yWNfcIpN489bvZe3uMgC+fswg0nz22hsTMmVIdx5+bw3qS4/5vpSRJkwe0q2FIzMhbT1hjHfdxVTueQstjVM9bDqN6Ry24lWpy5eg42wGuqrqdOBn9bQNquqCiNvS8AYiMgb4Fq738h5VfU9VfwY8DPxCROwdv5ntKavij2+s5vlPt7GvMr4hQCa2nSWVfLL5C8D1OraFRGv8ADd0tWh/Ndu+iHb9xzSXx71ex+wMH1/90oDkBmMaRUQ6icifRWS7iFSKyBIRuSTOx/YSkcdFZI+IlIvIfBE5ubljThWdstLpsHmee5/V6J9qR/buzMKNeymr8rdwdO2bqvLc4m1c9+QiHvlwEyu3l6Zu4hj0U7FpCTmrXuHPX51AzqpXKP7g3+SseoW8ufez+z+/IHvH0pROEOvTYfNc7r14AgQDaIz/tfo8u3gbry7fYf+LKSQhf9Ha2L+Y2M7FDa9+LGL7Y8DVwBnAUwl+TuNRVa57YjEfbSoCIDPdx/EjenLexH7MGNenxROfsio/768uZPKQbvTsnJoL0r+24kCV1RkpPmQ1ZMKAA/MeP91azIBuOUmMpv3YWlTO25/vAuDcCf1s6F3qeg74EvBTYA1wGfC0iPhUNeb5TUSygLeBPOAmYDdwPTBbRE5R1febPfIUkL15LjsKtsYs7mEFPFpWaC7j/PV7Wbm9NNnhNEpd8xN7d8kme8fS2h7F9qR3l2w6bPqQiqHTG1SJNSSo8O8Fm5n58Rb7X0wRybgc0kFEdgI9gR24Ya6/UtWisDZjgUJV3Rnx2GVh+2MSkV7e8cMNa3zI7csLSwpqE0eAan+Qtz7fxVuf7+LY4T343QXj6N81eqIQDCpbisoZ0C0nIUPp9pZVcfnDC1m1cx9dstO5/ewxKfnG8vKyA0NWj+if+kNWAQ7L70JGmlATUJZsKebs8X2THVK78O8FmwldqLdCOalJRGYApwKXqerT3uZ3RWQQcI+I/EdVAzEe/i3cOXCqqs73jvcubtrI74EpzRt9aoh3sXMbOte8VJXnPy3ghSUFqVn4ppVWP21t6rtYEw/7X0wdiRq2Gq+lwI9wcxnPAB7HFcSZKyKdwtp1B4oiH6yq+4Fqb39drgNWRNxebGLs7cK+yhruenUVAD06ZfGPrx/FxUf1J7eDezP4cN0ezvjzHJ5auOWQIQrrdpdxwd/mccIf3uOmmZ82OZai/dW1iSNAaaWfH/53KVf/axG7SyubfPyWsmnPfhZ5Q1a/fETflEt8Y8nOSOPwfLfcyNJtVjSnJewqrWTmR1sAmDKkG4flp+5yL+3ceUAZMCti+2NAX+pOAM/DFZmbH9qgqn7gCWCyiPRLcKwpzeevJLNwNdn9D485hBXcRVMbNpdYZVV+7n1zNbMWbUuZxDHdBxmFq9vd8NOmCl2syZv3ADmrXqFi05JGH+u5xdvYlUKf8VpSWZWfV5bt4P631/L0R1viriydaJLoEaci0gMoJEq11RjtLwCeAX6oqn/ytr0BDFDVw6K0rwIeU9Vr6zhmrJ7HF1esWMGYMWPi/XHanV+//BmPfLgRgD99dTznTXRXf0ora7jrlc+Z+fHW2rZDe3TkrCPyOXNsPnPX7eGeN1ZT7Q/W7n/2u1OZNKhro+Io2l/NZf9YUJs4njiqJ8sLStlTVgVA15wM/vXNKYxLgV68e99YzQPvrAPgrR8ez/BenZMcUeLc9uIK/jl/M1npPlbccToZaS19Par9CASVyx9ewIIN7rraw18/ilMOtyqr0axcuZKxY8cCjFXVlcmOJ5KIzAfSVHVyxPYxuIud31HVv8d47A5gjqpeHLH9LOBl4HRVfaOO5455fjz9V0+Q23dog3+ekCVLl1BSXEJunntfLikuoVPnLow4fCxrP1tB2b5SOnV2FzxCX7fEvmBmJ4Id67vmDH1ys+hqw8CbTFXZU1bNnrLWuxSKVJdTXV5KZkYmCFRXV5OVkcHwoYPYsGpl0v5W29K+nJ4DCHY4ML2loXp0yqRHp8w2c8G9KUL/U3vLqgnP2kSgX24H+uZlN+h1Ktm+gdfvvAIaeY5sDcmjDygFXlHVr3rbngZOVtVeEW074q7W/p+q3trAuMYAKyx5jG31zn3MuH8OgaAyeXA3/vOdow/5Y3x/TSE/fXYZO0qiXxUSgTQR/EHl+JE9+dc3J0dtV5cqf4DzH5pXOy/i/In9uOei8ZRW1HDbSyt5ael2AHI7ZPDkt6cwthVXLg0GleN+/y4FxRWMH5DHi9dPS3ZICfXc4m388L+u3tX/bjg2JZL5VPXHN9dw/9trAbhoUn/uuWh8kiNqvVIgeVwDbFDVMyK25wPbgVtV9f9iPLYaeDTyAqqIHAPM4+ChsNEefztwW7R9+d98kMyegxryoxhjjEkx1YWb2fHo9dDIc2Rr6YMXIBj2/XLgEhHpEzHvcZx3v6LFImsnVJXbXlpBIKik+YQ7zhkT9SrG9JE9ef0Hx/P0wi28snwHy7aV1O4b3D2Hey4az/+Wbudf8zfzwZpCFm/5giMHNqz38bXlO2sTx/O8xDHNJ3TtmMn9l07kqMFd+dWLKympqOHyhxe26gRywYa9FBS7SqQXTmp7Y/jDi+Ys2VZsyWMzmbtuDw+84xLHEb06ccc5dgGsDajrym19V3Wb8tiHOHS47DDgxSP655LbN3HFzMur/fhbQSXNL8qr2VlSVW+7PrlZ7Nm0Juk9Nqm2b81nK6iUbDJye4IkfvRJp6w0sjPS8PlAVAiqkpYmdMxMZ3+1n0BAkYh9XbIzbAmjViJWr1kcD0RVSS8tQDTYav/+W8P/lAgcOSCP9DhHf5VkFbOj/mYxtYbk8UIgB1gQtu1F4DfAlcDdYduvwq0JObulgmsvFm/5onY43NeOHlTnXKou2Rl8Z/owvjN9GFv2lvP6yp0EVLnymMF0yEyjf9cOzPxoK9WBIPe9tZZ/NrD38dnFbsJ015wM7r7giENOAF8/ZjDAQQnkU1dPYUzf1pe4PONN/s5M8/GVI9pGldVwg7t3pEt2OqWVfpZsKeZrR1uvRaLt3lfJTTOXoOqW5njw8iPJyWwNb92mCfYSfe5+KHM7ZM5/gh6Lqu7GVWitFbpQeO/FExI6Mmfl9hJKK5I/j7Csys91Ty6KOe9OVZGgn1+fcxS3fOM21n80j75eQZTQ17/6yUtc/9TPbF/Evh/e9BzXLVtERs9Bdc4pbYg0gdH5XZg6tDuTh3a3uYZtRFmVnzlrCnli4YGib3USQURIq/iCnHVvsX7eO63u77+59n1z7ssEQtVr46AKFx01gEsmD4yr/cqVXXj9zriaRpWw/0gRORPoCIQmdB0uIhd6X7+Km2PxFDATWIe7Ojod+D6wEreGIwCqulJEHgHuEJEA8DFwGnAN8IuIyqwmAZ5ZVABAmk+4/sThcT9uYPccrj7+4Dky+bkd+OqXBvDvBZt5f00hS7YWH9RDVZftxRV8uG4PAOdM6EdmevSrKJEJ5A1Pfcrs7x9HVnpa3LE3t7IqP6+tcB3npx7eu00uqeDzCeMH5DFn7R6WbP0i2eG0SX97b0PtXN87zxnLyN5tZ85sO7YcuFRE0r1iNyHxjK5ZHtYunI3MiaFTVjrnTuhXW8nxIKqICBlFG4BjWjy2VFYxaBrffeIT/D1Hug1NmJtmCWPb1ykrnTPH5VNRE4j+vxhDdf4RVPc6jFx6of4tzRhh67CrtJKKwce6i1oN+J8q3Ff/6IpESeT4gr/ihsI86n1/kff9LKAXbl7jLuCHwLO43sULgPuBaV4l1XDXAb8DbgTewPVQ3qSqdyUwZgNU1gR42ZtHeOKonglZS/G7JwwjI8390d/31pq4H/f8pwW1F1rqG+b59WMG86PT3Elr4579PDxnY+OCbSavLt9BRY2rtn/BpLZbADF0YWB94X5KK5NT+autUlXe/NxdgJg8uBsXtcGhz+3U80An3Dkw3JW4OY8L63nsaBGprcgqIunAFcBCVd2e4FjbhPMm9uOiSf1rz0u1vA9nNT1Hcd2Ti6gY1LbmpTeX3KmXUDF0Ov5g/W3rMqZvF64+bih/+9pR/OKswznpsN6WOLZxof/FyH/FOvnSyTvuCirb+P9nxaBp3PzfJeBLa3ChoJZcBz1hyaOqDlZViXHbpKpfqOr5qjpEVXNUNUtVR6rqLapaEuV4Nap6u6oO8tqOUtUHEhWvOeD1lTvZ55UovyBBa+v0zevAxUcNAODd1YWs3H7Ir/gQqsqz3tWoUb07M6Zv/csQfGf6MEb2dqu8/OWddbXzC1uD0M/So1MWx4+ILG7YdoT3Ki/bWv/v2cRv3e4ytha5v+nTxvS2qnNthKq+BrwJ/FVErhaRE0Xk77glrH4SWuNRRB4REb+3/mPIo7jROrNE5DIROQX4LzAKuKVlf5LUISKcf2R/Hrp8Uswq4DUBpWLodHKnXtLC0aWOYHo2Ff2OInfapU0appqRJlw0qT8/n3EYJ43uZQljOxL6X7z34gnxz0sVQVWpGDytzS7jEbog05hVbbLSfZw5tuWmRtR4CCsAACAASURBVFldfcOzi92Q1bycDE46rFc9reN37fRhtV+/+dmuetsv3lLMhj2uA/rCSf3j+qCckebjznPGAlBRE+C3r3zWyGgTR1V5cUkBCze60dXnH9kv7knMqWh8eNEcG7qaUG99fmBq2smH2bIcbcz5wL+BO3Hz+KcAl6rqk2Ft0rxb7ZuhqlYBJwPvAg8A/wPygTNV9f2WCT21LatrXVpVuhx9EcH07JYLKAUo7sNt8dQbqRh5GuJLa/Qw1UmDuvLQ5ZM4/8j4zvOmberdJZvzJ8Y/KktEwJfOzbOWtqkRAom4IHP9icPJzclIcGSxtd1PtCYuO0sq+XBtIQDnjO+b0DmDA7rl1PYKzlm7p972oUI5aT7hnIl9436eo4d25+zxrv2ry3fyYRzP1VwK91Vx7ROLuGmmWyA33SdcfFTbHmrYo1MWA7vlANQmzCYx3lnlLroM7dGRIT06Jjkak0iqWqaqN6lqvje6Zryqzoxoc1Vo9E7E9l2qeqWqdlfVDqp6jKq+1aI/QIpauHFv3QvWi+DLyKK656iWC6qVK6vyUzb2QvKOuwJ8je8hDPU23nzqSOtpNEAdw8nrEAi2jRECibggk5Xu44enjuTGk+KvVZII9t/bzj336bbaqlcXNMN8quNG9GTNrjKWbC2mtLKGLtnRr4xU1gT4nzfvcvrInvTq3LCrvj8/6zDe/nwX+6sD/OqlFcy+6fiYxXaay7urdvPD/y7hi3I37697x0x+d8ERDO/V9gucTBvegy0fbWHhxiIqawJkZ7SewkWp6ov91Sza7HpyTxqduBEBxrRnJeXxzcvWzE7NHElqSERRnDF9uzB1WA8mD+lmSaM5SGgI62lj+vCveZuYsy7Oi/+qdJl6CRUb3iVr5/LmDbKZVA6aRl4DKqqGmzrMdZqcOTa/RXscQ6znsR0Ln2M4sncnxjXDWonHjugBuCtF89fvjdnuzc92sa+y8fMue3fJ5nsnjwBgQ+F+Zi3a2ohoG+/Nz3Zxzb8/qU0czzoinzd+cDynHt4+hhoe7/2eq/1BPt5kvY+J8N6a3bUXdmzIqjGJEe8HLakua+ZIWr+mFsWxeY0mXp2y0vn61MHx90CK4EtLp2LEqRRPvZHcqZc0bA3JJAuvqNqQCzJpPuGqqYN58ttTuGTywKQkjmDJY7u2ZGsx6wvdHMMLmmnuwZQh3cj05vvVNZw0tB5ibocMTm7kvMtvTBtCv7wOADz07nqqm1oGLk5vfbardg2xzDQf910ygQcvO5LunVqu8lWyTR3Wg9C893iGKJv6heY7ds5O56jB0Qt8GGMaZsqQ7nV/QFUlWFNFZuHqlguqlUnEHCyb12gaKrSkToOlWCXWxlZUTRO496LxXHH0oKT/T1ny2I69uMQNE/WJG3feHHIy02sr283x5lZG2lVaWbvvK+PzGz3kMTPdxw3euO+C4orahLQ5vfXZLr4bljj+v69P4pzGvPmluNycDI7o7wrnWPLYdDWBIB/8f/buPD6q8l78+Oc7M1lIyEJCAgk7hEUBAVFQcAG3urVal9pa69LW3lZr9+W2va22t+2vy+2itra3tS5dtL1Yt9atVcENBUVBQJAd2RMSSAhZZ+b5/fGcM5kMk2SyzJKZ7/v1mtck55w58+QkmXO+5/k+3+dd+z+xaGo5WWlccEmpROrxAlWE1j0baSublnFFcwZiDJaOa1T90adpPNxKrOMW0Njq73n7JAj6cmmpmE35VT/oc0XVy04czYjC1PhM0v/sDPaKk1s+b0IJ5XH8gzx9ynBe3VbLjtomdtU1McYpruJ65K09ofS8K+aO6dd7XX7i6NCUHb9euoUr5o6O29jHd/Y2cNNf3uwIHD82l8VTM3ds2umTh7N612E27Gug5khrQuccSjevb68LTZ9zto53VGpAuTdLH129J2rxnCHjZ9HELJomn5sxE5ND/8ZgeQSuOWUcp08u06BR9Zk7BnJh1XC+vGQNgWBsf4siAt4sXtoUvZMiWTpuyFwF3iyG9GEfWV7h0tmj4tbJ0xd6OztDHWxsZXO1HdNx6sThcX2v06s65jiM7JUyxoR6CKvKhzJrdP/GXWb7PNy8uKP38eE349P7GAwavv3YOtoCQXwe4bcfO5HFGX6Rf3rYXJavxDroXUX13EabsuoRW0BKKTVwwud8vPH0iV3PKTzI0uH6o69jsFyXnziaC2ZUaOCoBkRvp/Fw/XnFzpSZxqO/VYo9AteeOi4l0781eMxQK7Z1FDU5ZWJJXN9remUhw5xBvS9v6XxX6O3d9WxxgtiBGnd5xdzRobGPv1q6hfbAwI99fPitPaFKmDcsHM9Z07SgyZyxxeRn25TjF7tIUVY9M8bw3AY7RcdJ40oYlp+d5BYplZ6G5viYN6GETQeORN9gEKTDDYS+jsGCjjTVVOoVUemhL9N4BA0pMY2HW6W4vR9VilP5howGjxnqtW228mm2z9Npkvd48HiE05xeqVe21HZKQ3B7HQdy3GW2z8NNiycBsPtQM0veGNjex/rmdn701AYAygty+Pw5UwZ0/4NVltfDqZNKAVscyfSx0EKm21vfwo7aJoCM781WKt56mvfRTYdbmaZz2LoVVfsyBkuL4qh4Cs8QuPaUcaGifD1yp/EYfXJSxi33t0qx15P6N2Q0eMxQK7bb4PHEscUJmZPv9CqbGlvf3M7aPfUAtPoDPO7M7Xj65DJGFg3cP/mVc8dQ6ezvu/9Y322l1976xb83cbCxDbDzS6biXaFkOc35PVcfaWXTAS113xdrdh0OfX2yVllVKq5inffxcFNbnFuSWP2pqKpFcVQiDc3xccHMitincUvSNB4DUaXYraia6jdk9L8+Ax1s7LiwP2ViaULe053vEWDZu9XMHlPMcxuqqW+2J+7L5/Z+bsfuZPs8fP+DM/jUH1fR6g/yiftf5w/XndypHX2xYV8Df3x1B2CnIfnArMr+NzaNnD4lfHxrDVNHFiSxNYPTaid49HqE6ZUDP/eqUqpDrPOkFeelR/p4ZAGP3lyealEclUxuT9zf39xNjHV0QuOWG2vejUvqeWOrn+aK2ZRfdRGHx86wqd/92F8qVVTtjvY8ZqDw9Jv5ExITPFYWD2FSWT4Av3x2Mx/41cv88tlNgJ3H7rzjB37M4FnTRnDnR+bg9UgogPzHmr2s3V3P2t31bD5whGDMn0DW9594h6CxF/bfu2RGSt8ZSoaJw/ND4011yo6+Wf2eDR6njSxgSHb8swKUihfp12VUYvQ076MxBoL+rovqDDIt4xb2uYBHKo/BUunPTWP96PxxvXkRAO1lU7npL6sGtJhO87iFdp/TLmTI+Fng6fv5erCNHdZPgAwUPt5xztj4jncM95F5Y/n+E3as4Nu760PL3z+rMm6psxfMrOBXwGcffItWf5BbHnyr0/o5Y4v5nytnMalsaI/7en1HHa9sscfumvljtVctChHhtKrh/O2NXazYXktLeyAhadHpwh8IhtK6Z8d5LLJS8TY0xxfKLklV7ryPS7qYF1hEQHx89aE1+MYthJXLE9zCgRNeUbVXk5N7hMvmpNZUASpznTGljL++/l63Y5WjaQ8Y2ieeSflVxbS07CG7ZmOv3zvoy6WtbBrlV11E8/hZ9GmwcJjplYUsmDSceRNKBtVNmcHTUjVg3Eqrc8YkZryj65OnT+S0ycN54u19PPH2PrYdPEq2z8M1vbmL1AcXzKzgTuBzD76FP6Kn8a33DnPh7S/x1fdN5YaFE/B2MyL79mc3A5ATNh2IOtYZU8r42xu7aGkPsmJ7nU410QubDjTS3B4AiHshK6XirSgviz2Hm5PdjB71NO8jdFx4Fi3YBYNw3sdOFVV78Tp3DNZgSKVTmaGnGz496e08rtFSU/syX2O48LkbB2MGmwaPGaa2sZV3nbLk8xM03jHctJGFTBtZyJfOncLWmkayvV7GlubF/X0vnFnBnLHFrN/TEFq2fGst9y7fTqs/yPef2MC/1h/gd9fOjTq25Y0ddbzszF149fyxlOuJtEunTxmOzyP4g3bKCQ0eY7dmd0exnDkaPKpBrjDXh9cjMU/0nSydJib/vzUEuip2YQyFp1xJ8LVf4/G3JLaR/eBWf+xL1ZDBMgZLZZZYbvj0KGw85IGGFloqZlO0YCzNI8pBhCLfWI5Mm8dNf1lF+7QL+x0wuuaOG8anz5w0qHoaIw3elqs+CR/vGO/5HbsjIlSVJzbts6JoCBVFHf/+5xw/ggtmjuSrS9awo7aJlTvquOYPK/jzJ+YfE0De/pztdcz2efj0mZMS2u7BpjA3i3kTSli+tZbnNlTz3Q/0LkUqk7njHYfm+GJKpVYqlYkIhUN8HDqa2qmrrnV767sOHMFWcczKoa1sKrn71iSuYX0U9OXSOmIGRVVn2+qPvfgcDu8ZUSrVuDd8zps+kpc21fDnFTtjL6LTsRPAjof8wt9Ww7QLKZ4Gbq5E8WRoh36nproGe29jOC2Yk2FC4x29Hk4cq9MAnDy+hKc+fwYXnVABwLo9DXzsDys7lW9ftbMuVPzl6nlj9S5sDM4+zhZA2nO4OdTTrXrmVlo9YXQRnpgntVIqdRUPGTxVSmOdtqO9tCop88fFqqOi6i00TzkP8XhjDhw9AteeOk7nb1SDQq+n8UiCdPyf0p7HDLPC6XmcneDxjqlsSLaX26+ajQD/fHsfa/fU87F7VvDxhRMQgT+9uhOwvY6fWaS9jrE4e1o5//3PdwB4bkM100amR6XCeGps9bOp2gbaWixHpYviGKfCSAWxTtvRXjaVwyUTYxovlWiNrX4aZ1xBcdmUPs0151ZUVWowcXvIH3lrN/5gkhsTIR3/p7TnMYMcOtrGxv324jSZKaupyOf18MurZod6IN/eXc8X/raaz/91NW/sPARor2NvjB+eH5qa5bkNB5LcmsFh7e760LWeBo8qXeRmecnNGhyXGj1N29GJM16qZQBL//dX87iFfObPb9BeNsUu6GVF1cE0VYBS4dw01t9ccxJzx6VGVt1gm36jN7TnMYO4KXEAJ43X4DGSz+vh9qtmk+P18PBbezqtGz40W3sde+ns40awtWYbb+06TG1jK6VDc5LdpJQWXixHg0eVToqGZNHS3prsZvSoV1UcRTDG0DxuQVwmH++tUFGcPvS6aEVVlS6G5vj48rlTeOStPf0rptNHXoFpFYUsmFjKvImlg7ooTnfS86dSUb0VFjzqNADR+bwefn7VbL52/jSa2jouCCqLh2iaby+dPa2c3724DWNg6bs1XDE3dcckpAK3WE5lUa5W81VppTgvmwMNqR88Qu+qOIoIeLM6FaJLtP4UxXFpRVWVTsKL6azcXsfyrQdZv7eh5xf2w2Cdr7Gv0v8nVCFrnOBxYlk+RUMGzziUZBhZpCfS/po7bhhFQ7Kob27n+Y0HNHjsgZsZMHus3thR6aUw14dIn4bgJVz4hedvX9jKKmfYQneqGxI/bUdHUZyrwJvVq7kbXVpRVaWzoTk+zppWzuKpZTzy1p64jIdMpwqqvaHBY4YwxoTS4jQlTiWCz+th0dQyHlu9lxc3HaTNHyTbNzjGPiXa/voW9jsXoLNG6/+nSi8+r4ehOT6OtCQ/vTNWQ3N8zBlbHFPw+M+1+8getxBWLk9Ay6yWcQspnnhmnyJyj8A1p4zj9MllGdFLojJbX24IdSdTUlO7k3k/cYbaUdvEYacMuQaPKlHOmlbOY6v30tjqZ+X2Ok6bPDzZTUpJ4eOR9f9TpaPivKxBFTyCLaBz//IdPaavBoKG5olnUrRgFySg+uqBhhaax5+GMX2bQzcdqz8q1ZO+jof0eWDWmGFMHJ5PcV52xqSmdiezf/oMskYvTlUSLJpSjtcjBIKGf7+zX4PHLrz1nr0T6hGYObooya1RauCV5Gezq6655w1TSK8K6BhD4SlXEnzt13j88UtjbR63kC//32rweHudqqppqirTRY6HPNzURnFeNtMrC1m/t4HDTW0MyfKCQHNbQIPFLujRyBBuz0a2z6Nz7qmEKcrLYv6EEpZvreXp9fu59f3T8XgyZ1xArF7echCAmaOKyMvWj2WVfvKyfaEx0IOJG2g9/OZuuu2oEMGTlUNT1TnkbXk2Lm0JVVTtw9jRueOG8ekzJ+lFsFJ0jIcMp0WjYqefIhnCrbQ6vbJQx52phLpwZgXLt9ZyoKGVVe8d4mSdJqaT2sbWUCW40yeXJbk1SsVPZXHuoAse3Z6KtkCQx1bv7XH7tooTaCs/jiLKMQOUwtqfiqqZWtBDKRU/GjxmgFZ/gA3OxammrKpEO3/GSL7z2DqCBp54e58GjxHcXkdA03pVWivOyyYv20tTWyDZTem1soJezFPr8VF8+jW0bHuhz+/X2OqnuWI25VddxOGxM3qdpqpFcZRS8aJdUBlgw74jtAVsfWINHlWiDR+aw/wJpQA8tW4fweAgqNefQC9vtsFjXraXE8cOS3JrlIqvikE6DdL8CaVkeWMM30QwxtA8fiEH+jCNR/O4hdz0l1U0T7uQIeNngaf3cwy7RXE0cFRKDTQNHjPA6vc6yhJr8KiS4cITbGW/Aw2tvPle/8pkpxNjDC85weMpE0s1pVylveFDc8j2Db70Sbd4TqxEBDw+vrxkDc3jFva4fdCXS0vFbMqv+gHNE8+MuRJkJK9HuHLuaC2Ko5SKG70llQHW7K4HbLW7sSV5SW6NykTnTx/JrW7q6tp9nKSpqwBsqW4Mze94uqasqgzg8QjlBbnsPjS4Kq9CR/Gc3pT5d6fxKL+qmOa2AyBCkW8sLWUldsqNiNTUIf1on1fgZ1fO0sIfSqm40uAxA7iVVmeNLtIB8yopygpymDehhNe21fHU2v18+6LjteoqhHodQYNHlTlGFOay93Azgy2DPbzM/x+X7+ClsPHKPRkyfhZuuFw8GZqAL/xtNUy7sF8BY7jLThytgaNSKu40RyrNHW5qY/vBowDM0pRVlUQXzbSpq/sbWnhrl6auAry0uQaw48AmlQ1NcmuUSoxsn4eRg3TsI9gU1msXjI99DGScZXk1VVUplTgaPKY5N2UVdLyjSq73zRgZqjD/xNv7k9uYFNDqD/DatjrA9jpqVoDKJKOH5ZGTNXgvQXo7BjIePALXnjqOuz46l8tOHK2fIUqphBi8n9wqJqvfOxz6WoNHlUzlBbnMc8Y6atVVeHPnYZrb7ZQFp+n8jirDeD3ChNL8ZDejXz44ZxRXzh1NsjogtaKqUioZNHhMc89uOADAxLJ8ivOyk9walekudqqu7qtvYeWOuiS3Jrle3mJTVkXgtCod75hpRGSoiPxSRPaKSIuIrBaRD8f42utFxHTxGBnvtg+UYfnZlA4dvOcldwzkzz40G28Cx3BrmqpSKpn0dlUae3f/EdbusWmr7z+hMsmtUQouPqGS7/3zHdoDhodW7eaUiaXJblLSuMVyplcWUpI/eC+gVZ89DJwM/CewCbgaeFBEPMaYB2Lcxw3AxohltQPXxPgbX5pPfXM7/j5OTZEKRhTmctmcUSxZtTtu7+EVmFZRyIKJpcybWKq9jUqppNFPnzT29zc7TmSXnzg6iS1RyhqWn83Z00bw9Pr9PLl2H9/9wHTyM/AiqPpIS+jGzmlVmrKaaUTkQuBc4GpjzIPO4qUiMg74qYj8zRgTiGFX64wxb8StoQmQ7fMwriSPrTVHk92UfunLNB6xmF5ZyIJJw5k3oUQDRqVUStC01TTlDwR5+M09AMybUMLYUp3fUaWGy+faGxlNbQGeXpeZhXOeWX8A41xfnnt8eXIbo5Lhg0AjsCRi+b1AJTA/4S1KovLCXEYU5iS7Gf3iprDe9dG53Hj6RKZXFvZrf25q6rcuPI6zppVr4KiUShn6aZSmXtp8kIONrQBcMVd7HVXqWDS1jNL8bGqPtvHQqt2hYDKTPPn2PgBGFuYyZ8ywJLdGJcEMYIMxxh+x/O2w9ctj2M8/RaQMqAeWAd8xxqzr7gUiUg5EdndPiuG94mrC8Hxa/UEON7Unuyn9MjTHx1nTylk8tYxH3trTq55ITU1VSg0G+smUph5yxl4MyfJyoTO/nlKpIMvr4ZLZo7jnle28uq2W3YeaGD0sc3rGDza2smK7HZZ2wcyReBJYaEOljFJgW5TldWHru7Mf+AHwGtAAzMSOnXxNRBYaY9Z089qbgFt719z4ExGmjChg/d56jrbGkrGb2tyeyPOmj2Tl9joON7UxJMsLAs1tAYrzspleWcj6vQ0cbmqjOC9bU1OVUoOCfkqlofqmdv79jq2yesGMkXoyUinnirmjueeV7QA8/OYePnf25CS3KHGeXrcfd5aSi/TGzqAnIouApTFuPscYs9r5urvuqG67qowxTwNPhy16UUSeANYC3wMu6ebld3Fsuuwk4LHu3jMRvB5h6sgC1u1poM0fTHZzBoTbE9mVEYW5CWyNUkr1n0YVaejxt/fSFrAn3kxMCVSp7/jKQo6rKGTDvgb+/uZubjmrKmMmuH5ybUfK6oljNWU1DbwL3Bjjtu85z7VE710scZ57PY+NMWaHiLwMnNLDdtVAdfiyVPrfy/F5mTGqkE37G2lsjczqVUoplWwaPKahvzspq5VFuZyawVMhqNR2xdzR/Pc/32FnbROvbqtlwaT0n+vwYGMrr22zKavnz9CU1XRgjNkH3N3Ll60FPiIivohxjzOd527HLXZDgEHfZZfj8zK9spCtNY0cbGxLdnOUUkqFGZBqqyJSICI/EZF/iUiNM1HxbV1se6KIPCsijSJyWEQeFpGJXWx7i4hsFJFWEdkuIreKSNZAtDldvbq1ltW7DgO211EvTlWqumR2JT7n7/MT973B/ct3EAwO3rneYvHM+rCU1RM0ZTWDPQIMBS6PWH4dsBdY0dsdisgEYCF2HOSg5/EIk0cUMKZkCCnUMaqUUhlvoKbqKAU+BeQAj3a1kYhMw1aEywY+BHwcmAK85FSMC9/2W8Dt2ImU34cdp/FN4NcD1Oa00x4I8p3H7A3rIVlerp4/NsktUqprw4fm8MVzpwDQ3B7g1sfXc/Xdr7GrrinJLYsfN2V1RGEOczVlNWMZY54C/g38RkRuFJHFIvI74Hzga+FzPIrIH0TE78wB6S57VkS+IyKXishZIvJ54GXsWMlvJ/jHiavRw/KYNbqYoiF631gppVLBQAWPO4FhxpgzgW90s933gFbgYmPMk8aYh4GLsGXDv+JuJCKlwH8BvzfGfNMYs8wY81Pgu8AnReT4AWp3Wrl/+Q42VzcCcMvZVVQUDUlyi5Tq3s2Lq3jgk/MZVWz/Vl/bVsfFd77Muj31SW7ZwKttbOXVrU6V1RkVmhWgLgP+hD0vPo2d2/Ejxpi/RGzndR7hfzBrgauAPwLPAF8DngdO6mmqjsFoSLaX4ysLmTJiKEOyvclujlJKZbQBCR6No7ttRMQHXAz83RjTEPbandhKdR8M2/x8IBc7YXK4e7En0EsHot3ppLqhhV8+uxmAicPz+eRpUTOBlUo5C6qG88wXz+CjTk95fXM71/xhBev3plcA+XRYyuoFM0YmtzEq6YwxjcaYzxtjKowxOcaYWcaYv0bZ7npjjBhjdoQt+6IxZroxptAYk2WMGWWM+ZgxZlNCf4gEKx2aw+wxxRxfWUhZQTZ6/0UppRJvoHoeYzEJGELHJMjh3gaqRMStWT3DeV4bvpFTmOBg2PqoRKRcRKaHP0iBSZDj6YdPbghVprvtA9PJ9iXyV6tU/wzN8fGDD87ktvfbpILDTe189O70CSCNMTywwhbaHFGYw0njS3p4hVKqK0VDsqgqL2DuuGFMG1lAZXEuBbk+DSaVUioBEllt1S37Ga0EeR22R3EYsM/ZttUYc7SLbXsqIZqSkyDHy8rtdTy6ei8A508fyRlTynp4hVKp6fqFEzDAd//xDoeb2vnw716jqnwoYD8gzppWzs2LB9+0Hqt2HmL9Xptw8dH54/DqVa5S/ebzehiWn82w/GzA3qRpCwRpaQ/S6g/gDxgCQfsIGoMBbI6UIVqulLve3T4QNPiDhvZAMOr2SimViZIxVUesEyP3eQJlUngS5Hj4zbItAORmefj2+3U4qBrcblg4AWPge/98hyMtft5673Bo3ZvvHaa8IJcPnTwmiS3svXuX7wAg2+vhI/O0kJVS8SAi5Pi85Pi8wMAW2GkPBGnzB2lpD9DcHqClPUhzW4CmNj9pXiRaKaU6SWTwWOs8dzUxsgEOh22bKyJ5xpjI0oslwKru3ijVJ0EeSNUNLbywqQaAy08cHSo8otRg9vHTJlBWkMMjb+2hPWCnrVu7p57DTe185/F1zB5bzJQRBUluZWz217fw9Lr9AFx8QgVlBTlJbpFSqreyvB6yvB7yczpfNgWDhqb2AI0tfo60tNPQ0k6bX6NJpVT6SmTwuBVopmMS5HAzgS3GmBbn+7Vhy0PzXYnISGA4fZ9AOe08unpP6K7nFXNHJ7cxSg2g98+q5P2zKkPfL99ykI/+YQUt7UFu+subPP7ZheRlJyN5onf+smInAeef9LoF45PbGKXUgPJ4hKE5Pobm+BhZZMs2NLX5qW9u59DRdo60tGvPpFIqrSSsqooxxg/8A7hMREJdBiIyFliMnc/R9TTQAlwfsZvrsT2UXc4lmUmMMTy0ajcAk8rymT2mOMktUip+FlQN53NnTQZgS3Uj33lsfZJb1LNWfyBUKGf2mGJm6f+oUmkvL9tHRdEQjq8s5KTxJUwdWUBZQQ5Z3vTMgFJKZZYBu20vIhcA+YAbGB4vIlc4Xz/ppJ/eCrwO/FNEfoSdjuN72AqqP3P3ZYypE5HvA/8tInXAv4CTgduAu40x7wxUuwezdXsa2HTAzut4+dzRaZuaq5Trc2dPZuX2Ol7dVstDq3azeGo5F51Qkexmdemfa/ZRe7QNgOu111GpjOP1CCX52ZTkZ2OMoaHFz6GjbdQ1tdHaHkx285RSqtcGsufxN9giNfc4bRwKhQAAIABJREFU31/pfL8EKAcwxmwEFgHtwEPAfcAW4AxjTE34zowxPwC+AFyBDR5vAX4E3DyAbR7UHlq1CwCPwGVzNGVVpT+vR7j9w7Mpcaor3rVsCz1MMZs0rf4Af3h5OwBlBTlcODN1g1ylVPyJCEVDshg/PJ8Txw7jhNFFjB42hPwcb7KbppRSMRuwnkdjzPgYt1sFnBPjtncAd/SjWWmr1R/gsTV2eo6FVcNDYy2USnflhblcd+p4fvHsJtbvbWDVzkMpN29iqz/AZ/78Ju/sc6fnGKtzryqlOsnP8ZGf42NMSR6t/gCHjrZzqKmNhmYdJ6mUSl16NTNILd1YzeGmdkAL5ajM85H5Y0Ljh+5zpsFIFa3+ADf9+U2e32gLPp88fhifOmNiklullEplOT4vI4tyOa6ikJPHl3BcRQGVxbnaK6mUSjmpX6pQRfXQqj0AFOT4eN/0kUlujVKJVV6Qy8UnVPLIW3t4et1+9te3JK33fdOBI7y2rTY0ifjzG6tD0+ecNG4Y994wb1BUhVVKpQaPRyjOy6Y4z6bntweC1De309DczpEWP01tgSS3UCmVyfSKZpBpavPz46c28uyGAwBcPKuC3Cy9M6kyz3ULxvPIW3vwBw1/WbGTL583NaHv3+oPcMdzm/ntC9tCU3GEO2ncMO77+DyG5ujHrFKq77K8HoYPzWH4UDtHrD8QpLHVz5EWP0fb/BxtDdDm1+I7SqnE0KuaQeS1bbV87aG3ea+uCYC8bC+fOG1CklulVHK4U1+s2XWYB1e+x2fPqiLH17sbKS3tAbK9Hjye3lUqXru7nq8sWcO7B45EXb9oahm/uvpEDRyVUgPO5/V06pkE2zvZ1BaguS1Ac7t9bvHboDJFa4oppQYpvbLpBWMMG/cf4biKwoS95/76Fp5cu48n1+7jjZ2HQsvnjS/hp1eewLjS/IS1RalUc8OC8Xzhb6s52NjGE2/v47ITYxv/2x4I8uulW7hr2VaKh2Rx4cwKLjqhgrljh/UYSD60ajdf//vbod7G6ZWF/L/LZjJ6WB4AXhGK8rL694MppVQvZHk9FA3xUDSk82ePMYZWf5BWf5A2f5C2QJB2fxB/MEib3+APBmkPGAJBEzWDQimlImnwGKPDTW18ZckaXtx8kEdvWsjxlfENIJvbAnx5yWqeXLu/0/LcLA9fe980rl8wvte9JUqlmwtnVvD9JzZwsLGVe17ZzqWzR/X4f7FhXwNfWbKG9XttJdTqI63ct3wH9y3fwajiIfzyw7M5uYvqrQ+t2s1XH1qDMeDzCJ87ezKfWTSJLK/WHlNKpR4RITfLG9PwlmDQEDAdgWTQGIJB7LMxBA0YDMZgH87XAG7YGT51Urx6PCP3azj2jaK9t+m03nSxvPNS+3N2XtflMQg/Ps57hJ4N9viFlsX0oyqVkjR4jNGmA408v7GaoIHPPvAmj99yWtxS0prbAnzi/tdZvrU2tGz0sCFcdEIFV88bq72NSjmyfR4+On8stz+3mXV7GvjNC1u5eXFVl9vf/dI2fvz0RtoD9sw9dUQBZQU5LN96kKCBPYebue6eldz/8XnHBJB/Dwsc87O93P/xeSk3RYhSSvWVxyN4ELSMQvwZNxh3noNONBkM+z4YPPbrQOjrjgA/ECQU8NvgP4g/YHS6FxU3GjzGaN6EEr54zhR+9u9NbDt4lP96ZC2/uGo2IgPb+9fcFuCTf+wIHE+dWMp/XjCNE0YXDfh7KZUOPnn6BB5bvYcdtU38/N+bmDehJGrP4e3PbuYXz24CwOsRPnPmJG45246TPNjYypI3dvOTZzbS1BbgeieAPGl8CXVH21jyxi5+9PRGDRyVUkr1m4hgZ5uK33VdMGjwO0GlPxh0ng3+QNffB0LbG+0dVV3S4LEXblpcxYrtdby85SCPrt7LqZNKuerksQSChlU7D7EprHiGR4QZowqZOapz0Fd9pIVXt9Zy4thhjCnJ67T/5rYAN/7xDV7ZYgPHhVWl3H3tyQzJ1tuASnWlIDeLX119IpfdtZy2QJBbHniLJz9/OiX5HcUk7niuI3AsL8jh99eexKwxxaH1w4fm8JlFkygvyOErD63haFuA6+5ZyZyxw3h1W21oLFBetpf7NHBUSimV4jweITs0jKP315Fu8On2cgaMwQSd3k/nYZye0fBnODbFN1xvYtLI9GL7bUdqcPh7B8PbpgFwXGnw2Atej/CLq2Zz4R0vUXOkle88tp41u+t59p0DVB9pjfqaMSVDuHBmBRWFuTy9fj8rttdhDOT4PHz1fVO5YeEEvB5h1c46vrrkbbYdPArAgkkaOCoVqxmjivj2xcfx7cfWs7+hhS/+bTWfPcumr764qYY7n98C2MDxr586hYllQ6Pu5/K5ozHAV50A8uUtB0PrKotyuf0jc7ocD6mUUkqli87B5+AU3uvqFoZqDwSdh/26zd/xvRaNio0Gj71UVpDD7R+ezTV3r6DVH+SBFe91u/2uumb+94Vtxyxv9Qf5/hMbeHrdfmaOLuK+5TtCd0hOqxrO7689SQNHpXrhmlPG8dq2Op5Yu48XNtXwwqaaTuvLC3J4sJvA0XXFXFux9ZuPrKVoSBYXzhjJRSdUctK4niuxKqWUUio1eD2C1xP7tbQbXLpVid0As9WpUNzuN7QFgvgDwYweU6rBYx8smDScL583lZ8+8y5ej3DqxFIuOqGC0ycPJ9tnqy42tQZY+m41T7zdMcVGRVEuF8yo4ITRRfzi2U3srG3ijZ2HQuuzfR6+fO4UPnn6RLx6kapUr4gI/+/ymWzY1xDqwXeVF+TwwI2nMKmHwNF1xdzRXHxCRZ/mgFRKKaXU4OMGm7FUJ/YHgvidYNMfMLS740gDHWNN3Z7P8JRa4xQ5Ck/zHWw0eOyjmxdXce7xIyjNz6Z0aM6xGxTADcMncMPCCRxoaOFwUzuTy4eGLkTPmz6Cnzz9Lvct3wHArDHF/OzKE6gqL0jgT6FUeinMzeLRzy5k3e760F1Bj8CcscN63ZMfy8lDKaWUUpnH5/Xg8/bvWsGEj9k0x44Rdad/CZcKnUsaPPbDlBGxBXojCnMZUZjbaVleto/bPjCdK+aOZlddE+cePwKfzhWnVL8V5maxoGp4spuhlFJKKdUlEUEEPHGsuhsPGjwm2YxRRcwYVZTsZiillFJKKaVUt7SrSymllFJKKaVUjzR4VEoppZRSSinVIw0elVJKKaWUUkr1SINHpZRSSimllFI90uBRKaWUUkoppVSPMqnaajbAli1bkt0OpZRScRT2OZ+dzHYMInp+VEqpDNHfc6QYY3reKg2IyAeAx5LdDqWUUglziTHm8WQ3ItXp+VEppTJSn86RmRQ8FgFnAruAtj7uZhL2BHsJsHWAmpYO9LhEp8clOj0u0elxia4vxyUbGAO8YIypj1fD0sUAnR9B/4a7osclOj0ux9JjEp0el+j6elz6dY7MmLRV5+D06w60iLhfbjXGrO93o9KEHpfo9LhEp8clOj0u0fXjuLwVh+akpYE4P4L+DXdFj0t0elyOpcckOj0u0fXzuPT5HKkFc5RSSimllFJK9UiDR6WUUkoppZRSPdLgUSmllFJKKaVUjzR47J0a4LvOs+qgxyU6PS7R6XGJTo9LdHpcBg/9XUWnxyU6PS7H0mMSnR6X6JJyXDKm2qpSSimllFJKqb7TnkellFJKKaWUUj3S4FEppZRSSimlVI80eFRKKaWUUkop1SMNHpVSSimllFJK9UiDR6WUUkoppZRSPdLgUak+EpHrRcSIyPXJbktfdNd+ETlPRJaLyCFnm0fD1p0kIv8WkYPOutUJbXgSicgyEdES1UoppbokIouc8+NtcX6f25z3WRTP91EqnAaPKmYicoWI3CkiL4lIg/OB9ecB2rcRkWX9eP0wEfmOiKx0Ap5WEdklIv8nIucORBtTkYjc5xw79xEQkXoR2Soij4rIZ0WktJf7HA88BkwA7sXOIfRXZ10h8AQwz1n2XeC3A/cTKaWUGigi8q2w88PUAdyv3khLgMF+k1qlJ1+yG6AGlf8CZgGNwG5gWnKbY4nIGcDfgeHABuAvwBFgMnARcKUT5H7SGNOatIbG12OA2wNYAIwBTgcuAX4gIp83xtwX8ZpHgNeAfRHLzwFygS8bYx6IWDcPKAe+ZYz54cA1f9C4FshLdiOUUqonIiLAJwADCHAj8JWkNkoNtF9hb+S+l+yGqMyhwaPqjS9ig8YtwJnA0uQ2B0TkeOBJYAjwOeBXxhgTtn4M8ChwDdCGPZGmo0cjg0MR8QEfB24H7hWRVmPMg+56Y0w9UB9lX5XO895erkt7xhg9QSulBovzsBkk9wEXANeJyDeNMW1JbZUaMMaYg8DBZLdDZRZNW1UxM8YsNcZsDg/OuiMi2SLyORF500klbRKRHSLymIic42xzfVjqy5kRKZi3xfA2dwD5wE+MMXdGts0Yswu4GDgEfFxEFka00TjpNyNF5G4R2eOkfl4ftk2ViCxxfoajzljAi3r42UeLyK9EZJuTQlsrIo+LyMlRtg2NWRCRq0VkhYg0isiOGH7+Lhlj/MaY3wE3OYt+LiJDwt63UzqMO0YDm4oKsDTsd+H+nu531t0bvi5sn3ki8g0RWe0cq0YReVVEPhLl5w6NCRGReSLyhIjUOcvGh23X12N5hZPG3OTs968iMirasRKREhH5gYisc7avF5E1IvIjEckP2+6YVK2In2O283Mcdvbzgogs6OI9K0TkXhGpFpFm55hdJwkaK6OUSns3Os+/x2bkDAc+GLmRdAx/GB9lXafPIxEZ73wGnul8H37OXhbx2rki8nfnM65VRHaKyF0iUhGtsc754+si8oaIHHHOHxtE5A4RGRGxbYWI/FrsNUWbiNSIyMMiMjfKfkPnOhE53/kcrw//LJfYrgViPr91xTkmtzvnlzoRaRGRzSLyMxEZFrHtMuzQEeh8zg39rqSbMY8icraIPB32Ppucc1pRlG2XOfvxicg3nTa5w39+LCLZsf6MKv1pz6OKp/uAjwDrgD8Czdieq9OA84FnsamW3wVuBXY6r3Et627nIjIBOBtoBX7S1XbGmH0icjfwVeBTwCsRm5Rg0zcbgYeBIHDAeY/JwKtAKfCU094qbG/mU12060TgX85+n3H2ORy4FHhZRD5ojHkyyku/DJwL/APbq3vMB3wf3Y89vuOAs7BjFqPZgf1dLMJeGNzvLIOO39NsbCpseJrsagARKQaeB+YAbwL3YG9QvQ94QESmG2P+K8r7ngp8A3jZec1wbC9xf47lTcAHgMeBF4D5wFXALBGZHZ6+7PwdLXWOzyrgN067p2B7238LHO3imIU7Cfga9u/lbmAscDnwnPOe74a9ZzmwHBgPvOh8PRK4y/l5lVKqz5xg6wPAJmPMchFpAL6EPQf+rR+7Pow9F1yP/cz8bti6HWHvfzF2OIkAD2HP73OBzwCXiMhCY0z49sOwn8OzgHex54I2YBI2g+ZhOs7LE7Dni0rsOedB7FCNK4GLRORyY8w/o7T9Cuy1x1PYz/XxEeu7uxbo6/kt0o3YAP4F7DWQFzgR+7u5QETmG2OOONvehz3ekedcnOVdEpH/wJ7LjgJLgGrsuf3rwPud4x9tHw9gh7w8BTQAF2LPa+XADTH8fCoTGGP0oY9eP7AfQgb4cxfri7AfvG8A3ijrSyO+N8CyXrbhY87rXolh23OdbbdEeV+DDW59UV73L2f95yOWXxL22uvDlvuwab0twJkRr6kE9mDHGOaELb/N2c9RYE4vj8F9kW3oYrs/Odt9N2zZ9dFeG9aeRVH2E/U1EW35WsTyXOBp5+9hdpS/IQP8R5T99edYNgAzI17zgLPuQxHLX3GWfyNKG4YDuWHfL7Mfm1H/F6Idy/9wlt8VsfwPzvIfRyyfhb0ZYoDbevO3oA996EMf7gP4z8jPNezNsSBQFbGt+9k9Psp+FkX7PIr2WRi2big2lTIAnB6x7uvO/v4Vsdz9fP4N4IlYVwAUhX3/jLPttyK2WwD4gVpgaNhy97wVBM7vos09XQv09fwWedzGEf2ayB2b+vWI5W7br++i3e45b1HEe7Riz4PTIra/y9n+d9F+n87fSEnY8nzseTgAjEz237U+UuOhaasqXtwB+q3YD9XOK42pHYD3cFNfdsWwrbtNZZR1bcBXjDH+8IUiMhobdG7HDkoPMcY8hr1zGOki7J3SO40xL0S8Zi+2h3Qktsc00u+MMW/1/KP0yR7nuSweOxdb0fUa4A1jTKdeYGNMC/aCQYCro7x8tTHmf6Ms78+xvMMYszZi2e+d53lh7Z6LveBYDfw4cifGmINO+2Pxijm2KNE92IuZ8PfMxvbI1wPfj3i/NdiLF6WU6hMREeCT2HNv+OfJfdjP4U/GuQmXYLN1/maMeSli3c+wPZTnishYp73l2MyQfdhzcadrBmPMEWPH6Lvn5fOwBWIizzXLsb2QJcBlUdr1mDHm6W7a3dW1QH/Ob50YY3YaYwJRVt2DDfbe19M+YnANkI2tAbExYt23sAUFPyYiOVFe+3VjTF1Ye49iU5492OwapTRtVcWHMaZBRP4BvB9YLSJ/B14CVhhjmgbobcR9u35uu8MYUx1l+Rzn+eUuPuyX4Yz7CHOq8zyuizFrk53n47CFfsKtjLL9QOnNseqLk7HpN12N1ctyno+Lsq6rn7s/x/KNKNu7NxDCx5Wc4jw/E3nB0gfHvKcxpl1EDkS851Rsgac3TEd6UriXif/FnVIqfZ2FvfH2jDFmT9jyB4D/Aa4XkW8bY9rj9P4nOs/PR64wxvhF5EVsyugcbBB4MjY4edEJVrrjnpdf6qL9z2ODpzkceyOup3NsV9cC/Tm/dSIiWdiMlA8Dx2OztMI7cqKOy++l7o7/IRF5CzgDWzF/TcQmsZ47VQbT4FHF01XYO3JX0zEuokVEHsLe3TvQz/27U0yMjWHb0RGvCbe/i9e4Yw67ame017lzKl7ZQ3uG9qIdA8Htca2J0/7dn/tk59GV3vzc/TmW0cZyuHeTvWHLip3nPfRfV2NQ/BHv2dPfVX//L5RSme1TzvN94QuNMbXOTd3Lsb2DD8Xp/d3PuGjn2/DlxRHPsXwO93bf4Xo6x/Z0LurL+S3S37BjHrdhxzHux2ZoAXwBiNYb2Ft9PkYm+jjIaOdOlcE0eFRxY4xpxubj3yZ2yowzsPn712DvOp7ez7d42XmeKyLFXXzouc5xniOL5UDXvXHuNBYjulg/spvXXGKMebyb9kQTl15BEfFgjz3Aini8Bx0/9y+MMV/q5Wt7Ov59OZaxcv9mBuJub6wanOeu/q66Wq6UUt0SkTJsQTGAB0XkwS42/RQdwaObdRHtmjBaENYT97M72jkSOoacuNv15nO4t/sO19M5tqdzUV/ObyEichI2cHwWuDC859Q5T3+tr/uOEH6M1kdZ390xUqpHOuZRJYQxZpcx5i/YfP7NwGnOOAJXkF7e1TLGbMNWZ8vBVlKNyqk656YB/q4Xb+GOPzxNRKK1bVGUZa85z/0NjAfS9dje2X3Eb27Oldjf4UD+3Ik4lu57vM85eSfCRmzl4RNEpCDK+tMS1A6lVPq5DjvebRW2MFe0Rw1wjlO1FOxUVmArlkbqapxbAKCLc6N77lwUuULs/MPuZ9ybzrN7/jhDwqZG6kL4eTlasLs4Yt8DYaDOb1XO8+NRUm7nYYczRHKHzPTm+qi741+MrZreAmzoxT6VCtHgUcWFiJSJyPwoq/KxldP8ONMxOGqJfuLqyeeBJuDrIvKZKO0YBfwTO4D+XmNMtJ7HqIwxu4F/YydZ/mzEfi/h2PGOYNNQtgI3i8iF0fYrIqeKSF6s7egrZ76mG4FfY++ofrEXxV96xRkn8hfgJBH5drSTuohMCrtYiUXcj6UxZhV2mozZ2BTryP2XikhuX/ffxXu2YVOXioBOpd1FZBZw7UC+n1Iqo7g3Sm8yxnwy2gP4XzoXznHHAt4YviMRmYk9x0bjFr2LNmzkUaAO+IiInBKx7gvAROBZY8x7AMaYGuCv2B6x/4m8kSciQ925CcPOy+OdfYVvNx87TOYQ8EgX7e61ATy/7XCeF0W8thx7no6mu+PclT8D7cAtIlIVse6/gUJspfzWY16pVAw0bVXFTEQupSMdxk0ZOVVE7nO+PmiM+Yrz9SjgNRHZgL0DuAv7gXWx89o7IoqFPAd82BmPsQobXL5ojHmxuzYZY9Y680k9BNwlIjdje9eOYO/yXQTkYT/4jwkuY3Azdt6+X4rIedjB5VXY1BO3IFB4e9pF5DJsKfEnRGQ5tpJnEzY4Phl74qxwlg2US91Jg7EB+ljsXdIKbGrKfxhj+jO3Vyw+iy1i8z1sJbeXseP3KrGFBE7GVhndHsvOEngsr8EWP/qhiFzufC3Oz3IetqjAjn7sP5r/xBa1+JpzwbMc+3N8CFv851KiVClWSqmuiJ0ofiqw1hjTXXGYP2Crbt4gIrdib9RtxgZ7o7HDG8bSMb/gh6Ls4znsePSHReRJbDbFTmPMn4wxjSLycez8gi+IyBJsYZy52M/U/diiMeE+C8wAPg0sEpFnsDeYJ2Azlj5Ax9zPn8YOQfmpc15+g455HoPADV0UI+uPgTi/ve60+zLnfPYydpjCBdi5LfdGec2r2PPbF0SkhI4x8Xe6FWgjGWN2iMgXsAHpmyLyf9je5jOxheg2EuVmqVKx0uBR9cZsbEpMuInOA+wkwG7wuAM7Mf0ibBrJcOydyHexF85/jdjP57G9Y2djJ6X1YIvsdBs8AhhjlorIFOAWbHB6LXbupRrshfjvjTF9mnjdGLPZuXP6I+y4yUXA29iL+zIigkfnNW87PUhfctpzA/aEtg+bTnIrdg6sgXSJ8whi54uswd5NfhZ4ILz0drw4FXbPxI6luRpblCEXe7LbDHwRe8e4N/uM+7E0xmwXkROx400uxV4ktGD/hn+GnVx5QBljDojIAuCH2L/3+dj/jZuwv79L6RgbqZRSsXB7Du/ubiMnuHgWOxXV+40xj4jI2dhKrOdiA6F12M/xOqIHj3dj5xP8MPaz04edvupPzns8JiILgW9ig78ibND4W+C/nemWwtt0yPlM/AK22N6nsCmbu7DTWLwTtu02Z/zgf2E/PxdhPy+fBn5gjHm926PUBwNxfjPGBETkA9gpmi4EPoctEnS3s+ydKK855NzUvBV7/nPTev9MN2MWjTF3icgW7DXZ5dib6LuAnwI/7KFGhFLdEmPiVblfKaVUb4nID7AXXOcbY55JdnuUUkoppVwaPCqlVBKISGXk3XdnjNFybLrWqHiNUVVKKaWU6gtNW1VKqeR4w0krWodNVZ2MHaPrAT6tgaNSSimlUo32PCqlVBI4hSouxVYNLMDOdfYa8D/GmGXJa5lSSimlVHQaPCqllFJKKaWU6pHO86iUUkoppZRSqkcaPCqllFJKKaWU6pEGj0oppZRSSimlepQx1VZFpAg4EztJaluSm6OUUip+soExwAvGmC4n0laWnh+VUiqj9OscmTHBI/bE+FiyG6GUUiphLgEeT3YjBgE9PyqlVObp0zkyk4LHXQCPPvooVVVVyW6LUkqpONmyZQuXXnopOJ/7qkd6flRKqQzR33NkJgWPbQBVVVVMnz492W1RSikVf5qCGRs9PyqlVObp0zlSC+YopZRSCSYiBSLyExH5l4jUiIgRkdt68fpyEblPRA6KSJOIvCoiZ8exyd2qb2rnwZXvccdzm3lw5XvUN7UnqylKKaXiKJN6HpVSSqlUUQp8ClgDPAp8MtYXikgO8BxQDHweqAZuBp4WkXOMMS8MfHOjM8Zw5/Nb+PXSLbT6g6Hltz2+npsXV3HLWVWISKKao5RSKs40eFRKKaUSbycwzBhjRGQ4vQgegU8AM4AFxphXAURkKTYQ/Qkwf6Ab25U7n9/Cz/+96Zjlrf5gaPnnzp6cqOYopZSKM01bVUoppRLMOPr48g8C77qBo7M/P/BnYJ6IjBqINvakvqmdXy3d0u02v166RVNYlVIqjWjwmGF++sxGbnnwLZra/MluilKqC//7wlY+/adV1B3Vei8qqhnA21GWu8u6rHrjjJWcHv4AJvWlEU+u20dbWKpqNK3+IE+t29eX3SullEpBmraaQXbVNfHrpVsBmDOmmI+fNiHJLVJKRao50sr/e2ojAHPHDePGMyYmuUUqBZUCdVGW14Wt78pNwK0D0YiaI60Dup1SSqnUpz2PGWTv4ebQ10vfrU5iS5RSXVm3tz709daaxiS2RKW47lJeu1t3F7bnMvxxSV8aUFaQM6DbKaWUSn0aPGaQmsaOu78rttVp6qpSKWj9no7gcfvBo0lsiUphtUTvXSxxnqP1SgJgjKk2xqwPfwBb+9KIC2dUkOPr/jIix+fhghkVfdm9UkqpFKTBYwapbugIHtsCQZZvqU1ia5RS0azf2xD6eketBo8qqrXAzCjL3WXrEtGIorwsbl5c1e02Ny+uoigvKxHNUUoplQAaPGaQ6ohxJ5q6qlTqCQ8eDzS0aoaAiuYRYJqIhKbkEBEfcA2wwhizN1ENueWsKr507pRjeiBzfB6+dO4Ubjmr++BSKaXU4KIFczJIZNGCZe/WYIzRCZyVShH1ze28V9fUadmOg00cX1mYpBapeBKRC4B8oMBZdLyIXOF8/aQxpklE/gBcB0wyxux01t0D3AwsEZH/BKqxhXCmAuck7AcARITPnT2Z604dz1nXfYmte2qYNKqM5+//ufY4KqVUGtKexwxSfaSl0/d7DjezpVoLciiVKt4J63V0aepqWvsNsAQbDAJc6Xy/BCh3lnmdR+gunzGmFTgbWArcCfwDqAAuMMa8kJCWRyjKy6KgZi31r/6Ngpq1GjgqpVSa0p7HDOL2PE4sy2dbjb0gXfpuNZNHFHT3MqVUgqwPq7Tq0qI56csYMz6Gba4Hro+y/AC2R1IppZRKGO15zCBu8DhpAxoVAAAgAElEQVRvfAnjSvMAWLqxJplNUkqFcXseS/KzKc3PBmCHBo9KKaWUShEaPGaI9kCQ2qNtAJQX5LB4qs2Ien1HHUda2pPZNKWUwy2WM72ykPHD8wFNW1VKKaVU6tDgMUPUNraFvi4rzGXR1DIA/EHDK1sOJqtZSilHS3uALTV2DPL0yiLGl9rgcfvBpu5eppRSSimVMBo8ZojwYjnlBTmcMrGU3Cz769fUVaWSb+P+IwSCBrA9jxOG29Tyg42tmh2glFJKqZSgwWOGCJ+mo6wgh9wsL6dOLAXg1W21yWqWUsoRXiwnPG0VYGet9j4qpZRSKvk0eMwQ1WHBY3lBDmBT4wB2H2qizR9MSruUUpY73jE/28v40vxQ2ipoxVWllFJKpQYNHjNEdUPnnkcg1LMRNBwzMblSKrHW77E9j8dXFuLxSKeeR624qpRSSqlUoMFjhqhptGMei4ZkkePzAoTGVIFenCqVTP5AkI37jwAdGQFDc3yhGz3bteKqUkoppVKABo8Zwu15dFNWgU5pcTodgFLJs7XmKK1O6vjxlYWh5ROc/1G9uaOUUkqpVOBLdgNUYrhjHsvCgseS/GwKcn0cafHrmCqlkii8WM4Mp+cRYPzwPFbuqGNHAgvmVDe08NsXtnG4qWN6n/HD8/nMoklkefV+o1JKKZXJNHjMEG611fCeRxFhwvB83t5drz2PSiXR6l2HAcj2epg8YmhouTvuse5oG/XN7RQNyYp7W37zwlbufWXHMcsnlw/lgpkVcX9/pZRSSqUuvY2cAYwxHcFjYW6ndeNCaXFaMEepZDDGsOxdO9fq3HHDOvXuhaeW70zQDR43CyHb52H0sCGh5VpUS8Uq4M3hwZXvccdzm3lw5XvUN+k8pUoplS4SHjyKSIGI/ERE/iUiNSJiROS2LrY9UUSeFZFGETksIg+LyMQEN3nQa2j20xaw46nKhuZ0Wjeh1BbN2VvfTEt7IOFtUyrTbT94NBSYLZ5W1mldMqbrcG80LZxUyktfW0yWVwDb+6lUdwxQtODD7J57E994eC0///cmvvHwWub98FnueG4zxphkN1EppVQ/JaPnsRT4FJADPNrVRiIyDVgGZAMfAj4OTAFeEpGyrl6njlV9pCX0dXlh5+DRTYszBnZpz4JSCbfU6XUEWDy1vNO68Z0qIifm/zN8fLSIUJKfDUCtBo+qB/WjTqX49Gsw4u20vNUf5Of/3sSdz29JUsuUUkoNlGQEjzuBYcaYM4FvdLPd94BW4GJjzJPGmIeBi4Ay4Cvxb2b6cC8GoXPBHKDTXHJaNEepxFv2bjUAo4qHUFU+tNO6vGwfI5wbPokYlxwIGmob3fHRNsW9NN++v/Y8qu7UN7VzeNQptndRJOo2v166RVNYlVJqkEt48Ggc3W0jIj7gYuDvxpiGsNfuBJYCH4xvK9NLTVjwWF4Qmbaq03UolSxHW/2s2FYHwKKpZUiUi243dTURN3dqj7YSdD6d3SyF0qHa86h69uS6feDxRf0bdrX6gzy1bl8CW6WUUmqgpWrBnEnAEODtKOveBqpEJDfKOgBEpFxEpoc/nH1mpPC01bKCzodtWH52qILjdi2ao1RCvbq1NjQeOTJl1TXByQ5IRMEcdz5Y6Bgf7aat1h1tjfoapaDzTcqB2E4ppVRqStXgsdR5rouyrg4QYFg3r78JWBfxeGwgGziYuCfrbJ+HwtxjZ2dxU1d1InKlEmupk7Ka7fWwoKo06jYVRbbi6aGmdlr98S1qVdMYlqVQGBE8NmrPo+pa5JCI/m6nlFIqNaVq8OjqLr21u3V3ATMiHpcMYLsGleqwOR6jpRS5FVc1bVWpxAmfomP+xBLysqNPuxte5OpgnAO4mk49j+6YRxs8Hm0LaEVm1aULZ1QgQX+3FVVzfB4umKFzhSql1GCWqsFjrfMc7VZ8CTZwPNzVi40x1caY9eEPYGsc2jkouKlokeMdXW7P4776Fprb9OJQqUTYXN3InsPNQNcpq9B5ep3qhpYutxsI0XseO95fxz2qrhTlZVG05zV7g7KLAPLmxVUU5WUluGVKKaUGUqoGj1uBZmBmlHUzgS3GmPheRaUR94Kwq3ShCWEVV3fWae+jUomwdGN16OtFU7uefSi857E6zuPF3OC0INdHbpadbsFNWwVNXVXdK9rzKodf+jNiOt+EzPF5+NK5U7jlrKoktUwppdRAiZ4nlWTGGL+I/AO4TES+Zow5AiAiY4HFwC+S2sBBxr0gLC+IXmMofCLyHQePMm1kYULalamMMTyxdh/5Ob5ue5xUenNTVseV5nW6gRMp/KZPT8VGVmyrZdvBo3zopDF4PV1XvexK+ByPLrfaKthqrEp1RYD65X9lZm4dTSVT2Lqnhkmjynj+/p9rj6NSSqWJpASPInIBkA8UOIuOF5ErnK+fNMY0AbcCrwP/FJEfAbnYuR8PAj9LcJMHrZb2AA0tfqCbtNXS8LketeJqvP39zT18ZckaAB64cT4LJg1PcotUoh1paef1HbYe2OKp5d1ObzB8aA5uJmB3PY91R9u49p6VtPqD5GV7uWT2qF63q+bIsSnunXoeNW1VxcAbaKWgZi31r75AwZlnauColFJpJFlpq78BlgD3ON9f6Xy/BCgHMMZsBBYB7cBDwH3AFuAMY0xNYps7eIX3VHSVtlqUl8Uw5+SuFVfjq7HVz4+f3hj6/nv/eAe/M1WDyhyvbDmI35lQ8cxuUlYBsrweSvJsANddz+MLm6pp9du/pZXboxWq7llHz2NHlkKpBo9KKaWUciQleDTGjDfGSBePHWHbrTLGnGOMyTfGFBljPmiMydjCN30R3lMRPnYqUmi6Dq24Gle/XrqlUwCwcf8R/vr6riS2SCXD0o32/ldulodTJ0afoiOce+On5kjXQ73dfQKs39vQ6zYZY0Jzwob3PBbmZuFzUmC1YI5SSimV2VK1YI4aIJ16HodGH/MIMKFUg8d4e6+2iT+8tB2AWaOLGFVs5+/72b/epb6pPZlNUwlkjAnN73jqxNJQYZruuMFjV2mrgaDhhU0dwePG/Q0Egt3NZnSsxlY/Le225zI8ePR4hGE616NSSiml0OAx7YX3VMTS83igoZWmNn/c25WJfvDkO7Q5Kaq3fWA637roOMBO/n77c5uT2TSVQO/sawgFgYunxVYwyS121VXa6updh6hv7rgB0dIeZFtNY6/aVd1Nirubuqo9j0oppVRmS8lqq6p3mtr8PLV2P/MmlDCmJK/TOveCUKTz2KVI44eHV1xt4vjKxFZcrW9u5x9r9nKkpSNwPa6igEVpUo10+ZaDPLP+AACXzRnFnLHDmG0M8yeUsGJ7HX98dQdXzx9DVXlB9ztSg55bZRVg0ZTY/r470lZbCQYNnohKquH7dK3f28DkEbH/PYUHppGVmd2iOXVabVUppZTKaNrzmAZ+u2wrX16yhpv+8uYx6w4403SU5mfj83b9657QqeJq4lNXf/rMRv7r0XX8+OmNocf1977O+r31CW9LPNy1zA7Vzcv28rXzpwEgInzn/ccjAv6g4XcvbktmE1WCLHNSVieV5TO2NK+HrS03jdQfNBxuPjbF2U2DnTJiKFleG1iu29O7/53ueh5LtOdRKaWUUmjwmBY27D8CwNo99TS0dL6wfNdZ1908cgCTyvNxZwvYsK/3xTb6a/OB6Cl26/ckvi3x4Abk5x4/gpFFHb060yuLmDe+BIAt1b1LM1SDT31TO6t2HgLo1Ryf4cFcdUTRnOqGFtY5/yfnHT+SKU5vY2+L5rjzwcKx0/qU6phHpZRSSqHBY1oI7zHYEHbB6A8E2egEj9Mri7rdR162j4lOgLkuCb197lyUZ00r5+3bzgst33O4OeFtGWjGmFBK4MjCY4sWjRpmC+fsPdx1JU2VHl7cXINbx6Y3KdnhwVx1Q+fU0WVhhXIWTytjupNyvn5vPcbEXjSnptHuN8srFEfMy1eSb9//SKufVn8g5n0qpZRSKr1o8JgGasJ6DMJ7G7bWHA3N+xbLGMYZo4qO2UeiNDipeMV5WRTmZoV6WvbVD/7g8XBTe6hQTrS5Nt2qq9VHWmjXOR/Tmptempft5eQJw2J+XXnYTYfIojluGmxxXhazxwwL3ShqaPGz+1Ds/z81TlBaNjQHkc5jKkuGdoyXPnRUKwMrpZRSmUqDx0HOGBPqMYDOgV/4mKcZPfQ8AqEei5ojrcekxsWbGzwWDbE9HpVOamc69MaF/36iBY8VRTZ4DJqOMarq/7N35nFu3OX9/3x17yXtpT1tr+21vWuvTeKExFcS2zkoSUkhoYGk5Af0RykQSlOgF7QUSAi05VfaQgltSUshCUkIhAC5aA47ceIrceLE1/rcw9771K5Wt+b7+2PmOxrdI620ktbP+/Xal73SjDTSjLTzmc/zfJ7FhyRxvKwE22xbVQ+rKf2IDkF02WrkeAqGJew5NQ4AuGa1E0YDUz/HADLqGRbHqTOBO64N25qg0ByCIAiCuGgh8VjiTHuCCIYjpWnak0UhJC1GA1Y3VqZ9LG1p60K6j2GJY9Yvl63abYp4VNy4wUXgPGrLDGNTLAGgpTpy25CLxONi5eigSw2cyaTfEQAqrSaUW2SxqXUe3+ybUj87OzudAIC1zXa1fzmTz/GoxnmMpVYjHid1huacGpnF672Tup+fIAiCIIjih8RjiaN1tQDg9KgbvqDckySE5JqmSphTJK0KtI7F8QUUj7OakB/hPAo3bnDam1HfVjEy5o4IwkTOoxDKgPx6icXJK5rexB0dzozXF32P2qqAl5XHZEx2HgGgwmpSA7IyEo/K4yaaB1uXoXgcnfXhlu+/htv+fR9+8/ag7m0gCIIgCKK4IfFY4sSGZ4QljlMjs+Cc47iSmtrVnL5kFQCqyy1q/12mMf/zYcYbme1oF2WrihvnC0qY9pR2j1WU85jgxLxZk766GMp0icScUhKFWxy2qAsGenGq4jFyPL1zQf6cdjRWoU7jGIoqAr1lq4GQhCnlcxabtAog6rEndCSuvnRiFHMB+SLWN585AU8glGYNgiAIgiBKARKPJU6i3sRjgzM4P+nFrJJgur41fViOIJLUuHDOo0szt85uMwGIduNKPXFVnOzbzAZUWU1x91fZzKhSXjc5j4uX3gl5XMsKZ+qxOckQJc/jyvHEOVfFYWwglvgcj8z44wJ2EjGepi+3uswMg1IKq8d5FMFAgFyK/e8v0wxTgiAIglgMkHgscbQnhhalNPXogCtq3MY6HWE5AuFY9E964mZG5ouZBGWri6mUU+wjZ1V8iqVAOL6l/lqJxHDO1VmfbXXZicdY53HI5VPdwthArExDc7RuZqK+XIOBoaZcLl2dSCMeAyEJr54ej7rtP14+W/IXgQiCIAiCIPFY8oiTvjKzERuWREZtiBNGxoC1zVW6H68QfY9RzmNM2ipQ+iEyai9ZgpNyQSQgqLRfK5GYybmAWgmwYp7i0e0PwRMIRVUHdMU5j5mFX2kvQiVyHoFIaM6EO7WT+UbfpFqy+n82twEA/CEJ33rmRNrtIAiCIAiiuCHxWOJoXS1xAtk9PKP2Qq2sr0C5Jb5UMhldmhLXhep7nPHGO4/1lVaYjbJLV0xunCcQwv5zEwhlMI9R3UcJUiwFzepokuJ5rUTuECWrALC8Ptuy1cjxMzbrj/p8xpat1lZY1Aswei4CacvfE/U8iscE0pet7lbGkRgY8IUb1uB972oGADz1zhAO9lD6KkEQBEGUMiQeS5yIq2VVS9d8QQn7zk4AANa36i9ZBYAmu01NVlwo51FbtiqcR4OBRRJXi8iNu/ep47j9P/fjzx47rHsd4Q4nCssRCOfR5Q1izk/hIouNnnGP+v8V9eVZPUbsrEfhKLbVlaNKGXGjRZSrvzMwnfaxtc5jfZKLHHWV+sTjrm6533HjshrUVFjwpZvWwmqS/9T8ywun0m4LQRAEQRDFC4nHEkfrPGrdh5Akj7eILWdLB2NMfZyFCs0RZatGA0OFJTI4vRjduAOKc/LUO0NxfV2J8AXDarliMkcHiJ31WDyvl8gNvUq/o4EBS2uzE4/asuexWT+OK6Xpsf2OgsvbagAA5ye96NM4n4kQFzhqys2wmBL/WVDLVlOIx/OTHpwelVNldyrjSFqry/C7G2T38eyYO+V2EARBEARR3JB4LHFUV6vKijWNVWqpp6Arg7Cc2HXOjEVmRuYTMarDbjNFBcqIEJmhIhKPWofmnqeOpS1f1dNLBgAtDm1AUPE4rURu6FHEW0t1GawmY5qlE6M9fk4Oz6qOfGzJqkA7S1KUkiZDjJNJ1ZdbWyE/v8sbRDDJcb87apZlg/r/emXbS33sDpEdLk8Qjxzsx3dfPI1HDvbDRccBQRBEyULisYSJcrXsNlhMBqxuiA7HydR51K4Tlji6h2fnv6FpEM6jKFkVNCtu3PCML6Mew3yhfb8BeW7fTw/2p1wnupcsfWAOUFxOK5EbhPO4Ist+RwCoq7DAqMzL2K0ZhZHsM97ZVIUmu3zMaUdnJGLMHalgSPX8gilPYvfxZeV5nFVWrGuObJfoZfaHpAW5IEUUD9OtW3DlN1/Al544gu88fwpfeuIIrvzmC/jui6fBOS/05hEEQRAZQuKxhIlytZQ+Je1Mx9bqMlSXW+LWS4e2T1LvkPH5IHoeHTHiUQgqiUePEigUieblfef5U5hOciIdu06qE/NGuw3CdCXxuLjgnKNvQu55XJ5l0iog9wHXK32H72jCcpJVFzDGsLNTdh/3nZ2AN5BctI3NRHqnk1GrEY+J+h59wTBeOyP3Wu9Y44TBEKkiqClPLzyJxYdj6+2YXnoV/KHoi3/+kITvPH8K33vpTIG2jCAIgsgWEo8ljNbVciphLNoTyWxcRwBoqy1HpTLMfiH6HkXaqj0m9CO6lLPwgkr7ft9x5VIAchnev7xwOsU62vl5yU/MLSaDegGgmAKCiPkz7g7ArYQgZZu0KhAXIIRh02i3prwoIUpH/SEJ+89NJFyGcx5xHlOEOmmdx0l3vAA82DMJr+Iq7uxsiLqvujzy2abS1QiMsUrG2L8wxgYZYz7G2GHG2O061vs4Y4wn+WlaiG1PR9hohWPLhyIHawK+v+sMlbASBEGUGCQeS5hEzqNWMGbT7wjIDoeYDbkQ4jFStho9UkRbylkMA8ZFXxgAfGRTG7a21wEAHtzfh/OTnoTriH1kYEBdilEdgGbWYxG8ViJ3aMd0ZJu0KogtfU73Gd+2ql7tg05WujrlCSIYlk/wU42T0R6/iUJzRF+l0cCwbVV91H1a8UjOYxRPAPgYgK8DuBHA6wAeYYz9gc71/xDAlpifxFcJFhhPXQeYyQIwlnQZf0jCs0eHFnCrCIIgiPlC4rGEiXK17KJs1YGltWUwGhhuWNeY9WO3OysBAANTiUVRLplR+ghjy1aboxJIC+/Gjbmj3++/em8nALk39MUTIwnXEYKztsKq9qslQySuFsNrJXJHz7hmxuM8ylaBePc6XXVBpdWEK5bXApDFXaIes9Mjkb7mZSmSYLVlqxPu+BLuw+enAAAbWh1xn+Xqssi65DTJMMZuAnADgLs45//BOd/FOf8kgOcBfJsxpidZ6SjnfH/MT1G8wWGzvmM9UTsAQRAEUbyQeCxhhDAxMKBOSUK0mY14/vPbcfDL1yVNYdSDOEmdmAvkPazGlaRs1W4zo0opny0GNy72/X7XEocmkCRxmqV2Dmc6RJnu4LSXgiQWEdoxHUtq5uc8xpao6ilN36mUrvZPenBuPH5kh7a6oCvFXNgajXsY2/MYljhODMkiVNt3ra5boXUei0LbFAO3AHADeDzm9h8BaAGwacG3KIcYg6nHwwhSlV0TBEEQxQeJxxJGXLGtq4x2tWxmY9oSyXQ4FVHEeeq5bvPFFwwjoIQpxKatAhH3sRjGVwghKN5vbSDJ/nOJA0mEW9mQopdM0KyUrfpDUtpB7ETpIMpWl9SUJ52hqJd45zF9abo4RgFgV3d86aoQj9XlZrQ4kicCm4wGtfw09juhZ3xO7XdMtE1a53HaS8e2wnoAJzjnoZjb39Hcn46nGGNhxtgkY+wJxljadRhjDYyxLu0PgPYMtz0t5RMnIQX9KXserSYDblzfnOunJgiCIPIIiccSJhNXK1O0vU/aXr9cI8JygMTisZj6AMc0MzUF6QJJxHuXqpdM0Kop0y0GsUzkhp5xJWl1nmE5QLRL4ygzY0lNWYqlZdqdlepyieY9ikTlrhZ71JzVRIjS1diLG9pU5kRuaJnFCKsinCkwR6UOwGSC2yc19ydjGMB9AP4IwE4AXwFwBYD9jLFL0jzvXQCOxvz8Sv9m68MY9mNm/+Mpex4/u3MVHOXx3/sEQRBE8WJKvwhRrOiZzZYtWqdMFqnZhe+kQ4zpAAC7Lf5wFOJxyFV48TiaQDyKQJJgmGPXydGolMmwxFWHRo/zGDXr0eXFhiX5ec+JhUMe06HMeKybX8kqADg1gTnrmtOLPUAe2bGjw4mH9vfjYM8k5vwhVCjl4L5gGGdG3QCA9TpczLoKC86NzcU5j8K9NBkY1jRWJVoV1eVmjMz4U462uQhJVZ+e9D7O+XMAntPc9Apj7GkARwDcA+D9KR73fsSXyrYjDwLStfdRLF++HN4V10SN67CaDPjszlX43LWrcv2UBEEUCaL9hnP5y0ziXPm/8q/m/0DkC0/bthO5TfvAGWxDzMKxhRCxD5VJy9BCNhfVlFvS5mYsJCQeSxjhauXbecxnoIHLG6nYig3ZAKCW0U15gvAGwiiz6MmQyA/ifdCK9UqrCVeuqMVrZybwUvcovv57XD2hn5wLICylT7EUNBfZaBJi/ozO+uFRyplz4TxqP+uZjOLZ2dGAh/b3IxCW8NqZcbynS57mcGpkFiHlGNXTIy2cx/GYwBzhPK5qqITNnPgzWlNuwciMn3oeI0wgsbtYq/ybyJVMCue8lzH2KoDNaZYbBRBVv6znIkS2VA/sw8s/vAfXfuwLODswhvZWJ1768XfIcSSIBEiSLHc4F/8mFluJhBYAdR1wWayFOYckcUgcmv9zhLXPwxH1XJIUEXriMTjnCEuR7QLihRiRPzYuq4bRULjz31hIPJYoYYmrJ3D5cB61jzmaR/Got2wVkN04kQK70Gjf79hxCTs7GvDamQlcmPLi7NgcVjXI26idC9lgT95LJqirsMBiMiAQkkg8LhKiklZzIB6bHTYsqy1H/6QnozTlLe116rG1+9SYKh6jwnJ0OI8r6isBjKBnfA6TcwHUVljAOVcfJ9VjiItDlLaqcgTAHYwxU0zf4wbl36NZPCYDkN+EsyxwlJtRNXYErn0vo2r7dhKORF4JhSWEJI5AWEI4LIsliUcLMiDe9ZIkWVTJyyuCS/ldK5T0iiYhsyLiTPv8QpzFbxdBFDskHkuUybkAFMMgTszkApvZCEeZGS5vMK/Oo7ZsNZHzGOvGFUo8Tsz51fc7Vqzv6GjAN54+AQDYfXJUFY/a902PO2wwMDQ7bOib8GCQxnUsCno14nHFPMd0AHJozTN3X41JdwDLMiiDLbeYsHllHV45NYbd3aPgXHbIhWNYZjZihQ5xu32NE//+8llwDuw5PYb3X9qKQZdP7WNM5YaKsB2a86jySwCfBPBBAI9pbv8YgEEABzJ5MMbYCgDbALyQqw0kigtJ4ggpAickSQlK7pKsqBFLYrl4MaPcrxFTsU4XjxFRqZ5bu55arijKGNNtb9zmxy8Y68TJ74uEUJirf6sJgsgPJB5LlChXK09R584qK1zeYNRz5RqX1nm0xYvH1uriKOVMJQTbnRVYWluG85Ne7Do5ij+6eiWAaMdWrzvc4iiTxSM5j4uCHqXf0WRgusJt9FBpNaHSmvlX984OJ145NYZBlw+nRtzoaKpSHcN1LXZd/RTvXl6DSqsJbn8Iu7pH8f5LW3F0IBKWsz7lqA+55HXaS84jAHDOn2WMPQ/gB4wxO4AzAO4A8F4Ad3LOwwDAGPsvyIKynXPep9z2AoBXICezzkB2K/8S8nn5Vxb6tWRC2GjFIwf7MTbrh7PKipvWN5MTGQPnHL6gBE8gBE8gjLlACHP+SDI5QRBEISHxWKKMZSFMMqWhyoozo+4FLFuNPxwbHZHXVsgEUu17EBt+wxjDjjUNeHB/Hw72TMLtD6HSaooRnPrcYTGaZIjSVhcFwnlcWlsOk7Gw4dY7Ohrw9d8cBwDsUhzybmU2o97+SbPRgKtW1eO5Y8N4+dQYwhKPKn1d25w4LAeAKhBcnqDqfBK4FXJq6j2Qex27AdzBOX9Us4xR+dG+YUcAfBjAnwMog9zD+BKAeznnpxZguzOGA3BsvR0XLr8dX3riiHr71359TA3PudiOiUBIwpw/BF8oDH9Qgj8kwRcMwxcMk3tGEETRQuKxiPEGwghKUkJHbjQLYZIpQpTmNzBHFo82swFWU3wzsNVkhLPKirFZf9E4j87K+Pd7Z6cTD+7vQzDMsVcJJBHrVFlNuoN+hNM6MutDMCzBXGDBsdgISxwz3iBqKizpF07B1FwAFVZT2rmNvWJMRw6SVufLivoKLK8rR++EB7u6R3H92gbNbMYMwnc6nXju2DCmPEG8fWEax5XS1+V15ahK8F0lEM5jICzBEwiria8XM5xzN4C7lZ9ky3wcwMdjbvt8XjcsD7hat6B66VVxAR/+kITvPC/r3T+9bnUhNm3BkBO4/ZiaC8LtD5GTSBBESUJnpkXKrC+Im//tVbz73heiysIEC+U8ArJQzSS+OBNmlLTVRAJZIBJXBws4rmMshfMIAFtW1qtC4rljwwAipcWZ7B/R48k5MEx9jznnY/99EFfc9wKefmco68fYfXIUG+99Hnf8cD+C4eQnf5LE0TcpO49tOeh3zAViLukbfVPYdzYyl1RPWE7sYwDy3MijA+nDcgCgWtPTTKWrFxcuTxDTrZvlvyNJ3MV/ffE0/vvVnkUZqOTyBCvLGjUAACAASURBVHFmdBaH+qZwdlQOmyLhSBBEqULisUj5t11ncGbUjUBYwmOvn4+7PxtXK1OEoxkISZjxhdIsnR0iMCdRWI5AnfVYyLLVGfm5q2ymhKMIyixG7FjjBAA8+dYAuodnEo72SEe7MyIyDvVNzWeTiRjGZv149cw4QhLHV399FLO+7E5SH9rfD0DePw/t70u6XP+kB76gfILY3lCYoKdYxBzSsMTxwz09AACzkWF1o/7ta7TbsK5ZdiqffGsAw8pno6s1tXtZXR5xe6fmKDTnYuKZo0OAwZSyLDUscdzz1HFc+c0X8N0XT+ftguVCEQxLGJj24q3+KRwfmsHYbGR0E0EQRClD4rEI6Rmfw3+/2qP+vuvkaNwfUtXV0jF8Plu0omcsT6E5omw10ZgOgXDjBl3egp1QjOkYi/LF93TAwOTo7XufOq6WFmciHi9rq1HDUHadHE2zNJEJIlkUAMbdAfzbS2cyfgx/KIzXzoyrv//z86cwmUQIHdU83/oMykLzyaYVtbCZ5a/9/km5pHZ1Q1XCkvFU7Ox0Rj0GoMN51ISiuMh5vKjIpPVBlLF+L4vPZ6HxBcMYcnlxfHAGb/ZNoX8icgGJIAhisUDisQi57+kTCIYjIkmeH+iOWkZ1tXQMn88Wbaro6Ex++h71OY+yA+oLSgUbMC5ef6pk246mKnxkUxsA4LUzE+ib8Cjr6O9JNRsNuHp1PQCogSREbtAGuwDAf7/WEzWHUQ8HeybVPkEAmPGF8M/PJ84nEc9nYEBnU3GIR5vZiK3t9VG3ZdLvKNCWrup9nBqt80jjOi4qsmmt+P6uM0VXwipJHL5gGLO+ICbnAhh2+dAzPofjgzM41DeFt/qn0TvugcsbpMAbgiAWLSQei4w9p8fwwokRAMDmlbXq7bu6x6KWE66WnuHz2aLt7RPOW65RnUdb8vCMliIY1xFxEVO/31+4YU2cEE7UI5mKncqJ+bQSSELkBuE8Vihl3sEwx31PH8/oMcTn0GhgeHdbDQDg4QN96B6eiVtWiMd2Z2XeSsuzYWeHM+r3bMTjxqXVUZ/ZRrsV9WkuZGmdx+kiEwVEfrlpfTOYFMqocsQfkvDs0ex7kwF55EUoLMEfCsMTCGHWF4TLIwu/Cbdf/Rl3+zE268forA8jMz4MTHvRNzGHM6NudA/P4J0L03ijdxIHeibxVv80jg7M4OTwLHrG5zDs8sHlDVIPI0EQFw0Ud1dEhMIS7lGi9CssRnz3jo34/R/sQ/+kB7tOjuKT18jzAznnqhOWT+dRmyqaifM45w/pTlJUA3N09DwCsnhMNUsuH3DOVac33UzNmgoLPn/9anztNxFRkuk+2q45ud/dPYrLltXoWi8UliBxpE0AjcUbCMNsZAUfJZFvhJjbuqoe1WVmPH7oAl44MYpXTo3hmjXONGvL7D4llxJfvqwG37hlPW781z1yr9ZvjuPhP9qk9nRxznFMCbrKRpzlE9k1PKb+ns3nyWQ04Jo1TjylBA+t1xG4o72oMk3O40WFo9wMx8B+TC+9Sk4D0zmSY2zWj1BYwpw/DE9QnnnoD0qQOFd+IoPuAaiD6Dlkl5DcP4IgiNyzuM8WS4yfH7qA06NyeeqfXLsaDVU21SV4vVeeHwjIbp0oncvU1coEe1lkFIFe5/HhA31Y/7Xf4lvPnki7rCRxNbRET9kqAAwVIIHU7Q9F3m8d5Vcf2dyGVZqAlEz3UaPdpgqOXSfH0iwt0z/hwWX3Po+bvrsno1KvM6OzuPwbz+O9/7oHPk055mJjxhdUy4i7Wuz4i/d2qA7kfU+f0OWI9E3M4dyYXOa6o9OJNY1VuHPTMgDA3rMTUT2qIzN+TCi9kJkkmS4ES2vL1eOTMWBtc3bidqemdFWPQLaZjShTwqbIebz4cAzsw/Seh8C4/u8ZTyCEQ31y4EzvuAejM364vEHM+kKY84fhDYThC0ryjMSghEBIQjDMEQqTcCQIgsgXJB6LiFeVII76Sgv+71XLAQA7lHTEYJirQR0P7ImE6azOY4ojY0x1zUTaaDp+cegCOAeeOzqcdll3IKT+gU81qqO+wgqzUb5SXYiy1UzHopiNBnzt5i4YDQzlFmNWJ+c7lIsGRwZcajhSKn5+6DxmfCGcGXXjX17UPyP88UMX4AmEcWbUjX3nJtKvUKKc0PQ7drU40FBlwyeulp38kyOzamJoKnZrhLwQTp+/YY0qQn99eFC9XxvOky6FtBD83iUtAIDLltVkPW9xZ2cDqpR1r1qtz7kVpauF6l0mCgcD4Nr7KJYcuh81PS+Ah0OyVZiCB17twc8PXSj55FWCIIjFBInHIqJ3QnY11jbb1fTDLSvrYFXcv90nR3F+0oP/3HMOAHDJEkfU1f98IFyzUR1peWGJ48TQLAB9zsKMJnExlfNoMDBN4urCO4/a1643/Oaq1fV4+k+vwlOfuyptL1gitPv1ZR3uo9ah/Mm+PpwemdX1PLs1vbS7uxdvuuvRKPEoi7ktK+vU244NxPcsxiKcxSa7DZ1NVQDk8RNXK8JJG3CkDefpai4u5xEAPrOjHf/zh1fghx99d9aPUVthwa/+ZBt+/uktuHJFbfoVEBnX4fJS2erFijHsh2PkLbj2Ppq2fDUY5nj80AX88q2BBdo6giAIIh0kHosEzjn6xuWyura6cvV2m9mILe3ySe6u7jHc9/QJtTH/727ugsGgr3ckW0SZpp6o9Z5xt1reOeMLpk0K1cb128tSux/NDlm0FcJ5jBKPGZSgdjbZsdKZnTN86dJqVVDvTiMeR2d9ODIQcbrCEse9OkoxB6a9OKkRmbtOji3aK/zCCaytsKjH0jpNqWVsEmssvmAY+87KzuyODmfUvDoxtmJKE3Aknm9JTRkc5ckvjBQKs9GAHR0NqK2wpF84BSudlXj3cn3CEQCqy8h5JGRcex9F9flXYTGm/xv25OEBtW2DIAiCKCwkHouEibkAZpU/jsvrKqLuEy7U8IwPzx2Ty0E/cGkLLm/TF6QyH0SZph7nUXsCznm0s5gIEZYDpC5bBYBWJTRnqNBlq3kMKNIiAkkA4JXTYwiFkyf5aZ3JS5ZWy+ucGks7J3J3zP39kx6cy3B0RalwXDk2u1rsqvBzlJmxrFa+UKOdyZiIfecm4Fcu2sSOqdD+LoT+0YHI8xERairkzzkF5hAAYO19FR++Ylna5YJhjoM9k/nfIIIgCCItJB5ziKSzQz+REOjVnLSvqE8sHgVlZiP+6sbOLLYwc0SZpssbhD+UOugg1r2ZTiMeo53H1OKxWQnNGZ7xpRRS+UD0HJqNLGrcQL4RYUmzvhD2nB7H1FwAU3OBuONMCJbqcjN++NHLUaWMULj3qRMp4+PFemJoPADsWoSlq75gWA2iWhcj5oS4O57GeRQlvWYjw7ZVdVH3NdptWKf0te4+OYppTwADykUOPSmkFxOOMlG2Ss7jxYykVDgEQ5LuoC664EAQBFEckHjMAZxz/PFP3sAV972At/qnUi67q3sUXV/9Lb70xDtRt2uHlS+PEY/L6sqx0hm57a4d7WoPYL7RBsSkK109FuPepBsEPuPT1/MIRMZ1SFyfC5pLxOt2VlqjyhXzzTVrnGpL0B/+z+vYeO/z2Hjv87jhn19W37tQWMIrp2URePVqJxqqbPiz69cAkI+phw/0JXxsfyisBjDdtKFZdXbTlciWIieHZ9US6tjkUyEeB6a9mJpLfryKntIrlteiKoFLLgKO3rngwsunIu9hMYblFJKacuE8BhdtiTSRGs4BTyAiGPWWdYt+WYIgCKKwkHjMAWOzfvzv8RFMzAXwpSeOpOz1+9HeXvhDEn72xoWoK64iLMfAgKU15XHr3fwuOR1xWW25Ou9xIWjQKR4553HOY7qRETMZOI8tjuhZjwuJKh7t+sJyckV9pRWbV9TF3X52bA7fe/E0AODN/mnM+uTyX+FUfnRLmyoG95weT/jYr/dMqSdwOzsa1L69gz2TmFtkvUXa43J9nPMYEZPHhxK7jy5PEP2Tcj/ytlX1CZfZ2RmpDvjB7rMJH5+IpK2GJE49bBcpc4FQVPXEphV1QDj1xQSzkekOZSIIgiDyS1GLR8ZYJWPsXxhjg4wxH2PsMGPs9kJvVywDGjHTPTyLR1/vT7icJxDCfmUcQljiODkcCSvpVcJyltSUJxzy/ifXrsIPPnIZfvGZrbAps9IWAm26aCrHb2DaG5ewOp0mUVGIR8agRv4nQziPwMInro7OyK9bz4zHXPPdOzbim7dswNduXoev3bwOG5SB7v+ztxfnxtxqXyNjUHskzUYD1iuOV2+SHkaxnoEB16x2qqXRgbCEvWcX18gO4YhXWIxx/cRdUaE5ifseeyYi72F7kgCkjUurYVfKhbuVz3V9paUgx0wxo3WPaNbjxUls2X2l1YSyvr1yVUcSAfmBS1tRmeVIGYIgCCK3FLV4BPAEgI8B+DqAGwG8DuARxtgfFHSrYhicjhYz//S/pxL29Ow7OxHVg6Z1RETZamzJqsBsNODGDc265gzmEu3zpRKPidIqp+bSOI+KY1ZpNaVNjRU9j0ABnEe34jwWQAg4q6z4g03L8PFtK/DxbSvwzVs2gDE5QOK+p0+oPYrvWlIdNRJEHEf9k56EPaJCPF7eVgNHuRlb2uvUixbpgnZKDXFsrm22xx1nDXabul+PJhnXkaofWaANOBJ0tTgWtMy5FKjWVBiQeLy4CKToVbf1vYbpPQ8BUrQbbTYy3Hb5EtyysTXfm0cQBEHopGjFI2PsJgA3ALiLc/4fnPNdnPNPAngewLcZYwtnv6VhyBUtZibnAviuUlaoJfakXDgdnHO1bHVFXXzJaiGpq7SofXepylYTiUe9gTnp+h0BOY1VuJMLmbgaCEmYVHrhisFF2rDEgdsuXwIAeLF7VHW5RMmqYIXisIUkHuWMA0D/hAfnxuTjTSSFlltM2KSUhe3uHl00/WihsITu4dTJp+L2pM6jRjy2pfh8xgZbUdJqPDWa0SDpeqKJxUUonPw7hUEZ3bH3eyjvfhrTrzyI8u6ncf9HLsetly2hizAEQRBFRNGKRwC3AHADeDzm9h8BaAGwacG3KAni5LzcYlT7Mn68txdnlIRHQBaIsWEkQnCNzfrV/rNkzmOhMBsNqFVKzcZmk5eLHldOvFfUV6jle+nS8UTZaroxHQLhPg5M56ZsVY9AGndrZjxWLWzPYzL+/Hc64kq4YoWL9jjqiSld3X0qchFDu574/6DLh1MjbhQb2Qjac+Nz8AVlx6OrNXH/oRB558bn4AnE9+GJCzstDlvKkvHtHfHOIxFNlPNIiasXDaGwhJCUPiXbEPLBNvQ2XPseg23obSpVJQiCKEKKWTyuB3CCcx57NveO5v6EMMYaGGNd2h8A7fna0CFFzDQ7bPjqzevAmOz4fOPp4+oyZ8fcuDAli8wKi3wCemJoBqGwFJ20Wldc4hGIlGvqcR7XtdhVdyFdWZpIDNXjPAKRvsdYpzcbHjnYj0u+/r/46YHE/amCqBmPReA8ArKI/dy1q9Tf6yosai+kQFteGdv3KEpdG+1WrG2uUm/Xhr68VGQjO86MurH5Wy/iT376ZkYiUusmJnce5feOc+DE0Gzc/b1pSsoF9ZVWXLIksh/IeYwnuueRnMeLhWlvEMiimMHtD+HF7hE88eYFvNg9QiFLBEEQRUAxi8c6AImmAk9q7k/GXQCOxvz8Kqdbp2FQETMt1WXoanHg9iuWApDHHogT9V3dEdfxzi1tAAB/SMK58TnV2QCKz3kE5L4wIHnP44TbjyElxKarxa66C+nK0kTZqr1M39VlMZ4kFz2PP3qtBzO+EL6/60xKMaLdN82O4nAeAeDj25ZjpXKs3LihKb6Xr8qKcuUiRe+ER71dkjje6JXHyVy92hlVDraivkJNaT2apISzUPzizQsYmfHjqXeGMhrVIhxUo4FhdUNVwmW0sxiPx7xuznnafmQt713fDABostuwrLa4StCLAQf1PF6UZHOhwNu2DXc9fAgP7OnB44cu4IE9Pbjr4UN44s0Li6asniAIohQpZvEIpL5Wmeq++yE7k9qf9+dwu6IQgTlinMQX39Oh9ufd+/RxBEKS2u+4rLZcHbsByM5Ij5K0ajQwLKlZmPmNmeBUglhE6mgs2n7HrhaH6i6kGwQ+45WvIustW21VylanPEF4A/oGSyfCFwzjrNLzNzDtjSovjkUMjzcZGFY3Jk7aLARWkxGPfmoz/uGDG/DXN66Nu58xhjbFxdY62+enPJhVrt5rXTLB0lrF3V3gUKJ0JAqX0oNwDZfWlCVMMQbk11yllFrHhuZMeYJqsNMKHVUBn7hqBf7xg+/Cg5+4Mm0I1MWIxWRQKy+o5/HiYSrDCwWOrbfDu3I7gjF9ksEwx+OHLuCXbw3kcvMIgiCIDChm8TiBxO6iGPaUyJUEAHDORznnx7Q/AM4mW34++ENhtS9OlFXWV1px9/WrAQDnxubwg91n8XqvvLk7OpxY01gFs1E+sTw2MBN1gms2Ft8uabDL4nHc7Y+LWQdixaNdneWm13nUW7barJ31OI/S1W7N0HggdbqoeG2rGiphNRVNRhMAuXz1w1csS9oXtKJedr607ql2X61L0JMnjuHYBOFCwjmPcgSTjR9JhB7XkDGGdc1KaM5QtPOoNyxHYDEZ8KErlmJ1Y2KXk4iUrqabA0ssDkISTxmWE4tkssGx5UNJx3YAwJOHB6iElSAIokAUn1KJcATAWsZY7JnxBuXfowu8PQkZ1swc1I6T+OiWSFnhP79wSr2CurOjARaTAWuUk8tjgzPqyX0xlqwCkZTRkMQTCkLRV9Zkt6G+0oqa8vQ9j4GQBG9Qdg/tGfY8AvMrXY1N1dSWFGvhnKvLlmL4ieifvTDlRVCJyRevx8AQ1e8oEGWro7M+dZ1CMzrrx7g7ctxp5y6mgnOOPqVkN10vsdi/p4bdUa9bz5gOIjP0XlwiFgeJRgWlIuDsBDNZgBQJq8Ewx8GepNePCYIgiDxSzOLxlwAqAXww5vaPARgEcGDBtygB2jEIrRpxYzEZ8Lfviy4ntJoM2LxSNlNFmMbRQVdEPBZhWA4QHRQz5o4vXRVulnhNwkmc9YWSnjiIsBzt8ulo0YjzoXk4Y7GliW/0TWLWFy90B10+tdyqFMNPxMWIsMRxflIWUeK1r3RWotwS71gKd1fiwMhMcbiPRweixb5e53Fkxq9eoEgn/MT+DYQlnNYkzYrPJmPAUuphzAnqxSVKW70oCCWoVkkFt+j7O0iBSwRBEIWhaMUj5/xZyDMdf8AY+yRjbCdj7D8BvBfAX3LOs296yyFaERMbqLKzowHbNYPDt7TXoUzp9xFOx6wvpI4SKFZnQzuiYiSm73HWF1RPsMUohJryiBhM1vc4o7ldb2BOk+b9jZ1dmAmiBNJmlg//YJjjtTMTccsd04iW9UnGPBQz2osRYh/FCv1YogS6qzjEY+wM0d5xT5Ilo4lKMU7z2dLuX21YkAgbanGUpRzTQejHoXw/UNnqxUGiVodUsIC+i0Pa5F6CIAhi4Sha8ahwK4AHAdwD4DnIsx3v4Jw/XNCt0qAtn9SWVQJyL9VX3rcWJiU443e6mtT7Ep28F2vZqjY18mdvnI+6739e61VbUy5dKp+AR8XxJxOPvki/it7AHKvJiHolvCfbcR3BsIQTw/I4hls2tsKqhKjsTtD3qBUtiUo8i53l9ZH91jPuweiMT+3PTS4ec1ManEtiy4x7J+Z0nZBqez3Thd20OytQpojD1zXlcMLlLNYLO6VIDZWtEimwjHVDCvpT9jyajUydqUwQBEEsLEUtHjnnbs753ZzzZs65lXN+Cef80UJvl5ZBxZ2pq7AkdCZWNVThkT/ejG/dugEffvdS9fa1zfa4lg49aY6FoMlhw82XyAmxT78zpPaaDLt8uH+3nEPU2VSF7WvkOYHV5do4/sQniNoy0Sqd4hGIJK5mG+hydsyNQEh2ei9bVoOt7XIZ8a6To3Hx70I8Lq8rz2gbiwVnpVVNtuwdn4sSw+uT9HBq3fNiCc0R2y0+L/6QhGEdJbVC+JmNLMpRTYTJaFCPhd2nxiBJHJxzzYxHKlnNFdVlkTTmTF0pYvFjCPkws//xlD2PH7i0NWlQGEEQBJFfilo8lgLCnWlOcXJ6xfJa3HHlsqjo/gqrKcrN0HOCW0j++sZOtczz6785hrDE8Q/Pdas9ZV+9uQtG5fVFDwJP7DzOapxHMSZBD2oaaJbO47GB6LEiOztlwTsy448bEH+8hMNyANn5Fm5278RclIO3LonzWGUzq/ujGJxHlyeIC1PydlyxPOI06Ol77FFTjMth0pFivEM5FsZm/Tg+NIOJuYA61qRY+5FLEXFxSeLR3wMEIXDtfRRl515WU8kFZiPDbZcvwS0bWwu0ZQRBEASJx3kiTrBbHJnPZ9SKEr0nuIWitboMn97eDkB2gv72yaPqrK0b1zdhS3tkqkq1JgAn2Xwvt+akMZMryCLQZXDam9WgaOFiWYwGrG6sxA7FLQWiR3ZMzgVUV7mrtfTCcgRa8SjCclqry1L2C7VWR97jQqMVvO97V7P6fz2Jq5mmGO/Q9Cfv6h6lpNU8EV3WTqWrRGLK+l7D/R+5HOXdT2P6lQdR3v007v/I5bj1siVgKVxJgiAIIr8Ur1opATjnEfFYnbl4XK9xf4q131HLp65pR4tS1vjIwX4Acqrsl2+KTpWtiXIeE58catNW9fY8ApFAF19QSjkKJBlCjHQ0VcFsNGBZXTnanfJ7r+171IqWUnUegUgp9MCUF29fmAaQPjlWlK4OFkFgjrbU9oZ1jbAoF1jECI5kSJL+MR2CpbXlWN1QCUAuXc0kcIfQjzZQK9HFpck5EpSETKXVBNvQ23Dtewy2obd1X2h0+0N4sXsET7x5AS92j9BMSOKiQnv8P3NkEM8cGaLPApFTqGlgHsz4QpgLyGWb2ZScakVJKZTFlVmM+Oub1uJPH3lLve2TV6+IG2FQZTPBwOSyND1lq5VZlK0CcuJqTYX+xD1J4jieIG10R0cDzo714FDfFKY9AVSXW6JESymO6RAI0SPxSHpquuTYlgI5jxNuPz7z8JvoarHj7963DowxVcTXV1rR7CjD0toynB2bixJ2iRie8cEfEinG+vsVd3Y24PSoG2/1T6GzSQ5JMjC5MoDIDal6ov2hMK76h5fQUl2Gu69brfZaE4QeOOf45VsDePLwgDpbGQB+9GoPOpvt2LKyDptW1lG/JLEoSXb8a/nx3l584NJW3LKxNaWD7/aHcKBnAi5PEI5yMzatoM8NEYGcx3mgTfxszqJsdX2rHRYl7TNZD1qxcfO7mnHF8hoAQEOVFXftWBW3jMHA1NmNycrShHissBjVXkk9aEX2L968oHs9ADg/5VF72LSC8Dql103iwH++cg5AxPFqtFvVhNdSJJFwSieGhXh0eYOYW8CrlE+8OYCDPZP40Wu9+M07QwDiR4uI8tF0PY+9WbqGOzrk0lWJQy3LXlJTrn5OifnjrIxcaDs7Fr0fD/ZMwhMI48yoGwYqTSQy5JdvDeDxQxfiTpzDXP4ueeDVHtz18CE88eaFrNoeCKKYSXb8awmGOR4/dEH9+6bF7Q/hhRPD+MbTx/Hphw7hgT09ePzQBTywhz43RDR0RjQPUo3p0EN1uQX/fudl+Kv3duL3SuQKO2MM93/kcnzu2lV48BObUJHkSpToa0rmPLr98u2ZuI6APDJj80o5OOXBfX04MzqbZo0IWjdxncb13byyDpcurQYAPLCnB/0THtXxKuWSVSCxo53uNUXPelw491GboPqtZ05gci6As2NuABHxKF5P36QnZVKnticyE1f/3W216tVVj1JV0FZHrmMuWVpbpvbVxo7I2dU9BgAwGhiuWl2/4NtGFC+SyZayFNXtD+HJw/EnxLGkOnkmiFJF7/EvePLwgPoZ4pzjiTcv4K6HD+G/Xu3FscEZhGP+vtLnhtBC4nEeaEcZZJuUem1nIz6zo72knA1nlRVffE8HOpqSzz4UpWnpylYzHYHBGMPfva8LBgaEJI57njqh+0qYEIQGFj230WBg+OrN6wAAgbCEv/3VUbUscn2JOMLJqK2woEoj8OsqLGi0p3ZSteFPCzmuY3TWr/5/yOXDF352GOLvlxC8wkUMhKSUibvCebQYDRld2LGYDNi2qi7qNgrLyS2MMdXhPXBuEp5ARAQIMXl5W41avUBc3HAAjq23Y3rr51I6IQd6JlI6LrFoT56J/EC9pwtHpsd/MMzxk729cPtDuhxLQaafGzoGFidUwDwPhPNoNDA0VBXvmI1CUK2zbDWTMR2CdS123H7lMvz0QD9eOTWGXSdHcW1nY9r1RNroSmclyi3Rz7txWQ1u3diKJ94awCunxjTPVdrOoxjXcWRAcVJbHWmTCrViayH7Hsdmo4Xq7pOR/bC+NbpsFQB6xz1YkqQXsWdcDstZVleeUVk0AOzsaMBvj42ov5dCP3KpsbOjAQ8f6EcgLGHvmQlcv64RfRNzOKeIfiEuCcLXtg3VK7cDPLETAgDv6WrCW/1TGT1uMMxxsGcS13Y2pF+YyIhkvXd6++2IzHFlESC458w49p0bRybjdvV+bqj/eHFTOnZXESICSJrstoxPUBc7InF1ai6Z8yjfnqnzKPjiDWtU4XnvUycQUMJRUhHbPxfLX763E2VmY9RtpRyWI9D2/Ol5PY12mzqfeyETV4XzuCw2gMlqUgNrtCWkqcZ1qGM6shB+Ozqi/yiS85h7tq6qU5NzxYgc7cWCnR10Qk/IroV3+TbZXUwiNn6hlNsd6pvO+PGTpYET2SFcpvueOZHQyaLSx/zg9oeybjEJSchIPAL6PjfUf7y4IfE4DwbUMR3kOsbiUMpWXd4k4lEpXajK8qpTXaUVd1+3GoA8DP4n+3pTLj8648O4WxYnyQRUk8OGz+5sV393lJmxpCbzXtZigznQ6wAAIABJREFUY4VGcOkRjxaTAU4lJGhBnccZef/s7HBGzXRc22KHQbk40+IoU0u8k4XmhCWOfmVMRyZJq4Imhw1rm0trjE6pUW4xYZPSu7z75Bg456qIbLLb1KRb4uLmQM8EYDCldKkkjozK9bSkmndL6EfbM/fAnp6ofIFEUMlwbtC+76+emViw5033uaH+48UPicd5IK70ZJO0utgRzqPbH0roCs6nbFXw0S3LsVKZ0fjQ/r6Uy0aP3kheivpHV69Uwzw2LqteFKU1nYoQYgy4ZEm1rnVE6epCBeZ4A2H1gkKD3YYv3bQWVkUkXrasRl3OYGBoU5zJZOJxcNqLQFg+5rIVftevlZ2vCotxUVxAKEaEwzsw7cWRARf2nZVPfnZ2OhfF546YP9mU4unFbGS4ckVt3h7/YiKTnjkgUvpIzI9M3/dcYGCALxhOKv7d/hB+vLcno236xZsX8MyRIbqgUEJQsXGWSBLHsFLSl03S6mJHO8vN5Q3CWRUd0hIpW83+ELSYDPjQu5fi75/tRu+EBz3jc0lLDI8qPX9AavfNZjbiJ5+4Eo8c6McfbFqW9bYVE+9Z14i7r1uNJTVlcTM5k9FSbcPh8wsXmDOmCctxVlnRWl2GH//fK7Hr5Cg+s6M9atnl9RU4PepOWrbam2XSqpY/vmYlfMEwNq+sg9lI19jywc4OJ+59Sv7/t57pVudyxpYNExcvjvL8hSZ94NJW6rfKAZmmfAqoZHh+ZPu+zxeJAw/u78Ojr/dH9a/qmTGZyWPOBcI0Z7KIoT2RJeNuv/oBobLVeLRlDdOeQJR4DIYl+ILyiWK2PY+CnR0N+PtnuwHISY0r6lckXE44j63VZWlLLtqdlfjb962b13YVEyajAZ+/YU1G64jE1cFpLzjneXeCRjVhOeJY2byyDptX1sUtKy4QnJ/0IBSWYIoRd9nOeNRSZTPjb3538RwDxciK+gq01ZWjb8KDfedk19FsZNi2ikZ0EDKbVtThgd2nwNOUrqaESwCLfEeYDHIFBgfwYvdIyZ+UFnqYe6Ypn4LYfAEiM/S+7+bhYwADgo1dOX1+bWDVrZctUV3QXDzma2fGMaY5xwYoaKfYoHc/Swa0Mx6pbDWOak3M/nRM36MoWQXm5zwCwJrGSrQ4bBh0+bDr5Bj+cFsS8Tgk5jaWfgDOQiDcdH9IwuRcAHWVqcd7zBet89hQlfq5hJsYDHMMuXxxbmqv0u9oNRnQbKcLO8UKYww7OxrwP3t71duuWF5LJwWESqXVhLK+vfCKtNUsBGTZ6efBpBAGRyfhXHsl0NSJQ/3TONQvB+yUagJosSSaZlta/Mjr/fAGwyX3vhcLet93k2cc1oFDmKxdBYPJktlnSAqBMwMYWNL1njw8gG2r6nPqgiYK6hNBO8cGZ/DjfaX5mV1MUD1WlkTPeCTxGIu2bDV21qNbIx7ne6LIGMN2pcxt/7kJeJXB7lpc3iDOT8piP1W/IxFB66YPLUDi6mhM2WoqlmtCcHoS9D0K57GtrlwN2iGKk+0xIzkoZZWIxdb3Gqb3PARIGfZDcQ4p6Id15BhsQ28DjCHo7Fg0CaDJ+t0W+vVkW1pciu97Mc0s1Pu+s4AbhpAPM/sfz0g4WobeQdnZXWDMkHK9YJjjFwvcd1mKx85ig8RjlmiDRKhsNZ4aTWnoVExvw4wvIibnW7YKyL1TgDw4ft+58bj7j2vCcsS8QCI12gsiwmV/9sgQPvXgG0mDauaDcB4NDKirSC0eo2Y9Juh77JnHmA5iYdmysk4NRgLksByC0MIAuPY+iuq934Nl6J0MVmSY2f84DCEfJJMNji0fipsVqaWUEkD19Lst1OtZ3+KY16iyUnjfY9NkHz90AQ/s6cGnH3wD33j6OF48sfBCctOKOpiNKd535eKJZewkAPkzVHbuZZjSnfUr65WfeQEw6ksjnixQ/yoF7RQOEo9ZIk6oyy1GOMry19RfqmivisWWV2jLVu3zLFsFgG2r6tUv0V3dY3H3HxvUhuWQ86gHbYLw0LQXveNzuPvRw/jtsRH8xytnc/58ouexvtKa9kSkscqm9sucGXVH3RcISTg/KcZ0kHgsdmxmI65SehyX1pah3VlZ4C0iihVDyAejd0rfsgwoO/cyXHsfBQAEnJ1gaUr2SikBVE+/W75fjxBUf/HztxHOdFCghlJ434txZmGl1YQPXNqafAHNxRNBWd9r+MGd74ZZEZQJL6Zo1mMBfReKa/WOvOHp53FnggjaKfV5kbGO9siMT/39mSODeObIEO7fdQaPHOzPawJ1JlBzSZZ0NlXh+rWNMBpANdcJqLKaYDQwhCUe5zzO5th5rLCasGlFHV49M45dJ0fjAl5EWE5dhQWN9vz27i0W6iossJgMCIQkDLp8uO+ZE+r4iz6lpzCXiLLVdCWrgDyuo6OpCofPT0e5ygBwamRW/QOvndVIFC9fumktaios+P3Ll1xU36WMsUoA3wDwIQC1ALoB/D3n/FEd6zYA+EcA7wNQDuBtAH/LOX8xf1tcePSezN65qQ1PvfSa+ju36LuQVCoJoHpPIN/sm8SVK/LTR6wnIMXA9A2gL+b3PdOZhYAcIJNv3P4Q7GUmdLXY0T08GyXgzUYG0+nd6Nv7KHDl1qj1Kq0mVB79BXpMy1C99cOA0Zx0PctYN9zt16XslTQbGW7c0IS95yaSX0TgHFIogOo3HkCwbhU87deBGYxZ9TAnQrz358bc+PSOVQXrm48Nr1rf4sDRQRdcniBsZgMABl8wrN53ZGAa+89Nxu2/VHzt18fw2Z2r8LlrVxX07yWJxyz58BXL8OErFscoh3zAGEN1mRkTc4G4wBxtiUFlDpxHANjR4cSrZ8ZxYcqLs2NurGqIDBkXzuO6FvtFdXI6HwwGhmaHDX0THjxzZAgXpiJl2vnogRRlq+nCcgTrW+2yeByaQVjiqlupdZmpRLk0WNVQif932yWF3oxC8ASAKwD8NYBTAP4AwCOMMQPn/KfJVmKMWQG8CKAawN0ARgF8FsBzjLHrOecv533LC0S6k1nOOZgUwtVrnHhKc7te0ZkuibtYsOlMKj3UP427Hj6U83CRdIKKcw7Gw7jtyhV47I3zaR9v2OWD2x8qyrCsTNNknzw8gPd0NeXttSQdiSGF4O0/ijrfAP71m1/FX/3hfUkfQ5SCL8coAs4ODI5OoqWhNm490StZffWdSR/LWWnFV399LLX4UdzM+pALpoFDGBoZS/mY2ZKv4z0Vbn8I+8+NZywCs8UfkvCd508BAP70utV5fa5UUNkqkTdEaE7sVcVcpq0KtLPhtKWr3kBYLW1c30olq5kgUoS1whGIjO/IJZk4j0Ck/NgTCEf1PQqXucxsxIp6KoEkihPG2E0AbgBwF+f8PzjnuzjnnwTwPIBvM8ZSqYNPAFgP4EOc84c5588D+H3IAvQf873thSRl8IdScVLWtzfuxN0y1g0p6E/Z82g2Mly5ojbXm5xTRKnoIwf7dK+Tj3CRdIKKMQYYTHI/cziY9u/FnjPjBe0fTEWmZYL5LsNNVkILZkTZ8kvBLZW6hash5INt6G249j0G29DbCdcTvZLJ+isHXb6Ux4LZyKJKyLWPmbb/MgtycbzrCUbS9sH+16u9ODY4k3fhqOX7u84UtISVxCORN8RV3Ni01eiy1dyIx3ZnBZbWymJn96lR9fbu4Rm1bIbGdGRGbIpwW52ccirGd+SKsMQx4RbOo77wKe2+PKYpXRX/72yumleIA0HkmVsAuAE8HnP7jwC0ANiUZt2TnPN94gbOeQjAQwCuZIylaIQqfZKezEohTO95CLa+1+LW0ZM2+YFLW4vS+dIihEMoi9axXAbT6D1p9QbDKOvbK4vJNAIyWf9goRNOs0mTzVcZbkrHlzFwzuFt25rz96is7zXc/5HLU/dKxsA5B6QQvv37l6AswWdSV//lPMg0TMftD+GFE8P4xtPH8emHooORPvPQG/h/v+1WHlPuQbzvmROJRfwC4Q9JePboUEGeG6CyVSKP1KjOY+LAHIvJAKspN4OCxcy4n+zrw8GeSbUERissKCwnM7Qpwktry/CFG9bg7kcPA5BH1eRq9uPEnF8V+HqdxzWNVWpP7bFBF37vkhaEJY4TQ/L+pgsFRJGzHsAJRfRpeUdz/94U6+5JcLtYtwtA0svuSr9kbKxtOwB88WeH4WiZiV9JJ0PrPozGlvdiqFr+rm1seS9mquy456ljmLn0I2hsvxkzVfJnU/w/m/uCVXasrK/AmXN98AeDsJrNYEEPbG2XYLbq6oTr2WZnYPBOg5dVQ3u6xwDUVVpwZGAaRzVl78VGWOI4PeJOv2ASgmGOr/zqSFQSerbbMTyjr3Vhz5kxBGqWIzg9ArPDCfndTo9wj36llGZq99d/7elBXaUF9ZWWBSlLDEscDEAmEuG3x4fx9oXpnF/AnPIE0ju+RjO+8qsjOf28zVTZ8e3fdiNYvyYuUyLltjAT/v65E0kf8zvPn4RksiU/PgIehMNhGG2VGfdHijCdh/b3qceLxOW0/1CYw2AAwBnCkgR/SMKcP5x0H4ckRM2GLRb+7aUzWTusrsFz83puEo9E3nCUCecxpmxVuRJUleOrvEI8BsMcPz3Qhz++pl0Vj5VWE9pihskTqdGOuvibm9ah2RERk4MuLzYsyY0YH52JzHjU2/NoMxuxuqES3cOzODYg7+Oe8Tl4lDmfdKGAKHLqACT66z2puT/Vuonq4vSsCwB3AfhqojveueCCxT+Pkjv7MtjsgPhE2+xACMCJoVmgpg22Gvl3AOr/s73v1IgbqKiDGYBsxNXBVr005XqJDDsOYNwdwLi7eENbcsWwy49hlz/9gjl8PtS0IdtYvEACoVQK+2vGG8KMN3uhP1/E+57zzxtjOuV/ZtuS9PiwlGO+9kIpHC/ZcmHaiwvT3vQLJiAwNr8LZSQeibyhOo/exM5jrkpWBVetrke7swJnx+bwvRfP4JaNS3BchOU022lgfIa875JmHOqfQlttOX6nqzHqy3cwyy+sRIy5NeIxgzTcrhaHLB4HXeCcR4flkHgkip9UZkY6o2M+696P+HLZdgC/etcSBxwtuev78wRCCC1gH1A2nD5+FO7ZGVRW2bF63fqo3wEUzX2SzQGprHper7XBbsFk3+mstuXkufPy83OuywWqr7TEVZKMzfpzchLPOQcDx5omO851H0v7eirs1eDmcviDIVjNJqxa2ZbxepbyKsBSrt+BVN4ng3caHSuX5uYYsFRCqkh3bQhocljn7TDHku2+y+W25Or4WQwwBly2tBomY3bdhy7rNOZT9ErikcgbIjDHEwjDHwqrJaqi5zEXYzq0mI0GfOV96/DxH72OWX8If/9sN04MzwKQk1aJzLCajPjmLRvU3+sqLLAYDQiEpZwmro5pnEdnpb6eR0AuTf3Fm8CUJ4ghl08d22EyMKxporAcoqiZQGKHUCi3VPbffNYF53wUckKriihD+6cPXYqurq5Uq2fEsUEXZrzFE36SiM/+9Es4e3AvWq7cir/7y19H/Q6gaO7zNV8KT+dN83qtU3NBmKd6MfL4t9G09VoEnJ3wjU2i1lmLT336/fjyrsfU3y1j3Ti79yW0XLkVn/r0z/BnA9O6ShbNRpY07fLF7hE8sKdnXq8BEMcrw/Y1DRh/9MtJ37+7fvoljJuWwaaMpBAudc/4nPo+6F2PAzAZgHctqYY/JKVP1lR6ECVrJT51TTvumecx0LT1Wvgb18PTfm3KMRdmI8O979+Q8/7dbPZdrrdFJM3+8q3s+n4XE5+/fs280laPHbPjt/dk//wkHom84dBcbXJ5gmiwC/GYH+cRkFNXr+1swEvdo/jFm5EZVNQDN38MBobmanl8x0AOncfR2YgQ1dvzCMSH5ogS5VUNlTnrpSWIPHEEwB2MMVNM36O4WnM0zbobEtyuZ11Cg9sfgq/5Uji2LoPPWVtUKZ+x6Jm5l45gmCO4cjta/ngNph0NgMGI6k7AA+DPHjsMdN6k/u5ZfQMcaICndSm++LPDgMGYtmTx6tX1+OiW5UnFwqYVdfjx3t6chYyMpum99LVtQ/XK7XFhLOJ9aPhwNXy+AVjGunWtF5KAN/uncdvlS/Bn16/BT/b2Ys+Z8aTPL/r+vvCzwzCu/yAcJvk4i32+VHAAjq23Y1oRsun2Qb6Cn7LZd7neFsYYbr1sCd7T1YR/f/ksDvVN5eyxSwWryaDOeSwkJB6JvFGjSSmb8gTRYJddJbciHvOVbPc3v7sWr5waiyqXojEduaHFUYa+CQ+Gclm2qozpqLKaUGbRL/q0bvLRAZcadkH9jkQJ8EsAnwTwQQCPaW7/GIBBAAfSrHs/Y2wT5/wAADDGTADuBHCAcz6Yn01ePETNytMIprsePgRT2zbgYLKsosKhZ+ZeV4sdJ4dn0roy5ppmHU9oQvXVd8IH6E6LabLbUv5dr7Sa8IFLW/H4oQtJl8mEp44MwZJkf7n9IXiXb0vplpYtvwQeXKIKZR7q17WemOXY5NBXKSNxQHJ2oNrZESXMxfOJCxjexgaAMVVkuv2hpEI2Fq3jmw8y2XcLsS1fvGFN4nmXJYqRAZ3NdmxdWYeuVgeODc5g2hNAmdkIMKCm3IJmhw03rm/OKgE415B4JPJGdVnEedSG5uSrbFXQ7qzEx7cuxwOvyiUWFpMBqxqojDEXNCsJrIPTuStbVWc8ZtDvCMjHz/K6cvROePDCiRE11Xd9K7nMRHHDOX+WMfY8gB8wxuwAzgC4A8B7AdzJOQ8DAGPsvyALynbOuRju998APgvgccbYX0MuQb0LQAeA6xf2lZQmYuRFLMKRcmw9D4T6C7BlqXHtfRTNrUsRWr0j6oRZe7L+7NFhPLhf/xzIpGThblbr6G0TgiIXJ/1hicObZH8d6JkADCZ9AS9CKJ97Wdd6YpZj1ifxyvO55sZx18OH1AsY4pJs9Wr5YsanH3wD4RVXpxSyBgbcubkNV6925n3UTLJ9ZzIAlyytwcr6ClSXW3Dlitq8b4vWhdxzagwPHehDMbRXpxOB3kAY1eUWdLXY1fsSvWeN9ugLExuXVcNmLp6KKhKPRN6o1nyxaucC5rNsVfC561bjl28NYGIugLVNVTBn2VRMRNOqzH4cnfUhGJZy8r4K51Fv0qqWrhYHeic8NJKFKEVuBXAfgHsg9yt2A7iDc/6oZhmj8qOeOXLO/Yyx6wD8I4DvASgHcBjAjZzzlxdo20uWlLPyAIBz2DffBmn/92EI5e4iWa4o63sN//C1L+Jgz2TCE09fMFyQ7TIbGa5ckT5sSXvSf+DcBPadm8CJoZnsT/yT7K+MBqhrZiSKv0fpmPYE8J6upuzKcBUhKFXUQ0qxbpgDYIaUQlbicj7BQswo1e67ZMffQlNpNeHGDc3wBsM5c7SzoavFjq3t9WlFoJZU9xU7JB6JvKEt6RABK5LE4Q7I4tGeR/HoKDPj+x+5DPfvPovPbG/P2/NcbDQ7ZPEocWBkxoclNfMff6I6j1WZf5Gua7Hj6SPRmWFrm6vmvU0EkW84524Adys/yZb5OICPJ7h9BLIjSWTIgZ6J1Cf7jMFgtiLg7IBt6O2F27AMqLSacG1nQ8L7ClXSlml/W6XVhOvWNuK6tY1w+0PZ97Al2V+Zvg9iRuKkzjTP6nJLzstwsyV2HFq+SXX8FQrhiuYqTMfIgI6mKpSZjXhnwJX0OyNVQNRihsQjkTfqKiywmAwIhCQMueSCDHcgpJbu56tsVbB5ZR02r0wfa03op6VaM+txev7ikXOuBuZk5zxGl6guryvP+3FFEETpoteR4pbSbHXIdShNOowGhls3zq+/LVUPm4FBlysZu7/WtzgAKQzODBmd1NdWWIBwENxgSrqe1mUVr/uJNy+gUK13esqFFzvzDdNJVXrr9odUpzW2/LSQrmshufheMbFgMMbQ4rChd8Kj9siJsBwAqMyj80jkhxalbBWAekFgPrj9IfiC8mXCTJJWBbElql0UjEQQRAr0OlIsULgh7/NhId0wIwP+6bZLclJ+l6wk0hcM6+rh1O4vb9s2/MXP39aVEBuLzWyAebIHQeeapDMttS6r2O5tq+rxxcffTj2+Iw/oLRe+WEh1IUIrEDMRgcXotBYaOnsn8kpLdZksHhWhMasRj/nseSTyQ7OmFDkX4zpGNf0l2TiPziorGu1WjCizImkkC0EQqUjrzHEOKRSAZezkwm5YDsllKE0qbr1sSc77tmJP1N3+EB59vV/3/nJsvR3elduRrQ342BsXAOca+ZcY4ZgqRbTRbsOtGxe+hDVfozlKmWLszVxs0LtI5BXRIzc4LcRjpGSIygtLjyqbGVU2E2Z9IQzlIHF1dEYrHrM7CelqcWBkZlT9P0EQRDLSOnOMYWb/46gvwrAcvcSePO89Ox4VKjZf8j2KQUsm+0sy2eDY8qGkjuF8uLytBp/e3p5SfCyUaAdyUy682CHHMH+QeCTySqvSIzc660cgJJHzuAhorS5D9/CsekFgPoy5I+Ixm7JVAFjfYsdL3UI8kvNIEERqUo0cYCOyg+VrvjSjYe75RDLZEHB2wrE1Mv9Pj4MiTp53djgTlvHFjhV4cH9fyl6xZImS+Ubv/uJGM5gpff+f3j5KLe9cmE67TKxon5rzo2fCg7fPT+UkxEWQy3JhgsgGOnsn8kqz0iPHlXTOWb9GPFL5QEnS7LDJ4tGVC+cx8hjZlK0CwB2blmH/uUlsWlmL+srsHoMgiIuHZCf571yYRjDJMPdCwCGXYU5v/TBgNKO6U57/d9fDhzJKeNRbxpesV6zQiZJ69xckfWNKNrQ68PYFV0bbIGY76nGyEpXeZp0mm4B8lAsTRCbQ2TuRV7QBK4PTXipbXQSIfZpL59FsZFFzQTOh2VGGn316y7y3hSCIiwtxkv/EmxcSn9hrhscXAl/bNlSv3A41olwhGOZqGeetly3R/XjpyviKvVcs7f5i+uYOm7KcT5ztSIxMQ1w8/lBEHCcR8QRRSAr/bUAsalpiZj1S2WrpI8SjyxvEnD+EinmcVIwpPY/OSutFNSOJIIjiwO0P4cnDA4nvFMPjl29Dz7gbvuZL1dLRfJe0uv0heJdvA+c86Xfjk4cH8J6uppwLu2LuFdOzv5jy/0SYjQzrmu1ZuYDzGYmRjTDXjogoJhFPEHQUEnmlWeM8Dkx74QnI4tHAgHKLsVCbRcwD7azHIZcXqxqqsn4skbbqpBIcgiAKwIGeiZThJowxgJnw5V8eBTpvUktH813SeqBnAjCYUo6ayKSUcrGga3+l4AOXtuKaNc7UCa4JyNVIjEyEeTGLeOLiJjvvniB0Umk1wVEmlyMOubzqnMdKa/IBvERxIxJ0AajzO7NlbDbiPBIEQSw0Lk8w/UKJECWtbdtyu0EKercr21LKUiXb/WU2Mtx2+RLcsrFVTXDNBBqJQRAR6JNA5J1mhw0ubxCD0z5UK0KS+h1Ll9aYPtZsGXf70Tc5BwBotJN4JAhi4XFk2WutlrS2bYVbEwSXK/Ru13xKKUuRTPeXgQF3bm7D1audUeJP71gN6jMkiHhIPBJ5RzvawaC4jdTvWLo02m1gTM5wmE/i6j/97yn4gnJ++Q3rGnO1eQRBELrZtKIOP97bm9VcPsYYYDRjz6mxrJ7b7Q8l7aPctKIOD+w+BW5IXqWTq1LKUiLT/SVxwGoyxrmGyXoQu1rsODY4Q32GBJEC+kQQeadZ6ZEbnPaqJax2ch5LFovJAGelFaOz/qydx2ODLjz6utwrtH2NEzs6qK+DIIiFJ+0Qeh08dKAP1rZtwMG9utfxtm3DXQ8fQjBJH2Wl1YSyvr3wirTVBALyYiylzGZ/pSrtTdRXSGMwCCI11PNI5B2RzjnjC2FEmetXSc5jSSOCkIZcmYtHzjnu+c1xcA6YDAxfed/aXG8eQRCEbm7Z2IrbLl8CY5Zt+BIHvCu3w7H1dl3LO7beDu/K7fHuWUwfpa3vNUzveQiQostitf17FyOZ7q+LrbSXIPINncETeadFE7DSN+kBQGWrpU5rtQ1vn88uMOfZo8M40DMJAPjoluXzSmslCKJ4MRlK4/q0KGHctqoeX3z8bYSlzEtYwTnsm2+DtP/7MISSfy9KJhscWz6U2E2M6aNkAFx7H8VyjOK2L/8blVIqZLK/LsbSXoLIN6XxzU6UNC2agBUx65jEY2kjElcHp73gXP+Jli8Yxn1PnwAA1JSbcfd1q/OyfQRBFJ7qbMNoCkSj3YZbs3XzGIPBbEXA2ZFysYCzE8xkSTqHMFEfpSHkw7WdDbj1siW4trPhohaOWvTsr4uxtJcg8g19ooi80+yI7x+gtNXSRlwQ8IckTMwFUK9z1MYPXzmHAaVP8ovv6cg+6ZAgiKKnptwCYK7Qm5ERelM4k8EtlWnur9D1OA/u74Np/QfhMMlhOm5/iERQApLtL0pJJYj8Qd9ERN5pckTSOQX0R7C0aa2OXBAYmvbpEo/DLh/u330WANDZVIXbr1iat+0jCKLwWEwGVNlMmPXlfpRFvkiWwjnjDeKxN86nXz/gTnqfZLIhXKavhJIDCDo7UO3sgAfAXQ8fUsUQzUiOkGx/XeylvQSRTxb0k8UYqwLwFQCXAtgIoB7A1znnX0uy/GUA/hHAZgAhAC8B+HPO+bkF2WAiJ5iNBjRUWTEy41dvs1PZaknTrOljHXR5sWGJI+06//BcN7zBMADg725eB5ORquYJYrFTU2EpKfEo+P/svXmYZGV59/+9q6ur95nu2ZiNfZA9bEHcAYUIiAKiMfrTgHlF/WGixtdXo9HgmpD4qolGNAkimigqsooIso4gKAIzLAMDzMAw+0zPTE/vtd/vH885p55z6pzauqqruvv7ua66qvts9dRzTp3n+Z57C2bhHEtlceOardHWSFXks2kkBp8rXgWTJGf/a94FtNXmbZHJqZdh9O0nr6zpGLOZsKyphJDGMN2zt4UAPgigA8BXOMqAAAAgAElEQVTNpTYUkaMA3A8gAeDPAfwVgFcAeEBEFje2maTe2HGPAN1WZzr2+aykXMfjm4dw05ptAIBzjl2K1xy+qGFtI4S0DgOzxDXdLRERiQhGfn99aLKc5MGvRf/r3wvEpv7Q9Oa12zCWmnlinBAye5hu8fgygAFVPR3AZ8ps+yUAKQDnq+rtqnojgLcAWAzgk41tJqk3dsZVgAlzZjoLexJIOJbDHcOlM67m84ov/vIZAECiLYbPnsfSHITMFboTcXS2zw4vA7dERHugRkR7m6DrxdUYfuinRfuMpbKYPOS1JrFYHdxNMznFI062akIIaQbTOoPXCtMyikgcwPkAfqSqI9b+L4vIfQAuAvDpxrSSNILl/f6kObQ8zmxiMcGy/k68vHfCS4ATxU1rtuGJLfsBAB94/aE4aGH3dDSRENIiLOhJ1FTWp9UoFV/36fd/NXSfP7y0F4jFUc8oxVJF7wkhpNG0qvnncABdAJ4MWfckgLNFpFNVQ0cjEVkCY6EMHpM0iWUByyMD2Wc+y+Yb8bijhHgcT2Xxz3esBwAs6evA5Weumq7mEUJahIFZIh5dwuIhk8tOxPzXmMyoicH13rrhiUzdP59F7wkhzaRVZ/ALnfcw34x9AATAAIAdEftfDuCKBrSL1EhxzGOrXnqkUtxzWmpSeNX9G7B71CRK+tQ5R/GhASFzkL6OONrbpKbSF62MquKmNdtMmYijzkP/UcAEgIkjzsZ8LIFmN9e9HBGL3hNCmk3NgQgicoaIaIWvE2v8mFIjTal1VwE4LvC6oMY2kDoQdFudR7fVGY8bx7p7NIlMLl+0fsu+CfzXAy8BAE5YOb/24tuEkBmNiMxKa9lNa7bh+sdCMrDG4uh//XuRPPi1OO3QhUAug1JROzFBURxlFCx6TwhpNlO5Az0H4LIKt91c5bH3Ou8LQ9YtgBGO+6N2VtXdAHbby1gXqbkELY+9tDzOeNxzmldg10gSKwf8sYz/ePuzSGeNqPyHtx6LWIy/QULmKot6ExgcTZXfcIYwlsri5rXbwleKQFUxefBrAABdLz+EycNON8WOQ+YiF1txlEPjKby0dwJPbt3PoveEkJak5hm8qu4AcHUd22KzEcAkgOND1h0PYENUvCNpTRb2JJCIx5DO5tGdaEMbhcSMx7Ym7xj2i8eHN+7Fr5/eCcBkKDzl4IFpbx8hpHXo705g5UAXtg6VL+0zE/jDS3tLuuGKCNDWjkde2ofOl3+HHdu2oD9Q59EWhCJSFEfJoveEkFakJe9EqpoVkV8CeLuIfEpVRwFARA4CcCaAbza1gaRqRATL53di094JxjvOEqJqPebyii/+ch0AoKu9DZ8+56hpbxshpPU4cEE3Mrk8do3MfAtkpYlwdo8kkVp2IjC4D10b78M7L7kMk+lcWUHIoveEkFZl2mfxInIugB4Afc6iY0TkHc7ft6vqhPP3FQD+COA2EbkSQCdM7cc9AL4+jU0mdWJ5f5cjHhnvOBtYNr9gebTLddy5bifW7xwFAFx+xuFYOr+zaF9CyNzk0EU9yOYVe8dmdrmJShPh3PbkDuScZDqTAK57ZDMuPHEFzjxyMcNpCCEzkmZU7v0ugOsBXOP8/07n/+sBeI/ZVHU9gDMAZAD8AsC1ADYAeIOqDk5fc0m9uODE5WhvE7z1T5Y3uymkDvR1tntW5B1WxtU/bjJJkhNtMVz2hsOa0jZCSGsiIli1uBeLemd2Ap3TDl1YUZKbXCBRTianuP6xrbhpTUS8JCGEtDjTbnlU1UOq2PYxAGc1rjVkOnnXqQfhwpNWoCPe1uymkDqxor8L63eO+txW120fAQActawPne0814QQP7GY4IgD+rC4L40X94wjlSnO1tzq9HbEceGJK3D9Y1tr2v/mtdvwZ8cuZRwjIWTG0QzLI5nDUDjOLlzX1e3DxvKYzyuedcTjscvnNa1dhJDWp787gRNX9mPlQBdmYg61i05agXeeshLxGmZSmZzikZfCSlkTQkhrQ/FICKkZN2mOa3ncMjSB0VQWAHDM8vlNaxchZGYQiwkOXNCNEw/qxwHzOsIqWbQsIoK3n7wS737lwTXtv39iZsd9EkLmJvSXIITUjCsehyczGE9lPZdVgJZHQkjldMTbcNjiXizv78KO4ST2jKWQLVEKo5VIZnI17dffPbPjPgkhcxOKR0JIzfhrPU7i6W3DAICYAEcvpXgkhFRHZ3sbDl3Ug4MXdGPfRBqDoymMpbItLSQrzbxq094meOWhCxrQGkIIaSwUj4SQmlk+3671mPQsj4cv7kVXgvGthJDaiMUEi3o7sKi3AwCQyuYwmc4hlc0jl1fkVaEK84IRlqowywGoKnJ5U3c2l1fkVL39cnmzb7047dCF+OFDm5CpQuBeeOIKJsshhMxIeOcihNSM67YKmLjHdUyWQwhpAB3xtoYlXFNXiAKeuMzk8sjmFJl8HumseWVyav7O5ZHJ5T0BWk3m1fY2wYUnrsBFJ61oyHchhJBGQ/FICKmZA+Z1QsQ88X9i637sGUsBAI5lshxCyAxBRLxEPW0QtLehbJkhVUU6l0cyk0cyk8PlZxyO9ngM1z+6xWeBjMeAEw4cwGGLetDfncArD11AiyMhZEbDOxghpGYS8RgW93Zg92gKdz2z21tOyyMhZDYjIp41dH6XiXn8x4uOx8fPOgI3r9mGLfsm0dneRrFICJl18I5GCJkSy/u7sHs05VkdAeAYikdCyBxkSV8nPviGwwGYLKy7RpIYHE1VFQ9JCCGtDOs8EkKmhJ1xFQBWDnQxBT0hZM7T2d6Ggxf24OSDBnDk0j4s6EnMqDqWhBASBi2PhJApYWdcBeiySgghNrGYYEFPAgt6Esjk8tg/YerijqWymEjnkMvTKkkImTlQPBJCpsSy/qB4ZLIcQggJo70thsV9HVjc1+EtS2VNCZKUk3wnmclhIp3DZCZX15IihBBSDygeCSFTYkXAbZWWR0IIqRyvDIn/Vop8XjGZyWE8ncVEKodkNodsTpHNK3L5fNFxbKEZpjlNXUz11lOYEkJqgeKREDIllgcsj8etoOWRkHKISC+ArwD4cwALAKwHcKWq/rSCfS8F8IOI1ctUdWe92kmaRywm6OmIo6cjDvQ15jPcGpeAKyj94lJhrQ/87ztO2HFREKyqpoameusrbF+YDPa1t1Cb0xXV6awim897tTrpFUxIfaF4JIRMiWVWzOOi3gSWWO5YhJBIbgRwKoC/A/A8gPcAuE5EYqr6kwqP8X4Y0Wmzt35NJLMdu8als6RZTWko+bwi5wpjT3z6hXDO2UbzQE4VedWI/SpDg/tZ4tsV6kbYFpblHaEdFOrechSEuX1s61MLx8pTOJPGQPFICJkSC3sSSMRjSGfzOGb5fAjTCRJSEhE5D8DZAN6jqtc5i+8TkYMBfE1EfqaquQoO9bSqPtqwhhIyS4jFBLFZKoxLoY5VNm9ZaI0oNuI0rwErMQpW4ry6ArRwDFuclv9s5906ZlAYB63d9n6wllYr3INtsPuj+OjR25NwKB4JIVMiFhO86rCF+O3zgzj76CXNbg4hM4GLAIwBuD6w/AcAfgLgNAAPTXejCCGzCxFBvG3uiebpIChEG0mrPZSneCSETJn/+stTsGnPBF5xQG+zm0LITOA4AM+qajaw/ElrfSXi8TYRWQxgGMD9AP5BVZ8utYOILAGwOLD48Ao+ixBCiEOrCbrphOKREDJlOuJtOHJpgzI6EDL7WAjgxZDl+6z1pdgJ4KsAfg9gBMDxMLGTvxeR16rqEyX2vRzAFdU1lxBCCDFQPBJCCCE1IiJnALivws1PUtW1zt+lfJ5K+kOp6h0A7rAW/VZEfgXgKQBfAnBBid2vQrG77OEAbin1mYQQQghA8UgIIYRMhecAXFbhtpud970Ity4ucN73hawriapuEpEHAbyqzHa7Aey2l81l9ytCCCHVQfFICCGE1Iiq7gBwdZW7PQXg3SISD8Q9Hu+8l4xbLIEAKK4eTwghhNSJWLMbQAghhMwxbgLQC+DiwPJLAGwH8IdqDygihwJ4LUwcJCGEENIQ5pLlMQEAGzZsaHY7CCGENBDrPp9oZjuiUNVfi8hdAL4rIvMAbADwbgDnAHivXeNRRL4PIyoPV9WXnWV3A/gtTHZWN2HOp2BiJT9fQ5M4PhJCyBxhqmPkXBKPBwLAhRde2Ox2EEIImR4OBLCm2Y2I4O0wGVO/BBPruB7Au1X1p4Ht2pyXHZj4FIB3AfgkgC6YGMZ7AXxZVZ+voS0cHwkhZO5R0xgp01nkspmIyHwApwPYAiBd42HcjHQXANhYp6bNBtgv4bBfwmG/hMN+CaeWfknADIqrVXW4UQ2bLdRpfAR4DUfBfgmH/VIM+yQc9ks4tfbLlMbIOWN5dDrn1qkcw8pIt1FV1025UbME9ks47Jdw2C/hsF/CmUK/tKrFseWox/gI8BqOgv0SDvulGPZJOOyXcKbYLzWPkUyYQwghhBBCCCGkLBSPhBBCCCGEEELKQvFICCGEEEIIIaQsFI/VMQjgi847KcB+CYf9Eg77JRz2Szjsl5kDz1U47Jdw2C/FsE/CYb+E05R+mTPZVgkhhBBCCCGE1A4tj4QQQgghhBBCykLxSAghhBBCCCGkLBSPhBBCCCGEEELKQvFICCGEEEIIIaQsFI+EEEIIIYQQQspC8UgIIYQQQgghpCwUj6RlEZFLRURF5NJmt6UcInKI09Zrm92WWijVfhE5QkRuEpGdzjb7rXVLReSHIrJVRHLO+v5pbXyTEJEvON/3jGa3hRBCSOsgImc448MXGvw5HIfItEPxSEIRkYUi8gFHNGwQkUkRGRaRB0Xkf4lIy147IhJ32vgbEdktImnn/S7nO8Wb3cZGYIlt+zXmCLu7ReRLInJElcdsA3AzgPMA3AZTjPZKa5NrAbwPwGoAX3HWJ+vxfQghhEwNEfl7azw4so7HvV9EWCi8wcykh+hk7jArJ9GkLrwTwHcB7ABwH4DNAA4A8HYAVwM4V0TeqaotNXiIyEoAtwI4CcAuAL+C+Q5LAZwL4CwAl4vI21R1a9Ma2liegBF8ANAFYAmA0wB8HsDfi8i3AXxSVbPWPtsAHA1gOHCsQwEcA+C/VPWD9goRSQA4G8Ddqvr/1f1btD7/DuCnML8NQghpKUREAPwvAApAAFwG4JNNbRSpNxyHyLRD8UiieB7A2wD8SlXz7kIR+SyARwBcDCMkb2hO84oRkW4AvwZwHIAfArhcVScC668CcAmA20XkVfb6WcRaVf1CcKGInAljKfwYgE4AH3bXqWoGwPqQYy133reHrFsK470Qtm7Wo6p7AOxpdjsIISSCP4N5AHgtzMPTS0Tks6qabmqrSN3gOESaQcu6HpLmoqr3quovbeHoLN8J4HvOv2fY62z3ChE503FrGRWRERH5lYgcHfZZIrJKRK4XkSERGReRh0TkLTU0+xMwwvEhAH8VFIbO/3/lrD8ewN8G2nG/0/6EiPyDiDwnIik7DlBE+kTkG44raFJE1ovIJ1DityQi3SLyGRFZ63y/MRF5WETeHbKtFychIq90+m2fs+yQGvrE/v73AXgzgDSAD4rIydbnFsU8Oi5Jq51/r7Bcn74gIpsAvOysu8Ra5+3vHOPdInKfc26TIvKsiHxORDpCvrs652CpiFwtItvExFFeam1Ta1+e6PTlfhGZEJHVIvKasH4SkTYR+bCI/E6Mq/akGNftq223X4mINbG+xyIR+U8R2eFcR+tE5P0Rn9nhHO9FZ9uXROQrznIVkfvD9iOEkBJc5rz/F4AfA1gE4KLgRiJybdQYI4HYPXesAHC6878dJnF/YN9TROQGMWEjKRF5WUSuEpFlYY117u+fFpFHxcwdxpwx41sickBg22Ui8h0R2SQmNGVQRG4UkVNCjmvPTc5x7s/DYrnd1nv8icLpk38TkSfEjO1JEXlBRL4uIgOBbe8H8APn3x8E+voQZ5vImEcReZOI3GF9zvMicqWIzA/Z1p3/xEXks06bUiKyRUT+WYynESEAaHkktZFx3rMR688HcAGMFfB7MG6P5wE4VUSOcZ6UATDJWAA8DGChs/1aAKtg3C5/XWW73IHyK0HR66KqeRH5Kow76wcBfDVksxsAnOp8/s0Adjtt7QBwj7PuCZjBuB/GHfT0sM8TkzzmXhg32scBXAMjNN8M4Ccicqyqfi5k11cD+AyAB519FsGIvimhqutF5OcA3gvg3U6bovgigENgLLWrAdzvLL8fwH5n3cfgd5Nd6+4sIt+HEetbAdzo7PMqAF8G8CYROTvgOgsACwD8HsCYs08exv14Kn35pwA+BXOdXQ3gIBjL+T0icqKqPme1OQFzbZwFYAuAnwAYcb7rRTDn44USfebSD+B3MOfsFzCW3ncAuEZE8qr6Q+szBeaae4tz7H8H0A7gUgDHVvBZhBDiwxFbbwPwvKo+JCIjMA9YPwjgZ1M49H6YseFSAAc7f7tssj7/fJj7msDcA18GcAqA/x/ABSLyWlW1tx+ACZE5AcBzMPf3NIDDYcaRG1EYCw6FuRcvhxkTrgNwIEy4zVtE5GJVvS2k7e8AcA4Kc5NDAusbMf4EuQxmLFkN4G4AbQBOhjk354rIaao66mx7LUx/XwDgFljjq7M8EhH5EEzo0TiA62HmMWcA+DSAtzr9H3aMnwB4PUwfjcDM3T4FE/4S+vCTzEFUlS++Kn7BPHB4CiaG4s2BdZc6y7MA3hRY90/Ouk8Flv/GWf6xwPILnOUK4NIK2nWgs20GQFeZbbuc7RTASmv5/c6yJwEsCtnvs876GwDErOWHAtjnrLs2sM+1Ed+7E8AdMIPTidbyM6zv/aEqz82lYW0I2c6NgVltLTskov1ue74QcpzQfQJtuTF4PgB8IeKcu9/7RwDiIcecSl9eGtjnQ87yqwLL/9FZfiuAjsC6DgCLQ77HGRHf42oAbdbyY2B+G88Etn+fs/1vASSs5f0wrsQK4P56/Yb54ouv2f8C8HfOveMz1rLHnPvkqsC27r31kJDjhI4BcMbLiM/uhXGlzAF4fWDdp53j/Saw/CfO8u/CGl+ddX0A5lv/3+ls+/eB7V7j3GP3Aui1lrvjUR7AORFtbtT4E+y3g+1xwVrujsufDix3235pRLuLxiHnM1Iw4u+owPZXOdv/Z9j5dK6RBdbyHgAbnHO5tNnXNV+t8aLbKqmWK2FcQ29X1Tsjtvmpqt4TWPafzvsr3QViktucDeAlGGuLh6regoLLZCW4bjB7VXWy1IbO+r3Ov8tDNvm8WtZRi/fDDBCfUsuyqaovAfhWcGMRWQhj4XtUVf8l0IYkzCAqAN4T8llrVfU/Sn2PKbDNeV/coOMDxiKZhXEfDp6PL8P0f1iSnTSKk/lMtS9/p6rXBpZd47TPvh7bAFwOYBLAh1U1FficlKoOhhw/jAkAn1DVnLX/MzDWyKNFpM/a9hLn/XNqxSKpeSr85Qo/jxBCAHjeDB+AGa9+ZK26FuY++YEGN+ECGG+in6nqA4F1X4exUJ4tIgc57V0C4F0wye0+qcXhMqOqOuxsuxImlnMzgOBY8BCMFXIBTE6GILeo6h0l2t2I8ceHqr5sjwsW18CIvTeXO0YFvBdAAsC/q2owl8HfAxgF8D4JCR+BEa/7rPaOw3hZxWC8eAih2yqpHBH5KID/DWMNeV+JTR8NWbbFebd9+k9y3h+MuJnejwh30LDmOe+VZn8ttf0jRRubyf4qAFtUdWPIPvcDuCKw7FQYl5SoWk/tzntYLGhRG+pItX1V3cFNYqITYJ48f9zMY4pIIfx7b1LV3SHLp9KXRdejqmZEZBf81+NRAOYD+IOqTjUJ0AuqOhKy3P0d9MMM4ID5HeRhYnGDPDjFdhBC5h5vhHH3vFNVt1nLfwLg/wK4VEQ+ryZRWiNw4+nvDa5Q1ayI/BbGc+UkGBF4Kow4+a0jVkrhzhseiGj/vTDi6ST4hTNQflxtxPjjQ0TaYTxf/gLGG2U+/DkTVpQ7RgWU6v8hEVkD4A0wY94TgU0qnb+ROQzFI6kIEfkIgH8D8AyMS+q+EpsX+dE7AwZgbsAubtD2rojj7KyiiTuc90Ui0lXK+igiXTBPJu39yn1uLW1d6Lyf6ryi6K3wePXCtbZWakWrlgEYgboYxYK6HFHfeyp9GRUbkoX/eux33reFbFstpT4TKP4d7As+7XaIut4IISQKt6zStfZCVd0rIr+Eifm+ACYWsRG442XY+Gov7w+8V3LvrfbYNuXG1UaMP0F+BhPz+CJMHONOmIepAPBxmPCIqVJzH2l4HGTYuEXmMBSPpCwi8nEA3wTwNIxwDHsyVwtuTcEDItYvrfRAqrpZRLbAxD6egdLJds6AufY3a0itR1UNs8jV0lZ3n2+q6idKtCeMhlgFHc503v/QoOO733uNqp5ccstior73VPqyUtxBsx5PfqthBMACEYmHCMio640QQooQkcUALnT+vU5ErovY9IMoiEfXTTRsThgmwsrh3q+jxvBlge2qufdWe2ybcuNqQ8cfEflTGOF4N4DzbMupiMRgEtPUA7uP1oWsL9VHhJSFMY+kJCLyaRjhuBbAmXUUjgCwxnl/nRNvFuSMKo93tfP+WYnwlXRu0J91/v3PsG3CUJP9bAOAFSJyeMgmZ4QsewRmUH59pZ/TaETkKJiMdArjwlR3VHUMZsA6VkQWlNu+QqajL9fDTGL+RETCYmEbxRqYe3FY6ZDXTWM7CCEzn0tg4t0eA/D9iNcggLOcrKUAMOS8HxhyvKg4txzgxYoHccf2M4IrRCSOwn3Nzfbt3t/fICI9EZ8XPPbrnGMFcR+OlsokXi31Gn9WOe+3hrjcvhImmV8QN6SnGqtfqf7vB3AigCSAZ6s4JiEeFI8kEhH5PEyCnMdgLI51LUTrWP3ugslW+teBz74Alcc7unwD5mb4OgBXO+6p9jG7YOpdvQ7GivrNKo//A5jfzD87ItQ97qEAPhrc2BHaPwbwpyLy+bCBTkQOtwbwhiIip8NkhUsA+K6qBmMd6sk3nM+5xhmsgm0ZEKvOZDmmoy+duNurYAbw7wWTCYip/9mIJENuXM5X7FpaTi2uzzfg8wghsxc3Gc7lqvqBsBeA/4A/cY4bC3iZfSAROR4m+VkYbtK5g0LW3QyTgfzdIvKqwLqPAzgMwN2quhkAnERkP4WxiP1fe3x12tHr1ia05g2HOMeytzsNJmnNEICbItpdNXUcfzY572cE9l0C4DsR+5Tq5yj+Byaj/N+IyKrAui8DmAfgf4JJ4QipFLqtklBE5BIAX4J56vUAgI+GGPM2hWSxrJaPwNTf+1cR+TOY4O1VMK4dvwTw1koPpKpjInIOTJmFvwJwnojcDhNTcABMvaJlMFbUt6rqRJVt/TqMO9DFAB4XkTthYgveBVNm4W0h+/w1gCNg+vJ9IvIgTBzbcpjg+lNh6i2+VGVbSnGiFdTfAfPdT4MJzs/DCLt6uceEoqrXiCnWfDmAjU5fbYaJNT0UJlj/BwA+XMVhp6MvvwjTV28F8LyI3AaT2OZAmAx//weBOKI68COY5AnnAHhaRG6FScBwMUzygiNRcCsjhJBQxBSKPxLAU6paKjnM92Gybr5fRK6Aib17AUbsrYQJaTgIhfqCfx5yjHtgvFhudMbZSQAvq+p/O2PxX8HUF1wtItfD3P9PgbmP7oRJGmPz1zCZ3D8M4AxnzEjDjBdvhhlf73e2/TBM5uqvOfOGR1Go85gH8H4t1EqsF/UYf/7otPvtIvIQTEK0AwCcC1PbMixR28Mw2bs/7njyuHHw33Yz0AZR1U1OuNF3YOYqP4exNp8OU0N6PUyGWEJqguKRROE+QWtD4OmexWpMcSKtqi84TyavhCnMfgZMncULYRKuVCweneNtFpFTYWojvQtmwOmH8e1/AiaBy7W1ZJlT1ZSInAVTV+ldME9kNwH4CsxTziLxqKojjsXvgzBPRC+GqQu1C2aw/luYp6j15ATnBZhBZwhmsPgFgP9W1Q11/rxQVPUjIvJrmIH+LJjzsA9mEvE1mKej1Ryv4X2pqmnnAcSHAfwljAuYwAzqN6EB2U9VVUXkIhh36vcB+BuYhAY/hLGEXgATF0kIIaVwLYdXl9rIERd3w5TKequq3iQib4LJxHo2jBB6GuY+uw/h4vFqmHqCfwHzMDIOMyf4b+czbhGR18Lc194M86B1J4DvAfhyMKO1kwX0NTDzjXfB3OdzMJk+r4FJ1udu+6ITP/g5mIfCZ8DcI+8A8FVV/WPJXqqBeow/qpoTkbfBzBnOg/FY2gbTl1+B9R2tfYZE5GKYucv7YeouAmb8jIxZVNWrRGQDgE86be2G6cuvAfjHiMQ4hFSEhOcGIYQQ0mxE5GwAvwFwpap+ptntIYQQQsjchjGPhBDSZMIS9DiFqa90/q1b/A4hhBBCSK3QbZUQQprPN0TkBAAPwcSmrISJg1kA4D/KxC8RQgghhEwLFI+EENJ8boRJnPBWmNjQJEy5k2tQJn6JEEIIIWS6YMwjIYQQQgghhJCyMOaREEIIIYQQQkhZKB4JIYQQQgghhJSF4pEQQgghhBBCSFnmTMIcEZkP4HSYIqnpJjeHEEJI40gAOBDAalWNLKRNDBwfCSFkTjGlMXLOiEeYgfGWZjeCEELItHEBgFub3YgZAMdHQgiZe9Q0Rs4l8bgFAG6++WasWrWq2W0hhBDSIDZs2IALL7wQcO77pCwcHwkhZI4w1TFyLonHNACsWrUKxx57bLPbQgghpPHQBbMyOD4SQsjco6YxctoT5ohIn4j8i4j8RkQGRURF5AsR254sIneLyJiI7BeRG0XksGluMiGEEFJXqhkLI/ZfIiLXisgeEZkQkYdF5E0NbHJJhicyuO6RzfjWPS/gukc2Y3gi06ymEEIIaSDNsDwuBPBBAE8AuBnAB8I2EpGjANwPYC2APwfQCeBLAB4QkRNVdXBaWuFNL7sAACAASURBVEsIIYTUn4rGwjBEpAPAPQD6AXwMwG4AHwFwh4icpaqr69/ccFQV3753A75z3waksnlv+RduXYePnLkKf/PGVRCR6WoOIYSQBtMM8fgygAFVVRFZhOgB80sAUgDOV9URABCRxwC8AOCTAD49HY0lhBBCGkClY2EY/wvAcQBeo6oPA4CI3AcjRP8FwGn1bmwU3753A75x1/NFy1PZvLf8o286YrqaQwghpMFMu9uqOpTaRkTiAM4HcIMrHJ19XwZwH4CLGttKQgghpHFUMhaW4CIAz7nC0TleFsD/AHiliKyoRxvLMTyRwb/ft6HkNt+5bwNdWAkhZBbRqglzDgfQBeDJkHVPAjhbRDpVNRm2s4gsAbA45JikRcjm8rjkB49gLJXDtZeeioGeRLObRAghM4XjADwQstwdM48FsC1sx3qOj7c/vQNpy1U1jFQ2j18/vQN/8cqDavkIQgghLUariseFzvu+kHX7AAiAAQA7Iva/HMAVDWgXqRPP7RrF7zbsBQD85JHN+MiZTA9PCCEVshDR46O7Poq6jY+Do6m6bkcIIaT1mXa31Sop5dJTat1VME9m7dcFdWwXmSLJTM77+4bHt6J27y1CCJmTNH18XNzXUdftCCGEtD6tannc67yHPT1dADMw7o/aWVV3w2Sf82C2t9YinS3MbV4cHMfaLftx0kEDTWwRIYTMGPYienwEwq2SAOo7Pp533DJ84dZ1viyrQTriMZx73LKajk8IIaT1aFXL40YAkwCOD1l3PIANUfGOZGaQyfknGzc+HhqeQwghpJinED0+AsDT09GI+d3tZUMOPnLmKszvbp+O5hBCCJkGWlI8Olnjfgng7SLS5y4XkYMAnAngxma1jdSHYJKFW5/YjlQ2F7E1IYQQi5sAHCUiXkkOJ0v5ewH8QVW3T1dD/uaNq/CJs1+Bjrh/OtERj+ETZ78Cf/NGxrMTQshsoiluqyJyLoAeAK4wPEZE3uH8fbuqTsAE9P8RwG0iciWATpjaj3sAfH2am0zqTNDyODyZwb3P7sa5x9O9iRAyN6hkLBSR7wO4BMDhTrkqALgGwEcAXC8ifwfjhno5gCMBnDVtXwDG5fWjbzoCl7z6ELzxkk9g47ZBHL5iMe794TdocSSEkFlIs2IevwvgYOv/dzovADgUwCZVXS8iZwD4ZwC/AJAFcC+AT6rq4DS2lTSAdK44RuaGx7dSPBJC5hJlx0IAbc7LC0xU1ZSIvAnAvwD4NoBuAGsBnKuqqxvf7GLmd7ejb/ApDD+8Gn2nn07hSAghs5SmiEdVPaTC7R7DND9FJdOD7bb6ulWL8OCGPbj/uUHsGUthUS8z8xFCZj+VjIWqeimAS0OW74KxSBJCCCHTRkvGPJLZTyZXyLb6F688EACQzStuWTttoTqEEEIIIYSQKqB4JE3Bjnl89WELcfDCbgDAnet2NqtJhBBCCCGEkBJQPJKmYLutdrS34Zhl8wAA+8bTzWoSIYQQQgghpAQUj6Qp2Alz2tsEXYk2AMBkmuU6CCGEEEIIaUUoHklTsN1W22MxdLU74jFD8UgIIYQQQkgrQvFImoLrttreJojFBN20PBJCCCGEENLSUDySpuBaHtvbzCVoWx7zeY3cjxBCCCGEENIcKB5JU3BLdXjiMVEoOZqykukQQgghhBBCWgOKR9IUXIGYiLuWx8KlOJHONqVNhBBCCCGEkGgoHklTcN1WE47lsduyPE4w7pEQQgghhJCWg+KRNIVCzKMAADqdhDkAkGTGVUIIIYQQQloOikfSFNIBt9Xu9oJ4pOWREEIIIYSQ1oPikTSFYLbVbsvyyFqPhBBCCCGEtB4Uj6QppAPZVm23VdZ6JIQQQgghpPWgeCRNIRN0W6XlkRBCCCGEkJaG4pE0hXQg22oXYx4JIYQQQghpaSgeSVMIZlvtouWREEIIIYSQlobikTSFYLZV2/I4mc42pU2EEEIIIYSQaCgeSVNIB7Kt+sVjviltIoQQQgghhERD8UiaQiYQ8xhvi3l/T2RoeSSEEEIIIaTVoHgkTSGTNaU6XLdVoBD3yFIdhBBCCCGEtB4Uj6QpBN1WgUK5DopHQgghhBBCWg+KR9IU3DqPtnh04x4nmG2VEEIIIYSQloPikTQFr85jiNtqkpZHQgghhBBCWg6KRzLtqGpBPDp1HgHL8kjxSAghhBBCSMtB8UimnVxeoSZfjt9t1Y15pNsqIYQQQgghLQfFI5l2Mjn1/va5rbYzYQ4hhBBCCCGtCsUjmXbSTrIcICLbKi2PhBBCCCGEtBwUj7MAVcUz20eQypYXXfvG03h57/g0tCoaN94RANpDEua0csxjNpfH09uGkc9r+Y0D+63bXv1+c42Ng2MYSWaa3Yw5japi3fbhiu4nhBBCCJlbUDzOAn708Ms471sP4PL/ebzkdpPpHP7sm6tx+tfux9PbhqepdcVkLPHY4SvVEQcAJFvY8njFretw/rcfxD/fsb6q/T5701N4y7cexDfvfr5BLZv5PLxxL9709dU4/1sPIkeR3TR+8LtNeMu3Hix7PyGEEELI3IPicRbwx037AABrt+wvud3zu0axZywNAHhya/PEo89tNV7IttrtWR6zUG1N8fDQxr0AgDVl+jrI45vN9o9uGqp7m2YLjzrX8eZ9E9g7nmpya+YutV7jhBBCCJn9UDzOAvZPGDe/crGCW4cmvb8n0tmGtqkUtuUxLNtqXoGUJTBbhXxesc3pw/FUdf3nbj80ka57u2YLQxMFd9XxVOtan2c7W4cmAAAjk5mWfYhDCCGEkOZA8TgLcAXJZCZXcrLnTgqB5sYVpqPEo5NtFWhN19XBsZTX9rEqxeNY0my/f4LxfFHst4S1219k+nEfkGTzyuRVhBBCCPFB8TgLcAWJKpDMRFvstu0vWB7Hm2h5tN1WEyEJc4DWTJpjW26rETeqirE0LY/lsPtmNEWR3QyGJzMYtR6MjExSxBNCCCGkQMuKRxE5Q0Q04vWqZrevlbAn3aUsBT631Sa6BfrqPIaU6gBas1yHbbmtxvI4kc7BNQinsnnWsYyAbqvNx77GATDzLSGEEEJ8xJvdgAr4LID7AsuebkZDWpFUNuez0k2ks1jQkwjd1p4YNtPyGBXz2Gm5rbaiwLLFdyqbRyaX97U/iqDQHJpIoyvRVff2zXR8bqu0PDYF+xoHgFGKR0IIIYRYzATx+IKq/r7ZjWhVgjF0UbGCqoVkL0BzLY9Rbqutbnm03X4BkwSnvztcqNuEicfl/RSPQWzL4xgtj01hW0A80m2VEEIIITYt67ZKKiMYQxcVK7h/IoNxa11TYx59lsdCqQ47YU6rxzwCwGiFcY/B+EgmzSkml1efiyQT5jSH4DVOt1VCCCGE2MwE8fgdEcmKyIiI3Ckiryu3g4gsEZFj7ReAwxvVwD1jKfzZN1fj1f90D254bGujPiaUoXH/5C7K3TNoNWumOLPdVhMhpTqAVnVb9ceDVSrAg2U9mDSnmOHJDOxEwdWWQiH1Ydv+QMzjJMUjIYQQQgq0stvqMIB/A3A/gL0AVgH4PwDuF5G3qOqdJfa9HMAVDW+hQ2d7G57fNQYA017cfH/Q8hjh7hkUPk0t1RHptlq4HCczrSUegm6/QOXWsdEi8cgJeZCgoK62FAqpD8WWR54HQgghhBRoWfGoqmsArLEWPSAiNwF4CsC/ACglHq8CcH1g2eEAbqlrIx16Em2IiSluP90xQkEhkowQhcFJ4UQLJszp8iXMiS450gz2jKWRyvrbFBSFURS5rY7T8hgk+BCkUpdgUl/otkoIIYSQUrSseAxDVfeLyG0APiwiXao6GbHdbgC77WUiErZpXRAR9HW2Y3gyM+2TrUpjHoOTwmaWQkhbpTraI9xWmyluwwhaboHKXSuD7q20PBYTdL+m2+r0M5rMYDjgpsqEOYQQQgixmQkxj0FcFaglt5pm5nUZHT7dMUJBi01UltJWsjxGua12tXCpjmDMKFCF22pRwhxaHoPQbbX5hF3jtDwSQgghxGZGiUcRGQBwPoC1qppsdnts5nW2A5j+GKGgFStKdIXFPObzzdHfUQlzEvEY4jHzbKDVSnUExTdQucBhwpzyBDPQUjxOP1v3Fa5x93fIhDmEEEIIsWlZt1UR+QmAzQAeBbAHwBEA/jeAAwBc2ryWheOKx+kuql2p5THMqjCZyaGnY/ovgUw2vFQHYKyPo6lsy5XqcJPl9HbEPWFTqcAprvPICXkQWh6bj32PWLWkF+t3jjJhDiGEEEJ8tLLl8UkAbwZwNYC7AXwVwDMAXqOqdzezYWEU3Faba3kME13DkxnPdXLlQKE4fbNqPbp1HmMCxNv8l6Ab95hsOcujsdweuKDbc6+tNC4vKITotlpM8DpmzOP0417jiXgMhy3uAQCM0vJICCGEEIuWtTyq6pUArmx2Oyqlz3NbbW7CnMkQQWiXmHjFAX2eC2az4gpd8djeVvzswhWPrWZ5dPts5UAX9oylMJnJVW55TNLyWI6goK40npTUD+8a7+/C/K4EAJbqIIQQQoifVrY8zii8mMcpPKlPZnK47cntoS6mUQRjxcLcVu14x1cc0Of93ayMq5msibVMhIlHx6rXSjGPquqdkxX9Xeh1XH3HKuy/oIV3JJlBrknxpq1KkdtqOgvVqfeRquKuZ3bhxcGxKR3npT3juP2pHVM6b5lcHres3YZNe8an1JZG4V3jA10FTwomzCGEEEKIBcVjnXAnW+PpHLK52moUXvvQJvz1T9bgQ//9aEXb5/NaZLEJs9jZyV6OXNprbdsst1XTRjvTqotreWylbKtDExmvX1cOWOKxwol10IqmiqKSCHOd4EMQ1fpYn3/8h8247EeP4p3fe7hmV1hVxXv+6/e4/MeP4xePbam5Lf+xeiM+9tO1+MtrHqmLMK43tnXdfRiWzuZbzoV8NiEivSLyryKyXUSSIrJWRP6igv0uFRGNeC2djrYTQgiZm1A81gl3sgXUXuD8hV3GOvLM9hFfOYsoRpNZBA0hYRM916LQ2R7DgQPd3vLxJgk01/IY5rbanWg9y6NtuV050I2eDtPGSt1WR0O2Y8ZVP0HxCNQnac7//P5lAMDe8TTueHpnTccYS2WxY9gkd35o496ajpHPK657xAjPzfsmvOO1ChPpLPaNm2ty5UA35nUWIhpofWwoNwK4BMAXAZwL4I8ArhOR91S4//sBvDrwqu0iJYQQQiqA4rFOzOuaungcS5lJWl6BnRVMLsMESLjl0YifFf1dvuyqE01KSuKW6miPS9G6rnbTvlaKebRjRo3l0Zzrit1WnX4+YF6Ht4xJc/y417LdR1MVj+u2D2P9zlHv/xse31rTcey4v2d3jNR0jN+/tNfnjl7rcRqFfY2v6O/y3c+mOwnYXEFEzgNwNoDLVfU/VPU+Vb0MwF0AviYibaWPAAB4WlV/H3hR7RNCCGkYFI91oh5P6u0YxGBdxjDCxGN4zKPrjtaNnkShnc2yPKYc8Rga8+i5rbbOhHVrkXh0LY/Vua3aVt+hcc7vXCbTOaQcS7vdR1NNmnPDY9t8/z/84t6q4old7PI7GwfHa3LjDLal1cRj8Br3e1LwWm0QFwEYA3B9YPkPACwHcNq0t4gQQggpA8VjnejrtJ/U1zbZst0bt1YwybVd/Rb1GotNWKygnQiju6PwMLtZMY9uncdQt9UWTJjjCvnejjjmd7Wj13lQUEnCoXxePZFul0mh22oBuy98pWSmYHl0k9PYx1QFbqrB+mhb3nJ59dzLK2U8lcWvn97hW/ZMq4lH635jJ8wBmHG1gRwH4FlVDXbwk9b6ctwmIjkR2SciN4pI2X1EZImIHGu/ABxeZdsJIYTMUSge64R/slWr5dESj0PlxaM96V7R3wmgWHSNpbKeyFw50OXFFALNcw113VZLJcxpKbdVK9OqiBTcViuYVNuZVg9cULCqhcX4zVXs69juo7BY0UpZ/dwg9joxfB8/6xU4aqnJMnzD49uqTlYTfBhUrdXwjqd3etfzfMcd9Nkdo6V2mXbcByTtbYIlfZ0+y+NUMkiTkiwEsC9k+T5rfRQ7YWoffwDAmQA+D+BUAL8XkRPKfO7lAJ4OvG6pvNmEEELmMhSPdcI/2aox5jFpi8dK3FYLk7rl/ca6EhRd/ni9bnTG2yBOqGGzYh7TFbittlKGRzsLJQDPbTWdyyOVLd1O2zq5dH4n2mKm82l5LGAL6XpZHt34xu5EG849bikuPnklAFNyY82W/VUdK/gwqFqr4Y1rTFsW9iTwntMOAgBs2js+pe9Xb9xrfHl/F9pi4vekoNtqIyn1JCNynareoaqfU9XbVPW3qvodAK939vlSmc+8Csaqab8uqK7ZhBBC5ioUj3XCl2CiDpbHbRVYHt2kKyLAAfOM5TEZEI+2CF3R34VYTDzX0FbMturWeczk1LNQNhNVDRGPVtxoGddVOy6ytyOOfuc6GaLl0cNnebRjHmsUV/sn0rjn2d0AgHOOW4qejjguOGm5J9xveKw619Wg5a0a8bh9/6SXofVtJy7HCSvnAzAutHYyn2bj3m9WOA+hfJ4UTJjTKPYi3Lq4wHkPs0pGoqqbADwI4FVlttutquvsF4CN1XwWIYSQuQvFY53o64h7Fr1aYoRUFWPp2txW53e1e+UjJjI5n1uefZwDHfHT3eFmNG3MpLCcW2Day7YaXaoDqH/co6oinc17r0rqcY5MZj0Rs8LpPztjbTnXVTvzbl9nHP3dRjw2O9tqo+sMVnP8IZ/l0XJbLaqPWdkxf/nEdu8ae4djcVzS14k3HLHIW1+NZTvYjmd3jFTclpvWbIO76cUnr8TRy+Z568qJ0Eo/ox7nMviApKu9DXFHbFeTMKcV61e2ME8BOFpE4oHlxzvvT9dwTAHQ/KduhBBCZi0Uj3UiFhPPIlVLjNBEOgd73rVzJFlW3LiT7oHuBLqdLKq5vHoTZ6AQr5eIx7ykOj2OQKsk4Uu13P7UDpz4pbtw9QMvRm7j1rAMc1vtbLfEYx0to8lMDud/+0G84nO/9l7HXnEnfv7H0kXftwRqPAJGBLqUs47ZfdyTiGOgOwGguW6r/3b3C/iTL/4Gv1lXW93DcmzZN4HXXnkvPvDDR5EPFiINYf94oS8OmN/hWQhtS/yLg2N49T/di49et6bs8W543CTKWdHfhVcdVjDsXHyKEZIjyaxnmayEoCfBaDJb0cMd0xZj5TxqaR+OXT4PBw50e/eJqNjJfF5x2Y8exav+6R5s2F06Oc9DG/fg5C/fhS/+cl1F7Qkjmclhz1gKALCi31zjIuJ5U1TqSXH3M7twwhd/g2/85rma2zLHuAlAL4CLA8svAbAdwB+qOZiIHArgtQB+X5fWEUIIISFQPNYRN+6xFrfVoAjJ5RU7R0rXenStV/3d7T7RlUwXxOMu5xgHzOtAzJmUu0KzEZbHHz28CcOTGfyshCgrJMwprvPoszzWUTw+8tI+rNvun6ynsnn87NHS4tGut+nGlfosj2XEo89ttTOOfkc8NjNhzs8f3YLRZBbfuOv5hhz/3vW7sX04ibuf3YWNg+Uzk7oPQXoSbeiIt3niyu7bXz+9EztHkrj1ie0YLtF3qoqntg0DMC6r7jUPAGcdfYCXpGnN5qGKv0+Y22YlrqujyQxeHBwHAJx73DKICGIx8ZL3PLM9/BiPbNqHu57ZhV0jKdzz7K6Sn3H7UzswNJHBtQ9twvYaypAAwO6RlPf3MifxFlAoP1Sp2+pNa7ZhJJnF91a/2HTL+kxAVX8NU9PxuyJymYicKSL/CeAcAJ9S1RwAiMj3RSQrIge7+4rI3SLyDyJyoYi8UUQ+BuOyqjDJcwghhJCGQPFYR/qqnGzZBF3jgPKuq26tQGN5tLKoZgrHcq2g/V0Jb5nr4lpvy6OqehPiZIlEMq54DC3V0aBssLtHCxPkD73hMG8CPzReepI7OFbYb3Gfsdz6Yx7LicfCd+jraMdAtxvz2LzJtftwY/3OUazbPlz349uirxKRVXgIYq7RMPG423qQMlqivuZ4OoecY+1c4pwvl872Nm+ZfV7L4fbX0nkFYVVJxlW7lqctyo5ZblxXn9s56rXVxo7JLPdwYsK5vlSNeKsF+1pc0F24T1Rredzn/JbSuTx++cT2mtoyB3k7gP+GSXJzB0xtx3er6o+tbdqcl/207SkA7wLwIwB3AvgUgHsB/Kmq1uLuSgghhFQExWMdqXayZRMmQsolzbEtj10R7p6uKLVdLT3LY51jCrftn/TiPZOZaJfbit1W69i+PZZY+OibjsApBw8AKC/iBi3RuajXL26A8uUkxqxroaejDQM9rttqpinxYarqu9aCxevrgW3RrqQkhXsOBnrM78cTj9YDlT1jhfNU6qGH7TJuJ7FycR8A7KlBPC7v78RBTimRKKuhjX1tDViizI17nMzksGnvuG+fiXQWtz9VqAlZTjzav5EbHtta0zXla2dPoc88T4oK3fDt4/zi8fpfV7MRVR1T1Y+p6jJV7VDVE1T1p4FtLlVVcRLiuMv+VlWPVdV5qtquqitU9X2q2hh3AkIIIcSB4rGOVDvZsgmbJJa1PFoxj10RFjt34muXEnGte/Uu1WELhVQJ4ZfOOdlWQxPmFIRZPd1WXRHY1d6Gno5C7OHwZKZkXJ4rMuZ3taMjbvqtt7Nyy6Od0bbXSpiTzuZLCuxGMZnJwf66t6zdVvestra4q8TyaF/HQKF/7RqZtogfK2F5tB/c2Ne8ixv3ax+vHK4nwbyudhzjCL9nd1YrHgttOcZKmhO0YN65bqfvmimXkMn+rb9YQxkSwO9C3W+JXM+TosIEYPZxntiyv2y8JiGEEEJmHhSPdcRNbx/mglqOcPEYXesxmcl5VoeBgOXRziRZmPiGWB7rXKrDtsYks9GCJFOqzmO7LYLrJ25dseBanlwRl9fSluLgfoDf8lhpttX2NkFHvM1ngWqG62qwvXvH01j93GBdP8NveazebbUnxPJou5mW+n3Z6+xr3sU9j9WIx1HrAYxrNdyyb7Ksh0GUKDtyaR/cUMygBTNoCa7G8mj2r64MCRBtIXXFd6XZVoPXs5ssiBBCCCGzB4rHOjKlhDnWpHeB49q4rUQCjODENCpWMMzy6MU81jlhji0U0tl8pEXPc1sNsTx2NahUR1AE+kVcefHouqwCJmuqS1m3VcdK5gpO2wLVFPEY0t56T/Jty9ngaKqsUCtYHk3f9IXEPNrHqNhtNcTyuNixPA5NZCq2uI5Yrt9uvCIArC/jkhtleexsb8Nhi3sB+H8z2/dP4ncb9/iOUVY8Bh4AVVuGxLTT9JmIsbC7uOK7khjuyXQOqcADo5vXbAuN6SSEEELIzIXisY642QnHUtmKShTY2ELuyANMMpdSbqtBa0FYrGAml/eEpB3/5Vke65wwJ+iimI6YnBcS5hRnW+1qULZV1/3UFQ92bFcpEedavBb3FRKexGJilTuprFSHa02zLVDNyLhqixHXhfOeZ3fXNTtm0B26lPUxl1fvAUfB8tjma+tkOudrd8VuqyViHgFg71j576yqniCd19WOo5f1eevKWVXthxLzA21xLZj2b8auCemem7IJc5z7hns9VluGBChYfud1tntlUtz/AXM/SZfwJAD8v6HjV8wHAOwYTuLhjXuragshhBBCWhuKxzriTlZVy1ukgtjudkc5E9Tt+ycjn9wHrRphJS58LnxWnJ470Uzn8mUnhZUymsxg8z6/m22YBSSfV2Sd7xSabbVBCXNcEbiozwgUv4iLFhF7Rv2i0yXMtTIM9xwULI9Ndlu1rsv3nHYQgPpnxxwPiP5SImt4MuMJJtc619th3t2+DSa3GStpeSx8PztJlMsi6zxW4ro6mcl51+u8znas6O/yfkvlkuYURFkc8cC17orQXSMp7B1LQVU9C/ARS3rxp05Cp3IPJ9y42TOPWuK1q1pLctDy62KL73Kuq/a1/N5XHeR5FdB1lRBCCJldUDzWEdtNLippzv6JNP717ufxeKDOnDupj8fEc2nL5hW7R8NrPQbdVsPcPe0JX5+dMKej/klp1u8sduELSwhjWyPLua3WKyYzlc15/bW411gQfSJuPPxcjaeynhBaHCj74CZ1GSvj+utO/l0h43dbrZ/lMZ9XXP3Ai7jtydIi0Ba7Zx29BCuc2pX1zI4ZvKZKJc0Ji7crJMzJIZ9XX5kVoLRgt393YeLRPo+DY6XrqJrj+WMoRcSzGpZLmuOJsp5E0To7ac7f3fgUPv6ztV5NyHecsrJwfZVNmGPW93e34/wTlgMAVj8/WFVMZzDm1MWOGS2XNMe+Hx20oAdnH3MAAOCOp3eWtZ7aDE9m8JEfP44v3LoOa2tI/kMIIYSQxkLxWEf8k61wYXD1Ay/hX+9+AX/7s7W+5a7I6O2MY+VAl7c8ynU1mF6/u73w2a7o8k98rZhHS6DVK+4xzLqUCqn1aMeZhSXM6YjHII7nXLWxW1HY7omFmMfybqu2xcuOeQTCy0mE4U6cQ91Wy9SYrIbVzw/iK796Fh+9bg12DEe7O9vnu6+zHRedtAKAyY5p11KcCsFrqpTl0bb69nuWR//1GRRCpa5Z93fX2R7zsuPa2LUf94yW7//RkOytrnh8budoSff0KFEGwBc7edczu3DLWiP6YwJcdNKK0FqXYbgPiroTcVx8sjmXubzi3vW7Sn8xC69USsDy2NdRm+VxoKcd7zh5pde+3z5feUKm3SNJ/OqpHbj2oU1FngyEEEIIaT4Uj3XEtjxGZYR8bpex0G3ZN+GbeLoipCcRx8p+WzyGT6DsJ/0D3Ql0Jgqn0hVd/rIFVrbVjmKhOVXCXPjCLI+ZXOE7h7mtiojnulqvtoWJwHmd7V7Gy6jYQ1u0FFkenT4sH/Pod1tNxGOeeK+n5dG9rvIKbNw9HrmdLXZ7O+I48cB+7//tw/URj8FY2o2D45EPAmyrr2d5tETLeCpX3ntrUQAAIABJREFU5LZaSbbVsGQ5QMBttYJaj2ExlIcu6gEApLL5kseIEmUAsKSvEx86/TAsndeJJX0dWNLXgWXzO/G3Z70CS+Z1+sRjVO3GfF6931hnexuOc2INAWD3SOWWR/ccDBRZHm1PitLX+VDgfnTKIQPe/y/vrVwEhtVVJYQQQkjrUOzXRWqmrwK3VdeS6JaIcK0SY5Z74wrL8rgtyvLoWK0622PobG+DqqItJsjl1XNliyqY3t2AchiVWh7tGMswt1XAuK6Op3N1i3kME4GxmGB+VzuGJjIVWR6D4rGnQsvQaEA8AsYSNZ6erGuSGvshQ6kSL3Ysbm9H3Pe99lTh6lgK1zK4qDeBPWNp5PKKF3aN4fiV84u2DXNb7bEsj2OpTLHlsUSfe9mFQ5LlAOba6u2IYyxVbNEMPZ5tvXcewAQ9Aw6Y11m0HxAtylw+c+7R+My5R4euc6+vvJqHMLY7t0vS+n11J9rQEW9Dd6INE+lcVQ8mKnNbLVOWZNxvQe6It2F+VzuGJzMlr8cgthhfEvjNEUIIIaT5UDzWkUpihOyJ1NBEsXjs7YijOxHHwp4E9o6nS7it+iemrsVuNJUtuK1GZJ7stt0C65BxNZvLezGPRyzpxQtOcfBwy2NhWZjlESjEPdYrHjPKgjjQncDQRKYyy2MgYY5bTqJcTc+xZLF4HOhpx7b9k3VNmGNfJ6Wy9LrCqy0m6GyPYVFfdZa4cqiqd/2dcvAA7lxn3Cef2TEcKh59sbtOBlw7VnEslStqVynB7tU1DYl3dFnc11G5eAyJG1450O0t2zo0gVMOHijaD7BFWbiQLUWv1f7RVCZUPNqWeTdh1kB3AhNVPJhIZ/NeXG9RwpwKHoa5uPcjV8QCwIr+Lkc8Rl+PQfy/uXBRTgghpLVQNckQ86pQhfeuzjrzDkAB8x8Q4VRTOKZ1bPd/ex9FFVUNNPTPwHcI2y18a3db9/tNhbDdezriXtm+VoTisY6Um2wNT2Z8YmNoIo1DYVzgxgOxcSsGurB3PB1Z6zHMWtCZMOLRc1uNyDxp1ymsh+Vx095xr8bbSQf1W+IxxPLoE4/FpToAoKu9ceLRdlt0J/VRIs7dTwRFP2L3PJWKv8vl1bOe9tji0Tln9XRbtS3UpeqDFtyj2yAiPtfAapKsRJHK5r0Mwcctn4/Vzw8imcnj2YiaiG7fx2PiCXL7+hxLFou8kglzHLHXF+G2CpgHAS/tGa/MbdVnvS/8Nl2ihJFflFU/ANhxn2PJLJb0FW9j/z7cUj393dU9mPDFnPaUcFstZ3n0XHQLx1g50IVndoyUvB6DuOck0RbzPYwjhBBSH/J5vyRSVeQs0WeH8udVkcrkkc7lkcrkkLeUjqoZ81PZPDK5fFkxSCpncV+C4nGuYAu0sMlW0AXVnriNWglzADPxenLrcNmEOba1wLU+TKT92VZFgF5rQt7jS0gydYG2zop3POmgAfz8UZOeP1g0HPC7rXZEuq06dSjr5Lbqup/2dcZ99TDLiTh3IruwJ1FUasHOhqmqECkWwraFzL42XMFfL7dVVQ1YHqPdBN0yF664st0L6yEebWtYX2ccRx7Qhye2DkdmXHX7vr+73evDXp/lMRNSqqN8ttUot1WgYH2uxE13xFfuxk3oE0d/dzv2T2TKPtwBwmMeyxGM+wzDduu2LY9A5Q8m/LGK/nb2JNoQE+M6W87CPhRiZXUttFuHJiJ/I0Hca3BRb6Ki7QkhpFnk8opkJmeEVx6OACtY2dSY2YosZi4KjRRctkXL3SYfEHjuZ9nb2MfMOZbAwnvhGIRMBYrHOhJvM8lQxtO50AQTwUm9nSzES6yScMWjmXhtG5pEPq+IxfwTqf0TxfFUQYudO/Ht64j79u+2LY9V1qMMw7UqtcXEKxAOhFseK3JbbTfLJ+sUj+mKwGDcYjkRN+hk41zUWxx75bqhZvOKVDbvE6Uudmye3/LoWjzrY3ncN572CYlSboJjKfOZthvt4r4ODE8Wi7RasC3Z3R1xHLN8Hp7YOoxnd4yECogwC7rdtrFUrtjyWDLmsbzbqmttrcZtNRGP+c7xyoEu7J+IdskcCpTSqRa7D0ZT4deJLdS7LMsjUPmDibCYUxcRQV+nebBQqduqfQzXQpvM5LF3PB36OwrinpPgb5UQQhqFOoIqZwmtTE6RzhqLWyab97lQZnKK8XQWqZDQHELmAhSPdaavsx3j6VxoavuglcKeuHmxcc6k162/l87lsWcshSWBpBxhT/q9WEHPbTXcCmO7BdbD8uhalQ5b1IP51mfVKh5dcVvvhDnBuMWBcm6rEaITCAqcbKh4HAskp3Hpd/poJJlBLm8SHU2FoIDZNZJEOpsPTUjkWrFs6/Oi3gQ27K6P22owDs8tazGazGLr0CQOXNDt2967jq3rxte3ycoT5qiq97urxPLouniHnTuXQgyl/3gr+rvw9LaRSCtvKVFWCXYfRFoebfFYo+UxrFSKzbyuuBGPZes8hlke/Ym/KB4JIdNFJpfHWDLrC5VRNfOKSSchH10tCakNisc6M68rjp0j4W6rwUm+az3M59UTca6Fyp54bRma9InHfF4xPFmJ5dGZSAcmvnbyjXpY99xMq8csn4eO9oJgCXNbTVWSbbXOpTo8V7jAhNQt3p7M5ENFxJ4I0QkEJ/fZ0ImxTzyGuK2qmjjYqfq1Bx9K5BXYOZzEQQu7i7YtuEcXronFfebaKhcDqKrYN57GwhIiwGdtTcSx1Lpu712/G688dIFve7ekhM/yaPXVjpGkd83EY4JsXn0ZY22SmbxXCiaqVAfgFyaDo6kiQWtTyN7qv1XangGlLKrmu00tYc5YhOVxMlPoB/c34z4QqfTBRLDERhDTj5M1WR6DWWlPsMrCRLFnLNraTwiZ+QRr4+aDbp4WvuQonrumcdnM59WzFLqvbF6RzeUxlsqGJuwjhNQHisc6405aK3JbdSaYvsLtVsIcez87o+NIMuMFNPeXiHl029AXcOFLxGNItMWQzuWnbHkcHE154uzoZfN8Aizc8li6ziNQELfJutV5NP0cFIF23w1NpLFsfqHPVbWkFcR2Q42KBwvWVHQZ6Cl87r7x9JTFY5j1a+vQRKh4HEu6bquF8+T2SznL4yd+/gRuWrMN33zXCbjopJWh2wQtj0c5lkcAuOLWdZHHtuPtOuJtaG8TZHKKTXsKNSsPWtiNFwfHjStRiGXVn124dLZVl8GxMuJxMjwBjyuMUtk89oyli64Rnyir4fz6y5VEWR4LkyPXWl/tg4lyFlLvflYiYU4ur956+zyu7PdnpS1HLq/YN07LIyFTJZnJ+YSXJ7pC4vJcNJCO0l2fU0XeyqJpE5210hJ5qshk1bh/0tJHyKyA4rHOzOuKnmwFLUSu5XEsJDbOLgcQ3G93ROkJV7h52VZLuPB1JdqQnsxPOebRru949LJ5viQ4YZbHjG15jHRbdURwHdxWJ9JZr3+DE1J7sjw0nvGJxxHL3SVsImsL8ig3yvEIt9Wl8wqfs3nfOFYt6a3ou0QRFne3NSKRi+sCGYx5BIzwG09lfcLY5r7ndgMAfvv8nkjxGIzz7O2I49RDBvDHTUMlv8NJB/nLXfR2xDE0kcGmPQXRcejCHrw4OO59TiLuFzu2daxUtlXbqlVOMEfFULpu5YD5fRaLx6klzOmzEuZEZZe140s9y2OP/4FIOfHo3oM64rHQciCuCA97GOYyPJnxJoS2BXleVxx9HXGMprIVZVzdO57yHopRPBJSGbm8ib8bT2UxmsxiNJlBOkuFRghpHBSPdcadZFbitupZHkPcG+2MjsH97Kf4tmtYcbbV8HgtwGRSHJ7MTNnyaGfRPGbZPCTaYhBxUjiXKdVRzm21HqU69owWJvHFCXMK/RJMMBJV3sOlJxDzGMZohHg8elmh7sKzO0bxxqMOiGx/JbhZfA9bXBBXUYlcxgIlYQD4ynXsGUuFikcTT2j2DYvndQmrPXjNpafiDy/uQzYf7ka0qLejqFZijyse9xYsj4cs6vF9j6BFz2d5LFPn0aVckqCoGMpgrccTAy6ZrihLxGPe9VwNne0xL9Np1MMJ27LvCj9bvFWSNGdovLjEho177yh1zn2ZZS3xKiJYMdCF9TtHK6r1WKquKiFzmUwuj6GJNCZSOc8SmHNq6jJpCyFkuqF4rDOe5THwpH4slS0qRu+6ttluj33WxH1Ff3hGR/v/FZZrmCe6ihLmFJ/mbudzplrn0bU8Lu7r8CblHfGYiSMMszxWUufRmQi7NQOnklBmcCzp/V2cMMeyPAbOzWCEddclmDAnjCi31f7uBJbP78T24SSe2R5ewqIa3OvhsEU9GE9lsWskVVQWBnBjawsZeF2CMYAHL+wp2ncinfPqN5ayQtku2K4I7etsx1nHVCeQ3f6yrddB8RjEblephDkLe6qwPEYlzClT67EgytprKjkhIujtiGMkmY28viZKJMwxbSifNMculRJGwZMi+pyXyiy70hOP5d1WXfdyoDg+mZDZjKoimcmbDJ7ZvG+5Wx+a7p6EkFaB4rHOuO6Mo8mML5GGPZnvbDfiar9neSxMAm2rz8qBLqzbPoJtgYmXe6z2NsESa5Ll1kecdCb6ruUryvIY/OxacMXj0VZsW2d7G5KZfLjlMVtJqQ5/3GSUG2UlDJawPPrFY8DyODZ18RhVqgMw/bV9OOlz+60FU+PRXB8r+rswNJHBrpFU6GR9woqD6YkQj1GWONuqVyr+bSJVbHmshd5Af7XFBAdagi3MGue3PEaLx0Q8hoHudgxNlK9tGZUwZ35XO/o64xhNZkOFelgCmWpxxWNUTK2djTiYMMe0obzlcf9Eacujez8bS2WRzeWL6p3axwg7TrnEQja0PJLZSDaXNxk+Mzkk0/miLJ8KIxxzeapDQsjMoKXFo4j0AvgKgD8HsADAegBXqupPm9qwEriT1ryaMhjuJNiezB+zbB4e37zfm9zZ2RR7feLRLbLtn3i5lo4V/V2++o3uBDKdy/smdMGEOUAhwcZULI/JTA4bHTfJY2zxGG8DkAnNdma7rXZEuK3aomMiPUXxWEIElnJb3VNmIuvLhhmVMMcROIl4rMhF95jl83DP+t14ae84JtJZX+3NarBdj1cOdGNoIoPHXh4KtYb5LKFW+xdXEANoW/VKZd70u63Wft56A9fswp6Ez5oYlnHVto6VSpgDGFfZcuIxmcl5DzvCxOjKgW48uyO8XEdY6Ypq6e2MA8PRbquuW3dHPOZZ5/1uq5VYHh3x2BNhebS+91gqG1qz0p+xNTyx0Hg6h/0TmZLJg8pZ+wlpBtlc3pfVM+8UWnfdR7NWps9CUpn/x96bx8lRnffev9N7z/TsM5JGox0BQgizKGYRxizGjuHasQFjwHBD7k2c2HjLvbxOHCevtySOk9zkTV4bfJObxHFsDJjVK3ZsjG2CWByJTWIVSEIzGu2z9cz0Wuf+UXWqT1XXcqr36X6+n898Zqa7qvrU6ao65zm/Z9FrAS7kipYF03qQzhbw5N7jmFnIo68rivPWD5UtvhEEQdSSVn/C3A/gzQA+BeAVAB8AcCdjLMQ5/1ZTW+aCPMGdXcxLxmNpMn/GWB92vjFtloiYc3FvFEk57BkdTaVJUmIAq9F1eLY0EXNy4RPZHKsph/Hq4bS5WirH8YlyHZmCQ7ZVBeXRL2NrEMSElDGUJQ9JRMNIRsNYzBfL3VYNozMSYpbalYKuaNiM7XSb3AvjscdhIBdKLefAS4fmcI4tYYwq8nW1aiBpGgOHZjNlSpFb3cnB7ph5Lq7Go0V5dF9wEIsRskFTCfbJz0hP3Fb/0cltVU15FMd79UjaM+bRmr3VyXhMGsajk/LoreipIM7Xz21VTnTTm4ggHGIoalxReRRuqy4xj5bnmbPxaC1LYn1fTiw0PrWoZDwmo+GqFowIwglN48gUiua4WyiKUg+amRWUc/05WND0zKD5YnmG0VaBc44Hnp7Ag89MWLKYf337Prz3rDFcdfZYRS7zBEEQfrTsCM0YuxLA2wF8gHN+p/HyI4yxtQD+mjF2N+e8NrUcaog8aZ3N5LES+uRJZBuMhUPYuLxkaE0t5BwT5gC2IttSRkdxLDkVPgAkZONxrhTr5zSRLimPlXfhC5Mz5t+nr7Qrj3AM5LeU6nBVHkt9UG2tRzEhHeiKORqrA11RLM4Uy91WRW3IVNyi7gpCIYbuWATpbMG17qBTchqBrNS+cHC2CuOxpHqNDSRNI7iocRyazVgSu7gZj5FwCEPdMRxL51xrPcqGWTpbcI1FFTGP1U7+/YxHL7fVWDhUVrPTjriXvGpbyos6Tgl4hGE0MV3ukulnlKnQ7WM8CrfVLulcGWPoT0ZxfD5XtiBih3OOabNerJvyWDpvN3dlce+EQ6ysn6xZoxdwxqo+1/YIQ55URyIImqYn85pZzGNBqn3Kuf4czBc1o/5fi1qBFfLA0xO4Z8d42ev5Ijdfv/oc56zYBEEQ1dCyxiOAqwCkAdxje/1rAL4F4DwA2xvdKD9kdznZ1U9WC4e6rUktrKU6ShNBp4yOi7mimVhilV15lCaRR2Yl49EpYY4Z81i52+qLk3MAdJVpnZRkJeGhPFqyrbrWeSy9Xm1CH3NC6hJD1d8Vw8GZTJmLn8pENhXXjUe/Uh1OLkRrBrvQHQtjPlesKu7Rqjx2WQyG8alFyzXkVjoE0I3kY+mcJUZUxh53l84U0OdgcIiYx2riHZ3aN5KK+2a4NZPb+LisiuMB+iKBWyyen5Ip7r+FnK5cC2VbxShTQY43dEK4rSZsfd3fpRuPftlWZzMF03PANdtq0roY5oSZdCdZnhxolU9iIRmvuqpEZ8G57gYqDD+u6bGBuirIkZUUxPlsAZ0WLpjOFvDgMxOe2zz4zATecfoKcmGtIeQiTBA6rXzVbwHwIufcPnN6Tnrf0XhkjC0DMGJ7+aTaNs8Zub6cPPmU4xTtsXaiCHgsHEI8UpoIym6pIimHXC/Ny2310Izktlov5dHIFLppRY/FPVKcg5PLqTVhjku21Wjpslyskduq24RUxHq5KY9eE1lh6LuW6si4G4+hEMOm0V7s2D9lKXfiRbZQxGce3I3lfQn8j8tPBmPMvK66YmEMdEWtarVtsi4bgHZlcKQnjpcOzbkrjzbDYTaTdzQeTeWxinhHp/YN291WPZRHP5dVcTwAyOQ1pLMFx7qQfjGU9sUdYTyqGGUqiD50jXnMOxvq+mfO+7qtermbCiyeFC5Zdr3iO/u7ouiKhbGQK/objz4LPUR7kS9qmMsUMGtkE80VNaO4PDomeUylxsgvXzlq8eJxIl/keGrvCVy2aVmtmrtkqdboIxdhgrDSysbjEIDXHV4/Ib3vxi0APlvzFikgu23NSYlwxER+1UCyrESESJgjq46ANaOjmHhZazyqua06xeyJz5rPFXyzIDrBOXfMtAqUYh6zHqU6omHm+plyP1SbDbbkfuo8ORaTZrvy6LcfAKTMGnjebqv25C+C00Z7sGP/FF4+NAdN447usTI/2nUId//nAQDA+RsGse2kYcuiBGOsLMZMRjZC7EmUxIT9mGvCHGv/zCzmsdphO7EY0RWvTnl0al84xMwYVaeYR/E99HiU6ZCPJziWzjkbj4rKI6Df329apdd6tBplVSbMgXtCJqHK2+tIul3TdrwS3Qh6VNxW590zyzLGsGogiVcOp5WVx+Geyg1uYmlwPJ3FniPpjlMMBZUaI2K/+3aWu6s6oVLrtZ2pldFHLsIEYcXZb7B18BpavN67HboyKf+8p4btcsWeYALQJ3nHjbpvY/124zFnGkhORoYwBoTRaKnx6OG2enimZDx6ZVvlHI5ZUf0Yn1o0Y/3KjEdTeXTItloQxqP7pScbu9UMfpzzkprhpjx2lSuPmsbN78vbbdXb9XfeI+YRADaP6vFfC7ki9p/wr4O3a6IUY3rfDt1lyYx/Na6FRDSM4ZSIjbUe0+oeXa48AiU3Tjv2JDluhoR5zjVWHkX7xD0y7+DObNY1dTHWnY4HqCUJckuYI5DvS6tRVoOEOcYCj51F4/5K2vra6Zp2YkpBeZSfHW7X+ZSpPDofo5Q12v0azxaKmDG+v5FUwqPVxFLn6FwWr3aw4QiUjBG7eiiMkQeednZJFfup9l01MdftQKX9LKPqIuzmgUQQ7UgrG4/H4awuDhq/Tzi8BwDgnB/hnO+WfwC8Vo9G2rGs1BuTIdl9cNVgudtqyb3RuRwAUDISxO9IiGG5zbBJuiiPTu4ZFnWvgrhC2dVy80qr8ZgwlUeHbKuG8mgvXSETtNyAG3PZgmmsuhuP+mfNLOZNV6mphZz5t5cLnV82zLRHzCNgzVArXIC9EDGmAPDQrkks5AqOmXeFUWNXetwS5gCl/skVNcdsqnbl0c2F0VQeax3zKIzHuKij6uG2qqI8qhiP0jk6KY99yahjKR7ZKHMrgaGCODbnzu7li6byaL2XREbTqYW8o9EpsNZndG6nJc7URQGdXvCO7zQTC3koj8fT7vVYiaVHMRzHnU+9gf//4Vdx51NvYMa4Ro7MZvDa0XTLZjBtBJUaIyr7yUTDDOeuH/TfsE2pldH35N7jyi7C7UQ6W8DDLx3G/TvH8fBLh8k4Jiy0stvq8wBuYIxFbHGPZxi/dzWhTb7EI2EkoiFk8po5mR2ftiY1sZeIKCVWKZ9wy4aAXhBeP9Zof6KsYLdTqY5UPOJY2FvOaLpYQdyjnORl04oey3si06VTttWc8RD2Uh6DlhtwQ6VunDBUOdcNpIHumK02pLsKIibWbq61aY/vFQA2rehFiOk1QV+cnMV/edOo62fJbsKAbkzc85/jphEluzCvGkjimQPTrsZjJMTKamwO22o92l2d7caam/JYL+NRtC9l9rlHwhwF5dF6vhnHbeaMc4yEmLkgIiPchF8+PGeJRVaJJVTBniDIrsaWYh6tr4vFqVxBL0juVm9TuJsC7gppNBxCPBJCtqC5Th5KtSLdlEf9GTaX1TNiOrnRU43H9oAD6Nt2Pca3Xo8/uv958/XPfnc3PnDuGrxj8/KGx4a1WpKTIMaIHK+osp/Me88a6+hkLpX2s50ZxQXsdnERpvhOQoVWVh4fAJACcI3t9ZsBHATwZMNbpIhQKcRk1uJqaqzCy65lXgqVPaOjqTT1J8u2lcsTiGyhbhPp7liVyqOhlK0Z7CqLFxOGiVfCHLdMq0Cp3AAAM2tlJcgT0mEXBVFWS8Qk2Lqf++S/x1TByttYKGqm266TogzoSvG6YT1LrV/SnCNzWdOVVvDVn5fEdNmFUqiQkzOLlsQTQjlKJSJlD38/Jc5uLLrFeYo4vK5qS3XYYx5tymO1CXMGu2MQIabH0s6Dvqxkug2WTiqvilGmguzF4HS+iw51Hu2f6VWuQ0x2GPNWa72yvi7mimZss1t8pz2xkBOq9xzR2syMXYD+i24CZ9ZrMlfQ8K/b9ym5CdYKzjnu3zmOW+7YgX96dC/u2TGOf3p0L265Ywfu3znuqcrXk0qNEdX9Qgy4dusqXHX2WOC2tRO1MvqcEsM50S4uwrVw9SXan5Y1HjnnDwH4CYCvMsY+yBi7lDH2jwDeCeAPWrHGo0BMtkzl0ZgwRUIMy3t1JUtOauFVD9CelKOUeKerbFtZYRDjotukUJ7cV5KU5sVDIllOT9l7pvLokTDHy20VKE1Eq1nNU1EznCbaqipIKf6uWDYRkfvULWEOUKr36FeuQzYuRYzpIakci7yYIK6NfJHjiKSqeZUOsRiPDhlXy91W3WIe9fPurqHyGIuEzEWQbhe31Uy+aC5MqLithkMMQ1K5DidUlEy7ZwBgNcqcVDZVUj4uo0LltSfMsSyIzLvfP+J670tGHWt2CrzqTVpcdF0mT2MK5TqOpUl5XOrMLOQxPXa+fh+4LLY0MjasVSfBlRojqvvddN5aXH3OqpZQh5rp+lgro++89UOumeEF7eIiTPGdhCotazwaXA3gGwC+AOBH0Gs73sA5v6OprfJBTF7FBFcYfCv7k+YkTS4RIW5Ep8Q2spH42tE0jhgTXXuNR6B8Eul2TMDqVhi0luJsJo8DJ/RzEklfZMw6jw7Ko5xt1QsxEZVVnKBYJqSudR7Lk/OoTmTFpLqo8bLkQHKmXTe3VaBkCE7OZDwn+nJM5B9feVrZ+3a3VYE8WZ/zMh7l7KOOyqO/22pR466ulEGR2ziSipsToR6XhDmyManitiqOCzgby4BaDKUwjNLZgmlsCqOsN+FtlPnRbVngsZ4v59y1VIdqzLDpbuozefJyFZ5SiJv0Kh8jUPESIFqbH+6aBELlXg0yjYoNa+VJcKXGiN9+nHOgmMdFp9irlDWeVlB9a2X0peIRvPcsbxW3XVyEOzW+kwhOSxuPnPM05/wTnPNRznmcc34m5/yuZrfLD9Nt1VQeS+UUBBblMeOeoVLe56l9JxxfFzjFZbm58MkTzqDK40tS4hYn5VFkWy1oHIWi1agqGY9+yqNI+lG98hgOMdcJspfyGI+EPAeEHuk92VgE7Mlp3I0POdmQl/oo3hvtS+DCjUOWONN4JGRx9VvV7zxZ91Ie+5JRRAxDR015dHBhlBYL7GVngiK3cVgy4M3amh7GrIryKB/XXXn0d4OVjfYDhodBySirXHUErH0wZ5vkZgua6V2QKFMerdmc3RCGpV85ETe1Vz6Gfhzne2yoO2Y+m9yUR3HN9SQiZedDLA3c7iM7jYgNa+VJcKXGiOd+Rrmt5P7tLWHEtILqW0uj76qzx3Dt1lVlxmg0zNrKRbjT4juJymlp43GpIiavh2Yy+N6zB7Hv+DwA6wq8mFgeS2fNSbeTe2N/V9R0AXzy9ePm605uq4yxMvXRbSItG6pBlccXDpZKRtgzrQJWI9buuir+93NbHTDdVr0fZrmChu2vHXM8BzGZGeqOudZQHLCoNNaYx5GeuOcqereH66+s0ngZUpulMidecY8vSDXWDY4hAAAgAElEQVQ1GWO4RqopNTaQtLTT6iZYijHzco8OhZip+NgngZzzMqXRSXlckM65WuWx26Y8CoQhbu9vv5qMTpi1LV2UR2Es9Sb93VaBUibkklFWXQxMykN5lJNc2ZXHAQc13QlV5VEskjjFRqu4rcr1R+3lYwTyPUcsTVS/u0bEhrWSIetEpcaI237QCph+9JtI7H+sXk1WppVU31oZfYwxXH3OKtx+41Z0vfQDTP/yG+h66Qe4/catLeMiXAs6Lb6TqBwyHuuAcJs7MpfFx+582pxMygafmGjJq/lOK2CMMdMYeO3ovPm6k9sqUD6RdHPh67KU6gioPB6aM4/tpIAK5REod11VVR5L5Qa8B/c/+8EL+MD/eRJ/eN/zZe9NGrUuvSY1PYmImThFfNZBhf0A6/dlb6fsbuu1srmsJ44h41zdjMeFXAF7j+nfvTA233P2StMl0r6Q0BWLmMeUlR45YY4TIy5KXLagla0gOyUJkstJVKs8xiIhc4FB/h6EC3CuqFlKwchutW6u2nbk89UcCqcJA7nHQzmW+36f8R3VTHn0SJizIN1X9gWjfuWEOcGUR6e4S2tNS/9+8ot59CqNQ7Q2V24ZBdOca5IK/NwEq42RE+6S33/2oNL2zZoEV2qMuO3Xv/3LmNl+F1rBhGkl1bfWRl8qHkFi8lnMPH43EpPPtoTK60Sl91EnxXcS1UHGYx249NRlZbFOsXDIkg7aadByexDZjYMQA1b0OZeQsLt8KSmPAQdokahlzVCX48PXS3kUg4pXtlWgNKHNFjTPUiLPjusq6A+fn7QYPVPzOTy5V1dqZXXPTijEJBfZPI7OZbFj/xSAUjyiG6csL7mOPvziYct7D7+k/x8JMWwYSbkegzFmZlydnHYuGfHyoTnTRVG0aVlPAu8z1Me3b15eto9YcJBLSJhZfV1UQWFM2ZU4p+Q4Tm6rsjJVrfIIAG/btAwhpv8WpFzUXovyqOi2unpQ76OCxrH/RLkiZibM8VAeB7qi5gLKQ7sOAZDrHtZOebS7jMr3hD3baiwSMr0VvBZflGMePbKtTktxul4TcaFqu3kSkPK49OnriqJv4gl9THAxIN3cBGsVIyfcJVUqWlQzCa5VIphKjRH7fqGC89jRDOrp+lhpvy8Vo69aqr2POim+k6gOugLqwOWbl+OpT7/NMnEbSSUsLgFOq/RuipBdZRztS7oqd3bl0U2FkdUKpwLkXkz5TI5lA9auPOaU3VatcVvJmLPSKpK7FDWO7zwzgd+5aAMA4PvPHTQN1avO8X4Y9ndFcWI+h+mFHL777EGzvMXVPi4t64a7cfaafjz9xjQe2DmBW99+KkIhhky+iO8/OwkAuOTUEQy61L8T+CVueVGKMZXdhL90zRn41BWbHOvrrRpI4rnxGavymPVWHkXcpF15lF1UY+EQckXN2W3Vw5WyEm6/8RzMLhYs901KcklNZwpm31piHhXdVuVFhRcnZ7HeMOKBUo1Ev+MxxnDV2WP4yiN78MyBabx2NG3e99WqGvFICJEQQ0Hjnm6rTomy+rtimM8tuhpr2ULR/L78FFLhtuqcbVU/fncs7HlPC8XYSbEGStccJctZ2vRNPI59+/Zh4MLrwVnpORMNM7NGnBPC6LMjYuQA4GrJVd8JFXdJmVOW9+DJvccD1X2kGnj+1MP1kfpdDb/76PWjaXzoko2e17u4R+197XcPE50FKY91YigVx8ZlPeaP/YHqZHg5xaIB5clxnFxFBXYVwm3iGwoxc4IfNOZx2mdyLBegt2chVc+2Wl5/0Q7n3GLo3LujtLJ27059EjHWn8T564d8PquU2fU+48G7bqgLW9cOeO4HwIw9PDiTweNGTOq/v3DYTHByjc+EB3B3FxW8MKmrq12xMNYOllRoxphrYfZSjNkiNI2jqHHTWHC7zkQ7js/nLG6cM5LKuLJfV7yd1Mj5GsY8Avr52e8bOXOtbMxYsq16KIUyp67oMSsKyNls9eOpK5lXS4sTdz75hrJR5gdjzLVMhpycyKmv5WzOTqgkuhGINmTyWlkCLL9ngcCrrM1CrmC6zpPyuLRhAGa234VVO27H0Gs/UnITrFWMnIq7pMzug7OBVJl0toC/+cnLTU8E0+rUw/WxFRLw2NEiiaaVIXFC5T7a8ca07/XeKfGdRHWQ8dgknOKMehTdVt3iHYFyFcJr4ismnUFjHkVJCbfJcVxqgxyXBuixaoB6tlXA3dVtdrFgHg/QYzF3H5zFniNpPHtgGoA+sXdLliMQ57FrYsaMO1R9SL77TStNF1xheIrffckoLjttmeu+AqG2zCzmy/oLKCmPm1b0+J6LQFwzuYKGY+msxaXU7ToTCmhR4xajQ1b1xHHnsoWyOMFaxjy6IWeulQdrYcxGQuVJo9zoikVMtdGe6TaIMbphJIVz1vQDAO7+1QHz9X4fxVmFlIvxKC/42BeMAGlBxOXeUUl0Y28DUJ6oyHR97VaLm3Qqa3NsTvLQIOOxLQgXs+g5+rySm2CtYuRU3SWdju1lgAhXwA9/8z+xY/+057E6vQZeOlvAk3uPW0I6nAji+nh4NoP7d5araTKN7HcOoG/b9Zje9rGmlSFxQnXxRNXg7hRXX6IyyHhsEkGUR7ux6GU8lifM8TIeDeUxwEO3UNTM5CRuakPCkjDHOlGs1G3VCSc3z/t2juM+aaBRcbEQ5yGXQ1B1zejriuLyzbqB+NCuQ3j9aBqPvnoUAPDuM0ctyYPckCfMx9PWc9U0bho2fjGYMvI1cmBq0aIKuifMKcXRyn0rG1LiuJwDaZtibckwWwPl0Ylui/JYmizKNRmDrIyKPrUnKwrqBitc6uRrqFrlESi5nduT1ai4rQLucUVyQie/dlpLhlgn6H4u7AJ5wcI+yTuaLsVrkfHYedQqM6qqu6QbbgaIUL1s4fuOdGoNPHus3e6DzsnfgmQ5Fce89dvP+MawNrLfM2svRP9FNwEh6xjXbPU56OJJpy90ENVBxmOTcJpsua3sjNmMRfv/MmVuqx6qiTAegyiPM4v+k864lDAnU3DOtuqXMMfqtuodJwWUJqfffeYgHjBcVs9Z0++ZrMbpswDg/A2DWD1YXgrFDeGaupgv4uN3PQ0hyKm4rALWCbN9IvXGiQVT0QtiPI7ZSkjIxofbIoVcK1Juh+yiKrtM25O41Drm0YkeSwZSOWFOoex9FUTc4+RMxlTU5eMBagl43v2mlWULItUmzAFK35W9TIbVbdVJeTTcVufd3FbVEt0A3llfg7qtOh1DvtYo22rnUOvMqCrukl44GSBB4yiBzqyB5+ZWKljc90xg18cgyY+AYP1eaeKddLaAxXUX6uqiyzk0yygLunjSKIO7VsmliNaCdOgmIUpEyJ5/bsajKLItVDynGo+CZNR6DC/VRExMg8Q8WlPz+yuP2bKYR/2EA7mtukyAZXXsxvPX4n//4jUcl7a9Zqua8WaflKgafYK3njKC4VQMx9I57JrQV1w3jHTjrNX9Svt7GY+yO6VTTU03ZCNvfGrBokS6uq26tENW4WSjdHYxb/kc2cBxM1CrRT6ubBCbyqNishyBPWnOto3DluMBagZpX1cUbz9tOX7w/KT5ml8JDBVMt1UPQ93JbVVc07OZAgpFDRHb/Wa5jxVdToHyepMl5dHnGDHn7w2wGY+kPHYMbsk9nFCJkROZIh2P6THZl7EbIEHjKIHOq4Hna2BzjvjYaYg98TNl18dKjHbVfl9ceyFuuWNHRYl3ntx7HAhFPEuiCKNMzq7fCM5bP4Svb98X6Hqtx0KHcF2ens9h7/F5PDc+Q0mO2hBSHpuEXCJC4DbhZoxZDEbPmMeY9Sv1mviaymNWXXm0Khb+ymNZzKOi26q13IC/8njT+WssCkwsEsK73rTS8zMEshGcjIZxxRmjSvsJouEQ3mNLb31NgMByWfGzl8kQ7pSM6TGPqvQkoub3M25zW/VLmGNvh1DhomGGZZJrqz1pjnClDDFr0qRaknIxZERbVJPlCGSDXHZdtZT+UDRIr9lqvQZqoTy6xTzKWYydYx5LbZ5xSG5UacyjrDYXNW4a2VUpj4arNmPwzUxMtAeVZkb1Uy3cisKDq41x9us4qCvgUq6BV6lC5GtgM4ZQNI7cyKnKbQlqtKv2e9+267G44eKKE+/UswwJUJ0iqhJraqeWCx121+V7d05gx/7pivuaFMvWhpTHJiJKRADWouhOjPUnsedIGozppTrcsGde7PFSHo1tveoo2lFSHr1KdSgmzAHkcgPOD2Jh4ETDDCv7krhiy6gZ7/j2zcvRp1jvT55oX7FlRUWB4decswr//B97AeiT4Kt9yoPIyOUJ3JTH9UPdgTOYjvUnMb2Qx8SU1W3V7fxS8QjikRCyBc1ReexNRC19OmtTkMQiRFcsUrcVRVnBkuMLhVETVHlc1hPHYHcMJ+ZzlpIoswGyrQreevIIhlNx87qsp/G44BPzaI0ZzmOgK4Y/uO85/OylI8b++vHikVBZbVi3NgDWhaaZxbxZzq/fp49SXjGPc6X+UnkuEEufSjKj7j4466taiEyR7zh9BT7x6c/j4JETWLlsEJGpfZj+td9BKBJzVSCdDJCgroBLsQZetWUwVA0qHvMPIQl6TIFKv2uRBPoueL+nCv3gMxN4x+nuc4B6lCEBKv8O3PZTwel6F0bozEIefV1RaBHneuJOBPEkANz72u2cvvYfe7FptBcXbBjCeRvUy+tUgr0fgpTz6RRopG4i8gTPzZVQIFSnDcPdnkamPBFMRr1rrwlD4MhcRjlDmIpikYjIymPJbZVzLsU8+hsXfuUGxKRzqDuOUIjhujevNt+77tdWO+7jhBzfeG2A/WQ2r+zFGWN9AHQjwsvAt5OIhtFrKDP2JECvHkkD0MtKBEUo1ONTC5YJu9tDkDGGZb26IXtotjzmsTcZtSh7duVRGCT1incEdMW+21TMq3dbZYzhtFG9b2XlUbgfJ6Nh8/P8iIRDuMZYNBhOxZGIVv947XZxWxUxj9EwczS4ZK+A6YUcfrXvBO7dMY4T8zmcmM+ZLvDrhrrL9rVjVQ1L37nlWeDj+uqmGAPA8bS4j0l17BTqlRlVYM8UGcnMYPaJezxdV50MENU4StVEMK2oplRbBkPVoGK5tHKbVI8ZDqkn4MmNbALzWDwA/OMAz1s/BBTznvOlStTnSr8Dv1hTAIBLW+Xr3a4aigyy09s+hr5t18NvdliJm3G+yPHoK0fLXnc7pyI3yuv8R/0y27r1Q7Mz6bYiZEo3EVnxcsuAKfjQxSehJxHBJad6+9HLE3c/F76Tl+srgVMLeRyZy2J5r/8qk8Vt1WXCGHdRHgsaN59jfm6rgH+5AWE8CnfLc9cP4ss3nI2ixvHWU0Z8jy/YMtaHv7zmDERCIVxwkndNSC9uv/EcfOeZCVz35jWB9x3piWM2U7AofprGcXB6EQCwJkACH8FYv77PxPSixd3Q61ob60/iwIlFTEwtmK+JfXsSEYuSPWsr+D7vU0eyVqQSEcznitaYR8O1NqjbKqDHPT625zj2HJlDrqAhUyjix7sPAdAV7CAq6u9ffgp6EhGcv2GoJuqrXB9R07hZqkV4C7iphnbl8Scv6OcTDeuLLAy60Wl3tXVsg0U1LN3PgZLuxJ0VY6B0Hal6ChBLn1pkRvVSiJyY2X4XRsdWo3DyJcrFz1XiKKNHX8btt97o2RYvZSmy9kLgqe3K51FLVGtsevW1b6wd59AKOcSOvqzcLr9jcs7BeBF/c92vKc1bAIDH/BfKAG+X01Q8guT+7VjccLGrgum0COGlZFX6HajEmmpaUVeIwqX9nK53V9UwFEH/RTch8/ovPNtXSWwwAHzzyf1YzBdNZVXVCBVGNVDKdF4L3PqhXp+3lCHjsYnIEy6/0gYD3TF89LKTfY8pu7D5qTByspAXDs4qPYSFIRcJMVe11KI8Sglz8lJNRlW3VcD9YW43HgHg3WeqxTnaqcTgs7N6sEvpO3JiOBXHa0fnLbGGR+ay5gPZK87VDbFPJq/hjRMlY9CrBqMeW3sC41OL5muyqifH0JZlW83WX3kEhHGaNUuF5AqaqcR5uWm7IbLY5osce46k8dz4tKmYqyZdEiRj4YqvASdS0nc1nyuY5yeMR7e+lo3HyZlF/PB53Xi89NRl+LP3nhGoDbLyKhvs1nIf6jGPduXRdDkm47FjqCS5h0ylSUmS+x/DX37uVotL699/8bOehp+YZJe5BmoFTG+/G+sLbyAVv9nzc70mpfkNF6Nv2wGg8Eagc6mWdLaAr2/fq1xj062vPQ1sAGAMs0/cg+FCxvn9oMfkHIwxJPc+huW9b1E+JsvNK23ntxCW2P8YJicOoH/bdUC49MxyMspU3FGD1DmVvwOlWNNwBMlXfgymFVyvd0+DjTFwzrG4dhsOz2aw6+CMowFcqSeBxmExyoIaoQ8+M4ELNw67tisItVhI6SSoB5pIEOVRFTl5hl+WSLn0wwuTs7hUYSAupeZ3r6cXCYcQCTEUNG4p1ZEvyKu9KsqjcFt1fjAJQ6sd0vsLA1hWHscl9c8rw64bssH50iHdDTMWDnnWnhTZU4/MZZEtFBGPhC3JaKLhELpiYSzkimVuqyLbar1qPAp6bK6cc5aajBUojyutGVdF3OyynjjeYmRfbRapeOkZMZ8tmsbjgmEsO8U7AlavgLt/dcB0jwtqDAP6/ZyMhrGYL7q7rfooSclo2MwubXfBLS1O0HDUKdQjM2qQz05MPouZp7Zjw7nbfCeCbnGUsaMvY//2n4Gdu81zfxWFqPf8a6E9cVslp+P4eV7xWpXEyXn1dTpbQG8ygtNX9uKlQ3MoalZVN/Lqz7F/+12ATz/Z8TPaB3yMbXs/RKb2QstnA8e92mHQVex1OILcyKmeixAqSpYq9u9A2WCLJJDY/5jr9e5nsDHGgHAUt97zrOW7lQ3gWnkSBDVC80Xu2a4g3j+VGvEy9mtuy8o+07DVw1gYMvmir5Gbzhbw1N7jYOwQRnriuHLLaNV9XGtotG4i8gpXrVYyLMqjz0r+QHcMo30JTM5kyoqkuyHUBr/VuXgkhEKuaMZWAUC2WDIkVdxWS+UG8ihqHOFQ6UFQ1LhZlmO4Z+nHSjkbjyX1z6u2pxvyPi8f0pPB+C1SyAbnwekM1g93m4lxhJLdm4jqxmPGHvNoqGEeymYt6JbcfQBr4p5K1KuTRlKIhUPIFTU8tOsQfrVvCoA+eZGvuWZQHm+oewcsGoZ60sVQ74lHzAUcUbB7oCuKS33c3t3ojkcM41F2Wy19/37PA8YYuuMRzGUKZXFeJZfj1hoc6w1jLAXgzwC8H8AggJcAfIlzfpfCvssA/BWAdwHoAvAsgD/hnD9cvxbXFlfjgBcB5j8eyteck8FUa+xGpyr1yEbqhkoZiqCJTQDn+9vVCNUKWHxjF4YyE/j7L34Wf/jf/lx/OZLAwy8dVlaIKjXaXdt17u8ie+AFJNed6fqZQRIehQoZz0UIVSXrekWvJ/t3UKtYU1WDTTbQAKsB/I7TV1TtSfBv2/dh3bCaa7Fqu4K4mKr2w879J3Du+kGL2/ETrx/DE6+fKFs88cLJyHW7dj/33d34yKUb8bHLNrZMeRMyHpvIQB2MR0vMo4IL3+bRXkzOZCz1BL0QaoOf0pCIhjGfK1pKdcg3QyyA8si5ntlRTuM/tZAzb9J2Uh7nc0Us5AroikUwMS0Zj/2VuK2W1Eqh3nq5rNr3GZ9a0I1HKWGO/juCQ7OlSb9AGI/1Vh7FvSLcH63KY3ADJBoO4eTlKew+OIufvnjYfL0Sla7WyG6rsuEm3HTd3FYZY+jviuJYurRa/Z6zxpQWbZzoSURwLJ21GH7iWRAOMSXVsMfBeNQ0bn5/lXx3S5z7AbwZwKcAvALgAwDuZIyFOOffctuJMRYH8DCAfgCfAHAEwEcA/Igxdjnn3DtAqUWoRWbUVo0llKlHNlInRBkKuCRdAfRJftDEJm5qnKsRysJIrjsL/PUZpOIRcKNt09uuwz89utfcTJ48z+eKrmppUKPdK34vue5MRE7sBRvZoBz3WimqShYzPt9rW6fvoFaxprVSDT1dlxV4dM8xPP76sbL655Vy385xJKJhvPWUEYuh53ad+WUdF+x4Yxq33LED7zlzJcAYvlNBplug/L58cu9xPP7acXOxVyZb0PC3P3kFAPDxt9UuLKYayHhsIrIBVqskI1bl0f+Yp4324uGXjmDvsXnTaPFCqA0qyiMAi/KYlzKvRiMK2Va7rMaibDxaC4urp5NuVeRyHcfmclgzFDHdVge7YxVdH31JPUbRkiwn7j1QyMrjxNQisoWiGf8nDAQxyS9THhsU8yge9uK8ZCO2UvXqtNFey0P7jLG+wDWz6oH8fcnunsJQd3NbBfR7VDYer6ki0F8sOsxbjEfjWZB0d2G3HqM8c+x8rmBOFCpJdrRUYYxdCeDtAD7AOb/TePkRxthaAH/NGLubc9fihL8NYAuAbZzzx43jPQJdffwrAOfVt/W1xck4mH3iHvRfdJPrPkIhun/neMvFEtpRnpwXMoGUORnVMhSJaDjwRNctAYxKnFw6W0Bm7YXoFwlmJMTk+YXJWbxyeK4mheRV2lXoW4W/e9+Z+PTn/1w57rUSVBcNZhbzeNOqPuzYP+26jdN3UKtY01rFH7t5EgQxBqUpYtVoHPjGE/tx16/ecDX0vr59n/neg0+rG775Ise9O4Mtwrhx385xZRfy2x7Zg5svWNcSLqxUqqOJyBeAX3yiKsmgyqMR78V5ybXRiyDKI2DNtpqTEubEwv4Ghr3cgIycWGY41T5uqwBwNK0/7IXbaiWqo8C+b8pHeVzRl4Dw1ByfsmZpFfF24lp1y7Zad+PRzEAq3FblmoyV3Udy8igAZsmNZtNtUR5L34VImJP06Gv5Hj1leQpbxnpdt/Uj5WD4yfHPSsewfW8AHK+vDuEqAGkA99he/xqAlfA2AK8C8LIwHAGAc14A8E0A5zLGWuPirYKZ7Xch+fovyspkyCUxlGMJA9Sqqwe+5T44h1YsYPGkt1VcHkC1DIVqeArgXX5ENU7u0VeOYnHdhfo5uLRt98HZisuEVNqu3QdnLaVc6pEARXWC//3nJ10NR78SMFedPYZrt65yvE+Sr/8CM9t9PeBNI9QRxdIU0ws505Pg9hu3ouulH2D6l99A10s/wN++/yzf8iZ2QgxKJXJUEIbevS6lUMR7tTRcg6BxKBvu2YKGh3ZN1rlFanTOUm8LMhAg26oq1oQ5/g8vOWnOi5NzOHvNAAB9Qv7g0xO49NRlZh1EzrmpPPplVxTlOuQ6jzlZeVSp8ygrj/NWQ8WqPLaB26qkPIpzmzCMx0oyrQpWDXThJWlRwG+QjIZDGO1LYmJ6ERPTi5akOMIwE+peWbZVUeex3qU6JEOGc25pY6UGiHwfRMMMv+E2mDaYHll5lI1Hn4Q5ANCXLN0/15yzqqpYCaGAzjm4rfo9C0rHsCrGgM3w7yzjcQuAFw2jT+Y56X03n8stAB51eF3sezoA11m3ES9pr2V0EgDc+u1n0LdS3cCwM7n5Oixf+U5M9us1b5evfCdme3rxhe/v9txv9qwbsfykd2O2R78Pl5/0buR7erFhuBt7Xt+PbD6PeDSK9RvWYtfBGew6OIOphZxSLOHsOTcjlEubx//C93dbPs+vbX7tVDlGX9LqQl7WznDEVZl75OUjjmOc3BYt0afU/pcPqX23LJvG+jUrzL4uahyzmTwKRY5QCJjPuIniVu5/ehwIRVDpk+feHeN4dnxaud/leYEXDz49XvdroKjpLql+ZkFZjJxhaLPcAtavXmZ+B16sd7hPXj+2Dstv+Aula5VzjuFUDMfTOVt7OaDw7T2656iljbnlW5DomkWupxf/8MvXEMrNQ0v2KyfD0jgw2BXB8UOHUAjFEE6klPbrBL7ysz2BF1WcmDn4elX7k/HYROSi2LVSHmUjVKVu2trBLjN75guTpZv/T7/3Au7ZMY5fW3sQ935YdyVayBVN9VDdbVWOeZTdVtXrPALWzI5A+xmPyyzKYw6axjE+XQvj0bqvivvrWL9uPI5PLViT0UgJcwBYjLZcQTMnct0NKdWh1w3NFjQcni1dC5Vm7JSVx0tPXWZxkW4mFuVRMrT8SnUApedLiKHqWJ6Ug9uqqgt76RjWWFXA7nLcUcPREACn0fuE9L7Xvk6VzFX2BYBbAHzW6Y3nxmcQy7oXSfeldw0SvYC4IxO9QAH6wqQnA2uRGNC3BWD+/crhNNA9hCgATfwfEK17CFr3kHnMFyfnLJ/n2zaFdgY6hhsuk+Nj6Zyz4Wlriwpy3LQXPJ6qqK8r/TzXdsD4zmvc70fTuda8BgDzOuCxrmDfgf0+qUU7mZpz4qGZLA7NSIa7vW+T/cbx1A3AY3N5oHsI9Z1NLD3GpxfNuWE15I56L0j40VGjdauxrDeBd5+5Es+NT+Ptm5fX5JirBpJ4x+blePVIGpef5p9ZMRRi2LSiBzvfmDYfKnOZPL733EEAegkPbtRVCpKaX09L7K48xlXqPHbLbqvOymMiGmqLmjuD3TEwpi/MHZ3L4lg6a/ZXNW6rduNRZZFi1UAST+3T3VatymMpYQ6gZzkV18aC5IroFzdbLT2WDKQF/OB5/VrdMNJdsfLY1xXFDeeuwU9fPIyPXraxJu2sBZb6iDkpYY7xt1eQ/3vPHsPPXj6Cq88ZwzLFQtp+7XBKmOP3LDCPES8/huX66izlEfAWJfwEi2r2vR3l7rInAfjOm1b1oW+ld6mCICzkCigYysqrL+xCem4WKUMJEX+fvHmL8vHkYwyvO8U6YXVhRV/cUx2Xj3ny5i0Vt9NrP/Fed28/RtZuRLHIEQ4zaJpeFsmP0PxxhHJp17YUNY5XD6ddv3jOORg4TlnRiz37xj1VoOFUDCM9cbz6wi4ssgSi/ZXNTRj0hV2V8/NjOBXDcCrm6D0h973z4TcAACAASURBVDtnIRR6jThJF0OFATh5ecqSSdvtGuju7QePdiGbLyAejWDjhrWeGbidroGukdXgyX7rd8M1JcNsRV8cx/a94nhdbdh0uqE2qrWNc45j6Vy5usg15GeOIsEzOMXhGtfnIw6LF8b1E1qcxqkbVpf1oRNFjePQbKYs2Z4X4nr0bEuHwBhwzup+RBTmz37MxKdRjQPs0p91L3G+fMPZNT0eYwz/+Ju/Fmif00Z7DeNxFprG8dDzh8xENwu5IqYW9EynQVLzi0ltNu+cbVVFeZTLDdiVRxHzOJyKt0zq4mqIhEMY7Irh+HwOR+eylpWlSmo8lva1KY8Khp3Y5/BsBifmS/1uVx6LGsdCrojueMRi2PhldK0W+RyeeP24uTpbTUIYAPiLq8/AX+CMqo5Ra+KRsJmJT3b39Mu2CgAXnDSEX/3x5TVph708CufcTJgzoKjS2o8B2ONVO8p4PA5nhVBYbl7yXzX7gnN+BHqGVhPxDP2b95+F008/3Wv3QOw+OGNOFD/yrT/Ca09tx0ojKY74+zN/8F3l48nH+NNP3I8Pfu1x8FDEdQyIhhn+9D1neNZT+8QjdyNz9AQGRwbxPz9xDf6wwnZ6nZ947+xzt+H/+2TpOG4Jf+zED+9Ccv9jnm1xPZaxwJd8/Zf45M234uOf/jZOJMaQXLMFYKXnh5xxlDGGD3/788hf8FFlV0M779uqZ9K1lw6phGPpHC49dZlj6QV7v78eWeOZbOl9W1eVHUc+xmf+4Lu45Vt/hGORNUhsuw4IR01Fb++xec9EPuI4K7ZdhtzIJv26WjiAL37209g1MYPHXz9ulHNQm/xftHEEDz/42bLrauDaT2LvsXXQJLXRr23u1xpDtH85Yq//Ap9513Vl73qVZJnefjfWF97AZz7+3bI+dCOdLQS6JmYW8/iLq98EALjljh1K+zQCfUEGDXWn/R+Xn1KzbKu7d/fix1+ofH8yHgkzac5Crog3Tizg3p3WB8zE1CIGu2OBlEfHbKuy26rCyolcbmDKrjwaxmM7uKwKRnriJeNRqvG4arCahDlWw9OvziNQqg+pceDlwyUXF3vMI6BP/rvjEbPuIFB/5VE+h3/bvh+A/vyuZZr1ViIVj2BqIW+6e+YKmqnmeMU81pIeY/KdK2jG52umMq6aMKdHUi+FYm1NmNNRw9HzAG5gjEVscY9i9WKXz75Oqxwq+7YNqXgEyf3b9fIULgaOW90+y4R405Xo3wQsQJ+cVlLiI50tIDN6Fvq2rUFmZBCxoy8p7VerWn2AR91MY5KfGFutT9o3XQkxooQZsGm0F9s2DOHcDdbsrmYSnoDYjVC/Eg7iWeCHKAnh52k0s/0ujI6tRuHkSyoux+GXIRYoryGYzhawOHoWll33XzC9ZgsQCpvX1SfvfRanLO9xLMPgRTIaLruuVEqyOLVNNTuuvX/lkjpP7T2B6YUc+rtiuOeLH/Wst+mGb5ZYGyKbKwevehGiljRStIhHQmadx1aho0Zrwhk5WciPdx/CU3utC9fjUws4Y1WfxYDzUxtM5VGq8yi7sKrUeQRK5Qbs2VaF22o71HgU6OU65nAsnTXLdAC1dVtVcfGVlc4XpMHOnm0V0JOfjPYB89nGKY/yOTy1T79Wt500hJVV9FMrk0roxqNQ7BYlldcr22otkWNl57MFLEgeBaoJc8QxOIepWFuTHXXUcPQAgA8CuAbA3dLrNwM4COBJn31vZ4ydxzl/EgAYYxEANwF4knN+sD5Nbj0S+x/D5MQB9BsKkcDPUHCrBRi0xIebEbpw8tvRh2XgPseoVa0+wHuSP41lyDgYHEWuZzvdPNpbNjbwWPCC7VvXDuBDF59kOZabURsJAdrcMWjdw0rqpjAiLtvkH46T3P8Y/vJzt1r6QS7s7kU6WzAzxLoZCLIha78GnEahfJEHNhxDDLjzV2+UX1cs5FuSxW5kq2ah9erfVDxiee8+nxIgXohr4r6d40plPOzzv0Zy+sreslIyXsgLMqeP9WH3wVlML+SQjIbx3MQ0njmgHmu47aQh/MaZK3HFltGWKM8h01GjNeHMphU9ZrzdbY/sKXtfqGDyDeynNvgpjzGFOo9ASeF0S5gz3GbKI6Cfm8i0qtdqrPyh0d8VRXcsbLqVqgyesrH6opHaPcRKiXDk2DQx+ZfLLySjjcm2KlOty2orI9x0TeNRMtzqrfIK5D5PZwuYkYy+oDGPgG6AdscjpttqIhpCPNI5qRE45w8xxn4C4KuMsV4AewDcAOCdAG4SNR4ZY/8M3aA8iXO+39j9XwB8BMA9jLFPQXdBvQXAqQBq46e8RGDQlaZ1OIJrP/0VJUNBucTHE7ch5DNB9ipI33/RTci8/gvP/WtVq89+THmSfw+gVAPSbnCw3LzyZwrOWTPgq1xNzWex9/gCnhuf1g1HfSOl4wcxIuz9oMqTe4/7ZoiVDVnXa6BKNA5odoPFw0XbqW0C1ZqTjTLSxDWRiIbxjSf2+27f3xUD9w3lFsdWrjDiibwAdWQui1u//SyKHgcOMeCm89fiopNHLPfAcinfQCwaUjIewyGG/3r+Gnz23ae3bFgW1Xkk0BWLYP2QvsoosmtuGes146kmjPg7uVxGf1JNecwUXLKtBlAeAWvCnHxRM1XQdlIeTeMxncWBGpTpAPSH9Jh0DBW31dH+hDmWi2QHvVIheLvbKgAsNFJ5tJ1DdyyMd25ZUdfPbCamu6dxb8rJiZKxxjzC5cFwLlMIFP/seAzDEBbxcB2YLAcArgbwDQBfAPAj6LUdb+Cc3yFtEzZ+zBkE5zwL4G0AHgHwZQDfAzAK4ArOube10qaEChlctkmPibts0zLPRTI/FUaU+MiNnOr5mUFcAb2oRa0+L1RrQNo9jmJHX4KWzyrPxKNhhnPXuydbEsYcYww79k9V5IKo+qyphiCGlu9CRAVEQoBr3psKjWxV1aoR/Svz1lNGfMu2ievKt16qse37t66uqk0hBvzmBWtx+41bcbVR4mrXwRlPwxHQjf14JOz57FE5hzAD/ubaM3HT+Wtb1nAEyHgkDE5baS+Svso0XIQLpVD/UvEIYj4Jb0oJc5yzrfrtL3BSHo9L2bbaKubRMIRzBc1U/KpxWRXIbqgqpTrikTCW91izc8qTe7kchpj8zzcy5tF2DlecMdowBa4Z2BPNyMpjvVVegTXra8EW/xzceBTxm2LxocOS5QAAOOdpzvknOOejnPM45/xMzvldtm1+i3POOOf7bK8f5pzfzDkf4pwnOecXcM5/2tATWKKoGgdaot+IN7semdGzyozAIK6AXsjF1T940QZcu3UVPnjRBtx+41Yk9z+mtyWS8GyLG+lsAfkhtTgp2eBIZwvIjWxCduIlZYPFLb7U3p5KjS0/47RWBDG0fBciAnLRycO44dy1Sq6cXtiNQD+jhXMOaAWcbpsHqlKK+Q12fQrl3QtxXalue/nm5Up1xN245pxVuGLLqOVarpVyq3IOV5+zyqJWtirtO+MiArF5tBc/eE5P3BsJMfzGmSvx6KvH8MrhdJnbqkqCDNNttVA0YwcqUR7FxHRqIW8ep91qPAqGe0oPfHGO1WRaFcjqZY+C8QjoSXMOzZZcpeQafI7KYwOzrdonKO3ssgqU10dsRsyjxW01U7AMkspuqwnrMQCYCXMqrc9JEEFRNQ4ya863JD255Y4dlkQwtXYFdHKz5AD6tl2PaSOm060tdixxeCOnKH1+f1dMKX7PTpBENNUYWyrGaSXYkx1tWdkHFPO+WXzPXT+If999qGbtiIYZfvOCdVUf08nI9nOP1kubRPDJe5/1vK6cWFx7oZmISfX6lHGLiXW6rlS2VUnS5BTH6HUd11K5DXK+rQyN2AQAa5H0S05dhqFU3FS9JqYWran5FW4QoTxyDuSKGuKRMHKWGyWY22quoGExX0RXLIKj6ZJRM9xObqup8tWmat1WAat6qaI8is/dsX/K/F9WHnssyqMR85htnPLYFQubcQ1j/Umc14DV6GYiJkxzjjGPTTAeswVL8qxK3FbTNuWxmrheggiCSpIaMFZWh8+ezbIRroCVZP0EPGIxXRAGh99+p6/sxdY1AwDTF7GCJKIB1BUce9vqMal2S3b0yXufRWRmHIXB9b5ZfGuZxKRWx3Qzsl2z8Ur4XVd2Ksn8asct0ZPTdaW6rYqBNp8rKidU8n1mQF0ZD3K+rczSaSlRV85c3Y9ENIRMXsON560BUDJc5rIFzC4WKlIeAT3LajwStritxgO6rQK6+tgVi+DYXGkld1kbKY9OKupYDYzHs9cMANANDdXj2Y1W2WCMR8KIR0LIFjRTOZKVx3obNIwxbBjuxmtH5/GB89Yg5FEYuR0YSumTz+PpLDL5oqWvG1Wqw6IaZktuq92xsLILuqPxuNi5bqtEc1BJUqOSadNvQsk5B9MKOHf9IO6roJ1Bs37K+wV1DRWudH77vXJ4Dr9/+SkVT3JVDaOLTh7Git6EUvKjSkqkAN4ZdzG4Hov7nkVy9WbPLL4qRoWMiuIV9Jhux7EjjJYLNw77Jn9RKYuiRRIVJWJyI0iCI79tVQy0oJ/np2YGVcYrTejUKpDxSAAABrtjuPdD23BiPoe3njICwOoyeWBqIZDyGJcmtZl8Eb2JaFUJcwBgaj6Hsf6kWeMRaDPl0cF4rIXyeO76QXzzt8/DcE9MOTGJvT6kfb/eZBRH57JlbquxSEj5u62Gf/vt8/DsgWn8+untmyhHcOoK3StA4/rkLZNvbqmOtJQwJ4iq0u2oPJLbKtF43JSJENPvMy9XOzmbpeuE0jD4kvu3IxW/qKI2Bs36Ke+nanjIBsfPXj7iu1+QchlOqCo4v3nBOs+JeLUlUlQy7sbHNqH3qX/EdX/wN67qkGrNwiCKV9A6iIBziRQ3VJK/qHzPKnVAq71eqqWWBlq7uJvWChqxCZMtY32W/2WVamJ60VQbVGKcErLyaCTNEcZjiOmpiFWQP0tMWEU8YCoeadjkuRH0J6MIhxiKUrR8LWIeAeAtJw8H2t5utNqVod5ERDceF60ZQLsb9H2M9SdrkkxoKSC7lL84OWtJptAo5bE75qw8DnSrK4Y9NvWSc07KI9EU3MpHPP3GlP/OKMUxuroCagVMb78bAwq1It2oNKZSdT+7wdGIcg61UnCqLZGimnG3MLDO1/hwuwbken/nbhgKpHiJY96/c9zuEeqIU4kUN2r1PavWAW1mjcZa0i7uprWi886YUEY2IPYfnzddFFXUBll5zBrlOoTbqqqbGwAMdEvKo/EQEsZjOyXLAYBQiGE4FcPhWf38ehIR9DVpUl1mPDooj0ApZm3eKNXRzllPm8X64W7TpfyFg7NYM1QatBsV8xgOMXTFwljIFS0xj6qZVgHdVV0sjqQzBWTyGgqGJdyhpTqIJiMm8vfvHLfEePshxkC3CeU9X/wo9m//Gdi52ypuW6Uxlar72Q2ORpVzqFbBCVIixW1Sr2pA8VjKd5t6GBUWF9N7nrUsKNsJmoW2Vt+zah3QRpf/qDdL3d20VrRsqQ7G2CWMMe7yc36z29cJDHXHkIjql8jug7Pm60GVx4yhPOYM5TGIW2O/RXk0jEfDbbWdajwKZIO4mcrayn678mgdBMVkXyhHQnlslDHTSYRDzHRdfXGyOW6rgDXrayn+WX1iwBizHEMsPABWVZIgnKi0HIDKcYPECLpls5TrTIYKGZe91Tlv/ZCe9dPDxdCpLar18Gq1X1C8SpOIunpe1KJEiqoBxXJppe2A8mugFmrU8t4ErvYxpoPG2tXqe1apA9qo8ipE42lZ41Hi0wAusP3samqLOgTGmGnAPD8xY74uq4FuJByUR+G2GgtiPCZl5VGfbB5rU+URsBrEtXJZrYRENGzpX3s2TDHZFzFr80bMY1cHum80gs2jPQB0t1WR2TbEgt1L1SJnfZ2aV3dhdzuGWHgAyG2VcIdzjvt3juOWO3ZgYdOV6L/oJixsuhK33LEDi2svrPr4QctH1KtkhJ1UPILk/u26MeQyQXdqS5DaebXYr1IqNbZq4Xbpa0BxDq1YAA/HarZIUSlXnT2Ga7euKmtvNMxw7dZVgWPtavU9hwoZzD5xj2cd0EbdK0TjWQrf6quc8yea3YhOZdVAF147Oo+9x0ouCkpuq07KYwVuq7FICKl4xBJnJdxWh1Pt5Q4BWBMA1SJZTjWsGkiafW1PaCIm+3MiYU62sTGPnYaIe5zLFvDqEX01vCvmXoesHoiMq7OLeXPRIKhLkpvySAlzCDe8smLmN1yMvm0HgAbEFoaYXlO2kYkxEvsfw+TEAfQbdR4Ffi6elbqGLoWkILVwu1TJuBsKR7B48tsD1SysB/Vwi62F63Bm9Czg6AlEj74CrDi1Za8Xoj7QiE14IgwYeeFTyW3Vlm0VgPlwCZqNs78rinRWz/CYyRfNendtqTz2tI7xONafxNNvTANwSpgj3Fb1xCem8kgxj3XhNClpzk4jNivRoGQ5AjFRmZhaNF8LrDwaRmLaKP8jIOWRcEIlK2bv+ddCe+K2ij9D1Ri56by1uOKMUd/t7OUjDs9mLP97xeLZYQBmtt+FdTiCaz/9FWXDoVKDYykkBQlSIsULlbqHQPDah/WilrF2lX7PTllu8wAinGPr2gFsGO5uueuFqA9L4du9jTF2F/RMzI8D+FPO+X80uU0dg1NdQJUkGVa3VXvMY7DVu4GuGManFrH9tWP46LeeNl8n47G+yG6z5Qlz9EdHrqjho996GgdOLAAAuuOkPNaDTZLxeNxwGW10fKkotTE+LRuPwZRHcYx0tmhTHsl4JMpRzYqZGzm14s9QLR9xkVHCyg238hG/f/czgPR/JUpWqJCpyHCo1OBo5aQgnqphgBIpsgH16CtH8c0n98MjL02gmoVLhaDfs5sXQEEDduyfwobh7pa9boja0soxjzMA/h7A7wG4FMAnAKwG8HPG2K977cgYW8YYO13+AXBS3VvchjjF3fUrrNRa3VZ1VSpj1gIMNukVBtXh2Sx++uJh8/XlvYlAx1kKjPaVzmn1YPNiHgFg7VDp8wdtca5D0v8/eH7SjAtpVnbYdicVj1i+D6BxZToEPcakSbifA2rPAqdjpDMl11egPCETQQC1zYrpRq1iwMTEWqVW4j07xvHA0+pJeggrbnGA0AqYfvSbSOx/TPlYqXgEsWjI03AESjULOxWVxFIPPjPR9BhRojE0ZMRmjF0C4BHFzc/mnD/DOX8awNPS648yxh4A8DyAvwLwY49j3ALgs5W0lbBiV78iIaa08uakPE7O6BnolvcGUwx/760bcDydNd1VAWDLyj5cuDFY7cKlwCWnLsMVW1ZgpCduqe/XDN71plH89IXDOHl5D1b0WQ31d24Zxb/vPoy9x0uxsMPdcdx43tpGN7NjOG1FL/YfXzD/b3SN026H+z648qi3OW1PmEPKY8egRRLIjWxScuOsR1ZMJ+paPsKFdlSyGkWtS6Q0osblUkclsZQwsEl9bH8a9dR6GcAHFbd1jXznnE8zxr4P4EOMsSTnfNFl09sB3GN77SQA31FsA2Gwylayob8rpuRq46Q8jk/pE9+g7pjnbRjCdz76lkD7LFUS0TC+etPWZjcDgJ5h9Z9/682O7/Ul3d8j6sPmlb340e5D5v+NVh5TDkltghqPqbhuDMxLbquxcMjyvCDaEw6gb9v1mDaSv6i4cfq6lHIOrZBD7OjLVbWt2li/oBlbAZpo1wK72+V9FZZIaVSNy6UMGdiETEOMR875JIB/qtHhxOji+qTmnB8BcMSyUxOyZLUDw6k4YpGQ6aqmmiDDmjBHw6zkptbMEhQEsVQ5zaZENzrm0WkS3d8dtFRHufLYm2xs1liiOWTWXoj+DReXlZ3wSkiikhUzO/ESciObAiWicaPSWD/VibUdmmi3Bqpxr51cs5AMbEJmSS33MsYGALwLwDOc8+qr8BK+hELMoj6qKg2ykpAtFC0ZGsf6m5sIhiCWIptXWo3HRJONx0iImTGMyseQ1MtDhhs7uay2P+lsAYvrLtQL3rssFLjFS7nGtxkk151p1n28f+e4/hkNRnVibYcm2rWjlOX2emRGzwoUe9foGpdLEd/amCADu5NoWeORMfYtxtiXGGPvY4xdwhj7IPRsq8sBfLLJzeso5IyrqgkyQiFmFjDP5DWMS8Zjs7OIEsRSZGVfwlIPsavBbqv2mMf+rmhgxVC4rQLAwWndeOyhJEtty2hfEst743j2wDQQ8laY3RKSCJfS22/cig9etAGnr3SOBW9mIhqVibUdmmjXBs457t85jlvu2IGFTVei/6KbKlpMcFukiIYZrt3a2PqerQgZ2IRMK3/LzwG4DsCHAKQAnADwHwD+K+f8V81sWKchG3tBYpzi0RByRQ2ZfNGMd9SPR26rBBEUxhg2r+zFE6/rE+xmu61WoprIpVwOzugLSr0OsZREezDYHcNgdwwxxZhWLzfOVDyCc9cP4l+37/U8RjMS0fi61zpAE+3a4FY+Imh9xqVQ47LZVJtYimgfWvaO4Jx/CcCXmt0OwmrsBYlxSkTDmMsUkC2UlMd4JIThFLnqEEQlnDZaMh4b7bbaYzPyVOOf3Y4xZ8RAk9tq+6Nak9dvQaKVMz6qFp0PksFVd8P0z0rbqaiWjwiymNDKNS6bDRnYhIC+bcKXipVHY7U5my9iyihsPjaQpOQYBFEhcvmWrmhjH9/lbqsVKI+x8jZTjcf258oto/j0vU9DY2HX57+KG2crZ3x0m1ifvrIXuw/OKk+0Oed44OkJ3QjddKVSVtpOpZUXE9oZMrAJGrUJX8YsCXOCKY+AXudxfFqU6SCXVYKoFDnjajLW2JB1+4S3EuXRqdwHKY/tT19XFH0TT2B69Vv0bKsOxo+KG+dSyPjoNLFe3ptw2bqcWrlhdgKtvJhAEO1MyybMIVqH00Z7MdgdQ4gBW9cOKO8nlEc95lF3W6VMqwRROacs78GaQX0B5qzV6vdiLSg3HoNP0J2Mg15KmNMR9E08julHvwnGi5bX45EQPnrpRvzRFZtwyvIUNi5LYcNIN1YPJjHal8BITwxDKT128tdPX24mYnNjKSeiUXXDDJJJtJ1ZCosJBNGOkPJI+NIdj+CRWy/BfK6AlQGMP6E8Hp/PYdpYIaRMqwRRObFICD/4+FswNZ/HmqHGqvh21bCSCZmj8UgJczoCBmBm+104I3ECH/mL/4Ojc1mM9MRxxZbRQKUuPnrZRvztT15xfX8pJ6IhN8xgUH1GgmgOS/MJSzScvq5o4FpWiai+Qvza0bT5GhmPBFEdPYkoeprg6mkvDVIrt9VmnAvRPMLFLK4/d03F+3/sso0AgNse2YNsQTNfj0dC+NDFJ+HDl2wwYwKLGke+yFEoasgXOTL5IjKFIjJ5DYWihoLG0YSykK6QG2YwVLLcLuXFBIJoVeiOIupGPKJPNkVWRYCMR4JYqoRCDKl4xHSZq0R5jEfCiIaZRSmghDlEEBhj+PjbTsbNF6zDQ7smK1YwBZrGUeS6Ecmh/y5oHPmChnxRQ17j+jbGdmL7osahaUBB06BxjkKRQ6vSECU3zOBQ+QiCaDw0ahN1QyiPMpQwhyCWLt3xsGk8VqI8ArpaMCUpLJQwh6iEvq5oVQqmIBRiCMEhe6ladZEyONeNyIKmYTFXxILxk8kXsZgvouDhYklumMGh8hEE0XjoziLqRiJidXOLhUMYSVU4IhME0XRS8QgOIwsAGOiuTP3othuPlDCHaCMYYwgzIBwKIx4Jo9+2XpozFE0A4NCNzcV8EQvZIuZzBbxv6yrc+dQB1+OTG6YzVD6CIBoHPYGIuhG3KY8r+xMIhag+FUEsVVKSSthfhfIoQ8oj0UnEIiHEItaxsScRBXr0v7941RkY7UuWxXTGwiG89+yVeO9Z5IZJEERzIeORqBtxm/JILqsEsbRJxUv3dH+yMuWxzHikmEeCMPGL6ZTdYjM5DfO5AhZyRcxn9d8EQRD1hkZtom7YlUdKlkMQSxth+KXikTL1RPkYUsbVcIghacviShCEe0yn3S1WTrKTL2pIZwpIZwsoStl7OPTMsxrXfziHJUGQE+L90n4wt+W2neyHaKUMtgRB1B4yHom6YY95HAtQI5IgiNZjeW8CQHX3crekPPYmImZZBYIgqiMaDmGgO1ZxPHIt0Qyjs2hkos0XNeQKGop2w5PrxqfmkqrWNFihG7C68ctR0KwZb4vifzJcCaLukPFI1I2ETVFYNUjGI0EsZX73rRsAAO9608qKj9EjG4+ULIcg2hKRxTYCoJH5fQpFDfPZIuayeaSzBeQLJWtS4xzZgmZRZQmCCA4Zj0TdiEfsbqsU80gQS5lVA134wnu2VHWMlEV5JOORIIjaEQmH0NcV8qyZmckXsZgrIq9pgFA+DddcUdMzX9SQM9TSfFFXO4XJSW65RKdDxiNRN+zKI7mtEgRhcVulZDkEQTSYRDRcNj8JQq5g1PDMF5DJayhqmulSq9ujXIoPNX5LkaGy8VkySMstUm5uy033Xm667lbcfIKoGhq5ibqRkBLmRELMjJciCKJz6ZES5vTESXkkCGJpIcqt9KF5zy9uJjEqV0SF8co5UOQcxaIee6obt8Z+xl5yzKkmHVM/jv53tqAhW9BVWDJaCYCMR6KOyKU6VvYnEaYajwTR8ZDy2HnMLOQxt+xN6Ns2irllI5hZyHu6FRIE4Y3Iugs0bl7FbYqnxjlyRQ3ZvO7iW9B049RUR1Eybp0UVM/Pkoxby2/b68Ha7/1ZXvs4bSEb2ZV8rhfhUGXZzBsFjdxE3ZCVR3JZJQgCoJjHToJzji//bI9e8H7Dr6N/A3AcwLlf/Ck+culGfOyyjZRtlyCWCIwxyLdrCAyRcAhdzU/uSzQYMh6JuiErj1TjkSAIwGY8UrbVtubLP9uDv/3JK2WvZwua+frH33Zyo5tFEARBVEFr66LEkkZWHinTKkEQAJBKWOs8WG9nowAACuRJREFUEu3JzEIeX3lkj+c2tz2yBzML+Qa1iCAIgqgFZDwSdUPOZjZGyiNBELAqjz3kttq2/HDXJHIFzXObbEHDQ7smG9QigiAIohaQ8UjUjVOW92DjshSGUzFcfMpIs5tDEEQLsHFZCptW9GCwO4a3nDzc7OYQdeLoXLam2xEEQRCtAfkMEXUjFgnhx7//VmicIxqmdQqCIIBoOIQffvwiFDSOWISeC+3KSE+8ptsRBEEQrQGN3ERdCYcYGY4EQVgIhRgZjm3OlVtGEff5juOREK7YMtqgFhEEQRC1gEZvgiAIgiBqSl9XFB+5dKPnNh+5dCPVeyQIglhikNsqQRAEQRA152OX6cbjbY/sQVZKnhOPhMw6jwRBEMTSgoxHgiAIgiBqDmMMH3/bybj5gnV4aNckjs5lMdITxxVbRklxJAiCWKKQ8UgQBEEQRN3o64ri+nPXNLsZBEEQRA3oJOMxBgB79ngXLSYIgiCWNtJzPtbMdiwhaHwkCILoEKodIxnnvHataWEYY78B4DvNbgdBEATRMN7DOf9usxvR6tD4SBAE0ZFUNEZ2kvHYB+BiAAcA5Co8zEnQB9j3AHitRk1rB6hfnKF+cYb6xRnqF2cq6ZcYgNUAfsE5n6lXw9qFGo2PAF3DblC/OEP9Ug71iTPUL85U2i9VjZEd47ZqdE5VK9CMMfHna5zz3VU3qk2gfnGG+sUZ6hdnqF+cqaJfnq5Dc9qSWoyPAF3DblC/OEP9Ug71iTPUL85U2S8Vj5FU55EgCIIgCIIgCILwhYxHgiAIgiAIgiAIwhcyHgmCIAiCIAiCIAhfyHgMxlEAnzd+EyWoX5yhfnGG+sUZ6hdnqF+WDvRdOUP94gz1SznUJ85QvzjTlH7pmGyrBEEQBEEQBEEQROWQ8kgQBEEQBEEQBEH4QsYjQRAEQRAEQRAE4QsZjwRBEARBEARBEIQvZDwSBEEQBEEQBEEQvpDxSBAEQRAEQRAEQfhCxqMCjLEUY+zvGGMHGWMZxtgzjLHrm92uRsEYu4wx9i+MsZcYY/OMsQnG2HcYY1sdtj2HMfZTxliaMTbNGLufMbahGe1uNIyx32GMccZY2uG9juoXxthbGGM/ZIxNMcYWGWOvMsb+X9s2lzPGHmeMLTDGjjHG/pUxtqxZba43jLGzGWMPGs+RBeN++gxjrMu2XdteK4yxHsbYXzHG/p0xdtS4Xz7nsq1yPzDGPmb0Z5Yxtpcx9lnGWLSuJ0OYdPIYSeOjOjRGlqAxspxOHyOX0vhIxqMa9wO4GXotlSsA/ArAnYyxDzS1VY3jwwDWAfh7AFcC+ASAZQCeYIxdJjZijG0C8HMAMQDvB/DfAZwC4FHG2Ehjm9xYGGNjAP4XgIMO73VUvxj3xS8AzAD4TejXzF8CYNI2FwN4CMBhAO+Bfk1dDuBhxli80W2uN4yxzQC2Q7+Pfh/AuwDcBeAzAO6Utmv3a2UIwO8CiAN40G2jIP3AGPtj6M+m+wH8OoDbAXwawG21bz7hQiePkTQ+KkBjZAkaI8uhMRLAUhofOef04/ED/abmAG6wvf7vACYAhJvdxgb0wTKH11IADgH4qfTat6EXKu2VXlsLIAfgL5t9HnXuo+8B+C6AfwWQtr3XMf0CYAxAGsDtPts9BWA3gIj02jbjXvtws8+jDv3yZ8a5nWR7/R+M1wc64VqBPjkS9YWHjXP/nMN2Sv0AfbBdBPAPtv0/DUADsLnZ59zuP50+RtL4qNxPNEZyGiM9zrfjx8ilND6S8ujPVdBv9Htsr38NwEoA5zW8RQ2Gc37E4bU0gBcArAYAxlgE+krRfZzzWWm7/QAegd6PbQlj7CYAFwO4xeG9TuuX3wHQDX0V1RFjBfrNAL7BOS+I1znn2wG8gvbrEwDIG79nbK9PQ3+I5zrhWuEGXtsE7Id3AkhAfx7LfA36QPzeWrSb8KSjx0gaH/2hMdICjZHOdPwYuZTGRzIe/dkC4EX5BjZ4Tnq/42CM9QE4B/rKGACcBCCJUr/IPAdgI2Ms0aDmNQwj/uDvAHyKcz7usEmn9ctbAZwAsMmIeyowxo4wxv43Y6zX2EbcM2590o731NehD4JfZYxtMGIb3gXg9wDcxjmfR+ddK24E6QdxrTwvb8Q5nwRwDO15LbUaNEbaoPGxBI2RZdAY6QyNkWq0xPhIxqM/Q9BvdDsnpPc7kdugr579ufG/6Ae3vmIABhrQrkZzO4CXAXzV5f1O65cxAF3QVYi7ocdo/DX0uI4fMsYY/Puk7e4pzvk+ABdAf1i/BmAWuhvX16HHsgCdd624EaQfhgBkjYmF07Ztdy21IDRGlkPjYwkaI63QGOkAjZHKtMT4GKl0xw7DS0b2lJjbEcbYnwK4EcDHOOc7bG93TF8xxq4B8G4AZ/u5GqBz+iUE3U3i85zzLxmv/ZwxloO++vw2aVu3826n/gAAMMbWQR8IDwN4H/R4hfMA/An0+KjfljbvlGvFD9V+oP5qPvQdGND4WILGSEdojHSAxsjANHV8JOPRn+Nwts4Hjd9O1n/bwhj7LPSb+Y8551+R3jpu/HbrKw7dJaEtYIyloK8ufxnAQcZYv/FWzHi/H7oPf0f1C/TzPRnAj22vPwR9YDwHwLPGa2590o731JcA9AI4S1oF/CVj7BiAf2GM/Rv0BBtA51wrbgS5Z44DSDDGujjnCw7b2ifvRO2hMdKAxscSNEa6QmOkMzRGqtES4yO5rfrzPIDTjCBVmTOM37sa3J6mYQyMn4Oe/emLtrdfg57V6Qz7fsZrezjnmfq2sKEMA1gO4FYAU9LPDdDdlaYA3IHO6xcnP3yglIJcQ+meceuTdrynzgLwgoP7yK+M38JVp5OuFTeC9MPz0usmjLEV0O/RdryWWg0aI0HjowM0RjpDY6QzNEaq0RLjIxmP/jwAXTK/xvb6zdDrFT3Z8BY1AaYXr/0cgD/jnH/e/r6RLOF7AK5mjPVI+60BcCn0GjPtxCHo52X/+TGAjPH3n3Rgv9xn/L7C9vqVxu8nOOcT0NOQ38QYC4sNGGPnAzgV7dcngP6sON1YjZe5wPg93oHXiiMB++FH0O+337Id5regr8C61soiakbHj5E0PjpCY6QzNEY6Q2OkAi0zPlZbl6QTfqDXqzoB4IPGl/OPRsff2Oy2Nej8bzXO9yEA59t/pO02AZiDXvz2Cugpg5+HXutrpNnn0aC++leU17DqqH6BXssrA91963IAn4K+UvY9aZtLoLss3W9s8wEAbxj9Em/2OdShT34D+ory49CL+l4GvdbSHPSMjLFOuVaM83ofgP9mPFe+bfz/PgBdQfsBwB8bffvn0MsB/D/G9fePzT7XTvnp5DGSxsfA/UVjJI2RTn1CYyRfOuNj0ztqKfxAX1X9ewCTALLQ/dGvb3a7Gnj+PzcuYscf27ZbAfwUwDz0ej0PwFb0tZ1/nAbGTusX6Gmkv2QMdHkA+wF80T7gAXi7MVAsQvfN/zocCm63yw9Kq+6TABagZyD8XwCGOulaAbDP43myrpJ+APBxoz+zxvX2OQDRZp9rp/x08hhJ42Pg/qIxksZIt37p+DFyqYyPzDgwQRAEQRAEQRAEQbhCMY8EQRAEQRAEQRCEL2Q8EgRBEATxf9uvAwEAAAAAQf7WIyxQFgHAkkcAAACWPAIAALDkEQAAgCWPAAAALHkEAABgySMAAABLHgEAAFjyCAAAwJJHAAAAljwCAACw5BEAAIAVWTqQPTVG9ksAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.rcParams.update({'figure.figsize':(9,7), 'figure.dpi':120})\n", + "\n", + "# Importando dados\n", + "df = pd.read_csv('https://raw.githubusercontent.com/selva86/datasets/master/wwwusage.csv', names=['value'], header=0)\n", + "\n", + "# Série Original\n", + "fig, axes = plt.pyplot.subplots(3, 2, sharex=True)\n", + "axes[0, 0].plot(df.value); axes[0, 0].set_title('Original Series')\n", + "plot_acf(df.value, ax=axes[0, 1])\n", + "\n", + "# 1st Diferenciação\n", + "axes[1, 0].plot(df.value.diff()); axes[1, 0].set_title('1st Order Differencing')\n", + "plot_acf(df.value.diff().dropna(), ax=axes[1, 1])\n", + "\n", + "# 2nd Diferenciação\n", + "axes[2, 0].plot(df.value.diff().diff()); axes[2, 0].set_title('2nd Order Differencing')\n", + "plot_acf(df.value.diff().diff().dropna(), ax=axes[2, 1])\n", + "\n", + "plt.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Para as séries acima, a série temporal atinge a estacionariedade com duas ordens de diferenciação.\n", + "Mas, olhando para o gráfico de autocorrelação para a segunda diferenciação do lag, entra na zona negativa muito rápido, o que indica que a série pode ter sido super diferenciada.\n", + "\n", + "Então, tentarei fixar provisoriamente a ordem da diferenção como 1, mesmo que a série não seja perfeitamente estacionária (fraca estacionariedade).\n", + "\n", + "\n", + "# Como encontrar a ordem do termo AR (p)\n", + "\n", + "A próxima etapa é identificar se o modelo precisa de termos de AR. Você pode descobrir o número necessário de termos de AR, inspecionando o gráfico PACF (Plot de correlação parcial).\n", + "\n", + "Mas o que é PACF?\n", + "\n", + "A autocorrelação parcial pode ser imaginada como a correlação entre a série e seu lag, após excluir as contribuições dos atrasos intermediários. Portanto, o PACF meio que transmite a correlação pura entre um lag e a série. Dessa forma, você saberá se esse lag é necessário no termo AR ou não.\n", + "\n", + "\n", + "Agora, como encontrar o número de termos de AR?\n", + "\n", + "Qualquer autocorrelação em uma série estacionarizada pode ser retificada adicionando termos de AR suficientes. Portanto, inicialmente consideramos a ordem do termo AR igual a tantos lags que ultrapassam o limite de significância no gráfico PACF." + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# PACF plot da serie diferenciada 1x\n", + "\n", + "fig, axes = plt.pyplot.subplots(1, 2, sharex=True)\n", + "axes[0].plot(df.value.diff()); axes[0].set_title('1st Differencing')\n", + "axes[1].set(ylim=(0,5))\n", + "plot_pacf(df.value.diff().dropna(), ax=axes[1])\n", + "\n", + "plt.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Você pode observar que o lag 1 do PACF é bastante significativo, pois está bem acima da linha de significância. O lag 2 também é significativo, conseguindo ultrapassar um pouco o limite de significância (região azul). Mas vou ser conservadora e, provisoriamente, corrigir o p como 1.\n", + "\n", + "\n", + "# Como encontrar a ordem do termo MA (q)\n", + "\n", + "Assim como observamos o gráfico do PACF para o número de termos de AR, você pode ver o gráfico do ACF para o número de termos de MA. Um termo MA é tecnicamente o erro da previsão atrasada.\n", + "\n", + "O ACF informa quantos termos de MA são necessários para remover qualquer autocorrelação na série estacionarizada.\n", + "\n", + "Vamos ver o gráfico de autocorrelação das séries diferenciadas." + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.pyplot.subplots(1, 2, sharex=True)\n", + "axes[0].plot(df.value.diff()); axes[0].set_title('1st Differencing')\n", + "axes[1].set(ylim=(0,1.2))\n", + "plot_acf(df.value.diff().dropna(), ax=axes[1])\n", + "\n", + "plt.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Algumas defasagens estão bem acima da linha de significância. Então, vamos tentar usar provisoriamente q como 2. Em caso de dúvida, siga o modelo mais simples que explica suficientemente o Y.\n", + "\n", + "\n", + "# Como lidar se uma série temporal é um pouco abaixo ou acima da diferença\n", + "\n", + "Pode acontecer que sua série esteja ligeiramente menos diferenciada, aonde diferenciá-la mais uma vez a torne um pouco super diferenciada.\n", + "\n", + "Como lidar com este caso?\n", + "\n", + "Se sua série estiver um pouco menos diferenciada, a adição de um ou mais termos adicionais de AR geralmente o fará. Da mesma forma, se houver um pouco de diferença excessiva, tente adicionar um termo MA adicional.\n", + "\n", + "\n", + "# Como construir o modelo ARIMA\n", + "\n", + "Agora que você determinou os valores de p, d e q, você tem tudo o que é necessário para se ajustar ao modelo ARIMA. Vamos usar a implementação ARIMA () no pacote statsmodels." + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " ARIMA Model Results \n", + "==============================================================================\n", + "Dep. Variable: D.value No. Observations: 99\n", + "Model: ARIMA(1, 1, 2) Log Likelihood -253.790\n", + "Method: css-mle S.D. of innovations 3.119\n", + "Date: Fri, 25 Oct 2019 AIC 517.579\n", + "Time: 21:57:36 BIC 530.555\n", + "Sample: 1 HQIC 522.829\n", + " \n", + "=================================================================================\n", + " coef std err z P>|z| [0.025 0.975]\n", + "---------------------------------------------------------------------------------\n", + "const 1.1202 1.290 0.868 0.387 -1.409 3.649\n", + "ar.L1.D.value 0.6351 0.257 2.469 0.015 0.131 1.139\n", + "ma.L1.D.value 0.5287 0.355 1.489 0.140 -0.167 1.224\n", + "ma.L2.D.value -0.0010 0.321 -0.003 0.998 -0.631 0.629\n", + " Roots \n", + "=============================================================================\n", + " Real Imaginary Modulus Frequency\n", + "-----------------------------------------------------------------------------\n", + "AR.1 1.5746 +0.0000j 1.5746 0.0000\n", + "MA.1 -1.8850 +0.0000j 1.8850 0.5000\n", + "MA.2 544.7269 +0.0000j 544.7269 0.0000\n", + "-----------------------------------------------------------------------------\n" + ] + } + ], + "source": [ + "# 1,1,2 ARIMA Model\n", + "model = ARIMA(df.value, order=(1,1,2))\n", + "model_fit = model.fit(disp=0)\n", + "print(model_fit.summary())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "O resumo do modelo revela muitas informações. A tabela no meio é a tabela de coeficientes em que os valores em \"coef\" são os pesos dos respectivos termos.\n", + "\n", + "Observe aqui que o coeficiente do termo MA2 é próximo de zero e o valor P na coluna 'P> | z |' é altamente insignificante. Idealmente, deveria ser menor que 0,05 para o respectivo X ser significativo.\n", + "\n", + "Então, vamos reconstruir o modelo sem o termo MA2." + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " ARIMA Model Results \n", + "==============================================================================\n", + "Dep. Variable: D.value No. Observations: 99\n", + "Model: ARIMA(1, 1, 1) Log Likelihood -253.790\n", + "Method: css-mle S.D. of innovations 3.119\n", + "Date: Fri, 25 Oct 2019 AIC 515.579\n", + "Time: 21:58:38 BIC 525.960\n", + "Sample: 1 HQIC 519.779\n", + " \n", + "=================================================================================\n", + " coef std err z P>|z| [0.025 0.975]\n", + "---------------------------------------------------------------------------------\n", + "const 1.1205 1.286 0.871 0.386 -1.400 3.641\n", + "ar.L1.D.value 0.6344 0.087 7.317 0.000 0.464 0.804\n", + "ma.L1.D.value 0.5297 0.089 5.932 0.000 0.355 0.705\n", + " Roots \n", + "=============================================================================\n", + " Real Imaginary Modulus Frequency\n", + "-----------------------------------------------------------------------------\n", + "AR.1 1.5764 +0.0000j 1.5764 0.0000\n", + "MA.1 -1.8879 +0.0000j 1.8879 0.5000\n", + "-----------------------------------------------------------------------------\n" + ] + } + ], + "source": [ + "# 1,1,1 ARIMA Model\n", + "model = ARIMA(df.value, order=(1,1,1))\n", + "model_fit = model.fit(disp=0)\n", + "print(model_fit.summary())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "O modelo AIC reduziu, o que é bom. Os valores P dos termos AR1 e MA1 melhoraram e são altamente significativos (<< 0,05).\n", + "\n", + "Vamos traçar os resíduos para garantir que não haja padrões (ou seja, procure média e variação constantes)." + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Plot erro residual\n", + "residuals = pd.DataFrame(model_fit.resid)\n", + "fig, ax = plt.pyplot.subplots(1,2)\n", + "residuals.plot(title=\"Residuals\", ax=ax[0])\n", + "residuals.plot(kind='kde', title='Density', ax=ax[1])\n", + "plt.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Os erros residuais parecem bons com média próxima de zero e variância uniforme. Vamos plotar os valores reais em relação aos valores ajustados usando plot_predict ()." + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Atual vs Previsto\n", + "model_fit.plot_predict(dynamic=False)\n", + "plt.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Quando você define dynamic = False, os valores lag na amostra são usados para previsão.\n", + "\n", + "Ou seja, o modelo é treinado até o valor anterior para fazer a próxima previsão. Isso pode fazer com que a previsão e os dados reais pareçam artificialmente bons.\n", + "\n", + "Portanto, parece que temos um modelo ARIMA decente. Mas esse é o melhor?\n", + "\n", + "Não posso dizer isso neste momento, porque ainda não previmos o futuro e comparamos a previsão com o desempenho real.\n", + "\n", + "Portanto, a validação real de que você precisa agora é a validação cruzada de Out-Time.\n", + "\n", + "# Como encontrar o modelo ARIMA ideal manualmente usando a validação cruzada Out-Time\n", + "\n", + "Na validação cruzada Out_Time, você dá alguns passos para trás no tempo e projeta no futuro quantos passos você deu. Em seguida, você compara a previsão com os dados reais.\n", + "\n", + "Para realizar a validação cruzada fora do tempo, você precisa criar o conjunto de dados de treinamento e teste dividindo a série temporal em duas partes contíguas em uma proporção de aproximadamente 75:25 ou uma proporção razoável com base na frequência temporal das séries.\n", + "\n", + "Por que não estou amostrando os dados de treinamento aleatoriamente, você pergunta?\n", + "\n", + "Isso ocorre porque a sequência de pedidos da série temporal deve estar intacta para usá-la na previsão." + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Cria Training and Test set\n", + "train = df.value[:85]\n", + "test = df.value[85:]\n", + "\n", + "# Cria Modelo\n", + "# modelo = ARIMA(train, order=(3,2,1)) \n", + "model = ARIMA(train, order=(1, 1, 1)) \n", + "fitted = model.fit(disp=-1) \n", + "\n", + "# Previsao\n", + "fc, se, conf = fitted.forecast(15, alpha=0.05) # 95% conf\n", + "\n", + "# Cria como um pandas dataframe\n", + "fc_series = pd.Series(fc, index=test.index)\n", + "lower_series = pd.Series(conf[:, 0], index=test.index)\n", + "upper_series = pd.Series(conf[:, 1], index=test.index)\n", + "\n", + "# Plota\n", + "plt.pyplot.figure(figsize=(12,5), dpi=100)\n", + "plt.pyplot.plot(train, label='training')\n", + "plt.pyplot.plot(test, label='actual')\n", + "plt.pyplot.plot(fc_series, label='forecast')\n", + "plt.pyplot.fill_between(lower_series.index, lower_series, upper_series, \n", + " color='k', alpha=.15)\n", + "plt.pyplot.title('Forecast vs Actuals')\n", + "plt.pyplot.legend(loc='upper left', fontsize=8)\n", + "plt.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A partir do gráfico, o modelo ARIMA (1,1,1) parece fornecer uma previsão direcional correta. E os valores reais observados estão dentro da faixa de confiança de 95%. Isso parece bom.\n", + "\n", + "Mas cada uma das previsões previstas é consistentemente abaixo dos valores reais. Isso significa que, ao adicionar uma pequena constante à nossa previsão, a precisão certamente aumentará. Portanto, definitivamente há margem para melhorias.\n", + "\n", + "Então, o que vou fazer é aumentar a ordem de diferenciação para dois, que é definido d = 2 e aumentar iterativamente p para até 5 e depois q até 5 para ver qual modelo oferece menor AIC e também procurar um gráfico que fornece dados reais e previsões mais próximos.\n", + "\n", + "Enquanto isso, fico de olho nos valores P dos termos AR e MA no resumo do modelo. Eles devem estar o mais próximo de zero, idealmente, menores que 0,05." + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " ARIMA Model Results \n", + "==============================================================================\n", + "Dep. Variable: D2.value No. Observations: 83\n", + "Model: ARIMA(3, 2, 1) Log Likelihood -214.248\n", + "Method: css-mle S.D. of innovations 3.153\n", + "Date: Fri, 25 Oct 2019 AIC 440.497\n", + "Time: 22:07:14 BIC 455.010\n", + "Sample: 2 HQIC 446.327\n", + " \n", + "==================================================================================\n", + " coef std err z P>|z| [0.025 0.975]\n", + "----------------------------------------------------------------------------------\n", + "const 0.0483 0.084 0.577 0.565 -0.116 0.212\n", + "ar.L1.D2.value 1.1386 0.109 10.399 0.000 0.924 1.353\n", + "ar.L2.D2.value -0.5923 0.155 -3.827 0.000 -0.896 -0.289\n", + "ar.L3.D2.value 0.3079 0.111 2.778 0.007 0.091 0.525\n", + "ma.L1.D2.value -1.0000 0.035 -28.799 0.000 -1.068 -0.932\n", + " Roots \n", + "=============================================================================\n", + " Real Imaginary Modulus Frequency\n", + "-----------------------------------------------------------------------------\n", + "AR.1 1.1557 -0.0000j 1.1557 -0.0000\n", + "AR.2 0.3839 -1.6318j 1.6763 -0.2132\n", + "AR.3 0.3839 +1.6318j 1.6763 0.2132\n", + "MA.1 1.0000 +0.0000j 1.0000 0.0000\n", + "-----------------------------------------------------------------------------\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Constroi Modelo\n", + "model = ARIMA(train, order=(3, 2, 1)) \n", + "fitted = model.fit(disp=-1) \n", + "print(fitted.summary())\n", + "\n", + "# Faz previsao\n", + "fc, se, conf = fitted.forecast(15, alpha=0.05) # 95% conf\n", + "\n", + "# Cria pandas dataframa\n", + "fc_series = pd.Series(fc, index=test.index)\n", + "lower_series = pd.Series(conf[:, 0], index=test.index)\n", + "upper_series = pd.Series(conf[:, 1], index=test.index)\n", + "\n", + "# Plota\n", + "plt.pyplot.figure(figsize=(12,5), dpi=100)\n", + "plt.pyplot.plot(train, label='training')\n", + "plt.pyplot.plot(test, label='actual')\n", + "plt.pyplot.plot(fc_series, label='forecast')\n", + "plt.pyplot.fill_between(lower_series.index, lower_series, upper_series, \n", + " color='k', alpha=.15)\n", + "plt.pyplot.title('Forecast vs Actuals')\n", + "plt.pyplot.legend(loc='upper left', fontsize=8)\n", + "plt.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A AIC reduziu de 515 para 440. Bom. Os valores P dos termos X são menores que <0,05, o que é ótimo.\n", + "\n", + "Então, no geral, é muito melhor.\n", + "\n", + "Idealmente, você deve voltar vários pontos no tempo, como 1, 2, 3 e 4 trimestres e ver como suas previsões estão se saindo em vários pontos do ano.\n", + "\n", + "Aqui está um ótimo exercício: tente retroceder 27, 30, 33, 36 pontos de dados e ver o desempenho das proibições. O desempenho da previsão pode ser avaliado usando várias métricas de precisão discutidas a seguir.\n", + "\n", + "\n", + "# Métricas de precisão para previsão de séries temporais\n", + "\n", + "As métricas de precisão comumente usadas para avaliar previsões são:\n", + "\n", + "Erro percentual absoluto médio (MAPE)\n", + "Erro médio (ME)\n", + "Erro Absoluto Médio (MAE)\n", + "Erro percentual médio (MPE)\n", + "Erro médio quadrático da raiz (RMSE)\n", + "Lag 1 Autocorrelação de Erro (ACF1)\n", + "Correlação entre o atual e o previsto (corr)\n", + "Min-Max Error (minmax)\n", + "\n", + "Normalmente, se você estiver comparando previsões de duas séries diferentes, o MAPE, Correlação e Erro Mín. Máx. Podem ser usados.\n", + "\n", + "Por que não usar as outras métricas?\n", + "\n", + "Como apenas os três acima são erros percentuais que variam entre 0 e 1. Dessa forma, você pode julgar o quão boa é a previsão, independentemente da escala da série.\n", + "\n", + "As outras métricas de erro são quantidades. Isso implica que um RMSE de 100 para uma série cuja média é de 1000 é melhor que um RMSE de 5 para séries de 10. Portanto, você não pode usá-los para comparar as previsões de duas séries temporais em escala diferentes." + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'mape': 0.022501305114356305,\n", + " 'me': 3.2307774659756165,\n", + " 'mae': 4.548320385364536,\n", + " 'mpe': 0.016420975902695575,\n", + " 'rmse': 6.373234889679405,\n", + " 'acf1': 0.5105507587572337,\n", + " 'corr': 0.9674576520337695,\n", + " 'minmax': 0.02163154042918869}" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Metricas\n", + "def forecast_accuracy(forecast, actual):\n", + " mape = np.mean(np.abs(forecast - actual)/np.abs(actual)) # MAPE\n", + " me = np.mean(forecast - actual) # ME\n", + " mae = np.mean(np.abs(forecast - actual)) # MAE\n", + " mpe = np.mean((forecast - actual)/actual) # MPE\n", + " rmse = np.mean((forecast - actual)**2)**.5 # RMSE\n", + " corr = np.corrcoef(forecast, actual)[0,1] # corr\n", + " mins = np.amin(np.hstack([forecast[:,None], \n", + " actual[:,None]]), axis=1)\n", + " maxs = np.amax(np.hstack([forecast[:,None], \n", + " actual[:,None]]), axis=1)\n", + " minmax = 1 - np.mean(mins/maxs) # minmax\n", + " acf1 = acf(fc-test)[1] # ACF1\n", + " return({'mape':mape, 'me':me, 'mae': mae, \n", + " 'mpe': mpe, 'rmse':rmse, 'acf1':acf1, \n", + " 'corr':corr, 'minmax':minmax})\n", + "\n", + "forecast_accuracy(fc, test.values)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Cerca de 2,2% do MAPE implica que o modelo é cerca de 97,8% preciso na previsão das próximas 15 observações." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/3. Modelos regressivos/Exercicio_ARIMA/[Solu\303\247\303\243o] Prevendo Vendas Shampoo.ipynb" "b/3. Modelos regressivos/Exercicio_ARIMA/[Solu\303\247\303\243o] Prevendo Vendas Shampoo.ipynb" new file mode 100644 index 0000000..d954760 --- /dev/null +++ "b/3. Modelos regressivos/Exercicio_ARIMA/[Solu\303\247\303\243o] Prevendo Vendas Shampoo.ipynb" @@ -0,0 +1,401 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Prevendo vendas de shampoo\n", + "\n", + "\n", + "Agora vamos praticar em python como criar um modelo ARIMA.\n", + "\n", + "Vamos analisar um dataset que contém vendas de shampoo durante um período de 3 anos. As unidades são vendas e ele possui 36 observações." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "#Primeiramente vamos importar as bibliotecas que iremos utilizar\n", + "\n", + "\n", + "import pandas as pd\n", + "import matplotlib as mtpl\n", + "from statsmodels.graphics.tsaplots import plot_acf, plot_pacf\n", + "from statsmodels.tsa.arima_model import ARIMA\n", + "\n", + "from sklearn.metrics import mean_squared_error" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Month\n", + "1901-01-01 266.0\n", + "1901-02-01 145.9\n", + "1901-03-01 183.1\n", + "1901-04-01 119.3\n", + "1901-05-01 180.3\n", + "Name: Sales, dtype: float64\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#função para tratar campo data\n", + "def parser(x):\n", + " return pd.datetime.strptime('190'+x, '%Y-%m')\n", + "\n", + "#Agora vamos importar nosso arquivo \n", + "series = pd.read_csv('shampoo-sales.csv', header=0, parse_dates=[0], index_col=0, squeeze=True, date_parser=parser)\n", + "print(series.head())\n", + "series.plot()\n", + "mtpl.pyplot.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Podemos ver que o conjunto de dados de vendas de shampoo tem uma tendência clara.\n", + "\n", + "Isso sugere que a série temporal não é estacionária e exigirá diferenciação para torná-la estacionária, pelo menos na ordem de 1.\n", + "\n", + "Vamos também dar uma olhada rápida em um gráfico de autocorrelação da série temporal. Isso pode ser feito usando o Pandas. O exemplo abaixo plota a autocorrelação para um grande número de lags na série temporal." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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1w3lc1tA8p6P2SbG8efMwRvVK48FZK7nrzWWUV1a7HcsYc5ry5ZDXY8CFqjpCVYcDFwFP+GHbg4ECVV2vquXANGCs9wKqOl9Vjw4KsghI98N2m5Tm0RH889pMbjmvG6/nbuGa5xaxp8SurzDG+J8vlw1/4+wh1DnvpDcscgUwWlUnO9PXAWep6s9qWf4fQKGqPuxMVwJ5QCXwqKq+Xct6U4ApAGlpaZnTpk1rSOyAKCkpIS4u8CfOF+2o5PllR2gZJUzuF80ZSWGINPxuyMbKHyiW3z2hnB2aTv6RI0f6dNlwvWMEAy8AzwPZzuNfwIu+jC9cz+teCTznNX0d8Pdalr0Wzx5KtNe8ts7XLsBGoGt92wz2MeUbw9db9umQ383VjnfO0suf+kznrSrU6uqGjV/fVMbVDlahnD+Us6s2nfz4cUz5m4EVwK3AbXjumL/Jh/XqsxVo7zWdDmw/fiERGQXcC1ymXjdXqup25+t6IAcY4IdMp73+6Ql89ItsfntZHwr3l/F/L+Vy8V8/4Z28bVRW2fkVY8yp8+UqryOq+riqXq6q41X1CfXPXfNLgO4i0llEooCr8Fyi/C0RGQA8g6eY7PKanygi0c7zFOBsPIXO+KBZVDgTh3Ui51fZ/PnKM6msVm6blsf5j3/Mq19s5khlVf0vYowxx6n1xkYRma6qE0RkGZ6+u46hDTyHoqqVIvIzYA4QDrygqitE5EE8u1czgT8BccAbzrH+zeq5oqsX8IyIVOMpio+qqhWUkxQZHsYVmelcPqAdH6zcydM5BdwzYxl/nbeGyed04YdndaB5tC/3vhpjTN13yt/mfB0TqI2r6vvA+8fNu9/r+aha1lsI9AtUrqYmLEwY3bc1F/VJ47OCIp7KKeCR91fxZE4BN57bheuHdqRFjHXhYoypW62HvFR1h/P0J6q6yfsB/KRx4pnGJCKc0z2FV28cwoyfDCOzQyJ/mpPPuX+cz5PzCzhYVuF2RGNMEPPlpPwFNcy72N9BTHAZ0CGR5ycNYubPzrbCYozxSa0FRURuds6f9HS6Pjn62AB803gRjZv6pydYYTHG+KSucyivAv8Dfg9497N1UFX3BjSVCTpHC8s3W4v569y1/GlOPv/6ZD03ntuF1mXVVFcrYW4NGWmMCQq1FhRV3Q/sB64GEJFWQAwQJyJxqrq5cSKaYFJTYQG457PZdEyOpWNyczomxdIxpTmdkmPplNycNvExjTbYlzHGPb4MAXwp8DjQFtiFZ2z5VUCfwEYzwexoYVm5/QDT5n5BdHI7NhaVsrmolAVrdnPEqxPKyHChe6sWPHXNQDqlNHcxtTEmkHy5yeBhYAgwV1UHiMhInL0WY3q3bcl5HSLJzv6uo+jqamXXwSNsLDrE5qJSNhYd4t+fb+LXby/n3z8a7Jf+w4wxwceXglKhqkUiEiYiYao6X0T+EPBkJmSFhQmt42NoHR/DkC7JALSOj+H+d1Yw8+vtjM1o53JCY0wg+HJgu1hE4oAFwFQR+SueHn6N8dk1Z3Wkf3o8D7+3iv2H7eowY05HvhSUscBh4HZgNrAOuDSQoczpJzxMeGRcP4pKjvDYB/luxzHGBIAvnUMeUtUqVa1U1ZdV9W+qWtQY4czppV96PNcP7cS/F23i6y3FbscxxvhZXTc2HhSRA16Pg95fGzOkOX384sIepMZFc8+MZdZdvjGnmbr68mqhqi29Hi28vzZmSHP6aBETyQOX9mHF9gP8e9Emt+MYY/zIp7vNROQcEbnBeZ4iIp0DG8uczi7p15oRPVJ57IM1FO4vczuOMcZP6i0oIvIAcCdwtzMrCvhPIEOZ05uI8ODYPlRUVfPQLBvGxpjThS97KOOBy4BD8O3Quy0CGcqc/jomN+eW87rx3rIdzM/fVf8Kxpig50tBKXcGqVcAEbG+M4xf3Di8C11Tm3P/O8spq7Bhh40Jdb4UlOki8gyQICI3AnOBfwU2lmkKoiPCeXhcP7bsPcw/PipwO44xpoF8uQ/lz8B/gTeBnsD9qvp3f2xcREaLSL6IFIjIXTW0R4vI6077FyLSyavtbmd+vohc5I88pvEN7ZrM5QPa8cyCdRTsOuh2HGNMA9TZl5eIhANznLHdP/Tnhp3XfhLPiJBbgSUiMlNVvc/S/gjYp6rdROQq4A/AD0SkN3AVnh6P2wJzRaSHqtpxkxB0z/d6MXfVTn799nJeu3HIt51Hqno6mVyz8yBrdpawdudB1uw8SOH+Mm7O7sp1Qzu5G9wYc4w6C4qqVolIqYjEO+Oj+NNgoEBV1wOIyDQ83bx4F5SxwG+c5/8F/iGevzZjgWmqegTYICIFzut9XtcG8/Pzyc7O9uf34BfFxcUkJCS4HeOU+SN/ZKv+LCq7iP43PIKKUNEshYrYFKojYr5dJqyilMjDe0DCue+dMv709Iskbv6YhvZdbO+/e0I5O5y++VXCKI9txZEWbSlr4Xtnrr70NlwGLBORD3Gu9AJQ1Vt93krN2gFbvKa3AmfVtoyqVorIfiDZmb/ouHVr/K5FZAowBSAyMpLi4uDr8qOqqiooc/nKH/m1+BPCE3tysPUApLyUsJJdRGz/mvCSXYSV7PR8Lfd8/BRBe43hQMchHJYYYpe9iVSfen+l9v67J5Szw+mTvzqyGVUJHahM6EBlYgeq4tMhPAoAObzP59fzpaC85zz8raZ/LNXHZXxZ1zNT9VngWYCsrCzNzc09mYyNIicnJyj3nHzlr/xlFVUcKKsgNS663jFTVJVnFqzn0f9Bz2HZPHtdJgmxUae0XXv/3RPK2SG083+xvogn389l25Fo1u32/LMWESb0bduSgR0TyeqYxMCOCbSJb4b87TqfXtOXcygXqOq1DU5/oq1Ae6/pdGB7LctsFZEIIB7Y6+O6JsTERIYTExnu07Iiwk0jutImPoZfvfENV/zzc166YRDpibEBTmlMaKuuVv4xv4An5q4hNgLO6prE5QPTyeyYyJnpCTSL8u13sCa+nENJFZEoVS0/5a3UbAnQ3enGZRuek+w/PG6ZmcBEPOdGrgA+UlUVkZnAqyJydGji7sBiP+czIWBsRjvSWsYw5ZVcxj+1kBcnDaJvu3i3YxkTlPYdKuf26Xnk5O9m/IB2jE7ex0WjBvnt9X25D2Uj8JmI3Ccidxx9NHTDqloJ/AyYg2eM+umqukJEHhSRy5zFngeSnZPudwB3OeuuAKbjOYE/G/ipXeHVdA3pksybNw8jKjyMCc98bnfeG1ODb7YWM+bvn7KwoIiHxvXl8QlnEh3h3+G4fTmHst15hOHnLldU9X3g/ePm3e/1vAy4spZ1HwEe8WceE7q6p7XgrZ8M44YXlzD55VweGdeXqwZ3cDuWMa5TVV5dvJnfzlxJaoto3rhpKGe2D8yVafUWFFX9LYCItPBMaklAkhjTQGktY5h+01B+MvUr7nprGd9s28+QLsl0S42jS2pzn8/PGHO6OFxexb0zlvHW0m2M6JHKX36QQWLzU7t4xRf1FhQR6Qv8G0hypvcA1zuHnYwJKnHRETw/MYsHZq7gtcWbefWLzQCIQHpiM7qmxtEtNY6ureLo1srz3JjT0frdJdz8n69Ys+sgt4/qwS3ndSMszL+HuI7nyyGvZ4E7VHU+gIhk4+nLa1gAcxlzyiLDw/jd+H7cP6Y3G/YcYt3uEgp2lbBu9yEKdpXw+boijlR+N1rkD3pGEaJXfhpTo9nLd/DLN74hMlx46YbBjOiR2ijb9aWgND9aTABUNcd6HDahICYynF5tWtKrzbEDjFZXK9uKD1Owu4SXF27kzTW7uXHXQbq1slEZTOg6XF7FrG+28+rizSzdXMyZ7RN46pqBtEto1mgZfCko60XkPjyHvQCuBTYELpIxgRUWJrRPiqV9Uix928aT/ce53PXmMqb/eGjADwkY42/5hQd5bfFm3vxqKwfLKumS2pz7xvTm2iEdiI5o3POGvhSU/wN+C7zlTC8AbghYImMaUWqLaK7qGcXzy/fx6uLNXDuko9uRjKlXWUUV732zg1cXb+bLTfuICg/j4n6t+eHgDgzunFRvTxOB4stVXvuAhvbbZUzQOqddBKvLWvCH/61mVK80WsfH1L+SMS7YsOcQr3y+kbe+2sb+wxV0SWnOvZf04vuZ6SQF8OotX/kypvyHIpLgNZ0oInMCG8uYxiMiPDKuH+VV1dz/znK34xhzgupq5flPN3DRXxbwn0WbGN4jldduHMK8X4zgxuFdgqKYgG+HvFJU9dvuNFV1n4i0CmAmYxpdp5Tm3H5BDx7932pmL9/B6L5t3I5kDACF+8v45Rtf82nBHkb1asXvxvejVcvg3Iv2peuVahH59pZjEelILT37GhPKJp/Tmd5tWnL/OyvYf7jC7TjG8P6yHVz0lwV8uWkfvxvfj39dnxW0xQR8Kyj3Ap+KyL9F5N94TsrfHdhYxjS+iPAw/vD9/uwpOcKj/1vtdhzThB0sq+CXb3zNT6Z+RafkWN679Rx+eFYH1062+8qXk/KzRWQgMMSZdbuq7glsLGPc0S89nh+d05l/fbKBcRltOatLstuRTBOTu3Evt0/PY9u+w9x6XjduOb87keG+/O/vPl9TDgOynceQOpc0JsTdfkEP0hObcfeMZZRVWCfWpnFUVFXz2Af5THjGM5L5GzcN5Y4Le4ZMMQHfrvJ6FLgNT1fxK4HbROT3gQ5mjFtioyL43fh+rN99iCfnF7gdxzQBqwsPcMXTC/n7RwV8f2A67996Lpkdk9yOddJ8ucrrEiBDVasBRORlYCl2HsWcxob3SOXyAe14OmcdY/q3pWfrurtlKa+sZtWOA6QnNiM5LrqRUppQt+9QOY9/uIapX2yiZbNInrpmIJf0C90rDH0pKAAJeIbeBc8wvMac9n49pjc5a3Zz55vf8ObNwwj36pblQFkFX23aR+7GfSzeuJevtxRzpLKaFtER3H5BD64f2pGIEDpUYRpXRVU1Uxdt4om5ayk5Usn1Qzvx81HdSYgNjvtJTpUvBeX3wFIRmQ8IMBy4J6CpjAkCSc2juH9Mb37+eh5P5xTQMbk5uRv3smTjPlYXHqBaITxM6Nu2JdcO6Uj/9Hje/GobD85ayRtfbuXhcX1C8rCFCaxP1u7mwXdXsnZXCed0S+H+S3vTI+306JjUl6u8XhORHGAQnoJyp6oWBjqYMcFgbEZb3lq6jT9/sAaAZpHhDOyYwK3nd2dQpyQy2ifQPPq7X6PLzmzL7OWFPDhrJd9/+nOuzEznrovPsMNgho17DvHwe6uYu2onHZJiefa6TC7onRb0lwKfDF8G2JqnqucDM2uYd0pEJAl4HeiEZ8z6CU6fYd7LZABPAy2BKuARVX3daXsJGAHsdxafpKp5p5rHmNqICI9POJPZywvpnx5PrzYt67zqRkS4uF8bhvdI5W8freX5Tzbwwcqd/Oqinlw9uMMxh81M03CwrIJ/zC/ghU83EBUexp2jz+D/zunU6D0BN4ZaC4qIxACxQIqIJOLZOwHPH/i2DdzuXcA8VX1URO5ypu88bplSPCNDrhWRtsCXIjLHqxuYX6nqfxuYw5h6pcRFn3QvxM2jI7j74l5cMTCd+95Zzq/fXs703C08PK4v/dMDM563aXyqyv7SCrbvP8z24sNs31/GjuLvnm8vPszOA2VUVClXZqbzq4t6BvWd7g1V1x7Kj4Gf4ykeX3nNPwA82cDtjsVzTwvAy0AOxxUUVV3j9Xy7iOwCUoFijAkR3dNa8NqNQ5j59XYefm8VY5/8jKsHd+DGc7vQOcXGqavW0OvFSVX5ctM+XvxsI/NWllI254Nj2iPChLSWMbRLaEZmx0TaJjTj4r6tm8Q/EqL1/EBF5BZV/btfNypSrKrePRjvU9XEOpYfjKfw9FHVaueQ11DgCDAPuEtVj9Sy7hRgCkBaWlrmtGnT/PeN+ElJSQlxcaE7trnl901phTKjoJx5myupVuiZGMbw9AiyWkcQHX5yh8Iqq5WC4mo2Haimd4sjtE8Ojfe/WpX1+6vJ21XF0l2V7CqtZnz3KEZ3iiQswOcSKquVJYVVFB9R+qaEkx4nJ3X+oqJaWbyjkg82VbLpQDWxETAgRUmPjyY5RkhqJiTHCPHREvDvxV98/eyPHDnyS1XNqm85XwoQ5gLTAAATh0lEQVTK9TXNV9VX6llvLtC6hqZ7gZd9LSgi0gbPHsxEVV3kNa8QiMIz5v06VX2wzm8EyMrK0tzc3PoWa3Q5OTlkh/Cg5pb/5Ow6UMZ/v9rK60u2sKmolBYxEYzLaMcPBrWnb7var8rfeaCMj/N3Mz9/F5+u3cPBI5UAxEbA76/I4LIz2wblCd7S8ko+WbuHeat28tHqXewpKSc8TBjcKYlDB4r5Zk8VQ7ok8diEjIAMV7v74BGmfrGJqV9sZvfB7/7vbBMfQ3bPVozsmcrZ3VKOubjC264DZfzni828+sUm9pSU071VHJPO7sT4Ae1YvPDTJvHZFxGfCoovlw0P8noeA5yP5xBYnQVFVUfVEW6niLRR1R1OcdhVy3ItgfeAXx8tJs5r73CeHhGRF4Ff+vB9GBMUWrWM4SfZ3bh5RFcWrd/L9NwtTM/dwr8XbaJP25ZcNag9l2W0o3lUOEu3FDN/9S5y8nezcscBANJaRvO9/m3I7plK+6RYbntlIbdNy+ODlTt5ZFzfU7qXobi0nHe/3k67xGYM65pCTGTDThgX7i9j3uqdzFu1i08L9lBeWU2LmAiye7ZiVK9WZPdoRXxsJPPnz2d3i278duYKRv9lAQ+P68vYjHYN2vZRy7bu58WFG5j19Q7Kq6oZ2TOVG87uTPe0OBas2c381bt59+vtvLZ4M1HhYZzVJenbAtM5pTlfb93PS59t4L1lO6isVs7r2Yobzu7M2d2Sg7JwBwNfLhu+xXtaROL5bnz5UzUTmAg86nx95/gFRCQKmAG8oqpvHNd2tBgJMA6wUZFMyBERhnZNZmjXZH5zWR9m5m3jtcVbuO+dFTz83iqiI8I4UFZJeJiQ2TGR/ze6JyN7tuKM1i2O+YN29+AYVkt7nvhwDUs27OWPV/Qnu6dvQxbtPniE5z5dz38+38Shck+/Zc2jwsk+oxUX9WnNyJ6ptIiJrPd1jlRW8eXGfXy8Zjcfr9nN6sKDALRPasY1Z3Xggl5pDOqcdMIVciLChKz2DOmczO3T87htWh7zVu3ioXF9iW9W/3aPV1FVzZwVhbz02UZyN+2jeVQ4PzyrA9cP7UiX1O8O7fxgUAd+MKgD5ZXV5G7aS07+bj5avYuHZq3koVmQ3DyKokPlxEVHcO2Qjkwc2olOds6rXr7eKe+tFOjRwO0+CkwXkR8Bm4ErAUQkC7hJVScDE/DcRJksIpOc9Y5eHjxVRFLxXHmWB9zUwDzGuCq+WSTXDe3EdUM7sXzbft7I3UJZRTUjnMMxdf1xDQ8TfprdjRE9Urn99TwmvbiEa4d04J5LehEbVfOv+Pbiwzy7YD2vLd5MeVU1Y/q35cfDu7Cn5AhzVuzkw5U7ee+bHUSFhzGsWzIX9WnNBb3TSPG6n2ZzUSkfr9nFx2t2s3BdEaXlVUSGC1kdk7jr4jMY2bMVPdLifPpvvkNyLK9PGcLTOev4y7y15G7cy2MTMhjatf7eno9UVrFqx0E+XbubqV9sZsf+MjokxXLfmN5cmZVOyzoKYlREGMO6pjCsawr3XNKLLXtLycnfxeKN+8jskMD3M9N9KqjGw5f7UN7luwG1woFewPSGbFRVi/AcOjt+fi4w2Xn+H+A/tax/XkO2b0ww69suvs5zKXWt9+4t5/CnOfk8/+kGPiso4rEJZzKww3enJzfuOcTTOet4a+lWVGH8gHbcnN31mP/es3u24uFxfflq8z7mLC9kzspC7n5rGffMWEZWx0S6tWrBovVFbNhzCPDshXx/YDojeqQytGtyreci6hMRHsYt53fnXKcw/vC5RUw5twt3XNjj23s2VJWt+w6zdEsxSzfvI29LMSu2HaC8qhqAs7sl89DYvow8o9Up3fPTPin228JuTp4vP/k/ez2vxLNXcHVg4hhjGiImMpz7xvTm/F6t+OX0r7ni6YX8dGQ3RvdtzbML1vPu19uJCA/j6sEdmDK8C+mJsTW+TniYMKhTEoM6JXHv93qxasdB5qwoZM6KQt5euo0hXZKYOLQjI3q2olNyrF/PKWS0T+C9W8/h4fdW8cyC9SxYu4dL+rbm663F5G0pZk9JufO9htG/XQI3nN2JjPYJDOiQSOv40/cej1DgyzmUj5271n+I5zDUBuDNQAczxpy6YV1TmH37cH4zcwV//6iAv39UQGxUOJPP7cLkczqf1M11IkLvti3p3bYlt1/Q0KPdvjk6hMB5PVtx55vf8NiHa+ia2pwRPVoxoEMCGe0T6Nm6RUiNFdIU1HrZsIj0AK7CszdShKerlF+q6sndMhxEOnfurA888IDbMU5QXFxMQkLo3vRk+d1VX/78kiiKysPJiC8jNjy4biT05b2vqIZKFZoFWXY4/T87R91www0Nvmx4NfAJcKmqFgCIyO2+BjXGBIeeceVuR2iQyDCIJPiKiamBqtb4AMbj2SvZAvwLz0n0DbUtHwqPzMxMDUbz5893O0KDWH53hXL+UM6u2nTyA7nqw9/YWg9AquoMVf0BcAaeO9VvB9JE5GkRuTDAdc4YY0yIqfeMlqoeUtWpqjoGSMdz38ddAU9mjDEmpJzUJRKquldVn1G7D8QYY8xx7Jo7Y4wxfmEFxRhjjF9YQTHGGOMXVlCMMcb4hRUUY4wxfnFq3YKGqKKiIl566aVj5vXp04dBgwZRUVHB1KlTT1gnIyODjIwMSktLmT79xE6Ws7Ky6Nu3L/v372fGjBkntA8dOpSePXuyZ88eZs2adUL78OHDASgsLGT27NkntJ9//vm0b9+eLVu2MG/evBPaR48eTevWrVm/fj0LFiw4oX3MmDGkpKSQn5/P559/fkL7+PHjiY+PZ/ny5dQ0muWECROIjY0lLy+PvLy8E9qvueYaAJYsWcKKFStOaJ80aRIACxcuZM2aNce0RUZGfrv+xx9/zIYNG45pj42NZcKECQDMnTuXrVu3HtPesmVLLr/8cgBmz55NYWHhMe3JyclceumlALz77rsUFRUd0966dWtGjx4NwFtvvcWBAweOaU9PT2fUKM84cdOnT6e0tPSY9s6dOzNixAgApk6dSkVFxTHtPXr0YNiwYQAnfO7Af5+9srKyGl/fl89ely5dXP3sAQ367EVGRtpnrwGfvaqqqhrb6/vs1cb2UIwxxviHL7fTny4P63olMCy/u0I5fyhnV206+Wlo1yvGGGPMybCCYowxxi9cKSgikiQiH4rIWudrYi3LVYlInvOY6TW/s4h84az/uohENV56Y4wxNXFrD+UuYJ6qdgfmUXtnk4dVNcN5XOY1/w/AE876+4AfBTauMcaY+rhVUMYCLzvPXwbG+bqieAavPg/476msb4wxJjBqHQI4oBsVKVbVBK/pfap6wmEvEanE011+JfCoqr4tIinAIlXt5izTHvifqvatZVtTgCkAaWlpmdOmTfP/N9RAJSUlxMXFuR3jlFl+d4Vy/lDODk0n/8iRIxs8BHCDiMhcoHUNTfeexMt0UNXtItIF+EhElgEHaliu1qqoqs8CzwJkZWVpdnb2SWy+ceTk5BCMuXxl+d0VyvlDOTtY/uMFrKCo6qja2kRkp4i0UdUdItIG2FXLa2x3vq4XkRxgAPAmkCAiEapaiWfQr+1+/waMMcacFLfOocwEJjrPJwLvHL+AiCSKSLTzPAU4G1jp3GQzH7iirvWNMcY0LrcKyqPABSKyFrjAmUZEskTkOWeZXkCuiHyNp4A8qqornbY7gTtEpABIBp5v1PTGGGNO4ErnkKpaBJxfw/xcYLLzfCHQr5b11wODA5nRGGPMybE75Y0xxviFFRRjjDF+YQXFGGOMX1hBMcYY4xdWUIwxxviFFRRjjDF+YQXFGGOMX1hBMcYY4xdWUIwxxviFFRRjjDF+YQXFGGOMX1hBMcYY4xdWUIwxxviFFRRjjDF+YQXFGGOMX1hBMcYY4xdWUIwxxviFFRRjjDF+4UpBEZEkEflQRNY6XxNrWGakiOR5PcpEZJzT9pKIbPBqy2j878IYY4w3t/ZQ7gLmqWp3YJ4zfQxVna+qGaqaAZwHlAIfeC3yq6PtqprXKKmNMcbUyq2CMhZ42Xn+MjCunuWvAP6nqqUBTWWMMeaUuVVQ0lR1B4DztVU9y18FvHbcvEdE5BsReUJEogMR0hhjjO9EVQPzwiJzgdY1NN0LvKyqCV7L7lPVE86jOG1tgG+Atqpa4TWvEIgCngXWqeqDtaw/BZgCkJaWljlt2rRT/6YCpKSkhLi4OLdjnDLL765Qzh/K2aHp5B85cuSXqppV74Kq2ugPIB9o4zxvA+TXsextwLN1tGcDs3zZbmZmpgaj+fPnux2hQSy/u0I5fyhnV206+YFc9eFvrFuHvGYCE53nE4F36lj2ao473OXsoSAiguf8y/IAZDTGGHMS3CoojwIXiMha4AJnGhHJEpHnji4kIp2A9sDHx60/VUSWAcuAFODhRshsjDGmDhFubFRVi4Dza5ifC0z2mt4ItKthufMCmc8YY8zJszvljTHG+IUVFGOMMX5hBcUYY4xfWEExxhjjF1ZQjDHG+IUVFGOMMX5hBcUYY4xfWEExxhjjF1ZQjDHG+IUVFGOMMX5hBcUYY4xfWEExxhjjF1ZQjDHG+IUVFGOMMX5hBcUYY4xfWEExxhjjF1ZQjDHG+IUVFGOMMX5hBcUYY4xfuFJQRORKEVkhItUiklXHcqNFJF9ECkTkLq/5nUXkCxFZKyKvi0hU4yQ3xhhTG7f2UJYDlwMLaltARMKBJ4GLgd7A1SLS22n+A/CEqnYH9gE/CmxcY4wx9XGloKjqKlXNr2exwUCBqq5X1XJgGjBWRAQ4D/ivs9zLwLjApTXGGOOLCLcD1KEdsMVreitwFpAMFKtqpdf8drW9iIhMAaY4kyUiUl8hc0MKsMftEA1g+d0VyvlDOTs0nfwdfXmxgBUUEZkLtK6h6V5VfceXl6hhntYxv0aq+izwrA/bc42I5KpqreeSgp3ld1co5w/l7GD5jxewgqKqoxr4EluB9l7T6cB2PNU0QUQinL2Uo/ONMca4KJgvG14CdHeu6IoCrgJmqqoC84ErnOUmAr7s8RhjjAkgty4bHi8iW4GhwHsiMseZ31ZE3gdw9j5+BswBVgHTVXWF8xJ3AneISAGecyrPN/b34GdBfUjOB5bfXaGcP5Szg+U/hnj+4TfGGGMaJpgPeRljjAkhVlCMMcb4hRUUl4nIRhFZJiJ5IpLrdp76iMgLIrJLRJZ7zUsSkQ+drnA+FJFENzPWppbsvxGRbc77nycil7iZsS4i0l5E5ovIKqfrotuc+aHy/teWPyR+BiISIyKLReRrJ/9vnflB3xVUHdlfEpENXu99RoO2Y+dQ3CUiG4EsVQ2Jm6NEZDhQAryiqn2deX8E9qrqo06fa4mqeqebOWtSS/bfACWq+mc3s/lCRNoAbVT1KxFpAXyJp5eISYTG+19b/gmEwM/A6aWjuaqWiEgk8ClwG3AH8JaqThORfwJfq+rTbmY9Xh3ZbwJmqep/63wBH9keijkpqroA2Hvc7LF4usCBIO4Kp5bsIUNVd6jqV87zg3iufmxH6Lz/teUPCepR4kxGOg8lBLqCqiO7X1lBcZ8CH4jIl043MaEoTVV3gOePBtDK5Twn62ci8o1zSCwoDxcdT0Q6AQOALwjB9/+4/BAiPwMRCReRPGAX8CGwjpPoCspNx2dX1aPv/SPOe/+EiEQ3ZBtWUNx3tqoOxNOr8k+dwzKm8TwNdAUygB3AY+7GqZ+IxAFvAj9X1QNu5zlZNeQPmZ+BqlapagaeHjoGA71qWqxxU/nm+Owi0he4GzgDGAQk4bnH75RZQXGZqm53vu4CZuD5kIaanc7x8aPHyXe5nMdnqrrT+UWrBv5FkL//zvHvN4GpqvqWMztk3v+a8ofazwBAVYuBHGAITldQTlPQdwXllX20cxhSVfUI8CINfO+toLhIRJo7JycRkebAhXjGigk1M/F0gQMh1hXO0T/EjvEE8fvvnFh9Hlilqo97NYXE+19b/lD5GYhIqogkOM+bAaPwnAcK+q6gasm+2usfEcFz7qdB771d5eUiEemCZ68EPB11vqqqj7gYqV4i8hqQjafb653AA8DbwHSgA7AZuFJVg+7kdy3Zs/EcalFgI/Djo+cjgo2InAN8AiwDqp3Z9+A5DxEK739t+a8mBH4GItIfz0n3cDz/jE9X1Qed3+NpeA4ZLQWudf7jDxp1ZP8ISMXTi3secJPXyfuT344VFGOMMf5gh7yMMcb4hRUUY4wxfmEFxRhjjF9YQTHGGOMXVlCMMcb4hRUUYxqBiJzypZjGhAorKMYYY/zCCooxLhGRS51xNJaKyFwRSXPmpzrjmnwlIs+IyCYRSXE7rzH1sYJijHs+BYao6gA8d1r/P2f+A8BHTqehM/DcAW9M0IuofxFjTICkA687/SlFARuc+efg6dMKVZ0tIvtcymfMSbE9FGPc83fgH6raD/gxEOPMF/ciGXPqrKAY4554YJvzfKLX/E/xDIuLiFwIBO2AU8Z4s84hjWkEIlLNseNkPI5ntL8n8BSVRcAgVc0WkVbAa3gKycfAD4DOwdaDrTHHs4JiTJBxhmGtUtVKERkKPO2MtGdMULOT8sYEnw7AdBEJA8qBG13OY4xPbA/FGGOMX9hJeWOMMX5hBcUYY4xfWEExxhjjF1ZQjDHG+IUVFGOMMX7x/wH4Wcdl83sjHQAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "pd.plotting.autocorrelation_plot(series)\n", + "mtpl.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Executando o exemplo, podemos ver que há uma correlação positiva com os primeiros 10 a 12 lags que talvez seja significativa apenas para os 5 primeiros.\n", + "\n", + "Um bom ponto de partida para o parâmetro AR do modelo pode ser 5\n", + "\n", + "\n", + "# ARIMA com Python\n", + "\n", + "A biblioteca statsmodels fornece a capacidade de ajustar um modelo ARIMA.\n", + "\n", + "Um modelo ARIMA pode ser criado usando a biblioteca statsmodels da seguinte maneira:\n", + "\n", + "Defina o modelo chamando ARIMA () e passando os parâmetros p, d e q.\n", + "O modelo é preparado nos dados de treinamento chamando a função fit ().\n", + "As previsões podem ser feitas chamando a função predict () e especificando o índice da hora ou horas a serem previstas.\n", + "Vamos começar com algo simples. Ajustaremos um modelo ARIMA a todo o conjunto de dados de vendas de shampoo e revisaremos os erros residuais.\n", + "\n", + "Primeiro, ajustamos um modelo ARIMA (5,1,0). Isso define o valor do atraso como 5 para regressão automática, usa uma ordem de diferença de 1 para tornar a série temporal estacionária e usa um modelo de média móvel de 0.\n", + "\n", + "Ao ajustar o modelo, são fornecidas muitas informações de depuração sobre o ajuste do modelo de regressão linear. Podemos desativar isso definindo o argumento disp como 0" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " ARIMA Model Results \n", + "==============================================================================\n", + "Dep. Variable: D.Sales No. Observations: 35\n", + "Model: ARIMA(5, 1, 0) Log Likelihood -196.170\n", + "Method: css-mle S.D. of innovations 64.241\n", + "Date: Sat, 26 Oct 2019 AIC 406.340\n", + "Time: 11:08:48 BIC 417.227\n", + "Sample: 02-01-1901 HQIC 410.098\n", + " - 12-01-1903 \n", + "=================================================================================\n", + " coef std err z P>|z| [0.025 0.975]\n", + "---------------------------------------------------------------------------------\n", + "const 12.0649 3.652 3.304 0.003 4.908 19.222\n", + "ar.L1.D.Sales -1.1082 0.183 -6.063 0.000 -1.466 -0.750\n", + "ar.L2.D.Sales -0.6203 0.282 -2.203 0.036 -1.172 -0.068\n", + "ar.L3.D.Sales -0.3606 0.295 -1.222 0.231 -0.939 0.218\n", + "ar.L4.D.Sales -0.1252 0.280 -0.447 0.658 -0.674 0.424\n", + "ar.L5.D.Sales 0.1289 0.191 0.673 0.506 -0.246 0.504\n", + " Roots \n", + "=============================================================================\n", + " Real Imaginary Modulus Frequency\n", + "-----------------------------------------------------------------------------\n", + "AR.1 -1.0617 -0.5064j 1.1763 -0.4292\n", + "AR.2 -1.0617 +0.5064j 1.1763 0.4292\n", + "AR.3 0.0816 -1.3804j 1.3828 -0.2406\n", + "AR.4 0.0816 +1.3804j 1.3828 0.2406\n", + "AR.5 2.9315 -0.0000j 2.9315 -0.0000\n", + "-----------------------------------------------------------------------------\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/talitabarcelos/anaconda3/lib/python3.7/site-packages/statsmodels/tsa/base/tsa_model.py:171: ValueWarning: No frequency information was provided, so inferred frequency MS will be used.\n", + " # Now, if no frequency information is available from the index\n", + "/Users/talitabarcelos/anaconda3/lib/python3.7/site-packages/statsmodels/tsa/base/tsa_model.py:191: FutureWarning: Creating a DatetimeIndex by passing range endpoints is deprecated. Use `pandas.date_range` instead.\n", + " # also a given frequency, raise an exception if they are not\n", + "/Users/talitabarcelos/anaconda3/lib/python3.7/site-packages/statsmodels/tsa/base/tsa_model.py:171: ValueWarning: No frequency information was provided, so inferred frequency MS will be used.\n", + " # Now, if no frequency information is available from the index\n" + ] + } + ], + "source": [ + "# fit modelo\n", + "model = ARIMA(series, order=(5,1,0))\n", + "model_fit = model.fit(disp=0)\n", + "print(model_fit.summary())\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A execução do exemplo imprime um resumo do modelo de ajuste. Isso resume os valores do coeficiente usados, bem como a habilidade do ajuste nas observações na amostra.\n", + "\n", + "Primeiro, obtemos um gráfico de linha dos erros residuais, sugerindo que ainda pode haver algumas informações de tendência não capturadas pelo modelo.\n", + "\n", + "Em seguida, obtemos um gráfico de densidade dos valores de erro residual, sugerindo que os erros são gaussianos, mas podem não estar centrados no zero.\n", + "\n", + "A distribuição dos erros residuais é exibida. Os resultados mostram que, de fato, existe um viés na predição (média não zerada no residual)\n", + "\n", + "Observe que, embora acima tenhamos usado todo o conjunto de dados para análise de séries temporais, o ideal seria realizar essa análise apenas no conjunto de dados de treinamento ao desenvolver um modelo preditivo.\n", + "\n", + "A seguir, veremos como podemos usar o modelo ARIMA para fazer previsões.\n", + "\n", + "# Modelo ARIMA de previsão contínua\n", + "\n", + "O modelo ARIMA pode ser usado para prever futuro\n", + "\n", + "Podemos usar a função predict () no objeto ARIMAResults para fazer previsões. Ele aceita o índice das etapas de tempo para fazer previsões como argumentos. Esses índices são relativos ao início do conjunto de dados de treinamento usado para fazer previsões.\n", + "\n", + "Se usamos 100 observações no conjunto de dados de treinamento para ajustar-se ao modelo, o índice da próxima etapa para fazer uma previsão será especificado para a função de previsão como start = 101, end = 101. Isso retornaria uma matriz com um elemento contendo a previsão.\n", + "\n", + "Também preferimos que os valores previstos estejam na escala original, caso realizemos alguma diferença (d> 0 ao configurar o modelo). Isso pode ser especificado configurando o argumento de tipo com o valor 'levels': typ = 'levels'.\n", + "\n", + "Como alternativa, podemos evitar todas essas especificações usando a função forecast (), que executa uma previsão em uma etapa usando o modelo.\n", + "\n", + "Podemos dividir o conjunto de dados de treinamento em conjuntos de treinamento e teste, usar o conjunto de treinamento para ajustar-se ao modelo e gerar uma previsão para cada elemento no conjunto de teste.\n", + "\n", + "É necessária uma previsão contínua, dada a dependência das observações em etapas anteriores para diferenciar e o modelo de AR. Uma maneira grosseira de executar essa previsão contínua é recriar o modelo ARIMA após cada nova observação ser recebida.\n", + "\n", + "Nós mantemos o controle manual de todas as observações em uma lista chamada histórico que é semeada com os dados de treinamento e à qual novas observações são anexadas a cada iteração.\n", + "\n", + "Juntando tudo isso, abaixo está um exemplo de uma previsão contínua com o modelo ARIMA em Python." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "predicted=349.117636, expected=342.300000\n", + "predicted=306.513010, expected=339.700000\n", + "predicted=387.376466, expected=440.400000\n", + "predicted=348.154255, expected=315.900000\n", + "predicted=386.308811, expected=439.300000\n", + "predicted=356.082028, expected=401.300000\n", + "predicted=446.379518, expected=437.400000\n", + "predicted=394.737242, expected=575.500000\n", + "predicted=434.915541, expected=407.600000\n", + "predicted=507.923456, expected=682.000000\n", + "predicted=435.482818, expected=475.300000\n", + "predicted=652.743768, expected=581.300000\n", + "predicted=546.343465, expected=646.900000\n", + "Test MSE: 6958.327\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "X = series.values\n", + "size = int(len(X) * 0.66)\n", + "train, test = X[0:size], X[size:len(X)]\n", + "history = [x for x in train]\n", + "predictions = list()\n", + "for t in range(len(test)):\n", + "\tmodel = ARIMA(history, order=(5,1,0))\n", + "\tmodel_fit = model.fit(disp=0)\n", + "\toutput = model_fit.forecast()\n", + "\tyhat = output[0]\n", + "\tpredictions.append(yhat)\n", + "\tobs = test[t]\n", + "\thistory.append(obs)\n", + "\tprint('predicted=%f, expected=%f' % (yhat, obs))\n", + "error = mean_squared_error(test, predictions)\n", + "print('Test MSE: %.3f' % error)\n", + "# plot\n", + "mtpl.pyplot.plot(test)\n", + "mtpl.pyplot.plot(predictions, color='red')\n", + "mtpl.pyplot.show()\n", + "\n", + "\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "X = series.values\n", + "size = int(len(X) * 0.66)\n", + "train, test = X[0:size], X[size:len(X)]\n", + "history = [x for x in train]\n", + "# Cria Modelo\n", + "# modelo = ARIMA(train, order=(3,2,1)) \n", + "model = ARIMA(history, order=(5, 1, 0)) \n", + "fitted = model.fit(disp=-1) \n", + "\n", + "# Cria Training and Test set\n", + "train = df.value[:85]\n", + "test = df.value[85:]\n", + "\n", + "# Cria Modelo\n", + "# modelo = ARIMA(train, order=(3,2,1)) \n", + "model = ARIMA(train, order=(1, 1, 1)) \n", + "fitted = model.fit(disp=-1) \n", + "\n", + "# Previsao\n", + "fc, se, conf = fitted.forecast(15, alpha=0.05) # 95% conf\n", + "\n", + "\n", + "\n", + "# Previsao\n", + "fc, se, conf = fitted.forecast() \n", + "\n", + "# Cria pandas dataframa\n", + "fc_series = pd.Series(fc)\n", + "lower_series = pd.Series(conf[:, 0])\n", + "upper_series = pd.Series(conf[:, 1])\n", + "\n", + "\n", + "# Plota\n", + "mtpl.pyplot.figure(figsize=(12,5), dpi=100)\n", + "mtpl.pyplot.plot(train, label='training')\n", + "mtpl.pyplot.plot(test, label='actual')\n", + "mtpl.pyplot.plot(fc_series, label='forecast')\n", + "mtpl.pyplot.fill_between(lower_series.index, lower_series, upper_series, \n", + " color='k', alpha=.15)\n", + "mtpl.pyplot.title('Forecast vs Actuals')\n", + "mtpl.pyplot.legend(loc='upper left', fontsize=8)\n", + "mtpl.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A execução do exemplo imprime a previsão e o valor esperado a cada iteração.\n", + "\n", + "Também podemos calcular uma pontuação média de erro quadrático final (MSE) para as previsões, fornecendo um ponto de comparação para outras configurações do ARIMA.\n", + "\n", + "É criado um gráfico de linhas mostrando os valores esperados (azul) em comparação com as previsões de previsão sem interrupção (vermelho). Podemos ver que os valores mostram alguma tendência e estão na escala correta.\n", + "\n", + "Neste exercicio,aprendemos como desenvolver um modelo ARIMA para previsão de séries temporais no Python.\n", + "\n", + "Você aprendeu especificamente:\n", + "\n", + "Sobre o modelo ARIMA, como ele pode ser configurado e suposições feitas pelo modelo.\n", + "Como executar uma análise rápida de séries temporais usando o modelo ARIMA.\n", + "Como usar um modelo ARIMA para prever previsões fora da amostra." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/3. Modelos regressivos/Exercicio_ARIMA/dataset.csv b/3. Modelos regressivos/Exercicio_ARIMA/dataset.csv new file mode 100644 index 0000000..80cfd6a --- /dev/null +++ b/3. Modelos regressivos/Exercicio_ARIMA/dataset.csv @@ -0,0 +1,101 @@ +"x" +88 +84 +85 +85 +84 +85 +83 +85 +88 +89 +91 +99 +104 +112 +126 +138 +146 +151 +150 +148 +147 +149 +143 +132 +131 +139 +147 +150 +148 +145 +140 +134 +131 +131 +129 +126 +126 +132 +137 +140 +142 +150 +159 +167 +170 +171 +172 +172 +174 +175 +172 +172 +174 +174 +169 +165 +156 +142 +131 +121 +112 +104 +102 +99 +99 +95 +88 +84 +84 +87 +89 +88 +85 +86 +89 +91 +91 +94 +101 +110 +121 +135 +145 +149 +156 +165 +171 +175 +177 +182 +193 +204 +208 +210 +215 +222 +228 +226 +222 +220 diff --git a/3. Modelos regressivos/Exercicio_ARIMA/shampoo-sales.csv b/3. Modelos regressivos/Exercicio_ARIMA/shampoo-sales.csv new file mode 100644 index 0000000..f43d430 --- /dev/null +++ b/3. Modelos regressivos/Exercicio_ARIMA/shampoo-sales.csv @@ -0,0 +1,37 @@ +"Month","Sales" +"1-01",266.0 +"1-02",145.9 +"1-03",183.1 +"1-04",119.3 +"1-05",180.3 +"1-06",168.5 +"1-07",231.8 +"1-08",224.5 +"1-09",192.8 +"1-10",122.9 +"1-11",336.5 +"1-12",185.9 +"2-01",194.3 +"2-02",149.5 +"2-03",210.1 +"2-04",273.3 +"2-05",191.4 +"2-06",287.0 +"2-07",226.0 +"2-08",303.6 +"2-09",289.9 +"2-10",421.6 +"2-11",264.5 +"2-12",342.3 +"3-01",339.7 +"3-02",440.4 +"3-03",315.9 +"3-04",439.3 +"3-05",401.3 +"3-06",437.4 +"3-07",575.5 +"3-08",407.6 +"3-09",682.0 +"3-10",475.3 +"3-11",581.3 +"3-12",646.9 \ No newline at end of file diff --git a/3. Modelos regressivos/Exercicio_Autoregressao/.ipynb_checkpoints/Prevendo Temperatura-checkpoint.ipynb b/3. Modelos regressivos/Exercicio_Autoregressao/.ipynb_checkpoints/Prevendo Temperatura-checkpoint.ipynb new file mode 100644 index 0000000..a205be6 --- /dev/null +++ b/3. Modelos regressivos/Exercicio_Autoregressao/.ipynb_checkpoints/Prevendo Temperatura-checkpoint.ipynb @@ -0,0 +1,269 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Prevendo Temperatura\n", + "\n", + "\n", + "Vamos investigar a autocorrelação de uma série temporal univariada para então desenvolver um modelo autoregressivo e usa-lo para fazer predições.\n", + "\n", + "\n", + "Vamos usar o arquivo \"daily-min-temperatures.csv\" que possui a temperatura mínima de 10 anos (1981-1990) da cidade de Melbourne, Australia.\n", + "\n", + "As unidades estão em graus Celsius e existem 3.650 observações. A fonte dos dados é creditada como o Australian Bureau of Meteorology.\n", + "\n", + "\n", + "Para concluir esse exercicio faça os passos abaixo:\n", + "\n", + "1. Importe as bibliotecas que irá usar\n", + "2. Importe o arquivo 'daily-min-temperatures.csv'\n", + "3. Plote grafico de autocorrelação\n", + "4. Faça o fit do modelo\n", + "5. Faça a prediçao" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "#Vamos importar as bibliotecas que vamos utilizar\n", + "\n", + "import pandas as pd\n", + "import matplotlib as mtl\n", + "from statsmodels.graphics.tsaplots import plot_acf\n", + "from sklearn.metrics import mean_squared_error\n", + "from statsmodels.tsa.ar_model import AR" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Temp\n", + "Date \n", + "1981-01-01 20.7\n", + "1981-01-02 17.9\n", + "1981-01-03 18.8\n", + "1981-01-04 14.6\n", + "1981-01-05 15.8\n" + ] + }, + { + "data": { + "image/png": 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MJHze5kauuJYY4sR8EeQIx+j9G9mCA+s9xiTDKwKo5QY8Hmnx1O94aqJ1cMPisZv4KA2rjcCOns5Fy6d/x1sBjniB6HdRUFhY7Fi8tBs1Fef/Z6b9iYwIjZKQRMNzJF20jzB79h47i/f/3F48TfX/pv0nMWGxEsLbKA846QhfOzFWDTBr7xntfl8u3u3uOkbpu8Uq3w+pI+CfVW8jv7B6dj/yJTuvEFmng9uIjYm5qaQhxkCaL7GWhtz8QiQlEPywIhOPfL8GgD8N8t8/W4b1BquFNXPBTR8uAgDc3K0hXyVhMnEdRFqGBDDUtpq45oWlQUyAOQktnL2fb8fvVx8aJSHA+w6EnPwCrN5zHF0bVYscM7Kn+u36GJtk86emYHC72pi0dp+v6Z52EVDQKA+CKibF5yR8tHk7PC/z6BnkFcSXA07r2dGYniyv+mmV73473y3Ydhjdm6Q5CsvhR/kIKs9DY246dDLH/qQSwOjfNuD6DxYKGVTPbwXhFqNGgFe8Hm7mJt3nXi/NQp9XZ8eXlsVv+me8Yewi5xf6iFW2+7kpFQAMHbcYE2LMchQ0akOwAsbmwNi0giA0SuLtWcFNPvEctWxWg+llncpFfoH5pJz/K64dTFz7K0IURtKINCfxwZ87fNvu1Mj8FgvrOQkv5BUU+t4wx3LSYuQZhCi7bDz8tOy85I05mLo+/tAt+rVJhZFRSty3tSQ0SqK0oDXON324CE2fnGJ6nu8B/gTzJjOWx8jcxE/D+7Xd6f9mbjX9LcgOjVXHgYKi2ZNT8NB3q4MTyIaIwuM4X6SVx9z8Qtz1+fK40xvwxhxd2nIkISllfLFoFzKyzLaGNZiXMagjrHuPe46cwSfzdxqkHVzr7CQtVkrd61NpImpxiz6dv9O2l+03QYwkKKw7Jqxl2KbbvEi7td9FMXRK4tr3FuC3NXt5i8GcfG2oblDZjXqofq8HcDLRxrqhfMpFT3zEF8sx0yBuzyWta7EUCf/30WI89+sGrhO1QY6NWDzXqZx8jPp1A26MnbcIGBFWXPvamQjo8ULj3QQoGb5s11Es23UUl51bx790OJgsmj45BVe0N36m/eoKZz2lPQrsFJPQ3GkVyjJN51S2YvO2ihHEFzHk0kuh2c21vONFEErCLgk/RzPa88k5CR1+ZXhOfgHemLEF2Xn+7vBkxy+r9zpunEXwAd928BS+XuJu0ZVXnFYE1vVFSze2wQl0JOEgLWYT11ZKxyIRfXmkATVedgTxiiioZUJ+BsGULrAxXNS8hm8Z/tmCXXhjxlZ8NK+47TkInvt1vetr8n0sfFZeVXo27T+JkT+u9U0OPbzaG2KyvFyUEN1aQ2FUHLx0elg0PJosWuwnp+WJNSfVkYyfZad4eBIfE4tNO6B0QqMkGtdI9W34qG1Wrm05GHQn/ZP5Ga6v+W2NP2sWjp3JRdMnp+DDuTvsTw4QXr3Sokib0cdFawxW7TlW7NjOw2wnjp2G+9PqaQIh+HbpHjR9cgr+OnbW+EIXrNx9FDku9nPOzg3eMuDEXZkVQc25hGpOYtGOLF/uqy/8eQWFeOsPc5fDko42/7HvePF5kNKIUcz+nYdPB2Zms8OqmWDdiFg5M+iT0tZKJBDFhAoA2w+eQt0q5TynvSvrNIa8uwCXtj3H8TVBjPZ4mn2LPHz97UGFRkkkJRDs97nhKqQUP67IxNKMo76mYwV3Oy6nMm+3CMtpRWCdf0ZK4sq35+FEgJOy+oYo0gCrQxwnISHcpeX+mlg0UyghhFkwSC0cuJnDghGP/eC/KXT8wl0Y0rGu7+kYo+RqIaW+KqvQKIkgNnV5d3bx6KOlDV5ug42fmMwlXSP0CivSyOmyJUgFEUuHf09DxZRkzB95se25a/86jsY1UlG+jPNq7rX3rb+uQDeSiPweZ7kSwVHDjCB3aNSjZcmC7Vl4ftJG39IJzZwEAVCjIlv3xsi9BfL35LUvgYaodTHId6R3YDDzbgqSWAWlt+9bNZ6P/7gWd09Y4Tktr9cVKQkS6dwJWqyYwMs9Wq+bjBZ8siI0I4nf1+/Hl6oduHGNVE/3GDNlExITgEcGtGQpmq/4FQ/IDD77Apsn6na/BBa6ZOvBouCKmrlJNOVJKQUhxLbxXbCd3TyeZTA9XQZpjWYCQ80eT/b7bYXg5b0lA/zFsCvrTMSlLTnBm9jv/7kd78wS26QUW579igdkBo8es1WSjR6fjAe/DTYekH40F9Rm8275bnkmAOAJGxdkt3sse31Kfa92/IIMAEpZjpic4sy+695fGN8NfIS3uQnwd6QWGiWhp3L5ZN4iCMH2Q6fsT3KJaI0hoMQDCmJOyggRzE1GPKpu/LSDsZur1ajO6hXo53E+W6iMfjOPnkWRjnCXf1PW7sPazOOR77waYidwUxIBpRNKJZHk5zZgLnlt2mam93PTFh46mYMNe0/gsrfmutqsxwoe5d1JkkfPBLddo56ikQSX5AGYN7CPqYrCjhFfOI8+6vUxB+qikxre1+WNR0xYgcvfnudRmmj8bi38XNhqhYwCa0EiYyURTy816E3W9eQXULw4ZSPW/XUCy3axctsNvsA7GRGdCXBhlL44aFE3c/MLDResBYFZW/DNsj2OrnfjNuqV0ybvR6tbw8Yv810GXszdetjX+09dvx97jhSPjizDcljAckIszOQxmDDLOpWDj+ftjPRKZm4sHlnVby553boXGgS5+YV4b/Z25OQXGI7m/jt9C656Z36UCcQPvlqyG5lHoxsE0eJEuUHW1PhYmnEEd32+HBe8PKvYb/oRpp9lJDTeTXoEsjYxZ/42F94oDPLhgW9WYe7Ww+jWuBra1Kkc+rUiiYne+j2fLczAS79vMjXtrP1LUQ63f7rEq2i2nMrJx+M/rkWDauUx59E+keOBxonyFt/P/JoSXFeDYK9FOJPCgJyqQjmS2HM0/jgwJQEW9e/4WWUla36BuBODQXA6RzGXvPz7ZizecaTY79pI6/Ap/+ZGtMnx2L0rgoS1Qlrt88graOLdy6bx45Nw7XsLmMgiJ64t0O/OxIIVzOz5kpKAkceQn8ohFlHVtZe5u0Mnc3yQxD0/rczEDgbegBNXxackCik8zx/+HjO3FNTEdSjNTSx59PvVhjuchQFRGxOuCOaq6gYRLDMhzj5L/vXNaiQnEmx9YVBc9+EZHuQfMV5qciQREN8uy+Qtgmeycwuw5cBJ+xMtKGmNgtfHEWV/CKB4QyRKWHIeSmzW5oNIHzmJyb3yGJhURaov0gVWYsvD363GgRPeh/PTNxzA+r0ly2ZcUEjx4ZwdOJPrbt2ISJU/liBFEy2Q3pS18e+bwnLyXKTcCZ0LLCHkY0LIQULIOt2xUYSQvwghq9S/+MZ6kijMfNOd8vfPljFZJDZjw4H4b8KIyWv34YXJG/HKVLaLHIMk1va/ZGfxiXSJc7YcYDeHKdLK+zCamz4FMNDg+OuU0g7qnzjxoBny1sytSB85ydWuWRr7joffU+vOz8RZKKV5KZ3iGM47XrhuZGPx2+EAvK6aPzmFmXnJDwTSEeEbSVBK5wAolV2ej9QwvWdy7JXE8bN5+GR+0eK17i/+wUQGESY9RUDr6bk1MYhQ93nFp9Kz1GLUsiuLbZwoI3I5RVR1wsET2fhzyyHeYkT4brmzFffxEoR3072EkFsBLAPwEKW0mP8XIWQ4gOEAUOacpgGIxBY3Gv2pn9fh19V7se94tlBbhArQPklUKPiNJkZY7D/Bo4jw3l9Fj2ihRVbuDiZMjN8T1+8BaAKgA4B9AF4zOolSOpZS2plS2tlneXzFSUN7TA1UN3bODvy6Oj6fa5YcO5MX9zA/4/BpnMzOYySRN4La99cPNMVwJrcAGVnFY/WURo6d5bewMJasU2Ks+QgaX5UEpfQApbSAUloI4EMAXf1Mz4rVPgZnc9PrE8mmqWfP0fgbpd6vzsaNYxcxkMY7Xs1Nor2YPq/O5pq+KKFvpq4XxymChznw55V/BZ5mLL4qCUJIbd3XIQCC3UFHx5XvzOeVdCCs2nMMwz5d6nmXLFY97/V7TzC5j1e0pp63+cyLuUgkNVVIgZtiFL4IcyaljVmb+c+BMJuTIIR8BaA3gOqEkEwAzwLoTQjpAKX8ZwC4i1V68bD90CnUqVwO5cok8haFGf+dvgWAstFLenXj7V33HT+LMokJSKvgz17hIiCKnz+lHibPxRA9wsId0cEmRcnbeDh+Ng+Vy3nbtCxoHSlKfjNTEpTSmwwOf8Tq/izp+9qf6NuyJj76Wxcm94v0Xm164xMW7+K2eQ5Q5EmVMWZwsd9EWnEcD0X1yl2NZv30e46eQcM0b3uxi0pJGEnsP57tWUmUVkrtimuWG8RHsKhDm/afwJM/rfPdHFMC6nFceJ6TYMxlb3rYVU1wPS1Kz5YXwY8kgk3PjNAqic8X7UL6yEk44dGbhvXudgDQ/rlppr/l5bN54/1b12Jyn1ie/InbdBFTikZ1fDnJaDtZkSgJHlfxjJiD9pgTREeEV0k8/bPSqB084W2tActewUkHq3tZpVe/ank2NyqheO19idBrKykmv5IK79EpL0KrJIrw9uYSCMHK3cHtI8GqgNkNgHg1drd+7N+ObW7wvuKafwMtgqIq6Xw6P8PztSx1hJMQPqKY94RWEmOubofP7rBeWuE1IxMIcNfny+1PZASroWqdKuWY3Oehb1czuY/GHEHCFYR5MV1Jx2orzqD4eqn3UBYsd8Rcsct+3ZYYKkJwJXFj1wa4sHkNy3PenrXN070TE0igLyGBUU7/rUc6k/v8sCK8+2hYoXUalmYcwXfL9nBdJbs28zgWbDvs+HxRGgW/6DGGTZyyIFm+6wiWZRzBwZPZKGARMlllaUZ4wtwJrSSc4DV+yeFTucjOiy/UthtY9WwTOC+FPadSCtf07dCq8ab9J/HI92twt0UsoqjrfGihL397HoaOW8z+xoLw3s2deIvgG98t24PXp2/BNe8txLXvL8Qdny5len9tXZMVglibxFMSjU0WgvmBkwlnVgx4Y04g6fT2OZyD6JN3sfH+DzkcSWxlvG+6F0SxQTule5M03iJ4In3kJLz/53bLcx75fg3+N3Nr5Pu6v4KPJCDCPBkgoJJILetufZ8oGRkmMuOI0yS4jije+3JQPNZmHsd0ATZO8rsk/7ZmL7N5gfb1q8TtRj5t/X5kHGYXfvyj25zHB33Ho5m6NCKcknBLobjh57lh1yO94m3vcaxEX3UbazZ20vDGozTDAqUU9365ElcximFGEH9ZGP75cqYj376tauG8hlVR3kG4HT/WSbFGlIFl6JUEAHT89zSM+CI4TyXRsZtfOxLHDmOC6wjEqgU7hfnilI2WeygEiZ+NgnbvgyfZTORv3n9SmEixen4Y0QNvD+1oe16C+AVZGEKvJLLzCnD0TB6mrNvvWxpuhrF+Ua9qOfz2z16OzvVzH17RK5fbR//gzx3+CCIYrEvE2bwCT84Yr07djD1H/B259WlR0/Yc0cuxSIReSWTZ9Io37juB+79eGVcaDdP4r3JuUqMC2tat7Ohclq56sYhet0TaqN4tf2zyb17Ej3zxUhbenrUNg9+cy1wWPU7MYH6Ogp67og0Tzy9RinLolYQd93y5AhNXudsBrnqFsnjx6nYYf0dXPH9VWzSpUcEn6ZyjL9RPDmpleW5s4TqRnec5fEksTupWQSFF+shJeHd28JODHuatuXLLR4vR+5VZAIDHfljrWzp+LGTz2hs/YeBVuHzX0bh2RnxqsHWdiMXPkUTFlCSkJMe/DYEoTjlB7HEdOvq0qIGbujbgLUYU+kJ9ZYc6eGHyRtNzY3uNvV+ZHdc8hB4nvbTcfMWb4H8ztuLu3sHuWR6rIEXpjZkxd6uy2O60zwEBL3plNvN7smxnf1kV3w5sd17Q2NX5fk5clzRTVokfSXhRxiK2K1HlzqYM7oqJ1slKQThIGgDwD9WJgEddiVWQIvTGnJj/Rv2yPgBJ2BJPY7grK9r1NSc/WDdFP8tmUiJhUu5E6eAIqSTG3nIeXrqmnefrM4+eQfrISfhzyyFPryqel1Po03yAvgdvN2H4zET/wn53qF/F9pw/1ThOPOInxS6QZFHRfry7R1zX7zhkv1DPbm6NJV63uI0lnre1MdN/AAAgAElEQVT79MRopZgfR73x0uD7OZJgFZVAEB0hppK4pM05uKGLd3PP8l1KdNfvlnkP5uUVvyZO9WXarlIU+OndJKLfowUssqJTg6pxXS/a2pKnYzoRf2w64MnjyOqxLmhW3fX9vDKsZ6Nix+w8Ev0yCb17cyd0Tq8mzCiABUIqiXjRV8qgQx341UDre+V2xdvPR45HR1BK8cRPa7Hur+MAgJ2HT+Nf36xiJJm4iKZXJ6+Ndhe/49Nl6Pvan67vE6v8HhvYMvL5vr7NLK9lWS+N2vv2NiNev97JoHa1md1LlDAtJVJJaHjN4njsiUbv9RCDBUz6KLJ2PVMKJT7NixaT215JTnReZGLF3Hs8G18u3o3rP1gIAHj4u9X4aWV8E5ZOyMkvQPrISfh8YYbvaRlx8Wt/2r6LIPWIUeOTy8AENaJ3k8jnICdvjeqDXep+yxdv+74r6zTajTLf6TJISpSSmLX5IABdAaEeFUUcL9hokrLLCzO831Alek7CGR/MYb9QzE3dij31ireUfZ/z1AYpiGaEUhqZp9ACti3akYXN+096vudzV7Rxfc0Hc3YgN78QXy/Z7du8lVNYpm623wtvC5tdR0oED6T8gkJ8tWS3YZuxeIc4ocRDoSSu71zP0Xm3f6KE89W//6BHbH4lF+XcxNPe5ILYiqpNzhIQXPXOfCzbFczOgImqHNrk6I1jF8UVlbd1nUqerntv9naM/HEtfjZw95y56aBneVzDsHjY7ffCCztzkghza+MX7sLjP67FhMW7iv/IX7wIoVASL11zrqfrvJqNxGhio9H3fOx6SZw7qhFO5eTjTK6B/z8BVu1xvw/IDZ3rGx4fdXlrfPK3Loa/URS9z4ICNhmjHwm8cq3zsnlYDVseZIh6XgTZjzFKy86zbuO+E0gfOSmyKdUbM7bEtZgvFiePd+xMrvo/D+v+Oo70kZOY7xjJglAoCbfeIVoBodSboohnJOrXZJNeJjv51u097osMAHBeQ3eePle/u6DYsVyPPvFmz/23no3Qp2VNw98pLTIB5sWEDN6d5S2GkFfnBK0sHjmdi8lr93m6BwvMpF+T6VxxvzCkreXv9vNmPvdkHNbhLQcU9+Q3Zmy1OdMdbtuBH1coo0ttx0gRzGEaoVASbonX3HRr93TPaftV9BNczEmw0lP9WtVE4+qpKJtUVEyGdHRm+tPYFIftP5brHJodY9HckmNtvxeq4TBc30+na9x0YLT38r+ZW3H3hBVMFzm6wawBcxNCvnmtipa/2+UK0xD/Bok5tSaJsNgSAApiMkQcFVEClcS+42cjPVVKvTWYThaMBU30SML/InRjl/r4z5B2+OPh3hgnQBTcjDGDcV7DapbnGOUKBY0oiTwDc1P1CmUcpZ+WWnSe95FENPlxtpQZYwYzkcMt/3d+A9u1I/oiWs4gjlFs4+y2RH8+rGjC3Mi05LiOBKAjrjvPuHNzJlfZPpnS6DLldhRSs2JZ78I5oMQpie4v/oEHVN97Hr0EVr14fSUAgHa6CLBB9DLGXHMuaqorR3msnPaC0VwMpUC+xVxEepqz7XJ/u68oTHvdKuUin5vUcL7dbmzZCEu+xvL8Ve1crVg2OnVRjPeO22pjV8945GzV8smGx1+5rr3h8Y/m7QQA/LgyM2qU+/Oqv6Jc3nlTogP8UQr85UP0S+tE479F+TKJuKBZtNfIjboV6EGbKwVwBPEMBfD98kzT3516WNWurCiGxwa2RNOaFTDvsT6gFKhfzXsYeRbvsVpqGddmqyCc3/QK0A/7uj6ygdHtnaYZmxXPTFyHUZfbuzgPblcbk3TzSkue6Ivyuq2X3WTxrqwzUfN0//pmNf5xUROLK6Lx+3Uy01eEkI8JIQcJIet0x6oRQqYTQraq/z3HN3hkQAs2gvoMi9HLOzGx6DPGDEY53ZaMQfdAuzaqhpu6NsDcR/tEHW8QRwMZFJRGNyJeJ80B5T1oC8bqVS3vQUGwr84rnu7v+pogRtj6PH/cJrS9F+yewKte+mzhLuxwsO92bB2tUr4MKuiVhMssPn42L+r7WSOvQBP8VvosRxKfAngbwGe6YyMBzKSUjiGEjFS/P8YwTUvEmJJyT+Pq1iaMoEcSSYkJePHq4gEXOzesit0+7zIGAN//o3tc13dNV+YyKqUk4eHv+LkYFjc38SeI0A9O531cwUhso8d3Wr++GX4+AMWluUxSdH/b7UZl2vxEkQwilA4FZiMJSukcALHLBK8EMF79PB7AVazScyZTkKmxSXPeY33Q0KGdnDc/Ogyp4SQKqhWd04smrHu3qIEO9atg1TPOetCHT+XgfXXleYWySZi2wb9tbu0opiQ4NQR6OYKoI05MP25WoS9/ql/UaMjo7s7NTd4zoFvjNHRrnIZ+rWsV+61VbW8LLkXE7+mRWpTSfQCg/rfffJYhMzb6tx2kGfHWuXpVxTfhuOXuCSuY3evT27vi53t6okp5573TOVrockJ8NdXZRT6NbZA6jZ7OXAYn+7FTk88scbOu56N5Ox13OAAgrULZKOVmdH/Hzk2Cmhu0hZdOqF+tnP1JcSDExDUhZDiA4QDQoIFYO8KJSEpyIprUSMX2Q/a208yj7s1BXdOtXU3DDM9RvDANUtRIgq1QP9/TE0kJ0crYLs9H/7bBdTr6gYehC6zD+wT1SqqWT8bRM3n2J6r8tsb5Ystxt3bG0owjuPQlL5LZ4/dI4gAhpDYAqP8NA9RQSsdSSjtTSjvXqMEnFswD/axDG9v9rhFb6aau98e8McLhtqAXv+o+BPSSDHGCi93czbzT0L91LbQ8x3pRl56EBL7zAE52qIsXt20+a5E61K+CtnUrR48kfMh1O+Xm1Nz01M9r0efV2QwksmZOjNMHS9IqlMXAtuxClMfi90jiFwC3ARij/p/oc3qeqVOlHB6/tCWa1Khg+PsD/ZpHlu4TYl4Zo4bylOKuz5czltQdLEJA80TvMRLLh7e6W+RHQLhOCK7YHUxAQzu0MpF1KgfnPR9/hGIj3Gy36wVW3k17jgTjIl8xxXgNRRhg6QL7FYCFAFoQQjIJIcOgKIf+hJCtAPqr34XlrouaGE5CuUGvPL7lsDOeiMQTmoNlRzeB8B1JJLnYi8OMB/s3t/y9nkP79PGzeXh12mZH5wrkaBOhvm7uro1BVF6RvIPCDrORBKX0JpOf+rJKw0/8KFIrdrmPdOoUEXatalCtfCAusKwghK+WYLEo0ei1L3+qH5ISEnDsbK5jz7j7v16J2ZsPOTp3478HouXTv7sR0/e1PK3rVMKfj/RGIQUaWbiMn1uvMtZkKgEvyyYlICeOdTLxwjt9rwi0+JsvbnZcs0LvwZKUWLJ7Mzd2NQ7dLSoEfEcSLOz/Ri6baRXKonL5ZFeu004VBKA4SrglqiPvU3+mYVqqpYLIGDMY9/YpmrurU4WNF1C6yzUQGmEd3Ajh3SQCbmLRWHXic/MLsTvrDPafyI5b8dSpnIK9x7PjukfYMTIleIUQvmYIFjvSBT2A/OCW82zP+WFEd5RNilYkIraHTl/9kp1sHDcm3dcLZ2MWyYURqSRUkh30+iuXS8aANrXw7TLzWED//nUDpm1Q1mcM69UoLpmmPXiR8aY9cNc5q5SShBOcN7oZN9fbVqpXdqjLTAZCiK+9OfvNoFgoiWC1hF20VwC20Xl5huPWp+zU4+nxH9cySbtNncpR38Ma0FGam1R6t7Bf57f62Uvw8rXGER01NAUBxN/rq1A2CTUrpsR3EwAnc9gqCC30s5tC//ykjUxl8ILfE9e2eygwMTcFi9cGnucWwmbwDlT5lRrGI15Skoua7SAGxqEZSfi5efwlrWt5srva4WsPysWtWVfSaf+6EJv3n8TWg/GF27CDdcyfBOLOBfbne3oy7bmzmOQPvMH1nJ54vWZW0Wi9miz92Kdm9sO9md8zltCMJLxu9OIEUSaUFj0eCkcw1K9WHv1a14oynzwxqCXzdO7r62wBoxvchNXuUL8KOjowt3RsUAXn1qtsex4LgjbdaKktedJd2dTXKZ5bcUaH7xCkoseJ3owdRJy30CgJP0cSbnEaldStXjuncvymJV7ETlyyIJ5tZI1guZWqnp/u7olf7u1lf6IHercoikAwsM05uLNXY/z9gkb47I6uFlexJx6zpx+jdKfo84+3uYkVQzqym6dzQmiURL6PSsLthFLn9Gp4yGZRU2lAb4phZZaxC5InMn50VPW3fP+W81A1tQyeHNwaFzYPJnwNi9daMYWfVTslORFPqvtZuA3fbUaPJmlM7hMPbsLRxEto5iREMzeVkJFrXOj1Nqu3w9M0ISK8TSR681b1CmXRJd3ZvmGa1IkJBKkWoVWC4M4LGqFPy5qYufEAJq+NP5baqCvsd67zmx9G9Ci2UZFfhEZJVPIx9olsl+Ljnxc7CzbohJJiEmDFc1e0wR+bDONiBoK+b7bsqX6ur29QrTz36ACEEDStWQE1KpbFi1M2xX0/Vgtv4yG1bFJgyjc0SuLvFzRGpZQkvDNrO/afCMcCs6+X7vbt3jx9zyMyqCIQsPO6kSOJaOLZQ5sn/EtncSqXi7+jOe1fFzKQJFzwV4kOKZOUgFu6p7taGe0UL4tcypWx16/Zef7FaenaiL9dNOLdxLBhTwjxUCK8kpvjtbHXRg+EiKkwvHB953poXiu4uQBRCI2S0KhZqSzze1ZNdd/DSOLcmFnFrAkKrfITsJyTYHQjDvCeP/ADr+Vc6z+wHhn60Ul0iiiLAoMmNOYmjQ9v7YwJi3bj9RlbmNzvgX7NcNeFTVxfxyLEQuhR84BlQ5BACD69vQuzYGwlgXMqpXAzsdaq5M31tVBnimRJnxZ8NiUDSs6IyC2hG0lUr1AWf78wvphIem7u1hDlyrj34+7ZNLyumkYseryv6xXOfVspe29c3LIms8nJBELQu0XNUA7r/VrnMu3BC7Fg5MW+3NsvtDmzBEKY9sDfHtqJ3c1cUlr7haFTEgBQvkwSMsYMRhmOXgZhbMSsOKdyCga3U7ZAvNrhYp329asgY8xgtGO42jjMFpt6Vf0Z/VRKSXY1snrvZn4NqUahOh3H+n3yXJhXpXx4d5eLh9CZmyT+oe2c1tpDeG5Wvaww2/Xv7NUYqWWSMGfLIczk6LZ6abvaSCDs9692Q2Fk4prdjNVv//RnVbsT7u/bDCN6uzdLlwRCOZIoiYgwES2JjzJJCbithz8eeG5Z/lT/QFflmsEyK9rWDSY+lhG3dm/IdRTDE6kk4uDjv3Vmcp8Lm9fAuNvY3IsFXkYFIqzbEIUnBrXCufUq47yGzlYn+0HV1DL4/YELkTFmMJf0C3VODSIsPouXMI9w4yXUb493w8RqrcL427ugSY0Kcd3jpWvaxS2HCNWA9+pcjXg2jEqvnopf7u2FH0b0iEuG+tXC6+FVGHGBVSKVvnzNuajEMYZTvIhQN3gRaiXBgniCj4lUcFhMpMfTPAvStgMAnr+qbdz3aFWb3bapXklOCG/1bKCuFL/5/IYAgOu71Ee1VLb7gwRJKR5IlG4lkTFmsBB2RhZDWZbDYS+3ur5zfSZpPzKgRdz3qMAgps2ANrXivkfcMHqlLJSmW6qllkHGmMHMyoWkiKSAOw+lSklc3r4O0/slOdgXOyhYSuJlVFCVUS8xnk1UmtdSTHYszJAVfQwo6RRW71SUXnDXRtZ7YVvRgrPLuSj7U4+5uh3SA3ZyKVVK4slBrfDs5a2Z3a9sUiKqV2AfJsQt9/RpwqQhEKMaeOeHET3w5yO9477Pbd0bxi+MSjwjo5I2WTr6qraed/D7foSzjb58Q5BXcWPXBoGnGWol4bbHm5KcgNt7slutDQCNa/B3XX1kAPutQ8NIxZTkuEYi3RunYcaDF+G5K9mZZ+rGEV5EAE9appRNSkRTDw4a1VLLcB/ZlTB97YpwKwmX5yf54Yon0IRtGOjXqibuY7j/BEu+Gn4+mtaMz8ssHtrFrANgZeIQxVQChLe6BJ2DRrvf/e/GDgFLoRBqJeEWPyK38nbD1YjHu+imAIewZZMTcUcc7qVhw035aB3jUVUSe69uXJxTkktV8xSFUTZd2SHYva01wuu4DPc+9bzDexsx48GLPF/72MCWyC9QguR41RF1KqfgxauVNRbDLmiEFbuP4upO/hVGUdZBhIGSNifhFsWLpxBpIXadLQmEWkm4jU2jhUuY+dBF2LD3BBMZOtSvgqUZRz1fH495Qx9Lxk3je1WHOvh51d5ix2tXLocf7+7pWR5JcdzoxFa1oz14SqKKcFNl+7aqiZ5NquOC5vwjLpfmrk0g4zlCSAYhZC0hZBUhZFkQaZrIAQBoUqMCM3fYRweKMWnsphDf3adoTiDowi/qQOLStuf4en+7dRe3nN8Qt/VIx09398DL15wLAGDlDi/SgMTu/etXur90zbm4vkt91K4c3pXnJYEgjX59KKUdKKXMghR9cnsXVrfyjChxadyMJHjuI02p/7uLeZmofe//zvNBkqJGsbzFdrcZYwZj9FVtQQhBxwZVI6HXq5bnY2ZhvZ7IDr2CvuvCxpHPIix0lYR84rpPi5q8RRAGrTHq1KCK7blct4AE5e7OGCSRLV5dZHnLcyri31e2wRs3BO/NkpKcgLdu6ujb/WO7MiMvbYmLmhftNlfT4054Thl3q7c+aphDpMRLUE9OAUwjhCwnhAyP/ZEQMpwQsowQsuzQoUMBiVR6SdS1WLzMP+3r2yuzkkChOnGW6EJLEEJwa/d0pAmwUJM1l59bO+p7IiG4oUtwoTv6tXYebqVnU8UNtU2dSp52r/RKL8F2vQxq4ronpXQvIaQmgOmEkE2U0jnaj5TSsQDGAkDnzp0FtVqLTV6Bkm1O4rrw7BTFKqVG1VOx8/BpPsIEQIH6wDxHb25STktVFNOYq9th1Z5jzGW5pE2Raalbo2q49rx6wnpxTbjzfOb3fOumjvjnVysNf+vZNC2S5k1jFzFP2yuBNBeU0r3q/4MAfgLQNYh0SxPZ+QUA4KjHo6+UfqzzmHiPuYdUrEeaFgIjMYHgg1v8mRew4/Nh/hXHAvWBEwR0v47lpWva4evhSiN1Y9cGGKNOoPvFN3d1ZxbzKyxc3r4O7jRZJ8RzrtAK35UEISSVEFJR+wzgEgDr/E63YVp5v5OIm/kMN7fXwh1ce1493HK+dewhv9cqWJmSruigTIpe37keAKCB+p7a1KmEAW389TAy44JmNexP8oi2+Y4bcxMvbujSAPWr8a83S57oi3mP9eEtRuD43XnzShAjiVoA5hFCVgNYAmASpfR3PxPMGDMYl8TYHvWTYyKQQOKL6xNL/WrlkTFmMC5vX8dWQep1RJBzEiN6N8EVqufMzd0aImPM4EiARJZy9GlZs1iIC15ERhLi6whhqFkpBfWq+q+salf2d5LcjNvVkUTs9rKVy5k7dCxg2KF0i+9zEpTSHQDa+51O2OC5ST0v10IrRcCy51S5XDJ+/WcvpI+cxOyeXtEau2a6UNfJiSQyhxQEIowORISX3q5bpVxkW9nPFmbgmYnrAfDZ98MJJdavK9a+F4LRfmBULZ8cWWPCe1CrNaLXncfew+XLO7sxv6db+reuhR9G9MDN3YriY913cbNAZejZtDp+ursH+pt49vRqWr1U1g8RJsxv7Z4e+Ww1kuBJqMNyWEIsv3KnSnl+BYIQgjYCbM8JFO1g5gc9mlZHxpjBkRFFjyZpWLA9y5e0rDivYdWo7zwUc8cGVU1/++LObhFX3dJEmJY+8NRnIcqm+BBhz2L9Qp6fOcZI0tvHRQ2T4QeieI/wynOrdMPgfcUaq/Lwpo8LCr3AM9x7iVMSWqRXfaZe0Kw6HuzfnJdIAIC01DJRC3mC3oJQDyHE96HVS9e0K3aMt8eGvk04v7H3rTTjhV8+iNsjWPj4xYF7NJlVgYf6N484WPBCpM5biTM3jbxUCbinbxA61K/iz4ZDKjd3a4BzKqXgtelbTM/5F2clZY4/pVH0uDs8Q4OIOJLgDY8gfkYjiQUjLw7c62lIx7q24XSqV+C3nqTEKQltMirI0fMLQ9ohN7/QUklo5fHLv3cL1LPFDK0R71Df3FYdD4YNEufH1k9UvnzNuXgqcR0uiwkTEQRyHCEGsTqid4saqMPQLd0pr9vE6Bp5aUtfO7l2lDwlEfkfrA3Pqbm7RxMx4rJUSknGb//s5dse3bxNS0boX1HV1DJ45+ZOfATh1KWXGz5FI8oclR28pSx5SkLN0SADcgH8X6Qep659bRkvOHtyUCvszFLiMBUWMr01E2pULHkB89wgVUQ0oVESnMUscRPXGnde0AjJicHlrl3DzMM7ITVgRfn3CxvjP0OUCetCg14r70bq2ctbc5ZAgZu5ifcLEAzeja9TeHo2ASVYSZRNSsRXf1eClfUMIPSuSOVNk6UgplXQ4iUFgYgNkij7WPDKm6A3ExKd2I6dSHVYT5dG/DzxgBKoJPQvunN6NWx74VKc3ziNmzw80Mp+7Pqol645F9v/MygQGcokFS9a0iauwGu+5trz6mHbC5dySVtEYp1bRFiBHcsXw7qhA+e9V0qckogNDBaUV4Bd+Qqy/EWSimmLCCGB7WvAw2tIYg9PLxmNt4d2xE939+AthtBzElrV5bkPiUaJmrhuVrOCq52nWGI/JxEc2urZWHNTkCQlJiAttQyyTudyk0FUeA+oJt3XC/Wqlkf756ZxSf+yc8UwexUbSfARQ3hKjJKoX60ct01rRCU5kURCVfNAGpeM4Z0vbeqIEUadOzIIqCNKjJKY+yi/eOtOCLIAaj3VIR3rombFFPxv5tbgEreAdw9aFGQ+iEFslRRxTkIEkfgbKEsJ7eoGP/mUlJDANRzIjQFucB8mRFxoWBqJbYAFaI+FJPRKYnC72nhsYEveYliy+fmBaF0nuCi0mhcR717IIwNaYM4jpW8bSjtu7tqQ265okiKKjyS4iGHIyEtbomFaeSF2WAy9knjn5k4Y0bsJbzEsKZsU7KI2rZ/Ku8wTQpCoW9Ao+88KDdLKY+HjfXmLIYmB96I1PZ0aVMWfj/RBaln+MwKhVxKS4mg2bxFsrKVxMxtJOCi2mI5/dRESqSRKIIWCmJuA6ElaOWEbzfWd6wk/Ci7JaNXjjp6NAADlBA9vzwv+YxkJc+qq4Y4bVitvc6b/8FyrITovX9uetwhozHHzK95onaj+rWuhQkoShqnKQhKNVBI+kZxIuO0bMbDtOfhiWDf0aMI/HAnPdRoSa369txfqVQ1+/wTeVExJQmICicxBJBBw37lSZKSS8AmebSMhBL2aibFvRWlshMJCu3r8PWd4sOLp/gCAmz9cDEA6VNgh5yR8QvagFVKSE/HU4FYA5PoAiRgkJyYgOTEhMikhLaLWSCUh8R3Ni0RWRolIaBPXsvNijVQSPpEkQPRGURBlcZ9EokeWR2fIOQkfGHV5a3RvUh0D3pjDWxQh0ExvpV1xfj38fBw4kc1bDEksciBhiVQSPvA36UoXheYGm8BRSVSvUIZb2hqlbfMr0dG8m6SOsCYQcxMhZCAhZDMhZBshZGQQaUrEQVt1nchpfL/l+UuxYKQMgyGJ5sFLmiMttUyp9fJyiu8jCUJIIoB3APQHkAlgKSHkF0rpBr/TlohBQaHyn9cuW7FbqdaoWJaLHBKx6JJeDctVd1iJOUGYm7oC2EYp3QEAhJCvAVwJoMQriQQCVCqXzFsM7mjmJhG2Ypx4T0/UqSLXbkgkTglCSdQFsEf3PRNAtwDS5c7G0QN5iyAE13Sqi4/n7cSQjnV5i4L2nDeVl0jCRhBKwqj7GDVXRAgZDmA4ADRo0CAAkfzhxavboXmtipHvQYcIN+OFIW25blnZMC0V654bwC19iUTinSCURCYA/RZl9QDs1Z9AKR0LYCwAdO7cObTOBjd1FVPB3dytIW8RJBJJSAnCu2kpgGaEkEaEkDIAbgTwSwDpSiQSiSROfB9JUErzCSH3ApgKIBHAx5TS9X6nK5FIJJL4CWQxHaV0MoDJQaQlkUgkEnbI2E0SiUQiMUUqCYlEIpGYIpWERCKRSEyRSkIikUgkpkglIZFIJBJTCBVsuzBCyEkAm3nL4YHqAA7zFsIDUu5gkXIHRxhlBrzL3ZBSWoO1MCLuJ7GZUtqZtxBuIYQsk3IHh5Q7WMIodxhlBsSTW5qbJBKJRGKKVBISiUQiMUVEJTGWtwAekXIHi5Q7WMIodxhlBgSTW7iJa4lEIpGIg4gjCYlEIpGIAqXU8g/AxwAOAlinO9YewEIAawH8CqCSejwZwHj1+EYAj1vdxyS9gVBcYLcBGKk7fq96jAKobnF9IwCLARwHkA1gvXr8QlUmCmCXE7mh7IMxSz22HsD9HuT+FMBOAKvUvw4m1+uf71BMfg8DcFp9niwHcqcAWAJgtSr3cxZy3wZgq/p3m+74DQDWqNe/bHJteQCTAGwCcFSVcZ36WwNVhtMAzqrvxEk5yVCPrwKwzEN+T1CPr1PLXLKb/IaySdaXqsxnAcxxKHcVAN+rebERQHeXchMALwDYol5/n8n12vMdVeXT5O4N4KQuvzc5KCctUFQuVwE4AeABp+2Aevw6tYwUAuhs8b6qAZgOpV7mAtigHn9ElVUr3xSKK6ddft+vvuP1ZjLb5PdHUOrHGvW9VXBZvh8EsF09dgrADF1+lwHwiSr3agC9dfc8Tz2+DcCbUK05LuTuC2CF+r7mAWhqcr1lOgAehk1bGjnX9gSlce2E6EZrKYCL1M93ABitfh4K4GtdBmcASDe7j0FaiWrGN1YzejWA1upvHQGkq/e0UhLfQtmz4kL15e9Vj6erhWoqgGudyA2gNoBO6vGKUCpwa5dyfwrgWgf5rD3fPgAX6wpjFSiV/jpd5bCTm0At9FAq2mIA55tU3B3q/6rq56oA0gDsBlBDPW88gL4mlaiP+vliKIU3Q/0+VpXnIgCtofh9Oyknlu/XQX4PUp+fAPgKwKfr2KUAAAriSURBVAiX+T0IwDFV7vPVPHEi93gAd+oaiSou5b4dwGcAEtTvNU3k1p7vQgC/o6h899bkdlMvY2TbD7WBdtIOqMdbQVE2s2GtJF4GMFK9z5sADsW2JwAuh6IM7Mp3Wyh1uTwUN/4ZAJq5zO9KuvP+C11D7LB89wGwXJV7BJQOkSb3PQA+0d6jep72XpcA6K6+wykALnUp9xYArdTPdwP41CS/TdOB0vmdCqWzbKskbM1NlNI5AI7EHG4BpYcFKL2Da7TTAaQSQpIAlIPSYzhhcZ9YugLYRindQSnNBfA1gCvV61dSSjOsLiaEECgv83s1vQlQGneo1zaA0ig4kptSuo9SukK9/iSUAmy0UbOp3E7RPV8OlF6LxlAoZsHv1e8/OpCbUkpPqeckq3/UINkBAKZTSo9QSo9CyZOBUArnFkrpIfW8Gbo09TKfoZTOUj//AaV3k6yT7Rwo5aQylApuW04cYlVOJqvPT6FUlHpGN7DI7yuhVMw5lNJFqqw3WMlNCKkEpfH7SL13LqX0mBu5oTQ0/6aUFqr3OGgit/Z8c9Tn0691SoXLeqmjL4DtlNJdJuka1l9K6UZKqZPFr1cCGK/e53MAlXS/ae3JTVB64HZytwKwSC1/+QD+BDDEIE2rcnICiLQZ5WBQP6zKt3q8mSr3IiiNsSZ3awAz1fMOQlHenQkhtaEop4Vq+fwMwFVu5Fbl1PKuMmJ2+VSfyS6d1wE8avTMRnidk1gH4Ar183Uo2p70eyjDr31QeqKvUkrtFIOeugD26L5nwrhRNiMNwDG14ABKzyhZ9/s6nayu5CaEpEPpfS72IPcLhJA1hJDXCSFlXTwPADSHUjnXEEKWA3jJidyEkERCyCooJoLplFI3cm8D0JIQkq5W0KsQvQVtMQghVQD0gzL0BoBRAAqgmHImQ6lMTvKbAphGCFmu7n1uhG05IYQkA7gFSm/bDXWh9OK08l2gu7eZ3I3V5/yEELKSEDKOEJLqUu4mAG4ghCwjhEwhhDSzElJ9vqtRlN8aOwghU6CY09zUyxuhjLz8ohalVOugHUK0clsHZXQ/EEp9tZN7HYALCSFphJDyUEZXRuXTspwQQj6B0ka0BPCWlfAG5VuT+woo5uBDOhlWA7iSEJJECGkExfRTX00700weh3LfCWAyISQTSvkeY3K9YTqEkCsA/EUpXW31vHq8Kok7ANyjNloVoWh4QNGABQDqQJkbeIgQ0tjFfYnBMUfazuJ6PXdAKRAvwYXchJAKAH6AYvs06vFayf24mmYXKGadxxw9SRFJAA5AaewTofT+NSVoKjeltIBS2gFKT7orIaStU7nVUcUIAN8AmAtlFJBvcK5yE0WRfAXFtJanHr4JwNtQhugHAPwfnOV3T0ppJwCXQiljFzqVO+b7u1BGA3PN5DZ7HAAvoqh8J+meyUzuJCimmPcopR2hNGwjXcpdFkA2VVbafghlDsCKd6GMJM6o31cA6AZlbqkplMbEafkuA6Wx+84mTb+4A8BTUNqjJNjITSndCKUOT4fSCVgN4/JpWU4opber996IotFi8ZsYl29N7ucB/A3AMp3cH0NpmJcBeAPAAlU+p+2b1Xn/AjCIUloPyqjrv06vVxXqkwCeMfjdFE9KglK6iVJ6CaX0PCiZt139aSiA3ymleeowaz4A0+XlhJD6hJBV6t8/oGSsvkdQDwbDqZh7TFWvHwfF7l1FfamAYu6IvFRK6SYoBesxp3KrPbYfAEyglP7oVm7VZEUppTlQXmpXA7mtyATwM6W0r9ro/4GiuC62+a2aPWYDGEgI6aaT+wobuX+llHajlHaHMoG2VRudqH//1l03FkrjpG/YhgF4Wy0nLaGYdTRThqnclFIt/YMAfoKi4FyVE0LIswBqQJlc1I65yW+qK9+A4nhgJXcmgEzdaO17AJ1cyp0JpZxBfe5zzeTWPd9o7Ril9ASldIUqdzMo81i2+a1yKYAVlNID6v1j5XYNIeQT9XptR8oDqhkEquyRRl2tlzug2Ngd1UtK6UeU0k6U0guhjLS3emlPKKUFUDpD17gs39r9kqCMJL/Q5KaU5lNK/0Up7UApvRLKvOJWVZ56MdfvdSo3IaQGgPa6cvYNgB4GchumA2W02gjAakJIhnp8BSHkHFhBbSYtFJOWMumr+15T/Z8Axd51h/r9MSgNIYFiH90A4Fyz+xikkwSlsDRC0YRNm5hzMmA9cf0dgBvVzxOgTuxpckPpDVznRG71+2cA3rDJH1O5AdRW/xMovYoxNvfKgGLW0iZSW0Ex1SSpsh0F8LSN3DWgTpxCsbfOBXCZQVrVoDSAVdW/nQCqxbzjqlBssc1N5H0eSuOWoH+/UCbL/ql+bg2lx2uX36kAKqrnpELpgQ10md93qteVc1i2Y/N7MBR7MoEy8XfYTm71t7kAWqifRwF4xaXcY3Tp9Aaw1ETeyPPF5Pc5unfWDYpZxGm9/BrA7W7bgZjfZsN64voVqJPDUEYB+onrJlAa+gpw2J7onrUBFO+jqk7zW71fU129fBWKKctN+e6olp1mKN4OlgeQqn7uD2VEq91vKRSHCG1CeZALuZOglMfm6nnDAPxgIreTdDLAyLvpKyg2wTwoGmoYFA+bLerfGBQtyqsApZFer77QR6zuY5LeIPW+2wE8qTt+n3pdPhStOM7k+sZQhuEnofSmtPRGQ5lAKkSRrdxSbgC9oAzz1qDITbBYZtvI/QcUV7R1UHobxVztYp5Pk69Ql98TofTEc6BMItvJfS6Alarc6wA8Y/F+74AyB7ENuoZCfV8b1L8bTa6tp+bPRijKK099P5lQzAc7VJmzoTREdnI3hlIhNNfdJy3kNsvvfPWY9r4Mn90mv+dCMR3kQOlUOCnfHaCYF9YA+BkGjZaN3FWguFuuheJe3t7keu35tPwuUOWeAKV+5UAp9587lLs8FLfqym7bAfX4EPV7DhSz4lST69OgKN+T6rn69mQClAlpN+3JXPXYahh43lnlN5RGfT6K6uUE6LydHJbvDarM2erfVp3c6VBG3xuh1NeGunt2VtPcDsUca+YCa1ZOhqDItXY2gMYm19umA4dKQq64lkgkEokpcsW1RCKRSEyRSkIikUgkpkglIZFIJBJTpJKQSCQSiSlSSUgkEonEFKkkJKUeQkiBuhBpPSFkNSHkQUKIZd1QQ5YMDUpGiYQXUklIJMBZqqyObQNl8dMgAM/aXJMOZUWwRFKikeskJKUeQsgpSmkF3ffGUFasVgfQEMrCNC1g372U0gWEkEVQVsPvhBIm/E0oC8F6Q4nD9A6l9IPAHkIi8QmpJCSlnlgloR47CiUw40kAhZTSbDUy61eU0s6EkN4AHqaUXqaePxxKqIjn1Ui/86HsAbITEkmISbI/RSIplWiRNJMBvE0I6QAlBEZzk/MvAXAuIeRa9XtlKHF9pJKQhBqpJCSSGFRzUwGU8OzPQolJ1B7KHF622WVQAhpODURIiSQg5MS1RKJDDcf8PpQw5xTKiGAfVXaMuwXKnh6AYoaqqLt0KoARamh5EEKam2w8JJGECjmSkEiAckTZxS8ZSpTPz1G0mcu7AH4ghFwHYBaUDYUAJdprPiFkNZRIsf+D4vG0ghBCoEQZNtqaUiIJFXLiWiKRSCSmSHOTRCKRSEyRSkIikUgkpkglIZFIJBJTpJKQSCQSiSlSSUgkEonEFKkkJBKJRGKKVBISiUQiMUUqCYlEIpGY8v/EbVguz8eVBwAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#Primeiramente vamos importar os dados e armazena-los em um pandas dataframe\n", + "\n", + "series = \n", + "\n", + "#Vamos plotar as 5 primeiras linhas para verificar o dataser carregado\n", + "print(series.head())\n", + "\n", + "#E Então plotar em um gráfico de linhas para analisa-lo\n", + "series.plot()\n", + "mtl.pyplot.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#plotando correlação\n", + "pd.plotting.lag_plot(series)\n", + "mtl.pyplot.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " t-1 t+1\n", + "t-1 1.00000 0.77487\n", + "t+1 0.77487 1.00000\n" + ] + } + ], + "source": [ + "#criando um dataset diferenciado\n", + "values = pd.DataFrame(series.values)\n", + "dataframe = pd.concat([values.shift(1), values], axis=1)\n", + "dataframe.columns = ['t-1', 't+1']\n", + "result = dataframe.corr()\n", + "print(result)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#Uma outra forma de plotar a autocorrelaçao\n", + "plot_acf(series, lags=31)\n", + "mtl.pyplot.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Lag: 29\n", + "Coefficients: [ 5.57543506e-01 5.88595221e-01 -9.08257090e-02 4.82615092e-02\n", + " 4.00650265e-02 3.93020055e-02 2.59463738e-02 4.46675960e-02\n", + " 1.27681498e-02 3.74362239e-02 -8.11700276e-04 4.79081949e-03\n", + " 1.84731397e-02 2.68908418e-02 5.75906178e-04 2.48096415e-02\n", + " 7.40316579e-03 9.91622149e-03 3.41599123e-02 -9.11961877e-03\n", + " 2.42127561e-02 1.87870751e-02 1.21841870e-02 -1.85534575e-02\n", + " -1.77162867e-03 1.67319894e-02 1.97615668e-02 9.83245087e-03\n", + " 6.22710723e-03 -1.37732255e-03]\n", + "predicted=11.871275, expected=12.900000\n", + "predicted=13.053794, expected=14.600000\n", + "predicted=13.532591, expected=14.000000\n", + "predicted=13.243126, expected=13.600000\n", + "predicted=13.091438, expected=13.500000\n", + "predicted=13.146989, expected=15.700000\n", + "predicted=13.176153, expected=13.000000\n", + "Test MSE: 1.502\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# divide dataset\n", + "X = series.values\n", + "train, test = X[1:len(X)-7], X[len(X)-7:]\n", + "\n", + "# treina autoregressão\n", + "model = \n", + "model_fit = \n", + "print('Lag: %s' % model_fit.k_ar)\n", + "print('Coefficients: %s' % model_fit.params)\n", + "\n", + "# faz predições\n", + "predictions = \n", + "\n", + "\n", + "for i in range(len(predictions)):\n", + " print('predicted=%f, expected=%f' % (predictions[i], test[i]))\n", + "error = mean_squared_error(test, predictions)\n", + "print('Test MSE: %.3f' % error)\n", + "\n", + "# plota resultados\n", + "mtl.pyplot.plot(test)\n", + "mtl.pyplot.plot(predictions, color='red')\n", + "mtl.pyplot.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/3. Modelos regressivos/Exercicio_Autoregressao/.ipynb_checkpoints/[Solu\303\247\303\243o] Prevendo Temperatura-checkpoint.ipynb" "b/3. Modelos regressivos/Exercicio_Autoregressao/.ipynb_checkpoints/[Solu\303\247\303\243o] Prevendo Temperatura-checkpoint.ipynb" new file mode 100644 index 0000000..4f0e75f --- /dev/null +++ "b/3. Modelos regressivos/Exercicio_Autoregressao/.ipynb_checkpoints/[Solu\303\247\303\243o] Prevendo Temperatura-checkpoint.ipynb" @@ -0,0 +1,457 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Prevendo Temperatura\n", + "\n", + "\n", + "Vamos investigar a autocorrelação de uma série temporal univariada para então desenvolver um modelo autoregressivo e usa-lo para fazer predições.\n", + "\n", + "\n", + "Vamos usar o arquivo \"daily-min-temperatures.csv\" que possui a temperatura mínima de 10 anos (1981-1990) da cidade de Melbourne, Australia.\n", + "\n", + "As unidades estão em graus Celsius e existem 3.650 observações. A fonte dos dados é creditada como o Australian Bureau of Meteorology.\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "#Vamos importar as bibliotecas que vamos utilizar\n", + "\n", + "import pandas as pd\n", + "import matplotlib as mtl\n", + "from statsmodels.graphics.tsaplots import plot_acf\n", + "from sklearn.metrics import mean_squared_error\n", + "from statsmodels.tsa.ar_model import AR" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Temp\n", + "Date \n", + "1981-01-01 20.7\n", + "1981-01-02 17.9\n", + "1981-01-03 18.8\n", + "1981-01-04 14.6\n", + "1981-01-05 15.8\n" + ] + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#Primeiramente vamos importar os dados e armazena-los em um pandas dataframe\n", + "\n", + "series = pd.read_csv('daily-min-temperatures.csv', header=0, index_col=0)\n", + "\n", + "#Vamos plotar as 5 primeiras linhas para verificar o dataser carregado\n", + "print(series.head())\n", + "\n", + "#E Então plotar em um gráfico de linhas para analisa-lo\n", + "series.plot()\n", + "mtl.pyplot.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Verificação rápida de autocorrelação\n", + "\n", + "Há uma verificação visual rápida que podemos fazer para checar se há uma autocorrelação em nosso conjunto de dados de séries temporais.\n", + "\n", + "Podemos plotar a observação do periodo anterior (t-1) com a observação do próximo periodo (t + 1) em um gráfico de dispersão.\n", + "\n", + "Isso pode ser feito manualmente, primeiro criando uma versão lag do conjunto de dados de séries temporais e usando uma função de plotagem de dispersão incorporada na biblioteca do Pandas.\n", + "\n", + "Mas existe uma maneira mais fácil.\n", + "\n", + "O Pandas fornece um gráfico embutido para fazer exatamente isso, chamado de função lag_plot ().\n", + "\n", + "Abaixo está um exemplo de criação de um gráfico de lag do conjunto de dados de Temperaturas Diárias Mínimas." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "pd.plotting.lag_plot(series)\n", + "mtl.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A execução acima plota os dados de temperatura (t) no eixo x em relação à temperatura no dia anterior (t-1) no eixo y.\n", + "\n", + "Podemos ver uma grande bola de observações ao longo de uma linha diagonal do gráfico. Isso mostra claramente um relacionamento ou alguma correlação.\n", + "\n", + "Esse processo pode ser repetido para qualquer outra observação para trás , como se quiséssemos revisar a correlação nos últimos 7 dias ou com o mesmo dia do mês passado ou do ano passado.\n", + "\n", + "Outra verificação rápida que podemos fazer é calcular diretamente a correlação entre a observação e a variável lag.\n", + "\n", + "Podemos usar um teste estatístico como o coeficiente de correlação de Pearson. Isso produz um número para resumir a correlação entre duas variáveis entre -1 (correlação negativa) e +1 (correlação positiva) com valores pequenos próximos a zero indicando baixa correlação e valores altos acima de 0,5 ou abaixo de -0,5 mostrando alta correlação.\n", + "\n", + "A correlação pode ser calculada facilmente usando a função corr () no DataFrame do conjunto de dados com lag.\n", + "\n", + "O exemplo abaixo cria uma versão defasada do conjunto de dados de Temperaturas Diárias Mínimas e calcula uma matriz de correlação de cada coluna com outras colunas, incluindo ela própria." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " t-1 t+1\n", + "t-1 1.00000 0.77487\n", + "t+1 0.77487 1.00000\n" + ] + } + ], + "source": [ + "values = pd.DataFrame(series.values)\n", + "dataframe = pd.concat([values.shift(1), values], axis=1)\n", + "dataframe.columns = ['t-1', 't+1']\n", + "result = dataframe.corr()\n", + "print(result)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Esta é uma boa confirmação para o gráfico acima pois mostra uma forte correlação positiva (0,77) entre a observação e o valor de lag - 1.\n", + "\n", + "Isso é bom para verificações pontuais, mas trabalhoso se quisermos verificar um grande número de variáveis de lag em nossa série temporal.\n", + "\n", + "A seguir, veremos uma versão facilitada dessa abordagem.\n", + "\n", + "\n", + "# Gráficos de autocorrelação\n", + "\n", + "Podemos traçar o coeficiente de correlação para cada variável de lag.\n", + "\n", + "Isso pode rapidamente dar uma idéia de quais variáveis de lag podem ser boas candidatas para uso em um modelo preditivo e como a relação entre a observação e seus valores históricos mudam com o tempo.\n", + "\n", + "Poderíamos calcular manualmente os valores de correlação para cada variável de lag e plotagem. Felizmente, o Pandas fornece um gráfico interno chamado função autocorrelation_plot ().\n", + "\n", + "O gráfico fornece o número de atraso ao longo do eixo x e o valor do coeficiente de correlação entre -1 e 1 no eixo y. O gráfico também inclui linhas sólidas e tracejadas que indicam o intervalo de confiança de 95% e 99% para os valores de correlação. Os valores de correlação acima dessas linhas são mais significativos que os abaixo da linha, fornecendo um limite ou ponto de corte para a seleção de valores de lag mais relevantes." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "pd.plotting.autocorrelation_plot(series)\n", + "mtl.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A execução do exemplo acima mostra o balanço na correlação positiva e negativa, à medida que os valores de temperatura mudam nas estações de verão e inverno a cada ano anterior.\n", + "\n", + "\n", + "# Gráfico de Autocorrelação de Pandas\n", + "\n", + "A biblioteca statsmodels também fornece uma versão do gráfico na função plot_acf () como um gráfico de linhas." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plot_acf(series, lags=31)\n", + "mtl.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Neste exemplo, limitamos as variáveis de lag avaliadas em 31 para facilitar a leitura.\n", + "\n", + "# Gráfico de Autocorrelação de Statsmodels\n", + "\n", + "\n", + "Agora que sabemos como revisar a autocorrelação em nossas séries temporais, vejamos a modelagem de autoregressão.\n", + "\n", + "Antes de fazer isso, vamos estabelecer um desempenho de linha de base.\n", + "\n", + "# Modelo de persistência\n", + "\n", + "Digamos que queremos desenvolver um modelo para prever os últimos 7 dias de temperaturas mínimas no conjunto de dados, com todas as observações anteriores.\n", + "\n", + "O modelo mais simples que poderíamos usar para fazer previsões seria persistir na última observação. Podemos chamar isso de modelo de persistência e fornece uma linha de base de desempenho para o problema que podemos usar para comparação com um modelo de autoregressão.\n", + "\n", + "Podemos desenvolver um equipamento de teste para o problema dividindo as observações em conjuntos de treinamento e teste, com apenas as últimas 7 observações no conjunto de dados atribuídas ao conjunto de testes como dados \"não vistos\" que desejamos prever.\n", + "\n", + "As previsões são feitas usando um modelo de validação direta, para que possamos persistir nas observações mais recentes do dia seguinte. Isso significa que não estamos fazendo uma previsão de 7 dias, mas 7 previsões de 1 dia." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Test MSE: 3.423\n" + ] + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# cria lagged dataset\n", + "values = pd.DataFrame(series.values)\n", + "dataframe = pd.concat([values.shift(1), values], axis=1)\n", + "dataframe.columns = ['t-1', 't+1']\n", + "\n", + "# divide em treino and test \n", + "X = dataframe.values\n", + "train, test = X[1:len(X)-7], X[len(X)-7:]\n", + "train_X, train_y = train[:,0], train[:,1]\n", + "test_X, test_y = test[:,0], test[:,1]\n", + " \n", + "# cria modelo persistencia\n", + "def model_persistence(x):\n", + " return x\n", + " \n", + "# walk-forward validation\n", + "predictions = list()\n", + "for x in test_X:\n", + " yhat = model_persistence(x)\n", + " predictions.append(yhat)\n", + "test_score = mean_squared_error(test_y, predictions)\n", + "print('Test MSE: %.3f' % test_score)\n", + "\n", + "# plota predição vs esperado\n", + "mtl.pyplot.plot(test_y)\n", + "mtl.pyplot.plot(predictions, color='red')\n", + "mtl.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A execução do exemplo imprime o erro quadrático médio (MSE).\n", + "\n", + "O valor fornece um desempenho de linha de base para o problema.Os valores esperados para os próximos 7 dias são plotados (azul) em comparação com as previsões do modelo (vermelho).\n", + "\n", + "# Modelo de autoregressão\n", + "\n", + "Um modelo de regressão automática é um modelo de regressão linear que usa variáveis lag como variáveis de entrada.\n", + "\n", + "Poderíamos calcular o modelo de regressão linear manualmente usando a classe LinearRegession no scikit-learn e especificar manualmente as variáveis de entrada de lag a serem usadas.\n", + "\n", + "Como alternativa, a biblioteca statsmodels fornece um modelo de regressão automática que seleciona automaticamente um valor de lag apropriado usando testes estatísticos e treina um modelo de regressão linear. É fornecido na classe AR.\n", + "\n", + "Podemos usar esse modelo criando primeiro o modelo AR () e depois chamando fit () para treiná-lo em nosso conjunto de dados. Isso retorna um objeto ARResult.\n", + "\n", + "Uma vez ajustado, podemos usar o modelo para fazer uma previsão chamando a função predict () para várias observações no futuro. Isso cria uma previsão de 7 dias, que é diferente do exemplo de persistência acima.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Lag: 29\n", + "Coefficients: [ 5.57543506e-01 5.88595221e-01 -9.08257090e-02 4.82615092e-02\n", + " 4.00650265e-02 3.93020055e-02 2.59463738e-02 4.46675960e-02\n", + " 1.27681498e-02 3.74362239e-02 -8.11700276e-04 4.79081949e-03\n", + " 1.84731397e-02 2.68908418e-02 5.75906178e-04 2.48096415e-02\n", + " 7.40316579e-03 9.91622149e-03 3.41599123e-02 -9.11961877e-03\n", + " 2.42127561e-02 1.87870751e-02 1.21841870e-02 -1.85534575e-02\n", + " -1.77162867e-03 1.67319894e-02 1.97615668e-02 9.83245087e-03\n", + " 6.22710723e-03 -1.37732255e-03]\n", + "predicted=11.871275, expected=12.900000\n", + "predicted=13.053794, expected=14.600000\n", + "predicted=13.532591, expected=14.000000\n", + "predicted=13.243126, expected=13.600000\n", + "predicted=13.091438, expected=13.500000\n", + "predicted=13.146989, expected=15.700000\n", + "predicted=13.176153, expected=13.000000\n", + "Test MSE: 1.502\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# divide dataset\n", + "X = series.values\n", + "train, test = X[1:len(X)-7], X[len(X)-7:]\n", + "\n", + "# treina autoregressão\n", + "model = AR(train)\n", + "model_fit = model.fit()\n", + "print('Lag: %s' % model_fit.k_ar)\n", + "print('Coefficients: %s' % model_fit.params)\n", + "\n", + "# faz predições\n", + "predictions = model_fit.predict(start=len(train), end=len(train)+len(test)-1, dynamic=False)\n", + "for i in range(len(predictions)):\n", + " print('predicted=%f, expected=%f' % (predictions[i], test[i]))\n", + "error = mean_squared_error(test, predictions)\n", + "print('Test MSE: %.3f' % error)\n", + "\n", + "# plota resultados\n", + "mtl.pyplot.plot(test)\n", + "mtl.pyplot.plot(predictions, color='red')\n", + "mtl.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A execução do exemplo imprime o primeiro lag ideal escolhido e a lista de coeficientes no modelo de regressão linear treinado.\n", + "\n", + "Podemos ver que um modelo de 29 lag foi escolhido e treinado. Isso é interessante, dado o quão próximo esse atraso está do número médio de dias em um mês.\n", + "\n", + "A previsão de 7 dias é impressa e o erro quadrático médio da previsão é sumarizado.\n", + "\n", + "É feito um gráfico dos valores esperados (azul) versus os valores previstos (vermelho).\n", + "\n", + "A previsão parece muito boa (cerca de 1 grau Celsius por dia), com um grande desvio no dia 5.\n", + "\n", + "Previsões do modelo de AR fixo\n", + "Previsões do modelo de AR fixo\n", + "\n", + "Neste exercício, aprendemos como fazer previsões de autoregressão para dados de séries temporais usando Python.\n", + "\n", + "Você aprendeu especificamente:\n", + "\n", + "Sobre autocorrelação e autoregressão e como eles podem ser usados para entender melhor os dados de séries temporais.\n", + "Como explorar a autocorrelação em uma série temporal usando gráficos e testes estatísticos.\n", + "Como treinar um modelo de regressão automática em Python e usá-lo para fazer previsões de curto prazo e contínuas." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/3. Modelos regressivos/Exercicio_Autoregressao/Prevendo Temperatura.ipynb b/3. Modelos regressivos/Exercicio_Autoregressao/Prevendo Temperatura.ipynb new file mode 100644 index 0000000..a205be6 --- /dev/null +++ b/3. Modelos regressivos/Exercicio_Autoregressao/Prevendo Temperatura.ipynb @@ -0,0 +1,269 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Prevendo Temperatura\n", + "\n", + "\n", + "Vamos investigar a autocorrelação de uma série temporal univariada para então desenvolver um modelo autoregressivo e usa-lo para fazer predições.\n", + "\n", + "\n", + "Vamos usar o arquivo \"daily-min-temperatures.csv\" que possui a temperatura mínima de 10 anos (1981-1990) da cidade de Melbourne, Australia.\n", + "\n", + "As unidades estão em graus Celsius e existem 3.650 observações. A fonte dos dados é creditada como o Australian Bureau of Meteorology.\n", + "\n", + "\n", + "Para concluir esse exercicio faça os passos abaixo:\n", + "\n", + "1. Importe as bibliotecas que irá usar\n", + "2. Importe o arquivo 'daily-min-temperatures.csv'\n", + "3. Plote grafico de autocorrelação\n", + "4. Faça o fit do modelo\n", + "5. Faça a prediçao" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "#Vamos importar as bibliotecas que vamos utilizar\n", + "\n", + "import pandas as pd\n", + "import matplotlib as mtl\n", + "from statsmodels.graphics.tsaplots import plot_acf\n", + "from sklearn.metrics import mean_squared_error\n", + "from statsmodels.tsa.ar_model import AR" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Temp\n", + "Date \n", + "1981-01-01 20.7\n", + "1981-01-02 17.9\n", + "1981-01-03 18.8\n", + "1981-01-04 14.6\n", + "1981-01-05 15.8\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#Primeiramente vamos importar os dados e armazena-los em um pandas dataframe\n", + "\n", + "series = \n", + "\n", + "#Vamos plotar as 5 primeiras linhas para verificar o dataser carregado\n", + "print(series.head())\n", + "\n", + "#E Então plotar em um gráfico de linhas para analisa-lo\n", + "series.plot()\n", + "mtl.pyplot.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#plotando correlação\n", + "pd.plotting.lag_plot(series)\n", + "mtl.pyplot.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " t-1 t+1\n", + "t-1 1.00000 0.77487\n", + "t+1 0.77487 1.00000\n" + ] + } + ], + "source": [ + "#criando um dataset diferenciado\n", + "values = pd.DataFrame(series.values)\n", + "dataframe = pd.concat([values.shift(1), values], axis=1)\n", + "dataframe.columns = ['t-1', 't+1']\n", + "result = dataframe.corr()\n", + "print(result)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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3bjAiMeWuRd1ef+XxD+J2bo3GaeyYvH4HXCAi54jI2cCngAcdOPfJwHYR2SkincCzwBWhA0RkqYhYtUneA0bgIDNHG2aOxkE0M4zKN0xNbpWBOdDQzrCcyJFmALlpSdS3uptgWdXUwaljC8LuU6orc97tlgJWIcx7rjyu174Onx8BVuys6bXPDSJ937rxmeZwxU7YcJKIbLFeiMhWpZQTUV/DgX0hr8uBU/oY/z/Af0NepyqlVgE+4H4R+U+4g5RSNwE3ARQVFbFs2bLgvt0Nxt3quytX077XuXpWARESFFw8Jqnb+cJxoNlwAi95bzVtEWRobm7u930isa+6hRJPa5/H11V48QWEsteXkZWsIo6Lhp4yV9S1UuxpiyjHNZOSeWZzJ+c9sISHzu2dL+MUb+w0VmJpdTtYtmxXt325bcZ8ePmtj/CWR47Oc4qnNhnh4mkeuOG4FJbt87KhJsDcf69jSMvOqN5rIHNkMNFyxxe35bZzFV2llPob8E/z9Zdwxikf7soV9pZNKXUtMBM4J2TzKBE5oJQaC7yhlFonIjt6vaHIY8BjABMnTpRZs2YF9+2paeHnK5YxctxEZs0cGfsn6cGhxnYCi5ZwytQJzDptdJ9jWzp8/PTtReQNG8OsWePCjlm2bBmhcttlX20rzQuX4skqYNasmRHHqa1VPLP5A9b5hvLTC46N+jzhCJVZRGhdvJBjx41i1qzw739MXSvPbF7KsLwsZs1yrxDDR96tqG3buOKCWXgSuy/QzxHht6sWsL4xjd/MOss1GSy+uvBVAN67/QJy0pK4obmDGfcspiAjOerfO9Y5EkqHz8+q3XWcPq6g26rRTZyQezDQcofHjsnrm8AG4LvA94CNwDccOHc5EHoVHwH0SgRQSp0H3A5cHppcKSIHzL87gWXA9GgFsLK1reKJTrFih2Ey6Sup0SIjxUOyJ8EVH8aeGsOMdvq48KYmizPM/W6Zmyoa2+n0BSLcLhiMyEvnhBE53Volu8F/Vu9HhF7KBLpMbxvjkA9j1ZAryEgOzsOCzBRuOW88ta2dxvcVR97dUc3Eny3kS399n3vDdPbUaOxgJ8qrQ0R+LyKfFpGrRORBh7LmVwLjlVJjlFLJwBcwQpSDKKWmA3/GUCaVIdvzlFIp5vNC4AwMRRcVVviq0z6UW55bA0CxDYUChmJrcCHKygpBPSWC78LCk5jAsSXZNDusWC3mvbsb6D8bPj3ZE1TGbrHXpq/KbV/OnS+vB+D+zxzfbfuo/HREYHNF/CpAf7inji/+5f3g69BmbBpNNERUKEqp582/68yw3W6PgZ5YRHzAzcAiYBPwvIhsUEr9UillRW39FsgEXugRHnwshinuY2Aphg8laoXiSUwgLz3JtQKRVgZ4f7ilUKxukPl9ZOtbFGYmU+1SkqdVLeCha/peRO6vb6PTH3At2dRqtzy2MLKPpiDVWKWU17mXj9LW6WdteQMAsyYWdds3Z9IQkhJVsKBnPLhr/vpurzv9AbYecj7yUXPk09cK5Xvm30uBy8I8BoyILBCRCSIyTkTuNbfdKSLzzefniciQnuHBIvKuiEwVkRPMv3+LVYYReemOXzzOGl/IuKKMiJ0ae5JjRlk5zYH6NjwJypZCKcpMocalmmJ7alrJTU9iWD8K9vozRgO41pp5+ZYqAM6fEr4MDcAtM4xVZXmde43PnlixGzBuOJJ6mN5y0pPw+oVnV+7jwzjUN2v3+llv9sPZdd/FvPrdMwG44ME3XT93OFlG3/oqU+5c6HpLB407RFQoInLQfPotEdkT+gC+FR/x3CcvI9nx1UFju4/hefYzz0flp7tSwv5Py4zeIz0vWuEoyEx2rfTJzqoWSgv6j9yaZrYUcMvc9O2nPwLgwimRi0AOzVB4EpSrd+gbDxgX8Ac/Py3s/q+ayZ/xqK921Z/eBeAH509AKRUsxQPwoJmMGg8O1Lcx6Y6FALR0+hlz2wJ26rYChx12nPLnh9l2kdOCDBZZqR7W729w9D2b2rxkpdoPQx5TmEFFY3uwGu9gkJueTJvX78pd8caDjUwuyep3nOVzcsME6QvpzDllWPi6ZgBJCYq8jGQeWbrDtbvkD/fUce6kYk4e0zvJE+Cuy4z8XrdbVENXQc5TTFmUUjz25RmAUVFgXbmz/xvh8AeE0+9/o9f2c3+3PC7fgcY5+vKhfFMptQ6Y2MN/sgsYsA/lk0JmsgdfQBw191Q2dVAURbFFqzyKFZXlBG2dhnKyqgH0hxVl9vV/OlumraHVS0OblzF9+C0srHL+BxucX6EcMpXUr66aSrKn7/soS6FtOuj8KqW2pZP99W0c24eCVUpxweQh5PVTtmeghF6sQ5XbBVOGcsnUEgDW7HPf7BbaNfX2i48NFgsFdytxa5ynr/+spzF8JfPp7juZISLXxkG2uHDpCcY/zlqHVilN7V6aO3yURBH+WpxljH3xo3JHZACoNRXE0Bx7iu1rZxn95q0iiU6x4aDxvR5T3LtbZE9SPImMzE9j2ZbKfsdGyzbThDWuqH/FdutFkwB3+tRYyurYENNSODJSPOyoanG1WKQVHv2TCyf2yjt5+IvTKchI5oUPnZuTkXh/lxHZt/L28/ja2WP51qxj2HXfxQD89KV12p9yGNGXD6VBRHaLyDWm36QNI5MgUyk1Km4SusxQ08ziVMhshXl3HU0+xQzzIh6pIvBA5MgN00c+HMXZqUwuyabT72z+g2VOtDoz9seZxxSxz4UIq22HDHv8hCH9m94uO8EopLnPBcf8f9cbrsmePWF6kmBe4N/Y7LxyBSPZ9IFFRgGM68Ik3yqlOHVcgWsBEqFy/GahIUdoEItSKrhqGnPbAq1UDhPsFIe8TCm1DdgFLAd2070EymFNpunrsEJKB4plrinJsRcyDIYiyUhOdDTB8oVVRlUby4xkh5KcVMfNTQcb2slITgwm7/VHcVYKtS2deB1WbFsPNVGYmUKejYi3kuxUkj0J7HYhUMIqGnr8iMh+HICbzz0GgO89u8ZxGcBYnWyrNJRsRkp4f9/EIVlUN3dGLKjpBFVthqKwzL6h/CYkR6fOpc6qPVlbXs/vX9vC6FtfZfStr/LVv3/Qzf+m6Rs7Tvl7gFOBrSIyBpiD0WP+iCA71bjQORUmWhFUKNFlfOdnJlPb4pyJxTJhTB9p34SVmeph08FG/A5W231hVTn5mcm2S3kUmnepTueibK1sZsKQ/s1uAAkJitL8dHY76NMC4258Z5WhpLJS+1awffXRcYJnPjDyXKaPyo04xlplP79yX8QxA2VlhXET9fure0e8jS7MCEa8Ldl0yDUZLJZuruTyh9/hj29sD25btqWKV9bqTp52saNQvCJSAyQopRJEZCkQPt7xMCQjxUN+RrJjvTh21bSgFBRnR9cBMT8jhVoH78Ia27yMLcogISH6mkxOBSi0e/00d/iYUNy/mcnCMkFur3QuZFRE2H6oyZa5y2JMYYbjYauWkz9cpeOeeBITOGt8IeDc6tnCHxCefM9QKI9eOyPiuGxz9X7HyxscPX8oL2w15nyk3+aW88YDULb2YNj9TuH1B7h+3sqw+77/3Me8rYMDbGFHodQrpTKBN4GnlFL/i1Hh94ihOCslmFU+UDYcaGRySXa/fVB6kp+e5OgKZW9tK8OiMLsBnDupGIAmhy5gVsKo5ZOww6ShWeaxzq0Oalo6aen0R9WV8pjiTPbUtDpqettdY6xOZtgMfPjMiUa3Bqfzciqbut6vuI/k29nmfABcqeSwx/w+LplaEtEkmpueTElOKsu3Vjl+/lC+9+zq4PN3bj2XzXdfyO77Lwn+Btf+7f1BDes/XLCjUK7AcMh/H1gI7MChTPlPCgWZydQ5VJyxvrXTdoZ8KCmeRNbvb3TM+Vhe18rowuja+lq1zVoc8ycZCiUa89/QnFSUgv31zl1ELcdyNMmmI/LS8QXE0UgvSzHYKRoKXRf7ykZno83eNC/ON5wxpk9TZIonkU9PHw7AKrNtspNYddu+PfuYPsdZEXEbDriTE9Pa6WPBugoANt99IcNz04IBMr+7+oTgON1Ns3/sFIdsERG/iPhE5AkR+aNpAjtiyEtPdsxmX9fa2W8ETzgWbjAm9NvbB760bvf6qWv1Bs1HdrGcs05FvFkX8v5KroSSlJhAZoqHjxxMsOySI5pQbuNifsjBi/l7O2tITUog12aAwhBTETsdafXaBsMfYTn+++LnV0wBnO9q6vMHuPXFdQD9+rZ+81nDOf/Kx+6YvZ4L8RGFi7T84PY5ALyx2X0/zuFOX4mNTUqpxpBHU+jfeArpNvkZzimU6qbOqCKrLE4yu0c6Ec1i+R9G2Sh3Ekqa+c/0gUN3owfq21EquhBqMNoJvL292rHV2qPLjWZVdot1QpcPrNJBc9Oq3XWcMqbAtl9rVH46yYkJbK109mLe2O5lRmmerRpvVtDKbxdt6WdkdKw3y89MyEsI20oglMLMFGZPLOL5VfscDx+uaurgF68YJW52/OrisGOKs1I5Z0IRf317l2uFS48U+spDyRKR7JBHVujfeArpNvlmPa+Bhge2dPho8/opiCJL3sIqY+51oA+GZVqx2gvbpdT0MThVfuVvb+9CBFu1xEL5ymmlgNG+2AmsTGy7ocvQFfa93SHH/N6aVmpaOqPKfk9KTCAjJZE/L4+ue2NfiAhbKpqCvio7pCcbNxpO+lH+aZbI/+YJ9v5Xzp1UTG1Lp6MrRoCT7l0MGObexD4U/ZdOGYUIXPLHtxw9/5GGrf90pdSZSqnrzeeFSqkx7ooVX6w7tYGuDqziigU27vx6Yl3snIjosez+0a6UctOTGVeUEfSlDJRYP4vlxF/jsM06mi6ERVkplBaks3afM3Z7K0nywuMiF6YMx6lmLxunGrCV17XR2O6zVbnAwmo7sM3Bgpn/NqtC5KXau9kYZ8rrZJ+Y0NXO4h+c08dIOMdsM3Cwod21dhcdPj8NbV5W7a6lucPHA4uMfJiF6ytcOZ8b2ElsvAuYC9xmbkoGnnRTqHjTpVAG9k9b02JdyKNfoVgXcWcUSmfMcgx1MLkxLSmRG86I/t5j6vAcslI9LN868Cxxq3TJ3AsnxSTHOodK8limkjGF9i/kAFefZDQ13XrImZXSItNXN3ticT8juzh+hJGr4lTzswbzxi0aH99xw41E0IdDckQGipXYeeelk/s1y6Z4EvmDWR3ajV41IsLEny3khF+8xmcfXcFxdy3i4aXGZ/3Gkx9y9aMrqDsMzG12bkWvwmiv+xEYrXeVUvbXy58gWltbmTdvXrdtU6ZMIT/PuOg9/e/5jE7vvkqZNm0a06ZNo7W1leeff77Xe86cOZPjjjuOhoYGnn/5v0AO7y59jT3vGYrhtNNOY+LEiVRXV1NWVtbr+LPPPpuxY8dSV11JAsKKlavJ2PN2cP+cOYZDcN++fSxZsqTX8RdeeCFDhw5l586dvPmm0cNi+aEMUhJSefapf3LppZdSWFjIli1bWLFiRa/jr7rqKnJycli/fj2rVq2iuTKLXa1Jwe/p6quvJj09nTVr1rBmTe+s7S996UskJSWxcuVKNmzoyleoqm2gzXtMMOLt3XffZevW7uXQk5KS+NKXvmTIvHw5u3btCu7LJpc1W3YDRpTN4sWLKS/vXlcqOzubT3/60wAsXLiQiorud3IFBQWMm2HceVbt2si83d3NFUOHDuXCCy8E4MUXX6SxsZH6+np2794NgMc7lP31fnZXt/DBG6/S2to9lHnMmDGcc47x/k899RReb/e5M2HCBE4//XQAXl78FpDJ0ldfZEWicWc8ZcoUTjrpJLxeL0899VTPr5Zp06YxcbRRKPGJ/7zGxrzuij507q1ZsyYot0W4ufffikzSE1NYVvZCcO5VVFSwcOHCXuefM2cOI0eOpL2+kvwkH797fStZ+7pymsPNvVAizb13a9KATL4/uxQ6yoNzryc9515xSh6r9tTxp789QXqiRJx7Fl/96leN80WYex2lxm+T17ybefOWd9ufnp7O1VdfDXSfe+mJBSz+YC3JeZXB3uyR5t5llxnBsK+88go1Nd2Vcejc+9e/X2T5vk6g+2V1VH56sMPoB7trmX736xyb2cHVwxsZO9b+3Au95lnz287c6+vqsxsTAAAgAElEQVS6Fwk7681OMdaGAqCUis7TexhgleNo8UWfBBhKo8/4OrM80ftBlFKkJgptgYHJANDkTSQzBhkAcpL8NPkS8A7QldMaMOzusZj/ANISA7T6B/5dWP+QBTG0qh+eYZz/P2v2D1iOOm8iaYkBUhOjcyqX5KSS4kmgzjvwOm9+gQ/r0+iIYY7lJhkTosOBtJx3ag1f3aQh0V1KLio2VhQbGqNfeYfjg121jMhLIz/Nvo9vXEYn6xpTaXfg/9Tinzs8vFJhKJObx9Ry18Qq7jw5ieU/nsWu+y7mK2O7biQ2Naew4FB0q9x4ovqLmlBK/QgYj9EX5T7gBuBpEXnIffGcZeTIkXL33Xf32t7sUzywvZCLips4JT92c8/y6nSWVmdwx8QqEmOYb7/dVkCLP4GfT+qexFVfX09ubuQSGT15eGcehcl+vjAienvzB3WpLDiUxfWj6ilNj92n9PGhTl6qG841wxuYmBX9Uv3fB7LY15bELeMGFnH2r/1ZrG9K5Sfjq0m3cTEP/a59AvdsKeLsghbOLRpYouXPNxeR7fHzg2Oi/zy/2VZApifAt8ZEDpawM0c+bkjhpYPZjEj1cuPo6PxTm5uSeXZ/Dv9TWsfItIGZZf+4I48hKX4+P6Ixqrnd4lP8dnshWR4/P4zhewzlzep03qjO4KTcNi4Zat+cuK/Nw9/25DEptZEvjB64L6WiPZFHdxtFMM8tbOHswvDzTAS2NBu/AcD3xtaQlxy9do/2WmJx/fXXfygiM/sbZycP5QHgX8C/gYnAnU4pE6XUhUqpLUqp7UqpW8PsT1FKPWfuf18pNTpk323m9i1KqU8NRI70RCFRCQ2+gd0FtvoVKQmBmJQJgNe83g1kdSAC9d5E8pJiy+rNTzaOq/NGF5nVky3txh1XbnJscqQnBmhzYIWyvslYmqQlRB9u6lGQ7fFTP8DVQbv5OdKiXJ1YtPoTqOzwMNCI2YPthoX7ulHRBzsMSfF1e4+BUOv1kBXD/MzwCENSfAx0VojAG9XG6ujkvOhyfEam+ShO8bGnM52Blryr60wIKpNZfSgTAKVgUlYnXzV/u//dWcCWpthW/z3xBeClA1k8XZ7N7tYkGrwJwTkbNSIS8QEkAov7GhPrw3zvHcBYDEf/x8DkHmO+BTxqPv8C8Jz5fLI5PgUYY75PYn/nnDBhgkTirF+/Id95+qOI++3w3Wc+krN+/UbMx//1rZ1SOrdMDtS3dtu+dOlS2+9R09whpXPL5G9v7YxJhtYOn5TOLZMHX98S0/EWx95eJqVzyyQQCMR0/B9e3yqlc8uk0+cfkBylc8vk7N/Y/016ftefe/Rd+ez/vTMgGd7dXi2lc8tkyaaKmI6/7cW1Ujq3TA7Wt0UcY2eOlM41fpNYCAQCcvK9r8vX/7EqpuMt/rlit5TOLZNfvrJBRKKb2yIijyzdJqVzy6S+pTNmGQ7Ut0rp3DI57s6FMc3Plz4ql9K5ZbJmb13MMoiIfPPJVVI6t0wu+sObUR1376sbg7/lE+/uiupY6/v2+vzy0JKtwffp+Zh610KZ+6+PZV9ti4iIAKvExnXdjslrPvBlEXG07oFS6jTg5yLyKfP1bQAicl/ImEXmmBVKKQ9QARQBt4aODR3X1znT09Pl5JNPDrvv4ORrUOJn6Cb7DqieVEz6LAFPKsPWxxYE15I/gaoJVzBs7TySW7vMXtEsUzvSizl4/HUUbfkPGXXbYpKjfNqNJLdUUrxtfkzHA+ydej2p7dUUb3slpuMbh0yndsx5jFz1CIm+2MxNgYQk9p58C7l7l5N74ANbx/T8rqvGXUR79ihGrv5zTDIA1I08i4bhp8b8WdqzRlAx5RqKt7xIet0OW3L3xJecSfmJ3ySppZLh656IWgaAqmMupS17FKM++lNMxwPsPvXHABRtm09GzZaoTTBt2SM5NPkLFG95ifS62CK+mgsmUT3+MkrW/YOUluiz3/2eNPbN+BbZB1aSv693MIId2jNLqDjuWhK8rYz88JGoV11NRVOoGWckYo56/0ESxJ4Zsr6+nvSScRw44YZu29OrN5G7fwWteePoyByGLyUXb0YRiJDauJctj37blsnLzvq1HVinlHodCDaIEJHv2voEkRkOhNbFLgdOiTRGRHxKqQagwNz+Xo9jh4c7iVLqJuAmMCI76uvDL/cDrXX4M4dE3G8Hr0pGtTbG/B7eBEOJNLT7SAp5D7/fb/s9vclGB8q2mv14G2P8LM01dHjSYv4cgiKQlov/0IaY36MzzYiKqesET4yfw59h5A501lXYlqPnd+1rOIS/cDJ1jc2oQGy+g4ZTTwWgqTq2MujS2AyTAzQk5tIZ4XP0N0c6hxj/Hknb3oj5N/HX7CVQeCx1TW0of/T+A0noutx07lyFV/xRzW0AaWiCSX4aPJG/i/5oHTYEfO20HthGm8RiX67Hc2gTjcNPQW1ciPJH7yOsn2lcPtNXPUFDQwyfo/4d0tp9tE25nPLJXyTr3UdQ0r8Z0ZuY2qVMAn7S1/2LpIr1KAnQCnBwBykYph9/5hA6S6bSWXysfbn6W8IA14V72Fn+9PO+nwP+GvL6y8BDPcZsAEaEvN6BoVAeAa4N2f434DP9nbMvk9ed/1knU+9aaHPhGJ7T71si339udczHb9jfIKVzy+TVtQe6bY/GLPD3tw2zWVVTe8xyWMveDm9s5qZ9tS1SOrdMnn5/T8wyfLCrRkrnlsmnHlwe83s8/IZhHlm1u8b2MT2/61c+3i+lc8tk/f76mGSwTIgz7n4tpuMtzn1gqXztiZUR9/c3R36zcJOUzi2T2uaOmGVYsPbAgH7XPdXGvPjVgo3BbdGavERELn/oLTnpntelsS02s9e5DyyV6x5/P6ZjLe5/+nUpnVsmd728Pupj39h8SErnlslN/4j8e9rlG/80zGan/mqxtHX6Io5bs7dOzvnNG8H/bcvkaBdsmrz69LwqpRKB88UoCtntYV9lRaQcGBnyegTQ8xYuOMY0eeUAtTaPjYqirBQa230DKlFd29IZc5gsdGW2D6SU/oGGdpI9CQOSY6qZRFYRY4KjFao7Morqvj2xWgYPpCihVX9qZJQlaEKxku+sZNFoWWnWRbv7iv57oPTFpKHZwR7wsfDIUsNUlhtF6ZeeTDTLtfx5eXizW3/87OX1AJwxrjBmGQBuOX8ClU0dfBxDFYM/LdvOjqoWThqdPyAZThpqBGrMe3d3VCWbKhvbuf7vRt+VX4d0pIyVR754Ip+dMYKDDe1MumMh68ob6PD5WbDuII3tXn7w/BpG3/oqVzzyTrBh3HWnlfKzS6JYdUSBHR/KIuAyEXE0TdNUEFsxOkDuB1YCXxSRDSFjvg1MFZFvKKW+AHxaRK5WSk0BngZOBoYBS4DxIn2v+SKFDQN8VJ/K/IqsmMPxOgPwq61FzClq5qyC2KrD+gXu3lLErMIWZoVEfERjZ35hfxYH2z18d1zs9bi2NifzdHkON5bWMSKGENE1DSn852A23xlbS0GMUV5ghNoCvcKo7fLwzjxa/AnMHW8/w7vnd13TmcBDOwu4sqSRaTnRm3nKKjJZVZ/Gj46pJtMTe1jQWzVpLKnK5Nbx1WFzWfqaI1b4M8T+XVr8cUcemZ4AN5RGfzG3fs+fTqgi2byVjSWM1Qrzv7C4mVPzo/tfu2dLIT5RfHtMLUUpsc/N+vp61viGsaw6gwkZHXxxZP/KPiDwS/N3GJHm5cZSZ0oLhb5vX3xlZD353ipXw4bt+FB2A++YzvlQH8rvo5YqBDF8IjcDizAivh4XkQ1KqV9iLK/mY5iy/qmU2o6xMvmCeewGpdTzwEaMZl/f7k+ZAAQCgV4ZrRkZGWRlZZGeYFw491bW0eHpmqSZmZlkZmbi9/upqur9z5iVlUVGRgYNHcY/ua+5ngpv18U8Ozub9PR0vF5vr2xZgJycHNLS0ujs7KS2tpZUlUdVYzsVPkNO68dvb28Pa2vOz88nOTmZtrY2Ghoa2NKUzxBPW/BzFhQUkJSURGtrK42NvSd9YWEhHo+HlpYWmpqM1UCbLw3IYVdVEyXDk0lMTKS5uZnm5t7x+sXFxSQkJNDU1ERLizE99rcXAdm01hygoGQIAA0NDbS1df/nV0oxZIixv76+nvb27iui6amKdR1GLau6ujo6Orpf0D0eD4WFxt1ubW0tnZ1d9zxeUVR3FnJOgaGYa2pqemUTJycnk59v3KlWV1fj8/nw+XxBOVJSUsjMNvYfamijoq17KZjU1NTg73Po0KFelXDT0tKo8xqrvebqg/T89qy5FwgEqKzsXWYmdO7RUgtksrOilvxE43uw5p7P56O5ubnX92fNvbo24wbpzLQDVFR0zcGec68nubm5pKamdpt7hXjY2pbHvoOHGFKQ123u9SR07tU1NJFAISekVFFbaTjCrd8udO6FUlRUFHbuiUASeWxqSubU/LZucy+UoUONumnW3Kv3J+OTIooSWwnUH4A+5l5iYiJFRcZFOtzcCwQCTC9qZ1l1BltbUth5oDp4DQHDX1tQYMxda+6tbS8I7r8kYzdgzB1r7oWSkpJCXp6xSq+qqjLmQAihc6+q8hBfz6nguabx1Ad6Z/B+IWsLuYmd0ATN5vyOZu6Fu+5Fwo5COWA+EuhZG2CAiMgCYEGPbXeGPG/H8LWEO/Ze4N5ozpeQkBCcZBZWCYIV2yt59q8rycgrZGhG14XHbumV+at2wZ6NjC7MZGhGVyav3dIrVvmL1BZFqycrKOecOXPYsWMH48aN67f0yrLlb+KrTyQ1JTl4fLSlVwDSvQnQDFulhIeuuSDq0itSkUlqh5+RJUP6LX8RqfQKwJDGbFYfUFxz7Zd5a9nSqEqvVHcmQoPiqvPO4Mrpw/stfxFaesX6Rx0xYgRz5szh93csJCkzn6H53S3EdkqvLFrpZ87IVIbSuyhkNOUvyue9BHshJbc4OD9DS6/8/e9/73Xnac29b/7jPaCG0QXpDM3sMnnZLb0SWvZnRHUyW6thT/Jovnb5ObZLr7zwxkoCDYox+akMzTG+i6uuuorVq1dTWFhoq/RKKN6GRPa0JfK5a65l49rVtkqvvHvAuHydXOhnRPGIPudepNIrFm1tbXzza1+hbv4G5r27m7VqDFcO7VKKPUuvrC1v4N16Q0HcPLaW40ZN6jX3QhkxYgTnnXceAM8//7ytsj+3lDQBTQQEJk0MLb3SO2LUrdIr0TjRs4BMu+M/iY++nPKbDzZK6dwyKfv4QMQxffEPM76+oiFyroAdwuUK2HVcVja2xxSbHkmObz35YUzHXv/3D+TMexYMWIa/vLlDSueWybry6B3i72yvktK5ZfLO9qqojgv3XZ9+3xK55dnogy0CgYAcd9dCueM/66I+tieWQ/v2l9aG3d/XHLHmVEuHd8BytHUaQQYPLdka1XGWDBv2N3TbHotTXkTk969tkdK5ZXLD3z+wNb6lw2vkngww8MbCkrvD6w9+tkhOces7K51bJpc//LYj54+VWL9vnHDKAyiljlNKrQbWAxuUUh+aPowjiuw0Y7HW2B5buZGD9W0kJSqKYqjwG8r0UdHbNy0sJ7rdFrN9MXFIFp0x9oc5UN9GfurAs9zHFRk1i97fFX2ZDattrhPfxf76Nl5aHX09r9qWTprafVH3pQnHkBxjXr2wqryfkb0ZW5jB7IlFpCcPPMvd6mj4wGtb+xkZQZYiZ0oBfnPWOACWbLZXkbrM7PY4szTPkfNbJHsS+PSJRkj2UxGqEP/kX2sBo/r3y98+w9Hzf9KwU1/jMeAHIlIqIqXAD4G/uCtW/MkyO9M1xthEaOuhZkbmpdvuxheJCyYb5oDWzuid4fut3ulRdCaMREluKjtibC5V0dhOgQMK5ewJRSQlKiqboo82q4iyf3tfWL1DWqJsLWBF1YwpHPhFNMWTyHfnjKfDFwiW5LdLXWsnw/MGPid6stJmZ08rCuqyE4aFbbEbC6lmawSl7P2v/OTfxkX9N589oZ+R0XPPlUYE391lG7vNERHhi395j/kfGwGoz3ytZ5rdkYcdhZIhIkutFyKyDDjiKg5nJCeSleKJuX93RWNbsOPhQCiwQodjCFN1UqFMGprNvtpW/FEWLGrr9FPf6iXPAYWSmKAozEyJ6bs41NhOZorHkWZhN509FjB6wkfDB+bKasqwnAHLAMZKA7o6ctrB5w9Q1+olP8OZCr0AS35o2O432wxjtsLITxtb0M/I6Dh7QiEisLqfRmzvbK8GYNLQrGA7BScJXflNuWsRje1eFm88xLV/e593zR4yd146mfFDDsuuH1FhR6HsVErdoZQabT5+Buzq96jDDKUULZ0+/rMmtnSWqqYORyarlYvy1rbqqI89UN9GWlLigHINLEoL0vH6hYMN0SnYVXuMi2hWsjPlvbNSPTS3R79aW1ve4Mj3AATNmP/zRG/HcV88+PpWkhMT+m3eZBerq+fP52+0fcwxt/8XgAaHOj5CV2tp6867PxasM8xNZ40fWP5JT04wG3997R99/y7feuojAC6YEl23zGh46yezg8+P//lr3PiPVbyz3VAm864/iRvOPKKa3EbEjkK5AaN+1ovmoxC43k2hBouAGH2zpZ/cnJ60dfqpbu50xLximQR++tK6qI+tauqgODslqla3kRhmrnKi7d64u9oI3xydPbBqxRZZqUnBlsZ26fD5+XBPHeV1sa02ezJ7kv3uhhYVDe10+gMMy3VGmQDMGG3Y/+2uokMT7n5wwUTH5EhKTGBGaR67qnuH6obj/V21TBqaNaAE03BYfYxaO/10+sL7+xpavTSYZuxvnDPW0fOHMjI/nQ9+OoerpnevALXgu2cxK4rumIc7dsrX14nId0XkRPNxi4jEnjX3CebkMUbOQbRteLdVNuEPCMeWZA9cBjODd/bE/hOVelLT0jGgDPlQhpsXwmhNgAcb2vEkKEY5pFDGF2eydn9DVKY3yyE/K4bvMBJfPGVUVCue1XuNf5FbL4q+9XAkslOTyEtPYmd1i62KDrXmquTuK6YEVzdOMefYYqqbO/v9XxER1u1vYNrI2INN+uKOSycDcNlDb4fd/9AbRoHU8ycPcSQooS+Ks1N58PPT2HXfxWy79yJ23Xcxk4cN/JpwOGEnyut1pVRuyOs8M3v+iOOak41qLlVN0d0RWzZ+J0wbnsQEpo3MxRdDs4Wa5k4KBhhlZlGSY6xQ9kepUCpN01+CA6skMPqZd/oCQTu8HdaWG0l2155S6ogMYPgv6lu9wd7w/fHhHkOhTBrq7AXlrPGGklyzr/8sa2seO+k/sbDK6pTX9f27LNpQQX2r15GbrXCca64etxxqYm159+9kT00Lf33bsM7/xoEyJ3ZRSpGUmOCIpeBww85tZKGIBH8pc3VyRK7hirMMhVAZpUIpNy+6hQ794xZmJsdUO6qmpTPogxkoGSkectOTOFgfncnr5TX7I5ofYsGyu7+2oaKfkV08uNgIaS1w6LsAGGFeQO2u2OrbvBRmpjDagQivUH52qVGDyY5DfK4Z2TSpxHlncKF54/L7fsKHv/Gk4b8occiP1JMxhRn84fPTALj84a5+9yLCBQ8ayZbnTx4SNI9p3MWOQgkopUZZL5RSpZj95Y80LKd6tCuUO/5jFL0rzHJm0hZkpFAZRSQPQE1zB1VNHY5EeFkMy0mLyuTl9Qfw+mVAxS17MjI/nYKMZHbX2LPXA0HzyvRRzuUcWHlKr5oO5v7YXtnM+GLne38XZaaQl57Euv39K5T15pixDis1gBlmPkdfeVsfhOQPnRuDH8ouV4b4LV5aXc6q3bWMuW0BHeaNzX2fnurauTXdsaNQbgfeVkr9Uyn1T+BN4DZ3xRoc8s27GLtmDQvLb+GUjXZoTio1LZ1BZ6IdLCe+U3H+YNzh10YRHbT1kFF6wkm/ARg5MQeiWCmt39/A6eOcDVHNNvOU/m9Z/5V2RYT1+xuC+StOopRiRF46//6o7wTHvWYOzJxJxa6YXpI9CVwxbRhbDzVHDGJ5abUh49tzZ+NJdManFomnbzRyPL7/3Md89tGuEkM/umBCcDWlcR87TvmFwInAc+ZjhogckT4U66IRbeLYmMIMR2Ps05MNpfDCqn39jOwiM8WQ/XMzRvYz0j5N7T5W7623XT1gZ5WxinDSGQ4wuiCDndX2kiw7fQE2VzQNuDx5T0ZEkRj4cXkDvoCQnuKccg9l3X7DR9TXKvat7Ub9ppvPPcYVGcBoMVDb0snnHu1dI67TF+CZD/YxdXhO0FzoJlYEXCh/u24mN5873vVza7qwe9twOjDLfJzqljCDTbIngbSkRBqjzHuob/OSl+FcFM34IcadrXXhsEO7z8/ognRyHMq9gK4EuiWb7LVJtXJWnDS7gWGK3Fdrz/S2ucIw86QkOXtHnJuezBdPGdX/QOB3rxl9WAba9yMSD3zOyPaOlAciItz+kmGGdSu6Cggq7VV7ugd9tnX6uemfRm7I1TNHuHb+UFI8iey672JeuflM5t98Brvvv4Q5xw6Jy7k1XdiJ8rof+B5GqfiNwPeUUvf1fdThS3aaJ+ryK/WtneSkOef0O+MY40I0IYrM2oP1bcHcEaewnJ12EwsP1LeTleIJlrFxCqvEx8L1/TvmF28yajuNL3beEV1nmkLL1kZO6Gvu8AWTUp02u1lYK8B7Xt0UNpzaUr7jijJcjTQ6tiSLrFTDzBtaHufzj61g2RZjhfTpE+OjUMAwB04dkcPxI9xTopq+sXMbdzFG18bHReRx4ELgEnfFGjxy0pKoi8JvICJGqREHVwbJiQl4ElRUtaMO1LcHQ32dYppZqLK+1Z6CPVDfRomDiXwWXzl1NICtrP0/LjHyDtxwAn/+JMOc+IPnPo44JjR01S2/QWFmStDRXh9mrt5hdkb8+eXu1nBVSvH0jYbB4uR7lzDvnV0s2XQoGLYNRrSg5ujB7owPVfnOFCb6hFKclRpV2HBzhw9fQBwr8wHGP2p6ciKtnfY6ynn9ASqb2oPJiE6R4kkkLSnRdnDAgYY2x5UawFVmNddfvNJ/yZGsVA8lOakkDrBIZzhmTSwmPyOZcX042y3/9NddzMqGLt/ILc+tIdBjlbJ8q7E6cDLKLRLHDe/KL/n5Kxu7ladZ+qNZrp9f88nCjkK5D1itlJqnlHoC+NDcdkRSnJ0SzLS2w3s7DXPM8FxnHY8ZKR7bK5Rd1S0EBMdNXgBtXn8wOawvOn0BtlY0M2GI85FNSTbv9Ns6/TS1+5g63L17ns+fNJJth5rwRijt/88VewB6leBwGsus+Na26mBlZYB3dxjmtumjch0pjNkfSimWhVEca39+gSNVljWHF3aivJ7BcMRbtbxOM7cdkQzJTqWyqd12Pa8K0wxz/AhnL2IHG9p54UN7vS82Hmg0ZXDPdtzzLrgnu2ta6PQHHKus25OvmxV/I13Iocshn5fuXhLbMUWZ+AISMXN/oZmAme2wH6knoYEPf1q2HYB2r58v/uV9AL55zjhXzx/K6MKMYKAAGNWI3f78mk8mdpzyS0TkoIjMF5GXRaRCKdW7F20UKKXyzZIu28y/vdbmSqlpSqkVSqkNSqm1SqnPh+ybp5TapZRaYz6mDUSeUIZkpeD1C3U2/QbWOCcKQ8aKVcBxdKHz4Zk/vdjIKenPr/TcSiPE2Y3cCyBYWLCujxyhQ+bK8tpTnSu50hOrQdSOyt5hzKFK143VYiihK8En39vLsn1eptzVFc3vZmXdcHx2xgh2338Ju++/JNgYTXP0EVGhKKVSlVL5QKFZvyvffIwGhg3wvLcCS0RkPLDEfN2TVuArIjIFIxDgD6E1xYAfi8g089G72XmMWIrBbs+JutZOMlM8JHucdcDeaJa7trNSqmvtJDUpwZXid1YOQX9+pXnv7gZwrWZTmpmwGakrHsDeWiMPZpQDfWkiYSnM+/67ude+NaZD/nMz3I9s8iQmsPv+rtiYeRs6gxFfPzx/guvn12jC0ddV8OsY/pJJwEfm8w+Bl4FHBnjeK4AnzOdPAFf2HCAiW0Vkm/n8AFCJUUbfVYqzjazaCpsKpb7V66hD3mL9ASNSZnNFU79jH3tzJ+1e5+pnhWKVo+lLwTa0efEHhOmjcl1xhkNXxNmKHZGbXO2paSU3PcnxyrqhWL6LXdUtwcoAFveUGUEDX4+juSncjcxNLgcEaDSRUP3dASulviMiDzl6UqXqRSS0gnGdiEQMSVFKnYyheKaISEApNQ84DejAXOGISNhbaKXUTcBNAEVFRTOef/75PmWraw/w/WVtnFqSyDdO6N+Mdf8HbXT44a7TnDVxLN7j5clNnXzrhBQmZ7WTmRnejBAQ4YZFhj1/3oXOO0Fr2gL8cHkbX52SzKyR4S/UOxv8/HJFO9+elsJJQ41VUnNzc0SZY+XHy1sZnZPAt6f1/l221Pq574N2jslN4Genxv5b2JF7Q7Wf365q5/xSD1861lC4/oDwP68Zv8Nj56eTnBifSrO+gPDkxk6WlRsBHD89JZUJee5k6LuBG/MkHhxtcs+ePftDEZnZ70AR6fMBfCXcw8Zxi4H1YR5XAPU9xtb18T4lwBbg1B7bFJCCoWju7E8eEWHChAnSH35/QErnlskX/ryi37EiIqf+arF8/7nVtsZGw8H6NimdWyZPvrdbli5dGnFcTXOHlM4tkz8v3+64DCIiDW2dUjq3TErnlkUc89JH5VI6t0y2VjQGt/Ulc6xc/L9vSuncMmnp8PbaZ8n4h9e3DugcduT2+vzB87V7fVLR0BZ8/bvXtgzo/LHQ1O6VGx5ZKNVN7XE/90BxY57Eg6NNbmCV2LjG2jG6nxTyPBWYg2EC+0c/iuq8SPuUUoeUUiUiclApVYJhzgo3Lht4FfiZiLwX8t5WydcOpdTfgR/Z+By2SEhQnD2hyFbuhc8f4GBDuytRRYWZyShlOJqH92HBsboZupH/AZAR4pcpr2sNW5dpZ3ULSrnruyhRJoYAABJ2SURBVICu0vGvbTjUrcLszqouB3loXoRbeBITOGdCEcu3VvH717by0ur9wX1XTBuoezF6MlM8fHlyimO9cDSaWLETNvydkMfXgOnAQK+g84HrzOfXYfhluqGUSgZeAv4hIi/02Fdi/lUY/pf1A5SnG3npSX1GE1l8bDpho+wYbAtPYgIiXZnfkbBa7rrVbyIxQfHjT000z9U7VLahzcsfl2xDxEiEdJMnzYqytzzXPQbj+yGvZ8ep3eqfvnQiAH9+c2cwYOGGM8boCCfNUU0soUmtwEDDSO4HzldKbQPON1+jlJqplPqrOeZq4Gzgq2HCg59SSq0D1mH0uL9ngPJ0Iy892ZZC2XjQcMpeOd3du9JOf2SNtcmUYayLF7JPmSGo4RzzlpPcqpDsJqG1zUJ71nxslvr4zIkjSHApKKAnGSmeXgmUd142OS7n1mg+qdjJQ3lFKTXffLyK4c/4z0BOKiI1IjJHRMabf2vN7atE5Ebz+ZMikiRdocHB8GAROVdEporIcSJyrYjYq21uk4qGdpo6fNQ09x0qazXWcrq6rsUfr5kOQGVrZIWytdJQKE7WEutJkWlK+eELvWtYWaG6i39wjmvntwjNmL9vwSbavf5uYdW3X3Ks6zKE8sp3zmSiqeR+F5LYp9EcrdjxoTwQ8tyH4Qy/xh1xPhnMKM1j4YYK9tS29mmXLi1IZ09N32MGQqmZzFfZGjkkeEtFE2ceU+hqVVmrW2E4dlW3kJ+R7Hoin8WXThnFU+/v5cXV+3lx9f5gczPoapAWTxbectZR2TtcowmHHR/KcqABo8LwU8DdwCaX5RpUTjPLjvfXCtgfEC6ZWuKaHKMLjDDgfU3hFcr2yma2Vzazo8rRBVovQi+Yizd29UZp6fCxYkdNXGs29VyFWO2GX7n5zLjJEIpWJhpNF31lyk9QSt2plNoEPAzsw8hbmS0iD8dNwkGg2Ezm66sjntcfYH99W5+VZwdKTnoSQ7NTI5q8lm0xguNuPMv9RDYr+9rqTQIw5a5F7K5ppdTl6K5Q0pM9/OOGk3ttn+pwLTWNRhM9fa1QNmOECF8mImeKkdxor576YU5BZgoJCnaYLW3DUdnUgYh70VUWQ3JSaegIr1B21xjyXXuqvU6CA+Fbs41y6X9+cydAt8ZOpfnxrSp79oSibmVHPrrj/LieX6PRhKcvhfIZoAJYqpT6i1JqDob/5IgnMUERkK76VOGwqgwPdVuhZKVQ3R7e5LW7upUTRua6Hq4Lxndimbam3LmQ1zd2dU88c7w7nQn7Y82d5/PebXMGxXei0Wh6E1GhiMhLIvJ5jFpey4DvA0OUUv+nlLogTvINOu3e8IuyigYrodBdhTIyP51DLRJWjl3VLYyJo7npITPqrKXTzzee/AiAX39mKjNK8+MmQyi56cmuK3SNRmMfO075FhF5SkQuBUYAawhfHfiIJFLGvNWOtiTb3eim6aNyEQwHfCjtXj8HGtoYHUeH+HHDc7jouO5l0c8c73q9To1Gc5gQVWKjiNSKyJ9F5Fy3BPqkYOWANEZQKPe8agS69RVS6wSThhqlRLb0qDpctvYgIu71H4lEz/IqQwexD4xGo/lk4X6P0MOUpnZDkby0ej8/uXBSt32h0V9uh42ONi/gf1q2nc+E9Nm4b4Gh0I4f7l6XxnDccMYYRhdkcPXMkXj9AdfK1Ws0msMPZ7tCHUFcMNkw7WSm9ta5fzed9YWZ7juDPWZ2+I6qlm5Z4ceWZMelIGNPhmSncs3Jo0hMUKQmHT5l0jUajftohRKBwsxkUpMSONTQOxel3myHe+nx8akse8pQ48L96jqjyHLA7Gl+bpwKIWo0Go0dtEKJgFKKdm+AJ1bs6bXPKul+x6XxKQY4rdg4381Pr+bZD/Zy96sb2VvbSlO7Ly7n12g0GjtoH4oNNhxoYMqwrkzs+jYvw3JS4+Y/CD3LrS+uCz4//ZjByf/QaDSacOgVSh9cZTZx6tmTpL61kxwXmmpFYubQxLCNm245b6BdBDQajcY5tELpg19/5niAYIlyMFomr9lX71rJ+nB4EhS/v3pat21LfzQrbufXaDQaO2iTVx8kewx9+8c3tvODC4yuhc98sI/q5k7GFcW3flVigmLjLz/FwYZ23RVQo9F8ItErFJtsOtgIwFKzwu/kYe73Lu9JerJHKxONRvOJRa9Q+uHS40soW3uQR5fv4OU1B4LbL4tTyLBGo9EcLgzKCkUpla+Uel0ptc38mxdhnD+kn/z8kO1jlFLvm8c/p5RyzUP+gNnaNVSZAHHrXa7RaDSHC4Nl8roVWCIi44ElRC422RbST/7ykO2/Bh40j68D/sctQXU2uEaj0dhjsBTKFcAT5vMngCvtHqiM4lnnAv+K5fhYuPeq47q9fu6mU908nUaj0RyWqND6UHE7qVL1IpIb8rpORHqZvZRSPoxy+T7gfhH5j1KqEHhPRI4xx4wE/isix/U83tx/E3ATQFFR0Yznn38+annLmwL87J02PjXaw5XHJJPmia+5q7m5mczMw8sZfzjKDFrueKPlji+xyj179uwPRWRmvwNFxJUHsBhYH+ZxBVDfY2xdhPcYZv4dC+wGxgFFwPaQMSOBdXZkmjBhgsTKqt014vX5Yz5+ICxdunRQzjsQDkeZRbTc8UbLHV9ilRtYJTausa5FeYnIeZH2KaUOKaVKROSgUqoEqIzwHgfMvzuVUsuA6cC/gVyllEdEfBhNvw6EO95JBqsroUaj0RwuDJYPZT5wnfn8OuDlngOUUnlKqRTzeSFwBrDR1JZLgc/2dbxGo9Fo4stgKZT7gfOVUtuA883XKKVmKqX+ao45FlillPoYQ4HcLyIbzX1zgR8opbYDBcDf4iq9RqPRaHoxKImNIlIDzAmzfRVwo/n8XWBqhON3Aie7KaNGo9FookOXXtFoNBqNI2iFotFoNBpH0ApFo9FoNI6gFYpGo9FoHEErFI1Go9E4glYoGo1Go3EErVA0Go1G4whaoWg0Go3GEbRC0Wg0Go0jaIWi0Wg0GkfQCkWj0Wg0jqAVikaj0WgcQSsUjUaj0TiCVigajUajcQStUDQajUbjCFqhaDQajcYRtELRaDQajSNohaLRaDQaRxgUhaKUyldKva6U2mb+zQszZrZSak3Io10pdaW5b55SalfIvmnx/xQajUajCWWwVii3AktEZDywxHzdDRFZKiLTRGQacC7QCrwWMuTH1n4RWRMXqTUajUYTkcFSKFcAT5jPnwCu7Gf8Z4H/ikirq1JpNBqNJmYGS6EMEZGDAObf4n7GfwF4pse2e5VSa5VSDyqlUtwQUqPRaDT2USLizhsrtRgYGmbX7cATIpIbMrZORHr5Ucx9JcBaYJiIeEO2VQDJwGPADhH5ZYTjbwJuAigqKprx/PPPx/6hBonm5mYyMzMHW4yoOBxlBi13vNFyx5dY5Z49e/aHIjKz34EiEvcHsAUoMZ+XAFv6GPs94LE+9s8Cyuycd8KECXI4snTp0sEWIWoOR5lFtNzxRssdX2KVG1glNq6xg2Xymg9cZz6/Dni5j7HX0MPcZa5QUEopDP/Lehdk1Gg0Gk0UDJZCuR84Xym1DTjffI1SaqZS6q/WIKXUaGAksLzH8U8ppdYB64BC4J44yKzRaDSaPvAMxklFpAaYE2b7KuDGkNe7geFhxp3rpnwajUajiR6dKa/RaDQaR9AKRaPRaDSOoBWKRqPRaBxBKxSNRqPROIJWKBqNRqNxBK1QNBqNRuMIWqFoNJr/b+/uYuWqyjCO/x/7hRECrQWsBbQ1TbRRUxrAEgkxSkppYiqmar2xUSJGJdEYIyVNFC+8wESaqASsAfEr0goam/hRi6CEC4oIbWlTSw8UY6GhMRSUmyL09WK9p52ezMw5p92z9x7P80smZ8+alemzV/c57+yPWdusEi4oZmZWCRcUMzOrhAuKmZlVwgXFzMwq4YJiZmaVcEExM7NKuKCYmVklXFDMzKwSLihmZlYJFxQzM6uEC4qZmVXCBcXMzCrRSEGR9DFJeyQdk3RJn34rJO2TNCJpXUf7AknbJe2XtEnSzHqSm5lZL03toewGPgo81KuDpGnAbcA1wGLgk5IW58u3ABsiYhFwBLhusHHNzGw8jRSUiNgbEfvG6XYZMBIRz0TEq8A9wCpJAj4I3Jv9fgx8ZHBpzcxsIqY3HaCP+cA/O54fBN4HvBl4KSJe62if3+tNJF0PXJ9Pj0raPYCsgzYX+FfTISZpGDODc9fNuet1qrnfNpFOAysoku4H3tLlpfUR8ZuJvEWXtujT3lVEbAQ2ZqbHIqLnOZu2Gsbcw5gZnLtuzl2vQeceWEGJiKtO8y0OAhd2PL8AeJ5SXc+RND33UkbbzcysQW2+bPivwKK8omsmsAbYEhEBPAiszn5rgYns8ZiZ2QA1ddnwtZIOApcDv5W0NdvfKul3ALn3cQOwFdgLbI6IPfkWNwJfkTRCOady5wT/6Y0VrkadhjH3MGYG566bc9droLlVPvCbmZmdnjYf8jIzsyHigmJmZpWYEgWl1xQubSHpWUlPStoh6bFsmyNpW04vs03S7GyXpO/muuyStLTGnHdJOtz5XZ5TySlpbfbfL2ltQ7lvlvRcjvkOSSs7Xrspc++TdHVHe23bkaQLJT0oaW9OU/SlbG/1ePfJ3fbxPkPSo5J2Zu5vZvsCdZnmSdKsfD6Sr799vPWpOffdkg50jPeSbB/sdhIR/9cPYBrwNLAQmAnsBBY3nWtMxmeBuWPavg2sy+V1wC25vBL4PeX7OMuA7TXmvBJYCuw+1ZzAHOCZ/Dk7l2c3kPtm4Ktd+i7ObWQWsCC3nWl1b0fAPGBpLp8FPJXZWj3efXK3fbwFnJnLM4DtOY6bgTXZfgfw+Vz+AnBHLq8BNvVbnwZy3w2s7tJ/oNvJVNhD6TqFS8OZJmIVZVoZOHl6mVXAT6J4hPKdnHl1BIqIh4AXTzPn1cC2iHgxIo4A24AVDeTuZRVwT0QcjYgDwAhlG6p1O4qIQxHxeC7/h3Kl43xaPt59cvfSlvGOiHgln87IR9B7mqfO/4d7gQ9JUp/1qTt3LwPdTqZCQek2hUu/DbwJAfxR0t9UpooBOD8iDkH5JQXOy/a2rc9kc7Yp/w2523/X6KEjWpg7D6dcTPn0OTTjPSY3tHy8JU2TtAM4TPmD+jS9p3k6ni9ff5nyFYbGc0fE6Hh/K8d7g6RZY3OPyVdJ7qlQUCY1VUtD3h8RSykzK39R0pV9+g7D+kBFU+cM0O3AO4AlwCHgO9neqtySzgTuA74cEf/u17VLW5tyt368I+L1iFhCmX3jMuBdfTK0NrekdwM3Ae8ELqUcxroxuw8091QoKL2mcGmNiHg+fx4Gfk3ZmF8YPZSVPw9n97atz2RztiJ/RLyQv4jHgB9y4rBEa3JLmkH5o/zziPhVNrd+vLvlHobxHhURLwF/ppxjOEfS6BRVnRmO58vXz6YcVm1D7hV56DEi4ijwI2oa76lQULpO4dJwpuMkvUnSWaPLwHLK/WK2UKaVgZOnl9kCfCqv1lgGvDx6CKQhk825FVguaXYe9liebbUac97pWsqYQ8m9Jq/iWQAsAh6l5u0oj8ffCeyNiFs7Xmr1ePfKPQTjfa6kc3L5jcBVlPM/vaZ56vx/WA08EOXsdq/1qTP33zs+dIhy3qdzvAe3nUz2LP4wPihXNjxFOSa6vuk8Y7ItpFwVshPYM5qPcjz2T8D+/DknTlzVcVuuy5PAJTVm/QXlcMV/KZ9orjuVnMBnKCcrR4BPN5T7p5lrV/6Szevovz5z7wOuaWI7Aq6gHHLYBezIx8q2j3ef3G0f7/cCT2S+3cDXs30hpSCMAL8EZmX7Gfl8JF9fON761Jz7gRzv3cDPOHEl2EC3E0+9YmZmlZgKh7zMzKwGLihmZlYJFxQzM6uEC4qZmVXCBcXMzCrhgmJWA0mvjN/LbLi5oJiZWSVcUMwaIunDeS+NJyTdL+n8bD9X5V4nj0v6gaR/SJrbdF6z8bigmDXnYWBZRFxMmZ79a9n+DcpUHkspc7td1FA+s0mZPn4XMxuQC4BNOe/STOBAtl9Bme+KiPiDpCMN5TObFO+hmDXne8D3I+I9wOco80NB96nEzVrPBcWsOWcDz+Vy5z28HwY+DiBpOeWWrGat58khzWog6Rgn31/iVsqMrxsoReUR4NKI+ICk8ygzJM8G/gJ8AlgQ5d4WZq3lgmLWMnm71tcj4jVJlwO3R7kjn1mr+aS8WftcBGyW9AbgVeCzDecxmxDvoZiZWSV8Ut7MzCrhgmJmZpVwQTEzs0q4oJiZWSVcUMzMrBL/A38kiJVqZE2KAAAAAElFTkSuQmCC\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#Uma outra forma de plotar a autocorrelaçao\n", + "plot_acf(series, lags=31)\n", + "mtl.pyplot.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Lag: 29\n", + "Coefficients: [ 5.57543506e-01 5.88595221e-01 -9.08257090e-02 4.82615092e-02\n", + " 4.00650265e-02 3.93020055e-02 2.59463738e-02 4.46675960e-02\n", + " 1.27681498e-02 3.74362239e-02 -8.11700276e-04 4.79081949e-03\n", + " 1.84731397e-02 2.68908418e-02 5.75906178e-04 2.48096415e-02\n", + " 7.40316579e-03 9.91622149e-03 3.41599123e-02 -9.11961877e-03\n", + " 2.42127561e-02 1.87870751e-02 1.21841870e-02 -1.85534575e-02\n", + " -1.77162867e-03 1.67319894e-02 1.97615668e-02 9.83245087e-03\n", + " 6.22710723e-03 -1.37732255e-03]\n", + "predicted=11.871275, expected=12.900000\n", + "predicted=13.053794, expected=14.600000\n", + "predicted=13.532591, expected=14.000000\n", + "predicted=13.243126, expected=13.600000\n", + "predicted=13.091438, expected=13.500000\n", + "predicted=13.146989, expected=15.700000\n", + "predicted=13.176153, expected=13.000000\n", + "Test MSE: 1.502\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# divide dataset\n", + "X = series.values\n", + "train, test = X[1:len(X)-7], X[len(X)-7:]\n", + "\n", + "# treina autoregressão\n", + "model = \n", + "model_fit = \n", + "print('Lag: %s' % model_fit.k_ar)\n", + "print('Coefficients: %s' % model_fit.params)\n", + "\n", + "# faz predições\n", + "predictions = \n", + "\n", + "\n", + "for i in range(len(predictions)):\n", + " print('predicted=%f, expected=%f' % (predictions[i], test[i]))\n", + "error = mean_squared_error(test, predictions)\n", + "print('Test MSE: %.3f' % error)\n", + "\n", + "# plota resultados\n", + "mtl.pyplot.plot(test)\n", + "mtl.pyplot.plot(predictions, color='red')\n", + "mtl.pyplot.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/3. Modelos regressivos/Exercicio_Autoregressao/[Solu\303\247\303\243o] Prevendo Temperatura.ipynb" "b/3. Modelos regressivos/Exercicio_Autoregressao/[Solu\303\247\303\243o] Prevendo Temperatura.ipynb" new file mode 100644 index 0000000..4f0e75f --- /dev/null +++ "b/3. Modelos regressivos/Exercicio_Autoregressao/[Solu\303\247\303\243o] Prevendo Temperatura.ipynb" @@ -0,0 +1,457 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Prevendo Temperatura\n", + "\n", + "\n", + "Vamos investigar a autocorrelação de uma série temporal univariada para então desenvolver um modelo autoregressivo e usa-lo para fazer predições.\n", + "\n", + "\n", + "Vamos usar o arquivo \"daily-min-temperatures.csv\" que possui a temperatura mínima de 10 anos (1981-1990) da cidade de Melbourne, Australia.\n", + "\n", + "As unidades estão em graus Celsius e existem 3.650 observações. A fonte dos dados é creditada como o Australian Bureau of Meteorology.\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "#Vamos importar as bibliotecas que vamos utilizar\n", + "\n", + "import pandas as pd\n", + "import matplotlib as mtl\n", + "from statsmodels.graphics.tsaplots import plot_acf\n", + "from sklearn.metrics import mean_squared_error\n", + "from statsmodels.tsa.ar_model import AR" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Temp\n", + "Date \n", + "1981-01-01 20.7\n", + "1981-01-02 17.9\n", + "1981-01-03 18.8\n", + "1981-01-04 14.6\n", + "1981-01-05 15.8\n" + ] + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#Primeiramente vamos importar os dados e armazena-los em um pandas dataframe\n", + "\n", + "series = pd.read_csv('daily-min-temperatures.csv', header=0, index_col=0)\n", + "\n", + "#Vamos plotar as 5 primeiras linhas para verificar o dataser carregado\n", + "print(series.head())\n", + "\n", + "#E Então plotar em um gráfico de linhas para analisa-lo\n", + "series.plot()\n", + "mtl.pyplot.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Verificação rápida de autocorrelação\n", + "\n", + "Há uma verificação visual rápida que podemos fazer para checar se há uma autocorrelação em nosso conjunto de dados de séries temporais.\n", + "\n", + "Podemos plotar a observação do periodo anterior (t-1) com a observação do próximo periodo (t + 1) em um gráfico de dispersão.\n", + "\n", + "Isso pode ser feito manualmente, primeiro criando uma versão lag do conjunto de dados de séries temporais e usando uma função de plotagem de dispersão incorporada na biblioteca do Pandas.\n", + "\n", + "Mas existe uma maneira mais fácil.\n", + "\n", + "O Pandas fornece um gráfico embutido para fazer exatamente isso, chamado de função lag_plot ().\n", + "\n", + "Abaixo está um exemplo de criação de um gráfico de lag do conjunto de dados de Temperaturas Diárias Mínimas." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "pd.plotting.lag_plot(series)\n", + "mtl.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A execução acima plota os dados de temperatura (t) no eixo x em relação à temperatura no dia anterior (t-1) no eixo y.\n", + "\n", + "Podemos ver uma grande bola de observações ao longo de uma linha diagonal do gráfico. Isso mostra claramente um relacionamento ou alguma correlação.\n", + "\n", + "Esse processo pode ser repetido para qualquer outra observação para trás , como se quiséssemos revisar a correlação nos últimos 7 dias ou com o mesmo dia do mês passado ou do ano passado.\n", + "\n", + "Outra verificação rápida que podemos fazer é calcular diretamente a correlação entre a observação e a variável lag.\n", + "\n", + "Podemos usar um teste estatístico como o coeficiente de correlação de Pearson. Isso produz um número para resumir a correlação entre duas variáveis entre -1 (correlação negativa) e +1 (correlação positiva) com valores pequenos próximos a zero indicando baixa correlação e valores altos acima de 0,5 ou abaixo de -0,5 mostrando alta correlação.\n", + "\n", + "A correlação pode ser calculada facilmente usando a função corr () no DataFrame do conjunto de dados com lag.\n", + "\n", + "O exemplo abaixo cria uma versão defasada do conjunto de dados de Temperaturas Diárias Mínimas e calcula uma matriz de correlação de cada coluna com outras colunas, incluindo ela própria." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " t-1 t+1\n", + "t-1 1.00000 0.77487\n", + "t+1 0.77487 1.00000\n" + ] + } + ], + "source": [ + "values = pd.DataFrame(series.values)\n", + "dataframe = pd.concat([values.shift(1), values], axis=1)\n", + "dataframe.columns = ['t-1', 't+1']\n", + "result = dataframe.corr()\n", + "print(result)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Esta é uma boa confirmação para o gráfico acima pois mostra uma forte correlação positiva (0,77) entre a observação e o valor de lag - 1.\n", + "\n", + "Isso é bom para verificações pontuais, mas trabalhoso se quisermos verificar um grande número de variáveis de lag em nossa série temporal.\n", + "\n", + "A seguir, veremos uma versão facilitada dessa abordagem.\n", + "\n", + "\n", + "# Gráficos de autocorrelação\n", + "\n", + "Podemos traçar o coeficiente de correlação para cada variável de lag.\n", + "\n", + "Isso pode rapidamente dar uma idéia de quais variáveis de lag podem ser boas candidatas para uso em um modelo preditivo e como a relação entre a observação e seus valores históricos mudam com o tempo.\n", + "\n", + "Poderíamos calcular manualmente os valores de correlação para cada variável de lag e plotagem. Felizmente, o Pandas fornece um gráfico interno chamado função autocorrelation_plot ().\n", + "\n", + "O gráfico fornece o número de atraso ao longo do eixo x e o valor do coeficiente de correlação entre -1 e 1 no eixo y. O gráfico também inclui linhas sólidas e tracejadas que indicam o intervalo de confiança de 95% e 99% para os valores de correlação. Os valores de correlação acima dessas linhas são mais significativos que os abaixo da linha, fornecendo um limite ou ponto de corte para a seleção de valores de lag mais relevantes." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "pd.plotting.autocorrelation_plot(series)\n", + "mtl.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A execução do exemplo acima mostra o balanço na correlação positiva e negativa, à medida que os valores de temperatura mudam nas estações de verão e inverno a cada ano anterior.\n", + "\n", + "\n", + "# Gráfico de Autocorrelação de Pandas\n", + "\n", + "A biblioteca statsmodels também fornece uma versão do gráfico na função plot_acf () como um gráfico de linhas." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plot_acf(series, lags=31)\n", + "mtl.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Neste exemplo, limitamos as variáveis de lag avaliadas em 31 para facilitar a leitura.\n", + "\n", + "# Gráfico de Autocorrelação de Statsmodels\n", + "\n", + "\n", + "Agora que sabemos como revisar a autocorrelação em nossas séries temporais, vejamos a modelagem de autoregressão.\n", + "\n", + "Antes de fazer isso, vamos estabelecer um desempenho de linha de base.\n", + "\n", + "# Modelo de persistência\n", + "\n", + "Digamos que queremos desenvolver um modelo para prever os últimos 7 dias de temperaturas mínimas no conjunto de dados, com todas as observações anteriores.\n", + "\n", + "O modelo mais simples que poderíamos usar para fazer previsões seria persistir na última observação. Podemos chamar isso de modelo de persistência e fornece uma linha de base de desempenho para o problema que podemos usar para comparação com um modelo de autoregressão.\n", + "\n", + "Podemos desenvolver um equipamento de teste para o problema dividindo as observações em conjuntos de treinamento e teste, com apenas as últimas 7 observações no conjunto de dados atribuídas ao conjunto de testes como dados \"não vistos\" que desejamos prever.\n", + "\n", + "As previsões são feitas usando um modelo de validação direta, para que possamos persistir nas observações mais recentes do dia seguinte. Isso significa que não estamos fazendo uma previsão de 7 dias, mas 7 previsões de 1 dia." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Test MSE: 3.423\n" + ] + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# cria lagged dataset\n", + "values = pd.DataFrame(series.values)\n", + "dataframe = pd.concat([values.shift(1), values], axis=1)\n", + "dataframe.columns = ['t-1', 't+1']\n", + "\n", + "# divide em treino and test \n", + "X = dataframe.values\n", + "train, test = X[1:len(X)-7], X[len(X)-7:]\n", + "train_X, train_y = train[:,0], train[:,1]\n", + "test_X, test_y = test[:,0], test[:,1]\n", + " \n", + "# cria modelo persistencia\n", + "def model_persistence(x):\n", + " return x\n", + " \n", + "# walk-forward validation\n", + "predictions = list()\n", + "for x in test_X:\n", + " yhat = model_persistence(x)\n", + " predictions.append(yhat)\n", + "test_score = mean_squared_error(test_y, predictions)\n", + "print('Test MSE: %.3f' % test_score)\n", + "\n", + "# plota predição vs esperado\n", + "mtl.pyplot.plot(test_y)\n", + "mtl.pyplot.plot(predictions, color='red')\n", + "mtl.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A execução do exemplo imprime o erro quadrático médio (MSE).\n", + "\n", + "O valor fornece um desempenho de linha de base para o problema.Os valores esperados para os próximos 7 dias são plotados (azul) em comparação com as previsões do modelo (vermelho).\n", + "\n", + "# Modelo de autoregressão\n", + "\n", + "Um modelo de regressão automática é um modelo de regressão linear que usa variáveis lag como variáveis de entrada.\n", + "\n", + "Poderíamos calcular o modelo de regressão linear manualmente usando a classe LinearRegession no scikit-learn e especificar manualmente as variáveis de entrada de lag a serem usadas.\n", + "\n", + "Como alternativa, a biblioteca statsmodels fornece um modelo de regressão automática que seleciona automaticamente um valor de lag apropriado usando testes estatísticos e treina um modelo de regressão linear. É fornecido na classe AR.\n", + "\n", + "Podemos usar esse modelo criando primeiro o modelo AR () e depois chamando fit () para treiná-lo em nosso conjunto de dados. Isso retorna um objeto ARResult.\n", + "\n", + "Uma vez ajustado, podemos usar o modelo para fazer uma previsão chamando a função predict () para várias observações no futuro. Isso cria uma previsão de 7 dias, que é diferente do exemplo de persistência acima.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Lag: 29\n", + "Coefficients: [ 5.57543506e-01 5.88595221e-01 -9.08257090e-02 4.82615092e-02\n", + " 4.00650265e-02 3.93020055e-02 2.59463738e-02 4.46675960e-02\n", + " 1.27681498e-02 3.74362239e-02 -8.11700276e-04 4.79081949e-03\n", + " 1.84731397e-02 2.68908418e-02 5.75906178e-04 2.48096415e-02\n", + " 7.40316579e-03 9.91622149e-03 3.41599123e-02 -9.11961877e-03\n", + " 2.42127561e-02 1.87870751e-02 1.21841870e-02 -1.85534575e-02\n", + " -1.77162867e-03 1.67319894e-02 1.97615668e-02 9.83245087e-03\n", + " 6.22710723e-03 -1.37732255e-03]\n", + "predicted=11.871275, expected=12.900000\n", + "predicted=13.053794, expected=14.600000\n", + "predicted=13.532591, expected=14.000000\n", + "predicted=13.243126, expected=13.600000\n", + "predicted=13.091438, expected=13.500000\n", + "predicted=13.146989, expected=15.700000\n", + "predicted=13.176153, expected=13.000000\n", + "Test MSE: 1.502\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# divide dataset\n", + "X = series.values\n", + "train, test = X[1:len(X)-7], X[len(X)-7:]\n", + "\n", + "# treina autoregressão\n", + "model = AR(train)\n", + "model_fit = model.fit()\n", + "print('Lag: %s' % model_fit.k_ar)\n", + "print('Coefficients: %s' % model_fit.params)\n", + "\n", + "# faz predições\n", + "predictions = model_fit.predict(start=len(train), end=len(train)+len(test)-1, dynamic=False)\n", + "for i in range(len(predictions)):\n", + " print('predicted=%f, expected=%f' % (predictions[i], test[i]))\n", + "error = mean_squared_error(test, predictions)\n", + "print('Test MSE: %.3f' % error)\n", + "\n", + "# plota resultados\n", + "mtl.pyplot.plot(test)\n", + "mtl.pyplot.plot(predictions, color='red')\n", + "mtl.pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A execução do exemplo imprime o primeiro lag ideal escolhido e a lista de coeficientes no modelo de regressão linear treinado.\n", + "\n", + "Podemos ver que um modelo de 29 lag foi escolhido e treinado. Isso é interessante, dado o quão próximo esse atraso está do número médio de dias em um mês.\n", + "\n", + "A previsão de 7 dias é impressa e o erro quadrático médio da previsão é sumarizado.\n", + "\n", + "É feito um gráfico dos valores esperados (azul) versus os valores previstos (vermelho).\n", + "\n", + "A previsão parece muito boa (cerca de 1 grau Celsius por dia), com um grande desvio no dia 5.\n", + "\n", + "Previsões do modelo de AR fixo\n", + "Previsões do modelo de AR fixo\n", + "\n", + "Neste exercício, aprendemos como fazer previsões de autoregressão para dados de séries temporais usando Python.\n", + "\n", + "Você aprendeu especificamente:\n", + "\n", + "Sobre autocorrelação e autoregressão e como eles podem ser usados para entender melhor os dados de séries temporais.\n", + "Como explorar a autocorrelação em uma série temporal usando gráficos e testes estatísticos.\n", + "Como treinar um modelo de regressão automática em Python e usá-lo para fazer previsões de curto prazo e contínuas." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/3. Modelos regressivos/Exercicio_Autoregressao/daily-min-temperatures.csv b/3. Modelos regressivos/Exercicio_Autoregressao/daily-min-temperatures.csv new file mode 100644 index 0000000..9e37e69 --- /dev/null +++ b/3. Modelos regressivos/Exercicio_Autoregressao/daily-min-temperatures.csv @@ -0,0 +1,3651 @@ +"Date","Temp" +"1981-01-01",20.7 +"1981-01-02",17.9 +"1981-01-03",18.8 +"1981-01-04",14.6 +"1981-01-05",15.8 +"1981-01-06",15.8 +"1981-01-07",15.8 +"1981-01-08",17.4 +"1981-01-09",21.8 +"1981-01-10",20.0 +"1981-01-11",16.2 +"1981-01-12",13.3 +"1981-01-13",16.7 +"1981-01-14",21.5 +"1981-01-15",25.0 +"1981-01-16",20.7 +"1981-01-17",20.6 +"1981-01-18",24.8 +"1981-01-19",17.7 +"1981-01-20",15.5 +"1981-01-21",18.2 +"1981-01-22",12.1 +"1981-01-23",14.4 +"1981-01-24",16.0 +"1981-01-25",16.5 +"1981-01-26",18.7 +"1981-01-27",19.4 +"1981-01-28",17.2 +"1981-01-29",15.5 +"1981-01-30",15.1 +"1981-01-31",15.4 +"1981-02-01",15.3 +"1981-02-02",18.8 +"1981-02-03",21.9 +"1981-02-04",19.9 +"1981-02-05",16.6 +"1981-02-06",16.8 +"1981-02-07",14.6 +"1981-02-08",17.1 +"1981-02-09",25.0 +"1981-02-10",15.0 +"1981-02-11",13.7 +"1981-02-12",13.9 +"1981-02-13",18.3 +"1981-02-14",22.0 +"1981-02-15",22.1 +"1981-02-16",21.2 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Modelos regressivos/Exercicio_Regressao/.ipynb_checkpoints/Regress\303\243o-Exerc\303\255cio-checkpoint.ipynb" "b/3. Modelos regressivos/Exercicio_Regressao/.ipynb_checkpoints/Regress\303\243o-Exerc\303\255cio-checkpoint.ipynb" new file mode 100644 index 0000000..0d991d4 --- /dev/null +++ "b/3. Modelos regressivos/Exercicio_Regressao/.ipynb_checkpoints/Regress\303\243o-Exerc\303\255cio-checkpoint.ipynb" @@ -0,0 +1,509 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Execício Regressão linear\n", + "\n", + "- Treine uma Regressão linear usando a biblioteca sklearn e o dataset day.csv\n", + "- Calcule os erros utilizando MSE, MAE e R²\n", + "- Com base nesse resultado, responda: O modelo está bem acurado? \n", + "- Responda: Qual variável contribui mais para esse modelo? E qual contribui menos?\n", + "- Retire a variável que contribui menos e treine novamente a regressão. O modelo ficou melhor?" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd \n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.linear_model import LinearRegression\n", + "from sklearn.metrics import r2_score, mean_squared_error, mean_absolute_error" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_csv('day.csv')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- season : estações (1:primavera, 2:verão, 3:outono, 4:inverno)\n", + "- yr : ano (0: 2011, 1:2012)\n", + "- mnth : mês ( 1 to 12)\n", + "- hr : hora (0 to 23)\n", + "- holiday : feriado\n", + "- weekday : dia da semana\n", + "- workingday : dia útil\n", + "- cnt : contagem de bicicletas alugadas no dia (desfecho)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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"outputs": [], + "source": [ + "X_treino, X_teste, y_treino, y_teste = train_test_split(df.drop(columns='cnt'), df['cnt'], test_size=0.3)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,\n", + " normalize=False)" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lr = LinearRegression()\n", + "lr.fit(X_treino, y_treino)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "predito = lr.predict(X_teste)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([2344.37994089, 5552.04551956, 3069.24158597, 6221.11907543,\n", + " 6651.03534274])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "predito[:5]" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R²: 0.50751691531315\n" + ] + } + ], + "source": [ + "print('R²: ', lr.score(X_teste, y_teste))" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MSE: 1738789.1667719518\n" + ] + } + ], + "source": [ + "print('MSE: ', mean_squared_error(y_teste, predito))" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MAE: 1095.0153055355827\n" + ] + } + ], + "source": [ + "print('MAE: ', mean_absolute_error(y_teste, predito))" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 855.60601825, 2248.63014859, -61.82601379, -815.67116546,\n", + " 54.7336682 , 108.41291539])" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lr.coef_" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "season : 855.6060182490698\n", + "yr : 2248.6301485913264\n", + "mnth : -61.82601378972231\n", + "holiday : -815.6711654631983\n", + "weekday : 54.73366820182173\n", + "workingday : 108.41291538734858\n" + ] + } + ], + "source": [ + "for i,coef in enumerate(lr.coef_):\n", + " print(df.columns[i],' : ', coef)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1449.2793666335833" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lr.intercept_" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "X_treino, X_teste, y_treino, y_teste = train_test_split(df.drop(columns=['cnt','weekday']), df['cnt'], test_size=0.3)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,\n", + " normalize=False)" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lr = LinearRegression()\n", + "lr.fit(X_treino, y_treino)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "predito = lr.predict(X_teste)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R²: 0.5287166294031452\n" + ] + } + ], + "source": [ + "print('R²: ', lr.score(X_teste, y_teste))" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MSE: 1866548.107287827\n" + ] + } + ], + "source": [ + "print('MSE: ', mean_squared_error(y_teste, predito))" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MAE: 1125.6664714291146\n" + ] + } + ], + "source": [ + "print('MAE: ', mean_absolute_error(y_teste, predito))" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "season : 907.8131080507219\n", + "yr : 2168.494289658153\n", + "mnth : -87.9001222832203\n", + "holiday : -891.0322296982831\n", + "weekday : -22.95639621269676\n" + ] + } + ], + "source": [ + "for i,coef in enumerate(lr.coef_):\n", + " print(df.columns[i],' : ', coef)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/3. Modelos regressivos/Exercicio_Regressao/.ipynb_checkpoints/Regress\303\243o-checkpoint.ipynb" "b/3. Modelos regressivos/Exercicio_Regressao/.ipynb_checkpoints/Regress\303\243o-checkpoint.ipynb" new file mode 100644 index 0000000..6b4fea6 --- /dev/null +++ "b/3. Modelos regressivos/Exercicio_Regressao/.ipynb_checkpoints/Regress\303\243o-checkpoint.ipynb" @@ -0,0 +1,423 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd \n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.linear_model import LinearRegression\n", + "from sklearn.metrics import r2_score, mean_squared_error, mean_absolute_error" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_csv('winequality-red.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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fixed acidityvolatile aciditycitric acidresidual sugarchloridesfree sulfur dioxidetotal sulfur dioxidedensitypHsulphatesalcoholquality
07.40.700.001.90.07611.034.00.99783.510.569.45.5
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" + ], + "text/plain": [ + " fixed acidity volatile acidity citric acid residual sugar chlorides \\\n", + "0 7.4 0.70 0.00 1.9 0.076 \n", + "1 7.8 0.88 0.00 2.6 0.098 \n", + "2 7.8 0.76 0.04 2.3 0.092 \n", + "3 11.2 0.28 0.56 1.9 0.075 \n", + "4 7.4 0.70 0.00 1.9 0.076 \n", + "\n", + " free sulfur dioxide total sulfur dioxide density pH sulphates \\\n", + "0 11.0 34.0 0.9978 3.51 0.56 \n", + "1 25.0 67.0 0.9968 3.20 0.68 \n", + "2 15.0 54.0 0.9970 3.26 0.65 \n", + "3 17.0 60.0 0.9980 3.16 0.58 \n", + "4 11.0 34.0 0.9978 3.51 0.56 \n", + "\n", + " alcohol quality \n", + "0 9.4 5.5 \n", + "1 9.8 5.5 \n", + "2 9.8 5.5 \n", + "3 9.8 7.0 \n", + "4 9.4 5.5 " + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 1599 entries, 0 to 1598\n", + "Data columns (total 12 columns):\n", + "fixed acidity 1599 non-null float64\n", + "volatile acidity 1599 non-null float64\n", + "citric acid 1599 non-null float64\n", + "residual sugar 1599 non-null float64\n", + "chlorides 1599 non-null float64\n", + "free sulfur dioxide 1599 non-null float64\n", + "total sulfur dioxide 1599 non-null float64\n", + "density 1599 non-null float64\n", + "pH 1599 non-null float64\n", + "sulphates 1599 non-null float64\n", + "alcohol 1599 non-null float64\n", + "quality 1599 non-null float64\n", + "dtypes: float64(12)\n", + "memory usage: 150.0 KB\n" + ] + } + ], + "source": [ + "df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "#separando os dados em 4 dataframes diferentes(X: variáveis independentes, y: variável resposta)\n", + "#com 30% dos dados sendo usados para teste.\n", + "X_treino, X_teste, y_treino, y_teste = train_test_split(df.drop(columns='quality'), df['quality'], test_size=0.3)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,\n", + " normalize=False)" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lr = LinearRegression() #Criando a regressão\n", + "lr.fit(X_treino, y_treino) #Ajustando/treinando o modelo" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "predito = lr.predict(X_teste) #predito é um vetor com todos os valores preditos pelo modelo" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([6.82354046, 7.22776382, 6.21457404, 5.91348643, 5.79182465])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "predito[:5] #mostrando as predições das 5 primeiras observações do dataset X_teste" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R²: 0.36442757009897475\n" + ] + } + ], + "source": [ + "print('R²: ', lr.score(X_teste, y_teste))" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MSE: 0.5530264674857078\n" + ] + } + ], + "source": [ + "print('MSE: ', mean_squared_error(y_teste, predito))" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MAE: 0.5999073163548215\n" + ] + } + ], + "source": [ + "print('MAE: ', mean_absolute_error(y_teste, predito))" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 4.02859333e-02, -1.19442941e+00, -3.05910775e-01, 1.20540871e-02,\n", + " -2.10100780e+00, 6.95028284e-03, -4.21156726e-03, -2.22864992e+01,\n", + " -4.11180424e-01, 1.06313525e+00, 3.28951918e-01])" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lr.coef_ #coeficientes de cada variável independente" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "fixed acidity : 0.040285933319629846\n", + "volatile acidity : -1.1944294141122032\n", + "citric acid : -0.3059107754728927\n", + "residual sugar : 0.012054087057890225\n", + "chlorides : -2.1010077965174654\n", + "free sulfur dioxide : 0.006950282844835953\n", + "total sulfur dioxide : -0.004211567256740656\n", + "density : -22.286499161426104\n", + "pH : -0.4111804241892592\n", + "sulphates : 1.0631352529534328\n", + "alcohol : 0.32895191814165825\n" + ] + } + ], + "source": [ + "for i,coef in enumerate(lr.coef_):\n", + " print(df.columns[i],' : ', coef)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "26.408817550439913" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lr.intercept_" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/3. Modelos regressivos/Exercicio_Regressao/Regress\303\243o-Exerc\303\255cio.ipynb" "b/3. Modelos regressivos/Exercicio_Regressao/Regress\303\243o-Exerc\303\255cio.ipynb" new file mode 100644 index 0000000..0d991d4 --- /dev/null +++ "b/3. Modelos regressivos/Exercicio_Regressao/Regress\303\243o-Exerc\303\255cio.ipynb" @@ -0,0 +1,509 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Execício Regressão linear\n", + "\n", + "- Treine uma Regressão linear usando a biblioteca sklearn e o dataset day.csv\n", + "- Calcule os erros utilizando MSE, MAE e R²\n", + "- Com base nesse resultado, responda: O modelo está bem acurado? \n", + "- Responda: Qual variável contribui mais para esse modelo? E qual contribui menos?\n", + "- Retire a variável que contribui menos e treine novamente a regressão. O modelo ficou melhor?" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd \n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.linear_model import LinearRegression\n", + "from sklearn.metrics import r2_score, mean_squared_error, mean_absolute_error" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_csv('day.csv')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- season : estações (1:primavera, 2:verão, 3:outono, 4:inverno)\n", + "- yr : ano (0: 2011, 1:2012)\n", + "- mnth : mês ( 1 to 12)\n", + "- hr : hora (0 to 23)\n", + "- holiday : feriado\n", + "- weekday : dia da semana\n", + "- workingday : dia útil\n", + "- cnt : contagem de bicicletas alugadas no dia (desfecho)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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"outputs": [], + "source": [ + "X_treino, X_teste, y_treino, y_teste = train_test_split(df.drop(columns='cnt'), df['cnt'], test_size=0.3)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,\n", + " normalize=False)" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lr = LinearRegression()\n", + "lr.fit(X_treino, y_treino)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "predito = lr.predict(X_teste)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([2344.37994089, 5552.04551956, 3069.24158597, 6221.11907543,\n", + " 6651.03534274])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "predito[:5]" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R²: 0.50751691531315\n" + ] + } + ], + "source": [ + "print('R²: ', lr.score(X_teste, y_teste))" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MSE: 1738789.1667719518\n" + ] + } + ], + "source": [ + "print('MSE: ', mean_squared_error(y_teste, predito))" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MAE: 1095.0153055355827\n" + ] + } + ], + "source": [ + "print('MAE: ', mean_absolute_error(y_teste, predito))" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 855.60601825, 2248.63014859, -61.82601379, -815.67116546,\n", + " 54.7336682 , 108.41291539])" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lr.coef_" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "season : 855.6060182490698\n", + "yr : 2248.6301485913264\n", + "mnth : -61.82601378972231\n", + "holiday : -815.6711654631983\n", + "weekday : 54.73366820182173\n", + "workingday : 108.41291538734858\n" + ] + } + ], + "source": [ + "for i,coef in enumerate(lr.coef_):\n", + " print(df.columns[i],' : ', coef)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1449.2793666335833" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lr.intercept_" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "X_treino, X_teste, y_treino, y_teste = train_test_split(df.drop(columns=['cnt','weekday']), df['cnt'], test_size=0.3)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,\n", + " normalize=False)" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lr = LinearRegression()\n", + "lr.fit(X_treino, y_treino)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "predito = lr.predict(X_teste)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R²: 0.5287166294031452\n" + ] + } + ], + "source": [ + "print('R²: ', lr.score(X_teste, y_teste))" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MSE: 1866548.107287827\n" + ] + } + ], + "source": [ + "print('MSE: ', mean_squared_error(y_teste, predito))" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MAE: 1125.6664714291146\n" + ] + } + ], + "source": [ + "print('MAE: ', mean_absolute_error(y_teste, predito))" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "season : 907.8131080507219\n", + "yr : 2168.494289658153\n", + "mnth : -87.9001222832203\n", + "holiday : -891.0322296982831\n", + "weekday : -22.95639621269676\n" + ] + } + ], + "source": [ + "for i,coef in enumerate(lr.coef_):\n", + " print(df.columns[i],' : ', coef)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/3. Modelos regressivos/Exercicio_Regressao/Regress\303\243o.ipynb" "b/3. Modelos regressivos/Exercicio_Regressao/Regress\303\243o.ipynb" new file mode 100644 index 0000000..6b4fea6 --- /dev/null +++ "b/3. Modelos regressivos/Exercicio_Regressao/Regress\303\243o.ipynb" @@ -0,0 +1,423 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd \n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.linear_model import LinearRegression\n", + "from sklearn.metrics import r2_score, mean_squared_error, mean_absolute_error" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_csv('winequality-red.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " fixed acidity volatile acidity citric acid residual sugar chlorides \\\n", + "0 7.4 0.70 0.00 1.9 0.076 \n", + "1 7.8 0.88 0.00 2.6 0.098 \n", + "2 7.8 0.76 0.04 2.3 0.092 \n", + "3 11.2 0.28 0.56 1.9 0.075 \n", + "4 7.4 0.70 0.00 1.9 0.076 \n", + "\n", + " free sulfur dioxide total sulfur dioxide density pH sulphates \\\n", + "0 11.0 34.0 0.9978 3.51 0.56 \n", + "1 25.0 67.0 0.9968 3.20 0.68 \n", + "2 15.0 54.0 0.9970 3.26 0.65 \n", + "3 17.0 60.0 0.9980 3.16 0.58 \n", + "4 11.0 34.0 0.9978 3.51 0.56 \n", + "\n", + " alcohol quality \n", + "0 9.4 5.5 \n", + "1 9.8 5.5 \n", + "2 9.8 5.5 \n", + "3 9.8 7.0 \n", + "4 9.4 5.5 " + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 1599 entries, 0 to 1598\n", + "Data columns (total 12 columns):\n", + "fixed acidity 1599 non-null float64\n", + "volatile acidity 1599 non-null float64\n", + "citric acid 1599 non-null float64\n", + "residual sugar 1599 non-null float64\n", + "chlorides 1599 non-null float64\n", + "free sulfur dioxide 1599 non-null float64\n", + "total sulfur dioxide 1599 non-null float64\n", + "density 1599 non-null float64\n", + "pH 1599 non-null float64\n", + "sulphates 1599 non-null float64\n", + "alcohol 1599 non-null float64\n", + "quality 1599 non-null float64\n", + "dtypes: float64(12)\n", + "memory usage: 150.0 KB\n" + ] + } + ], + "source": [ + "df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "#separando os dados em 4 dataframes diferentes(X: variáveis independentes, y: variável resposta)\n", + "#com 30% dos dados sendo usados para teste.\n", + "X_treino, X_teste, y_treino, y_teste = train_test_split(df.drop(columns='quality'), df['quality'], test_size=0.3)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,\n", + " normalize=False)" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lr = LinearRegression() #Criando a regressão\n", + "lr.fit(X_treino, y_treino) #Ajustando/treinando o modelo" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "predito = lr.predict(X_teste) #predito é um vetor com todos os valores preditos pelo modelo" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([6.82354046, 7.22776382, 6.21457404, 5.91348643, 5.79182465])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "predito[:5] #mostrando as predições das 5 primeiras observações do dataset X_teste" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R²: 0.36442757009897475\n" + ] + } + ], + "source": [ + "print('R²: ', lr.score(X_teste, y_teste))" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MSE: 0.5530264674857078\n" + ] + } + ], + "source": [ + "print('MSE: ', mean_squared_error(y_teste, predito))" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MAE: 0.5999073163548215\n" + ] + } + ], + "source": [ + "print('MAE: ', mean_absolute_error(y_teste, predito))" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 4.02859333e-02, -1.19442941e+00, -3.05910775e-01, 1.20540871e-02,\n", + " -2.10100780e+00, 6.95028284e-03, -4.21156726e-03, -2.22864992e+01,\n", + " -4.11180424e-01, 1.06313525e+00, 3.28951918e-01])" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lr.coef_ #coeficientes de cada variável independente" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "fixed acidity : 0.040285933319629846\n", + "volatile acidity : -1.1944294141122032\n", + "citric acid : -0.3059107754728927\n", + "residual sugar : 0.012054087057890225\n", + "chlorides : -2.1010077965174654\n", + "free sulfur dioxide : 0.006950282844835953\n", + "total sulfur dioxide : -0.004211567256740656\n", + "density : -22.286499161426104\n", + "pH : -0.4111804241892592\n", + "sulphates : 1.0631352529534328\n", + "alcohol : 0.32895191814165825\n" + ] + } + ], + "source": [ + "for i,coef in enumerate(lr.coef_):\n", + " print(df.columns[i],' : ', coef)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "26.408817550439913" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lr.intercept_" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/3. Modelos regressivos/Exercicio_Regressao/Regulariza\303\247\303\243o-Exerc\303\255cio.ipynb" "b/3. Modelos regressivos/Exercicio_Regressao/Regulariza\303\247\303\243o-Exerc\303\255cio.ipynb" new file mode 100644 index 0000000..07b35f9 --- /dev/null +++ "b/3. Modelos regressivos/Exercicio_Regressao/Regulariza\303\247\303\243o-Exerc\303\255cio.ipynb" @@ -0,0 +1,789 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Execício Regularizações\n", + "\n", + "- Utilizando o dataset winequality (apenas com as 250 primeiras observações), crie uma regressão linear e meça os erros beseando-se na predição dos dados de treino e depois de teste.\n", + "- Esse modelo está super ajustado(overfitting)? \n", + "- Treino o modelo agora com as regularizações. \n", + "- Mostre o R^2 de todas as opções e avalie qual a melhor escolha de modelo.\n", + "- Mude o valor da penalização dos modelos para saber se acontece uma melhora." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd \n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.linear_model import LinearRegression, Lasso, Ridge, ElasticNet\n", + "from sklearn.metrics import r2_score, mean_squared_error, mean_absolute_error" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_csv('winequality-red.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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fixed acidityvolatile aciditycitric acidresidual sugarchloridesfree sulfur dioxidetotal sulfur dioxidedensitypHsulphatesalcoholquality
07.40.700.001.90.07611.034.00.99783.510.569.45.5
17.80.880.002.60.09825.067.00.99683.200.689.85.5
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" + ], + "text/plain": [ + " fixed acidity volatile acidity citric acid residual sugar chlorides \\\n", + "0 7.4 0.70 0.00 1.9 0.076 \n", + "1 7.8 0.88 0.00 2.6 0.098 \n", + "2 7.8 0.76 0.04 2.3 0.092 \n", + "3 11.2 0.28 0.56 1.9 0.075 \n", + "4 7.4 0.70 0.00 1.9 0.076 \n", + "\n", + " free sulfur dioxide total sulfur dioxide density pH sulphates \\\n", + "0 11.0 34.0 0.9978 3.51 0.56 \n", + "1 25.0 67.0 0.9968 3.20 0.68 \n", + "2 15.0 54.0 0.9970 3.26 0.65 \n", + "3 17.0 60.0 0.9980 3.16 0.58 \n", + "4 11.0 34.0 0.9978 3.51 0.56 \n", + "\n", + " alcohol quality \n", + "0 9.4 5.5 \n", + "1 9.8 5.5 \n", + "2 9.8 5.5 \n", + "3 9.8 7.0 \n", + "4 9.4 5.5 " + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 1599 entries, 0 to 1598\n", + "Data columns (total 12 columns):\n", + "fixed acidity 1599 non-null float64\n", + "volatile acidity 1599 non-null float64\n", + "citric acid 1599 non-null float64\n", + "residual sugar 1599 non-null float64\n", + "chlorides 1599 non-null float64\n", + "free sulfur dioxide 1599 non-null float64\n", + "total sulfur dioxide 1599 non-null float64\n", + "density 1599 non-null float64\n", + "pH 1599 non-null float64\n", + "sulphates 1599 non-null float64\n", + "alcohol 1599 non-null float64\n", + "quality 1599 non-null float64\n", + "dtypes: float64(12)\n", + "memory usage: 150.0 KB\n" + ] + } + ], + "source": [ + "df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "X_treino, X_teste, y_treino, y_teste = train_test_split(df[:250].drop(columns='quality'), df['quality'][:250], test_size=0.3)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,\n", + " normalize=False)" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lr = LinearRegression()\n", + "lr.fit(X_treino, y_treino)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "predito = lr.predict(X_teste)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R²: 0.24660293822988266\n" + ] + } + ], + "source": [ + "print('R²: ', lr.score(X_teste, y_teste))" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R² treino: 0.2360911841200337\n" + ] + } + ], + "source": [ + "print('R² treino: ', lr.score(X_treino, y_treino))" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MSE: 0.5954234264856048\n" + ] + } + ], + "source": [ + "print('MSE: ', mean_squared_error(y_teste, predito))" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MSE: 0.4626541094089626\n" + ] + } + ], + "source": [ + "predi_treino = lr.predict(X_treino)\n", + "print('MSE: ', mean_squared_error(y_treino, predi_treino))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Como o R² de treino é bem melhor que o de teste e que o MSE de treino é bem menor que o de teste o modelo está super ajustado (overfitting)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Ridge(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=None,\n", + " normalize=False, random_state=None, solver='auto', tol=0.001)" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "l1 = Ridge()\n", + "l1.fit(X_treino, y_treino)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "predito = l1.predict(X_teste)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R²: 0.2517303294510842\n" + ] + } + ], + "source": [ + "print('R²: ', l1.score(X_teste, y_teste))" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R² treino: 0.21781142249851548\n" + ] + } + ], + "source": [ + "print('R² treino: ', l1.score(X_treino, y_treino))" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MSE: 0.591371155771027\n" + ] + } + ], + "source": [ + "print('MSE: ', mean_squared_error(y_teste, predito))" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MSE: 0.47372507319077156\n" + ] + } + ], + "source": [ + "predi_treino = l1.predict(X_treino)\n", + "print('MSE: ', mean_squared_error(y_treino, predi_treino))" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "fixed acidity : 0.18518799466758878\n", + "volatile acidity : -0.8895761686884909\n", + "citric acid : -0.4319317466420524\n", + "residual sugar : -0.0047527832266144885\n", + "chlorides : 0.046972783206248044\n", + "free sulfur dioxide : 0.01343026899416854\n", + "total sulfur dioxide : -0.007453535373321475\n", + "density : -0.004588667826377633\n", + "pH : 0.437830182430155\n", + "sulphates : 0.17551893470679236\n", + "alcohol : 0.15770253095363854\n" + ] + } + ], + "source": [ + "for i,coef in enumerate(l1.coef_):\n", + " print(df.columns[i],' : ', coef)" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Lasso(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=1000,\n", + " normalize=False, positive=False, precompute=False, random_state=None,\n", + " selection='cyclic', tol=0.0001, warm_start=False)" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "l2 = Lasso()\n", + "l2.fit(X_treino, y_treino)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "predito = l2.predict(X_teste)" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R²: -0.032657509147810515\n" + ] + } + ], + "source": [ + "print('R²: ', l2.score(X_teste, y_teste))" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R² treino: 0.06840390147707931\n" + ] + } + ], + "source": [ + "print('R² treino: ', l2.score(X_treino, y_treino))" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MSE: 0.8161280467941258\n" + ] + } + ], + "source": [ + "print('MSE: ', mean_squared_error(y_teste, predito))" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MSE: 0.5642123174013881\n" + ] + } + ], + "source": [ + "predi_treino = l2.predict(X_treino)\n", + "print('MSE: ', mean_squared_error(y_treino, predi_treino))" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "fixed acidity : 0.0\n", + "volatile acidity : -0.0\n", + "citric acid : 0.0\n", + "residual sugar : 0.0\n", + "chlorides : -0.0\n", + "free sulfur dioxide : 0.0\n", + "total sulfur dioxide : -0.004984907732967799\n", + "density : 0.0\n", + "pH : -0.0\n", + "sulphates : 0.0\n", + "alcohol : 0.0\n" + ] + } + ], + "source": [ + "for i,coef in enumerate(l2.coef_):\n", + " print(df.columns[i],' : ', coef)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "ElasticNet(alpha=1.0, copy_X=True, fit_intercept=True, l1_ratio=0.5,\n", + " max_iter=1000, normalize=False, positive=False, precompute=False,\n", + " random_state=None, selection='cyclic', tol=0.0001, warm_start=False)" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "en = ElasticNet()\n", + "en.fit(X_treino, y_treino)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "predito = en.predict(X_teste)" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R²: -0.03330796257918256\n" + ] + } + ], + "source": [ + "print('R²: ', en.score(X_teste, y_teste))" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R² treino: 0.07005526330717127\n" + ] + } + ], + "source": [ + "print('R² treino: ', en.score(X_treino, y_treino))" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MSE: 0.816642111993646\n" + ] + } + ], + "source": [ + "print('MSE: ', mean_squared_error(y_teste, predito))" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MSE: 0.563212185813781\n" + ] + } + ], + "source": [ + "predi_treino = en.predict(X_treino)\n", + "print('MSE: ', mean_squared_error(y_treino, predi_treino))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A melhor escolha seria uma Ridge " + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R²: -0.0027479379901573786\n", + "R² treino: 0.09798031401380193\n", + "MSE: 0.7924899676893802\n", + "MSE treino: 0.5462996444262413\n" + ] + } + ], + "source": [ + "l2 = Lasso(alpha=0.15)\n", + "l2.fit(X_treino, y_treino)\n", + "predito = l2.predict(X_teste)\n", + "print('R²: ', l2.score(X_teste, y_teste))\n", + "print('R² treino: ', l2.score(X_treino, y_treino))\n", + "print('MSE: ', mean_squared_error(y_teste, predito))\n", + "predi_treino = l2.predict(X_treino)\n", + "print('MSE treino: ', mean_squared_error(y_treino, predi_treino))" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "fixed acidity : 0.02355774106283645\n", + "volatile acidity : -0.0\n", + "citric acid : 0.0\n", + "residual sugar : 0.0\n", + "chlorides : -0.0\n", + "free sulfur dioxide : 0.011897971350488755\n", + "total sulfur dioxide : -0.007731880907108915\n", + "density : 0.0\n", + "pH : -0.0\n", + "sulphates : 0.0\n", + "alcohol : 0.0\n" + ] + } + ], + "source": [ + "for i,coef in enumerate(l2.coef_):\n", + " print(df.columns[i],' : ', coef)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.8" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/3. Modelos regressivos/Exercicio_Regressao/day.csv b/3. Modelos regressivos/Exercicio_Regressao/day.csv new file mode 100644 index 0000000..58835b6 --- /dev/null +++ b/3. 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Modelos regressivos/Exercicio_Regressao/winequality-red.csv b/3. Modelos regressivos/Exercicio_Regressao/winequality-red.csv new file mode 100644 index 0000000..0075c66 --- /dev/null +++ b/3. 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Adele Kiamie ""Jane""",female,15,0,0,2667,7.225,,C +877,0,3,"Gustafsson, Mr. Alfred Ossian",male,20,0,0,7534,9.8458,,S +878,0,3,"Petroff, Mr. Nedelio",male,19,0,0,349212,7.8958,,S +879,0,3,"Laleff, Mr. Kristo",male,,0,0,349217,7.8958,,S +880,1,1,"Potter, Mrs. Thomas Jr (Lily Alexenia Wilson)",female,56,0,1,11767,83.1583,C50,C +881,1,2,"Shelley, Mrs. William (Imanita Parrish Hall)",female,25,0,1,230433,26,,S +882,0,3,"Markun, Mr. Johann",male,33,0,0,349257,7.8958,,S +883,0,3,"Dahlberg, Miss. Gerda Ulrika",female,22,0,0,7552,10.5167,,S +884,0,2,"Banfield, Mr. Frederick James",male,28,0,0,C.A./SOTON 34068,10.5,,S +885,0,3,"Sutehall, Mr. Henry Jr",male,25,0,0,SOTON/OQ 392076,7.05,,S +886,0,3,"Rice, Mrs. William (Margaret Norton)",female,39,0,5,382652,29.125,,Q +887,0,2,"Montvila, Rev. Juozas",male,27,0,0,211536,13,,S +888,1,1,"Graham, Miss. Margaret Edith",female,19,0,0,112053,30,B42,S +889,0,3,"Johnston, Miss. Catherine Helen ""Carrie""",female,,1,2,W./C. 6607,23.45,,S +890,1,1,"Behr, Mr. Karl Howell",male,26,0,0,111369,30,C148,C +891,0,3,"Dooley, Mr. Patrick",male,32,0,0,370376,7.75,,Q diff --git "a/4.0 Modelos de classifica\303\247\303\243o/notebook/titanic.ipynb" "b/4.0 Modelos de classifica\303\247\303\243o/notebook/titanic.ipynb" new file mode 100644 index 0000000..81e2f02 --- /dev/null +++ "b/4.0 Modelos de classifica\303\247\303\243o/notebook/titanic.ipynb" @@ -0,0 +1,1322 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "name": "titanic.ipynb", + "provenance": [], + "collapsed_sections": [], + "toc_visible": true + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + } + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "nKuIfr_KaNxn" + }, + "source": [ + "# **Desafio prático - Classificação de dados com a competição do Titanic**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "oYuFbfSeu6_i", + "colab_type": "text" + }, + "source": [ + "![](https://media.giphy.com/media/Uj3SeuVfg2oCs/giphy.gif)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "1P5IpCFCgmvc", + "colab_type": "text" + }, + "source": [ + "O problema de classificação que iremos resolver é o descrito na competição do Kaggle [Titanic: Machine Learning from Disaster](https://www.kaggle.com/c/titanic). Esse desafio é muito famoso e utilizado por quem está começando na área de Data Science e/ou a participar de competições pelo Kaggle (apesar de ser um assunto #badvibes).\n", + "\n", + "![](https://media.giphy.com/media/4ryp9Ihw0BEyc/giphy.gif)\n", + "\n", + "O objetivo da competição é simples: **criar um modelo utilizando Machine Learning para predizer se um passageiro do Titanic sobreviveu ou não ao naufrágio**." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "SOk7RZDCaOw-", + "colab_type": "text" + }, + "source": [ + "## **Bibliotecas auxiliares**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "xs-67JclxaiL", + "colab_type": "text" + }, + "source": [ + "Aqui nós vamos importar as algumas das bibliotecas necessárias para fazer a análise e visualização dos dados (lembram dessas aulas?)" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "KHvOv5sCXZ02", + "colab_type": "code", + "colab": {} + }, + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "6fQYMoroiKTb", + "colab_type": "text" + }, + "source": [ + "### **Conhecendo nossos conjuntos de dados**" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "88gyz2_Ea42A", + "colab_type": "code", + "colab": {} + }, + "source": [ + "train = pd.read_csv('train.csv')\n", + "submission = pd.read_csv('test.csv')" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "QfB36o6QA_zi", + "colab_type": "text" + }, + "source": [ + "Vamos ver a carinha dos nossos conjuntos de dados?" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "J8BqMyy9cOe3", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "Rlfws1wQcT4w", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Iig0D3thGIUw", + "colab_type": "text" + }, + "source": [ + "Na tabela abaixo podemos conferir o significado de cada um dos atributos presentes no conjunto de dados:\n", + "\n", + "|Atributo| Descrição|\n", + "|--------|----------|\n", + "|**PassengerId**| id do passageiro|\n", + "|**Pclass**| classe do ticket|\n", + "|**Name**|nome do passageiro|\n", + "|**Sex**|gênero do passageiro|\n", + "|**Age**|idade do passageiro (em anos)|\n", + "|**SibSp**|Quantidade de irmãos/cônjuge que também embarcaram no Titanic|\n", + "|**Parch**|Quantidade de pais/filhos que também embarcaram no Titanic|\n", + "|**Ticket**|Número do ticket do passageiro|\n", + "|**Fare**|Tarifa paga pelo passageiro|\n", + "|**Cabin**|Número da cabine|\n", + "|**Embarked**|Porto de embarque|\n", + "|**Survived**|Indica se o passageiro sobreviveu ou não ao naufrágio (é o nosso target)|\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "-GWYyJWDAnut", + "colab_type": "text" + }, + "source": [ + "Vamos verificar o tamanho dos conjuntos de treinamento e teste?" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "VWN5erVhcVPv", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "GSa79i8pdEwi", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "eqS3i_i7E5qI", + "colab_type": "text" + }, + "source": [ + "Vamos ver os tipos dos dados do conjunto de treinamento (também podemos verificar a quantidade de valores faltantes para cada atributo)?" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "qAXDw6mYE6CA", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "e8Ato1xlkYHL", + "colab_type": "text" + }, + "source": [ + "### **Remoção de features irrelevantes**\n", + "\n", + "Algumas features presentes em nosso conjunto de dados não são úteis para nos ajudar a predizer se um passageiro sobreviveu ou não ao naufrágio do Titanic. Essas features geralmente estão relacionadas a identificadores únicos de um indivíduo e, portanto, não ajudam na generalização do modelo.\n", + "\n", + "Que features seriam essas?" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "-6Dj3ZUeCpOo", + "colab_type": "code", + "colab": {} + }, + "source": [ + "def count_unique(df):\n", + " print(\"Quantidade de valores únicos para cada feature no conjunto de treinamento\")\n", + " for i in df.columns:\n", + " print(f\"{i}: {df[i].nunique()}\")" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "lJ9nEWv1DWc6", + "colab_type": "code", + "colab": {} + }, + "source": [ + "count_unique(train)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "bo993xJcwH-M", + "colab_type": "text" + }, + "source": [ + "Podemos remover esses casos que não fazem sentido do nosso conjunto de dados:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "truQJtlzmEUS", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "fPyuOc-_mY8y", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO " + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "zMNkRTQ1nHoj", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "xZvTPTRHa9AP", + "colab_type": "text" + }, + "source": [ + "### **Análise exploratória (Exploratory Data Analysis - EDA)**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "9cDdg22XKWK5", + "colab_type": "text" + }, + "source": [ + "Antes de treinarmos nosso modelo, precisamos fazer uma análise dos nossos dados para entender o nosso conjunto de treinamento e verificar quais atributos fazem sentido e verificar se alguma transformação será necessária." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "eQmK-xjVHK-K", + "colab_type": "text" + }, + "source": [ + "### Survived (Sobrevivência do passageiro)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "k_Dy_9sCnacz", + "colab_type": "text" + }, + "source": [ + "Primeiramente, é interessante olharmos a proporção do nosso target no nosso conjunto de dados:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "Nz0T5pz8dyxR", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Z8FdHyzmAJla", + "colab_type": "text" + }, + "source": [ + "Os passageiros com o target igual a 0 são aqueles que não sobreviveram ao naufrágio, enquanto que os que sobreviveram estão com o valor 1 no target." + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "bxRQMnCMxmy_", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "fUC1g1MMnwQj", + "colab_type": "code", + "colab": {} + }, + "source": [ + "print(f\"Considerando nosso conjunto de treinamento, {train.Survived.value_counts()[0]/train.shape[0]*100:.2f}% dos passageiros não sobreviveram ao naufrágio :(\")" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "kSuYbv4VQzhy", + "colab_type": "text" + }, + "source": [ + "### Pclass (classe do ticket do passageiro) \t \t \t \t \t \t" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "E7D2TfpDLx9r", + "colab_type": "text" + }, + "source": [ + " De acordo com a descrição das features no Kaggle, os valores para esse atributo têm os seguintes significados:\n", + " - 1 - Classe alta\n", + " - 2 - Classe média\n", + " - 3 - Classe baixa\n" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "jCA-3PuvFrLl", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "NrTwgvf_MpBp", + "colab_type": "text" + }, + "source": [ + "Podemos agora comparar a classe dos passageiros com relação ao nosso target para verificar se ela é relevante:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "Fq4UcZPTMy3O", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "MB1RXriqN3LZ", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "xYlPUaxCFpy1", + "colab_type": "text" + }, + "source": [ + "### Sex (gênero do passageiro) \t \t \t \t" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "a5ptqq6tQgtL", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "zVjG8eHGQhLS", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "HPdFb7-RQhae", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# proporção de sobrevivência por gênero\n", + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "FAw8t4PFdhM8", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "8obKrHmBFpca", + "colab_type": "text" + }, + "source": [ + "### Age (idade do passageiro) \t \t" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "mrHK8SDiSwt4", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "DZIVZ6FIOex9", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "4A6oLcnIYW0n", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "A_fqbGoGx7Ml", + "colab_type": "text" + }, + "source": [ + "### **Tarefinha pra casa**\n", + "\n", + "![](https://media.giphy.com/media/geONXs3YIr0Aw/giphy.gif)\n", + "\n", + "Por conta do tempo, não vamos conseguir fazer a análise de todas as features :(\n", + "\n", + "Então sugerimos que vocês façam a análise das features que ficaram faltando:\n", + "- Fare\n", + "- Embarked\n", + "- SibSp\n", + "- Parch\n", + "\n", + "Algumas ideias de análises que podem ser feitas:\n", + "- Comparar a tarifa paga pelo passageiro dependendo de sua classe\n", + "- Analisar se o tamanho da família influenciou na sobrevivência (o tamanho da família pode ser dado pela soma das features `SibSp` e `Parch`)\n", + "- Analisar se há diferença da tarifa paga dependendo do porto de embarque\n", + "- Verificar a correlação entre as features utilizando um heatmap" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ZgXMhU4STKuL", + "colab_type": "text" + }, + "source": [ + "## Feature Engineering" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "rCxYn5BufcGL", + "colab_type": "text" + }, + "source": [ + "Alguns algoritmos exigem que algumas transformações sejam feitas para que possamos treinar o modelo...\n", + "\n", + "![alt text](http://giphygifs.s3.amazonaws.com/media/720g7C1jz13wI/giphy.gif)\n", + "\n", + "Algumas dessas transformações são:\n", + "- Converter features categóricas em numéricas\n", + "- Fazer normalização ou estandardização dos dados\n", + "- Fazer o tratamento de valores faltantes\n", + "- Etc...\n", + "\n", + "Como exemplo, vamos fazer a conversão de features categóricas e o tratamento de valores faltantes:" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "v5-o4tVxhD4c", + "colab_type": "text" + }, + "source": [ + "#### **Tratamento de valores faltantes (missing values)**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "NqbxB0e_WtRu", + "colab_type": "text" + }, + "source": [ + "Como pudemos observar nas descrições acima, há casos de passageiros sem informação sobre suas idades. Podemos substituir esses valores faltantes pela mediana das idades:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "Bm9M9y8P0EOO", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "r_uBx6ZiWtoW", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "2PGbcitmhmPc", + "colab_type": "text" + }, + "source": [ + "Que outras abordagens poderíamos adotar para realizar essa substituição de valores faltantes?" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "GjH6ay0jib29", + "colab_type": "text" + }, + "source": [ + "#### **Conversão de features categóricas**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "MtsYp4uCig--", + "colab_type": "text" + }, + "source": [ + "A feature que indica o gênero dos passageiros é categórica. Iremos transformá-la em uma feature numérica. Há diversas abordagens para realizar essa transformação:\n", + "- Uma delas é utilizando o [LabelEncoder](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html)\n", + "\n", + "- E outra delas é fazendo o [One-hot encoding](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html)\n", + "\n", + "Por exemplo, se tivéssemos a seguinte feature:\n", + "\n", + "|renda|\n", + "|-----|\n", + "|alta |\n", + "|baixa|\n", + "|media|\n", + "|alta |\n", + "\n", + "Com o LabelEncoder, teríamos o seguinte resultado:\n", + "\n", + "|renda|\n", + "|-----|\n", + "|0 |\n", + "|1|\n", + "|2|\n", + "|0 |\n", + "\n", + "Já com o One-hot enconding teríamos o seguinte resultado:\n", + "\n", + "|renda_alta|renda_baixa|renda_media|\n", + "|-----|----|----|\n", + "|1 |0|0|\n", + "|0|1|0|\n", + "|0|0|1|\n", + "|1 |0|0|\n", + "\n", + "No nosso caso, vamos utilizar o LabelEncoder:\n" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "9Ld4Q9yBkKqc", + "colab_type": "code", + "colab": {} + }, + "source": [ + "from sklearn.preprocessing import LabelEncoder\n", + "\n", + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "9SL3tPjVkVjt", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "RyY2Kg3hjuLk", + "colab_type": "text" + }, + "source": [ + "### **Tarefinha pra casa**\n", + "\n", + "![](https://media.giphy.com/media/geONXs3YIr0Aw/giphy.gif)\n", + "\n", + "**Que outras transformaçõs poderíamos fazer em nosso conjunto de dados?**\n", + "- Criar categorias para a idade (criança, adulto, idoso, por exemplo)\n", + "- Criar uma feature para indicar o tamanho da família (soma das features `SibSp` e `Parch`)\n", + "- [Aqui](https://triangleinequality.wordpress.com/2013/09/08/basic-feature-engineering-with-the-titanic-data/) também algumas ideias de feature engineering para esse desafio\n", + "\n", + "Tentem fazer algumas dessas transformações ou fazer outras que vocês acreditam que façam sentido :D " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IPSGxrqIoSBD", + "colab_type": "text" + }, + "source": [ + "## Treinamento\n", + "Agora que nosso conjunto de treinamento está bonitinho, vamos treinar o nosso primeiro modelo \\o/\n", + "\n", + "Antes de treinar o modelo, precisamos separar as features do nosso target (**tomar muito cuidado para não treinar o modelo com ele!!!**). \n", + "\n", + "Além disso, nessa primeira versão, vamos utilizar somente as 3 features que analisamos na aula:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "DAaKrINZmIoc", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO\n", + "\n", + "# nossas features\n", + "\n", + "# nosso target" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "K7SqWejgA7Hf", + "colab_type": "text" + }, + "source": [ + "Uma outra coisa que precisamos fazer antes de treinar o modelo é separar o nosso conjunto de dados entre o **conjunto de treinamento** e o **conjunto de teste**. No nosso caso, vamos usar 75% do conjunto para treinamento e o restante para teste:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "SZmKZ-3kL3yd", + "colab_type": "code", + "colab": {} + }, + "source": [ + "from sklearn.model_selection import train_test_split\n", + "\n", + "# Separando os dados em treinamento e teste\n", + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "QysSeLtaBPHu", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "23s2Mhitm_6Q", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "B5nvF8CUCV3Z", + "colab_type": "text" + }, + "source": [ + "\n", + "Esse nosso primeiro modelo será uma Árvore de decisão. O scikit-learn já contém uma implementação dela [aqui](https://scikit-learn.org/stable/modules/tree.html).\n", + "\n" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "io8_yKZGKqJa", + "colab_type": "code", + "colab": {} + }, + "source": [ + "from sklearn.tree import DecisionTreeClassifier\n", + "\n", + "#TODO \n", + "\n", + "# Instanciando o classificador\n", + "\n", + "# Treinamento do modelo" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "fv6askV-ngY_", + "colab_type": "text" + }, + "source": [ + "**UHULLLLL! Temos nosso primeiro modelo de classificação \\o/**\n", + "\n", + "![](https://media.giphy.com/media/OU1marLMNNtnO/giphy.gif)\n", + "\n", + "Vamos ver a carinha dela (esse código para visualização da árvore nós encontramos [aqui](https://www.kaggle.com/jlawman/complete-beginner-your-first-titanic-submission))? :)" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "wXLwYat0F9qA", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# arquivo de texto que armazena a estrutura da nossa árvore de decisão\n", + "from sklearn.tree import export_graphviz\n", + "export_graphviz(model,out_file='titanic_tree.dot',feature_names=['Age', 'Sex', 'Pclass'],rounded=True,filled=True,class_names=['Sobreviveu','Não sobreviveu'])\n" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "MH2oh9cJHxOh", + "colab_type": "code", + "colab": {} + }, + "source": [ + "!dot -Tpng titanic_tree.dot -o titanic_tree.png" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3m-UB7ntM1ey", + "colab_type": "text" + }, + "source": [ + "Após converter o arquivo de texto, podemos visualizar a árvore abaixo. As cores ajudam a identificar a classificação dada pelo modelo:\n", + "\n", + "- Nós ou folhas em azul significam que a nossa árvore de decisão acredita que o passageiro **NÃO SOBREVIVEU**\n", + "- Já nos nós e folhas em laranja, a árvore acha que o passageiro **SOBREVIVEU**" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "2XqQGAlcHCja", + "colab_type": "code", + "colab": {} + }, + "source": [ + "from IPython.core.display import Image, display\n", + "display(Image('titanic_tree.png', width=1900, unconfined=True))" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "X0cyg7DILLQv", + "colab_type": "text" + }, + "source": [ + "**O que vocês acharam dessa árvore?**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "aj5_1pz16uh2", + "colab_type": "text" + }, + "source": [ + "## Avaliando nosso modelo" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "0Mjmy5R47DCm", + "colab_type": "text" + }, + "source": [ + "Agora precisamos avaliar se o modelo está bom ou não!\n", + "\n", + "Para isso, precisamos utilizá-lo para realizar as predições para nosso conjunto de teste:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "7T5kx7cX9wHE", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "DebndYd19yiy", + "colab_type": "text" + }, + "source": [ + "Como a métrica de avaliação do Kaggle é a acurácia, vamos utilizá-la primeiro:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "7dXxL-P_7Yys", + "colab_type": "code", + "colab": {} + }, + "source": [ + "from sklearn.metrics import accuracy_score" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "uc2S3Wi19jA4", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "-0-CA-jMC4ZF", + "colab_type": "text" + }, + "source": [ + "Outra avaliação que poderíamos fazer é utilizando uma matriz de confusão:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "rHFTQm3Gzt34", + "colab_type": "code", + "colab": {} + }, + "source": [ + "from sklearn.metrics import confusion_matrix\n", + "import itertools" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "yovWpGiDzbag", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# plota a matriz de confusão. Código retirado da documentação do próprio Sklearn\n", + "def plot_confusion_matrix(cm, classes,\n", + " normalize=False,\n", + " title='Matriz de confusão',\n", + " cmap=plt.cm.Blues):\n", + "\n", + " if normalize:\n", + " cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]\n", + " \n", + " #plt.ylim(0.5, 0.5)\n", + " plt.imshow(cm, interpolation='nearest', cmap=cmap)\n", + " plt.title(title)\n", + " plt.colorbar()\n", + " tick_marks = np.arange(len(classes))\n", + " plt.xticks(tick_marks, classes, rotation=45)\n", + " plt.yticks(tick_marks, classes)\n", + " plt.ylim(1.5, -0.5) \n", + "\n", + " fmt = '.2f' if normalize else 'd'\n", + " thresh = cm.max() / 2.\n", + " for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):\n", + " plt.text(j, i, format(cm[i, j], fmt),\n", + " horizontalalignment=\"center\",\n", + " color=\"white\" if cm[i, j] > thresh else \"black\")\n", + "\n", + " plt.ylabel('Classe real')\n", + " plt.xlabel('Classe prevista')\n", + " plt.tight_layout()" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "_6sxzSLg7A5n", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "rwXkkoZAng2_", + "colab_type": "text" + }, + "source": [ + "## Predição\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Vc44HmLH71eM", + "colab_type": "text" + }, + "source": [ + "Agora que nosso modelo foi avaliado, vamos fazer as predições para o conjunto sem o target e fazer a [submissão para o Kaggle](https://www.kaggle.com/c/titanic/submit)? :D\n", + "\n", + "![alt text](https://media.giphy.com/media/l4JySAWfMaY7w88sU/giphy.gif)\n", + "\n", + "Antes de fazer as predições, precisamos fazer as mesmas transformações que fizemos no conjunto de treinamento durante a etapa de feature engineering:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "RVQ_ICmgozjo", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# substituímos os valores faltantes pela mediana da idade do conjunto de treinamento\n", + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "84S7WJcgox8U", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# utilizamos o encoder que foi criado com base no conjunto de treinamento\n", + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "07lRmNJJoDif", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# realiza a predição para o conjunto de teste\n", + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Cy9y1iDfo8fO", + "colab_type": "text" + }, + "source": [ + "Para a submissão no Kaggle, além da predição, precisamos fornecer também o ID do passageiro:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "2a8_n9v18dD6", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# transformar o array em um DataFrame para concatenarmos como ID\n", + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "WeuQAzXopSMD", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "YI1I6AujpcW_", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#TODO" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "2ptwDdcDIYIR", + "colab_type": "text" + }, + "source": [ + "Se observarmos o resultado da acurácia no conjunto de treinamento, tivemos uma certa diminuição na acurácia do conjunto de teste. Por que isso ocorre?\n", + "\n", + " ![](https://hackernoon.com/hn-images/1*SBUK2QEfCP-zvJmKm14wGQ.png)\n", + "\n", + " \n", + "No nosso caso, o modelo sofreu **overfitting**. Isso também explica a alta complexidade da árvore. No caso da nossa árvore, é necessário podá-la para que ela possa **generalizar** o problema." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Emhu6vuJFjSK", + "colab_type": "text" + }, + "source": [ + "## Próximos passos\n", + "\n", + "Ainda podemos melhorar **MUITO** o nosso modelo :) \n", + "\n", + "O que podemos fazer?\n", + "\n", + "- Como pudemos ver, nossa árvore está sofreu overfitting. Podemos mudar diversos parâmetros da nossa árvore para evitar que isso aconteça. Alguns parâmetros que podemos alterar:\n", + " - **max_depth** (profundidade máxima da árvore) - podemos determinar um valor para que ela não se aprofunde demais\n", + " - **min_samples_split** (número mínimo de exemplos para dividir um nó interno) - podemos aumentar o número (o mínimo *default* é 2) para diminuir o número de divisões\n", + " - **min_samples_leaf** (número mínimo de exemplos para que um nó seja uma folha) - podemos aumentar o número (o mínimo *default* é 1) para diminuir o número de folhas\n", + "- Podemos realizar outras transformações na etapa de feature engineering ou criar novas features\n", + "- Também podemos treinar o modelo adicionando as outras features que não vimos nessa aula. Talvez elas possam ajudar na predição ;)\n", + "- Além disso, é interessante ver as outras métricas de avaliação para entendermos melhor o nosso modelo e como podemos melhorá-lo!\n", + "\n", + "### **Tarefinha pra casa**\n", + "\n", + "![](https://media.giphy.com/media/geONXs3YIr0Aw/giphy.gif)\n", + "\n", + "\n", + "Tentem fazer algumas (ou todas) as sugestões feitas nesse notebook e fazer a submissão das predições no Kaggle novamente! \n", + "\n", + "Na próxima aula vocês nos contam se a acurácia do modelo melhorou :D " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "JJPMfwGM6Qdc", + "colab_type": "text" + }, + "source": [ + "![](https://media.giphy.com/media/3o7budMRwZvNGJ3pyE/giphy.gif)" + ] + } + ] +} \ No newline at end of file diff --git "a/4.0 Modelos de classifica\303\247\303\243o/notebook/titanic_gabarito.ipynb" "b/4.0 Modelos de classifica\303\247\303\243o/notebook/titanic_gabarito.ipynb" new file mode 100644 index 0000000..aa29f7c --- /dev/null +++ "b/4.0 Modelos de classifica\303\247\303\243o/notebook/titanic_gabarito.ipynb" @@ -0,0 +1,2451 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "name": "titanic_gabarito.ipynb", + "provenance": [], + "collapsed_sections": [] + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + } + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "nKuIfr_KaNxn" + }, + "source": [ + "# **Desafio prático - Classificação de dados com a competição do Titanic**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "oYuFbfSeu6_i", + "colab_type": "text" + }, + "source": [ + "![](https://media.giphy.com/media/Uj3SeuVfg2oCs/giphy.gif)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "1P5IpCFCgmvc", + "colab_type": "text" + }, + "source": [ + "O problema de classificação que iremos resolver é o descrito na competição do Kaggle [Titanic: Machine Learning from Disaster](https://www.kaggle.com/c/titanic). Esse desafio é muito famoso e utilizado por quem está começando na área de Data Science e/ou a participar de competições pelo Kaggle (apesar de ser um assunto #badvibes).\n", + "\n", + "![](https://media.giphy.com/media/4ryp9Ihw0BEyc/giphy.gif)\n", + "\n", + "O objetivo da competição é simples: **criar um modelo utilizando Machine Learning para predizer se um passageiro do Titanic sobreviveu ou não ao naufrágio**." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "SOk7RZDCaOw-", + "colab_type": "text" + }, + "source": [ + "## **Bibliotecas auxiliares**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "xs-67JclxaiL", + "colab_type": "text" + }, + "source": [ + "Aqui nós vamos importar as algumas das bibliotecas necessárias para fazer a análise e visualização dos dados (lembram dessas aulas?)" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "KHvOv5sCXZ02", + "colab_type": "code", + "colab": {} + }, + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "6fQYMoroiKTb", + "colab_type": "text" + }, + "source": [ + "### **Conhecendo nossos conjuntos de dados**" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "88gyz2_Ea42A", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# esse conjunto que o Kaggle chama de teste não será usado dessa forma porque ele não \n", + "# contém a classe dos exemplos e, dessa forma, não podemos avaliar o modelo com ele.\n", + "# para a avaliação, vamos separar o conjunto inicial que vamos chamar de \"df\" entre treino e teste\n", + "# e fazer as predições para submeter para o Kaggle com o conjunto chamado de \"submission\"\n", + "df = pd.read_csv('train.csv')\n", + "submission = pd.read_csv('test.csv')" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "QfB36o6QA_zi", + "colab_type": "text" + }, + "source": [ + "Vamos ver a carinha dos nossos conjuntos de dados?" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "J8BqMyy9cOe3", + "colab_type": "code", + "outputId": "7df028ab-2bb0-4922-f6ec-72ebeb1fb5b0", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 112 + } + }, + "source": [ + "df.head(2)" + ], + "execution_count": 3, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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Fare Cabin Embarked\n", + "0 892 3 Kelly, Mr. James ... 7.8292 NaN Q\n", + "1 893 3 Wilkes, Mrs. James (Ellen Needs) ... 7.0000 NaN S\n", + "\n", + "[2 rows x 11 columns]" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 4 + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Iig0D3thGIUw", + "colab_type": "text" + }, + "source": [ + "Na tabela abaixo podemos conferir o significado de cada um dos atributos presentes no conjunto de dados:\n", + "\n", + "|Atributo| Descrição|\n", + "|--------|----------|\n", + "|**PassengerId**| id do passageiro|\n", + "|**Pclass**| classe do ticket|\n", + "|**Name**|nome do passageiro|\n", + "|**Sex**|gênero do passageiro|\n", + "|**Age**|idade do passageiro (em anos)|\n", + "|**SibSp**|Quantidade de irmãos/cônjuge que também embarcaram no Titanic|\n", + "|**Parch**|Quantidade de pais/filhos que também embarcaram no Titanic|\n", + "|**Ticket**|Número do ticket do passageiro|\n", + "|**Fare**|Tarifa paga pelo passageiro|\n", + "|**Cabin**|Número da cabine|\n", + "|**Embarked**|Porto de embarque (C = Cherbourg, Q = Queenstown e S = Southampton)|\n", + "|**Survived**|Indica se o passageiro sobreviveu ou não ao naufrágio (é o nosso target)|\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "-GWYyJWDAnut", + "colab_type": "text" + }, + "source": [ + "Vamos verificar o tamanho dos conjuntos de dados e o que iremos submeter no Kaggle?" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "VWN5erVhcVPv", + "colab_type": "code", + "outputId": "7a22df3f-eaf2-4f0b-a7c5-ffd288f81c00", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + } + }, + "source": [ + "df.shape" + ], + "execution_count": 5, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(891, 12)" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 5 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "GSa79i8pdEwi", + "colab_type": "code", + "outputId": "1668a91b-88b4-4914-95c3-5000348ae6c0", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + } + }, + "source": [ + "submission.shape" + ], + "execution_count": 6, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(418, 11)" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 6 + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "eqS3i_i7E5qI", + "colab_type": "text" + }, + "source": [ + "Vamos ver os tipos dos dados do conjunto de dados (também podemos verificar a quantidade de valores faltantes para cada atributo)?" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "qAXDw6mYE6CA", + "colab_type": "code", + "outputId": "5123e9ab-6be9-4d4d-d8bd-805daae82620", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 312 + } + }, + "source": [ + "df.info()" + ], + "execution_count": 7, + "outputs": [ + { + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 891 entries, 0 to 890\n", + "Data columns (total 12 columns):\n", + "PassengerId 891 non-null int64\n", + "Survived 891 non-null int64\n", + "Pclass 891 non-null int64\n", + "Name 891 non-null object\n", + "Sex 891 non-null object\n", + "Age 714 non-null float64\n", + "SibSp 891 non-null int64\n", + "Parch 891 non-null int64\n", + "Ticket 891 non-null object\n", + "Fare 891 non-null float64\n", + "Cabin 204 non-null object\n", + "Embarked 889 non-null object\n", + "dtypes: float64(2), int64(5), object(5)\n", + "memory usage: 83.7+ KB\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "e8Ato1xlkYHL", + "colab_type": "text" + }, + "source": [ + "### **Remoção de features irrelevantes**\n", + "\n", + "Algumas features presentes em nosso conjunto de dados não são úteis para nos ajudar a predizer se um passageiro sobreviveu ou não ao naufrágio do Titanic. Essas features geralmente estão relacionadas a identificadores únicos de um indivíduo e, portanto, não ajudam na generalização do modelo.\n", + "\n", + "Que features seriam essas?\n", + "\n", + "- IDs (identificadores únicos em uma tabela no banco de dados, por exemplo) \n", + "- Números de documento (um CPF ou RG se enquadraria nesse caso)\n", + "- Nomes, telefones, e-mail, etc... Tudo que for específico para uma determinada pessoa não deve ser fornecido para o modelo." + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "-6Dj3ZUeCpOo", + "colab_type": "code", + "colab": {} + }, + "source": [ + "def count_unique(df):\n", + " print(\"Quantidade de valores únicos para cada feature\")\n", + " for i in df.columns:\n", + " print(f\"{i}: {df[i].nunique()}\")" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "lJ9nEWv1DWc6", + "colab_type": "code", + "outputId": "ee27ed5f-4a91-43b5-9b77-0db244d352d9", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 243 + } + }, + "source": [ + "count_unique(df)" + ], + "execution_count": 9, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Quantidade de valores únicos para cada feature\n", + "PassengerId: 891\n", + "Survived: 2\n", + "Pclass: 3\n", + "Name: 891\n", + "Sex: 2\n", + "Age: 88\n", + "SibSp: 7\n", + "Parch: 7\n", + "Ticket: 681\n", + "Fare: 248\n", + "Cabin: 147\n", + "Embarked: 3\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "bo993xJcwH-M", + "colab_type": "text" + }, + "source": [ + "Podemos remover esses casos que não fazem sentido do nosso conjunto de dados:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "truQJtlzmEUS", + "colab_type": "code", + "colab": {} + }, + "source": [ + "columns = ['PassengerId', 'Name', 'Ticket', 'Cabin']\n", + "\n", + "df = df.drop(columns, axis=1)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "fPyuOc-_mY8y", + "colab_type": "code", + "outputId": "67aab350-cfa6-4fca-a931-72c64f4501be", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 112 + } + }, + "source": [ + "df.head(2)" + ], + "execution_count": 11, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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SurvivedPclassSexAgeSibSpParchFareEmbarked
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" + ], + "text/plain": [ + " Survived Pclass Sex Age SibSp Parch Fare Embarked\n", + "0 0 3 male 22.0 1 0 7.2500 S\n", + "1 1 1 female 38.0 1 0 71.2833 C" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 11 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "zMNkRTQ1nHoj", + "colab_type": "code", + "outputId": "8a1391b4-eec6-4188-ad40-05d20059cad8", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + } + }, + "source": [ + "df.shape" + ], + "execution_count": 12, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(891, 8)" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 12 + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "xZvTPTRHa9AP", + "colab_type": "text" + }, + "source": [ + "### **Análise exploratória (Exploratory Data Analysis - EDA)**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "9cDdg22XKWK5", + "colab_type": "text" + }, + "source": [ + "Antes de treinarmos nosso modelo, precisamos fazer uma análise dos nossos dados para entender o nosso conjunto de dados e verificar quais atributos fazem sentido e verificar se alguma transformação será necessária." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "eQmK-xjVHK-K", + "colab_type": "text" + }, + "source": [ + "### Survived (Sobrevivência do passageiro)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "k_Dy_9sCnacz", + "colab_type": "text" + }, + "source": [ + "Primeiramente, é interessante olharmos a proporção do nosso target no nosso conjunto de dados:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "Nz0T5pz8dyxR", + "colab_type": "code", + "outputId": "d0a90c96-b2dc-4532-f490-d7f06d26a6dc", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 69 + } + }, + "source": [ + "df.Survived.value_counts()" + ], + "execution_count": 13, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "0 549\n", + "1 342\n", + "Name: Survived, dtype: int64" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 13 + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Z8FdHyzmAJla", + "colab_type": "text" + }, + "source": [ + "Os passageiros com o target igual a 0 são aqueles que não sobreviveram ao naufrágio, enquanto que os que sobreviveram estão com o valor 1 no target." + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "bxRQMnCMxmy_", + "colab_type": "code", + "outputId": "551227ab-6182-4707-f737-4428506ff5a5", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 295 + } + }, + "source": [ + "sns.countplot(data=df, x = 'Survived')\n", + "plt.title(\"Contagem de sobrevivência\")\n", + "plt.xlabel('Sobrevivência')\n", + "plt.ylabel('Contagem')\n", + "plt.show()" + ], + "execution_count": 14, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "fUC1g1MMnwQj", + "colab_type": "code", + "outputId": "1f35710b-5a86-4065-fe2d-1df3fe8fbfd9", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + } + }, + "source": [ + "print(f\"Considerando nosso conjunto de dados, {df.Survived.value_counts()[0]/df.shape[0]*100:.2f}% dos passageiros não sobreviveram ao naufrágio :(\")" + ], + "execution_count": 15, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Considerando nosso conjunto de dados, 61.62% dos passageiros não sobreviveram ao naufrágio :(\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "kSuYbv4VQzhy", + "colab_type": "text" + }, + "source": [ + "### Pclass (classe do ticket do passageiro) \t \t \t \t \t \t" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "E7D2TfpDLx9r", + "colab_type": "text" + }, + "source": [ + " De acordo com a descrição das features no Kaggle, os valores para esse atributo têm os seguintes significados:\n", + " - 1 - Classe alta\n", + " - 2 - Classe média\n", + " - 3 - Classe baixa\n", + "\n", + " Contando a quantidade de exemplos de cada uma dessas classes, podemos observar que a maioria dos passageiros era de classe baixa:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "jCA-3PuvFrLl", + "colab_type": "code", + "outputId": "10d4aefd-98c6-4021-b60c-27c57b801347", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 86 + } + }, + "source": [ + "df.Pclass.value_counts()" + ], + "execution_count": 16, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "3 491\n", + "1 216\n", + "2 184\n", + "Name: Pclass, dtype: int64" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 16 + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "NrTwgvf_MpBp", + "colab_type": "text" + }, + "source": [ + "Podemos agora comparar a classe dos passageiros com relação ao nosso target para verificar se ela é relevante:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "Fq4UcZPTMy3O", + "colab_type": "code", + "outputId": "8e58707f-9815-497e-9e05-c4c3844ac736", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 295 + } + }, + "source": [ + "p = sns.countplot(data=df, x = 'Survived', hue = 'Pclass')\n", + "plt.title(\"Contagem de sobrevivência de acordo com a classe\")\n", + "plt.xlabel(\"Sobrevivência\")\n", + "plt.ylabel(\"Quantidade\")\n", + "plt.show()" + ], + "execution_count": 17, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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" + ], + "text/plain": [ + " Survived\n", + "Pclass \n", + "1 62.962963\n", + "2 47.282609\n", + "3 24.236253" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 18 + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "TCaoHl-hOnjD", + "colab_type": "text" + }, + "source": [ + "Apesar dos passageiros da terceira classe serem os mais numerosos, podemos observar tanto pela contagem de sobrevivência quanto pela proporção que esses passageiros foram os que menos sobreviveram, enquanto que os passageiros da primeira classe foram os que mais sobreviveram." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "xYlPUaxCFpy1", + "colab_type": "text" + }, + "source": [ + "### Sex (gênero do passageiro) \t \t \t \t" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "mKkPuIBMRTnF", + "colab_type": "text" + }, + "source": [ + "Com relação ao gênero, podemos observar que a maioria dos passageiros eram homens:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "a5ptqq6tQgtL", + "colab_type": "code", + "outputId": "4abcfb1f-2965-4133-d1f7-759304d7a00d", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 69 + } + }, + "source": [ + "df.Sex.value_counts()" + ], + "execution_count": 19, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "male 577\n", + "female 314\n", + "Name: Sex, dtype: int64" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 19 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "zVjG8eHGQhLS", + "colab_type": "code", + "outputId": "30331d74-1bfc-4381-b234-9000ddaa97ff", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 295 + } + }, + "source": [ + "p = sns.countplot(data=df, x = 'Survived', hue = 'Sex')\n", + "plt.title(\"Contagem de sobrevivência de acordo com o gênero\")\n", + "plt.xlabel(\"Sobrevivência\")\n", + "plt.ylabel(\"Quantidade\")\n", + "plt.show()" + ], + "execution_count": 20, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "HPdFb7-RQhae", + "colab_type": "code", + "outputId": "962ac323-fc00-4c33-c2b0-0017d14f7388", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 143 + } + }, + "source": [ + "# proporção de sobrevivência por gênero\n", + "df[[\"Sex\", \"Survived\"]].groupby(['Sex']).mean()*100" + ], + "execution_count": 21, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Survived
Sex
female74.203822
male18.890815
\n", + "
" + ], + "text/plain": [ + " Survived\n", + "Sex \n", + "female 74.203822\n", + "male 18.890815" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 21 + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ZQutd4HnSMGv", + "colab_type": "text" + }, + "source": [ + "Aqui também podemos observar uma situação similar ao que ocorreu com a classe: os passageiros do gênero masculino, apesar de mais numerosos, tiveram uma baixa proporção de sobrevivência quando comparamos com as mulheres.\n", + "\n", + "Uma outra análise interessante de ser realizada é observar as taxas de sobrevivência dependendo do gênero e também da classe:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "FAw8t4PFdhM8", + "colab_type": "code", + "outputId": "e3b02b97-fda7-4406-86f5-cb549c78e0ec", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 369 + } + }, + "source": [ + "sns.catplot(x=\"Pclass\", y=\"Survived\", col=\"Sex\", data=df,kind=\"bar\");" + ], + "execution_count": 22, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "b6jRrOc1eRc9", + "colab_type": "text" + }, + "source": [ + "O gráfico acima nos permite observar que tanto para homens quanto para mulheres houve uma maior sobrevivência para os passageiros da primeira classe. Ele também nos permite observar que a taxa de sobrevivência das mulheres da terceira classe é mais próxima da taxa de sobrevivência dos homens da primeira classe do que das mulheres da primeira e segunda classe." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "8obKrHmBFpca", + "colab_type": "text" + }, + "source": [ + "### Age (idade do passageiro) \t \t" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "depgS5NzVyBB", + "colab_type": "text" + }, + "source": [ + "Observando a descrição abaixo, vemos que, na média, os passageiros tinham em torno de 30 anos:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "mrHK8SDiSwt4", + "colab_type": "code", + "outputId": "597651c1-f978-4731-92b1-5f0975821672", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 173 + } + }, + "source": [ + "df['Age'].describe()" + ], + "execution_count": 23, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "count 714.000000\n", + "mean 29.699118\n", + "std 14.526497\n", + "min 0.420000\n", + "25% 20.125000\n", + "50% 28.000000\n", + "75% 38.000000\n", + "max 80.000000\n", + "Name: Age, dtype: float64" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 23 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "DZIVZ6FIOex9", + "colab_type": "code", + "outputId": "1f9c78f9-ee42-46e8-bc9e-9c4c36446cfe", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 295 + } + }, + "source": [ + "_ = sns.boxplot(df['Age']).set_title(\"Idade\")" + ], + "execution_count": 24, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "mDnwfi8UYF8o", + "colab_type": "text" + }, + "source": [ + "Podemos checar também a distribuição das idades por sobrevivência. Se tentarmos ver a distribuição da idade do jeito como nosso dado está, teremos um erro porque a idade tem valores nulos. Para fazer a distribuição, temos duas alternativas:\n", + "- Ignorar os nulos e ver a distribuição da idade só para os passageiros que possuem essa informação\n", + "- Substituir os valores faltantes por algum número (0, média ou mediana da idade, por exemplo)\n", + "\n", + "Aqui vamos só ignorar os nulos:\n", + "\n" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "ydVCHQRBXVNk", + "colab_type": "code", + "colab": {} + }, + "source": [ + "survived_age_not_null = df.loc[(df.Survived == 1) & (df.Age.isnull()==False), 'Age']\n", + "not_survived_age_not_null = df.loc[(df.Survived == 0) & (df.Age.isnull()==False), 'Age']" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "4A6oLcnIYW0n", + "colab_type": "code", + "outputId": "2eef63cd-03e8-40b9-f0ee-4ac3bb365627", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 295 + } + }, + "source": [ + "sns.distplot(survived_age_not_null, hist=True, label='Sobreviveu')\n", + "sns.distplot(not_survived_age_not_null, hist=False, label='Não sobreviveu')\n", + "_ = plt.title(\"Distribuições das idades de acordo com o target\")" + ], + "execution_count": 26, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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oHut0FcElKdze9TRbjp4h9tiZWtelaS2ZTgBa/bHbIWUndBpSo8WUUny54wT5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\n0DuEXb0fZGjpbub6b+OexdvZEK/PCWi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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ZMEPqVXKUwKw", + "colab_type": "text" + }, + "source": [ + "Se fizermos as distribuições das idades entre os passageiros que sobreviveram ou não, podemos notar que há pico de sobrevivência para os passageiros com menos de 10 anos, indicando que crianças tiveram mais chances de sobreviverem ao naufrágio do que adultos." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "A_fqbGoGx7Ml", + "colab_type": "text" + }, + "source": [ + "### **Tarefinha pra casa**\n", + "\n", + "![](https://media.giphy.com/media/geONXs3YIr0Aw/giphy.gif)\n", + "\n", + "Por conta do tempo, não vamos conseguir fazer a análise de todas as features :(\n", + "\n", + "Então sugerimos que vocês façam a análise das features que ficaram faltando:\n", + "- Fare\n", + "- Embarked\n", + "- SibSp\n", + "- Parch\n", + "\n", + "Algumas ideias de análises que podem ser feitas:\n", + "- Comparar a tarifa paga pelo passageiro dependendo de sua classe\n", + "- Analisar se o tamanho da família influenciou na sobrevivência (o tamanho da família pode ser dado pela soma das features `SibSp` e `Parch`)\n", + "- Analisar se há diferença da tarifa paga dependendo do porto de embarque\n", + "- Verificar a correlação entre as features utilizando um heatmap" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ZgXMhU4STKuL", + "colab_type": "text" + }, + "source": [ + "## Feature Engineering" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "rCxYn5BufcGL", + "colab_type": "text" + }, + "source": [ + "Alguns algoritmos exigem que algumas transformações sejam feitas para que possamos treinar o modelo...\n", + "\n", + "![alt text](http://giphygifs.s3.amazonaws.com/media/720g7C1jz13wI/giphy.gif)\n", + "\n", + "Algumas dessas transformações são:\n", + "- Converter features categóricas em numéricas\n", + "- Fazer normalização ou estandardização dos dados\n", + "- Fazer o tratamento de valores faltantes\n", + "- Etc...\n", + "\n", + "Como exemplo, vamos fazer a conversão de features categóricas e o tratamento de valores faltantes:" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "v5-o4tVxhD4c", + "colab_type": "text" + }, + "source": [ + "#### **Tratamento de valores faltantes (missing values)**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "NqbxB0e_WtRu", + "colab_type": "text" + }, + "source": [ + "Como pudemos observar nas descrições acima, há casos de passageiros sem informação sobre suas idades. Podemos substituir esses valores faltantes pela mediana das idades:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "Bm9M9y8P0EOO", + "colab_type": "code", + "colab": {} + }, + "source": [ + "median_age = df['Age'].median() " + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "r_uBx6ZiWtoW", + "colab_type": "code", + "colab": {} + }, + "source": [ + "df.loc[df['Age'].isnull(), 'Age'] = median_age" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "2PGbcitmhmPc", + "colab_type": "text" + }, + "source": [ + "Que outras abordagens poderíamos adotar para realizar essa substituição de valores faltantes?" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "vLgxZR1Lh4-S", + "colab_type": "text" + }, + "source": [ + "- Poderíamos ter analisado a idade de homens e mulheres e substituir pela mediana dependendo do gênero do passageiro\n", + "- Poderíamos substituir pela média da idade ao invés da mediana (tomar cuidado com outliers nesse caso!)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "GjH6ay0jib29", + "colab_type": "text" + }, + "source": [ + "#### **Conversão de features categóricas**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "MtsYp4uCig--", + "colab_type": "text" + }, + "source": [ + "A feature que indica o gênero dos passageiros é categórica. Iremos transformá-la em uma feature numérica. Há diversas abordagens para realizar essa transformação:\n", + "- Uma delas é utilizando o [LabelEncoder](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html)\n", + "\n", + "- E outra delas é fazendo o [One-hot encoding](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html)\n", + "\n", + "Por exemplo, se tivéssemos a seguinte feature:\n", + "\n", + "|renda|\n", + "|-----|\n", + "|alta |\n", + "|baixa|\n", + "|media|\n", + "|alta |\n", + "\n", + "Com o LabelEncoder, teríamos o seguinte resultado:\n", + "\n", + "|renda|\n", + "|-----|\n", + "|0 |\n", + "|1|\n", + "|2|\n", + "|0 |\n", + "\n", + "Já com o One-hot encoding teríamos o seguinte resultado:\n", + "\n", + "|renda_alta|renda_baixa|renda_media|\n", + "|-----|----|----|\n", + "|1 |0|0|\n", + "|0|1|0|\n", + "|0|0|1|\n", + "|1 |0|0|\n", + "\n", + "No nosso caso, vamos utilizar o LabelEncoder:\n" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "9Ld4Q9yBkKqc", + "colab_type": "code", + "colab": {} + }, + "source": [ + "from sklearn.preprocessing import LabelEncoder\n", + "\n", + "encoder = LabelEncoder()\n", + "df['Sex'] = encoder.fit_transform(df['Sex'])\n", + "\n", + "# ao invés do LabelEncoder, também poderíamos ter feito só um map e passar as transformações que queríamos:\n", + "# df['Sex'] = df['Sex'].map( {'female': 0, 'male': 1})" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "9SL3tPjVkVjt", + "colab_type": "code", + "outputId": "5fdfba40-ced0-4ee3-c4f9-4220bfc96bf1", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 69 + } + }, + "source": [ + "df['Sex'].value_counts()" + ], + "execution_count": 30, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "1 577\n", + "0 314\n", + "Name: Sex, dtype: int64" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 30 + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "fF5t4y_xYie3", + "colab_type": "text" + }, + "source": [ + "Se a gente comparar essas quantidades com o que tínhamos na feature _Sex_, as substituições foram feitas da seguinte maneira:\n", + "- Se o gênero do passageiro fosse feminino, a feature _Sex_ ficaria com valor 0\n", + "- Se o gênero do passageiro fosse masculino, a feature _Sex_ ficaria com valor 1" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "RyY2Kg3hjuLk", + "colab_type": "text" + }, + "source": [ + "### **Tarefinha pra casa**\n", + "\n", + "![](https://media.giphy.com/media/geONXs3YIr0Aw/giphy.gif)\n", + "\n", + "**Que outras transformaçõs poderíamos fazer em nosso conjunto de dados?**\n", + "- Criar categorias para a idade (criança, adulto, idoso, por exemplo)\n", + "- Criar uma feature para indicar o tamanho da família (soma das features `SibSp` e `Parch`)\n", + "- [Aqui](https://triangleinequality.wordpress.com/2013/09/08/basic-feature-engineering-with-the-titanic-data/) também algumas ideias de feature engineering para esse desafio\n", + "\n", + "Tentem fazer algumas dessas transformações ou fazer outras que vocês acreditam que façam sentido :D " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IPSGxrqIoSBD", + "colab_type": "text" + }, + "source": [ + "## Treinamento\n", + "Agora que nosso conjunto de dados está bonitinho, vamos treinar o nosso primeiro modelo \\o/\n", + "\n", + "Antes de treinar o modelo, precisamos separar as features do nosso target (**tomar muito cuidado para não treinar o modelo com ele!!!**). \n", + "\n", + "Além disso, nessa primeira versão, vamos utilizar somente as 3 features que analisamos na aula:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "DAaKrINZmIoc", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# nossas features\n", + "x = df[['Age', 'Sex', 'Pclass']]\n", + "\n", + "# nosso target\n", + "y = df['Survived']" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "K7SqWejgA7Hf", + "colab_type": "text" + }, + "source": [ + "Uma outra coisa que precisamos fazer antes de treinar o modelo é separar o nosso conjunto de dados entre o **conjunto de treinamento** e o **conjunto de teste**. No nosso caso, vamos usar 75% do conjunto para treinamento e o restante para teste:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "SZmKZ-3kL3yd", + "colab_type": "code", + "colab": {} + }, + "source": [ + "from sklearn.model_selection import train_test_split\n", + "\n", + "# Separando os dados em treinamento e teste\n", + "x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.25, random_state=42)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "QysSeLtaBPHu", + "colab_type": "code", + "outputId": "0db3da65-6bdc-4d32-ad89-ae7e09e4ff6b", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + } + }, + "source": [ + "x_train.shape" + ], + "execution_count": 33, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(668, 3)" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 33 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "23s2Mhitm_6Q", + "colab_type": "code", + "outputId": "1423f5bb-5239-4dbb-d996-e28ca27da241", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + } + }, + "source": [ + "x_test.shape" + ], + "execution_count": 34, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(223, 3)" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 34 + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "B5nvF8CUCV3Z", + "colab_type": "text" + }, + "source": [ + "\n", + "Esse nosso primeiro modelo será uma Árvore de decisão. O scikit-learn já contém uma implementação dela [aqui](https://scikit-learn.org/stable/modules/tree.html).\n", + "\n" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "io8_yKZGKqJa", + "colab_type": "code", + "outputId": "1576472a-d3cb-4bcf-8f4b-f8aefdc8a6d0", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 121 + } + }, + "source": [ + "from sklearn.tree import DecisionTreeClassifier\n", + "\n", + "# Instanciando o classificador\n", + "model = DecisionTreeClassifier(criterion='entropy', random_state=42)\n", + "\n", + "# Treinamento do modelo\n", + "model.fit(x_train, y_train)" + ], + "execution_count": 35, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "DecisionTreeClassifier(class_weight=None, criterion='entropy', max_depth=None,\n", + " max_features=None, max_leaf_nodes=None,\n", + " min_impurity_decrease=0.0, min_impurity_split=None,\n", + " min_samples_leaf=1, min_samples_split=2,\n", + " min_weight_fraction_leaf=0.0, presort=False,\n", + " random_state=42, splitter='best')" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 35 + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "fv6askV-ngY_", + "colab_type": "text" + }, + "source": [ + "**UHULLLLL! Temos nosso primeiro modelo de classificação \\o/**\n", + "\n", + "![](https://media.giphy.com/media/OU1marLMNNtnO/giphy.gif)\n", + "\n", + "Vamos ver a carinha dela (esse código para visualização da árvore nós encontramos [aqui](https://www.kaggle.com/jlawman/complete-beginner-your-first-titanic-submission))? :)" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "wXLwYat0F9qA", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# arquivo de texto que armazena a estrutura da nossa árvore de decisão\n", + "from sklearn.tree import export_graphviz\n", + "export_graphviz(model,out_file='titanic_tree.dot',feature_names=['Age', 'Sex', 'Pclass'],rounded=True,filled=True,class_names=['Não sobreviveu','Sobreviveu'])\n" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "MH2oh9cJHxOh", + "colab_type": "code", + "colab": {} + }, + "source": [ + "!dot -Tpng titanic_tree.dot -o titanic_tree.png" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3m-UB7ntM1ey", + "colab_type": "text" + }, + "source": [ + "Após converter o arquivo de texto, podemos visualizar a árvore abaixo. As cores ajudam a identificar a classificação dada pelo modelo:\n", + "\n", + "- Nós ou folhas em laranja significam que a nossa árvore de decisão acredita que o passageiro **NÃO SOBREVIVEU**\n", + "- Já nos nós e folhas em azul, a árvore acha que o passageiro **SOBREVIVEU**" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "2XqQGAlcHCja", + "colab_type": "code", + "outputId": "3f0121ad-ecae-479a-b5de-4de5c3ced199", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 589 + } + }, + "source": [ + "from IPython.core.display import Image, display\n", + "display(Image('titanic_tree.png', width=1900, unconfined=True))" + ], + "execution_count": 38, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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z7S52bl7B6De8xxUREREREZE/t9DQUOLi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\nEREREZHKmas6AREREZG/O2toBAaDkYJDe6ouh7A6YDBQdPRghbaio+nlMdX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plgTvw9ZaxbSPOxEwZi7rdh2nR8tGpk4rV0kp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PctqDx7j63JycnFm1fBknjx+nQ6fOKJX//u4eP5Y9ri9ZslRO2ZXoKFo1b0LZ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\naFzu8UVERERERG5kmv+W7FrOf+O3ziNhxxLqPvoF9m4+5SlTREREROQfQ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BYuXUHPoQ+Q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\nVu0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WbtlPn/a34ux46Tuw7FwLAD4etg+YOnomhs37TwIlrI16ubL14EWyciw4Olz6yd36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cnBz27dtHy5YttdbcKpVK4uPj2bJlS5mvMXPmTLKzs/Hy8tI67uPjQ2ZmJunp6UBJzTln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p6+WMX6USAOw6EUnfab/zeD1fto/rkf19Ze8pXpm1mej4ZMb3bWyRTHtPRdPlk7W0rF6KNaMe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pw8uNhrCAv2ZX9COpXVpjfA7Yg3XlMY2LG5xXbYmp/G1rMz3vS6xqFE42Tf4a38LLYJwNFO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\nZo5jSk+XTV5rz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x8R8cJxKJ0KBBA1y7dk1JyYhIXXF+cFKGGzduoGfPnoiNjS2wVgKQt17CnDlzOGcSERER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\niL8nK+4y0T+8R2rofowGHRp3P9ybB1Ou2/NYaSxvxhb/TQ4ODrRt25Y9e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4TaOhD41o4i\nY138m9N89mYiNi3i4KzO5OqysPUoT7l2g6j25BQUVuZNI4W1mnrj3ufi9/NJvXIajEZc/JtTe+Sb\nWKktB2JU6DCCqN8+xalyfRwr1i3V87lfKgdXWs77ifD1b3Pk9WAMWWnY+VSj1lML8Os4ssTyfp1G\noXb25Or2zzk4syNGgx4b9/K4VGtM1b5TsfUqGLhSpecE7DwrcnX75xya1QlDVhq2Hn5UaP8UVXpP\nNHtN7qdeIYQQQpRdzevX5I9vFvHOZ2vo8PR00tIz8fZwpX+XtrwyZhA2anWp6h3Wsz0//nGAZ2cv\nxdHeloNrlxcZ26pRHbZ/+S5vrviOVkNeIitbh5+PJ8N7d+TVZ4dgbWVlFq9Sqfh0/hReW/YlJy+E\nYzTm0bJhbZbMGI+djeU15zP9urF81RYa1a5Gff9/ZvJKN2dH/vhmEfM+/Jb2I18mLSOT6pXKs3D6\nOMYO6F5i+U6BTVizZBaLv9pA7R6jUSiUBDSszc6vF9KkTg2zWCulkh8+ms87n61h7OwlxCYk4+7i\nRPd2zZn3wggc7GWAsRBlQf0mLfjm5z18uuQtng4OIj1di4enN12fHMiYSTPQaEq3CGXwwGH88fNm\nZk98BnsHJ9btPFJkbKMWgXy5ZScrFr3B4E4tyM7KxLe8H70GjWDc1JlYWZu3mVVqNfM/+Jylr8/g\nwukTGI1GGjYP4NW3lmFja2dRf/8RY1n1yQfUrt8Y/7oNLI4/DM6u7nz7816Wvz2HET3bkZGmpVK1\nGkxfsJiBo8aVWD6wfWeWfrWeL5cvpHszfxRKJY2aB/DNT7up07CpWeyLr86nUtXqbFz1JWu/WkF2\ndhbunl60aNOeRZ99j1+Vahb1a2/dAsDeoXSTQQshzM3//Ac8XBz59LUxqFWmz6x+7ZtzMiyK5eu2\nczr8Kk1qVX60SQohSuXtHVcxGOGLITVxszO9v3vXc+fUjTQ+OxjL4ataAirJ96kQ/5SrG9+GXAM1\nX/gCawc3ANxb9CYt8hSxv3+GNvwwTv4BjzhL8U9p2bIlBw4c4I033qB169ZotVp8fHwYPHgwM2fO\nxMamdO3ZESNGsGnTJkaOHImTkxMnT54sMrZ169bs3buXefPm0bhxYzIzM6lYsSKjRo1izpw5WP+l\nPatWq/n666+ZNm0ax44dw2g0EhgYyPLly7Gzs2zPjhs3jqVLl9KkSRMaNmxocfxhmDZtGkuWLDHb\nN336dKZPnw7A8OHDWb16dZHl3d3dOXDgADNnzqRVq1ZotVr8/f15//33ee655x5q7kIIGZ8kRFmT\nmp0LgJ3aqoRI8bhrVrsyv3/wMu+t+pUuLy0hLTMLLzcn+gc15eVhXbFRq0pV75DOLdj652nGv/ct\njnY2/PnJq0XGBtStyq/LJvP2t7/QZvw7ZOn0VPByZWiXAGY81R1rK6VZvMramhXTRzDr0x84efGq\nqW+8blUWvjgQW41lX/7TPVvz0cY/aFjDj3r/Z+++43u6/geOvz47e4tEZFgRxAgxolaN2itqd9Pa\nq6hqaSmtPVuzlKrWrNpKS+0Ve4uIxA6yE9mf/P7IT3zTfCKJ+iTB+/l45EHO533ufZ9wHfeec88p\n45Ltc2OwszLnrznDGb90M00HTyc2PpGyJR2Z3P9tPmpbP9f6TXwrsHL8J8xctRPvnmNRKhTUrlSa\nnXOG4+Pp9lznSkhKZuexjHdmqrzzlcHzvteyLt8P7/kfWi6E+C9O3Y5lRUAY09qVoWWFjOdPtd2t\n+LKZG4sO3+N6eAJlHWS+ixBCCCGEEEIIIYQoGL7l3dk5YzBTfttF8+FziX2ciKOtFf4NqzG8a1NM\ntM+3dFvXJr5sOnSOvtN/w9LMhP3ff5pjbJ2Kpdg2bSCTfvmT+gOnk5CUQsliNnRvWpPPeryVbQxB\nq1Ex/9NujFmymVOBtzLGECp6MKVfR8NjCC39mLdhH1XLlsS7dInnak9+2VmZs2vGIL5Zvp1mw+YQ\n+ziRMiUdmdSnAx+1rptr/THvt6KMSzGW7zjC4s0HSUxOoZiNJQ2rlWP5F+9RuoTD88Uu2cwPv+/N\ncq6xS7YwdskWALq8WYPFn8kYwquqursdW4c2Ysafl2kzey9xiSkUszKhg09JhrzlhU7zfOPOnWu6\nsfXsHQatPIGFiZq/RzbJMbZWaXs2Dm7ItB2XaDptNwnJabjYmtKlljufNvdCrVRkideqlczp6cu4\njec4czMSfXo6NUvZ822napgaGCd/t24pFv5zjcolbajkYv1c7ckvW3MtW4c24rutF2k9cy+xiSmU\ncbRggn9V3n+jdK71+zfxxM3enB/3BdFk6m5iE1NwszfjnboeDG7mlaWd4zeeY8E/WTf++GbTeb7Z\ndB6ATr5uzHu3JgAf1CtNMUsdP+4LovGUv0lO0+NiY0p1dzuGNa+Au735C/wpCCGex+eff05qaiob\nNmzAwSGjv+7atSvHjx9n5syZ7N+/nwYNGhRylkKIZ4mMjOSNN96gc+fOtGzZEj8/vxxjJ0yYQFxc\nHKtWrcLe3h6A9u3bM2bMGEaPHs3gwYPx8vIqqNSFEEIIIYQQQgghhBBCCCGEEK+Z6m42bBlYh5l/\nBdF23lHiElMpZqmjfTUnhjQug06tzP0gBnSuUYJt5+8zePU5LHRq/hr2Ro6xNT1s+aNfLabtCqLZ\nrEMkpKThYmNKF18XhjUtk33+mErB7K6VGb/lCmduR6PXQ00PGyZ2qICpgflu79ZxZdH+ECq7WFGp\nhOVztSe/bM00bBlYh+92BNLmh6PEJqZSppgZE9pV4D0/11zrv+/nRjELHT8eDKXJzEMkp+pxsTHB\nx82GT5uWwd3+6bpxKqWCX3vXYOZf1xm46hxhMYnYmWtpWsGRz1uUw0KXfc5vdEIKAJYGPhNCFIzn\nXXN4d2Akq049oHVFe7ZdCi/otIV47cj6ikIULZP/vom9mZq5/uXQqDLuE9p623PmbhwLD93l3N04\nqrlYFHKWQgghhBCvFnmCKIqEqIRUZu+7za4rkdyPTcZCp6JqCXOGv+ma7Sbg0I1o5u6/w5k7caTq\n0ylpraNT1WL0reuM9n8GPd5deZnr4Yks7VaesdtvcPZuHGqlkmblbfmudSn2XIvi+wN3CA5PwNFC\nQ+86zvSq45xZ3/+ni9yKSmRZdy/G/RnC2btxpKdD9ZKWjGvhTkWnZ7+wffF+PDP+uc2x0Bjik9Nw\nttLSsoI9wxqWxNLk6WBHftr+oj2MT6F3HWfe8S3OqduxRj2XeLnER0ey9ccpnNm3naiH9zExt8Cj\nog/t+nxBKe+sG91eCdjHtqUzuHHxBPrUNOycXfFr3Y3m7w5CrX260fqcQZ24HxrEgBm/smraKEIu\nnkSl1lClfgveGT2L84d2sv2nmYSFBmHl4EizHgNo0v3pJkRTerUg/O5NBs5axZoZowm5dIr09HRK\nV65F1+Hf4epZ+ZltunX1HJsWTeLa6cMkPY7HxtGZ6o3b0fbjUZj+z4a7+Wn7i1ajaQes7RxRa7Iu\noFOidAUAHt0NxaNSdaPmIJ5PanwUt7fMJvLMLpKj7qMyscDcoyqu7YdjUapaltjoy4e4s20ucTfO\nkK5PRWdfkmJ+nXBu3hel+umf/eXZ75IYdp3yA5Zy47exxIWcRalSY1u1GaXe+Y6oc3u4s/17EsKC\n0Vg54tysN85Ne2XWvzjFn8RHt/AatIyQ1eOICzkL6elYlqmOe9dxmLtWfGab4m9e5PbmGcQEHiMt\nKR6tjTP2NVpSsu0wVKZPB+Xz0/YX7eGB1Sh1ZjjUfTtLuWO9rjjW65qlLCX6Ic7NelO84TvEBue8\nWZwwHiuPyvgMW5ZrXE4xzn4dcPbrkKVMY2FDrbEb81QfwKZsDXxHrc5DtpCuT8PKozI1v1ift/i0\njEkark0/yFP8i2Ji70KVfvNyjbP3bkDzlfeylRev2YriNVvl6VzFa7WheK02eYvNx3GFEEIIUXRV\nq1CGNbPG5BqXU0zn5g3o3DzrQmq21pbsWjolT/UBalX2YvP8CXnIFvT6NKpVKMOOxd/lKT4lNWMD\nyE+6tM5T/Ivi6lSMn74dkWvcm7WrEX96a7byNo3q0KZR3jZWNzPRMWHwB0wY/EF+0xRCFKAKlX2Y\nvTz3+8+cYlp06EKLDl2ylFnb2PHTpt15qg9QpUZtFqzelodsQZ+WRoXKPvz4+648xaemZNwzd/mw\nT57iXxQnF1e+m7c817jaDRpz5n5StvJGLdrSqEXeJpS27fIubbu8m+fcvpg8hy8mz8lzvHh5RMbE\nM2XFVrYfPsP9R1FYmJngU96DLz5oR40KpbLE7jt1hRkrt3Hiyg3S0vS4Frej21t+DOraHJ3m6TB+\np1FzCLp1n18nDGDU96s4eSUEjVpFC78qzBr2DjuPnmfmr9sJuh2Go50VA95uRt9OTxcIbzF4Cjfv\nh7Pq24GM/mENp66GkE46tSqW5rsBXalc5tkvQJ0LusWkZZs4fP4a8QlJODvY0K5BdUa91xYr86eb\nbean7S9ah0Y1cLS1RqvJOv2hQqmMDQlC7z+iupeHUXMQrz6Z01A4cxoalLHhjVLWmS9lPVHFOeO8\nNyOSqONu1BREESXjs4UzPmtTqQHWFd5AbWGXpdzCowoASQ9vgmfenlmIV0P16tXZuHFjrnE5xXTr\n1o1u3bplKbOzs2P//v15qg9Qp04ddu7cmYdsIS0tjerVq7Nnz548xaf8//1s//798xT/IkyfPp3p\n06fnKbZp06akp6dnK3dzc2PlypUvOjXxkpG+snD6SpmfJHIi95SFc08Zk5iKiUaZbUEjIQypWs6V\n377JfRwjp5hOb9ag05tZ55nbWpqzY9awPNUHqFmhFH9MHpiHbCFNr6dqOVe2Th+Sp/iUtIyx8d7t\nCnYjtJKOdvw4+oNc4xpV9yL67+zzIFvXrULrulVe2LlMdVqD5xHCEOm/C6f/Xn3qIWZaJW9XdchS\n3tXHka4+jkY9txBCCCGEEEIIIYQQhlQtW5Lfvvoo17icYjo19KFTQ58sZbaWZuyYlnVM4FnnqOnl\nzoZv8/Y+Rpo+naplS7Jlct7mu6T+//t1vdvkvMGIMZR0tGXxZz1zjWvk40nUjpnZyrs3rUn3pjXz\ndK68xk7s3Y6Jvdvl6Zji1VS5pA3Le/vlGpdTTIfqrnSonvX9DBszLZsGN8xTfYAaHnas7lcvD9lm\nXO+VS9rw+8C8jQGmpGXMNfuwfpk8xb8oLrZmzHs392uwQXlH7s/plK28TTUX2lRzybX+1x2q8HWH\nvI0tArSu6kLrqrkfV4iIiAgmTJjA5s2buXv3LpaWlvj6+jJu3Dhq1aqVJXbPnj189913HD9+nNTU\nVNzd3Xn33XcZPnw4Ot3TtfhatWpFYGAgGzZsYMiQIQQEBKDRaGjTpg3z589n+/btTJo0icDAQJyc\nnBg6dCiDBw/OrN+gQQNCQkLYtGkTw4YN48SJE6Snp1OnTh1mzpxJ1apVn9mmM2fOMG7cOA4cOEBc\nXBwuLi74+/szduxYrK2tn6vtL1qzZs1o3LgxDg5Zxw1r1MiYmxEcHEyDBgU7B0K8vOQ6LpzrOCws\njKFDh/LJJ59w9OjRZ8auWbOGRo3YIDTAAAAgAElEQVQaYW9vn6W8Y8eOfP7556xfv54xY3Jf90QI\nIYQQQgghhBBCCCGEEEIIIZ5XZRcrln2Q+76AOcV0qOZMh2rOWcpszDRs7F87T/UBarjbsPpj3zxk\nC2np6VR2sWJ937yN/T6ZP/ZBXbc8xb8oLjYmzOue+7yuBuXsuTetRbbyVpWL06py8Tydy1Sj4stW\nnnzZyjNP8ZM6VmRSx2eveSVeH7K+xMuz5nDk41RGbLpOO2976npYs+1SuFFzFEWLrK8o6yuKokX6\nz8LpP1tXtKeYhQaNKuv6iuWLmQFwOyrJ6DkIIYQQQrxu1LmHCGF8/dYFEvgwgcVdPPF2NicsNoUJ\nO0PosvwSf/atQml7EwCO34ylx4rLtKxox/5B1bDUqfnzSgSDN1wjPD6F8S09Mo+pUSmJeJzC6K3B\nfN3cA09HU1YEhDFxVyh3o5PQqZUs7VYeG1MVY7aH8NWOEKqXtMSnZMZNh1alIDw+lWEbr/NNSw+q\nuVgQGpHIe79eocvPl9g/yCfbw78nzt6Nw/+ni9Qvbc3m3t44WWk5EhLD8I3XORYaw6be3pkLy+e1\n7f8W8TiVylMCcv3Z7htUjbIOpgY/K+tgmuNn4vW2aPQH3Au+St+pK3DzqkL0wzDWzvqS6X3b8NWv\nByjuXhaAa2eOMLN/R2o0bsfEDScxtbDm9D9bWTr2Y2IjH9JtxNPN3VUaLXFR4ayc9CldPv0Ol9IV\n+GfdEtbPGUtk2B3UWh0DZvyGmZUNv00Zwappn1Gqsi+lvTMGGDVaHbGRj1g2rj/dRkymlLcvD24H\nM3dwZ2b0acvEP05iYWNvsD0hl04ztVcLKtRuxOhlf2PrWIKrJw+wbPwArp0+zOhlf6FUqfPV9n+L\niwpnaOPcNzOduOEETh6GB/ya9TC8mM7twPMoFApKlKmQ6/FF4Qhc2I+Ee4F49luMuZs3KdFhhKyZ\nwKVpXajy9Z+YFC8NQOy141ye2QO7Gi2p9u1+1KaWRJz+k2tLBpMSE45H9/GZx1SqNaTERhD8y2g8\nun6NqYsnYf+sIHTdRJIi7qLU6Cg/cCkqMxtCfhtDyKqvsCxdHYvSGQtBKdRaUmPDuf7TMDy6f4NF\nqWokPgjlypz3uDS9Cz7f7s+2Sd8TcSFnuTjFH+sK9fH+YjNaWydirhzh+vLhxAQew/uLTSiU6ny1\n/d9S4yIIGFI5159ttYn7MHU2fN3FBAVg7lopy8BITkydy+Z4HCEMMrBp3rPc2DofnbUjJd7IvriQ\nEEIIIYQoGPn8Lxyzfv6d4va2dG3VyCj5CCHEq8rQRvPP8vP8mTg4FqdVp+5GykiIouODbxZxNeQe\nK8b3pUo5N8LCo/lywVrafDqdA4u/oqxrxgtER85fo+PImbRrUIOTKyZibWHK1gOn+fi7pTyMimXK\nwG6Zx9SqVYRHx/HprJV8N6ALFTxcWLLpH8YuXM+dB5HotGp+mzgAG0szRsz5jc++X4VvxVL4Vsh4\nNqvTaHgUFUv/ycuYPKgbvl6lCL77gM6j59J22AxO/jIRe2vDkzJPXw2hxeCpNKpRgb/njaaEgy0H\nzlxlwNRlHD53jb9+GI1apcxX2/8tPDqOUu2H5vqzPbFiIp5uTgY/6/92M4Pl54Nuo1AoqOBRItfj\nC5EbmdNQOHMaPqpt+Lq/H5sMgJudzuDn4tUn47OFMz7r1MTwhkPJkfcB0BUr2Be8hciv/N7PTps2\nDScnJ3r2zH3jKSGKGukrC6evlPlJIidyT1k495TRCWlYaFUGPxPiZZff/9vOXfM3xe2s6NIkb5ui\nCiGk/y6s/jvgZgyVnMyzLNIihBBCCCGEEEIIIYTIu/yOIcxZ/w/FbS3p/GYNI2UkhDCW/L5PO393\nII5WJnSq4WqchIR4RXXr1o1Lly6xbt06fHx8uHfvHiNGjKBJkyacPHkST8+MteQOHjxI8+bN8ff3\n58qVK1hbW7Nx40beffddHjx4wOzZszOPqdVqefToEf3792fGjBlUqlSJBQsW8Nlnn3Hr1i1MTEz4\n448/sLW1ZdCgQQwZMoTatWtTu3bG5mA6nY6HDx/y4YcfMnv2bGrVqsX169dp06YNTZo04cqVKzg4\nOBhsz4kTJ2jQoAFNmzbl8OHDuLi4sHfvXnr16sWBAwc4dOgQarU6X23/t0ePHlGsWLFcf7aXL1/G\ny8vL4GeDBg0yWH7nzh0ASpc2PA9QCEPkOi6c69jLyyvHz/7XrVu3CA8Pp2LF7JselS1bFo1Gw8mT\nJ3M9jhBCCCGEEEIIIYQQQgghhBBCvE7yPX9s7w0cLXV0qi7r8wphiKwv8fKsOfz51mBS9elMbFWK\n7Zcicj2/eLXI+oqyvqIoWqT/LJz+82M/Z4Pll8LiUSjA09Es1+MLIYQQQoj8kZUxRaFLStVzMDia\nxuVsqOFqiU6txM1Wx8yOZdGqFewNisqM3XklAp1aydi33CluqcVMq8S/igN13K1Yc+ZBtmPHJqYx\nqL4LPiUtMNeq+NjPGXOtioBbsczqUAY3Wx1WJmr618sYYDh4IzqzrkqpIClVT/83SuDnYYWpRolX\ncTPGvOVO5ONU1hk43xPj/wzFxlTN4i6elHEwxVyroqmnLaObunHmThxbLoTnu+3/Zmem5s54v1y/\ncroBEyInKcmJXD6+D+83mlGmSi00WhMcXNz5cPwCNBodF47szow9s3cbGp2OzsMmYlPMGZ2pGXVa\ndcGzRj0Obf4127ET4mJo9eFwSnv7ojMz5613BqAzMyfo7DE+Gr8ABxd3zCytafnBMACuHN+XWVeh\nVJKSnEiL94dS3rc+WhNTSpatROehE4iLjuDwlt9ybNOaGaMxt7al39QVOHmUQ2dmTpX6Leg0aBw3\nLpwkYNcf+W77v1nY2LPkVEyuX04ehl98NSQm/AE7V8xl9+pFtPl4FCVK5/5Sqyh4+pQkoi8fxKZy\nYyzL1ECp0aFzcKPsRzNRaLREXdibGRtxeidKjQ73LmPR2hRHqTPDoY4/Vp51eHBoTbZjpyXE4tJ6\nEBalfVDpzHF+62NUOnNigwIo89EsdA5uqM2sKNGyPwDRVw5m1lUoVehTkijRsj9W5f1Qak0xK+mF\ne+cxpMZF8uDQuhzbFLpmPGpzGzz7L8bUqQwqnTm2VZvi1mk0cTfOEB6wJd9t/ze1hR1+S+/k+vWs\nB/hJj26itXXi4eH1nBvfnGN9SxMwqCLXFg8kOfJejvWEeFHS9WmkJScQumMxdw+uw+u9iSg1svGs\nEEIIIURRlqbX8zgxie9XbuS3rXuYPqoPJlptYaclhBCvHH1aGokJj1m5aC5b1q5k1Lez0OkMTzoT\n4lWRmJzCvlOXaVbbm1qVymCi1eDu7MCCUR+i02jYHXAhM3bbwTPotBom9u2Ms4MNZiY6ujSrQ72q\nnvy641C2Y8fEJzD8nVb4ViiNuamOAZ3fwtxUx7GLQSz4/CPcnR2wtjBjWI+WAOw7dSWzrlKpIDE5\nhaHdW1C/WnlMTbRUKl2SCX06ExETx29/Hs6xTaPnrcHW0pwV4/tRztUJc1MdLfyqMO7jTpy8fIM/\n/gnId9v/zd7agpi9S3L98nQz/HKGIQ8iY5i7ZieLNuxm1Htt8PKQl83EfyNzGorWnIaHcSn8eOQe\nXo5m1HS1zFdd8WqQ8dnCG581JCXmIff++hEzFy8sy9bMV10hiqK0tDQeP37MrFmzWLFiBXPnzsXE\nRO5nxctF+sqi1VcKIfeUhXdPGZOYilqlYPo/t3jzhzOUnnAMn+kn+XLbDaISUnP+QxPiFZGm15OQ\nlMy83/ew6q9jTB3QGROtprDTEuKlIP134fXfN6OScLLSsv7MQ5ovPEfpCceoODmAgb9f415Mcs5/\naEIIIYQQQgghhBBCiDx7MoYw/499rN59gin9/DHRGl7IWAjxckvTp5OQnMaivddYGxDKt52qotOo\nCjstIV4aiYmJ7N69m5YtW+Ln54eJiQmlSpVi2bJl6HQ6du7cmRm7adMmTExMmDZtGiVKlMDc3Jye\nPXvSsGFDli9fnu3Y0dHRjB49mtq1a2NhYcGwYcOwsLDg8OHDLFu2jFKlSmFjY8OoUaMA2LNnT2Zd\nlUpFYmIin332GY0aNcLMzIzKlSszdepUwsPD+fnnn3Ns06effoqdnR3r1q2jfPnyWFhY0KZNGyZN\nmsTx48dZu3Ztvtv+bw4ODqSnp+f65eWVv/X0wsLCmD17Nt7e3rzxxhv5qiteX3IdF63r2JCwsLDM\nc/6bUqnEzs4uM0YIIYQQQgghhBBCCCGEEEIIIUTepenTSUhJY/H+ENadvMPEDhXQqWXbYiH+TdaX\neHnWHN5w7hFbL4bzbevS2JvLGjqvG1lfUdZXFEWL9J9Fp/98GJfCwkN3+enYfYY2LIlnsfz1vUII\nIYQQInfyVFUUOo1KiYO5hj8vR7DjcgSpaekAWOpUXBhVk49qP93Yb+xb7gR+WQsXa12WY7jZmhCb\nmEa0gYXZa7lZZf5erVRgY6rG1UaHo+XTTZ6L/f8DuYdxKdnqNyprk+X7uqUyjncp7LHB9sQmpRFw\nM4Y3Slmj/dfAxZvlMo51+k5cvtsuREFRq7VY2Rbj9D9bOfXPFtJSM64LU3NLZv8TQpNufTJjOw+d\nyLyD97BzKpnlGA4l3EmIi+FxTPYHCeV8/DJ/r1SpMbeyxaGEG9YOT/++W9k7AhAdnv3ly0p1m2T5\n3su3AQC3rxneSDQhPpags0cp71sftTbrvx3edZsCEHwhIN9tN6YHt4LpXd2KT5uVZfPiSXQaPJ62\nH39WIOcW+adUa9BYORBx6k8iTu0gPS2jL1KZWlJzzgWcmnyUGeveZSy15geis3PJcgyTYm6kJcSS\n+jiaf7MqVyvz9wqlGrW5DToHV7TWjpnlGqtiAKREP8xW36ZSo6zH86oLwOPblwy2Jy0hlphrAVh7\nvYFSrc3ymY33mwDEBZ/Od9tftHR9GvrkRKIvH+LBwdWU7TUb3znn8ey3kNigAM5PbE3q4xijnV8I\ngPtHN7G7V1lCdiykcr8fcKrdtrBTEkIIIYQQufh9536Kv/E236/cyNKJw/FvVq+wUxJCiFfSzk3r\nqFvGnl8WzubbH5bRrG2nwk5JCKPTqtUUs7Fi68HTbDlwipTUNAAszU0J2TybPv5Pxzcm9uvMvR3z\nKFncLssx3J0diIlPICo2+zikX+Vymb9Xq5TYWpnj5uSAk711ZrmjbcY4ZlhE9mfNTWpVyvJ9A5+M\nhTYvBN822J7Y+ASOXgiivk95dJqsi/s3reUNQMDl4Hy33ZiC7zzAqlFvynb8lEnLNzO+Tyc+e0+e\n2Yn/TuY0FJ05DVEJqXy46gqxSanM8S+LSqko0POLokHGZwtnfNaQ1Pgornz/IakJsZTtPQeFUjYI\nES+/NWvWYGlpycyZM/nll1/o3LlzYackRL5JX1l0+kohQO4pC/OeUp8Oyal6zDQq1nxQibMjfZnY\nyoOtF8Npteg8cUlpRj2/EIVtw96TlGjzKT+s383iz9+nQ8PqhZ2SEC8N6b8Lp/9O06eTmKLnUHA0\nq08/YHbHspwf5cvCzp4E3Iyl9eLzxCRm/3kKIYQQQgghhBBCCCHyZ8O+M7h0HM0PG/axaGRPOtSv\nWtgpCSGMZNPp25T5bBML/7nGD+/WpG21krlXEkJk0mq1ODo6snHjRv744w9SUjLG7qysrHj06BGD\nBg3KjJ02bRqxsbG4ubllOUapUqWIjo4mMjIy2/Hr1Xv6jrtarcbOzg4PDw+cnZ0zy4sXLw7A/fv3\ns9Vv3rx5lu/ffDNjPt25c+cMticmJoZDhw7x5ptvotNlHd9s0aIFAMeOHct32wtCREQE7du3Jzo6\nmhUrVqBSybx1kTdyHRed6zgnCQkJQEa+hmi1Wh4/NjwfQgghhBBCCCGEEEIIIYQQQgghRM42nb1P\n2S//ZuH+EH7oXoW2VWQ/VCEMkfUlXo41h+/HJDNm+w1aeNnRztu+QPMSRYOsryjrK4qiRfrPwu8/\nQyIScfn6CNWmnWDm3tt80dSNoQ3lnREhhBBCCGNQ5x4ihHEpFbC8pxcD11+j9+qrmGqU1HC15M2y\nNnSr7oiN6dO/pkmpen4+Hsa2S+HcjEwkMiEVfXrGgq8A/38Pk0mlVGBpkvWFTYWCLMfMKMt4WPfk\nOE+oVQpszbLGPqn7yMANG0BYbDL6dPj97EN+P5v9QQvA3eikfLddiIKiUCoZNGctP37Zi/nDe6I1\nMaVMldp4121KvfbvYm5tmxmbkpzIP2uXcHL3Jh7dDiE+JhJ9Whp6fcYGCU9+fUKpVGFqYZX1fAoF\n5la22coA9Gn6LOUqtQYL66wboz7JJzr8gcH2RD+8R7pez9Htazi6fY3BmMj7d/LddmNydC3NklMx\nPI6J4srJA6yaMpLjO9czfMFmzKxscj+AKFgKJV6Dl3Nt8UCuzuuNUmuKZZka2FR+E8d63VCbP/0z\n06ckEfbPz4Sf3Ebiw5ukxkeCXk/6k2vlX9eMQqlCZWr5r/Mpshwzoyjjmkn/d32VGrVF1r+3aouM\nuikxjww2JzkqDNL1PDzyOw+P/G4wJinibr7b/qIpFEpQKElLiKH8wKWozTI2PLau2IDS703m8qx3\nuLdrEa4dRhotB/HqqvHZqjzFOdf1x7muv5GzEUIIIYQQebFp3jd5iuvSshFdWjYybjJCCPEKm79q\na57iWvp3o6V/NyNnI0TRolQqWDtpEL0m/kjPsfMxNdFSu2IZmtb25t2W9bC1Ms+MTUxOYcnGf9i0\n/yQhdx8RGRtPWpqeNH3GuMiTX59QKZVYmZtmKVOgwNbSPGvZk/GVf9XXqFXYWVlkKXuSz4OI7BPP\nAe6FR6PXp7Pmr6Os+euowZg7DyLz3XZjKu3iSMzeJUTFPubAmSuMnLOK9buPs3nGcGwszQokB/Fq\nkjkNRWNOQ2hEIu+svMzD+BRW9KyAt3PB/NsiiiAZny2U8dl/S3wQyuXZ75AS85AKQ1Zg7uZdYOcW\n4nn8+eefeYrr0aMHPXr0MHI2QhiZ9JVFoq8U4gm5pyy8e8otH2f/P2rrivYoFAo+Xn2VeQfvMKqJ\nm4GaQhRtGyYPzFNc58Y16dy4ppGzEeLVJP134fTfSoUCpQJiktJY2q081v9/rgZlrJnctjTv/HKZ\nRYfvMbKxq9FyEEIIIYQQQgghhBDiZfb7xE/yFNf5zep0frO6kbMRQhjTqn718hTnX8MV/xryXF2I\n56VUKtmyZQs9e/bE398fMzMz/Pz8aNGiBR999BF2dk/XwktMTGT+/Pn8/vvvBAcHExERQVpaGmlp\nGXPonvz6hEqlwtraOkuZQqHIcswnZYbqazQa7O2zbmjzpG5YWJjB9ty9exe9Xs/KlStZuXKlwZhb\nt27lu+3Gdv36dVq1akVYWBhbt27Fx8enwM4tXn5yHReN6/hZzMwy3vtMTk42+HlSUlJmjBBCCCGE\nEEIIIYQQQgghhBBCCFjV2zdPcf4+zvj7OBs5GyFefrK+xMux5vDwTdcBmNS2dIHlJIoYWV9R1lcU\nRYr0n4Xff3rYmXBnvB/RCakcDolhzPYbbLrwiNXvVcxct0kIIYQQQrwY8r8rUSRULWHB/kE+BNyK\nZW9QFPuCopiwK5TvD9xhzfsVMx+o9V0byF+BkXzayJVOVRwoZqFFq1Ywakswq089eOF5Kf//5iyL\n9CefPbtujxqOTGtXJtdz5LXtQhQkj4o+TNxwkqCzR7l4eDcXjvzNutlj2L5sBsMXbMbNqyoAi0Z9\nwNn9O2j7yef4te6GlX1xNFotKyYO4eCmX154XgqlMltZenrGRak08Nn/qt/xfd4f+32u58hr2wuC\nmZUN1d9si72TKxN6NmD7spm8PSRvm9uLgmXhURWfb/cTGxRA1IW9RF3cR+jaCdzZ9j0VR6zJ3Pgu\ncGFfIs/+hWu7T3Go0wmtdTEUGi3BP4/iwcHVLzwvhcLAdfHkeaOhz/6HY4MelHl/Wq7nyGvbXziF\nAo2lPWpza9RmWV+It/L0A4WC+JsXjHNuIYQQQgghhBBCCCGEMMCnvAcnV0zk6IUgdh+/yN8BFxiz\nYB0zft3O5hnDqVouY3PpD8YvYsfhs3z+flu6veVHcTsrtBoNQ2as4JftB194XobGPPM6vvJ+6/p8\nP/L9XM+R17YXBBtLM9rWr45rcXsafDKBmb9t55s+bxfY+cWrSeY0FO6chhO3YvnwtyuYa1Vs7OWN\nl6Ms4vu6k/HZQhif/R+xQSe48v2HqEzM8R69ETMXL6OfUwghRP5IX1m4faUQ/yb3lEVrnvybZW1Q\nKOD07bgCP7cQQoiXh/TfBd9/KxRgb67B2kSdbUERP3crFAq4cC/eKOcWQgghhBBCCCGEEEIIIYQQ\nwhBfX1+uXLnCoUOH2LlzJzt37mTkyJFMmjSJv//+Gx8fHwC6du3Kli1b+Prrr3nnnXdwcnJCp9PR\np08ffvrppxeel6H3wfL6rljv3r358ccfcz1HXttuTIcPH6Z9+/ZYWFhw8OBBvL1l/p/IP7mOC/c6\nzo2zc8bGgw8fZt88JTU1lYiICBo0aFDQaQkhhBBCCCGEEEIIIYQQQgghhBDiNSLrSxTtNYdXn3rA\n3qAoFnb2xNFCY/R8RNEl6yvK+oqiaJH+s2isr2htqqZlBTtcrHW0XHSOHw7e4ctm7gV2fiGEEEKI\n14E69xAhCoZCAbXcLKnlZslnjV05eSsW/58uMnPvbX7qXp6w2GR2XY2kfWUHPm1UMkvd21FJRskp\nOVVPbGIaliaqzLKIhFQAHHJ4mOdspUWpyF9OubXdkIjHqVSeEpDrsfcNqkZZB9M85yLEEwqFgnLV\n/ChXzY8O/cdw/dxxpvRqwebFkxk4cxVRD+9xZt92ajV/m3Z9RmepG37vllFySk1OIiEuBlMLq8yy\nuOgIAKzsHQ3WsXV0QaFUEn7vZp7Pk1vbDYmLCmdo41K5HnvihhM4eXhmK4+4f5vNiybhWaMeddt0\nz/KZc+mMfwfuBl/JcxtEIVAosCxXC8tytXDt+Bmx109ycbI/tzfPpPzAn0iOCiPyzC4carWnZLtP\ns1RNCr9tlJT0qcmkJcSiMrXMLEuNy7hmNFYOButo7ZxBoSTpUT5yyqXthqTGRRAwpHKuh642cR+m\nzmUNfmbuXpm44FPZytP1qZCejkKlzXsbhPiPTk7tTuTV4zRder2wUxFCCCGEEAa0H/AVR05f4sHh\n9YWdihBCvJb6d2/D6WOHORIcUdipCGF0CoUCv8rl8KtcjjG9OnD84nVaDJ7C5OWbWfXtQO49imL7\noTO83bgWoz9ol6XurfvhRskpKSWVmPgErMyfjhlGxGRsdu1oa2WwjksxW5RKBTfD8p5Tbm03JDw6\njlLth+Z67BMrJuLp5pSt/HZYBJN+3ky9qp50b143y2fl3TMWAr0ScjfPbRDiWWROQ+HMaTh1O5Ye\nKy5TrpgpP/f0wsFcXrwS/0/GZwt8fBYgNvgUl2f2wLREObwG/5xju4R42bRo0YKDBw8SFxdX2KkI\n8eJIX1kofaUQOZF7yoK9p0xJS+fKg8dYaFWUsjfJ8llyqp70dNCpn71IghCvEv/Pf+DIhevc2zqr\nsFMR4qUi/XfBPxOu7GzOqdvZ781T9emkp4NWlcuKKkIIIYQQQgghhBBCiHzrNGYxRy4Gc/ePyYWd\nihDiBem+4CDHgsMJnta+sFMR4pWgUCioV68e9erVY8KECRw5coQGDRowfvx4Nm7cyN27d9m8eTPd\nunXj66+/zlI3NDTUKDklJSURHR2NtbV1Zll4eMY7YMWLFzdYp2TJkiiVynzllFvbDXn06BHFihXL\n9diXL1/Gy8srx8+PHj1K8+bNqVChAlu3bsXR0fAag0LkhVzHhXMd50WJEiVwcnLi4sWLBo+fmppK\nzZo1/9M5hBBCCCGEEEIIIYQQQgghhBBCQPclJzh+I5Lr3zYr7FSEKJJkfYmiu+bw5bDHAPRdF0jf\nddmP0WTeWQBCv66DWilrUrzyZH1FWV9RFCnSfxZs/3knOomZe2/j527F29WyzvP0LJYRH/ggIc9t\nEEIIIYQQeaMu7ASEOBISw8Dfr/FLTy8qOplnltdwtcTRUkPk4xQAklLTAbAzy/rX9trDBI6GxACQ\nnp7+wvPbHxxF64r2md8fvhENgJ+7tcF4c62K2u5WHA6J4UFcCo7/c7N2LDSGUVuCmeNflqolLPLc\ndkPszNTcGe/3X5snRDZXTx5kyZe9GTx3Ha6eTx++lalSCxsHJ+KjMh4OpiYnA2BhY5el/r0bV7l6\n8iBgnGvy0tE91Gja4Wm+AQcA8Kxez2C8zswcT5+6XD1xkOjwMKztn77geu30YVZMHEKvCYvxqOiT\n57YbYmFjz5JTMc/dLgtbe47vXM+tq+fwa9UVhfLpJhM3L2cMFDi6lnru4wvjibl6hGs/DsRryC+Y\nu1bMLLcsUwONjSMpcZEApKdmPJxTW2S9ZhLuXSPm6tGMGCNcM1EX92Pv2zrz++grhwGwLm+4D1Hp\nzLHyrE3M1cOkRD9AY/10EYSYwGMErxhF2d5zsPComue2G6K2sMNv6Z3/1DaH2u2JOr+H6Ev7sa7Y\n4Gme/99Gq3K1/tPxhXid6FNTuLjkU+4eXE/57l/h0bpftpgb2+YTuGpCjsd46+dbKFRyiymEEEII\n8aKdvHiN6T+tJeD8VcKjYihZvBjtmtRl9MfdsDDPefJiXHwCtbsOJOROGAHr5lGxrHsBZi2EEK8O\nvV7P6p8WsH7Fj9wOCcbK1paGb7Vh6JhvsbS2yRJ7MziI778bS8Dh/cTHxlDCzZ12Xd/jw4EjUCpl\nY+FX3cGzV+k9YQnrpgymchnXzPJalcrgZG9DREw8AMkpGRM+7awtstS/GnqPg2evAsZ5VrznxCU6\nNKyR+f2B0xnnqlfN02C8uamOupU9OXjmKmER0RS3ezo2evjcNYbMWMHiL3rhU94jz203xN7agpi9\nS567XfY2Fqzfc5xzQbfo2i+itWcAACAASURBVMwP5f+8cHH22k0ASrnIYr/iv5E5DYU3p+FWVBI9\nf7lCGQcT1rxfEQudKvdK4pUn47OFNz6b9OgWV2b1xMSpDBVHrEFlYpF7JSFEgYqNjaVq1arcuHGD\n8+fP4+3tXdgpiUIgfWXh9ZVCGCL3lIVzT5mUqqfD0gv4uFiw/sNKWT7bfS0KgHqlDbdRCFG06NPT\nWbxxH8u2HuTG3YfYWprTwq8y33zcAWsL0+eOFeJZpP8uvGfC7Ss7sOdaFPuvR9OgzP+MTf3/z7OW\nu9V/Or4QQgghhBBCCCGEEOLVk5yaxuDZa1i9+wQTerdlUKc3DcZdv/OQb5Zv5+C5IGIfJ+JW3I4e\nzWoxtEtjlApZ9F+IouL6g1gmbb3IgWsPSUpJw9XOjHY+Jenf2BNznTrfsUkpabiP2PjMc/b0K8WM\nbtWN1ibx8tq3bx89e/Zk27ZtVK1aNbPcz88PZ2dnwsPDAUhKypiL5+CQdcOOy5cvs2/fPsA444Z/\n/fUXb7/9dub3//zzDwANGzY0GG9hYUH9+vXZu3cv9+/fx8nJKfOzAwcO0KdPH1asWIGvr2+e226I\ng4PDf25vSEgILVu2pHz58uzevRtLS8vcKwlhgFzHhXcd50ePHj2YP38+Dx8+pFixp5uTrFmzBrVa\nTbdu3QosFyGEEEIIIYQQQgghhBBCCCGEEEXL/L03mLDtao6f35rSHLVSQVKqHo/Ru555rJ61SzL9\nbVmXTWQl60sU/TWHx7f0YHxLj2zlvwSE8fnWYHYPqIqXo9l/ykUUfbK+oqyvKIoW6T8Lp/+0N9Ow\n6fwjLt6Lx79qMf5nSw7O38vYC8TDzuS5jy+EEEIIIQyTXQdFoavmYoFaqWDIH9c5fTuOpFQ9UQmp\nLD58j7vRyXSvXhyAkjY63G1N2HE5gisPHpOUqmfPtUh6r75Km0oZN0ln78aRpn9xN2ImGiWz9t5m\n//VoElL0XA57zLd/heJooaGtt32O9b5s5o5KoeD9Xy8T9CiBpFQ9R0JiGLIhCK1KmfnAL69tF6Ig\nlapUA6VKxU9f9SX4wglSkhOJj45k18ofiAi7Tb0O7wFg7+xKMRcPTv+zlTtBl0hJTuT8wV3MG94T\n32YdAAi5eAq9Pu2F5abVmbLlx6lcOvoPyYkJ3L52gfVzvsLavjg13/LPsV6nId+gVKqYO7gz90MC\nSUlO5OqJAywd+wlqrQ6XshXy1XZj0OpM6TLsW0KvnOXnCYN4dPcmyYkJBJ46xPJvBmJmaU2T7v2M\ndn7x/CxKVUOhVHN96RDigk+jT0kiNT6Ke7sWkxxxl+L1uwOgsy+JSTF3Ik7v4PGdK+hTkog8t4er\n83pjX7MNAHE3zpL+Aq8ZpdaE21tmEX1pP/rkBB7fvkzo+m/RWDtiX7NtjvXc3/4ShVLF5Tnvk3Av\nCH1KEjFXjxC0dAhKjRYzF698td1YHGp3xKq8H0FLhxITeAx9cgLRVw5z49cxmDh64NjAuOcX4lWR\nEh/NySndeBwW+sy41PiMgY8mi6/SfOW9bF8KlfqZ9YUQQgghRP4dPHWBZh99hlajZvfyadz85zfG\nDXqPxWu20rbfWPTPeBb62fQfCbkTVoDZCiHEq2nyF0OZN2UcAz8fz4HAMKYu/pU92zcxoEe7LJMD\nHz0I4/22jYiNjWbljoMcuv6IYWMnsXTOFCZ/MbQQWyAKSo3ypVCplPT97idOXA4mMTmFyJh4fli7\ni9sPInivdT0AXIvb41GiGFsPnObSjTskJqew6+h5eo6dR4dGvgCcuhJCml7/wnIz1WmZumIL/5y4\nREJiMheu3+arRespbmeNf6OaOdb7pm8nVEolnT+fS+DN+yQmp3DgzFU++W4pOo2aCqVc8tV2YzDV\nafm2XxfOBoYyaPrP3Lz/iITEZA6dDWTg1OVYW5jRz7+J0c4vXg8yp6Hw5jR8ue0GSal6FnUpn+NL\nWeL1I+OzhTc+e+PXL9GnJFG+/yJUJhZGPZcQ4vkMGzaMGzduFHYaopBJX1l4faUQhsg9ZeHcU1ro\nVIx405UjITGM+zOEezHJxCamseVCOF/vuEFFJ3Pe8ZV5+kK8DEbMXcPEZVsY82FbQjdOZ9nYj9h6\n8AydRs/LtohDfmKFeBbpvwvvmXDHyg74eVgx9I8gjoXGkJCi5/CNaMZsu4GHnQndqzvmfhAhhBBC\nCCGEEEIIIcRrIyouAf8vF3Hj3qNnxoVFxtJ8+PfEPE5g95yh3NowiW96tWXGmr8ZOe/3AspWCJGb\nwPsxNJu2h4dxSWwa3JAL37ZhRMuKzNsdyCfLjz1XrE6j4v6cTga/lvfOWES9vU/JAm2neHnUrFkT\ntVrN+++/z7Fjx0hMTCQiIoKZM2dy69YtevXqBYC7uzulS5fmjz/+4MKFCyQmJrJ9+3b8/f3p3Lkz\nAAEBAaSlvbi5eKampkyYMIG//vqLx48fc+7cOUaNGoWTkxNdunTJsd6UKVNQqVS0adOGK1eukJiY\nyN69e3nvvffQ6XR4e3vnq+3GMnDgQBITE1m3bh2WlpZGPZd4tcl1XHjXcX588cUXODg40LVrV4KC\ngkhMTGT16tVMnz6dMWPG4ObmVtgpCiGEEEIIIYQQQgghhBBCCCGEKCQxiSkAXP2mCfemtcj2pVYq\nANCplQY/vzetBcs+qA5Au6rOhdYOUXTJ+hKy5rB4Ocj6irK+oihapP8snP7TRKPkq+YenL8Xz8jN\n17kVlURCip6joTGM2HQdKxM1H9VxMtr5hRBCCCFeV+rCTkAIU42SPz7yZsbeW3yy9ioP41Kw1Kko\n62DKws6emTc7SgUs6ebJVztCaPfjBVRKBb6uFizs4omZVsmFe/F8+NtV+tcrwagmL+aFLY1KwayO\nZflmZyhn78ShT0/H19WSCa1KYapR5ljPp6QFm3p7M2vvbdovuUBcUhrFLDS083ZgcAMXdGplvtpu\nLN/sDGXR4btZyibsCmXCrlAA/Ks48H2nckbNQRQ9WhNTRv20k80LJ7Fw5HvERDzAxNwSZw9P+kxZ\nTs1m/gAolEr6z/iV1dNG8d0HTVCp1JSpUou+U5ajM7Pg5pVzfD+sGy0/GEbHAWNfSG4qjYYPxy9g\n3awvuXHxJOl6PWWr1qH7Z1PRmpjmWK+0ty+fL/+LLYsnM+nDZiTExWLtUJyab/nT+qMRaLQm+Wq7\nsTTq3Bsre0f+/m0B47v6kZqSgp2TC6W8fWn78SiKuXgY9fzi+Si1pnh//ge3Ns3g6oJPSIl5iMrE\nElPnsnj2Xfj0QbpCieeAJYSs+ooL37ZDoVJhUcYXz74LUerMiL95gavff0iJVv1x6zjqheSmUGko\n+9EsQtd+kzF4kK7HsqwvpXpMQKnN+ZqxKO2D9+hN3N4yiwuT2pOWEIfGuhgOtdrh0nowSo0uf203\nEoVSRYWhv3B78yyClgwmOeo+Ggs7bKs2w7XjZ1k2IAxd+w13dy7KUj907QRC104AwKGOP+U+/t6o\n+QpRFKXER3NsfFucarfFoWpjjo1rk2Ns6uNoAFQ6s4JKTwghhBDitTfu+xU42Frz44ThaDUZj/M7\nvVWfkxevMWfFBk5fDqJGpezP7/48EMDPG3fRockbbNx9qKDTFkKIV8a5k8dYu3wRX81YQONW7QGo\nXrseQ8d+y4oFswm5HkipsuUBWDzzOx7HxzFl4S9Y22aM7zRq0ZaPh41m7rdj6N57QGaseDWZmmjZ\n+f0oJi3fzHtfL+RBZAyWZiZ4ujmz/Os++L9ZEwClUsGvE/ozau5qmvT/DrVKRa1KZVj+dV8sTHWc\nu3aTbl9+z7AeLRnbq+MLyU2jVrFg1Id8uWAdJ6/cQJ+eTp1KZZk6uDumJtoc6/lWKM1fP3zO5J+3\n0GzgJGLjEyhuZ41/45qM6NkaE60mX203lt7tG+Foa8WC3//Gr9d4UlJScXG0w7dCKUa91xaPEsWM\nen7x6pM5DYUzpyEhRc/uwEgA/GafMhjTvboj09uXMVoOomiS8dnCGZ/VJycQeW43AKdG+RmMcazf\nnTIfTDdaDkKIZ9u2bRtLly6lU6dO/P67bFL1OpO+svDmMsn8JGGI3FMW3jz5fm+UwM1Wx5Ij93hr\nwVlik9JwtdHRs0ZxBtZ3eWYbhRBFQ8DlGyzdcoC5n/akbb2qANStXJbxH3fgh/W7uXb7AZ6uxfMd\nK0RupP8uvP5bpVTwyzsVmLX3NoM3BHE/Nhk7Mw3NPG35rImrLOAlhBBCCCGEEEIIIYTIFBWXQPNP\n59KhflWa1qxAs2Fzcoyd9tsu4hKSWDrqXeyszAFo5efNyO7NGL9sG33aN8DT1bGgUhdC5GDilguk\n6vUs61UHO/OM+UDtfUpyOjSChf9c4+j1R9Qp45DvWEPik1L5Yv0Z2vuUpEF5uf6FYWZmZhw4cIBx\n48bRuXNnwsLCsLKywsvLizVr1tClSxcAlEolGzZsYMiQIfj5+aFWq/Hz82PNmjVYWFhw+vRp2rdv\nz6hRo5g4ceILyU2r1bJs2TJGjBhBQEAAer2eunXrMnfuXMzMcl4XqHbt2hw6dIhvvvmGN954g5iY\nGJycnOjatStffPEFJiYm+Wq7MTx+/Jht27YBULp0aYMxvXr1YsmSJUbLQbw65DounOsYYMSIEcyY\nMSNL2ciRIxk5ciQAPXv2ZOXKlQDY29tz6NAhvvjiC/z8/IiJicHT05PZs2fTt29fo+YphBBCCCGE\nEEIIIYQQQgghhBCiaItOSAXATPd8Wy7HJ6Xx5cZLtK/qTINyxn1XXrycZH0JWXNYvBxkfUVZX1EU\nLdJ/Ft76TO/VLI6DhYalR+7RbP5ZktPSKWGtpXpJS4Y2LIm7rYlRzy+EEEII8TpSpKenpxd2EuKp\ntWvX0rVrV+6MN7xpjig4PX+5TMDNWAK/rFXYqYgCsuVCOH3XBWKsfxafXN9LTsUY5fivulkDOhJ0\n9ijzDt4r7FRELhaOep9SNmrWrl1rlON36dKFPTcS8Oy3KPfg19jlWT2JvRZArfmBhZ2KeE5HerkY\n9aV5hUJB1UGLcKrdzijHz6+UuCiub5zJg1O7SIq8j9rUAqtSVSnrPwLrMj5ZYiMuHSR401yir58m\nXZ+KiUNJStR7G4+W/VBqnm5efXJaTx7fD6bakKVc+WUs0cFnUKjUOPo0o8KHk3l0ZjfBm7/n8f3r\naK0dcW/xMe7Ne2fWPz6hAwmPbuEz7Geu/voV0cFnIT0d67I18HpnHJZulZ6ea2p3Iq8ep+nS65ll\nsaEXCdowncirR0lLjEdn60zxmq0o02EYajOr52r7ixZ/N4jIK0cp2fgdooJOcmxcG8p3/wqP1v2y\nxZ6bP4AHJ7bT9KcbRs3pRbp/bDNnv+9jtP/fCSGEEP/WpUsX0qLu8cvUzws7lRcuMjqWyT+uZtu+\nY9x7EIGFuSnVK5bjy7498PX2zBK77/hZpi5dy4mLgaSlpuHq7EiPNo0Z/G5HdFpNZlzHgeMICr3D\nqplfMmLqIk5dvIZaraJlg1rMGd2fPw+eYPpPawkKvUNxB1sG9GxP/+5P///6Vq9RhN4NY+2ssYya\n/iOnLgWRnp5OzSpeTBnem8qepTJj2w/4iiOnL/Hg8PrMsnNXg/l24W8cOn2R+McJlHC0p13juoz+\npBtWFubP1fYX7YdfN+Fob0OXFg2zlK/c/Dd9vp7NL1M/x79ZvSyfRUTH4tupP/V9vanvW4Uh384j\nYN08KpZ1N2quhe3dzyajsnE22vMI8Xrp0qULUYl6pv34W2Gnkik6KoLFM79j386tPLx/DzMLSypV\nrU7fkWPx9qmZJfb4wb0snTOZC6dPkJqaSomSbrTu3JP3+g1Fq9Vlxg3s0Y7Q4GvM+GktU8d8ysUz\nJ1FrNDRo1oovJs/l4O4/WTp3KqHXr+HgWJyenwymR+8BmfU/at+Eu7dCmP3z70z7aiSXzp4kPT2d\nKjVqMWL8NDwrVcmM7d+9DaePHeZIcERm2dULZ1kwfQKnjx7icXwcjs4laNK6A58M+wILK+vnavuL\n9s2I/uzYsJp9V+5l+dkZ0rBCCSr7+PLDb5uzlIdev0b7N7wZMGocHw8bbcx0862ak87oz5+Wf90H\n/zeN++cknq3jyFkcvRDEvR3zCjsVUYCsGvU2+vVdEJOKxbPJnIbXk8vXR4x+fRfEizyvIhmffXmE\nB2whcGFfo88Pet3GpyIiIpgwYQKbN2/m7t27WFpa4uvry7hx46hVK2tftWfPHr777juOHz9Oamoq\n7u7uvPvuuwwfPhyd7um9V6tWrQgMDMxcWD8gIACNRkObNm2YP38+27dvZ9KkSQQGBuLk5MTQoUMZ\nPHhwZv0GDRoQEhLCpk2bGDZsGCdOnCA9PZ06deowc+ZMqlatmhnbokULDh48SFxcXGbZmTNnGDdu\nHAcOHCAuLg4XFxf8/f0ZO3Ys1tZP71vz03ZjCQ8Px9vbm4YNG9KoUSP69evH+fPn8fb2LpDzFxXG\nvv6eHN9v6R2jHP9VJ33lyyNwQR8alzI16vy/hEt7WNTFuGMs4tnknvL11GdtIKYVGxv1+k55cJ2f\nx/YyyvELU2RsPFNX7mD74fPcD4/GwlSHT3l3Rr/XihpeHlli95++yvTfdnLyaihpaWm4OtrRrVlt\nBnZugk7zdHGpt7+YT9DtMH4d9wmfzVvHqauhaNQqWtSpzMzBXdl1/CIzVu3k+u0HONpa0b9TY/p2\nbJRZv+WwWYTeD2f1hD6Mnv87pwJDSU+HmhVLMalvJ7zLuGTG+n/+A0cuXOfe1lmZZeev32bSz9s4\nfP468QlJODtY065+NT57pyVW5k8XEclP21+0wTN/Y92eAEL+mJblZ/dfY19F709YisaxjPTfrzjp\nv19Pxu6/hRBCCCGEEEIIIQrCk/H2qB0zCzsVo4iMfczU33ax4+hF7kdEY2Fqgk85Vz5/pzk1ymdd\niHj/2WvMWP03J6/eJDVNj1txW7o29mVgp0ZZnm93HvsjQXcesHLsh4xauJFTgTfRqFS0qF2RGQPf\nZlfAZWau+Zug2w8pbmdJvw4N6du+fmb9liN/4GZYBKu+7sXoRRs5fe1WxjiClzvffdIe79IlMmM7\njVnMkYvB3P1jcmbZ+eD/Y+++46qs/gCOf+7gXvaeDsAJ7oXiHpmr1By5UjNHmqY5ypEzR5maMy1X\nmubINM1VqZkLcCuCCg5wI3uDl/374yaGXEMU1H59368XL7nnOec83y94ee5zz7nn3GP2hn0cvxia\nO47QoVF1xvVqjaXZo0WBC5N7Ubt6JxK/iyG8164Bp4Nv0Wr0YmYO6sCIri3y1S3bYwp1Krqydeb7\necqv34vCa9BsJr3bjrG9WhVrvC/LjqP+9J+9/oXNZ3v4fA9f3PWFnK+4xKems2BfEPsC7xOeqMNc\nq6aGqw1j21ailpttnro+V6NYfCCY87diyczOoZStKd3qujK0RUU06kcLhb+zwpfQyCTWDGzA5J8v\n4H87DiOVglZVXPiyey0OXg5nyYFgQiKTcbQ0ZnCz8gxqVj63/VtLjnAnJoV17zdk6o4ALtyOI4cc\n6rjbMr1TDaqUfDSnrde3PpwMjSF03lu5ZRfvxfPVb0GcCIkmJS0TF2sT3qxegtFtKmFp8uhzv4XJ\nvah9dzSErOwcBjcvn6d8+9k7DFt/isXveNHD263QdQ2ZtiOAjcdv4DOpDc5W/x+Lne86f5fB35+U\n+bH/AW3btsXX15ekpKSXHYp4QV7U/Fh5fr848jwWD8nzTwghhBBCCCGEEEIIIYQQQvw/eTj+dX9e\n25cdSrGIT81gwR8h7L8cSXjCX3OrSlvxSevy1Cptlaeuz/UYlvwZyvnbCfp5ZTbGvF27JEObueeZ\nV9b7u7OERqXwXb9aTNkZhP+dBNQqJa0qOfBll8ocDI7i6z9DCYlKxdFCw/tN3BnU+NG8qE7fnORO\n3APWvVebqbuCuXA3gZwcqONmzWcdPKlSwiK3bq/VZzh1I46Qzx/Nl7wUlshX+69z4kYcKWlZuFhp\neaOaE6NfL4+l8aN5rYXJvah9uOkCv16M5MYXzzbPc9ruYDadvMuxcU1wtvzn9cX/zXZdCGfIBv9i\nn18i+yu/OLK+hHjoRe2vLOsrPhtZX/HfQ9ZX/G+Q6+d/k6zPJIQQQohitvW/t8KtEIWQg3woSohX\ninxQUYhCkeuY+De5sPQDUu5docZHq7B0r0ZafARXNk3n9OxuNJi1HzPnsgDEXTnFmTm9cPJ6g8bz\njqE2tSTyzO8ELB9OekIMnn1n5PapVGtIT4rl8vcT8Oz9GeYlPbh9cB1XN89EFxuG0khLrdFrMDKz\nJmjdRIJ/mIJ1+dpYlautb2+kJT0xhosrR+HZdwZW5WqRGnGTc1/15fQX3Wg8zweNheHFihJvXODU\nzE7YVm2K97Q9GNs4Exvkx8VVY4i7chLvqbtQqNSFyv1x6UmxHBpapcCfbeO5xzArUd7gMbMS5Z94\n7HGZqQmojM2fqq4QQggh/v+8O2EuwaG32TDvU2p4liU8Ko6JC7/jzSET8dm0mApu+o3k/M5fpuOw\nqbzVsiH+O1ZgaW7KnkMnGDh5PlGx8cwdOzi3T42Rmuj4REZ98Q2zxwykUjk3Vm/dy6RFa7kXHoVW\nq+HHBZOxsTRnzJzljJ27krpVPahbzeOv9kZExyYyZNoi5o0dTJ2qFblx5z5dP5rOG4Mn4v/LCuys\nLQ3mc+7yNVoPGE+L+jU59P08XBztOXYmgKHTl+B3/hIHv5+HWqUqVO6Pi4lPxLXFOwX+bM/vWE5F\n91IGjw3v/ZbB8sCrN1AoFFQul39R3JGfLyMzK4v54z/gl4N+BZ5fCPHvMH5IH0KvBvHVqs14VKtJ\ndEQ4C6aPZ/Dbbdm8/wRu5SoAcP6kL0N7vknLNzrxi08g5paWHPptF5OG9ycuOpKxM+fn9qnWaIiL\njeGLCR/x8WdzKOdRma3rVrJwxqeE37uL1ljLwrVbsbSy5stJo5k7eQzVatelWm395DUjrYa4mGim\njnqfcTPnU7WWF3duhjKiTyfef7stO30DsLa1N5jP5Qtn6f9WS+o3fY11e4/g6FyCM35H+Wz0YM6d\n8GXd7sOo1OpC5f64+Nhomlc2/Df673b4BFCmvIfBY/6n/PCoWgON5p8/qBEedpeEuBjKelTKd6x0\nmXKojYy4HHCuwFiEKC4yvCLE/y8ZCxLi1SLPSfFf1rNnTy5fvszWrVupVasW9+/f55NPPqFly5ac\nPXuWihX1H0jz8fGhTZs2dOnSheDgYKysrPjll1/o27cvkZGRLFq0KLdPjUZDdHQ0w4YNY/78+VSp\nUoVvv/2WcePGcefOHYyNjdmxYwc2NjaMGDGCkSNH4u3tjbe3NwBarZaoqCj69+/PokWLqFevHiEh\nIbRv356WLVsSHByMvb3h+9YzZ87QtGlTXn/9dfz8/ChZsiSHDx9m4MCBHDt2DF9fX9R/3bc+be6P\ni46OxsHBocCfbVBQEJ6env9YZ+jQoWRmZvL111/z888/F9inEC+LXCuFeLXIc1KIp9d/1hqu3Apn\n3dRBVC9fiojYRCYt306HsUs4+u0EypdyBOD4xRA6T1hKh8Y1ObN2KlZmJuzxvcDgL9cRFZ/El8Pe\nzu1To1YRk5DCmMU/8vkHXank7sLq3ceYunIH9yLj0GrUbJo+BGtzU8Yu/Ynxy7bi5emOVyV3fXsj\nNTEJyQyd9wNzhnWjjqcboWHRdJ/0LR3GLubM2qnYWRme73f+6m3ajV5A89qeHFjyMSXsrTl24RrD\nv9qAX2AI+xd/jFqlLFTuj4tJSKZs1/EF/mxPr51KxdJOBo+dvBRK9XKl8mx++ySFqSvEv5lcv4UQ\nQgghhBBCCCGEePUM+HI9wbciWDepH9XL6d9Ln7x6Fx0//ZYjX4+hfEn9/JATl27QZdIKOjSqzplV\nn2JpZsye44EMmbeJqIRkvhzSKbdPIyMVMYkpfLz0Z2YN7kglV2e+2+vH1O92czcqHmONERunDMDa\nwoRx32xnwvIdeHm64uWh3+BD+9c4wrAFm/lySCfqeLhy434M3aetpuOn33J61QTsLM0M5nP+2h3a\nfbKU5rUqsn/BR5Sws+JYQAgjFv3I8Yuh7Jv/Ue44wtPm/riYxBTK9ZhS4M/21MoJVCxteCyiYmnH\nJx77u3tR8cQmpuDhln88omwJe4zUKvyv3S2wH/HfMuT7k1wNT2LVAG+qlbQmIlHH9J2BvL3sGPs/\naUk5R/043MnQaHp+e4w3apTEZ1IbLE3U/BYQxvANp4lOSmNmlxq5fWpUSmJT0pmw9TyfdaqOh7Ml\n63xCmbErkHvxDzBWK1k7sAFWphombfNn8vYL1Ha3pbabfk0TrVpJTEo6ozadYWaXGtRyteVmdDJ9\nVvrx9rKj+E5qja2Z4c8/Xbgdx1tLjtDUw5G9o5vjbGWC3/UoRm8+y4nQGHaPao5aqShU7o+LTUmj\n8sQ9Bf5sfSa2pryThcFjA5uWM1geHv8AADd7s2eq+7i7samsORbCiNc9cLYyLjBmIV5FxbWpixDi\nxZHnsRBCCCGEEEIIIYQQQgghhBBC/Lt8sNGfKxEprOpbk2olLYlITGP6nmC6rTjF/pENKeugn7N0\n6kYcvVad4Y1qThwb1wRLYzW/X4xg+I8BxKSkMaPjo/WrNSqFfl7Z9st81sEDDycL1h2/zcy9VwiL\n16E1UrKmX22sTdRM/CWIKTuDqO1qRW1Xa+CveWXJ6Yz6KZAZHStRy9WKm9Gp9F1zlm4rTuEzrgm2\nZhqD+Vy4m0Cnb07RtIIde4bXx9nSGL/QWMb8FMjJ0Dh2Da+fO6/saXN/XGxKOlU++7PAn+2xsU0o\n72i4j4QHmZhrVQX2YcjduAes9b3F8BZlcbb85/XFhXgVyfoSQvw7yHNViFeLPCeFEEIIIURRU77s\nAIQQQgghhBD/bdkZacReOoZ9jZZYV/BCaaTFxMGVqoMXoVRriAk4lFs38tzvKI20eLwzFa2NMyqt\nKS6NumDr2YB7x7bkSrEk+AAAIABJREFU6zszNZGyHT/CqlxtVMZmuLcdjMrYjLirZ6g6eBEmDq6o\nTS0p02E4ADGXfHLbKpRKsjPSKNN+GLaVGqLSmGBRuhIevaaQkRxH2LGfnphT8IZpGJlZU3PEKsxc\nyqEyNsOhVisq9phIQsh5wk/uKnTuj9NY2NJmw/0Cv8xKlC/078SQjJRElCo113+eh+/4Zhzo787h\n4TUJWjeRjOT4IjmHEEIIIV5NuvR0Dp/yp3UjL7yre2Ks0eBe0okV00ehMTLij+PncuvuOXwCY60R\nn48egIuDLWYmxvR4ozmN61Tlh10H8/WdmJzCJwO6UbeaB+amxgzv0wlzU2NOXAhmxfRRuJd0wsrC\njI/f02+Kd+R0QG5blUqJLj2dMe91pYlXNUyNtVSp4M6sUQOITUhi4+7853towvzV2FhZsGHup1Rw\nL4W5qTHtmtZjxoh+nLl4le37jxU698fZWVuScn5PgV8V3Us99e8iMiaexeu38+3m3Ux4vyeeZV3z\nHN/y62G2H/BhwYSh2NtYPXW/QohXW1qajlPHDtH4tbZU96qPVmtMSVd3ZixahZFGi9/hA7l1D+/b\njVZrzJhpX+Lg7IKJqRlvdO1FnQZN2Lnlh3x9JycmMPCjcVSrXQ9TM3P6DP4IUzNzLpw5zoxFqynp\n6o6FlTX9h38CwCmfw7ltVSoVaWk6+n/4MV4Nm2JsYkqFSlUZPXU2CXEx7Nqy4Yk5fTV1HFY2Nsxb\nvRn3chUxNTOnaas3+GjSLC6eP83+XdsKnfvjrG3t8Q9PK/CrTHmPJ/Zx7/ZNHJ1LsPunDfRs5Y23\nmxVNPZz5dFg/Iu7fy60XGxWRe87HKZVKrKxtiImKfOJ5hBBCCCGEEOLfTKfTcfDgQdq1a0eDBg0w\nNjamTJkyrF27Fq1Wy759+3Lr7ty5E2NjY+bNm0eJEiUwMzOjd+/eNGvWjO+//z5f3wkJCXz66ad4\ne3tjbm7O6NGjMTc3x8/Pj7Vr11KmTBmsra0ZP348AH/++ehD/yqVCp1Ox7hx42jevDmmpqZUq1aN\nuXPnEhMTw7p1656Y05gxY7C1tWXr1q14eHhgbm5O+/btmT17NqdOneKnn34qdO6Ps7e3Jycnp8Av\nT0/Pf/z5b9y4ka1bt7J06VIcHAxvoCWEEEIIIZ6dLj2DI+eu0KpeZepVLoOxxgg3Zzu+HdcXrZGa\ng2cu59b91S8ArcaIWUM642Jnhamxhu4t69Koenk27juRr+/ElAeMeacNXpXcMTPR8mHX1zAz0XLy\ncijfjOuLm7MdVuYmjOrZCoCj/ldy26qUCnTpGYzq0YrGNSpgotVQpUwJZg7uRGxiCpv2n3xiThO/\n/RkbCzPWTR1EhdJOmJloaVu/KtMGvcXZ4JvsOHK20Lk/zs7KnIQ/lhX4VbF0/o1XH7oVHo2LvTWb\nD5ykyQdf4vTGKNw6j2XQF98TFhX/zHWFEEIIIYQQQgghhBBCiKKiS8/kyPlrtKpbiXqV3DHWqHFz\ntuWbMT3176WfDc6tu/f4RbQaI2YO7ICznaV+HKFFHRpVK8emA6fy9Z2YomN0j5Z4ebhhZqJlWOdm\nmJloORV0k2VjeuLmbIuVmQmjur0GwFH/67ltVUoluvRMRr79Go2rl8dEq6GyuwszBnYgNjGFzQdO\nPzGniSt3YmNhyrpJ/ahQylE/juBdmWn93+TsldvsOOpf6NwfZ2dpRvxvCwr8qljasdC/k8dFxifl\nnvNxSoUCGwtTov6qIwRAWkYWx65G8VplZ7zc7dAaqXC1M2PRO3XQqJUcDo7Irbsv8D5aIxXT3qqG\ns5Uxpho1Xb1caVDOgS2nbuXrO/FBBh+97kltN1vMtGoGt6iAmVbNmRsxLOrthaudGVYmRgx/Xf9Z\nJ5+rUbltVQoFaRlZfNjSg4blHTDRqKhUwoqpb1UjLiWdLaduPzGnqb8EYGOqYXX/+pRztMBMq6ZV\nFRcmta/K+Vux7Dp/t9C5P87WTEv44q4FfpV3sijU7yMqKY2VR67h6WJJ3TJ2RVJ34f5gtGolQ5oX\nzVosQgghhBBCCCGEEEIIIYQQQgghhBBCiP9vaZnZHLsWS0tPe7zcrNGqlbjamrCoezU0KiWHrkbn\n1v39UiRaIyVT23vibKnFVKOiS+0SNChry5bT9/L1najL5KPXylLb1RozrYrBTd0x06o4cyuORd2r\n4WprgqWJEcNblAXA53psblulUkFaZjbDmpelYTlbTIxUVHKxYEp7D+JSM/jpTNgTc5q2KxhrUyNW\n9a1JOQczzLQqWlVyYOIbFTl/J4FdF8ILnfvjbM003J/XtsCv8o7553g++vlkoFYpmbf/Os2+8sH9\n0/3UnHmIiTsuE5+a8eRfGrDoYAhatYohTd3/sZ4QQgghhBBCCCGEEEI8ifJlByCEEEIIIYT4b1Oo\njdBY2hN59jcizvxGTpZ+soTaxILXll/GtfXA3Loevaby+urrGNuVzNOHiYMrmamJZKQk5OvfpmK9\nR+dSqTEys8bEoTRa60ebiGgs9ZvipSdE5WtvX71Fnse2lRsBkHTb8EYmmQ+SiL96GtvKjVAaaQz2\nlRByvtC5v3Q52WRnpqPSmuI1cSstlgVQ6d1ZhJ/czfGpbcnUJb/sCIUQQghRTDRqIxxsrNl96Di7\n/jxORmYmABZmptw5vJmhPTvk1v1i9AAifLdR2jnvpsPuJZ1ITE4hPjH/a4aGtSrnfq9WqbCxtMCt\nhCPO9ra55Y521gBERMfla/96wzp5HjerWw2AwKs3DOaTlJLKcf/LNK1bHa3GKM+xVo30fZ0OvFro\n3ItTyJ37mNVqT5nX+/DFik3MHPkeEwb3zFMnLDKGMXOW06FFfd5u0+SFxCWEeDGMjDTY2jvw52+7\n+PPXnWRm6O8dzSwsORIURq+Bw3Lrjp76JX4hMTiXLJ2nj5KuZUhOTCAxIf/f0Vr1GuZ+r1KrsbS2\noURpN+ydnHPL7Rz0C2jHRIbna9+wRas8j+s2ag7AtaBAg/mkJCXif9qPuo2ao9Fo8xxr1KINAIHn\nThU696KWnZVFmu4Bp3wOs/PHdcxYvJpDl+8xd+VG/E/50addI5IS9JuH6nQPcuM1xMhIg+5BarHF\nKoQQQgghhBAvk0ajwdHRkV9++YUdO3aQ8de9m6WlJdHR0YwYMSK37rx580hKSsLV1TVPH2XKlCEh\nIYG4uPz3rY0bN879Xq1WY2tri7u7Oy4uLrnlTk76sd/w8Pz3rW3atMnzuEUL/ZhtQECAwXwSExPx\n9fWlRYsWaLV571vbtm0LwMmTJwude3G4d+8eI0aMoFOnTvTo0aNYzyWEEEII8V+lMVLjYGPBHt8A\ndvtcICMzCwALU2NubJ/LkE7Nc+vOHNyZsN0LKOVom6cPdxd7ElMeEJ+Uf6ygQdVyud+rVUpsLMxw\ndbLD2dYqt9zRxhKAiNjEfO1belXO87hJzYoAXArNvwgYQFKqjhMXQ2hSsyJaI3WeY6/X1fd1Juhm\noXMvalnZ2TxIy+Co/1U2/H6c5eP6EvrzHL6fPJATl0J4bfhcEpIfFLquEEIIIYQQQgghhBBCCFGU\nNEYqHKzN2esXyB6/wDzvpYdumcmQjo8+4zVzUAfubZ9NKUebPH24OduSmKIj3sB72Q2qlM39Xj+O\nYIqrky3Otpa55Q42FgBExhkYR6jjkedxk+rlAbh4w/DmHkmpOk5eukHTGuXzjyPUqQTA2Su3Cp37\ny6RL08/n0ajVBo8bqVWkpqW/yJDEK85IrcTeQstvAWH8GhBGRlY2ABbGRgR90YGBTR+N7019qxoh\nc9+ipI1pnj5c7cxIfJBBQmr+/1v1ytrlfq9WKrA21VDa1hQnS+PccgcL/by1yCRdvvYtPJ3yPG5U\nXv9Z3qB7+ddaAUjSZXA6NIZGFRzQqPMuOdmikv6zY+duxRY69xchPjWdfqv8SHyQydd96qJSKp67\n7r24VH46dYuBTctjZWr4c2BCCCGEEEIIIYQQQgghhBBCCCGEEEII8XdGKgX25hp+uxjJbxcjyMjK\nAcDCWM3l6S0Z2Mgtt+7U9h5cn9WKktbGefpwtTUhUZdJwoOMfP3XK/NobqlaqcDaxIjSNiY4WT5a\nA83BQj/fKSopLV/7Fh72eR43Kqefp3b5fpLBfJJ0mZy+GU+jcrb555V56Oeknb8dX+jci0N2DqRn\nZmOqUbF1SF0Cpr3GrLcqsTsgnLZLjpOclmmw3b14HT+ducfAxq5YmRgZrCOEEEIIIYQQQgghhBAF\nMfwJdSEEG/tWetkhCCH+ZvSyHS87BCH+VSqN3viyQxDiqSkUSmp/sp6AZcPwXzQAlcYE6wpe2Fdv\nQclmvTAyt86tm52Rxu0/vifi1F4eRN4iIyWOnOxscrL1i4M9/De3b6UKtanlY+dTYGRmzWOFhtur\njDAyz7ug2sO26YlRBvNJi4sgJyebMN+fCfP92WAdXcy9Quf+snl/tidfmVO99qBQ4r94IDd2L6VC\ntwkvITIhhBBCFDelUsG2JVMZMPEren38OabGWupV96R1ozq8+1YrbKwscuvq0tNZueVXdh705cbd\ncOISk8jKyiYrW7/o48N/H1IplViam+UpUygUefp8WGaovZFaje1jdR+2jYyNN5jP/ahYsrNz+HHv\nIX7ce8hgnbsRUYXOvTiVK+1Cyvk9xCcmc/RMIB/PWc7W34+yZ/ksrC3NARg6fTEAiyd9+EJiEkK8\nOEqlkiU/7ODTYf0YM6A7xiam1PDypmGLNnR6px9W1o82FE1L0/HT2hX8sXcH926FkhAXR1Z2FtlZ\n+vvdh//m9q1SYW5pladMoVDk6fNhGUDWY+3VRkZY2djlKbOy1t9Hx0RFGMwnMuI+2dnZ7N22ib3b\nNhmsEx52t9C5FzWFUolSqSQ5KYEFa3/C0kqfV/1mLZk8dxkfvtOBH1YsZti4aRib6BdtzsgwvAB4\nenpabh0hXrQd80a/7BCEEMVE5jQI8WqR8VnxX6ZUKtm9eze9e/emS5cumJqa0qBBA9q2bcuAAQOw\ntX1076bT6fjmm2/4+eefCQ0NJTY2lqysrNz7zcfvO1UqFVZW+e9b/97nwzJD7Y2MjLCzy3vf+rBt\nRITh+9awsDCys7PZsGEDGzZsMFjnzp07hc69OAwcOBCAb7/9tljPI0RRkGulEK8WuacU4ukpFQq2\nzBrKoC/W0uezlZhoNdSrXIbX61amb7sG2Fg8Gu/WpWewetdRdh3z5+b9aOISU8nKLmC83MwkT5lC\nATaWeccUHm5TmJWdk6fcSK3C1jLvePvDeAxt+ApwPyaB7Jwctvxxii1/nDJY515UXKFzL2pKhQKl\nQkFiygM2fjYYawv9z6RFHU8WjepF10+XsXTbQSa9175QdYX4N5PrtxBCCCGEEEIIIYQQrx6lQsGP\n0wfx/pwN9Jm5Vv9eeiU3XvfypE9rb2wsHr3nr0vP5Ls9vuzyvcDN+zHEJaWSlZ1TwDhC3o1AFICN\n+WPjCLmfu3uacQR926j4ZIP53I9J1I8j/HmWLX+eNVjnblR8oXN/mUy0+s1P0jMNb/aRnpGJ6V91\nhAD9/+0f3m/IsB9OMeC745hoVHi529GikhPv1HfH2vTR/5e0jCzW+oSy98I9bsWkEJeSTnZOTu7z\nMSsn7/NSpVRg+dimMgoFefp8WAYGntcqJTZmeetamz3c4EdnMJ+IBB3ZOTlsO3ObbWduG6wTFpda\n6NyL283oFHqv8CEqKY0NQxpSrdST114pTN2fTt0mMzubPg3LFEfYQrwQv//++8sOQQjxnOR5LIQQ\nQgghhBBCCCGEEEIIIYQQ/y5KhYL1A2ozbFMAA9adx8RIhZe7NS087OlVtxTWpo/mhaVlZvO93232\nBoZzK+YBcakZeeeVZRuYV2acdzthhUKRf17ZX//mn1emwMY077y0h/FEJacZzCciMY3snBx+PhfG\nz+fCDNa5F68rdO7FYc/w+vnK2ld3RqlQMHD9eZYeusGEthXy1dl65h6Z2Tn09i5drPEJUVxkfQkh\n/h1kfUUhXi1y/RRCCCGEEMVBXXAVIYQQQgghhChelmVq0HieD3FXTxMTeIjogMNc2TyD0N1L8Jqw\nFUv3qgBc+HoIkef3U77zx7g06orW2hGlWsOlNeO4d2RzkcelUCoMlOY8PPiPbUs1702VQV8VeI6n\nzf1VZV+jBSgUJIScf9mhCCGEEKIY1a5cgfM7lnPcP4g/jp/jD7+zTFy4hnlrtrJ3+SxqeJYD4N1x\nc/j16CkmDulFzzdb4GRng1ZjxIhZS1n/y4Eij0tp4PVazl8LZCoLeL32Xuc2LJs6osBzPG3uL4K1\npTkdX2tAaRcHGr8ziq/WbmXWyP6s/+UAf/idY/2c8TjZ2byweIQQL07lGnX4xScQ/1N++B0+gN+h\nAyycMYE1S+ayYutveFarCcD4wb05sn8vQz6ezJtvv4O9oxMajZaZYz/kl83fF3lchv7WPu3f4S69\nBzB1fsGb1T9t7kVNoVBgY2ePpZUNllZ5/7Z6NWyCQqEgONAfAAdHFwDiYqLy9ZOVmUlCfBx1nEsU\nS5xCCCGEEEII8Srw8vIiODgYX19f9u3bx759+xg7diyzZ8/mjz/+oFatWgD06NGD3bt3M23aNPr0\n6YOzszNarZYhQ4awZs2aIo9LqfyH+1YDx/5u0KBBrFq1qsBzPG3uRW3NmjXs27ePLVu24OzsXCzn\nEEIIIYQQerUqunJm7VROXArl4OnLHDwTxJSVO1iweT+75o2genn94k/9Z63ht+OBTOj7Bj1er4eT\nrSUaIzWjFm7ih9+PF3lcSsU/jJcX8Hq33xsNWTKmd4HneNrci5pCocDe2hxrc1OsH9sstlH1CigU\nCgKu3yl0XSGEEEIIIYQQQgghhBCiqNWqUJrTqyZw8vJNDp4N5uDZK0xZvZsFWw6yc/ZQqpcrCUD/\n2ev4/eRlxvduTY/XvHCysdCPIyzZyob9J4s8rn8cRzBw7O/ebVufJSO7F3iOp839ZXK2tQQgOiE5\n37HMrGziklJpWNXqRYclXnE1XG3wmdiGUzeiORwcwaGgCGbsDGTJgSts/bAJ1UpZAzD4+5Psv3Sf\nj9tW5m0vVxwttWjUKsZuOcfmEzeLPC5DT92Hz2vDa6M80rtBGeb3rF3gOZ429+J0+kYM/VYdx0yr\nYtfI5ni6WBZJXYA9F+5S09WW0ram/1hPCCGEEEIIIYQQQgghhBBCCCGEEEIIIf6uRikrfMY24fTN\nOA5djebwlWhm7LnCkj9D2Tq4LlVL6ucuDdngz/7LkXzcqjxda5fA0UKLRq1k3LZLbD59t8jjUhic\nL6r/t6D5or29S/HV2wXvifW0ub9ILTztUSjg/O14g8f3BIZTs5QVpW1MXnBkQgghhBBCCCGEEEKI\n/yfqlx2AEEWp9w9BnLqdyLVJ3i87lEIb8fM1tgdE5z4+Mbo2pa21Ly2epl/7ExL9AAAbUzUXx9d9\nabGIf6+FH3bmuv9xlvmGv+xQCm315EGc+PWn3Mdf7rmIfQnXlxbP5C51CL95DQBzK1sWHbr50mIR\nxStoYW8Sr53C+5trLzuUQru2agTRJ7bnPq495wRa++LZ5KGo+U9qyoPwEADU5jbUXXzxJUf0H6VQ\nYONRDxuPepR/ezzx185walZnQnbMp9botaTFhRN5bh8uDTpRrsvHeZrqoot+wgpAdkY6mamJqE0f\nTRxJT44DQGvlYLCNsa0LCoWSB4WJqYDcDUlPiuXQ0CoFdt147jHMSpR/+lgMyM7MIPluMGpjM0yd\ny+Y9lpEOOTkojV7ea1chhBBCvBgKhYKGtSrTsFZlpg7rw8mAYFoPGM8XKzazZeFk7kfFsvfISbq1\nacrEIe/kaXs7LLJYYkpLzyAxOQVLc7PcstiEJAAc7QwvKlnC0R6lUsHt+08fU0G5GxITn4hri3cM\nHvu78zuWU9G9VL7yO+FRfLFiE03qVOOd9q/lOeZZVv8eRXCofsO6i9duAPDu+Dm8O35Ovr7qdvsQ\ngIQzO1GrVAXGJIR4NSkUCmp5N6KWdyM+HP8ZAWdO0L9TS5bPn8Wi77cRFX6fw/v20LZTdz74JO/f\npvt3bxVLTOnpaSQnJmBu+Wjh6/i4WABsHZwMtnFyKYlSqSSsEDEVlLsh8bHRNK9c8MLhO3wCKFPe\nw+CxStVqEXjudL7yzMxMcnJyMNJoAHBwdsHe0YmQK5fz1Q29FkxWZiZVankVGIsQD3Ueu5DjgdcJ\n/33Zyw6l0AZ9vpqfDpzIfXzxxy9xdbZ/afHU6TuZa3f041S2lubc3LXopcUiBMichqIkcxpEUZHx\n2aIjY65CoVDQuHFjGjduzMyZMzl+/DhNmzZl+vTp/PLLL4SFhbFr1y569uzJtGnT8rS9dat47lvT\n0tJISEjAyurRfWtMTAwATk6G71tLlSqFUqksVEwF5W5IdHQ0Dg6Gx5z/LigoCE9Pz3zlAQEBAPTo\n0YMePXrkO16tWjUAMjIyUKtlqrB4NnKdLDpynRRFRe4ri47cV4rCUigUNKhajgZVyzG5fwdOXb5B\nu9EL+HL9r2yaMYT7MQn86hdA1xZ1mPDuG3na3o6ILZaY0jIySUx5gKXZo8WnYhNTAHC0sTDYpqS9\nNUqFolAxFZS7ITEJyZTtOr7Avk+vnUrF0oZfm9eo4MqZoJv5yrOysvTjNH97nVuYukK8aHL9Ljpy\n/RZCCCGEEEIIIYQQryqFQkH9KmWoX6UMk95tx6mgm7wxdilfbtzHpqkDCI9J5LcTl+jarBYTerfJ\n0/ZOZHGOI+iwNDPOLYtNSgXAwcbcYJuS9lYoFYpCxVRQ7obEJKZQrseUAvs+tXICFUs7PnUshjjb\nWeJkY0HwrYh8x67eiSAzK5vaFf8d66KIF0uhAO+y9niXtWf8G1U4czOGTouPMP/3IL4f1IDwBB37\nLt6nU+3SfNK2Up62d2NTiyWm9MxsEh9kYGlilFsWl5IOgIOF4ffvXaxNUCoU3I1NeerzFJS7IbEp\naVSeuKfAvn0mtqa8k+GxTICzN2Pp+a0PFZws2DC4EfZPyKuwdQFuxaRw6V4CH7Uy/DkyIYpT27Zt\n8fHxITk5+WWHUmh9+vRh48aNuY9v3LiBu7v7S4vH09OTK1euAGBnZ0d0dHQBLYQoXvL8Ljry/BZC\nCCGEEEIIIYQQQgghhBBCvOoUCqhXxoZ6ZWwY36YCZ27F0/mbk8w/cJ2179UmPDGNfZci6VTThY9b\n5d0n6m78g2KJKT0zm0RdJpbGj9ZUiEv9a16ZucZgGxcrY/28srinj6mg3A2JTUmnymd/Ftj3sbFN\nKO9olq88Iyub4PBkzLRqytqb5jmWnplNTg5o1cp87W7FpHIpLImPXiub75gQxU3Wl3g5ZC0KURiy\nvmLRkfUVRVGR62fRkWuiEEIIIUTRk9VshXiFaNRKbkzJf/OYkZXDJztD2HYhiimt3figUYnnOs+N\nGB2z/7jN8ZsJJKVlUdpaS/dajnzYuCRKhb7O0RE1ARiw+Qqnbic+1/mE+LdSa7QsPxGVrzwzI511\nM4ZzfO+PdBs1izbvfvRc5wm/eY0dy2YQdPoImWlp2JVwxatVZ9q+OxKtqX6Qcdb2swAsHdOL6+eP\nP9f5hChOSrUG7xU38pTpIm5we/tsEoKPk6VLQmtXGsfG3SnZ7kNQ5B8Qfyo52dw/uJaIIxtIi7yJ\n2swam5qtcX17EmpTy/zVMzMI+f4Too5vw637FEq0+SDP8ZqfHwXgytIBJF479WwxiWcWG3ScwG+G\nUXvsBixcq+SWW1fwQmvtSEayfrGw7Ez9ZBEjc9s87VPCrhEb/NffxpycIo8v5uJRnOq1fxTvZV8A\nbDwNL1KkMjbDxtOb2CA/0hIi0Vo9WmAs7spJLn03lupDv8ayTI2nzt0QjYUtbTbcf970nkp2Zhqn\nZnTEqlwt6k7anudYtP9BAOwqN34hsQghhBDixTt29iIDJs5j+9efUa1imdxy7+qeODvYEJugf+8o\nLT0DADubvK/Jr9y4g89Z/aSbnGJ4vXbwhD+dX2+U+/jIaf0myE3qVDVY39zUmEa1qnDsTCARMXE4\n2dnkHvM9d4kRs5ayetYYaleu8NS5G2JnbUnK+YIXr3wSexsrtv1+lIArofR8owXKh2/cAf5B1wEo\nW8oZgLljBzN37OB8faze9hsjP1/G6a3LqFze7ZljEUK8XGePH+XTYf1YumEnFatUzy2v7lUfB0dn\nEuL0947p6WkAWNva5Wl/41owZ44fA4rn7/Dxowdp1b5L7uPTvocB8GrYxGB9UzNzank35ozfUaIj\nI7B3fLTB57mTPsz85EM+X7qGyjXqPHXuhljb2uMfnvZcubXt3AOfP/dx4shB6jdr+bccjwBQq96j\n60+7Lj35ae0K4mKisLFzyC3ft3MrKrWatp26P1csQvybaI3URB1Ynqfs2p1wZqzawZHzQaSlZ+Lq\nbEfn5l6M7NkWM5Nnn5SanpHJ8Hnr+HH/cWYN7cZHPfJujnD2h1kA9Jq0lOOB15/5PEIIPUNzGkKi\nHzDn4B18biSQlplNaWst7avYMbRRCcw0qmc6j8xpEOLpvajx2QfhIdzZPoeEIB+yM9PQ2pXGrm57\nSrQdikqrn9cgY67/XUeOHKF3797s3buXGjVq5JY3aNAAFxcXYmJiAEhL09+j2dvb52kfFBTEkSP6\n+6ziuG89cOAAb7/9du7jQ4cOAdCsWTOD9c3NzWnSpAmHDx8mPDwcZ2fn3GPHjh1jyJAhrF+/Hi8v\nr6fO3RB7e/vnynfRokUsWrQoX/ny5csZOnQogYGBVK1q+D1SIf4rXtg8JmRukhBP6/H7ym99w5i1\n/9YT69+aVh/138bInpbcV4qi5BNwjfe/+J6tnw+jarmSueX1KpfBydaK2ET9ponpGZkA2Fnl3Tz1\nyu1wfAP0C38U/atdOHQ2mLea1sp9fMz/KgCNqlcwWN/MREvDauXxuXCNiNhEnGwfje/7BV5n1MLN\nrJjQj1oVXZ9KfSnkAAAgAElEQVQ6d0PsrMxJ+GPZc+X2dgsvDpy6xKGzwbSo45lbfvSvHBtUK/dM\ndYUQhWPofeHsHFh78j4bzkRwMy4NaxM1rT1smNTKNc9CgYUh128hhBBCCCGEEEII8W/kGxjCoDkb\n2DrjfaqWfbQeVL1K7jjZWua+l56WO46Qd6OKK3ci8A3UL3xdHPNmDp2/wluNH81pOXZBP2bRuFp5\ng/XNTLQ0qFoWn4AQIuKScLKxyD12/GIoo5ZsZfnYd6hVofRT526InaUZ8b8teN70ntrbLWrz3R5f\nohOSsf/bWM72I+dRq5R0bVbrH1qL/5rj16MYtv40G4Y0okpJq9xyL3c7HC2NiUvRr3uSnpkFgK1Z\n3s1yrkUkcfy6fr2qYnhac/RKJO1rPhq7872mP1fDcg4G65tp1XiXs8fvejSRiTocLY1zj50MieaT\nLedY2qcuNVxtnjp3Q2zNtIQv7vpcud2JTeWd5T6Uc7Rg2/CmmGufPOZQmLoPnQrVz+erWtL6ueIU\n4r9Iq9Wi0+nylaenpzNo0CB++OEH5s2bxyeffPLc5yqoz+DgYAA6deqEj4/Pc59PiP+6x5/f8+bN\nY9y4cU+sn5GRgVpduHkBT9unPL+FEEIIIYQQQgghhBBCCCGEEK+q46GxDNsUwIYBdahS4tHcSi83\naxwttcSm6vdnSM/MBsDWzChP+2uRyRwP0a+jXRzrThy9Gk376o/WSvO9rj9Xg3K2BuubaVV4l7HB\nLySWyKQ0HC0erQt88kYcY7dd4ute1ahRyuqpczfE1kzD/XltnzmvtMxsOi47Sa3SVmwfWi/PsYNB\n+rlzjcvb5Wt3+mY8AFVK5N/DTgjxz4py3eHktCxafXuB23FpHPywBp6Ops8Uk6xFIUResr6iEK8e\nQ9dP/3vJLD12j3N3k4lNzaCElZY3KtkyqlkpzLWybr8QQgghxL/Js99VCSFeiIQHmfRaf5mbsfk/\nBPssIpMzeOu7iySlZbJncDWuTqzH5NZufH30HpP2hhbJOYT4f5aaGM/CDzsTefdGwZWfQlhoMDN7\nNyExNorxq39nwR8hdBwygX3rFrN8Qr8iOYcQL1NGQiQXZ79FZmoS1Sbvod6yq7h1m8y9PV8TunHS\nM/cbunESd36Zh2vncdT9OogKHywn9txvBC/snW81nMzUBC4v6IUu6uZzZiOKi1W5mihUagKXjyQh\n5BzZGWlkJMdz87cV6GLCKNnsHQCM7Uth4uhG5JlfSb4bTHZGGlH+Bzm/aADO9ToAkBDqT052VpHF\nptIYE/LLQmIuHiEr/QFJty9z9cdZaK0cca7f8YntKvacjEKp5NxXfUkJu052RhqxQX4ELh+B0kiD\neSnPQuX+sqmNzSnXdSyxQccJ3jAVXex9MlMTCT+5i+ANU7BwrUKpln1fdphCCCGEKCZ1qlRArVLx\n/pQFnA68gi49nbiEJJb88At3w6Pp16k1AK4ujpQp5cyuP49z+fotdOnp7PM5Q88xn9OlVWMAzl66\nRlZ2dpHFZqLV8OXKzfx54jypujQuXrvJlMVrcbKzoUvrJk9sN3Nkf1RKJV1HTOfqzbvo0tM5diaQ\n96csQKsxonJ5t0LlXhxMtBq+GDMQ/6AQPpy5hFthEaTq0vA5d5Fh05dgZWHG0F5Pfk0qhPj/UaWm\nFyqVmskfDSTw3CnS0nQkxMfyw/LFhIfdpfM77wHgUsqVUm5l+PO3nVwPvkRamg6fg78zpn93WnfQ\nL6Z7yf8s2VlFd9+sNTZh1YIvOHHkILoHqVy9HMjimROxd3Sidce3n9hu1JTPUSlVfNSnEzeuXyEt\nTccZv6NMHj4AjVZLOc8qhcq9uLzRpSd1GjRlysiBnDvpg+5BKqd9j/DlxFGULlOOzr3759YdNHI8\n1rZ2jBvcmzs3QkhL0/H7Lz+x/puFvD/qU5xLli7WWIV4lQXfDKPJ+zOJik/k9yXjCdmxgAn9OrL4\nx330m778mfuNT0ql89iF3AiLLMJohRCFcTXqAW1XBBCdksH2AVW4MNaLMc1L861vGB/8dO2Z+pQ5\nDUI8n+IYn30QdpWAGW3JSIqmyoTteC28QOmOYwj7/VuuLf+g4A7E/726deuiVqvp168fJ0+eRKfT\nERsby4IFC7hz5w4DBw4EwM3NjbJly7Jjxw4uXryITqfj119/pUuXLnTr1g2A06dPk1WE960mJibM\nnDmTAwcOkJqaSkBAAOPHj8fZ2Znu3bs/sd2cOXNQqVS0b9+e4OBgdDodhw8f5t1330Wr1VK1atVC\n5S6EeDUU1zwmmZskxLNL1Ok3vQz6tC73pjfI96V++MniQpD7SlHU6ni4oVIpGTJ3HWeCbqJLzyAu\nKYWl2w5yLyqOvu0aAlDayRZ3F3v2+Fzg8s0wdOkZ7D95iT7TVtKpWW0AzgXfKuLxciPmbPiNQ2eD\neZCWzqXQe0xd9QtOtpZ0aV77ie2mv98JlVJJ98nfcvVOBLr0DHwuXGPInPVojNRUcncpVO7FpVtL\nLxpXr8DQuevxC7zOg7R0jvlfZezSrZQt6UC/v52/MHWFEM9v0t5Q5v15h3EtXQmaUJfl3SrwW1As\nvX8IfqaNbeX6LYQQQgghhBBCCCH+rWpXLI1apeSD+Zs4c+UWuvRM4pJSWbb9CPei4nm3TX0ASjvZ\n4O5sx27fQIJu3keXnsn+00H0nbmWTk30i+yeu3qnSMcRjDVGzN10gEPnrurHEW6EMW3NHpxsLOjc\ntMYT200f2B6VUkGPaau4eicSXXomPgHXGfLVJv04gptLoXJ/FXzc43VsLc3pP3s9oWHR6NIz+fnI\neb7++TCf9GpFKUeblx2ieIXUdLVFpVLw0cbTnLsVS1pGFvGp6Sw/dI2w+Ae8U98dgFK2prjZmfFb\nQBjB9xNJy8ji4OVw+n93nA61SgHgfzuOrOyi27rH2EjFgn1BHLkSyYP0LC6HJTBzVyCOlsZ0/Ouc\nhkzpWBWlUkGflX5cj0giLSMLv+tRDN9wGq1ahaeLZaFyLy6fbjuPLjOb1f29Mdeqi6zuQyGRSQC4\n2Zk9d6xCCIiLi6NNmzaEhIS80n0KIQonPl6/IV5cXBw5OTn5vtTqp7vuFnefQgghhBBCCCGEEEII\nIYQQQgjxItUsbYVaqWDklgDO3Y4nLTOb+NQMVhy9SVi8jnfq6edvlbIxxs3OlF8vRhIcnkxaZjYH\ng6MYsO48HWo4A+B/J6HI55Ut/COEI1djeJCRxeX7Scz69QqOFlo6/nVOQya/WRGlQkHfNWe5HplC\nWmY2fiGxjNgcgEatxNPZolC5FwdzrZqxrctzPDSWqbuCuZ+gI1GXya4L4UzZFUyVEhb0bZB/ze/r\nUSkAuNmZFFtsQvxXPM+6w5/9fpPbcWnPdX5Zi0KIgsn6ikK8ek7cSqTzmksYqRTsHFSVwPF1+bSl\nK9+fCqfX+iCe5XZArolCCCGEEC+PfOpFiFdYwoNM3vruIu2r2PFaBWs6rLr43H0uOnKXlPQsvnm7\nIjam+j8BbTxtGdmsJLP/uM3A+i6Ut5cBCCEMSU2MZ3b/Vni16ky1Rq34ol/L5+7z5yXTyMrK4sP5\nGzG3tgOgbuuu3Lh4lv0blnL1nC8Vazd67vMI8bLc3b2IrLQUKg75BrW5fgEk21ptKNlhJLd/no1L\ny4GYuJQvVJ9JoeeIOLSecv3mYVu7HQCWFb1xfXsS9/et4EF4SG6fmakJXPziLezqtse62mtc/LxD\n0SYoioRKY0K9KTu5vv0r/Je8T3pCFGoTC8xKlKfGiBU4e3cEQKFQUmvUdwT/MIUTn7VHoVRhXcGL\nGsNXoDY2I/FWIOcXvkeZ9h9SoduEIolNodZQdfAirmyaTkKoP2RnY12xLpXenYVK8+TXTFblauM9\nbTchOxZwckYHMh8ko7VywLn+W5TtOBKlkbZQuReXK5umc/PXvBtuX9k8gyubZwDg0qgL1YcuA6DM\nm8MwdXDl1r5VHJ/0OpkPkjCxL02pFn0o03HEP/48hBBCCPHvZmqs5cCauXy+YiN9xs0mMiYeCzNT\nPMqUYv2c8XRt3QQApVLB5vmTGDt3BS36fYxKpcK7eiV+mDsBMxNj/IND6D5qJmP6v820D/sWSWxG\nRkasmD6aTxd+x7lLV8nOzsG7RiXmjx+CqbH2ie3qVvPg4PfzmL1yM6+9N5ak5FSc7G3o2roJ4wZ2\nx1ijKVTuxeX9bm/gaGvNN5t24d19BBkZmZRytsermgcT3u9JmVJPnkgthPj/YWxiytpdh1g+byZj\nB/UiJioSMwtLylTwYO7KjbTu+DYASqWSBWt+Ys7kj3n3zaao1Gpq1PFmzsqNmJqZExzoz8h+Xek/\n/BOGT5heJLEZaTRMX7yKBZ+N55L/WbKzs6lRtz4TPl+IsYnpE9tVq12P7/ccZsX8z3mvfXOSkxOx\nd3CiTaduDBw5Hq3WuFC5FxelSsWyTTtZMf9zJn3Yn6iI+1jb2tG01ZsMnzAdM3OL3LpWNnas23OE\nJV9Moe+bTUlJSsStXAXGzvyKbv0GF2ucQrzqpq38maysLDbO/BA7K3MAur5Wl7PBN1j60358L1yl\nUY2KheozPimVVsNn07m5F628q9Fy2BfFEboQogBfHLhFZjas7umB7V/zDzpWteP8vSRW+t3nxK1E\n6rtZFqpPmdMgxPMpjvHZW9u+gKxMPD5cjdrcFgC7eh1JunGe+/tXknj1BJYVX52Ne8SLZ2pqyrFj\nx/jss8/o1q0bERERWFpa4unpyZYtW+jevTugv2/dvn07I0eOpEGDBqjVaho0aMCWLVswNzfn/Pnz\nvPXWW4wfP55Zs2YVSWwajYa1a9fyySefcPr0abKzs2nYsCFLlizB1PTJ963e3t74+voyY8YMGjVq\nRGJiIs7OzvTo0YOJEydibGxcqNyFEK+G4rhOytwkIZ5Pgi4LAFONqsj6lPtKUdRMtBr2LRrD7HV7\neXfGaqLikrAwM6ZiaSe+nzKQzs1qA6BUKNj42WDGL9vK6yO+Qq1SUq9yWb6fMhAzEy0B1+7Qa+py\nRvVszZT+RXO9MFKr+XZsXyat2M65K7f04+VVyjJ3eDdMtJontvOq5M7+xR8z54dfaf3RfJJSH+Bo\na0nX5nX4+J02GGuMCpV7cVEplWybPYwvf/iNwV+uIzwmATtLc9rUr8qUAR0wNzV+prpCiOdz7m4S\n609HMK9jOdpV0r9X5O1myaRWrqzwu09IzINCX2vl+i2EEEIIIYQQQggh/q1MtBp+/2oEszfso9/n\n6/TvpZsaU6G0I2s/fZfOTWsC+nGEDVP6M375Dl4fswS1Ukm9Su6s/fRd/ThCyF3emf4do7q9xuR+\nbxRJbBojFd+M6cnk1bs4d/WOfhyhsjtzhnb+53EEDzf2zf+IOZv20+bjJSSl6nC0saRLs5p83ON1\njDXqQuVeXCav3sXSnw/nKZuyejdTVu8GoHuLOqwc1xsAW0sz9s8fwYzvf6XV6MUkpeooV8qR2UM6\nMeDNhsUap/j3MdGo2DWyOfN+u8ygNSeISkrDwtiICk4WrHzPm4619BvXKBUK1gxswOTtF3hz4SHU\nSgV1ytix8j1vzLRqAu/G02+VH8Nf92DCm1WKJDaNWsni3l589ksA/rfjyM7JoW4ZOz7vWhOTfxh3\nr+1my55RzZn/exDtFx0mWZeBg6UxnWqVYmRrT7RGqkLlXhwepGfxx6VwAOrN+N1gnXfqu7OgV51C\n1f27+NQMAMyNjYoqbCH+s+Li4mjUqBHdunWjXbt2NGjQ4JXsUwhRePHx8QCYm5u/0n0KIYQQQggh\nhBBCCCGEEEIIIcSLZGKkYucwb77af533f/AnKikdC2M15R3NWNGnJh1r6PcKUCoUfPduLabsDKL9\n0uOolEq83KxZ0acmZhoVgfcSeW/tOT5sUZYJbSsUSWwalYJFPaoxfXcw/ncTyM6Guu7WzOpUCROj\nf5hX5mrN7uH1WXDgOh2WnSBZl4mDhZa3ajoz8rVyaNXKQuVeXIY1L4OrrQmrfG7x+kI/knSZlLY1\noY93KUa8VtZgjgkP9HPFLLSyTbMQz+tZ1x0+eDWOzeciebOyHXsvxzzz+WUtCiEKJusrCvHq+fKP\n29iZqlnSpQJGKgUAHara4R+WzHLfMALCkqlZsnBzKuWaKIQQQgjx8si7jOKl6LLmEhfCkgkY54XZ\nYx8in3PwNkuO3mNb/yo0cNe/Oed7I4ElR+/hfy+ZzOwcSllp6VrDgQ8auqD56w1/Qzp9d5GbsTr8\nx3rlKV97MpzJv97Icw6AS+EpzD90l5O3EklJz8LFUkO7SnaMblYKC+OiW2T+aUWlZDCovgt9vJw4\ndzepSPrcdTGahu6WuTdfD7WrZMcXB26z91IMI5sV34fuxatpzsC23Lp8noUHQ9GamuU5tmPZDPZ+\n9xVjV/2KR53GAASfPsLe7+Zz49IZsjOzsHUpTYM3e9Km7wjUmidvtP7lgNZE3gllwYHrecr/3LKS\nTXM+YezKvXh4PdpE/c6VAHaumM21836kpaZg7ehC7dc60uH98ZiYF27TwKKQGBtJq97DaNqlP6GB\np4ukz8r1X8OzXjPMre3ylLtVqgVA1N2bVKzdqEjOJYrWpTldSL55Aa9FAai0eZ83t7fP4d7eJVQZ\ntw1LD/2iAglBvtzbu4TkG/7kZGeitSuFQ4OuuLT5AKX6yQslXZzdCV3kTbwW+ucpD/9zLTc2Ts5z\nDoCU25e4u2s+iVdPkpWWgsbaBbs67SjVYTQqE4vHuy920ad3YenRMPcN/ofsarfj9rYviDm7l1Lt\nRxaqz6hjP6LUmmLfMO9m346Ne+DYuEeesoyEKFxaDcKpWR+SQs89WxLihTC2K0HV9xcUWM/CtQp1\nJ203eKzx3GP/Y+++43O6/gCOf7Kn7EgkSBQxY+8Rau8RsVvVH1VaiqJWzZpVSktp0aL23pQiJEYS\nxAgRISJGyJAt+8nvj1T0aZ7sJ6L1fb9effX1nHPuud8nLzcn555zv1fpc93xv6ls57I8++9w3VIW\ndNwcmq08Q5GOiaMzDaftzjWu+l9ty1Zm4uicYwx/l9/vXhyqDJpFlUGz8t3eplE3bBp1K8aIhBBC\nCPG2KmtrxepZef/t7uxUgePrFqms8923Runzju+/VtnO/+iv2coszUxI8D2crVyhSKdOtYoc+2VB\nrnEdWDU3W1mdahVzjOHv8vvdi0vPts3o2bZwSWWHu3VmuFtnNUckhCgJtnZlmf39z3m2c6pRi/X7\nTqqs2+d5Q+nz8g2q57rHLgdmKzOzsOLas+Rs5Yr0dKo512XtnhO5xvXTtuy/w6s5180xhr/L73cv\nLvoGhoz9ej5jv56fZ1tb+3IsWLWh+IMSb41OXyzGN+AhQfu/x8hAeX1k7rp9fLf5CEdXTKJF7SoA\nnL16h6Wbj3D5zgPS0xWUs7FgQIemjOnfET2dnJfuO4xeRNCTMO7tU76H9Mu+00xcsZUjyyfRsk6V\nrPIb9x6x8LcDXLgZSEJiMmWszOjhUo/JQ7pjYvTmN2K2aVCdVvWqYmmqvLG0rpMDAMGh4TSv7VSg\nPsOiYvnMrT0fd3fB53aQ2mIV4hXZ05A/LhXNaF7BNOuBrFdqlcm83kNeJNPEoWB9yp4GkRNZn82f\n4lifNavhgmm15mgbWyiVGzvWAiA5PAScmhQtcPGvV65cOdavX59nu9q1a+Pu7q6yzt/fX+nz/v37\nVbYLDg7OVmZlZUVGRka28vT0dOrVq8fp06dzjev48ewvhKlXr16OMfxdfr/7mzJy5EhGjhxZ0mGI\nN0zGyfwpjnFS9iaJnMi8Mn9ik9LQ19FEW1NDbX3KvFIUB3trc1ZO/CDPdjUr2nNk2TiVdT6/zVT6\nvHXupyrb+W35JluZpakxMX+uylaerlBQu3I5Dn+X+/i1d9HobGW1K5fLMYa/y+93Ly4GerrMGd6T\nOcN7qrWtEKrI+J0/26+GY6iriVttK6Xy/nVL079u6UL1KeO3EEIIIYQQQgghhPg3s7c2Y+X4/nm2\nq/meHUe+/VxlnfcvU5Q+b535P5Xtbm6cka3M0sSI6GPZcxWkKzKoXakshxZ9lmtce+aNyFZWu1LZ\nHGP4u/x+9+Iwb3gP5g3vke/2ZUub88tXg4sxIvFfYmdmwPcD6+fZroa9KfvGuKis85zWQenzhuFN\nVba7PCv7858WRno8W9EnW3m6IgPnsmbsGa36nK9sG9UiW5lzWbMcY/i7/H53dTPQ1VL5nYva9u8W\n9a3Dor51CnyceLe4uLhw+fJlwsLCMDZWfg5q+vTpLFiwAHd3d1q1agXA6dOnWbBgAd7e3qSlpeHg\n4MCHH37IhAkT0NPLORdfixYtuHfvHs+ePVMqX7lyJWPGjOHMmTO0bt06q/zatWvMnj0bDw8P4uPj\nsbe3x9XVlRkzZmBqaqq+H0A+PX/+nHHjxjFixAguXbr01vYpxN/J9Z0/0dHRGBgYoK2tvlTVxdGn\nEEIIIYQQQgghhBBCCCGEEEK8aXZm+izrVzPPdjXsSrF3VCOVdR6TWip9/m1oPZXtfKa1ylZmYaRL\n6JJO2crTMzJwtjdh90jV53xl2/AG2cqc7U1yjOHv8vvdi0u3WrZ0q2Wb7/YLe1dnYe/qxRiR+C+Q\n/BL5U5i8w1Ev05h44D49alrSzNGUI7cjC31+yUXxbpP8ivkj+RXFmyTjZ/50rW6JtbEOOlrK+RWr\nWBsC8Dg6mTr2xqoOzZGMiUIIIYQQJUeehhElwq22NV4PYzkZEEUvZ+XkrwduRlLeXI8mDpkTI++Q\nOAZt8qdzdQvOjalDKT1tjt95wRd7A4lMSGVOZ0e1xHT9aTyuv96i5XumHBxeE1sTXS4GxzJh/328\nHsZyYHjNHBPNv3iZhvNinzzPcXZMHSpZ5f8Fi5WsDArUPi9PY1KIeplG5b8mcH/naKGPtpYGN54m\nqO184t+jWbeBBPpe4Pq5YzTq5KZU5318N1b2DjjVaw5A4LWLLPusN/Xb9GDe3isYGJvie+Yw62d8\nQlxUOAMmLlZLTMG3ffl2WCeqNW7N1N/+xLy0HQFXPPhtzucE+l5g6m8n0dRSPYzFR0cyrk2FPM8x\nb+9lbB3z/3JRW0enArXPj7YDVCfRjwp7CoB1WUe1nk+oj3VTN2LvehF17SRWjXsp1UV6H0DPqjwm\nf73wLi7QG/9lg7Co35k688+hbVCKF77HCVz3BamxkTgOnKOWmOKDr3NrsSum1VpSc9pBdM1tib1z\nkfsbJhB714ua0w6goan6ukmLf4HPWOc8z1Fn3lkMylTKVzwpL56SFh+FoV3lbHX6pR3R0NImIfiG\niiNzF3vPB6NyNXJdHHnFoEylfMcrhEoqXhgohBBCCCHeHvLnmhBClKwM+UUs3nEDOzbjwo1Ajl24\njltb5Yeedp/2xqGMFc1rZa4rXLwZSO9Jy+jhUp8rm+ZhamzAYQ9fPlmwnvDoOBaPHqCWmHwDgun0\nxbe0rl+NP1dNxc7KHI9rAXz+7W9cuBHIyZVT0dZSvcE1MiaeCj1Vv6j47y5vmodT+fw/BPWpa1uV\n5U8jogBwLGOd775ecSpvW6AYhCgo2dOQP/9rrPo6fBaXAkB5i5yTG6siexpEbmR9Nm/FtT5r21b1\nS31SojKTk+tZly9wn0K8KTJvFe8KGSfzVlzjpOxNEjmReWX+xCSmY6yrvoekZV4p3jXy964Q6iXj\nd/74hMRSw9Yo14QqBSHjtxBCCCGEEEIIIYQQxUPWEYT475HLWojiN2TIEDw8PDh06BADBw5Uqtu+\nfTsVKlTAxcUFAE9PTzp27Iirqyt37tzB1NSU/fv38+GHHxIWFsby5cvVEtPly5dxcXGhXbt2XLhw\nAXt7e9zd3Rk2bBgeHh6cP38ebW3Ve/EiIiKwts77uS1/f3+qVq2a75iqVq1aoPYl1acQfyfXd/5E\nR0dTqpR6X0hUHH0KIYQQQgghhBBCCCGEEEIIIYTIJPvKhCgcyS+RP4XJOzzlcBBpigzmdanA0dsv\n8n2uf5JcFELyK+ZN8iuKN03Gz/z5pGkZleW3nyegoQFOpbOPbbmRMVEIIYQQomSpnuUJUcy617Dk\n66MPOOgXqTQBu/o4jodRSUx4vxwaf811/rjzAj1tTWZ0cMCmlC4ArrWs2HrlOTuuhaltAjbn+EPM\nDLT5pZ9TVkLadk7mTG1XngkH7nPIL5LetaxUHmthqM2TOU3VEkdxCk/IvPFpYZj90tfUAHMDbcIT\nUt90WOIt0KB9b7YunoT3iT006uSWVR5004fwJ8H0+HQqGn9dlNfcj6Cjp0ff8fMws868SdCkSz88\n9m/k/MEtDJi4WC0x7Vg6FSNTc0Z9uwlt3cyb9bVadqLPmNlsmPM5Pif20bhzX5XHGptZsu5qrFri\nKAmxkWH8ufUn7CtVp1KdJiUdjsiBZcPuPNj6NZE+B5Vu8scFXSUp/CHlek7g1WD2wvcPNHX0cOg3\nA10zGwCsmrjy/NxWws7vUNtN/oc75qBtZIbTZ7+gqZ05ZprXbkf5PlO5/9sEIn0OYdW4t8pjtY0t\naLr+iVrieCUlNjyr72w0NNE2Mif1rzYFkRwRgmHt9oRf2E3oybUkhgaiqaOPmXMbHPpOR9dc9Q1M\nIYQQQgghhBBCCCGEUKferRswacVW9pz2xq1to6xyn9tBBD8NZ+rQHlnrK0c8r6Gnq8O8kX0pY2UG\nQL/2Tdh4xIMtx86zePQAtcQ0ddUOzEsZsWnOKPR0MtcEOzWtxexP+vD5txvYd8aHvu0aqzzW0tSY\nWPd1aokjL2FRsfy0+0+qV7CnibNs6hZvH9nTUHjh8amsvRhK1dKGNCxXsES9sqdB5EbWZ/NWXOuz\nqqTGhhN6ci2G9lUpVamhWvoUQghReDJO5u1NjpNCgMwr8ys2KQ1tLQ2+O/OII7cieRiVjKmBNl2q\nWTCpTTnMDAr2uIvMK4UQQhSFjN/5ExKdTHsbQ3ZfC2ftpVACwxPR19GkTWUzprd3oIyJboH6k/Fb\nCCGEEHVAwPUAACAASURBVEIIIYQQQgghhBBCvC369u3LmDFj2LFjBwMHDswqv3TpEkFBQcyePTvr\nWbEDBw6gr6/PkiVLsLOzA2Dw4MGsW7eODRs2sHz5crXE9OWXX2JhYcGuXbvQ08vMxdetWzcWLlzI\nsGHD2LlzJ4MGDVJ5rJWVFRnyxi8hALm+8ys6OhodHR1mzZrF7t27CQoKwtzcHFdXV+bOnYuFhYp9\nuCXQpxBCCCGEEEIIIYQQQgghhBBCCCFEUUh+icLLLe/w3hsRHL4Vyeq+Tlga6RTtPJKL4p0n+RXz\nJvkVxZsm42fhhMensud6OL96PWNcq7I4WRsU7HgZE4UQQgghSpRmSQcg3k2l9LXoUNWcM/eiiUtO\nzyrfdyMCDQ1wq22dVTajgwN3pzfC3lRPqY/y5vrEJaUTk5hW5HjiktPxCYmleQXTrMnXK+9XznwZ\no++T+CKfp6QlpSoA0NVSfenraGmQ+Fcb8W4xMDahTqsu+F34k8SEuKxyr2M70dDQoFm31w+C9h03\nj1WeoVjYllXqw8rOgcT4WF7GRhc5nsSEOO5dv0SVBi3R1lW+9ms2awdAkJ9Pkc/zNkqIiWLl+AEk\nxscwbO7PaGpqlXRIIgdaBqUwr9OB6JtnSE98fd1EXNoHGhpYN3PLKnPoN4NGP91Fz8JeqQ996/Kk\nJ8aR9jKmyPGkJ8YRG+iDadXmWTf4XzGr+T4A8UG+RT5PQShSkgCyxfOKhrYOipTEAvWZoUhHkZJE\njP95wjy3U2nYchqsuInTqDXE3fPh5ryupL2MLXLsQgghhBBCCCGEEEIIkRcTIwO6NK/Dn95+xCW8\nvte5808vNDQ0GNSxWVbZvFF9CT22irI2ypuiHcpYEZuQSHTcyyLHE5eQyCW/e7SsWwU9HeUNme0a\n1QTAxz+oyOcpqqjYBAZMW0lMfCI/TxuGlqZsWxBvH9nTUDjRiWl8vO0OcclprHCthJamRoGOlz0N\nIjeyPpu34lifVSUtIZo7P35MWmIclYavQEP2NQghRImTcTJvb2qcFOIVmVfmjyIDUtIUGOposWNo\nDa5PasC8Lo4cvhVJl59vEv+3n11+yLxSCCFEUcj4nbd0RQZJqQrOB8Ww3TeM5b0rcXNyA9b0dcIn\nJI6uv9wkNqlg313GbyGEEEIIIYQQQgghhBBCCPG2MDU1pUePHhw/fpzY2Nc5rLZu3YqGhgZDhgzJ\nKluyZAlxcXGUL19eqY8KFSoQExNDVFRUkeOJjY3l/PnzvP/+++jpKa9NdurUCQAvL68in0eId4Fc\n3/mjUChITk7GyMiIU6dO8ezZM3744Qd27dpFw4YNiYuLy7uTN9CnEEIIIYQQQgghhBBCCCGEEEII\nIURRSH6Jwskt7/Cz2BS+PvqATlUt6FHTssjnklwUQvIr5k3yK4o3TcbPggl+kYT9rIvUWXKZZe6P\nmdauPONalc37wH+QMVEIIYQQomRp591EiOLRt7Y1h/wi+cP/BW51rElXZHDoViRNHEwob/56spWc\npmCj93OO3I4kJCqJqMQ0FBmZCWQB0jOKHsvzuBQUGbDnejh7roerbPM0JrnoJyphBjqZL19KSVc9\nyUpJy8BAR162+K5q2m0gPif34nvmMM26DUShSMfn5D6c6rfAyt4hq11qShJndq7jyqkDRDwOJiE2\nCkV6OgpF5s2UV/8vipjwUDIUCi4d3cGloztUtol69qTI53nbhD9+wPIxfYiNDOOLFbsoX7V2SYck\n8mDdrC+RPod44fsH1s3cyFCkE+lzCBOnJuhZvX6IW5GazPMzG4m8coSk8BDSEqJAoSDj1fWihusm\nJfo5ZCgIv7iH8It7VLZJfvG0yOcpCC09AwAUaSkq6zPSUtDUNShQnxoamqChSXpiLFVGr0fb0BQA\n0+ouvDdkEf7ff0DoiZ8p12tS0YIXAqj/1baSDkEIIYQQQuTiwKq5JR2CEEK8037adrikQxDirTCw\nY1P2nvHhsKcvAzs2I12hYN8ZH1rUdsKhjFVWu6SUVNbtP8OBc1cIfhpBVFwC6ekK0hWZ63av/l8U\noZExKBQZ7Dh5iR0nL6ls8ySs6IlGi+LB03D6TF5O2ItYdi36gtqVy+d9kBAlRPY0FMzDF0l8sNmf\n8IRUNg2uRs0yRgXuQ/Y0iLzI+mzuimN99p+Swh7iv/wDUmPDqTZ2E0blaxapPyGK0/Hjx0s6BCHe\nKBknc/cmxkkh/knmlXk79En2vye7VrdEQ0ODT7YHsMrzCZPb5v/+kcwrxbtk76LRJR2CEP9JMn7n\nTlNDA00NiE1OZ/2AKpgaZD6a6lLRlEXd3+OD3/35+UIok9qUy3efMn4LIYQQQgghhBBCCKF+e+aN\nKOkQhBBqtm1Ui5IOQYh3xpAhQ9i5cyf79+9nyJAhpKens3PnTlq1akWFChWy2iUlJfHTTz+xZ88e\ngoKCePHiBenp6aSnZ+7Be/X/onj69CkKhYLNmzezefNmlW0ePXpU5PMI8a6Q6ztvFy9ezFbm5uaG\npqYmffr0YfHixcybN6/E+xRCCCGEEEIIIYQQQgghhBBCCAHbhjco6RCE+FeT/BIFk1fe4QkH7gOw\nsPt7ajmf5KIQIPkV8yL5FUVJkPEz/xwt9HkypykxiWlcCI7l66MPOOAXwfYh1bPyNuWHjIlCCCGE\nECUr/3+5CaFmrSqZYWWkw8FbkbjVseb8g1jC41OZ3t5Bqd3InXc5eTeKL1uXo08tK6yNddHV1mDy\noSC2Xw1Ta0yD6pdmSY+Kau3zbWJTSgeAyJep2erSFBlEJ6bRuJTumw5LvCVqNmtLKQtrLp/cS7Nu\nA7njfY7YyDDcvlB+sfrPk4dy/dwxuo+YQtOuAzCxtEFHV5dN88bieeB3tcbUsvdHfDTjR7X2+ba6\nf92LH8cPQN/QiCm/nsC+UvWSDknkg1nNVuiYWBHpcxDrZm7E3jlPamw4Dn2nK7W7u2YkUddPUq7H\nl1g16YOuqTUaOroEbZxMmOd2tcZU2mUQFT9aotY+C0vH1AaA1LjIbHUZijTS4qPRdWpcsE41NNAp\nZYm2kSnahqZKVSZOTUFDg4QQv0LHLIQQQgghhBBCCCGEEAXRtmFNrM1LsffMZQZ2bMa5q3cIi4pl\n7qduSu2GzvmZYxeuM+Wj7gzo0BQbCxN0dXQYu3QTvx/1VGtMH3VtyY+TPlJrn+rg5XefAdN/xMhA\nnxMrp1C9gn1JhyRErmRPQ/5dfhTHx1vvYKSrxf5hNala2rBQ/cieBpEXWZ/NXbGsz/5N3L3L3Pnx\nY7T0jag5dT+G9lUL3ZcQQgj1k3Eyd8U9TgqhiswrC+/9SmZoaIDv4/gCHSfzSiGEEEUl43fuNDTA\n0kgHU33tbAlFmjqYoKEBfqEJBepTxm8hhBBCCCGEEEIIIYQQQgjxNunYsSOlS5dm586dDBkyhNOn\nT/P8+XMWL16s1K5///4cOnSIWbNm8cEHH2Bra4uenh6ffvopv/76q1pjGj58OGvXrlVrn0K8i+T6\nLrxOnTqhoaGBl5fXW92nEEIIIYQQQgghhBBCCCGEEEIIIUR+SX6J/Msr7/D2q2G434tmTV8nShvr\nqOWckotCgORXzIvkVxQlQcbPgjM10KZzNQvsTfXo/PMNVno+yfbzyo2MiUIIIYQQJUs77yZCFA9t\nTQ16OVuxwecZsUlp7L8ZgZGuFl2rW2a1eR6XwomAKHo6W/Fl67JKxz+OTs7zHFoaGqQrMrKVhyco\nT0DKmOiiqZG/PlV58TIN58U+ebY7O6YOlawMCnUOdbAppUtpYx3uhiVmq7sXnkiaIoM69sYlEJl4\nG2hqadO4kxtndq7jZVwMXsd3oWdoRP12vbLaRIeHcu3sURp1dKPHp1OVjo8MfZT3OTS1UKSnZyuP\njVS+mWJe2h4NTU0iQ0MK9V3ioyMZ16ZCnu3m7b2MraNToc6hTkE3fVj2eS/KVKjC2BW7KGVhXdIh\niXzS0NTGqlEvnp3ZQNrLWCK89qOlZ4Rl/a5ZbVKinxN17QRWjXpStseXSscnRz7Oxzm0yFBkv25S\nY8KVPutalAENTZIj8u5TlbT4F/iMdc6zXZ15ZzEoUylffeqa2aBjWprEp3ez1SU+vUeGIg1jxzoF\njtXIwZn4oKvZyjMUaZCRgYaW3Ex81135diBRAd60W3+/pEMpsBurPyf0/N6szy7fe2NgXa4EI8o/\nz0ktSAjN/JnrGJvTZs3tEo5ICCGEECWt5+czueh7m7ALu0s6lAL73/Tv2HHUPevz7SPrcbCzKbm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4Z04YedJxk6b3229tFxL+k9eSUPnsqLGUXByfidu97OVjR1NGHcvnt4PYwlMVXBhQcxfH3k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Gsa9CqK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\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pQvLNS4T//iXxYadRZ6Ri4eBGmSav4dnjk9zJvYBZPUi6Ecwry0MwsbTWeR3X/OYRsf1r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\nBFuY8t/Nxj6E1/rj5+OOe2U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h1vi4qxzctZVfvv+SsDW/8+vmA/jVrEVKYgIA3lV9SxzD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\nuVu936209G7XQOUmk6Z/fUL5RaXKKShWSNQR5ReV3lTPrx3IvKTM8wX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CFE8ZaTT9NMYcvQ5sUrnzZuGxfu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FwM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qWZnCJTsTOtjrALSfxwJI6PJ3QlbtVY1r7UgxOXU3hy6U6D2JlvfXu+mdKLyIRUnpj5PR7/\n+pKRK3+mQ1NXVowLNWg7ObuQ2RvC6de6MYPbeT6EqxX+rvILizh2JobObZ9ApTTM1ekVEghA5Pk4\no+O6t29lsO3qJC1EnJxuYkIHQFdezrAnO+u3c/IKOBUbT+eglkb5T92qznMo8pxROz07Gi5E3KVt\nSwDOx0sLAKmU5jw7oAdR0XHEXr6ur7f5l0PIZDLGDuplsq8Pqrgq/8m81vwnc4pK6p5o4Z0ZE0hM\nzWDi3A+5cjOZvIJCvtu9jy82/wRIeWQA5RUVFJdqOXjiLOt27WPN4hlcP/AD6z+YTcSZWLqMeY3c\n/Nq/d7Nz8xk5/W3yCgr5YulMFHLxmp0gCIIgCIIgCIIgCILw8OUXazlxKYlO/g1Q3jXO36NlYwBO\nXjbOBe8S0Mhg20WjBiAlu+5FAgB05RUMbt9Uv51TWMKZK6l08m2AytysxvMciTVcIB2gW1X/bgv1\nk2IjMTek2IjSXMHTof6cSkjhwq0Mfb3txy5KsYYu/ib7+qBKqt6TNK811qCgqPTe5y+4lZnPxsMx\nvPhkazRqwxxGfVwi5ibfH4rh4389yaXPXuKLV5/ixKUkei/4gdyi6nHP5OwCZn17gH5B3gxp/+ji\nLYLwOIg8DOG/XX6pjsjruYR42aE0M4wVdWsqxQFP3cw1Oi7U295g26VqsvPUfNMTjusqKhnU0kW/\nnVus4+ytfDp62qG6qw+3zxN+JZu7dW1q2IeOnnYAXEiRnhWUZnJGtHHl9M08LqZWx8x2nk1FJoOn\ng9xM9vVBlVTF88zNap5k3lwhp7js/hYyyCkq4/l158gv0fHRSD8U8uq2Kysr0ZZXYKWUs3lia87O\n7cSSgU3Zcz6Nvp9EUVBafS5fV2u+HNuCkzdyCVx2lEbzDvLM12do30TDh0PFfVsQBEF4MLa2tgQG\nBjJu3DiWLVvGnj17SEhIICsri6ioKFavXk3Pnj3Jzs5mzZo1DBw4EC8vL+zs7AgKCmLcuHG8//77\n7NmzhytXrlBZWfnAfYmOjiYhIYHBgwcTHBxMeHj4Q7zSv4/8kjJOXMkkxMfZ6Dmuu6/0juOpa8b5\nXJ2buRhsu9hIYwAp9zQvSiWD2jTQb+cUaTlzI5sQHyfjeVGaS+c5esl4kaVuVf27LcTHGYDYROl9\nPqWZnJHtGnP6ehYXk6ufRXecvCGNt7RvwqNSUvWMplTUnEdlbianWFv3c1xFpbT4pJXSjG2vdiH6\nnQG8M6I1u0/fpPeHv1NQw3jN1fQCXF7dQsCcPSz/OZZ5A1swo49fredIzC5i8/HrTOjig8aq5nc3\nBUEQBEEQBEEQBEEQBEEQBEEQBMEUkT/2aDzO/DFp7YYKjiRks+lkMqtG+BI9P5TPRwcQeS2Xfv+J\nIq+k9pzyuvLSBEEQBKEuZmZmeHp6MmDAAN566y3WrVtHVFQU+fn5REdHs2HDBsaOHYulpSVbtmxh\n1KhRBAQEYGVlhb+/PyNHjmTRokVs2bKFmJiY+84ZKyoqIjExkfLyctauXUvjxo1ZvHgxhf8j68eJ\ndbUeDbGuliAIgiAIgiAYMzNdRRAEQRAE4Z8jNz2ZyooKIvZuImLvphrrZKckGmzL5QqsbQ0D1LKq\nwGpFuekJvmQyGbZO1S/WZqdJi6rYOroY1bWxd66qYzghm8LM3KgPalspSJ6bWf0ib5dhz7Nvwycc\n2bWep19/D4DI37bhG9wVB7cGPCpKC2mwubxMW+P+srJSlBaWdbbRult/pq3exvaP32b+sLaorNT4\ntevGSx+sY9HTHbFQWz9Q3479tJFv3p5C7zGv0HXERGwdXbgRd471S6exdEwXZn31G/XsHB+obUEw\nxfe1DfdUzzF4CI7BQx5xbwTh8UpOTaeiooIfduzlhx17a6xzK8kwmKhQyLG3szUok1ctoHN7gZ66\nyGQyXJ2d9NtJKdI90tXZ+Hve2dHeoM5t5mZmRn2ws5W209Iz9WUTnhnGR19u4NvNu/hg/usAbNnz\nG907BdPQ49ElpllaShOEaMtqDiSWasv0dWozsHc3dn2zmgUffEyrnsOwVlvRvVM7vv/0A9r2eRpr\na7W+7vfbf+Jfb77NtBfHMGnMCFydHTkbE8eU2UsJGTCGA9u+wtFeeiY5vONbo3MN7dcTuVzOqMkz\n+fen37Bo5pQHvXRBEP5GUnKKqKisZGtEAlsjEmqsk5htmMCjkMuwU6sMyuQy6XeVrrzC5Dllsuok\nF4CUqvbvLLvNyUb67ZF8Vx/MFXKjPmjU0qQ96XnViTNjOzfjs99j+P5oPItHtgNgZ9RVOvu6U9/h\nwX6X3AtLpTQcX1Ze8z2vtKxcX6cmcpkMuUxGfrGWr1/qoZ+QqIufO8vHdGTUqt/4bF8Mbw1qDcDP\ns4wn1h0Q2Bi5TMbzn+1n9S/nmT24jVEdQRAen6w0aRzr8J6NHN6zscY6mXePYykU1NMYjiHdfqYu\nr+X75U4ymQw7x+pxrMxUaRzLzsnVqK7GQRrHyko1XEBYYWZu1AfrGsaxeo14gR+//Zj929fx3FvL\nADj681ZaduiGk3tDk319UKqqMSpdbeNY2lKUlsb3lzu16zGAuZ9vZ8PKRUzvH4iFlZqWHbrx+srv\neH1IeyzV9fR1/zP/ZQAmLfw/k327n3YFQRAet9TkZCoqKti+aQPbN9U87pmUeMtgW6FQYGfvYFAm\nk1Xdl3T3Fl9xdq0eZ0lJku45zi7G9yVHZynmkpJseG80Mzc36oPGTrpPpael6sueff5F1n6yio3r\nv2bhe8sB2L1tM6Fde1C/geGCOQ+TpZV0zynT1nxf0paWYmnivtSn/yDWb9vDsrfn0bVtC9Rqa0K7\n9eDzdZvo1bENamvr+64rl8uRy+Xk5eXyxYYt2Gqke3nnbj1ZtuoTxgztz5qP/4+Zcxc9hE9BEATh\n72XHh6/dU70RPYMZ0TP4EfdGEIT7IeLzgiD8VW7HzrYcu8yWY5drrJOUZbjoqkIuw97aMLZ/O3ZW\nXm76hfu7Y2fJ2UUAuGjqip0VGZSbK+RGfdBYS7G0tDtiZ+M6N+ez387z/ZE4ljzdHoCdJxLo4utB\ng0cZO1NJcTFtLfkitxcCqc2dsbNvXumFxkq6tq5+Hiwf14mnV/7Cp7+dZ9bgQAA2H4tn+teHeal3\nC57r5oeLrRXnb2Tw+roj9Fqyk59mD8ShnvR5TfvmMAAfjg15aNcr/D0lp2VSUVHJxp/2s/Gn/TXW\nuZViOKGDQi7H3tbGoEx2OzZ+r/lPTtVxlqQ0KV/pzrLbnKtydm7Xuc3czMyoD3a2UowhLTNHX/bC\nsD6s/m4H63b+xrKZLwKw9dfDdAtuRUM3Z5N9fVBWFtK/pbI68p+sLFQ17rttQLcO7Ph4MQtXf0Pg\n0H+htrKke3ArvvtwDsEjp2BtJX33yWUy5HIZeQVFbFwxD42N9L3VvX1rPpr3KoOnzOej9duZ//JY\no3NcuZnM0FcWkJqZw7bVi3iiudefuWxBEARBEARBEARBEARBqFVKdoEUazhygS1HLtRYJzEz32C7\nrliDruIe39PRVI/zJ2dLsQwXjdqorlNVTCL5rnhHjbEGtbSdnlsdlxjXvQWf/nyS7w/GsGRMFwB2\nHIujS0AjGjgajmU+TPr3dGqLNZSVY6W696m1NoXFoquoYGy3Fkb7bscl8opK+fa1AfrPoWuLRix/\noSdPf7CdT/eeZNbwjgBMW/MbAMuf73Ff1yQIj5PIwxAESWqelorKSradTmHbaeOJ1gGScg0X6FHI\nZdhZmRuU3V7/RVdxbzkBzvWU+u3kPKn9O8tuc7KWzpN8Vx/MFcZ90FRtpxdU566PaefBmiM32RiV\nxKKnpEnfd51LJdTbnvqauucs+DMsqyazL9PV/Hloyyv0de7FtcxixnxzlowCLevGtyTA3fAdrD0v\nBRkd0z/AGblMxsTvzvPJoeu81dsTgK2nU3h92wUmdWrI+PYeuNRTcj6pgDd3XKTvx1HsmhyIg9rc\nqD1BEARBeBAajYbAwEACAwMNynNyckhISCAmJobY2FhiYmJYtWoVycnJ+uO8vLzw8/PD399f/19P\nT886z1dYWEhKSop+YaCTJ08SEhJC9+7dWblyJS1btnw0F/oXSMktkeZFibzO1sjrNdZJzDHMq5Tm\nRTF85qoeb7nH3E6b6meolKoFgFxsjOdfdKpa7DH5rkWCpHlRDPugnxfljoUhx4Z48vmBS3x/7BqL\nhz4BwK6TN+nczIX69nW/j/hnWCqlZzRtLfPEaHXl+jq12ft6d6OyAa3qI5fJeOGLcFbvu8js/gEG\n+5s4WZO6egQ5RVrC49OZs/U0O0/eZPMrnfVzq9xp84nr0jhOSBOjfYIgCIIgCIIgCIIgCIIgCIIg\nCIJwr0T+2KPxOPPH9PPPlOj4ckwLbC2l/PHOPva8P6QZz359ls/DbvBGL+N4u6m8NEEQBEF4EObm\n5vj7++Pv78+IESP05Vqtlvj4eE6ePKnPGVu/fj1Xr16lsrISGxsbfHx87jln7MKFC/o8MZ1Oh06n\nY8mSJaxcuZJFixYxZcoUzMzu/b2qfxqxrtajIdbVEgRBEARBEARj/72/rARBEARB+J8WOmQ84+ev\nfiznksnkyOU1BIgrjQPKlVRWHSMzbKNq0W7Dw6W68jv2uTZuStM2IUTs3cSI6Uu4FR9DyrV4Bv5r\n9p+5BJNsHaVFVvOzM4z2VZTrKMzNRtPG9MInLUJ60SKkl0FZ4uVYAJw8Gt93vyrKdWxYNgOf1h0Y\nNvVtfblnQBAvvP0pb4/uxK/rVjF82pL7blsQBEG4N8+PGsKny+Y/lnPJ5TIUitrvmYZl0n/vvufK\na7rnYnzPbebVmE7t2vD9jr28O3s60XHxXLpyjXmv/evPXIJJbs6OAGRkZhvt0+nKyc7NxcPVdIDx\nya4hPNnV8N4cEyctStekoYe+vWnzl9GxbWuWvjVVX69tqwDW/vttgvuNZsXn63h39rQ6z9W7S0dk\nMhknzkSb7JcgCP8sYzo1ZcW4x7PAoVwmQyGXGZXf/o42KKvlO/7u7Tvryu/Y5+NqSwcfV7YcT2DB\n8CAu3Mrmckoubwxo/SeuwDQXWynZJjO/xGifrqKCnEItbk1rn3RJJgOHehZorJRGkxV1bOqKTAbn\nb2bWcnS17gEeyGRw8mq6ybqCIDwePYY/x0uLP34s55LJ5cgV9ziOVVnzOFZNz9To61bv8/Bsil9Q\nCIf3bGTszKXcuBRD0tV4np4y909cgWkaJ1cA8moYxyov11GQm42fs5vJdlqH9qZ1aG+Dshvx0jiW\nS/3GAOzfvo4zR35nxop1aKrGzx5Gu4IgCH+l0eNf4MPVnz+Wc8nlchQ13JdqHuu5//vSnfu8mzYj\nOCSU7Zu+Z+6SZVyMiSYh/hIzZi/4M5dgkouLdF/KzDB+/tbpdORkZxEcEmqynW69+tCtVx+DsrjY\nGAAaNfa877oymQwHRydsNRpsNXYGdduHdEYmkxF99ozJfgmCIAiCIAiCIPwvGdO5OSvHm/4N9zDU\nGjurMz/CsPyeY2duGjo0dWPLsXgWjminj529OSjQ6PiH6fbL67XGzgpKcb2X2JlahcbK8MX2jk3d\npNjZjQx9e299d5RgH1fmD2+nrxfo6czHL3Sh29vb+fiXsywcEcz3R+I4EH2LLyb3wLmGF+yF/07P\nDX2STxbUnR/zsEj/vu8x/+l2zjF3j4nV/v1w576mTRrQKTCAH37az9LXXiAm/hrx124xd/Kzf+oa\nTHF1ksabMrJzjfbpysvJzs3HPTDAaN/dencKoncnw0UbYy9LCzc1qS+Nu8lkMhztbNHY1ENjYzhJ\nRaegFshkMs5eNJ6sI+LsBUZOextrK0v++GY5ft6N7u3iBEEQBEEQBEEQBEEQBOFPGNutBSsn9jJd\n8SGo/T0dY7XGGuo43iDW4G5Ph+b12Xw0loWjQ7lwM4PLydm8NazjA/b+3rho1ABk5hcb7dOVV5BT\nWIKbXf17bm/38Uu09nSloZON0T6ZDBxsLNGoLdCoDRc+CPGtj0wG566lAbDhUDT7z13ji1f741zV\nR0EQBOHv75m27iwf2vyxnOvB7tMP9j6tt5MV7Zto2HY6hXl9vbmYUkBCehEzezR54P7fC5eqhYky\nC8uM9ukqKskpKqN9Y809tRV1PZfn1p9DrVSwc3IgzV3u/f7arak9MhmcupmnP/ecXXG0a6Rhbh8v\nfb02DWxYNcKPXh+d4NPD15nX1/uezyEIgiAID0Kj0RAYGEhgoGGeXnZ2NjExMfrFfmJjY9m3bx8p\nKdKig3Z2dnh6euLn50dgYKB+0SA3N+m96YsXLxrkIZVXLcgSFhZGq1atGDZsGMuXL6dRo/+eXJln\nOzZhxegg0xUfggeaF4W7n+OM29Xnft2xz8elHh28ndgaeZ0Fg1tyISmXy2n5vNHP/8Ev4B642Ejj\nHpkFpUb7dBWV0rwoXpYP1HZ3X2lelFPXsmqto7FS0u8JDzzsrej9we+s3neR+YNaGtXbc/oWrRra\n08BejL0IgiAIgiAIgiAIgiAIgiAIgiAIf57IH3u4Hmf+mEwGDmpzbC3NsLU0XJa5QxM7ZDKITiq4\n73YFQRAE4WFTKpX6fK875ebmcvnyZYO8sVWrVpGcnAxIuWa3j/Pz88Pf358WLVoQGxuLXC6noqJC\n35ZOpyMnJ4cZM2bw0UcfsWzZMoYPH17js8N/C7Gu1sMl1tUSBEEQBEEQBGNmpqsIgiAIgiD8c9g5\neyCTy8lMvvGX9cHetT4ymYyc9BSjfblVZXYuHgblOm0pxQV5WFpXTw5WkCu9rGrj4GxQt8uwF1g7\ndwIxEQe4GHkIta0dbboNqLNPBTmZTO9uOpC+dHsUro2bGpVrnNywdXAhMeGC0b6kq3FUlOto4t/G\nZPs1STh3HADv1h3u+9jM5JuUFBbg1qSZ0T6Xxj5S/67EPVC/BOF+XFj5LHnxJwj+T/xf3RVBeGw8\nXJ2Ry+XcSEz+y/pQ390VmUxGcqpx0C0lTSqr7+ZiUF6q1ZKbX4BtverFf7KqFh5ydnQwqDvx2WE8\nN20ufxyJ4GB4JPYaWwY92a3OPmVm5eDRprvJvp/9YzvNvBoblbu5OOHi5EDsJeNFiC5evopOV05g\nyweblCPi5DkAQoKkoOyNxGTyCwtp7m38jNDUs3HVOa8AoC0rIyYugXpqK7ybNDSoW6rVUllZiYVK\neXczgiD8Q7nbWSGXybiZZZyc+tj6YK9GJoOUHOMJmVNziwDwuGtSHq2unLxiLTaW1d9H2YXSBENO\nNoaTCY3r0oyXvjjEodgkwi4mY6dW8VRrw++3u2UVlNB8xg8m+3508VB8XG2Nyl01VjjbWHIxKcdo\nX3xyLrqKClo3dqyz7ZYNHThVQ7KJrryCykowN5MWDdTqKriYlI21hTmezoaTUJfqpLoW5gqT1yII\nwqPl4CqNY2Uk/XXjWI5V41hZ6cbP9dkZ0jiWg6vhBPhl2lKK8vOwqlf9/ZKfI41jaRwNx7F6jZzA\nqjdf4Fz4fs5HHMLa1o52Pesex8rPzuT5ENOTCK768RQensbjWPbObmgcXbh52XgcKzEhjvJyHV4t\nHmwR47jTEQD4BkoLE1yPiwZgxYxxrJgxzqj+jEHSosKbzuegUNQelr27XUEQhL+Cm4cHcrmcxBt/\n3X3Jvb50X0pNMb4vpVWVuXsY3pe0paXk5+VSz6b6GTw7S0rmdnI2vC+NfeFFXpkwjrADv3P00AE0\ndvb0HTC4zj5lZWbQsombyb4fjIrGu2kNsQo3d5xcXIm7EGu073LcRXQ6HU+0ebDJZqOOHwOgbQfT\nLxvUVDfgidacjjphVFdXrqOyshJzpRjrEQRBMGXIGys5dv4yKb988ld3RRAERNxeEIRHx91ejVwm\n41ZG/l/WBw997KzIaN/t2Jn7vcTOCqSXq++OnY3v2pzJaw5wKCaRsAtJUuysTeM6+5RVUEKzaetN\n9j186Qh83Iwn4HHVWOFsa8XFpGyjffFJOVWxM6c6227ZyJFTV9KMynUVlVRWglIhxc5uZRRQUFJG\n0xr64V0V17uULMXwYm5K490TP/uDiZ/9YVS/84KtACSvnYCZXF5n/4S/P3cXR+RyGTeSjP9/9LjU\nd3WU8p/SjScoSEnP0te5U6m2jLyCQmysq//dZ+VI31HO9nYGdScM78fzsz9g/7HTHIw8i51tPQZ2\nrzsekZmTR8Ouo0z2/fSOz2napIFRuZuTAy6OdsQmGI81xl25ia68nEB/4xjPvYg4K42zdWhdnT/V\nytebyPPGucLlunIqKytRmpsblJ84d5FBL82jWZMGbFu9CCf7e5skTBAEQRAEQRAEQRAEQRAelLt9\nPek9nYy8v6wPHvb1pFhDtvG7Qqk5UpmHQz2Dcm1ZOXlFpdhYqfRl2fnSez5OtoaTtj7XoyX/+mQv\nB6OvExZzEztrC54K8q6zT5n5xTSb/KnJvh/78Dl83O2Nyl3trHHWqLl4y3h89VJSFrryClp7uRjt\nq8n1tFxibqQzfWC7Wus80diFkwnG+Y26Cuk9HaWZ9J5O7I0MACau/pGJq43bCX1rHQAp66ZjphCx\nBuHvS+RhCP8r3GxVUk5AjvFk5Y+Lu60KmQxS80qN9qXla/V17qTVVZBXosPGovp9pewiaeEcJ2vD\nPPCx7TyYsimGw/FZHE3IRmNlTl//uuPxWYVlBCwNM9n3wzPa4+1kPJm7yDVgTAAAIABJREFUi40K\n53pK4tKMnz3i0wrRVVTSqkE9o313O3kjj9FfncHHWc268S1xtDbOcS8rr+BiaiHWSgVNHA37otVJ\n+QMWVe/e3souoaC0HB9n4z57VR0bn2acmyEIgiAIj4udnR2dOnWiU6dOBuWpqalER0frF/uJiYnh\nxx9/JDtbyr9zdnYmICAAtVpttMAPQFmZ9Jywa9cu9uzZw/Tp05k1axYazT83b8ZdYyk9x2X9dfdu\nd42VNN6Sa/wsmZonlXnYGeZranUV5BWXYWNZndOUXSg98znVszCoOy7Ek5e+Pc6hi6kcuZSGxkpJ\nvycM56+8W1ZBKb6zd5vs+5F5ffBxMX4ec7W1xNnGgrhk43Gs+JQ86TmukfE4zW1l5RVcSMqV5jpx\nsjbYV6orp7ISVObSs1lidhHL98bSwceJke0M5xZo5irNYxCXYtyP6xmFxCTmMK3341mMUxAEQRAE\nQRAEQRAEQRAEQRAEQfjvJfLHavZPyh8DaOFRj1M3jWOLt+efMVfIHqhdQRAEQXgcbG1tCQwMJDDQ\ncO2MtLQ0zp8/r88Xi46OZtOmTeTmSuvsubi4YG5uTmmp8TNERUUF165dY+TIkbRp04aVK1fSuXPn\nx3I9j4tYV6tmYl0tQRAEQRAEQXj4al91UBAEQRAE4R9IZaWmaeuOxEUdITczFVuH6gm64k+Hs27p\nNCYsWUNjv9b33bb89sIdlZV11rO0tsGzZTviosLQlhajVFUPjkYfkxYHCejYw+i42Ij9BPasXnQ0\nLlIKajdtY/hSdmCPgfzwgT0RezcSF3WE9n1HYqY0DLrfzVrjwBen/twEccF9R3Bg8xfkZ2dQz656\nIDXy1+3IFWa0e3J4ncdvWj6Ls2G/sGRbJAoz6SXkyooKDm37GrcmzfB+ov1998nGwQUzpYrEy8aL\nqCZVLfjt6F73wLMgCFCpKyPhm5mkH9tKo5HzcX9yco31ilMSuLn9fXIvHKFCV4rKoQEObfvj3ucl\nFCp1jccI/72s1VaEtG3N4WNRpKZn4uLkoN939MRppsxZypcrlhDY0u++2759z600cc+1rWdNcJuW\nHIqIorikFEuL6vvhvsPSAte9uhgvXvRHWARD+/XUbx88FglA5/ZtDOoN6duDGYs+4IcdezkUEcWo\nwX1RmVgE28FeQ8m1U3XWMWXUoL58vn4zGVnZON6xQNPWH3/FzEzByIFP1nn8G4uXs3d/GGd+34a5\nmTT0U1FRwZc/bKO5dxM6BD0BgIuTAyqlkpi4y0Zt3C5rVN8dgFKtlu7DnyfoiQD2bVprUPeXA0cA\n6Nqx9olOBUH4Z1GrzGnv40J4XAppecU435HwERGfyszvwvn4hVBaNao7waImMrmU8GrqO97GUkmQ\npzNH45IpKSs3SLA4EJMIQDc/40mKDsUmMSCwsX77yEVpkuWOTQ0nbx7QphFz1Cq2RiRw9FIKw4I9\n9ZMu18be2oK0Nc/XWceUYcGefHXwIpn5JTjcMRHTzsirmMnlDG7rWefxQ9t58kf0LQ7FJtHFz11f\nfiROus5gb+k6tbpy+r//E22aOLFzZl+DNn4/fxOATs3d/tS1CILw51lYqfEN7Ej0iTByMlLROFZ/\nV104Gc7nC1/l1WVr8QpoU0crNZPJ7m0cy6qeDU1btSPmRBjakmKUFtXf+WeO/A5Aq049jY47e2w/\nHXpXj2NFHz8MgF+Q4ThW+96D+Opdew7v2UjMiTA6938acxPjWPXsHNga++cSJ0P7j+SXH9aSl5WB\njX31/eroz9tQKMzo1K/ucaxvlr1F1MGfWfXjSYNxrH1bvqa+ZzOatZbGsZ6f/QHPz/7A6PjfNn3B\nmrens2LXCRr6+N13u4IgCH8Ftdqadh07EX7kEOmpKTi5uOr3HQ8/wqxpL7FqzTe0bB1YRys1u9ex\nnno2tgS2a8+xsEOUFBdjYVl9Xzr4xz4AuvTobXTc4f2/89TgYfrto2EHAWjfqYtBvX4Dh2Jn/xrb\nNn7PsSOHGDJyNEpV3fclewdHbuWV1VnHlCEjRvHtF5+RmZGOg2P1S4+7t2/GzMyMQcNH1nn8olmv\n8/svP3Ew8jxmVQtXV1RUsOHrtfg0a07b9h0fqO7gEU9zYN8vHD7wO527Vd/vww8fBKBdh5A/dd2C\nIAjC39upi9f494a9RF24QmZuAR5OdgzsHMhb4/pjbWVhugFBEB66e43bC4Lw+KlV5rRv6srRuGTS\ncotwvmNx04hLKby+LoxPJnalVeO6J7qpSVXojLp/MVfFzrxcCI9LpkSrw0JZ/RrIgehbAHT3b2B0\n3KGYRAYENdFv346dhTQzjBMNCGzCHOtjbDl2maNxSQxr731PsbP0L1800fO6DQv24qsDsUaxsx2R\nVzCTyxkS7FXn8UODvfjj/E0OxibS9Y7Y4ZGLSQAE+0jjG862VijNFFxIzDZq43ZZw6oFbt8Z3YF3\nRncwqvfNwQu8sf4IhxcPx9fDzmi/8M9kbWVJSOsAwqLOk5qRjYtj9f+2R09F8+qS1Xzxzkza+Pnc\nd9ty2b2NidlYqwlu2ZzDkecpLtViqarOTfo9/CQAPTsaj8n9cew0Q3pVx2UORZ4FIDQowKDeoB4h\n2Nva8MNP+wmLOs+oft1QKc2pi4PGhsIze+usY8rTfbuyZvNPZGTn4mhXPenD1l8PY6ZQMLxPlzqO\nhrc+XMPPh09wcsdnd+Q/VfLVtp9p1qQBHVpVx19G9unKb0ei2B9xmu7tq/PDb38mHVpX172elMrg\nKfPxaezB3jXvYa02nABDEARBEARBEARBEARBEB4FtYU57Zt7cDT2Jmk5hThrqt/HjYhLZMaX+/jP\n5L608nSpo5WayW+/p2Mi2mBjpaKtjztHY28axRr2n7sOQLeWjY2OOxh9nYHtmuq3j8RK76R09K1v\nUG9AWx9mW1uw5cgFjl64xfAQX5QmJlt1qGdJxoYZddYxZXjH5ny57yyZecU43PH+086IOMwUcoZ0\nuLdFwY9fkt5VCmjkXGudoR2b8fvZqxw8f52uLaoXKL/9mQQ3k97zeWdsV94Z29Xo+G/+OMfMr34n\n7P1x+Na//3eyBEG4PyIPQ7hXaqWC4Ma2HLuSTVq+Fud61fG649dyeHNHHB+N8OOJ+qYXnrlbdU6A\nifu0hRmBDW0Jv5JDSVkFFuZy/b6D8ZkAdGtqb3Tc4ctZ9A+ovneFX5Hi3+2baAzqPRXgxLw95mw7\nk0L4lRyGtnJBaSanLvZqc5Le615nHVOGPOHKNxG3yCwsw0FdHaPcfS4NM7mMQS3rfva5mV3Cs1+f\nwcvJis0TW2OtqvnZolRXyaDPTtK6vg3bJhm+h/dHXAYAIV5SLNi5nhKlmZyLqYVG7VxMld5nq28n\ncigFQRCEvx8XFxdcXFzo0cNw7sLk5GT9Yj8xMTFERUXVusAPQFmZ9J7cihUr+PTTT5kzZw7Tpk17\n5P1/FNQqM9p7ORIen05aXgnONtX38IiEDGZuPMnHY9vRquH95/vJZbfnRam7no2lOUGNHTgan2Y0\nL8rBCykAdPN1NTruUFwqA1pVj60cjU8DoIOPYR5q/1b1mbP1NFsjrxMen87wtg1NP8dZq0hdPaLu\njpswNKghX4clkFlQioN19fuXO0/dxEwuY0igcb7qbaW6CgasPECbRvbsmNbVYN8fsdJnEtpUeoZ1\nsFax49QNohNzGN62of5zBzh3U3q2bexobXSOE1ekZzx/D43RPkEQBEEQBEEQBEEQBEEQBEEQBEG4\nHyJ/rGb/pPwxgMFPuLA/LpPD8Vl09qn+rG5/Ju0aV38m99OuIAiCIPyVnJ2d6dGjh1HO2M2bN4mJ\niWHu3LmkpaXVenxFRQUAZ8+epUuXLnTv3p1+/fo90j4/TmJdrZqJdbUEQRAEQRAE4eGrezRVEARB\nEAThH2jYtMXI5Qo+mjqClGuXKNOWEBcVxpfzJ2GmVOHh7ftA7WqcpAHBK9GRlGlLqCjX1Vp3xLQl\nlBQV8PXCl8lIvE5pUSGxxw+w85MleLdqT2CPQQb1lSpL9qz9gNiIA2hLirkVH83WVQuwdXChbe+h\nBnXNlCo6DniGE79uIyc9mU6Dxz3Q9dyvfhNmYm3nwOezniPt5hXKtCWc+HUrv67/iP4T38DetfrF\n4tjjB5jYxobNK+fqywJCepGeeI0Ny16nIDeL3MxU1i2dSmLCBcbPX43sjpdw75XK0oonx07l0qmj\nbP/4bbJSb6EtKebK+Ui+XToVq3q29Hzm5Ydy/YLw30pXlEvsitGUpF+rs15x0iXOLe5DWX4G/rO2\nE7TyLA0GziDpl0+J/0xMfva/6t3Z01Ao5Ax5YSpxCdcoKdVyOCKKF2bMR6VU4t/M+4HadXeRJqY4\ncSaaklItOl15rXXfmz2NgoIiJs1cyLWbiRQUFrH/yHEWLv+EDkGtGNLHMCBtaaHivY/W8kdYBEXF\nJZy/GM/c91bh4uTAsKcMFxNXKZWMHTaAzXt+JTk1neeeHvxA13O/3poyAQd7O56dMouEazcpKdWy\nec+vrFyznlmvTKSBe/UkH/uPHMeicRtmvbNSX9a7awhXbyQybf4ysrJzSU3P5OXZS4mJS+DTZfP1\n91y1lSWvTRrLkROnWPDBx9xKTqWouIQTp88zZfZSNDb1eOX5ZwCop1Yz/7XJhB0/yRuLl5OYnEpu\nfgFbf9zHzMXLaenblInPDEMQhP8eC4YFIZfLeHb1PuJTciktK+doXApTvjqM0kyOr/uDLXDoppEW\nxzx5NYPSsnJ0VQlANVk4rC2FpWVM/SaMGxn5FJaWcfhCEu/tPEU7b2f6BzYyqG9hruDfP53hUGwS\nxVodsbeyWbI9CmcbSwbdscglgNJMwaiO3uyIvEpKThHPdmrK4zC93xM4WFvw4pqDXE3Lo7SsnB2R\nV/nkt2hee+oJ6ttXT+h9+EISzpO+ZtGWSH3Z0HaedGzqyqvfhBERn0qxVseRuGTm/BBBE2cbxlRd\nh7WFOW8NbE34pRTmbz5BUnYhecVadkVdZd6mE/jXt2d852aP5ZoFQajb2NeXIFcoePel4SReuURZ\naQkxJ8JYPetFzJQqGvr4mW6kBvYu0jhW/LkoykpLKK9jHGvs6+9QXFjAJ3Mnk3brGiVFhZw7doAf\nVi2meZv2tO991ziWhSVbP13G2fD9lJYUcT0umu/+PR+Nowsd+xqOY5krVXQd/CxH9m4lKy2Z7sPH\nP9D13K+hk97ARuPAitfHkXLjCmWlJRzdu5XdX69i2OQ3cXSrnmTu3LEDDPezZt2Hc/RlrTr1IvXW\nNdYumUF+ThY5Gal8tvBVbsbHMnnxJw80jvUo2xUEQXhY5i5+D4VCwfgRg7h8KY7SkhKOhR1i+qTn\nUKpUNPP1f6B2Xd2lhPPTkccpLSlBp6v9vjR3yTIKCvKZ8fJEbly/RmFhAWEH/uCDJQto274j/QYZ\n3mssLC35vw/e4fCB3ykuLuJC9HneXTAHJxdXBgwdblBXqVIx4pmx7N62idTkJEaPe+GBrud+vTpz\nFvYOjrz03DNcu5JAaUkJu7Zu4rOPVjD1jTl41G+orxt24A/q25izZO6b+rJuvZ7kxrWrzHn9VbKz\nMklPTeGtqZO5eCGGD1Z/bnD/uJ+6g0eMpn2nzrw2eQLHw49QXFxE+OGDzJ85ncaeXowe/3g+H0EQ\nBOHxO3r2Ek++ugyluYJ9H8/i6s6VLHxxKGt27mfQzBVUVJiYsVwQhIfuXuP2giD8dRYMb4dcLuOZ\nVb8Sn5xTFTtL5uUvD6I0V+DrYTxpzr1ws5NiQyevpJmMnS0aEUxBiZZXvz6kj50dik3k3R1RtPN2\noX9QY4P6Fkozlu85xcHYxKrYWRaLtx7H2daKQXe9SK00U/B0Rx92nEggJaeIMaGPJ440/alWOFhb\nMPGzP6pjZycS+OSXc8wY0Jr69tWLeByKTcRpwloWbj6uLxsW7E3HZm68+uVBIi6lSLGzi0nM3hAu\nxc46Swu8WqnMmNKnJccuJfPOtkgSswop1uqIupLGjHVh2FopmdQr4LFcs/D3s2T6CygUcoZNXcil\nq1KeTljUOV6c929USnP8vBqZbqQG7s4OAESej5Pyn8prz39a+toECoqKmLxgBdcSUygoKubA8dO8\n/ck6OrTyY3DPEIP6lioly9b+wP6I0xSVlBJ96SrzV32Ni6MdQ3t3NqirUpozZmAPtv56iOT0TMYP\nMcyPelTemPg0Dhobxr75Hgk3kygp1bLll0OsWreNt14cRQPX6oWLDhw/jbpVP2av+EJf1iskkKuJ\nybz27n/Iys0jNSObV5Z8ROzl63yycJrBONfIfl0JDWzBpPkrOHoqmqKSUg5HnuP1ZZ/i1cCd54f0\n0ded8d6nlGrL+O7DOVirqyfwEARBEARBEARBEARBEIRHbeGoUORyOaOX7yQ+KYvSMh1HL9zk5U9/\nRmmmwLeBwwO162YnjaWfupxCaZkOXXkd7+mM7kxBSRmvfv4r19NzKSwp41D0Dd7dcpTgpu4MaOtj\nUN9Caca/dxzn4PnrFGt1xNxI5+2NYThr1AxubxhLUJorGNXZnx3H4kjJLmBM18cz7j59UDAO9SyZ\nsPpHrqbmUFqmY8exOD7+KYoZg4Op71C98MKh6Bs4PruCBRsOGbVzOblqgXFn21rPNayjLx196/PK\n578SESfFX47E3mTWN/tp4qJhbLcWD/8CBUF4ICIPQ7hfc/t6I5fJGPftWS6nF1GqqyD8SjZTN8ei\nVMho7qo23UgNXG1UAJy+kUeprgJdHbl58/t6U1BazvStF7iRXUyhtpywy1m8/9sV2jaypd8di/YA\nWJjLWfnHNQ7HZ1FcVs6FlAKW/pyAcz0lA1sa1lWayRnZxo1dZ9NIzSvlmSB3Hoep3RphrzZn8vfR\nXMssplRXwa6zqXwadoNp3RvjoameGD7schbus/ezeO9lfdnc3XGU6ipY82xAnQvuWKsUzOzpybGr\nOSz8MZ7k3FLySnTsPpfGgh/j8XOzZmywdM1WSgUvhTYk4moO7/2aQFJuCcVl5Zy8kccb2y9iY2HG\niyENaj2XIAiCIPzduLm50bNnT6ZNm8aaNWto2LAhWq3W5HFlZWXk5eUxZ84cvLy8ADCxbs3f0vxB\nLZHLZYz57AjxqfmUlpUTHp/OK+tOoDKT4+tm80DtummkvKJT17Kqcjtr/3AWDG5JQYmOqd9FciOz\nkML/Z+++o6K6ugYO/xhm6B0EUREQsYMKWDB2Y1dsEVs0GrvYe6/Ye4vR2BM19m7svRfELooIVhAE\npEiH7w/yYhCM4CeCZj9rZb3h3n3u7DPrDTPcve85cYmc9gli+r7bVCxiRuNyhdLFa6nUmXfwLqfu\nBxETn8Td52+YvPsW5gZaNCuf/nuIhlJBm0o27Lr2lMA3MbR3Tb9uSk4ZWK8kproadF99kcfBUcQl\nJLHr2lN+OebDoAalKGiskxZ72icIi35bmbjzBgB6mkqGNy7Ned9gxu3w5kV4DBExCez2esrY7d6U\nLmhEp+/s0t6Lic3LcvNpGEM2XuNpaDQx8Ulc8A1m8MarGGqr6F7DPkN+vq8iAbA208twTgghhBBC\nCCGEEEIIIYQQQojskv6xnPGl+scAWpS1wNXWiAHb7nHJP5yYhCTO+YUxZs8DbEy1aV/h3Zyzc10h\nhBAiL7KysqJBgwaEhISQkoWmr6S/1706ceIEw4enrnkeHBGTozl+KbKvVs6QfbWEEEIIIYRIT5nb\nCQghhBBCfG5Fyrgwcu0R9q6YwfQudYmJisTQzIIK9VrS+OehqDS0Pn6RTLg2bsu1Y7tZNa4n2rr6\njN909oOxRctVZvjKv9j961QmtfuO+NgYTPIXokrT9jTpPgKFevqvYeoqFV0mLWPr/DE8vnONlORk\nipatTLvhs9DQyrjZQPWWXTj8xxKsS5TFqtiXWRhMz9CEUWuOsGPJRKb9VIfY6EgsrIvSdugMav7Q\n9aPjS7vWwWPOBg6snsuIxqVRqCmwK1uJkasPY1OqfLrYLfPHcPj3xemObV0wlq0LxgJQuZE73TxT\nN31o4TEOi8J2nNqxhuOblxMfG4uhqTklKlSn18x1mFul37hGCPFO4ts33J7WDNMKTTByqM3tqU0/\nGBuwbRokJVLcYyVKvdQNrEwruhH5+DovD68g4sFFDIpV/lKpizyiQrkynNi+lmkLV1CrVRcioqKw\nyGdG6yb1GO7xM1qaGp903fYtG7Pz4DG6DhqHvr4ul/Zv+mCsq0s5jm5ZyeR5v1KpUTvexsRiVTA/\nHX9oyqh+3VEq0zdQaahUrJgziZFT53Pt5h2Sk5Op7FyWeROHo6Od8TtC1/YtWbjyD8qXKYFjyS9T\n0DQxNuTk9jWMn7WE6i1/IjIyGvsi1syZMJTuHX746Pi61V3ZvHwOs5aupljVxijU1KjsXJbj21bj\n7FgqXezEoR4UtS3Myo07WLZuMzFxsZibmVKzSgU2LJ2Jnc27RUIG9/wJG6uCLFmzkYqN2xEZGY11\noQJ0bduSYR5dMn3/hBBfLyfbfOwf0Zg5+7xpMnM/kTEJmBtq09zFlgGNHNFUfVqDauvKduzz8qfv\n6tPoaak4Nq7ZB2MrFjVn99BGzNxzndpT9hATn0hBE13aVCnKkMblUCoU6eI1lOos6lyNiVuvcN0/\nhOSUFCrYmTOtbSW0NTLeCu9YrTjLjtzBsbAppQt92gad2WWsq8m+EY2ZtvMaDWfsJyo2niIWhkxt\nU5GfapT46Hh1hRqb+tdlzj5v+qw+TVD4W0z0tKjnWIhRzZ3R01KlxXrUd6CwmT4rjt2l9pQ9RMXG\nY2WqR8dqxRjQ0DHT90QI8eXZO1Zg6oajbP1lBmM61CEmKhIjMwu+a9SKlj2GodL8tO9YNdzacfHw\nLhaN7I6Onj6zt5/7YGwJp8pMXn+QzUumMrRVFeJiYshnWYiazTvQuvcI1N+7j6VUqfCY+ivrZ4/G\n99Y1UpJTKF6+Ej+PmYOmlk6G69dt/TN71y6mSKly2BT/Mvex9I1MmLrxKBvmT2RUu1rEREVSwKYo\nXUbNpF6bbh8dX67q9wxftJEdK+bS+/uSqCkUlChXGc8/jmBXxumT88qp6wohxOdS3qUiu46cZsEM\nT5rXrU5UZAT5LPLj1rI1/YaORFPr0z6XWrXtwIHdOxjQswv6+gYcPHv5g7EVKldh+1/HmTt1EvW/\ncyEm5i0FC1nRun1HBo4Yg1KZ/nNJpdJg3rJVTBkznBvXrpKcnIxLZVcmz1qAtnbGz6UOXbqzYskC\nHMqWp5SD4yfNJ7uMTUzZdeQUMyaOw61OVSIjIyhS1J5JM+bRsWuPj46vUacev23YypK5M6lcuigK\nhQLnSq7sOnwKx/LOnxyrrq7O79v3Mn+GJwO6dyYw8AUmpmZ836ARw8dNRk9PHyGEEN+mSb/twMxI\nn+WjuqKhSv1sbVmrAl73/Vm0+RDeDwJwKmGTu0kK8R+Snbq9ECL3OBcx58AoN+bs9aLx9D3vamcV\n7RjYuNyn185c7dl77TEeK0+ir63BsQktPhhbsagFu0c0Zdaua9SauCO1dmaqR9sq9gxp6pSxdqau\nYPHPNZiw5RLXHweTnJJCxaIWTGtfJdM6UacaJVl2+BaO1maU/sQNZ7PLRE+L/aPdmLr9Cg2m7iYq\nNh47C0OmtnOlc82SHx2vrlDjz4ENmLPHiz4rTxD4v9pZ2cKMbuGSrnY2uoULRSwMWH/qPiuP3yE2\nPol8htpUK1GAVb3qYGv+aZu+iK9fBYfiHFs7h+nLN1K781Aio95iYWZMq/rVGd61zaf3PzWpze5j\n5+g+di76ujqc37z4g7Gu5UpxaNUsPJf9gWubfsTExmFlmY8OTb9nZI92KNXT/45RqVQsnzSIUfNW\n4nXnIcnJyVQqW4q5I3uho6WZ4fo/t2rIot93Uq5kURyKfZmeWhNDA46tm8uERWup1XEwkdFvKWpd\nkFnDetKtdaOPjv++ijOb5o1jzqrNlGzYBTU1NSqXK8nRtXNwKpV+gx91hYIdSyczfflGuo2Zw8vg\nUEyNDGhYvSIT+nZCTze1D/ttbBwHz6Temyzd+OdMX/enFvX5ZcKA/+fshRBCCCGEEEIIIYTIyLmo\nJX9NbMvsHRdoNOlPImPiMTfUpXnlYgxqVglN1ac94+FetRR7Lz+kz7K/0NfW4Pi0jh+MrVSsAHvG\nuTNz23lqjf6DmLgECpoZ0LZaKYa2qIxSPeNzOot71mf8hlNc9wskOTmFisUKML1T7cxrDbUd+eXA\nNRxtzCldON8nzSe7TPS0ODCxLZ6bz9JgwiYiY+Kxy2/MtI616Fwn6z2C4dGxAOhrf/iesLpCjc3D\nWzJ7xwV6//IXgWFRmOhrU698Eca4f4ee1qfdTxZCfF7ShyE+hZOVAXt6OzPv2GPcfr1GVGwi+fQ1\naOZoQf+a1mgqFR+/SCZ+KJ+f/beD6b/1Lnp7lBzuV+GDsRWsDdnRw4k5R/2ot+gKMQlJFDTSorWT\nJYNq26BUqKWL11BXsKB1SSbv98X7WQTJKeBibYhnU3u0M+lh+LFiAZaffYJDAX1KWep90nyyy1hH\nxZ5ezkw/5EeTZVeJjE3CzkybyU3s6VSp4L+OjUlI4uj91wBUnnUh05h2LgWY2yr1udw+1QtT2ESL\nleeeUXfxZSJjk7Ay1qJDhQL0q2mT7j0ZUa8Itmba/HH5BWsuPCM2IRkzPQ2q2hmzon0ZbEwzrvMk\nhBBCfC1u3ryZpQ1+1NTU0NDQID4+nhcvXgDw+3k/6paxRFfz61mHwsnGhH2DajH34F2azDtOVGwC\n5gZaNHOyYmD9kp/e21nRmn3ez+j7+2X0tJQcG1H3g7EVi5ixe2BNZu2/Q52ZR4iJT6KgsQ5tKtkw\nuEHJjN/jlAoWdqjAxJ038X4Smrouiq0Z034oh7ZGxnw7fleEX48/wNHKmNIFjT5pPtllrKvBvsG1\nmbrnFo3mHScyJgE7c308W5Xjp6p2Hx3vUac4hU11+e3kQ+rMPEIPEbHVAAAgAElEQVRkTAKFTXXp\nWMWW/vVKpptn52p25DPQ4reTD6k1/QjxSckUNNLGycaUwQ1KYm2WcWPNN2/jAdDX+nr+vyqEEEII\nIYQQQgghhBBCCCHyLukfyxlfsn9MXaHGH13KMu+YP/023yUoMg4THRXflzBjRL0i6Gmqf9J1hRBC\niLwqNjaWZ8+efTROpVKRlJREcnIyCoUCU1NTXr16xc4rj+lSswQq9U/7npNXyL5aOUP21RJCCCGE\nECI9tZSsPKkjhBBCCPH/sGXLFtq0acNKr4jcTiVPmu/RAt8bF1l69mWWxzz3vcsE98r8NH4J1Zp3\nysHsRHb8OuInbI2UbNmyJbdT+Sg1NTWK9foV0wp5Y/GqxOhwnu1dQJj3YeLDA1HX0kPXpixWzYag\nZ1suXeybe+d4vn8RUY+9SUlORNO0EPlcW2FZvxcK5buF8u4t6Ehs0COKe6zi8cZxRPnfQKGuxLhs\nXWx/nEb4zeM8P7CYmCA/VAbmWNbthuX3XdPG35nZktiQp5Totwb/PycS5X8DUlLQt3PCus1EdK1K\nvXut+R2IeHiZSr88TDsW/eQOz/bMJeLBJZLiotEwssTUuSGFmg5CXfvdJrrZmfvnFvPSl4gHF7Go\n8SORfl7cntoUa/dxFKjfK0Ns4LHVpCQnYVm3e7rjIZd28nBFX4r+PJ9837nnaL7Z9frKXh782itL\nC1TkNnd3d5LfhrNh6czcTuWb1rSTBxeu3SDkztksj7nj44tzfXd+nTmezm2a52B2Ird08BiBQsfo\nq/j8Fnmfu7s7cX5XWNmzVm6n8p/TZuFhLvu+4vHiH7M85v7zMKpP2sX8Tt/RoWqxHMxOfAndlp9A\ns0gF+X0uPgt3d3eeRSQyZP7vuZ1KnuPZozn3vS7wx9WgLI958vAug5tVpPeUpdRp9VMOZiey64dS\nemzevBl397z197wQ4p3/1VeeRSTkdip5UocWjbl68Tw+L8OyPMbn7h3qVC7H7CUraNepSw5mJ7Kj\n10/t0Faqyfd58Z+npqbG2gk9aVnrww9rf2vCIqKZuX4fB857ExgSjp6OFuWL2zC6sxvOJW3TxZ7y\nus/cP/Zz9f5jkpKSsbIwoW09V/q1qZ9uQ7RWIxbi+zSQDVM8GLF4E9fu+6NSqtPA1ZH5g37k0MVb\nzNtwAN9nQZibGODxQ116taqTNr5B/5k8CXzNpql9GbVkM14+/qSQQsVSRZjm0QYHO6u02BbD5nPh\nli+BB5emHbvp+5Tpa3Zz/tZDomPisDQzwq26EyM6NcVA990GIdmZ++f2y7YjmBsb8kOdiumObzh4\njt4z1rBuYi9a1HTJ0RzyGoOa3XL076O8Vp//EKnb5/26fV72NdXnRe5yd3cn7vE1VvWu8/Fg8cnc\n5//F5YdB+P/SOctj7j0Po/r4bSzoXJ0O1YrnXHIi13RddgxNW+cc+/vb3d2dpPBAfp89KkeuL1I1\n6zOOi953CTq/Pctj7voGUOGH3vwyYQA/taifg9mJ3NJx2HTUjfLL/TUhhBBCCCGEEEL8J6ipqbGy\nXxOaV5bnQHKS+8wdXHrwnIBV/bI85t6zEKqNWM+C7vX4sWaZHMxO5BazDvNyvf/c3d2d449jKNZ7\nea7lkFXShyF9GP8fF7oWzPX/3j7F//rfX0yvndupfNPar/Hmiv8bHk6qkeUx94Oiqb3gEnNblaCd\nS4EczE7klj03X9Fr023p3xJCiP+w+Ph4dHR0SEpKSndcqUx93iIxMRGA/Pnz4+TkRLly5ShbtiwO\nDg6UKlWKFV0q08zJKsN1xefT9pczXPYLwW9OiyyPuf/yDTWmHWZ+exfau+bssyYid1j02/pV/v0n\nhBBCCCGEEEIIIYQQQgjxPukf+zKkf0xkRvrHhBDiv+XmzZuULVs27ef3e8TMzMwoW7YsTk5OlClT\nJq1HbPfu3bRp04ZXK2Rd9twg+2r9t+2++pjuK07K9zUhhBBCiK/PVuXHY4QQQgghRI7L5o21Q+sX\nYmhqQeVG8uCm+DY8+LU3MS8fUKz3CnQLlyHhTRD+m6dwd7Y7jhMOomVRBIDIh5e5N689Js4NKTf1\nNEptfUKvH+Thyv4kRLzGpt2ktGsqlCoSIkPx+30UNm0moF2wGEEn1hOw1ZO40BcoVJoU77sKdR0j\n/DeOxX/TePSLOKFXpDwAakoNEiNf82j1IGzaTUbPthyxrwK4v7ATd+e4U37qaZR6JpnOJ8r/Bndm\ntsSwZDXKjN6DhnF+Iu5f4NHaIUQ8uESZ0btRUyizNff3JUaFcmWAw0ff23Kep9C2LJrpOW3Loh88\n9778dX7O9Hh8WCAAmvkKZ+k6QuS27Baz5q1Yj0U+U9o2b5RDGQkhhPhcUsje7/glh29jbqDND5Xs\ncigjIYT4NmW3P2z36gUYmVlQvUmbnElICCHEf1p27/UsWziXfBb5aeneLocyEkIIkR2dJy/Hx/8l\n6yf1wtG+MEGv3zBm2RaaDJ7DmRXjKWplAcCFWw9pMWwebtWdubbeE0M9bfaduU73aasIDo9kZt+2\nadfUUKrz+k0Ug+f/wTQPd0raFGTl7hOM+3Ubz1+FoamhZKOnB0b6OgxduJHhizfhUsoWl5KpNTlN\nlYqQ8Ej6zFjDjH5tcSlhi9+LV7QetYimg+Zy7XdPTA31Mp3PdR9/GvSfRU3nkhxdOooCZsac8fbB\nY9Yazt98yJElo1CqK7I19/e9fhOFbbOBH31vr673pFjh/Jme6/ND3UyP3/J9hpqaGiVt5EH9/yqp\n2+f9ur0QQmRHdmtnSw/ewNxQhx8qy+8kIfK67N4Tm79uGxZmxrRpVCuHMhJCCCGEEEIIIYQQQnyL\nsts3vmTfVcyNdGn9XYmcSUiIr4z0YUgfhhA5KbvLfy87HYC5vgYty2XeVyiEEEKIr5+vry9JSUlp\nP2tra1OqVClcXFxwdHTEwcEBR0dHDA0NczFLkd37LUuP+mBuoEUrF1nfTQghhBBCCCGEEEIIIYQQ\nQgiRSvrHhBBCiP+2u3fvAqk9YiVLlsTZ2RkHB4e0HjETk8yfCxG5T/bVEkIIIYQQ4uujzO0EhBBC\nCCFE1iQnJ5EYH8+p7as5v28TvWauQ6WhldtpCfH/lpwQx5t7ZzGv1hZ9O2cANM0KU/TneXiNdCX8\n9kny/72gV+j1QyhUmli7j0PDKHUDRLPKLQk6vZFX5zanW8wMICkmkoKN+6UtUGZZrzvP9swn0vcK\nTrOvoGFoDkCBhn0IvrCdN/fPvlvMTKFOckIcBRr2waC4KwA6hUpg3XosD5b35tW5rRSo3zPTOQVs\nnoRS14hifVagUGoAYFz2ewq3GsWjNUN4fWUvZpVaZGvu71PqmeC66vmnvemfSUJEMC+P/IZOwRLo\nF62Qq7kI8TklJSUTFx/Pyo3b2bB9HxuWzkRLUyO30xJCCPEZJCWnEJ+YxLrTPmy54MvKnrXQVKnn\ndlpCCPHNSU5KIiEhjiObV3Nq90aGzP8dlabcxxJCCJE7kpKSiI+P44/Vv7Ft0+/8um4TmlryuSSE\nELktNj6BU1736NiwKhVLpz5UZG1pxrIRXXBoN4pjV25T1Cq1Hrj/rDeaGio8e7XG0swIAPe6lVm3\n/wwb/jrHzL5t0107IjqGIT82wqVkap3No3U9Zqzby6U7vtzZPIv8pqmLlw9q35DNRy5yyut+WqxC\noUZsfAID2zWgWrniAJQuUogpPVvTZfJyNh48T7829TKd06ilmzHW12X9pN5oqlJbMxu4OjKxeys8\nZq1l54krtP6+Urbm/j5TQz0iTq78tDf9A16FRfDn4Qss33GMEZ2aUMKmwGe9vvg6SN3+663bCyHE\n/0da7ezkPTaff8iq3nWkdibENyIpOZm4+ARWbTvAxr3H+H32KOl/EkIIIYQQQgghhBBCfHb/qzWs\nPXaDzWfusqp/k7SeCSH+y6QPQ/owhMgLkpJTiE9K5vdLL9jqFcjy9mXQVCpyOy0hhBBC5JDExEQm\nT56ctqGPra0tampquZ2W+ASp91uSWX/uEVsuB/Dbz67S2ymEEEIIIYQQQgghhBBCCCGEyBbpHxNC\nCCG+XVWqVOHRo0fSI/aNkn21hBBCCCGEyFtk9QwhhBBCiK/ElUM7WDmuO0b5LOnm+RsudVvkdkpC\nfBYKpQqVgRmhXgcxdqiNcdm6qKkrUdfWp8LC2+lird3HYe0+LsM1tPIVJsLnAolv36DUMUx3zsC+\nYtq/qymUKHWNUFNppC1kBqAyyAdAwpvgDNc2Kl0z/fVKVAHg7bO7mc4nKSaSiIdXyFe5RdpCZmnX\nKlMLgCi/65hVapGtuec1idHh3F/chcSYSEoMWI+aQoo94tuxdd8hfh40DkuLfKyZ70mrxnVzOyUh\nhBCfya6rj/FYdZr8Rjr88nN13JxtcjslIYT4Jp37azuLRnbDJJ8l/WeuxLW+3McSQgiRe/bu2EL/\n7p2xsCzAot/W0qTFD7mdkhBCCEBDqSSfkQH7zl6nXmUHGriWRaVUR19XG/89C9LFevZujWfv1hmu\nYW1pxhlvH8Ij32Kkr5PunKuDfdq/K9UVGBvooqlSkd/0XS3R3NgAgKDQNxmuXadi6XQ/Vy9fAoDb\nfs8ynU9kdAwXb/vSuk6lDJuafV+xDABX7vnR+vtK2Zp7TvJ7/opyHUYDoKutyaSerejzg9RE/quk\nbv911u2FEOL/a9eVR/T57WRq7axbLdxcMt90UQjx9dl+6DRdx8zGMp8pq6YOpWXdarmdkhBCCCGE\nEEIIIYQQ4hu066IPvX/5i/zGeizr3ZBmlYrldkpC5AnShyF9GELkBXtuvqLflrtYGGiw2L0UTR3M\nPz5ICCGEEF8tR0dHHB0dczsN8Rns9nqKx/rL5DfUYmmniriVL5TbKQkhhBBCCCGEEEIIIYQQQggh\nvjLSPyaEEEJ8uwoXLpzbKYgcJPtqCSGEEEIIkbcoPx4ihBBCCCFy0qClO7MUV6lhayo1zLjBnRBf\nPTUFJfqv5eGKvvgs7YZCQxt9O2eMHGphXrUtSl2jtNDkhDiCTqzj9bX9xAY/ITE6DJKTSUlO+jsg\n6b1Lq6Ourf/e66mlu2bqITWAd9f533F1JUo943THlHqpYxMiQjKdTnx4EKQkE3xhO8EXtmcaExf6\nIttzz0tiXwVwb8GPJEQEU3LAenQLl8ntlITIkr3rl2Yprm2zhrRt1jCHsxFCCPE5bR5QL0txrSoW\noVVF2cRSCCE+1dgVu7IUV62JO9WauOdwNkIIIf7rNuzcn6W45q3b0bx1uxzORgghRHYpFGpsmd6P\nrp6/0WHcL2hraVCplB3fVypDx4ZVMTbQTYuNjU9g5a4T7D59Df8XIYRFRpOUlExScjJA2v/+j7pC\ngYGudrpjaqhhrK+b/tjfNcLk98arlOqYGOilO/a/fF6Fvsl0Pi9fvyE5OYXNRy6y+cjFTGOevwrL\n9txzUpGC5kScXEl45FvOeN9n2MJNbDt2mT1zh2Ckr/NFchB5iNTtv7q6vRBC/Jstg7LW89CqUlFa\nVSqaw9kIIT6n3b9MyVKce8OauDesmbPJCCGEEEIIIYQQQgghvllbRrTMUlyrKiVoVaVEDmcjxFdI\n+jCkD0OIHLSxS7ksxbUoZ0GLchY5nI0QQgghhMiqP/tUy1JcS5fCtHSRDZuEEEIIIYQQQgghhBBC\nCCGEEBlJ/5gQQgghxNdJ9tUSQgghhBDi66TM7QSEEEIIIYQQQs+mLOWnnibS9wrht08SfucUAVum\n8Hz/YkoN3Yxu4TIAPPi1F2E3jmDlNhizyq3QMMyHmkoDv3UjeHX2z8+el5qaIuPBlP+dzOTcP5hX\nb4/dT7M/+hpZnXteEel7lfuLu6CupUuZUbvQKSiLNAohhBBCCCGEEEIIIYQQQojsK1/chmvrPbl4\n25djl+9w9Mptxi7bytwNB9gzdwhl7VMXr+48aTl/nb/ByJ+a0raeKxYmBmioVAyYu57fD5z97Hkp\n/t4I6Z9SUlKLhArFv9cIf2pcjcXDfvroa2R17l+Ckb4OTas5YWVhSvUeU5i38QCTe/7wxV5f5B1S\nt/966vZCCCGEEEIIIYQQQgghhBBCCCGEyNukD0P6MIQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGE\nEEIIIYQQQgghhBBCfJ2UuZ2AEEIIIYT4fOZ7tMDX+wJLzwXmdipCZJ+aGvr2FdG3r4hVi+FEPrrG\nnRktebZnHsX7riY+PIgw78OYVWxGIbfB6YbGvX6WIyklJ8aTFBOJurZ+2rHEqFAAVAZmmY7RMLEE\nNQVxIdnI6SNzz0xiVChXBjh89NLlPE+hbVk067n8i0g/L+7Na492AXtK9F/3wfdAiG9J004enL/q\nzeu753I7FSGEEDmgzcLDXPINwn9xx9xORQghvmmePZpz79oFNlwLyu1UhBBC/Md1aNGYKxfO8SAw\nPLdTEUII8Tc1NTVcHexxdbBnbNfmXL7ziAb9ZzJj7R42Te3Ly5BwDpzz5ofaFRnV2S3d2KeBr3Mk\np7iERCKiYzDQ1U47FhoRBYC5sUGmYwrmM0ahUONJUNZz+tjcM/P6TRS2zQZ+9NpX13tSrHD+DMef\nBYUyfd0eqpYtRrv6VdKdK25tCcB9/xdZnoP4BkndPs/X7YUQIqe4z/+LSw8DCfilS26nIoT4zJr1\nGceF63d4dWFHbqcihBBCCCGEEEIIIYT4D3KfuYOLPs95srpfbqcixJcnfRjShyFEHtJ+jTeX/d/g\nO6lGbqcihBBCCCEy0faXM1x6FMLjuS1yOxUhhBBCCCGEEEIIIYQQQgghxDdG+seEEEIIIfI22T9L\nCCGEEEKIvEmZ2wkIIYQQQggB4H/HiwOr5+J3+ypR4a8xtiiIcx03mnQbgZauXm6nJ3JQhM8FHv7W\nlxIDfkfXqlTacX07Z1RG5iREhQGQkhgHgFLPJN34mJcPifC5mBqTkvLZ8wu/cxpTl8ZpP7+5fx4A\nw+Kumcara+piUKwSET7nSXjzCpWhedq5iAeX8Fs/gqLdFqJnUzbLc8+MUs8E11XP/7/Ty7K4kKfc\nn98Brfx2lBq6GXUt+e9SiLzugZ8/E2Yv5eT5K8TGxWFdqACtGtdlUI9O6OnqpIu9fvs+k+b+woWr\n3ryNiaVwIUuaN6jNyH7d0NfVzaUZCCGE+DfJKSmsOnGP9ad8eBwcibGuJvXLWjGupQuGOhq5nZ4Q\nQnxTEhPiWTbOg1N7NtFp2FTcugzINM7vznU2LZqCj/dFEuLiKGBrT+OOfajdstMXzlgIIcS3Lioq\nknquTjwJ8OfYRW+KlyqdISYhPp6hfXuy/c8/GOs5k179B2dyJSGEyD1nb/jQbcpKts7sj4OdVdrx\niqXtyG9qRGhENADxCYkAmBimr035BLzk7A0fIGdqhMev3qV5Dee0n89cT32tquWKZRqvq61JFYdi\nnPX2ISj0DRYmhmnnzt98yIC561kxuivli9tkee6ZMTXUI+Lkyk+el6mRHtuOX+am71Pa1HVFoVBL\nO3fj4RMAbAuaf2i4+IZJ3f7rqNsLIYTInG/gG6buuMLZey+ITUyisKkebhWK0LeBI7qaqk+OFULk\nLVHRMVRy98D/eSBXti2jVFHrzxIrhBBCCCGEEEIIIYQQH3LjcRDTt57n8sMXxCYkYm9pQo8G5elQ\no0xupybyOOnDkD4MIcTn9Sj4LTMOP+LsozDiEpOxMtamqYM5vasXRldDPV2s97MIFp8MwOtpBKHR\nCRQ00qRR6XwMrG2Lnqb6B15BCCGEEEL8f/i+imT63tucffCK2IQkrEx1cStfCI86xdHVTL/0uV9w\nFNP23OKcbzCRMQkUNtWlTSUb+tUtjkJN7QOvAFFxidSafpgnr6M5NboeJSwNPxgrhBBCCCGEEEII\nIYQQQgghhPg2RcUl8f3CyzwJi+H4wEqUsHi3l84vp5/g+ZfvB8c+mVoLpeLDNUkhhBBCCPHp4hOT\nGbT+LFsvPmLiDxXoUy/z5+98A98wbZcXZ++/IDYhicJm+rg52+BRv4ysAyiEEEIIIfIkRW4nIIQQ\nQgghxAOvc8zoWh91lQYj1xxh/vHHtOw3geObVzCvTzNSkpNzO0WRg/Rsy6GmUPJo1QCi/K6TnBBH\nYnQ4Lw+vID70BRbV2gGgaVoIrXzWhF7/i7fP75OcEEfYzeP4LO2GaYUmAEQ9vkFKctJny02hocWz\nvfN5c/c0yfExvH12j4BtU1EZmmNaoekHx1n/MAY1hTr3Fv5EzEtfkhPiiPC5gO+qAShUGugULJGt\nuecFjzeMITkhjuJ9lqOupffxAUKIXHXvoR+uTTrw6nUoR7es5Mm1o4wZ2JN5y9fxY9+R6WKv3bxL\n9ead0NfV4dKBTby4cYLZ44ayZvMuGnXoTbJ8DgshRJ40cuNFZuzyYlRzJ3wXduC3HjXZfz2AtosO\nkwNr/AohxH9WdEQ4U7o3I/Cp37/GXTq6hxFtaqClo8usrWdZe+EJNZt1YNn4vuxZs/ALZSuEEOK/\nYtLIITwJ8P/g+TfhYbRv0YiAx4++XFJCCJFNzsVtUVdX0Gvaaq7e8yM2PoGwiGiWbDnMs1ehdGpc\nFQArC1NsCuRj35nr3H38nNj4BA5fvEWHcUtpXtMFAK/7/iR9xnvZ2poazFq/lxNX7xITG8/tR88Y\nv3wbFiaGtKxZ4YPjJvdqhbpCQeuRi3jwJJDY+ATOePvQY9oqNFVKStoWzNbcc4K2pgZTe7tz40EA\n/eas40lgCDGx8Zy78YC+s9ZiqKdD75Z1cuz1Rd4ldfuvo24vhBAiI58XYdSZvIOQyBj2jGzKvfk/\nMszNmSUHb9Lt12OfHCuEyHuGz1mB//PAzx4rhBBCCCGEEEIIIYQQmdl/1Ze64zaiq6XimGcHfJf3\noU21Ugz67QhL91/N7fREHid9GNKHIYT4fB68iqb+kiuERCWws6czN8dUY0gdG345HUCvjbfTxV58\nHE7z5V6o1BXs6eXM7XFVGVnPjjUXntNu9XWS5eFbIYQQQojP7kFgBHVnHiUkMpbdA2tyZ7obwxqW\nYulRH3qsuZgu9lVELE3mHSciNoGDQ+rgN6cF45s5svDwPUZtvf6vrzNuuzdPXkfn5FSEEEIIIYQQ\nQgghhBBCCCGEEHnchH0PeRIWk+m5iNhEAO5PqM6L6bUz/KNUqH3JVIUQQggh/jPC38bTZuEh/IMj\n/zXO52U430/dk7oO4LBG3J3bjqFNyrHk0C26rzj5ZZIVQgghhBAim5S5nYAQQgghhBA7lkxC39iM\nrlOWo1RpAFChbkv873hxaP0iAu55Y1PaKZezFDlFoaFNmZE7ebp7Lj7LepAQEYy6lj7alkUp1uvX\nd4uGqSko5rES/03juT3VDTV1dfTsXCjW61cUmjpEP7mNz+IuFGjUh8ItRnyW3NTUVRT9eT4BWyan\nLpSWkox+URds209BoaH9wXF6RcpTZtRunu2dz+3pzUiKiUJlmA+zim4UbNwfhUoze3PPIQFbJvPi\n0PL3jk0hYMsUAMwqt8S++2KS42MIu5m64ZHXCNdMr2VerR12nefkaL5CiKwbO3MRiYlJbPl1LqYm\nRgC0blKPq963WbjyD85e9qJqxdTP1vGzl6BUqrN89kR0tLUAaFSnGgO7d2T8rCWcv+qdFiuEECJv\nuOYXzNpT95nX6TsalbcGoLK9BeNbuvDLkdv4Br3BPr9hLmcphBBfv+iIcMa0r4Nrg5aUr1aX0e1q\nfzD2j7njMMlnSf+ZK1FppP7d37RzP549us/mxVOp3bITeobGXyp1IYQQ37Bjhw6waf0aGjVryYHd\nOzKcfxMeRvO61WnS4gdq1W2AW52quZClEEJ8nLaWBocWj2D62j10mvArr8Ii0NfRolhhS9ZO6EnL\nWhUAUCjU2DClDyMW/UmdPtNQqqtTsbQdayf0Qk9bk5sPn9B2zGIGtW/IuK4tPktuKqU6y0Z0Ycyy\nrVy7/5jklBQqly7KrP7t0NbS+OA4l5JFOLJkJDPW7aVu3+lERsdgYWJIy9oVGNqhMVoaqmzNPad0\na1YTc2MDlm0/imvXSSQkJFLQ3ASXkraM6NQUmwL5cvT1Rd4kdfu8X7cXQgiRuSnbLpOYlMI6j7qY\n6KX2PDSvWASvx69YdvgWFx68xLWYZbZjhRB5y8Ezl1m38xDNv/+OXUfPfbZYIYQQQgghhBBCCCGE\n+JBJm86Q31iPZb0boqFSB6BPI2cePH/NjG3naV+jDMZ/1xuEeJ/0YUgfhhDi85l68BGJySms+tEB\nE93UPkw3RwuuP41k+dknXHwcTmXb1PUUph96hKmuisXuJVGpK/6ONefGswiWnXnCzeeRlCtkkGtz\nEUIIIYT4Fk3ZfYvE5GTWdKuCiV7q34bNnKzwCgjl1+MPuOAbjGvR1OdU5h28S3RcIss7V8ZYN/X5\nnAaOBRhUvyRT996iWw177C30M7zGkTsv2XjhMU3KFWKf97MvNzkhhBBCCCGEEEIIIYQQQgghRJ5x\n9P5rNl19QeMy+dh/OzjD+YiYBAB0NNS/dGpCCCGEEP9Z4W/jaTJzP27ONtQpU4iGM/Z9MNZzx1US\nk1JY27v2u3UAK9hy3T+YZUfucOFhIK72+b9U6kIIIYQQQmSJMrcTEEIIIYTIS6LfhLHvt5l4nzpA\neHAgWrp62JQqj1vP0diWcU4Xe//KKfavmsvjO1dJTkzCxNIK18Ztqd+xH8q/N3wGWNivFYEBvnjM\n3cCm2SPwv3MNdaUKx2oN+HHUfG6dO8SB1fMICvDFwMycuu09qNOuV9r4mV0b8PrFE/rO38TmuaPw\nv+tFSkoKRRwq0mbINKyKOfzrnJ763GT38uk8vH6euLfRGJlb4lTbjabdR6Ct926BkuzM/XNz/r45\nhibmKFXpN84rUKQkACEvArAp7ZSjOYjcpWFSALsucz8ap2tVitLDt2V6rpznqXQ/F++7OtM4p1mX\nMhxT6pnguup5xuDkZHStHSg1bOu/5lVy0IaMuVo7fDCHf21NXLMAACAASURBVMrq3HOCtft4rN3H\nfzROoaGd+fsjRBaEhr9h+qLf2Hf0FC+DgtHT1cXZsRRjB/WkQtky6WJPnr/CzKWruOp9h8SkRAoX\ntKR9y8YM7N4RTY13nxHNOvfj4eMANi+fy5CJs7l28w4qpZKGdaqxyHMUB0+cY/bS1Tx8HIBFPjP6\n/dwejy7t0sbXce9KwNMXbFs5n2GT5+J16y4pKSlULO/ArHFDcCxZ7F/ndOOuD57zl3PuynWiot9S\nIL85zRvUZlT/7hjq633S3D+3OlUrU7NKRUxNjNIdL++Q+tn6+MkzqlZM/Wx99iIQczNTdLTTLzxa\npLBVhlghhHhfWHQc8/bf4OCNJwSGv0VPS0U5azOGNS2Hk236TaPP3H/JggM3uO4fQmJSMlamerSu\nXJQ+9UqjoXzXGNtu0REeBb1hbe86jNl8kev+IajUFdR1tGJWe1eO3nrGwr9u8ijoDeaGOvT8vhTd\na5dKG+82+wBPX0exvk8dxm25jHdACCkp4FIkH5PdK1K6kMm/zun201Bm7b3OpYdBRMclkN9Ilybl\nrRncpCwG2u8+j7Iz989t47kH6Ggqca9sl+54u+/safedfY6+thAid0S9CWPbshlcOXGA0Fcv0dbV\nw660E236jqaog0u62FuXTrFj+Wx8b10lKSmJfAWsqOHWjqad+6P6xz2rqT1b8tL/IcMWbWL19GH4\n3vJCqVTiXLMh3ccvwOv0IXaumMOLAF+MzCxo0smDRj/2Ths/rmM9gp8/YcTSzayZMYJHt69DSgrF\nylbgp5EzsCn+7/es/O/fZPOSady7do7Yt9GYWBSgcl03fug1Eh39d/essjP3zy085BWNO3lQ1/1n\nHty4/MG46IhwXgY8okqDluneY4AqDVpybPs6rp06SA23dh+4ghBCfD3Cw0JZMHMqhw/sJSjwJXp6\n+jiWd2bI6PGUc66QLvbcqRMsnjsD76tXSExKpJBVYVq1/ZGe/Qahofnu92XHVk3x833Ayg3bGD9i\nEDeuXUWpUvF9g8ZMm7+Y44f+Ysm8mfj5PsTc3IJuHgP4uVfftPGtGtTi6ZMAVm/awcRRQ7jpdY2U\nlBScKlZiwrQ5lHJw/Nc53bl5g3nTJ3Pp/Fmio6OwtCxAQ7cWDBwxBn0Dw0+ae04JC33N0L49cWvl\njmvVGhzYvSNDTPCrV3TrM4AOXbrhdSXj/XAhhMhLCpmbsHR454/GOdhZcWDhsEzPXV3vme7nTVP7\nZhp3Z/PMDMdMDfWIOLkyw/Gk5GTKFrNm3/yh/5rXztmDMhwrW8z6gzn8U1bnnlPcqjvhVl3u/Yv0\npG6ft+v2Qoi8Lyw6jrl7vTjoHfCudmSTj+HNnDPWze69YMF+b7wevyIxOQUrUz3cXe3pU98hXd2s\n7YKDPAp6wzqPuozeeJ7r/sGo1BXUK1uYWT9W5ejNpyw44J1aNzPQplfdMnT//l0/QtOZe3kaEsnv\n/eoz9s8LePsHp9bN7MyZ0qYypa1M/3VOt5+8Ztaea1x8EPiubuZsy5Cm5TPUzbI698+tZulCVCtZ\nMO2h7v8pa2MGQEBwJK7FLLMdK8Q/hb2JZMaKTew/dZGXwaHo6WjjVNqeMb064FKmeLrYU5dvMGvV\nZq7e9iEpMQmrAha0b1yb/p1aoqmhSotr0Xc8vgHP2TR3LENnLcfrzgOUSnUaVq/EwtEeHDx7hTmr\ntuAb8AwLMxM8OjSjT/tmaePr/TycgBdBbFkwnhGzV+B19yEpKSlUcCzBzKHdcShW5F/ndNPHj6nL\n/uDc9TtEv42hgLkZbnWqMKpHOwz0dD9p7jkl9E0EfSYt5If61anm4siuo+c+S6wQQgghhBBCCCGE\nEF+LsKhY5u68yF9ejwgMi0ZPW0V52/wMb+WKk136xU3P3HnC/N2X8XoUSGJyMlZmBrhXLYlHIxc0\nVP+oQczaiW9gGOsGNmX0+pNc9wtMrUE4FWF2lzoc8X7Mgt2XeRQYhoWhLj0bOtGjfvm08U0mb+Zp\nSAR/DG7GmD9O4u0XREpKCi72BfD8sQalC/97feB2QDAzt5/nos9zomMTsDTWo3GFogxtURkDnXf9\nhdmZ++cUHh2LX2AYzSsXS/e+ATSrXJw/Tt7miLcf7lVLfeAKQkgfhvRhiG9R+NsE5h/35/C9EAIj\n4tDTVKdsIQOG1LGlvJVButizj8JYdMIf72cRJCanUMhIix/K56dXtcJoKBVpcT+uvYFfyFtW/ejA\nuL0P8X4WgVKhRt2SZkxvVpzjPiEsOhmAX8hbzPU06V7Viq5VCqWNb7Hci6dhsazt5MCEfQ+58TyS\nlBRwLmzAxMb2lLLU49/ceRnFnKN+XPJ/Q3RcEpYGmjQqk4+BtW0w0Hq3RGV25v651ShqQlU7Y0x0\nVemOOxbUByAgNIbKtqlrKjRxMCefngYqdUW62GIWqTXQp2GxlCuUs/kKIYQQIveEv41n7sG7HLr1\ngsA3sehpKilX2JhhjUpT3jr9OiNnH7xiweF7XPcPTe3jNNGhdUVretcunu77WvtlZ3j0Koo13aow\nZvt1vAPCUKmrUbdMAWa2ceLYnZcsPHyfR68iMTfQokcte7rXeLfmR7MFJ3gS+pb1Pb5j/HZvvJ+E\nkUIKzjamTG5ZltIF068N9b7bz8KZ/dcdLvqGEB2XiKWRNo3LFmRwg1IYaL/7fpSduX9uNUpYUK2Y\nOSZ66Z+xL2tlDEDA62hci6beK9rl9ZTv7PNhrJt+vclGZQviuecW+7yfMah+yXTnwqLjGbzxKs2c\nrPjOPh/7vJ/l4GyEEEIIIYQQQgghhBBCCCGEyJz0j+VO/9j/hL1NYOiOe7g5WlCliBH7bwdniHkT\nm4iWSoFSofZFchJCCCFE3iL7Z+XO/lnBETH0qFOKTtWLc80v43e0f6pRsiBVi1tmWAfQ0fof6wDa\n59wzg0IIIYQQQnwK5cdDhBBCCCH+O5aP6sxLPx96zVpP4RKOvAkOYsv8Mczp1YTxG85gYV0UgIfe\nF5jXpwXOtd3w3HENbT1Drp/Yx6px3YkMC6bt0HcbyamrNIgKf80f0wfjPngaBYuU5MTWlWxbOI6w\noOcoNTTxmLsRHQMjNs4cyqbZw7F1cKFImdTNrFUamkSGhbBmYh/aDp2BbRkXXj3zY1H/1szt2RTP\nndfQM8p8Uxb/u9eZ1bUBJSvVZNSaoxibF8Dn2hnWTPLg4fXzjFpzBIW6Mltzf19U+GsG1rb96Hvr\nueMq+W2KZXqubvs+mR5/9uAWampqFLArmel5IXJaCim5nYIQX72O/UZx76Efm36ZRdnSJQh8FczI\nqfNp2L4XF/ZtwN7WGoDzV7xp0qkPzRvU5ubxHRjo67Hn8Al+HjSO4NdhzBn/bsNVDZWK16Hh9B87\nnVljB1PSvggr/tjK6OkLefYiCC1NDbasmIuRoQGDJsxkyKTZVCzvQIVyqRueaWpoEBIaRo+hE5kz\nYSguZcvgF/CMFj/3p0H7ntw6thNTk8wXyrh28y7fu3eldtVKnNyxhgIW5py+eI2ewydx7vJ1Tmxf\ng/LvgmxW5/6+16HhFHSq/dH39saxHRS3s8n0XJ/ObTM9/iLwFQC2hd816ZUpYc/+o6d4ExmFof67\nhrxHAU8AKGH/75tDCSH+23r8dpIHL8JZ1asWDlamBL15y4RtV2g17xBHx7phZ5HahHvJN4g2Cw7T\n2Mma85NbYqCtwQHvADxWnyYkMgbPNpXSrqlSKgiNimP4xvNMbl2R4gWMWHvyPpO2X+VFaDSaKnXW\n9amNoY4mo/68yJg/L+Fsmy+tgURDqU5IZCz9157Fs00lnGzN8A+OpMPiI7Sce5ALU1pmaOz4H++A\nENxmHaBGqQLsH9EYS2MdzvkEMnDdWS76BrFvRCOUCkW25v6+0KhYSgze9NH39tzkltjnN8z03GXf\nV5SxMknXBCSE+LbNH/ITTx/dZ+j837EtWZaw4EDWzR7NxC6NmbXtHAVsUu/b3Pe6gGe3ZlSq68bC\n/dfR1Tfg8rF9LBrRjTevg+kyalbaNZUqDSLCX/PblIH8NHw6VkVLcejP3/h9zlhCAp+hoanF8MWb\n0DU0ZpXnEFZPG4a9owv2jhWA1HtWb8JCWDq6F11GzaKoozNBTx4zrfcPTOrSmEX7r6NvnPk9q0e3\nvRjXqT6OrrWYtvE4JhYFuHP5NL+M7cPdq+eZuvEo6n/fs8rq3N8XGfaaLt9l/p37nxbu86Jgkczv\nWRUsUuyD5/4pJSX1/oGaWsYHPfQM/16ozucW0O6j1xJCiLyuT+cOPPC5x/L1f1LGsRxBQYFMGTOc\nNk3q8deZyxQpmrpQ6eUL5+jQohEN3Vpw6tpt9A0NObRvN/27dyYk+BWTZs5Lu6aGhgahr18zenBf\nxk+bTbGSpVi/cjlTx43kxfOnaGpqsXLjdoyMjBg7dCDjhw+ivEtFyrtUTB2vqcnrkGAG9+nKpBnz\nKOdSgQA/P35q3Yw2Tetx6tptTEzNMp3PzevXaNmgFtVq1mH30TPkL1CAC2dOMdSjB5fOn2XXkdMo\nlcpszf19oa9DcLT9+EbyJ6/epmixf99Ae9SgviQlJjJl9gIO7N6ZaUzRYsU/eh0hhBD/LkVKhELk\nKVK3F0J8LXr8egyfl+Gs6l0Hx8JmqbWjzRdpOXs/xya0wM4ite5z6WEg7vP+orGzDRemuqfWza77\n02flCYIjYpjazjXtmhpKBaGRsQz7/SyT21SmREFj1py4x6Stl3j+d91sfd+6qXWzjecYvekCTkXM\ncS5iDoDm33WzfqtPMbWdK062+fB/FUH7hYdoOecAF6a2/nDdzD+YpjP3UaNkAQ6MbpZaN7v/kgFr\nT3PxwUv2j3Z7VzfL4tzfFxoVS/EBv3/0vT3v2Rp7y8z7OLrVKZ3p8ZdhbwGwzqf/SbFC/FOnETO4\n7/eEP+aMpmxxOwJDQhk9bxWNe4zm7KZF2FsXBOD89Tu49R5LszpV8N61AgM9XfaduEDXMXMIDgtn\n1rCeadfUUCoJCYtg4LSlTB/SnZJ2hVm5dT9j5q/meWAwmpoa/Dl/LMYG+gyesYxhs5ZTwaEEFRxS\n7/toqFSEhL2h5/j5zB7eA+cyxXn89CWt+k2gUffReO9egalR5jVrr7sPqddlGLUql+fEurlYmpty\n5uotek9cwHmvOxxbNwelunq25v6+1+ERFK6Zef/SP13fuZxitlb/GjPAcymJiUnMHdmbXUfPfbZY\nIYQQQgghhBBCCCG+Ft2X7Mfn2WtWD2iKo00+AsOjmbDhNC2mbeW454/YWab2K1/0eU7rmTtoUqEo\nF+d0xkBHkwNXfem97C9CImKY2rFm2jVVSgWhkTEMX3OMyR1qUKKQGWuO3mDiptM8fx2JlkrJ+sFu\nGOlqMXLdcUavP4GzXX6ci6b2wmmq1AmJiKHv8kNM61QTJztLHgeF0372TlpM3cqFOV0w1dfOdD7e\nfkE0mbKZGmUK89fEdlga63Hu3lP6rzjMRZ/nHJjQFqW6Iltzf9/ryBiK91r20ff2wuzO2BfIuGju\n/3pH1MjYH26sm1pbuR0QjHvVj76EEHmO9GEI8el6/XmHB0HR/NahDGUK6BMUGcfk/b64r7zOoX4V\nKGKmA8Bl/3Dar/amUZl8nBlcGX0tJQfvBtNvy11CohOY3ORd37lKXY3Q6ARG7vJhQmN7ilvosu7i\nczz/8uVFeCyaKgWrOzpgpK1izJ4HjNv7gPJWBjj9vYGOhlLB6+h4Bm67x+Qm9pS3MsD/dQyd1t2k\n9crrnBlcGRNdVabzufEskhYrrlGtqAl7ezmT31CT835hDNl+n0v+4ezu5Zy2KU5W5/6+0OgEynie\n+eh7e3pwZYrmy/waP/9j86J/ehkRB4C1ybvvHN2/y7z2ePdlFGpqUNxC96O5CCGEEOLr1WPNRR4E\nRrDyZ1ccChkRFBHLxJ03aLX4FEeGf4+deWqP4KVHIbRZeprG5QpxblwDDLRV/HXzBR7rLxEcGYdn\nq3Jp11QpFYRGxzFiixeTWpSluKUBa88+YvKum7wIe4umSp213atgqKPB6K3XGbvNG2drU5xsUu83\naCjVeR0Vx4A/ruDZqhzlrU3wD4miw69nabX4FOfHNsBETzPT+Xg/CaPZghNUL27B/iG1sTTU5vzD\nYAZuvMLFRyHsG1w77ftaVuf+vtCoOEqO2vPR9/bs2AbYW2R+jW41Mn/W/+WbGACsTVO/g70Ie0tY\ndDzF8mfsa7PNp4dKXcGNJ2EZzg3ffI3E5BSmty7PPu9nH81VCCGEEEIIIYQQQgghhBBCiJwg/WO5\n0z/2PyN3+ZCYnMJUt2Lsv/0q05iImET0NGVrZiGEEOK/SvbPyp39s+zzG37w3Pu61c58P+LAsGhA\n1gEUQgghhBB5kyK3ExBCCCGEyCsS4mO5d/kUZb6ri51jRVQaWpgVtKbLpGWoVJrcvnAsLdb75H5U\nmpq0HuSJUT5LNLV1qNzInWLOVTm3Z0OGa8dERdCoyxCKlHFBU0eXej96oKmji++NS/w8aRlmBa3R\n0TekYedBANy/fCptrJpCQUJ8LA1+Gkhxl2poaGlTqGhpWg+cQtSbUM7v3fjBOW2eOwpdQ2N6z1pP\nfht7NHV0cazWgFb9JvL49jWuHN6Z7bm/T8/IlJVeER/9J7/NxzfO/p+I1684tH4Rx/5cTpPuIyhQ\npESWxwohhMg7YuPiOXHuMvVrfkclJ0e0NDX+j737jquy+gM4/rmDe4HL3jgQF+4t4jY1Vz/3ylGO\n1Nx75ao0R2Y5MnNnWZqaaTnLvUURcSuigpshG2TD74+r0JWrSIFofd+vFy+9z3POec5XX/A8nO95\nzsG9aGFWfDkdjcaEvYdPZpbdvvcQplotcyaPxtXZEZ25Gd3bv0MDrxr8+Ev2BSOiY+OYMKQvnlUr\nYqEzZ0S/97DQmePte56VX07HvWhhbKwsGTeoDwAHT5zOrKtSKklMSmbMoN40rF0TczNTKpYtxezJ\no4iIjObHX7c/N6YJM7/C1saa9d9+gUcJdyx05rzTtAEzJw7H5/wlNu/ck+vYn2VvZ0Ni0Nkcv8qU\ndM/V/0foo3AWf7eeCmVKUadG1qIjk4YPwFSrpd+Yadx/GEJySgp7j5xk0aqf6NK6OZ5VKubqOkKI\n/46klDSOXn1I04pFqFnCCa2JCjcHS77u0wCNWsnBy/czy+4+dwetiYpPOnviYmOOuVZNZ6+S1PVw\nYcOJG9najklIZmSrylQv7ohOa8LAZhXQaU3wuRnK133q4+ZgibW5hhEtKgFw9NrDzLoqpYKklDSG\ntaxEvTIumGnUlCtsy8edPImMT2LDyezXe+rjTaex1WlZPbAxpVys0WlNaF65KFM71uRsYBi/nwnK\ndezPsrMwJXRF3xy/XjRZ5fajWFxtdGw6eYOmM7dRdOhaPEatY/Cqwzx4MklFCPHvkZKUyAXvQ1Rr\n0ByPql6YaE1xKuLOsFnLMdFoOXd8X2bZ0/t3YKLV0mv8LOycXNGa6WjQ+l3Ke9bn4G8/ZWv7cWwM\nHQaMo3RlT0zNdbTuPQxTcx3+fqcYOmsZTkXc0Vla077/GAAuemeNWSlVKlKSEmnXbzQVajVAa2qO\nm0cF3h83k9ioCA7+ln2M7Knv536EhbUtYxf8SKHipTE111HjrVb0HDOdGxfPcGL3llzH/ixLW3s2\nX4nL8atwiZcfs3oeC2tbXNxKcO2sN6kpyQbnrp7VP/tHh4f94+sIIURBS0pM5NjhAzRu1oIatWqj\nNTXFrZg785euQqPVcnj/nsyye3ZuQ6s1ZerMz3F2LYS5uY4OXXtQu35DNq1bm63t2Jhoho2dSLWa\ntdDpLBgwdCQ6nQVnTp1kwdJVuBVzx8rahqGjxwNw/PDBzLpKpYqkxESGjBpHnQaNMDMzp2yFikz5\nbA6REeH8sv75m8pPnzQOG1s7lq/dQMnSHuh0Frzd8n989Okszvn6sGPrL7mO/Vl29g7ci0nJ8auU\nR5kX/vtv3bSeHVs3M/PLRdg7OL6wrBBCCCGEEEKIVyspJY0jVx/QtFJRPEs6Z+WOPmiE1kTFwUtZ\nm0/s9ruN1kTFp129svJmtUtR18OVDcevZ2s7JiGZUf+rSo0STui0JgxqXlGfN7sRwuIPGmXmzYa3\n0s8DOHrtQWZd5ZO82fBWlalXxlWfNytixyddvIiISzR6vaembfTGVqfluyFvZ+XNqrgxrZOnPm/m\ncyvXsT/LzsKUsNUDcvwq7WqTq/+PsJgElu+9SLnCttQq5ZJnZcV/U2JSModOn6N5/Zp4VS6nnwNU\n2IXlM0ajMTFh3wnfzLI7DnljqtUwa0x/XB3t0ZmZ8u47jalfoxI//p49pxETF8+4fl3xrFQGC3Mz\nhr3XAQtzM7zPX2X5jNG4F3bB2lLH2L5dADh8+nxmXZXqyfynvp1pULMy5qZaKpR2Z+bofkREx7Bu\n2/NzKB99uRJba0t+mjeZ0u5FsDA3o1XDWswY0Yczl/zZsudormN/lr2NFfHnduX45VHc+GaMT23c\ndZAte48yf9IQHGxfvOBDbsoKIYQQQgghhBBCCPGmSEpJ5cilO7xdtTiepV3Rmqgp5mjN4oEt0KpV\nHLgQlFl2t+9NfQ6iRyNcbC0w15rQuV456pYtys9HLmdrO+ZxEqPa1qJGKVd0piYMalUdnakJPtcf\nsHhgC4o5WmNtrmVEG08Ajl65m1lXpVSSlJLKiDae1CtXFDONmvJFHfikR0Mi4hLZePTKc2Oa+tMh\nbHWmrBnRhlKutuhMTWherQTTutXn7M1gfj91PdexP8ve0oxH68bk+FW6kJ3R+rYWphR3tuHU9Qck\np6YZnPO+rn9n6FFMwnOvL4QQ4t8nKTWdYzciaVLGnhpu1mjVStxszVjQpRwatZJD1yMyy/555RFa\ntZJprUrhbKXFXKOiY1UX6hS3ZZPvw2xtxySmMvwtd6oXtUKnUfFh/aLoNCrO3IlmQefyuNmaYWWq\nZmijYgAcvxmZWVel1PdtaMNi1C1hi5mJinIuFkxrVZLIxylsOpv9ek99ujMAGzMTVvaoSElHc3Qa\nFc3KOjC5RUn87saw/UJormN/lp3OhAdzmuT4ldNGPs8Ki0tm5fG7lHXW4Vns+bnBsLhklh69w3cn\n7zG6SXE8nHS5uo4QQggh3hxJKWkc9Q+lSXkXaha3189ltNex6D1P/RogV0Myy/5x8YF+/ZP2lXGx\nNsNco6ZTTTfqlHJk46mgbG3HJKQwonlZqrvbodOqGdjYA51WjU9gOIve88TNXoe1mQnDm+nfDzx6\nPWvjwcz1T94uQ93SjphpVJQrZM0n7SsTGZ/MxtO3nxvTJ1vOYavTsLpfHUo5WaLTqmlW0ZUpbSvh\ndzuCbWfv5jr2Z9lZaAlZ3CXHr9LOudtkJyw2kRUHAyjrak2tEg4AhMYmZV7zWUqFAhtzDWGxiQbH\nfz1zh21+9/i8SzXsjdQTQgghhBBCCCGEEEIIIYQQ4lWQ+WMFO39sy7lgtl8MZXZbD+x1Js8tF52Y\nilqp4Mt9gby14BTFpx2i2uxjTNl2najHKS+8hhBCCCHebLJ/VsHtn/VPhcUksHz/FcoWtqVWSed8\nu44QQgghhBB/l7KgOyCEEEII8bpQqzVY2Trid3AHZw9uJy1Vn4Q101my8GAQTbsNzCzbZdRMlhx7\niJ1LEYM2HAoVIyEuhscxUdnaL12tTubflSo1OitbHAq5Ye2QtYGIlb0TANHh2V+crVC3qcHnsjUb\nAnAv4JLReBLiY7lx3psyNRug1hi+wFqx7tsA3Lrkk+vY81Po3Vv0r27FmGal2LZiDp1GTKfNgAmv\n5NpCCCHynsZEjaO9Ldv2HOT3Pw+SkpoKgJWFjgd+BxnSp1tm2TmTR/Ho8jGKFjLcWMu9aCGiY+OI\njI7J1n5dz2qZf1erVdhaW1GsaCFcnBwyjzs72gMQEhaerX7zhnUNPr9VpyYAF68FGI0nJi6ek2fO\n06hOTbQajWFbjfRt+Zy7lOvYX4WIqGg69R9NTGwcq+fPQKXKGhKqWLYUG5d/ibfvBUrWaYVVaS/a\n9BpKg1rVWfL5tFfaTyHEm8VErcTB0pRd5+6wy+82KWnpAFiamuC/oAf9m5TLLPtpZ08CF79HETvD\nhRLdHCyJSUgm6nFytva9SmVNslArldjqNBS1t8DZOmtSrqOVGQCh0dkXUG5SobDB5/plXQG4ci8y\nW1mA2MQUTt8IpV5ZVzRqldG2zt4Ky3XseS0tPYPElDSOXnvIzycCWNynAdfmd2flh405dTOUlnN2\nEG3k31MI8eZSm2iwtnPk9P7tnNq3LWvcxsKSNSfu8E7PQZlle42fxU9nQnBwNdw406mwO49jY4g3\nMmZVrnrWc7FKpcbC2g6nwm7YOmY9m9s8GbOKepR9zKpq/bcNPlf00o9Z3b7+nDGruFiu+XlTsVZD\nTJ4Zs6pavxkAARd8ch17Qes1fhbhIff5emJ/gu8G8jg2hoNbf2LPhpUApKbKCx9CiDefiUaDvaMT\nf+7Yxh/bfyM1Rf+zzdLSiotBwfQdODSz7NSZc/F/GEnhIm4GbbgVcyc2JproqOzP5bXq1Mv8u1qt\nxsbWjqJuxXBycc087uCkvyeFhgRnq9+oaXODz3UbvgXA1UsXjcYTGxuDj/cJ6jZ4C43W8J7U+G19\nW2d9Tuc69vwQ/OA+U8eNomXrdrTt1DVfryWEEEIIIYQQIvdM1EocrMzYdTaInWeDsnJHZhr8F71P\n/6YVMst+2tWLoG/7UMTOwqANN8enebOkbO17lc4ar9XnzbQUdbA0yJs5vSBv1riC4TzHrLyZ8QV1\nYhOSOR0QQn1jebOK+vFn37/mzV4y9lchMj6J9xfvISYhmSX9G6NSKvKkrPjv0piY4Ghnw/YDJ9l2\n4ETmHCBLnTl3D29gcPe2mWVnj+5HyIlfKeriaNCGe2FnYuLiiYqJy9Z+3WpZ3yNqlQpbKwuKFXLC\nxSFrA2InexsAQsKzj6m9Xbe6wedGnpUBuBgQaDSekNEv7gAAIABJREFU2PjHnDx3mYaeVdBqDBe5\nalavBgA+F/1zHXt+eBAazpjPl9KmcR06t2iYZ2WFEEIIIYQQQgghhHiTmKhVOFibs+vMDXaeuWEw\nDn99+RAGtMh6x3J6j4bcXj2cIvaGm3MXc7Ii5nESUfGGm2kDeJXJevdGrVJiqzOlqKM1zjZZ7/84\nWen/HhoVn61+48ruBp8blNfnES7fCTMaT2xCMqevP6B+haJoTAxzEE2ftOV742GuY88P03s05EFE\nLEOW7iYoJIqYx0n8fOQya/adByAlLS1fry+EEOL1YqJS4GBhwh9Xwth9OYyUtAwALLVqLk9rwAd1\ns/Ly094pRcD0RhS2MTVoo6itKTGJqUQnpGZrv5Z71uLoaqUCG3MTitia4WyZtaaBo4X+76Gx2ecV\nvOVhZ/C5bglbAK4GZ89RAsQmpeJzO5p6JW3RqA2Xomz8pK2zd6NzHfurEPU4hb5rLxCbmMrXXcsb\nzfUHhSdQaNIBqsw6xvx9gUxuWZJRTdxfaT+FEEII8Wrp1wDRsvvCA3adv2+wBsi1z9vRv1GpzLKf\ntK/MrS87UNjWcEPBYvY6YhJSjK9/UiJrPSv985qGonbmOFtlPfM5Wur/HhaTfQymcTnDNbXqlda/\nJ3nlfvZ3/+HJ+ie3wqlX2inb81qTJ22dDYrIdeyvQtTjZHqtOE5MQgrf9KqV+byWmKIfS9GojC+F\nbqJWkpCcNd7yMCqByb/40apyYdpVL2q0jhBCCCGEEEIIIYQQQgghhBCvgswfK7j5Y8ExSUzZdp2W\n5R1pW9n5hWUzMjJITkvHXKNkU/9qnJ9Sn8/aerD9YiitlpwhLknmfwshhBD/VrJ/VsHsn/VPRcYn\n8f6S/fp1APs2kHUAhRBCCCHEa0ld0B0QQgghhHhdKJRKhi/axMop/fh2bE80pmaUrOxFxbpvU7/d\n++isbTPLpiQncnDTKnz3/86je0HEx0SSnpZGero+afv0z6eUShVmFlaG11Mo0FnZZjsGkP5kIPQp\nldoEC2vDxPnT/kSHhxqNJzrsIRnp6Xjv2oj3ro1Gy0QG38917PnJqWgJVp2N4XFMFNd8j/Lz3PGc\n/nMzY5duw9zK5pX0QYinyo1eV9BdEOKNp1Qq2bJ6EX1GTuHdgWMxNzPFq3plmjeqS++u7bCzyZpU\nlpiUzPIfN7F1934C79wjMiqGtPQ00p7cE7PdG1VKrC0NN0ZTKBTYWj9zv0V/b017ZmFNE7UaO1tr\ng2O21vrPoWHhRuN5GBJGeno6P2/dxc9bdxktc+9BcK5jz2+3bt+jXZ/hhD4KZ+t3i6haoazB+fVb\ndjJwwnRGDniPD9/rgouTA+cv+zN00kzqtXmPg79+h4Pdq3kWEEK8WZQKBT8Nf5vBqw7TZ+kBzDRq\napZwpGnFInSvVxpbnTazbFJKGt8dusaOs0HcDosl6nESaekZpKXrJ+2mpz/zc16pwMpMY3AMhQKb\nv7T55BAAaRkZBsdNVEqD6wPY6PTthcVkn/gCEBz1mPSMDDZ732Sz902jZe5Hxuc69rymVChQKhTE\nJiSzZnBTbMz1cTUqX4gv36tLt0V7WLb3MhPb5e+i1kKIV0ehVDLp219YNOED5o3ogdbUHI+qtajW\noBlNOvbC4q9jVkmJ/PHzSrz3/kbI3SDioiNJT08j/cnzcPozz8VKlQpzy+xjVs+OQ2WOWT0z5qVS\nm2BpY1jWIocxq4hQ/ZjVke0bOLJ9g9Ey4X8Zs3rZ2AtaraZtmLJ8C+sWfMqo1jUwNddRuU5jxi74\nibEdamOms8y5ESGEeM0plUp+2PQbw/q9T/+eXTAzM6eGV23eersF3d7vg41t1j0hKTGRH1YtY9fv\nW7gdFEhUZATpaWmZYzTPjtWoVCosrQzHSxQKhUGbT49B9nuS2sQEWzt7g2NP64aFhhiNJ+ThQ9LT\n09mycR1bNhofD35w/16uY88PY4d+CMCcBd/k63WEEELA1nmjC7oLQoi/kLy9EOJNoVQoWDeiOYNW\nHKTPkr2YadR4lnSmSaUi9KhfJnve7OAVtvsG6vNm8YnP5M0M817G8mYKBdnyUU/zZs/m3UxUSuws\nDBcIsrHQ1w3NIW/2y8kb/HLyhtEyDyLich17fgsKjaHbwj8Ii0lg/ciWVHKzz5Oy4r9NqVSw+etP\n+WDSF3QfMxNzUy21qpSjed0a9GrfHFvrrPH/xKRkVmzaye/7jhF4P5jI6FjS0tJJe/J9mZYtL67E\nysJwQQj9/CfLbMfgOfOfnpkr9bRuaLjxTYIehoaTnp7Bhp0H2LDzgNEy94LDch17fhj86UIAFk0Z\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wKlr8edWF+NdRqjV4LQ80OJYYEsidLXOIvnaStMRYtPZFcarflcKthoLi708WyUhN4eb3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pbO/yYs4ZtOH3JlzY/smDWIhzHxNOv3I49jEzLjTIyNSEpRMXDm7zSpVYlJfTqgVCgICYukQe+J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DNfzjfvfnxPUEIpd1KZLt6t001p0M41J4CunZ+VS1NGaAgzXTOtfGyqzoMcj6sxEsO3KLWhVN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\ncurYYX4Z1ZR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QHEkmIiIyctnZ2Rg9ejT69+8P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\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enhw9epSoqCjUajUNGjTA3d2dJk2a0LZtWypXrlzW4Ra4N5/H7WW9yzqUp97KIzeZs/sK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377P+1C3Wn7qlt054fGqJYzeEdX63GPXraYa0rsrbzSrjbG3ChdB4xqw5Q/u5e9kyqhX2FoZ9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\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LRAJv+dK4RVu03qqvNG3dAQCf65cK9fG6/vCa+o3lWtZdf8VxOTnZ2Ti+UV9J\nTUnmlvcNGrdsW6im0aK9o7yNvBqNvqERbbv04PrFM6S+oUmdPCyvk/QYWHx9RRk/VWL5XyA1LZ1r\nAQ9oVrcaampvjBNWkxDoupaDKyYV67tg9BCizv1JeUvFSeu2NhYkv3xFUop8IX4tDQ0sTAw5fsWX\nY5d9yMrOAcBAT4cI998ZOcBRJbvSYvWk4aipqfHTsq3vtFM2D0kpqfg9CKO1fU20tTQVbNs71AHg\nil/xE+yVzc/79uPYrL7C66Z1qwLgG6i4sEF2Tg79OzbLf52SmsbNO49oY18LqaZif52a1QPAJ68N\nQ31durWy59zN26SkpuXb7T9zHYlEgkvX1kW+d2X9VIlFIBAIBAKBQCD43LGxsWHViuU8c19HvM+J\nTx2OQPD/IzeX0G0TIOmZfA2BfxmpGdncCInFoZJZoXnWfvO6s3tkq2J9Z/epR+iKvpQ10VU4b2um\nR3JaFkmv5PNhNTXUMDeQcvL2c9xvPSuYH6ytyYMlvfm2rZ1KdqXF0kH2qEskTNpb/CKNoHwekl5l\nEvA4kZZVLQrNf25TwxKAa49iiu1H2fy8bz8da1krvHaoLNeD/CISFM5ny3LpbV+gPaekZ+EVGk/L\nqmXQ0lBcpqtDTflcbb9weRuGOpo41bXhQmAUKelZ+XauPo+RSMC5iW2R711ZP1ViEQj+K6RmZHMz\nNB6HSiaFruO+Mzux+7umxfrO6lmLkMVdKWuio3C+gqkuyelZvEiTf9401SWY62tx8k4U7nei3rj+\naHB/fhdGtK6kkl1psbR/XdTVJEw+cPuddsrm4UVaFreeJNGiijnSt64xbaqZA3AtKI7iUDY/79tP\nxxplFF47VDQFwD9CcaHdbFkufRqUzX+dkp6Nd1giLe3MC10729eUt+mX14ahtiZd6lhx4UEMKenZ\n+Xaufs/k12MHxTUJXqOsnyqxfM6I8SACwcfn3z4eRCAQ/PdJzcjmRlA0TSpbFNZbFvXjnzEdivWd\n078RYWuHUM5UcdO7Cub6Regt2rgHPME94LGCTvBwpTPftq+hkl1psXRIU9TVJEzadfOddsrmIelV\nJgER8bSsZlmEDiLXOjweFr9Bn7L5ed9+OtYpq/DaobIFAP7his+B2bJc+jSumP86JT0Lr5BYWla3\nKrSWXIfa8jb9wuXfCwx1NHGqV44L954r6CaHvMLk69M1q1zke1fWT5VYBAKBQCAQCPI164qmhTXr\nWZ3Z/f07NOtetQlZ0q14rfbV25p1JO53IhW11gVORWjW77YrLZYOqCfXrPffeqedsnl48SpPS7Z7\nh5YcrIxm/e78vG8/HWsWo1k/TlI4L9esC/QbuU6cQMuqRejENV7rxPI2itWefZ/KtefGivNpXqOs\nnyqxCAQCgUAgEAgEAsGHQuxHKBB8XD7lfoTKkJqZw82wRBrbGhXS17yntmLn8AbF+s7sVpWgee0p\na6y4vkZ5Ux2S07PfGhOqyanAGE7eiyErR36xMZBqcG9WW75pUV4lu9JicZ8aqKtJmOL64J12yubh\nRVoWt54m06KySSHdq3VVuZZ1PaT48YrK5ud9++lQ3VzhdWNbIwD8n7xQOJ8ty6V3Pav81ykZ2XiH\nv6BlFdPCmla1vPkBeW0YamvQpZYFFx/Fk5JRoJMdDohCIoGB9orzC16jrJ8qsQgEAsHnjJibVzxi\nJVPQKAAAIABJREFUbp6YmycQfE6kpmdy/f5jmlQvV+h6fnvTWPZNG1Ss77xhHXmyczLlzA0VztuW\nMSb5VQZJqekAaGqoY26kh7vXI457PXxjL2YpwX9N4PuuDirZlRYrvuuKupqECZvd32mnbB6SUtPx\nD4mkZW1bpJoaCrbt6srHKnjcDS+2H2Xz8779dGpYReF1k+ryeW++Qc8VzmfnyOjbomb+65S0DDwf\nPKV1HdtC94+ODSvntSHfQ9tQV0pXh6qcDwghJS0j3+6gxz0kEhjctuh9y5X1UyUWgUAg+FBolGwi\nEAgEpY+dnR0HDrnS1cmJyqZaTGxfusUNgeC/zKtMGcP3BmNgYcPBQ64KGyiUBnZ2drgeOoCTU1e0\nylSmfO+Jpdq/QPCheBkWQOhfPzN69GhGjhxZKn2qq6uTo8KgpJgXr8jNBXMDnZKN3yIjK4et5+9y\n3CeE8NhkklLTyZHlkiOTB/D6XzWJhH/GdeOHzef4at0pdLQ0cLCzomPdCri0qYmJnlQlu9KinJk+\n0/o1Yeaea/xz9QEurYuetK9sHiIT5Zs9WBrrFWrDwkhHwaYolM3P+/SjpaGGqb7iQAxTfbltXHKa\nwnmJRLHtqKRUZLm5HLj+iAPXHxUZ+7OEl/n/H9SyOke8gnH3C2NQy+rkyHI54hVCi+plsbUwLNJf\nWT9VY/nQZMty0VFXL9nwPVFXVycjM11p+6joaHJzc7GwMC/Z+C3S0zPYtOVPXN2OEhoWTkJiEjk5\nOeTkyDcXef2vmpoabgf3Muyb7+k/ZBi6ujo0a9IEJ8eODP/yC0xNTFSyKy0qlC/HvJkzmDh1Btt3\n7ubrYUOLtFM2D8+eRwJgbWVZqA3LMhYKNkWhbH7epx8tLS3MTE0VzpmbyQudsbGKkwYlEolC288j\no5DJZOzeu5/de/cXGfuTpwVi9Jcugzlw6DBux04wzGUwOTk5HDh0hDatWlKpYtGFTmX9VI3lQ5Od\nnY22lnbJhh+AkSNHEhh4j5+3bKaskZQGZfVLpV+B4H+BgGcv+flIKKPHlN7z+ZvIP9+BjNqwmfLm\nRjS0E4vnCQQfCv/g54zacLzUv3/LcrJKNswjLkb+fG5qpvrzeUZGOvu2bebs8cM8jQjlRWIiObIc\nZK+fS2UFz+frdx7ml1FfMW64M9o6utRv3JRWHbrQ1+UrjIxNVbL72JhZlMHl21G4fCvfHPVJeCiX\nzpxg62/LcNv7NzuPX6acbSViouQDOiwsrYpsAyA6UvFZUFNTC2MTxc0YjU3luU+Mj1U4L5FIFNqO\njYpEJpNx/OA/HD/4T5GxRz17mv//XgO/4LTbQS6cPEov5y+Q5eRw2u0gjZu3pmyFisW+f2X8VI3l\nQ5OTLZ9MoKHx8cvFampquB48gEPT5gRvGE6NSQdRk+qW7CgQ/MuQZbwieMNwbMwMcD10sFTqK68/\nozk5OagroU3FREeRm5uLmYWFyn1lpKfz15ZNHHNzJSIsjKTEBAWtRPaGZrT7oBsjvxnG10MGoKOr\ni0OTZnRw7ILLl8MxMTFVye5jY1HGkm9/HMO3P44BIDw0hNPux1m7chl7du3A/fwVbCtVJvK5/J5k\naVV4QpZFGbmmEvlc8Z6kpaWFqaniPen180B8bOF70pttR0U+RyaTcWDvbg7s3V1k7M+fPsn//yCX\nYbgdOoD7MTcGuQwjJycHt0MHaNGqDRUqFr8QlzJ+qsbyMcjJzka9VPWZQLbMHomZdQUq1rYvlX4F\ngg/NsS1L8D3vxqmTJ7GzK90JRwKBQFDavL5/j96ymfLmBjSsXLieJhAI3g//0GhGbzlXqvrrm4j6\nqUDw8fgU9VNV6yvxsfL6ivF71FcyM9LZv30z508c5unjMJLfqq/I8iauqqmpsXaHKzNGf83EEYPQ\n1tGlXqOmtGjvSO8hivUVZew+NmYWZRj8zSgGfyOvrzwND+XK2RNsW7+co/v/ZrvbJcraViImUq5l\nmZcpXF8xzauvvLZ5jaamFkZvaXLGedpWYkIR9ZU32o6Nltc03A/twf3QniJjj3peUNPoMWAoZ48e\n5OKpY/QYOBRZTg5njx2kUQn1FWX8VI3lQ1Ma9RUNDQ1y8v6GSyI6/gW5ubmYmxio3E96ZhZ/uJ7D\n7ZIX4c9jSExOJSdHRo5M3vfrf9XUJOxfNokRczbgMn0NutpaNKlTlU5N6/Flj7aYGOqrZFdalLc0\nY+b3A5j22252nbjCF93bFGmnbB6ex8oXGbMyMy7URhkTIwWbolA2P+/Tj5amBqZGivk1M5L/TcQl\nJSucl0gkWJkXtB0Zl4hMlsve09fYe/pakbE/jSnYoMula2tcL3hy7IovLl1bkSOT4XrBk1YNamBr\nXXxtQhk/VWP50GTn3UNKo34qEAgEAoFAIBCAXB+9FxjI5i0/IzUri36l4hetFgj+zTw5uooE3xOc\nPlV64xc01NWRKbkDRExyOrm5YGag+hzmjKwctl0N4XjAUyLiU0lMzUSWWzC/WPbGPOudP7Ri1A5P\nhv95HR0tdRpXMqNDTStcmlfCWFdLJbvSoqyJLlN71GaW6y323AxnSLOKRdopm4eoF/L5ypaGhee0\nW+TlP/JFWqGfvUbZ/LxPP5rqapjoKebXNG/edvzLDIXzEglYGhaMZYt6kY4sN5eD3hEc9I4oMvZn\nSa/y/z+wiS1ufk84efs5zk1syZHl4ub3lOZ2FlQwKzw3XBU/VWP50GTn/a6FfiL4/6Curo5MlfUy\nUjLk1/H3WIsiI1vGtmvhnLgVKb9+vcpSuH69uV7Gzm+bMGqXH99s85Zff2xNaF+jDC5NK2Csq6mS\nXWlR1kSHX7rWYLbbPfZ6PWFwk6LX5lI2D5FJ8nUOLA0L57rg+lr8WgjK5ud9+in6Oi5/HZ+aqXBe\nIoEyb7QdnZx37fR9ykHfomtIz5MK7hvOjctxNOA5J+9G4dy4HDmyXI4GPKd5FTMqmBY/D0YZP1Vj\n+dDk5OYqNSfhQyDGgwgEH49PPZ9eIBD8d9FQV89/NiyJmOS0PL1F9blgGVk5/HX5Icf9HxMR+5Kk\nVxkK67m9qbfsGt2eH//y4OvfL6OjpUHjyuZ0rF2WIS2qKKxrp4xdaVHOVI+pvRow64APe66HMKRF\nlSLtlM1DVN73fEujInSQPP0i8h1agLL5eZ9+tDTUCuX39Tp38SmKz/QSiWLbUUmv5M/GnqEc9Awt\nMvZnCQX9OTergptvBCcDnuDcrLJcN/ENp0VVSyqYF/+sqYyfqrF8aITeIhAIBALBpyV/PQ9ZLupq\nkhKs39Cs9VWv62Vky9jmEcaJ25FExBWh1ea+oVl/15RRO/345q88rbWiCe1rWOLStLxi7VEJu9Ki\nrIkOv3Srwewj99jr9ZjBTSoUaadsHl7rxG/W7V6jdO1Rify8Tz/v1KyLqD2WeaPtfJ3Y5ykHfYrR\niRPf0Kwdysu15zuRODuUf0N7NqeC2Ts0ayX8VI3lQ5Mjy0WjlDRrgUAgEAgEAoFA8O9B7EcoEHw8\nPsV+hKrqa7H5Y0LfT1/bfuMpJ+5G8zghjcRX2W+NhZTbqUkk7PiqAaP33mXEztvoaKrTyNaI9tXM\nGNLYRmFMqDJ2pUVZY22mOFZhzvFH7PN5zqDGRe9xoWweIpPlOlUZw8K5tsjTN1/bFIWy+XmffjTV\n1TB5K7+meXpdQqrimjUSCZQxKGg7OjkDWW4uh/wjOeRf9B5Rz5MK+htgb83R29GcuhfLQHtrcmS5\nHLsdTfNKJlQwLX4vP2X8VI3lQyPLFfqaQCB4P1Suj4m5ecUi5uaJuXmqIu7fgg+Jqtfz6KRU+Z7W\nhqrvEZSRlc3W074cvfmA8Ogkkl6mkSOTvfE9JG+tOomEPVOd+X7tEb5cfhAdqSZNqpWlY4MqDO1Q\nH5O8vZOVtSstypkbMmNwW2bsOMfui7cY2r5+kXbK5iEyPgUAK5PC41st8vaIjkxIKTYeZfPzPv1o\naahj+ta+5mYG8r+J+GTF659EApZvrG0YlfASWW4u+6/cZf+Vu0XG/iyuYL27wW3rceT6fU54PWJw\n27rkyHI5fD2QlrVssS1TeH09VfxUjeVDkyOToaEhrucCwf8aYrS/QCD419KxY0c2bNzIDz/8wMtM\nGb92rqDUlwSBQFA80SmZDN8XzPM0dW5cOoWxcfFfYj4mHTt2ZOPGDfzwww/I0l9SYeCvSNTElxHB\n50PSnQuEbBlFxw7tWbN6dan1a2RkxPP0bKXt1fLumxnZOSr3NWLjaU4HhDO5twPOLapRxkgXLQ11\nJm6/zO6r9xVsG1Qqw83FLngGRXLx7hMu3HnM7H3XWXPcF9cpvalra66SXWnxfed6HLzxiNl7r9Gl\ngS0SSeHnDFXyAJBbxAKSr08V0bwCquRHtX6K7/jt96wmkRT5vDWsbS1WD2/37jcAtK9THnNDHY54\nBTOoZXWu3n9KbPIrZjs3/2B+ysbyoUlOz6b8R7xvGhkZERRd9ACNoni90FZGhuqDNwZ/OZzj7qeY\nNf0Xhg52xsrSEqlUi5Fjx7Pt710Kto3tGxLo78W1G56cOXeeM+cuMGX6LJYsX82ZE0doWL+eSnal\nxdhRP/DPvgNMnjaT7l27FPn5ViUPUNznTn6uqPbfRJX8qNLPu/ot9PlWUytygbYRX3/Jlg1r3xk/\ngGOnDpSxsGD/ocMMcxnMxctXiI6JYcmCOR/MT9lYPjQvkpOxsilXav2tXr2GkKAgBu+8yMb+VehQ\n9dM8kwsE/yUuBCUx6lAI7dt3ZPXqNZ8sjtWrVxMSHESfBXvZ+nNvOjUsemEmgUCgPOf8Qxix1o12\n7TuU6ufbyMiI8OfRStu/fs7KzMwswbIwk78byqUzJ/hx0q/0GOCCeRlLtLSkzJ08msP/bFewrd2g\nEceu3cHf6zrXL57l2sWzrJw7lT/XLuOPgyepWbeBSnalSfmKlRn2/Vjad+lB1yY12LJmCfNWb87/\neVHPwbzHc/DbX4ol/8feeUdFdXV9+GFAQLoiRbFh19grtiRqrBG7xh4TY4rpXWPvxprEmKj5EtNM\n0Rhj74oiXar03quUoc4AA98fI+rAwMxgwTc5z1p3Lb3szdnsmXvuvb99ikSCRM1z8PR5L7N217ca\n4x46YjRNm9lw/sRfTJo1H68bLmRnZfL+qs0PzU/bWB42BQVSgMemEVtZWXHuzCkGDhpM+I4ZdHjz\nIIZWdo+lbYHgYVCal0H03pfQl6ZyzsvjsV07lpbKjV3z86U0aaJ5w+m796R6aEavLJzD+TOn+Piz\nVcycPQ9bO3sMjYz48O03+O3ngyq2vfv2w8M/BG8Pd65cusDVS+dZ+9mnfLn9c46evkCPXr11snuc\ntG3XntfeepdxzzvTv3sndm3bwpfffnf35zppQA9Bm5m/aDG79+6vcb46I54bQzMbW44fPcILcxfg\neu0qWZkZrN645aH5aRvLoyA/X0qrFjU3L39U7N69m+joGHa94cySLT/SY+jox9a2QPCgVFQo+OuL\nVVw8tJf9+/czatSohg5JIBAIHgtV+uu0z4/z3dKxPNerTUOHJBD8z3MpMIEl35xnxMjHq79WR9RP\nBYKHT0PVTy0tLYlL0b6+IrkzbrisVHct69PX5nP94mle/WAFz0+fi/Wd+srGT97k+B8/qdh269WP\nv12DCPTxwN3lIh4uF/liw3IO7tnOt4fP0KV7b53sHict27Zj7pK3eWbMRJwHd+X/vtzKml0Pv76i\nh3b1lalzX2LVDs01jSHPKuskF0/+xcSZ8/B2U9ZJ3llRd31FFz9tY3nYFBYoJ/c+So3Y0sKc/CLt\nFoXQ11cuwiYv1X5scRUvrtrDWTd/lr88ldljh2JnbYVhIwPe2fYDv5y6pmLbt4sjfr9vx/NWJJe8\nbnHZK4iVe39n5y8nOfnlMnp1aquT3ePijZljOXzenc++/o1xQ3urHU2rSx6gFg0Z7cYR6pIfXdqp\nfg2r/EztOOGai/e96PwsXy97pc74AUYN6oFNEwv+vuLJ3PHDuOYbSmaOlPVLZz80P21jedjkFyoX\nommoOTYCgUAgEAgEgv8mX+zeTVR0DFd3zab9q99g1WNkQ4ckEGhNZYWCxCMbSbv43WMfv2BpYU5+\nSZlmQ7g7X7a0vELndpYc9ORCcCofjX+KGQNaY2thjKGBPh//7stvnnEqtr1bN8Ft5Ti8Y29zNSyd\nq+EZrPsniC8vhPPX28/Qo6WVTnaPi1ee6chRn0TWHgtkTPfmalUGXfIA9zQMlXNV85/r0DFAt/zo\n0o4Ow89rnWc9b4gju+b0rzN+gBFd7WlmbsQJvyRmDWzDjchMsgpkrJrc46H5aRvLw6bgznUn9BPB\ng2BpaUmKXPs++UH68Vd/8uVCaDofjunMjP69sTU3xtBAwsdHgvjdK1HFtlcrK24sG4l3fA4u4Zlc\njchi/clQvrocxZE3BtPDwVInu8fFK8MdOeqbzNoTIYzuZqe2n9UlD4Ca3vX+dSzq7sd1yY8u7dTZ\nj1f7f639uFNrds5Svxjv/TzbxZZmZkacCEhlVv+W3Ii+TVaBnFUTuz40P21jedgUyCto/Rj7cDEe\nRCB4+Dwp8+kFAsG/E0sLcwpKtJsnr69X/3Xtlnx3nfO3kvno+V7MXOSIrUVjDBvp89GvnvzmHq1i\n27uNNe5rJ+Mdk8nV0FSuhqay9qgvX54L5q/3nqNHq6Y62T0ulozowlGvONYe9WVMDwf1eosOeYB7\nz8rqzml6TtclP7q1o/2Dem3P6fOHdWDX/LrXpgMY8VQLmpkbc9w3nllO7bgRkU5WvozVU/s+ND9t\nY3nYVF13Qm8RCAQCgaBhqFrPo0BWptXmkFXPwvXTrG9yISSdD8d2ZsbcPndqbhI+PhyoXrNePhLv\nuBxcIjK5Gp7J+hMhfHUpiiNLq2nWWtg9Ll4Z3o6jvimsPR7K6G72arVdXfIAGtZe1lB71CU/urTz\nUGqPTm3Y+YKOmvWAVtyIuqM9O3d7aH7axvKwkZaUYWlhrtlQIBAIBAKBQCAQ/OsQ+xEKBA+fhtqP\n8J6+Vo6VSSON9pIH0Nde++0WF8Oy+GBUO6b3aY6tuSGGBhI++TuMP26mqtj2ammB64dD8EnIwyUy\nG5fIbDaciWKPSzyHX+lL9xbmOtk9LhYPacXf/umsOxPFc12bqS3J6pIH0FAD1hCPLvnRpZ06S9xa\n6mtzBziwY3rd4zoBnu1kTTMzQ04GZTCzb3PcYnLJKixlxfiOD81P21geNtKSciwtzB57uwKB4H8f\nnetjYm5enYi5eWJuni5Ii0V9TPDwuLt/SbGMJmaNNdpXXZfyMt3H/r686xjnfCP5ZObTzHq6O3ZW\nZhga6PP+gTMcuhKoYtunfXO8v3wDr4gkrgTEcjkwltW/XGb3MXeOrZ5LT0d7neweF69OGMgR1xBW\n/3yZsf06qu1tdckD1P2epGlTa13yo0s7D6M/XzCqN1++/nyd8QOM7NUOG0tT/nEPZfYzPXANjidL\nWsTa+XWvp6GLn7axPGykxTIszUV/LhD816i5eqdAIBA8QSxZsoRDhw7xs+9tFv8ZTYFc9wd/gUCg\n5FZaERO/D0NubIOHlzft2zfspvRV1/ftaz8T/c1iFCUFDRqPQKAVlZWkXfqeiK8WMXvmdE78c0zt\n5q2PCkdHR6LT87S2b9HUDImeHhl5RTq1k55XxDn/eKYM7MgnUwbQ1tYSE6NGGOhLSMpWf63q6YFT\np+YsnzaQi2tmcHblNApkZWw77lMvu/vJLpDRbNE3Go+otFyd/k59iR5fvDSC/JJSPjt0g0b6qq9H\nuuTBwdoMPT1Iz6u5AUdV/h2aai6Ca8pPfdopLVeQX22hhZw7GxbYWNQtwLZoovwOJd3Wro820Jcw\n3akjLsFJSIvl/O0ZhalxIyYNaPfAfrrGIpHoUVFZswiYlV+ilX91otOltGtX99/xIDg6OhIZWXMh\nhtpo6dACiURCWrr2GygBpKalc/L0WWbNmMrqzz6lfTtHTE1NMDAwICExSa2Pnp4ew4Y4sX71Cjyv\nX+bGlQvkFxSwfvPn9bK7n9vZ2eibNtF4hEdG6fR36uvrs3/vl0jz83n/4+U0amRQ7zy0aumAnp4e\nqWnpNdqpyn+rlg4aY9KUn/q0I5fLkebnq5y7nZ0NgJ2tTZ3xtGyh/A7V9rlXx8DAgNmzpnPx8lXy\npFJ+P3wUMzNTpk+Z/MB+usair6+PQlHz3TAjM1Mr/+pERkY/0uu7Ovr6+hw7foLps+aw6LcIvvdM\nU1sQEQgEmqmshO8901j0WwTTZ83m2PETj/X5vDr6+voc++c402fOYs7Ww+w/4yOub4GgnlRWwv4z\nPszZepjpM2Zx7J/jj/39Oz46Umt7u+YOSCQSsjLSdGonMz2Nq+dPMW7yTN74aCWt2rajsYkp+gYG\npCYlqPXR09Oj76ChvLVsLb+fd+PX09coLMzn2x0b62V3P7k5t+lhZ6TxiIuKUOtfVlbKj9/s5tfv\nvq61DYfWbdE3MCAhVvn+Y9+iJXp6emSl18xdVoby2djeoZXK+dJSOYX5UpVzeTm3AbC2sau1bQC7\nFsrPKjVZfX6ro29gwISpL+DucokCaR5njv2JiakZY5ynPbCfrrFI9PWpUNR8z83O0u29sIqq7/jj\nfBZu37493l4e2BrICds8kaKEW4+tbYHgQShKuEXY5onYGMjx9vJ4rPUVR0dHAGKitNNGmju0RCKR\nkKGmX62L9LRUzp0+yZQZs/j4s9W0bdceE1NTDAwMSE6s/Z40aMhQlq9ex4Xrnpy5coOCgny2b15f\nL7v7ycm+jY2pgcYjKjJcrX9paSl7v9zJgb1f1dpG67aOGBgYEBujzK1DS+U9KT2t5gS2qny2aFnt\nniSXk1/tnpSTrbwn2djWfU9q0UL5WdWW3+oYGBgwbdZsXC5fRCrN4+/Df2BqZsakKdMf2E/XWGrT\nZrLqqc0AREdGPnZ95p9/jjFzxnT2vDeLy7/vU795ukDwhFFSVMA3H87l2pH/49ChQyxZsqShQxII\nBILHxl39ddYLzNt1kgMXAoX+KhDUk8pKOHAhkHm7TjJ95guPXX+tjqifCgQPj4aunzo6OpIQo3t9\n5XZGzbEydZGVkca1C6cYM2kmr324kpb31VfSkmsu/g1Kjar3wCEs/WQNv5y5wY8nlXWTAzs31cvu\nfvJysunbwljjER9de33l529389v/1V5faXGnvpIYV62+oqY2lZWpzKddi5Yq59XXV5TjjDTVV2zv\nfFa15bc6+gYGjJvyAh7XLlGQn8e5O3WS5yZOfWA/XWOR1KJlZWfVT8uKj3n09RVHR0eiE7W7LlrY\nNEUi0SM9W7fxs2m3czlzw4/po5xY/vI0HB3sMDE2wkBfn6T022p99PT0GNyzM6uWzMDl/9Zzef8a\nCopK2PLDsXrZ3U+2tADzofM1HpEJNfXbutCXSNizbDH5hcV8+uWvNDJQ7RN1yUNL26bo6emRdrtm\nrtNvK8d2O9hq3jxMU37q0468rIz8QtVxxdlS5Vhb26Z1b+LgYKv8DtX2uVfHQF+fmaMHc8X7FtLC\nYo5cdMe0sTFTRwx8YD9dY9GXSFCoqZ9m5kjVWGsmKlHZpz5OrVogEAgEAoFAINDX1+fEP8eYM3M6\nEV8tIu3S9+pX3BIInjAUJQVE7V3M7Ws/N8j4hbZt2xKTWaiVbXOrxsp51lKZTm2kS0s4fyuVyX1b\n8dH4brRtZoaJoQEGEj2SctXP2dbTg0Htm7FsYnfOfzSK0x+MpFBWxo6zIfWyu5+cQjl2bx/ReERl\n6LZeg75Ej51z+1MgK2Pl0YCa86x1yEMLKxPl/Gc1uc7IV55zaKJ5UUlN+alPO6XlFeSXlKmcyymS\nA2BjblxnPC3ufIeSc2rO61aHgUSPqf1a4xKegbSkjGO+iZgaGeDcp+UD++kai75ED4Wa+0pWvm7X\nQxXRmcrvl9BPBA+Co6MjMVnar33R3NJY2Y8X6NiP58s4H5LO5N4OfDS2E22tTTEx1MdAUvs1pKcH\ngxyb8un4Lpx7bzin3hlGoaycnecj62V3PzlFpdh/cFLjEa3l/a0KfYkeO1/oRYGsnFX/BGOgr7rA\nqi55aNHEGD091N4zM/OVfWYLq7r7TNCcn/q0U1peQb6sej+uXD/DxtyozniqvkPJOdqtMWEg0WNq\nXweuRWQp+2O/FEyNDJjYq8UD++kai0Sih6JCTT9eINfKvzrRWUViPr1A8D9KQ48HEQgE/w3atm1L\nTEa+ZkOgeROTO3qLbut4pUtLOBeUzJR+bfl4Yk/a2phjYnRHZ8hR/yyspweDOtiybFJvzi+bwJlP\nxlFQUsr2U0H1srufnEI5tq//ovGIStdtHIK+RI9dC5zILyll5ZGbGKjRW7TNQ4smprWvN3cn/w5N\nTDTGpCk/9WlHua5dtef0QuVzvq3Gde1MlWvJZWv3fmgg0WPagLa4hKYhLS7lb584pW7St80D++ka\ni35tz+n1XtdOed0JvUUgEAgEgobh7noeWurWza3uaNY61lrSpTLOB1dptZ1p2+w+rTa3Ds263R2t\n9f2nOfXucAplZew8F1Evu/vJKSrF/v0TGo/6a9ZlrDoWrOZZWPs83NWS1eQ68865FlZa1h7ryE99\n2qlTszarW0e/qxPX8rlX57Fo1lrGUqtmXVg/zTo2q1A8BwsEAoFAIBAIBP9hxH6EAsHDoyH3I7yr\nr93WTl+4NyZUNz0hI1/OhdAsJvW048Pn2tHWuvE9XSlPvVanpwcD21rxyZj2nHlrICeXDlCOZbwU\nWy+7+8kpKqPFsksaj2gdxsuCUl/bMb0rBbJyVp+MrDG2X5c8tLCs0r1q5jqzQKllaTsmtK781Kcd\npb5WrnIup7hKXzOsM567mlae9mNCp/Sy51pUNvkl5RwLTMfUUJ+JPWwf2E/XWGod219YqsZaM7G3\ni2nXrmH3HxUIBP+b3L1/Z2o3B03MzasbMTdPzM3ThZisAlEfEzw07vbnqTla2bewtrizp7WsaGEe\nAAAgAElEQVRu4wDScws4ezOSqUO68enM4TjaNbm7l3NylvrxtXp64NSlFZ/NfobLW17i/KZFFJTI\n2XbEtV5295NdUEzTmZs0HlEp2Tr9nfoSPb54fQL5xTI+O3ihxlp1uuTBoZkFenqQllvznpJx51xL\nawuNMWnKT33akZcpyC9WfX/LLlD2iTaWpnXG08LaXDnetpbPvToG+hKmD32Kq4GxSItkHL0Rgqmx\nIZMHd31gP11j0ZdIqFA33kHHPd6riEnNeaz6i0AgeDKQaDYRCASChmXOnDlcuepCUHYlz+y9xZGA\nLDGxXyDQAWlJOavPxjPxu2Ce6uuEh7fPE/PgP2fOHFyuXqEyOYhbq54hy/2IWKhQ8MRSlBhC+I4Z\nJPy5lk2bNvLTjwcxNKy7CPyw6devH6m3paTWMnG9Oo30JQzsaI9rWAryMtUBTE+v/JPR6/5S61dl\na11NJI9MzcU9omojBeW16h6eSo/3fyIkSXXh/QEd7LGzNCH3zuRsbe3UYW1uzO0fl2o8OjZvUndC\n1NCjTTNeG9OLo55ReESqbhKhSx4sGhsyoL09buEpyEpVBw1cCU4CYET31rXGoW1+6tvO1Ts/q8Iz\nUrlhwcCOzWuNCcDUuBFOnZvjFp5CplS1AOEZmcaQz34nIE51U5QXhnamTFHB+YB4zvjFMal/e0yM\nGtXZjjZ+usZia9GY3EJ5je/+9dBkjbFUJzWnkLRsKX369NHZV1v69etHckoKySnabVbSqFEjhjgN\n5KrLdWQyVWG098ChOD09Sq2fXK60bWZtrXI+LCKS6zfcAO5uenzN1Y3WHbsReCtYxXbwoAE0t7cj\nJydHJzt1NLO2RlGUq/Ho0qmjppTUoE+vnrz75hv8fvgvXN086p0HSwsLBg8awLXrNygpUe2rLly6\nDMDY50bWGoe2+alvOxcvXVH5v5u7JwBDnAbVGhOAmZkpw4cO5prrDdIzVK9jVzcPuvcdxE0/f5Xz\nC+bOpqysjFNnznH85GmmT5mMqanmBUE0+ekai62tLTm5uTW++1dcrmmMpTrJKamkpKY+0utbHYaG\nhhz88Uc2btrE2vMJzPgpnJD0+gn7AsF/lZD0Imb8FM7a8wls3LSJgz/+9Nifz9VhaGjIwYPK63vF\nT5dwXneIW/EZDR2WQPA/xa34DJzXHWLFT5fuXN8/Nsj7d3pqChmpKVrZGzRqRO8Bg/G+4YJcrvos\nN+3ZfswZO1StX1mp8nnGqtpzaWxUODc97gwwufNcetP9OqN6OxIRorroXK/+TtjY2iPNzdHJTh1N\nmjbjVoZc4+HYsbNa/0aNDLl48m++2rya1KQEtTbXLp5BUV5Oh87dADCzsKRXfyd83K4jl6kOXHdz\nuQDA0BGja/wed5dLKv/383IHoPeAwbX+fQAmpmb0dRqGj/t1bmeq9s9+njeYPKwXIQG+KucnzZpP\neVkZLhdOc+XsCUY7T6OxSd0DUbTx0zUWaxtbpHk5Nb5jnq5XNcaijiA/H6yaNKFNm7oXunvYtG/f\nHm8vD5z6PEXwponE/76a8uL6bcgoEDxqyoulxP++muBNE3Hq8xQ+Xh6Pvb7i6OhIkyZNuOnlodkY\npWY0wGkwri5XkctU+4unB/ZmzNNOav1K72gl1tbNVM5HRoThfuM6cE8rcXe9Ts+ObQi5pXqvGTDI\nCTv75uTc2UBaWzt1NLVuRlZRucajY6cuav0NDQ05eewom9atIikhXq3NhbOnKS8vp0vXpwCwsLCk\n/yAn3K9fQ1aiek+6ekl5Txr53Jgav8fl0kWV/3u6K7WlAU5135NMzcxwGjoMN9drZFbb8NzT7QZD\n+/YgwE/1nvTC3AWUlZVx/swpzp48jvOU6ZiYar4nafLTNRYbWzvycnNqfMdcXS5rjEUdqSnJpKWm\nNIg+8+PBg2zauJE/dy5j56sTSIqofYFfgaAhqaysxP3kb6ye1o+UMD+uXr3CnDlzGjosgUAgeOzc\nr7+uPOTK5C3HCE7IauiwBIL/KYITspi85RgrD7k2mP6qDlE/FQgenCehfnq3vpKmfX2lZ38nvN1c\nKK2mfc8a1Z8FE4ap9avSsqyaqtZX4qLC8fVU1leqtCxfD1fG9W1HZKjqO3/PfoNoZmtPXm62Tnbq\nsGpqjV+qTOPRtkPt9ZVLp/9m79Y1tdZXXC8p6yvt76uv9Ow3iJvu12rUVzxclHrVEDX1FY9rqvWV\nAG+lltWrv3rdsAoTUzP6DBrKTY/rZFerafh7uTH9md6EBqpqWRNnzqO8rIzrF87gcu4kz02cqlV9\nRZOfrrFY29iRn5db4zvm7ao65kpbgv28H3l9pW+//viExmhl28hAn0HdO3HNNxRZqeqCGU4Ll/Ps\nK6vV+pWWKcefWluaqZyPiE/lhn84cO86uuEfRucpb3MrOlHFdmD3jthbW5EjLdTJTh3WluYUuP2q\n8ejUpu5F69XRq1Nb3nxhHIcvuOMeqLqpgS55sDAzYWD3Drj6h1EiV11Q67K3su94blDPWuPQNj/1\nbeey9y2V/3sEKjfVHdS97rGXpo2NGdKrC67+YWRkq9bs3AMj6D/vE/zC41TOzxk3nLJyBWdu+HHq\nui9TRgzExLjuzXa18dM1FtumluQWFNb47rvcrH1xnrrwCY2miZXVY6+fCgQCgUAgEAgEhoaG/Pjj\nQTZt2kjCn2sJ3zGDosT6PdcKBI+cykqy3I9wa9UzkBKESwONX+g3YCB+iXla2TbSlzCgnTU3IjNr\nzDV9dssFxu5QP+aptLwCAGtT1XfeqPR8PKKUNcqqFRHco7PoveoUISmqMfV3tMbWsjG5dzb+09ZO\nHU3NjMjYM1Pj0dHOvO6EqKFHSytefbYjf99MxDNGdY6zLnmwaNyI/m2tcYvKRFYt1y5hynFpI7ra\n1xqHtvmpbzsu4ap6otedv3WAo3UN2/sxNTLAqX0z3KOy7m74WIVnzG2GbTpPQGKuyvlZA9tQpqjg\nwq1Uzgal4ty7JSaGBnW2o42frrHYmBuRV1Ra47vvGqk6h1Nb/OKzaWJpIfQTwQPRr18/UnMKSKtl\n843qNNKXMKBtE25E3UZ+p0+qYsT2a4z7Qv3irlX9V1NT1XpZVEYhHjHKuk/V0jYeMdn0WXeRkNR8\nFdv+bZtga2F8t//R1k4dTU0NSd/lrPHoYGtW6++ojR4Olrz6dDv+9kvBK1Z1zpAuebAwbkT/Nk1x\ni8mu0b9ejVD2GyO61L75hbb5qW871yJUxwh5xSn/1gFtm9YaEyj7zkHtmuIek01mtQ1kvGJzGP75\nVQKTVO89s/q3VPbHIRmcvZXOxJ7NMTFUXcRXHZr8dI3FxsyIvOKyGt991yjV+7U2pOXJSMspFPPp\nBYL/QZ6E8SACgeC/Qb8BA/FNyNVsyJ3n9PY23AhPr/HO+cyGk4zdekatX+kd26ZmqjpDZLoUj0jl\ne/vdOYyRGfRadpSQZNWY+rezUa7HdmcjGW3t1NHUzIjMfQs0Hh3tLTWlpAY9WjXltVFdOeodh2e0\n6nu4LnmwaNyI/u1scIvMqPn8HKpcp2xEt9rH02ibn/q24xKqulaaV4zybx3QzqbWmOCOxtHRFvfI\nDDLzVce/eUZnMmztCQISVMfszXJqf0c3SeZsQBLOfdtgYqSF3qLBT9dYbCyM1eot18NV52Vqi2/8\nbaG3CAQCgUDQgDg6OtLE0oKb8dptjtZIX8IAx1o0620ujNt9Xa3fXa3WrLpWW4BHtBrNeu2F2rXW\n4lKd7NTR1NSQ9N2TNB4Pplkn4xWr+kynSx4sjBvRv21T3KLVaMnhSr14RJfanzu1zU9927kWXl2z\nVsY/wLHudbHv6sTR6nTibIZvVaNZD2h1T3sOTmNiLy01aw1+usZiY16LZh1Zvzm+fkkF9OnXv16+\nAoFAIBAIBAKB4N+B2I9QIHgwnoT9CKv0Nd9E7daVbqSvR/82lrhF59bQGEZ94cmEr73V+slrGwuZ\nWYRnrLIWWnlnVLtHbC59N7sSmlagYtuvtSW25kbkFpfpZKeOpqaNSN36nMajg43m9TWq072FOUuG\ntuZYQDpecao6kS55sDA2oF9rS9xjc5GVqebaJVKpZY3oVPs4em3zU992rkWpaofe8cq/tX+buuvz\npob6DHK0wiM2l8wCVQ3UKy6PZ3Z5EJisqgnO7NucMkUlF8KyOBeSxcQedlrpa5r8dI3FxsyQvOLy\nmvpatHb6dHX8U4qEviYQCOrF3fpYXO3rad2PmJunGTE3T8zN0xb/RKm4fwseGo6OjjSxssQnUrs9\neRvpSxjYuSXXb8UjL1Pd/3jYh98xavlBtX739nJW3ac0MuU2bqHKtdSq9By30ESeeu0rgqvt0zeg\nkwN2VmbkFJToZKcOa3MTco6s0Hh0dKi7b1JHT0d7Xn9+IH/dCMEjTHWdOF3yYGFixIBOLXELSai5\n13RgLAAje7erNQ5t81Pfdq7e+VkVnuHKPa4Hdm5Za0wApsaGDO7aCreQBDLzVNcT9AhLwum9/fjH\npKmcf+GZHpQpKjjnG8Vp7wgmO3XRbk9rDX66xmJjaUpuYUmN7/61W6pr62mLb0w6vfv2q5evQCD4\n30XS0AEIBAKBNgwePJjQ8Eimz1vEh8djcf4+lJPB2ZQpRBVWIKiNzMIy9rimMHzvLU5Gy9m3/wDn\nLlzEysqqoUNTYfDgwUSGh7JoznRif/yQ0C3OZPucpLK89qKmQPA4KYwPJOaH9wneMJ5OVhJ8vL1Z\ntmxZg8QybNgwTE0acz4gXmufVTOdkJeV8/r+S2TlFyMtlrP5qBehydksGvmUWp9WzcxpY2PBad9Y\nwpJzkJcpuBSUwIt7zjFpgHLwhn9cJoqKSvq0s8VAImHpgSv4xmQgL1OQWyTnm3OBpOQUMu/prgBa\n2zUEy6YOoHUzc/7yiFQ5r0seANa8MJhCWSlvf3+FhKx8imRlXAtJZvNRLwZ1bI5z/9qFM13yo0s7\niooKjBrp8+UpP9zDUymSleEXm8nqP9yxtTRh5pBOGvOzZuZgJBI95uw+TVRaLvIyBW7hKSw9cAlD\nA326tlQVLHu2saGLQ1O2/XOTvCI5c4ap35C5Otr46RLLqJ5tqKisZNs/PuSXlJIpLWb1H27kF9e+\nQENtnPOPx9SkMcOHD9fZV1uGDRuGqakpp86c09pn8/q1yORyFix+lYzMTPKkUlat28itkFBee+Ul\ntT5tWreinWNb/jlxiuDQMGQyOWfPX2TG7PnMmDYZgJu+/igUCgb064uBgQEvLXkDL5+byGRycnJz\n2f3VXpKSU3j5xQUAWts1BGtXLqdtm9b89ucRlfO65AFg68b1FBQW8vLrbxIXn0BhYRGXr7qwat1G\nhg4exLQpk2qNQZf86NKOQqHA2NiIz3d+wTVXNwoLi/C+6ctHy1dib2fLvDmzNOZny4a16OtLmDT9\nBcIjo5DJ5FxzvcGiJa9jZGRE927dVOz79u7FU127sH7z5+Tm5fHi/Lka29DWT5dYxo95joqKCtZv\n3oo0P5/0jEw+Wr4SqTS/xu/VxMnTZzE1NX2k13ddLFu2DG9vHyR2nRi/P5j3/4khMLX2jY8EAgEE\nphby/j8xjN8fjMSuE97ePg32fF4XyuvbGyzsGfnpD7z1zakaBUeBQKCKf0wab31zipGf/gAW9ng3\n8Pu3iakpLhdOae3z3sqNyGUyli9dRHZWJgXSPPZsWUNUWDCzXlyi1qd5y9a0bOPI5TPHiQ4PQS6X\n4XrpHO+9NIuxztMBCPb3pUKhoHuf/hjoG7Di7cUE+Xkjl8uQ5uXw874vSU9NZtrcRQBa2z0qVu/Y\ni3FjE16eNoYzf/+BNC+H8rIyMlJT+OPgPj5762WaO7TitfeX3/X5YPVmigoLWPnOElIS4ykuKsTz\n+hX2bFlDn4FDGP381Lu2CoUCIyNj/m/Pdm66X6e4qJBb/j5sX/MJzWztcJ6heUOJ91dtQl+iz5vz\npxAXFYFcLsPH/TrL33oZQyMjOnRV1Uu69uxDh87d+HbHRvLzcpnygnbvONr46RLL8JFjqaio4Nsd\nGynMl3I7M4Ptaz6hMF+7CS/VuXb+JOPHjUNPT69e/g+ClZUVF8+f48D+fcgDTnJr5XBSTu+hTFq/\nwYsCwcOmTJpJyuk93Fo5HHnASQ7s38fF8+capL6ip6fH2LFjOX9W+3vS6vVbkMtlvL54IVmZGUil\neWxet5qwkGAWvfKaWp+WrdvQxrEdp0/8Q1hoCHKZjEvnz7Jo9kwmTZsBgL/vTRQKBX369cfAwIA3\nlyzC18cbuUxGbm4O3361m5TkJOa/+DKA1naPip179tG4sQlTJozm6OHfyc3NoaysjNSUZH448C1v\nvrKIlq1a88Gnn931WbvxcwoLC3j79cUkxsdRVFjItauX2bxuNQMHD2HilGl3bSsUCoyMjfly5+e4\nu16nqLAQv5s+rF7+MbZ29sycM09jjKs3bEWir8/c6ZOIigxHLpPh5nqNpUsWYWhkSNduqveknr37\n0KVrN7Zv3kBeXi5z5r+oVS608dMllufGjKOiooLtmzeQny8lMyOd1cs/Jr8e2gzAudMnnwB9xhsr\nw0o2zH+Gg2vfID7Uv0FiEQiqU15Wis/Fv9n64kh+Wv8mc2ZOIzwslMGDBzd0aAKBQNCg3NVfLVsw\navWfvP3dJQLixDulQFAXAXGZvP3dJUat/hMsWzSo/loXon4qEOjOk1Q/raqvXL9wWmufd1ZsolQm\nY8VbLynrK/l57P18LdFhwcxYWHt9xaGNI1fPKusrpXIZNy6f48PFLzB6orK+EhJwkwqFgqd690Pf\nwIDV77xCsJ8PpXfqJr/u/5KM1GSmzFGOsdLW7lGxcttejBs35rWZYzl77L76SloKh3/cz6q3F2Pv\n0IpX3rtXX3l31RaKCwtZ896rd+srXq5X2Pv5GnoPGMyoCffqKxUKBYZGxhz8ege+Hq4UFxUS7O/D\nrnWfYm1rx4Tpmusr767YjESizzsLpxIfHUGpXMZN9+useudlDA2N6NBFVcvq0qMP7Tt3Y/+ujeRL\nc3GetVCrXGjjp0ssQ+/UV/bv3ERhvpTszAx2rfuUwoL6aVnXLpx65PWVsWPHcjM0mswc7WpA6994\nAXlpGa+s+4bMHCnSwmLWHzhCSEwSi6eMUuvTyq4ZbVvYcvL6TUJjk5GVlnHeI4C5n33B1JEDAfAN\ni0VRUUHfru0x0NfntQ37uBkag6y0jNz8Qvb8cZbkzGxedH4GQGu7hmDFK9Np3dyGPy+4q5zXJQ8A\nG5fOobBYxhubDpCQlkVRiYyrPsGsP3AEp56dmPzsgFpj0CU/urSjqKjA2LARu349yQ3/MIpKZPiG\nxrB8zyHsrC2ZPXaoxvxsWDobfYmEmR/vIDIhFVlpGa7+YSzZsA+jRo3o1k51kn7vzm3p6tiSLT8c\nI6+giPkTtNN2tfHTJZYxTr2oqKhkyw9/k19YTEa2lM/2HCK/sFireKpz5kYA48Y3TP1UIBAIBAKB\nQCAApT7q4+1NJysJwRvGE/PD+xTGBzZ0WAIBAJXlZWT7nCR0izOxP37IojnTiQxvuPELY8eOxS/u\nNlkFMs3GwMpJPZCVKVj6szdZBTKkJWVsORVMWKqUF4epn/fbsqkJbZqZciYohfA0qXJ+cUgaL/2f\nO859WgHgn5CjnGfduin6Ej3e/sUHv3jlXOS84lL2XYkkNbeYuYMdAbS2awg+ef4pWjU15ejNBJXz\nuuQBYPWUnhTKynnnVx8Ss4sokpdzPSKDLaeCGdiuGc/3rn0xQF3yo0s7iopKjBrps+diOO7RWRTJ\ny/FPyGHNsUBsLYyZMUDzRturJvdEItFj/r4bRGUUIC9T4B6VxVs/e2NkIKFrcwsV+56tmtC5uQU7\nzoaSV1zKC05tNbahrZ8usYzs1pyKykp2nA0lv6SMzHwZa44Fkl9Sv3U8zodkMG78BKGfCB6Iu+tl\nhKZr7bNiYldkZRW8+asfWQVypCVlbD0TTlhaPi8OVn8Nt2zSmDbWJpy9lUZ4WgHy8gouh2Xy0kEf\nnHu3ACAgKQ9FRSW9W1mhL9Hjnd/88UtQbjCSV1zGvmuxpOaVMNepNYDWdg3Bx+M606qpCUf9VBfw\n1SUPAKucu1IoK+fd3wNIzClW9q+RWWw9E85Ax6Y837N5rTHokh9d2lFUgJGBhK8uR+MRk63sxxPz\nWHs8BFtzI6b3d9CYn1UTuyLRg/nfeRGdWYi8vAL36Gze+s0fIwMJXar14z1aWtLZ3pyd5yORlpQx\ne2ArzR+Cln66xDKqq62yHz8fQb6sjMwCOWuPh5BfUl7j92rifEj6I18voy7EeBCBQHeepPEgAoHg\nv8HYsWPxi80kK187vWXV1D7IyxW88cMNsvJlSItL2XI8gLCUPF58Wv2aZi2tTWnTzIwzAUmEp+Yp\ndYbgFF7ad41J/ZTP9v4J2Uq9pa01+hI93vrRDb+423fXY/v2UigpuUXMG9oBQGu7huCTib1oZW3G\nUW/VTRN0yQPAmml9KZKX8c5P7iTeLlQ+P4elseV4AAPb2zKxb+3ahi750aUdRaVSb/nqfDDukRkU\nycvxi7/N6r98sbVozIxBta+1V8XqqX2RSPSY9/VVotKVupNbZAZvHnTDsJE+XVuozuft2bopnVtY\nsf1UEHnFpcwerN1Gltr46RLLqKccqKisZPvpoDt6Swlr/vKloKT2zaTq4vytVKG3CAQCgUDQgOjp\n6TF23HguhN7WbHyHFRO73dGsfWtq1kPaqvVp2fSOVht0v1abwUs/3K/V5qpq1of87tNaS9nnEqPU\nWgcpn8u0tWsIPh7fRalZ+1bTrHXIA8Aq5273tOTs+7XkMKWW3KtFrTHokh9d2lFUVN7RrKPu06xz\n79Os694craq9mjrxbd46pEmzjkBaXMbsgdrVI7Tx0yWWu5r1uWqatUx3zTqzQI5f3G3GjRuns69A\nIBAIBAKBQCD4dyH2IxQIdOdJ2o+wSl+7GJ6jtc+K8R2QlVfw1h/BZBWWkl9SzucXYghLL2Shk3pt\npWUTY9o0bczZ4EzCM5QaxuWI2yz+JYiJPewACEjOv6OvWWCgr8c7h0PxS5LeHcu43zWRVKmMOQOU\nWo+2dg3BR6Pb0apJY/4OUN3TQpc8AKya0JFCuYL3joSQmFNCUakC1+gcPr8QzYA2VkzobltrDLrk\nR5d2qvS1r13i8YjNpahUgX9SPutOR2Frbsj0PrWPU61ixfgOSPT0WPhjANFZRUpNKzaXdw6HYGgg\noYu9mYp9DwdzOtuZsutyLNKSMmb109yGtn66xDKyszUVlZXsvBRLvqyczIJS1p2OpKBe+lopfvE5\nQl8TCAT14m59LCRDax8xN08zYm5e3Yi5eZCZL8M3NkvcvwUPDeX+JeM45xejtc+aeSORl5Xz6lfH\nyZIWIS2Ssel3F0ITM3l5dF+1Pq1sLGlrZ8Up7wjCErOQl5Vz0S+aBdv/YvJg5d7K/tGpKCoq6du+\nOQb6EpbuPYlvVArysnJyC0v45pQXKdn5zB/VG0Bru4Zg+QvP0NrGkiOuwSrndckDwLr5oygsKeXN\nvSdJyMyjSFbKtaA4Nv5+jUFdWuI8qPa9nXXJjy7tKPtzA774xx230ESKZKX4Raey6qdL2FqZMevp\nHhrzs3b+SCQSCbO3HCYqJRt5WTk3QhJ4Y89xjBrp0621jYp9r3b2dGllw7bDruQVyZgzopfmD0FL\nP11iea5PeyoqK/n8sCv5xXIy8wpZ+dOleu1pnZlXyM3IJNGfCwT/QfQqKytF5UIgEPxPERQUxOqV\nKzl1+jSNDQ0Y6mhOd3sTmlsYYm6k39DhCQQNhqKikryScuJyZPilluCfKMXK0oIlr73O8uXLsbS0\nbOgQNRIUFMTKVas5ffoUBoaNMe86FJNW3TFs0hz9xuYNHZ7gP0JFqYzywhyKU8IpjnSnMDOJLt2e\nYsXyZcybN6/BJ8wuXLiAoBuXuLxmmmbjO3hFpbH1b28C4rOorKyks0NT3hzXm0kD7k1KnrXzFJ6R\naSTuV26gEpJ0m+WHbhAYn4WBRMKADnasmjkYM+NGzN51mrhMKe9M6MNn0weRklPItmM+uIQkkZVf\njHljQzo2b8Irz/VgysB7k721tXsU7LsQyMrf3PD5fB6OdjX7w0tBiczepdxQ2XXjbLq2bKpzHgBu\nxmTw+TFvfGMyKCktx8HanEkD2vHRpP6YGDWqM0Zd8qNtOxM3HyPpdgGH3pvAqt/d8IvLRFFRyaCO\n9myaO4wuDk3v2i746iwXAuLJ+OGNGrEFJWSx/fhNPCNSKZCVYWtpwpSBHXjfuR9NTI1q2H912p/1\nRzxoY2PBzW3zqX7ZTNt2goC4TGK/fUUnP11iUVRUsuO4D3+6RZCeV0zzJqYsfLYbHZs3YeFXZzn8\n4URG9tBuEtPItUfpPXwMP/38s1b29WXhwoWE3ArCx81Fax83Dy/WbNiMr58/lZWVdOvahQ/ffYvp\nUyfftRk/eQZuHh7kZ6YAEHgrmPc/XoavfwAG+gY4DRrAlg1rMTM1xXnaLKJj4/jkg3fZsGYlSckp\nrNu0lUtXrpKRmYWFuTldOnfkrddfZeb0exsGaWv3KPjy62/54NPPiAjypUP7mgXecxcu8fzUmcq/\n3ced7t266pwHAE/vm6zduAVvn5sUl5TQulVLpk+ZzMplH2NqalJnjLrkR9t2nh0zgfiERP458jsf\nLVuJj68vCoWCIU5O7N6+hae63hPRp74wj9Nnz1OaX3OiqV9AIBu2bOOGmwf5BQXY29kya/o0ln/y\nAU2bNKlhv23XFyxftQ7Htm2ICvavcV8c/fwUfP38yUlL0MlPl1gUCgUbtmzjl9/+IC09gxbN7Vny\n8iK6dOrItNnzOXv8L8Y8p34jo+r0H/IMPXr15qefftLK/lFRWVnJoUOH2LJpI6HhEbSyNmNIaxO6\n2pnQxMQAYwNJg8YnEDQksrIKcorLCc8sxj2xmKTsQp7q2oVln614Ip7PNVF1fW/dvHW14WAAACAA\nSURBVImQsHBa2zVleLdWdGttQ1MLE4wbGTR0iAJBg1FSWk5OQTFhiVm4hiaRmJFD925d+XT5Z0/E\n9b1w4UJ8A4P586Kn1j7+3u7s/XwdIYF+VFZW0r5TV15c+j5jnO+9w78+eyJ+Xu54xyknKUSEBLF1\n5YeEBvqhb2BAr/6DeH/lJkxMzVg6bzKJcTEsfusj3l6+jvTUZL7ZvgEPl0tkZ2ViZm6BY8fOzF28\nlLGTZ9xtQ1u7R0VaShI/f/sFntevkJwYT6lchomZOY7tO/H06PHMe+VNzC1VJ4gE+Xqxd9t6gvx8\nkJUU09yhFaOdp/H6B5/R2MT0rt2Lk0eRmhjPnl/+ZseaT7jlfxOFQkGfgYP5dONOOnTudtf2nRdn\ncO3iGQJTa272Fxbkz7c7N+Hn6UZhYT7NbO0YN3kmS977FEurpjXsf9izg90bV+DQui1nvcNrfD9f\nmTGOkEA/PKIydfLTJZYKhYJvd27ixOFfuZ2Rjo19c2YueAXHjp15d9FM9v1xiqEjRmv4dJQkxEbj\nPKQ7x48fx9nZWSufR4VUKmXLli3s2/8d+fl5WLbrQ+N2fWls2w59U0v0JKLuI3j0VFYoKC/KQ5YZ\nR0msH9JYfywsrHj9tSVPRH3lxIkTTJkyBa/AMBzba6ejenu4s3XDGgL8fJWacNeuvPnuhzhPnX7X\nZtbkCXh5uJGQqdxQOORWEJ99/B6B/n4Y6BvQf5ATqzdswdTUlDnTJhEXG83bH3zCZ2vWk5KcxLZN\n67l25RJZmRmYmVvQsXNnlrz+FpOnz7zbhrZ2j4rkpES+3fMF169cIiEhHrlMhpmZOR06dWL0uAks\nWfo2ltXuSTe9vdi2cS2+Pt6UlBTj0Ko1k6ZM58NlKzAxvXdPch7zLEkJCfx65B9WL/sIP18fFAoF\ng5yGsHH7brp0vXdPWvjCNC6cPU16fs1BfUEB/uzYsgFPtxsUFORja2fPlOmzeO+TZTRpUvOe9NWu\nbWxY9Rmt2zpyMziyxr1l+vNjCPDzJSYtWyc/XWJRKBTs2LKRP3/7hYz0NOybt2Dhy6/QsVMXXpw9\nncPHzzDiuTF1fzj3MWpIf3r36vnE6DObt2wlLDQEW4c2dOw3nJYdn8LMyppGhjW1cIHgUVBSVEBu\nRgpJEUGE+1ynVFbM889PZMOG9fTs2bOhwxMIBIInipr6axOGdW5O11bWWJs3xqiReKcU/HeRlZaT\nXSAjPDmbGxFpJGbkPlH6qyZE/VQgqJ0nvX66cOFCbgYGc+ich9Y+AT4efLt9HaGBflBZiWOnLix8\n/X2em3ivvvLmXGcCvN1xi1ZqHpGhQWxf9SFhQf7o6xvQs/8g3lmxERMTM95eMIWk+BgWvfkRb366\nlozUZPbt2IDn9cvkZGViam5O2w6dmfPyUkZPulc30dbuUZGeksSv+7/Ey/UKKffVV9q278SwUeOY\n88qbmFuoalm3fL3Zt2M9t/yV9RV7h1Y89/w0lry/XKW+snjqKFKTEvjip6PsWvcpIXfqK70HDOaj\n9Ttof1995YOXZnL90hluJhXViDH8lj8Hdm3G3+tOTcPGjjGTZ/LyO5+ora/8uHcHX21aiUPrtpzw\nCKvx/Xx91nhCg/y4Hp6hk58usVQoFBzYvZlTR+7VV6bNX0zbDp358OVZ7P3tJIOf1a6+khgXzdRh\nPR55faWkpASHFi14d/YYPlwwSSsfz6BINv7fX/iFx1FZWUmXtg68O/d5powYeNdm6gfbcA+MIOPy\n9wDcik7kky9+wT88DgN9CYO6d2TdGy9gZmLM9I92EJucwfvzJ7L61ZkkZ2az+fu/ueodTGauFHOT\nxnRq04LXZ45h2shBd9vQ1u5RsPfPcyz76lcC/9xJu5Z2NX5+wTOQ6R9uB8Drl610a9dS5zwA+IRE\ns+n/juITGkOJTE5Lu2ZMGTGQZS9NwcS4bg1Rl/xo287YpRtITLvNn9s+4LM9h7gZGktFRQVOPTvx\n+bvz6ep4b3GV2ct2c87NnzzXmmNhAyLi2XrwGO6BERQUlWBnbcn0UU58tHASTSzMatjv/vUkq7/9\nkzbNbbh1ZFeN69T53S34hceRcv6ATn66xKKoqGDrD8f47dwNMm7nYd/Mipcnj6RTmxbMWb6bY7s+\n4blB2ulpMUnp9Jnz8RNRPxUIBAKBQCAQCKr00Y2btxARFoqZbStMOg3BxKErBuZNkDQybugQBf8R\nFCUFlOamUZwUTEGYG+WlJTz//EQ2PgHjF0pKSnBobs8bT7fh3TG1L3h3P96xt/n8dAiBiblUVlbS\nqbkFS0d1xvm+hUlnf+OKV8xt4nYq5/uFpOSx8q8AApNyMZDo0d/RmpWTemJqZMC8fa7EZRXy1ugu\nLJ/YndTcYrafCcUlIoOsfBnmjRvR0c6cxU93YHLfVnfb0NbuUXDgahSr/g7Ac/V4HG1qvu9fDk1n\n7reuAFz7bAxdmlvqnAcA3/hstp0OwS8hh5JSBQ5NTHDu05IPxnXFxLDuOTS65EfbdiZ/cZXEnGJ+\neXUoa44F3l0gd2C7Zmyc3pvO9y3Q+uJ3blwMTiP1y5qacFBSLjvPheIZfZtCWRm2FsZM7tuK98Z2\nxcrEsIb9novhbDxxi9bWpnivmVBjvvSMr68RmJhL1LYpOvnpEouiopKd50I57JVARn4J9paNWTC0\nHR3tzFn0nTt/LB3OiK72dX4mVcRmFTJkwzmhnwgeCgsXLCDw+lkuvDdEax/vuBy2nYsgMCmPykro\nZG/O0mfbM7HXvY0V5hzwxCs2h9itEwAISc1n5bFggpKlGEj06Ne2CSuf76rsv77zIv52EW+N7MCy\nCV1IzSth+/lIrkVkkVUgx9zYgI62Ziwe7sik3vc2rNDW7lFw4Hosq/8JweOzkTg2M63x8ythmcz9\nzgsAl4+fpUtzc53zAOCbkMv2cxH4JeRRUqbAwaoxE3s154MxnTAxrHssji750badyV+7kZRTws+L\nB7L2RAj+iXnKftyxKRumPEVn+3trES36wYeLoRmk7JhYI7ZbyVJ2XojEMzabQlk5NhZGTOntwLvP\ndcTKpOY6IF9fiWbjqTBaNzXBa8WoGv3xzG89CEySErl5nE5+usSiqKhk14VIDt9MJiNfhr2FMQsG\nt6GDrRkvHfTh91edGNHFpmYDahi9240+zz7/yNfL0IQYDyIQ1M6TPh5EIBD8+6nSW5aOaM+747pr\n5eMdk8nnJwIJSMimEujU3JI3R3fDue+9zV1e+OoyXjGZxH85B4CQ5FxWHPYhMCEbA30J/dvZsGpq\nH0yNGjH36yvEZebz9tjuLJ/cm5TcIrafDOJaWBpZBSWYGTeio70lr4zowuR+99rQ1u5RsP9yGKuO\n3MRrwxQcbWquk3k5OIU5X18B4PpqZ7q0sNI5DwC+cbf5/GQgfnFZSh2kqSnOfVvz4YSemBjVrbfo\nkh9t25m04zxJ2UX8svRZ1vzli1/8beVzegdbNs3sT+cW98a5LfzWhYu3kkn7Zn6N2IISc9hxOgiv\n6EwKSkqxtWzMlP5teXdcd7Xr2u05H8KGY360bmaGz4apNZ63p39xkcCEbKJ3z9bJT5dYFBWV7Dwd\nxJ+esWRIS7C3aszCYR3paG/Ji/tc+POdUYzopt37YWxmAYPXHBd6i0AgEAgEDUzVeh7utWiv6vCO\ny2Hb2XBVzXpEeyb2uvccMGe/J16x2cR+/jxwR6v9+5aqVjuxm1KrPeCp1GpHdbynWZ+LUNVa7cxY\nPLxdTc1aC7tHwYFrsaz+JxiPFaNq16wPKNftcvlkhKpmrWUe4I6WfDb8npbcpEpL7qydZq1lfrRt\nZ/IeN5Jyivn5lYGsPV5Ns57aXVWz/t5bqVnvrPmsdytZys7zEXjG5lAoK8PGwpgpvVvw7uiOamuP\nX1+OZuOpUFpbm+C14jk1mrU7gYlSIreM18lPl1juatY+SUrN2rJKszbnpR+8+f01J0Z0qX0D8fv5\n6lIU+9xSSU5No3Hjxlr5CAQCgUAgEAgEgn8/Yj9CgUA9T/p+hFX6mttHg2lrXfeePVX4JOSx/UIs\ngcn5VFJJJ1szXn+6DRN73NMW5v7gj3d8HtHrRwAQmlbAqpORBCXno6+vR//WlqwY1xETI30WHAwg\nPruYN59ty6dj2pMqlbHjYizXo3LIKizF3FifDjamvDykFZN63luHQFu7R8F3NxJZcyoS94+HqM3b\nlYhs5h/0V/77fSe62JnpnAcA30QpOy7G4p8kvTNW05jnu9vx/ihHzfqaDvnRtp2p+2+SlCPjpxd7\nse50FP5JUhSVlQxoY8V65850trunNb70cyCXwm+TtLnmvkO3UgrYdTkWr/g85ThMc0Mm97TnnRFt\n1Y4J3Xstnk1no2ndtDEeHw+toZPN+j8/gpLzCV/7rE5+usSiqKhk9+U4jvilkVEgx97CiPkDHZQ5\n/SWQ317uw7OdrGv/QO5jz9V49ntlCX1NIBDUm6r7t8eqcWrnmKlDzM0Tc/PE3LwHm5v35YVw9rkm\nivu34KFS1Z/7fPUG7exr7jWqDq/wZLb8eQ3/mDQqqaRzSxvenjSISU5d79rM2PQ7nmFJJP/6CQDB\n8RksP3iBgNh0DPQlDOjkwJp5IzE1NuSFLX8Ql57Lu5MHs2LOs6Rk57P18HVcAuPIkhZh3tiIjg7W\nvDp+AFOG3GtDW7tHwbenvVnx40Vu7lmqNm+X/GOYtfkPANx2vkrX1jY65wHgZmQKWw5fxzcqhRJ5\nGS2bWTJpcBc+njFc857WOuRH23aeX/0ziZlSfls2i1U/XcI3OhVFRQWDurRiy6LRdGl1b47a/G1H\nOO8bRdafn9WILTA2ne1/ueIRlkRBiRxbKzOmDunKB9OG0sSsZv/25T8erDt0hTa2Vvh9/WaNfnnq\n+kP4x6QR/9NHOvnpEouiopLtR1z541oQGXmF2Dcx58XRfejYwpoF2//irxVzGNm75v7H6th9zJ29\nZ/1JTkkV/blA8N/iiF5lZWVlQ0chEAgE9SE5OZkTJ05w5fJlAgP8yMzMIr+w5qLjAsF/BYlEDysL\ncxwdHek3YBDjxo1j/PjxGBv/7y3sV3V9X758Bb+AQLKyMikqyG/osAT/EQyNjLG0sqL7U08xdMhg\nnJ2dGThwoGbHx4SPjw+DBg3ix7fG8nw/7V76BQJB/TntG8uir8/j5eXFgAEDHmlbVdf3X7/9zJRJ\nNRcZEwgED5d/TpxixtyFj+X61gVvb29OnjyJh7sbIcHB5EmlyOSlDR2WQNBgGBsZYmVpyVPduzN4\nyNAn7vlcF6qub08Pd0KCg8nNkyKTyxs6LIGgwTA2MqKJlfL6dho85Im7vquez3f/8CejJkxu6HAE\ngofKsqUvEh54k4jwcPT1n4xJbSUlJZw7d47z58/j6XOT+Lg4CvKlVCgUDR2a4D+AnkSCuYUVju0c\nGdS/3xNXX1EoFHTp0oVefQew7+AvDR2OQPBQOX3iH16aO/OJ1WfcPTwJCQkhLy8XuUzW0GEJ/iOY\nmZljY2dHn969GDVyJJMnT8bBwaGhwxIIBIInnrv6q7s7ISFCfxUI7uqvT3XHaciTp7/qgqifCgSq\nPOn106r6yo7/+4MR40V9RfDvYsVbi4gMvElExKOvryxbtozvD+zD//dtWJlrt6mAQCCoP4vXfYtf\nTBrhEZFPTP1UIBAIBAKBQCCAe/qom7sHwSEhSPPyKJWL8QuCx4OJmTk2Nrb069ObUaOevPELy5Yt\n4/tv9+C2YrTaxT4FAsHDZenP3gRmSwiPjBL6ieCBqaonfb+oPxN6aLfosUAgqD9nbqWz+MebT+x4\nbTEeRCBQ8qSPBxEIBP8NlHrL17ivnSj0FoHgMfDGD24E3q4UeotAIBAIBA2MQqGgS6cO9Gyq4Jt5\nfRo6HIHgX4+0uIyhn19j8Rtvs3Xr1oYORyAQCAQCgUAgEDyBiP0IBQJVnvT9CBUKBZ07daCXpZyv\nX3iqocMRCP71SEvKGLbLm1eWviP0NYFAUG+U9bGO9LKu4JuFYqyqQPCoySsuZeimi6I+JnjoVPXn\nvR1MOfCOWPNRIHjU5BXJGPjeARa/tlT05wLBf48jepWVlZUNHYVAIBAIBAKBQCDQngXz53Pj0hnc\nNs7CqJGYwCsQPCpKyxUMX3WEIaMm8PMvj2ej7QULFuDudoNbNz2emAFUAsG/EblcTq+BQ3EaPISf\nf/65ocMRCAQCgUDwhLJgwQKuubpxzDUAIyPxfC74dxDg48FC5xEcP34cZ2fnhg5HIBBoyYkTJ5gy\nZQrHz11h8LDhDR2OQPBQKJXLeXpgb4YMdhL6jEAgEAgEAoFAIBAIBP8iFixYgIurG3+5+GMo6iuC\nfwmBNz15efLjq68UFBTQuVNHpj7dh8/fnf/I2xMI/st43Ypi9BvrRf1UIBAIBAKBQCAQCP7HKCgo\noHPHDkzsasnG6b0bOhyB4F+NT1w2zruvCv1E8FBZMH8+rhdOcv3j4RgZSBo6HIHgX0tpeQXP7rzB\n0NET+fmXXxs6HIFAIBAIBE84VXqLc3drNs7s39DhCAT/anxispi447zQWwQCgUAgeEKoWs/j2JtD\ncGpv3dDhCAT/alYeC+ZEqJTI6BgsLS0bOhyBQCAQCAQCgUAgEAgED4Eqfe3oq31xcmzS0OEIBP9q\nVp2M5GREkdDXBALBA3O3PvbOMwzuYNPQ4QgE/2pWHg3geHCOuH8LHglV/fnJtfMZ0q11Q4cjEPyr\nWX7wAse844iMjhb9ueD/2bvz8BrP/I/jn5MIQYnaBaG0BKFBrC2xRTepNoilpLRThi6npW1SxUQV\nCaFzZhSJtjRFCaIaSi1V+04W+xR17IrEUhFZzu+PGZ3pb9ppa8mdc/J+/dvlvHtdfZ778b3PuR8U\nPgv4JTwAAADgZKInTNCFa1manLTLdArg0iZ9uUvnrtxQVHR0vn1mdHS0zv9wQeMmTMq3zwQKo7HR\nMTpz9pyioqJMpwAAgAIsOjpaly7+oBkf8MwA15CVdUNjI6wK6tyZg+EAJ/P000+rc+fOevet15V1\n44bpHOCumBQ9TufOnmE+AwAAAACAi4mOjlb6xR/0kS3/vnMF3Es3s24oenj+7q+UKlVKY94fq7hF\nq5R86Pt8+UygMLpxM1tDJ8erc1AQ+6cAAAAA4GRKlSqlMWPHaeaGI0o9kW46B3BZWdm5iliYos6d\nOjI/wV0VPWGCLv6Yo7+uOmw6BXBpH6w6rPNXsxUVPcF0CgAAcAK35i2ffHtIqfZLpnMAl5WVnavw\n+bvUOagT8xYAAAqIp59+Wp07ddSIJQeUlZNnOgdwWWknL2vWpu81LipaXl5emjdvniZOnKhLl/gz\nKAAAAAAAzuzWfG3UsiPM14B7KO3UVX269eRP8zUAuBM/7Y8tTlNWdq7pHMBlpZ5I18wNR1i/cc88\n/fTT6hzUSe98ukZZ2TmmcwCXlXL0rD7+erfGRUVxPwcKKTfTAQAAAAD+GG9vb02MmaQPlu7SlzuO\nmM4BXNKXO47og6W7NDFmkry9vfPtc729vTVx4kSNnzhZixYvybfPBQqTRYuXaPzEyZo4cWK+Xt8A\nAMD5eHt7K2biRM2wRWtlUqLpHOCOOBwOjbIO1NlTdn04ZYrpHAC3YcqUKTp5wq7XBv9JDofDdA5w\nR5IWL9JfJ45nPgMAAAAAgAu6tb/yyd+itXop+ytwbg6HQ5FvDDKyvzJgwAC1a9dOvd75q85c4IXm\nwN3mcDg0ZNwMnTh/SVM+/NB0DgAAAADgNgwYMEDtAtvp+Y+26ezlTNM5gMtxOCTr3F06dTlbU6ZO\nM50DF+Pt7a2JkybJtuY7LU05YzoHcElLU87ItuY7TZyUv+dlAAAA53br+yphset1NoN5C3C3ORyS\n9bOtOnU5S1M+nGo6BwAA/IcpU6fp1JUcvT4vRRznAdx9Zy/f0PMzd6ldYKAGDBggSTp58qTef/99\nVa9eXQMHDlRaWprhSgAAAAAAcLumTJ2mU1fzNHTRAeZrwD1w7kqWBsze+7P5GgDcqSlTp+nU5Wy9\nPncX6zdwD5y9nKnnP9rK+o17bsqHU3Xy0o96Zeoy7ufAPXA2/aqem7hI7dpxPwcKM/fIyMhI0xEA\nAAAA/piAgABdvHhR789YqPZ+1VTl/pKmkwCXsefYefX729f68+DBGjlyVL5//q3r+y/vva+gju1V\n1btKvjcArmrHrt16tmdfDRo0SCNHjjSdAwAAnMCt5/OYsZFq1a6TKlbm8Fs4p2kx72vhZx/pyyVL\nFBAQYDoHwG0oW7asAgICNGrEu8rLy9MjbQNNJwG3Zc+unerXM0R/Zj4DAAAAAIDLurW/MnncaLUM\n7Mj+CpxW3OSxSpxtZn/FYrHo6aef1mez52jJmi3qGdRaHh5F8rUBcGXjP1msT778Rku+TGL/FAAA\nAACclMVi0dNdu2r23M+1dMd36hZQXR7ubqazAJcRs3yfPtv8vZYkMT/BvXFrP2nsp8vUrk55Vfby\nNJ0EuIxke4aen7XL2HkZAADAef3z+ypdNXvO50rafljdmtWURxHmLcDdErMsRfEbvmPeAgBAAVS2\nbFkFNGuuv0yarry8PLV+sLzpJMBlXL+Zq94zdsi9dAV9vWqNihcvLklq3bq1Xn31VVWtWlWLFi3S\n6NGjtXTpUnl6eqpBgwZyc+PPowAAAAAAOIuf5muT45TnyFPrWvebTgJcxvWbueozK1VFSlfU16v/\nPV8DgDt1a/0eFTPtn+fdP1TRdBLgMq7fzFGv6ZvlXqr8z/bHgHvhn/fzZhoV9Vfl5eXp0QY1TCcB\nLuN6Vra6j50v9xJl9PWq1dzPgcJrv3tkZGSk6QoAAAAAf1znzp21desWTZy7Un7Vy6lWJS/TSYDT\nW51qV9+/rVBg+/b69NN4Yz/+6dy5s7Zs2aKxURPk36ihHqxdy0gH4EpWrFytZ0J7q23bQH366af8\nuA8AAPxunTt31patWzQlZrx8Gzwsn1oPmk4Cfre83FzFjI7QJ3+P0bRp09S9e3fTSQDuQK1atVS5\ncmUND39LV69eVdv2HfnzLZzKmpUr1Df0GQW2bct8BgAAAAAAF3drf2XqpPGq06CRfB5gfwXOIy83\nVx+MeUezppjdX/H09NQTTzypyX+boqR1O/R4a3+VKsEPgYE7kZuXpxFT5mry7KWaNm06+6cAAAAA\n4OQ8PT31xJNP6oMP4/RV8gkFNais+zw9TGcBTi03z6HRX6Tq76sPadp05ie4t/55XsZWxSzaJD/v\nUnqgQknTSYDT++bAeYXN3KXA9h2MnpcBAACc17/nLbH6as9xBflVZd4C3KHcPIdGL9qtv329j3kL\nAAAFWK1atVS5ShUNt32qazdy1KZOBblZLKazAKd29vIN9Z6xQ6euOfTNt+vk7e39s79etGhRNW3a\nVEOGDFGnTp10+PBhRUVFKS4uTlevXpWfn59KlChhqB4AAAAAAPwRt+Zr7/7tM13LylWbB8syXwPu\n0LkrWeozK1Wnf7T84nwNAO7UT/tjf52pqzey1bZuJdZv4A6dvZypXtM369TVPNZv5Jtb9/N3JkzV\n1etZCmz0APdz4A6dTb+q7mMTdDLjhr5Z+y33c6Bw2+8eGRkZaboCAAAAwB/n5uamHj1CdeTYMf0l\ndpG8ShRVk1qVxOwM+OMcDmnG6lS98tE36tW7j2bPmSsPD3OHUPzz+u6hI0eO6J0Ro1TGy0vNA5rK\nwgUO/GEOh0NTpsVpwMAh6tWrl2bPnm30+gYAAM7n1vP50SNHFBU5XKVKl1HDJs14PkeBd+3qFb05\n8Dl9vWSB4uPj9fzzz5tOAnAXNG3aVHXq1NHoUSO1Z9dOBT3xpIoVK2Y6C/ifHA6HPpo2Ra8MfIH5\nDAAAAAAAhcR/7q9MGP2uSnmVkV9j9ldQ8P149Yoi/txXK78sGPsrZcuWVUi3bvp0zueKW7BCj/r7\nqnL5MkabAGd19cdMhY2aokVrtheI6xsAAAAAcHf8c37SXfHzFumTNfvU+sFyquRV3HQW4JSu3sjW\nwJnbtCT5tOLjP2N+gnvup/Myjh5T5Kzl8iruocY+93NeBnAbHA7p443H9NrnKerV5znj52UAAADn\n9u95y0J9vDpVrR+qyLwFuE1Xb2TrpY826ovdduYtAAA4gZ/O85gSr2T7ZXWqX1HFiriZzgKcUtrJ\ny+oRu13upSvqm2/XqXbt2v/z7/fx8VGPHj3Ut29f5eTkaPr06YqKilJqaqqqV6+uatWq5VM5AAAA\nAAC4Xbfma+9Nna2UU1fV0bcc8zXgNqWduqrQT1JUxOv3zdcA4Hb9tD/291lKtqerU4PKKlbE3XQW\n4JRST6Sr+4eb5F6qAus38t2t+3nk5FjtOXJGnZvUVjGPIqazAKeUcvSsnhkzT+4lvPTN2m+5nwPY\nb3E4HA7TFQAAAADuTFRUlN599121rOOtcX1ay8+nvOkkwGnstV/Q8LmbtfXwaY0dO1YRERGmk37m\n1vX9aOuW+mBilPwbNTSdBDiN5NQ0vfFWhDZu3logr28AAOB8bj2fN2nxiMLfnyRfv4dNJwH/xeFw\n6MuE2frb2JGS8vTF4sVq1aqV6SwAd9mWLVv07LPPShY3jXhvrHr26ceLtFEg7U1N0fC3Xte2zZuY\nzwAAAAAAUEjd2l9p3Ly13hwzSXUbsL+CgsfhcGjpgjmaMn6ELHIUuP2VjIwMhfboobVr1+qlkE4a\n/mKIypQqaToLcAoOh0NzV2xU5PQFcri5a/EXSwrU9Q0AAAAAuDsyMjIU2r271n67VgPa1NabT9RX\nmRJFTWcBTsHhkBK2f6+xSw9IHp5avORL5ifId//cTxquFrUqaEzXevKrWtp0EuA09p66opFLDmjb\n0R80duw4vq8NAADump/NWwLr6q0ujZi3AL+TwyElbD2i979MlYowbwEAwNls2bJFz3Z9WsrO1LtP\n1lGPgOriOA/g97l8PVsTvz6kWZu+V/t27ZSwcJHKlCnzh/89N27cUEJCgmJiGn/m9wAAIABJREFU\nYpSWlqamTZvqtddeU+/eveXh4XEPygEAAAAAwN3y7/nadb0T9IB6NKnCfA34nS5nZitm9TF9uvXk\nHc3XAOCP+vf6fUPvdqmn0OY1Wb+B3ynj+k3FLN+vmRuOqH279kpYuJD1G8Zs2bJFzz7TVZacmxrZ\nu616BTbifg78Thk/3lB0wnp9/PVutW/fTgkLuJ8DkCQtcI+MjIw0XQEAAADgzjz66KPq0qWLln+z\nQePmrJb9wlV5319Sle/nRQ/Ar0k+dl5jE7cr/LMNqlbbV4mLv1BoaKjprP9y6/pe9tVyRY4Zq2Pf\nH1fVqt7yrlLFdBpQYO3cvUcjIt/Xq0PfknfVakpMTCyQ1zcAAHA+t57Pv17xlWxRo3XK/r0qVamq\nipW9TacBys6+qdVLF+svbwxSwqczFNavrxYtWqQ6deqYTgNwD1SvXl0vvPCCzp49o7Gj/6LVX3+l\n0qW9VOvBh+Tu7m46D1Dy7l0aGzlSEUNfVbWq3sxnAAAAAAAoxG7tr6xc8ZX+Hv2eTp/4XhWrVFUF\n9ldQAGRn39Q3yxZr9LA/a9FnMxTWr1+B3F/x9PTUc337qlq1apry8WeavuBr5ebmqna1yrqvhKfp\nPKBAupmdoyXrdujlqI/08RffqN/z/bVoUWKBu74BAAAAAHfHv+cn1TV1bpI+/vaQcnLzVKvCfSpZ\nrIjpPKBAys7N09Lkk3pj3h59uvGI+g14UYsSmZ/AjFv7SSu+3ayoRVtkv5Qpby9PVfZiBg78mpQT\nGRq//JCGJ+5VtYcaFNjzMgAAgPP62bxlzhJ9tGa/cnJzVatiKZUs5mE6DyiQbubkaekeu16fvU2f\nbjisfv2ZtwAA4IyqV6+uF178k85euKSxs5ZpzcELKuXprloVSsrdjbekAb/k/NUsfbzhmF6em6LD\nl3L1ge1vmjR5sooXL35b/74iRYro4Ycf1uDBg9WpUycdPnxY0dHRio2N1YULF1SvXj2VLl36Lv9X\nAAAAAACAu+Hf87V0jftshdb8I12lirmpVvkSzNeAX3H+6k19svmEXk44qH9k6I7nawDwR/1sf2xm\nktYcOK9SxdxVu2Ip1m/gV5y/ckMfrftOL3+2U4cv5rB+o0D45/38RZ394YLej/1cq5KPqnTxYqpV\npazc3dxM5wEF0vmMa4pbvlOD/p6kQ2ev6oO/2jRpEvdzAD/Zb3E4HA7TFQAAAADuDofDoTlz5ihq\n3FjtO3BQPhXv16N1K6letXIqV8pTxTz+94GFDklsm8BV3biZo4tXb+jgqYvaeOic7OfT5Ve/nsLf\nGa7nnntOFkvB/r//p+s7Kkr79u1TzRo+ate2jRo2qK/y5cvJs1gx04mAMZk3bujChYvau/+Avl2/\nQd8ft8vPz0/h4eFOcX0DAADnc+v5fPz4KO3fv09VfWqo2SPt9FA9P91ftpyKFeOwaeSPa9eu6Nzp\nUzqYlqxtG7/VjczreqpLF4157z01atTIdB6AfJKamqpRo0Zp6dKlKl6ihNoEtlfDh/3lXbWaSpXi\n4Brkj8wbmbp04YIO7N+nTeu/lf3498xnAAAAAAAoRPLy8uT2Gz/y/a/9leo11LR1oB6q56cyZcur\nKN9/Qj758dpVnTt9Uof2pWiHE+6vXL58WePHj9eMuFhlXL6igPoPqnmD2qpdvZLKlCrJD+5RqF35\n8bpO/5CulH8c1/pdB3T9Rpa6PPWU3hszximubwAAAADA3fHT/CR2ujIuX1GTByqoaY0yqlXhPpUp\nUVRuv3EALb+1hiu7diNbpzMylXbysjb+4wdl3sz+1/zkfeYnKBB+2k8a9772Hzgkn/Kl1bqWl+pV\nKa2yJYvK04MZOAqvzOw8Xfrxpg6euaLNRy/LfuGKGtT3VcQ77/J9bQAAcM/917ylVkUF1CyrWhVL\ny6tkUbnzLIJC7OqNbJ1Ov669J9O14dA55i0AALiY1NRUjRo5QkuXLlPxYkX06IPl5Ve1lLy9iquU\n5/8+4xlwZbkOhzKuZ+vYDz9q54nL2nPsosp4ldZLg/6sd955R15eXnf9M0+fPq24uDh9+OGHunLl\nirp27arXX39drVu3vuufBQAAAAAA7o7U1FSNGjFCS5f9a75W6341qFJS3l6eus/T3XQeYExenpR+\nPVvfX7yuXSevac/x9Hs+XwOA3+un/bFly1S8qIcefaiCGlbzkneZ4rrP08N0HmBMXp5D6ddv6tgP\n17TreIZ2H/uB9RsF2s/u58WKqq1fDTWsWUlVy5VSqeKc+QjX9HvOCMjNcyj9WqaOnk3Xjn+c1u5/\nnFQZLy+9NHAQ93MAv2SBxeFwOExXAAAAALj7tm/frqSkJG3dvFn79u1VesZl3cjKMp0FGONZrJju\nL+OlBg381LJ1awUHB6t58+ams27LT9f31q3at2+f0tPTdePGDdNZgDGenp66//771aBBA7Vs2dKp\nr28AAOB8bj2fb/nX83kGz+fIR/eVKqVKFSvJ3/9hdejQQV27dlXVqlVNZwEw5OTJk/ryyy/1zTff\nKCU1VefPndOVK1dMZ6GQYD4DAAAAAEDhlZSUpLffflsrVqxQjRo1ftc/89P+ypZ/7a9ksL+C/OMq\n+yuZmZlasWKFvv76a+3auUPHjh1TxuUrys3NNZ0GGOPm5qbKlSqqVevW6tCho9Ne3wAAAACAu+M/\n5yc7t2/T999/r4wrV5Sbm2c6DTCmVMmSqlixgvwbN1GHjsxPULD9+7yMTdq3d6/SL1/WjaybprMA\nYzyLFdX9Xl5q4Oenlq0f4fvaAADACOYtwH8rdV9JVazAvAUAAFf303kea9YoJXm3zp//QVeu/Wg6\nCzDGzc1NZUqX0gMPPKCmzZrr8ccf1xNPPCFPT897/tlZWVmaP3++Jk+erJSUFDVt2lQDBw5UWFhY\nvnw+AAAAAAD445ivAT/37/laTTVt1iJf52sA8HuxfgM/Z3J/DLgT/3k/T01J1rnz53Xl6jXTWYAx\n/7yfl1atWg+oSUAz7ucAfssCi8PhcJiuAAAAAGBOZmamRo8erUmTJqlly5aaMWOGfH19TWe5nNDQ\nUElSQkKC4RIAt2Px4sXq1q2brl+/zrD1Nu3atUuhoaHKysrSvHnz9Oijj5pOAgAAwP9w9epV+fj4\n6K233tLw4cNN5zitkSNHavz48Zo1a5b69u1rOgcA8C99+vRRZmamFi9ebDrFacXFxenVV19VmzZt\nNGfOHFWqVMl0EgAAAAAAyGdpaWl65ZVXtHHjRr344osaP368ypUrZzqr0EhISFDPnj3Fz8KAgsNi\nsWj+/Pk/fWcY+esf//iH3njjDS1btkwhISGKiYnRAw88YDoLAAAAAOAkvvvuOw0aNEjr1q3Tq6++\nqvfff18lS5Y0neVymJ8AwL/Z7XY1bdpUnTt31pw5c0znuJy8vDx16dJF+/bt086dO1WhQgXTSQAA\nAHACt86YmjVrlsLCwkznuJyzZ8+qSZMmatGihRITE2WxWEwnAQAAwEnxewrcsmvXLtlsNs2bN09l\ny5ZV//799corr6hatWqm0wAAAAAAQCHhcDjUq1cvffvtt9q1axdziXtg3rx56tOnj+bNm8dvEQAA\ndwXr973H+g0Av4zvO9w7P/74o0aMGKG///3vCgwMVGxsrB588EHTWQCc3wI30wUAAAAAzNmwYYOa\nNGmiadOmKSYmRuvWrZOvr6/pLAAocOx2uypXrixPT0/TKU6radOm2r17t1q1aqX27dsrMjJSeXl5\nprMAAADwK6ZNm6bc3FwNGTLEdIpTGzNmjN566y31799f8+bNM50DAPgXu92uGjVqmM5wagMHDtSm\nTZt07NgxBQQEaOPGjaaTAAAAAABAPrl8+bIiIiIUEBCga9euaePGjYqLi1O5cuVMpwEACrGHHnpI\nS5cu1erVq3X48GH5+vrKarXqypUrptMAAAAAAAVYTk6ObDab/P399cMPP2jTpk364IMPVLJkSdNp\nAAAXlp2drV69eqly5cqaMWOG6RyX5ObmptmzZ8vDw0O9evVSTk6O6SQAAAAUcIcOHVL//v312muv\nKSwszHSOS6pcubLmzp2rpUuXavLkyaZzAAAAALiApk2bKj4+XsePH9ef//xnffLJJ6pdu7ZCQ0O1\nevVq03kAAAAAAKAQmDRpkhYtWqTZs2erWrVqpnNcUq9evfTqq6/qxRdf1L59+0znAABcAOv3vcf6\nDQDIbyVLltQHH3ygnTt36vLly2rUqJEiIyN18+ZN02kAnJyb6QAAAAAA+S8jI0ODBg1SYGCgateu\nrb1798pqtcrNjT8iAMAvsdvt8vHxMZ3h9Ly8vJSQkKCYmBiNHz9ejz32mM6dO2c6CwAAAP9PVlaW\nbDabBg8erDJlypjOcXrjx4/X0KFDFRYWpiVLlpjOAQDon7Oe6tWrm85wegEBAdq9e7datmyp9u3b\nKzIyUnl5eaazAAAAAADAPeJwOBQfH6+6detqxowZmjBhgrZv365WrVqZTgMA4CcdO3bUnj179Pe/\n/11z586Vr6+v4uLimF8DAAAAAP5LSkqKWrVqpYiICL355pvauXOnWrRoYToLAFAIvPHGG0pLS1NC\nQoJKlChhOsdllS1bVomJidq2bZsiIiJM5wAAAKAAu3btmkJCQtSgQQNNmDDBdI5La9euncaNG6eI\niAitW7fOdA4AAAAAF1GlShVFRkbqxIkTmj17tk6ePKmgoCA1bdpUcXFxyszMNJ0IAAAAAABc0ObN\nmzV8+HBFRUUpKCjIdI5Li4mJUePGjRUSEqLLly+bzgEAODHW7/zD+g0AMMHf319bt27V+PHjFRMT\no2bNmmn79u2mswA4MTfTAQAAAADyV1JSkvz8/LRkyRLNmjVLS5cu5aW3APAb7Ha7fHx8TGe4BIvF\nIqvVqo0bN+rIkSMKCAjQpk2bTGcBAADgP8yaNUsXL16U1Wo1neIyoqOj9dJLLyk0NFRJSUmmcwCg\nUMvOztbp06eZ9dwlXl5eSkhIUExMjMaPH6+uXbvq4sWLprMAAAAAAMBdtmfPHrVp00YDBgxQ586d\ndejQIVmtVrm7u5tOAwDgvxQpUkQDBw7UoUOH1KNHDw0ZMkTNmzfnu4oAAAAAAElSZmamIiIiFBAQ\nIE9PT+3evVuRkZEqWrSo6TQAQCEwf/58ffjhh5o2bZrq1atnOsflNWrUSDNmzNCkSZM0a9Ys0zkA\nAAAogBwOhwYMGKCLFy9qwYIFzIjywZtvvqlnn31WPXv21KlTp0znAAAAAHAhxYoVU48ePbR582bt\n3LlTDRo00CuvvKKaNWsqIiJCdrvddCIAAAAAAHARZ8+eVffu3fXkk09q2LBhpnNcnoeHhxISEnTt\n2jU9//zzcjgcppMAAE6I9Tt/sX4DAEwpUqSIrFarUlJSVKFCBbVq1UqDBg3StWvXTKcBcEJupgMA\nAAAA5I8zZ86oe/fu6tq1qzp06KB9+/YpLCzMdBYAOAW73c4Lwu+yZs2aaceOHXr44YfVrl07RUZG\nKi8vz3QWAABAoZebm6tJkyapf//+8vb2Np3jMiwWi6ZMmaIBAwaoe/fu+uqrr0wnAUChderUKeXm\n5jLruYssFousVqs2btyoffv2qXHjxrxQFwAAAAAAF5Geni6r1apmzZrp5s2b2rJli+Lj41W+fHnT\naQAA/KayZcvKZrMpLS1N5cuXV5s2bRQaGsoh/gAAAABQiK1fv17+/v6aPn26YmJitG7dOtWrV890\nFgCgkDh8+LAGDhyo1157TX379jWdU2j07t1bw4YN0+DBg7Vr1y7TOQAAAChgJkyYoC+++ELz589X\n1apVTecUChaLRZ988onKlSun7t276+bNm6aTAAAAALigpk2bKj4+Xna7XUOHDtWcOXNUq1YtBQcH\na/Xq1abzAAAAAACAE8vOzlZoaKhKlSql+Ph4WSwW00mFQuXKlbVgwQItX75cEydONJ0DAHAyrN9m\nsH4DAEyqXbu2Vq1apZkzZ2rRokVq1KiRVq5caToLgJNxMx0AAAAA4N5yOByKi4uTr6+v9uzZo5Ur\nVyo+Pl7lypUznQYATsNut6t69eqmM1xOuXLllJSUpJiYGI0bN07PPPOMLl26ZDoLAACgUFuwYIGO\nHj2qYcOGmU5xORaLRVOnTlXPnj3VvXt3rV271nQSABRKt17w6uPjY7jE9TRr1kw7duxQo0aN1K5d\nO0VGRiovL890FgAAAAAAuA0Oh0Px8fGqW7euEhISNHXqVG3dulXNmzc3nQYAwB9Wr149rVixQkuW\nLNGuXbtUr149RUZG6saNG6bTAAAAAAD5JCMjQ4MGDVK7du1Up04d7d27V1arVW5uHL0EAMgfP/74\no0JCQuTr68sB1gZER0crMDBQ3bp10w8//GA6BwAAAAXE2rVrNWLECE2YMEGBgYGmcwqV++67T4mJ\nidq/f7/efPNN0zkAAAAAXFjlypUVHh6uI0eO6PPPP1d6erqCgoLUpEkTxcXF6fr166YTAQAAAACA\nkxk6dKj27NmjxMRElS5d2nROodK6dWuNHz9ew4cP18qVK03nAACcCOu3OazfAACTLBaLwsLCtHfv\nXj366KN67LHHFBoaqgsXLphOA+AkOJEEAAAAcGHfffedOnbsqJdffln9+/dXamqqOnXqZDoLAJxK\nVlaWzp07xwvC7xGLxSKr1aqNGzcqLS1N/v7+2rx5s+ksAACAQmvixInq0aOHHnroIdMpLsnNzU0z\nZ87Us88+qy5dumjdunWmkwCg0LHb7SpatKgqVapkOsUllStXTklJSYqJidG4ceP0zDPP6NKlS6az\nAAAAAADAH7Br1y61bt1aL774onr37q2DBw9q4MCBvBQZAOD0goODdeDAAY0bN06TJ09WnTp1FB8f\nbzoLAAAAAHCPLViwQHXr1tWXX36p+fPnKykpSdWqVTOdBQAoZIYMGaLTp09r3rx5Klq0qOmcQsfd\n3V1z586Vu7u7evfurZycHNNJAAAAMOzMmTN67rnnFBwcrNdff910TqFUt25dffrpp5oyZYo+/fRT\n0zkAAAAAXFzRokXVo0cPbdy4UTt37lSzZs30+uuvq2rVqrJarTp+/LjpRAAAAAAA4AQ+//xzffjh\nh/r444/VoEED0zmF0tChQ9WtWzf169dPJ0+eNJ0DAHACrN/msX4DAEyrXLmy4uPj9eWXX2rr1q2q\nW7eu4uLiTGcBcAKcxAwAAAC4oOzsbEVHR8vPz0/p6enasmWLbDabSpYsaToNAJzOiRMn5HA4VKNG\nDdMpLq158+basWOHGjZsqMDAQEVHR8vhcJjOAgAAKFSWL1+u3bt366233jKd4tLc3d0VHx+v4OBg\nPfXUU9qwYYPpJAAoVOx2u6pXr87Ly+8hi8Uiq9WqjRs3Ki0tTf7+/tqyZYvpLAAAAAAA8BsuXbok\nq9Wq5s2bq1ixYtq9e7dsNpu8vLxMpwEAcNcULVpUVqtVBw8e1BNPPKEBAwaoffv2SklJMZ0GAAAA\nALjLTp8+rZCQEPXs2VOPPfaY9u3bpx49epjOAgAUQtOnT9fs2bM1Z84cPfDAA6ZzCq2yZcsqMTFR\nW7Zs0fDhw03nAAAAwKDs7Gz16NFDpUuX1qxZs2SxWEwnFVrPPPOMhg4dqsGDB2vPnj2mcwAAAAAU\nEk2bNlVsbKyOHTumiIgILV68WLVq1VJwcLBWr17NWbgAAAAAAOAXpaWl6aWXXtKwYcMUGhpqOqdQ\n+/jjj1WhQgV1795dWVlZpnMAAAUY63fBwfoNACgIgoODlZaWpr59+2rw4MF68skndfz4cdNZAAow\n3mwFAAAAuJgtW7aocePGGj16tEaPHq2dO3cqICDAdBYAOC273S5J8vHxMVzi+sqXL6+lS5cqJiZG\nI0eO1DPPPKP09HTTWQAAAIVGVFSUnnjiCTVp0sR0istzd3fXZ599po4dOyo4OFg7duwwnQQAhcaJ\nEyeY8+ST5s2ba8eOHfLz81Pbtm0VHR3NgUcAAAAAABRAeXl5io+PV926dbVw4ULNnDlTa9euVcOG\nDU2nAQBwz3h7eys2Nlbbtm3TzZs31aRJE4WFhen8+fOm0wAAAAAAd8jhcCguLk6+vr5KTU3V6tWr\nFR8fr7Jly5pOAwAUQikpKRo6dKjeffddPfHEE6ZzCr2HH35YM2bMUExMjObNm2c6BwAAAIZYrVal\npKQoMTFRpUuXNp1T6EVFRal58+YKDQ1VRkaG6RwAAAAAhUilSpUUHh6uI0eOaN68ebpx44aCgoJU\nr1492Ww2/fjjj6YTAQAAAABAAXH16lWFhobq4Ycf1rhx40znFHr33XefEhMTdfDgQQ0dOtR0DgCg\ngGL9LlhYvwEABYWXl5dsNpvWr1+v77//XvXr11d0dLRyc3NNpwEogNxMBwAAAAC4O65fv66IiAi1\nadNG5cuXV3JyssLDw+Xu7m46DQCcmt1uV4kSJVS+fHnTKYWCxWKR1WrV6tWrtXPnTvn7+2vr1q2m\nswAAAFzetm3btH79ekVERJhOKTQ8PDy0YMECtWnTRp07d9auXbtMJwFAoWC32+Xj42M6o9AoX768\nli1bppiYGI0cOVLPPPOM0tPTTWcBAAAAAIB/2bBhgxo3bqw//elP6tOnjw4ePKiwsDBZLBbTaQAA\n5IuAgABt3LhR8+bN07p161S3bl1FR0fr5s2bptMAAAAAALdh7969at26tV5++WUNGTJEe/fuVYcO\nHUxnAQAKqYyMDIWEhKhly5b6y1/+YjoH/9KnTx9ZrVa98MIL2r17t+kcAAAA5LM5c+Zo+vTpmjlz\npurXr286B5KKFCmi+fPnKzMzU/369VNeXp7pJAAAAACFjIeHh3r06KFVq1Zp165dCgwM1DvvvKOq\nVavKarXq2LFjphMBAAAAAIBBDodD/fv3V0ZGhhYsWCAPDw/TSZBUp04dffrpp5o2bZpmzpxpOgcA\nUMCwfhdMrN8AgILkkUceUUpKikaNGqVRo0apefPm/N4QwH9xMx0AAAAA4M599dVXqlevnuLi4jR1\n6lStXbtWderUMZ0FAC6BF4Sb0bZtW6WkpKh+/fpq06aNoqOj5XA4TGcBAAC4rLFjx6pFixZq27at\n6ZRCpWjRolq4cKFatWqlxx9/XHv37jWdBAAuz263q0aNGqYzChWLxSKr1arVq1dr586d8vf319at\nW01nAQAAAABQqJ05c0ZhYWEKDAxU+fLllZycLJvNplKlSplOAwAg31ksFvXo0UP79++X1WpVZGSk\nGjZsqGXLlplOAwAAAAD8TtnZ2YqOjlZAQICysrK0bds2RUVFydPT03QaAKCQcjgceuGFF3T9+nXN\nmTNH7u7uppPwH2JiYtSmTRuFhITowoULpnMAAACQT1JTUzVw4EC9/fbb6t69u+kc/IdKlSpp4cKF\nWrlypcaPH286BwAAAEAh1qRJE8XGxur48eN655139MUXX+jBBx9UUFCQkpKSOBcXAAAAAIBCaOzY\nsUpKSlJCQoK8vb1N5+A/dO3aVW+99ZaGDBmi3bt3m84BABQgrN8FF+s3AKAg8fDwUHh4uHbt2qWi\nRYuqZcuWioiIUFZWluk0AAWEm+kAAAAAALfv/PnzCgsL01NPPaUWLVro4MGDGjhwoCwWi+k0AHAZ\ndrtdPj4+pjMKpfLly+urr75STEyMRowYoZCQEKWnp5vOAgAAcDkHDhzQsmXL9O6775pOKZSKFSum\nhQsXqmHDhurYsaP2799vOgkAXJrdblf16tVNZxRKbdu2VXJysurXr6927drJZrOZTgIAAAAAoNDJ\nycmRzWaTr6+v1q5dq1mzZmnNmjWqX7++6TQAAIwrWbKkIiMjdfjwYbVo0UJdunRRUFCQ9u3bZzoN\nAAAAAPA/bN68Wf7+/nrvvfc0evRo7dixQ02aNDGdBQAo5CZMmPDTweFVqlQxnYP/x93dXXPnzpWb\nm5t69+6t3Nxc00kAAAC4x9LT0xUSEqIWLVro/fffN52DX9CyZUvFxMRo1KhRWr58uekcAAAAAIVc\nhQoVFB4ermPHjumLL76QJD399NPy9fWVzWbTtWvXDBcCAAAAAID8sGbNGkVGRmry5Mlq06aN6Rz8\ngnHjxqlt27YKCQnRxYsXTecAAAoA1u+Cj/UbAFDQ+Pn5adOmTZoyZYqmTp0qPz8/rV271nQWgALA\nzXQAAAAAgNuzYMECNWjQQGvWrFFiYqISEhJUsWJF01kA4HLsdrt8fHxMZxRaFotFVqtVq1ev1vbt\n29W4cWNt27bNdBYAAIBLGTdunOrWraunnnrKdEqhVaJECS1dulS+vr7q0KGDDh48aDoJAFxSRkaG\nrly5wqzHoAoVKuirr77S6NGjNWzYMD377LPKyMgwnQUAAAAAQKHw7bffqnHjxnr77bfVv39/HThw\nQGFhYaazAAAocKpXr674+Hh98803On/+vBo3biyr1arLly+bTgMAAAAA/IcrV67IarWqTZs28vHx\n0f79+xUeHi53d3fTaQCAQm7Lli0aOXKkxo8fz8HhBVi5cuWUmJiozZs369133zWdAwAAgHsoLy9P\n/fr10/Xr1zVnzhwVKVLEdBJ+xauvvqp+/fqpb9++OnbsmOkcAAAAAJCbm5uCg4O1atUq7dmzR+3a\ntdPw4cNVtWpVDRo0SAcOHDCdCAAAAAAA7hG73a5evXopNDRUr7zyiukc/Ap3d3fNnTtXFotFvXv3\nVm5urukkAIBBrN/OgfUbAFAQubm5aeDAgTp48KD8/PzUsWNHhYWF6dKlS6bTABjkZjoAAAAAwB9z\n7NgxPfbYY+rZs6dCQkJ08OBBPfvss6azAMBl2e12Va9e3XRGoRcYGKjk5GT5+voqMDBQNpvNdBIA\nAIBLOHHihObPn6/hw4fLzY2tQ5NKlCihpKQk1ahRQ0FBQTp69KjpJABwOcePH5ck+fj4GC4p3CwW\ni8LDw7VmzRpt27ZN/v7+2rZtm+ksAAAAAABc1unTpxUWFqb27durZs0vNHXEAAAgAElEQVSaOnDg\ngGw2m+677z7TaQAAFGjt27fXnj179NFHH2nevHmqXbu2bDYbB8gAAAAAQAGwdOlS+fn56bPPPtO0\nadO0fPly1ahRw3QWAAA6d+6cunfvrscff1zDhg0znYPf4O/vr7i4OE2YMEHz5883nQMAAIB7ZMyY\nMVq5cqUWLFigKlWqmM7Bb5g2bZpq1qypkJAQZWZmms4BAAAAgJ/4+/srNjZWp0+f1nvvvaeVK1fK\nz89PQUFBSkpKksPhMJ0IAAAAAADukhs3bqhbt26qUqWKZsyYYToHv6FcuXKaN2+e1q9fr7Fjx5rO\nAQAYwvrtXFi/AQAFlbe3txYvXqz58+drxYoV8vPz08KFC01nATCENzoCAAAATiInJ0c2m02NGjXS\n6dOntXnzZsXGxqpUqVKm0wDApZ04cYIXhBcQFSpU0PLlyzV69GgNGzZMISEhysjIMJ0FAADg1KKj\no1W5cmX17NnTdAoklS5dWitXrlTlypXVvn17ff/996aTAMCl2O12SVL16tUNl0CSAgMDlZKSorp1\n6yowMFA2m810EgAAAAAALiU7O1s2m02+vr7avHmzkpKSlJSUpFq1aplOAwDAabi5uSksLEwHDx7U\nn/70J7399ttq1qyZ1q9fbzoNAAAAAAqlc+fOKSwsTMHBwWrZsqUOHTqkgQMHms4CAECSlJeXp379\n+snDw0OzZs2SxWIxnYTf4bnnntOrr76qAQMGaPfu3aZzAAAAcJetXr1aY8aMkc1m0yOPPGI6B79D\n8eLFtWjRIp04cUKDBg0ynQMAAAAA/8XLy0tWq1VHjhzRF198IUnq2rWr6tSpo+joaKWnpxsuBAAA\nAAAAd+qVV17Rd999p8TERJUsWdJ0Dn6HFi1aaPLkyRo9erSWL19uOgcAYADrt/Nh/QYAFGQ9evTQ\noUOHFBwcrNDQUAUHB+vkyZOmswDkMzfTAQAAAAB+W2pqqlq3bq233npLL7/8snbu3KmWLVuazgIA\nl/fDDz/o+vXrqlGjhukU/IvFYlF4eLhWr16trVu3qnnz5kpOTjadBQAA4JTOnz+vTz75ROHh4fLw\n8DCdg3/x8vLSqlWrVL58eQUFBenUqVOmkwDAZdjtdpUvX54v4hcgFSpU0IoVKzR69GgNGzZMISEh\nysjIMJ0FAAAAAIDTW7NmjR5++GENHz5cQ4cO1d69e9WlSxfTWQAAOK37779fUVFRSk1NVZUqVRQY\nGKjg4GB9//33ptMAAAAAoFBwOByKj49XgwYNtGHDBq1YsUIJCQmqUKGC6TQAAH4ycuRIbdiwQYsW\nLVLZsmVN5+APmDRpklq0aKFu3brpwoULpnMAAABwlxw/fly9e/dWr169NHjwYNM5+ANq1qypWbNm\nac6cOfroo49M5wAAAADAL3Jzc1NwcLBWrVqlAwcO6Mknn9SYMWNUo0YNDRo0SPv27TOdCAAAAAAA\nbsOMGTP0ySef6JNPPtGDDz5oOgd/wJAhQ/T888/rueee09GjR03nAADyEeu382L9BgAUZPfff79i\nY2O1du1aHT58WH5+frLZbMrLyzOdBiCfuJkOAAAAAPDrMjMzFRkZqWbNmqlo0aJKSUlRVFSUihUr\nZjoNAAoFu90uSfLx8TFcgv+vXbt2Sk5OVs2aNdWqVSvZbDbTSQAAAE7HZrOpVKlSeuGFF0yn4P8p\nU6aMVqxYoWLFiql9+/Y6c+aM6SQAcAknTpxgzlMAWSwWhYeHa9WqVdq6dauaN2+u5ORk01kAAAAA\nADilkydPKiwsTJ06dVLt2rW1b98+RUZGytPT03QaAAAuoW7dulq2bJlWrVqlo0ePqn79+oqIiNDV\nq1dNpwEAAACAyzp69Kg6d+6sAQMGqFu3bkpLS9Njjz1mOgsAgJ/56quvFBUVpb/97W9q2rSp6Rz8\nQUWKFNHChQtlsVjUp08f5ebmmk4CAADAHbpx44a6desmb29vxcXFmc7BbejSpYuGDx+uV155RTt2\n7DCdAwAAAAD/U926dWWz2XT69GnFxMRo/fr1atiwoYKCgrRgwQL2HgAAAAAAcBLJycmyWq0aMWKE\nnn32WdM5uA1Tp07VAw88oJCQEF2/ft10DgAgH7B+Oz/WbwBAQRcYGKjk5GT9+c9/1rBhw9SuXTsd\nPHjQdBaAfOBmOgAAAADAL1u/fr0aN26sv/71r5owYYLWr1+vevXqmc4CgELFbrfLYrGoWrVqplPw\nCypWrKjly5crPDxcQ4cOVbdu3XT58mXTWQAAAE7h6tWrmjp1qqxWq4oXL246B7+gQoUK+uabb1Sk\nSBG1b99eZ8+eNZ0EAE7PbrfLx8fHdAZ+Rfv27ZWcnKyaNWuqVatWstlsppMAAAAAAHAamZmZio6O\nlq+vr7Zu3arly5crKSlJNWvWNJ0GAIBL6tSpk5KTkzV+/HhNnz5d9erVU3x8vBwOh+k0AAAAAHAZ\nOTk5stlsatSokc6dO6ctW7YoNjZW9913n+k0AAB+xm636/nnn1evXr300ksvmc7BbSpXrpwWLVqk\nTZs2aeTIkaZzAAAAcIdefvllHT16VImJiSpRooTpHNym0aNHq0OHDurevbsuXLhgOgcAAAAAflPp\n0qU1cOBA7du3TytXrpSnp6d69uypunXrKjo6WpcuXTKdCAAAAAAAfsWlS5cUEhKi1q1b6y9/+Yvp\nHNwmT09PJSYm6uTJkxo0aJDpHADAPcb67RpYvwEAzqB48eKKiorSzp07lZmZqcaNGysyMlI3b940\nnQbgHnIzHQAAAADg5zIyMjRo0CC1a9dODz30kNLS0mS1WuXmxuM7AOS348ePq3LlyipWrJjpFPwK\nd3d3RUZGatWqVdq8ebOaN2+ulJQU01kAAAAF3rRp05Sbm6shQ4aYTsH/ULFiRa1atUo5OTl67LHH\ndPHiRdNJAODU7Ha7fHx8TGfgf6hYsaKWL1+u8PBwDR06VN27d9fly5dNZwEAAAAAUKAlJSWpQYMG\nGjNmjN58802lpaXp8ccfN50FAIDL8/DwkNVq1ZEjR9StWze98MILatGihbZs2WI6DQAAAACcXnJy\nslq1aqWIiAi9+eab2rlzp5o3b246CwCA/5Kdna1evXqpcuXKmjFjhukc3KHGjRsrNjZWUVFRSkhI\nMJ0DAACA2xQbG6tZs2bps88+U+3atU3n4A64ublp9uzZcnd3V69evZSbm2s6CQAAAAB+Fzc3N3Xq\n1ElJSUk6dOiQunfvrqioKNWoUUODBg3S3r17TScCAAAAAID/kJeXp+eee065ubmaN2+e3N3dTSfh\nDtSoUUOff/65Pv/8c8XGxprOAQDcI6zfroX1GwDgLPz9/bVlyxZFRUUpJiZGzZo10/bt201nAbhH\n3EwHAAAAAPi3pKQk+fn56csvv9SsWbOUlJSk6tWrm84CgELrxIkTvCDcSXTo0EHJycny8fFRy5Yt\nZbPZTCcBAAAUWFlZWbLZbBo8eLDKlCljOge/oWrVqlq7dq2uXr2qTp066dKlS6aTAMBp2e12Zj1O\nwN3dXZGRkVq1apU2bdqk5s2bKzU11XQWAAAAAAAFznfffacuXbro6aefVoMGDbR//35FRkaqWLFi\nptMAAChUypUrJ5vNpu3bt8vT01OPPPKIwsLCdPbsWdNpAAAAAOB0MjMzFRERoYCAAHl6emrPnj2K\njIxU0aJFTacBAPCL3njjDaWlpSkhIUElSpQwnYO7oG/fvnr55Zf14osv8iJWAAAAJ7R9+3ZZrVaN\nHDlSTz31lOkc3AVly5ZVYmKiNm/erMjISNM5AAAAAPCHPfTQQ4qKitLx48c1adIkbdiwQQ0bNtSj\njz6qBQsWKCcnx3QiAAAAAACF3qhRo/Ttt99q0aJFKl++vOkc3AVBQUEaMWKEXn31VW3atMl0DgDg\nHmD9dj2s3wAAZ1GkSBFZrValpKSoYsWKatWqlQYNGqRr166ZTgNwl7mZDgAAAAAgnTlzRt26dVPX\nrl3VoUMH7d27V2FhYaazAKDQ4wXhzqVSpUpasWKFwsPDNXToUPXr14+hNgAAwC+YNWuWLl68KKvV\najoFv1P16tX17bffKj09XU8++aSuXLliOgkAnE5OTo7OnDnDrMeJdOjQQTt37lSlSpXUokUL2Ww2\n00kAAAAAABQI169fV2RkpPz8/HTkyBGtXLlSSUlJzD0AADCsSZMmWr9+vZYsWaINGzbowQcfVGRk\npLKyskynAQAAAIBTWLdunfz9/TV9+nRNmjRJ69atk6+vr+ksAAB+1fz58/Xhhx9q2rRpqlevnukc\n3EWTJ09W06ZNFRwcrIsXL5rOAQAAwO906dIl9ezZU23bttXIkSNN5+Au8vf3V2xsrMaOHavExETT\nOQAAAABwW0qXLq2BAwdq7969WrVqlby9vdW7d2/VqVNH0dHR7EkAAAAAAGDI0qVLNX78eE2ZMkUB\nAQGmc3AXjRo1SkFBQerdu7d++OEH0zkAgLuI9dt1sX4DAJxJ7dq1tXLlSs2cOVOLFi1So0aN9PXX\nX5vOAnAXuZkOAAAAAAozh8OhuLg4+fr6KiUlRStXrlR8fLzKlStnOg0AIMlut/OiLCfj7u6uyMhI\nrVy5UqtWrVJAQIDS0tJMZwEAABQYubm5mjRpkvr37y9vb2/TOfgDfHx8tGrVKp04cUJPPPGErl69\najoJAJzKqVOnlJOTw6zHyVStWlXffPONwsPDNXToUIWFhenHH380nQUAAAAAgDFJSUmqX7++bDab\nRo8erZSUFAUFBZnOAgAA/yE4OFj79+/XyJEjNWnSJPn5+WnBggWmswAAAACgwEpPT9egQYPUvn17\n1alTR3v37pXVapWbG8ciAQAKrsOHD2vgwIF67bXX1LdvX9M5uMs8PDw0f/585eTkqHfv3srNzTWd\nBAAAgN+Ql5enPn36yOFwaO7cuXJ3dzedhLusX79+evHFF9W/f38dPHjQdA4AAAAA3DY3Nzd16tRJ\nCQkJOnjwoEJDQxUdHa1q1aopLCxMqampphMBAACA/2PvzuOqqhP/j7+53AuimfuSJi6juaSZirtl\naSqpaCLuec2apNKi1MJyKnLGCbNFzCywGkNLAXEJcUnLLfcNE3PJLDAxc1RMBfFe7v390Td/OW4t\ncj8XeD0fD//wnOPM64/0c/iccz4fACg2Dh48ePFZ5COPPGI6BzeYxWLR7NmzZbPZNHDgQN4HBYAi\ngvG7aGP8BgAUNj4+PrLb7UpPT1eHDh0UHBys/v376/jx46bTANwArHoCAAAAGPLNN9+oU6dOGjly\npB566CHt2rVL9913n+ksAMBvZGZmqkaNGqYz8Cd07txZ27ZtU6VKldSqVSvFxcWZTgIAAPAKSUlJ\nOnTokMaMGWM6BX9CvXr1tGrVKh06dEjdu3fXuXPnTCcBQKGRkZEhSQoMDDRcgj/KarUqKipKn332\nmT777DMFBQVp9+7dprMAAAAAAPCoAwcOKDg4WL1799bdd9+tffv2KTIyUn5+fqbTAADAFQQEBCgy\nMlL79u1T27ZtNWDAAHXu3Jn5bQAAAAD4H0lJSWrQoIFSUlKUmJiolJQU3XrrraazAAC4pnPnzik0\nNFQNGjTQ5MmTTeeggFSpUkWffvqpvvzyS7388sumcwAAAHAd48eP15o1a5ScnKyKFSuazkEBmTZt\nmho0aKD+/fvznT0AAACAIqFu3bqKjo5WRkaGYmJitGPHDjVt2lQdOnRQUlKSnE6n6UQAAAAAAIqs\n3Nxc9e/fX7Vq1VJMTIzpHBSQcuXKaf78+dq0aZNefPFF0zkAgL+I8bt4YPwGABRGVatWVXx8vFJS\nUrRp0ybVr1+f/XOBIsBiOgAAAAAobhwOhyZNmqQmTZooOztbmzZtUkxMjEqVKmU6DQDwG3l5eTp2\n7Jhq1qxpOgV/0q233qpVq1YpMjJSjz/+uOx2O4t4AACAYm/y5Mnq16+f6tWrZzoFf9Jtt92mzz77\nTPv27dMDDzyg8+fPm04CgEIhMzNTfn5+qlKliukU/EmdO3fWtm3bVKFCBbVu3VozZswwnQQAAAAA\nQIE7d+6coqKi1KRJE/30009at26d4uPjmeMAAKCQqF69uuLj47Vp0ybl5OSoefPmCg8P1/Hjx02n\nAQAAAIBRWVlZ6tOnjwYMGKBu3bopPT1dYWFhprMAAPhdRo4cqaysLM2dO1d+fn6mc1CAmjVrptjY\nWP373/9WUlKS6RwAAABcxaeffqpJkybpnXfeUYsWLUznoAD5+/tr3rx5Onr0qB599FHTOQAAAABw\nw5QuXVojRoxQenq61q1bp2rVqmnQoEGqWbOmoqKi9N///td0IgAAAAAARc7jjz+ujIwMzZ8/XwEB\nAaZzUICaNm2q2NhYRUdHKzk52XQOAOAvYPwuPhi/AQCFVc+ePZWenq6hQ4fq8ccfV/fu3ZWRkWE6\nC8CfZDEdAAAAABQnGzZsULNmzfTKK6/olVde0bZt2/hwHAC81OHDh+V2uxUYGGg6BX+B1WpVVFSU\nFi1apCVLligoKEjp6emmswAAAIxYunSpduzYoWeffdZ0Cv6iJk2aaOXKldqxY4d69+6tvLw800kA\n4PUyMzNVo0YNWSy8KlOY3XrrrVq9erWee+45PfbYY7Lb7Tp37pzpLAAAAAAACkRKSooaNmyoqVOn\n6rXXXtPWrVvVvn1701kAAOBPaNWqldavX68PPvhAixYtUv369RUTEyOn02k6DQAAAAA8yuVyKS4u\nTg0aNFB6erpWrlyp+Ph4lS9f3nQaAAC/y3vvvadZs2bp448/Vu3atU3nwAN+XXT14Ycf5ht1AAAA\nL/TNN9/IbrcrPDxcDz/8sOkceEBgYKDmzp2rxMRETZs2zXQOAAAAANxwHTp0UGJiog4cOKChQ4fq\n7bff1q233iq73a60tDTTeQAAAAAAFAlvv/0274MWMw8++KBGjBih4cOHa+/evaZzAAB/AuN38cP4\nDQAorG6++WbFxMRo7dq1ysjIUKNGjTRp0iTl5+ebTgPwB7HDFQAAAOABOTk5GjdunO6++25VrFhR\nu3btUmRkpHx9fU2nAQCuIjMzU9Iviz+g8OvZs6d27typChUqqFWrVnr//fdNJwEAAHhcdHS07r//\nfjVv3tx0Cm6Apk2bauXKldq6dav69OmjvLw800kA4NUOHz7MPE8RYbVaFRUVpUWLFik1NVVBQUFs\nrAAAAAAAKFJ27dqlu+++Ww888IDuuece7d+/XxEREbxvCABAIWexWGS32/Xtt9/qqaeeUmRkpJo0\naaKlS5eaTgMAAAAAj0hPT1f79u01atQoPfHEE9q9e7c6depkOgsAgN9t165dGj16tMaPH6/777/f\ndA48aMqUKWrRooVCQ0OVnZ1tOgcAAAD/59y5cwoNDVX9+vU1ZcoU0znwoM6dOysqKkqjR4/WunXr\nTOcAAAAAQIGoU6eOoqOjdeTIEcXFxSktLU3NmjVTUFCQ4uPj5XA4TCcCAAAAAFAobdq0SWPHjtWE\nCRMUHBxsOgce9Pbbb+uOO+5QaGiozpw5YzoHAPAHMH4XX4zfAIDCrH379kpLS9NLL72kl19+WS1b\nttSOHTtMZwH4AyymAwAAAICibsmSJWrYsKHi4uI0ffp0rVq1SvXq1TOdBQC4joyMDJUsWVIVK1Y0\nnYIbpEaNGlq9erWee+45hYeHy263Kycnx3QWAACAR2zevFlr167VuHHjTKfgBmrWrJmWLFmiL7/8\nUoMHD5bT6TSdBABeKzMzU4GBgaYzcAP17NlTaWlpKl++vFq1aqX333/fdBIAAAAAAH9Jdna2IiIi\nFBQUpJycHK1fv17x8fGqVKmS6TQAAHADlSpVSlFRUUpPT1eTJk3UvXt3hYSE6NtvvzWdBgAAAAAF\nwuFwaNKkSQoKClJeXp42bdqk6OholShRwnQaAAC/W3Z2tkJDQ9WmTRu9/PLLpnPgYTabTQkJCcrN\nzdWAAQOUn59vOgkAAACSnnjiCWVlZSkhIUH+/v6mc+Bh48ePV0hIiPr376+srCzTOQAAAABQYEqU\nKCG73a6vvvpK69atU506dfTII48oMDBQ48aN05EjR0wnAgAAAABQaBw7dkxhYWHq1q2bnn/+edM5\n8DCbzaY5c+boxIkTGjFihOkcAMDvxPhdvDF+AwAKO5vNpsjISG3btk3+/v5q3bq1xo0bp/Pnz5tO\nA/A7WEwHAAAAAEXVsWPHZLfb1aNHD7Vu3Vr79+/XiBEj5OPjYzoNAPA7sEF40WS1WhUVFaWFCxcq\nNTVVQUFB2rNnj+ksAACAAjdx4kS1bt1ad999t+kU3GBt2rTRsmXL9Nlnn2nQoEFyOp2mkwDAKzHX\nUzTVqFFDa9as0XPPPacRI0bIbrcrJyfHdBYAAAAAAH+I2+1WfHy8GjRooNmzZ+v111/Xli1b1KZN\nG9NpAACgANWtW1eJiYlauXKlvv/+ezVs2FARERH6+eefTacBAAAAwA2zfv16NW3aVBMmTNArr7yi\nrVu3qnnz5qazAAD4Q9xutx5++GHl5OTo448/lq+vr+kkGFClShXNmzdPa9as0SuvvGI6BwAAoNib\nMmWKZs+erU8++US1atUynQMDfHx8NHPmTJUtW1b9+vWTw+EwnQQAAAAABa5Dhw5KTExURkaGwsPD\n9f7776tOnTrq37+/NmzYYDoPAAAAAACv5nQ6NWDAAAUEBCg+Pl4WC1s5F0c1atTQ3LlzlZSUpJiY\nGNM5AIDrYPyGxPgNACgaGjdurA0bNuidd97R9OnT1aRJE33xxRemswBcBz+BAAAAAAUgKSlJjRs3\n1ueff64FCxYoMTFRlSpVMp0FAPgDDh8+zAbhRVhISIh27typsmXLqk2bNvrkk09MJwEAABSYvXv3\nKjU1VePHjzedggLSrl07LVmyREuXLtXf//53uVwu00kA4HUyMzOZ6ymirFaroqKitHDhQqWmpqpl\ny5bas2eP6SwAAAAAAH6XHTt2qEOHDho+fLi6du2q/fv3KyIiggUHAAAoRjp37qydO3dq2rRp+uST\nT9SgQQPFxcXx3BcAAABAoXb69GlFRETo7rvvVq1atfT1118rMjJSvr6+ptMAAPjDXnvtNaWkpCgx\nMVG33HKL6RwY1Lp1a8XFxelf//qX5s2bZzoHAACg2Nq4caMiIyM1ceJEdevWzXQODCpdurQSExO1\na9cuPf/886ZzAAAAAMBjqlWrpqioKB05ckQzZszQgQMH1L59ewUFBSkuLk7nz583nQgAAAAAgNeJ\njIzUli1blJiYqLJly5rOgUGdOnXSP//5T40dO1Zr1641nQMAuAbGb/yK8RsAUBT4+PhoxIgR2rdv\nn5o0aaL77rtPdrtdJ0+eNJ0G4CpYHRoAAAC4gQ4dOqSuXbtq4MCBCg0N1b59+/TAAw+YzgIA/Als\nEF70BQYGau3atRo5cqQefPBB2e125eTkmM4CAAC44f7973+rfv366tGjh+kUFKC77rpLCxYsUEJC\ngv7+97+zMSAA/EZ2drZ+/vln5nqKuF69emnnzp0qU6aM2rZtqzlz5phOAgAAAADgqk6dOqWIiAi1\natVKvr6+2rlzp+Lj41WxYkXTaQAAwACr1aoRI0Zo//796tevn0aOHKlWrVpp/fr1ptMAAAAA4A9b\nvHixmjRpotmzZ+vdd9/VkiVLVLNmTdNZAAD8KRs3btSLL76oV199VXfddZfpHHgBu92u8PBwDR8+\nXHv27DGdAwAAUOwcO3ZM/fr1U3BwsCIjI03nwAs0adJEM2bM0JtvvqnExETTOQAAAADgUf7+/rLb\n7UpLS9O2bdvUqFEjjRw5UrVq1dK4ceP0ww8/mE4EAAAAAMArLFy4UG+99ZbeffddNWvWzHQOvMC4\ncePUu3dv9e/fX1lZWaZzAABXwPiN/8X4DQAoKqpVq6b58+crISFBy5cv1+2336558+aZzgJwBRbT\nAQAAAEBR4HQ6FRMTozvuuEM//vijNmzYoNjYWJUuXdp0GgDgT8rMzGSD8GLAarUqOjpaCxYs0OLF\ni9WyZUt9/fXXprMAAABumMOHDyshIUHPP/+8LBYeDRZ1Xbp00YIFC/TJJ58oPDxcbrfbdBIAeIXM\nzExJYq6nGAgMDNTatWv1xBNPaMiQIbLb7crJyTGdBQAAAADARS6XS/Hx8apfv76SkpL04Ycfas2a\nNbrjjjtMpwEAAC9Qvnx5xcTEaPfu3apUqZLuuusu9e/fXxkZGabTAAAAAOC6fvzxR9ntdoWEhKhN\nmzbav3+/RowYYToLAIA/7dixYwoLC1NwcLDGjBljOgdeZOrUqWrWrJlCQ0OVnZ1tOgcAAKDYcDqd\n6t+/v0qWLKn4+Hj5+PiYToKXGDRokEaNGqVHHnlEe/bsMZ0DAAAAAEa0aNFC8fHxyszM1GOPPaYP\nPvhAf/vb39S/f3+tXLnSdB4AAAAAAMbs379fw4YN05NPPqlhw4aZzoGX8PHx0X/+8x+VL19eYWFh\nunDhgukkAMBvMH7jShi/AQBFTb9+/bR//3716tVL/fv3V0hIiH744QfTWQB+gx0fAQAAgL9o165d\nateunZ599lmNGjVK27ZtU+vWrU1nAQD+osOHD7NBeDHSu3dvpaWl6eabb1abNm00d+5c00kAAAB/\niNPpvOLxSZMmqWrVqho4cKCHi2BKcHCw5s6dq48++kjPPPOM6RwA8Aq/bpBao0YNwyXwBKvVqujo\naC1YsECLFy9Whw4ddPDgQdNZAAAAAABo27ZtateunR555BENGjRI+/btk91uZ0MaAABwmQYNGmjp\n0qVatGiRtm/frkaNGikqKkq5ubmm0wAAAADgMm63W/Hx8WrcuLG+/PJLLV++XImJiapYsaLpNAAA\n/jSXy6WhQ4fKZrNp5syZPNPDJWw2mxITE3Xu3DnZ7Xa5XC7TSQAAAMXCs88+q+3bt2v+/PkqU6aM\n6Rx4mTfeeEPNmjVTaGioTp8+bToHAAAAAIy55ZZbFBUVpR9++DjvEToAACAASURBVEGzZ8/W4cOH\n1aVLFwUFBSkuLo530gEAAAAAxcrZs2cVGhqqRo0aafLkyaZz4GVKly6t+fPnKz09XePGjTOdAwD4\nP4zfuBbGbwBAUVO2bFnFxsZq1apVOnDggBo3bqyYmBi+WQS8hMV0AAAAAFBY5ebmKioqSi1btpSf\nn5927dql6Oho+fn5mU4DAPxFx48fV05OjgIDA02nwIMCAwO1evVqDR8+XIMGDZLdbucjNQAAUGis\nXLlSrVu31sKFCy8+jP/pp5/04Ycf6rnnnpPNZjNcCE964IEHNGfOHL3zzjsaM2aM6RwAMC4zM1MV\nK1ZUqVKlTKfAg3r37q2dO3fK399fzZs319y5c00nAQAAAACKqRMnTigiIkKtW7dWQECAdu7cqZiY\nGN18882m0wAAf1J2drZOnTp1yS9JOnfu3GXHnU6n4VoUZiEhIdq7d6/+/e9/66233tJtt92m+Ph4\nud1u02kAAAAAIEn69ttv1aVLFw0fPlx9+/bVV199pa5du5rOghdg/gRAYffiiy9q3bp1Sk5OVvny\n5U3nwAtVrVpV8+bN02effaYJEyZc8Zrt27d7uAoAAKDwW7du3RWfiSckJGjKlCmaPn26GjdubKAM\n3s5msykxMVFnz57VsGHDrvjf0fr165mLAgAAKGScTudlzxfPnTsnSZcdz87ONlwLeBd/f3/169dP\nGzdu1LZt29SoUSONGjVKtWrV0rhx43T48GHTiQAAAAAA3BBOp1Pr16+/7Ljb7dbDDz+sEydOaN68\neewphytq0KCB4uLi9NZbb2nWrFmmcwCg2GD8xl/B+A0AKIo6duyotLQ0PfbYYxozZow6duyoffv2\nmc4Cij2L6QAAAACgMFq7dq2aNWumKVOmaPLkyVq7dq0aNmxoOgsAcINkZGRIkgIDAw2XwNP8/f0V\nExOjBQsWKCUlRe3bt9fBgwdNZwEAAFxXVlaWtm7dqj59+qh+/fqKj4/XW2+9pdKlS+vhhx82nQcD\n+vbtq48//lgxMTF6+eWXLzvvdrv11FNP6euvvzZQBwCedfjwYeZ5iqmaNWtq9erVGj58uAYNGiS7\n3a7c3FzTWQAAAACAYsLpdCouLk7169dXcnKy/vOf/2jVqlVsRAMARUBYWJjKly9/yS9Jevjhhy85\nVrlyZZ08edJwLQo7Pz8/RUREaO/everevbuGDx+ue++9V7t27TKdBgAAAKAYczqdiomJUdOmTXX8\n+HFt3LhRsbGxuummm0ynwUswfwKgMFuyZImio6M1depUtWjRwnQOvFibNm0UGxurCRMmKDk5+ZJz\nb731llq3bq3du3cbqgMAACh8nE6n+vTpox49eig7O/vi8f3792vEiBF6+umnZbfbDRbC21WtWlVJ\nSUlasmSJXn/99YvH3W633nzzTXXs2FGrV682FwgAAIA/7OTJk6pcufIlzxh/XU/rf59HhoWFGa4F\nvFeLFi0UHx+vzMxMjR49WrNnz1bt2rUVEhKilStXms4DAAAAAOAvWb16tTp27Kg333xTbrf74vHJ\nkydrwYIFSkhIUPXq1Q0WwtsNHDhQERERevzxx7Vnzx7TOQBQLDB+469i/AYAFEUBAQGKjo7W9u3b\ndf78eTVr1kxRUVG6cOGC6TSg2LKYDgAAAAAKk+zsbIWHh+uee+5RvXr1tHv3bkVERMhi4dYaAIqS\nzMxM+fj46NZbbzWdAkMeeOABpaWlyc/PTy1atFBCQsJVr83OztayZcs8WAcAAHC5H374QX5+fpKk\nb7/9VsOHD9dbb72lli1bGi6DSf3799f777+vf/3rX/rXv/518bjL5dLw4cP19ttvX7KQHQAUVZmZ\nmQoMDDSdAUP8/f0VExOjBQsWKCUlRR06dNDBgwevev2qVav0448/erAQAAAAAFAUrV27Vi1atNCo\nUaM0ZMgQ7d27l01oAKAIGThw4HWvsVgs6tixoypXruyBIhQH1apVU2xsrDZv3iyn06nmzZvLbrfr\np59+Mp0GAAAAoJhJS0tTmzZtNG7cOI0dO1Zbt25Vq1atTGfByzB/AqCwyszM1LBhwzRw4EA9+uij\npnNQCAwbNkyPPvqohg8frq+//lo5OTkaMmSIxowZI0maO3eu4UIAAIDCY9WqVTpx4oRWrFihO+64\nQ7t27dKZM2fUp08f3X777Zo0aZLpRBQC7dq106uvvqrnn39eK1as0NmzZ9W/f389++yzcrvd11xH\nCgAAAN6ncuXK6tix4+9a+/v3PKMEiruqVasqMjJShw4d0pw5c3Ty5El16dJFzZs3V1xcnHJyckwn\nAgAAAADwhyUkJMjtdmvs2LHq16+fzp49q1WrVmn8+PGaNGmSOnbsaDoRhcDrr7+uFi1aqE+fPjp9\n+rTpHAAo8hi/cSMwfgMAiqqmTZtq48aNio6O1uuvv66goCBt3rzZdBZQLF3/rTUAAAAAkqSUlBQ1\nbtxYn376qWbOnKmUlBTVqFHDdBYAoABkZmaqatWq8vf3N50Cg2rWrKk1a9booYce0sCBAxUeHq68\nvLxLrnG73Ro2bJgGDRrEJuEAAMCorKwsuVwuSb/co7hcLuXl5WnZsmWqXr26oqKidPLkScOVMOGh\nhx7SjBkz9NJLLyk6Olr5+fkaOnSoZs+eLUmaNWuWjhw5YrgSAApWZmamAgMDTWfAsAceeEBpaWmy\nWq1q0aLFFRdtzcrKUlhYmEaMGGGgEAAAAADg7TZt2nTdD+COHj0qu92ue+65R5UqVdKuXbsUExOj\n0qVLe6gSAOAJYWFhstls173Obrd7oAbFTVBQkNatW6e5c+dqzZo1ql+/viZNmnTZ+43/KyMjQ7t2\n7fJQJQAAAICiKDc3V+PGjVNQUJBKliypnTt3KioqSn5+fqbT4IWYPwFQGDkcDg0cOFBVq1bVjBkz\nTOegEJk6daoaN26sXr16qV27dkpKSpLb7VZ+fr5mzpwpt9ttOhEAAKBQmDNnjvz8/OR0OnX06FG1\nbNlS9957r7Kzs5WcnMw8FH630aNHKzQ0VIMGDdKdd96phQsXyuVyyeVyKSEhQRcuXDCdCAAAgD9g\n6NCh173GarUqNDTUAzVA0eDn56d+/fpp/fr12rZtm1q2bKmIiAhVr15dERERysjIMJ0IAAAAAMDv\n4nA4lJiYKJfLJbfbrU8//VSNGzdWWFiY+vTpo2eeecZ0IgoJq9WqxMREnTt3Tna7nXc/AaAAMX7j\nRmH8BgAUZVarVREREfrqq69UpUoVtWvXTuHh4Tp79qzpNKBYsZgOAAAAALxdVlaW+vbtq969e6tT\np05KT09nYTkAKOIOHz7MBuGQJPn7+ysmJkbJyclKTExUu3bt9O233148P3XqVC1evFhnz55lk3AA\nAGDUDz/8IIfDcdnx/Px8ZWdna+LEiapRo4YmTZpkoA6mPfzww5oyZYpeeOEFde3aVQkJCcrPz5ck\n+fj4aMqUKYYLAaBgZWZmqkaNGqYz4AVq1qyptWvX6qGHHtLAgQMVHh5+ceFWp9Opfv366fTp00pJ\nSdEnn3xiuBYAAAAA4E0yMzPVs2dPhYeHy+VyXXbe4XAoJiZGDRo00KpVqzRz5kytXLlSDRs2NFAL\nAChoZcuWVXBwsKxW61Wv8fX1Ve/evT1YheLEx8dH/fr10969exUREaGoqCjdcccdWrx48VX/zNix\nYxUcHKwjR454sBQAAABAUbF69Wo1bdpUsbGxeuONN7R69Wo1aNDAdBa8GPMnAAqjZ555Rrt371Zi\nYqJKlixpOgeFiL+/v8aMGaOjR49q7969l3zjlZWVpU2bNhmsAwAAKBwcDoeSk5Mv+dbL4XBo+/bt\nCgoKUoUKFQwXojD59b2KM2fOKDMzU06n8+K5M2fO6IsvvjBYBwAAgD+qT58+13zuaLVadf/996t8\n+fIerAKKjhYtWig2Nlbff/+9xo0bpwULFqhOnToKCQnRypUr2TgVAAAAAODVVq5cqZ9//vni7x0O\nh44cOaIzZ84oJCREPj4+ButQ2FSpUkXz5s3TsmXLWMsfAAoQ4zduJMZvAEBRV6dOHX322Wf6z3/+\no+TkZDVp0kTLly83nQUUGxbTAQAAAIC3crvdiouLU4MGDbRr1y6tWLFC8fHxfBAOAMVAZmamAgMD\nTWfAi4SGhmrz5s3Kz89X8+bNlZSUpK1bt2rs2LFyuVxyOp1sEg4AAIzKyMi45nm32y2bzabu3bt7\nqAje5rHHHlO7du20Zs0a5efnXzzucDj0zjvv6NSpUwbrAKDgOJ1OHT16VDVr1jSdAi/h7++vmJgY\nJScnKyEhQe3atdOhQ4f00ksvXZz/8fHxUXh4OBviAgAAAAAkSWfPnlX37t11+vRp7d69W++///4l\n51etWqVmzZrp+eef1zPPPKNvvvlGdrvdUC0AwFOGDBlyyXO337JarQoJCVGZMmU8XIXipmTJkoqK\nitKBAwfUunVrhYSEqEuXLtqzZ88l161du1bJyck6fvy4goODdfbsWUPFAAAAAAqbU6dOKTw8XJ06\ndVL9+vW1e/duRUREyGJhySJcH/MnAAqThIQEvfPOO3r33XfVsGFD0zkoZOLi4jRgwACdP39eFy5c\nuOScn5+f5syZY6gMAACg8FixYsUlG/z81tKlS9WqVavrfk8PSFJ+fr5efvllDRgwQE6nUw6H45Lz\nNptNCQkJhuoAAADwZ9x8883q2bOnrFbrFc/n5+frwQcf9HAVUPRUqVJFkZGROnjwoObOnavz58+r\nS5cuatSokWJiYnTu3DnTiQAAAAAAXCYhIUE2m+2SY06nU06nU3a7XU899dRlzwyBa2nbtq0mTZqk\n8ePHa/ny5aZzAKBIYvzGjcb4DQAo6nx8fGS327Vnzx7dddddCg4OVv/+/XX8+HHTaUCRx8oqAAAA\nwBV888036tSpk0aOHKknnnhC6enp6ty5s+ksAICHZGZmKjAw0HQGvMxtt92mjRs3asCAARowYIC6\ndet2yXk2CQcAACZlZWVd9Zyvr68CAgK0cuVKNWnSxINV8BYXLlxQWFiYNm3adMUNFRwOh959910D\nZQBQ8I4cOSKn08lcDy4TGhqqzZs3y+FwqGnTpoqOjr44TrrdbuXl5WnEiBGGKwEAAAAAprlcLg0e\nPFj79++X0+mUy+XSs88+q//+9786cuSI7Ha7OnXqpNq1a2vPnj2KiopSiRIlTGcDADygd+/eCggI\nuOI5NhSAp9WoUUPx8fFatWqVjh8/rmbNmikiIkKnT5+Wy+XSU089JV9fX+Xn52v//v3q27evnE6n\n6WwAAAAAXi4pKUn169dXSkqKkpKSlJKSoltvvdV0FgoR5k8AFBYHDhzQiBEj9NRTT/FvE/6QnJwc\nDRgwQI8//rjy8/Plcrkuu+bChQv6+OOPmZMFAAC4jitt8PMrp9OpPXv2qHnz5lqzZo2Hy1CYHD9+\nXJ07d9bEiRPldruveI/ucDg0b948XbhwwUAhAAAA/qwhQ4Zccd0kSSpRooR69uzp4SKg6PLz81O/\nfv20YsUKbd++XXfffbeef/55Va9eXREREfr+++9NJwIAAAAAIOmX9/OSk5PlcDguO+d2uyVJ06dP\n13333cfm6PhDnn76aT344IMaPHgwcyEAcIMxfqOgMH4DAIqDKlWqKD4+XosXL9bmzZtVv359xcXF\nmc4CijSL6QAAAADAmzgcDk2aNElNmjTR6dOntWnTJkVHR7M5CwAUM5mZmWwQjisKCAhQbGysmjdv\nrrNnz16y8B6bhAMAAFOcTqeys7OveM7X11clSpTQF198oaCgIA+XwRvk5eWpT58+Wrp06VUXNHE6\nnXr99deVm5vr4ToAKHiZmZmSxFwPrqh+/fpKTk5Wfn6+fHx8LjnncDi0ZMkSffzxx4bqAAAAAADe\n4Pnnn1dqauol7wfk5uYqLCxMt912mzZv3qylS5cqJSVFtWvXNlgKAPC0EiVKqE+fPlfciCwgIEDB\nwcEGqlDc3XPPPdq+fbtiYmL0ySef6LbbbtPo0aP11VdfXbyfcTgc+vzzz/XEE08YrgUAAADgrY4c\nOaI+ffpowIABCg4OVnp6uvr27Ws6C4UQ8ycACoNz584pNDRUDRo00OTJk03noJB57rnnlJiYKJfL\ndc3rTp48qS+++MJDVQAAAIVPXl6e5s+ff8UNfn7ldDp18uRJPfPMMzp79qwH61CYTJkyRWvWrLm4\nMdTVnD17Vp999pmHqgAAAHAjdO/eXaVKlbrsuM1mU9++fVWyZEkDVUDR17x5c8XGxur777/X888/\nr4ULF+pvf/ubunTpopSUlOv+/AUAAAAAQEH67LPPrvv82O12a+3atZoyZYqHqlBUTJ8+XdWqVdOA\nAQOUl5dnOgcAigzGbxQkxm8AQHHRo0cP7d69W0OHDtXjjz+u+++/X99//73pLKBIspgOAAAAALzF\nhg0bdOedd2rChAl65ZVXtHXrVrVo0cJ0FgDAw/Ly8nTs2DE2CMdVvfnmm9q5c+cVF5Bhk3AAAGDC\n0aNHr7hosK+vr/z9/fX555+rZcuWBspgmsvlUu/evbVkyZJLNiq+kp9//lkzZ870TBgAeFBGRob8\n/PxUpUoV0ynwQk6nU0OHDpXT6bzi/ZSPj48ee+wxHTlyxEAdAAAAAMC0+Ph4vfbaa5f9zOhwOLR2\n7VoNHz5cu3fvZrNaACjGBg8efNl7ZDabTf3791dAQIChKhR3vr6+evzxx3XgwAH17dtXH3300WXX\n5Ofn6/3331dMTIyBQgAAAADeyuVyKS4uTg0bNlR6ero+//xzxcfHq3z58qbTUIgxfwLA240cOVJZ\nWVmaO3eu/Pz8TOegkHn77bf10UcfqUyZMrJarVe9zmaz8e05AADANSxbtuyaG/zYbDb5+voqMjJS\nGzdu1E033eTBOhQmEydO1OrVqxUYGHjde/S5c+d6sAwAAAB/VYkSJdS3b9/L5vIdDocGDx5sqAoo\nPipXrqzIyEgdOnRICxculCT16tVLDRo0UExMjM6dO2e4EAAAAABQHM2ZM0c2m+2q561Wq2655RYt\nW7ZMEydO9GAZioJSpUpp/vz52r9/v55++mnTOQBQZDB+oyAxfgMAipObb75ZMTExWrdunTIzM3X7\n7bdr0qRJys/PN50GFCkW0wEAAACAaT///LMiIiJ01113KTAwUHv27FFkZKR8fX1NpwEADMjMzJTb\n7VZgYKDpFHihLVu2aNy4cVfcHPxXbBIOAAA8LSsr67JjFotFNptNS5cuVevWrQ1UwRtYLBZNmzZN\ndrtdvr6+11yY3OVy6dVXX+WlDABFTmZmpmrUqCGLhVdkcLnx48dr69atl2029Cu32628vDw9+uij\nHi4DAAAAAJi2fv16/f3vf7/qeV9fX23ZsuWaiwoAAIq+rl27qly5cpccY0MBeIty5copICBAZ8+e\nldvtvuy82+3WM888c3ExfgAAAADF2+7du9WuXTuNGjVKTzzxhNLT03XvvfeazkIRwPwJAG/23nvv\nadasWfr4449Vu3Zt0zkohHx8fGS327V//34NGDBAkq743rrD4dC8efOUm5vr6UQAAIBCISEh4arv\n4lksFt1555366quvFB0dLX9/fw/XobDp2LGjvv76a40ZM0YWi0VWq/WyaxwOh+bPn889OgAAQCEz\nePBgXbhw4ZJjZcqU0X333WeoCCh+fH19FRISohUrVmjHjh2655579MILL6hatWoKDw/Xvn37TCcC\nAAAAAIqJ8+fPa+HChVdcS9RqtcrHx0fDhw/Xvn371K1bNwOFKArq1aun+Ph4xcbG6sMPPzSdAwCF\nHuM3PIHxGwBQ3LRr105paWl66aWX9PLLL6tly5bavn276SygyGCnKwAAABRrqampatKkiWbNmqV3\n331XS5cuVa1atUxnoZDLycnRqVOnLvl14cIFXbhw4bLjOTk5pnOBYu3YsWN6+umnNWXKFCUnJ2vr\n1q1KS0uTJAUGBhqug7c5efKk+vTpo/z8/Gte9+sm4Y899piHygAAQHF35MiRS35vsVhks9m0dOlS\n3X333Yaq4C3q1q2rjz76SAcPHtSwYcPk6+t7xQUR3W63jhw5onnz5hmoBIAbY8mSJfrHP/6h2NhY\nLVmyRHv27NGhQ4eY58EVpaamavLkyded63E4HFq6dKlmz57toTIAAAAAgGnff/+9evXqJZfLddVr\nnE6ntm3bpo8++siDZSiunE7nZe8enjt3TpIuO56dnW24FiherFarBg4cKD8/v4vHypUrp3vvvddg\nFfCLgwcPaurUqXI6nde8bsCAAdqyZYuHqgAAAAB4G4fDoUmTJikoKEgWi0U7d+5kU23cUMyfADBt\n69atOnr06GXHd+3apdGjR2v8+PG6//77DZShKKlSpYpmz56tVatWqVatWrJarZddk5ubqyVLlhio\nAwAA8G7nz5/XokWLLtvgx2azqUSJEvr3v/+tTZs2qVGjRoYKURgFBAQoOjpa27dvV6NGjeTr63vZ\nNefPn9fy5csN1AEAAODP6ty5s8qXL3/x9zabTUOGDLniWkoACl6zZs0UGxurI0eOaMKECVq+fLlu\nv/12denSRSkpKXK73aYTAQAAAABF2NKlS5Wbm3vZcavVqrp162rjxo2Ki4vTTTfdZKAORUmvXr0U\nGRmpkSNHavv27ZedP3v2LN/qA8DvxPgNT2H8BuANWD8SnmSz2RQZGandu3erTJkyatOmjcaNG6fz\n58+bTgMKPR83b8AAAACgGDp27JieffZZzZo1S/369dM777yjSpUqmc5CEREXF6fw8PDfdW1sbKxG\njBhRwEUAriY/P18333yzzp8/L7fbffFDIV9fX1WvXl21atVSnTp1VLNmTTVu3FhhYWGGi2HSvn37\nFBMTo+TkZB0/flx+fn66cOHCNf/M7NmzNWTIEA8VAgCA4mratGkaPXq0HA6HLBaLbDabli5dygL5\nuKKMjAy98cYbeu+99yTpksURLRaLGjRooPT0dPn4+JhKBIA/LTU1VT179pSvr6/y8/MvHi9RooRq\n1qypunXrqnbt2qpRo4a6du2qO++802AtTFuwYIE++OADrVixQg6HQzab7apzPT4+PipdurT27dun\nW265xcOlAAAAAABP+vnnn9WqVSsdOnToss1l/pePj4/KlSunQ4cOqUyZMh4qRHF0/PhxVatWTU6n\n87rX3nfffVqxYoUHqgD8at26dbr77rslSX5+fnrssccUExNjuAqQ7r//fn3++efXvafx9fVVuXLl\ntGPHDtWoUcNDdQAAAAC8wZdffqkRI0YoIyNDL730ksaOHXvFTZGBv4r5EwAm9e/fX1988YWSkpIu\nfmeTnZ2tFi1aqGbNmlqxYgXjH26o3NxcTZo0SRMnTpSki8/4rFarevbsqQULFpjMAwAA8DrJycnq\n16/fxXWffv2+uWvXroqLi1NgYKDJPBQBTqdTb7zxhl566SW53e6L71FYrVaFhoYqISHBcCEAAAD+\niKeeekqxsbEX14ZYt26dOnToYLgKgCS5XC6lpqZq6tSp+vzzz1W3bl098sgjCg8PV9myZU3nAQAA\nAACKmP79+2vhwoUXn//ZbDa5XC6NHTtWEyZMkJ+fn+FCFCUul0vdu3fXvn37tG3bNlWsWFGStH//\nfoWEhKhatWpavXq12UgAKAQYv+FJjN8ATGP9SJjidrs1Y8YMjR07VpUrV1ZsbKw6d+5sOgsorJJ8\n3L9+7QIAAAAUci6XSxaL5ZrXuN1uzZo1S6NHj1bp0qX13nvvqVu3bh4qRHFx8uRJValS5boTZ1ar\nVT/++KMqVKjgoTIAV3LPPfdo7dq1utoUya+bh7/44ouaMGGCh+vgjVwul3bu3KmUlBTNmjVLhw4d\nks1mu2zDFB8fH5UqVUr79u1T9erVDdUCAIDi4IUXXtAbb7whp9Mpq9WqJUuW8BAd15WRkaE33nhD\n7733niRdcj+7fPlyde3a1VQaAPxpJ06cUKVKla46zyP9MtfjcrmUlpamO+64w4N18Fa5ublauXKl\nEhMTtWDBAp07d05Wq/WyOX6bzabOnTtr6dKlhkoBAAAAAAUtPz9fPXr00BdffHHZOwD/y8/PTw6H\nQ263W//4xz/0z3/+00OVKK66deumlStXyuVyXfO6Dz74QA8//LCHqgBIv7xPVr16df3444+SpPXr\n16tdu3aGq1DcLV26VN27d5fVapXb7VZ+fv41r7fZbKpbt642bdqkm2++2UOVAAAAAArC7/nW+vTp\n03rppZc0bdo0BQcHa/r06apZs6aHClEcMX8CwJTc3FxVqFBB58+fl4+Pj/75z39q3LhxCgsL08aN\nG7Vjxw7dcsstpjNRRO3evVuPPPKItm/ffvEZn81m008//cSGpwAAAL/Rr18/LVq0SA6HQzabTTfd\ndJOmTJkiu91uOg1FzMGDB/XII4/oyy+/vHiP7u/vrxMnTqhUqVKG6wAAAPB7bdiwQe3bt5ckVa1a\nVUeOHLnuM3IAnrd//35Nnz5dH3zwgSwWiwYNGqSIiAg1atToun/26NGj+sc//qH33ntPNpvNA7UA\nAAAAgMImJydHFStWVG5uriTJYrEoKChIM2fOVMOGDQ3Xoag6efKkWrRooXr16mnp0qVatGiRhg4d\nqvPnz0uSsrKyVKVKFcOVAOC9GL9hAuM3ANNYPxImZWVladSoUVq4cKEefPBBvfXWW9fdO/33rFUB\nFDNJ/I0AAABAkTFq1CitWLHiqucPHTqkrl27avjw4erbt6+++uordevWzYOFKC7Kly+vrl27ytfX\n96rX+Pr6qmvXrtedzABQ8O66665rftyTn5+vEiVK6KmnnvJgFbyZxWJRixYtFBUVpW+//VZpaWl6\n4YUXLr4Y4OfnJ4vFIrfbrdzcXIWHhxsuBgAARV1WVpYuXLggX19fpaSkqHPnzqaTUAjUrFlTU6dO\n1f79+2W32+Xr6yubzSYfHx9NnDjRdB4A/CkVKlS47qZE59LhwQAAIABJREFUFotFPXv21B133OGh\nKni7gIAAhYSEaNasWTpx4oRSU1M1bNgwlStXTtIvcz2S5HA4tGzZMs2ePdtkLgAAAACgAI0dO1Yr\nV66Uw+G45Piv7wFIUsmSJdW6dWs99thjmjlzptLT0zVhwgQTuShmHnzwweteY7PZFBoa6oEaAL9l\nsVg0dOhQSVK1atXUtm1bw0WA1KZNG61YsUKvvvqqBg4cqPr16198t91qtV6c+/6Vw+HQN998o9DQ\nUDmdThPJAAAAAG6AM2fOKDg4WGfOnLnqNSkpKWrcuLHmzp2r//znP0pNTb3uO1fAX8X8CQBTli1b\npvPnz8vtdsvlcunFF19U06ZNlZKSosTERN1yyy2mE1GENWnSRJs2bdLUqVNVqlQp+fr6yuFwaOHC\nhabTAAAAvEZOTo4WL1588Tn1wIEDdfDgQdntdsNlKIrq1q2r1atXa9q0aRfv0fPy8rRkyRLTaQAA\nAPgD2rZtq1tvvVWSZLfb2YAK8FL169dXTEyMjhw5on/+859asWKFGjdurC5duigpKUn5+flX/bPv\nvfeePvzwQ/Xq1Us5OTkerAYAAAAAFBapqanKzc2VxWJRyZIlNW3aNG3atOnifjFAQShfvrzmzp2r\ntWvXqlevXgoLC1Nubq5cLpd8fHyUnJxsOhEAvBrjN0xg/AZgGutHwqRq1app/vz5WrRokb744gs1\nbtxY8fHxV73+3LlzCg4OVnZ2tgcrAe/n43a73aYjAAAAgL8qPj5ew4YNU40aNbRv3z6VLFny4jmn\n06l33nlH48ePV506dTRjxgy1bt3aYC2Kgzlz5mjIkCG62o9cFotFs2fP1qBBgzxcBuB/LVmyRD16\n9LjqeZvNptGjRys6OtqDVfAUt9ut7777Tt99951OnTp11X+3f68ff/xRmzdv1saNG/Xdd99d/N97\n8sknddddd92IZKDAlC5dWlWqVFGjRo3k7+9vOgeAl8jLy9OePXv0008/XXNTAJg1YcIE7d27V889\n95yaNWtmOucv8/f3V7ly5XT77berfPnypnNuiJMnT2rPnj06deqU8vLyTOdc0fHjxzV//nytXr1a\n+fn5evXVV/W3v/3NdBaKmKL49xve56GHHtLHH398zY1Kt2zZopYtW3qwCp5yI+9fXS6X9u3bpy1b\ntmjjxo06deqUJCkgIEBTpkxRuXLlbkQyUCAsFovKli2r2rVrq3bt2vLx8TGdBAAACokb/fwUKExW\nrlypuLi4i/fPbrdbJUqUUPPmzdW+fXu1aNFCQUFBzJvCmDNnzqhSpUpXfc5gtVrVo0cPNo8shhi/\nvcN3332nyMhI9enTh3eDDeL9p2vLzc3V7t27lZaWpp07d2rbtm1KT0/X+fPn5ePjIx8fH7lcLnXu\n3Fnh4eGmcwEjmF8HAACFmdvtVkhIiFJTUzVq1Ci9/fbbl5z/8ccf9dRTTykpKUn9+vXT9OnTVbFi\nRUO1nsX8iXdg/sQ7MH+C4mbIkCFKSkqSw+G4eMxms6l06dJavHix2rZta7AO11LUxu+TJ0/qgw8+\n0NatW9WkSRO9+OKLppNQiDB+Aygsitr4Dc/YuHGj3nrrLVWoUEGPP/647rjjDtNJNwTj99V5y/oV\nJ06c0IwZM7Rjxw61bt1aY8aMMdaCgsf37QCAG8lb7meKuzlz5mjBggWaNGmSateubTqnWOJ9S/xR\nLpdLX3zxhWJiYpSamqo6dero0Ucf1aOPPnrJffqFCxdUrVo1nThxQlarVc2aNdPy5ctv+Bov/HsO\n/IJ/zwEAgDfg/hx/xhtvvKHNmzerefPmevTRR1WhQgXTSX8Z9+eFw3//+1916dJFu3fvVn5+/sXj\nFotFbdq00fr16w3WAZ7D+I0/g/EbpjB+AzCJ9SPhLbKzsxUZGakZM2aoR48emj59umrUqHHJNU8+\n+aSmTZumHj16KCUlhXsb4BdJPm6+kAIAAEAhl5aWptatW+vChQuyWq16+umnNXnyZEnSrl279Pe/\n/13p6emKjIzUCy+8ID8/P8PFKA5ycnJUoUIFnT9//ornS5QooePHj+umm27ycBmA/3Xq1ClVqFDh\nqovI+Pv7KzMzU5UrV/ZwGQpKfn6+UlNTNWfOHC1ftkynsrNNJwFexWq1qn27duoTGiq73c7m9kAx\ndOrUKcXHx2v+/AXasGG9nE6n6SQUY3Xr3abevUI0fPhw3X777aZz/pA9e/boww8/1OKUFB345hvT\nOYDXua1ePYX06lUo/37Du8XGxmrkyJGXvFT9K6vVqk6dOmn58uUGylBQfr1/XTB/vtZv2MD9K/A/\nypUtq27BwRo8eLC6d+8uX19f00kAAMDL8PwUuDaen8Kb9OvXT4sWLbpkw9JfWSwWJSQkKCwszEAZ\nPO3i+P3JJ1q+fJlOZZ82nQR4FavV9//G776M39dw6tQpzZw5U3PmfKIdO3Ze8dkKUJyVK1dW3box\nvw4AAAqPf/3rX3r55Zflcrnk4+Oj9evXq23btnK73Zo1a5aeeeYZlSlTRu+99566du1qOrfAXTJ/\nsmyZTp1m/gT4LavVV+3btlWfvmHMn6DIysvLU4UKFXTu3LnLzv36c/7EiRMVGRnp6TRcxaXj91Kd\nOv2z6STAq1h9fdW+HeM3AO/C+A1cG+P3Ly6uX7FggTasZ/0KmFWv3m3qVUjXrwAAmHNxPYPkeVq/\nYaOcvG8JXKJcmZvVLfh+DR4yhPct8bscOHBA77zzjj788ENJ0uDBg/Xkk0+qcePGmj17tux2+8U1\nom02m2rVqqXPP//8so3o/ij+PQeujX/PAQCAJ3F/Dlwb9+feafv27erVq5eOHz9+xXVffHx8dPjw\nYVWvXt1AHVDw/v/6z8n/t/4z4zfwW+XKlvllfQrGb6/C+A3AG7B+JLzJ2rVrNWLECP3444965ZVX\n9OSTT8pisWjjxo1q37693G63LBaLXnnlFf3jH/8wnQt4gyQf99V2OgcAAAAKgVOnTqlp06Y6evTo\nxY97LRaL1q1bp08//VSvv/662rZtqxkzZqhBgwaGa1HcDBo0SMnJyZdNnFmtVoWFhWnOnDmGygD8\nrzp16ui777677LjNZtOoUaP05ptvGqhCQfj00081ZvRofXvokO5udae639NGrZs20t8Cq6tcmZtl\nsfgUyP/vqdNndCL7Z9WtyYNbeK8z53KU9dN/lfb1N1rx5ValfL5B+W6Xnn32OT333HMqWbKk6UQA\nBSwnJ0evvfaaXps8WT4+vgrq3FN3duii2o3uVPnK1RRQ6ibTibiK9M1r1Lh1R9MZN4zjQp7OnDqh\nzG/2aM+Wtdq68lNlZXyrkJBeevPNN1S3bl3Tidd08OBBjRk9Wp+mpOhvNW9V7/vaq2OrZrq9Xm1V\nKFdG/n4204m/y5Fjx3VLpYoFdo+M4invgkMnTp3Wnm++05otO7Vo5Xp9m/GDeoWE6I033/T6v98o\nHL766is1bdr0que//PJLtW/f3oNFKCi/3r9OnvyafH0sCuncTl06tNSdjeqpWuWKKl2q4H6O3Xco\nU9UqV9TNN/GzMryTy+XWqdM/69vMI9q862stWb1Ja7ek6W916uiNN99Ur169TCcCAAAvYer5KeBt\njv50QlUqlr/kv3men8IbLVy4UKGhobrSp2ABAQE6ceKEAgICDJTBkz799FONeeZpffvd9+rQpI6C\nW9RVy/o1VLtqeZUrHSCLD+O3KYs371XP1g1NZxRrZ3PzdPTkGe06dFSf7zyo1C375XL76NnnGL9/\n6//Pr0+Wr8WiXsGd1O3eu9SsSSNVq1pFpW8qpaPHjuuWKpVMpwIe53K5dDL7tL79LlObtqcpdcVq\nrdmwmfl1AADg9VauXKlu3brJ5XJJ+uUb1po1ayolJUVPPvmk1qxZoyeeeEITJ07UTTcV/XfCfzt/\n0r7hrerWNFAt61ZV7cplVO4mf+ZPDErdfkg9WtQxnVGsnT3v0NFTZ/VVxn/1+e5MLdmZIZdbeva5\nSOZPUOSkpqaqZ8+e17zGx8dHYWFh+uCDD1S69P9j777jori2AI7/6B0ERYpYEBURe4ldsWAHe40l\nGo1G8uwmaizRWGJP7NHEbuwSQWPvGntFxQJiLyhdkLq8P4goEVADMstyvp/P+3weM3d3z5qdOXfu\n3DnXLIciE+lJk79L2dDE1YaqjvlxLGBKPhN9jcrf0XGJhMfEU8hSzrniw7yMS+RJ+Cv8HoRx0P8Z\nu/yeoEJL8rcQQnFp87etRudv8enceBJBaTsLpcPIdmnz99M8m7/frl+hra1DLXcPqtV3p6RrRQrY\n2mNsoh7XYVHhYcTHxZLfxk7pUMQnkhAfR0RoCEE3r3Hx1BFO7NnOw7uBeHh6Mme2+tevEEIIoZzU\n+ZYzpqONimauBWngbE15B3NsLQwxNdBVOsQ8bZffU5qXs1U6jDxLlZxMeEwCQS9iOH8vjL3+L/j7\n9nOcHIsye+4vMt9SfJDw8HBWrFjBwoULuXPnDu7u7jx+/Bh/f3+Skt4sJK2np4e1tTUHDx7E2dn5\noz8n7fk8meYVHGjoak/5IlbY5TPG1DB31IQT4lNQJScTHh1PUHAkZ+88Z+/VJ5y48Rgnx2LMnvuz\nnM+FEEIIke3eGW8pY02DUvkpX8gcWwsDGW8RH+RpZByGutrkM9as67nU8ZaQGM7fi2DvjRD+Dngh\n4y1qYtGiRQwePJjk5OQ04xZv09XVZfbs2QwaNCiHoxPi00qTv7WgZbVSNKpYnAqOtthZmWFqpK90\niCIXeBoWhYGeLpammlUbS5WcTNjLVwQ9CePsrYfsvhDI8at3ZXxNTUj+FkKoC6kfKdTNq1evmD59\nOlOnTuWzzz5j0aJFdOrUicDAQBITE4GUZ2937txJ8+bNFY5WCMVt1kpO7wwuhBBCCCFELqBSqWjR\nogUHDx4kISEhdbuurm5qMcIZM2bQt29ftKQwgFDAjh078PDweGe7lpYWPj4+7y0eJoTIOb1792bd\nunVp8gmkPPATFBREoUKFFIpMZJeAgAC8Bg5k3/79dGrZkLFevXAqIv9dhchMVHQMv230Zfqv68hn\nacXPv/xC27ZtlQ5LCPGJeHt7M2jwEMLCwmnb/1vcO/fFyETzC/2L3CE5OZlLx/fxx+yxPLkfyLCh\nQ5kwYQKGhoZKh5ZGbGwsEydOZO7cOZQo6sCUYf1wr1NNxqWEyERycjL7jp/l+9nLCLj/kKFDh6nl\n8S1yF5VKhbm5OdHR0Wm26+rqUqdOHQ4dOqRQZCI7eXt7M2TwYMLDQvmu/+f07eyBmUneKIIrxH8V\neP8RkxeuYtPOg7g3bszCRYukUK0QQgiRh8n9UyE+ntw/FeogPj6eAgUKEBUVlWa7np4eXbt2ZdWq\nVQpFJnLC2/m7fd1yjOrsRnE7K6XDEkKtvXwVx4o955i19TiWllb8PG9+ns/f3t7eDBkymPCwMEYP\nHsBXPbtgZmqidFhCqLXAu/eZOHM+G//cibt7YxYulPF1IYQQQqiXe/fuUbFiRSIjI1GpVKnbdXR0\nMDIyomTJkvz2229UrlxZwShzRsr4ydfs23+A9jVL8V3rqjjaaN5i4kJkp5exCaw8dJXZvhextMov\n4ydCo2T07PjbdHR0sLW1ZcuWLdSoUSMHoxOvvZ2/21UtysjmLjhayzNtQmTmZVwiq44HMnfvzX/y\n9wLJ30KIHPVu/i4j+VuI93iTv2/kmfzt7e3N4MFDCA0P53Ov7/D4vC/GJmZKhyUEkPJ8+9kj+1g2\n/Xse3g1Q2/oVQgghlOXt7c2QQf8jLPQFQxoWp2etIrIYuRDvEfQimll7AvC++Aj3Rg1ZuHiJzLcU\nH0SlUvHXX38xb9489u3bl24bXV1djI2N2b17NzVr1vzg935zPg9hWHNXetUrhamhXnaFLoRGCgqO\nYsaOy2w7E4R7o0YsXLxYzudCCCGEyBap/fOQFwxpWJSeNQrLeIsQ7xEUEsOsvYF4X3oi4y0KunXr\nFm5ubjx9+pTMlv7W0tKiWrVqnD59OgejE+LTSsnfgwgLC2FEu1r0dq+MqZG+0mEJodbuPA3jp01H\n2Xr8Gu6NG7FwkYyvKUHytxBCnUj9SKGuLly4QN++fbl9+zavXr0iKSkpdZ+2tjYmJiZcunSJ4sWL\nKxilEIrbrJWcWY9SCCGEEEIINTZhwgQmT56cpjjha9ra2owePZrJkycrEJkQKRISEihQoACRkZFp\ntpuZmfHixQv09eXGpBDqYunSpQwcODDNIKKenh79+vVj4cKFCkYmssOBAwfo2KEDhe2smTPmG2pV\nLqt0SELkKsEhYYyf+xtr/tzDqFGjmDJlClpaWkqHJYTIJsnJyXz//ff89NNPuLXpTrehE7HIX1Dp\nsIRIV1JSIvs2/s6m+ZMoW6YM27f/ScGC6vF7DQ4Opk3r1vhfv8b4/31B384e6OroKB2WELlGYlIS\nv230ZdL8lbiUceXP7dvV5vgWuVODBg04cuTIO5OsDx8+TP369RWKSmSHt/uvPdo0ZdLQvhTMb6l0\nWELkKn9fuMqwqQt48OQ5m7dsoVGjRkqHJIQQQogcJvdPhcgauX8qlNanTx/WrVtHfHx8mu27d++m\nadOmCkUlPrWU/N0eBysTpn/ZjBouRZQOSYhc5Xn4SyatO8AfBy/l2fz99vh6z05tmTxmGDbW+ZUO\nS4hc5cSZ8wwZO4X7j56webOMrwshhBBCPcTGxlK9enX8/f1JSEh4Z7+Ojg4XL16kXLlyCkSXsw4c\nOEDH9u1xsDRkWrda1Chlp3RIQuQqzyNj+HHzadYfv5Fnx0+EZklISCB//vzvFEh9TUdHB5VKRd++\nfZk9ezZmZmY5HKGA1/m7HYUs9JjarjzVnQooHZIQucrzqFim+F5lw6m7kr+FEDkmbf6uIPlbiI/0\nJn8HaWz+fnt+QtMOPeg7chKWBeR5YaGekpIS8V33GyvnTMLV1YXtf6pP/QohhBDKebs/07laYca0\nKIW1mYHSYQmRq5wJCuX77Td5FJnI5q3bZL6l+GDdu3dn06ZN6c6BgZR7fHp6enh7e9OsWbNM3+vt\n83mXWiUY26YS1uaGnyJsITTW6YBgRm86z6PwODmfCyGEECJL0oy3VC3EmOYlsTaVtZqE+Bhn7obx\nvc9tHkUlSf9cIREREYwbN44FCxagra2dZm2rt2lpaREUFETRokVzOEIhstfb+bubWwXGf+6GtYWJ\n0mEJkaucuvGA71bs52FoNJu3bJX8rQDJ30IIdSL1I4W6un79OhUqVCAxMfGdfXp6epQsWZKzZ89i\nbGysQHRCqIXNWsn/XvlKCCGEEEKIXGDHjh14enq+s5Dr2/T09Lhy5QqlS5fOwciESKt///6sXLky\ndeBMT0+P3r178+uvvyocmRDibX5+fpQvXz7NNh0dHQIDA+UmWy63bNkyvLy8aNukHkt+HIGhgUzu\nFOK/Wrt9L99MmIOHpwdr1qzFyMhI6ZCEEFn06tUruvfoga+PL19NnE/91p8rHZIQH+RR0C1menVE\nlyT+2rkDV1dXReO5du0arVq2RIcktiz8EWdHWXxTiP/qZtB9OniNIwkdduzcqfjxLXKv8ePHM336\n9NRxWR0dHSpXrsyZM2cUjkxkxatXr+jRozu+Pr4smDiM7q2bKB2SELlWbFw8A8bNwnvvURYuXEi/\nfv2UDkkIIYQQOUTunwqRfeT+qVDK/v37cXd3T7MtX758PH/+HF1dXYWiEp/SsmXL8Bo4EM9aZVjg\n5YmBnvx3FuK/Wn/oEkOX7MDDw5M1a/NO/k4ZX++Br68Pi2dMokenNkqHJESuFRsXR79h37Ntx14Z\nXxdCCCGEWujduzdr165Nt7gWgK6uLhUrVuT06dNoa2vncHQ5J3X8pJoT8/q4YaCno3RIQuRaG47f\nZNiqI3h4eLBm7bo8M34iNM+ePXsyXABSV1cXW1tbVq1aRcOGDXM4MvHa6/ztUbEQP3erIvlbiCzY\nePouIzZcwMPTU/K3EOKTepO/HSR/C5FFKfn7vMbl79T6Fb6+DJuygCbtuysdkhAf5H7gTcb164BO\nchI71aB+hRBCCOW8evWKHt0/x9fHh5kdytKpmoPSIQmRa8Ulqhi60Y8dV56ycNEimW8p3is4OBgH\nBwcSEhIybaetrY22tjZr1qyhS5cu6bZJOZ93x9fHh9ndq9O5ptOnCFmIPCEuIYnBq0/ie+G+nM+F\nEEII8Z+kGW9pX4ZOVeyVDkmIXCsuUcXQzdfY4Rcs/XMFnThxgi+++IKgoCCSkpLe2a+np8dPP/3E\nsGHDFIhOiOyROr7m68Pcr5rT1a38+18khEhXXEIi3yzaic+pG5K/FST5WwihDqR+pFBHKpWK2rVr\nc+7cuUzrVXTq1Il169blcHRCqI3NmlupRQghhBBCaKy7d+/SvXt3tLS03tu2b9++JCcn50BUQqSv\na9euqQsOAyQkJNCtWzcFIxJCpMfV1RUTE5PUv/X09Pjiiy8oWrSoglGJrFq/fj39+/fn235dWTF9\ntCxkKEQWdW/dhJ2/z+TQgf306NEdlUqldEhCiCxQqVR079GDfQcOMvb3HdRv/bnSIQnxwQo5luLH\nPw5hUsCeRo3defDggWKxPHjwAPfGjbEvYM6RP+bj7FhEsViE0ATOjkU48sd87AuY4964saLHt8jd\natasmWZcNikpiSlTpigYkcgqlUpFjx7dOXRgPzt/n0n31k2UDkmIXM3QQJ8V00fzbb+u9O/fn/Xr\n1ysdkhBCCCFygNw/FSJ7yf1ToZSGDRtSoECB1L/19PTo3r27PMiroV7n72Ht67B0cFsM9OS/sxBZ\n0bVBRbwn9ODg/j306J438nfK+HoPDh08wO6NK+jRqY3SIQmRqxkaGLB6wUxGDfpKxteFEEIIobgl\nS5awatWqDAtrASQmJnLhwgWWLFmSg5HlrNfjJ0NbVWLJV41kIXohsqhLHWe2jfTg4L499Oj+eZ4Y\nPxGaacuWLejp6aXZpqOjg5aWFr1798bf35+GDRsqFJ14nb8Hu5diUc/PJH8LkUWdqxdj8zf1OLh3\nt+RvIcQn8yZ/O0v+FiIbaGL+fl2/Yv+BQ8xcs5Mm7bsrHZIQH6yIkzPztx7BvKA9jRWuXyGEEEI5\nKpWKHt0/5+DeXWzq/xmdqjkoHZIQuZqBrjYLu1VgUENHmW8pPsiSJUs+aB0BlUpFYmIi3bp1Y86c\nOenuf30+3zKkMZ1rOn2KcIXIMwz0dFjcpw5DmrnK+VwIIYQQHy3NeEu/KnSqYq90SELkaga62izs\nUo5BDYpK/1xBtWvXxs/Pj7Fjx6Krq/tOrZfExETWrFmjUHRCZF1K/u7OwX178B7Xja5u5ZUOSYhc\nzUBPl6WDWjOsbU3J3wqS/C2EUAdSP1Koo8WLF3PmzJn31qtYv349v/76aw5GJoR60Ur+kBktQggh\nhBBCqImYmBiqVavG7du3SUhI+KDX/Pbbb3z55ZefODIh0qdSqbC3t+fZs2cAWFtb8/TpU7S1tRWO\nTAjxbw0bNuTw4cMkJyejra3NjRs3KFmypNJhif/o3Llz1K9Xj36dPZg2sr/S4QihUf6+cJWWX45k\n+IgRTJkyRelwhBD/0ZgxY5g5cxbfL9uO62f1lA5HiP/kVfRLJnRvhLmRHieOH8PU1DRHPz8mJga3\n+vWJCnvBoXW/YGGWs58vhCaLio6hUfch6BqZcuz48Rw/vkXuFx4ejpWVFcnJyejo6FChQgXOnz+v\ndFgiC8aMGcOsmTPxWTad+p9VVDocITTKqBmLWbrRl4MHD1GzZk2lwxFCCCHEJyL3T4X4dOT+qVDC\nkCFDWLx4MfHx8QCcOHGCWrVqKRyVyG4p+bsuvZtU5sdeTZQORwiNcsr/Pm0nrmH4iJEan7/HjBnD\nrFkz2fnHb7jVrq50OEJolG8nTmfJqg0cPHhQxteFEEIIkeNOnz5N3bp1P/g5axMTE27cuIGDg2Yt\nWPh6/OQLt9JM6izjY0Jkp1O3ntB+pi/DR36r8eMnQvMkJSVhbW1NWFhY6jYdHR0cHBxYtWoV9evX\nVzA68Tp/96pVlB/ayOIAQmSn04Ev6LjwmORvIUS2S5u/KygdjhAaJSV/H9WI/D1mzBhmzprF9JU+\nVKwp110id4qJjmJIx0aYGuhyXIH6FUIIIZSVUs9gBuv7VaN2ifxKhyOERvnBx59Vpx5y8NBhmW8p\n0pWQkECRIkUIDg5GT08PlUpFYmIiH7KU1rhx45g0aVLq36/P5xsHNaKOs+2nDFuIPGfC5nOsOBYg\n53MhhBBCfLDU8ZYvK1PbyUrpcITQKD/suMmq04+lf64wPz8/evXqxeXLl1GpVGn2BQQE4OTkpFBk\nQvx3r/P3lu+7UrdsUaXDEUKjjF21n+X7LnHwkNR/VpLkbyGEkqR+pFAnDx8+pHTp0kRHR39Qez09\nPY4dO0b16lLHTuQ5m7WVjkAIIYQQQoiP0a9fP27fvp1hgUIdHR10dHQAsLCwwMPDA21t6fYK5Whr\na9O9e3f09fXR19enZ8+e8psUQk3VrVsXPT099PT06NatGyVLllQ6JPEfhYSE0KplS9xqVGLK8K+U\nDkcIjVOrclnm/zCUadOmsW3bNqXDEUL8B9u2beOnn36i/6QFuH5WT+lwhPjPjExMGblgE/cfPqLf\nVznf7+vb90vuBgXivXgKFmZSyEuI7GRmYszmBZN49PA+X33VT+lwRC6UL18+ihcvDqQs6DBx4kSF\nIxJZ8br/unDScOp/VlHpcITQOFNHDKBhzSq0bdOGkJAQpcMRQgghxCcg90+F+LTk/qlQQteuXVMf\n5LW3t5fiDhooJX+3oF7ZYkzs6a50OEJonBouRZjTv6XG5+/X4+tLZv6IW215gF6I7PbTuJE0qleL\ntm1lfF0IIYQQOSs4OJg2bdpkuuCVnp4eWlpaaGlp4ejoSLdu3Xjy5EkORvnphYSE0KpFc+q52PND\nJxkfEyK71Shlx+xe9TV+/ERopiNHjhAWFgaArq5BLdktAAAgAElEQVQu2traeHl5cf36derXr69w\ndHnb6/xdt2QBxrcup3Q4aq/LomM4DvdWOgyRi1R3KsDMzpUkfwshslXa/F1e6XDUXpdFR3EcLudg\n8eFS8nflXJ+/X89PGD51IRVrauZ116gvPGlZ1lrpMMQnZmxixqSlm7n/SJn6FUIIIZTzuj8zq0NZ\napfIr3Q4aq/r0jM4jd6tdBgiFxnvUZp6JfPTtrWnzLcU6Xr58iVTpkxhxowZjBgxgn79+tGlSxca\nN25MpUqVKFq0KPny5Utdd+BtP/74IwMGDCApKSn1fD6new3qONsq8E1yl87z9lNs0B9KhyFykQkd\nqlC/tK2cz4UQQgjxQVLHW9qXobaTldLhCKFxxrcsRb0SVtI/V1i5cuU4d+4cixcvxsjICF1dXSDl\nmZ4tW7YoHJ0QH+91/v65fwvqli2qdDhCaJxJPRvhVr4Ybdu0lvytIMnfQgglSf1IoU6ePHlCt27d\nKFGiRGpdCkNDwwzbq1Qq2rRpQ3BwcA5GKYR60ErOrLqLEEIIIYQQamT+/PkMHjw4TYFCfX19EhMT\nUalUFChQADc3N+rUqUOdOnWoXLkyWlpaCkYsRIrz589TtWrV1P9fuXJlhSMSQqRn165dtGjRAm1t\nba5fv46zs7PSIYn/yMvLi21bNnHJdwXmpsZKh5OjqrT+Ev+Au/Tt7MG88UOUDkcR8QmJDBw/iz98\n9jF1RH+G9O6ULW3fNnf5Rr6fvTTD/ZFX9qKbzoOCmmbA2JkcPncN/xs3MDbOW8eaELlZTEwMzqVd\nKFm1Pl9PXqx0OB9keOtqPAjwx71zX/qN/1npcHLc46DbrP/lB66ePkJCfBzW9kWo2bQdnn2GYGhs\nkqZt4NXzeC+bze0rZ4kKCyG/bSGqu7em/YBRGJmYZvo5Pst/Zu3ssRnuX38lHB0d3Wz5Ttnt4tE9\nTPu6PYcOHcLNzS1HPvPw4cM0aNAA78VTaVovby2al9f7nLeCHvDDL8s5fPoicfHxFLW3oV3T+gzp\n0xlTY6PUdlntM0qfM8Weo6dp+/WYHD2+hebo06cPK1aswNXVFT8/P7lfkEvFxMTgUro0blVdWTJ5\npNLh5DjJux+WdwEuXrvFxPkrOHXpGnFx8ZQsVhivHu3o1a75ez9H8i5Evoyhokdv2nXoxMKFC5UO\nRwghhBDZTO6f5t0+9fmrN5m57A/OXvEnJCwCB9uCtHavy6gB3TEzSftb+Jj+979JnzqF3D8VOa1Y\nsWLcu3ePUaNGMW3aNKXDEdnMy8uLbRvXcfqXgZgZGygdTo6qNXgRNx4E07tpVWb3b6V0OIp6+SqO\nusOWcO9ZGCd+HohLkYKp++b/eYIJq/dl+NrgzePR1dHOcH9WX68p/rdwO8duBuN/85bG5e+YmBhc\nXErToGY1ls2donQ4Oa5iAw+u3wzgq55dWPDTBKXDUVTUy2iqNG7D3fsPuXjQB9fSJdPsv+h3nR9m\n/MLfZy8S8+oVRQrZ07aFO6OHfI2ZqUkG75pi9qLfGT15Vob7Y+5fRVdXs68FIqNeUq5eS9q27yDj\n60IIIYTIEUlJSTRp0oRjx46RkJAAgJaWFvr6+sTFxaGtrY2TkxMNGjSgcePGuLm5YW2tmQsUe3l5\nsW3DGk5O6YyZkb7S4eSoOt9v4MajUL5o4MqsXpq5uPb7xCeqGLL8EJv+vsnEzrXwal4x3XZ3nkUw\necspTtx4RNSreAoXMKdrndIMalkJ7Q+YU5jV12uCQb8f4nhQpEaOnwjN5eXlxaJFi9DR0aFUqVKs\nXr06tdaDUJaXlxdb16/mxJjGmBnqKR1Otlh66Dbjtl16Z7uejjb2lkY0cLFlSBMX7PJlft89PV0W\nHeN04AuCZrfNjlBzvYDgKKb5XuX4rWBiE5IonN8Ez0oOeDVyxsQg82feFh64yaQ/r2S4/9EvHdDV\n1pzcPuSPc5x4EIf/zduSv4UQWfYmf7trUP6+9QH5u8x/zN9H/8nf7bIj1FwvJX/7pZO/S39g/r6c\n4f5Hv3TUwPwdmyvzd0xMDKVLu+Baw42R05coGsvW5QtYNPnbd7br6uljbVeIanUb87nXdxSwtf/o\n9x71hSd+506y8+rz7Ag113tw5xbLZ/3AxZOHiY+Lw8ahKPVbtKPzV0MwMs68rsXGpXNZ+tP3Ge7f\neztS8boWpw/vYUyftvJ8uxBC5BExMTG4OJeklr0uczuXUzqcbLPsaBDjt19/Z7uejjb2+Qxxc7Zm\nSOMS2FpkvIhTRrouPcOZoFACpzXLjlBzvcDgaKbtusHx2yHEJaoobGWERwU7BroVf++1z6JDd/hx\nh3+G+x/MbKEx1z5RsYnUnXmc9t16snDhIqXDEblYVFQUYWFh7/yvXLlydGjXltpFjfmlp+Ysmvjr\nAX/GbTr7znZ9XW3s8pnQwNWeoS3KYZfv48cTOs/bz+mAYO7O65YdoeZ6Ac8imfrnRY7feEJsQhJF\nCpjiWaUoXk3Kvn8sa+81Jm49n+H+x4t7aND5PIFaP/jSvmsPOZ8LIYQQIkOp4y12OsztWEbpcHKc\n2+wT3Hz2kp41CjO9Xd77/pceRDDvUBAX74cTEp1AoXyGtChrw9DGxTH9V9/a71Ek0/cEcPZuGK8S\nknDIZ0SLcjYMafRu239bdCSIH3feynD/g5+aaEw/PCNRsYnUnXOS9t16Sf9cDQQFBdG3b18OHTpE\ncnIy5cqV48qVjOctCqFuUvJ3KeqWsmb+1y2VDifH1Rq2lBsPntO7SWVm93t/HWNN9vJVPHVHLONe\ncDgnZn+FS5G0zyYGPA7hx/WHOeZ3l9iERIpY56NNTRf+17oGJoaZP+M33+cUE9YcyHB/8IbRGl/r\nJupVHNWHLKNdl26Sv9WA5G8hhBKkfqRQR5GRkZw5c4b9+/dz8OBBLl26REJCAvr6+iQmJqJSqQDQ\n09OjRo0aHDx4EF1d9VzDTohPYLP82oUQQggBQGhoKNeuXSMsLIy4uDilwxHiHTdv3mTChAkkJycD\nKcUJ7ezsKF++PKVLl8bFxQVLS8vU9nfu3OHOnTsf/TkGBgZYWlri6uqKlZVVtsWvJDm+1UPBgikL\nMAQGBhIYGKhwNHmTHN/ifaKjowGoXr06V65ckRtrGTAzM8PGxoYyZcpgYKB+Cw1du3aNpUuXsnjS\n8Dy3kOHxc1fwD7hLEXsbNu44wNQR/d+7KJ+mCY+MosugCcQnJGZr23+LiHoJwJNT27Ewy7wAiSb7\ncVg/yrfoxYwZM/jhhx+UDkcI8YGmT59OaGgYXQbnjoWu/M+d4EGAP9b2RTi+YwM9RkzB0DjzhaY0\nycPAG4zuXJ/iZSowafVeCtgX4eLRPSwaO4DAaxcYvXhralv/cyeY3M+Tao1aMXntfkwtrLh0fB+L\nvh+A//m/mbx2P1raGU9gjI6KAGDFqUeYmFl88u+WnSrVa0pVt+YM9PqGK5cvffIb/klJSQweNIgW\nDWrRtF71T/pZ6iav9zn9A+9Rr/NAKpYpyf7Vcylsb8Oeo2foP3YG56/dwnvx1NS2We0zSp8zRdN6\n1WnuVpNvvLy4dPmyRk/oSU5OJigoiKCgIMLCwlLHwsV/p6+fMvm/WbNmbNmyReFo1JO2tjb58uXD\n0dERR0dHtNRwcZrp06cTFhrKD4P7KB1KjpO8++F512f/cboN/YE27vU4sWkxttb5+X3TDrwmzCYs\nIoohvTtl+lmSd8Hc1JhJQ77k63Gz+Oqrr6hQoYLSIQkhhBAim8j907zbpz5+7goe/b7Fo1FtDq6d\nh6WFOfuOn6H/9zM4cd6Pg2vnof1P0ZqP6X+nR/rUKeT+6X8j85/+uypVqnDv3j3y58/P5s2blQ4n\nV8kV859+/ZV5Xp6YGatffJ/S39fvceNBMIWt87H5qB+TejV5b6EXTTZmxR7uPQtLd19EdCwAQWtG\nYWHy8YswZPX1mmJ898ZU+2aBRubvlPH1MCaNGqJ0KDnu2KlzXL8ZQBEHe9Zv8+WncSMxNclb10Nv\nGzFhGnfvP0x33/nLV6nn2ZU2zd05u3cb+a0sOXryLH2HjOboqbMc9VmPdiZzTSIiowAIvnGGfOZm\nnyR+dWduZsrk0UP5avhYGV8XQggNIPN3RG6wdu1aDh48mPq3np4eJUuWxNXVFRcXF0qWLJlmvOPw\n4cP/6XNyy/jJL33cMDPKW2MHJ28+5sajUArnN2PLyVtM7FwLE0M9pcPKUeHRcfSav5uExKRM2wVH\nxNB88jbKFSnA3vEdsLM04cCV+wxYup9HoS+Z2bPeJ329phjfsQafjd6gtuMnkr/FvyUnJ7N27Vq0\ntbVp164dbdu2Tf2NaLrckr/ndquCmQbmrt++rIlHRYfUv0NfxnEy8AVjNl/kr8uP2P+dOzbmeXc8\nPqtuPY2k6cwDlC+cj+1D3HCwMuHAtScMWnuWy/fDWDegTqavj4hJSHmfGW2wMNK839+/jfUoR83J\ne9U2fwshcg/Nz9+10snfz9/K300kf2dBSv7eT/nClmwf0uCt/H3mn/xdN9PXR8TEp7zPjLZ5KH/v\nyZX5e/r06YSGhdFn+A9Kh5JqwsJ11GveNvXviLAQrpw5zvwfhnF8rw9LfE+Sv6CtghHmbvdu+zOw\nbT1KulZk7sb92BQqzJlDe5jxbX9uXTnP1OXemb7+ZWRKXYvtl55gaq6edS2quzWlZsPmeHl9w+Uc\nqF8hhBBCWdOnTyc05AWjvtTMez/LelWmVXm71L9Do+M5dSeU77ddY5ffU/YOq4uNufqNKecWt569\npPnPxynnYMGf39TEwdKIA/7BDNlwhcsPIljbt1qmr498lTJ2eXNyE8w1/NrHzFCXMc1KMGzJr3z1\nVX+Zbyn+MzMzM8zMzChSpEia7RMmTCA05AVjBnkqFNmn9Xv/+nhULpr6d+jLOE7efsboDWf46+J9\nDoxthY1F3nl+NrvdfBJB02k7KV/ECp+RzXCwMmH/1UcMWnmCS3dD+ON/jTJ9/euxrNtzu2BhrNlz\nmcwM9RjbugJDfpXzuRBCCCEyljre8kUtpUPJcafuhHHz2UscLI3YdvEJ41s5Y6Kvo3RYOebUnTA6\n/3aO5q4F8fGqTj4jPQ7dfMGQTVc5HRSGj9dnaP9T8/Tyw0g8Fp6iRVkb9g2phZWJHifvhDF4ox8n\n74Ti61U9tW16Il+lrC9yc2IjzI3y5r0cM0NdxjR1Uuvxlri4OK5du0ZwcDBRUVFKh/PJ9e/fHxcX\nF5YvX46fnx/z5s3Dzs7u/S8UGi+31H8ODQ1hbJcOSoeS4/6+fp8bD55T2NqCzceuMqlHo7xd62bl\nPu4Fh6e77+bDFzQatZwKxW3ZOaknha0t2HcxAK+Fvly884SNoztn+t6ptW5WDs+ztW7MjAwY17Ue\ngyR/qw3J3yIjuSF/f6y8dnyrK6kfqTw5vjNWpUoVqlSpQlxcHLdv38bf35/r169z69YtEhISSExM\n5NixY7Rv357u3btn4zcQInt8quM7b44+CiGEEAJIedB6+fLl7PDZzq2AQKXDEeKjJCcn8/jxYx4/\nfszu3bs/yWeUKuGER+s29O7dG1dX10/yGZ/K6+Pbd7s3twM1vzBVbtKpU+YLjoqcUdLJEc827XL1\n8e3t40tQwG2lw9FIJ0+e5OTJk0qHofZ0dHSpUas2Hdu3pWfPnlhaWiodEgBjRo+mYpmSdPN0VzqU\nHLdsow9mJsbMHOVF50Hj2bTzAH06tlI6rHS9io1j+/7jrN62i9nf/w8Xp6Lvf9F7hEdG0fDzQbRr\nWp8mdT/Drdv/sqVtuq+PigbAJA8tFpkea6t8fPtVN6bMnMHgwYPV5jwghMhYWFgYM2fNov3XY7C0\nzh3FqfZuXIaRiSlfjJrOzEFdOb5zI4079lE6rHTFx77i9H4fDm1bTZ/vZ+PgVDrL77luznhUSYmM\n+GU9Zpb5AajVvD0BfufYsWo+/udO4FK1NgB//DwBc8sCfDNtGbp6KZNEazZrR8DV8/iu+IU71y/i\nVLZKhp8VE5UysdLQ2CTLcSuhx7c/MdyzKhs2bPjkN/zXr1+Pv78/a32Wf9LPUUd5vc85bs4yEpOS\n2PDLRPJbphSX69DcjXN+/sxbtYXj565Qp2p5IOt9RulzvjH926+p4tknR47vnJaUlMTOnTtZv349\nu/fsITws/QVdRdbMnj1b6RByhXyWljRr2pRu3brRokULdHSUf2g0LCyMWbNm8v3XPbC1zq90ODlO\n8u6H592xc5ZiZ12A338ajYF+SpGzQb06cCPwLpMXrKRXu+ZYWmS8CK3k3RSfe7qzdIMP48eNY7uP\nj9LhCCGEECKbyP3TvNunnvDz7xSwzMdv00ajr5fy2Ej7Zm6cv3qTn1ds4uL1W1Qp6wx8XP87PdKn\nTiH3Tz+czH/KXiNHjlQ6hFxLfec/jaKCkz2d62d87tVUy3efxdTIgKl9mtFj+ga2HPWjV5OM73Eq\nKTY+Ad9T/qw7cJHpfVvgXNg6W99/7/lbrN1/AY+aZfA9ef2d/a8L3PzXAkJZfb2msLYwYXj7Okyf\noVn5O2V8fRbjhg3EziZ7f5u5wa+r1mNmasKcSWPo0OcbNnjvoG939ZzD/yo2lj//2sfKDdv4efJY\nXEo5Zev7/7X/CCvWb6VtyyZ479z7zv5x0+aiq6PLsrlTMTZKKZbV0t2NIQN6M27aXE6cuUDdGlUz\nfP/wyEgATI2NszXu3KZ7x9YsWbWe8ePHsX27jK8LIURukzp/548/2LN7F2ERkUqHJMRHSUhI4Pr1\n61y//u61Y3bQ1dGhdq0atG3fUe3GT8o7FqRTLWelQ8lxyw9ew9RQjymf16HnvF1sPXWbnm5llA4r\nXbHxiew4f4d1R/35qUc9nO2z/vsJj46jxZRttK7mRKPyRWn249YM287yOUd0XAJLv3bHyjTlmqd5\nZUeGe1Tlxy0n+cq9HCXtMo4pq6/XFAXMjRjWqiIzZkxXm/ETyd/iQ23evDlPFkRV6/xdxIqO1bJ+\nPzw3sDI1oGWFQiQnJ/Pl7ydZfjSA0a3KKh1WjohNSGLn5Uf8cTKIaR0rUcrWPMvv+eN2PxJVKlb0\nrYWVacrC1K0rF+bCvVCWHLzFyYDn1CyR8Xh45KuUBThNDPJG2c0CZgYMaVKKmWqUv4UQudOb/F1M\n6VByREr+diA5Gb78/W+WH73N6FbllA4rR6Tk74f/5O/K2ZS/r2SQv0M+MH8nAHktfzvnuvz9un5F\nj0Hfk7+g+tavsLDMT92mrUlOTmbiwG5sX/MrfYZPUDqsHBEX+4rje7aza9Nq/vfDbIqWdMnyey6b\nMY6kxEQmLtmAxT81MNxadcD/8jm2/D6PK2eOU/6zOhm+Pjoypa6FkYl617X4eux0+jStopHPtwsh\nhHgjLCyMWTNnMLyREzbmBkqHkyOsTPRpUc6W5GTou+o8K07cZVTzvHHfNTYhib/8nrL+9AOmtCtL\nKRvTLL/nlJ03SFQls/yLKliZpMzLbl3Rnov3I/j1yB1O3QmlRnGrDF8fEZty7WOcR659OlZ1YOWp\nh4wfN5btPr5KhyM0yOvz+cgWZbGxyBvPOFqZGtCyUhGSk5Pp8+sRlh++wejWlZQOK0fEJiSx48I9\n1v8dwNQu1XG2s8jye07edp7EpGRWDmiQOpbVpmoxLga9YPH+65y8/YyaJW0yfH3E63tRhnpZjiU3\n6FTDiRVHA+R8LoQQQoh0pY63NCyWZ8Zb3rbq1ANMDXT50bM0vVddxPviE7pXd1A6rHTFJiTx19Vg\n1p99yJTWLtkyVjJ19y3ym+gzv0s59HS0AfCsYMulhxEsPnKXKw8jqVg4pQ8/bdctdLS1mdupLEZ6\nKbVP3V2sGVC/GNN23eZMUDg1imd83zTiVSIAxgbK101VUsfK9qw89YjxY8ey3Vc9+udhYWGsXr0a\n762bOfH3KRKTkpQOSTGDBw9WOgShhiwtzGnarDndPv9cveo/z5zBdx1qY2OZ9XyQ2yzfex5TI32m\nfuFOj5lb2HL8Gr0aq+dYW2x8Ir6nb7Du4GWmf9kUZ4cC2fr+ey8EsPbgJTxqlMb31I139k9cd5Ak\nlYrVIzuQ3yylxkTbWmU4f/sxi3ac5u/r96lVpkiG7y+1blJ0qV+e5fsuqtX4muTvNyR/i/SoY/7+\nUHJ8qy+pH6keNOL43raVE3//TWLipz++k5OTAfDx8cFH1rEQas4ynwVNmzWjW7esH995Y2aXEEII\nIdIICAhg+LCh+PjuoLh9AVpVK8mUztUoU6QgVmbGGOjlnosHkTe8iIzBzMggR36bcQlJhEbFcP1+\nMMeu3sN7/Spmz56Np0crZs+ZS4kSJT55DFkREBDA8KFD8dmxA0drU5o7mzOhlgsuBY2xMtZFX1db\n6RDzrMAXrwBwKpA3HghQR/GJKkJjEvEPjuHvoAi2rf415fhu1YrZc3PH8T102HB2+PpgauuIeaXm\nuHhMwLiQC7pmVmjr5u2blNkl7PJ+LCs0VjoMtZYU+5L4sKdE3/fj9tXDfDt6LKNGj+G7b0fy7bff\nYqzggg4PHz5k519/sWrm92hpaSkWhxKeh4azfd8xOjRvQAu3mtha5+e3TTsyXMxw8TpvFq/z5v7j\nZ9gVLEDvDi1xcSpK50Hj2bzgR1o2qJXa9sqNACYvXM2J81eIjnmFvU0BWjeuy+gBPTA3+7iiGheu\n3WTVtt1s3HmAZFUyHVs0pFDB7Jkc8iwkjG96tqdPx1acuZx5EeuPaZueiMiXGBkaoJuLbrx8Kn07\ne/DTknWsWbOGQYMGKR2OEOI9Vq9ejZaWDu6d+yodygeJCH3O6X0+1GrenipuLbC0tmXfpuU07tgn\n3fa71i1h97rFPH/8AMuCdjTu8AUOTqWZOagr3y7YSNUGLVPb3r1xhc0Lp+J//gSxMdFY2dhTvbEn\n7QeMwtjs4wrUBV67wKFtqzm+cxPJKhW1W3TCqqB9lr77a+VrNaRs9fqY/VME67XirimTQJ89DMKl\nam0AajRpS74CBdHVS3ttULhESkGu4Ef3cSqb8UKJ0ZER6BsaoaOTO28f2hV1olqjVixe8usnL6a1\nZPFiPBrVoUTRQp/0c9SN9DmhUa0quFWvlLog9muVXEsBEPTwSeqi2FntM0qf840SRQvh0agOvy5Z\nolHF8nx8fBg2fDh3AgOpUac+34z4nkqf1aCYoxMWllZoa8tYblapVCqOHtiDm3tzpUNRWyqVioiw\nUO4GBXLxzCkO7N5B69atKe7kxJzZs/H09FQ0vtWrV6OjpU3fzh6KxqEEybsfnnfDI6MIuPeI9s3c\nMNBPWxSnXTM3Vm7dxa4jp+jm6Z7hZ0neTaGlpcXgXh344tupPHz4EAcH9Xx4XAghhBAfTu6f5u0+\nddsm9ShYwBJ9vbRjvi4ligFw79FTqpRNKdb8MeNe6ZE+9Rty/zRzMv8p+4Vd3odlhYyveUX6csP8\np9+Gts97+Tsimh2n/GlbuyzNqpXCxtKMlXvP0atJ+vc4l/51mmU7z/DgeTi2Vmb0dK+Cs4M1PaZv\nYN3orjSv9mZRAr+gp0zfeJiT1+8RHRuPXX5zWlV3YWSnepgbG35UnBcDH7PuwEW2HPVDlZxM+7pl\nsctvlqXv/m+hUTEMWuhD29plqVO2GL4n353fFBEdi6G+Hro6/+1+QlZfr0l6N63KzC3HNCp/r169\nGh1tbb7q2UXpUHJc8IsQ/vxrHx1bN6eluxt2NtYsW7ORvt07pdt+4fK1LPx9LfcfPsbOtiBfft6R\nMqVK0KHPN2xbuZBWTRqmtr187QaTZi3gxOlzvIyOwd7OhrYt3Bkz5GsszD/uPHD+8lVWbtjGBu8d\nqFQqOrdpib1twSx9938LCQtnwIixdPRsTv1an+G9c+87bR48fkpB6/wYG6U9FzoVLQxA0L0H1K1R\nNcPPCI+IwsjQEF3dvH0toKWlxdD+X9DDa6SMrwshRC7j4+PDsCGDuXP3HrWKWzK4phVVChehmJUR\n+Yx00c5bl2UiF3gSGY+dec6Mob2MS+JpVDx+j6M5HHCbsaO+ZczoUYz89ju1GT9ZOsCdPDZ8wovI\nV+w8H0ibz0rStGIxbPIZs/LQNXq6lUm3/bL9fizbd4WHIVHY5jOhR/0yOBeyoue8Xawd3IJmlYql\ntr16/wXT/zzLqZuPiY5LwM7SlJZVijOidVXMjT7ud3cpKJh1x26w9eQtVMnJtKtREjvL7FnY+Xlk\nDAOaVKCnWxnOBT7LtO2fpwOoU9oeK9O01zwtqzgyafNJfM4GMtwz42uerL5ek3zRoCyzfC+qxfiJ\n5G/xPkEhsRS2NEA3D/4YckP+XtKrep7L36XtU+7D3w+JTrP90r1QZvx1jXNBISQDLvYWDGniQsMy\ntpm+3/Fbwfy815+Ld0NJVCVT2MqYjp8V5euGzmnqyYTHxDN793X2+D3maUQspga6VCxiycgWrlQq\navXR7T7EpfthrD8VxLZz91GpkmlbtQi22bTgav3SNtQtVTB18c3XKhROWeznXkg0NUtYZ/j6iFcJ\nGOrp5KlzQ686TszZc1Mt8rcQIneS/J1Z/n7xVv4u8xH5O+St/F0sk/z96K28bJVJ/s683Ye4dD9U\ngfydEuP783d8Hs3fN3JV/l69ejXa2jp4fJ476lc4lkoZR3v64G6a7TevnGflzz9y/cJpkpOTcXQu\nS3ev76hWP/O5eRdPHuaPhTO5cfkcSUmJ2BQqgnvbrnTsOxg9/Te//ajwMNYsmMbf+3cS8uwJxiam\nlCpfmV6Dx1K6QtWPbvchbvpdYPemVRzw2UiyKpmGnh0pYJs9tRGq1GlEpZpuWPyrBkapcik1MJ7c\nD6L8Z3UyfP3LyAgMckFdi0LFSlDH3YMlOVC/QgghhHJWr16NNip61sp4UUpNVdo2Zd7jg9CYNNsv\nPQhn5u5bnLsXDsnJlLYzZ0jjEjQonXH/HeB4QAjz9gdw8X44iapkHCyN6FC1EF/XL/6va58E5uy7\nzd5rz1KuaQx1qeBgwYimpahUJN9Ht/sQl6qPM04AACAASURBVB9EsP7MA7wvPEKVDG0q2WNr8XFz\nyDNSr1QB6pTIj5VJ2nuq5R1Sri3vhcRQo3jG12qReWzsUksLBtQtysB1f8l8S5GtUs7nyfSqV0rp\nUHJc6UIp90ruv3iZZvvFuy+Y4XuZc3eek5wMLoXyMbRFORq6Zn5teOzGU37e5cfFuy9ITFJROL8p\nHWsUZ6B7GfTfmjMeFh3HnJ1X2H35IU8jYjA11KNi0fyM9KhA5WIFPrrdh7h0L4Q/TgSw7UxQynyU\nao7Y5cumsawy9tQpbffOWFb5oinXvveev6RmSZsMXx8Zk7fGsrS04OtGzgxYLudzIYQQQrwrdbyl\nRmGlQ8lxL17Gs9PvGa0r2OLuYo2NuQGrTz2ge/X0+0u/n7jP8hP3eBAWi625AZ9Xd8DZxpTeqy6y\n8otKNC3z5pnTa4+jmLUvgFNBYUTHJWFnYUCLsjYMbeyEueHH3XO5/DCS9Wcf4n3xScpYSUXbbBsr\n8ShnSwEzffT+9fy6s40pAA/CXlGxcMq4yaOIWKxN9TH611p0xaxS5jreC42hRnHLDD8rMjZvjatk\nREsLBtQpzMD1yvfPY2JimDFjBjNnTEc7WUUz53z83KY45exNsDXTx9Qg7z2LHPDiFSVknToBqJIh\n/FUid0Nfcf7BS/ad20frTZsoXqwoc37+RS3qP2trQW/3yorGoYTnEdHsOH2TtrXK0KxqKWwsTVm5\n7wK9GldKt/3SXWdZtuscD55HYGtpSs/GlXB2KECPmVtY911Hmld9M0bpd/cZ0zcd5aT/g5RaN1Zm\ntKruzMgOdTE3Nkj3/TNyMfAJ6w5eZsvxqym1bmq7YmeV3bVuXjFo8U7a1ipDHdei+J668U4bt/KO\n1C1bjPxmaZ9NqOhkB8Dd4HBqlcn4vltKrRvdPF/rRksLvFp+Rr95f0r+VkOSv8Vr6p6/30eOb/W2\n72YY7s4ZX/OKT0tzju8Z6GhDy9oV+XVUHyqUKop9gXyYfmRdxf/q0fMwClnL71ioF5UqmbCoaO48\nCubMtUB2nbxC69abcCruyOw5c//z8a3es96FEEIIka1iY2OZOHEic+fMobidFZvGdKFRRac896C1\nyH0KmOdcUSEDPR3srMywszKjUUUnJnzekAOXApmw7jBlXV0ZOmwYEyZMwNAwZy5QP9Sb43s2jvmN\nWNPdhQYl8snxrUacZHBecfq62tia62Nrrk+DEvkY0xgOBYQzZf8RyrqWYeiw4Wp9fM+eMxcjG0dc\nhqwhX9kGyAH+aVhWaKx0CGpPx9AUI7sSGNmVoED1tiTFvuTZ4TVMmzmHZb8vZ8G8X2jbtq0isW3f\nvh0TI0NaNaytyOcracWWv4hPSKR7m6bo6GjTzbMxc37fyIVrN6ns6pym7bINPgyfuoBBvTow+ItO\nxCck8MMvy9nguw8Afb03i2ZfuHYT955DaVCjMofWzcfepgDHzl5mwNiZnDjvx8F18967oF9oeCTr\nffezcttfXLsVRGVXZ6aN6E/HFg0xNU7JjyFhERSu0+693/PijhU4O6Y/ccPZsUiG+7LSNj3hUS9T\nY8/rzEyM8WhUi21bt+aaYkJC5GXbtnlTtVErjExMlQ7lgxzcspLEhHjc2nRHW0eHep5d2f77XAKv\nXcDJNe2E0L0bfmPF1BG06vU/PL4YRGJCPOt/mchR3w0A6Oq9KZYQeO0CE3o2pVyNBkxedxArG3uu\nnT3KkrED8T//Nz+u2//ewlFR4aEc893AwW2ruH/rGk6ulekxYgq1W3TC0DilUH1UWAhf1in63u85\nd8cFCjmm/wB5888HpLs99NljAGwcHFO3tezplW7bezf90NLSonAJl0zjiI6KwMg4d/w2MlLXowuz\nBnXl2bNn2Nhk/NB0Vjx9+pSTp06xaf6kT/L+6kz6nPD15+lf6zx+9gIARwe71G1Z7TNKnzOtrh6N\n6Dxowic9vnNKQEAAXl5e7Nu3D8/2Xfht4w6KFndSOiyNpK2tjZt7c6XDUGva2tpY5i+AZf4CVKpa\nnT4DB3PvTiA/T5tImzZtaOzuzqKFCylRooQi8Xlv24ZHo1qYmSi3+IRSJO9+eN5NTk7Znt6QuZVF\nyoNJfjcDgYyL70refcOjUR2MDQ3x8fFh4MCBSocjhBBCiCyS+6d5u0/9Tc/26W73uxmIlpYWLiWK\npW77mHGv9Eif+g25f5o+mf/06VhWyHyxGZE+dZ//ZGxoQPPPSivy+Upas/8C8YlJdG1YER1tbTq7\nlWee9wkuBj6mkpN9mrbLd59l1G+7GOhZk288axGfmMTkdQfYdOQKQJoC0xcDH9Py+xW4VSjOnmlf\nYpffnONX7zJo4XZO+t9j99Qv31skJjQqhk1HrrD2wEWu33tGJSd7JvVyp33dcpgYptyLDomMoeQX\nM977PU/P/4aShTIvWD38150kqVRM79cc35P+6baJiI7F7CMXYs/O12sSUyMDWn7mzLatWzQmf3t7\nb8OzWUPMTE2UDiXHLf9jC/EJCfTs1BYdHR0+b+/JrEW/c/7yVapUKJum7a+r1jN07BSG9P+CoQN6\nEx+fwLiffuaPrb4A6L11LXD+8lUatu1Bw7o1Oeq7HntbG478fYb+w8dy/PR5jmz/A13dzK8FQsLC\n+WOrDyvWb+Wq/y2qVCjLT+NG0rlNS0z/uRfyIjQM+7K13vs9/Y7uxLlE8UzbfDNqIomJSfw8ZSze\nO/em26asSyl27j1ERGQUFuZvin0F3L0PgEupzO9jRkRG5snfWXo8mzfG2MhIxteFECKXCAgIwGvg\n1+zbf4A25a1ZPagixazU63kyIdJjZ55z13GmBjqUMDCiRAEj2pYvwMu4JNace8acGdNY/tsyfpm/\nQNnxEwN9mldyfH9jDbPmyHXiE1V0rVsaHW0tOtVyZv5fF7kUFExFx4Jp2q44eJXRa48xsFkFBjar\nSHyiiilbTrH55C0A9N5acPFSUDCtpv1J/TIO7BrXHrt8Jpy48YhByw9x6tZj/vq+3fvHT17Gsvnv\nW6w76s/1hyFUdCzIxC61aFe9JCaGKddXIVGxOP9v+Xu/58lpXSlpl37xt5J2lhnue9uj0JeEvoyl\nlP27Cys62ligp6PN5bvPP9nrNY2poR4tKhVl25bNio2fSP4WH8oxf979Xah//tajeXn79zfWMNce\nhgNQouCb8beL90LxmHuIPvVKMLNLFUwMdJm9+zqfLznO6v61cXdN/x796cAXdF54lJYVHTgxrhnm\nRnrsuvIYr9WneR4Vx+T2FVPbfrXiFLeeRvJbn5qUc8jHs8hYfvC+TPv5R9j3bWOc/onnQ9tlJCw6\nni1n77HuZBD+jyOoWMSSCW3K07ZKEUwMUp7PC30Zh8ton/f+Wx0f24ySNul/Xt/66c9nfxLxCoCi\n+TMfp4x8lYDpRy56lNuZGujSvJydovlbCJG7vcnfmS8OrYne5G/z1G0p+ftgOvn7GKv713lP/j7y\nT/5u/k/+fvRP/o5lcvs3iwZ9teLkP3m51r/y8mH2fev+Vv7+sHYZeZO/7/yTv62Y0KZCOvl7+3v/\nrY6PbZ5J/i6Z7nbJ3xnLjfl7m7c3tdw9MDbJ3sWlPpVAfz8AChd/8/u8cfkcgzs1pk2P/gydPB8j\nY1PWLJjG6C/bMnnZFmo0aJbue1099zff9fSkbrPWrNx/CRMzc07s82XasC8JC3mO17iZqW1/HNST\newH+TFiwjhKuFQgNfsqSqaMZ8XkLlviewMGx5Ee1y0hkWCj7/1zPX5tWEnTzGs7lKtN/9DQaenZM\nrSMRERZCuyrvX3x1xb6LFHFyTndf215fp7v9xdOUGhh2RTIfu30ZGZ5rap40atOVCQM6a8Tz7UII\nIdLnvXULzVwLYmqQt/qeANceRwLgZP0mL1+8H07rBSfpXbsoMzqUw8RAlzn7btP9t7Os+rIqjV0K\npvteZ4JC6frraVqUt+XYqPqYG+qx++pTvvnjEiFR8UxqUya17YA1F7j57CXLelamnIMFzyJjmejj\nT8clp9k7tA7FrU0+ql1GwqLj2XLhEetPP8D/SRQVClsw3sOFNpXs31z7RMfjOn7fe/+tjn1XnxIF\n0++/fFmnWLrbn0bEAlA0f+a1MiJeJea5Rfaal7PByEBX5luKbOW9dQvNKzhgaqj3/sYa5tqDUACc\nbCxSt124+wLPmbvp41aamZ/XSDmf77xCt/kHWePVAPdy6S8sfDogmM6/7KNl5aL8PbE15kb6/HXp\nPl4rjvMiKpbJnaqltv1q2VFuPYng9/71KVfYimcRr5iw5Rzt5+xl//etcLIx/6h2GQmLjmPzqTus\nOxGA/6MwKhbNz4T2VWj3mWOasazSwze+99/qxMTWlLS1SHdf3wbpP8f1NDwGgKLWmV/HRsTE57nf\nX/OKRTDS15PzuRBCCCHe4b11C83KWOfJ8ZZ1Zx6SkKSic9VC6Ghr0aGyPQsPB3H5YSQVHNL2fVed\nfMDY7f70r1eMAfWKkZCk4qfdt9l6IeV+i/5bc7cvP4ykzeIz1CtpxQ6v6thaGPJ3YCjDNl/ldFAY\nPl7V0dXOvHZHWEwCWy48Zv2ZR/g/jaKCgznjWzrTppIdJvopYxOh0fG4Tjz03u95bEQdShRMf2ym\nX930a7FfexKFlhY427zpW7vYmrH3ejCRsYmYv3VvOCgkpR9eyuY9/fA8OK6SkeZlCyo+3uLt7c2Q\nQd8QFvKCYXXt6FHVRv77ACVkrTrxD20tsDLWxcrYjMoOZvSracfd0FhmHXpEmzZtcG/UkIWLlyhY\n/3krLauVwjQP1iBZc+BSSq2bBuXR0daic71yzNt+kouBT6jklHZO2PK95xm1fC8DW1XnG8/qxCeq\nmPzHITYdvQr8u9bNE1qOX41beUf2TOmFnZUZx6/dY9DinZz0f8Duyb0+oNbNKzYd82Ptgctcvx9M\nJSc7JvVoRPs6rm9q3UTFULLP3Pd+z9M/D6BkofyZthm+bBdJSSqmf9kU31M30m3zVfNq6W5/EhoF\nQLGC+TL9jIiYOMyMDN4bb17Q4rNSGBnoS/5WQ5K/xWvqnr8zI8e3+nN3fv9z0uLTyfXH9+BBhIeF\nMrpXS770dMPUWJlnagtZy+9YqB9tbS3yW5iS38KUamWK49XRnTuPgpmywifl+G7cmIWLFn308Z33\nRruFEEKIPCo4OJg2rT25ftWPST0a0Nu98nsHcoUQKWuNNK7khFt5R1bsu8DUBfM4cvgQf273oWDB\n9B9CyWnBwcG08fTgut9lxjV2oEc1m/dOtBBCpBzfDUvmo56TBWvOPmPmvLkcOXSQP3181er49vBs\nw+Wr13HoOA4btx5oaculvFAvOoam2Df7GutaHXiwdRrt27dn1KhRTJkyBa0cXrTr0KGD1PusIvp6\nees4UamSWb55B8UcbKn/WUqhvh5tmzHn9438ttGXRZPSFtb4ecUmihayZeqIAWj/02dYOvVbyrfo\n9c57fzd9MZYWZqybOwED/ZQHi5rXr8GkoX35etwstu4+TOeWjdKNKy4+gT7fTWXnob8xNNCnc6vG\n/D5tFOVLvzuAmd/SgphrB7L075CTIiJfoqeny+QFK/H+P3v3HRbF8QZw/Hv0KlUUkK4IggrSLNhL\nNPaCvcReYokaa2wxtkSNyc9EE3uJJXbR2HsBu6Ai9oZSRAQB6Ry/P8523iEgUsT5PI+Pj7uzu3Pg\n3js7O/POgRPcfxyBYSl9WjfyZcqw3hgZfB5Jaj6VRrW8GDhpLqmpqWhqioEzglBcpaSkEBAYwJCZ\nfxd1VXIlSyrl0OaVmJWzxcW7DgD12vZg5/IFHPx3OQ7Tq8mV37Xyd0pb2tDj+5lIVGR9Xt/O+pvh\nX7spnHvNz+PRMzBi1IK1qGvIvrc86jaj68gfWTx5CIH7tuHbvKPSeqWnpbJwXF8uHN2DuqYmtVt0\nYujspdg6VVEoq29kwqaQxHz9HJR5EfOU/9b+iVWFSlR0r/7Bcif8N7B33V+0HzSecg4fXjAyKT4O\nVXV1Nv0xkzMHthP1+AF6pQzxbtSKTsMmo2dQ/F+iV65RHxUVVY4dO0anTp0K5BrHjh1DVUWFetWr\n5Vy4BBFtzuw9jYnlj7VbqVTBjhrubxcPzG+bUbQ55dWv4YGqikqB3t+F4fDhw3Tw88OinDX/7jmK\nZ/VaRV0lQVBgY+/AgqVr6NZ3INPGjsDL25stmzfTsKHy7+KCImu/BrJk5phCvW5xIOJu9pTFXSMD\nfRysLQm8FEJaeoZc32DARdmEqOjncR88r4i7b2moq1HXx40jRw6LZDuCIAiCUAKI96eiTf2upzGx\nrPc/yOJ125kwqDvODsoT6LxbXlm/lzKiTS1PvD+VJ8Y/CZ+DYjX+6cgRarvayiV4+RJIs7JYfeAi\nNmWMqO1qC0C3Bu78b/tpVu6/gPuQVnLl/9gZgLWZIdN7NUHl1e/oz+Ft8Pp2ocK5J63cj5GeNiu/\n90PzVbvoK09HpnRvxLA/d7IjIIQOtSsrrVdqegYDf9vGvvM30dRQw69OFRYPb0tlu7IKZU1K6fB8\n27R8/BRkNp+4ws6AEJaP7oBpqewXKXiRlIKaqipzNh5lZ+B1HkTGYqinTcvqzkzoUh8jvQ8nFsnv\n8SVNAzcHhv7hXyLid0pKCgEBgSz/bVZRV6XQSaVSlv2zCVvrctSr5QNAr87tmLdoOUvWbOTv+TPk\nyv/610psrCyZM3kMKq/Gmiz/bTaVfBUXchszbQ5GhgZsXPobmhqyxFjNG9djxsSRDBg1iS279tK5\nbQul9UpNS6PX0LHs3n8ELS1NurRrycr//UxVF8VxHKbGRqSFh+br5wCwYdsutu7ax7q/fqW0iXG2\n5X74bjCHj5+m9/DxLJw9mdKmJhw7fZbf/16FX6tmeLkrjod5V9yLBNTU1Jg+byFbd+/n/sPHGBmW\nos3XjZk6ZjjGhsqT5ZdEGurq1PP14ciRI6J/XRAEoZg7fPgwfu3bYakH2/q44G39ZfVdCcLH0tNU\nZXAtCzpULc3sw2FF3n/i62SBhtqXlSdBmpXFmmPXsSldCl8nSwC61nZi4Z7LrDoawm928nNi/9gb\nhLWpPtM61XzTf/JH/4b4jFuncO5JG05jpKvJyqFfvemXauJmy2S/6oxYfpSd5+/SvrryhabTMjIZ\n9Pch9l2+j6a6Gh1qOLJoQENcrU0Vyproa/FsVeG0l6NfJL255vtUJBIMdbWIjk8usONLogauVgxb\nfqxI+k9E/BaEj1Pc4net8qVR/4LyHMUlpXHmzjOmbg/GwkiH3rUd3uybvuMK5obaTGtb5U2c/rFt\nVf4LesKqk3dp7GKu9Jz7roajqa7K1DZVKGsg68dv72nNPwH3+PfsA2a0l42RSE3P5OTNp3SpYYun\nnSxpv7WJLr9398Jr2h6OhkbhYKaf63LKpGVIGbL6LPuuhqOlrkp7L2v+6OGNaznFBP7GeppELfT7\nyJ9k9qITUlhy9DZO5gZ42yu2Pd71IikNdVUVftkTwq7Lj3kY8xJDbXWau5VjXHMXDHVK5uIV9Z3L\nMGLdmRLx/kMQhML35cbvaKZuD1ISv4Nfxe+q78Xvx6w6eecD8fvJq/hd9Z34bcM/AfdfxW934N34\nbackLv/H0dDI9+L3h8spI4vfZ96L3z4fiN/K59rnhyx+38pl/E5/Fb+vKYnfriJ+FwMpKSkEBgQw\nZu6Soq5KjhLiYrly/jSLZ46jtHk5WvUY+Gbfkjk/YFrWgkETZ7/JUzF44hxO7tuJ/9q/qV5fcQwB\nwOmDu9HQ1GLghFmYlJF9BzRs3Zn//l3F/i1r+XbyXADSUlO4FHCUZn49qVRNNpahrJUtY+f+Tbe6\nlTh/4hDl7Crkupwy6WmpzBrZh4BD/6GhqUWj1p0YP3855SspvvM3MDLh8L2kj/xJZi/22VO2rvwD\nO8dKuHrU+GDZxPgXqKmrs+q3GZzYu52IR/fRNzDE96vW9B45BX3D4pPXwqNWfVRUCzZ/hSAIglB0\nZPkMzvBbJ+XjiEuquKR0ztx7zlT/61gYavNNrbfzi37afQNzAy2mtnJ+8+wzrZUze65Gsur0Qxo5\nK8/Tu+9aFJrqqkxp4UzZUrL3a+2qWbLuTBj/ng9jeptKAKRmSDl5O4Yu3uXwtJXFfGtjHX7rXBWf\nWUc5ejMa+9K6uS6nTFqGlG/XBbE/JAotdRXaVbNkYRc3XCxLKZQ11tUgYn7zj/xJZi86IZWlJ+7j\nVFYfL9sPt23ik9NRU1Vh7v5b7A6O4GFMEoY66nxduSxjm1bEUEf9k9evqKmrquBb3oQjh0U+A+HT\neP19/r9eH34WKWliX6Zy9s5Tpmy+gKWRLn3qvZ03O33rRcoa6jCtg8fbviw/T/67/IiVx27SuHI5\npefcGxwm68tq70FZQx0AOvjYs+7UHTYG3GVGR9lCz6npmZy8EUnXWuXxtC8NgLWpHv/7phaeE7dx\n9Ho4DmVK5bqcMmkZmQxefor9V8LQVFOlvY89f/auhauV4th4Yz1Nnv7d8yN/ktmLjk/h78OhOFkY\n4u3w4Vz1L5JfvYvaFcSuiw958CwRQx0NmrtbM66VG0a6xbuf52NoqKlQu2JZ8X0uCIIgCIKcN/0t\nfpWKuiqFTpqVxT9nH2NtrE0tB1m7tbOnJX8eu8+aM2HM7+AiV37x8ftYGWkzpbnjm3b7bx0rU+uX\nkwrnnrrrBoY66izt7vZmDH1j59JMbObIqM3X8A+OpJ278nfWaRlSvt1whf3Xo2V9Je7mLOxcGRcL\nxffKxroaRPzyVb5+Du+LTkxjy8VwVpx+xMiGDjiW0Xuzb2Qje47ffsbwjVeZ3dYZUz0NTt99zt8n\nHtC6alncrT48P/VNv8qBO+y+GvW2X8W1DGOblC+R/SrZUVdVwdfBuEja51lZWfzwww/MmTOHju5m\nTOhShdJ6X87PXhDyw9ZYiz/aO9DTy4zJ+87j7enB5q3biib/c0Agf36rPFdCSSbNymL1ocvYmBlS\n28UWgG71q/K/nYGsPHAJ98Hy7xD+8D+DdWkDpvds+DbXzdBWeA1bpHDuSasPynLdjGqPprpsrtZX\nHhWY0rU+wxbvZkdgKB18XRSOA1n/28D/7WTfhVtoqqvhV9uVxcNaUdm2jEJZE30dnm/+IT8/BgA2\nn7zGzsBQlo9si2kpnTwdG/3iJYt3n8PZujQ+TlYfLPviZQpqqirM+fcEO8+E8iAqDkM9LVr6ODGh\nU50vKteNhpoqdVxtRPwWhM9McYnf2RH3tyB8vM/p/u7WtBbTBozCzEj5u1ZBEOTZW5qxfFI/+rWu\ny5j/bcTby5PNW7bm6f7+cmZWCYIgCMIXLCQkBB8vL6Ie3eXAjJ70b+qJ2hc0wVoQPgU1VRX6N/Xk\nwIyeRD26i4+XJyEhIUVdLUJCQvD28iDy3nX8+zrT26csaiqFm3hJED53aioSevuUxb+vM5H3ruPt\n6VFs7m8PL2+uP4zEeYI/ZRv0FgshCcWaeqnS2Pf+FYc+C/hl7nzad/AjOblwE5peCQ6mqrPiQnkl\n3f6TZ3kUHkX3Nk3fJGCsaGeNj1slNu85Snzi2wQc8YlJ3H8cQS2Pym8WMgRQV1OjdSNfufPGJyYR\nePkadb3d3ixk+FoTX28Azl+5kW29UlJT2X7gBNXdXLi2dy2/Tx6hdCHDz5E0K4vUtHR0tLXZs2Ie\nD45vYf7EoWzbfxzfjoNJePnpk54UZ26VKpCens6NG9n/fxAEoeiFhoaSkZ6OnXPVoq5Krlw6uZ/o\n8EfUa9PtTXyztHPE0c2H03u2kJyY8KZscmICUY/v4+xR802CLQBVNXV8GskvCpicmMCNy2dw8a6D\nuob8xFg338YA3L5yPtt6paWmcObADiq6+bBw71X6Tf4NW6cPL3z1KSW+iOWXoZ1ISohn6OylqKgq\nLgIZ+egeHV306F/Hns2LZtFt5HTaDx6X47mlWVmkp6Wiqa3DlBX/sfT4PXpPnMeZ/duZ0LEOyS8T\nC+IjfVKaWjqUs6/A1atXC+waV65cwdHeGh2tkjex+kNEm1O52BcJ+A2dTHzCS5bPHo/qO/3u+W0z\nijanPB0tTRztrQv0/i5oS5cupVmzZtRp8BVbD5zCs3qtoq6SIHyQZ/VabD1wijoNvqJZs2YsXbq0\nUK8fGhpKeno6VZ2VJygtyUTcVe5DcXfW9wN5EhVN3/GzuRcWTnzCS9bu2M/Sf/0BSM/I+OC5RdyV\nV9W5PFevXCnqagiCIAiC8AmI96eiTQ1w99ETdFwaYlunA7MWreGnkf0ZP7jHB4/5UPtbGdGmlife\nn74lxj8Jn5viMf4pSGnylZLu4MXbhEXH0aW+25v4XcHSFK+KVmw7dY2EpNQ3ZROSUnkQFUsNZ5s3\nyXEA1FVVaVHdWe68CUmpnA19RO3Ktmiqy3//NHSXxeGLtx5nW6+UtAz8A6/j7WTFxUXDmTegOZXt\nyub782Yn4nk845btpbmPE21ruX6wrFSaRVpGBjqaGuz8sRc3V37Pz/2asTMghIZjlpCYnFqgx5c0\nVe3NSc/IKBHx+3X/upurc86FS5i9h0/w6HE4PTu2ffssUN6e6h5ubNq5h/iEt+Me4hMSuf8wDF8f\nD1TeGWuirq5G268by503PiGRgPOXqVfLB00N+QUFv6pfG4Bzl7LvU01OSWXb7v3U8HInNGA/C2dP\noaqLU74/b3bCI6P47ocZtGraEL9WzT5Y1tXZkU3LF3L2YhB2HvXRs6lCi6798a3uyeK503O8ljRL\nSlpaGjo6OuzftIqw4JMs+OkHtu7aT41mfiQkvvxUH+uz4ObiLPrXBUEQirmlS5fSrGlT6tpo4d/H\nGW9r5YsiC4KQvdJ66vza2p4FbRyYP/cX/Dq0L4L+k8tUtjYp1GsWB4eCHxIWk0BnXyded4lUMDfC\nq3xZtp29Q0Jy2puyCclpPIyOp7qjxXv9Jyq08LSXO29Cchrnbkfi62yJhpr82PSGla0BuHg3Ktt6\nJadl4H/+Ll7lzbnwSzfm9qyDq/WH8RdJ0QAAIABJREFUF3MvDCnpmYCsz0gZDTUVklKzH1OU3+NL\noio2pYuk/0TEb0HIv+IQv4ODLlG53IcXZvnc9VseSJlhm9/8cZ24i8nbgmhWxZIDYxpirCebh/Qy\nNYPAu9F42ZnIxWkViYRL05uzbpBvdpdgapsq3JvXFksj+QT7Nia6xCenE5ckaw+oq6lgqq/J3ivh\n7Al+QnqmFAB9LXVuzGlNv7rl81ROmeT0THYFPcbL3oSzU5vxc8dquJYz/Iif3MeJS0qj55LTxCen\n80dPb1RzyLMjzZItNK2jocbWYXW5NrMlM/3c8b8cRpO5h0gsoXG9SjnDEvP+QxCEwhccdPkLiN8B\nlBm26c0f14n+78TvRkrit6mS+N2CdYNqZ3uNqW2qcm9euzzE7ydK4nIb+tWtkKdyyryN36acnfo1\nP3f0KObxO+ud+F2PazNbMdOv2qv4fbAEx2+jzyZ+vx6fUKFS8ctf8eO33Whor/PmTwdvWxbNGEut\nxi1ZvPMUBkay/sXkpESunDuFS7XqcnkqJCoqbDh1k1krtmd7jYETZrH72lPMLOQXsTIvZ8vLhHgS\nXsQBoK6ugZFJaU4f2MWp/f5kZKQDoKNXiu0XH9O21+A8lVMmNSWFE3u34+JRnbXHrjHip98pX6nw\ncmAkxMUyeYAfLxPiGT9/udIcGO/KypKSnpqKtrYO8/7Zw5ZzDxg6dT7H92xjcBtfkl4mfPD4wqSp\nrYO1veNnPb9dEARByF5oaCjpGRlUtizZCyP1X30J89H/vflTZdpBpu68TjPXMuz7rhbGurJxkS9T\nMzhzLwZPWyOFZ58LkxrwTz+vbK8xpaUzd2Z9haWR/AKd1iY6xKdk8CJZ1rZRV5VgqqfB3mtR7L0a\nSXpmFgD6Wmpcn96Yvr62eSqnTEp6JruvROBla0TghPrMae+KSyH+juOS0vlmxQXiU9JZ2NUtV88+\naRlSdDRU2Ty4Old+bMyMti7sCo6g6W+nSuyzj6uFPleCLxd1NYQS4s33uZVxUVelQPX9+zhmA9e8\n+eM6ZjOTNp2nmZsVByY2l+/Luh2Ft4OZYl/W7PasH5b9YmbT2ntw/39dKWesK7fd2lSP+OS09/qy\ntNgT9Ig9lx/J9VHd/LUT/eo75amcMslpmey69BAvezPOzWjLL119cC3E33Hsy1R6LDpCfHIaf/bx\nzeW7qEx0NNTZOqoJIXP9mNXZG/+LD2kyaw+JKemFVPPC5WplyJXgoKKuhiAIgiAIxciX0t+izOEb\nz3gcm0wnT8s3Y73Lm+niaWPIjqAIElLePuMnpGTw8HkyPnZG7431lvB1Zfk8AwkpGZx/EEctB2M0\n1ORzv9SvKBuzfTnsRbb1SkmXsvtqFF62hgSOq82ctpVwsSj4sbj3Y5IwH7ufKtOPMv/gHX5o5sjI\nRg5yZZzL6rOipzsXHsZRbeZxrCccpMuyi1S3N2Zue5ccryHN4m2/ygBPrkypz4zWzuy6EknT/wWW\n2H6V7Lia6xV6f0tycjJ+Hdozf+4vLGjjwK+t7Smtp57zgYIgyPG21se/jzN1bbRo1rRp0eR/zsig\nit0XmOvm0h3Col/QpX6Vt3O1LE3wcrRk2+kQEt7Ju5KQnMqDqDhqOFsrztXyke/nSkhO5eyNx9R2\ntUFT/b25Wu6yeV0Xbz/Jtl4paen4nwnFu2I5Lv4xhHn9mxZoLqKI5wmMW76f5t4VaVuzUp6OjU1M\npuvPm4lPSmHx0Fa5ey+SnomOljo7p3bj5rLv+LlPE3YGhtJw/AoS35kf9yWobFuGq1eCC/WaIn4L\nwqdR1PFbGXF/C8KnUXzv7w7MnzePxeN6s2jcN5gZfXn9b4KQXzUqV+DQn+Np6OFEs2Z5u79FFmVB\nEARBKOHCwsJo3LAhNiZa/PN9T4z1tXM+SBCEbFWwNOHAjJ50n7eVxg0bcvb8eaysrHI+sADI7u/6\nWGmns6KPM0Y6onkvCPlR3lSbXX2c6fPvbRo3rM/Z8xeL9P6u37Ax6YZWOI9egZqeUZHUQxA+Ruma\nfmiaWrNnUV+6de/Bls2b5BbKKEjh4RGUK1u6UK5VnCzZ6I+KioQebb6S296zbVO+nforG3YdZGCX\n1gBEPXsOQGljxYQ85W3Kyf07IvoZUmkWG3YdYsOuQ0qv/Tjyabb10tLUpE3jOuw5FoDr1z3p3KIR\nff2aU7miQ7bHfC6OrV+osK1tkzqoqEjoMmIavy7fyNThfYqgZkXDsoxswG9ERARVqxa/JD2CIMhE\nREQAYFK2XA4li4cDG5chUVGhXpvuctvrt+3O31OHcWLXBr7qMgCAuGey5PIGxortAHMb+bjzPDqC\nLKmUk7s2cnLXRqXXjonMfgCkhqYWPo1bc/HYXoZ/XYXaLTrRyK8PNhUr5+nzfYyosPvMGtSWFzFP\nGb94C3bOyr9zy1rbsykkkZfxcYScO8GKWd9zeu8WJi/bhW6p7JPyzVx/RGFb9SZtkKioMH9EV3Yu\n/5XOw6d8ss9TUIzKWL75/14QIiIisBRtzje+5DbnvbBw2g6aQFRMLFsXz1JYWD2/bUbR5lRkUca0\nQO/vgrRhwwYGDhzI8LGTGD5u8pvFJwWhuNPU0mLB0jXYla/AwIED0dPTo0uXLoVy7df3u+jreUvE\n3ezjbsuGtdjx12ym/Lacai17o6ujTYMaHqxbMBXvtv3R09HJ5swyIu7KsyxTmoiIyKKuhiAIgiAI\nn4B4fyra1AAO1pYkhRwmLj6BE+eCGTVrIZv3HuW/Zb9gWEoxQU9O7W9lRJtannh/KiPGPwmfsyId\n/xQRQTnTgn/3WNys2HceFYmErg3c5LZ3a+DGd4t38e/xYPo18wbgaVwiAKYGugrncTCXXwg+MjYB\naVYWm45fYdPxK0qv/eRZfLb10tJQo2WNSuw/fxPPIQvxq1OZXk08cLUtm6fPl1vD/vAHYP7AFjmW\nPTCnn8K2VjUqIZFI6PXLv/y+/TQ/dG1QYMeXNBYmsontJSF+v+lftzAv4poUviVrNqCiokKvTm3l\ntvfq3I7BY6awbos/g3t3BSAq+hkAZqYmCucpb2cj9++IqKdIpVLWb/Vn/VZ/pdcOC8/+Paa2liZt\nmzfhvwNHqVSrKV3ataBf945UqZR98vr8GDBqEgB/zJmWY9l1W/wZMPoHvhvwDQN7daFsmdIEXQ1l\nyNip1Gjmx7Gd6yhtkn3SfGVjb9q1+AoVFRU69hvOvD+X8eO4ER/9WT435SzKEhH5eb7TFgRB+BK8\nHr8zsq4lo+pZIYbvCEL++LmVxtpIk77/7qFH925s2rylEPtPIrGsZ1so1ypOVhwJQUUioYuv/LNE\n19pOjFx5jE0Bt+jb0BWApy+SADAtpZhXwr6M/DuRyLiXSLOy2Bxwi80Bt5Re+8nzxGzrpa2hRktP\nB/YH3cdr7Do61HSkV71KuFiZ5unzfWraGrI59+mZmUr3p2ZkoqOZ/bz8/B5fElkY6wGF238i4rcg\nfFpFGb8jIqOwqJHz4iyfs2V9a9DSLed5e0/jU8jKAhN9zTxfIzU9k5Un77I76DEPY14S+zINaVYW\nmVLZQsjSV3+rSCSsHejLkNVn6b0sAG0NVTztTGjgXJauNeww1NHIUzlltNVVaeFWjv1Xw6k+fS/t\nPa3pUcseF8vs5659Kg+eJdJ18SmiE1JYN8iXyuVyvuae0YrvPFq6lUNFIqHPsgAWHrzBhBauBVHd\nImVuJBtDXRLefwiCUPgiIiOxqFHyvhvftaxvzUKO34m5jN+nX8Vl0xzid/bllJGP33to72lTyPH7\n5DvxO+exZHtGKy5MLovfvIrfoUxoUfLG2HxO8fv1+ITSFsUvf8XUP9dRp1nbHMs9j44iKysLQ5O8\n92Wlpabg/88STuzdQUTYfeLjYpFKM5G+6k+SSmV/S1RUmLFsK7O+683UwZ3R1NbBxd0Hr7qNaebX\nC31DozyVU0ZTS4s6TdsQcHgPPeu70qh1Z5p36YuDc8HfI+GP7jGhd1tin0Uxa9lWyrvk/P924dZj\nCtvqNGuLREWFaYO7sPGvX+kzemoB1PbjmJa1+GzntwuCIAgf9vr73cJQq4hrUrCW9qpGiyo5jyl9\nmpAqe/bRy/65IjupGVJWnX7Af1cieRiTRGxSutyzT+Y7zz5r+noxZN1l+qy6KHumsTGivlNpunhb\nYaijnqdyymipq9K8SlkOhDyl5uyjtPOwpHt1a1wsCn4RrAcxSXRbeo5nCams7eeFay4Wvt89vJbC\nthZVzFGRSOi76iJ/HLnL+GYVC6K6RcrcQIvIyMdFXQ2hhHj9fW5prDjHpCRZPrAuLavZ5Fju6Yvk\nV9/nH9eXteL4TXZfesjD6ETiklLJlCrvy/pnaAMGLz/JN38dQ1tDDU/70jR0saBLrfIY6WrmqZwy\n2hqqtKhmw4ErYfhM3kF7Hzt61nbEJRf9Svn1IDqBLgsPEx2fwrqhDahslf14+tf2jmumsK1lNRtU\nJBJ6/3WMhfuvMaG1e0FUt0hZGOkSGXWnqKshCIIgCEIx8qX0tyizOjAMFYmETp6Wcts7e1ry/dYQ\ntlwKp3dNawCiE1IBMFXSD2NvKp8zMSo+FWlWFlsvhbP1UrjSaz+JS8m2XlrqKjSvXIYD16Op+fNJ\n2rlb0L16OVzMFfPNfEp2JjpE/PIVL5LTCbj7nIk7b7AjOIJN/T0x0Jb17Wy5FM6ozdcYWNuWXjWs\nKFNKk6tPEhi7NYSmC8/gP8QbE93s+6p2D/VR2NaichlUJNB3TRB/HLvP+K8qFNhnLG7MDTSJjLxf\naNeTSqX06N6NI/v3sLGnEz42YhF6QcgPTTUV/mjngL2xRpHlf7Y0+fLu4xUHLsly3dSTH+vQrX5V\nvvt7D/8ev0q/pp4API17CYCpgWJ+Ywdz+f6jyOeJslw3J66x6cQ1pdf+cK4bdVpWd2L/hdt4DluE\nX21XejVyx9W2TJ4+X24NW7wbgPn9m+bpuPtRsXScuZHoFy/ZOKETVexyzsVzYOY3CttaVXeW5bqZ\nt5XfdwTwQ5d6earH58zSRJ+IyMLL/yzityB8WkUZv98n7m9B+LSK3/3dnSOHD+I/fxQ1q3w5fR2C\nUBC0NNRZPqkfFVaXydP9/WVllRAEQRCEL0xSUhLt27allEYWG8Z2wED3y3vZLQgFwVhfm03jO9J0\nylpatWjOydMB6OnpFWodZPd3a/RIYXUXJ0ppiaa9IHwKRjpqrO3qSJuVN2jZ/GtOBQQWyf3dum17\nUtT0cBq6GjUd0SkufH5KOfpQ4dsV+M/vzOTJk5k5c2ahXDcpORldbcUktSXZg8eRHDx1Dqk0i4qN\nlHcGLtu0681ihimpsgGeEiWZT5VtA/imw9cs+nF0nuumqaHO+t+mEhP7gg27DrF6+16WbNiJh2tF\n+vq1wK95A3S1S9YzSmNfbyQSCeevhBZ1VQqVno7svktISCjimgiC8CEvX8oGCWpqKw4SLG6ePn5A\n0KmDZEmlDGnkrLTMwU3L+arLAADSUpNlG5XFsmziW8MO3zDwxz/yXDd1DU1G/7aOhNgYTuzayNHt\na9i/YSkOrh408uuNb3M/NLU//YTwm0Fn+WVoR7R09Php7SGsKlTK8RjdUoZ4N2qFqbkV4zvWZsey\n+XQb9VOer+3m2wiJRMLtK+c/puqFTlNbl8TE7BccyK+kpCR0tfI+yf1zJtqcis4EheA3dDJ6Otoc\nWfs7lSrY5frY/LYZv9Q2J4CetlaB3t8F5cKFC/Tr14++337HiPFTiro6gpBnEomEEeOnkJiYQJ8+\nfbC1taVGjRoFft3X7deS1neQExF3FeU27jap7U2T2t5y267flk1ItbP6uEWPv9S4q6ejTeKre1AQ\nBEEQhM+beH8q2tTvMiylT6tGvliZm1Gr42DmLdvAjFED5Mrkp99LmS+5TQ1f9vtTMf5JKAmKbvxT\nCjpa2SenL4keRsVy+PIdpFlZVBmwQGmZVQcu0q+ZrO8nOS0dyNPrYXo0qsbvQ1rluW6a6mqsHtOR\nmPgkNp24wrrDl1m+7zzu5S35pokH7X1d0dHK+4IHyqw7fJkjQXdYMdoPM8OPH7fayL08EomEC7c+\nLjl+fo//XOm++j2WhPj9pn9d5wt7Fnj0mP1HTyGVSnHwUlzUF2DpP/8yuHdXAJJTZMkt8/Is0Kdr\nB/6al/dxF5oaGvy79HeePY9l/dZdrNq4lb9WbcDTrTL9unekU5vmn+z3tWrjVg4cO8X6v36lrNmH\nF6vLyMhk+MTp1PL2YOYPb59xvKtVYfnvs/Fq3JZfF69g9qTv81yPJvVrI5FIOHcpOM/Hfs70dHVI\nTBT964IgCMXRhQsX6NenNwNqWjC6vlVRV0cQSgwfm1Ks6FyBzmv8C7//ROML6z+JjufI1UdIs7Jw\nG71GaZnVR0Po29AVgJT0DCCb/pNsrtGjbiUW9K6X57ppqKmycuhXxCSksDnwJutP3GDF4Wu425nR\ns14l2levgI5m4f++yhjK5k3EJCQr7MvIlBL3MhVzo+zH/ef3+JJI99XvsbD6T0T8FoSCUZTxW1dD\n5EQBUFWRReO0DGmej+2/8gwHroXzfTMXOnhZY1ZKCw01VcZsuMj6M/KLuLhZG3F6UlPO3XvG0dBI\njt6I4scdV/j9wA22DKtL5XKGeSr3Pg01FZb3rcHzxFS2nH/E+jP3WXnyLm42xvSsaU9bTyt0CuB3\nfv5+DD2XnEZXQ41dI+vjZG6Qr/M1cC6LRAKXHjz/RDUsXl7fdyXh/YcgCIVPxO+33sbvzDwf239l\n4Dvx2/ud+H1BSfw25vSkZu/E5Uh+3BHM7wdCX8VlozyVe58sftd8Fb8fvorfd96J39YFFL+fvRO/\nG3yC+G0u4ncx8Xp8glYB5FYoLKoqqgCkvxpPnBc/DetB4OE99Bw+kUZtu2BsWgZ1TU0WTBzG3s2r\n5cpWrFyNVYeCCLkYyPkThzh/4iB/z57I+sVzmbd2D+Vdquap3PvUNTSZumg9L2JjOLR9A3s3r2bn\nP0uoWMWDFl360qClH1o6n/73FHLpDJP7+6Gtq8fvm49g55hzDowP8a7TGIlEQmhQ8cproaWj91nO\nbxcEQRBy9ro9UxDt4M9RfvouB665xIHrUYxu4kh7D0vM9DXRUFNh7OarbDgXJle2qpUBp8bV4/yD\n5xy9Gc2xG8+YviuU/x2+w+ZB1XG1LJWncu/TUFNhWS8Pnr9MY+vFJ2w4F8aq0w9xszKkew1r2rpb\noKOhmufPmJPzD2L5ZsUFdDVV2TmsJk5l87egev2KpZFI4PKjuE9Uw+JFV1OVxCTFd7GC8DHE97m8\n19/nqR/zLmrpCfZfCeP7FlXx87HHrJQ2GuqqfP9PIOtP35Er62ZjQsCPbTh39ylHQ8I5ej2caVsv\n8vu+a2wZ2ZjKVsZ5Kvc+DTVVVgysy/PEVDafvcf603dYeewm7ram9KhdgXZeduhoFkBf1t1oeiw6\ngq6mOrvHNsXJQvm7stxq4GKBRAIX7z/7RDUsXnQ11Uh8mVTU1RAEQRAEoRh50z5X//TP3sXZo+fJ\nHL35DGlWFp6zjists/bMY3rXtAYg+VV7PS9jvbt5l2NeB5c8101DTYVlPdxkfSWXIthw/gmrAh/h\nZmVAd59ytHUzL5C+ktcMtNVp5loGS0NtvvpfIAuP3mfS145kSLOYsD0Ub1sjfvja8U35atYG/N6p\nMo1+C2DRsQdMbu74gbMrV7+i6at+lRef8qMUe7qaaoXa3zJp0iT8d/qzvkdFfGxEThlB+BQkEhhd\n34rENCl9en9T6PmfdTQ/Te6Uz8XDp3EcvnxXlutm8EKlZVYdvEy/pp4AJKe+znWjLD+F8mv0aOjG\n74Oa57lumuqqrB7dnpiEJDaduMa6I8Es338R9/IWfNPInfa+Lp9srta6I8EcCbrHipHt8pTr5tzN\nx3T7eTO6Wurs/akXztal81WPRm4OSCRw4U54vs7zudHV0ijU/jURvwXh0yuq+P0+cX8LwqdXrO5v\nf3+2z/2OmlUqFPr1BaEkkkgkTPimFQlJKfTp3TtX97cYkSIIgiAIJVi/vn15cPcWB2f1wkD3y1oo\nURAKmp62BuvHdqDxxNUM6N+f9Rs2FOr1+/Xtw/1boezuV4lSWqJZLwifkp6mKis7l6fFsusM6N+P\n9Rs2Fur1+/TtR+id+1SauFsshCR81vQreGPX82dmzx6Jh4cH7dq1K/BrZmVlZTvIoaRavmkXUmkW\nZ7ctoXJFB4X9s/9ay08LV3E26Do+bpUwMZQlxXkeF69Q9v5j+UENlmVKo6IiISw8Kl91NDEyYGjP\n9gzt2Z6L126yettexs/7i3G/LKZj8wbMHDWA9IwMrHxz/j9yefdKKtpZ56s++ZWWnsH12/fR09Wh\nvI2l/L60NLKystDU+LIGKr0ecJSVlVXENREE4UNe36PZLVhVnBzctIIsqZS52wKxqVhZYf/Wv+bw\n78IZ3Ao6i6ObD/qGJgAkxikmbXv6+IHcv03KWCJRUSE6/FG+6qhvZELznt/SvOe33L12kSPb1rJ2\n3kTW/DIe3+ad6DbqJzIz0unra5PjuRbsvoSlXfYTC24Hn2Nm/1ZY2jsxfvEWDIwVBzQ+iwhj86LZ\nVPL0pW7rrnL7yjk4AfD4zo1sr5GRnkbY7eto6epjbiPfpsh4Fd80ND6P/kWJRFKgMUnW5iz+99Gn\nJNqc8s4FX6dV/3FUtLdm2+JZlDZWnKyf3zajaHMqV9D3d0GIiYmheYsW1KjTgPE/zinq6ghCvkyY\n/jMP7t6hTdu2XA8JwcTEpECv9zm1Xz8lEXfl5SbufsiZoBAAalZTfK54TcRdRRKJ6OcRBEEQhJJC\nvD/9ctvUYRFPmbVoDb6eVejWuoncPicHWb916J2Hcts/tv0t2tSKxPtTMf5JKDmKbPxTtmnaSqZV\nBy4izcrixK+DcLUtq7B/7ubjzN5wlPM3w/CqaIVJKdlC3LFKFuJ+EBUr928Lk1KoSCSERecvWZtJ\nKR0Gt6jO4BbVuXznCf8cvszkVQf4YeV+OtSuzLSejUjPkFLhm19yPNfZhUOpYGmqsD3koayN0Wf+\nZvrM36ywv9Z3iwB4unkK0qwsQh89RU9bAwdz+b7a1PQMsrKy0PpAIvO0jMx8HV8SlaT4/aX2ry9d\n+y9SqZQLh7ZTpZKTwv6ZCxbz49z/ceZiENU93DA1li2AGPNccZGM+w/lFx6xNC+LiooKjx7nL3GU\nqbERw/v3ZHj/nlwIusqqjdsYN/0XxkybQ+e2LZj1w2jSMzKwcK2Z47munviPiuXtFbdfvwVA10Gj\n6DpolMJ+9watAEh6dI1Hj5+QkPgSpwqK53F0sAXgxu272dYhLT2dkBu30dfTpbyd/PiY1FfPAlpa\nmjl+lpJEQsn4HhEEQShpYmJiaPF1U2rZ6jOpcdHORRCEksjbWp+fW9gxcvZsMX+sAK0+FoI0K4vj\nP3XExUqxX2Ge/wXmbDvH+TuReJUvi7GeNgCxiSkKZR9Ey78TsTDSk/WfPMvfAuMm+loMalKVQU2q\ncvn+U9adCGXqxgAmbzhN+xqOTO1Yg/QMKRWHrcjxXIGzu1DBXPnC9blV1lAXMwMdbjyJVdh3KyKW\njEwp7nZmBXZ8SfT6viuM5x4RvwWhYBVV/BZkzA21UZFIiHqhGKc/JPJFMvuvhtPGw4rvm1WS2xcW\n+1LpMRIJ+DiY4uNgyvgWrly4H0Pr344yb28Iq/vXynM5ZYz1NBlQvwID6lcg6OFz1p95wLQdwUzZ\nFkQ7T2smt65CRqYU5wn+OX7GU5OaUqFM9gskX3wQQ6c/T1ChbCnWDfTFVD93/Y/pmVJCw1+gp6WO\nfWn5RQpSMzLJygJNdZVcnetzU5jxWxCEkkd8d7yV//htzffN5BflC4tVvoCL8rh8hHl7r+cifiuW\nU0YWvx0ZUN/xVfy+/078tnknfu/M8TOemtQsD/G79ieO3yVzAcnPKX6XhPEJpuay3BMx0ZF5Oi4m\nKoKAQ/9Rv6UfPUf8ILcv6onyPBYSiQRXz5q4etak96gpXL90lu86NWbN/2Yy/e9NeS6njIGRCe37\nDKV9n6HcvHKRvZtX89es8SyeMY4GrTsyYNxMMjLSaedhleNnXHnwMtYOFbPdf/3yOcb1bIV1+YrM\nWr4NQ5PcLeqVkZ7G/ZvX0dHTw9K2vNy+1+OONTSL11iDz3F+uyAIgpA7b9szRVyRYsLc4NWzT3xq\nno6LjE9hf0gUbdwtGN1EftGpx7HKF5+WSMDbzhhvO2PGNa3IhQextP0zkPkHbrGyt2eeyyljrKtB\n/zp29K9jR1BYHBvOPWa6/3Wm7bxO22oWTGrhTEamFJcpB3P8jCfH1aW8WfYLoF58GEeXJeeoYKbH\n2n5emOrlbh5VeqaUGxEJ6GqpYW+qK7cvLVMqe/ZRK6F9l4g2lvDpiO9zeeZGOq/6svK2gHBkXBL7\ngsNo62XLmBZV5faFxXzgXVR5M3zKmzG+tRsX7kXTau4+5u4KZs2Q+nkup4yxniYDGzozsKEzlx88\nY/3pO0zbcpEpmy/Q3tuOye2qkZGZhdPof3P8jKd/bE2FsgbZ7r94L5qOvx/E0dyQdUMbYKqfu7yL\naRlSboTHoaelhr2Z/FzK1AzZ97lWSe3L4vPoxxIEQRAEofB8qe3ztWfCkGZlcWhkTVzMFd+fLjh0\nl18O3OHCwzg8bQwx0VEHIPZlukLZh8/l+1PMDbVQkUiy7WfJLWNdDfrXtqF/bRuCwl6w4fwTpu++\nybRdN2nrbs6krx1lfSU/Hs3xXCe/96W8ma7C9idxKcw/eIca9sb4eVjI7XMsIyt/KyoRkPUbJaZm\nUEFJn4tDaVkugdtPE7OtQ3qmlBuRiehqqmFvqiO3Ly2jZPerZKcw2+fbtm1jzpw5LGjjQE277J+z\nBEH4OJOb2HD/eRptW7ckJPRmIeZ/LtDLFDurDl6S5bqZ2w9X2zIK++duOcXsf49z/tYTvBwtc8h1\nI5+zwsJE/9PkutHXYXBzbwYYfr8+AAAgAElEQVQ39+bynXD+ORrM5DWH+GH1QTr4ujKtewPSMzOp\n0GdBjuc6+9sgKlgq/l8KefgUgD4LtqHsNLVGLwHg6cYJqKnKYuuFW09oP2MDjuVM2Ti+I6UNFNsF\nyshy3US/ynVjLLfv9ZgwLfUvLNdNIb4vEfFbEApWYcfvd4n7WxAKVnG4vxeP600dd8WcaoIg5M+M\nQX7cffKUtm1aE3I99IP395f1pCIIgiAIX5Bjx46xYeNG/p3QCevS4qH6S3Y34jk/rT/G6ZCHJCSn\nYlXagK71qzKiTQ1UcvEGJfheJLP+Pc7ZG2Ekp6ZjVdqAFj5OfN/eFz1txckFaRmZjFj8H/+euMr0\nHg0Z2qp6tufOS9niyLq0AX8M/ppOszcyYOBA6tWrVyjXld3f/7K2uxNWhsVrwqpQfN2PSWH2oUcE\nPnhBQmomVoaadHQ341tfS1Ry8TI1v8d/bqwMNVnQ2pYe//zLgIGDCvX+/nfjBpxGrEXTNOcJ88Ln\nLSXqPo+2zebFjUAyUxLQNLHCzLcjls2+BUnOg8Pye3xhKF3Tj4SbgQwb8R1NmzZFR0cn54OEXEtL\nz2D19n1UcSqvdCFDgO6tv2LGH6tZtmkXPm6VsChjShlTY84FX5crl56Rwfb9J+S26eloU8ujCifO\nBRP17DllTN8Ohjh98SrDpv3KsjnjqeaSfeKO93m4VsTDtSI/jx3MjoMnWbNtL0+ePsPZwYakkMN5\n+PRFJzUtjYY9RuBZ2Yn9q36V27fvxDkA6lV3L4qqCYIglAgZ6Wkc3b4GW6cq2FSsrLRM3dbd2PTH\nTA5uWo6jmw/GZSwwNC3DreBzcuUyM9I5s3+H3DYtHV2cPWoScu4kcc+iMDR9O8Ay9GIAS6YNY+ic\npTi4VMt1nR1cPXBw9aDX2NmcPbiTI9vW8PxpOOUcnNgUkv2kgdyIfvKQWQPbYmHnyJQV/6Gtqzwp\nRCkjUwL2bOHBjSvUadkZicrb9uD90GAAyljbZXud9LQ0JvdoTPnKHkxbtU9u36UT+wFwrV43X59F\n+DyJNqe8h08iaT1wAhXsrNizYh76usqfcfLbZhRtzpJjypQpIFFhwZLVqKgUj2d1Ifce3L3D3J8m\ncebUcRIT4ilnbUOHrr0YOGJMrn6f14Iu8evMqVw8F0hqagr25R3pPWg4ft2/yVfZd71MTOBr32qE\nPXzAvoAgHJ1dPlg+P1RUZP+XG3m7MmXKFP78888Cu9aXSsRdebmNuwBjf17E3mNnuLRrBepqsuFw\nUmkWyzf/h5O9NTXcs783RNwVBEEQBEEoOUSb+i1TIwM27zlC8I07dGnZGJV3BvcEhd4GwN76beKc\nvLS/3yfa1ML7xPinL4sY/yTkV1pGJusOX6ayXVlcbcsqLdOlvhtzNh5j5f4LeFW0wty4FGaGepy/\n9ViuXHpmJv4B8jFdV0uDGpVsOH3tAU/jEjEzfPu+NfD6Q0b+tZvFI9ri7iCfUO5D3Mtb4l7ekpm9\nv8I/MJR1hy8TEZNARavSPN82Lfcf/j2z+jRlVp+mCttX7r/A6L93c/q3IThbyxYYT0xOpdnEFXhU\nsGTXT9/IlT94SRbr61TO/v1wWnpGvo4XhOImLT2dVRu3UdXFiSqVlCct6NmxDdPnLWTJmo1U93DD\nomwZypqZcvZSsFy59PQMtv53QG6bnq4Ovj4eHA88R+TTZ5Q1M32z79TZiwwZO5WV/5uDR1XXXNfZ\n060ynm6VmTttHNv/O8CqjdsIj3yKs6MDaeGhefj08uZPn8D86RMUti9Zs5Gh43/k8hF/XJxki62U\nMSuNpoYGITduK5R/vc2mnGW210pNTaNe6254uVfm0NY1cvv2HT4OQL1an9ccIUEQBKFkmjJlMqQl\ns7Cda4mcAycUDDEXM2/83EoT+DCB74YPE/0nBSAtQ8q6EzdwtTbFxcpUaZnOtZz4efs5Vh0Nwat8\nWcyNdDEz0OHC3Si5cumZUvzP35XbpqulTvWK5py+8YSnL5IwM3j7+ztzK4JRq46xqH9D3OzMcl1n\ndzsz3O3MmNGlFrsu3GPdyVAiYl9S0cKIZ6uG5OHT50+HGhVYfvgaMQnJmOhrv9m+4+wd1FRVaOtT\n4QNH5/944eOJ+C18DBG/80bE76KjrqqCl70Jp249JTU9E813Fn6sN/sAmuqq7P++ocJxaRlSAEx0\n5XPM3I6MJ/B2NACv08AH3IlmyOqzrBvki4ul4ZuynnYmmBloE/syLU/lcsvNxhg3G2Omt6vK7qDH\nrA98QOSLZBzLliJqoV+ezvW+sOcv6bLoJOXN9Nk6rC56mrlPn5maIaXlgqNUszFm+4h6cvsOX48E\noLZj7ts6giAIwpfnw/F7/6v43UjhuLfxWz5Pnyx+yxbRkY/fZ1g3qHY2cTk1T+Vy6238dnsVv++/\nE7875ulc75PF7xOv4ne9j4jfR17Fb/kFwQ9fjwBE/BY+DTU1dVyqVedywHHSUlPQ0Hy7yHu/Zl5o\naGqxaMdJhePS02T3moGRfML3R3duEHxWVv71Qk3BZ08ya2RvZi3fjoPz2/wZlar5YGxWlhexz/NU\nLrcqVvGgYhUPBv/wMyf37WDv5jU8i3yCTQVnDt9LytO53hf5+CETerfGyr4C89btQUdXcVHT7KSl\npTKiY0Ocqnry64b9cvvOHZPluXCvWS9f9RMEQRAE4eOoq0rwtDXi9J1npGZI5RbLbjDvBJpqquz9\nrpbCca+ffYzff/aJSiTwbgwAr9ewDLwbw5B1QfzTzwsXi1JvynraGmFWSovnrxZAz2253HKzMsTN\nypAfWznz35VINpwLI/JFCo5l9IiY3zxP53pf2PNkui49h0NpXTYP9snzs0+rPwJxtzZk2xD58ZaH\nQ2XPjb4VlL8jFgRByI66qgpeDqU5dSNSoS+r7vRdaKmrsn/C1wrHvfk+19OS234r4gWBt2TvU14/\n6wbcimLw8pOsH9YQl3JGb8p62pemjIHO276sXJbLLXdbU9xtTfmpoxe7Lz1k/ek7RMQlU9HcgKd/\n98zTud4XFpNI54WHKV/WgK0jG6OnpZ7rY9MyMmnxy16q2ZmyY/RXcvsOXZXNffKtqHzOlCAIgiAI\ngvD5S8+UsuH8E1ws9HExV/7OpKOnJXMP3mHNmTA8bQwpa6CFmb4mFx/FvXeuLHZfiZTbpquhio+d\nEQH3nvM0IRUz/bfjx87ej2XM1hAWdq5C1XKlyC03KwPcrAz4sWVF/rsaxYbzT972lfzyVc4nyIaJ\nrjo7giK5Fp5A+2rmcmviXX2SAICtiWysopm+JhpqKtyISlA4z41IWT53KyNthX2vpWZIabXoHO5W\nBmwb5CW37/CNZwD4li+8xdm/JElJSYwcMYyO7mb4uZUu6uoInxEx1jv3VCSwsJ09df+8ypQpk/nz\nz0VFXaUSJy0jk3VHgqlsWwZX2zJKy3SpV4U5m46z8sBFvBwtMTfWf5Xr5olcufRMKf5n5PND6Gpp\nUMPZitMhDxVz3YSGMfLvPSwe1gp3B/Nc19m9vAXu5S2Y2asx/mdusO5oEBHPE6hYzpTnm3/Iw6eX\nN6t3Y2b1bqywfeWBS4xeupfT8wfgbP32+/5R9Av8Zm2kgoUJO6d0U7qGbXbS0jNpNnk1HuUt2PVj\nD7l9By/dAaCOq81HfhLhQ0T8Fj6WiN+5V1TxW9zfwscS93fuFen9/d0IujWtRdemNQvlmkLxdPdx\nFD8u3cbJoJskJKVgXdaEbk1rMbJLM7lc09kJuvWQn5bv4Oy1O6SmpVPBuiyD2zeix9e+SsunpWcw\ndO5qNh4IZMZgP4Z3Ut5fGHzrIT+t2MGZq3dITk3DqowJrepUY2yPFujpaCk9prhRUZGwbGJfPHpN\nyXH9peKRGVcQBEEQhE8qMzOTEcOG0tSrIo2rlS/q6hSp8Jh4jP1m8ij6RVFXpUg8jUuk2aTVxCel\ncHB2bx6uGcOPPRry67bTjF22P8fjL9+NoMnElehpaXB8bj/urhzNzG8a88+RINr+tB7p69kUr8S9\nTKHDjA3cj4rN8dx5KVucNa5Wnq88HRk6ZDAZGRkFfr3MzEyGD/2Wxk6mNKhglPMBAgAR8WlYTg0k\nLC5vA7xLiqeJ6bRefo2E1Ax2D6jMrYneTGpiw8ITT/jhv3sFfvznqkEFIxo7mfDt4EGFdn9/O2w4\npu6NMarSoMCvV9TSYiMI7GtJ6rOwoq5KkUh/8ZRrs1uTkZRA5Um78f7zFjZ+k3iyeyH31uX8kjy/\nxxcmq/YTeRb7gl9++aWoq1LibD9wnGfP4+jRJvuBkVbmZtT1dmPrvmPExcsGNPbv3Iob9x4xZcEy\nnj2P41F4FD1Hz6CUvq7C8TNG9UdVVYV2Q37g5v1HpKSmceJ8MP0mzEFDQ4NK5T9u0R9tLU26tGzE\n3pXzcXYo3oMpjgReQselIRPm/gWAvq4Ok77txcnzwYz9eRFPoqKJT3jJ1n3HGDPnTypXdKBvx5ZF\nXGtBEITP15kDO4h//ox6bbpnW8bU3AoX7zoE7NvGy3jZpIUmnfvx5N5N1i+YSvzzZ0SHP+K30b3Q\n0VeciNBt1E+oqKoyZ0gHnty/RXpqCiHnT/LHhP6oa2hiXb7SR9VdQ0ub2i07M3XlHso5KF9cLK+W\nzxxNWloqo35di7auXrblNLS06TFmFvevB/HX1KFEP3lIakoSoRdO89fkIejqG9Cs++A35a8GHqWj\nix5r504EQFtXj47f/sD186dY/fM4YqKekJQQT+C+bayaMxabipVp1LHPJ/lMwudFtDnljZy5kNS0\nNNb9OvWDC2Lntc0o2pwlU0hICEuWLGHs1JnoKYlHxV1k+GPsjdR5/OhhUVelSEQ/jaRD0zokxL9g\n+6EArj56zvgf5/Dn/DlMHTM8x+P3795Bm4Y10NHTw//oWS7di6J9l55MGDGQpQt//eiy7/tp4mjC\nHj7Iz0fNEz39UoyZMoO///6b4ODgnA8Q8kTEXXm5jbsATXy9uP84nO9++h/P4+KJevacodPmc/32\nff6cPhrJO5OBRdwVBEEQBEEouUSbWv58s8cMIuj6bb6dOp+HTyJJSknl1IUrDJk8HwN9PYZ0b/em\nfF7a36JNLXyIGP/0ZRHjn4RPwT/wOs/iX9Klvlu2ZcqZGlDb1Zbtp0OIS0wGoE9TL249jmb6P4d4\nFv+SsOg4+s3fQiklkz+n9WiEioqEzjPXc/vJM1LTMzh17QGD/7cdTXVVKll/3OJgWhrqdKxbhZ3T\ne1HRqnATIehpazKhcz1OhzzghxX7CI+JJz4phR2nQ5i4Yh+utmX5ponnm/LHr9zDuN00Jq868FHH\nC0Jxt233fqJjntOzU9tsy1hZmlOvlg9b/PcR+yIegAE9u3Dj9l0mzfqV6JjnPHocTrfBozDQVxyf\nMeuH71FVUaVNz0HcvHOPlNRUjgeco/fwcWhqqOPiVOGj6q6tpUXX9q04sHkVzo4OH3WOj6Wro82o\nwX04eeYCk2cv4HF4JEnJKZy9GMzgMVMwLKXPsP5vk+IfPhmIhoUz46bL4qG+ni5Tvh/KicDzfD91\nNk8iInkRn8AW/72MnjKbKpWc6N+jU6F+JkEQBEF4X0hICEv+XsLEBhboa6rmfIAAiLmYYi7mx5nY\nyIoXsc9E/0kB2HXhLjEJyXTxzX58ejkTPXydLNlx7g5xrxbK6t3AlVvhsfy0+QwxCcmExSTQf9EB\nSukoJtmd6lcDFRUJXRb8x+2IWFLTMzl94wlDlhxCQ00V53IflwhfS0MNv5qO7BjXmooWhT8n/rsW\nHpjoa9N30QHuR70gNT2T7Wdv88feIEa19KCcydvnv+MhjzH9ZhFTNgZ81PHCpyPi98cR8VvE748h\n4nfRmdSqMinpmQxZc47ohBReJKcze/c1QsNf0MvXXukx5Yx1sDHVZc+VJ9yIkMWlQyER9F4WQEt3\nKwAuP3xOpjQLd2tjVFUkDFt7nksPnpOanklcUhp/HblFeGwSXWvIxjbktlxeaamr0sHLhm3D6+JY\n9tPMpZiw6TIpGVKW9a2R42LKJ25GUWbYZqZtl41319NUY2xzFwLuRDN5WxDhccnEJ6ez81IYk7YG\n4WJpSM9ahds/KwiCIHx+JrWq8ip+n30nfl99Fb+Vx5Hs4/fpD8Tvc1x6EKMkLsvaCLktl1dv43e9\nTxi/L72K3zVzGb83vRe/XUX8FgpF/3E/kZaawuyRfYh99pTE+BesmP8j92+G0LJbP6XHlLG0xtza\njlMH/Ll/6zppqSmcPbafqYO7UPdr2fjcm1cuIs3MxKmKB6qqavz8fT9Cg86TlppCQlwsW5b/j+iI\nx3zdsRdArsvllaaWNo3adGH+ur3YVHD+uB/SexZOHUlaaipT/1yHjq7yRU1fu3T6CA3tdfhr1gQA\ndHT16fXdJILPnmTRjLFERz7hZUI8x/7byp/Tx+DgXJmWXfp+knoKgiAIgpB3k5o7kZIu5dt1l4lO\nSCU+OZ05e28SGpFAz5rWSo8pZ6SNjYkOe65GciMygdQMKYdDn9Jn1UVaVpUtYhoUFkemNAs3K0PU\nVCSM2BDMpUdxpGZIiUtK5+/j9wiPS6arj+xZKbfl8kpLXZX2HpZsGVwdxzKf5l3fxG3XSE3PZGmv\najk/+9x6hvno//hxl2xRWD1NNcZ85Ujg3Rim7LxOxIsU4lMy8A+KYPKO67hYlKJHdeU/d0EQhA+Z\n3K4aqRmZDF5xiuj4FF4kpTF752VCn8TSq46j0mPKmehiY6rPnsuPuBEeJ+vLuvaE3n8do5WHLQCX\nH8bI+rJsTVBVlTB05Sku3X9GanomsS9TWXzoOk9iX9KtlmxsfW7L5ZWWuiodfOzZNqoJFc0NPuoc\n7xu/4Rwp6ZksH1AXPS31D5Y9ERqB2cA1TNtyAQA9LXXGtXIj4FYUkzedJzw2ifjkNHZeeMCkTedx\nKWeU7c9dEARBEARB+PztuhJFzMs0OnlaZlvG0lCLWg7G+AdH8iI5HYBeNay4/fQls/beIuZlGo9j\nkxm0Lhh9bcX26KSvHVGRSOix8hJ3nr4kNUNKwN3nDNt49f/s3WV4FMcfwPHvSdxDSIAEd9fg7u7u\nUqS4F3ctbSmlWKFAobgUKS0txR1K0aAhaIiQhHhyySX5vwgE7n8RErgc8vs8z7243ZnZ2Uvmfrtz\nszOYqpUUyZaxfg5zExXtyuVg50D399JXYm6iYnrzwlz3DmXsTg+evIgiKjaOc14vGL3zBrYWavpV\nT5xTx9JUxZe18nDO6wXz/7zHs+BoomLjuPQ4mLG7PLC1UPNFjdfz75y4F0j28X8x8/c7wMt+lYb5\nOesVxLT9t1/3q1z1Zeq+2xTPbkOPym7vfE5C38KFCwkKCGBCXfl800PGestY7/SyMVMxsa4rq1bK\n/M+GsO/cbQJCI+lSp1SKadycbKlRPA+/nblFcEQ0AH0bleOudwCzNh0lIDSSJ89D+GLxb8nPddO9\nLkqlks7zt3PPOzBxrhuPR3y5dO/LuW4yNk+NuamajjVLsHd6dwq7OWWojHcxfs1BomO0rBvTFmsL\n/WfU3nT82gMcO8xl6oZ/ALC2MGVip1qcvvmYyesPvZzrRsOeM7eYtO4QJfK40LtBucw4jc+OxO+M\nkfgt8Tu9jBG/pX1njLRvad/pZaz2/SIokGlfpDyn2ufA+/kLbGt/wWPfAGNXxSj8gkJoMHQBIRFR\nHF0xGe8/fmT2oA588+sBxi7ZlGb+/Sf/o/agOVhbmHHip6k82r+Ero2qMuybX/hh21966YPDImkz\nbjEPnvmnWu7lOw+pO3geNpbmnF4znUf7lrBgaGc2HDhFyzHfER+fkOFzzmw2VhbM+KJNmusvpT4q\nTAghhBAfpS1btnDr9m1+/m6AsatidKc8Hhu7Cka1aOcpwqNjWDOyDY42FgA0dS/E2HbVmbX5CAOb\nulPQNeUJ2GZvPopKpeTHwc2xMEv8wb9R+YIMaVGZ2ZuPcu7WE6oWS3woIDgimsaTf6F1laLUL5uf\nhpPXp1huetJ+DOb0rEfV0T+xdetWundPebH692HLli3cvn2HFUNS/iFI6DvzIMTYVTCq748/JSIm\njuXtC+FgmXgb2KiIIyNquTL/n8f0q5ydAk4WBsv/MZveMBd1ll3LtPZ95/ZtSs1aYdDjfChCbp9J\nO9En7On+74nTRFBo4HLU1okTmTqWbYRrixE83jWf7PX6YZG9gMHyZyYTWyeyNx3Owq8XMWLECBwc\nMn/i1k/V6q37MFGr6dQs9QXUerRpzLHzl/l1z98M7dmOrwZ0Q6OJ4de9f7F0w07yuGbny26tsbCo\nwsDJX/PG2ti4lyrKkV9/YN6KjdTtNpyw8EhcnBxp36Q24wd0w9ws9cEVmWniopUsWb9DZ9ukb1Yx\n6ZtVAHRuXo+1CyelO21yRvXtRB637CzbuIvK7QYSFh5Bbtds9G3fjLH9u2BpbvY+T00IIT4rf29d\njUptQvVmHVNNV6dND26cP86xPZto1nMIbQeMJ1aj4djeTRzY8CPOrrlp3O1LzCwsWD55EIo3AlzB\nUu7M+fUfdq5YwNRu9YgKD8PeyYWqTdrRZsA4TMz0B00agyY6kv+OHwRgaKMSyaap264Xg2YtA6Bh\n5y+wc3Lmj43LGNu2MtrYWJyyuVKglDvtB03AxS31CXhb9h2Js1se/ti4jPHtqhIVHkZW11zUb9+H\n1v3HYmae+gLA4tMk15yvRUZrOHj8HADFGnVLNk3vdk1YPmss8O7XjHLN+fGbNGkSJUqXpU0nw/Yp\nGcq5U8eNXQWjWvr1XCLDw1my5lccHBN/R2nQtCVDx05i0azJ9B40jPwFC6eYf+GMiThny8F3K9dj\napbYXvsNGcm9Ozf5fv5MOnTvjb2DY7rTvuno33+wfeM6Grdsy8F9u9/3R5Citp17sOnnlUybNo29\ne/dm2nE/BxJ3X0tv3K1fzZ2tS2ayaPUWijToilKpoFKZ4hz+dQnliqfcVl+RuCuEEEII8WmQa2pd\n/Tu3xNnJgWUbd1OpbX9iYrW4ZcuKe6miTBjUg7xuiRMqp/f6OzlyTS1ekfFPnxcZ/yTeh7UHL2Ki\nUtG+ZslU03WtW5YT1x+w5dhVvmxemTHta6CJ1bLl6BVW7D9HLmd7BjSrhIWpCUN/3KMTv8sXcuPg\n/H4s2n6cxhN/JixKg7O9NW2qlWB0+xqYmXycj1cOa12N3C4OrPz9HLXGrCQsUkNOZ3t6NijPqLbV\nk8b+Gyq/EB+SVb9sxcRETec2zVNN16tTG46eOsfG7XsY3r8nE0cMRKPRsGH7Hpb89At5crkxpG93\nLC3M+WLUJJ2xJhXLleL4vs3M+W45tVp2JTQ8HJesWenYqglfDR+IudnHec0786sRFMibmzW/bmf5\nuk1ERUfj7OREneqV2PLT9+TPk/oiImMG9yNvLjeWrtmIe4O2hIaFkzunK/26dWD8sAFYWnwYY3CE\nEEJ8viZNmEDJHNa0K52xiTE/V/IspjyLmRFOViYMr56dRV8vlP6T92zdkRuYqJS0r5L6AlhdaxTl\n5C1vtp6+zaCGpRndojyaWC1bT91hxV9XyZ3Vlv71S2JhpmbYmiO80X1C+fwu/DmlLYv2/kvTObsJ\ni47F2c6S1hULMKpFecxMVIY9yXSYtvUMyw9e0dk2fdsZpm9L7K9tX6UQKwfWB8DR2pw/Jrdlzs5z\nNJ6zi7CoGPJns2det+r0rlM8zWO9a36RMRK/M0bit8TvjJD4bTwV8zmxe3gtFh7woMqsgyQkJFAo\nuy1r+lWhRZnkJ2BWKhSs+6IqU3Zeoem3R1ArFVTIm4Wf+lTBykzNjacv6PXTaYY2KMLE5iXYP7IO\ni/64Sb+1Z3keGo2NhQkFXWz4qU9lWpVLXCjZwlT1VumMLSomjkMePgC4z/gj2TRdq+RlcdcKKZYx\npF5hcmWxYvWxe9RbeIiwqFhyZbGiR9W8DG9YFAvTD+d6RwghxIcpMX7XZuGBG1SZ9efL+G3Hmn5V\n04jf1Ziy8zJNvz38Mn47vYzfJi/j96mX8bsk+0fWZdEfHsnE5Sr/F7/TTmdsuvH7QLJpEuO3e4pl\nvI7fd6m38O834nc+id/ivSpRvgrfbv6T9d/NpmfdUpCQQO6CRZi+bBM1myS/gIJCqWTmiq0smzWW\nYW1ro1KrKFauElOXbsTC0grPm1eZ2r8DnQeNoe+Y6SzZ/g+/fD+XmUO68SLAHytrG3LmL8zUpRup\n3awdAGYWlm+Vztg0UZGcO5o4B0a3WsWSTdOkY2/GLlieYhmdBowie8487Fq3jIHNKhMRHkY2t9w0\n69yXLoPHYmYh81oIIYQQxuKe14FdX1bm64N3qLbgGAkJUMjFmtW9ytG8VPZk8ygVCn7uXZ6pe27S\n/IczqJQKKuS2Z1XPsliZqrnuHUrvtf8ypG5+JjQpzN6hVfjmr3v0/+U/nodpsDFXU8DZmlU9ytGy\nTOIxLExVb5XO2KJi4vjnVuLiR5XmHk02TddKOfm2Y8pziA+uk49cWSxYfeIh9b89SVi0lpyOFnSv\nnIth9fLLvY8QIkMq5ndm9+iGLNx3hcpTfyMBKJTdjp8H1qJFudzJ5lEqFKz/sjaTt12gyYI/UKuU\nVMiXldX9a2Jlrub6kyB6LjvCsMYlmNiqLPvHNWbR/qv0W3Wc52FRWJubUDCbHav716RVhTwAWJiq\n3yqdsUXFaDl0/SkAFSYnP4dTt2oFWNyzaoplDGlYnFxO1vx0+BZ15+wnPDqWnFms6VGjECMal8DC\n9ON8dkkIIYQQQqTtl7NPMFEpaFs29f6KzhVcOeUZxPZ/n9G/Rm5G1M2HJjae7Ze8WXXyEbkcLehX\nLRcWJipGbr+h86x8uVx27B9Sie/+uU+L5ecJj9aS1caMVqWzMaJuPszUSgOf5dvrVSUnWW1MWX3q\nEfUWnyFGG4+rvTllc9kzul4+cju+Hos5oVFB8jlZ8eu5J6w985jo2DicbMyont+Rn7qXIW+W1H8z\nGlwrL7kcLVl98hH1v7PuBAgAACAASURBVD/7ul+lohvD6ubF4gMaA/+pePHiBd8s+prRNbPjbPPh\nzLH0MZCx3jLWOyPal87KL/8+Z9qUKezdv9/Y1fmkrP3rUuKzWtWTX/vjla51SnPixkO2HLvGl80q\nMqZtdTQxWrYcu86KA+cT57pp4o6FmQlDl+1H8cbTWuULunJwTi8W7TxJ4ym/vJ7rpmpRRret9lHO\ndROlieXv/zwBKDtkWbJputctww9fNkuxjGEtK5Pb2Y6VBy5Sa1ziHEA5s9rRs34ZRrWpJnPdGIDE\n74yT+C3xOyMyM35L+844ad/SvjMi89v3Iib2aka2LHYGPdaH7tSVO8auglF9veF3IqI0rJs2AEdb\nawCaVSvD+B7NmbF6N4Pa1adQrmwp5p+2ahfZs9jz0+Qvku5BhnZsyO1HPsxdt5ceTarjYGsFQHBY\nJA2GzqdN7Qo0qFSSeoPnpVjujNW7UatULB/fBwvzxBjUuEophnVqyMzVuzl7/R7VShd6Xx+DwXVp\nVIXV+44zbepU9u7bl2waRUJCQkIm10sIIYQQBla9ahWcFKGsG5X8A4QfqusP/Vi4/QRnbz0hIjqG\n7I42NK9UmHHta2Br+Xpi5I7ztnL/WRDbJ3dm2obDnL31mLj4BIrndmZOr/qUK5ADgPZzt3DkildS\nPjMTFT6bJ9B+7hYe+r5g/Zh2DFq6j/s+gTz99StUSgXnbz/lm12n+PeeN5HRMbg4WNO4QiEmdKyJ\no83rG8Jm0zbw2D+ETV91YPL6Q1y+70MC4F7QlTm96lMijwsAzadv5PJ9H26vHoGNhe7kzot/O8Ps\nzUfZNaULdUrnM8hnWqDvd5QrkIPtkzrrbL/vE4T78BVM6lyLse2qp5i/0siVaGK0XFk+VGf7njO3\n6Lt4Nz8OaUHX2okPFNzzDuTMrcf0ql+Wf+9603Dyemb1qMfQlpX1yk1P2o9Fn8W/EYg9J0+fNuhx\nqletjGOYFys7fBgLXBiCh28E3x59yvlHoUTExJHd1pQmRbMwqpYbNuavB0v0+PUW9wOj2dS9KLP+\nesj5x2HExydQ1MWS6Y3zUMY18Waz28ZbHPMMTspnqlbyYGolum28xcOgaFZ3KsSw3Z54BUbjObki\nKqWCi4/DWHL8KZeehhMZG4eLtSkNCjswtk7OpE4jgLZrPXgSHM26LkWYcfAhV5+Fk5AA5dxsmNE4\nN8WyJd6YtlvrwdVn4VweVwEbM90BH0tPerPgn8ds7lmUWvntDfKZllh4kbKu1mzsXlRnu1dgNDV+\nuMz4ujkZUSv5SSXeR/6P3aAdnrywzc/J02cNepzKVavjpXWkwKCVBj1ORkQ89uDpvm8JvXueOE0E\npvbZyVK+CW4tRqGysElKd+v7HkT73afoyE083D6LsLvnSUiIx9KtKHk6Tcc6b5nEdIu7EXzjWFI+\npdqUSqsecGtxN6L9H1Jo8Go81wwj2teLiis8UShVhHle5On+JYR7XSJOE4mpnQsOZRqQs9XYpMWA\nADwWtiU64AlFhq3j4dYZhD+8CgkJ2OQvR+5OM7DKWexlunaEP7xKhe8u65wDgPcfS3m8awFFR2/G\nvngtg3ymF0eUwDpvWYqO3KizPdrPi8uTapCzzXjcmo8wWP7MFhcdzpWx5Vm0YC7Dhw832HEUCgUb\nv51Ku8a1DXaMT9mS9TuYuGglRzctpVKZ5CfbECIllsXrsW3bNjp27GjsqgghUrB9+3Y6derEdo9w\nY1clU+1f/wMbF01izqbDFCpTydjVEZlg8egeuNmq2b59u0HK79ixI3Gh/vz63TSDlP+pk2tO8S66\nj56FytbZYO37fXr69Cl58uRhyZpfadq6vcGPd/P6VZYsmMXFs6eIiAgnW/YcNGrRhmHjJmNj+3qA\nVt8OLfC6f5f1Ow4wb+p4Lp49RVxcHEWKl2TynEWULp84eWrv9s04cfjvpHymZmbc9g2nd/tmPHpw\nn+W/bGf0wF48uH8PD+8QVCoVl86f4cdF87j873kiIyNwdslOvcbNGDlxOg6OWZLK6tS0Dk8fP+Kn\nzbuZM2kM1y9fIiEhgTLulZgy9xuKlkj8zaFzs7pcv3yJ83eeYG1jq3O+KxYvZNGsKfyy6w9q1G1g\nkM+0fP5slC7nztoduoPpHnjeo557MUZPnsnQsZOSzRsS/IKyeZ1p1qYDS9du1tl38sgherVryrcr\n19GmU/d0pX3Ti6BAGlcpQ6XqNalUvRZTRw/h4JkrFCqaOQvMHPhtByP79+Dhw4e4uRmmb/jV9Wuk\nx2GDlP85kLgrMmrXwWP0GDMbGVYohBBCfPzk99N3I9fU4l18rr+fyvgnGf8EMv7pXSkUCtaO6UDr\narKYdEYs23eGqev/5q/5/XAv/GEscCY+Ho5tZ3wS8ftV/3rMs1vGrspHa/HKdXw162tO7N9C5fJl\njF0d8RHZue9Pug4aLf3rQgjxgXj69Cl5cudmefsCNC+eJe0MHyl5FvP9k2cxMy5cE0f5764wd+Ei\ng/efrBnckNYVP93nrA1p+cErTNt6hj+ntMW9QMqTewmRHKfeyw3afyLxW+J3Rkn8zrjMjN8/9alM\nq3LSdy9EZnMZtuOT+P1DCJH5EuN3FYnfQhiBy7DtH0X8fjU+4bBXpLGrIoRBzRraHWcr1UfxfLsQ\nQoj0eXU94/NtygtSCiEMY98VHwZu/E/GW4r34tX3uf+qnsauihCfnb3/PqT/6hPyfS6EEEKIJEn9\nLV83MnZVPlorTzxk5u932D+kEhVyG2bMpfg07bvqy8BNVw16fb5kyRKmTBjPpdFlsP6/8cKfEhnr\n/f7JWO+M238jkCG7PHn46JHB538O2jHZIOV/DpbtP8/UDf/w19zeuBdyNXZ1xEfk1VrAEr/fncTv\n90/id8ZlRvwGad/SvjNO2nfGZWb7njp5Ind2LMLa0txgx3nfrnk+Yf66vZy5fo+IKA3ZnexpWbMc\nX/Vsga2VRVK6dl8twfOJL7u/HsnkFTs4c+0ucfEJlMjnxrzBHSlfNC8AbcYt5vBFj6R8ZiZqnh9a\nSZtxi3nw7DkbZ33JgLk/4/nEF9+/lqNSKjl3w5OvN/zOxZteREZrcMliR9OqpZnUpxWOttZJZTUe\nvpDHvoFsmTuUiT9u4787D0kggYrF8jFvSCdK5k98jqbJiK/5785DPHd9i80b5wDw7aY/mLl6N3sW\njaKuu2HmDc3TciTli+Zl10LdOVk9n/hRrsdkpvRrzfgezZPNGxwWSa4Ww2lbx5310wfq7Dty0YPW\n4xbz06R+dG5YBYC7j305ffUufVrU5OJNL+oNnsecLzswvJN+X2+FnlOIjtFyY+sCne27j16k98xV\nrJjQh26Nq73LqWe63Ucv0m/OmpTWX9qhNEalhBBCCGE4vr6+nD1/gU41Shi7Kuly+b4PjSavJz4h\ngb/m9uL+utEs6NuQ7Sdu0Hb2ZrRx8UlpTdUqAsMiGbBkD70blOXGquEcnNMLvxfhdP96J5pYLQA7\nJ3dhSIvERb6vLB+Kz+YJAJip1URoYvlq7V80dS/EvN4NUSoUnLjxkBYzNmJjaco/8/vgtX4My4e2\n5Pfzd2g549ekcgFMTdQEhEYydPnvfNWxJvd+HsWheb3x8g2i9axNBIYlPpjaq35ZojSx7Dr1+gbg\nld2nPXBzsqVWqbzJfiaBYZE4dpib5uued2Cy+b0DQwkKi6Kwm5PevrzZHDBRKbnq5Zvq36VYLmf8\ngiMIjdTobPfyDQKgyBtlF3TNQq/6ZVMtLyNpPxYdaxTnzLlz+Pn5GewYr9p3u1Kf7uRlV5+F03LN\nDeITEtj3RQk8Jrgzu2ledl19TucNN9HGv/7RwUSlJCgyliE779HD3YV/R5dnzxcl8AuPpe+WO2i0\nid8bm3oUZWDVHACcG1WOB1MTvxdMVQoiY+OZ8sdDGhVxZFbjPCgVCk4/CKH9Og+szVUcGFCSmxPc\nWdK2AH/eCqL9eo+kcl+VERihZdSe+4ypk5Nr4935vX9JHgZF0/GXmwRFJn5vdKvgQlRsPHuvB+id\n897rAbjamVEjX/IdZkGRWlynn03z5RkQlWz+ZyExvIjUUjCrpd6+PI7mqFUKrj2LSPFv8q75PwVt\nS2XhzLnzBm/fF86fJUuVdgY7RkaFP7zKjfktSYiPp8Skfbj/4EHerrN5fnYXN7/tTEL86/ioVJsQ\nGxbEvZ+G4FKrB+W/+ZcSE/cQG+LHnR/7Eh+bGE+KjtpEjkaJnTrlFp6j0qoHACjUpsRrInm4eQqO\nZRqRp8ssFAolIbdO47GwPSoLa0pOOYD70psU+GIJQf/9icei9knlvipDGxbI/bWjyNlqDO7fX6Pk\n5N+J9nvIzW86og1PjGEutboRHxNFwIW9eucccH4vZo6u2Berkexnog0P4mw/1zRfUT6eyeaPCXqG\nNvwFljkK6u0zd86DQqUm4uG1FP8m75rfGFTm1tiXbcz2nbuNXRUB/Lr3b/qMn0e0JkZn+6UbtzE1\nUVO0QB7jVEwIIYR4B8f3buKH8X2J1UTrbL9/4xJqE1NyFpCFeoXITHLNKT53e/fuxdLSigZNWxr8\nWNcvX6J9wxrEx8ez86+TXPbyY/rC7/lt2yZ6tm1CnPZ1342JqSkvAgMZ0b87Xfv057THA3b+dQJ/\nPx8GdW+P5mUcXb/zAF8MHQXAiaue3PYNB8DU1IyoiEhmjB9Bg6YtmTr/O5RKJWdPHKVz83pY29ry\n2z9nuPLAn29WrOXv3/fStUX9pHIBTM3MCAp4zvgh/RgxYRoXPZ+x+5/TPPK6T/dWDXkRmNiH2qX3\nF0RFRbJv5za9c96/axs53HJRrXa9ZD+TF4EB5HMwSfN1/96dZPP7eD/hRVAgBYoU1duXO19+1CYm\n3LjyX4p/k1eD5xUKhd4+ewdHAG7duJbutG+aOmYo2jgtMxZ+n2I9DKlhs1ZYWFiyb98+oxxf6JK4\nK4QQQgghxLuRa2oh3g8Z/yTjn16R8U8iM2w5eoUBi3fpjO8H+O/eM0zVKorkdDZSzYQQH5ON2/fQ\nc8g4ojW6z8v8e+U6piYmFCtUwEg1E0IIIcT7sHfvXizN1DQq4mjsqhiMPIupT57FNC5rMxWNC9uz\ne6csiPsh2HrqDgNXHkITG6ez/fIDf0zVSoq4frrfj+LjJfFb4rfE78wn8VsIIYQQQgghhBBCCCGE\nEEIIIYQQQgghhMhc2y89Y8iWazpjNgGuPAnBRKWksIt1CjmFMJ7fdu2kcWF7rM1Uxq6KwchYb30y\n1tu4Ghd1xMJULfM/fyC2HLvGgCV79Oe68Xw1143+WrFCGJvEb4nfEr8zX2bFb2nf0r6lfWe+TGvf\nu3fRrFoZrC3NDXqc9+nynYc0GDKf+IQE/lk2kUf7lrBoeFe2/n2WVmO/Qxv3RltRqwgMCafv7NX0\nbVGL2zsWcejHCfgGBtN16jKiY2IB+G3RKIZ1agjAja0LeH5oJQBmpiZERmsYt2QzzaqVYcGwzigV\nCo7/d5umI77G1sqCoysm83j/D6ya2I/9Jy/TbOQ3SeUCmJmYEBAcxuAF65jYpyUP9izmyPJJ3Pf2\np8WobwkMSVyfqU/zmkRFx7Dj8AW9c9515AJuLo7ULp/8moiBIeHY1v4izdfdx77J5n/qH0RQaDhF\n8mTX25fP1RkTtYordx6l+Dd5vQ6S/j4HWysArt9/krStUK5s9GlRM8Xy3lQ8nxv+QSGERuh+13h5\n+wNQJHeOtyrnQ9K8elkszU1TbN/KTK6PEEIIIQzs2LFjqJQKapXMY+yqpMuUXw7hYG3ButHtKJAj\nC1bmpjQqX5BpXevwn+cz9py9pZM+NFLD0JaVaVCuAJZmJhTNlZW+jcrj+yIMj0f+qR5LoYDA0Eia\nuhdmUuda9GlYDoUCZv56BHsrc1YMbUn+7I5YmZtSvXhupnevw83H/uw6fTOpDJVSgSZWy/BWVahe\nPDcWZiYUy+XMzB71CAqLYuux6wC0rFwURxsLfj1yVacO97wD8XjkT7c6pVEmd2ULZLGxJGjH5DRf\nBV2zJJvfPzjxJjaLrf6NrlKhwN7aAv/g8FQ/q3Htq2NuqubLpft4FhhKjDaOI1e8WP77edpULUa5\nAh/fBbKh1C6ZF5VSwbFjxwx2jGPHjqFSKKiez85gxzC2mQcfYW+h5qeOhcjvZIGVqYr6hRyYWD8X\nV7zD2X8jUCd9WHQcg6rloG5BByxNlRRxtqSXuwt+YTHc8otM9VgKhYKgiFgaFXFgfN2c9HB3QaGA\nuX8/xs5CzZI2BciXxRwrUxVV8tgyqUEubvtFsvf66zqolAo02ngGV8tBlTy2WJgoKeJiyZSGuXkR\nqWXHlcTvo+bFHHGwVLPlP93vJ8+AKG75RdKpbFaUyX8V4GipxntmlTRfBZwsks3/PCImqZz/p1SA\ng4Wa5xGxevveV/5PQY18dqgUhm/fCqUKu6LVDXaMjHq0bSZqK3sKDf4Ji2z5UZlZ4VC6PrnaTST8\nwRUCL+7XSR8XFUaORoNwKFUXpZkllq5FcKndi5hgPyKf3krhKIkUCgWxYUE4lGlEzjbjcandAxQK\nHu+ci9rKjgL9lmDukg+VmRW2hauQq/0kIp/eJvCNBY0UShXxsRpyNBmMbeEqKE0tsHQrQu4OU9CG\nv8D/9A4AHCs0R23tgP/JLTp1iPLxJPLpLbJW7wSK5LtN1NaOVPnZO82XRfbkF4GICX2eVI7+h6BE\nbeVA7Ms0hshvLHbFa3H+7Bk0/7dohsh8dtZWbP/jCCNnL8EvIIjQ8EjW7TzA7r+OM6BLK2yt9a8f\nhRBCiA+dpbUtp//YwZrZowgO8CMqPIzDO9dx9q/faNSlPxbWNsauohCfFbnmFJ+7o0ePUrlGbUxM\nTQ1+rDmTx2Lv4Miy9VvJV7AQllbW1G3UjPHT5nL10kUO7Nmhkz4sNIT+Q0dTu0ETLC2tKFS0ON37\nDsLP9xm3b1xP9VgKhYLAwOc0aNqS0ZNn0q3PABQKBQtmTMTO3oFvVqwlb4GCWFpZU7l6LcbPmMud\nmzfYv+v14gAqlQqNJpqBI8ZSuXotLCwsKVysBBNmzudFUCC7tmwEoEnLdjg4ZmHHpnU6dbh/7w63\nPa7ToVsvlMrk+24csjjh9SI2zVf+goWTzR/gn9iP65hF/wEKpVKJvYMjAf5+KX5O9g6O5M6Xn3/P\nnSE2JkZn38VzpwEIfP483Wlf2btjM3/s2cnMr5fg6JQ1xXoYkompKVVq1uHIkSNGOb7QJXFXCCGE\nEEKIdyPX1EK8HzL+KZGMf0LGP4lMYWtpzq5TNxi76gD+weGERWrYcOgSe8940K+xOzaWZsauohDi\nI2Bna8O2PQcYNmEWvv4BhIaF8/OmHez6/S8G9e6CrY1MlimEEEJ8zI4eOUzVPLaYqFJ4aO8TIM9i\n6pNnMY2vVgE7zpw9L/0nHwBbS1N2n7/HuA3H8Q+JJCwqho3Hb7L3wn361i2JjYXhxzcKkV4SvyV+\nS/w2DonfQgghhBBCCCGEEEIIIYQQQgghhBBCCCFE5rE1V/PbFR8m7L6Jf5iGsGgtm84/Zf81P3pX\nzYmNuf6YRiGMKTo6mjNnz1G7wKe7Zh7IWO/kyFhv4zJRKaiW15Yjh/8xdlUEYGtpxq7THoxdfTBx\nrpsoDRv+uczes7fo16g8NhYy1434sEj8lvgt8ds4MiN+S/uW9i3t2zgyr32fpUHFEgY7hiFMXLYN\nBxsrNsz8koI5s2FlYUbjKqWY0b8dl2494LejF3XSh0ZEMbxTIxpWLomluRnF8rryRas6+AQE43H/\naarHUgABwWE0q1aWKf1a069lbRQKBdNW7cTexoqVE/tSIKcLVhZm1ChTmJkD2uHh9ZRdRy4klaFU\nKoiOiWVkl8bUKFMYC3NTiudzY/bADgSFhrP54BkAWtWugKOtNRv/PKVTh7uPfblx/yk9mlRHmUKD\nzWJnTeixNWm+CuXKlmz+5y9CX5ajv+aiUqnAwcYK/5dpkuNga0U+V2fOXfckJlars+/s9XsvjxGW\nYv7UjO/ZHDNTEwbM+xnv5y+IidVy+KIHP24/RLu67pQvmjdD5RqTqYmammWLcOTI4WT3Jz+rrxBC\nCCE+WteuXaOgmzMWZibGrspbC4vScP72U2qUyI2ZiUpnX72y+QC4dM9bL1+tkroXZy4OiRMt+wSl\nfTGojYunTdWiSe+DI6K5fN+HasVzY2aie2NY++VxTt14qFdO3dL5dN5XL54bAI9HiYuAmpmo6FSr\nFP95PuPW49eLEuw65YFCAV3rlE6zrhkVHZN4sWyqViW731StIipGm+y+V4rlcmbD2PZcvPuUEoOW\nkq3LAtrP3ULVorn4flDT917nj5mFmQkF3Zy5fj31xXLfxbVr18jvYoOFyad5GR+miePi41Cq5bXD\nVK17jnUK2gNw2TtcL1+NfLodic7WiRMQ+obF6KX9f9r4BFqWeL2gb0iUlqvPwqmSxxaz/6tDzZfH\nOf0wRK+c2gXsdd5XzWsLwM2XHXemaiXtS2flinc4t/1fd+btuR6AQgGdyjqnWdeMio6NT6yDKvn/\nGxOVgqiXaQyR/1NgYaIkv4uNwdu3TY78KE2T7/w0lrioMELvXcSuSDWUat3JPe1L1AEg3OuyXj67\nYjV03pvaJ/6PxwT7pnnMhHgtThVbJr3XRoYQ/vBq4sJGJro/WtsVqwlAyO3TeuXYF6+t8962SFUA\nIp/eBECpNiVr1faEP7hCpPftpHQBF/aAQoFz9U5p1jWj4mOik+qQHIXahPiYKIPlNxar3CXRamO5\nfft22omFQbWoV42tS2Zy98ETSjfvTa7qbfhxwy5mj+rPgnFfGrt6QgghRIa412vB2CWbefbgLiOb\nl6Vf9dwc2LCMbqNm0XPcfGNXT4jPjlxzis/d1WvXKFaqjMGPEx4WyqXzZ6hcozamZrr9JjXrNwTg\nyr8X9PJVq11P571ztsQBPn6+z9I8ZpxWS/O2HZLehwS/4PrlS1SuXgszM/Nkj3Pu5DG9cmrUbajz\nvkqN2gDc9kjsgzM1M6NN5+5cvXSRu7c8ktLt37kVhUJB+2690qxrRkVHJ/armJgk3/diYmJKVFTq\ngzYnzlqI77OnjB7Um8cPvAgLDWHn5g1sWrsSAG1sbIbS+vp4M2P8SBo2a0Xzth3f6TzfVbFSZbhm\nwD5T8fYk7gohhBBCCPFu5JpaiPdDxj+9JuOfZPyTMLxmlYqwYXwn7j0LoOLQHynY+2tW/H6O6T3q\nM7tPI2NXTwjxkWjZuB47fl7K3fsPKFmzKTlKVOWH1b8wd9Jovp7+lbGrJ4QQQoh3dPXKZUpk+7D6\nKd4neRbTMORZzHdXMrsVsVqt9J98AJqWy8svw5rg6RNM5QmbKTxsLSv/usq0jpWZ1aWqsasnRLIk\nfkv8zgiJ3+9O4rcQQgghhBBCCCGEEEIIIYQQQgghhBBCCJF5Ghd3Zm3Pstx/HkGNRacoPvMoP516\nxOSmBZnRvLCxqyeEnlu3bhGr1VIiu5Wxq2IwMtbbMGSs97srkc2Ca1evGLsaAmhWsTAbxrbn3rNA\nKo5YScG+i1lx4ALTu9dldq/6xq6eEHokfkv8ziiJ3+/O0PFb2re074yS9v3uMqV9x2opVTCXwY7x\nvoVFRHHuhic1yhbGzESts69+xRIAXLzlpZevToWiOu+zZUlsVz6BwWkeUxsXT9u67knvg8MiuXzn\nITXKFMbc1EQnbe3yxQA4cfmOXjn1KhbXeV+zbBEAbng9BcDMRE2XRlW4dOsBNx94J6Xbefg8CoWC\n7k2qpVnXjIrSJK5RZKpWJbvf1ERNVHTq321zvuyA9/MXDJj3Mw+ePSc0IopNB0+zZu8xALTauAzV\nrXg+NzbNHswFj/sU7TAOpwaDaDNuMdVKF+KHMT0zVOaHoFSBnFy/ejXZfepktwohhBDio+Xj40MO\nR2tjVyNdfIPCiU9IYPuJG2w/cSPZNN4BoTrvVUoFjja6EzkpFQoA4uLTvnlTKMDFwSbpvU9gGADZ\nHPQ/u6z2iZ0UPkFhOttNVEq9OjhYJ773D4lI2ta7fllW/H6eX49eZe7LDvfdZ25Sq2RecmbVvdl/\nnyzMEi/1YlK4OI7RxmFhmvrl4LYT1xm+/HcGt6hE34blcXGw5voDX0b99Cd1v1rLn3N64WRr+d7r\n/rHK7mCNj4+Pwcr38fEhh/WnewnvFxZDfALsuvqcXVefJ5vmWYhG571KqcDBUvczUSZ+FRAXn5Dm\nMRUKcLZ+fbPt87KjzcVGf4ERp1edcaG6N6xqlX4d7C0S3weEv16kt3sFF1af9WHrf/7MaJwHgH03\nAqmRzw43e90FXt4nC5PEm++YuOS/G2O0CViYJN8h9j7yfyqyW6sN3r7V9jkMVn5GxQT7QUI8z8/u\n4vnZXcmm0QTpLhKuUKpQWzvwfxsBSIh7iw4bhQITu9cdyTEvEj93U3sXvaSmtk4v0+gusqRQqfXq\noLZO7NyODQ1I2uZSszs+f6/G/9RW8nSaAUDghX3YFa2BWRa3tOuaQSqzxOuFeG3yHWAJ2phUF8Z6\n1/zGYuqQHUj8fy9durSRayNa1KtGi3qG6wQWQgghjMG9Xgvc67UwdjWEEC/JNaf4nPk8e0YO15wG\nP46frw/x8fHs2b6JPds3JV8X76c671UqFQ6OWXS2KZSJfTdxWm2ax1QoFGR1yf66Dj6JfUPOLtn0\n0jplTezP8fXx1tmuNjHRq4O9gyMAAc/9krZ16d2ftcuXsP3XdUyZ+w0Av/+2nWq16+GaM3eadc0o\nC4vE3z1iY5Pve4mJ0SSlSUnDZq1Yu2M/38yaQoPKJbGysqZa7XosW7+NptXLYWVjnaG0E4YNAGD2\ndz++62m+s+w53PA1YJ+pSB+Ju0IIIYQQQrwbuaYW4t3J+Kc308r4Jxn/JDJDs0pFaFapiLGrIYT4\nyLVsXI+WjesZuxpCCCGEMAAfHz9ylPzw+ireF3kW0zDkWcx3l9028W8v/Scfhqbl8tK0XF5jV0OI\ntybxW+J3Rkj8i7/vxwAAIABJREFUfncSv4UQQgghhBBCCCGEEEIIIYQQQgghhBBCiMzVuLgzjYsb\nboF3Id6nV+t15bDTH4P8qZCx3oYhY73fXXZbU3x9Zf7nD0WzioVpVrGwsashxFuR+J1I4nf6Sfx+\nd4aO39K+E0n7Tj9p3+8us9q3m7OjwY7xvvkEhhAfn8C2Q+fYduhcsmm8/V/ovFcplTjaWutsU7xs\nsNoU/r900ioUZMtil/T+WUBi+S5vbHvF2cE2sZ7Pdetgolbp1cHB1goA/6CQpG19WtRi2Y5DbPzj\nFPOHdAJg15GL1C5flJwuumsuvU+W5onfMzHa5Oe/1cTGYmGeehxoXr0suxaOYObq3bj3moqVhRl1\nyhdjw4wvqdpvBtaW5hmq29a/zzLk6/UM7diQL1rVxsXRjmuejxnxzUZqDZrD30sn4GRvk6Gyjck1\nqwM+vn7J7lMnu1UIIYQQH63IyEgsTT/OEN+jXhmWDGqWKcdSKhSoXt1ZvyEhmXvspG0K3fTK5PK/\nUf4rBV2zULVYLnacuM7M7nW5+dgfz2eBTOhYM6PVfyvZHBJvCgJCIvX2aePieREeRZWiuVLMr42L\nZ9yag1QumpPp3eombS9f0JVlQ1pQa9walu49y8weMvH1K1ZmasLDww1WfmRkJBYfZ/NOl67lnVnU\nMn+mHCvl7wL9L4NX2/4/tVKhn//Vl8GbRRdwsqByblt2XwtgSsPc3PaL5H5AFGNqG27BFQAXm8RO\nwcDIWL192vgEgqO0VEqmk/B95f9UWKoxePvmA1y85hXnml3J32tRphxLoVCiUKr0tqfWLv8/RisU\nyXTkJsXz1/ssshfAtlBlAs7uJneHKUQ+vU2U733cWo3JcP3fhold4sJOsWGB+tWM16IND8a0UCWD\n5TcWlVliB2VYWJiRayKEEEIIIYQQQhhWZGQkFpaWmXa8Tj37Mn/Jqkw5llKpRKVKX9+NQu/3Ff2+\nm1dplW/03eQvWJiKVWuwZ/tmJs5cwO2bN/C6d5cRE6a90zmkJWu2bAAEBugP7ozTagl+EUTFqjXS\nLKd2/cbUrt9YZ9vdWx4A5MqTL91pd/y6nhOH/2bp2s1kdc72lmdjOJZWVgbtMxVCCCGEEEIIIcTH\nRcY/vSbjn2T8kxBCCCGEEEII44uMjsbSVP/+/FMjz2K+X/Is5ruzetnupP9ECJEREr/fP4nfEr/f\nhsRvIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCJGSiIgIACxNZKz3+yRjvWWs99uwMlURHhll7GoI\nIT5CEr8NQ+K3xO+3Yej4Le3bMKR9S/t+G5nWvs0/vs+xV7MaLB3XK1OOldhek1vzSD9tAimsmZRM\ne01aM+mNsgvlyka10oXYdugcswd1wMPrKfee+DKxT8t3OYU0uTjaARAQrP/crzYunhehEVQrZZ9m\nOQ0qlaRBpZI6224+8AYgT46s6a6XNi6e0d9vokrJgswc0C5pe4Wi+VgxsS/Vv5jJkq1/MXtQ+3SX\nbWxWFuaEv2yD/0+dyXURQgghhIElJCT8/3oAH7wcWWxQKhQ8eR5itDq4OtmiUIDPC/2LVL+X29yy\n2Ops18TGERqpwdbSLGnbi7BIAJztrHTS9m5QjgFL9nDs2gNO3HiIg7UFzSoWTrVOgWGRFOy7OM26\nn/9+EAVds+htz+Zgg7O9Nbef6i9Wetc7AG1cPOUKZE+x3CcBIYRHxVDI1UlvX8EcWV6Wo78Iw+dM\noUi+s+V9+Rjbd3pktzVFqYCnwRqj1cHV1gyFAvzC9DuI/MMTt+WwM9PZHqONJyw6Dhvz1x2aQVFa\nAJysTXTSdq/gwtBd9zhxP4TTD0Kwt1DTpKhjqnUKitRScuHFNOt+fFgZCjjpL6bjYmOKs7UJd/31\nO308n0ehjU+gjKt1iuW+a/5PRWa0b/0uWeMzdcwOCiWagKdGq4OZoysoFMQG++ntiw3xf5kmh872\neG0McVFhqCxskrZpw4MAMLHVjWsutbtz76ehhHicIOTWadRW9jiWa5JqnbThQVwcUTLVNABl5hzH\nInsBve2m9i6Y2DkT9eyu3r6oZ54kxGuxzlMmxXLfNb/RvAxihmxLQgghhBBCCCHEhyCxL9fwfT3Z\nc7iiVCrxfvLY4MdKsQ6ubigUCvx8ffT2PffzSUrzphiNhrDQEGxs7ZK2vXiR+HuDk7OzTtquffoz\nsn9PTh77h7MnjmLv4EijZq1TrdOLwADKp/L7xyuHLtwgf0H932pcsuUgq3M27t2+qbfP8+5t4rRa\nSpWtkGb5ybl0/iwAFSpXS3fa2x7XABjWtyvD+nbVS9+4amJ/0L3nUajUhh8OpFAopJ9HCCGEEEII\nIYQQSWT8U8pk/JM+Gf8khBBCCCGEEMLQEhISPsCeivdHnsVMnjyLaXyvhs1J/4kQIiMkfhuexG99\nEr8lfgshhBBCCCGEEEIIIYQQQgghhBBCCCGEEEKIlL0aYyrr5hmWjPXWJ2O9E2dzknHeQoiMkPid\nOSR+65P4bfj4Le07c0j71iftOzPb98fTwF2zOqBUKnjsF2i0Org5O6JQKPANCNbb5xsYAoCrs4PO\ndk2sltCIKGytXreVoNBwAJwdbHXS9m1Ri35zVnP0Xw+O/3cbB1srWtQol2qdAkPCydtqZJp1/3fD\nHArlyqa3PbuTPS6Odtx64K23786jZ2jj4ilXJG+a5Sfn/I37AFQpqT/PbFqe+AUSHhlN4dz660EV\nzOmSVL+PUWpr1ht+9SchhBBCiDRYmZtSpWhOTns8wj84HGf71zdfZ289YdSqP1gxrCVl86e9cOf/\nU77lpPu2lma4F3LjtMcjomO0mJu+vkw6ctULgLpl8unlO3bNi5aViya9P3njEQBVi+fWSdeiUhEc\nbSzYfuI6pzwe06FGCcxMVKQmi40lQTsmp5omLe2rF+fnvy4REBqJk61l0vbfTt9ErVLStlrxFPO6\n2FtjZqLi1pPnevtuPU5cfCJXVju9fUJklJWpikq5bTnzMBT/8Fic3+hwOv8olK/2e7GkbQFK50h/\nB40yaQKq1NPZmKso72bDmYchRMfGY26iTNp3zDPxxrx2AXu9fCe8gmlWLEvS+zMPEm/Yq+TWbSPN\nijky9U81u68958yDUNqWcsJUrSQ1jpZqvGdWSb3iaWhdyolfLvgRGBFLFqvXn+veGwGolQpalcyS\nSu53zy8+XiozK2wLVSL0zhliQ/wxsXu9GHfo3fN4bfiKAl8swTpP6fQXrnj1v596w1RZ2GCTvzwh\nd84QHxON0tQ8aV/wjWMA2BevrZcv2OMEWSo0S3ofcvsMAHaFdduTY/lmqK2n8vzsbkLvnMGpcluU\natNU66S2dqTKz/odW+nhVKk1fkd/ITYsEBOb120o4OJeFEo1WSq1Mmh+IT4Xno+8mf79Gk5cvEpY\neAS5X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tZm57HzH1Q+PV0xdjPgm9EfVP7fUtqyLKs2bSu0nEOzlvhGpam83rqD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Yxt3WqX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\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6S2MDIrdOzfXHxcEyx/d/6ylvdp/x4dvPWmNlIgmNxJuVmJLG6XtPaeZihmtxYxTamjiZ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\netiYGWFmpAIgLTNb7/FpGVmYGaueSVuFMCSZ6y3E01MqFKz+7HU++O4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ftY1cMJgOCIWOpULFpi9oiYRAZ38qX/q3U4eSWk2NoqxAM9fr1AQGgCZ8fWw+KRD3G+3hPMggMh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\nnD3FmhVL6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1bHYs3JL0vj7w79J9d3LeaIxNto4qdd8Pf14EBAeN6VXzPzRn/OiT1/ZX3e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q+5hbj0ar5d1v1/FRh/qc/24wGye9QUxiKh0n/Eps8sMDNVWWlqSqNQz/cQuvhIbweZ9WKBUK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i2B0WnqGwL1apso83eqdvvtY1KzOeobzeiu9nw0oi1N6phjamiAgb4eEcllnwvo6UGv5nWY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\neYHvM4DnyMnJ0cMPPqCdu3ZpUNiViut2lfpe11r+DeqbT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Tp04hISEBIpEIBgYGyMrKym23fv16jBs3TsCkRERERNrBzc0NZ8+exdq1azFhwgSh45Ce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48fJPzRQww0GmrVa8To6f/DqUHuhUuebmfY/OVybnpdIj09HZsKFenWfwjvjJmCSpXz/9DE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\n29ubDh06MGHCBGbOnKmX2IyMjFi9ejVjx47Fy8uL9PR0G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bCu0BCVhZ1GuYVbVQCSwu9B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\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OzNnlQq/vj6Ohrkazahb89kkn9LU1uBMQxuh155jUsz6zBjTJ3nbrGjwOi2X3NW/W//UP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\nyy+/pFWr+w9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i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\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OudvxqRrOhicRUNEW9b9yaPngPAdD4/Xqae2rO6a6WSXtQkyXHiwyZGaipH89F86EJXHl\nXt74zk3no1EoYFAD4y1QnJaZrc1Blf9UuKYqBakPYoxR/lnQqLw1sfEJMn/LE6BL3XL8OKoZQZGJ\nBM7ZTo0PtvDNnutM7VmbGX3qlnV6Qgiho2sjH34e142giFj8319Btde/4+vtZ/hwUCAzh7YwXIEQ\nQohiOXnyJJ5ONnjYPT3PzYlpGo6HxhHo46j/HFzNBYDTt/THx7as4qyz7WqrHT8XGZ9m8Jya7Bx6\n1c9rO4xPzeTsnXia+TjqPQe3eHCeg0G6i+0+mt9DgT7aRSwvRWjb5cxMlAxo7Mnp2/FcuZvXVvf7\nmXAUChjs52Uw15LKe47Nf2FO7XNs0cbChkSn4DFhG3Vn7mLRzutM6VqNd9r76sTU8LDhh5ENOBEa\nR8PZu/GetJ0hy4/jX9mRBf1r/7eLeQp42JlTztHaqOP/Tp48iaejFR62+Y+NfNpJm5hxSJvYf+dh\na0Y5B6unZnzvseMnqFSnidHPk5qcSNDZI1Rr3AKTf82fWruZtq9U8AX9+VNrNG2js23nrJ0/NS7K\n8Pyp2Vka/Dr2zd1OSYgj9NJpqjVugamZ7nefmk1bA3D1hP78qbWatdPZrt5YO+b+znXtPIsmZmoC\nug8h5MJJwoLy5k89+td6FAoFgT2HGcy1pDLTtWPcVQXNn2piljvHakEGvD2b2Mgwvp/6ClF3QkhN\nSuDgH7+wZ91yALI0hb8TK4iXby1eX/gLN84dY0KXGoxp6sziN/pQtWEgI6YtLVGdJVWxtp9R508V\nRdelric/jn7QVj37L2pM+oNvdl9naq86zOhjvPe/QgghxL8FBwcTG59A4/I2ZZ2K0chzs3HIc/N/\n16CcOadOHDNa/XJ/y/1dUnJ//3eP5f6Oi6dJVU+jnaO0ST9v45B+3o9fI18PTp88UdZpCCGEEEII\nIQwwMRwihBBCCCGEEEIIYwoNDUXtWslw4GOWERcJOdlEHd5A1OEN+cak3w/X2VYoVZhYO/CvnQDk\nZBVhkKFCgaldXkePjFjtIBAzeze9UDNb5wcxugsuKlQmejmYWGs7n2QmROfuc2s5jIgd33HvwG9U\nHDQdgJhjf2BXowVqJ+MNyFSpLQDI1uTf+SZHk4HSzMJo5cuKxYP/4yEhIVSq9OT9f39W9erWmV7d\nOpd1GkL8ZzdDQ2nVd6TRzxMdGUFOdjZ/b1rN35tW5xtzL+KOzrZSpcLWwVF334PPvqwswwPsFAoF\nTi7uj+Sg/Wx1cnXXi3V01n5GRt/V/fw1MTHVy8HGXvtZGBsdmbuv25CXWf/DMv5a+zOvTf0EgD1b\n19MwsC1unt4GzMCPNwAAIABJREFUcy0ptYUlAJmZ+X92ZWak58YUJLBjD+b9sInvF37ISx0aYmFl\nRaPAtnz0xS/8r2sTLK2s8y23Y+MvZGVp6Db4pf92EY+BZyVfdm361Wj1h4SEAODr62sg8ukVHh5O\ndnY2q1atYtWqVfnG3L59W2dbpVLh5OSks0+p1N7DmiIMklUoFHh45E0oEham7dz56L6H3NzcdGIe\nMjU11cvB0VF7T0dG5t3Dr7zyCosXL+aHH37g008/BWDNmjW0b9+eChUqGMy1rFhaau/vjIz8/wak\np6fnxjyrqlSpwooVK8o6DSGEEEIIIZ4ID59PK3sab9BnaYuIiSc7O4c1O4+wZueRfGPC7sXqbKuU\nShxtddsrFErtRI2aLMMDRhUKBe5OeYN7w6O19bs52enFujpoB9xGROnmYGqi0svBwdYKgHv38wby\nvtSjFV+s28nKPw8w741BAGzYdZzWjWpQ3k33ebU0WZprBytnaPJ/f5SemYmFeeETIXZv3oANn4xj\nxncb8Rs5DSsLNW0a1WTF9NdoNmo61pYlmyj1tx2HeWP+T7w5sCOje7XGzdGOc0G3GLdwJa3GzGbH\nskk42z99A9J9vNz47R/jDfZ7eH+bu1Y02jlKQt55Gsfz+s4TwNy1cu7/d1G2enZsQ8+ObQwHCiGe\na92aVKNbk2plnYYQQgghhBDiOdS7d2969+5d1mkIIcRzSdqEhBBCCCGeLKGhNxnq51/WaRTL3ftJ\nZOfksHbfBdbuu5BvTFh0gs62SqnA0Ua3v4tSoe03mJVdlH6D4OaQ1y8tIka7sIC7g/7YSRd7bV/A\nfy8+YKpS6uXgYK3dvhefnLvvxfYN+GrrUVbtPsuckdqFQDceukSrOpUo76LfT7G0WKi1014W1G8w\nQ5OFhVnhU2Ou2XeesV9u5fUeTXm5YyPcHKw5H3KXd77dRtuJP7Bt9kicbZ/tsWpFVdlDO0bRmPM7\n3Lx5k4HNnQ0HPqUiEzPIzoENZ6PYcDYq35jw+HSdbZVSgYOl7v/jB12IycrOMXhOhQJcrU1ztyMe\nLArkZqPfp9b54cJBCbr98ExU+jnYW2i3o5Myc/cNa+zGd4cj+O3UPaZ3rgjAHxdiaFHZDi973UWD\nS5PFg8VXMgroU52hycHCNP/Fe0qj/LOgkqP2b7vM3/Jk6FK3HF3qlivrNIQQoki6NvKhayOfsk5D\nCCGeC6GhoVRyejLHRhUkMiGd7JwcNpwKZ8Op8HxjwuLSdLa1z8GmOvsetolpivocbJP3DBoRr63f\nzVb/udTF5uFzsG4Opir9HOwfbEcl5T23D2/qzbf7Qll9/A4zemgX69x8JoKWVZzxcjDev9XDZ9SM\nrPx/Hxma7NxnXUMqOVsSsaAL8amZHLpxn8mbLrHpTARrX/HDzkJ7zetPhvHuuvO82rISIwO8cbNV\ncz4sgfc3XKDz0kP88YY/TlaFj9192lV2tjLq+L/Q0FAqORqv7aSsSZuYcUibWOmo7GT+1IzvDQ0N\npXbnYUY/T3yUdv7UI3+u4cifa/KNib2rO++hUqnC2k537tKHc2FkF3H+VLtH5k+Nvaf93mDnrD+O\n3tbR9UFMhM5+lYmpXg5Wdtpx9fEx93L3ter3Ejt/+YIDm1cy6L15ABzfsYEaTVvj5FHeYK4lZWau\nfdeUVdD8qZnpmJkX/v2hQZvujFu2gY2fz2BaPz/UllbUbNKG1+avYPqgZpgXMH+qIYf/7zd+mvEG\nHYe9SesBo7FzduPW1XOsnD2O2cNaMemHHdg4PJ53N27ePpzY9ttjOZcwrEtdT7rU9SzrNIQQQjzn\nHn5fr+hYsnm/ngby3Gwc8tz831V2smDDQeM9M8v9rSX3d/HJ/f3fPa77u5K7o4HIJ4f08zYO6ef9\n+Pl4OLD2YP5zHAshhBBCCCGeHIU/CQkhhBBCCCGEEMLo4uPjUVg8uQtGurYcis/IBY/lXAqFEoVS\nfzBiTo5+R5XcfQ9ejj9ah37ww4N5xyw8fLGt6k/04Y1UGDCVlDtXSL17A69e75U4/6IwtdMOTslM\njNFPM1uDJikOs6pNjVa+rKgstf/H4+LiyjgTIcTTKDExAWtb43Us+reug17kvXlfPpZzKZRKlKr/\n+Nmn1P/sexj76DFvn2rUbdKcvzet5pUP5hBy5SK3g68xctyU/3IJBjk9GKwZFxOtdywrS0NiXCzO\nTQxPcNakdUeatO6osy/k2iUAPLzzn6hu37bfqVa3Ee5eFYqb9mNnbWtHQkK84cASSkjQdjq0s3t8\n91JZGT16NN99991jOZdSqURVzHtY8a97WFnIPfzoserVq9OyZUtWrVrF/PnzOX/+PFevXmX69On/\n5RKMzsPDA4CoKP0O7BqNhvv379OyZcvHndZjZW9vT3y88e5vIYQQQgghniYPn09trZ6+AVgju7Vg\n2YSRj+VcSoUCVb7Pi/qxORTwvPmvbW15/efNqt7uBNarypqdR5g1ZgAXg+9w/fZdPnip53+5BIPc\nHLVtFNFxiXrHNFnZxCYkE1jX3mA9HZrWoUPTOjr7LoVoJySrWM6l2HlpsrJ597NfCKhThRmv9Mvd\n37hGZb764GWaj57Bkt+2M2tM/2LXXdbsrS2JT9D/fZeWh/f3w3dCTxp551m6ntd3ngBY2Mg7TyGE\nEEIIIYQQQgghhBBCCCGEEEKIIkpISsTO8ulcAGR4u/osGdPtsZxL228wv35/+rG5+/TGqeVT/pH6\nH6ri6USzmt6s23eeGcPacunWPYLCY5g00LhjvB4ueBAdn6J3TJOVTWxSKgE1vAssr8nKZsLyv/Cv\nUZ6PXmibu79RFU++eKMHrSYsZ9nmw8wY3q70k38K2VpqF2gxZl+nhMRkbM31F3d91gxt5MqCnj6P\n5VwF/y0oZMxqPnXoBz88lrfL19kC/wq2bDwXzdSOFbgSmcKN6FTea+1V0vSLxM1Gu4BRTEqm3jFN\ndg5xqRqa5rOgUWmVfxbYmGv7qEpfRiGEEEIIIZ5c8fHx2KifzsVHX2hanoX9az+Wc5WkTezf0f8e\nW/to7KPPyL6uVvhXdmTDyXCmdavOlYhEbkQlM75jlZKmXySuttq20ZikDL1jmuwc4lIyca9cvPZT\nOwtTutR2w9PenE5LDrFsVzBTu1VDk53DB79foklFR6Z0rZYb39DbniWD6tJ+8UG+3BPMtG7V/9tF\nPeFs1AqjPjPHx8djY5ZP+8szRtrESpe0iZUOG7Onp00sKTEBSxvDcyWUlhZ9RjJy2rLHci6FQoky\nn3H0+X2AFzQXRmHzpz46F4Z7xapUbRjIkT/XMODtWdy5fpG7odfp+eoH/+USDLJz1r77SIzVnz81\nO0tDcnws9g0DDdZTJ7ADdQI76OwLC9LOn+riWbHYeWVnafjl43ep0iCAfmNn5O6vXLsxL8/4ihlD\nmrN9xRL6j5tV7LpLwtLGnkQjzp8qhBBCiKfPw/mnHr7TfpbJc3Ppkufm/87WXEVCQpLR6pf72zjk\n/pb7uyge1/39sM/p00T6eZcu6ef9+NlZmhOfaLz5YYUQQgghhBClw6SsExBCCCGEEEIIIZ53WVlZ\noHjyOq2YOXqAQkl69J0yy0Ht6AkKBZlxkXrHMuPvPYgpp7M/W5NBVmoiKou8hSY1SfcBMLV11ol1\naz2M69++SfzFfcRfPoiJlT2ODbsUmpMm6T7Hx9UpNAag/uy9WHj46u03s3fD1M6V1PBresdSw4PI\nydZgXbF+gfX+1/JlRaHUNkNpNJoyzkQI8TTSaDT5D/grZS4eniiUSiLDbhv9XAVx9fBCoVAQExmh\ndywm6m5uzKMyM9JJTkzAysY2d19CrPazz8FZdxLF7kNHMfftlzi5fxenD+/Bxt6B5p0KX9g7PjaG\nvo3KG8z9x52n8fapprffyc0DRxc3bl6/pHfsVtBVsrI0VK/byGD9+bl48ggAdRo30zsWcSuEG5fP\nM/S1CSWq+3FTKlVG/Zx8WLeJybP7asjLywulUsnNmzfLLIfy5cujUCgIDw/XOxYREZEb86j09HTi\n4+Oxs7PL3RcTo10E281N9x5+9dVXeeGFF9i5cye7du3C0dGRPn36FJpTdHQ0Li4uBnO/fPky1auX\n/kQd5cqVw93dnYsXL+Z7To1Gg5+fX6mf90miUhn3/hZCCCGEEOJpkvt8qnp6JrH0dHFAqVRwKzKm\nzHLwcnVEoVBwN1p/crK7MdrJkTxdHXT2p2dqSEhOxdbKInff/QcDOV0dbHViX+7RilGzv2P3iYvs\nPXUFB1srerRoWGhOMfFJVOr1tsHcT6yYTVVvd739Hs72uDnacTkkTO/Y1ZvhaLKyaVi9ksH683P0\nwg0AAurov6cx5HZkDEkpaVSr4KF3rEp5t9z8nkZKpeKxtD89fCf0pJB3nvmTd57/gUKlfccvhBBC\nCCGEEEIIIYQQQgghhBBCCCEM0miyUOWzoOOTrJyTDUqFgttRZbd4oaezLQoFRMTqT/Ae+WCfl5Nu\nX8D0zCwSUtJ1FmSITdROyO9qZ6UT+2KHhryyZBN7zoWw70IoDtYWdGuiPz70UTGJKVR5ebHB3I9+\nNoYqnk56+90dbHC1t+bKnSi9Y9fCorX9Bn31++49dDs6nqTUDKp6Ousdq1LO6UE9ZdfX80nzsK+u\nUfsNZmWhym8xmWeEh60ZSgXciUsvsxw8bdUoFBCZqL+Yzb0k7b5ydrqLsGRosklMy9JZfOl+qvb/\ngbO1qU7ssMZuvLnhOvtuxHMwJB57CxO61HAsNKf7KRrqfHLcYO5736qPr7OF3n43GzNcrU25di9V\n71hQVCqa7Bzqe1oXWO9/Lf8sMHmwKIyMWxVCCCGEEOLJlZWVhclT9sjsYWeOUqHgTqz+89bjUs7e\nAoUC7iboP4vfS0zPjXlUhiabhDQNtuZ54xpjUzIAcLHWXQB2uH953vj1LPuuRXMgKAZ7S1O61tad\n3+nf7idnUGv6PwZz3z+hJb6uVnr73W3VuNqouRqp3853PTJJ+xxb3k7v2ENhcaks2hFEgI8jAxp5\n6hyr6qZ9/r0WqR07fCc2laR0DVXc9PPwcbF6cM5kg9fytDNRYNTxf1lZWaiesvu7OKRNLH/SJvZk\nUBn5/i5NGo0GxWOYU8PBVTt/akzELaOfqyCO7tr5U+MezJX6qPgH+xzcdD/DNBnppCYlYGGd964r\nKV47jt7WyVUntlW/l/luyiguHtnNleN7sbJzoGGbHoXmlBQXw9ttDc9VMXvjCdwrVtXbb+/igZ2T\nG2E3LusdCw+5SnaWhkq1Cp+PoyA3zh0FwLdBQLHLxkTcJi05CY9K+u/03CpW0eYXfLVEeZWEQqWU\ndmohhBBC6MidX0757D44y3Nz/uS5ueypFAo0Rnxmlvv78ZD7W5/c34/x/n6K5oeVft75k37eTx+V\nUolG83S0eQshhBBCCPE8e7JWXBBCCCGEEEIIIcQTQ6W2wrZqUxKuHiIz/h6mdnmDIRKuHSV4xUR8\nRy/BumK94leuePgSP6fwHCxssPFpRPzVQ2RnpKE0M889FndhDwD2tVrrlYu7uA+nxt1yt+OvHALA\nrpruQAfHRt0wsZ5G1OGNJFw9hLN/X5QmuoM2/83E2pGA7/UXJi0O56a9idz9M5mJMZja5L3gjj6+\nGYXSBKemvYxaXojnxfUbIUydNY+9Bw6RkJhIRe/yjBg6iPfHvYGyCBNHnjpzjg/nzOfwsROkpadR\n1deHsWP+x0vDBpcoNi09HWv3wgeEjRoxlG+WLCz+xYpSYWFpTV2/QM4e2cf9qEgcXfIG6Z8/fpBP\np7zFpEXLqVan+APvcv/P5RT+2WdlY0vNBk05c3Qf6WmpqM3zOi6e2LcTAL+W7fXKnTzwDy279Mnd\nPnNkLwD1mjTXiWvZuTefO7zH35tWc+boPtr3GoypmW7HzX+zc3Din+CUQmMMadtzEH+s+pa4+9HY\nO+Z1wNq9dT0qlQltegwotPyXs9/nyD/b+GHnKUxMtJ1Hc7Kz+b/V3+PtW51ajfQHM144eRgAn5p1\n/1Pu4ulhbW1NixYt2LNnD3fv3sXdPW+h+f379/Pqq6+yYsUKGjduXOy6H97DOQbuYTs7OwICAtiz\nZw+pqalYWOTdw9u3bwegU6dOeuV27txJ//79c7d3794NQKtWrXTi+vXrx9ixY1m1ahV79uzhhRde\nQK0u/B52dnY2mLexDR06lC+//JKoqChcXFxy969ZswYTExMGD9b/bBVCCCGEEEKIJ4WVhZpmdapy\n4MxVIu/H4+aYN6nioXPXGbdoBd9OHkWDahWLXbdS8fB5s/A4WysLmtSqzP4zV0lNz8BCnfcu459j\nFwBo51dbr9yuE5fo3apR7vb+09qJm5rX152QqmerRjguXc1vO49w4MxVBrb3R21aePdSJztrEvYs\nLzxxAwa0b8ryTbuJjkvE2d4md//G3ccxUSnp37ZJoeUnfb6Gvw6f5fjPszA10Q5Czs7O4ccte6lW\nwQP/2r7FzsnN0Ra1qQmXQvTfBV0OCQfA211/gKF4csk7z/zJO08hnh5BIbf4cMHn7D1ygsTEZCp4\nlWP4gB6MH/Ni0d55nr/MjEVfcuTkWdLSM6hauQJvvjyUkQP177HTF64wY9GXHD5xhpTUNLy9POjd\nuS2T3hqNjVXeZAGffvMzk+ctKfCcSUHHMTFRFXhcCFH6bkTcZ9avezh48SaJqemUd7FjaJt6jOsd\ngLIIC++dDb7L3DV7OXrlNqnpmZR3saN70+qM79ccawv97xUZmizGffV/rNl3npnD2/FmT/8C6y5O\nrBBCCCGEEOLZl5GRwejRo1m5ciULFixg/PjxRS57/fp1Jk+ezJ49e0hISKBixYq8+OKLTJw4sUjt\nJEII8ayRNiEhhBBCCOOxMjcjoEZ5Dl68yb24JFzt8xaKOHz5Nu988ydfvdWTBj4FT2hfkIff1QyN\n97K1VONX1YuDF2+SlqHB3CyvT9+us8EAtK1fWa/cnnPB9PSvkbu9/8JNAJrVqqAT16NpdRxtLFi7\n7zwHLt5iQIvaqE0Lf9fvZGPJ/XVTCo0xpH/zWny//STRCSk421rm7v/94CVMVEr6BtYqsKybvTVq\nUxWXb+svMnD51j0AvF0KXjhbiOKyMlPRtIIth0ITuJeUiesji+McvZnAxC3BLOnrS71yxV9M5uG6\nSIb6ENuYq2jkZcOh0HjSMrMxN81rB9sTFAdAa197vXL7guPoVjOvX96hEO2iJwEVdO+RbjUdmbbN\nhI3nojgUkkDfus6YmRTe1uZoaULYjOIvUvuo3nWd+flYJDHJmThZ5f1eN1+IxkSpoFcd/YVGSrO8\nEKL4gqOSmLvlAgevR5GYlom3kxWDmlbgrfbVDLZFffHPVWZuPl/g8bDP+uksGBd0L5F5Wy9w4FoU\naZlZlHe0omcDL95oVxUrte44h7O3Y/nk/y5yPCSGtMwsfF1t+F/rKgz1r/ifrlcI8XQLvhvH7HWH\nOHg5jMTUDMo72zCkZU3Gdm9U6N+s9MwsPF/+otC6h7euxeJR7fI9lpSWQavJv3IzKoH9816ghpfu\nd5KgiFjmrDvM/ku3ScvMwtvZll5NfXmzayOszE3zrVMIIR4nK7WKppUcOHQjhnuJ6bja5M1pdDQk\nlgnrL7BsSF3qeRW//aWoz8G25iY0rqDNIS0zC/NH2qt2X40GoHU1/fGd+65F071u3lxTB4PuAxDg\no/u3uHsdd6ZaXmLDqXAO3YihX4Nyhp+DrcyIWNCl8MQN6NOgHD8duklMcgZOVnnvYjefjcBEqaB3\n/YLbGZ2szNh0JoIL4Qn0a1hO57PsfFgCABWdte1srjZqzEyUXLmbpFfPw33lHfUX4xXiUdImlj9p\nExNPKrWlFVUbNOPqiQPEx0Ri55Q3f+r104dYMXsco2Z9S8WaDYpdd1HnT7WwtqVy3SZcPbGfjPRU\nzNR5nzUXDv8DQO1m+s9Rl47solH73rnbV4/vB6BqQ935Uxu168nq+Y4c+fM3rp44gH+XgZgYmD/V\n2t6J5acSCo0xpGmXAexeu5zE2GhsHPK+fxzfvhGlyoQmnfoXUhrWLJzE2f1/MWvDcVSPzJ+6d8OP\neFSqhm+94vensnVyw8RMTVjQJb1j4UGXAXAu513seoV4WgRHJTH3j/McDIoiMfVhO3VF3upQxHbq\nTecKPB62pL9OO/WjktI1tJm3g1sxyeyd3JHqHgU/ExUnVgiRJzgqiblbL3LoehSJaRq8nSwZ1KQC\nb7avavD+/vKfa8z840KBx+8s7qNzfxfnXGduxbJ051VO3bxPTFIGng4WdK3nybudqmOtlqVfn1fy\n3Jw/eW4WzwK5v/Mn97d4Ekk/7/xJP28hhBBCCCGEMA6Z1UoIIYQQQgghhBAFqtB/CgqlistLRpIa\nEUR2ZjoJVw8T9P04lKZmWHpWL1G9Zg7awZKJwafJzkwnJ1tTcA4DppKVlkTQj++QHn2LrPRk4i/t\n59bv87Hx9cOxcVedeKWZOXe2LCb+0j6yM1JJuXOZm+vnYGrnipNfD91YEzNcmg0g+thmMuIicW0x\npETXU1xe3cZiYu3I9a/HkHYvlOzMdKKPbSbir6/x6jEOtaNnbmz8pf0cHuXJzbUzS1RePL/uhEdg\n4lCO0Fu3yzqVMnH33j1adu5JfEICh/7+P2JvXefjGdP4eNFSxk4w3AFl09Zt+LfrirW1FUd3/8W9\n4EuMGDKQV8eNZ9Gyr0oUa65Wo4kNz/dn4y8/AjCwjyxsWtb+N3E2SpWKKaP6cuvGVTLS0zh7ZB8f\nvzcaMzMzKlWtWaJ6nd3KAXD5zHEy0tPIyir4s++VD+aQkpTE/Pdf5e7tUFJTkjh1cBc/LJpB7UYB\ntOjSWydebW7BymXzOHngH9JTUwi+coFvP56Ko4sbrbv104k1NVPTse8wdm1dR0xkBF0Gvlii6ymu\nF15/HzsHJ2a9NZywmzfISE9j95Z1rP3uM4a9ORHXcuVzY08d3EW7ypZ8PfeD3H1+LTsSfjuEpR++\nTULsfe5HRbJo8puEXLvEe/O+QJHPwIzbwdcB8PCuZPwLFE+MTz75BJVKRffu3bly5QppaWns2bOH\nESNGoFarqV27donq9fTUfr86evQoaWlpaDQF38Pz588nMTGRl156iZCQEJKSkvj777+ZOnUqgYGB\n9Oune19aWFgwa9Ysdu7cSUpKCufOnWPixIm4u7szcOBAnVi1Ws3IkSP57bffCA8PZ9SoUSW6HmP6\n+++/USgUOov0TJ48GWdnZwYNGkRQUBBpaWn89ttvLFy4kKlTp+LtLQOHhRBCCCGEEE+2mWP6oVIq\nGTBpKddu3SUtI5P9Z67yytzvUZuaUKNSydrlyzlrB9QevxxMWkYmmqzsAmNnjRlAUmoar3/yIzcj\noklOTWf3yUvM+n4T/rV96dWqkU68hdqM+Su2sPvEJVLTMrhw4w4ffrMeN0c7+rb204lVm5owtHMz\nNuw6RkR0HCO66U6QZSzjh3XFyc6aF2d8Q3DYPdIyMlm/6xhLf9vOhOHd8XJzzI3dffIStq1HM+Wr\ntbn7OjStTWhEFO999gv3E5KIvB/P2EUruBwSxrIJI/NtMzLE0lzN2MGdOHj2GjO+28ide/dJTcvg\n+KVgxi78GTtrS17v375Url88PvLO0zjknad4HMIiIjGv2JCbd8LLOpUyERkVQ+t+LxGfmMSBTSuJ\nurifuZPHMf+LH3j7w08Mlt+8fTfNew3H2sqSQ1t+IfzMbob178Frk2ax+NsVOrEnz12iZe8R2FhZ\ncvTP1YSf3c2CaeP5cc0mur7wGtnZed9T4hO0E0DfPbeXtNBTej8mJoVPGiBEaQuPScBxwBxuRcWX\ndSpl4l5cEl2m/kxCSho7573EzRUTmDG8HZ9uPMj7y7cbLH/6RgQdJ/+ItbkZexeM5saP7zHnxQ6s\n2nWGPrN+Jftfk5PEJafRf/ZqQiJjDdZdnFghhBBCCCGedXfu3EGhUBAaGlrWqZSZ2NhYOnXqxI0b\nN4pd9u7duwQGBhIfH8/Ro0dJSEhg/vz5zJ07lzfffNMI2QohnnTSJiRtQkIIIYQQxjZ9WFuUSiWD\n563lelgM6ZkaDly8yWvLNqM2VVHT26VE9Xo42QBw8no46ZmaQvsNzhjWjqTUDN74Ygs378WRnJbB\n3nMhzF69l6bVvejRVLffk7mZCQvWH2DPuRBS0zO5ePMe01ftwtXemj4BNXRi1aYqBreqy8aDl7gb\nm8iwtvVKdD3F9W7fQJxsLRm1eCPBd2NJz9Sw8eAlPt9yhPf6NcfL2TY3du+5EBwHzGHair8BsFSb\n8mYPfw5dusWsX3cTFpNAanomJ66F8fY3f2JnZc6r3Zo8lusQz48pHSqgUigY+ctlgqJTSddkczg0\ngXEbgzBTKanuamm4kny422oXfj99J5F0TTaa7IIXDpnasQJJ6Vm8symIW7HpJGdksT84nvn/3MLP\n24auNR114s1NlSzec4d9N+JJzczmcmQKc3bexNXalB61dRe+MTNRMqC+C5vPRxOZmMGQhq4lup7i\nGtvCC0dLE8asu07o/TTSNdlsPh/N14ciGNfKC0+7vIV89wfH4/nRYWZuv1mi8kKUhvC4VNzGruf2\n/eSyTqVM3EtIo/vi3SSkZfLX+LYEL+jNh73qsGTHFT5Yd8Zg+fjUTACufdKLyKX99X4eXYDz2t0E\nOsz/h+jEdDaPa83FuT2Y0KUGX/xzlVd+PKJT75/nwui8cBdWahN2jG/H1Y97MqhpBd5bfZIvd10r\n3V+CEE+R8PtJOA9fyq3o/7bo/dPqXnwKXWauIyElgx3TBxL63RimD2nO4j+OM/HnPYWWVZuqiF45\nNt+fle90B6C3f9UCy09dtZ+bUfn/3q+G3afttN+ISkhhy9T+XPliNBP6NGHZ/51i1OfbSny9QghR\n2qZ2q4ZSoWD4DycJupdMuiabQzfu89bqs5iZKKnublOiet1tzQE4dSvO4HPwtG7VSErP4u0157l1\nP5Xk9CxX2UuVAAAgAElEQVT2XY/hk7+u4VfRgW513HXizU1VLP47iL3XoknNzOJSRCKz/7yCq42a\nnvV0Y81MlAxs7MWmMxHcTUhnSJPyPA7j2vngaGXGqyvPEBKdQromm01nIvhqbwhvt/fF094iN3bf\n9Rg8JmxjxtYrudf3UY/qnA9LYPy6C9yOTSU1M4sjwfd5d915bC1MGRWoXSDU0kzFa60qcST4PvO2\nXSM8Lo3UzCxO3oxj/PoL2FqYMrp5xcdyzeLpJm1ixiFtYsJY+o2biVKpYunYAdwNvUZmRhpXT+zn\n+2mvYGKmxtO3huFK8mHvop0/NfjCcTIz0sguZP7UAeNmkZaSxI8fvU502E3SU5K5dHQ3m76YhW99\nfxq1051n10xtwZbv5nPpyG4y0lK5c/0C65d8iJ2TG34d++rEmpipadZjKMe2byAuKoLmvUeU6HqK\nq+uo8Vg7OPHNpBe5dzuYzIw0jm1fz/aVS+k+egKO7l65sZeO7mZ0Q1vWLs6b67h2YAeiwkL55eP3\nSIq/T3xMJCtmjyXsxmVGTltWorkw1BaWdBo+lmunDrLx8xncj7xDRloqweeP8/PssVja2NF+6Oul\ncv3iyRMel4rbW+ue73bqT3dp26nfa0fwwj582KsuS3Zc5oN1pw2Wj0950E49vzeRywbo/TzaTv1v\n0zac4VZM0X7vxYkV4qGIuFTcx23k9v2Usk6lTNxLSKPHZ3tJTM1k23ttuDG/J9N61mHJzqtMXn/W\nYPmH76GuftyDu0v66v08en8X51xHbkTTc8leTFVKtrzdmktzuzG5ey1+3H+DQV8e0OtrLZ4v8txs\nHPLcLJ4Ecn8bh9zfwhikn7dxSD9vIYQQQgghhNBnUtYJCCGEEEIIIYQQ4sllXbkBtT/YzJ0ti7kw\nrxdZqUmY2rng3KQnnt3GojQtWacGl4D+3D/5J0HLx6KysKHuRwVPMmvj60etiRu5s2khZ6d3JDsj\nFbWTJ67NBuDV420USt3mDYXKFN+XF3Nz7UySQs6Sk5ONjW9jKg2dhdLMQq9+t1bDiNjxLVYV6mBV\nvmaJrqe4TKwdqD15M7c2fMz5OT3ISkvEws2HikNm4tZ6uNHLi+fD3gOHyjqFMjVn/mckJSXzy/Kv\ncHJ0AKBn105MHv82U2bO5c0xo6hexbfA8h9Mn005dzd+/noZarW2g9w7b7zK5avXmDFvIS8NG4Kj\ng32xY/OTlJzMuPenMLBvT9q1blFavwJRQjXq+7F03S5WLpvL2AFtSUlMxNHFjdbd+/PC6+9jpjYv\nUb0d+gxl31+b+Pi90Vja2PDNlsMFxtZuFMDi33bw82ezeaW7P+mpqbiWK0/HfsMY/uYkVCrdzz4T\nU1Pen/8tX8/7gKtnT5Kdk02thv689dFC1Bb6HUO7D3mZ9d8vpUrt+vjUqFOi6ykuWwdHlq7fxfIF\nH/FW39YkJyVSvpIvb0xbQI8XRhss79eyPTO++o3VXy1gaIvqKJRKajVqypJ1/1CtTsN8yyTFayeP\nt7IueAKJr+d+wLrlS3T2fTNvMt/MmwxAu16Dmbz4h6JepngCNG3alIMHDzJz5kwCAwNJSEjA3d2d\nQYMGMXnyZMzNS3YPDx8+nA0bNjBixAhsbW05depUgbGBgYHs3buXjz76iAYNGpCSkoK3tzcjR45k\n2rRpmJjo3sNmZmb8+OOPjB8/nuPHj5OdnU2zZs1YunQplpb69/Arr7zCp59+SsOGDalX7/F0vhw/\nfjyLFi3S2TdhwgQmTJgAwAsvvMCqVasKLO/k5MTBgweZPHkyAQEBJCQkULVqVT777DPGjBlj1NyF\nEEIIIYQQojQ0rlGZnZ9P4uOft9DhzXkkJqfi5mhH37Z+jH+hG+ZmpiWqd3DHADbvO8mrc7/HxtKC\nA999WGCsf21fti15nzk/biZw9AxS0zPwcnVkaOdmTBzRHROVUife1ETFVxNfYspX6zh5JYTsnBz8\na/kyf+wQLMzN9Op/qUdLPl+7g3pVK1DH5/FMYOloa83Ozz9g+vKNtHt9Lokpafh6ufHxW4MZ1bO1\nwfLt/Grxy6w3WLTqT2oNmohSqaRpLR92fD6JBtUq6sRO+Woty9bs0Nk39at1TP1qHQADO/izfIq2\nnWraqD74eLrx49a9fPP7LtLSM3B1sKNlw+r8PH0MlT0fz+BlUXrknadxyDtP8TjsO3KyrFMoU3OX\nfkdySgorl87D0cEOgB4dWjPpzdFMm7+MN14aQjWfigWWn/LxEjzcXPhh8SzUZtrP/3Gjh3H5ejCz\nFn/NyIG9cLTX1vvhgs8xMVHxzYLpWFpo29K7tmvB2/8bzofzP+fQiTM0b6J9JxOXkAiAdT5t2EKU\nhQMXb5V1CmVqwfoDJKVlsPztPjjaaL8ndPWryvh+zZn56y5e7epHFU+nAsvP+nU3KpWSz1/vjoVa\n+2zTqVEV3ujhz6xfd3Pk8m2a1fQGtAt5d57yM70DatC+gQ8dp/xUYL3FiRVCCCGEEOJ5sGfPnrJO\noUzFxsYSGBjIgAED6NKlCwEBAcUqP2vWLJKSkli9ejVOTtpnnF69ejF16lQ++OADxo4dS/Xq1Q3U\nIoR4lkibkLQJCSGEEEIYW6Mqnvw1eyQL1u+n89SfSUxN106236wG7/YNRG1asikcB7Wsw5YjV3ht\n2WZsLNXsmV/w+Mqm1b3YOmM489buo9WE5aSmZ+LlbMeQ1nWY0L+FXr9BMxMVn7/egw9X/s2poAiy\nc3JoUs2LT17umPu971EvdmjAl1uPUq+yO7UrupXoeorL0caCv2aPZNavu+k0+ScSU9PxKefI3Bc7\n8lLH/MeKPmrKkNZU9nDk579P891fJ0jL0OBiZ0XL2hX54d2+VHZ3yI2dtuJvvthyVKf8hyv/4cOV\n/wAwoEVtvhnbq9ix4vnSwMuazaNrs3jPHXotv0BSehYu1qb0rO3M2JaeqE2UhivJR/96Lvx56T5j\nfw/C5k8V28fULTDWz9uGjS/XYuGuO3T8+iypmdl42qkZUN+Vt1t56S1OaapSsLiPLzO33+RsWBLZ\nOTk0Lm/DrK6VsDDVz3dYIze+PRRBHQ8rarpbleh6isvB0oTNo2vz8d+36PHdeRLTs/BxsmBm54oM\n9zP89+i/lheiuA5djyrrFMrUp9svk5yu4ZuRTXGw0vZF7FynHO90qsGcLecZ3cqXKm4Fz+mQ8GAR\nTiu14e9Ps/44jyY7mx9HB+Bope3j3atheU7djOXr3dc4fCOaAB9nbezm87jbmfPF8CaYPfh7PKZN\nVa7eTWT+nxcZ6l8Re0v9sRNCPOsOXr5T1imUqYWbjpGcnsm3b3TG0VrbJ7pLw8q816sJs9Ye5JWO\n9alSzsFALbqS0zKZtGIvffyr0qpW/mOudp4JZdXei/Tw82XL8SC94zPXHESTlc3P47rh9KBdv49/\nVU4HR/LlttMcvhJGQHXPYl6tEEKUvobe9mx5M4BPdwbR44vDJKVpcLFR06u+B+Pa+pT4OXhAI0/+\n7/xdxv52Fmu1CTvfCSww1q+iA7+/1pQFO67TYfEBUjOz8LS3YGBjT95p76v3HGymUvDZoLrM2HKF\nM3fiyM4Gv4r2zO5dEwtTlV79w/3L882+EOp42lKrXMHfY0uTg6UpW970Z+62a3T//DCJaRp8XKyY\n1bMGIwK8DZYfGeCNi7Wa7w6E0u7TA2RosvG0t6CBtx3vtvelglPe+J5JnatS2dmKVUdv88PBm6Rl\nZuFso6a5rxPfDq9PJee82Blbr/D13hCdc83ceoWZW68A0LdhOb4Y8njmtxJPFmkTMw5pExPGUrl2\nYyb9tJMt337MvJc6kJqUiJ2zG34d+9Lt5fGYmpVs7sWAboM5+c9mvp/2KhZWNny4+kCBsb71/Xl/\n+TY2fz2HGUMCyUhLxdHdi2Y9htL9fxNR/mv+VJWpKS/N+Ip1i6cQcvEkOdnZ+NbzZ8j78zEz1x9H\n37LvS+xY9TkVqtejfNXHM3+qtZ0jH/y4k42fT2fuyHakJSfiVsGXweM/pnX/UQbL1wpoxxsLf+HP\nHxYxsVstlAolPvWaMumHHVSs2UAndu3iKexYuUxn37rPprLus6kA+HcdyOjZywHo88Y03Lx92Lvx\nR3at+YaMtDTsnFyp7teSMZ/8jGv5yqX0GxBPmkPX75V1CmXq078uadupX/TPa6eu+2g7dRUD7dQZ\nQNHaqR+182IEvx4OoXt9L7aeKbzdrTixQjzqYNDz/h7qCsnpGr4e2eSR91AevNOxOnO2XmB0Sx98\nC7m/44vxHqo455q79SJO1mo+H94Y0wf9c3o28OLMrVi+3HWdc7fjqO9dvLZm8eyQ52bjkOdm8SSQ\n+9s45P4WxiD9vI1D+nkLIYQQQgghhL6SPWEKIYQQQgghhBDiuWFVoQ7V3vzBYFxBMc5NeuHcRPeF\np4mVPbUmbixSeQCbyg2p8e6vRcgWyM7GqkIdak5YV6TwnCxtR033NiOLVn8pUTt6UuV/ywzG2dVs\nQcD3YSUuL54OZ89fZMbHCzlw+ChJycl4enjQp0dXpkx4Gztb29y47gOGcf1GMFvX/cL702Zw4PBR\nsrKyqVOrBgtnf4RfI+2Anq79h7Ljnz0A+NZrilptRvLdULr2H0pwSChrf17OiFff4vqNGySE3UCl\nUnHo6HHmLPiMoydOkpySioebK907d+SjD8bj5JjXIaJ11z7cvHWb33/9iXcnf8TJ02fJycmhqV8j\nFs2ZTt3a2gVG23Try8nTZ7lz9Qy2NrqdpT9evIypM+exbcNqOrRtZZTf6drfN9OqeTOd3AF6d+/C\n5Blz2LB5K1PGv51v2di4eK7fCGFAn56o1boT+wzo3ZMfVq7mzx1/M2xQ/2LFFmT63AXExSewcM6M\nEl6tKG1Vatdn5jdrDcYVFNOmxwDa9Bigs8/G3oHP1uwsUnmAmg2a8MnPfxQhW8jOyqZK7fos+mVb\nkeI1Gg0AvYa9UqT40uJarjyTFxv+TtEwsC3/BKfo7Q/s0J3ADt2LfL6xMz9j7MzPCo0ZM3keYybP\nK3Kd4unQsGFDNm3aZDCuoJjBgwczePBgnX2Ojo7s27evSOUB/P392b694MW/H5WVlUXDhg3ZtWtX\nkeIzM7XfX19//fUixZeGhQsXsnDhwiLFtm/fnpycHL393t7erFq1qrRTE0IIIYQQQojHpl7VCqye\n86bBuIJi+rdtQv+2TXT2Odha8dfSiUUqD+BXszKbFrxThGwhKzubelUrsHXx+CLFZ2qyAPhfr9ZF\nii8tXm6OLJ9S8CDHh9o0qknCnuV6+7sF1qdbYH2D5ee8NpA5rw0scl5DOzdjaOdmRY4XTz5552kc\n8s5TPOrspavMXvwNB4+fJik5hXLurvTu3JYPxv4POxvr3LheL77F9ZCb/PHT50yau5iDx06TlZVF\n7RpV+GTqu/jVqw1AjxFvsHPfYQCqNe+O2syM+GtH6DHiDYJv3WH1Vwt4+Z2pXA++xf3Lh1CplBw+\ncYZ5y5Zz7PR5klNScXd1plv7lnz4zms4Otjl5tBu4Chu3g5n/fLFTJi5iFPnL5GTk0OTBnWYP+09\n6taoCkD7gaM5df4Socd3YmutO3nF/C9/4MP5n7N15Re0b1G8xcuLat3W7bT0b6yTO0Cvzm2Y+slS\nNv75Nx+8lf/naGx8AkEht+jfvQNqM933mP27d+CnNZv4a9cBhvbtBsCd8Lu4OjthaaE7sWdlb+2C\nBSG37tC8iXYwfnxCIhbmakxM9CfFFsKQ86GRfLJ2H4cv3yY5LQMPRxu6N63GhP4tsLVU58YNnPsb\nN8Lvs3bKYD5c8Q+HL98iKzuHWhVcmT2yPQ19ywHQf85qdp0JBqD+65+jNlUR8esk+s9ZTejdWH56\nrx9jlv3BjYgY7qyaiEqp4OiVOyzccIAT18NIScvAzcGazo2rMmlgy9yFswG6fbiCW/fi+WXiAKb8\ntJPTNyLIAfyqeDJ7ZPvcSTK6f7SS0zciuPLdOGws8q4BYPHvh5j16242TB1Cm3rGmUj190OXaF6r\ngk7uAN2bVmPGL7vYfOQy4/s1L7B8WEwCrnZWepOCVHLT9rcIvReXu/B3VFwyr3Vvwsj2DThxTf+z\n/VHFiRVCCCGEEOJJc+bMGaZPn87+/ftJSkrC09OTvn37Mm3aNOzs8p7Tu3btyrVr19i2bRvjx49n\n//79ZGVlUbduXRYtWkSTJtr3Ap07d87tT1apUiXUajVpaWl07tyZGzdusH79eoYPH861a9dITk5G\npVJx8OBBZs+ezZEjR0hOTsbDw4MePXowY8YMnJyccnNo2bIloaGhbN68mXfeeYcTJ06Qk5ODv78/\nn376KfXqaRdkatWqFSdOnCAiIgLbR/qnA8ybN4/Jkyezfft2OnbsaJTfaWRkJG+//TavvPIKR44c\nKXb5NWvW0Lp1a51rB+jTpw+TJk1i/fr1TJ06tbTSFUKUMmkTKn3SJiSEEEII8XjUq+zOqvcHGIwr\nKKZvYE36BtbU2edgbcH/zRxRpPIAjat6smHqkCJkC1nZOdSr7M7mj4YVKT5Tkw3AqE6NihRfWryc\nbYs04X6rupW4v26K3v4hresypHXBi6E8NGtEe2aNaF+knIoTK54/dTys+GFINYNxBcX0quNMrzrO\nOvvsLUzY+HKtIpUHaOhlw68jahQhW8jO1ua87sWahoOBzGzteNCRTdyLFF9aPO3ULOtXxWBci8p2\nhM3Q759V1PLi+XMhLI4Ff17iyI1oktM1eNhb0K2eJ+92qoGtRV5byNCvD3DjXhKrX2vO9E3nOHoj\nmqzsHGqWs2NGn7o0qOAIwOCv9rP7ciQAjadvw8xEye1P+zL4q/2ERifz/csBvLHyGDfuJRK6sA8q\npYJjwTEs3n6Zk6ExpGRk4WprTqfaHrzftVbuwpIAvZbs4db9FFb8rxkfbjzLmVux5JBDo4pOzOxT\nj1qe2ncSvZfs4cztWM7P7o6NuW57zpKdV5i75QJrXm9B6+rGWfRn06nbBFZx0ckdoGvdcsz+4zxb\nz9zhnU4F/42KT83E3FSltyBZflpVd6NFVVccrXTb3OqVtwfgZnQSAT7OxKVkEByVRK8GXpj9a7G1\nXg28+PVwCDsvRjDAr0JRL1OIMnHhZhSfbDzKkWvhJKdl4uFgRTc/X8b3aoKtZd49N3jhZoIi4lg7\noRcfrj7Akath2vbz8s7MHNqChj7a+3/g/M3sOn8TgIbv/ISZiYrwH99g4PzNhNyL56exXXnt6+0E\nRcRx+/vXte3n1yL4dPMxTgTdJSU9Ezd7Kzo1qMTEfv44Wuf1K+4+ez23oxNZ9U53pqzax5mQe+Tk\n5NDY153ZL7Sklrf2+06PORs4ExzJpc9HY2Oh+3fjsy0nmL32EOve702bOt5G+Z1uOnKN5jU8dXIH\n6NbYh5lrDvLH8SDe6+VXrDo/3nCE+OR0Zg1tke/x/2fvvqOjKtoADv9203slCST0ltB7C71LldA7\nCAKKIiCogDSpooIiwoeoKCC9gwiCEHrvBEIvIb2R3jab749NYdkkm4QSwPc5Zw/n3vveuXM3zE32\nndmZiNhEPvnlAN0aVMDTw5VdZ+/oxDSvUoImlYrj8Exev3opJwAehEbT0N01X/USQoiXpaqrNSuH\n6F/MMaeYd2sU5d0aRbX22Zobsf3DBnk6H6B2SVvWv5+353VqWhpVXa3ZPKqe/mAgJVWTExvS6NX+\nrehqa8ZPfavrjWta3oHAb97R2d+hqjMdqubtb/5edVzpVUf/75XpndyZ3sk9T2WK/x7Jib0ckhMT\nL0tJ9+p8tHCd3ricYuq160G9dtpz5lrY2PH5r3vzdD5Amap1GfeT/vkfAdTqVEq6V2fC8t15ik9V\nab5H37zX+3mKf1HsXdwYPlt3jotnVarfgl8uROvsr9G8IzWad9R7fq9xc+g1bk6e69Wocz8ade6X\n53jx6l17/IRv/vbh1J1n8tTtK2nnqZcd1eSpP2zCjG2Xs/LUrjbM7FY9K0+99CiHbgQBUGf6Hk2e\nelF3+iw9yoOwWH4d1pDRq9Lz1N95peepwzR56vtP5amrFtPNU39/SJOnHuHJtC2XtPPUXtWp7KrJ\nzb77gzeXHkVwdU5n3Tz1P77M3XWVDaObvvo8dXXXF56nzhAZl8z4tefoWqs4nuWLsPvS4xcSK95s\n1/yj+Pbv65y6G57VvqsVY1w7d+32vfw490JiWTvKk5nbr3LqXhhqNVQqZs2Md6tRs6RmvG7fZcc5\n5Kvph6o7cy/GhkoeffcufZcd50FYHL+8V5+P1pzlbkgs97/pmtkP9f0/vpx/EJHZvttWceGzdypp\nt+/FR/ALj+OP9xsybdsVLj96kt6+7Zn5brWsfqjFR7jsF8mVWR102vfi/TeZu9uH9R94vrT2vePi\nYxqVd9Rp3+9UK8bsXdfYdcmfce1y/uwanY/2nZ9rdaruShErE4wMtPuhKrpovo/jFxFPjRLaax+I\n/xb53PxyyOdm8TqQ9v1ySPsWL4OM8345ZJy3EEIIIYQQQmhT6g8RQgghhBBCCCGEeHOkkZav+IC9\nyzCyccKxgddLqpEQuTt/8TKN23ZGrVZzdN8uQu5d5/uvZ7Fmw2bae/VFpVJlxhobGxEWHsGA9z9k\nxNCBPPA5z9F9OwgKDqH7gPdITEoCYM/mtYz/aBQAdy6fJi7oAQAmxsbExSUw5rMpdO3QjoXzvkKp\nVHLoyDFaduqOtbUVJw7sIfT+dVYu+4Htu/fQqnOPzHIBTEyMCQ0L573RY5n+xacE3rnKiQO7uXvv\nPm269iQsPAKA94cMID4hgfWbdb+MtWHLdkq4udKqefYTXISFR2BoV0zvy/e27sQXAH7+AYRHRFLJ\nvYLOsXJlSmFkZMSFS1dy/JmkpWmeI4psxm/b22m+hHLl2vV8x2bnod9jflqxkk8+eJ9iLi9nQLt4\n++X3d9/GnxdhX8SZVl37vKQaCSHyI+N3SV598803uLi40L9//5dUIyGEEEIIIYQQb4N8ftzkh/X7\ncLa3oVebBvqDhRAvnfR5ijfN+SvXae41BHWaGu+tKwm4dIiFMz7jz61/0WnAh6hUqZmxxkZGhEc8\nYfAnkxnerzt3Tv7NoS0rCQoJo9eIT0lMSgZg16qfGPv+QABuHttN1C3NIuEmJsbExScwbvrXdG7T\nnG+nT0CpVOB94ixt+ryPtZUFR3esIvCyN78u/Iod+w7Rtu/7meWCpt80LCKSERNmMHXcSPzO/8uR\nbau4+8CP9v1GEh7xBIBh/byIT0hk407tCSsBNu3cR/FiLrT0rJ/texIe8QTTUrX0vm7efZDt+Y8D\ng4mIjMKjvO5CwWVLFsfI0JCLV2/k+DPJ7MdEtyPTLn3R+is3bmXuq+JenuDQMKJiYrVi7z58BID7\nU/V4Eh2DpYVFjtcWIicX7wbSbsrvqNPS2DdnMHdXjmf+e23ZeOQaXrPWokqfVB3A2NCA8Jh4Rvyw\nnSFtanJt+Rj2zh5McGQsAxZsJilFM5Zi85S+jO6saYeXln5E4NovADAxNCQuKYXPf9tHh7oVmDuk\nLUqFgiPXHtB5xmqszI05MG8o937/lKUfdWH36Zt0mbEms1wAYyNDwqLj+Wjpbj7v1ZTbv45j/9wh\n3AuK4N2v/iQ8Jh6Awa1rkpCUwpZjPjr3vPW4D26O1jSrVjrb9yQ8Jh77nnP0vm77h2d7vn94NBEx\nCVR0c9Q5VtrFDiMDJZfvBeX6c6lUwongJ3FExydp7b8XpBn/4f5U2eVdHRjcumau5RUkVgghhBBC\niNfJuXPnaNSoEWq1mhMnThAeHs7ixYtZvXo1bdu2fWZstzFhYWH069ePkSNH4ufnx/HjxwkMDKRb\nt24kJiYCsHfvXj799FMA7t+/n7nfxMSEuLg4Pv74Y7p27cr333+PUqnk4MGDNG/eHGtra06fPk1E\nRAR//PEH27Zto0WLFpnnZ5QRGhrK0KFDmTFjBiEhIZw6dYo7d+7QqlUrwsLCABgxYgTx8fGsW6e7\nEMf69espUaIErVtnPxFeWFgYCoVC78vX1zfH99Xd3Z0RI0bk86eh4efnR3h4OJUq6U5IWq5cOYyM\njDh//nyByhZCvHySE9IlOSEhhBBCCPGy5Pd7aj/uPImTrSU9m1R5STUSQhSG/I4/XHY8ACdLI7yq\n6X7OFOJNc+lRJB0XHkKdlsZf41twc34X5navwaazD+m19CgqdVb7MDJQEhGXxAd/nGaQZxkuftWB\n3eNaEBydyJBfTpKUohn3uP6DJnzQUjN3ybkZ7+C3UDNW19jQgPgkFZM3X6R91WLM9qqBUqHg2K0Q\nui32xsrUkL8/bcnN+V1YMqAue64E0O3Hw5nlaspQEh6bxCd/nmXiO5W4Prczf49vyf3QWLovOUxE\nnCZ3M9CzDAnJqWw776dzz9vP++FqZ07Tik7ZvicRcUk4j9ms93U7OCbb8wMi44mMS6ZC+sKWTytd\nxFKTi/KLzPXnEh2fjKWpYa4xGYY3LceI5rqLdwVGJQBQ0tFS+0A2k73YmmsW8PTxj8rTNYUoLJfu\nh9D+q02o09L4e1pPbi8bwbyBzdh47AY9FmzTyp8bGRgQEZvAiKV7GdKyCld+eI8903oS9CSOQT/s\nzny2bPysKx92qAXAhUVDCFg5GgBjIwPik1L4fJU379Qqw9yBTVEqFBy9/piuc7dgZWbMPzN7c+d/\nI/lpZBv+On+Xd+du0XpmmRgaaPLnP+/nc6/63Fz6Pvtm9OZ+cBTd5m0lPEbTTge3qEJCsoqtJ7PG\nKWfYdvIWbg5WNKtSPNv3JDwmAceBi/W+bgdk/9zxD48hIjaRCq4OOsdKO9tonln3Q/Ly48nkFxbD\nL/svM6p9DVzssh8/PXHlIVLVacwf1CzHct5vW51R7Wvo7A+MjAOgVBHd56wQQoi8ye93aZd638fJ\nyoTutYq9nAoJIQqF5MSEeMPk8xf4vlU/YOPgTIMOvV5ShYR4cTR56oOo1fDXpy25+XVX5vaoqclT\n/1gU/cEAACAASURBVHREO09tmJ6n/v2UJk89qyO7x7cgOCqRIStOZOWpP3wqTz2zA36LugOaHHN8\nkorJm9Lz1N2fylP/4I2VqRF/T2jFza+7smRgPfZc9qfbYu9n8tQGmjz1mrNM7FCZ6/O68PenrTR5\n6h8PExGbhzz1hUe556ljk3D+eJPe13PlqR/pyVMnpOQ5T53hsw3nUanTmNdT/5jI/MSKN9flR5F0\nWuSNOg3+GtcM33mdmNO9OpvOPaL3smNa7dvYQElEXDIfrDrLIM/SXJz5DrvGNiM4OpGhv2b1Q637\nwJMPWmj6Rc5Ob8+j797VnG+oJD5ZxeQtl2lftRizvKqnt+9QvH48gqWpEXvGt8B3Xid+HFCbv68E\n4LXkyDM5XSXhccmMXXueie944DOnI3vGteB+aBw9fjpKRJxm/o2BjUqnt+/HOve8/cJjPf1Qybh8\nslXv605O7ftJApFxyVR0zq59W2BkoOSK35Ncfy5ReWzf+b3WiObl6FZbN5ftExCFQgEVXaz0XlOI\n14l8bhbi7SXtW4g3h4zzFkIIIYQQQog3k7KwKyCEEEIIIYQQQgjxqqWpU1EnJxD4zwpCT2ymdL9Z\nKI1MCrta4j/q0ykzsLezZcPvK6hYviyWFhZ0bNeGOdMmc/b8RTZt36UVHxUdzacffcA7bVphYW5O\nZQ93Rr43iICgYK5eu57rtRQKBaHh4XTp0I6ZUz5j5NBBKBQKvpgxBztbG1Yu+4EK5cpgaWFBs8aN\nmDtjCteu32DDlu2ZZRgYGJCYlMTET0bTrHEjzM3MqFLJg/kzpxIeEcmqdRsB6N6lEw72dqz8c71W\nHXxv3+Gqzw2G9O+DUpl9etLRwR5VZIDel3v5ctmeHxISCoCDg73OMaVSib2dLcHpMdmxt7OlXJlS\nnDh1luTkFK1jx06d0VwjNCzfsdmZ++33mJqY8MmHBVvcQIi8UqemkpQQz+bffuSfrX/y0fTvMDYx\nLexqCSHyKDU1lfj4eBYtWsSqVatYvHgxpqbShoUQQgghhBBCPJ9UtZqExGR+2rSfdftOsGBMX0yN\njQq7WkKIPJI+T/E6+Wz2d9jZ2rB26QIqlCmFpYU5HVo1YfbnH3P28jU2//WPVnxUTCxjRwyifYvG\nWJibUbliOUYM6ElgcChXfXUn/n+aAgVhEZF0btOc6Z9+yPv9e6BQKJgy/wdsra355btZlC9dEksL\nc5o2qMOcz8dwzfcOm3btzSzDQKkkMSmZ8aMG07RBHczNTKniXo65k8cSERnF6i2aPlqvDq2xt7Ph\njw07tOpw8+4DrvreZnCvrjn2eTrY25L44ILeV8WypbI9Pzg0PLOcZymVSuxsbQgOy34hYAB7WxvK\nlirOifOXSU7R7sc8ce4SACHhEZn7Jn38PqYmJgwbPxX/wGCSU1LYf+QkP/yyhp6d2lK3etaEAE+i\nYzAyMmTWov9Rs00PbCs2oFS9toydNp+IJ7J4isjZl3/sx87SjJXju1OumAMWpsa0q12eaf1acOFO\nANtP3tCKj45P4qMuDWhTqxzmJkZ4lCjCe+1qExQZg8/D3BfjUCggPDqeDnUrMrlPM4a2rYVCATPX\nHMTWwpRlH3WhbFF7LEyNaVy5JNMHtOD6oxC2HM8ad2GgVJCUomJM14Y0rlwSMxMjKpVwYubAVkTE\nJLDe+yoAXRp4YG9lxpqDl7XqcNs/HJ+HIfRvoZlgLzsOVuZEbJqi91U+m4VJAEKeaBYBcbA21zmm\nVCiwtTQj5Elsru/VxB6NMTU25IMfdxIQHk2yKpWDl+6xdPdpujWqRK1yMsm9EEIIIYT4bxk/fjz2\n9vZs2rSJihUrYmlpSadOnZg3bx5nzpxh48aNWvFRUVFMmDCBDh06YGFhQZUqVfjggw8ICAjgypUr\nuV5LoVAQGhpK165dmTVrFqNGjUKhUPD5559jZ2fHH3/8QYUKFbC0tKR58+bMnz+fq1evsn591vhs\nAwMDEhMT+eyzz2jevDnm5uZUrVqVBQsWEB4ezh9//AFAjx49cHBw4LffftOqg6+vL1euXGHo0KE5\nj+12dCQtLU3vy93dvSBvuV7BwcGZ9XiWUqnE3t4+M0YI8fqRnJAuyQkJIYQQQojClKpOIyEphWW7\nT7P+8FW+fq8tJkb5W/ROCPHmS1WnkZCiZsXJQDZfCmVWh9KYGMrUtOLNN33bZezMjfn1vYaUc7LC\nwsSQNlWKMqVzVS4+jGDnBe1FaqMTUviwZQVaV3LB3NgQ96LWDGlchqCoBK4H5D4WTgGExybRvmox\nvuhYmcGNy6BQwKydV7ExN+bHAXUpm16HRuWL8GWXKtwIiGLbU3XQ5KJS+ahVRRqVL4KZsQEexWyY\n3rUqkXHJbDj9EIDONdywszBm7akHWnW4HRzD9YAo+jYolWMuyt7ChODFPfS+yjtnv2BlSExSejnG\nOseUCgW25saEpsfkJCohBSOlkgV7rtNk7j+U+HQb1b7czaRNF3kSn5zruQChMYn87H0H96LW1Cut\nyZnZmhtTuoglZ++FkZKq1oo/c08zx0uYnnoJUdi+/PMIdhamrBzTgXJF7bAwNaJtzdJM7eXJhbvB\n7Dh9Wys+Oj6Z0R1q0bp6KU3+3M2B91pVJSgyDp9HOc9tBOnPrJgEOtQqw6QeDRnSsqomf77+GDbm\nJvw0si1lXWyxMDXC08ONab09ue4XztZTWeO6DZRKklJSGdOxNp4ebpgZG1KpuAPT+3gSEZvIhqOa\nfH+XeuWwtzTlzyM+WnW4HRCJj18Y/ZpWyiV/bkbY6jF6X+WL2WV7fmh0gqYcS925ODT5c1NCo+Jz\nfa+etXDHGUyMDBnVPvuFvDefuMmOM7eZP6gZDlZm+So7NCqe/+27iIebA/UqSF5eCCFeJs3n4FR+\nPvKATef9mf1uJfkcLMR/kOTEhHizqNWpJCcmsP/Pnzixex19P1uAkbHMvShef9O3XsLOwphfhz2T\np+6SS566VUVaVy6anqe2YUiTsnnLUyvS89TVXPmiUxUGNy6ryVPvuJJDnrpqznnq1s/kqd+tpslT\nn3kmT33yvlYdbgfHcN1fT57a0oTgH3vqfenNU1vqzqWRladOzPW9iopPxshAyYI9PjSZs48S47dS\nbcquHPPUW849YufFx8zvWROHbK5b0FjxZpu2/Sp25sb8MrR+ZttqU9mFKZ0qc/FhJDsvPtaK1/RD\nlafVU/1QgxuXISgqkesB0bleK7N9Vy3K5x0qMdiztKZ977qmad/9a1PWyVLTvssVYUrnKtwIiGb7\nhaw6GCg07Xt0qwo0KpfRvq2Z1rXKM+3bFTsLY9adfqBVhzsZ/VD1S+bSD2VM0A9eel/lcmjfodGa\ntmtvmVM/lJHe9h2d3g/1zd83aDrvACUn7KD61D1M2nxJq30/77VCY5JYevA2vx65y/h2HlRwsc61\nXkK8ieRzsxBvL2nfQrw5ZJy3EEIIIYQQQrx+JIsihBBCCCGEEEKI/5zwszs5/WEFAv5ZTrnhi3Go\n06mwqyT+o6JjYjhx+izNm3hiYqI9CLhd6xYAnDl3Qee8Vs2baG0XdXEGICBI/yT2KpWKXl5dM7cj\nn0Rx/uJlmjVuhKmJ9hcGMq7jffSETjltWzbX2m7epBEAV300E3OYmBgzsE9Pzp6/iM8N38y4DZu3\no1AoGNy/t966FlRCombQtLFR9osWGxsZEZ+QkGsZX381jccBgQwe9TF37z8gKjqaP9ZuYPlvmgUR\nUp5aMDE/sU979NifVes28dGI97Cztcn3fQqRH4f+2kzHqk5s/mUxkxb+SrMOXoVdJSFEPmzYsAEr\nKysWLlzI6tWr6dmzZ2FXSQghhBBCCCHEW2DrwbMU7TCaJRv/YcWU4XRrXqewqySEyAfp8xSvi+jY\nOE6eu0yzhnUwMdbu82zbTNOHePbSNZ3zWnnW19p2cdIs5h0YHKr3mipVKj07tc3cjoyK5vyV6zRr\nWAfTZ/pdWzbWXMf75Dmdcto2baS13byh5nfhVV/N4gkmxsYM8OrE2cvX8Ll5JzNu4869KBQKBvXs\noreuBZWYqJmYLuc+T0MSEnKfuGre5LH4Bwbz3rgvuffwMVExsazevJOfV28CQJWiyoyt4l6ODcu/\n5dT5K5Rt+A7W5evTedBomtSrxU/zp2qVq1arSUpOxtzMjL1rl/Pw3AEWzviMLX8dwLPLAGLi4p7n\n1sVbKiYhidO+j2lSpSQmRgZax1rVLAPA+dv+Ouc1q1paa9vZzhKAwIgYvddUparp1sgjc/tJXCIX\n7wbiWbmkziQXzdOvc+zaA51yWlYvo7XduHJJAHweasZomBgZ0LtZNS7cCeDGo6xn2JZjPigU0K9F\ndb11LajEZE07NjY0yPa4saEBCcmqbI9lqFTCiVUTenD21mOqjPoRl77z6TFnHY08SvD9qA4vvM5C\nCCGEEEK8zqKjozl+/DgtWrTA5Jlx1e3btwfg9OnTOue1bt1aa7to0aIABAQE6L2mSqWid++scdWR\nkZGcO3eO5s2bY2qqvWhFxnUOHTqkU067du20tlu00IxFv3LlCgAmJiYMGjSIM2fOcO1aVq5m3bp1\nKBQKhg4dqreuhSUhfdy3sbHupNsZ++Pj87dooxDi1ZCc0MshOSEhhBBCCPE8tp24TvGB3/DT7jP8\n7+OudG3oof8kIcRbZ+e1cCrMOc3yEwEs9ipHp8oOhV0lIZ5bTGIKZ+6F41mhCMbPLFjV0kMzJ8uF\nhxE65zWt6Ky17Wytyc0HReU+Pg9ApU6ja63imdtP4pO59CgSz/JFdPJhGdc5flt3jGQLDxetbc/y\nTgCZC/0aGyrpVa8kFx9G4BuYtTjotvN+KBTQt34pvXUtqMSU1Mw6ZMfIUKk3F6VOSyNJpcbc2IAt\nHzXl2uxOzOlRg52XHtP2m3+JTcr5/CfxyQz6+QTRCSksGVgPA2XWYqPTu1Yj4EkCo1ed4UFYLNEJ\nKaw//YDfj90DICVVnd/bFeKViUlI5sytQBpXctPJ9baqpslHn78bpHNesyoltLadbS0ACHoSq/ea\nqlQ17zaokLn9JC6JS/dDaOzhpvPMalZZ82w7dl178WKAFun1y9CkkibWxy8c0OSoezf24MLdYG48\nDs+M23rqpuaZ1bSS3roWVEb+3CiX/Hl8cvbzQGXncXgM64/e4P221bG10F3IOzAyli9WedOhdlm6\nPfXe5kVkbCIDFu0mOj6ZpaPaaj3fhBBCvHg7LgdSbsp+/nfkPkv6VqdzNRf9Jwkh3jqSExPizXJ2\n31ZGNy7KP2uWMHz2Cuq06VbYVRJCr8w8dXmnbPLUmr9BLzzIT54697mzIZ95avf0PPWtEJ1ycsxT\n+z8BMvLUpdLz1FGZcdvOP9LkfBpoj/t8kTLz1Aa55alTcy1DnUZ6ntqQLR8349qczszpWZOdF/1o\n+80BrTx14JMEJm+6yDvVXLXe2+zkJ1a82WISUzh7LxzP8rr9UBntJ9t+qApOWtuZ7Ts6b+373Zpu\nmdtR8SlcfhRJo3KO2fRDaa6TbT+Uu/YzxrNcEQBu+D/VD1W3BBcfRmr3Q114jEIBfepr54RfpIz2\nbZRT+zZQkpCir32nkaRKxdzYgM2jG3N1VgfmdK/Orkv+tPv2UGb7Lui17ofF4vLJVqp++Rff7b3B\nlM5VGNfOPc/3KMSbRD43C/H2kvYtxJtDxnkLIYQQQgghxOvHUH+IEEIIIYQQQgghxJvBY9yfeYpz\nrN8Nx/ryJQ5R+AKCglGr1fy5cQt/btySbYyfv/YiAAYGBjjY22ntUyo1A4hVqtwnyAFQKBQUdc4a\nBB4QGAigtS+DcxHNwGz/9JgMRkZGOnWwt7MFIDg0a8D38CED+H7pz6xcs55v58wAYOO2HbRq3oSS\nxd14WczNzABITsl+8o2MhQlz07Vje3ZvWsOUr+ZRtUEzLC0saNW8KRt+X0HNxq2wsrIsUOzTVq/f\nhEqlYtjg/gW8UyFg/u878xTXqktvWnXprT9QCPFK7d27N09x/fr1o1+/fi+5NkIIIYQQQggh3hbb\nvhmXp7ierevTs3X9l1wbIUR+SZ+neNMEBoeiVqtZt20P67btyTbmcYD2YgQGBkrs7Wy09mX1eeY+\nGRNo+jxdnIpkbgcEaSadc3Fy1Il1crTXislgZGioUwc7G812SGjWwgPD+nVn8a9/8sfGHSyY+ikA\nm3b9Q8vG9SnhWlRvXQvKzEwzkVfOfZ4pmTE56dK2BTt+/5FpC5ZQo3V3LC3Madm4HmuXLaBu+95Y\nWlpkxq7d+hcjP5vJJ+8PYMSAnrg4OXLZ5yajJ83Gs/MADm35Dcf0PuIj2/7QuZZXh9YolUr6jJrA\nd8t+Z8aE0QW9dfGWCoqIRZ2WxsYj19h45Fq2Mf5h0VrbBkoF9lbafftKhWaxi1S1/oV6FApwtrPK\n3A4M1ywW7mKn24dfJH1BlGcXFDcyUOrUwc5Ssx0SFZe5b0jrmizbfZo1hy4zZ3BrALaeuE6zqqUp\nXkT7WfMimZlovhaWnMOzM1mViplx7l8d23DkKmOW7ubDzvV5r21tnO0suXo/iHE//03Lz3/j79mD\ncbQ2f+F1F0IIIYQQ4nUUEBCAWq1mzZo1rFmzJtsYPz8/rW0DAwMcHLQnv8z32O6iWTkGf39/AK19\nGZydnbViMhgZGenUwd5ekxMJDg7O3DdixAgWLVrEb7/9xsKFCwHYsGEDrVu3pmTJlzdB9/MyN9d8\nJklOTs72eFJSUmaMEOL1Ijmhl0NyQkIIIYQQIjubp/TNU1yPxpXp0bjyS66NEKKw/Dkwbwt/dKvm\nSLdqumOthHiTBUUlok5LY/PZR2w++yjbGP9I7YU1DZQK7CyMtfYplZpclCqvuSjrrHF8QVGJgPa+\nDEWsTADNwrBPMzJQ6tTBNn07NCYxc9/ARmVYfug2a0/d56tu1QHYccGPphWdcbN/eXkcM2PNYqLJ\nquzfD00uKvf5W/aMb6mzr3MNN5QKBe/9epIf999kUifdv08ehMXS73/HCY1J5M+RnlR1s9U6/k61\nYqwd1Zi5u67ReM4/WJgY0qyiE7+814AW8/djaSpTbovXV1BkHOq0NDYd92XTcd9sY/wjYrW2DZQK\n7C21ny+Zz6zUNL3XVCjA2TZr7HBgpKZ8Z1vdZ0gRG3OtmAxGBkqdOthaaJ5voVHxmfsGtajCsr0X\nWXv4OrP6NwFg26nbNKtcguKOVrwsGbnxlBzy50kpKsyNs58HKjsbjvmiUqsZ2CL7z1CfrPgXgG+H\ntshXPR+ERNH7mx2ERsez7tPOVC1ZRP9JQgghsrVueN08xXnVLIZXzWIvuTZCiMIiOTEh3izjftqW\np7j67/Sk/js9X3JthHixsvLUD9l89mG2Mf5P4rW2s81TKzLy1HnM+WjlqTU5aGdr3bxtZp46Kj95\n6qTMfQM9y7D80C3WnnzAV17peerzrzBPnZpbntog1zL2fJpLnvqXE/y435dJnaoAMG7tOQAW9K6l\nt275iRVvtuCM9n3uEZvPZd8PFZCXfqiMMdF5zOk6PdW+M9qus00u/VBRiVr789y+G5Vmufcd1p16\nwMxu1QDYfuExTSs4veT2nZ7Tzal9p6oxM8q9ff81rrnOvk41XFEoFAz77RRLDtzii46VCnyt0o6W\nBP3gRVR8CsfvhDJl82W2X/Bj04dNsDE3yrVuQrwu5HOzEG8vad9CvDlknLcQQgghhBBCvLnkmylC\nCCGEEEIIIYQQQhSyYYP6sfyHb1/JtZRKJQYGuoOK09J0B4Bn7FOkDxLPKkORY6xSoczc516+HE0a\nNeDPjVuYP/NLrl335ebtu0z7YsJz3YM+Li6ahQ7CwsJ1jqlUKiIin9CkUQO95bRv3ZL2rbW/rOFz\nQzOBSulSJQscm2HLjt3UqVWDUiWK662LEEIIIYQQQgghhBBCCCGEEK+zoX26sWz+1FdyLaVSgYGB\nUmd/9n2emn91+zyzOZ80nWMVy5aicb1arN22h7mTxnLt5m1u3XvAl+NGPs8t6FXUSTOBRlh4pM4x\nlSqVyKgoXF30TwzXrrkn7Zp7au3zuXkHgNIlXDPL+2TqfBrVrcnsz8dkxtWtUYUV382kfoe+LFy+\nirmTPsn1Wm2bNUKhUHDmUvaLOgsBMLBVDX4Y1fGVXEupUGCQ7fgG3djMfXkZH/FU+RnKuzrQqFIJ\nNh25yswBLbn+KIQ7AeF80atpQaufJxmLmIdFxescU6WqiYxNoKFHiRzPV6WqmfjLXhp4FGd6/6wx\nD7XLu/LT6M40m/gLP+44ycyBrV585YUQQgghhHiNDR8+nBUrVrySa72Ysd0550mePubu7k7Tpk1Z\ns2YNCxYs4OrVq9y8eZMZM2Y8zy28dEWLFgUgNDRU55hKpSIiIoKmTV/u5y8hxPORnNCLJTkhIYQQ\nQgghhBBCiJz1b1iahX1rv5JrFSQX9UwqSmdbE5sxf8tTuShnKxqWdWTz2UdM61qNGwFR3AmJYWKH\nSgWuf15kLCIcHpusc0ylTuNJXDJFy+ouKpwXLT1cUCjgwkPduWHO3g9n0M8nsDAxZNfYFrgXtc62\njFaVXGhVyUVrn29gNAAlHSwKVC8hXqWBzSuzaNirycXm+MzKJjbzmfXM/mf7KZ8+/+kuy/LF7Gjo\n7srG475M7+PJjcfh3AmM5HOv+gWqe14522rafXhMgs4xVaqaJ3FJFLXP+7Nh55nb1CzjTAlH3WfQ\nn4evc/DqQ3756B2cbPK+GPKZ24EMXLQbCxMj/praEw83hzyfK4QQQgghhBBCiDdD/0alWdi3ziu5\nVs45n1y+c/9M1if3PHXWvvLOVjQsV4TNZx8y7d2n89Qvd5H6rDx1ks6xF5anfhABwNpT9zl0I4if\nhzbAKf26OclPrHh79G9Yiu/66J/j4UV42f1QTy0jQDlnKxqUdWTzOT+mdq3KjYAo7obEMPEdj4JW\nP0+c8tAP5VLWsUBlt/RwTu+Hingh17IxN6JDtWK42ZnT9tuDLD5wk6ldqhSobkIIIYQQQgghhBBC\nCCGEeHMYFnYFhBBCCCGEEEIIIV6VG4v6E337DPWX3i7sqggBgFuxoiiVSh76PS68OrgWQ6FQEBAU\nrHMsMDgEgOKuxbT2JyUlExUdjY111kQV4ZGaRQidnYpoxY4YOpCB74/mgPcRDh05jr2dLe92fCfX\nOoWFR+BSTv9A5mtnjuBevpzO/mIuzrg4OeHje1PnmO+t26hUKurUrKG3/OycOH0OgMYN6j1X7L0H\nD7ly7TpfjPu4QPUQ4mX4YkgXrp47yV/XdBfLEEIUjvbt23Ps2DFiY2MLuypCCCGEEEIIIf7Duk1c\nxMmrdwja+1NhV0UIgfR5itePq4sTSqWSR/6BhVYHt2IuKBQKAoN1+ziCQjT73Io6a+1PSk4mKiYW\nGyvLzH0RkVEAODlqT6o/vH93hnwyhX+PncL7xFnsbW3o2q5FrnUKj3iCa62WucYAXP53KxXLltLZ\nX9S5CM5FHLh+667OMd8791GpUqldrWCT4506fwUAzzo1AXjkH0hMXBzu5UrrxFYoUyr9mvcASE5J\nwefmXawszClXWnsx4aTkZNLS0jA1MS5QvcTbrZiDFUqFAr/QqEKrg6ujNQoFBEbG6BwLTt/n5qC9\nYEdSSirR8UlYm5tk7ouM0Syy7WSjvSDIkDa1GPHDdryv3OfItQfYWZrRsV7FXOsUHhNP+fcW6a37\n6e9HUd5Vd8EPFzsrnGwt8X2s+/y75R+GKlVNrXJFcyzXLyyK2IRkKrjqTk5XvphDejm6iy0JIYQQ\nQgjxtnJzc9OM7X74sNDqULx4cc3Y7oAAnWOBgYGZMU9LSkoiKioKGxubzH3h4Zq/5Z2dtXMiI0eO\npH///uzfv5+DBw9ib29Pt27dcq1TWFgYRYoUyTUG4MaNG7i7u+uNy69ixYrh4uKCj49PttdUqVTU\nrVv3hV9XCPH8JCeUPckJCSGEEEKI112POes4dcOPx2s+K+yqCCEKqP/qG5x5FM3tKfULuypCvDLF\nbM1QKhQ8jowv1DooFBAUnaBzLDg6EQBXO3Ot/ckqNdEJKVibGWXui4zTLEJZxEp78dhBnmX4YNUZ\nDvsGc+xWCLbmxnSo5pprnSLikvCYtEtv3Y9NaUd5Zyud/S42ZjhZm3IzSDfHdzsoGpU6jRol7HIs\nNyVVzY2AaCxNDSlTxFLrWJIqlbQ0MDEy0Np//kEEvZcepbyzFX+ObIyjlQn5cfZ+GAD1C7g4qBCv\nQjF7S03+PEw3d/2quNpbaZ5ZkXE6x4KfaPa5Omg/F5JVqUTHJ2NtnjVWODJW83wrYq39fBvSogoj\nl+3D+5ofR6/7YWdpSsc6ZXOtU3hMAhU/XKG37ie/Hkj5YrrPHhc7C5xszPF9HKFz7FZAJKpUNTXL\nOOscy87DkCh8HoUxtnP2C7df99M8a4Yv+ZvhS/7WOd5k0p8ABP3+EYYGmlWVz90JoueC7VQoZs+6\nT7vgaF2wRcqFEEI8n76/nOXM/Ujuzmlb2FURQrwikisT4u21aHQ37lw6yU/Hgwq7KkIAT+WpIwoz\nT22uyflEJeocy8pTa+ck8p2n/uO0dp66up48dWwSHpN26q37sS/b556nDozWOZaZpy5pn2O5mjx1\nFJamRrnkqTX5m+v+mlz4iJWnGLHylE5Zzeb+A4D/Dz3yFWuoVORYP/FmKPpatG9NP1RwNu07JL19\nF7N9nvZdmg9XneWIbwjHbmf0Q2mvS/CsiLhkKk3erbfuxya3oVy27ds0l/Ydg0qdRk09/VC+gdFY\nmOj2QyWr1Jr2bajM97X8I+P5dq8vDcs50quu9pwaFVw093ErSLccIV538vlYiP8eafdCvL1krLcQ\nQgghhBBCvDqGhV0BIYQQQgghhBBCCJE3aaoU7v4+gdCTmynZayrF2o0q7CqJ52RpYUHjhvU5fOwk\nQSEhuDg5ZR47dvI0H4z9jN//t5jaNavnu2ylUjPIOC0tLdc4G2trGtStzeFjJ0hITMTMNGsQxsmq\nTAAAIABJREFU9j//egPQtqXuQoYHDh2he9dOmdveR08A0NSzgVacV+eOjLX/kj83bOHwsRP06+mF\niZ7F/xwd7FFF6i5gkB99e3Zj2S+/ExoWTpGnFmvcuHUnhoaG9O7eNdfzP508nb/27efqqcMYGWkG\nq6vValb8sQaPCuVpVL9ugWIznDh9FoDqVQu2QKMQIsuGnxfx8/wpOR7/53Y0BgbSHSLEq3bz5k2m\nTJnCwYMHSUxMpFSpUvTs2ZOJEydiaWmpvwAhhBBCCCGEEOIFuOD7gO/+3MO5G/cIj4rFtYgdXZrW\n5vNBnbA0N9VfgBDihZM+z7ePpYU5nnVrcuTkOYJDw3EuktU3d/zMRUZPns2vC2dRu1qlfJed5z5P\nK0vq16rG4VPnSEhMwsw0a+GP/UdOAtCmWSOd8/49egqvDq0zt71PavrwmjaopRXX7Z1WjJ+xgHXb\n9nD41Dn6vPsOJsa593k62NuS+OBCrjH69On6DstXbyQsIhJH+6xJqjbv3oehoQG9urTL9fyJX33L\nnoNHuXRgC0aGmr4StVrNr+u24F6uNA3raPqhnYs4YGJsjM/NOzplZOwr6aaZqCspOZmWPYZSp3oV\n9m/QXmxh76FjADRvVK+AdyzeZhamxjT0KM5xn4eEPInFyTarr+DkDT/GLd/Dso+7ULNszotU50Sp\n0EyCqO9ZYW1uQt0Kbhz3eUhisgpT46w+xIOX7wHQskYZnfO8r9yjSwOPzO2j1x4C0KhySa24zvXd\nsbcyY+ORqxzzeUTPJlV0Fip6loOVORGbcu7rzIsejSvz677zhEXH4/jUYirbjl/H0ECJl2fO4xKc\nbS0xMTLghp/uwuE3HoUAUKKIzXPVTwghhBBCiDeJpaUlTZo0wdvbm6CgIFxcXDKPHT16lJEjR7Jq\n1Srq1Ml+wb/c5DnPYWNDw4YN8fb2JiEhATOzrMm49+3bB0C7dro5gf3799OjR4/M7UOHDgHQrFkz\nrbju3bszZswY1qxZg7e3N/3798fEJPdFVB0dHfXW+2Xr168fS5cuJTQ0lCJFimTu37BhA4aGhvTp\n06cQayeEyInkhLInOSEhhBBCCCFejdiEZJpMWMHDkCcc/24EHiWK6D9JCPFaSElNY8KOu2y+HMrU\ntiUZ5Zn9IoOX/GNZctSfC49jiYhPoZiNCR087BnbzA1Lk9w/n4u3j4WJIQ3KOnLidigh0Yk4WWeN\nFT91N4wJ6y+wZGBdauSyYGROsnJRucdZmxlRp5QDx2+HkpiSiulTeSLvG5oFqVu4O+ucd/hmMJ1r\nuGVuH7+tyds0LOeoFdephhuTt1xi87lHnLgdSo86JTBOX8AyJ/YWJgQv7pFrjD5etUuw8thdwmOT\ncLDM6lPYfuExhkoF3WoXz/HcJJWazt8folZJe7aN0e6z+Pe65j1pUj5rrh2/iDj6LjtKOScrtnzc\nDEuTnOeJmLr1Mvt9Ajk6uS1GBpr3QZ2Wxurj9ynvbE290o45nitEYbMwNaJBxWIcv/GYkKh4nGyy\n8rynbgYw/reDLB3VlhqlnXIpJXsZ60rrfWaZG1O3XFGO33ismz+/qsmJt6haQuc872uP6FKvXOb2\nseuPAWjk4aYV17leOSatPsymE74cv/GYHo0qYmyoL39uRtjqMblXXI8ejSry64ErhMck4GCV1de6\n/fQtDA2UdGtQIU/lnL4dCECVktl/jpgzoClzBjTV2f/7watMWHmIo/P64+GWNa7+UVg0vb/ZQbmi\ndmyb1A1L09zHogshhBDZueofzdd7b3H2QSQJKam42ZnRoYoLY1uXzfZv55RUNeM3XWPzeX+mdXLn\ng2alC6HWQojncTcsga//9ePY/SiSVGqK25rQqbIDH3gWw8JY8l9CvMke+Fxgz2/fce/aOWKfhGPn\n7ErtVl3oNPxzTC1knsY3lf489XmWDKz3ivLUITnnqT1cdM7TzVNrxhI2LK+dG+lUw43Jmy+y+exD\nTZ66bh7y1JYmBP/YM/eK6+FVpwQrj2aXp/bLW556UXqe+pPmWscy89QVNHm42d1rMLt7DZ0y/jh2\nl882XODw5La4F7XJd6x481mYGFK/rAMn7oTptO/Td8OYsOEiSwbUoXoB2rdCmccx0Rnt+45uP9Qh\n32AAWnjo9kMduRlCpxqumdsZ/VCNyj7TD1XdlSkWlzX9UHdC6V6neB76oYwJ+sEr1xh9vGoXZ+Wx\nezrte8dFTT/Uu7XccjxX0w91mJol7dj2sXa+9kB6+25cISvPntdrOViasP2CH9ceP6FHneKZz2CA\nK35PACjlKL+vhXjV8jKWZNnxAGb/8zDHMh5Ob4ChUpHjcSHE60PyYkL8N8hYbyGEEEIIIcSbIPfe\nEiGEEEIIIYQQQgjxWlDFR3F9YV8SQx8UdlXECzZ/xhQMlEq69B6E7+07JCYlcfjYCYaMGoOxiTGV\nK7kXqNxiRTVfrDhz/iKJSUmoVKocY7/+aioxsbEMGz2W+w8fERsXx7/eR5k2+2sa1a+LV5cOWvFm\npqbM/mYRBw4dIT4hgas+N5g0fTYuTk707NZFK9bExJhBfXuxYesOAoKCeW9gvwLdT359MX4Mjg72\n9H1vFHfuPSAxKYkNW3fw3ZJlTJ7wCSXcsgag/+t9FEO7Ynw29avMfe1ateDeg0d8PHEy4RGRBIWE\nMGrsRHxu+LJ88bconhqAnZ/YDLdu3wWgTKmSOseEEPkTGx0FwI5Lgfx7L17nZWCQ8wRfQoiX4/r1\n69SuXZuQkBCOHDlCcHAw06dP55tvvqF3796FXT0hhBBCCCGEEP8Rxy/fot3H8zE2MmD/ki+4v30R\n09/34uftB+k6YSFqdeEuXCvEf5H0eb695k76BAMDJd3eG8PNuw9ITErmyKlzvDd+KibGxlSuWE5/\nIdko5qz5YvaZS9dITEpGpUrNMXbepE+IjY1nxITpPPDzJzYunoPHTjP9259oWKcG3dq30oo3MzVh\n3uIV/Hv0FPEJiVz1vc2UeT/gXMSB7h3basWaGBszsHtnNu7aR2BwKEN6v1ug+8mvz0cPw8Hejv6j\nv+DuAz8Sk5LZuGsfi35ezRcfDad4sazJ9g4eO41pqVp8MWdR5r62zT25/8ifT6bOJyIyiuDQcD6c\nNBufm3dZNn9qZj+mhbkZ40YM5NiZC0xbsITHgcHEJyRy5uJVRk+aja21FR8N1fTzWllYMHXcKI6e\nPs/Er77FPzCYqJhYNu/ez4SvvqWaRwWG9+v+St4f8eaZMaAlSqWSPvM2cts/nKQUFcd8HvLBjzsw\nMTKgUgEnYyjqYAXA+dsBJKWoUKWqc4ydOaAVsQnJjP5pFw9DnhCXmMzhK/eZve4w9d3d6Fxfe4yG\nqbEh32w+hveV+yQkpeDzMIQZaw7iZGtJt4YeWrEmRgb0aVaNrcevExQZw4CW1Qt0P/k13ssTB2tz\nhi3ayr2gSJJSVGw9fp0lu07xaffGuDlaZ8YevnIf+55zmLrqAADmJkZ81LkBJ64/YtbaQ/iHR5OQ\nlMK5W/6MXb4HGwtTRnas90ruQwghhBBCiNfF119/jYGBAZ06dcLX15fExES8vb0ZNGgQJiYmVKlS\npUDlurpqxi6fPn2axMTEXMd2L1iwgJiYGIYOHcr9+/eJjY3lwIEDfPnll3h6etK9u/ZnbzMzM2bN\nmsX+/fuJj4/nypUrfP7557i4uNCrVy+tWBMTEwYPHsz69esJCAhg2LBhBbqfl+nAgQMoFAomTJiQ\nuW/y5Mk4OjrSu3dv7ty5Q2JiIuvXr+fbb7/lyy+/pEQJ3YUohRCvB8kJvRySExJCCCGEEEK/yb/v\n52HIk8KuhhAin6ISVPRddZ0HEYm5xp16GE2333wwMlCwY3gVrn5el0mtSvD7mSD6rrqBDBP+b5ra\ntSpKpYIBy49zOziGpJRUTtwO5aPVZzExVOJR1Fp/IdkoaqNZ0PPCwwiSUlJR5fIfbFrXasQmqhjz\n5zkehccRl6TiyM0Q5v3lQ70yDnSsob1gpamRAQv33uCwbzAJyalcD4jiq51XcbI2pWtN7cVrjQ2V\n9K5Xiu3n/QiKSqBfw9IFup/8GtvWHQcLY95feYr7obEkpaSy/YIfSw/eZFw7D1ztzDNjj9wMwXnM\nZmZsvwKApYkhn3WoxIk7oUzdepmAJwlEJ6Sw4+JjvtxymcquNgzyLJN5/qRNl0hUqfnlvQZYmuQ+\nT0RLDxcehsXxxaaLRMYlExKdyKfrL3AjMIqFfWuTzVQvQrxWpvfxRKlU0Pe7ndwOiCQpJZXjNx7z\n4f/+wdjIAA83hwKVW9ROswDthbtBmmdWLvnz6X0aE5uYwscrDvAwNJq4xBQO+/gxd9NJ6lcoSue6\n2mPATY0N+W77GbyvPSIhWYWPXxgzNxzHycacd+uX14o1NjSgTxMPtp28RVBkHAOaVS7Q/eTX2C51\ncbAyY9iSv7kf/ISklFS2nbrFkr8uML5rXdzS+xcADvv44ThwMdPWHdMp505gJAClnF7Mgt2f/+FN\nYoqK3z7ugKWp8QspUwghxH/L5cdRdPzxBJYmhuwf15jrM1szs4sHa8/40fvns6jTtD+nRCWk0GfF\nWR6GxxdSjYUQz+tWaALtl18hLC6Fre9V5vLEOoxvXpxlxwMYtfF2YVdPCPEcbl04zvxh7TAwMuaL\nlftZdPA+Xh9P5+CGn1n4YVfS1Dl/lhevv6ldq2ny1P87pp2nXnXm+fLUtmYAXHiQhzz1u+l56jVn\nn8pTBzNv9zXqlXHMIU99PStP7R/FVztyyVPXL4w8tYcmT/3bU3nq834s/fcm49pXeiZPHYz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u0eNmxYHpGF57PPPuOzzz7LV2zz5s3JzMzMcbxUqVKsWbOmsJsmhPgHSJ9Q0ZA+ISGEEEKI4isq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Jv7B0+4lcn5cQz1ubytbYmxmy61IUHvUd8L4VR2RCGtM6umqVG73pOoeuR/NxWxf6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\nDcAjLSxvHmFr+1S1ni1X/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vAZkCiVSmVhD0IQBEEQBEEQBEEQ/usuXrxI3bp1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\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Pi7//RqU+zm73sWLdZnh6+0ChUKCNdSss/Hoexo8eUdhm+IRP4eTiDklUKADA1z8QCxYv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\n6NKleuc3EREREVF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KVHFsvzWlfr95\n8wYbNmzAtWvX0LhxY0yaNEmwLFT0dHV1YW5uDgcHB1hYWAgdh7TYzp070b9/f+S3pI9YLMa2bdvQ\nt29fNSej4uR/5z+lp6fj7t27iImJQVRUFO7fvw+5XA6RSASVSoV27dph5MiRQscmKnRsv4mIiEgT\naOL6BETPnz/H5MmTkZWVBQsLC7Rt2xYtW7aEjY1NkZ2zOPbPWb//m9TUVEyZMgVv374tcENG0h7F\nsX6TMDh+TpoiMjISw4YNQ1RUFKZOnYoZM2bkWBsuLS0NNWrUwNOnT7FlyxZ4e3sLmJaIiIiIiCin\np0+fonbt2khKSkJ4eDhat26d43hERASGDx+OFy9eYN68efD19YVYLBYoLZUEb9++RenSpfMdR5dK\npejWrRsOHDig5mRE9KVYv0lTJCYmYurUqdiwYQO6deuGNWvW5Jor5uvri9WrV6Nbt24ICwsrFnOr\niIiIiIiIiIiIiEhQe0Wq/J58JyIiIiIiIiIios9StWpVxMbG5nlMIpHAwcEB+/btQ9WqVdWcjD4m\nKioKGzduRNjBg7h3967QcagEk0qlaN68OXr06AFvb2+Ym5sLHYmIiIiIiIiIiIiI6D9bvHgxpk+f\nDrFYjO7du+dYwCctLQ2rVq3C/PnzYW1tjR9++AE9e/YUMO2XS0hIQGBgIIKDg3H27FkoFAqhIxFp\nFHNzc3Tq1An9+vVD165dIZFIhI5EJUzNmjURExOT5zGpVAo7Oztcv34d+vr6ak5GQspuv4P24+y5\nc1AosoSORKRRzM1M0alzZ/Tr15/tNxFpjH/a76D/b795/U30b+ZmZv/ffmvf9feH+r0/KBjnzp1F\nFus3CahK1Wpwc3XB4MGD4eDgIHQc0jJpaWmwtLTEu3fv8jyup6eHV69ewcjISM3JSNt9mP90MCwM\nd+/dEzoOkcapVrUqXFxd2X4TERGRWmT3z0MP4G7sA6HjEGmcalUqwcWth1b2z7PXHwk5gHv3Wb+J\n/lfVypXg6q6d9ZuEx/Fz0iQKhQIBAQH47rvvULlyZWzYsAGNGjUCAHz77bdYsWIFFAoFdHR0cPHi\nRdStW1fgxEREREREREBGRgaaNm2KW7duQalUokKFCrh9+zb09PSQmJiIqVOnYsOGDejWrRvWrFmD\n8uXLCx2ZSoiePXsiJCQEcrk81zGxWIzdu3fD09NTgGRE9KVYv0mTnD59Gj4+Pnj58iXmzp0LX19f\niMVinD9/Hs2bN4dKpYJYLMbcuXMxc+ZMoeMSERERERERERERkXbbK1KpVCqhUxAREREREREREWm7\nhw8folKlSgWWkUql0NHRwcaNG9G7d281JaOCxMbGYtKkSQgNDYVdpSro7OqOZi3boIa9IywsS0FH\nV1foiLk8f/YEhoZGMDO3EDoKFaKUlLd4+ddfuHX9Gk4e+wO/HwyBUpmFb7/9FlOmTIGBgYHQEYmI\niIiIiIiIiIiIPsu+ffvQq1cv/Ptx9T/++APOzs4ICwvD2LFj8erVK0yePBnTp0+Hrgbel/lUaWlp\nWLJkCfz9/SGRSODu7o7OnTujfv36KFeuHIyNjYWOSB9x4MABuLu7Cx2jWFIqlYiPj0dsbCzOnz+P\nsLAwnDx5EpUrV8bSpUvh6uoqdEQqQZo1a4bz58/neUwmk+HSpUvcqKEEyW6/lyyBRAx0a14Xzo0c\nUadaRdiUMoORgV6RZ1AqVbga8xBONe0gEomK/HxEn0qpVCHhbSoePI/Dpaj7+O38DUT8GYPKleyw\ndNlytt9EJJh/rr+XQCISw6V9Mzi3aIi69lVhU6YUjA35nB3941rUHdR3qC50DLVRKlVISErG/SfP\ncfH6bRw+eQGnL0WicqVKWLpsmca33x/q95Il/oBYgrptusGxmTMq1qwDs9I20DPUjM0eU5MSIM98\nB7PSZYWOQkVEkZmBt4lv8Dz2NmIun0ZkeChePnkAFxdXLFu2FFWqVBE6ImmRvn37Yv/+/bk2PpBK\npfD09MTOnTsFSkbaKDY2FpMmTkRoWBgqV/wKbh2ao3WjenCoagdLc1Po6sg++hkqlQoPn71ApfI2\nakhMpD4ZmXK8SUhC1L2HOHXpT4QcO4v7j5/B1cUFS5ctY/tNREREhe59/3wCQsMOws7aHN3q2KBF\ndWvULGcOSyNd6EglQkckgjxLCZVKpfbfx0xFFt6kZCD6eQLO3HmJQ9f/wsOXCXB16Y6ly5ZrfP88\nR/0uY4qujqXRvEop1CxrAktDHehIxUJH1DrHo/9G+5pWQsegQpCpUOJNaiaiXyTjbOxrHL71Cg/j\nkrSmfpNm4fg5aZr79+9jxIgRCA8Px7BhwzBo0CC0bNkSWVlZAN7/bpYpUwbXr19HqVKlBE5LRERE\nREQl3fDhw7F582YoFAoA769Zpk6disaNG2PUqFFQKBRYsmQJvL29BU5KJc2BAwfg4eGBvLZC1NfX\nx5s3b6Cvry9AMiL6UqzfpGnS09OxePFi/PDDD2jUqBHWrFmDXr164f79+9l9JJFIhEOHDqFLly4C\npyUiIiIiIiIiIiIiLbZXpMrrDgkRERERERERERF9llWrVmHixInZD3rmRSwWo2nTpti+fTsqVqyo\nxnT0v969e4e5c+di+fLlsKtcBTPmLUKbDp24sRZpjJSUt9j263r85P8DzMzNsHLFCvTo0UPoWERE\nREREREREREREn+Ty5cto2bIlMjMzsxf0kUgkqFixIqytrXHhwgUMGjQICxYsgLW1tcBpv0xwcDDG\njx+PxMREzJw5EyNHjoSxsbHQsYg0WmxsLObMmYOdO3fC2dkZAQEB3AiE1KJ79+44dOhQrtfFYjEW\nL16MyZMnC5CKhBAcHIzx48YiMSEe3w7oiqGubWBkoCd0LCKN9uB5HBZsCsW+4xfh3KEDAtasYftN\nRGr1vv0eh8SEeEwd0R/DervA2NBA6FhEGu3+k+eYH7AFew6d0Oj2Ozg4GGPHjUd8QiK6Dv0WbTyH\nQs/QSOhYRAAAlUqFW+eOIWjlLPz99D4mTpiAOXPmQE+P15D0cQcPHoSLi0uu10UiEUJDQ9G9e3cB\nUpG2+Wf+0zJUqfgVFkwcDucWDTn/iagAKpUKR89cxndLNyD2yTNMmDCR7TcREREViuz++bJlqGRl\ngtnuddDOoRzYPSfKn0oFnIh6jnnBkXgQl4wJEydpZP88R/0ubYhZXaujbY0yrN9EBVCpgPCYOMw7\nfAcPX6VobP0mzcTxc9JEKpUKv/zyC6ZMmQKxWIzk5OQca8nJZDK0aNECR48ehUQiETApERERERGV\nZFu3boW3t3eu18ViMVQqFYYOHQp/f3+YmZkJkI5KuszMTJQqVQpv377N8bpMJkPfvn2xZcsWgZIR\n0Zdi/SZNde3aNQwbNgz37t1Deno6srKyso+JxWIYGhoiMjISlSpVEjAlEREREREREREREWmxvSLV\nh9X1iYiIiIiIiIiI6D/r0KEDwsPDoVQqcx2TSqVQqVSYOXMmZs2axcn8AouLi4O7uztu347G5Jlz\nMWCID6RSqdCxiPL0Ou5vLJz7HfZuD8S0adOwYMECLtpNRERERERERERERBrt4cOHcHJyQlJSUo6F\nUoD3i6XUq1cP69atQ4MGDQRKWDhUKhW+++47LFq0CIMGDcLChQthZWUldCwirXLmzBn4+vri8ePH\n2Lt3L9q3by90JCrmvLy8sGPHjhzPdshkMjRs2BCnT5/m8xwlwL/b7/6dm8PPxwNlzE2EjkWkVc7f\nvIdvf9qFp68SsXfffrbfRFTk/t1+e7l3wrwJw1DG0lzoWERa5dy1W5j4w2o8ffEKe/ft05j2+9/1\nu7lrf3iM8YOJZRmhYxHlSZmlwMl9GxGy9ns42tsjNOQAypTh7ysVTC6Xo1SpUkhOTs7xurGxMV6/\nfg0dHR2BkpG2iIuLg7ubG6JvR2G27yAM6+0CKccwiT6ZIisLv+wOw7xVm1HT3gEHQkLYfhMREdF/\nFhcXB3dXF9y+dRPTXGphYOvqkIo535voUymUKmw5dQeLwm7C3rEWDoSGaUz//J/6fQNTO1WFdzNb\n1m+iz6BQqhB47hEW/34P9o61Nap+k+bi+Dlpsg/3sPNaR04sFmPmzJmYO3euAMmIiIiIiKiki4yM\nROPGjZGZmZnrmFQqReXKlREVFcU5kiSoIUOGYPv27bl+T48cOYJOnToJlIqICgPrN2mq27dvo06d\nOlAoFLmOyWQyVK1aFZcvX4aBgYEA6YiIiIiIiIiIiIhIy+0VqVQqldApiIiIiIiIiIiItFlKSgos\nLCwgl8tzHZNKpbCzs8Pu3btRr149AdLRv0VFRaFb9+4Qi6XYuPsAqlSrLnQkok+yd0cgpo0bBRcX\nF2zduhX6+vpCRyIiIiIiIiIiIiIiyiU5ORkNGzbEw4cP87x3BgAmJiZ48OABLC0t1Zyu8KSnp8PL\nywthYWFYv349Bg4cKHQkIq317t07DBkyBPv27UNAQACGDx8udCQqxsaMGYP169dnt1EikQiGhoaI\niopChQoVBE5HRS09PR1eAwYgLCwMP03yQr/OzYSORKS13mXK8c3izQg5fRUBAWvYfhNRkXl//T0A\nYaFhWD13Iga4dRQ6EpHWepeRiZGzfkTwH6c14vo7PT0dA7y8EBYaBq+ZP6GZSz9B8xB9qpeP7mL1\n+F7QESlx+NBBODg4CB2JNNyIESOwefPm7I0PZDIZBg8ejHXr1gmcjDRdVFQUunfrBgmysC/ge1S3\n4/gl0X915+ETeI6ehSxIcPDQIbbfRERE9NmioqLQvWsXiDJTsG1UK1S1NhU6EpHWuvcyCQPWnoJK\nxxgHD/8meP88u36/S8bWIQ1QpYyRoHmItFlsXAq8Nl6BUs8Ehw4fEbx+k+bj+Dlponv37sHR0THX\nhtb/JhKJsH//fvTo0UONyYiIiIiIqKSLj49HnTp18PLlSygUijzLiMViLF26FOPHj1dzOqJ/HDt2\nDM7OzjleMzMzw6tXryCVSgVKRUSFgfWbNJFSqUTz5s1x5cqVfPtIUqkUvXr1wvbt29WcjoiIiIiI\niIiIiIiKgb1ioRMQERERERERERFpuz/++CPXg54SiQQikQiDBw9GZGQk6tWrJ1A6+uDp06dwdnaG\nVdlyCDl+BlWqVRc6EtEn69nPGztDfseJE+Hw8vKCUqkUOhIRERERERERERERUQ5yuRyurq54+PAh\n5HJ5vuXS09Mxb948NSYrXEqlEl5eXggPD8exY8cwcOBAoSMRaTU9PT1s374dM2bMwIgRI7Bz506h\nI1ExZmpqCrH4n6lUKpUKGzZsQIUK3Ei5uFMqlfAaMAAnjh9F6NKJ6Ne5mdCRiLSano4Mv84chsn9\nu7L9JqIi8/76ewDCjx/DoV/9McCto9CRiLSanq4ONi2ejinD+wrefiuVSgwY4IWjx05g4s+haObS\nT7AsRJ/L2rYapm05AT2LsmjfwRlPnz4VOhJpuL59++bYMFQul6NfP/67RwV7+vQpnDt0gE0pE5za\nsQrV7Th+SfQlqttVwKkdq2BTygTOHTqw/SYiIqLP8vTpUzi3bwcrPQWOTOmIqtamQkci0mpVrU1x\nZEonWOkp4Ny+naD98+z6LXuHw75NUaWMkWBZiIqDKmWMcNi3GaxlGYLXb9IOHD8nTaNSqeDj4wOV\nSlVgOZFIBG9vb8TGxqopGRERERERlXRKpRJ9+vTB33//nWvt6/8tN23aNDx48ECN6YhyateuHUqV\nKpX9s0wmw4ABAyCVSgVMRUSFgfWbNNHatWtx6dKlAvtICoUCO3fuxLp169SYjIiIiIiIiIiIiIiK\nC/HHixAREREREREREVFBDh48mOOhY5lMhjJlyuD48eNYv349DAwMBExHAJCWlgaPr7+GkYkpNu0+\nAHMLS6EjEX22Rs1a4NedQQg7eBCzZs0SOg4RERERERERERERUQ5Dhw7F2bNnIZfLCywnl8sREBCA\n6OhoNSUrXDNnzkRoaCj27duHli1bCh2HqFgQiUTw8/PDhAkTMGTIEJw/f17oSFRMmZr+symbTCaD\nl5cX+vTpI2AiUpcP7fdWvxFoVruq0HGIigWRSITpg1wxuqczhgwezPabiArdzJkzERoSiu3L56B5\ng1pCxyEqFkQiEb4bPRC+3l9jyBDh2u8P/fMRS7aiar1mgmQg+hJGphYY+9N+6BhboLuLK1JSUoSO\nRBqsVatWsLKyyv65dOnSvLdABUpLS8PXHh4wNdTD/oD5sDAzEToSUbFgYWaC4LU/wNLEEK4uLmy/\niYiI6JOkpaXh6x7uMJYqsG1Ua5gb6godiahYMDfUxc7RbWCukwXX7t0E6Z+/r99uMBZnInCIE8wN\nddSegag4MjfUwfZhDWEmlcOle1def1OBOH5Ommbjxo04efLkR+fDKJVKZGRkwM3NDWlpaWpKR0RE\nREREJdmsWbNw4sSJj16vAEBGRgZGjRqlhlREeROLxejfvz90dN6Pu8vlcvTt21fgVERUGFi/SdM8\ne/YMU6dOhVKp/GhZlUoFX19fXLx4UQ3JiIiIiIiIiIiIiKg4EQsdgIiIiIiIiIiISJsplUqEhoZC\nLpdDJBIBAFxdXXHr1i20bdtW4HT0wbBhw/Do0WME7guDiamZ0HGI/rOGTZtj0Yo1WLhwIYKCgoSO\nQ0REREREREREREQEAJg/fz62b98OhUJRYDmxWAwdHR1kZWVh4sSJakpXeIKCgrBo0SJs2LCB9wKJ\nioC/vz+cnZ3Ro0cPvHnzRug4VAyZmpoiKysLEokEVlZWWL16tdCRSA0+tN+rJnujVb0aQschKnbm\nj+yJtk410cPdje03ERWaD+13wLxJaN2ortBxiIqdHyaPRLumDdDD3V3t7feH+u09axVqNGyl1nMT\nFSY9QyOMXr4bj589x/DhPkLHIQ0mFosxYMAA6OjoQEdHB97e3hCLudQP5W/YsKF49PA+gtcugKmx\nkdBxiIoVY0MD7F09D8+fPYGPz3Ch4xAREZEWGDZ0CB7F3sHO0W1g3ovzAAAAIABJREFUaqAjdByi\nYsVIT4ato1rj+eMH8Bk+TO3nHzZ0CB7eu4PtQ51gqi9T+/mJijMjXSkCBzfA80fC1G/SHhw/J00j\nFovh5uYGc3NzAIBUKoVMlnc/QS6X4+7duxg+nOOMRERERERUtEJCQrBw4UJkZWXleVwkEkEqlQIA\nZDIZmjRpAicnJyQlJakzJlEOffv2RWZmJgDAxsYGTZs2FTgRERUW1m/SJC9evEC/fv1QpUoViEQi\niEQi6Onp5VteqVTC3d0dcXFxakxJRERERERERERERNpOpFKpVEKHICIiIiIiIiIi0laXL19Go0aN\nIBKJYGxsjA0bNqBXr15Cx6J/OXnyJNq2bYste0PRrmMXoeN8kvZN6uBu9G14DfHBD8sDhI4jCHlm\nJr71HYH9u7Zh5veLMWJs7g1hf165FAtmT8v3Mx6+Sc+emJaXL32/kCaNHobzp8MREx0NAwMDoeMQ\nERERERERERERUQm2Z88e9OnTB//7WLpUKoVIJIJcLgcAWFpaolGjRqhduzbs7e3RoEED2NvbQyQS\nCRH7s6WlpaFmzZpo3749Nm7cKHQctXN0dERUVBRGjhyJtWvXCh1H7S5fvoyFCxfi4sWLeP36NcqX\nLw8PDw/MmjULxsbGAIB3795BX1+/wM8ZNmwYNmzYkO9xf39/TJkyJd/jcrlcY+9fFZbk5GTUqFED\nPXr0QEBAybxXSkVn165d6Nu3L0QiEcLDw9G6dWuhI1ERS0tLQ80a1dHK0RZrpg4SOo7aNR40G9GP\n/sJQ1zZYPnGA0HEElZL2Dk2H+uHxi9e4sGku7O3K5Th+LeYRlm4/jCvRD/AmKQXlSpvDtVUDTPXu\nDiOD/Bf/++D+s78xd0MQIiLv4G3aO1SwtkT/zs0xoW8XiMXa0d/9Em9T09Fg4Gx49OrL9puIvtj7\n9rsG2jg54Of53wodR+0auA1FdOwjDOvtgp9mjxc6jqDepqahscdwPHr2ElcO/AL7qnY5jv8ZdRdz\nV23ChcgoZGRkoqpteYz28sBAj48/K7x84258t3R9vseTb/wBqUTyxd9BkyWnpKGuy2B4ePZSW/ud\nlpaG6jVqwrZ+Kwyas0Yt5/xSs3s2xl/3o9HGcygGzFgudBy1OrJlJfatnJXv8fWX4yGW5BynUsgz\nsWXeGJw/tAs9x89HJ++xRXYuTXHzzB9YOdYT4eHhaNOmjdBxSENdvXoVTk5O2X+vX7++wIlIU32Y\n/xS89gd0atVY6DhqVZL7wZ/aN32XkQmL+gX3dQd5dsWauZMKLBP7+DnmrPgFpy9fx9uUVFQsZ40B\n7p0waWjfEjGOBQC/n76IHqNmsP0mIiKiAn3on+/wbY8OjuU+/oZipOXcUNz5KxEDW1WDf/8mQscR\nRKZCiQlbz2HvhQfw+7oBvunokGe564/fYFFoJC7ff4V38ixUsTaBT7ua6Ne8ykfPEfBHFObuv5rv\n8b/WekFaAvrox249R79Vx9XaP/9Qv7cPb4z2Na3Uck51a70kHHdevsXAZrZY7Flb6Dhqdz8uBQsP\nRyPi3mtkKJQob2EA1zo2+KZtZRjq5j/WnJKhQDv/k3gSn4aT37ZFjbLGhXauNeGxmBd2O9/Pefaj\nS7Gr88ej/0b/DRd5/U0F4vg5aaoHDx7gzJkzOHv2LE6cOIH79+8DeD9H5sP8GAAQiUT46aefMGbM\nGKGiEhERERFRMXbv3j3Uq1cP6enpUCqVAJA9v1ihUEBfXx+NGzdG69at0aJFC7Ro0QJ6eh+fA0Wk\nDra2tnj8+DGmTZuGhQsXCh2HiAoR6zdpouTkZFy6dAnHjh3DiRMnEBkZCblcDh0dHSgUiuy+lEwm\nQ5MmTXDixIliv24LERERERERERERERWKvRxNJiIiIiIiIiL6D+Lj4xEVFYWEhARkZGQIHYcEtGfP\nHgCAg4MDxowZA5FIhL179wqcSn10dXVhbm4OBwcHWFhYCB0nl6ysLIwdNw7OXbqjXcePb+6gCS6e\njcDd6Nv4qnxFBO/Zie/mL4ahoZHQsdQqKTEBw/v3hFyeWWC55KREAEDUk1cwMTX77PN86fuFNN3v\nB7Sub48lS5bAz89P6DhERERERERERET0H2VkZCAqKgpxcXF4+/at0HGIPltMTAzmzp0LlUoFsVgM\npVIJsVgMKysrVK1aFba2trCzs4OtrS0MDQ1zvPf27du4ffv9xgZisRhmZmaws7ODnZ0dRCLN29Bg\n8eLFSEhIwIIFC4SOonanT59GVFQUKlasiO3bt8Pf3x9GRiXn/tXp06fRsWNHuLu74+zZs7CwsMCR\nI0cwePBgRERE4OzZsxCLxdDT04NKpcrzM0JCQuDu7o7evXsXeK7ExPf3rxISEmBmpl33rwqLiYkJ\nFi5ciKFDh8LHxwd16tQROlIubL+1140bNwAAHh4eiIuLK1HPdxQFrWm/499g9rAJQkdRu7PX7yL6\n0V8ob2WJ3ccuYP6onjDU1xU6lmCmBezG4xev8zx29vpduE9ehu4t6+Ho6mkwNzbE0Uu3MGrxJpy7\ncRdHV08vcCPsv+OT4DxmEWpVKY/wtd+hbGlzHLt0C8Pmb8DzuHgsmzCgqL6WxjA21IffsB4Y7b9O\nY9tvItIe79vvePiNGyJ0FLU7c+UGomMfoYKNFXYfPI4fJo+AkYG+0LEEM3XxGjx69jLPY6HHzqDf\nBD+4O7fC2T1rYV3aEr/uOYjRc5YiIektxg/uVeBnJ71NAQC8uBACU+OSM8bxbyZGBpg3fihGzfpR\nbe334sWL8SY+ARNGzy7ycxWGu9fO4q/70bAsWx4XftuNnuPnQ9fA8ONvLCbSU5IAAD+degoDY9OP\nlk9LTkTA5P5QfOT578I4lyap1aIj6rbqjG9Gj8GN65EauSA45z9phjJlygAA7t+/n71hKKmXNsx/\nGjd2LLq2bYZOrRoLHUetSno/+FP7pnq6OkiLOp7nsYMnzqKX72x4dm5b4Ln+fh2PdgPGok6Nyji9\nKwA2ZUrh6JlLGDJ1IZ69fIWVs8b99y+iRTq1aowubZpizOjRiLx+XSPbbyIiIhJWVlYWxvmOQac6\nFdDBsZzQcdTq/L2/ceevRHxlaYj9lx7Cz9MJhrolq7+UmJaJwWtPIjMrq8Byh/98giHrTqF7/Qo4\nOqMbrEz1sSXiLiZuPY/E1Ax809GhwPcnpb0fR7u3vA9MDXQKLb+26eBYDh3rVMDob0bh+o2bRd4/\nz8rKwljfMejoaIP2Na2K9FxCuXD/De68fIuvzPWx/+ozzHaxL1H1+O7fb9F5+WnU+soMIWNa4CsL\nfRyP/hvjdkYi8mkitg/Pf9xl9oFbeBKfViTnSkqXAwDuLOgCU33Zf/+CWqR9TSs4O5bF6G9G4vqN\nWxp5/c3xc83A8XPhafr4+X9RGPVbX18fHTp0QIcOHZCQkIDo6GjExMTg1q1beP78OVQqFVQqFcaN\nG4fExERUr169kL8F0ZcrjvWbiIiosHB+IGm6d+/eYdq0aUhNTc2es2diYgIHBwfY29ujRo0aqFCh\nQvaxhIQEhIWFffZ5tGF+4Odi/dYMDRo0wOPHj2Fpacl5vAJh/aaiwvotPNbv/DVo0AANGjRARkYG\n7t27h+joaNy+fRt3796FXC6HQqFAREQEvv76awwYUPznfpP2KY71m4iIiIiIiIiISNtp3kwIIiIi\nIiIiIiINFRUVhY0bNyIsJBj37j8UOg5pmFu3bmHkyJFCxxBU1cp2cHX3wODBg+HgUPDiVOqyc+dO\nxERHI2DzbqGjfLLAX9fByMgYfouWYlh/TxzYuwv9Bw0TOlae3qWn47ewYOzeuhnf+69E1Ro1v/gz\nkxIT4N6xFbq7e6Ktc2e4dWiRf9mk95thGhj+t404vvT9QipVugx8J0+H/6J5GDduHMzNzYWORERE\nRERERERERJ8oISEBgYGBCA7aj7PnzkGhKHjDCCJtoVQqs//74sULvHjxAqdPn/7szzE3M0Wnzp3R\nr19/dO3aFRKJpLCjfraEhAT8+OOP8PPzQ9myZYWOo3Zr166FsbExVqxYgR49emDHjh3w8fEROlae\n0tPTERQUhI0bN2LVqlWwt7f/4s+cMWMGSpcujcDAQOjovN94p1evXrh8+TJ+/PFHXL16FQ0bNsz3\n/SkpKfD19UXv3r3RoUOHAs+VmPj+/pWRkfbdvypM3t7eWLNmDWbPno2QkBCh4wD4V/u9fy/OnrsA\nxUc2fCLNtn//fuzfv1/oGMWKuakJOnXugn79Naz99vfH9IHdYG1pKnQctfs15CSMDPSw2LcP+s0M\nwJ5jFzHYpZXQsfKUnpGJsNPXsPW3M/Af2w81bG0K9fN/v3ADgYci4NaqAUJOX811fO6GIJQyM8a6\n6UOhI3s/3dKjbUNci3mEn3b/jsi7j1G/hm2+n78k8CBS0zOwabYPLEzet+HdmtfFFK/u8NsQhJFf\nd0C1CtaF+p00Ud9OTbEh9BRmz5qFkNBQoeMQkZZ6f/3tj+9GecG6tKXQcdRuw+5QGBsawH/aaPQe\nOxt7Dh3HkJ7dhY6Vp/R3GQg5dgaBQb9h6Xe+qFm5YqF+/pFTF7B5/29wd26FA0dzjy/NXLYeZUuX\nwq+LpkNX5/2GmWMHeiLm/iPMX70ZAz26wNzUON/PT3ybCgAwNNAv1Nzapr+rM9bvClVL+52QkAB/\n/x/RzWc6TEtpR9/o5N5foWdohD6TFyNgUj9cPLIHrTwGCx0rT5kZ6bh2PAxnQrai31R/2FSq8cWf\nmfY2CQCgZ2D48bLJiVg42BlOzj1Qq7kzfhjYvsjOpYl6TlyIOZ6NsGvXLo1ZEJzznzRXr169hI5A\n0Nz5T9HR0dgWulHoKGpX0vvBX9o3TUlLx8QFq+DZpQ3aNa1fYNmFP29Dalo6tvjPhIWZCQCge7vm\nmDpyAGYv/wXfDOiB6nYV/lMObbN4yig0cB2iUe03ERERaY6dO3ciOiYG6+e4CB1F7TafugMjPRkW\n9GqEgWvDsf/SA3i3rCZ0rDy9k2fh4LXH2HkuFj/0aYzqZb/8uYDEtEx0X/IbXBtURHuHcuiy+Ld8\ny84LugZrM32sGdICOtL3z0iM6mCPu38lYnHYdfRtXgXmhrr5vj8pPRMAYKgn++Lc2m6eZ320nBum\nlv75zp07ERMTg3XftinS8whp87lHMNKV4nv3Whi86RKCrj2HV9PCvY9TWN7Js3DoxgvsvPQEP3jU\nQjWr/O/tfKr5B6OhUKqwaXBDWBi+f97TrW45/Pk4ET+fuo8L99+gSeXc9yGP3f4bOy4+QffaZXHw\nxotCP1dSuhwAYKhbspYBn+tij9b+JzXq+vvD+PnB0BDcjb0vdBz6F46fa4ZqVSrDxc1do8bPP5VQ\n9VupVGLWrFlqOx/Rf6XN9ZuIiKiwcH4gaSuVSgUASE5Oxvnz53H+/PkiOY8mzg/8VFy/Q3N9++23\nQkcgaOb6HZ/qn/Z7H86eP8/6rUFYvzWDuen/129tbr/V2D//0K8KDQ1FKOdBk4bT5v45ERERERER\nERFRcVKyZoEQEREREREREf0HsbGxmDRhAkIPHoRdaSN0qW6COc1qomYZA1gYSKEjFQsdkQSiyFLh\nUcI7VClVcjcCyFQoEZ+mQHRcGs49TEJQ4DosXboUrt27Y+ny5ahSpYqg+X7++Wd06uYGu8rC5vhU\nr1/F4bewYLh69EKHLt1Rxrostm9cj/6DhuVZftO6AGxatxrPnj6BlXVZ9Bs0DNWq18Sw/p7YuDMI\nzl3/WWQu6uZ1LFs4D5fOnUFqagqsy9qgi2sPjJ/yHYxNPm9xsxt/XsWurZtwYO8uqJRKuHn2hrVN\n4WzE9SouDsO+GYf+g4bh2uWLBZZNTkqCnr4+pNL/NtT9pe8X2oChPli5ZAG2bt2KsWPHCh2HiIiI\niIiIiIiIPiItLQ1LliyB/5IlkIiBbs3rYt20IahTrSJsSpnByEBP6IhEnyUpJQ3GBvoQi0Vf/FlK\npQoJb1Px4HkcLkXdx2/nb8DNbQ8qV7LD0mXL4erqWgiJ/7vAwEBIJBKMHDlS0BxCiIuLQ1BQEHr3\n7g0XFxeULVsW69atg4+PT57lV61ahVWrVuHx48ewsbHB8OHDYW9vjx49eiAkJCTH/8vIyEj4+fkh\nIiICKSkpKFeuHDw8PDBr1iyYmn7e/asrV65g48aN2LFjB5RKJfr27Yty5cp90Xf/wNPTE1ZWVtDR\n0cnx+ocFsB89eoSGDRvm+/7Zs2cjMTERy5Yt++i5EhMToa/F968Ki0gkwqRJk9CvXz88e/YMX331\nlWBZ/mm/F0OsUqJzdTOscK+EWjaGsDbWgZEuF8zRJk8SMpClVMHOkv2uwqBUAYnpCjyKT8fVpyk4\neuUo3PbsQSXbili2YqVmtN9iYKhrG0FzCOFVwluERlyDR9uG6NKsDqwtTbEx7BQGu7TKs/y6oOP4\nOegEnv79BtaWZhjUvSVq2Nqg38wA7FowBl2b180ueyP2KRZuCsG5m/eQmp6BsqXM4NqqPqZ6u8DE\n8POeofrzziNsPXwGe45dhFKlQs/2jWBT2vyLvvv/ik9OwZglW/B1u4ZoUbc6Qk5fzVXGvU0DlDE3\nhY4sZ/tb0+79szCPX75G/Rq2+Z5j/4nLaFG3OixMjHK87tKyPuas348Dp65gipdmbmBemEQiEXx7\ndsDQ+b8I3n4TkfYKDAyERCTGsN4lb4PdV/GJCDkaAc8ubdG1TVNYl7bEL3sOYkjPvNuQtduDsXZ7\nMJ789TfKlimFwZ7dULNyRfQeOxt7V3+Pbm2bZZe9EROL+QGBOHv1BlLT0mFjVQpuHVpi+kgvmBgb\nflbOa1F3sCXoCHYfOg6VUoWeXduhXJlSX/Td/1d8YjJGzV4Kzy5t0KphXRw4ejrH8cTkt4h9/Bxf\nd24DXZ2cm+R6dG6Dzft/w2+nLqCfq3O+50hKToG+ni6kJXwRVJFIhHEDPTFoyg9F3n4HBgYCYgna\neA4tsnMUprfxr3DtRCgadvRAndZdYFrKGqf2bUQrj8F5lj++ax1O7PoZb148hVlpa7TsMQg2lWog\nYFI/jFm+C3Vbd80u+/TODYSsW4h7f55DRloqzMqURf12rnAZPhX6RiaflfPR7T9xJmQrLv62ByqV\nEo069YR5mcJ5pjvtbSJ0dPUhlnx8nCo5Pg7O/b9BK4/BeHDzcpGeSxNZVaiMem27Y+3P6wTfzJbz\nnzTX/dfpAIDKJXj+kdA0fv7T2rVwad8CVSoWzr0NbcF+8Jf3Tb9ftRlJb1OxeMo3Hy2777dwtGxY\nBxZmOfscru1bYNayDQj+/TSmjdSMjdmLWpWK5eDSvgXW/fyz4O03ERERaZ6f1wSgS90KqFTm88Zq\ntN3rt+9w6M8ncHOyRcfaX8HKVB+Bp+/Cu2W1PMv/Eh6DX07E4Fl8CqxMDeDVsiqqlzXDwLXhCPym\nLTrXKZ9d9tbTeCwJu46LsXFIzZDD2swA3etVwMRutWGir5Pn5+cn8vEb7Dgbi6BLD6FUqeDR0A5l\nzQrnevtVcjp82teEd8tquPrgVb7lEtMy8SAuGW5OttCR5uzLuznZYvvZWBy7+Rw9m1TK9zOS0zKh\nJ5NAWgjPX2q7SmVM0KVuBaxbu6bI++c/rwlAF8eyqFT6864LtcXrlAwcuvEC7vVs0NHBClYmegg8\n/wheTSvmWf7XiIf49cwDPI1Ph7WpHgY0qYhqVsYYvOkStgxthE4O1tllbz1Pwo+/38GFB/FIzVCg\nrKkeutUuiwkdq8FET5bn5+fn+tNE7Lz4BEHXnkOpUqFH/XKwNi2c57laVyuNFlVLwcIw578ttcu/\nfyb1cXwamlS2zHEsITUTE3dHwq1uOTSrYomDN14U+rmS0xUlss5XKm2ILo5l1VK/PyY2NhaTJk5A\naNhBVCpriW4NKuF7jzqwr1AKlkb60JGV7PuGQop9kQAAqFK2cJ8bo0+XKc/Cm5R03H7yGmduP0Xw\njs3vx89dumPpMuHHzz8mZ/22QLd6FfG9W3fYf2UJS2O9XP21opCpyMLb9ExYGvM+EGmWTEUW3rx9\nh9vP3uBM9HME79ikVfWbiIiosHB+IGmbDIUSqZlKWBgU/TOVmj4/8GO4fodm++3cdXRpVkfoGCWW\npq/f8TE52m+o0LW+LQKGtUPtiqVQ1twIRp95b4IK1++Rj9Cprq3QMUospUqFhJQMPIxLwuXYl/j9\n+rn39dvOFkuXr9Cu+i1g//xFcibKmnze8wpERU3b++dERERERERERETFkXauhkREREREREREpAbv\n3r3D3LlzsXzZUthZ6mPrgJpoW8UMopK1rgYVQCoRoUoJX4hZRyqGtYkOrE100LaKGWZ0AMJjE7Hg\n2Ck4OthjwsRJmDNnDvT01D8B5uXLlzh//jx+2bFf7ef+r3YGboQ8MxM9+3tDIpHg6z79sXbFj7jx\n51XUrtcgR9mtv67D7CnjMXzMeIwYMwFyuRyL581C0O7tAADZvzajvPHnVXzdpS1atmmPA0cjYG1j\ng/MRp/DtGB9cOncGwX+c/uiGkgnxbxC0ewd2bd2ImKhbqF2vAWbOXww3z94wNHy/mVX8m9eoU6ns\nR79n+OVbqFKtep7HqlSrnu+x/5WclAgjI+NPKlsU7xeakZExOnV3Q1BQEMaOHSt0HCIiIiIiIiIi\nIipAcHAwxo8bi8SEeEwf2A1DXdtw8SjSeqZGBoX2WWKxCJamRrA0NUJD+0oY3dMZD57HYcGmULi7\nu8O5QwcErFkj2ELDwcHBcHd3h7Gx9t5X+K9++eUXZGZmYtCgQZBIJPDy8sKSJUtw5coVODk55Si7\ndu1ajB07FhMnTsSkSZOQmZmJ7777Dtu2bQMA6Pzr/tWVK1fQqlUrdOjQAefOnUO5cuVw8uRJDB06\nFBERETh79uxH71+9efMG27Ztw6+//oqbN2/CyckJ/v7+6Nu3L4yM3t+/ev36NUqXLv3R7xkdHY0a\nNWrkeWz8+PF5vn79+nWIRCI4ODjk+7mPHz/G6tWrMW3aNNjYfHwj7sTExBL5e5YXd3d3GBgYIDQ0\nFN988/ENTItCcHAwxo8dg4Q3rzGxZVl4OVlxcVctV8FcV+gIxYpYBFgYSGFhYIz6XxljeNOyeBT/\nDj+GP3/ffrdvh4C1PwvXfgftR7fmdUtkv3vLodPIlCvQv3NzSMRi9OnYFCt2HsGfdx6hXnXbHGV/\nCTmJb3/aiTG9OsK3V0fIFQrM/SUYu49eAADoyP5pj/+88widxy5BmwY1cSxgOmxKmSMi8g5GL9mE\nczfu4ejq6ZBKxAVmi09Owe4/LiDw8BlEPXiGetVtMX9UT/Rs3xiG+u/r6JukFNi55d3+/tuVwPmo\nVsG6wDITlm2DIisL/mP7IeT01TzLfOPpnOfrN2OfQSQSoaZt/m34s7h4xCenoIZt7udlKpUrA5lU\ngsg7jwvMWJx0b1EPBno6grbfRKTdgoOC4NK+GYwNC2/MQVts2ncYmXIFBrh3gkQiRj/XDlj2625c\ni7qD+g45n6ncsCsUk35YjbEDPTFuUC9kyuXwW7kRu8KOAgB0ZP8san0t6g6cvSegbZP6CN++CjZW\npRBx+TpGzvTH2as3cWL7T5BKCr7OiU9Mxs6wY9gcdBhRdx+ivkN1LJw8Aj27toORwfvnqN8kJKF8\nC4+Pfs8/D25CdbsKBZYZO28FFFlZWDbDFweORuQ6rlK9/29ez/RbmL6/pr555z6AvNt4AEh8m5Kd\nvaRzad8CBnp6Rd5+7w8KRt023aD3/88ca7rTwVugkGeiuWt/iMUSNO3WB0e2rMCj23/C1r5ejrIn\n9/6CnUu+RccBY9DRyxcKuRzBAXNx4fBuAIBU9s+Y2KPbf2LJ0M6o2bgNpm86BvMyNrhzNQKb5o7G\nvT/P4f/Yu8+wKo42AMMPvUsRKSKIgoodEbF3jRp77y2ixhp7ib3EiBpNNLHFjgUVGxqjxt577BUR\nUCkKgqBIPXw/SDDnA1QQOKDvfV38YHd25t2jw86Z2ZmZuPYv1DXe3yf2+tVLzv+xldO7N/DU9zb2\nZSrRccRsqjbtiI5+ygbGryPDGdGg2Afvc/bOy1jZp7+Zd0z0K3Q+8t/Lyr5khvl8jMyUlVdV/boz\nS0d3IzQ0FEtLy1wvX+Y/5X0OX/jco7wgz89/On+ebUtm5nrZqibt4E9rmwYGhbJ8827GuHfF2qLg\ne9M+DXnBy8goSjsUTXPOwc4GLU1N/r7zIEtx5FddWzak8/BpKnt+CyGEECJvCgkJ4dyFC6wfVF/V\noeS6jacfEp+ooEt1RzTU1ehYrTi/HrzNtYBwnIsqtzfXnbjP914XGdSoDIMalyEhScGc3X/jfcEP\nSPkO9q9rAeG0mn+AuqWt+WN8M6xN9DlzP4QRG85y/uFz9o1vhqb6+zsxIt7Esf28H5vO+HL3WQTO\nRQsyrX1l2rkVw0AnpT/t5es4nEZv/eB9npnRmhJWxumeK2FlnOG5/0r+p6M6vahNDFLGvW8/fUlH\nimeYx6uYeNmk8j86uNnTZ/mJHG2f/1u/1/WtkiP55wWbzgeSkKSgcxU7NNTV6OBahN+O+nL9SSQV\nbU2U0q4768+kXTf5tq4D39Z3ICFRwY/77+F95SkAWv95/+P6k0ha/3qGOiUL8cfwWlgZ63L2UTgj\nva5x3u8le4fX+oh6HI/3ladsvhDI3eAoKtqaMLVVGdpWsnlXj9/EU2bKgQ/e5+kJDXC0SL9PuV/t\n9PvGQ17FAlDULO045DjvGyQqkpnTrjz7bgR9sPyslPXqbQKGOl/mEuDtKxem79rzeaD/fCHFrUzx\nGteWhhWKSf95HuJobarqEL542loaWJsaYm1qSMOK9kztUpsjNx4zw+sM5cqWZeSoUSrrP38f5fpt\ngteoFjQsb6eS+q2tqUFBIxkLEnmPtqYG1qYGWJsa0LC8HVM7VufIzUBmbL+g8vExIYQQIrfI/ECR\nH+loqqOj+f75Wdklr88PfB9ZvyPva1ajoqpD+KLl9fU73icG6WJ5AAAgAElEQVTl+T2MiJfhjGtV\niT71y8m4Wh7TxNle1SF80dTV1ChopEtBI11cHSwZ1KQij0NfMXf3pX/qd0N+W7osD9fvvNE+ty6g\n/eFEQuSy/Nw+F0IIIYQQQgghhBDic/VlzgQRQgghhBBCCCGE+IDnz5/TplVL7ty8zpRGRehZxfKD\nC48IIVI2VmhQwoQ6DsZ4Xgpl/uJFnDh2lN0+e7GwsMjVWI4fP46Ghga16jXI1XKzSqFQsHntKmyL\n2lOjdj0AOnXvw7KfF+C5ZgXzl6xUSr988U8UsSvK5FkeqKunTNRatGw1tV1Kp8l7xvdjMDE1Y/l6\nL7R1UhYQa9S0OROm/cCYof3Zt2s7bTp2TTeu+Lg4hvfvzaE/96Kjo0vbTl35ecU6ypZPO6nGrKA5\nT14lfMrHkClRryLR1NLipzkz+GPPDgL9H2NsYkqzlm0YM2k6JqZmOXp9XlC3YWNGD3YnLi4OHR3Z\nuFAIIYQQQgghhBBCiLwmOTmZSZMmMXfuXLo3rcn0AaOwMC2g6rCEyBeK21iwerI77q3rMnaxF25V\nXNnuvYOGDRvmahyxsbGcPXuWAQMG5Gq5eYFCoWDlypUUK1aM+vVTNjjq27cv8+bNY/ny5axatUop\n/YIFC7C3t2f+/Pmp41fr1q2jZMm0G0GPGjUKMzMztm/fnjrG0aJFC3788Uf69evHtm3b6NatW7px\nxcXF0aNHD3x8fNDV1aV79+5s2LABZ2fnNGnNzc1TN9/JLqGhoXh6erJkyRKmTJlCmTJlMkw7e/Zs\ndHV1GTly5EflHRkZiZaWFtOmTcPb2xs/Pz9MTU1p164dM2fOxMws749fZRdtbW0aNGjA0aNHc3Qz\n+vT89/ndqZIFE7tWoJChLBInxMewN9Pl1/YO9KpiwZQDl3Bzrcz2HTtV8/w+d47l4/vmarl5gUKR\nzNq9JylqbU6dSikbZvdoVouftxxgtc8Jfh1rr5R+8daD2FmZM/vbjqj/837c8gnfUKnHpDR5T/xt\nK6ZGBmyYMQgdrZRpiU2rV2B6//YMmbeOXccu0bFR1XTjiktIpP/s39l/9jo62lp0blSVFd/3o4Kj\nbZq0BY0NiTq+Kp1cMmfbX+fZdfwya6cOxNzE6KOvex4Rhdehc6zYeYTxvVrgZF84w7QvIqL+iTlt\n/urqapgaGfD8nzRfAm0tTepUcuLo0SO5/vwWQuR//z6/V/4wVtWh5DqFIpk12/dhX8SKum4p3217\ntm3KwtVbWbV1L0tnllJK//PabRS1sWLOmG9Tn98r54yjwte90+Q93mMZpsZGbFo0DR3tlO81zepW\nY+ZIdwZNWcCOA8fp3Dz9tlpcfALfjJ/DH8fOoqujTecWjVj94wQqOKVdLLSgqTExt4980ucA4LXv\nCDsPnmDDgimYm5mkm8bU2AgHOxvOXb1NfEIi2lrvlks4e+UWAC9eRr63nFdRr9HS0mT2r+vYdegk\nj58GY1LAiNaNajF1WF9M03m2f660tTSpW9U5R5/fsbGxnDt3lr7Tl+dI/tktWaHg5M61mNsUpZRr\nHQBqte7BgfU/c8J7NfZTf1VKf3DDYswL29FxxGzU/ukT+2bGcia1qZQm760/TcTA2JRB8zagqZ3S\nJ1ahdlPaD5vOuhlDuHRoF1WbdUw3rsT4OH6f3J/rJ/ajpa1D1a8702/WCmxLVUiT1tCkIKuuflo7\nNCb6FZqaWuxZPocrh3fz4qk/+gVMcGnQijaDJmFgnH0bc+ZmWTmlTNX6qKtrcPz4cTp37pyrZcv8\nJyGyJs/Nf1JXp141l1wtV9WkHZziU9qmc1dsRFdHm2G923+wnOfhL1Nj/n/q6mqYGhvxPDwi6zeS\nD9WvXhkNdXWVPL+FEEIIkXf92z6v42Sl6lBylSI5mQ2nHmBnbkitUin33rWGI78evM36E/dx7lVD\nKf1vh+5gW9CQaR0qo66W0j5f3Kcm1absTpP31O2XMDXQYfXAumhrpmzi9lWFIkxu68KIDWfZc9mf\n9m7F0o0rPjGJQatPc/DGE3Q0NWhftTi/9a1JOdu071CZGerwfEWvT/ocPpapgQ7FLIy4+Og58YkK\ntP+zKe8F3+cAvIiOfW8er97Go6Whzry919h7JQD/sNeY6GvTvJId41s5Y2rwZa0bULe0NRrqajna\nPv+3ftcuUShH8lc1RXIynuf8sTPTp6ajOQBd3ez47agv68/6s7Cz8vuVy475Ymumz9RWZVLr8S9d\nnanx49E0eU/dcxtTfS1W9XZN/f/euIwlk5qXZuTWa/hce0Y7lyLpxhWfqGDwpqscvBWCrpY67V2K\nsKRbJcrZpP1+amagTcjCVp/yMaTrRXQcK0/44WRtRJViyn8/dlx5yt7rQazoVZmChp++4WNGZUW9\nTUBLQ435B+6z93oQAeFvMNHX5usK1oxvWgoT/c93s8k6JQqp7Pt3Sv95K+7cvsmMrrXo07ACmhq5\ns5G6EPmZmho0qliMeuWKsu7IDX78dTEnjh1jt49PrvefZ+Rd/b7BjE5V6VO/rNRvIT6Cmho0qmBH\nvbJFWHfsNj/++kueq99CCCFEdpH5gUJkXV6ZH5gRWb9DiKzLK+t3ZOS/9btrLSemjGtMoQL6qg5L\niHyhmKUxKwY2om/9skzcfBY3V1e278ib9Vva50JkTl5vnwshhBBCCCGEEEII8bmTN5SFEEIIIYQQ\nQggh/s/t27dxq1KZEL87+PQrTd+qVrIQshCZpKmuRt+qVvj0K02I3x3cXCtz+/btXI3hxo0bOJQo\niZ5e/nhp/+ihP3n6JIBO3Xuj9s9iSY4lS1HZrRo+3tt4Hf1uQf7X0VEE+j+mao3aqRtpAmhqadGs\nVVulfF9HR3H5/Flq1K6Hto7yol/1Gn0FwN+XL2YYV2zsW/7YswNXt+qcvnaPOQt/pWz5ip98v9lB\noVAQHxeHvr4BW30O8ffDp8yct4g/du+geb1qvH4dnaPX5wXlKrqQkJDAvXv3VB2KEEIIIYQQQggh\nhBDi/7x9+5aOHTrw04IFLBvfl6Xj+8hCUkJkQfXyJTj82wQaVnaiWbOm/P7777la/t27d0lISKBS\npbSbN3/u9u/fT0BAAH369Ekdv3JycqJ69ep4eXkRFfVu/CoqKgo/Pz9q11Yev9LS0qJdu3ZK+UZF\nRXHmzBnq16+Pzv+NXzVt2hSACxcuZBjX27dv8fb2pkaNGvj6+rJ06VKcnZ0zTJ9dfH19UVNTw8rK\nihkzZjB37lymTJmSYfrAwEDWr1/PsGHDMDX9uA2rFQoFcXFxGBgYcOTIEUJCQli8eDHbt2+nSpUq\nREfn/fGr7FSpUiVu3ryZq2WmPL/b89P8eSxq48DC1sVlISkhssDNzgifb0pTt6guzZqq6vmdSIUS\ndrlabl5w6MJNnoSG071pzdTnd0k7K9zKOuB95CLRb96mpo1+8xb/oBfUqFAidQNtAC1NDVrVUd58\nPPrNW87f8qV2pVLoaGkqnWvkVg6AS3f9MowrNi6e3SeuULWsA9c3zWHhyB5UcLT95PvNSFBYBGMW\nb6ZFrUq0b1Dlo67xe/acAvXccWw7ih/X+TBjYHvG9Wr53mvexiUApG5a+P+0tTR5GxufueDzuQqO\ntty8fl3VYQgh8qF/v39XLF1C1aHkuoOnLhAYFEqPNk1Tn9+litlR1bkM2/cfI+p1TGraqNcxPH4a\nTM3K5f/v+a1J60a1lPKNeh3Dub9vUdfNGR1t5e81X9VyA+DSjYzfPYyNi2PXoZNUcy7LrT89+WXK\nd1Rwcvzk+81IUGgYo35YQsuGNenQrN57084ZM5BnoS/oN+FH/J4EERX9Bs/dB/l9qw8ACYmJ771e\nkZxMXHwC+np67F+zAP8T3vz0/VB2HjxBrU6DiH4T897rPzcVSzty88aNHMv/7t27JCYkYOdUIcfK\nyE43zxwiPPgJNVt2T62TVvYlcajgxsWD3rx9865/5u2baF4886dEpRqo/adPTENTC5cGyhvWvn0T\nje/185RyrY2mtnKfWLkajQDwu3Upw7ji42K5cng3DhWrMsfnOj0mLsS2VM59pskKBQnxcejo6TN6\nxV4WHval27h5XD68i9k96hL75nW+LCunaOvqUbhYiVzvy5L5T0J8urwy/6lkcTv0dXU+nPgzIu3g\nFFltmz4Jfs6m3YcY1L0NJgWMPljOv31U2lrpj3loa2kS8zYu6zeSD+nr6lCyuF2uP7+FEEIIkbfd\nuHEDR2sz9LQ1P5z4M3L45jOehr+hS3VH/mmeU8LKGNfihdh12Z/o2ITUtNGxCQSERVOthAXqav9p\nn2uo06KS8hh9dGwCF31fULOUVZox1QZlCwNw9XFYhnG9jU9i79UAqhS34OLstszrVpVytmafervZ\nYnp7V4IiYhiy9jT+L6KJehuP19lHrDtxH4DEJMV7r1ckQ1xiEvraWuwY9RW353dkThc3fK4E8NWc\n/bz+z2f+JdDT1sTR2ixH2+c3btzA0dIYPe30x/fzuyN3n/M04i2d3WxT67GjhSGu9qbs/vsZ0bHv\nxk6iYxMJCI+hWnGzNPW4eXlrpXyjYxO59PglNR3N0dZUXsK6fmkLAK4GRGYY19uEJPZdD6JKMTPO\nf9+IuR0qUM7G+FNv96NFxsTTe81FomITWNLNBY3/9CsEv4rl+503aVbeitbONjlaliI5mbhEBfra\nGngPrsHNmU34oW059l4Losmik7yOe//YVn6mp62Bo6WxSvrPq1ZxJTTQlwPTOuH+lTOaGrIMuxCZ\noamhjvtXzhyY1onQQF+qVnHN9f7z9Lyr3w85MKkN7o3KS/0WIpM0NdRxb1SeA5PaEBrwMM/UbyGE\nECK7yPxAIbKHqucHpkfW7xAie6h6/Y70vKvf81nSrwGL+9WnUIH8saa8EHlJtZLWHJjUhvplLPPY\n81va50J8qrzYPhdCCCGEEEIIIYQQ4ksgbykLIYQQQgghhBBC/MeTJ09o3LA+luqv2ftNaRzN9VQd\nkhD5mqO5Hnu/KY2lxmsaN6zPkydPcq3s4OBgrG1ybtOo7Oa5egXq6up07N5L6XinHn2IiXnDDq9N\nqceeh4YCULBQoTT5FHNQ3gglJDgYhULBzq2bsDXWUvpxdSoKQNCzpxnGpaurx9et2nH54jlqVyrN\npNHDuHMr5zZ8yIw9h09z3S+YQSPGUMjSCqMCxjRv3Z45i34l0P8xSxfNz9Hr8wJrm5RFpYKDg1Uc\niRBCCCGEEEIIIYQQ4r8UCgU9e/Tg6JG/8PlpFN2a1lB1SELka7raWqye7M6Y7l8zcOBAtmzZkmtl\n/9sHb2ubf8adssuyZctQV1enT58+Ssf79u3Lmzdv8PT0TD0WEhICgIWFRZp8SpRQHr8KCgpCoVCw\nceNG1NTUlH5s/hn7eN+4op6eHu3bt+fs2bOUKFGCIUOGcP369aze5kdzdHQkOTmZly9fsmHDBn7+\n+WeqVatGREREuuk3bNhAYmIi/fv3/+gyzp07x4sXLxg3bhxWVlYYGxvToUMHli1bhp+fHx4eHtl1\nO/lCkSJFcnUcLOX53Z2jB/fj1cuJjs5px2OFEB9PR1OdX9s5MKyWlcqe30Us8sYmcLlp1Z5jqKur\n0aNpTaXjPZrVJCY2ji2HzqceC30ZBUAh07SbRTsUUX6mB4e/QqFIZutf5ylQz13pp1SHMQA8e57+\nMxFAV0eb1nUqc+H2I5y7f8/onzdx81HOvUc0xGMdAItG9fjoa4rbWBB1fBWBexez8vt+LN1+mAaD\nfiAyOv0NtwH0dbUBiE9MSvd8XEICev+k+VLYFDIlOCRU1WEIIfKh1Oe31ZfXDl/p5YO6uho92zRR\nOt6rbVPevI1ly96/Uo+Fhr0EoJCZSZp8HIsWUfo9+EUYCkUyW/YeRr9sQ6Ufh/qdAHga8jzDuHR1\ndGjTuA7nr92m3Ne9GDF7MTfvP8ryfX7It1MWALB46ogPpm3ZsCa7l//IQ/+nuLTsS+km3Tl06iKb\nFk0DwFD//Yt+H9+8hCendzKqX2cszc0oYGRA26/qsHjaCB4/DWbhaq9Pv6F8xMayEMHBITmW/7/1\n28yyyAdS5g3Htq9CTV2dmq2U25I1W/Ug7m0M5/94990mKiyl3WNklvZvl4Wdg9Lvr14Ek6xQcH7/\nVtxdCij9jGlSCoCIkGcZxqWto0vlhq15dP0C37d2ZtPc0Tx5kHMbp36//gg/H31M094jMC5oiZ5h\nASo3akPP7xfx4pk/f65blC/LyknGFja52pcl85+EyF6qnv9kI+3gVF9aOzirbdNNew6RmJRE3w7N\nP6ocfV0dAOITEtI9HxefgL6eTtZuIh8rbGkuc7KEEEIIoSQ4OJjCJrqqDiPXrTtxH3U1NbrUUO7T\n6lrDkZi4RLaf90s99vzVWwAKGaX9nIpbKm+4GhIZgyI5Ge8LflgM3KD0U2G8NwDPIt5kGJeetgYt\nXIpyye85VafsZvyWC9x+mvG4dG5q5mzLlmENeRQaRa3pe6gyaRdHbj9j9YC6ABjqvn/zuj/HN+Pe\nT50Z2qQsFgX0KKCnTUuXoszvXo2AsGiWHLyVG7eRp1ib6OZo+zw4OJjCxp/v9551Z/xT6nEVO6Xj\nXdzsiIlPwvvyu76O59GxAJgbpv08ihUyUPo9NCo2pR5feYrVKB+lH+fphwAIinybYVx6Whq0qGDN\npccvqT7nCBN23OB2UFSW7zMz/MPf0PyX0/iGvmaje1XK2xgrnR+19RoAHh0q5nhZf3xXmzuzmjKk\ngSMWRjoU0NWiRcXCeHSoQEB4DL8e8f3kGPIya2MdFfSfN8BKHw5M70yJwl/eO2RCZKcShc04ML0z\nVvrQuGGDXO0//3+p9VtPwYFJbShhbaqyWIT4HJSwNuXA5DZY6SlUXr+FEEKI7CLzA4XIXqqcH/j/\nZP0OIbKXKtfv+H+pz++/DrBzbEu61CqlsliE+BzoaGmwYkAjRraolHfqt7TPhcgWeal9LoQQQggh\nhBBCCCHEl0JT1QEIIYQQQgghhBBC5BUxMTG0b9saQ2JZ39WJArrSdSJEdjDV18SzW0narL1Hy+Zf\nc/rsOQwNDXO83JiYGPT1DT6cMA94EuDP8cMHUSgUVCvrkG6ajWtX0rv/IABiY1MWQ1JTU0uTLr1j\nAF17f8O8xSsyHZu2jg4rPLfyMjyMnVs3s3XjWjasWk5FF1e69+lP646d89znXK9RE9TU1Lh2+aJK\nrs9NBgYpdSk6OlrFkQghhBBCCCGEEEIIIf5r8uTJ+Pj4sGv+CGpUKKHqcIT4LKipqTGxTyuiY2L5\npm9f7O3tqV69eo6X++ZNymYzBgZ5azwkpz1+/JgDBw6gUCgoWrRoumlWrFjBkCFDAHj7NvPjV+7u\n7vz++++Zjk1HRwdvb2/CwsLYuHEja9asYenSpVSpUoUBAwbQtWvXHP33MjU1pW3bttjZ2eHq6src\nuXPx8PBIk87b25sqVapgb2//yWU2bdoUNTU1Lly48Ml55SeGhoa8fv0618qbPHkyPnt82NyzFFWL\nFvjwBUKID1JTg9H1bXkdr+Cbvn1y/fmtr6ud42XlJQHBYRy+eAuFIpkyncelm2bt3hMMaFsfgLfx\n8QCokc7zO51jAL2b12bJ2N6Zjk1HSxPPmYMIf/WarX+dw3P/GX7ffQwXJ3v6tqxLx4ZuqRtSfyrP\n/ac5cuk266YNxNLM+MMX/B8TI31a1nbB1rIgdQbMYuHm/cwc2CHdtP/mHxaZ9r2NxCQFEVFvqFkh\n7SblnzMDPV1ev8l4w0YhhMhI6vdvvS9rk13/pyH8dfoiCkUypRp1TTfNqm17Gdi1NQCxcXFA5r5/\n9+nwNUtnjM50bDraWmz+eRrhEa/Ysvcw63f9ycote6hcrhT9OragY/MG2fbvtX7nnxw+cwnPn6Zg\naf5xmzF+VduNr2q7KR278/AxAMVsrbMUR+NabqipqXHpxt0sXZ9fGerr5ejz+9/6ra2nn2NlZJew\nZwHcOnuYZIWCcV+XSTfNCe+11O80AID4uMz3idVu25veU5ZkOjZNbR0GzffkdWQ45/Zv5cxuT45t\n+x37si7UbdcXt6Yd0cmFz7hcjcaoqanx+Nblz6qs7KCtZ5BrfVky/0mInKHK+U8G2dQvkl9IO/jD\nPtQ23XXoJJXLlaKojdVH5WdVqCAAYS8j05xLTEoi4lU0hS3Msx5wPmWop5urY1FCCCGEyPtiYmLQ\n11JXdRi5KjDsNUdvB6FITsZl4o5006w/+YBv6qVsuhibkJRyMIO2eHp61CrBwp6Zf1dAW1ODNQPr\n8vJ1HNsv+LH5jC9rj9+nkr05PWuXoF2VYujrqK5fpGE5GxqWs1E6di8opc1d1NwoS3k2KFsYNTW4\n8jjsk+PLbwy01HO0fR4TE4Oe1sf/v81PAl/GcOzecxTJyVSe9Ve6aTacC6BvrWIAxCYogPSrcUZV\nu3u1ovzUqWKmY9PWVGdVnyq8fBOP95WnbLkQyLoz/jjbmdCzWlHauhRBX1sj0/l+yCX/l/RefRED\nHU18htXCyVq5Tm65EMixe89Z2csVC6NP65f5UFnv08DJAjU1uBoY8Ukx5HX6Wmq53H/eBiOtZDaN\nboWx/pfV7yZETjEz1MVrbGu+nrmdVi2ac+rM2VzpP/+v1PqtqWDTd02lfguRTcwMdfEa+TVfz9mt\nsvothBBCZCeZHyhE9lPV/MD/J+t3CJH9VLV+x//7t35vH92CaiWzNhdECKFMTQ3GtanC69gE1T+/\npX0uRLbKK+1zIYQQQgghhBBCCCG+FLKijxBCCCGEEEIIIcQ/3Pt9w+MHd9nnXkYWQhYimxnqaLC2\niyMtVt1hQH93Nm/xyvEyk5OTM1zQN6/ZuGYlCoWCg2euUKZchTTnf5n3Awt+mM6Vi+ep7FYNM7OU\nBXgjXoanSRvo76f0u7WNDerq6jwNDPykGM0KmuM+eDjug4dz/epltnquZdbkccz8fgxtOnbh+5k/\nkpCQQMXiH540cezSLRxLlvqkeBLi47l39zaGhkYUc3BUOhcfF0dycjI6uhkvrvyp1+cV//4fT05O\nVnEkQgghhBBCCCGEEEKIf+3cuZO5c+eybHxf6lRyUnU4Qnx2Zn/bkUfPntO2TWtu37lLwYIFc7S8\nf/vg88u4U3ZZsWIFCoWCa9euUbFi2g08Zs2axdSpUzl37hzVq1fH3Dxlc8jw8LTjV35+yuNXRYoU\nQV1dnYCAgE+K0dzcnBEjRjBixAguXbrEmjVrGDNmDKNGjaJbt254eHiQkJBAoUKFPpjX3bt3cXJK\n+zc7MDCQGTNmULduXXr16qV0rkyZlA3B79y5k+Y6Pz8/rl+/zsSJEz/6fuLj47l16xZGRkaUKKG8\nEGHcP+NXuvlg/Co7qamp5do42L/P70VtHKhRzDhXyhTiSzLlq6I8fhlP29YtuX33vjy/c8iavSdQ\nKJI5s3oa5R1s05z32LCPH9bs5uLtR7iVdaCgccpmDS+j0m625B/8Qul3m0KmqKurERia9lmfGQWN\nDRncoTGDOzTm6j1/PPefZtLSbUz8bSudGlVl5sAOJCQmUaz1iA/mdXnDbErapd3s+pbfUwD6zFhB\nnxkr0pyv1ncaAC+PrCQkLJIf1/tQq2JJujapoZSuVNGUd2Du+QdlGIO1uQmWZsbcffwszbn7AUEk\nJilwcSr2wXv5nKipyXssQois+VKf36u37UWhSObCzpWUL+WQ5vyPyz2ZtWQdF67doapzGQqapHxf\neRkZlSbt46fKzywby0Koq6vxJCj0k2IsaGrM0F7tGdqrPVdu3Wf9zj+ZsGA54+cto1PzBvwwagAJ\niYnY1mr3wbz+3reWUsXs0hy/9SCl76Dn6Fn0HD0rzXnXNu4ARN04hKZGxhuCnr92G4AaLuUzTBOf\nkMidh48xNNDHsajyJr3x8fEp749qa3/wXj4nOf38zk/1+8SONSQrFEzzOoNtybT/j/b97sHuZT/w\n6MZFHCq4YWiS8t3mdeTLNGlfPPVX+t3UwgY1dXXCgz/tnW5Dk4I07jaYxt0G43/7Kqf3eLJt0SS2\nLpxI1aad6PDdTJISExjR4MPt0Nk7L2NlXzLN8cSEeJ49uouuviGWdsp/mxLjU/qpNLWzZ3PF3Cwr\np+VmX5bMfxIi58j8p9wh7eAUWW2bPn4azM37jxjbv9tH34+1RUEszc2445t2fO7+o0ASk5KoXO7L\ne78hN5/fQgghhMgfUtrnqo4id60/+QBFcjLHprSkbBHTNOd/+uMGHj7XuOz3AtfihTAzTOmriXgd\nlyZtQFi00u+FTQ1QV1PjSXjaMenMMDPUYWDD0gxsWJq//cPYfMaX6d5XmLr9Mu3dijGlnQuJSck4\njd76wbzOzGhNCaucezfo4qPnAFR1tMgwTXyigntBkRjqalLcQnnDu7hEBcnJoKuVcV/45yo3+qo/\n1+q94aw/iuRkjoypR9nCaTdRXHjoAfMO3OOyfwSu9qaYGaR813z5JiFN2oDwGKXfrY11UVdT4+nL\nmDRpM8PMQJsBdYozoE5xrgVGsuViIDN87jBtz23auRRhcsvSJCYlU2bKgQ/mdXpCAxwtDDM8fyUg\ngi4rzlPC0pCN7lUxN0zbx3wnOKWPYcCGywzYkDaPevOPAfB0QUs01TP+n/MxZSUkKbgXHI2BjibF\nCxkonYtPSqnzOprqGZbxOVAj994lce/XD/9HDzg4vQvG+vljfEGI/MJQV5uNI1vSZLoXA/r3Z/OW\nLblavnu/b/D3fcDBKW2lfguRzQx1tdg4vClNZu3KtfExIYQQIifI/EAhclZuzw/8L1m/Q4icldvr\nd/zXv/V7Sb8G1Cpt8+ELhBCZMr1zdfyeR9G2dStu372nkvot7XMhcoYq2+dCCCGEEEIIIYQQQnxJ\nZFUfIYQQQgghhBBCCOD48eNs8dqKZw8nbE1korf4OI/DY/nxcCDn/F8RHZeErYkOnSpZMKSWDe9Z\nyyXbrs9vbE10WNTanp4btzJg4LfUq1dP1SHlCQnx8dXVJDkAACAASURBVGzduI6y5StSplyFdNN0\n6NaTn+bMYOOalVR2q4ZVYRsKWVpx9dIFpXSJCQn8sXuH0jEDA0PcatTi3OkTvAgNoZDlu02wLp49\nzfgRg/hlxToqVKr80TFXdHGloosrU+csYL/PTrZ6riMkKIgSTqV58irtgk85IS4+jnZN6uJcuQrb\n/ziidO7ooT8BqFGnfo5dL4QQQgghhBBCCCGEEOmJiYlh5Ijv6N60Jt2a1lB1OEKFHj0NZcbvOzl1\n7T7RMbHYWRWke9OajOzaDPWPGAi69iCAWat3c+GWL3HxCZSws2JQ+0b0/LpWuunjExIZOn89XofO\nMXtQR4Z3bpJuuusPApi1Zjfnb/ryNi4eW8uCtKrjwrieLTDU1/2ke84t6upqrPq+H5V7T2Xq1Kn8\n9ttvqg7psxMfH8+aNWtwdnamYsWK6abp3bs306ZNY/ny5VSvXh0bGxusrKw4f/68UrqEhAS8vb2V\njhkaGlK7dm2OHz9OSEgIVlbvxq9OnTrFwIED2bBhA66urh8dc5UqVahSpQoLFy5kx44drFmzhmfP\nnlGmTJlP2kCiUKFCeHl5ce3aNXr06IG6+rsNN65evQqAg0PaTUrPnDkDgLOz80eXFRcXR61atXBz\nc+P48eNK5/bv3w9AgwYNMnsL4iPExMQw8rthdKpkQUfnQqoOR+Qj8t7Ix1NXgyXtilP3t5tMnTqF\n335bquqQPjvxCYl47j9NBUdbyjvYppume5MazFm7h9U+J3Ar60Bhc1MszYy5dMdPKV1CYhK7T1xR\nOmagp0ON8iU5fe0+oS9fYWn2buG9szce8t1PG1j5fT8qlbL/6JhdnOxxcbJnzpBO+Jy8iuf+0wS9\niMDJvjBRx1d9/M3/H4+hXfAY2iXN8dU+xxm5cCPn186gTLGUhUELmhjiffQiN3yf0LlxdaW2+vWH\ngQAUs8l4kz6Ajo2qsmr3McIiozE3MUo9vvPYJTQ11OnQwC3L9yKEEOLzFp+QyPpdB6jg5Ej5Umm/\nWwL0aN2E2b+uZ9W2vVR1LkNhS3Mszc24eP2OUrqExER2HTypdMxQX4+alStw8uJ1QsNeYmlulnru\nzJWbDJu+kFVzJ+BSttRHx1y5XCkqlyuFx7hB7P7rFBt2/smz52GUdihKzO0jH84gA/MnDGH+hCFp\njq/aupfhM3/m8u5VlClRLPX4OI+l/Hn8PFf3rkFLM2W5BIUimdXb/8CpuB3VK5XNsKy4+Hga9vwO\n1/JOHFy3UOncgZMXAahXrVKW70XkX4kJ8Zze44ltqQrYliyfbpoaLbuzZ/kcTnivxqGCG6YWhTEu\naInfzUtK6ZISE7hyeLfSMR19A0pWqsH9y6d5FR6KcUHL1HMP/z7Lhtnf0W/WSuzLfPz/P/uyLtiX\ndaHT6DlcPeLD6T2eRDwPonBxJ1ZdjcrE3StLjI/Ho+9XFCtXmbG/71c6d+P0IQBKu9XNcv6qKutz\nIfOfRFZIP1bmyPynnCXt4Hey2jY9d/UWABWc0v/8MtK5eQNWevkQ9jISczOT1OPeB46hqaFBx69l\nHpUQQgghxJcmPlHB5rO+lLM1o2wR03TTdK7uwLy911h34gGuxQthbaKPRQE9rjx+oZQuIUnB3iuB\nSscMdDSpVsKCsw9CeR71FosCeqnnzj98zphN5/i1by2ci378hlSV7M2pZG/OrE5V2Hc1gM1nfAmO\nfEspa2Oer+iVibv/NFO2XeLQzaecnt4aLY2Ud8oUycl4nnpISWtj3BwyHmeOT0yixbw/cSlmzu7R\nyu96Hr75FIBapazSu1SINBKSFGy5GEg5G2PKFi6QbprOVWyZf/AeG87642pvirWxLhZGOlwJiEiT\n177rQUrHDHQ0qVrcjLOPwnkeHYeF0bs+yQt+4YzZfoNfu1Wioq0JH8vZzgRnOxNmtC7LvhvBbLkQ\nSMirWEpaGhGysFUm7j6tJy9j6LbyPA6FDPEeVANDnfSX3Z7Vphyz2pRLc3z9WX/Ge9/g+Nj6OFkb\npXNl5suKS1TQcslpKtmZsGtITaVzh++EAlCrhPnH3J74gJT+cy+8xrbFrlD69UF8GfxCIpi99Qxn\n7j4h+m08toUK0LVOWYa3rIK6Wsad2nEJidj0WfzevHvWL88i98apvyuSk1l16Brrj9zg8fNITA10\naeLiwLSutTHWz3gc53VsPHUneBLw4hWnPHpRukj++DtgV6gAS/o3pst8LwYMHJhr/ef/jo95jWqO\nnfn7/z6Lz5tf6Ctme5/nzL1nKfXbvABdazkxvHmlD9TvJGz6r3hv3j3rlmFR33qpv/uGRPKD9wVO\n3X1KbEISduZGtK7iwNBmlTDQ1VK6NjNp8yo7cyOW9KtLl4UyPiaEECJ/kvmBIqvkvaqPp6r5gbJ+\nh/iXrN+Rc1S1fkfK83s4XWs70aXWx7/PJz4/0ueTc9TV1FjWvwHVv9+a+89vaZ+LLJD2+ceT9TuE\nEEIIIYQQQgghhMgd6h9OIoQQQgghhBBCCPF5S0pKYvjQITR2MqdBifQXKBJpBUfFYzPtHE8i41Qd\niko8f51A69W3iI5LZN+A8jz43o3JXxVlyclnTPrDL8evz68alDClsVNBhgz6lsTERFWHkyf8sWcH\n4WEv6Ni9d4ZpbIrYUaN2Pfbu2s6ryJQFlXr1G4jv/XvMnT6J8LAXPH0SwOC+3SlQwDjN9d/P+BEN\nDQ16d2qN74P7xMXGcu70Cb4b2AcdbR1Klc5404v30dXTo13n7mzd9xclnEpnKY+sMjQ0YvTEaZw/\nfZIZE0cTHPSU6KhX7N21nekTRlOmXAV6fNM/Nf2p40ewNdZi1uRxWbpeCCGEEEIIIYQQQgghPoaH\nhwcRL8OZ6t5W1aGo1LMXERSo505gSJiqQ1GJ0JevaDx0Lq/evOXYskk82/8rs77tyIKNfzDml00f\nvH7vqavU+3Y2hno6nFw5hYC9v9CtSQ2GLVjP4q0H06SPjI6h7dhFPA56/t58/77vT4PBczDS1+XM\nqmkE+PzC3KFd2PDHaVqNXohCkZzle85tRgZ6THdvy4oVK7h+/bqqw/nseHt78+LFC/r06ZNhGjs7\nO+rXr8+2bduIiEgZvxo0aBB3795l4sSJvHjxgoCAALp06YKxcdrxKw8PDzQ0NGjRogX37t0jNjaW\n48eP06tXL3R0dChXLu0mGx9DT0+PHj16cPToUcqUKZOlPP4/vwULFnD16lX69++Pv78/MTExnDx5\nEnd3d0xMTBg+fHia6+7fvw9A8eLFM8z78OHDqKmpMWbMGACMjIyYMWMGJ06cYOTIkTx9+pRXr16x\nbds2RowYQcWKFRk4cOAn35NIy8PDg5dhYUxoUETVoeQr8t6IvDeSWUY6GkxsYMOK5fL8zgl7Tlwh\nLDKa7k1rZpimiKUZdSqVYtexS0RGxwDQr3U97gcEM33lDsIio3kSGk7fmSswNtBLc/3Mb9ujoa5O\nxwmLeRAYQmx8Aqeu3WfAnNXoaGlSuphNlmLX09Gmc+Nq7Fs0Bif7wlnKI6v0dLT5YVAnrj8IYNiC\n9QSGhPE2Np4z1x8wdN46jA31GdSuYWr6Y1fuUKCeO5OWbUs9NqbH1xQ0NqTPjBX4PXtObHwC3kcv\nstjrIGN7tqCIpVl6RQshhBDsOnSCsJeR9GyT/qLgALbWFtR1c2bHgeNERkUD0L9LK+75BTJ10SrC\nXkYSGBRKr9GzKWBkkOb62aP6o6GhTrvBk7j/OJDYuHhOXrqO+8S5aGtrU8axWJZi19PVoWvLRvy5\n9idKOxTNUh6f4qtaVXj8NIgRsxbzMjKK0LCXDJ3+E3cePua3maNR+89iz0fPXUW/bEMmzl8OgJGB\nPpOH9ObUpeuM81jKs9AXREW/YceB44yd+xvlSznQr1PLXL8noXpXDu8hOiKMmi27Z5jGzKoIpVzr\ncOnQLmKiIgGo17EfwY/vs2PJdKIjwggPfsKKCX3RM0rbJ9b+u5moq2uweHhHQvwfkBAfy/3Lp1g9\nZQCa2jrYOGbtfWxtHT2qfd2ZMSv2Ubi4U5by+C9dA0Naffs996+cZuuCCUSEPuPt6ygu/bUTrwXj\nsS1Znrrtv8lS3ncuHMPdpQDbFk3K8bI+RzL/KWukH0v6sbJC5j/lHGkHv5PVtulD/ycAFLO1zjDv\n/28HA4wb0J2CJsb0HD2LR4HPiI2LZ/v+Y/y8dhvjv+2BrbXFJ9+TEEIIIYTIX/ZeDSA8OpYu1R0y\nTFPEzIBapazYc8WfyJh4APrULcWD4FfM3nWV8OhYnoa/YcDvJymgl3bDu6ntKqOurkb3X4/yMOQV\ncQlJnHkQwpC1p9HW1KB0YZMsxa6rpUGHqsXZOeorSlmn7YvLaQ3K2hDw4jUTtlwg4k0cz6PeMtrz\nHHefRbKwZ3X+uyfhybvBWAzcwHTvywAY6moxvpUzZx+EMmXbJYIiYoh6G8+ey/5M3naJskVM6V2n\nZK7fk8if9l4PIvx1PJ2r2GaYxsZUj5qO5uy59oxXbxMA6F3Tnoeh0fzwx13CX8fzNOIt33peoUA6\nG1dOaVEGdTXo8fsFfJ+/Ji5RwVnfMIZu/hsdTXWcrAtkKXZdLQ06VC7CjsE1KGlplKU8/t/EnTeJ\nTUhiVR9XDHU0syVPgJMPXmA1yocZPrczXZahjibjmpbi3KNwpu6+RXDkW6JiE/C5FsSU3bcoW7gA\nvarbZ1usX6qkpCS+GzaUppUdaeSctb6fz0XQy2jMuy8k8EWUqkNRieeRb2g2w4uot3EcmtkN/1VD\nmd61Dov2XGD8uqPvvVZHS5OwTaPS/fEc1RqANtWUN6Uev+4oP24/w/edauK3cgirh7fgj8sP6eyx\nk+T3TM+Y7HmcgBevPvl+VaGRczGauDgydPCgXOk/T63fLsVpVCH330/IS4Jevsa8z1ICw6JVHYpK\nPH8VQ7PZO4mKiefQ1A74L+/P9E7VWbTvCuM9T733Wh0tDcLWDU73x3N4MwDauDmmpr8fFEGDadt5\nERXD3oltube4L2NbV2HJn9fot/SQUt6ZSZvXNapQlCaViuVa/RZCCCGyk8wPzBp5r0req8osVcwP\nlPU7Usj6HbJ+R05TxfodHh4evAwPY1K7qrlSXl4lfT7S55PTjPS0mdzeLffrt7TPM03a59I+zyxZ\nv0MIIYQQQgghhBBCiJynruoAhBBCCCGEEEIIIVRty5Yt3Lt3n2lfZbywiUjr7OP8uZhAdvn5xFPe\nxCextENJiprqoq2pThMnM76ra4Pn5VB8w97m6PX52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R6d1t/h5LBKmOlr0t3VkvM7othz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3/Abd5e6M2yIS9SqZhTSnntUgUo6GhLaHRyHlh8ogFI3ujuvwJuhnMgIHmTy9x4Dt/te5N2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\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1rVZIlLLrqPC0f99/8sZeHxNCCPFukfWBMqdK5lS9vesDZf8O2b9D9u94e/fvyOzf93Q7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KV93ISOo3X3EzOx+HgUzt19hlylGvYWhujhbouxHzjB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5tGr95Sc7u+V+tz3vF2NQrmOtcnrvnaxy+9LQuNQiz5mZncPAxi557+OSM7gUEEtbV3t0/2nD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dWVpg3r0b5tax7v1ws/X5+c2JTUVD77+lsWLlvByVNniI6NJTPTTmZm9o2YMu12h7FNJhPe\nXp4ObQYM+Pn4OLYZDNn9Mx1v6GSxmCnh6+vQ9lffiMuRTuu5cDECu93OnAWLmbNgsdOYs+cuFLh2\nERERERERERERkaLyyy+/FHUKIlJINL9Fii/Nb5F/zmgw8P1LvXlq6mIefW8BrjYLjauVpW3dKvS/\n5058PVxzYlPTM/hq5S6WbD1EeEQssYnJZNrtZNqzACfXMxgNeLnZHNoMBgM+fxszu40/+2c5tFtM\nRvw8HWP/yudS3BWn9VyMTsSelcW89aHMWx/qNOZcZHyBay8Mw6YtA+D9JzsU6n5EbjU6fosUX4ve\nG1nUKYjI3+j6fJFbi9bBIsWX5rfIP2c0Gpj31jAGTvqS/q9+iquLlSY1q3Bvk9o80rEFvl7uObEp\naelMX7yWn9bvIvx8JDEJV7L/3d2f56dzn6c24uV+zTlpDPh6uju2/Xmi2n5Nf4vZhJ+Xh0PbX/lc\nio5zWs+FqDjs9izmrt7K3NVbncacuxRT4NoLU+WyAcSvm05sQhIb9h7ihanfs2DNdpa8/xw+nm43\nJQeRwvD9082KOgURucnmje5R1CmI3DaMBgPfPNmUId/sYsDX23G1mmhY0Y+7qwfwUJMgfNysObGp\nGXZmbDzJ8j/OcyryCjFJ6dizsq5eL5LleL2HyWjAy8Xi0GbA4DAm/O3+F06uF/F1d4z9q+/lhFSn\n9UTEp2DPymLBzjMs2HnGacz5mOQC116YKvm7c3FKN+KS0tl0PJKxP/7B4j3nmD/4LrzdLLhaTACk\nZ9qd9k/LsONqNd2UXEUK05xHahR1CiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiN4y5qBMQERERERER\nEREREbmdNKhbhwObf2Xz9l2sWrueVWvXM/r1t3hn6jRWLviGunVqAfDQk8NYtnINrz4/nP69ulMq\nwB+b1cYzz7/MzO/m3/C8jAZjrrasP2+4ZTTm3vZ3Ax7uw+eT38pzH/mtXURERERERERERERERERE\nRG6uelUC2T71GbYdPsNve0+wZt8Jxn2zhimLNrNo3EPcUak0AAMmL+KXXUd4sVcrereqTSkfD6xm\nEyO/+Jk5v+274XkZjYZcbX89/stoyL3t7x5pW5epgzvluY/81n6jzfltH7/tPcHXI3sQ4OORdwcR\nERERERERERGRYqxeSEV2zZ7E1tBjrNl+gF93hPLKtPm8P+dnlrz/HHcGBwHw+PjPWbF5Hy891oW+\n7ZpRys8Lq8XCiPdn883PG294Xs7ORef339091qklH73wWJ77yG/tN4OPpxtdWtanfKkStHpqIpO/\n+5kJT/e8afsXERERkZvrzvI+bBzTlu0no1h3+BJrD11iwpIDfPjrUeYPuYs6Zb0BeGrWDlYduMhz\n7avT86FyBHi5YDUbeWHeXr7fdvqG5+XskpC/1uGGPK4X6d+0Au/3qZvnPvJb+83g7Wbh/jqBlPNx\npd3k3/lwzVFe7VKTAC8XAKISU3P1ybBnEZuURmnvEjctTxERERERERERERERERERERERERERERER\nEcmbuagTEBERERERERERkaIVNqU/8Ue30+TTo0WdSoEd/XIYkVsX5ryv/85WbP7liyyfvWNbkXzx\nOABmD18aTQ0tslykcBkMBpo3aUjzJg0Z/9Iotu7czd1d+zDxvQ/5cfbnnL8YwdJffqVP9y68+sII\nh76nz5wrlJxS09KIi0/A28szpy0qJgaAgJL+TvuULROI0WgsUE551e5MZHQMgdUb5Dl26KbVhARX\nyXcuIiIiIiIiIiIiUjx06NCBjRs3kpiYWNSpFNjDDz/MnDlzct6fPHmSihUrFlk+1atX5/DhwwCU\nKFGCyMjIIstFBDS/byTNb7nVaH7fOJrfciMZDNC0enmaVi/Py31bs+PIOTqNm8278zfw7Yu9uBiT\nwIqdR+jRvCaje7V06Hv2clyh5JSankl8UipebractpiEJAACvN2d9ilTwhOjwcCZAuSUV+3ORCUk\nETxgSp5jb/tgMMFlcz9468CpSwAMmLIQZ8M0f+4LAC79MAaz6X8/UFjkZtDx+8bR8VtuNd1fmMKW\n/ce4+MsnRZ1KgQ16YzrzVm/NeR/6w9sElXZ+zePN0OCRVzh65iIAfl4ehC/54P/Yu+/oqKq9jePf\nTCaZ9JAKISQBhdCLSAtdUQEpAaRaQF+9iooiCBcRFVGKiIKIYgNFroggHVEQRaQm9E4gIdRASC+E\n9Mn7B/eGOzcJSWAQiM9nrVmss+vvzGLP2XNmZ59bFovcubQ+33q0Pl+sRXNh69FcWG43Gt/Wo/Et\n1mJjY0NIw1qENKzFG0/3YsfhE3R5eSrvzVvFwknDuJCQws9b99H3/haMfbKnRd2zsYk3Jabs3DzS\nMjJxc3YsTEtKu/K54evhVmwdfx8PDAYbzlwse0ylnXtxElMvUSP0lVLb3jV/IsGBVYqkn7uYxJRv\nV9G2cTCDOre2yKsd5AdAxKnzZT4Hkb/CoC+2Ex6dSPTU7rc6lHJ78bvdLN19rvB455sPEuDpdMvi\naTPld07EXfk883C25+jErrcsFhGA/lOXEXYshjNfv3SrQym3obN/YcnWo4XHez56hkCf4ucJf4VW\no74h6sKVfQI8XRw4/sULtywWuTPY2EDLu7xoeZcXY7rWZdepJHrN2sKHayOY93RLYlOzWHcoll73\n+DOqc22LuueSM29KTDl5ZtKycnFzsCtMS76cC4CPq6nYOn7uDhhsbDiXfLnM/ZR27sVJysih3hu/\nlNr2lrGdqOnrUiQ9JjmTD9ZFEHK3N/2bW95DD65yZb+P4xfTAaji7oCvq4ljselF2om8mE6euYB7\nAiuVGovIzfLYv46y40wakeOKHy+3s5eWRrLswNV7WGEjmhJQqfjPl79C+1n7OJFw5TPVw8nIoTHN\nb1ksIiIiIiIiIiIiIiIiIiIiIiIiIiIiInJjtIOoiIiIiIiIiIiI3NEMRntC5sYQMjemcKP5rIsn\nOf7Zs+wc3pCw56qz9/V2xPw8CwrM191PZuwJjs9+lp0v1SP8+bvZ90ZHzq78gPzsjMIyTSZtImRu\nDJ73dL7h85Lb06Zt4VRv3JoDh49apLdq1hS/yr4kJl/ZVC0nJwcAL08Pi3IRx6PYtD0cgIKCAqvH\n99ufWyyON2658oCUDq1bFFvexdmJtq2a8+e2MGLj4i3ytoTtpGHbh9i97yBQ9nMvjrenB7lx0aW+\nate6u9znLCIiIiIiIiIiInKrmUwmCgoKKCgosHg4X05ODoMHD8bGxoYPPvjAKn2V1mZERAQFBQWE\nhoZapT+RvzuNb5GKS+NbKpqtR85Q/7mPOXTqokV682B/KldyISn9ykNmsnPzAfBytXwo5fGYBLYe\nOQPATVjOwMYD0RbHmw+dBqB1/aBiyzs72BNSN4Cth08Tl2L5IO/tR8/S6pUv2HviAlD2cy+Ol6sT\nST+OK/VVy9+r2PqTn3qw2PIf/uPKgza3fvgsST+Ow2irP+MUsQZdv0UqLpOdkbSNc0jbOIfAKt4A\nRJ6N5Ym3PiOwx8tU7vwCzYe8yeRvVpKRmX1DfeXk5vHs5Lm4dXyGjxetK5K/+18TSds4h25tmtxQ\nPyJ3sr9qfT5AQV4uUXOGs/1pf86v+7xIvtbni1yhubBIxaXxLRXJlv3HqNN3NAdPnLVIb1H/bqp4\nVSIp7crfYebk5gHg6e5iUe7Y6Qts2X8MuDl/d7dh1xGL4817r/TVtklwseWdHU20bhjMln3HuJiU\napG37UAkzYe8yd5jp4Cyn3txvNxdCr8TX+sVHFil+PqVXFiyYQezl/6O2Wz5vu2PvHLfv4a/b4n9\ni0j52RsNxM4IJXZGKAGeV35zO3A2hUe/DCN47M8Ejl7N/dP+YGH4mRvuKzffzEsL9lBlxEpm/xFV\nJH/r2E7EzgilS4PiPyNEpHzs7WxJWDCShAUjqVzJCe/Hpl/zNWLO+uvqJ+pCMk/NXE3NZ2dT7amP\naf3PeUxduo2MrNzCMmEfPEXCgpF0vVd/ey/Xtv1EAve8vY7D5y3nrM2qe+Lr5kDy5Sv/r3LyrtzL\n9XSxtygXeTGd7VEJwM2Zh286ZrmHxdbIK8et7y5+HYazyUjLu7zYFpVIXLrlb0Lh0Ym0e28D+8+m\nAGU/9+J4OtsXXs+v9arp61JsfS8Xe1bsjeGrTScw/8/7duDclXiqe11dm9Pn3mpsi0og8ZLlOa3c\nG4PRYEOve6qVGKuIXJu90UDMhBBiJoQQUMlUmJ6bX8DwZVH4j9/O51vP33A/JxOzeHbRcRpO3Un1\nd8Jo9/FeZm2O4b+/im96qQkxE0LoXMfzhvsTERERERERERERERERERERERERERERkVtLu4iKiIiI\niIiIiIhIhZKbGsehKaHkXU6n4Rs/0eLT4wT1e4OYn2YRvWDcdbWZef44B97pQm56AvVfW0azGfsJ\n6DmS82s/I/LzoVY+A7mdNbunEUZbW54aNoode/aRlZ1NUnIKH302l7MxF/i/x/oDEFjNnxpBgaz8\n+VcORxwnKzubX37bSN+nnqdvz4cB2LX3APn5+VaLzdHBgUkfzuK3P7dwOTOTg0cieP3d96ji60Pf\n0G4l1pvy1hhsDbaEPvY0xyJPkJWdzZ9bw3jyxVcx2dtTv25wuc5dRERERERERERERCA5OZnOnTtz\n4sSJ27pNESk/jW+RikvjW+5kTe/2w2hr4IVPV7M7Mobs3DySL2Uy+6dwYhLTeLxTEwACfNypXrkS\nP+04xtEz8WTn5rF+TxRPTFtCaEhdAPZGnSffbL0HfDnYG5m2ZAsbD5wkMzuXw6fjePu7DfhWcqH3\nv/ssztuP34/BYGDglMVExiSSnZvHlsOneX7WSkx2ttQL9CnXuYtIxaTrt0jFFHHqPO3+8S7xKWms\n/XgMJ5ZP57UhPZn5wzqGTPj8uttNSb9M79EzOHk+zorRilR8N2N9PkDe5VSOTB9EVvwp6wUr8jei\nubBIxaXxLXeqe2vXwNbWwNDJX7PraDRZObkkp2XwyeJfOReXxOBubQEIqOxF9ao+/LR5L0dOxpCV\nk8uvYQd57M1P6dWxGQB7Ik6RbzZbLTZHkz3vz1/NH7uOkJmVw6ET53jriyVUkprJHQAAIABJREFU\n9nSnT8fmJdZ7Z+gj2BoM9HvtY46fiSUrJ5fN+47x7OS5mOyM1K3hX65zvxkcTfZMer4/+4+f5qUP\nvuVMbAKZWTls3X+cYe/Pw93Fief7dLpp/YsI/HzwAl1mbMLZZMu6VzsQMelh+jcP5NVF+5j9R9R1\nt5t6OZcBn2/nVGKGFaMVkbIy2RlJWDCy2Ne/RoYC0KtV7XK3eywmkfvHfUd86mVWv9WfiM+GMrpP\nCLN+2sXTs36y9mnI30CTAA9sDQZeXrCXPaeTyc4zk3I5h883nuB8SiaPtgwEoJqnI0Fezvxy4AIR\nF9LIzjPz+9GLPPX1Dno0uTKv3Xc2xbrrRexsmf7rMf48Fk9mTj5Hzqfx7uoj+Lqa6PnvPovzZo96\nGGzg8a/CiIq7RHaemW1RCQxbsAeT0UAdP7dynfvN4GBny/ie9Tl4LpVXF+3jbNJlMnPyCTuRyMgf\n9uLuaMcz7e8qLD/8gWA8XUw8++0uTiZkkJ1nZsXeGGb/EcUrD9XG38PxpsUq8neUmpnHoPlHOJWU\nZZX24i7lEjr3EOnZefz0bEOOv96CNx4KYtamGMatibZKHyIiIiIiIiIiIiIiIiIiIiIiIiIiIiJy\nezHe6gBERERERERERERErOnc6o/Iz84g+LnZGF08APC8pzP+PYZzZukU/Do9jaNfzXK1eXrJZMjP\no/aLczC6eALg1aIn6Sf3cuHXL0k7HoZbcCurn4vcfpwcHflj9WLemfYRA59+kYvxCbi5uFC71t18\n/9Us+oV2A8BgMLBk3meMGPcObbv2wWg00qpZUxZ+NQsXZyf2HjxCn8H/YPRLQ3ln7KtWic3e3o65\nH7/PP9+ewq69+zGbCwhp3pSPJo/HybHkzZ9aNG3CpjU/MvGDWbTv3o+09HSq+PrQr1d3Xhv+Ag4m\nU7nO/Wb559uTmTF7jkXamLenMObtKQA82jeUb2fPKHdZEREREREREREREWtLTk6mTZs29OvXj65d\nuxISEnJbtiki5afxLVJxaXzLnc7RZMfP7w7mvcWbePLDZcSnZuDqaKKWvxdfj+hDr9Z1ATDY2DB/\nVF/GfvMrD42bh9HWQPNgf74e0QdnB3sOnIzlsfd/ZHhoCOMGdbRKbPZGWz55oQdv/es39kRdwFxQ\nQIva1Zj6fw/haLIrsd69tfxZO3EI05Zspssb35KemY1vJRd6t67LyD5tMNkZy3XuIlLx6PotUnGN\n/3Ip+fn5LHj3RbzcXQB45P7m7I44ySeLf2Xr/uO0aRxcrjZT0i/z4LAp9O7YjAdbNqTTC5NvRugi\nFdLNWJ+fdzmVQ5ND8WrenUoN7+fQpB43I3SRCktzYZGKS+Nb7mSODvasmzWGKfNWMXj858Qlp+Hq\n5EBwoB/zxj9Hn/uaA2Aw2LDg3RcY8/EPdHphMkZbW1rUv5t544fi4mjiQOQZBo6bxYhHu/Lm072t\nEpud0ZbPxjzFuM9+ZHfEScwFBbSqX5P3Xx6Eo4N9ifWa1b2L9Z+8xnvfrubBYVNIz8iksqc7fe5v\nzqjHuuFgb1euc79ZngntiK+HG58t/Y2QpyeQm5uHv68nzerWYMzgHlSv6nNT+xf5u5u4+jCV3R34\n9LF7sTcaABja8W6OX0xn2toIHm0ZSCWnkj9ripN6OZfuH2+mZ5Oq3F+3Mt0+2nQzQheR65CRlctr\n326gd6vadGgQWO767/ywmTyzmW9H9MTL9crf//duVZu9J2KZ/fNutkecI6RONWuHLRWYo70tq15u\ny7S1ETwzbyfx6dm4OhipVdmVL4c0o2cTf+DKepGv/685byw7RLeZmzEabLi3uidfDmmOs8mWg+dS\nGDInnGGdavHaw9ZZZ2Fva2DmoKa8vfIQ+86mYC4ooHl1Tyb1aYijvW2J9ZoGefDT8PZ8uC6C7jM3\ncykrFx83B3o18Wf4g7Uw/ft6W9Zzv1mebFMDH1cHvtp0gvun/UFOnhl/D0eaBnky4qFggrycC8t6\nONvz08vtmLzmCN0+2kR6Vh53+7rwbu+GDGld/abGKfJ3k5qZR+jcQ3Sv78X9tSrR46tDN9zmR3+e\nIyMnn9l9g/FwurJmrXMdT4Z38GfKb2d4upUfNb1L3tdHRERERERERERERERERERERERERERERO48\nxlsdgIiIiIiIiIiIiJTN4al9uHRqP80+OoCtydki78yyqcSs+Zj6/1yCW+0rG7KmHt1KzJqPuXRy\nHwXmPExe1fAJeQS/zkMxGEveNO7QlF5kxZ2i2Yx9FumxG77h5II3LPoAyDhzmHOrPiTteDj52RnY\nV/LD696uVOsxAltHVyu+A2WTsHMVbrVbF240/x9eTbtyZslkEnevoVr34eVqs1L99rjXbYPRxdMi\n3aV6IwCy489AcKsbC1zuGAH+fnz10dRSyzWqX5ffVywsNu/Q1vUWx0vnf1Fsuag9m4ukeXt6kBsX\nXSQ9Pz+fexo1YP2yBdeMa82ieUXS7mnUoMQY/ltZz/1meP/t13n/7detXlZERERERERERETKrn37\n9uzatYu4uDhcXFws8saNG8fkyZPZuHEjHTp0AGDDhg1MnjyZHTt2kJeXR1BQEE888QSvvvoqJpOp\nxH7atm1LVFQUsbGxFumffPIJL730En/88QcdO3YsTN+3bx9vv/02mzdv5tKlS/j7+9OnTx/efPNN\n3N3drfcGlNHFixd55ZVXePbZZwkLC7tt2xT5bxrfZaPxLXcije+y0fiWisDfy41Zz3cvtVyD6pVZ\nPeGJYvPCPxpqcfzdP/sVW27/7GFF0rxcnUj6cVyR9HxzAY3vqsLK8Y9fM64l4wYVSWt8V5USY/hv\nZT33v8pTDzXlqYea3uow5A6m63fZ6Potd6IuL09l77HTRK+YgbOj5fh8Z85yPvhuDT/PHE3bxrUB\n+HNPBB9+t4ZdESfJzzcTUNmTgQ+F8NKAzpjsSt4m4KFh7xEdE0fU8ukW6V8u38Comd+z5qPRtGtS\nuzD9QNRZpnyzkm0HI8nIzMbPuxI92zdlzOAeuDn/9Q+tu79ZPTo0rYOXu+Vn4D3BQQCcuhBPm8bB\n5WozLjmNF/o+yFM92rPzSNE1mPL3pPX5ZXMz1ufnpsbj9+AzVO7wOOnRe6wZrtzhNBcuG82F5U6k\n8V02Gt9yp6vm68mn/3yy1HIN7w7g55mji83bNX+ixfHCSUXvRwMcXlT0b9y83F1I2zinSHq+2Uzj\n4CB+mjHqmnEtnzaiSFrj4KASY/hvZT33m6Vn+6b0bK/70mJdobO2sP9sCoff7YKzyfJe1JQ1R5n5\n23GWD2tDyN3eAGyJTGDmb8fZezqZPHMB1Twc6dc8gOc71sTeaCixn54fb+ZkQgYH3+likf715pO8\nvuwAy15sQ+ua3oXph2JS+WBtBGHRSWRk5+FXyYFuDasyonMwbg52VnwHSpd6OZfo+Ax6NvEvco49\nm1Tl+7DTrD9ykX7NAsrVbvylbJ7tcBdPhFRn9+lka4YsAkD3dxax7+RFjn32PM7/M24mLd7KjJXh\nrHqjP63rVgNg8+EzzFi5gz0nYskzmwnwdqN/27q8+HAz7O1sS+yn24QfiL6YwtHZlr9Dz/l1H699\nu4GVb/SjTd2r4+PQ6XimLt1G2LEYMrJy8fNwoVvzmozq3Qo3p5K/B/yV3luyjdSMbN59vMN11e/Y\nIIh29QPxcrW89964RmUATsWlElKn2g3HKX8vVSs5MmPgPaWWq1/VneXD2hSbt2VsJ4vjeU+3LLbc\nrrceLJLm6WxP7IzQIun5BQU0rObO0heL7/M/Fj4XUiStYTX3EmP4b2U995ulWyM/ujXyK1NZfw9H\nPn383psckVRkfb4+zP7zlzjwz2Y421tef6f+foaPN8Ww5Kn6hFR3A2DryVQ+3hTDvphLV+bn7iYe\naezD0NZ+15yf95p7iFNJWewb3cwi/ZvwWN74+aRFHwCHYzP48I9zhJ9OIyMnHz83e7rW9WJEh2q4\nOpQ8T7hZ4jNyeaaVH483q8yec+lWaXPVoQRaV3fDw8nye1HXul5MXn+GNYcTGd5B128RERERERER\nERERERERERERERERERGRiqTkXd5ERERERERERETktuIT0pe04+Ek71uPd8teFnmJO1Zi8g7ELbgV\nAOmROzg6/VE87+1Kk0mbMDq6krR3LZFzXiY3LZHqgyZYJaZLp/ZzeGof3Ou2o8Hrq7D3qEJaxHZO\nzHuVtOPhNHh9JTaG4m9D5l1KYufwhqX20WTinzj61SxTPDlJ58m7lIxT1VpF8hx8q2NjayTj1IEy\ntfXfqnT6v+L7S76yMbDJJ7DcbYpYW0HBrY5AREREREREREREKrrBgwezefNmVq9ezaBBgyzyfvjh\nB2rUqEH79u0B2LJlC507d6ZPnz5ERETg7u7OihUreOKJJ4iLi+Ojjz6ySky7du2iffv2PPDAA2zb\ntg1/f382btzI008/zebNm9m6dStGY/G/VSQkJODj41NqH0ePHqVOnTpljqlOnTrlKn+r2hT5bxrf\nZaPxLXcije+y0fgWuXkKtKBBpNx0/S4bXb/lTjSoc2u2HYjkl2376duphUXekg07CPLzpk2jYAC2\nH4yk9+jp9Gx/L7vnT8TdxZGfNu/lH5PnEp+SztRhA60S095jp+jy8vt0vLcuv306lqreHmzed4wX\n3/+GbQciWf/JWIy2xT8MMDH1EjVCXym1j13zJxIcWKXMMT3Xp1Ox6ecTrjz4urpf6Z8p/ys4sEq5\nYpC/B63PL93NWp/v6FezzDHI34vmwmWjubDciTS+y0bjW+Tm0G1qkevTv3kA4dGJ/Ho4lt5Nq1nk\nrdgbQ6CXE63u8gYgPDqRgZ9v4+FGVdkythNujnb8cvACwxbsJiE9m3d7l/59tSz2n00hdNYW2gf7\nsGZ4O6q4O7AtKoERP+wjLDqR1cPbYTTYFFs3KSOHem/8UmofW8Z2oqavS5niKeDKB4xNMV16ONkD\ncCQmDZqVqblCNX1dyhyDyPUY0K4eYcdiWLfnBH1aW84Vl22PIMjHnZA6V8Z92LEY+k1dRvfmNQn7\n4EncnEz8vCuK5z/7hYS0TCY90dEqMe2Lvkj3dxfRoUEgv7w9CD8PF7YePcvLX/5K2LEYfh4/sOR7\n1emZ1B76Wal9bJ/2JLWqel53jGcT0pjz616G92xBFY/rG6P/6HxPsekXki4BUN3X/brjE7ndaL2I\niHX1bexD+Ok01h9LpldDb4u8lQcTCfQw0SrIDYAdZ9J5dP5RutbzZNNLTXA1GVkbkcTLyyJJzMhl\nQtfqVolp//lL9Pn6MO3ucmfVMw2o4mbP9lNpvLriBOGn01j5TIOS5+eX82g4dWepffz5UhNqejuW\nOaaa3o7lKl+a86k5JF/Oo5aPU5G86p4OGG1tOHA+w2r9iYiIiIiIiIiIiIiIiIiIiIiIiIiIiMjt\nofi/ZhMREREREREREZHbjlfzHhjsTCTuXGWRnh69h6z40/i26Ve4W1zS3nUY7EwE9X8T+0qVMZic\n8G7VB7fgVsRtXWS1mE4vmoDRuRLBL3yJY5W7sTU549H4AQIfGculk/tI3Lm6xLpGF09C5saU+irP\nJu85afGFbRdhY8Do7EHuv8vcqNy0eC6s/won/zq41mxulTZFRERERERERERERG5n/fr1w8HBgUWL\nLH9rCAsLIzo6miFDhmDz798qVq5ciYODA9OmTaNq1ao4Ozvz2GOP0aFDB+bNm2e1mEaOHImnpyc/\n/vgjtWvXxsXFhe7duzNlyhR27NjB4sWLS6zr7e1NQUFBqS89GE/+DjS+RSoujW8REZE7j67fIhVX\n747NcLC3Y+mGHRbpO49Ec+p8PI92bl04vtds2YfJ3o6JQ/vh510JJwcT/R9sRdvGwSz4ZavVYhr7\n6SI8XJ2ZP+F5agVUwdnRRJeQRrz9j0fYffQky/8o+QF8Xu4upG2cU+orOLDKDccZl5zG7CW/Ua+G\nP60aln1tsci1aH1+6f7K9fkioLmwSEWm8S0iInLn6dGkKiajgZV7YyzSd59O5nRiBv2bB/7nazPr\nDsVisrNlfM/6VHF3wMnelkfurUbI3d4s2nHWajG9teIQHk52zHmyOXf7uuBsMvJg/SqM616PvWeS\nWbUvpsS6ns72xM4ILfVV09elzPFUcrKnhrczO04mkZtvtsgLj04EIOFS9vWdrMhNFNoyGJOdkeVh\nxyzSd0Vd4HRcKgPa1ysc37/sPoHJzpa3H+1AFQ8XnEx29G1Tl9Z1Ali46bDVYnrju414ODvwzcs9\nqOnngbODHQ/dcxdvDmzLnhOxrAw/XmJdL1dHEhaMLPVVq2ox97jKYfqKcEx2RoZ2bXpD7fyv+NTL\nfL52D3WredMi2N+qbYuISMXRo74XJqOBVYcSLdL3nEvndHIW/Zr4Xp2fRyRhMhp486EgKrva42Rv\noE8jb1oFubFoX5zVYpqw9jSVHI182T+Yu70dcba35YFgD8Y+EMi+mEus/p9Y/5unk5GYCSGlvmp6\nO1ot3usRn5FTGO//MtiAh6OR+IzcvzosEREREREREREREREREREREREREREREbnJDLc6ABERERER\nERERESkbW0dXPJo8RMrBP8jPTC9MTwhbDjY2+LTuW5gW1P9NWsw+jsnTcrMnB59A8jPTybucesPx\n5Gemkxa5E/c6bTAY7S3yKjW4D4BL0XtvuJ/yMOdkARSJ5z9sjHaYczJvuJ+8jBQiZj1FXmY6NZ+Z\niY3B9obbFBERERERERERERG53bm7u9OzZ0/Wrl1LWlpaYfr333+PjY0NgwcPLkybNm0a6enpBAYG\nWrRRo0YNUlNTSU5OvuF40tLS2Lp1K/fddx8mk8kir0uXLgCEh4ffcD8ifwca3yIVl8a3iIjInUfX\nb5GKy83ZkYfbNOG3HYdIz7i6nnXxb+HY2NjwaOfWhWkTn+/HhV8+pVply4fTBvl5k5aRSUr65RuO\nJz0jk7BDUbS7pzYmO8uH1z3QogEAO49G33A/Nyo5LYOBr39C6qVMvnj9aWwN2iJBrEPr80v3V63P\nF/kPzYVFKi6NbxERkTuPm4MdnRv4sSEijvSsvML0ZbvPYWMD/ZsFFKa91bM+J97rhr+Ho0UbgZ5O\npGXlkno594bjSc/KY+fJJNrU8sHeaHl/6L46vgDsOX3j84TyeqtnfS6kZPLid3s4lZBBWlYui3ac\n4dutpwDIzTf/5TGJlMbNyUTXe+/i9wOnSM/MKUxfui0CGxsY0K5eYdqER9tzeu5LVPNytWgjyNeN\ntMvZpGRk3XA86Zk57Dh+nrb1A7C3s9y3oVOj6gDsjrpww/3ciHOJ6fyw6TD/6HwPlZwdrNZu8qUs\nHp++krTL2cx+vgu2BhurtS0iIhWLq4MtD9Xx4I+oFNKz8wvTlx9IwMYG+jb2KUx786Egjo9rgb+7\n5X2vQA8H0rPySc3M40alZ+ez80wabWq4F52f16oEwN6YSzfcz62WlXtlPm9vW/xv1Ha2NmTmas4v\nIiIiIiIiIiIiIiIiIiIiIiIiIiIiUtEYSy8iIiIiIiIiIiIitwuf1v1I3LmapL3r8GndlwJzPok7\nV+MW3AqT99UNbs252Vz841sSd68hK/4MeRnJYDZTYP73Zh7m/BJ6KLuclItQYCZ++1Lity8ttkx2\n0vkb7qc8bE1XNgk05+UUm1+Ql4PB3rHYvLLKijvN0Y8eJzctnrrD5+Mc2OCG2hOxhjWL5t3qEERE\nRERERERERORvYvDgwSxevJgVK1YwePBg8vPzWbx4MR06dKBGjRqF5bKyspg9ezZLly4lOjqapKQk\n8vPzyc+/8hvFf/69EefPn8dsNvPdd9/x3XffFVvm7NmzN9yPyN+FxrdIxaXxLSK3ypJxg251CCJ3\nLF2/RSquQZ1DWPbHTn7aspdBnVuTbzaz/I+dtG0cTJCfd2G5rJxc5qz4g5WbdnPqfALJ6Rnk55vJ\nN195kNx//r0RFxJTMZsLWLQ+jEXrw4otExP31z9A+7+dPB/PI2M+Ii4pjR/fe5nGtQJLryRSDlqf\nf21/xfp8kf+lubBIxaXxLSK3wvJpI251CCJ3tP7NA1i1L4ZfDl6gf/MA8s0FrNoXQ8jd3gR6ORWW\ny84z882Wk6w5cJ7TCRkkX87FXFBAvrkAgPyCghuO5WJaFuaCApbsOsuSXcVfp88nZ95wP+XVtaEf\n3z/bislrjtLuvQ04m4y0D/bhqyebc/+0P3Bx0Hafcnsa0LYeK8KO8/OuKAa0q0e+uYAVYcdoXSeA\nIB/3wnLZuXnMXb+fn3ZGcioulZRLWeSbzVfHt/nGx3ds8iXMBQX8uOUoP245WmyZmMT0G+7nRiza\nfIQ8s5kn7mtotTZPXUxhwLTlxKdeZuHoXjSs7mu1tkVutYXPhdzqEEQqpH6NfVh9KJF1R5Po28SH\nfHMBqw8n0irIjUAPU2G57Dwz3+64yJojiZxJziI5Mw9zAf81P7/xWC6m52AugKX741m6P77YMudT\ns2+8o1vM0c4WgJz84n+fz8krwNHO8FeGJCIiIiIiIiIiIiIiIiIiIiIiIiIiIiJ/Af11qIiIiIiI\niIiIyB2kUoMO2Ll5k7hzFT6t+5IWsZXctHiC+o2zKHf886Ek719PQM+ReLd6BHt3H2zs7In+dgxx\nW36waky+7R/l7iHTrNrm9bJzrwxAbnpikbwCcx55l1KwD2553e2nR+0iYtZT2Do402DsCpz861x3\nWyIiIiIiIiIiIiIid6LOnTvj6+vL4sWLGTx4MBs2bODixYtMnTrVotyAAQNYvXo148eP5/HHH6dK\nlSqYTCaee+45vv76a6vG9Mwzz/DVV19ZtU2RvyONb5GKS+NbRETkzqPrt0jF1al5A3w8XFn2xy4G\ndW7Npj0RxCWn8c5zfS3KPTnhC37Ztp/XhvRg4EMhVPZ0w97OjuEfzudfP2+xakxDurVj1ughVm3T\nGsIPnWDguFk4Ozrw6yevUa+G/60OSSogrc+/tpu9Pl+kOJoLi1RcGt8iIiJ3no51fPF2MbFqXwz9\nmwewJTKB+PRs3uxR36Lcs9/u5NfDsbzauQ59H62Gr5sD9kYDoxfvY2H4GavG9FirID4c0MSqbd6o\n++tW5v66lS3SIi6kARDk5XwrQhIp1X2NquPt5sSK8OMMaFePzYfPEJ96mfGD2luUe/rjNazbe4LR\nfULo36YuvpWcsTfa8urc31jw5yGrxvTEfQ2Z8cyDVm3TWlaFH+eeu6oQ6ONmlfZ2HD/PE9NX4uxg\nx5rxA6hbzdsq7YqISMXWoWYlvJ3tWHU4kb5NfNh6Mo34S7mMezDIotzQxcdZfzyZkR0DeKSRNz4u\n9tgbbRizOpof9sRZNaZH7/VlWs+7rdrm7aSyqx0AiZdzi+TlmQtIycyjpav9Xx2WiIiIiIiIiIiI\niIiIiIiIiIiIiIiIiNxkxlsdgIiIiIiIiIiIiJSdjcGId4texP4xj7zLaSSEr8DW5IzXvd0Ky+Sk\nXCR53694twilWs+RFvWzE8+VoQ9bCsz5RdJzU+Mtju09/cDGQHZC6W0WJ+9SEjuHNyy1XJOJf+Lo\nV7NMbdpXqoyduy+Z548Xycs8H0WBOQ+X6te3wV969B6OTn8Ux6q1qPPyt9i5aUMtuXm6DXiSreG7\nSDll3U3w/gpDXhjB90tWFh5H7d5EUEC1WxZP/dYPcDwqGgAvDw9ij+2+ZbGIiIiIiIiIiIhUBEaj\nkUGDBjF79mxSUlJYuHAhLi4u9O179WHV58+fZ9WqVQwcOJDx48db1D99+nSpfdja2pKfX/S3iosX\nL1ocV6tWDYPBUKY2i5OQkICPj0+p5Y4ePUqdOnWuqw+RO4nGt0jFpfEtIuXRd9JCwo6e5dx3/7zV\noZTbcx+v5MfNV9da7Js9jEAf91sWT4vhnxN1PhEAT1dHor4eWUoNkat0/RapuIy2Bvp2asmcFX+Q\neukyP/4ejrOjiV4d7y0scyEhhZ+37qPv/S0Y+2RPi/pnYxNL7cPW1kC+2VwkPS4pzeLY38cDg8GG\nMxdLb7M4iamXqBH6Sqnlds2fSHBglXK1vfNINL1GT6d2kB8/ThmOj4frdcUoUhqtz7+2m7k+X6Qk\nmguLVFwa3yJSHr1Hz2D7wShi1356q0Mpt2cmzWHx+rDC40M/vEdglVv396j3PvEGkWdjAfB0c+HU\nqo9uWSxy5zEabOjd1J95W0+RmpnL8j3ncDYZ6d64amGZ2NQs1h2Kpdc9/ozqXNui/rnkzFL7MBhs\nyDcXFEmPv5Rlcezn7oDBxoZzyZev61ySMnKo98YvpZbbMrYTNX1drquP/7bzVBIALWp43nBbIjeD\n0dbAI63r8PX6faRezmbZ9gicHezo2aJWYZnY5Eus3XOC3iG1+WefEIv6ZxPS/rfJIgwGA+bixndq\nhsVxVU9XDDY2ZWqzOInpmdQe+lmp5bZPe5JaVcs/Jk/HpXL4TDyv9GxxPeEVsSvqAv2mLiW4qhcL\nR/fC283JKu2KWMOgL7YTHp1I9NTutzqUcnvxu90s3X31/vrONx8kwPPOGF9tpvzOibhLAHg423N0\nYtdbHJHcrowGG3o19GbezljSsvJYcTABZ3tbutXzKixzMT2HX48lE9rQm5EdLfd6OZeSXWoftjYl\nzM8zci2O/dzsMdiUrc3iJF3Oo+HUnaWW+/OlJtT0dryuPqyhsqs9vi52HI8r+t0mKj6TPHMBTfxv\n/PuDiIiIiIiIiIiIiIiIiIiIiIiIiIiIiNxejLc6ABERERERERERESkfn9Z9ufDbHJL3/0rSnrV4\nNuuGwXR1A5qCvCubZBhdLDeiyrwQSdqxKxtIFhQU3XTjP+zcvMmL3IE5NxuDnakwPfXoFotytiZn\n3IJbknZsG7mpcdi5+xbmpR0PJ3r+GGo+MxOX6o2L7cfo4knI3JgynnXZebfsxcU/viU3PRE716ub\nlSTsXImNwYhXy9Byt5mdcJaIGY/hUOVu6o1ahK2DNuEQuRaTvT2XzkUyVTsbAAAgAElEQVRYpJnN\nZmbPnc+X8xcSffI0nh6V6Na5E1PeHEMld7dy9/Hhp1/y2oT3SszPPB+J0WjL4W2/AfDI4OfYGr6r\n3P2IiIiIiIiIiIhIUYMHD2bmzJmsXr2aFStW0LdvX5ydnQvzs7Ov/Fbh7W35IKujR4/y559/Atf+\nraJy5cps2bKFrKwsHBwcCtN///13i3IuLi60a9eOjRs3EhsbS5UqVx8ovXnzZp577jnmz59Ps2bN\niu3H29v7mnGI/B1pfItUXBrfIvJ3YbKz5cL3r1mk7Y06z4zl29gVeZ6k9Mv4e7nRvWVtRvdth4uj\n/XX3lZOXz/DP1rBo00HeeaITw3q2ssjfMXMoAI+//yNhEWevux/5+9L1W6TievShED5b8hu/bNvP\nT1v20qtDM5wcrq7ZzcnNA8DT3XK96rHTF9iy/xhw7fHt6+HG9oORZOXk4mBvV5i+cc9Ri3LOjiZa\nNwxmy75jXExKpbKne2HetgORDP9wPl++/jT31K5ebD9e7i6kbZxTtpMuhzOxCfT550fUCqjCT9NH\n4eLkUHolkRug9fnXdjPW54uURnNhkYpL41tE/i5Mdkbi139ukRZ5NpZ3vlrOn3uPkp2TR2AVL3p3\nbMbwgV1wdjSV0FLpcnLzGDbtW374dTsTn+/HywM6W+Tv/tdEAAaN+4TtB6Ouux/5++rfPJCvNkXz\n6+FYfjl0ge6Nq+Jkb1uYn5NnBsDTxfI3l8iL6WyPSgCuff32cTWxIzqJ7DwzJqOhMH3z8QSLcs4m\nIy3v8mJbVCJx6dn4ul4dN+HRiYxavJ9PHmtK44BKxfbj6WxP7Azrf4d9a8Uh1h+OZdNr92NneyV+\nc0EB/9p+mlqVXWlRw6uUFkRunQHt6vHF2j2s23OCn3edoGeLYJxMV+8pZ+flA+Dl6mhR73hMEtsi\nzl05uMa02NfdifBjMWTn5mGyu7r17abDZyzKOTvY0aqOP1uPnCUuJQPfSle/I4Qdi2Hk3PXMHtqV\nJndVLrYfL1dHEhaMLNM5X4/w41fuuTUI8i2lZOnOxKcxYOoyavp5snxcX1wcrv/3ahEpyt5o4My0\nHhZpJ+IuMeXno2yOjCc710yApxM9m1Tlhftq4my68tmUnWcmaPTqa7b9WKsgPhzQpNwx7TuTwse/\nHWfPmWQSL+Xg7+HIw438GPlQbVz+3f/WsZ0AeHJuOOEnk8rdh/y99G3iw5ywC/x6LJm1EUl0q++J\nk/3VeXR23pWLs6eT5bbzkfGZhJ1KA649P/d2sWPHmbwi8/Mt0akW5ZztbWkZ5Ma2U2nEXcrF1+Xq\nHCL8dBpjVkczs09NGlctfo8mTycjMRNCynjWt1avRt58u+MiiRm5eDlfPc+VhxIwGmwIbag5v4iI\niIiIiIiIiIiIiIiIiIiIiIiIiEhFYyi9iIiIiIiIiIiIiNxOnIMa4lS1NudWTSfvciq+bfpb5Ju8\nquHgE0TS3l+4HBOBOTeb5AMbOPbpM3g17w7ApZP7KTDnF9t+pYb3Q4GZc6umk5+ZTm5qHKcWTSAv\nM71I2aC+47Ax2HJ05hAyL0Rhzs0m7dh2ouYOx2Bnj5N/Heu/AaWo1u1ljC6eRH4+lKy4U5hzs0nY\nsZILaz+nWo/hmDz9C8umR+5g+9P+nFww7pptnlwwDnNuNrVf+AJbh+I3GRGRa3v5tfGMf28674wd\nSXzUPr7/ahYr16yj+8CnrmsD7JTUK5sMxUfuIzcuusjLaLQtpQURERERERERERG5Xk2bNqV+/fpM\nmDCB5ORknnzySYv8oKAg7rrrLpYvX86hQ4fIysri559/pk+fPvTr1w+AnTt3kp9f/G8VXbt2xWw2\nM2HCBFJTU4mNjeXVV18lNTW1SNmpU6dia2tL9+7diYiIICsri40bNzJ48GBMJhMNGjSw+vlb05Yt\nW7CxsWHYsGG3OhQRQOPbmjS+5Xaj8W09Gt8id5ZtR87w8FvzsTPasnbSECK/HsGbj97HnHW76TPx\ne8zX+dDulIws+k5cyMmLyVaOWOQqXb+tR9dvud00Dg6ibvWqTJm3ipT0yzzWtbVFfkBlL6pX9eGn\nzXs5cjKGrJxcfg07yGNvfkqvjs0A2BNxinyzudj2H2zZELO5gPfmrSItI5OLSam8PnsxaRmZRcq+\nM/QRbA0G+r32McfPxJKVk8vmfcd4dvJcTHZG6tbwL6aHm+vVj74nOyeXf014Hhcnh2uW3X4wEreO\nzzBq5oK/KDqpiLQ+/9puxvp8kdJoLmw9mgvL7Ubj23o0vkXuLBGnztPuH+8Sn5LG2o/HcGL5dF4b\n0pOZP6xjyITPr7vdlPTL9B49g5Pn46wYrYilhtXcqV3FlQ/XHSP1ci4DWwRY5FfzdCTIy5lfDlwg\n4kIa2Xlmfj96kae+3kGPJle+M+47m0K+ufjfZDrVrYy5oIAP1kaQlpVLXHo2b688RFpWbpGyb/ao\nh8EGHv8qjKi4S2TnmdkWlcCwBXswGQ3U8XOz/htQivvq+HI68TJjlx4gOSOHuPRsRi3eT8SFND4c\n0AQbm6tlw6MTqTJiJWOXHvjL4xQpTqPqvtSp5sX7y8JIychiUPv6FvkB3m4E+bqzZmcUR88lkJ2b\nx2/7TjLko1X0bBkMwN7o2JLHd+MamAsKeH9ZGGmXs4lLyeCtBX+SdjmnSNnxA9thMBgY9MEKIs8n\nkZ2bx9ajZ3nhs1+wN9pSN8DL+m9AGUVduPKbcHVf9xLLhB2Lwfux6YyZt+GabY35dgNZufl8Pbw7\nLg72Vo1TRIo6HpvOgx9uJD49m5XD2nLo3S6M6lybTzdE8ey3uwrLmYwGYmeEFvua93RLAELvKf9v\nZmEnEuk5azN2RgOrX27HkYldeb1bXb7ZcpIBn2277jUr8vfW0M+Z2r5OTN94jtTMPPo38bXIr1bJ\nRJCHA78cTSIi7jLZeWY2RCbzzA/H6F7/yvV0//lLJV6/769VCXMBTN94jvSsfOIu5TJh3SnSs/KK\nlB33YBC2NjYMWXCUqIRMsvPMbD+VxvBlUdjbGqjj62T9N8CKdpxJx3/8dsatOXnNci+3q4ank5Gh\nP0ZyKimL7DwzKw8m8Pm2CwzvUA1/d9NfFLGIiIiIiIiIiIiIiIiIiIiIiIiIiIiI/FUMtzoAERER\nERERERERKT/v1o+QFXcak3cgbsGtLDNtDAS/OAcH3xocmtST3SObELvhG4KHfk5A73/i6FeTY7Oe\n4uzKD4pt26d1X6r1HEHCjpXseqURByeHYufqRWCfMQCYc7MLy7rcdQ8Nxq7E5OnHoSmh7HghmMiv\nXsLr3oepN2oxBru/frMKo4sHDV5fiV2lKhyc1IMdw2oT89PHVB/0DtV6jiy2jo3BWGJ75pxMkg/8\njjk3mz1jQtj+tH+R14l5o27W6YhUCOG79/LFvAVMmzCOXg93xtHBgbatmjPlrddIv3SJ41HR5W4z\nJTUNABdnZ2uHKyIiIiIiIiIiImXwxBNPcOLECWrUqEH79u0t8gwGA8uWLaNmzZqEhITg5+fHJ598\nwqJFi5g4cSJ16tQhNDSU8ePHF9v24MGDeeutt/jhhx+oXLkyrVu3xsfHh0mTJgGQnX31t4qWLVuy\ndetWqlWrRps2bXB1deWJJ57gkUce4ffff8fB4doPi74ZRo0ahY2NDTY2NoSEhAAwevTowrTHH3+8\nSB2jseTfKq63TZHrpfFdMo1vudNpfJdM41uk4np34R94uTnz2Us9CfRxx9XRRK/WdXm6873sOh7D\n/hMXyt1mSkYWXcZ9S+u6gUwc/MBNiFrkKl2/S6brt9zpBj4Uwsnz8QT5edOmUbBFnsFgw4J3X+Au\nf186vTCZWn1e5YvlG5g3fihvPd2b4MAqDBw3i8nfrCy27UGdQ3htSA+WbNjJ3b1G8MCLU/Cu5Mpb\nz/QGICf36oP6mtW9i/WfvIa/jwcPDptC1a4v8uykOYR2aMrq6aNwsLe7eW9CMTKzclgXdoCsnFwa\nDnoNt47PFHkNm/ZtkXq2trbXbHfcZ4sL63d6YTIAb3z2Y2HaM5Pm3JTzkTuH1ueXzNrr8wFOL36n\ncC3+oUk9/p32bmFa5FcvWf085M6juXDJNBeWO53Gd8k0vkUqrvFfLiU/P58F775IvRr+uDg58Mj9\nzXk6tCO/hh1k6/7j5W4zJf0yDw6bQpvGwUx+YcBNiFrkqn7NAjiVkEGglxOt7vK2yDPY2PD1/zWn\nurcL3WZuptFba5m7+SRfDmnOaw/XoaavC0PmhDNtbUSJbb/auTYr9sbQ4M21dJ+5CS8XE2MfrgtA\ndp65sGzTIA9+Gt6equ4OdJ+5mbvH/MSLC/bQvVFVlrzQGpPxr99a8746vnz9fy04cj6NZu+up83k\n34hNyWT1y+1oUcOz2DpGg80125yw8jBVRqykyoiVdPtoEwDvrLqa9uJ3u61+HvL31b9tPU5dTCHI\nx52QOtUs8gw2Nswf0ZMaVSrRZfxC6r3wBXN+3cecl7oxrl8balX15PHpK5m6dFuxbQ9oV4/RfVqx\nfHsEdV74nK5v/4CXqyPj+rcBIDs3v7DsvTX9+OXtgVT1dOHhCT8Q9PQnPD97Ld2b12L56/0w2V17\n3nszpWRkAeDqaF9qWaNtyZ9DmTl5rN8bTXZuHve+Mhfvx6YXeb3y1a9Wi1tEYOJPR8gzF/DN/7Wg\njp8bLiYjoff482Sb6vx+9CJhJxKvWT8jO4/Xlx4g9B5/2gf7lLv/yWuO4OVi4pPHmhLg6YSrg5Ge\nTfx5qk0Ndp9O5sDZ1Os9Nfmbe6SxN6eTsgj0MNEqyM0iz2ADcwYGU8PTgZ5fHaLJtN18Ex7L5/2D\n+WenAGp6O/LU98f44I+zxbbdt7EPIzpWY+XBBBpN20XonIN4Odkx5oFAwHJ+fk81F1Y+0wA/NxOh\ncw4RPGkHLy2N5OF6Xix+st4tmZ+/s+40/uO34z9+Oz2+OgTAu79eTXtpaWSROqXNzz2cjKx8pgFV\nXO3o8dVBak/ewcebYninS3VGdqx2zboiIiIiIiIiIiIiIiIiIiIiIiIiIiIicme6dX/RJiIiIiIi\nIiIiItfNv+uL+Hd9scR854B61P/nkmLzmkz80+K47ogFFsc2BlsCQkcREDqqSN2QuTFF+wpqSO1h\nX5cl7L+MydOfWv+YVWo511otqNrleYzOlUosY7B3LPa8RQDu6zmA3fsOcv7oLlycnSzy3pz8Ae99\nNJvfVyykfeuWAPyxeTvvffQpO/fuJy8vn8AAfx7v15sRLzyDyb7kDeA6dO/HiZOnOXd4h0X67Lnz\nGT72bX5b/j0d2lx98MT+Q0d45/2ZbAnfyaWMDKpWqULv7p0ZN/Il3N1crfgOlM033/+Is5MTj/Xv\nbZE+ZFBfhgzqe11tpqal4ejggNF47Qe4iIiIiIiIiIiIyM0xZswYxowZU2J+48aN2bhxY7F5R48e\ntTheu3atxbGtrS0TJkxgwoQJReoWFBQUSWvatCkrVqwoQ9R/jQ8++IAPPij+ob//q23btowePRpP\nz+If/HM9bYrcKI3vkml8y51O47tkGt9yJ+r21nz2nrhA5NwRODtYrjmYuHAj05dtZfWEJ2hT78qD\neDYdOsWMZVvZHXWevHwzAT7uDGjfkBd7tMJkV/Jv713f/JboC8kcm/OKRfpXa3cxZu46Vr39OG3r\nBxWmHzx1kamLN7H96FkysnLw83Sle8vajO7bDjcnkxXfgbLp2aouvu7O2P/P+oI6AVce0nUmPpV7\nalYtV5vxKRk8370FQx64h13Hta5Ibi5dv0um67fc6UY82pURj3YtMb/h3QH8PHN0sXm75k+0OF4+\nbYTFsa3BwOtPhfL6U6FF6qZtnFMkrXFwEAsnDStL2Dedo4N9sTGWJKRhLYYP7IKHm/M1y016vj+T\nnu9/o+FJBab1+ddmzfX5AEH93yKo/1vWCk8qKM2FS6a5sNzpNL5LpvEtd6IuL09l77HTRK+YgbOj\n5T3gd+Ys54Pv1vDzzNG0bVwbgD/3RPDhd2vYFXGS/HwzAZU9GfhQCC8N6IzJruQt8R4a9h7RMXFE\nLZ9ukf7l8g2Mmvk9az4aTbsmtQvTD0SdZco3K9l2MJKMzGz8vCvRs31TxgzugZuzoxXfgbK5v1k9\nOjStg5e7i0X6PcFX7q+fuhBPm8bB5WozLjmNF/o+yFM92rPzSLTVYhUpzrBOtRjWqVaJ+fWrurN8\nWJti87aM7WRxvPC5EItjW4MNo7vUYXSXOkXqxs4oen+rYTV35j3dsixh/2W6NKhClwZVSi3X8i4v\nXri/Jh5OJf89McD40PqMD61vrfBErunlHs15uUfzEvPrB/qw6o3i761un/akxfHiMX0sjm0NNox5\npDVjHmldpG7CgpFF0hpV9+VfI4uO+1vt/Sc78f6Tna5ZplVtf4Z1b4aHs0OJZRztjcWet8j1CJ21\nhf1nUzj8bhecTZbz6ClrjjLzt+MsH9aGkLu9AdgSmcDM346z93QyeeYCqnk40q95AM93rIm90VBi\nPz0/3szJhAwOvtPFIv3rzSd5fdkBlr3YhtY1vQvTD8Wk8sHaCMKik8jIzsOvkgPdGlZlROdg3Bzs\nrPgOlE2H2j60reWNp7PltbdRwJV72KcTM2h1t1eJ9d//JYK0zFwmhDa4rv67N66Kj6sJO1vL97h2\nlSt7fpxNukyTwGvfTxcpzott/XmxrX+J+fWqOLPkqeLnk3++1MTieMETdS2ObQ02jLovgFH3BRSp\nGzMhpEhaQz9nvh5Uu0j6rfJW5yDe6hxUekGgRaArz7epSiXH0rfo93c3MeuRkr8TiYiIiIiIiIiI\niIiIiIiIiIiIiIiIiEjFUvpKcxEREREREREREZEKKu9yKgnhK6g/+sdbHYrcoZ7o34ctYTv5ad3v\nDOzTwyJv0fKfqB4YQLuQFgBsDd/FwwMG07tbFw5t+w13N1dW/ryeJ18cSVxCItMnvmmVmHbvO8h9\nPQfQqUMbNq9ZQlW/Kvy5NYxnXxnDlrCdbPppCUZj8Q9xS0hKxq/OvaX2cWjremrXurvMMW3bsZvG\nDepisr/2BpXlkZKahqvLtR/eIiIiIiIiIiIiInK7S05OZuHChWzYsOFWhyIiVqbxLVJxaXzL7WJg\nh0ZsP3qWtbsieaSt5cN7lm09TJBvJVrXDQQgLOIsfScupHvL2uyYORQ3JwfW7DjG0FkrSUi9zOSn\nHrRKTHtPXKDbW/Pp2KgG6yYNwc/TlS2HT/PyZ2uuxDpxCEbb4h8ilph+mVr/N6PUPsI/Gkot/5If\nxPW/nu/Wotj0w6cuYmMDdQJ8ytzWf9Ty9ypXDCJy6+n6LVJxpaRfZsnv4fw0Y9StDkVE0Pp8kduR\n5sIiFZfGt9wuBnVuzbYDkfyybT99O1nej12yYQdBft60aRQMwPaDkfQePZ2e7e9l9/yJuLs48tPm\nvfxj8lziU9KZOmygVWLae+wUXV5+n4731uW3T8dS1duDzfuO8eL737DtQCTrPxlb8r3q1EvUCH2l\n1D52zZ9IcGCVMsf0XJ9OxaafT0gGoLpf+e9VBwdWKVcMInLrpV7OZfmeGJa+0OZWhyIiVpaSkcWy\nbcdYMa7vrQ5F/ib6Nw8gPDqRXw/H0rtpNYu8FXtjCPRyotVd3gCERycy8PNtPNyoKlvGdsLN0Y5f\nDl5g2ILdJKRn827vhlaJaf/ZFEJnbaF9sA9rhrejirsD26ISGPHDPsKiE1k9vB1Gg02xdZMycvh/\n9u47PIriDeD49y7l0ntCKEnohI7Se++9NwEVUFGQHyC9SleUIoKioICo9N57hyRAAoQkdEgIBNJ7\nvbvfH9HgmYTkIJAY3s/z3KO3+87Mu8NNdrK3ma007UCObZyd3JKyTha5zmlo49JZbg+JSgLAzT77\n9SoeRSbwy9n7jGpZDmdrk1y3+U8fNc16TY4bj2NQKKCCs+VL1SuEyBvRiWnsvB7Glvcr5xwshBBC\nCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQ4q1imN8JCCGEEEIIIYQQQgghRH4xNLOm5jeX8jsN8R/W\ns0sHRk+exZade+nXo3PGdo/L3tx/GMiM8aNRKNIXpNp94AgmKhULZ06mmHMRAAb06sovv29i/cat\nLJ47PU9y+mLGXOxsbdi4ZgUqY2MAOrZpwbxpExj+v4ls2bWP/j27ZFnWwc6W1Gf38iSPf3rwMIgq\nbVvy2+btfLfqVwJu3cHU1IR2LZsyf/okShTTf9HZqOgYjIyM+PLrpWzbc4D7DwKxtbGmW8e2zJo4\nBjtbmzw/DiGEEEIIIYQQQgghhMhrtra2BAUF5XcaQojXQMa3EIWXjG9RUHStX5EJaw6x47wfPRs9\nfyDNpVvBPHgaxcQ+TfjrlgX2e91CZWTI7EGtcLZNf5BU78ZV+O2YD3+cvMr8D1rnSU7T1h3B1sKU\nX8f2RGVkAEDbmuWYMaA5o37Yy84L/vRqlPXDc+wtzYjYMjVP8niR0Oh4Np26zk8HvBjfszEVSji8\n9jaFEPlPzt9CFF42lmb4b1mU32kIIf4i9+cLUfDIXFiIwkvGtygoujerxfhlf7DtuCe9WtbJ2O7l\nd48Hj0OZ/H6XjL+v23fWB5WxEXM/6U1Rh/S//erTuh7r9p3h9wPn+GpkvzzJafKKTdhamrP+yxGo\njNKX2WtXvxqzhvfks6/XsuOEF71b1c2yrL21BTEnV+dJHjl5FhnDyq1HqVSqOPWqln0jbQoh8pe1\nmRHeM9vkdxpCiNfAxtyEa8uH53ca4i3SuUYxpmy7xi7vYLq/WyJj++WHkTwMj+eLdu4Z94wc8g1B\nZWTAzC6VcbY2AaBnzRL8fvEhmzyDmNO9ap7kNGOnL7ZmRqx+vzbGhkoAWld2ZmqnSozZ6M1un2B6\n/CPXf7IzNyZkSdc8ySMnobHJ/HT6Lu5Frahdyi7buCWHb6EyVPJx0zJ52vaWS0GsOXOPsW0qUN7Z\nMs/qFkLoz9rUkEvjauZ3GkIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCEKIGV+JyCEEEIIIYQQ\nQgghhBCvQpOWwoWhxbkwtDjJYfm7gK3P1CZcGFqcCO9D+ZqHeHOsrSzp3K4Vh46fIiY2LmP7n9t2\no1AoGNS3R8a2r2ZNJvK+L64liunUUdK1BNExsURGRb9yPjGxcZz3vEyzhvVQGRvr7GvTogkAnld8\nXrkdfajVahKTkjhx5jzr/tzKL8sX8STgMn/8vJzzHpdp2K47UdExeter0WhJTk7G3MyUw9s28OiG\nJ0vmz2Tb7v3Ua9ON2Lj413A0QgghhBBCCCGEEEIIkVlycjIKhQKFQsGDBw/yNRd3d3cUCgW7du3K\n1zyEKCxkfAtReMn4FoWBlZmK9rXLccznLrGJyRnbt569gUIB/Zo+f1jX7EEtCfptPCUcrHTqcHOy\nISYhmaj4pFfOJzYxGY+ARzSu4obKyEBnX8t3SgNw+XbwK7fzsu6FRGLXex4Vhi3lqy1nmDmwBV/0\napRv+Qgh9CfnbyEKr+TUNKyaDcOq2TACQ8LyNZeag6Zh1WwY+8692XsthShI5P58IQoemQsLUXjJ\n+BaFgZW5KR0a1uCopy+x8YkZ2zcf9UChUDCgbYOMbXNH9ObJgRWUKGKnU4dbUQdi4hOJik145Xxi\n4xO56HuHxu9UQGVkqLOvVZ0qAHj533vldl5VZEw8/aZ8T3RcIqumDMVAKcsBCvFfkZKmwXnMLpzH\n7CIo4tV/br2KhguO4TxmFwd9Q/I1DyEKi5RUNQ4DF+MwcDGBofr/7XteqvfFrzgMXMyBy3fzNQ9R\ncFmZGNG2SlGOBzwjNiktY/v2y49QKKBPLZeMbTO6VObuwo4UtzXVqcPVzoyYpFSiE1JfOZ/YpDS8\n7kfQsJwjxoa6c9vm7k4AXHkY+crtvKqohBSGrPEgJjGV5QPfxUCpyDIuODKRzV5BDG1cGmszo1du\n935YPM5jdlF1xkG+PXSTqZ0qMaZNhVeuVwiRPj8vPvMCxWdeICgqOecCr1GT5T4Un3mBQwER+ZqH\nEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCiFdnmHOIEEIIIYQQQgghhBBCFEzlhi+n3PDl+Z1G\nhhrzTud3CiIfvNenB1t27WPXgcMM6tMDtVrN1l37aNKgLiVdny+SlZSczI+/bGD73gPcfxhERFQU\narUGtVoNgFqjeeVcnoQ8RaPR8PvWnfy+dWeWMY+Cn7xyO/pQKpUolUqiY2PZ8usP2NpYA9CqaSNW\nfDOXTv0+YOmPa5g1cYxe9Z49sC3Ttp6d26NUKunzwQgWLf+R2ZPH5ckxCCGEEEIIIYQQQgghRHY2\nbNjAhg0b8juNDAEBAfmdghCFhoxvIQovGd+iMOnXtBo7z/uzz/MW/ZpWRa3RsuO8Hw0rueHmZJMR\nl5yaxppDl9l9MYAHT6OIiktErdGg1miBvLlnISQiDo1Wy+bTvmw+7ZtlTHBY/j0wr7SzLRFbphIV\nn8TZGw+ZuOYQ28/5sX3GAGzMTfItLyFE7sj5W4jCa/XUYayeOiy/08hw+be5+Z2CEPlK7s8XouCR\nubAQhZeMb1GY9G9bn+0nvNh71pv+bRug1mjYccKLRtXL41bUISMuKSWV1TtPsOv0ZR48DiMyNj79\n7+v+ukadJ39fFx6NRqNl05GLbDpyMcuY4GeRr9zOq7j/OJSeE5fyLCKGLQs/p3o513zNRwiReyve\nq8mK92rmdxoZzk1umd8pCFFo/Phpe378tH1+p5Hh4jcf5HcK4j+gT20XdvsEc+D6E/rUdkGt0bLb\nJ5j6ZRxwtTfLiEtO0/Dr2fvsu/aYh2HxRCakotFqn98zotW+ci5PY5LQaLVsvRTE1ktBWcY8jkx8\n5XZexYOweAb+dJHQ2GQ2DK9H1eLW2cZu9goiTaPhvfpuedJ2KQdzQpZ0JTohlXN3w5i67Ro7vYPZ\n8kkDrM2M8qQNId5Gy3uWY3nPcvmdRobTo2rkdwpCCCGEEEIIIRmC0wkAACAASURBVIQQQgghhBBC\nCCGEEEIIIYQQQggh8ohhficghBBCCCGEEEIIIYQQQvyXtWneBCcHe7bu2segPj04cfYCT0PDmD9j\nok7cgOGj2HvoGNO/+JyBvbtTxMkBlbGKEV9MYe0fW/I0pw/f68uqxQvytM6XpVAocLS3w8bGGlsb\n3QWxmjSoi0KhwOf6jTxrr22LJigUCjwv++RZnUIIIYQQQgghhBBCCCGEEEIIIURB1KJ6aRytzdl5\n3o9+TatyxvcBodHxzHqvhU7ch4t3cPDyLSb0bkKfJlUoYmOBsaEBY37az+/Hr+ZpToNa1mDZJx3z\ntM68ZGNuQqc6FSjhYEWLib+wdMf5TP0lhBBCCCGEEEIIIYQQIvda1q6Co60l209con/bBpy+EsCz\nyBhmf9xLJ+79L1dx4PxVJg3pTL829SliZ4WxkRGjv13Pb/vP5mlOQzo2Zvn4IXlaZ17w8L1Lv6nL\nMTc14fD3k6hUqnh+pySEEEIIIf6jmrk74WChYrdPMH1qu3D2dhihsclM71xZJ+6jdV4cvhHCuLbu\n9BpQAicrE4wNlYzf7MOfHoF5mtPAem5827dGntaZF7zuRzBkjQfmKkN2f94I96JWL4zfe/UxNVxs\ncbEzy9M8rM2M6FC1KCVsTGmz+BTfHbvN9M6V8rQNIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGE\nEEII8eqU+Z2AEEIIIYQQQgghhBBvC/8lA/H4tFx+p/GfVVD7z++bvniOdM/vNEQ+MjQ0oG+PLhw5\neYao6Bg2bt+NhbkZPTu3z4h5HPKUPQeP0qdbJ6aPH03pkq6Ym5lhaGhAYFBwjm0YGBigVqszbX8a\nGqbzvnixoiiVylzVmZWwiEiMnErn+Lp5+65e9b5TrQqhYeGZtqelqdFqtRgbGelVX0pKKt7XfLlz\n70GmfcnJKWi1WkxMVHrVKYQQQgghhBBCCCFEQdWuXTssLCzyO40Cad26dVhaWvLBBx+QmpoKwOzZ\ns1m/fn0+Z5azgvrv2qpVK2xsbPI7jbdGQf0cFAQyvvOejO83q6B+DgoCGd95T8b3283QQEnPhpU5\ncfUe0fFJbDt7A3MTY7rWr5gRExIZy4FLt+jeoBITezemVBFbzFRGGBooeRQanWMbBkolGo020/bQ\nqHid98XsLVEqFATlos6shMcmYNd7Xo6v28GZ7z/IzqOwGEb9sJeNp65n2udewhGAm4/CMu0Tb6eC\n+nO+IJDzd96T8/eb1X38EpzbfZbfaRRIfxw8T9H2nzFi4a+kpqXfo7hw3R7+PHQ+nzPLWUH9d+0y\n9ltKdByV32m8NQrq/eX/FQW1/+T+/DevoM6ZCgKZC+c9mQu/WQX1c1AQyPjOezK+326GBkp6tazL\n8Us3iI5LYMsxD8xNVXRrVjMj5klYFPvP+dCzeW0mv9+FUsUcMTNRYWigJCgk5+u+BgZK1BpNpu3P\nImJ03hd3tEWpVBD4NPfXkv8pPDoOq2bDcnzdCgzRu24vv3t0G78Yt6IOnPhhKpVKFX+pHEXh1n/V\nBUpP3JvfaRRIm72CKDNpH6P/9CZVnf7z4NtDN9nsFZTPmeWsoP679v7hPOUn78/vNN4afb7ajuuH\ny/M7jQJp4xk/3IYuZ9SqQxnje9H2i2w645fPmeWsoP679pi/ldLDV+R3GuI1M1Qq6P5ucU7dDCU6\nMZUdVx5hrjKkU/ViGTEh0Ukc8g2ha43ifNG2AiUdzDEzNsBQqeBRZGKObSiVCtRZ3TMSl6Tzvqi1\nCUqFgkeRCS91LBHxKTiP2ZXj686zOL3rvvwwkn6rLuBqb8aBMU1wL2r1wviH4fHceBxN4/IOL3Us\nfwuOTGTMRu8s5yrlnS0BuPU09pXaEK/fwN/8KTfPI7/TKJC2+IRSfp4nY3beIU2d/nNiyclHbPUJ\nzefMclZQ/137rvPDfYFnfqchhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQAlDmdwJCCCGEEEII\nIYQQQojCIy0hhscHf+D6vE5cGlODi8Pd8PysAtfndCD4wAo0aSn5naIQr8WgPt1JTU1j7+Fj7D5w\nhB6dO2BuZpaxPyUl/bNvb2erUy7g1h1OX0hfIEarzbwI1t+KODoQERVNUnKyzvbjp3UfuGJhbkaj\nerU5df4iIc90F8g5e9GLqo3acNkn8wPO/uZgZ0vqs3s5viqUK/OC3sisb4/ORERGcfTUWZ3tJ89e\nAKBh3dp61ZeckkLTTn34eOzkTPsOHD0JQPNGDfSqUwghhBBCCCGEEEIIkT+WLl2KQqHAxcWF2Nis\nF7T//vvvUSgU+Pr6ZmxTq9XMmTMHX19fypQpQ+/evQkNDWXnzp3UrVv3TaUvhHgBGd9CFF4yvoUo\nWPo2rUqqWsPBy7fZ53mTrvXcMVMZZexPTlUDYG9pplPuVnAY5/wCAXjBLQs4WpsTGZdIcmqazvZT\n1+/rvDc3MaZ+RRfO3XjIsyjdh29d8A+i3v9W4X33Sbbt2FuaEbFlao6vcsXts0/2XxyszNh+zo9V\n+z3R/Osgr95Lf1BvqSK2WRUVotCR87cQhdfKrUewajaMir3HE5eQlGXMTzuOY9VsGH73gzO2qTUa\nvlq/B8+1sylV3JHBM38gLCqWfWe9qVWp9JtKXwiRA7k/X4hXJ3NhIQovGd9CFCwD2tQnNU3NgfNX\n2XvWm25Na2FmosrYn/LXNWY7awudcjcfPuHs1ZvAi/++zsnWisjYeJJSUnW2n7zir/Pe3FRFg6rl\nOetzk6cR0Tr7zl+7Te0h0/G++SDbduytLYg5uTrHV3lX5+w7IwuBIWH0mLCUci7O7F38BY62lnqV\nF6Kw+OnUXZzH7OKdLw8Tl5yWZcwvZ+7jPGYXAU9iMrapNVoWH77JqYnNKWlvzvC1XoTHJXPw+hNq\nusl3PUIUBD8evILDwMVUG/UzcUlZX7NafdgHh4GL8X8UlrFNrdHyzY6LnP1qCCWL2PDhsj2ExySy\n//IdapYt+qbSF+I/q09tV1LVGg7fCOGA7xM6VS+GmbFBxv6UNA0AdhbGOuVuP43lwp30sfiiebij\npYqohFSS/6rnb2duhem8N1cZUre0PefvhPMsVndNDI974TReeJyrQVHZtmNnbkzIkq45vso6WWRb\nR1aCIhIYsOoCZZws2PppQxwsVDmW8bwfAUCV4tZ6tfVv9hbG7PQO5ufTdzPds3LtUfrvKiXtzbIq\nKsQb8/OFJxSfeYFa314mLlmdZcyvHiEUn3mBgGcJGdvUGi1LTj3i+GfVKWlrwkebbxEen8rBgAje\nKaHfOBVCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghCiJlficghBBCCCGEEEIIIYQoHNSJsfjO\n68Sj3UtwrN+T6rOPUfeHO1SbeRjryk0J3DqfgGWD8zvNPFfpi03U+T4gv9MQ+eydalWoVKEccxYt\nIzIqmiH9eursdy1RnFJuruzaf5gbAbdISk7mwNGT9PpgBL26dADgkvc11OqsF8dp17IZGo2GOYuW\nER0TS8izUMbPnEd0FotVL5gxEQOlAV0HDuXm7bskJSdz6txF3v9sHCpjYypXLJ/3HZCD/j260KRB\nXYaOGs/Zi14kJCZy8uwF/jdlFmVKufHhe30zYs95XMLIqTSfT5qZbX2WFubMnPg/Tp/3YNz0uTx6\nHEJ0TCxbdu1j3LTZVKtckeFD+r+JQxNCCCGEEEIIIYQQQuSRR48eMWXKlFzH37lzh0qVKuHm5sa0\nadNo1aoVpUuXpn79+lSoUOE1Zlq4HT16lKio7B+2IMTLkPFdMMj4Fq+DjO+CQca3qF7aGXcXR77e\nfIao+CT6N6+us9/F0ZqSRWzY63kT/8BQklPTOHLlDoMWbaVr/YoAeN95jFqT9cO9Wr1TBo1Wy1eb\nzxCTkMyzqDimrTtKTEJypthZ77VAqVTSb8FmbgeHk5yaxtkbDxmxfBcqIwMquTrmfQe8gImxIXMG\nt+TqvRBG/7iPwNBoEpNTOe8XyOc/7sXa3ISPOtTOiL8YEIRd73lMWHPojeYpxJsk5++CQc7f4nUI\nDo1k1s/bcx1/L/gZ7iWL4VLEngmDOtG8ViWq9p9EncplKOei3wPtxXO7F4/j0b7l+Z2GKCTk/nwh\n8pbMhQsGmQuL10HGd8Eg41tUL+9GxZLFWLB2N1GxCQxs30Bnv0sRe0oWc2TvGW/87geTlJLK4YvX\nGTh9Bd2a1QLgSsAD1BpNlvW3rlsVjUbLwrW7iYlP5GlENFNWbiYmPjFT7OxPemKgVNJ70nfcCgwh\nKSWVMz43+Wj+GlRGhlQsVTzvOyAH45b+QXJKKr99OQILM5MXxl64fhurZsP4Ytnvbyg7Id68J1GJ\nzN/nl+v4B2HxlC9iSQlbM8a0KU+T8k7UmXuUmiXtKONk8RozLdy2jGjArQUd8jsNUcg8johl7qaz\nuY6//zSKCsXtcHGwYly3ujSt4sa7Y1ZTu1xRyha1fY2ZFm7bp/Ti3s+f5Xca4g2oWsKaCs6WfHvo\nJtEJqfSr46Kzv4SdKW725hy49oSAJzEkp2k45v+UD37xpHON9HmxT1BUtveMtKxYBI1WyzcHA4hJ\nSuVZbDKzdvkSk5SaKXZ650ooFfDezxe58yyO5DQN5++EMfL3K6gMlbgXtcr7DsjB5G3XSEpVs3pI\nbSxUhrkqc/dZHABu9ubZxnjcC8d5zC4mb7uWbYyJkQEzu1Tm+qNoxm3yISgigcQUNRfvhjN2ozfW\npkYMa1JavwMS4jV5EpPCwmOBuY5/EJFEeUdTStioGN20BI1LW1N/qTc1XSwp42D6GjMt3DYNqUTA\n5Dr5nYYQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIHd/iSKEEEIIIYQQQgghhBA5CPPYSWLI\nXUr2nYVziw8ytps4ueHaYyJpCVE8PbGeqBunsKncNB8zFeL1eK9Pd6bM+ZqSri40rq+7uIpSqWTr\n2h8YM3U2jdr3wNDQkHq13uXPn5djYW6G93U/egwezvhRnzB78rgs634Q9IjfNm1n2Y+/UNS5CMMH\n92fOlHH0GvIJySkpGbF13q3B6X1bmPvNcpp06k1MbCzOTo707taJSaM/xUSleu198W8GBgbs+fMX\n5n6znPc/Hcvjp09xsLOjQ5sWzJ48DkuLzAthGRq++CuMcZ99RElXF5b/9Cu1W3QkJi4ON5cSDB3U\nj4mjP8XMVBYIEkIIIYQQQgghhBDiv6Rnz56sXLmS9957j7p16+YYX6FCBXbv3p3xfuTIkYwcOfJ1\npiiEeEkyvoUovGR8C1Fw9G1SlS9/P46bkw0NKrrq7FMqFKz/oheTfz1Mm6lrMTRQUrt8cX4Z0wNz\nE2Ou3Q9h4NdbGN21PlP7N8tUd7+m1Qh6Fs3GU9f4YZ8HzraWDGn9DtP6N2PQoq2kpKozYmuWK87B\nuUNYtPUM7aatIzYxGScbC7o3qMjYHg1RGb35P2f8sE1NHK3NWbXfi8bjfiYlTU0JBytqlivG+F6N\nKVnEJlMZQ6XyhXVOX3+UFXs8dLbN+O0YM347BkDvxlVY9XnXvDsIIfKQnL+FKLy6NqnJ6l0n6Nem\nHrUq5vzgyHIuzmyaPyrj/UfdW/BR9xavM0UhhJ7k/nwh8pbMhYUovGR8C1Fw9GtTn5k/bcOtqAMN\nq5XX2adUKvh9zqdM/G4jLT+dj6GBAXUql2HtzE+wMFVx7XYg/aYuZ8yA9kwf2j1T3f3b1icwJIw/\nDl1gxZYjODvY8EHnpswY1p0B01aQkpqWEVurYmmOfD+Jhev20HrkAmLjEyliZ02PFrX5YmBHTIyN\nXntf/FNiUgqHLl4DoGr/SVnGDO7YmO/HD9HZZmBg8MJ6p/6wmeWbDutsm/bDFqb9sAWAPq3rsXrq\nsJdNW4jXqlP1Yqw9+4BeNV141802x/gyThasH/b8PP9h41J82LjU60xRCPGSOtcpxy9HrtK7YUVq\nli2aY3zZorb8Pq5bxvthbWowrE2N15miEIVO71ouzN3rh6u9GfVKO+jsUyoU/PJhbaZt96XjsjMY\nKhXULGnHT0NqY64y4PqjKIas9mBky3JM6lAxy7qDIhLY7BXEqlN3cbY2YVD9kkzuUJEPfvEkOU2T\nEfuumy17Rzfh20MBdFp2hrikVBytTOhWozijW5dDZfjiezHyWmKKmqN+TwGoM/dIljED6rmxuK/u\nz5yohFQALExyvsfFUKl44f73G5bC0dKEn0/fpcWiE6SkaShua8q7bnaMaVMeN/vM62wIkR86VrJn\nnWcIPas58k4JixzjyziYsnaAe8b7D+o680Fd59eZohBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQ\nQgjxRr3Zv4QRQgghhBBCCCGEEKKQirvvg//SQXiNqojnSHd8F3YnyvdEjuWi/c/h901fPD+rgMeI\nMvhMa0rwvu/QpKXoxKXFR/Fg4yy8JzXA45PSXPpfNfyXDiLuvs9Lxb0OaXGRAJiXrJblfpcuY6n+\n5VGs3RvqbI+944X/kvfwGlWRix+5cWV8He7/PjWjvn9SKA2ID/LD79t+GX124+texAf66sT5LxmI\n9+SGxAf5cXVmSzw+LoVWk/7gqfjAG9z8/kO8Pq/MxY9LcmVifR5uno06MTaj/I2veuAxogzq5PhM\nOQRu/4oLQ4sTc/MCQPq/30h3vcvlNhcA3wXduDQm86JlIcd/zVSnyD/jR31C6rN73L50CoUi86JN\n1SpX5NjOP4m870vobR/2/PkLVSu5U8rNFd9zR0h8fJvZk8cBsG/TWqIePP9cGxgYMHPC/7hz+TRx\njwK4fekUEz7/hK7t25D67B5tmjfRaeudalXYtn4VT29eIfHxbe77nOfrWVOws838ALM3xczUlPnT\nJ3DnyhkSgm8ReP0iP347HycHe524hnVrMe6zj3B2csyxzp6d23Nyz2aeBFwm/tFN/C4cY+7U8Vha\nyKJXQgghhBBCCCGEEOK/wcvLiw4dOmBra4uNjQ2NGzfm4MGDOZY7fvw4rVq1wsrKCjMzMypWrMj8\n+fNJTk7WiYuIiGDMmDGUKVMGU1NTnJyc6NChA56eni8V9zrNmDEDJycnhg8fTmpqaq7K5LYfAM6d\nO0f79u2xtbXF2NgYNzc3Ro4cSXh4eI7t6NM/+rRjYGDA1atXad26dcYxNG/eHG9vb524du3aUa5c\nOa5evUq1atUwMTFBrU7/3sPHx4du3bphb2+PSqWidOnSfPHFF0RHR2eUb9KkCWZmZsTFxWXKYerU\nqSgUCk6dOgVAq1atsLGx0btcbnMBaNSoEc7OmRd7//7771EoFJw8eTLTvv8iGd/PyfiW8S3jO52M\n73QyvmV8i9djdLf6RGyZiveKz8jilgWqlCzCni8HEfTbeO6vHcfmKf2o7OZEySI2eCz9hGcbJzO1\nfzMAtk7tz6MNEzLKGigVTOrbBJ+VI3nyxyS8V3zG/7o1oGOdCkRsmUqLGqV12qpe2pkNE3pz99ex\nPNs4Gd8fRzFncCtsLUxfZxe8UOe67uz9chAP13/Bkz8m4vXdCH4c1ZUyRe104uq5uzCqSz2cbF98\n38Gcwa2I2DI129eqz7u+zsMRL0HO38/J+VvO34Xt/H0l4AE9Jy7DpdPnlOg4irajvuKop2+O5U5d\nCaDL2G8p1mEkRdp+Sq3B0/hmwz6S//HgeIDImHgmfb+JagMm49RmBKW7jaHnxGVc9r//UnGv08Qh\nnXG0sWLUovWkpqlzVSa3/QBw0fcOPSYsxaXT59i3+phKfSfwxbLfiYjJ/Nn9N336R592DAyUXL8b\nRNdxizOOoeP/FnH1dqBOXPfxS6gxcArX7wZR/8NZOLb+BLUm/eGk1+4E0X/q97h1GY1D60+o2n8S\nU3/YTEx8Ykb5dp9/RZG2nxKfmPnn3uzVO7BqNoyzV28C0GXst5ToOErvcrnNBaDNyIWU7T42U50/\n7TiOVbNhnPG5mWnff5Hcny/35+tbLre5wNt1f77MhZ+TubDMhQvbXFjG93MyvmV8F7bx/V82ZkB7\nYk6u5vqfC7P8+7qqZVzYv2w8Tw6sIGjvd2z7ajRVypSgZDFHLq2fS8Sxn5g+tDsAOxaNIeTgioyy\nBkolUz7oiu/GhYQe+ZHrfy5k7ID2dGr0DjEnV9OydmWdtqqXd+PPeSN5uHsZEcd+wn/LIuaN6IOt\n1Zv/uzNTE2NiTq5+4ev78UMy4utXLcfofu0oYmf9wnrnjejzwjpXTx32ug9N6MknMIoBP12kwpT9\nlJ+8n67Lz3I84FmO5c7eDqP3D+cpO2kfJSfspdGCYyw7eouUNI1OXFRCCjN2+lJ37lHcxu+h8vSD\nDPjpIt6BkS8V9zqNbVMBBwtjxm3yIVWtybkAue8HAM/7EQxYdYEKU/bj8sUeas4+zORt14iMT8mi\nZl369I8+7RgoFdx4HE2ffxxDjxXnuB6se77rv+oC9ecd5cbjaJp/fQLX8XtQa7QA+AZH8/4aD9yn\nHsDliz3UmXuEL3fdICbp+Ryo6/KzlJywl/jkzNf4Fuzzx3nMLi7cDQOg9w/nKT95v97lcpsLQJfv\nzlB1RuZ56i9n7uM8Zhfn74Rl2vdf5H0vhH5f76DM8BWUHr6CTrM3cezqgxzLnbkRSI/5Wyk59HtK\nfPAd9cevZckuD1JSda/xRsYlMe23k9Qcs4bi739HhRE/0O/rHVy5G/JSca/TF93r4WBtxpjVR3I9\nvnPbDwAetx7T9+vtlBm+gqKDl1Lj85+ZuPY4EXFJObajT//o046BUsGNwFB6Lnh+DF3nbuH6A92f\n8X2+2k7tsb9wIzCUJpPWU+z9Zc/H98NQBi3eRbmPV1JsyDJq/m8NM34/RUzC899ROs3eRIkPviM+\nKfPvPfM2n8Nh4GLO+z8CoMf8rZQevkLvcrnNBaDjlxup+OmPmepcfdgHh4GLOecflGmfeD1GtixH\nyJKueE5rneU9I5WLWbNjZEPuLuzIzfkd+OOjelQqZoWbvTlnJ7fk0bddmNShIgB/flyfe191yihr\noFQwvp07XtNbE7ioM57TWjOqZTnaVy1KyJKuNHd30mmraglr1g6tS8C89jz6tgveM9sws2tlbMyM\nX2sfZMXU2ICQJV1f+FrcN/N14oW9qhGypCtlHC2yrbtuaXs+bVEWJyuTHPPoWK0oO0c24vaCjjxc\n1JnzU1rx/cB3X1i/eDN8guMYtMGfigu8cF/gSfc1vpy4E5VjuXP3o+m7zo8K8z0pM9eDpst9+O50\ncOb5eWIasw4+oMFSb0rP8aDa15cYtMEfn+C4l4p7ncY0K4GDuRFf7L5LmlqbqzK57QcAr8BY3vst\nva/dZl+kzuIrTN13n8iEzHPPf9Onf/Rpx0ChwC8knn7/OIZev97A94nud1IDf/On4TJv/ELiabny\nKqXmeGScv2+ExPPhnzepvNCLkrMvUn/pFWYfekhs0vM5TI9fblBmrgfxKZnnNV8dC6T4zAtceBAD\nQN91frgv8NS7XG5zAei2xpcaiy5lqvNXj5BMdQohhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIcTb\nTJnfCQghhBBCCCGEEEII8V8Xd98H34XdMC1ahmpfHuXdry5iUbI6/ksHE3ntWLblYm974r94AIYW\nttSYd5raS69TotNoAnd8TeCWeTqxt34cQfilPZQdvpzay/2pOm0vSiMT/Bb1IenpPb3j/i0tLoIL\nQ4vn+Ep8cifbOqwq1AMg9NxmtJrMi2AYWTliVqIiCgPDjG3R/ue48VUvDEwtqDptH7WX+1F22DIi\nrhzgxqJeaFJ1F4TSqlO5s/pzirf/jJrfXqbKpB2kxobjt6gPaXERGXEKQ2M0yQk8+GMadjXaUrL/\nbBQKJXEPruK7oAtajYYqU3ZT+7sblBowh9AL2/D7tl9G3o71e6FJSSLS50im4wj33IXKwRWr8vUy\n7dOnXG5zEeJtExkVzaYdu+nRqV1+pyKEEEIIIYQQQgghxGvl6elJo0aNcHd35+rVq9y7d49atWrR\nsWNH9u3bl225s2fP0rZtW+zt7QkICCA0NJRp06Yxbdo0Jk6cqBPbr18/tmzZwoYNG4iMjMTDwwNT\nU1NatmzJrVu39I77t7CwMBQKRY6vgICAHPvD3NycZcuWcf36dRYtWpRjvD79cPz4cZo1a4aVlRUe\nHh5ERESwbt06duzYQfPmzUlKevFDQHLbP/q2k5qayuDBg5k4cSLBwcGcOXOGZ8+e0bJlS8LCnj/k\nRqVSER8fz6hRo+jatStLly5FqVRy6dIlGjRogEaj4fz584SHh/Pdd9/x22+/0aZNG9LS0r9rGDx4\nMImJiezZsyfTsW3cuJFSpUrRpEmTTPv0KZfbXN4WMr51yfiW8V2YyPjWJeNbxrcQhU1UfBLbzvnR\nua57fqci8pCcv3XJ+VvO34XJZf/7tBm1kPKuzlxYM4vrfy7knQol6TVpGYcuXsu23IXrt+k+fjF2\n1hZcXj+X+7uWMGFQJ+as2cmMVVt1Yt+fvYqdJy+xeuowAvd+x4kfpmKqMqLT2G+4E/RU77h/C4+O\nw6rZsBxftwJzflCvuamKr0b148a9RyzbmPnhyq/SD6euBNBh9NdYmZty4oepBO75jlWTh7LnjDcd\n//cNSSmZHyD7T7ntH33bSUtT8/H8NfxvQDtubf2GQ8snEhoVS+ex3xAe/fzhfypjIxKSkhm/7A86\nNqzBwlH9UCoUeN98QOvPFqDRajm6YjIPdy9j0ecD2Hj4Al2/WEzaXw8q7t+2AYnJKRw4fzXTsW09\n7olbUQcaViufaZ8+5XKby9tC7s9PJ/fny/35r0rmwrpkLixz4cJExrcuGd8yvoUobKJiE9h6zIOu\nTd7N71REHvIOjKTzd2co52TB8fHN8ZzeiuouNrz300WO+mV//cjjXjj9fjyPrZkxZye3xG9ue8a0\nqcDC/f7M2XNDJ/bj9ZfY4xPMivfe5daCjhz4XxNMjZT0kBhuGQAAIABJREFUWnmeu6Fxesf9W0R8\nCs5jduX4uvMs+zr+ZmZswNweVfF/EsPKE9n/bvwy/XD2dhg9vj+LhYkR+8c0IWBee5YPeJcD15/Q\nY8U5ktNefJ0lt/2jbzupai2jfr/CyJbl8PmyLbtHNSIsLpleK88REZ+SEWdsqCQhRc2UbddpV9WZ\nOd2rolQouBoURadlZ9BoYd/oxgTMa8+87lXZcimIvj9cIE2jBaBPbReSUtUcvpH5muJO72Bc7c2o\nV9oh0z59yuU2l7fFlbshdPxyE+WK2XFq4WAuLxlKjVJF6L9oB0e8s79+dPFmML2/2o6dpQkXv3mf\nWz+OYFy3uszfco4vN57RiR3+/T52edzix087cO/nTzk8ewAmxoZ0n7+Fu08i9Y77t/DYRBwGLs7x\ndftxRLZ1/M1cZcT8Qc3xCwrj+71eOcbr0w9nbgTSde5mLE2NOTx7AHd++owVI9qx79Idus3dTHLq\ni+eOue0ffdtJVWv49IeDfN65Dr4rPmLfjL6ExSTQff5WwmMTM+KMDQ1ISE5l4trjtK9ZhvmDmqNU\nKPC595R2s/5Eo9VyYFZ/bq/6lAVDmrP5rD+9Fm7LuD7ct3ElklLSOHTlbqZj234hADdHa+q7l8i0\nT59yuc1FiLdddEIqO64E07FasfxORbwkn+A4uq3xpYyDKUc/rcbF/71L9eIWDN7gz7Fb2Z8zPQNj\nGbDeH1szQ06PqsH1CbUZ3bQEXx8PZN6RQJ3YEVtusedGOMt7lsV/cm32Dq+KiaGSPmv9uBeepHfc\nv0UkpFF85oUcX3fCErOt429mRkpmty9FwNMEVp57nGO8Pv1w7n40vX69gYWJAfs+qorfpNos61GW\nA/4R9Fp7I8f5eW77R992UjVaPt9+h88aF+fyuJrs+LAK4fGp9FnnR0TC83O9sYGChFQN0/Y/oK27\nHbPblUyfnz+Oo8tqXzRaLbuHVeHGpNrM6VCKbVdD6bfeL2NO3Ku6I0mpGo7czPy52nU9HFdbFfXc\nrDLt06dcbnMRQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIkXvK/E5ACCGEEEIIIYQQQoj/uodb\n5mJsU5SSfWagsiuOobkNJfvOQGVblKcn1mZbLsL7EEojFW59pmNsUwSlygyHej2wKl+PZ+c2ZcRp\nUpOJ9j+LTdUWWJapidJIhcrBlbIfLkZhZEyU70m94rJiaGFH/TXBOb5Mi5bNtg7LcnVw6zODsIvb\n8Z7UkAebZhF+eR8pUdkvQhi4dR6G5taUHboMkyKlMVCZY1WhPq69ppDwKIBwz1068ZqUJIq1G4F1\npcYYmFhg7lYN1x6TSEuIJvT88wdPKBQKUmMjsK3RFpfuEyjSbBAoFDzc9CWG5jaU//QnTJ3LYKAy\nx7Z6K1x7Tibuvg/hXukLzNrX7ozSSEW4126d9mPvXSEp9CFODXuDQpHpePQpl9tchHjb2NpYc9/n\nPGVLl8zvVIQQQgghhBBCCCGEeK0mTJhA8eLF+eabb3B1dcXOzo5vv/2WEiVKsHLlymzL7dq1CxMT\nExYtWkSxYsUwNzdn4MCBNG3alLVr12bEJSUlcezYMdq3b0/9+vUxMTGhVKlS/Prrr6hUKg4dOqRX\nXFYcHBzQarU5vtzd3XPsD61WS58+fejYsSNz5szhzp0XP+Qnt/0AMHHiRGxtbVm3bh3ly5fHwsKC\nZs2asXDhQq5fv87GjRuzbUef/tG3ncTERMaPH0+rVq2wtLSkZs2azJ8/n8jISNavX58Rp1AoCA0N\npWvXrsyZM4dPPvkEhULB2LFjsbOzY8uWLVSoUAELCws6derEggUL8PT0ZPPmzQD07t0bExMTNm3a\npNP+xYsXuXfvHkOGDEGRxfce+pTLbS5vCxnfumR8y/guTGR865LxLeNbiMLGxtwE3x9HUaaoXX6n\nIvKQnL91yflbzt+FyfQft1LUwYZ5I/pQoogdtlbmzP+0D8Ucbfl554lsy+0764PK2Ii5n/SmqIMN\nZiYq+rSuR6Pq5fn9wLmMuKSUVE5d8ad13SrUqVwGE2Mj3Io68MPED1AZGXHMy1evuKzYW1sQc3J1\njq/yrs459odWq6VH89q0rVeNr9fv5V7wsxfG57YfAGas2oqNpTk/Tv6Qsi5FMDdV0bhGBb78qCc3\n7j1i23HPbNvRp3/0bScxOYXR/drRvGYlLMxMqFHejZnDexAVm8Cfh85nxCmAsKhYOjZ8h2lDuzG0\nSzMUCgWTV2zC1tKc9V+OoJyLM+amKtrVr8as4T257H+fHSfSH1TcvVktTIyNMrXv5XePB49DGdC2\nQZbjW59yuc3lbSH356eT+/Pl/vxXJXNhXTIXlrlwYSLjW5eMbxnfQhQ2NpZm+G9ZRJkSRfI7FZGH\nZu/2o6iNCTO7Vqa4rSk2ZsbM6lqZojYm/Hr2frblDvmGoDIyYGaXyjhbm2BmbEDPmiWoX8aBTZ5B\nGXHJaRrO3AqjRcUi1Cpph8pQiau9GUv7v4uxoZKTAc/0isuKnbkxIUu65vgq62SRY39ogS41itOq\nUhEWH7rJ/bD4F8bnth8A5uy5gbWZMcsHvksZRwvMVYY0KOvA1E6V8H8Sw84rj7JtR5/+0bedpFQ1\nnzYvS5PyjlioDKnmYsOUjpWITkhls9fzY1AA4XHJtKvqzMT2FRnSoCQKBczY6YutmRGr369NGaf0\n9lpXdmZqp0p4B0ay2ycYgM41iqEyVLLLO1in/csPI3kYHk+f2q5Z/QquV7nc5vK2mPXnaYraWvDl\nwCaUsLfE1sKE2e81pZidBWuOXs223IHLd1EZGTBrQFOcbS0wUxnRq2FFGri78OfpGxlxyalpnPYN\npFWNUtQuVxSVkSFujtYs/7gtKkMDjl97oFdcVuwtTQn7fWyOr3LFcv4eVQt0q1ee1u+U5psdHtx/\nGvXC+Nz2A8CXG89gba5ixSftKFPUFnMTIxpWdGFGv0b4BYWx/cLNbNvRp3/0bScpJY2RHWvRtIor\nFibGVC9VhGl9GxEVn8SmM34ZcQoFhMcm0qFWWSb3bsj7LauhUMC0DSexNTfh1887U/av9tq8U5rp\n/Rpx5W4IuzxuAdC1bnlURobsuKjb/qU7T3j4LJq+TSplOb71KZfbXIR421mbGeE9sw2lHc3zOxXx\nkuYefkhRK2NmtC1JcWsVNqaGzGhbkqJWKtZ6Zv89zKGACFSGSqa3caOIpTFmxkp6VHOgnpsVm3ye\nzxWT0zScvRdNi3I21HSxTJ9X2qpY3L0sxoYKTt6J0isuK3ZmhgR/WT/HV1kH0xz7Qwt0rmJPy/K2\nLD31iAcRSS+Mz20/AMw7HIi1qSHLupeltL0J5sYG1C9pxZTWrgQ8TWDX9fBs29Gnf/RtJylVw4iG\nxWhc2hoLlQHVipkzqZUr0YlpbPUJzYhTKBRExKfS1t2WCS1cGFS7CAoFfHnwITamhvzUpzxlHEwx\nNzagVXlbJrdyxSc4jj2+6e11rmyPylDJbl/d9q88iuVhZBK9azhlPT/Xo1xucxFCCCGEEEIIIYQQ\nQgghhBBCCCGEEEIIIYQQQgiRe8r8TkAIIYQQQgghhBBCiP8ydXI8MbcuYlm2Fij+cblNoeTdRZ64\nj/4t27JufaZTZ+UtVHbFdbabOLqiTowlLSEaAKWhEUZWDkRcOUjElQNo1WkAGJhaUnuZL84tP9Qr\n7nUq1vZj3l3kSbG2H5P07CH3N0zh8rh38Z7cgMBtC0iNfb44RFpCNHEPrmJVoT5KI5VOPdaVmgAQ\nHaD7MAkA26otdN5blq0FQOx9b53tWk0aDnW6ZLxXJ8YSc9sLa/eGKA2NdWJtqjQHIO5eeh0GppbY\n1mhD1PUTqBNjM+LCLu4AhQLHBr2yPP7cltMnFyH+i5JTUjByKo2RU2keBmW/MOabULlBK4ycSrP7\n4JF8zUMIIYQQQgghhBBCiH+Ki4vj9OnTNGjQAKXy+fcLSqWShw8fsm/fvmzLLlq0iNjYWFxdXXW2\nlypViujoaCIjIwEwNjbGycmJnTt3smPHDlJTUwGwsrIiLCyMUaNG6RX3pqxcuRIDAwM+/vjjF8bl\nth8iIyO5dOkSzZo1w8TERCe2VatWAJw4kf3DwXPbPy/bTvv27XXeN2jQAABPT90HRKelpdG3b9+M\n9zExMZw7d47mzZujUul+z9KuXTsAPDw8ALC2tqZLly4cPHiQmJiYjLg//vgDhULB4MGDszz23JbT\nJ5e3gYzv7Mn4lvH9XyfjO3syvmV8C1GQJKeqses9D7ve8wgMjc7XXOqM/hG73vPY7yUPxMsvcv7O\nnpy/5fz9XxefmMy5a7eoW6UsSuXzJ6MplQr8Nn3N1oWjsy07d0RvnhxYQYkiug+tdSvqQEx8IlGx\nCQAYGxriaGPF3rPe7DlzhdQ0NQCW5qY82L2Uj3u01CvuTVky5j2USiWjv13/wrjc9kNUbALeNx/Q\nuEYFTIyNdGKb1awEwGnv7B+wm9v+edl2WtetovO+buUyAFwO0H2IeppaQ48WtTPex8YnctH3Do3f\nqYDKyFAntlWd9Dq9/O8BYGVuSoeGNTjq6UtsfGJG3OajHigUCga0bZDlsee2nD65vA3k/nxdcn++\n3J//smQunD2ZC8tc+L9Oxnf2ZHzL+BaiIElOTcOq2TCsmg0jMCQsX3OpOWgaVs2Gse+cT77m8TaL\nT07j4r0wape0Q6n4x7UshYLLM9rw+0f1si07o0tl7i7sSHFbU53trnZmxCSlEp2Qfn4xMlDgYGHM\ngetP2H/9CalqDQCWJob4z23P0Mal9Yp7U77qVR0DpYLxm1/8+cxtP0QnpHI1KIoGZe1RGeous9mk\nvCMA5+5kPyZz2z8v207LikV03tcuaQuAd2CkzvY0jZZuNZ5f34hNSsPrfgQNyzli/K/2mrs7AXDl\nYXodViZGtK1SlOMBz4hNSsuI2375EQoF9KnlkuWx57acPrm8DeKTUrkQ8Ija5YtlGt8+3w1n4/ju\n2Zb9ckATHq4ZRQl7S53tbk5WxCQkExWfBICRoQEO1mbsv3SHfZfuPP9cmhpza9WnDG/7jl5xb8qi\nD1pioFQwds3RF8blth+i4pPwufeURhVdMl1HbVrFDYCzfkHZtpPb/nnZdlrWKKXzvk65YgB43w3R\n2Z6m1tCtXvmM97GJKXjeekyjyi4YGxno1lmtJACX7zwBwMpMRfuapTl27QGxiSkZcdvOB6BQQN/G\nlbI89tyW0ycXIQqqlDQNzmN24TxmF0ERCfmdTq41XHAM5zG7OOgbknOweGXxKWouPoyhlosl//iq\nGaUCPMe+y2/vuWdbdnobN25NrUNxa93rGK62JsQmqYlOTJ9HGRkocTA34qB/BAf8I0hTawGwVBng\nO7E2H9Z11ivuTVnQqRQGSpiw+8XfTea2H6IT07j6OI76Ja0yz5tLWwNw7kH293fltn9etp0W5Wx1\n3tdySZ+PeAfH6mxP02jpUsUh431sshqvwBgalrLOPCcuZ/NXHXHpuZoY0MbdlhN3oohNVmfE7bgW\nhkIBvao7ZnnsuS2nTy5CCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghcs8w5xAhhBBCCCGEEEII\nId4eir8X2dJq4R8LbmUnNToUtFqMLO31bkuTmszTE+sIv7yPpNBA0uIjQaNBq/lrAYa//6tQ4v75\nWm7/NJKbK4ahNDbFskxNbKo2x6lRPwzNbfSLe82MrBxxbvlhxuL2Sc8eEnn1MMH7V/Ds3GaqTN6J\niaMbKZHpCz0Z2xTJVIexVfoCGCmRugvVKAyNMLTQXUjDyCL9IRRp/1jIPj1YgZG1U8bblKinoNUQ\nemEboRe2ZZl7csTjjP93bNCbcK89RHgfwrFBL7QaNeFee7AqXw+Vg2uW5XNbTt9cXg/t88+7EHlo\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O9pnjOzZJUT93YxLZfvIKbzSswKjOjSjlVhwbjUXmMdrInI/zqVTQsEJJPuvWmL+mvMm2\nib1ISElj5trDTxT3qKiEFFzempPv4/KdaEXv00yt4utBrxKfrGXMb3uxMDO+/K2SOpR0skelymzz\nuHuxmdtKOtvnm1N+9XmSftLSdcQnG+8XohMy/3+G1UJcAAAgAElEQVQqUcwmz3wefody+9wfZ26m\npot/RfadCScuWcvawyHYWlnQoX75f91OaS5qtRp9TuM7Ttl4eCgiNuk/Oz/v9cNhyozeXNRpPJNW\nHb9J2U+38NHvwVlrSWbvCGXVcdOPhRSVZ/Vz7fZdIH6fbS3qNJ4p7u7u3EnIMDne08EStQruJ6Tn\nH/yIewlp7AyNoUNVF4Y398LXyQobS3XmvDQ2598PVCqo72PPqJe92TK4GhsHVSVRq2POvltPFPeo\n6OQMSk44nO8jLDLn3x1yY6ZW8VWHsiRodUzYHo652nh+rqQOJR00mfPmHGp9PzFzm2exvOfCkH99\nnqSftAw9CanGx5mikzNjS9gZH1N8nMff36HcPvfHmatVvFHNhf1XYolPzWD92UhsLc1oV9n5X7dT\nmouZKpf5eZKy8fDQ3cSM/+z+WwghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIfKizj9ECCGEEEII\nIYQQQogXR6VKlTA3tyDphmk3IVKZmWNfri5xIYfQpxtfFOH0hJacnZrzhckNGZmx5nZORttTIi4T\nH3okM8aQeeGE+NDDBI2oQ9LNC0ax9mXrYFHclfTEGEVxOTG3c6LR4tv5Pqw9yuVcB3MLok5s5sba\nL9FG5nzRnZgzuzDoM7D29APAzNoe+7J1iAsNRJ9mfMG22HP7AChepXm214k9v9/oecLlY5nvs1zd\nXN8fgJnGFge/BsSHBmZdzP6h+EtHOfV5cxLDTxttL+HfFYMug5jTO4k+uR2nuu1Qa/K+4JYp7ZTm\nYuHgQkZSbLbvWNzFg/nmkhO9NpmEO1eoVq3aE7UXBeubH5Zg4VqG0jX9SUjM+WJnCxcvxcK1DOdD\nLmVt0+l0TJv9LacCdlC2lA89336fB1HRbNj2Fw1q1yys9IUQQgghhBBCCCGEeCFVqlQJCwsLTp48\naVK8hYUF/v7+7Nmzh9RU42Pk1atXp379+jm202ozjxO7uLgYbb948SL792ceP394fmH//v14eXlx\n+rTxse9GjRrh4eFBVFSUoricuLi4YDAY8n1UrFgxv5JkU6tWLT7++GNWrFhBQEDAE9ehWLFiNGrU\niH379pGSYnwh8x07dgDQunXrXPMwtT5P2s/OnTuNnh88mHns39/fP9ecAOzs7GjSpAn79u3j7l3j\nm4EHBARQuXJlTpw4YbS9b9++pKens2nTJtavX0/Xrl2xtbXNsx9T2inNxc3Njejo6Gzf/d27d+eb\nS06Cg4ML9JyHjG8Z3zK+ZXw/JOM7fzK+ZXybqqDHt3hy3205hlO3aVQd8i2JKWk5xvy0/QRO3aZx\n8caDrG06vYFZaw4SOGcwpdwdGTD7TyLjk9l67BJ1y+d9U0khlJD9t+y/Zf/9/O6/M8e3OacvXTcp\n3sLcjAZVyrE/OITUNOObkjUaOJHmQ6bm2C4tPfMmgE7F7Iy2h16P4ODpUOCf7/XB06FU7DqSs1eM\n18XWr1IWd+fiRMcnKYrLiXMxO+L3Lcr34eej/OZpNcr78F63V1i96yiBZy4Z/UxJHRxsralfpQwB\np0JJ0RrPD3YfOwdAy3pVc83D1Po8aT+7j583en747GUAGlTJec3zQ7bWGvyr+XHwVCj3ouOMfhZ4\n5jL1+o0jODTcaPubrRqRnqFjW+BpNh8M5o1mdbGxyv/mhPm1U5qLq6MDMQlJ2b77+05ezDeXnJwJ\nu0m1GjWeqK0pZH2+rM9/lKzPf3LVq1cnNDSU5ORkk+JlLpw/mQvLXNgUSUlJhIaGyvj+m4zvf8j4\nlvEtCtbCNX/h0HwQlbqNJDE5NceYH9ftwaH5IC5cu521TafX8+XSTRz7ZTKlS5ag74TviIxNYMvB\nYOpWLlNY6YsXQPXq1Qm7G0dKms6keAszNfVKO3Hw8gO0GXqjn7WYuZc2c/fn2C7t71gnO0uj7Zfv\nJXA4LBL4Z791+EoktSbu4Pwd42MLdUs54epgRUxyuqK4nDjZWnJ3bsd8H+Vc7XJ9jdxUK1mMwU3L\nsvbkLY5ejX7iOjhYWVC3lBOHwiJJTTf+fPaGZP6+2KKia655mFqfJ+1nf8gDo+dHr2W+13qlnbLF\nPspWY06DMs4EhkVxP8H4d9mjV6NoMmMPp2/GGm3vXs+HdJ2enefvsu1cBO1reGJjaZZnP6a0U5pL\nCXsNscnp2b77AZci883lcclpOsLuxhX4/DzsdiQpaRkmxVuYqanv50nA+Rto043bNP10Ka+OW5Fj\nO21G5vfG2d7aaPul29EEhtzKfJL5tSbw4i2qffAj528Yf3/qlffArbgtMYmpiuJy4mxvTeTy4fk+\nynvm/V3NSbVSrvyvTW3+DAzhcOhto58pqYODjYZ65T05dOEmqY99PnvOZJ5baFG9VK55mFqfJ+1n\n71nj8xtHLmW+1/p+eZ8vt7WyoGHFkhy6cJP7scbnE46E3sZ/1C+cunrPaHuPJpVJ1+nZcfIKW09c\noUN9P2w0Fnn2Y0o7pbm4FrMhJjE123f/wPkb+ebyuGRtOmG3I2V+/oz6cf8V3IdtoNaknSRqc/7/\ncUnANdyHbSAkIj5rm05vYM7OUPaPbkEpZ1ve+eU4UYlatp+NoI6vY2GlL14A1atX58q9BFLS9fkH\nA+ZmKup623PoWly2OUrLhadp92PO57S0GZk7JScbc6Ptlx+kcCQ887ufNT8Pj6fO7CAu3DX+/7SO\ntz2u9hb/zM9NjMuJk405tyc1yvdRzsU619fITVUPWwY19GDdmUiO3Uh44jrYW5lRx8uewPA4Uh/7\nfPaFZc4Zm5crnmseptbnSfvZf8V4Dv3wvdb1ts81JwBbSzMa+DoQGB7P/UTjz+jo9Xiazz/F6TuJ\nRtu71ixBhs7AztAYtodE066KEzaW+d8aIL92SnNxsbMgNiUj23f/4FXj34FMkZym58q9BNl/CyGE\nEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghnkv5r/gWQgghhBBCCCGEEOIFotFoaNjIn7i/L3ZuCt+u\nY9CnpxL201DS4x+QkRzPjXVfknwrBLfmfXLux9kLqxK+RAdvI/l2CPp0LTFn9hC6YBDO9doDkHjt\nNAa9DrvSNVGpzbmy+CMSrwajT9eSkRRLxM4fSYu+g1uTXgAmxxWUMn1nYmZpzfmvuhN5dB0ZSbEY\ndBmkxURwd++vhC36EI1TSbzaf/xP7bp9ji41kbCfh6GNvIFOm0TchQBurJuJfbl6ONVtmxVr0OtQ\nW2i4vXU+8aGH0WmTSLx2ivCVk7Eo5kqJRl3yzdG361hUajMuzutHSkQY+nQt8aGHCVv8EWoLS2xK\nGl8g2Na3GjaeFbi1cQ4ZyXG4Nu5uUi1Maackl+LVXgaDnlsb56BLSSA97j7hKyeRkZKQ7XVNEXfx\nIAa9jubNmz9Re1E4bt25y+fTvjI5/sq161SuUB5fr5KMGf4BLZs1xq9uUxrWrYVfOblY7ZPa8ecy\nIsNO5x8ohBBCCCGEEEIIIV5oGo0Gf39/tm/fbnKbGTNmkJqaSu/evbl37x6xsbF8/vnnnD17liFD\nhuTYxtfXlzJlyrBu3TrOnTtHamoqW7dupXPnznTr1g2A48ePo9PpqFevHubm5vTr14+jR4+SmppK\ndHQ0c+bM4ebNm7z99tsAJscVhUmTJlGqVCmWL19utF1JHQBmzpxJQkICAwYM4Nq1ayQmJrJr1y4+\n//xzGjduTJcuuZ9jUFIfJf3odDqsrKyYMWMG+/fvJzExkWPHjvHJJ5/g7u5O7969863Pl19+iZmZ\nGe3btyckJITU1FT27dtH37590Wg0VK1qfHPs2rVrU6VKFSZNmkRMTAz9+/fPtw9T2ynJ5bXXXkOv\n1zNp0iTi4uK4e/cun3zyCXFxyi8grtVq2bNnDy+//LLitqaS8V0wZHznTca3jG8Z3zK+H5LxLYrK\nnah4pqzYa3L8tbvRVPB2wbtEMUZ0eYlm1UtT6/0F1PMrSTlP5wLM9Pm2bvxbhP86oqjTeKbI/rtg\nyP47b7L/LsT5eaNG/HXsvMltJv2vC9q0dN6Zuoj7MfHEJSYzZfE6zl+9xdsdmufYxtvNmVKeJdgc\nEMyFa7dJTUtn55GzvDVuAW80rwvAyZBwdHo9dSqUxsxMzZDpSzhx8SqpaenExCcxf9VObt2Ppm+7\nlwBMjisKYwd0xMfdhVW7jhptV1IHgClDupGYksp7X/7M9YhIklK07A26wJTF62lYtRwdm9XJNQcl\n9VHSj15vwMrSgjkrtnHwdChJKVqCLl5jzMJVuDkVo2erhvnWZ/KQLpip1XT79Bsu3bhLalo6AadC\nGTx9MRoLcyqVLmkUX8PPl0qlPPnil43EJiTz1mv++X8IJrZTksurDaqh1xuY8ctG4pNSuBcdx5iF\nq4hPSjEpn0dp0zM4EBzCyy+3VNzWVLI+/8nJ+nxl7Z739fnNmjVDp9Oxa9cuk9vIXDh/MhfOm8yF\nYffu3eh0Mr5lfMv4lvEtisrtBzFM/GmtyfFXb9+nYilPvN2cGdWnPS3qVqZar0+pX6Us5b3dCzDT\n59vGOZ9wa8u3RZ3GM6VZs2bo9HoOXHpgcpux7SuTmq7n/WVBPEjQEpeSzoytF7kYEU8//9I5tvFy\nssbX2ZZtZyIIiYhHm6Fn98V7DFhyjNdrZh4rOHUzFp3eQE1vR8zUaj5cHszJ6zFoM/TEJqfx/b4r\n3IlN4c0GPgAmxxWFka9VxNvJhj+DbhptV1IHgHGvVyExNYOPfg/mRlQySdoMDlx6wIytF6lf2ol2\nNTxzzUFJfZT0o9Mb0Jir+Wb3JQ5fiSRJm0HwjRgmbjiHq72GLnW98q3PuNcro1ZB75+OEHY/EW2G\nnsCwSD5YfhKNuZqKHg5G8dW8ilHB3Z7ZO0KJS06nZ33v/D8EE9spyaVlJTf0BgOztocQn5rO/QQt\nEzecIz413aR8HhVw6QE6vb7g5+d6A/vPXTe5zbieTdCm6xiycBsP4pKJS9YyffUhLtyMpP8r1XNs\n4+3igK9rMbYcD+PirUi06RnsOnWNfl9vpEMDPwCCr95FpzdQq6w75mZq3vtuO0FhEWjTM4hJTGXh\n1iBuRyXwVvPM+ZKpcUXh067++JRwYM2hi0bbldQBYEKvpiSmpjP0hx1cfxBHUmo6+8/dYPrqQzTw\n8+T1euVzzUFJfZT0o9Pr0ViYM2/jMQIv3iIpNZ2TV+4yftl+XIvb0q1xpXzrM6FnE9RqNb1mrefy\nnWi06RkcuniT977bhqW5GZW8jc+5Vy/lSkUvZ2auPUJsUiq9mlbJ/0MwsZ2SXFrWKI3eYGDm2iPE\nJ2u5H5vE+OX7iU9OMymfRx04fwOd3iDz82dcRGwK07dcMDk+PDIJPzd7vBxtGNbKj6Z+rtSfuos6\npZwo62pXgJk+31a/68+lL9rmH/gCadasGTqDgYCrph8fGPOqL6kZeob+GcaDxHTiUzP4cvcNQu4l\n06euW45tvIpr8HW0YtvFaELuJ6PN0LPncgyD/gilfZXM/x9P30nMnJ+XtMNcreKjdVcIvpU5X4pN\nyeDHwAjuxKXRq3ZmH6bGFYURLbzxLq5h7Rnj33uU1AHg81a+JGp1DFsfxo0YLUlpOgKuxjFz9w3q\n+djTtrJTrjkoqY+Sfh7Oz+cH3OZweDxJaTpO3U5k8o5wXO0s6FK9RL71GfuqL2YqFf2WXyQsMgVt\nhp7D4fF8tDYMSzM1FV1tjOKredhSwdWGOftuEZeSQfearvl/CCa2U5LLy+WLozfAnH23SEjVcT8x\nnUk7wklIzTApn0cdvBaHziD7byGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghxPNJXdQJCCGEEEII\nIYQQQgjxrOnapROxwdvRpSaaFG9frh5VRq4mIzmW4DFNODmyHnEXAvB790dcX+qZcyOVGr/3F2Hl\nWppz0zoQNLwmd/f8jN+Q7/HuNAprj3KEfjuAmxtmoba0puqn67D1rU7od4M59kEFgsc0IerkNvyG\nfE+Jvy9kbmpcQbH1rky18dtwqtmK25u/JWhEXY78rzSnxrXgwaFVeLw6mOqTdmHp+M9FM+3L1aPK\n6LXokuI4PbEVx4dW5upvo3H170bl4StQqc2zYg0ZaZjbO1O2/2xubZpL0LBanJ/ZBStXXyqP+AMz\na/t8c7QrU4uqn21A4+TBuS86cuw9Py7/NBTnOm2pPGIVagtNtjYu/l1IvX8djYsPDn753xjC1HZK\ncinh3xWvDsOIPLaBEx9X5+z0jljYO+PTeTQA+nStyXkBRB75kwYN/XFzK7qLvoj8dW7fhu9/Xsax\nk6dMivcrV4Z1v/2U9fy9t/sSc+0c3345uaBSFEIIIYQQQgghhBBCPKJTp06sX7+ehATTbhTauHFj\n9uzZQ0xMDH5+fvj4+LBr1y5Wr17NwIEDc2yjVqtZu3Yt5cqVo1GjRnh4eDB//nxWrlzJ1KlTqVix\nIh07dmTChAnY2NgQEBBAnTp16NatG8WKFaNChQqsW7eOlStXZt1kzdS4omBra8vChQsxGAxG25XU\nATJrvX//fmJiYqhVqxZOTk4MGTKEfv36sWPHDszNzXPqHlBWHyX9aLVaSpQoweLFi5k8eTIeHh40\nb96csmXLsmvXLooVK5ZvfRo0aMChQ4fw8vKicePG2Nvb06dPH7p06cLu3buxsrLK1qZPnz5cuXKF\n0qVL07Rp03z7MLWdklz69u3L+PHj+eOPP3Bzc8Pf358SJUowbdq0rNqYasOGDSQnJ9OhQweT2zwJ\nGd9Pn4zvvMn4lvEt41vG96NkfIui8HrDiizeEUTQ5dsmxZfzdGbF6H/WJr3Tpi43fxvJV4PaFFSK\n4gUm+++nT/bfeZP9dyHOzzt3YcuhYBKTU02Kb1i1HJvnjiA2MYlavcdSqfso9p64yNJJ79Kn7Us5\ntlGrVSyf8h5lSrrS8r3plO/8CT+s28MvE4Yw/u1O+Pm403Pst0z/eQPWVpbs+HY0NSv40nfC93i1\nG0rtPmPZFBDMLxP+x1ttGgOYHFcUbKw0zB32Vg7j2/Q6QGatt80bRUxCMo0HTcLn9Q/5ePZvvNnG\nn/WzhmFulvslC5TUR0k/2vR0XIrbs2BUf778dRPlOg+n7cdfUcbTlY1zPsHB1jrf+tStVIa/5n9K\nyRKOvPrBF3i+9j6Dpy2iY7PabJozAitLi2xterZqxLU7D/D1cKFxdb98+zC1nZJcerVuxKf9XmfN\nnuOUfWMYr7z/BS7F7Rk/qBMAaemm36hvy8FgklPTCnx8y/r8JyPr85W1e97X57u7u9OoUSOWLVtm\nchuZC+dP5sJ5k7kw/Pbbb/j7y/iW8S3jG2R8i6LRsWkdFm3Yy4mLV02KL+/tzsrpQ7OeD+70MhHb\nFjD747cKKkXxgnJ3d6dRgwb8edK08ygA9Us78ef7jYlNTsN/+i7qTNrJgUsPWNS/Hr0a+OTYRq1S\nsWRgPUq52NFuXgDVx29nccA1fuxXj0/bVqScqx39Fh3lq+0hWFuasfHDl6juXYxBvxyn3Kdb8J++\nm21nI/ixX1161M/sw9S4omBjacaXXavz2O5bUR0gs9brh75EXHI6r8zaR8Wx2xi1+jTd6/vwxxB/\nzNWqXHNQUh8l/Wgz9DjbaZjbsxazd4RSfcIOOs0/RClnW1a/1xgHq+zHoR5X29eRzR81xbOYFe3n\nBVB29GbeX36S9tU9WfOePxrz7MfoutX1JjwyCR9nGxqWccm3D1PbKcmlW11vPmldgfXBt6k6bjvt\n5x3A2U7DZ20rZdXGVGuCbuPfsGHBz88b1Gf1oRCT2zTw82Td2G7EJmmp/8kSagz9if3nbrDko/a8\n1axqjm3UKhVLh3WgtHtx2kz4ncrv/cCinadYNLQdY7s1prynE73nbODLPwOxtjRn8/ge1CztxsBv\nNlN60AIajviZrSfCWDS0Pb2aVgEwOa4o2GgsmDmgZY7j29Q6QGatN47rTmxSKi3GLKPc4AV8smQX\nPZtUZvWnXfI+Vq2gPkr60abrcHGw5pvBrflq3REqv/89HaauopRbMdZ+1hUHm+zHxx5Xp5wH2yb2\nxNPJjraT/sD37fm8u3A77euVZ92Ybmgssv/e0f2lyoTfi8W3RDEaVfTKtw9T2ynJpUeTyozs3JB1\nh0Oo+N73vDbxD5ztrRnbvXFWbUy16mAI/g0byPz8Gde+hie/HAzn5PUYk+LLutqxdFCDrOcDm5Tm\nyox2zOhavaBSFC+oh/vvtWeiTG5Tz8ee1f2rEJuSQZNvgqk35yQBV+P4sYcfPWu75thGrYJFPf0o\n7WRFh5/OUfOrIH4+epfvu/sxqqU35VysGbAilFl7b2JtoWbdwKpU97Rl8KpQKkw/RpNvgtl2MYrv\nu/nRvVYJAJPjioKNpZrp7cvksP82vQ6QWeu1A6sQl6Kj1fenqTzjOKM3XaVbTVdW9Kmc9/xcQX2U\n9JOmM+Bsa87sN8oyd98tan0VRJefz+PraMUf/Spjb2WWb31qedmxYVBVPBw0dFx0Dr9pxxj652Xa\nVnZmVf/KOc7Pu9Rw4Xp0Kj6OGhr6OuTbh6ntlOTStUYJhjX3YsPZSKp/dYKOi87ibGPB6Fcyf9dR\nMj//83Sk7L+FEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBDPLZXh8StWCCGEEEIIIYQQQgjxgouJ\nicGzpBdu7Yfj2ebdok5HiKcq9d41zoxvwS8/L6F3794F1k/37t0xaJP4fdF8Re1OBJ9h0syvOXLi\nJAaDgaqVKvDZsPdp/XKzrJh2Pfpz6OgJYsPPZW3bG3CYGV8v4HjwaTIydPh4l6R3t04Me28QGkvL\nrLjomFimzZnPpu27iLh7D3s7W+rUrM74kR9Rr3YNxXEF4ZsflvDJuKmc3LeVtt374eLsxLFdm7B4\n5OJoCxcv5aPPJnLqwHaqVPznpiCm1gEg8FgQ0+fM52hQMEnJyXi4udKuVUsmjP4YZ0fHPHNUUh9T\n+2nXoz9HTpxk78aVjJownWMnT5GRoaN+nZrMmjyWmtWqGMVeCb/OqiUL6ffecC5fuUbc9fOYmZlx\n+twFJs+cx8Gjx0lMSsLT3Z1O7VszdvhQijlk3pSiRYceBJ06y52LJ7CztTHKd9z0Wcz4eiG71/9O\nU/8GtO7Sm6DTZ4kMO62oHWBSLgDN2nfjyrXr3Dp/zOg1H37Ou9atoFlj02920WvQB6g0tqxatcrk\nNkIIIYQQQgghhBDi34uJicHLy4uJEycycuTIok5HiOeewWCgYcOGuLu7s2HDhgLtS8a3EIVLxrcQ\nz6/CGt+rVq2iR48eRK8eq6hdcNgdvlh1gOOXbmMwGKjs48onXRrTsmbZrJiu037nyMWb3Fo2Kmvb\ngXPhzF17iKCwO2To9HiXKEaPptV4//WGaCz+uTFMTGIKs9YcZNuJS0REJ2JvbUnNsh582r0ptct5\nKo4rCN9tOcbYX/4iYNY7dJn6Oy4ONuyd+TYWj9zM7qftJxi9eAeHZg+mks8/N9QxtQ4AR0NuMevP\ng5y4fJvk1DTcHO1oU9ePT7s3xcneOs8cldTH1H66Tvud46G32TK5D+N+203Q5dtk6PTULV+Sqf1e\noXppd6PY8Lsx/PJJF4Z8u5ErEVHcWjYaM7WKs+H3+HLVAQ5fvElSahoeTva0b1CBkV2bZN3kr934\npQRfieDy4mHYWhmv5Zj6+z7mrD3Epkl9aFzZh06TlxN8JYLwX0coageYlAvAa+N+5WpEDKGLPjZ6\nzYef88aJvXmpim+en8mj1gdeZODctdlutP40yf5biMJV6PPzkiX5rF87PurZpkD7EkJkju+X359B\nybKV2bBxY4H2JevzxfOssNbnAyxbtoyBAwdy/vx5ypcvX6B9CSHg8uXLVKlShSVLZHwL8bwprPHd\nvXt3Mh5c49eJQxS1OxkSzrSfN3Ds/BUMBgNVyngxsk87XqlfNSum08i5HD4bxt3tC7K27T8Zwuxl\nWzgRcg2dTo+3mxM9WzViaI/WaB75u7SY+CS+XLqZrYGnuBsZi52NFbUqlGJM/w7UqVRacVxBWLjm\nLz6dv5LAxRPpNHIuLsXtOfDjOCzM/znW/OO6PYyYt4IjP0+icumSiusAcORcGDOXbub4haskp2px\ncy5GW/8ajBnQEScHuzxzVFIfU/vpNHIuxy5cZfs3o/h84WqOX7yKTqenbqXSTH+/BzXK+xjFXrvz\ngN8mv8vgaYsJu3mXuzsWYqZWcybsJl/8vIHAs5dJStHi4VKcDk1rM7rv6zjYZh4bb/PhlwSHXufq\n+rnYWmuM8p28aB2zlm1h67yRvFSjAh2Gz+ZkaDi3tnyrqB1gUi4ArT6YwdXb9wlbN8foNR9+zlu+\nHkmTmhXy/Ewe1W/i95iXKF2gf1+3bNkyBg7oz/5RLShTwrbA+hFCZLr6IIlmM/ey5OdfCmd+PqA/\nh77sSxn3vP/eWgjx7129G0Pj0UsLfHx3796d1MuH+KlfPUXtTt2IZeb2EILCozEYoJKnAx+96sfL\nFV2zYnr9cJijV6O4+mX7rG0HL0cyb9clgq/HkKE34OVoTbd63rzbvByW5v+swYhNTmPOzkvsOHeX\nu3Ep2FlZUMO7OCPbVKCWj6PiuILw4/4rjF9/jj0jW9Dz+0Cc7TTs/KSZ0VqSJQHXGLP2DPtGtaCi\nh4PiOgAcuxbN1ztDCboeQ3KaDlcHDa2quDOqTUUcbY3XSTxOSX1M7afXD4c5ER7N+qEvMWnDeU7+\n/R5q+zoy6Y2qVCtZzCg2PDKJRQPq8cGyk1x5kMi1L9tjplZx7nYcs7aHcORqNEnaDDyKW9GumifD\nWvvhYGUBQMdvD3L6Ziznp7TBVmP8e8sXWy4yb9cl1n3QmEZlXej2XSCnb8Ry6Yu2itoBJuUC0OGb\nAK5FJnF2svE524ef89r3G+NfziXPz+RR7/x6HKvyjQt+ft6/P3vfr05pZ6sC60cIkelaVCotFpxh\nyS8FPz8XQgghhBBCCCGEEEIIIYQQQgghhLi1vQUAACAASURBVBBCCCGEEEKIIrBanX+MEEIIIYQQ\nQgghhBAvFkdHR0aPGknE5q9Ji7tf1OkI8VTdWDmRcuXL07Nnz6JOJZvjJ0/T7PVuVChfhqC9W7l0\nfD91alanw5tvs/Wvvbm2O3T0BG179MXZyZFzgbuICDnBmGEfMP6L2Xw2+Uuj2LcGf8ifG7ey9Ls5\nPAg7ReCOdVhbaWjV5S0uX7mmOO5xkdExWLiWyfcRevlKvvWwtbFhzrTxnLsYyuwFP+Ybr6QOewMO\n0/KNnjjY2xG4fR33L51iybez2LB1J6+88SapWm2efZlaH6X9pKdn0P/9Txj54RCunznCvk2ruB8Z\nRasuvYmMjsmK02gsSU5O4aPPJtLhtVeZM20carWaoFNnadK2K3qDnoAta7gXGszX0yewfNU6Xuve\nl4wMHQB9uncmJTWVzTt2Z3tvK9dtppSPN00a1c/2MyXtTM1FCCGEEEIIIYQQQjw/HB0dGTlyJFOm\nTCEiIqKo0xHiuffrr78SFBTE5MmTC7wvGd9CFC4Z30I8vwpzfCt1MuwOr41bSvmSLgTMeofgBe9T\nq6wHPaavZOfJsFzbHQm5Sdepv+Nob82xeUMIWzKcEV1eYtof+5i0bI9R7Ntz17H+8EV++PANwn/9\nhL++GIC1pQUdJy3nSkS04rjHRSUk49RtWr6Py7ej8q2HjZUFMwa04sKN+3y74XC+8UrqcOBcOK9P\n/A17G0t2fTGAq798wsIPOrD5aCgdJi5Dm56RZ1+m1kdpP+k6He/O38jHHRtx4YeP2DqlLw/iknhj\n0nKiEpKz4jTm5iRp0xm9ZAdt6/kxvX8r1CoVwVciaD32F/QGAzum9ePKz8OZMbAVqw6co/OUFWTo\n9AD0bFad1LQMtp+4nO29rT10Hl/X4vhX8sn2MyXtTM3lv0r230IUrkKfn48axczftnA3Kq7A+xPi\nRbdiRyCnQsOZPGVKgfcl6/PF86ww1+f36tWLypUrM3z48ALvSwgBw4YNw8/PT8a3EM+hwhzfSgVd\nvEaroTPw83Hn8OKJnP19BrUqlKLrp/PYceRMru0On71Mp5FzcCpmR9DSqVzbMJdRfdozZfF6xv+w\nxii2/+QfWL/vBIvGDuLG5m/Y+91YrDUWtB8+i7Cb9xTHPS4qLhGH5oPyfVy6cTffethaa/hyaE/O\nX73FvD+25xuvpA77T4bQ9qOZONhas/e7sdzY9A0/fPY2mwKCaffxLFLT0vPsy9T6KO0nI0PH/6Yv\n5uM323BpzSx2fDuaB7EJvD58FlFxiVlxGksLklO1jJy3gnaNazJjaM/MY9Wh4bz6/hfoDQZ2LfiM\n6xvn8dWHb/LHzsN0HDEn6/hwr9b+pGjT2BZ4Ott7W7PnGL4eLjSu7pftZ0ramZrLf1WvXr2oXKki\nEzZeKOpUhHghTNhwnvLlyxXe/LxSJcYtDyjwvoQQ8PnyA/g9o9e/CL4Rw+vfBFDe1Y49I1twbNwr\n1PAuTu8fj7DrQu5z4qNXo+j5fSCONpYc/KwlF6a+xrBWFZix9SJTNp03iv3f0hNsOnWbBb1rc+mL\ndmz7uCnWFmq6LgzkyoNExXGPi05Kw33YhnwfYfdzf42HbCzNmNq5Ghcj4lm4N/e1NE9Sh4OXI+k8\n/yB2VhZsHdaUkGmv8e2btdl2NoLOCw6hzch77mhqfZT2k64zMHT5ST5oWZ5Tk1qzcehLRCZq6brw\nENFJaVlxluZqktN0jPnzLG2quTOlUzXUKhWnb8bSfl4AegNs+agJIdNeY1qnaqw+cZMe3x0mQ28A\noHs9b1LTdew8n/33pPXBt/FxtqFhGZdsP1PSztRc/qt69epFpcoVmbTzZlGnIsQLYeKOG4U2PxdC\nCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQoiioC7qBIQQQgghhBBCCCGEeBaNGjUKF2cnbq2dUdSp\nCPHUxJzZQ9TpXXy/cAHm5uZFnU42n06egae7OzMnjsHHyxMnx+J8NWkMXp7ufP/zb7m227jtL6w0\nGmZM+AxPdzdsbWx4s2tHmvo3YOkf/1ykNVWrZU9AIK1bNqNh3dpYaTSU8vFm0TdfobHUsHPvAUVx\nOXFxciT9/tV8HxXKl823HgaDgW4d29H21RZMm/0tV65dzzPe1DoAfDZlBo7FirFk/izKly2Nna0N\nzRo3ZNq4UZy7GMqqdZty7UdJfZT2k5KayicfDKZl08bY29lSu0ZVpo4dQUxsHMtWrs2KU6HiQVQU\nHdq8yqRPhzO431uoVCpGjJ+Kk2Nx/li8AL9yZbCztaFdq5eZ9vkojp88zeoNWwDo0qEtVhoNq9dv\nNur/aFAw167foG+PzqhUqmzvXUk7U3MRQgghhBBCCCGEEM+XUaNG4ejoyNixY4s6FSGea/Hx8YwZ\nM4b//e9/1KhRo1D6lPEtROGQ8S3E86soxrcSE37bjYeTPVP6tsTLxQFHO2um9HsFT2d7Fu8IyrXd\n1uOX0FiYM7nPK7g72mOjsaBbk6o0ruzLin3/3AhVm57BgbPhvFKrLPX8SqKxMMfXtTjz32+PxsKM\n3aeuKIrLibO9DdGrx+b7KF/SOd96GAzwhn8lWtUux1drDnL1bkye8abWAWDSsj0Ut7Xiuw86UNbD\nCVsrS16q4suE3i24cOM+fx7K/aapSuqjtJ/UtAyGdmhEs+qlsbO2pGYZD8a92YLYpFRW7j+bFadS\nQVR8Mm3rVWBMz2YMaFUblQo+//UvHO2s+Xl4F8p5OmNrZUnrOuUZ/2YLTobdYf3hiwB0bFQJjYU5\n6wKN+z9x6Tbh92Lp2bw6OSxZUNTO1Fz+y2T/LUThKLL5uZMzkxetK5T+hHhRJSSlMGnR+kIf37I+\nXzxvCnt9vpmZGV9//TWbN29m69atBd6fEC+yrVu3smXLFubPny/jW4jnTGGPb6XGfb8GD5fiTHu3\nO15uTjg62DL9ve54lnDkp/V7c2235eApNJYWTB3SDQ+X4thYaej+akNequHH8m2HsuJS09LZf/Ii\nrzaoSv0qZbGytMDXw4XvRg9AY2HB7uPnFMXlxLmYHfH7FuX78PNxz7ceBoOBzi3q0bphdWYu3czV\n2/fzjDe1DgDjf1hDcXtbvv9sIOW83bC11tCkZgUmDe7C+au3+HPPsVz7UVIfpf2kaNP4qGcbWtSp\njJ2NFTX9fJnwTmdiE5L5fUdgVpwKiIxNoF3jWnz+9hu83aE5KpWKzxasxNHelqWT3qW8tzu21hra\nNKrOxHe6EHTxGuv2HgegU/O6WFlaZOv/+IWrhN95wJut/XP8+zol7UzN5b/KzMyMr7+Zz1/n7rD7\nwr2iTkeI59ruC/f463wECxZ+X3jz82++ZcfJMHadulbg/QnxItt16ho7T15h/sLvnsn5+eSNF/Ao\nbsWEjlUo6WhNcRtLJnasgkdxK34+mPv/DzvO3UVjYcaEDlVwL2aFjaUZXep40aisCyuP3cyK02bo\nCbgUycuV3KhbygmNuRofZxu+7lUbS3M1+0LuK4rLiZOtJXfndsz3Uc7VLt96GIAONUvySmU35uwI\n5VpkUp7xptYBYMqm8xSzseTbt2pTtoQdthpz/Mu5MLZ9ZS5GxLP+5K1c+1FSH6X9pKbreK9FOZr6\nlcBOY0517+KMaVeZuOR0Vh3/5z2ogKhELW2quTP6tUr08y+FSgXj15/D0caCRf3rUdY1s79Xq7gz\ntn1lgm/EsPHUbQBer+mJxlzNhuDbRv0HXY/helQS3ev55LiWREk7U3P5rzIzM2PeN/P5KySSPZfz\nXuckhPh39lyOYVdoFAu+K5z5uRBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQhQFdVEnIIQQQggh\nhBBCCCHEs8jGxoZv583l/qFVPAhcXdTpCPGvaSNvEv7LMHr07EXz5s2LOp1sEpOSCTh8DP/6tVGr\n/zl0rVaruXLyIBtXLMm17ZcTPyPm2jl8vDyNtpfy8SIuPoGY2DgALC0scHVxZuPWnazfuoP09AwA\nHOztuBsaxPuD+imKKyzffjkFMzMz3h0xJs84U+sQExtH0KmzNGvcECuNxii2ZdPGAOw7eCTXfkyt\nz5P206ZlM6PnjerVAeB4sPHN4TIydHR7o33W8/iERAKPBdG8cUM0lpZGsa1ebgrAsZOnACjmYM/r\nbV5hx579xCckZsX9/udGVCoVfXp0zvG9m9pOSS5CCCGEEEIIIYQQ4vliY2PD3Llz+eWXX/j111+L\nOh0hnkt6vZ7evXuj1+uZPHlyofUr41uIgifjW4jnV1GNb1MlpaYRePEG9St4oX7kzklqlYoz3w1l\n5Wc9cm07uU9Lbv42Ei8XB6Ptvq7FiU/WEpuUCoCFuRkuxWzZeuwSm4+Fkq7TA2BvrSFsyXAGv1ZP\nUVxhmfXOa5ipVQz/Ie+bkJtah9ikVIKvRNC4ii8aC+MbwTSvVhqAg+fCc+3H1Po8aT+v1Cpr9Lx+\nBS8Agi7fMdqeodPTyb9S1vOEFC1HQ27RpKovGgszo9iWtcr8/RqZN81ysNHwWr3y7D51hYQUbVbc\nmoPnUamgZ7NqOb53U9spyeW/TPbfQhS8Ip2ffz2P5dsPsWJ7YP4NhBCK6fUGBk1fjEFtXujjW9bn\ni+dJUa3Pb968Ob169WLAgAGEh4cXWr9CvEjCw8MZMGAAvXrJ+BbieVNU49tUSSlaDp25RIOq5VCr\nHzlWrVZxYeVM1sz4KNe2U9/tRsS2BXi5ORlt9/VwIT4phdiEZAAszc0pUdyBzQeD2RRwkvQMHQD2\nttaEb/ya/3VuqSiusMwd1hu1Ws1Hs5fmGWdqHWITkgkODadJzQpYWVoYxTavUxmAA8GhufZjan2e\ntJ9XG1Q1et6gSuax66CQa0bbM3R6Or/8z3mDhKQUjpwLo0mtCtmOjb9SP/M1j1+8CoCDrTVtG9dk\n17FzJCSlZMWt2nUUlUrFm639c3zvprZTkst/WfPmzenVswcfrTzDzejkok5HiOfSzehkPlp5hl49\nexT+/LxnT4b+9Bc3HsQXWr9CvEhuPIhn6E9/0atnz2dzfq7N4MjVSOqVcsq2liRofCuWD26Ya9vx\nHapwZUY7SjpaG233cbIhPjWduOR0ACzMVLjYWbLtbARbz0b8swbCypyLU1/j7SZlFMUVli+71sBM\nrWLkqryvl2BqHeKS0zl9Mxb/cs5ozI0vk93UrwQAh8Iic+3H1Po8aT8tK7kZPa9XyhGA4BsxRtsz\n9AbeqFky63lCagbHr0XTuHwJLB/rr0VFVwBOXs98DQcrC1pX9WBPyH0SUjOy4tYG3UKlgu51vXN8\n76a2U5LLf9nD+fmwDeHcjNXm30AIodjNWC3DNoQX+vxcCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQ\nQgghCpt5/iFCCCGEEEIIIYQQQryYOnfuzKeffsrMr0Zi6VSSYhVzvnihEM86XWoiYfMHUM63JIt+\n+rFQ+lSpVOgNBpPj791/gMFgwMXZWXFfqVot3y9ZxtrN27h2/SbRsbHodHp0usyLqOr0mRdrUqvV\nrF+2iD7vfky3/u9iY21Nw7q1aN2yGf17dcPJsbiiuMLi4+XJpE+HM2L8VH79fQ39enXNMc7UOty5\new8AdzfXbK/hVsIFgNsRd3PNx9T6PEk/lpYWODs6Gm1zccp8/iAqymi7SqXCw61E1vOIu/fQ6/Us\nX7Oe5WvW55j7rdsRWf/u3b0zqzdsYcO2nfTp3hmdTseaDVto6t+AUj45XwzL1HZKc3naDAaD0UXl\nhBBCCCGEEEIIIUThenh+4Z133sHHx4cWLVoUdUpCPFdGjhzJX3/9xZ49e3B+gvMK/4aMbyEKloxv\nIZ5fhT2+VX+fLzUYwJRTp/dikzAYwMXBRnFf2vQMFu8IYuOREMLvxRKbmIJOr0enz1wzkbVmQaXi\n90+7M3jeevp+tQZrjQX1/UrSsmZZ3nq5Bo521oriCouXiwNjezZj7K+7WL73NG+1qJFjnKl1iIhK\nAMDd0S7ba5QobpsZE52Qaz6m1udJ+rE0N8PJ3ri+zvaZ34moeOMbuKpU4OZon/X8bnQieoOBVQfO\nserAuRxzvx35z00iezarzvrAi2w5domezaqh0xtYF3iBxpV98XXNfV2KKe2U5vK0GTBkjcGCJvtv\nIQrWszA/H/rVV3i5OdG0VsVC7V+I593n369m74mL7Nm7t8jGt6zPF/91RbE+/1GLFi2iefPmtG3b\nlsDAQIoXL9z17UI8zxISEujQoQOenp78+KOMbyGeJ0UxvlUqFQYlf18XHZf593XF7PMPfkxqWjqL\n1u9lw4Egwu9EEpOQlPl3ZX8fm/3n7+tUrPpiKG9P/Ym3xi3E2sqSBpXL8kqDqvR57SUcHWwVxRUW\nLzcnxr39Bp8tWMmybYfo/VrjHONMrcOdyBgA3JyLZXsNV0cHACIexOSaj6n1eZJ+LC3McXIwPrbt\nXCzzeWSs8XFtlUqF+yOvHREVh15vYOVfR1j515Ecc799/5/+erVuxNq9x9l8MJherf3R6fWs23uc\nl2r44evhkuv7N6Wd0lyeNoOh8I5VL1q8hOZNX+KtRcfZNNSfYtYWhdKvEC+CRG0GfZecoGSpMvz4\n06JC73/R4sU0b9qEnrM2sG1Cd4rZaAo9ByGeV4mpafSeu4mSPqX58aefCqXPzPm56fH3E7QYDOBs\np3zsazP0/HzwGlvO3OF6ZBIxyenoDYZ/1lD8nYhapeK3dxry3m9BDFxyDGtLM+qWcqJFRVfebOBD\ncRtLRXGFpaSjNaPbVmLC+nP8cewGPev75Bhnah0i4lIAcHOwyvYaJew1f8ek5pqPqfV5kn4szNQ4\n2hrX18k2MzYqUWu0XaUC10de+158KnqDgTUnbrLmxM0cc78Tk5L17+71vNl46jbbzkbQvZ43Or2B\njadu06isCz7Oua9pMqWd0lyetsw1XIU7P++z4jIbB1bEwUouvS7E05Ko1THgjzBKlipXJPNzIYQQ\nQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEKEzyFwlCCCGEEEIIIYQQQuRh6tSphIReYuv3gyn33mIc\n/BoUdUpCKJKRGMPlhQPRpMWydfNR7Oyy3+SqINjZ2XEn6r7J8WZmagC0Wm0+kdm9+c5QNu/YzbgR\nH/JWt064ubqgsdTw7ogx/LJitVFsnZrVOB+4i8BjQezce4Cdew8weuIXfDnvO3as+Y2a1aooiiss\nH7zTjxV/rmfUxOm0bfVyjhc6UlIHIMeLCT/clt+FlJTUR0k/KnLv9/GfqdVqzMzMssUN7N2DH+Z8\nkWf+AK1aNMXVxZk1G7bQp3tn9h48zL0HkUwfP/qptTM1l6ctITEJb1fPQu9XCCGEEEIIIYQQQvxj\n6tSpXLp0ia5du7J+/XqaNGlS1CkJ8Z9nMBiYNGkSc+fOZfny5TRq1KhI8pDxLcTTJ+NbiOdXUY3v\nh2sjUtLSsdHkf8NNM3Xm+Whtuk5xXwPnrGN70CVGdWtK96ZVcStuh6W5GcN+3MryPaeNYmuV9eDY\nvHc5GnqTPaeusvv0Vcb/tpu56wJZN/5Nqpd2VxRXWAa3rc/qgPOMX7qb1nXK53hmX0kdgBxvsJa1\nLZ81C0rqo6SfvLp9/GdqlSrre/OoPi1rMm9IuzzzB3i5RhlKFLNlfeAFejarRsC5cB7EJTGx98tP\nrZ2puTxtiSlp2NsV3o2gZf8txNP3TM3PQ0PpM/EHfp/yHv7VyxdJHkI8TwwGAzN+3cSC1X8V+fiW\n9fniv6yo1uc/ysbGhj///JMGDRrw+uuvs379epydnQs9DyGeN1FRUbzxxhtERkZy9KiMbyGeJ0U1\nvu3s7Lh1I93keDN15t/XpaWb3uah/pN+YFvgaT7t9zo9WzXCzckBSwsLPpq9lN+2HjSKrVWhFEFL\np3LkXBi7j51n1/FzfP7damYv38rG2Z9Qo7yPorjCMqRLS1b+dYSx362iTaPqkMPRaiV1gFyOIWPa\n39cpqY+SfvLqNdvf16lUWd+bR/Vr14RvR/bLM3+AlvWqUsLRnrV7T9CrtT8HToZwPyaeyf/r+tTa\nmZrL05aYkoavvX2h9GVjY8Of6zbQoF5d+i4+zi8D6uJoa1kofQvxPItJSqP/zyeIzbDg6OatRTc/\nX7eeBvXq8tbsjSwd9jpOdlaFnocQz5voxFT6zt1ETKqBowFbCnV+HpWew8QsF2Z/z9PSMvSK+xr8\n63F2nr/LJ60r0vVNL1wdrLA0VzNy1Sl+P3rDKLaGd3EOftaSY9ei2Bd6n70h95m88Tzf7LrM6vf8\nqVaymKK4wjKoSRn+DLrFxA3nebWyW45rLpTUAfJe45H37FxZfZT0k/dakpzm59kbvNXQl9k9aubz\nDqB5RVdc7DRsPHWb7vW8OXg5kgcJWsa9nve1TZS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318/uxZZs6cma/9FLQDBw7QvXt3PDw8MJlMlC9fnsDA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RSQ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\ntVg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0Gti+5wAdej2CxWoh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+ "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [], + "image/png": { + "width": 1900, + "unconfined": true + } + } + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "X0cyg7DILLQv", + "colab_type": "text" + }, + "source": [ + "**O que vocês acharam dessa árvore?**\n", + "\n", + "Está bem complexa né? Vamos voltar nesse assunto daqui a pouco :)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "aj5_1pz16uh2", + "colab_type": "text" + }, + "source": [ + "## Avaliando nosso modelo" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "0Mjmy5R47DCm", + "colab_type": "text" + }, + "source": [ + "Agora precisamos avaliar se o modelo está bom ou não!\n", + "\n", + "Para isso, precisamos utilizá-lo para realizar as predições para nosso conjunto de teste:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "7T5kx7cX9wHE", + "colab_type": "code", + "colab": {} + }, + "source": [ + "y_pred = model.predict(x_test)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "DebndYd19yiy", + "colab_type": "text" + }, + "source": [ + "Como a métrica de avaliação do Kaggle é a acurácia, vamos utilizá-la primeiro:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "7dXxL-P_7Yys", + "colab_type": "code", + "colab": {} + }, + "source": [ + "from sklearn.metrics import accuracy_score" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "uc2S3Wi19jA4", + "colab_type": "code", + "outputId": "ba45f8b4-3196-4a09-e54b-52c9c7b5e05c", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + } + }, + "source": [ + "accuracy_score(y_test, y_pred)" + ], + "execution_count": 41, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "0.7623318385650224" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 41 + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "-0-CA-jMC4ZF", + "colab_type": "text" + }, + "source": [ + "De todas as predições que nosso modelo fez, ele acertou em 76,23% dos casos.\n", + "\n", + "Outra avaliação que poderíamos fazer é utilizando uma matriz de confusão:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "rHFTQm3Gzt34", + "colab_type": "code", + "colab": {} + }, + "source": [ + "from sklearn.metrics import confusion_matrix\n", + "import itertools" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "yovWpGiDzbag", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# plota a matriz de confusão. Código retirado da documentação do próprio Sklearn\n", + "def plot_confusion_matrix(cm, classes,\n", + " normalize=False,\n", + " title='Matriz de confusão',\n", + " cmap=plt.cm.Blues):\n", + "\n", + " if normalize:\n", + " cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]\n", + " \n", + " #plt.ylim(0.5, 0.5)\n", + " plt.imshow(cm, interpolation='nearest', cmap=cmap)\n", + " plt.title(title)\n", + " plt.colorbar()\n", + " tick_marks = np.arange(len(classes))\n", + " plt.xticks(tick_marks, classes, rotation=45)\n", + " plt.yticks(tick_marks, classes)\n", + " plt.ylim(1.5, -0.5) \n", + "\n", + " fmt = '.2f' if normalize else 'd'\n", + " thresh = cm.max() / 2.\n", + " for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):\n", + " plt.text(j, i, format(cm[i, j], fmt),\n", + " horizontalalignment=\"center\",\n", + " color=\"white\" if cm[i, j] > thresh else \"black\")\n", + "\n", + " plt.ylabel('Classe real')\n", + " plt.xlabel('Classe prevista')\n", + " plt.tight_layout()" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "_6sxzSLg7A5n", + "colab_type": "code", + "outputId": "993a774e-6d72-4405-870f-e07e41596d31", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 297 + } + }, + "source": [ + "cnf_matrix = confusion_matrix(y_test, y_pred)\n", + "\n", + "plot_confusion_matrix(cnf_matrix, classes=[ 'não sobreviveu', 'sobreviveu'])" + ], + "execution_count": 44, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "hf4pxu26XrDz", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 297 + }, + "outputId": "774efe16-f70c-4f1a-ee98-0c15efc31a9b" + }, + "source": [ + "plot_confusion_matrix(cnf_matrix, normalize=True, classes=[ 'não sobreviveu', 'sobreviveu'], title='Matriz de confusão normalizada')" + ], + "execution_count": 45, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "7KfcKUhKE6Xp", + "colab_type": "text" + }, + "source": [ + "Pela matriz de confusão acima, podemos notar que nosso modelo se confundiu mais para 34% dos passageiros que sobreviveram, predizendo que eles não haviam sobrevivido." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "rwXkkoZAng2_", + "colab_type": "text" + }, + "source": [ + "## Predição\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Vc44HmLH71eM", + "colab_type": "text" + }, + "source": [ + "Agora que nosso modelo foi avaliado, vamos fazer as predições para o conjunto sem o target e fazer a [submissão para o Kaggle](https://www.kaggle.com/c/titanic/submit)? :D\n", + "\n", + "![alt text](https://media.giphy.com/media/l4JySAWfMaY7w88sU/giphy.gif)\n", + "\n", + "Antes de fazer as predições, precisamos fazer as mesmas transformações que fizemos no conjunto de treinamento durante a etapa de feature engineering:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "RVQ_ICmgozjo", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# substituímos os valores faltantes pela mediana da idade do conjunto de treinamento\n", + "submission.loc[submission['Age'].isnull(), 'Age'] = median_age" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "84S7WJcgox8U", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# utilizamos o encoder que foi criado com base no conjunto de treinamento\n", + "# como o LabelEncoder já \"aprendeu\" com o conjunto de treinamento como substituir esses valores,\n", + "# a gente usa só o transform e não fit_transform como fizemos na feature engineering \n", + "submission['Sex'] = encoder.transform(submission['Sex'])" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "07lRmNJJoDif", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# realiza a predição para o conjunto de submissão do Kaggle\n", + "result = model.predict(submission[['Age', 'Sex', 'Pclass']])" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "pSowZWRbonXb", + "colab_type": "code", + "outputId": "0ea30d72-e976-4507-e5c7-edbc86ab2f39", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 347 + } + }, + "source": [ + "result" + ], + "execution_count": 49, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "array([0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0,\n", + " 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1,\n", + " 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1,\n", + " 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0,\n", + " 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", + " 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 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"tags": [] + }, + "execution_count": 49 + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Cy9y1iDfo8fO", + "colab_type": "text" + }, + "source": [ + "Para a submissão no Kaggle, além da predição, precisamos fornecer também o ID do passageiro:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "2a8_n9v18dD6", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# transformar o array em um DataFrame para concatenarmos como ID\n", + "results = pd.DataFrame(list(result), columns=['Survived'])" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "WeuQAzXopSMD", + "colab_type": "code", + "outputId": "847c9b7f-0652-4979-c4af-ba9dbde8eb61", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 206 + } + }, + "source": [ + "submission = pd.concat([submission['PassengerId'], results],axis=1)\n", + "submission.head()" + ], + "execution_count": 51, + "outputs": [ + { + "output_type": "execute_result", 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" + ], + "text/plain": [ + " PassengerId Survived\n", + "0 892 0\n", + "1 893 0\n", + "2 894 1\n", + "3 895 1\n", + "4 896 1" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 51 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "YI1I6AujpcW_", + "colab_type": "code", + "colab": {} + }, + "source": [ + "submission.to_csv(\"titanic_submission.csv\", index=False)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "x7fWIGrxFbUL", + "colab_type": "text" + }, + "source": [ + "Se todas fizemos tudo igualzinho, a acurácia que obtivemos no nosso modelo inicial foi de **0.68421**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "2ptwDdcDIYIR", + "colab_type": "text" + }, + "source": [ + "Se observarmos o resultado da acurácia no conjunto de treinamento, tivemos uma certa diminuição na acurácia do conjunto de teste. Por que isso ocorre?\n", + "\n", + " ![](https://hackernoon.com/hn-images/1*SBUK2QEfCP-zvJmKm14wGQ.png)\n", + "\n", + " \n", + "No nosso caso, o modelo sofreu **overfitting**. Isso também explica a alta complexidade da árvore. No caso da nossa árvore, é necessário podá-la para que ela possa **generalizar** o problema." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Emhu6vuJFjSK", + "colab_type": "text" + }, + "source": [ + "## Próximos passos\n", + "\n", + "Ainda podemos melhorar **MUITO** o nosso modelo :) \n", + "\n", + "O que podemos fazer?\n", + "\n", + "- Como pudemos ver, nossa árvore está sofreu overfitting. Podemos mudar diversos parâmetros da nossa árvore para evitar que isso aconteça. Alguns parâmetros que podemos alterar:\n", + " - **max_depth** (profundidade máxima da árvore) - podemos determinar um valor para que ela não se aprofunde demais\n", + " - **min_samples_split** (número mínimo de exemplos para dividir um nó interno) - podemos aumentar o número (o mínimo *default* é 2) para diminuir o número de divisões\n", + " - **min_samples_leaf** (número mínimo de exemplos para que um nó seja uma folha) - podemos aumentar o número (o mínimo *default* é 1) para diminuir o número de folhas\n", + "- Podemos realizar outras transformações na etapa de feature engineering ou criar novas features\n", + "- Também podemos treinar o modelo adicionando as outras features que não vimos nessa aula. Talvez elas possam ajudar na predição ;)\n", + "- Além disso, é interessante ver as outras métricas de avaliação para entendermos melhor o nosso modelo e como podemos melhorá-lo!\n", + "\n", + "### **Tarefinha pra casa**\n", + "\n", + "![](https://media.giphy.com/media/geONXs3YIr0Aw/giphy.gif)\n", + "\n", + "\n", + "Tentem fazer algumas (ou todas) as sugestões feitas nesse notebook e fazer a submissão das predições no Kaggle novamente! \n", + "\n", + "Na próxima aula vocês nos contam se a acurácia do modelo melhorou :D " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "JJPMfwGM6Qdc", + "colab_type": "text" + }, + "source": [ + "![](https://media.giphy.com/media/3o7budMRwZvNGJ3pyE/giphy.gif)" + ] + } + ] +} \ No newline at end of file diff --git "a/4.0 Modelos de classifica\303\247\303\243o/slide/Modelos de classifica\303\247\303\243o.pdf" "b/4.0 Modelos de classifica\303\247\303\243o/slide/Modelos de classifica\303\247\303\243o.pdf" new file mode 100644 index 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file mode 100644 index 0000000..f9c6edf --- /dev/null +++ b/4.1 Clustering/notebook/clustering.ipynb @@ -0,0 +1,929 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.1" + }, + "colab": { + "name": "clustering.ipynb", + "provenance": [] + } + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "X6nz7i2ZOBEH", + "colab_type": "text" + }, + "source": [ + "# Clustering\n", + "\n", + "Nesse notebook iremos explorar alguns dos modelos de clustering :D" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "gGaqgTw4OBER", + "colab_type": "text" + }, + "source": [ + "### Tipos de clustering" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "E_c8_uQHOBES", + "colab_type": "text" + }, + "source": [ + "- **Por partição**\n", + "- **Hierárquico**\n", + "- **Por densidade**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "FNwKRsNZOBET", + "colab_type": "text" + }, + "source": [ + "## Por partição: **K-means**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yBsjDKaWOBEV", + "colab_type": "text" + }, + "source": [ + "![](https://media.giphy.com/media/VryvUKuOxNLqM/giphy.gif)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ByeYhvydOBEa", + "colab_type": "text" + }, + "source": [ + "### Exercício 1" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "gZNt5KYJOBEc", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# imports necessários para a aula\n", + "import numpy as np\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "PyK_D3FkOBEf", + "colab_type": "code", + "colab": {} + }, + "source": [ + "plt.rcParams['figure.figsize'] = (12, 7)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "nvNt828SOBEi", + "colab_type": "code", + "colab": {} + }, + "source": [ + "import warnings\n", + "warnings.filterwarnings('ignore')" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "bNE8ROZGOBEl", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# importar o dataset\n", + "df = pd.read_csv(\"https://github.com/WoMakersCode/data-science-bootcamp/raw/master/4.1%20Clustering/data/case.csv\")" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "niW64awfOBEb", + "colab_type": "text" + }, + "source": [ + "Vamos utilizar uma base fictícia contendo dados de visitas de clientes em um site que gostaríamos de segmentar: \n", + "- **Visitas**: quantidade de visitas realizadas durante o mês\n", + "- **Tempo**: tempo, em segundos, que os usuários ficaram no site" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "Sx4vqHR4OBEo", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# TODO\n", + "# Ver a carinha do nosso conjunto de dados" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "860GfxAbOBEu", + "colab_type": "text" + }, + "source": [ + "**Vamos visualizar a distribuição desses dados?**" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "L6CCLCR1OBEv", + "colab_type": "code", + "colab": {} + }, + "source": [ + "plt.scatter(df.visitas, df.tempo, alpha=0.5)\n", + "plt.xlabel('Tempo')\n", + "plt.ylabel('Quantidade de visitas')\n", + "plt.show()" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "y4Z_QZ1jOBEy", + "colab_type": "text" + }, + "source": [ + "**IMPORTANTE**\n", + "\n", + "Como os agrupamentos são definidos com base em uma medida de distância, primeiro **precisamos normalizar os dados**!" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "JJvabX7ZOBEz", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# Importar o StandardScaler e normalizar os dados\n", + "from sklearn.preprocessing import StandardScaler\n", + "\n", + "scaler = StandardScaler()\n", + "df = pd.DataFrame(scaler.fit_transform(df),columns = df.columns)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "ePVH15znOBE2", + "colab_type": "code", + "colab": {} + }, + "source": [ + "plt.scatter(df.visitas, df.tempo, alpha=0.5)\n", + "plt.xlabel('Tempo')\n", + "plt.ylabel('Quantidade de visitas')\n", + "plt.show()" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "UPlMoD7OYRmG", + "colab_type": "text" + }, + "source": [ + "**Voltando ao K-means...**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "VjnK1lCEOBE6", + "colab_type": "text" + }, + "source": [ + "\n", + "\n", + "O Sklearn já conta com uma implementação do [K-means](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html). Podemos importá-la:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "qbP4y6RaOBE7", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# Importar o K-means\n", + "from sklearn.cluster import KMeans" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "Z4_TSzuvOBE-", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# cria uma instância do K-means\n", + "kmeans = KMeans() \n", + "kmeans.fit(df)\n", + "# salva os centroides\n", + "centroides = kmeans.cluster_centers_\n", + "# salva as labels dos clusters para cada exemplo\n", + "y_kmeans = kmeans.predict(df)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "3o8_JRwdOBFA", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# plota os dados identificando seus clusters\n", + "plt.scatter(df.visitas, df.tempo, c=y_kmeans, alpha=0.5, cmap='rainbow')\n", + "plt.xlabel('Tempo')\n", + "plt.ylabel('Quantidade de visitas')\n", + "# plota os centroides também\n", + "plt.scatter(centroides[:, 0], centroides[:, 1], c='black', marker='X', s=200, alpha=0.5)\n", + "plt.show()" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "1aPfoNAWOBFF", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# TODO\n", + "# Rodar o K-means definindo o número de clusters como 50" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "xKse31GuOBFM", + "colab_type": "text" + }, + "source": [ + "Altere o número de clusters e rode o algoritmo de novo. Vamos ver o que acontece :D\n", + "\n", + "Não se esqueça de adicionar uma seed!" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "tLnMzzGsOBFN", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# TODO\n", + "# Rodar o K-means escolhendo o número de clusters que você acha que faz sentido" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "fSEANPcCOBFW", + "colab_type": "text" + }, + "source": [ + "![](figures/inercia.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "356T2hleOBFW", + "colab_type": "text" + }, + "source": [ + "Para escolhermos o número de clusters, observamos o gráfico do cotovelo com as inércias e escolhemos o ponto no qual a inércia começa a ficar mais plana e formar um \"cotovelo\":" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "jfKSvn9bOBFX", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# Quantidade de clusters que serão testados\n", + "k = list(range(1, 10))\n", + "\n", + "# Armazena das inércias para cada k\n", + "inercia = []\n", + "\n", + "# Roda o K-means para cada k fornecido\n", + "for i in k:\n", + " kmeans = KMeans(n_clusters=i, random_state=8)\n", + " kmeans.fit(df)\n", + " inercia.append(kmeans.inertia_)\n", + "\n", + "# Plota o gráfico com as inércias\n", + "plt.plot(k, inercia, '-o')\n", + "plt.xlabel(r'Número de clusters')\n", + "plt.ylabel('Inércia')\n", + "plt.show()" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ErS5tjXFOBFc", + "colab_type": "text" + }, + "source": [ + "### Exercício 2" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "oGIZQ5FtOBFc", + "colab_type": "text" + }, + "source": [ + "Agora vamos fazer mais uma segmentação de clientes com o K-Means, dessa vez com mais features. O dataset que iremos utilizar é uma adaptação [deste aqui](https://www.kaggle.com/vjchoudhary7/customer-segmentation-tutorial-in-python) presente no Kaggle.\n", + "\n", + "Dessa vez, vamos supor que estamos envolvidos em um projeto de um e-commerce que tem como objetivo segmentar e entender seus clientes para realizar campanhas de marketing." + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "P9_01aeGOBFd", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# importar o dataset\n", + "segmentation = pd.read_csv(\"https://github.com/WoMakersCode/data-science-bootcamp/raw/master/4.1%20Clustering/data/customer_segmentation.csv\")" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "_6cnOLNqOBFg", + "colab_type": "code", + "colab": {} + }, + "source": [ + "segmentation.head()" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "a8-ntnYuOBFo", + "colab_type": "text" + }, + "source": [ + "Esse conjunto de dados possui 5 campos:\n", + "\n", + "- **id**: código identificador do cliente\n", + "- **tem_cartao**: indica se o cliente tem cartão de crédito do e-commerce ou não\n", + "- **idade**: idade do cliente\n", + "- **renda**: renda mensal do cliente, em reais\n", + "- **score**: score indicando o gasto do cliente. Quanto maior, mais o cliente gasta no e-commerce" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "gX5wY4EBOBFp", + "colab_type": "text" + }, + "source": [ + "**Observando os dados acima, quais pré-processamentos vocês acham que serão necessários antes de realizarmos o agrupamento?**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "C5szPP7mOBFq", + "colab_type": "text" + }, + "source": [ + "**`1° - Remoção do identificador`**\n", + "\n", + "O conjunto de dados contém o id do cliente que não iremos utilizar para a segmentação. Precisamos remover antes de realizar o agrupamento:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "PXgzDb53OBFr", + "colab_type": "code", + "colab": {} + }, + "source": [ + "segmentation.drop(columns='id', inplace=True)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "7Z_-AUeEOBFt", + "colab_type": "text" + }, + "source": [ + "**`2° - Lidar com feature categórica`**\n", + "\n", + "Temos mais um ponto para resolver antes do agrupamento: a feature `tem_cartao` é categórica e o **k-means só lida com dados numéricos**." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "odqpOVFaOBFu", + "colab_type": "text" + }, + "source": [ + "![](http://giphygifs.s3.amazonaws.com/media/dJtDZzyjLF66I/giphy.gif)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Yjkf9C9NOBFv", + "colab_type": "text" + }, + "source": [ + "**O que podemos fazer para lidar com variáveis categóricas então?**\n", + "- Feature engineering (One-hot enconding, Label Encoder, etc.)\n", + "- Utilizar outro algoritmo que permita usar esse tipo de variável\n", + "\n", + "No nosso caso, vamos utilizar o [LabelEncoder](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html):" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "AwuSc9BKOBFv", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# importar o LabelEncoder\n", + "from sklearn.preprocessing import LabelEncoder" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "Z2aeM2YyOBFx", + "colab_type": "code", + "colab": {} + }, + "source": [ + "label_encoder = LabelEncoder()\n", + "segmentation['tem_cartao'] = label_encoder.fit_transform(segmentation.tem_cartao.values)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "2elcvXu8OBFz", + "colab_type": "text" + }, + "source": [ + "**`3° - Normalizar os dados`**\n", + "\n", + "As escalas das features são diferentes, então precisamos normalizar os dados:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "HHQC_zDZOBF0", + "colab_type": "code", + "colab": {} + }, + "source": [ + "from sklearn.preprocessing import StandardScaler" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "_wAmbU__OBF3", + "colab_type": "code", + "colab": {} + }, + "source": [ + "scaler = StandardScaler()\n", + "scaled_segmentation = pd.DataFrame(scaler.fit_transform(segmentation),columns = segmentation.columns)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "l1UEqjzGOBF5", + "colab_type": "text" + }, + "source": [ + "**Agora sim podemos aplicar o K-means \\o/**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "DcSH7RzfOBF5", + "colab_type": "text" + }, + "source": [ + "Primeiro, vamos utilizar a regra do cotovelo para escolher o número de clusters:" + ] + }, + { + "cell_type": "code", + "metadata": { + "scrolled": false, + "id": "ndosxe9uOBF6", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# TODO\n", + "# Fazer a curva do cotovelo aqui para escolhermos o número de clusters" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "uIJhbaSQOBF9", + "colab_type": "text" + }, + "source": [ + "Com base no gráfico acima, podemos escolher a quantidade de clusters que serão criados:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "dHByqJCVOBF9", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# TODO\n", + "# Rodar o k-means no nosso conjunto de dados" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "uKkCV7DtOBF_", + "colab_type": "text" + }, + "source": [ + "Após o agrupamento, precisamos reverter a normalização para podermos interpretar os clusters formados!" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "DP8KSNTEOBGA", + "colab_type": "code", + "colab": {} + }, + "source": [ + "original_segmentation = pd.DataFrame(scaler.inverse_transform(scaled_segmentation),columns=segmentation.columns)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "KgTs3SUOOBGC", + "colab_type": "text" + }, + "source": [ + "Como utilizamos 4 features para criação dos clusters, não podemos visualizá-las como no 1° exercício. Podemos utilizar o [pairplot](https://seaborn.pydata.org/generated/seaborn.pairplot.html) para tentar interpretar os clusters:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "sVg7rTZlRyEh", + "colab_type": "code", + "colab": {} + }, + "source": [ + "original_segmentation['cluster'] = clusters" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "3st56dolOBGD", + "colab_type": "code", + "colab": {} + }, + "source": [ + "sns.pairplot(original_segmentation, hue = 'cluster');" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "REBB9M_POBGP", + "colab_type": "text" + }, + "source": [ + "## Hierárquico: **Agrupamento Hierárquico Aglomerativo**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "eHbZqM9bOBGQ", + "colab_type": "text" + }, + "source": [ + "![](https://media.giphy.com/media/pSNCWCEAsgrAs/giphy.gif)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "KBa752quOBGS", + "colab_type": "text" + }, + "source": [ + "### Exercício 3" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "8qLAQVG0OBGS", + "colab_type": "text" + }, + "source": [ + "Vamos utilizar o mesmo conjunto de dados utilizado no segundo exercício do K-means para realizar um agrupamento hierárquico aglomerativo. Para esse agrupamento, precisaremos importar o dendograma do [Scipy](https://docs.scipy.org/doc/scipy/reference/cluster.hierarchy.html).\n", + "\n", + "O sklearn também possui um [módulo](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.AgglomerativeClustering.html) para realizar um agrupamento hierárquico aglomerativo, mas é complicado visualizar o dendograma com ele, então vamos ficar com o scipy mesmo." + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "fFXGd-5fOBGT", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# importar os módulos dendogram e linkage\n", + "from scipy.cluster.hierarchy import dendrogram, linkage" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "OtoD0a9aOBGV", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# TODO\n", + "# Usar o método linkage para fazer o agrupamento hierárquico\n", + "h_cluster = " + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "zEnzqb8HOBGX", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# TODO\n", + "plt.title('Dendograma')\n", + "plt.xlabel('Exemplos')\n", + "plt.ylabel('Distância')\n", + "# Chamar o dendrograma aqui\n", + "plt.show()" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "6sFsDczyOBGa", + "colab_type": "text" + }, + "source": [ + "**Vamos testar outras abordagens de agrupamentos e métricas de distância?**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "8XT03nllOBGa", + "colab_type": "text" + }, + "source": [ + "![](https://media.giphy.com/media/12zV7u6Bh0vHpu/giphy.gif)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "HziBNsH_OBGe", + "colab_type": "text" + }, + "source": [ + "## Por densidade: **DBSCAN**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "g0d6X_10OBGf", + "colab_type": "text" + }, + "source": [ + "![](https://media.giphy.com/media/lCL2GQewp7fkk/giphy.gif)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "mukUxpTHOBGh", + "colab_type": "text" + }, + "source": [ + "### Exercício 4" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "H9fxh4oNOBGh", + "colab_type": "text" + }, + "source": [ + "Vamos utilizar novamente o conjunto do primeiro exercício com o DBSCAN, que vamos importar do [sklearn](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html):" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "POKAI1vHOBGi", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# Importar o DBSCAN\n", + "from sklearn.cluster import DBSCAN" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "hcpdXFOTOBGk", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# TODO\n", + "# Escolha um epsilon e um minPts\n", + "dbscan = \n", + "# salvar os clusters atribuídos para cada exemplo\n", + "clusters = " + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "3xdXTRrjOBGl", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# plota os clusters encontrados\n", + "plt.scatter(df.visitas, df.tempo, c=clusters, alpha=0.5, cmap='rainbow')\n", + "plt.xlabel('Tempo')\n", + "plt.ylabel('Quantidade de visitas')\n", + "plt.show()" + ], + "execution_count": 0, + "outputs": [] + } + ] +} \ No newline at end of file diff --git a/4.1 Clustering/notebook/clustering_gabarito.ipynb b/4.1 Clustering/notebook/clustering_gabarito.ipynb new file mode 100644 index 0000000..0d5255f --- /dev/null +++ b/4.1 Clustering/notebook/clustering_gabarito.ipynb @@ -0,0 +1,1897 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.1" + }, + "colab": { + "name": "clustering-gabarito.ipynb", + "provenance": [], + "toc_visible": true + } + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "X6nz7i2ZOBEH", + "colab_type": "text" + }, + "source": [ + "# Clustering\n", + "\n", + "Nesse notebook iremos explorar alguns dos modelos de clustering :D" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "gGaqgTw4OBER", + "colab_type": "text" + }, + "source": [ + "### Tipos de clustering" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "E_c8_uQHOBES", + "colab_type": "text" + }, + "source": [ + "- **Por partição**\n", + "- **Hierárquico**\n", + "- **Por densidade**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "FNwKRsNZOBET", + "colab_type": "text" + }, + "source": [ + "## Por partição: **K-means**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yBsjDKaWOBEV", + "colab_type": "text" + }, + "source": [ + "![](https://media.giphy.com/media/VryvUKuOxNLqM/giphy.gif)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ByeYhvydOBEa", + "colab_type": "text" + }, + "source": [ + "### Exercício 1" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "niW64awfOBEb", + "colab_type": "text" + }, + "source": [ + "Vamos utilizar uma base fictícia contendo dados de visitas de clientes em um site que gostaríamos de segmentar: \n", + "- **Visitas**: quantidade de visitas realizadas durante o mês\n", + "- **Tempo**: tempo, em segundos, que os usuários ficaram no site" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "gZNt5KYJOBEc", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# imports necessários para a aula\n", + "import numpy as np\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "PyK_D3FkOBEf", + "colab_type": "code", + "colab": {} + }, + "source": [ + "plt.rcParams['figure.figsize'] = (12, 7)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "nvNt828SOBEi", + "colab_type": "code", + "colab": {} + }, + "source": [ + "import warnings\n", + "warnings.filterwarnings('ignore')" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "bNE8ROZGOBEl", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# importar o dataset\n", + "df = pd.read_csv(\"data/case.csv\")" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "Sx4vqHR4OBEo", + "colab_type": "code", + "outputId": "d9658259-4504-46a8-bdbb-dad410318f90", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 204 + } + }, + "source": [ + "df.head()" + ], 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" + ], + "text/plain": [ + " visitas tempo\n", + "count 3000.000000 3000.000000\n", + "mean 30.221000 41.165333\n", + "std 24.852097 24.983863\n", + "min 0.000000 0.000000\n", + "25% 9.000000 19.000000\n", + "50% 19.000000 42.000000\n", + "75% 56.000000 62.000000\n", + "max 87.000000 104.000000" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 99 + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "860GfxAbOBEu", + "colab_type": "text" + }, + "source": [ + "**Vamos visualizar a distribuição desses dados?**" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "L6CCLCR1OBEv", + "colab_type": "code", + "outputId": "b45579df-be46-436b-d264-12fdf1f9310d", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 442 + } + }, + "source": [ + "plt.scatter(df.visitas, df.tempo, alpha=0.5)\n", + "plt.xlabel('Tempo')\n", + "plt.ylabel('Quantidade de visitas')\n", + "plt.show()" + ], + "execution_count": 100, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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1DOX7VR0Xf3dlCY7LkYrpcFyOv7uyhKrjSrfgVRILs5YRWYeq1EHaN9vF21eD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\nxnjHgSxhqPHD6G8/hDDU3HHA/GYziXZJ4pq5V2R6bk213+esQdB2vqr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g2rFj6/Ctt27Q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\nBbuZvi2I1EiR/ijqoOycD+P+J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WuoNxzwFTtUmgIIxvDV5w+veS6KRkXF8bXPHm1mHCmj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\n5H9mwHARavlEGux9tSijEtDd7t791dnuNEmot9d+bKm3M9Ik4YMnD5Bm9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" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "y4Z_QZ1jOBEy", + "colab_type": "text" + }, + "source": [ + "**IMPORTANTE**\n", + "\n", + "Como os agrupamentos são definidos com base em uma medida de distância, primeiro **precisamos normalizar os dados**!" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "JJvabX7ZOBEz", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# Importar o StandardScaler e normalizar os dados\n", + "from sklearn.preprocessing import StandardScaler\n", + "\n", + "scaler = StandardScaler()\n", + "df = pd.DataFrame(scaler.fit_transform(df),columns = df.columns)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "ePVH15znOBE2", + "colab_type": "code", + "outputId": "f08d9a01-f591-409a-e586-205cf25927b6", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 442 + } + }, + "source": [ + "plt.scatter(df.visitas, df.tempo, alpha=0.5)\n", + "plt.xlabel('Tempo')\n", + "plt.ylabel('Quantidade de visitas')\n", + "plt.show()" + ], + "execution_count": 102, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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ZgWXqyKR0eD7HGzMreOLk0D2dT7Yt6R7JPi+q45SRnQ9Ivn/bTbn8NPsRQgghBwmVbShS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\nMnEE1Rk0tpR9RrZO2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11flGSpfpSotldsF7mEBoV5H+8pDMglNFRsl6xTVhRd0RXwaIeK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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "UPlMoD7OYRmG", + "colab_type": "text" + }, + "source": [ + "**Voltando ao K-means...**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "VjnK1lCEOBE6", + "colab_type": "text" + }, + "source": [ + "\n", + "\n", + "O Sklearn já conta com uma implementação do [K-means](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html). Podemos importá-la:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "qbP4y6RaOBE7", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# Importar o K-means\n", + "from sklearn.cluster import KMeans" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "Z4_TSzuvOBE-", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# cria uma instância do K-means\n", + "kmeans = KMeans(n_clusters=4, random_state=19) \n", + "kmeans.fit(df)\n", + "# salva os centroides\n", + "centroides = kmeans.cluster_centers_\n", + "# salva as labels dos clusters para cada exemplo\n", + "y_kmeans = kmeans.predict(df)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "3o8_JRwdOBFA", + "colab_type": "code", + "outputId": "98bdfd2b-882c-4a52-e5b2-0f9fc21eada3", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 442 + } + }, + "source": [ + "# plota os dados identificando seus clusters\n", + "plt.scatter(df.visitas, df.tempo, c=y_kmeans, alpha=0.5, cmap='rainbow')\n", + "plt.xlabel('Tempo')\n", + "plt.ylabel('Quantidade de visitas')\n", + "# plota os centroides também\n", + "plt.scatter(centroides[:, 0], centroides[:, 1], c='black', marker='X', s=200, alpha=0.5)\n", + "plt.show()" + ], + "execution_count": 105, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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Gk9JfXx+NeGuzydYpK93Txk7FKMWN9To31usnfH+j1uwtSwZhcyPA/qKgjCJm\nw6axm+p1blp1nPOevxwM+M54TAy4cH3v6XS4uV5nzhj++cIC/3zVPKz3fKbf5/40nRx3x2jEe9tt\nrl/1GiuV3vPpXo8Hs+yE1/tAp8MVScKnej0eWjH2tTC2JYp4co0Og7NTAuc8VG55Is9JqKp83DEc\n8ptzc1z2Aj6HC8WcMbxFVpqFEEJcQCRt4wyLvefZsJGtEcqWxVS5nEed4y/6fTaFMnVbo4jtxnDX\neMyeKVUlLokiLotjDlhLGUqlHQrVN7ZEEV8cDNhsDNuMYWv4+vpoxKN5zt8MBmxZ8f0txnDHaMS1\nccwmYzgSOijasIq9YAyve4H5wiczYwxda9FASymaSuGVYtG5qcHl00XBd8Zjtodr3RZFbNSaz/X7\nUzdEPpHn3Jem7Fhx3GzoWphP2YT4aJbxQJadcFxHKf6s1+OBNOVHq8ZaSvFn/T631GoYmGx2y0M1\nktc0GrSmXN/94zGP5zk7jGFzOGcCfKbXmzTCEUIIIcT5Q4LnF8B5z/6i4JmimARk9+c5LaWYjyLK\nEEQ1tWZOa745GuGBmKqNczdU5jDAk1NK1WmleP/sLLfW6xy1lkPWcm2S8DtzcxwIQbdRip5zdJ2r\nVryp6iCv7gYYhbED1vLvN2/mxlqNQ+GcN9Vq/IctW6iHYK/0nj1FwbNF8ZxOiEUY23uSsZ61/GW/\nz5f6fcZhQ9jesuSaWo2NxnDce3rec0kcc3kcs3fKjcOP85w4vAfLalpjvWfflOMeyTLqVCu7zxYF\nB8uSesgZ3x9SVk7moSw7oRkOUG0A9J57xmNaq8ZaWjN0DqcUvzs3x5YoYn/YCPn2Vot3rFhVHTnH\n03nOoVAxBeDBLGM2NJfZUxQcKUvaWnPMWhZfYK70ILze0ZO8T9PGpulZy9N5zvEX2MlRCCGEuFBJ\n2sY6HSlLPtnrcSh0CqwpxbvbbRL+vr7xcnqCAg5ZS0Mpus7x7aKoSrCFahwLxlTdAadoac0/7HT4\nhXb7hIB4X1kydI57xmPSUMkiVorNxlBbIw1k+c+UVFUlXh5SQeaNmVQQeTrP+WSvx9C5SerB+2Zn\n2RnH7A5jozA2Zwy/1umwPY75xPHj/Kdul4KqokZDKf6nhQVqobFK1zmSkM6waC2xMScE96stpzKs\ntnwTspaa1jyZ5zxVFJOugC2tua5Wm/p6daVO2k59+VrWGouBhTjmgxs2kIdOiMsBvw+B998Mh7jw\n5y9PEt7b6RADD2QZzxTFpOTgbKhkst6/nN57vj4c8vVws+aAa5OEX+p0qIfc+DtDFRAHXF+r8Yvt\n9uSm6WSc93x5OOSuFce9rIJCzvoAACAASURBVFbjH3Y650VDGCGEEOLFIivP6+C85xPdLl3n2B4e\ntTeU4pP9PlfGMS2t6YVAVgFZ+PUvtNvsCXm/M6Eigw+b07ad5iYpo9QJwd8OY9hdFGShBfZMWJV9\nqii4tdGgphTDk3QD3BFFfGxpCYBLk4RLkwQPfGxpqeqE2O2iqMrybY8irPd8dGmJo2XJx7pdzIqx\nwjk+2u3yQJryf3W7aKr22rOhOcy/OXKEGaV4sijw3tM2ho4xDJ3jmRVdBE/mhpCfnK0IWpespaM1\nO6fkBNeAx4oCQxU0t5RiYC0/SlO2TgkSb240yDmxDOFx59gaRbyx2SRdNXbMOXZG0aS8HlS1ileu\nlO8uCv5qMGBea7ZFEduM4ek857O9HkopnigKaivmedw5nszzdW8afCjL+HLo3LctpAY9mud8aTDg\nwSzja6MRCyvGHsoyvjwcTj3nfWnKN4bDKj0oXMMPsoyvneI4IYQQ4mIjwfM67C1LjlrL/IogrBEC\n4ceLgn+9aRORUhy2lsOhc99vz87SMYZLQqDdd45BKGN3WRxzaJ2PwQ9Yy644JlKKQTgn4ZxL1vL+\nTmeSf3ugLEm95/2dDgfKkrH3VaOSoK01I+/5xmhEtmqsE7oW3jkcknl/QhfCWWMYOMdHFxdxcEIL\n7abWZN7zuX6fXVGEXzHPulJcEkXsn5I6sDmK+KV2m65zHAjXECnFr8/NTV1BvjdNJykWeSiP19Qa\noxQPTum8eFkc886ZGY6F0mn7y5KO1vxqp8PlScLPz8xMSvDtL0vmtOZXZmen1iX+XppSV2pSE1op\nxVZjeCzP+c5oRFsp7Ip5tpViHKqkrMc94zGzK26ylFJsMYb705S/G42eM7bVGO5N06m54HeNx8wb\nM9l4qsM5vz0en1C3XAghhLjYSdrGFIX33DUacfd4TOo9N9RqvLXVIvce7z2787zqIkhVOm45+HxV\nkvCqWo2vjEaUwC1JwqsbDYYh//m2ZpOetTiqFdpj1p6yFvBSWfL/LS1xd8hjfnmtxj+anyfznpbW\n3N5o0A3n6GjNIWvJvGfOGDxVHWJP1Vhkzhi6RUHpPT/O80nwuj2KqCnFyDkK73ksz6vau2EsUYqh\n95Te82ieczCM7QjH9cMK+8kMnWM+irjaGHqhi2AndBHMvWfJWv52OOSHoZLFaxoN3tBqkSjFLY0G\n19Rq7C1LYuCScLMAVerHHcMhD2YZdaW4rdHgdc0mPeeYCavfWWgsU1OKI8s3GFO8ttnkpnqdfaHD\n4M4omgSNm4yh6xyPhtd758wMM6dIWxha+5wUExUqo/TD55c6xzCke7S1JgX61rJtyqr83qLgK8Mh\nu0M1lzc1m9xSrzPyntR7nkxTlpyjoRSXGTO5cRl5zxNpypK1NLRmVxThQl3ytVIwRs5RW/W9iCov\nXqpYn5z3nvvTlK+PRixZy+VJwttbralPTIQQQpz/ZOV5is/3+3x5OKQGbNKaH2UZf7i4yKzW7ClL\nHi8KIqABHAy1lHdozf94+DB3jMdsMmbyyPxfHD5MmyqNw3nPBmPYaAwGKIErpzT1cM7xr44c4euj\nES2l6CjFd9OUf3HoEBuNmXTsmw951ssf6o4o4vcPH56sGm40hm8vHxdygveElIEasCfUL76+VuPJ\nPOfZMJZQ5UA/FToaPp7n7FsxtjvPebIoeFOrhQvzXWZDQP3WVgtLtTlyozFsMGYSdG3Smo8sLXFf\nmjKvNU2tuWM04s97vcnGuqbWXB1KAy4HziPn+NDiIg9mGZtCE5ovD4f8Rb/PaxoN8hA0N0MTmNx7\nDHBjbXUY+FwzWnNNrcZlcTwJnPfkOf/y8GF25zlbjaEZKm38b8eOTT3X9bUa/XDDtWwYgvtbajUO\nWktOlVNtlOJQeP+mNc45VJZ8aGmJfUXBZmOw3vPpfp+7x2N2GsP30pS+tbSoSub9MM+xVDXHv5+m\nDJyjFVJ87ssyFNCcchNwY63G8VU3Hced4/IkkZznNdwzHvPpfh/rPZuNYV9R8KGlJQ6u84mCEEKI\n84MEz2s4bi33pynbjaEeHvdvMYa+c9w3HtNUCu09GZBSbaBqac1joRX3Fq1JwuPxhbBa+a3xmJ+Z\nmanSOUJ3wn3W8vJ6fWpN3+9mGU+FboDL59xsDEfLkgfSlDc3mxwMKSJHQjrBaxsNnspz9pYlm7Um\nDmkDW4zhoLV8czxmJuTUpmGl0nvPjDEsWjtJy8jCGFQB5fKYXzGmwtht9TrXJwk9qlXTnrUMgDc0\nGrx9ZoZb63X2hes+HCp8vGNmhn0hDWZbFBEpRU0pdhrDj7JsajrLj7KMbujqZ5SirjU7jOEHacrN\n9TovDYHpcWs5Yi3dkLIydxqNUk7ms6HM3UZj0OH1thjD343HUwOim+t1dsUx+0IXyAMhlecX2212\nxDFNpci8n3zhPZdE0Uk3Si77Vti4Nx/m0gpz+dvhsHrCETaEplQVR5YD3FEYK7wndY7ce+qhAsu0\nFeTXN5vMGcO+0D1y+YnEz0mN5pMqvOdrIUe8pTVaqckG4rukZbsQQlzQJG1jDcetRa3a+AXVZrDd\nRcHmKGIhingizym957I4pqMUjxcFSikG3rMYUjpmtUaHTXzvnZsjVoqvDAakwJuaTd7SbKJV1VDl\n2bLkwZB/en3ozrdcWm11Xq2iWhH+x/PzXJkkPJhlWO+5IXTn+2Svd9LjoOoiuN0YNofNawAvCRUe\nlru9NbXmcGj2stkYRqGG9SVxTEOpydgWYxh6Txf40NatfGow4KuDAQnwznabd7ZaKKV4Z6vFwDnu\nGA6pKcUvtNu8rtnkbwYDIuCotRwJOc2bowhNlZaxdY1gd39ZPmfVUyuFBsbe8+83b+aO4ZC7x2Pa\nSvEz7TY3T2mQcipPFQUx1arxKKxit7VGAfuKgnljeDTL+HGeM6s1N9frLEQRNa35rbk5HklTHi+K\nE8b+djTiTa0Wj2cZB8qShta8rFZDq6r04MIamxv3leVz0kUSpcjC+/LKep2+9yxaS1MptoYc+APW\n8qp6na5zLDlHUym2RRHHnWPs/ZopKLPG8I83bODBNGVPWbIlinjZaXZCHDrHA2nKvnDczfX6Cfn0\nL6autfwwyzhcllwSRdxYr9M8C3MZOkcGzK96P2eUmlqaUQghxPlPguc1zBuD9x7n/QkBdO49l8cx\n96UpR62dBGvPFAUNpXjXzAxf7Pc5CJP8375zGOBSY7h7NOKvBwMipYipOv71nePd7XbVKTAEkhr4\nTpry6kaD7SF49N6fEAh74LIkQSnFriRh16rUjx1rHAfVxrivjUb0rGU5/Hk8y5iNIt4aRTyW55M0\nkOVzjKzl0iji8ZOMDa1lgzEkxvDrs7P8+uzsCa/nnON/PnqU72UZy7P8f44f52BZcmutxpNFwdg5\nIsArxTN5zqYomtqqeZsxfG/VZjXnPRaYC6kaP99u8/Pt9prneD52RRH3pima6vPxVJU/khDs/9HS\nEk+Fn4PCe/5uPOb9nQ7X1GokSvGyRoOXrWpAs2AMd4SOkJtCVZNH87y6GZsS1O2IIh7IMporvpd7\nTwJcGsf8OMvYHqqhQFXxpa4Uu6KIJ4qCHXHMjnBcGlI4GqdIv2hqzaubTV79PN6zRWv50OLiJPf6\n/jTlm6MRvzc3x8I6nwCs18Gy5EOLi6Rhtf3+NOVb4zG/Ozd3xtuht0IaUeb9CSUjB95z04t83UII\nIc4sSdtYw7wx3BLSDFLnJl392lrz8kaDUdg4V6eqtKGpguTNWlMohaPK742ogqwSaKzoBrjFGDZF\nETtCpYMHs4y/WR4Lq9o7jOG74zFbjOHyUJEjD697yFo2RRFvarXWvIbbGw12RhGHwwbA0lddBLca\nwxsaDQYhJaKuFPVQmWJgLdckCdtDFYzCewrv2R+qeryu2WRrGCtXjF2ZJFw6JSi4Zzzm+yGdZWPI\nv95kDJ/r9+l5zyDkRteVogaTzW2tKQHdDfU6s2FzpPWezDn2WcvN9TqbzkKAcm2thvUeF4J8vVwd\nI+SzPlUU7AjXtjV0Jvxsvz+1GkVDVaUEI6BOtalx+TOOp1z77c0mnuoJifOekXMctJa3tFq8sdXC\nKjUZGzrHIed4cxgrqILa5bHD1vLWVmuS230mfX04pO89O6KIeWPYHkXkzvHlweCMv9apfGEwwFNt\nfl2ey6K1fPMspFHESvHmVovD1jJyDud91X2S6rMTQghx4ZLgeYp3tdv8dKtFChxxjhtqNT64YQNd\n57g0jrk6SSiAofdsjSKur9X4dpYxrzUbtaYAMqpHtQshEPYwSUc4bu1kE919aVo121gRwGilMMAz\nZcm/XVjgTa0WQ+9Z8p5X1ev8xy1bJq2fc+95Ms95Is/JwsauSGv+/ebNvLZer9qDW8ur63X+w5Yt\nHHWOK5OEnVFEz1cd/3ZGEVcmCYes5bfm5rgiirhjOORrwyHXJwnvn52lpjW/PTfHqxoNFp2j5xyv\nbzZ5X6dzynJtetUq/nK3w3tGI65NErZFEWOqG40r4rjKEw6PuEfO8Xie83RIk4Fqde/3NmzghlqN\nI84xBn661eIfnuZK89A5fpznPHOSLomDk4wdd47X1uvMRhED7ymU4ro45tok4bvjMTNKkQPHQvfI\n5cD46JS87b1lyctrNVpacyzkIN+YJLS1ntrFb2sU8cG5OXaEmyqlFO9pt3lteFLxwbk5toUxoxS/\n0m5zW6PBjjjm90InxIPWEivFezsdXvkC0lmm+VGWsTF0YTwaOi/OG8Mjef6ith/PveepPD+hvCTA\nvNY8OKW75wvx2kaDX2q3UUpxyFq2xzEfnJtbMw1JCCHEhUH+FZ8iVoo3tVrPWd1dLsl2eaj+sGx/\nWdIxhnzFn1FUm7QIdZOPWss9eT6pqauVYkFrXlavc7JQwlOtxs5FEf9y06aTzvOZouATS0vV61Dl\nvv5qp8PVtRrdkFpya0gXMErRDakGo7DquPxDcNhaFsLx/+uhQ3w+BPsA//b4cfYWBb+/sMCM1ryr\n3eZdzyMdYkZr/BrBdTvkTF9Xq3Hdiu8v5zT/IE353IoV3Flj+MDsLNtCWscvdzr88mnPpPKd8Zi/\n7vcnm+Q2hnMuRBF3j0Z8aTCYjC0Ywwfm5mhQ3Sg1lGJnCIBKoKDKfX4oyyaBsleKGWBzHE+tRtFQ\nVT3wvnPUta5avlvL5lAacJqdccxvz82ddOySOOZ31xi7LI75vQ0bpp77TKkpxY+yrNpDQPXzvMEY\nLonjNcsang2G6mat5MTOlAWclZxnqPYa3NpoTP7uCSGEuDjIyvM67IwiNhrDsRUrg8utsX+m1aJn\nLSVVEJqEer4957g51CpOfdVkZEZrlPc8XZbcVKvR0ZqlFeccOUekFC+dUlpt7BwfW1oiUmqS49pU\nij/u9ThUFHy81yMJm8K2RRF1pfhEr0dHa54pClwI6tuhbNmeomB/nvP58bhq4x2+FPDxfp9H1vmI\n+22tFiZc07Ju6Ir47rA6t3LsuLXMGUNdKf6s12N2xfUVzvHxbnfdzTmeLQo+3++zMTy63x5FDJzj\nT7pdns5z/nowOGGsF8a2RBFPlyU1pSaf33HnWLSWK1aNtVXVKbBnLRumBGfL56wrxYxStLXmSEgV\n6pzhPNxzYc4Y9hQFreX3LGyYmwlpQi8WoxSvaTQ4ZO2kZKD1nkXneK0Et0IIIZ4HCZ7XwSjFB2Zn\nmdWafWXJvrJk6D2/2unwbOg6l1A9Kl5eYe5Qdb27LIpoaU3fuWp1WimuiGMOW8tvzM1R13rSSS9b\nLq22IoiyIR922VNFMQnGXdjg2NSawnvuDJ0CW1pTOEfu3GTse2nK5UlCrNRkLrFSXJ4kfKTXwwMr\nQzdDtWr4/3a7p/Ueld6fkApxWZLw323YQAEcCmXqGkrxbzZtYnsc82udDqn3PFsU7M1zZrTmN2Zn\neTTUIF7ZtXDOGHrWsjdUIYGqNNjq1Iu1PJCm1YbNFcHbRmM4Yi13jkbVDYNS2HDN81pzsCz5cVFw\nZRyTU6V19J1jIWycfMLa54xtMoY5Y06oj1yEz2jZwbLkqjgm4+/L+201hoYxdJdXsUNu+cnSHJbH\n/DpvJM6242XJFXHM0Puqq6b37Ao3JC/2nN/SanFzrcaBUGrvsLW8odnkFWcpZUUIIcTFSdI21qmj\nNVcmCXtHI3LvuapWY3MUsT+kQWzSmsUQ1HRCObOR98RasyEEEtZ7NhlDIwS326KIfzo/z4FQ4m57\nFE0CvKFzfHUw4N6QG31DrcY7ZmYmm/YeDjWRvfdsDmXmMu/pW8tnRqNJALdBa66t1chDhYWXNJv0\nw1g7BO7jKaW0slMEPEvW8qXBgB9lGQZ4RaPBW1stWlpza7PJu8qSu8djYqpgZrk5TBRK3z2S5xil\neK3WxEDO2nd4BXCkLPnSYMBjeU6sFK9uNHhzs3lCsL1aGsrMncxyd77705TjIV/4kiiirjWj8Bld\nnSTVJr9QX/lgWTJ2ju0nG7OWItwUfHEwYE9RUFeK1zebvK7ZrLpAhpupRao0h41RROQ9JVVKzhcG\nA/aFKh4/1Wrx2kYDoxRPZRlfGg7ZV5a0tOaNzSa3NRrPKa94LpVUNyZLobNjM+wHsN7j4UVN3UiU\n4ldmZ3lruEnZaMxFsbovhBDixSUrz+vgvefPej3uGo/ZEUVcFcc8W5Z8eGmJq6NoUvO4GQKoFFjy\nntfV6zwduvp1tGY+pH48lmWTlr1GKXbGMZfF8SRwdt7ziW6X76Upm0Jt5ofynI8sLbHFGJ7Mc/aV\nJY3wmofKkifznGvjmHvGY445N0m/WHSO74zHXJMk6HDu2dDG2vmq4cnPtdtVJ8QV1+yoAp13TmmK\nkTnHR5aWeCTP2RKqTnxnPOaPu13G1vKRpSV2hxSVa2o17s0yPtnrcbQoqs59RcE2Y9ikNfekKf/6\nyBGuiiKKMM+Vr2OUYk5rPrS0xFOh49+c1vzdaMSf9/tTP7/rarVJU5hlY+eoKcUNScKDeU43VFap\nKcXjoRX5baHFekS1+j0TAuqW1rymXmewamzoHG2lwHs+vLTEkbJkW2ia8TfDIV8dDtkZRdyXZeTO\nMa81daV4JMvoO0fqHB9eWmIxHNdQii8MBnx9OGR/UfCfu1261laNfIC/7Pe58zxrwLEQqskoqiA6\nAu4P7cTPVZC/0RguTxIJnIUQQqyLrDyvwxFreTjP2WHMJG9zkzHsL0seynMuiWN25zmjkO/sYNI2\neza0iV7eROiAjjH0p1RWeLYsJ01Nll9va+j29oM0ZYMxHLeWEX+/krdBa74xHuOogublMHE5/eLB\nPOetrRZfHQ4nJcqs97w9lDP7i36fZ507ocvd1VHEOzudNef5WJ5zzNpJfWmA7cbwdFFw52jE4oox\nHcaeynP+NFRh2BKCGQ1s1poni4Ke97yq0eC7YbXahfm/p9PhiTxnGFZ8l4/bYQwPZRlHynLNOsJX\nJwk312r8IMsm51RK8b52m71FwaxSpKGMm6dasWwqxaVxzPW1Gg+vOM4oxfs7HXYlCQ/lOY/mOQnV\nimukFL8+O8u9aYqDSc3qWrj2e0YjrguNRvLwJMJTrT7HWvPN0QgNk7SdulJsVYpvjseTjZ6zK8a2\nKcWdoxG3N5vnTcvssfe0jSEL6UYWaKmqo+LJ6o8LIYQQ5zsJnteh6xya53bui6kC3StD2bVHsowS\n2BXHbIki9oc82PkQNJZUjTeaSnEs5IA+WRTcl6aU3nNjrcZ1oWKGoiqVdrAscTAJNPeXJZtD3drd\nRYH3niuShBjYUxRoqsBqucV2I/z62aLgN2dneUmS8Ego1XVtrTYJbj+/fTv/y9ISfxvq8f7szAz/\namEBqILsx/KcH6YpRilurtd5SRxXFRW853BZcshaNFVJNbxnX1ninOPbwyHPhLFrkoSNWvO09+hQ\n63nk/77dtwIOlCXvmpnhZbUaP85zakpxfUiR+Xy/T6QUB0P+akSV6mLCZzTrPT9KUx7Oc5pK8YpG\ng8viGKOq7oYNpbgnTekoxc+221xbr/ODLOPqOOa4c+wtCmpKcXWS4JVi5D3vC0H7U0VBS2tuqNUm\nzWJ+bXaWJ/Kc3WHsxlqNDcbwjeGQGrC3KDgWmpVsjyK8UuwrS15Wq5H7qhtgXVUNV5as5dmw0e6E\nnzGlsL7qRNlalZoSh2oSI+dIzsKq6nJr+qeLgq1RxK2NBhvD6/Ss5b405ZmiYFsYmzeGnnPcVq9z\nPOSBt7RmQWsOOzephS6EEEJcSCR4Xod5Y/Dw3O6DwEvimO+OxxwrS2a0RivFUWvpOccbGw3uHo1Y\nCk0xDEwqNPyyMXxtOORroxF1VXUtfCDLuKVW47WNBnvLkm5ZEoeg8lBZ0lCKtzWbfCN0Cky0RinF\nE1lGS2tur9f55njMOASkUK0E2jBPFVJEllNGlnnv+UKaUgDvaLfxQN97vjgY8LMzM3y23+fe8ZiW\n1njg/jTlp5pNLokinipL0pAm4qmC+1mteWO9zofHY0beT7rzfTtNWdCaX+10uHs0oh9ykT1VMGaU\n4sokQSvFFUnCFas6KG41hkeyjMJ7EqWqMm9FwaYoYlZrPtHt8uMsY0ZryrBJ8h+029xSr/OJbpcn\nw8bE1Hv+tNcj954tUcRn8hxLteJcUq3Sbwk3PUYprglpJ6stV0ZZXR1laxRNGnQkSnEc2JPnXJok\nvLJW47tpyrYoYiEEorn3mBC0fz/LWFkocblj3VVxzA9XdRhMnaMOzwmqz4RFa/mDxcUqAFaKJ/Kc\ne0J3vobW/OHi4qSpzeNh7Pfm5tgZxxwIAfW2cK6etdVNjqw6CyGEuABJzvM6bDSGW+t19pYlo9DY\nYn9ZsskYbqjVqkfSoZpDRJVKkXlPMzy+dr7qHpdoDWGDWkrVqntb6Lw3bww7jeGHIQUhcw6UmuQu\nQ7XxbWZ5VXnFmApjr6jXSZSiWDH3AiYb69ayryz5fpqyI8xjozFsN4a7xmN+kGXcl6aTjnEbjWGb\nMXxzNGLkXDXPEMwmSuG9JwOeKktGITiOgYTqh++oc8yGoL8IQb7ynoKQijCloUQtXPukpJ5SuJAS\n8HSe83ieszPUgl6IIjYbwxcGA34wHvNUUUzGNofA9a8Hg8l7p4BY6yqADpv34jVnMl2s1CQgXv6M\nLNUK/m1hc+Oh0M2xHzoFvq3V4nWtFnHYSLk8dqgseUurxRuaTQzVhsnCe3rWcsRa3j4zM7Uz4Xrd\nORwy9J7tUcRs6KAYwSQHe7xibFsUoYEvDoe8tdVi7KvueoX3LFlL33t+ekpnTCGEEOJ8JivP6/TO\ndpstUcS3w8rubY0Gb2g2OVCWXBpFWKrucdZ7Lo1jGkrxcJZxWZJQ+KrbmfWenXFMR2seSlOgWnU9\nEtr4zoW23z/Mcy6PY0ah652n6sDXNoaHioLL4xgXUiM8TErQPVaW3N5o8FiWsT/kVO8whpfWahx1\njiuoHvE/E0q+XRbHNLVmX/j9ylV1E/K3H0xT9EnGPPBQnvOSJGHkHHvKEg1cVauRKMV30pSEKpBc\nrtjRUoqMagX6NfU6z4YSfVoprl1OdSnLSV7vanvKkhuShKWQYhErxdVxTKI196Yp9XD+nrUYqtxh\n5z3fT1MaYR7LK9xzoQLEw1nGzfU6+8uSvUVBohTXJQmJ1hy2lku0ZndIWekYw2sajVM22dhbFLw8\nlEg7GGo635QkEFbu/9HcHH81GPBgyF9/b7vNzfU6SqnJ2I/SlHljeF+nw03LYxs28JHFRe4ejViI\nIn5ndpZbzlLZtUf+f/bePFqyq7zy/J1zpxhfxJtzUCpTQ2qeEKARCRAzNC7AGBuwMcLVLpfdvVZ1\nL9ru8qJsd62qrna32+2228sGl23AZhIzGApkQCAkZDSSGlNDZirnfPN7Md7xnP7jfhEZ+ZTvSSBk\njH33Wm8pM8679557I1Kxz3f2t3ccP8Ovuile4XNp+ozkvnGt2R/HbGs0+NXxcW7rdjkico9Xjris\nWFl4LmUZE47DdtctdNAFChQoUOCfNAry/CPCVYrrKhWuq1ROeX1FvJvPdF3OHJFDHEtTmo5DL4o4\nIVZwDrnPb+q6edNgFPHkSPy0BqZclyuV4kSS8KSQcYA9UcRO1+WaUglHmtl2rUs7rEtzYsVxOMtx\nQCQTkehuHw1DPjWS3Ocpxc+PjVHegAxaJCnwNGMKGFOKljEsCFmFPJBk1nUZ1zr3TR6RkETSMDkh\nCYM3rnuWx0SashEGiY1LWTaM+j6cpmyRivL9UcSSLCggr3Zv9X2aWnN/GLIy8FEmr2JvcV2aSvGN\nkfcIcnJ/SRAQWMsfLC7yzV5veM4xrfmP09ObBtnUxQ98Rby0M3K5zlbXxQO+1+/zVBxTFXvB7/R6\n7JR5fr/fZ5+MhdbybRkLgN+cm+PROEYBB8Tm709mZ7n4BSDQda3piCPJAKk8t7rMe7TinZDr6x3y\nRdl7T5N2GBnDJ1stHpd7sMBu3+edY2OUXqDUvwIFChQoUOD5oviG+jFjh8gDFkeSzDri+3t9uczR\nJCEWuUVdaxylOJwkXOB5HE0SkpExLWO7PI/HpRmwqjVVqUjvS9PccktrlkeutyaNZy+Vaq6xlrqc\nE3KCWdOaT7bb1NXJ5L6aUnyi1WKrNDGOhnSsZBljWvPKapWyUrRGxpZl7PJyOW9StHlqYU0pEmM4\nmiS8uVYj46RDhYKhnORdY2O4StERv2lrLYtZxrTEOG+EadflcJriwjAlsWctc1mW2wdKNXowl540\nM57jeRxNUzzyxUBdazpyzZLKE/ACcu1wVSliY3g8ivhBGHJrr8ek1sw6DrOOQ2gM/3lxEWPMhvOc\ndF0OZxnByDxXpTnySJLw3X6fLSJ32Oa6rBrDZ9ttHgpD7hApz2Bs2Rg+327zp8vLPBJF1MkJfEOs\n8X57fv5H+dg+K15WLrNqDIk9mc43l2VcJzsuy1k2XIRl1jInux6b2dHd3uuxN47ZNkhzdByejGNu\n+ydmt1egQIECBQqMJv1SawAAIABJREFUoiDPzwEdY1gQt4hng1aKX2o2mXEcDiYJB0Rm8UtjY3Ss\nZafINNrW0hK/4nN9nz1RxC4ZW05TlpMEV8a+I815ZanwRTYPW6lrzQNhyM3NJg3ZQj8QxwRac3Oz\nybIxnO37VLSmZQwtYwgk3OWefp/EWspa0xdP4bI01h1LU25uNgm0zhP/hGy/t9lk3HF4b7OJpzVP\nJwkHk4SG43Bzs5kTU9/HlSplx1rGHIezPI/jxnCJ7w/13wl51fLF5TKxUvxyo5FXjuV6M47DLzWb\nw6Yya+1JTbXgaJJwnu+jpOLdMoZJx2GH6/JwHLPb87Cis21Zy5QQ0EeThN2ehwFWjWHNGGaEoN4Z\nhjSVApF1RNbScBxcrflcu00ApzS6NaX6vTeON/xMHE9TLvB9UnIXkJYxbHcc6lpzR79PTalTzjml\nNU/HMXf0erkenLyJMLOWaa15Ko65tdcjUAo9UqGtAseyjKc3mcuPistLJV5brbJszDCd7+pSiVdU\nq7yoVOI11SqLWcahJOFEmnJdpcKNz6Jr/n6/z/SI/aJSihnH4Z5+/zmlD2ZiJ/hckyULFChQoECB\nHwcK2cYmWElT/nB5eejTu811+R/Hx3nRJs12kH+pH0wS9sQxxlp2GUPfWjxyuUdFKVZFslAmd2DI\nyAnSwThmZaAJjmMqYmOmlUJLcyFyHkse9xwbw/4k4dEowpI3vIXiquGQb5+vyXEVIWopeWrhVzsd\nlqWKPOk4nO15ZEBZkuCOisxiUgI8ICe/+6OIJ0UbPUg5zMgrq7sljlnL9Y5LVXKL5+EDR8V6b5fr\n0nQcMiGoE47DvNjYTTrO8Hon0pQvtdscTBK0UlweBLxBKtmeUpSUomsMWp6tlubDFFjKsmEMuraW\nCa1Jxb96YJ+myP8hTDoOsbW4WmOlyqql8TOVxsf1ddQB8UvYGKm1lJQi0JpQJCZVce5I5DmdDjGw\nmqY8agx9ub8djkMggTbrMSqH+XFDKcVN1SrXlMusZhl1If8DTDgOgewe1KXp9dls6DKeuXpX5HKQ\nzWCt5R/6fb7V7dKzeTT9a6tVrhQteIECBQoUKPBCoqg8bwBjDP9hYYF7w5AJrZnRmqUs4/cWFzm8\nSWXPGMMHFhbYE0XMaM02x2E+TfkPCwuUgQNJwnFpgptwHNaMYW8cc5GkAa5ai0+uz+1by31hyIt8\nn7ZECpe0piTV4pYxXBIE/PbCAk+KndoWCSX57fl5JrRmXxyzmGU0HYemJBo+Fcdc7PvcH4YspykV\nIZ1Lacr9UcSk1vy1pAGe5Xns8jyeSFM+srbGcpry2/PzHEpTtsj1HpeEwDNdN7fwIyfRVa2JyQn8\nFaUST8QxLWvZ6rrMui5zWcb+KGJCa/5ydZUTacrZrsuZrsuDUcTH19ZoSzLhnKTsTUu1/ZOtFtvF\nqq5rDBOOQ0Mq5YfimLNcl/vCMHckEfnF0SzjoShil+9zbxgSSgJgVSkOJQkPhSHXl8ssijNEWSl8\nYClNia3lTdXqM5IJO8ZQ05oL19nojWK73E8i86xpzRNxzGqWcW25zJp4fA+wZgyzrst5nseD0lha\n05oAeDxJ6FvLdeUyMWBHKvE9axnXmnM3cSh5vqhozTbPO4U4PxaG3NJu5xZ6vk9TKb7U6XC3NMFu\nhCtKJRbXhQMtZBlXBMGmJPi+MOQLnc7QL9sDPt1u84j4lRcoUKBAgQIvJAryvAH2xjH74php0SUr\ncWSIreXLEhxyOuyJIg4mySnHjTsOobV8odNhUl7vGEPb5olyk1pze7+PJa+AWvkZVO5u7/XY6bpY\n0bV2jSElT6nbG8csZBlTEneslWLScWhlGV/rdpmSbfGOHAd5ZPK9YYgj8o8EsbDTGhf4Rq/HUpYx\nM3LOLbII+HS7PZRHDMamHYeFLGNfHPPqSoW5LONYmnI0TVnOMt5Sr5MYw6Q0G7ZtHojiyFzvDkO6\nck4llfHBIuC2bpeekM7B2FYnjyR/OkmYcBwyoCPn9OR53xOGBPL8B/cXyH+/0+kQkEtsYnltKImR\neUZA1+ZJkAOf6RuqVa4IAuaMGQbBxNbyP01M5LaDG6At0duJ/LlrDBWl8gCWIOCSUoljWcbxNOWY\nNDi+vV6nZe3wszMIkKlIJfzXJibY4jiskWvc16Qy/YGpKZwXICBlM9zW79NQaug6EmjNlNbc1u1u\nKr+4qVpl2nU5Ki4rR8Xu8dWbyD2stXyr22VKFpGQv3dNrQutdIECBQoU+EdBIdvYACeyDIR8jcIl\n17BuhDmRJPSBtqQBVrVG2zwVbsJxQCkejyIya9np+2x1HA6n6VA+0Jdzlci3sY9kGWcFATNZxhNR\nRAac4/s0xcoNa+lkGR0h4zWV+ysfTxImtcYYw36p8J3lukxoPbRMC41hVa7XBHytOZ4kGGM4niSc\nkPvZIsEwR5MENiBEi8bwxmqVx+OYb3W7eErxpmqVy4KAb/d6nOG61ByHZbGjm3IcVsS7eD3dU9JU\neEKSA9ePaeB4lnGO6xJIw6QjRH7FGI6mKXV57wba8gnHoW8tR7KMmlL5eyRpkTOuSypjV0uj5WFJ\nGLy4VMot9oAPTE3xsXabu3s9mlrzC40GV69zCVmP5SzjfM/jxMCqTmvO931SlftUv3tsjANJwuEk\noa41FwQBVbmnC4OAY0nCXJZR0ZrzPC9fCGjNLdu387lOh/v7fbY6Dr/QaHDGJhXw54LVLOP7kiI4\n4zhcU6ls6rUNeWW+vm7xUFKKY1mWLxjknIclLOWacpkZ16WuNf92fJwnoogFaRA9T6wNN4Ild7TZ\nvm6BUFGKpU0i7gsUKFCgQIEfFwryvAF2i8tDZu0pzVwJcPEmBGW379M1htZIGuBilpFZyyWex2c7\nHRaEEGrgiTjmsNa8t17nm70eISe3A7rk5PkS3+fBOKaVZYy57jC2etkYfr5e5+vdLl0hiAALoum9\nwPP4cKs1TDRUwKNJwliW8a9rNT5jDMnI9RYBzxjOc10+H8f0B9Zk4kRR1Zo3V6t8Pwxzy7mRZj6A\nXY7Dv19YYK+k+iXW8pF2m/1JwtsbDTKlcicReX5GyP75vs/+5FTV8GDsAt/n6XVjmYxd5PscShKm\nHYcxIVODsYtFmuFKtdpCHuGtct/mPbLFr2HoyV1Rikt8n4+0WkBuE5gBe6OILZ5HVSk+3GpxIk05\nX7ToX+h0UEpx1SY6+G2Ow5fjGE1OelNreSCKOFMs9bTKkxTPWfe52uq63Nrp4IquOzaG+6OIs12X\nMa3xlOLdjQbvbjQ2vPYPg6Us489XVugbQ11rjqUp90URN4+Ncc4mVnxneR77koSpEULbNiZ3B0lT\nPrS6SgzUVR5Hfl8YDtMHfaW45Iew1tNKscPzWF3n/71qDLs2cWYpUKBAgQIFflwoZBsbYIfv8/JK\nhXlpOOtJ8tuU4/DGWm3D4yalkSpTeVy0tZbUWlylmPa8IZH1lMJVCtdaQmPIxH5uPRRwhuvmDWlS\ncdXk1dfMWmalsS4W0mjJGw8Dpag4Dm1jcMWD15PrdYzhqBBsve4nQyK8rQWbJwJqqWRn1nJNucwu\nz+OEPJOuPJdLfZ+2MTwex2yRZ9DQmlmtuTMM88ZJz+NoltGTRr2jWcZLSiWulmjvo5LY2DaGI1nG\nVeUy11QqbFs3dky0wleXy2xZN3Y0Tbm+UuGSIMCBoX3aoLmyIZrjQe1cyzMePDtPa4y8pmR8EMX+\ncBRxPE3ZLlXTScdh2nH4aqdzigvIemidB7AoOOV5Wp7ZgDgKF8jE+WMQTGOsHf79x43vdruEokmv\nac2M41AFvvJs8otaDQPMSzT7kuyCvL5a5Vu9HsZatspzn3UcXOBrm0ifng2vr1ToyoIuFCecBDaV\nexQoUKBAgQI/LhSV503w/okJtjsOX5b44RtKJX51YoIx2cbuGcO+OCYBznRdplyXE2nK5b7Pcpax\nL0lIgXNdl62uy54wpKY1ZaVoG4Mh9wCOrOXuXo9Z0Sq35PplYEJrHopjdsk1j4kUZLfropXiiSTh\nylKJ/VHEPpGT7HQczi2VeCiKqDkOrrUsG4OFoUb4/ijKdb9AOHK9jLwh62zPIxLXEEUuE/G0Zsla\n/q/paf621eJ7/T4KeGOtxrsaDf5iZQUtrhQtcc0Yk+r7k3HMexoNvtxu841uF19rfqZW41XVKo5S\nvLfZ5NZOh+/1+wRK8eZqlWsrFRyleF+zyT/0euyJIqrirHBFqYRWil9pNrmr1+MhGXtdtcrlpRJf\nbLd5WaXC/jjmaJriKsUVQcCU5/FwHLPNdQmFcLtKMSOE+gdhyOVBwILotgOluFSqrg9GEbV1koJA\nnDgWs4xtSnEiyziWJJS15hzPI9CaI0nCi8tlVrKMRZGMXCjWdctZxuwGsoijacpLgoAjacpCllFR\niitLJTLypsKJTbTN1lqOpCnzYjN4tqRODsYOpykL68aeiGMa5D7gK1lGVeVhP3NpSmgtgYwtpunQ\ngtCVpr1/Oz7O7b0eh5KEs12XG6tVzvQ8PtZqMb5unuNasy9JMKIn/2FxdhDwa3K942nKhaUSN8gi\n69mQWsuBJKGVZUy5Ljvk31GBAgUKFCjwXFGQ501wNMs4kKacK9vpffJ46puqVZ5OEv5mbW1oHaeA\n11SrnO15oDWX+j6XjmzlH0tTZuTLfRCUMcCcNOfdE4aM+hP0gRPGMOU4LMo2+BnrUgsnHYcHez0O\nj1QGn8wyWr0eP9ds0klT+jCsch7PMirAhb6PAVAKX441UhGdkmruwAnBAgeThBnXpaoUY67Lr09M\n8Ovrnte047BmLXPibQ1wnFzz3XQcPra2xmfb7eHYHy8vg7W8tl7nvjDk7jAc2uh9s9dji+tybhBQ\n0ZqbajVuOk3Fv6o1r67VePW6sTGlmEtTUhiS0xVjCIxhVpoRRwNYrLXMG8MWx+G7YTiM9E6t5ck4\nZrvnMSONkaMYVJBLSvHlTod/6OeKdSXv88Ab+5B4Up8nxxlrhzrmjTCmNXclSd5cSW5B90Qcc4br\nDm38TofEWj7davHwiPvElHhxV7XmllaLR0fGZsS7u6IUX+p2aY9U0R9QipeWy1jgo2trPCFOM0qe\n63sbDcYchy2uyzvGxk57D6G1pyw6ImuHi6ofFTs874eWq7SyjI+srXFiJHVyt+/zrrExgk3ehwIF\nChQoUGAUxTfGBkis5eNra/hKsd112e66zDoO3+j12JckfGxtjWBkbMZxuLXbxZJbk81J4p+1lrUs\nw1eKt9ZqOREeGWsZgw9cHwScztgrk7lMCnEbHLeSZZRVHioxIM6u/ChgzloqxtBF5AicXCl1gddX\nq1hycjiQbKRCBN9Qr3NcSGJNdMqGnKxPb1Ld2+l5Q0cPT34suZ2bktS8cX0yna+sFH+yssLeMOSr\nnQ7TjjN8nhWVpx1uJofYDJPSoOeRk9iakLjlLOPt9TrIvCAnsgvGcLbncXEQcCJJ8NXJZMK+tawa\nw8sqFYy1w3s01nI8y7goCJjPMr4njXvbJYwltZZb1tZ4aalESr5TAbku+3iWcXmp9IxGu1GMa81c\nmlIauYc10alvFlt+f7/PnjBk28jzXDOGL7Xb3Nvv80gUnTK2bAxfbrdZyjKWjaFEviipKEXXWo4m\nCff0+8M0wMH9zacpX+92N30fXl6psGxOJhMm8qxvrFT+0T2Zv97tMpembJP73uY4PB7HwwVPgQIF\nChQo8FxQkOcNcCxN6Urj1ACOUnjAHb0effHenUtTDiUJSrb/H49jfrHR4GzP41CaclBcLW5uNpn0\nPP7z9DQ7PI/jWcaxLKMM/M70NJ/dxGbrm90u72022S6NWU8mCXWleN/4OF/tdIYuHaMWdwr4QqfD\nhNb45IEbMbl/9ITW7IljXlwqEQCR/ATAS0ol9sUx50iD3IoxrBhDQ2QIR5KN40AeiiLGxe5uaA8n\nLhef73SGVnyp6MAr0jz3lW4XDUNZAeR+wqG1HBIpijGGg3HMidM4nQxSBLvm1PTBC0bTDo0ZRlzX\nXJf3j4+jVR7gMp9lXOD7/N70NEezbOjZvJRlrBrDGbJwUsAvSRLicbGquywIeGu9zgNhSFWs+wZo\nas2ceHO/a2yM2FqeThKOpSlXlkq8eRPtPORpgRcHwTDsZS3LONt1Kes8MXIj3BeGjI8k90GeWvhE\nHHNXv8+41lhZFKQ2Ty3cG8c8GkVMy1hs85CZaa1ZMobv9ftMaX3KOWcchz1hOCTGp8OLSiXeVK2y\nKsmEK8bw6kqFa58laGiAWBY88SbXeC5IrGVPGDIzIiFRSjGl9bP6URcoUKBAgQKjKGQbG2CzBikL\nrGQZt3Y6Q1s5h9wZ4rpy+ZRGM0tOugcUXCEVWanyaqWeNYnNWEs7y7iv32e/bJuvZRk3if5ZkZPU\nwYwVedPfsIGQU1PbBt4GY1pzURAM7ehmHYcxSa+LreV4mtKS5xBbS/U5bG27UrHty3F1acAz5BXX\nYyNEqDzSVMkGVUgL3N3v88fLy0MrsvN9n9+ammKr63IoSfhcqzWUU1wcBPxMvY6R+zvH9+lL42Og\n1NBm8Kwg4Oog4Ok0xVeKq8tlqqJ77hjDCdH5Qv4eVYV0nR8EvN/3WRFSXHsOz2TwPuvBeyTv+bPV\nXS251OCEPDNFnkZZFdvAzY57RhLiyNh8mnI4TUnFMeUMx6Es91fTmmlZ1DgDpxXR5/8oUEpxY7XK\nNZUKa1lGfcSfeTMYa7mj1+NbvR6pNLy+qlrl+nK5SBEsUKBAgQI/URSV5w2w3fMoS9VygMxaEuAa\n3+d7/T598gfokMsrHoljwizjY2trPJkknOm67HJdOsbwV6urLCcJH1hYYJ/43W53XTrW8nuLi7xp\nk0rcNeUy/35+niNJMkz1WzaG311Y4HXVah5pLORKyTwBfqZeZ1G2+QeSjpQ8lvrFQcC+JKFlDDPi\nGrFmDE8lCReWStwfhnStpQbUyK3HHogitmzSpPaSUomWbNGXlaKs1DDU5fWVCmvGEBszlHR0jaFr\nLW+oVjFSBR2gZwy+UjjW8p8WFugaw7SEbzwRx3xgfp7lJOGvVlfpGcNWeS6PRhGfWFvjYt8nIidh\ng0CSjjFUJKnvw2trpEpxYRBwlufxYBTxmVaLGvADiVUfJBMeT1MeCcOhdtpRiilxpBjg8iCga+0p\nsdlrxjDtOMTG8Ldrazjktm7bJBhms7AdyMn+njhGyVwqSvF0mvJ0ktDYhIBeWSqxIhKfARaN4Vzf\n50xJLXTknGXZLdHW8vJqNY9xF7Kq5bNyvu9zbanEkjk1CXHB5AmX3nMgs75STLvucyLOAPeGIV/t\ndmlozVax5vu7Tof7f8QqsacUl5ZKLIz8e7ayMHjxJjZ8BQoUKFCgwHoU5HkDeErxrrExQms5mqYc\nSVNOZBmvrFTYE8dknLQzG5VKfLrV4nCaMqs1WkkyoeMQWcvnOx3mJAxiMNaQZLuvbiLb2J8kLI8k\n8CmlGNeanrWcSFPeVKmQkMcz960lBm4sl7Ej1naZ/Az+/r1+n1khwm1xnRiEoXy/16OkNa5SJPLj\nCgF9YLMIZKXYKSEeXWtzMgmc6/ukWrNDLPdGx3b7PlXH4XXVKnNZxlFJmutYyzvHxvhmr0eCuHZI\n9XZKPIi/0OmQiv3cYGyQTFjSmldUKpzIMo7IOUNredfYGA9LQM1AkqNVnlr4eBzzvX6fstagFJEs\nlkrki44Dm0hWLgwCri6XOT5yPZTiHY0G94QhnlLDyv0gJfEHYXjK4mw99kQRZaWGMooEqJIHmaxu\nEgjy4nJ5mFo4eJ51rfmZep21LGNGa0JOph02HQcDvKvR4FzPY17sB+fSlDGt+Z8nJri+UuFc3z/l\nnJNa84ZnkZ78qPhOt8uk1sPAFF8pJrTm288jRfD11SqTWg/nfyzL2O37XP8sITcFChQoUKDAKArZ\nxibY6bqc73l8vtMhtJarg4AXl0p8eG1tKL8YyCEG9dhFY9gJPBJF7EsSMnKf5q1iY2eNYc4YVkWu\nUNcax1rmyEnteiqlgSUhWAOSa8m317GW+Szjf9+yhbf0etzSapEBb6vXuaFa5fcXF/FlngN5SZlc\ni7yQZTS1JjJmSArP8jwaWjOfpvjkgR6rcu1BTPSKSAju6fd5IAzRSvHSUokXSdX5fN/nsiDgqCQm\nnul5dIxhMU25KAi4vFTiaJKghWi3pfp8dblMyxjuFKu61wpZu6XVQpGHYHSF4I8JCT2eZaTW8v1+\nP7ejIyfjDVlY3FCp0Msyvh9FVJXiDdUqOz2Pu8MQDeyPY+alqXCH56HFcWNc5R7ZkTRTlrVmSWzm\nzt3gs6KV4i21GleVShwTnftu36ek86RAyO36lrKMQCnOFKePrjEspyl/u7bGI3FMU2t+dmyMm6pV\nltKUCZHA9KzFJQ9u6djcepAs485ej6eShAmteVmlwtm+j68U7x4b41CaMifE+Rx5fc0Yzvc8ns4y\nlsSO7gLfJyRfMP7x7Cx39fscEHeVGyuVoSPIzY0GTycJi1k2lMQ8l6rzDwsrDZrrdzlKSp1SOf5h\n0XAcfmNigv1xzJq42OzyvMKqrkCBAgUK/FAoyPMm+MPlZW7t9agqhQ/cHobsnZvjfc0mH15bI+Zk\nyEZCXoG+1PN4MAxZSFMCsePaG0UcSBLePznJF9ttYk6S7SUhhG8LAp48TTOcAS72PL4fx3TSdEhW\nFkXvfIFsOV9VqXDVugraZb7PJ8grzoM3OpRzXub7fLLToStuHwCPJwlHs4xfbzT4WrdL11o8IU6L\nSYJSinNdl4+trfF4HOeNZ8Bn2m0OJAlXBgEZuUvEhMzLWEsbuKhU4skkYVZrJiVRLrOWFrmN2kfW\n1jggJDCzli91Oiwbw4W+z1c6HRxr8eV6J5IER2su9Tz+QJ5noBQJcE+/z6zr0tCav1xd5USaMqXz\ntMPPdjqsGsMO1+XjUYQi113HwA+iiGnH4ZpSiU8nCU2lhlXPRCQx5z9Lgp1Siu2ex/Z1v7fd8/hi\np4NLTgDb1nJvv8+Zvk83y/hfFhboGUNNKY4aw/+xtMTxJOFc3+fLnQ6BNKoa4EiS0BQ3kj9bWaFn\nDE2tOZhlPLa6yjvHxrisVELJ4mTnurlscV0+1evhK0VFKRJruTuKuNT3qciuxg3VKjec5v60Upzt\n+5y96VN4/lAqT1w8miSneFmvGsM5zzNF0FOK8wuZRoECBQoUeB4oZBsb4GiS8M1ejxmtGdOailis\nzWcZT8cxY+RkOSMnNQPpxosrFVrGDDWjg0jmxFqORBFqXWPfoI6WbVL9KosvdEKubc7ECaGsNds3\nsY670PepKjWUbGTklfKybIGHUs10VB5h7QKh6HYrWpOqPMUws5ZMZAehFa9hSYyra80ZIkEoac35\nvs+RNKVtDGsiYbimXOalpRK7fZ8jkti4Ktv/15XLLGUZTycJZzgOVa0ZcxzOcF3+od+nKVv3qcrD\nSBKZS1NrliRZbvRZe0qxagz3SoDGdtelojUNx2Gb4/CdXi+3zpNnNFTwSvPcG2s1ZhyHuSyjYwyr\nxrBkDP+qXmf8OYRwnA7WWpQ9mXQ4iDZX1vLZdpue6M4rOk9lHFeKW9pttjsODjl5H9y7VYotWnNf\nGOZab3HfmHAcJrXmq53OUPO+EZTc72A+Subz/Pwsfrx4bbVKSu6B3jWGuSzDyOsFChQoUKDATxJF\n5XkDPC6uFs46UusB94chN5bLPBSGHBRXi3HgJdKENyCscyKxaCpFA3ggjvOEP5sn0hnyKm1JKR4I\nw2cSOnJC+HAcc0UQsJimPJkkGOB812WL5zGXZVwA7Itjbhef6esqFS4IApaA60oljqYpB6SqfZ6k\nqj2WptREyzxwsZh0HFJgb5pype9zLE3ZL5KO83yf7a7Lk2mKJtdXr8g5J4VULmUZ72o0uK3T4bv9\nPi7w5lqN6yoVtFL8YqPBh1dWuLXTwVeKtzcavLFW49ZuF8cY5oBjSYID7PJ9FLAvTblWnuvhNEUr\nxcW+z6zjsCeOaZJX/VeNQQMz4q98fxxTUoqWEHVXKSalivlEHHOp73M0yzgsns4XS+NbohR/MD3N\nH62scF+/T9Vx+O8bDd4m3tCbwYq13pEkoSwVzqros18kriYn0pSyytMOM6V4MIqoKEVoLZG4glS0\npp1lHEpTXlWp8EgUsZBlVLXmsiCgpDWPxvEzmgbLWnNcFid1rTmQJBxPUxpac55ISE6kKVeXSixk\nGStZRtNx2CHSmr61VDdZxKXWsj9JmEtTJhyH3SIFeSFwhufx6+Pj3NXrcTRNOd91ua5S2dRnvECB\nAgUKFPjHQPFNtAFmHGcYSDJqjZWQb8Pf1+txRDSxCmgDP0gSfrFUYj7LTgk8WbKWFeClSrE3y+gK\n4YbckSFUiis8j6fgGdU/A8yK9njZ2uE2dttaPNEtf2J1lY+2WsNjb2m3eVu9zssrFTzH4fog4PqR\ncx5LU2Zdl7bMc5gGmGWUyJPjfhCGHE1TrFIo4Kk0JbaWl9Vq3Nnr8dhIw5pKEmakanxXr8ft/T5W\nntXXez3GHIeLPY/fWljgjpFAioE84cog4ME4PiW97+E45lzX5SVBwN8lCQtZNqyOPhbHpJ7HBb7P\n7WKrN3iHDqYpNWC743Bbr3dKWp4CtnkeVzgOX+10WBKLPoDvdrtcJL7X/9/qKg9EEY7ojT+ytsY2\nz+O6TRrLMqkijy6Cyp0ONzebjGvNbWlKzxi0UkTAY1HEGZ6XN2iua0RUaUrgOGzzPL7d7YI4VQAc\nSlPO9DzOcxwOJAmjM0qEfDucTAMcWCY2tOZ9zSaTjsNRY9jt+8PjYmuJR2Qqp0PfGD66tjaMa4c8\n6v1Xmk2amziwPB/Mui5vOU1qYYECBQoUKPCTRCHb2AAX+T7n+D7zxgy9iNfEZu211SpPSkNcID8O\nuX65lSSnTQoceB0PiPPArm3gyXytRCCfDi8ul5lP09w+TeWJfwqYS1MSa/loq0VTn0zum9Saz7Xb\npNYyJVKTwT0T5NGTAAAgAElEQVQsSLXxqlKJHjmx8uXHAj1y4nlEGvBqWlPVGm0tB0U/PC/3Pkwf\ntJa5NCWzlq93u8yMpNA1leIz7TZf7fW4o9ejRk7kGlpTAj7aauUVWWncq8r1sJb9Qm6HY6LTBdif\nppS1JpZnOCCNljxBcZfrspBl+T0oRVU00YNq+XyWEQCVwTmV4qk45p5+n++HIdNaMyPP01eKP1xe\nJt6kWe3RKOL+fp/tI8l9DvCpVosxrVmUJsy63F/XWkJreVEQ5J7Y1uIrhWstfXlGWyWNMhg5rmMM\nGXBjpUJkT6YdJuK8cm25zINRxONxzHbHGabphdbyxU6HGysVutYO0w4Tm8eE31CpbNr8d2evx8Ek\nYZucc5ukFn71Wez2ChQoUKBAgX9uKMjzBtBa8x+np7kiCJg3huPiMPC709M8Hsd58xcndcQOOYn+\n0iZRv98NQybFrzfhZOLflNbcFoYEPDPcwgfuiyLO8n2mdR7PvCqJf+f5Pt/s9XICPEJ8XPnz3f0+\nNzebnOW6PJ0kHEgSdrgu72s2eSSOmRACO0gYLAGTWnNrt0tda8paExpDaAxV0Td/u9fjXN+n4Tis\nGjP0Mj7H97lHPHgdcheJnjEEopv+UquFUgpH9N/pSAPgFzodmloTjFxvzHGoKcWtvd5Q99wTwjkm\n/su393oEnLTiSzm5EPj7Xo8LfZ+SaKBb1rLDdTnD87ij32dCaxyVx0/3rc2vrxRfaLfzc448z5rW\ndI3hIbHpS2SxMGoX92AUUdWnJvA1HIeVLOPxJOHSUglXa9oijzjH82g4DkvGcKU4PnStJQTOcl3O\ndl2eSpJh899AVnGe51FSuf3hL0pV9liasmoMN1WrvLpa5f4wZHzdXCa15kAcs8V1eefYGNnIca+p\nVHj5SFV9NU15KAyZH2lgvV8+uxl5iExs82TCR6Poeaf/FSjwk4S10DkB7ePDVoACBQoU2BSFbGMT\nuEqxOwiGDXrTWtPUeuiUYQfkRBq5jGybbwRN7iRQVQollT9PXhtUTrc4DolopV2gI/+11hLJ7ypy\n4p3xTE32KfMn35Jv2zwtbkDCIvm7liZAR74xSlKBHUR9G7kecq1BhdfIeQcrr0iaDAek+R+ShL7c\nX11rJh0HRxr+FkTrPZiflv+addcb/I4j9zqouAJkxlATH2rIyfLg9z0h6x7QEUmHlvcospbK4Llm\nGa3BNYFIJDDeJo1zjlI8EoZ8od0eJjhe6Pu8dWxsKI8YxSBF0iG319tZLhOPSCuOZxlaKc4MAi4p\nlehYS0kpPJXHhrvkmvidlQqxtbhKoa3NjyN3MLkgCOgYQ2nEE9k5zT2MNqleVipxcRDQXXecMYYP\nra3xd+32sAn26lKJ35yaQgMHk4RjWZafy1q2SXhJYfRW4KcV7WNw7wdh7VD+9/pWePG/gebOn+y8\nChQo8E8bReV5A1hr+cTaGk8nCTs9j3N9H1drPtJq8ZJSiYycNDpCaozNQyx+bhM3gGtKJXqy1V5S\nipLOo6tbxvBz9TquUkTG4GmNL1U+S+7bvD9JaBvDmDoZrPJUHPPqSgUHCEckBZE0z11dqfDXq6us\nZhlnui47HIe2Mfz16iqX+z4dYwitJVB5AEpoLR1jeFO9TtsYImOGspRQ3CdeWamwL46JjKHhODTk\nnPuThMt8n6fimMieTOdriY/0qyoVYnKyOiCPg+r7W2s1WsaQSaU6QCrX1nJjucyyEG5fLNsGftOD\ncBhDvtBx5D0xwKurVZ5IEqxSNCR2fD5NOZam7HJd1uRZeTKXiDxN763VKgmc4lixJnZwk1rz8VaL\nQCm2ui5bHIe9ccxnWy1eJO/t6HHL4oZxg0gljDxrVymWjeEM1+UG8bdGKcYcB19rloxhp+fxsnKZ\nNUn1C+T+Fo3hbN9nTHTGenDcyCLqpaUSqyI3GmBBPLgHns3OaY77cqfD59ptxrRmWuQ/d4Uhf7q8\nzJTrsjdJKJHLYCpK8WQcU5IFR4ECP23IYvjeH0BvARpn5j9RO38t+dGzeAoUKPAvAAV53gDHs2yY\nFDiohla1xlrLPWHIxUGQVyzJCVsGbHMcDm2y73c4TTnPdVGyRd81eXT2Ls+j4br8D40GCTlZWzOG\nPvC2Wo0zg4AzPA9HKTrW0hZitN3zMMBvjI/TE+3qXJbRtpb3NRpk5MEqE6PJhI5D1xj2xjG7fR9D\n7pzRkyrpbt+nZQzneh52ME9rsVqz2/M4JPZvlpOhLY5SbHddnkgSdnhe7u1sDB2pcG9zHA6ONLeN\nph3WrOVIkrBrkD4ooSlK5eEdTyUJNfJFxCBlzyGvaIfAVscZLmQG2YcXBwHHsoztrksyMpeSUsw4\nDveFIS4nrQIH1WcFlB2H11QqLBrDvKTsOcD/OjXFD6IIR6k8gRCGiYaPxzHTjsONkmg4SLAra83P\nj41xYRDwsnL5GWNvHxvjklKJ6ysVjmcZx4Tc13QelHJpucy168bGtOatz+L88aJSiStLJY6PpgE6\nDj/zLMd9qdOhJpVvyAn2pNbc3uuxnGVsdRx68jy71ubR4+sWDAUK/LRg4THor0B1BmTTjcokxG2Y\ne+gnPbsCBQr8U0Yh29gAffECPpamHE5TUmuZdV2qSrGcZZzpeUw5Dg9J1PNZnsdWz2NBGu088qrq\noDkwBVaM4dIgYCnLOGTM0Elju+PQMYa3NpucMIavdDqkwMtKJX51fDwnW+TpgAekCrvDdakrRdsY\nrqtU+Hq7zfejCAO82Pe5oVzmiDF5CEa/z0FxdDjT85hxXVrGMOu6pMYMbezO9Dy2ylhTazJjaMvz\naFrLuNa0pOLsK8Uhsa3b4br4oi2echzO831WxR2jniR87S//kqdKJSbe9jbqnseKMSilmDCGhz/1\nKb6cZZz3nvdgXJfDSYIGzvE8plyXedE/u6JbVjDUKy9Zy0VBQByGLEm1/SzXZbvjsJxlTIjm+Hia\n4irF+b5PWWsOWEuZ3H974NQxCC9ZMob3T03xljjmB2FITWtuqFSoas1DUcT6eI2BjCaUps+lNOUH\nYUjTdbmpUmFKFi4XBAHf7nZ5JI6pa807ajUmdR7hfl25zHKa8mAUMe66vLpSYUIWbW+p17m2XOZE\nmlLVml2eN5SrLKQp3+71eEosEG8sl7kgCHCV4ufqdW6oVJiX486SxddmaElD7Chc+ey2sozLSyUi\naTYMZAfkhKQ8nkhTbut28wWn6/IKSTt8ofB0HPNt8fI+w3V5RbXKjucQoLJPjpsX15JXVipse57B\nKwV+OpF0T/+6JSfQBQoUKLARisrzBtgiRO6ROCYV3ezhJOHhOObiIOBwmrIvjpkR94GVLOPhKOKV\nlcpQX1qW7e2BDvqaSoU7+n0OiGbVI/eCvr3fZ1wpfnd+nq93u0w6Dlsdh/vjmPfPzdFQivujiCeS\nBG0tnrUcTBLuCUNmlOLmo0e5M4rwyJv+7olj3nviBOM2T7LbG0XDOT0eRdzX77Pbdbm/32d/kuQS\nEqXYH8fc2++zXSm+E4aMfn+sAreFIeeKK8XhJKEyOC5JeDpJuNT3ycg1yLOuy3iacudf/RXzjzxC\n9MADHPzUpwiMYbvnsQU48MlPsnrvvUSPPcYXP/QhDnY6lEWysjeO+UG/z4t8nxNZRkt0zA4wb0ye\nPui6fKfXY9nkKYkOuaXeXWHIbtflzl6Po+LjrIAHw5CHwpBrgiCvYNs8DKasNamQ6Gsk/fBc3+ft\nY2O8vlbL3T/Iva4766qsoQTiBErx5ysrPJEkbPc8PODT7Ta393ocimN+c26ORyV+O7WWD7VafGht\njdUs44Orq+xPU3Z4Hq61fLzV4q6RxtNZ1+XyUimXDqmTCZN/trLCw1FESSmW0pSPtFrcJ02bSqQl\ng+OejTgDXOL7tNfdX1sqzJcGASvGMKY1W1yXccdhzRh2eB7zacqfr66yTz5Lx5KEv1hd5fEo2uBK\nzw9PRREfWl3lsFzvQJLwwZUVDq2z/FuPx8KQ/7q6ynE57qk45s9WVzn2LMcV+OeJxk7Agh0x0bEi\n9m+e9ZOaVYECBX4aUJDnDZCIdZiSZsEUhrrbcEDklBo6RyAE6lzf53LfJ4Jh8EVEHpRyne/Ts3Yo\nGVDklb0M+EK7zUNRxBZJmiuJ9dyxNOUrnU7eMIY01Akhz4DPdbsczTIa5JVUX2sawEKW8bftNgmn\nOnH4Muf7wpBY7tHC0LEjAT7Z6ZzSYDY4OgP+W79PIMcMHC4GNmuzrstlQcDRLGOh1+Prf/EXPPXw\nw1x61lm87Nxz4YEHuO/jH2e512PPxz7GkXvv5aKzz2b8jDPo7N3L0sc+hhHCNXDXWJRK9KjEQgPa\nWv4hDHO987rn2TJmODaIF4e8mbBtDG8eG2PKdWkBPWNoZxk94I3VKls3qZZeFgSc4bocSVPWsoyF\nNGXJGN5cq/FQFNE1hi2OQ6AUda3Z4jh8q9fjk60WoZBQX8amtObv2m2+1e3SN2ZoiTfmOGxxXb7R\n7W7qYnFXv09C7kfui657Wmu+3unkn8cfAe9pNilrzbwErSxmGbG1/Nr4OK+s1SgrxfE0pSXWggnw\nxlqN23o9PPKYdV+kQQ2t+Vq3i30BJB1f73apK8WEXG9Snvk3uhuUEsl7GL7W7dLUmnE5bspxcIHb\neoXA9V8i6tvg7NfAytPQXYDeIqwcgDNvgPEXOoO+QIECP9UoZBsbYDHLmHVdZlyXfXFMLFZnTcdh\nXxyzxXFoas1jUUQC7JQGshNZxl9v2cL/ubrKV8Rr+cog4D/NzPCZdhuXXDsdCakYNMA9FsdDXfIo\nHBim0Lk6j6S2wLjjYKzlEakq962lJ04IZXIyvHdwnFIsiq3ahOOQGsPjSUKZnFwui5/yhKTz7RMC\nqznV9SIjDyg5v1TCJfdf1sCWICC2lmVjeHu9zoRS/N8f/CDzjz7KS88+mx2eh1KKt15wAbft2cOT\nBw+SLC9z/e7dXBQE3NnrUdu2jd7evTz1N3/DzHvfy6xowx9NU2aAPtAiJ8izYnH3WBwTkDcLRlI5\nrond3YNxzKRSWCHMmpxo9m2e7vg3W7fywZUV7g5Dqlrzc/U6b2s0Nv1MlLTmvY0GX+t0uDeKaGrN\n22s1LimV+PDq6tCDegBPGkkflcTBZ4wBD4sU5IEw5KikU15aLpNYy1qWbZio93SSMLbunCWtWZHG\nzh8luOQs3+ePZ2f5dKvFE3HMNtflbfU6F0k1/jfGx7mv3+egSDNeWiox7bocTBLG9Knr8JpSHEtT\nUniGFOT5wFjLkTRl+7r7a2g9rDz3jeExSWXc6rpcEARDj/P1cfYNrYeSpgL/sqAUXPpOmL4IDt0J\nNoMd18HWK/OxAgUKFNgIBXneAA0hIsdFD6zIG/6WjeElpRJ39HrsG/nSfTiOOeY4vKFW4xFJk3ul\nOG9kwF1hyJlCCB1rh1IAyL/sd7gue9P0GYmGRil2ui4PRlEepiE4kWX4wOVa86C1jNbO2jLfM3yf\nA93uKaEtJyR0Y7vncU+/TzTiVXwsTSkBZ/s+J+KYkd3MoU3cdtGHzrousyNE5FiaUleK23o9vt3v\n45XLGGt5Io7zpkHX5WCW4ezYQXVxkfLOnZzIMsbluA4QG0OlVCJWiiPi9HF9ELCH3JkD8kXBvDGU\ngXN8f6hHVzLWET31WY7DnYM0PCGqi8bgAFtdl2nP4wMzMxu9/adFavOgkYdEItMyhk+325Sl6r4v\nSRil35k0Ye5wXe6X5MPRMcitCf9ybW24mLLAvnaby4OAmt54Y2jWdXk0DIfuGZDvlrhwyms/LLZ7\nHv9ucvK0Yw3H4aZa7Rmvz7guS2lKY4TQhtbS0PrH/j8YRR4j37f2lMVKV/zGl7OM/7qywpq81yn5\ns7q50aCuNX1jhg2fg+NmN1igFPjnD6Vh64vynwIFChR4rihkGxtgTGtWpRmqqnJvZhdYyTImtOZg\nmqLkC7yqFD55tXrRGD7XbjOuNVtdl62uyzbH4c5+n/N8nynHyf2FjcGIW0WgFP9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U4MwP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OIwOuq3WS5z3q67jqBmbMwvK5U4t9ddR5B17JjfllJsUDzguaJYJIBxXV67p4cg77bbmEGc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vVOtPJJ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\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ERpiSJFKLdFp3o02fTn4+nN+0G71OJztHYzzoRJuCorpOWW+8ze+rzYSiuk516LZrVCFf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\n+LdfYuPmFmfO3MP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QvPN8iKy1XN34EkV9FSXbqNDVu77xX7DWUjc71KaPEjlK5ljbUNY3\nSNOT1M1W8A57ZLe1DVV9gzQ+wbi4EAoz7+F1rmFSXSKOj4Z83j1rBhiMnZAlx5mUl7G2QJIiSLCu\npqguB9gHxHHMUu8BlnsPzQpn5wybu4/RmB2y+AhZfARtBmz1H0Pbks3+YzRmlzRsa/Qum7uPIUTC\npHgzFJZ+ndbVjIs3ieM1nCvffr3cmDy9099LuD2Ah7UNCEmndZaq2UAITRqvkcYrOAqqZote+36E\nNCERQnr4jGsAS6d1F5PyMmAC8S9Fm2F4LWFz91GkMHTyO2llZyiqa2wPHqesNrix+V8wriFS3ZAy\ncpVrG3+CIGFSXQ65xzGCmCYM3nXad+PhKb6D75zveAvwHdtwM6FkipRRgMm0aed3YW19oJuqzSRg\nuQ/PIm1lpzDOZ2krmYahvwlRtMBg/Bpbg0fBef+0IKGornD5xr+jk9+FtZW/uRBRAPYUJNES7fx8\nsGnsHVPbEWmyugc5EVFI9nh7EXu7bf3R82wPvoEkCskeKYPRs2zuPkorOxOIjXvn3pgheXaSKFx3\nQYQSGUJElNU1fz7fi7Sz76D645cYjV8mkm1itYBABm/41ge9tLnmmmuuud6D5sXzISrr69TNFkru\no+zJHIdhZ/QEkeoENPWUMGi9H7je8tuE2mexsCjVYzB5MQwYqlk4nB+EE/SHfzl7Zc9+4YuL4eRl\n3z18G2EwCkXk7VXVm2gzIlbdQLYTIRliwmj8KtpMDmyLVRdtxvSHTxD62/vW6b8qW7vfOPT9RsWL\n9DofpjHD0G3cwdiCpe7Hca4JMX4ueG5L34VUPQQKJbuA3efthjhapayuhSQOAcL488cH6A/Hz+Gc\n2UfuE0SqR11vsj143FsEZD77/JTsUNWb4XpOj2n3jolFuAQlPUXQ3zz4tWTpMdJkmXZ+lsb0qfWO\npwjiWO59nFZ2jHZ+5sA2gKXex96xSGxlJ8nTk+h9+wkhWe49zPbgm+DEPlqeRJBR1Nfp5neRpUcx\ndjQjE0oZcWTlp+m07iBPjvq1NJ5WqWTKYuftA4t/Ve2OnkSIZG8tIkLJDv3x87Szc7OIwjrQMWPV\nYaH9IayrUFEH62pvdbG1v6F0zQ+0bcNazbh43SPChbcp+ScoCaPi9Q94dXPNNddcc70XzW0bh8iY\nESAOxLyBL3Z100eIlEaPsW7qZ01oZwtoO0SpHOcMZf0WzlmSeJkk6mHMECDkKwdrBgqQmEB3cwg8\nKdBBSETQZoAkQkjflQTfiXROY8wIY2pubP8Fo8nLALTzcxxd+akQp3a7ws1hzNgT6sor1I3vhCXx\nCpFsUdsBIMKwo7c1+MHABuOm6Q6SPRCMt6vUuk+crFJVfcrmKgJBnt1BEi0zKS8SSZ8RXdXbHigS\nr/vzYEI7O0tZ3aA2W574Fx0hSZZoTB8pE09CtAVC+Eg9T1vsY0zNYPIk1vrPK1YrpMkRoI+1jom+\nzpS8KMiRMkabfhj2q3G2BCRR1MFZi7ED2tk5n69t/HBgKz1BpLo4V7PY+Sjt7Cx1s4OUCVmyPrMg\ndNv34ZxhXF4mUhkLnQdmFhljSkbFhRBNl9Fp3UmWrCOEZKF9PzjHpLpCrNosdD9CHPUweuy/KWaC\n93TLMEToMK7g5PrnGRcXKOu3iKMOnfweosjDQXqdB7DDpynr68Sqx2L3QaKoE75PY0aT16maTWLV\npdO6MyC/3+Hvg50gRXzwRSFx1uPZ1xZ/hKrZ9P541SJL1mY3kO30LNaVGFuhggVH2+E7vt/3u6xr\nQj76QXy8FPEefXOuueaaa67vS807z4coDVFy9hYvq3OGPD3DcPL8vsIZoGZcvkIkuxTlVcbl5RmY\noqpvMiou0M5O44tmvW8/AzRkyYmQIjGNlpP4ok+Tp6cwrqIJBT1IGjP2sIt4jYvXf5/+8IkAXqkY\njJ7ljau/h2RKyNvr8Dnny/M4XmNSXaaormBtg7UNRXXFx87FJwAbfL1y1mF3GFrpsemRmBb+U89r\nKz3Fxcv/irJ5E5+QoZmUr3Dh2r8iirqMqwuU1VsIAQ4b3u8yabzOuLyAtn2P1Cai0jcpqqtk8bFA\nc/QI8WncnDYT4miVYfES1g6Ypow05ibj4jXSaB1jd8P19J18xwRjh6TpcbTpY22BQ/jEbd3H2JI0\nPsqofB1jxyiZIoRkUl6mrG+EJwqCJF6i0zpHKzs5K5yNrdjc/R8U1VUi1cY555Hb5UWMrdjY/Qqj\nyStY21A322zuPsq4uIgxJZu7Xw1FbgfrGrb6X2dcXCKOF4EqfF8cYLBugnOWLDmKlJJu+zxrSz8c\nimNfOGszZmP3K1TNBrHqYm3F5u5jFOV1tBlzc+f/Y1y+gbM+wm5j5ysU1Y13/vsQr2PMQbuOdRWR\n6np6pZBkyTqd1jny9OisaEziVazz1pY0XiZSHT9oGS//QNs2VEipuTUqUtuCNFn/gFY111xzzTXX\nd0Lz4vkQJdECvdZ9GDtE2wJjK2rTJ456CBmxF492UDe3v4a2hfehBu+ykBHOaZrGd3RvJ6mSfdum\ntg2vOFpCiRRva/A/AouQEY0eUDWbCJH5rp5MECKjMbtMyou00pM0ZgdjygDi2CFLj/tesW0Cwjn8\nILG2Jo67CBExjYhzIQJPipTVhZ9GMI2SM0xTLqTIaXQRoBwRQkQeI01Eo3fZ6T+FszpcOxneV2Fs\nSVnf8HaNfWvBeQ+vsfVtrpkA5xiOX8MXzXLfDzhKhsXFQz5Zj+F+uxxC4LvwzoTib2+djRkfkpnt\nNSkvoc04kPtSItUiUj36o+cZTS6EYn8RKRMi1SaS3bDtdYwtiKOFfds69EfPEcvuvu/Dvu/KLake\nt2o0eR3napLZMTsomdMfPcNg9Iq30Ki9bVLm9EfPvqONYnXhEYQQaDP0GedmhHOald4j70gY7HXu\nC2TCQdhviEPT63z40H1+ECSEZKHzANpOPIDG1tS6j5IJnfyOD3p5c80111xzvQfNbRvvoPXln/Dx\nbKPncK6hm9/DSu8TXN340qH7GLfjix6hwgCgt1ggJOPqInuXvAn/74u0sryCkh2cbbD4iDKBz+it\nm7fIs1NoPaRqNnA40ugIcdyjrC/jCz+LDp1BJWKcE0yqq5xc/yx24NgZPAnAYvcBlnsfZ7v/OEom\niH2PkSPVwbmGurlOOztP3WxQ6x0AkmidNFlDRTXnT/0fXLjyexjXD+e3yp0nfodLb/3b2XWYplhM\nwSaT6s2QmNFgnO8iK9FFCF94Ktny2BczAUSwGBiq+ipStMOQZRWuSwelIqrmOntFswvbYhyaRt9k\nv6Vkby2WcXWJKFoApzGm8lYQ1QFnKOrLSNnx24IvO1JdrGsomw1askVRXWJSXkWpnF7rbqKoQ1Vv\nID3TSZAAACAASURBVFzsB0n1ACUT0ngFnKGsryJFirEFxpQIoUJ3WjOpryNEGtDbRUCgt3G2oTG7\nCHo4RrNzEHRRKqbWO6Tx6t5wqkxJkyNIGVE1G0iRoc3ERyXKOMBRhpTNDZQ4SBhUMqXRu1hXI4mp\nwjEj1SJN1pFCkWfHOLn+S2zsfJWy2SSJFlld/GE6rTvC522pmk0a7SMPp7aNJFpgfelvMZq8TqN3\nSKJVuq07Z3YW5yxVvUFjRsSqHSISD1odvl/Vyo6j5GcYFa9jzJhOdiKg4Vvffue55pprrrm+ZzUv\nnt9BUkqWew+y3Ds4aJXEq1C8csheKdqUuJlvGYwd4ohIxRHgBnteYZiCPaTsgB1hqdjroDY4B5Hq\nUTbXfQqDavu9XIU2E9Jk1XufZ8Uq4deSJOpxffO/sjt6YraWzZ3/Tt1s0c5Oe5CLaGaPz6cJDVHU\no252EFKQxsv7zqNEypSL1784K5z965tcuflHRKob/uzeWqZFX6x6jPUb7BWyYNwuGEUrO4surwB6\n1mNt9A5SpIiog3UX2C/HCG2igASfHCi2plm6SrTRboe9AnqaBS0CqGOTOFqa/Q2wzmLsiEgtUNVv\nYUNiiANqvYmSLaRocW3zPwf6oNdW/+scX/27SNFiXH5rls0MUJRXyLJjZMkxxsXzYXh0KkmSLJNE\nbQbli7h9XW1fdC4BOY4rt5z7EK0zlMjYHnyTorqGH+70N2kri59Gypzx5MWZX316zDReJVFdGj04\nQBh0zvgnDQ42B48FGqD/TkSqzeriDyNFzKh4HakSWuo4AOPidbL0KFJEbPa/FrzzInzeXVYXP41S\nOXHUvS0l0diKrd2vzYYrwT/xWVn89CwV5PtdabJCmqx80MuYa6655prrO6i5beNdaLHzyUO3LbTv\nB+Fj1nyqhgoFYUO7dZY9Ct5UDrB023fNaHj7LQjW1aTJeuhi+6xYKXxhofWAPDnNrY/1vSyCmN3R\nEwh8goRPkUjoj54GJE4YrDXM4uiswQlDOzuL1gNwU8JgFrrCA4bj12n0W+E99pDZk+oCSXx4kZDE\na+wvnPdkQmxdE/JFVEggcT4iThxmJdAsdn8I74NuZnYW0EiRsbTwqdl12LvO/tquLvwoING2mNEV\njR2Rxuvk6bFQdIq3fQ5l/Rbj8iJKdohVj1j1AMGNrf9KY8ZoOwJUuGYJ1mnqegulOmgzRAg1owi6\ngDuPVRejh4DaRwMssehZ1/9WOUrGxQ2K8hqxWpyR+6xr2B0+hRIZ2oz2UQsDcEU4uu17fEJMKNad\nMzSmTyc/z7h8k6remB0ziRYxtqQ/fDYMGG7MSIFJtIi2E/qj5xhOXqNutg7s15gR/fELh34fAIbj\nl2n07myfJFqk0YM5fXCuueaaa67vac2L53chba57KMjblGDsDkp6KIpD49AI/GP6SflaiGTbn1qg\nULLNpLxAJFv4YnQ6VCjDtosk8aonBdoCawuUzEmTdUbFS0wL2INS9MfPAoQhuwptqpmvdTB+nlZ6\nekZCtK4iinJa6SmK6jpJsoZSrVncXqw6pMka2/0nZsff/14Aw/ELSHnrI2lBJDsMi1e4rXcZyWD0\nfOioy33XLEGpdgBM3F51fY0jyz+FIJpdMyW7nDn2GyRxRpYcZ8/S4RCktLM7SZKcY6t/B0mMNgO0\nGdJKT3Ji7eeo6rdCdvYe8lyKDCVa9IdP+tQTRIjU81F4xhZMileJZMeDXpzGOUMUdUEIJtUlsvg4\nQshAJqz95ylzKr1Blp3wGSt6iLEFabyGkinG3r54BhgUT/tUFwyNHqJtiZJt6maLWm+TpScAh7YT\nrKvJ4qPgJHHUY7n38bBfH20n9Fr30m3fzaS8RCTbTGmHzhki2aGsb9yeIig7lNW1QBHsHNgvVl2K\n8srsSYC1DY0e+tzvoEl5OTyt2FOkOkzKyx9YjJ2xtV+n03+tbXPNNddcc/3N0dy28a4kkTLC2cxT\n70LyhFIJ02LN7ctp3vu93y+Nj2Ost3UIEWHsOMR6adhn94AGa32msbBuVog4wDodgu0Et+88O0+d\nczV7CR7hT7pwDsJjlEUofpVqIaRCCJAyJkvWZoWCFIGkd8jA496VUVhipgOVQsQgpP952zqDT1lI\nnHX7zkSEuOv913C/pn9S0G2dp6p3aPQWQkS089Ok8RJ1s0WkeiSRpwUKp0iSBSKVAj7vupWdCOhs\n6YcoZRwG8SRKpjPYi5JpyOeWIZlkhz0SYuK3hRxuXwx6W45zgfgnJFHUIpUrns4X3qMxAwQCo0fU\nJlAKrT/tXL5zIoNAUpTXqfXm7HsRqR5Zuh7uiM3e98U5rDNI4a9ZKztFnp7A2Aop4wM49brZpTY7\nPmYNb+Hxnn2xj3T59tVUeptG7/rPxQniaCFENjqGk5cZTl6ZXZdOfp5e+16mhMzb3VK933LO0B+9\nwLh4A4T/u9prf4hOfg6w9EfPMS4uhsUpFtofop3f8QOdGDLXXHPNNdftNe88vwvl6SmMmQTyXIwI\nNgpjxrSzO/dtUwgR4bAYM6HXvjd0HyuUjAPBzds4eq2PYJmwV2D6f5QdJWl0hKrZxNgJSuazjOeq\nvkknu5fb2yEsSXL68HNITlI2G1hboVRr1mWu6k1a+VkEAms1UkRIEc0wz6tLUzvE/rQR/+vF7sNo\nO8YjymMEEc41aDOml999yEoc3daHMHYSitAYT/Zr0HZCt/WhfX92fxoJLHU/xmb/a0gpaGUnyRJ/\nnbb63ySKFqiat5BSkkQLRFGbRg8DSluyPfgGCEmarJHEy1T1W2wPvhViAQucIySXxMHHbOm078G4\nAutcSCNRIXfbsdD5qO+auykER4aItg7d/L4Zjl3KOKSMjEmiBYTIvG/ZCaRMESJBmz5VvUmijtzm\n3AEkabxGWV/HORn2i2nMLnWzQxqvUFY3ECIiki2Uyqj1Bs65GTVQCEmk8gOFc6S6lM11TwOUGUIk\nVPUGUija+R1oO76FoBgoglGXqr4xowhKmVA1b6FkSlFdYTB+nki2iNWCfwoxedlHN+Zn0GY4O6Zz\njsYMaWVn3/eidDh+hdHkNSLVIVYLPp1k+DRFdd2TAosLRKobtmXsjp6i/DbxfnPNNddcc/1gal48\nvwtVzc2Q7+szgp3TYSQtZVJd8sUM8pZtCdoMWF/8SR9bZzwVztiCxe7D1DMf8VR7Rcpg/DxxvBiw\n1VOioSOOlxgUzx+6znF5+Lb++GlitRiKZG/NEAhitQDOsNR7GGMnM2KccSXL3Y+zsvAxsuRsOMo0\nqg46+f1IGSFIQtNY+5xrJEIklPWt57enoroyg394uqBFIFAiJUl6wHR4bF98X7xK2VwDZ1HS5xsL\nIYhkl1rveO9utIhzJlglKl9MBiuILyTTvf1Uj6rewDodkiB0sCDUgCRNjuBw/voc2KbIknXa+R10\nsjsxdkRtBn4oT0QcXfkZ2vlJ2vmdBwh8UsYs9T7mz12mobGr8RjyBGMr2q1z7Nlj9s49T04wKS+H\n/VxINrEIEoyd0DQ7RNGCTzaxpb9Bkm0Q4h0tB9YWRKq3t5+rPA0Q74PPk2MHKYLRAgud+7G2PLif\n9fnP1jYMxq+gZHs21CmEJJIdRpNX6eR3kSZrs2M2pk8ar9Br33PoGr8bcs4yKl73MZQhAtATFHNG\nk1cYFxc8CXP/NpHPSYFzzTXXXH9DNbdtvIOcc0zKS4yLC1jXkKcn6LTOo+0YKRJk1MKYIQ6Hknno\nKk9ARCFtIwxloVAyodFjlrpnkf3OLGIuUav08rvZGhyOvTZ2QkwXSGnMBuCzn6VIZyTEg5Fs3iLx\nTrnE2hQkySrWVjPCYBqvIJUHOyi1QFnfpKxvAIIsOU605P2pZ45+nqsbf8q4vIBA0Gndy4m1v8PG\nzqNEKkfJZYwtAYFSGcZOvDWFBIhw4boIUhAN2o6QsoXCzdIqItXBYdBmQK91nkl5DW37+K7rEbJk\nFW3GOBxlfdMP5CGJ4yV/zcyINF5GpkcxpgAhiWQLbUZoM8SYgq3xK1hXAJI4WiZPj2PsmDw+SuGg\nMX1AkaXHiGQbaye0spPUeoem2UWIyNs9hAQ0x9d/jqK8TlFfRcmcTuuuWae3k5/HmIKiukIkc7qt\nD8087Eq2kDION1rSxwfaEY6STnYPk/oS1k4ASSs5S5y0qerN/7+9dw2y7Lru+35rn9d93+7p7nli\nHngMKAEkAJIQCRCExcSKLFGyKCmyrFiVSC6rEuftVKpSrjwdfXJSKbsqqcRRrKgsOynFKcmWaFu0\nSqJjkaJFkaAEESRAAiBAAIN5Tz/v85yz986Hvft290z3oDnEzKCB9auawu277zlnnX1PN9ZZZ+3/\nf2YDv9kKEmQHgy55ni5Q1SvUdgNjChr5kVAZdzUku//aWzelWZwALM6ViKQY06SO7SWH+h+lqlep\n7YDENMizhXBD50paxUm8r4KxjmRBKs+tx8R6Zx+8SIq1Q4zJWOw/RVktR1OaNvldME/x3sY2qOvc\nRCUL7o4+uDvuHNty+1QURVHeW2jl+SasDb/GyvpXggqGFwajl7i68gcU2RLOl9T1AJGMRHKsnVLb\nIe3GfVi7zvY+Y7BYt06eH+KVN3+JSbkpdWYo7RVeufArGFnaM44sOcJo+jrT6iLiBfFCVV1lNPk2\nRXGaTcWOLUIrSJ4e2X2HQCM7yXj8GpPy0syYZFJeYjx+HXyLV9/8u0zK8/HTnkn5Bt8690uU5YRz\nl/8Rk+oCRXqILJ1jPHmVc5d/KyzQEw+SkKVdsrTD5iXWbt4H4mcax2nSnlXyOq37cW5EbScYyUIL\nQj3EuSmt4iSDyas4PyKRJkYKyvoqo+kbNLLjTKbnmZbXwIPzlvHkPFW9QqtxEucrhIws7ZPNFqYF\nfenB+EXczGrcUdVXGIxeJE+X2Ji8HJLOaEYSHAYvUORHGE3ewNpxNBcpmEzPU9uNmfV1s3GMQ73H\n6XceniXO1o65uvp5ptWlWLk2rKx/mcH4FVrFPXiqWOkMLQ/eVxjJyNMFRtNvga/DIlSTMy5fp6xW\naRYncX66tZ3k4abHNCjSw4ymr2F9WFgKntHk2+Ad5iYScI3iKM5PSEyTLO1HvekpWdqPpjfBXbHV\nOBn1mE3c7gjWj6IsXZ80aeH8hCJboFkcjfbiW1g3Is+XEJFg054v0GqcosgX7koPsUhKlvZxbqeD\novUjGsXxWEWf7hir3YhGfvROhqkoiqK8Q9DkeQ9qO2Y4eiU6xjUwJgv6wHadslqOj6JDW4bzFhGP\nMVmUOdt9YdXK6nNUdp0tB74EkRzvS9YHz+wZy7Q+H/brTVi4JYL3JrQeyGbV+UZkV0WQgLUVztex\nd3fz8wnO11xb//1Ykd2MMwXCwsbLK/+caX2N1ARb5sQUJEmPSXkhVjiPYWP1s3ZDardOp3mWw/Pf\nH9soJlg3xboJngmtxmnajXsRk4E4nLexkuqiesRa6COWuHBSZOaEGKTh0pndN97F8YQiX6LIFqns\najAgsQMqu0av8xBroxfid2TYrgPt/Dg8ivc+JobhfSMptR3h7GS28HHreFHOzu/Wdx4Yjl/DuUl0\n9ctIkiZp2mN9+Dz93qMkpkVp16ndhMoOQotM/0nK6ursewEwm26H9RqHeh8kMQ2quF1tBzg/ZaH/\nVLgWxYAPcW62z4Te4r1VLLqtsxjJZlbllV3HUTHXeeSmSW239T5E0h3beSz9zvvpxj7/cseYC5KO\n7xBEhLnOIziq2Eo1oarXMJLRa5+l33kER7ltbJXEFHRaD9zt0BVFUZS7gLZt7EFtB0H04TobZCMZ\nk+lFGvlRrOswnlzAY8myeYp0ifH0HFsawZuL6oI6RGWvxp99VOkAoqZx7VfZi9qukaVdJMmw0Q0w\nS4ND3Xj6Jon0oi32ZrU7PDZ37tqe+7QsY0wxU4QASEwHEc9kEhZCbT93EYP3MJqEarT3JWU9JrRm\nNIM1il3mnsM/ycr6swzGLyKS0Gs/RK/9MMYY7j3281y4+ruhmkrCXOcDLM59Pxvjb9DKT1PbNcpq\nGSShWRzFSJNJfYHENDEis/aLLI2Of+V58mSJyi3H1pOEVuMEiWlg3Zj57kdZ2fgyG6OXSSRnvv9h\nOs37efPKP2WnSY3E78GG+Uy6oRfclwgmtJ74CZPpBZr5CcpqObr/pTQbJzBiqO2IxCesDr7CYPQq\nSdJmof99NIuwiFFMQW2HWDsKvddpUOVIJOWeIz/F1dUvMB6/QZr0WZz7KN32g7y68SekSehddm4K\nkpJlsQoqwj1Hfjo4/k3Pk6bzLPSfoNu+n0vLn6XVOIO1o2gik5M35mJve0mSNHa9JtKkxdLc06wM\nvsp0epEsnWOu+xhFfmjP6yhcix0Oz3+C4fjblNUyWdqj3byXLA3V/kNzT3J1+V8xnl4gSw6xeOhj\n5NlcmH1fM5lepK43SNMujfwoxoQ/S87VTMptY9GQ5XZQ5AvxHF6lqjcoGqdpN8+EG52kHV0SX6W2\nGxSNM3Fs93lUFEVR3t1o8rwHiWngvY9Vz62qm/M1eTYXjSGuxARbqOsVvC9pN+5nxLfYqUYRqn3G\ndLDuGjtbLDY/VwB79VAGww229TDPeoPTedz0dXa2iQRnwjw/QjW+ym5kaY/R5HWCPvKmg+AakNJu\nnKKaLO8eSdZnPH1jZj0OhJ5lycmSLsakLMw9zsLc4zu2894znLyKMZ528z4ECXbR5XlS08K6dZwv\nSbMOeKI9tKfIjzD0r0XVungTUg8wkpDKHGvlv8Jtc/UbjF8iSxYRCi4ufya2Kwi1wMVrv4NzFanp\nYu0aW1VYH+dByPMFyvISadIDmkBwH8SHPvOVjS/N+rlhymD0Es0iaCi/cv7vUtXL4IPU3sbw6xxZ\n+EHStM3G6JuxBz1eS+Vl8vwQIhkbg2fxvqLZOI7HsTF6iSJfIk27TMor4foTCdrM1RpJkmMoWBt+\nFbA0i2OAY2P0TRrFImnSxdoxRb44m5fwlKEOFf49cK5kef0rlPVyqCTbdZbXv8Ti3MdjC87epEmL\nfuehG94v63XOX/5N6jr05td2g/OXL3PP4Z8kTdpcXf0CVexXB0eadFicewqAq6tfmEkJelx0LXzq\ntiWtWdpjrvvonmPzvd3HFEVRlPcW2raxB2nSoZkfpbKr0b3OU9shxuQ08nuo6uWg/Cs5hhxIqO2A\nLN27d7nb+p49x3rtvf/HfHju+8G7oDvsDXiD9xbvLc3iRFR9kB3/PBXN7OSe+2wVp9lKnDed9EIS\nOdd5LDgjbnPu875CJGO++/g22+ftDnwVWTq35/GqepWN0UtRe3ku6ACbNquDP0EkobbDINcmRayI\nO6wb0W6cBr+pWbx5PBuTySoupJNt7SVCbZfZGL/MaPJtEtMlS4MbYCIFV1Z/n1ax97wcnnsaIYnm\nIg7na6zboFmcCDdJbgSk4XuXHO8d0+oaV1e/SFUtIzRIkmbsNRYuL38W7/JwfpJEh8g8VpMrJtOL\nTKYXyZI+WRrmRjCsrP8xjfzETP5u89w9NYlpMa0uRzfAsF2Ye8/KxrO0m/cHy3Y3iRrPNbVdp9M6\ni5HdDHUCg9ErlPUyeTo/i8X5irXBV/fc5q24uvy5+HvRC33wSQ/nJlxe+ZesD79BZTfi9dCLbVFD\n1oYvsDZ8gcoOyeLYpmvh+vAbtxyLoiiKorwdaPK8ByLCfO/DNIvTjKfnGY5fIzEtluaeoqyvYCQn\nTZo4apyvQi+raTGavkhieux04BOMtJiUrxPcBa/vH02o6gs08tM3xFFkhxFjaTVOkZoujgnOB4WG\nZuMUo/FLhAcI279KAyQMJi+RmM4NY4lpM5x8KzrzJYRKuINojT0p3+Tkkb+IkSbBtKXCSJtTR3+W\nsr5MatpRjzlsZyS4AYaWFajrCddWv8zy+rPUdZBGm5SX47xuxWJMCt4xmp6jURzDJA3qeiMmW3MU\n2QLT+jKt4hQmaeB9ifclWTpHqzjFYPxyPPdkdjMhBFOW9Y0/BZLQ+zs7Xo73lrK+hKF13feQYKSL\n81OOL/0IqWlT27WQwDcf4NjSJxmVb8aFggnOl/GGISheDMYvxORY4k2Ow0jogR9NX6ZZ3BN/nuKp\naeRHSE2TwfjVKLXngnukLzGmEXqf3ZBmcQojaZSjsxTpYfJskeH421HhZescEtOirFbIkjaH+k8g\nklLbdZyb0m9/gG7r7A3X13ZG0zeiw+AWqekwLS9HA5/vnOH09WgLv4Ux7ehM+Pq2hZyBLOkymrzB\neHJul7EO4+kbtxTHfqntmLJawd5EqUZRFEV5b6NtGzdhPL3I1dXPYW2obk6ry0BKq3EsOAbGx/nE\nhEnEBPtmkSghtumXF9QsxGQhXZNs5l4nsedZJCHPOnRbZyirYBxR5D2qejUmQUNKu9XyUdkVTJ2T\n5ofZtJ/e2YYgEBclpklnZosc+kljfLNttjshhu2MScmzHnUdbgLStBsTtQxESCTDOYn7DK0AIimX\nlz/HldXPs9mOcpHPcGzxR0jT5p7OcUZSqmojGnnYMNe+RuQYhhRESE0TFy/XxDRmyh1bif/mGVTg\nYyV6l8VxoS6fIiZFXCPOAcF5MC42FDHk2SHSpAMi5Fkf8dE90ZWxbSNQ1jaajQSpOeu32nU8gggk\nkuElJW+cibGGhL62axhJGNtVqul6+C48JKZNlrUxklBk86Etw9fh+0SCdJxJ8HbL6nrr/EKLR7M4\nGuTpfB0Xpr71fXJYMHr9Pn10iLw1FQyRJDgT7tjcxcWfJrZFbT9aWNwYnizE17Oxze/87cd5y+rG\nnzKevB7dFIVu60G67ffdFQUQRVEU5Z2LVp73wFrLucu/jnMTRMKjeBCW1/8A50Ibg7PT6MCX4b3H\nugnd9sNYO4yavSkiGR6PdSP6rYdh0zhFttwHPZa57mMYybBuSp51KfJeqPZJ0FgOFbdQHd5cZDit\nLlEUJ9heOd6qJFv67Q/ERWI1xuQYk+OcDZXI1iOEto3t7RAOqGnkJzl/9bdx3pJn8+TZPM5XXLjy\nz2jmx3BugnN2tk/rymiyknFl9XOEm4E8KIlQc+HqPyEzXYiuhbM5dhOM5OTZItPqQnT1ayCS4VzJ\neHqOIj/KtLoCPvTVJkmT2o0oqxU6zQcISfpmWwNsGrfMdz+Kj20Xm9RujDENuu2HgmW3GNKkIDU5\n1k7AWRLTYWX9mSD5li+Qp/OU1TLL618mSxeitu9mcp4ANc5NaTcfBGxIxWdKHUG3udd+FOdLNm+S\nQvvHgDxbIM8WmZSXt7nzFdR2FWtLOq2zIU5C1dyIoXYbFPlhOs0HqN14p+Of26DIj+4wfzEzy/G3\npt24N2hnb3P8q+16rJrfWtLabZ7F+tACA6F/vHZB0rHbup/abVx3vA06rfvoNO+9wX2wthu0G/fe\nUhxvxfrwG4wmr5Em/eCEmLRZHz3PePrmbTmeoiiKcnDR5HkPNkbfiIvycoyJzmImwwPL639EIz+G\nbD6+d1PAkaeLlPW1kABi8Gy2EghCsCxu5CcQJDjwRVm7NDlElrRYmHsC7y1VvRZkv/yI+e6HWR9+\nna0E0e94vbrxLEYahGRt0/FPECmwdiW0fQgzF0HEk6eHqew1wiLF67ajYDB6Ae9rUtOczUdqmjhX\nMpi8Qp4dBvGzfRoxNLKjXF37IiFB3C5/l+GxrA6fC66FfkRVr1LVq+Adh+aeYDw5h0iBiGw5DMaq\n+WjybfL0EOCwfhKPF7Sbq3oVyLedQ6iiJ6ZFlhXM9T6EdeOZm6MRw7HFHw6V5XSBYAYyja0SKUV+\nlOHkJRCzrZoeXAun1TUm00vRQdGHNhFsrFRnGJORmh5gQ684NZDQbJwgz+fott5HZTco6zWqepXU\ntMJ82CFFOo9npxugMRl5dohO82yQR6yDC1+WdJnrPkarcQ/d1gNBoWQ21mN+jwVv+6HdPE2neSY6\n/q0FlZdsgX7n1mXlFuc/HuQL3YDKbmDdgEa2xOH5T9Bpn6VZHJ+dQ2XXaORH6bbeR7f1Phr50R2x\nNPNjdNo3bz25Fby321wEQ5VZJCExLXURVBRFUW5A2zb2wLkhILPEeYYXrB/TSA/TapxiUl7GY8nT\n8Jjf2eAE57e1E3iIjmtDsrSHtZbSXiYkzn1axeFQuTUFVT1gNHkVj6OZH0NMESTaZnvarDRKjHM6\nW7jmmcaRjEQKajtGTB7bDNwsfpOF9wwZjp29nUJwVXPOMXXLUclCMKaBx8wc46blNTyhfUF8G5M2\nqctliInlTrdDqOsxRX6YZnEPg/G3MJLQap0hS/tYN8Z7wfkJW+ojGUZa1HZElnaDEYcdI2JITDMm\nYsGYw9sER1DAMNIhOD1O6bcfYjK9yHj6BiIpnZiQTcpLNPLDmKRBVa2E9oj8GEYSajvGO8e4vhBc\nCyUJybsInglJ0o5ygVU4Hq1ocT6iWdzDpHyT2g4QSSiy46SmA9T0Ow/Rbp6hqldjtf0Qm3brxrRx\n9Xpwi5SURnY0zJu3tJunKetVJtMLpEmLVuN+EtNARGg3T1PVq4ynF0mTNu3mAzMTlOH4da6u/SFl\ndZXEtJjrfpC5ziM3Xs/bv3sxtJv3UtZrTMvLZGmPTuP+WSX7VkhMzj2Hf4pJeZ6yukaWzodKdoyj\n3biPqt6grK6Rp/O0m/fPpOoW+k9E7egRSdLekdy+nfjNxbjXuwiSYO10940URVGU9yxaed6DTvMs\noc1gq4fVuZAQd1tnKetlyuoqqWmSmS7WDpmUF2g1z2DdOjvl6MD5AXlymNH0DWp3lUQKEmni3JDB\n5NsYafPa+X/AcPIyYeFezrg8z2sX/i+axZm4l+09vOF1Mz8dHn0zZVNf2lNSuw3S5BijycvXxeIZ\nTb+FYQHH4IZ9OgYU6WmsG2LdCB87h60b4dyQIj3OYPwynjFbyh5DhqMXaRf3siX7tkl43Wk9GLSM\nJ6+Tp/OkpsvG8BusrH8lyO35dXbK+1U4v0andXZW4c3SLmnSJnYT0ypOYe1GvAEICwedH2DtiNgW\nOgAAFfNJREFUiCzpc+7ybzAtL5ImPRJpsLbxp1y4+hnydJ7x9E2cHZElXRLTZFpdoorVzfH0HFW9\nHhZUehhPz1PX6xT5CWq7Oqsqg8GygXVTGvlRhpOXsX6KMU0gZVK9yaS8FHqnCW0nzeI4Rb44a6VI\nkibD8YtYO0QkD8cr36Asl/E4rqx8jqpapcgWEMlYHTzDYPwtqnojjq1TZIuIJKysf4nh+FVGk/O8\neeXTlOVVjDRxbsrVld9nef1LN73my2qVK7HHv8iWwAvLG3/EaPLdLdIzxtBq3MNc91HazVOzxHky\nvcK1tS/gXBldO2uurX2B8fQSEKr+eTZHszhOnvZvW++xSEqezc/kHzep3SjKACqKoijKFpo870Ge\nz9Nrvx/vp1g7ibJfE7K0z1znsdjnLDhfx2TKYyRjMHptz32uDV+I7Rom2lhHJzvvWR0+FxYH0sCY\nFGPCY2Nnxwwnr7D7VyUYE7SPt9haALg22DtZWh3+4Z5j4+nLMblzbFW7HSIJG5NvsNUnvV0az8bF\ncps6wluVd6FAJGg3Z+lc6BM3GVkyz2R6nsHwlT1jsXZAszhOZVep7ZCq3qCyG/Q6D8eWmM152bIo\nFzGsDr6KdRPSpBuPl5MkXYaTV5lWK1Hv2OOpcdSzRYbOlyGJxW2NYeLYFHY5njGG8eQ8xAad0LoS\nK5dutO3JwY2Mphfj/pMd29Vug/XhS0HfOO3GNoKCNOmxMfwmG6OX8HjStBOr8Q3SpMf68AWW176I\nAGnSxsSxxLRY3fiTm6pmbIxeREhm1ulJ0iA1bdYGz+/orX672Bi9gJGCNGnF/vMWiTTYGL7wth/r\nZmw6DAab9jVqO6KsV0mTproIKoqiKDegbRs34Z7DP8pK8xQr61/BuZJO8wGW5j9GZTfI0h7GNBhP\nL4C35PkiWdJjUu69wMjaVdK0SWIMVR2qvmnSwiNMqwsAsT+5jK8TQCjLyzOnOeuGhES9hUgWFUDi\n4kMftyMs1Kvs2t6xuOGeY2V9jcSEdoQ6fi5NeuA90yg5t9NBMQVqKnuZduNBSnuZqloGhCI7TJYc\noqyu4qxnVJ9nWl1GSIJjnMkp68tsuTK6ba8to8l5jhz6NyirNTaGL2IkY77/Ybqt+1kfPE+S9GLf\neaiEZ0kPRJiUF+KCvi2MGCzCtLxEsziG947aBsOV0D5SMq2uBrMSb+NYSpb2ca6krK4GPWVvsX4y\nSzSdL5lUF0mTbmzFCM6ExjRwbsy0XiFJmoynFymr0BPfapwgTdpU1TJp0gvfrZ8ipGRpD+enTKYX\nZm0YW+eQYv2QaXWFRHaahRiTYu0wOBpKFm/4apCExOQ4W1PbAbnZXY+7rFYQySmrNawbY0weYrHD\nqPOd73nNOFcxnp4P/dxJl2bjxFu2e5T1KqnZKUdnTIOqXr3BnOh2k2fzHD70rzEav05lNyiyQzQb\nJ7+rlhVFURTl3Ykmz2/BfPcR5ruP7HjP+Zrx9ApVvWV/PZm+SWWWaRb3MinP7bovY7rYegPHlhxY\nZTeAhKY5xcRfxPrRrJrqfR0qj9khqulr4P0OzVzvK/JsgUl5MSQ3s2QxVMKztEtV796zmZgm1m3s\nOpbn85TVVXyspgNxUaRQ5Eep7TJbSS4QzydLDlHZaxhMeOwvPhicMMRIj+H0i9vcAIVqtEqSzFEk\nC9R2bcdCQx/VGfJsidcv/n0m1SXwBhHPpeXfZVqG/llrn4v95RAs0NcwpkEnu5+q3nnzEBQfPEVx\nmPHkHHk6R5724/E8lpI8W6Cu124YczKlkS1S1SvB0IPe1j59RZEvMZq8TmpaJDRmY55guHN17Q+Z\nlleitnZwA1zsP0me9pmWsfocbxiqeg2TZDTyJSbVJRK2EjjvLYghTw8xKS9Gg57N86tje0uf4fi1\n+PQgVMLrehAqyclOzeUd10TSYn34PHgXTHJwTMsrNIujO76b67F2wtXVP6CyAwwpjjqc39zTN3Um\nzJIe1k52OAY6PyVNb09v81uRJm16ne+948dVFEVRDhbatnELCAmVXcF7mTnNQULtxkGJYg967e/F\nS1CFkGhIEqhpNk/OHt1vqTaHpLDfeTQqdGwuakri43dPv/3IrFVga7vQutFrfXDPWFrZ+/eOs/kY\nHh8S2G2OhuA51H2ckJBtb+kAMMx1PhAW/7EprZbPJPycG86qw5tKGgDWrjHX/3BQJ5k5GlqgJpEW\n3jsm1aXo3NfAmCZCzurgT/ASZP42j795OXtXM9f9EEYyaju8wSlwrv1+jMmp6o2ZA19lV2k3TtJt\nnUVMTm0HW2P1Cq3iNPP97wstFdv3addpN+5lce5jCGZrzNVYu0GneT91vRbdAOeCy17ax0gWXQSP\nhSTbx5sRL3hqUtOm2w6OlLUdhVhcRVWvRf3hBwG/Y6yu14NKRXE8Kr34YBXuCftMutHcZneM5GHh\nqqSIyaKpSxl1y/f+U7ExepHKDsjTOdK0E50Ja9YGX9tzG4Bu+3uwbjxzQrRuinXjmzpxKoqiKMrd\nRpPnW2A0fZ3EFGRpe6bTnJiCxDQZlS9Hh8HtUyvR/e08iWnH6rHD48J2SYfp9HU6jQdCghP7hRPT\npN28j8peo908TZ4dij3TJXnWp908Q1lfptO8jzTpbNuuRad5H2V1jhvdDEM8tT+H0L5uXBDalPYC\n7cYpsrSPlxqkJsvmaDVOUdkV2o37EAo2E2cjTTrNs0zrizTyI+RpD+eCA1+RH6LIlhiMXyK4+GXB\nNMN7jBSIGKrqCvcc+enohhiUOvJ0iTPH/3JY8Oh3qp4Yk4B3DIcvkZguRoJ8nOBn82vtGicO/zhF\nvoh1A5yf0ms9xPGlP0+SNFiae5oiX6K2azg3pdf6Xua6j5ImTZbmPh4q0Jtj7YeY636ARr7IicOf\niovLBnhf0u88yrHFH6KRL3H88I+RZ3NhjIp+9xGOLvwgo8mbJNK4zg2wgXXjoGvcvBeTFEG6UByN\n/BhFtoiRhKW5j4cnCHYNT02/+yjd1oPkaZ/FuafI0k4cC1rhndYDeF/RbtwXHBWpQKCRnQjW2H5v\n9YjartFqnA5JswufaxYn483AjYYsm4ynb84WRW6Smg6T8tLsCcJuNIujLPSfwEhGZdcQSTjU+wit\nxvE9t1EURVGUu422bdwCm9W7NGmTxMfgglDZDRLJg2ZwdjKqc4QFZZVdx5g8KAikC1vugyJUdh0x\nBYkI893HsFHhIzEJZb1KIhkiGb32gzu2K+tVRDKSpMF894NYG7dLwnZ4H8ZNkzq60aVJhnVBwi5N\nc7JkkaqObRdpNovT+Jxe+3t2nkO9ipiMNO2wOPfEDXGKZIgkNIvjNAo/m5eyXo1mHcQe3i25Pess\nSZLTa5+l1/7PZnbeaZrG4+Z75P+x6m8SsuTwzITDiInzmdMsjnHq6F+MVXqzIwHP0i6Lc0/MKr7b\nE9ss7bE49+SuY63GPZw+9pd23We7cZL2sZ+9YSwxOdV16iub36MxOWnSYb7z6Owcgovg2kwmb2n+\n6V1jKbIFlub/zA1jRjLytEezODL7/kQI0nvsbXZiJCMxnrx5hk3nRbyndoNo/LI7IsFmfef35KKx\nys3bL5qNYzQbx3Y9P0VRFEV5J6KV51ug3TgdElI3ivoKMqvMLfSfJDFFdLMLCZRzFYKw2H8CIzm1\nG8dH4RIXBwqHeh/CmAbWjklMQmKCFbRg6LQfJJEMayc7thMSeq2zs8VhSZKQJGE7IwkL/ScRDM6V\npElGmmSzfS7NPR3VIKZkaUaWBndDIWG++8GwMM1NZ+dg3SQk8M0Hg42zK2dxbjoF9lrvmx1vc17C\n+RQs9J9ky2EwKHRYN0Ukod/Z6ilP03SWOAPM9z4UmkR2OBMGZ8eFuacBHxwUxUQHviGJadIqTs4+\nH9RLdr/URcyeCdvNxm62z+vHWs3TOF/OLNm999ENcJFu60GcC2NGTFykuU6RH4mult95nO3mvVg/\nxnuHMWGstus0G/fMzF92o928D+uGeO9CK5CHyq7Tapy6qcNgp3kftRvscAOs7Dqt5r37ToZvdn6K\noiiK8k5Ck+dbwJiUY4s/Eh83r1PZDZyfstj/GO3myTiWbBsrWZh7mlbzJMeWrh+rWJz7M7NH2CKh\nwlvWqzhfcqj3feRpj4W5J0Ggim5yzlcc6n+ELItj+Di2FsZ6H6XZOMqRhR8EIfaWjgHPYv8TdFqn\nOTz/A4Clshtx4aLj6MKfo8gPcaj3Uby30RFvDfAszD1JlnU51PsIzlfbxmBx7okw1t8ciy6CIiz0\nn6DTOsNC7ymgnsVixHB84UdJtyWJ19Nt3c989yPXbZdwfOnH6bbPsNj/GM5P4jmsY6Tg+OKPzow2\n3gkU2RL99vuj1F5w0suSPvPdD1Hkh+l1Hqa2g62xdJ757t796m9FszhBt/U+6uhMWNs18nyJfucD\nN92u1TgZbL/jdpuOf/32zR0G2817g9nJNqfAZnGCXut9t3wOiqIoivJORW6Hfuvt4vHHH/fPPPPM\n3Q5jhnM1o+kbOFfSKk6Spq0dY8PJ6+ArmruOvQa+plmcJk231Aa8d5T1CnhHls7vSAK9d5TVCuDJ\nsqCXvDVmKavVODa/o1Jo7Zi1wfOAp9d5eEeyal3JaBy0qVvN0yRmu3qDpapWgCDlJdv26XxNVa0C\nwcjixrEVwMTttu7RymrAYPQ8SEa//TBJsrf82XbKco2N8TcRyem3H9qxXV2PGE3fwJicVnHyHZU4\nb8e6aVDSkJzsOtMP6yZU9fquY7d8PDsOrUSmERcL7m+ftR1R28EtbDektqHyn6Xdt95AURRFUd7B\niMhXvPeP3/C+Js+KoiiKoiiKspO9kmdt21AURVEURVGUfaLJs6IoiqIoiqLsE02eFUVRFEVRFGWf\naPKsKIqiKIqiKPtEk2dFURRFURRF2SeaPCuKoiiKoijKPtHkWVEURVEURVH2iSbPiqIoiqIoirJP\nNHlWFEVRFEVRlH2iybOiKIqiKIqi7BNNnhVFURRFURRln2jyrCiKoiiKoij7RJNnRVEURVEURdkn\n4r2/2zHsGxG5Arx2t+N4h7EIXL3bQbwL0Xm9fejc3j50bm8POq+3D53b24fO7XfPae/90vVvHqjk\nWbkREXnGe//43Y7j3YbO6+1D5/b2oXN7e9B5vX3o3N4+dG5vH9q2oSi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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "KdGGWBXqOBFD", + "colab_type": "text" + }, + "source": [ + "**Acham que 8 clusters fazem sentido nesse caso? Podemos mudar o número de clusters!**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "TjaZH4XrOBFE", + "colab_type": "text" + }, + "source": [ + "**IMPORTANTE²**\n", + "\n", + "Além de definir o número de clusters, também é **importante escolher uma seed**. Isso porque como os centroides iniciais são escolhidos aleatoriamente, clusters diferentes podem ser gerados pelo K-means dependendo dessa iniciação e do número de clusters." + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "1aPfoNAWOBFF", + "colab_type": "code", + "outputId": "e93cc714-d2bf-459e-a49b-0cedca3d7d14", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 442 + } + }, + "source": [ + "# Sem o seed\n", + "kmeans = KMeans(n_clusters=50) \n", + "kmeans.fit(df)\n", + "\n", + "centroides = kmeans.cluster_centers_\n", + "y_kmeans = kmeans.predict(df)\n", + "\n", + "plt.scatter(df.visitas, df.tempo, c=y_kmeans, alpha=0.5, cmap='rainbow')\n", + "plt.xlabel('Tempo')\n", + "plt.ylabel('Quantidade de visitas')\n", + "plt.scatter(centroides[:, 0], centroides[:, 1], c='black', marker='X', s=200, alpha=0.5)\n", + "plt.show()" + ], + "execution_count": 106, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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lSkA3GZaRYYhJMsRJ4HGePCFCG0kaiZGjwh10EcXjEP3UCNhAOxvpuGyS4XST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O8UwhR1QY7db7sik+Oz4yc47FjDQu2XQhX/ns57jqoovom9XW29vLORs28D8//RlWedGZwHk4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YYhqNlC7DXG/Pyt98AN7yH0Gzz8xS+z68AhBvtXIU6c++KksCSDLWl2nTQDSjtu3YxtyViS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\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dboLnH7MWSbIXQin1CyXOAAd/DBipOIejso/RODz76OKelRW8trBSeb4MZnSB/qCfAJ9W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\n8PH/zpqzlzLcP0GgNTVnXwxl0N7ScUIRQWvNcP8Eq85exBUfOpdR/xA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1J32w\nqHOkzA60CvC1h0EtDVBrAjwSZitHKs9gYBM2EoSNBI6KMFjZhxd45PUEACYOJnaNlE8RN5rQSMLg\njMWdJsCnylJnI6COu3DMLKBYEdqMpVwqQVEkD4GmEpSwlEPsrR+Q5LaJ8dmQlIkxiCfIX30dPUc3\nE1MTNMWnaIxPEQkmeOTopfhtCxk+KJwoFJVFAYP7RCLxxG2QaIbGedA0H0IxeOif4KKPn/p4bnhX\nmd+MCHFOOJ0krC4GSz08dewm1l5R4pmJmxgo9pB0ukjYnYwUd/FMZhuX/ZeyXGPUKtpBII4dlgNv\n/6/C1YpyfSPhWkPQugTKedj1S0i2yhwb58lzH/oneOSf4IXHhdBHGiCSAjT88P+F/es3MVSu0FAs\nkjANEgriR4/y6LLV7I4meCBXot02mW9bzLMtKoHmu+PTaP0SepUami2DY1WPkFIkDIO4ocgEmnKg\niRqnrqxMeT7Dnk9YQcxQRBXktaa34tHqmAxUfcIIOY8binHfB6Vx150rsoaKRMnj+zA+DKdvhDM3\niz64WjlxbP15Lx/G8PSjcHivVKPTHVK9HjkGj90NOx+C/v0ETW3o5nYZGzoi1nfM/G00QT3MpI46\n6qijjt8T1Mnzb4GRSsDhgnf8C76ks0TMJK4RI+f7TFZ9lDKIm81M6xFSZntN0uFR9H0MDFJmG/lg\ngkD7WMphuKw5WgK0AUoxVN2PpRwsZVPUYkumsLCVw5jXR8psx1IOGQ8mKgZKW5I6aClWhTafVHk2\nWOJupMmdx5rIJbhGmCJ5ihRwDJfVkYtxUq3wN1+BhkYK0xkK0xlobIb/9XcMjrcQLFuDGbbIj1Yo\njJVxki7B0jU8fY9DOCH65GJOGp7dKITisPPnsndrjhTNjYiu2XUhdZIJAkD7qoDvfH8b494uEnYn\naNFfJ50uRqo9/O1X/pxcpIeE1UXgK7SvSIU7KSd38dDz2zj/I4FItStCnJ0wbPm6uBldtEX2Mbgf\nhg9B2wp4y4eg/xkxilAG5DOit44k5d9P3F5r9K4FL+pAXl+lAL98voPt19+I5XvEjx0lPjBAZv0G\nfv3e9/NArkTUUDUXDUGjaTBY9RnxTk0Mj1Z81oZsAiAXaKa1ZrFjETMVmVpVuej7PFsoM1SZ1b08\nXazSYhoEKMpaU0GRNg2mvYC9xSqnhW08YDoIyAcBy10LA0V+4XK4+F2iVx4bkk737nNh46WwZDVc\n9A4h0GNDohfe8BY466LZCVdKMNAn689g9w5oaD7xNmpjC+x5Gp7dTjnWwFfufoBv/vJBvEpFxp5/\nCrTG8zy++c1v8pWvfIVyuXzK4/R7jRmN+KsJyaijjjrqqONNg7ps42UwVAr40/3TPJUT6UOLY/Df\nl0Q5KwlF3+besQU8m3PQaNrdgKvSw6QsTYDDsdJiBsqSTNhg2ayOldBoBsuKf+gP01t00VqRdip8\nfEGB7jhUtOJA3qVU41q2AUvCZQJLM1SO85W+NfQWReDb6gZsXXCUTlezIHQabeZKRoODBDqg1VyG\nbddcMswUQ6GNHAsmUQS0GY0sNyWaeuq0tTz0vW8wkB1BA/MSLVxgtaKfgKlclGdfeAuVvEzGnTDo\nXKdobhSyWchwvJmvlINY47+dhNy1ATLDMHqo5paxDOJNCns8glLSJKgD4WCGqUgYXZQqI6RTXUz7\nCq/GrdwIlJUmFIpw8UcUTggOPQFWGDZcBUvOkudlh8WpY2pEyLBhwplvk31MDsHuB0TaqxBnj7bl\nIrvTARSzs82IpiMvNfA0I2tP58G1pxEZH8MLhSgnU1SqnuS0nPR6lZILgVPXnUWg02rbLA0pioHG\nVgpHwYDnEwB/NzjJtyfylLRc6a4L23x1YTMBEDUNWgyFp8FUMj7sBQQo2m2LJa5NUWscpbCRbWql\npMq8aoMQunD0RPlE97mw+swXjwUB3Pk9uPc2IYOWCedcBtdulbGXbJjUlCsVtt1zH7sO9qJ1gD56\niC2XXYAVieFVq9z0rW/R09ODUopt27axdetWXNd9iW39HsKrwuP3wq7H5Y0VicFbrv73OYjUUUcd\nddTxpkO98nwKBEHAJ/ZM8VS2SputaLMVOS/gc3tzHCtE+NehNM/lbNrcgA5Xk60afGcgjRks4Pnp\ngNFKmaRl0WDZlHyf3dNVjGAe/6e3mSNFmwbLo9GukvVM/r4/Tb7SyUBJ42sPS4GlZA6jFZ+yt4S/\nOLiQ3qJFowWNFoxWLL50aAFlX6zDbNumw13J/NDq48TZ0wG/8AYYpkyzkaTJaGCMCnd4gxQCj194\nA4xQoSmRpjmRZpgKd3gDuKmAgzugWlSYronpmpQLigOPQ+sKKExycoAi0+OwcrP86s+RWVdKUqVe\nfAYM7gWvBG1LoXUR5Mdh5LDiE390A632JqYqvShDowyRYmitWLamlcygIvDF79l0NCOZXpKVTVx3\n3Q386hsKrwQrL4AlZ0LfM/DwrTB0AP71L6R3LdUOyTT07YLv/zcIJcQKz68KEXciMDkA/U/Dmouh\nWhLiPFOBrtSS1jdfbpEPNL5pkm9to5xMMeUHNFoGF8ZdpoOAYI5EY9LzSVsGLdapP2ZnRBymggAD\niJkGrqGY8APm2SYPTBX52lgetCZVk2Y8VajwR/1jXBIPkQvEe8WpVbwnA81C1+KiuMukX9umYeAo\nxagfsMy1idWCU7CdmtPGS+iOX2rskTvh57dKc09Ti9hKPXwH/ORmWH2GuHDMladMjlLuXMW2Hc+z\na+9+OlMxuppS9AxPctMd91AKRY4T566uLjo7O9m1axfbtm37j1OBfvw+ePJBsfNLt8sFxt0/gGO9\nb/TM6qijjjrqeBWok+dT4KmczwuFgDZHYRiyNNgG1QBuGqgwVm4j7ZQJKONTJmaXMElw/2SU30wt\nJ2VVcY0cjjFNwi7SV1jA14+G2J1rosUtEzYrhM0KzU6ZwVKC//ZClNsGVxO3qqSsAim7QINd4sHx\nRfzNoQTZaoRG2wPlg/JJWVUqgcvdo6f+Ew7oElmqNCjneNR3SjnktMdvdIYcHqk5Yw3KIYvHwzuk\nHDvjXKGDmuRVw4M3n/qY7boLNlwDmREYPypLIQPnfUBMFpKtIq0o5qSya1jyWDhice6yLbS5m8iU\nevGqGrRUs6eGZd9KQeBrMqVeFsQ3saF1C7vutPCqEE3VqtWGNAoOH4SHvyvFvmjN9MGwIJGG4QPw\nzL01T34lxUGvWgti8YVMRxpFBlItQbXG4+avgSWBzXkxl4Gqz5Gqx9Gqh681H26Kc1rEZWMsxEDV\n52htDAUfbIphvExX+Pqoy5kRh2OerHes4mEpxfsbY3x7fBoDTajmWmEqRcJQ7CpWuTjhsiZsM+wF\nDFY9hqo+roI/a0+xKRZmbdjhWNXnSEXmEjOUNCy+Utx3uzixzDQaWraQwkfvhtM3QXsnjA6I1nlk\ngCDRyLbn+9l1qJfOdAPK91DVCl0Rh56JIn/+wzvoeewxurq6jr//5hLo33sNdKUMu3qguX3W2SQU\nEfeAXY++sXOro4466qjjVaEu2zgFRitSuTNOatqyFPQVAhKWzd2jrQxWfDSKuAnnpxwGK5pstYE7\nRzYw5Y+j8AmrBhJWnKoOyHsuOzNt+MqTWG1MPG0xoAKGcos4XEizMjaIic8LhVb6ig0siwQoLLwg\nzqQXoNEkLQMTxWBFU/R9bvP62ckUAZrTSfKH1nyKyq/5Qp8IrSCrq3g64IUgxyAlFNBGiISymMz7\nKFNjNflUatoFRxlUx00KGdnejMQCRIIRVGHymASXTHxD5BKGASvOh9bFsO8xIcpeBUZ6hZh3rBDi\nOz0GyzdaONHr+OnOA5QZoa29lUhCiLbpSMJgdnoE10xzZud12IZFZkCa/3pug1xNmtGyBOathMyA\nqAmO7Ba9Mkrs8NwITB4FNy6PF7Myz0RLzSlpGFa9RarUkwOi3+7slrmX84o/WBhlYyzEkXKViGmw\nImQfTw+8MhGmGmj+f/bePMqu6r7z/ex9pjvfmueSSkhCs8RkIzEYMAYbMxiDwRPYZjDGJN1e6XQ6\nq5PXmVZW8l53Oisdk8EOg+M4ncQJBhsbB9vYmFEMAqERCQ1VKtWgGm/d+Z5h7/fHvlUqCaSkebYJ\neferdZZu3X3PObvOvVf6nt/+/r7fl0s1mi3J9c1J+hwjZ5iLFM8WKuyphjRZgovTcVbFHGwhuCab\nINSaV8s+bbbF9dk4XY7FTBghgFyo8AELiAvTYDcTav58SSvPlmrsLfu0OTZXZOJk61Xu65viRFqz\nu1Kjy7a5sTlJe30u02HEU4UqB2oBHbbFJek4A96/8E9BYdYIxU/4MrhG3qE13PB5GDlUt5NqQvQt\nJ/HAg+gggO5e04QYBgjLYaDHY2JiYoE4n/DZ1JpEIvGm5991qFXMB8o+6bp6cVOlb6CBBhpo4F2L\nRuX5FNiQNkQjVCcqVn00F7fY/ONEwLAPIRYRklwk+e50SJeteTEf8sS0YGehjV2FTp6edXlixufC\nrENFw5yyKEYeBeUxp2xKGs7P2lQVHKik+P7kSr47uZo9pWYqCrZkbAqRYrSmibREaYtjNciFmnUp\nwR+Ge/kJk5QJqRLxLFP8fvg6SWWZYJVFy+laGzrdS4w3dJEDFPFR1FAcoMg+XWRZr0XkhVRSAaQU\npBTlVEDoRfStN8fSzIeaHF+tX/5e+O9Xw6EXDbEOA9j5I/h/rjHkc/9zMLrPaINVCIdfMVvXStj7\ndMjTe76GLyZJux0UJiE3bkhttWCIbtzuoBxO8ty+r5GfDulcCTt+UCfKkTnf6F7Y/WNoXwHTw1Ar\n1qvnkSHpuTFDhmdHTFVcYPadGYFyHvrXwp4noTBpnEIsCw6/ao6baTc65iWuzYXpOGcnvAXiXIwU\n904W2F4OaLMtQuDBqSLPl2oUIsWXj83xRL5KJVIM1kL+YiLP88Uqc5Hi3sk8u6sB7bZFqVrlP/z3\nP+I3vvxn9ElNUUOlfr39MGT4m3/L1Dfu5wypsKXkknScuzuzfKwluUCcp8OIP53Ic6AW0O7YFJXm\nK5MFdpZrTIURfzI+x3PFKlWleb0a8KcTc+wu/wtSif6V5gItRqVoYocT9Qu1ZKWpQi9bg3Bc7rjj\nDracczaDY8fQXtz4O8cTiDCgs6cXsShcRWvN4OAgW7Zs4Y477nj3k+dE2lyX6kkhRqW8CaNpoIEG\nGmjgXYsGeT4F+mM2H+nwGPM1s4GiECqO1hR9nkVMCmqn6AK790iF2UDhSlOltgS4EnytGfGPL0XP\n5/rNP05YAqv+hD7pNcsTgqwtCLRJigu1JtAQl4JarMwIFZJYePUticUEVfbpAitEigldo6RDyjpk\nQtdYJpIIoEqEjcCqG+DZCKpEJK4oYq2pwTEbVRCogoBjNs5ZZT7yZz5uEnRodMlRYB4nm41bRWkO\n7JgpSjoeODGYGYYXHzL6Z9s1VWdpm8flPAzvCdk2dh9jtedp8gaQlkBaENYW6aeF8dOet7HbMXMf\nO38coqL68eobwlSTD730FhcSM+dqsf6jPv681iA0TA4aYm8tnqcN+SnTKHkqvFSqMR1G9LoWSUvS\nYlt02RaP5so8U/dj7nXthbGOhbEKuVDT49h4YcDr33iQwut7+N7TzzD5rb9Dh8ZhQ4ch+Yf/ntr2\nl4n27eX+v/iLU2qDnypUqShNt2OTlJI226LZkjySK/PEXIWqPj7WbltkpeTbc+UT9Npvwkc+Zy7I\n7JQhhLlpE6Zy/W2nTBi0bZs7/9vvsWVZH4NHR9CBD5WSeRMWEcjFxPnOO+/EPrla+26EZcEl10J+\n1lyrStk4mMQSsPGCd3p2DTTQQAMN/H9AI2HwNLis2abVlhypKSSCa9td/u8z03z5SIV95bfWZBYi\naHMEGQtyIQQKmhxISsFEoMkFGgcWMgFjgCehrDSu0HgC5g+dtaDTBcey6I1ZZG2YqpPJNUmLDWkL\nP14k75WwEJQJ8VFIJBGapLa4weknrwJe1TNM6RpniSYutzt5Tc8xpMsksKkSodFkcLAQxCyL5AeK\noMz/+TSHtF1dpufXZ+hPx7jyox7bD5QohxG6KaDjvT6/8b9dnvgrU9m1pFmlnye2KjTaYUsayUhx\nxhDjVItpAPzJ9vsYmnme5vgAYSCMPVwCQDNXnMAWSbQWhqhrQTrZxGy0i7GRKVrludiuQGuTNG67\ndV11PX1cyDoxBiwP0EbL7KVMX1zkG/luc4/Zt5IHhMaN1YhqPrYdkO4QaCUZOBtaehUvlGo8Olvi\nQC2k25UkpOSH+QrlQDEdKfZXasxEiiZbUlaaYmTs9KoaJsKQitKkLElBKfKRwgIKlRo/euCrjO7Z\nTXv/EkhnGdqzB2dmGlacSe7b38Tfvo2m3j5iTVnU0CHGh4dpWruBfUHEbKRosixsIfhOrowtoBhp\nJsOIqoK0ZVIL50JFqp58OA9PCo6FERelYrhaGfnF4deNH3Q6a4hgSzusPtvY1M1OGT/nW/+TsbID\nY8M2fBAG95mKdLoJpIVMZ1l/wcW8sHUruXyeVEc3LF9jqtAASjFx6A2ahOI/3foJ3Jb2EyMj381o\n6YC+FVAtmWWRVZvg/TdApumdnlkDDTTQQAP/CjQSBt8GpJR8qjfOp3rjJzy/MnHqgn1WQj7QFFS9\n8KkUR6uCmISNKXhNY6zFMBU3X2ssJL0OjNcE+Uhj13lNWQER9HuS7cWIqQDaHXPufASTgeZc22YQ\nxRzHyXyNEAm0SI+/84/wEyYWirDf1EcZ9SussjMEKPz5NEOgSIgAmoXDeKJA9ZdGSWgAQVVASdvE\nsfjjth0M/dXxuMA88GXSdHStRUemwjyPKAC0sYLb94zRRs9j+gjYMY3dWyb0BdXguFVwKacpi0H6\nu9o5PDZISh7Xx9ZKECCwWspQ01i2WMjwmE8YTLUY2ca8Rd38XATQ0meaClv7j89FKchPQHNPxNzR\nIpnMNEljZIIOJdWom1Sbw38ZmeWFYr3iK+CByQK/19tMkxR8o1RlNtILBe1Xy+/8R00AACAASURB\nVD4b4w7r4wkezZUpLmqCc4AlnsMqz+Kx2RK7v/ZVCvt2E+/p40gQkbUkzX19HNi+DXlkEDUzjdXb\nR1EI4kqzbOlSvvXiNr6T+xPOuf0LCClpsiVfaM/QZEn+OV+lHB2vJLsClsdculyLkSAitoig+srY\n2XmhD9/7hiHB89w62wofvcNodV95xvy9Yp0Z2/4sLFtlHDi+89eGWM/v19IB199OGEvyte88xmQ8\ny8CFJ0XqBj7s205HMc/gzBxf+61f585rP4h94+eN5OHfA3oHzNZAAw000MC/GzRkG28Dv9LnnnLs\npi6HkgalwQ1qRA9/leC7X6cchFza4hDpulogClHf+zrBw18l8Gtc2eqRDw3xcuub0FCMYEPKYqQW\nEWnI2mYTwEhVsd5N8lbRCwrwlOBJJoghSWGTwiaG5BmmkZEmrOcWOggcBCGKEM0anWYGHzQksEgg\nUVozTcCOYJYhKgjMndf83ddOCjRdP2d+OMnGDgHdZx4nzkKaDSCsSj514z20yE0UwqG6VZ0mHwzS\n6Wzhhgt+n05nC4VoEK01WmuK0RCt1ib+82/eg7QkQfV4SGJYNVZ0l91pKs4qMlPQ9blYDnzoS4ZQ\nl+vVaRUa4ty9Ci772OsIVaNaSaJxUDjkZ9P09B5kW1uR54s1OmxJl2NkGVLAH4zPkgtDJkKFhyYt\nBUkpCJTmQC2kwzKV3RgmRTAlBEWlKUeKTkdyLFJ48TiOBkcIfKWJtLkBs3r70JUyVm/fws1DFZj2\nQ2aCkPZUkj7Poc+1qSrNP86WyErBRKCIS0HGkiSlYE6Za3d5NkFJacp1Ih9ozVgYcVk6hrNzKwwf\nMCmAHb1mK+Xhqe8aonz0oLFcmx8rzMLTj8ErT8PY0In75aYJn3qM++67b8GO7k065tFBKBUQqQwD\n/X08Pz7Lfd/9AeFzj/9LX8EGGmiggQYaeMfQkG28DTyZi/jpTI3SScqNjIS0IylFGoIauUceIDy4\nBzE5QqI4TbBsAyUNfhBSfewbhHteRuQmSU4fRa3cQAGJVlDWEAGegBYHLCnq7howEUA5ghZHMBC3\nCLOzTNslThaROMAsAUUiHDQ1IkKMRCAAQqFpES4VIkpEBGhS2CwTKTwp8YVpLJwfywqHdumxXc9Q\nRJ2wZCExZL04KHGeaybwNdpTYGkkgmy7YGbY6JuFqLt0aOPSISVU5mzavXOYLQ8zU91HNczRn93C\n+cvuZOqgSzY6i0o0wWy0A1/N0eaexYb0PbR0e5x3HRx6SYHy0ZEm3W5x9wOmUTA3DsVp47Un0LhJ\nyaoLYeMHYNk5MPiqIqrkCWsR/RtdPva70Bx8l9bmQwwdWIKKIqLAon/lJDd85hG+43RwVKSIS0G9\noE5cSqZDxWRoQtG1EPhaoxA02xKNICEFKSkoKChrTQgMODYZWxICMSHQK9eQm56isP912pub8CzJ\nSGBCTeRJ7hNaa+aGh1nxnvN5z6duZaZ+s5K1JMNBiK8hISEXafJKE2k4M+bgSsFHmpL0ujZ7qwHT\nUYSv4QOZOFdk4sgnHjZRkNIybhEIUwEeHTJJhImU0bjMIxY3nsUzE5DKmDuiWgWEQMeS3PePD/P8\nyBQDy5Yhouj4mJBMTEyQHD2E8OIgpbFRTMTZNT7F1MH9nHvDJ9+ZpsFKyTiI2M6bg19ON9ZAAw00\n0MC/OzRkGz9DmCZAQZOtKdQTkx0gaZvmu8ivUXjkAdShPYjOPqN33fUSQ49YOJffTNdP/oHpN7bh\nLFmCIwS5w3s4/M378T/4WYrCYz6EOdTgKOPvG9WbBEXdfC5QECmQb2FFB4bMSiBAsbitrIw2Fnym\nA48WPGxtysAZ4WALiUDgIlglMwR1PzpHSCZ1DXGK84FxopAtAbwvjxIKBNihhdiVQQgb9HF7O6g/\nFoZzWXhsarqH7dGfY4sEG5vvQGgbKSGR8Ll+3YW8cHSMQFV5b9eVjA5JpIBLPzHOhRc+w/SRAC8W\nkV3Sgey9kGMHkqw6Z4RrbnqO4ozAiwXgtbNn74UIEWfVWSOs+P1nqeUrWLbGbetHNl1AOC5Zs34v\nq9bvwq/YWFaEE6tbikiLSqjIK4i0KaknpUBrjSXAE4IuxyLUGikEQmsmIoUU0GxbnOE51HS9kRQY\nDSKkEEyGESNa4F7/cYTSjO94hb6lA295jbXWRCNH6dm8Ge/6m/nHQg1VX83ocSRnxlyEpYkwc5SY\n1YxAaeLSfFrOTXpsSrgUI0VcmmAW8wYCx0aMV/P8G9XeY5wjpDwxBAXqqwr1N3Bs+IT9dFsvZd9H\neBJGDpvKdH3lYJAY7Ws3Mjgzx0Cnd8InSiAoB+GCK8wvDGEAzz0OO7aany0LtlxpEhejEJ75Pux6\n0VwD24ELPmiSGt/triANNNBAAw38H6Mh23gbuDBjMRVoSiHEJSTqLg+TvubyJsHoQw9QPbAHu7MP\nRxq6W+voJ77/Zabv+0OmXnuRZO8SPEuihcDu7KdleC9j33qQQCkE5o3RwEwIm1IW+8ohM6Gm2RY0\nO4KKgr3lkPPs7ALZXowIWE3mTRVprRSR1qzUcUZUhbIOyWCTwaakAo6GJdaINAKBrxWOkDhCUtPG\nmePDonvh+IvPJYDLejPkOsvoCBxt4ShJEGpyvSXWX6VOIM5mMoZrnX0dFKYNgX5P55c4q+0uwppN\naQa2fKxEZ88olrA4v+dTXNh3GzFH0NM3zOWfzxMN/RAhFO3LU6R7MujyMaLhJxlYO8eKvicQaFIt\nHk4iSUyOsnrFkzS15VDDT4AQxFpbsDMt6MJR1NGnEE0rICwhNcQSGscVEJRAK85o6mMmMgTQEwIX\nzUxk4rBvak5S0UZuYQuBxFR+222LqzNxCsqQ2JgU2EIwHSn6XJsmAa9VAiytybgufR+9GT/bwvjE\nMTqs41/PecMQNTON3dLKdbfcyu5QY2vTjJoQcCSIGPJDzojZ7KwEeELQZFlkLIs3/BCFJlk/pi0E\nTbZ1nDgDtHTCoT3GJiWRMs4QQ2+YzsqNmyE386YUQc7cZPTNh/aesJ88so97rryETZ2tDO14Be16\n6HiSwWKVLSnB79/0YbZcdDGDI2NopdBaMzQ1w6a2NPfc/UXkL7qy+/KTRtPd3A5tXaah8clH4eAe\nkxS4/Vkz1t5tquw/ecQ0VTbQQAMNNPD/OzTI89vA9pIiY5kKdKChVm8OTEl4oaCIx+MINKreHAjG\n0SDWvYTz3BqyawnFCAqhphJpzk7bzPgK4cUXlqrnm84k8NCxGktjFrYwjYJzdR3v0pjF837ulPN8\ngZkTfo5qPq/f+w8cuP8RngwnaMdDCkGZiGJY47X7H2Lfvf9A0a/xftlBkZBJXWNS1ygTcbns4DK3\ni7WYZq6wvgG8lyb0ihry41OISQc1aqNGXaw5B+4e54hbeOtJSjj8ovFU1hoiX6JCgZQQS8PGLYOs\nPvsQxXyaSilBtZSkWonzgZu302S/ZiQZtmnoFEKg3Sy6MklTfAet/ZpyIU45D5WCoFJrYvn6Y4jc\nDiMbsWPH9/OaUaUxtAog3moE2lEVVA2EhUj3klUVel1JTUNRaUoaXDSrYiZ58LJ0jMlQMR5EjAcR\nroTf7mliYzLG+9KL0gf9kLgUfKo1xbayT0pKlBBUg5CxR74JuRl0cyv9rs08hZzXbcuWVpryM/zD\n33ydpIpQwtgmBghSQjAbKo7WQnocizKQjzQFpWm1LNCC2km+5SegkDOJeNWycdqolKG51XRarnsP\nLF8Lk2MwMWq21i648ENQnIO2TuPlVyoYeUNzO54KuGdVJ5vOGGBoJs/g5AxbVi3nzqsuJ7brBe78\n7T9gyzlnMXh0hKGjI2xqSXHPzTfgXXTlqef480AUwqvPQmvncTmG40IqbUj1zq2GUC8eS2Zg+zO/\n2Hk20EADDTTwbwIN2cZpoLTm+VzAEzM+5Qjek7W5otVlOtAkbUmLoxn3DUludoxkYyKA9mtuIYg0\npd0vQ1c/jhB4EkoKzuvr5o2JKkeqphLZakNi6iiZje9BXvAJowldNAcNTAaK9Z4kJTWvlxUaWB6X\nZB3IKeOsITheDbbq+1UW1aSjms/+v/wncjsPoLXmRS35yO234lqSkbDA3ge/TX7rHuLC4mt//hV+\n+e57GLFLDGJcNc4gSbMwH5cvOat4IDjEDuYQwPm0cIuzlO9GY9hX5smcHVDbGQdLEzurQj5bJf+M\nwk2adOJayUw4ljLhJ3OTkGxWtPWU8UvGciOWcSnlYwTFEld+ZpiNW/YzecjFchT96xTp7gQEMSNK\nKI2iqzmQFiLeBoAI8jT32aS6TGOgtCDVIhChAD+PCoowtcNUlRGQ6IRMPzIooFN9hsnXZo0wO7ME\nnAyVqMIFiSSyPEO1mkNKm2yqiylbUkPw+30t7Cz7vFbxabIEl6bipOrBJZemPObCiG1ln2ZLcnUm\nToctmY00rZbAUZpDD/89ascrtPcvoYJpDFzh2hwNIipaYwG9rk186QBHt71IJlQs+/inCS0LC0Fc\nCibCiKlQs8KzGPQVE0FISkpWx2x8oKo13qkEEZUinLnRuGBUy3UC2QTT40aecM2tcOyoSRFMZqBn\nwBDKatnY2NUqhnB7MTM+fQxPl7jng5fy5z95joTrcsdlW7ClhMkx7ESSO798P+KP/4hybpp77roL\nb2DlKX2jf24IA/M7n+wv7cZMU2QQsGDnsjDmQf7UN64NNNBAAw38+0WDPJ8G/3SsxvenfNocs9T+\nz5M+2wsht3Z7FEJNTmlillEBF0JNoDW39cb46WxIcNUtCA16z8sEXf3MRYJWR3D/aJVcaIiQ0Jqp\n4WF+vP48/senPs0Lw29Nas5KwFO5kFyoidd5xb6SYqiq+b0lSUbqFeb5vedJ9FJi7Kd6AnFOLOkC\noLR1Dw/zNwzcehWH/+YxJrbuILG0mwjJwe27uOnPfodld9+A6xlnkTco8pvRbv6n2sC9HGScKp3E\nAM0u8nw1PMRFopVnAas9JHl5CQBVFzavXeKZMRdSpuCLqk90w2Uhz/1tFSteIJGxAY3yK+gAms9o\nhom9dLVEdLXN+9H5kM9A53no8ZfMb255oEL03CDaTiA73wvjL+DENU2JejVfhaAhtNPIqR3Ua7mA\ngvIo+Hn0qo/D8JOGPFue0ZXkDqETrfT1Xs2zI0P06RJp2wWtqBWOYCe66bCNr92GhMuGxIluLLlQ\n8eWJAiWl6HVsalrz1zMlikpzTsLl4dmAykN/R+m1bWT6lhBivpjNluT5io+amSbW0ooWgtEgot2x\nWD6wjL2vvkzMkiz7xK0IISgqRVoKVscsHpiukpCSjGU02FtLNTYmPNLyNBrdgdWw+2VTRU5lzHPF\nOVONdmOGQHf1m20xlq6Cg7uMfGPevzk/Cz1LIZnBO7yXL33oUoQQZmVlbgb6zgApsV2Xu379v6K1\nRv6iSfM83Jj5HUv54/MHQ47XnmtcQcoFc0OweGzT5l/4VBtooIEGGnjn0ZBtnAIzgeJH0z5LY5KM\nLUlYgiVxi7Ga4kA5osMVhEBNGa/mEEhaAj+KjAbYsrE/+AlEU5up1AG7CgFzoQlJsQSIuSmc5jai\nKz7BVyZPTWpeLmgqyjQlzhMQGyMZKfnuwpu4YMmGIdJZbLRS7P/KQwvEeX7/pqU9jG19jVd/5yuM\nb91JemkvlpAmxGRJMxM793PwKw9hKbCROECekL/mCMd0lRYcYsIiJmxacDisS3jCZkAkmSGgpEMK\nOmCWgE0yyzUfSdDWZ8JLaiWT8lfJw4rz4dJPHKVryTRzM2nKRZdy3iOfy7BxyxukYwdN6om06s1p\nmGpwWEUHBfNYYF6jI2qB4sv/8Bz3//3jRF47ojqNDkpoP09YmuK+xw9x7//6E2p+yPGPf11RHBbR\ns/vMVVzwQRam6uiXWF8+QK8uMiwzzAmXSRlnQqa5rroHV8/H3rwZL5SqFCOT6heTgqwl6bYtHstX\nuKk5SYslmCmVCYQJy6lpODfhMh2EBCPDWPE4/ugwYBoRi5FifcLFsQSzpTL5MGIqiigqzT3tGbSQ\nOEKgME2DEUbjrOu661Pi3PcZB43JMSO/mDlmUgQvufb0jXHvvcwkzEyNm/2mj5lq7kUfhvMvB8tG\nzkwgykWYOmYCVS66amF3IcQ7R5zNBMzvWKua37lUMNcgFjfX5JJrTUV9YWwUEkk466J3bs4NNNBA\nAw28Y2hY1Z0Cg5WIF/IBTfaJ/6nXlLGKi0nI2oLxmiLUcEZc8t6MxetlzVBVYUchtX/+3+jhA8i2\nboQQxiEDQ9UCIPIS6Olx1NwMxYH1RKcgEOUQWj1Jiyuo1uPy2jyBBWTSVRLJKgq9INLwMMS5iiG8\nuV0HKA0fw21KL2iqhRC42TR+rojT04oW4CCxENSIKObyNJ3RR9s5awzhRhBhvKEjNAJBDp8yIRaS\nAE2vjHOj1U8MizwBWeFypd3F1bIb2xWce60mLBUpT1dJt9S4+BbFjb/rIIsHWL1+O25MUZyVZJrL\nXHLjIS6+ejfUZkwkoOWaijMCvCwgEJYHMm5iAitT1KoV/vJ7B9hxYIKjx3JMBk1sWt2PyB8i9Kt8\n7cdjbN0xyPjQXoYn5jh7RQf2AkdeVNW2YmDX4wgtB9wsoHGkzUZRIhvlKdWK9EU5bnDzrCOHzCwl\nkB7fmC7xZ5NzPF+o0uPatDsWP8hX8LWipDSjQURJmca9slJcnIlxdTZBceVqBo8cgaFDXNzVzpkx\nl6f3H6D57HPp+9xdlHOz+G/sI5ttIgLSE6N88NxzWfHpzzElJD2Ow691ZflANsHjcxU6bRMjHwEt\ntmR93CUSgi2pGLFTVZ+9OMHKDRzVFscqFfI9K4hdcSPOyZXmkxFPwsqNRsIRBjCwCi6/0TTXxZOm\nyrx/JwzuN8mD138OupeafQMfDu6GN3ZAuQjp5uMSCb9WH9sJ5RJkmn9+FnGZJli+7nhD5Oqz4f3X\nm3NmW+CMtcYUXANrzjVj6expD9lAAw000MC7G6eyqhP6ZPupf8M477zz9Msvv/wLOddYLeK3DpTo\n9+QJfrNHqhGXNjvcP1JhbzFC14uhGpP+d2WrzZ8NlQkf+wZ6j9E8z+/fbsPkSdYYWmsYHya7/jxK\nH7oFcbK2EuixDZ9wvRN3rtRsvrAiYn/zMLWTfDVcBGvIsJ05dBhy4MHvMLl1J6ml3SAEnXhMU3tT\nwIrQGntoCnvzatbddj1ykQ60hmIjWfZTwEfVbes0GkEMyRft5ZxlNb/l9dRaoya2oaZ2nmB3J3ov\nRqsQdfBRiMrAIku0WBMke2Ds+flXmyutNUgb+j8ARx6HoETNV/zlo7vYcWiapb1diK73MLj7ec5f\nmeYzH97E1x97ja27R1i29nx07hBDw8NsXN7K3deuw3MXVZnbzoLiUXPueSgNwRz0vs9IOsKyea2o\n75Negr/uDj42VGTQDxeethH8Vo85zjdmSlTrMd0akBqWeg5/2NvMP+XK7Kn44Nd45a8fYHbfbla6\nNrNrNzFz9ceQto0OQ6a+9XeUX92GZUl++YL30vSJz3JYS2wBkTYrH19sz/CDfIX91YA2+zjR9JVm\nTil+t6cZ9xTkuawUX50sMFQLsYWxO8xYki+2Z+hw3iZpnRqH//mrZvVFWGaFIJWFX/kfkG2Gh++H\n6UmwLVORbmqFG+40+37rPshN10l5BK3tJu1wsXyigQYaaKCBBn5OEEJs01qfd/LzDdnGKdDlSjal\nbY5UFWE9nW3CVyQtwQUZmwNlYymXtgQpS+AB4zXFmphAff9v30ScAc6MC/TsJItvWERdR9p7aBvR\n9/+Wt7qZ+b9WuHheQLEmsJTEVpKyL5B2yHuyFjXUgpXZ/FZDs7LuiiFsmxW3XUf75g0Uh8bQWtOG\nR8RxVw+BaZAsDI1x+eaLWH3bRwhtiar/8VG4SD5Aez3S2zQmWnVCW0PRob1TX9DqNGpqJ3gtEGuF\nWCvayaBHnzUe0EEBtKxXfWOAQvgFRPOZJgJQq7pEo07AhDBV4qCEUpKvfHcvOw7PsrQjhQjLUJ1m\naQts3TvBbz/wPFv3TjDQ0wa5NxDxVpZ2pthxcJqvPLobtciBQi67ykg2/JIhzSoCP4fILqvLRYog\nHFOZntdEl4/x51NVBv2QrBQ0WZImKZFo/nAsRxzFTBjhCuOIkRSCqjaSn71Vn90Vnz7Hoj+V5Oo7\n76JrzQb0xnP45Oduo2oZj2nPtum84ZM4Z51Hx9p1bPncHRzSkj7Hotux6XNtlIZvzpS4JOVR1ZpC\nZCzgakozHkZcno6dkjgDPF2oMuSH9Ls23Y5Nr2NTUZpHcqXTfVVOj3/6qiHArZ3Q0mb+Lhfh7++F\nF38Ms1PQ2WOe7+iBuVl4/odmm5s1z7V2mtfkps0+DTTQQAMNNPAOokGeTwEhBHf0xnlfk8Ur+YCn\nZwM6HPjVgQS7y4qUDa2upBJpypEmZgvaXMGjUwGZsIK1iDRLICE0+weP4MSTiPHhE0iyDcwoyXJR\nRZxEnjcmBLiaW1ZXOCOjmQ4Uk76iO6759Ooqu2XOaKg5rnm2MPHer5GjGWN3JmybM269mnh7M3py\njmNUkYgT9gsmZ0m0N7P6s9fxq94aUhiHBh/IYPNr1iqGZZUMDh7WglVdHIsMNm9QBKAahvwwHOfJ\n8BjV0FTLVXEEgUCIRd7FlgNaoecOItL94CSMw4WfB68VEl2I0ig0rQQnDlHFWMfFWyG7HKZ2gXQQ\nlkXclWgV1Qm2gMIwQlgM9LRQrvoM9LSYqr5W5vjSRWtB3LPrcl4b3GZkVMFe82lwU1CbNq9tXY+1\n+pOIuYPgZuqV0JqRi7hZEJIX5qZxABtNQlXxdEBCSipK81TR5+y4S0wKCnVN8+qYQ5MteLZYI2tJ\nImAuUgSOwxV33c3Ax29lRlhsiTs4UlLSENo2W275LJff+UVeCk1D4eKbsxZLMuyHtDg2n29L40nB\naBhRUoprmxJclomf9jP/cqlGq3XiPwltlmRfNaB6Oou702HPNiPVWIxsC7yxC/a8As1tJ461tMPr\n22Hfa+bxYjS1mrGfJwo5GB82dnsNNNBAAw008BZouG2cBjsKAX8wWGHKNzrjXSXj3XtOxq17OOuF\nHjZfmeS4uG3R9NHbqT50P7UDJmFQClDjw7Secz61S24iePzvqe16GdHVb8YmjtK8bgPvvfUubskk\nmKz51DT0xVyOVCI8ofHdKv2rpmgLQSDxbEVIAps4IFAcbwZTGALtIJFIsjhUQ5/X/+b7qMk5Mkt7\n6hVjTmgg89qbKQ2N8/zXH+K8z3+BZlyc+uuyuEgpcCIjunCRC3deDiaV0BaSR4IRHlEjC/P5Oke4\nnWVsEW/9UdOAsFx0dQ7KY6bSKzSoAJ1egpCO8WF2UiDqLhZ23MgfLAtUhEBx21VnonVkKsydGUPS\nhUYIQUdL+qRzCgaPldi8vp/bPrwOYUlw68RS2GhpQaJrQVttxZsRGpAOhFWzUY/1UxG4SSxh0aSK\nrPfHkdqsBOSsJK/Z3cSkwEGw1LUJ6++NAEbDCFfAUT9kLIgWrlm7JWl1LDwBfZ7D+oRLVYMjTKV/\nNIyICfkmqY7GHNgC1sRdVsccqlrjCnHCzdyp4ApB5SSSPO9H8rbvsm2LN6XjKAW2NNZw6uSxyDwv\nhHm8WOOs1Jvt5H5WCHx48tvw+qsmMRHgPZfBe9/fSBFsoIEGGmjgBDQqz6dAFEXcsjPPbKBpsqDF\nFtho/mioSqQUFQWFSBOTxl9Xac1sqPlYp8O0cBHX3I63fC1y8ihqbJhgzXl86a7bUU4M8aFb8Naf\nh5gYJjp2FM5Yy29+6ZdIx2PkQ0W759IXc6lGGiHh7ISp6kZAwoa4rVDAEGVWkCCg7qhQ3xSmIXEL\nbVSIqIY+Bx58lKmtu0gu7SYUmiUkFsjavGwDIUgs7WLs+R3856/+CWEY0CZitIkYPooHg8MMkKRM\nRIjCxcLFwkdRIcILBd9SI4DGReIhCVHcHx2ikDbJhDoKFq6xDium6S/RCcUj5kk7BjIGUQ3mDqHT\nS9ClMaNzdpPgJCEoocuT0LwOU/vW2LbN7R9ey+Y1HQyO59GZAbPPYuIW+WhhMzQLm1e3cvs1Z2HH\nEiYZLyiDilBuGn30pwg7hkx0IuLt6PIE0dGfmnkG9YqktM2mAggrXJey6AhmqAqLioxRlh4qCjg7\nHOOmpgQlZd4jRwgTyR0plrk2yz2H16sBLpCWkoyUHA0iSpHmsnScvNIoBHEpsYXkWBixKuZyadoj\nF0WoRSsVE2HEuphLql49FsLs968hzgAXpGImMbF+TK01xwLFuQnvtHKP0+LcS4xt3TwpV9ronzde\nYKKvZyePa9y1hpkJk2a4cTPMnDw2CRt+TvZwL/zIVMlbu0wgSlMbPP8D2L/j53O+BhpooIEG3rVo\nVJ5PgYcngwXiLOvEIW4JqqHm3uEqZ6dtXsmHFCNdr84JVick+yqaZhtyMY/wutsRjz6I5cZpvubT\nvF6TnJuxeSUPwVW3gBYIv8Lqm26jIxXnP7Rb3HukwnDVtPFZAu7sjfGqO4ZSx6UZYB5HwFNMkcSi\nTHRC818cyaRVpT/0+NHXvsXY1tdIL+0BIchgUxAhloLS5Axee/PC8r8jJHqgnaNbtxMTkvPuvBkh\nBElhM6N9dpOnjwRjVKjWzyiBpcR5nHE0GnvRPZmLqZB+Xxa4ufd9MPoMBKpecfawllxOOP6S0Tpr\nZcgomCqvsGD2dYi3gV+AsFIfcyHWbCQeMmakHFphW4LPfHA1B8crTM3kaU8vgcLw8YsibaZ0N22t\ngs98dDm2zpsmtfnzpfthejcIibBMldukFjYhyhPosO7EoXyjw64fE+lxk7+HnIh4nB6E1mghyMqA\n/2a9wXJ3HVdm4zwxV1kw4+6wLT7ZmuLR2RIDrsV0pBakEa2WRVwKlno2l6VjPF2sIhBojN3dzc0J\nMpZk0I94dtFYr2NzY0vybX/mz095HPFDXirVkMKsZizzbK5pSrztY3LDbC4FggAAGqBJREFUnTB6\n2MR3C2HIc/8K+MQvmfjvqbHjY1rDstWm4gtmbHD/8bEV64x13M8aYQA7thpt9bzjjW0bucn2Z2DV\npp/9ORtooIEGGnjXokGeT4GZwDgjyJMqbhKYDjTrU5KLmyx2FBWh1iyPW3R6FjO+8XFWCnzHQ19/\nF7YQxBzBVKDpjxnLuj0lm+iaz7DU06zLeBSjuvVdNeLJ2YAIOCdlk7EEJW0cHBQn+jgLoExEDAuF\nplxfxo8hiWNRUCGetqiUy0QCfBQWRkLg64jy0Bh2exPFoTGSS7uRQmAjCLQCATPlIodUASktEnUb\nu5IOSWMxhqZUP18WiyQOx+pphCEaVZ/pvDykqENkqococwZ6Zo8hnS2rINZi3Cs0pvo7b7gnPbCT\nEBQRsRZDbIOyIVJOCmo54/PsJCGSEFYJlebrPzrC5FyNM/ozCDeN8vNQnTFEPNFFR3YZh19/ma8/\nYXH71Ruw/VkjDUj1GwIdlFBKQf4I+PVowngHWgjjBuImjAhc1cynwU6CEMiwyF1OgRsLuyiEhnz2\nJFqxZQahAj6cTbM56XHUj0hKwYBnYwlBUUGzbarN06HCE4KOmPHVDjScn/Q46ofsrPi0WBaXpFyy\nda3z5qTH0VrI7qpPm21xScojU/+8vlSq8tWJAgdrIS225OMtCW5sSp7WT9kWggtSMUb9kH21gG7H\n5tKUt1DJfluIJ+FX/xgO7ISxIWjvNTZw8/PYdIGpNo8NQWc/nHWhSe8DuPazxlO5kDOWcW3dPx8J\nRRRBGL45RdBxTHNjAw000EADDSxCQ7ZxClzZ5tW1zMeXxZXShBquanc5WInYW1a0OIJuTzIRaF4t\nBFza4nLEN9HKAEJKIiEYDWBdXPB8LuT1MqQsaHYFx0LJT3MBXbbiw9vm+OFMgCchKWFbIeTqV+ZY\nEWROCECB401+a0kzi08ZtaBNraKYJWBAx9ghCyz/wo00bVhB+cg4kdaM6SqlwVGym9ez8Xe+QPvm\nDZSGxlBaU9YR6sgEyQ1nMPCF6+tkS1MgZI6QZTrBduYoLjrfHBGvkGM9WRSGPM/Dr0tD3qOzRIOP\nw9wBiLebRruJ7aiRp9GxTghysChOHFUDfxbZst5UeYWN8LIINwNamUp50wrwcxD5hNrigcdeZ+uu\nQQY64uAkUBOvQG0O7LghxsVh9MweBpYtZ+tL23ngoZ8S2imwE1AcMQ2C6SWQP2z8paVxuiA/CNVZ\nSA+Yv1WAue8UhmBHFXSqF6Z30xpMMyBqLNFl7MJBY3vnGj/gFttiY8JlecxZkFI024KfFGrMhoqk\nMO/sy2Wfg7WQSGu+PJHnqB+x3HOIScE3Zso8VahyLIj48kSe0cCMuULw9ZkSzxZr7CjX+C/Dsxys\nhWQtE6ryJ8cKPDB9eiI47IfcOzHHTKRY4TkA3D9dYlup9q/92rw1pIQzN8El15nEvnniPHwQHr7P\nxHr3nQFBzVjXDe4340JAR6/xX27v+flpj13PEPfCSXHb+RwsX//zOWcDDTTQQAPvWjTI8ykwELf4\neJdLIYJcqMmHmtkIlsYlt3Z6JCzTMFdTUFVmNTouJU/N1E6Z4vbtiRpVbZwwNAKFwJYCreHvxn0O\nVyKaLfCkwJWCFkeQCzXfG3vrJYLFyYKLacW87/QTTAJgeS5n3v2xBQJdGhpDbV7J8tuuw4p5LK/b\n2JWGxigfGcfbcAbr7r4Z6bmmJ65+PBvBNmYXGhLnq98SQ5h9QjwEGiMpmZeRJJF01ebQtRzEWhHS\nNk2CsTZUfgimdp/yfVBBAZlZCtUptF8wx/BziM7z6s2FFlprHnxsF1v3jDPQmUZIC10cMU2HlsfE\nbAkt6jZ4lSkIygz0tLB15zAPfvsFo8MWEiFddFg1shCtDWlXIQgLIR2IqvVmsvmrUtdTCwvmBs3Y\nwjgmeCUoocNTOzfsKQdIYZpNo/oVdQVMRYon8hVCrelwLGwhSFuSLtvi8XyFn+QrRJw41mlb/PNc\nmQemCiA0rbZcGGuxJN+cLVE9uUFvEX6cr2AjaLXNMbOWpNWWfG+ufIK2+meGrT+EeMrII6y6TCKZ\nga0/+Nmf63QQAi691nyepsYNiZ4YNRHlZ1/4i51LAw000EAD/+bRkG2cBl9ek2VzU4WvjVQphpoP\nttr8ytIkR31Nb8wiawu25wN8BSuTFv2e5MW58Lhvcv0482T2cA2aHYFtCY75CqWhzRVIBK8WDXVS\nQlCJDFFxpUACu8sRa3DxUeTr1dkkFjEkw1SxETjIBQ1yrN6oN8HxiuE8gd7/lYewEzH6PnctkW1E\nFdK2WX7bdSYFsVxl4AsfxfFcBJI8AQLI4KLRHK1LM2Q9cRCMNMOM1TiXLENUmKCGAPpI0IVHPsjR\nEmn03CCUxw3JTC9BWi66MgrUied8g580ThrMHUav+Ci6MgNTO8BykX0XY7WuRR3bhnab0EGFSi00\nhUk7Zo5TyxlXjdEZ2ptTDI7OGLs6qFvhNSG9kEooIdaCTLShoyqicgyyA4Y0+3mQNiLWgg5rUBoz\nHtUqMvpraYGbNpZ1pdG6O4c0zY5Smop2UILyFNpOogvD6PI42AlkdhnCTXPYD+m2JVWlKSiNi6DL\ndSgqza5qQOokmYUnBdORZn8tIH3SWEwKZiPNgWpIXAiKSlFRGkcIUlIyFykmQ0W/+9b3zEN+SEIK\nRv2QXKRISkGXYzMVRVS1JnG6ym+tYtIAj41ASwes3ACJ1KlfD/XXnmRHl0wb4qr1L9blorMPPvkf\nYe82IyPpXmrkJfG3ryFvoIEGGmjg3yca5PlfwKe743y6+0R/3LKO2FsM2F+KjFWdhlfyIYddwfub\nHF4oRG+SWAD0OjASKErqeKV4pKZxBFyQlbxWiJj19cKqdkVplIblMROEotGksReOV0XThccgZXwi\n7PpRw7pUohWXoycR6NW//HHTNCgcZhcJLKRts/yO60FrumWaEapAhFevb1eI6o2BCY7ho9ALNwXz\nR+kixghVLCQ9mCazAE2eiKRIwszuejof5gJUp1FeK8Q7TEVYLvo41iukOtGLfvVPjayiTqbUGw/h\nl45BrB38l5A64gvXbuAvv7ODHQenWNrdBPF2BofH2XzWSj5zzXl8/bsvs3XHIAMdCXDTDB8+wMZ1\nq/jip6/G8hy01oiwAvFORHXWaLFjLWYOWiGiKjrZbeYZawKajs8z8iHVDbNvGALtxE/8Hdw0+sgP\nUcUx40utI6LJ17CWXkGv67C76mNhbpQCYMwPiFsWq2I2e6shiylooDW2EAy4NnuqAclFPNhXZqzX\nlWwt1rDqseoaxaQOydoWrfapF5taLcn35kxF2wKUFuyvBayLuXinI7KlPDz0V8ZFw/GM7dtLP4Eb\nPw/N7afer7UTyvkTEwMrRfP8O2EPl22BzVf84s/bQAMNNNDAuwoN2cbbgCMEhysKKUwkctKuL7X7\nmvUJyan+27++y/j1am2W6Z06+/Q1XNRs40hDntCGkIf1IuzH2uMIDEm1ME19Yb0l7yJakcxXuY0S\nOkIjELyPtjfNQUjTbHY+TW8eEwIhJe+jDV0/zryuOaqf7wraEbCQTjh/VgvYQiul+kisblWn0ZRE\nSLIyCWEJY0TsGA2yFkZb3HexqeJGgSGcSoEOTWOgjoxu2IqbSq6dMM2Eo8+BqL8O8DyHuz9yFhuX\ntzI0PsfQjGDzhqXcftVaYo7F7deew+Y17QxNRwxPh2xYvYy7b7oI17XRKkBUpxBNK7Da14PloGt5\ntNZoFUB1GtG0Erv/EkPw/UI9fTAwEpKWVdhLrjAV7/mxqD7WuhZqs+iiqVoLLwuxFrTlEY08w8a4\nQ6BBaVUPu9FUNbRagiszcbTWzIQRWmsqSjEamKTAyzNxIq2ZXTQ2FoZ8IBNnU9zDx8iB7Pp7WNPQ\nZUvipyGlCSkpRKZpMSklMQmlSGNLTm939/JPYW7G6JOb20wqYODDM/986n0ANn8ACnkoF8yXolw0\nOuPzLz/9fg000EADDTTwDqJBnt8Gns8FZGzocCWhNrrnlCNpdwTfnw3p84yueR4W0OHAS3lFhyto\ndQWRNm4KaRu6XMFTOcUVrQ59MUGIMXRodeH9LTbDyme1yNCJ8VuuoWjFY41Ic0TW2EATzbhECCIE\nGRzWkeYNSlhvMX8JHKZKdlHQyfzzWSSDoswq0rTi4qPx0bQTYxVpxq2AdWSIIxeaFlNINpJlSFZY\nIuO0Co8qETUUXSJGj4hzrHjYEE/bNdIMrUzEtbCQpVHkhi+Al8E0DUaQ7Eae+2sws5O67cmiidbd\nrCd3mWY8OwY6wnMFd994PptW9XLhuWu467/+KU62F4I8NgF33HE7F37oU5x19rn88m/8EfGWJYja\nDCKsIjrORnZvQThJrIGrkMmOhTHZcQ6y63xksgt73WcQ8TYI5iDyEV3nY628GZnqxl77WUSsPqZ8\nRPdmrBU3wtwg2o6fkAYo7Dg6KJH3q1yc9EhZlkkRRLAx7rA85uAIyT0dWbpcm5EwwtdwY1OCyzNx\nel2bezoytDsWI2FEANzckuKydIyS1lyc9IhLSVkbff3ZcZcex6JwmqTAkSDk/KSHJwT5yNyOnZdw\n8RWn1Uqzf4dJ/1uMbAsc3gtR+Nb7gLGlu/Yz4MaMq4bjwtW3wIpGk14DDTTQQAP/dtGQbbwNJCwA\nQbsraTOmBAgBYzVF2ha4UnJ+k0QpU621pGS0asYkghUJuRDPLYRgtKrI2CAiyae74ygV1fezOFKN\niEv1/7Z3/8FylXcdx9+fc87e3Ztf996QkBtCSECiMQUbYghJC4r9AQQdAhUYWqrglLGoUDujo536\nq/IXOk4ddGzVQaboOFin1RbHdphC1SIz/RFrNFDslDJWCAm5IT8g4f46u1//OCdh8+PenED2bvbm\n85rZydnznD33u0+e3fnuc57zPIwq4bJk6MiNW4nESIxRV8KcJOUntJhmOWdxmqaMxDi0ghoJg2Tk\nRZ82GTUOklMnoU7GUtXJoyxTjb0xTl0Z/WqxXnOLaduAJEkYiXHqJAwmfWzWUvLy72Vpyp4Yp66E\nWiQsTfpZ2fb+RmKcTDWKXucGR2X0rRyyBtniS2Hx/eT5GJCRlSvJTWSNqf8jsgZMZsVy3WVSWE/E\nPbf0U1vzAdKhC2HoblqtHEjoSxI+vDqIiGIWkQVLiGgBOjqxbQyRrnjvCcuSgYtILrv3yDnbp35L\nBi8iWXd8WTOtFz3obSKKYS/9ScKiWsL7+vtoRqv8MVOsIliTWFlPuefcBTSj6EFuj+XCeo2PLBk4\nrqyhhKV9Gav7+8hbxTlD4uW8VVztmEJ/ktBMYdO8BlEOy8kD9uRNpr6eQjFbRTMvkt/DWs3iuU7y\n+/yH1hSPZrP4geTV/MzM7Aznnuc34aqhGkOZ2DtRzAUtwWi5WMq9y/sZyMTeyRZJkpAmCaPNYhnv\ne5fPYX4m9k0WU61J4vW8KLtzWT8LyrIkSUmTlEPNIJW4as486qQcipykXKFuLJpkJKxLhugj4fXI\nSdOUNE3LMrE5XUqCyvHQNTJqTNAkRdyYnEdGwljkZKqRqcZY5NRI+MlkERliNJokSZEEvh5Fwr02\nGSKj/PtpSpamR8ouS4ZIyrLD7+9Q5PSTsuzcy4uKalthsLixLkPDG47syrLGkcQZIF12VbHRauvB\nbBYzYmjldUA5RCJR8Zg4SFKfh4ZWHTk8SbIjiaykoxJeKTkqIW03XVn7OU9WpqFV0BwnWkUCHRFo\nYj+aO8ymgQUcagV5BKkSQOzKm6xu9DHYNj45laaM5diyK+fV2d9s0YwgK4fp7JpssW5Ojf5p5nm+\ncl6dveXrVA772JU32TC3Mf0Kg2/fBPtfeWOp7Qh4ZTdcuuHoKwbTSVMnzmZm1hOcPL8JfUnCA6vn\n05+KHeMtdo63eK0Z/PrKfjYO1Xlg9XzqiXhpvMVLZdlvrpzDhqE+Hlg9j1pZtnO8uHnw4xfO4cfm\n17j3gjlkifi/sSYvjBVLNN99foPhesb12TACXolx9sQ4E7S4JlnCUNLH5mwpAexpK7suHWZFNpcP\npisI4BA5h8hpATfrPH6kNsD70+XkwL6YYF9M0AQ+mK1gOO3nunSYnNaRcwawOVvKwqSPa5MlTLSV\n0VZ2zTFlAjZnwzQGL4YV1xRjlCcPFeOflZCuvp20b+pZGdJz1sD5P1Uug334dRnpmjuoLfxhtOJa\naI4W8zmP74esTrb6dpLkzLmoorlLSZZcjiZfJcb2FuO8GwtJll3J6kaNnxmYw0jeZOdkzo7JJsv7\nMm59CysFvn1OH+9d0GBX3uSlyZyX8iarGhlbBqc/5/q5da6e/8brduRN1jT6+OnB/mlfx6VXFMtp\n79kFI7uKIRgXXwIbPHbZzMxmH0Un5m/tkPXr18fWrVu7HcYRE60WT+3POZQHGwdrLGqbAmyi1eLf\n9+WMtYKNAzUWtpWN5S2eOjDJeAveMVBjs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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "0b4sApqGOBFH", + "colab_type": "code", + "outputId": "68175adc-a3b1-4d4b-829e-efb402f9877d", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 442 + } + }, + "source": [ + "# Com o seed\n", + "kmeans = KMeans(n_clusters=50, random_state=8) \n", + "kmeans.fit(df)\n", + "\n", + "centroides = kmeans.cluster_centers_\n", + "y_kmeans = kmeans.predict(df)\n", + "\n", + "plt.scatter(df.visitas, df.tempo, c=y_kmeans, alpha=0.5, cmap='rainbow')\n", + "plt.xlabel('Tempo')\n", + "plt.ylabel('Quantidade de visitas')\n", + "plt.scatter(centroides[:, 0], centroides[:, 1], c='black', marker='X', s=200, alpha=0.5)\n", + "plt.show()" + ], + "execution_count": 107, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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3IfU9swLe/W5IvsesiteqMPQPMPQ9kxvT/S5I3l8fw2OIGYaZA6CHJrppWSrptpoy7qqZ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TUzusakrhrpJGAcnxCNK+anM6UQSAR9uvRaNfU8zgJUI83xcsRE7fR5yEqpRYGzEMYRcDaA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\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+Wcbqpc/biIxw2Eobs7SoE9AkYIYWPWTYQJHNF43N0qKXDAEKD60Jm0sfFECIpEnABvKU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E+zu3BxLe6l/z97bx5t11XfeX72PuOd3/ye3iA9eZAtW7ZsyZZsbDMY3JBgMDgQitHGGJJyh87q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\nmZll5OLZzMzMzCwjF89mZmZmZhkpIhodQ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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "xKse31GuOBFM", + "colab_type": "text" + }, + "source": [ + "Altere o número de clusters e rode o algoritmo de novo. Vamos ver o que acontece :D\n", + "\n", + "Não se esqueça de adicionar uma seed!" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "tLnMzzGsOBFN", + "colab_type": "code", + "outputId": "7820bc87-ab8b-491e-c204-cd52a6aec24b", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 442 + } + }, + "source": [ + "# TODO\n", + "kmeans = KMeans(n_clusters=3, random_state=8) \n", + "kmeans.fit(df)\n", + "\n", + "centroides = kmeans.cluster_centers_\n", + "y_kmeans = kmeans.predict(df)\n", + "\n", + "plt.scatter(df.visitas, df.tempo, c=y_kmeans, alpha=0.5, cmap='rainbow')\n", + "plt.xlabel('Tempo')\n", + "plt.ylabel('Quantidade de visitas')\n", + "plt.scatter(centroides[:, 0], centroides[:, 1], c='black', marker='X', s=200, alpha=0.5)\n", + "plt.show()" + ], + "execution_count": 108, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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5TyYPvb1MjhoayNTR2Ijd46PQ1cX5Rso8Eq0tGh0d7GeypyiKoijKxwyNPI+V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E1K/n+zXvMvbpXPAE+LnUEKv3kSbgoj9lBXkuaCE+L8XD96O2HVj7IbbJG6Y0aWAPK+/+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\nPJSdRJro53ziEbb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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "fSEANPcCOBFW", + "colab_type": "text" + }, + "source": [ + "![](figures/inercia.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "356T2hleOBFW", + "colab_type": "text" + }, + "source": [ + "Para escolhermos o número de clusters, observamos o gráfico do cotovelo com as inércias e escolhemos o ponto no qual a inércia começa a ficar mais plana e formar um \"cotovelo\":" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "jfKSvn9bOBFX", + "colab_type": "code", + "outputId": "e1eb4db8-c34a-4bbb-ee52-46fb86f8e6c2", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 442 + } + }, + "source": [ + "# Quantidade de clusters que serão testados\n", + "k = list(range(1, 10))\n", + "\n", + "# Armazena das inércias para cada k\n", + "inercia = []\n", + "\n", + "# Roda o K-means para cada k fornecido\n", + "for i in k:\n", + " kmeans = KMeans(n_clusters=i, random_state=8)\n", + " kmeans.fit(df)\n", + " inercia.append(kmeans.inertia_)\n", + "\n", + "# Plota o gráfico com as inércias\n", + "plt.plot(k, inercia, '-o')\n", + "plt.xlabel(r'Número de clusters')\n", + "plt.ylabel('Inércia')\n", + "plt.show()" + ], + "execution_count": 109, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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SAkUbkqSrzi7T2GG5Wrhko+8oAAAAaYGiDUlSdiSk6y+eqlVb6rR6S53vOAAAAEMeRRuH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\nBmX843Je29imtdvqtaexVa0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" + ], + "text/plain": [ + " id tem_cartao idade renda score\n", + "count 200.000000 200 200.000000 200.000000 200.000000\n", + "unique NaN 2 NaN NaN NaN\n", + "top NaN Sim NaN NaN NaN\n", + "freq NaN 112 NaN NaN NaN\n", + "mean 100.500000 NaN 38.850000 6056.000000 50.200000\n", + "std 57.879185 NaN 13.969007 2626.472117 25.823522\n", + "min 1.000000 NaN 18.000000 1500.000000 1.000000\n", + "25% 50.750000 NaN 28.750000 4150.000000 34.750000\n", + "50% 100.500000 NaN 36.000000 6150.000000 50.000000\n", + "75% 150.250000 NaN 49.000000 7800.000000 73.000000\n", + "max 200.000000 NaN 70.000000 13700.000000 99.000000" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 112 + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "a8-ntnYuOBFo", + "colab_type": "text" + }, + "source": [ + "Esse conjunto de dados possui 5 campos:\n", + "\n", + "- **id**: código identificador do cliente\n", + "- **tem_cartao**: indica se o cliente tem cartão de crédito do e-commerce ou não\n", + "- **idade**: idade do cliente\n", + "- **renda**: renda mensal do cliente, em reais\n", + "- **score**: score indicando o gasto do cliente. Quanto maior, mais o cliente gasta no e-commerce" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "gX5wY4EBOBFp", + "colab_type": "text" + }, + "source": [ + "**Observando os dados acima, quais pré-processamentos vocês acham que serão necessários antes de realizarmos o agrupamento?**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "C5szPP7mOBFq", + "colab_type": "text" + }, + "source": [ + "**`1° - Remoção do identificador`**\n", + "\n", + "O conjunto de dados contém o id do cliente que não iremos utilizar para a segmentação. Precisamos remover antes de realizar o agrupamento:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "PXgzDb53OBFr", + "colab_type": "code", + "colab": {} + }, + "source": [ + "segmentation.drop(columns='id', inplace=True)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "7Z_-AUeEOBFt", + "colab_type": "text" + }, + "source": [ + "**`2° - Lidar com feature categórica`**\n", + "\n", + "Temos mais um ponto para resolver antes do agrupamento: a feature `tem_cartao` é categórica e o **k-means só lida com dados numéricos**." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "odqpOVFaOBFu", + "colab_type": "text" + }, + "source": [ + "![](http://giphygifs.s3.amazonaws.com/media/dJtDZzyjLF66I/giphy.gif)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Yjkf9C9NOBFv", + "colab_type": "text" + }, + "source": [ + "**O que podemos fazer para lidar com variáveis categóricas então?**\n", + "- Feature engineering (One-hot enconding, Label Encoder, etc.)\n", + "- Utilizar outro algoritmo que permita usar esse tipo de variável\n", + "\n", + "No nosso caso, vamos utilizar o [LabelEncoder](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html):" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "AwuSc9BKOBFv", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# importar o LabelEncoder\n", + "from sklearn.preprocessing import LabelEncoder" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "Z2aeM2YyOBFx", + "colab_type": "code", + "colab": {} + }, + "source": [ + "label_encoder = LabelEncoder()\n", + "segmentation['tem_cartao'] = label_encoder.fit_transform(segmentation.tem_cartao.values)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "2elcvXu8OBFz", + "colab_type": "text" + }, + "source": [ + "**`3° - Normalizar os dados`**\n", + "\n", + "As escalas das features são diferentes, então precisamos normalizar os dados:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "HHQC_zDZOBF0", + "colab_type": "code", + "colab": {} + }, + "source": [ + "from sklearn.preprocessing import StandardScaler" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "_wAmbU__OBF3", + "colab_type": "code", + "colab": {} + }, + "source": [ + "scaler = StandardScaler()\n", + "scaled_segmentation = pd.DataFrame(scaler.fit_transform(segmentation),columns = segmentation.columns)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "l1UEqjzGOBF5", + "colab_type": "text" + }, + "source": [ + "**Agora sim podemos aplicar o K-means \\o/**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "DcSH7RzfOBF5", + "colab_type": "text" + }, + "source": [ + "Primeiro, vamos utilizar a regra do cotovelo para escolher o número de clusters:" + ] + }, + { + "cell_type": "code", + "metadata": { + "scrolled": false, + "id": "ndosxe9uOBF6", + "colab_type": "code", + "outputId": "87a6db6d-66fd-4135-f2a5-d6415a988bb4", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 442 + } + }, + "source": [ + "# Quantidade de clusters que serão testados\n", + "k = list(range(1, 15))\n", + "\n", + "# Armazena das inércias para cada k\n", + "inercia = []\n", + "\n", + "# Roda o K-means para cada k fornecido\n", + "for i in k:\n", + " kmeans = KMeans(n_clusters=i, random_state=1)\n", + " kmeans.fit(scaled_segmentation)\n", + " inercia.append(kmeans.inertia_)\n", + "\n", + "# Plota o gráfico com as inércias\n", + "plt.plot(k, inercia, '-o')\n", + "plt.xlabel(r'Número de clusters')\n", + "plt.ylabel('Inércia')\n", + "plt.show()" + ], + "execution_count": 118, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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KKpEk7/o+7/4jmNk0Mysys6Ly8vJg1g6cUHJ8rGZOHqOLT++pf35xlWbM3+h3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\nye3HWbbih2C213lC0hVHjd0r6U3n3GB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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "uIJhbaSQOBF9", + "colab_type": "text" + }, + "source": [ + "Com base no gráfico acima, podemos escolher a quantidade de clusters que serão criados:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "dHByqJCVOBF9", + "colab_type": "code", + "colab": {} + }, + "source": [ + "model = KMeans(n_clusters=4, random_state=1)\n", + "clusters = model.fit_predict(scaled_segmentation)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "uKkCV7DtOBF_", + "colab_type": "text" + }, + "source": [ + "Após o agrupamento, precisamos reverter a normalização para podermos interpretar os clusters formados!" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "DP8KSNTEOBGA", + "colab_type": "code", + "colab": {} + }, + "source": [ + "original_segmentation = pd.DataFrame(scaler.inverse_transform(scaled_segmentation),columns=segmentation.columns)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "KgTs3SUOOBGC", + "colab_type": "text" + }, + "source": [ + "Como utilizamos 4 features para criação dos clusters, não podemos visualizá-las como no 1° exercício. Podemos utilizar o [pairplot](https://seaborn.pydata.org/generated/seaborn.pairplot.html) para tentar interpretar os clusters:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "3st56dolOBGD", + "colab_type": "code", + "outputId": "d1d0587f-d3f6-47af-9fca-84c7a7f709f1", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 905 + } + }, + "source": [ + "original_segmentation['cluster'] = clusters\n", + "sns.pairplot(original_segmentation, hue = 'cluster');" + ], + "execution_count": 121, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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IiIhIVVGiKyIiIiIiIlVFia6IiIiIiIhUFSW6IiIiIiIiUlWU6IqIiIiIiEhVUaIrIiIi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\nsw9lwusTYmz7ljMepq+zwBRMSyNMnzY5mH5k+tAbge47Qoh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9kRA36S4+3WdYouiTphpv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\n/tPKhCzFwfvYUErx44PsPLjCx2tr2zn5O1Ywm5lg9RDpV98BIOXooyOe35q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dm7A7UqugkQ2tFkOLpDsJlkHrvgWK5c8168XOexC47Flk/CiZEgvHBxcoeGFy6GH/xxcseV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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "cZQQfp9_OBGI", + "colab_type": "text" + }, + "source": [ + "**O que podemos identificar com base nos clusters criados?**\n", + "\n", + "- **Cluster 0** - esse cluster compreende os clientes mais velhos e menos engajados, visto que não apresentam o cartão de crédito e que apresentam score de gastos mais baixos.\n", + "- **Cluster 1** - esse cluster compreende os clientes adultos que possuem o cartão de crédito e um score relativamente alto, indicando que esse cluster contempla os clientes mais engajados.\n", + "- **Cluster 2** - esse cluster compreende clientes um pouco mais velhos que, apesar de possuírem o cartão, não gastam tanto no site. Pode ser interessante realizar campanhas com promoções e mostrando as vantagens da utilização com o cartão de crédito do e-commerce voltadas para esse público mais velho.\n", + "- **Cluster 3** - esse cluster é similar ao Cluster 1, com a diferença de que os clientes nesse cluster não possuem o cartão de crédito do e-commerce. Pode ser interessante realizar campanhas para engajar esses clientes a adquirirem o cartão.\n", + "\n", + "Além disso, para esse agrupamento, a renda mensal não parece diferenciar muito bem os clusters, visto que todos apresentam uma distribuição relativamente similar. \n", + "\n", + "Talvez com uma quantidade maior de clusters, a renda poderia variar conforme o cluster que o cliente pertencesse! Só temos que tomar cuidado porque quanto maior a quantidade de clusters, menor é a quantidade de exemplos que estarão em cada um deles:" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "JpFxgzmIOBGJ", + "colab_type": "code", + "outputId": "82429638-0654-4963-db53-4856347e0787", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 102 + } + }, + "source": [ + "original_segmentation.cluster.value_counts()" + ], + "execution_count": 122, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "2 56\n", + "1 56\n", + "0 48\n", + "3 40\n", + "Name: cluster, dtype: int64" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 122 + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "zupZTR0fOBGL", + "colab_type": "text" + }, + "source": [ + "Além dessa análise dos clusters considerando a distribuição das features em cada um deles, **também poderíamos utilizar os centroides para caracterizar cada cluster**, visto que eles são os representantes de cada grupo." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "8vxAWsfNSeFt", + "colab_type": "text" + }, + "source": [ + "### Exemplo - compressão de imagens" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "aK-DCxZuSmmE", + "colab_type": "text" + }, + "source": [ + "\n", + "Vamos agora ver um exemplo de aplicação do K-Means trabalhando com imagens :D" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "k-Y-gRDwSmCL", + "colab_type": "code", + "outputId": "6b352409-be28-4bf9-fd05-9747a51ec8a5", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 428 + } + }, + "source": [ + "# Importar a imagem\n", + "img = plt.imread(\"data/mario.jpg\")\n", + "plt.imshow(img)\n", + "plt.show()" + ], + "execution_count": 123, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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Eq3lOiBYja62lzM9XVaYwstls+Ge/67vw3h+yc+dcRbS0rnEhsd50+MbSrRqM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\nbhPf1fPu/+QX2P5n/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9kMP0VURmgLSh4o7z22aSmlcOPGYdV2SSfs+efu8eabb2Ir03EX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Kw4ECJcrcR5foKXZ0W5slaaxSrSEFT3KctCLYqYMuN8S05CANUTZoW3S0otjNudFBmqiWlq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\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CUJr3JDGXoMVZ31VRERTGlIsg+ERMPcrUdBvFt3//Dt5HFFtUumHTHRHDnJygHwSuF6yW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jlirXeGc4at7BlTdoeYv5zoK2gtoVigheKkxZMgynDLGm+CkdJ1RUTPIdDvcesnftkCI3WV4e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\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SmF11FN/ep3s04qsRtVHYkGjbjivXZhztlyhdUG+P+LH/8u/x2W9/mWvNdQ7GRxw1ga0t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QnUiDHLWFjJhSHxlO44clh1o7m5sl8uWmtuSXVa0F2oQk0txENXlFXUWDHeiLQBQYPEEBm6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\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QAAvuRGM2DXOegSSRz9Uaqq5pdNDoCCpnAlBGi99pzg4zL53AP3pNced8CznQmMptqyPh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\n5YzYnZPKqwzxg0gdkWAY6x3k/Asc5VfZP9ozHzx2rEwXhXI9YnLATJ4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+310HB7QwCJU+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EMTZtDsoAAAt9SURBVCMUEfZqqdviFkkVhVS9A57ZH9EKc4hdB11zY6tt7CXR7uShop7+xIsN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\nAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "VMwVe04FSmFL", + "colab_type": "code", + "outputId": "26a0c9be-fc70-47d0-932a-0880d6bef189", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + } + }, + "source": [ + "# dimensão da imagem\n", + "img.shape" + ], + "execution_count": 124, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(675, 1200, 3)" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 124 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "MBA_AvvVSmK6", + "colab_type": "code", + "outputId": "5201f8fd-b97b-4327-d81a-87acbd2a3342", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + } + }, + "source": [ + "# redimensionar a imagem para termos somente duas dimensões de dados\n", + "x, y, z = img.shape\n", + "img_2d = img.reshape(x*y, z)\n", + "img_2d.shape" + ], + "execution_count": 125, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(810000, 3)" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 125 + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "pIIG5AuBTQZg", + "colab_type": "text" + }, + "source": [ + "| Pixel | R | G | B |\n", + "|---------|-----|-----|-----|\n", + "| Pixel 1 | 255 | 0 | 0 | \n", + "| Pixel 2 | 255 | 102 | 102 | \n", + "| Pixel 3 | 0 | 0 | 0 | " + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "Txy5hiHSSmIE", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# TODO\n", + "# Escolha um número de clusters e use o K-means para realizar os agrupamentos\n", + "kmeans_img = KMeans(n_clusters=15, random_state=8)\n", + "kmeans_img.fit(img_2d)\n", + "\n", + "cluster_centers = kmeans_img.cluster_centers_\n", + "cluster_labels = kmeans_img.labels_" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "0-XBTNdYTXkU", + "colab_type": "code", + "outputId": "a1bb21bf-9894-48f2-c4c1-5f8220bb4d0a", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 428 + } + }, + "source": [ + "# Plotar a imagem após a compressão\n", + "plt.imshow(cluster_centers[cluster_labels].\n", + " reshape(x, y, z).astype(int))\n", + "plt.show()" + ], + "execution_count": 127, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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+MovofWtv8Iq5tnwuk55iWSMaN5MAb9BkeQRV4EqHSSmm1Fni7/UHwA2iMT7r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\nJOP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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "rK3M6OtrPaJw", + "colab_type": "text" + }, + "source": [ + "Quanto maior o número de clusters, mais colorida a imagem ficará." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "REBB9M_POBGP", + "colab_type": "text" + }, + "source": [ + "## Hierárquico: **Agrupamento Hierárquico Aglomerativo**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "eHbZqM9bOBGQ", + "colab_type": "text" + }, + "source": [ + "![](https://media.giphy.com/media/pSNCWCEAsgrAs/giphy.gif)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "KBa752quOBGS", + "colab_type": "text" + }, + "source": [ + "### Exercício 3" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "8qLAQVG0OBGS", + "colab_type": "text" + }, + "source": [ + "Vamos utilizar o mesmo conjunto de dados utilizado no segundo exercício do K-means para realizar um agrupamento hierárquico aglomerativo. Para esse agrupamento, precisaremos importar o dendograma do [Scipy](https://docs.scipy.org/doc/scipy/reference/cluster.hierarchy.html).\n", + "\n", + "O sklearn também possui um [módulo](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.AgglomerativeClustering.html) para realizar um agrupamento hierárquico aglomerativo, mas é complicado visualizar o dendograma com ele, então vamos ficar com o scipy mesmo." + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "fFXGd-5fOBGT", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# importar os módulos dendogram e linkage\n", + "from scipy.cluster.hierarchy import dendrogram, linkage" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "OtoD0a9aOBGV", + "colab_type": "code", + "colab": {} + }, + "source": [ + "h_cluster = linkage(scaled_segmentation, method='complete', metric='euclidean')" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "zEnzqb8HOBGX", + "colab_type": "code", + "outputId": "6eab5b83-236a-43d8-b430-9cec0eecb4ab", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 458 + } + }, + "source": [ + "plt.title('Dendograma')\n", + "plt.xlabel('Exemplos')\n", + "plt.ylabel('Distância')\n", + "dendrogram(h_cluster)\n", + "plt.show()" + ], + "execution_count": 130, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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qC0Nbf7PRlCTNTc0NLQ2StHZ6rdbPrB9qGlBOXQNkd98YP14q6TZ33ypJZrajpF0LThsA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\nR7ZdZmbK5cVyl7dS2bLj8m9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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "6sFsDczyOBGa", + "colab_type": "text" + }, + "source": [ + "**Vamos testar outras abordagens de agrupamentos e métricas de distância?**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "8XT03nllOBGa", + "colab_type": "text" + }, + "source": [ + "![](https://media.giphy.com/media/12zV7u6Bh0vHpu/giphy.gif)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "DmQgH8amOBGb", + "colab_type": "text" + }, + "source": [ + "**E como podemos escolher o número de clusters?**\n", + "\n", + "Podemos visualizar o dendograma e observar onde há a maior distância entre os grupos formados." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "HziBNsH_OBGe", + "colab_type": "text" + }, + "source": [ + "## Por densidade: **DBSCAN**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "g0d6X_10OBGf", + "colab_type": "text" + }, + "source": [ + "![](https://media.giphy.com/media/lCL2GQewp7fkk/giphy.gif)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "mukUxpTHOBGh", + "colab_type": "text" + }, + "source": [ + "### Exercício 4" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "H9fxh4oNOBGh", + "colab_type": "text" + }, + "source": [ + "Vamos utilizar novamente o conjunto do primeiro exercício com o DBSCAN, que vamos importar do [sklearn](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html):" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "POKAI1vHOBGi", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# TODO\n", + "# Importar o DBSCAN\n", + "from sklearn.cluster import DBSCAN" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "hcpdXFOTOBGk", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# TODO\n", + "# Escolha um epsilon e um minPts\n", + "dbscan = DBSCAN(eps = .1, min_samples = 8)\n", + "# salvar os clusters atribuídos para cada exemplo\n", + "clusters = dbscan.fit_predict(df)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "3xdXTRrjOBGl", + "colab_type": "code", + "outputId": "879d2ce4-d23e-4105-dc75-701f4d1f15e8", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 442 + } + }, + "source": [ + "# plota os clusters encontrados\n", + "plt.scatter(df.visitas, df.tempo, c=clusters, alpha=0.5, cmap='rainbow')\n", + "plt.xlabel('Tempo')\n", + "plt.ylabel('Quantidade de visitas')\n", + "plt.show()" + ], + "execution_count": 133, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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XWYzFkQaUrwTyFhy6x3o89LVQDLft5O9y6gVcLBmLgXY+RYnEGg8EPfyNi3VDEARBEI6C\nBYOGYbgAPAXgVtM0RyzBMk3zftM0F5mmuSgr68imstj5FLDhHmCgg5G3iueA9b9iuWiAJZ8LTmaO\n40kTzqYJ/PnPwEMPUbx6vcCjjwJ3300h/ac/AQ8/TAE6MAD8/e/AH/9Ii8U99wCPPMLtAwPA3/7G\n78daAFhaylRzkd9Rn/PygN//nlk1fD4K7Qce4NimTOExExMZbS4s5OJBgKI6Gj4f8OtfA08/zRuB\nzk6O8YknJmL2RuDvB9b9L7DnpcE83i3A+3fRupA9d+QiwaCPmVbiEoG3/wfY+xoAk7mk37uTIvxI\n098KrP3pYKTcZJXFdb/gjWAscuYB/cMi6F437Sk2x+j7CIIgCMLHjUmNJRmGEQcK50dN03x6Mscy\nHE8XsPdlVrazWLkt3kmLxv5NQPFpkzm6CGprgfffB8rLdYjT5QK2b2e0dtOmkW1btwJvvgls3kwv\ncmTbhx8C+/YBU6eOfrxp04BFi4APPgDS0ymc3W7g3HMplnftGtnn+vXAypWMOm/ZAqSlafvGRRfF\nXmi4dStQXc0+FUlJwKpV7HMMCw4Phob3KJhTSwc3OHmTVPEsFx+mFPE3YE/jojp/P3Di54HGDcBA\nJ5A6mD4vLhGIcwK7ngZKlo+MWB9O9r5CUZ9SGDEWB7DjCUbQ1e95ONMuZLS9uw6wpzKaHg4Ci74y\nOdFzQRAEQTgambTIs2EYBoAHAOwyTfOOyRpHNPqaABgjhYbNDnREz6x25Nm/n/aFSHWjvAQ7dujP\nw9t27uTfvj6K5X37+F71GQ2LBfjKV4DLLuP3/X7g058GPvMZCnmrdVg5wMGxtbSwIMoNNzBCXV4O\n3HorcPXV/J5pcv+XX6bobx8Mge7bR4tJJOoYh8Er3b6botfTyevsrhlcDGoCvl7gtO/xxmlgMPPH\nyTcDZWdyv+FFW2wJFJ8DbRM+zNjnsIviPpJ4F9Mq+mM4ZJzZwBk/psXDkQ4Ungqc+eMD2z0EQRAE\n4ePEZEaeTwPwWQDbDcPYMrjtP03TfGkSx/Rv7Kn0PJvmUC0Y9E2iRWM0UlOjt+XnA9u2jd6Wm0vx\nuWXL0O05ObH7BBj1fe65QbOvH/i//2PO5owMXT1wtHHGx9NXfcYZQ9tME3jqKeCFF9inaQKPP06R\nnp1Nu8bw74fDBx7nOHDlADseHxSZg9fdsDKiHO8CdjwG1K3nTZW3G9j8IH8rSXkU0JEB5nAIrIQY\nuwL5xJ9DPgV0ZPq8kJ9if7ineTiJGcCcqw7v+ARBEAThWGYys22sM03TME1zvmmaJw6+jgrhDACu\nPCBnPtBdy+ihaQL9gwvGCpdM9ugimDEDKChgBb9wmK+mJtoZLr6YArqxUbft309Besop/J5hMHVc\nyqDCa2riQr5o7N8P/OMfPGZJCV85OfRVl5TQytHcrAVufT23R7OBALRlvPACvc8lJfRVp6fTyz1n\nDoV5ayv7DIWYX3r27Nhe6XHiSAf6WwBLAkVvQjIXzHndjELXvU1LR2oJX7YEYNOfgOJlAEzafUyT\nJcW767jdfoTF89TzWeDENxhlDvpYXGbq+RTQgiAIgiCMn0lfMHi0YhjAoi/Tr9rbRCGUlAec9l1m\nUgBAldTSQoE4PMexaVJE1tdT8I3W1tAwsi0Wpklxq4QyQAvDt78NzJ8PVFYyb/LUqcB3vkPRedtt\nwLx5HEd9PTBrFnD77RTUc+ZQ+KrUcbm5FKVVMcok7tzJccTF6W0JCTyPhgYet7yc3ufKSuCkk4Bv\nflNnxvD7gQ0bGPFW57B1q7ZidHfTDuJw8LutrcB3v8sFhnV1FO+nnQZ87Wv6kUBfHyPhKtvIIdC5\nD8hfzJskXzd9v5kzuGhu32usdBj5JMKeSsEMAEtvp3Wjp55WjakXAPM/fUjDGRcZ04BTvs6IeXcd\n4O1iNHn6xUd+LGPB38cqkL4DJF0RBEEQhKMBST4Vg7hEYMEXgHnXMvoc54wQTh0dzPqwdy83JicD\nX/oSBWlbG3DfffTrGgbtBV/6EoVrayv3q65mW1oacOONjCDHoqkJuPdeCmDDoEXiK19hFouBAfYb\nH6/LZvf3c7/0dODrX+d3AGa7AFgS224HlizRtoi4OBY8sUZZUQZEbzMMtvX18fyVT7mlRRdGefVV\n4L/+iwLZNCmI//AHHtftpjD3etmWlkYxb7Uywvz97/OcbDaOW/G73wE/+xmzcgC8GXj0UeDkk2PP\nZxQsNgrk0jMH07NZuc1dC9jiaeWJxDQHrT0Wiuyz/h/FoC1hcqO8eQuB3BMHx+IArHEH3udIY4aB\nnU8D+14ZnEMAU1YCs66MvqhREARBECYbiTyPAZudftd/C+dwGLjrLi5wU1X2rFYKuZYWpmurr9dt\nAHDnnRS4d9zB6KlqC4e5rasr+gACAVbwi6zq5/dzW0cH/3Z1MSPFlCkUoL/5jRbQAEVzYoThdc4c\nitaBAf6NfD87RqHHefN4rh6P3tbXR+Gen8+xBAIcR3k5hfQdd/Am45vfZGS4oIDfbWvTCwh37GD0\nXllIOjoo8MvLeQzDYOaOSOG8di3wox+xLT2dNyltbVyEOM4IdNGpTEVohiiALTbadZLygKkX0g4R\nWTBkoI1R6aR8PcyEpKPDHmFYaDs5GoUzAFSvZhYTVy6zmLjygIoXgKrXJ3tkgiAIghAdEc/joaaG\nFoL8fK2ok5Io2J57jpaIvDzdlpxMYfjccxTXubm6LSWFQvjDD6Mfr6KCYjI7W++Xlkax+/zzFM6q\n4p9q6+9nurpopKQAX/0qI761tXy53bRDJMeoZZ2ZyUh5Z6fer68PuOUWil2vVy/kMwyOub2dkXi/\nX3urVZGUzk5m2Cgr4xy53YxMJyTQ/1xfH30sf/wjQ5bqpsBi4dg7O5kXehxkzABmXc48ze7awYiz\nHVh8E/M8z7wU6G2MaHMAi78qqdzGw96XKZxV8RWLjTcpe1+e3HEJgiAIQizEtjEeBgZGV0s2G4Wi\nadKyUVVFQVhUxKhpR8fo+1mtFIyxjhcO00NcU8P3xcUUmJ2d0YuaqNRz0Sgtpeh/aXCd5sUXD82n\nHI1TTmF0urKSgnXGDArYF1+MriLbBvO1tbbqKoVKZLe10cJx4ok8H4uFIn3/fm03idbn8CqD6nNL\ny4HPYxQMA5h5CdPRdVXT+5wxQ0dvZ13ORYDuGtp6MqZHRHZbW7nwcfNmntsFF7ASoijrUfF2UzxH\nYrOz0uHwLDeCIAiCcLQgkefxUFzMf9kjU6iZJqOup59Oi8LmzXph3Z49LFayaBG3RS4uNE32E8vz\nXFIC7N6tI8lWKz/v2ME+gaE2BVXxL5YQDgaZn/mZZyigk5KYLu7Tnx65+HE0kpK4GHDBAh35nTaN\n44gU86qvs87izYMqzQ1Q4HZ3s8BKIMCbgfx8RuZVHyUl0cdw7rk8XmR6vECA12blygOfQwwSM4GC\nxYw2D7c9OLMG2+ZEtHV10Xv9zju8UervZwXH558/pHEcz+SeyMwmkfS3AjkniHAWBEEQjl5EPI+H\n5GTgqqtoKWhuZrS5upqR07Iy+nItFtoU/H4KQYeD2y+7jJaPyP0WLeJiwmh4PNxf5VX2+7ndbudY\nzj+f9omWFkZjq6uB5cu1X3g0XnuNkeOCAu2HLiigKF+1anzzMnUqI61VVRxHSwvP9eKLgZkztUXF\n6+XL7+cCv3nzOAdVVZwTlaXk8stpQYnGLbfwRqazk9Fst5t/L78cmD59fOcwXt5+m8cuLORNQHIy\nhf/zz8eOnn+MmXU5veHddSxK011Hn/bsKyZ7ZIIgCIIQHbFtjJfzzqNQXreOUcbFiykAd+6koEtP\nZ/Q5EKCQKyxkKrerr2bU9p//pKi6+GLg0ktH2g8iaWnhsWbNoqgMhyl0AwFaGz75SYrMp59mpPeq\nq4ALL9QFR+rq6Kk2TUaKS0sZDTeMocdV1QD37h3fnFgszCpy0kks3x0XByxdysWJzzwDnHkmx19R\nQYvLCScwa0h7O/3XJ5/M/ex2pqNTNxSmSaG/bRtvIk46iZ5yl4ui9Re/AF55hZ8//3ngC1/gfuGw\njtAnJvIa5Yyhwk0oxFR7H33Ea7V4sc59HQrxGu/cSYG8eDEtJnv2jPSKx8VxDGqhZzSCQY6xooLX\ncfHi2DcNxwlJecBZPwVq19Iik1oKlCxj1F8QBEEQjlYMM5pf9ihk0aJF5saNGyd7GLGpr6d4razU\nz57DYQqs+++naHzwQS1cAwFaDK69Nvqz6j17aAkoKRn6nZoa4KabGHl9/HEtfkMh4BOfYJT7lVeA\nJ57gcQG2XXYZBdt3vjOy0EhjI/CrX/E7E8k77wDf+x5tGlarLqKSl8cUfNEsJuEw8MgjwJtvajEK\nUKSfemr044VCwAMPAOvXMxNIKMS5+drXKL6jEQxyceMHH+j9LBbgG9+gmL/nHlpwVJvVyjLjO3Yw\nYl9YOHQM+/czC0tS0ujH8/mYneWjjxixDgbZ9223xS4sIwiCIAjCYcUwjE2maS4avl0izxNNfDzt\nBxYLo52GQYHU2spczW++SU+vyoMcDtNCccop0cXSlCn0E+/dy4izYdDakJ3Nz/fey7+qcInK7FFe\nztLZhYVD2/71L6Z4y8vTFQcBnQnkggsmfl5U+rn4eApJ06RPuKODUfpoVFZyzkpKdJTc6wUeeoiF\nYZzO0ff76CM+FSgr0zccAwPAX/4CzJ2r5384W7YA778/dL++Pt74XHMNC7yUl+u23l5WQrz9do6z\nrY03Sn4/nzScf3504QzwpmL79qF9dnVxnP/7v7GfSAiCIAiCcMSRf5kPhXCYXuM9e3SRjnXrKJay\nshhV9vloJ8jMZBQ4HKaAdLt1pgyrlWIvGiryecYZFM2NjbRffPe7tGSoPrq6dLYKAHjrrZHVAG02\nbeVQxUQaGvg65RRuU7mUg0GdNWR43uRAgG3V1SPburuBv/8dePJJnQ+6qoo2jZwcCszOTt4UzJwZ\nu6Lhtm0cf6SItNs5turq6Ptt3kyLh8/HcdbX68+1tdH327SJ1ysywq8WAL7+Oq0ZkW1JSfQ6h0KM\nrBcUsP/ubuDKK2mpUfT382agsVEviHz/fd489Pfz5qipiZk6Wlpo9zgUenp4vNEyj8Rqi4HXDXRU\nMve1IAiCIHwckcjzeGluZp7hhgaKKbudBT8cDgq9nBxGdE2TnxsbGYnu7ATeeEMXMLHZmGEiWiRU\n4XIB118PfPaz7FPZMGpqGP18/XUtVBMSGFV2OEbvyzAo4AMBivzly7k9M1NnEKmspEWhp4ef09KA\nm29mRLaigufe18exZGayraQEuPtu4Cc/0Ysab72VNgi7nZHfzs6hlRDj44eK++HY7UOzaShMk/vG\n2m/nTnqeVfYRlSEk1vEcjtFLrZsmo9zR2uLi6Gv+z//kudtsWvCbJq/5k0/qbCQzZ9LnnZAAvPee\n9pmbJsX0gcYZC9Pkk4fnntPjO/FEWl0cDj55eOEFfjccpldf/XajdRkGdv4D2PsqAINFZAqXACd+\nnsVkBEEQBOHjgkSex0M4TJ9qRwcFY3Exxe099zD/cXIyo8DK1+z1cr/PfY5R0J4eXUkPoMCLtaAs\nEqtVC2dAi1mPR/cZDLLP5cspiHp79ff7+ijYSktZ+Q+gZaC8nOd1552MRt55J8evKhoGg/y+arPZ\nuL2khNHc3/6WUdQf/pDnnJ7Ol99PYZaaykV4psn3aWkc1549sVPqqfR+ag4BbfWIlU3E4QC2buU4\nVSq+nh7aLob7vCNZupTno8Q/QMtNcTHwH//BeY5MUagWc+ZGJCyOjx8aKa+ooG87K0vPZ2UlPdmG\nQZHvcOhxtrZyrsa7aHDTJuAf/+ANlDreli30vm/YQPGcn6+v38aN/H4M6tax+l9SAasBphQD9e8C\nFc+Mb4iCIAiCcKwi4nk8VFdrz7EiMZEib/t24A9/oGjbv58RZ7ebntjUVAq+xEQ+1u/upmCdNo3f\nGw+1tdw/Lo7Hcbu5fdo0isyvf11bFerqGP295RbaGAYGtIAHOL6+PkYllRhXpKXpNp9vaGaJ9HQK\n4TvuYGQ1sgx4UhKF74MPMutIOKzP3eGgdSOWjSI/nxHTzk6Ov66O4vTWW4feRAxn7Vo9fq9X22ds\nNor8aEydCnzmMxTF9fUcW1oaFxrOmMGFnc3NHEdtLbOFfPUAJQbXrOGcqEi5YdCHvm0bfdJpabw5\n8fn4UnNdVxe9z1i8/jqviX/hNDoAACAASURBVJofdbz161nIJiNjZNvbb2vr0Sjse435rS3Wwd0s\nLEte9cbQcuWCIAiCcLwjto1YBALAq69yQZ/HwxRil11GMRYOM6K4bx+FT0GBFj1nnQWcfTbT0fn9\nLJxyzjkUmElJLO7R1cU+0tIoxg5UDbCzE/if/+FYQiFg2TLgBz/gWFJSmA5OeajT02kn8XgolEyT\n4sg0gRUraLOorOT5bdumRVpJCe0Ovb0j20pLdRTb52NUt66OEdbSUu7X3T26iDQMtmVlcZFfVxf3\nS0vjTYPXy7E/8wwtDPHxnK8LL2SUfOlS+qWrqtg2ZYoWf+3tTNG3YQPHd+65XKTndnOuMzI4DxYL\n25uatBUlGueeS/93TQ33KS9nxB9ghLmjg5Fcp5NFZSJvMkajt3ekxUQ9lejp4Tj7+/X3UlP5+UDj\nrK7mb2z3bl7Tiy9mir/eXt4Y7drF+UlM1Hmve3rY944dPA+nU9/UqEI1o+DvY/W/SCw2IBQAwiFd\nYlvQmCZQvx6oeJ5VEzNnArOvBNLGUMRTEARBOHqRyHMs/vpXZqtwOOhh/uAD4Oc/pyDbt49R5vh4\nRjQbGvi4vLSUeYafeor7lJVx8dqnPqWjtaEQxU52NkVZMEi7RzTCYeC664Bnn+Wx0tKA1asZBVV5\ni02T4jQ7W1sGysoo7l59ldtzcui9/dSnKAJ37uR5OBx87d3LbYsWcQFjZFtlJbctXsy/1dUUZQkJ\nvInYtYviTaWgUyiP8BVX6NRu2dk8f/W9vDzmal6/nm0uF60Ff/6zXljndLKYyowZWjj39/N6fPAB\nz83hoP3g4Ycpvr1eilSXi2P1+Xj8U0458LVPTqbQnzZNC+d9++g5r6hgtNbpZFaM73wndl+LFlHM\nR6aF7O3lMZYuZYTb79eR8fr6wTrhM6P32djIbBzV1bxxUyn2XnuN1/2tt3jM5GTO87vv8jvTpzMS\n3tPDtlCI824Y0TOXAMhfzOp/kQy0AVkzxfMcjapVwMb7GJlPLgDc1cDb/wv0NEz2yARBEIRDQcRz\nNNraKCpUxNVmo2Dq6mJGDZeLompggK9wmBHEbdtYkKSwkNFYtSCwq4si9pprtJ2juZnRzWXLKNKi\nsWYNo4sFBewzPp7vm5tpQbjkEgqu/fsZWa2pYfR0926Kq/x87hMfz3HV1wMvvaQjpuocTJPb2ttH\ntgHc1tpK0WWa3K4WKaakMKq9cCGjyG43z7m7m17hK66gB7umRmcMUUVjqqvZb1ER58tupwDcuDG2\nnWXDBh6rsJD7ORy8Xu+8Q1G6YAH3V2kClY0lVmq8WDz4IAV4Tg6Pl5jIuX3pJZ5LNE49laK1poZj\nqa/nvNxwA8frdHIePR491+Xlscukv/oqBa+6WUpK4jw8+yyFuctFQT4wwJuIhARes9HaHI6RNz3D\nmHYhkJgBuGsoorvrABjA3GvHMY8fA0IBYPczFM0JSbS5OLMBGLTACIIgCMcu8rA1Gm1tFCXD8+za\n7VrI5uczCuv3U/ympDAabRiM7LW2UpSkpbGf3bvpj42P5+N2j4fFTFSFQdOkNeH999nnSSfRjlFd\nPbIaIMBtlZXAf/83I9cffMBI4qJF/PzHP/J7o+UK3rOHNo38fEZSAUZ24+J4vNJSiqzGRh6noIDW\nkqoq2iYSEynWLRa29fZSyK5axYWTTz/N87zuOka/DYNR2+5u2jMSEriA8vzzGd232egzbmri+4IC\n9t3WNrTwSCS1tSNtBuqa9fUx7d5TT3FMqalMGxersMqB2LWLx1PWB5tNP02oqaGQ3byZv4H0dB4r\nL4+/mdtuY9uOHUPbnn2Wv4EdO2iDcTqBJUt4Y+Z2D12IGEl19ciKhgkJ2t9+xhmc6/Z2XseiIt48\n1NfTVtTZyc+qrb2d5zS8z0EcacAZPwYaPwA69wJJ+UDRUm4/EL5e7tdVDaQUAoWnAvYDOF0OF54u\noOFdoGc/kD4FKDgZiI8ecB83vh4g6B0UzBHYk4GuGJkZBUEQhKMfEc/RyMpiJC4cHio+vV4+Tl+3\njhFUi4VCp7KSgvL665nVoL5e7+d2U2hNmUIh9+ijFKlxcUwn5nbT6vHaa9xX5TV+8016p0tLdWQw\nciymyQVuhsHIpvK1KlQ2iuH7ART7zzzD6LCyQSjRd+ml9DRnZemy1KZJQTplCr+Xna0XTKq2rCy9\nmO/WW4ceLxwGvvxlLuRTqep+9CPO07JltIv09+sqgpWVFJfq+KNRXMyo/PDjKFuM3U7h/ulPR+/j\nYJg+neO3WvlSpbcTEngTcscdPA+nkzc/L77I/Nzz5/M7S5bwFUl+Pi0qgQCFcjBIkT19OgV/NMrK\n6A93ufQ2n4/HmT6d16+khC+Av1u7nW0ffcTfVGkp2zweRq5j2DYAisyys/gaKwPtwNs/BzydQJyD\nHuA9LwGnf5/luY8kPQ0cS9BD/3b9emDvyxzLWG4CDoaEZB4j6B3qFff2AEUxHFqCIAjC0Y/YNqKR\nlcXFV9XVFBehEKOwaWlcANjbS6GTmMiX1cqIZGEhRYzKxRwXx/d+P8XJE09QMBUUUCyVlnIx34YN\njMAWFPCVl8e21asZGZwxQy+u8/v5PjeXlo1orFxJkdXUxH1U1buiIi7G6+7m99Q5qIV9J5xA0VVb\nS1Hn9/P99OmsPlhUxCipaqup4Q3FlCnRx7JqFYVnQQFtD7m5/PvggzxmT4+uyqgyl3R3x67Ot3ix\nXhwZDHJuampo2VBe8Ilk4UIeJxTSeZy9XorcmhoK57IyHruoiL+VBx6Ibb9wOnnucXE8b4eDcxoI\nxM5jvXIl56i1lSK+r483IpdcQptMMMiofTjM32pjIxe7Xnwx+25v123797NNebsnkIrnWFgltYRR\n2NQSIOhjzugjzfbHmK86pViPZaCdYn6iscYBMy4Behq52NIMDxaWMYEpKyf+eIIgCMKRQ8RzLD73\nOXpyPR4K0MWLge9/n4+7p01jmWe/n8KlsJB2iddf11FZv19H9fLzGSVV1QDb2yl8lBBT2TAiC2NE\nRrUfeYTCqK+P0eIzzgAee0xHHv1+2gp27tQ5kW02RrlXrOCxWlq4kO7RRxk1nz2bYq+zk6+yMm5r\naKDNYNYs2i+efZbn9o1vMLJ5++3AmWfyHNxuCvFbbomdrm3t2pE2GCUOV62iP7moiOfn93McM2ZQ\nlAI6Q0RlpRajLhevx8kn83z6+4GrrgI+//mxXd/eXkbR9+wZWSWxp4dte/fqttZW4LzzuGC0u5si\ndOFCjn31atp2fD7Oc2cnhXFvL8cWjaoq3owlJ3M/r5fnk5pK8RuNwkIWZCkr4/WyWIAbb6SoLi4G\n/uu/+Lehgb+Dr3yF1760lHNWUMC2uDhaic44Y2xzdpDs3wi4cigg+1poZ3BmA82bKSiPFCE/0LZr\npI3CmQ3s33B4jjllJXDSlwBYGPVOLQGW/SdT/AmCIAjHLmLbiEVcHCN1F188dLtKyTZz5tCMCHV1\nFD0+H0WlYVD89vfzfUoKhZQSuMrHnJfHDBCR2RgUpsloZHq6LmoynD17gLvu0unu7HbmJZ43jyLO\natVVBG02brPb+f39+7Vgb2zUixK/8Q1mG1Fj+sY3mG3izjsp9K67jq+xEiudW0oKxerChXwplKf5\n3XeBhx7SxUnS02kLKSqiPePGG/k6GFav5k2EEsY5OewzN5c3QE88oSsT5uWxTUWJExO1JSYYpNhP\nSeHTA1Xu2jQ5TwUFsatHOp28Mevq4nUOh3nDUFh44KqTZWW8kRmN8nKWbx+NqVMpoI8A1gSgcSMw\n0ArAAGACiVlAWvng5yOEYWU0OBzkX0XID8S7ou93SMc0gJLlfAmCIAjHDxJ5Hg/q0bwSSoDOkvDp\nT1Ocqpy5CQn8V7Sri3aCqip+NzWVgstiofg99VQ+5u/o0H329VHYLlgQfSwDAxS0cXHa4+pysUx2\nYyMrISYk6EpzDgfb0tJ0VDU1la9QiGOpqWG6N1XGW0WI77qL+Y3Hw2WX6YV8io4OCswvfIFtqmQ5\nwKhrZiaF6v33UzCr8/P7gd/9LrYdIhZVVTy/7GzdZ08P56WyEvj739mmKvB1dXHxZUEB2+12Xrvk\nZEbf29oYpd+zR7epzCRdXTyPaKgFm4mJer+mJv0bOcZJzAC69gDxSVwkGD+4YC4hJfaDionGYgXK\nz2EEWN0PhkO0UpSfe+TGIQiCIBz7iHgeD1YrI5Hp6RSaNTUUhTfdRAGVkUHBqirbAfzu22/TN5yc\nPLQa4MyZFLrf+hbFraqk5/WOTK0WCg0Vjbt20Rqi8vmGw0MXrHm9tI0of7LLxTGtWUNbRHw8x9Hd\nzTHPnAn8+tfsO7KCn/Ju/+QnY5sj5Q1WTJvGvMQ+H8+1sZHj/NOfKFBvuYWCsaqKr+Rk4JvfpFg3\nDIpSRUYGRWlVRNqCQGCk9SIaqhBLpKc4O5ui9YUXdFsoxHPOzqafePt22kn8fl0lMTeX7Tt3jmzL\nz+dYI+0XgcDQlHANDcyo4vHo30RxMeemq4vfMc2R+ylU22hPLY4CBtqBzNmAv5feZ18PkDkD8HYd\n+SHPuBQoOpVp9rrrgd5GYPpFQMmyIzsOQRAE4dhGbBvjJTVVp5Hz+eh/LiigkI6P56N+tSgrLY0C\nsK+PbVlZFEmhEMWX08k+iopY9KOujm0lJdpS0dfHtGtvv80+Fy+mHzsQ4GvzZgo80+Q4kpIoyLq6\n6ClWAi4zkynwlKheuVKL+NRUHjsyAjwcFWGPRkcH8OSTzNFssdAucvnlFO3Ll9NHvmoVz+vyy3Vx\nGFXO/MMP+X7lSs6V1zt6qj2AQrWpiRaLbdv4/bPPpjc8UmwPx+OJvjiuv5/t69dzzlSWFIeD16C4\nmNkz1CK/pCTOe38/r9dobX4/hf7jjzPan5jIhZfnn89jpadTbLe1cdyqeE4gwJuxxx/n78zpBC66\niHNjtTL14RNP8DeXnMyFgitWRJ+vSSAUoK94oI3COT6Jn8NBACaOqHXDlgAs+gow63KmrHPlAPZj\nP7gvCIIgHGGOnn9ljyVMk1aCV1+lhWPOHIqcn/8cOPFELhJTpY+Tkyk429splnbvpoBKS6NIamlh\nWjHlobVa2efUqVo4h8O0X6xZQ7FdUMBqhr/6Fb2xquKfy0XB1tDAxXULF1KotrZqC0l7O6sMLlhA\nkRUOU7ylp1OwGwYLuQBDI7nqfSyfs9cL/PKXFPIqm8ibb9LuMTDAtooK+rtPOIGLCP/wB87Bddcx\nil5SQkvMqlW0c8ydOzLq6vVS1GZmsjLh7t288cjIYMGSv/wl9vU76SRdFEbR30+BvHgx82x3dtJC\nYbcz4lxfT2Ha08NjZ2Tw2vb18e/ZZ49s6+3V1otf/IJCv7iY1+jJJ3kzVF7Ooi4eD38PTidvILq7\nue2Xv6SoVtHoxx5jesPaWl7/zk7OmcPBRaUvvnjAn++RJCkPqHubnmNXLv3Gdeto5zAm6f8+zmxG\nv0U4C4IgCONBIs/joamJAqe0VBs38/IoaDZsYKRy924KK8Og8MvJoVhNT+eiwcg2FXmMxr59FNzF\nxfp4hYWMOL77LiPZra0Ua4ZBUZiZCTz/PPuPj9fiMy6OQvj99xn5feopHYUNhYArr2QE869/ZbQ0\nUkDPmxc7Z/K2bRyHyh8MUNjt2UNR196u2ywWtu3aBdx7L89fFUOJj6flYedORs7POosL/FQOaAD4\n0pd409DTo3MZx8ez/02beI3yoiQSnjePHnNl31A3DTffzDnNyKC47u3lXCYkUPBOm8asI5s2cZsq\nN/6Nb9ACs2kTbxzsdgr+uDhaT9TTAuV9tts55lWrKOTT0vjkQdluVNnzl1/mPGVkcD+Hg7+Bl1/W\nCz2Vpcfh4A3Eiy8yI0isNHdHEH8/RWrQw8V5Zoh+54CXU3skfc+CIAiCMBGIeB4PKoPF8H/54+Mp\ndGfNosj58EOKqBkztNjNy6OQ3rWLbdOnU5i1tFBN7NxJy0AgwJRlqtw1wAhkXR0FVmEhj19bS6GZ\nnc0+TZPHT0ig4LZaGbFUVozERArDffvosZ47l4IPYDRaiduPPqKH+5lndDT6rrvYFgoxWv7ee+x/\n6VL209rK7ypPs9VKQWeajIyHw4xEV1YyQjt/PsddWanzZPf2UjAmJ7OvujpGpZcsoTh3OCg48/OB\nv/2NAlKVJleLJi0WzllGBm9mNm3iHJ9+OgWw1Ur7iMvFzBppacCnPsXzf+cdjqulhWNOTOS5qdLW\nN9/Mudm1i2NctEgXcrnlFrbt3s22xYspmJ97joK5upr9Ohxa8FdX89x8Pt5cqJLf7e28fsPzXKub\nn6qqkW3x8bSI9PZqwT2BeLsZRe7YAyQXAaXLdeo3rxuoXQd07mEe5ZLlgDOL3uayc2jb8HazVLUr\nD+hrYqo6Y+JTSwuCIAjCYUXE83jIzh69+qDyPq9ZQ5Gksmk0N9NXfPHFFGvt7RRBNhttDA4Hq+89\n8wyrzTmd3O+99yhMzzuPIquzkwLJMGjNcLkYPX7+eUZo4+O5386dFFbnnUcbQ1+fHmd/P8XX3Lns\np6yMr0hMk/YAv5++alWw5IknKKIfegh46y29SHH9ep6birj391O8mybFfUYG23/xi6Fjef113kzc\ndBOrK7rdOgre1cX3s2bx+8PTAgIU5ps3c5wqElxTQ7tIejqtLtu3c5yBAK/L9dez+M1dd3GelK3m\nnntoBykqYuGWYJB9+v2M0hcVUSRbrRTX8+eP/F3YbLSjnHDCyHE+/riOYgeDFMbTpjG/8po1/I6K\nlPt8/H3Mm8eodaRI9nrZx5w5FPqRFQY9HorvKCW2D4WBdmDtzyiSE5KA1h1A1Srg9O+x8uDan3FR\nYLwLaN0OVL3OtrRyLtBLKQZUskKvm58tIpwFQRCEYxDxPI+H7GyKnupqikGfjyIxN5fR4oEBbZdQ\nYndggEJHVSuMj9dp7Dwevp57jhHrnBwKtfJyCuimJrYD3Ceyz6QkvYhveNvpp2sBaJq60mF8PAtm\nRKOmhuK4tJTnmpPDSOmrr9Im8vbbFNxZWbrtpZcY8fR4eHw1FtPkWJSNxWbTbVYrbzLS07mP36+F\ntd9PIagitKORkKCPp+YzHOb1qKigcC4rY/Q3L48R3cceo+hU1QAzM7k9P595n9X1sFiGZt1Q8zYe\nVOYVq1Wfu8qacu65jEo3NupMHQ0NTO13wQX87v79bHO7+b3LL2dhGptNV490u/n+yiuHFtqZICpf\npDhOLQEc6UBKEf3L2x8DKp6nPSOleLBt0F300RPAzMvY1t/GxYMDHYxGz75qwocoCIIgCEcE649/\n/OPJHsOYuf/++39848EWwzhczJ2ryzJ7PMwk8fnPU8BUVlJ0ut0USGVlFIHBIMVkRgYFkcdDgVxa\nSjHV1kYx3NZGC0NCAoWn3899k5K0YJ8yhUIbYFtmJo8XDnOxYW6uFmuBACO5pslxnHYaI7qlpYwS\nf/QRo+PJyRRrmzczRVxkijyLhcIuGKQ9Iy1t9DbTpOjdv5+fZ82iwN66lfvZ7VrMu1y6jHl5Ofvp\n6uLfuXP5mj2b5zIab72lFw82NbGvuXMp6lXWDJuN86luXlQaOSXU29r4PdWm0v75fLSDBIO0zqSn\n09aRlkZh/uKLvGEqLj6wWH3xRfYfCPBmwWpln04n/dxnnMH5UhlDvvAFVnB0uXjM+nouAHU4gBtu\n4G8tKYlt777LhZfBIL3Xy5YdFiPxloeBhGTAEvGsyuYA3FUUxs7MoZHkuESgcy9wwnVA7nwWSelt\nouhecAOQPYffM02guxboqKQn2p4qPmhBEATh6OAnP/lJ049//OP7h28X28Z4sdmYfWHFiqHb29v5\nr//UqXwp6uoomnt6KIYMg33U1VEcpqZSvO3YoSvpWSxsW7aM0cjt2/UCvvfeo196xQqKsSlT6K1W\n1NToaodOp26zWvXj/Q8/ZJ5ldbz4eJZqdjpHVzCmyT6jJehNT6e1pKlJ54iuqqI/OzOTAi8c1n17\nPPycnc15ueCCof3V1nKc0VAFRVpbdZRbLazMyKCobG3V41XFYjIzgXXrKJxVm92u9/vXv3hdFG+8\nQW+z3Q585ztsV/ORlgb8+c/MshJrnDU1PF58POehooLHS0igZWXHDgpir5die/p0juXNN+mvVk8Y\nXniBbYmJwLXX8hoaBiP7W7ZwbCedFH0s4yQhhanmbBEZAMMBfranAkEvYI0IzIf8QJyTgjp9KnDq\nt0f2GfQCG+4FWrbi39UHs+cCi28C4hwTfgqCIAiCMCGIbWOiKS+nBUBFQgGdwuy88ygIfT4KqtRU\nbq+qYhSxulqXek5NpdCtqqJY2rqV/SUlMTJqs9F6MHMmBVykEOzqogA+80wuDAyHdRVBtXgvOZlZ\nLlJTdZW95GRW0isuZtRTLVQ0Td4UpKYCn/jEyAIebW0UzkuW8HgWi66g6PfzeJ/9rC6cYrPxO6q4\nx003MXrb06P7bG6m1WLKlOhznZfH+YmL09X5BgZ04ZGqKopVNZa+Pl6X2bNHtvX08JiJiTwHh4Pz\noQTttm28YfnnPxlJLyjgTYHHw4WCoxUwUeTk6D7V8To6GB2vqqLlpahIVzTs6AAeeICLHV99VVeH\nLCnhXD/0EPCjH1E4p6Vx7jMyePN1/fWH8uuNytTz6XsODd5nhUOs1jdlJTDtQm3LUG29g22x0tHt\neQlo3gKklNAOklJCL3Xl84flFARBEARhQhDxPBaUsIolkBQWC6sPFhQwRVtFBcXgrbdS3EyfTrHj\ndlOc2mwUeiqSnJpKgdTaSlE4Zw6jjcnJFK1eLwWbEozr1wO33UYRtWePLh992220CMyapYVwVxcF\n3KxZtDwoX/HAAPt0Oiloa2u5v8NBcVddzWPddhtF2re/TeFZWcljpqdzW2MjhWl8vLZHpKYy6l1X\nx+itxcLjeb0c5/LlvJn41rc4f/v28Zj5+ZwztYDQNCk2vV491zU1XFSnyp+73Yxil5ezSMu8eVr4\nd3ZSbBcXM/vG/PlD2woKKGBffZWRadPknHi9nFubjRFmu31o5cX0dAryWGXL6+oYmQ4EeCy3m1ae\n1FTglVc4t5FFW3Jz+bt55RVdYMfn441HXh5tNk89xah15ILVlBReu8rKA/9OD5LCJcCcq4D+Vl2d\nr+wcYPrFQPFpwOzLgf6mEPqretFXH0T5Slbvi0X1m8wDrR5EGAaQlA9Urx5b9cFwCPD18q8gCIIg\nHCnEthGL9nbgu9/lAjnTpPD66U/pGY5FKET7wHvvUXBPn07hpxbJuVy6+mBiok4x5vdTjLa3s5+k\nJL78fr0ozuPhWFS5bLXf7t2MRJomI6wDAzrK63TqKLLLxW2BAG8KnniCQh1ghHTmTO7ndFKIVlfz\n2Dk52kLh8fB427ezTVU5DIUo4ObO1SnnXC6KR7+f86dStlksFNWqOEt6OkVrQ4O2qzgGn903NDAt\nnUppt3Qp8MlP6owYDgePp+bWZuPxAgGem9utbTLZ2dpD3tJCga8WB2ZlUaTabLw2gQDblG/c5xtZ\nvc9i0XMQjUCAY1QedlV90GodukgyEiWYOzt5Xfv7+f3ycvYVDEY3B0feYEwQhgHM+MRg2rl2WjXs\nKbp9ZvZ6TEv8J4Kt3bCmOGDLvRSwrkCsEoLh4MhUdYZlsPpgDEyTwnv3M0Cgn1UL51wJFJ0ufmlB\nEATh8COR52iEw1yc9dZbFFx5eRRbX/4yxV+s/T7/eWZ0yM+nYNy/H/jiFyk+d+9mdDA9nWKtq4uW\njEWLWDSjo4MC026nYHrrLYr17m6KQIeD/fT3c9/Fi5kHeft22giKiigyr7+e4965k5HRzEy+Wlro\nr120SPt+lUhvbWUkOycH+PWvGf2cOZMid9s24I47KOw/9zntLS4qYttnPkOPt0rhl5LCPn0+ir7T\nTuN5ut3cr6CA3u/duzkPv/wlP8+axRRu773H6oPd3WxraKBtIT+f477nHkZvN2+mcM7KYpRWFZSZ\nNYs3PQMD2n5RXc1+Z8ygH9rj4ThdLu63YQOtNc3NFLyJibwOLS08j2uv1ZlUFN3d7GPBgui/ifJy\nprsLBjnO5GRer44OetbVYk6FioTPm8cFgYEAj+FwcA4HBlii2+sdOpa+PvY/Z864f/YHIt5Ji0Wk\ncMaWLcCf/gSrw4aE2cWwZSTxZmfNmph9FS1lvudIepuAolNji+C6t7mAMS6RmT1sCcDGPwNNm8Z7\nVoIgCIIwdkQ8R2PLFj4ez8/XHt3MTEYKH3kk+n7vvsvo8fD9BgZYtS83l9t7eii8VPXBF1/ke1VF\nLxzm9wyDbdOmcVtvL1+BAEXoli26mp7FoqO2XV0sAZ2byz6UjQLg2Nau5bHi4igMVW5hmw14+mkK\n6fx83WdhIW0Z991HAawqJlosPHZzM4X65ZdT6NbW8tXaypsJn49jCYV47soHnpPDG4TeXr43DF1c\npbKSOaz7+ngjoNqKi3ksldUkGOS59fQwgpyZSeGmbA0qOm+387svvqjbfD62ORwUowMDHKfHo+da\n5Zm+8EJWJlRFYBobuf/Pfx47jZ2yk/h8uhCMy8VjzpvHG5maGkboa2sppL/4Rb2f18vz6+3lTUBc\nHPDDH3KOurootlXhnrvvHmoBORI89xxvBp1Ofrbb+Zt49tmY/osZl9Cm4a6hFcRdA7hygFmXRz+U\naQIVz7LUt1pUGJfIct8Vz03YGQmCIAhCVMS2EQ1lHxj+SF1lyIhGY6P29arUcUlJ3LZvny7RvGUL\nheS0aRSDVVUUPXFxjCqbJsWVxcK2WbMoZrdvZ5+zZtF/rMSWEuOmySilaXKcWVl8/9FH/Dt7NgVZ\nXR1FjterbSKZmdymqhjW1/O9YXCM4XD0qLtpUsR/+tOMjj73HAXltdcCp5xCEVxeTu9vayvPNSeH\n0de6uqE+YoDHNAyOYXgqOMPgvNTWch7sdkbQbTaKtvZ2zll6Oseliq+oFHZVVfQbq+i92i8U4vmd\ndRavlVrkt2gRx+DxR/fWzwAAIABJREFUMOJ9993MwJGRwcWOZ50V+7fU0sLCKWo+nU56roNBveCw\nooLHU1Fsl4vztGABhXVDA39H8+frG4FNm4C//IVPC4qLmSlleMGbg6Wjg6XQKyr4e1uxgiL9QOeX\nmjp0m8PB8QcCnP833+T5FRczx3h+PuwpwBn/DTRvYwTalQfkzGMkOSomc0WnDEv/He8E+lrGdcaC\nIAiCcFCIeI6GWmwWDA4Vdn5/7FRg8+ZRyKqKf4Cu6rd4McVOUxPFmGFQDFdVccHdv/5F0a0Ee18f\nv3PKKRRI3d16AVldHQXjV77CCHNvrxaZjY0UugsWAL/5DcVkwqAi2biRovK73+UCOOXrBRg9jouj\n0HvgAY7F4dDZL5KTac9YvXpodUVlHZg5k1k1tmzRXu077mCqtS99iXOZnEyBqPYLhymod+0aOo/h\nMI97wgm0dkQSCrFt4UJaNPLydN5p1bZ48dDoejhM+4zNxuv33ns6x3QgQIHqcnG/O+9km4qUb9nC\nyHtSEuezvp5j9nqBhx/m9TjzzOi/idJS4O9/p4BPTOTx3nmHNpfMTM7jrFl8RVJcDPzjHxx/YiKP\nt24db4DS0rj9llv4mghaW4H/9/943dXiw3XruFB0+NgimTGDTwIi83G73bTZtLYCP/uZziJTU0M7\nzfe/D5SVwRoPFCwa+xANC6sWDrSzIIvC0wlkzoi+nyAIgiBMFGLbiEZZGUtKNzZStPb3M/qXmwt8\n6lPR98vJoUhQC+hMk+8jo6I2m65epyLNwSDF1fDH3IYxtMCK1cqXWqRWWMhIps+nxaiKTCYlcexK\nQMbF8Zg9PRRGoZCO4qqFb6EQRXtwcNWWxaLHFQgwEjl9Ouelr4+ivb6eotPtZtS5sFCnUMvPZwaL\nUIj71dRwv+5uRnmXLwfOPpsp6VQBGNV21lmMUpaW8nN/P9tqajiOs89mVLSmhm1uN9+vXMnxKGGs\n5sXnY7RYReZVdNswdAVGZe1QFhGLRe+/cSNvWkpL2UdODq/p44/HXqRnsei5Vn2q38ZoiwUVNtvQ\n/axWnSs71n7j5eWXKZyLiniTk5/PG4rHHoud/uLSS/XNicfDSHRPD0u7P/ss21SfBQX8HT755LiH\nOftqwN/HSHPAQ590yM9qhoIgCIJwuJEKg7E45xwKmB07KCrOPRe46y4+/gco2LZupWBLSKDQqKyk\nwMrM1AvBZsxgpLKjg0IzI4MCF6DATEigCFXb1KI0p5NiPS6O38vL4/cMg3YP5RFWBUIaGijiyssp\nHjs7OZakJArLQIDjstnY1tZGsagyRTidFGVxcRROaWmMOAeDjHaqbBxf/SqFqDrv665jdPHJJ2kP\niYtj33197N/j4X433MA5WbuW4uqaa/iKi+N4fT4uPgyHmU3j0kvZdvLJPM7+/TyXq66i/1i1xcUx\nmp+czP3OO4/RTSU+VUrAk0+mgN+7Vz9RUF7vggKONS6O86xKh1utjOAnJXHuVQVFhc3GczrpJArq\nhgaeQ0eHTnGnUg0mJHBOXC7+HhIS+FQhOXn039+zz/K6+/3sLyGB5xAfzwWYymM8Giqf944dvOFI\nTx+a9q+qitcqsu2RR9hnfT19+z09/P01NHBOrVbO3c6dnIv0dP5elNWkv5/jnDKFnu0ZM4AHH+R/\nL5FiX+XS/sQnxpUew5lJe4evG/C6gezZwMIvAqmlB943HATadgLtFRTcjjTJ0CEIgiCMjlQYHA/V\n1bQMqOwF/f3ABx8Al1xCkfy731GsqijmFVfw8bbVSjG4eLHuq7aWghTQBUsUDQ0UbKtXU2gq+vrY\nf14exWFJyVBPa00N/cvvv08xAnAsO3ZQLN94IwWQ8lCrcTidFDvhMMWlsnSoaKgqPtLcrJVFZSUF\nZlISx/7f/81XJHl5FKoNDXpbfT3FYUYGbzweeECP5Qc/4N8rrqCgfvNNzl0gADzzDKOVc+ZwvJdc\nwtdwXC7gssv4iiQ9ndHxQIDjBnR58Px8XtfICpDhMOe4uJgR2K4uPZYdOxhtzsujgI9ERawTE2nN\neOMNbjcMnRs7O5vXZ948vtTxGho4/mikp7O/7m6OxeulzaesLHblxUAAuP9+Zg9R5OZyLMnJrCr5\n4Ye6LT+fbU4n8OijugAOQLvQGWfwHO+8U6cnBPiE4dvf5u+hsJC/t9HOQWU8UXi9nJtDUK1p5cDJ\nNx/cPl438O4dXJwI4N8VDU++eWjlREEQBEGIhdg2ohEIMFVaQgKFU2kpRdi//kV/7t130w9cUqLb\n/vlPiozSUgo3Jay6utjPDTdQxLS0aCuAajv33KHCWREMMvKYk6OrFqriHklJPO6+fTqPsfJS19dT\nYPX08DjKJgIwanjNNbp/ZQlQFf8++Um9UFBV7jNNCu+8vOhzNm2ajoxHeo1Vlo8HHmAUsrBQ201+\n+ENGap94giJOzbXLxWqH481ZrBZFRlYR9HgooL/0JY5RVTRUwnnGDEaQGxp4TdR+KqJ64YU644na\nr66O+zQ2ssx2cTHHr6w2f/oTxWcgwH4A3qTU1bEio/J/j0ZGhr6OqakUoJ2dOo1eNNato6db/TZL\nS7nfI48ws8nGjUPb2too/Nva+NtMTNTp/ZTFZ/VqPmVR1ShLSngj8X//F/s6XHQR51w9VQkEuN9F\nFx3xkO9H/wf0NDLVnqpo2LINqHr9iA5DEARBOMYR8RyNmhqKpEhxo8Tpyy9TCCUnUzTt3avF69at\nwNe/zgj03r18/J2YCNx+O4Xjww/TVlFXpzMv3Hsvt0fj6acZ4Ssr4yPzHTs4rttvpx/VYuGxlbBW\nKfL++leKSJVVw+ulKMzOZkq900/XtgqPhzcDy5ax/9mzKZ7a2vhKS+M5VVVFH+eGDTxHVaREVTBU\n562KuwQCFJYuF9+rxXSRWTVcLo53715+Doc5l5FRbYVpUtwqUQvwqcGJJ7JPlcZOCduUFOaxtlh4\nDRob+d377+d1P/FEXs+WFt6klJXp6PWtt+pMJg0NtF2ovN4qq4oiI4N9OxzAzTfzfCoreYzTT+fi\nyljU1jLTRyDAsXR10f6SmMgnC9FYu5b2nEhxmpvLm5TXX9cZWPr72XdeHvNlb9zI8wyHOVa/nzc0\nLS3MQa5sQor8fD71iFUgZulSZmBRlqW2NqYzXLEi9rkPEvQNlv72j+nrUQkFgIb3mRpPYRiAMweo\nWXNofQuCIAgfL8S2EY1oC6TU4rL2dkaaBwa43Wql6DrvPL3AS/WjFokB2lOs+ldR3wONxe2mKNq9\nm587O/VCLYCiWPWpFv6Zpl4opxYAer06apmWxowV9fXcRy30M01+r66Ogk1Vu0tKOvC8xcWxDxVl\nTUnRmTOCQQpCFU12OrXgjzbfpsmczT/4AUUcwHRtd95JMbxvH321yk6xaBFFaTjMccyezWtkteo0\nfACjzGefTTEbH8/3yck8nloEOTCgr6WyHcyfT+Hd3k5RHGlHiBZJjVzoqc5T5fA+EG43x6yqG8bH\n8zrEWsCnbESRqM+mSUFfVUXRaxi8mXO5ButjJ1EkqycShqGfeIwnUmwYwAUXcH67unSxlwNghoG9\nrzB3c8gPWOOBmZcCU847hID1KFOm/nMWBEEQhLEikedolJVRUKhH+wAFqd/PqNmqVVqUWa1s27iR\nEdy776Y3dMoULlDr7gZ+9SsKruuvp+1DPfp2u5lu7tpro49lxQpW9auu1lUE29poP7j6aiqAYFBn\nzQiFuN9119G37PdTrKnsEy0tzHKxcycFTX4+o49dXdy2YAEjqT09+vG9281tsXL+Ll/OPnw+CmOn\nUxdEufpqtqnod0KCbrvmGo45MoLZ16ezkdx0EwVtXh5fO3YAX/gC5+BXv+J3VbXDDz+k3WPRIl2B\nz+mkcO7p4TW125lyzu/nDc/MmYyg3n8/z/edd3SpcZeLgn/TJs49oHNURwrnJUs4xsiKf52dHK/P\nB/z+99xvxgxGv1evpr84FnY7nxBYLLRtuFyMvldW6tR8o7FsGecmUhU2NdE/PmUKffs2G8/P6WRE\n2mKhlUL5nVUp+ZYWztGKFXw/vE+VA/tAJCQMLbl+AGrXAtsfB+xprCJoTwO2PQrUrRvT7iOwxgEF\npzAzh8I0gb5moGT5+PoUBEEQPp6IeI6GEm0eDx+zV1fzMf0nPkFBo9KZKVSU7r77GNUrKNDp3zIy\nKOQeeohRv8hqgKrtsceij2XnTvpGI6v6ZWZSNNbVUXgrT21/P8XaRRdRAKoIZyik057ZbEwfp4Sw\nKv0NcNsbb+jME6oCX3w8t73zTux5mzqV3+/t1X7rOXO4rbx8aJtpAnPnUpxffTXnpqaGr54ezv+/\n/sV90tL0uefkUND+9a88b5X7WlVCrKxkdP3iixlBrq5mnx4P7RMbNnAu1KJNi4Xie/t22hpUFguP\nR1tP/P6R+aYjWbCA0dW6On0OhsEbozVrOJcqcq+qJK5fP/TmbDjvvquj82osLhctEB0d0fdbtoyL\nVWtr9bmnpvJmqrOTN0uqQIzKmhEKcW5mz+Z1qK/n7z0tDfjFL5j+b/ZsfW5qsaryzk8wlS+wiqAq\nmGJLAJzZ3D5e5lwNuLJZybCrBuiuBbLmAFNWTsSIBUEQhI8LYtuIxbRpfEz/8MOMMp91FoXJb3+r\nU8SpRXbKc9zSwv02baLoDQYpGouLKUjUY/P2dl0N0Gaj7cBq1RYHhYr+ARS4brfeD2D07+GHGYm9\n914e74YbgPPPB771Lb1QUNlLEhMpiJubKZo8Hi0KZ82iWGpqolC227VIUyK/rY37v/UWxZ/VygVx\np51GMXbCCfQB19RQlE6dSnHe3EyLyKmnUtBZrZwnVXZaPdZ/7TVGJ6+8kqL7vvvYT0cHhaaKwgI6\nV/Xq1ewzLo5iPD2dfV5wAW8w3nyTwvWTn+Qx16xhP7t3c97j4/mkwTAoGDMytOfaYqGAbWnhS2Ve\nGY7FwqcDZ57JcSUmciyq0p7FwtRwzc3cNmUK9+vt5Zz+/vf8zWRm8lpecgn3y86m0FVFcHJzOQ9t\nbdz/1VfZb3Y2r/nMmTyfW26hX7yxkb+VOXO4vauLv+k9e3ThmxNP5O8gPp43K6tW6QqD//Ef2uZz\n++28MWlu1paYsUSdDxJTVREc9pAjLpGVCMeLIw048ydA+y4WVXHlAhnTWXhFEARBEMaKiOdYfO97\n9DUnJfGx80svsdrcd77Dx/7Kh2qx6GIcixfTAqAEqGFwn4oK7vPwwzq3MEBBZhgUvNu2jRyDqkz4\nxhsUTSpjRnMz2xYs4Ofly/mKZMkSWhhCIX08j4fjXLKEpaa7uzlOgIvGqqqAn/yEWRR6enQaOyXg\nZ8+mLWXbNgo902TVxIoKCuhQiAvSsrP5/XCYgv+kk2i3KCzUbaEQxVxuLisRVlRw31AI+NvfeMyF\nCxmVV4VlgkEKXKuVIv3b39ZFYZSoLyykAP7lLxkJzsnhd/7yF4rw8nJmUjEMXWDmvfc4jhUraN9Q\npcoB7muxUHTGwjB0BotIysuZ6cJm04v91q6lkO/rY9Gd3l7eFFRV8aanro7i+5FHOI6EBF0+PD2d\nv8mf/pTCOj2dYnjzZuBrX+O8qFzg06YNHUtREW+yVBEdv583H6econ3PF1zA13AsForzmTNjz8Mh\nYhhA1mxGiJ1ZevtAO7cfCtY4IOcAl1EQBEEQYiExl2jU1jLXsCoW4nJRlDU2as+pypMcCvG9zcYo\nbFcXxaryQythp1LKATq6rBZiqQV9o+FwMHro9+tMFcpOUFISfT9V3CMY5H5qX5UBY2BAe1utVh2h\nDgYpKiP3CwQYpYzMNaxKbZeV0c7hdDLyXFVFgdjZSbF3zjmcl7lz+dntpohV1QBbWjinZWU6j3RZ\nGW8Y0tN1IZdgUI8pM1P7udU5KIHd0cEiKfX12ruens65euEFnU5PzX/kQstrruE1b2jgzUN7O4/z\nuc/xmOMh0getjqeO/+c/czwFBZy/jAwe5777OHaVuUSddyjEpxhr11I4FxVxP3XD8vjj2vMejciK\niuHw0M9HCbOvBMIBppbz9QI9DVxEOOuKyR6ZIAiC8HFHKgxGY+1aWgiG5+H1+Sgw587l+85OCpDs\nbApBj4eizWajKOzv1+K3r09nrejro8jJzKRgam6m6Itc/q98vMEgo8+pqfpx/dy5jISWljK6uGsX\no7Xr1+vKhLt2Ucg7HBSCNhv3U6W06+spLFX1waws7c3NyeH71lae3/z53Ndi4RisVt5IuN2Miqoq\ngpdcwnHv2KFzRl96Kb+/aBGtBC+/zH6vuoppzNato6ju7WWqv6YmnoOK5rtc/KvOfdEiLryrquI8\nGobOf5ybq1MKqrlrbGTfiYnaE+5ysa2ujn0vXMgboqVL6SHfs4eRcLudBURuueXAaR5MkzdIGzbw\n2qenU8y/+KLO5NHezvlatIh9q6cNKn+036+vV0oKr63Hw89OJ61DWVn6uqonEQDft7byCURCAm0p\nmzZxbtLTOSf//CcFd1wcj5WZyacCgQBvctSThtEIBmkR2byZTywyMjjXhwFHGpC3kBUBgx4g90Rg\nwQ1ASuFhOZwgCIIgjEAqDB4s+fm6kElk7t5AgBHBtWsp+JRto6uLC7xuvZU+WuUxBiikOjoofLZs\n0YvElOgbGKAXWAlOhYoGFhTwe8oDC1C02mwURffcw9Rtat/77qMN5KKLKJLOO48vRe3/Z++7w+Oo\nzu7PbNFqVyvtqhdLltwLNrgbMBiDaXYMmOYEwgeEBEhPIMmPlC89pJBAAl8qCSGhhIQSgglgIKa4\nYIwbbrItN3VZdVVW2j7z++Pozd2VtWsh3DBznmcfSXt37tx7ZySd+855z1vDPjs7E8cp1QdLSzmX\ngwdVlHTHDpLOxYuBFStIoASaxvXKyqJe9oUXeFw4TPmH10uyeMMNPFbwpS8x+nzuuXSAaGhQbRs2\nUKc7fz59oBsbeR5dJyEMhxlZf+EFVYADIOGVyPVzz6kCLQCvU3k5CfITTyjJTFcXCf306STY3/42\nI9dWK8n2fffxuIsuSn6/xGIsArN2rSLZGRmqwuDy5ST6Fguj91u2cIxlZdRkx0ejNY3EurwceP55\nVfURIDkfO5YbmaqqxAqFkYhyVZFqgBYLj8/JodyoqIjXdcoUdZwkhYpMZTD09bHPvXvVOPPzgbvu\nIok+BsgaAUy76Zh0bcKECRMmTAwbpmwjGWbMoL63qYkRN10ngbXbWU56506SCKeTL4k0t7UlElKB\n9NHTo4qFSDXA3l4meyV7bL5gAYmlrquKf+K/Gw6zTHhurqrcV1BAIieR2MZGlYjY1MRo4/nnq7Ld\nklRoGCR45eUkaXa7sqqzWknWCgvZn8WixqLrHF8sBjz1lKoUWF7Oc/3pTySrK1aQ2Obm8uVycexS\nMEY8jDMzOb9du3ieujql0ZW2ykqlVxYHEUna7O6mRWBTE+fg8XAeoZCKXjc28rpJn7rOPl9/na8R\nI/gqLWU09utfTyTpA7F5Mwm3aJ4rKrhmv/8959zczDlIpcCeHkaUzz6b18FiYbvNxvsnJ4fyjEOH\n1HGZmST6kQgT+QIBVRgmEuEaXnQRNffbtqlrUFHBPv/6V25+pGQ7wDnV11PjnCr57+WXef3jKwz6\nfKwMacKECRMmTHyIYMo2kkHT+Bh71y6Sqs5OEsf77mNEb+VKkirRoYpMYM+exEp38WhsJAnSNBKf\nWIx95OSQXIlEIl62IdHAsjJF0Pv6GPWrqGCfe/awD4HVSoKUn88EsoYGyiHa2hhx/OxnOf4tW1RB\nlFiMZDY7m8d2dHBsUoUuK4s/22xqTC0tnMeIESR60ahyYvD7VRlpn48R2fp6ZfsmJcMDARLacJjj\nFs2118v2tjaup8Wi+szOZlttrYriy+YkPZ1tmsb5B4OM+odCTNwrKqKcQY7r6VGSFYuF0fdAIDGi\nm57OccyezXlGIpxnNKp8i//5T/YlNncA25qaVPVGv5/njUQox/B6ed/YbFzL3l5eh3HjKEuJRNhf\nVxePjUb5fkYGcOWV/H7HDp5D7AmXLlXJifGR5IwMbog++lFGvLdt470UDtN+cckS9YSlo4P9StEU\ngBugzExENBd6e90ADNg8Tt57ixYdudCPCRMnKQwD6G2mtj7NfdyrxpswYeIkhinbGA7sdmDqVEWQ\ni4sTdZ7xJDe+NHYyiO+zuBoYBgmpVB202Rg1DoVURFjkGbGYsk4D+BnxcU4Gm42fkwRGgP0Fg6rq\nYWam6sPpVBX1BkpWpAiLFISJH4uQb6uVBHLlShXZ9Hq56bDZ2EdTk0qgk2ixnC8WSzyfjCUcJoGU\npEpdJ5mXcQupB5QjR1oaiWoopIidkGIp2d3ZqcYSCJBAx1dqHAirlZKRv/xFRe2nT2d57vjqgQK5\nJ6Tq4rhxHI/MubaWX8eOJTHv7lbOGrW1/Fxe3uDHWSx8OjJtGo9zOpVeWSLwA8ciGvq5cymjER24\n6KZ1Hfjxj1m8RSpUnn8+8KtfwbBYsW//eOyungZd5zUaVb4fU3IOwWKyDRMfUPQ0Ahv/AHT1Fx7N\nLAZm3g54U+RhmzBhwoQp20gGw6DN2549lABMnqy0pPPnk1wEAio5TaoP3npr8j4XLiRh6ekh2RFH\nC5+Px8kje4eDJErI4q23Mlrq85GEiT/zzp3AVVcpba5AiO0FF9Aer6ODvsJjxpA0/uIX1Fh3damo\nqNPJ77u6qE0W4il+z9J22WU8byDAjURODse1ezft73bs4PlFKtHRwbYrrlAV/4QERiJ875ZbVMKf\n06mqAfr9jKZKtTwhln19fO+667jmEvm32VRE/6qrGF0Vva/4V9fUMGLb0cG1SktTm4zmZo5F3C0E\n7e2ca2EhLe7S01VFw3ffpURm3jyVBCpobeXnFi1S1QdFmtHSwgjwokWqQI3Xy3bxCr/0Uq6tzN1m\n4xwmTUos8OL1Jib6nXceI+XxLh9NTXRCkci41aqi+4LHHmOp8+xsSm8KC7kR+s530FC8FNs3T4TL\n2QuPpxuZmT3Yv70EVa5rj4nXswkTxxqxMPDWL4C+Vlax9Ixk9PmtXwCRQZR3JkyYMCEwyXMy1NXx\nMfeIEeo5XmYmicyqVYzcifwiECDZKi+nA0SySNzBgyQwFouqsheJkMzl5tK3NxolWevoIBn7xCco\nNxDbsviIaUUFydr3v8/P1tfz5fMxOSwa5Wfz8zkmTWMks7ubko0pU5QOW8jd1Kk8/rTT2Hd825Qp\nXJOKCq5DZyfHY7Pxve3bOdZYTLXZ7Wzbt49RX8NQtnOaRpJdXa1kCt3dPJ/Vyqjqjh1KkyyJbVYr\njwsElFwkECARB3htqqt53nBYjcXlIilcvVoRPpF7SFTW5aKm/dAhtZ42G4uYvPUWvxcCarGQQG/d\nyqcSixfzvqmp4fldLlYYnD6dRDi+ze0GbruNY734YtVWU8NNx6c+BcyZQ9/p2lrVlpPDeyIV5s1j\nEqZUO6ypIRH+n/9Jfdwjj/DcQqhtNh734ovY1zoDrvIMWP0+oLMTlm4fMksM7AueB/0IzngmTJyM\naN0FBHysXCl/Hl25QLgHaN5+okdnwoSJkxmmbCMZJJJbU0NCHImQSGdmMjI4Zgz1s++8w7aJE0nk\npFJgejrJnMgvIhFGIufM4fF79yonjYoKkrtbbiHheeIJkrpLLwW+9S2S7owMvnbvJtkbO5aRw64u\nJok99RRLSxsGidOiRTwuFGJFvb17OZ+xY3lOn4/JcJEIo+vSVlZG4p6Xp7TegPIfljank4RY03ic\nw0HSX1REWzux3cvLY9SzuZltWVmMulqtlKj4fGwfN46ke/9+tk2ezM+Lhtpu51hEyyz67xkzVNRY\ninhUVHCtCwo4DpFAnH4617Cqil/Ff9ti4Xw6O9nPPffQ13ndOo538WKS3fXrD3ekkP+6fX0kus3N\nJNm5udQfFxWx/Ywz6JyxaROJ/6c/zfFZLCTPLS28l/LyGDWXDc9NN7HfujreexMmKIlKUxP7rKzk\n5xcv5obDZuPTikWLqHfPyuJxR9Il+3yHW9XZbEAkgmCHAduZ04DgKG7U0tNhzclFrE6jH3MdsGc5\n4DtAl4zxlwF5x7CWSnsVUPU8H7d7RwMTLgOyRx/5uNZdPK6nEcgZy3Gaj+g/nIj0Dv6+ARJoEyZM\nmEgGM/KcDKWlJJ8bN5JgWiwkixs20Bd3/36SluJikrW2Nn72iitUHxkZJF1CdhYupOPE7t1K51xf\nz8qF+fmMNj71FKN9ZWWMcH/sYyRUa9ZQhiCFQPbsISkuLqYbx4oVJD5OJ6vsLVjAPlevprRA9Ldb\nt7J96lS27d6tZBu7d7Nt7FgWExHiDJCEPv88j9u5k/PPzOQcKys5ntmzVRLkiBGM8gphW7hQJSWO\nHs0ovd3OMZ1zDuUBBw9yvRwOjnndOkZRJZouhWcaG0k2Z8zgOFtaeIzVyrH85z+Mkr/yCvt0OEhE\n16/n9bvgAmXrJnMQTfcFF3C8p53G67FsmUoePP10lWgokLLWTifwox+pAjJpabQMfPFFrtX115M4\n5+TwXHffTX1xezuP27WL62KzUS60cqU6x4gRlMScdpq6l5qb+aRi40aeu7mZkqLVq9muabyHzjyT\nG5GhJPTNns11jkdXF1BSgsK5DvS2atywlZYCeXkIdGjIHgN0NwJv/pDE1OYEOmuA1T8BDg1SMPNo\noGUnsPrHQMcBwOYC2nYDq34EdOxPfVzTFmDNT0m4bU6gZQew6occr4kPHzzlAAwW3xEYOt/zjjpR\nozJhwsQHASZ5ToZIhARISm9HIirBLxBQiX7SBvC9yZNJWAIBRiPla24uI4h+vyKBmsbvo1HaiL3z\nDgmP202SWVbGqOnjjzNCKo/T4497+GFVsln0wtnZjNg+8ABlCxJN1DT2EQ6TZEl1PomeSttvfqP0\nsuJjDfB8f/87+9N1NXdxBSktZTLawYPcTLS0MHK/eDHJ4/TpJMIdHWxvbKRrhGiF4+eXlkb5hkSU\nxeNZkhitVhLRlc7yAAAgAElEQVRMXVeWf1JlsLOTdnPi6CF9Ohxs+/jHuUHx+XiOri5+vf56Pj1I\nhrlzSXAPHuQcmpq4zjfcwGvX3c01EGu5sjJ6Tf/2t7wPSkrY5vEwIv344/R/7u1VlnjZ2fz+mWd4\nzZPh1Ve59iUlyrGluJibr1TVKlPhjju4kZDiN+Li8b//i/GXWZDmBjpr+ai7u56a0SnXAVXPATYH\n4C7kV1ce4MwBKp88NkULK58CHB6W7v7veZ3Arn8mP8YwgJ1P8rG8K6//uCLAYgOqlh/9MZo4+ZFZ\nAoy+CPBVA72tLP/uOwiMPHdoTzFMmDDx4YUp20iGQ4eUb/LOnSQRY8aQBFdWkhjl5FA7LNZjpaUk\nh6+/Dtx5J+UXkQijp3/5CyORdjvJsehzxa5t0yalu42HxcKIqbhiNDeTFObnq4IhAAmY30+WINri\nzZtV5LulhZ/Lz+eYtm4lUbLblfdxQYGqIgcoF4z47zdtojTAbqeUwGIh4QwGeY5bbyUxfOEFzu3G\nGxl11jRaqP3ylySUDgcLytxyC/CVr5BQ9vWRVFssJIWaxsjqiBFsa2/nOEaM4Ji2bFEe28EgP5+V\nxc++/TbnCpAk22w8zu/nONesYcT39de5trfeysIyqeB0cqxPPsmof14ej5s1C7j3XmXrJkhL46Zg\n8+ZECztp03VGwp1OSj1ECz13LjcxPh/XcjBUVamkwfjxtbaq6n/vFRMmsCT9gw/y/qio4PWZMQMZ\nABZ8D6hdTclEZilQcR7dCdr3AenZiV05soCuGlYItB7FfEJDBzqr+6OGcXBmA759/D7SBzRtBnoO\nMQms6AwABuA/dLhEw5kDtO89euMz8cGBpgFTrwPyJwO1awEjBpSdzcqWpoGMCRMmUsEkz8mQk0Mi\nUlfHnzWNj99bWuhmsGIFH7VLaG3DBpKf664j4fP76UyhaSSkr7xC1w6xs8vKUufq66NU4t13D69o\nqOsk5uvXJzpq1NeTgJ55Jomi36/afD6ed/Rokqz4oi11dTxu1CgSQCHxAKPcTifdHOrqEp0j5PtR\n/c8zpYiIoKaGZG75cso7rFZuOB5/nER7/ny2VVVRUmEY9H6eMIESjtraxIjpgQOMvl96KYllOKyi\nz42NJJmTJlFKI1F8KZCiaez35ZfVhiQWYyTVZiPZLyqic8Z7QfwTgrQ0rvODD6qqjLt2MXIcv2aG\nweuwZk1iqXeZa2kpNdZ9feo/dmUl3VDi75GBGDFCbY4E4bDanA0X5eWUlAwCZzYw4fLD388qAfzN\nJKKCSB9/thztvzAa4CqgXjUtfup+wF3MCOLanwJ9HTy3HgGySoGzvwqkezguu0sdF+qhRtvEhxOa\nBSiezpcJEyZMDBWmbCMZvF6So2iUEcWsLBKTtjZGNKVMsVSoczgYFW5qot1Xfr6yMysvJ3meOpUR\n1c5OEitdZ5QwPR34yU9ITBsblQPEoUMcx//8D8nVwGqAgQAJebwlmcAweP7BjgsGSWADgcH7/OhH\nk6+LlJuWioexGIlvRQXX4PnnOeeyMkVSH3mEeu0XXzy87a9/ZV9CJuNlIoEAyaVElWWcus73li3j\nmMUfWtMYVU9PZ9JdKKQ8n+129peezs3IcLB5MzcqFRUcV3k5ieof/sCnCxYLo+NSmrymhj7Jn/uc\nKsUuY29oYKJnVRU3PmlpyhZQtOkDk/ficcklnKtY2QWD3PAsXpz6uGOAcZcBwU4SUYAE1X8ImLj0\n6EfwNA2YtJRkPSxFEv1AoB2YsBTY+Q8g2M0Ic9YIwFsBdDcAe18CJlwB9DQpG7JQNxDqGnxDYMKE\nCRMmTCSDSZ6ToaaGEcNx4xiBFteCGTMYdc7M5KNxn4+E2uHgY/yXXyZhS08nMRZyY7czorhihXKj\naG0lgXzySUaeH3mEJKy2lpHX8eNJLnfsoEbX4yFJkmIfRUXAs88mEk5A/fzvf5PoSmnqUIjjLiwE\nXnqJX0VCEgyyLT+fEenCwsQkM6uVmtqdO2mDN2UKI61VVYx+33EHEw5FP+3zcf5Cdl97TfU3sO2l\nl9gmhUZkvSwWaniLi5XXdDDIDUV+PiP1CxaoOYTDJLULF3Is55+vvKalZPfcuby2ANdj/35e26GI\nczdsYH/xjDAri33rOnDXXVy32lqec+lSJnzOmEEdeU4ON1c9Pdyg/OIXjKpL+XPZUGVm8h5auzb5\nWCoquJGxWEjoa2r41GPJkqHd342N1IyL08pQ2wZB0enA3C8CFiuT72JhYManqB09Fig9C5h5KyUh\nkuw3+/NA4RTKNTKLEz/vLgLq1wEVC4DptwDREI+z2IG5X+JjexPHF4YBdNXRnSWWouq9CRMmTJyM\nMGUbyWCzMSK4ZQuJHkCSFIsxQtzTo3TEAAlTRgZlDz091NKKhMBuV4ld+/ZR3iFkt7VVkcD6epJR\niQLX1pLcidVdIKDIaTCoXB6ELIu0QoiYRCAdDiUZEH9jh4MELRRSZFD6lKpzRUUq6pueriz4OjqY\nNOdyKTmLeDp3dpJUS7Kb263Ir89H8h0Oc36ZmSqJDlDRY0DN0+FQxFjIdzDIY1wuzn/UKEbYLRZu\naKxWvi9e2eLq0dqqypyvX8+NidgJjhkDfOYzqbXC6emJUhYgkeyPHElrwVBIJYUKFi4kme/uTqzq\nJ04g8fpliVynkm3oOpMKX3yR3+/bx2PmzOEmLtVx3/42NyXy8+zZwO9+x/N985ssNS7jmDNHtaVA\nySygeCYQDTIZTzuG23JNA8rnAyPPIRG2pferdvR+qUYMsMYrn6KAtX+ZR51PrXYsrN4zcXzhbwY2\n/IbkWdMAewY3W0VnnOiRmTBhwsTQYEaek6G0lNrWri6SPI+HZGjLFlqGxRNn+Q/c20vicuAASaTH\no0hrZSWJmUgw8vL4sliA732PtnS3307iXVpKkme1MppZVsZItUgS0tNJetramLCm6yTCUu5aIpif\n/zz7CwaVHV04TAJ37bU8XqLkUtGwrQ245hoeF4mQ/GZksI/ubtr0/fKX/UxkFCOgfX1MmCspIXGO\nRtXcu7sZwZwzh2ug63xfPKr37gVuvlk5aUgEWtxNPvEJVQ3Q4SApDYU4zgsuIBm3WBiJzsnh+wcP\nkshu2cK+srL46upi9FjTgN//ntd15Ei+amvpipEqAj1vHjcw4q4C8D6oqFCJffEbjYGQaoDxVf1u\nuIHXRAq1aBrXbMQIJmYmw9NP02klN1fpz7duZUJjKjz6KPC3v/HeKynh6513gK9/HfjTn/gUpKCA\n7xcX0y7wm99M3SfU1O3OY0ucE85n6T+fpn6uOJ8yDbmMRn+i4KgLEo8Twm3i+MLQgfX3U5suVf1s\n6cA7/wf0thz5eBMmTJg4GWCS52TYsIFELSOD5EYS6zweWsDFI55wPf00yZTLRbLW1UUyOW4cSUtf\nX2IUz+Uicfr+9/nZ+KhhZiaJ2h//yEQ0i0XJLwASsd27aY+naRynRHXHjWO/Z5zBNqloaBh8b8MG\n9qlpqk9N43ubN1Naous8RiLo06ZRIhAIJCa/5eZy7G+9RflJfPVBh4PvbdnCr7rOts5OFTV2OKgf\nlohrOMy5zpxJQuj1qgqD4s+cnU1Zw7hxfK+ri+MUQvzSS2qdg0Eem5FBUvvoo6owCsC5FRdz09PQ\nkPyemDCBOuumJlX1TwqeDJeJffWrjEh3dXGT0N7OcT/2WOrjHn2U8xEibrGQwK9bl7ixG+w4jyfx\nuOJiPimRNvGSlj7/85/EpNOTGBOXAoVT6fTRVcuvI88BRl94okdmAqBMw99Ee0H5lUnLIKlueOfE\njs2ECRMmhgpTtpEMnZ0kEW43H/fHYiQWFkti8ZCB6OkhGbTZKMOIxUjm3G5GRQ2D8gVJ1hNpRVcX\nCeKOHfxeLOc8HpIqp1NV5zMMkmwhorNmURawYQPbZs5UZNnjURpkgERXIsJOJ78XqzqxsROLNL9f\nJUaOGUM9b3c3NwPbtjFBTSLQaWls83q5Rvv38+vYsYzEdnYyMmyxkKRarSTM0nbOOVyvnTu5aZkz\nR+mVMzJIfv1+ni8nh+dra2NU/owzOGarlW0NDWzLyuLPwaAiy01NJKi9vdSLNzSwL6kQGQgw8fO5\n52jLl5lJx4/zz2f/ZWW8PuJ0ccMNymGjqYl9bt3KdV28mC4jFgvP8+yzLKLi9bL63/z57PN3v2M0\nf9UqrvGdd1InDXCN//lPrktODjXN8+ZxreMj2ADPYxi89gUFye9Pw2C/fX3sIydHbZQGqzAYjfKz\nDQ0cy759jEwvXUrv7veBlp3A7mepQfaMBCZeSe3ycGF3AmfdyYqHfe0kaZkl72uIJo4iokEAg+wz\nNSsQ8h/+vokjI+Bjdc/6dYzij1oIjL0EsKYd+VgTJkwMD2bkORnmzCHRaGoimXM6Sd6am4Grr05+\n3NSpjMDu3EkikpFBovLaa3RICATYL0CyEwjwddFFJCdiM2ex8HP19STGEpl0u0nourv588KFimhf\ndBFLPQuZmz6dEdjWViWHaG/ne2efrRIa3W6+fD4S2XPPZaXBAwdIQDMzSZhWrSKp27GD5Dg9neRr\n1y5GwGfNIqmurSUh83j4vlQf3LpVtWVmqoTDWbOo++7sZHS3ooLn27uXCX51dVx7m41zkAIrS5ao\nCn9FRST/0Sg/s2SJKr0tRWdCIbbNmUP3k7o6FX3etInyhawsVv7bsEGVyP7rX6kRPniQspudOymT\nSE+n08Zdd3Fd776b8xAP7oceom9yayv73L6dbbEYJRJSHfFHPyKZv+QSzv/hh6llPnSIfe7aRTIc\nifB8L79Mu8SBm7ieHm6qxE4w2f158KBat1hMlX8/77zDKwz6fNzk+Hx0hKmr41p3dQH33ccnEcNE\ny05g7T18XO8uAvpagbfuef+VCTWNRLx4ukmcTzZ4yimbiU8SNAwgFgIKTjtx4/qgIhIA1v4MqFkF\nOHOp49/5FLD5oRM9MhMmTm2Ykedk0DSShqoqEg2pJuj1qkjtYDh4kJFOu13pWCVhbdcu5RoRi6nn\nljabsjiTl4wBIIktLiaRlj6jURKlcePY/3PPsW9NY5TwwgtJgKXstPQliYWvvsoo56FD6pyxGIlR\nc7OysNN1lRAXi5E4ut0kahI9B0iGfT5+jW+zWFSb202SKG2axvc6O0neZCMhbRkZJNyiBZZxxhdv\nmTWLvtput6p4ePPNdABZvpxk3uXiOkSjLMxy8CD7E324PAHo7iah7elRlQZtNpL5V14hwZZqgNLm\ncLAgzJQpXHc5TsqMv/gijwkGGbWWtvJy2vr5fByztInt4fLlvA6xmPLTzszkNfnXv6hDfu013hPp\n6Urq8uMfH15oJx6jRvHzwSDPG4txPceM4dq8/XZinzYbJUUvvMD3RFbk9bLt6ae5wRmGbGX3s/Re\nFn9oZw6J1a5n6OBh4tSDI5NVKbc9CljS6NAS9gOlZ5quJ8PBoS39xX8q+LPVDmSPogRm4hXm5tGE\niWMFkzwnQ2srCVF+PqOQUkVwyhSStWRobCS5yshQco/cXJK9d98lYQ2HFUHNzSWZ2rFDJZpJpUBX\nfzWH7dsZRS4oIBnUdSYtjhlD8nvllSwYsn49zzdnDts/+lFF3iUBT5w7du9mNLi9nefWNB6Tl8fE\nPtEHy0ahsJDks7KSUoxgkBsLi4WyCauVkeIJE3iOxka2lZZyPlVVbGtq4ibCZqOG2uNhZHrKFPbR\n2Mi2sjIeV1mpyK84f0gFxW3bgC99ieu6aRPHfPbZtBgEqDF/6ikSX6+X6zF/PstzFxSQqHd08Hwl\nJbwumzfz59WrGf12OrlODgeJvFwTgeiDt2zh9du6lVrojAxGeQ2DcxhYfVA2VJWVhztZpKWptXY4\nOKb6evYxdapKHP3HP1hg5e23acN3xx18apAKnZ30wN64kdfC4+Ga6Tqv/fLl1D5v2sT768Ybed2e\nfDJR5w7wOtTUMKIvjimDobeXUf3qalXCPSsLndWH/3N3eKhVNgySqoZ3+LO3HBgxRxVGCXUDDRv6\n2yr62wYUcRwMwS6gfj3Q08ASzCNmJxZNMXHsMXohr1n9OkZOS2YChaeTSB8JndW8J2JhoGg6kD/p\n+CWonozoqjtcniGxht4WkzybMHGscETyrGnatQBWGIbRo2na/wKYAeBHhmFsPuajO5HIy1NyBJFR\n7N3Lx+wLFpAsDYaiIkYgu7pUxFeiyh/5CElLby9Jl2Hwc3197HPTJhIjOU6qzk2cSIIkFneaxghw\nayvwhS/0V46YxFc8Jk2inZkkGALq+7FjlR+x2LPV1/OcS5aQeIrswTB4bqeTJO3ppzlum42ka9s2\nbjIuu4xEvKhIuU8YBuc7ejSlCiIhMQxGTseM4brs2UNiVVysjhNv5g0bVMRdtLl2Owm3zcbo86xZ\nh18Llwu46Sa+4jFmDCP10agqrLJ/P8npuHGMtPb2qrkfPMikzAUL+H08olGVoPnzn6trK1H66dNJ\naNesSbSjk3OPH89rG09MIxFVhvznPyfJl7XesYNRdbudWunOTkppQiEmGZaUcH7JUFTEdY/FuNax\nGO/JadNI+LOygK997fDjysv5BERKngOcq+jPk6G9nXKP9nYS7FWrGN3/xjeQVVaEQAcrFwpC3awI\n2NcKrP4Ji6/Y0vlYuurfwLnfpBXd6h/zs9K29wXgnG8ArhROg90NwJqfkpTb0oGaN4F9LwHnfB1I\n9yY/zsTRR84Yvt4LDvwH2PYYoNn60ypeASouAKbd9OF1TskaAcQiie8ZBhMwXSkcK02YMPH+MJQ9\n+7f7ifM5AC4E8BCA3x3bYZ0EsNlIFiwWkoqMDEYBfT4StWR/ra+7jmRCHnnb7SRKsRgjfKGQKtEt\npCMcZvRWCGK8zELXSdzq6pT7h7gstLSQSCbDokX8Gu8GIt9feqnSt0qfAMlYWZki2TIHceWoqOBn\nRFaRkaGSIOfMIXmrq+OcpcrepEkkTi0tHLccZ7ezfcoUblYkwTIcJlmfPp2kO76CoqxLNJpa25sK\nOTmq3LdUH9R1vnfggPKGdjiUFGbvXuD66/leSws/HwgwUn7JJcrKT/ynMzKUB/b553Mdm5t5XF8f\n533ppUwqtFhUImhfHzc1ixfz834/Ny0ul3Jm2b+fTiMHDnANCgspF3E4qJdOZbeXkaGSDcWXXDZp\nqeQel11GstzRoZIS5alHquOWL1e66cJCfg0GgaeewsQrgaCPBNkwGBUOtAOTrgQqnyHJ9ZYz6c9b\nzsqBu54FKp8CooHENkmaSoUdT7Bc93+Pq6Dn8N6XUh9n4sQj2AVsf4KRVE8pv3orgOrXgY59J3p0\nJw7FM7hh7G7gpjIaAjoP0nM90yw7b8LEMcNQyLNUhfgIgAcNw3gBwKmfx/v226oaXzBI4uB283H/\n8uWq2EY8CgoYmZw3j4+6e3pIHAoKSKDWrOH3eXmMLoZCjPQVF1ODXFLCn2MxvpxOvvfqq4neyKIf\nzs5mciLA/vbsYaRciO+77/J4SYoDSO7Ev/e000iGOzr4qqggUV+1ihFKj0fZ2Hm9XIuVK0l2y8tJ\n7Pr6GMWeOJFE8mtfYxTznXcoYVi4kH7T69apRMHubq5nbi7nu3EjfYZPO43rvm0bieXtt1OK4nKp\nSL3ok10u6okBjqGykjKLgUVMBsOWLUpaI9rfwkKO5+WXVRGTSIQkPStLPXl4+GES1upqzuPGG1Wl\nQCn40tvLY0tKOO6WFmqUx4zhxiIcZuLh0qW8Ft/4BvusrWXbTTcBl1/OiHtpKfuUTVdpKftesYLj\nDQTYf1cXr1FDg0okPHiQDh/r16sNSHU1pStutyr+M2+eekIAKClPfOXF8eNZWTI3l+O024HPfpbH\nClpbeVxTk3pvwwaubTwKC4HNm1E0RceZdwJpmZRfpGWw4l/RdKBxI5MI45FZRMlF0+bD29yFQGMK\nq7NYmAmKGQOG4i4EGtYnP87EyQHfAQBGokRBs1Dq0Vp55ONjEaC9CmjbTYJ5qsDu4pOTkllATyM3\nouMvB2be9uGNxpswcTwwFM1zg6ZpfwBwEYCfaZrmwFFy6dA07c8AlgBoMQzjfRhUHQO43aoCn1Tw\n6+0lacjOJhlJT1cFMyT65vWSINXVKYeLtjZGESdP5nEWiyrzLAl88nO8d68U2vB4SFQ7OhQJ6uvj\nudxuksZf/1pFoZ1OEpuMDI5xzpzE6oP19Tyutla5iQCMJJaUMIoZbw0HcCMgBUe6ukimpIiHpjGS\n6nCQ6P/hD8oX+777SLQzM7l+PT1qDnV1XEu3mwlpf/wjySPAoiujR3PuhqEKw8gcdJ3zX7eOhFbk\nE4WFwBe/yHkkg8fD6ybXEuCxus6xyOZFrqlUIZTNS3Gxki8YBtcpK4vXRCQXIskRu8ORI+npLMmQ\n8aio4KZjYFtmJonxyJGqTdc5nqwsbo6EqBoGNycjRnDcd97JhEQ5Zvx44M9/VhuG+fNVn9Eor73F\nAjz+OH2d5b484wxuYlwu3r/f/e7h44xGKRl5800ep+u0S/zUp3hcJJIo7RDNtqaheBpQPO3wLu0u\nRonjdbCxCAm2HuH3Nkdimz2F5lmzMJlKj/LrUI8zcXLA5hj8gYphHFmz7jsArH+AMh8AsDmBWZ+m\nH/ipAFceMOt2EmbAJM0mTBwPDIUELwPwMoBLDMPoBJADYBBR5LDwFwCXHqW+ji7OPJNEzu9XFfg0\nTSVc+Xxsj2/r6GBy2YYNKqqclUUCtXUr5R59fXw5narcc3c3JQHiyiDVAKVt6VJGA3WdhE/IbkcH\nialU/JNqeU4ncP/99E5OTyeJEyLf00Mis2wZI6mxGEmh10tSU1VFba8QdZlfLMZNwNKlPL6nR2Wm\nSCTcbmfpZ6eTEdLSUv53+8IXqAkWGz7pMxJhnx4P7drcbnVcOMwNwOLF/Fz83CUKe+aZwIMPkjSO\nHMm16Onh3FNFoOfPV9ITGYvfz2Ouv14Rf1u/uDIY5NpVVDCZrqCA31dUkLz+/vfUNft8yk/a4VAl\ny8ePV+dO9Z9tYNv113NcIjHRdZLc6dMphdm9m2TY4+F9JnKZp5+mI0dhoaoiWFVF8n7hhbyXxO3F\nMBhhPuccPgFYsUJVuCwv530rpbyTjfP110m4y8r4GjmSvwPPPUf7xEOH1MZHznfRRQn9DOxyzMWM\npBlymM6fx1zMgic98VUEdToOjL4o+dJabNTHdter4/QYk6rGpDjOxMmBnHHUpfe1q/fCvdxcFaew\nGo8GgXX38XupaGh3sqJhMIVd/wcR8ufYhAkTxx5HJM+GYfQZhvFPAF2apo0EYAew+2ic3DCMVQA6\njkZfRx319YyeZWSogiPhMCvv7dzJiKXDoarXASRx8tjf5WJbIMC/aF4v/ZXnzCFZk8p9hsEIbl0d\n26TYiLTNmEFCk5ZGAieWa6LXfeIJkvH4hDO3m2NqbCSRBNh/fT2Pvfdetk+YQILY1UUyabfzvddf\nVwVhhOzbbHxkv2sXHS5CIUabq6s5rjvv5Dh1XemgJVrb28viGhLllXVJS2OfDz6Y6C4ia9ndzaj6\nlCkke2Jll5ZGucDKlRyjRKUNgxHhlhaOSyB2dIJIhK4V4bCae2Ym19piIdmNRnku2czMm8f5ibe1\noLiYGmSfj4Q2FFLVDnNyeJ729uRjSYVrrmERFvG1bmyk9OO++0jaJ03i2sr5yst5nR5/nPMRqYum\nUYazfj2Pv+wyElipknjGGdxMrVzJ9ZMnHppGIr16tXoiMBhefZX9S6Re0xgBf+01ypUWLlRPY2pq\nuJZLlqSc+thLgfL5dBOQV8UCkufxS4Cyef0VBPvbRi/kKxUmLaUrhxzX08DzjDyCQYmJEw+rncVv\nbOn9168WiPQCc76QOjGubTdJdnxCaJobiIbfv5+4CRMnMwyDAYKh/rsx8d4wFLeNywHcC6AEQAuA\nkSB5Pi6W9pqm3QbgNgAYKR66xwPhMLXJn/gESUYkQkIgRMVuJ8kQUiGkSkpZC6kBSL5yctTjfYkE\n6jqjg3l5bPN4SMb27WNbURGP6+khEcrLU0Td4SDp6+1VyX7x0DQSv7lzgc98htpXw2Dk+OyzGVHM\nyqLOWDSyXi/n6vezf/GjBjhXm43nKynhcUJeFywg6fL7uU67dql18HrZl0TwxS0DUNFq+exg6O5W\nFRT37OEaT57MjYBsav7xD8pirFbqr8eM4XVpaqLF2rvvcgwXX0zSJnNobWVU1GYjSczKYp+zZnGt\nDxzgcfGbqIE69//6QvUy4trWphIjR47khkASIP/xD65NZiYj6hdfrIjqYLBYgB/+kLIJsTmcOVNt\naiZMIDmXqpZut6ocGI3ynMGgKmduGPx52TIVEZZ7TuYwcH5Wq5KxJEMwePg9aLMp7+mbb+a6t7Zy\ns5Ss+mH8ae3AjE8BE64A+tpIkDLijD5m3c7Ewr52vj8UZwFbOjDnc4xSB3zUO4vHtImTH54y4MKf\n0q5OjzJhMF66MxiS6Zs1ALHgUR6gCRMnAQyDOSOVzwC9h5hcO/kaJpeaOHoYimzjhwDOBFBlGMYo\n0HFj+GXF3iMMw3jQMIxZhmHMyo+3yTrWKC9XEoGKCsoOnE4SyquuYuRONK3yucZGEkmpFCiEU0ob\nn3UWkwb37SNRy84m0XrjDUafV61SVf2ys0lu3nyTkUJAJRE6nSqye801bBPttXwOIJG87z7qgmfO\nJCncsIEJbuJUIV7TubmqqMmCBZxLIKDkHn4/35s2jfZpGzcy8jluHMd4//08R1MT1yUtTRV/aWlh\nAuChQ4qYi3NJSwvnEIslumpISe0rr+TaulzsX3yObTZ+v3Il+8jMJDmvrOR8vV5apFVWUkqQnU0p\nw8MPkyyuXMnzZ2eT+O3cycjs7Nn82ttLEl5czCS42loSeClvLfD7ee7RoxmB7enhhsflIuHdto3E\n9Cc/YR/l5Wz7298YjR8KSktJPmfPVtHduXOV/Vt+Pu8Zn49znT1bbfgcDp6/ro7nlQIv2dm8fiUl\nauNy1hPDMXEAACAASURBVFmHFwBqaWEyaHzS6UDMmcPNSzyam3mvCBnPy+P5hkCc45GRTy/fjEF+\n9TMK2PZeLbncRTzOJM4fPFistLjLm3Bk4gwAOWN5e8fbuen9fx7zJh6bMZowcSLRtAl45wFAD7Oi\nZyQAvP0r4NDWEz2yUwtDSRiMGIbRrmmaRdM0i2EYr2ua9qtjPrITDacTuOUWJr9pGglkMMhHziLF\nkOQoQBGQ1147vAqeEJ7XXydJFCeH+OqDL76YWMREZBmGwfNdfTU9m+Vcus4I8o03MiL55JOKqEQi\nKsJ68CDJv6CsjBFJn49R6GefVRrqSIQbgz171Pjj52ex0GmksVH1abUywrpvH9sdDkYcJSKvaXyv\nqkq5RgjRNwyu8+jRJOxvvJHoqvHFL1JLLKXBHQ5Fsj/5SZJk0SWHw6q/YJB6254eklWAx1ZU0M0j\nL08dJ8Vj0tO5yTl4kMQ7GCQx1nUV1R0/nnrjLVt4HvHk/tKXWIrbbj+8T5+PYxFfZbm3ystZvGXx\n4sGfHBwJ553HjZCUSZekvJtvpuY5M1PJbXRdVRGMT4QciIsv5tyqq9W1crtZVCYVlizhBiP+uKws\nFqUxYeIEwpULnLaMNncWmyoNPm4RkFV2okdnwsTRx65/Aq58wNFfeyvdw7yQ3f8Cis44sWM7lTAU\n8typaZobwCoAj2ua1gKg99gO6yTB3Lkkm++8QyJ6xhmUDDzwAAlVdjbf13USonCYRE80sWL9JYlu\ne/bwc1ar8vzNySHBkdLdsVhi9UGHg9Hohx5i1O5vf+Mj+csvB371K/Z16aX8+uyzPP7qq1l45K23\nVFnwXbs4lokTeZ72dn6mvp5yAk0DPvYxEqEXXlAa695e5QKi60xSc7sZQd+1i0RsyhSObe9eronP\nR+IKKHu6PXsYIQ2FKG2wWBj1tFgYJb33XiYI/uc/XKsbb+TPFgulM2edxUiuVPwrLQUeeURVaPT7\nlYtJezsjyQOr3olryu7dHIuuU7Jis3H8fj+PmzaN10DIoFQK7OkBbruNG5U33yQJv+46tu/fT3Ic\nDrPPtDT22dNDYul2J45FNglSmvy9wuXi5u6nP+X9WVrK8tqjR3P9r72WG4HGRq7J6adzLL29icVa\n4pGZyY3AY4+RRFdU8DpItDoZvF4Ev/xdtD66CeHtB2AbW4r8G2fDVcSqisFOoHYNH7d7RlKvnKqY\nyftFXxvP113PKoJl8/gP5ESgp4lj6W0G8iaxDPVQKiGe6mjfC9StZVSseCZQMoPk9lhg7KWMMjds\nBIwYEwxzxr2/5DpDB1p20DpRAzDiTKBgipmwZ+LEwjCYWO0pT3zfkcW/hyaOHjTjCGpyTdMyAARA\nicfHAXgAPGYYxvtO9NM07QkACwDkAWgG8F3DMB5K9vlZs2YZG1OVxj5eWLWKxDM7OzGK195ON4Pn\nnhtcpb9sGaONErmWCLLNRi/k//s/tkmfUkzlD3+g/OCZZ9Rj+ECArhF//jPff/55EirRrl5wAQnn\n0qWJdnTiafzUU3SJkCQ4gNHWRYsYobzrLhJx0eTGYhzLN78J/Pa3JH0yTomqfvGL9AIeOHeLhU4P\nv/kNiX/8cRkZXK8vf5nRaSlYEotx7I8+mvw63H8/1yye3Ok6CeP//i8j2fFRd12nfKGkhGsqsho5\nX1oa8J3vsC0a5c+i9y0tBf7yFyY3VlWRaEoU/TOfYbT3z39mf/F9ulx0IHnrLW7EBOEwNxH3359a\nEpEMjY2Uu7S08PhQiNf+l7/k9V6/PtGuLxBgJPqXvzxc1yzw+YC77+a4xFrQbue9ICXPB0FfG7Dq\nbpLkNDcTuawO4NxvUGe86m7ahEmbzcm2rCNw8uGgqw5Y82NqXe0ZLLSS7gHO/dbg0o9jibbdwFu/\n6LdTc3IsmSWshOjIPPLxpyr2vwpsf4z3iMUGhHqYyDn7s0Mr0X2iYRisdLj/1f6NkAFE+hjNnnLd\niR6diQ873vgeczriK7f2tQOZxazQauK9QdO0TYZhHFbCeCia5+8YhqEbhhE1DOOvhmE8AOCuozEo\nwzCuMwyj2DAMu2EYpamI80mF+fMZyevoICmJRPi9280CF8k2JHa7eqQvJMswSNSEjAEkl0Jao1FG\ndJ99lgS1oIBRU3FBeOYZRorLy5lgWFhIwvjGGyTckryWnq4s1FpbKV945RX2U1DAV0kJ3UIkch7v\nfSS2ZhKtlQp8Dge/b25Wke6B0HXOTVxCbDY1v3CY56yq4mYkK4uRUY+HpHpbipT4j3+cke3GRvbT\n20tyfN55JJZ5eaooiUhYzj+fchddTyyFHg6r5Lm+PuXikZ6uqiVu28YIekUF+x4xguv2yCOMvuu6\nmiPAOefkUJrhdHKckQiTHOvqqGUfDnEGuBFpbeX1y83ltXO5gB/8gBs4gNckGqUGvamJa5KMOAPc\nSEmxnNxcynHsdkaiU2yy9ywnOfaWM6LsGckl2PEPYPdzJBbxbUYM2Pnk8KZ9JOz4OwCN53Hl8rwh\nP1D1/LE5XzIYOvDuX7hh8JRRl+2tYCS6+vXjO5aTCaFuYOc/WP0us4S69ezRTHBq3XmiRzc0dNcB\nB1cC2RVMOnUXMdK372VW+jNh4kRi0tVAqJOEWY8yuBHuASZddaJHdmphKOR5MBfURUd7ICctIhE+\nyt+8WblnACR8S5eSnPj9lHS89BIJrRBjgSTdrVlDcltcTDISi5GkFBeTuDidjMRGoyrZy+kkyRW0\ntpIQSwRX2nSdZOnQIbYB1F97PDxHKMTIck4OyemKFfxMNMr+pOS0YVA6UVREQi8aY49HVTt0OFQi\npHhWp6Vx7kDis0shpy+8wHlmZyu7tqIiks8XX+TnolESc3Hf0DSuKcD3tmyhBEL01Hl5tOpbsEAl\n8n3qUySWbjcr9517rrpuN95Iwt3UxJLaUgxG0ygFmTOH1/nMMxklDgbZNmsWSeqbb5Lcd3QA27cr\n949AgHKdSy7h9RUpz1ln8b6IRoFvfYtk++23mTx6yy1HtGtLiTVrOJZ4eDx8+iHny8qiLrytjRKY\n+fNT97lpEzdmPT0k+h0dvF8OHOAck6BpM0lEPFz5rPzWuJEEKR4ZBUDzduXhnAyGAXTWAI2baE12\nJMslPcpzugZEmN0FHOPxRLAT8LckWqQBTFJsPAkenp0odNXyuidUCtSY/NcyhEqBqRAN8r469C6j\n/EcDkT4mWh3ayu8BwHew3wEy7r+nxQoYYGnsE4FQN9C0hVKSWApXyQ8b/M38+9FedeS/N6cKCqcC\n8+5ipLmvjdr+c75hJsgebSQNQ2ma9hkAnwUwWtO0+PBfJoC1x3pgJwVqa/mYWwpqaBo1rhdeSEKS\nlwdccQU/KwVUxBFkoI61t5fkpq+PxCxeTtDQQFIZn2gHKLeLnBx+ZsuWxAQ+KdFdVUWCL4l4ViuJ\nbkUFiZQ4VwAco/QpJElYicXCPnNySCrDYRWFDgaVzruvL9EZo6ODfebmcl0GuvUbBufe2ZlYMETm\n7vVyrmJhJ+N0OLjGb75J+Ya4iGRlAXfcwfmNGUMpxWDIzWUC3c03J77v8fD6LF2aOMbaWs69vp6e\nz4O1Pf88vYoFTiddQE4/nVKJtDR1bf1+zis9ndrk5cv5fk0Nye1DD9GBYjjweLju8ZCot9MJfO97\n3DxJ9cf6euCvf+WGIRkyMoC1a9U1FJ/uUaOU7GcQOLIok4gnRLEwYE8H7G4gFhpQ1S/c/7g7hT40\nGgQ2/A5o3gpu8XWW7Z716eQuC5qF54yFEz8TDankmeMFW3/dJD02oEpiCHCMOL5jOZlgc4IscwD0\n6PuTsrRXAW/fT4KraYBmBWZ8khrz4aJ5O7DhN7yfjP7S4LM/QwnOYNpmTeuf33FGzSpg6yPqT7LD\nDZz5ZUb0P6wwdGD734EDr6o/ZZ4y4Mw7EuUMpyryJ/Nl4tghVeT5bwAuA7C8/6u8ZhqGccNxGNuJ\nRSxGPW00SknEyJGMKj72GKOMDzzA30ip6ldYSE3s0qUkS4GA+msmFeJ+8AOSz9ZW1SZlr2+7LZE4\ny1/nWIyJiz4fvxephCSbnXsuk9UiEVUpEOAYFy0iaZdyyCJB6OtjwmFnJ/uRPkWSceGFg7f5fKxE\nF0/g48d56638XtcTZR6axoRAu10lEuo6SZrXq6oIAlwLOTYUIil9+GFuSsrLlXvG/fcn2vO9F5x1\nFsfb1x9KMgxVgOTyy1WBFGlraCDpl1LoTicJvDha7NhBW8B9+yidkIp/bW1cx9deo+ymsJDR59JS\nruWXvpS4CXkvuPFGXlu5Z6T64Lx5tOR79VVuoOR8DQ3UnaeCeFu73WoO9fXcEKQgz2MuYUKc3v/A\nw9BZgGTMJcC4xYz+SJseU8VJUiVX7fk3cGgLH4d7R/Jr0yZg74vJj9EsPGdPg4oy6dH+KoKXpJ76\n0YbdBYycRw22jCUWBoLdwJgLj+9YTiZkj6Jco+eQ2rOH/bx2I2YPr89okMTZ5qBMxzOSEf5NfwR6\nW498/GAI9QDv/BpIy2R/3nJuwDb8hpG8NDd1pYJAB8l/wXGpfqDQ3QBseZhPW7wj+dIsXI/YMP88\nngpo2Ajse4l5FXL9epoopTJh4mggFXk2DMOoBvA5AD1xL2iaduo7pFZXk/zk5pJoiRWYzUYJQmen\nkiBIm9VKB4rHHlPWZ34//0vccQej1H/6E/tsaiKh0XXgnntoYxeffCj/WTSNZCgvj+cQ+YVU/Fu5\nkg4amZl8ZN/eTrI7aRLdKQZWLUxL43tr1yrLNqmSKIVYXnyRZFXagkEel5fHxLj4hMb4qPX69Tyv\npilphsVCSYTXS39oSdprbOT6/fGPlErY7Ycfl57OdquVcxJkZ3P9Dxw48nWMRklq29rUe6WlwOc+\nR/JZW8vX6NGUNpSXA5/+NEn+gQPUSY8dy6TA1auVH7asmdfLcb/1Fol+OMxrIJ7LeXm8H1wuVXBE\nKiEePEjph6ylFDcZCNloSNlwgJaCn/wkz1Vfz3tpxgxuUp55huOKv5+King/tLQkX6tDhziHvj5V\nDGjiRPUUIgnKzwUmXgn4m1TFv1ELgXEfASrOAyZcxgxw30HqRUdfRPKcDIYBVL9GXWy85D6zBDj4\nWvLjAJ5z1EI1Dn8TMHEpx3i8MeU6EsKuOsoVeluB0z8OFEw9/mN5v4hFGNUdTDoTi9A1YyiVzDQL\nMPfLfKQslQJjYWDulw6X9yQdS5iEWdC2h2NzZHGzpEcZHTb0/icXw0BrJZ9YxDujpGVwrp3VwFlf\nAWxpag52Z/976Um7PCZo2qJkL4J0LzWuHfuG1kckcOpJPWreYIQ5/qlPZjHQvI0SFxMm3i9SmQP9\nDcASAJvAB23xcSIDwKn9UCgaJWnZupWPvXWdxKmwkCQmGiUZqa1lW14e9bvhMLWs995LqUEoxAiw\nRGVPP53JfJs3s23mTJLEFStIdiSpEFCuDaEQiZeQZ0DZ3wmh6ugggQKoLS4q4mcLC0myRJ5RXEyy\nFQqxv8JCEj1AbQakz1hMkSaJCIdCSt4hftSifw4GqfEtLqaMxGql7ZvXy/WaNYvev6tWcexLljDa\nGwgkOlQASisdCCQSZ4GmDU404/Hgg9Q9i4Z67FhKJ8aO5VhOP51rlp7O9RKmJkmZzc1sKy9X/tHx\nsharlfOQgjKGwacKXV0cf0YG10KSSqurlcY6J0dF13ftYknt+nqe75JLmExos3G899xDYutwcAP2\nne/wc1dcQTK8dy8jxddfz6+SCDkQhpG6zHYkwqI3kydzY5GeznPW1aWMkGsWYPLVLJ3d1wqkZ6tH\no4bBSJ3Nyei0Mw/IGsnH6qkQixzuvKBZj/xP3moHpt0ETLyC0UBX/olztrA7WdGwr42RTHchI9If\nJESDrFRW/QagR2jxdvrHmfwYCQC7ngGq3yRhzR0HnH4DI32pkJEPnPcdbmxiYW6SrMkfbPwXoR4m\nmta/xduxYArHokfZT+MmoKee/5wyChh9Hm70VY8Orioy+tuyRwELf8qnHNCArBGJGujjBT2MpPIn\n/Qh/Hrvq6BrSXsXftfL5wORred9+0BELD/I3RuNSHWldTJgYCpL+uhuGsaT/6yjDMEb3f5XXqU2c\nARKmfftITOQxdlcXSe/cuXx/3z7V5vOxbfRoJqytXUtJxSWXMMr8s58pyYLFQvI2b56yibvpJuUA\nIQmHYpN29dUkSVLiWmQhzc10j1i1Svn5ZmXxs6tWqYp00SijrWVl/ZkumpJt9PRwDm43v+/qoozi\n0CGSRSHpgQDncf31HK+uq8f5QnhvvJGOFB0dLB09ZgyJ1+7dJJE/+xmjrUJc162j/OWss1QpcJGC\niHTixhu5JvHlofv6eN4U9mlYtQr4whe4ZuIysncvkwsFaWnU80p5aoDk92c/Y0R3yhTql1esoF54\n8WIl9ZAkye5uRv1lUxQIKE11ZSU3WOefr5w2xJ2ksZH9eDys+CgFXXJyWHnwmWd4D33lK6qceGYm\n8Pe/Uy994AA3aBLZr6ig//Ty5ZTd+HyJhLe9nXONt68biHnzOP+0NG6knE7eY1OmHO6ZPQgcmdRZ\nxmsKm7YAG35L0lgwBUjPArY8BNStSd6PplGr2tOU+L6/CSg7+4jDAMDoW/bok8MSzpVHsvVBI84A\nJQH7XyEZ9ZTzCcLanzGTf8tD1JS6C0mYuxuANT9NlDMkgzxJ8FYMjTgbBvDO/wG1awF3CfWr7XuB\nNT9jRLF9N9BVQ5mFIwvoa2GUMWfM8OadO14VVBHE+mMFuf1pGxYr5+0pOzHEGeBTDD2qqiYC3NRY\nbKnnHuzkdeyu4xzcRcCB14BNDw7tCcLJjrKzgUB74lwC7byH0z8EmmcTxx5H/JXXNG1ev9czNE27\nQdO0+zRNO0Js4RSAz8dIc7zkIRplRLKmhl/t9sQ2KRSyaxd10DYb/9oWFfEzmzYlP59YgwEkWRL5\nzs7mSzyc45MKXS4SLJstsbKfEN79+0l2Gxs55tpafr9sGc9XUcFz+f0kb5EI39u6lVFVi0UReLHP\ny8qi7CMQIKnr7WX0VKLIBQX8iyWP/a1WRrdXrSJZLy5WfZWVcQOyffvgUhCbjdfhkkuUvKKmhkTw\n1ltT27x997uqeI2cT8jg008nP27tWq5DXp6qAFleTqJ/8cXcODU0cB3r67nBuPtuXluHQ1U7jER4\nvu5u9pGbyzXr6eF622yM8r78MseWna2qSpaXU7P829/ycx6PkrEUFVE29OyzPJ/Ho6o4lpWR6N9+\nO/tuaOCGp76eY/jxj5NXFwRIukePZoS8vp5rnZFx5AqDKVC1nJZx8vjb7iLZ2p3ECl0w6SpGKDur\nae7fWc1/8BOvGPZQTLxH9LYCDe8ogqtpvCbRELD3BbqGeCr6K/dJWxCof/voj6XzIMmyp4ykVbMA\nmUVA0MfId0Yh3wt182UYfK+vfXjny8in7KaniY4vXbWMMk/56OHOMicSOWOBcZcq+UhnDZ90zPhU\n6s1a/TtAuJebIk3jNfSW06nEf+j4jf9YoWweNxb//fvRn+M9/RazkI2Jo4Oh1HT6HYAzNE07A8BX\nAPwJwKMAzjuWAzvh8PlIoHJzKUEIhUgscnMZTZW2HTtIlMaMIQGqrlaSg3iIF7JhMDq7ejX7nDuX\nr85ORkV37SJ5NQyeb/p0kkavV0kJDIPnj8UYyXU6+WprU22BAMd5ww3UIUufZ5yhbNcmTeJ7e/dy\njOPHU+N64ABJXFqairRmZHC8NTU89s9/ppbXaiVZ+9jHgH//mxsATWO02WplRLaggHMA+LW+nm2S\n/HfgAPuPxVQBGbHJO3iQBVQAEkqXi+R/5ky+FwqR2G7YwLYFCyg7qKtjPyKxEWIK8Hpec83g172h\ngeddvpxjdTioJS4oUEVG7rqL18/r5dgWLSLRzcvjpqGri6S3tJREuqaGxHv3bkVI587lfXLgAO+N\nvXt5bV0uRoh1nXN3DfgPmJbGNnnqMbBNnlw89xznsGkTSfU115B4p0JGBmUuUmq7oID338AxvAf4\nDzHyGg97BqOEMIDeNuqbfQdJ0irOJzlxZgMLvkeLsJ5GPtovOkNpO/2HgIOvs5/sMUDFguNfBOVk\nRMc+rkugAyiaBow8Z/gVDYOd/UR1wJ8ym5PXSxukzeoA/I3DO18qBHyHm/gAJH3ddSTK+ZP7ExF1\n2hMGu4dPngFgzEXs89C7/LnojGNT2GcoiOgGNvnD2OSPIM2i4azMNJzmskHTNJz2MWDEXKBlJ38/\niqYdWT/ubzzctUbTuAEJ+hjNH9Y4+4C6tyihSffy9zJvwvD6EoT9QM1qPklw5fJvhETVQz1A7Wo6\no2Tksy17FOd21p3Urnfs43FF00+OJ1EmTg0MhTxHDcMwNE27AsCvDcN4SNO0Tx7rgZ1wFBWRgInW\nND2dRKemhnrUN96gPELcKPbvJ2m54gpax+l6YpQvFCIpevZZJgBmZpJAbt1K4nfVVUy4a2xkm6bx\ne7+ftmNP9leVkGhrVxeJ78yZLM8sEU6A4zIM4LT+1O8RI/iKR0EByWhXlypYsnMnyePtt7PNMFSf\n4h4yfTrnedttfMWjpITr0tXFNYlG6UdcUkLy9tRTJJPp6eyroYEbkJkzOXdAjUVcSGbNorRj+3al\nnX7oIZ5j0SKS2cpK1bZ+PYn85Mm8JvH/baX4yfnnJ7/ukhQZDnOefj+jw2PG8OdlyzjurCwS8+9/\nn2MZP55rJnMIh1W58mnTgF//mmMpLibB3biRfc6bxzLrEln2+UiaJ0zgWr/6Ku8HgWjAZ89mkmI8\nge7rUzIiGeuyZcnnOhjsdp53+vT3dlwS5IwFfAcS/5kHOwHvKJLiVXfz0bgjk5HF6jdYBcszkslX\npXMP77OzGlj9ExZbSXOr4+Z/i1KADyvq3gI2/oGaVasDaKsksTj3m8OTjLgL+w1zoomlsyO9LHHd\nVXO4FV80AGSPff9zGYjMYpJiQ0+USMQijDC2VnJTltt/bsMg4faUDd7fUJE1gq8TiZhh4E/Nvdja\nG4HXZkHMADb5I/hItgOX5TqhaZQovRdrupyxwME3Et/TYwAMPuEZDqJBYO093File/m0oP4tYNot\nTBweDsJ+YPXdQHcT4PTyb0ntGlajzJsErP4R3XzSvYBvP2375nwBKJnJ+7JwKl8mTBxtDEWp1aNp\n2jcA3ADgBU3TLACGoFL7gMNuJxmLrwYIkBSJREJKa4s8IxxmdPiCC0iAurtJaKqrKYcoLaVP8MiR\n/FxODgn1u+9SL93ayvNK1NfhUMU/XC6SNSlkIvKMs84i6YpEVJu4f4xN8V9s2zaOz2ZTMg+bjUQw\nNzdxjqLFdjppVZcMDQ0cr8Oh5pCWxoi4WOYBqiy2JMyNjfuPJxDHDbGCGzWK61VQwPX7179IzCsr\nE9vKyqgXnjpV9RMvBbFaD/eajseqVcrf2mZTLiq1tYy2NzTwHF6vSiz83e/UOTQt8cmDrvP6iF2h\nzF1cN+Q+G9im63T/cDgovQgGSaxbW1kIZskStjU0sK29nZ9btix1FcHjjElX8TG//xD/ufa28LH6\n5GuBXf8E0O+/mu7tJzoaUJlCVQMwacxiZRRQjtMjwO5/HY8ZnZyIhYFtj5P4uIsYufeOYlJY3VvD\n69ORRavBzmpueCIBPv7OKKCjydhL+9u6GHHsrOG5h2s5lwqZJYyi+w7y/gn3Ar5qRiBHLaRG3neA\nkchwL9BVTW3y8baOOxaoCkSxvS+KCocV2TYL8uwWjHRY8HJnCO2R4VldFs8Eskp4zSJ9vIad1XTC\ncQ7TS6t+Pa9P9ijef+4iwF0MbP9bojvKe0HNakpnsiv4u55ZzPtv66PAgZUsROSVthImCG971EwK\nNHHsMZT/sh8FcD2ATxqGcahf7/zzYzuskwD19SRlo0YpH+Xx4xkF3LiRkorCQkaNIxFGCsvLGZ3+\n+MdJ8FauJDm8/HI+tt+7t79ygs6osq6T9Nnt9ALOyiIhipdm6Dp1uOecwzFVVvK9yZNJyHfsYGJi\ndbVqk2S9hgZ+rr6eEUxdBy66iGNbs4bndbmUg4fbTbK6ahVw6aXsr7qabVOmUNJRX6/kFgOxYQMj\nrRYLCbPFQoIZifB8p5/OSO6+fSSKU6dyDO+8Q0La06OcMfLzVXVFhyMxgiyblXXr+Jn4Nruda1dZ\nyXm2tKhKgVL2e/NmJv8NhnXruCZ2u3IWkeI2L75IaUNPD182G69fJMKId0WFaktL42ZJ19l2zjl8\nklFfz/6lRLhcv+ZmvtxuRqrDYW5inniCkektW/g05JvfBK69luP69rc5pp07+WThttvUpuEkQfZo\n4LxvA1UvkNzkjgfGL2Hk6+37+M81Hhn5/dUHjcG1iYbOKKNnwC2YUcDHuicC0SCw9yVuEAqnAqVn\np5aWDwXhPmDfi5QdFE0DSman7tPfzKjvQOlKuofSl9FH8JaOBoHWXf2R49Eq+jjpShKW/a/S/mzc\npfTMTssAJl9DOc2BVxkhHLeYjisS5Y4EeK1iYV7v9yurmXYzkwV3Pc0+x1zK8dnSgOmfpBNI9euM\nRk+6mnO2DOE/XKgbaNvd/yd3QmJVyO6ojr3BKAwA49NtyLId28xAX1THvkAUVg0Y77TBbbVgfyAG\nuwZocb8QVk2DBgP14Rhy7RbsDUTxVncIDouGizzpyE1LPU67Ezjn67yu9eu4UZp89dATcgdDy/bD\nZRG2dG5sexqHV7SleevhVTrtLuq669cd3paWQe13X3tqbbphKB27I4vV94Zyr6SCYTDa3tPEzUPu\nhMMdg0ycOjji7WIYxiEA98X9XAvgkWM5qJMCGRmJRVAEtbUkMStWUE8qjgZtbSSaV11FYrhgQaKz\ng/Tp8zHqKzZrmkaCuWABo7NNTSpKWlfHY4qKSJC6u/nYH+Dj+44OEuzaWuppAf6H3beP/WZlAY88\nwkQxOd899wBf+xrPabGQyMVrWgMBtgWDdPmIR03N4TrbeBQUMHLdF2cIW1PDDUdBAeUszc08r2Hw\n7LmRSAAAIABJREFU59JSRp5tNhL0eNTXkxRWVR1+Ll1nn/sGmJlKBLioSLmbiFNEMEiynZ/iv3hh\nITdLGRmqSqSu89oUF1PrHO+3XFNDAj1iBKO/8VFtXef1lLLmPh/nGQ6TNFdUsM+uLhJmQSzGjY9c\n+z/9afCxFhWxzPdJDm8FLdsGIj2HZC0t7paKBvmPJ2lSj9Zf0TCYaKkVCRz+j/R4oH0v8K+b4opx\nGCS6Sx8evudv8w7guU8w2ivV+MrPAz7yOxLFwSBrOFDWEA1S75kKXbXAW/f2+9/2n2/cR0iONQsJ\n1WCkSrOwEMzIeYe3dewD1v2SEg+A13PSNSTYw03YatvDBFRDByx2EuXMEmD0BUxoHL2Qr/eCps3A\nxt8BsSgAg2Rn+ic5383+MP7a0oeYQadWqwbcmO/CzMwkF+F9Yk1XCP9oC/RfAgNpmoZbC13w2DTE\nBkmuNaAhw6Lhlw3deLw1CLl4DzT68YORWbgwO/UNKIR58tUpPzZkOPP4lClhjP1/jtNS/NtIBVeu\nkoH8t8/+f7nuQv7+waPa9BgALbXOX48Cmx8i+RabP3chcPZXD8/PGCpiYWDj73k/SZ+eMnp/p3tS\nHmriA4qk21NN09b0f+3RNK077tWjadqpbzNeVkZS19CgiKC4R5x3HqOXhkFi5nQyUika6WQYMYJk\nKxxmNNPrJZmqqWEksqtLWcCJt3F3NzXB1dUkwB6Pcl+oqWEEfMcO/pyZyZfNRjLt89EJIiuLJLW0\nlJHhn/+czgoOB/sXaUZ3N+fyjW/wHJKAaBgkvTk5qctJT5yoZCYi2dB1zmvePM7BalUR4HCYxP+m\nm7h+XV3sR9d5vuJikkO7nQmVgKr4V17OiL5ITaRNKgVOn86xWCxKRhKL8b3TUjzL/cIX+gWTATWW\nzk5uoM4+m5Fz6VM8ufv6WHQlGiXJluOamjiOyZM5T5dLzd3nY1+LF/NckpgpRWTOPjtR63wKYnx/\n9UHx4o1FGLUZm+ShAEDiNe4jTHiSR7OxMOUg4z5y7Mc8EK9+DejrUNpYdwnQsB7Y8Pvh9afrwMt3\nkHRmjaA0xV1Corjt8eTHObP5KD6+omG4l2tasSD5cYbOqnmGTrcFbwV9uaueB9p2DW8OsQiw/v9Y\nztpbwZe7BKh8ipG54SAS6K/45+7vs5yEZ9ujjGoOB6FuEuf0bDV3Vz6J1aFmHX9p6UO2zYIyhw1l\nDitybBY80tKHzugwq4KmwKFwDH9vCyDfbkGZw4oyhw1uq4Y/tgQw3mmDw6L997yGYeBQOIaiNAva\nIjE81hpAnk1DcZoVxWlWODTge3Xd6D4G40yF8nOYhxD282dD5/1YOHXoBXAGouIClrSPSDFYnZu9\n0jOB8Zfx/fi27lpufFKR9dq11E17yvuvezkTbLe+j5DggZVAw4bEPrsbgB1/H36fJk5upPJ5Pqf/\na6ZhGFlxr0zDMLKO3xBPEDSNhEiIT20t37vjDibFifVZNEoSKITq+edVH36/KnMNUNIxcSIjpm1t\nSuM8ZQrw0ktKqiBVBO12vvfaayStubk8rq2NnzvtNJ7P41Hyi1CIhN7jYbnwWIxt0Shf6el8b8sW\nehdnZpLI+Xz8/i9/ITH96ldJtOvqOPfiYr4njhW6rqzvBBs3Kgs/GYvTyfmuWKH8gjs7SXjz8ykx\nMQyWQk9L4/mEHP/5zzz2K18hSa6qYlR4/Hjgi19k25138lrs3avW9/OfZyJmQYFy3AiHOb/cXEoz\nkmHxYmVz19HBsUqi544d7BNQfUoZ64wMJnZGIlyTpiZuen79a25yZszg+ouF37hxXF+vl9UL+/o4\nh+pqbjTi7eFiMY4leLhwUI/xD/9wNYUnEuXzgdOuZWGVrjoS4ElXMpKYCqMvBCYsJfHuquMj3NOW\nURM7FMTCfKz7XnWR0VDicf4WoHVnIjGwWACHB6h67r31LfDtJ8F0xkXALBaSgd3/TH3stJuBEXNo\nzSWV++Z8jqQwGbrrGTWPj05brHw0Xpfi1yQVOg9S4hEfcbPa+Vi8ccPw+uzYy3s8nhRZ0wBoyg3j\nvaJtNyPO8cmUtnQSwHe3xBAzAKdFQ0g3ENINpFs0RAHsCRx9QW1lXwSAAYdFheUzrBaEdAMtER2f\nL86AQwN290WwNxhFucOGzxS58aovBCs02OOOc9ssCOnAmm6GgQ3DQGdUhz92bMl0VikrRUajBhqa\ndbQ0GSieDsy87cjHJkPOGGDWZ7gRbNkJdOwHSs8CTv8fFuWZ9WmS565a3ssjz2XhnFSoXc37Pf4J\niLuYcrFQz/DGWbOqP8E2xs10NMinIg3rT73qjSaII8o2NE17AMAThmEM80/pBxheL8lZRweJYEEB\nidqbb7I9HFZ64VhMVcnr7mZ1wY0b2VZeDnziEyqZr6GBEWrDYKQyJ4fESkpuS5TV7VYFQ6JRHidO\nGoEAj9N1jmnECJWQZ7cry7VYjIRUIqIul4o0z5rFUtSrVrHtvPP4HsDI+w9+wPOJBln+2rz7LvD/\n/h+TIgES+3vv5bnsdo7L3x9+8Hg43liMJPO00zgWi4XEWqrXjRtHP+d332Uf8+cropqWpsYNkKhK\nUlxaGgm5rJ+UwZZEPatVnU8qKKaolgeAZP3220my8/OVpEIcVDRNiXLFHSQWoy3gNddQb52bq7Th\nuk6JxcSJqsBLfOW+9HRVbCZ+DgCfcDz2GO8JqxVYuJByGrsdjRsZjQx10TZszIXAxKuGVnTiZIBm\nASZcziSloI+PZofiCmGx8lHzuEWUNqRnD60qmqEDVf+m/lqP0J1h8rUs3Z1KSqDH6Eu9fwWJc1om\n/X6TaTg1S2LRivcCQ8fgFeM0FVFOhrQMYPZngOB1JBQZBUfWcSb12h7C+YbTp57C23s4fWp4n+NM\n0q+hA0Fdx/qe2H+T8nLsFmTbtGSHvC8kWxetf4gdER1b/BHUhnljRXQDV+emQ8fgU5Cp1YaieLw1\ngIZQDBqAaRl2LMt3ItN6bLTbPeOj2PDlPjT6ddisQDQ3Dae7nEhaBnEI6Kqjd3jA17+RzKQHt90J\nlJ0FlMziBjzNTSnKkZD0dwxIej8cCbEo0LyFkis9yr8BueNJ/k+FojMmDsdQfoM2Afi2pmn7NU37\nhaZps471oE465OQw8iqE5qqrGAUMBPie1ao8ihcsoLXa5s0koCNHMlJ8zz0kb2vXkjhnZpJM9vby\nvfPPJ+nu6lJ622CQxP0jH6HWtrWVx3g8/OyaNSScVqsqty1ev5pGOURnJz8rlnp+P88xdy7lG9XV\nLHoyZw7J8C9+oYqwaBo1wBLBBTieW26hHrm4mK+9e3muuXMZwQ4G1RxkTsuWkShGo9wUuFxcL7ud\n57jnHvY9fToJ9rZtXEefj20+H6PUY8dSa/7rX1NjfM897H/iRMo1Nmyg5/L8+VyvSESdr62N5PXs\nIWTFuN1MrozXIk+dqjY9UmGwo0NJawAS4RkzEpMqzz6b10H8q9PTOfaSEo7n/vv5X2HiRN4zr7zC\nSoL793MNLBbeR4WFTBB86im0V7HimlQ5yygA9vz7yNHJkxF2J6M079VOze76/+y9d5gc1Zk1fm5V\ndVfnyXk0QVkCSYCEQIiMwRgwwQYbgxPrxTiu7cWfw/f7/C378wZ72fXa64CNF2ccWQPGIMAYDEJk\nEAjlNNJocuzp6Vjpfn+cLlXPaKZnNJoxIrzP089M9+2qulXdfevc9573nPx207QT3vsQsO13zDqV\nNHH7zf89deZy9x+BnXdzSb+kiRqyL3yfWejyxUBmwHuv43AisOiyozsXN8oXka6RGRq7T2OUhZbT\nCVd5YDoFULFGUj6yce816ZA2MpFM4HTCdVMszOI5NjNw9afMbJ8Vi5hpdpfoAdJDpAPUrJzZPivz\nBV2FqzZ2XhRn2UoFuzIWBk0bMVUgpgoMmTZ2pS00+We/CmxZyAcJwCxAWhlbQhNAWJH4bFscg5aD\nBp+Cep+CnRkbn9gfx3klPjiQsArQd9p24BPAiSEf/qsrhbjpoNGvoN6v4OWUgTt60pBzgOh6DRvf\n6U4iB4n5pSoaIgqeShi4sy814322bwL+/GX+X+o6If4JePjvvfeoPn7fpwOcAa5QpQfGgtpUL4sG\np7uP8aEoVBtRVBZNajoLmFP9R+ppvxVvjJgSPEspfyqlvATAqQB2Afi6EGLPnPfseI79+wliC7PC\nLv+5s5Ogp7HRy1JWVhIk/eY3zCwGAh6tQVX5fNMmZnAdx1OdMAxSBnbs8HjQ2Sy3c/fT1sZM6dAQ\nAe2hQwSNN95IwLVkiZcNHx0lyF+4kIC3v9+zpnY1iPv6mDmdLO6+m/tyCw4VhaCur48ThtZW9ttV\nnXCVQWIxqkR0drLPBw4QEN90E/nZqZTn6qcovH7795OWkskwk1vYtmcP21xVCrdt3jxer0yG78vl\nvHNXFFJHXI700UZnJ0Gz43C/riFJIEBqxmSxZg0VNdrbed6ukc5HP0pKjt/v8Zs1jZ/b44/TdCYQ\n8Io03bZHH0XbH9PQQt4ytuojsNv3yOuTwjHXIR264sUa8sv9IOgOlPH1ycI2gb0bWPzjZvR9Id5k\n9z4AvO3rfJ7o4GO0k7rDaz8xs34qCnDhrYCqjd1nw1rg5Btmts+ix1OBNZ/geQ4fYHHWSDupMdUn\nTrn5hKH6uU8jyf3FD9DIZPFlnBzMJHwhYM1NzD4OH+BjtJMrByVNU209cQRK6TiX6mcf4wdoAb/i\nA0CyzEGdjy4wCUci4bBosN6vYmAOuMQNuoqrKoLoMRy05yy0Z20MWw4+VB3Cn+I5ZByJMp8CoQgo\nikCNX0GX4cCWwJXlQfRZDroMG12GjVEH+FJDGPuzFrKORLlPgRACihBo8KvYm7XQYcxwaaRIPD3K\npEtJXpFEFQKNuoKXU9aMJfU23+EBUoATwmgdcPBxIDFDrnvTmdSBdj/z+AF+v0760Mz2B9AUxh8l\nbcPKMvusR0lhst6ibbwh42jEWRYCWAqgGcAMS0neINHTw2x0NEpuq2ujHY0SYLl0i8Lw+TzHutJS\nAld3O8si6J0/n8v7r7xCkLt0KWkDHR0EUdXVBJlSMqvb38/j/8M/MHP94IPc7sILmb198knuY80a\nqlJISeCcTBLsThaJIvWgxQoiOzqYOT79dE4gFIX8ZBdIX3ops7I7d3rqGmVlNE8B2MfOTm7X2srX\nOjt5Lffu5f41bWybohBId3byGre28rXOTmpgHzrEbXWd2WHXbr2+iJvG6Cjw2GPMcMdiLK5cuZLX\nurmZE55C2233c1iwYOL9qSonMxdcwIlDLMZzD4X4OYx38HNXOFxZu8LIU4OynSkIEULfVt78/WE6\n7Umb/EAjSRmqge1AuBZY+HbKhU0VqT5g38PA4C7KkC24aGYSU8db2CavS3Cc8oQvxHOeLKwss5Eu\n4D68XZic55oTgQ8+Cuz6A4sYq1fQme5YZK8aTs3v814uR9etpnPaVPJ3UpKDve8RIDtER7XW86eu\n9i9fAFz4daBvK69R+QIWPh2LjXH1cuCiW7lPMwtULub36Vj2WXOyRNVXDDz5gg3TAk5ZqaBpsY5j\noQRUrXPQU5rGphdt2I7EulM0XLg8hFfSEtV+BctDPgyYBJqVPhUDpo1R24HpSDyXNA4DxnVRP06L\n+qEJAcOReG7UwNNJAyqAM6J+nBr1Q53i5M+K6Ri1HTwynINfSFxWEcDKsA/3DmYBCQybNpIOzzam\nCgjpYMAGvtIUw2XlATydyEIXCi4qC2BeQMNdA2n4xh1SCAEBIGlLdGRtfPXQCJ4ZNRFQBd5VpuPz\nDRGo6swy6/2mA33cOSpCQBHAqO2gwjf5FzhhOXgiYWBLykCZpuC8Eh1LQz6MdtHRcsw+NQACSPVw\nArz/EcrkhSooo1i5tHg/VT9w2t9RqSNxiJOo6hM9dZz0gDd2Ruo4Bk41dmaHOImTDscLRQO0EPto\nJAFthtrZxSLRCex7iAC9tJX9fK0cMN+MMR3O878BuArAPgC/BvBVKWW8+FZv8Fi5koApk/E0hxMJ\nPm66iZlP2/ZAkGsGcuGFzD7H4575xuAgwfMZZwB33sl9lOW1ulz1jptvZkGhq1QBeLxl1wlu0SI+\nCqOhgceuqGBW1+1LMkkKwubNYwV1XWWNxiK/wFWr8rZjjnc3dznEp59ON77qamaj3bZEwnM4dKke\nhdHc7E0YXG7zs89ygnL11bxmjsMJQyZDLnJlJbm/v/udZyKTTtN1r7oauPJKOgUC7Ittk09dW1sc\nOKfTwNe+5rkfDg6Sz33ddXT1e+UVXh/3c8hm+R1YvnzyfQK8xgsWHAmwly+nlXZJAcLJZJjhXrOG\n1zNWsJaYSgHRKEKLy7DlvwDFzxtIqo8ZlJpVzHps/CdqBQfLCGC6nucNo67IsnmyB3jiqyyMC5SS\nztD5LHD6zQSJr+dQ/byxZOO8Jm5kBsmZnCz8YdI1comxS7rpQXKlASAQA1a9f3b7Gyo/+kzzgb8A\nL/+YGTAtQEDf8TRw9lemtiX2R6hgMJuhx45NN3h83DWQwaNGDmWnKFAA3Gs52NVj4ZN1YWgzQOWO\n4+Az+0fwnGEidhJB6R12Ds/vz+ErjVGysxSgKcDbpJQSEECtT8FP+lJ4MWmiPJ9l/UVfBrvTFj5Y\nHcSP+tJ4Jd8mAfy0L4PdWQsfqAqN0WouDFtK3N6TwvY0t3MA/G4gi35TYkVIw8/7HGhCwJWZ7jYk\nhABWhNi3kyN+nBwZO8Nr1TU8Ko0jjiPBG/+lOwYwbDkICCDlAN/pSePVjI1fLJkZ0lsS1PByykTh\n/NRwJBQA1b7JAfmo7eAbnUkMWDbKNAXxrI0tqSSurwqh/lQdW389dgJoZvh7DldzvMrGaewyMMAM\n8JqbgHkTyCcWhlBI2xlvHZ7qBx7//0kPCpaxiLDzORZC1hUxXa1eQdpGtBZAXiYvO0Jt87mQ0Iwf\noDsrBMefQ8+wwPes/03a1Fsx9zEdzvM+AOuklBdLKX/ypgfOxcLltF58MZfmXT5sWxszsGecQdBl\nmgTMts3/AwECSLcQbfw+ly3jsn9Hh6dU0dHB7PLFF0/en5YWAtr9+73t9u8nKDvvPPKc3bZ4nP08\n7TQvsztRXHwxs6adndyf25f160nLWLGC+xkZ8aymzz23OGB1oxgPr/Cm49JMJnrP+PdNto/J4tln\neW4tLfwsKysJlv/nf4D3vpfPOzqYnR4c5CTqQx8i0J9JnHsut21v56Smv58TpmuvpbFOSYnX1tfH\nx/veB6ga8vfy/Lnh8JN9DxM4l8wjKIrUMOP66i+LF1fteYBLjLHG/Ha1gF4KbP3l67/oRQgWGRmj\nlMMzkszcCLU4l1gowIrryUFO5rNII4cAX4AFi8dLWDlg22/I/QxXESyXNhMMtD/5Wvfu2KPPtPFE\nwkCzrqJUUxDTFDTrKnZlzBmrXzyfMvHCqIEGn0BMUxDVFDT4FLyatnEw52BNxI+DOQcjFh8HczZO\nCpO7szllokVXUaIpKNEUNOsKXkiZeDJh4NWkhWZdRSzf1qQreHbURKcx+Y9vd8bCjrR5eLvS/Plt\nTOQQ0wQCKjPajgRsSVBaoipFs7krwj7MD6g4mGO2fNhy0J6zcWGpjl/3pzBsOijTFARVBWFVQYkK\nbEwY2JaaGc9gTcSPWp+C9pyNpO1g0HTQadh4Z3kAIXXysfeZhIEBy8nL8/Gc6vwq7hnK4sS/lQiU\n8LdqJIHUAFdj1nyM0nCZODO+/gjBdKQWePXXnvzl0ca+h6g9f8TYeWfxsfP0zzHb7I4tqT7+PeOL\nx26YNFFsv4s0slg9+xmr54RiKnfWt2L2Qr3llluKvuGWW2558ZZbbkkXfdNfKW6//fZbPvrRY9C9\nma14/HFmOEtKPBpFZSVBUCRCE5J58wiuVJXyZ9deS15sZ6dnJqKqBMarVnG/ts3t0mm2LVnCrGlD\nAyXy+voI7kZHgXe8A/j+971l/cFBqnu0tTFr6VJHTj6Zx+vv5+tXXsmCR01jW2Ul28Jhtl11lZcx\n7+vjPtvb2R4KcSR45zvzFRIdfP0jH6FMm99PakR5Obd1ec6XXFJ8BHnqKYLDqipez2CQAL20lJMM\nn8/TtbYsZv6rqryJRzDoqYKsWsXj53Lsr9/P81NVtpWU8G9FBc/rpZcIVktLSe144AF+NqZJKkYq\nxXNMJukSeN11/Hxc85Obb6ZdtjvxaWvzrNbLyjxpv8kiEOAkxufjZGvePILx1at5XmvXsu/Dw5xg\nfehDwEknYec9QLgGUPW8sUgpl/chyQv1h8dSDTSd4K/l3MnNO7b8AtAjYykHqk7e7cK3E0gO7GQh\nTHaEy6Rz6aDlWMyau3SCUMVYA5CjjXAVULuKWSUrw0zSKR8hh7JYRGqYWTKS3K7hNHJlZ6pdOxcx\n2g20Pcpsb7KbS88Ab7COOXUG2EjS4GFgN7/KesmxUSxmO/ZmbWxOGijRvC+cEAJpR6JcVbE4dPQ8\nmUfiOTyXNMa4BgohkLQc1PsV/G1dBBU+BYOWg6AqcGl5AJeWBbEza2Fr2kTpuL6M2JRx6LcclI7b\nZ8KWmB/Q0KBP/IN5MWliX9ZGxpHYkTLRk7MR1hQYkgIQYUVBWBVIOhK6EDg54sOCgIbFIR9qJylg\nVIXASWE/IorAgCVRpgm8qzyIc0t03NqZxIDljJHGUwRl+ebrGk6O+NBpOHg5ZaDPdBDTxJj3ThQ+\nReDksIakI7ErYyGoAtdXhbA+pk+acQeADcNZ5CSlAN3QhMCw7eCMej9OvlRBdgRI91KD/KwvA6s+\nAOz4HwBybEGe6uOq0FRaz9IBBndzdS0zxMy1ogGv/orjY6Fi0eGx87zJx85oLaU30wMcfyuXAOd9\nFVj09qKXbMbx0h2cKIwx1w3SxXXJ5cfXb3emYWX5+fTv4L2gqHnWHMY//uM/dt9yyy23j3/9GA0p\n36RRW0twZhieC52bTW5oINBzFSwKIxrlp3/KKXy4cfAggdiOHQRP8+Z5bQcOEAx+9avAbbd5FIlf\n/YrH//GPSWP44Q+9NiGoE/y2txEkn302H+PD55vYCREg5/fnP/f2qapU2Vi/nsD85pv5GB+6Tm7v\nBUdh9VVRQeA5ntbgXpdf/tIzqxECeOQRguuzz+b/w8N83TSpxdzYSKD75z+PbXv1VQLQaJTX7+GH\nvWMFg5QlrKriPkZGvONpGjPRsRjb/+VfjjwH2+ZnsXGj9wuPRnmNWlqKn39ZGSko4x0dAX7211zD\nR0GEq5lVrD4BQN7zxTY9fdH4gbEuW7ZJV7bx/MEx+6xihqfwBmEb3MaxgWdvJXh2I1ILrP8Cbzyz\nHbkE8PR/AHG3DlNQr3jd309NQSgWpS1c1j3aKF8AlM+wCPCvEXqUWfV9WwiWWd5GCkcxWgpA7dyn\n/4OrFch/5VvPB1a+/9gmK7MZEVXAmYDbbEmgfDyxd5oxadZWCFT7NWhCYH1Mx/rYWLkEyrxNrCdY\n5VMgMhPtVCJaJPtaqgq8ksrhkCEh8qs8L6UtLA6oODPmx25hY11Mx7qCbdpzdtF9AkBIFXhbWeAI\nt8EGv4pX02Mz9tJxIAE0+lX8fjCDR0eMw2NgQAh8rC6MRcHJIYMjJe4fzuHZUROqAEZtid8OZFHp\nU9EamHy7ap+CvVkLpeP2BQlEVYFYM/D2fz9yu3ANV4EK6VSuRGQx4GwbwPO3cbLoDtXBCmD9/+IY\nOLRvrPKPbXDsnErVp+ZE4LLbir9ntiJUyYRC4VhopqkP/0YAzqPdwFO3eqpDUrLIc83Hjx8p1uNk\naHydxUkneTzmQie9TKa4DNr8+QRSHR18v5Re1vfyywnsCtvc7G04TMmyUIhAs6KCwOyuu6h+cccd\nzC63tHiWz3feSZe+mURfH4Fzba23z6oqmpbE54C1s2aNJyXn8qndAsrSUoJoXee1cFUptm8nSO7q\nIrh1HRtzOV7TBQvY5vd7RibZLM+tv5/FlfPmeecXCADf/S6BbFeXV9gZizHTPDRUnJqxeTNXJJqb\nvX0KAfzgB1PrSs8gFlwEWGnPzcs2Wfyy4G3AknfydSM1ru2i4rJJiy4FcnFPDsw2mHVefCmzmv07\n8g5aLXykB+bOQWvnPbwxuscqbeaEYNd9U2z4Jg09RvBsjPL/YCmgBpiFLmY57NjAC9/jKkVZC/mS\nJU35Iqytf7XuTxmtuoomXUW3YcORElJKDJgOIqrAivDM7qYXxHRUaCr6DQfSkZCOxKDpIKYKXFzE\n2nppUEOFJtBn2JD5vvQaNqo0BReXBVCiCfSb49p8alHgaUuJgzkJPyQiqkBEFRBSYnfWxpqwirAq\nMGg6kFLCkRJdho0mXUXLJJnsqeLjdRGoQiBlO5COA8dxMOIAtT4VzbqCR0ZyaPAraApoaNJVBFXg\njt4UzCJC3dvTFp5IGGj0K2jSNTTpGnwC+HFvKm9xPnGsj+mwJbnPAGBJiUOGg7VR/5hVgfEx/wKO\nUa4komMBIwe5ulbMnrv9SaDrhYKxpYXSjC//FFj4jvzvqGDsHMmvvI0vGn4tY8k7SQ1xlZWsLE2j\nlsxQIvN4CilZu2Gmx35Gnc8Dhza9xp0riGmBZyHEmUKIG/L/Vwkh3tyUdNcFrr6ey/rJJDOX69cT\nALoxOEhKgAueFAX4zGdIO+joIG2gupqGIyUlwGc/S85woavfF74A/OEPnuW1YfDhmoT86Eeec6Ab\nfj/f70rOuUDcNViZKnbsYJ99Pp5fKkUwadtUypjtiMWAL36Rk4Jdu6iOsWoVXQQ3biS1xO/35P1c\nZZOHH+ZEJhz2nPuamwmcn32WtJRAwJOqa23l48EH+XkVVpW72tnPP08wr2n8/OJxKpQ0NvJzmSye\nfprnUUhPKS/nBKaYQsk0wjZpQZwrEEGpWAys/TQ5ygM7PZC79F2sNj/1E8xAjrSTI7j4cmDpFcWP\nU7MCWH0TB+KRdi5/Ln8XbyjtGz0Hrdwob1qROhbozLaDlpS8wUXG0SmidUD7E7N7rPFhJHk4zaka\nAAAgAElEQVStrdzcHme2I9nDwsbKpTyHbJxfxbo1XMp1IxtnVsd1SUx0cJm5sKhJKFQT6Xj2r3sO\nxUIRAh+rDWNpQMX+rI09WRuVmsDf1UVmbPgR0hR8d0EpWgMqeiyJHkuizq/i2/NLxtAuxoeuCHyq\nPoJ5uoq9WRt7szaadRWfqg8jqin4dF0EdT4FW9MWtqcttOoqPlUXOVzU6DgOtqdN7E6bcPL3hqcS\nBkpVgYCiIONIZBxJHrYq8ErawafrIqj0KegwHHQZDk4IafhYbRjKDNOMJ0X8+FpzDAFFYMgG4jaw\nMKDiziWl2JKxETisyuEg60hEVQUpW+JQEYm7F5MGwvnL5m5XoikYzsvoTRYNuopP1IYgQO53R87G\n2TE/rqksnuotm88iaEtIHBiw0T/kYOHFNDAqFu1PckJZeOnCNRxHYw0cO60sn492kQax5PLi+5xO\nWFnuzwXm022bKOat58pQLsGxOpfg86azjr2fr3XkRugoGq7xXhOCtL3jqX5jOmob/wBgDYAlAH4M\nwAfgFwCmqGd9A4eiMFN6zTUEzqZJ8OVKpw0NAf/93wShrs7zjTdSDaO0lKDQ1VwuKSAXlpURXI9v\nc01YensJlAHPnEVVJ1+nURRyc3/4Q88NcN486gsXU9QQguf12GPsi5TsW1XV3FQ/AJwQuKYzQvB/\ny+JzTWO/LYvHV1XvWkejlOPLZvm638+Jh6oSzE7UpmmTTyJU1dPudq+raY5VF5lsu/H7dNVLjmEd\n7dAm8vDMDACZHzSvJ7XCyhAgKxoXkc2MV9TSeBqX63MjXIKcjKs3PprOpOpCLkEAdThTLYCh/ZRF\nQt6hq6QlXwU/B8uEQsERbl9Szh2NwLFooNL2Zx5W1YBl76be8ethGVQo5J/XrAKqTuD5aAFOnITC\nm/LLPwG6XwQguKx90ofH2nKPiTm81jMNSwJZSekzRQJZOdZUZCaxKKjhV0sr0JmzSFnQp8dkNB0e\n32VNsC/8vzNn45F4Dn2mAwmJEdvBeaU6Knx+PDuawy3to+g36Q04T1fxz80lUBXPFdD9vvGnLCEA\nNOoq/ldDBAlbQhGYFYfAUk1BZT7DLQRQ41ehCyqZDJk2tmdMZPOYt8qnoFJTiv7UFSEwYNrYkjJh\nODyXGr+Cck1B8S15/QyHpjAAkMkXR04VHQtzePwTWSRzEkIFjFI/FmlBqEWON9HY4oYEpRUdExAa\nx1MrPXMXS4Dj1r6HgB13c6VHgHKWy97NguW9G+hgerjt7cCydxWvJxGC2fDW8/NKQNHjKzN+TFFQ\n/F4Yczn+zySm05WrAFwOIAUAUsouAMfAOnwDxPz55P2OjPCva/ts28yEfutbzJ42NfFhGHTuGx72\n9hGNEkhPdGce33b11QSApukBZstiFva972WGOF1Q0+mCxYUL6SLY0+P1ZXCQfclMSMxjuMYsyaTn\naDg8zNfmz4Ho7/Aw+5TLcYKxYAF1or/5TWpDOw7P3efjeY2OMqN8/fUe0HUd/0ZGeP3e8Q5ed9v2\n2uJxXteLL+axLGtsH8rLWai3eTNfq6jgZ+sWehabcJxxBq+XXZBhGRjgNrW1M7osA7uAF24niC2Z\nR53cg0+QKtG/HXjxh1yiL18IxJqAtseAbb/1tldU8pGnC5wPb6fltyugeETrgJ6XuC+9hOCrbwuB\n+Wxz0IQAms9hJsbFRlIyY9py3uwey41df6DpSaQWKGmkecorPyMv8vUQ4RoWU6UH+Hn4grzh50aB\npvU0m+h6gUoqruHLs//F94SruMrghmNzyXTeusmP99cOW0p8rzuJgzlmcucHNWQdie90p5CYBdOS\nBl2bNnDOOBLf6U5i0HTQqqto1VX0mza+251Ed9bG59riGLUl6nwK6n0q+i1K4rWlDdzcNoJRy0Gt\nJlCrKegxHHxmfxyrQz6M2BKG4yCgkGOctB2M2sCZMaIiIQRKNGVWgPPutImvtCcAIdAS9KHJr2Fv\nxsZn2uJo9CnYlrHgOEBME4iqQJdho92wMM8/+bGbdYU8aglE89u152z0GDbqimzXnrNwR28KAUXB\n/DxN5IWkiV/1F9cp2Je18OO+DEKqQHNURUNQwdOjBu4aKHJvA7Oz6cGxuY5kN1feRg4CL/+IKzEV\nCz0K0/ZjcG7tfA7Ycmfe2bSRY8zu+6ludOgpqiAVtu36A8H2dEL1cds3DHAGEzKVy/iZuCEdamk3\nT1C69VrFdH6FhqSXpwQAIUQRNtGbJHw+4NOfJgBzHeO6umhBLSWzm/X1Hvh15emef35mx9u1y8tC\nF2ZFw2ECwo99jH8PHmRf+vuBG27g36Ehz15bCGaP43Fg27bJj+eagUjpydEpCnm8nZ0zO4di8eKL\nHh0DYD/r60ltqa+nwkR/P4/d0cH3/vu/k+JyzTW89u7nYBj8bJYto6pIZydfd5U6PvUpSvxdccXY\nNsdh28AAzz2X8+T9XMm6/v7Jz2HlSoLyjg6vL7rOz2aGqcu2RwhO3UIV14r74EZaRvuj49rm0XnL\nLH7vmFFkhoFoI7mB2TizHZEa0hucyVdkZxxLLic1ZeQgiwZHDgJVS0lNme1wLMr7xeZ5SiOazgnE\n3gdn/3hzEUKQcqPpnmta4hCw8GIWkHZv5nfHzdz486oq7ZuAUz/J1wu3W/xO3sCOl9iftdFrOqj1\nq4eVG0o1Uhy2pGaoSzbD2Jk2MWpLVOad+4QQqPKpGLYkftqfQsr23ACFIlChKRixJb7VnUJmXFul\nT8Gw6eDFlIkFugILAklLImmz5HN5QMWwPfs1E78byMCREtE8PUUoAtWaQHvOxjNJE41+DYYERiyJ\nUZt619U+FX3W5OngPtPBPL+GrJQYsSQSNhBRgDKNiiWTxaaEAZ8Qh+XsFCHQ6FewOWUiXmS7x0dy\nCCpAML+dmt/uuVEDySLXrGk9V9hGDua/8wf5W1/1QWDfg0wOuAkHReW4cODRmVO59j5AmogLcBWN\nv8m9D9HdNFw9ti3WQGD9epcHPZY46cP8TNwxaaSdk57G42hCP52p9m+FED8AUCqEuBHA3wD44dx2\n6zgJx6Ft9iOPMLO7di3w9rczGzt/PqXdfvc7tl1wAbWY9++fGCy5cmOWRR7vo48S6K1bR/OUcJgZ\n4+9+l0WApkm1jM99joCuvJwZWZe3XFVFYNfXR+WJSy4B7rmHfb74YvJ2X3hh4vNyjVImi2SSWddQ\niO59QjAj7PezLZOhksXGjaRAuIodbgb8kUd43TQNOP984Jxz+P/AAPCNb3Bbn4+yeJ/8JEGqNsFX\n0aWPfO5znIDcdx/7dMMNvDZCMDO9di0z/X4/TUeCeUR5xRW8vvv2EcguW+a1vetd5Kjv28cs9vLl\n/Hv//aR6BAJev6qqCNCTSc/8ZXwoCmXszjmHYDwU4j6nkqorEunBIyu83aW8ZO+RGWXFXWbMTF0Z\nfrRhJCj/ZKVJAdACHNwSHXnqyCxL1vnDwJlfogtYeoDZ0fKFc7NsZxu8MSrjMui+oFft/XqIWAPw\ntq+xsNNMsbgz1kBwMJE0uhbgtY3NA5a/m/SgXJw3qWOlqzhS4tlRA38ZMZB1JFZHfDivVEdUVWBL\niWdGDTyRb1uTb4sUyaimHQkxwVq7CiBuS2QdBz/sSeKBIQMWgHNifny8NoKKIhnPmUbKYSHg+JCQ\ndCOcaMkZEn2mAzFRoyDwnB/UIIWFtqwNBcCSgIp6XUXaLo6ieg0L3+9OY+OoAb8ALi/X8Tc1YfiL\n0Mz6TPsIYxmhCAgI9Jg2FgZVhBQNcUtCFUClT0GP6SBVpC/DlsTioAZd0TBikYJRUbCdJhw8MpzF\nq2kLMU3g/JiOkyM+DJrOETJ4rjNhypawpYNH4llsTVso0wQuKNGxMuzLG7yM3U4V/JakHYnIJGOS\nogGrP8qJ5WgnV+8ql/L1zNDE46qTVzIqVnA9WWSGmXDY9wiQGeDx6k8lNcyxjizoVXXA6GV9iXiT\n6qGFqyj1N7CTBZzRhvzk/zii0E350Ugp/10IcSGABMh7/r9Syj/Nec+Oh/jtbwmmKisJ9h54gEv6\nX/kKTTMeeohtZWXAE08QOH/ykwSnluUBQikJlJcuBX76U+AvfyEgU1UC5VdeAb70JeoFP/UU96co\nwK9/zcK3f/on7kfXPQMTxyG4W7uWig7PPedlmB94gADuPe/x3jveDbCpafLznjePFA3T9KT4duwg\noKyvJy1l+3YCyWwW+NnPgN27yaX+z//k/9XVbPvJTwjAP/AB9ufgQU4EMhlOFLZsoZzbffeN5Qe7\nlIqaGuDrX2ex3kkn8fW77uLE4YMf5HuqqviYKKqr+ZgoamqOBMMrVvBaVlV5yh65HD//6Ri9NDR4\nborHGDWrgJ13j5ViMpJ83ngasGfDWKmiXIKAdi4crWpWcYkx1uhJ06UHqc6gzuCGMp1wXcCwZMq3\nHlNoQQ7M2eGxsnvpAaDpOFomnE6ofmpZF0aklq9b2bHAIJcAalZymXj7XVz+1ZuAzhfIbT/nH4pL\nfhWL3w9m8Kd4DpWaAp8QeDiexZa0ic83RHHvYAaPjeRQ6VOgQuDBeBavpk3c3BCdVEu40a9CQsCW\n8rDNtZQSFoBWv8Df7Yvj+aSJUpWg6+6hDF5KGfjlknIEZrlOo9GvQgpOENyCPUdKCAicHvPj0YQB\n6UgIxS0QJOA8K6ZjZzY9ps126Ph3akTD/2lPIudIBPP8521ZG12mxD8WkeJLWg4+sieObtNGqcpM\n/A960tiZsfHN+ZMPBKdH/Ng4ao7pi6ukcU7Mjz8OG6jUBMI6r53rFFiMfrE8pGFzykCFTzsMXHOO\nhA8CYUXgG52jiFuS2tmmg9t703iXFcAJIQ3bMxbKCtBIJq9n7RPArZ2jyNgS5T4F/aaD23pSuLYy\nhBNDPvxhKItYwXYpmwos5UUKPgHeZkqb+SiMmlVchSpU68glSIsqHIePJnxhUsAUjb+/7BCw+z5g\nwcVA62mkhsUKbhnpAaBi0Vi9/TdjqD5SaY7XmNaoIqX8k5Tyf0kpP/+mAc7Dw1RzaGkhZSIU4nJ+\nVxczp3/+89i2lhYCvAMHmJFub2dWeGiIoHrFCoLGjRsJgF0JutZWFvP99rfAM8+QIxuNsq2hgW3t\n7cx4d3WRszw0RHrA6tXkNb/4IjPh0Sg52K2tBLfpNDPCbW3M+g4O8v8zzyzuIujyix3Ho4m4ah87\nd/LR2so+RqM89vPP85rs3s1rUdj2zDPUQG5vJzB32xobmaHO5aiu0dbGc+vv53svu4x/29u5z1CI\n1621lcWMxWgUM421a9nntjZ+B3p7ed3f9z4va/1XitbzuKQXP+ipJKQHaRCw4CKCncNtXfy78oNz\nk51dfBkzsSPtNEhJdBKMrbju+MoGzCSEYBGmmeZ5ZUd4nr7w8eUiONPQdJ7faDdVOTLDwHAb5Z+q\nT+SNvKSJky5fEChtopPboadndrxhy8FfRozDbnlBVWCerqHbsPFEPHvYKTCqKgipAk26hs6cg1eL\nONtV+BRcWKrjUM7BgEm3vIM5ByvDGtIO8FLKRINPQURTEFIV1GkKDmZtPDw8+7IpzbqK06N+HMzZ\nGDLppNees7E+6sdVZTrWhH3ozPdx2HTQbTo4K6bjI9UBnBTS0GnKMW3nl+gQQoEpmc0SQkCBgE8y\ng9phTJ7tvW8wg27TQb1fRUgViGgK6n0KnkwY2J6enM5yRUUQC3QVnSbdEwdNB32Wg2sqArigLIiF\nQToTxi0H/aaNLsPGleWBoqsDqyN+NOsaDuYsxC0HfaaNHtPBuysCeCVlYtiSaNRVBBWBUk1Bo1/B\nA8NZrAj5UO9XcDBnY8Ry0GvY6DcdvKcygOeSJlK2g3pdRSC/Xb1fxR+Hszgl7EOVT0F7ltv1GDYG\nLQfvrQzOyK4d4LgaKPXG1URe5WjlB2Y+zvVtzRf05sGw0Pj/8B6qIGk6ZTndcdUx6Yb6VhzfMenc\nRggxiklrUgEp5QznYa+T6O72lC4KIxgEXn6ZmdxslsV4lsVMpa4TKF93HYHnj35EAHv55cBNNxHQ\nKsqRqg2axmyny2kezQtXhsM8/iuvMNt7wgnAL37B91x7LekMmzdPbEstBDm9H/wgt3vySQLgM88k\n6C42EnR3ezSNQ4f4Xrfwcfv2yY+3bRvPZaK2557jecfjBKWKQmqIEOR0f/KTpJ08+KBHzTj3XGbf\nA+PX0RRu19MzecYZ4Pnu3UuwHwxSuq6iwmvbs4dtoRBNa8rLeazPf550nEcf5Wsf/jBtywF+rrt2\ncZIQjXK70mmkeg0D2LCBKwmVlSwCzWf/HRsY2EFx/kApne/0GB9n/x8WCfZtJZBuOY/ZXgA4+yvk\nP/dvZWak9fwjMymzFeFq4Nx/BA78hc5c0VOosxqdRjLeytGVMNFB+bm6k46+iHGuo2Ixz6/tUS7l\nNp8NtJzjZaKNFNCzmcY0Za1UtDhexPqnE01n8Tty4C8Ez4suBZrPJKCW8shz8Yf5OS+48OiP1WvY\nHDrHjTEBReDVjAUFQNaR6DVt2JLA2C8kDuRsrClSin55eQACwJ39KRgOcElZAB+sDOL3eYA84kj0\nZS3I/D6FlNiWMnF5RRA9ho2tKRM2mCFtLOBOdxs2tqVMOACWh3xonEI7WQiB66tCqNIUPBjPQgC4\nqjyAC8oCUIXAfy0oxV39aWwYzkERwKVlAVxdGYSmKPjewlL8uj+Nh4dzUAVweUUIV5Xr+HpHEmWq\nQEhVMGpLCIXqFwnLwZ6shdXRielfWzImVCmRdSTStgMFQCgPcHenLSwPTfwlDWkK7lhUhl/2p/DY\niIGwKnB1RRAXl+pQFIGP14Zx71AWGxM5RFWBG6rDODVa/AsfUAQ+WRvGPUMZbEoYKNMErq8J4ZSI\nH7d1JxFWgEHTwZBlwy8EavwqbAlkpMSna0P4fk8amxI5VGgKbqwN49Sojm92jiI2DrDrioBhOrAA\n3NwQwTMJA9vSJip9Ks6K+dFcxJBlqgiWA+f8X465/ds5XrWez3qSmcbIQaBsgeds6tfJq84McuXw\n3FuAtr8Aw3uBklM5xk/lejpVWFmg5xUmVaINXI2aCeXkrZg8Jv2WSSmjACCE+CqAbgA/B9lc1wM4\nxo/2dRBlZZ5ZSeFNIJtlBvrZZ2nD7LZv384s9HveQxrDP/8ztxeCBid791LHeSL5MstitjOTIfh2\nw7WcbmoineP552nZDRDAPfwwQe5kUVFBoHnqqXwczbkrCjPDhQoTBw/y+auvTrxdQ8PkbS0t1KvO\nFWSCursJQOvqSF/ZsIGThXSaJi2hEGkVxriMlGukUgy0Og4/h8ce82Tkfv1rygSeeCInNhs3em2/\n+Q1lApcto8HMpk3Mvo+M0IQmGuW1v/12ZtI1jcf4zW/oTLikCLcgnSZt5eWXvePdcQfw3e/CPuNc\nPPdd2pC6nOVtvwXO+DxBmh5j1nfxBOL3gRKK4v+1hPGD5ZRQOprIJYBN/0bgrGiAbQGRamD9F4vI\npL1GEWtgVn98jHYDm76e107O8x/LF9PtcLa55XMZFYv5KIxAKQCH37vCFQszM72J0URRoin5YU6O\nsWXOOUCTX8ULSQNbUqwyFRDYlZGIqQqurCi+ZPKzvhS+052GBCkS3+9N4UDOxvklPgwYDlIFqZ7h\nnAMdQJ0msWkkh18NZPKcaYE/DAGXlQfwjrIANo7k8JuCtnuHMriiPIiLipikAMBjIzn8cTgLBQIS\nEvcOZ+FXBM4tDSCgKHh/TQTvrzmS8xJQFHy4JoIPj2tr1BU4AohpyhgawogtUDeJ/TYANPkVJBwH\niRwl7SQAmDZUIVGnF7+eMU3Bx+qi+Ni4u7kjJX4/mMWm0RxUCCRt4M6BNCJqCMvDk9dw2FLirsEM\nnhs14RMCCRv4eV8aEVVBtU/BvUMW0raEEBKQAjsyFubpKvwC+EzbCLakbagS6DQtfP5AAv/aIlDr\nV3EgZ6MwU2dJCQi6D0ZUBReWBXDhFJ/X0USgdPa0nQEWVif7yON1w0iTEuUPAUoMOOHq2TkWQN72\npn/jKpOi0Scg1sAxN1Aye8d5s8d0Fngvl1J+T0o5KqVMSClvAzCF3cIbIGprybF1VRpco5FQiMWB\nAwOkN8RifGiaV8z3ta8R2DU2ElDW1ZGH3NZGsNveTkkzKZk9LS1lJtJxCBRd10Lb5jGWLSNXuraW\nwL25mfSHu+9mdnrePGaIbZv76Owkz/fEE2d27ieeyO27urg/2yZNpLGRBXpuAZ3bdugQAf5llxGw\nd3ePbWttZYbWlcfz+fiQ0jNg2bDBk9NrbuYx7riD5x6JkD7hcsnb29nHYtJxO3Ywc9zc7O2zrIz8\n8M2byVEvbCspYduLLzJL39LC69rczOPffjsnL089NbYtFOJ2hRJ14+OnP+UxGxrIm25o4PflS1/C\noY0Wel7iEnrJPGaOFRV46b/fGNXWu+5j9qO0hXzpshYO7jv+57Xu2fRjy8+ZyXHPoaSFWdm2P7/W\nPTv2CFWwgj1+kDdZKcm5VDQqEswkan0KTghpOJRzYOVd9vpNGyFF4KyYH4OGA0si76QHqBDotxyU\nFOGp9hoWvtedRqlGMFnrV1CjKXhwOItew0ZK5vW58w8AyAKQQsVvBjKo9ilo1DU06irq/QruH8pg\ne9rEbwcyqCloq/OruHcog54iph59po17BrOo86lo1FXM0zXU+lTcNZjFoDkzZYx3VoQQU8npdRwJ\n25HoMWw06QrWF8n4nhLVYTiA5Uj4BeATQE5KqELBCTPMwO7KWNg0amCe3z0/FSWqwI/7MjCKiC9v\nTVt4dtRAk66gIb9dWBX4SW8KEQUYMB34hERMURBRBTK2g7QtsWEog1dSNuo1gVqdtAyfAL7ansAZ\nUR8kgLhFd0XDkYdNVIpRSI6nWP2xvGthvkbfzPA3tuL9c8Nr3nE3V8gOj7mtwGgPsOve2T/Wmzmm\n8+1LCSGuF0KoQghFCHE98prPb+gQggVw553HbPC2bQQ9X/oSqQeLFpFv7HJ0S0sJEDds8HSHczlP\nc1lVSUn4u78jdaKriyBw4UK66/X3U62jsdFzLayo4Gsvvkgw6vfTBS8e96gLO3cy83nKKcxG79xJ\nmsYXvkBQOpPw+7n9CSdwf7t3c/8330wg+YUvUEni0CGex9q17IPbtngxweuePWz77GeZpa+p4XVx\nXRJLS/na73/v0T3icZ5jIMDr2N/Pa97SwuvV0wOcfTbw8Y8Xp5689BKPVUiRCYcJ4B96iKC3sC0S\n4XV/+GG+r3DfsRj79PDD/L+wraSEfS4m4ffAA9x/4fHKyoDBQQz/YSsC5WN3GSgDkl00uJirMFJ0\nnptrNYmOp8Y6RQFcCu145tiMBwBmgof3j3VenO0wUlSvCNfwppcZZuY5XEWZt7mMVD+5yXMhPVgY\nqz5EF8l0P7ne4WrgzC+OzZQdTQgh8KHqMM6M+XAga2NnxkSdX8Fn6iOI2xILghpaAxpSDjDqUMps\nZciHA7nJAeumBCkXgYKCQlURUITALweyCAggIGgsYoMgMiCADfEsHBBYjtoOEhapDRLAxpEcZP69\nCYttLvDek5mcL7w3Y0GCahLudj6RN8PIWpNuVyzKXbfDPA+523SwOuzDd+aXQiummmE4OCPmR6lP\nQdIBMg7QpGs4LepDex7Im45Ee85Cd95OvDDctp6CtldSJgKCGd6OnIVew0ZQkGpTzGHwpSTpH4Wr\nDdE8DeWVtIXVER8txzMmDuVMLNIVVPsV/HE4h7ACyPwxjLy7Ytx2MGxLfCrvItlh8Pk7ygK4ovzY\nl3w6sjZ+35/Gi6NHZ5F6tGPn8neTYgdBSpiVAdZ8DFj3uaPv81QhJdDx9JG0j2gtC77fitmL6cx7\nrgPwrfxDAtiUf+2NH+k0AaLPR3DX08Oiu1CIwC4e94CxaygSDDILefAggTPgueQFgwRRH/kIl/Fd\nAw+AIDEUooRaNkuwHApxP7pOYPfoo+RDC0FwWVfHvo2OMjPs7qujg3SDysqJz2s6kUjw3AMBHq+9\nna+VljIr/NnPsp9CjAXpIyMEksGgt10ySUAuBM/JVSFxucyBALPy27Z5tI5YjFlaTeOk5Ytf9BwI\npyP/5mbuJwr3M5qszZkE1QUCR27n0nAmktor3G78Pt3nQR1yAtVAibnJSkhJDdGdd+cz2w7QcDp1\nNeeCE6f4jwTJ0snLws2wAMexKKt24DFvHwvfDiy/evaLJZU8y6brBWbQBXjMkiageuXsHssNI8WV\nh56XvUKjE69lAelchKYDK67lTd4xqT5yrEWgGUei0ySo1ISKPlNi2LKhKwo0IbAirGF5SIMDwCcE\nOnPkwU4WkzEQJCT0/IeuFWyuCsCR3C5tA08kDKQcUht0BajxqfAJgZQt2WbTyiCoCFT71aIFZ1p+\nu7+MGMjkM7EhVaDGpxx2HJxJ+IXA/KCGiCqgAGgKaFPab/sVgTJNxTWVfmQcCTX/WkfOhiqA7SkD\nP+vPHJaYm6er+JuaECp9KramDPy8P3NYCq85oOKG6jB8gpOHXRkbNgBIoEQTWBX2FQUMfkUc4Qro\nAnJdUbApnkK3O3zaQK9p4ewYoAsFSdvBkOW5LIYEACGgC4FFQQ1fbowg7UjoiphxMaAbtm3j020j\neGDYAPIkoPm6gjuXVqC+CEVGSurr77o3P3ZKurGu+tDUY+fJN5ASlh4iLUSbQ1MTl/5XGNJ5Yxmp\nHA8x5a1GSnlASnmFlLJSSlklpbxSSnngr9C31zakBL79bU/pYf58gqBvf5t/9+8ndaO01DP32LqV\nznapFAGtrnuAa3iYGsBu+P1j1RsWLyawdLOuoZAHTi+6iFnl0VEer6SEdI4dOwgw/+M/2Nbayodl\n8bViWs7FIpnk9qbJ825t5Tl94xvehABgP8cD5298g9fO3S4e577OOovXwLZ5bsGgd50uvZTA2bUk\nj8WY0d+zZ6wqiOsUOJ1Yu5b9L+RLDw5yQnHJJXzdLMguDQyQqnLJJZ6boxv9/ZyoXH+4EX4AACAA\nSURBVHaZZxte2NbUxPbJ4pprOBEr3G5gAGhtRe3VS5AdGWs0kuwBqpaNlU2breh6Edj6K2ZSS+ZR\n4/fQU5Qqm4toPZ9OUYVOgYlOFsXM9B6490HKSUUb8s6LdaSHHHh89vrthhYggB3clS/iLAG0EAsg\nC+WlZjNe+SnQ+woBesk8fg9e/gkz4HMZqo+mPMcKnB0pcXtPCp05G026ipaACl0At/emEVKAmCoQ\ntxyoQsAnBHKOhAOJVeHJ6QlnxXQEFGC0wDQj55Cn/Km6CGwAhkMArQnAdgBDAteUh7AnayFpO4ip\nAlFVwHSA3RkLq8M+7MlSzSGmCcQ0BTkpsSdjoalI0WCTX8WujIWsdLcTSDss7GueothwshixHHyv\nJwlIYGHQh9aAhmHLwW3dycMSchPFijBpDZS4E/ArAiMW5dqiisAPetPwCdp7N/gV9Bg2ftCTQnfO\nwu29aegFbZ05G7f3pKALgS1pCyokIqpAWAGGbQcvJU00FJHNOzVCAG8VZLcHLQd1fgUH0sZh4KyA\nk1ALwBMJC+eW+DFkUcfbrwj4BTBsU196cYDXUwiBsKocM3AGgO/1ZHDfUA4hRaJEUxBTJPblbNy4\nZ7jodl0vsB7l8NjZyNWnHdN0H1Q01nvMJXAWAmi9gBnu8e6srefP3XHfjPH6IA29FnHwIB91dd7d\nJBzmN3HDBtIrXIvukRGCrYULWTh4yileRjiR8HjLVpElvUCA2dxczjv24CBw440EbPPnc5/xOB+O\nQ9OUTZuOzDKXlhKsTVa8N1Vs3Upg604KAFJIRkYI2CeLl18m8CwpqEqoqvKA8IknErQmErw2ikLl\nj+3bee1s23P1K5T/m0m0tgLvfz9XC9zrqWl0H1y8mGol3d1em66zbelSFn12dXltoRDVQJYtA979\n7rFtkcjUFJKrr6YhTG+v55JYWgp861uoXa1gyWUsqHPd9MJVwMkfmdlpTxX7HwKCFZ66glDyzoR/\nmbmDVrFY+HagYW3+3Nr5t+ZEYOkMqyakJHiONXjGLIrGopw9G2av327YBs0Kog1AboRUETMJlLYC\nqb7ZP14u4dlou18pTSeoPfDY7B9vLuJQzkanYY1xAwyrCqSU2JK2cFNd+PD7DuVsDJgOrq0MoaEI\n8IxpCv65uQQWgG7DQbfhIG5JfLIuhDpdxcqQBiGArMPCRFsAi3SBhJRo0ZllTlgSCYu6yq0BFVsz\nJlryWeaE5SCRd/Vr0RV0GZNzijpNGy26AgWigO4h0OJX0VFku2LxasqE4fA8AYLFSp+KIcspSgWp\n96u4viqIAcs5fD0dADfVhvFq2oIj5WFusMgrXHQbDjbkFUrChW0+BZ2GhUfiWURUAeQnNgaYCRYC\neCU9OW1jUUDFlRVBdBsOOnIWDuXIc/+bmjAeiPN4h4sa82Hnz71F15CVtCRPOUBIEVga8mFk9s0V\ncecAJw2+PB1GURSUKORsd2QnP799D3EiWzh2xhr5u7SPjvkxp7H4Mq6KFY659atJzXorZi/e5DLc\nRSKT4Z16/3660Jkm6QOlpcwaxmJ0BhwcJOgrKyNIHBwk4D75ZG5nWSwsc4F0sVi0iJnb3bu53aJF\nBGfPPcfjnnAC9y8lJdS6u7nPXI6ufvv2EVS3tvKYqRlS09PpiavVpPSK/iaKVGpyEBmPE3yuW0ct\nbFUl+O/pYUa6vp5az0NDbCsvJ0hNpwlS//VfOVHQdepo//3fE9QWiwsvpMrI/v3cbvFiTkAArhCc\nfjrpIoEAr7Xb5iqfvPACj/GBD3gGNJdfTmfCgweZCV+0yKNs9PRQUWTzZn5e73gH+e2Kwuz73/4t\n+esVFSw69fshAJzwXmZiRw6xArt84ew79rmRTRy5xChUqmDYxuxTN1Q/MP9CZpsH97BgcP7bj0Gl\nQtI9b3xWXtUp/TTbYRu8STafQ/c9K0tbdEVlAZBL6dj9R4LpyqXAsquYNZ5JuPzm8fQTTSdwfz1E\nJp8RbstaOJC1YUqJOr+KEo1gs1JVUKoKPD6SgyGB06O+aWVsV4d9uKDEjz8M5WBJibOjflxUGkCf\n6aDBLzBoAO0mwVm1CswP+jBiMXvapKvYm7XgSKDVryKs0jK7RFOxNO9WJyX51z2mjYzjIONIPDKc\nxVN5Tuy6qB9vKw0g61AdxCeA/TkC2xa/ioBKzm7KdvCneA7PjBpQBLA+quOCUn0MX3t8pBwJy5HY\nnjbRadhQATTpKjSBw9SQyWJdTMcJec64TwALAhr8isALSQMZW+LB4Sy6cjZUIbAoyCzziO0gbjp4\nPJ5Dv+VAFcB8XcXykA8jtkRYEXBAe25VAGWaiqxDfeo9GQvf7BzFy2kTQUXBleU6PlpLR8NWXUXW\ndvBSykJYBa6tDKJSE8jmQXDhmbhAuteSWBJSkUk66DUldEViWciHmCqQtuUY85TZiLQtMf6jcJ8O\nWzYaMfF3MTty5Pjoqu/YxvFDi/AFqQQ00u65s8bmebfm3q3A7nuBkQ4WEy69iqYsb8XRxVvgebJo\navLMRUpKCLAOHCCIvv56AjLb9tzrpGTW9ayzKEsnBMGi2zY4yCK7qULXaahSGC0t3v+uI57j8LF2\nrUfRcHWhd+9mX2+5ZWbnPn8++1/oTOhyfYuZqyxa5PXL3c7Ntq9fz0x4JOKdn9t25pnMdvv9Hv3B\nNNmHkhLgve/l9auoYD/uuIOZ7J/+dOpzcQs5J4qysrHZdYBZ4euuI2ivrmam/HvfY8b4m9/keyoq\nPL1oN4aGKE+YzXruirffztevvJLvWbbM+06Mi3A1H3Md9auZuS0Ed9lhPp+pm1yxGNwNPPmv3HfV\nUmZWn74VWHfzkU540wmhANUruN9Irfd6qg9oOAo1xumGLzyx+2D8IA1UDj5BfnKogu0DO4En/onu\nfDOhdYQqyYnMjY51j8wOv34yR426igNZC8OWjaiqQFcEDmUt7Afw4eowPn9gBE+PGijXFEQF8Oyo\niY/sjePXS8sndYZzHAef2R/H5pSJCk2BIoBnUyb+dm8c32uO4rGEibQNuPil3wIeHTHw4eog7h6y\nkLUlIhrNsdsNGzBs3FAdxLa0CQVAtY+AyZEE/k26itu7U9iVsVCTd9V7aDiHfVkbV5Tr2JW14UiJ\naJ7kvD9nQRMCtT6B23pSaMvaqPEpkADuH86iLWvhk3XhMcV0hdHkV7EtY+Z1mimctyNtIagqaCrC\nw3UjpilYOe7a1ftVPJ4w4EAiKAQcSGxJmeg0FFxUGsCtnUnYEtDzxY47Mjb6TAefrQtjYyKHgACC\neRDdY5KTXudXcOPeYaRsiXJNwJIO7uhN41DOxqfrI7hxXxwZW6LKJ2A6Ev/dm0aX4aDVL/Bqbuwk\nwH12blTDrV1pqEKgRBOwJPD8qImFQXn42s9mnBL24dFEDoXz90xe/WV5cPJrXb8a2PvQWC39zBDV\nd3zhSTd7TWIyB8Wel4Gn/5OSdaEKAuyN/wKc9eUjZSzfiuIx5TdTCFEjhLhDCLEh/3y5EGKOFpWP\no8hkmFnUNE81Q0pPpeF97yOg6uoi77WtjRSEdevIce3oYGbYbVuzZlLgNGVUVwPvfKenNtHXx32e\ndZbHwfX7Pf1j1x1w+/aZHa+5mSojBw6QauBSHy65pDi3d+FC9unAAfaxp4d9vuIKmoysW8dJR18f\nr82hQ6RBnHYaH4VtHR2kOzz4ICcwDQ2cwLjSfJs20dp7tuNHP+JEpK6O1zQS4bHvv599miyeeIKZ\n94YGXv9olNfx/vtnvgIwB7HgIgK0+EG6FY4cYjZ11TE4aBWLHXcTOIcqmaUJlvNxLBzrE97DbPlI\ne/4c2klrWHrl7PXbDSF4bawsr1V6ME+tqSSHcMf/kHMdKOVybiQ/t9374MyOp6jASTcQLCc6mDka\nbgNKmmcuHffXjqwjEcgrYeSkRM6RkIKgcGfawLNJA/U+ugv6FYFav4JBy8Y9A+lJ97k5ZeGVtIl6\nHx0LdYWSdX2mg9t6U8g5lKhzPZk0AdgSeGzEQEgwx2k45EVLkK4QURW8rVRHR85Gn2mj37TRbjg4\nM+aH4QC7sxaadAUBRSCgCMzTFezNWtidsRBSBKQkRSSXtwMIKQI70zbasuRM6/ntmvwKdmRMtBVR\nE8lKiZCqwAEO9xOQCCkCmRlKVm5LGZCCBY4OcFhZJG1L3DeYhiP53N29XwAJi5zlqCpggLSNnMPi\ny0a/gnuHMkjaDmr9CvwKTV3qfAoeHTFwW1cSKdtBTb4trCmo9Sl4OJ5DVJt4cBEAtmccCAEogjQO\ngEYoA4aNEXP29Tq/PI/qHcOWg6RFh0VTCnyxIQJ1vClaQSy8mL/7+AFv7LRzwMr3vz5cVqXkuOuO\nwYrGcdkfBnbe81r37vUX08k8/wTAjwH8f/nnuwH8BsAdc9Sn4yP6+giEFi8mADQMUgsUhaDvwx8m\nFeOHPyTYeuc76SKoqrTSnj+fmsDpNKkDJ598pFvhRHHwIJf2DYM600uW8Jd51VXk4z79NLOyp58O\nrFzJ40ciBPUDA/yFVFURVO/Zw+dtbdynlMzCLljAfUpJqsfmzTz2Kad4WecPfIB9fvppnvO6daSN\nFAsh6Ay4ejVNZHw+4Iwz2G8hyN9eu5Y0FF3nPt3zu+kmAujnnydIPuMMXvtPf9qjU7jhyvTt3s1r\nMJuxbduRjoaaxmPu3k2t7a1b+b6SEp5PdTWvY3ScPZo7iRkcJOg/DiJQSgetQ0/T1TBSDzSf5YG+\n2Y54GwfowtBLyMNzbILSrhcIgGONzB5PlQGPNQLnfxVof5I3srIFQNP6vOHHHET5QuC8r9LNMdkF\nVCwFms6g6oeRPJJCEiilW9hUkRkCOp4l3aR8MZ0XVT9Qs8I7XmaAFtoNp82tIUufaWNz0sSo7WBp\n0IelIe1wcVavYeOlFAvrloV8WBrUjnAPLIwB00GdrmJhUENnzoYhJWp9zBZvTVtQIKCMWzfXhMCO\n9OTc3n154CnGbacC2JKhskREFTCkq8BBRYxX0wSyJZrAtjRpG0tCGipUgV7TwRVlAcRUBfcPZWFL\nicvLg7ioxI9nkyaAsSYvIg/C23I2WnQVpl/F3gz7fELIB00A+7OUjGjLWtiXpZviorze8oDpYP4k\nXh69poNFuoKMQ4BORRIfVKGgz7TR4FewO2tha8qEXwicHPEfdkI0bBs/68tgw3AWYVXB+6qCeEd5\nELszNipVgaAiMOpIqBCIagIjlsS2rEN5PwUwgbwKCa/ZyykL58d07M+a2G840AWVNqKqii0p8/C1\nTefVPSL57PvLaQuBcd8LTREQQuKQKREFtbfd40UF4Ahga9pEjSow5EjETYKSRl2BBYEDOQsV0y0S\nHxeGI/FqysS+rIVyTcHqqB9lmoIlIT/uWVKOW9rjeDVjo1pT8LmGCC6tKE4DDJQCq/63gzufymBn\nr436qILr1gVQ3sjP18qyIHt4PyfU9ae+dqYkRhLofJ4T8JImoH4Ni58THUC4lhNyY5RjcbiafX4r\nji6mA54rpZS/FUJ8GQCklJYQoogjxBskXIpAWRn5t24cPEhQ/YMfALfe6tlt33YbaQk/+hHB1uLF\nfBxN/PnPdNZTVe5zwwYqbVx3HcHi8uVHUj+amgjQEwkPVPb3e2333w/cdZfHy73/fmaC3/Uu4N57\nabTigtM//pGvX3EF97Vy5dGDU1Ul6D755InbTjllYhqFpjE7v2bN2NcXLmT2uTBc58dCOstsxeLF\n1IgefzzHYZHot7/NyUYwyEnMPffQmbCpiZn+QhqIS0sZTw15jcMfoe3yTKyXjzaiDdQPLgSYRpID\neDZOSkd6gAO7lQN23wec+eWpNYaD5bPnADadiNQc6QJm52XdrOxYu/FcAqiZ4mcztA946t+4D8UH\n7PsTeYfrbiZIjjVQPu6vEVtTBm7vTUNKCU0I/Dmew0kRHz5SE8a2lIk7etOAIFB9NJ7DKREfPlwT\nnlT5oExT4EiJUlVBWYGCRnvOxokhDY+M5CAdOQYI247EgiJL5k1+UiDGb+dAYlFAxfYMoEHCp7pa\nDgAciUV+Bc+nTbTn7Lzsm8TzowZq/ApuVAUeGTFwz2AWPgFACNw3SCMQqjwceX4CpKVsGM4hbuX3\nKYEdGQK0t5cq+Hm/iV7DPiwztzuv3lFaxASmUhVoyzkYzfNxbQlsS1uo8ikoUwV+M5DBE4kc/IIZ\n7wfjWbyvMoS1EQ1X7RjGlrR5WCbvL4kcPpDIoTWg4tERoEpT4M5HpSMRB7BIV9Bt2NBVBfrhNgcS\nwPKwhg3DBjIO6SwSwL6MjQZdYIGu4cVkForwlq0HTAm/omBZUMXjibHQwHYkeea6ipcsCzUF18Bx\nHCQcgVZdwf1xFjoCBNd7cg7KFILomUTGkfhudxL7szYCgsorD8Sz+HRdBDU+FXcPZ1Hq9+Ftug+G\nBB5NmDgxbBW19u41LNzQFUdvgw1fo8CLUuLhoTT+q6QUJ0o/Nn2dPGJfkGPZznuBM780d6o8k0Wq\nn+NqZojjUtufOa6u/xLpJfsfzsuFakwACOX1Qwk7nmK6JikVyK/uCCFOBzAyp706HqKmxisoy+UI\nnrq7WSi4YAHwn/9JhYv6emYjGxvpTPfAAzM7XjxOW+j6etISGhq47P/w/2PvvcMku8pz399aO1Ts\nnHtyljTKCQkkkZQIwmRjkLkE22Bjk3yPD/bh4Ot77nHA2ARzgWNjsLENBqMDQmBASEISEpJAWSiM\nRhN6Zrp7enq6u7or7rTW+ePb1Wmme0YjjZDEvM9Tz0z37tp77V1Vu971rfd73+tlDEvhzDPl3ygS\nmYHnyf+tledfc81czPbKlbLvZlPbtdfKz/O3ffvbIrd4tuAtb5Frvn//XALj8LCc91Ja5qeCd7xD\nquIHDsjxGg2Ra7z4xaJfvu8+0X0PDAhhbm+HL35RNN2+P5cy2WjIisVllx1akf4VwkmvFZLcmJbL\nEpSFTJ/8OlkqbJQkCavYL/q8YOborZ9+2XA82HKV+D+H1bSfdlKahza9cunnWQv3fQmcrFSFWgbk\nGkxsl2r6M4nIWP5lvE67o1iZcen3HdZkHO6vRNxTDvnX8TodrmaF79DvO6zOONxTiXhkmSpxn+9w\nTsFnT5AQGouxlrEwodVRvLEry2l5l5HIyDZjGQ8NRVfzuq6lS+vnFz02Z11GY0OUJvAdCA1tjuZj\nq1rp9xxKBhJjMEaW4vNa8aaePPtCg6sgr0Va4SnYHxr2RwnfmWwwmNEMZhwG00S9H5UCCo5mdcZh\nbxATWzsbGLLCdzg17zIVC0ksaCg4Uu2eiuU4Y6Hog+V44t+8L5RxLYUWV1OKLcpailpTcMQzuRRb\nSrHh1pmAVb4kIA5mHPo8h29M1PnHA3Ueqke0OxKL3uZqihr+bbzBuQWfFlczHkpqYWgsI5HhtLzD\nn6ws4ivFTCLjioxhysCGjMMFLRmmY4OL2NTltcgpysZwQatPYiWK20MmVKGV6/BbfUU8pTiYpiQG\nxrI/EhnMR1a24ihFOTbY9HilBM7Ou+SUIkEmJs2ESAtUrNgaHgvunAnYmVoH9vlOGgOu+LfxGrdN\nN9id2ig2t7nA1w7WDwmRmY8vjNYYixIGfYceTzPgO1gLf76vzBM/hJkRacBr3stMDA999ZiG/5Tw\nyDflPjt7X10r99nHvyPEPizLpN8rCLkOZkT2dgJPDkdDnj8MfAfYoJS6HfgK8AfHdVTPFrzznVKF\nnZoSqcbWrfDHfywVZmOEZNXrUvkFIa433CD/TxLR8G7bttAbeSns2DEXttF07TBGqrXLaZeHhkRn\nvH69jKNaFRJ8ySUigVgc4OG68rvbbjv8NmOk4RGEhG/fLj8vttmrVCSp78Ybj+78jhX9/fAv/4I5\n9XTiPaPE4yXsVVcJYV0meeuYsWEDfPnLQpCHhuS1//Vfh898RqQvLS0LBW7Fosh3okiSELu6RI/9\nxBNieffGNy59rF8B9J0GF3xIdHXTQ1LtOO/3xL5u+GcLm/5A0geHfzZn9lIdF3/j6nFMW3wq2HCF\naJRtIueX74YX/Vf5wloK9Unxvp4vM1FKqun77jzuQ16AkTChlthZyzIZi6LoKG6ZCQmMJT+PwCil\nyDuKB6pLJ/ABvK03zxUdWUqxYTg0nJRz+eBgkTbP5VPrO7iyI8NEZNgXGjbnHb6woZ0+f+mqn9aa\nz67v4KWtPgci2efWvMMXNnbQk/H4jy2dnJP3qFrFjFFsyjp8bUsn24OENkfR7moaaQJfq6NpdzU3\nlJoJg3Pn5yiFtZbdQczv9hc4t+BzfzXi/mrEWQWP9w0UGU3PZ4XvMBVbpmLL6ozD5qzLj6cD8ZN2\nFXUDDSsBI20OqRRE5ARP1GN2NuJZT+ShIGFrwWUw41BOJRHrcy6bci4/LUc4qAWBKZlUc/3dybr4\nJis1S/I9pbBYfl6N+NyGdk7OO4zFlpk0ne+T6zs4uZjlixvbWeU7zBhFwyouavH5+kld7AoSzip4\ndLiK8dhSTixbcm7qb51wcatPm9ZMJZaKsWzJOZxV8Mg4ir9b3866rByvaixv6Mrx56tbeUFrhr9b\n30af71AyisAqrujI8C8ndXBfPaGQVrJjhKgXkGXx22bE6aScGLbVI4aDQ1MSD4e7qxEdi+K72x3F\n/tBwezmic5EGu8OVYJmZZOl931YOaV+0z05HMRQkbP+pOaThu9AL44/IytRTQe1geg88CmvMpvvP\n4vtqoQ/23ila7dUXS7U5mBaZ2OpLRI52Ak8OR5RtWGvvVUq9GNiCTA63WWuXv3M+X5DJSEPb618/\nR2RB9MVRJBXhZgiH1rK9WJTK6Gc+Myef8H3R+55zztLH8n0hpDfcMGcH57pSiV6swV38vHxeNNfN\nyobW0rS3lM5WqYUBLYu3+b74OX/+83NBK21t8Pu/L+Ty2mvhox+Viry1Uhn+5CeFsB8HjNS3cm/3\nN0guCbHKpZjVvKAGLcdJ40qtJpX/rq6561GrzSVLzkczYdDz4CtfgW98Q16H3bvlmmzdurxDya8A\nBs6C/jOFYCpnbu7h5VLZwry7kInmfv/gVySEQGlZZlx9EZzx9jmf1WcDlJLkv7UvSZdCj6KtYXb8\nYuwwCxM98137nhZnB2sX6nsjC8UltiUWckeYt2a04te6crymM4uBBRrpurFktOYFRR+rLDnHOaId\nG0hTXcHRXNjqS9Of1gTpPW9NzuVbW7sJE0nFy6X36p2NhMRCYOfsyWrWoq2iqBWH7eFTiqzW3FMN\n+fKBGtVEjvFPoWFt1qXFESJ+MDazX6DjkaHfh4J2SBCnCQeLtVAzcv55R/NoNeTLB+rUjfhNt7uK\n3+kvkE0r1GcWfU63koSolBKvZEecMhbDIo19kYVSYmcnnFpJg1/eUZyS9/jy5i5CI2PV8woOL27P\ncmt7lnqS4MNss1xOS2hLKbFkmvZmsWHA0xQd2B8mzBiJPLfASGjo8WT857T4fHXL4Y/3qs4cr+rM\nHXK8LJaGFdJs00cNyFho0YobSg2+M9mQWy2wPuvyW335WU/swyGnFAcXXbLmjwUHJhffxpGP4hJ9\njTJOBWWz8EObIKQ/mwdTh/kWHjaRe5s6RttRE8OD/wpDt8hBrJFEw7PeubwtnpuR586/F5k4va9q\nmaS3rmL2pKMaHObtdQJHwJLvPqXU65sP4DUIed4MXJX+7lcHSi1s9rvoIqm2VipCbJvkdnpaqsCf\n+pRUgFevlkdrq9idjY0tfYx166TKW60KUW0GjTz22PLa3pNPFlI3PT2nv65UhPi/6lVCkuf7S5fL\nMt5XvUr+LZfnts3MyN+vWgWf/rQQwuY5WDvnQf2RjwihHBwUkpkkQqxLT78RbWU//Pxzku7Wtt6n\nfZ0mKMOdn1qYyve0YedOqTx3dUk1f+1aket8/vPSxNhoLEwtHB2VCcUDD0jzZleXXJPBQZF7vO99\nS8d9/wpBqfSLZN6X0/pLpeLRjJK1ViQQ6y+VQIKhWyXApfnYfbMkCz4bodTRe3NnWqH/LPG+bhIe\nE4sH9/GK4F4KA57IEw5Ec+/R0FgiC1d2ZBj0HQ4uSvWLrKTJHQ2UUguIc2It/2u0SiWxrM65rMl6\ntDiKL43VGAuX/kBHxvK50QoNC6szLmsyLnmt+IexGhPzxu47zixxBnhRq08llRBktLh0xEYqpld1\n5shp8Z5uopIYfAXdjua/Dc2gsAxkHAYyDg6W/zY0Q1bBE42Y2FjaPE2bpwmNZUcj4fKOLJVEPJsz\njibryLZqYjkt70qqnxbd9KqMQ2Lhc6NVNuU8HJoexAqlJIWx6CiuaM/iKEV9XlV0KhbJypu6c8Sp\nyZKj5BEYMMDruuZMiX2tFxDZ+cg5zgKXiRW+w+NBjKvmpCBTkWEkNHS7ikcbMZ6yFF1Ni6upGMuD\ntYj+eZPgJ3O8jTmPGOFvzWcYRPvcouGag3V6Xc3KjMNKXzMUxPzb+NLOLAAXt/pMJ3Nph9ZaRiPD\nmQWXS9tkRSSZt20kTDi76C1YgVmM13VlmU5EMgSiHz8QGy5o8Tnpck11fOG9bGafNGMf62R/5w2w\n8yYhus174J7bYfsyylClxFd/QcKgkZWuDZfDukvlvgOpl7yV79j1lx7bGH+VsVz94Kr08W7EWeNt\n6eOLwLuO/9CexRgelsa2JjGdmRFCddppUnE8eHBh4l8+L+/ku+9eep+7d4tPci43l7JnrbhRDA0t\n/bxcDj70Ibl77tkjj3pdXCoGB2VbHM9tCwJ4//tFs/uBD8jPzW1RJCmHu3YJSZyv1W2mFn7xi/J3\ni7fV6yLjOAo0i7VHg+G7U4uleZqsQo/oZo+2Q/jJHI/bb5eJQTN2XCm5Vjt3yqrC1VeLrnnPHnld\n+vvhve+Fr35VntPsDNdadPPbt4t05yjQ7Ev8VcGGK2TJcHqP2D5ND8GqF4peeMf10DI4FxaitPy8\n80e/3DEfKxa//878v6BzQ3rue2TScMrrpEL/TEIpxbv68nR7mr1Bwr4g4WBsbu7umgAAIABJREFU\n+PXuHOtzHu/uz9PmaPY0YvY2YiZiw1u7c8s2Vs2HtXbBMvvudP/d3txXT05LI9/986Qgi5+3oxEz\nnRg6XT27Le8oEmt5sLZ0vNuByHBmwcNVikpsRHOL4rS8Qwj87kCBBNiXnnvDSDrfXVWRrLTMq24W\nXSHC356ssyHr4MxLLfS0NNPtCAyn5WR5pZJYKikZPrPg8bNySGih6MydQ7urqSSWicjw7v48VWPZ\nG8TsDcSp4/cGCgxmHN7Vm2fG2DRFUIjtewcKtDoOW7IOiZJ0xYYR+7nzix7jR7k+bMxCPfZIaNiU\ndYksTEeG6cjQ7orG98bpiDZHY1HUIkMtMhSUQgP3z0sfTJKEJDn8ZGjxa7uzEc9W8JujUMh5/PtE\nQMFReOmygVKKAU/zcC1mat6kZ7Ge/PSCx6s7suxP0w73hYZ1GZc3d+c5q+jxio5smoSYsC80bMx6\nvLF7eTubt/fmuaw9w4HYimY+NmzJufzpqlZWXyRpqjN75z7T/WfCKW9a/tovhx3XQ0v/wntg6wr5\n/XLfZ5tfBSsvnEusnd4Lay4R8rzlqjTxtXnP3SurZk+GPB/1d+nzHEveAa217wRQSl0PnGKtHU1/\nHkDs6351EQRiB/eudwmBiiKp1pZKQqQP14Wu9Zw2eql9FovirjE1JSyqo0N8pJdL9QNxpPjEJ4Tg\nWStV7Cb527xZtu3aJdvWr58jeCefLNXknTvT9ed1su3HPz78caxdOiXR2jmJxxKoT8Ij18DwXVKF\nXPdS2Pya5S244uoSFT0lHpvLoTImzROj98gx1l8uxGzZSkC1ulAHDnPmsUEgDYAXXCDkOZ+Xpkyt\n5bosfl6z8nKE67LnNvjJX8DENqlKnvobcOGHFsoZno9wPDjnt8U1ozYueuFiv7yVotqh1nOOJ++h\n5wqslSXXbdfJuLs3wylvFtKcaRVXkZm90tzTuuL4We0dCe2u5uyCx96gQSWxnFv02JSTN1+Hozm3\n6HHtpGijz8+7bMgd+Y0ZGsuPSgE/ng4IjOWsosdVnVlCYw/jYSGyhqoxNIzlh1MNbp0JiAycU/S4\nqjNHaEUu8lgtYihIMFZCQIquor7MClSQEtQBT7EjEKnEoKfoTBPz1mdd/sfqVnYHCRZYk/oz315e\ngpArSQNsczWn5D1KsU2voWI4NNQSw6qcyzmtPsOBELpVGc3+SDTAkWkGlSRoYFXGIafFD3tD1mVr\nzuWWmQAHeEmbS08a3rIm67I166aOG3BWm0eP53CviTgl79HlabanJPT0vEvRcwiPwHIeq0X89b4y\nD9ZifAVXtGf58Ioi1cSS04p6YtgfGVyl2OwqfKAcG2JjOJjMEd1sbOl1Rad9Y6nBnw7NsDc0eApe\n1ubzt+vbKDoOw0HCdybrPFyLKTqKS9szvLQtQ83OBbU0X8osUtkrxdJMuuAlUBJ2ExjLnTMBnxyp\nsKORUHQUb+jM8rsDBVytObXg8ou65uFqTKcH5xRcio5U9X+tK8eL2zLsDyXIZ9DXSwbYNOFqzcfX\ntbOjHrOtHtHnOZxVcGcr7APnSHrfxKNQXCFWde4yissjIapBblEWl+OlGupFkq8Ff+NLCuqBh6Wq\n3DIobhrN773z3wflUbHIPNpwLmulH+Oxa6E6JkmxJ78Jeo8i9+35iqPpuFrVJM4pxoBjDJ99nmDt\nWpFxRJGQ0S1bpALcaMBLXiLbgnnMzhj521NPXXqfTX/lOJal/54eIV9JcnThKp4n4zjppDni3ITv\nz21b7Jnp+/L7LVvmtm3cKP/OrxzEsYzv1a+WT9J87W8YyraLlk5xiBtw+1/JB7A4ILqr7f8Jd39+\n+Zls72lCkuf/TRyIjmy5pqxgRpKT9j8gdml+iwRaPPDPSz8HEAePSmXhAatVeX1XrpSfW1rmtMxN\ngnzFFfK8+RWQcnlhouJhMHo/XPfbUiEoDoJy4eefh5v++xHG+TxCsU+8jJtNLkqJL2llkelLeb9U\nTZ4r2PFDSR9UWlw1ZobFQmp6r2xXSn7fu/WXR5xBlsWvnWzQ7zuckncZChI+OVyhFBu+OVHnO5MN\nBnyHk/MuOxoJnxypMB0vv0Tyb+M1vjtZp9WRVLoHqxGfGqnQ6Sq0EuLThLUSYHJy1uWfD1T5YalB\nm6Pp9zX3ViI+NVKm21E80YjZXo/JamloHA5iHq5GrM0urZdZ5WnumAnYFRhatKJNK0Yjw0/LEtQC\novvelHPZnHPJpBXOFxSFacTzxtlcrr+0PTvLW7o8TVeaJKiAF7T4gMJTig05mWjolOydU/B4pB6x\nN4gpaPFY3pmGrgy4mk+PVLivGrEp57I263JTKeKL+6vUE8Onhys8WIvYkndZnXW5cTrkS2NV1vgO\nD9YipiLD2ozLYMZlR5Cwox6zapl0vtEw5r07SvyiFtPjKgqO4tuTdf5wV4k+T3HLTMDByNDqKLIa\nHqnG3FuNWOUpDswjziDezftiUNbyO0+UGA4TWrXFU5bvTwVc/dgUE5HhkyMVnmjErPAleOaagw2+\nPVFnc9ahmhJnlT7qQGDhNV0ZphOzoFJdTgwdrmYsjPngrmn2BQn9rsIBvnSgxl/tqzASJnxqpMJk\nZNmad2l3HL56sM4Npbnv5XZXc1LeY0XGOSJxno8NOZdXduY4p8WfJc6TT8DtH4e4Bn1nSrHm7i/A\nnp8c9W4PwYrzhajOR2U/DJw9V40+HB74V7j5YyIFa18n7j83fkQKV020DMg992hTbffeJt/VJpJ7\nVm1CrDYntj/583q+4GjI841KqR8qpd6hlHoH8D3ghuM7rGc5CgV4+9tFw9xMEty1S+zKzjtPlvb3\n7xeHjtFRkWRcfLEQ1KXQ0TGXWrhvn1Sch4bg5S8XYv1MYuVKSRPcs2duPHv3SlDLK18pj5EROcf9\n++U6vPWty57f/gegPCa6Le3I7LhtLYw9KEtIS6H7JOkOLu2S2fL0XtFvnfGby4dp7LtLCHTroBzP\nzQrZ3nP7EZwbmh7Vu3bNvYYTE/Dudx868ZiPt79dzn94WGQdw8NCpj/60WUbPu/5e+HbhW7h4X5e\nSORj34Lac6jK+nTjlDfI61sakhWE0hBkW8Xi7rmAJIRt3xG9ol8Qopzvli+9HUenbnpGMB0bbpsJ\nWZVxZlMB+3xp4Luh1OD2mZDV87b1+w7VRLySl8KBKOGeSjhbxXWUpAFOx5Zt9YS3dOcYixKGg4T9\nYcJQaHhBq0fR0TxYjVntzz1vMOMwERvuroa0OhK0UjNSxbVK0eooqvHSpedHGjEGSc9LEDcHLyWz\nv1jGbu/Ugs9rOnKMRYYDoTz2x4ZXtmd5eVuGy9qz7AsSRkN5DIcJr+jIckbB4+VtPvvS34+ECSOh\n4arOLL4W1w+LNBHW0ti/NkdxdzXiQGRYkXFwlSQvrs5oHqtH3FBqcDBOGMyIVMRPUwsfrsXsDiLa\nHIVRiqpJg0uUotXRlJepyF9zUJICe32Nk2rBBz3NPdWYH03VcZCAkyit+Ge0opIYrp8+/HKfAf7H\nvmlia2l1Re/sa027A/fVYv5jvEZgDL2eg1YS3LIqo7llOmQyTmYnI82GQRASvcp32ZT12BMaDkQJ\n+4KYSmJ5W0+OrxyoYyx0ehqlxQWm19NcN9ngPydktbbL07MOMYO+ww9KwYKJ29OFbdcJYc51ymc9\n0yL38Ue/NaeDfrLY8msSslLaPXcPdHNHloLc8wUJP8m2yXdKtk2KRz/77LGNwxo5j0KfnFfTGcgr\niP3dryqOxm3j99MGwYvTX/29tfZbx3dYzwFcfLFUoO+6S+QYZ50lASZaiyfw2rWSpNdoLNy2HC67\nTKq+P/uZVKrPPnsunW8ZWAsHHxM5hDWyXNS7dfnZ6bJQCvuGNzGeO4/h6/ajXMWKNw7QfflqCSj4\n9KfhFa+A666TivdrXysV92VQHgbncGoILVY87WuWGIqGs98tXcb775ebx8rzZfa7HGb2HLpkprQ8\n6hPLhHB4nujFH3pImgDb2kSmsVwsOUiF+ZprJJDm1ltF83711cuvNgCT2w/12HR9eR3L+yDfefjn\nPd9R6IWX/r9iWze9R94fK84/cvrgswVBWVZbFld2Mq3yZXgkPFQN+cZ4nf1RwvlFnzf15JcN2Whi\nJEy4qxxQii2n5FzOLPqz1dTDYTI24q+76B6T04rt9RitZJ+P1mIaxrIm49DrafYu09w3GRmUUkwn\nluEwJjKWPk/jpft6S0+eVRmXeyohDWM5rSCphQ/X4lnbtfnwlGJnI2HA1+Q1/KIaE2PZnHMZ8DRj\nkWheb5oO+e5kg9BaLm/P8urODHsbCfk0RnoiEs+KLlfTMGJHZ4zhR9MB35tsYIHLO7K8oj2DqzUf\nXVlgXdbhmpSIvb4rx9XdWZRSvLrdZzwyfHuijlbwus4cV7Z5KKV4XVeO0wo+D1RDFHBW0WddxuGG\nUsAa36HhaXbUYxylOKkgjYJDQYLGciBMGI0MDiJLUSh2NBKwlkdrETsbMQ6KLXkXF8uuwLAx61Ax\nUsX2lGJL3kNrxWQsUdkP12IeqITktOK8Fp+1WZfH6yLxKMeGqhEnklZHo4BHG4ZOR6z2SonFVdDv\naSIUY+FCogtSgbPAzrphsSJOa40yhvtqIR3uwhWC5ntuJLS0KvGLDhCf5xZHHF92BQlX9+T47EiZ\nOyoR3Z7md/oKbMl77GgkFBZ9JHytSDA8Wo9pWeQRndGKODKUE0PmaLt7jxLTe4SwLhhLQQhv3JDm\n9n13SoW6daX0duS7Dr+vJvJd8JI/k6TA0m6ZiK98gRDYpWCMVKeLgwt/n2mRotOxIA6gPnXod3Sm\nda7wVTsohanyCHRtlnE+V+7Vx4qjUlVaa/838ByJLngGsWqVPA6HNWvk8WSxbt2TtjZ77FsSOOHm\nhJDuuhk2XAqn/+YRefdhYS089DXFjuvX4eXXYQ3s+hpsqUpFEK3nKtBHiZaVsoy0+DjWHDlNTmnx\nC+5bWv1wCNrXwdCiwAlrAAP5IxwP1106JXE55PNSgX7724/6KV1bpLFjfoxrHIos5UgThOc7Mi2w\n/uW/7FEcGzKth08fbEzDqiOk3P/nRI3/Z6/o5D0F91QivjPV4J82dtK1zFL8g9WQf9hfQwO+hp+X\nQ24vh/zeQJHsEgS6K62EJtYuINA1Y7kg53HLdIXH65KWp7EMR4aihsvbl15N6fI0+4OE/VGCm1Z5\nh8MEX6vZIJSVGYeVmdwhzzMcao0XW8umnMO3JhrsacQ4WvZ5XyVil6t5ey/81XCF/zhYx9PSvHZn\nOeRHpQxv7spQNZZyYnDSsRyMhURvyLr82d4y10018NKmt9tnIn5cCvjE2la+Uwq4sxyyIW2OvLMc\nUnQUr+3I8JE9ZW4shWS0EMe/2y+ShP+5tg2lRAayaZE2vM/T7AwSKol4MRvg4WpIp+/wykyG/5xM\nqBiT+jTD7kZEt+dweZvHV8ZDpmKLixxvKIhZlXG4oiPD96ek0dFVihiJJO/xFB2u4stjVe6tRBQc\nRWLh5pmQt3Tn2JR1+P6UQSs1G0pSihJcBVtzLvdWLAbQKaHdHRgKDvS6sGtRI2KzsLolr3motrDM\naow0aJ5XFL/sjnkTwNhaULAu67Av1Ujn0rHUErHcW+E7/NYTU+wLE7JKUYoT/svuGT62MmFj1uHW\nmYT5HC00FhfFaQWX+6oxxXkcOTAWX0tV/ulGxzrxYi72zRtLBXIdol2+7S9kJdHLw8jP4YnvS/rg\nke7xfvHJOfBoLTLFYGbhd0pQFtJ+LHCzQuTDykJCHEwLUZ7aJZLMJJR73vDPZHXt4j/55crRjjeO\n+C5SSl2glPq5UqqilAqVUolSaomusRN4plEZk+XhZlJZsV/E/LtuElJ2LJjeIzY5zYSilgHZ/+PX\nHapDPVr0nyGNC6Uh+ZBFdZFiDJydek4+zVhxvty4pveKZ3BUkw/5mhcfecb/TOK835XGwOoBmVwE\nZajuh61vfn7feJ7vcDyRmMwMyxeZSeSzqpR0vS+F0Bg+MVKloKHP13R6mhUZabb6yvjSjaextXx1\nvE6HK1KHbs9hTdbliUbMPZWlJRatruYlbZIGWE0MsbWMhtJ8dV7RZ08gVcmchqxWZJDQjNFwaclD\nXivqxpJYSzZdoldWbNhyy1TBBzzNOQWPoSChkTbXDYcJPZ7DhozLaJjgaZWORXyFp2LDw7WYayYa\n9HmaXk/T7WkGPM0dlYCpWEhZZKWiqREdc9PN4btTDfrc+c8Tve/3SwE3lgJWpil0zSS6m6ZDrp8O\n+fF0QL+n6PY0PZ6m39X8oNTggerS1zrniPRBYcmm52BTV44OV1M2sgowuw1F2VhqCUxFFh9ZEchp\nIbyjocFD5BoKm27TJNZQTWA0TLi3ErEm49DjSUJkv6f55kSdzTkPg9j2OUquiwTiaAZclzjVTzhK\nrpsBYos4iSyBPxpsldTC2JAYQ5BIiuD5BZc3dOcpOBIJHltLNTHsDRJe3pbhFR0ZUMweEyvyml5X\nc9N0g72BpPp1epo+XxIU/2a0xm/25nAUHIyM2A/GhgOR4bVdWa7syOEgEqLEyuRpJEx4ZUcGf5n3\n4LFi81XSm1Mdl896Y1o+76e8SXp76iWp3BZ65gjzL772tA8DgPPeJ/ec+pR8p9SnhPie//5j259S\ncMob5TuqUZLzqx2UwsDmq8SLWrtyXoUeOc/q+LNLnnY8cDRTsM8CvwFsRyaGvwX8/8dzUCdw9Jja\nCaiFzgwqrYZMPnFs+5zcMbefJpqrXEdrD7cYbkaS19a9VJwH4jqc/AY45z3HVh0/EvyizHxXvVA+\n6CaG098Gp1/99B/rqaB3K7z2n6HnZBmn48EFH4YX/+kve2QncLSwVj4Xo/ctTAFb93KZHLlZmXR2\nbYaL/5s4ayyFJxoJ5cRQdERaUE0ssYEWR3HbzNLeY2OhobooKRCgxdFHTAN8bVeOt3TnsEi08pkF\njw+vKLIzSMhrJIYYITetrsg2fp7uM7aWx+sxv6hGs37Je4OEtVmXrXmPijFMxob+jMOZBY9djaXl\nHkopru7N82tdORpG4q4vbPH5wGCRh+oS792VJvdVDRQdRYej+WGpAWnlvJbINUMptFXcNBNyYYvP\nppxLw0LNwuqsw4tafW4rRyiEGI4ECSNBQnNKcEupMau/HY8SxqMkrbBabp4OZgM7JiIzKwcBuDtN\nEZyMDddN1vneZH32uuwJErbmPFb7DqU0uW9D1mVzVqqkW3MeK32HUiLbNuUcNmUdbi2HdLqa1jQl\nMbTQ42taHMUt5YjT8x69nsNomDARJWzOeWzIOdw2E5LRakEV39cS+/1wPeYlrRkGfIdKYgktnFbw\nOLfocXctYtDXtLhq9nr0+5pOV/Nww7J4zUEjxGAktnx5UwddGsZjmEngla0OX9nSQYer+dBgkU2p\nZKQUW36jJ8dVnVkaVvGyVp9WRxEqMAq25hwuaHG5qRRQXCS/KLqaSiJV88+ub2fQ0wwFCXVjeU9f\njv+yoki/7/DhFS1syrociAwZpXhnX56Xts010x+MEh6qRuxuxJin6L/WsU6+b9rXyGc90wIXfEDk\nhiP3iHzLzUyTbd2Hl50k32MZf1QKSQAmnCau7iMJpo4qQXE5nPpmuOzj0mNROyiE9spPw0mvOfZ9\nrngBnP8Budcd+IUUdi76YymsTe081BWk0CNyk+czjla28YRSyrHWJsCXlVL3AX98fId2AkeDpWze\nFMeeV+/nlwgcUk/NeifbJglxZxy9quEpId8teumz3/3MHO9YseI8ePM1R/67E3j2IZiBu/5OJqpK\niTRo/aVw2ltl8rnqhfI4WrSmy+u7GxHRPC8qF0lWWwrZpZICjT3iMrWjFC9pz/KSRVKMvToBBW1a\n0T7v2GOh+P6OhAlfGK0wmdq1aeCN3TnWZBxqxjAcJGgUvoKxlGAWjzAWXyuu7MhyZcfCsbQ6ULeW\nscjO2pmNGktRC4GOSNgVxDRzRBTgomh3FLtji7EiAWhuqyfQnpUq6Z5gjvzuCQ2tWiryI7WIx2ox\nsagLcBT0e4qBvEclMYxFZlayoIGClsnKNQerfGK4SpQ+z9dlPrayhVZXM51Y9kdmNhJ8OEhY4Tu0\nOorp2DAWG3ykIr0vNAz6mpW+JrDi9uEouTdPJxZXiTTj3krMjoZY7WEtd5RDzih4nFfU7GwcukJg\nEaeJijG4WrE6I69taCVMpsPVYk83r8psjWV/bGh3FCMRzP9qURasgjYS/nh3md3pIRPg29MJLxyv\n8/a+Ag9UIx6rx7Q6Is+5dTrklLxHUStCi1TGlQwwqyFA0+7C+KKGUJOm/BUVfHGizlBoyDuaCPju\nVMgVnYZ1WQlVee/AocJbYy3XTNS5ZTpMJ0+WdVmX3+krLJtaeCR0boQX/dGhv8+0JrT13UXbwC5A\nXsDadD/1gxeBcmiM3Ulc2S3bsDj5AbJ9F6H00QURHQ6nvCGVWD5NiGqw+0aRauQ6JABm6BY47W1S\nuDPxQgvYJJSmwuczjuadUlNK+cD9SqmPK6U+dJTPO4FnAN0nyyx3vv9tY1pIde+T0AjPR++pQqAb\n8wID65NynJ5fYV/HEziBxXjw36Ty0rZ67vHED2HvHce2v5UZl4KjKBvwkVQ8B8t0Yjm/Zekv0y5P\nc0reZSSas/UKjKVh4MLWY/sSPqvgsjLjcDC22NShoGFEC/v6zhz/sL9Kw4hX8aqMQ4+n+frBOrG1\n7AsSKok0frW6Ck9JQ9vAMprt5XBOQTyVYyvOGb4S0lZKLJd1+NSThSmCxlrKRhoHdwUJkbW0uopW\nV8jLriDm3LzLVCJk0mWukjRt4Iy8y85QUuhaXUWLKxHZuwLDi1p8po1U4ZpjsRZmDPQ48PHhKnkt\nFn39vsYH/mxvmaxS7ApitGV2LJG17AwSTit47EqbBltcTaujCBLLrkbC5W2SWmisaHYzWtFILA1j\nOTXn8lg9kcQ/RyznYmu5vxJxSas0MDbjxa21jEcJfZ7mjLzLjkaMp2QsLQ5UEtGmv7U7h4HZRENr\nLAdjy4Dv8OYu8dxuSjq0hRCJtb51JuKRhkEDXvpIgI8MlXm4XOfbE3X6fD2brliKDf80VhMteCMm\nq2Xy2OLARGyZSQxX9+QJjCVclOq3Ne9wby3h+6WAXleu9aCvGY8Mf7J7etn30r2VkBtLgUxMMg6r\nMy57goRvHFw+tfBYsfnyJ8i17CCsdhDVOwjr7TjOKFte+QBJZRtReRfK70BnOlB+B0ltlHDyoeMy\nlmPFI98UTXfbmrn73O5bYO9PZTV5Zt+cq4iJxcpu/WW/3DEfbxzNnew3EdnT7wNVYBXwNM5pTuCp\nwM3AhX8oFeHSkOiVlZKl/+W6cpeDX4QLPyyVs2Za0vzjnMAJPJdhjWjun2pSVlST5p/WFXPSI6VF\nU7/75mPbZyk2bM659HqaqlXpkrrilJyDnechnlghT/OXeK/uybMh67IvlKrvVGx4W09utuHtyUJr\nzd+sbac/o9kfG0aDhKqxfHCgQK/vMB4ZujxNnFYsfa1wFdxQClidcen0JIFvOq06n5R12RvMVRGb\nzzscDoYxw/OqpndVIjpdha8lfjowcs3bHbirHHFO0SerJa2vmkj1/Yy8ZnsgjWV5R1OKDFNRgqth\nU87lW1MN/FTvG6cPjZDh66YCNmVdsloxGcZMhjG+UmzMudw6E9KZ2uaFRh6Ogk5H8+/p5CHvCIE3\nVmKsQyv66k1ZF0fDVJRQiqRiuiHrcF81YnPqCT0dG6bTcJCNOZcdQcwZeUktLCeSkph3NOcUfW6c\nDmjToJWiYUR+kXc0OUexvZHwW3156gZ21COGGjFdrsN7BgrsCw1bsu6s9KSUWDo9qUL3Zlz+cLBA\nLY2tHo3E0u5v17XT6jmclFEkCupGmgnzGi4o+vzHlNjYNd03LEIcIuCTow3yjsJNX3djLT2p3OLR\neszJeZdGYpiIYkpRwqCv6XAUZ7X4vKMvL/HggYxlQ9blL9e28b8nauSVrJzEVj7PPa6c9970vWOM\noRQbwnmfnZ/MhHS4Wl73dCwDnuaBakwlefojXjtWb6M42EJQUTRmIJhR5Drb6N2yg2hmG9prmV0t\nUkqhvDaimSewdm7SY004+/MzjSQSv+rF97lCL+y6EU5+Pay6cC6xsDIKp7xeJCtPFSYRbfWzMdXw\naKzqmm1ndeDPju9wTuBY0L4GLv1LeeNak3opP8V0us6NcNlfz5Hx1lVLJP2dwAk8R2CtkNrHvi1y\ni0IvnPrr0rR6LDBxelNfpNlXTpoCdgyIrCWnNa/vynEwEhuxXk/IV4RUFa8vBdxUCmgYy+qMwxu7\nc6zPurS6mvcPFBiLDDUjlcLlGvSOBiszDr/ZneXayZCasZzb4vKS9qw09FnLj6YakvgHdLiKk3Me\ntYwEZHQ4iqlYtNKdjtjFhdZSN5brJur8tBwSWzg57/KGrhz9vsP2WszbHp9gKE3n63AVf7mmFZMG\nj/S6zFaLW7WQjbqBLk/xtu4so5EhAQY9zWgkEwwFVGLDcCgkvt8z9HuauhGHjYKSoA+QZLsIqMeG\nBMWeIJmVpXQkCZ2OomEdmjLcZntgsxmx2Sg5GoqrhkK02cY2x2Ipx4b9kfx/BTDgCfHNakWboxlO\nxA6uw5VzbhjozQix3hMkOAo2ZkXqUTPix+xYS2jleFkUCaKNtsDeRsxjqcVd3lG4ShGmDiSPVmMa\nyFu4Qyf0tGkiC5e0ZdkTJPy8EpHTitd0ZliVcbizLGPZE0RU0+e1KSi4mmZuznyFfarCoGIMfqK4\nox5SikV+sjbjkNPQMA61xLInNNSMuGyEJPS6Qopf3ZljMrL8ohbR6kqKYI/nEBioGcO+WkJo5fp3\nOOBrTd1YfjhZ5zOjVcaihIxWXNUhCYqBFX/zB6sJlUQkNOuzDp5Ws7KfpxcxXVtc2tdJiIqTBTen\nsaHBmhjlLPZUVWBlkhmVhwgn78fGVZSbw+84Hbdl/ZMKdXmqsEZI7GJiCnnRAAAgAElEQVTrW+2K\njZ2bhXPfK02FjdKcH/RTgUmk4fDx70mRonWlJO8+mxINl6w8K6UeUko9uNTjmRzkCRwZSguJ7lj3\n9MU6a0f21772BHE+gec+dt8M931JVlHa10ha1p2fgvFHjm1/fotEbdfmhe5YKz+vuvDY9tntanp9\nTSmx9PgOa7MuOa0oxYZzW3yunahz3YQk9630NROx4TMjFUZT32WVBpmsT5/3VPG18Ro3TktV9Nyi\nx0Rk+dRIhaKjuLsc8kRdltuLGqYjw23lgM1Zh92BYUdDmvy6XcV0ZHmgGrHG13x5rMot0yE9nmaF\nL57HnxqpMBWEvPqRg+wODBkgA5Riy/t2TtOhpYmulEils6Cl8jkZGy5ty6BRRChWZFxWZ1xUavf2\nwqLHHeWQ4TChoC0t2jIeG+4oR7yy3SdKrdiaMoMQcea4tCPDreWQydguGMut5Yhz8pr9kaFu5+Qe\ndQtjseGKdp/p2FKOLb4SR4/p2DKdwItbPO4oR4zHhhZtKWhxE7mjHHF2weXhWsR4lNDlajpczVCa\nqHhOweUX1YhSbBjwxTljT2DYXo+5tM1nMjbUjSWvNVmtmYwNZWNZ7Sn+YEeJoTBhpafp9RQ3z4T8\nwY4pjEm4oyLE2UvPYdLA9aWANkfxqZEK47Hh3KLHlpzLj2civnqgRkbBT2YiAmTSkVUwnMBPpgNO\nzx9KJ5pc9M1dPndXQiqJpcURTfOj9ZixyNKmLT8tRwRGJi+eFWu8OyoRxlo+PVKhbiU2fm3G5btT\nAddO1NmUdRgOLZGR1QJHwYFYJjATUcxH95QpJ4Z+V1PQiq8frPMXeyus8TV3lUNCY2h1NJ5W3F+N\niIzIRp5uuMV12KiMm4VsZ9qLFJVx8yvwWmTbAkRl3MIq4uoIwditgEVnOgBNcOCOVB/9zMHNQN/p\n4h4yH5Wxhf0c+W4puj1V4gzi7PXQ12Rfbaul2HHHJ47OI/+ZwnKyjVcDVwE/SB9vSx/fB/7z+A/t\nBE7gBE7g6YE1sO1a6Q5vNtJmWiXYYNsxpmQpBWe+QyaWpSGxpSvtFleNtU/Cm3XhPhVv78kTWXGt\nGAkT9oQJW/Mep+RcbpkJWZkm9yml6EwbnG5bIvntqeBglHB3JWJVRqpySim6PYeGMXx3ok5oDFkt\n1cHAgtYKD/hZOaDDEQlHNbFUEkgQWcDuMOHhWsyqjDSlNRMNK4nl4yM1Soklh/jV6tSyLbLw2f01\n1mUdEivpglUjDW79vljF/Xp3jgORYV8QMxwk7AsNl7VnOBCb1PdayHWEVF4dBXtCy6qMJknHH1qp\nkvd7mp1pE6GXuj8YJbpegG9OhGjkyzO1jp/9eVtDUgIjZIxVAzESLvNwLcJVcvzmWPzUl/recki3\np7CIVKeSWLRSdLmafWFCp6dIUFSMbHMUdLkKayWAJrSKihHHFasU6zOa66YCasbSnSbwuVox4Gq2\n1WP+Yaw6q/VuSixc5Dr8r9EKdWPp8SS22ksTDe+phnz7YE3SB5XomW2q+a4mli5XL16EAYRkH4zF\nrSO0UDFQTSCjIO8ovl8K0Aj5NSrdJzCVWK45KAE1na4kBWa0YmXG4daZkPEoEb15Kp+JrIzLUfCP\nYxJe0+bKuWe0os/TfH+qwVgo8d6BhbIx1BIrjayppeHTDb/9ZLTfgQkmMeE0JpgEx8fvPhuvfSva\nb8U0mtumwMnid51FNPUQuAWUIw4hyvFRXpFw6pnXQ5/2G3LfnNo9d59rXwMbr3j6jxUHsP37soLu\nZtNEww7QHuz40dN/vGPFkjXKplxDKXWZtXZ+WsR/VUrdC3zkeA/uBOZgrURZ77lNlotXXgCD50iV\n2Zp02+2ybdULZSn6RLX4BE5AkITSSHtISlaLpGIdK1pXwsv+HEbvEW/Tzo3ScOssjlp7ElibdfnT\nVS3cX42Yig0bcy5bcmK5hYVKYtkbxCnBEcuykbTyvLsRc3s5ZCoynFZwOa+YIZ9W034yHfDv4zWm\nEsMLW3ze2luYJd+Hw3RK0oYaCQ/XIgILqzOaFb7D4/WYjNZ0OoqDkVi8tTvikbkjMHR5Dl2e5rFa\nTGAtazMuna5iT9pQdmiKIGyvi07VNklM2pSmgH1hwnktPit8h4eqEQmwOevR6ykmYriyzeGbE/Dd\nyQaJhYuKLi9uLXDdZEjOEW/kg5HoCjpdTWAse4KY81synFkQr2hr4aS8S07BrkaMo6QSGaZyBF/D\nTGLZFyX46c/NTJC8FrnC7kbMGXmPswoeO+oJWkkYSwLsCg05xKFjKpV+93riyzwUGlb7Dt2uZUdD\npBlbch6OUgyHhjWeZtgmPBFI+uCpeY9OB/ZFlrNymvttzN4QHCxb8y7rMpqd6X5mYpOS8bkUwZFI\nJB4OovVWzFXeH65F9Pman8/E7AkNvoJT8h5ZrRgKEzxkkhEgTZstChINeyLY4MH+GCqpjGLQU2Qc\nzRNBzJacw7ZazN7QkNVwdtEnrzWPVCPyWkhSI9WPFxxFzVgeq8doZfneRMBoZMhrzdlFlxZHqs7r\nfUWoNOVYPMC7PU0ptuwKEvKLmLynFQny+r2gxaNuYCo25LSs1oynMqlj9YGejg0/LYfsqMf0+5qL\nWjP0+w7KyZJbcTlxdRgTTqG9FtzCyllSnOm7hGD8ZyT1UZxsN5nu89FeERPNgM6Q1MawSQ3l5FB+\nB8RlrDXYuEY08wQmmERnOvFaN6K9I8f6VQ/IKtz0HujYAGtfPOeMUdkv22b2yb1szSWyrdgPL/v/\nYPRe+Zv2tZLd4BxFL/LMsOyzMgrdJ8HqixcGuCxGWJFVwcX7zrTIuJ4tOJoFfqWUepG19vb0hxdy\nwm3jGccj34Bt34NMUSQaI3cLST73PfDQv0tiUaZVbkAjd8Oai+Hs3z4+HsoncALPNTgZ+QIIZuRz\n0kR9Ury2nwoyLbD2JU9tH4vR6moumedJC0L6SrHh3kqMpyVRbjwyWCwfHGzh7nLIlw9U8dMK3aP1\nmJ/ORHxgsMjXD1b57GgVVykyCr5cq/HDUsA/b+5ckkD3uJqHKyE7Akme0wrurSQ8omP+aEWR7001\nKBuLRiq5pcQSG8sb8y53VCIOhAm+1vhaXCb2hYpLOzLsChKMlcpqE6G1XNDqcUs5om6F1AEkViqc\np2Qd9gbSUNbmNgmgYSKBd/mKyx6Z5OF6MvvF9IOZmIsfmuCz61ooJ5aZ2OCmxzsYJVgUpxZc7q3G\nbMi6bMzJbMday97QcEZec/NMiLaWXGqv12zYPCXnsLMuqX5eegoNI6T/9ILHrsCwwtesTC3gZJ8J\np+VdvjUhxNNJxcDDKTk9reDxTwfqNIx4ElvgoWpEh6e5st3niwciyolIQSILd5RDBnzNFe0ZPl2O\nqSVzzXn31mJGInhnX55bZ0JclVrcGZiOYhyt2ZJxOBAnJMw1+IXpv+cVPb50oC7np8Xmb6RkWJvR\nbMloHmvMNa5ZYNqCY+G0vMM3JmKwkEst9cYiS6uV5sRPjFQI033OJHBTKWBL1mFzzuWm6RAvfY8Z\nK1IXR8GmjMPfjFblmgHVxPD9qZCTcw7ntnjcPC369W5PXqPAWDwNp+ddbi9HC9IHG8biazg973FP\nJWIwDcABcRYpOOqQSO+jxURk+JuRMjOxocXRbK/H3DYT8v7BIuuzLkq7eC1rgIWzdxPO0Bi5HpuE\nKDePCUs0Rm4gu+JStFcU1w3lSCUsrkJ9DK9tCzaaoTb8I7CREOzGfqKZ7eQHL0Nnlk7XKg1J2mES\niTHA+CPS9HfJR6WJ+ra/lALc/G0Xf1SSE/2C8Iong4Pb4Kd/Lf/3CnDgYdj1YzleruPwz8m2yd9G\n9YVWvI0S9D/J0N/jiaMhwe8GPqeU2q2UGgI+B7zr+A7rBOajMgbbf5AmFPWKtqhjPQzfKdXmndfL\nTLDQk25bJxYyxxpocgIn8HyDUpLaWJtI07ECqaCYGDY/hfCAZxKuEolAAnhKzUZKy1Kz5esH6/S4\nkiTX4WpWZxz2hjG3lOr8w1iNzjRJr83VDKaphd8Yry55vMjAaGxwgYxW+Eos52rGUkkMba4mSDus\nFOIprZXipJyHFMlFuuGpuQS7Xs/lolafocBQTgyNtAI84Dtc3VucJV1NOUST3L22KyvOHEr26WpQ\nWEIDd5YDHqknZJlL58sBByLLTaVoVvohIxLy6iq4sMXn9DTRsJqY2aa1TVmX3+vLs9J3mDIQJGla\nnoEBz+GD/Xn8pmwhdXlIEBnCGzoybMq60vyWSJLeUGpFtyrjSPx4ek66+XoqkTaEaXOjq1OJiBJX\nkanIUElEC+wrmYy4iJ3bz2sJtUSqYJ6WariDhJR0OY68P4wM0mKJlNgHvq2vMOsy0pRtJIh2PZcm\nRHpYfKVn7RL3RwZvXlU2HeIs2hwJYFHp693cZozlQCipkRkNGaXJpnKV4chyUYuPUmnCoBHyHAN9\nnuKhekhk5T3kanloYGcj4W09eTIaDoSGwFimY8N4ZHhLd473DBTx1MJtB2PD1d15rujI4mrFaJgQ\npGE8+6OEX+vMzk6wnixuKDWoxpZVGZf29POV0Yr/OFhfNvQknPoFmBid6UC7ebTfjlWacOJ+Ic02\nkQuq0pZUKxO/cOJBsAbtN5/XAdYQTj6w7Dgf/roU39pWCXltWy33wseulcRDx1u4LarD4989pkuC\ntfDgvwgRb10p+2xfI4mHy6UPaleSGSuj8rdxADMjMrb1lx7bWI4HjkierbX3WGvPAM4ATrfWnmmt\nvff4D+25jaguiWPDP1vowXwsaIrk58swlAK07B+1aFv6qj6fyPPkDrjvy9JEUHuK1/MEnn5YK/Hn\n++6EicfnPD+fTRg4Cy76SPqFUZOK8yX//VApx7MV45Ghw1W8oOinWmPLyozDBUWPR1J5RG5R5azV\n0dwyE842VVUTcVkIjSWvFT8tLx0n/WA9JK8U/RlHdMFGKuJ9nuaOSsjZBY9zWzwsQoxXZxxe1pZh\nWyNhTZoo6CshVOuyLmcVPHY1Yt7UneNN3VlmYvGDfmFLhvcPFBmPDFd2+Ay6c+S5TcHl7R67Q8uG\nrGZjxmEqJUmDnsPWvMv1JTkHNc/GzqaX4eaZgAuKPpuzDlUDZSM65xe1+OyPLO/sLfCyNp/H6wmP\n1CNe2OLxnoECOdfl2pO7uKI9g9IapTWXt2f4zildTFrNy9p9VntS6Y2A1T68rM1nzCjeM1Dg7ILL\nneWAuyuyz3f1FvhFLabX03S6iigliL2eosfV3FmJOSUvFoX7Ggn7w4S1Gc3GrFzrTlfR6mqqiTQH\ndqdynZtLgUSVp+ceGig4QjZvnQl5SavPioymaiAyitNyDucUPPaGhsvbfdrUHIFe68GVHRnuqMT0\neg4FV+LEG8bS62sKjuLeWkwx1SSDEOSikkrzbeWYVb6ioOSaWGDQhTZXcVslYsBz8JTYMdYSS78v\nBHN3kHBlmy8SFiWTgHMLDucXPe6rJhS1nE+SsvzW9LtuIrb8/cYOtuZdpmJLRin+aLDA7/cXOCnv\n8YWN7Zxd9Ais+KD/yWCR9/Tn6fMd/u8VRc4qeNRTN5v3DRS4IPVRt6lP+c/LIdvqEck88muM4a5y\nwFfGqlw/1Zi1wHuoFtHpLaRTHY5ibxDTWEZHndSGwV0otVBugaQ+RhKUcNs2ob0CyiZoN4/TthmS\nKlFtGLVIoqG8InFtZEmybhKpJud7Fv6+0CtyjInth0kK7IX99y09/vn7PviY3P9LQ/J9EJZFEpdZ\nJNEodAs3Wg5rLoYLPiQFwbgmQWKXfEwq4M8WLCnbUEpdba39V6XUhxf9HgBr7d8e57E9ZzGxXbr4\n45rcQJSSxLFjnTX5haW35bpYIg7w6el6fTbgJ38J9//jnNfjT/6nxI2uf/kvd1wnIIgDuPvzsP9+\nZruoOjbChR+UqsOzCT0ny+O5iLyWhrI+XzOQmZN0jIUJPZ6WxLtFcoggJYuRtQw1DPG8/Wng/GXE\n2Z2upLZVwwSrFFpBObFooMd1KBlLKTb0ecJmLDAeGy50FbsUrPIdVs/zmN4XxLS74u37g6mABGnk\nu6McMuhrVmdd9gSGg4noby0SLLCtFnNlR47hUsIjdZEaYOHuWNw7NuZEU1yZN2ELrRC7LlexoxHz\ncC2ZvU0+XjfERBS14nuTNf5muEqcbv3MaBUsXN1XoMd3+OKmQ2PShsOE0TBh0igKaYl1KoH9oSGv\nFZ/YO8M/Hqhj031+bE/MVJTQ6ThUE2l4bL5CE7Gl1YFuT4jwUGSx6dhvnI7YmnV4UZtPKTbUTXqr\nt7A3NBQ1rM67bGuw4HWdSoTc9vkOt880GA4tDgqrLNsaBk8bXqDhkWpEDbnWIFrlvYFhc8bhjiih\n3rxgFoYCQ5urWOU7jEcyCWjCGsO0UfS5sLthqds5i7oDCbQr6HUVD1WTOSJpYVsjocfV9GfkffbW\n3jmRq7GWkdDQ7iQcCKVK39xnLV2OGPg/7L13nCVHee/9raoOJ86cmdnZCZulXQmtshASQoCQQIAM\nBl4DNlwwGBxwtl/72r72NdfY2O+9zvbFNiaZYJKJNgZMlkSStMp5WWlX2rw7eebETlXvH0+fCaud\n0SKtUJrf59MfrU5PV1X36dP91FO/5/fzFXc0E4pGcXE1ABy7Istk5hjUcHY54N1bj0/KHQkMbx56\n6Is1dY6PjbfYUV/w9xwNNL88UiEAfn3PDLc2k5wOqRj2Ne8+tUav0UynUkDbReJENs9XD+lmHsoU\ncS5hgagEuFTcBbWPwuFVNi+61nGeHdO5rd+i87MpyissK2OntCgEZdFSv4a0I7zmaE5qQ7xw6b7C\nMvSKLjqzcP3fSNDcff6vuwjOffPx3QfTDlRHV25TKUl2jDyBaBrHYqXMc/fOqh5ne4K9Ep84yGK4\n4f/KDdi7SbJalWG446Oiw/xIMHC60DEaRxcCyPaUVL8+4xUSQDfHFva1JiVoeaQOg08k7L8Obn0/\nFAdl6adnvVTdfu23pLBgFY8/dn9dMhe9m6C2UShE07vhnlXL8ZOKXk/zzIrPgViCZBBZrsjBi/sK\nnFv2OLhoXysT7d+f6C8SKGhYR6iEgqGco2EdF6/gPri9YMTKGgnGQq0gV7t4QU/A0TijZRdcBAMF\n+6KMM0oiKXYkXnA7rGcWoxRnlzzee6RJoGBjaNgYGoZ8zWcm28zFKXfkhXthTr/wnKhiJJnl7rZw\npStaUfEUHo7dkeWyPPt9LBxwSTXk7pZwoUMlbRpgd1uMZP7iYJOyUYwEhpHA0GsUf3+4yQPHsbXu\noqQVP2hbDOLqV9EKjePeTsa+dsIHxtoUtaPmaWqeJlSOvz3cptfTzGUOnGSKuxOE2dQx5CseiB3G\nyRhDLe59d3cythUM9ZzvEeRZ38xB3cJFZX8+cO5SJbr85bNCUQ0JcVQ8RUVrUuu4u5XSso4DicN3\nC1QX6+C2ZsK2kqFhpf9uf2leqPqrQ0Ucik7XtdBaZi0M+ZqLK8Fxj2tmjkFf0c6LCD0WeNYzqeWV\nfQUS5+YdDa1zHIwt55Y9ruoriG50zhPXSKFiVStaGVw7G7E+MLnLpcdsavnY2MpUiZVwQz3m+rmE\nDYGed84cSyyfmmjxL2NNbm4mjPg6v180Y4nlHfvmeGFvyFS64ISYOcehJOOKnnBFKohfOwOXNHBW\nKkids7h4Dr92BmHfdlxSx7nF++r4te0EtTNxydyifRkuqeP3Li+ErBRsu0oK+GzXQj2R2GHbj4ly\nxpJ9sRRBb7tq5Wt21ydh9oA892sb5T2w/zo4cB1svgLm9ktmGiTR0pmBU1/6MF/EkwArqW28J//n\nN7rFgl0opS59TEf1JMbU/RA35SbqwgRCWTp8i/CJflgYH57z23DTe4TCoZQsZzzzF2XG2N03u0/+\nvjoCz/yFlTPWJ4qoLv09XhnEnf8u/XuL3vGFXvmR7/22/OhX8fhi79UyQVz8juhZJ65U57zx6aH6\nksUi5h9UH9vz/ak1JaxrcWszQSsIleJn1opJytBgCWhxSyPBOglo37q2TGA0Z5d97mrGTKQAUjx3\nfsnQWYFeczh1nF/2uauVMpFaSC2BVpxfNBxILBsDj3FtOZpkuDyoPbNo2B9n/NxwmY+MtdjZTnAO\nBjzNLw6XaVgJwjaECxcp0AqD4oNjHTzA6AXJsFxBjE9OdKh4CufEUAQHvtaEwGemIkIWCt668IEv\nT3fm5cu6nFqTR24fPNogsY6Sr+eX5gtaYZ3l69NtfmFElu66rnOVvHDw+/WYaj6WVr6vZDRFBe8/\n0sTiCLS0qYDQaNqp5ePjTQZ8qGfMX/eihoqn+OR4e8Ht0HWvi/z7s5MRA56ikTpy75jcylrzrbmE\nAKFJWJhX0AiAf5vq0OfpJU6OPXmx5WcmO4QyFxK3xrzNzMFXZiIGjATncd5o2SiqWlELfH57pMj/\nPdxiKneO3BgaPrCtxj8cajLgwVwqxznEIKZqFN+dSwiRDHnXYzJEzvfB2PKWtWU+Md5kb0eK+p5V\nDXj9YIl/HWuxvWDYFWUk+Vj6DFxUFXfFHk+DE/v6UIt6yf2dlJnM0ecpUms5HAs/v2cFZZkuvjsn\nFJkuFclXMjG4s5myq51QMwq1KLs86Club6VsKRhevabAl6c68ysjl/eEvKQvXK4rALzqKbisRTx9\nt6xUOAmo/dozAIVL20TTd4NLQRmCvjPxe0+Xg7MW8ezOfIVDEfSdhd+7bcX+Tn2J0Cl2f12+e6XF\n3GTjpUK1i5vwwDdyXr6ROpH1K2jWpxEcvAGq6xY+U0roHg9eDZf9EWQdeVejJBN9zk+LUseTHSei\ntvEu4FgPruN9tgrkBlxunumyZXacACrDcNn/yjPMWR6s5M+C6ii84B35Piu8oGPdgH5YNMfg9o/A\n+N3yQxo+V2760sDDHnpSYbMF/uJiKGTWvIrHHzYD79jV//zFvByl6KkCm8GuL0hBr02gUBOK1uiF\nj01/JaP42eEyM6nNM3p6XlrLU4qa0fNSb2WtqRiFc1DSmp9YU2Y6tbTz42YzOx+oHffcnGSbtxU9\ndDshQ/i5g4E3H6xNJBmHcsvtqlEM+KKb7Cuo5RrQmZUgqmQUrcwd9/moVF7YlisudO+bboYydQ4P\nxXAgFBQHBEpxJLGk7qFt5iUh84GaXrSj+7cZOT0gtx0HySpnODInCgr/NtHi3paQOs4oefzUmiKZ\nk7HOZmKHDdB2ll6jSBF1ivFk4dr6SmTiEgfOKVLr5rPFsZXESibxj4x50bmTB/0GhVEL/Xn5OVon\n6hK+lQBaIUFppuX8AqVYHxiS/Br589dM2l3MeE9sfqyFotF4WlYZNNDnyWQgA9aGPqGGdiZZ5j5P\n0+uJtrWvZJxpTt3wFSjkmoYa+nNJPwN4WtRjEusYz1LuaGWMJaLsUjVyH2VOrNQ9LRSXQMHpRY+i\n1qQ4HmjH3N22806SW0KxO7cOPjvR5J8Ot5jLHAa4shby++urlFYIojPnGE8sNzXSedm8zaGhaDTW\n5ffmcWCd4spagef2hEwllh5PUTUP/xJWShH0nY3fczo2baK90ryEnXNO5Om0wSURyvNRpgiI5now\ncB5+7Qxs2lpy3ErQBs78Kdj2MinGKw0s6N4rLXrOp71cssOL9y2L/Bl/bHJdabBWEofn/YxYeHdm\nJennFY7X0JMPy367SqlLlFK/DQwqpX5r0fYOlhB0VrEYfafKDRMvKmK3qQS8w+c9uraVksC4OvrQ\n4Hh+38ijD5zTCL73F8Ld7tko2fLxe+C6v15Y0vlRYdtVQLa037gJOhB9ylU8/tj4PKmMXozGYeG9\nnSy3yycqdn0B7vmcvGh6N8pv74Z3iUTTY4map1kXmiWatJ+eaHP1bMSGwHBawRA7xz/mmdA+TzOb\nijnEaCj20o3McWF1edrG+tBwIM7Y00lZ4xuGfWnztmbC+UXDTY2YfVFG1Sh6jGSEr6vH9BnFB4+2\nuLEZsyU0nFY0TKeOvz/UFBqDVjSzhZR35sTq+6fXFkmdBGWeki3JCwBfvaaIATrO4WsxF0lzBYk3\nrAnpkNeXsEBdiICX18J5ExdDrmvsJJD9yYEisxnzEnCBgqZ1zKWS+fyHww12tVNGA836QHN/O+Uf\nDjU5IzSMpxLIdtuMHIyljqtqIVHe/uJ9HQsvq4WMp46EBWfCGDiSOF7VXxCjD7tw7h0rY31Vf4Hx\nxIoDn5KtYWEitbyiPySyMpEJu4WD+Tm+aahE6hzWiXaxrxUtawk0XFj1ObZU1CIUnVf1BYznQW1F\na0paM5lkYj1uLb//4ByxgwEDNU+K5V6/c5KzSz5HEgmcC/n1nE6FF//qgeL8ZCLUGk9rWplwxPsM\nvH1/g9haNoSGQU/zrdmI//ngHJtDwy2tFJXfj2t8w852ymyasdZorm9kWGupGEVROXZ1MnZ1LHc3\nY/6/Aw1sbqRT8xRfmu7wzgNzK/6u1odyX+McPZ6ioBV3toVKdGUtZDp1OLsw45xMHacXDQOBvHSL\nWrEuNCcUOC+GMgEm7FsSAKeNvUTjN6BMiCkNobwS8cRNpPXdi44LH3LciSCoyHv9eMFxWF1+37Hw\nCjB0LtSPLHzmnCTfNi7iJ4Q9C6YnTxWs9A0HCLfZYynfeQ54zWM/tCcn/CI8820yc5t5MHceOwCn\nvwJqWx7v0Z0Yxu4SOa/qSK6SoyVgrx+WitofJTZfDqe9UmTF5g7IFtdlOaiwvJzlKn6E2PpSmTRO\nPyD3+8yDwtE/87WP98geW2SxZJx7NyzU7QQVoUvt/sqPdixzqeWGesyG0OApyUx19ZCvn4t5y1CJ\n2AkneX+UsT/OuKQn4KzS8rObqdTSlxuM1DPHXOaInWLIV9zVykido6gVcR6caqUoaLh6NmJnO2V9\nYDD5WAZ8MSa5u5XwlrVF5jLHvk7G/ijlYGx5ca3ASGjYFiqcEuvtjs0VKTw4s2D4zdEys6njUCzO\ni+Op5ZX9RdpWzRe9LV7sMMCBJOOUPBMZ5VvqYF2gqXiarUWTF3Bu3WQAACAASURBVBsKBzx1sDnU\n7I0sY7HYYev8HIYDw3hq+c+ZDoY888tSusSt7YyuNG3KggFJCaF7LHfcocQy4mvSPGjuWHHb2xpo\nDkUppZzQHCObVlAyYlKy1pN+usc5BaeFimeWfK7qKzCWWg7n16xh4XdHy+xuHV9lRQG7o4wRXxM5\ncTus526H20LNP+eTsZIRBRKtNTUtdto3zUUUVO74R55hVlA08PK+kDNKHrO59N50arEo3rmxh09N\nRiigmmeEPS2FeNc3YvZEUpwYOcVsaqlnjqqRCdgNjYSiFkfFyDoSFKVczeN9R0XvvJK36ecOg9+a\niZlKl+cqzaaWtb6m7ZSYy1hHrxYax1uGymwteBxOHYcjy6HYUjaKt2/oWba9R4Nk5m6UV5LiQUBp\nP3cYvOsx6e+R4uw3CJWyG+/M7pWi7C1P8YL+lTjP1wLXKqU+1HUbXMWJYeR8uPLPxfUvi2HNGVLo\n9ngYlthM5GP2fUdmhBufCxsuWTkj2JlZYd/syR/jStAaXvxXEog9eI3Mhk9/hWhZr+KJgaAMz/sD\nWZ2oHxIppKGzT8x96smMpHV8Jyy/LJO9h8PkfbDnG5KlGTobtlxxYhPCXe2Ua2cjplPLWSWf5/YE\n1DMn+rrHPGRKWjGWWjaHhtevKfCZyTbTqeOSasCr+gsYJRbPO/M25zLHuWWfS/M2a55ha9FnLBYX\nwT5Pk1jHviijoDVrfCWW0M5RMJpGatkfW2pGsbOdck8rJXFiTz0aasYTywtrBd6x0ePuVkJsHduK\nPusCzV2tlLMrIRuCjFubCZmD00o+632YdoqfHCxS1opPTLToOPixviI/vbbE3x6sEyjRSm7mXNtS\nXgB3IHKcXwm4oOK4pyVtnl7y8ZXiaOI4tWAI82I/B5xW0GwMPY7GGRmOWxvxvPPh1oJHv685FEv2\nVqT/8uDYiMLHwShjTaBxWMbz+HQ4AKc0BxNLgLwHukoWJSVB9P444/m9IR3r2NWKMUpxVjnAAgfz\nFYPZVIrzFDDoQUFr9qeOC0ua6xqWCSvZsE0enFH0aDrFOzdWedVAke/OdShrxUv6imwqePzZgQYe\nuVZ1fq90Xwl7YsulVZ8Exf5I3BS3lXzmMsctjRjtYDaxMmHKz905KUAcNDCRQTPPvA954OGYzuBf\nTu3hd/c2uKUZU9aaXx4p8ZrBEp+ZbOMrmMod/jwlbpUK2NdJ2Rpo7mqnHIozilpxQSWgYjT3d0T+\nzlOKjnN4QNloxhKZKBSOed96WmFxTCYWBXx7NuIH7ZQ1vuby3pAtBZG8O6vk82CUciS2VLXirLJP\nxwqF6e9P6eWfjjS4oymTw18aEVk8EArTtbMR93Uy1vmGF9QCNoQPv/Q2lmRcMxPxQJSxLjBc3huy\nLjTYpEFreoC93x1kZm+JnnUtNj1/gkr/EZyzqEe7xHySUB6EK96ZJ90mpd5lzRlP/VqXE1lUDZVS\n7wU2L/5759wVj9Wgngoo9p9817EfFs7BrR+QwLmQKy7d/F4YuxMu/KXlg/me9YDLCwrUQls4+WH8\nqKG1BPwbVihcWMXjC+3B0DmyPV0Q9kiwGzeWFtR2ph/+t39wB9z4j+CVZLVq1xdh33elrmGlAPr6\nesRHjrYpGSlu+/J0mx31mF8ZLeMhGbhwEZWjnjlOK3h8dy7m4+MtKkYC3h2NhH1Rxm+tq3BjPeaT\nE+08owdfmOxwcyPm54fL8xzkDYsk5/ZFKVf2hlw9F4MTFZAupoBnV3w+OdHmYJxJEZyCO5qWH7QV\nrxuQteCap7m0Z+lS80ggMnbTqWWk4KGA6cwylyl+LjR8brLNN2YiNhR8DHBzM6Z9xHFerjiRWaEt\ngHCJLfCsqs/BxLEuMEsc//bFljOKmn8ZS5hK7PxxO9sZhxLLa/tD3j8WMxVbCrl29o56TK+nedNg\ngW/MxGJWkx/XziQIvbDs8ck8k9qba5TNpQ6040VVnztaGc4tLPl2bawvqYbc1kw4pWA4tSjXyDrH\ngTjj3LLH5yZF2q8bjxxJoaAsZxY1vzdm5zPcDnggganZhHdukczws6oBzzqGnnN6QbM7WpqB7TLj\nXtwTcks7ZWPozV+z1EkG+qyiZlcnm6fHWGAmdzc8p2z4aEta6e47mMqkZo2neevuWSbSjGHfEDn4\nh8Mt2ha2lzxuqMeEWgxwYgszSUrZ05xe8PjzQ82ceiIGPVfPRmwvGS4oB3xlJmIk0BRzJnsnv/8v\nKPtcM7fUYbCVOSnQNPCXB+vUUykkPJpk3NyI+YWhMusCzVemOwRKUTaayMH35mLOLfm0reXvDjdp\nW3GEbGWOfz7S4leGod83/PXBBh0rdI9b4owdjZhfHSlzeml5OchDccZfH6yTWqh6ipsbGTc2Yn5j\ntEJ5agPf/5shHAFhJeHgzX0cuLHKJb8eUDn1iRE4d+EVHrs6jycqTuQb+DRwK/CHwO8s2lbxBMfs\nPnEarG0Rd59iX+5MeMPKBioD22DoPJjZI9qPnVn5+3UXiwzNKlaxirzA5r+JnFNzTLj4cwfkRXLq\ni5c/zmZw58ehtFbqFMIe4Uu3p+GBby1/XGwdn53oMBRoBn3hVW4IPSZSy22NhFf0FziUZJLByyz7\no5R+T3Fexefzkx1GApOba4j74JHE8r25iH+f6rBu8b6C4UCUsaudclVfgQORLLM3M8u+KGXYN7y4\nr8jL+wocSSyzqaWZWg7FGUO+4fJayGRqc1c4hVHCUY4c7GkvXzShUPkkXYrUNLmDX74Uf81szMbQ\n0O+JS+KmwHBvK6FkNBWt5gPoLKd7BBqu6gu5qOqzN7LMpeJquDfK2J4Xnc1loqjQdWz082zyzk5G\nPbXirperdQRa0bSWtZ6iYCRru7i/goHLevx5R0Ob840ToKwVZ5TMfIB7LL3kgpLmtJK4HdYzuaZ7\no4xLqyGdbMGVsBu0dlU5vjGTzAfOXY61AuYs3NlYvqJaL+LtHotnlD1GA8O+KKORyXe/P8p4SV+B\nU7s25vnf5gImBArqeTWjWrSBUDg+PdFiIskYDQwVTzOQW2p/dKzNhpzek1i5Xt3CxGFf8WAs9CA/\nv498rTDA4djxxsESZaM5EltamWU6sUwmlp9ZW+IXR6oUNRzNnR67VJGfHSpxfT2mkTnWhx5Vo1nr\nyz31mUnR5u6em0Ll35dUP35rJqKTyUSsajRDubThpyc7fH2mQ+zcPN95ODBUjOKzk50VZfP+a6qD\ndTC66LiCUnx+ss2ea88BHJXBWfxSTGVwDuOl3P/NJ7D48dMIJ5J5Tp1z734sOldKvRT4e+Q3/37n\n3P95LPp5umIu15VevLqjlDzw5vZD/6nHP05puOhXYO93JGutFDzjlUL5eDyoJ08FOCecsNl9QnMY\nPFMyjk80OCt0gsZhEccf3L5U4H4VSzF6ITz/f8L9/yVUjc0vEDmocu7ilUaiWBPVZdWm71TRaI/q\nUlNQPyymBd0s9tE7pTL9eJhMxWp4zTFOZj1GcU8r4ddHKwwGmm/NRMymlhfVClzeGzKXWRLnCPXS\n4ypGcVMjwSJZuRvqMR3r2FQw9BnFva2Unx0qMeJrrpmLaKSOl/UVeV5vQMko3r6hwsZQ8YmJDs3M\ncWVvgd8cLXFrM80LuDQTqWRFa0Z4o3fkwXM9s+zMKR2nFDyGA8OhOGNzwTCXKm5rpmTOsbXgsaFg\nuLOZoBBO8pE4wwL9ngRTtzUTrugNuK+dcl9H9p0aaraXfMZSeMNgiWG/w5emIjInLnov7SvyifEW\nPUah82I/gDWeGNFcV4+pGikYm8r39fuKKIM7O5YX9vj8oJ3xYJ69PT3UnFY07IrE9ntvJ+W+jkUD\nZxY16wset7YsoznNZTZP+g4aKBrFzsjxi8Nlvjzd5pvTMb6G1w4UeUEt5M27pikiQWrEAofaAjc1\nYjR5IWT+vQaqG1hHXN5X4Ehe9OkrxTNKEjDeG7v5QL6LrrLJNbMxvzZS5iPjHa6eiagYxZvWlrii\nFvIfUy02+YqpzNHMaSLDnkwsbm2L+6BVUuSpFfRoKYK8ei6iqETBZDazeLnZTwrc2065smL4TjNl\nIpViyYsrHiOBx+3NhFFf07Awl1l8JQV5LeuIgA9urfFXBxvc1kzo9xS/M1ThlWskc/+Bbf2870iD\n25spowXNG9eWeElfkT/bP0ftGCfOitHsjzIyZ7m0J+CBTsrRWAoRL61KEejtzZReA7vbKVNpRsVo\nTgk1Y4m4dvYfo+LRaxT7Y3EYLC7z3tzZThk45rg+T7Gnk3Hqfb30bFyPS8dxWRvl9VDdNMjU7qKo\nej0GyecsgYl75RlVHoI1pz82/TwVcCLB838qpX4Z+Dzy2wXAOfeoTJKVUgb4R+BK4ABwo1LqC865\nex5Nu6tYQLCMw6BSy+/rwgTi4Lfq4vfoYTO47YMyGelOPsJeuPR3corMEwRpBDveJbQeR67gMgyX\n/q7QkFZxfAycJtuxaByF7/+lFN92k0+jF8K5b4K0LVqrWbTw90EVzvqp5fsp54VLmXOYRbPYtnWs\nCQxKKc4s+Zx5zDJx5vICtWPdBzPHSNFw3VzMzXkQDXBXSzLWl1QDlFKcVwk4r/JQAvsDseXutmVb\nUV4jdWu5vpGy3tdEFhpWnAkVMJtL1A35ih+0Et5zpEnkJKungJf1F3lGwXBvM+aejp2/XpPNhL1R\nyiVljx2p5a5Wmku5ORRSiPicasD11pEpxeaCN79vOnXUjOLOZsKXckdDFHx9JqbmGQZ8zVRsaSyK\nIPfFjrJyDPeG3NZMaS/K0M6kubtiYNjTydBac0pBIgulYC5TDPqa3e2UB2O5mhbY2bFkZFzWExA7\nhdbQtyggSZzoYF83F/HNmRiUI3GKL0x3WONrRgNFhwXZPYAGUtHfb8TFb/G+Ti4Tty7QfGmqw5en\n2/NKJKFSvG24zFpP8UC0VDare6YbA8P/OdjgqzPR/I6375tD6x6GPU3TSbDcpbqIDJ5ina+ZTC21\nRcGgs5ZYKUY8xdXtbF6/GxyHEsuAp1hr4KOz6XxwkTi4pp5ybsmxJfS4o5WKxjMQKcfudkafr6kZ\nxdWzMUrB+WUflGJHM+GinoyRwLCt6PEXWx7KgRrwNLs7KeVFJ5844Vqv8TXfmIloZBadF67e0Uw4\ntejR68GnJiJmc6MbpRw7tNx/m0KPyXyloovYQVFrghUSTv2eppFZ/EXHdZzIPlb6Ie0UCHsWzCGS\nVv4sfgySWJ0Z+P5fyepZ1+VyzRlw8W88MRM9jzdOZE7xZoSm8X3g5ny76ST0fRFwv3Nuj3MuBj4J\nvPIktLuKHINnSPFW/Ui+/OnkhV7sh7VnPt6je/rg0M3w4LXiNlnbLJtNxdjmERphPSZ44JtS5Nq7\nWQoya5ulAOTOjz/eI3ty4rYPQdSQ69i9ngdvhMO3SoanM7OQcfaKUmxZXEFHvcfTXFwNOBDbeVOP\nRmZJHDxvBafAfl9zQdnnQLRwXD2zWOCynoDbmwmOBQc+H5hIHXui5YXpU+d4/5EmoYKNocfG0GNd\nYPjaTIeCkhdvx0mAFyCBe9s6LigHvP9oi7JRbAwNm0KhCHxxqsNEnHFvx6Lcguud5+BwIrrIh2LJ\noPcYybYbJZzRbQXNoSgjW7RPK7HRLmr48FiLfk8vcTT89ESbkmI+cO5SHkCK3S4s+cROqDKhkmuT\n5G6Oz68GHEoylHP05DJ9LneUG/AVeyKLh6NqxH1RIxJqF1V92jktIUC22DliCxtCoQ2M+Dq/noaa\n0XxorMXmwJsPjo+lQ1y2jNSgA84vGb403WE0kOu8MfQoG8X7j7b4qTXFecpFFxb57mtajFKGPM1o\nYBgNDYGCd+ytc37Fp2XlZRJqRYAUP3rAb6+rAIp2LkNorWXGwqZQsy705i3TvfxaO4QP/r3ZaD5w\n7tJ1AO5sZYxosSXXLLgyJkBiLYejlOvr8bwN/MbQEFnHR8daK1IlrqgVaGay2tK9lw/FGc/vDVjr\na47EGSUtajUVI7x7BcymIg9YUo6qpyhrnVOZMl5SC5lJRW8a5F45nFheVAuXTHSPxYtzilPXxCa2\njiOxtHfayxTNMUlqgIgP1A/Dtpc/NivAd39a2u8+r3o3w/i9sPurJ7+vpwIeNnh2zm05znbKSeh7\nHbDYsPpA/tkSKKV+QSl1k1LqpvHx8ZPQ7dMHJoDn/Hfo2wxz+4Qy0LMenvM7Ty29xSc6DnxfpHwW\nL3+V1sgMvzn26NrOEpkQLdYVf6TY+x1xhlr8YK6OiDNmGi1/3CoeimgOJn8gnOYulIJSP+z5mgTL\ng9ul2DCaBRyMPkuoPSvhNWuKPK8n4EhiORCJQsQvDJfYuKiqv55ZxpJsPlAGeP1giWf3BOyLMu5r\nCxf2l4ZL3JUXeJWMBE+pkwLdEFn2Xw7Ch3VLXNuMUgRKcfVczIUVn5FAbJ4bVjKVF1UDftBJ6VhL\nxYh6xESSzVs2/+t4Gw8JmuPc3a4bNP37ZIdtBY9h3zCZWMZTS1E5thc9bmykbCv6rPUN9Uwc/CpG\ncUbR4/pGQuocBQXTqXBifSUZ73+baBMq5lUnugV5gYKvzna4uBrQ6ylmMzFE6fHkHO5sp5xe8Obt\ntucyR79nOL3o8fXpiF4jQeVc6phLHUUlAf3VcwkXV3zKWlO3ioZT9BvNxVWf788lch0UTCZSNFky\nisTBN2ejeTe+LjygCFzbTDmOPxEF4GOTET6gnGN/lDIWC9Wg44Q2cm7JmzeSyZDCvuf3+vzHbCxm\nJ4uyoVVP07SO25spF1UCNDCRWKatY31gOL/is7Xo8wfrShitmUkdc1ZxesHw8dMGuKmZUMjHliH3\nWiHnku9oS7DdpY10s+QOuLaZMeTJszN25BQgMf354nRMzdM4oJlZYutY43WLTpcPnk8rerx1qETb\nOu5vpxyKLVf0hvx4X5H9keX8ik/qHFOppZHJPQZwS27N7ZQitqJNPuIpptKMdaHhpwdLNDLHwShj\nIrVcVQu5sray/vIFFZ/XrSlRz4+bSi2vHChyWW/IhueIMVk0KzTL1qSsTG15wcLxaUfoYmlnxW4e\nFjYVVa7q6MJn3ZXHvd9+dG0/VXFCFgZKqbOA7chvEgDn3Eceq0EthnPuvcB7AS688MInUJ7uyYHK\nEDz3f0gxEkiWa5W3/CPGMtf70X4N+78Hd35SlvJATGPOet1TXyLuyYJlk18KjBFlksHtklHyi1KY\n+3C/zYJWvH6wxCv6C7StmJ90M1utzPHpiRY35YViVU/xujVFzikHONx8MK1QUpiFBLzdG7E7Xofw\nVR/u/lzh9PC0Yl1gcLnjXp9RVIyUYDUzx+cmWkzkAU5RK7aXPIY8cXFr5DQTh2QZfSutdqxjb5Qx\nmR/XyqBsJPAK8+A8sm4+MDsQZ/OUkesm2sxkEppVjOaMokevUSi39DwX/1uoLov+3y38TVFrLql6\nRG7he9kXyUSgZS3T2UJWt5lCn5HsZagVo4GikIlG83DgEWiFUjCWWK6djefdDvs8xfaSLwWLGjy7\nwGsu6AUNaaNkbN3sdMBCceH9nZTPTyXzzoQ9Gi6qBFCQLLxxlolMAoFNBY9eo7G5TfRy3+19rZij\n3c4c7OpkDAcapeAXRnv4maEyt7cyBjzFKXmBoUImQf15YacGjFbMpBa7KCO9uBCxS7Pp9QwbTS5H\np0TT+0gq13Mszrg5zuZpHaOBXqL+shxSHBaX1wDJPdqlqjknZCLlwOkFPW4Q6tRa35B2qVPOMZY6\nlFJc2htyUTVgNpPJYWE5O8LF11MpXlALeU5PwFxm5zWsu9j6EthyuTwbwh7w8ljcWbjvy/CD/5TA\nVxs47cfhtJedZI7yasS1LB72Miul/gix434XcDnwF8ArTkLfB4ENi/5/ff7ZKh4DdNU2VgPnHz02\nPEcefm7RGmlrXNwby2sfWZsTO4X24RfFpKM6Cnu+KUtvjxSbng+NsaVBX/2Q8HS9H87A6mmPsEcC\n48YxzlutSTjlSug/DZpHpRgzKAMKOlPi1ngiKBvNGt8sWRL+t4kWO+qJOOKFBgO890iL/VHKx8db\n3NhI2BQathY9jFK850iLM4uiANHKwNOyOSeUixetkDXbGBp6jBhJdJE6R2wdL6yFPNgRrd0Bz7A2\nMKTAnc2EC8seOxox44mloiVDnFjLjnrMZVVvCbdXsVAk99wejxsbsRRqKUdFOSJrubGZcnbJw1cy\neQi1mLoIt1ZxadXnhnrMTJr3pxWt1HJjI+GqvoAOEoTOuw8iRiov7S2wox6LSYZR9BoxDNlRj7mg\n7KOVZEILWooKO9ZhlDj3TWYLAVc30zqRwaVVj53tlLZTrMkVJyZTy652yhlFw45GQifrjlPMRHbU\nY17RF85L7wW5i2DHCjf4Vf2F+QDeZ4HWEAEXlz1uaiSkuTNhCMxl8J16zAUlw12tBKvEqXJtoDkU\nZ+yNUl7dXyDBkS6aOcylUjzXziz7jxFMyYBr5hIG828uMIZnVYP5wBngVf0lEiRQ9bVktZupBJkv\n7A3mKSSLr5kH/PxAYcE63YgV/VTmGAkMF5QNtzUTtJOJYsUo7s+t1vu85V90P2gnfGSsTcVoTi0I\n3eiauYgvTLVZF2hubaYECvp8RVVLUZ9DlFtmMqGs+FqoQROp48ySmS8W9LVijW9OKHBejCA/LjzO\ncSbIba0X/Rz3fhvu+rfc2XSDrGTe86lHniXWnryn6ocWPuvSPB9vyd0nKk5kjvIa4IXAEefcW4Bz\ngd6T0PeNwDal1BalVAC8DvjCSWh3Fat4QmH0meK2NLtvwYXJK8CFb3vkk5ndXxNt4a6FqjbyEH3w\nGkjaj6zNLVeIwc/s3gW3wMoQnPX6R9be0x3n/cwi560H5bpuuAQ2PRfOf6sUCC7et/F5sP7Zj6yv\nmdRycyNhfajniwIrRuMp+Np0xO3NlA3B0n1awdVzMeeUPLRacKhLlJhwbF6h0slTip8fLhM72B+l\n7IskWL6qr0DFaIYCyaDVc8pD4iQTfd1cjEKC3MhBZCVrV9TwxekIj4Ul+27oZoDrGwmegkApYmTT\nSlFSijtaCW8dKjGXS+ntizLGEstPrinyYGSFX9ztz0lWPMTx7bmEHr2Q5ewG7VUNN7YSQiUSdt3j\nfK0IlWRa37i2yGQifNd9UcZkannzYIlvzcbzWd8uFPKi/exkxPrACNc3k80oWB8YrpmJKOLQi8YZ\naJXzz2G9D5la6iK4PdTMpJZSfg7ponPoNfC5qTZeTo3oFo16SJb6G7Mx60ND4mA2FepJqGAoMJxZ\n8vnx3JnwUJxxODfIeefGHj43eXx+gAPeP7E8zedtw0UuLPviMJhaZlKLUoq/2tzDP5/SM++S2HVQ\nVMAfrq/wupEql1ZDjqSWg3HG4ViK8v50Uw/TGYwGhnZ+DvVMzHlCpeYD7uPh6pmIcj7J6t7L6wLD\nd+ZixmLLaGBoWpc7GooxkAPeNFjm7LLH4fy6HIozap7mjzaejHDoh8OuL8mzubvKaAIoD4te/CPF\n9tcIrXOxU+Das1aW3Xw640RoG23nnFVKpUqpHmCMpRnjRwTnXKqU+lXgq8jz8V+cc3c/2nZXsYon\nGpSG894Mp1whD6WgIlnJR5PNbU0sBM5daA9cJjSOR1Id7YXw7N+E6d1SOFKoSdHpSm6Uq1ge5UG4\n4k+l6CaakxdTbXPOJRyCF/6ZuDJGdZn49G565JOpZuZQznFvK+HulshjjfqabUWPI0luanFM4wWl\nOBxbNhc8hgPNTY2UyIob4OlFnxmrsdbyifE2n53q0MgcF1d8fnGkzLrQY1NoeGV/gc9Ntmlax3N7\nAl5QCzkYZdSMZluvKBBkDmqe0DWOZJaCNgz6ipZ1uDx7O5M5DiWOQEFFLTgFFnOnwKOJw0ey29N5\nhNijRVv5aOw4uxzwxxs9dnVSrINTCx4DvuYjR5sEWmOdYzIVDd8+o/BzfeCarxkAjubr/mvyQOlI\nnOI7x0wmyhYAFSQonU4yXtVfYKyW8ZUZMUR5SS3k7LLPWJwuCfy7UHkfQ76mlcHunFIi3GnFkdRS\nNoYBX9G2QicoasV4bDmSWC7sCdnZTNgTiQrEmQXDpoJhLIXenCOe5P2WgDIiv+cp8POgWwFlIwoS\nB2LLet9Q0jIB8JXwk41SNB388aZeXrOmyI5GQlkrruwtMBBoWvmJ6UXn2F0h2N3JmE0tV89G3NZM\n6DGKy3tDziv7BMbw15uq/OGBOrc0Uspa8YtDRV5SC9Fac+32ft6+v8n3GzG9RvM/11V46UARpRTv\n2FDhfWOaHY2EAU/xc2vLnFPyxTAn0NzZSjmaWAoanlkJCHC0rKOyjMPdZGopHpM29JQiczCZWZ5Z\n9omBRuYItahzHIpFEeNDW/v4Tj1hVztlONC8sCekdAI0kZUwu1+kLifvg9pG2Ppjy8vIdtGeWspP\nBnnmzytlrPAcmd4D930JZvZB/1bY9mPy/Cn0wmVvh4kfSPuVIdl/IjSQyV2w68tQPyjvjK1XSb3M\nUxkn8lq8SSlVA96HKG00gOtORufOuS8DXz4Zba1iFU9kKCVGGL0bT057Q+fKA3Cxs11UF23mE7F4\nXg5KyQOzf+ujH+MqJCM0fO4K+847Of0M+pqdnZT7WimhESOJPVHGA1HGn2ysMpm4h7oPWsuLqkXe\nc7jBocSyxtcYoGXhxkbMywcKvHN/g3+falM1YiLyXzMdbmgkfOK0fr5Xj/jydId+T8xVrq/HPNjJ\neNtwGZB7aSSQCMY5x0TqeFE14BszMc5B1chb2VlHYh0v6i+IFB0S8IFQE1IHz6v6fHCsQ8wCn3fa\nwpx1PKMoffR4mguPkdQ7u2SYSC2xlTYVstSuleMtgz43NhKUc1Rz3d96arFK8eyy4auzyZIguA40\nMjglgPcfbXJnM2Eg19z+4lTEwdjyzKLHN+YeagRjgUuKin+dimlZR65wxx2thH2x5r+Plvl+PcXL\nzwMgsxIFXVj1ePveNtGigPDeTsZY6vhvgyGfPUY0tgV0jg78LAAAIABJREFUMnhLn89HJiJScjpO\nPn6n4PJqwD+NtcReWyssosE9kCtsAJxdDji7vPR6nhoo7oq63PmFcwN4RX+Rvz3YYCIVus54YnnP\nkRY/MVDgzJLHz++ZYzazrAsMiXP809E2MxbeNlzhXWMdQk/zEwMlIuf4wkxE0dOcVwn4myNN6qkT\nlz/n+NB4iwQY8BT/OBtLgaRyxA6umY04s2georm8GGeWfL4506FsFv6mq9N8Ttnj23Mx6wJDXx4d\nzaWWQV9TMbLacVlvyGW9J4fHNrMXvv2n8lsp9MHYPXDoFinqX7t9+ePWniUB6+KC5Oa4fL5S4Dx+\nL3zvL2TlM+yRYvBDN4lWfW2zJEp+WCWuw7fCDX8HfkXeR/uvEwfVy/7XQwP8pxJORG3jl51zM865\nf0Y0md+c0zdWsYpVPE7YcoU8bGf2Cp+6fhjak3DOG4XCsYqnF1rWcTTKhIuJvEB9JRJx97VTXj0g\nboDjScZcKtnGdYHhvJKPUQrlpGiqW6hnlGIizvjSdIdhX4qwSkYxEhgmk4wPjTX4+kzEhtDM79sY\nSpZ7dyflZf0FDkQZE8mCW95pBY8X9RV5RV+Bo4m4vs2llkOJ5dSCx+vWlBjw9XzAnCH/LWgJwhdz\nobv/dcCBlST10PM82sUZYY0EXL0GUiU6v4lzJEp42EdiuySz2u3TAd+aS7mrlbIpd4WrGs2m0HB7\nM2FXZ3kHxZ2djNjJ96KVBGK+ku9uS8Fje9FwML9e04nlcGK5ojfAOeFwe+THIXSOhnV8Y+r4NAqL\nZPRDlV9Hm2/AoKfozfny3WtinahyGNQS+bpj8Y9b+9F5+90NYIvILDOeWjaEHiWjqHma9YHmS9Md\nPny0yWxmGQkMJSMycGt9zWcmOnxtqsN0Ks59JaPo8zQjgeELUxFXz0TMpZb1oaFoFP15cP8fUx3u\nbqY4Jw6RSikMCg84kjg62fK0jRf0hvR4mv1RylxqORJnzKSOn1xT4IreAhWj5vcdjTNmM8drBwpL\nNNJPFnb+uwSs1VHJHHcdR+/51MoypttfDVjJNEdzecbZwhmvXrm/uz8FYVX68YuSHdYe7Pz8Ixu/\nc3DXJ0RiszwobfasA2uFWvJUxsNmnpVSzz/eZ865VQGTFdCagCO3SyX94BmPbkl2Fas4FsU+WWJ7\n8BoYuwsq22HLi0SfcxVPbdQzy13NhLlMgq6tBcPudkrBaNZ6omCQOpH0AsXOdsofbQoZDAzfmYuY\nSS2X9/pc0hMwlliGfENFwY31mMjB5qLHM0LNLS3JvHrHFDEVtOLGZsxaz8M75qFW1IrdnYw3DBbp\nMWIzLP0V+PH+AoFW/OGGCkO+4sNjTdqZFCb+wfoq+xPHZT0BD0YZd7cSMgenFDXbiz63tNKcgyyU\nDhBpNQfcmsvt7WwlfHW6TergBb0Fzi973NtKxDXQOSbyuHaNDxrFXR3LMysBE0nGzrYE4GcUxXb5\ntrbFIEF21+S6qwZxWzPhlKJHwzomEjluMM9A39laPni+o2PpMYqK0dTz4G5toKlbx/2djPecUuOf\njjT58nSHooE3ry3xlqEy79xfp0c5IgVTiZjKjAQKpRS7ogWZt24ga/J/X99I+bH+kJ2tlH1xhodk\nXUcDzb3tlHOKHvdHKbvbKYFSPLPqUzWGIzmX93g4qxLwn6fXeNOuGSZzlYzLqh6f2NrLh6eE4rEY\nfm7sc1MjIXSOI5FM3oyCkdBggR3NmLIW6/aDucbytqJHiuOOZkyPWTqWUCvixHJ/J2F9IG00rcPX\nsC40zKSWfXHG9mXOoeZpfnu0wqcn2tyaOxi+drDEGbm50O+uq/LduYgftFOGfMNlvQEbwkfHXcsS\ncRqdPSBB5vC5kv2d3PlQA6pCTXjHNl3e3bV3I7zgj6VIfOYBGHmmGJpVhpcfg83kb6vrYO6gyJuG\nVel/4geP7LySlmS8a5uWfl7ql6L2pzJO5I74nUX/LiDmJjcDVzwmI3oK4NDNcNO75ebvpjy2/Rhs\nf+1qAL2Kk4dCDZ7xKtlW8fTAvijlXYeatKy43WUOzq94vLgW4hCZsi5VAmAslqwdiL7tacWlj/xe\nK+oDd7TS+UzX7c2UPR34tWEx0nDWoZY4pzm2BB5163DOLeFSRxbW+pp7WgmfnJBA1ijNtXPiBPea\ngSKfn2rzgbE2GQqtFd+cjdGqwduGy0zmhV8bQoNCAq9DieWisoeF+cwtLOgFb/QVHz7a4B8Ot3B5\nvvjjE21e1V/kwrKhYyFDUcovS8cBODaGhuvrMRMprPGlkG/agk4dG0KP65vpEue+bli8PjAcjjPu\nai4EyvcCg75iXcHn/iTheBjxNUdT0cbuWfQ11GPhQl/bSHgwtpxZlojpjlbGrc2EEeM4lC4E8QAP\nxo4yjnWBYjp289rI3esCsLWg0Urz0v6FAgjnHPtjy6in+MBsNG89Do6vTMecWTL0esvbz8ZZxh8f\naNJRwgFHwS3NjI9ORgwFHne2lqZLbb6iMeorrqs70kVEmIlWRp+BjYHmX8bazKQyMUA5bm3EnF8N\nOK+vwB3NZIlCQVdycUNguD1NGfQ13fgzteJ2OOQtv/wWWcfHxtvsbItl+dHU8pGxFr82WmE0MNQ8\nzcv7i7x82RZ+OMRNuO6vhWusjNSllAfh0t+TIr/ONJhFVLukJauKD1drUhmGc95w4uNQWupk9nxd\nknrd2MSEIof3SOCF0mbaWeodETceGlA/1XAitI0fX7RdCZwFTD/2Q3tyImnBze+V2Vxts9xAPRuE\nnzq95/Ee3SpWsYonK6xzfHishVEiFbc+NGwMNbc0UsYSy3OqYp6SWofL1QJQ8Ma1pWXbDLTj3nYK\nbpGrHzCbQcMqzikZDqcLbU4nFk8p3jpc4eyyz/7IkjoJoicTS6AV55R9PjTWpjd3EVwfGtYFmqtn\nI25qJvzVwSZVoxgNDMOBZsjXfG02Ymc7YTzJyJzYE1eNZFHHEjGx0AgHWjnQObXDApf0hPzjkRY1\nT2glI4Fhraf596m2FIIhjm+BEqfA1DpSp7i0J+BoYrE557nHKHCOo7Hlsp7lI5fn93gcjYXgIuOU\nzPbRxHLJclVqwJsGC/QYzXhicdZhrfQ1nBd2fmmqw2ig2RB6bAg91viaj463mbJqPnBe7MDXBF6b\nB8aOh9JSfn+0TEkrJpIMlzsbHogtzyh6TGSWyVSKMLsOihrY2c4wK/AF3ne0zd3thF4NNV9T8zS+\ncvzvg03OKXsYRE3DOUeaB+oXVnwCrYjzNroOgxaoW0gymxfxOcpGONgZcF875YU9AdbBbN5mYh0H\n4ozn9gS8dbhM5oSn7qzIJB5NLJf3BgwEy4c219Uj7mklbMglHTeGHolzfHJ8ZWfCR4r7vyLv/tpm\nKcyrbRaq3V2fFG3m1uSCyVXX9OT0V578RJtS4JWkGNAvS4GgX5ZV8qDnkbWpPTjt5ZLJ7hppxQ2h\nkmx72ckb+xMRj6RM9ABwxskeyJMRzsmNPrs/zzIjPxKbLFVC0AaUD0dvf3zGuYonBtJIOMqtycd7\nJE99RHNyrU+G8+KJoD0t/f2wMoHtKTnuRBzCxhPLWGzpW7QcrZSix1PsqCf82aYerqyFTKWOI6mY\ngfzZxh7OLS/vmvPNaVGLqBhRG8icFJeVFHxrLuKvTunj+VUJMg8klpqn+MvNvWwrevz0YJnn9gr1\n40AsRVW/MVpmLnN0rFtSkNV1H/yPPBtdMguRgdEKD8V/TEZsLXhsCA0zqahj9HiKs4s+t7cyLusN\n6DcShHUQ5YhLKgE7mgnWidTaTGKZSuy8yct/TUdcUg0YCjTN3O2w39c8uxpwezPl9KLPcKCZSi1T\nqWWNp3lGyefrszEhD5WcCxDO8xklj0HfUM8c9cwxFIhCybdmYpbDt+sp/3BqjS2h4Ugq5hpnlzze\nfWqNPZ3caXFRxFTQ8p18ZbozTyHp8owNEoTe2E45v+ixOGQPgSt6PerK8BujFQZ9xe3NlHtbKReV\nxV3v6tlY3BX1gkxfSUu7X8mdJVup5cZ6zM5WgrVCCvnidHveWruRWtqZpaBkNeKmesKvjVaoeZoD\nsWU8sVzeE/C6wRK3NFNKasHN0SL3mKfgv2YT1noapRT1TNRAhgKNxjFjHb8yUkYrx62NhD2dlBfX\nCvw/A0Uuroa8Y30ZX0t/U6nj5f0F/mjDypHgjroUenac40CUMpN/73s62Tyd5mRi//egPLT0s8qw\nFOutPUskS20iUqZxE859kxhedXE0TrmhHnE4Xp4SdCJwVp43654t/XVmJQu+4RJRyXik2PoSOPv1\n4oQ4u08+u+hXRVHq0eKHeT7+qHEinOd3sXRCex5wy2M5qCcDWhNiUjF9P6CE5H/+z0mgfNyfn12V\n/Ho6Y9934Y6PQRbJpGvk/Fzrt/Lwx67ixGFTyeg88K0FiaXTXpZnck6m81aOtAO3/yscuA5Q8vs/\n49WijbpS5ihpw20fgkM7AC3PhrNet/LyqVFiMnEsVcLlAW/F0/z5lhqN1FK3liFPo/XKJx3kdIyS\nWdC9VcBcZgmUqHZsKfq0nCyXD3h6XpmiZMTt8CcGiiTOUdbCw929TNGcdQv9LTeWtnU0c0qKBtrW\nESN81kBrtpY8xqMUFPT4hoonAW3LOm5upPPUCo3I4wUaymheOSB2zNZJUL8vSvGVnFPLsuDS6KBi\nHQWt8DQMepokk8DRN5rpVOy9fa15VtWQ5HrCvpYiM1+r+QJDu2gs3b/ZXvL5xDMGGI8zjFbzqhD3\nR+k85eRY+Dm3e3EhX5a3GyiFcpZAdekosnqAk8LR2+odvjgVCU/cOVrWcklvgSAvFkwXpasztfA9\nfG6iyd8datK2cs+dEnr85ZZePBQtC3OLBqOQgD3QcErB4/fWVWhYR6DUvLpLoCVQ7vfU/NjJbcID\nrZhOLbN24d3ZzhxrAo2vFN+Zi/jmTJy7JIoz4KXVgMHAUPM9ziwaGoHolm8MzcOmbLWz3FyPuL9j\n57P1w77mrFzv/GRDe0sNskD+XxnQGjY+F9ZfAklTkm7dOCG1lj/ZX5fJjJNxXt4b8Cebeig8zO96\n2bEYqG6C/lOEh218Sepky8/5HhZKCy311BfLcy0oP/pnbdKG2z8sqh0ouSZn/qQUyj9RqK8ncoo3\nIRznmxGJut9zzr3xMR3VExzOwg3vEhHxnlx+TBm44e8liA4rMqvrIovzgOmCx2/Mq3j8MHkf3Pw+\nuTe6cnWHb4XbPvx4j+yph/u+DLu/KkUxPesl43PP52Df9x6b/u7+tEyMetYvOH3d+bGHX2W682Nw\n4AahdPVuEJrXbR8U3eflMOBpthQ8xpOFN3HmHHXreE51QTqr4mlGAu9hA2eAF/YGVIymkVqUkhdT\n5kSb+TUDRT5wtMWeTsqW0LCt6BNqxfuPtjgUL7CBQy1FcN2AflNo6M0LF7uIrdiB/9RAkZJe6kwo\n+xyvXVNgdydlKrHUPE3NF33mna2U88s+u9sp06ljIDCsCTxSCztbGc/v8ZlIHAkLGVkLTKaOiyoB\noVY0MktRK8pG526Aiuf1huzqpDQyS6+RYLtjHbs6KW8YLKFRRJnFNxrfaKLMolH8/FAJT0mA52uF\nrxWtzOErxRvWluYD3a6kXjdb/PpF3OPBYKmc2pklH4UiWmTuUc/HfFVf4bgKGBa4vKq5o2NxTlwJ\ny0jm9vv1hE6a8ScHmxjEtnrE1xyMLL+xZ4Yra4E4E7oFZ8lO7mK4IVD87wNNfAXDgWbY0+yNMv7f\nB2bY6C9wv7twyErAi3LKilLqITbTrx4oiYJKbmutlKJhodfTbC8YpnMdaj///iJgKrEc6qS8+0iT\nilFyDp7mrlbK/3hwlv+fvfcOs+yqzrx/e590c+XqrqrO3ZJaagmhnBEIEIhggsHggPGAMQYbE+ax\nxx7PfN8zHqcP2xjMGA+2Gc+AbewBmySQQEIgISGhgLKEOqeq6q5cN5+09/fHOpVaXSVR6haS6Pd5\n7iP1PbXP2efce89Ze613ve/OVsI/TbTo9hxOK3hszrk80Ej4vxPNZb7tzM/v0WaKryxFR1FUQgXZ\n104pOSd+hb3pZeImOscIsVZoDhuuWAiUtSPPh8UJtk8fafC1qTY9jmKNr+lzFTfPRPzVcP3JB3ka\nUFrcAmvDgMp8BhTUR1fPeV4M7UoD4olIUjzyeTh818J9Nd8twfT4c8gJ5Omc5heA+7PXF621J+kx\n9PzBzH6oHhR5mblVUFCWEsiR++GSD0pZZM6lp35USjGVdT/RaZ/CTwgHvisSPnPGJUrJDWHkXin3\nn8KJgTWw+5tQXrcg1+d40pyz+8YTf7ykLXa4HesXHhiOD0EH7Llp+XFRXbRQF49zA6lC7L15+XFK\nKX65v5DJbKUcDlOGI8MrO3zOLqyurOU7Dh/fXMHVEuzOJIaaUVzTGXBth8/edsJabyEwLjoaDdxd\nWz5V5SrFr60tYoFDYcqhUDjZb+nJcUbR4482VjDAaGQYjVKmEss7+wsMBkLZyDmKamqoJpYExcbA\n4UeZNJyvoJaK9m4KbAocvjETzdtrGyQrOxeI3VWPeM+aAk0DB7NrNpUYfrmvQNvIeCejC1Sz5rmN\ngUPB1XxoIE9oF65L2yp+c22eiyo5/kN/gZnUZOeXUk0N71pTILSKYvZMmJP9AygrGE2On1kG6Pcc\nfrE/z2RiOBQmHApTQgPvWVPgcJQe90HtAZ+fijLpu8xFUC00VP7ZSJ3UWkpZkK60os/XjMWG2RTW\ne4pYLbgWagXnlTy+OCFUnoKzaJyrOBim3FU/fjOkAr5eW14y8Ff787ykw6dmsuuZ8eP/anMHDzai\n+RL4HKVjjhry6SNNfKXm7a6VVqxxNQ82E74y2aSgmQ/StVIM+Zr76jG1dHnBvfvqMRVXkWaLlQhF\nRYt5ylSy/LjVYsvLYehiiQVmDgi1oXubOPqthC9NhXS7al7txtGKHk/xtelwnkbz42L7G6H3zMzt\nNotPBi6Ara9a1e5OCuKmJDsqx94fy7Bnhfvjs41l77hKKQ/4M+AdwH7k97FGKfVJa+2fKqVebK19\n4NmZ5nMLcYulZLgM2pWMc/dWuPbPRf7FxPJDeSbGFS8UhDVxUjp4hwQZm6+BLa9YXo7nhYLWjHQ0\nL4bS8kpaUA/hia/C0YdkhX3aa+Vm+1TlqeowPPEVyVYW+qRxY+D8505Z69mGydwVrYWpncJ7znVl\nJcpnUJZcDkkINpGq02K4OWjPrDCuDWT9ElM75X5S7IfS4MrjAPo8h99fX2Z3K6FpLOsCh35vwYjk\n7nrEzTMRs4nhRUWPV3UF9HkrC3+/vDPH/9hs+dTRJrXUck054L2DJWZTCf/uq8c83kqIrWjxbsu7\nzCaGyBj+7kiDr06FtIzhopLPbw2W2Jhz2RC4/LcNFXa3E6JMx3hO/uzCssdru3J8cbJFlDkTvrkn\nz0xiKWnF5sBhZzshMZaNmfrBVGZDXdDwRCsVlY1AU3EVExmVIlDQmKMuKNE1nkrk2FdXfG6YFpOV\nV1QCziy4PNpM6HActnd4TCVSwu92NUfilGZq+PXBCt2uy+cnm1gka/72fjGA2ZBzKWrFzbMLDoPr\nA5fvzLTpcjU6MdSzuVS0GJ/MpoZGavj2TMhd9QgHxZUVn5d1BPjZefvArfUYF8Xru30GfYepBPJK\nAso5MYuSlgzwVOYiWHY0iRW1ClcpZrOGwNRYHm3E1E1GZXGEbjOWpJxd9GjVRW1EA1t8xZCnmUgM\niTE80khpZOO6XLFQb5qFwHYufPOQoHc0SpmMDd+cafNgI6akFS/vDLi07OM4Dv90Rg8/qIZ8Zzak\n29W8rTdPh+fweweq5LLPbm55ESDHmUhSjnWJ11qhEE51YuCBesx4kpJXii054U22jaW8zNd+NrX0\nuxpPKyIrx8lpxZHYUEsM+1oJfz1aZ2c7odfVvKMvz5t68k+rknM8OD5c9BtQPSSJtHwXdG156gxt\nIzUoa9kfivOnrxRrPbGmn6ts/Ljwi3DF70hvVmtS7jsnQkb3yIOw82tyT+s5XWhyq1XbiFuAfbJf\ngZuD8DmUbFrp+v8FokazyVp7gbX2fKRRcItS6m+AVcpqP/8xlzFKFy3CrZWH6Zw7j5sTLcfBC08F\nziDBy/f/XMrqcxnYR/4Zfvj3K4vBvxCw9sVPDoqihmQalRaHqeF7pWwX1uDuT8Keb628z/oRuO2/\ny00rqIjc0V0fh/23nrzzeK7D8aQCtP/bEjg7gTSc7P220DhONIIKlAakUWYxmhMrU7Ty3ZJ9PniH\n3DOcQExuDtwKnVue+riuUmwveJxf8ucDZ4BvzoT8w9EmLWMoO4p76hF/MVxfQp84Hr421eaLUyE7\nCh4vqQQcTQwfG6lR0or7GzH31CLSzIziQDvhlpmQNZ7iP++v8vdHm8TGkNOK26oR7941zXhG6Qi0\nYkfB47ySv0Q3+Lf3VvnXCVHjWOs73F2PePeuGTocxd52ymOthFzWCDkcpTzUjHlx3uEH9YhHmglu\nFigfaKd8bzbi6rJHbCWwdJFgLrYQAVeWPf5hrMEN0236PYd1vsOtsxF/c6TBoK9BWbSCNb7DWt/B\nFa001gcOf3ekwV2NmEvKAZeWA+5pJHx6tEE7TXnvrmlunGmLbrNWfG2qzXt3T7M970gQlgVlDjBr\n4EhkODun+dRogxunQwIlnOQvT7b4h7EGjTjlV3fPcEs1pMORQPX/TrT5wN5pLi05hFbOaU4RpW1E\ntu/aDj8zOJFMrqcVxhpAcWXZ43BsqZkFk5iJFI5ElnPz0hQ5lYj+rAvsDC23VkPOKbgcPGbcWGIZ\niy3n5fV8dniO2z1nC/7SjoCPjdS4qxpR1IrQWj471uT6RUYul1QCfnd9hV8bKNGRfXc3+pr6osAZ\nhLbRsvDKjoD6MU18zdSQ15rzii531iKOxAm+gtBa7q7HVI1Z0WHw4pJP1Vh8rSg5irwjtJ5uVzMW\nJfzG3hkeb4mF+FRi+MPDdf5hfGUqyFNhzmF26KKnb3nd52r2hIbQWBykKXNPaOjQ4K4ykJ+bS/dW\nSdB0bnrmgfPhH8izvTEmVbfxx+WZNtc8+OMi3wX53qXUV5B7+cAFz2yuJxIrfQKvAd5jra3NvWGt\nrQLvA94O/PxJnttzFkFFNJurh+Wh15yA6X0SJPWf/ZOe3XMTRx6SMlHnJllY+EUJFIZ/8Mw6fZ8P\n2HCFnPf0PlHaqA5Da0KoPAdulZV2ZVAyFLkOKVf96EsL0j/Hw55vSXNceSAb1yk0ose/uHRR99ME\na8XZygnkGqRRZjQQnJzMs1Jw7jslEK4ezjrD90OxV0q1y2FO/91xZV5plsH2cqvvKm+mlhun26zz\nxfXO1yIFV08Nd1SXP/lqIpnQDZlbXqAVg4HDbGK5ZabNbGzmy+IGaXoDy+3VkO9WIwY8TdGVcWt9\naaj7wgqc08eaMXfWIwY9TSE73oDvMJGk/NtEk5yj0NYSW4jNglPegcjQMguUhDnzFgvUUktf5kw4\n94oyubt+z+HhRixUDEfK/xsCzd52wmxquaYj4FAozosTccrBMOXysi986lbCBl+T19JMucHX7Gon\n/PNEi71hyoCryWkJvgY9za52yg1TbSxLH6w6m+9ttYT9YcLGnENOKwqOUFIeaiT840SLkcgw6C9s\nG/I0DzUT8kpTzDLNsYEocwrsdxXvXltkU85hOhX1i2piqBp4VadPI6MuzMVGcyGoAb4x1ZJG0ywC\nVpkSRjWF+2tt1KJzmDuf1EJv4C7Z39w+8woeqyfMJpahwCHQwnteHzjcPBOuSKM4Eh6/wTQFXt6Z\nZ43vMBymTCeiNjObwgcGClgUgYbUSgZ5LousUazAkOHdawt0uQ4j0cI+mwY+MlDgf4+1wEKvJ7+h\nDlfT7Wr+z9EW0SqpEqtFbGVhN0dFmss2L0+OefZhjbgWltZIUsDx5P+VFnne1UBpePE7M+fEYXlm\nzuyX/W566Ymc/TPDSkQ5Y48jemitTZVS49bau07ivJ7z2HqtBEQHb5cu2cGLYfCCZ66oUT0sJitp\nLJnr7m0vjDJ89ZCUYZqT0Dgipe7yoPxQ6kdX5oNbA5M7hdbg5uU6lwefvbk/U3gFuPJ3RZHh6ENi\nZbrpaslE7L5RFmOL4WbBX3t6eceoqd1Prmh4eWiOy02n0HNyzuW5DJPIb3HLtdKT0J6VG3p5ULIi\nJwO9Z8DL/gD23ybf694zYf3lkgFfDu1ZaSre8ooFOb1in1BMVruQnE7MouB2AWVHs28Fy+jJLCt9\nrFNgQSt+2IgpOJqCA+NxSmLEnU1ZeLCZoBEe5mIEWvFoS453NEp5oBHTMpYzCy6n5Vz2tBMJzI4Z\n5yrFQ82Edb5mWy5gODQkWAbmnPvaKUWt6HBFHs4gFI+GsTzSSrmq4jEeWx5riTPhtsBhfc5hdztF\noailliOZ3nG/76AtHInSeaWQL463SbG8sSfP23oC7m4kYC3V1HI0G7fGd7BYHm8mJHHK3hQmRPiD\nXhdcA4+1sqY3tYhioSTYfbAZUXaW1qKVEnWOh5sx+pinrdIKbeHxMOXVXQEH2gl7QoOr4KyCS7+r\nqRnF17Z38p7ds9xVS3A1vL0nx59srPDWJ6YpKlFpaVsJvApamiIfaScEGjwl/1ZAOWuYfLxtKGY8\n6nBunCPZ7sdbKZt9xWhsadmMy+kqCo7mh82IvCJbiIhay4DvgILJ2BAouHE65M5aSI8rCiin5V1G\nkoUmz7nwNECCxF3tmL/b1skfHKxyTy2iy9P81mCJN/QU+PPhGheXfA5HKcNRSkkrdlR8IguzqaEL\nzaPNmD3thG5Xc37Jp8PVrAtc/vH0Tv55vMkP6zGDvsMv9Bc4t+jzsdEmReeY30Jm1z4WG9YFy+cb\nq4nhq5NNHmombAoc3tSbZ8BffUAwnVrOzGkmEkvTWPJK0ecpZo0ocURW8VAj4nCUMuQ7nFv0l0hA\nPhuIW5I0OJaike+Cyd2r32//DrmvHrhV7t29Z8Hx9t/sAAAgAElEQVSGy59b6lQrfbKPKaV+2Vr7\n2cVvKqV+CTFU+qmGUvLg7D3jxO1z33elo1Rp2f/Or8Fpr4Ydb3/+B9DFNTC1C9pVkeexVuw7S2uf\nbE+6GNbAA5+F/d+RVa01kpU9/z2iT/l8gZcXjvfma5a+37FeVtW5RRZaaSzfgWOD6sWoZA2Hi28m\naZQ1rK0QuL2QoV35LimWaoy2pqByEmgbcygPwjlvf/p/H5Rl8ejmYM05C+/XRuT7sBpUXNEzm1Mz\nmEPTWIZWeOB3uVqCFmvRi8a1jOHFRZ9vTLWpJoBSaCV8UWMtlwYuI1F0XPfBLTmH++sR/+toE5D5\nfGs65LKKz1l5CUCPHZday7acw3Ascni9i+goh8KE03yHbyvJcBYWGWDUopStOYd9Ycr5JZcLyv6i\ncSkbA4dbqxEPxSk6y5nubifzGcWPDdf454nW/La/Gqmzr53ytr48I5Hh4WyRIONSejzNKzoCDi+O\n9IAjGW/4ksDhgWYqZi7ZtkYWgG7JuRyNl0bI1opA3Tbf4U61tGRkjcUo2JpzeKhpeUlnnpcsGnco\nSqkowy/tqsliJtNs/tfJkJxTY3PO4d5GTIerKc3v09BSsMV3uDNKSJXMxwK1RCa9OXD4YZpQdjXl\nRePaKLbmHL4ylS7IzQFHE0uXNZyWc/jCZDtrPrRYq3iiFbPed/A1/OruaR5piKtfiuULk23+33Ul\n+j3FdLogTwgLih7bcpqP7JtlVyvB05rZ1PInh+tUXM0aV3PjdJvIWFwlEnr31iK25l08pfgfow12\ntRJ8LZJ810+H/NZAkY05lzW+y4eHnnyDXZdZly8OQkNj8TV0r6DEMRolvHvXDEcjg6vhFmv5l4kW\nn9zauaLO+kro8zSziWFjbuG3UE8MPa6mZuDjwzUmkxRPKSJruWG6zYcGy3R7J0GTcxm4OXkGxa0F\nOiYI/bD7tGe278oQnPMLz2wfJxMrXeXfAH5DKfVdpdRfZK9bgd8C3v/sTO+nB+1ZeOhzEkx2rM8k\nWjaIesDM/p/07J45ch2SdVZKumb9kjR4NSdXDp4nd0rg3Llx4ZoU+0XW69kywDiZ2PxywMp1sFbK\n9rMHYdurlxrtHIut10ozamtKxsUtMes57bUSQP80Qik4801SyYgacl3CqvDNz3jDT3p2C3BzcNp1\n8nnFLZlnc1LUera8cnX7LDuaqzr8TKVhwfFPA1dUgmXHdbqay8s+B6OFceNxSk5rXtuVo5BJu7kK\nfCXufDFwXVeOC4oeI7EhytzyJmKRVvuZrjyfG2vR40mWb8B3WB9o7qxKZvKsgstoYoizceOxoeho\n3rWmwFkFl0OhIbYSpB+JUjpczdv78mzLufNuh8ZYxiJDp6P5lTVFtuU8Dkfidphay2iU0utqLir7\nTMUi5VZ05KWUyKBNx4bPT7Tpc7VIsvmafk9z/XSLw2GcZeXt/DiwTMQpR8Lj02AMUNJqPoM6FwzO\n/ft1XQH9nmYkTEkzB77DWfD/zrVFuhzFWGQwxpIYy5HEsCVw+cXeAt2uZjRKMdYSZ06BZ+Q9bqvF\nPNgUx78OVxz/itry2bE2b+jKEyhRLjFGmgBnjKiJ/EpfAYMEldqKa2MC5DX81w0VPCVygsYYYmOY\nNnBaTtPvu2Sso/nzUwh1Zq2nmU4sLpay1hQdCeoa1vKtyTYPN1IGPU2/rxnwHQoKPjrS4PVd/nF1\nrCsa7m8k7GolS8YFCv74UJ2cgplEMtxFnWXHM9rOA7WIna2YDYHOvn/CZ/+n8daKLoLvWlMktpmj\nobG0Uvl+vrk7R2EFHvWnRhocjVMGA/kODfgOsYU/OVRbdsxT4T/056mnlnpWHWokhpnU8o6+PF+f\najOTGNYHLmt9cUmcTewSfvmzAe3A9jfIwn+uWbs9IxXA039aHQattcPW2kuAP0DUNvYDf2Ctvdha\n+wJnqZ5cWCMB8dTuBS7m9B553/FFvqw1lf2xfm5pG64W03uFhlIelIAmbgglpXf7yrblRx+SjPPi\nBgs3JyX6mX3y7yQULeWZA08Wo3+uozIklI7SGpENiuri1rT9jSuP69wIl/+OUEBmD4hqx7nveOHf\nsJ4K668Qxy5rZBHiBHDphxYaeZ8rOOMN8KJflN/B7AGhbVzxn1afeQZ4U0+en+nJU0sluBrwNR8a\nLC1pKjwe3tqb57WdeWazcRsClw8OlmhZy/klj+0Fl9CIO1+Xp7mqHDCWWP58cyfXdeWE2pBYNucc\n/mpLJ0YJXzOnJAiZyiglvobH2ikf39LFNR0+o5Fhf5SyOXD46y0drA083rWmyEs7fCZiw0hkODPv\n8qHBEmXP4VNbunhJxWc4MuyPDKfnHf5maye9nsOvrS1wVcVnPDaMRoZzCh4fGCwxGhtOK7isDzRH\nI8ORyNDnaM4quNw8GwJ2CdVljkd903TIGXmXId9hOrFMJaI0ckbe5RszyzcVfGs2ZI2nySONdDFQ\nAAZ8zSPNlA8MlDi74LGznbC3nXBZ2efX1hbp9hz+ZlsXp+c0e8KU/WHKFSWPT23tpOSJU+B6X3Hz\nTMgdsyGXFh1+dU2RG6dD4VRboQ3UEoNjxdjk4VbC32/rZNBzmMk+v4uKLl/c3kNLKV7S4VNyRKM5\nVrDOV7y04lNyHf5mawd9nmYqhXoKV5RcPn9GDz+oheRZkAU0SMOhD9w4E3FhyaPTc+ZdJs/K+wz6\nLt+YbVPUIqXXMpbQiMZyIzXMGMUlRVdMa7J9DrhwTafPN2dCSo5aUqWouJqZJOW+RswlJZ+iI1KD\nsYVzCi4lrbitJooei82EuhyV8ZwleK6lht2thKNROh9QX9kR8IfrS5QdzWhiiSz8Sn+BDw6uzBe4\noxbRlSmetDKr8B5HsbudPmXD7nJ4c2+R3xkqoZTIBKbAhwaL/GJfnnvrEf3HWJD3+5r7GtH8uUzF\nhl2thOmTIL+3GJtfDue9WyqmswclMXbZf4SeZ5h5fq7jKQk51tpbgFuehbn8VKA6LGoKcxxMNw8X\nvBe0Jw/SvTfLCg4y8v2gBIvPd7iBBDJDFy0EuEpLwLuSVJ2bWz4gdnyhLvzwM9J0hRWN34t/U4LR\n5wu6t8FL/osspLT79EXm+7bD1f+PZKB/nHEvZCgljl3rr8iui/fcpDwpLdWFrdfKQvBEzNNVYqjx\nqs6AxK7s5rcYnla8rifHa7oDUrvAmz4cprhK8bLOHFdbO79tNErJZ/Jrf7Spg8iIZNhcZm5fO6Fl\nLN+rRfNKCQ4w4GkCpRgJEx5pprjK4lo4GKU83ow5u+iT14q39hV4c28eY5dyuPeHCY82U1wFnrXs\nC1OeaEacXvAoOpq39RV4S29emgmzizkcKWZiwyPNhNCKpMPDxrLdOKz3XY6nOaqQczmaiCb03ENy\nMjH4WjKfy8FXipoxRCxkpkKgnVpyjmY8TtkTJhSz+T2RBTclR/PtqQZ31kXaTwHfmo14dT3iuu48\nHz88y2fGQ+Y8VB5p1fGy7G7DwOL85izCGS440vB2WSXgnCTBAutzcrPNaYUHrA9colSUsTt9B6s0\nnhJ1ECeTRgOoG3EBLCpNSjqfJbZIxtoFKo6ibeGSsk9q7fz5H44MRa2ppQmTycK4nBLOd0krzix6\nvKQzRz1JySlwtOZwlFLQhrFjEsXWWCyKotYYLJdX3Ccdr6A1zWMa/Gz22ToIxeGGqTYooSztKHj8\ncn+BoqN5dU+Ba7tyNI1IIz4diTpfCce/tWiuBS3Ni6stBCaZk+j2nINRDsqCozQpikBJU6S76LuY\nWubf/9fxJnfVImk4tHBlxectvfkn9TacCCgFm18qfTzP5Xvuicapx+2zCJPAnR+T7OKc05yXl2Da\nLwtFIaoLxSHXscAL7lilXuJzCWvPk4Ahbi1oHLemhdfbc/ry4wYvXKAzzKE5Kc1Vbh7u+ZRwSDs2\nyHVqTojT4/MtAw2yGPhxA2ClVjfuhY756/Icv4krfeLnqZV62oHzseMWB6uDvmbQ10zE6fy2yIgS\nxoWlhZDA13pJSXudLyYuM4ml4igqjsJRsLOdsMZTfGRfldnEMBi4DOZcckrx0eEGjzUXMrrOMXNp\nJobf3j9LMzUMBQ6DOZdAwR8ON9jTSpaMWxwgrPE0P2zExNZScrQYhljLQ+2UV3T5+Jr5sjiIDJqj\nFG/uzrG7Jfq6HZ6mw9PExrKzlfDeNcVlr+Ev9+SZTiV76rLQCDeVWrb4mk8fbeAq0YnekHOJLHxq\ntMG9tZA/HWmhsXR54q4YG8sH987ypfEGfz8Woq3QKvJaVDc+sr/KOlcd130wBC4sav7X0SZFrdic\n99mS95lJDP8zk+l7op3gKOjyXbp8h6nYcjhMORomfGI0c/ULXAY8h4nE8JF9s1xYdInI1E6QRVGC\nZNjf2RsQWnGMnHMRHI8N6wOHl1V8phOLRiTifAUzRtQk3tgV0DBCRym5Dq7jMBYbtuY83t6Xp53R\nWOYwnli25hze2Junmgr9ZY7nfyQ27Ci4vKIzYDYxpFkW1lrLkdhwTtFlX5jylck2/b5myBf5wkeb\nCf8+ufCQ0Vq+K09X2/ncostEYvGwBFrhY5lILIO+syLdYyXcNhvy3dmIdTmXzTmPDTmXO2ohN82G\nXN0ZcGRRxtxmFKerOwK+PRtyRy1kKDu/IV/z3dmQW2dXkG86AXi+3HNPFE49cp9FTO6C9pRY+M7B\nL0lQvfcm6NqWCYHPyssaKX2sVi/xuYRiH1z0PuFDzbkbKSUl9ZU4uuVBuOA9QmOZPSglbseXcaP3\nAWopN7i0RuQDXwg88VM4hZ8ktFK8e02RkrPgaDieGN7Wm2dTbvmi5XBkGAo0ZS2ufdVEAu4tOZfv\nVmOmEkPPoqYmac6yfGWitew+b62G1FIJLBfGaVJruX56eWm8OzPNYV+Lm1yYBXYlrXi0kfCHGyrE\niMHHkcjQsvBfhookKLbkNK5WVFNR3XC0YkugcRzFwHFOf50LT8QGjwVJsbnGOk/B5yaahEb46XPo\ncjW11PLXI3UslvyibUVXE1rLnx6uYYHFfWC5rAnuS1Pt4/l1oYFPjrSw2CXNb32ew0RseLCRsC3n\nEtuFz6jiwFCg+aeJFhqWuPr1OoojccruyFDSCxnnOb3nHk/RQPPWnhzjseFwKLJ/na5w2bVSbMu7\ntK0SHq+BklLsyHv0BS5v6s5zNJJxh8KUPk/zzv4Cr+vK8aaePOOJ5UgklJx+X/Onmzo4u+Dyuq4c\no9m4OdWJX+gr8OKix3VdOUYWbVsfOLy9t8D3qiEdrsLLojylxPr7nlpE8xhN6aeLiuOwIXBoWkUj\ntdQt9LmKocAhNqvb53dmI/o9Pb8w0Eox4Dl8Zybk5RWfi+aURsKUQ1HKBSWfV3T43DITMuA58w3A\nWinWeA7fOcnB808bnqGw2gsbaQx7vimaunFTRMW3v0kCwVXtLwR7nDud0tIwmCtD37UiUWaNZFfr\no8JnfSFg8ELo2yH8bu1C19an5y64/nJYc65wnLUnAu/aFRmbY12IQILy1erl/jRgajc89gVZzBX7\nhX+77tIXTsZg5D740ZdF9q1zM5z5s9B/1lOPO9GwVqQsd14vEoK920UfvmvzyTmeSWHfd2D3N+R+\nsvZcOfdnojTS42kuLXl8ZapNzVguK/tsfwor8NBailpzdYfLTGJJsXQ44hI4k6RYLFOxYSY1GCvB\npAWqRgwhbpoJuW02JLSWi0o+r+2WEvpxQxCrqMbiKPfN6Tbfq4qhy8Vln9d25agbg6dhvefSyoIY\ncZNLqaWGS8sB719b4MtTbVILr+/M8dKuPI82Eyquw/aCw0zGke10hTPbSC1Xd+YoKOY1tK+o+DSt\nYjpO8LTI1bWylHBBi2FLLXMDfKQRi+W2gg2+aCLPpHaZE4SGscttmnf8C5QE0yjhH7esKKMMLJP1\nrKaGAd9hR8FjNjU4qOz8DLNZo+SRyFBPDVpBlyMR81QsWtQFLTQOV4km8lhsaRo4s+DxaDPm7npM\n2VFcVvbpdjUNC2cWXEqO8HdzGl5U8PC0JrJipvN4K+beekyno7ms7NPpKrRSvGtNEUfB3bWYblfx\njr48GwMHpRRrfM1YlPJEO6HiKM7OuxS1BMTnlTx2thIebMb0uZrLSh5lR1FPebJrIbIQiKzl+vEW\nfzZcZyw2lBzFW3sC/uu6Mo7jsLed8NWpFntaEuBf1xVwYcmnbeHarhz11DAZG8qOZq2nGI4tKbCv\nlfC1qRb72ylrfYfXdAW8uOgt4WQ/6bNNJXN+fyNlNrWUtWJbziFFqjLvWlvkNVGOyUQMXgZ8B5tx\nrmNj2N1OqRpLh6PYkl2vUzhxOJV5XgEP/h8RAHfz4iQ2fDfc/idCrVgNOjdLgLLYsMEayTxvvApQ\n8u9CrwQ12pEO/N7tJ+R0nhPw8mIk07v9x7Pl9ovZuDMWtLTXvEiC5MXN00ko218IVJeTgZn98L0/\nEe59ZZ0sEO/51AvHmXD4bvjBx+U3WlknQev3PwoTTzz7c9nzLbjvb+U3XFkn1Zbv/bFouZ8MPP4l\nuWdpVyo244/B9/5IqEyrxRcnWnx5qk2/73Bm3mVXK+Fjw3WqKzQhrfMdHCUNXN2eps9z8JQEuK/u\nylFPLWNROp+RrSZi63xx0eNzYw2+PtWi5Cj6Pc3dtYhPDNd5UUHMORZn8YyxWGW5vOLxmaMNvjkT\nUnEUPZ7m+9WQT4zUeXHRAxSplQxswVFyw7BwacXn00ca3F5NOKfgc17R595mzF+PNFiXNWMpJDjs\n9fR8hveisg8oujyHN/QWeENvgU5PTKuv7coRGdFE9rW8Wkauxas6fB5vxRwIE/JaAt5dbVGTeE1n\ngFVgFvF0UyN53Vd15rPzZdE2+e+1XTnh8trseEq4rwA/35cntCxRlwgzqsQV5YC2EdfIPs+hOzOZ\ncRVc3eEzFhtqSYqnJEg4EqU0jeVnumVcTsFg4NDvO0RWsuKbAoe/HKmzp52yPe/S5zr822SbL022\n2Ow73FuLqSaGdb5Dp+PwcDNmLE5wlOUvR+ocaKeclXfpdjX/MtHi+qk243HKx0ZqTCaGS8oe6wKH\nf5lsc8N0yCONiA/sneFwlLLO0/gKPn20yUeH64xGKR8brjMWp+zIS9D+ufEW354NOb/kMXWMZOBM\nahnwHW6fbfM7+6tMxSkVLUHoZ462+I8HqhwME/5yuM5IaBj0NZG1fOZok+9XI84rukzEKb2ewxkF\nj8HAYSq1bMs7DEcpnxiRYHzQ1zRTw6ePNLivvrKb1VpPc0ctomUsZS2L0jtqEd0u81nltdkCaMCX\nLJJSih4Xbq9FtK2MaxnL7bWItaukj5zC8XHqai6DxrjY53ZukoBPO/IAbE3LA3o1yHXA2W8XWZfq\nsFgsz+yHDVdJI91Zb4XaYdk2Rz3Y+DLJ0J7Ck9G3A4YugZm9ci1nD0um/kW/JMH2KTwZu74hi5ZC\nb6YlXRaXwh99STKXz2dYC4/9GxT65bemtMgg+iXJRD+bSGN44iuS9Z2zYS/2AeqprddXg6gOe24U\nFRavIPer0lpZTB64bXX7nE4Mt1cjNgQOea2kgcx3qKeWe+rLuxYWHc3bevMcjVNGwpSxOOVAKGXl\nrTmXdZ5YPLdMprwAdDoKq0SabGPmUOcqKXuPZ417v9CXYywWR7jx2DCaWC4tBWzJuTzWjNngi2Oh\npxTrApfR2BBbeFN3jqPZuLHYMBpbru4I6HE0u9sJGwI9b229PnA5FIn74LWdOQ5HaUbpkNL/KzoD\nXlxweXmHz6Hs/dFIKC2v7sxxXsGl2xW6RmjklQJ9jqLoOlmWXWXnLkFv2VW8rMPnnLzHTCqqGbOJ\noZrCdV0+f7SxxHpf086uWdsIp/nKistfbCoz6Ctax2y7psPj9T15Li56HAhTjkYpI1HK0Tjl53ry\nXFD2OL/kcSCSz2ckzLb15lnnO1RcRYR8Pi0DFnFmfFV3njMLLiOxYSI2HI0M04nl/WuKPNZKaKaW\ntb6Do8R5cX2guXU2YjKRLG6KaI9L4K4IUNw6GxFlJjRayQJnfeDw7dmQm6fbJBb6MxpC0dGs9x1u\nmmnzd0caWCvVEa3FqKXf03x1ss03JqVc25uNKzmaQd/hhumQi0seQ4HmYJgwHqccDoXb/vN9ef5y\npI7CzvOd846m5MD1UyFfm2zi6+x4SmXZZYfrp9u8tCOgx3M4GIpT5eFQmjDf0lPghqk2Ra3odmVc\nxdX0eZqvTrVXlM1rW8hrRZR9VyIjJjfR8crXixBbJX+3aFxRK9rL1i9OYTU4RdtYBs3xhca2xXBz\nMPMMOMhbXynBy6NfkKzpGT8jsmRz3fc9p4tldRqJj3v/jmdWTrdWGhGH7wYsDF4kWd+n2qe1MPE4\nDN8jcxu6WOZ2sio/JhVJvpH7RJlj3aXQtWXlMdqBC39d7K9HfwheUcYd63Z0CguY3gdBx9L3vIJk\nJ+PGysYsz3WYBBpHZcG7GEHHQt9AaxoOfV8WsN1bZfF1MhZaYVV+38X+pe/nKitLM64WrekFve/q\nYaGZFddI1Wy1x5tKpGRfTy0jUUKU8TiDTDoLRJHjnnpII4Vzih47Ci6uUlxWCdAKvjzZopZaXtmZ\n43XdAbvbKWcVfc4qWh5vJcQGtuQcyhr2h6JLfWx52VOK0djw4aEKF5YCvjrVIjSWV3bluK4z4KFm\ngkKoDyNhggHW+hoHy9HY8LtDRTbnHb4w1iIBXt+d41f689zflIarqcRyJE6wVjJ51sJEnPIz3TnO\nLHjcny0Uziv5nJaT8vcbugJmEsNXsiazN/XmeU2nz/dqMVeXfSaN5YmmUDPOyrt0OLA/FFm+0Fr2\ntBK0UuwoejjAtFH86+kVfn1vje/VIhzgjT05Prq+iO+63HFOD3883OCG6Ta+gl/qK/K+TD7tlh3d\nvG93jbsaES7wlp48/98WsR/9xf48na7mltk2Ba14U2+BSzPd73f0F+ieCrlltk3FUbyxp8Al5YDP\njjW4phIwlVgOhCmBhjPz7nzQ/5nTuvjyRIvv1SI6Hc2be/JcUPb52yMNAg2jYcpYkhJkix+lYG+Y\ncHbBYXcr4WCUktOK84segdbsbiUUj+M4aYGdbXEOXPJ90ApjYVdL6B/VxNDKjFIqjhiwPNZKKB/j\nthdoRRwbUuDDQ2UeqEfsaif0eQ4XlTx6PYfR2D5JTcXXmmZieayZ0u8v5QnmHcVEaPC04reHStxf\nj9kbJqz1HC4q+3S5mkNR+qS5zPURRJZl1VumEsPLOgKOxoZqKlSQQU8zltgnmRrNwVrLTGq4piNg\nNBtXcTRrMg3uUzhxOBU8L4NCn1AorFkaQCdt6Nyw+v3uuQke/ifh7joePPFVaM3A+e+S43RvldeJ\nwo++JFm3Obm7vTfDaa+BHW9bPhC2Fh79F9h1gzx8sTJu+xvgzDefuLnNH8/A/f8LDn5PAjmTijnM\nue8QC+OVoB1Y+2J5ncJTo2uzaGcvdoOKm6L24j3Ps/XalYAxrC11WQxnRY1l9hDc/qfSQ+Dm4NAd\nsPsGuPI/i53siURQkWMk7aVSk+0qrD8J/Ot8tzTVjt4LaPldzB6Ua7LxqtXts9sVPukDkahtaOBQ\nKGoJ13YF3F0L+exYEweFq+GOasiLSx7vXlPknlrEP443cVEEWnHTbJupJOW6rhwWyzrfYV2w8Pg5\nGEoD2562BLSLA+jYLth0X9URcFXHUtOXHlczEiWMRwZXi931gTClrBVrXMVN1ZjbqxEb80L9eKCR\n8KWpkPOKHoejlOkkziS/FPvDlIoj+1RKcXre5fT80sekMYbfP1jjW7OhNJ1Z+KvROvvaCW/tLaAd\nzQUFlwsyaWBxAzRsChy+Md2mlkqgZ4BHGxE9vkOXtrxtZ42HWvG8Qse/T7ZpW8v/3NZNznX5g40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1cjShpUZh+utKakRd/5FJ4dnKJtPMuoDMHL/1gebiaR7J7jw/jDyzxcFcSrNGUBKeG+8qMS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\njtX52GCBHYFc2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QWe9BueVBgDlYJkgEGy2T/7DoepeZme7S4v85BLm+DOfys/gtYIheBM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\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pgrm8JgvjOctXnvaZm1ebBst3X/F582StZJVN6RxC4gxKgZycvbjNqVnDml5zzYCYq8EY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\nl+r5jYypx/szH/E4fEKoLY8boeS15XZpiVaj2HVYox/I5Xn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N9A/+P4nIAXQx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\nAklEQVRJgcf/+kAAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ofbkYYS5Mt56", + "colab_type": "text" + }, + "source": [ + "No gráfico acima, conseguimos notar que todos os exemplos em roxo foram considerados outliers pelo DBSCAN, ou seja, não foram colocados em nenhum cluster.\n", + "Para esses casos, o DBSCAN retornará o valor -1 para indicar que o exemplo é um outlier." + ] + } + ] +} \ No newline at end of file diff --git a/4.1 Clustering/slide/Clustering.pdf b/4.1 Clustering/slide/Clustering.pdf new file mode 100644 index 0000000..3adb58c Binary files /dev/null and b/4.1 Clustering/slide/Clustering.pdf differ diff --git a/4.1 Clustering/slide/clustering.pptx b/4.1 Clustering/slide/clustering.pptx new file mode 100644 index 0000000..f5b4fca Binary files /dev/null and b/4.1 Clustering/slide/clustering.pptx differ diff --git "a/5. Algoritmos de Machine Learning e aplica\303\247\303\265es em larga escala/data/survey.csv" "b/5. Algoritmos de Machine Learning e aplica\303\247\303\265es em larga escala/data/survey.csv" new file mode 100644 index 0000000..7730f44 --- /dev/null +++ "b/5. Algoritmos de Machine Learning e aplica\303\247\303\265es em larga escala/data/survey.csv" @@ -0,0 +1,1009 @@ +Timestamp,Age,Gender,Country,state,self_employed,family_history,treatment,work_interfere,no_employees,remote_work,tech_company,benefits,care_options,wellness_program,seek_help,anonymity,leave,mental_health_consequence,phys_health_consequence,coworkers,supervisor,mental_health_interview,phys_health_interview,mental_vs_physical,obs_consequence,comments +2014-08-27 11:29:31,37,Female,United States,IL,,No,Yes,Often,6-25,No,Yes,Yes,Not sure,No,Yes,Yes,Somewhat easy,No,No,Some of them,Yes,No,Maybe,Yes,No, +2014-08-27 11:29:37,44,M,United States,IN,,No,No,Rarely,More than 1000,No,No,Don't know,No,Don't know,Don't know,Don't know,Don't know,Maybe,No,No,No,No,No,Don't know,No, +2014-08-27 11:29:44,32,Male,Canada,,,No,No,Rarely,6-25,No,Yes,No,No,No,No,Don't know,Somewhat difficult,No,No,Yes,Yes,Yes,Yes,No,No, +2014-08-27 11:29:46,31,Male,United Kingdom,,,Yes,Yes,Often,26-100,No,Yes,No,Yes,No,No,No,Somewhat difficult,Yes,Yes,Some of them,No,Maybe,Maybe,No,Yes, +2014-08-27 11:30:22,31,Male,United States,TX,,No,No,Never,100-500,Yes,Yes,Yes,No,Don't know,Don't know,Don't know,Don't know,No,No,Some of them,Yes,Yes,Yes,Don't know,No, +2014-08-27 11:31:22,33,Male,United States,TN,,Yes,No,Sometimes,6-25,No,Yes,Yes,Not sure,No,Don't know,Don't know,Don't know,No,No,Yes,Yes,No,Maybe,Don't know,No, +2014-08-27 11:31:50,35,Female,United States,MI,,Yes,Yes,Sometimes,1-5,Yes,Yes,No,No,No,No,No,Somewhat difficult,Maybe,Maybe,Some of them,No,No,No,Don't know,No, +2014-08-27 11:32:05,39,M,Canada,,,No,No,Never,1-5,Yes,Yes,No,Yes,No,No,Yes,Don't know,No,No,No,No,No,No,No,No, +2014-08-27 11:32:39,42,Female,United States,IL,,Yes,Yes,Sometimes,100-500,No,Yes,Yes,Yes,No,No,No,Very difficult,Maybe,No,Yes,Yes,No,Maybe,No,No, +2014-08-27 11:32:43,23,Male,Canada,,,No,No,Never,26-100,No,Yes,Don't know,No,Don't know,Don't know,Don't know,Don't know,No,No,Yes,Yes,Maybe,Maybe,Yes,No, +2014-08-27 11:32:44,31,Male,United States,OH,,No,Yes,Sometimes,6-25,Yes,Yes,Don't know,No,No,No,Don't know,Don't know,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 11:33:23,42,female,United States,CA,,Yes,Yes,Sometimes,26-100,No,No,Yes,Yes,No,No,Don't know,Somewhat difficult,Yes,Yes,Yes,Yes,Maybe,Maybe,No,Yes, +2014-08-27 11:33:26,36,Male,United States,CT,,Yes,No,Never,500-1000,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Don't know,No,No,Yes,Yes,No,No,Don't know,No,I'm not on my company's health insurance which could be part of the reason I answered Don't know to so many questions. +2014-08-27 11:33:57,27,Male,Canada,,,No,No,Never,6-25,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Somewhat easy,No,No,Some of them,Some of them,Maybe,Yes,Yes,No, +2014-08-27 11:34:00,29,female,United States,IL,,Yes,Yes,Rarely,26-100,No,Yes,Yes,Not sure,No,No,Don't know,Somewhat easy,No,No,Yes,Some of them,Maybe,Maybe,Don't know,No,I have chronic low-level neurological issues that have mental health side effects. One of my supervisors has also experienced similar neurological problems so I feel more comfortable being open about my issues than I would with someone without that experience. +2014-08-27 11:34:20,23,Male,United Kingdom,,,No,Yes,Sometimes,26-100,Yes,Yes,Don't know,No,Don't know,Don't know,Don't know,Very easy,Maybe,No,Some of them,No,Maybe,Maybe,No,No,My company does provide healthcare but not to me as I'm on a fixed-term contract. The mental healthcare I use is provided entirely outside of my work. +2014-08-27 11:34:37,32,Male,United States,TN,,No,Yes,Sometimes,6-25,No,Yes,Yes,Yes,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,Yes,No,No,No,No, +2014-08-27 11:34:53,46,male,United States,MD,Yes,Yes,No,Sometimes,1-5,Yes,Yes,Yes,Not sure,Yes,Don't know,Yes,Very easy,No,No,Yes,Yes,No,Yes,Yes,Yes, +2014-08-27 11:35:12,29,Male,United States,NY,No,Yes,Yes,Sometimes,100-500,No,Yes,Yes,Yes,No,No,No,Somewhat difficult,Maybe,No,Some of them,Some of them,No,No,No,No, +2014-08-27 11:35:24,31,male,United States,NC,Yes,No,No,Never,1-5,Yes,Yes,No,No,No,No,Yes,Somewhat difficult,No,No,Some of them,Some of them,No,Maybe,Yes,No, +2014-08-27 11:35:48,46,Male,United States,MA,No,No,Yes,Often,26-100,Yes,Yes,Yes,Yes,No,No,Don't know,Don't know,Maybe,No,Some of them,Yes,No,Maybe,No,No, +2014-08-27 11:36:24,41,Male,United States,IA,No,No,Yes,Never,More than 1000,No,No,Don't know,No,No,Don't know,Don't know,Don't know,Maybe,No,No,No,No,Yes,Don't know,No, +2014-08-27 11:36:48,33,male,United States,CA,No,Yes,Yes,Rarely,26-100,No,Yes,Yes,Not sure,Don't know,Yes,Yes,Don't know,No,No,Yes,Yes,No,Yes,Don't know,No,Relatively new job. Ask again later +2014-08-27 11:37:08,35,male,United States,TN,No,Yes,Yes,Sometimes,More than 1000,No,No,Yes,Yes,No,Don't know,No,Very easy,Yes,No,Some of them,Yes,No,Yes,No,No,Sometimes I think about using drugs for my mental health issues. If i use drugs I feel better +2014-08-27 11:37:23,33,male,United States,TN,No,No,No,,1-5,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Don't know,Maybe,Maybe,Some of them,No,No,No,Don't know,No, +2014-08-27 11:37:59,35,Female,United States,CA,No,Yes,Yes,Rarely,6-25,Yes,Yes,Yes,Yes,Don't know,Don't know,Don't know,Don't know,No,No,Yes,Yes,Maybe,Maybe,Yes,No, +2014-08-27 11:38:12,34,male,United States,OH,No,No,Yes,Sometimes,26-100,Yes,Yes,Don't know,Not sure,No,Don't know,Don't know,Somewhat difficult,No,No,Some of them,No,No,No,No,No, +2014-08-27 11:38:18,37,Male,United Kingdom,,No,No,No,Sometimes,6-25,No,Yes,No,No,No,No,Don't know,Very difficult,Yes,Maybe,Some of them,No,No,Maybe,No,No, +2014-08-27 11:39:03,32,Male,United Kingdom,,No,No,No,Never,6-25,Yes,Yes,No,No,No,No,Don't know,Don't know,Yes,Yes,Some of them,Some of them,No,Maybe,No,No, +2014-08-27 11:38:55,31,Male,United States,PA,Yes,Yes,No,Rarely,1-5,Yes,Yes,No,Yes,No,No,Don't know,Somewhat difficult,Yes,No,No,No,No,No,No,Yes, +2014-08-27 11:39:31,30,male,United Kingdom,,No,Yes,Yes,Sometimes,500-1000,Yes,Yes,Don't know,No,No,No,Yes,Somewhat easy,Maybe,No,Some of them,Yes,No,Yes,Don't know,No, +2014-08-27 11:39:36,42,Male,United States,WA,No,Yes,Yes,Sometimes,26-100,Yes,Yes,Yes,Yes,Yes,Yes,Yes,Very easy,Maybe,No,Some of them,Some of them,Maybe,Yes,Don't know,No,I selected my current employer based on its policies about self care and the quality of their overall health and wellness benefits. I still have residual caution from previous employers who ranged from ambivalent to indifferent to actively hostile regarding mental health concerns. +2014-08-27 11:40:51,40,female,United States,WI,No,No,Yes,Sometimes,1-5,No,Yes,Yes,Yes,No,No,Don't know,Don't know,Maybe,No,Some of them,No,No,Maybe,Yes,No, +2014-08-27 11:41:17,27,Male,United States,NY,No,No,Yes,Rarely,6-25,No,Yes,No,Yes,No,No,Don't know,Very easy,No,No,Yes,Yes,Maybe,Maybe,Don't know,No, +2014-08-27 11:41:37,29,Male,Canada,,No,No,No,Rarely,1-5,No,Yes,No,No,No,No,Don't know,Very easy,Yes,Maybe,Some of them,No,No,No,Don't know,No, +2014-08-27 11:42:08,50,M,United States,IN,No,No,No,,100-500,No,Yes,Yes,Yes,No,Don't know,Don't know,Don't know,No,No,Some of them,Yes,No,Maybe,Don't know,No, +2014-08-27 11:42:15,35,M,United States,TX,No,No,Yes,Rarely,More than 1000,Yes,Yes,Yes,Yes,No,Yes,Yes,Very easy,No,No,Yes,Yes,Maybe,Maybe,Yes,No, +2014-08-27 11:42:25,24,Male,United Kingdom,,No,No,Yes,Sometimes,6-25,No,Yes,No,No,No,No,Don't know,Don't know,Maybe,Maybe,Some of them,No,No,Yes,No,Yes, +2014-08-27 11:42:31,35,Male,United States,MI,No,No,No,,More than 1000,Yes,Yes,Yes,Not sure,Don't know,Yes,Don't know,Somewhat difficult,Yes,Yes,Some of them,No,No,Maybe,Don't know,No, +2014-08-27 11:43:07,27,Male,Canada,,No,Yes,Yes,Sometimes,1-5,No,Yes,No,Yes,No,No,Yes,Very difficult,Maybe,No,Some of them,No,No,No,Yes,No, +2014-08-27 11:43:22,30,Male,United States,IN,No,No,Yes,Sometimes,26-100,No,Yes,Don't know,No,No,No,Don't know,Don't know,No,No,No,No,No,Maybe,Don't know,No, +2014-08-27 11:43:36,38,Female,United States,TX,No,Yes,Yes,Sometimes,26-100,No,Yes,Yes,Yes,No,Yes,Yes,Somewhat easy,No,No,Some of them,Yes,No,No,Yes,No,Our health plan has covered my psychotherapy and my antidepressant medication. My manager has been aware but discreet throughout. I did get negative reviews when my depression was trashing my delivery but y'know I wasn't delivering. +2014-08-27 11:43:45,28,Male,United Kingdom,,No,No,No,,26-100,No,Yes,Don't know,Not sure,No,No,Don't know,Don't know,No,Maybe,Some of them,Yes,Maybe,Yes,Don't know,No, +2014-08-27 11:43:48,34,Male,United States,TN,No,No,No,,6-25,No,Yes,No,No,No,No,Don't know,Don't know,No,No,Yes,Yes,Maybe,Yes,Don't know,No, +2014-08-27 11:43:56,26,m,Canada,,Yes,No,No,Sometimes,1-5,No,Yes,No,Yes,Yes,No,Don't know,Don't know,No,No,Yes,Yes,No,No,Yes,No, +2014-08-27 11:44:43,30,male,United States,IL,No,Yes,Yes,Rarely,26-100,No,Yes,Yes,No,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,Yes,No,No,Don't know,No,I just started a new job last week hence a lot of don't know's +2014-08-27 11:44:55,22,M,United States,TX,No,Yes,Yes,Often,6-25,No,Yes,No,Yes,No,No,Yes,Very difficult,Maybe,No,No,No,No,Maybe,Don't know,No, +2014-08-27 11:45:32,33,Male,United States,UT,No,No,No,,100-500,Yes,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,No,No,Some of them,Yes,Maybe,Maybe,Don't know,No, +2014-08-27 11:45:33,31,M,United States,,No,No,No,,100-500,Yes,Yes,Don't know,No,Don't know,Don't know,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,Maybe,Maybe,Don't know,No, +2014-08-27 11:45:51,32,Male,United States,TN,No,No,No,Never,1-5,Yes,Yes,Don't know,Not sure,No,No,Don't know,Don't know,Maybe,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 11:46:49,27,Male-ish,United States,NY,No,Yes,Yes,Rarely,26-100,No,Yes,Yes,Yes,No,No,Yes,Don't know,Maybe,No,No,No,No,No,Don't know,No, +2014-08-27 11:46:55,32,maile,United States,TN,No,Yes,No,,6-25,Yes,Yes,Don't know,No,No,No,Don't know,Somewhat easy,No,No,Yes,Yes,No,No,Yes,No, +2014-08-27 11:47:10,24,Male,United States,NY,No,Yes,Yes,Sometimes,26-100,Yes,Yes,Don't know,No,No,No,Don't know,Don't know,No,Maybe,Some of them,Yes,Yes,Yes,No,No, +2014-08-27 11:47:33,26,Male,United States,TN,No,No,No,,26-100,No,No,No,No,No,No,Yes,Somewhat easy,No,No,Some of them,Yes,Maybe,Yes,Don't know,No, +2014-08-27 11:47:56,33,male,Canada,,No,Yes,Yes,Often,6-25,Yes,Yes,Don't know,No,No,No,No,Somewhat difficult,Yes,No,No,No,No,Maybe,Don't know,No,In addition to my own mental health issues I've known several coworkers that may be suffering and I don't know how to tell them I empathize and that I want to help. +2014-08-27 11:48:57,44,Male,United States,IA,No,Yes,Yes,Sometimes,More than 1000,No,No,Yes,No,No,Don't know,Don't know,Don't know,Yes,Maybe,Some of them,No,No,Maybe,Don't know,Yes, +2014-08-27 11:50:27,27,Male,United Kingdom,,No,No,No,Never,100-500,No,Yes,Yes,Not sure,No,Yes,Don't know,Somewhat easy,No,No,Yes,Yes,Maybe,Maybe,Yes,No, +2014-08-27 11:50:46,35,male,Canada,,No,No,No,Sometimes,6-25,No,Yes,Don't know,No,No,No,Don't know,Somewhat easy,No,No,Some of them,Yes,No,Maybe,Don't know,No, +2014-08-27 11:51:07,40,Male,United States,CA,No,Yes,No,Sometimes,More than 1000,Yes,Yes,Yes,Yes,Yes,Yes,Don't know,Don't know,Yes,Maybe,Some of them,No,No,No,No,Yes, +2014-08-27 11:52:07,36,M,United States,TX,No,No,No,Sometimes,100-500,Yes,Yes,Yes,No,Don't know,Yes,Don't know,Don't know,Maybe,No,Some of them,Some of them,Maybe,Yes,Yes,No, +2014-08-27 11:52:41,31,Female,United States,NM,No,No,No,,26-100,Yes,No,Don't know,No,Don't know,Don't know,Don't know,Don't know,Maybe,No,Some of them,No,No,Maybe,Don't know,No, +2014-08-27 11:52:44,34,Male,United States,NY,Yes,No,No,Rarely,1-5,Yes,Yes,No,No,No,No,Don't know,Don't know,Maybe,No,Some of them,No,No,No,Don't know,No, +2014-08-27 11:53:25,34,male,Canada,,No,No,No,Never,6-25,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Somewhat easy,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 11:54:27,23,Trans-female,United States,MA,No,No,No,Rarely,More than 1000,No,Yes,Yes,Yes,No,No,Yes,Somewhat difficult,Maybe,No,Yes,Yes,No,No,No,No, +2014-08-27 11:56:17,38,Male,United Kingdom,,No,No,No,,26-100,No,Yes,No,No,No,Don't know,Yes,Somewhat easy,No,No,Some of them,Yes,Maybe,Yes,Yes,No, +2014-08-27 11:56:29,33,Male,United States,CA,No,No,No,Never,More than 1000,No,Yes,Don't know,Not sure,Yes,Don't know,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,Maybe,Yes,No, +2014-08-27 11:57:30,19,Male,United Kingdom,,No,No,No,,1-5,No,Yes,No,Yes,No,No,No,Somewhat difficult,Yes,No,No,No,No,Maybe,No,No, +2014-08-27 11:57:33,25,Male,United States,WA,No,No,No,,More than 1000,Yes,Yes,Yes,Yes,Yes,Yes,Don't know,Don't know,No,No,Yes,Yes,Maybe,Yes,Yes,No, +2014-08-27 11:57:54,31,Male,United States,WA,Yes,Yes,No,Sometimes,1-5,Yes,Yes,No,No,No,No,Yes,Somewhat difficult,No,No,Yes,Yes,Maybe,Maybe,Yes,No, +2014-08-27 11:59:31,32,Male,United States,UT,No,Yes,Yes,Sometimes,26-100,Yes,Yes,No,No,No,No,Don't know,Somewhat difficult,Yes,No,Some of them,No,No,Yes,No,No, +2014-08-27 12:01:50,38,Male,United States,NY,No,Yes,No,Sometimes,100-500,Yes,Yes,Yes,Yes,No,Yes,Don't know,Don't know,No,No,Yes,Some of them,Maybe,Maybe,Yes,No, +2014-08-27 12:02:40,23,Male,United Kingdom,,No,No,No,Never,26-100,No,Yes,Yes,Not sure,Yes,Don't know,Don't know,Very easy,No,No,Some of them,Yes,Maybe,Maybe,Yes,No, +2014-08-27 12:02:52,30,male,Canada,,No,No,No,Never,26-100,No,No,No,No,No,No,Don't know,Don't know,No,No,Some of them,Yes,No,No,No,No, +2014-08-27 12:03:30,27,Cis Female,United States,NY,Yes,No,Yes,Often,1-5,Yes,Yes,Yes,Yes,Yes,Yes,Yes,Very easy,Maybe,Maybe,Some of them,Yes,No,Maybe,Yes,No, +2014-08-27 12:05:13,33,Male,United States,CA,No,Yes,No,Never,More than 1000,No,Yes,No,No,No,No,Don't know,Don't know,Yes,No,No,No,No,Maybe,No,No, +2014-08-27 12:05:37,31,Male,United States,TX,No,No,No,,26-100,No,Yes,Don't know,Not sure,No,No,Don't know,Don't know,No,No,Some of them,Yes,Maybe,Maybe,No,No, +2014-08-27 12:07:08,39,Male,United Kingdom,,Yes,No,Yes,Often,6-25,No,Yes,No,No,No,No,Don't know,Very difficult,Maybe,No,Some of them,No,No,Maybe,No,Yes, +2014-08-27 12:10:43,34,female,United States,OR,No,Yes,Yes,Rarely,500-1000,Yes,Yes,Yes,Not sure,No,Don't know,Don't know,Don't know,Yes,Maybe,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 12:11:00,29,F,United States,FL,No,No,Yes,Sometimes,26-100,No,Yes,Yes,Yes,No,No,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,Maybe,No,Yes, +2014-08-27 12:11:07,32,M,United States,IL,No,No,No,,500-1000,No,Yes,Don't know,No,No,Don't know,Don't know,Don't know,No,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 12:12:47,31,Male,United States,NY,No,No,No,Never,500-1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Somewhat easy,No,No,Some of them,Yes,No,No,Yes,No, +2014-08-27 12:13:30,40,male,United States,TX,No,No,Yes,Sometimes,26-100,No,Yes,No,Yes,No,No,Yes,Very difficult,No,No,Yes,Yes,Yes,Yes,No,No, +2014-08-27 12:14:13,34,Male,United States,OH,No,No,No,,26-100,No,Yes,Don't know,No,No,No,Don't know,Somewhat easy,Maybe,No,Some of them,No,No,Maybe,Don't know,No, +2014-08-27 12:15:19,25,F,Canada,,No,No,Yes,Sometimes,26-100,No,Yes,Yes,Yes,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,Yes,No,Maybe,Don't know,No, +2014-08-27 12:15:30,29,male,United States,MN,No,No,No,Never,26-100,No,Yes,Don't know,No,No,Don't know,Don't know,Don't know,No,No,Yes,Yes,Maybe,Maybe,No,No, +2014-08-27 12:16:21,24,Male,United States,MO,No,Yes,No,Rarely,26-100,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Somewhat easy,Maybe,Maybe,Some of them,No,No,Maybe,Don't know,No, +2014-08-27 12:18:02,33,Cis Male,United States,AZ,No,No,Yes,Sometimes,6-25,No,Yes,No,Yes,No,No,Don't know,Somewhat easy,Maybe,No,Some of them,No,No,Maybe,No,No, +2014-08-27 12:18:04,30,M,United States,IN,No,No,Yes,Often,1-5,No,Yes,No,Yes,No,No,Yes,Somewhat easy,No,No,Yes,Yes,Maybe,Maybe,Yes,No, +2014-08-27 12:18:14,26,female,Canada,,No,Yes,Yes,Sometimes,26-100,No,No,No,Yes,No,No,No,Very difficult,Yes,No,No,No,No,Maybe,No,Yes,In my previous workplace which had mental health protections policies and access to counsellors my Director went so far as to say to me in somewhat casual conversation A woman was murdered across the street. At best though she was bipolar and at worst - who knowsI have bipolar disorder. I have zero faith that an organization with policies in place could appropriately handle mental health. I have even less faith that a workplace without the policies in place could appropriately handle mental health. I can only imagine it's worse in full tech environments. +2014-08-27 12:18:38,44,Female,United States,MA,No,No,No,Never,100-500,No,Yes,Yes,Not sure,Don't know,Don't know,Don't know,Don't know,Maybe,Maybe,No,Some of them,No,No,Don't know,No, +2014-08-27 12:19:52,25,Male,United States,NY,No,Yes,No,,26-100,No,Yes,Don't know,No,Don't know,Don't know,Don't know,Very easy,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 12:20:10,33,Male,United States,WI,No,Yes,Yes,Sometimes,26-100,Yes,Yes,Yes,Yes,Yes,Yes,Yes,Somewhat easy,No,No,Some of them,Yes,Maybe,Maybe,Yes,No, +2014-08-27 12:22:55,29,Male,United States,NY,No,No,No,Never,More than 1000,No,Yes,Yes,Not sure,Yes,Don't know,Don't know,Somewhat easy,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 12:23:48,35,Male,United States,MO,No,Yes,No,Rarely,6-25,No,Yes,Yes,Not sure,No,No,Yes,Somewhat easy,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 12:23:59,35,M,United States,OR,No,Yes,Yes,Sometimes,26-100,Yes,Yes,Don't know,Not sure,No,No,Don't know,Somewhat easy,No,No,Some of them,Yes,No,Maybe,No,No,I've seen negative consequences towards mental health conditions in previous workplaces.Working remote is empowering in this way. +2014-08-27 12:28:12,34,m,United States,TN,No,Yes,No,Never,6-25,Yes,Yes,Yes,No,No,No,Don't know,Don't know,Maybe,No,No,No,No,No,Don't know,No, +2014-08-27 12:28:16,32,Male,United States,WA,No,No,Yes,Sometimes,26-100,No,Yes,Yes,No,Yes,Yes,Yes,Somewhat difficult,Maybe,No,Some of them,Yes,No,Maybe,Yes,No, +2014-08-27 12:29:25,22,Male,United States,NY,No,No,Yes,Sometimes,500-1000,No,Yes,Yes,Yes,No,Don't know,Yes,Don't know,Yes,No,No,No,No,Yes,No,No, +2014-08-27 12:31:02,28,Male,United States,CA,No,No,Yes,Sometimes,26-100,No,Yes,Yes,Yes,Yes,Yes,Yes,Somewhat easy,No,No,Some of them,Some of them,No,Maybe,Yes,No, +2014-08-27 12:31:03,45,male,United States,MO,No,Yes,Yes,Rarely,6-25,Yes,Yes,Yes,Yes,No,Yes,Yes,Very easy,No,No,Yes,Yes,Yes,Yes,Yes,No, +2014-08-27 12:31:14,32,Male,United States,NY,No,No,No,Never,100-500,No,Yes,Yes,Yes,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 12:31:28,28,male,United States,TX,No,No,No,,More than 1000,No,Yes,Don't know,No,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,No,No,Maybe,Don't know,No, +2014-08-27 12:31:34,26,Male,United Kingdom,,No,No,No,Never,6-25,No,Yes,Don't know,No,No,Don't know,Don't know,Very easy,No,No,Some of them,Some of them,No,No,Don't know,Yes, +2014-08-27 12:31:41,21,Male,United Kingdom,,Yes,No,No,Often,1-5,Yes,No,No,Yes,No,No,Yes,Very difficult,Yes,No,Some of them,Yes,No,Maybe,No,No, +2014-08-27 12:31:41,27,Male,Canada,,No,No,No,Rarely,6-25,No,No,Yes,Yes,Yes,Yes,Yes,Very easy,Maybe,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 12:31:43,18,Male,United States,CT,No,No,Yes,Rarely,1-5,Yes,Yes,No,No,No,No,Yes,Very easy,No,No,Some of them,No,No,No,Don't know,No, +2014-08-27 12:32:24,35,Male,United States,CO,No,No,No,,26-100,Yes,Yes,Don't know,Not sure,No,Don't know,Don't know,Don't know,No,No,Some of them,Yes,Maybe,Maybe,Don't know,No, +2014-08-27 12:32:59,29,Male,United States,GA,No,No,No,Never,More than 1000,No,Yes,Yes,Yes,No,Yes,Don't know,Don't know,Yes,Yes,No,No,No,No,Don't know,No, +2014-08-27 12:33:00,25,Male,United States,DC,No,No,No,,26-100,Yes,Yes,Don't know,No,No,No,Don't know,Very easy,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 12:33:23,33,Male,United States,MN,No,Yes,Yes,Sometimes,6-25,Yes,Yes,Don't know,No,Don't know,Don't know,Yes,Very easy,No,No,Yes,Yes,No,Maybe,Yes,No, +2014-08-27 12:33:36,36,Male,United States,WA,No,No,No,Often,6-25,No,Yes,Yes,No,No,No,Yes,Don't know,Maybe,No,No,No,No,No,Don't know,No, +2014-08-27 12:33:56,27,Male,Canada,,No,No,Yes,Never,100-500,No,No,Yes,Not sure,No,No,Don't know,Very difficult,Maybe,No,Some of them,Yes,No,Maybe,No,Yes, +2014-08-27 12:34:11,27,Male,United States,WA,No,Yes,No,Never,500-1000,No,Yes,Yes,No,Yes,Yes,Yes,Don't know,Yes,No,Some of them,No,No,Yes,Don't know,No, +2014-08-27 12:34:13,27,Male,United Kingdom,,No,No,No,,6-25,No,Yes,No,No,No,No,Don't know,Don't know,No,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 12:34:35,32,M,United States,OR,No,No,Yes,Rarely,100-500,No,Yes,Yes,Yes,No,Yes,Yes,Don't know,Yes,No,No,Yes,No,No,Don't know,No, +2014-08-27 12:34:48,31,Male,United Kingdom,,No,Yes,No,Sometimes,6-25,No,Yes,No,No,No,No,Don't know,Somewhat easy,Maybe,Maybe,No,No,No,No,Yes,No, +2014-08-27 12:34:57,33,Male,United States,IL,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,No,No,Don't know,Very easy,Maybe,No,Yes,Some of them,No,Yes,No,No, +2014-08-27 12:35:23,32,male,United States,CA,No,No,No,Rarely,1-5,Yes,Yes,No,Yes,No,No,Don't know,Very difficult,Maybe,No,Yes,Some of them,No,Yes,Don't know,No, +2014-08-27 12:36:03,27,Male,United States,NE,No,No,No,Never,26-100,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,No,No,Yes,Yes,Maybe,Maybe,Don't know,No, +2014-08-27 12:36:53,24,Male,Canada,,No,No,Yes,Never,26-100,No,Yes,Don't know,No,No,No,Don't know,Don't know,No,No,Some of them,Yes,Maybe,Yes,Don't know,No, +2014-08-27 12:37:09,39,M,United Kingdom,,No,No,No,Never,26-100,No,No,No,No,No,No,Don't know,Don't know,Yes,Maybe,No,No,No,No,Don't know,No, +2014-08-27 12:37:26,28,Male,United Kingdom,,No,No,No,Never,6-25,No,Yes,Don't know,No,No,No,Yes,Very easy,No,No,Some of them,Yes,Maybe,Maybe,Yes,No, +2014-08-27 12:37:31,39,Male,United States,IA,No,No,Yes,Often,More than 1000,No,Yes,Yes,Not sure,No,No,Don't know,Somewhat easy,No,No,Yes,Yes,No,No,Don't know,No, +2014-08-27 12:37:50,29,Female,United States,MD,No,No,No,,6-25,No,Yes,Don't know,No,No,Don't know,Don't know,Somewhat easy,Maybe,No,Some of them,No,No,No,Don't know,No, +2014-08-27 12:38:11,38,Male,United States,OR,No,Yes,Yes,Sometimes,100-500,No,Yes,Don't know,No,Don't know,Don't know,Don't know,Don't know,Maybe,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 12:38:18,37,Male,United Kingdom,,Yes,No,Yes,Sometimes,More than 1000,No,No,No,Yes,Yes,Yes,Yes,Very difficult,Yes,Yes,Some of them,No,No,Maybe,Yes,No,I'm not a permanent employee so do not get they benefits they get.My client is extremely supportive of permanent staff with mental health issues. +2014-08-27 12:38:25,35,M,United States,TX,No,No,No,Never,26-100,Yes,No,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,Yes,No,Some of them,No,No,Maybe,Don't know,No, +2014-08-27 12:39:14,-29,Male,United States,MN,No,No,No,,More than 1000,Yes,No,Yes,No,Don't know,Yes,Don't know,Don't know,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 12:39:18,30,Female,United States,PA,No,Yes,No,,More than 1000,Yes,Yes,Don't know,Not sure,No,Don't know,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,No,Maybe,Don't know,No,I'd be more worried about coworkers and workplace culture than the employer--they're probably legally obligated to do some things but reputation among people I work with is something else. For instance I've heard people make snide remarks about men taking paternity leave I don't want to know what they'd say about mental health leave. +2014-08-27 12:39:21,37,Male,United States,IN,No,Yes,Yes,Rarely,100-500,No,No,Yes,Yes,Yes,Yes,Don't know,Somewhat easy,Maybe,Maybe,Some of them,Yes,Maybe,Maybe,Don't know,No, +2014-08-27 12:39:48,24,M,United Kingdom,,No,No,No,Never,6-25,No,Yes,No,No,No,No,Yes,Don't know,Maybe,Maybe,No,Some of them,No,No,Don't know,No, +2014-08-27 12:39:57,23,Male,United States,WV,No,No,No,Sometimes,6-25,No,No,No,No,No,No,No,Somewhat easy,Yes,Yes,No,No,No,No,No,No, +2014-08-27 12:40:06,29,Female,United States,MI,No,No,No,,100-500,Yes,Yes,Don't know,Not sure,No,Don't know,Don't know,Don't know,Maybe,No,No,Some of them,No,Maybe,Don't know,No, +2014-08-27 12:40:36,19,Male,Canada,,Yes,Yes,No,,1-5,Yes,Yes,Don't know,Not sure,No,Yes,Yes,Somewhat easy,Maybe,No,Some of them,Some of them,Maybe,Maybe,Don't know,No, +2014-08-27 12:40:53,32,male,United States,CA,No,Yes,No,Never,26-100,No,Yes,Don't know,Not sure,No,No,Don't know,Very easy,No,No,Some of them,Some of them,No,Maybe,No,No, +2014-08-27 12:41:20,36,Male,United States,IL,No,No,No,Never,6-25,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,No,No,Some of them,Some of them,Maybe,Maybe,Don't know,No, +2014-08-27 12:41:59,37,Male,United Kingdom,,No,Yes,Yes,Rarely,More than 1000,No,No,Yes,Yes,Yes,Yes,Yes,Somewhat difficult,Yes,Maybe,Some of them,No,No,Yes,No,Yes, +2014-08-27 12:42:24,25,Male,United States,IL,No,Yes,Yes,Sometimes,26-100,No,No,Don't know,No,No,Don't know,Don't know,Somewhat difficult,Maybe,No,Some of them,Some of them,No,Maybe,No,No, +2014-08-27 12:42:52,27,Male,United States,CA,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Don't know,No,No,Don't know,Don't know,Don't know,No,No,No,Some of them,No,Maybe,Don't know,No, +2014-08-27 12:43:28,26,male,United States,OK,No,No,No,Often,26-100,No,No,Don't know,Not sure,No,No,Don't know,Don't know,Yes,Maybe,Some of them,Yes,No,Maybe,No,No, +2014-08-27 12:43:28,27,male,United States,UT,No,No,Yes,Rarely,26-100,Yes,Yes,No,Yes,No,No,Don't know,Somewhat difficult,Maybe,No,Some of them,Yes,No,No,Don't know,Yes,Had a co-worker disappear from work for a few weeks and then come back to let everyone know he was bipolar. His responsibilities and schedule were adjusted to accommodate but he got worse didn't show up didn't work etc and was eventually let go.It was tough because on the one hand he was struggling with some mental health issues but on the other hand he went through a period of months where he wasn't performing. +2014-08-27 12:43:40,25,Male,United States,IL,No,Yes,Yes,Sometimes,26-100,No,Yes,Don't know,Not sure,No,No,Don't know,Very easy,Maybe,No,Some of them,No,No,No,Don't know,Yes,Family history of depression. Currently dealing with depression and anxiety as well as drug addition.Employer provides & pays premiums on insurance which covers therapy and prescriptions. Employer allows work-from-home and unlimited PTO which makes episodes easier to control.I don't speak of my problems to anyone at work except for the people that I consider friends and even then I don't go into great detail.I would never bring up a mental health issue during an interview for fear of discrimination and rejection (and therefore greater depression). One co-worker had serious anxiety problems and would not inform his team of episodes and was eventually let go for being unresponsive. +2014-08-27 12:43:53,36,Male,United Kingdom,,No,No,Yes,Sometimes,More than 1000,No,No,Yes,Yes,Yes,Yes,Yes,Somewhat easy,Maybe,Maybe,Some of them,Some of them,No,Maybe,Don't know,Yes,I feel that my employer and colleagues have created my mental health issue. Additionally I have contributed to this by staying in the same job with the same employer for 10+ years. +2014-08-27 12:44:51,25,F,United States,NY,No,Yes,Yes,Sometimes,500-1000,No,Yes,Yes,No,No,No,Don't know,Don't know,Yes,Yes,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 12:44:51,31,M,United States,CA,No,No,No,Never,More than 1000,No,Yes,Yes,No,No,Yes,Don't know,Don't know,No,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 12:45:44,26,male,United States,MA,No,Yes,No,Rarely,6-25,No,Yes,Don't know,No,No,No,Don't know,Don't know,Maybe,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 12:46:03,33,F,United States,WA,Yes,Yes,Yes,Sometimes,1-5,No,Yes,No,Yes,Yes,Yes,Yes,Very difficult,No,No,Some of them,Yes,No,Yes,Yes,No,Many of these questions become irrelevant once 'Yes' is selected for 'Are you self-employed'. It would be preferable for there to be a 'Not Relevant' option on these. +2014-08-27 12:47:25,27,Woman,United Kingdom,,Yes,Yes,No,,1-5,Yes,Yes,No,Yes,No,No,Yes,Somewhat easy,No,No,Yes,Yes,No,Maybe,Yes,No,as a UK-based company we don't have any medical provisions as it's all provided on the National Health Service (for now!) However if we do need to take days off for any kind of health problems everyone is understanding :) +2014-08-27 12:48:06,34,Male,United States,MN,No,No,No,Never,26-100,No,Yes,No,No,No,No,Don't know,Very easy,Maybe,No,Some of them,Some of them,No,Maybe,Don't know,No, +2014-08-27 12:48:29,42,male,United States,CA,No,No,No,,6-25,No,Yes,No,Yes,No,No,Don't know,Very difficult,Maybe,No,Yes,Yes,No,Maybe,No,No, +2014-08-27 12:48:39,24,Male,United Kingdom,,No,No,No,Rarely,100-500,No,Yes,Don't know,Not sure,Yes,Don't know,Don't know,Very easy,Maybe,Maybe,Some of them,Some of them,No,Maybe,Don't know,No, +2014-08-27 12:48:40,26,Male,United Kingdom,,No,No,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,Don't know,Don't know,Yes,Somewhat easy,No,No,Yes,Yes,No,No,Don't know,No,My employer employs 17k people worldwide and my previous employer only 140 globally both have been very supportive and accommodating with my moderate depression and intense anxiety. +2014-08-27 12:48:51,31,Male,United Kingdom,,Yes,No,Yes,Often,6-25,No,Yes,Don't know,No,No,No,Don't know,Don't know,Maybe,No,Some of them,Yes,No,Maybe,Don't know,No, +2014-08-27 12:49:27,23,Female,United States,NC,No,No,No,,6-25,No,Yes,Don't know,No,No,Don't know,Don't know,Don't know,Maybe,Maybe,Some of them,Yes,No,Maybe,Yes,No, +2014-08-27 12:49:30,34,Female,Canada,,No,Yes,Yes,Sometimes,More than 1000,No,No,Yes,Yes,Yes,No,Don't know,Somewhat easy,No,No,Some of them,Yes,No,No,No,No, +2014-08-27 12:49:39,31,male,United States,MO,No,No,No,Never,26-100,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Don't know,Maybe,No,No,Some of them,No,Maybe,Don't know,No, +2014-08-27 12:50:36,28,Male,United Kingdom,,No,No,No,,100-500,No,No,No,Not sure,No,Yes,Yes,Somewhat easy,No,No,Some of them,Some of them,Maybe,Maybe,Yes,No, +2014-08-27 12:50:57,32,Female,United States,MA,No,No,Yes,Often,6-25,Yes,Yes,Yes,Not sure,Don't know,Don't know,Yes,Very easy,No,No,Yes,Yes,No,No,Yes,Yes,I am not sure about my company's healthcare because I've opted out of it and I'm covered under another policy.I currently work at a great company though in past jobs I don't think I would have felt comfortable talking about mental health at all. +2014-08-27 12:51:25,45,F,United States,CA,No,No,Yes,Sometimes,1-5,No,Yes,Yes,No,No,No,Yes,Somewhat difficult,No,No,Yes,Yes,No,No,Yes,No,In small startups it is very hard to keep mental health issues truly private no matter what management does. +2014-08-27 12:51:36,33,Male,United States,TX,No,No,No,,6-25,Yes,Yes,Don't know,No,No,No,Don't know,Very easy,No,No,Yes,Yes,No,Maybe,Don't know,No,A close family member of mine struggles with mental health so I try not to stigmatize it. My employers/coworkers also seem compassionate toward any kind of health or family needs. +2014-08-27 12:51:51,28,Female,United Kingdom,,No,No,No,Never,26-100,No,Yes,Don't know,No,No,Don't know,Yes,Somewhat easy,No,No,Yes,Yes,Maybe,Maybe,Don't know,No, +2014-08-27 12:51:55,45,M,United States,CA,No,No,Yes,Sometimes,More than 1000,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,Yes,Yes,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 12:52:08,43,Male,United States,WA,No,Yes,Yes,Often,More than 1000,Yes,Yes,Yes,Not sure,No,Don't know,Don't know,Very difficult,Yes,Maybe,No,No,No,No,No,No, +2014-08-27 12:52:46,37,male,United States,MA,No,No,No,,500-1000,Yes,Yes,Yes,No,No,No,Don't know,Don't know,Yes,No,Some of them,No,Maybe,Yes,No,No, +2014-08-27 12:52:49,24,Male,United Kingdom,,No,No,No,Sometimes,6-25,No,Yes,Don't know,No,No,Don't know,Don't know,Somewhat easy,Maybe,No,Some of them,Yes,Maybe,Yes,Yes,No, +2014-08-27 12:53:05,23,male,United Kingdom,,No,Yes,No,,1-5,Yes,Yes,Don't know,No,No,No,Don't know,Don't know,No,No,Some of them,Yes,Maybe,Yes,Don't know,No, +2014-08-27 12:53:13,35,Female,United States,CA,No,Yes,Yes,Never,More than 1000,No,Yes,Yes,Not sure,Don't know,No,Yes,Somewhat easy,Maybe,No,No,No,No,No,Don't know,No, +2014-08-27 12:53:40,28,Male,United States,MI,No,Yes,Yes,Sometimes,26-100,No,Yes,Yes,No,No,No,Don't know,Somewhat easy,Maybe,Maybe,Some of them,No,No,Maybe,No,No, +2014-08-27 12:54:11,35,Male,United States,CA,No,No,Yes,Rarely,6-25,No,Yes,No,No,No,No,Yes,Don't know,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 12:55:01,35,Female,United States,NY,No,No,No,Never,500-1000,Yes,Yes,Don't know,Not sure,No,No,Don't know,Don't know,Maybe,Maybe,Some of them,No,No,No,Don't know,No, +2014-08-27 12:55:38,26,Male,United States,CA,No,No,No,Rarely,More than 1000,No,Yes,Yes,No,No,No,Yes,Somewhat easy,No,No,Some of them,Yes,No,Maybe,No,No, +2014-08-27 12:56:13,27,Male,United States,TN,No,Yes,No,,6-25,Yes,Yes,Yes,Yes,No,No,Don't know,Somewhat easy,Maybe,Maybe,Some of them,Some of them,No,Maybe,Yes,No, +2014-08-27 12:56:56,28,Male,United Kingdom,,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Don't know,No,No,No,Don't know,Don't know,Maybe,Maybe,Some of them,No,No,Maybe,Don't know,No, +2014-08-27 12:57:38,27,Female,United States,OR,No,Yes,Yes,Sometimes,26-100,No,Yes,Yes,No,No,No,Don't know,Very easy,No,No,Some of them,Some of them,No,No,Yes,No,My seniority at the company and rapport with the owners has helped me gain support for seeking help regarding my mental health as well as being able to take time off or work from home when an episode starts.However I don't feel that the company's stance on mental health is as clear as say something like vision or dental. There's very much a stigma. +2014-08-27 12:57:52,34,female,United States,MN,No,No,Yes,Sometimes,500-1000,No,No,Yes,Yes,Yes,Yes,Yes,Somewhat easy,Maybe,No,Some of them,Yes,No,No,Yes,No, +2014-08-27 12:58:10,41,male,United States,FL,No,No,Yes,Often,6-25,Yes,Yes,No,Not sure,No,No,Don't know,Very difficult,Maybe,Maybe,Some of them,Some of them,Maybe,Maybe,Don't know,No, +2014-08-27 13:02:14,32,Male,United Kingdom,,No,Yes,Yes,Sometimes,100-500,Yes,Yes,Don't know,Not sure,No,No,Don't know,Somewhat difficult,Yes,Maybe,No,No,No,No,No,Yes,I've answered 'Yes' on remote working but 50% is the maximum time we're allowed.The branch of the company I work for doesn't offer any medical benefits. It's not as common in the UK as we have the NHS for the moment. There are international branches that may so I've answered 'Don't know'. +2014-08-27 13:03:05,21,Male,Canada,,No,No,Yes,Sometimes,6-25,Yes,Yes,No,Yes,No,No,Don't know,Somewhat difficult,No,No,Some of them,Some of them,Maybe,Maybe,Yes,No, +2014-08-27 13:04:18,30,M,United States,MA,No,No,Yes,Often,26-100,No,Yes,No,Yes,No,No,Yes,Somewhat easy,Maybe,No,Yes,Yes,No,Maybe,Don't know,No, +2014-08-27 13:04:45,24,male,United States,KS,No,No,No,Never,26-100,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Don't know,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 13:06:00,40,Female,United States,DC,No,No,No,,26-100,No,Yes,Yes,Yes,Yes,Yes,Yes,Somewhat easy,No,No,Some of them,Yes,No,No,Yes,No, +2014-08-27 13:06:12,37,Male,United Kingdom,,No,Yes,No,Sometimes,26-100,No,No,No,No,No,No,Don't know,Don't know,Yes,Maybe,Some of them,Yes,No,Maybe,Don't know,No, +2014-08-27 13:07:24,26,Male,United Kingdom,,Yes,No,Yes,Often,1-5,Yes,Yes,No,No,No,No,Don't know,Don't know,Yes,No,No,No,No,Maybe,Don't know,No, +2014-08-27 13:07:40,32,F,United States,TX,No,Yes,Yes,Sometimes,6-25,No,Yes,Don't know,No,No,No,No,Don't know,Yes,Maybe,Some of them,Some of them,No,Maybe,No,Yes, +2014-08-27 13:07:42,32,f,United States,MA,No,No,Yes,Sometimes,100-500,No,No,Yes,Yes,Don't know,Don't know,Yes,Very easy,No,No,Yes,Yes,No,Yes,Yes,No, +2014-08-27 13:07:46,27,female,United States,MI,Yes,Yes,Yes,Sometimes,1-5,Yes,Yes,No,No,Don't know,Don't know,Don't know,Very difficult,No,No,Some of them,No,No,No,Don't know,No,Many of these questions were difficult to answer as a self-employed person; I did my best with the available options. +2014-08-27 13:09:24,31,M,Canada,,Yes,No,No,,6-25,No,Yes,Yes,Yes,No,Don't know,Yes,Very easy,No,No,Some of them,Some of them,No,No,Yes,No, +2014-08-27 13:09:37,29,F,United States,NY,No,No,Yes,Never,500-1000,No,No,Yes,No,No,Don't know,Don't know,Somewhat difficult,Maybe,No,Some of them,No,No,No,Don't know,No, +2014-08-27 13:09:39,41,Male (CIS),United States,VA,No,No,No,,26-100,No,Yes,Yes,Not sure,No,No,Don't know,Very easy,Yes,No,No,Some of them,No,No,Don't know,No, +2014-08-27 13:12:31,34,female,United States,WA,No,No,No,,6-25,No,Yes,Yes,No,No,No,Don't know,Somewhat easy,No,No,Yes,Yes,Maybe,Maybe,Yes,No,One of my coworkers has mental health issues and she's open about them (eg: my enjoyment of this project may be due to my recent change in meds). I believe the response has been generally supportive. We're a very small tight-knit company. +2014-08-27 13:12:43,33,Male,United Kingdom,,No,No,No,,26-100,No,Yes,Don't know,No,No,No,Don't know,Don't know,No,No,Yes,Yes,Yes,Yes,Don't know,No, +2014-08-27 13:14:53,28,male,United States,PA,No,No,No,Rarely,6-25,No,Yes,Don't know,No,No,No,Don't know,Don't know,No,No,Some of them,Some of them,No,Maybe,Don't know,No, +2014-08-27 13:15:19,28,Male,United States,MI,No,No,Yes,Sometimes,More than 1000,No,Yes,No,Yes,No,No,Yes,Very difficult,Yes,No,No,Some of them,No,No,No,No, +2014-08-27 13:15:25,23,Male,United States,PA,No,No,No,Never,26-100,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,No,No,No,Yes,No,Yes,Yes,No,A strong mind goes a long way. Stay strong. Take some time off to help. Its all in your head. +2014-08-27 13:18:18,24,M,United States,OR,No,No,No,,1-5,No,Yes,Don't know,No,Don't know,No,Yes,Very easy,No,No,Yes,Yes,Maybe,Yes,Yes,No,Would you bring up a mental health issue with a potential employer in an interview?Poignant. +2014-08-27 13:18:44,32,male,United States,WA,No,No,No,Rarely,1-5,Yes,Yes,No,Yes,No,No,Don't know,Very difficult,No,No,Some of them,Yes,No,Maybe,Yes,No, +2014-08-27 13:21:00,24,Male,United States,PA,No,No,No,Never,6-25,No,Yes,Yes,Not sure,No,Don't know,Don't know,Very easy,Maybe,No,Some of them,No,Maybe,Maybe,Yes,No, +2014-08-27 13:22:42,26,male,United Kingdom,,Yes,No,Yes,Sometimes,1-5,No,Yes,No,Yes,No,No,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,Maybe,Yes,No, +2014-08-27 13:22:49,36,Male,United States,OH,No,No,Yes,Sometimes,26-100,No,Yes,Yes,No,No,Yes,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,Maybe,Don't know,Yes, +2014-08-27 13:23:38,41,Male,United States,TX,No,No,Yes,Rarely,500-1000,Yes,Yes,Yes,Yes,No,Don't know,Don't know,Don't know,Maybe,Maybe,Some of them,No,Maybe,Maybe,No,No,I found it difficult to answer all of the questions effectively as many of them would depend on the nature of the mental health issues as some seem more socially accepted than others. For some people telling your current supervisor that you have a history of bi-polar disorder might be easier than telling a potential employer that you have a history of compulsive gambling. They might both be bits of irrelevant information (past behavior and not indicators of future behavior). However western culture pushes us to appear as capable as possible to our supervisors in pursuit of excellence in our work. Providing information that could create a negative bias seems like a more genuine and yet more risky approach to the discussion. +2014-08-27 13:24:34,38,Male,United Kingdom,,No,No,Yes,Sometimes,More than 1000,No,No,Don't know,Not sure,Don't know,Don't know,Don't know,Very difficult,Yes,No,No,No,No,Maybe,No,No, +2014-08-27 13:24:57,38,Male,United States,NH,No,No,No,Sometimes,26-100,Yes,Yes,Don't know,Not sure,No,Don't know,Don't know,Don't know,Maybe,Maybe,Some of them,Yes,No,Maybe,No,No, +2014-08-27 13:26:54,25,Male,United Kingdom,,No,No,No,Never,26-100,No,Yes,No,No,No,No,Don't know,Somewhat difficult,Yes,Maybe,No,No,No,Maybe,No,No, +2014-08-27 13:27:18,37,Male,Canada,,No,Yes,Yes,Often,26-100,No,Yes,Yes,Yes,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,Yes,Don't know,No, +2014-08-27 13:29:45,34,Male,United Kingdom,,No,Yes,No,,6-25,No,Yes,No,No,No,No,Yes,Somewhat difficult,No,No,Some of them,Yes,No,Yes,No,Yes, +2014-08-27 13:29:57,37,F,United States,NC,No,Yes,Yes,Sometimes,More than 1000,No,No,Yes,Yes,Yes,Yes,Yes,Somewhat easy,No,No,Some of them,Some of them,No,Maybe,Yes,No, +2014-08-27 13:31:03,28,Female,Canada,,No,Yes,Yes,Sometimes,6-25,No,No,Yes,Yes,Yes,Yes,Yes,Don't know,No,No,Some of them,Yes,No,No,No,Yes, +2014-08-27 13:32:31,34,male,United States,FL,No,Yes,Yes,Sometimes,1-5,No,Yes,No,No,No,No,Don't know,Somewhat difficult,Maybe,No,Some of them,Some of them,No,Maybe,No,Yes, +2014-08-27 13:32:48,33,M,United States,CA,No,Yes,Yes,Sometimes,26-100,No,Yes,Yes,Yes,Yes,Yes,Yes,Somewhat easy,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 13:34:03,27,Male,United States,GA,No,No,No,Never,More than 1000,Yes,Yes,Yes,Yes,Don't know,Don't know,Yes,Somewhat easy,No,No,Some of them,Yes,Maybe,Maybe,Yes,No, +2014-08-27 13:35:23,40,M,United States,OH,No,No,Yes,Sometimes,More than 1000,Yes,Yes,Yes,Yes,Yes,Yes,Yes,Don't know,Yes,Maybe,No,No,No,Maybe,No,Yes,I have only discussed my mental illness with close family members. I feel completely uncomfortable discussing with anyone at my place of employment as I am concerned it would have negative consequences. +2014-08-27 13:35:40,21,Male,United States,KY,No,No,Yes,Often,6-25,No,No,Don't know,No,No,Don't know,Don't know,Don't know,Maybe,No,No,No,No,Maybe,Don't know,No, +2014-08-27 13:37:18,29,Male,United Kingdom,,No,No,No,,6-25,No,No,No,No,No,No,Yes,Very easy,No,No,Yes,Yes,Maybe,Yes,Yes,No, +2014-08-27 13:37:47,32,M,United States,NC,No,Yes,Yes,Sometimes,1-5,Yes,Yes,No,No,No,No,Don't know,Don't know,Maybe,No,Yes,Yes,No,Yes,Don't know,No, +2014-08-27 13:38:17,29,f,United States,NY,No,Yes,Yes,Rarely,500-1000,Yes,No,Yes,Yes,Yes,Don't know,Yes,Don't know,Maybe,No,Some of them,No,Maybe,Yes,Don't know,No, +2014-08-27 13:39:00,23,Male,United States,AL,No,Yes,Yes,Sometimes,26-100,Yes,No,Don't know,No,No,Don't know,Yes,Somewhat easy,Maybe,No,Some of them,Some of them,No,Yes,Yes,No, +2014-08-27 13:40:58,28,Male,United States,GA,No,Yes,No,,100-500,No,Yes,Yes,No,No,Don't know,Yes,Somewhat easy,No,No,Some of them,Yes,No,Maybe,Yes,Yes, +2014-08-27 13:42:38,31,male,United States,CA,No,Yes,Yes,Rarely,100-500,Yes,Yes,Yes,Yes,Yes,Don't know,Yes,Very easy,No,No,Some of them,Yes,No,Maybe,Yes,No, +2014-08-27 13:44:05,27,Male,United Kingdom,,No,No,No,,100-500,No,No,Don't know,Not sure,Don't know,Don't know,No,Very easy,Maybe,Maybe,Yes,Yes,No,No,Don't know,No, +2014-08-27 13:44:47,24,Male,United States,VA,No,No,No,Sometimes,6-25,No,Yes,Don't know,No,Don't know,Don't know,Don't know,Don't know,No,No,Yes,Yes,Maybe,Maybe,Don't know,No, +2014-08-27 13:46:03,29,Male,Canada,,No,No,No,Often,6-25,No,Yes,No,No,No,No,Don't know,Somewhat difficult,Yes,No,No,No,No,Maybe,Don't know,No, +2014-08-27 13:47:05,23,Female,United Kingdom,,No,No,Yes,Sometimes,6-25,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,No,Maybe,Yes,No, +2014-08-27 13:47:27,42,Male,United States,WA,No,No,No,Never,6-25,Yes,Yes,No,Yes,No,Yes,Don't know,Somewhat easy,No,No,Some of them,Yes,No,No,Yes,No,No benefits at this organization but my employer/direct supervisor has had positive and constructive conversations with me about physical and mental health. Supervisor offered solutions advice time/energy to get help if I ever felt that needed it. (though it would have to be at my own expense). I feel safe sharing personal info with this particular person/company but this environment is the exception rather than the norm in my 15+ years as a tech worker. I would never feel safe enough to reveal info about any mental health concerns with any previous employers in the tech industry for fear of negative perceptions job loss performance dings etc. +2014-08-27 13:48:01,24,Male,United Kingdom,,No,No,No,,1-5,No,Yes,No,No,No,No,Don't know,Don't know,Yes,No,Some of them,Some of them,No,Yes,No,No, +2014-08-27 13:49:32,27,Female,United States,TX,No,No,Yes,Rarely,6-25,No,Yes,Yes,No,No,No,Yes,Don't know,Maybe,Maybe,Yes,No,No,Maybe,Don't know,No, +2014-08-27 13:52:05,27,Male,Canada,,No,No,No,Sometimes,6-25,Yes,Yes,No,Yes,No,No,No,Very difficult,Yes,Yes,Some of them,Some of them,No,Maybe,No,No, +2014-08-27 13:52:57,30,Male,United States,FL,No,No,Yes,Sometimes,100-500,Yes,Yes,Yes,Yes,No,Yes,Yes,Don't know,No,No,Yes,Yes,Maybe,No,Yes,No, +2014-08-27 13:53:44,43,Male,Canada,,Yes,No,No,,6-25,Yes,Yes,No,Not sure,No,No,Don't know,Somewhat easy,Maybe,No,Yes,Yes,Yes,Yes,Don't know,No, +2014-08-27 13:53:51,32,male,United States,NV,No,No,No,,6-25,No,Yes,No,Yes,No,Don't know,Don't know,Very easy,No,No,Some of them,Yes,No,Maybe,Don't know,No, +2014-08-27 13:54:00,41,Male,United States,AL,No,No,Yes,Sometimes,26-100,Yes,Yes,Yes,Yes,Don't know,No,Don't know,Very easy,No,No,Yes,Yes,Yes,Yes,Yes,No,I think I am very lucky in my workplace. Our CEO has a degree in psychology. +2014-08-27 13:54:24,32,Male,United Kingdom,,Yes,Yes,Yes,Sometimes,1-5,Yes,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Very easy,Maybe,Maybe,Yes,Some of them,Maybe,Maybe,Don't know,Yes,Some of these questions were difficult to answer as being self-employed they didn't all apply to me. +2014-08-27 13:55:16,37,Female,United States,CA,No,Yes,Yes,Often,26-100,No,Yes,Yes,Yes,No,No,Yes,Don't know,Maybe,No,Some of them,Some of them,No,Yes,Don't know,No, +2014-08-27 13:55:22,32,Male,United States,CO,No,No,No,Never,6-25,Yes,Yes,No,No,No,No,Don't know,Very easy,No,No,Yes,Yes,No,No,Don't know,No, +2014-08-27 13:56:27,23,female,United States,MN,No,Yes,Yes,Never,100-500,No,No,Yes,No,Don't know,Don't know,Yes,Don't know,No,No,Some of them,Yes,Maybe,Maybe,Yes,No, +2014-08-27 13:56:35,30,Male,United States,NJ,No,No,No,,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Very easy,No,No,Some of them,Yes,No,No,Yes,No, +2014-08-27 13:59:24,34,male,United Kingdom,,No,No,No,Sometimes,26-100,No,Yes,No,Yes,No,No,Don't know,Somewhat easy,Maybe,Maybe,Yes,Some of them,No,No,Don't know,No, +2014-08-27 13:59:35,38,Male,United States,PA,No,No,Yes,Rarely,26-100,Yes,Yes,Yes,No,No,No,Don't know,Don't know,Yes,No,No,No,No,Maybe,No,No, +2014-08-27 14:01:25,33,Male,Canada,,No,No,No,,100-500,No,Yes,Yes,No,Yes,Yes,Yes,Don't know,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 14:01:35,34,male,United States,MO,No,No,No,,26-100,No,No,Yes,No,No,No,Don't know,Don't know,Maybe,No,Some of them,No,No,No,Don't know,No, +2014-08-27 14:03:16,28,male,United States,MN,No,No,Yes,Rarely,100-500,No,No,Yes,Yes,Yes,Don't know,Don't know,Very easy,Maybe,No,Some of them,Some of them,No,No,Yes,No, +2014-08-27 14:03:54,23,Male,United States,PA,No,Yes,No,Sometimes,100-500,No,Yes,Don't know,No,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,No,No,Maybe,No,No, +2014-08-27 14:10:15,18,male,United States,TX,No,No,Yes,Sometimes,6-25,No,Yes,Don't know,No,No,Don't know,Don't know,Don't know,Yes,No,No,No,No,Maybe,Don't know,No, +2014-08-27 14:10:47,35,male,United States,NY,No,Yes,Yes,Sometimes,26-100,No,Yes,Yes,Yes,No,No,Yes,Somewhat difficult,Yes,No,No,Some of them,No,Maybe,Don't know,No, +2014-08-27 14:10:53,25,Male,Canada,,No,No,No,,100-500,No,No,Don't know,Not sure,No,No,Don't know,Don't know,No,No,Some of them,Some of them,No,Yes,No,No, +2014-08-27 14:11:46,27,Male,United Kingdom,,No,Yes,Yes,Sometimes,6-25,No,Yes,No,No,No,No,Yes,Somewhat easy,Maybe,Maybe,Yes,Yes,Yes,Yes,Yes,No,Hi Ed it's Paul Dragoonis. I have Aspergers/High Functioning Autism :-) +2014-08-27 14:11:52,26,Female,United States,WA,No,Yes,Yes,Rarely,More than 1000,No,Yes,Yes,Not sure,Don't know,Don't know,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 14:11:55,18,Male,United States,WA,No,No,No,Never,26-100,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Very easy,No,No,Some of them,Some of them,No,Maybe,Yes,No, +2014-08-27 14:13:02,38,Female,United States,TX,No,No,Yes,Sometimes,1-5,No,Yes,No,Yes,No,No,Don't know,Don't know,No,Maybe,Some of them,No,No,No,Don't know,Yes,The form of mental health problem that I suffer is anxiety. +2014-08-27 14:13:16,26,Female,United States,TX,No,Yes,Yes,Rarely,More than 1000,Yes,Yes,Yes,Yes,Yes,Don't know,Don't know,Somewhat easy,Maybe,No,Some of them,No,No,No,Don't know,No, +2014-08-27 14:14:52,35,male,United States,CA,No,No,No,Never,More than 1000,No,Yes,Don't know,No,No,Don't know,Don't know,Don't know,Yes,Maybe,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 14:15:13,45,male,United States,NY,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,Don't know,Don't know,Yes,Don't know,Maybe,No,Some of them,Some of them,No,Maybe,Don't know,No, +2014-08-27 14:15:21,32,Male,United States,CA,No,No,No,Never,More than 1000,No,Yes,Yes,No,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 14:15:57,56,Male,United States,,No,No,Yes,Never,More than 1000,No,Yes,Yes,Not sure,Don't know,Don't know,Don't know,Don't know,No,Maybe,Yes,Some of them,No,Maybe,Don't know,No, +2014-08-27 14:16:00,24,Female,United States,CA,No,No,No,,500-1000,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Don't know,Maybe,Maybe,Some of them,No,No,Maybe,No,No, +2014-08-27 14:18:20,30,F,United States,SC,No,Yes,Yes,Sometimes,26-100,No,Yes,Yes,Yes,Yes,Don't know,Don't know,Very easy,No,No,Yes,Yes,No,Yes,Yes,No, +2014-08-27 14:18:41,60,male,United States,CA,No,No,No,,More than 1000,No,Yes,Yes,No,Don't know,Yes,Don't know,Don't know,No,No,Some of them,Yes,Maybe,Maybe,Yes,No, +2014-08-27 14:18:44,33,Male,United States,CA,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Yes,No,Yes,Yes,Don't know,Don't know,Yes,No,No,No,No,Maybe,Don't know,No, +2014-08-27 14:19:08,37,M,United States,NY,No,No,No,Never,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Don't know,Don't know,No,No,Some of them,Yes,Maybe,Maybe,Don't know,No, +2014-08-27 14:19:12,23,Female,United States,NY,No,No,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Don't know,Don't know,No,No,Some of them,Some of them,No,No,Yes,No, +2014-08-27 14:20:08,31,f,United States,CA,No,No,Yes,Sometimes,More than 1000,No,Yes,Yes,Not sure,Don't know,Don't know,Yes,Somewhat easy,No,No,Yes,Yes,No,No,Yes,No, +2014-08-27 14:20:43,26,Male,United States,MA,No,No,No,Rarely,100-500,No,Yes,Yes,Not sure,No,Don't know,Don't know,Don't know,No,No,Some of them,Yes,No,Maybe,Don't know,No, +2014-08-27 14:21:37,28,female,United States,WA,No,Yes,Yes,Often,100-500,Yes,No,Yes,Yes,Yes,Yes,Yes,Somewhat easy,Yes,No,Some of them,Yes,No,No,Yes,No, +2014-08-27 14:21:42,37,F,United States,CA,No,No,Yes,Rarely,More than 1000,No,Yes,Yes,Yes,Don't know,Yes,Don't know,Somewhat easy,No,No,Some of them,Yes,No,No,Yes,No, +2014-08-27 14:22:00,26,male,Canada,,No,Yes,Yes,Often,6-25,No,Yes,Yes,No,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,Some of them,Maybe,Maybe,Yes,No, +2014-08-27 14:22:36,30,queer/she/they,United States,IL,No,Yes,Yes,Rarely,26-100,No,Yes,Yes,Not sure,No,No,Don't know,Somewhat easy,Maybe,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 14:22:43,26,M,United States,IN,No,No,No,,26-100,No,Yes,No,No,No,No,Don't know,Don't know,No,No,Some of them,Some of them,No,No,Don't know,Yes, +2014-08-27 14:22:43,25,Male,United States,OR,No,No,No,,26-100,Yes,Yes,Don't know,Not sure,No,Don't know,Don't know,Don't know,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 14:23:51,27,Male,United States,TN,No,No,No,Sometimes,100-500,No,Yes,Yes,Not sure,Yes,Yes,Don't know,Don't know,Maybe,No,Some of them,Yes,No,Maybe,Don't know,No,The thought of going through my employer directly to get help is fucking scary.Getting help is the hardest part of getting help. +2014-08-27 14:23:53,25,Male,Canada,,No,No,Yes,Often,6-25,Yes,No,Don't know,No,No,Don't know,Don't know,Somewhat difficult,Yes,Maybe,No,No,No,Maybe,Don't know,No, +2014-08-27 14:24:15,35,male,United States,OR,No,No,Yes,Rarely,100-500,No,Yes,Yes,Not sure,Don't know,Yes,Don't know,Don't know,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 14:25:41,36,Male,United States,WA,Yes,No,Yes,Never,1-5,No,Yes,No,Yes,No,No,Don't know,Somewhat easy,Maybe,No,Some of them,Yes,No,No,Yes,No, +2014-08-27 14:25:54,26,Male,United States,CA,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Yes,Not sure,No,Don't know,Don't know,Don't know,Yes,No,No,No,No,No,No,No, +2014-08-27 14:26:32,27,Male,United States,CA,No,Yes,No,,More than 1000,No,Yes,Don't know,No,Don't know,Don't know,Don't know,Very easy,No,No,Yes,Yes,Maybe,Maybe,Yes,No,Don't know because I haven't checked not because it's difficult to find out. If you didn't have the don't know option I would've looked up the answer. +2014-08-27 14:27:20,30,male,United States,VT,No,No,No,,6-25,No,No,Don't know,Not sure,No,Don't know,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 14:27:27,29,M,United States,NY,No,No,No,,100-500,No,No,Don't know,Not sure,No,Don't know,Don't know,Don't know,Maybe,No,No,No,No,Maybe,Don't know,No, +2014-08-27 14:27:28,25,Male,United States,UT,No,No,No,Never,More than 1000,No,No,Yes,Yes,Yes,Yes,Yes,Very easy,No,No,Some of them,Yes,Maybe,Maybe,Yes,No, +2014-08-27 14:27:51,22,Female,United States,NY,No,Yes,Yes,Often,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Somewhat easy,Maybe,No,No,Some of them,No,No,Yes,Yes, +2014-08-27 14:28:41,41,Male,United States,SD,No,Yes,Yes,Rarely,100-500,Yes,Yes,Yes,Yes,Don't know,Yes,Yes,Somewhat easy,No,No,Some of them,Yes,Maybe,Maybe,Yes,No, +2014-08-27 14:28:43,29,Male,United States,CA,No,No,Yes,Sometimes,More than 1000,No,Yes,Yes,No,No,Don't know,Don't know,Don't know,Yes,No,Some of them,Some of them,No,Maybe,No,No, +2014-08-27 14:28:49,32,Male,United States,OR,No,No,No,Never,500-1000,No,Yes,Yes,Not sure,Don't know,Yes,Yes,Somewhat easy,No,No,Some of them,Yes,Maybe,Maybe,Yes,No, +2014-08-27 14:28:51,24,female,United States,CA,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,No,Yes,Yes,Don't know,Maybe,No,Some of them,No,No,Maybe,Don't know,No, +2014-08-27 14:29:19,25,Male,United States,CA,No,No,Yes,Rarely,6-25,No,Yes,Yes,No,Don't know,No,Don't know,Don't know,Maybe,No,No,No,No,No,Don't know,No, +2014-08-27 14:30:33,25,m,United States,CA,No,No,No,,More than 1000,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,Maybe,No,No,No,No,Maybe,Don't know,No, +2014-08-27 14:31:06,30,Female,United States,CO,No,No,No,Never,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Somewhat easy,Maybe,Maybe,No,Some of them,No,No,Don't know,No, +2014-08-27 14:31:28,25,Male,United States,CA,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Don't know,Not sure,Don't know,Yes,Don't know,Don't know,No,No,Yes,Yes,No,No,Yes,No, +2014-08-27 14:31:44,30,Male,United States,OH,Yes,No,No,Never,1-5,Yes,Yes,No,Yes,No,No,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,Maybe,Don't know,No, +2014-08-27 14:32:46,24,Male,United States,WA,No,No,No,,26-100,No,Yes,Yes,Not sure,Yes,Yes,Yes,Very easy,No,No,Some of them,Some of them,No,Maybe,Yes,No, +2014-08-27 14:33:44,25,Male,Canada,,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,No,Don't know,Don't know,Don't know,Yes,Maybe,Some of them,No,No,No,No,No, +2014-08-27 14:34:47,31,Male,United States,OH,No,No,No,,100-500,No,No,Don't know,No,No,No,Yes,Somewhat easy,Maybe,No,No,No,No,Yes,No,No, +2014-08-27 14:37:46,46,M,United States,WA,No,No,No,Never,26-100,No,Yes,Yes,Not sure,Yes,Don't know,Don't know,Very easy,No,No,Some of them,Some of them,Maybe,Maybe,Don't know,No, +2014-08-27 14:38:06,30,Male,United Kingdom,,No,No,Yes,Sometimes,26-100,No,Yes,Don't know,No,No,Don't know,Don't know,Don't know,Yes,Maybe,No,No,No,Maybe,Don't know,No, +2014-08-27 14:38:13,29,F,United States,CA,Yes,No,No,Sometimes,More than 1000,No,Yes,Yes,Not sure,Don't know,No,Don't know,Very easy,Maybe,Maybe,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 14:38:26,24,Male,United States,MA,No,No,No,,More than 1000,No,Yes,Yes,Yes,Don't know,Don't know,Yes,Don't know,Yes,No,No,No,No,Maybe,Don't know,No,I think there might be some bugs in my thought but I haven't sought treatment because they're not worse than annoying and I worry about having the label. +2014-08-27 14:38:49,29,male,United States,WA,No,No,No,,26-100,No,Yes,Yes,Yes,Yes,Yes,Yes,Very easy,No,No,Some of them,Yes,No,Maybe,Yes,No,I think a lot of our policy is based on a situation that occurred in the past 5 years. A very public mental illness happened with a coworker that unfortunately ended negatively. It was definitely a catalyst to talking about our options but the overall sentiment of it being OK to take time off talk with your supervisors etc. has always been there. It's a great company. +2014-08-27 14:38:54,35,Male,United States,MI,No,No,No,,26-100,No,No,Don't know,Not sure,No,Don't know,Don't know,Don't know,No,No,Yes,Yes,No,No,No,No, +2014-08-27 14:39:07,33,f,United States,WA,No,Yes,No,Sometimes,26-100,Yes,Yes,No,Yes,No,No,Don't know,Very difficult,Yes,Maybe,Some of them,Some of them,No,Maybe,No,No, +2014-08-27 14:39:20,27,Male,United States,CA,No,No,No,Sometimes,More than 1000,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Very easy,Yes,No,No,No,No,Maybe,No,No,Regardless of a stated lack of negative consequences for discussing mental health issues with coworkers/superiors unconscious bias is a very real thing - as long as I don't *need* to inform my co-workers my mental health issues do not need to be public knowledge. +2014-08-27 14:41:09,36,Male,United States,IA,No,No,No,,More than 1000,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 14:41:16,33,Male,United Kingdom,,No,No,No,Rarely,1-5,Yes,Yes,Don't know,No,No,No,Don't know,Don't know,Yes,Maybe,No,No,No,Maybe,No,No, +2014-08-27 14:44:29,25,F,United States,WA,No,Yes,Yes,Sometimes,26-100,No,Yes,Yes,Yes,No,No,Yes,Don't know,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 14:45:12,23,Male,United States,AL,No,Yes,Yes,Sometimes,100-500,No,No,Don't know,No,No,No,Don't know,Don't know,No,No,Yes,Yes,Maybe,Yes,Don't know,No,YOU MAY WANT TO THROW OUT MY ENTRY.I answered all of these questions with the assumption that Attention Deficit Disorder is considered a mental illness and with ADD in mind. +2014-08-27 14:45:45,54,M,United States,CA,No,Yes,Yes,Never,More than 1000,No,Yes,Don't know,No,Yes,Yes,Don't know,Don't know,No,No,No,Yes,No,No,Don't know,No, +2014-08-27 14:47:10,22,Male,United States,CA,No,No,No,Sometimes,More than 1000,No,Yes,Don't know,No,Don't know,Don't know,Don't know,Don't know,Maybe,No,Some of them,No,No,Maybe,Don't know,No, +2014-08-27 14:47:28,25,non-binary,United States,CA,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,Don't know,Don't know,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,No,Yes,No, +2014-08-27 14:49:30,27,Male,United States,MA,No,No,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Don't know,No,No,No,No,No,Yes,Yes,No, +2014-08-27 14:51:29,30,Male,United Kingdom,,No,No,No,Never,6-25,No,Yes,No,No,No,Don't know,Don't know,Very easy,No,No,Some of them,Yes,No,Maybe,Yes,No,A co-worker recently had mental health issues and my employer was very reasonable with them I don't know the full story but I do know that he was given ample time off and eased back in to the work place. +2014-08-27 14:52:44,26,male,United States,CA,No,Yes,Yes,Often,More than 1000,No,Yes,Yes,Not sure,Don't know,Yes,Don't know,Don't know,Maybe,No,Some of them,No,No,No,Don't know,No, +2014-08-27 14:53:11,31,Male,United States,CA,No,No,Yes,Sometimes,500-1000,No,No,No,Yes,No,Don't know,Yes,Don't know,No,No,Some of them,No,No,No,No,No, +2014-08-27 14:54:23,33,M,United States,IN,No,Yes,Yes,Sometimes,26-100,No,Yes,Don't know,Not sure,No,No,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 14:54:56,34,M,United States,WA,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,Don't know,Yes,Yes,Don't know,Maybe,Maybe,No,No,No,No,Don't know,No, +2014-08-27 14:57:46,34,Male,United States,WA,No,No,Yes,Sometimes,100-500,Yes,Yes,No,No,No,No,Don't know,Somewhat easy,Yes,Yes,Some of them,Some of them,No,Maybe,Don't know,No, +2014-08-27 14:58:01,29,M,United States,IN,Yes,No,No,,1-5,Yes,Yes,No,Yes,No,No,Yes,Very easy,No,No,Yes,Yes,Maybe,Maybe,Yes,No, +2014-08-27 14:59:59,33,Femake,United States,WA,No,No,No,,6-25,No,Yes,No,No,No,No,Don't know,Somewhat difficult,Maybe,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 15:04:41,26,male,United States,OK,Yes,Yes,Yes,Rarely,100-500,Yes,No,No,No,No,Don't know,No,Don't know,Maybe,No,Some of them,Yes,No,Yes,No,No, +2014-08-27 15:05:00,32,Male,United States,MI,No,Yes,Yes,Rarely,More than 1000,No,No,Yes,Yes,Yes,Yes,Yes,Don't know,No,No,Some of them,Yes,No,Yes,Yes,No, +2014-08-27 15:05:21,329,Male,United States,OH,No,No,Yes,Often,6-25,Yes,Yes,Yes,Yes,No,No,Don't know,Don't know,Maybe,No,Some of them,No,No,No,No,No, +2014-08-27 15:09:58,28,Male,United States,GA,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Somewhat difficult,Maybe,Maybe,No,No,No,No,No,No, +2014-08-27 15:11:30,35,Male,United States,CA,No,Yes,No,,More than 1000,No,Yes,Yes,No,Yes,Yes,Yes,Very easy,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 15:13:33,36,Male,United States,,No,Yes,Yes,Often,100-500,No,Yes,No,Yes,No,No,Yes,Very easy,No,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 15:14:50,21,Male,United States,IN,No,Yes,Yes,Rarely,100-500,No,Yes,Yes,No,No,Don't know,Yes,Don't know,No,No,Yes,Yes,Maybe,Maybe,Don't know,No, +2014-08-27 15:15:29,21,Male,United Kingdom,,No,No,Yes,Sometimes,6-25,No,No,Don't know,Not sure,No,No,No,Very easy,Yes,No,Some of them,No,No,Maybe,No,No, +2014-08-27 15:15:42,22,F,United States,WA,No,No,No,,More than 1000,No,Yes,Yes,No,Yes,Yes,Yes,Somewhat easy,No,No,No,Some of them,No,No,Yes,No, +2014-08-27 15:20:53,41,m,United States,WA,No,Yes,Yes,Often,More than 1000,No,Yes,Yes,No,Yes,Yes,Don't know,Somewhat difficult,Maybe,No,Yes,Some of them,No,Maybe,No,Yes, +2014-08-27 15:21:59,55,M,United States,PA,No,Yes,Yes,Rarely,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Very easy,No,No,Yes,Yes,No,No,Yes,No,My refer to the mental health issue of depression. I might answer differently if I was talking about a more serious issue like schizophrenia +2014-08-27 15:22:20,32,F,United States,WA,No,No,Yes,Sometimes,26-100,No,Yes,Yes,Yes,Yes,Yes,Yes,Somewhat easy,Maybe,No,Some of them,Yes,No,Maybe,Yes,No,My employer does what they can providing a wellness program and pointing it out after particularly stressful times. But the interaction between the wellness program and the medical insurance is unpleasant and finding a long-term therapist / psychiatrist covered by insurance is amazingly difficult. My current lack of active treatment is due to insurance friction more than workplace friction. +2014-08-27 15:22:26,21,F,United States,CA,No,Yes,Yes,Rarely,26-100,No,Yes,Don't know,Not sure,Don't know,No,Don't know,Somewhat easy,Yes,No,Some of them,No,No,Yes,Don't know,No, +2014-08-27 15:22:43,45,M,United States,MA,No,No,Yes,Never,26-100,Yes,Yes,Yes,Yes,Don't know,Don't know,Don't know,Don't know,Maybe,No,No,Some of them,No,Maybe,Don't know,No, +2014-08-27 15:22:45,27,female,United States,WA,No,No,Yes,Rarely,More than 1000,No,Yes,Yes,Yes,No,No,Yes,Don't know,Yes,Maybe,No,No,No,No,No,No, +2014-08-27 15:22:50,25,Female,United States,WA,No,Yes,Yes,Sometimes,26-100,Yes,Yes,Don't know,No,No,No,Don't know,Don't know,Maybe,No,Some of them,Yes,No,No,Yes,No, +2014-08-27 15:22:52,34,woman,United States,NY,No,Yes,Yes,Rarely,More than 1000,No,No,Yes,Yes,Yes,Yes,Yes,Very difficult,Maybe,Maybe,Some of them,Some of them,No,No,Yes,No,I work for a university. +2014-08-27 15:23:06,26,F,United States,CA,No,Yes,Yes,Never,More than 1000,No,Yes,Yes,Yes,No,Yes,Yes,Don't know,Maybe,No,No,No,No,No,Don't know,No, +2014-08-27 15:23:07,41,Male,Canada,,No,No,Yes,Never,500-1000,No,Yes,Yes,Not sure,No,Don't know,Don't know,Somewhat easy,No,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 15:23:19,27,Male,United States,CA,No,No,Yes,Rarely,More than 1000,No,Yes,Yes,No,Yes,Yes,Yes,Don't know,No,No,Some of them,Yes,No,Maybe,Yes,No, +2014-08-27 15:23:30,31,Make,United States,IN,No,Yes,Yes,Sometimes,26-100,Yes,Yes,Yes,No,No,No,Don't know,Don't know,No,No,Yes,Yes,No,No,Don't know,No, +2014-08-27 15:23:51,26,M,United States,NV,No,No,Yes,Sometimes,6-25,No,Yes,Don't know,No,No,No,Don't know,Don't know,Yes,Yes,Some of them,No,No,No,No,No, +2014-08-27 15:23:51,27,female,United States,CO,No,Yes,Yes,Rarely,More than 1000,Yes,Yes,Yes,Yes,No,Don't know,Don't know,Don't know,Maybe,Maybe,No,Yes,No,No,Don't know,No, +2014-08-27 15:24:22,29,Nah,United States,CA,Yes,Yes,Yes,Sometimes,1-5,Yes,Yes,Yes,Yes,No,No,Don't know,Very difficult,Yes,No,Some of them,No,No,Maybe,No,No, +2014-08-27 15:24:27,25,female,United States,CA,No,No,Yes,Sometimes,6-25,No,Yes,Don't know,Not sure,No,No,Don't know,Somewhat difficult,Yes,No,Some of them,No,No,Maybe,Don't know,No, +2014-08-27 15:24:47,40,female,United States,PA,No,Yes,Yes,Rarely,More than 1000,No,No,Yes,No,Don't know,Don't know,Don't know,Somewhat easy,Maybe,Maybe,No,No,No,No,Don't know,No, +2014-08-27 15:24:49,31,Male,United States,SC,No,No,No,Never,More than 1000,No,Yes,Don't know,No,No,Don't know,Don't know,Somewhat easy,Yes,No,Some of them,No,No,No,Don't know,No, +2014-08-27 15:24:55,26,Male,Canada,,No,Yes,Yes,Often,26-100,Yes,Yes,Don't know,No,Don't know,Don't know,Don't know,Very easy,No,No,Yes,Yes,No,No,Yes,No, +2014-08-27 15:24:56,24,female,United States,TX,No,Yes,No,,500-1000,No,No,No,No,No,No,No,Very difficult,Yes,Maybe,No,No,No,Maybe,No,Yes, +2014-08-27 15:25:03,29,Male,United States,TX,No,No,No,Never,More than 1000,No,No,Yes,Not sure,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 15:25:09,48,M,United Kingdom,,No,No,No,,26-100,No,Yes,Don't know,No,No,No,Don't know,Don't know,Maybe,Maybe,No,No,No,No,No,No, +2014-08-27 15:25:16,35,Male,United Kingdom,,No,No,No,Sometimes,6-25,No,Yes,No,No,No,No,Don't know,Very difficult,Maybe,Maybe,Some of them,Yes,No,Maybe,No,Yes, +2014-08-27 15:25:41,32,female,United States,AL,No,No,No,Never,100-500,No,Yes,Don't know,Not sure,No,No,Don't know,Don't know,Maybe,No,No,Some of them,No,Maybe,Don't know,No, +2014-08-27 15:25:47,29,Male,Canada,,No,No,Yes,Sometimes,100-500,No,Yes,Don't know,Not sure,Don't know,Don't know,Yes,Somewhat easy,Maybe,No,Some of them,Some of them,No,Maybe,Yes,No,Being in Canada there are several health options that are available to Canadian citizens/perm residents for free so employers may not provide resources because they are available elsewhere. Otherwise good quiz. I hope this benefits everyone who's dealt with mental health issues in the past! +2014-08-27 15:26:05,26,Male,United States,OR,No,Yes,Yes,Often,6-25,No,Yes,Yes,Yes,No,No,Don't know,Somewhat difficult,Maybe,No,Some of them,Yes,No,No,No,No, +2014-08-27 15:26:37,28,Male,United States,NJ,No,Yes,Yes,Sometimes,26-100,No,Yes,Yes,Yes,No,No,Don't know,Don't know,Maybe,No,Some of them,No,No,Maybe,No,No, +2014-08-27 15:26:40,23,male,United States,CA,No,No,No,,More than 1000,No,Yes,Don't know,No,No,Don't know,Don't know,Don't know,No,No,Some of them,Yes,No,Maybe,No,No, +2014-08-27 15:26:57,35,M,United States,CA,No,Yes,Yes,Sometimes,100-500,No,Yes,Yes,Yes,No,No,Don't know,Very difficult,Maybe,Maybe,Some of them,Some of them,No,Maybe,No,Yes,I'm troubled by the way that our hiring process tends to filter out non-neurotypicals of all stripes. Competent people who act a little funny can be hard to hire. +2014-08-27 15:27:31,26,Male,United States,CA,No,Yes,No,,6-25,No,Yes,Yes,Yes,No,Yes,Yes,Very easy,No,No,Some of them,Yes,Maybe,Maybe,No,No, +2014-08-27 15:27:38,33,Male,United States,NH,No,Yes,Yes,Never,26-100,Yes,Yes,Yes,Yes,Yes,Yes,Don't know,Don't know,Yes,Maybe,Yes,Some of them,No,No,Yes,No, +2014-08-27 15:27:39,33,Male,United States,CA,No,No,No,,More than 1000,Yes,Yes,Don't know,No,Don't know,Don't know,Don't know,Don't know,Yes,No,Some of them,No,No,Maybe,Yes,No, +2014-08-27 15:29:03,33,male,United States,OH,No,Yes,Yes,Often,More than 1000,Yes,Yes,Yes,Yes,No,No,Don't know,Somewhat easy,Yes,No,No,No,No,No,No,No, +2014-08-27 15:29:07,31,Female,United States,OH,No,Yes,Yes,Rarely,More than 1000,No,No,Don't know,Not sure,No,Don't know,Don't know,Very difficult,Yes,Maybe,No,No,No,Maybe,No,No, +2014-08-27 15:29:23,21,male,United States,MA,No,Yes,No,Never,More than 1000,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,No,No,Some of them,Some of them,No,Maybe,Don't know,Yes, +2014-08-27 15:30:51,31,Enby,United Kingdom,,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Don't know,No,No,No,Don't know,Don't know,Yes,Maybe,No,No,No,Yes,Yes,No, +2014-08-27 15:31:10,26,F,United States,OK,No,No,Yes,Sometimes,100-500,Yes,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Somewhat difficult,No,No,Some of them,Some of them,No,No,Yes,No, +2014-08-27 15:31:18,30,Male,United States,CA,No,Yes,No,Often,6-25,No,Yes,Don't know,No,No,Don't know,Don't know,Somewhat easy,Maybe,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 15:31:40,55,M,United States,ID,No,Yes,Yes,Sometimes,1-5,Yes,Yes,No,Yes,No,Don't know,Don't know,Don't know,Yes,Maybe,No,No,No,No,No,Yes, +2014-08-27 15:34:23,32,Male,United Kingdom,,No,Yes,Yes,Sometimes,6-25,No,Yes,No,No,No,Don't know,Don't know,Somewhat easy,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 15:34:31,28,Female,United States,NY,No,No,Yes,Rarely,More than 1000,No,No,Yes,Yes,No,Don't know,Don't know,Don't know,Maybe,No,No,No,No,No,Don't know,No, +2014-08-27 15:34:32,21,M,United States,CA,No,No,No,Sometimes,6-25,No,No,Don't know,Not sure,No,Yes,Yes,Don't know,No,No,Some of them,Some of them,Maybe,Maybe,Yes,No, +2014-08-27 15:35:21,24,Male,United States,TX,No,Yes,Yes,Sometimes,100-500,No,Yes,No,Yes,No,No,Don't know,Somewhat difficult,Yes,No,Some of them,Some of them,No,Maybe,No,Yes, +2014-08-27 15:35:37,26,Female,United States,MD,No,No,No,,More than 1000,No,No,Yes,Not sure,Yes,Don't know,Don't know,Don't know,Maybe,No,Some of them,No,No,No,Don't know,No, +2014-08-27 15:35:50,23,Male,United States,IN,No,No,No,,More than 1000,No,No,Yes,No,No,No,Don't know,Don't know,No,No,Yes,No,No,Yes,Don't know,No, +2014-08-27 15:36:13,24,Female,United States,OR,No,No,No,,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Somewhat easy,No,No,Some of them,Some of them,Yes,Yes,Yes,No, +2014-08-27 15:36:41,28,Male,Canada,,Yes,No,No,Never,100-500,Yes,Yes,Don't know,No,No,No,Don't know,Somewhat easy,Maybe,No,Some of them,Yes,No,No,Yes,No, +2014-08-27 15:38:07,24,F,United States,NY,No,Yes,Yes,Rarely,6-25,No,Yes,No,No,No,No,Don't know,Very easy,Yes,No,No,Some of them,No,Yes,Yes,No, +2014-08-27 15:38:27,33,male,United States,MS,Yes,No,Yes,Often,1-5,Yes,Yes,No,No,No,No,Yes,Somewhat easy,Yes,Maybe,Some of them,Some of them,Yes,Yes,Don't know,No, +2014-08-27 15:38:31,34,male,United States,NJ,No,No,No,Sometimes,26-100,No,Yes,Don't know,No,No,No,Don't know,Don't know,Maybe,No,Yes,Yes,No,Maybe,Don't know,No, +2014-08-27 15:38:32,27,female,United States,CA,No,No,Yes,Sometimes,26-100,No,Yes,Don't know,Not sure,No,No,Don't know,Somewhat difficult,Maybe,Maybe,Some of them,Some of them,No,No,Don't know,No,I talked to a psychiatrist once about taking medical leave for mental health issues with his referral. He was willing to help but warned me that I may not want to as he's seen that sort of thing follow people throughout their tech careers (word gets out even if it's confidential at work). I've been terrified of bringing mental health up anywhere that coworkers or potential employers could see ever since. +2014-08-27 15:38:37,28,Male,United States,TN,No,No,No,Never,6-25,No,Yes,Don't know,No,No,Don't know,Don't know,Don't know,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 15:39:31,26,Male,United States,WA,No,No,No,,More than 1000,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,No,No,Some of them,Yes,No,No,Don't know,Yes, +2014-08-27 15:43:17,23,female,United States,MA,No,No,Yes,Sometimes,26-100,No,Yes,Yes,Yes,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,No,No,Maybe,Don't know,No, +2014-08-27 15:43:27,29,Male,United States,PA,No,Yes,Yes,Rarely,1-5,Yes,Yes,Yes,Yes,Yes,Yes,Yes,Somewhat easy,No,No,Yes,Yes,Maybe,Maybe,Yes,No, +2014-08-27 15:43:30,26,Male,United Kingdom,,No,Yes,No,Sometimes,6-25,No,Yes,No,No,No,No,Don't know,Don't know,Maybe,Maybe,No,No,No,Maybe,No,No, +2014-08-27 15:43:45,36,Male,United States,KY,No,No,No,Rarely,More than 1000,Yes,Yes,Yes,No,Yes,Don't know,Don't know,Somewhat easy,Maybe,No,No,No,No,No,Don't know,No, +2014-08-27 15:44:16,41,m,United States,PA,No,No,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Don't know,Maybe,No,Some of them,Yes,Maybe,Yes,Yes,Yes, +2014-08-27 15:44:20,33,female,United States,MA,No,No,No,,100-500,Yes,Yes,Yes,No,Don't know,No,Don't know,Don't know,No,No,Some of them,Yes,No,No,Yes,No, +2014-08-27 15:46:12,23,M,Canada,,No,Yes,Yes,Sometimes,6-25,No,Yes,Yes,Yes,No,No,Yes,Very easy,No,No,Yes,Yes,No,No,Yes,No, +2014-08-27 15:46:39,39,Male,United States,CA,No,Yes,No,Often,More than 1000,No,Yes,Yes,No,No,Don't know,Don't know,Don't know,Yes,No,Some of them,Some of them,No,Maybe,No,Yes, +2014-08-27 15:47:26,34,M,United States,VT,No,Yes,No,,More than 1000,No,Yes,Yes,Not sure,Don't know,Don't know,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,Maybe,Don't know,Yes, +2014-08-27 15:47:33,26,F,United States,CA,No,No,Yes,Sometimes,100-500,No,Yes,Yes,Yes,No,No,Don't know,Somewhat difficult,Yes,Maybe,Some of them,Some of them,No,No,No,Yes, +2014-08-27 15:50:26,24,Male,United States,AZ,No,No,Yes,Rarely,26-100,No,Yes,Yes,Yes,Yes,No,Don't know,Don't know,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 15:51:36,37,Male,Canada,,No,Yes,Yes,Rarely,More than 1000,No,No,Yes,Yes,Yes,Yes,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 15:53:39,43,Male,United States,MA,Yes,Yes,Yes,Often,6-25,Yes,Yes,Yes,Yes,No,No,Yes,Very easy,No,No,Yes,Yes,Maybe,Maybe,Yes,No,So much depends upon the organization. +2014-08-27 15:53:59,40,Genderqueer,United States,VA,No,Yes,No,Never,More than 1000,No,Yes,Yes,Yes,Yes,Don't know,Yes,Don't know,Yes,Maybe,No,Some of them,No,Maybe,Yes,No, +2014-08-27 15:54:45,30,male,United States,WA,No,Yes,Yes,Often,More than 1000,No,Yes,Yes,Yes,Yes,No,Don't know,Very difficult,Yes,No,Some of them,No,No,No,No,Yes, +2014-08-27 15:55:07,34,M,United States,CA,No,No,Yes,Sometimes,6-25,No,Yes,Don't know,Not sure,No,No,Don't know,Don't know,Yes,Yes,Some of them,No,No,No,Don't know,No,Now at starutp. Previously worked at big tech company which was actually quite good at supporting mental health issues. Still wouldn't share with bosses/other employees though as there remains a strong negative stigma. +2014-08-27 15:55:07,27,Male,United States,OR,No,Yes,Yes,Sometimes,100-500,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Don't know,Yes,No,No,No,No,Yes,Don't know,No, +2014-08-27 15:55:08,36,Male,United States,MI,No,No,No,Sometimes,More than 1000,No,Yes,Don't know,No,No,No,Yes,Somewhat easy,No,No,Yes,Yes,Maybe,Yes,Don't know,No, +2014-08-27 15:59:41,32,Male,United Kingdom,,No,No,No,Never,6-25,No,Yes,No,No,No,No,Don't know,Don't know,Maybe,No,Some of them,No,No,Yes,Yes,No, +2014-08-27 15:59:47,37,M,United States,OR,No,No,No,,500-1000,No,Yes,Yes,No,No,No,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 16:00:16,29,Male,United Kingdom,,No,No,No,,26-100,No,Yes,Don't know,No,Don't know,Don't know,Don't know,Don't know,No,No,Some of them,Yes,Maybe,Maybe,Yes,No, +2014-08-27 16:01:39,33,Female ,United States,CA,No,No,No,Never,500-1000,No,Yes,Yes,Not sure,Yes,Yes,Don't know,Very easy,Maybe,No,Some of them,Yes,No,No,Yes,No,I currently have the best managers I've ever worked with. I don't have any issues but one of my coworkers recently did and it was handled extremely well. +2014-08-27 16:01:52,28,Make,United States,UT,No,No,No,Sometimes,6-25,Yes,Yes,No,Yes,No,No,Don't know,Somewhat easy,Yes,Maybe,Some of them,No,No,No,Don't know,No, +2014-08-27 16:02:16,26,Female,United States,CA,No,Yes,No,Never,26-100,No,Yes,Don't know,Not sure,No,No,Don't know,Somewhat difficult,Maybe,Maybe,Some of them,No,No,Maybe,No,No, +2014-08-27 16:03:20,27,M,United States,TX,No,Yes,Yes,Sometimes,6-25,Yes,Yes,Don't know,No,Yes,Don't know,Don't know,Somewhat easy,Yes,No,Some of them,Yes,No,Maybe,Yes,No, +2014-08-27 16:04:01,38,Male,United Kingdom,,Yes,No,Yes,Sometimes,26-100,Yes,Yes,No,No,No,No,Yes,Somewhat easy,Maybe,Maybe,Some of them,Yes,No,Maybe,Yes,No, +2014-08-27 16:06:46,57,M,United States,CA,No,Yes,Yes,Rarely,More than 1000,No,Yes,Yes,Yes,No,No,Don't know,Don't know,Maybe,No,Some of them,Yes,No,Maybe,No,No, +2014-08-27 16:07:32,28,Male,United Kingdom,,No,No,Yes,Sometimes,More than 1000,No,Yes,No,No,No,No,No,Very difficult,Yes,Maybe,No,Some of them,No,Maybe,No,No, +2014-08-27 16:13:31,31,Male,United States,OR,No,No,Yes,Sometimes,100-500,Yes,Yes,Yes,Yes,Yes,Yes,Yes,Very easy,No,No,Some of them,Yes,No,No,Yes,No, +2014-08-27 16:13:40,58,Male,United States,CA,No,No,Yes,Rarely,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Somewhat easy,Maybe,No,Some of them,Yes,No,Yes,Yes,No, +2014-08-27 16:13:42,29,Male,United States,OH,No,No,No,Sometimes,6-25,No,Yes,Don't know,No,No,No,Don't know,Very difficult,Yes,No,No,No,No,Maybe,No,No, +2014-08-27 16:14:04,39,Female,United Kingdom,,No,No,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,No,Yes,Don't know,Don't know,Yes,No,Some of them,Some of them,No,Maybe,No,Yes, +2014-08-27 16:14:43,34,Male,United States,OH,No,No,No,Sometimes,6-25,Yes,Yes,Don't know,No,No,No,Don't know,Very difficult,Maybe,No,Some of them,Yes,No,Maybe,Don't know,No, +2014-08-27 16:15:26,57,Male,United States,CA,No,No,Yes,Sometimes,More than 1000,No,Yes,Yes,Not sure,Yes,Yes,Don't know,Don't know,Maybe,Maybe,No,No,No,Maybe,Don't know,No, +2014-08-27 16:17:05,30,female,United States,NY,No,No,No,,100-500,No,Yes,Don't know,Not sure,No,No,Don't know,Don't know,Maybe,No,Some of them,Yes,No,Maybe,Don't know,No, +2014-08-27 16:17:41,23,Male,United States,VA,No,No,No,Never,26-100,No,No,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,No,No,Yes,Yes,Maybe,Yes,Yes,No, +2014-08-27 16:18:44,43,M,United States,CA,No,No,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Somewhat easy,Yes,Maybe,No,No,No,Yes,Don't know,No, +2014-08-27 16:19:05,18,Female,United Kingdom,,No,Yes,Yes,Sometimes,1-5,Yes,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,Maybe,Maybe,Don't know,No,I don't have a job :D +2014-08-27 16:19:25,29,male,United States,IL,No,No,Yes,Rarely,6-25,No,Yes,Yes,Yes,No,No,Don't know,Don't know,Maybe,No,Some of them,No,No,Maybe,Don't know,No, +2014-08-27 16:20:36,48,M,United States,TX,No,No,No,Never,6-25,No,Yes,Don't know,No,No,Don't know,Don't know,Don't know,Maybe,No,No,No,No,Maybe,Don't know,No, +2014-08-27 16:21:11,28,Female,United States,NY,No,Yes,Yes,Sometimes,26-100,No,Yes,Don't know,Not sure,No,No,Don't know,Don't know,Yes,Maybe,Some of them,No,No,Maybe,Don't know,No, +2014-08-27 16:21:24,30,Male,United States,CA,Yes,Yes,Yes,Often,1-5,Yes,Yes,No,Yes,No,No,Yes,Very easy,No,No,Yes,Yes,No,No,Yes,No, +2014-08-27 16:22:10,31,Male,United States,CA,No,No,No,,More than 1000,No,Yes,Yes,Not sure,Don't know,Don't know,Yes,Don't know,No,No,No,Some of them,No,No,Yes,No, +2014-08-27 16:22:17,30,M,United States,PA,No,No,No,Rarely,100-500,No,No,Don't know,Not sure,No,No,Don't know,Don't know,No,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 16:25:26,24,Female,United States,CA,Yes,Yes,Yes,Sometimes,1-5,Yes,Yes,No,No,Don't know,Don't know,Don't know,Don't know,No,No,Some of them,Some of them,No,No,Don't know,Yes, +2014-08-27 16:26:03,25,male,United States,WA,No,No,No,,26-100,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,Maybe,No,Some of them,No,No,No,Don't know,No, +2014-08-27 16:27:04,23,Female,United States,NY,No,Yes,Yes,Often,More than 1000,No,Yes,Yes,Not sure,Don't know,No,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,No,Yes,Yes, +2014-08-27 16:27:47,36,m,United States,TX,No,No,Yes,Sometimes,More than 1000,No,No,Yes,Not sure,No,No,Don't know,Somewhat difficult,Yes,Maybe,Some of them,No,No,No,No,Yes,Stigma is the worst. People first language is a small step but we can't get that right. +2014-08-27 16:28:10,25,female,United States,CA,Yes,Yes,Yes,Often,1-5,Yes,Yes,Don't know,Not sure,No,No,Yes,Somewhat difficult,Yes,No,Some of them,No,No,Maybe,No,Yes, +2014-08-27 16:28:20,54,Male,United Kingdom,,No,No,Yes,Sometimes,More than 1000,Yes,No,No,Yes,Yes,Yes,Yes,Very easy,No,No,Yes,Yes,Maybe,Maybe,No,No, +2014-08-27 16:29:23,38,female,United States,AZ,No,No,Yes,,26-100,No,Yes,Yes,Yes,No,No,Yes,Don't know,Maybe,Maybe,No,No,No,No,No,No, +2014-08-27 16:32:31,32,male,United Kingdom,,No,No,No,,26-100,No,Yes,No,Not sure,No,Don't know,Don't know,Don't know,No,No,No,Some of them,No,Maybe,Don't know,No, +2014-08-27 16:35:02,35,Female,United States,OH,No,No,Yes,Sometimes,100-500,No,Yes,No,Yes,No,No,Don't know,Don't know,Yes,Maybe,No,No,No,Maybe,No,No, +2014-08-27 16:36:57,46,male,United States,CA,No,No,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Don't know,Don't know,Maybe,No,Some of them,No,No,No,Yes,No, +2014-08-27 16:39:00,42,male,United States,KS,No,No,No,Never,100-500,No,No,Yes,No,Yes,No,Don't know,Very difficult,Maybe,No,Yes,Yes,Maybe,Yes,No,No, +2014-08-27 16:39:01,32,male,United Kingdom,,No,Yes,Yes,Sometimes,6-25,Yes,Yes,Yes,No,No,No,Don't know,Don't know,No,No,Yes,Yes,Maybe,Maybe,Yes,No, +2014-08-27 16:40:35,47,M,United States,CA,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Don't know,Very easy,No,No,Some of them,Yes,No,Yes,Yes,No, +2014-08-27 16:42:00,22,Male,United States,CA,No,No,No,,More than 1000,No,Yes,Yes,Not sure,Yes,Don't know,Yes,Don't know,No,No,Some of them,Yes,No,Maybe,Yes,No, +2014-08-27 16:42:55,33,Female,United States,NY,No,No,Yes,Sometimes,500-1000,Yes,Yes,Yes,Yes,Yes,Yes,Don't know,Very easy,No,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 16:47:48,25,f,United States,WA,No,No,No,Sometimes,6-25,No,Yes,No,No,No,No,No,Somewhat easy,Maybe,No,Some of them,No,No,No,Yes,No, +2014-08-27 16:53:54,29,M,United States,CA,No,No,No,,More than 1000,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Don't know,Maybe,No,No,No,No,Maybe,Don't know,No, +2014-08-27 16:55:04,39,Male,United States,WA,No,No,No,Never,26-100,No,Yes,Yes,Yes,Yes,Yes,Yes,Very easy,No,No,Yes,Yes,No,No,Yes,No,I work for an extremely supportive company and we are amazingly open about mental health issues. Employees often share their struggles with the whole team and receive a high level of support in return. +2014-08-27 17:00:15,38,male,United States,VA,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Yes,Not sure,Yes,Yes,Yes,Don't know,Yes,No,No,No,No,No,No,No, +2014-08-27 17:03:02,43,Male,United States,NC,No,No,No,,6-25,Yes,Yes,Don't know,No,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,No,No,No,Don't know,No, +2014-08-27 17:04:29,46,Male,United States,OH,No,No,Yes,Rarely,500-1000,Yes,Yes,Yes,Not sure,Yes,Yes,Yes,Don't know,No,No,Some of them,Yes,No,Maybe,Yes,No, +2014-08-27 17:08:18,38,Female,United States,PA,No,Yes,Yes,Sometimes,More than 1000,No,No,Yes,Yes,Yes,Yes,Yes,Very easy,Maybe,No,Yes,Yes,No,No,No,Yes, +2014-08-27 17:10:56,34,Male,United Kingdom,,No,Yes,Yes,Often,26-100,No,Yes,No,Yes,No,No,Yes,Very easy,Maybe,Maybe,Yes,Yes,No,No,No,No, +2014-08-27 17:12:01,62,M,United States,CA,No,No,No,Never,More than 1000,No,Yes,Yes,Yes,Don't know,Yes,Don't know,Don't know,Maybe,No,Some of them,Yes,Maybe,Maybe,Yes,No, +2014-08-27 17:14:36,23,F,United States,TX,No,No,No,,More than 1000,No,No,Don't know,Not sure,Don't know,Don't know,Yes,Don't know,Maybe,Maybe,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 17:15:25,35,Male,United States,AZ,No,No,No,,More than 1000,No,No,No,No,No,No,Don't know,Don't know,Maybe,Maybe,No,No,No,No,No,No, +2014-08-27 17:22:29,36,M,United States,IL,Yes,Yes,Yes,Sometimes,1-5,Yes,Yes,Don't know,Yes,Don't know,No,Yes,Somewhat difficult,Maybe,No,Some of them,Yes,No,Yes,Yes,No, +2014-08-27 17:32:04,41,Female,United States,,No,Yes,Yes,Rarely,500-1000,Yes,Yes,Yes,Yes,Yes,Yes,Yes,Very easy,Maybe,Maybe,Some of them,Some of them,No,No,Yes,No, +2014-08-27 17:33:52,29,M,United States,NC,No,No,Yes,Sometimes,6-25,No,Yes,Yes,Yes,No,Yes,Yes,Very easy,No,No,No,Some of them,No,No,Yes,No, +2014-08-27 17:37:41,31,Female,Canada,,Yes,Yes,Yes,Sometimes,100-500,Yes,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,Maybe,Maybe,Some of them,Yes,No,No,Yes,No, +2014-08-27 17:39:58,27,Male,United Kingdom,,No,No,No,,6-25,No,Yes,No,No,No,No,Don't know,Don't know,No,No,Some of them,Yes,No,Yes,Don't know,No, +2014-08-27 17:47:45,21,Male,Canada,,No,No,No,Never,26-100,No,Yes,Don't know,Not sure,Don't know,No,Don't know,Don't know,Yes,Maybe,No,No,No,Maybe,Don't know,No, +2014-08-27 17:49:21,39,M,United States,WI,No,Yes,Yes,Often,26-100,Yes,Yes,Yes,Yes,Yes,Yes,Don't know,Somewhat easy,Yes,No,Some of them,Yes,No,No,No,No, +2014-08-27 17:49:30,26,M,United States,CA,No,Yes,Yes,Never,More than 1000,No,Yes,Don't know,No,No,Don't know,Don't know,Don't know,Maybe,No,No,No,No,No,No,No, +2014-08-27 17:52:31,27,Male,United Kingdom,,No,No,No,Never,6-25,No,Yes,Don't know,No,No,No,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 17:56:50,22,Female,United States,CA,No,Yes,Yes,Sometimes,500-1000,No,Yes,Yes,Yes,No,Don't know,Don't know,Don't know,No,No,Some of them,Some of them,No,No,No,Yes, +2014-08-27 18:00:39,26,F,United States,MN,No,Yes,Yes,Often,100-500,No,No,Don't know,No,No,No,Don't know,Somewhat difficult,Maybe,No,No,No,No,Maybe,No,No, +2014-08-27 18:02:32,31,Female,United States,PA,No,Yes,Yes,Rarely,100-500,No,Yes,Yes,Yes,No,No,Yes,Somewhat easy,No,No,Yes,Yes,No,No,Yes,No, +2014-08-27 18:02:42,32,male,United Kingdom,,No,No,No,Never,6-25,No,Yes,Don't know,No,No,No,Don't know,Don't know,No,No,Yes,Yes,Yes,Yes,Yes,No, +2014-08-27 18:12:55,28,female,United States,CA,No,Yes,Yes,Often,100-500,Yes,Yes,Yes,No,No,Don't know,Don't know,Don't know,Yes,Yes,Some of them,Some of them,No,No,No,Yes, +2014-08-27 18:13:38,28,Androgyne,United Kingdom,,No,Yes,Yes,Rarely,100-500,No,Yes,No,Not sure,No,No,Yes,Somewhat difficult,Yes,Yes,Some of them,Some of them,Yes,No,No,Yes,I bring up my depression in interviews solely because I have a large gap on my CV due to mental health issues which could be mistaken for a gap taken to say have children which I feel would harm my chances much more. I have other MH issues I would never bring up with employers or peers. +2014-08-27 18:14:59,23,female,United Kingdom,,No,No,No,,6-25,No,Yes,Don't know,Not sure,No,No,Don't know,Very easy,Maybe,No,No,Some of them,No,Yes,Yes,No, +2014-08-27 18:16:52,30,Male,United Kingdom,,No,No,No,Never,26-100,Yes,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Very easy,No,No,Yes,Yes,Maybe,Maybe,Yes,No, +2014-08-27 18:18:18,36,Male,United States,CA,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Yes,No,No,Yes,Don't know,Somewhat difficult,Yes,No,Some of them,Yes,No,Yes,No,No, +2014-08-27 18:22:05,21,M,United States,CA,No,Yes,No,,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Don't know,No,No,Some of them,Yes,No,Maybe,Yes,No, +2014-08-27 18:39:43,25,Woman,United States,CA,No,Yes,No,,500-1000,No,No,Don't know,Not sure,No,No,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,Maybe,Don't know,No,I'm not aware of anyone with mental health issues at work it's definitely not something that's discussed publicly. There's also a lot of other personal info I don't know about my coworkers so it may just be that we tend not to talk about personal issues. +2014-08-27 18:43:06,29,female,Canada,,No,No,Yes,Sometimes,1-5,No,Yes,No,No,No,No,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,No,Yes,No,The family history question needs a don't know option. +2014-08-27 18:56:46,21,Agender,United Kingdom,,No,No,Yes,Sometimes,26-100,No,Yes,No,Yes,Yes,No,Yes,Somewhat easy,Maybe,No,Some of them,Some of them,No,No,Yes,No, +2014-08-27 19:05:52,32,Female,Canada,,No,No,Yes,Often,More than 1000,No,No,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 19:13:21,33,M,United States,NY,No,No,No,,26-100,No,Yes,Don't know,No,Don't know,Don't know,Don't know,Don't know,Yes,No,Some of them,No,No,Maybe,Don't know,No,I'm afraid I haven't seen mental health issues arise at work yet. They are very accommodating with maternity leave but I don't know how that translates to anything else. +2014-08-27 19:16:15,24,M,United States,CA,No,No,No,,More than 1000,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,No,No,Yes,No, +2014-08-27 19:17:07,65,Male,United States,FL,Yes,No,No,,6-25,Yes,No,No,No,No,No,Don't know,Very easy,Maybe,No,Some of them,No,No,No,Yes,No, +2014-08-27 19:25:42,27,Male,United States,OR,No,Yes,Yes,Sometimes,100-500,Yes,Yes,Don't know,No,No,Don't know,Don't know,Don't know,No,No,Some of them,No,No,No,Yes,No, +2014-08-27 19:28:35,36,Male,United States,CO,No,No,Yes,Rarely,26-100,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Don't know,No,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-27 19:34:26,40,Male,Canada,,No,No,No,Never,26-100,No,Yes,No,No,No,No,Don't know,Somewhat difficult,No,No,Some of them,Some of them,No,No,No,No, +2014-08-27 19:34:56,28,male,United States,GA,No,No,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,No,No,Yes,Somewhat difficult,Maybe,No,Some of them,No,No,Maybe,No,No, +2014-08-27 19:38:44,39,Male,United States,OR,No,No,Yes,Sometimes,500-1000,No,Yes,Yes,Not sure,Yes,Don't know,Yes,Don't know,Yes,Maybe,Yes,Yes,No,Maybe,Don't know,No, +2014-08-27 19:41:28,32,Male,United States,CA,No,No,Yes,Sometimes,More than 1000,No,Yes,Yes,No,No,Yes,Don't know,Somewhat easy,No,No,Yes,Some of them,Maybe,Yes,Don't know,No, +2014-08-27 19:45:36,31,male,United States,CA,No,Yes,No,Sometimes,More than 1000,No,Yes,Yes,Not sure,Don't know,Don't know,Don't know,Somewhat easy,Maybe,No,No,Some of them,No,Yes,No,No,Mental health issue I have dealt with: acute depression +2014-08-27 19:59:12,38,Make,United States,PA,No,Yes,Yes,Sometimes,100-500,No,Yes,Don't know,No,No,No,Don't know,Don't know,Maybe,Maybe,Some of them,No,No,No,Don't know,No, +2014-08-27 20:13:06,23,Male,United States,CA,No,Yes,Yes,Rarely,1-5,No,Yes,No,Yes,No,No,Don't know,Don't know,Maybe,No,Some of them,Yes,No,No,Yes,No, +2014-08-27 20:17:52,42,Make,United States,CA,No,No,Yes,Often,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Somewhat easy,Maybe,Maybe,Yes,Yes,Maybe,Maybe,Don't know,No, +2014-08-27 20:33:33,27,Female,United States,NY,No,No,No,Sometimes,500-1000,No,Yes,Don't know,Not sure,Don't know,Yes,Don't know,Don't know,No,No,Some of them,Yes,No,No,Yes,No, +2014-08-27 20:48:54,26,Female,United States,MA,No,Yes,Yes,Sometimes,26-100,No,Yes,Yes,Yes,No,No,Yes,Somewhat difficult,No,No,Yes,Yes,No,No,No,Yes, +2014-08-27 20:52:20,50,Male,United States,,No,No,No,Never,26-100,Yes,Yes,No,Yes,No,No,Don't know,Don't know,No,No,No,No,No,Maybe,No,No, +2014-08-27 20:52:31,37,Male,United States,PA,No,Yes,No,Never,26-100,No,Yes,Don't know,No,No,Don't know,Don't know,Somewhat easy,No,No,Yes,Yes,No,No,Yes,No, +2014-08-27 20:53:22,23,Male,United States,RI,No,No,No,,26-100,No,Yes,Don't know,No,Don't know,No,Don't know,Don't know,No,No,Yes,Yes,No,Maybe,Don't know,No, +2014-08-27 20:55:48,33,M,United States,MI,No,Yes,No,Sometimes,6-25,Yes,Yes,Don't know,Not sure,No,No,Yes,Very easy,No,No,Some of them,Yes,No,No,Yes,No, +2014-08-27 21:05:41,29,male,Canada,,Yes,No,No,Never,26-100,Yes,Yes,Yes,Yes,No,No,Yes,Very difficult,Yes,No,Some of them,No,No,Yes,No,No, +2014-08-27 21:15:09,34,Male,United States,IL,No,Yes,Yes,Sometimes,26-100,Yes,No,Yes,No,No,No,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,Maybe,Don't know,No,Thanks for doing this. It will help end the stigma! +2014-08-27 21:17:31,41,male,United States,CA,No,Yes,Yes,Often,More than 1000,No,Yes,Yes,No,No,No,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,No,No,Don't know,Yes, +2014-08-27 21:21:31,50,Male,United States,OR,No,Yes,No,,100-500,Yes,Yes,Don't know,No,No,Don't know,Don't know,Don't know,No,No,Some of them,Yes,Maybe,Maybe,Don't know,No, +2014-08-27 21:35:24,29,Male,Canada,,No,No,Yes,Never,More than 1000,No,No,Yes,Not sure,Yes,Yes,Yes,Somewhat difficult,Maybe,No,Some of them,No,No,Maybe,Don't know,Yes,For clarity I work at a casino. +2014-08-27 21:39:23,35,Male,United States,IN,No,No,No,Never,6-25,No,Yes,No,Yes,No,No,Yes,Very easy,No,No,Some of them,Yes,Maybe,Maybe,Yes,No, +2014-08-27 21:54:29,40,Female,United States,MA,No,No,No,Never,26-100,No,No,Don't know,Not sure,No,No,Don't know,Somewhat easy,Maybe,Maybe,Yes,Yes,Maybe,Maybe,Don't know,No, +2014-08-27 21:55:28,29,f,United States,MI,No,No,No,Never,26-100,No,Yes,Yes,Yes,Yes,No,Yes,Don't know,Maybe,No,Some of them,Some of them,No,Maybe,Don't know,Yes, +2014-08-27 22:00:36,31,Male,United States,OH,No,Yes,Yes,Sometimes,6-25,No,Yes,No,No,No,No,Don't know,Somewhat easy,Maybe,No,Yes,Yes,No,Maybe,Don't know,No, +2014-08-27 22:04:43,43,Male,United States,OH,No,No,Yes,Sometimes,6-25,No,Yes,No,Yes,No,No,Don't know,Somewhat easy,No,No,Yes,Yes,No,Maybe,Don't know,No, +2014-08-27 22:04:47,34,Male,United States,NH,No,Yes,Yes,Sometimes,26-100,Yes,Yes,Yes,Yes,No,No,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,Yes,Don't know,Yes, +2014-08-27 22:06:14,29,Male,United States,OH,No,Yes,Yes,Sometimes,26-100,No,Yes,Don't know,No,No,No,No,Somewhat difficult,Yes,No,Some of them,Some of them,No,Maybe,Don't know,No,It has come to interfere with work as life progresses.Between burn out and enduring more of the work and balancing a family. Changes in my mental health have a larger pond to make ripples in. +2014-08-27 22:07:34,19,Male,Canada,,No,Yes,Yes,Sometimes,1-5,No,Yes,No,No,No,No,Don't know,Don't know,Maybe,Maybe,Some of them,No,No,Maybe,Don't know,No, +2014-08-27 22:11:16,41,m,United States,TN,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Yes,Not sure,Yes,Yes,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,No,No,No, +2014-08-27 22:12:55,29,Male,United States,OR,No,Yes,No,Never,100-500,No,Yes,Yes,Yes,Yes,Yes,Don't know,Don't know,No,No,Some of them,Yes,No,Maybe,Yes,No, +2014-08-27 22:13:55,23,Male,United States,PA,No,No,No,Rarely,100-500,No,Yes,Yes,Not sure,Don't know,Don't know,Don't know,Don't know,No,No,Some of them,Some of them,No,No,Yes,No, +2014-08-27 22:14:23,24,Female,United States,,No,Yes,Yes,Sometimes,100-500,No,Yes,Yes,Not sure,No,No,Don't know,Somewhat difficult,Yes,Maybe,No,No,No,No,No,Yes, +2014-08-27 22:14:46,31,M,United States,NY,No,No,No,,26-100,Yes,Yes,Don't know,No,No,Don't know,Don't know,Don't know,Yes,No,No,No,No,Maybe,Don't know,No, +2014-08-27 22:21:48,43,Male,United States,WA,No,No,No,,500-1000,Yes,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,No,No,Yes,Yes,No,No,Yes,No, +2014-08-27 22:26:03,31,Male,United States,NY,No,Yes,Yes,Rarely,100-500,No,Yes,No,No,No,Don't know,Don't know,Somewhat difficult,Yes,Yes,Some of them,No,No,No,No,Yes, +2014-08-27 22:32:36,29,Male,United States,CA,No,Yes,No,Often,100-500,No,Yes,Yes,Yes,Yes,Yes,Don't know,Don't know,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-27 22:35:40,35,Male,United States,TN,Yes,Yes,No,,6-25,Yes,Yes,No,No,Yes,Yes,Don't know,Very easy,No,No,Yes,Yes,No,Maybe,Yes,No,The supposed divide between mental and physical health needs to done away with and probably will be as our knowledge of the brain increases. That said we are often employed for our ability to provide value. If any issue prevents is from providing value that creates a very real challenge for the employer who is responsible to shareholders and other team members who are providing value. There are no easy answers here. +2014-08-27 22:36:34,33,Male,United States,WI,No,Yes,Yes,Sometimes,100-500,No,No,Yes,Not sure,No,No,Yes,Somewhat difficult,Yes,Yes,No,No,No,No,No,No, +2014-08-27 22:55:13,30,cis-female/femme,United States,WI,Yes,Yes,Yes,Often,1-5,Yes,No,No,Yes,No,Yes,Yes,Somewhat difficult,No,No,Yes,Yes,No,No,Yes,No,Because I'm self-employed and the only person in my organization I would have liked a not applicable option. I don't want my answers to be misleading. +2014-08-27 22:59:23,27,male,United States,PA,No,No,No,,More than 1000,No,Yes,Yes,Not sure,Don't know,Don't know,Yes,Don't know,Maybe,Maybe,No,No,No,Maybe,No,No, +2014-08-27 23:09:46,32,Male,United States,MI,No,No,No,Sometimes,100-500,No,Yes,No,Yes,No,No,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,No,No,No,No, +2014-08-27 23:10:16,50,Male,United States,WY,No,No,No,Sometimes,1-5,Yes,Yes,Don't know,No,No,Don't know,Don't know,Don't know,Yes,Maybe,Some of them,Some of them,No,Maybe,Don't know,No,I work for a very small firm that doesn't really have a dedicated H/R person. Also for the question:If you have a mental health condition do you feel that it interferes with your work?...I don't have a diagnosed mental health condition but I suspect I might have some slight depression issues. Definitely have Imposter Syndrome. +2014-08-27 23:10:23,24,male,United States,KY,No,No,No,Never,26-100,No,No,Don't know,Not sure,No,No,Don't know,Don't know,Maybe,Yes,Some of them,No,No,Maybe,No,No, +2014-08-27 23:14:58,27,Male,United States,NY,No,No,No,,26-100,No,Yes,Don't know,No,No,No,Don't know,Don't know,No,No,Yes,Yes,No,Maybe,Yes,No, +2014-08-27 23:54:08,32,Male,United States,TX,No,No,Yes,Sometimes,6-25,No,Yes,No,Yes,No,No,Yes,Somewhat easy,No,No,Some of them,Yes,Maybe,Maybe,Yes,No,I went through a divorce and was pretty depressed I went to therapy and my boss (one of the owners) was extremely supportive. I'm not sure I would have got through that rough time with out my co-workers and boss. +2014-08-27 23:56:33,42,Male,United States,WI,Yes,No,No,Rarely,6-25,Yes,No,No,Yes,No,No,Don't know,Very easy,No,No,Some of them,Yes,Maybe,Maybe,Yes,No, +2014-08-27 23:57:16,37,Male,United States,WA,No,No,No,Often,More than 1000,No,No,Don't know,No,No,No,Don't know,Don't know,Maybe,No,Some of them,No,No,No,No,No, +2014-08-28 00:02:36,29,Male,United States,WA,No,No,No,Rarely,More than 1000,No,Yes,Yes,No,No,No,Don't know,Very easy,Yes,Maybe,Some of them,No,No,No,Don't know,No, +2014-08-28 00:05:34,30,Male,United States,GA,Yes,No,Yes,Often,6-25,Yes,Yes,No,Not sure,No,Yes,Don't know,Somewhat difficult,No,No,Yes,Yes,No,Maybe,Yes,No, +2014-08-28 00:17:24,35,Male,United States,MI,No,No,No,Never,26-100,No,Yes,Yes,No,Yes,Don't know,Don't know,Don't know,No,No,Some of them,Some of them,Maybe,Maybe,Yes,No, +2014-08-28 00:43:40,35,Male,United States,MD,No,Yes,Yes,Rarely,100-500,Yes,No,Yes,Yes,No,No,Yes,Very difficult,Yes,No,Some of them,No,No,Maybe,No,No,I'm diagnosed with Bipolar Disorder. My benefits for mental health exist but are terrible. The deductible is $800. I see a therapist once or twice a month at the cost of $150. The insurance company only values it at $40. My psychiatrist is $180 for 15 minutes. The insurance company values it at $80. It is IMPOSSIBLE to hit my deductible. I don't even bother making the claims. +2014-08-28 01:04:45,22,Male,United Kingdom,,No,Yes,Yes,Sometimes,100-500,No,Yes,Yes,Yes,No,No,Yes,Very easy,No,No,Some of them,Yes,Maybe,Yes,Yes,No, +2014-08-28 01:30:12,31,Female,United States,WA,No,No,Yes,Often,26-100,Yes,Yes,Yes,Yes,No,No,Don't know,Very easy,Maybe,No,Some of them,Some of them,No,Yes,Don't know,No, +2014-08-28 01:38:53,23,female,United States,CA,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Somewhat easy,Yes,Maybe,No,No,No,No,Don't know,No, +2014-08-28 01:41:17,31,Female,United States,OR,No,Yes,Yes,Sometimes,100-500,No,Yes,Don't know,No,No,No,Don't know,Don't know,No,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-28 01:56:43,28,Female,United States,CA,No,Yes,Yes,Rarely,500-1000,No,Yes,Yes,Yes,Yes,Yes,Don't know,Somewhat difficult,Maybe,No,No,Some of them,No,No,No,No, +2014-08-28 02:15:08,37,Guy (-ish) ^_^,Canada,,No,Yes,Yes,Sometimes,100-500,No,No,Yes,Yes,No,No,Don't know,Somewhat difficult,Yes,Maybe,Some of them,Some of them,No,Maybe,No,No, +2014-08-28 02:17:42,34,male,United States,CA,Yes,Yes,Yes,Sometimes,6-25,No,Yes,No,Yes,No,No,Yes,Somewhat easy,No,No,Some of them,Some of them,No,No,No,No,thanks for what you're doing. FYI these questions dont quite work for entrepreneurs where employer == cofounders / sr mgmt / me +2014-08-28 02:19:29,32,male leaning androgynous,Canada,,No,No,No,Sometimes,26-100,Yes,Yes,No,Yes,No,No,Yes,Very difficult,Yes,Maybe,Some of them,No,No,Maybe,No,Yes, +2014-08-28 02:30:00,28,Male,United States,MI,No,Yes,Yes,Sometimes,26-100,Yes,Yes,Yes,Not sure,No,Don't know,Don't know,Don't know,Yes,No,Some of them,Some of them,No,No,Don't know,Yes, +2014-08-28 02:32:11,24,Female,United Kingdom,,No,No,Yes,Sometimes,100-500,No,Yes,No,No,No,No,Don't know,Don't know,Maybe,No,No,Some of them,No,Maybe,Don't know,No, +2014-08-28 02:41:47,56,Male ,United States,MA,No,Yes,Yes,Rarely,6-25,No,Yes,Yes,Yes,No,No,Don't know,Don't know,Yes,Maybe,Some of them,Some of them,No,No,Don't know,No, +2014-08-28 02:49:34,34,female,United States,CA,No,No,Yes,Sometimes,100-500,Yes,Yes,Yes,Yes,No,Don't know,Don't know,Somewhat easy,Maybe,No,Some of them,Yes,No,No,Yes,No, +2014-08-28 03:06:14,30,Male,United Kingdom,,No,No,Yes,Often,26-100,No,Yes,No,No,No,No,Yes,Somewhat easy,No,No,Some of them,Yes,No,Maybe,Yes,No, +2014-08-28 03:13:10,35,Male,United States,,Yes,No,No,,1-5,Yes,Yes,Yes,Not sure,No,No,Yes,Very easy,No,No,Some of them,Yes,No,No,Yes,No, +2014-08-28 03:36:10,57,Male,United States,CA,No,No,No,Never,26-100,No,Yes,Yes,Yes,No,Yes,Yes,Somewhat difficult,Yes,Maybe,No,No,No,Maybe,Don't know,Yes, +2014-08-28 04:07:34,39,M,United States,FL,No,No,No,Rarely,More than 1000,Yes,No,Don't know,No,Yes,Yes,Don't know,Don't know,No,No,Some of them,Some of them,No,Maybe,Don't know,No,I mostly suffer from social anxiety which keeps me from attending conferences. In my small dev group a big problem is a supervisor who's a workaholic and will never say no when asked to do something so he's doing the job of at least two ppl (poorly) and working crazy hours setting the tone for the test of us that work/life balance isn't important. +2014-08-28 04:09:14,29,Male,United Kingdom,,No,Yes,Yes,Never,100-500,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,Maybe,Maybe,No,No,No,No,No,No, +2014-08-28 04:11:27,54,male,United Kingdom,,Yes,Yes,Yes,Sometimes,1-5,Yes,Yes,Don't know,Not sure,No,No,Don't know,Very easy,No,No,Some of them,Yes,Yes,Yes,Don't know,Yes, +2014-08-28 04:23:01,32,M,United States,WA,No,No,Yes,Never,500-1000,No,No,Yes,Not sure,Yes,Yes,Don't know,Very easy,Maybe,No,No,No,No,No,Yes,No, +2014-08-28 04:37:54,30,M,United Kingdom,,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,No,Don't know,Yes,Don't know,Maybe,No,Some of them,Yes,No,Yes,Yes,No, +2014-08-28 05:12:15,27,Male,United Kingdom,,No,No,No,Never,1-5,No,Yes,Don't know,No,No,Don't know,Don't know,Don't know,No,No,Some of them,Yes,Maybe,Maybe,Don't know,No, +2014-08-28 05:14:28,32,Male,United States,CA,No,No,No,Never,More than 1000,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,No,No,Don't know,No, +2014-08-28 07:03:03,23,Male,United States,NC,No,Yes,No,Sometimes,6-25,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Don't know,Maybe,No,No,No,No,Maybe,Don't know,No, +2014-08-28 07:12:03,26,Man,Canada,,No,No,No,,100-500,Yes,Yes,Yes,Not sure,Don't know,Yes,Don't know,Somewhat easy,No,No,Some of them,Some of them,No,No,Yes,No, +2014-08-28 08:06:43,35,Male,Canada,,No,Yes,No,Sometimes,26-100,No,Yes,Don't know,No,No,No,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,No,No,No,No, +2014-08-28 08:18:06,28,Male,United States,IL,No,No,Yes,Sometimes,26-100,Yes,No,Don't know,Not sure,No,Don't know,Don't know,Don't know,No,No,Some of them,Yes,No,Maybe,Don't know,No, +2014-08-28 08:39:49,29,Female,United States,OH,No,Yes,Yes,Rarely,6-25,No,Yes,Don't know,No,No,No,Don't know,Don't know,Yes,No,No,No,No,No,Don't know,No, +2014-08-28 08:43:23,45,Male,United States,VA,No,No,Yes,Often,1-5,Yes,Yes,Yes,Not sure,No,Yes,Don't know,Very easy,No,No,Yes,Yes,No,Maybe,Yes,No, +2014-08-28 08:43:58,38,Male,United States,MN,No,No,Yes,Sometimes,More than 1000,No,No,Yes,Yes,Yes,Yes,Don't know,Don't know,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-28 09:02:16,19,Trans woman,United States,MO,No,Yes,Yes,Often,26-100,No,No,Don't know,Not sure,No,No,Don't know,Somewhat difficult,Maybe,Maybe,No,No,No,Maybe,No,No, +2014-08-28 09:09:30,29,female,Canada,,No,No,Yes,Rarely,More than 1000,Yes,No,Yes,Yes,Yes,Don't know,Yes,Somewhat easy,No,No,No,Yes,No,Maybe,Don't know,No, +2014-08-28 09:16:21,21,Female,United Kingdom,,No,No,No,,6-25,No,Yes,No,No,No,No,Don't know,Don't know,Yes,Maybe,Some of them,No,No,No,Don't know,No, +2014-08-28 09:40:42,33,female,United States,NC,No,Yes,Yes,Rarely,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Somewhat easy,No,No,Some of them,Yes,No,No,Yes,No, +2014-08-28 09:53:42,49,Male,United States,NY,No,Yes,Yes,Sometimes,100-500,No,Yes,Yes,Not sure,Yes,Yes,Yes,Somewhat easy,Maybe,Maybe,Some of them,Yes,No,No,Yes,No, +2014-08-28 09:53:57,28,Male,United States,NM,No,No,No,,26-100,Yes,Yes,Don't know,No,No,No,Don't know,Don't know,Maybe,No,Some of them,No,No,No,Don't know,No, +2014-08-28 09:54:21,27,f,United Kingdom,,No,No,Yes,Sometimes,6-25,Yes,Yes,Don't know,Not sure,Yes,Don't know,Yes,Very easy,No,No,Yes,Yes,Maybe,Maybe,Yes,No, +2014-08-28 09:54:38,23,male,Canada,,No,No,Yes,Sometimes,6-25,No,Yes,Yes,No,No,No,Don't know,Somewhat easy,Maybe,Maybe,Some of them,Some of them,No,No,Don't know,No, +2014-08-28 09:55:14,28,Female,Canada,,No,No,No,,More than 1000,No,Yes,Yes,Not sure,Don't know,Don't know,Don't know,Somewhat easy,No,No,Some of them,Yes,No,No,Don't know,No,I am a contractor so my lack of knowledge of workplace wellness stems directly from my lack of access to that material since I am not covered by it. I am aware that mental health services are available and am aware of a colleague who has taken a leave of absence to deal with mental health issues but am otherwise uninformed. +2014-08-28 09:56:03,32,Male,United Kingdom,,No,No,No,,6-25,No,Yes,No,No,No,No,Don't know,Don't know,Yes,No,No,No,No,Yes,No,No, +2014-08-28 09:56:04,32,Male,United Kingdom,,No,No,Yes,Sometimes,26-100,No,No,Yes,Yes,No,No,Yes,Very easy,No,No,No,Yes,No,No,Yes,No, +2014-08-28 09:56:21,39,F,United States,TX,No,No,No,,More than 1000,Yes,No,No,Yes,No,No,Don't know,Very difficult,Yes,Maybe,No,No,No,Maybe,No,No, +2014-08-28 09:57:02,29,Male,United States,SC,No,No,No,,6-25,No,Yes,No,No,No,Don't know,Don't know,Somewhat difficult,Maybe,Maybe,Some of them,No,No,No,Don't know,No, +2014-08-28 09:57:10,30,M,United States,FL,No,No,No,,100-500,No,No,Yes,No,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,Yes,No,No,Don't know,No, +2014-08-28 09:57:25,33,M,United States,WA,Yes,Yes,Yes,Rarely,1-5,Yes,Yes,No,Yes,Yes,Yes,No,Very difficult,No,No,Yes,Yes,No,No,Yes,Yes, +2014-08-28 09:58:08,37,male,United States,CA,No,Yes,Yes,Sometimes,100-500,No,Yes,Yes,Yes,Don't know,Don't know,Yes,Don't know,Maybe,No,Yes,Yes,No,No,Don't know,No, +2014-08-28 09:59:39,23,Male,United States,OH,No,No,Yes,Often,26-100,No,No,Yes,Yes,Yes,No,Yes,Somewhat easy,No,No,Some of them,Yes,No,Maybe,Yes,No, +2014-08-28 09:59:39,43,M,United States,TN,No,Yes,Yes,Sometimes,26-100,No,No,Yes,Not sure,No,Yes,Don't know,Somewhat easy,Yes,No,No,No,No,No,No,No, +2014-08-28 10:00:48,32,Male,United Kingdom,,No,No,Yes,Rarely,100-500,No,Yes,Don't know,No,No,No,Don't know,Don't know,Maybe,No,Yes,Yes,No,Maybe,No,Yes, +2014-08-28 10:01:15,26,Male,United States,NY,No,No,No,Never,26-100,No,Yes,Don't know,Not sure,No,No,Don't know,Don't know,Yes,Yes,Some of them,No,No,No,No,No, +2014-08-28 10:01:31,32,Male,United States,NY,Yes,No,Yes,Sometimes,1-5,Yes,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Very easy,No,No,Yes,Yes,Yes,Yes,Don't know,No, +2014-08-28 10:02:09,37,F,United States,MO,No,No,No,,26-100,Yes,Yes,Don't know,Not sure,No,Don't know,Don't know,Don't know,Yes,No,Some of them,No,No,No,Don't know,No, +2014-08-28 10:02:23,29,Male,United States,NY,No,No,Yes,Often,26-100,No,Yes,Yes,Yes,No,No,Yes,Very easy,No,No,Yes,Yes,Maybe,Maybe,Yes,No, +2014-08-28 10:02:45,34,Male,United Kingdom,,No,No,No,,6-25,No,Yes,No,No,No,No,Don't know,Somewhat easy,Maybe,Maybe,Some of them,Yes,No,Maybe,Don't know,No, +2014-08-28 10:04:41,30,male,United States,TN,No,Yes,No,Never,100-500,No,Yes,Don't know,No,No,Don't know,Don't know,Very easy,No,No,Some of them,Yes,No,Maybe,Don't know,No, +2014-08-28 10:05:43,29,Male,United States,CO,No,No,No,Never,6-25,No,Yes,Yes,Yes,No,Yes,Yes,Don't know,Maybe,No,Some of them,Some of them,No,No,No,No, +2014-08-28 10:07:37,32,Male,United States,PA,Yes,Yes,Yes,Sometimes,1-5,Yes,Yes,Yes,Yes,Don't know,Don't know,Don't know,Very difficult,Yes,Maybe,Some of them,No,No,No,No,No, +2014-08-28 10:07:53,-1726,male,United Kingdom,,No,No,Yes,Sometimes,26-100,No,No,No,No,No,No,Don't know,Somewhat difficult,Yes,No,No,No,No,Maybe,Don't know,No, +2014-08-28 10:08:34,37,male,United States,NY,Yes,No,No,,6-25,Yes,Yes,Yes,Yes,Yes,No,Yes,Somewhat easy,No,No,Yes,Yes,Maybe,Maybe,Yes,No, +2014-08-28 10:11:52,27,Man,United States,MN,No,No,No,,26-100,No,Yes,Yes,Not sure,No,Don't know,Don't know,Don't know,No,No,Yes,Yes,No,No,Don't know,No, +2014-08-28 10:13:44,33,Male,United Kingdom,,No,No,No,,6-25,No,Yes,Don't know,No,No,No,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,Maybe,Don't know,No, +2014-08-28 10:15:52,30,male,Canada,,No,Yes,Yes,Sometimes,More than 1000,No,No,Don't know,No,No,No,No,Very difficult,Yes,No,Some of them,No,No,Yes,No,Yes, +2014-08-28 10:16:55,29,male,Canada,,No,No,No,,1-5,Yes,Yes,No,Yes,No,No,Don't know,Somewhat difficult,Maybe,Maybe,Yes,Yes,No,Maybe,Don't know,No, +2014-08-28 10:17:19,25,Male,United States,MO,No,Yes,Yes,Never,6-25,Yes,Yes,Don't know,No,Yes,Don't know,Don't know,Don't know,Yes,No,Some of them,Yes,No,No,No,No, +2014-08-28 10:18:34,33,Male,United States,WY,No,Yes,Yes,Sometimes,1-5,No,No,No,Yes,No,No,Don't know,Don't know,No,No,Some of them,Yes,Maybe,Maybe,Don't know,No, +2014-08-28 10:24:19,29,Male,United States,MN,No,No,No,,More than 1000,No,No,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,No,No,Yes,Yes,No,No,No,No, +2014-08-28 10:29:47,37,m,United Kingdom,,No,No,Yes,Often,6-25,No,Yes,No,No,No,No,Don't know,Don't know,Yes,No,Yes,Yes,Maybe,Yes,No,No, +2014-08-28 10:30:44,29,Male,United States,MD,No,No,No,,6-25,Yes,Yes,Don't know,Not sure,No,No,Don't know,Very easy,No,No,Yes,Yes,No,No,Don't know,No, +2014-08-28 10:34:01,31,Male,United States,KY,No,No,No,,26-100,No,No,Yes,Yes,Yes,Yes,Yes,Don't know,No,No,Yes,Yes,No,No,Don't know,No, +2014-08-28 10:35:55,5,Male,United States,OH,No,No,No,,100-500,No,Yes,Don't know,Not sure,No,No,Don't know,Somewhat easy,No,No,Yes,Yes,No,No,Yes,No,We had a developer suffer from depression and pretty hard burnout but he refused treatment even when the company said we'd foot the bill. Eventually he had to be asked to resign which was a shame. I don't know if we have any specific programs for mental health but we're definitely on the lookout for those types of issues. +2014-08-28 10:42:09,33,Male,United Kingdom,,Yes,No,No,Never,100-500,No,No,No,Not sure,No,No,Don't know,Very easy,No,No,Yes,Some of them,No,Yes,No,No, +2014-08-28 10:45:21,43,male,United States,NY,No,No,No,,More than 1000,No,No,Yes,Yes,Don't know,Yes,Yes,Don't know,No,No,Some of them,Yes,No,Maybe,Don't know,No, +2014-08-28 10:47:12,33,Male,United Kingdom,,No,No,Yes,Sometimes,26-100,No,Yes,Don't know,Not sure,No,No,Don't know,Don't know,Maybe,No,Some of them,No,No,Maybe,Don't know,No, +2014-08-28 10:51:08,27,Male,United Kingdom,,No,No,No,,6-25,No,Yes,No,No,No,Yes,Yes,Don't know,Maybe,No,Yes,Some of them,No,Yes,Yes,No, +2014-08-28 10:52:33,36,Male,United States,TN,No,Yes,Yes,Sometimes,More than 1000,Yes,No,Don't know,No,Don't know,Don't know,Don't know,Don't know,Yes,Maybe,No,No,No,Maybe,Don't know,No, +2014-08-28 11:02:41,39,Male,United Kingdom,,No,No,Yes,Sometimes,100-500,No,Yes,No,No,No,No,Don't know,Very easy,No,No,No,Some of them,No,Yes,Yes,No, +2014-08-28 11:04:00,31,Male,United States,TX,No,Yes,Yes,Sometimes,26-100,No,Yes,Yes,Yes,No,Don't know,Don't know,Somewhat easy,Maybe,No,Some of them,Yes,Maybe,Yes,Don't know,No, +2014-08-28 11:04:17,36,Male,United States,OH,No,No,Yes,Sometimes,100-500,Yes,Yes,Yes,Yes,No,No,Don't know,Very difficult,Maybe,Maybe,Some of them,Some of them,Maybe,Maybe,Don't know,No,I am a 15 year vet of the industry and I get 2 weeks of combined sick and vacation time a year and I have children to fit into that too. I've had heart problems from the stress. Fuck everything about startup culture. +2014-08-28 11:07:23,30,Male,United States,TX,Yes,No,Yes,Sometimes,26-100,Yes,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,No,No,Some of them,Some of them,No,Yes,Don't know,No, +2014-08-28 11:09:03,28,male,Canada,,No,No,No,,6-25,No,Yes,Yes,Not sure,No,Don't know,Yes,Very easy,No,No,Some of them,Yes,Maybe,Maybe,Yes,No, +2014-08-28 11:14:21,35,Male,United States,CA,No,Yes,Yes,Rarely,6-25,No,Yes,Yes,Yes,Yes,Yes,Yes,Very easy,No,No,Some of them,Yes,No,No,Yes,No,Since I am the CEO of my startup some of the would you feel comfortable and do you know the policy questions are interesting. Of course I feel comfortable since no one can fire me and I know the policies because I chose them!However now I am curious if my employees know just how supportive the company would be of their mental health needs and this survey is making me realize that we probably haven't done a great job communicating that to everyone. Thanks for doing this. +2014-08-28 11:15:42,19,Male,Canada,,No,No,Yes,Sometimes,26-100,No,Yes,Don't know,Not sure,No,No,Don't know,Somewhat difficult,No,No,Some of them,Yes,No,Yes,Don't know,No, +2014-08-28 11:21:17,37,Male,United States,MI,No,Yes,Yes,Sometimes,100-500,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-28 11:22:04,36,M,United States,CA,No,No,No,Never,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Very easy,No,No,Some of them,Yes,No,No,Yes,No, +2014-08-28 11:26:15,29,Female,United States,OR,No,Yes,Yes,Sometimes,26-100,Yes,No,Don't know,No,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,Yes,No,Maybe,Don't know,No, +2014-08-28 11:27:56,38,f,United States,NC,No,Yes,Yes,Sometimes,26-100,No,No,Yes,Not sure,No,Don't know,Don't know,Don't know,Maybe,No,No,No,No,No,Don't know,No,I work for the state so the health plan is large and cumbersome. I believe it covers most medical as a state benefit but I haven't seen any promotion of it. And it's not really the same as a tech company where I am. We are an IT department but hardly run like any tech company around. +2014-08-28 11:29:20,26,M,United States,CA,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Yes,No,Yes,Don't know,Don't know,Somewhat difficult,Yes,Maybe,No,No,No,Maybe,No,No, +2014-08-28 11:34:36,21,Male,United States,IL,No,No,Yes,Often,More than 1000,No,No,No,Yes,No,No,No,Don't know,Yes,No,Some of them,Some of them,No,Yes,No,Yes,I have Narcolepsy and have been fired from a job before for falling asleep standing up during a meeting. I was standing up in the back of the room so that i could pace and try to prevent myself from falling asleep. I still managed to fall asleep while standing and fell over against the wall. I was fired the next day. The worst part is this is a condition i had given months of notice about to my boss and i reminded her of it before the meeting. I worked at a hospital at the time. I would have thought that they would be more accommodating. +2014-08-28 11:36:48,31,Male,Canada,,Yes,Yes,No,Sometimes,1-5,Yes,Yes,No,Yes,No,No,Yes,Somewhat easy,No,No,No,No,No,No,Yes,No,I feel like most of my answers were useless due to answering that I am self-employed early on. Since my employer is me... my employer does/doesn't offer mental health benefits or would I be comfortable bring it up with 'them' doesn't make sense... +2014-08-28 11:38:30,37,Female,United States,CA,No,Yes,Yes,Rarely,26-100,No,No,Yes,Yes,Yes,Yes,Don't know,Don't know,Maybe,Maybe,Yes,Some of them,No,Maybe,Yes,No, +2014-08-28 11:47:35,27,Female,United States,CA,No,No,Yes,Sometimes,100-500,No,Yes,Don't know,Not sure,Yes,Don't know,Don't know,Somewhat easy,Yes,No,Some of them,No,No,Maybe,No,No, +2014-08-28 11:50:06,33,Female,United States,AZ,Yes,Yes,Yes,Sometimes,1-5,No,Yes,Yes,Yes,Yes,Yes,Yes,Somewhat easy,Maybe,Yes,Some of them,No,No,No,No,No, +2014-08-28 11:50:28,27,Male,United Kingdom,,No,No,No,Never,26-100,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Somewhat easy,No,No,Some of them,No,Yes,Yes,Don't know,No, +2014-08-28 11:54:23,36,F,United States,CA,No,No,Yes,Never,6-25,Yes,Yes,Yes,No,No,No,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,No,No,No,No, +2014-08-28 11:58:21,28,Male,United Kingdom,,No,No,No,Never,26-100,No,Yes,Don't know,Not sure,No,No,Don't know,Somewhat easy,No,No,Some of them,Yes,Maybe,Yes,Don't know,No, +2014-08-28 11:59:23,39,male,United Kingdom,,No,No,Yes,Sometimes,500-1000,No,No,Don't know,No,No,No,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,No,No,Don't know,No, +2014-08-28 12:02:59,33,Male,United States,VA,Yes,Yes,Yes,Sometimes,1-5,Yes,Yes,No,Yes,No,No,Yes,Very easy,Maybe,Maybe,Yes,Yes,No,No,Yes,No,My current work situation was constructed in part because of my mental health issues. One of the reasons I'm self employed is to give me the most flexibility for coping with my mental health issues.I have been removed from a client project in the past because of a mental health condition. This was while I was an employee for a large consulting company. +2014-08-28 12:05:41,32,Male,United Kingdom,,No,No,No,,More than 1000,No,No,Don't know,Not sure,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,Yes,Don't know,No, +2014-08-28 12:06:55,28,Male,United Kingdom,,No,No,No,,More than 1000,No,No,Don't know,Not sure,No,Don't know,Don't know,Don't know,No,No,Some of them,Some of them,Yes,Yes,No,No, +2014-08-28 12:07:28,37,Male,United Kingdom,,No,Yes,Yes,Rarely,6-25,No,Yes,No,No,No,No,Yes,Somewhat easy,Yes,No,Some of them,Yes,No,Maybe,No,Yes,Some of these questions are not really suitable for non US people. +2014-08-28 12:08:30,39,Male,Canada,,No,No,Yes,Sometimes,100-500,No,No,Yes,Yes,Yes,Yes,Yes,Very easy,Yes,No,Some of them,Yes,No,Maybe,No,Yes, +2014-08-28 12:09:18,43,msle,United States,VA,No,No,No,Sometimes,6-25,Yes,Yes,Don't know,No,No,Don't know,Don't know,Don't know,Maybe,No,No,No,No,Maybe,No,No, +2014-08-28 12:10:08,32,Neuter,United Kingdom,,No,No,Yes,Sometimes,More than 1000,No,No,Don't know,No,Yes,Yes,Don't know,Don't know,No,No,Yes,Some of them,Yes,Yes,Yes,Yes, +2014-08-28 12:10:42,27,Female,United States,WA,No,No,No,,More than 1000,No,Yes,Don't know,Not sure,No,Yes,Don't know,Don't know,Maybe,No,Some of them,Yes,No,No,Don't know,No, +2014-08-28 12:12:49,31,Female,United Kingdom,,No,No,No,,6-25,No,Yes,Don't know,No,No,No,Don't know,Don't know,No,No,Yes,Yes,Maybe,Maybe,Don't know,No, +2014-08-28 12:15:08,43,Male,United Kingdom,,No,No,Yes,Never,26-100,No,Yes,Don't know,No,No,Don't know,Don't know,Don't know,No,No,Yes,Yes,Yes,Yes,Don't know,No, +2014-08-28 12:19:34,33,Male,United States,WI,No,No,Yes,Sometimes,6-25,Yes,Yes,No,Yes,No,No,Yes,Somewhat difficult,No,No,Yes,Yes,Yes,Yes,Don't know,No, +2014-08-28 12:19:42,34,male,United Kingdom,,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Don't know,Not sure,Don't know,Don't know,Yes,Very easy,No,No,Some of them,Yes,No,Maybe,Yes,No, +2014-08-28 12:22:14,33,M,United States,CA,Yes,No,No,,1-5,No,Yes,Don't know,No,No,No,Don't know,Don't know,No,No,Yes,Yes,No,Maybe,Don't know,No, +2014-08-28 12:23:37,25,Male,United States,CA,No,No,No,,6-25,No,Yes,Don't know,No,No,No,Don't know,Don't know,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-28 12:30:20,25,Male,United States,NE,No,Yes,Yes,Sometimes,More than 1000,No,No,Yes,Yes,Yes,Yes,Yes,Don't know,Maybe,No,Some of them,Some of them,No,No,No,Yes, +2014-08-28 12:40:46,32,Male,United Kingdom,,Yes,Yes,No,,1-5,No,Yes,No,Yes,No,No,Yes,Somewhat easy,No,No,No,Yes,No,Maybe,No,No, +2014-08-28 12:42:12,25,Male,United States,CO,No,Yes,Yes,Sometimes,26-100,No,Yes,Yes,Yes,Don't know,Don't know,Yes,Don't know,Maybe,No,Some of them,Some of them,No,Maybe,Don't know,No, +2014-08-28 12:53:21,29,M,United Kingdom,,No,No,No,Rarely,100-500,No,Yes,Don't know,Not sure,No,No,Don't know,Somewhat easy,No,No,Some of them,Yes,No,Maybe,Don't know,Yes, +2014-08-28 13:01:26,33,Male,United States,NY,No,No,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,Don't know,Don't know,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,No,No,Don't know,No, +2014-08-28 13:04:30,37,female,United States,TX,No,No,Yes,Often,6-25,Yes,Yes,Don't know,Not sure,No,No,Yes,Somewhat difficult,Yes,No,Some of them,Some of them,No,Yes,No,Yes, +2014-08-28 13:08:36,35,Female,United States,LA,No,No,Yes,Sometimes,100-500,No,No,Yes,No,No,No,Yes,Very difficult,Yes,Maybe,No,Some of them,No,Yes,No,Yes,I work for the state government. While things are slowly changing regarding covering mental health with state employees it's just not something that is acceptable in this kind of strict environment so I have to be careful about what I say and how I say it. I often take mental health days but have to call in with a physical illness because mental health problems are not acceptable excuses for using sick leave. +2014-08-28 13:11:05,22,Female,United States,WA,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Very difficult,Yes,Maybe,Some of them,Some of them,No,Maybe,No,Yes, +2014-08-28 13:17:40,38,Male,United States,MI,No,No,No,Never,26-100,No,Yes,Yes,Yes,No,No,Don't know,Somewhat easy,Maybe,No,Some of them,Yes,No,Maybe,No,Yes, +2014-08-28 13:26:17,32,Female,United States,CA,No,Yes,Yes,Often,100-500,No,Yes,Yes,No,No,Don't know,Don't know,Don't know,Yes,No,Some of them,Yes,No,No,Don't know,No, +2014-08-28 13:35:25,35,female,United States,CA,No,No,Yes,Sometimes,100-500,Yes,Yes,Don't know,No,Don't know,Don't know,Don't know,Very easy,Maybe,No,Some of them,No,No,Maybe,Yes,No,It might be safe to talk about it where I am now but I don't know for sure and I err on the side of being over cautious. Struggle with depression and anxiety which sometimes affects my productivity but I try to make up / cover up for it instead of being open about it. +2014-08-28 13:39:12,29,Male,United States,MD,No,No,No,Never,100-500,No,No,Yes,Yes,Yes,No,Yes,Very easy,Yes,Maybe,Yes,Yes,No,Maybe,Don't know,No, +2014-08-28 13:39:40,23,Male,United States,CA,No,Yes,Yes,Sometimes,6-25,No,Yes,No,Yes,No,No,Don't know,Very easy,No,No,Some of them,Yes,Maybe,Maybe,Yes,No, +2014-08-28 13:40:08,39,M,United States,CT,No,No,No,,26-100,Yes,Yes,Yes,No,No,No,Don't know,Don't know,Yes,Maybe,No,No,No,No,Don't know,No, +2014-08-28 13:41:51,30,Female,United States,CA,No,No,No,,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Very easy,No,No,Some of them,No,No,No,Yes,No, +2014-08-28 13:47:37,32,M,United Kingdom,,No,No,No,,26-100,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Somewhat easy,Maybe,Maybe,Some of them,Some of them,Maybe,Maybe,Don't know,No, +2014-08-28 13:47:57,28,Female (trans),United States,CA,No,No,Yes,Sometimes,26-100,No,Yes,No,Yes,No,No,Don't know,Somewhat difficult,Yes,Maybe,Some of them,Some of them,No,No,No,Yes, +2014-08-28 13:48:30,40,female,United States,WA,No,Yes,Yes,Sometimes,100-500,No,No,Yes,Yes,Yes,Yes,Yes,Don't know,Maybe,No,Some of them,Yes,No,No,Don't know,Yes,I'm comfortable talking about mental health with my current supervisor & my immediate at my current job but this is a first for me! +2014-08-28 13:54:47,36,f,United States,CA,No,Yes,No,,6-25,No,Yes,Don't know,No,No,Don't know,Don't know,Don't know,No,No,No,Some of them,No,Maybe,Yes,No, +2014-08-28 13:57:01,27,Male,United States,IN,No,No,No,,26-100,Yes,Yes,Don't know,Not sure,No,Don't know,Don't know,Very easy,No,No,Yes,Yes,Maybe,Maybe,Yes,No, +2014-08-28 14:00:02,41,Male,United States,TX,No,Yes,No,Sometimes,More than 1000,No,Yes,Yes,Yes,No,Yes,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,Maybe,No,No, +2014-08-28 14:01:56,29,Male,United Kingdom,,No,No,No,Never,6-25,No,Yes,Don't know,No,No,No,Don't know,Don't know,Maybe,No,Some of them,No,No,Maybe,Don't know,No, +2014-08-28 14:02:07,29,m,United Kingdom,,No,No,Yes,Sometimes,100-500,No,Yes,No,No,No,No,Don't know,Somewhat difficult,No,No,Some of them,Some of them,No,Maybe,No,No, +2014-08-28 14:04:54,35,Male,United States,MO,No,No,Yes,Often,1-5,No,No,No,No,No,No,Yes,Very difficult,Yes,No,Some of them,Some of them,No,Yes,No,Yes, +2014-08-28 14:12:58,28,Male,United States,NV,No,No,Yes,Never,6-25,Yes,Yes,No,Yes,No,No,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,No,No,Don't know,No, +2014-08-28 14:15:02,36,F,United Kingdom,,Yes,No,No,Sometimes,1-5,Yes,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,Maybe,No,Some of them,No,No,No,Don't know,No, +2014-08-28 14:31:00,39,Female,United States,WA,No,No,No,Sometimes,26-100,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Don't know,Yes,No,No,No,No,Yes,Don't know,No, +2014-08-28 14:38:50,39,Male,United States,FL,No,Yes,Yes,Sometimes,500-1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Very difficult,Maybe,No,Some of them,Yes,No,No,Don't know,No, +2014-08-28 14:41:47,44,male,United States,,Yes,Yes,Yes,Sometimes,1-5,Yes,Yes,No,Yes,No,No,No,Very easy,Yes,Yes,Some of them,No,No,No,Yes,No, +2014-08-28 14:52:46,40,Female,United States,WA,No,Yes,Yes,Sometimes,100-500,No,No,Yes,Not sure,Yes,Don't know,Don't know,Don't know,Yes,Maybe,Some of them,No,No,No,Don't know,No, +2014-08-28 14:53:32,38,M,United States,IL,No,No,No,Never,More than 1000,Yes,Yes,No,Yes,No,No,No,Very difficult,Yes,Yes,No,No,No,No,Don't know,No, +2014-08-28 14:57:10,34,Male,United States,FL,No,No,No,,More than 1000,Yes,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,No,No,Some of them,Yes,No,Maybe,Yes,No, +2014-08-28 15:01:46,43,M,United States,MA,No,No,No,,More than 1000,No,Yes,Yes,No,Yes,Yes,Don't know,Don't know,No,No,Some of them,Yes,No,Maybe,Don't know,No, +2014-08-28 15:25:39,48,Female (cis),United States,CA,No,Yes,No,Often,26-100,No,Yes,Don't know,No,No,No,No,Very difficult,Yes,Yes,No,Some of them,No,No,No,Yes,None of us who are already in marginal groups in tech--the non-young the non-male the non-white--will risk our careers to admit another source of stigma: poor health. +2014-08-28 15:32:03,20,Male,United States,WA,No,No,No,Never,26-100,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,No,No,Some of them,Yes,Maybe,Maybe,Yes,No, +2014-08-28 15:37:04,40,M,United States,MI,Yes,No,No,Sometimes,1-5,Yes,Yes,Don't know,Not sure,No,No,Don't know,Somewhat easy,Yes,Maybe,Some of them,No,No,No,Don't know,No, +2014-08-28 15:40:32,29,female,United Kingdom,,No,No,Yes,Rarely,6-25,No,Yes,Don't know,No,No,No,Don't know,Don't know,Maybe,No,Some of them,No,No,Maybe,Don't know,No, +2014-08-28 15:43:37,35,Male,United States,MI,No,Yes,Yes,Sometimes,1-5,No,No,No,Yes,No,No,Yes,Don't know,No,No,Some of them,Yes,No,No,Yes,No, +2014-08-28 15:48:12,29,Male,United States,WI,No,Yes,No,Sometimes,More than 1000,Yes,No,Yes,Yes,No,Yes,Yes,Very easy,Maybe,No,Some of them,No,No,No,Yes,No, +2014-08-28 15:50:12,40,M,United States,CA,No,No,No,Never,100-500,No,Yes,Yes,Not sure,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,Maybe,Don't know,No, +2014-08-28 15:54:35,29,F,United States,CA,No,Yes,Yes,Rarely,100-500,No,Yes,Yes,Not sure,Don't know,No,Don't know,Don't know,No,No,Yes,Yes,No,Maybe,Don't know,No, +2014-08-28 15:56:47,34,male,United States,TX,No,No,Yes,Sometimes,1-5,No,Yes,No,No,No,No,Don't know,Don't know,Yes,No,No,No,No,Yes,Don't know,No, +2014-08-28 16:09:35,44,Male,United Kingdom,,No,Yes,Yes,Sometimes,500-1000,No,No,Don't know,No,No,No,Don't know,Somewhat difficult,Maybe,No,Some of them,Yes,No,Maybe,No,Yes, +2014-08-28 16:17:09,24,female,United States,NY,No,Yes,Yes,Often,6-25,No,Yes,Yes,Yes,No,No,Yes,Very easy,No,No,Some of them,Yes,No,Yes,No,Yes, +2014-08-28 16:31:00,47,F,United States,PA,No,No,No,,100-500,Yes,Yes,Don't know,No,No,Don't know,Don't know,Very difficult,Yes,Yes,No,No,No,No,No,No, +2014-08-28 16:42:49,43,m,United Kingdom,,No,Yes,No,,More than 1000,No,No,Don't know,No,No,No,Don't know,Very easy,Maybe,No,Some of them,Yes,No,Maybe,Don't know,No, +2014-08-28 16:52:23,36,M,United States,PA,No,No,No,Rarely,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Somewhat difficult,No,No,Some of them,Yes,No,No,No,No, +2014-08-28 16:52:34,43,male,United States,GA,No,No,Yes,Sometimes,More than 1000,No,No,Don't know,No,No,Don't know,Don't know,Very difficult,Maybe,No,Some of them,Yes,No,No,Don't know,No, +2014-08-28 16:52:34,36,male,United Kingdom,,Yes,No,No,Sometimes,6-25,Yes,Yes,No,No,No,No,Don't know,Somewhat difficult,No,No,Yes,Yes,No,Maybe,Don't know,Yes, +2014-08-28 16:54:49,31,Female,United States,NY,No,Yes,Yes,Sometimes,100-500,No,Yes,Yes,Yes,No,No,Don't know,Somewhat difficult,No,No,Yes,Yes,Maybe,Maybe,Don't know,No,I have been incredibly public about my own struggle in my own conversations and in social media insofar as how I can use my depression to raise awareness or help others. Because of that my employer - or any future employer - kind of knows by default. It's not a secret. That said the downside of that openness is that I have no faith that I wouldn't be discriminated against at a future job simply because the information is public. Likewise I worry I'm seen as less-than by my employer in some circumstances. Regerdless I don't regret being public and raising awareness. My point is that even those of us who do publicly discuss the issue fear systemic retribution. +2014-08-28 16:55:07,35,Male,United States,CA,No,No,No,Sometimes,More than 1000,No,Yes,Don't know,Not sure,Yes,Don't know,Don't know,Don't know,Maybe,No,Some of them,No,No,No,Don't know,No, +2014-08-28 16:55:31,33,male,United States,TN,No,Yes,No,,26-100,No,No,Yes,No,No,No,Yes,Somewhat difficult,No,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-28 16:56:57,34,M,United States,TN,No,No,Yes,Sometimes,100-500,No,Yes,Don't know,No,Yes,Don't know,Yes,Don't know,Maybe,No,Some of them,No,No,No,Don't know,No,At a previous employer I witness a bad thing happen to a coworker with mental health issues get swept under the rug... :( +2014-08-28 16:57:07,40,m,United States,TN,Yes,Yes,Yes,Sometimes,1-5,Yes,Yes,No,Yes,No,No,Yes,Very easy,No,No,Yes,Yes,No,No,Yes,No, +2014-08-28 16:57:46,40,M,United States,IL,No,No,No,Rarely,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Don't know,No,No,Some of them,Some of them,No,Maybe,Don't know,No,While not personally affected I do have immediate family with mental health illness and my employer has been very supportive. Thanks for doing this survey. +2014-08-28 16:57:49,42,Male,United States,WI,No,No,Yes,Sometimes,1-5,Yes,Yes,No,Yes,No,No,Don't know,Somewhat easy,Maybe,No,No,No,No,Maybe,Don't know,No, +2014-08-28 16:58:33,23,M,United States,KY,No,Yes,No,,26-100,Yes,Yes,Yes,Yes,No,Don't know,Yes,Don't know,Maybe,No,No,Some of them,No,No,Don't know,No, +2014-08-28 16:58:33,21,Male,United Kingdom,,No,Yes,No,Never,6-25,No,No,No,No,No,No,Yes,Somewhat easy,Maybe,No,Some of them,Some of them,No,Maybe,Don't know,No, +2014-08-28 16:58:50,26,Male,Canada,,No,No,No,Sometimes,6-25,Yes,Yes,No,No,No,No,Don't know,Very difficult,Yes,Maybe,Some of them,Some of them,No,Maybe,Don't know,No, +2014-08-28 17:01:06,31,Male,United States,,No,Yes,No,,6-25,No,Yes,Don't know,Not sure,No,No,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-28 17:01:21,25,M,United States,CA,No,Yes,No,,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Very easy,No,No,Some of them,Yes,Maybe,Yes,Yes,No, +2014-08-28 17:01:25,51,Male,United States,MN,No,No,No,Never,More than 1000,Yes,Yes,Yes,Yes,Yes,Yes,Yes,Very easy,No,No,Yes,Yes,No,No,Yes,No, +2014-08-28 17:02:27,24,Male,United States,TN,No,No,No,,6-25,No,Yes,Don't know,Not sure,Don't know,No,Yes,Somewhat easy,No,No,Some of them,Yes,No,Maybe,Don't know,No, +2014-08-28 17:02:29,33,Male,United States,MN,No,No,No,,100-500,No,Yes,No,No,No,No,Don't know,Don't know,Maybe,No,Some of them,Yes,No,No,No,No,The company I work for was started by engineers and so anything other then the engineering department has always lacked a bit. Now that we've grown things are better but I feel that overall our total benefits package (including healthcare) isn't well communicated. This reflects negatively on the mental health questions above but would also reflect negatively on any other sort of survey about the benefits. That is I don't think the company is purposefully doing less for mental health. They just aren't doing enough across the board and that includes mental health. +2014-08-28 17:02:56,32,male,United Kingdom,,No,Yes,Yes,Rarely,6-25,No,No,No,No,No,No,No,Don't know,Yes,Maybe,Some of them,No,No,No,No,No, +2014-08-28 17:02:44,32,male,United Kingdom,,No,Yes,Yes,Rarely,6-25,No,No,No,No,No,No,No,Don't know,Yes,Maybe,Some of them,No,No,No,No,No, +2014-08-28 17:03:42,26,Male,United Kingdom,,Yes,No,Yes,Rarely,1-5,Yes,Yes,No,Not sure,Don't know,Don't know,Don't know,Somewhat difficult,No,No,Yes,Yes,Maybe,Maybe,Yes,No, +2014-08-28 17:07:11,23,M,United States,IL,No,No,No,Never,100-500,No,No,Don't know,No,Don't know,Don't know,Don't know,Don't know,Maybe,No,Some of them,Some of them,Maybe,Maybe,Don't know,No, +2014-08-28 17:07:28,33,Male,United States,TN,No,Yes,Yes,Often,6-25,Yes,Yes,No,Yes,No,No,Don't know,Very difficult,Yes,No,Some of them,Yes,No,Maybe,No,No, +2014-08-28 17:07:39,46,Male,United States,IL,No,No,Yes,Rarely,More than 1000,No,No,Yes,Yes,Yes,Yes,Yes,Somewhat easy,Yes,Maybe,No,No,No,Maybe,Yes,No, +2014-08-28 17:08:16,34,male,United Kingdom,,No,No,No,,6-25,Yes,Yes,No,No,No,No,No,Somewhat difficult,Yes,Maybe,No,No,No,Yes,No,Yes, +2014-08-28 17:09:03,35,M,United States,DC,No,Yes,Yes,Sometimes,6-25,No,Yes,Yes,Yes,No,No,Don't know,Somewhat easy,Maybe,Maybe,Some of them,Some of them,No,No,Don't know,No, +2014-08-28 17:10:00,39,M,United States,KS,No,No,No,,1-5,Yes,Yes,No,Yes,No,No,Don't know,Very difficult,Maybe,Maybe,Some of them,Yes,Maybe,Maybe,No,No,Thank you for all you are doing to study this topic and raise awareness in our communities. +2014-08-28 17:11:48,56,m,United States,CA,No,No,Yes,Rarely,More than 1000,Yes,Yes,Yes,Yes,Don't know,Yes,Yes,Somewhat easy,No,No,Yes,Yes,Yes,Yes,Yes,No, +2014-08-28 17:12:30,32,Female,United Kingdom,,No,Yes,Yes,Sometimes,100-500,No,Yes,Don't know,No,No,No,Don't know,Somewhat difficult,Maybe,No,Some of them,Some of them,No,Yes,Don't know,Yes, +2014-08-28 17:14:31,41,male,United Kingdom,,No,No,No,,26-100,No,No,Yes,Yes,Yes,Yes,Yes,Don't know,Maybe,Maybe,Some of them,Some of them,No,Yes,No,Yes, +2014-08-28 17:16:53,39,Male,United States,TN,No,No,No,,More than 1000,Yes,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-28 17:19:05,37,Male,United States,OK,No,Yes,No,,500-1000,No,No,Yes,Yes,No,No,Yes,Very easy,Maybe,No,No,No,No,No,No,No, +2014-08-28 17:19:27,30,m,United States,CA,Yes,Yes,Yes,Sometimes,6-25,Yes,Yes,Don't know,Not sure,No,Don't know,Don't know,Very difficult,Yes,No,No,No,No,Maybe,Don't know,No,The main reason for the openness answers are because of an experience with my last employer. I felt I could trust my direct supervisor so I divulged information. It ended up spreading to more supervisors and eventually my coworkers. Supers highly suggested treatment but rushed things that shouldn't have been rushed and I ended up being incorrectly treated in a psych ward and mentally scarred from the issue. I lost most of my desire to program due to the experience not to mention thousands of dollars I lost - lost work time vacation time they used for treatment time doctors expenses etc. I have major depressive disorder high anxiety and mild agoraphobia. After seeing what treatment has to offer I will likely not seek it again and continue as is. (Long story short.) +2014-08-28 17:19:53,31,Male,United States,TN,No,No,No,,26-100,No,Yes,Yes,No,Yes,No,Yes,Somewhat easy,Maybe,No,Some of them,Some of them,No,Maybe,No,No, +2014-08-28 17:20:23,29,M,United States,TX,No,No,No,,More than 1000,No,No,Don't know,Not sure,No,Don't know,Don't know,Don't know,Maybe,No,No,Some of them,No,Maybe,Don't know,No, +2014-08-28 17:20:41,23,Female,United Kingdom,,No,Yes,No,Never,More than 1000,No,No,No,No,No,Yes,Don't know,Somewhat easy,Yes,Maybe,No,No,No,Maybe,Don't know,No, +2014-08-28 17:21:01,31,male,United States,CO,No,No,Yes,Never,26-100,No,Yes,Yes,Yes,No,Don't know,Yes,Very easy,Maybe,No,No,No,No,No,Don't know,No, +2014-08-28 17:21:43,29,Male,United States,TN,No,Yes,Yes,Sometimes,26-100,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,No,Yes,No, +2014-08-28 17:22:18,30,Mail,United States,GA,No,No,No,Never,26-100,Yes,Yes,Yes,Yes,Don't know,Don't know,Yes,Very easy,No,No,Some of them,Yes,Maybe,Maybe,Yes,No, +2014-08-28 17:22:53,37,Male,United States,TN,No,No,No,Never,500-1000,Yes,Yes,Yes,No,Yes,Don't know,Don't know,Don't know,Maybe,No,Some of them,Yes,No,No,Yes,Yes,(yes but the situation was unusual and involved a change in leadership at a very high level in the organization as well as an extended leave of absence) +2014-08-28 17:23:19,36,male,United States,VA,Yes,No,No,Never,1-5,No,Yes,Yes,No,No,Don't know,Don't know,Somewhat difficult,No,No,Some of them,Yes,Yes,Yes,Yes,No, +2014-08-28 17:27:03,35,Male,United States,TN,No,Yes,Yes,Sometimes,26-100,Yes,Yes,Yes,Yes,No,Don't know,Don't know,Don't know,Maybe,Maybe,Some of them,No,No,Maybe,No,No, +2014-08-28 17:27:47,41,M,United States,DC,No,Yes,No,Never,500-1000,Yes,No,Don't know,No,No,No,Don't know,Don't know,Maybe,No,No,No,No,No,Don't know,No, +2014-08-28 17:28:46,31,Male,United Kingdom,,No,No,Yes,Rarely,6-25,No,Yes,Don't know,Not sure,No,No,Don't know,Don't know,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-28 17:28:58,38,m,United Kingdom,,No,Yes,No,,500-1000,No,No,Yes,Yes,Yes,Yes,Don't know,Somewhat easy,No,No,Some of them,Yes,No,Maybe,No,No, +2014-08-28 17:33:05,39,Male,United States,TN,No,Yes,No,Sometimes,More than 1000,No,Yes,Yes,No,Yes,Yes,Don't know,Don't know,Maybe,Maybe,Some of them,Yes,Maybe,Maybe,Don't know,Yes,I would add that while there were negative consequences for coworkers with mental health they were given a HUGE amount of leeway. I think the team at large tried their best to be kind but that's how the person suffered. The company actually gave this person a lot of help. Which was cool. But the team still discriminated. +2014-08-28 17:33:20,42,male,United States,VA,Yes,Yes,No,Sometimes,6-25,Yes,No,Yes,Not sure,Don't know,Yes,Don't know,Don't know,Maybe,Maybe,Some of them,No,No,Maybe,Don't know,No, +2014-08-28 17:34:30,32,Male,United States,TN,Yes,Yes,Yes,Rarely,1-5,Yes,Yes,No,Yes,No,No,Don't know,Very difficult,Yes,No,Some of them,No,No,Maybe,Don't know,No, +2014-08-28 17:35:14,29,m,United States,TN,No,Yes,No,,100-500,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-28 17:36:48,30,Male,United States,TN,No,Yes,No,Never,100-500,No,Yes,Yes,No,Don't know,Yes,Don't know,Very difficult,Yes,Yes,Some of them,No,Maybe,Maybe,No,No, +2014-08-28 17:39:06,40,M,United States,TN,No,Yes,Yes,Often,500-1000,Yes,Yes,Don't know,Not sure,No,Don't know,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,No,Yes,Don't know,No,Bipolar spectrum is tricky. +2014-08-28 17:45:21,51,m,United States,TN,No,No,No,,100-500,No,No,Don't know,Not sure,No,Don't know,Don't know,Somewhat difficult,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-28 17:46:37,33,Male,United States,IN,No,No,No,Never,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Somewhat easy,No,No,Some of them,Yes,No,No,Yes,No, +2014-08-28 17:47:49,50,Male,United States,VA,Yes,No,No,Never,1-5,Yes,Yes,No,Yes,No,No,Yes,Somewhat easy,No,No,Some of them,Yes,No,Maybe,Yes,No,A lot of these answers aren't really applicable since I'm self employed as a sole proprietor. +2014-08-28 17:50:32,24,Male,United States,TX,No,No,No,Sometimes,26-100,Yes,Yes,Don't know,No,No,Don't know,Don't know,Somewhat easy,No,No,Some of them,Yes,No,Maybe,No,No, +2014-08-28 17:56:02,25,Male,United States,TX,No,Yes,Yes,Rarely,26-100,No,No,No,No,No,No,Don't know,Don't know,Yes,Maybe,No,No,No,Maybe,No,No, +2014-08-28 17:57:39,43,Male,United Kingdom,,No,Yes,Yes,Rarely,26-100,No,Yes,No,No,No,No,Don't know,Very difficult,Yes,Yes,Some of them,No,No,No,No,Yes, +2014-08-28 17:57:42,25,f,United States,CA,Yes,No,Yes,Often,1-5,No,Yes,Yes,Yes,Yes,Yes,Yes,Very easy,Maybe,Maybe,Some of them,Some of them,No,No,Yes,Yes, +2014-08-28 17:59:31,24,Male,United Kingdom,,Yes,No,No,,1-5,Yes,Yes,No,Yes,No,No,Yes,Very easy,No,No,No,No,No,Maybe,Yes,No, +2014-08-28 17:59:54,51,m,United States,CO,Yes,No,No,Never,1-5,No,Yes,No,Yes,No,No,Yes,Somewhat difficult,No,No,Some of them,Some of them,Maybe,Maybe,Don't know,No, +2014-08-28 17:59:57,49,Male,United States,OR,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,No,Yes,Yes,Somewhat difficult,Yes,Maybe,No,No,No,Maybe,No,Yes, +2014-08-28 18:01:00,30,Male,United States,OK,No,No,No,,More than 1000,Yes,Yes,Yes,No,Yes,Yes,Don't know,Don't know,Yes,Maybe,No,No,No,No,Don't know,No, +2014-08-28 18:02:09,25,female,United States,OH,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,Yes,No,Don't know,Don't know,Yes,Yes,No,No,No,No,No,No,While I have not seen any direct retaliation against people with known mental illness many people do freely use insults commonly associated with mental illness (r****d for example) and criticize people behind their back for taking extra leave for doctor appointments (Oh I bet they are just hung over or other comments about how lazy they are.) +2014-08-28 18:07:42,36,Male,United States,TN,No,No,Yes,Rarely,500-1000,Yes,Yes,Yes,Yes,Don't know,Don't know,Don't know,Don't know,Maybe,No,No,No,No,Maybe,Don't know,No, +2014-08-28 18:17:41,48,Male,United States,VA,No,No,Yes,Never,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Don't know,Maybe,Maybe,Yes,Yes,No,Maybe,Yes,Yes, +2014-08-28 18:21:23,53,Male,United States,OR,No,No,Yes,Rarely,6-25,Yes,Yes,Yes,Yes,No,Yes,Don't know,Don't know,Maybe,Maybe,Some of them,No,No,No,Don't know,No, +2014-08-28 18:21:58,24,Female,United Kingdom,,No,Yes,Yes,Often,6-25,Yes,Yes,No,No,No,No,Don't know,Very easy,No,No,Yes,Yes,No,No,Don't know,No, +2014-08-28 18:26:35,33,Male,United States,OR,No,Yes,Yes,Sometimes,26-100,No,Yes,Don't know,Yes,No,Yes,Don't know,Somewhat easy,No,No,Yes,Yes,No,No,Don't know,No, +2014-08-28 18:50:47,25,Female,Canada,,No,Yes,Yes,Sometimes,6-25,No,Yes,Yes,Yes,No,No,Yes,Somewhat easy,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-28 19:03:47,30,Male,United Kingdom,,No,No,Yes,Sometimes,26-100,No,Yes,No,No,No,No,Don't know,Somewhat difficult,Yes,Maybe,Some of them,No,No,Maybe,No,No, +2014-08-28 19:04:05,30,Male,United States,PA,Yes,No,No,Never,1-5,Yes,Yes,No,Yes,No,No,Yes,Somewhat easy,Maybe,Maybe,Some of them,Some of them,Maybe,Maybe,Don't know,No, +2014-08-28 19:15:35,34,male,United Kingdom,,Yes,No,Yes,Sometimes,1-5,Yes,Yes,No,No,No,No,Yes,Somewhat difficult,No,No,Some of them,Some of them,No,No,Yes,No, +2014-08-28 19:26:03,31,Male,United States,SC,No,No,No,,More than 1000,Yes,Yes,Yes,Yes,Yes,Yes,Yes,Very easy,No,No,Some of them,Yes,Maybe,Yes,Yes,No, +2014-08-28 19:28:27,22,F,United States,CA,No,Yes,Yes,Often,More than 1000,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Don't know,Yes,Yes,No,No,No,No,Don't know,No, +2014-08-28 19:35:39,28,Male,United States,TN,No,Yes,No,Sometimes,6-25,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Somewhat easy,No,No,Some of them,Yes,No,Yes,Don't know,No, +2014-08-28 20:12:08,35,Male,United States,UT,No,Yes,Yes,Rarely,26-100,No,No,Yes,Yes,No,Yes,Yes,Somewhat difficult,Maybe,No,Some of them,Some of them,No,No,No,No, +2014-08-28 20:31:02,28,Male,United States,CA,No,Yes,Yes,Sometimes,26-100,No,No,Yes,No,No,No,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,No,No,Yes,No, +2014-08-28 21:22:40,33,Male,United States,MO,No,Yes,No,,500-1000,No,Yes,Yes,No,Don't know,Don't know,Don't know,Very easy,No,No,Yes,Yes,Yes,Yes,Yes,No, +2014-08-28 21:24:48,29,male,United States,CA,No,No,No,Sometimes,More than 1000,No,Yes,Yes,No,Yes,No,Don't know,Don't know,Yes,Maybe,No,No,No,No,Don't know,No, +2014-08-28 21:27:19,43,M,United States,,No,Yes,No,Sometimes,500-1000,No,No,Yes,Not sure,No,Don't know,Don't know,Don't know,Maybe,No,No,Some of them,No,Maybe,No,No,My employer gives access to basic counseling and referrals but I don't know (and it's not obvious) what might be covered in the way of expenses for therapy medication etc. +2014-08-28 21:30:35,29,Male,United States,NY,No,No,No,,26-100,No,Yes,Yes,Yes,Yes,Yes,Don't know,Somewhat easy,No,No,Some of them,Some of them,Maybe,Maybe,Yes,No, +2014-08-28 21:33:32,25,Male,United States,TX,No,No,No,,100-500,Yes,Yes,Yes,No,No,No,Yes,Don't know,No,No,Yes,Yes,Maybe,Maybe,Don't know,No, +2014-08-28 21:38:12,31,Male,United States,MO,No,Yes,No,Never,100-500,No,Yes,Don't know,No,Don't know,Don't know,Don't know,Very easy,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-28 21:41:53,35,Female,United States,GA,No,Yes,Yes,Sometimes,6-25,No,No,Yes,Not sure,Yes,Yes,Yes,Somewhat difficult,Maybe,Maybe,Some of them,Yes,No,Maybe,Yes,No,* Small family business - YMMV. +2014-08-28 21:47:33,34,male,United States,TX,No,No,No,Often,1-5,No,Yes,Don't know,No,No,Yes,Don't know,Very easy,No,No,Some of them,Yes,No,Maybe,Yes,No,* Small family business - YMMV. +2014-08-28 22:16:34,43,Cis Male,United States,WA,No,No,Yes,Sometimes,100-500,Yes,Yes,Yes,Yes,No,Yes,Yes,Very difficult,Yes,Maybe,Some of them,No,No,Maybe,No,Yes,* Small family business - YMMV. +2014-08-28 22:17:15,38,Male,United States,WA,No,Yes,Yes,Sometimes,100-500,No,Yes,No,Not sure,No,No,Don't know,Very difficult,Yes,Yes,No,Some of them,No,Maybe,No,No,* Small family business - YMMV. +2014-08-28 22:18:41,26,Male,United States,WA,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Don't know,Not sure,No,Yes,Yes,Very difficult,Maybe,No,Some of them,Some of them,Yes,Yes,No,Yes,* Small family business - YMMV. +2014-08-28 22:20:33,38,Male,United Kingdom,,Yes,Yes,Yes,Rarely,1-5,Yes,No,No,No,No,No,Yes,Very difficult,Maybe,No,No,No,No,No,No,No, +2014-08-28 22:22:39,42,Male,United States,TX,No,No,Yes,Often,6-25,No,Yes,Don't know,No,No,Don't know,Don't know,Don't know,Yes,Maybe,No,No,No,Maybe,Don't know,No, +2014-08-28 22:35:10,32,Male,United States,WA,No,No,Yes,Rarely,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Somewhat easy,Maybe,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-28 22:39:57,44,male,United States,WA,No,Yes,Yes,Sometimes,6-25,Yes,Yes,Yes,Yes,Yes,Yes,Yes,Somewhat difficult,Maybe,Maybe,Some of them,Yes,No,Maybe,No,No, +2014-08-28 22:46:40,28,Male,United States,WA,No,Yes,Yes,Rarely,More than 1000,No,Yes,Yes,Yes,Don't know,Don't know,Don't know,Don't know,Maybe,No,Some of them,No,No,No,No,No, +2014-08-28 23:03:05,40,Male,United States,WA,No,Yes,Yes,Sometimes,More than 1000,Yes,Yes,Yes,Yes,Yes,Yes,Yes,Very difficult,Yes,No,Some of them,Some of them,No,Maybe,Don't know,Yes, +2014-08-28 23:13:18,31,F,United States,AZ,No,Yes,Yes,Sometimes,500-1000,No,Yes,Yes,Yes,No,Don't know,Yes,Somewhat easy,Maybe,No,Some of them,Yes,No,No,Yes,No, +2014-08-28 23:16:30,32,male,United States,WA,No,Yes,No,Sometimes,100-500,No,Yes,Yes,Yes,Yes,Yes,Don't know,Don't know,Yes,No,Some of them,No,No,No,Don't know,No, +2014-08-28 23:57:07,28,Male,United States,WA,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Don't know,No,Don't know,Don't know,Don't know,Somewhat easy,Maybe,No,Some of them,No,No,Maybe,No,No, +2014-08-29 00:05:07,39,Male,United States,AZ,No,Yes,Yes,Often,26-100,No,Yes,Yes,Yes,No,No,Yes,Don't know,Yes,No,Some of them,No,No,No,No,No, +2014-08-29 00:06:49,45,Male,United States,NY,No,No,No,,More than 1000,No,No,Yes,Yes,Yes,Yes,Don't know,Don't know,No,No,Some of them,Some of them,No,No,Yes,No, +2014-08-29 00:11:17,43,Male,United States,WA,No,No,Yes,Rarely,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Don't know,Somewhat easy,No,No,Yes,Yes,Maybe,Yes,Yes,No,I have an exceptional employer. I haven't run into problems with any employer I've had but consider myself lucky. +2014-08-29 00:41:25,35,Male,United States,CA,No,No,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,Don't know,Yes,Don't know,Very difficult,Maybe,Maybe,Some of them,Some of them,No,No,Don't know,No, +2014-08-29 00:43:37,40,Male,United States,WA,No,Yes,Yes,Sometimes,6-25,No,Yes,Yes,Yes,Don't know,Don't know,Yes,Very easy,Maybe,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-29 01:14:09,24,Male,United Kingdom,,No,Yes,Yes,Often,26-100,No,No,Don't know,Yes,No,No,No,Somewhat easy,Yes,Maybe,Some of them,Yes,No,Maybe,No,Yes, +2014-08-29 01:40:36,36,Female ,United States,WA,No,Yes,Yes,Rarely,6-25,No,Yes,Don't know,No,No,Don't know,Don't know,Don't know,Yes,Maybe,Some of them,No,No,No,Don't know,No, +2014-08-29 02:10:57,38,Male,United States,TN,No,No,No,,6-25,No,Yes,No,No,No,No,Yes,Don't know,Maybe,No,Some of them,Yes,Maybe,Maybe,Don't know,No,Some of these should not be required. +2014-08-29 03:02:16,30,male,United States,WA,No,Yes,No,Never,More than 1000,No,No,Don't know,No,No,Don't know,Don't know,Don't know,Yes,Maybe,No,No,No,No,No,No, +2014-08-29 03:08:25,26,Male,United States,CA,No,No,Yes,Rarely,More than 1000,No,Yes,Yes,Not sure,Don't know,Don't know,Don't know,Don't know,No,No,Some of them,Some of them,No,Maybe,No,No, +2014-08-29 04:39:23,33,M,United Kingdom,,No,No,No,,More than 1000,No,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,No,No,Some of them,Yes,Maybe,Maybe,Don't know,No, +2014-08-29 04:53:12,32,Male,United Kingdom,,No,No,No,,6-25,No,Yes,Don't know,No,No,No,Don't know,Very easy,No,No,No,Yes,No,Maybe,No,No, +2014-08-29 05:39:21,24,M,United Kingdom,,Yes,Yes,No,Often,1-5,Yes,Yes,Don't know,Not sure,No,No,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,Maybe,Don't know,No, +2014-08-29 05:47:19,55,male,United Kingdom,,No,No,Yes,Often,More than 1000,No,No,Yes,Yes,Yes,Yes,Don't know,Somewhat easy,Yes,Maybe,No,Some of them,No,Maybe,No,Yes, +2014-08-29 05:54:26,33,Male,United Kingdom,,Yes,Yes,Yes,Sometimes,1-5,Yes,Yes,No,Yes,No,No,No,Very difficult,Yes,Maybe,Some of them,Some of them,No,Maybe,No,Yes, +2014-08-29 05:57:48,26,Female,United Kingdom,,Yes,Yes,Yes,Sometimes,1-5,Yes,Yes,No,No,No,No,Don't know,Very easy,Maybe,No,Some of them,Yes,No,Maybe,Yes,No,I am a Trans woman and suffer from depression relating to that. I'm a contractor so I've answered the questions as relating to my current contract. +2014-08-29 06:06:46,25,Male,United Kingdom,,No,No,No,Never,6-25,Yes,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Very easy,No,No,Yes,Yes,No,No,Don't know,No, +2014-08-29 06:37:49,45,Male,United Kingdom,,No,Yes,No,Rarely,100-500,No,No,Don't know,No,No,No,Don't know,Don't know,Maybe,No,Some of them,No,No,Maybe,Don't know,No, +2014-08-29 06:42:57,33,female,United Kingdom,,Yes,No,Yes,Sometimes,1-5,Yes,Yes,No,Yes,Yes,Yes,Yes,Very easy,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-29 07:12:43,43,Male,United States,MI,No,No,No,Sometimes,More than 1000,Yes,Yes,No,Not sure,No,No,Don't know,Very difficult,Yes,Maybe,No,No,No,Maybe,No,Yes, +2014-08-29 07:21:30,30,Male,United Kingdom,,Yes,No,Yes,Sometimes,6-25,No,Yes,No,Yes,No,No,No,Very difficult,Yes,Yes,No,No,No,No,Yes,Yes, +2014-08-29 07:28:17,40,Male,United States,IN,No,Yes,Yes,Rarely,6-25,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Don't know,No,No,Yes,Yes,No,Maybe,Don't know,No, +2014-08-29 07:51:42,49,Male,United States,GA,No,Yes,No,Never,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Don't know,No,No,Yes,Yes,No,No,Yes,No,Thank you for shining a light on this topic. +2014-08-29 08:46:31,38,cis male,United States,WA,No,No,No,Never,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Somewhat easy,Maybe,Maybe,Some of them,Some of them,No,Maybe,No,Yes, +2014-08-29 08:57:14,28,Male,United Kingdom,,No,Yes,Yes,Often,26-100,No,Yes,No,No,No,No,Don't know,Somewhat easy,Maybe,Maybe,Yes,Yes,No,No,No,No, +2014-08-29 08:57:42,40,Male,United States,ME,No,Yes,Yes,Sometimes,1-5,Yes,Yes,No,No,No,No,Don't know,Don't know,Maybe,Maybe,Some of them,Yes,No,Maybe,No,No, +2014-08-29 08:59:08,37,Female,Canada,,Yes,Yes,Yes,Rarely,1-5,Yes,Yes,No,Yes,No,No,Yes,Somewhat easy,Yes,Maybe,Some of them,Some of them,Maybe,Maybe,Don't know,Yes, +2014-08-29 08:59:40,34,female,United Kingdom,,No,Yes,Yes,Often,26-100,Yes,No,Yes,Yes,No,Yes,No,Somewhat easy,Yes,Yes,Some of them,No,No,No,Don't know,No, +2014-08-29 09:01:01,28,male,United States,NY,No,Yes,Yes,Often,100-500,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,Yes,Don't know,No, +2014-08-29 09:01:45,27,Male,Canada,,No,No,No,Never,26-100,No,Yes,Yes,Not sure,Yes,No,Yes,Very easy,No,No,Yes,Yes,Maybe,Maybe,Yes,No, +2014-08-29 09:02:04,29,Male,United Kingdom,,No,No,Yes,Sometimes,6-25,Yes,Yes,No,No,No,No,Don't know,Very easy,No,No,Yes,Yes,No,Yes,Yes,No, +2014-08-29 09:02:56,39,Female,United Kingdom,,No,Yes,No,Rarely,500-1000,Yes,Yes,Don't know,Not sure,No,No,Don't know,Somewhat difficult,Yes,Yes,No,No,No,No,No,Yes, +2014-08-29 09:03:50,28,male,United Kingdom,,No,No,No,Often,6-25,No,Yes,No,No,No,No,No,Somewhat difficult,Yes,No,No,No,No,Yes,Yes,No, +2014-08-29 09:10:08,23,Male,United States,PA,No,Yes,No,Sometimes,26-100,No,Yes,Yes,Not sure,Yes,Yes,Yes,Somewhat easy,No,No,No,No,No,Maybe,Don't know,No, +2014-08-29 09:12:16,38,Male,United Kingdom,,No,No,No,,1-5,Yes,Yes,No,No,No,No,Yes,Somewhat easy,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-29 09:13:43,19,Male,United Kingdom,,No,No,No,,6-25,No,Yes,Yes,No,No,Yes,Don't know,Very easy,No,No,Yes,Yes,No,No,Yes,No, +2014-08-29 09:14:45,30,Female,United States,IL,No,Yes,Yes,Sometimes,26-100,No,Yes,Yes,Yes,Yes,Don't know,Yes,Very easy,No,No,Some of them,No,No,No,Yes,No, +2014-08-29 09:15:05,28,male,United Kingdom,,Yes,No,No,,1-5,Yes,Yes,No,Yes,No,No,Yes,Very easy,Maybe,Maybe,No,No,No,No,Yes,No, +2014-08-29 09:19:25,35,Male,United Kingdom,,Yes,No,No,Sometimes,1-5,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Somewhat easy,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-29 09:24:34,39,male,United States,MN,No,No,Yes,Rarely,100-500,Yes,Yes,Yes,Yes,No,No,Yes,Very easy,Maybe,No,Some of them,Yes,No,No,Don't know,No, +2014-08-29 09:23:22,31,Female,United States,TX,No,Yes,No,Never,More than 1000,No,No,Yes,Not sure,No,Don't know,Don't know,Don't know,Yes,Yes,No,No,No,No,Don't know,No, +2014-08-29 09:23:44,32,Male,United Kingdom,,No,No,No,Rarely,500-1000,No,Yes,No,No,No,No,Don't know,Don't know,Yes,No,No,No,No,No,Don't know,No, +2014-08-29 09:29:37,25,Male,United States,PA,No,Yes,Yes,Often,6-25,Yes,Yes,Yes,Yes,No,Don't know,Yes,Somewhat easy,No,No,Yes,Yes,Maybe,Maybe,Don't know,No, +2014-08-29 09:31:37,42,male,United States,IN,No,Yes,Yes,Sometimes,6-25,Yes,Yes,Don't know,No,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,Yes,No,Maybe,Don't know,No, +2014-08-29 09:31:49,34,male,United States,PA,No,Yes,Yes,Often,100-500,No,Yes,Yes,Yes,No,No,Yes,Very easy,No,No,Yes,Yes,Maybe,Maybe,Don't know,No, +2014-08-29 09:33:43,26,female,United States,OH,No,No,Yes,Sometimes,26-100,Yes,Yes,Don't know,No,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,No,Maybe,Maybe,Don't know,Yes, +2014-08-29 09:35:46,35,Male,United Kingdom,,No,Yes,Yes,Sometimes,1-5,No,Yes,No,Yes,No,No,Yes,Very easy,Yes,Yes,Some of them,Some of them,No,Maybe,Yes,Yes, +2014-08-29 09:36:04,34,Male,United Kingdom,,No,No,No,Never,500-1000,No,Yes,Don't know,No,No,Don't know,Don't know,Very easy,Maybe,No,Yes,Yes,No,No,Yes,No, +2014-08-29 09:36:46,38,m,United States,PA,No,Yes,Yes,Sometimes,100-500,Yes,No,Yes,Yes,No,Yes,Yes,Very easy,No,No,Yes,Yes,Yes,Yes,Don't know,No,While mental health is a part of our insurance program the UCR is 50% of 140% of medicare which means a solo mental health practitioner who will charge in my area $150-$180 a session will only result in a $45-$60 reimbursement and thus a very high out of pocket expense. This usage of a different schedule for UCR and often the lower rate is very hard to determine before purchasing insurance even in the new health insurance exchanges. +2014-08-29 09:40:13,34,M,United States,SD,No,No,No,Sometimes,100-500,No,Yes,Don't know,No,No,No,Don't know,Don't know,Yes,No,Some of them,No,No,Maybe,Don't know,No, +2014-08-29 09:42:23,39,M,United States,IN,No,Yes,Yes,Sometimes,6-25,Yes,Yes,No,Yes,No,No,Yes,Somewhat easy,No,No,Some of them,Yes,Maybe,Yes,Yes,No, +2014-08-29 09:46:56,44,F,United States,CA,No,No,No,,100-500,No,Yes,Don't know,Not sure,No,No,Don't know,Don't know,Yes,No,No,No,No,No,Don't know,No, +2014-08-29 09:47:10,40,male,United States,TN,No,No,No,,More than 1000,No,No,Yes,Yes,Yes,Yes,Yes,Don't know,Maybe,No,No,Yes,No,No,Don't know,No, +2014-08-29 09:47:30,33,female,United States,TX,Yes,No,No,Never,1-5,Yes,Yes,No,Yes,Don't know,Don't know,Yes,Somewhat easy,Maybe,No,No,Some of them,No,No,Yes,No, +2014-08-29 09:51:35,24,Female,United States,TN,No,Yes,No,Sometimes,More than 1000,No,No,Yes,Yes,No,Don't know,Don't know,Somewhat difficult,Yes,Maybe,Some of them,Some of them,No,No,No,Yes, +2014-08-29 09:53:38,38,Female,United States,OR,No,Yes,No,Sometimes,26-100,Yes,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-29 09:53:50,31,male,United States,SD,No,No,No,Sometimes,More than 1000,No,Yes,Yes,Not sure,Yes,Yes,Yes,Don't know,Yes,Maybe,Some of them,Some of them,No,Maybe,Yes,No, +2014-08-29 09:54:11,26,F,United States,NY,No,No,No,,6-25,No,Yes,Don't know,Not sure,No,No,Don't know,Somewhat easy,No,No,Yes,Yes,No,Maybe,Yes,No, +2014-08-29 09:58:55,46,Female (trans),United States,CT,No,No,Yes,Often,More than 1000,No,No,Yes,Yes,Yes,Yes,Don't know,Don't know,Yes,No,Some of them,Some of them,No,No,No,Yes, +2014-08-29 09:59:39,30,Male,United States,CA,No,Yes,Yes,Sometimes,26-100,Yes,Yes,Yes,No,No,No,Don't know,Don't know,Maybe,No,Some of them,No,No,Maybe,Don't know,No, +2014-08-29 10:03:24,25,Male,United States,,No,No,No,Rarely,26-100,Yes,Yes,Don't know,No,No,No,Don't know,Somewhat easy,Yes,No,Some of them,Some of them,No,Yes,Don't know,Yes,My work is using my brain. I do it incredibly well.I make an effort to avoid diagnosis of anything mental health related because I am convinced it would only affect me negatively. +2014-08-29 10:05:57,19,M,Canada,,No,No,No,Never,26-100,Yes,Yes,Don't know,No,No,No,Don't know,Somewhat easy,No,No,Some of them,Some of them,No,Maybe,No,No, +2014-08-29 10:06:29,30,Female,United States,GA,No,Yes,Yes,Sometimes,500-1000,No,No,Yes,Yes,Yes,Yes,Yes,Somewhat easy,Maybe,Maybe,Some of them,Some of them,No,No,No,Yes, +2014-08-29 10:12:10,32,m,United States,TN,No,No,No,Never,6-25,No,Yes,Yes,Yes,Yes,Yes,Don't know,Somewhat easy,No,No,Yes,Yes,No,Maybe,Yes,No, +2014-08-29 10:13:39,32,Male,United Kingdom,,No,No,No,,6-25,No,Yes,No,No,No,No,Don't know,Don't know,Maybe,Maybe,No,No,No,Maybe,Don't know,No, +2014-08-29 10:13:43,37,Male,United States,IN,No,Yes,No,Sometimes,26-100,Yes,Yes,Don't know,No,No,No,Don't know,Somewhat easy,Maybe,No,Some of them,Some of them,No,Maybe,No,No,My employer is extremely easy to work with and e.g. I have enormous leeway with flex time so I could take care of myself under that umbrella but I don't know and don't have a history of bring up mental health at the workplace so I am cautious in that area. +2014-08-29 10:16:45,42,M,United States,CA,No,Yes,Yes,Sometimes,6-25,Yes,Yes,Don't know,No,No,Don't know,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,No,No,Don't know,No, +2014-08-29 10:27:15,25,female,United States,OR,No,No,No,Never,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Don't know,Don't know,Maybe,No,Some of them,Yes,Maybe,No,Yes,No, +2014-08-29 10:30:09,19,Male,United States,IN,No,No,No,Sometimes,1-5,No,Yes,Don't know,Not sure,No,No,Don't know,Don't know,No,No,Some of them,Yes,Maybe,Maybe,Don't know,No, +2014-08-29 10:32:24,40,female,United States,GA,No,Yes,No,Never,100-500,Yes,Yes,Yes,Yes,Yes,No,Don't know,Don't know,Yes,Yes,No,No,No,No,Don't know,No, +2014-08-29 10:33:45,34,Male,United States,IN,No,No,No,,More than 1000,No,No,Yes,Not sure,Yes,Don't know,Don't know,Don't know,Maybe,Maybe,Some of them,Yes,No,No,Don't know,No, +2014-08-29 10:38:23,26,Male,United States,MN,No,Yes,No,,6-25,No,Yes,Don't know,Not sure,No,No,Don't know,Don't know,No,No,Some of them,Yes,No,No,Yes,No, +2014-08-29 10:38:29,31,Male,United States,MN,No,Yes,Yes,Rarely,6-25,No,Yes,Don't know,Not sure,Don't know,Don't know,Yes,Don't know,No,No,Yes,Yes,Maybe,Maybe,Yes,No, +2014-08-29 10:55:24,40,Male,United States,NC,No,Yes,No,Sometimes,More than 1000,Yes,No,Yes,Not sure,Yes,Don't know,Don't know,Don't know,Yes,Maybe,Some of them,Some of them,No,Maybe,No,No, +2014-08-29 10:59:57,31,Female,United States,FL,No,Yes,Yes,Often,26-100,No,Yes,No,No,No,No,No,Very difficult,Yes,No,No,No,No,Yes,No,Yes, +2014-08-29 11:01:41,36,M,United States,MN,No,No,No,Never,100-500,No,No,Don't know,No,No,Don't know,Don't know,Don't know,Yes,Maybe,No,No,No,Maybe,Don't know,Yes, +2014-08-29 11:02:23,35,Male,Canada,,No,Yes,No,Sometimes,6-25,Yes,Yes,No,Yes,No,No,Don't know,Don't know,Maybe,No,No,Some of them,No,No,Don't know,No, +2014-08-29 11:05:00,44,m,United States,MO,No,No,No,,More than 1000,Yes,No,Don't know,No,Don't know,Don't know,Yes,Don't know,Yes,No,Some of them,No,No,No,No,No, +2014-08-29 11:11:00,34,Female,United States,CA,No,No,No,Sometimes,1-5,No,Yes,No,Not sure,No,No,Don't know,Very easy,No,No,Some of them,Yes,No,Maybe,Yes,No, +2014-08-29 11:12:22,35,Male,United States,OR,No,No,No,,6-25,Yes,Yes,No,No,No,No,Don't know,Don't know,No,No,No,No,No,No,Don't know,No, +2014-08-29 11:19:46,28,female,United States,OH,No,Yes,Yes,Sometimes,26-100,Yes,Yes,Don't know,No,No,No,Don't know,Somewhat easy,Yes,No,Some of them,Some of them,No,Maybe,No,No, +2014-08-29 11:20:13,33,Male,United States,NY,No,No,No,,6-25,Yes,Yes,Yes,No,Don't know,Yes,Yes,Don't know,No,No,Some of them,Yes,No,No,Yes,No, +2014-08-29 11:20:28,40,M,United States,WI,No,Yes,Yes,Sometimes,More than 1000,Yes,Yes,Yes,Yes,No,Yes,Don't know,Don't know,Yes,No,No,No,No,Maybe,Don't know,No, +2014-08-29 11:20:52,26,Male,United States,WA,No,No,Yes,Sometimes,6-25,No,Yes,Yes,Yes,No,No,Yes,Don't know,Maybe,No,Some of them,No,No,Maybe,Don't know,No, +2014-08-29 11:22:46,29,f,United Kingdom,,No,No,Yes,Often,More than 1000,No,No,Yes,Yes,No,No,Don't know,Don't know,Maybe,No,Some of them,No,No,Yes,No,Yes, +2014-08-29 11:23:21,26,Female,Canada,,No,Yes,Yes,Sometimes,100-500,No,Yes,Yes,Not sure,No,No,Yes,Don't know,Maybe,No,Some of them,No,No,Maybe,Don't know,No, +2014-08-29 11:27:47,41,Male,United States,IL,Yes,No,Yes,Often,1-5,Yes,No,No,Yes,Yes,Yes,Yes,Very difficult,No,No,Some of them,Some of them,No,No,Yes,Yes, +2014-08-29 11:32:22,39,Male,United Kingdom,,Yes,Yes,Yes,Sometimes,1-5,Yes,Yes,No,Yes,Yes,Yes,Yes,Somewhat difficult,No,No,Yes,Yes,No,Maybe,Yes,Yes,These result may be a tad confusing so a summary follows.* Currently self-employed so employer is me :)* Last place of employment was amazing when I first discovered I was bi-polar and helped me as long as I was there up to and including a mental health course for the whole team (although no mention why to others which was great).* I've never had a negative reaction yet but I know others who have.* I've been very lucky with company I keep which is why my experience is largely good. +2014-08-29 11:32:44,26,female,United States,WA,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,No,No,Don't know,Don't know,No,No,Some of them,Yes,No,Maybe,No,Yes,I should note one of the places my employer fails with regards to mental health is that the company-paid health insurance policy does not cover trans healthcare needs. +2014-08-29 11:33:54,23,Female,United States,IL,No,Yes,No,Sometimes,26-100,No,No,No,No,No,No,Don't know,Somewhat difficult,Yes,No,No,Some of them,No,Maybe,No,No, +2014-08-29 11:36:38,36,Male,United States,FL,No,No,No,Never,1-5,Yes,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Very easy,No,No,Some of them,Some of them,No,No,Don't know,No, +2014-08-29 11:39:33,42,M,United States,TN,No,No,No,Rarely,More than 1000,No,No,Don't know,No,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,No,No,Maybe,No,No, +2014-08-29 11:40:29,39,Male,United States,WA,No,Yes,Yes,Sometimes,500-1000,No,Yes,Yes,Yes,No,Don't know,Yes,Very easy,No,No,Some of them,Yes,No,No,Yes,No, +2014-08-29 11:43:12,27,Male,United States,CA,No,No,No,Never,6-25,No,Yes,Don't know,No,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,Yes,Maybe,Maybe,Don't know,No, +2014-08-29 11:44:33,33,male,United States,FL,Yes,No,No,Never,6-25,Yes,Yes,Don't know,No,No,No,No,Very easy,Maybe,No,Some of them,Yes,No,Maybe,Yes,No, +2014-08-29 11:46:27,31,Male ,Canada,,No,Yes,Yes,Often,More than 1000,No,Yes,Yes,Not sure,Don't know,Don't know,Don't know,Don't know,Maybe,No,Some of them,No,No,Maybe,Don't know,No, +2014-08-29 11:53:59,28,Female,United States,OR,No,No,Yes,Rarely,6-25,No,Yes,Yes,Yes,Don't know,Yes,Yes,Very easy,No,No,Some of them,Some of them,No,Yes,Don't know,No, +2014-08-29 11:54:38,29,Female,United States,NJ,No,No,Yes,Often,More than 1000,Yes,No,Yes,No,No,No,Don't know,Somewhat easy,No,No,Some of them,Yes,Maybe,Maybe,Don't know,No, +2014-08-29 11:56:18,27,Male,United States,CA,No,No,Yes,Sometimes,100-500,No,Yes,Don't know,Not sure,No,No,Yes,Very difficult,Maybe,No,Some of them,No,No,Maybe,No,No, +2014-08-29 12:00:33,44,M,United States,FL,Yes,No,No,Never,1-5,Yes,Yes,Don't know,No,No,No,Yes,Somewhat difficult,No,No,No,No,No,No,Don't know,No, +2014-08-29 12:08:12,25,Male,United States,UT,No,No,Yes,Often,6-25,Yes,Yes,Don't know,No,No,No,Don't know,Somewhat easy,Maybe,No,Some of them,No,No,Maybe,Don't know,No, +2014-08-29 12:26:21,34,M,United States,NJ,No,No,No,Never,6-25,Yes,Yes,Yes,Not sure,Don't know,Don't know,Don't know,Somewhat easy,Maybe,Maybe,No,Some of them,No,Maybe,Don't know,No, +2014-08-29 12:27:54,26,Male,United States,PA,No,No,No,Never,More than 1000,No,No,Yes,Yes,No,Don't know,Don't know,Somewhat difficult,Maybe,No,No,Yes,No,No,Don't know,No, +2014-08-29 12:45:11,48,Male,United States,IN,No,No,No,Never,26-100,No,No,Yes,Yes,Yes,Yes,Yes,Don't know,Maybe,No,Some of them,Yes,No,Maybe,Don't know,No, +2014-08-29 12:54:31,39,Female,United States,OH,No,No,Yes,Sometimes,6-25,Yes,Yes,No,No,No,No,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,No,Maybe,No,No,I've never heard of a workplace that would actually allow you to call off for mental health reasons. So many places require a doctor's note for calling off sick. It's all set up to make you feel worse if you can't just suck it up. Thanks for working to change this!!! +2014-08-29 13:17:33,43,Male,United States,OH,No,No,No,Sometimes,More than 1000,Yes,Yes,Yes,Not sure,No,Yes,Don't know,Don't know,Maybe,No,No,No,No,No,Don't know,No, +2014-08-29 13:23:40,41,M,United States,IL,No,No,No,Rarely,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Don't know,Don't know,Maybe,Maybe,Some of them,No,No,No,Yes,Yes, +2014-08-29 13:58:25,25,Male,United States,IN,No,No,No,Never,More than 1000,No,No,Don't know,No,No,No,Don't know,Don't know,No,No,Some of them,Yes,No,No,Don't know,No, +2014-08-29 14:04:59,31,m,United States,CA,No,No,Yes,Sometimes,100-500,No,Yes,Yes,Yes,No,No,Don't know,Somewhat easy,Maybe,No,Some of them,No,No,Maybe,No,No, +2014-08-29 14:09:21,40,Male,United States,WA,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Don't know,Yes,Yes,No,No,No,Maybe,No,Yes, +2014-08-29 14:31:00,43,Male,United States,VA,Yes,Yes,Yes,Sometimes,1-5,Yes,Yes,Yes,Not sure,No,Don't know,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,No,Maybe,Don't know,No,This survey was tough as a self-employed individual. You may wish to discard responses from self employed people for much of your analysis. +2014-08-29 14:51:49,27,Female,United States,WA,No,Yes,Yes,Often,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Very difficult,Maybe,No,Yes,Some of them,No,Maybe,No,Yes,I answered based on previous job at large technical company where I was pushed out of my role within 3 months of disclosing diagnosis.I had been struggling for 3 months prior to disclosure and was incredibly relieved when finally diagnosed. Growing up in a family open about mental health and also at the end of my rope I immediately shared with management what was going on. I requested a temporary reduced workload so I could reduce anxiety. (At time I didn't know it was anxiety as took me a year to accept that the (to me) deserved stress was anxiety caused by my core diagnosis.) When disclosing I didn't deeply understand details of the state of my mental health; I simply knew I was so stressed out by having been unable to get myself to do work in three months that I couldn't juggle all that was currently on my plate.It was at this point my direct manager and I began an almost daily struggle. After working on a single project and making progress (compared to 3 months before diagnosis when management didn't even know how bad I was doing) I requested increasing my workload. This was never granted; boss said I hadn't proved myself and implied I could not be trusted.Two huge issues stick out to me from that experience:1) Company assumes things would be better and back to 100% within months. They did not understand what one goes through when figuring out meds: things at times got worse. They did not understand how long it takes until meds are figured out: mine took two years. They most certainly would not truly understand why to this day four years later despite being stable I'm in counseling every other week in addition to being on meds. Rather than supporting that it would be seen as oh I'm sorry. I was a problem to my manager because he didn't see improvements each week.2) Accomodations.- There was no option for me to reduce work temporarily to part-time (too complicated). Instead they pushed me to take disability leave. I told them that wouldn't help; they told me to double-check with care providers. That required me to see a psychologist unnecessarily as psychologist said I didn't qualify for leave. (Expensive unnecessary appointment).- The assistance I needed the most at work was understanding: I was open but my manager told me to not tell my co-worker assigned to support me. That was disasterous for colleague's stress/frustration levels. He knew something was up but was barred from asking and I was implied it was better to keep my mouth shut.- Accommodations weren't understood by even Benefits as they're not trained in mental health nor do they have people come in to assess how they're doing in supporting those with mental health issues. Should be no different than people coming in to assess for physical accessibility of the workplace. When in a meeting with my manager supervised by HR I shouldn't feel like I'm asking too much of manager when requesting he put the negative critiques on the back burner and help me figure out whether I'm doing anything right. That this didn't stop him from coming into my office that same day and putting on my dick hat to yell at me for something that wasn't even my fault (he had brought in co-worker for this yelling and turned to finish yelling at this person): FUCKING UNACCEPTABLE.While I will never return to that company and as such took the severance package I will NEVER agree with their legal reason for being unable to do the job: me being medically disqualified from this role. I was too expensive in the short term for them; I'm not worth the cost. +2014-08-29 14:59:43,37,female,United States,NJ,No,Yes,Yes,Sometimes,26-100,Yes,Yes,Yes,Yes,No,Don't know,Don't know,Don't know,Yes,Maybe,No,No,No,Maybe,Don't know,No,If a man in tech is afraid of speaking up about these things it is even worse for women in tech who are already fearful of and fighting against the stigma of incompetence. On the other hand if a female in tech does not commiserate with her male coworkers on mental health problems she will no longer be seen as a team player. It is really a catch-22 for women in STEM. +2014-08-29 15:59:55,25,Male,United States,UT,No,Yes,Yes,Often,1-5,No,Yes,No,Yes,No,No,Yes,Very easy,Maybe,No,Yes,Yes,No,Maybe,No,No, +2014-08-29 16:17:32,30,Female,United States,TN,No,Yes,Yes,Often,More than 1000,No,No,Yes,No,No,No,Don't know,Somewhat difficult,Yes,No,No,No,No,Maybe,No,No,This issue for me is very real at the moment. I have missed several days of work recently because of a bad reaction to a depression/anxiety drug and I hate not being able to discuss it with my boss without worrying that I will be labeled a liability. +2014-08-29 16:21:16,34,female,Canada,,No,Yes,Yes,Often,26-100,No,No,Don't know,No,Yes,Don't know,Don't know,Somewhat easy,No,No,Some of them,Some of them,No,No,Yes,No, +2014-08-29 16:30:50,32,male,United Kingdom,,No,Yes,Yes,Sometimes,1-5,No,No,Yes,Yes,Yes,Yes,Yes,Somewhat easy,Maybe,Maybe,Some of them,Some of them,No,Maybe,No,No, +2014-08-29 16:56:06,38,male,United States,IN,No,Yes,No,Never,More than 1000,No,No,Yes,Not sure,Yes,Yes,Don't know,Don't know,Yes,Maybe,Some of them,No,No,No,No,No, +2014-08-29 17:04:07,32,Male,United States,IN,No,No,Yes,Sometimes,26-100,No,Yes,Yes,Yes,Yes,Don't know,Yes,Don't know,No,No,Some of them,Yes,No,Maybe,Don't know,No, +2014-08-29 17:04:12,28,Female,United States,CA,No,Yes,Yes,Sometimes,100-500,No,Yes,Yes,Yes,Don't know,Don't know,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,No,Yes,No, +2014-08-29 17:26:15,11,male,United States,OH,Yes,No,No,Never,1-5,Yes,Yes,No,Yes,No,No,Yes,Very easy,No,No,Some of them,Some of them,No,Maybe,Yes,No, +2014-08-29 17:32:31,43,male,United States,TX,No,Yes,No,Never,100-500,No,No,Yes,Yes,No,Don't know,Don't know,Somewhat easy,Maybe,No,Some of them,Some of them,No,Maybe,No,No, +2014-08-29 17:35:16,32,Male,United States,TN,No,Yes,Yes,Often,100-500,No,Yes,No,Yes,No,No,Don't know,Very difficult,Yes,No,Yes,Yes,No,Yes,No,No, +2014-08-29 17:54:32,25,M,United States,WA,No,No,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,Yes,Don't know,Yes,Don't know,Yes,No,No,No,No,No,Yes,No, +2014-08-29 18:33:32,37,Male,United States,UT,No,No,Yes,Sometimes,100-500,No,Yes,Yes,No,No,Yes,Yes,Very easy,No,No,No,Yes,No,No,Yes,No, +2014-08-29 18:39:07,36,male,United States,AL,Yes,No,Yes,Sometimes,1-5,No,No,No,Yes,No,No,No,Very difficult,No,No,No,No,No,No,No,Yes, +2014-08-29 19:32:13,24,Male,United States,WI,No,Yes,Yes,Rarely,6-25,Yes,Yes,Don't know,No,No,No,Don't know,Very easy,No,No,Yes,Yes,Maybe,Yes,Yes,No, +2014-08-29 19:34:40,40,male,United States,WA,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Yes,Not sure,Yes,Don't know,Don't know,Somewhat difficult,Maybe,No,Some of them,Some of them,No,Maybe,Don't know,Yes,Really manager dependent. I have had managers who work with my strengths and others who want my to work on my weaknesses which are directly tied to my mental issues. +2014-08-29 20:53:09,29,Male,United States,WI,No,No,No,,More than 1000,No,No,Don't know,Not sure,Yes,Don't know,Yes,Somewhat easy,No,No,Some of them,Yes,No,Maybe,Yes,No,Though it doesn't affect me (male) good job for making the Gender field a text input instead of a drop down of only two options. +2014-08-29 20:53:58,43,Male,United States,NY,No,No,No,Never,500-1000,No,Yes,Don't know,No,No,Don't know,Don't know,Don't know,No,No,Yes,Some of them,No,No,Yes,No, +2014-08-29 21:26:44,29,Male,United States,NY,No,No,No,,6-25,Yes,Yes,Yes,Not sure,No,Yes,Don't know,Don't know,Maybe,No,Some of them,Yes,Maybe,Yes,Don't know,No, +2014-08-29 21:28:14,26,Male,United States,OH,No,Yes,No,Sometimes,100-500,No,Yes,Don't know,Not sure,No,No,Don't know,Don't know,Maybe,No,Some of them,No,No,Maybe,Don't know,No, +2014-08-29 21:40:26,33,Female,Canada,,Yes,Yes,Yes,Often,1-5,Yes,Yes,No,Yes,No,No,No,Very difficult,Yes,Yes,No,No,No,Maybe,No,Yes, +2014-08-29 22:08:51,35,Female,United States,WA,No,Yes,No,Sometimes,6-25,Yes,Yes,Don't know,No,No,No,Don't know,Somewhat easy,No,No,Yes,Some of them,No,No,Yes,No, +2014-08-29 23:51:01,45,M,United States,CA,No,No,No,Never,6-25,Yes,Yes,Yes,No,No,No,Don't know,Don't know,Yes,Maybe,Some of them,No,No,Maybe,Don't know,No, +2014-08-30 00:09:55,25,Male,United States,SC,No,No,Yes,Rarely,6-25,Yes,Yes,No,Yes,No,Don't know,Don't know,Somewhat easy,Maybe,No,No,Some of them,No,Maybe,Don't know,No, +2014-08-30 05:47:08,33,female,United States,CA,No,No,Yes,Often,More than 1000,No,Yes,Yes,Yes,Don't know,Don't know,Don't know,Don't know,Yes,No,No,No,No,Maybe,Don't know,No, +2014-08-30 13:23:57,25,Male,United States,MN,No,Yes,Yes,Sometimes,1-5,Yes,Yes,Don't know,No,Don't know,Don't know,Don't know,Very easy,No,No,Yes,Yes,Maybe,Yes,Don't know,No,I was (wrongly) diagnosed clinically depressed at 12 then bipolar I at 15 and medicated for a decade until decided myself to go drug free. Since then I've never been happier. Insomnia and my insatiablility for learning and programming have always had a symbiotic relationship.It might also bear mentioning that I'm self-employed in addition to my more traditional day job. +2014-08-30 13:48:34,40,m,United States,WA,No,No,No,,More than 1000,No,No,Yes,Not sure,Don't know,Don't know,Don't know,Somewhat easy,Maybe,No,Some of them,Some of them,No,Maybe,Don't know,No, +2014-08-30 13:55:45,24,Male,Canada,,No,No,No,Sometimes,26-100,No,Yes,Yes,Yes,No,No,Yes,Don't know,Maybe,No,No,No,No,Maybe,Don't know,Yes, +2014-08-30 14:00:22,40,Male,United Kingdom,,No,No,Yes,Never,100-500,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Very easy,Maybe,No,Yes,Some of them,No,Maybe,Don't know,No, +2014-08-30 15:57:04,46,Male,United States,PA,No,Yes,Yes,Sometimes,6-25,No,Yes,Don't know,Yes,No,Don't know,Don't know,Don't know,Yes,Maybe,No,Some of them,No,Maybe,Don't know,No, +2014-08-30 16:13:40,38,Male,United States,NY,No,Yes,Yes,Rarely,More than 1000,No,No,Yes,Yes,Yes,Yes,Yes,Somewhat easy,Yes,No,No,Yes,No,Yes,Don't know,No, +2014-08-30 16:38:02,34,Male,United States,VT,No,No,No,Never,1-5,Yes,Yes,No,Yes,No,No,Don't know,Don't know,Yes,Yes,No,No,No,No,Don't know,No,My employer currently does not offer any health insurance I have to get that on my own. However at past positions I have had health insurance but no one ever mentioned mental health issues nor would I wish to discuss those with my co-workers bosses etc for fear of negative reception. +2014-08-30 18:29:00,32,Male,United Kingdom,,Yes,No,Yes,Rarely,1-5,No,Yes,No,Yes,Yes,Yes,Yes,Very easy,No,No,Some of them,Yes,No,Yes,No,Yes, +2014-08-30 19:35:58,44,Male,United Kingdom,,No,No,Yes,Sometimes,More than 1000,No,No,No,No,No,Yes,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,No,No,No, +2014-08-30 19:56:23,33,Female,United Kingdom,,No,No,Yes,Never,100-500,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Very easy,Maybe,No,Some of them,Some of them,No,Maybe,No,No, +2014-08-30 20:12:33,45,female,United States,MI,No,No,Yes,Rarely,26-100,No,No,Don't know,No,Don't know,Don't know,Don't know,Don't know,No,No,Some of them,Some of them,No,Maybe,Don't know,No, +2014-08-30 20:19:37,35,Male,United States,NY,No,No,No,,6-25,No,Yes,Don't know,Not sure,Don't know,Don't know,Yes,Don't know,No,No,No,No,No,No,Yes,No,Mental health at work is not an issue if you leave work problems at work that may be easier for those of us not in a support role. +2014-08-30 20:46:35,20,female,United States,NY,No,No,Yes,Sometimes,26-100,Yes,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,No,No,Some of them,Some of them,Maybe,Maybe,Don't know,No, +2014-08-30 20:55:11,-1,p,United States,AL,Yes,Yes,Yes,Often,1-5,Yes,Yes,Yes,Yes,Yes,Yes,Yes,Very easy,Yes,Yes,Yes,Yes,Yes,Yes,Yes,Yes,password: testered +2014-08-31 09:19:43,28,male,United States,MI,No,No,No,,More than 1000,No,No,Yes,No,No,No,Yes,Somewhat easy,Maybe,No,No,No,No,Yes,No,No, +2014-08-31 15:03:12,42,F,United States,WA,No,Yes,Yes,Sometimes,26-100,No,No,Yes,Yes,No,No,Don't know,Don't know,Yes,No,Some of them,Some of them,No,Yes,No,No, +2014-08-31 15:23:16,32,male,United Kingdom,,No,No,No,,26-100,No,Yes,No,No,No,No,Don't know,Don't know,Maybe,No,No,No,No,No,Don't know,Yes, +2014-08-31 16:48:13,36,F,United States,TN,No,Yes,Yes,Rarely,More than 1000,Yes,Yes,Yes,Yes,No,No,Yes,Somewhat easy,Maybe,Maybe,Some of them,No,No,No,Don't know,No, +2014-09-01 04:28:55,27,Male,United Kingdom,,No,No,Yes,Sometimes,More than 1000,No,No,No,No,No,No,Yes,Somewhat easy,Maybe,No,Yes,Yes,Maybe,Maybe,No,No,suffer from CR-PTSD so all answered based on that +2014-09-01 06:52:31,25,Male,United Kingdom,,No,Yes,Yes,Sometimes,26-100,Yes,Yes,No,No,No,No,Yes,Very easy,No,No,Some of them,Yes,No,Maybe,Yes,No,Since being advised by Occupational Health that the tempo and spontenaity of the office environment was likely to have a negative effect on my mental health (I'm schizoaffective) I've been moved to 100% remote (home) working. The company have furnished a home office for me and I am only required to attend the office once a month to keep in touch +2014-09-01 06:53:28,41,M,United Kingdom,,No,Yes,No,,6-25,No,Yes,No,No,No,No,Don't know,Somewhat difficult,Maybe,Maybe,Some of them,Some of them,Maybe,Maybe,Don't know,No, +2014-09-01 08:23:15,21,Male,United Kingdom,,No,No,Yes,Sometimes,More than 1000,No,No,Don't know,No,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,No,No,No,Don't know,No, +2014-09-01 10:40:32,27,female,United Kingdom,,No,Yes,No,,More than 1000,No,No,No,Yes,No,No,Yes,Don't know,Maybe,No,No,No,No,Yes,Yes,No, +2014-09-01 12:45:24,26,F,United States,NY,No,Yes,No,Sometimes,26-100,Yes,Yes,Don't know,No,No,No,Don't know,Don't know,Maybe,No,No,No,No,No,Don't know,No, +2014-09-01 17:59:14,38,Male,United Kingdom,,No,Yes,Yes,Sometimes,1-5,No,Yes,No,Not sure,Don't know,Don't know,Don't know,Very easy,No,No,Some of them,Yes,Maybe,Yes,Don't know,No, +2014-09-01 21:03:25,39,M,United Kingdom,,No,Yes,Yes,Sometimes,More than 1000,No,No,No,No,No,No,Yes,Very easy,Maybe,Maybe,Some of them,Yes,Maybe,Maybe,Yes,No,Despite the impression that several 'no' responses might give my employer has been very supportive. But then I work in health care. +2014-09-01 21:34:12,35,M,United States,IN,No,Yes,Yes,Often,More than 1000,No,No,Yes,Yes,No,Yes,Don't know,Somewhat easy,Yes,No,No,Some of them,No,Yes,Don't know,No, +2014-09-01 22:58:47,32,male,United States,NC,No,No,No,Rarely,6-25,No,Yes,Yes,Not sure,No,Don't know,Don't know,Don't know,Maybe,No,No,Some of them,No,Maybe,Don't know,No, +2014-09-02 03:13:53,32,Male,United States,CA,No,No,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,Yes,Yes,Yes,Somewhat difficult,Maybe,Maybe,Some of them,Some of them,No,No,Don't know,Yes, +2014-09-02 04:00:58,26,Male,United Kingdom,,No,No,No,Never,6-25,No,Yes,No,No,No,No,Don't know,Don't know,Yes,Maybe,Some of them,No,No,Maybe,Don't know,No, +2014-09-02 08:00:33,38,Male,Canada,,No,Yes,Yes,Rarely,100-500,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Don't know,No,No,Yes,Yes,No,Maybe,No,No, +2014-09-02 08:24:43,34,Female,United Kingdom,,No,Yes,No,Rarely,26-100,No,No,Yes,Yes,Yes,Yes,Yes,Very easy,No,No,Some of them,Yes,Maybe,Maybe,Yes,No, +2014-09-02 09:57:22,39,Male,United States,TN,No,Yes,Yes,Often,26-100,No,No,Don't know,Not sure,No,No,Don't know,Somewhat easy,Yes,No,Some of them,Some of them,No,Maybe,Don't know,No, +2014-09-02 13:18:35,32,male,Canada,,Yes,No,No,Never,6-25,Yes,Yes,Don't know,Not sure,No,No,Don't know,Very easy,No,No,Yes,Yes,Maybe,Maybe,Yes,No, +2014-09-02 20:23:49,31,male,United Kingdom,,No,Yes,Yes,Never,6-25,No,Yes,Don't know,Not sure,No,Don't know,Don't know,Somewhat easy,No,No,Some of them,Some of them,No,No,Don't know,No,When I've had a depression I was lucky to have an awesome manager who was very understanding and found a budget to pay for my therapy sessions. +2014-09-02 20:57:56,30,m,United States,MN,No,Yes,Yes,Rarely,6-25,No,Yes,No,Yes,No,No,Don't know,Don't know,No,No,No,No,No,No,Don't know,No,People have often felt uncomfortable with my story while most of it happened a decade ago. I used to be quite open about it and have since kept it quietly tucked away. While I sometimes have waves of depression I have learned to cope with the affects. +2014-09-03 13:09:52,29,M,United States,NC,No,No,Yes,Sometimes,26-100,No,Yes,Yes,Yes,No,No,Don't know,Don't know,Yes,No,Some of them,Some of them,No,Maybe,Don't know,No, +2014-09-04 06:23:48,31,Male,United Kingdom,,No,No,No,Never,100-500,No,Yes,Yes,No,No,Yes,Don't know,Don't know,Maybe,Yes,Some of them,No,No,No,Yes,No, +2014-09-04 17:38:22,26,Male,United States,TX,No,Yes,Yes,Sometimes,6-25,Yes,Yes,Don't know,No,No,Don't know,Don't know,Somewhat easy,Maybe,No,Some of them,Some of them,Maybe,Maybe,Don't know,No, +2014-09-04 23:42:28,46,Female,United States,CA,No,No,Yes,Often,100-500,Yes,No,Yes,Yes,No,No,Yes,Don't know,Maybe,No,Some of them,Some of them,No,Maybe,No,No, +2014-09-05 14:15:48,32,Male,United States,CA,No,Yes,No,Sometimes,More than 1000,No,Yes,Yes,No,Yes,Don't know,Don't know,Don't know,Maybe,No,Yes,Yes,No,No,Don't know,No, +2014-09-05 14:19:00,29,Male,United States,IL,No,Yes,Yes,Sometimes,26-100,No,No,Yes,Yes,Yes,Yes,Don't know,Don't know,Maybe,No,Some of them,No,No,Maybe,Don't know,No, +2014-09-08 21:30:59,32,Female,United States,PA,No,No,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,No,No,No,No,No, +2014-09-09 13:49:50,29,Male,United States,IL,No,No,No,,More than 1000,No,Yes,Don't know,Not sure,No,No,Don't know,Don't know,Maybe,No,Some of them,Yes,Maybe,Yes,No,No, +2014-09-11 17:00:30,30,Male,United States,IL,No,No,No,,More than 1000,No,No,Yes,No,Yes,Yes,Don't know,Don't know,Yes,Maybe,No,No,No,No,Don't know,No, +2014-09-12 19:18:18,40,F,United States,MN,No,Yes,Yes,Sometimes,26-100,No,Yes,Yes,Yes,No,Yes,Yes,Somewhat easy,No,No,Yes,Yes,No,Maybe,Yes,Yes, +2014-09-13 07:52:27,23,Male,United Kingdom,,No,No,Yes,Sometimes,1-5,No,Yes,No,No,No,No,Don't know,Very difficult,Maybe,No,Yes,Yes,Yes,Yes,No,Yes,I burnt out this year. I worked too much had too much pressure on myself from being the sole developer on a delayed project that seemed to grow in size with each week it was delayed by and worried about money a lot.I became depressed and anxious and had trouble eating sleeping and generally being myself. As my depression worsened I was regularly late for work couldn't perform as well as I should and became irritable with my colleagues.My employers response after a while was to send me private messages complaining about my lateness which only worsened the situation. I was prescribed 3 weeks off work by my doctor which my employer agreed to only to come back after to find I had been on 'statutory pay' which was roughly half of what I was expecting and was not enough to cover my rent bills AND food. This made me worse and sent me into another depression until I eventually admitted defeat gave up working and left the company. It took me months to recover and I'm now left (over 6 months after this all started) recovering from the fallout I created leaving employment with hardly any money to my name.I had previously been told by my employer that I was too young to burn out and (stupidly) trusted them. I did not feel comfortable discussing my problems with my employer because each time I was met with an attitude that I had to get myself together and ultimately given the amount of employees before me who had left the company by being fired after an altercation with the employer left me with no option but to hide it from them so I too wouldn't be fired. +2014-09-14 20:50:05,38,male,United States,NY,No,Yes,No,,6-25,No,Yes,Don't know,No,No,No,Don't know,Somewhat difficult,No,No,Some of them,Yes,No,No,Don't know,Yes, +2014-09-20 13:51:05,26,Female,United States,MI,No,Yes,Yes,Rarely,100-500,No,Yes,Yes,No,No,No,Don't know,Don't know,Maybe,Maybe,No,No,No,Maybe,No,No, +2014-09-23 20:05:05,29,Male,United States,OH,No,No,No,Never,26-100,No,Yes,No,No,No,Don't know,Don't know,Don't know,No,No,Some of them,Yes,No,Yes,No,Yes, +2014-09-26 21:25:14,32,Woman,United States,NY,No,No,Yes,Sometimes,26-100,No,Yes,Yes,Yes,No,No,Yes,Don't know,Maybe,Maybe,Some of them,No,No,No,No,No, +2014-09-30 09:19:01,38,male,United States,CA,No,Yes,Yes,Sometimes,More than 1000,No,No,Yes,Yes,Yes,Yes,Yes,Don't know,Maybe,No,Some of them,No,No,Maybe,No,Yes, +2014-10-02 21:25:16,72,Female,United States,IN,No,Yes,Yes,Never,500-1000,Yes,No,Yes,Not sure,Don't know,Yes,Don't know,Somewhat easy,Maybe,Maybe,Some of them,Yes,No,No,Don't know,Yes, +2014-10-05 21:16:10,35,female,United States,IN,No,Yes,Yes,Sometimes,1-5,Yes,Yes,No,No,No,No,Yes,Don't know,Maybe,Maybe,Some of them,Some of them,No,No,Yes,No, +2014-10-09 11:14:59,28,F,United States,VA,No,No,Yes,Often,6-25,No,Yes,No,Yes,No,No,Don't know,Very difficult,Yes,Maybe,Some of them,Some of them,No,No,Don't know,No, +2014-11-05 10:08:44,27,femail,United States,OK,No,No,No,Never,100-500,No,No,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,No,No,Some of them,Yes,No,No,Yes,No, +2014-11-06 11:24:38,56,female,United States,OR,Yes,No,No,Rarely,1-5,Yes,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,Maybe,Maybe,No,No,No,No,Don't know,No,I'm self-employed on contract with small start-up. Covered through spouse's insurance. +2014-11-16 08:42:35,38,Male,United States,AL,No,Yes,Yes,Sometimes,26-100,Yes,Yes,Yes,No,No,No,Don't know,Don't know,Maybe,No,Some of them,Some of them,No,No,Don't know,No, +2014-12-15 00:43:49,40,Male,United States,AL,No,Yes,Yes,Sometimes,6-25,No,Yes,Yes,Yes,No,No,Yes,Don't know,Maybe,No,Some of them,No,No,No,Yes,No, +2015-01-03 03:38:30,44,M,United States,OH,No,Yes,Yes,Sometimes,100-500,No,Yes,Yes,Yes,No,Yes,Yes,Don't know,Maybe,No,Some of them,Some of them,No,No,Don't know,No,My mental health issues were the direct result of the trauma from childhood abuse. Most (all?) of the Prompt-sponsored/related presentations I've seen have been about congenital mental health issues that are treatable with continued medication. For me medication only provided temporary assistance. I needed years of (continuing) therapy to deal with PTSD and related disorders (depression anxiety suicidal tendencies others). I haven't seen many in our community discussing trauma-related mental health issues but they are just as real and just as debilitating. +2015-02-21 04:16:05,34,Male,Canada,,No,Yes,No,Sometimes,More than 1000,No,Yes,Yes,Not sure,Yes,Yes,Yes,Don't know,Maybe,No,No,No,No,Maybe,Don't know,No, +2015-02-21 04:16:23,37,Male,United Kingdom,,No,No,No,Never,26-100,Yes,Yes,Don't know,No,No,No,Don't know,Somewhat easy,No,No,Some of them,Yes,No,Yes,Don't know,No, +2015-02-21 04:41:28,32,Male,United States,TX,No,No,Yes,Often,26-100,Yes,Yes,Yes,Not sure,No,Don't know,Don't know,Very difficult,Yes,Maybe,Some of them,No,No,No,Don't know,No, +2015-02-21 05:11:37,28,Female,United States,TX,No,No,Yes,Rarely,6-25,No,Yes,Yes,No,No,No,Don't know,Somewhat easy,Yes,Yes,Some of them,No,No,No,No,Yes, +2015-02-21 05:55:13,24,Male,United Kingdom,,No,No,No,,100-500,No,Yes,Don't know,Not sure,No,No,Don't know,Somewhat easy,Maybe,Maybe,Some of them,Yes,No,Maybe,Don't know,No, +2015-02-21 06:19:41,34,Male,United Kingdom,,No,Yes,No,Often,26-100,Yes,No,Don't know,Not sure,No,No,Don't know,Somewhat easy,Maybe,No,Some of them,Yes,Maybe,Yes,Yes,No, +2015-02-21 08:21:36,23,Male,United States,TX,No,No,Yes,Sometimes,1-5,No,Yes,No,Yes,No,No,No,Very easy,Maybe,Maybe,Some of them,Yes,No,No,No,No, +2015-02-21 09:18:20,34,Female,United Kingdom,,No,No,Yes,Sometimes,More than 1000,No,No,No,Yes,No,Yes,Yes,Somewhat difficult,Maybe,Maybe,Some of them,Yes,No,Maybe,No,Yes, +2015-02-21 09:22:23,33,Male,United States,FL,No,No,Yes,Often,26-100,Yes,Yes,Yes,Yes,No,No,Yes,Don't know,Maybe,No,Some of them,No,No,Maybe,Don't know,No, +2015-02-21 09:30:14,27,Male,United Kingdom,,No,No,No,Rarely,More than 1000,Yes,No,Don't know,Not sure,No,Yes,Don't know,Don't know,No,No,Some of them,Yes,No,No,Don't know,No, +2015-02-21 09:48:13,38,Male,United States,TX,No,No,Yes,Sometimes,More than 1000,Yes,Yes,Yes,No,Yes,Yes,Yes,Very easy,No,No,Yes,Yes,No,No,Don't know,No,I openly discuss my mental health struggles. I have found that doing so encourages people who also struggle to seek treatment. I'm willing to risk losing the support of people who don't understand if it helps those who understand all too well. +2015-02-21 10:00:50,46,Male,United States,CA,No,Yes,Yes,Often,26-100,No,Yes,Don't know,No,No,No,Don't know,Don't know,Maybe,No,Some of them,No,No,No,No,No, +2015-02-21 10:45:51,46,male,United States,MD,No,Yes,Yes,Sometimes,100-500,Yes,Yes,Don't know,Not sure,Don't know,Don't know,Don't know,Don't know,No,No,Some of them,Yes,Yes,Yes,Don't know,No,Just starting a new job hence the numerous I don't know selections. +2015-02-21 11:55:46,23,Male ,United Kingdom,,No,No,No,Never,26-100,No,Yes,Don't know,No,No,No,Don't know,Somewhat easy,Maybe,No,Some of them,Some of them,No,Maybe,Yes,Yes,Although my employer does everything they can to accommodate employees with mental health problems when those individuals cannot carry out any work assigned to them (even over the course of months) they appear to have no alternative but to terminate their employment. However I believe this would be the same for a physical health problem. +2015-02-21 18:59:05,25,Male,United States,MN,No,Yes,Yes,Sometimes,26-100,No,Yes,Don't know,Yes,No,No,Don't know,Somewhat easy,Yes,No,Some of them,Some of them,No,Maybe,Don't know,No, +2015-02-24 08:54:35,23,Female,United Kingdom,,No,Yes,Yes,Sometimes,6-25,No,Yes,No,Yes,No,Yes,Yes,Very easy,No,No,Yes,Yes,Maybe,Maybe,Yes,No, +2015-02-24 08:58:08,24,Cis Man,United Kingdom,,Yes,No,Yes,Sometimes,6-25,Yes,Yes,No,No,No,No,Don't know,Don't know,Maybe,Maybe,Some of them,Some of them,No,Maybe,Don't know,Yes, +2015-02-24 09:00:56,25,Male,United Kingdom,,No,Yes,Yes,Sometimes,More than 1000,No,No,Yes,Yes,Yes,Yes,Yes,Very easy,No,No,Yes,Yes,Yes,Yes,Yes,No,I work at a large university with a track record of health and wellbeing support +2015-02-24 09:13:49,23,Male,United Kingdom,,No,No,Yes,Rarely,6-25,No,Yes,No,Yes,No,No,Don't know,Don't know,No,No,Yes,Yes,No,Maybe,Don't know,No, +2015-02-24 09:15:13,24,"ostensibly male, unsure what that really means",United Kingdom,,No,No,Yes,Sometimes,6-25,No,No,Don't know,No,No,Don't know,Don't know,Don't know,Yes,Maybe,No,No,No,Maybe,Don't know,No,i'm in a country with social health care so my options are not dependant on my employer. this makes a few of the early questions less relevant than they would be for a resident of the US. +2015-02-24 09:18:25,23,Male,Canada,,No,No,Yes,Often,26-100,No,Yes,Yes,Yes,Yes,Don't know,Don't know,Don't know,Maybe,No,Yes,Some of them,No,No,Don't know,No, +2015-02-24 10:32:32,60,Male,United States,CA,No,No,Yes,Often,More than 1000,Yes,Yes,Don't know,No,Yes,Don't know,Don't know,Somewhat easy,Maybe,Maybe,Some of them,No,No,Maybe,Don't know,No, +2015-04-02 15:47:43,28,Male,United States,TN,No,Yes,Yes,Often,More than 1000,No,No,Yes,Yes,Yes,Yes,Yes,Somewhat easy,Yes,Maybe,Some of them,Yes,No,No,No,Yes, +2015-05-05 14:22:18,43,f,United States,FL,No,Yes,Yes,Rarely,More than 1000,Yes,Yes,Yes,Yes,No,Yes,Don't know,Don't know,No,No,Some of them,Yes,No,No,Don't know,No, +2015-05-05 15:16:25,32,female,United Kingdom,,No,No,No,,More than 1000,No,No,No,No,No,Don't know,Don't know,Don't know,Maybe,No,Some of them,Yes,No,Yes,No,No, +2015-05-06 16:55:58,32,Male,United States,OR,No,No,No,Never,100-500,No,Yes,Yes,Not sure,Don't know,Yes,Don't know,Somewhat easy,No,No,No,Some of them,Maybe,Yes,Don't know,No, +2015-06-25 12:24:31,41,Female,United States,WA,No,Yes,Yes,Sometimes,26-100,No,Yes,Yes,No,No,Don't know,Don't know,Don't know,Yes,Maybe,No,No,No,No,Don't know,No, +2015-07-22 18:57:54,30,M,United States,CA,No,Yes,Yes,Sometimes,26-100,No,Yes,Yes,Yes,Don't know,No,Yes,Very easy,No,No,Yes,Yes,Maybe,Maybe,Yes,No,Bipolar disorder +2015-07-27 23:25:34,30,Male,United States,CA,Yes,Yes,Yes,Often,26-100,No,Yes,Yes,Not sure,Yes,Yes,Don't know,Don't know,No,No,Some of them,Yes,Maybe,Maybe,Yes,No, +2015-08-20 16:52:09,29,male,United States,NC,No,Yes,Yes,Sometimes,100-500,Yes,Yes,Yes,Yes,Yes,No,Yes,Don't know,Yes,No,Some of them,No,No,Maybe,No,No, +2015-08-25 19:59:38,36,Male,United States,UT,No,Yes,No,Rarely,More than 1000,No,No,Don't know,No,Yes,Yes,Don't know,Somewhat easy,Maybe,Maybe,Some of them,Some of them,No,No,Don't know,No, +2015-09-12 11:17:21,26,male,United Kingdom,,No,No,Yes,,26-100,No,Yes,No,No,No,No,Don't know,Somewhat easy,No,No,Some of them,Some of them,No,No,Don't know,No, +2015-09-26 01:07:35,32,Male,United States,IL,No,Yes,Yes,Often,26-100,Yes,Yes,Yes,Yes,No,No,Yes,Somewhat difficult,No,No,Some of them,Yes,No,No,Yes,No, +2015-11-07 12:36:58,34,male,United States,CA,No,Yes,Yes,Sometimes,More than 1000,No,Yes,Yes,Yes,No,No,Don't know,Somewhat difficult,Yes,Yes,No,No,No,No,No,No, +2015-11-30 21:25:06,46,f,United States,NC,No,No,No,,100-500,Yes,Yes,No,Yes,No,No,Don't know,Don't know,Yes,No,No,No,No,No,No,No, +2016-02-01 23:04:31,25,Male,United States,IL,No,Yes,Yes,Sometimes,26-100,No,No,Yes,Yes,No,No,Yes,Don't know,Maybe,No,Some of them,No,No,No,Don't know,No, diff --git "a/5. Algoritmos de Machine Learning e aplica\303\247\303\265es em larga escala/notebooks/average.png" "b/5. Algoritmos de Machine Learning e aplica\303\247\303\265es em larga escala/notebooks/average.png" new file mode 100644 index 0000000..fffec29 Binary files /dev/null and "b/5. Algoritmos de Machine Learning e aplica\303\247\303\265es em larga escala/notebooks/average.png" differ diff --git "a/5. Algoritmos de Machine Learning e aplica\303\247\303\265es em larga escala/notebooks/bagging.png" "b/5. Algoritmos de Machine Learning e aplica\303\247\303\265es em larga escala/notebooks/bagging.png" new file mode 100644 index 0000000..24e257b Binary files /dev/null and "b/5. Algoritmos de Machine Learning e aplica\303\247\303\265es em larga escala/notebooks/bagging.png" differ diff --git "a/5. Algoritmos de Machine Learning e aplica\303\247\303\265es em larga escala/notebooks/boosting.png" "b/5. Algoritmos de Machine Learning e aplica\303\247\303\265es em larga escala/notebooks/boosting.png" new file mode 100644 index 0000000..85363ee Binary files /dev/null and "b/5. Algoritmos de Machine Learning e aplica\303\247\303\265es em larga escala/notebooks/boosting.png" differ diff --git "a/5. Algoritmos de Machine Learning e aplica\303\247\303\265es em larga escala/notebooks/ensemble-gabarito.ipynb" "b/5. Algoritmos de Machine Learning e aplica\303\247\303\265es em larga escala/notebooks/ensemble-gabarito.ipynb" new file mode 100644 index 0000000..67f2d07 --- /dev/null +++ "b/5. Algoritmos de Machine Learning e aplica\303\247\303\265es em larga escala/notebooks/ensemble-gabarito.ipynb" @@ -0,0 +1,2013 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "# Aula 21 - Ensemble & Random Forest\n", + "\n", + "\n", + "## 1. O que é um ensemble?\n", + "\n", + "![#trabalho em equipe funciona!](https://thumbs.gfycat.com/SlimyTepidAtlanticridleyturtle-size_restricted.gif)\n", + "\n", + "

#teamwork

\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "Junção de vários modelos, geralmente mais fracos, que juntos geram um melhor preditor. Basicamente segue a ideia de que várias \"cabeças\" pensam melhor do que uma." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "### Vamos ver se isso é verdade mesmo!" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [], + "source": [ + "## imports necessarios\n", + "\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "import pandas as pd\n", + "import numpy as np\n", + "from sklearn.preprocessing import LabelEncoder\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.neighbors import KNeighborsClassifier\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "from sklearn.ensemble import RandomForestClassifier\n", + "from sklearn.ensemble import VotingClassifier\n", + "from sklearn.metrics import accuracy_score, precision_score, recall_score\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "\n", + "Criaremos um modelo para predizer pessoas que devem procurar tratamento para saúde mental em empresas de tecnologia.\n", + "\n", + "Vamos ler os dados e analisar o dataset:" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "df = pd.read_csv('survey.csv')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> Dataset retirado do [kaggle](https://www.kaggle.com/osmi/mental-health-in-tech-survey/kernels), porém foram filtrados apenas os países Canada, United Kingdom e United States para facilitar a análise" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 1008 entries, 0 to 1007\n", + "Data columns (total 27 columns):\n", + "Timestamp 1008 non-null object\n", + "Age 1008 non-null int64\n", + "Gender 1008 non-null object\n", + "Country 1008 non-null object\n", + "state 740 non-null object\n", + "self_employed 991 non-null object\n", + "family_history 1008 non-null object\n", + "treatment 1008 non-null object\n", + "work_interfere 811 non-null object\n", + "no_employees 1008 non-null object\n", + "remote_work 1008 non-null object\n", + "tech_company 1008 non-null object\n", + "benefits 1008 non-null object\n", + "care_options 1008 non-null object\n", + "wellness_program 1008 non-null object\n", + "seek_help 1008 non-null object\n", + "anonymity 1008 non-null object\n", + "leave 1008 non-null object\n", + "mental_health_consequence 1008 non-null object\n", + "phys_health_consequence 1008 non-null object\n", + "coworkers 1008 non-null object\n", + "supervisor 1008 non-null object\n", + "mental_health_interview 1008 non-null object\n", + "phys_health_interview 1008 non-null object\n", + "mental_vs_physical 1008 non-null object\n", + "obs_consequence 1008 non-null object\n", + "comments 133 non-null object\n", + "dtypes: int64(1), object(26)\n", + "memory usage: 212.7+ KB\n" + ] + } + ], + "source": [ + "df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "scrolled": true, + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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TimestampAgeGenderCountrystateself_employedfamily_historytreatmentwork_interfereno_employees...leavemental_health_consequencephys_health_consequencecoworkerssupervisormental_health_interviewphys_health_interviewmental_vs_physicalobs_consequencecomments
02014-08-27 11:29:3137FemaleUnited StatesILNaNNoYesOften6-25...Somewhat easyNoNoSome of themYesNoMaybeYesNoNaN
12014-08-27 11:29:3744MUnited StatesINNaNNoNoRarelyMore than 1000...Don't knowMaybeNoNoNoNoNoDon't knowNoNaN
22014-08-27 11:29:4432MaleCanadaNaNNaNNoNoRarely6-25...Somewhat difficultNoNoYesYesYesYesNoNoNaN
32014-08-27 11:29:4631MaleUnited KingdomNaNNaNYesYesOften26-100...Somewhat difficultYesYesSome of themNoMaybeMaybeNoYesNaN
42014-08-27 11:30:2231MaleUnited StatesTXNaNNoNoNever100-500...Don't knowNoNoSome of themYesYesYesDon't knowNoNaN
\n", + "

5 rows × 27 columns

\n", + "
" + ], + "text/plain": [ + " Timestamp Age Gender Country state self_employed \\\n", + "0 2014-08-27 11:29:31 37 Female United States IL NaN \n", + "1 2014-08-27 11:29:37 44 M United States IN NaN \n", + "2 2014-08-27 11:29:44 32 Male Canada NaN NaN \n", + "3 2014-08-27 11:29:46 31 Male United Kingdom NaN NaN \n", + "4 2014-08-27 11:30:22 31 Male United States TX NaN \n", + "\n", + " family_history treatment work_interfere no_employees ... \\\n", + "0 No Yes Often 6-25 ... \n", + "1 No No Rarely More than 1000 ... \n", + "2 No No Rarely 6-25 ... \n", + "3 Yes Yes Often 26-100 ... \n", + "4 No No Never 100-500 ... \n", + "\n", + " leave mental_health_consequence phys_health_consequence \\\n", + "0 Somewhat easy No No \n", + "1 Don't know Maybe No \n", + "2 Somewhat difficult No No \n", + "3 Somewhat difficult Yes Yes \n", + "4 Don't know No No \n", + "\n", + " coworkers supervisor mental_health_interview phys_health_interview \\\n", + "0 Some of them Yes No Maybe \n", + "1 No No No No \n", + "2 Yes Yes Yes Yes \n", + "3 Some of them No Maybe Maybe \n", + "4 Some of them Yes Yes Yes \n", + "\n", + " mental_vs_physical obs_consequence comments \n", + "0 Yes No NaN \n", + "1 Don't know No NaN \n", + "2 No No NaN \n", + "3 No Yes NaN \n", + "4 Don't know No NaN \n", + "\n", + "[5 rows x 27 columns]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "Vemos várias variáveis como objetos e vários *NaN*s, vamos tratá-los.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [], + "source": [ + "# Timestamp:\n", + "del df['Timestamp']" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "### Variáveis com NaN:\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "12 I'm not on my company's health insurance which...\n", + "14 I have chronic low-level neurological issues t...\n", + "15 My company does provide healthcare but not to ...\n", + "22 Relatively new job. Ask again later\n", + "23 Sometimes I think about using drugs for my me...\n", + "Name: comments, dtype: object" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# comments:\n", + "df.loc[df['comments'].notnull(), 'comments'].head()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "Nao aprendemos NLP... ainda" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [], + "source": [ + "del df['comments']" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "work_interfere:" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Sometimes 389\n", + "Never 173\n", + "Rarely 139\n", + "Often 110\n", + "Name: work_interfere, dtype: int64" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['work_interfere'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "df['work_interfere'].fillna('DontKnow', inplace=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "self_employed:" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "No 896\n", + "Yes 95\n", + "Name: self_employed, dtype: int64" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['self_employed'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "scrolled": false, + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "df['self_employed'].fillna('No', inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "CA 138\n", + "WA 70\n", + "NY 56\n", + "TN 45\n", + "TX 44\n", + "OH 30\n", + "OR 29\n", + "PA 29\n", + "IL 28\n", + "IN 27\n", + "MI 22\n", + "MN 21\n", + "MA 20\n", + "FL 15\n", + "NC 14\n", + "VA 14\n", + "MO 12\n", + "WI 12\n", + "GA 12\n", + "UT 10\n", + "CO 9\n", + "AL 8\n", + "MD 7\n", + "AZ 7\n", + "OK 6\n", + "NJ 6\n", + "SC 5\n", + "KY 5\n", + "IA 4\n", + "DC 4\n", + "CT 4\n", + "SD 3\n", + "KS 3\n", + "VT 3\n", + "NV 3\n", + "NH 3\n", + "NM 2\n", + "NE 2\n", + "WY 2\n", + "WV 1\n", + "MS 1\n", + "RI 1\n", + "ME 1\n", + "LA 1\n", + "ID 1\n", + "Name: state, dtype: int64" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['state'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "del df['state']" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "### Variaveis categoricas" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "Gender:" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "scrolled": false, + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['Female', 'M', 'Male', 'female', 'male', 'm', 'Male-ish', 'maile',\n", + " 'Trans-female', 'Cis Female', 'F', 'Cis Male', 'Woman', 'f',\n", + " 'Male (CIS)', 'queer/she/they', 'non-binary', 'Femake', 'woman',\n", + " 'Make', 'Nah', 'Enby', 'Genderqueer', 'Female ', 'Androgyne',\n", + " 'Agender', 'cis-female/femme', 'Guy (-ish) ^_^',\n", + " 'male leaning androgynous', 'Male ', 'Man', 'Trans woman', 'msle',\n", + " 'Neuter', 'Female (trans)', 'Female (cis)', 'Mail', 'cis male',\n", + " 'p', 'femail', 'Cis Man',\n", + " 'ostensibly male, unsure what that really means'], dtype=object)" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['Gender'].unique()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "Vemos muitas categorias aqui, vamos tratar:" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "male_str = [\"male\", \"m\", \"male-ish\", \"maile\", \"mal\", \"male (cis)\", \"make\", \"male \", \"man\",\"msle\", \"mail\", \"malr\",\"cis man\", \"Cis Male\", \"cis male\"]\n", + "trans_str = [\"trans-female\", \"something kinda male?\", \"queer/she/they\", \"non-binary\",\"nah\", \"all\", \"enby\", \"fluid\", \"genderqueer\", \"androgyne\", \"agender\", \"male leaning androgynous\", \"guy (-ish) ^_^\", \"trans woman\", \"neuter\", \"female (trans)\", \"queer\", \"ostensibly male, unsure what that really means\"] \n", + "female_str = [\"cis female\", \"f\", \"female\", \"woman\", \"femake\", \"female \",\"cis-female/femme\", \"female (cis)\", \"femail\"]\n", + "\n", + "for (row, col) in df.iterrows():\n", + "\n", + " if str.lower(col.Gender) in male_str:\n", + " df['Gender'].replace(to_replace=col.Gender, value='male', inplace=True)\n", + "\n", + " if str.lower(col.Gender) in female_str:\n", + " df['Gender'].replace(to_replace=col.Gender, value='female', inplace=True)\n", + "\n", + " if str.lower(col.Gender) in trans_str:\n", + " df['Gender'].replace(to_replace=col.Gender, value='trans', inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "male 772\n", + "female 220\n", + "trans 15\n", + "p 1\n", + "Name: Gender, dtype: int64" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['Gender'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "df = df[df['Gender']!='p']" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['female', 'male', 'trans'], dtype=object)" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['Gender'].unique()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "Vamos ver quantos países temos:" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "scrolled": false, + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df['Country'].value_counts().plot(kind='barh', figsize=(10,7),\n", + " color=\"coral\", fontsize=13)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "Vamos criar as dummies" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "df = pd.get_dummies(df, columns=['Gender', 'Country', 'self_employed', 'family_history', 'treatment', 'work_interfere',\n", + " 'no_employees', 'remote_work', 'tech_company', 'anonymity', 'leave', 'mental_health_consequence',\n", + " 'phys_health_consequence', 'coworkers', 'supervisor', 'mental_health_interview', 'phys_health_interview',\n", + " 'mental_vs_physical', 'obs_consequence', 'benefits', 'care_options', 'wellness_program',\n", + " 'seek_help'])" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(1007, 71)" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "scrolled": false, + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['Age', 'Gender_female', 'Gender_male', 'Gender_trans',\n", + " 'Country_Canada', 'Country_United Kingdom',\n", + " 'Country_United States', 'self_employed_No', 'self_employed_Yes',\n", + " 'family_history_No', 'family_history_Yes', 'treatment_No',\n", + " 'treatment_Yes', 'work_interfere_DontKnow', 'work_interfere_Never',\n", + " 'work_interfere_Often', 'work_interfere_Rarely',\n", + " 'work_interfere_Sometimes', 'no_employees_1-5',\n", + " 'no_employees_100-500', 'no_employees_26-100',\n", + " 'no_employees_500-1000', 'no_employees_6-25',\n", + " 'no_employees_More than 1000', 'remote_work_No', 'remote_work_Yes',\n", + " 'tech_company_No', 'tech_company_Yes', \"anonymity_Don't know\",\n", + " 'anonymity_No', 'anonymity_Yes', \"leave_Don't know\",\n", + " 'leave_Somewhat difficult', 'leave_Somewhat easy',\n", + " 'leave_Very difficult', 'leave_Very easy',\n", + " 'mental_health_consequence_Maybe', 'mental_health_consequence_No',\n", + " 'mental_health_consequence_Yes', 'phys_health_consequence_Maybe',\n", + " 'phys_health_consequence_No', 'phys_health_consequence_Yes',\n", + " 'coworkers_No', 'coworkers_Some of them', 'coworkers_Yes',\n", + " 'supervisor_No', 'supervisor_Some of them', 'supervisor_Yes',\n", + " 'mental_health_interview_Maybe', 'mental_health_interview_No',\n", + " 'mental_health_interview_Yes', 'phys_health_interview_Maybe',\n", + " 'phys_health_interview_No', 'phys_health_interview_Yes',\n", + " \"mental_vs_physical_Don't know\", 'mental_vs_physical_No',\n", + " 'mental_vs_physical_Yes', 'obs_consequence_No',\n", + " 'obs_consequence_Yes', \"benefits_Don't know\", 'benefits_No',\n", + " 'benefits_Yes', 'care_options_No', 'care_options_Not sure',\n", + " 'care_options_Yes', \"wellness_program_Don't know\",\n", + " 'wellness_program_No', 'wellness_program_Yes',\n", + " \"seek_help_Don't know\", 'seek_help_No', 'seek_help_Yes'],\n", + " dtype=object)" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.columns.values" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "df.drop(columns=['family_history_No', 'treatment_No', 'remote_work_No', 'tech_company_No'], inplace=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "Vamos dar uma olhada na distribuićão da variável resposta:" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df['treatment_Yes'].value_counts().plot(kind='bar')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## Finalmente, vamos ao treinamento!\n", + "\n", + "Vamos separar os dados em treino e teste:" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(855, 66)\n" + ] + } + ], + "source": [ + "X = df.drop('treatment_Yes', axis=1)\n", + "y = df['treatment_Yes']\n", + "\n", + "X_train, X_test, y_train, y_test = train_test_split(X , y, test_size = 0.15, random_state=0)\n", + "print(X_train.shape)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + " Vamos usar os dois métodos mais dummies que aprendemos até agora para tentar predizer " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "## Relembrando Árvores de Decisão:\n", + "\n", + "\"drawing\"\n", + "

Exemplo de árvore de decisão para classificar sobreviventes do Titanic

" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "DecisionTreeClassifier(class_weight=None, criterion='gini', max_depth=None,\n", + " max_features=None, max_leaf_nodes=None,\n", + " min_impurity_decrease=0.0, min_impurity_split=None,\n", + " min_samples_leaf=1, min_samples_split=2,\n", + " min_weight_fraction_leaf=0.0, presort=False, random_state=10,\n", + " splitter='best')" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# crie o modelo com random state igual a 10\n", + "model_tree = DecisionTreeClassifier(random_state=10)\n", + "model_tree.fit(X_train, y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Acurácia: 1.00\n", + "Precisão: 1.00\n", + "Sensibilidade: 1.00\n" + ] + } + ], + "source": [ + "y_pred_tree_train = model_tree.predict_proba(X_train)\n", + "print(\"Acurácia: {:.2f}\".format(accuracy_score(y_train, y_pred_tree_train[:,1]>0.5)))\n", + "print(\"Precisão: {:.2f}\".format(precision_score(y_train, y_pred_tree_train[:,1]>0.5)))\n", + "print(\"Sensibilidade: {:.2f}\".format(recall_score(y_train, y_pred_tree_train[:,1]>0.5)))" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "scrolled": true, + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Acurácia: 0.81\n", + "Precisão: 0.85\n", + "Sensibilidade: 0.80\n" + ] + } + ], + "source": [ + "y_pred_tree = model_tree.predict_proba(X_test)\n", + "print(\"Acurácia: {:.2f}\".format(accuracy_score(y_test, y_pred_tree[:,1]>0.5)))\n", + "print(\"Precisão: {:.2f}\".format(precision_score(y_test, y_pred_tree[:,1]>0.5)))\n", + "print(\"Sensibilidade: {:.2f}\".format(recall_score(y_test, y_pred_tree[:,1]>0.5)))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## KNN " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "![#knn!](https://importq.files.wordpress.com/2017/11/knn_neigh.gif?w=656)\n", + "\n", + " - algoritmo de abordagem \"preguiçosa\"\n", + " - assume que elementos similares estão em proximidade\n", + " - Calcula a distância para os *N* vizinhos mais próximos e determina a classe de acordo com a classe dos vizinhos\n", + " \n", + "Mais informações: https://www.analyticsvidhya.com/blog/2018/03/introduction-k-neighbours-algorithm-clustering/" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "scrolled": true, + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\n", + " metric_params=None, n_jobs=None, n_neighbors=5, p=2,\n", + " weights='uniform')" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# crie o modelo com random state igual a 10\n", + "model_knn = KNeighborsClassifier()\n", + "model_knn.fit(X_train,y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Acurácia: 0.78\n", + "Precisão: 0.81\n", + "Sensibilidade: 0.76\n" + ] + } + ], + "source": [ + "y_pred_knn_train = model_knn.predict_proba(X_train)\n", + "print(\"Acurácia: {:.2f}\".format(accuracy_score(y_train, y_pred_knn_train[:,1]>0.5)))\n", + "print(\"Precisão: {:.2f}\".format(precision_score(y_train, y_pred_knn_train[:,1]>0.5)))\n", + "print(\"Sensibilidade: {:.2f}\".format(recall_score(y_train, y_pred_knn_train[:,1]>0.5)))" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Acurácia: 0.69\n", + "Precisão: 0.71\n", + "Sensibilidade: 0.72\n" + ] + } + ], + "source": [ + "y_pred_knn = model_knn.predict_proba(X_test)\n", + "print(\"Acurácia: {:.2f}\".format(accuracy_score(y_test, y_pred_knn[:,1]>0.5)))\n", + "print(\"Precisão: {:.2f}\".format(precision_score(y_test, y_pred_knn[:,1]>0.5)))\n", + "print(\"Sensibilidade: {:.2f}\".format(recall_score(y_test, y_pred_knn[:,1]>0.5)))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "### Como acham que podemos combinar esses modelos?\n", + "- Fazendo votação das predições\n", + "- Fazendo média das predições\n", + "- Usando as predições como entrada para uma segunda camada de modelos" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "VotingClassifier(estimators=[('tree', DecisionTreeClassifier(class_weight=None, criterion='gini', max_depth=None,\n", + " max_features=None, max_leaf_nodes=None,\n", + " min_impurity_decrease=0.0, min_impurity_split=None,\n", + " min_samples_leaf=1, min_samples_split=2,\n", + " min_weight_fraction_le...ki',\n", + " metric_params=None, n_jobs=None, n_neighbors=5, p=2,\n", + " weights='uniform'))],\n", + " flatten_transform=None, n_jobs=None, voting='soft', weights=None)" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model_vot = VotingClassifier(estimators=[('tree', model_tree), ('knn', model_knn)], voting='soft')\n", + "model_vot.fit(X_train, y_train) " + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Acurácia: 0.82\n", + "Precisão: 0.87\n", + "Sensibilidade: 0.80\n" + ] + } + ], + "source": [ + "y_pred = model_vot.predict(X_test)\n", + "print(\"Acurácia: {:.2f}\".format(accuracy_score(y_test, y_pred)))\n", + "print(\"Precisão: {:.2f}\".format(precision_score(y_test, y_pred)))\n", + "print(\"Sensibilidade: {:.2f}\".format(recall_score(y_test, y_pred)))" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [], + "source": [ + "x_novo = np.array([y_pred_tree_train[:,1], y_pred_knn_train[:,1]])\n", + "x_novo = x_novo.transpose()\n", + "\n", + "x_novo_test = np.array([y_pred_tree[:,1], y_pred_knn[:,1]])\n", + "x_novo_test = x_novo_test.transpose()" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n", + " intercept_scaling=1, max_iter=100, multi_class='warn',\n", + " n_jobs=None, penalty='l2', random_state=None, solver='warn',\n", + " tol=0.0001, verbose=0, warm_start=False)" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model_lr2 = LogisticRegression()\n", + "model_lr2.fit(x_novo, y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Acurácia: 0.81\n", + "Precisão: 0.85\n", + "Sensibilidade: 0.80\n" + ] + } + ], + "source": [ + "y_pred_lr = model_lr2.predict_proba(x_novo_test)\n", + "print(\"Acurácia: {:.2f}\".format(accuracy_score(y_test, y_pred_lr[:,1]>0.5)))\n", + "print(\"Precisão: {:.2f}\".format(precision_score(y_test, y_pred_lr[:,1]>0.5)))\n", + "print(\"Sensibilidade: {:.2f}\".format(recall_score(y_test, y_pred_lr[:,1]>0.5)))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## 2. Tipos de Ensemble:\n", + "\n", + "Existem vários formas diferentes de combinar os modelos. As principais são:\n", + "\n", + "\n", + "### **1. Voting Based Classifier:**\n", + "\n", + "**1. a) Majority Vote**\n", + "\n", + "A ideia é fazer uma votação entre as predições dos modelos. A classe que tiver mais votos vence. Também podemos ter uma variação desse algoritmo, o **Weighted Voting Classifier**, em que na votação alguns modelos tem mais peso que outros.\n", + "\n", + "![](voting.png)\n", + "\n", + "\n", + "**1. b) Average Classifier:**\n", + "\n", + "A ideia é similar ao anterior, porém ao invés de uma votação é calculada a média das predições. Da mesma forma podemos ter alguns modelos com mais peso que outros tendo um **Weighted Average Classifier**\n", + "![](average.png)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "### 2. Stacking:\n", + "\n", + "Nesse modelo as predições dos modelos anteriores são combinadas por um outro modelo para obter a saída final. Podem ser criadas várias camadas com modelos diferentes.\n", + "\n", + "![](stacking.png)\n", + "\n", + "### 3. Boosting:\n", + "\n", + "Os modelos são treinados com os mesmos datasets, porém os pesos das intâncias são ajustados de acordo com o erro das predições anteriores. Veram mais na próxima aula...\n", + "\n", + "![](boosting.png)\n", + "\n", + "## 4. BAGGING: \n", + "Todos os modelos deste tipo de ensemble são do **mesmo algoritmo**, porém os dados de entrada de cada um são amostras do dado original, com a **mesma quantidade de dados do dataset original**, selecionadas usando o método bootstrap (**aleatória com repetição**). \n", + "\n", + "**AQUI TEMOS A RANDOM FOREST**\n", + "\n", + "![](bagging.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## 4. RANDOM FOREST" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "### Como Funciona?\n", + "\n", + "![#OOB!](https://cdn-images-1.medium.com/max/1600/1*yoW30XVqAnKOA-7AArXqNg.gif)\n", + "\n", + "- Algoritmo de bagging que usa árvores de decisão\n", + "- Cada árvore terá um conjunto diferente de dados e de features\n", + "- Out-of-bag score: os dados que não foram usados naquela árvore são utilizados como teste" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": { + "scrolled": true, + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',\n", + " max_depth=None, max_features='auto', max_leaf_nodes=None,\n", + " min_impurity_decrease=0.0, min_impurity_split=None,\n", + " min_samples_leaf=1, min_samples_split=2,\n", + " min_weight_fraction_leaf=0.0, n_estimators=10, n_jobs=None,\n", + " oob_score=True, random_state=0, verbose=0, warm_start=False)" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model = RandomForestClassifier(n_estimators=10, random_state=0, oob_score=True)\n", + "model.fit(X_train, y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "0.7543859649122807" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.oob_score_" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Acurácia: 0.86\n", + "Precisão: 0.85\n", + "Sensibilidade: 0.89\n" + ] + } + ], + "source": [ + "y_pred = model.predict(X_test)\n", + "print(\"Acurácia: {:.2f}\".format(accuracy_score(y_test, y_pred)))\n", + "print(\"Precisão: {:.2f}\".format(precision_score(y_test, y_pred)))\n", + "print(\"Sensibilidade: {:.2f}\".format(recall_score(y_test, y_pred)))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "scrolled": true, + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "Vamos testar outras combinações de parâmetros?\n", + "\n", + "`Dica 1: Manter o mesmo random_state para comparação de resultados\n", + " Dica 2: Os parâmetros são similares as árvores de decisão\n", + " Dica 3: Número de estimadores e de features são os mais relevantes ` " + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "OOB Score: 0.80\n", + "Acurácia: 0.88\n", + "Precisão: 0.87\n", + "Sensibilidade: 0.93\n" + ] + } + ], + "source": [ + "model = RandomForestClassifier(n_estimators=20, random_state=0, oob_score=True)\n", + "model.fit(X_train, y_train)\n", + "y_pred = model.predict(X_test)\n", + "print(\"OOB Score: {:.2f}\".format(model.oob_score_))\n", + "print(\"Acurácia: {:.2f}\".format(accuracy_score(y_test, y_pred)))\n", + "print(\"Precisão: {:.2f}\".format(precision_score(y_test, y_pred)))\n", + "print(\"Sensibilidade: {:.2f}\".format(recall_score(y_test, y_pred)))" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "OOB Score: 0.82\n", + "Acurácia: 0.89\n", + "Precisão: 0.88\n", + "Sensibilidade: 0.93\n" + ] + } + ], + "source": [ + "model = RandomForestClassifier(n_estimators=40, random_state=0, oob_score=True)\n", + "model.fit(X_train, y_train)\n", + "y_pred = model.predict(X_test)\n", + "print(\"OOB Score: {:.2f}\".format(model.oob_score_))\n", + "print(\"Acurácia: {:.2f}\".format(accuracy_score(y_test, y_pred)))\n", + "print(\"Precisão: {:.2f}\".format(precision_score(y_test, y_pred)))\n", + "print(\"Sensibilidade: {:.2f}\".format(recall_score(y_test, y_pred)))" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "OOB Score: 0.82\n", + "Acurácia: 0.89\n", + "Precisão: 0.88\n", + "Sensibilidade: 0.94\n" + ] + } + ], + "source": [ + "model = RandomForestClassifier(n_estimators=50, random_state=0, oob_score=True)\n", + "model.fit(X_train, y_train)\n", + "y_pred = model.predict(X_test)\n", + "print(\"OOB Score: {:.2f}\".format(model.oob_score_))\n", + "print(\"Acurácia: {:.2f}\".format(accuracy_score(y_test, y_pred)))\n", + "print(\"Precisão: {:.2f}\".format(precision_score(y_test, y_pred)))\n", + "print(\"Sensibilidade: {:.2f}\".format(recall_score(y_test, y_pred)))" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "OOB Score: 0.81\n", + "Acurácia: 0.91\n", + "Precisão: 0.90\n", + "Sensibilidade: 0.95\n" + ] + } + ], + "source": [ + "model = RandomForestClassifier(n_estimators=50, random_state=0, oob_score=True, max_features=7)\n", + "model.fit(X_train, y_train)\n", + "y_pred = model.predict(X_test)\n", + "print(\"OOB Score: {:.2f}\".format(model.oob_score_))\n", + "print(\"Acurácia: {:.2f}\".format(accuracy_score(y_test, y_pred)))\n", + "print(\"Precisão: {:.2f}\".format(precision_score(y_test, y_pred)))\n", + "print(\"Sensibilidade: {:.2f}\".format(recall_score(y_test, y_pred)))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "Feature importance:" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": { + "scrolled": false, + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "importances = model.feature_importances_\n", + "std = np.std([tree.feature_importances_ for tree in model.estimators_],\n", + " axis=0)\n", + "indices = np.argsort(importances)[::1]\n", + "\n", + "\n", + "# Plot the feature importances of the forest\n", + "plt.figure(figsize=(15,15))\n", + "plt.title(\"Feature importances\")\n", + "plt.barh(range(X.shape[1]), importances[indices],\n", + " color=\"r\", yerr=std[indices], align=\"center\")\n", + "plt.yticks(range(X.shape[1]), X.columns[indices])\n", + "plt.ylim([-1, X.shape[1]])\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [ + { + "data": { + "image/png": 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SJVeqJKl/3XSw69g5iUTi4GDfrkXTCcOfnTbuudo1vakTAAAAAABzePnllz/55JOsrKzHly7GK24kq7o38rB8Vag+/Ou5b3yxTZqyaOft7MNROTHZ2opf27SWS+9mXiPa1erTzMt8FZrI0cFuxtP1pnavezAyZ/ONzLA0tU5vqMiFni7SIW1qTO1Wt2vD8v8bkTk7HHg1YNHJpO2hWRWMX0EB9d2/Hdns86FNjkTn7ovIvp2mVhWWfTZbgJPU3r+eW++mXpM612lay0XE8myuTgD/ZrdSVRfjFWUu1a5d+6WXXrJkMXYGg5g/Lf7m7+9/586dx1+fPW/hW/M+NUdGAKjmNGrV+l9X7tywVp6XU+Ugrf07zHjr/RHjX7Czs6tyEP86zgKr0VllDDSsguTE+B0b1uzfsVmlLPtnXmW179J96utzho+bJEq0MpUUF585dnDX5t+vX7pY/m5BUkfHwSPGvDRzdueneolS2z/ZSp2wvEFdWjxMTTG2uvXIedG/0LeuXX551ABjq/X8Gpy9HS9uRgCozn5d/tWq5V8//nq7du2io6MtXw9MsWvXrkmTyv7Nc+UVcX6/BYAKKipQn9/20+V9fwg8VbFcvi0Dnn3pnS5DJpjST3i/p9DJdbG+PeakJlzeu+76kW1atdEbGCqlUbuufV94s8vgQFGiPa60pDjy4pGQAxviQoNNDOUgdWzff1SfCa837dBDlNr+hw2VCgv7akyAPDPV2Oqc306I/oVODL/686xhxla96/p9doDfnwGY3aZPpoefO/D46xMmTNi1a5fl60FlTZw4cffu3Y+/3qrv6JGfrLd8PQAAwNYVa9U3d/8cfmSDVln1LlztZgHdJrzd9tlAiQlduJVDawmsvn+y6uX9kyI9MfzwH1GntheJ1IWr17pLl7Gz2jxrxuHapbriuMtHI45uTAm/ZGIoe6ljy2dGdh79mq//06LU9k+2Uies4veXO6qyjDbiXlh5TPSvdVrU1Z3/GWFs1aO232tbI8TNCAAAnmDG3q3s3Llz4sSJFi4GJjJ201+bwA/aTPjA8vUAAIB/CZ1WHXt4VeKpjcWqvCoH8Wrs3+L52Q2fGWdKK/7ApHoCq2N2ZlQ58j9pMhITTm1MvvBniUacVnyNFp2bD3+9wTNjRYn2OL2u5OH1Y4lnNudEXzYxlL2DY/2nhzcb9mqt1k+JUtv/sKFSYWEn3+qqzUkzttrny0Oif6Fz710L/ny0sVXXWr5DV90SNyMAAPiXU6XcP/tBvzKXoqKi/P39LVwPTGTsZs9tq78LHGX0xisAAFCdqdSalWvWr928MydPXuUgHdq1fv/NGS+MGWHKaAjnBkK/HBalinMfd3xS8ppNOzbv3K/IV4kSsHun9nNmTp00Zrgo0cpUXFJy8PiZ37fuuhhy3cRQjlLpmOGDZ7/yUq/unUWp7Z9spU5UB7Vad1drCsSNKdZ3CQAAUD29OOv9vUdOPv4641ZshbFxKx0GjHn5640WLwcAUF0UFagvbPvpyn7T5ta2COj30judTZtbO6+X0Nza5SGiza29sm/dDfHm1jZs17XPpDc7m3NubdTFI1cObIi/JcIw2ID+o3oHvt7EbHNrbaVUWNg3YwMUxufWvrXmhOhf6MTwq6veFJpb+8l+OpkA8O8Sfnb/1k9fKXPJTM/hhflER0cHBASUufTSmks1G7excD0AYDHFWvWtPb9EHdmgza96D8enmX+XwDmt+4835Vbrn5/zEVidc7zqj1r+J2V6YsSR9XdPbS8S6Vbruq27dBozq1X/caJEK1Oprjgh5GjUsU2pYkwTbd5rZMfRM+u3M8vUU5uoE1axcVongamngd8dFf1rnR59de8HI42tymr7vbI5XNyMAGB117Yuu75t2eOv88xiW/HFF18sWrTo8dcbtmiz6mio5esBAAB4Mmg16n3rvj+24/d8edX7n03btB83c26/kRNNOcM2qrW7wOrh+5oqR/6nhw/ij27//cy+zZp8cfqfrTp0Gz3trb4jzTjpXVdSfOX0oRN//hFxLcjEUFKpY88ho0e9PKttl56i1PZPtlInLG/Gs22y01OMrS7bcUb0L/Sd0JD5Lw42tupTv8GGC/fFzQgAAPDEmz2ia0rcvcdf//zzz7/44guLlwOTGLvfedzQfltXfmb5egAAAIDHqTQFP6zftXbnoVx51f9Bp33r5nNnTJo0YoAp/4Dl5j9QYLUg+myVI/9TfHLa2h2HNu8/oVSpRQnYrX2bt6eOnzh8gCjRylRcojt05tIfuw5fvB5mYihHqXT04N5vvjS2Z+eyb1szha3UieqgTveR6gKtuDHF+i4BAAAAWIaxd8E7d+6cONGMhyRhbgsXLvzmm2/KXBrQ0nvLlLYWrgfVWaaq+FKC8k5mQXyONjG3ML9QpynWF+r0ni4ONd0ca7pJa7o51pY5dm3g0buZl6+Xk7XrrTRNcen1ZNWVxPy7mZq8Ap1cq8srKCko1rs52rs5OdT1cGzh49qytluvpp6d/WQO9pXuKz7ML94bnn0jWXU/q0BRqNMW62XODjXcpPU8nDr4yjr7yTo3kDXwdq5y/QaD5IG8MCJdE/lQHZutVRWWqopKVUU6VVGpqqjU0d7O00Xq5eLg5Sr1dJHWkTl28JV18pO1q+smdah6j/QJrhPAv8pLW+5eiCt7tvann3765ZdfWrIYqSWTAcC/k8Fg2L153c9LF+XlZJsY6n50xPzZ0zeu/uHDRcue6t1PlPJEl5ebvWrZ17u2rCvV6UQMG3nrxrxZU3ds+O3jxSvbtu8kYuRHQq9e+vz9NxPjYkSJpispOX5g9/EDuwOnzJi3aKnMw1OUsBLbqROW9zA15WGq0ftmpY6O7Tp2ET2pf6euUkdHXUlJmasZaampyUkNGjURPS8AAADwb2AwGK4e3Hh87WK13NR+Qnps1LYvXr+w/ZfR73zTomsfUcoTnVqRc3Ldt1cObNSXitlPSL4TuvWzmZf3rhv3/jK/Vh1EjCyRSBLCruxa8k5Wcqwo0Up1JWFn9oWd2dfj+anPv/ONi7uHKGEfsaFSYWHyzFS58WdJOkgdG7YRvxHXsG0nB6ljqa7sfoIiMy0v/UFN38ai5wUAAAAAoAwGQ8SxTSGblxQoTH3WZnZC1PGls0L3rur3+lcNO/YWpTrRaZU5IVuWRR7bJG4XLuP+rWPfvh5+ZP2zby6p00LkLpxEIkmLunLq+/fkqXGiRNPrSu5f3H//4v72z73c7/WvnNxE627ZSp2wClVWqsDTQO2ljnVait+Iq9uqs73UUW+kEafKTlNmPPCqRyMOAAAAAAAAZmYwJJ3dcnfXsiKlqa145YPo0J/fiju8pv3UL3z8nxGlOtEV5efe27086exWg6iteHnc7Zs/vZl4amOHV772atJexMgSiST33rXbv72vTo8XJZq+tCQt5GBayMHGA15qP/ULqauY/W0bKhUWps1J0+akGVu1d3D0btZR9KTezTvZOzjqS8vuw2tz0wuykt3qNBI9LwAAAAAAAKobg8GwbtvuRSt+zs7JMzFUxJ370+fM/+G3jcs++7Bfr6dEKU902bl5X69ctW7bLp2uVMSwN8Iip74977fNO1Z++XGnAPGfVHHpWuibH34eE58oSrQSnW73oeO7Dx2fMTlw6WfzPD1kooSV2E6dAAAAAAAAqA4MBsO1gxtP/i7G3Nq4qB2LXg/a8cuod75p3qWazq3VKHJOrfv26kGR59am3And/vnMK/vWjZ4r/tzaxPAru5e8ky3eMNjwM/vCz+x7+vmpI+eIPAzWhkqFhSkyUxWCc2sbMLcWAAAAAIQZDFHHN1/dskRr8tTTnIToU8tm3d77a+/XvmpQfaee5l7bujT6+GZxeziZ92+dXPp65JH1fd9cUru5yLdaSySS9Kir534Uc5pobND+2KD9/sNe7v3alyJOE7WVOmEV5U89bWGGqacthaaeqrPT8jMeeDL1FAAAAACAJ5fBYDi5c/3Wn75S5pp6hi3xXuR3H8zYv/7HVz/6tsPTfUUpT3TKvJztP39zcuf6UlH7nzERN5f/55Wj239/Y+GKZu3En5gXffPyzwvfSksU52yYTlcSfGxP8LE9QyZMf/Wjb91kovUVbaVOWF52ekp2eoqxVanUsbl/Z9GTtgjoIpU66ow0P3MepmamJtVt0ET0vAAAAAAAAAAAExkMhvW7j37584bsPIWJoSLvx8+Yv/jHjbu+/fDNfk+JfxBXFDl5iq9XbV6/64iuVMwJsTcj702f983aHQe/+3hOx7YtRIz8yOXQyLc+/y4m0Wj/v1JKdLo9xy/sOX5heuDwb+e96SlzEyWsxHbqBAAAAADArGbPnr18+fLi4uLHl87FKsLS1J38eAwK/lLXw2l8x9rjrV2G+bg7OTzbwvvZFt5mil/f0+ntPn5mCi6RSOzsJE1qujSp6fJ8QC3zZTGdrdQJ4N/jVqrqQlzZ//Dk7Ow8a9YsC9djb+F8APBvk52Z8fqkkYvmvZ2XY+p9s3+7Gxk2Y/zQpZ9+UFxcJFZMsZw6vG94j4AdG9aU6sS8b/Zvt65dnji4589LF4kYU63K/+rDd6aNHpQYFyNi2Ef2bF0/pl+XK0HnTA9lK3XCWu5E3hZYbdu+k7Ozi+hJnZ1d2rYXOgV1Lypc9KQAAADAv0F+TsbaueN3L51r+rMk/5YWE7F6zvMHfligK6l2/YTwcweXTOh6ee86cZ9D8LfE8KsrX+l/4vfFYgUs1Kj2LP/Pr7OHZ4n0gMZ/unpo8/KXesbcuCBKNBsqFVaRel/onbtfqw5SJ/H7CVInF+HHu6bFRoqeFAAAAACAx2nyMvd+MuHMT/8pMPlpoH/LiovYPX/MhTWflFa/LlxM8KH1M54KP/yHmbpwaVFXt709MGTzEhFjFheozv48b+cHo8R6yuY/RR7fsumN3sm3L5oeylbqhBVlxkUIrNZp3l7q5Cx6UqmTcx3BZ/Rmx0eJnhQAAAAAAAD4p0J5ZsjiyWG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+ "text/plain": [ + "" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sklearn.tree import export_graphviz\n", + "# Export as dot file\n", + "export_graphviz(model.estimators_[0], out_file='tree.dot', \n", + " feature_names = X.columns,\n", + " class_names = ['1', '0'],\n", + " rounded = True, proportion = False, \n", + " precision = 2, filled = True, max_depth=4)\n", + "\n", + "# Convert to png using system command (requires Graphviz)\n", + "from subprocess import call\n", + "call(['dot', '-Tpng', 'tree.dot', '-o', 'tree.png', '-Gdpi=600'])\n", + "\n", + "# Display in jupyter notebook\n", + "from IPython.display import Image\n", + "Image(filename = 'tree.png')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "### Quais tipos de problemas podemos resolver com random forest?\n", + "\n", + "- Tanto regressão quanto classificação\n", + "- Problemas variados de negócios, ex: churn, predição de vendas, etc.\n", + "- Basicamente **quase** todos os problemas\n", + "- Ruim para trends (tendências) e problemas com dados em que haverão muitos dados não vistos no treinamento" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "### Quais vantagens e desvantagens vocês enxergam?\n", + "\n", + "*. Vantagens:\n", + "- Tanto regressão quanto classificação\n", + "- Pouca parametrização\n", + "- Não causa overfitting\n", + "- Média interpretabilidade \n", + "- Também pode ser usada para tratar missing-values e análise de grupos (clusters)\n", + "\n", + "*. Desvantagens:\n", + "- Quanto mais árvores maior o tempo de **predição** e **gasto de memória**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## Desafios legais para serem resolvidos com RF:\n", + "- https://www.kaggle.com/c/sf-crime\n", + "- https://www.kaggle.com/c/house-prices-advanced-regression-techniques" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 5. LightGBM (Gradient Boosting Machine)\n", + "\n", + "\n", + "![](https://image.slidesharecdn.com/stratauk17salvarisfierrofastretraining-170523090635/95/speeding-up-machinelearning-applications-with-the-lightgbm-library-6-638.jpg)" + ] + }, + { + "cell_type": "code", + "execution_count": 156, + "metadata": {}, + "outputs": [], + "source": [ + "import lightgbm as lgb" + ] + }, + { + "cell_type": "code", + "execution_count": 168, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "LGBMClassifier(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\n", + " importance_type='split', learning_rate=0.1, max_depth=10,\n", + " min_child_samples=5, min_child_weight=0.001, min_split_gain=0.0,\n", + " n_estimators=50, n_jobs=3, num_leaves=8, objective='binary',\n", + " random_state=None, reg_alpha=0.0, reg_lambda=0.0, silent=True,\n", + " subsample=1.0, subsample_for_bin=200000, subsample_freq=0)" + ] + }, + "execution_count": 168, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model = lgb.LGBMClassifier(objective = 'binary',\n", + " n_jobs = 3, # Updated from 'nthread'\n", + " silent = True,\n", + " max_depth = 10,\n", + " min_child_samples=5,\n", + " learning_rate=0.1,\n", + " n_estimators=50,\n", + " num_leaves= 8)\n", + "\n", + "\n", + "model.fit(X_train, y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 169, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Acurácia: 0.92\n", + "Precisão: 0.89\n", + "Sensibilidade: 0.98\n" + ] + } + ], + "source": [ + "y_pred = model.predict(X_test)\n", + "\n", + "print(\"Acurácia: {:.2f}\".format(accuracy_score(y_test, y_pred)))\n", + "print(\"Precisão: {:.2f}\".format(precision_score(y_test, y_pred)))\n", + "print(\"Sensibilidade: {:.2f}\".format(recall_score(y_test, y_pred)))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Quais vantagens e desvantagens vocês enxergam?\n", + "*. Vantagens:\n", + "- Tanto regressão quanto classificação\n", + "- Tem alta performance\n", + "- Funciona bem com datasets muito grandes\n", + "\n", + "\n", + "*. Desvantagens:\n", + "- É mais propenso a overfitting, por isso não funciona bem com poucos dados" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "## Desafios legais para serem resolvidos com ensemble:\n", + "- https://www.kaggle.com/c/avito-demand-prediction/data\n", + "- https://www.kaggle.com/c/recruit-restaurant-visitor-forecasting\n", + "- https://www.kaggle.com/c/sf-crime\n", + "- https://www.kaggle.com/c/house-prices-advanced-regression-techniques" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.7" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/5. Algoritmos de Machine Learning e aplica\303\247\303\265es em larga escala/notebooks/ensemble.ipynb" "b/5. Algoritmos de Machine Learning e aplica\303\247\303\265es em larga escala/notebooks/ensemble.ipynb" new file mode 100644 index 0000000..cda6911 --- /dev/null +++ "b/5. Algoritmos de Machine Learning e aplica\303\247\303\265es em larga escala/notebooks/ensemble.ipynb" @@ -0,0 +1,1192 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "# Aula 21 - Ensemble & Random Forest\n", + "\n", + "\n", + "## 1. O que é um ensemble?\n", + "\n", + "![#trabalho em equipe funciona!](https://thumbs.gfycat.com/SlimyTepidAtlanticridleyturtle-size_restricted.gif)\n", + "\n", + "

#teamwork

\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "### Vamos ver se isso é verdade mesmo!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [], + "source": [ + "## imports necessarios\n", + "\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "import pandas as pd\n", + "import numpy as np\n", + "from sklearn.preprocessing import LabelEncoder\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.neighbors import KNeighborsClassifier\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "from sklearn.ensemble import RandomForestClassifier\n", + "from sklearn.ensemble import VotingClassifier\n", + "from sklearn.metrics import accuracy_score, precision_score, recall_score\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "\n", + "Criaremos um modelo para predizer pessoas que devem procurar tratamento para saúde mental em empresas de tecnologia.\n", + "\n", + "Vamos ler os dados e analisar o dataset:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "df = pd.read_csv('survey.csv')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> Dataset retirado do [kaggle](https://www.kaggle.com/osmi/mental-health-in-tech-survey/kernels), porém foram filtrados apenas os países Canada, United Kingdom e United States para facilitar a análise" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true, + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [], + "source": [ + "df.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "Vemos várias variáveis como objetos e vários *NaN*s, vamos tratá-los.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [], + "source": [ + "# Timestamp:\n", + "del df['Timestamp']" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "### Variáveis com NaN:\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "# comments:\n", + "df.loc[df['comments'].notnull(), 'comments'].head()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "Nao aprendemos NLP... ainda" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [], + "source": [ + "del df['comments']" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "work_interfere:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "df['work_interfere'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "df['work_interfere'].fillna('DontKnow', inplace=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "self_employed:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "df['self_employed'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": false, + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "df['self_employed'].fillna('No', inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "df['state'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "del df['state']" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "### Variaveis categoricas" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "Gender:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": false, + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "df['Gender'].unique()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "Vemos muitas categorias aqui, vamos tratar:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "male_str = [\"male\", \"m\", \"male-ish\", \"maile\", \"mal\", \"male (cis)\", \"make\", \"male \", \"man\",\"msle\", \"mail\", \"malr\",\"cis man\", \"Cis Male\", \"cis male\"]\n", + "trans_str = [\"trans-female\", \"something kinda male?\", \"queer/she/they\", \"non-binary\",\"nah\", \"all\", \"enby\", \"fluid\", \"genderqueer\", \"androgyne\", \"agender\", \"male leaning androgynous\", \"guy (-ish) ^_^\", \"trans woman\", \"neuter\", \"female (trans)\", \"queer\", \"ostensibly male, unsure what that really means\"] \n", + "female_str = [\"cis female\", \"f\", \"female\", \"woman\", \"femake\", \"female \",\"cis-female/femme\", \"female (cis)\", \"femail\"]\n", + "\n", + "for (row, col) in df.iterrows():\n", + "\n", + " if str.lower(col.Gender) in male_str:\n", + " df['Gender'].replace(to_replace=col.Gender, value='male', inplace=True)\n", + "\n", + " if str.lower(col.Gender) in female_str:\n", + " df['Gender'].replace(to_replace=col.Gender, value='female', inplace=True)\n", + "\n", + " if str.lower(col.Gender) in trans_str:\n", + " df['Gender'].replace(to_replace=col.Gender, value='trans', inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "df['Gender'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "df = df[df['Gender']!='p']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "df['Gender'].unique()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "Vamos ver quantos países temos:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": false, + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "df['Country'].value_counts().plot(kind='barh', figsize=(10,7),\n", + " color=\"coral\", fontsize=13)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "Vamos criar as dummies" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "df = pd.get_dummies(df, columns=['Gender', 'Country', 'self_employed', 'family_history', 'treatment', 'work_interfere',\n", + " 'no_employees', 'remote_work', 'tech_company', 'anonymity', 'leave', 'mental_health_consequence',\n", + " 'phys_health_consequence', 'coworkers', 'supervisor', 'mental_health_interview', 'phys_health_interview',\n", + " 'mental_vs_physical', 'obs_consequence', 'benefits', 'care_options', 'wellness_program',\n", + " 'seek_help'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [], + "source": [ + "df.shape" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": false, + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "df.columns.values" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "df.drop(columns=['family_history_No', 'treatment_No', 'remote_work_No', 'tech_company_No'], inplace=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "Vamos dar uma olhada na distribuićão da variável resposta:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "df['treatment_Yes'].value_counts().plot(kind='bar')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## Finalmente, vamos ao treinamento!\n", + "\n", + "Vamos separar os dados em treino e teste:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "X = df.drop('treatment_Yes', axis=1)\n", + "y = df['treatment_Yes']\n", + "\n", + "X_train, X_test, y_train, y_test = train_test_split(X , y, test_size = 0.15, random_state=0)\n", + "print(X_train.shape)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + " Vamos usar os dois métodos mais dummies que aprendemos até agora para tentar predizer " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "## Relembrando Árvores de Decisão:\n", + "\n", + "\"drawing\"\n", + "

Exemplo de árvore de decisão para classificar sobreviventes do Titanic

" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [], + "source": [ + "# crie o modelo com random state igual a 10\n", + "model_tree = DecisionTreeClassifier(random_state=10)\n", + "model_tree.fit(X_train, y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "y_pred_tree_train = model_tree.predict_proba(X_train)\n", + "print(\"Acurácia: {:.2f}\".format(accuracy_score(y_train, y_pred_tree_train[:,1]>0.5)))\n", + "print(\"Precisão: {:.2f}\".format(precision_score(y_train, y_pred_tree_train[:,1]>0.5)))\n", + "print(\"Sensibilidade: {:.2f}\".format(recall_score(y_train, y_pred_tree_train[:,1]>0.5)))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true, + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "y_pred_tree = model_tree.predict_proba(X_test)\n", + "print(\"Acurácia: {:.2f}\".format(accuracy_score(y_test, y_pred_tree[:,1]>0.5)))\n", + "print(\"Precisão: {:.2f}\".format(precision_score(y_test, y_pred_tree[:,1]>0.5)))\n", + "print(\"Sensibilidade: {:.2f}\".format(recall_score(y_test, y_pred_tree[:,1]>0.5)))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## KNN " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "![#knn!](https://importq.files.wordpress.com/2017/11/knn_neigh.gif?w=656)\n", + "\n", + " - algoritmo de abordagem \"preguiçosa\"\n", + " - assume que elementos similares estão em proximidade\n", + " - Calcula a distância para os *N* vizinhos mais próximos e determina a classe de acordo com a classe dos vizinhos\n", + " \n", + "Mais informações: https://www.analyticsvidhya.com/blog/2018/03/introduction-k-neighbours-algorithm-clustering/" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true, + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [], + "source": [ + "# crie o modelo com random state igual a 10\n", + "model_knn = KNeighborsClassifier()\n", + "model_knn.fit(X_train,y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "y_pred_knn_train = model_knn.predict_proba(X_train)\n", + "print(\"Acurácia: {:.2f}\".format(accuracy_score(y_train, y_pred_knn_train[:,1]>0.5)))\n", + "print(\"Precisão: {:.2f}\".format(precision_score(y_train, y_pred_knn_train[:,1]>0.5)))\n", + "print(\"Sensibilidade: {:.2f}\".format(recall_score(y_train, y_pred_knn_train[:,1]>0.5)))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "y_pred_knn = model_knn.predict_proba(X_test)\n", + "print(\"Acurácia: {:.2f}\".format(accuracy_score(y_test, y_pred_knn[:,1]>0.5)))\n", + "print(\"Precisão: {:.2f}\".format(precision_score(y_test, y_pred_knn[:,1]>0.5)))\n", + "print(\"Sensibilidade: {:.2f}\".format(recall_score(y_test, y_pred_knn[:,1]>0.5)))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "### Como acham que podemos combinar esses modelos?\n", + "- .\n", + "- .\n", + "- .\n", + "- ." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [], + "source": [ + "model_vot = VotingClassifier(estimators=[('tree', model_tree), ('knn', model_knn)], voting='soft')\n", + "model_vot.fit(X_train, y_train) " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "y_pred = model_vot.predict(X_test)\n", + "print(\"Acurácia: {:.2f}\".format(accuracy_score(y_test, y_pred)))\n", + "print(\"Precisão: {:.2f}\".format(precision_score(y_test, y_pred)))\n", + "print(\"Sensibilidade: {:.2f}\".format(recall_score(y_test, y_pred)))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [], + "source": [ + "x_novo = np.array([y_pred_tree_train[:,1], y_pred_knn_train[:,1]])\n", + "x_novo = x_novo.transpose()\n", + "\n", + "x_novo_test = np.array([y_pred_tree[:,1], y_pred_knn[:,1]])\n", + "x_novo_test = x_novo_test.transpose()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "model_lr2 = LogisticRegression()\n", + "model_lr2.fit(x_novo, y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "y_pred_lr = model_lr2.predict_proba(x_novo_test)\n", + "print(\"Acurácia: {:.2f}\".format(accuracy_score(y_test, y_pred_lr[:,1]>0.5)))\n", + "print(\"Precisão: {:.2f}\".format(precision_score(y_test, y_pred_lr[:,1]>0.5)))\n", + "print(\"Sensibilidade: {:.2f}\".format(recall_score(y_test, y_pred_lr[:,1]>0.5)))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## 2. Tipos de Ensemble:\n", + "\n", + "Existem vários formas diferentes de combinar os modelos. As principais são:\n", + "\n", + "\n", + "### **1. Voting Based Classifier:**\n", + "\n", + "**1. a) Majority Vote**\n", + "\n", + "A ideia é fazer uma votação entre as predições dos modelos. A classe que tiver mais votos vence. Também podemos ter uma variação desse algoritmo, o **Weighted Voting Classifier**, em que na votação alguns modelos tem mais peso que outros.\n", + "\n", + "![](voting.png)\n", + "\n", + "\n", + "**1. b) Average Classifier:**\n", + "\n", + "A ideia é similar ao anterior, porém ao invés de uma votação é calculada a média das predições. Da mesma forma podemos ter alguns modelos com mais peso que outros tendo um **Weighted Average Classifier**\n", + "![](average.png)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "### 2. Stacking:\n", + "\n", + "Nesse modelo as predições dos modelos anteriores são combinadas por um outro modelo para obter a saída final. Podem ser criadas várias camadas com modelos diferentes.\n", + "\n", + "![](stacking.png)\n", + "\n", + "### 3. Boosting:\n", + "\n", + "Os modelos são treinados com os mesmos datasets, porém os pesos das intâncias são ajustados de acordo com o erro das predições anteriores. Veram mais na próxima aula...\n", + "\n", + "![](boosting.png)\n", + "\n", + "## 4. BAGGING: \n", + "Todos os modelos deste tipo de ensemble são do **mesmo algoritmo**, porém os dados de entrada de cada um são amostras do dado original, com a **mesma quantidade de dados do dataset original**, selecionadas usando o método bootstrap (**aleatória com repetição**). \n", + "\n", + "**AQUI TEMOS A RANDOM FOREST**\n", + "\n", + "![](bagging.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## 4. RANDOM FOREST" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "### Como Funciona?\n", + "\n", + "![#OOB!](https://cdn-images-1.medium.com/max/1600/1*yoW30XVqAnKOA-7AArXqNg.gif)\n", + "\n", + "- Algoritmo de bagging que usa árvores de decisão\n", + "- Cada árvore terá um conjunto diferente de dados e de features\n", + "- Out-of-bag score: os dados que não foram usados naquela árvore são utilizados como teste" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true, + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [], + "source": [ + "model = RandomForestClassifier(n_estimators=10, random_state=0, oob_score=True)\n", + "model.fit(X_train, y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "model.oob_score_" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "y_pred = model.predict(X_test)\n", + "print(\"Acurácia: {:.2f}\".format(accuracy_score(y_test, y_pred)))\n", + "print(\"Precisão: {:.2f}\".format(precision_score(y_test, y_pred)))\n", + "print(\"Sensibilidade: {:.2f}\".format(recall_score(y_test, y_pred)))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "scrolled": true, + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "Vamos testar outras combinações de parâmetros?\n", + "\n", + "`Dica 1: Manter o mesmo random_state para comparação de resultados\n", + " Dica 2: Os parâmetros são similares as árvores de decisão\n", + " Dica 3: Número de estimadores e de features são os mais relevantes ` " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Feature importance:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": false, + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "importances = model.feature_importances_\n", + "std = np.std([tree.feature_importances_ for tree in model.estimators_],\n", + " axis=0)\n", + "indices = np.argsort(importances)[::1]\n", + "\n", + "\n", + "# Plot the feature importances of the forest\n", + "plt.figure(figsize=(15,15))\n", + "plt.title(\"Feature importances\")\n", + "plt.barh(range(X.shape[1]), importances[indices],\n", + " color=\"r\", yerr=std[indices], align=\"center\")\n", + "plt.yticks(range(X.shape[1]), X.columns[indices])\n", + "plt.ylim([-1, X.shape[1]])\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "outputs": [], + "source": [ + "from sklearn.tree import export_graphviz\n", + "# Export as dot file\n", + "export_graphviz(model.estimators_[0], out_file='tree.dot', \n", + " feature_names = X.columns,\n", + " class_names = ['1', '0'],\n", + " rounded = True, proportion = False, \n", + " precision = 2, filled = True, max_depth=4)\n", + "\n", + "# Convert to png using system command (requires Graphviz)\n", + "from subprocess import call\n", + "call(['dot', '-Tpng', 'tree.dot', '-o', 'tree.png', '-Gdpi=600'])\n", + "\n", + "# Display in jupyter notebook\n", + "from IPython.display import Image\n", + "Image(filename = 'tree.png')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "### Quais tipos de problemas podemos resolver com random forest?\n", + "\n", + "- .\n", + "- .\n", + "- .\n", + "- ." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "### Quais vantagens e desvantagens vocês enxergam?\n", + "\n", + "*. Vantagens:\n", + "- .\n", + "- .\n", + "- .\n", + "- .\n", + "\n", + "*. Desvantagens:\n", + "- .\n", + "- .\n", + "- .\n", + "- ." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 5. LightGBM (Gradient Boosting Machine)\n", + "\n", + "\n", + "![](https://image.slidesharecdn.com/stratauk17salvarisfierrofastretraining-170523090635/95/speeding-up-machinelearning-applications-with-the-lightgbm-library-6-638.jpg)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import lightgbm as lgb" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "model = lgb.LGBMClassifier(objective = 'binary',\n", + " n_jobs = 3, # Updated from 'nthread'\n", + " silent = True,\n", + " max_depth = 10,\n", + " min_child_samples=5,\n", + " learning_rate=0.1,\n", + " n_estimators=50,\n", + " num_leaves= 8)\n", + "\n", + "\n", + "model.fit(X_train, y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "y_pred = model.predict(X_test)\n", + "\n", + "print(\"Acurácia: {:.2f}\".format(accuracy_score(y_test, y_pred)))\n", + "print(\"Precisão: {:.2f}\".format(precision_score(y_test, y_pred)))\n", + "print(\"Sensibilidade: {:.2f}\".format(recall_score(y_test, y_pred)))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Quais vantagens e desvantagens vocês enxergam?\n", + "*. Vantagens:\n", + "- .\n", + "- .\n", + "- .\n", + "- .\n", + "\n", + "*. Desvantagens:\n", + "- .\n", + "- .\n", + "- ." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "## Desafios legais para serem resolvidos com ensemble:\n", + "- https://www.kaggle.com/c/avito-demand-prediction/data\n", + "- https://www.kaggle.com/c/recruit-restaurant-visitor-forecasting\n", + "- https://www.kaggle.com/c/sf-crime\n", + "- https://www.kaggle.com/c/house-prices-advanced-regression-techniques" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.7" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/5. 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Algoritmos de Machine Learning e aplica\303\247\303\265es em larga escala/slides/Machine Learning Part 1.pptx" differ diff --git a/5.1 Deep Learning/README.md b/5.1 Deep Learning/README.md new file mode 100644 index 0000000..f4ba890 --- /dev/null +++ b/5.1 Deep Learning/README.md @@ -0,0 +1,7 @@ +# 5.1 Deep Learning + + +## Pré-aula: +Acessem o link: https://drive.google.com/open?id=17Wbk2x4hE8ok_qBJj0bTkrhAsGNzBx77 e copiem o dataset para o drive de vocês (Copiar para o meu drive) + +As primeiras células do notebook: https://colab.research.google.com/drive/1nyiabCK8doIxONt8GjK49d3giDHtUPa6 são para que ele consiga enxergar os arquivos que estão no drive. diff --git a/5.1 Deep Learning/data/Churn_Modelling.csv b/5.1 Deep Learning/data/Churn_Modelling.csv new file mode 100644 index 0000000..3cbdbd0 --- /dev/null +++ b/5.1 Deep Learning/data/Churn_Modelling.csv @@ -0,0 +1,10001 @@ 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+29,15728693,McWilliams,574,Germany,Female,43,3,141349.43,1,1,1,100187.43,0 +30,15656300,Lucciano,411,France,Male,29,0,59697.17,2,1,1,53483.21,0 +31,15589475,Azikiwe,591,Spain,Female,39,3,0,3,1,0,140469.38,1 +32,15706552,Odinakachukwu,533,France,Male,36,7,85311.7,1,0,1,156731.91,0 +33,15750181,Sanderson,553,Germany,Male,41,9,110112.54,2,0,0,81898.81,0 +34,15659428,Maggard,520,Spain,Female,42,6,0,2,1,1,34410.55,0 +35,15732963,Clements,722,Spain,Female,29,9,0,2,1,1,142033.07,0 +36,15794171,Lombardo,475,France,Female,45,0,134264.04,1,1,0,27822.99,1 +37,15788448,Watson,490,Spain,Male,31,3,145260.23,1,0,1,114066.77,0 +38,15729599,Lorenzo,804,Spain,Male,33,7,76548.6,1,0,1,98453.45,0 +39,15717426,Armstrong,850,France,Male,36,7,0,1,1,1,40812.9,0 +40,15585768,Cameron,582,Germany,Male,41,6,70349.48,2,0,1,178074.04,0 +41,15619360,Hsiao,472,Spain,Male,40,4,0,1,1,0,70154.22,0 +42,15738148,Clarke,465,France,Female,51,8,122522.32,1,0,0,181297.65,1 +43,15687946,Osborne,556,France,Female,61,2,117419.35,1,1,1,94153.83,0 +44,15755196,Lavine,834,France,Female,49,2,131394.56,1,0,0,194365.76,1 +45,15684171,Bianchi,660,Spain,Female,61,5,155931.11,1,1,1,158338.39,0 +46,15754849,Tyler,776,Germany,Female,32,4,109421.13,2,1,1,126517.46,0 +47,15602280,Martin,829,Germany,Female,27,9,112045.67,1,1,1,119708.21,1 +48,15771573,Okagbue,637,Germany,Female,39,9,137843.8,1,1,1,117622.8,1 +49,15766205,Yin,550,Germany,Male,38,2,103391.38,1,0,1,90878.13,0 +50,15771873,Buccho,776,Germany,Female,37,2,103769.22,2,1,0,194099.12,0 +51,15616550,Chidiebele,698,Germany,Male,44,10,116363.37,2,1,0,198059.16,0 +52,15768193,Trevisani,585,Germany,Male,36,5,146050.97,2,0,0,86424.57,0 +53,15683553,O'Brien,788,France,Female,33,5,0,2,0,0,116978.19,0 +54,15702298,Parkhill,655,Germany,Male,41,8,125561.97,1,0,0,164040.94,1 +55,15569590,Yoo,601,Germany,Male,42,1,98495.72,1,1,0,40014.76,1 +56,15760861,Phillipps,619,France,Male,43,1,125211.92,1,1,1,113410.49,0 +57,15630053,Tsao,656,France,Male,45,5,127864.4,1,1,0,87107.57,0 +58,15647091,Endrizzi,725,Germany,Male,19,0,75888.2,1,0,0,45613.75,0 +59,15623944,T'ien,511,Spain,Female,66,4,0,1,1,0,1643.11,1 +60,15804771,Velazquez,614,France,Male,51,4,40685.92,1,1,1,46775.28,0 +61,15651280,Hunter,742,Germany,Male,35,5,136857,1,0,0,84509.57,0 +62,15773469,Clark,687,Germany,Female,27,9,152328.88,2,0,0,126494.82,0 +63,15702014,Jeffrey,555,Spain,Male,33,1,56084.69,2,0,0,178798.13,0 +64,15751208,Pirozzi,684,Spain,Male,56,8,78707.16,1,1,1,99398.36,0 +65,15592461,Jackson,603,Germany,Male,26,4,109166.37,1,1,1,92840.67,0 +66,15789484,Hammond,751,Germany,Female,36,6,169831.46,2,1,1,27758.36,0 +67,15696061,Brownless,581,Germany,Female,34,1,101633.04,1,1,0,110431.51,0 +68,15641582,Chibugo,735,Germany,Male,43,10,123180.01,2,1,1,196673.28,0 +69,15638424,Glauert,661,Germany,Female,35,5,150725.53,2,0,1,113656.85,0 +70,15755648,Pisano,675,France,Female,21,8,98373.26,1,1,0,18203,0 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+158,15623595,Clayton,586,Spain,Female,28,2,0,2,1,1,92067.35,0 +159,15589975,Maclean,646,France,Female,73,6,97259.25,1,0,1,104719.66,0 +160,15804017,Chigolum,631,Germany,Female,33,4,123246.7,1,0,0,112687.57,0 +161,15692132,Wilkinson,717,Spain,Female,22,6,101060.25,1,0,1,84699.56,0 +162,15641122,Wei,684,France,Male,30,2,0,2,1,0,83473.82,0 +163,15630910,Treacy,800,France,Female,49,7,108007.36,1,0,0,47125.11,0 +164,15680772,Hu,721,Spain,Female,36,2,0,2,1,1,106977.8,0 +165,15658929,Taverner,683,Spain,Male,29,0,133702.89,1,1,0,55582.54,1 +166,15585388,Sherman,660,Germany,Male,31,9,125189.75,2,1,1,139874.43,0 +167,15724623,Taubman,704,Germany,Female,24,7,113034.22,1,1,0,162503.48,1 +168,15588537,Robinson,615,Spain,Female,41,9,109013.23,1,1,0,196499.96,0 +169,15574692,Pinto,667,Spain,Female,39,2,0,2,1,0,40721.24,1 +170,15611325,Wood,682,Germany,Male,24,9,57929.81,2,0,0,53134.3,0 +171,15587562,Hawkins,484,France,Female,29,4,130114.39,1,1,0,164017.89,0 +172,15613172,Sun,628,Germany,Male,27,5,95826.49,2,1,0,155996.96,0 +173,15651022,Yost,480,Germany,Male,44,10,129608.57,1,1,0,5472.7,1 +174,15586310,Ting,578,France,Male,30,4,169462.09,1,1,0,112187.11,0 +175,15625524,Rowe,512,France,Male,40,5,0,2,1,1,146457.83,0 +176,15755209,Fu,484,Spain,Female,35,7,133868.21,1,1,1,27286.1,0 +177,15645248,Ho,510,France,Female,30,0,0,2,1,1,130553.47,0 +178,15790355,Okechukwu,606,Germany,Male,36,5,190479.48,2,0,0,179351.89,0 +179,15762615,Campbell,597,Spain,Female,40,8,101993.12,1,0,1,94774.12,0 +180,15625426,Ashbolt,754,Germany,Female,55,3,161608.81,1,1,0,8080.85,1 +181,15716334,Rozier,850,Spain,Female,45,2,122311.21,1,1,1,19482.5,0 +182,15789669,Hsia,510,France,Male,65,2,0,2,1,1,48071.61,0 +183,15621075,Ogbonnaya,778,Germany,Female,45,1,162150.42,2,1,0,174531.27,0 +184,15810845,T'ang,636,France,Male,42,2,0,2,1,1,55470.78,0 +185,15719377,Cocci,804,France,Female,50,4,0,1,1,1,8546.87,1 +186,15654506,Chang,514,France,Male,32,8,0,2,1,0,95857.18,0 +187,15771977,T'ao,730,France,Female,39,1,99010.67,1,1,0,194945.8,0 +188,15708710,Ford,525,Spain,Female,37,0,0,1,0,1,131521.72,0 +189,15726676,Marshall,616,Spain,Male,30,5,0,2,0,1,196108.51,0 +190,15587421,Tsai,687,Germany,Female,34,7,111388.18,2,1,0,148564.76,0 +191,15726931,Onwumelu,715,France,Female,41,8,56214.85,2,0,0,92982.61,1 +192,15771086,Graham,512,France,Female,36,3,84327.77,2,1,0,17675.36,0 +193,15756850,Golovanov,479,France,Male,40,1,0,2,0,0,114996.43,0 +194,15702741,Potts,601,France,Male,32,8,93012.89,1,1,0,86957.42,0 +195,15679200,Crawford,580,Spain,Male,29,9,61710.44,2,1,0,128077.8,0 +196,15594815,Aleshire,807,France,Male,35,3,174790.15,1,1,1,600.36,0 +197,15635905,Moran,616,Spain,Female,32,6,0,2,1,1,43001.46,0 +198,15777892,Samsonova,721,Germany,Male,37,3,107720.64,1,1,1,158591.12,0 +199,15656176,Jenkins,501,France,Male,57,10,0,2,1,1,47847.19,0 +200,15811127,Volkov,521,France,Male,35,6,96423.84,1,1,0,10488.44,0 +201,15604482,Chiemezie,850,Spain,Male,30,2,141040.01,1,1,1,5978.2,0 +202,15622911,Jude,759,France,Male,42,4,105420.18,1,0,1,121409.06,0 +203,15600974,He,516,Spain,Male,50,5,0,1,0,1,146145.93,1 +204,15727868,Onuora,711,France,Female,38,2,129022.06,2,1,1,14374.86,1 +205,15627801,Ginikanwa,512,Spain,Male,33,3,176666.62,1,1,0,94670.77,0 +206,15773039,Ku,550,France,Male,37,3,0,1,1,1,179670.31,0 +207,15755262,McDonald,608,Spain,Female,41,3,89763.84,1,0,0,199304.74,1 +208,15679531,Collins,618,France,Male,34,5,134954.53,1,1,1,151954.39,0 +209,15684181,Hackett,643,France,Male,45,5,0,1,1,0,142513.5,1 +210,15612087,Dike,671,France,Male,45,2,106376.85,1,0,1,158264.62,0 +211,15752047,Trevisano,689,Germany,Male,33,2,161814.64,2,1,0,169381.9,0 +212,15624592,Tan,603,France,Male,31,8,0,2,1,1,169915.02,0 +213,15573152,Glassman,620,France,Female,41,9,0,2,0,0,88852.47,0 +214,15594917,Miller,676,France,Female,34,1,63095.01,1,1,1,40645.81,0 +215,15785542,Kornilova,572,Germany,Male,26,4,118287.01,2,0,0,60427.3,0 +216,15723488,Watson,668,Germany,Male,47,7,106854.21,1,0,1,157959.02,1 +217,15680920,Marchesi,695,France,Male,46,7,49512.55,1,1,0,133007.34,0 +218,15786308,Millar,730,Spain,Female,33,9,0,2,0,0,176576.62,0 +219,15659366,Shih,807,France,Male,43,1,105799.32,2,1,0,34888.04,1 +220,15774854,Fuller,592,France,Male,54,8,0,1,1,1,28737.71,1 +221,15725311,Hay,726,France,Female,31,9,114722.05,2,1,1,98178.57,0 +222,15787155,Yang,514,Spain,Male,30,7,0,1,0,1,125010.24,0 +223,15727829,McIntyre,567,France,Male,42,2,0,2,1,1,167984.61,0 +224,15733247,Stevenson,850,France,Male,33,10,0,1,1,0,4861.72,1 +225,15568748,Poole,671,Germany,Male,45,6,99564.22,1,1,1,108872.45,1 +226,15699029,Bagley,670,France,Male,37,4,170557.91,2,1,0,198252.88,0 +227,15774393,Ch'ien,694,France,Female,30,9,0,2,1,1,26960.31,0 +228,15676895,Cattaneo,547,Germany,Female,39,6,74596.15,3,1,1,85746.52,1 +229,15637753,O'Sullivan,751,Germany,Male,50,2,96888.39,1,1,0,77206.25,1 +230,15605461,Lucas,594,Germany,Female,29,3,130830.22,1,1,0,61048.53,0 +231,15808473,Ringrose,673,France,Male,72,1,0,2,0,1,111981.19,0 +232,15627000,Freeman,610,France,Male,40,0,0,2,1,0,62232.6,0 +233,15787174,Sergeyev,512,France,Female,37,1,0,2,0,1,156105.03,0 +234,15723886,Fiore,767,Germany,Male,20,3,119714.25,2,0,1,150135.38,0 +235,15704769,Smith,585,France,Female,67,5,113978.97,2,0,1,93146.11,0 +236,15772896,Dumetochukwu,763,Germany,Male,42,6,100160.75,1,1,0,33462.94,1 +237,15711540,Pacheco,712,France,Female,29,2,0,1,1,1,144375,0 +238,15764866,Synnot,539,Germany,Female,43,3,116220.5,3,1,0,55803.96,1 +239,15794056,Johnston,668,France,Female,46,2,0,3,1,0,89048.46,1 +240,15795149,Stevens,703,France,Male,28,2,81173.83,2,0,1,162812.16,0 +241,15812009,Grant,662,Spain,Male,38,4,0,2,1,0,136259.65,0 +242,15651001,Tsao,725,Germany,Female,39,5,116803.8,1,1,0,124052.97,0 +243,15813844,Barnes,703,France,Male,37,8,105961.68,2,0,1,74158.8,0 +244,15596175,McIntosh,659,Germany,Male,67,6,117411.6,1,1,1,45071.09,1 +245,15576269,Madison,523,Spain,Male,34,7,0,2,1,0,62030.06,0 +246,15797219,Ifesinachi,635,France,Female,40,10,123497.58,1,1,0,131953.23,1 +247,15685500,Glazkov,772,Germany,Male,26,7,152400.51,2,1,0,79414,0 +248,15599792,Dimauro,545,France,Female,26,1,0,2,1,1,199638.56,0 +249,15657566,Wieck,634,Germany,Male,24,8,103097.85,1,1,1,157577.29,0 +250,15772423,Liao,739,Germany,Male,54,8,126418.14,1,1,0,134420.75,1 +251,15628112,Hughes,771,Germany,Female,36,5,77846.9,1,0,0,99805.99,0 +252,15753754,Morrison,587,Spain,Female,34,1,0,2,1,1,97932.68,0 +253,15793726,Matveyeva,681,France,Female,79,0,0,2,0,1,170968.99,0 +254,15694717,Ku,544,Germany,Male,37,2,79731.91,1,1,1,57558.95,0 +255,15665834,Cheatham,696,Spain,Male,28,8,0,1,0,0,176713.47,0 +256,15765297,Yao,766,Spain,Male,41,0,0,2,0,1,34283.23,0 +257,15636684,Kirkland,727,France,Male,34,10,0,2,1,1,198637.34,0 +258,15592979,Rose,671,Germany,Female,34,6,37266.67,2,0,0,156917.12,0 +259,15750803,Jess,693,France,Female,30,6,127992.25,1,1,1,50457.2,0 +260,15607178,Welch,850,Germany,Male,38,3,54901.01,1,1,1,140075.55,0 +261,15713853,Ifeajuna,732,Germany,Male,42,9,108748.08,2,1,1,65323.11,0 +262,15673481,Morton,726,Spain,Female,48,6,99906.19,1,1,0,64323.24,0 +263,15686776,Rossi,557,France,Female,32,6,184686.41,2,1,0,14956.44,0 +264,15673693,Reppert,682,France,Female,26,0,110654.02,1,0,1,111879.21,0 +265,15700696,Kang,738,Spain,Male,31,9,79019.8,1,1,1,18606.23,0 +266,15813163,Ch'iu,531,Spain,Female,36,9,99240.51,1,1,0,123137.01,0 +267,15653857,Wallis,498,France,Male,34,2,0,2,1,1,148528.24,0 +268,15777076,Clark,651,France,Male,36,7,0,2,1,0,13898.31,0 +269,15717398,Fielding,549,Spain,Female,39,7,0,1,0,0,81259.25,1 +270,15799217,Zetticci,791,Germany,Female,35,7,52436.2,1,1,0,161051.75,0 +271,15787071,Dulhunty,650,Spain,Male,41,9,0,2,0,1,191599.67,0 +272,15619955,Bevington,733,Germany,Male,34,3,100337.96,3,1,0,48559.19,1 +273,15796505,Boyle,811,Germany,Female,34,1,149297.19,2,1,1,186339.74,0 +274,15725166,Newton,707,France,Male,30,8,0,2,1,0,33159.37,0 +275,15800116,Bowman,712,Germany,Male,28,4,145605.44,1,0,1,93883.53,0 +276,15758685,Dubinina,706,Spain,Female,37,7,0,2,1,1,110899.3,0 +277,15694456,Toscani,756,France,Male,62,3,0,1,1,1,11199.04,1 +278,15767339,Chiazagomekpere,777,France,Female,53,10,0,2,1,0,189992.97,0 +279,15683562,Allen,646,France,Male,35,6,84026.86,1,0,1,164255.69,0 +280,15782210,K'ung,714,France,Male,46,1,0,1,1,0,152167.79,1 +281,15668893,Wilsmore,782,France,Male,39,8,0,2,1,1,33949.67,0 +282,15669169,Hargreaves,775,Spain,Male,29,10,0,2,1,1,68143.93,0 +283,15643024,Huang,479,Germany,Male,35,4,138718.92,1,1,1,47251.79,1 +284,15699389,Ch'ien,807,France,Male,42,7,118274.71,1,1,1,25885.72,0 +285,15708608,Wallwork,799,France,Female,22,8,174185.98,2,0,1,192633.85,0 +286,15626144,Chu,675,France,Male,40,7,113208.86,2,1,0,34577.36,0 +287,15573112,Kang,602,Spain,Male,29,5,103907.28,1,1,0,161229.84,0 +288,15790678,Davidson,475,France,Female,32,8,119023.28,1,1,0,100816.29,0 +289,15727556,O'Donnell,744,Spain,Female,26,5,166297.89,1,1,1,181694.44,0 +290,15697307,Nnachetam,588,Spain,Male,34,10,0,2,1,0,79078.91,0 +291,15652266,Chidiebele,703,Germany,Male,42,9,63227,1,0,1,137316.32,0 +292,15607098,Ahmed,747,Spain,Female,41,5,94521.17,2,1,0,194926.86,0 +293,15655774,Booth,583,France,Male,27,7,0,2,1,0,51285.49,0 +294,15590241,Chuang,750,Spain,Female,34,9,112822.26,1,0,0,150401.53,1 +295,15785819,Shao,681,France,Male,38,3,0,2,1,1,112491.96,0 +296,15723654,Tsao,773,France,Male,25,2,135903.33,1,1,0,73656.38,0 +297,15774510,Tien,714,France,Female,31,4,125169.26,1,1,1,106636.89,0 +298,15684173,Chang,687,Spain,Female,44,7,0,3,1,0,155853.52,1 +299,15650068,Johnson,511,France,Male,58,0,149117.31,1,1,1,162599.51,0 +300,15811490,French,627,France,Male,33,5,0,2,1,1,103737.82,0 +301,15803976,Efremov,694,France,Female,31,10,0,2,1,0,160990.27,0 +302,15682541,Hartley,616,Spain,Female,36,6,132311.71,1,0,0,15462.84,0 +303,15695699,Calabrese,687,France,Male,35,8,0,2,1,0,10334.05,0 +304,15624188,Chiu,712,France,Female,33,6,0,2,1,1,190686.16,0 +305,15812191,Brennan,553,France,Male,33,4,118082.89,1,0,0,94440.45,0 +306,15636673,Onwuatuegwu,667,France,Male,31,1,119266.69,1,1,1,28257.63,0 +307,15594898,Hewitt,731,France,Male,43,2,0,1,1,1,170034.95,1 +308,15660211,Shih,629,Germany,Male,35,7,156847.29,2,1,0,31824.29,0 +309,15773972,Balashov,614,France,Male,50,4,137104.47,1,1,0,127166.49,1 +310,15746726,Doyle,438,Germany,Male,31,8,78398.69,1,1,0,44937.01,0 +311,15712287,Pokrovskii,652,France,Female,80,4,0,2,1,1,188603.07,0 +312,15702919,Collins,729,Germany,Male,30,6,63669.42,1,1,0,145111.37,0 +313,15674398,Russo,642,France,Male,38,3,0,2,0,0,171463.83,0 +314,15797960,Skinner,806,Germany,Female,59,0,135296.33,1,1,0,182822.5,0 +315,15631868,Robertson,744,Spain,Male,36,2,153804.44,1,1,1,87213.33,0 +316,15581539,Atkinson,474,Spain,Male,37,3,0,2,0,0,57175.32,0 +317,15662736,Doyle,559,France,Male,49,2,147069.78,1,1,0,120540.83,1 +318,15666252,Ritchie,706,Spain,Male,42,9,0,2,1,1,28714.34,0 +319,15677512,McEncroe,628,Spain,Female,22,3,0,1,1,0,85426.28,0 +320,15626114,Pearson,429,France,Male,24,4,95741.75,1,1,0,46170.75,0 +321,15810834,Gordon,525,Spain,Female,57,2,145965.33,1,1,1,64448.36,0 +322,15678910,Ts'ai,680,France,Female,30,8,141441.75,1,1,1,16278.97,0 +323,15694408,Lung,749,France,Male,40,1,139290.41,1,1,0,182855.42,1 +324,15585215,Yuan,763,France,Female,31,4,0,2,0,0,50404.72,0 +325,15682757,Pardey,734,France,Male,30,3,0,2,1,0,107640.25,0 +326,15736601,Tai,716,France,Male,35,4,144428.87,1,1,0,134132.65,0 +327,15601848,Scott,594,France,Male,35,2,0,2,1,0,103480.69,0 +328,15736008,Hunter,644,France,Female,46,9,95441.27,1,1,0,108761.05,1 +329,15669064,Mazzanti,671,Germany,Male,35,1,144848.74,1,1,1,179012.3,0 +330,15624528,L?,664,Germany,Male,26,7,116244.14,2,1,1,95145.14,0 +331,15598493,Beach,656,France,Male,50,7,0,2,0,1,72143.44,0 +332,15601274,Hsieh,667,Spain,Female,40,1,146502.07,1,1,0,19162.89,0 +333,15702669,Faulkner,663,Germany,Male,44,2,117028.6,2,0,1,144680.18,0 +334,15728669,Knowles,584,Germany,Female,30,8,112013.81,1,1,0,177772.03,1 +335,15742668,Day,626,Spain,Female,37,6,108269.37,1,1,0,5597.94,0 +336,15697441,Hsueh,485,France,Male,29,7,182123.79,1,1,0,116828.51,1 +337,15740476,Tsao,659,Germany,Female,32,3,150923.74,2,0,1,174652.51,0 +338,15648064,Kennedy,649,France,Male,33,2,0,2,1,0,2010.98,0 +339,15636624,Nwabugwu,805,Spain,Female,39,5,165272.13,1,1,0,14109.85,1 +340,15807923,Young,716,Germany,Female,39,10,115301.31,1,1,0,43527.4,1 +341,15745844,Kerr,642,Germany,Female,40,6,129502.49,2,0,1,86099.23,1 +342,15786170,Tien,659,France,Male,31,4,118342.26,1,0,0,161574.19,0 +343,15681081,Marrero,545,Spain,Female,47,5,0,2,1,1,38970.14,0 +344,15684484,White,543,France,Male,22,8,0,2,0,0,127587.22,0 +345,15785869,Pisano,718,France,Female,25,7,0,2,1,0,30380.12,0 +346,15763859,Brown,840,France,Female,43,7,0,2,1,0,90908.95,0 +347,15658935,Freeman,630,Germany,Female,34,9,106937.05,2,1,0,138275.01,0 +348,15747358,Russell,643,Germany,Male,59,3,170331.37,1,1,1,32171.79,0 +349,15735203,Seleznyov,654,Germany,Female,32,1,114510.85,1,1,1,126143.23,0 +350,15576256,Yusupova,582,France,Male,39,5,0,2,1,1,129892.93,0 +351,15659420,Foley,659,Spain,Male,32,3,107594.11,2,1,1,102416.84,0 +352,15593365,Shih,762,Spain,Male,39,2,81273.13,1,1,1,18719.67,0 +353,15777352,Ikedinachukwu,568,Spain,Female,32,7,169399.6,1,1,0,61936.22,0 +354,15812007,Power,670,Spain,Male,25,6,0,2,1,1,78358.94,0 +355,15625461,Amos,613,France,Female,45,1,187841.99,2,1,1,147224.27,0 +356,15739438,Reed,539,France,Male,30,0,0,2,1,0,160979.66,0 +357,15611759,Simmons,850,Spain,Female,57,8,126776.3,2,1,1,132298.49,0 +358,15661629,Ricci,522,Spain,Male,34,9,126436.29,1,1,0,174248.52,1 +359,15633950,Yen,737,France,Male,41,1,101960.74,1,1,1,123547.28,0 +360,15592386,Campbell,520,France,Male,58,3,0,2,0,1,32790.02,0 +361,15803716,West,706,Spain,Male,28,3,0,2,0,1,181543.67,0 +362,15696674,Robinson,643,Germany,Female,45,2,150842.93,1,0,1,2319.96,1 +363,15706365,Bianchi,648,France,Female,50,9,102535.57,1,1,1,189543.19,0 +364,15745088,Chen,443,Germany,Female,29,9,99027.61,2,1,0,10940.4,0 +365,15676715,Madukaego,640,France,Male,68,9,0,2,1,1,199493.38,0 +366,15613085,Ibrahimova,628,Spain,Female,33,3,0,1,1,1,188193.25,0 +367,15633537,Nolan,540,Germany,Female,42,9,87271.41,2,1,0,172572.64,0 +368,15594720,Scott,460,Germany,Female,35,8,102742.91,2,1,1,189339.6,0 +369,15684042,Blair,636,Germany,Male,34,2,40105.51,2,0,1,53512.16,0 +370,15583303,Monaldo,593,France,Female,29,2,152265.43,1,1,0,34004.44,0 +371,15611579,Sutherland,801,Spain,Male,42,4,141947.67,1,1,1,10598.29,0 +372,15774696,Cole,640,Germany,Female,75,1,106307.91,2,0,1,113428.77,0 +373,15694506,Briggs,611,Germany,Male,31,0,107884.81,2,1,1,183487.98,0 +374,15688074,Gregory,802,Germany,Male,31,1,125013.72,1,1,1,187658.09,0 +375,15759537,Bianchi,717,Germany,Male,35,7,58469.37,2,1,1,172459.39,0 +376,15758449,Angelo,769,France,Female,39,8,0,1,0,1,21016,0 +377,15583456,Gardiner,745,Germany,Male,45,10,117231.63,3,1,1,122381.02,1 +378,15667871,Kerr,572,Spain,Male,35,4,152390.26,1,1,0,128123.66,0 +379,15677371,Ko,629,Spain,Female,30,2,34013.63,1,1,0,19570.63,0 +380,15629677,Distefano,687,Spain,Female,39,2,0,3,0,0,188150.6,1 +381,15713578,Farrell,483,France,Female,50,9,0,2,1,1,111020.24,0 +382,15591509,Milano,690,France,Male,36,7,101583.11,2,1,0,123775.15,0 +383,15568240,Ting,492,Germany,Female,30,10,77168.87,2,0,1,146700.22,0 +384,15622993,Boyd,709,Germany,Male,28,8,124695.72,2,1,0,145251.35,0 +385,15689294,Onyemaechi,705,Germany,Male,44,3,105934.96,1,1,0,82463.69,0 +386,15720910,Black,560,France,Female,66,9,0,1,1,1,15928.49,0 +387,15721181,Oliver,611,Spain,Male,46,6,0,2,1,0,45886.33,0 +388,15776433,Greco,730,Spain,Male,62,2,0,2,1,1,186489.95,0 +389,15748936,Whitehead,709,Spain,Female,45,2,0,2,0,1,162922.65,0 +390,15717225,Ikemefuna,544,France,Female,21,10,161525.96,2,1,0,9262.77,0 +391,15685226,Morrison,712,Germany,Female,29,7,147199.07,1,1,1,84932.4,0 +392,15785611,Onyeoruru,752,Germany,Male,38,3,183102.29,1,1,1,71557.12,0 +393,15573456,Cunningham,648,Spain,Male,46,9,127209,2,1,0,77405.95,1 +394,15684548,Demidov,556,Spain,Male,38,8,0,2,0,0,417.41,1 +395,15620505,Celis,594,Spain,Female,24,0,97378.54,1,1,1,71405.17,0 +396,15807432,Cheng,645,Germany,Female,37,2,136925.09,2,0,1,153400.24,0 +397,15584766,Knight,557,France,Male,33,3,54503.55,1,1,1,371.05,0 +398,15612187,Morin,547,Germany,Male,32,8,155726.85,1,1,0,67789.99,0 +399,15762218,Mills,701,France,Female,39,9,0,2,0,1,145894.9,0 +400,15646372,Outhwaite,616,France,Female,66,1,135842.41,1,1,0,183840.51,1 +401,15690452,Tung,605,France,Male,52,1,63349.75,1,1,0,108887.44,0 +402,15747795,Pai,593,Germany,Female,38,4,129499.42,1,1,1,154071.27,0 +403,15781589,Carpenter,751,Spain,Male,52,8,0,2,0,1,179291.85,0 +404,15732674,Fennell,443,Spain,Male,36,6,70438.01,2,0,1,56937.43,0 +405,15642291,Fontaine,685,France,Male,23,8,0,2,1,1,112239.03,0 +406,15692761,Pratt,718,France,Male,36,9,0,1,1,0,45909.87,0 +407,15578045,Mitchell,538,Spain,Female,49,9,141434.04,1,0,0,173779.25,1 +408,15745354,Franklin,611,Spain,Female,37,4,0,2,1,0,125696.26,0 +409,15701376,K'ung,668,Germany,Male,37,10,152958.29,2,1,1,159585.61,0 +410,15691625,Ko,537,Germany,Female,41,3,138306.34,1,1,0,106761.47,0 +411,15566594,McKenzie,709,Spain,Male,23,10,0,2,0,0,129590.18,0 +412,15760431,Pino,850,France,Male,38,1,0,2,1,1,80006.65,0 +413,15686302,Fisk,745,Spain,Female,31,3,124328.84,1,1,1,140451.52,0 +414,15801559,Chiang,693,Germany,Female,41,9,181461.48,3,1,1,187929.43,1 +415,15810432,Moseley,795,Spain,Male,35,8,0,2,1,0,167155.36,0 +416,15809616,Hsiung,626,Spain,Male,26,8,0,2,0,0,191420.71,0 +417,15720559,Heath,487,Germany,Female,61,5,110368.03,1,0,0,11384.45,1 +418,15695632,Dellucci,556,France,Female,39,9,89588.35,1,1,1,94898.1,0 +419,15659843,Li,643,France,Female,46,6,0,2,0,0,106781.59,0 +420,15615624,De Salis,605,France,Female,28,6,0,2,0,0,159508.52,0 +421,15810418,T'ang,756,Germany,Female,60,3,115924.89,1,1,0,93524.19,1 +422,15716186,Richardson,586,France,Female,38,2,0,2,1,0,87168.46,0 +423,15674551,Fitch,535,Germany,Male,40,7,111756.5,1,1,0,8128.32,1 +424,15622834,Stevenson,678,France,Female,35,4,0,1,1,0,125518.32,0 +425,15566111,Estes,596,France,Male,39,9,0,1,1,0,48963.59,0 +426,15784597,Lattimore,648,France,Male,26,9,162923.85,1,1,0,98368.24,0 +427,15652883,Chung,492,Germany,Male,39,10,124576.65,2,1,0,148584.61,0 +428,15806964,Utz,702,France,Male,45,0,80793.58,1,1,1,27474.81,0 +429,15576313,Wei,486,Germany,Female,40,9,71340.09,1,1,0,76192.21,0 +430,15806467,Boyle,568,Germany,Male,40,1,99282.63,1,0,0,134600.94,1 +431,15597602,Nwachinemelu,619,Germany,Male,57,3,137946.39,1,1,1,72467.99,1 +432,15743040,Kuznetsova,724,Germany,Male,41,2,127892.57,2,0,1,199645.45,0 +433,15705521,Pisani,548,Germany,Female,33,0,101084.36,1,1,0,42749.85,0 +434,15595039,Manna,545,Germany,Female,37,8,114754.08,1,1,0,136050.44,1 +435,15799384,Collier,683,France,Male,33,8,0,1,0,0,73564.44,0 +436,15581197,Ricci,762,France,Female,51,3,99286.98,1,0,1,85578.63,0 +437,15693737,Carr,627,Germany,Female,30,4,79871.02,2,1,0,129826.89,0 +438,15624623,Hs?,516,France,Male,35,10,104088.59,2,0,0,119666,0 +439,15783501,Findlay,800,France,Female,38,2,168190.33,2,1,0,68052.08,0 +440,15690134,Hughes,464,Germany,Female,42,3,85679.25,1,1,1,164104.74,0 +441,15782735,Chukwuemeka,626,France,Female,35,3,0,1,0,0,80190.36,0 +442,15611088,Genovese,790,France,Female,31,9,0,2,1,0,84126.75,0 +443,15672145,Swift,534,France,Female,34,7,121551.58,2,1,1,70179,0 +444,15732628,Ugoji,745,France,Male,46,2,122220.19,1,1,1,118024.1,0 +445,15787470,Parkinson,553,Spain,Male,47,3,116528.15,1,0,0,145704.19,1 +446,15803406,Ross,748,France,Female,26,1,77780.29,1,0,1,183049.41,0 +447,15730460,Oleary,722,France,Male,37,2,0,1,0,0,120906.83,0 +448,15644572,Turnbull,501,France,Male,40,4,125832.2,1,1,1,100433.83,0 +449,15694860,Uspensky,675,France,Female,38,6,68065.8,1,0,0,138777,1 +450,15658169,Cook,778,Spain,Female,47,6,127299.34,2,1,0,124694.99,0 +451,15794396,Newbold,494,Germany,Female,38,7,174937.64,1,1,0,40084.32,0 +452,15785798,Uchechukwu,850,France,Male,40,9,0,2,0,1,119232.33,0 +453,15710825,Ch'en,592,Spain,Male,31,7,110071.1,1,0,0,43921.36,0 +454,15668444,He,590,Spain,Female,44,3,139432.37,1,1,0,62222.81,0 +455,15726631,Hilton,758,France,Female,39,6,127357.76,1,0,1,56577,0 +456,15733797,Sal,506,France,Male,36,5,0,2,1,0,164253.35,0 +457,15747960,Eluemuno,733,France,Male,33,3,0,1,1,1,7666.73,0 +458,15634632,Titus,711,France,Male,38,3,0,2,1,0,68487.51,0 +459,15707362,Yin,514,Germany,Male,43,1,95556.31,1,0,1,199273.98,1 +460,15662976,Lettiere,637,Spain,Male,37,8,0,1,1,1,186062.36,0 +461,15732778,Templeman,468,Germany,Male,29,1,111681.98,2,1,1,195711.16,0 +462,15718443,Chibuzo,539,France,Male,39,3,0,2,1,0,36692.17,0 +463,15670039,Sun,509,Spain,Female,25,3,108738.71,2,1,0,106920.57,0 +464,15773792,Evans,662,France,Female,32,4,133950.37,1,1,1,48725.68,1 +465,15613786,Ogbonnaya,818,Spain,Male,26,4,0,2,1,1,167036.94,0 +466,15726032,Enyinnaya,608,France,Male,33,9,89968.69,1,1,0,68777.26,0 +467,15663252,Olisanugo,850,Spain,Female,32,9,0,2,1,1,18924.92,0 +468,15593782,Brookes,816,Germany,Female,38,5,130878.75,3,1,0,71905.77,1 +469,15633283,Padovano,536,France,Male,35,8,0,2,1,0,64833.28,0 +470,15749167,Fisk,753,France,Male,35,3,0,2,1,1,184843.77,0 +471,15759298,Shih,631,Spain,Male,27,10,134169.62,1,1,1,176730.02,0 +472,15683625,Hare,703,France,Male,37,1,149762.08,1,1,0,20629.4,1 +473,15635367,Muir,774,France,Male,26,2,93844.69,1,1,0,28415.36,0 +474,15681705,Fanucci,785,France,Male,28,8,0,2,1,0,77231.27,0 +475,15603156,Elewechi,571,France,Female,33,1,0,2,1,0,102750.7,0 +476,15591986,Johnston,621,Germany,Male,46,6,141078.37,1,0,0,34580.8,1 +477,15798888,Pisano,605,Germany,Female,31,1,117992.59,1,1,1,183598.77,0 +478,15809722,Ankudinov,611,France,Female,40,8,100812.33,2,1,0,147358.27,0 +479,15677538,Nwokike,569,France,Male,38,7,0,1,1,1,108469.2,0 +480,15797736,Smith,658,France,Male,29,4,80262.6,1,1,1,20612.82,0 +481,15695585,Atkins,788,Spain,Male,34,6,156478.62,1,0,1,181196.76,0 +482,15744398,Burns,525,France,Female,23,5,0,2,1,0,160249.1,0 +483,15750658,Obiuto,798,France,Male,37,8,0,3,0,0,110783.28,0 +484,15578186,Pirozzi,486,Germany,Male,37,9,115217.99,2,1,0,144995.33,0 +485,15676519,George,615,Spain,Male,61,9,0,2,1,0,150227.85,1 +486,15637954,Lewis,730,France,Female,35,0,155470.55,1,1,1,53718.28,0 +487,15758639,Moran,641,France,Male,37,7,0,2,1,0,75248.3,0 +488,15613772,Dalrymple,542,France,Male,39,3,135096.77,1,1,1,14353.43,1 +489,15731744,Carslaw,692,France,Male,30,2,0,2,0,1,130486.57,0 +490,15807709,Kirby,714,Germany,Female,55,9,180075.22,1,1,1,100127.71,0 +491,15714689,Houghton,591,Spain,Male,29,1,97541.24,1,1,1,196356.17,0 +492,15699005,Martin,710,France,Female,41,2,156067.05,1,1,1,9983.88,0 +493,15624170,Tan,639,France,Female,38,4,81550.94,2,0,1,118974.77,0 +494,15725679,Hsia,531,France,Female,47,6,0,1,0,0,194998.34,1 +495,15585865,Westerberg,673,France,Female,38,2,170061.92,2,0,0,134901.34,1 +496,15804256,Hale,765,Germany,Male,36,8,92310.54,2,1,1,72924.56,0 +497,15662403,Kryukova,622,France,Female,32,6,169089.38,2,1,0,101057.95,0 +498,15733616,Sopuluchukwu,806,France,Male,40,5,80613.93,1,1,1,142838.64,0 +499,15591995,Barry,757,Germany,Male,26,8,121581.56,2,1,1,127059.04,0 +500,15677020,Selezneva,570,France,Female,58,8,0,1,0,1,116503.92,1 +501,15727688,Chizuoke,555,Spain,Male,32,4,0,2,1,1,54405.79,0 +502,15715941,Lueck,692,France,Male,54,5,0,2,1,1,88721.84,0 +503,15714485,Udinese,774,France,Male,60,5,85891.55,1,1,0,74135.48,1 +504,15730059,Udobata,638,Spain,Male,44,9,77637.35,2,1,1,111346.22,0 +505,15715527,Freeman,543,Spain,Female,41,4,0,1,0,0,194902.16,0 +506,15576623,Outlaw,584,France,Male,31,5,0,2,1,0,31474.27,0 +507,15805565,Obiuto,691,Germany,Male,30,7,116927.89,1,1,0,21198.39,0 +508,15677307,Lo,684,Germany,Female,40,6,137326.65,1,1,0,186976.6,0 +509,15773890,Okechukwu,733,France,Male,22,5,0,2,1,1,117202.19,0 +510,15598883,King,599,Spain,Female,37,2,0,2,1,1,143739.29,0 +511,15568506,Forbes,524,Germany,Female,31,10,67238.98,2,1,1,161811.23,0 +512,15761043,Macleod,632,Germany,Female,38,6,86569.76,2,1,0,98090.91,0 +513,15782236,Gibbs,735,Spain,Male,34,5,0,2,0,0,71095.41,0 +514,15593601,Isayev,734,France,Male,34,6,133598.4,1,1,1,13107.24,0 +515,15682048,Pisano,605,France,Female,51,3,136188.78,1,1,1,67110.59,1 +516,15746902,Belstead,793,Spain,Male,38,9,0,2,1,0,88225.02,0 +517,15752081,Vassiliev,468,France,Female,56,10,0,3,0,1,62256.87,1 +518,15781307,Schneider,779,Germany,Male,37,7,120092.52,2,1,0,135925.72,0 +519,15775912,Mazzanti,698,France,Male,48,4,101238.24,2,0,1,177815.87,1 +520,15745417,Knipe,707,France,Male,58,6,89685.92,1,0,1,126471.13,0 +521,15671256,Macartney,850,France,Female,35,1,211774.31,1,1,0,188574.12,1 +522,15653547,Madukwe,850,France,Male,56,7,131317.48,1,1,1,119175.45,0 +523,15595766,Watts,527,Spain,Male,37,5,93722.73,2,1,1,139093.73,0 +524,15742358,Humphreys,696,Germany,Male,32,8,101160.99,1,1,1,115916.55,0 +525,15763274,Wu,661,France,Male,48,3,120320.54,1,0,0,96463.25,0 +526,15786063,Chin,776,France,Female,31,2,0,2,1,1,112349.51,0 +527,15600258,Chesnokova,701,France,Male,43,2,0,2,1,1,165303.79,0 +528,15573318,Kung,610,France,Male,26,8,0,2,1,0,166031.08,0 +529,15653849,Lu,572,Germany,Female,48,3,152827.99,1,1,0,38411.79,1 +530,15694272,Nkemakolam,673,France,Male,30,1,64097.75,1,1,1,77783.35,0 +531,15736112,Walton,519,Spain,Female,57,2,119035.35,2,1,1,29871.79,0 +532,15749851,Brookes,702,Spain,Female,26,4,135219.57,1,0,1,59747.63,0 +533,15663478,Baldwin,729,France,Male,32,6,93694.42,1,1,1,79919.13,0 +534,15592300,Mai,543,Spain,Male,35,10,59408.63,1,1,0,76773.53,0 +535,15567832,Shih,550,France,Female,40,7,114354.95,1,1,0,54018.93,0 +536,15776780,He,608,France,Male,59,1,0,1,1,0,70649.64,1 +537,15592846,Fiorentini,639,Germany,Male,35,10,128173.9,2,1,0,59093.39,0 +538,15739803,Lucciano,686,Spain,Male,34,9,0,2,1,0,127569.8,0 +539,15794142,Ferreira,564,Germany,Female,62,5,114931.35,3,0,1,18260.98,1 +540,15762729,Ukaegbunam,745,Germany,Female,28,1,111071.36,1,1,0,73275.96,1 +541,15667896,De Luca,833,France,Male,37,8,151226.18,2,1,1,136129.49,0 +542,15626578,Milne,622,France,Male,26,9,0,2,1,1,153237.59,0 +543,15776223,Davide,597,France,Female,42,4,64740.12,1,1,1,106841.12,0 +544,15705953,Kodilinyechukwu,721,Spain,Male,51,0,169312.13,1,1,0,109078.35,1 +545,15802593,Little,504,France,Female,49,7,0,3,0,1,87822.14,1 +546,15615457,Burns,842,Spain,Female,44,2,112652.08,2,1,0,126644.98,0 +547,15708916,Paterson,587,France,Male,38,0,0,2,1,0,47414.15,0 +548,15720187,Han,479,Germany,Female,30,7,143964.36,2,1,0,41879.99,0 +549,15595440,Kryukova,508,France,Male,49,7,122451.46,2,1,1,75808.1,0 +550,15600651,Ijendu,749,France,Male,24,1,0,3,1,1,47911.03,0 +551,15750141,Reichard,721,Germany,Female,36,3,65253.07,2,1,0,28737.78,0 +552,15657284,Day,674,Germany,Male,47,6,106901.94,1,1,1,2079.2,1 +553,15763063,Price,685,Spain,Female,25,10,128509.63,1,1,0,121562.33,0 +554,15709324,Bruce,417,France,Male,34,7,0,2,1,0,55003.79,0 +555,15711309,Sumrall,574,Germany,Male,33,3,129834.67,1,1,0,193131.42,0 +556,15775318,Lu,590,Spain,Female,51,3,154962.99,3,0,1,191932.27,1 +557,15705515,Lazarev,587,Germany,Male,40,5,138241.9,2,1,0,159418.1,0 +558,15634844,Miller,598,Germany,Male,41,3,91536.93,1,1,0,191468.78,1 +559,15717046,Wentworth-Shields,741,Spain,Male,53,3,0,2,1,1,38913.68,0 +560,15571816,Ritchie,850,Spain,Female,70,5,0,1,1,1,705.18,0 +561,15670080,Mackenzie,584,Germany,Female,29,7,105204.01,1,0,1,138490.03,0 +562,15800440,Power,650,Spain,Male,61,1,152968.73,1,0,1,82970.69,0 +563,15665678,Tan,607,Spain,Male,36,8,158261.68,1,1,1,76744.72,0 +564,15665956,Pendergrass,509,France,Female,46,1,0,1,1,0,71244.59,1 +565,15788126,Evans,689,Spain,Female,38,6,121021.05,1,1,1,12182.15,0 +566,15811773,Hsia,543,France,Male,36,4,0,2,1,1,141210.5,0 +567,15651674,Billson,438,Spain,Female,54,2,0,1,0,0,191763.07,1 +568,15689614,Teng,687,Spain,Female,63,1,137715.66,1,1,1,37938.74,0 +569,15795564,Moretti,737,Germany,Male,31,5,121192.22,2,1,1,74890.58,0 +570,15706647,Jordan,761,France,Male,31,7,0,3,1,1,166698.18,0 +571,15728505,Ts'ao,601,France,Male,44,1,100486.18,2,1,1,62678.53,0 +572,15730076,Osborne,651,France,Male,45,1,0,1,1,0,67740.08,1 +573,15622003,Carslaw,745,France,Male,35,9,92566.53,2,1,0,161519.77,0 +574,15607312,Ch'ang,648,Spain,Female,49,10,0,2,1,1,159835.78,1 +575,15644753,Hung,848,Spain,Male,40,3,110929.96,1,1,1,30876.84,0 +576,15653620,Gordon,546,France,Female,27,8,0,2,1,1,14858.1,0 +577,15761986,Obialo,439,Spain,Female,32,3,138901.61,1,1,0,75685.97,0 +578,15633922,Gray,755,France,Male,30,4,123217.66,2,0,1,144183.1,0 +579,15734674,Lin,593,France,Female,41,6,0,1,1,0,65170.66,0 +580,15658032,Hopkins,701,France,Male,39,2,0,2,1,1,82526.92,0 +581,15692671,Dobson,701,Spain,Male,36,8,0,2,1,0,169161.46,0 +582,15737741,McKay,607,Spain,Female,33,2,108431.87,2,0,1,109291.39,1 +583,15576352,Revell,586,Spain,Female,57,3,0,2,0,1,6057.81,0 +584,15753719,Rickards,547,Germany,Female,30,9,72392.41,1,1,0,77077.14,0 +585,15803689,Begum,647,Germany,Female,51,1,119741.77,2,0,0,54954.51,1 +586,15718057,Onyinyechukwuka,760,France,Female,51,2,100946.71,1,0,0,179614.8,1 +587,15722010,Zuyev,621,Spain,Male,53,9,170491.84,1,1,0,35588.07,1 +588,15680998,Nwankwo,725,France,Male,44,5,0,1,1,1,117356.14,0 +589,15614782,Hao,526,France,Male,36,1,0,1,1,0,160696.72,0 +590,15591047,Ma,519,Spain,Female,47,6,157296.02,2,0,0,147278.43,1 +591,15788291,Okwuadigbo,713,Germany,Female,38,7,144606.22,1,1,1,56594.36,1 +592,15604044,Mitchell,700,France,Male,38,8,134811.3,1,1,0,1299.75,0 +593,15679587,Chan,666,France,Female,34,9,115897.12,1,1,1,25095.03,0 +594,15775153,Buchi,630,Spain,Male,32,4,82034,1,0,0,146326.45,0 +595,15603925,Greco,779,Spain,Female,26,4,174318.13,2,0,1,38296.21,0 +596,15680970,Lombardi,611,Germany,Female,41,2,114206.84,1,1,0,164061.6,0 +597,15697183,Uchenna,685,Spain,Male,43,9,0,2,1,0,107811.28,0 +598,15567446,Coffman,646,Germany,Male,39,9,111574.41,1,1,1,30838.51,0 +599,15637476,Alexandrova,683,Germany,Female,57,5,162448.69,1,0,0,9221.78,1 +600,15714939,Fallaci,484,Germany,Female,34,4,148249.54,1,0,1,33738.27,0 +601,15683503,Hudson,601,France,Female,43,8,0,3,0,1,110916.15,1 +602,15645569,Mai,762,Spain,Female,26,7,123709.46,2,1,1,169654.57,0 +603,15782569,Stout,687,France,Female,72,9,0,1,0,1,69829.4,0 +604,15592387,Burke,566,France,Male,30,5,0,1,1,0,54926.51,1 +605,15609286,Chadwick,702,France,Male,37,10,150525.8,1,1,1,94728.49,0 +606,15814035,Lawrence,601,France,Male,29,9,0,1,1,1,80393.27,0 +607,15661249,Bellucci,699,France,Male,53,4,0,2,0,1,111307.98,0 +608,15629117,Harper,584,France,Male,28,10,0,2,1,0,19834.32,0 +609,15607170,Boyle,699,France,Male,35,5,0,2,1,1,78397.24,0 +610,15586585,Duncan,698,Germany,Female,51,2,111018.98,1,1,0,86410.28,0 +611,15686611,Moss,495,France,Male,30,10,129755.99,1,0,0,172749.65,0 +612,15603203,Avdeyeva,650,France,Female,27,6,0,2,1,0,1002.39,0 +613,15619857,Crawford,605,France,Female,64,2,129555.7,1,1,1,13601.79,0 +614,15805062,Lynton,667,Spain,Male,38,1,87202.38,1,1,1,77866.91,0 +615,15660271,Duncan,688,Germany,Male,26,8,146133.39,1,1,1,175296.76,0 +616,15745295,Gether,727,Spain,Female,31,0,0,1,1,0,121751.04,1 +617,15719352,Davidson,754,Spain,Male,39,6,170184.99,2,1,0,89593.26,0 +618,15766575,Larionova,612,Germany,Female,62,8,140745.33,1,1,0,193437.89,1 +619,15594594,Loggia,546,Spain,Male,42,7,139070.51,1,1,1,86945,0 +620,15646161,Steinhoff,673,Spain,Female,37,8,0,2,1,1,183318.79,0 +621,15682585,Guerra,593,France,Male,35,9,114193.24,1,1,0,71154.1,0 +622,15603134,Pai,656,Spain,Female,40,10,167878.5,1,0,1,151887.16,0 +623,15636444,Craig,535,Germany,Female,53,5,141616.55,2,1,1,75888.65,0 +624,15773456,Lazareva,678,Germany,Male,36,3,145747.67,2,0,1,89566.74,0 +625,15745307,Ch'iu,477,Spain,Female,48,2,129120.64,1,0,1,26475.79,0 +626,15604119,Alderete,850,Spain,Male,35,7,110349.82,1,0,0,126355.8,0 +627,15626900,Kung,427,France,Male,29,1,141325.56,1,1,1,93839.3,0 +628,15605447,Palermo,752,France,Male,49,2,78653.84,1,1,0,7698.6,0 +629,15589030,Ts'ai,649,France,Male,47,1,0,2,1,1,145593.85,0 +630,15692463,Rahman,799,Spain,Female,28,3,142253.65,1,1,0,45042.56,0 +631,15712403,McMillan,589,France,Female,61,1,0,1,1,0,61108.56,1 +632,15811762,Pickering,583,Germany,Female,54,6,115988.86,1,1,0,57553.98,1 +633,15718673,Mirams,839,Spain,Female,33,10,75592.43,1,1,0,62674.42,0 +634,15724282,Tsao,540,Germany,Male,44,3,164113.04,2,1,1,12120.79,0 +635,15738181,Douglas,850,France,Male,31,6,67996.23,2,0,0,50129.87,1 +636,15633648,Jideofor,696,Spain,Female,51,5,0,2,1,0,55022.43,0 +637,15603323,Bell,660,Spain,Female,33,1,0,2,0,0,117834.91,0 +638,15583725,Mairinger,682,France,Male,48,1,138778.15,1,0,1,168840.23,0 +639,15588350,McIntyre,744,France,Female,43,10,147832.15,1,0,1,24234.11,0 +640,15798398,Pagnotto,785,France,Female,36,4,135438.4,1,0,0,190627.01,0 +641,15784844,K'ung,752,Spain,Male,48,5,116060.08,1,1,0,156618.38,1 +642,15580684,Feng,706,France,Female,29,5,112564.62,1,1,0,42334.38,0 +643,15809663,Donaldson,583,France,Female,27,1,125406.58,1,1,1,110784.42,0 +644,15640078,Chambers,660,Germany,Female,39,5,135134.99,1,1,0,173683,1 +645,15698786,Marcelo,819,France,Female,39,9,133102.92,1,1,0,27046.46,1 +646,15569807,Ejimofor,673,France,Female,34,8,42157.08,1,1,0,20598.59,1 +647,15730830,Dale,752,France,Female,30,3,0,2,1,1,104991.28,0 +648,15805112,Pokrovsky,578,France,Male,38,7,82259.29,1,1,0,8996.97,0 +649,15633064,Stonebraker,438,France,Female,36,4,0,2,1,0,64420.5,0 +650,15703119,Liang,652,France,Male,38,6,0,2,1,1,145700.22,0 +651,15730447,Anderson,629,France,Female,49,4,0,2,1,1,196335.48,0 +652,15813850,Christian,720,France,Male,52,7,0,1,1,1,14781.12,0 +653,15711889,Mao,668,France,Male,42,3,150461.07,1,1,0,108139.23,0 +654,15664610,Campbell,459,Germany,Male,48,4,133994.52,1,1,1,19287.06,1 +655,15751710,Ginikanwa,729,Spain,Male,31,8,164870.81,2,1,1,9567.39,0 +656,15692926,Toscani,498,Germany,Male,25,8,121702.73,1,1,1,132210.49,0 +657,15813741,Nnachetam,549,Spain,Male,25,6,193858.2,1,0,1,21600.11,0 +658,15698474,Sagese,601,Germany,Female,54,1,131039.97,2,1,1,199661.5,0 +659,15568595,Fleming,544,France,Male,64,9,113829.45,1,1,1,124341.49,0 +660,15603065,Grubb,751,France,Female,30,6,0,2,1,0,15766.1,0 +661,15592937,Napolitani,632,Germany,Female,41,3,81877.38,1,1,1,33642.21,0 +662,15699637,Anenechi,694,Spain,Male,57,8,116326.07,1,1,1,117704.65,0 +663,15667215,Chandler,678,France,Male,31,2,0,2,1,1,58803.28,0 +664,15788659,Howells,695,France,Male,46,4,0,2,1,1,137537.22,0 +665,15763218,Akeroyd,661,France,Female,41,1,0,2,0,1,131300.68,0 +666,15645772,Onwumelu,661,France,Male,33,9,0,2,1,1,84174.81,0 +667,15725511,Wallace,559,France,Female,31,3,127070.73,1,0,1,160941.78,0 +668,15575024,Uwaezuoke,503,France,Male,29,3,0,2,1,1,143954.99,0 +669,15640825,Loyau,695,Spain,Male,46,3,122549.64,1,1,1,56297.85,0 +670,15662397,Small,640,France,Female,42,5,176099.13,1,1,1,8404.73,0 +671,15576368,Bledsoe,624,Germany,Female,48,3,122388.38,2,0,0,30020.09,0 +672,15674991,Kao,667,France,Male,42,9,0,2,0,1,58137.42,0 +673,15721024,Wickens,642,France,Male,26,0,0,1,0,0,47472.68,0 +674,15745621,Wertheim,640,Spain,Female,32,6,118879.35,2,1,1,19131.71,0 +675,15642394,He,529,Spain,Male,35,5,0,2,1,1,187288.5,0 +676,15754605,Jarvis,563,France,Female,39,5,0,2,1,1,17603.81,0 +677,15607040,P'an,593,Spain,Female,38,4,88736.44,2,1,0,67020.03,0 +678,15715142,Repina,739,Germany,Male,45,7,102703.62,1,0,1,147802.94,1 +679,15810978,Pugliesi,788,Spain,Female,70,1,0,2,1,1,41610.62,0 +680,15668886,Blakey,684,Spain,Female,38,3,0,2,1,0,44255.65,0 +681,15780804,Nucci,482,France,Male,55,5,97318.25,1,0,1,78416.14,0 +682,15613880,Higinbotham,591,Spain,Male,58,5,128468.69,1,0,1,137254.55,0 +683,15775238,Achebe,651,Germany,Female,41,4,133432.59,1,0,1,151303.48,0 +684,15786905,Russo,749,Germany,Female,40,8,141782.57,2,0,0,86333.63,0 +685,15747867,Trevisani,583,France,Male,24,9,135125.28,1,0,0,89801.9,0 +686,15600337,Dobie,661,Spain,Male,42,2,178820.91,1,0,0,29358.57,1 +687,15801277,Maccallum,715,France,Female,31,2,112212.14,2,1,1,181600.72,0 +688,15579334,Watkins,769,Germany,Female,45,5,126674.81,1,1,0,124118.71,1 +689,15802741,Mitchel,625,France,Female,51,7,136294.97,1,1,0,38867.46,1 +690,15720649,Ferdinand,641,France,Female,36,5,66392.64,1,1,0,31106.67,0 +691,15589493,Otitodilinna,716,Germany,Male,27,1,122552.34,2,1,0,67611.36,0 +692,15688251,Mamelu,767,France,Male,43,1,76408.85,2,1,0,77837.63,0 +693,15665238,Beneventi,745,Germany,Male,36,8,145071.24,1,0,0,6078.46,0 +694,15740900,Perrodin,589,France,Male,34,6,0,2,1,1,177896.92,0 +695,15681068,Chinagorom,796,France,Female,45,2,109730.22,1,1,1,123882.73,0 +696,15748625,Napolitano,664,France,Male,57,6,0,2,1,1,15304.08,0 +697,15727299,Edgar,445,Spain,Male,62,1,64119.38,1,1,1,76569.64,1 +698,15620204,Walker,543,Germany,Female,57,1,106138.33,2,1,1,120657.32,1 +699,15669516,Steele,746,Spain,Male,36,2,0,2,1,1,16436.56,0 +700,15736534,Elkins,742,Germany,Male,33,0,181656.51,1,1,1,107667.91,0 +701,15803457,Hao,750,France,Female,32,5,0,2,1,0,95611.47,0 +702,15659098,Toscano,669,France,Male,30,7,95128.86,1,0,0,19799.26,0 +703,15603436,Savage,594,Spain,Female,49,2,126615.94,2,0,1,123214.74,0 +704,15566292,Okwuadigbo,574,Spain,Male,36,1,0,2,0,1,71709.12,0 +705,15808621,Mordvinova,659,Germany,Male,36,2,76190.48,2,1,1,149066.14,0 +706,15580148,Welch,750,Germany,Male,40,5,168286.81,3,1,0,20451.99,1 +707,15776231,Kent,626,Germany,Male,35,4,88109.81,1,1,1,32825.5,0 +708,15773809,Campbell,620,France,Male,42,4,0,2,1,0,6232.31,0 +709,15649423,Cooper,580,France,Female,35,8,0,2,0,1,10357.03,0 +710,15734886,Mazzi,686,France,Female,34,3,123971.51,2,1,0,147794.63,0 +711,15722548,Fisher,540,France,Male,48,0,148116.48,1,0,0,116973.48,0 +712,15650288,Summers,634,Germany,Male,35,6,116269.01,1,1,0,129964.94,0 +713,15629448,Brady,632,Spain,Male,38,1,120599.21,1,1,0,92816.86,0 +714,15716164,Nicholls,501,France,Female,41,3,144260.5,1,1,0,172114.67,0 +715,15807609,Yuan,650,Spain,Female,25,3,86605.5,3,1,0,16649.31,1 +716,15578977,Robinson,786,France,Male,34,9,0,2,1,0,144517.19,0 +717,15677369,Golubov,554,Germany,Female,37,4,58629.97,1,0,0,182038.6,0 +718,15804072,Chen,701,Spain,Female,42,5,0,2,0,0,24210.56,0 +719,15696859,Oldham,474,France,Male,45,10,0,2,0,0,172175.9,0 +720,15653780,Kambinachi,621,France,Female,43,5,0,1,1,1,47578.45,0 +721,15721658,Fleming,672,Spain,Female,56,2,209767.31,2,1,1,150694.42,1 +722,15578761,Cunningham,459,Spain,Female,42,6,129634.25,2,1,1,177683.02,1 +723,15736879,Obinna,669,France,Male,23,1,0,2,0,0,66088.83,0 +724,15571973,Chinwemma,776,France,Female,38,2,169824.46,1,1,0,169291.7,0 +725,15626742,Carpenter,694,France,Male,36,3,97530.25,1,1,1,117140.41,0 +726,15672692,Yin,787,France,Female,42,10,145988.65,2,1,1,79510.37,0 +727,15673570,Olsen,580,France,Male,37,9,0,2,0,1,77108.66,0 +728,15767432,Ts'ai,711,France,Female,25,7,0,3,1,1,9679.28,0 +729,15654238,Jen,673,France,Female,40,5,137494.28,1,1,0,81753.92,0 +730,15612525,Preston,499,France,Female,57,1,0,1,0,0,131372.38,1 +731,15812750,Ozioma,591,France,Male,24,6,147360,1,1,1,25310.82,0 +732,15790757,Cody,769,France,Female,25,10,0,2,0,0,187925.75,0 +733,15723873,Ponomarev,657,Spain,Male,31,3,125167.02,1,0,0,98820.39,0 +734,15744607,Martin,738,Germany,Male,43,9,121152.05,2,1,0,64166.7,1 +735,15612966,Milani,545,Germany,Female,60,7,128981.07,1,0,1,176924.21,1 +736,15784209,Tang,497,France,Male,47,6,0,1,1,1,90055.08,0 +737,15794278,Romani,816,Spain,Male,67,6,151858.98,1,1,1,72814.31,0 +738,15766741,McIntyre,525,France,Male,36,2,114628.4,1,0,1,168290.06,0 +739,15661036,Davis,725,France,Male,46,6,0,2,1,0,161767.38,0 +740,15705639,Onyemauchechukwu,692,France,Female,28,8,95059.02,2,1,0,44420.18,0 +741,15637414,Gell,618,France,Female,24,7,128736.39,1,0,1,37147.61,0 +742,15716835,Rossi,546,France,Male,24,8,156325.38,1,1,1,125381.02,0 +743,15696231,Chiwetelu,635,France,Male,29,7,105405.97,1,1,1,149853.89,0 +744,15641675,Kirillova,611,France,Female,49,2,88915.37,3,0,0,161435.02,1 +745,15670755,Shaw,650,France,Male,60,8,0,2,1,1,102925.76,0 +746,15640059,Smith,606,France,Male,40,5,0,2,1,1,70899.27,0 +747,15787619,Hsieh,844,France,Male,18,2,160980.03,1,0,0,145936.28,0 +748,15587535,Onyemauchechukwu,450,Spain,Female,46,5,177619.71,1,1,0,54227.06,0 +749,15813034,Martin,727,Spain,Male,38,2,62276.99,1,1,1,59280.79,0 +750,15698839,Okwudilichukwu,460,Germany,Male,46,4,127559.97,2,1,1,126952.5,0 +751,15790314,Onuoha,649,France,Male,41,0,0,2,0,1,130567.02,0 +752,15634245,Muecke,758,Germany,Female,47,9,95523.16,1,1,0,73294.48,0 +753,15677305,Hsieh,490,France,Female,35,7,107749.03,1,1,1,3937.37,0 +754,15661526,Anderson,815,Germany,Male,37,2,110777.26,2,1,0,2383.59,0 +755,15685997,Azubuike,838,Spain,Female,39,5,166733.92,2,1,0,14279.44,0 +756,15660101,Nnonso,803,France,Male,31,9,157120.86,2,1,0,141300.53,0 +757,15637979,Fuller,664,Germany,Female,36,2,127160.78,2,1,0,78140.75,0 +758,15815364,Ashley,736,Spain,Female,28,2,0,2,1,1,117431.1,0 +759,15647099,Ts'ui,633,France,Female,37,9,156091.97,1,1,0,72008.61,0 +760,15625944,Buccho,664,France,Male,58,5,98668.18,1,1,1,60887.58,0 +761,15583212,Chidozie,600,France,Female,43,5,134022.06,1,1,0,194764.83,0 +762,15582741,Maclean,693,France,Female,35,5,124151.09,1,1,0,88705.14,1 +763,15637876,Burns,663,Germany,Female,36,6,77253.5,1,0,0,35817.97,1 +764,15622750,Chu,742,Germany,Female,21,1,114292.48,1,1,0,31520.4,0 +765,15672056,Kenenna,710,Germany,Male,43,2,140080.32,3,1,1,157908.19,1 +766,15812351,Beluchi,710,Spain,Female,27,2,135277.96,1,1,0,142200.15,0 +767,15810864,Williamson,700,France,Female,82,2,0,2,0,1,182055.36,0 +768,15677921,Bobrov,720,Germany,Male,60,9,115920.62,2,0,0,157552.08,1 +769,15724296,Kerr,684,Spain,Male,41,2,119782.72,2,0,0,120284.67,0 +770,15685329,McKenzie,531,France,Female,63,1,114715.71,1,0,1,24506.95,1 +771,15584091,Pitts,742,Germany,Female,36,2,129748.54,2,0,0,47271.61,1 +772,15640442,Standish,717,France,Male,31,4,129722.57,1,0,0,41176.6,0 +773,15639314,Cartwright,589,France,Male,32,2,0,2,0,1,9468.64,0 +774,15685320,Johnstone,767,France,Male,36,3,139180.2,1,0,0,123880.19,0 +775,15789158,Nikitina,636,Germany,Male,49,6,113599.74,2,1,0,158887.09,1 +776,15752137,McElroy,648,France,Male,33,7,134944,1,1,1,117036.38,0 +777,15712551,Shen,622,Germany,Female,58,7,116922.25,1,1,0,120415.61,1 +778,15628936,Archer,692,Spain,Male,28,9,118945.09,1,0,0,16064.25,1 +779,15797227,Otutodilinna,754,France,Male,28,8,0,2,1,1,52615.62,0 +780,15769974,Shih,679,Spain,Female,35,8,119182.73,1,0,0,121210.09,0 +781,15737051,Denisov,639,France,Male,27,8,0,2,1,0,192247.35,0 +782,15585595,Owens,774,France,Female,28,1,71264.02,2,0,1,68759.57,0 +783,15654060,P'eng,517,France,Male,41,2,0,2,0,1,75937.47,0 +784,15745196,Verco,571,France,Female,35,8,0,2,0,0,84569.13,0 +785,15571221,Bergamaschi,747,Germany,Male,58,7,116313.57,1,1,1,190696.35,1 +786,15660155,Lorenzo,792,Spain,Male,36,5,92140.15,1,0,1,67468.67,0 +787,15605284,Outtrim,688,France,Male,26,1,0,2,1,1,104435.94,0 +788,15694366,Hou,714,Germany,Male,42,2,177640.09,1,0,1,47166.55,0 +789,15600739,Galkin,562,Spain,Female,35,0,0,2,1,0,119899.52,0 +790,15653253,Pagnotto,704,Spain,Male,48,8,167997.6,1,1,1,173498.45,0 +791,15763431,Echezonachukwu,698,France,Male,36,2,82275.35,2,1,1,93249.26,0 +792,15643696,Young,611,France,Male,49,3,0,2,1,1,142917.54,0 +793,15707473,Summers,850,Germany,Female,48,6,111962.99,1,1,0,111755.8,0 +794,15769504,Munro,743,Germany,Female,34,1,131736.88,1,1,1,108543.21,0 +795,15776807,Brennan,654,France,Male,29,1,0,1,1,0,180345.44,0 +796,15686870,Ball,761,Germany,Male,36,8,108239.11,2,0,0,99444.02,0 +797,15668747,Virgo,702,France,Female,46,9,98444.19,1,0,1,109563.28,0 +798,15766908,Trevisani,488,Germany,Male,32,3,114540.38,1,1,0,92568.07,0 +799,15570134,Padovano,683,France,Female,35,6,187530.66,2,1,1,37976.36,0 +800,15567367,Tao,601,Germany,Female,42,9,133636.16,1,0,1,103315.74,0 +801,15747542,Perez,605,France,Male,52,7,0,2,1,1,173952.5,0 +802,15762238,Fraser,671,Germany,Female,44,0,84745.03,2,0,1,34673.98,0 +803,15681554,Alley,614,Germany,Female,31,7,120599.38,2,1,1,46163.44,0 +804,15712825,Howells,511,Spain,Female,29,9,0,2,0,1,140676.98,0 +805,15640280,Cameron,850,France,Male,39,4,127771.35,2,0,1,151738.54,0 +806,15756026,Hooper,790,Spain,Female,46,9,0,1,0,0,14679.81,1 +807,15613319,Rice,793,France,Female,33,0,0,1,0,0,175544.02,0 +808,15798906,Cox,628,France,Male,69,5,0,2,1,1,181964.6,0 +809,15708917,Martin,598,Germany,Male,53,10,167772.96,1,1,1,136886.86,0 +810,15778463,Ikenna,657,France,Female,37,6,95845.6,1,1,0,122218.23,0 +811,15699430,Davide,618,France,Female,35,10,0,2,1,0,180439.75,0 +812,15649992,Alexander,681,Spain,Male,65,7,134714.7,2,0,1,190419.81,0 +813,15578980,Piazza,516,Spain,Female,33,3,0,2,1,1,58685.59,0 +814,15775306,Ni,421,Germany,Male,28,8,122384.22,3,1,1,89017.38,1 +815,15641655,Black,700,France,Female,26,2,0,2,0,0,50051.42,0 +816,15619708,Harker,745,France,Male,25,5,157993.15,2,1,0,146041.45,0 +817,15734565,Hughes,696,France,Male,29,8,0,2,1,0,191166.09,0 +818,15806438,Chiabuotu,580,Germany,Female,42,2,123331.36,1,0,0,103516.08,1 +819,15591969,Kuo,497,Spain,Male,27,9,75263.16,1,1,1,164825.04,0 +820,15747807,Gallagher,720,France,Female,43,6,137824.03,2,1,0,172557.77,0 +821,15596939,Calabresi,659,Germany,Male,36,4,132578.92,2,1,0,84320.94,0 +822,15716155,Shaw,841,France,Female,36,5,156021.31,1,0,0,122662.98,0 +823,15765311,Zhirov,642,Spain,Male,34,8,0,1,1,0,72085.1,0 +824,15757811,Lloyd,732,Spain,Female,69,9,137453.43,1,0,1,110932.24,1 +825,15603830,Palmer,600,Spain,Male,36,4,0,2,1,0,143635.36,0 +826,15660602,Ch'eng,464,Germany,Male,33,8,164284.72,2,1,1,3710.34,0 +827,15660535,Avent,680,France,Female,47,5,0,2,1,1,179843.33,0 +828,15666633,Huang,758,Spain,Male,56,1,0,2,1,1,10643.38,0 +829,15596914,Shaw,630,Germany,Female,31,2,112373.49,2,1,1,131167.98,0 +830,15639788,Yuan,577,France,Female,39,10,0,2,1,0,10553.31,0 +831,15695846,Hawkins,684,France,Female,34,6,0,2,1,1,130928.22,0 +832,15726234,Trentini,708,Spain,Female,41,5,0,1,0,1,157003.99,0 +833,15797964,Cameron,732,Germany,Female,29,1,154333.82,1,1,1,138527.56,0 +834,15625881,Koehler,634,Germany,Male,37,3,111432.77,2,1,1,167032.49,0 +835,15780628,Wu,633,France,Female,30,6,0,2,0,0,41642.29,0 +836,15575883,Manna,559,France,Male,34,2,137390.11,2,1,0,9677,0 +837,15585036,Okoli,694,Spain,Female,37,3,0,2,1,1,147012.22,0 +838,15589488,Ch'eng,686,Germany,Female,56,5,111642.08,1,1,1,80553.87,0 +839,15585888,Nwokezuike,553,Spain,Female,48,3,0,1,0,1,30730.95,1 +840,15727915,Artemiev,507,France,Male,36,4,83543.37,1,0,0,140134.43,0 +841,15707567,Esposito,732,Germany,Male,50,6,145338.76,1,0,0,91936.1,1 +842,15737792,Abbie,818,France,Female,31,1,186796.37,1,0,0,178252.63,0 +843,15599433,Fanucci,660,Germany,Male,35,8,58641.43,1,0,1,198674.08,0 +844,15672012,Jen,773,Spain,Female,41,5,0,1,1,0,28266.9,1 +845,15806983,Moss,640,France,Male,44,3,137148.68,1,1,0,92381.01,0 +846,15592222,Lo,505,France,Male,49,7,80001.23,1,0,0,135180.11,0 +847,15608968,Averyanov,714,Germany,Male,21,6,86402.52,2,0,0,27330.59,0 +848,15586959,Unaipon,468,France,Female,42,5,0,2,1,0,125305.34,0 +849,15646558,Clamp,611,Spain,Male,51,1,122874.74,1,1,1,149648.45,0 +850,15725811,Lim,705,France,Male,25,0,97544.29,1,0,1,59887.15,0 +851,15572265,Wu,646,Germany,Male,46,1,170826.55,2,1,0,45041.32,0 +852,15794048,Wan,667,Germany,Female,48,1,97133.92,2,0,0,113316.77,1 +853,15677610,Chambers,511,Germany,Female,41,8,153895.65,1,1,1,39087.42,0 +854,15745012,Pettit,653,France,Female,43,6,0,2,1,1,7330.59,0 +855,15601589,Baresi,675,France,Female,57,8,0,2,0,1,95463.29,0 +856,15686436,Newbery,523,Spain,Male,32,4,0,2,1,0,167848.02,0 +857,15693864,Iheanacho,567,Germany,Female,49,5,134956.02,1,1,0,93953.84,1 +858,15760550,Duncan,741,Spain,Male,39,7,143637.58,2,0,1,174227.66,0 +859,15686137,Barry,456,Spain,Male,32,9,147506.25,1,1,1,135399.21,0 +860,15809087,Landry,598,France,Male,64,1,0,2,1,0,195635.3,1 +861,15807663,McGregor,667,France,Male,43,8,190227.46,1,1,0,97508.04,1 +862,15809100,Nucci,548,France,Female,32,2,172448.77,1,1,0,188083.77,1 +863,15794916,Pirogov,725,France,Male,41,7,113980.21,1,1,1,116704.25,0 +864,15614215,Oguejiofor,717,France,Male,53,6,0,2,0,1,97614.87,0 +865,15805449,Ugochukwu,594,France,Male,38,4,0,2,0,0,186884.04,0 +866,15686983,Rohu,678,Germany,Female,25,10,76968.12,2,0,1,131501.72,0 +867,15808017,Cary,545,France,Male,38,1,88293.13,2,1,1,24302.95,0 +868,15756804,O'Loghlen,636,France,Female,48,1,170833.46,1,1,0,110510.28,1 +869,15646810,Quinn,603,Germany,Male,44,6,108122.39,2,1,0,108488.33,1 +870,15710424,Page,435,France,Male,36,4,0,1,1,1,197015.2,0 +871,15799422,Evans,535,France,Female,40,8,0,1,1,1,27689.77,0 +872,15692750,McGregor,629,Germany,Female,45,7,129818.39,3,1,0,9217.55,1 +873,15794549,Andrews,722,France,Female,35,2,163943.89,2,1,1,15068.18,0 +874,15803764,Stanley,561,France,Male,28,7,0,2,1,0,7797.01,0 +875,15674840,Chiazagomekpere,645,France,Female,38,5,101430.3,2,0,1,4400.32,0 +876,15653762,Chidiebele,501,France,Female,39,9,117301.66,1,0,0,182025.95,0 +877,15581229,Gregory,502,Germany,Female,32,1,173340.83,1,0,1,122763.95,0 +878,15800228,Bednall,652,Spain,Female,42,4,0,2,1,1,38152.01,0 +879,15656333,Jen,574,France,Female,33,3,134348.57,1,1,0,63163.99,0 +880,15697497,She,518,France,Female,45,9,105525.65,2,1,1,73418.29,0 +881,15585362,Simmons,749,France,Female,60,6,0,1,1,0,17978.68,1 +882,15571928,Fraser,679,France,Female,43,4,0,3,1,0,115136.51,1 +883,15785519,May,565,France,Male,36,6,106192.1,1,1,0,149575.59,0 +884,15743007,Seabrook,643,France,Female,45,4,45144.43,1,1,0,60917.24,1 +885,15777211,Herrera,515,France,Male,65,7,92113.61,1,1,1,142548.33,0 +886,15721935,Kincaid,521,France,Male,25,7,0,2,1,1,157878.67,0 +887,15591711,Sleeman,739,Spain,Male,38,0,128366.44,1,1,0,12796.43,0 +888,15625021,Hung,585,France,Male,42,2,0,2,1,1,18657.77,0 +889,15702968,Artemieva,733,Germany,Male,74,3,106545.53,1,1,1,134589.58,0 +890,15600462,Barwell,542,France,Female,43,8,145618.37,1,0,1,10350.74,0 +891,15768104,Wright,788,Spain,Male,37,8,141541.25,1,0,0,66013.27,0 +892,15780140,Bellucci,435,Germany,Male,32,2,57017.06,2,1,1,5907.11,0 +893,15585255,Moore,577,France,Male,42,9,0,1,1,0,74077.91,0 +894,15772781,Ball,703,France,Female,51,3,0,3,1,1,77294.56,1 +895,15669987,Sung,728,Germany,Female,35,8,125884.95,2,1,0,54359.02,1 +896,15697000,Mello,728,Germany,Male,32,5,61825.5,1,1,1,156124.93,0 +897,15733119,Mistry,718,France,Male,35,8,0,2,1,0,94820.85,0 +898,15782390,T'ien,621,France,Female,40,6,0,1,1,0,155155.25,0 +899,15654700,Fallaci,523,France,Female,40,2,102967.41,1,1,0,128702.1,1 +900,15632210,Hill,657,Germany,Male,25,2,171770.55,1,1,0,22745.5,0 +901,15642041,Burns,727,Germany,Male,40,1,93051.64,2,1,0,71865.31,1 +902,15709737,Hunter,643,France,Male,36,7,161064.64,2,0,1,84294.82,0 +903,15792388,Li,645,France,Female,48,7,90612.34,1,1,1,149139.13,0 +904,15786014,Ku,568,France,Male,28,5,145105.64,2,1,0,185489.11,0 +905,15794580,Ch'en,599,France,Male,58,4,0,1,0,0,176407.15,1 +906,15675964,Chukwukadibia,672,France,Female,45,9,0,1,1,1,92027.69,1 +907,15814275,Zikoranachidimma,685,France,Male,33,6,174912.72,1,1,1,43932.54,0 +908,15724848,Oluchukwu,516,France,Female,46,1,104947.72,1,1,0,115789.25,1 +909,15754713,Rivera,685,Spain,Male,31,10,135213.71,1,1,1,125777.28,0 +910,15693814,Niu,806,Spain,Male,25,7,0,2,1,0,18461.9,0 +911,15599660,Bennett,604,France,Male,36,6,116229.85,2,1,1,79633.38,0 +912,15746490,Wollstonecraft,648,Spain,Female,53,6,111201.41,1,1,1,121542.29,0 +913,15566091,Thomsen,545,Spain,Female,32,4,0,1,1,0,94739.2,0 +914,15655961,Palermo,756,Germany,Male,27,1,131899,1,1,0,93302.29,0 +915,15710404,Chinwendu,569,France,Male,35,10,124525.52,1,1,1,193793.78,0 +916,15775625,McKenzie,596,France,Male,47,6,0,1,1,0,74835.65,0 +917,15792328,James,475,France,Male,39,6,0,1,1,1,56999.9,1 +918,15719856,Lamb,646,France,Female,45,3,47134.75,1,1,1,57236.44,0 +919,15593773,Olejuru,784,Spain,Male,35,3,0,2,0,0,81483.64,0 +920,15733114,Hay,552,Spain,Male,45,9,0,2,1,0,26752.56,0 +921,15797748,Lu,729,France,Male,44,5,0,2,0,1,9200.54,0 +922,15743411,Chiawuotu,609,Spain,Male,61,1,0,1,1,0,22447.85,1 +923,15753337,Yeates,555,France,Male,51,5,0,3,1,0,189122.89,1 +924,15601026,Gallagher,572,Germany,Female,19,1,138657.08,1,1,1,16161.82,0 +925,15658485,Heath,785,France,Female,34,9,70302.48,1,1,1,68600.36,0 +926,15636731,Ts'ai,714,Germany,Female,36,1,101609.01,2,1,1,447.73,0 +927,15628303,Thurgood,738,Spain,Male,35,3,0,1,1,1,15650.73,0 +928,15633461,Pai,639,Germany,Male,38,5,130170.82,1,1,1,149599.62,0 +929,15677135,Lorenzo,520,Germany,Male,61,8,133802.29,2,1,1,90304.01,0 +930,15590876,Knupp,764,France,Female,24,7,106234.02,1,0,0,115676.38,0 +931,15790782,Baryshnikov,661,Spain,Male,39,6,132628.98,1,0,0,38812.67,0 +932,15700476,Azubuike,564,Germany,Male,41,9,103522.75,2,1,1,34338.21,0 +933,15634141,Shephard,708,Germany,Female,42,8,192390.52,2,1,0,823.36,0 +934,15737795,Scott,512,Spain,Male,36,1,0,1,0,1,135482.26,1 +935,15790299,Williamson,592,Spain,Male,37,9,0,3,1,1,10656.89,0 +936,15675316,Avdeeva,619,France,Female,38,3,0,2,0,1,116467.35,0 +937,15613630,Tang,775,France,Male,52,8,109922.61,1,1,1,96823.32,1 +938,15662100,Hsu,850,Germany,Female,44,5,128605.32,1,0,1,171096.2,0 +939,15668032,Buchanan,577,France,Female,37,4,0,1,1,1,79881.39,0 +940,15599289,Yeh,724,France,Female,37,10,68598.56,1,1,0,157862.82,0 +941,15754084,Palazzi,710,Spain,Male,35,1,106518.52,1,1,1,127951.81,0 +942,15676521,Y?an,696,France,Female,31,8,0,2,0,0,191074.11,0 +943,15804586,Lin,376,France,Female,46,6,0,1,1,0,157333.69,1 +944,15781465,Schofield,675,Germany,Female,29,8,121326.42,1,1,0,133457.52,0 +945,15729362,Lombardi,745,France,Male,36,8,67226.37,1,1,0,130789.6,0 +946,15709295,Wall,697,Spain,Female,25,5,82931.85,2,1,1,128373.88,0 +947,15745324,Milani,599,Spain,Female,39,4,0,1,1,0,194273.2,1 +948,15741336,Ejimofor,715,France,Female,38,5,118590.41,1,1,1,5684.17,1 +949,15783659,Blackburn,659,France,Male,67,4,145981.87,1,1,1,131043.2,0 +950,15620981,Wickham,684,France,Female,48,3,73309.38,1,0,0,21228.34,1 +951,15630328,Bird,635,France,Female,48,8,130796.33,2,1,1,43250.3,0 +952,15785899,Ch'en,789,Germany,Male,33,8,151607.56,1,1,0,4389.4,0 +953,15606149,Wood,571,Germany,Female,66,9,111577.01,1,0,1,189271.9,0 +954,15671139,Brizendine,694,Spain,Male,39,0,107042.74,1,1,1,102284.2,0 +955,15660429,Ch'in,665,Spain,Female,42,2,156371.61,2,0,1,156774.94,1 +956,15571002,Yusupov,706,France,Female,44,4,129605.99,1,0,0,69865.49,0 +957,15631681,Jibunoh,807,Spain,Female,43,0,0,2,0,1,85523.24,0 +958,15731522,Ts'ui,771,Spain,Female,67,8,0,2,1,1,51219.8,0 +959,15619529,Ndukaku,531,Spain,Male,27,8,132576.25,1,0,0,7222.92,0 +960,15628034,Wilder,629,France,Female,37,6,129101.3,1,1,1,23971.33,0 +961,15686164,Maclean,850,Germany,Female,31,1,108822.4,1,1,1,132173.31,0 +962,15582797,Ch'iu,685,Spain,Male,35,4,137948.51,1,1,0,113639.64,0 +963,15753831,Cox,642,Spain,Male,32,7,100433.8,1,1,1,39768.59,0 +964,15731815,Nepean,529,Spain,Male,63,4,96134.11,3,1,0,108732.96,1 +965,15580956,McNess,683,Germany,Female,43,4,115888.04,1,1,1,117349.19,1 +966,15602084,Coles,663,France,Female,42,5,124626.07,1,1,1,78004.5,0 +967,15589805,Benson,563,France,Female,34,6,139810.34,1,1,1,152417.79,0 +968,15720893,Gilbert,637,Spain,Female,34,9,0,2,0,0,26057.08,0 +969,15641009,Wilhelm,544,France,Male,37,3,84496.71,1,0,0,79972.09,0 +970,15605926,Sinclair,649,Germany,Male,70,9,116854.71,2,0,1,107125.79,0 +971,15805955,L?,638,France,Female,48,10,138333.03,1,1,1,47679.14,0 +972,15801488,Buckner,723,France,Male,25,3,0,2,1,1,134509.47,0 +973,15605918,Padovesi,635,Germany,Male,43,5,78992.75,2,0,0,153265.31,0 +974,15779711,Gray,750,Spain,Female,38,7,97257.41,2,0,1,179883.04,0 +975,15705620,Lu,730,France,Male,34,5,122453.37,2,1,0,138882.98,0 +976,15685357,Wright,750,Spain,Female,36,8,112940.07,1,0,1,9855.81,0 +977,15570060,Palerma,586,France,Female,43,8,132558.26,1,1,0,67046.83,1 +978,15582616,Y?an,520,France,Female,38,4,0,2,1,0,56388.63,0 +979,15799515,Wei,652,France,Female,48,8,133297.24,1,1,0,77764.37,0 +980,15642937,Padovesi,550,France,Female,46,7,0,2,1,0,130590.35,0 +981,15624729,Tsao,594,France,Male,27,0,197041.8,1,0,0,151912.49,0 +982,15566156,Franklin,749,Germany,Female,44,0,71497.79,2,0,0,151083.8,0 +983,15792360,Clark,668,France,Male,32,7,0,2,1,1,777.37,0 +984,15807008,McGregor,614,Germany,Female,35,6,128100.28,1,0,0,69454.24,1 +985,15704770,Pan,773,France,Male,25,1,124532.78,2,0,1,11723.57,0 +986,15756475,Kenniff,551,Germany,Male,31,9,82293.82,2,1,1,91565.25,0 +987,15655339,Spencer,566,France,Male,36,1,142120.91,1,1,0,79616.37,0 +988,15613749,Lees,569,Spain,Male,34,0,151839.26,1,1,0,102299.81,1 +989,15664521,David,659,Spain,Male,31,7,149620.88,2,1,1,104533.51,0 +990,15681206,Hsing,722,France,Female,49,3,168197.66,1,1,0,140765.57,1 +991,15745527,Burke,655,France,Male,37,5,93147,2,1,0,66214.13,0 +992,15806926,Watson,615,France,Female,35,2,97440.02,2,1,1,139816.1,0 +993,15724563,Hawkins,752,Germany,Female,42,3,65046.08,2,0,1,140139.28,0 +994,15782899,Ginn,661,Spain,Female,28,7,95357.49,1,0,0,102297.15,0 +995,15623521,Sozonov,838,Spain,Male,43,9,123105.88,2,1,0,145765.83,0 +996,15810218,Sun,610,Spain,Male,29,9,0,3,0,1,83912.24,0 +997,15645621,Hunter,811,Spain,Male,44,3,0,2,0,1,78439.73,0 +998,15608114,Manfrin,587,Spain,Male,62,7,121286.27,1,0,1,6776.92,0 +999,15659557,Artamonova,811,Germany,Female,28,4,167738.82,2,1,1,9903.42,0 +1000,15787772,Hansen,759,France,Female,38,1,104091.29,1,0,0,91561.91,0 +1001,15691111,Pai,648,Germany,Female,42,8,121980.56,2,1,0,4027.02,0 +1002,15592089,Larsen,788,France,Female,43,10,0,2,1,1,116111.51,0 +1003,15633897,Owen,725,Germany,Male,39,1,50880.98,2,1,1,184023.54,0 +1004,15701301,Murphy,646,France,Female,42,3,175159.9,2,0,0,67124.48,1 +1005,15723685,Ekechukwu,601,Germany,Female,26,7,105514.69,2,1,0,50070.59,0 +1006,15701602,Ayers,521,Germany,Male,52,5,116497.31,3,0,0,53793.1,1 +1007,15739189,Johnson,561,Spain,Female,33,6,0,2,1,0,45261.47,0 +1008,15573086,Millar,564,France,Male,42,7,99824.45,1,1,1,36721.4,0 +1009,15569050,Farrell,444,France,Male,45,6,0,1,1,0,130009.85,1 +1010,15750765,Sanders,650,Spain,Male,71,0,0,1,1,1,175380.77,0 +1011,15799811,Herrera,724,France,Male,40,10,0,1,1,0,127847.25,1 +1012,15698442,Eberechukwu,719,Spain,Male,35,3,122964.88,1,1,1,138231.7,0 +1013,15655274,Bardin,548,France,Female,29,4,0,2,0,1,48673.18,0 +1014,15603594,Nwankwo,635,Spain,Male,24,4,0,2,1,1,70668.77,0 +1015,15585961,Talbot,496,Spain,Female,43,3,0,2,0,1,199505.53,0 +1016,15686936,McGregor,676,France,Female,37,5,89634.69,1,1,1,169583.18,1 +1017,15770424,Onyeorulu,541,Germany,Male,40,7,95710.11,2,1,0,49063.42,0 +1018,15587451,Goold,778,Germany,Male,41,7,139706.31,1,1,0,63337.19,0 +1019,15602010,Zikoranaudodimma,850,Germany,Female,45,5,103909.86,1,1,0,60083.11,1 +1020,15600583,Garner,633,France,Male,31,1,0,1,1,0,48606.71,0 +1021,15654673,Onyinyechukwuka,625,France,Male,49,6,173434.9,1,1,0,165580.93,1 +1022,15717164,Genovese,485,Spain,Male,32,6,102238.01,2,1,1,194010.12,0 +1023,15765014,Mai,547,France,Female,48,1,179380.74,2,0,1,69263.1,0 +1024,15682639,Marshall,642,France,Male,32,3,0,2,1,1,88698.83,0 +1025,15729279,Naylor,718,France,Female,25,4,108691.95,1,1,0,63030.97,0 +1026,15759805,Pinto,582,France,Female,32,4,0,2,1,0,59668.81,0 +1027,15767864,Fulton,628,France,Male,33,6,0,2,0,0,184230.23,0 +1028,15769948,Palerma,737,Germany,Male,35,0,133377.8,1,0,1,64050.19,0 +1029,15686345,McCaffrey,828,Spain,Male,34,9,0,2,1,1,81853.98,0 +1030,15688071,Collins,609,Spain,Male,53,10,0,1,1,1,154642.91,0 +1031,15681174,Zuev,730,France,Male,39,1,116537.6,1,0,0,145679.6,0 +1032,15667521,Crawford,631,France,Female,22,3,0,2,0,0,30781.77,0 +1033,15750243,Genovese,830,Spain,Male,40,4,0,2,0,1,81622.52,0 +1034,15695475,Maclean,645,France,Male,29,1,130131.08,2,0,1,196474.35,0 +1035,15689176,Fabro,663,France,Male,46,3,0,2,0,1,176276.1,0 +1036,15652955,Price,678,Spain,Male,30,0,0,1,1,0,35113.08,0 +1037,15668958,Chatfield,521,France,Male,30,2,107316.09,1,1,0,64299.82,0 +1038,15631054,Volkova,625,France,Female,24,1,0,2,1,1,180969.55,0 +1039,15581479,Archer,523,France,Male,30,1,83181.29,1,1,1,138176.78,0 +1040,15577478,Ch'iu,714,France,Female,72,3,0,1,1,1,86733.61,0 +1041,15780870,McKay,580,Spain,Male,67,3,153946.14,1,1,1,7418.92,0 +1042,15692317,Craig,722,France,Male,30,5,0,2,1,0,166376.54,0 +1043,15593969,Abramovich,630,Spain,Female,39,7,135483.17,1,1,0,140881.2,1 +1044,15570417,Chien,579,France,Male,35,1,0,2,1,0,4460.2,0 +1045,15779059,Timms,670,France,Female,38,4,119624.54,2,1,1,110472.12,0 +1046,15785980,Williford,588,Spain,Male,34,6,121132.26,2,1,0,86460.28,0 +1047,15644200,Hamilton,807,Spain,Female,42,1,0,1,1,0,16500.66,1 +1048,15793949,Cheng,726,France,Female,48,4,0,1,1,0,114020.06,1 +1049,15645103,Su,812,Germany,Male,25,5,54817.55,1,1,0,131660.31,0 +1050,15705860,McKenzie,631,Germany,Male,40,3,107949.45,1,1,0,52449.62,1 +1051,15623828,Akobundu,682,France,Male,30,4,0,1,0,1,161465.31,0 +1052,15715003,Ko,625,Spain,Female,49,2,80816.45,1,1,1,20018.79,0 +1053,15623471,Marcelo,607,Germany,Male,38,3,98205.77,1,1,0,176318.27,0 +1054,15798348,Chukwuebuka,600,Spain,Female,50,6,94684.27,1,1,1,50488.91,0 +1055,15743016,MacDonald,602,Spain,Female,22,7,141604.76,1,1,0,30379.6,0 +1056,15769499,Lampungmeiua,545,Spain,Female,74,3,0,2,1,1,161326.73,0 +1057,15798521,Tai,675,Spain,Male,33,3,0,2,1,0,45348.08,0 +1058,15706534,Enyinnaya,581,France,Female,47,1,122949.14,1,0,0,180251.68,1 +1059,15706186,McKenzie,640,Germany,Male,33,8,81677.22,2,0,0,34925.56,0 +1060,15812197,Kline,850,France,Male,38,7,80293.98,1,0,0,126555.74,0 +1061,15650933,Ma,490,Spain,Female,48,8,155413.06,1,1,0,187921.3,0 +1062,15692991,Wood,710,Spain,Female,38,4,0,2,1,1,136390.88,0 +1063,15631189,Riggs,613,Germany,Male,38,9,67111.65,1,1,0,78566.64,1 +1064,15762198,Capon,812,France,Male,34,5,103818.43,1,1,1,166038.27,0 +1065,15699598,Smith,723,France,Female,20,4,0,2,1,1,140385.33,0 +1066,15692744,Davison,512,France,Male,36,4,152169.12,2,0,0,38629.3,1 +1067,15688963,Ingram,731,France,Female,52,10,0,1,1,1,24998.75,1 +1068,15599131,Dilke,650,Germany,Male,26,4,214346.96,2,1,0,128815.33,0 +1069,15680303,Gibson,594,France,Male,57,6,0,1,1,0,19376.56,1 +1070,15628674,Iadanza,844,France,Male,40,7,113348.14,1,1,0,31904.31,1 +1071,15648075,Hebert,686,Germany,Female,47,5,170935.94,1,1,0,173179.79,1 +1072,15586970,Pinto,695,Germany,Male,52,8,103023.26,1,1,1,22485.64,0 +1073,15625698,Dumetochukwu,624,Spain,Female,23,6,0,2,0,1,196668.51,0 +1074,15790497,Ross,503,Spain,Male,37,6,0,2,0,0,136506.86,0 +1075,15682618,Jamieson,535,France,Female,31,7,111855.04,2,1,1,36278.89,0 +1076,15762937,Chiganu,743,Germany,Female,32,6,140348.56,2,1,1,163254.39,0 +1077,15750929,Burgess,702,Spain,Male,39,8,0,2,1,0,99654.13,0 +1078,15729832,Cheng,658,France,Male,29,3,145512.84,1,1,0,20207.02,0 +1079,15633650,Woods,677,Germany,Female,41,8,146720.98,2,1,1,4195.84,0 +1080,15748856,Liang,664,France,Male,32,10,107209.73,1,1,1,112340.2,0 +1081,15589195,Bluett,766,Germany,Female,38,7,130933.74,1,0,1,2035.94,0 +1082,15699911,Chapman,461,Spain,Female,35,8,0,1,1,0,132295.95,0 +1083,15663438,Andrejew,688,Spain,Male,36,0,89772.3,1,1,0,177383.68,1 +1084,15692583,Udobata,678,France,Female,32,5,0,2,1,0,90284.47,0 +1085,15591257,Ejimofor,796,France,Male,24,8,0,2,1,0,61349.37,0 +1086,15646513,Spyer,803,France,Male,42,5,0,1,1,0,196466.83,1 +1087,15708063,Walker,712,France,Male,36,2,100749.5,3,0,0,70758.37,1 +1088,15696098,Palermo,498,France,Female,31,10,0,2,1,0,13892.57,0 +1089,15645517,Philip,850,Spain,Male,22,2,0,2,1,1,9684.52,0 +1090,15649744,Fallaci,628,France,Female,51,3,123981.31,2,1,1,40546.15,0 +1091,15604304,Perry,539,Germany,Female,34,4,91622.42,1,1,1,136603.42,0 +1092,15784092,Henderson,732,France,Male,36,7,126195.81,1,1,1,133172.48,0 +1093,15585198,Bergamaschi,715,France,Male,41,4,94267.9,1,0,1,152821.12,1 +1094,15624347,Fokine,651,France,Male,40,4,0,2,1,1,147715.83,0 +1095,15621687,Mackay,813,France,Male,34,0,0,2,1,0,43169.15,0 +1096,15689081,Wu,692,France,Male,29,4,0,1,1,0,76755.99,1 +1097,15813168,Maslova,756,Germany,Female,39,3,100717.85,3,1,1,73406.04,1 +1098,15604295,Wei,543,France,Male,36,6,0,2,1,0,176728.28,0 +1099,15724127,McLean,790,France,Female,26,4,141581.71,2,0,0,98309.27,0 +1100,15673055,Sung,494,Spain,Male,38,7,0,2,1,1,6203.66,0 +1101,15768201,Paterson,850,France,Female,39,2,148586.64,1,1,1,176791.27,0 +1102,15782219,Fanucci,703,Spain,Male,29,9,0,2,1,0,50679.48,0 +1103,15746410,Thompson,432,Spain,Male,38,7,0,2,1,0,150580.88,0 +1104,15780144,Tisdall,512,Germany,Female,32,2,123403.85,2,1,0,80120.19,0 +1105,15590476,Onochie,589,France,Male,28,7,0,2,1,0,151645.96,0 +1106,15624293,Mironova,514,France,Female,46,3,106511.85,1,1,0,55072.32,0 +1107,15618182,Ndubueze,678,France,Female,38,2,0,2,0,0,115068.99,0 +1108,15660316,Stephenson,420,Germany,Female,34,1,135549.9,1,0,0,149471.13,1 +1109,15678886,Golubev,679,Germany,Male,38,7,110555.37,2,1,0,46522.68,0 +1110,15616330,Liao,595,France,Male,31,4,0,2,1,0,189995.86,0 +1111,15592229,Mullan,713,France,Female,52,0,185891.54,1,1,1,46369.57,1 +1112,15798424,Glover,833,Germany,Male,59,1,130854.59,1,1,1,30722.52,1 +1113,15714750,Northey,690,France,Female,42,3,92578.14,2,0,0,70810.6,0 +1114,15648800,Paterson,731,Germany,Female,21,8,132312.06,1,1,0,106663.46,1 +1115,15626147,Maclean,608,France,Female,62,8,144976.5,1,0,0,175836.03,1 +1116,15626608,Howarde,479,Spain,Male,48,5,87070.23,1,0,1,85646.41,0 +1117,15723250,Teng,519,France,Male,42,8,0,2,1,1,101485.72,0 +1118,15592583,Colman,731,France,Female,47,1,115414.19,3,0,0,191734.67,1 +1119,15759381,Johnson,617,Spain,Male,61,7,91070.43,1,1,1,101839.77,0 +1120,15585241,Butcher,756,Spain,Male,29,2,117412.19,2,1,0,4888.91,0 +1121,15589358,Stanley,848,Germany,Male,31,4,90018.45,2,1,0,193132.98,0 +1122,15672704,Jackson,809,France,Female,24,4,0,2,1,0,193518.76,0 +1123,15789955,Hu,698,Germany,Male,56,1,112414.81,2,0,0,93982.02,1 +1124,15596800,Hill,779,Germany,Male,33,1,158456.76,1,1,1,197000.92,1 +1125,15627305,Pan,606,Spain,Male,35,7,0,1,1,0,106837.06,1 +1126,15645316,Han,612,Germany,Female,58,1,149641.53,1,1,1,115161.28,0 +1127,15593973,Wilkie,663,Spain,Female,33,8,122528.18,1,1,0,196260.3,0 +1128,15647301,Bray,549,Germany,Female,45,3,143734.01,2,1,1,96404.38,0 +1129,15750258,Ann,675,France,Female,32,2,155663.31,1,1,0,97658.66,0 +1130,15685309,Souter,669,France,Female,35,7,0,1,1,1,49108.23,1 +1131,15628205,Greco,571,Germany,Female,34,1,101736.66,1,0,1,195651.66,0 +1132,15733974,Mao,500,Spain,Male,37,9,125822.21,1,1,0,111698,0 +1133,15762110,Anderson,628,France,Male,37,0,0,2,1,1,171707.93,0 +1134,15706899,Ma,559,France,Male,34,4,0,2,1,1,66721.98,0 +1135,15732660,Black,769,France,Female,27,2,0,1,1,1,57876.05,0 +1136,15656121,Medvedeva,733,Germany,Male,31,6,157791.07,2,0,0,177994.81,0 +1137,15614220,Benson,750,France,Male,22,5,0,2,0,1,105125.65,0 +1138,15645269,Duncan,583,France,Female,42,4,0,2,1,0,17439.66,0 +1139,15698510,Onwudiwe,468,Germany,Male,42,9,181627.14,2,1,0,172668.39,0 +1140,15569247,Mitchell,727,Spain,Female,57,1,109679.72,1,0,1,753.37,0 +1141,15566251,Ferrari,618,France,Female,37,5,96652.86,1,1,0,98686.4,1 +1142,15716134,Russo,617,France,Male,40,5,190008.32,2,1,1,107047.92,0 +1143,15763625,Hazon,793,Spain,Male,41,9,0,2,1,0,152153.74,0 +1144,15605965,Henderson,630,France,Male,43,9,0,2,1,1,34338.04,0 +1145,15694821,Hardy,765,Germany,Male,43,4,148962.76,1,0,1,173878.87,1 +1146,15601688,Piccio,546,France,Male,28,8,0,1,1,0,159254.29,0 +1147,15575581,Dickson,614,Germany,Female,30,3,131344.52,2,1,0,54776.64,0 +1148,15671209,Holden,593,Germany,Female,29,5,101713.84,3,1,0,134594.99,0 +1149,15616529,Hsieh,613,Spain,Male,34,3,0,1,1,1,41724.72,0 +1150,15773906,Doherty,655,France,Male,38,4,0,2,0,0,110527.71,0 +1151,15722993,Page,700,France,Female,27,6,137963.07,1,0,0,8996.79,0 +1152,15752463,Samuel,826,Spain,Female,29,4,129938.07,1,0,1,190200.53,0 +1153,15589754,Malloy,652,Germany,Male,45,2,151421.44,1,0,1,115333.43,0 +1154,15669899,Fitts,755,Germany,Female,45,7,135643,1,0,0,143619.52,1 +1155,15766887,Iadanza,538,Spain,Male,39,2,122773.5,2,1,1,58467.08,0 +1156,15768006,Wu,729,France,Male,34,3,152303.8,1,1,0,12128.69,0 +1157,15741295,Yefimova,615,France,Male,49,3,0,2,1,1,49872.33,0 +1158,15811327,Pan,700,Spain,Male,54,1,79415.67,1,0,1,139735.54,0 +1159,15690007,Ts'ui,434,Germany,Female,58,9,125801.03,2,1,0,60891.8,1 +1160,15690664,Liang,729,Spain,Male,37,10,0,2,1,0,100862.54,0 +1161,15719348,Tsao,513,France,Male,35,8,0,1,1,0,76640.29,1 +1162,15781802,Abramov,755,France,Male,41,6,104817.41,1,1,0,126013.58,1 +1163,15752731,Millar,615,France,Female,30,9,0,1,1,0,87347.82,0 +1164,15600997,Demuth,747,Germany,Female,32,5,67495.04,2,0,1,77370.37,0 +1165,15750776,Genovese,850,France,Female,36,0,164850.54,1,1,1,62722.44,0 +1166,15723907,Lawless,712,Germany,Female,49,5,154776.42,2,0,0,196257.68,0 +1167,15633419,Brooks,622,Germany,Female,28,1,143124.63,2,1,0,81723.8,0 +1168,15702430,Ignatyeva,548,France,Female,35,10,0,1,1,1,31299.71,0 +1169,15710456,Balmain,607,France,Female,27,2,0,2,1,0,63495.86,0 +1170,15650351,Millar,653,France,Female,38,8,102133.38,1,1,1,166520.96,0 +1171,15590820,Ecuyer,699,Spain,Male,26,6,79932.41,1,0,0,150242.44,0 +1172,15640454,Parkhill,693,Germany,Male,40,0,120711.73,1,0,0,27345.18,1 +1173,15697789,Li Fonti,647,Germany,Female,43,3,122717.53,2,1,1,87000.39,0 +1174,15808182,Beneventi,478,Spain,Female,36,3,92363.3,2,1,0,44912.7,0 +1175,15588670,Despeissis,705,Spain,Female,40,5,203715.15,1,1,0,179978.68,1 +1176,15721292,Atkins,719,Spain,Male,39,5,0,2,1,0,145759.7,0 +1177,15604217,Williams,726,France,Male,34,9,0,2,0,0,14121.61,0 +1178,15651369,Wright,626,France,Male,21,1,0,2,1,0,66232.23,0 +1179,15782454,Hancock,552,France,Male,49,4,0,1,1,1,190296.76,1 +1180,15814032,Hsieh,807,Germany,Female,31,1,93460.47,2,0,0,172782.69,0 +1181,15570326,Wilkins,621,France,Male,34,6,0,2,1,1,99128.13,0 +1182,15624428,Longo,651,Germany,Female,24,7,40224.7,1,1,1,178341.33,0 +1183,15755638,Mancini,673,France,Female,43,5,168069.73,1,1,1,146992.24,1 +1184,15600992,Madukaego,652,France,Male,36,1,0,2,1,1,151314.98,0 +1185,15755649,Winter-Irving,584,Germany,Male,47,7,130538.77,1,1,0,92915.84,0 +1186,15795228,Stewart,756,France,Male,37,3,132623.6,1,1,1,58974,0 +1187,15589257,Grant,670,France,Female,35,3,103465.02,2,1,1,174627.06,0 +1188,15719302,Brennan,765,France,Female,50,9,126547.8,1,1,1,79579.94,1 +1189,15639882,She,528,France,Male,30,2,128262.72,2,1,0,50771.16,0 +1190,15791279,Murray,701,France,Male,40,5,169742.64,1,1,1,153537.55,1 +1191,15636935,Rischbieth,797,France,Female,29,1,0,2,1,1,132975.39,0 +1192,15686909,Lung,639,Germany,Male,27,3,150795.81,1,0,1,85208.93,0 +1193,15589572,Otutodilichukwu,785,Spain,Female,61,4,129855.72,2,1,0,170214.82,1 +1194,15779947,Thomas,363,Spain,Female,28,6,146098.43,3,1,0,100615.14,1 +1195,15573769,Fiorentini,764,France,Female,24,7,0,2,1,0,186105.99,0 +1196,15578866,Hughes,676,France,Female,43,2,0,1,1,1,55119.53,0 +1197,15739131,Whitworth,718,Germany,Male,28,4,65643.3,1,1,0,28760.99,0 +1198,15813444,McIntosh,590,Spain,Female,34,6,0,2,1,0,171021.44,0 +1199,15678058,Ayers,584,France,Male,38,9,104584.16,1,1,0,176678.72,0 +1200,15769169,Trentino,645,France,Male,41,7,0,1,0,1,28667.56,0 +1201,15804602,Boyd,772,Germany,Male,30,6,99785.28,2,0,0,197238.03,0 +1202,15651052,McMasters,399,Germany,Male,46,2,127655.22,1,1,0,139994.68,1 +1203,15724334,Alekseyeva,529,France,Male,22,5,0,1,1,0,151169.83,0 +1204,15569451,Miller,463,France,Male,35,2,101257.16,1,1,1,118113.64,0 +1205,15650098,Baranova,630,France,Female,40,7,0,2,1,1,34453.17,0 +1206,15724307,Mitchell,780,France,Male,76,10,121313.88,1,0,1,64872.33,0 +1207,15599268,Yobachi,584,Spain,Male,32,5,0,2,1,0,10956.82,0 +1208,15594864,Huang,752,Germany,Male,30,4,81523.38,1,1,1,36885.85,0 +1209,15616451,Genovese,697,France,Female,47,6,128252.66,1,1,1,168053.4,0 +1210,15715667,Sorokina,850,France,Female,32,7,0,2,0,0,155227,0 +1211,15658969,Gray,711,France,Male,51,7,0,3,1,0,38409.79,1 +1212,15738174,Ervin,452,France,Female,32,5,0,2,0,1,75279.39,0 +1213,15813590,Vance,610,Spain,Male,42,6,0,2,1,0,158302.59,1 +1214,15624229,Noble,694,France,Female,22,4,0,2,1,1,11525.72,0 +1215,15674148,Milanesi,579,Spain,Male,33,6,0,1,1,0,94993.04,1 +1216,15625080,Parkin,745,Spain,Female,54,8,0,1,1,0,173912.29,1 +1217,15682528,Cremonesi,572,France,Male,33,5,0,1,0,1,41139.05,0 +1218,15696900,Burns,505,Germany,Male,29,3,145541.56,2,1,1,58019.95,0 +1219,15730038,Docherty,706,France,Female,23,5,0,1,0,0,164128.41,1 +1220,15812272,Ugonna,693,Germany,Male,44,5,124601.58,2,1,1,46998.13,1 +1221,15654654,L?,725,Germany,Female,33,7,115182.84,2,1,1,177279.41,0 +1222,15697625,Bevan,791,France,Male,37,2,163789.49,2,1,0,75832.53,0 +1223,15616280,Hsia,536,France,Male,46,1,65733.41,1,1,0,61094.53,0 +1224,15654229,O'Neill,699,Spain,Male,47,1,0,2,0,1,30117.44,0 +1225,15628298,Johnstone,500,Spain,Female,47,8,128486.11,1,1,0,179227.12,0 +1226,15733387,Pham,707,Spain,Female,53,6,109663.47,1,1,1,52110.45,0 +1227,15775572,Bergamaschi,531,Germany,Female,42,6,88324.31,2,1,0,75248.75,0 +1228,15613844,Murphy,557,France,Female,28,7,146445.24,2,1,0,184317.74,0 +1229,15578515,Osinachi,659,France,Female,38,3,0,2,1,0,158553.1,0 +1230,15607598,Muravyov,575,Spain,Female,31,6,0,2,1,1,95686.42,0 +1231,15742480,Igwebuike,775,Germany,Male,36,2,109949.05,2,0,1,71682.54,0 +1232,15749482,Zack,772,Spain,Male,30,4,78653.05,1,1,0,1790.48,0 +1233,15607537,Crawford,587,Germany,Male,46,9,107850.82,1,1,0,139431,1 +1234,15575410,Chidiegwu,667,Germany,Female,39,4,83765.35,2,1,0,118358.54,0 +1235,15684865,Lucchesi,771,France,Female,66,7,143773.07,1,1,1,130827.88,0 +1236,15600700,Pan,523,Germany,Male,63,6,116227.27,1,1,1,119404.63,0 +1237,15774155,Trevisani,662,Germany,Male,33,0,103471.52,1,1,1,162703,0 +1238,15634267,Yudin,717,France,Male,42,5,0,2,1,0,172665.21,0 +1239,15619626,Wade,746,France,Male,24,3,137492.35,2,0,1,170142.09,0 +1240,15660422,Chung,569,France,Male,28,7,0,2,1,0,73977.23,0 +1241,15617934,Septimus,579,France,Male,36,9,129829.59,1,1,1,60906.12,0 +1242,15760774,Hargraves,519,France,Female,21,1,146329.57,2,1,1,194867.27,0 +1243,15813132,Chukwukadibia,696,Germany,Male,30,4,114027.7,1,1,1,193716.56,0 +1244,15593331,Sidorov,693,Germany,Male,25,6,146580.69,1,0,1,14633.35,0 +1245,15616709,Bunton,587,Germany,Female,38,0,132122.42,2,0,0,31730.32,0 +1246,15658052,Cameron,626,France,Female,44,10,81553.93,1,1,0,20063.63,1 +1247,15721189,Kung,666,France,Female,66,7,0,2,1,1,99792.82,0 +1248,15711288,Hay,512,France,Male,24,6,0,2,1,0,37654.31,0 +1249,15770030,Conti,689,Spain,Female,28,3,0,2,1,1,192449.02,0 +1250,15803681,Sims,803,France,Female,26,4,0,2,1,1,181208.47,0 +1251,15702789,Carter,548,Germany,Male,32,5,175214.71,1,1,1,155165.61,0 +1252,15814930,McGregor,588,Germany,Female,40,10,125534.51,1,1,0,121504.18,1 +1253,15658306,Lo,693,France,Male,68,4,97705.99,1,1,1,61569.07,0 +1254,15699523,Chu,499,Germany,Female,55,4,126817.65,2,1,0,123269.71,0 +1255,15610383,Dumetolisa,628,France,Female,46,1,46870.43,4,1,0,31272.14,1 +1256,15615032,Peng,624,Spain,Male,46,3,0,2,1,1,62825.03,0 +1257,15781989,Drake-Brockman,733,France,Male,42,9,120094.93,1,1,0,184056.45,0 +1258,15647402,Wan,628,France,Female,38,3,0,2,1,1,48924.73,0 +1259,15740494,Cameron,633,France,Female,33,3,0,2,1,0,191111.02,0 +1260,15701265,Tretiakov,559,Germany,Female,36,1,104356.94,2,0,1,54184.06,0 +1261,15743532,Ball,704,Germany,Male,27,5,147004.34,1,1,0,64381.33,1 +1262,15794870,Sal,744,Germany,Male,38,6,73023.17,2,1,0,78770.86,0 +1263,15747591,Chung,665,Spain,Female,40,1,173432.55,1,0,1,116766.79,0 +1264,15726557,Lai,638,France,Female,42,7,165679.92,1,0,0,32916.29,0 +1265,15732199,Gether,837,Spain,Male,31,9,104678.62,1,0,1,50972.6,0 +1266,15662291,Davidson,534,France,Female,55,8,116973.26,3,1,0,122066.5,1 +1267,15749050,Justice,548,France,Female,36,3,0,1,1,0,65996.9,0 +1268,15781586,Osonduagwuike,837,Germany,Male,38,2,126732.85,1,1,1,79577.38,0 +1269,15617078,Ewing,658,France,Female,44,6,148481.09,1,1,0,130529.13,0 +1270,15723339,Chin,554,France,Female,38,4,137654.05,2,1,1,172629.67,0 +1271,15671322,Chiang,724,Germany,Male,30,7,115315.04,1,1,0,15216.53,0 +1272,15793854,Ahmed,723,France,Male,42,2,99095.73,1,1,1,17512.53,0 +1273,15756539,Marshall,585,Germany,Female,39,7,165610.41,2,0,0,131852.01,0 +1274,15612064,Tsou,474,France,Male,33,5,0,2,1,0,181945.52,1 +1275,15625916,Chien,562,Spain,Male,32,6,161628.66,1,1,0,91482.5,0 +1276,15683195,Ubanwa,719,France,Male,32,9,146605.27,1,1,1,77119.45,0 +1277,15690182,Kapustin,635,Germany,Male,37,5,113488.68,1,1,0,95611.74,1 +1278,15721719,Calabresi,743,France,Male,42,7,77002.2,2,1,1,80428.42,0 +1279,15641690,Hsiao,681,Spain,Male,67,7,0,2,0,1,163714.92,0 +1280,15634896,Grant,521,France,Female,39,6,0,2,0,1,27375.15,0 +1281,15671590,H?,741,Spain,Male,25,4,0,2,1,1,73873.65,0 +1282,15779182,Chia,790,Spain,Male,46,8,182364.53,1,0,0,139266.48,1 +1283,15778287,Ugoji,622,France,Male,35,8,0,2,1,1,131772.51,0 +1284,15609510,Gregory,669,France,Male,45,7,149364.58,1,0,1,173454.07,0 +1285,15742229,Mackay,583,France,Male,59,7,127450.14,1,0,1,67552.71,0 +1286,15658532,Nnamutaezinwa,520,Spain,Female,63,5,162278.32,1,1,1,34765.33,0 +1287,15590993,Findlay,579,Spain,Male,37,5,152212.88,2,0,0,120219.14,0 +1288,15565701,Ferri,698,Spain,Female,39,9,161993.89,1,0,0,90212.38,0 +1289,15597239,Ku,548,Spain,Male,39,7,131468.44,1,1,0,164975.82,0 +1290,15688880,Amechi,672,Germany,Male,40,10,102980.44,1,1,0,1285.81,1 +1291,15813917,Kirk,653,Germany,Male,31,9,143321.97,1,1,0,83679.46,0 +1292,15679611,Andrews,734,Spain,Female,37,2,130404.92,1,0,0,34548.74,0 +1293,15636589,Murray,794,France,Female,41,7,0,2,1,1,74275.08,0 +1294,15687752,Griffin,641,France,Male,30,2,87505.47,2,0,1,7278.57,0 +1295,15584363,Longstaff,824,France,Male,30,0,133634.02,1,1,1,162053.92,0 +1296,15737748,McWilliam,534,Spain,Female,33,3,151233.62,1,0,0,199336.63,0 +1297,15803365,Coffee,653,Spain,Male,55,2,70263.83,1,0,1,62347.71,0 +1298,15793247,Hancock,498,France,Male,34,5,0,2,1,1,91711.66,0 +1299,15572360,Clark,683,France,Male,30,10,57657.49,1,0,0,79240.9,0 +1300,15795166,Creswell,618,Germany,Male,42,8,153572.31,2,1,1,76679.6,0 +1301,15724620,Dodds,538,France,Male,37,1,134752.08,1,1,0,162511.55,0 +1302,15800856,Ewen,643,Spain,Male,34,3,83132.09,1,1,1,21360.88,0 +1303,15671097,Carter,428,France,Female,31,2,0,2,1,0,54487.43,0 +1304,15683930,Ch'iu,593,Germany,Female,32,9,134096.53,2,1,0,53931.05,1 +1305,15749004,Tsao,718,France,Female,31,0,118100.59,2,1,0,103165.15,0 +1306,15800434,Burgess,811,Germany,Male,52,10,76915.4,1,0,0,146359.81,1 +1307,15709117,Fanucci,823,Spain,Female,46,3,81576.75,1,1,1,28370.95,1 +1308,15638806,Blackburn,645,Spain,Male,49,2,0,2,0,0,10023.15,0 +1309,15662294,Bennett,710,France,Male,33,10,118327.17,2,1,1,192928.82,0 +1310,15690079,Boniwell,591,Spain,Male,30,8,124857.69,2,0,0,50485.7,0 +1311,15759317,Vasilieva,748,Germany,Female,27,2,90971.85,1,1,1,131662.47,0 +1312,15750497,Longo,850,France,Female,37,7,153147.75,1,1,1,152235.3,0 +1313,15596181,Kwemto,542,France,Male,38,8,65942.26,1,1,1,68093.23,1 +1314,15576602,Lawrence,809,France,Male,38,3,0,2,1,1,80061.31,0 +1315,15644833,Duncan,675,France,Male,54,2,0,1,1,0,149583.67,1 +1316,15734634,Bocharova,607,Spain,Female,27,5,100912.19,1,0,0,7631.27,0 +1317,15808689,Morres,850,France,Female,31,4,0,2,1,1,33082.81,0 +1318,15720702,Shih,789,France,Male,37,3,0,1,1,0,121883.87,1 +1319,15665077,Vogel,598,France,Female,43,5,0,3,1,1,100722.72,1 +1320,15763612,T'an,756,Germany,Male,41,2,124439.49,2,0,1,47093.11,0 +1321,15596493,Wisdom,687,France,Female,47,7,0,2,1,1,177624.01,0 +1322,15704483,Lorenzo,724,France,Male,40,6,0,2,0,0,106149.48,0 +1323,15598846,Shahan,700,France,Female,44,2,58781.76,1,1,0,16874.92,0 +1324,15629244,Bryant,635,Spain,Male,50,7,159453.64,2,0,0,54560.79,1 +1325,15765537,Liang,687,Germany,Male,26,2,142721.52,1,1,1,153605.75,0 +1326,15729975,Chidozie,613,France,Female,46,8,167795.6,1,0,1,44390.38,0 +1327,15682773,Hayward,781,France,Female,38,3,128345.69,2,1,0,63218.85,0 +1328,15688007,Liu,703,Spain,Male,20,3,165260.98,1,1,1,41626.78,0 +1329,15574331,Alexeeva,593,Germany,Female,62,3,118233.81,1,0,1,24765.53,1 +1330,15645572,Calabresi,743,France,Female,40,6,0,1,1,0,28280.8,1 +1331,15742854,Lettiere,640,Spain,Female,46,8,0,2,1,0,89043.19,0 +1332,15575417,Chou,849,Germany,Male,37,7,143452.74,2,1,1,17294.12,0 +1333,15796721,Nnamutaezinwa,778,France,Male,38,3,145018.49,2,1,1,126702.41,0 +1334,15734942,Nnamutaezinwa,539,Germany,Female,38,8,82407.51,1,1,0,13123.41,0 +1335,15664772,Greece,489,Germany,Male,28,1,79460.98,2,1,1,167973.63,0 +1336,15576683,Yin,568,Spain,Female,43,9,0,1,1,0,125870.79,1 +1337,15682563,Larionova,618,Spain,Male,38,5,126473.99,1,1,0,91972.49,0 +1338,15650889,Golubev,710,Germany,Female,30,10,133537.1,2,1,0,155593.74,0 +1339,15612108,Norman,625,France,Male,52,5,164978.01,1,1,1,67788.49,0 +1340,15761132,Capon,682,Spain,Male,46,7,128029.72,1,1,1,62615.35,0 +1341,15645511,Chukwudi,727,Spain,Male,43,2,97403.18,1,1,1,107415.02,1 +1342,15609824,Fedorov,794,France,Female,41,7,176845.41,3,1,0,166526.26,1 +1343,15640268,Avdeeva,652,Spain,Male,71,4,0,1,1,1,120107.1,0 +1344,15645778,Reid,670,Spain,Male,42,3,81589.04,1,1,0,188227.8,0 +1345,15691104,Kennedy,460,Germany,Female,40,6,119507.58,2,1,0,91560.63,1 +1346,15714567,Chan,568,Spain,Female,26,6,0,2,0,0,166495.2,0 +1347,15777826,Wofford,643,France,Male,30,5,94443.77,1,1,1,165614.4,0 +1348,15668445,Mai,521,France,Male,37,2,0,2,1,1,86372.24,0 +1349,15576162,King,615,France,Male,32,7,92199.84,1,1,1,2755.53,0 +1350,15778135,T'ao,575,Spain,Male,43,3,0,1,1,0,83594.51,0 +1351,15613141,Hsu,717,France,Female,41,3,135756.96,1,1,1,103706.41,0 +1352,15635435,White,648,France,Female,54,9,120633.42,1,0,0,5924.38,1 +1353,15596552,Stephens,535,Germany,Male,48,5,134542.73,1,1,1,58203.67,1 +1354,15623644,Frolov,626,Spain,Male,29,7,0,2,1,0,49361.84,0 +1355,15683403,Lombardi,611,Spain,Male,52,7,0,1,0,1,73585.18,1 +1356,15615029,Munro,734,Spain,Male,39,6,0,1,1,1,95135.27,0 +1357,15769005,Hayward,709,France,Male,49,4,154344.49,2,1,1,38794.57,0 +1358,15746326,Fields,591,France,Male,43,3,0,2,0,1,198926.36,0 +1359,15722364,Onwumelu,664,France,Male,43,9,189026.53,2,1,1,56099.86,0 +1360,15704954,Suffolk,431,France,Male,37,0,120764.08,1,1,1,117023.08,0 +1361,15694409,Tsao,647,Germany,Female,22,3,97975.82,2,0,1,62083,0 +1362,15754068,Judd,578,France,Male,32,4,0,2,1,1,141822.8,0 +1363,15683841,Hamilton,555,Germany,Male,41,10,113270.2,2,1,1,185387.14,0 +1364,15789095,T'ang,775,Spain,Male,30,4,0,2,0,1,57461.13,0 +1365,15719958,Degtyarev,850,Germany,Male,39,3,124548.99,2,1,1,120380.12,0 +1366,15689514,Kang,625,France,Male,43,8,201696.07,1,1,0,133020.9,1 +1367,15621353,Hudson,645,Spain,Female,37,7,0,2,1,0,13589.93,0 +1368,15627232,Jibunoh,608,Germany,Male,44,7,114203.47,1,1,1,77830.36,1 +1369,15745843,Kinlaw,689,Spain,Female,31,4,0,2,1,1,136610.02,0 +1370,15722902,Chizuoke,652,Germany,Male,50,8,125437.64,1,1,1,17160.94,1 +1371,15791767,Lucciano,769,France,Female,26,7,0,2,1,0,176843.53,0 +1372,15792722,Omeokachie,611,France,Female,43,8,64897.75,1,1,0,114996.33,0 +1373,15723006,Gorbunova,489,France,Male,38,8,0,2,0,1,196990.79,0 +1374,15771942,Tikhonov,528,Germany,Female,46,9,135555.66,1,1,0,133146.03,1 +1375,15774738,Campa,632,France,Male,44,3,107764.75,1,1,0,185667.72,0 +1376,15574004,Mancini,429,France,Female,27,6,117307.44,2,1,1,24020.49,0 +1377,15587233,Donoghue,457,France,Male,41,8,73700.12,3,1,1,185750.02,1 +1378,15808228,Tuan,768,Spain,Female,44,6,60603.4,1,1,1,178045.97,0 +1379,15682834,Johnstone,715,Spain,Female,35,4,40169.88,2,1,1,199857.47,0 +1380,15571752,Romani,668,Germany,Female,32,10,92041.87,1,1,1,43595.9,0 +1381,15743067,Fuller,625,Germany,Male,26,3,130483.95,1,1,0,122810.53,0 +1382,15714466,Baxter,846,France,Female,41,5,0,3,1,0,3440.47,1 +1383,15617982,Pirozzi,661,Spain,Female,42,3,0,2,1,0,35989.41,0 +1384,15696637,Sung,571,France,Female,23,10,151097.28,1,0,1,17163.75,0 +1385,15690647,Rogers,582,Spain,Female,46,8,67563.31,1,1,0,44506.09,1 +1386,15672756,Mills,716,France,Female,35,8,112808.18,1,0,1,17848.3,0 +1387,15704586,Osonduagwuike,758,France,Female,42,7,0,2,0,1,76209.56,0 +1388,15674526,Byrne,725,France,Male,66,4,86459.8,1,1,1,141476.56,0 +1389,15775295,McIntyre,630,France,Female,40,0,118633.08,1,0,1,60032.46,1 +1390,15684196,Aitken,627,France,Female,55,2,159441.27,1,1,0,100686.11,1 +1391,15727281,Macintyre,653,France,Female,27,9,0,2,1,0,96429.29,0 +1392,15787835,Simpson,775,Germany,Female,38,4,125212.65,2,1,1,15795.88,1 +1393,15730540,Simpson,794,Spain,Male,45,8,88656.37,2,1,0,116547.31,0 +1394,15646276,Metcalfe,831,France,Female,32,2,146033.62,1,1,0,191260.74,0 +1395,15582180,Lees,561,France,Male,29,9,120268.13,1,1,1,173870.39,0 +1396,15697095,Zetticci,705,Spain,Male,46,7,0,2,1,0,117273.35,0 +1397,15748797,Dale,636,Spain,Female,33,0,0,1,1,0,92277.47,1 +1398,15754796,Byrne,487,Germany,Female,46,4,135070.58,2,1,1,44244.49,1 +1399,15628947,Praed,693,France,Female,38,3,0,2,0,0,78133.48,1 +1400,15775546,Laurens,517,Spain,Female,29,5,0,2,1,0,103402.88,0 +1401,15670481,Woods,684,France,Female,27,9,122550.05,2,0,1,137835.82,0 +1402,15619029,Bykov,620,Spain,Female,43,2,0,2,1,0,20670.1,0 +1403,15613282,Vorobyova,757,France,Male,29,8,130306.49,1,1,0,77469.38,0 +1404,15721487,Pirogova,739,France,Female,27,6,0,1,1,1,57572.38,0 +1405,15797276,Sturt,662,Spain,Female,41,4,90350.77,1,1,0,75884.65,1 +1406,15612494,Panicucci,359,France,Female,44,6,128747.69,1,1,0,146955.71,1 +1407,15629617,Cook,572,Spain,Male,23,2,126873.52,1,0,1,67040.12,0 +1408,15600821,Hardy,721,France,Male,69,2,108424.19,1,1,1,178418.35,0 +1409,15579062,Chu,707,France,Male,32,9,0,2,0,0,30807.02,0 +1410,15814268,Franklin,444,France,Female,40,5,84350.07,1,1,0,143835.76,0 +1411,15710164,P'eng,523,France,Female,73,7,0,2,0,0,130883.9,1 +1412,15693904,Chiang,685,Germany,Female,30,4,84958.6,2,0,1,194343.72,0 +1413,15588986,Grant,673,Germany,Female,29,4,99097.36,1,1,1,9796.69,0 +1414,15797733,Udobata,503,Germany,Male,30,10,136622.55,2,0,0,47310.24,0 +1415,15620507,Siciliani,485,Germany,Female,30,5,156771.68,1,1,1,141148.21,0 +1416,15685150,Evans,799,Germany,Male,28,7,167658.33,2,1,1,111138.25,0 +1417,15667651,Young,585,Spain,Female,33,8,0,2,1,0,114182.07,0 +1418,15774166,Mitchell,607,Germany,Female,24,2,109483.54,2,0,1,127560.77,0 +1419,15649280,Lucchese,521,Germany,Female,40,9,134504.78,1,1,0,18082.06,0 +1420,15705657,Hewitt,535,France,Female,44,2,114427.86,1,1,1,136330.26,0 +1421,15753969,K'ung,724,Spain,Male,45,5,83888.54,1,0,1,34121.81,0 +1422,15742378,Swaim,520,Germany,Male,32,5,110029.77,1,1,0,56246.69,0 +1423,15794874,Quinones,696,Spain,Male,41,9,127523.75,1,0,1,191417.42,0 +1424,15589221,Kennedy,657,Germany,Male,30,1,139762.13,2,1,1,23317.88,0 +1425,15596671,Endrizzi,603,Spain,Female,42,8,91611.12,1,0,0,144675.3,1 +1426,15583668,Ludowici,726,France,Female,42,2,109471.79,1,0,1,175161.05,0 +1427,15710206,Larson,591,France,Female,39,4,150500.64,1,1,0,14928.8,0 +1428,15799966,Chigolum,792,Germany,Female,59,9,101609.77,1,0,0,161479.19,1 +1429,15794560,Maclean,550,France,Male,57,5,0,1,1,1,133501.94,0 +1430,15626485,Lu,601,France,Female,26,8,78892.23,1,1,1,23703.52,0 +1431,15703143,Tuan,820,France,Female,29,3,82344.84,1,0,1,115985.38,0 +1432,15809772,Glover,667,France,Male,48,2,0,1,1,0,43229.2,0 +1433,15687959,Landman,573,Spain,Female,44,4,0,1,1,1,94862.93,0 +1434,15585282,Trevisano,755,France,Male,62,1,127706.33,2,0,1,142377.69,0 +1435,15714993,Longo,552,France,Female,41,9,124349.34,1,1,0,135635.25,0 +1436,15596021,K?,598,Spain,Male,44,8,0,2,1,0,148487.9,0 +1437,15646615,Muir,576,Germany,Male,28,1,119336.29,2,0,1,58976.85,0 +1438,15742632,Alexeyeva,670,France,Female,31,9,0,1,0,1,76254.83,0 +1439,15574068,Norman,504,Germany,Male,56,9,104217.3,1,0,0,55857.48,1 +1440,15806967,Simmons,778,France,Female,65,7,0,1,1,1,77867.23,0 +1441,15796334,Chukwualuka,558,Germany,Male,39,10,144757.02,1,1,0,22878.16,1 +1442,15688713,McCall,627,Spain,Male,44,6,0,1,1,1,114469.55,0 +1443,15796179,Moore,683,France,Male,43,8,0,1,1,0,96754.8,0 +1444,15598751,Ingram,556,France,Female,43,6,0,3,0,0,125154.57,1 +1445,15703019,Okeke,583,France,Female,38,10,0,2,0,1,113597.64,0 +1446,15646302,Shao,705,France,Female,24,7,100169.51,1,1,0,121408.55,0 +1447,15680855,Iloabuchi,637,France,Male,33,2,145731.83,1,0,1,109219.43,0 +1448,15697311,Nebechukwu,697,Spain,Male,56,5,110802.03,1,1,1,50230.31,1 +1449,15585367,Diribe,555,Germany,Female,46,4,120392.99,1,1,0,177719.88,1 +1450,15726556,Macgroarty,594,Germany,Female,26,6,135067.52,2,0,0,131211.86,0 +1451,15676242,Artemova,632,Spain,Male,31,3,136556.44,1,1,0,82152.83,1 +1452,15684198,McDonald,551,France,Female,38,10,0,2,1,1,216.27,0 +1453,15774882,Mazzanti,687,France,Female,35,3,99587.43,1,1,1,1713.1,1 +1454,15714227,Kelly,672,France,Female,53,7,0,1,1,1,136910.18,0 +1455,15608653,Davison,521,Spain,Female,34,7,70731.07,1,1,1,20243.97,1 +1456,15784280,Reilly,686,Germany,Male,35,2,109342.82,2,0,1,86043.27,0 +1457,15789546,Ojiofor,639,Spain,Male,28,8,0,2,1,0,126561.07,0 +1458,15590320,Shelton,850,France,Male,66,4,0,2,0,1,64350.8,0 +1459,15678385,Lange,465,France,Male,25,2,78247.31,2,1,1,10472.31,0 +1460,15571778,Trentini,817,France,Female,55,10,117561.49,1,1,0,95941.55,1 +1461,15657085,Gardiner,578,France,Male,23,10,88980.32,1,1,1,125222.36,0 +1462,15640627,Wan,611,Spain,Male,34,4,0,2,1,0,170950.58,0 +1463,15566211,Hsu,616,Germany,Female,41,1,103560.57,1,1,0,236.45,1 +1464,15669293,Hovell,517,France,Male,37,5,113308.84,1,0,1,31517.16,0 +1465,15595067,Zhirov,637,Spain,Female,40,6,0,2,1,1,181610.6,0 +1466,15753566,Espinosa,806,France,Female,32,3,63763.49,1,1,0,156593.09,0 +1467,15650391,Wallace,633,France,Female,29,7,169988.35,1,1,0,4272,0 +1468,15681843,Barbour,624,Germany,Female,35,0,180303.24,2,1,0,163587.9,0 +1469,15814846,Ozerova,691,France,Male,52,3,0,1,1,0,175843.68,1 +1470,15670374,Wright,819,Germany,Female,49,1,120656.86,4,0,0,166164.3,1 +1471,15762332,Ulyanova,568,Germany,Female,31,1,61592.14,2,1,1,61796.64,0 +1472,15700223,Steiner,806,France,Male,48,4,164701.68,1,1,1,21439.49,0 +1473,15729956,Akabueze,726,Spain,Female,26,1,80780.16,1,1,1,19225.85,0 +1474,15594862,Aleksandrova,552,France,Male,36,8,0,2,0,0,132547.02,0 +1475,15598782,Pinto,755,Germany,Female,30,6,154221.37,2,0,1,62688.55,0 +1476,15745080,Griffiths,634,France,Male,26,8,0,1,1,0,21760.96,0 +1477,15703399,McNeil,756,France,Female,26,5,101641.14,2,0,1,154460.68,0 +1478,15732175,Bruno,776,France,Male,37,2,0,1,0,1,8065,0 +1479,15630725,Johnson,649,France,Female,45,5,92786.66,1,1,0,173365.9,1 +1480,15640260,Okorie,595,Germany,Male,32,8,131081.66,2,1,1,69428.79,0 +1481,15716822,Moen,646,France,Male,30,5,98014.74,1,1,1,12757.14,0 +1482,15583748,McGuigan,592,Spain,Male,38,8,0,2,1,0,180426.2,0 +1483,15605968,Fancher,574,France,Male,26,8,97460.1,1,1,1,43093.67,0 +1484,15790683,Matthews,850,France,Male,36,1,104077.19,2,0,1,68594,0 +1485,15607713,Kaeppel,850,Spain,Female,29,1,0,2,1,1,197996.65,0 +1486,15700212,Shih,475,France,Female,46,10,0,2,0,0,122953,1 +1487,15626710,Yudina,642,France,Female,39,4,0,1,1,1,76821.24,0 +1488,15716491,Akabueze,710,Spain,Female,51,4,93656.95,1,0,1,141400.51,1 +1489,15625824,Kornilova,596,Spain,Male,30,6,121345.88,4,1,0,41921.75,1 +1490,15617705,Ozioma,609,France,Female,39,8,141675.23,1,0,1,175664.25,0 +1491,15761976,Su,797,Spain,Female,31,8,0,2,1,0,117916.63,0 +1492,15634891,Jamison,504,Germany,Female,43,7,102365.49,1,1,0,194690.77,1 +1493,15744517,Esposito,735,Spain,Male,50,9,0,1,0,0,166677.35,1 +1494,15686963,Hardiman,680,Spain,Female,30,3,0,1,1,0,160131.58,0 +1495,15808189,Woodard,449,France,Male,52,6,0,2,0,1,123622,0 +1496,15580845,Chienezie,685,Germany,Male,57,7,101868.51,1,0,1,113483.96,0 +1497,15799156,Okwuadigbo,569,Spain,Male,38,8,0,2,0,0,79618.79,0 +1498,15694296,Chineze,631,France,Male,35,9,112392.45,2,1,0,24472.23,0 +1499,15677049,O'Brien,595,Germany,Female,25,7,106570.34,2,0,1,177025.79,0 +1500,15583595,Tao,461,France,Female,28,8,0,1,1,1,103349.74,0 +1501,15590146,Mao,630,France,Male,50,1,81947.76,1,0,1,63606.22,1 +1502,15801548,Buckland,661,France,Female,31,7,144162.3,2,1,1,14490.79,0 +1503,15660833,Flannery,796,Germany,Male,39,5,86350.87,2,0,0,105080.53,0 +1504,15762277,Jamieson,710,France,Male,47,5,158623.14,1,0,0,83499.89,1 +1505,15791302,Swift,741,France,Male,32,8,0,2,1,0,143598.7,0 +1506,15798975,Doherty,606,Germany,Male,48,4,132403.56,1,0,0,36091.91,1 +1507,15599956,Payne,747,France,Male,27,10,0,2,0,0,13007.89,0 +1508,15577274,Genovese,549,Germany,Female,43,3,134985.66,1,1,0,6101.41,0 +1509,15701200,Lucciano,576,France,Male,36,6,0,2,1,1,48314,0 +1510,15638149,Rowley,528,France,Male,37,6,103772.45,1,1,0,197111.99,0 +1511,15786199,Hsing,535,France,Male,33,2,133040.32,1,1,1,110299.78,0 +1512,15701765,Vincent,575,Spain,Female,37,0,0,2,0,0,30114.32,0 +1513,15586974,Pearce,656,France,Male,39,10,0,2,1,1,98894.64,0 +1514,15729040,Lamb,440,France,Male,42,2,0,2,1,0,49826.68,0 +1515,15788676,Riley,539,Spain,Male,38,8,71460.67,2,1,1,10074.05,0 +1516,15602497,Honore,850,Spain,Male,39,6,133214.13,1,0,1,20769.88,0 +1517,15701333,Blackburn,646,France,Female,37,7,96558.66,1,0,0,163427.18,0 +1518,15812071,Endrizzi,744,France,Male,54,6,93806.31,2,0,1,140068.77,0 +1519,15634375,Duncan,710,Spain,Female,36,8,0,2,0,0,83206.19,0 +1520,15738267,Macarthur,544,France,Female,64,3,124043.8,1,1,1,111402.97,1 +1521,15786800,Gould,723,Germany,Male,52,5,131694.97,1,0,1,92873.5,1 +1522,15591130,Medvedev,507,Spain,Female,29,6,0,2,0,1,94780.9,0 +1523,15720662,Sholes,787,France,Female,35,1,106266.8,1,1,1,16607.15,0 +1524,15751531,Shaw,598,Spain,Male,41,8,0,2,1,1,161954.43,0 +1525,15653595,Ts'ai,796,France,Male,51,6,0,2,0,1,194733.28,0 +1526,15568360,Rolon,569,Spain,Female,41,4,139840.36,1,1,1,163524.7,0 +1527,15781210,Reid,711,France,Male,34,8,0,2,0,0,48260.19,0 +1528,15668058,Chinwendu,661,Germany,Male,35,8,124098.54,1,1,0,86678.48,0 +1529,15597131,Fu,415,France,Male,32,5,145807.59,1,1,1,3064.65,0 +1530,15697283,Mackenzie,578,Spain,Male,23,8,0,2,1,0,112124.98,0 +1531,15640953,Bligh,611,France,Female,26,2,107508.93,2,1,1,120801.65,0 +1532,15715031,Davidson,600,France,Female,28,6,0,2,0,1,52193.23,0 +1533,15589660,Lamble,661,Germany,Female,32,1,145980.23,1,0,1,56636.28,0 +1534,15769818,Moore,850,France,Female,37,3,212778.2,1,0,1,69372.88,0 +1535,15782736,Jose,573,Germany,Female,47,4,152522.47,1,0,1,164038.07,1 +1536,15614818,Trevisani,764,Spain,Female,33,9,168964.77,1,0,1,118982.51,0 +1537,15794014,Schofield,838,France,Female,34,8,0,2,1,0,27472.07,0 +1538,15732448,Stewart,821,France,Female,28,8,0,1,1,1,36754.13,0 +1539,15723411,Jamieson,607,Spain,Female,36,4,98266.3,1,1,1,46416.36,0 +1540,15797686,Howard,558,France,Male,38,8,113000.92,1,1,1,152872.39,0 +1541,15605950,Onwuamaeze,530,Germany,Male,23,1,137060.88,2,1,1,165227.23,0 +1542,15812497,D'Albertis,654,Germany,Male,37,5,112146.12,1,1,0,75927.35,0 +1543,15690678,Brooks,530,France,Female,33,4,129307.32,1,1,1,172930.28,0 +1544,15747677,Gordon,656,Spain,Male,69,6,163975.09,1,1,1,36108.5,0 +1545,15618926,Nwachukwu,520,Spain,Male,43,7,0,2,1,1,36202.74,0 +1546,15673908,Chinweike,602,Germany,Female,42,6,158414.85,1,1,1,131886.46,0 +1547,15727944,Simpkinson,701,Germany,Female,48,1,92072.68,1,1,1,133992.36,0 +1548,15807294,Walker,653,Spain,Female,30,2,88243.29,2,1,1,96658.26,0 +1549,15618581,Diribe,668,Spain,Male,25,8,0,2,1,1,135112.09,0 +1550,15584364,Trentini,652,France,Male,48,4,59486.31,1,1,0,163944.18,1 +1551,15599552,Conway,639,Spain,Female,54,2,0,2,1,1,53843.71,0 +1552,15749177,Maslow,730,Spain,Female,52,7,0,2,0,1,122398.84,0 +1553,15718779,Clark,780,France,Male,34,1,0,1,1,1,64804.04,0 +1554,15568106,L?,592,France,Female,38,8,119278.01,2,0,1,19370.73,0 +1555,15779481,Swadling,628,France,Male,34,4,158741.43,2,1,1,126192.54,0 +1556,15709994,Gallo,658,France,Female,40,7,140596.95,1,0,1,135459.02,1 +1557,15772777,Onyemachukwu,850,Spain,Female,29,10,0,2,1,1,94815.04,0 +1558,15706815,Samoylova,515,Germany,Male,37,2,90432.92,1,1,1,188366.04,1 +1559,15618018,Dickson,571,France,Female,35,1,104783.81,2,0,1,178512.52,0 +1560,15671032,He,760,Germany,Male,42,0,77992.97,2,1,1,97906.38,0 +1561,15634281,P'an,720,Germany,Female,43,10,110822.9,1,0,0,72861.94,0 +1562,15766374,Leak,632,Germany,Male,42,4,119624.6,2,1,1,195978.86,0 +1563,15600991,Artemieva,694,Germany,Male,31,6,109052.59,2,1,1,19448.93,1 +1564,15777576,Frost,559,Spain,Female,40,5,139129.44,1,0,1,32635.54,0 +1565,15742613,Warner,773,Germany,Female,42,8,152324.66,2,1,0,171733.22,0 +1566,15649523,Kennedy,581,France,Male,38,1,0,2,1,0,46176.22,0 +1567,15651063,Ifeatu,524,Germany,Female,37,9,127480.58,2,1,0,179634.69,0 +1568,15683124,Evans,713,France,Male,53,6,115029.4,1,0,0,191521.32,1 +1569,15618314,Chu,676,France,Male,40,8,114005.78,1,1,1,67998.45,0 +1570,15670823,Hsueh,651,Germany,Female,42,1,116646.76,1,1,0,44731.8,1 +1571,15607133,Shih,717,Spain,Female,49,1,110864.38,2,1,1,124532.9,1 +1572,15615012,Fan,594,France,Male,23,5,156267.59,1,1,0,160968.44,0 +1573,15725141,Whiddon,716,France,Female,44,3,109528.28,1,1,0,27341.63,1 +1574,15623560,Onyekachukwu,668,France,Female,35,6,102482.76,1,1,1,53994.64,0 +1575,15693018,Ermakova,678,Germany,Male,23,10,115563.71,1,1,1,91633.53,0 +1576,15636756,Marino,545,France,Male,23,2,0,2,1,0,189613.12,0 +1577,15647474,Niu,613,France,Female,40,9,95624.36,2,1,1,60706.33,0 +1578,15576714,Manna,687,Spain,Female,21,8,0,2,1,1,154767.34,0 +1579,15585047,Onyemere,715,France,Male,28,7,160376.61,1,0,0,196853.11,0 +1580,15743976,Archer,618,Germany,Male,41,8,37702.79,1,1,1,195775.48,0 +1581,15793881,Mitchell,721,France,Female,35,6,118273.83,1,0,1,3086.89,0 +1582,15576517,Everingham,445,Germany,Female,34,7,131082.17,2,1,1,70618,0 +1583,15631072,Huie,690,France,Male,38,1,94456,2,0,1,55034.02,0 +1584,15730394,Crowther,709,France,Female,43,8,0,2,0,0,168035.62,1 +1585,15631460,Swift,671,Spain,Female,42,3,0,2,1,1,128449.33,0 +1586,15692002,Skelton,538,France,Male,33,6,93791.38,1,1,1,199249.29,0 +1587,15595282,White,735,France,Female,33,4,0,2,1,0,149474.69,0 +1588,15789548,Giordano,592,France,Female,37,7,0,2,1,1,126726.33,0 +1589,15758035,Bateson,747,France,Male,61,7,155973.13,1,0,1,147554.26,0 +1590,15617518,Hu,675,Germany,Male,36,7,89409.95,1,1,1,149399.7,0 +1591,15651802,Day,632,Spain,Female,39,5,97854.37,2,1,0,93536.38,0 +1592,15631813,Beneventi,621,France,Male,39,6,0,2,1,1,58883.91,0 +1593,15729668,Elizabeth,521,Spain,Male,29,3,60280.62,1,1,0,154271.41,0 +1594,15741728,Atkins,591,Spain,Male,36,7,135216.8,1,1,1,122022.89,0 +1595,15576676,Serrano,706,Germany,Female,28,6,124923.35,2,1,1,50299.14,0 +1596,15711378,Willis,677,France,Male,38,4,0,2,1,0,187800.63,0 +1597,15765520,Stevenson,769,Germany,Male,27,7,188614.07,1,1,0,171344.09,0 +1598,15656726,Ch'ien,771,France,Male,32,5,62321.62,1,1,1,40920.59,0 +1599,15647842,Cunningham,601,Germany,Female,48,8,120782.7,1,1,0,63940.68,1 +1600,15719309,Stephens,670,France,Female,42,1,115961.58,2,0,1,29483.87,0 +1601,15748718,Gordon,517,France,Male,28,2,115062.61,1,1,0,179056.23,0 +1602,15594404,Bevan,834,France,Female,49,8,160602.25,2,1,0,129273.94,0 +1603,15751158,Mashman,571,France,Female,42,4,108825.34,3,1,0,55558.51,1 +1604,15593470,Tu,576,Germany,Female,36,8,166287.85,1,1,1,23305.85,0 +1605,15695129,Milanesi,718,France,Female,31,1,152663.77,1,0,1,17128.64,0 +1606,15640865,Romano,636,Germany,Female,31,9,80844.69,2,1,1,74641.9,0 +1607,15714080,Goliwe,566,Germany,Female,40,2,97001.36,2,1,0,154486.01,0 +1608,15648721,Hsueh,711,France,Male,64,4,0,2,1,1,3185.67,0 +1609,15801466,Gray,574,France,Female,39,2,122524.61,2,1,0,88463.63,0 +1610,15750248,Wright,619,France,Female,35,8,132292.63,1,1,0,65682.93,0 +1611,15758726,Chiemeka,588,France,Female,24,0,0,2,1,1,140586.08,0 +1612,15781553,Chung,760,Germany,Female,49,9,91502.99,1,1,0,117232.9,1 +1613,15649121,Pinto,665,France,Male,52,3,0,1,1,0,116137.01,1 +1614,15674811,Kellway,739,Germany,Male,29,3,59385.98,2,1,1,105533.96,0 +1615,15646037,Sopuluchi,641,France,Male,77,9,0,3,1,1,81514.06,0 +1616,15722578,Spitzer,685,Germany,Female,21,6,97956.5,1,1,1,164966.27,0 +1617,15665695,Potter,594,France,Female,49,4,0,2,1,1,23631.55,0 +1618,15801062,Matthews,557,Spain,Female,40,4,0,2,0,1,105433.53,0 +1619,15662955,Nicholls,697,France,Male,27,8,141223.68,2,1,0,90591.15,0 +1620,15770309,McDonald,656,France,Male,18,10,151762.74,1,0,1,127014.32,0 +1621,15657386,Fiorentini,712,Germany,Male,43,1,141749.74,2,0,1,90905.26,0 +1622,15777797,Kovalyova,689,Spain,Male,38,5,75075.14,1,1,1,8651.92,1 +1623,15783955,Miah,697,France,Female,25,4,165686.11,2,1,0,15467.98,0 +1624,15804516,Builder,589,France,Male,38,2,0,1,1,0,79915.28,0 +1625,15681758,Baddeley,525,Spain,Female,25,10,0,2,1,0,69361.95,0 +1626,15630321,Hu,680,France,Male,44,3,0,2,1,0,86935.08,0 +1627,15588248,Hs?,617,France,Female,28,0,0,2,1,1,7597.83,1 +1628,15591932,Ford,680,France,Male,32,5,92961.61,1,1,0,116957.6,0 +1629,15810347,Todd,662,Spain,Female,30,9,0,2,0,1,157884.83,0 +1630,15595303,Johnston,736,Germany,Male,46,5,130812.91,1,1,1,77981.54,1 +1631,15634950,Obiajulu,657,Germany,Male,57,8,107174.58,1,1,1,126369.55,1 +1632,15685372,Azubuike,350,Spain,Male,54,1,152677.48,1,1,1,191973.49,1 +1633,15745827,Padovesi,617,France,Male,30,3,132005.77,1,1,0,142940.39,0 +1634,15755868,Farmer,562,France,Male,35,7,0,1,0,0,48869.67,0 +1635,15735222,Ignatieff,705,Spain,Female,23,5,0,2,1,1,73131.73,0 +1636,15604804,Lu,516,France,Female,33,7,127305.5,1,1,1,120037.36,0 +1637,15718944,Artemiev,573,France,Female,37,6,0,2,1,0,193995.37,0 +1638,15678626,Okonkwo,538,Spain,Female,31,0,0,2,0,0,179453.66,0 +1639,15571550,Dore,699,France,Male,39,9,0,1,1,0,80963.92,0 +1640,15723053,T'ang,504,Germany,Male,32,8,170291.22,2,0,1,15658.99,0 +1641,15661528,Ashbolt,583,Spain,Male,47,5,102562.23,1,1,0,92708.1,0 +1642,15754177,Bazarova,712,Spain,Male,53,2,111061.01,2,0,0,26542.17,0 +1643,15683544,Buccho,626,Spain,Male,62,3,0,1,1,1,65010.74,0 +1644,15708048,Burn,631,France,Female,34,4,124379.14,1,1,0,106892.91,0 +1645,15701109,Andreyev,663,France,Female,37,7,0,1,1,1,185210.63,0 +1646,15600110,Endrizzi,506,Germany,Female,41,3,57745.76,1,1,0,4035.46,0 +1647,15651533,Brown,570,Germany,Female,50,5,129293.74,1,1,0,177805.44,1 +1648,15777904,Nock,703,France,Female,45,7,0,2,1,1,68831.72,0 +1649,15655574,Okeke,698,Germany,Female,40,8,150777.1,1,1,0,114732.62,0 +1650,15569423,Cunningham,731,Spain,Male,41,4,0,2,1,0,22299.27,0 +1651,15718106,Kelley,625,France,Male,34,6,0,2,0,0,197283.2,0 +1652,15585067,Wilson,634,Spain,Male,31,9,108632.48,1,1,1,179485.96,1 +1653,15675501,Woods,616,France,Male,59,5,153861.1,1,1,1,17699.48,0 +1654,15633233,McFarland,500,France,Male,56,1,100374.58,1,1,0,118490.8,1 +1655,15667134,Cisneros,446,France,Male,32,8,0,2,0,0,133292.94,0 +1656,15659105,Borchgrevink,669,France,Female,47,9,61196.54,1,1,0,58170.24,0 +1657,15575409,Rozhkova,581,Germany,Male,31,6,116891.72,1,1,0,107137.3,0 +1658,15752342,Bradley,704,Germany,Female,54,6,133656.91,3,1,0,145071.33,1 +1659,15654851,Obialo,748,France,Male,44,2,92911.52,1,0,1,85495.24,0 +1660,15741429,Hudson,680,Spain,Female,31,9,119825.75,2,1,1,101139.3,0 +1661,15682356,Veltri,655,France,Female,37,7,111852.84,2,1,0,10511.13,0 +1662,15806447,Mazzanti,690,Germany,Male,32,0,106683.52,2,1,1,137916.49,0 +1663,15800229,Thorpe,695,Germany,Male,40,7,139022.24,1,0,1,193383.13,0 +1664,15663441,Golibe,700,Germany,Female,40,4,148571.07,1,1,0,189826.96,1 +1665,15791991,Udinesi,773,France,Male,52,4,0,1,0,1,144113.42,0 +1666,15775082,Stewart,749,France,Male,42,1,129776.72,2,0,1,143538.51,0 +1667,15579706,Curtis,611,France,Female,46,5,0,1,1,0,77677.14,1 +1668,15718247,Hayden,606,Spain,Female,46,8,0,2,1,1,183717.94,0 +1669,15755722,H?,554,France,Male,24,10,0,1,0,0,92180.62,0 +1670,15582259,Campbell,567,France,Female,37,7,0,2,1,1,28690.9,0 +1671,15716994,Green,559,Spain,Male,24,3,114739.92,1,1,0,85891.02,1 +1672,15586880,P'eng,594,Germany,Male,41,2,122545.65,2,1,1,42050.24,0 +1673,15713854,Cremonesi,513,France,Female,37,6,0,2,1,0,110142.34,0 +1674,15780835,Liang,652,Germany,Female,26,1,131908.35,1,1,1,179269.79,0 +1675,15675896,Gough,680,Germany,Female,42,7,105722.69,1,1,1,90558.24,1 +1676,15658459,Bates,784,Spain,Male,33,10,0,2,1,0,162022.47,0 +1677,15658057,Padovesi,812,Spain,Female,44,8,0,3,1,0,66926.83,1 +1678,15801767,Yin,784,Spain,Female,40,8,0,2,1,0,108891.3,0 +1679,15569178,Kharlamov,570,France,Female,18,4,82767.42,1,1,0,71811.9,0 +1680,15731478,Nicholls,712,France,Female,42,1,87842.98,1,0,0,92223.59,0 +1681,15811236,Burns,705,Spain,Male,39,6,133261.13,1,1,1,78065.9,0 +1682,15746749,Fleming,681,Spain,Female,32,3,0,2,1,1,59679.9,0 +1683,15662758,Watson,620,France,Male,41,0,97925.11,1,1,0,85000.32,0 +1684,15709387,Obiajulu,711,France,Male,52,5,0,1,1,1,159808.95,0 +1685,15572093,Han,613,France,Female,24,7,140453.91,1,1,0,129001.3,0 +1686,15713826,Ferguson,613,Germany,Female,20,0,117356.19,1,0,0,113557.7,1 +1687,15570205,Tao,682,Spain,Male,36,5,0,2,1,1,147758.51,0 +1688,15589348,Le Grand,850,Spain,Male,37,4,137204.77,1,1,1,28865.59,0 +1689,15804610,Valdez,601,France,Female,41,1,0,2,0,1,160607.06,0 +1690,15700854,Cunningham,595,Spain,Male,35,8,0,1,1,0,100015.79,1 +1691,15758836,Godfrey,675,Spain,Male,36,3,54098.18,2,0,1,54478.52,0 +1692,15772933,Mai,591,Spain,Male,31,8,0,1,1,1,141677.33,0 +1693,15809006,Walker,602,France,Male,23,7,113758.48,2,0,0,84077.6,0 +1694,15689612,Pirozzi,554,Spain,Female,34,8,0,1,0,1,106981.03,0 +1695,15744614,Feng,541,France,Male,37,9,118636.92,1,1,1,73551.44,0 +1696,15704250,Akabueze,506,France,Male,34,7,0,2,0,0,115842.1,0 +1697,15700255,Robson,814,Germany,Male,44,8,95488.82,2,0,0,107013.59,0 +1698,15669410,Yevdokimova,683,France,Male,30,8,110829.52,2,0,0,24938.84,0 +1699,15807595,Ijendu,485,Germany,Male,51,7,144244.59,2,1,0,51113.14,0 +1700,15664523,Colombo,696,Germany,Female,31,8,122021.92,2,1,0,33828.64,0 +1701,15642833,Akubundu,608,France,Female,30,8,0,2,1,0,128875.86,0 +1702,15605279,Francis,792,France,Male,50,9,0,4,1,1,194700.81,1 +1703,15713644,Marshall,686,Spain,Male,22,5,0,2,1,0,158974.45,0 +1704,15750466,Rhodes,790,Germany,Male,42,1,85839.62,1,1,0,198182.73,0 +1705,15739054,Y?,654,France,Female,29,4,96974.97,1,0,1,141404.07,0 +1706,15612771,Bell,452,France,Male,35,4,148172.44,1,1,1,4175.68,0 +1707,15788483,Kerr,719,Spain,Male,38,0,0,1,1,0,126876.47,0 +1708,15732832,Jideofor,707,France,Female,40,5,0,2,1,0,41052.82,0 +1709,15772892,Robertson,699,France,Female,49,2,0,1,0,0,105760.01,0 +1710,15713843,Kao,850,Spain,Male,30,2,0,2,0,1,27937.12,0 +1711,15567993,Palmer,828,Spain,Male,28,8,134766.85,1,1,0,79355.87,0 +1712,15617603,Mackay,850,Germany,Male,30,5,123210.56,2,1,1,102180.27,0 +1713,15744983,Burgmann,712,Spain,Male,47,1,139887.01,1,1,1,95719.73,0 +1714,15630419,Davis,634,France,Male,44,9,149961.11,1,1,0,57121.51,0 +1715,15738828,Milano,730,Germany,Male,45,6,152880.97,1,0,0,162478.11,0 +1716,15778025,Dellucci,685,Germany,Male,43,9,108589.47,2,0,1,194808.51,0 +1717,15799479,Coles,809,Spain,Male,33,9,0,1,1,1,124045.65,0 +1718,15684269,Gray,707,Spain,Female,35,3,56674.48,1,1,0,17987.4,1 +1719,15762745,Macvitie,648,Spain,Male,32,8,0,1,1,0,133653.38,0 +1720,15746970,Townsend,760,Spain,Female,57,1,0,2,1,1,25101.17,0 +1721,15725024,Pope,805,Germany,Female,33,3,105663.56,2,0,1,33330.89,0 +1722,15592116,Jensen,585,France,Female,39,7,0,2,1,0,2401.26,0 +1723,15624391,Thomson,595,Spain,Female,30,5,100683.54,1,1,1,178361.04,0 +1724,15567422,Chiazagomekpele,630,France,Male,42,6,0,2,1,0,162697.93,0 +1725,15612627,Ozuluonye,627,Germany,Male,29,5,139541.58,2,1,0,80607.33,0 +1726,15574879,Wright,631,Germany,Female,37,2,121801.72,2,0,1,23146.62,0 +1727,15745107,Lung,776,Germany,Male,38,5,112281.7,1,0,1,89893.6,0 +1728,15734491,Lombardo,676,Spain,Female,36,4,0,2,1,1,3173.31,0 +1729,15675320,Leonard,758,Spain,Female,40,5,93499.82,2,0,0,123218.81,0 +1730,15643824,Johnston,637,France,Male,33,0,132255.99,2,0,1,74588.41,0 +1731,15643438,P'eng,850,France,Male,20,7,0,2,1,0,31288.77,0 +1732,15721730,Amechi,601,Spain,Female,44,4,0,2,1,0,58561.31,0 +1733,15680727,Fang,735,France,Male,49,5,121973.28,1,1,0,148804.36,0 +1734,15752508,Docherty,614,Germany,Male,32,7,99462.8,2,1,1,51117.06,0 +1735,15808846,Horton,672,Germany,Female,21,3,165878.76,2,1,1,164537.17,0 +1736,15727251,Vincent,642,France,Male,30,8,117494.27,1,0,0,61977.82,0 +1737,15663489,Onio,633,Germany,Female,29,0,138577.34,1,1,0,193362.99,0 +1738,15683677,Schiavone,769,Spain,Male,39,9,0,1,1,1,47722.79,0 +1739,15596414,Chandler,796,Spain,Male,41,8,107525.07,1,1,0,18510.41,0 +1740,15730639,Fiorentino,715,France,Male,23,7,139224.92,2,1,0,65057.71,0 +1741,15672132,Butusov,695,France,Female,42,7,121453.63,1,0,0,46374.64,0 +1742,15742638,Wang,747,France,Female,25,4,0,2,0,1,42039.67,0 +1743,15578603,Alexeieva,584,Germany,Female,54,1,77354.37,1,0,0,138192.98,1 +1744,15726088,Vinogradova,476,France,Male,40,6,0,1,1,1,22735.45,0 +1745,15682533,Hughes,850,France,Female,39,7,79259.99,1,0,1,186910.74,0 +1746,15772995,Ts'ao,529,France,Male,30,2,116295.29,1,1,0,75285.47,0 +1747,15765694,Bage,584,Spain,Female,59,1,0,1,0,1,130260.11,1 +1748,15659486,Yudina,586,Germany,Male,34,9,74309.81,1,1,0,15034.93,0 +1749,15568963,Naquin,674,Germany,Male,34,2,152797.9,1,1,0,175709.4,1 +1750,15703820,Endrizzi,552,France,Male,42,9,133701.07,2,1,0,101069.71,1 +1751,15569410,Tang,601,Germany,Female,33,7,114430.18,2,1,1,153012.13,0 +1752,15632256,Schroeder,541,France,Male,29,7,127504.57,1,0,0,86173.92,0 +1753,15724466,Swearingen,744,Germany,Female,41,2,84113.41,1,1,0,197548.63,0 +1754,15777639,McGregor,595,Spain,Female,23,10,101126.66,2,0,0,37042.8,0 +1755,15802501,Onyeorulu,724,Germany,Male,33,5,103564.83,2,1,0,121085.72,0 +1756,15778410,Clarke,533,Spain,Female,52,7,0,1,0,1,194113.99,1 +1757,15670702,Smith,618,France,Male,37,2,168178.21,2,0,1,101273.23,0 +1758,15704763,Kozlova,523,Germany,Female,39,1,143903.11,1,1,1,118711.75,1 +1759,15645544,Nekrasov,642,Germany,Female,30,5,129753.69,1,1,0,582.53,0 +1760,15757646,Olague,584,France,Male,35,9,0,2,1,0,192381.21,0 +1761,15701121,Holt,521,France,Male,38,5,110641.18,1,0,1,136507.69,1 +1762,15796313,Olsen,662,France,Female,36,4,166909.2,2,1,0,138871.12,1 +1763,15815660,Mazzi,758,France,Female,34,1,154139.45,1,1,1,60728.89,0 +1764,15602844,Niu,717,France,Male,38,7,97459.06,1,0,0,189175.71,0 +1765,15636238,Graham,611,France,Male,40,1,0,2,1,1,102547.56,0 +1766,15770101,Millar,766,Germany,Male,43,6,112088.04,2,1,1,36706.56,0 +1767,15645543,Bell,636,France,Female,34,3,0,2,1,1,44756.25,0 +1768,15596397,Kelly,814,France,Female,48,7,0,2,1,1,132870.15,0 +1769,15770525,T'an,760,Spain,Male,28,1,141038.57,2,0,0,16287.38,0 +1770,15684267,Davila,607,Germany,Male,39,2,84468.67,2,1,1,121945.42,0 +1771,15689980,Willis,725,Spain,Female,36,4,118520.26,1,0,0,131173.9,1 +1772,15633260,Dumetochukwu,600,France,Male,37,1,142663.46,1,0,1,88669.89,0 +1773,15756471,Giles,656,Germany,Male,27,4,118627.16,2,1,1,160835.3,0 +1774,15721303,O'Meara,640,Spain,Male,34,1,137523.02,1,0,0,24761.36,0 +1775,15802256,Yao,439,France,Male,28,7,110976.23,2,1,0,138526.96,0 +1776,15725664,Wallace,549,France,Female,38,8,107283.4,1,0,0,157442.75,0 +1777,15674851,T'ien,622,France,Male,38,5,0,2,0,0,105295.77,0 +1778,15701946,Ndubueze,715,France,Male,34,4,124314.45,1,0,0,97782.92,0 +1779,15748947,Chukwuraenye,657,France,Female,41,5,95858.37,1,1,1,68255.88,0 +1780,15673342,K'ung,703,France,Male,36,2,0,2,1,0,108790.95,0 +1781,15601008,Stevenson,802,France,Male,33,8,0,2,1,0,143706.18,0 +1782,15771636,Marshall,793,Spain,Female,36,0,0,1,0,0,148993.47,0 +1783,15642002,Hayward,554,France,Female,35,6,117707.18,2,0,0,95277.15,1 +1784,15693381,Tipton,533,Spain,Male,38,1,135289.33,2,0,1,152956.33,0 +1785,15607691,Gibson,658,France,Male,36,8,174060.46,1,1,1,94925.62,0 +1786,15589380,Fraser,713,Germany,Male,40,3,114446.84,2,1,1,87308.18,0 +1787,15603846,Fang,711,Spain,Male,37,2,0,2,1,0,83978.86,1 +1788,15753549,Dubinina,669,France,Male,25,1,157848.53,1,0,0,37543.93,1 +1789,15725355,Morey,439,France,Female,43,8,0,1,0,1,104889.3,0 +1790,15773017,Todd,763,Spain,Female,37,6,0,2,1,1,149705.25,0 +1791,15625641,Forbes,697,Germany,Female,74,3,108071.36,2,1,1,16445.79,0 +1792,15776467,De Salis,702,Spain,Female,35,8,14262.8,2,1,0,54689.16,0 +1793,15746451,Barry,686,Spain,Male,41,7,102749.72,1,0,1,194913.86,0 +1794,15777922,Afamefuna,629,Spain,Male,36,1,161757.87,2,1,1,146371.72,0 +1795,15606841,Ibbott,823,France,Male,38,1,0,2,1,0,156603.7,0 +1796,15757648,Marshall,683,Germany,Female,35,5,95698.79,1,0,1,182566.76,0 +1797,15677173,Law,555,France,Male,37,9,124969.13,1,1,0,60194.05,0 +1798,15764170,Pinto,647,Germany,Male,44,4,93960.35,1,1,0,36579.53,1 +1799,15610446,Chinedum,714,France,Female,51,4,88308.87,3,0,0,5862.53,1 +1800,15612776,McKay,850,Spain,Female,39,10,0,2,1,1,143030.09,0 +1801,15794122,Otutodilinna,713,France,Female,59,3,0,2,1,1,62700.08,0 +1802,15774931,She,452,France,Male,30,7,112935.87,1,1,1,99017.34,0 +1803,15779247,Pai,683,Spain,Female,24,8,98567.1,1,1,0,187987.01,0 +1804,15707078,Kruglov,577,France,Female,26,1,180530.51,1,0,0,123454.62,0 +1805,15605263,Chin,552,France,Male,33,5,140931.57,1,0,1,10921.5,0 +1806,15607381,King,769,Germany,Female,31,7,148913.72,2,1,0,53817.23,0 +1807,15683471,Hansen,691,France,Male,38,7,0,2,0,0,81617.4,0 +1808,15605037,Ting,818,France,Female,49,2,0,1,0,1,192298.84,1 +1809,15576085,Stone,739,France,Male,41,5,0,2,0,0,143882.25,0 +1810,15770435,McLean,639,France,Female,50,6,115335.32,2,1,1,53130.41,0 +1811,15592994,Zikoranachidimma,651,France,Female,65,0,0,2,1,1,190454.04,0 +1812,15624068,Fu,779,France,Female,26,0,0,2,0,1,111906,0 +1813,15595221,Trevisano,850,Germany,Female,33,7,134678.13,1,1,0,113177.95,0 +1814,15637131,Fallaci,829,France,Male,38,9,0,2,1,0,30529.88,0 +1815,15613471,Wiley,579,Germany,Male,31,2,90547.48,2,1,1,18800.13,0 +1816,15583499,Chiagoziem,510,France,Male,32,9,103324.78,1,1,1,46127.7,0 +1817,15752816,Murray,531,France,Male,29,3,114590.58,1,0,0,75585.48,0 +1818,15804075,Chuang,628,Germany,Female,36,3,91286.51,1,1,0,63085.94,0 +1819,15800517,Huang,633,Spain,Male,32,5,163340.12,2,1,1,74415.2,0 +1820,15712319,Chukwukere,714,Spain,Male,45,8,150900.29,2,0,1,139889.15,0 +1821,15797389,Hsia,604,Spain,Male,23,9,124577.33,1,1,1,7267.25,0 +1822,15621432,Lee,630,Spain,Male,35,1,0,2,0,0,186826.22,0 +1823,15779390,Theus,850,Spain,Female,31,4,91292.7,1,1,1,162149.07,0 +1824,15711219,Jennings,788,Germany,Female,57,8,93716.72,1,1,1,180150.49,1 +1825,15770498,Parker,798,France,Female,37,4,111723.08,1,1,1,83478.12,0 +1826,15678727,Tan,770,Germany,Male,45,4,110765.68,1,1,0,26163.74,1 +1827,15573893,Barry,569,Germany,Male,25,9,173459.45,2,1,1,44381.06,0 +1828,15740104,Tuan,425,Spain,Female,22,7,169649.73,2,0,1,136365,1 +1829,15792649,Patterson,547,Spain,Female,31,9,0,2,0,0,99294.22,0 +1830,15605275,Ofodile,725,Germany,Male,45,8,116917.07,1,0,0,173464.43,1 +1831,15572467,Chandler,506,France,Male,37,5,0,2,1,1,127543.81,0 +1832,15738219,Nash,632,France,Female,36,7,0,2,1,1,52526.65,0 +1833,15600710,Atkinson,620,France,Male,22,0,0,1,1,0,32589.45,0 +1834,15804394,Brenan,663,Germany,Male,32,8,130627.66,1,1,0,47161.25,1 +1835,15694188,Obidimkpa,700,Spain,Female,46,5,56580.95,2,0,1,45424.13,0 +1836,15583718,Terry,696,Germany,Male,38,6,142316.14,1,1,1,8018.49,0 +1837,15802478,Spring,767,Spain,Male,31,6,0,2,1,1,195668,0 +1838,15619343,Mahmood,561,France,Male,56,7,152759,2,1,0,133167.11,1 +1839,15758813,Campbell,350,Germany,Male,39,0,109733.2,2,0,0,123602.11,1 +1840,15761374,Bellucci,706,France,Male,54,9,117444.51,1,1,1,186238.85,0 +1841,15569209,Amaechi,464,Spain,Female,34,5,76001.57,1,1,1,158668.87,0 +1842,15788539,Foxall,501,France,Female,34,3,107747.57,1,1,0,9249.36,0 +1843,15747222,Bentley,745,Spain,Female,35,8,0,2,1,1,116581.1,0 +1844,15769346,Baird,587,France,Female,36,1,134997.49,2,1,0,44688.08,0 +1845,15699634,Howard,667,France,Female,48,2,0,2,1,1,148608.39,0 +1846,15589076,Henry,737,France,Male,36,9,0,1,0,1,188670.9,1 +1847,15812338,Sopuluchukwu,485,Spain,Female,30,7,0,1,1,0,107067.37,0 +1848,15758845,Rocher,590,Spain,Female,37,0,64345.21,1,0,1,61759.33,1 +1849,15685844,White,518,Germany,Female,35,8,141665.63,1,0,1,192776.64,0 +1850,15583090,Komar,581,Spain,Female,29,8,0,2,1,0,46735.19,0 +1851,15587581,Russo,785,Germany,Female,33,5,136624.6,2,1,1,169117.74,0 +1852,15633640,Loewenthal,799,France,Female,52,4,161209.66,1,1,1,89081.41,0 +1853,15573741,Aliyeva,698,Spain,Male,38,10,95010.92,1,1,1,105227.86,0 +1854,15633574,Montes,730,France,Female,41,4,167545.32,1,1,0,128246.81,0 +1855,15711455,Kuo,740,Germany,Female,36,4,109044.6,1,0,0,94554.74,1 +1856,15570601,Cheng,785,France,Female,47,9,122031.55,1,1,1,33823.5,1 +1857,15690925,McIntosh,527,Spain,Female,29,2,27755.97,1,1,0,97468.44,1 +1858,15709338,T'ao,544,France,Female,29,1,118560.55,1,1,1,164137.36,0 +1859,15780746,Tyndall,705,France,Male,61,4,0,2,1,1,191313.7,0 +1860,15681956,Bailey,684,France,Male,34,9,0,2,1,1,65257.57,0 +1861,15778190,Onyekaozulu,639,Spain,Female,28,8,97840.72,1,1,1,178222.77,0 +1862,15786852,Nwachukwu,565,Germany,Female,38,2,158651.29,2,1,1,179445.28,0 +1863,15726494,Romani,481,France,Male,44,9,175303.06,1,1,0,65500.53,1 +1864,15641183,Chin,731,Spain,Male,25,8,96950.21,1,1,0,97877.92,0 +1865,15805312,Bellucci,607,France,Male,45,7,123859.6,1,0,1,113051.57,0 +1866,15636572,Christmas,760,France,Female,32,7,0,2,1,1,105969.05,0 +1867,15632575,Moore,559,France,Female,70,9,0,1,1,1,122996.76,0 +1868,15740164,Genovesi,715,France,Female,33,3,85227.84,1,1,1,68087.15,0 +1869,15574947,Cartwright,656,France,Male,36,8,97786.08,2,0,1,21478.36,0 +1870,15597909,Johnstone,652,Germany,Male,33,7,128135.99,1,1,0,158437.73,0 +1871,15782574,Warner,624,Spain,Male,33,6,0,2,0,0,76551.7,0 +1872,15734999,Stephenson,634,Spain,Male,36,2,85996.19,1,1,0,15887.68,0 +1873,15706593,Ellis,850,Spain,Female,50,10,0,2,1,1,33741.84,0 +1874,15766686,Nebechi,659,Germany,Female,39,1,104502.11,1,1,0,20652.69,0 +1875,15590268,Chu,529,Spain,Male,35,5,95772.97,1,1,1,112781.5,0 +1876,15763055,Onuchukwu,572,Spain,Male,31,5,98108.79,1,0,1,119996.95,0 +1877,15664754,Steele,640,Germany,Male,39,9,131607.28,4,0,1,6981.43,1 +1878,15643630,Quaife,770,Spain,Male,55,9,63127.41,2,1,0,185211.28,1 +1879,15641043,Scott,648,Spain,Male,35,7,0,2,1,1,78436.36,0 +1880,15768095,Yeh,579,France,Male,31,9,0,1,0,1,139048,0 +1881,15811314,Y?,589,Germany,Female,36,9,140355.56,2,1,0,136329.96,0 +1882,15669922,Conti,530,Spain,Female,36,2,0,2,1,1,14721.8,0 +1883,15707114,Holder,831,France,Male,30,2,0,2,0,1,3430.38,0 +1884,15670602,Burgess,790,Germany,Male,24,7,107418.27,1,0,1,160450.21,0 +1885,15713479,Ozuluonye,656,France,Male,35,6,0,2,1,0,1485.27,0 +1886,15663830,De Luca,563,Spain,Male,32,6,0,2,1,1,19720.08,0 +1887,15566958,Li Fonti,667,Spain,Male,39,7,167557.12,1,1,1,41183.02,0 +1888,15680918,Freeman,613,Spain,Male,34,8,117300.02,1,1,0,139410.08,0 +1889,15663921,Pisani,429,France,Male,60,7,0,2,1,1,163691.48,0 +1890,15716324,Ignatieff,665,France,Female,23,9,143672.9,1,1,1,115147.33,0 +1891,15796969,Lahti,731,France,Male,33,4,0,2,1,1,74945.11,0 +1892,15574783,Perkins,584,France,Female,37,1,0,2,1,1,180363.56,0 +1893,15773487,Conway,634,Germany,Female,31,8,76798.92,1,0,0,196021.73,0 +1894,15802486,Hayes,488,France,Male,34,3,0,2,1,1,125979.36,0 +1895,15783398,Rizzo,535,Spain,Female,49,7,115309.75,1,1,0,111421.77,0 +1896,15649418,Krylov,776,France,Female,29,7,178171.04,2,1,1,115818.51,0 +1897,15604588,Li Fonti,850,Spain,Female,38,3,0,2,0,1,179360.76,0 +1898,15735428,Talbot,673,Spain,Female,37,0,0,2,0,0,82351.06,0 +1899,15629078,Matthias,850,Germany,Female,45,5,127258.79,1,1,1,192744.23,1 +1900,15806880,Boyle,627,Spain,Female,30,6,0,1,1,1,113408.47,0 +1901,15754999,Ch'eng,570,France,Female,33,8,0,1,1,1,124641.42,0 +1902,15781034,Mason,796,Spain,Male,67,5,0,2,0,1,54871.02,0 +1903,15622017,Bruno,773,Spain,Female,33,10,0,1,1,1,98820.09,0 +1904,15705885,Smeaton,752,Spain,Male,36,2,0,2,1,1,45570.84,0 +1905,15677382,Miller,625,Spain,Female,69,1,107569.96,1,1,1,182336.45,0 +1906,15566843,Gotch,535,Germany,Male,20,9,134874.4,1,1,1,118825.56,0 +1907,15608387,Fu,786,France,Female,29,4,0,2,1,0,103372.79,0 +1908,15810786,O'Toole,620,France,Female,67,3,0,2,1,1,43486.73,0 +1909,15626983,Ledford,605,Spain,Female,48,6,0,2,1,1,40062.99,0 +1910,15773605,Iadanza,670,Spain,Female,32,3,0,2,1,0,46175.7,0 +1911,15811261,Alaniz,617,Spain,Male,42,0,70105.87,1,1,1,120830.73,0 +1912,15590606,Saunders,595,France,Male,41,9,0,2,1,0,5967.09,0 +1913,15576644,Lin,687,Germany,Female,29,4,78939.15,1,1,0,122134.56,1 +1914,15750264,Pinto,757,Germany,Male,30,6,105128.85,2,1,1,62972.13,0 +1915,15741554,Streeter,746,Spain,Male,31,2,113836.27,1,1,1,174815.54,0 +1916,15769051,Shaw,503,Spain,Male,25,7,0,1,0,1,192841.13,0 +1917,15812198,Chen,543,Germany,Male,48,1,100900.5,1,0,0,33310.72,1 +1918,15699772,Barclay,428,Germany,Female,40,3,129248.11,2,1,0,72876.43,1 +1919,15744105,Kodilinyechukwu,768,France,Female,28,3,109118.05,2,0,1,50911.41,0 +1920,15739858,Otitodilichukwu,618,France,Male,56,7,0,1,1,1,142400.27,1 +1921,15723720,McKenzie,591,France,Female,31,7,0,2,0,1,48778.46,0 +1922,15638355,Woods,658,France,Female,35,5,126397.66,1,0,0,156361.58,1 +1923,15805637,Hsing,625,France,Male,36,9,108546.16,3,1,0,133807.77,1 +1924,15629575,Wheare,717,France,Male,36,2,148061.89,1,1,0,179128.69,1 +1925,15586243,Yobachi,667,France,Male,44,8,122277.87,1,1,1,91810.71,0 +1926,15757931,Fang,804,France,Male,24,3,0,2,1,0,173195.33,0 +1927,15716023,Pearson,693,France,Male,31,1,0,2,0,1,182270.88,0 +1928,15647782,Brown,729,Germany,Male,36,8,152899.24,2,1,0,177130.33,0 +1929,15716609,L?,484,Germany,Male,54,3,134388.11,1,0,0,49954.79,1 +1930,15623791,Padovesi,632,Spain,Female,40,3,109740.62,1,1,0,141896.74,0 +1931,15627262,Soto,536,Germany,Male,23,6,92366.72,2,1,0,120661.71,0 +1932,15652693,Greco,573,France,Female,26,4,129109.02,1,0,0,149814.68,1 +1933,15586993,Giordano,655,Spain,Female,56,5,0,2,1,1,41782.7,0 +1934,15815560,Bogle,666,Germany,Male,74,7,105102.5,1,1,1,46172.47,0 +1935,15584930,Grimmett,726,Germany,Male,30,5,111375.32,2,1,0,2704.09,0 +1936,15799031,Ayers,523,France,Male,39,3,0,2,1,0,6726.53,0 +1937,15810457,Miller,728,Germany,Female,33,9,150412.14,2,1,0,170764.08,0 +1938,15697879,Webb,701,France,Male,30,3,156660.72,2,1,0,45742.42,0 +1939,15594902,Lombardi,518,France,Male,38,3,90957.81,1,0,1,162304.59,0 +1940,15799710,Wei,739,France,Male,37,7,104960.46,1,0,1,80883.82,0 +1941,15659651,Ross,531,Germany,Female,31,7,117052.82,1,1,0,118508.09,1 +1942,15645956,Jideofor,452,Spain,Male,44,3,88915.85,1,1,0,69697.74,0 +1943,15651713,King,684,France,Male,45,6,148071.39,1,1,0,183575.01,0 +1944,15737265,Nwokeocha,728,Germany,Male,39,6,152182.83,1,0,0,161203.6,0 +1945,15687310,Humphries,783,Spain,Male,39,9,0,2,1,0,143752.77,0 +1946,15607347,Olisaemeka,734,France,Male,22,5,130056.23,1,0,0,121894.31,1 +1947,15698321,Yobanna,648,Germany,Male,34,3,95039.73,2,1,1,147055.87,0 +1948,15657812,Ch'iu,688,France,Male,52,1,0,2,1,1,172033.57,0 +1949,15569187,Fleming,680,Spain,Male,35,9,0,2,0,0,143774.06,0 +1950,15681562,Trevisan,516,France,Female,43,2,112773.73,2,1,1,139366.58,0 +1951,15615456,Aleksandrova,680,France,Female,37,10,123806.28,1,1,0,81776.84,1 +1952,15589793,Onwuamaeze,604,France,Male,53,8,144453.75,1,1,0,190998.96,1 +1953,15781884,Knox,624,Germany,Male,27,9,94667.29,2,0,1,4470.52,0 +1954,15675190,Chia,623,France,Male,21,10,0,2,0,1,135851.3,0 +1955,15600734,Townsend,624,Spain,Male,51,5,174397.21,2,1,1,172372.63,0 +1956,15779176,Dike,565,Germany,Female,58,3,108888.24,3,0,1,135875.51,1 +1957,15605286,Moyes,565,France,Male,55,4,118803.35,2,1,1,128124.7,1 +1958,15674922,Beavers,710,France,Male,54,6,171137.62,1,1,1,167023.95,1 +1959,15737506,Tretiakova,645,France,Male,42,6,0,1,0,0,149807.01,0 +1960,15780514,Fuller,707,France,Male,33,8,136678.52,1,1,0,54290.62,0 +1961,15623647,Dellucci,655,Spain,Female,36,1,135515.76,1,1,0,86013.96,0 +1962,15668472,Ritchie,705,Spain,Female,24,5,177799.83,2,0,0,79886.06,0 +1963,15692416,Aikenhead,358,Spain,Female,52,8,143542.36,3,1,0,141959.11,1 +1964,15771139,Douglas,578,Germany,Male,34,8,147487.23,2,1,0,66680.77,0 +1965,15738318,Kung,800,France,Female,40,5,97764.41,1,1,0,98640.15,1 +1966,15772243,MacDonald,612,France,Female,33,9,0,1,0,0,142797.5,1 +1967,15638463,Okwudilichukwu,681,Germany,Female,48,8,139480.18,1,1,1,163581.67,0 +1968,15598088,Ni,559,Spain,Male,25,5,0,2,1,1,163221.22,0 +1969,15693468,Simmons,488,Spain,Female,39,9,140553.46,1,0,0,12440.44,0 +1970,15671930,H?,717,France,Female,36,5,0,2,1,1,145551.6,0 +1971,15762268,Hancock,666,France,Female,41,10,141162.08,1,1,0,50908.48,0 +1972,15780954,Cran,582,Spain,Male,26,4,65848.36,2,1,0,30149.21,0 +1973,15700174,McKay,733,Spain,Female,30,0,83319.28,1,0,0,57769.2,0 +1974,15635728,P'an,693,France,Male,41,4,0,2,0,0,156381.47,0 +1975,15679283,Parkhill,694,France,Female,33,4,129731.64,2,1,0,178123.86,0 +1976,15591386,Golubova,622,France,Female,35,5,0,2,1,0,51112.8,0 +1977,15694192,Nwankwo,598,Spain,Female,38,6,0,2,0,0,173783.38,0 +1978,15585901,Johnson,717,Spain,Male,35,1,0,3,0,0,174770.14,1 +1979,15792329,Mao,494,Germany,Male,37,5,107106.33,2,1,0,172063.09,0 +1980,15635597,Echezonachukwu,644,France,Male,33,8,0,2,1,1,155294.17,0 +1981,15775880,McElyea,554,France,Female,30,9,0,2,1,1,40320.3,0 +1982,15630913,Rosas,476,Spain,Female,69,1,105303.73,1,0,1,134260.34,0 +1983,15756680,Phillips,667,France,Male,28,6,165798.1,1,1,0,147090.9,0 +1984,15587913,Palerma,748,Spain,Female,40,4,0,2,1,0,132368.47,0 +1985,15737605,Morris,531,Spain,Female,45,1,126495.57,2,1,1,164741.5,0 +1986,15627876,Pavlova,719,Spain,Female,47,9,116393.59,1,1,0,63051.32,1 +1987,15772601,Lu,845,Germany,Female,41,2,81733.74,2,0,0,199761.29,0 +1988,15758606,Yamamoto,738,France,Male,54,4,0,1,0,1,55725.04,1 +1989,15657107,Angelo,563,Spain,Female,46,8,106171.68,1,1,0,163145.5,1 +1990,15622454,Zaitsev,695,Spain,Male,28,0,96020.86,1,1,1,57992.49,0 +1991,15775803,Cawker,841,Spain,Male,41,1,0,2,0,1,193093.77,0 +1992,15570859,Froggatt,626,Germany,Male,36,2,181671.16,2,1,1,57531.14,0 +1993,15748381,Gorbunov,613,France,Female,29,6,185709.28,2,1,1,77242.19,0 +1994,15787189,Tai,824,Germany,Male,60,8,134250.17,3,0,0,153046.16,1 +1995,15666055,Rowe,705,France,Female,49,7,0,1,1,0,63405.2,1 +1996,15617648,Mikkelsen,584,France,Female,44,5,95671.75,2,1,1,106564.88,0 +1997,15755678,Kovalyov,534,France,Male,62,2,0,2,0,0,42763.12,1 +1998,15624781,Mbanefo,672,France,Female,34,1,142151.75,2,1,1,168753.34,0 +1999,15779497,Ts'ai,603,France,Male,43,5,127823.93,1,1,1,19483.35,0 +2000,15567399,Enderby,633,Germany,Male,43,3,144164.29,1,1,1,158646.46,0 +2001,15613656,Lombardi,842,France,Male,58,1,63492.94,1,1,1,83172.19,0 +2002,15734311,Hamilton,661,France,Female,27,3,0,2,1,1,76889.79,0 +2003,15657214,Hsia,601,France,Male,74,2,0,2,0,1,51554.58,0 +2004,15799350,Mao,632,France,Male,41,0,106134.46,1,0,1,105570.39,0 +2005,15729970,Ugochukwu,684,Germany,Male,29,8,127269.75,1,0,1,79495.01,0 +2006,15725835,West,785,Germany,Female,32,3,124493.03,2,0,1,52583.79,1 +2007,15745543,Hughes,687,France,Male,39,7,0,2,1,0,26848.25,0 +2008,15727384,Chukwuemeka,705,Germany,Female,43,10,146547.78,1,0,1,10072.55,1 +2009,15666916,Lira,639,France,Male,43,6,99610.92,2,1,0,187296.78,0 +2010,15732917,Li,729,Germany,Male,46,5,117837.43,1,1,0,104016.61,1 +2011,15612050,Castiglione,556,Spain,Female,48,8,168522.37,1,1,1,151310.16,0 +2012,15726267,Paterson,570,France,Male,32,9,117337.54,2,0,1,62810.91,0 +2013,15780124,Blair,841,France,Male,74,9,108131.53,1,0,1,60830.38,0 +2014,15742238,Dellucci,705,Germany,Male,35,4,136496.12,2,1,0,116672.02,0 +2015,15679024,Udinesi,553,France,Male,32,3,116324.53,1,1,0,77304.49,0 +2016,15715297,Yuan,779,Germany,Female,40,2,75470.23,1,1,1,52894.01,0 +2017,15633612,Yuryeva,696,France,Male,28,4,172646.82,1,1,1,116471.43,0 +2018,15602929,Wilson,728,Spain,Female,37,4,0,1,0,0,4539.38,0 +2019,15696703,Dean,691,Germany,Male,27,3,160358.68,2,1,0,142367.72,0 +2020,15756668,Ross,706,France,Male,30,3,98415.37,1,1,1,110520.48,0 +2021,15565779,Kent,627,Germany,Female,30,6,57809.32,1,1,0,188258.49,0 +2022,15795519,Vasiliev,716,Germany,Female,18,3,128743.8,1,0,0,197322.13,0 +2023,15761477,Golibe,501,Germany,Male,24,4,130806.42,2,1,0,80241.14,0 +2024,15731890,Chukwukere,601,France,Male,41,1,123971.16,1,0,1,172814.99,0 +2025,15633043,Fedorova,545,Spain,Female,39,6,0,1,0,0,38410.74,1 +2026,15752953,Chien,634,France,Male,45,9,0,2,0,0,17622.82,0 +2027,15603088,Rossi,451,Spain,Female,23,9,0,2,0,1,48021.71,0 +2028,15606613,Samson,655,France,Female,59,7,0,1,1,0,88958.49,1 +2029,15635939,Fenton,458,France,Female,39,9,0,2,1,0,116343.09,0 +2030,15666043,Mackey,520,France,Male,33,4,156297.58,2,1,1,166102.61,0 +2031,15746190,Payton,624,Spain,Female,28,2,0,2,0,1,104353.26,0 +2032,15591357,Cowger,765,France,Male,51,3,123372.3,1,1,1,115429.32,0 +2033,15658716,Banks,667,Germany,Female,37,5,92171.35,3,1,0,178106.34,1 +2034,15679909,Pugliesi,665,Spain,Male,41,8,0,2,1,0,132152.32,0 +2035,15634262,Fantin,709,Germany,Male,34,4,148375.19,2,1,1,21521.38,0 +2036,15799825,Bentley,583,France,Female,44,8,0,2,1,1,27431.62,0 +2037,15756875,Freeman,782,Spain,Male,34,6,147422.44,1,0,1,42143.61,0 +2038,15678146,Wong,668,Spain,Female,24,7,173962.32,1,0,0,106457.11,1 +2039,15710743,Onwuamaeze,621,France,Male,47,0,0,1,1,1,133831.37,1 +2040,15595831,Shen,579,Germany,Female,64,6,145215.43,1,1,1,164083.72,0 +2041,15626684,Huang,547,France,Female,38,5,167539.97,1,0,1,159207.34,0 +2042,15709846,Yeh,840,France,Female,39,1,94968.97,1,1,0,84487.62,0 +2043,15635459,Shih,667,Germany,Female,27,3,106116.5,2,1,0,3674.71,0 +2044,15642544,Henderson,723,France,Male,34,5,0,2,0,1,12092.03,0 +2045,15566494,Fang,487,France,Male,45,2,0,2,1,0,77475.73,0 +2046,15655238,Dellucci,668,France,Female,31,9,0,2,0,0,41291.73,0 +2047,15733429,Chou,520,Germany,Male,34,8,120018.86,2,1,1,343.38,0 +2048,15814536,Conti,549,France,Male,37,2,112541.54,2,0,0,47432.43,0 +2049,15771702,Roberts,567,France,Female,35,5,166118.45,2,1,0,127827.18,0 +2050,15723008,Lo Duca,720,France,Female,45,1,102882.4,2,1,1,35633.15,1 +2051,15797160,Glover,492,France,Female,49,8,0,1,1,1,182865.09,1 +2052,15792222,Johnstone,712,France,Female,37,1,106881.5,2,0,0,169386.81,0 +2053,15644765,Ashton,689,Germany,Male,26,4,120727.97,1,0,1,149073.88,0 +2054,15610686,Melton,850,France,Male,63,8,169832.57,1,0,0,184107.26,1 +2055,15730868,Marshall,747,France,Male,41,5,0,2,1,1,22750.17,0 +2056,15705991,Kenenna,469,Germany,Male,38,9,113599.42,1,0,0,11950.29,0 +2057,15577078,Zakharov,539,Spain,Male,38,6,0,1,1,1,152880.07,1 +2058,15679550,Chukwualuka,743,France,Male,32,9,0,2,1,0,175252.78,0 +2059,15787655,Chu,707,France,Male,47,3,0,2,1,0,174303.29,0 +2060,15668081,Capon,581,Spain,Female,50,4,0,2,1,1,80701.72,0 +2061,15747980,Cattaneo,737,Spain,Male,38,6,146282.79,2,1,0,198516.2,0 +2062,15710295,Patrick,445,Germany,Female,38,6,119413.62,2,1,0,175756.36,0 +2063,15724443,Taylor,703,Germany,Female,29,3,122084.63,1,0,1,82824.08,0 +2064,15571305,Stephenson,588,Germany,Female,35,1,103060.63,1,1,0,179866.01,1 +2065,15569503,Yeh,765,France,Male,44,6,0,2,1,1,159899.97,0 +2066,15581840,DeRose,626,France,Male,33,8,0,2,1,0,138504.28,0 +2067,15772262,Vavilov,545,Germany,Male,37,9,110483.86,1,1,1,127394.67,0 +2068,15767794,Browne,744,France,Male,31,9,120718.28,1,1,1,58961.49,0 +2069,15629338,Collingridge de Tourcey,658,Spain,Female,31,2,36566.96,1,1,0,103644.98,1 +2070,15790379,Rowe,629,Germany,Male,28,8,108601,1,1,1,119647.7,0 +2071,15750684,Jibunoh,719,France,Female,42,4,0,1,1,0,28465.86,1 +2072,15697214,Korovin,686,Spain,Female,36,5,0,2,1,1,152979.14,0 +2073,15711015,Hammonds,743,France,Male,36,4,0,2,1,1,190911.02,0 +2074,15573309,Ward,626,Spain,Female,48,2,0,2,1,1,95794.98,0 +2075,15805303,Olisanugo,661,Germany,Male,44,1,141136.62,1,1,0,189742.78,1 +2076,15741385,Gallop,710,Germany,Male,45,9,108231.37,1,1,1,188574.08,0 +2077,15780254,Gartrell,654,France,Male,40,6,0,1,0,0,183872.88,1 +2078,15744843,K'ung,569,Spain,Female,34,6,144855.34,1,0,0,196555.32,0 +2079,15815626,Oluchi,640,France,Male,63,2,68432.45,2,1,1,112503.24,1 +2080,15784736,Jamieson,562,France,Male,45,6,136855.24,1,1,0,46864,0 +2081,15813412,Barlow,721,France,Female,55,3,44020.89,1,1,0,65864.4,1 +2082,15809143,White,456,Germany,Male,32,9,133060.63,1,1,1,125167.92,0 +2083,15617617,Stewart,811,Spain,Male,39,7,0,2,1,1,177519.39,0 +2084,15779738,Buccho,534,France,Male,24,1,0,1,1,1,169653.32,0 +2085,15668669,Benson,423,France,Female,36,5,97665.61,1,1,0,118372.55,1 +2086,15687477,Thompson,594,Germany,Male,28,5,185013.02,1,1,0,16481.12,0 +2087,15578908,Todd,725,Spain,Female,32,0,0,2,1,1,138525.19,0 +2088,15687658,Burgin,716,France,Female,52,7,65971.61,2,1,0,14608,1 +2089,15615020,Nnaife,595,Germany,Female,41,9,150463.11,2,0,1,81548.38,0 +2090,15608886,Okwudiliolisa,679,France,Female,33,1,0,2,0,0,69608.48,0 +2091,15602551,Johnson,667,Spain,Male,39,9,0,2,1,0,68873.8,0 +2092,15672945,Parkes,661,France,Female,37,5,136425.18,1,1,0,81102.81,0 +2093,15757408,Lo,655,Spain,Male,38,3,250898.09,3,0,1,81054,1 +2094,15806132,Martin,555,France,Male,55,4,146798.81,1,1,1,74149.77,0 +2095,15813022,Kapustina,531,Spain,Male,70,1,0,2,0,0,99503.19,0 +2096,15673578,Page,611,Germany,Female,40,7,128486.91,2,1,0,10109.47,0 +2097,15757916,Amaechi,600,France,Female,38,9,0,2,1,1,58855.85,0 +2098,15689168,Munro,531,Spain,Male,37,1,143407.29,2,0,1,84402.46,0 +2099,15769216,Panicucci,601,France,Female,43,2,0,1,1,0,49713.87,1 +2100,15593295,Greathouse,548,France,Male,57,6,76165.65,1,1,1,133537.53,0 +2101,15804814,Ts'ui,759,France,Male,40,4,0,2,1,0,124615.59,0 +2102,15778934,Napolitani,678,Spain,Female,49,8,0,2,0,1,98090.69,0 +2103,15802351,Beers,755,Germany,Female,33,6,90560.3,2,1,1,42607.69,0 +2104,15630241,Tretyakova,594,France,Male,61,3,62391.22,1,1,1,192434.11,0 +2105,15719561,Lin,768,France,Male,42,5,0,3,0,0,60686.4,0 +2106,15615096,Costa,492,France,Female,31,7,0,2,1,1,49463.44,0 +2107,15659931,Ibezimako,637,Germany,Female,55,1,123378.2,1,1,0,81431.99,1 +2108,15714586,Marcelo,646,Spain,Female,42,3,99836.47,1,0,1,22909.56,0 +2109,15634949,Hay,593,Germany,Male,74,5,161434.36,2,1,1,65532.17,0 +2110,15589224,Moore,596,Spain,Male,41,5,0,2,0,1,141053.85,0 +2111,15795990,Lumholtz,722,Germany,Female,48,10,138311.76,1,1,1,3472.63,1 +2112,15603216,Simpson,642,France,Male,25,7,0,2,1,0,102083.78,0 +2113,15631201,Hill,472,Spain,Female,28,4,0,2,1,0,1801.77,0 +2114,15686255,Mouzon,738,Germany,Male,35,6,101744.84,1,0,0,85185.44,0 +2115,15746594,Wu,732,Spain,Male,33,8,0,1,1,0,119882.7,0 +2116,15718893,Pirozzi,404,Germany,Female,54,4,125456.07,1,1,0,83715.66,1 +2117,15671609,Ibeabuchi,701,France,Male,44,7,0,2,1,0,23425.78,0 +2118,15652540,Garnsey,683,France,Male,31,2,0,2,0,1,77326.78,0 +2119,15774857,Synnot,460,France,Female,27,7,0,2,1,0,156150.08,1 +2120,15791836,Wildman,690,France,Male,29,5,0,2,1,0,108577.97,0 +2121,15651554,Anenechukwu,618,Germany,Female,54,4,118449.21,1,1,1,133573.29,1 +2122,15583576,Tai,671,France,Male,30,2,0,1,0,1,102057.86,0 +2123,15732740,Plant,765,Spain,Female,32,9,178095.55,1,0,0,47247.56,0 +2124,15723320,Azubuike,651,Germany,Female,25,2,109175.14,2,1,0,114566.47,0 +2125,15603851,Galkin,704,France,Male,32,7,127785.17,4,0,0,184464.7,1 +2126,15777923,Johnston,544,France,Female,45,6,0,2,0,1,151401.33,0 +2127,15735719,Babbage,790,France,Female,40,9,0,2,1,1,70607.1,0 +2128,15703482,Walker,710,Germany,Male,34,9,134260.36,2,1,0,147074.67,0 +2129,15605835,Rice,743,France,Male,37,8,69143.91,2,0,1,105780.18,0 +2130,15664881,Norton,702,France,Male,34,4,100054.77,1,1,0,109496.45,0 +2131,15757568,Bogolyubov,704,France,Female,45,6,0,1,1,1,137739.45,0 +2132,15792660,Gibbons,614,France,Male,38,2,116248.88,1,1,0,105140.92,0 +2133,15599722,Chia,609,Spain,Female,43,6,86053.52,2,1,1,113276.46,1 +2134,15726354,Smith,688,France,Female,32,6,123157.95,1,1,0,172531.23,0 +2135,15610355,Hunter,713,France,Male,44,1,63438.91,1,1,0,64375.4,0 +2136,15704284,Ekechukwu,736,Germany,Male,57,9,95295.39,1,1,0,28434.44,1 +2137,15621893,Bellucci,727,France,Male,18,4,133550.67,1,1,1,46941.41,0 +2138,15588219,Ford,850,France,Female,38,1,106871.81,2,1,0,29333.01,0 +2139,15688619,Scott,718,Spain,Male,45,3,105266.32,2,1,1,193724.51,0 +2140,15765518,Gregson,643,France,Female,51,2,105229.53,1,1,0,34967.75,1 +2141,15616931,Moore,653,France,Male,41,8,102768.42,1,1,0,55663.85,0 +2142,15758372,Wallace,674,France,Male,18,7,0,2,1,1,55753.12,1 +2143,15782591,Cook,690,France,Male,35,6,112689.95,1,1,0,176962.31,0 +2144,15612109,Speth,819,France,Male,38,9,122334.26,2,1,1,181507.44,0 +2145,15613712,Boag,634,Spain,Male,34,1,0,2,1,0,61995.57,0 +2146,15639322,Grave,633,Spain,Male,33,4,137847.41,2,1,0,98349.13,0 +2147,15594349,Streeten,850,France,Male,49,5,122486.47,1,0,1,59748.19,0 +2148,15574167,Fox,665,France,Male,33,2,101286.11,1,1,1,159840.51,0 +2149,15811842,Artemyeva,630,Spain,Male,26,7,0,2,1,1,6656.64,0 +2150,15648794,Giordano,836,Spain,Male,57,4,101247.06,1,1,0,37141.62,1 +2151,15771211,Perkins,668,France,Male,38,10,86977.96,1,0,1,37094.75,0 +2152,15588614,Walton,753,France,Male,57,7,0,1,1,0,159475.08,1 +2153,15630698,Hay,745,France,Female,55,9,110123.59,1,0,1,51548.14,1 +2154,15694200,Gardner,693,France,Male,36,8,178111.82,1,0,0,58719.63,1 +2155,15721426,Milne,606,Germany,Male,65,10,126306.64,3,0,0,7861.68,1 +2156,15725997,She,660,France,Female,35,6,100768.77,1,1,0,19199.61,0 +2157,15762138,Hu,608,France,Male,42,5,0,2,1,0,178504.29,0 +2158,15750649,Uwakwe,744,France,Female,44,3,0,2,1,1,189016.14,0 +2159,15685706,Bird,731,France,Female,40,7,118991.79,1,1,1,156048.64,0 +2160,15641835,Anderson,683,France,Male,72,3,140997.26,1,0,1,52876.41,0 +2161,15586821,Bellew,727,France,Male,28,5,0,2,0,1,19653.08,0 +2162,15569678,Cocci,561,Germany,Male,32,6,166824.59,1,1,0,139451.98,0 +2163,15793842,Krichauff,700,France,Female,34,2,76322.69,1,1,0,128136.29,0 +2164,15667554,Cameron,605,France,Male,35,6,0,2,1,1,45206.57,0 +2165,15794479,Becker,767,Spain,Male,77,8,149083.7,1,1,1,190146.83,0 +2166,15585041,Ainsworth,511,France,Male,33,7,0,2,0,1,158313.87,0 +2167,15780650,Biryukov,667,France,Male,40,9,0,1,1,1,96670.2,0 +2168,15780846,Redding,787,France,Male,33,1,126588.81,2,0,1,62163.53,0 +2169,15805260,Wood,705,Germany,Female,56,2,143249.67,1,1,0,88428.41,1 +2170,15621629,Scott,773,Germany,Male,43,8,81844.91,2,1,1,35908.46,0 +2171,15662151,Gould,554,France,Male,40,4,0,1,0,1,168780.04,0 +2172,15747174,Hao,526,Germany,Male,58,9,190298.89,2,1,1,191263.76,0 +2173,15651585,Power,661,Germany,Male,35,2,117212.18,1,1,1,83052.03,0 +2174,15649738,White,698,France,Female,46,0,0,2,1,1,125962.02,0 +2175,15633108,Thorpe,646,France,Male,26,4,139848.17,1,1,0,164696.27,0 +2176,15769254,Tuan,757,Germany,Female,34,9,101861.36,2,0,0,187011.96,0 +2177,15704746,Inman,699,Spain,Male,35,2,167455.66,2,1,1,55324.49,0 +2178,15637644,Hanson,667,France,Female,24,4,0,2,0,1,34335.55,0 +2179,15609562,MacDonald,774,Spain,Female,43,1,116360.07,1,1,0,17004.14,0 +2180,15787459,Parkes,745,Spain,Male,40,3,88466.82,1,0,0,116331.42,0 +2181,15762902,Stanley,649,France,Female,42,7,0,2,0,1,22974.01,0 +2182,15738605,Fischer,634,Germany,Female,46,5,123642.36,1,1,1,49725.16,1 +2183,15724889,Chinweuba,665,Spain,Male,38,9,0,1,0,1,87412.74,0 +2184,15730735,Henning,713,France,Male,38,9,72286.84,2,1,1,26136.89,0 +2185,15689147,Ogochukwu,652,France,Female,40,1,0,2,1,0,126554.96,0 +2186,15730397,Narelle,739,Spain,Male,40,1,109681.61,1,1,1,193321.3,0 +2187,15762169,Bergman,556,Germany,Male,37,9,145018.64,2,1,0,90928.02,1 +2188,15589320,Sagese,699,Spain,Male,34,8,0,1,1,1,76510.46,0 +2189,15799211,Anenechi,708,Spain,Female,32,8,187487.63,1,1,1,120115.5,0 +2190,15798310,Palerma,480,France,Male,35,2,165692.91,1,1,1,197984.58,0 +2191,15609998,Okwudilichukwu,700,Germany,Female,59,5,137648.41,1,1,0,142977.05,1 +2192,15583548,Harrison,525,Spain,Female,47,6,118560,1,1,0,82522.61,1 +2193,15761763,Jamieson,845,France,Male,33,8,164385.53,1,1,0,150664.97,0 +2194,15764409,Goodman,613,France,Male,37,9,108286.5,1,1,1,114153.44,0 +2195,15710161,Ko,850,France,Female,34,2,0,2,1,1,171706.66,0 +2196,15735246,Norman,798,Spain,Female,58,9,0,2,0,0,119071.56,1 +2197,15791700,Ugochukwutubelum,773,Germany,Male,47,2,118079.47,4,1,1,143007.49,1 +2198,15670753,Uvarova,614,Spain,Male,35,2,127283.78,1,1,1,31302.35,0 +2199,15573876,Chia,473,Spain,Male,48,8,0,2,1,0,71139.8,0 +2200,15770174,Piazza,762,France,Male,29,6,141389.06,1,1,0,54122.89,0 +2201,15641114,Power,701,France,Male,37,8,130091.5,1,1,1,120031.29,0 +2202,15682435,P'eng,600,France,Male,35,4,143744.77,2,1,0,104076.51,0 +2203,15751788,Johnson,850,Spain,Male,28,9,97408.03,1,1,1,175853.64,0 +2204,15672598,Walker,613,Spain,Male,30,9,111927.45,1,1,1,175795.87,0 +2205,15762803,Innes,509,France,Male,31,3,0,2,1,0,15360.91,0 +2206,15812982,Francis,509,Spain,Male,38,2,0,1,0,0,168460.12,0 +2207,15597901,Chidozie,609,France,Male,34,1,0,1,1,1,181177.9,0 +2208,15731507,Mackenzie,456,France,Female,33,1,188285.68,1,0,0,58363.94,0 +2209,15809826,Craigie,728,France,Female,46,2,109705.52,1,1,0,20276.87,1 +2210,15764237,Manfrin,663,Spain,Male,33,9,0,2,0,0,91514.62,0 +2211,15769917,Onyekachi,673,Germany,Female,34,1,127122.79,3,0,1,76703.1,0 +2212,15641850,Pethard,717,France,Male,40,0,98241.04,1,1,0,110887.14,0 +2213,15770974,Nwabugwu,741,Germany,Female,37,8,170840.08,2,0,0,109843.16,0 +2214,15803749,DeRose,498,Germany,Female,41,4,87541.06,2,1,1,12577.21,1 +2215,15684999,Ch'eng,850,France,Female,26,4,62610.96,2,0,1,179365.1,0 +2216,15770225,Padovesi,493,France,Male,36,9,0,2,1,1,65816.53,0 +2217,15627484,Obielumani,686,France,Female,47,5,113328.93,1,1,0,124170.9,0 +2218,15610337,Stephens,666,Spain,Male,35,2,104832.49,1,1,0,175015.12,0 +2219,15752488,Emery,733,Spain,Female,31,9,102289.85,1,1,1,115441.66,0 +2220,15610056,Dufresne,631,Germany,Female,34,6,125227.82,2,0,1,128247.03,0 +2221,15806049,Lee,714,Germany,Female,49,5,140510.89,1,1,0,141914.94,0 +2222,15736069,Hsing,767,Germany,Female,35,6,132253.22,1,1,0,115566.57,1 +2223,15763662,Longo,711,Germany,Male,43,2,39043.29,2,1,1,175423.69,0 +2224,15615575,Vial,722,France,Male,34,8,0,2,1,1,133447.49,0 +2225,15691723,Chukwudi,631,Spain,Male,55,9,99685.06,1,1,0,114474.98,0 +2226,15774098,Grant,701,Germany,Male,38,3,125385.49,2,0,1,52044.66,0 +2227,15750808,Ma,790,Spain,Male,46,2,131365.37,2,1,1,180290.68,0 +2228,15744368,Sun,633,Spain,Male,58,6,98308.51,1,1,1,132034.13,0 +2229,15610594,Moss,644,France,Female,37,8,0,2,1,0,20968.88,0 +2230,15756125,Booth,757,Spain,Male,44,5,140856.16,2,1,0,158735.1,0 +2231,15623277,Ross,696,France,Female,30,8,0,2,1,1,196134.44,0 +2232,15795954,Ndukaku,746,France,Male,35,2,172274.01,1,1,0,22374.97,0 +2233,15671969,Pruneda,649,Spain,Male,36,8,0,2,1,0,161668.15,0 +2234,15791268,Neumann,565,Spain,Male,38,0,122447.76,1,0,0,67339.34,0 +2235,15713655,Calabrese,720,France,Female,38,10,0,2,1,1,56229.72,1 +2236,15633930,Yobachukwu,648,Spain,Female,56,6,157559.59,2,1,0,140991.23,1 +2237,15712849,Tung,632,Germany,Male,41,3,126550.7,1,0,0,177644.52,1 +2238,15639077,Marchesi,622,France,Female,30,2,158584.82,3,1,0,142342.55,1 +2239,15808784,Hess,835,France,Male,28,2,163569.61,2,1,1,154559.28,0 +2240,15648577,Pickering,493,France,Female,31,3,0,1,1,1,176570.28,1 +2241,15670345,Mazzi,785,Germany,Female,33,6,127211.45,1,0,0,191961.83,0 +2242,15633112,Madukaego,681,Germany,Male,42,3,118199.97,2,1,0,9452.88,1 +2243,15714397,Trentino,621,Germany,Female,30,2,101014.08,2,1,1,165257.31,0 +2244,15780038,Paterson,756,Spain,Male,38,6,119208.85,1,1,0,169763.89,1 +2245,15756305,Marchesi,515,France,Female,66,6,0,2,1,1,160663.11,0 +2246,15578799,Anayolisa,625,France,Female,58,10,53772.73,1,1,1,192072.1,1 +2247,15800326,Poole,717,Spain,Female,39,6,0,2,1,0,93275.61,0 +2248,15785485,Zhou,595,Germany,Female,41,2,138878.81,1,0,1,112269.67,0 +2249,15783958,Bates,539,Spain,Female,37,1,130922.81,2,0,0,2186.83,0 +2250,15727546,Olejuru,762,France,Male,35,9,0,2,1,1,43075.7,0 +2251,15739576,Bustard,706,Spain,Male,20,8,0,2,1,1,12368.11,0 +2252,15631333,Wade,677,Spain,Female,25,8,130866.19,1,1,0,42410.21,0 +2253,15604782,Tan,733,Germany,Female,33,7,187257.94,1,0,1,190430.81,0 +2254,15589643,Ngozichukwuka,684,Spain,Female,41,7,0,1,1,1,138394.37,0 +2255,15585533,Calabrese,679,France,Male,36,6,147733.64,1,0,1,172501.38,0 +2256,15681506,Lane,478,Spain,Male,43,1,0,2,1,1,197916.43,0 +2257,15630551,Forbes,696,France,Male,33,2,163139.27,1,1,1,7035.36,0 +2258,15698349,Davy,686,Spain,Female,35,4,0,2,1,1,159676.55,0 +2259,15776631,Ma,466,France,Female,36,5,119540.15,1,0,1,80603.99,0 +2260,15762216,Barrera,686,France,Female,41,4,129553.76,2,1,0,187599.8,0 +2261,15623927,Alexander,576,France,Male,55,9,0,2,1,1,94450.97,0 +2262,15681402,Ngozichukwuka,763,Germany,Female,61,1,66101.89,1,1,1,143981.27,0 +2263,15586264,Murray,572,France,Male,43,2,140431.98,1,1,0,26450.57,1 +2264,15594685,Hall,757,France,Female,49,2,0,2,0,0,164482.92,0 +2265,15812945,Padovesi,582,France,Female,29,0,0,1,1,1,84012.81,0 +2266,15734628,Lysaght,623,France,Female,35,5,0,2,1,0,101192.08,0 +2267,15629323,Kelechi,617,Germany,Female,37,4,116471.43,2,1,0,175324.74,1 +2268,15666823,Nebechi,425,France,Male,39,4,0,2,1,0,197226.32,0 +2269,15777553,Hanson,659,France,Female,56,9,123785.24,1,1,0,99504.03,1 +2270,15613097,Kao,605,France,Female,33,4,0,2,0,1,83700.66,0 +2271,15622217,Tu,538,France,Female,38,8,88758.95,2,0,0,28226.15,1 +2272,15703588,Palerma,665,Germany,Male,25,5,153611.83,2,1,0,35321.65,0 +2273,15570835,Fallaci,491,Germany,Female,57,4,112044.72,1,1,1,41229.73,1 +2274,15679299,Shen,726,Spain,Female,27,7,123826.07,1,0,1,78970.58,0 +2275,15808044,Ts'ui,580,France,Female,65,9,106804.26,3,1,0,107890.69,1 +2276,15579208,Chikezie,550,France,Female,48,6,0,2,1,1,191870.28,0 +2277,15684951,He,542,France,Female,59,2,68892.77,2,1,0,7905.06,1 +2278,15667620,Dreyer,732,France,Female,43,6,0,2,1,0,65731.53,0 +2279,15582960,Short,473,France,Female,33,5,125827.43,1,0,1,145698.73,0 +2280,15590730,Hunt,745,Spain,Male,34,9,0,2,1,0,50046.25,0 +2281,15763747,Ricci,732,France,Male,36,7,0,2,1,1,60830.24,0 +2282,15778320,Teng,848,Germany,Female,40,5,148495.64,1,0,0,158853.98,0 +2283,15642787,Ijendu,572,France,Male,37,1,133043.66,1,0,0,111243.09,0 +2284,15624633,Kibby,702,France,Male,45,9,74989.58,1,1,1,171014.69,0 +2285,15766765,Obiuto,664,Germany,Male,39,7,60263.23,1,1,0,170835.32,0 +2286,15783615,Ramos,630,Germany,Male,50,3,129370.91,4,1,1,47775.34,1 +2287,15640161,Calabrese,618,Germany,Male,44,5,157955.83,2,0,0,139297.71,0 +2288,15619889,Vasin,556,France,Male,26,4,0,1,1,0,195167.38,0 +2289,15579166,Munro,619,France,Female,30,7,70729.17,1,1,1,160948.87,0 +2290,15789097,Keeley,644,France,Male,48,8,0,2,0,1,44965.54,1 +2291,15674880,Archer,658,Spain,Male,50,2,0,2,1,0,52137.73,0 +2292,15778157,Murray,598,Spain,Male,27,8,90721.52,2,1,0,109296.18,0 +2293,15779064,Chidiegwu,677,France,Male,27,2,0,2,1,1,20092.89,0 +2294,15801265,Tang,689,Spain,Female,45,0,57784.22,1,1,0,197804,1 +2295,15589204,Farrar,591,France,Male,33,9,131765.72,1,1,0,118782.06,0 +2296,15664543,Shaw,699,France,Male,40,7,0,1,0,1,152876.13,1 +2297,15582714,Napolitani,749,Germany,Male,47,9,110022.74,1,0,1,135655.29,1 +2298,15797595,Greenhalgh,709,France,Female,40,9,131569.63,1,1,1,103970.58,0 +2299,15614034,Martin,607,Germany,Male,61,2,164523.5,2,1,1,35786.76,0 +2300,15763171,Hu,650,Germany,Female,25,2,114330.95,1,1,1,25325.07,0 +2301,15647266,Y?an,651,Spain,Female,45,10,135923.16,1,1,0,18732.84,0 +2302,15757577,Odili,676,France,Female,61,8,0,2,1,1,118522.73,0 +2303,15736656,H?,723,France,Female,49,4,0,2,0,1,89972.25,0 +2304,15635078,Chiemela,714,Spain,Male,45,0,124693.48,1,0,1,187194.15,0 +2305,15680141,Yuan,759,Spain,Female,35,7,147936.42,1,1,1,106785.7,0 +2306,15576945,Clements,582,France,Male,29,0,0,1,1,0,142516.35,0 +2307,15602034,Kolesnikov,697,France,Female,34,2,126558.92,1,1,0,73334.43,0 +2308,15732020,Rutherford,610,Germany,Male,57,6,106938.11,2,0,1,186612.47,0 +2309,15611029,Hsiung,488,Germany,Female,33,4,140002.35,1,1,0,123613.81,0 +2310,15621210,Angelo,599,Germany,Male,46,9,123444.72,1,1,1,31368.08,1 +2311,15569222,Mendes,781,France,Male,32,6,147107.91,1,1,1,40066.95,0 +2312,15664639,McGregor,645,France,Male,19,9,128514.84,1,0,0,175969.19,0 +2313,15724223,Bronner,545,France,Female,55,5,0,1,0,0,10034.77,1 +2314,15644621,Mironova,597,Germany,Female,40,9,106756.01,2,1,0,151167.94,0 +2315,15756056,Ku,561,Spain,Female,28,3,0,2,1,0,191387.76,0 +2316,15700353,Evans,662,France,Female,37,6,0,2,1,0,51229.17,0 +2317,15624388,Henderson,649,Germany,Female,50,5,155393.32,1,1,1,87351.42,1 +2318,15627212,Smith,630,France,Female,36,2,110414.48,1,1,1,48984.95,0 +2319,15648005,Russell,672,Spain,Male,33,2,0,2,1,1,182738,0 +2320,15681446,Sun,636,Germany,Female,37,9,157098.52,1,1,1,153535.27,0 +2321,15775888,McDonald,593,Germany,Female,38,5,85626.6,1,1,1,125079.65,0 +2322,15749019,Wong,545,Germany,Male,45,6,93796.42,2,1,1,162321.26,0 +2323,15709928,Niu,567,Spain,Female,41,1,0,2,1,0,3414.72,0 +2324,15784676,Fanucci,583,France,Male,51,6,125268.03,2,1,0,165082.25,0 +2325,15748116,Zetticci,681,France,Female,29,2,148143.84,1,1,1,52021.39,0 +2326,15612193,Hsia,762,Spain,Male,29,10,115545.33,2,1,0,148256.43,0 +2327,15762984,McIntosh,648,Spain,Male,35,7,0,2,0,0,122899.01,0 +2328,15613713,Kozlova,644,France,Male,30,5,44928.88,1,1,1,10771.46,0 +2329,15664204,Meany,706,Spain,Male,29,2,0,2,1,1,18255.51,0 +2330,15639415,Thompson,850,France,Male,35,3,162442.35,1,1,0,183566.78,0 +2331,15806332,Le Gallienne,484,Spain,Female,39,5,0,2,1,1,175224.12,0 +2332,15614929,Cheng,508,Germany,Male,28,0,96213.82,2,1,0,147913.56,0 +2333,15695492,P'eng,439,France,Female,29,6,156569.43,1,1,0,180598.66,0 +2334,15635972,Lloyd,484,Spain,Male,36,8,0,2,1,0,186136.48,0 +2335,15616380,Wheeler,803,Spain,Female,37,1,0,2,0,0,7455.2,0 +2336,15581440,Christie,724,Germany,Female,48,6,110463.25,2,1,1,80552.11,1 +2337,15654390,He,640,France,Male,33,7,154575.76,1,1,0,25722.28,1 +2338,15660688,King,701,Spain,Female,35,9,0,2,0,0,170996.86,0 +2339,15806307,Favors,537,France,Male,37,3,0,2,1,1,20603.32,0 +2340,15647975,Vida,651,Germany,Male,26,5,147037.32,1,0,0,141763.26,0 +2341,15595728,Thomas,523,Germany,Male,41,0,119276.31,1,0,0,122284.38,1 +2342,15735388,Wayn,717,France,Female,25,7,108664.85,2,1,0,190011.85,0 +2343,15788535,Tan,593,Spain,Male,44,5,0,1,1,0,128046.98,0 +2344,15765902,Gibson,706,Germany,Male,38,5,163034.82,2,1,1,135662.17,0 +2345,15642345,Y?,714,Germany,Female,49,4,93059.34,1,1,0,7571.51,1 +2346,15641250,Calabresi,794,Spain,Male,38,9,179581.31,1,1,0,23596.24,0 +2347,15706163,Enyinnaya,518,Germany,Male,46,4,113625.93,1,0,0,92727.42,1 +2348,15746708,Ritchie,589,Germany,Male,55,7,119961.48,1,1,0,65156.83,1 +2349,15775203,Chia,824,France,Male,45,3,129209.48,1,0,0,60151.77,0 +2350,15787907,Wang,719,Germany,Female,42,5,137227.04,3,1,0,149097.38,1 +2351,15646764,Lorenzo,617,Germany,Female,58,3,119024.75,2,1,0,35199.24,1 +2352,15678284,Pai,651,France,Male,35,7,74623.5,3,1,0,129451.29,1 +2353,15726791,Nuttall,637,Spain,Female,45,2,157929.45,1,1,1,145134.49,1 +2354,15813144,Osborne,554,France,Female,26,7,92606.86,2,1,0,192709.69,0 +2355,15669342,Ferri,731,Germany,Male,35,2,127862.93,2,1,0,139083.7,0 +2356,15710366,Hamilton,569,Spain,Female,42,1,0,1,1,1,83629.6,1 +2357,15614934,McEwan,625,Germany,Female,37,4,142711.81,1,1,0,35625.41,0 +2358,15588701,Lai,592,France,Female,38,4,0,2,1,0,35338.96,0 +2359,15665438,Hs?,669,France,Male,43,1,163159.85,1,0,1,15602.8,0 +2360,15644896,Thompson,663,Germany,Male,32,3,108586.86,1,1,1,182355.21,0 +2361,15670205,Boyd,518,Germany,Female,41,5,110624.99,1,1,0,89327.67,0 +2362,15635776,Trevisani,686,Germany,Female,43,5,154846.24,2,1,1,151903.6,0 +2363,15791053,Lucciano,709,Germany,Male,45,4,122917.71,1,1,1,11.58,1 +2364,15644005,Holman,571,France,Female,33,9,0,2,0,1,77519.62,0 +2365,15796343,Bazhenov,707,France,Female,31,2,82787.93,2,0,0,91423.69,0 +2366,15751057,Douglas,701,Germany,Male,32,5,102500.34,1,0,0,106287.77,0 +2367,15623430,Hill,672,France,Male,34,9,0,2,1,0,161800.77,0 +2368,15682600,Lo,620,Germany,Male,39,9,159492.79,1,1,0,80582.34,1 +2369,15769312,Forbes,557,Spain,Male,48,10,0,2,1,1,185094.48,0 +2370,15708212,Lin,648,Spain,Female,54,7,118241.02,1,1,0,172586.89,1 +2371,15650258,Sinclair,479,France,Female,35,2,113090.4,1,1,0,195649.79,0 +2372,15604345,Kemp,730,France,Female,22,9,65763.57,1,1,1,145792.01,0 +2373,15578297,Ebelegbulam,737,Germany,Female,43,1,125537.38,1,1,0,138510.01,1 +2374,15671789,Woods,616,France,Male,31,3,94263.91,2,1,0,168895.06,0 +2375,15726186,Genovese,639,Spain,Male,29,4,133434.57,2,1,0,97983.44,0 +2376,15764618,Tseng,815,Spain,Female,39,6,0,1,1,1,85167.88,0 +2377,15730738,Chiang,786,Spain,Male,31,9,0,2,1,1,18210.36,0 +2378,15637650,Williams,549,France,Male,50,9,94748.76,2,0,1,13608.18,0 +2379,15606267,Wilson,622,France,Female,38,4,98640.74,1,1,1,110457.99,0 +2380,15625904,Wang,624,France,Male,26,9,74681.9,2,0,0,31231.35,0 +2381,15654463,Moore,841,France,Male,34,4,0,2,1,0,141582.66,0 +2382,15774151,Iadanza,614,Spain,Female,41,7,179915.85,1,0,0,14666.35,1 +2383,15693259,Wallace,676,France,Male,30,1,128207.23,1,1,1,55400.17,0 +2384,15642468,Clark,697,France,Male,42,9,132739.26,2,0,0,174667.65,0 +2385,15758531,Y?,732,France,Female,40,10,0,2,1,0,154189.08,0 +2386,15728352,Yermakov,623,France,Male,27,4,120509.81,1,0,0,142170.44,0 +2387,15637240,Wei,541,France,Male,46,4,124547.13,2,1,0,94499.06,0 +2388,15595588,Chukwunonso,773,Spain,Female,39,4,0,2,0,1,182081.45,0 +2389,15778395,McIntyre,762,Germany,Male,34,4,88815.56,2,1,0,68562.26,1 +2390,15711825,Ts'ai,655,Spain,Female,35,1,82231.51,2,1,0,88798.02,0 +2391,15599251,Chung,602,Germany,Male,32,7,184715.86,2,1,0,113781.99,0 +2392,15570004,Tsou,850,France,Male,31,3,0,2,1,0,121866.87,0 +2393,15656912,Aitken,649,Spain,Male,51,4,0,1,1,1,150390.57,0 +2394,15657342,Dawson,850,Germany,Male,28,4,147972.19,1,1,0,60708.72,1 +2395,15716284,Ward,543,France,Male,43,9,0,2,1,1,78858.07,0 +2396,15672374,Pai,672,France,Male,52,8,170008.84,1,0,0,56407.42,1 +2397,15732476,Ifeanyichukwu,600,France,Female,27,3,0,2,0,1,125698.97,0 +2398,15747724,Briggs,671,Spain,Female,34,10,0,1,1,0,23235.38,0 +2399,15633877,Morrison,706,Spain,Female,42,8,95386.82,1,1,1,75732.25,0 +2400,15672516,Wall,541,Germany,Male,51,7,90373.28,2,1,0,179861.79,0 +2401,15607827,Nebechukwu,711,Germany,Male,34,4,133467.77,2,1,1,42976.64,0 +2402,15751336,Yao,630,Spain,Male,30,3,0,2,0,1,10486.69,0 +2403,15646539,Liao,531,France,Male,31,3,96288.26,1,1,0,56794.73,0 +2404,15756901,Ch'ang,641,France,Female,26,4,91547.84,2,0,1,28157.34,0 +2405,15809286,Burke,631,Germany,Male,37,8,138292.64,2,0,0,152422.91,1 +2406,15759021,Kay,685,France,Male,35,9,0,1,1,0,167033.83,0 +2407,15725039,McIntyre,702,Spain,Male,32,8,71667.74,1,1,1,126082.18,0 +2408,15579130,Chidiegwu,708,Germany,Female,43,0,118994.84,1,1,0,181499.77,1 +2409,15754112,Musgrove,653,Spain,Male,55,7,0,2,1,1,41967.03,0 +2410,15735522,Boulger,654,Germany,Male,37,2,145610.07,2,0,0,186300.59,0 +2411,15613326,Gow,596,France,Female,33,1,138162.81,1,1,0,85412.54,0 +2412,15739502,Amaechi,549,Germany,Female,31,9,135020.21,2,1,1,23343.18,0 +2413,15670914,Robe,754,France,Male,38,2,0,2,1,0,180698.32,0 +2414,15604073,Bibi,815,Germany,Female,25,8,135161.67,1,1,1,136071.05,0 +2415,15806027,Niu,556,France,Female,52,9,0,1,1,0,175149.2,1 +2416,15574886,Palerma,706,France,Male,32,6,94486.47,1,1,1,146949.74,0 +2417,15707120,Cocci,850,France,Male,46,9,117640.39,1,1,0,88920.68,0 +2418,15800845,Artemieva,732,Spain,Female,33,8,111379.55,1,1,1,45098.62,0 +2419,15603914,Arcuri,614,France,Male,40,6,0,1,1,1,20339.79,1 +2420,15722765,Owen,580,Spain,Female,57,0,136820.99,1,0,1,108528.74,0 +2421,15783305,Franklin,593,France,Female,46,7,98752.51,1,1,0,145560.38,0 +2422,15574842,Lorenzo,653,Germany,Female,25,2,158266.42,3,1,1,199357.24,0 +2423,15607837,Muriel,746,France,Female,29,4,105599.67,1,1,1,43106.17,0 +2424,15714877,MacDevitt,662,France,Female,29,10,0,2,1,0,137508.31,0 +2425,15782941,Chijindum,573,France,Male,31,2,0,2,1,1,91957.39,0 +2426,15630167,Gibson,684,Spain,Female,39,4,139723.9,1,1,1,120612.11,0 +2427,15759038,Whitehead,793,France,Female,41,3,141806.46,1,1,0,102921.17,0 +2428,15661821,Johnstone,798,Germany,Female,49,5,132571.67,1,1,1,31686.33,1 +2429,15728006,Endrizzi,524,France,Male,40,2,180516.9,1,1,0,180002.42,0 +2430,15712176,Burke,816,France,Male,31,8,0,2,1,1,28407.4,0 +2431,15689351,Johnson,742,Germany,Female,41,4,92805.72,1,0,1,73743.95,1 +2432,15782247,Yeh,540,France,Male,22,4,0,3,1,1,186233.26,1 +2433,15769064,Marshall,537,Germany,Male,39,3,135309.36,1,1,0,31728.86,1 +2434,15718153,Kao,759,Spain,Female,74,6,128917.84,1,1,1,48244.64,0 +2435,15613189,Browne,774,France,Female,52,2,56580.93,1,1,0,113266.28,1 +2436,15661734,Taylor,608,Germany,Male,42,8,131390.75,2,1,0,71178.09,0 +2437,15592645,Gibbons,704,Spain,Male,37,4,0,2,0,0,25684.93,0 +2438,15768387,Nott,581,France,Male,41,8,0,2,0,0,29737.14,0 +2439,15792525,Lei,628,Germany,Female,61,1,97361.66,1,1,1,149922.38,1 +2440,15586976,Alexeeva,566,France,Female,42,6,0,1,1,0,180702.12,1 +2441,15790659,Sheets,701,Spain,Male,59,7,0,2,0,1,27597.59,0 +2442,15691446,Tokaryev,735,Spain,Male,29,10,0,2,1,1,95025.27,0 +2443,15772632,Ts'ui,680,France,Female,34,1,0,2,1,0,167035.07,0 +2444,15706587,Johnston,560,France,Male,57,0,0,2,0,1,116781.71,0 +2445,15572461,Kung,663,Germany,Female,29,4,102714.65,2,0,0,21170.81,0 +2446,15654409,Unwin,665,France,Female,34,5,67816.72,1,1,1,29641.58,0 +2447,15568025,Hsueh,758,France,Male,51,8,81710.46,1,1,1,116520.07,0 +2448,15715769,Hao,621,France,Male,26,2,75237.54,1,0,1,44220.4,0 +2449,15667458,L?,764,Germany,Male,28,10,124023.18,1,1,0,166188.28,0 +2450,15567980,Frater,537,Germany,Female,46,5,100727.5,1,0,1,140857.76,1 +2451,15679294,Brennan,589,France,Female,46,10,107238.85,2,1,0,37024.28,0 +2452,15606507,Pisani,555,France,Male,24,5,0,2,1,0,27513.47,0 +2453,15578825,Golubev,734,France,Female,29,0,139994.66,1,1,0,17744.72,0 +2454,15619935,Vanmeter,783,Spain,Female,59,9,126224.87,1,1,1,4423.63,0 +2455,15636089,Hs?,678,Germany,Female,51,1,145751.03,1,0,0,109718.44,1 +2456,15727490,Scott,661,France,Male,47,5,0,1,0,1,107243.31,1 +2457,15591766,Crawford,607,Spain,Female,25,4,121166.89,1,0,1,115288.24,0 +2458,15641629,P'eng,537,Spain,Female,38,1,0,2,0,1,41233.97,0 +2459,15813303,Rearick,513,Spain,Male,88,10,0,2,1,1,52952.24,0 +2460,15756920,Genovesi,576,France,Male,63,9,70655.48,1,0,0,78955.8,1 +2461,15726403,Glenny,660,Germany,Male,41,1,129901.21,1,1,0,26025.6,1 +2462,15592765,Marks,637,France,Male,40,8,125470.81,1,1,1,174536.17,0 +2463,15704442,Fleming,672,France,Female,53,9,169406.33,4,1,1,147311.47,1 +2464,15641136,Davison,629,France,Male,32,2,0,2,0,1,77965.44,0 +2465,15725818,Chibuzo,583,Germany,Male,40,4,107041.3,1,1,1,5635.63,0 +2466,15612071,Wilson,763,Spain,Female,32,10,95153.77,1,0,1,81310.1,0 +2467,15719809,Endrizzi,516,Germany,Male,32,3,145166.09,2,0,0,111421.45,0 +2468,15716518,Yuryeva,617,France,Female,27,4,0,2,0,0,190269.21,0 +2469,15742210,Ugochukwu,700,France,Male,38,9,65962.63,1,1,1,100950.48,0 +2470,15630617,Lo Duca,727,Germany,Male,36,6,140418.81,1,1,1,113033.73,1 +2471,15720838,Gallo,689,Spain,Female,31,3,139799.63,1,0,1,120663.57,0 +2472,15595537,Trout,626,Germany,Male,49,9,171787.84,2,1,0,187192.23,0 +2473,15623196,Morley,686,France,Male,38,6,149238.97,1,1,1,97825.23,0 +2474,15679249,Chou,351,Germany,Female,57,4,163146.46,1,1,0,169621.69,1 +2475,15693199,Shao,739,France,Female,37,8,0,2,1,0,191557.1,1 +2476,15661219,Trentino,627,France,Male,32,10,0,2,1,0,103287.62,0 +2477,15617136,Mazzanti,451,Germany,Female,38,9,61482.47,1,1,1,167538.66,0 +2478,15760294,Endrizzi,512,France,Female,41,8,145150.28,1,1,0,64869.32,1 +2479,15652808,Monaldo,774,France,Female,41,5,126670.37,1,1,0,102426.06,0 +2480,15657139,Otutodilinna,652,France,Female,40,8,84390.8,2,0,1,107876.2,0 +2481,15803790,Allen,638,Germany,Male,37,2,89728.86,2,1,1,37294.88,0 +2482,15764105,Milne,475,France,Female,57,1,0,2,1,0,89248.99,0 +2483,15672610,Somadina,567,Spain,Male,40,4,118628.8,1,0,0,91973.63,0 +2484,15766896,Chieloka,750,France,Male,37,3,0,2,1,0,16870.2,0 +2485,15587735,Chukwuebuka,850,France,Male,39,6,96863.13,1,1,1,121681.19,0 +2486,15659501,Chioke,753,France,Female,38,6,142263.45,1,0,1,33730.43,0 +2487,15745001,Kovalev,683,Spain,Female,36,7,0,2,1,0,104786.59,0 +2488,15651140,Doherty,710,France,Female,32,3,0,1,1,0,94790.34,0 +2489,15571148,Baranov,645,Spain,Female,21,1,0,2,0,0,28726.07,0 +2490,15776824,Rossi,714,France,Male,28,6,122724.37,1,1,1,67057.27,0 +2491,15633141,Robinson,696,Germany,Female,35,4,174902.26,1,1,0,69079.85,0 +2492,15764174,Bidencope,612,Spain,Female,26,4,0,2,1,1,179780.74,0 +2493,15778155,T'ien,520,Germany,Female,31,3,108914.17,1,1,1,183572.39,1 +2494,15715920,De Bernales,782,Spain,Male,23,10,98052.66,1,1,1,142587.32,0 +2495,15671917,Wade,666,France,Male,46,5,123873.19,1,1,1,177844.06,0 +2496,15666548,Chung,466,Germany,Female,56,2,111920.13,3,1,0,197634.11,1 +2497,15625623,Stevenson,567,France,Female,45,4,0,2,0,1,121053.19,0 +2498,15748123,Chienezie,613,France,Male,20,3,0,2,1,1,149613.77,0 +2499,15648735,Cashin,718,France,Male,37,8,0,2,1,1,142.81,0 +2500,15634974,Seppelt,614,France,Female,37,8,75150.34,4,0,1,131766.67,1 +2501,15713378,Brownless,711,France,Male,38,10,0,2,0,0,53311.78,0 +2502,15753370,McDonald,691,Germany,Female,38,5,114753.76,1,1,0,107665.02,0 +2503,15782659,Mamelu,527,France,Male,32,0,0,1,1,0,109523.88,0 +2504,15583364,McGregor,476,France,Female,32,6,111871.93,1,0,0,112132.86,0 +2505,15625942,McDonald,619,Spain,Female,45,0,0,2,0,0,113645.4,0 +2506,15720284,Crawford,607,Germany,Female,37,4,135927.06,1,0,0,180890.4,0 +2507,15679642,Feng,695,Spain,Male,44,8,0,2,1,1,70974.13,0 +2508,15628007,Genovese,653,France,Male,33,1,0,2,0,0,53379.52,0 +2509,15661974,Pirozzi,677,France,Male,46,2,57037.74,1,1,1,158531.01,0 +2510,15689341,Gibbs,655,France,Female,50,10,0,4,1,0,179267.94,1 +2511,15607993,Milne,625,France,Female,52,2,79468.96,1,1,1,84606.03,0 +2512,15693267,Dickson,679,Germany,Female,34,7,121063.85,1,1,0,56984.58,0 +2513,15769522,O'Connor,734,France,Male,51,1,118537.47,1,1,1,116912.45,0 +2514,15755825,McGuirk,666,France,Male,39,10,0,2,1,0,102999.33,0 +2515,15598175,Toscani,592,Germany,Female,26,4,105082.07,2,1,0,132801.57,0 +2516,15744327,Ruth,564,France,Male,40,4,0,1,1,0,85455.62,1 +2517,15798666,Hughes,814,France,Female,36,6,0,2,1,1,98657.01,0 +2518,15577064,Onyekaozulu,592,Germany,Male,36,2,104702.65,2,1,0,107948.72,0 +2519,15759436,Aksenov,758,France,Female,50,2,95813.76,3,1,1,67944.09,1 +2520,15690231,K'ung,612,Spain,Female,62,0,167026.61,2,1,1,192892.05,0 +2521,15751561,Meng,498,Germany,Male,61,7,102453.26,1,1,0,187247.56,1 +2522,15739068,Nwoye,638,Germany,Male,25,4,148045.45,2,1,1,114722.42,0 +2523,15758056,Calabresi,558,France,Male,35,1,0,2,0,0,111687.57,0 +2524,15742269,Milano,756,France,Female,24,1,0,2,1,0,184182.25,0 +2525,15726490,Kirby,782,Spain,Male,52,4,0,1,1,1,52759.82,1 +2526,15738411,Ho,505,France,Male,34,10,104498.79,1,0,1,126451.14,0 +2527,15727919,Chukwuemeka,671,Spain,Female,29,6,0,2,0,0,12048.67,0 +2528,15709396,Hale,801,France,Male,42,6,0,2,1,1,95804.33,0 +2529,15654106,K?,604,France,Male,26,8,149542.52,2,0,1,197911.52,0 +2530,15621653,Rice,716,France,Female,29,10,87946.39,1,1,1,182531.74,0 +2531,15598086,Brown,624,France,Female,45,3,68639.57,1,1,0,168002.31,1 +2532,15752300,Sagese,607,Germany,Male,47,4,148826.32,1,1,1,79450.61,0 +2533,15658693,Aksyonova,827,France,Female,60,2,0,2,0,1,60615.83,0 +2534,15631838,Findlay,606,France,Male,61,5,108166.09,2,0,1,8643.21,0 +2535,15803804,Walker,717,Germany,Female,35,5,103214.71,1,1,0,172172.7,0 +2536,15578809,Hao,651,Germany,Male,40,1,134760.21,2,0,0,174434.06,1 +2537,15752026,Hammer,691,France,Male,58,3,0,1,0,1,194930.3,1 +2538,15723706,Abbott,573,France,Female,33,0,90124.64,1,1,0,137476.71,0 +2539,15752838,Lucas,723,Spain,Male,38,6,0,2,1,1,94415.6,0 +2540,15569571,Davydova,584,Germany,Female,46,6,87361.02,2,1,0,120376.87,1 +2541,15769703,West,550,Germany,Female,45,8,111257.59,1,0,0,97623.42,1 +2542,15679770,Smith,611,France,Female,61,3,131583.59,4,0,1,66238.23,1 +2543,15791102,Mai,549,Germany,Male,41,9,95020.8,3,1,1,131710.59,1 +2544,15655192,Fiorentino,850,Spain,Female,24,1,0,2,0,1,69052.87,0 +2545,15709487,Freeman,668,Germany,Male,34,5,80242.37,2,0,0,56780.97,0 +2546,15687130,Nkemjika,686,France,Female,43,0,0,1,1,1,170072.9,0 +2547,15755178,Ramos,660,France,Male,50,1,0,3,1,1,191849.15,1 +2548,15634772,Mario,682,Spain,Female,59,0,122661.39,1,0,1,84803.76,0 +2549,15617197,Chien,524,France,Male,50,4,0,2,1,1,31840.59,1 +2550,15631240,Dubinina,645,France,Female,36,8,0,2,1,1,12096.61,1 +2551,15784301,Wang,850,France,Male,42,0,0,2,1,0,44165.84,0 +2552,15631310,Hsieh,537,France,Female,53,3,0,1,1,1,91406.62,0 +2553,15756560,Moran,599,Spain,Female,46,7,81742.84,2,1,0,83282.21,0 +2554,15732270,Hung,727,Spain,Male,71,8,0,1,1,1,198446.91,1 +2555,15739357,Moss,756,Spain,Male,30,2,145127.85,1,0,0,7554.68,0 +2556,15771540,Fedorova,755,France,Male,38,9,148912.44,1,1,0,80416.16,0 +2557,15567486,Li,634,Spain,Female,41,4,0,2,1,1,164549.74,0 +2558,15714634,Nebechi,837,France,Male,26,4,89900.24,2,1,0,175477.03,0 +2559,15727021,Obialo,727,Germany,Female,30,8,119027.28,2,1,1,137903.54,0 +2560,15650670,Bateson,567,Germany,Female,40,2,105222.86,2,1,0,93795.86,0 +2561,15711834,Long,650,Spain,Female,30,6,0,1,0,0,67997.13,1 +2562,15729763,Nelson,655,Spain,Male,34,1,116114.93,1,1,1,49492.15,0 +2563,15646566,Bell,763,France,Female,58,9,187911.55,1,0,1,35825.18,0 +2564,15645463,Udinese,843,France,Female,27,5,0,2,1,1,67494.23,0 +2565,15672144,Mao,667,France,Female,38,6,144432.04,1,1,1,73963.17,1 +2566,15596088,Fanucci,705,France,Female,50,4,77065.9,2,0,1,145159.26,0 +2567,15614878,Yeh,660,Germany,Female,29,6,180520.29,1,1,1,123850.58,0 +2568,15635240,Onuoha,553,France,Male,42,1,0,2,0,0,23822.04,0 +2569,15775905,Moore,612,Germany,Female,47,6,130024.87,1,1,1,45750.21,1 +2570,15700657,Thornton,641,Germany,Female,40,2,110086.69,1,1,0,159773.14,0 +2571,15611905,Warlow-Davies,513,Spain,Female,31,5,174853.46,1,1,0,84238.63,0 +2572,15652527,Champion,680,France,Male,44,7,108724.98,1,0,1,72330.46,0 +2573,15785865,Mazzanti,711,France,Male,58,9,91285.13,2,1,1,26767.85,0 +2574,15645942,Macleod,689,Spain,Male,40,2,0,2,1,1,164768.82,0 +2575,15688691,Lei,665,Germany,Female,51,9,110610.41,2,0,1,1112.76,1 +2576,15592736,Lucchese,551,Germany,Male,54,5,102994.04,1,1,0,176680.16,1 +2577,15673529,Lombardo,645,Spain,Male,36,4,59893.85,2,1,0,43999.64,0 +2578,15724145,William,616,Germany,Male,29,8,149318.55,1,1,0,140746.13,0 +2579,15704629,Wright,582,France,Female,32,1,116409.55,1,0,1,152790.92,0 +2580,15597896,Ozoemena,365,Germany,Male,30,0,127760.07,1,1,0,81537.85,1 +2581,15731790,Boyle,697,Germany,Female,38,6,132591.36,1,1,1,7387.8,1 +2582,15634719,Chinwendu,704,France,Male,31,0,0,2,1,0,183038.33,0 +2583,15703205,Uwaezuoke,656,France,Female,46,5,113402.14,2,1,1,138849.06,0 +2584,15567333,Archambault,712,France,Female,31,7,0,2,1,0,170333.38,0 +2585,15754537,Ko,748,France,Male,40,0,0,1,0,0,60416.76,0 +2586,15612030,Udegbulam,724,France,Male,28,9,0,2,1,1,100240.2,0 +2587,15573242,Greene,691,France,Male,50,6,136953.47,1,1,1,2704.98,0 +2588,15601892,Hunter,563,France,Male,33,8,0,2,0,1,68815.05,0 +2589,15663885,Blinova,741,France,Male,32,5,0,1,1,1,64839.23,0 +2590,15701096,De Garis,778,France,Male,44,8,123863.64,1,1,0,144494.94,0 +2591,15710450,Okwudiliolisa,848,Spain,Male,22,7,120811.89,1,1,1,185510.34,0 +2592,15790846,Ts'ai,634,Germany,Male,38,2,148430.55,1,1,1,56055.72,0 +2593,15658956,Tuan,505,Germany,Male,40,6,47869.69,2,1,1,155061.97,0 +2594,15755223,Tseng,692,Germany,Male,53,7,150926.99,2,0,0,119817.19,0 +2595,15787318,Holmwood,537,Germany,Female,47,6,103163.35,1,1,0,16259.64,1 +2596,15737310,Thompson,633,France,Male,29,10,130206.28,1,1,0,184654.87,0 +2597,15763665,Y?,833,France,Female,28,4,136674.51,2,0,0,5278.78,0 +2598,15668818,Chidubem,592,Spain,Female,40,2,200322.45,1,1,1,113244.73,0 +2599,15765812,Trevisani,587,Spain,Male,48,1,0,2,1,1,8908,0 +2600,15704844,Hsiung,550,Spain,Male,62,7,80927.56,1,0,1,64490.67,0 +2601,15744582,Randall,680,France,Female,24,10,0,3,1,0,154971.63,1 +2602,15616700,Leach,622,Spain,Female,41,9,0,2,1,1,155786.39,0 +2603,15683521,Godfrey,594,Germany,Male,28,0,142574.71,2,1,0,129084.82,0 +2604,15583049,Wallace,643,Germany,Female,34,7,160426.07,1,0,1,188533.11,0 +2605,15643752,Wei,540,France,Male,25,5,116160.23,1,1,0,13411.67,0 +2606,15620398,Mitchell,635,Spain,Female,34,5,98683.47,2,1,0,15733.19,0 +2607,15715707,Light,657,France,Male,32,3,118829.03,2,1,1,73127.61,0 +2608,15814209,Capon,814,France,Male,31,1,118870.92,1,1,0,101704.19,0 +2609,15733768,Hou,600,France,Male,32,1,0,1,1,1,101986.16,0 +2610,15755242,Rowe,682,France,Female,46,2,0,1,1,1,114442.66,0 +2611,15729412,Holloway,682,France,Male,38,4,107192.38,1,1,1,15669.17,0 +2612,15746564,O'Sullivan,566,France,Male,42,3,108010.78,1,1,1,157486.1,0 +2613,15588446,Udinesi,550,Spain,Male,34,3,0,2,0,0,131281.28,0 +2614,15665221,Nwebube,630,France,Male,26,7,129837.72,2,0,1,197001.15,0 +2615,15640846,Chibueze,546,Germany,Female,58,3,106458.31,4,1,0,128881.87,1 +2616,15700209,Walker,486,France,Male,63,9,97009.15,1,1,1,85101,0 +2617,15658360,Gregory,762,Spain,Male,35,9,122929.42,2,0,0,149822.04,0 +2618,15602735,Kuo,692,Germany,Male,45,6,152296.83,4,0,1,108040.86,1 +2619,15724834,Wilson,498,France,Female,30,1,0,2,0,0,135795.53,0 +2620,15800062,Lanford,850,Spain,Male,49,8,0,1,0,0,25867.67,1 +2621,15685300,Meng,603,France,Male,35,6,128993.76,2,1,0,130483.56,0 +2622,15760102,Yeh,551,France,Female,36,5,0,1,1,0,183479.12,0 +2623,15787026,Onwuatuegwu,627,Germany,Male,27,0,185267.45,2,1,1,77027.34,0 +2624,15653696,Goliwe,515,France,Female,28,9,0,2,0,0,94141.75,0 +2625,15788946,Anthony,605,Spain,Female,29,3,116805.82,1,0,0,4092.75,0 +2626,15600724,Scott,567,Germany,Male,29,5,129750.68,1,1,0,109257.59,0 +2627,15574324,Genovese,568,Germany,Female,29,2,129177.01,2,0,1,104617.99,0 +2628,15707144,Onyeorulu,571,Germany,Male,25,6,82506.72,2,1,0,167705.07,0 +2629,15775891,Myers,634,Germany,Male,48,2,107247.69,1,1,1,103712.05,1 +2630,15711789,Davey,768,Spain,Female,42,3,0,1,0,0,161242.99,1 +2631,15600879,Parsons,554,Germany,Female,36,3,157780.93,2,1,0,6089.13,0 +2632,15681196,Chikere,629,France,Male,35,1,172170.36,1,1,1,159777.37,0 +2633,15716000,Hs?eh,638,Spain,Male,48,2,0,2,1,1,7919.08,0 +2634,15766776,Sal,576,France,Male,41,1,0,1,1,1,188274.6,0 +2635,15680278,Ts'ai,661,Spain,Female,42,9,75361.44,1,1,0,27608.12,1 +2636,15688637,Witt,592,France,Female,27,4,0,2,1,1,183569.25,0 +2637,15591179,Skelton,702,Spain,Male,30,2,0,2,1,1,145537.32,0 +2638,15677435,Kazantseva,647,France,Female,29,0,98263.46,2,1,0,164717.95,0 +2639,15698619,Bowhay,593,France,Male,43,9,0,2,1,1,76357.43,0 +2640,15581036,Beyer,712,Germany,Female,40,3,109308.79,2,1,0,120158.72,1 +2641,15622117,Fries,625,Spain,Female,31,8,0,2,1,0,151843.54,0 +2642,15599301,Tao,538,Germany,Female,28,6,164365.44,1,0,1,5698.97,0 +2643,15581548,Kaodilinakachukwu,637,Spain,Female,22,5,98800,1,1,0,122865.55,0 +2644,15586870,Ni,632,France,Male,27,4,193125.85,1,1,1,152665.85,0 +2645,15735263,Hsueh,736,France,Male,27,5,51522.75,1,0,1,192131.77,0 +2646,15765322,Connely,755,France,Male,23,5,84284.48,2,1,1,62851.6,0 +2647,15582944,Becker,425,Spain,Female,39,5,0,2,1,0,140941.47,0 +2648,15687162,Clayton,461,France,Male,51,9,119889.84,1,0,0,56767.67,1 +2649,15644962,Connolly,745,France,Male,21,4,137910.45,1,1,1,177235.23,0 +2650,15612615,Graham,616,France,Female,37,6,0,2,1,0,86242.18,0 +2651,15813439,Ch'ien,587,France,Male,33,5,100116.82,1,1,0,34215.58,0 +2652,15604544,Manfrin,850,Germany,Male,40,4,166082.15,2,0,1,44406.17,0 +2653,15761348,Kuo,601,France,Female,38,0,0,2,1,0,165196.65,0 +2654,15785078,Fomin,730,Spain,Male,26,3,0,1,1,0,34542.41,0 +2655,15759874,Chamberlain,532,France,Male,44,3,148595.55,1,1,0,74838.64,1 +2656,15643658,Barber,850,Germany,Male,53,2,94078.97,2,1,0,36980.54,0 +2657,15713267,Zimmer,779,Spain,Female,34,5,0,2,0,1,111676.63,0 +2658,15737782,Brazenor,562,France,Male,29,9,0,1,1,1,25858.68,0 +2659,15815490,Cocci,670,Germany,Male,40,2,164948.98,3,0,0,177028,1 +2660,15679410,Caldwell,729,France,Female,62,4,140549.4,1,1,0,30990.16,1 +2661,15756241,Yirawala,767,France,Female,44,2,152509.25,1,1,1,136915.15,0 +2662,15688409,Donaldson,742,France,Female,28,2,191864.51,1,1,0,108457.99,1 +2663,15742272,Ozerova,669,France,Female,44,8,96418.09,1,0,0,131609.48,1 +2664,15717898,Bruce,542,Spain,Male,32,2,131945.94,1,0,1,159737.56,0 +2665,15769582,Kang,586,France,Male,29,3,0,2,1,1,142238.54,0 +2666,15635660,Rossi,612,Germany,Male,30,9,142910.15,1,1,0,105890.55,1 +2667,15576723,Ts'ai,740,France,Female,37,7,0,2,1,1,194270.91,0 +2668,15591577,Moran,584,France,Male,35,3,146311.58,1,1,1,105443.47,0 +2669,15582325,Jennings,524,France,Male,52,2,87894.26,1,1,0,173899.42,1 +2670,15693947,Tokareva,614,France,Female,19,5,97445.49,2,1,0,122823.34,0 +2671,15760446,Pagnotto,598,France,Female,64,9,0,1,0,1,13181.37,1 +2672,15611105,Castella,799,Spain,Male,35,7,0,2,0,1,140780.8,0 +2673,15630920,Du Cane,724,France,Male,34,2,154485.74,2,0,0,78560.64,0 +2674,15574910,Ferguson,601,France,Male,50,2,115625.07,1,1,0,185855.21,0 +2675,15756472,Odinakachukwu,804,France,Male,25,7,108396.67,1,1,0,128276.95,0 +2676,15682890,Woronoff,745,Germany,Male,38,5,65095.41,2,1,1,140197.42,0 +2677,15641994,Meng,667,Germany,Male,43,1,103018.45,1,1,0,32462.39,1 +2678,15733297,Sinclair,518,France,Female,38,10,84764.79,1,1,1,162253.9,0 +2679,15767793,Hsu,819,France,Female,38,10,0,2,1,0,30498.7,0 +2680,15725698,Panicucci,520,Spain,Female,35,4,115680.81,1,1,1,90280.7,0 +2681,15813532,Burns,625,France,Female,39,5,0,2,1,0,32615.21,0 +2682,15576760,Onodugoadiegbemma,673,Germany,Male,36,5,73088.06,2,0,0,196142.26,0 +2683,15732102,Darling,656,Germany,Female,27,3,150905.03,2,1,0,16998.72,0 +2684,15739046,Maggard,850,Spain,Female,23,9,143054.85,1,0,1,62980.96,0 +2685,15631927,Thomas,574,Spain,Female,28,7,0,2,0,0,185660.3,0 +2686,15672115,Lettiere,679,France,Male,60,6,0,2,1,1,77331.77,0 +2687,15618765,Ponomaryov,530,Germany,Female,42,0,99948.45,1,0,1,97338.62,0 +2688,15679148,Oliver,508,France,Male,44,3,115451.05,2,0,0,67234.33,0 +2689,15728474,Chienezie,558,Germany,Male,32,4,108235.91,1,1,1,143783.28,0 +2690,15636999,Mao,414,France,Male,38,8,0,1,0,1,77661.12,1 +2691,15754261,Ho,648,Spain,Male,42,2,98795.61,2,1,0,89123.99,0 +2692,15629150,Lucchese,721,France,Female,37,1,0,2,1,0,70810.8,0 +2693,15736274,Prokhorova,751,France,Male,31,8,0,2,0,0,17550.49,0 +2694,15627697,Alekseyeva,662,France,Male,34,2,0,2,0,1,21497.27,0 +2695,15721585,Blacklock,628,Germany,Male,29,3,113146.98,2,0,1,124749.08,0 +2696,15639946,Sazonova,597,Germany,Female,39,8,162532.14,3,1,0,36051.46,1 +2697,15792176,Henty,698,Spain,Female,40,0,92053.44,1,1,1,143681.83,0 +2698,15699450,Li,723,France,Male,48,7,0,2,1,1,150694.58,0 +2699,15729954,Azuka,586,France,Female,28,5,0,3,1,0,170487.4,1 +2700,15600103,Alexander,633,Germany,Female,29,8,104944.1,1,1,1,97684.46,0 +2701,15786200,Brock,564,France,Male,31,4,0,2,1,0,53520.03,0 +2702,15797010,Shen,649,France,Female,31,2,0,2,1,0,15200.61,0 +2703,15670172,Padovesi,622,France,Female,30,4,107879.04,1,0,1,196894.62,0 +2704,15627352,Bulgakov,459,Germany,Male,46,7,110356.42,1,1,0,4969.13,1 +2705,15622494,Mazzanti,718,France,Male,27,2,0,2,0,0,26229.24,0 +2706,15585835,Lord,655,Spain,Female,34,4,109783.69,2,1,0,134034.32,0 +2707,15595071,Ramos,696,France,Male,22,9,149777,1,1,1,198032.93,0 +2708,15628203,Pai,637,France,Female,38,3,104339.56,1,0,0,119882.86,0 +2709,15667190,Yuan,630,Spain,Female,21,1,85818.18,1,1,1,133102.3,0 +2710,15780212,Mao,592,France,Male,37,4,212692.97,1,0,0,176395.02,0 +2711,15766869,Uspenskaya,634,Germany,Male,37,1,89696.84,2,1,1,193179.88,0 +2712,15775741,Powell,608,France,Female,28,9,0,2,1,1,125062.02,0 +2713,15628170,Brown,565,Germany,Female,32,9,68067.24,1,1,0,143287.58,0 +2714,15701318,Poole,763,Spain,Male,67,9,148564.66,1,0,1,87236.4,0 +2715,15710928,McChesney,665,France,Female,55,8,136354.16,1,1,1,93769.89,0 +2716,15682547,Lucchese,649,France,Male,38,1,122214,1,0,1,88965.46,0 +2717,15631170,Clements,695,France,Male,45,3,0,2,1,1,30793.61,0 +2718,15648702,Yuriev,775,Germany,Male,70,6,119684.88,2,1,1,74532.02,0 +2719,15783444,Endrizzi,788,France,Female,39,3,135139.33,1,0,1,113086.08,0 +2720,15809178,Pan,569,Germany,Female,42,9,146100.75,1,1,0,32574.01,1 +2721,15806688,Manfrin,726,Spain,Female,56,8,123110.9,3,0,1,130113.78,1 +2722,15576824,Kennedy,564,Germany,Female,44,3,111760.4,3,1,1,104722.47,1 +2723,15675422,Conway,544,France,Female,32,9,110728.39,1,1,1,14559.62,0 +2724,15681550,Lablanc,614,France,Female,41,8,121558.46,1,1,1,598.8,0 +2725,15812628,Dodd,453,Germany,Female,38,8,120623.21,1,1,0,129697.99,0 +2726,15597951,Muir,471,France,Female,58,4,114713.57,1,1,1,36315.03,0 +2727,15807045,Milanesi,829,Germany,Female,37,3,103457.76,1,0,0,1114.12,0 +2728,15581748,Shen,754,Germany,Male,57,2,101134.87,2,1,1,70954.41,0 +2729,15770420,Dillon,749,Germany,Male,46,10,78136.36,2,1,1,73470.98,0 +2730,15608230,Hoelscher,667,France,Male,23,1,0,2,1,0,91573.19,0 +2731,15730339,Bell,670,Spain,Male,30,3,133446.34,1,0,0,3154.95,0 +2732,15712584,Liao,670,France,Female,33,7,0,2,1,1,88187.81,0 +2733,15592816,Udokamma,623,Germany,Female,48,1,108076.33,1,1,0,118855.26,1 +2734,15641480,Sinnett,571,France,Male,32,5,131354.25,1,1,0,125256.53,0 +2735,15708505,Palerma,641,Germany,Female,37,7,62974.64,2,0,1,39016.43,0 +2736,15791131,Chimaijem,551,Germany,Female,30,2,143340.44,1,1,0,145796.49,0 +2737,15618225,Porter,741,Germany,Male,36,8,116993.43,2,1,0,168816.22,0 +2738,15644724,Fan,472,France,Male,31,4,58662.92,2,0,1,73322,0 +2739,15662098,Palmer,650,Spain,Male,41,3,128808.65,3,0,0,113677.53,1 +2740,15723894,Younger,625,France,Male,45,7,137555.44,1,0,0,124607.7,0 +2741,15787699,Burke,650,Germany,Male,34,4,142393.11,1,1,1,11276.48,0 +2742,15687738,Nwagugheuzo,535,France,Female,38,8,0,2,1,0,136620.64,0 +2743,15576126,Young,649,France,Female,41,2,125785.23,1,1,1,70523.92,0 +2744,15658889,Watson,689,France,Male,22,4,136444.25,1,1,0,51980.25,1 +2745,15667046,Tseng,694,Spain,Male,38,7,121527.4,1,1,0,113481.02,0 +2746,15669957,Drake,655,Germany,Male,52,9,144696.75,1,1,1,49025.79,0 +2747,15655794,Hanna,620,France,Male,36,8,0,2,1,1,145937.99,0 +2748,15599829,Padovesi,577,France,Female,35,10,0,2,1,1,25161.61,0 +2749,15753332,Loftus,401,Germany,Male,48,8,128140.17,1,1,0,175753.55,1 +2750,15671124,Buccho,599,France,Male,25,6,120383.41,1,1,1,24903.09,0 +2751,15767474,Lorenzo,481,France,Female,57,9,0,3,1,1,169719.35,1 +2752,15720671,Ibezimako,704,France,Male,42,8,129735.3,2,1,1,179565.57,0 +2753,15626787,Wei,698,Spain,Female,31,8,185078.26,1,0,0,115337.74,1 +2754,15774491,Ross,480,France,Female,28,6,0,2,0,0,48131.92,0 +2755,15579647,Oluchukwu,682,France,Male,42,0,0,1,1,1,160828.98,0 +2756,15625522,Walker,700,Spain,Male,31,7,0,2,0,1,145151.96,0 +2757,15765806,Wu,492,France,Male,29,1,144591.96,1,1,1,196293.76,0 +2758,15566708,Chidalu,444,France,Female,45,4,0,2,1,0,161653.5,1 +2759,15668347,Ingram,624,France,Male,36,6,0,2,0,0,84635.64,0 +2760,15575214,Ch'en,709,France,Male,37,7,0,1,1,0,159486.76,0 +2761,15591123,Iredale,557,Germany,Male,68,2,100194.44,1,1,1,38596.34,0 +2762,15573280,Gallagher,646,Germany,Male,50,6,145295.31,2,1,1,27814.74,0 +2763,15589018,Padilla,719,Germany,Male,28,3,106070.29,2,1,1,183893.31,0 +2764,15654495,Potter,706,Germany,Female,47,6,120621.89,1,1,1,140803.7,0 +2765,15597265,Mao,660,France,Male,38,7,0,2,0,1,146585.53,0 +2766,15733876,Schneider,667,France,Male,36,9,0,2,1,1,40062.29,0 +2767,15677217,Ibragimova,705,France,Male,30,1,0,1,1,1,181300.32,0 +2768,15747265,Huang,598,Germany,Female,27,10,171283.91,1,1,1,84136.12,0 +2769,15713379,Anderson,669,France,Male,26,4,0,2,1,1,197594.34,0 +2770,15730433,Nakayama,580,Germany,Female,38,1,128218.47,1,1,0,125953.83,1 +2771,15693347,Gardener,676,France,Female,32,5,0,2,1,1,75465.41,0 +2772,15715465,Aksenova,714,Germany,Male,28,7,77776.39,1,1,0,177737.07,0 +2773,15680736,Milne,597,Germany,Female,72,6,124978.19,2,1,1,7144.46,0 +2774,15610765,Onwumelu,559,France,Male,29,1,0,2,0,0,155639.76,0 +2775,15650034,Kudryashova,564,France,Female,28,1,0,1,1,1,162428.05,0 +2776,15782468,Hart,850,Spain,Male,51,3,109799.55,2,1,1,12457.76,1 +2777,15685109,Teng,689,France,Male,39,7,0,2,0,0,14917.09,0 +2778,15776233,Kruglova,758,Germany,Female,61,8,125397.21,1,1,0,182184.09,1 +2779,15761141,Palerma,604,Spain,Female,71,10,0,2,1,1,129984.2,0 +2780,15781702,Brookes,733,Germany,Male,38,9,111347.37,2,0,1,194872.97,0 +2781,15790235,Hsing,778,Spain,Male,40,8,104291.41,2,1,1,117507.11,0 +2782,15641416,Shaffer,732,Germany,Female,61,9,94867.18,2,1,1,157527.6,1 +2783,15775234,Laurie,646,France,Male,24,8,0,2,0,0,92612.88,0 +2784,15659475,Chung,597,France,Female,33,6,135703.59,2,0,0,74850.84,0 +2785,15642202,Whitfield,821,Germany,Female,37,5,106453.53,2,0,1,127413,0 +2786,15771417,Thomas,640,France,Male,43,7,132412.38,1,0,0,69584.3,1 +2787,15585100,Rioux,511,Germany,Female,40,9,124401.6,1,1,0,198814.24,1 +2788,15700487,Osonduagwuike,805,France,Male,46,6,118022.06,3,1,0,162643.15,1 +2789,15726589,Matveyev,540,Germany,Male,39,1,82531.11,1,1,0,114092.52,0 +2790,15747503,Hayward,705,Spain,Male,44,0,184552.12,1,1,0,68860.3,1 +2791,15595883,Nkemdirim,540,Germany,Male,39,4,127278.31,1,1,1,16150.34,0 +2792,15663826,Brim,532,Spain,Female,66,3,0,1,1,1,115227.02,0 +2793,15742820,Trevisano,535,France,Female,45,2,0,2,0,1,170621.55,0 +2794,15624793,Soubeiran,627,Germany,Male,23,5,184244.86,1,1,0,103099.22,0 +2795,15597930,Wilson,646,France,Male,52,8,59669.43,1,0,0,172495.81,1 +2796,15665110,Helena,515,France,Female,25,7,79543.59,1,0,1,38772.82,0 +2797,15770719,Duncan,697,France,Female,39,6,151553.19,1,1,1,44946.29,0 +2798,15731327,Hale,652,Germany,Male,27,2,166527.88,2,0,1,146007.7,0 +2799,15576044,Macdonald,579,Germany,Male,28,6,150329.15,1,1,0,145558.42,0 +2800,15775662,McKay,760,France,Male,43,8,121911.59,1,1,0,193312.33,0 +2801,15646817,Chiekwugo,769,France,Male,51,9,156773.78,2,1,0,40257.79,0 +2802,15596060,Skinner,498,Spain,Male,29,8,127864.26,1,1,1,46677.9,0 +2803,15723299,Sorokina,774,France,Male,53,4,113709.28,1,1,1,153887.93,1 +2804,15636982,Weller,705,Germany,Female,43,7,79974.55,1,1,1,103108.33,0 +2805,15751175,Bess,648,France,Female,44,2,0,2,1,1,58652.23,0 +2806,15618936,MacDonald,688,France,Female,51,5,0,1,1,0,91624.11,1 +2807,15787529,Gray,592,Spain,Male,38,0,0,1,1,0,65986.48,1 +2808,15780128,Ogbonnaya,705,France,Male,33,3,144427.96,2,1,0,113845.19,0 +2809,15615991,Udegbulam,654,France,Male,42,7,99263.09,1,1,1,67607.9,0 +2810,15757001,Mai,624,France,Female,32,2,79368.87,2,1,1,145471.94,0 +2811,15595388,Yeh,594,France,Female,30,10,0,2,1,1,124071.71,0 +2812,15699550,Babbage,695,Spain,Female,34,9,0,2,1,1,67502.12,0 +2813,15581620,Franklin,597,France,Male,28,2,0,3,1,1,78707.97,0 +2814,15600934,Randell,758,France,Female,52,7,125095.94,1,1,0,171189.83,1 +2815,15738672,Paterson,737,Germany,Female,40,2,162485.8,2,1,0,149381.32,0 +2816,15721307,Pickering,694,Germany,Male,37,1,95668.82,2,1,0,100335.55,0 +2817,15619280,Uspensky,683,France,Male,25,4,0,2,1,0,152698.24,0 +2818,15768244,Macleod,538,Spain,Female,30,8,0,2,1,1,41192.95,0 +2819,15806837,Nnaife,669,France,Male,37,4,0,1,1,0,132540.33,0 +2820,15643496,Randolph,730,France,Female,34,5,74197.38,2,1,0,96875.52,0 +2821,15813916,Kudryashova,622,France,Female,31,1,89688.94,1,1,1,152305.47,0 +2822,15626385,George,714,Spain,Female,33,10,103121.33,2,1,1,49672.01,0 +2823,15603582,Robertson,569,Spain,Female,34,3,0,1,1,0,133997.53,0 +2824,15764351,Yuryeva,668,Germany,Female,59,5,120170.07,1,0,1,50454.8,0 +2825,15667938,Hurst,628,France,Male,32,9,149136.31,2,1,1,16402.11,0 +2826,15576360,Ch'iu,600,France,Male,40,1,141136.79,1,1,1,67803.83,0 +2827,15628813,King,693,France,Female,43,4,152341.55,1,1,0,9241.78,0 +2828,15584190,Esposito,704,France,Male,36,7,120026.98,2,0,1,100601.73,0 +2829,15716449,Fraser,527,Spain,Male,33,9,132168.28,1,0,0,98734.15,0 +2830,15759913,Trentini,553,Germany,Male,43,6,85200.82,2,1,1,160574.09,0 +2831,15701555,Nicholls,575,Spain,Male,53,1,84903.33,2,0,1,26015.8,0 +2832,15758482,Montalvo,626,France,Female,32,0,0,2,0,0,187172.54,0 +2833,15758171,Tien,582,France,Male,20,4,0,1,1,1,55763.66,0 +2834,15680346,Chuang,683,Spain,Male,40,8,0,1,1,0,75848.22,0 +2835,15649124,Fang,850,France,Male,30,9,121535.18,1,0,0,40313.47,0 +2836,15812917,Kosisochukwu,653,Spain,Male,35,6,116662.96,2,1,1,23864.21,0 +2837,15768455,Young,679,France,Male,60,8,0,2,1,1,51380.9,0 +2838,15703059,Scott,549,Germany,Female,49,6,124829.16,1,0,1,93551.36,0 +2839,15646196,Yeh,850,Spain,Female,36,2,155180.56,2,0,0,169415.54,0 +2840,15585451,Vigano,558,Germany,Female,32,1,108262.87,1,1,1,6935.31,0 +2841,15714057,Windradyne,528,Spain,Male,40,4,0,2,1,0,25399.7,0 +2842,15748473,Curnow,801,France,Male,38,5,0,2,1,0,66256.27,0 +2843,15785782,Ugonna,513,Spain,Male,48,2,0,1,1,1,114709.13,1 +2844,15693233,De Neeve,666,Germany,Male,38,6,99812.88,2,1,1,158357.97,0 +2845,15757521,Ricci,606,France,Male,35,2,132164.26,1,0,1,164815.59,0 +2846,15812513,Nnaife,599,Germany,Male,45,10,103583.05,1,1,0,132127.69,1 +2847,15674950,Ebelechukwu,544,Germany,Male,39,4,142406.43,2,1,0,146637.45,0 +2848,15678572,Keating,529,Spain,Male,38,7,99842.5,2,1,0,90256.06,1 +2849,15713608,Tuan,850,France,Female,41,5,0,2,1,1,34827.43,0 +2850,15579262,Shearston,497,France,Male,41,9,0,1,0,0,22074.48,0 +2851,15610426,Tien,764,France,Female,39,5,81042.42,1,0,1,109805.17,0 +2852,15776454,Hamilton,603,France,Female,48,5,0,1,1,0,100478.6,1 +2853,15771483,Arnold,609,France,Male,40,6,0,2,1,1,97416.34,0 +2854,15648489,Ting,487,France,Male,53,4,199689.49,1,1,1,24207.86,1 +2855,15646609,Chao,748,France,Male,33,1,142645.43,1,0,0,69132.66,0 +2856,15693203,Powell,710,Spain,Female,75,5,0,2,1,1,9376.89,0 +2857,15813067,Williams,432,Germany,Female,45,3,110219.14,1,1,0,43046.7,1 +2858,15769829,Cheng,534,Spain,Male,51,3,0,2,0,1,20856.31,0 +2859,15662434,Zhdanova,607,France,Male,25,3,0,2,0,0,187048.72,0 +2860,15773503,Tsai,551,Spain,Male,32,4,0,2,1,0,53420.53,0 +2861,15705890,Nebechukwu,674,France,Male,45,7,142072.02,1,1,0,37013.29,0 +2862,15711398,Fetherstonhaugh,525,France,Female,25,6,0,2,1,0,89566.64,0 +2863,15752375,Ojiofor,645,Germany,Male,33,8,149564.61,1,0,0,149913.84,0 +2864,15659175,Severson,755,France,Female,43,9,0,2,1,0,18066.69,0 +2865,15597033,Speight,708,Germany,Male,37,8,153366.13,1,1,1,26912.34,0 +2866,15590228,Greenwalt,715,France,Male,21,6,76467.16,1,1,1,173511.72,0 +2867,15631848,Grover,727,France,Female,26,9,121508.28,1,1,1,146785.44,0 +2868,15654211,Milani,559,Spain,Female,27,1,0,1,0,1,1050.33,0 +2869,15707968,Akobundu,545,Spain,Male,36,8,73211.12,2,1,0,89587.34,1 +2870,15594084,Anderson,524,France,Male,22,9,0,2,1,0,74405.34,0 +2871,15651093,Chien,707,France,Female,55,1,0,2,0,1,54409.48,0 +2872,15798824,Kennedy,671,Spain,Male,38,0,92674.94,2,1,0,3647.57,0 +2873,15671591,Castiglione,439,Spain,Male,52,3,96196.24,4,1,0,198874.52,1 +2874,15707189,Marshall,667,Germany,Female,36,1,114391.62,1,1,1,53412.54,0 +2875,15733581,Duncan,831,Germany,Male,32,9,80262.66,1,1,0,194867.78,0 +2876,15641640,Uspenskaya,545,Spain,Female,33,7,173331.52,1,1,0,150452.88,0 +2877,15585284,Thomson,604,Spain,Female,35,7,147285.52,1,1,1,57807.05,0 +2878,15617866,Calabrese,657,Spain,Male,67,5,119785.47,2,1,1,107534.32,0 +2879,15667751,Herrera,487,Spain,Female,36,1,140137.15,1,1,0,194073.33,0 +2880,15669411,Muse,750,Germany,Female,52,6,107467.56,1,1,0,126233.18,1 +2881,15789425,Marsden,694,Germany,Female,37,8,98218.04,2,1,0,182354.46,1 +2882,15570943,Artemyeva,711,Germany,Female,35,2,133607.75,1,1,1,120586.32,0 +2883,15685829,McKay,551,France,Male,37,3,0,2,1,1,50578.4,0 +2884,15721917,Chuang,559,France,Female,38,8,95139.41,1,1,1,86575.46,0 +2885,15776047,Nicholls,620,France,Female,29,3,0,2,0,1,153392.28,0 +2886,15716024,Dennis,660,Spain,Male,42,5,0,2,1,0,115509.59,0 +2887,15675328,Knight,449,France,Female,37,6,0,2,1,0,82176.48,0 +2888,15604314,Webb,703,Germany,Female,26,1,97331.19,1,1,0,63717.49,0 +2889,15658339,Pugliesi,795,Germany,Male,37,2,139265.63,2,1,1,198745.94,0 +2890,15630402,Nebechukwu,594,France,Female,31,9,0,1,0,1,5719.11,0 +2891,15689616,Ward,586,Spain,Male,34,5,168094.01,1,0,0,20058.61,0 +2892,15774224,Nixon,613,Germany,Female,30,5,131563.88,2,1,0,170638.98,0 +2893,15701291,Chidubem,601,France,Male,44,3,0,2,1,0,30607.11,0 +2894,15719606,Rivers,657,France,Male,50,9,0,2,0,0,37171.46,0 +2895,15644119,Sochima,531,France,Male,31,3,0,1,1,1,42589.33,0 +2896,15646859,Heydon,621,Germany,Male,47,7,107363.29,1,1,1,66799.28,0 +2897,15606836,Lombardo,782,France,Female,33,2,94493.03,1,0,1,101866.39,0 +2898,15664150,Holland,528,Germany,Female,29,9,170214.23,2,1,0,49284,0 +2899,15624510,Tien,696,France,Male,52,6,139781.06,1,1,0,27445.4,1 +2900,15810944,Bryant,586,France,Female,35,7,0,2,1,0,70760.69,0 +2901,15668575,Hao,626,Spain,Female,26,8,148610.41,3,0,1,104502.02,1 +2902,15603246,Genovesi,498,France,Male,73,2,170241.7,2,1,1,165407.96,0 +2903,15804002,Kovalev,691,France,Female,33,1,128306.83,1,1,1,113580.79,0 +2904,15728773,Hsieh,568,France,Female,47,7,0,2,1,1,45978.39,0 +2905,15598044,Debellis,715,France,Female,35,3,0,1,1,1,152012.36,0 +2906,15694829,Chibueze,680,Germany,Male,32,7,175454,1,0,1,77349.92,0 +2907,15600575,Padovano,802,Spain,Male,41,6,0,2,1,0,47322.05,0 +2908,15727311,Yen,539,France,Female,22,0,100885.93,2,1,1,38772.65,0 +2909,15570769,Kibble,494,France,Male,69,9,93320.8,1,1,1,24489.44,0 +2910,15606274,Lori,594,Germany,Male,38,6,63176.44,2,1,1,14466.08,0 +2911,15746139,Enemuo,596,France,Male,33,2,139451.67,1,0,0,63142.12,0 +2912,15704987,Lu,649,France,Female,52,8,49113.75,1,1,0,41858.43,0 +2913,15628972,Nebeolisa,699,Germany,Male,32,1,123906.22,3,1,1,127443.82,1 +2914,15697686,Stewart,787,France,Female,40,6,0,2,1,1,84151.98,0 +2915,15733883,Ward,604,France,Male,28,7,0,2,0,0,58595.64,0 +2916,15617482,Milanesi,489,Germany,Female,52,1,131441.51,1,1,0,37240.11,1 +2917,15704583,Chikwado,651,France,Male,56,2,0,1,1,0,114522.68,1 +2918,15621083,Douglas,698,France,Male,57,6,136325.48,2,1,1,72549.27,1 +2919,15649487,Sal,578,Germany,Female,38,4,113150.44,2,1,0,176712.59,1 +2920,15736760,Douglas,538,Spain,Female,42,9,0,1,0,0,152855.96,0 +2921,15714658,Yates,696,France,Female,33,4,0,2,1,1,73371.65,0 +2922,15599081,Watt,507,Germany,Female,46,8,102785.16,1,1,1,70323.68,0 +2923,15705113,P'an,685,Spain,Male,34,6,83264.28,1,0,0,9663.28,0 +2924,15631159,H?,705,Germany,Male,41,4,72252.64,2,1,1,142514.66,0 +2925,15792818,Perry,499,Germany,Female,29,6,148051.52,1,1,0,118623.94,0 +2926,15633531,Lavrov,717,France,Female,76,9,138489.66,1,1,1,68400.14,0 +2927,15744529,Chiekwugo,510,France,Male,63,8,0,2,1,1,115291.86,0 +2928,15669656,Macdonald,632,France,Male,32,6,111589.33,1,1,1,170382.99,0 +2929,15581198,Jenkins,668,Germany,Female,39,0,122104.79,1,1,0,112946.67,1 +2930,15729054,Korovina,744,Germany,Male,32,4,96106.83,1,1,1,79812.77,0 +2931,15573452,Manning,663,Germany,Male,42,7,115930.87,1,1,0,19862.78,0 +2932,15776733,Wilson,638,Germany,Female,37,7,124513.66,2,1,0,158610.89,0 +2933,15724858,Begum,688,France,Female,54,9,0,1,1,0,191212.63,1 +2934,15713144,Ingrassia,588,Spain,Male,46,8,0,1,1,0,61931.21,0 +2935,15690188,Maclean,631,France,Male,33,7,0,1,1,1,58043.02,1 +2936,15689425,Olejuru,687,Spain,Male,35,8,100988.39,2,1,0,22247.27,0 +2937,15671766,Enyinnaya,599,France,Male,44,10,118577.24,1,1,1,31448.52,0 +2938,15782806,Watson,718,Spain,Male,28,6,0,2,1,0,146875.86,0 +2939,15764419,Langdon,730,France,Male,27,5,0,2,1,1,116081.93,0 +2940,15591915,Frolov,533,France,Female,39,2,0,1,0,1,73669.94,1 +2941,15772798,Chikezie,711,Spain,Female,28,5,0,2,1,1,93959.96,0 +2942,15792008,Zetticci,555,Spain,Female,26,9,0,2,0,1,158918.03,0 +2943,15715541,Yang,850,France,Female,42,9,113311.11,1,1,1,198193.75,0 +2944,15639277,Lin,678,France,Female,41,9,0,1,0,0,13160.03,0 +2945,15798850,Goddard,576,France,Male,32,7,0,2,1,0,4660.91,0 +2946,15776348,Rogers,835,Germany,Male,20,4,124365.42,1,0,0,180197.74,1 +2947,15727696,Zubareva,592,France,Male,42,1,147249.29,2,1,1,63023.02,0 +2948,15793813,Onochie,774,France,Male,36,7,103688.19,1,0,1,118971.74,0 +2949,15694395,Ts'ui,620,France,Female,29,1,138740.24,2,0,0,154700.61,0 +2950,15764195,Newsom,519,Spain,Male,39,4,111900.14,1,1,1,97577.17,0 +2951,15744919,Genovese,734,Spain,Female,37,0,152760.24,1,1,1,48990.5,0 +2952,15671655,Thorpe,763,Germany,Male,31,7,143966.3,2,1,1,140262.96,1 +2953,15654901,Horton,733,France,Male,51,10,141556.96,1,1,0,130189.53,0 +2954,15649136,Williamson,650,France,Female,43,6,0,2,1,1,16301.91,0 +2955,15775562,Shoobridge,538,France,Female,33,5,0,2,1,0,126962.41,0 +2956,15807481,Peng,577,France,Female,46,1,0,1,1,1,158750.53,0 +2957,15642885,Gray,792,France,Male,30,8,0,2,1,0,199644.2,0 +2958,15789109,Watson,686,France,Female,41,10,0,1,1,1,144272.71,1 +2959,15814004,Fyodorova,589,France,Male,29,2,0,2,0,1,98320.27,0 +2960,15673619,Bazhenov,530,France,Male,25,9,162560.32,1,1,0,64129.03,0 +2961,15595135,Solomon,778,Germany,Female,29,7,123229.46,1,1,0,181221.09,0 +2962,15583681,Layh,616,Spain,Male,31,7,76665.71,2,1,1,163809.08,0 +2963,15605000,John,550,France,Male,38,9,140278.99,3,1,1,171457.06,1 +2964,15718071,Tuan,655,France,Female,51,3,0,2,0,1,15801.02,0 +2965,15679760,Slattery,721,France,Male,46,1,115764.32,2,0,0,102950.79,0 +2966,15654574,Onyekachi,499,Germany,Male,36,5,131142.53,2,1,0,174918.46,0 +2967,15577178,Genovese,511,France,Male,45,5,68375.27,1,1,0,193160.25,1 +2968,15595324,Daniels,579,Germany,Female,39,5,117833.3,3,0,0,5831,1 +2969,15756932,Caldwell,696,Spain,Female,36,7,0,2,1,1,82298.59,0 +2970,15726358,Chiemenam,681,France,Male,34,7,0,2,0,0,130686.59,0 +2971,15595228,Wanliss,815,France,Male,45,7,0,1,0,1,52885.23,1 +2972,15782530,Bruce,681,Spain,Male,30,2,111093.01,1,1,0,68985.99,0 +2973,15592877,Wright,641,Spain,Male,42,9,132657.55,1,1,0,35367.19,0 +2974,15651983,Fang,591,France,Female,56,9,128882.49,1,1,1,196241.94,1 +2975,15746737,Eames,565,Germany,Male,59,9,69129.59,1,1,1,170705.53,0 +2976,15774179,Sutherland,487,France,Male,37,6,0,2,1,1,126477.41,0 +2977,15667265,Cavenagh,729,France,Male,39,4,121404.64,1,1,1,159618.17,0 +2978,15655123,Dumetolisa,505,Spain,Female,45,9,131355.3,3,1,0,195395.33,1 +2979,15595917,Mackay,580,France,Female,35,1,102097.33,1,0,1,168285.85,0 +2980,15668385,Dellucci,642,France,Male,40,1,154863.15,1,1,1,138052.51,0 +2981,15709476,Kenyon,850,Spain,Female,41,3,99945.93,2,1,0,71179.31,0 +2982,15711218,Parry,616,Germany,Male,39,2,121704.32,2,1,0,55556.3,0 +2983,15798659,Kennedy,526,Spain,Female,43,3,0,2,1,0,31705.19,0 +2984,15663939,Arnott,523,Germany,Male,35,8,138782.76,1,1,1,186118.93,0 +2985,15694946,Hanson,663,France,Male,35,9,0,2,1,1,195580.28,0 +2986,15631912,T'ao,840,France,Male,30,8,136291.71,1,1,0,54113.38,0 +2987,15768816,Shen,570,Germany,Male,42,0,107856.57,2,1,0,127528.84,0 +2988,15682268,Steere,676,Germany,Female,26,1,108348.66,1,0,0,60231.74,1 +2989,15684801,Abbott,689,France,Male,47,1,93871.95,3,1,0,156878.42,1 +2990,15636428,Sutherland,703,Spain,Female,45,1,0,1,1,0,182784.11,1 +2991,15809823,Thurgood,491,Germany,Male,19,2,125860.2,1,0,0,129690.5,0 +2992,15699284,Johnson,584,France,Male,49,8,172713.44,1,1,0,113860.81,0 +2993,15786993,Lung,810,France,Female,51,5,0,2,0,1,184524.74,0 +2994,15709441,Cocci,745,Spain,Female,59,8,0,1,1,1,36124.98,0 +2995,15710257,Matveyeva,625,France,Female,39,3,130786.92,1,0,1,121316.07,0 +2996,15582492,Moore,535,France,Female,29,2,112367.34,1,1,0,185630.76,0 +2997,15575694,Yobachukwu,729,Spain,Female,45,7,91091.06,2,1,0,71133.12,0 +2998,15756820,Fleming,655,France,Female,26,7,106198.5,1,0,1,32020.42,0 +2999,15766289,Dickinson,751,France,Male,47,5,142669.93,2,1,0,162760.96,0 +3000,15593014,Evseyev,525,France,Male,33,1,112833.35,1,0,1,175178.56,0 +3001,15584545,Aksenov,532,France,Female,40,5,0,2,0,1,177099.71,0 +3002,15675949,Fleming,696,Spain,Female,43,4,0,2,1,1,66406.37,0 +3003,15672091,Ulyanov,786,Germany,Female,32,2,104336.43,2,0,0,59559.81,0 +3004,15801658,Summers,580,France,Male,55,6,104305.74,1,0,1,175750.21,0 +3005,15706185,Clements,596,Germany,Male,47,5,140187.1,2,1,1,174311.3,0 +3006,15789863,Kazakova,683,France,Male,39,4,0,2,1,0,171716.81,0 +3007,15720943,Pirozzi,747,France,Female,45,1,114959.12,1,1,0,189362.39,1 +3008,15697997,Jamieson,602,France,Male,33,5,164704.38,1,0,1,180716.1,1 +3009,15665416,Ferri,779,France,Male,62,10,119096.55,1,0,1,116977.89,0 +3010,15660200,Mai,551,France,Male,31,1,0,2,1,1,185105.44,0 +3011,15619653,Hannaford,666,France,Male,47,2,0,1,1,0,35046.97,1 +3012,15773447,Fomin,526,Spain,Male,30,8,0,1,1,0,36251,0 +3013,15739160,Mahon,849,France,Female,41,9,115465.28,1,1,0,103174.5,0 +3014,15689237,Shaw,471,France,Female,27,4,0,2,1,0,122642.09,0 +3015,15679297,Volkova,628,Spain,Male,43,3,184926.61,1,1,0,122937.57,0 +3016,15591433,Miles,674,Germany,Male,43,8,85957.88,2,1,0,8757.39,0 +3017,15642725,Madison,797,France,Male,32,10,114084.6,1,0,1,125782.29,0 +3018,15701962,Scott,590,Spain,Female,29,2,166930.76,2,1,0,122487.73,0 +3019,15811613,Voss,588,France,Female,27,8,0,1,1,0,20066.38,0 +3020,15741049,Colebatch,577,France,Male,29,7,0,2,1,1,55473.15,0 +3021,15724423,Wilson,571,France,Female,38,6,107193.82,2,0,0,38962.94,0 +3022,15574305,T'ang,680,France,Male,36,3,116275.12,1,1,1,63795.8,0 +3023,15678168,Gibson,648,Spain,Female,27,7,0,2,1,1,163060.43,0 +3024,15697020,Hs?eh,618,France,Male,39,2,91068.56,1,1,0,26578.69,0 +3025,15610801,Pan,648,Germany,Male,41,5,123049.21,1,0,1,5066.76,0 +3026,15745232,Chikelu,759,France,Female,39,6,0,2,1,1,140497.67,0 +3027,15722758,Allan,585,France,Male,40,7,0,2,0,0,146156.98,0 +3028,15792102,Yefremova,774,France,Female,42,3,137781.65,1,0,0,199316.19,0 +3029,15675185,Chuang,697,Germany,Female,48,2,108128.96,2,1,1,103944.37,0 +3030,15801247,Fan,605,Spain,Male,39,10,105317.73,2,1,0,138021.36,0 +3031,15725660,Dellucci,676,France,Male,20,1,80569.73,1,0,0,68621.98,0 +3032,15638963,Garran,678,France,Female,22,4,174852.89,1,1,1,28149.06,0 +3033,15800061,Moretti,495,Spain,Female,45,3,89158.94,3,1,0,135169.76,1 +3034,15578006,Yao,787,France,Female,85,10,0,2,1,1,116537.96,0 +3035,15668504,Lucchesi,770,France,Male,36,2,89800.14,1,1,1,105922.69,0 +3036,15687491,Nkemdilim,817,Germany,Male,45,9,101207.75,1,0,0,88211.12,1 +3037,15610403,Anderson,659,France,Male,43,1,106086.42,2,1,0,26900.63,0 +3038,15741094,Sagese,693,France,Male,21,1,0,2,1,1,3494.02,0 +3039,15807909,Rubensohn,744,France,Male,47,9,0,2,1,0,113163.17,0 +3040,15666141,Baldwin,829,Spain,Female,26,8,101440.36,2,1,1,19324.5,0 +3041,15617134,Iqbal,716,France,Male,38,4,0,2,1,0,189678.7,0 +3042,15783029,Monaldo,671,France,Male,34,7,106603.74,2,1,1,26387.71,0 +3043,15622833,Mahon,835,Germany,Female,29,10,130420.2,2,0,0,106276.55,0 +3044,15746422,Muir,636,France,Female,38,1,0,1,1,0,45015.38,0 +3045,15750839,Burns,649,Spain,Male,29,2,45022.23,1,1,1,173495.77,0 +3046,15749130,Dyer,621,Germany,Male,27,1,74298.43,1,1,1,52581.96,0 +3047,15779862,Lyons,658,Germany,Female,31,3,133003.03,1,0,1,146339.27,1 +3048,15767871,H?,784,Spain,Male,48,7,0,2,1,1,182609.97,0 +3049,15679651,Gardiner,783,Spain,Female,37,1,136689.66,1,1,0,197890.65,0 +3050,15576219,Cameron,615,France,Male,32,4,0,2,1,1,6225.63,0 +3051,15699247,Chapman,791,France,Female,44,5,0,2,1,1,123977.86,1 +3052,15619087,Taylor,762,France,Male,53,1,102520.37,1,1,1,170195.4,0 +3053,15605327,Namatjira,607,France,Male,35,2,0,2,1,1,114190.3,0 +3054,15610140,He,601,France,Female,34,5,0,2,1,0,27022.57,0 +3055,15791174,Leibius,540,Spain,Male,67,1,88382.01,1,0,1,59457,0 +3056,15602373,White,812,France,Male,44,4,115049.15,2,1,0,165038.41,0 +3057,15762605,Wall,685,France,Male,58,1,104796.54,1,1,1,154181.41,0 +3058,15598840,Moretti,680,France,Male,33,1,123082.08,1,1,0,134960.98,0 +3059,15744279,Patterson,680,Spain,Female,58,8,0,2,1,1,65708.5,0 +3060,15670619,Coppin,631,France,Female,33,8,0,2,0,0,117374.22,0 +3061,15599533,Tsao,569,France,Female,43,7,0,2,1,1,77703.19,0 +3062,15757837,Kao,584,Germany,Male,33,3,88311.48,2,1,1,177651.38,0 +3063,15697574,Stewart,582,France,Female,40,9,0,3,1,1,60954.45,0 +3064,15578738,Tuan,609,France,Male,32,7,71872.19,1,1,1,151924.9,0 +3065,15762228,Barnes,506,Spain,Male,35,6,110046.93,2,1,0,26318.73,0 +3066,15614827,Sun,503,France,Male,42,8,104430.08,1,1,1,147557.71,0 +3067,15789815,Fallaci,503,France,Female,28,5,0,2,1,0,125918.17,0 +3068,15579781,Buccho,806,Germany,Male,31,10,138653.51,1,1,0,190803.37,0 +3069,15587013,Tien,653,France,Female,31,7,102575.04,1,1,1,11043.54,0 +3070,15570932,Pirozzi,666,France,Male,43,7,137780.74,2,1,1,119100.05,1 +3071,15794661,Liu,674,Spain,Male,32,2,0,2,1,0,140579.17,0 +3072,15581654,Long,798,France,Male,32,7,0,2,0,1,37731.95,0 +3073,15644296,Scott,740,France,Female,30,8,105209.54,1,1,0,1852.58,0 +3074,15614420,Gerasimova,531,Germany,Female,32,0,109570.21,2,1,1,172049.84,0 +3075,15609653,Ifeatu,614,Germany,Female,44,6,118715.86,1,1,0,133591.11,1 +3076,15594577,De Luca,556,France,Male,35,10,0,2,1,1,192751.18,0 +3077,15584114,Ogbonnaya,678,Germany,Female,43,2,153393.18,2,1,1,193828.27,0 +3078,15673367,Humffray,587,Germany,Male,33,6,132603.36,1,1,0,55775.72,0 +3079,15685576,Degtyaryov,527,Spain,Female,36,6,0,2,1,1,102280.29,0 +3080,15774727,Monaldo,757,Germany,Female,34,1,129398.01,2,0,0,44965.44,0 +3081,15694288,Cawthorne,468,Spain,Male,28,3,0,2,1,0,170661.02,0 +3082,15603319,Graham,693,France,Male,29,2,151352.74,1,0,0,197145.89,0 +3083,15759066,Carpenter,483,France,Female,44,5,136836.49,1,1,0,192359.9,1 +3084,15814816,Kambinachi,466,France,Male,40,4,91592.06,1,1,0,141210.18,1 +3085,15724402,Tyler,770,France,Female,30,8,0,2,1,0,100557.03,0 +3086,15571059,Martin,734,France,Female,54,3,0,1,1,0,130805.54,1 +3087,15674206,Walker,716,France,Female,22,8,0,2,1,1,92606.98,0 +3088,15715160,Khan,439,France,Male,36,2,165536.28,2,1,1,123956.83,0 +3089,15730448,Iroawuchi,538,Germany,Male,25,5,62482.95,1,1,1,102758.43,0 +3090,15662067,Summers,743,France,Male,40,8,68155.59,1,1,0,94876.65,0 +3091,15779581,Bottrill,734,Spain,Female,43,3,55853.33,2,0,1,94811.85,1 +3092,15662901,Hu,656,France,Male,37,2,0,2,0,1,67840.81,0 +3093,15689751,Jones,666,France,Female,31,2,79589.43,1,0,0,4050.57,0 +3094,15667742,Vincent,627,Spain,Male,41,5,100880.76,1,0,1,134665.25,0 +3095,15738448,Sanford,480,Germany,Female,25,3,174330.35,2,0,0,181647.13,0 +3096,15680243,Brown,792,France,Male,19,7,143390.51,1,1,0,33282.84,0 +3097,15745083,Lei,613,Germany,Male,59,8,91415.76,1,0,0,27965,1 +3098,15708228,Toscani,476,Germany,Male,30,3,134366.42,1,1,0,68343.53,0 +3099,15628523,Chien,539,France,Female,24,3,0,2,1,1,198161.07,0 +3100,15708196,Uchenna,696,Spain,Male,60,8,88786.81,1,1,1,196858.4,0 +3101,15735549,Lori,810,Germany,Male,35,3,96814.46,2,1,1,120511.03,0 +3102,15809347,Fanucci,763,Germany,Male,32,9,160680.41,1,1,0,30886.35,0 +3103,15660866,Chimaobim,640,France,Female,29,3,0,2,1,0,2743.69,0 +3104,15766609,Jowers,655,France,Female,47,10,0,2,1,0,167778.62,0 +3105,15654230,Miller,526,Germany,Male,31,5,145537.21,1,1,0,132404.64,0 +3106,15794566,Kirsova,678,France,Female,28,4,0,2,1,1,144423.17,1 +3107,15800890,T'ien,554,France,Female,45,6,0,2,1,1,181204.5,0 +3108,15697424,Ku,597,Spain,Female,30,2,119370.11,1,1,1,182726.22,1 +3109,15724536,Chin,560,Spain,Female,28,1,0,2,1,1,120880.72,0 +3110,15735878,Law,850,Germany,Female,47,10,134381.52,1,0,0,26812.89,1 +3111,15707596,Chung,546,Germany,Female,74,8,114888.74,2,1,1,66732.63,1 +3112,15657163,Cockrum,623,Germany,Male,42,1,149332.48,2,1,0,100834.22,0 +3113,15622478,Greaves,698,France,Female,40,7,105061.74,3,1,0,107815.31,1 +3114,15779529,Grant,620,France,Male,32,7,0,2,1,1,34665.79,0 +3115,15636023,O'Donnell,619,France,Female,40,10,0,1,1,1,147093.84,1 +3116,15582066,Maclean,561,France,Male,21,4,0,1,1,1,36942.35,0 +3117,15666675,Hsieh,753,France,Female,39,7,155062.8,1,1,1,16460.77,0 +3118,15732987,Hs?,721,Spain,Male,43,3,88798.34,1,0,0,45610.63,0 +3119,15789432,Mazzanti,451,France,Male,33,6,0,2,1,0,184954.11,0 +3120,15663161,Chiu,680,Germany,Female,51,5,143139.87,1,0,0,47795.43,1 +3121,15694879,Reeves,590,Spain,Female,23,7,0,2,1,0,196789.9,0 +3122,15593715,Castiglione,634,Germany,Male,27,3,107027.52,1,1,0,173425.68,0 +3123,15575002,Ferguson,676,France,Male,29,4,140720.93,1,1,0,36221.18,0 +3124,15622171,Nnamdi,642,France,Male,30,8,80964.57,2,1,0,174738.2,0 +3125,15795224,Wu,760,France,Male,39,6,178585.46,1,1,0,67131.3,1 +3126,15685346,Chu,736,Spain,Female,26,4,135889.13,1,1,1,165692.03,0 +3127,15691808,King,656,France,Male,43,7,134919.85,1,1,0,194691.95,0 +3128,15721007,Charlton,776,Germany,Male,33,8,115130.34,1,0,0,129525.5,1 +3129,15794253,Marsh,832,Spain,Female,34,6,138190.13,2,0,1,146511.2,0 +3130,15694453,Walker,631,Germany,Male,37,9,131519.49,2,1,1,51752.18,0 +3131,15813113,Chang,795,Spain,Female,56,5,0,1,1,0,35418.69,1 +3132,15614187,Pottinger,648,Germany,Female,39,3,126935.98,2,0,1,57995.74,0 +3133,15619407,Buckley,615,France,Male,39,4,133707.09,1,1,1,108152.75,0 +3134,15646227,Folliero,682,France,Female,27,1,97893.2,1,1,0,166144.98,0 +3135,15660541,Olisanugo,694,France,Male,34,5,127900.03,1,1,0,101737.8,0 +3136,15753874,Kent,694,France,Male,37,10,143835.47,1,0,1,33326.71,0 +3137,15617877,Jessop,607,France,Male,44,0,0,2,1,1,81140.09,0 +3138,15772073,Hodge,664,France,Male,48,10,0,1,1,0,140173.17,1 +3139,15701537,Ignatiev,756,France,Male,60,2,0,1,1,1,166513.49,1 +3140,15736228,Chambers,645,France,Female,40,3,129596.77,1,1,1,103232.6,0 +3141,15780572,Mansom,653,Spain,Male,30,4,0,2,1,0,120736.04,0 +3142,15769596,Yen,710,Germany,Female,24,2,110407.44,2,0,0,15832.43,1 +3143,15586996,Azikiwe,697,France,Female,76,7,0,2,0,1,188772.45,0 +3144,15722061,Allen,619,Germany,Female,41,8,142015.76,2,1,0,114323.66,0 +3145,15638003,Komarova,648,Spain,Male,55,1,81370.07,1,0,1,181534.04,0 +3146,15775590,Mackay,482,Germany,Female,48,2,69329.47,1,0,0,102640.52,1 +3147,15730688,Yu,548,France,Female,28,8,116755.5,2,1,1,158585.17,1 +3148,15753102,Curtis,752,Spain,Male,44,6,83870.33,1,1,0,178722.24,0 +3149,15810075,Fang,648,France,Female,39,6,130694.89,2,1,1,153955.38,1 +3150,15723373,Page,643,Spain,Female,34,8,117451.47,1,1,0,65374.86,0 +3151,15795298,Olisaemeka,573,Germany,Female,35,9,206868.78,2,0,1,102986.15,0 +3152,15584320,Brennan,686,France,Female,39,3,111695.62,1,0,0,136643.84,0 +3153,15724161,Sutton,644,France,Female,40,9,137285.26,4,1,0,77063.63,1 +3154,15750056,Hyde,702,France,Female,29,6,149218.39,1,1,1,9633.01,0 +3155,15609637,Nkemakolam,652,France,Male,51,7,0,2,0,1,43496.36,0 +3156,15794493,Chimaijem,641,Spain,Male,32,7,0,2,1,1,24267.28,0 +3157,15569641,Sung,692,Germany,Female,41,8,130701.29,1,1,0,59354.24,1 +3158,15815236,Chiganu,574,Spain,Male,34,5,0,2,0,0,28269.86,0 +3159,15811177,Beneventi,643,France,Female,31,3,167949.48,1,1,0,143162.34,0 +3160,15680587,Esposito,834,France,Male,23,4,131254.81,1,1,0,20199.3,0 +3161,15672821,Owen,591,France,Male,28,5,0,2,1,1,48606.92,0 +3162,15767681,Smalley,470,Spain,Male,34,9,0,2,0,1,89013.67,0 +3163,15600379,Hsiung,608,Spain,Male,34,7,86656.13,1,0,1,59890.29,0 +3164,15801336,Ch'ang,649,Germany,Female,37,8,114737.26,1,1,1,106655.88,1 +3165,15721592,Barton,665,France,Female,38,5,0,2,1,0,156439.56,0 +3166,15581282,Lucchese,651,France,Female,39,6,0,1,1,0,24176.44,0 +3167,15746203,Hsia,555,Germany,Male,62,4,119817.33,1,0,1,43507.1,1 +3168,15583137,Pope,637,France,Female,48,7,130806.99,2,1,1,132005.85,1 +3169,15680752,Horrocks,675,France,Female,49,0,0,1,1,1,80496.71,1 +3170,15688172,Tai,677,Spain,Male,40,5,0,2,1,0,88947.56,0 +3171,15791373,Chikezie,850,Germany,Female,35,2,80931.75,1,0,0,12639.67,1 +3172,15589449,Frye,815,France,Female,56,3,0,3,1,1,94248.16,1 +3173,15692819,Toscani,665,Germany,Male,32,1,132178.67,1,0,0,11865.76,0 +3174,15727467,Mellor,485,France,Female,27,3,0,2,1,0,141449.86,0 +3175,15734312,Kang,577,Spain,Male,43,6,0,2,1,1,149457.81,0 +3176,15764604,Sutherland,586,France,Female,35,7,164769.02,3,1,0,119814.25,1 +3177,15613014,Hs?,722,Germany,Male,29,1,107233.85,2,1,0,24924.92,0 +3178,15759684,Ting,528,France,Female,27,7,176227.07,2,0,1,139481.53,0 +3179,15609669,Chuang,542,France,Female,39,4,109949.39,2,1,1,41268.65,0 +3180,15685536,Chu,552,France,Female,34,5,0,2,1,1,1351.41,0 +3181,15750447,Ozoemena,678,France,Female,60,10,117738.81,1,1,0,147489.76,1 +3182,15663249,Howells,575,Spain,Female,37,9,133292.45,1,1,0,111175.09,0 +3183,15638646,Lucchese,669,France,Female,43,1,160474.59,1,1,1,95963.14,0 +3184,15734161,Nnonso,636,France,Male,43,6,0,2,1,0,43128.95,0 +3185,15631070,Gerasimova,667,Germany,Male,55,9,154393.43,1,1,1,137674.96,1 +3186,15761950,Woronoff,652,Germany,Female,45,9,110827.49,1,1,1,153383.54,1 +3187,15649668,Wilhelm,637,Germany,Female,36,10,145750.45,2,1,1,96660.76,0 +3188,15713912,Nebechukwu,516,Spain,Female,45,8,109044.3,1,0,1,115818.16,0 +3189,15586757,Anenechukwu,801,France,Female,32,4,75170.54,1,1,1,37898.5,0 +3190,15596522,Meredith,692,France,Female,42,2,0,2,1,0,145222.93,0 +3191,15625395,Chinomso,585,France,Female,28,6,105795.9,1,1,1,41219.09,0 +3192,15760570,Stephenson,590,France,Male,32,5,0,2,1,0,59249.83,0 +3193,15566689,Chimaoke,554,Spain,Male,66,8,0,2,1,1,116747.62,0 +3194,15725794,Winters,659,France,Female,49,1,0,1,1,0,116249.72,1 +3195,15673539,Napolitani,690,France,Female,26,3,118097.87,1,1,0,61257.83,0 +3196,15705298,L?,697,Germany,Male,29,0,172693.54,1,0,0,141798.98,0 +3197,15675791,Williams,610,France,Male,36,4,129440.3,2,1,0,102638.35,0 +3198,15747043,Giles,599,Spain,Male,36,4,0,2,0,0,13210.56,0 +3199,15736397,Wang,544,France,Male,23,1,96471.2,1,1,0,35550.97,0 +3200,15678201,Robertson,548,France,Female,46,1,0,1,1,1,104469.06,1 +3201,15720745,Murray,635,Spain,Male,24,4,140197.18,1,1,1,142935.83,0 +3202,15637593,Greco,722,France,Male,20,6,0,2,1,0,195486.28,0 +3203,15598070,Marchesi,564,France,Female,33,4,135946.26,1,1,0,63170,0 +3204,15787550,Chao,719,France,Male,69,3,0,2,1,1,58320.06,0 +3205,15603942,Hawthorn,547,Germany,Male,50,3,81290.02,3,0,1,177747.03,1 +3206,15733973,Bibi,850,France,Female,42,8,0,1,1,0,19632.64,1 +3207,15596761,Hawdon,515,Germany,Male,60,9,113715.36,1,1,0,18424.24,1 +3208,15652400,Moss,667,Spain,Male,56,2,168883.08,1,0,1,18897.78,0 +3209,15717893,Briggs,607,Germany,Male,36,8,143421.74,1,1,0,97879.02,0 +3210,15622585,McIntyre,525,France,Male,26,7,153644.39,1,1,1,63197.88,0 +3211,15733964,Russo,606,Spain,Female,53,1,109330.06,1,1,1,75860.01,0 +3212,15753861,Ballard,686,Germany,Female,27,1,115095.88,2,0,0,78622.46,0 +3213,15747097,Hs?,611,France,Male,35,10,0,1,1,1,23598.23,1 +3214,15594762,Pisani,827,Spain,Male,46,1,183276.32,1,1,1,13460.27,0 +3215,15667417,Tao,572,France,Male,33,9,68193.72,1,1,0,19998.31,0 +3216,15684861,Thomson,726,France,Female,32,8,0,2,0,0,185075.63,0 +3217,15742204,Hsu,579,Germany,Male,31,6,139729.54,1,0,1,135815.38,0 +3218,15623502,Morrison,598,Spain,Female,56,4,98365.33,1,1,1,44251.33,0 +3219,15774872,Joslin,663,France,Male,36,10,0,2,1,0,136349.55,0 +3220,15611191,Scott,505,Germany,Female,37,10,122453.97,2,1,1,52693.99,0 +3221,15674331,Bidwill,576,Germany,Male,30,7,132174.41,2,0,0,93767.03,0 +3222,15619465,Cameron,555,Spain,Female,24,2,0,2,0,1,197866.55,0 +3223,15575247,Cartwright,524,France,Male,30,1,0,2,1,0,126812.85,0 +3224,15695679,Yao,776,Spain,Male,39,2,104349.45,1,0,0,79503.05,0 +3225,15713463,Tate,645,Germany,Female,41,2,138881.04,1,1,0,129936.53,1 +3226,15785170,Neal,850,Germany,Female,32,0,116968.91,1,0,0,175094.62,0 +3227,15796351,Yao,603,Germany,Male,35,1,105346.03,2,1,1,130379.5,0 +3228,15639576,Burns,691,France,Male,26,9,136623.19,1,1,0,153228,0 +3229,15693264,Onyinyechukwuka,583,France,Female,29,10,0,2,1,1,111285.85,0 +3230,15589715,Fulks,584,France,Female,66,5,0,1,1,0,49553.38,1 +3231,15769902,Christie,679,France,Female,33,6,0,2,1,1,98015.85,0 +3232,15587177,Lloyd,646,France,Male,36,6,124445.52,1,1,0,88481.32,0 +3233,15814553,Ball,559,France,Female,34,5,68999.66,2,1,1,66879.27,0 +3234,15601550,Genovesi,595,Spain,Male,36,6,85768.42,1,1,1,24802.77,0 +3235,15664907,Alexander,527,France,Male,47,1,0,1,1,0,21312.16,1 +3236,15612465,Siciliano,684,Spain,Male,34,9,100628,2,1,1,190263.78,0 +3237,15810800,Ositadimma,673,Spain,Female,32,0,0,1,1,1,72873.33,0 +3238,15665760,Kazantsev,802,Spain,Male,38,7,0,2,0,1,57764.65,0 +3239,15588080,Giles,675,France,Male,54,6,0,1,1,0,110273.84,1 +3240,15776844,Hao,762,Spain,Female,19,6,0,2,1,0,55500.17,0 +3241,15717560,Martin,580,France,Male,50,0,125647.36,1,1,0,57541.08,1 +3242,15629739,Hartley,621,Germany,Female,31,8,100375.39,1,1,1,90384.26,0 +3243,15729908,Allan,411,France,Female,36,10,0,1,0,0,120694.35,0 +3244,15716781,Dolgorukova,815,France,Male,24,7,171922.72,1,0,1,178028.96,0 +3245,15646936,Nnamdi,631,Germany,Female,32,2,146810.99,2,1,1,180990.29,0 +3246,15768151,Romano,514,Germany,Female,45,3,109032.23,1,0,1,155407.21,1 +3247,15579212,Chuang,638,France,Male,57,6,0,1,1,0,33676.48,1 +3248,15721835,Owen,791,Spain,Male,25,7,0,1,1,0,89666.28,0 +3249,15800515,Singh,516,France,Male,35,5,128653.59,1,1,0,127558.26,0 +3250,15591279,Nwagugheuzo,734,France,Male,37,3,80387.81,1,0,1,77272.62,0 +3251,15587419,Shipton,611,France,Male,58,8,0,2,0,1,107665.68,1 +3252,15750335,Paterson,850,Germany,Male,43,0,108508.82,3,1,0,184044.8,1 +3253,15699619,Rivas,641,France,Male,31,10,155978.17,1,1,0,91510.71,0 +3254,15606472,Lung,585,France,Female,38,5,0,1,1,1,87363.56,0 +3255,15778368,Allan,552,Germany,Male,50,4,121175.56,1,1,0,117505.07,1 +3256,15671387,Fetherstonhaugh,507,France,Female,29,4,89349.47,2,0,0,180626.68,0 +3257,15573926,Lung,735,Spain,Male,38,7,86131.71,2,0,0,93478.96,0 +3258,15709183,Davidson,707,France,Female,58,3,102346.86,1,1,1,114672.64,0 +3259,15577514,Mai,698,Germany,Female,36,7,121263.62,1,1,1,13387.88,0 +3260,15778830,Dellucci,841,France,Male,31,2,0,2,1,0,173240.52,0 +3261,15768072,Mitchell,688,Spain,Female,33,2,0,1,0,0,27557.18,1 +3262,15768293,Sun,614,France,Male,51,3,0,2,1,1,5552.37,0 +3263,15654456,Napolitano,511,Germany,Male,48,6,149726.08,1,0,0,88307.87,1 +3264,15807525,Bailey,447,France,Male,43,2,0,2,1,0,33879.26,1 +3265,15574372,Hoolan,738,France,Male,35,5,161274.05,2,1,0,181429.87,0 +3266,15671249,Kent,422,France,Female,33,2,0,2,1,0,102655.31,0 +3267,15779744,Chou,537,Spain,Male,30,1,103138.17,1,1,1,96555.42,0 +3268,15624755,Pepper,707,Germany,Female,40,3,109628.44,1,1,0,189366.03,0 +3269,15611430,Abramowitz,690,France,Male,54,5,0,1,1,0,12847.61,1 +3270,15774744,Lord,664,Germany,Male,33,7,97286.16,2,1,0,143433.33,0 +3271,15629885,Wilson,850,France,Female,33,7,118004.26,1,1,0,183983.82,0 +3272,15708791,Abazu,584,Spain,Male,32,9,85534.83,1,0,0,169137.24,0 +3273,15793890,Harriman,728,France,Female,59,4,0,1,1,1,163365.85,1 +3274,15646091,Frankland,560,Spain,Female,43,4,95140.44,2,1,0,123181.44,1 +3275,15596984,Pinto,629,France,Female,31,6,0,1,1,1,16447.6,1 +3276,15800215,Kwemtochukwu,658,France,Male,25,3,0,2,0,1,173948.4,0 +3277,15577806,Chiu,794,Germany,Female,54,1,75900.84,1,1,1,192154.66,0 +3278,15749381,Yu,790,France,Female,41,2,126619.27,1,1,0,198224.38,0 +3279,15683758,Onyekachukwu,640,France,Male,44,7,111833.47,1,1,0,67202.74,0 +3280,15670615,Castiglione,652,Spain,Male,37,7,0,2,1,0,68789.93,0 +3281,15715622,To Rot,583,France,Female,57,3,238387.56,1,0,1,147964.99,1 +3282,15707634,Anenechukwu,775,France,Female,32,2,108698.96,2,1,1,161069.73,0 +3283,15806901,Henderson,584,France,Female,39,2,112687.69,1,1,1,127749.61,0 +3284,15775335,Ellis,635,Germany,Female,48,4,81556.89,2,1,0,191914.37,0 +3285,15724150,Nkemdirim,814,France,Male,48,9,136596.85,1,1,1,185791.9,0 +3286,15627220,Kang,735,Germany,Female,43,9,98807.45,1,0,0,184570.04,1 +3287,15672330,Lear,678,France,Female,31,1,0,2,0,1,130446.65,0 +3288,15668521,Jamieson,693,France,Male,37,1,0,2,1,1,82867.55,0 +3289,15807837,Mazzanti,640,France,Female,30,6,107499.7,1,1,1,187632.22,0 +3290,15592570,Marino,773,Spain,Female,23,8,0,2,1,0,56759.79,0 +3291,15748589,Winter,736,France,Female,30,9,0,2,1,0,34180.33,0 +3292,15635893,T'ien,693,France,Female,28,8,0,2,1,1,158545.25,0 +3293,15757632,Hughes-Jones,496,France,Female,41,1,176024.05,2,1,0,182337.98,0 +3294,15691863,Cody,751,France,Female,39,3,0,2,1,1,84175.34,0 +3295,15706071,Hunt,528,Germany,Male,39,0,127631.62,1,0,1,22197.8,1 +3296,15654296,Estrada,754,Spain,Female,19,9,0,1,1,0,189641.11,0 +3297,15755018,Dickinson,568,Germany,Female,26,10,109819.16,2,1,0,154491.39,0 +3298,15594041,Fanucci,592,Spain,Female,41,2,138734.94,1,1,0,90020.74,0 +3299,15670587,Yang,558,Germany,Male,25,10,111363.1,2,1,0,197264.35,0 +3300,15724527,Forbes,825,France,Male,34,9,0,2,1,1,31933.06,0 +3301,15801904,Heard,677,Germany,Male,28,0,143988,2,1,0,8755.69,1 +3302,15658195,Efremova,653,France,Male,34,5,118838.75,1,1,1,52820.13,0 +3303,15630113,Morphett,593,Spain,Male,35,4,161637.75,1,1,1,20008.46,0 +3304,15784320,Lenhardt,632,France,Female,44,3,133793.89,1,1,1,34607.14,1 +3305,15676513,Burns,601,Germany,Male,35,8,71553.83,1,1,0,177384.45,0 +3306,15574072,Ch'ien,786,France,Female,62,8,0,1,1,1,165702.64,0 +3307,15633854,Sun,654,France,Female,40,3,0,2,1,0,167889.1,0 +3308,15618566,Jamieson,572,France,Female,38,7,0,2,1,1,133122.62,0 +3309,15733014,Nolan,813,France,Female,62,10,64667.95,2,0,1,140454.14,0 +3310,15753343,Barry,523,France,Female,28,2,121164.11,1,1,1,59938.81,0 +3311,15746076,Saunders,506,Spain,Male,50,3,0,2,1,0,12016.79,0 +3312,15608226,McMorran,513,Spain,Male,72,3,98903.06,1,1,1,81251.24,0 +3313,15605684,Phelan,664,France,Female,31,7,104158.84,1,1,0,134169.85,0 +3314,15638988,Fu,684,France,Male,54,6,0,2,1,1,94888.6,0 +3315,15628767,Hotchin,608,Spain,Female,63,3,139529.93,2,1,1,175696.16,1 +3316,15737977,Aksyonov,527,France,Female,25,6,0,2,0,1,96758.58,0 +3317,15758116,Rossi,666,France,Male,53,5,64646.7,1,1,0,128019.48,1 +3318,15575119,Hughes,779,France,Male,71,3,0,2,1,1,146895.36,1 +3319,15625126,Duncan,629,France,Female,40,6,0,2,1,1,139356.3,0 +3320,15567114,McGarry,430,France,Male,35,1,118894.22,1,0,0,2923.61,0 +3321,15672242,Aksenov,712,France,Male,24,2,0,1,0,1,121232.51,0 +3322,15681327,Akhtar,682,France,Male,30,9,0,2,1,1,2053.42,0 +3323,15802585,Pisani,634,France,Female,41,8,68213.99,1,1,1,6382.46,0 +3324,15740630,Pisano,487,Spain,Female,31,1,0,2,1,0,158750.13,0 +3325,15815420,McDaniels,808,Spain,Male,47,8,139196,1,0,1,74028.36,0 +3326,15711468,Tennant,527,France,Female,32,7,0,2,1,1,44099.75,0 +3327,15799626,Donaghy,637,Germany,Male,50,4,126345.55,1,0,1,17323,1 +3328,15659325,Todd,802,Spain,Male,40,5,0,2,1,1,175043.69,0 +3329,15651352,Tobenna,529,France,Female,38,2,0,1,1,0,146388.85,1 +3330,15684925,Vicars,850,France,Female,43,3,0,2,0,0,2465.8,0 +3331,15657439,Chao,738,France,Male,18,4,0,2,1,1,47799.15,0 +3332,15574122,Tien,817,France,Male,34,5,129278.43,1,0,0,165562.84,0 +3333,15720508,Hsing,735,France,Male,31,3,119558.35,1,0,0,72927.68,0 +3334,15599078,Yang,619,Germany,Female,41,5,92467.58,1,1,0,38270.47,0 +3335,15702300,Walker,671,France,Male,27,5,0,2,0,0,120893.07,0 +3336,15660735,T'ang,581,Spain,Female,31,6,0,2,1,0,188377.21,0 +3337,15671390,Chukwukere,690,Spain,Male,36,10,0,2,1,0,55902.93,0 +3338,15647385,Ch'iu,579,Spain,Male,56,4,99340.83,1,0,0,4523.74,1 +3339,15739223,Pai,688,Spain,Female,24,3,0,2,1,1,102195.16,0 +3340,15631305,Franklin,599,Spain,Female,28,4,126833.79,2,1,0,60843.09,1 +3341,15809263,Y?,729,Germany,Male,29,5,109676.52,1,1,1,25548.47,0 +3342,15640866,Peng,718,France,Female,29,3,0,1,0,1,134462.29,0 +3343,15775663,Otitodilichukwu,712,Germany,Male,53,6,134729.99,2,1,1,132702.64,0 +3344,15631800,Pagnotto,474,France,Male,37,3,98431.37,1,0,0,75698.44,0 +3345,15654292,Vessels,565,Germany,Male,33,8,130368.31,2,1,0,105642.43,0 +3346,15648320,Heller,658,France,Female,31,7,123974.96,1,1,0,102153.75,0 +3347,15726747,Donaldson,714,France,Male,63,4,138082.16,1,0,1,166677.54,0 +3348,15694510,Ifeanyichukwu,725,France,Male,45,1,129855.32,1,0,0,24218.65,0 +3349,15572291,Kao,825,France,Male,40,6,132308.22,1,0,0,117122.5,0 +3350,15603465,Dunn,665,Germany,Female,45,5,155447.65,2,1,0,51871.95,1 +3351,15685628,Calabresi,670,Spain,Male,35,2,124268.64,2,0,1,84321.03,0 +3352,15792729,Holland,474,Germany,Female,34,9,176311.36,1,1,0,160213.27,0 +3353,15767414,Calabresi,591,France,Male,40,2,99886.42,2,1,1,88695.19,0 +3354,15568044,Butusov,508,France,Female,31,7,0,2,1,1,6123.15,0 +3355,15751333,Atkinson,695,France,Female,36,2,0,2,0,1,167749.54,0 +3356,15623062,Vasilyeva,660,Germany,Male,24,5,85089.3,1,1,1,71638,0 +3357,15713621,Mollison,687,Germany,Male,41,10,134318.21,2,1,1,198064.52,0 +3358,15670668,Webb,658,Germany,Male,29,5,75395.53,2,0,1,54914.92,0 +3359,15750638,Obiajulu,705,Germany,Female,33,5,116765.7,1,0,0,190659.17,1 +3360,15747878,Aiken,739,Spain,Male,60,4,0,1,1,1,51637.67,0 +3361,15726796,Brabyn,844,France,Male,38,7,111501.66,1,1,1,119333.38,0 +3362,15754952,Su,602,Germany,Female,48,7,76595.08,2,0,0,127095.14,0 +3363,15652192,Traeger,759,France,Female,33,9,160541.36,2,0,0,93541.14,0 +3364,15681924,Ekwueme,747,Germany,Male,38,2,129728.6,1,1,0,89289.54,0 +3365,15763544,Thompson,673,France,Male,47,1,0,2,0,0,108762.16,0 +3366,15764431,Chinwenma,671,Spain,Female,34,5,130929.02,4,1,1,28238.25,1 +3367,15684010,Tuan,640,Germany,Female,74,2,116800.25,1,1,1,34130.43,0 +3368,15648881,Tsai,581,Germany,Male,40,0,101016.53,1,0,1,7926.35,1 +3369,15733303,Liu,630,France,Male,67,5,0,2,1,1,27330.27,0 +3370,15643294,Robinson,703,France,Female,33,8,190566.65,1,1,1,79997.14,0 +3371,15749905,Carr,698,Spain,Female,47,6,0,1,1,0,50213.81,1 +3372,15625175,Palerma,742,Germany,Female,43,6,97067.69,1,0,1,60920.03,1 +3373,15643967,Chineze,652,France,Female,37,4,92208.54,1,0,1,197699.8,1 +3374,15578251,Fang,644,France,Male,37,2,186347.97,2,1,0,92809.73,0 +3375,15772573,Simpson,735,Spain,Male,55,2,103176.62,1,0,1,163516.16,0 +3376,15733234,Moretti,777,France,Female,58,4,0,1,1,1,62449.07,1 +3377,15721582,Hale,644,Germany,Female,40,4,77270.08,2,1,1,115800.1,1 +3378,15628219,Benson,665,Germany,Female,37,3,111911.63,1,1,1,110359.68,1 +3379,15571302,Estep,529,Germany,Male,72,5,94216.05,1,1,1,78695.68,0 +3380,15637178,Mishina,803,Spain,Female,45,7,0,2,1,1,128378.04,0 +3381,15601184,Abramovich,604,Spain,Female,26,3,0,2,1,0,155248.62,0 +3382,15629511,Lavrentiev,738,France,Male,49,6,106770.82,1,1,0,123499.27,0 +3383,15570629,Alexeyeva,655,Germany,Female,72,5,138089.97,2,1,1,99920.41,0 +3384,15665766,T'ang,698,Germany,Male,39,9,133191.19,2,0,1,53289.49,0 +3385,15693732,Kilgour,775,France,Female,66,9,0,2,1,1,67622.34,0 +3386,15765982,Chin,735,France,Male,41,7,74135.85,1,1,1,11783.1,1 +3387,15582016,Fiorentini,766,Spain,Male,41,6,99208.46,2,1,0,62402.38,0 +3388,15798024,Lori,537,Germany,Male,84,8,92242.34,1,1,1,186235.98,0 +3389,15588622,Marchesi,599,Germany,Male,25,7,108380.72,1,1,1,79005.95,0 +3390,15724863,Sheppard,420,Spain,Female,55,4,91893.32,1,1,0,144870.28,1 +3391,15618213,Nnanna,674,France,Female,32,7,85757.93,1,1,1,95481,0 +3392,15780411,Norris,570,France,Female,46,3,0,2,0,0,820.46,0 +3393,15725429,Vincent,623,Germany,Male,33,8,96759.42,1,1,1,174777.98,0 +3394,15600626,Bradley,710,France,Male,30,6,0,2,1,1,8991.17,0 +3395,15668460,Bellucci,466,France,Male,29,6,0,2,1,1,2797.27,0 +3396,15576263,Clements,759,France,Female,22,5,0,1,1,0,22303.17,0 +3397,15720354,Knowles,581,France,Male,71,4,0,2,1,1,197562.08,0 +3398,15691624,Chidiebere,820,France,Male,33,2,132150.26,2,1,0,23067.97,0 +3399,15793196,Kelly,759,France,Male,41,9,0,2,0,1,190294.12,0 +3400,15633352,Okwukwe,628,France,Female,31,6,175443.75,1,1,0,113167.17,1 +3401,15750874,Onyemere,676,France,Male,31,3,78990.15,1,1,1,124777.14,0 +3402,15588923,Murphy,591,France,Female,33,4,113743.37,1,1,0,124625.08,0 +3403,15715745,Elliott,690,France,Female,26,5,157624.84,1,1,1,49599.27,0 +3404,15611800,Loggia,624,France,Female,62,7,125163.62,2,1,1,151411.5,0 +3405,15576928,Walsh,573,France,Female,23,2,0,1,1,0,122964.18,0 +3406,15793693,Mahomed,694,France,Male,60,9,0,1,1,1,57088.97,0 +3407,15581252,Dolgorukova,632,Spain,Female,29,7,80922.75,1,1,0,7820.78,0 +3408,15797760,Bogdanov,632,France,Male,40,3,193354.86,2,1,0,149188.41,0 +3409,15790564,She,832,Germany,Female,40,9,107648.94,2,1,1,134638.97,0 +3410,15593736,Cook,598,Germany,Female,46,7,131769.04,1,0,0,184980.23,1 +3411,15595937,Bruno,430,Germany,Male,36,1,138992.48,2,0,0,122373.42,0 +3412,15815628,Moysey,711,France,Female,37,8,113899.92,1,0,0,80215.2,0 +3413,15782802,Beneventi,582,Germany,Male,26,6,114450.32,1,1,1,14081.64,0 +3414,15627412,Ferri,605,France,Male,39,3,0,2,1,0,199390.45,0 +3415,15734609,Skinner,657,France,Female,37,2,0,2,1,1,7667.48,0 +3416,15710689,Angel,578,Spain,Male,40,6,63609.92,1,0,0,74965.61,1 +3417,15565806,Toosey,532,France,Male,38,9,0,2,0,0,30583.95,0 +3418,15815530,Chin,612,France,Female,42,10,75497.51,1,0,0,149682.78,0 +3419,15632272,Lung,792,France,Female,42,2,0,2,1,0,92664.09,0 +3420,15684103,Mellor,674,France,Female,26,10,0,2,1,1,138423.1,0 +3421,15654519,Hassall,680,France,Male,31,1,0,2,1,1,3148.2,0 +3422,15767722,Richardson,593,France,Female,39,0,117704.73,1,1,0,197933.5,0 +3423,15654346,Poninski,679,Germany,Male,35,1,130463.55,2,1,1,37341.17,0 +3424,15660147,Dore,493,Spain,Male,32,8,46161.18,1,1,1,79577.4,0 +3425,15814998,Bonham,688,Spain,Male,42,5,0,2,0,0,197602.29,0 +3426,15802207,Ibezimako,769,Germany,Male,43,4,110182.54,2,1,1,87537.32,0 +3427,15658668,Hunter,581,Spain,Male,49,10,0,2,0,0,41623.59,0 +3428,15715079,Bold,465,France,Male,41,9,117221.15,1,1,0,168280.95,0 +3429,15570360,Wan,641,France,Female,35,4,0,2,0,0,125986.18,0 +3430,15674678,Bradley,731,Germany,Female,43,9,79120.27,1,0,0,548.52,1 +3431,15780925,Tretyakova,625,France,Male,37,1,177069.24,2,1,1,96088.54,0 +3432,15688193,Graham,468,France,Male,36,3,61636.97,1,0,0,107787.42,0 +3433,15778219,Izmailov,790,France,Male,26,5,0,1,1,0,20510.79,0 +3434,15696514,Calabrese,587,Germany,Female,37,6,104414.03,1,1,0,192026.02,0 +3435,15712303,Valentin,692,France,Male,66,4,159732.02,1,1,1,118188.15,0 +3436,15719090,Osonduagwuike,676,Germany,Female,34,4,89437.03,1,1,1,189540.95,0 +3437,15735632,Williamson,571,France,Male,41,8,0,1,1,1,63736.17,0 +3438,15619436,Pan,700,France,Female,32,3,0,1,0,0,95740.37,0 +3439,15722404,Carpenter,445,France,Female,30,3,0,2,1,1,127939.19,0 +3440,15662063,McIver,746,France,Male,36,7,142400.77,1,1,1,193438.69,0 +3441,15745605,Trevisan,722,France,Female,47,2,88011.4,1,1,1,90655.94,1 +3442,15636658,Rozhkova,596,France,Male,36,2,0,2,1,1,12067.39,0 +3443,15784130,He,850,Germany,Female,30,8,154870.28,1,1,1,54191.38,0 +3444,15606755,Moretti,597,Spain,Female,46,4,0,2,1,0,58667.16,1 +3445,15801699,Fishbourne,436,Spain,Male,43,5,0,2,1,1,35687.43,0 +3446,15784097,Gibson,660,Germany,Male,28,1,118402.25,2,1,0,14288.93,0 +3447,15764654,Zikoranachidimma,649,France,Male,37,9,87374.88,2,1,1,247.36,0 +3448,15612092,Palmer,646,Germany,Male,32,8,105397.8,1,1,0,78111.84,1 +3449,15610903,Chukwueloka,560,Spain,Female,31,5,125341.69,1,1,0,79547.39,0 +3450,15705777,Real,710,Germany,Male,49,10,129164.88,1,1,1,193266.72,0 +3451,15661936,Chikelu,513,France,Male,40,3,141004.46,1,1,0,105028.46,0 +3452,15700864,Fiorentini,607,France,Female,21,0,0,2,1,0,116106.52,0 +3453,15722965,Yefimova,757,France,Male,57,3,89079.41,1,1,1,53179.21,1 +3454,15737521,Ball,619,Germany,Male,40,9,103604.31,2,0,0,140947.05,0 +3455,15814465,Ch'in,612,France,Male,24,1,182705.05,1,1,1,171837.06,0 +3456,15580988,Odell,842,France,Male,29,8,0,2,1,1,123437.05,0 +3457,15789974,Enemuo,713,France,Male,33,6,94598.48,1,0,0,197519.66,1 +3458,15713370,Hunter,657,Spain,Male,36,8,188241.05,2,0,0,183058.51,1 +3459,15748673,Nepean,770,France,Female,37,9,0,2,0,0,22710.72,0 +3460,15754919,Nwebube,773,France,Female,40,10,0,2,0,1,69303.15,0 +3461,15641662,Enticknap,470,Germany,Male,39,5,117469.91,2,0,0,63705.9,0 +3462,15813422,Lu,781,Spain,Male,35,4,80790.74,1,1,0,116429.51,0 +3463,15713596,Ugochukwu,428,France,Female,62,1,107735.93,1,0,1,58381.77,0 +3464,15791216,Mann,600,Germany,Male,43,8,133379.41,1,1,0,177378.66,1 +3465,15689031,Murphy,697,Spain,Female,37,7,168066.87,1,1,0,35450.53,0 +3466,15763704,Docherty,692,Germany,Female,43,2,69014.49,2,0,0,164621.43,0 +3467,15631339,Adams,791,France,Male,28,4,0,1,1,0,174435.48,0 +3468,15771509,Hirst,538,Germany,Female,42,1,98548.62,2,0,1,94047.75,0 +3469,15769586,Horan,820,France,Female,49,1,0,2,1,1,119087.25,0 +3470,15656096,Cumbrae-Stewart,679,Spain,Female,26,3,76554.06,1,1,1,184800.27,0 +3471,15585280,Kinney,649,France,Female,36,2,0,2,0,1,75035.48,0 +3472,15743582,T'ang,632,France,Female,27,3,107375.82,1,1,1,62703.38,0 +3473,15761692,Muir,594,France,Male,40,9,122417.17,2,0,1,190882.69,0 +3474,15627840,Toscano,682,France,Female,42,0,0,1,0,1,91981.85,1 +3475,15778861,Wallace,720,Spain,Male,33,6,97188.62,1,0,0,91881.29,0 +3476,15770554,Fraser,769,France,Male,31,4,61297.05,2,1,1,7118.02,0 +3477,15806956,Iqbal,746,Spain,Male,30,1,112666.67,1,0,0,11710.4,1 +3478,15701908,Nina,623,Spain,Female,40,7,0,1,1,1,25904.12,0 +3479,15736990,Chuang,537,France,Male,28,3,157842.07,1,1,0,86911.49,0 +3480,15743714,Ch'ien,468,France,Male,46,7,91443.75,1,1,0,10958.18,0 +3481,15807993,Bruno,588,Germany,Female,30,0,110148.49,1,1,0,5790.9,1 +3482,15644686,Kennedy,729,Spain,Female,34,9,53299.96,2,1,1,42855.97,0 +3483,15677377,Lawrence,543,Spain,Male,37,3,0,2,1,1,78915.68,0 +3484,15626412,Mort,499,Spain,Male,39,6,0,2,1,1,81409,0 +3485,15643679,Goliwe,784,Germany,Male,28,2,70233.74,2,1,1,179252.73,0 +3486,15728456,Martinez,604,France,Male,33,3,0,1,1,0,42171.13,1 +3487,15630661,Vasilyev,614,Spain,Female,25,10,75212.28,1,1,0,58965.04,0 +3488,15734044,Black,671,France,Female,31,7,41299.03,1,0,1,102681.32,0 +3489,15705001,Napolitani,587,Spain,Female,35,3,83286.56,1,1,0,125553.52,0 +3490,15809817,Ch'en,593,Spain,Male,43,10,0,2,0,0,53478.02,0 +3491,15809137,Sagese,453,France,Male,29,6,0,1,0,0,198376.02,1 +3492,15751593,Fraser,570,Germany,Male,35,6,85668.59,1,1,0,105525.36,0 +3493,15626491,Hughes,655,France,Female,45,7,57327.04,1,0,1,47349,0 +3494,15765461,Giles,632,Spain,Male,47,3,0,2,1,0,178822.32,0 +3495,15568120,Lacross,681,France,Female,37,7,69609.85,1,1,1,72127.83,0 +3496,15787161,Pisani,591,Germany,Male,46,4,129269.27,1,1,0,163504.33,0 +3497,15812324,King,779,France,Male,27,1,0,2,1,1,190623.02,0 +3498,15588944,Maughan,456,France,Female,63,1,165350.61,2,0,0,140758.07,1 +3499,15694253,Palerma,686,France,Female,41,7,152105.57,2,0,1,132374.41,0 +3500,15759566,Tochukwu,617,France,Male,74,10,0,2,1,1,53949.98,0 +3501,15675675,Slate,850,France,Female,32,5,106290.64,1,1,0,121982.73,0 +3502,15802060,Ch'ang,646,Germany,Female,30,10,100548.67,2,0,0,136983.77,0 +3503,15660505,Romani,735,Germany,Male,46,2,106344.95,1,1,0,114371.33,1 +3504,15782630,Genovese,543,France,Male,35,5,137482.19,1,0,0,62389.35,0 +3505,15700710,Chiebuka,490,France,Female,37,3,116465.53,1,0,1,24435.77,0 +3506,15742834,Liao,640,France,Male,45,1,0,1,1,1,10908.33,0 +3507,15806511,Berry,445,Spain,Male,45,10,0,2,0,1,90977.48,0 +3508,15608166,Fallaci,761,France,Male,36,9,127637.92,1,1,1,81062.93,0 +3509,15614230,T'an,426,France,Female,34,3,0,2,1,1,61230.83,0 +3510,15729958,Wilkinson,777,France,Male,37,1,0,1,1,1,126837.72,0 +3511,15800814,Palerma,534,France,Male,35,2,81951.74,2,1,0,115668.53,0 +3512,15674727,Lazarev,777,France,Female,42,5,147531.82,1,1,1,38819.45,0 +3513,15657779,Boylan,806,Spain,Male,18,3,0,2,1,1,86994.54,0 +3514,15801395,Warren,790,France,Female,33,10,135120.72,1,0,0,195204.99,0 +3515,15757911,Trevisani,643,Spain,Female,32,2,0,1,0,0,131301.74,0 +3516,15665340,Trevisano,584,Spain,Female,37,8,0,2,0,1,100835.19,0 +3517,15787151,Liao,638,France,Female,34,7,0,2,1,1,198969.78,0 +3518,15757821,Burgess,771,Spain,Male,18,1,0,2,0,0,41542.95,0 +3519,15600688,Liston,600,France,Female,39,5,0,2,0,0,118272.07,0 +3520,15594878,Thompson,661,Spain,Female,41,5,28082.95,1,1,0,69586.27,1 +3521,15569248,Milanesi,554,France,Female,43,10,0,2,1,0,149629.13,1 +3522,15812706,Mazure,627,Spain,Male,49,4,111087.5,1,0,1,146680.25,0 +3523,15645045,Rudduck,659,France,Female,38,9,0,2,1,1,132809.18,0 +3524,15766746,Darwin,835,France,Male,35,6,127120.07,1,1,0,28707.69,0 +3525,15700383,Uvarova,763,France,Female,35,7,115651.6,2,1,1,104706.29,0 +3526,15632551,Buccho,625,Germany,Male,31,4,77743.01,2,1,0,75335.68,0 +3527,15795129,Gallo,799,France,Female,30,9,0,2,1,0,136827.96,0 +3528,15650545,Tomlinson,849,France,Male,69,7,71996.09,1,1,1,139065.94,0 +3529,15612769,Carr,692,France,Male,28,5,61581.97,1,1,1,70179.91,0 +3530,15710853,Ts'ui,623,France,Female,24,5,0,2,1,0,116160.04,0 +3531,15623712,Coates,453,Spain,Female,42,5,0,3,1,0,83008.49,1 +3532,15653251,Hickey,408,France,Female,84,8,87873.39,1,0,0,188484.52,1 +3533,15755077,Norton,778,Germany,Female,37,0,105617.73,2,1,1,133699.82,1 +3534,15808557,Mancini,695,France,Female,42,5,0,1,0,1,72172.13,1 +3535,15614687,Tien,677,Germany,Female,44,4,148770.61,2,1,1,191057.76,0 +3536,15626882,Stobie,662,Spain,Male,37,5,94901.09,1,1,1,48233.75,0 +3537,15748034,Drakeford,534,France,Male,29,7,174851.9,1,1,1,79178.31,0 +3538,15632324,Pisani,602,France,Male,59,7,0,2,1,1,162347.05,0 +3539,15761023,Murphy,554,Germany,Female,43,2,120847.11,1,1,0,7611.61,1 +3540,15761453,Kovalev,667,France,Male,42,6,0,1,1,0,88890.05,0 +3541,15646726,Crawford,672,France,Male,43,5,0,1,0,0,63833.09,0 +3542,15637169,Maclean,838,Spain,Female,67,4,103267.8,1,1,1,78310.04,0 +3543,15636024,Blackburn,692,Spain,Female,34,4,109699.08,1,1,1,37898.91,0 +3544,15801218,Bermudez,675,France,Male,49,8,135133.39,1,0,1,179521.24,1 +3545,15642655,Savage,731,Spain,Male,33,1,0,1,1,0,130726.96,0 +3546,15690130,Wyatt,468,France,Female,32,8,137649.47,1,0,0,198714.29,0 +3547,15653753,Chiemenam,542,Spain,Male,43,6,113567.94,1,1,0,89543.25,0 +3548,15641359,Shao,662,Spain,Female,35,6,0,2,0,0,2423.9,1 +3549,15776827,Langdon,770,Germany,Male,37,5,141547.26,2,0,1,180326.83,0 +3550,15647725,Napolitano,675,France,Female,61,5,62055.17,3,1,0,166305.16,1 +3551,15648455,Kung,647,Germany,Male,51,4,131156.76,1,1,0,29883.63,0 +3552,15580629,Blackwood,604,France,Male,31,6,134837.58,1,1,0,192029.19,0 +3553,15730161,Marcelo,833,France,Female,39,3,0,2,1,0,1710.89,0 +3554,15626612,Yin,741,Spain,Male,40,4,104784.23,1,1,0,135163.76,1 +3555,15662865,Storey,658,Spain,Male,36,1,0,2,0,1,84927.42,0 +3556,15629094,Fomin,528,France,Female,36,1,156948.41,1,1,1,149912.28,1 +3557,15651823,Nkemjika,590,France,Female,60,6,147751.75,1,1,0,88206.04,1 +3558,15594827,Glasgow,675,France,Male,34,1,124619.33,2,0,1,163667.56,0 +3559,15786392,Chen,765,France,Male,41,4,124182.21,1,0,0,100153.43,0 +3560,15727353,Ch'ang,650,France,Female,64,7,142028.36,1,1,0,32275.09,1 +3561,15733777,Evans,817,France,Male,44,8,0,1,0,0,65501.91,1 +3562,15614302,Crotty,699,Germany,Female,31,10,125837.86,2,1,0,189392.66,0 +3563,15723263,Cocci,495,Germany,Female,34,9,117160.32,1,1,1,116069.24,1 +3564,15687270,Iroawuchi,491,Spain,Female,61,8,0,2,0,1,139861.53,0 +3565,15803121,Chia,847,France,Male,51,5,97565.74,1,0,0,144184.06,1 +3566,15598700,Hysell,676,Spain,Female,30,5,0,2,0,1,157888.5,0 +3567,15741875,Williamson,746,Spain,Female,25,3,104833.79,1,0,0,71911.3,0 +3568,15631709,Ginikanwa,470,Spain,Female,31,2,101675.22,2,1,0,45033.75,0 +3569,15672970,Chigolum,714,Spain,Male,20,3,0,2,0,1,150465.93,0 +3570,15761670,Morley,695,France,Female,50,8,0,1,1,0,126381.6,1 +3571,15706005,Roberts,674,France,Male,46,2,174701.05,1,1,0,90189.72,1 +3572,15790336,Tokareva,664,Germany,Male,36,6,71142.77,2,1,0,122433.09,0 +3573,15754267,Fleming,697,Germany,Male,31,3,108805.42,2,0,1,123825.83,0 +3574,15791988,Chinomso,670,France,Male,68,4,0,2,1,1,11426.7,0 +3575,15683375,Compton,541,France,Female,32,4,0,1,1,1,114951.42,0 +3576,15625151,Wan,640,France,Female,66,9,116037.76,1,0,1,184636.05,0 +3577,15635285,Taylor,647,France,Male,28,8,0,2,1,1,91055.27,0 +3578,15574296,Kambinachi,757,France,Male,23,2,80673.96,2,1,0,93991.65,0 +3579,15711618,Chang,704,Germany,Female,39,1,124640.51,1,1,0,116511.12,1 +3580,15670943,See,778,Germany,Male,31,9,182275.23,2,1,0,190631.23,0 +3581,15634359,Dyer,639,Germany,Female,41,5,98635.77,1,1,0,199970.74,0 +3582,15586629,Campbell,637,France,Male,33,5,0,2,1,0,139947.17,0 +3583,15588461,Cremonesi,686,France,Male,35,4,0,1,1,0,8816.37,0 +3584,15773221,Harris,577,Spain,Male,43,8,79757.21,1,1,0,135650.72,1 +3585,15664227,Threatt,506,Germany,Male,28,8,53053.76,1,0,1,24577.34,0 +3586,15741745,Lane,757,France,Male,28,7,120911.75,2,1,1,131249.46,0 +3587,15652626,Grave,826,France,Male,55,4,115285.85,1,1,0,140126.17,0 +3588,15599410,Stanley,721,France,Male,41,2,0,2,1,0,168219.75,0 +3589,15571958,McIntosh,489,Spain,Male,40,3,221532.8,1,1,0,171867.08,0 +3590,15785406,Watts,446,France,Female,51,4,105056.13,1,0,0,70613.52,0 +3591,15687884,Alekseyeva,677,France,Male,37,3,88363.03,1,0,1,117946.3,0 +3592,15621685,Davies,769,France,Male,29,2,123757.52,2,1,0,84872.66,0 +3593,15628886,Matlock,677,Spain,Male,56,5,123959.97,1,1,1,60590.72,1 +3594,15699325,Fedorova,555,Germany,Female,62,10,114822.64,1,0,1,8444.5,0 +3595,15578369,Chiedozie,652,Germany,Female,37,9,145219.3,1,1,0,159132.83,0 +3596,15654156,Marcelo,722,Germany,Female,32,5,106807.64,1,1,1,76998.69,0 +3597,15707199,Cooper,643,France,Male,36,0,148159.71,1,0,0,55835.66,0 +3598,15671630,McMillan,796,Germany,Female,40,1,99745.95,1,1,0,177524.19,0 +3599,15632079,Hardy,720,Germany,Female,37,8,156282.79,1,1,0,45985.52,0 +3600,15767921,Madukwe,613,France,Male,41,7,0,2,1,0,60297.72,0 +3601,15573599,Adamson,506,France,Female,57,6,0,2,0,1,194421.12,1 +3602,15747208,Watt,608,France,Male,50,6,0,1,1,0,93568.77,1 +3603,15582762,Mazzanti,667,Spain,Male,77,2,0,1,1,1,34702.92,0 +3604,15772528,Mishin,750,France,Female,47,7,121376.15,2,1,0,54473.6,1 +3605,15755798,Feng,610,France,Male,33,4,111582.11,1,0,0,113943.17,0 +3606,15788683,Kang,588,Germany,Female,34,10,129417.82,1,1,0,153727.32,0 +3607,15616922,Kelly,479,France,Female,26,1,0,2,1,1,19116.97,0 +3608,15771855,Yu,682,France,Male,37,5,0,2,0,1,112554.68,0 +3609,15601873,Bull,677,France,Female,36,7,0,1,1,0,47318.75,0 +3610,15657868,Serra,850,Germany,Male,40,6,94607.08,1,1,0,36690.49,0 +3611,15711716,Ferguson,580,France,Female,56,1,131368.3,1,1,0,106918.67,1 +3612,15734246,She,746,France,Female,21,8,166883.07,2,0,1,194563.65,0 +3613,15792151,Hamilton,635,Spain,Female,37,3,0,2,1,0,91086.73,0 +3614,15770159,Nnanna,664,Germany,Male,25,6,172812.72,2,1,1,108008.65,0 +3615,15747649,Summerville,558,Germany,Female,36,0,126606.63,2,1,1,172363.52,0 +3616,15639357,Allan,415,France,Male,46,9,134950.19,3,0,0,178587.36,1 +3617,15738907,Tobenna,798,France,Female,60,6,96956.1,1,1,0,31907.44,1 +3618,15663446,Volkova,792,Germany,Female,29,4,107601.79,1,1,0,18922.18,1 +3619,15750867,Nucci,489,Germany,Female,46,8,92060.06,1,1,0,147222.95,1 +3620,15715939,Wright,730,France,Male,33,0,0,2,1,0,1474.79,0 +3621,15763806,Astorga,773,France,Male,41,4,0,2,1,1,24924.92,0 +3622,15637993,Pokrovsky,711,France,Male,36,9,137688.71,1,1,1,46884.1,0 +3623,15720338,Mazzanti,592,Spain,Male,55,8,85845.43,2,1,1,128918.42,0 +3624,15627162,Blesing,695,Germany,Male,27,6,125552.96,1,1,0,105291.26,0 +3625,15596710,Ku,640,France,Female,33,1,167298.42,1,0,1,145381.65,0 +3626,15781678,Pisani,470,Spain,Male,31,4,55732.92,2,1,1,103792.53,0 +3627,15634968,Hsueh,789,Germany,Female,37,6,110689.07,1,1,1,71121.04,1 +3628,15609475,Ricci,604,Spain,Female,39,7,98544.11,1,1,1,52327.57,0 +3629,15573319,Azubuike,493,Germany,Female,35,8,178317.6,1,0,0,197428.64,0 +3630,15738291,Nevzorova,671,France,Female,48,8,115713.84,2,0,0,83210.84,0 +3631,15782456,Odili,656,France,Male,46,9,143267.14,2,0,0,193099.43,0 +3632,15794841,Kung,739,Spain,Male,19,5,89750.21,1,1,0,193008.52,0 +3633,15684696,Lei,560,Spain,Female,26,3,116576.45,1,1,0,157567.37,0 +3634,15629846,Sheehan,827,Germany,Female,47,8,143001.5,2,1,0,108977.5,0 +3635,15674442,Kung,681,France,Male,23,7,157761.56,1,0,0,147759.84,0 +3636,15571689,Kelechi,740,France,Female,37,5,0,2,1,1,27528.4,0 +3637,15730469,Anenechi,663,Spain,Male,31,4,103430.11,2,0,1,36479.27,0 +3638,15809320,McElhone,845,Spain,Female,52,0,0,1,1,0,31726.76,1 +3639,15684367,Chigbogu,555,Spain,Male,27,5,0,2,0,0,96398.51,0 +3640,15793049,Atkins,680,Germany,Female,48,8,115115.38,1,1,0,139558.6,1 +3641,15603665,Colombo,638,Germany,Female,39,0,122501.28,2,1,1,95007.8,0 +3642,15613623,Tilley,640,Spain,Male,62,3,0,1,1,1,101663.47,0 +3643,15569572,Sopuluchi,778,France,Male,42,6,0,2,1,1,106197.44,0 +3644,15698791,Udinesi,679,France,Male,45,3,146758.24,1,1,0,48466.89,0 +3645,15626233,Onyekachi,593,France,Female,32,3,0,2,1,1,151978.36,0 +3646,15607263,McCartney,788,France,Male,55,3,0,1,0,1,13288.46,1 +3647,15610900,Thompson,770,France,Female,70,9,110738.89,1,1,0,22666.77,1 +3648,15624775,Onyeoruru,729,France,Male,67,2,94203.8,1,0,1,102391.06,0 +3649,15691703,Shih,545,France,Male,47,8,105792.49,1,0,1,67830.2,1 +3650,15745355,Golibe,597,France,Male,41,4,153198.23,1,1,1,92090.36,0 +3651,15724955,Lucchesi,537,France,Male,38,3,0,2,0,0,141023.01,0 +3652,15628999,Townsend,732,France,Male,79,10,61811.23,1,1,1,104222.8,0 +3653,15654341,Chao,542,France,Male,34,8,101116.06,1,1,0,196395.05,0 +3654,15744240,Shen,688,Germany,Female,46,0,74458.25,1,0,1,6866.31,0 +3655,15632365,Booth,542,Germany,Male,33,8,142871.27,2,0,0,77737.86,0 +3656,15729689,Chan,754,Germany,Male,35,6,98585.94,2,0,1,106116.84,0 +3657,15759284,Yeh,750,France,Female,37,6,0,1,1,1,117948,1 +3658,15602124,Badgery,731,France,Male,30,7,0,2,1,1,184581.68,0 +3659,15661903,Hsia,699,France,Female,43,3,80764.03,1,1,0,199378.58,1 +3660,15664668,Zarate,534,France,Female,42,9,144801.97,1,0,1,12483.39,1 +3661,15736431,Congreve,494,Spain,Male,27,2,0,2,1,0,22404.64,0 +3662,15748639,Hayslett,497,Germany,Male,35,7,110053.62,2,1,1,92887.06,0 +3663,15628123,Robinson,632,France,Female,28,5,118890.81,1,0,1,145157.97,0 +3664,15602731,Wong,724,France,Male,31,5,0,1,1,0,134889.95,1 +3665,15794137,Nevzorova,751,Germany,Female,37,0,151218.98,1,1,1,109309.29,0 +3666,15748696,Page,733,France,Male,42,9,150507.21,1,0,1,169964.12,0 +3667,15725068,Quinn,701,Spain,Female,21,9,0,2,1,1,26327.42,0 +3668,15807340,O'Donnell,525,Germany,Male,33,4,131023.76,2,0,0,55072.93,0 +3669,15586133,Pisano,666,Germany,Female,44,2,122314.5,1,0,0,68574.88,1 +3670,15576185,Sinclair,653,France,Male,29,2,0,2,1,1,41671.81,0 +3671,15660809,Loving,850,France,Male,28,4,0,2,1,1,12409.01,0 +3672,15616666,Artemova,646,Germany,Female,52,6,111739.4,2,0,1,68367.18,0 +3673,15706904,Robertson,750,France,Male,43,6,113882.31,1,1,1,74564.41,0 +3674,15606915,Genovese,764,France,Male,24,7,98148.61,1,1,0,26843.76,0 +3675,15749693,Ugonnatubelum,658,France,Female,32,9,0,2,1,0,156774.75,0 +3676,15791743,Corbett,727,France,Male,32,1,59271.82,1,1,1,46019.43,0 +3677,15796480,Reilly,687,France,Female,31,2,0,2,0,1,145411.39,0 +3678,15790442,Wright,631,Spain,Male,33,2,0,2,1,1,158268.84,0 +3679,15609458,Vincent,797,France,Male,30,10,69413.44,1,1,1,74637.57,0 +3680,15593897,Carr,650,Spain,Male,25,7,160599.06,2,1,1,28391.52,0 +3681,15604576,Eiland,850,Spain,Male,22,3,0,1,1,1,144385.54,0 +3682,15666270,Omeokachie,676,France,Female,40,2,147803.48,1,1,0,95181.06,1 +3683,15572626,Mackenzie,620,Spain,Male,44,8,0,2,1,1,15627.51,0 +3684,15727197,Pinto,576,France,Female,52,9,170228.59,2,0,0,148477.57,1 +3685,15714006,Gardener,482,France,Female,35,2,133111.73,1,0,1,79957.95,0 +3686,15642137,Fang,695,Spain,Female,39,5,0,2,0,0,102763.69,0 +3687,15665327,Cattaneo,706,France,Male,18,2,176139.5,2,1,0,129654.22,0 +3688,15626806,Labrador,668,France,Female,32,2,0,2,1,1,40652.33,0 +3689,15662578,Dettmann,679,Germany,Male,35,1,110245.13,1,1,1,178291.09,0 +3690,15790829,Gibson,703,France,Female,45,5,0,2,1,0,131906.44,0 +3691,15654959,Hope,670,Spain,Male,67,6,158719.57,1,1,1,118607.4,0 +3692,15760244,Ives,590,France,Female,76,5,160979.68,1,0,1,13848.58,0 +3693,15715394,Greece,613,Spain,Male,35,4,123557.65,2,0,1,170903.4,0 +3694,15722246,Omeokachie,742,France,Female,60,4,0,1,1,1,13161.66,1 +3695,15609704,Mao,608,France,Female,33,4,0,1,1,0,79304.38,1 +3696,15757628,Savage,571,France,Male,40,10,112896.86,1,1,1,121402.53,0 +3697,15633586,Brierly,595,France,Female,39,7,120962.13,1,0,0,23305.01,0 +3698,15565796,Docherty,745,Germany,Male,48,10,96048.55,1,1,0,74510.65,0 +3699,15717935,McDonald,589,France,Female,21,3,0,2,0,1,55601.44,0 +3700,15577700,Rapuokwu,749,France,Male,37,10,185063.7,2,1,1,134526.87,0 +3701,15747345,Bergamaschi,678,France,Female,22,6,118064.93,2,1,1,195424.01,0 +3702,15678317,Manfrin,603,France,Male,46,2,0,2,1,1,59563.49,0 +3703,15698335,Bergamaschi,504,France,Female,73,8,0,1,1,1,34595.58,0 +3704,15768451,MacDonald,739,Germany,Male,40,5,149131.03,3,1,1,60036.99,1 +3705,15753213,Lees,604,France,Female,34,7,0,2,1,0,193021.49,0 +3706,15769645,Senior,612,France,Female,35,3,0,1,1,1,48108.72,0 +3707,15657565,Nwokezuike,629,Spain,Female,44,6,125512.98,2,0,0,79082.76,0 +3708,15620323,Ekwueme,652,Spain,Female,42,3,83492.07,2,1,0,37914.12,0 +3709,15679983,Garmon,565,France,Male,34,7,0,1,0,0,74593.84,0 +3710,15812616,Enyinnaya,707,France,Female,49,10,0,1,1,0,82967.97,1 +3711,15601796,Chizuoke,645,France,Male,30,1,125739.26,1,1,1,193441.23,0 +3712,15729489,Hyde,762,Germany,Female,34,8,98592.88,1,0,1,191790.29,1 +3713,15613216,Cameron,639,Spain,Female,39,1,141789.15,1,1,0,92455.96,0 +3714,15657937,Lord,709,Germany,Male,22,0,112949.71,1,0,0,155231.55,0 +3715,15815428,Biryukova,823,France,Male,34,3,105057.33,1,1,0,9217.92,0 +3716,15640409,Carpenter,817,Germany,Female,46,0,89087.89,1,0,1,87941.85,1 +3717,15699492,Lorenzo,665,Germany,Female,27,2,147435.96,1,0,0,187508.06,0 +3718,15623536,Madukwe,646,Germany,Male,39,0,154439.86,1,1,0,171519.06,0 +3719,15707551,Hutcheon,568,France,Male,30,8,73054.37,2,1,1,27012,0 +3720,15577999,Sleeman,850,France,Female,62,1,124678.35,1,1,0,70916,1 +3721,15788775,Milne,473,Germany,Male,40,8,152576.25,2,1,0,73073.68,0 +3722,15758362,Williamson,731,France,Female,41,9,152243.57,1,1,1,88783.59,0 +3723,15807961,Bruno,619,France,Male,25,4,0,1,1,0,145524.36,0 +3724,15710978,Palerma,715,Germany,Male,42,2,88120.97,2,1,1,21333.22,0 +3725,15703541,Wang,772,Germany,Female,51,9,143930.92,1,0,1,46675.51,1 +3726,15626474,Onyemere,686,France,Female,31,1,0,2,1,0,4802.25,0 +3727,15608344,Dawson,749,Germany,Female,29,7,137059.05,3,1,0,102975.72,1 +3728,15768367,Nebechukwu,781,France,Female,27,7,186558.55,1,1,1,175071.29,1 +3729,15806210,Bateman,675,Spain,Male,66,5,115654.47,2,1,1,131970.86,0 +3730,15697702,Lord,730,Spain,Male,29,2,0,2,1,0,14174.09,0 +3731,15689152,Loggia,683,Spain,Male,38,3,126152.84,1,0,0,15378.75,0 +3732,15568573,Graham,554,Germany,Female,51,7,105701.91,1,0,1,179797.79,1 +3733,15689598,Dean,722,France,Male,46,6,0,1,1,1,93917.68,1 +3734,15713374,Jarvis,689,Germany,Male,67,9,157094.78,1,1,1,99490.01,0 +3735,15679733,Haugh,796,Germany,Male,40,2,113228.38,2,1,1,46415.09,0 +3736,15759274,Micklem,447,France,Female,32,10,0,1,1,1,151815.76,0 +3737,15607748,Bennett,498,Germany,Male,37,8,108432.88,2,1,1,14865.05,0 +3738,15607577,Roberts,663,Spain,Male,27,8,0,1,1,1,188007.99,0 +3739,15813697,Onyekaozulu,498,Germany,Female,44,2,120702.67,2,1,1,98175.74,0 +3740,15801125,Kegley,627,France,Female,32,1,0,1,1,0,106851.7,0 +3741,15777855,Manna,649,France,Male,45,7,0,2,0,1,75204.21,0 +3742,15635396,Thompson,738,Germany,Female,29,9,139106.19,1,1,0,141872.05,1 +3743,15698031,Romano,587,Germany,Female,39,6,101851.8,2,1,0,7103.71,0 +3744,15678944,Brown,655,Germany,Female,32,6,130935.56,1,1,0,9241.83,1 +3745,15718507,Su,647,Germany,Male,37,3,116509.99,1,1,1,149517.71,1 +3746,15808334,Mackay,776,Germany,Female,37,1,93124.04,2,1,1,196079.32,0 +3747,15804709,Watt,688,Germany,Male,35,5,111578.18,1,0,0,166165.93,1 +3748,15645835,Milani,605,France,Male,32,9,0,2,1,1,55724.24,0 +3749,15738166,Hsu,596,France,Female,39,10,86546.29,1,0,1,131768.98,0 +3750,15675360,Valenzuela,427,France,Male,33,8,0,1,1,1,13858.95,0 +3751,15793042,Sung,629,France,Male,39,2,129669.32,2,1,0,82774.07,0 +3752,15630106,Lo,496,Spain,Male,29,2,0,2,1,0,55389.59,0 +3753,15810385,Giordano,717,Spain,Female,36,2,164557.95,1,0,1,82336.73,0 +3754,15578211,Connolly,777,France,Male,23,6,0,2,1,1,163225.48,0 +3755,15572792,Bellucci,535,Spain,Male,35,8,118989.92,1,1,1,135536.72,0 +3756,15620030,Jamieson,744,France,Male,29,1,0,1,0,0,82422.97,0 +3757,15783541,Fomina,755,France,Male,31,5,0,2,0,1,194660.78,0 +3758,15679284,Aksenov,593,Spain,Female,45,6,79259.75,1,1,0,55347.28,0 +3759,15582910,Turnbull,514,France,Male,38,4,112230.38,1,1,0,16717.11,1 +3760,15688337,Dixon,721,France,Male,40,9,118129.87,1,1,1,160277.65,0 +3761,15734970,White,835,Spain,Male,38,7,86824.09,1,0,0,175905.97,0 +3762,15759140,Long,682,France,Female,64,10,128306.7,1,0,1,66040.83,0 +3763,15643042,Han,590,Germany,Female,40,2,117641.43,2,0,0,92198.05,0 +3764,15773868,Belov,653,Germany,Female,37,3,125734.2,2,1,0,134625.09,1 +3765,15615820,MacDonald,837,France,Male,49,8,103302.37,1,1,1,50974.57,0 +3766,15730273,Parsons,841,France,Male,27,8,0,1,1,0,171922.72,0 +3767,15724890,Cross,584,Spain,Male,36,4,82696.09,2,0,0,83058.14,0 +3768,15765952,Milanesi,769,France,Male,29,4,145471.37,1,1,0,188382.77,0 +3769,15685920,Lombardo,599,Spain,Male,34,2,101506.66,1,0,0,198030.24,0 +3770,15663263,Collins,698,France,Male,47,5,156265.31,2,0,0,1055.66,0 +3771,15568953,Alexeieva,477,France,Male,27,1,128554.98,1,1,1,133173.19,0 +3772,15643361,Cullen,477,Germany,Male,34,8,139959.55,2,1,1,189875.83,0 +3773,15699486,Johnson,745,Spain,Male,34,7,132944.53,1,1,1,31802.92,0 +3774,15747854,Rudd,749,France,Female,35,3,0,3,1,1,132649.85,0 +3775,15691785,Findlay,850,France,Male,61,1,0,1,1,0,53067.83,1 +3776,15709004,Mai,528,Germany,Male,22,5,93547.23,2,0,1,961.57,0 +3777,15652218,Morrison,750,France,Male,33,2,152302.72,1,1,0,71333.44,0 +3778,15697127,Monaldo,543,France,Female,31,2,147674.26,1,1,1,16658.76,0 +3779,15658486,Gidney,579,Spain,Female,59,3,148021.12,1,1,1,74878.22,0 +3780,15694160,Sagese,624,France,Male,37,0,0,2,0,0,112104.55,0 +3781,15685290,Wall,595,Germany,Male,46,5,142360.62,2,1,0,48421.4,1 +3782,15701042,Dalton,596,Germany,Female,27,2,151027.56,1,1,0,170320.58,0 +3783,15680449,Hsing,431,Germany,Female,44,2,138843.7,1,1,0,37688.31,1 +3784,15599860,Warner,647,Spain,Female,26,8,109958.15,1,1,1,136592.24,1 +3785,15723169,Williams,640,France,Female,31,9,138857.59,1,1,0,48640.77,0 +3786,15803842,Dunn,752,Germany,Female,45,3,105426.5,2,0,1,89773.45,0 +3787,15728224,Kerr,710,Germany,Female,41,9,149155.53,2,1,0,42131.26,1 +3788,15644174,Marchesi,638,Germany,Male,27,4,135096.05,1,1,1,186523.72,1 +3789,15707110,Endrizzi,660,Germany,Male,28,2,170890.05,2,1,0,41758.9,0 +3790,15765415,King,609,Spain,Female,45,4,89122.3,1,1,1,199256.98,0 +3791,15756751,Griffiths,596,Spain,Female,54,0,78126.28,1,1,1,153482.91,1 +3792,15795151,Hartzler,705,France,Female,38,3,123894.43,1,1,0,21177.1,0 +3793,15632859,Chukwudi,444,France,Male,36,7,0,2,0,1,138743.86,0 +3794,15584037,Denisov,727,Germany,Male,58,5,106913.43,1,1,0,25881,1 +3795,15621409,Endrizzi,496,France,Male,32,4,127845.83,1,1,0,66469.2,0 +3796,15581102,Baresi,554,France,Female,22,8,0,2,0,1,142670.61,0 +3797,15578096,Nnachetam,537,France,Male,26,7,106397.75,1,0,0,103563.23,0 +3798,15669887,Lambert,839,France,Female,51,3,0,1,1,1,69101.23,1 +3799,15621834,Game,700,Spain,Female,43,0,0,2,1,0,59475.35,0 +3800,15655341,Chinagorom,458,Spain,Female,35,5,166492.48,1,1,0,135287.74,0 +3801,15685314,Noble,850,France,Female,28,2,0,2,1,1,38773.74,0 +3802,15653997,Haynes,699,Spain,Male,31,6,114493.68,1,0,0,138396.32,0 +3803,15629551,Cattaneo,615,Germany,Female,44,9,126104.98,2,0,1,110718.02,0 +3804,15651264,Yobanna,850,Germany,Male,51,4,124425.99,1,0,0,118545.49,1 +3805,15760825,Fraser,604,France,Female,40,1,0,2,1,0,123207.17,0 +3806,15597394,Rhodes,668,Spain,Male,34,0,0,1,0,0,99984.86,0 +3807,15740383,Jimenez,594,Spain,Female,38,10,0,2,1,0,58332.91,0 +3808,15670562,Pharr,470,France,Male,30,3,101140.76,1,1,1,50906.65,0 +3809,15698117,Jerger,701,Germany,Male,41,0,150844.94,1,0,1,127623.36,0 +3810,15694805,McIntyre,664,Spain,Male,35,1,115024.5,1,0,1,169665.79,0 +3811,15746802,Onio,477,France,Female,30,6,131286.46,1,1,0,194144.45,0 +3812,15589428,Tomlinson,756,France,Female,42,9,0,2,1,0,35673.42,0 +3813,15790267,Onuoha,625,France,Female,40,7,141267.67,1,0,1,177397.49,0 +3814,15665402,Panicucci,703,Spain,Male,73,5,137761.55,1,1,1,159677.46,0 +3815,15642093,Piccio,646,France,Male,30,7,0,2,1,0,153566.97,0 +3816,15666181,Ramsden,650,France,Male,33,0,98064.97,1,1,0,52411.99,0 +3817,15602554,Vorobyova,664,France,Female,31,9,114519.57,2,0,1,79222.02,0 +3818,15724251,Todd,682,Germany,Female,29,6,101012.77,1,0,0,32589.89,1 +3819,15740147,Cremonesi,725,France,Female,44,10,0,1,0,1,93777.61,0 +3820,15718289,Bradley,553,Germany,Male,46,3,82291.1,1,1,0,112549.99,1 +3821,15763148,Stanley,576,France,Male,39,9,84719.98,1,0,0,191063.36,0 +3822,15685245,Jowett,608,Spain,Female,56,5,0,2,0,1,153810.41,0 +3823,15626985,Yefremova,850,France,Female,39,0,104386.53,1,1,0,105886.77,0 +3824,15585823,Wilson,627,France,Male,31,8,128131.73,1,1,0,96131.47,0 +3825,15728167,Abramovich,667,France,Male,44,2,122806.95,1,0,0,15120.86,0 +3826,15762928,Venables,548,Spain,Male,44,8,0,1,1,0,16989.77,0 +3827,15751774,Monnier,774,France,Male,76,4,112510.89,1,1,1,143133.18,0 +3828,15654733,Hsieh,794,Germany,Male,57,3,117056.46,1,1,0,93336.93,1 +3829,15809777,Gadsden,497,Germany,Female,55,7,131778.66,1,1,1,9972.64,0 +3830,15744200,Ni,587,France,Female,36,1,70784.27,1,1,0,30579.82,0 +3831,15720713,Chibueze,850,France,Female,29,10,0,2,1,1,199775.67,0 +3832,15695356,Chinwemma,722,France,Male,46,5,0,2,1,0,179908.71,0 +3833,15653315,Kang,555,Spain,Female,35,1,0,2,1,0,101667,0 +3834,15604792,Kuo,609,Germany,Male,38,6,140752.06,2,0,1,171430.16,0 +3835,15704819,Ositadimma,734,Spain,Female,39,6,92126.26,2,0,0,112973.34,0 +3836,15670859,Smith,718,Germany,Female,39,7,93148.74,2,1,1,190746.38,0 +3837,15602797,Okwudilichukwu,645,Spain,Female,49,5,110132.55,3,0,1,187689.91,1 +3838,15662533,Porter,598,Spain,Female,23,6,0,2,1,0,153229.19,0 +3839,15778154,Kung,628,Germany,Male,50,4,122227.71,1,0,1,14217.77,1 +3840,15806230,Trevisano,629,Germany,Male,40,2,121647.54,2,1,1,64849.74,1 +3841,15662884,Naylor,739,Germany,Male,58,1,110597.76,1,0,1,160122.66,1 +3842,15750778,Ponomarev,653,France,Female,60,2,120731.39,4,1,1,138160.11,1 +3843,15717185,Udinese,711,France,Male,28,8,0,2,1,1,64286.39,0 +3844,15677804,Aliyeva,783,Spain,Male,38,1,0,3,1,1,80178.54,1 +3845,15568915,Bailey,681,France,Male,38,6,153722.47,1,1,0,101319.76,0 +3846,15736495,Jackson,712,France,Male,34,8,114088.32,1,1,0,92794.61,0 +3847,15737354,Yin,554,France,Female,48,7,0,2,1,1,63708.07,0 +3848,15667889,Akobundu,611,France,Female,37,6,0,2,1,0,110782.88,0 +3849,15577831,Byrne,560,Germany,Male,41,4,152532.3,1,0,0,10779.69,0 +3850,15729836,Robinson,646,Spain,Male,32,1,0,2,1,0,183289.22,0 +3851,15775293,Stephenson,680,France,Male,34,3,143292.95,1,1,0,66526.01,0 +3852,15697597,Chiemenam,631,France,Male,26,1,149144.61,1,0,1,123697.95,0 +3853,15639669,Forbes,746,France,Male,36,9,127157.04,1,1,1,155700.15,0 +3854,15631392,Douglas,654,Germany,Male,43,9,84673.17,2,0,1,82081.35,0 +3855,15580935,Okechukwu,687,Germany,Male,33,9,135962.4,2,1,0,121747.96,0 +3856,15590344,Russell,708,Germany,Male,32,3,151691.44,2,1,1,172810.51,0 +3857,15653306,Ermakova,679,Germany,Female,32,0,88335.05,1,0,0,159584.81,0 +3858,15805025,Oster,636,France,Female,45,7,139859.23,1,1,1,108402.54,0 +3859,15658449,Chizoba,695,France,Male,45,9,43134.65,1,0,1,77330.35,0 +3860,15694450,Bianchi,677,France,Male,42,5,99580.13,1,1,0,21007.96,0 +3861,15605666,Peyser,720,France,Female,34,6,110717.38,1,1,1,9398.45,0 +3862,15615126,Cocci,780,France,Female,37,3,0,2,0,0,182156.81,1 +3863,15726588,Seleznev,653,Spain,Female,36,3,0,2,0,0,110525.6,0 +3864,15645095,Huang,674,France,Female,28,3,0,1,1,0,51536.99,0 +3865,15808960,Alleyne,620,Germany,Male,40,5,108197.11,2,1,0,49722.34,0 +3866,15729435,McKenzie,623,France,Male,40,6,0,2,1,1,66119.07,0 +3867,15656840,Zikoranachukwudimma,547,France,Female,29,6,104450.86,1,1,1,37160.28,0 +3868,15659149,King,530,France,Male,39,2,0,2,1,0,197923.05,0 +3869,15585490,Nkemdilim,746,France,Female,34,4,0,1,0,1,65166.6,0 +3870,15674929,Anderson,512,France,Female,31,7,0,2,0,0,49326.07,0 +3871,15746341,Ejikemeifeuwa,630,France,Male,40,8,0,2,1,1,42495.81,0 +3872,15662091,Adams,570,Spain,Male,21,7,116099.82,1,1,1,148087.62,0 +3873,15620123,Christie,605,France,Male,39,6,111169.91,1,0,0,9641.4,0 +3874,15616240,Yeh,530,Spain,Male,37,4,0,2,1,1,164844.37,0 +3875,15624186,McGregor,813,Germany,Female,25,5,123616.43,1,0,1,132959.33,0 +3876,15605036,Pisano,704,Spain,Female,37,9,155619.58,1,1,1,135088.58,0 +3877,15805151,Ginikanwa,565,Germany,Male,31,2,89558.39,2,1,1,4441.54,0 +3878,15753847,Hawkins,645,Spain,Male,45,4,0,1,0,1,174916.85,1 +3879,15653222,Otutodilichukwu,526,Germany,Female,32,6,131938.92,2,1,1,1795.93,0 +3880,15757541,Rickard,778,France,Female,33,9,151772.63,2,0,0,180249.94,1 +3881,15726945,Andreev,677,France,Female,72,8,0,2,1,1,153604.44,0 +3882,15794276,Steele,588,France,Female,64,3,0,1,1,1,189703.65,0 +3883,15568328,Black,488,France,Female,22,6,0,2,1,1,66393.89,0 +3884,15604355,Shand,519,France,Male,39,1,97700.02,1,1,1,30709.03,0 +3885,15735788,Chiagoziem,709,France,Male,31,6,0,2,1,1,71009.84,0 +3886,15618255,Fedorov,642,Germany,Female,56,6,103244.86,2,1,0,143049.72,1 +3887,15720941,Tien,710,Germany,Male,34,8,147833.3,2,0,1,1561.58,0 +3888,15769110,Stehle,653,France,Female,46,5,0,2,1,0,49707.85,0 +3889,15576094,Sung,743,France,Male,71,0,0,2,0,1,29837.65,0 +3890,15756150,Alexander,418,France,Female,39,2,0,2,0,0,9041.71,0 +3891,15719579,McIntosh,670,Germany,Female,33,9,84521.48,2,0,1,198017.05,0 +3892,15748854,Sung,723,Germany,Female,28,5,91938.31,1,1,0,143481.85,0 +3893,15612455,Yao,549,Germany,Male,45,6,124240.93,1,1,1,146372.51,0 +3894,15664802,Chinweuba,543,France,Female,42,5,0,2,0,0,101905.34,0 +3895,15735687,Chinweuba,595,Spain,Male,37,2,157084.99,1,1,0,134767.13,0 +3896,15664734,T'ao,673,Germany,Female,25,3,108244.82,2,1,1,103573.96,0 +3897,15767894,Ch'ien,741,France,Female,21,9,0,2,0,1,139259.54,0 +3898,15666884,Su,508,Germany,Female,41,5,82161.7,2,1,0,187776.49,0 +3899,15750156,Yu,662,Germany,Male,59,2,104568.41,1,1,0,8059.44,1 +3900,15751120,Loyau,752,France,Female,36,2,119912.46,1,1,0,124354.92,0 +3901,15575748,Conti,809,France,Male,36,9,68881.59,2,0,1,109135.11,0 +3902,15714610,Alexeeva,575,Spain,Male,30,2,0,2,1,1,82222.86,0 +3903,15720305,Power,591,Spain,Female,40,1,86376.29,1,0,1,136767.16,1 +3904,15678129,Hill,643,Spain,Female,45,9,150840.03,2,1,0,155516.35,0 +3905,15566633,Freeman,698,Germany,Male,55,8,155059.1,2,1,1,144584.29,0 +3906,15680436,Hsing,496,France,Female,29,4,0,2,1,0,164806.89,0 +3907,15674343,Esposito,597,France,Male,44,8,78128.13,2,0,1,109153.04,0 +3908,15658890,Belonwu,603,Germany,Male,46,4,98899.76,2,1,1,86190.34,0 +3909,15599004,Tsao,655,Spain,Male,37,1,0,1,1,1,106040.97,0 +3910,15726487,P'eng,431,France,Male,63,6,160982.89,1,1,1,168008.17,0 +3911,15698716,Baker,620,France,Female,70,3,87926.24,2,1,0,33350.26,1 +3912,15710527,Matthews,782,France,Female,35,4,0,1,1,1,119565.34,0 +3913,15655590,Garcia,581,Spain,Male,46,2,79385.21,2,0,0,188492.82,0 +3914,15732266,Field,553,Germany,Male,53,5,127997.83,1,1,0,165378.66,1 +3915,15669326,Gordon,658,France,Male,44,2,168396.34,1,1,1,14178.73,0 +3916,15672246,Jefferies,686,Germany,Male,43,2,134896.03,1,1,1,97847.05,0 +3917,15620276,Palermo,539,Spain,Male,36,6,0,3,1,1,118959.64,0 +3918,15640258,Chou,685,France,Female,50,6,94238.75,2,1,1,50664.07,1 +3919,15740283,Ewing,850,France,Male,29,1,0,2,0,0,152996.89,0 +3920,15759717,Mazzi,763,Spain,Female,39,7,0,2,1,0,19458.75,0 +3921,15620268,Thomson,634,Germany,Male,43,3,212696.32,1,1,0,115268.86,0 +3922,15743871,Nkemdirim,567,France,Male,59,3,0,2,1,0,25843.7,1 +3923,15614491,Lockyer,539,France,Male,39,3,139153.68,2,1,0,147662.33,0 +3924,15595047,Murray,764,France,Male,41,7,0,2,0,0,134878.34,0 +3925,15732334,Black,653,France,Female,40,0,0,2,1,0,35795.85,0 +3926,15701206,Torreggiani,566,Spain,Male,44,5,0,2,1,0,66462.79,0 +3927,15581280,Atkinson,714,Germany,Male,29,6,92887.13,1,1,1,69578.49,0 +3928,15651943,Richards,580,Spain,Female,65,1,0,2,0,1,103182.46,0 +3929,15609545,Azubuike,548,France,Male,29,5,83442.98,1,0,1,177017.39,0 +3930,15658548,Ignatiev,646,Germany,Female,36,6,144773.29,2,1,0,53217.3,0 +3931,15626008,Miller,622,Germany,Female,52,9,111973.97,1,1,1,162756.29,1 +3932,15774133,Cox,706,France,Female,35,8,178032.53,1,0,1,42181.68,0 +3933,15763798,McMillan,680,France,Male,23,5,140007.19,1,0,1,31714.08,0 +3934,15758013,Napolitano,698,France,Male,37,5,98400.61,2,0,0,25017.28,0 +3935,15705765,Lane,581,Spain,Female,46,1,0,2,1,0,104272.04,0 +3936,15648362,Kennedy,728,Germany,Male,45,3,108924.33,2,1,0,84300.4,1 +3937,15761102,T'ao,707,Spain,Female,32,4,132835.56,1,0,0,136877.24,0 +3938,15610165,Hsiung,761,France,Female,26,1,0,2,1,1,199409.19,0 +3939,15723717,Heath,483,Germany,Male,41,1,118334.44,1,0,0,163147.99,1 +3940,15654611,Parry,736,Germany,Female,25,9,81732.88,2,1,0,136497.28,0 +3941,15659736,Herbert,716,Germany,Male,66,5,121411.9,1,0,0,10070.4,1 +3942,15603170,Kang,654,France,Male,32,9,121455.65,1,1,0,190068.53,1 +3943,15786167,Andreyeva,649,Spain,Male,20,5,0,2,1,1,58309.54,0 +3944,15671915,Bowen,649,France,Male,46,5,0,2,1,1,76946.6,0 +3945,15794792,Golubev,612,France,Female,31,8,117989.76,1,1,1,54129.86,0 +3946,15652789,Hancock,657,Spain,Male,40,10,0,2,1,1,52990.7,0 +3947,15739168,Fowler,511,France,Female,31,5,137411.29,1,0,1,161854.98,0 +3948,15719950,Sutherland,682,France,Male,61,10,73688.2,1,1,1,172141.33,0 +3949,15743818,Rowley,748,Spain,Male,58,9,122330.7,2,0,1,124429.19,0 +3950,15717937,Gibbons,554,Germany,Male,43,5,99906.89,1,0,0,24983.39,0 +3951,15602841,Lockett,794,Spain,Female,28,5,0,2,0,1,86699.98,0 +3952,15619972,Akabueze,807,France,Female,47,9,167664.83,1,0,0,125440.11,1 +3953,15796114,Phelps,594,France,Female,34,7,141525.55,1,0,0,9443.15,0 +3954,15633546,Frederick,652,Spain,Female,33,3,124832.51,1,1,0,195877.06,0 +3955,15758755,Beneventi,729,France,Female,34,9,132121.71,1,0,1,105409.31,0 +3956,15695168,Bruce,625,France,Male,39,2,0,2,1,0,100403.05,0 +3957,15754342,Green,597,Germany,Female,60,0,78539.84,1,0,1,48502.88,0 +3958,15756610,Carlson,657,Germany,Female,38,5,123770.46,1,0,0,47019.66,1 +3959,15640917,Tang,633,France,Male,43,5,0,2,1,1,48249.88,0 +3960,15663164,Yudin,663,Germany,Male,49,7,116150.65,3,1,1,84358.71,1 +3961,15616811,MacDonald,535,France,Male,47,0,160729.1,1,0,1,145986.35,0 +3962,15610781,Watt,702,France,Female,29,10,88378.6,1,1,0,88550.28,0 +3963,15600911,Mbadiwe,712,France,Male,33,2,182888.08,1,1,0,3061,0 +3964,15629603,Chuang,607,France,Male,31,8,0,2,1,1,43196.5,0 +3965,15714981,Sabbatini,476,France,Male,37,4,0,1,1,1,55775.84,1 +3966,15775892,Caldwell,748,Spain,Female,23,8,85600.08,1,0,0,134077.71,0 +3967,15782778,Ewers,815,France,Male,35,4,0,2,0,1,198490.33,0 +3968,15786643,Tsao,602,France,Male,32,10,0,2,1,1,116052.92,0 +3969,15595657,Hannam,649,Germany,Male,40,4,95001.33,1,0,1,123202.99,0 +3970,15743673,Wood,551,Spain,Male,27,2,113873.22,1,1,1,85129.77,1 +3971,15634310,Ko,509,France,Male,30,6,0,2,1,0,180598.86,0 +3972,15790809,Lo Duca,685,Spain,Male,40,7,74896.92,1,1,0,198694.2,0 +3973,15668695,Endrizzi,536,France,Female,22,5,89492.62,1,0,0,42934.43,0 +3974,15669281,Ch'iu,711,Spain,Male,38,3,128718.78,1,0,0,114793.45,0 +3975,15621031,Mofflin,761,Spain,Male,27,8,0,2,1,0,63297.7,0 +3976,15720071,Fiorentini,535,France,Female,49,3,0,1,0,0,61820.41,1 +3977,15792180,Chiekwugo,566,Germany,Male,22,7,144954.75,2,1,0,102246,0 +3978,15813894,Bogle,620,Spain,Male,21,9,0,2,0,0,154882.79,0 +3979,15669490,Ifeanacho,837,Germany,Male,37,6,94001.61,2,1,0,140723.05,0 +3980,15783030,Owens,685,France,Female,40,7,0,1,1,0,72852.74,1 +3981,15695792,Ch'ien,673,France,Male,65,0,0,1,1,1,85733.33,0 +3982,15575676,Chung,638,France,Male,24,1,0,2,0,1,162597.15,0 +3983,15627665,Sung,614,France,Male,46,4,0,1,1,0,74379.57,1 +3984,15814092,Wang,626,France,Female,44,2,0,1,0,1,173117.22,1 +3985,15695225,Sun,834,Spain,Male,38,8,0,2,1,1,66485.26,0 +3986,15615091,Maitland,691,France,Male,24,6,0,2,1,1,92811.2,0 +3987,15794345,Ma,706,Spain,Male,38,8,0,2,0,1,46635.11,0 +3988,15726484,Pollard,633,France,Male,37,7,141546.35,1,1,1,124830.11,0 +3989,15650442,Hsieh,644,Germany,Female,32,8,141528.88,1,1,1,167087.34,1 +3990,15714256,Gerasimov,666,France,Male,30,7,109805.3,1,0,1,163625.56,0 +3991,15778752,Johnson,708,France,Male,32,10,86614.06,2,1,1,172129.26,0 +3992,15601659,Fiorentino,496,Germany,Female,59,7,91680.1,2,1,0,163141.18,1 +3993,15602811,Chioke,730,Germany,Male,38,0,38848.19,2,0,0,94003.11,0 +3994,15779414,Rossi,696,Spain,Male,40,3,153639.11,1,1,1,138351.68,0 +3995,15763097,Siciliano,809,Spain,Male,80,8,0,2,0,1,34164.05,0 +3996,15633666,Efremov,701,Spain,Female,33,7,123870.07,1,1,0,97794.71,0 +3997,15718789,Brigstocke,604,France,Male,30,5,0,2,1,0,75786.55,0 +3998,15690620,Olisaemeka,665,France,Male,39,10,46323.57,1,1,0,136812.02,0 +3999,15737071,Tang,639,France,Female,60,5,162039.78,1,1,1,84361.72,1 +4000,15665062,Lucchese,696,France,Male,19,1,110928.51,1,1,1,2766.63,0 +4001,15600692,West,520,France,Male,38,5,0,2,1,0,163185.76,0 +4002,15792064,Pai,545,Germany,Male,53,5,114421.55,1,1,0,180598.28,1 +4003,15811486,Tang,634,Germany,Female,29,8,130036.21,2,0,1,69849.55,0 +4004,15626141,Fedorov,750,France,Female,26,1,151510.17,2,1,1,19921.72,0 +4005,15738546,Gboliwe,530,Spain,Female,41,4,0,2,0,1,147606.71,0 +4006,15677052,Ko,589,France,Female,59,2,0,2,1,1,126160.24,1 +4007,15656454,Le Gallienne,654,France,Male,37,6,83568.55,1,1,0,47046.72,0 +4008,15645496,Seleznyova,648,France,Female,43,7,139972.18,1,1,0,143668.58,0 +4009,15612505,Joseph,835,Spain,Male,45,3,100212.13,1,1,0,152577.62,0 +4010,15708513,Bevan,446,France,Female,39,1,90217.07,1,1,0,191350.48,0 +4011,15685654,Allan,514,Spain,Male,66,9,0,2,1,1,14234.31,0 +4012,15732307,Lavrentiev,694,Germany,Male,33,4,124067.32,1,1,1,77906.87,0 +4013,15726814,Walton,554,Spain,Male,46,4,0,2,0,1,57320.92,0 +4014,15653776,Salier,720,Germany,Female,57,1,162082.31,4,0,0,27145.73,1 +4015,15597914,Evdokimov,641,Germany,Female,51,2,117306.69,4,1,1,26912.72,1 +4016,15631603,Ponomaryova,813,France,Male,32,1,122889.88,1,1,1,26476.18,0 +4017,15789753,Millar,480,France,Male,40,6,148790.61,1,0,1,79329.7,0 +4018,15678034,Grosse,811,France,Male,46,9,180226.24,1,1,0,13464.64,1 +4019,15690209,Hsiao,715,Germany,Female,32,3,104857.19,2,1,0,114149.8,0 +4020,15592091,Belbin,620,Spain,Male,31,2,166833.86,2,1,1,135171.6,0 +4021,15647453,Ifeajuna,721,France,Male,42,4,102936.72,1,0,0,1187.88,0 +4022,15697100,Wright,772,Germany,Female,48,6,108736.52,1,1,0,184564.67,1 +4023,15811290,Komarova,680,Germany,Male,44,0,129974.79,2,1,1,33391.38,0 +4024,15629187,Titheradge,535,France,Male,38,8,85982.07,1,1,0,9238.35,0 +4025,15758073,Dellucci,655,France,Female,20,7,134397.61,1,0,0,28029.54,0 +4026,15640769,Hobbs,660,France,Male,63,8,137841.53,1,1,1,42790.29,0 +4027,15606641,Beggs,762,Germany,Male,56,10,100260.88,3,1,1,77142.42,1 +4028,15718280,Luffman,662,Germany,Male,39,5,139822.11,2,1,1,146219.9,0 +4029,15764335,Caldwell,463,Germany,Female,41,8,123151.51,2,1,0,70127.93,0 +4030,15634218,Mancini,501,Germany,Male,27,4,95331.83,2,1,0,132104.76,0 +4031,15808760,Evseev,603,Spain,Female,42,6,0,1,1,1,90437.87,0 +4032,15648461,Hs?eh,688,Spain,Male,37,7,138162.41,2,1,1,113926.31,0 +4033,15593555,Chinedum,430,France,Male,38,9,0,2,1,1,12050.77,0 +4034,15569079,Hagins,632,Germany,Male,48,6,126066.26,1,1,0,64345.61,1 +4035,15800736,Kirwan,601,Spain,Female,42,4,96763.89,1,1,1,199242.65,0 +4036,15792607,Little,769,France,Female,38,2,0,2,0,0,75578.67,0 +4037,15640034,Milligan,551,France,Male,42,2,139561.46,1,1,0,43435.43,1 +4038,15807563,Ch'iu,841,France,Female,52,5,0,1,0,0,183239.71,1 +4039,15684461,McKay,469,Spain,Female,31,6,0,1,1,0,146213.75,1 +4040,15580134,Crawford,479,Spain,Male,27,2,172463.45,1,1,1,40315.27,0 +4041,15679075,Onyemere,701,France,Male,37,8,107798.85,1,1,0,16966.73,0 +4042,15742504,Azuka,593,France,Male,36,2,70181.48,2,1,0,80608.12,0 +4043,15567328,Ch'en,738,Spain,Male,38,5,177997.07,1,0,1,19233.41,0 +4044,15698294,Royster,635,Spain,Male,31,1,0,2,1,0,135382.23,0 +4045,15607142,Parkin,658,France,Male,32,8,0,1,1,1,80410.68,0 +4046,15738516,Kozlova,687,Spain,Female,36,5,0,1,1,0,17696.22,0 +4047,15806403,Hu,650,France,Male,37,9,0,2,1,0,17974.08,0 +4048,15656707,Ma,720,Spain,Male,21,2,123200.78,1,1,1,180712.28,0 +4049,15653715,Coates,602,France,Female,63,7,0,2,1,1,56323.21,0 +4050,15806184,Burns,618,Spain,Male,33,4,0,2,1,1,77550.18,0 +4051,15585734,Gouger,803,Germany,Male,41,9,137742.9,2,1,1,166957.82,0 +4052,15725639,Ignatyev,793,France,Female,63,9,116270.72,1,1,1,184243.25,0 +4053,15618401,Douglas,616,Germany,Male,41,10,113220.2,2,1,1,114072.91,0 +4054,15785385,Fiorentino,550,Spain,Male,51,5,0,2,1,0,153917.41,0 +4055,15734762,Ignatiev,602,France,Female,56,3,115895.22,3,1,0,4176.17,1 +4056,15767129,Munz,452,France,Female,60,6,121730.49,1,1,1,142963.29,0 +4057,15797204,Paling,655,Spain,Female,28,3,113811.85,2,0,1,76844.23,0 +4058,15769272,Clark,510,France,Female,26,6,136214.08,1,0,0,159742.33,0 +4059,15771966,Akobundu,557,France,Male,39,8,146200.01,1,1,0,177944.64,0 +4060,15691952,Fanucci,676,France,Male,37,10,106242.67,1,1,1,166678.28,0 +4061,15593250,Hsiao,640,France,Female,29,4,0,2,1,0,44904.26,0 +4062,15605333,Clancy,529,Spain,Male,31,6,0,1,1,0,10625.91,0 +4063,15800083,Macdonald,559,France,Male,45,8,24043.45,1,0,1,169781.45,1 +4064,15575691,Palerma,689,France,Female,58,5,0,2,0,1,49848.86,0 +4065,15689886,Holden,626,Germany,Male,39,10,132287.92,3,1,1,51467.92,1 +4066,15809838,Moore,697,Spain,Male,30,1,0,2,0,0,735.79,0 +4067,15736154,Gallo,823,France,Female,44,1,0,2,0,1,182495.7,0 +4068,15767391,Otutodilinna,565,Germany,Female,32,4,90322.99,2,0,1,118740.37,0 +4069,15704910,Rios,631,Spain,Male,23,3,0,2,1,0,13813.24,0 +4070,15656613,McGregor,646,France,Female,34,3,131283.11,1,0,0,130500.65,0 +4071,15611551,Hill,676,Spain,Male,48,1,131659.59,2,0,1,14152.15,0 +4072,15732430,H?,850,Spain,Female,54,4,120952.74,1,1,0,66963.15,0 +4073,15741865,Ferrari,810,France,Female,38,9,153166.17,1,1,1,93261.69,0 +4074,15634143,Onyemauchechi,581,Spain,Male,30,0,53291.86,1,0,0,196582.28,0 +4075,15609676,Nkemakonam,718,France,Female,35,2,167924.95,1,1,0,43024.64,0 +4076,15761600,White,713,France,Male,43,5,86394.14,1,1,1,130001.13,0 +4077,15676404,Kirillov,672,France,Female,50,1,0,1,1,0,12106.82,1 +4078,15659236,Iadanza,781,Spain,Male,33,3,0,2,1,1,42556.33,0 +4079,15690440,Stiles,656,Spain,Male,47,1,0,2,1,1,197961.93,0 +4080,15694601,Ankudinov,583,France,Female,31,4,158978.79,1,1,0,12538.92,0 +4081,15812262,Gaffney,808,Germany,Female,37,2,100431.84,1,1,0,35140.49,1 +4082,15762821,Udinese,721,Spain,Male,33,5,0,2,0,1,117626.9,0 +4083,15669301,Romani,778,Germany,Female,29,6,150358.97,1,1,0,62454.01,1 +4084,15672640,Kambinachi,850,Spain,Female,45,4,114347.85,2,1,1,109089.04,0 +4085,15750458,Hawkins,693,France,Female,39,4,0,2,0,1,142331.39,0 +4086,15627251,Tsui,520,France,Male,34,4,134007.9,1,1,1,193209.11,0 +4087,15764294,Ifeatu,759,Germany,Male,31,4,98899.91,1,1,1,47832.82,0 +4088,15659962,McIntosh,637,France,Male,60,3,0,2,1,1,70174.03,0 +4089,15788536,Armit,755,Germany,Male,40,2,137430.82,2,0,0,176768.59,0 +4090,15596979,Fang,662,France,Female,47,6,0,2,1,1,129392.75,0 +4091,15681220,Chou,503,France,Female,37,8,0,2,1,1,97893.32,0 +4092,15635097,Okeke,599,Germany,Male,39,2,188976.89,2,0,1,176142.09,0 +4093,15780779,Ramsbotham,583,Spain,Female,40,4,0,2,1,0,114093.73,0 +4094,15798470,Scannell,764,Spain,Female,48,1,75990.97,1,1,0,158323.81,1 +4095,15760880,Edman,513,France,Male,29,10,0,2,0,1,25514.77,0 +4096,15616929,De Luca,730,Spain,Male,62,5,112181.08,1,0,1,61513.87,0 +4097,15758775,Vasilyeva,820,Spain,Male,34,10,97208.46,1,1,1,59553.34,0 +4098,15663386,Tuan,597,Spain,Female,26,7,0,2,1,0,110253.2,0 +4099,15621267,Ejimofor,637,France,Male,32,5,0,1,0,0,148769.08,0 +4100,15720509,Hs?,696,France,Male,34,9,150856.79,1,0,1,8236.78,0 +4101,15693322,Shaver,635,Germany,Female,37,9,146748.07,1,0,1,11407.58,0 +4102,15589544,Wallis,673,Spain,Female,57,4,0,2,1,1,49684.09,0 +4103,15772030,Coupp,662,Spain,Male,33,3,0,2,0,1,68064.83,0 +4104,15693337,Perry,683,Spain,Male,41,0,148863.17,1,1,1,163911.32,0 +4105,15676571,Bezrukova,850,France,Male,55,6,0,1,1,0,944.41,1 +4106,15701392,Lucciano,815,Spain,Male,28,6,0,2,0,1,185547.71,0 +4107,15741092,Ingram,671,Spain,Male,34,10,153360.02,1,1,0,140509.86,0 +4108,15643865,Lo Duca,601,France,Female,40,3,92055.36,1,0,1,164652.02,1 +4109,15769389,Wan,709,Germany,Female,39,9,124723.92,1,1,0,73641.86,0 +4110,15807768,Cohn,702,Germany,Male,28,1,103033.83,1,1,1,40321.87,0 +4111,15801630,Yen,558,France,Male,40,6,0,2,1,0,173844.89,0 +4112,15705034,Peng,691,Spain,Male,40,1,0,2,1,1,145613.17,0 +4113,15763107,Little,700,France,Female,30,9,0,1,1,1,174971.64,0 +4114,15667085,Meng,667,France,Male,33,4,0,2,1,1,131834.75,0 +4115,15647008,Adams,624,Germany,Male,54,3,116726.22,1,1,0,110498.1,1 +4116,15584505,Hill,580,France,Female,23,5,113923.81,2,0,0,196241.43,0 +4117,15748068,Boyle,571,Spain,Female,31,3,0,2,1,1,194667.92,0 +4118,15663964,Pagnotto,561,France,Male,37,5,0,2,1,0,83093.25,0 +4119,15782311,Feng,529,France,Male,28,9,0,2,1,1,52545.24,0 +4120,15588197,Endrizzi,670,France,Male,36,7,0,2,0,0,59571.5,0 +4121,15610105,Shen,666,Germany,Female,21,1,121827.43,2,1,1,99818.31,0 +4122,15606133,Lay,628,Spain,Male,42,7,0,2,0,1,172967.87,0 +4123,15599403,Wu,577,France,Male,60,10,125389.7,2,1,1,178616.73,0 +4124,15648225,Shephard,652,Spain,Female,38,1,103895.31,1,0,1,159649.44,0 +4125,15608406,Schmidt,678,France,Male,26,5,111128.04,1,1,0,60941.27,1 +4126,15633378,Davidson,692,Spain,Female,49,9,0,2,1,0,178342.63,0 +4127,15664759,Lamb,675,Spain,Male,32,10,0,2,1,0,191545.65,0 +4128,15625545,Hussey,712,Spain,Male,52,9,0,1,1,1,117977.45,1 +4129,15772148,Ferrari,639,Germany,Female,37,5,151242.48,1,0,1,49637.65,0 +4130,15810829,Macfarlan,618,France,Male,48,7,0,1,1,0,13921.82,1 +4131,15731669,Szabados,554,France,Male,39,2,129709.62,1,1,0,173197.12,0 +4132,15738634,Yuan,533,France,Male,47,9,83347.25,1,1,1,137696.25,0 +4133,15737571,Matveyev,540,Spain,Female,28,6,84121.04,1,0,1,80698.54,0 +4134,15667602,Cheng,704,Spain,Male,33,3,0,2,1,0,73018.74,0 +4135,15684147,Palerma,678,France,Male,43,5,102338.19,1,1,1,79649.62,0 +4136,15789874,Wang,712,France,Female,29,3,87375.78,2,0,0,166194.53,0 +4137,15757952,Teng,651,France,Male,44,2,0,3,1,0,102530.35,1 +4138,15698732,K'ung,789,Germany,Male,51,3,104677.09,1,1,0,74265.38,0 +4139,15714355,Sinclair,775,Germany,Male,32,8,121669.23,1,0,1,125898.39,0 +4140,15599090,McKelvey,564,Germany,Male,40,7,108407.34,1,1,1,83681.2,0 +4141,15762048,Yuan,841,Germany,Female,33,7,154969.79,2,1,1,99505.75,0 +4142,15790596,Moran,850,Spain,Male,39,0,141829.67,1,1,1,92748.16,0 +4143,15609623,McConnell,637,France,Female,63,5,0,1,1,0,28092.77,1 +4144,15711901,Iheatu,500,France,Male,45,2,109162.82,1,1,1,126145.08,0 +4145,15779809,Giordano,655,France,Male,44,8,87471.63,1,0,1,188593.98,0 +4146,15729018,Alexander,666,France,Female,33,2,147229.65,1,1,1,56410.17,0 +4147,15698246,Gordon,658,France,Female,24,2,0,2,1,1,84694.49,0 +4148,15712409,Tang,749,Germany,Male,66,6,182532.23,2,1,1,195429.92,0 +4149,15758306,T'an,654,France,Male,32,6,0,2,1,1,137898.57,0 +4150,15621435,Davies,623,France,Female,39,1,160903.2,1,0,0,78774.36,0 +4151,15566295,Sanders,761,France,Female,33,6,138053.79,2,1,0,148779.41,0 +4152,15569098,Winifred,627,France,Male,44,6,153548.12,1,0,0,35300.08,1 +4153,15662532,Holmes,757,Germany,Male,31,8,149085.9,2,1,1,197077.36,0 +4154,15664001,Riddle,695,Germany,Female,53,8,95231.91,1,0,0,70140.8,1 +4155,15703437,Chinedum,726,France,Male,34,3,0,2,1,0,196288.46,0 +4156,15708003,Aleksandrova,587,Spain,Male,41,8,85109.21,1,1,0,1557.82,0 +4157,15599452,Conti,605,Germany,Female,43,8,125338.8,2,1,0,23970.13,0 +4158,15719793,Watson,850,Spain,Male,62,5,0,2,1,1,180243.56,0 +4159,15771580,Davison,850,France,Female,38,0,106831.69,1,0,1,148977.72,0 +4160,15732268,Cook,751,France,Male,29,3,159597.45,1,1,0,39934.41,0 +4161,15722350,Udinesi,627,Germany,Female,37,7,147361.57,1,1,1,133031.96,0 +4162,15611371,Siciliani,736,France,Male,43,4,176134.54,1,1,1,52856.88,0 +4163,15673584,Bell,652,France,Female,74,5,0,2,1,1,937.15,0 +4164,15636396,Jackson,627,France,Female,35,7,0,2,0,1,193022.44,0 +4165,15706170,Onyemere,636,France,Male,34,1,84055.43,1,0,0,37490.84,0 +4166,15725478,McClemans,775,France,Male,60,7,0,2,1,1,111558.7,0 +4167,15654562,Ma,850,Spain,Female,45,5,174088.3,4,1,0,5669.31,1 +4168,15737509,Morrison,850,Spain,Male,34,8,199229.14,1,0,0,68106.29,0 +4169,15690796,Chambers,516,France,Male,37,8,0,1,1,0,101834.58,0 +4170,15716728,Basedow,513,Spain,Female,42,10,0,2,0,1,73151.25,0 +4171,15605665,Nwora,673,Germany,Female,69,3,78833.15,2,1,1,37196.15,0 +4172,15748481,Howey,564,France,Female,27,6,0,1,0,0,7819.76,0 +4173,15757777,Pai,636,France,Female,35,2,0,2,1,1,23129.46,0 +4174,15747808,Ni,712,France,Male,29,3,102540.61,1,1,1,189680.79,0 +4175,15810593,Forbes,568,France,Male,51,4,0,3,1,1,66586.56,0 +4176,15693376,Baryshnikov,741,Spain,Male,43,0,0,2,1,1,2920.63,1 +4177,15579808,Kramer,754,Germany,Female,39,8,129401.87,1,1,1,87684.93,0 +4178,15598275,Sochima,709,France,Female,32,7,0,2,1,1,199418.02,0 +4179,15737080,Marchesi,510,France,Female,32,1,0,2,0,1,28515.17,0 +4180,15668580,Todd,716,Spain,Male,33,2,0,2,1,1,92916.53,0 +4181,15569438,Mai,607,Germany,Male,36,10,106702.94,2,0,0,198313.69,0 +4182,15675842,Pinto,656,Spain,Male,26,4,139584.57,1,1,0,36308.93,0 +4183,15577587,Reynolds,550,Germany,Male,52,5,121016.23,1,1,1,41730.37,1 +4184,15625592,Sal,486,France,Male,26,2,0,2,1,1,31399.4,0 +4185,15635141,Miller,598,Germany,Male,59,8,118210.42,2,0,0,60192.14,1 +4186,15642570,Scott,675,Spain,Male,35,8,0,2,1,0,29062.25,0 +4187,15702175,Herrin,755,France,Female,29,4,148654.84,2,1,1,28805.09,0 +4188,15677785,Stevenson,656,Spain,Male,32,5,136963.12,1,1,0,133814.28,0 +4189,15786153,McKenzie,644,Germany,Male,47,9,137774.11,2,1,0,151902.78,0 +4190,15759499,Gardiner,598,France,Female,32,4,111156.52,1,1,1,167376.26,0 +4191,15659568,Atkinson,850,Spain,Female,31,3,121237.65,1,1,1,31022.56,0 +4192,15715597,Onyemauchechi,679,France,Male,36,1,97234.58,1,1,0,188997.08,0 +4193,15610147,Ross,632,France,Male,60,2,0,2,0,1,2085.32,0 +4194,15802362,Newland,550,Spain,Male,45,0,0,2,0,1,70399.71,0 +4195,15660524,Hu,572,Germany,Female,54,9,97382.53,1,1,1,195771.95,0 +4196,15747168,Sanders,626,Germany,Female,47,2,103108.8,1,0,1,166475.44,1 +4197,15796910,Tsui,625,Spain,Female,57,7,0,1,0,0,84106.17,1 +4198,15707674,Marino,515,France,Female,58,2,131852.81,1,1,0,81436.68,1 +4199,15565706,Akobundu,612,Spain,Male,35,1,0,1,1,1,83256.26,1 +4200,15587596,Morrison,628,Spain,Female,39,8,107553.33,1,1,0,117523.41,0 +4201,15751943,Mai,529,Spain,Female,43,5,0,2,0,0,79476.63,0 +4202,15621227,Hs?eh,668,Germany,Female,46,7,161806.09,1,1,1,173052.19,0 +4203,15757588,Wright,526,France,Male,30,9,0,2,0,0,100995.68,0 +4204,15640922,Demaine,791,France,Female,52,7,0,1,1,1,122782.5,0 +4205,15567557,Chien,573,France,Male,27,2,128243.03,1,1,1,11631.34,0 +4206,15670103,Dickinson,565,France,Female,38,5,126645.13,1,1,1,168303.55,0 +4207,15720929,Kazantseva,604,France,Female,47,8,62094.71,3,0,0,9308.1,1 +4208,15732774,Marchesi,656,France,Male,37,7,112291.34,1,1,0,153157.97,0 +4209,15628558,Pan,447,France,Female,44,5,89188.83,1,1,1,75408.24,0 +4210,15729201,Harewood,682,France,Male,55,9,0,1,1,0,153356.8,1 +4211,15731117,Kao,437,Spain,Male,28,2,109161.25,1,1,0,152987.42,0 +4212,15615207,Yeh,792,Spain,Male,47,0,0,1,1,1,5557.88,1 +4213,15773512,Bischof,627,Spain,Female,25,4,0,1,1,1,194313.93,0 +4214,15572145,Ashton,767,France,Female,34,8,0,2,1,0,94767.77,0 +4215,15642710,Napolitani,686,France,Male,26,7,0,2,1,0,1540.89,0 +4216,15574213,Wilson,789,France,Female,53,1,158271.74,1,1,1,5036.39,1 +4217,15718852,Uren,794,France,Male,56,9,96951.21,1,1,1,71776.76,0 +4218,15583840,Okechukwu,587,Germany,Male,35,5,121863.61,1,1,1,23481.69,1 +4219,15782418,Ku,589,Germany,Female,19,9,83495.11,1,1,1,143022.31,1 +4220,15813504,Onyemachukwu,543,Germany,Female,25,1,146566.01,1,0,1,161407.48,0 +4221,15711314,Kao,589,Spain,Female,45,1,0,1,0,0,125939.22,1 +4222,15621064,Russell,701,Germany,Male,23,5,186101.18,2,1,1,76611.33,0 +4223,15627847,Woronoff,850,France,Male,40,6,0,1,1,0,136985.08,1 +4224,15588090,Ferri,726,Germany,Female,51,8,107494.86,2,1,0,140937.91,1 +4225,15735270,Ruggiero,767,Spain,Male,47,2,0,1,1,0,48161.18,1 +4226,15671804,Wilding,648,Spain,Male,36,8,146943.38,2,1,1,130041.45,0 +4227,15753215,Yashina,651,Spain,Female,36,8,0,2,1,0,91652.43,0 +4228,15789941,Yevseyev,633,France,Female,36,6,125130.28,1,0,0,125961.48,0 +4229,15691061,Rapuokwu,740,France,Female,37,9,0,2,1,1,73225.31,0 +4230,15808326,Maslov,592,France,Female,34,9,0,2,1,1,20460.2,0 +4231,15566660,Cole,670,France,Female,41,10,0,3,1,0,81602.02,0 +4232,15778947,Sullivan,628,France,Male,36,3,0,2,1,1,8742.91,0 +4233,15632977,Hsiao,745,France,Male,47,5,0,2,0,0,145789.71,0 +4234,15591747,Rossi,705,France,Male,32,3,0,2,0,0,129576.99,0 +4235,15567335,Allsop,559,France,Female,42,7,0,2,1,1,190040.29,0 +4236,15609299,Chamberlain,595,France,Male,29,6,150685.79,1,1,0,87771.06,0 +4237,15669945,Jackson,492,France,Male,35,4,141359.37,2,1,0,39519.53,0 +4238,15736271,Dumetochukwu,498,France,Female,29,9,0,1,1,0,190035.83,0 +4239,15710390,Uspensky,655,France,Female,39,6,94631.26,2,1,1,148948.52,0 +4240,15756481,Garcia,636,France,Female,39,3,118336.14,1,1,0,184691.77,0 +4241,15736730,Soto,634,France,Female,45,2,0,1,1,1,143458.31,0 +4242,15626040,McDonald,793,Spain,Male,63,0,0,2,0,1,27166.75,0 +4243,15746553,Castles,526,Germany,Male,50,5,124233.24,1,0,1,159456.87,1 +4244,15622518,Stephenson,768,France,Female,26,5,51116.26,1,1,1,70454.79,1 +4245,15684908,Davidson,540,Germany,Male,64,1,91869.69,1,0,1,95421,0 +4246,15569446,Tu,732,France,Female,34,8,122338.43,2,1,0,187985.85,0 +4247,15777504,Colbert,617,France,Female,30,8,0,1,1,1,92621.9,0 +4248,15677906,Owens,637,Spain,Female,54,5,0,1,0,1,150836.98,0 +4249,15703292,Chimezie,573,France,Male,26,8,86270.93,2,1,1,90177.3,0 +4250,15712938,Genovese,531,France,Male,44,3,0,2,1,1,34416.79,0 +4251,15631359,Daluchi,489,France,Female,38,5,117289.92,1,0,0,85231.88,0 +4252,15720847,Sheffield,601,France,Male,35,2,0,2,1,1,118983.18,0 +4253,15787830,Bailey,452,Germany,Male,33,7,153663.27,1,1,0,111868.23,0 +4254,15599869,Dyson,728,Spain,Female,29,1,0,1,1,1,83056.22,0 +4255,15592078,Davide,590,Germany,Female,27,8,123599.49,2,1,0,1676.92,0 +4256,15596228,Uwaezuoke,490,France,Male,29,4,0,2,1,0,32089.57,0 +4257,15578462,Hs?,596,Spain,Female,76,9,134208.25,1,1,1,13455.43,0 +4258,15756894,Onwuka,635,France,Male,29,1,0,1,0,1,24865.54,0 +4259,15796167,Flores,782,Germany,Male,35,7,98556.89,2,1,0,117644.36,0 +4260,15664808,Nicoll,790,Spain,Female,37,3,0,3,0,0,98897.32,0 +4261,15664555,Hughes,587,France,Male,40,2,0,4,0,1,106174.7,1 +4262,15607278,Romano,794,Spain,Female,46,8,134593.79,1,1,1,46386.37,0 +4263,15585222,Norman,515,France,Male,41,8,0,2,1,1,185054.14,0 +4264,15750299,Davison,746,Spain,Male,24,10,68781.82,1,0,1,47997.39,0 +4265,15761294,Manna,667,Germany,Female,56,8,137464.04,1,1,0,130846.79,1 +4266,15810454,Reed,709,France,Male,32,4,147307.91,1,0,1,40861.55,0 +4267,15673984,Daniels,536,France,Female,35,8,0,1,1,0,171840.24,1 +4268,15609319,Hunt,711,France,Female,41,3,145754.91,1,1,1,101455.07,0 +4269,15709941,Feng,753,France,Male,46,8,0,3,1,0,90747.94,1 +4270,15580252,Waters,748,France,Male,44,4,112610.77,1,0,1,2048.55,0 +4271,15741275,Yuan,623,France,Female,57,7,71481.79,2,1,1,84421.34,0 +4272,15707132,Yudin,465,France,Male,33,5,0,2,0,1,78698.09,0 +4273,15600708,Calabresi,640,Spain,Female,34,3,77826.8,1,1,1,168544.85,0 +4274,15804787,Onyemauchechukwu,562,France,Male,75,5,87140.85,1,1,1,39351.64,0 +4275,15690021,Martin,502,Germany,Female,42,0,132002.7,1,0,1,28204.98,1 +4276,15763895,Hung,536,France,Male,32,7,178011.5,2,1,0,22375.14,0 +4277,15623478,Maslova,670,Germany,Female,32,4,102954.68,2,0,1,134942.45,0 +4278,15797910,Zetticci,775,Germany,Male,51,2,123783.25,1,1,1,134901.57,0 +4279,15577751,Pisano,759,Germany,Male,30,4,101802.67,1,0,0,8693.8,0 +4280,15781777,Sutherland,604,France,Male,33,3,148659.48,1,0,0,42437.75,0 +4281,15740527,Lai,766,Germany,Female,62,7,142724.48,1,0,1,5893.23,1 +4282,15721251,Watson,554,Spain,Female,41,4,112152.89,1,0,1,36242.19,0 +4283,15602994,Gorbunov,487,France,Female,53,10,89550.85,1,0,1,90076.85,0 +4284,15750769,Padovano,725,France,Male,35,7,75915.75,1,1,0,150507.43,0 +4285,15740175,Raynor,732,Germany,Female,42,2,118889.66,2,0,0,87422.15,0 +4286,15679968,Ting,623,France,Male,40,5,118788.57,1,1,0,192867.4,0 +4287,15694404,Eberegbulam,781,France,Female,42,3,156555.54,1,1,1,175674.01,0 +4288,15657529,Chin,714,Germany,Male,53,1,99141.86,1,1,1,72496.05,1 +4289,15762882,Manna,577,Germany,Female,31,4,61211.18,1,1,1,145250.43,0 +4290,15642579,Chang,731,Spain,Female,37,1,128932.4,1,1,1,180712.52,0 +4291,15598884,Kent,650,Spain,Female,23,5,0,1,1,1,180622.43,0 +4292,15770185,Buckley,779,France,Male,32,10,80728.15,1,1,0,86306.75,0 +4293,15800287,Micco,706,Spain,Female,46,2,127660.46,2,1,0,150156.82,1 +4294,15665861,Avdeev,733,Spain,Male,44,3,106070.89,1,0,1,101617.43,0 +4295,15662203,Bremer,579,Germany,Female,42,3,137560.38,2,1,1,85424.34,0 +4296,15616454,Davidson,476,Germany,Female,34,8,111905.43,1,0,1,197221.81,1 +4297,15702788,Gadsdon,775,France,Male,40,9,126212.64,1,1,0,70196.57,0 +4298,15778149,Connolly,538,Spain,Male,68,9,0,2,1,0,110440.5,1 +4299,15680001,McDonald,602,France,Male,38,7,111835.94,2,1,0,124389.61,0 +4300,15711991,Chiawuotu,615,France,Male,30,8,0,2,0,0,3183.15,0 +4301,15633834,Milne,700,Germany,Female,28,3,99705.69,2,0,0,146723.72,0 +4302,15765266,Fleming,615,France,Male,32,1,0,2,0,0,2139.25,0 +4303,15791867,Hicks,544,Germany,Male,44,2,108895.93,1,0,0,69228.2,1 +4304,15675380,Logan,573,Spain,Male,56,3,154669.77,1,0,1,115462.27,1 +4305,15770576,Hammond,555,Spain,Male,50,7,128061,2,1,1,62375.1,0 +4306,15775294,Weber,692,France,Female,31,2,0,2,1,0,91829.17,1 +4307,15727059,Lettiere,476,France,Female,40,4,0,2,0,0,182547.04,0 +4308,15702499,Schnaars,770,Spain,Male,46,9,190678.02,1,1,1,14725.36,0 +4309,15611699,Tao,641,France,Female,40,7,0,1,1,0,126996.67,0 +4310,15654000,Algarin,705,France,Female,35,5,0,1,1,0,133991.11,1 +4311,15657881,Onyemere,784,France,Male,38,5,136712.91,1,0,1,169920.92,0 +4312,15719991,Korovina,727,Spain,Female,52,1,154733.97,1,1,0,80259.67,1 +4313,15720687,Chidubem,576,France,Female,41,4,112609.91,1,0,0,191035.18,1 +4314,15687079,King,646,Spain,Male,69,10,115462.44,1,1,0,40421.87,0 +4315,15582276,Greco,638,France,Male,34,5,133501.36,1,0,1,155643.04,0 +4316,15763980,Beneventi,632,Germany,Male,30,1,58668.02,1,1,1,78670.52,0 +4317,15720774,P'eng,850,Spain,Male,44,7,89118.26,1,1,0,104240.77,1 +4318,15592194,Metcalf,492,France,Female,28,9,0,2,1,0,95957.09,0 +4319,15803685,Greco,673,Germany,Female,77,10,76510.52,2,0,1,59595.66,0 +4320,15759456,Lupton,609,Spain,Male,34,7,140694.78,2,1,0,46266.63,0 +4321,15611544,Ibeamaka,701,Germany,Male,36,7,95448.32,2,1,0,189085.07,0 +4322,15794257,Hsiung,651,France,Male,34,4,91562.99,1,1,1,123954.15,0 +4323,15681697,Rueda,508,France,Male,31,8,72541.48,1,1,0,129803.08,0 +4324,15579566,Li Fonti,616,Spain,Female,43,3,120867.18,1,1,0,18761.92,1 +4325,15577970,Alexeeva,489,France,Male,34,5,0,1,0,0,43540.59,0 +4326,15727489,Madueke,567,Spain,Female,45,1,157320.51,1,1,0,62193.92,0 +4327,15764284,Torres,714,Spain,Male,27,3,0,3,1,1,129130.09,0 +4328,15581811,Chukwubuikem,678,Germany,Female,30,1,139676.95,2,0,1,16146,0 +4329,15622527,Holloway,581,France,Female,55,6,0,1,1,1,22442.13,0 +4330,15753362,Evdokimov,748,Spain,Male,60,3,0,2,1,1,78194.37,0 +4331,15666652,Anayolisa,781,France,Female,19,3,0,2,1,1,124297.32,0 +4332,15789714,Semmens,691,Spain,Male,21,3,103000.94,1,1,1,104648.58,0 +4333,15771543,Tu,507,Germany,Male,31,2,134237.07,1,1,1,166423.66,1 +4334,15748327,Anderson,724,Germany,Male,34,6,118235.7,2,0,0,157137.23,0 +4335,15754649,Fang,705,Spain,Female,57,3,0,2,1,1,34134.14,0 +4336,15810460,Fanucci,708,Spain,Female,64,5,0,3,0,1,112520.07,1 +4337,15771742,Boyle,580,Germany,Male,38,9,115442.19,2,1,0,128481.5,1 +4338,15642160,Milanesi,850,France,Male,38,5,0,2,1,0,16491.64,0 +4339,15798439,Davidson,714,Spain,Male,25,2,0,1,1,1,132979.43,0 +4340,15605293,McKay,559,France,Female,43,1,0,2,1,1,196645.87,0 +4341,15692631,Bogdanova,577,Spain,Female,44,8,115557,1,0,1,127506.76,0 +4342,15665376,Lavrentiev,647,Germany,Female,35,3,166518.63,2,1,0,147930.46,0 +4343,15772412,Corser,554,Spain,Male,30,6,135370.12,1,1,1,179689.05,1 +4344,15654577,Alexeeva,549,Germany,Male,54,5,92877.33,1,1,0,2619.64,1 +4345,15585427,Madueke,528,France,Female,26,10,102073.67,2,0,0,166799.93,0 +4346,15584536,Barber,720,Germany,Male,46,3,97042.6,1,1,1,133516.51,1 +4347,15585853,McCardle,743,Spain,Male,41,7,0,1,1,0,163736.09,1 +4348,15645271,Radcliffe-Brown,615,Germany,Male,24,8,108528.07,2,0,0,179488.41,1 +4349,15579387,Ni,635,Germany,Female,44,2,79064.85,2,0,1,113291.75,0 +4350,15623107,Chukwumaobim,686,Spain,Male,45,3,74274.87,3,1,0,64907.48,1 +4351,15754072,Dennis,840,Spain,Female,36,6,0,2,1,0,141364.27,0 +4352,15666163,Hayward,695,France,Male,43,1,100421.1,1,1,1,101141.28,0 +4353,15765192,Jones,564,France,Male,26,7,84006.88,2,0,0,183490.99,0 +4354,15804822,L?,805,France,Female,31,4,0,2,1,0,4798.12,0 +4355,15612893,Nelson,558,Spain,Male,45,4,0,1,1,0,131807.14,0 +4356,15593636,Cardus,657,France,Female,39,4,80293.81,1,1,0,97192.76,0 +4357,15693326,Whitehouse,641,France,Female,42,7,125437.14,2,0,0,164128.58,0 +4358,15809901,Johnstone,755,France,Male,36,8,0,2,1,0,176809.87,0 +4359,15759751,Tsui,483,France,Male,48,1,0,2,1,1,110059.38,0 +4360,15605425,Chia,545,Germany,Female,44,2,127536.44,1,1,0,108398.63,0 +4361,15801934,Su,678,France,Male,66,8,0,2,1,1,47117.03,0 +4362,15592000,Calabresi,781,Germany,Female,48,9,82794.18,1,1,0,124720.68,1 +4363,15618695,Ts'ui,571,Spain,Female,22,3,108117.1,1,0,1,53328.7,0 +4364,15637110,McCulloch,634,Spain,Female,35,10,0,1,1,0,82634.41,0 +4365,15727408,Koo,523,Germany,Male,27,8,61688.61,2,1,0,147059.16,0 +4366,15716328,Miller,501,France,Female,40,2,0,2,0,0,141946.92,0 +4367,15669060,Woolnough,662,France,Male,74,6,0,2,1,0,123583.85,0 +4368,15675854,Douglas,573,Spain,Male,50,0,159304.07,1,0,1,155915.24,1 +4369,15621116,Fang,648,Germany,Male,33,5,138664.24,1,1,0,29076.27,0 +4370,15781495,Munro,662,France,Female,22,2,126362.57,2,1,1,97382.8,0 +4371,15740470,Vinogradov,725,France,Male,39,4,160652.45,2,1,0,57643.55,0 +4372,15714391,Lai,563,France,Female,35,2,183572.84,1,1,1,66006.75,1 +4373,15730137,Udegbulam,628,France,Male,31,0,88421.81,1,0,0,72350.47,0 +4374,15596455,Mao,546,Spain,Female,45,2,0,1,0,0,197789.83,1 +4375,15717290,Onyekaozulu,688,Germany,Male,41,2,112871.19,2,0,1,65520.74,0 +4376,15616555,Fu,850,Germany,Male,41,8,60880.68,1,1,0,31825.84,0 +4377,15659820,Cross,614,France,Female,34,5,0,2,1,0,185561.89,0 +4378,15696301,Snider,719,France,Female,37,9,101455.7,1,1,0,25803.59,1 +4379,15771087,Harrison,757,France,Female,71,0,88084.13,2,1,1,154337.47,0 +4380,15808831,Dale,669,France,Male,29,7,0,2,1,1,138145.62,0 +4381,15812241,Udinese,438,Germany,Male,59,7,127197.14,1,1,0,51565.98,1 +4382,15680370,DeRose,492,France,Male,39,7,0,2,0,1,71323.23,0 +4383,15780561,Hay,622,France,Female,39,9,83456.79,2,0,0,38882.34,0 +4384,15800784,Bruce,645,France,Male,42,4,98298.18,1,1,1,676.06,0 +4385,15715796,Romani,728,France,Male,37,0,0,2,1,1,72203.8,0 +4386,15605375,Tseng,651,France,Male,35,2,86911.8,1,1,0,174094.24,0 +4387,15621520,Tang,783,Germany,Female,42,2,139707.28,1,1,0,2150.22,0 +4388,15665460,Isayeva,732,Spain,Female,67,1,0,2,1,1,177783.04,0 +4389,15801152,Hill,553,Spain,Female,39,1,142876.98,2,1,0,44363.42,0 +4390,15756425,Barnes,660,France,Male,30,7,146301.31,1,0,0,96847.91,0 +4391,15674328,Moreno,670,France,Female,40,3,47364.45,1,1,1,148579.43,1 +4392,15742404,McGregor,718,France,Male,38,7,0,2,1,0,38308.34,0 +4393,15757140,Genovese,787,France,Male,51,0,58137.08,1,0,1,142538.31,0 +4394,15570051,Gill,775,Germany,Female,38,6,179886.41,2,0,0,153122.58,0 +4395,15669175,Ts'ai,479,Germany,Male,24,6,107637.97,2,0,1,169505.83,0 +4396,15790324,Green,660,France,Female,20,6,167685.56,1,1,0,57929.9,0 +4397,15691119,Martin,721,Germany,Male,68,4,136525.99,1,0,0,175399.14,0 +4398,15743478,Johnson,659,Germany,Male,39,8,52106.33,2,1,1,107964.36,0 +4399,15707007,Onio,743,France,Female,39,8,0,1,1,0,94263.44,0 +4400,15572547,Vaguine,670,France,Female,45,9,104930.38,1,1,0,155921.81,1 +4401,15567063,Manna,766,Germany,Female,34,6,106434.94,1,0,1,137995.66,1 +4402,15689633,Toomey,845,Spain,Female,38,2,112803.92,1,1,0,179631.85,0 +4403,15720637,Bell,710,Germany,Female,46,10,120530.34,1,1,0,166586.99,1 +4404,15616859,Bonwick,602,Germany,Female,43,2,113641.49,4,1,0,115116.35,1 +4405,15766166,Folliero,604,Spain,Male,43,2,145081.72,1,1,1,23881.62,0 +4406,15617655,Holt,564,Spain,Female,35,9,0,2,1,1,105837.38,0 +4407,15623450,Brown,637,Germany,Female,27,7,135842.89,1,1,1,101418.05,0 +4408,15796612,Ch'ang,527,France,Female,31,1,112203.25,1,1,0,182266.01,0 +4409,15795963,Fiorentini,687,France,Male,34,7,129895.19,1,0,1,28698.17,0 +4410,15781598,Middleton,756,Germany,Male,41,6,149049.92,1,0,1,50422.36,1 +4411,15691871,Millar,503,Germany,Male,42,9,153279.39,1,1,1,151336.96,0 +4412,15740345,Osborne,657,Spain,Male,42,5,41473.33,1,1,0,112979.6,1 +4413,15662626,Feng,666,France,Female,40,2,0,2,0,0,36371.27,0 +4414,15596575,Vale,615,Germany,Male,39,5,113193.51,2,1,1,52166.25,0 +4415,15657321,Arkwookerum,712,Germany,Male,27,8,113174.21,2,1,0,147261.58,0 +4416,15575955,Lujan,764,France,Female,24,0,0,2,1,0,88724.49,0 +4417,15743893,Alexeyeva,471,France,Male,42,3,164951.56,1,1,0,190531.77,0 +4418,15697270,Gannon,608,Spain,Male,27,4,153325.1,1,1,1,199953.33,0 +4419,15644356,Prokhorova,682,Spain,Female,47,10,134032.01,1,1,0,144290.97,0 +4420,15677586,Romero,587,Germany,Female,32,3,125445.04,2,1,1,130514.78,0 +4421,15571261,Toscani,714,Germany,Female,35,6,126077.43,2,1,1,53954.24,0 +4422,15698758,Onwuamaegbu,630,Spain,Female,31,1,0,2,1,1,169802.73,0 +4423,15787014,King,648,Germany,Female,28,8,90371.09,1,1,1,146851.73,0 +4424,15739857,Trentino,785,France,Female,40,3,0,2,1,1,96832.82,0 +4425,15774630,Peacock,601,Germany,Female,47,1,142802.02,1,1,1,57553.02,0 +4426,15805523,Nnaife,717,France,Female,28,1,90537.16,1,0,1,74800.99,0 +4427,15749557,Chao,707,France,Female,44,6,0,2,1,1,192542.17,0 +4428,15681180,Barese,771,France,Female,23,7,156123.73,1,1,0,72990.62,0 +4429,15742028,Udegbulam,602,France,Female,35,5,0,2,1,0,31050.02,0 +4430,15686463,Fu,626,France,Male,38,7,141074.59,1,1,0,52795.56,1 +4431,15654379,Onwuatuegwu,588,Spain,Male,59,4,0,2,1,1,27435.41,0 +4432,15783629,Degtyaryov,616,Germany,Female,42,6,117899.95,2,0,0,150266.81,0 +4433,15751193,Nnaemeka,621,Spain,Male,33,4,0,2,1,1,40299.23,0 +4434,15724099,Udinese,674,France,Male,26,6,166257.96,1,1,1,149369.41,0 +4435,15568429,Mitchell,633,Spain,Female,46,3,0,2,1,0,120250.58,0 +4436,15648967,Ch'en,698,Germany,Female,64,1,169362.43,1,1,0,84760.32,1 +4437,15664498,Golovanov,508,France,Male,26,7,205962,1,1,0,156424.4,0 +4438,15779522,Efimov,736,France,Female,24,0,0,2,1,0,109355.73,1 +4439,15583850,Davidson,672,Germany,Male,68,0,126061.51,2,1,1,184936.77,0 +4440,15696539,Wade,613,France,Female,21,7,105627.95,1,1,1,36560.51,0 +4441,15760121,Maynard,712,France,Male,32,9,100606.02,1,1,0,165693.06,0 +4442,15628279,Murphy,624,France,Female,38,3,0,2,1,1,163666.85,0 +4443,15766163,Zotova,676,France,Male,38,1,0,2,0,1,35644.79,0 +4444,15566467,Hannah,683,Germany,Female,32,0,138171.1,2,1,1,188203.58,0 +4445,15639049,Cartagena,489,France,Female,31,7,139395.08,1,0,1,6120.84,0 +4446,15736413,Hall,739,France,Male,29,1,0,2,1,1,164484.78,0 +4447,15634815,Hunt,701,France,Female,37,3,0,2,1,1,164268.28,0 +4448,15716381,Greece,666,Germany,Female,50,7,109062.28,1,1,1,140136.1,1 +4449,15708162,Thomson,565,Germany,Female,40,1,89994.71,2,0,1,121084.27,0 +4450,15569364,Victor,666,France,Male,36,3,0,2,1,0,35156.54,0 +4451,15791191,Mitchell,633,France,Male,59,2,103996.74,1,1,1,103159.11,0 +4452,15621205,Olisaemeka,578,France,Male,34,4,175111.11,1,1,1,74858.3,0 +4453,15704788,Krawczyk,812,Spain,Female,49,8,66079.45,2,0,0,91556.57,1 +4454,15775756,Alexandrova,809,Germany,Male,33,8,148055.74,1,0,0,199203.21,0 +4455,15641312,Paterson,615,France,Male,36,6,0,1,1,1,27011.8,1 +4456,15782531,Chou,684,Spain,Female,31,8,0,2,1,0,188637.05,0 +4457,15724428,Abel,544,France,Male,40,8,0,2,1,0,61581.2,0 +4458,15743617,Chesnokova,713,Germany,Male,47,1,95994.98,1,1,0,197529.23,0 +4459,15585839,Niu,633,France,Male,37,2,0,2,1,0,182258.17,0 +4460,15658158,Sullivan,672,Germany,Female,23,10,110741.56,1,1,0,80778.5,0 +4461,15637678,Ma,661,France,Male,35,5,0,1,1,0,155394.52,0 +4462,15701809,Cavill,749,Spain,Female,28,3,0,1,1,0,3408.7,0 +4463,15676937,Nicholls,635,Spain,Female,32,8,0,2,1,1,19367.98,1 +4464,15778975,Nnonso,850,Germany,Female,70,1,96947.58,3,1,0,62282.99,1 +4465,15710375,Gibson,641,France,Male,41,6,0,2,1,0,65396.79,0 +4466,15579914,Garcia,633,Germany,Male,30,2,109786.82,2,1,1,139712.81,0 +4467,15595160,Renwick,413,Spain,Male,35,2,0,2,1,1,60972.84,0 +4468,15595391,Norris,538,France,Male,31,1,0,2,1,0,1375.46,0 +4469,15630363,Nkemakonam,437,France,Female,39,0,102721.49,1,0,0,22191.82,0 +4470,15692443,Piccio,612,Spain,Male,33,5,69478.57,1,1,0,8973.67,1 +4471,15593795,Linton,516,Germany,Female,53,1,156674.2,1,1,0,118502.34,1 +4472,15642824,Onyekaozulu,826,Spain,Female,56,8,174506.1,2,0,1,161802.82,1 +4473,15683524,Tobenna,660,Germany,Female,23,6,166070.48,2,0,0,90494.72,0 +4474,15713532,Wang,646,Germany,Female,29,4,105957.44,1,1,0,15470.91,0 +4475,15719827,O'Donnell,767,France,Male,36,3,0,1,0,0,65147.27,0 +4476,15578435,Langlands,640,France,Male,40,8,110340.68,1,1,1,157886.6,0 +4477,15723028,Smith,778,France,Male,33,1,0,2,1,0,85439.73,0 +4478,15595609,Sykes,679,Germany,Male,52,9,135870.01,2,0,0,54038.62,0 +4479,15622443,Marshall,549,France,Male,31,4,0,2,0,1,25684.85,0 +4480,15579112,Gibson,598,France,Male,47,2,0,2,1,1,186116.54,0 +4481,15648479,Stephenson,655,France,Female,45,0,0,2,1,0,166830.71,0 +4482,15659234,Y?,494,France,Male,30,3,85704.95,1,0,1,27886.06,0 +4483,15811970,Kang,653,France,Female,42,1,0,2,1,1,5768.32,0 +4484,15774192,Miller,539,Germany,Female,38,8,105435.74,1,0,0,80575.44,1 +4485,15595136,Kryukov,645,France,Female,37,1,0,2,1,1,68987.55,0 +4486,15630580,Y?,751,Germany,Male,34,9,108513.25,2,1,1,27097.82,0 +4487,15660646,Fanucci,528,France,Male,35,3,156687.1,1,1,0,199320.77,0 +4488,15614365,Lombardi,696,Germany,Male,31,3,150604.52,1,0,0,5566.6,0 +4489,15776128,Hs?,716,France,Female,44,6,155114.9,1,0,0,133871.83,0 +4490,15787035,Anderson,602,France,Female,35,8,0,2,1,1,152843.53,0 +4491,15792646,Trentino,647,Spain,Female,64,1,91216,1,1,1,41800.18,0 +4492,15726832,Donnelly,850,Germany,Male,61,3,141784.02,1,1,1,92053.75,0 +4493,15773260,Tsou,590,France,Female,32,0,127763.24,1,1,0,100717.54,0 +4494,15624437,Johnson,825,Spain,Female,32,1,0,2,1,1,42935.15,0 +4495,15717138,Watson,850,Spain,Male,31,6,82613.56,2,1,0,149170.92,0 +4496,15657317,Allan,789,France,Female,32,7,69423.52,1,1,0,107499.39,0 +4497,15626948,Butcher,701,France,Female,42,6,86167.82,1,1,0,153342.38,0 +4498,15758901,Henderson,713,Spain,Female,47,1,0,1,1,0,107825.08,1 +4499,15777759,Boucaut,570,France,Male,30,2,131406.56,1,1,1,47952.45,0 +4500,15773322,Obiajulu,536,Germany,Female,44,4,121898.82,1,0,0,131007.18,0 +4501,15697318,Ifeatu,771,Germany,Male,32,9,77487.2,1,0,0,33143.04,0 +4502,15678916,Kelly,512,France,Female,75,2,0,1,1,0,123304.62,0 +4503,15632118,Pirozzi,698,Spain,Male,45,5,164450.94,1,1,0,141970.02,1 +4504,15788118,Siciliano,656,France,Male,33,7,138705.02,2,1,0,37136.15,0 +4505,15788930,Silva,761,Spain,Male,37,7,132730.17,1,1,0,199293.01,0 +4506,15628583,Iweobiegbunam,709,France,Female,30,5,0,2,0,1,161388.22,0 +4507,15635177,Williamson,597,Spain,Female,66,3,0,1,1,1,70532.53,0 +4508,15587690,Madueke,592,France,Male,28,2,116498.22,1,1,0,144290.25,0 +4509,15627630,Chiagoziem,599,France,Female,41,1,0,2,1,0,96069.82,0 +4510,15610930,Kwemto,572,Germany,Female,35,1,139979.07,1,1,0,185662.84,0 +4511,15657747,Zito,611,Germany,Female,43,9,127216.31,2,0,1,17913.25,0 +4512,15568006,Ukaegbunam,634,France,Female,45,2,0,4,1,0,101039.53,1 +4513,15751748,Trevisani,666,France,Male,51,2,148222.65,1,0,0,156953.54,1 +4514,15722212,Edmondstone,696,France,Female,41,8,0,2,0,0,28276.83,0 +4515,15658670,Chien,669,France,Female,38,8,0,2,1,0,84049.16,0 +4516,15761654,Boni,726,Spain,Male,30,8,134152.29,1,1,1,147822.44,0 +4517,15812210,Yashina,497,Germany,Female,32,8,111537.23,4,1,1,9497.99,1 +4518,15787051,Georg,750,Spain,Female,39,7,119565.92,1,1,0,87067.73,0 +4519,15642991,Tung,850,Spain,Female,29,7,0,2,1,0,23237.25,0 +4520,15713769,Michelides,617,Spain,Male,38,7,0,1,1,1,27239.28,0 +4521,15605826,Korovina,652,Germany,Male,46,10,121063.8,3,1,0,151481.86,1 +4522,15648898,Chuang,560,Spain,Female,27,7,124995.98,1,1,1,114669.79,0 +4523,15705309,Yuriev,629,Spain,Male,39,5,0,2,0,0,116748.14,0 +4524,15734202,Chidimma,660,Germany,Female,52,4,86891.84,1,1,0,90877.76,0 +4525,15658852,Stevens,676,France,Male,38,8,0,2,1,1,133692.88,0 +4526,15612633,Kao,581,Spain,Male,43,9,78022.61,1,0,1,30662.91,0 +4527,15604818,Edmund la Touche,798,France,Male,34,9,154495.79,1,1,0,191395.88,0 +4528,15593900,Belousov,705,France,Male,38,1,189443.72,1,0,1,106648.58,0 +4529,15624995,McCane,714,Spain,Female,31,6,152926.6,1,1,1,50899.91,0 +4530,15570087,Parry-Okeden,664,France,Female,44,8,142989.69,1,1,1,115452.51,1 +4531,15802617,Hudson,697,Germany,Male,43,7,115371.94,2,1,0,64139.1,0 +4532,15656029,Marsden,609,France,Male,37,6,0,2,0,1,22030.72,0 +4533,15739194,Manfrin,548,Spain,Male,38,0,178056.54,2,1,0,38434.73,0 +4534,15607275,Ch'ang,850,Spain,Male,39,6,206014.94,2,0,1,42774.84,1 +4535,15629475,Clark,656,France,Male,41,2,0,2,1,0,158973.77,0 +4536,15635034,Aldrich,727,Germany,Male,37,9,101191.83,1,1,1,34551.35,1 +4537,15756333,Khan,642,France,Female,55,7,0,2,1,1,101515.76,0 +4538,15777436,Murray,710,Spain,Female,31,5,0,2,1,0,9561.73,0 +4539,15676835,Anayolisa,710,Spain,Male,33,1,0,2,1,0,168313.17,0 +4540,15574206,Shillito,718,France,Female,37,7,0,2,1,1,55100.09,0 +4541,15613017,McMillan,586,Germany,Male,32,1,149814.54,1,1,0,31830.06,0 +4542,15815131,Howells,617,Spain,Female,36,7,115617.24,1,1,1,71519.4,0 +4543,15585455,Stewart,630,France,Male,28,9,0,2,0,0,32599.35,0 +4544,15692929,Ikechukwu,791,Germany,Female,42,10,113657.41,2,0,1,139946.68,1 +4545,15758081,Repina,673,Spain,Male,39,8,138160,1,1,1,110468.51,0 +4546,15667476,Cox,477,Germany,Female,36,3,117700.86,1,0,0,74042,0 +4547,15738248,Lo,662,France,Female,37,5,0,2,1,0,151871.84,0 +4548,15672152,Grant,850,Germany,Male,37,9,122506.38,1,0,1,199693.84,1 +4549,15673372,Stevenson,635,France,Female,58,1,0,1,1,1,58907.08,1 +4550,15587611,Kauffmann,537,France,Male,59,9,0,2,0,0,103799.77,1 +4551,15803415,Samsonova,579,France,Female,39,3,166501.17,2,1,0,93835.64,0 +4552,15715673,Niu,651,Spain,Female,46,4,89743.05,1,1,0,156425.57,1 +4553,15655648,Bock,610,France,Female,25,2,0,2,1,0,123723.83,0 +4554,15763613,Barlow,581,France,Male,30,1,0,2,1,0,199464.08,0 +4555,15660385,Stevenson,592,France,Male,39,7,0,2,1,0,83084.33,0 +4556,15733261,Kung,688,Spain,Female,35,6,0,1,1,0,25488.43,1 +4557,15796231,Nwankwo,681,France,Female,18,1,98894.39,1,1,1,9596.4,0 +4558,15624866,Brewer,658,Germany,Male,37,3,168735.74,2,0,0,70370.24,0 +4559,15623730,Ch'iu,792,France,Male,34,1,0,1,0,1,86330.32,0 +4560,15668248,Quinn,528,Germany,Female,62,7,133201.17,1,0,0,168507.68,1 +4561,15694518,Kodilinyechukwu,624,Spain,Female,36,0,0,2,1,0,111605.9,0 +4562,15638028,Ifeanyichukwu,562,Germany,Male,31,4,127237.25,2,0,1,143317.42,0 +4563,15795895,Yermakova,678,Germany,Male,36,1,117864.85,2,1,0,27619.06,0 +4564,15694376,Sullivan,705,Germany,Female,64,3,153469.26,3,0,0,146573.66,1 +4565,15669204,Grant,650,Germany,Male,23,4,93911.3,2,1,0,69055.45,0 +4566,15773779,Jacka,593,Spain,Female,46,2,76597.79,1,1,1,54453.72,0 +4567,15580682,Tsai,652,France,Female,40,4,79927.36,2,1,1,33524.6,0 +4568,15768530,Emery,554,Spain,Female,27,4,0,2,1,1,135083.73,0 +4569,15672875,Piccio,584,Germany,Male,32,8,40172.91,1,1,1,137439.34,0 +4570,15617082,Sanders,516,France,Male,33,7,115195.58,1,1,1,11205.5,0 +4571,15760514,Sharp,789,Germany,Female,43,9,116644.29,2,1,1,60176.1,0 +4572,15761775,Myers,598,Germany,Male,20,8,180293.84,2,1,1,29552.7,0 +4573,15799964,Campbell,669,Germany,Female,30,7,139872.81,1,1,0,188795.85,0 +4574,15693906,Abbott,645,France,Female,24,3,34547.82,1,1,1,11638.17,0 +4575,15739514,Preston,659,France,Female,32,9,0,2,1,1,93155.75,0 +4576,15756926,Atherton,833,Germany,Male,29,1,96462.25,2,0,1,48986.18,0 +4577,15770984,Fanucci,697,Spain,Female,40,7,130334.35,2,0,1,116951.1,0 +4578,15703979,Evans,580,Germany,Male,39,3,119688.81,1,1,0,137041.26,0 +4579,15801821,Cookson,691,France,Male,38,1,0,2,0,0,44653.5,0 +4580,15711028,Nnachetam,534,France,Male,52,1,0,3,1,1,104035.41,1 +4581,15791842,Johnstone,478,France,Female,32,6,71187.24,1,1,1,110593.62,0 +4582,15746127,Hort,572,France,Female,47,2,0,2,1,0,36099.7,0 +4583,15663625,Johnson,501,France,Male,37,4,0,2,0,0,12470.3,0 +4584,15604891,Zaytseva,624,Spain,Female,38,8,0,2,1,0,95403.41,0 +4585,15589666,Sorokina,595,France,Female,39,9,136422.41,1,1,1,151757.81,0 +4586,15627881,Diehl,603,France,Male,30,8,0,2,1,1,47536.46,0 +4587,15664895,Onuchukwu,602,France,Female,25,0,0,2,1,1,101274.17,0 +4588,15676094,Osonduagwuike,500,France,Female,34,6,0,1,1,1,140268.45,0 +4589,15761720,Mead,422,France,Male,41,6,153238.88,1,1,0,11663.09,0 +4590,15611961,Stewart,615,France,Male,35,7,0,2,1,0,150784.29,0 +4591,15680167,Thomson,635,France,Female,78,6,47536.4,1,1,1,119400.08,0 +4592,15762543,Goliwe,711,France,Female,32,1,0,2,1,0,126188.42,0 +4593,15658475,Lori,834,France,Male,36,8,142882.49,1,1,0,89983.02,1 +4594,15779743,Onwuamaeze,633,France,Female,44,7,0,2,1,0,29761.29,0 +4595,15661532,Butusov,650,France,Female,31,1,160566.11,2,0,0,27073.81,0 +4596,15782360,Rogers,743,Germany,Male,65,2,131935.51,1,1,1,96399.67,1 +4597,15767908,Nicholson,567,France,Male,38,6,127678.8,2,0,0,45422.89,0 +4598,15677105,Rossi,706,Germany,Female,46,4,105214.58,1,1,0,108699.59,1 +4599,15641474,Hall,638,France,Male,46,9,139859.54,1,1,0,38967.29,0 +4600,15624451,Huddart,641,France,Female,38,3,0,2,1,0,116466.19,0 +4601,15577985,Chinomso,574,France,Female,34,5,112324.45,2,1,1,17993.43,0 +4602,15571666,Shaw,642,Germany,Male,30,8,134497.27,1,0,0,43250.54,0 +4603,15783691,Hargreaves,722,Spain,Female,35,1,120171.58,1,1,0,125240.8,0 +4604,15671172,Swain,623,France,Male,23,1,106012.2,2,0,1,191415.94,0 +4605,15731760,Butcher,681,France,Male,25,5,0,1,0,1,90860.97,0 +4606,15585599,Stone,530,France,Female,34,8,0,2,0,1,141872.52,0 +4607,15784958,Allan,797,France,Female,55,10,0,4,1,1,49418.87,1 +4608,15734524,Wang,653,France,Male,51,3,0,1,1,0,170426.65,1 +4609,15614103,Colombo,850,Germany,Male,42,8,119839.69,1,0,1,51016.02,1 +4610,15794895,McKay,581,Spain,Male,34,1,0,2,0,1,81175.25,0 +4611,15772381,Brient,589,Germany,Male,38,8,92219.21,1,1,0,99106.97,0 +4612,15710553,Yin,555,Germany,Male,48,3,142055.41,2,0,1,79134.78,0 +4613,15649292,Bellucci,748,France,Female,49,7,29602.08,1,0,0,163550.58,1 +4614,15792565,Duncan,745,France,Female,46,7,0,2,1,1,67769.94,0 +4615,15718245,Pirozzi,730,France,Male,34,1,0,2,1,1,126592.01,0 +4616,15703117,Findlay,565,France,Female,44,1,0,2,0,1,89602.81,0 +4617,15758136,King,778,France,Male,37,3,141803.77,1,0,1,179421.84,0 +4618,15799932,Iweobiegbunam,812,France,Male,24,10,0,2,1,1,156906.15,0 +4619,15633516,Tucker,526,France,Male,42,1,0,1,0,1,168486.02,0 +4620,15622532,Izmailova,708,France,Female,47,0,126589.12,2,0,1,132730.07,1 +4621,15798960,Meng,680,France,Male,33,2,108393.35,1,0,1,39057.67,0 +4622,15698664,Liang,567,Spain,Male,43,2,115643.58,2,0,0,174606.35,0 +4623,15703614,Hutchinson,564,Spain,Male,48,5,132876.23,1,1,0,79259.77,0 +4624,15699195,Shen,709,France,Female,24,3,110949.41,1,1,1,168515.61,0 +4625,15710543,Okwuoma,629,France,Male,46,1,130666.2,1,1,1,161125.67,1 +4626,15695499,Chinwemma,510,France,Female,45,10,103821.47,2,0,1,77878.62,0 +4627,15622321,Golubova,506,France,Female,32,3,0,1,1,1,80823.02,0 +4628,15715744,Schiavone,605,France,Male,39,7,0,1,0,1,119348.28,0 +4629,15788151,Moore,650,Spain,Male,32,1,132187.73,2,1,1,178331.36,0 +4630,15687153,Graham,850,Germany,Male,49,8,98649.55,1,1,0,119174.88,1 +4631,15684958,Amadi,489,Germany,Male,38,2,126444.08,2,1,1,82662.73,0 +4632,15706116,McKay,659,Germany,Female,30,8,154159.51,1,1,0,40441.1,0 +4633,15740557,Fedorova,753,France,Female,43,5,0,2,1,0,109881.71,0 +4634,15707291,Percy,477,Germany,Male,48,8,129250,2,1,1,157937.35,0 +4635,15583353,Floyd,610,Spain,Female,45,3,0,1,1,0,38276.84,1 +4636,15761024,Long,619,France,Female,33,2,167733.51,2,1,1,65222.48,0 +4637,15630709,Castiglione,619,Germany,Female,31,2,56116.3,2,0,0,2181.94,0 +4638,15639590,Melendez,758,France,Female,30,3,141581.08,1,1,0,156249.06,0 +4639,15659399,Mazzi,516,Germany,Male,50,7,139675.07,2,1,0,45591.23,0 +4640,15567078,Kovaleva,789,France,Female,27,8,66201.96,1,1,1,79458.12,0 +4641,15696373,Gill,687,France,Female,44,9,0,2,0,0,103042.2,1 +4642,15786617,Arcuri,485,Germany,Male,34,3,133658.24,1,1,0,70209.83,0 +4643,15657449,Chukwuma,446,Germany,Male,25,3,136202.78,1,1,0,176743.51,0 +4644,15672594,Stevenson,597,France,Female,60,0,131778.08,1,0,0,10703.53,1 +4645,15714240,Ponomarev,712,Spain,Male,74,5,0,2,0,0,151425.82,0 +4646,15782144,Gilroy,522,France,Female,34,3,0,2,1,1,3894.34,0 +4647,15665008,Sidorov,805,Germany,Female,26,8,42712.87,2,1,1,28861.69,0 +4648,15581733,Bates,781,France,Female,28,4,0,2,1,0,177703.15,0 +4649,15751392,Fanucci,689,Spain,Female,57,4,0,2,1,0,136649.8,1 +4650,15785815,Toscano,670,Germany,Male,31,1,142631.54,2,1,1,175894.24,0 +4651,15664214,Hearn,670,France,Male,33,2,141204.65,2,1,0,76257.46,0 +4652,15579996,Iroawuchi,524,Germany,Female,25,7,131402.21,1,0,0,193668.49,0 +4653,15675252,Martin,734,Spain,Female,39,3,92636.96,2,1,1,125671.29,0 +4654,15579617,Sinclair,489,France,Female,51,3,0,2,0,1,174098.28,1 +4655,15593976,Swanson,578,Germany,Female,31,5,102088.68,4,0,0,187866.21,1 +4656,15716041,Chinomso,622,Spain,Male,39,9,0,2,0,1,100862.36,0 +4657,15654489,Fomin,843,France,Female,38,8,134887.53,1,1,1,10804.04,0 +4658,15736302,McKay,687,France,Male,48,4,0,2,1,1,170893.85,0 +4659,15805909,Bergamaschi,700,Spain,Male,28,8,159900.38,1,0,0,22698.56,0 +4660,15572762,Matveyeva,410,Germany,Female,50,2,102278.79,2,1,0,89822.48,0 +4661,15724632,Madukaego,537,France,Female,41,0,0,2,0,1,175262.49,0 +4662,15670416,Ferri,780,France,Female,43,0,0,1,0,1,15705.27,0 +4663,15749528,Achebe,652,Spain,Male,58,6,0,2,0,1,170025.43,0 +4664,15578783,Mai,620,Germany,Male,35,0,76989.97,1,1,1,17242.79,0 +4665,15580719,Davis,697,France,Female,23,10,0,2,1,1,79734.23,0 +4666,15656293,Davey,786,France,Male,35,3,0,2,1,0,92712.97,0 +4667,15691875,Tsou,850,Germany,Female,39,5,114491.82,1,1,0,99689.48,0 +4668,15596870,Marino,749,Germany,Male,54,3,144768.94,1,1,0,93336.3,1 +4669,15780770,Kerr,445,France,Male,31,7,145056.59,1,1,1,175893.53,0 +4670,15751491,Hsiao,443,Germany,Male,50,3,117206.3,1,1,0,42840.18,1 +4671,15706200,Graham,637,Germany,Male,41,2,138014.4,2,1,0,140298.24,0 +4672,15808674,Ejikemeifeuwa,616,Germany,Female,45,6,128352.59,3,1,1,144000.59,1 +4673,15641411,Volkova,756,France,Female,23,1,112568.31,1,1,1,113408.11,0 +4674,15764661,Wang,644,France,Male,33,2,0,1,1,0,96420.58,0 +4675,15689492,Benjamin,850,Germany,Male,41,1,176958.46,2,0,1,125806.3,0 +4676,15602405,Ryrie,703,Germany,Female,38,9,99167.54,1,1,0,65720.92,0 +4677,15610271,Andreev,684,Spain,Female,42,3,103210.27,1,1,0,31002.03,0 +4678,15791780,Ts'ao,706,Germany,Female,48,10,104478.12,3,0,1,158248.71,1 +4679,15589147,Frolov,580,Spain,Male,61,8,125921.37,1,1,1,94677.83,0 +4680,15756975,Montemayor,777,Spain,Female,35,3,0,2,1,1,17257.72,0 +4681,15729582,Fu,676,Germany,Male,48,3,80697.44,1,0,0,101397.86,0 +4682,15742971,Whitehead,708,France,Female,44,2,161887.81,2,1,0,84870.23,0 +4683,15568046,Izuchukwu,809,France,Male,24,7,109558.36,1,1,0,183515.13,0 +4684,15694890,Lai,588,France,Male,38,1,124271.26,1,1,0,75969.19,0 +4685,15736963,Herring,623,France,Male,43,1,0,2,1,1,146379.3,0 +4686,15646490,Duffy,537,Spain,Male,42,1,190569.23,1,0,1,127154.8,0 +4687,15607314,Chiefo,536,Spain,Male,53,2,143923.96,1,1,0,2019.78,1 +4688,15576745,Fyodorov,769,France,Male,48,2,96542.16,2,0,1,197885.72,0 +4689,15669606,Chu,690,France,Male,33,5,0,2,1,0,138017.68,0 +4690,15737832,Robertson,771,Spain,Male,45,0,139825.56,1,0,0,170984.97,1 +4691,15681990,Palmerston,497,Germany,Male,24,6,111769.14,2,1,0,55859.27,0 +4692,15758050,Madukwe,622,Spain,Male,37,4,0,2,1,0,4459.5,0 +4693,15787848,Chinedum,602,Spain,Male,30,9,113672.18,2,0,0,102135.92,0 +4694,15713594,French,543,France,Female,32,7,147256.86,1,1,0,112771.95,0 +4695,15588186,Polyakov,520,Spain,Male,45,7,107023.03,1,1,0,32903.93,0 +4696,15786739,Clements,669,France,Male,37,1,125529.55,1,1,1,162260.93,0 +4697,15699467,Connor,631,Spain,Female,41,0,0,1,0,0,87959.83,0 +4698,15680706,Balashov,537,Germany,Male,48,4,131834.8,1,1,0,166476.95,1 +4699,15645717,Avdeeva,732,France,Male,62,2,0,2,1,1,25438.87,0 +4700,15748597,Chester,844,Spain,Male,56,5,99529.7,1,0,1,157230.06,1 +4701,15773709,Hung,838,Spain,Male,35,0,0,2,0,1,197305.91,0 +4702,15629787,Tu,652,France,Male,27,10,107303.72,2,0,0,44435.76,0 +4703,15661007,Thompson,660,France,Male,33,0,72783.42,1,0,0,181051.99,0 +4704,15686812,Jones,692,Spain,Female,44,8,0,1,0,1,159069.37,0 +4705,15754113,Li,588,France,Female,35,0,0,2,1,1,155485.24,0 +4706,15749489,Denisova,533,Germany,Female,22,10,115743.6,1,0,0,43852.05,0 +4707,15574352,Clogstoun,850,France,Male,43,4,161256.53,1,1,1,140071.57,0 +4708,15701281,Tan,511,France,Male,27,8,0,2,1,1,49089.36,0 +4709,15811985,Power,530,Spain,Male,44,6,0,2,0,0,55893.37,0 +4710,15713505,Harriman,554,France,Male,31,1,0,2,0,1,192660.55,0 +4711,15685653,Benson,585,Germany,Female,40,3,162261.01,2,1,0,137028.51,0 +4712,15758831,Thornton,754,France,Male,39,3,74896.33,1,0,0,34430.16,0 +4713,15618774,White,474,France,Male,54,3,0,1,1,0,108409.17,1 +4714,15764448,Mackenzie,837,Germany,Male,35,0,144037.6,1,1,0,145325.32,0 +4715,15611024,Kalinina,567,France,Female,23,9,93522.2,1,0,1,81425.61,0 +4716,15738220,Bennet,800,Spain,Male,38,1,0,2,1,0,51553.43,0 +4717,15805764,Hallahan,646,France,Male,18,10,0,2,0,1,52795.15,0 +4718,15580487,Martin,627,Germany,Male,38,8,106922.92,2,0,1,84270.09,0 +4719,15675787,Rivera,505,France,Male,26,8,112972.57,1,1,0,145011.62,0 +4720,15583580,Chiawuotu,566,Germany,Female,35,1,123042,1,1,0,66245.44,1 +4721,15780654,Sergeyev,619,Germany,Female,33,3,100488.92,2,0,1,36446.74,0 +4722,15695034,Christie,757,France,Female,44,4,123322.15,1,1,0,137136.29,0 +4723,15805671,Louis,648,France,Male,32,0,0,1,0,1,117323.31,0 +4724,15790658,Iqbal,621,Spain,Male,42,8,68683.68,1,1,1,74157.71,0 +4725,15578648,Marino,543,Germany,Male,49,6,59532.18,1,1,0,104253.56,0 +4726,15734987,Robertson,658,France,Female,43,7,140260.36,2,1,0,2748.72,0 +4727,15721740,Pai,633,Germany,Male,50,7,88302.65,1,1,1,195937.16,0 +4728,15641822,Barese,648,France,Female,19,1,0,2,0,1,22101.86,0 +4729,15765650,Chigolum,501,Germany,Male,40,5,114655.58,1,0,0,126535.92,0 +4730,15788556,Trouette,683,France,Female,42,4,148283.94,1,1,1,44692.63,1 +4731,15576550,Ugochukwu,619,Spain,Female,38,1,0,1,1,0,112442.63,1 +4732,15622230,Cribb,705,France,Female,35,3,0,2,0,1,66331.01,0 +4733,15653937,McIntyre,638,Germany,Female,53,1,123916.67,1,1,0,16657.68,1 +4734,15743538,Pickering,710,France,Female,31,1,0,2,1,0,20081.3,0 +4735,15591740,Fletcher,590,France,Female,54,4,0,2,1,1,93820.49,1 +4736,15650086,Uchenna,725,France,Male,43,2,165896,2,1,0,130795.52,0 +4737,15718773,Pisano,638,France,Female,32,0,0,2,1,0,160129.99,0 +4738,15615140,Corson,791,France,Male,36,6,111168.97,1,1,1,189969.91,0 +4739,15644361,Hooper,702,France,Female,40,1,103549.24,1,0,0,9712.52,1 +4740,15774536,He,607,France,Female,32,6,0,2,0,0,196062.01,0 +4741,15618661,Chidubem,535,France,Male,30,6,103804.97,1,1,1,125710.53,0 +4742,15605020,Schofield,651,France,Male,45,2,165901.59,2,1,0,23054.51,1 +4743,15762134,Liang,506,Germany,Male,59,8,119152.1,2,1,1,170679.74,0 +4744,15685279,Somadina,511,Spain,Female,57,8,122950.31,1,1,1,181258.76,0 +4745,15582849,McIntosh,757,France,Female,51,1,0,1,1,1,22835.13,1 +4746,15655410,Hinton,768,Germany,Male,49,1,133384.66,1,1,0,102397.22,1 +4747,15649129,Sal,757,France,Male,32,9,0,2,1,0,115950.96,0 +4748,15702380,De Luca,663,Spain,Male,64,6,0,2,0,1,15876.52,0 +4749,15759067,Bromby,537,Germany,Female,37,7,158411.95,4,1,1,117690.58,1 +4750,15683027,Chang,570,Germany,Male,29,4,122028.65,2,1,1,173792.77,0 +4751,15597487,Hunter,850,France,Female,35,5,0,1,1,1,80992.8,0 +4752,15763256,Sheppard,661,Germany,Female,64,8,128751.65,2,1,0,189398.18,1 +4753,15620111,Fan,659,France,Male,54,8,133436.52,1,1,0,56787.8,0 +4754,15623053,Muir,454,Spain,Male,40,2,123177.01,1,1,0,148309.98,0 +4755,15595592,Lai,708,France,Female,59,2,0,1,1,0,179673.11,1 +4756,15740072,Padovesi,720,France,Female,37,2,120328.88,2,1,1,138470.21,0 +4757,15778005,Kemp,785,France,Female,39,1,130147.98,1,1,0,163798.41,1 +4758,15583278,Greece,743,Spain,Female,36,8,92716.96,1,1,1,33693.78,0 +4759,15601263,Young,493,Spain,Female,48,7,0,2,1,0,48545.1,0 +4760,15709222,Chukwueloka,557,Spain,Male,34,3,0,1,0,1,123427.98,0 +4761,15713949,Woods,850,France,Male,40,1,76914.21,1,1,0,174183.44,0 +4762,15717706,Forbes,799,France,Female,32,3,106045.92,2,1,1,17938,0 +4763,15756071,Kang,756,France,Male,34,1,103133.26,1,1,1,90059.04,0 +4764,15696564,Nweke,752,France,Male,38,0,145974.79,2,1,1,137694.23,0 +4765,15657637,Ts'ui,696,Spain,Female,36,3,0,3,1,0,65039.9,0 +4766,15755863,Milano,630,Spain,Female,49,1,0,2,0,1,162858.29,0 +4767,15719858,Chao,659,Spain,Female,38,9,0,2,1,1,35701.06,0 +4768,15688876,Wan,685,Spain,Male,39,9,0,2,1,1,18826.06,0 +4769,15698528,Napolitani,599,Spain,Female,31,3,0,1,1,1,130086.47,1 +4770,15770345,Kovaleva,559,Spain,Female,31,1,139183.06,1,0,1,143360.56,0 +4771,15761506,Russell,615,Spain,Male,19,5,0,2,1,0,159920.92,0 +4772,15716619,Chiebuka,580,Germany,Female,36,3,74974.89,1,1,1,12099.67,0 +4773,15788367,Ellis,487,Spain,Male,44,6,61691.45,1,1,1,53087.98,0 +4774,15709451,Gordon,646,Germany,Female,35,1,121952.75,2,1,1,142839.82,0 +4775,15640421,Conway,811,France,Female,35,7,0,1,1,1,178.19,0 +4776,15580068,Buccho,526,Spain,Male,35,5,0,2,1,1,105618.14,0 +4777,15677123,Aksyonova,767,Spain,Male,37,7,0,2,1,1,24734.25,0 +4778,15619801,Batty,548,France,Female,33,1,80107.83,2,0,1,82245.67,0 +4779,15582246,Rowe,737,Spain,Female,45,2,0,2,0,1,177695.67,0 +4780,15711843,Pisani,613,Germany,Male,40,1,147856.82,3,0,0,107961.11,1 +4781,15680046,Onochie,711,Spain,Male,36,8,0,2,1,0,55207.41,0 +4782,15804131,Farmer,850,Spain,Female,53,7,65407.16,2,0,0,182633.63,1 +4783,15722611,Cameron,752,France,Female,53,8,114233.18,1,1,1,51587.04,0 +4784,15729224,Jennings,710,France,Female,37,5,0,2,1,0,115403.31,0 +4785,15811588,Eluemuno,664,Spain,Female,53,7,187602.18,1,1,0,186392.99,1 +4786,15702138,Swift,510,France,Female,22,3,156834.34,1,0,0,44374.44,0 +4787,15749799,Pisani,577,France,Female,34,2,0,2,1,1,84033.35,0 +4788,15752885,Nnonso,529,France,Male,42,1,157498.9,1,1,1,82276.62,0 +4789,15674932,Cameron,757,Spain,Female,44,9,0,2,1,0,177528.92,0 +4790,15743828,Stevens,691,France,Male,41,2,0,1,1,1,56850.92,1 +4791,15642022,Zito,621,Spain,Male,34,8,0,1,0,0,47972.65,0 +4792,15746461,Taylor,709,Spain,Male,35,2,0,2,1,0,104982.39,0 +4793,15809991,Ferrari,756,Spain,Male,19,4,130274.22,1,1,1,133535.29,0 +4794,15787322,Yeh,788,France,Female,41,6,0,1,1,1,25571.37,0 +4795,15575498,Gould,705,France,Female,39,5,149379.66,2,1,0,96075.55,0 +4796,15691387,Agafonova,483,France,Male,29,9,0,1,1,1,81634.45,0 +4797,15765457,Fowler,719,Spain,Male,35,1,100829.94,1,1,1,165008.97,0 +4798,15666173,Chidumaga,793,Germany,Female,32,1,96408.98,1,1,1,138191.81,0 +4799,15627377,Sabbatini,593,France,Male,41,6,0,2,1,1,99136.49,0 +4800,15656683,Johnson,551,France,Male,52,1,0,1,0,0,63584.55,1 +4801,15679810,Chapman,690,France,Male,39,6,0,2,1,0,160532.88,0 +4802,15606310,Birk,823,France,Male,71,5,149105.08,1,0,1,162683.06,0 +4803,15756871,Capon,512,Spain,Male,39,3,0,1,1,0,134878.19,0 +4804,15610002,Chidubem,802,Spain,Male,41,5,0,2,1,1,134626.3,0 +4805,15567802,Childs,450,Spain,Female,34,2,0,2,1,0,175480.93,0 +4806,15745452,Sun,651,Germany,Male,41,1,90218.11,1,1,0,174337.68,0 +4807,15617252,Lung,697,France,Female,33,1,87347.7,1,1,0,172524.51,0 +4808,15753248,Tao,611,France,Male,28,2,0,2,0,0,25395.83,0 +4809,15610755,Napolitano,643,France,Female,33,0,137811.75,1,1,1,184856.89,0 +4810,15662238,Davis,822,France,Male,37,3,105563,1,1,0,182624.93,0 +4811,15799186,Sagese,632,France,Male,38,4,0,2,0,0,192505.62,0 +4812,15686941,Hutchinson,575,Spain,Female,26,7,0,2,1,0,112507.63,0 +4813,15601172,Nelson,672,France,Male,31,6,91125.75,1,1,0,177295.92,0 +4814,15723858,Schiavone,517,Spain,Male,39,3,0,2,0,1,12465.51,0 +4815,15615896,Chienezie,621,Spain,Male,39,8,0,2,1,0,36122.96,0 +4816,15737647,Obioma,775,Germany,Female,77,6,135120.56,1,1,0,37836.64,0 +4817,15582841,Butusov,600,France,Male,29,8,0,2,0,1,34747.43,0 +4818,15760090,Pisano,640,France,Male,28,7,0,2,1,1,131097.9,0 +4819,15588587,Stetson,752,France,Female,36,1,86837.95,1,1,1,105280.55,0 +4820,15683157,Waring,613,France,Male,26,4,100446.57,1,0,1,149653.81,0 +4821,15694209,Fanucci,484,France,Female,32,3,0,2,1,1,139390.99,0 +4822,15655875,Thao,511,France,Female,33,3,0,2,1,0,132436.71,0 +4823,15805704,Murphy,745,France,Female,32,2,0,4,0,1,179705.13,1 +4824,15744789,McConnell,786,Spain,Female,32,6,114512.59,1,1,0,15796.66,0 +4825,15799357,Armfield,727,France,Male,35,5,136364.46,1,0,0,142754.71,0 +4826,15726153,Fanucci,622,France,Male,31,5,106260.67,1,1,1,2578.43,0 +4827,15713346,Panina,794,France,Male,24,10,146126.75,1,1,1,88992.05,0 +4828,15665053,Nixon,636,Spain,Male,52,4,111284.53,1,0,1,32936.44,1 +4829,15592379,Walker,741,Spain,Female,42,9,121056.63,2,1,0,39122.58,0 +4830,15692599,Chiemela,687,France,Male,34,5,128270.56,1,1,0,191092.62,0 +4831,15620758,Martel,660,Spain,Male,30,4,0,2,1,0,129149.06,0 +4832,15637428,Briggs,660,France,Male,35,7,0,2,1,0,13218.6,0 +4833,15808389,Iheatu,617,France,Female,79,7,0,1,1,1,160589.18,0 +4834,15807003,Jennings,762,France,Male,32,10,191775.65,1,1,0,179657.83,0 +4835,15702912,Ch'en,752,Spain,Female,35,2,0,1,1,0,44335.54,1 +4836,15590623,Kovalyov,561,Spain,Male,34,4,85141.79,2,1,1,29217.37,0 +4837,15728078,Yeh,609,France,Male,26,10,126392.18,1,0,1,43651.49,0 +4838,15708256,Chien,803,France,Male,28,3,0,2,1,0,159654,0 +4839,15582335,Brown,556,France,Female,40,9,129860.37,1,0,0,17992.94,0 +4840,15649150,Buddicom,531,France,Female,53,5,127642.44,1,1,0,141501.45,1 +4841,15691647,McGregor,411,France,Female,35,2,0,2,1,1,93825.78,0 +4842,15668270,Thompson,587,Germany,Female,44,5,125584.17,2,1,1,41852.24,1 +4843,15624820,Ross,683,Spain,Male,56,7,50911.21,3,0,0,97629.31,1 +4844,15736254,Ch'ang,654,France,Male,29,2,91955.61,1,1,0,37065.66,0 +4845,15720814,Warren,670,Germany,Female,36,2,84266.44,2,0,0,38614.69,0 +4846,15642997,Uspenskaya,655,France,Female,36,2,147149.59,1,1,1,87816.86,0 +4847,15693200,King,752,France,Female,36,7,0,2,1,0,184866.86,0 +4848,15624596,Trentini,534,France,Female,23,5,104822.45,1,0,1,160176.47,0 +4849,15807167,Konovalova,635,France,Male,42,1,146766.72,2,0,1,164357.1,0 +4850,15660301,Dellucci,491,Germany,Male,70,6,148745.92,2,1,1,17818.33,0 +4851,15593094,Goddard,516,France,Male,27,9,0,1,1,0,142680.64,1 +4852,15618239,Neumann,530,France,Female,48,0,0,1,1,0,85081.09,0 +4853,15574137,Ch'in,687,Spain,Male,35,3,0,2,1,1,176450.19,0 +4854,15614740,Walters,684,France,Female,41,6,135203.81,2,1,1,121967.88,0 +4855,15574071,Muravyova,706,Germany,Male,23,2,93301.97,2,0,1,127187.04,0 +4856,15671148,Barry,490,Germany,Male,33,5,96341,2,0,0,108313.34,0 +4857,15721921,Woolnough,796,France,Male,44,8,165326.2,1,1,1,57205.55,0 +4858,15717995,Keen,849,France,Male,27,0,0,2,0,1,157891.86,0 +4859,15632050,Liebe,779,France,Female,41,10,99786.2,1,1,0,86927.53,0 +4860,15647111,White,794,Spain,Female,22,4,114440.24,1,1,1,107753.07,0 +4861,15759991,Hunter,748,Spain,Male,36,4,141573.55,1,1,0,82158.14,0 +4862,15790204,Myers,663,Spain,Female,22,9,0,1,1,0,29135.89,1 +4863,15686780,Rogova,645,Spain,Female,55,1,133676.65,1,0,1,17095.49,0 +4864,15640491,Raff,464,France,Female,33,10,147493.7,2,1,0,100447.53,0 +4865,15783225,Cocci,737,France,Male,54,9,0,1,1,0,83470.4,1 +4866,15734438,Kanayochukwu,590,France,Female,29,4,0,2,1,0,121846.81,0 +4867,15688760,Obialo,522,Germany,Female,37,3,95022.57,1,1,1,129107.59,0 +4868,15768124,Liu,648,France,Female,34,3,0,1,1,0,54726.43,0 +4869,15661330,Gilbert,754,France,Male,37,6,0,1,1,1,116141.72,0 +4870,15781272,Coles,669,France,Male,50,4,149713.61,3,1,1,124872.42,1 +4871,15573888,Ponomaryov,648,Germany,Female,43,1,107963.38,1,0,0,186438.86,1 +4872,15575858,Bergamaschi,763,France,Male,40,3,0,2,1,0,134281.11,0 +4873,15645937,Guerin,790,Spain,Male,32,3,0,1,1,0,91044.47,0 +4874,15702337,Sinclair,581,France,Male,37,7,0,2,1,1,74320.75,0 +4875,15764537,Dominguez,703,France,Male,43,8,0,2,1,0,9704.66,0 +4876,15619616,Costa,571,France,Female,33,9,102017.25,2,0,0,128600.49,0 +4877,15585133,Wei,657,Spain,Female,27,8,0,2,0,0,6468.24,0 +4878,15573971,Mills,737,France,Male,44,7,0,2,0,0,57898.58,0 +4879,15579433,Pugh,793,Spain,Male,29,8,96674.55,2,0,0,192120.66,0 +4880,15777045,Price,783,Spain,Female,44,3,81811.71,1,1,0,164213.53,1 +4881,15611580,Wood,751,Spain,Male,33,4,79281.61,1,1,0,117547.76,0 +4882,15614778,Robertson,579,France,Male,31,6,0,2,1,0,26149.25,0 +4883,15771750,Sawtell,655,Germany,Female,36,10,122314.39,1,1,0,9181.66,0 +4884,15593280,Yuryeva,614,Germany,Male,43,8,140733.74,1,1,1,166588.76,0 +4885,15569274,Pisano,678,Germany,Male,49,2,116933.11,1,1,0,195053.58,1 +4886,15654408,Kharitonova,562,Spain,Male,41,5,165445.04,2,1,0,85787.31,0 +4887,15657468,Simmons,711,Germany,Female,53,5,123805.03,1,1,0,102428.51,0 +4888,15614213,Muramats,620,France,Male,37,0,107548.94,1,1,0,71175.94,0 +4889,15589869,Tang,437,France,Male,49,9,111634.29,2,0,1,166440.32,0 +4890,15693205,Peng,691,Germany,Female,41,8,109153.96,3,1,1,148848.76,1 +4891,15797113,Bevan,552,Spain,Female,34,4,0,2,1,0,140286.69,0 +4892,15676958,Zito,765,Germany,Male,34,5,86055.17,2,1,1,104220.5,0 +4893,15739592,Sokolov,707,Germany,Female,51,10,98438.23,1,0,0,70778.63,1 +4894,15656263,Teng,764,Spain,Male,29,5,0,2,1,0,65868.28,0 +4895,15636872,Amadi,585,France,Female,32,8,144705.87,2,0,0,171482.56,0 +4896,15589435,Davide,784,France,Male,31,7,0,2,1,1,143204.41,0 +4897,15640464,Parkes,605,France,Male,41,5,91612.91,1,1,1,28427.84,0 +4898,15723851,Mazzanti,699,Spain,Male,40,2,0,1,1,0,78387.32,0 +4899,15722122,Findlay,544,France,Female,40,7,0,1,0,1,161076.92,0 +4900,15696852,Hsu,803,France,Female,32,9,192122.84,1,1,1,54277.45,1 +4901,15634936,Chukwukadibia,735,France,Male,41,7,179904,1,1,1,137180.95,0 +4902,15575935,Baxter,673,France,Male,59,0,178058.06,2,0,1,21063.71,1 +4903,15634491,Kung,652,France,Male,30,2,176166.56,2,1,1,152210.81,0 +4904,15628530,Booth,694,France,Male,42,3,156864.2,2,0,0,88890.75,0 +4905,15678720,Evans,741,France,Female,44,7,0,2,1,1,190534.76,0 +4906,15627999,Kung,590,Spain,Male,30,3,0,2,1,0,83090.35,0 +4907,15571244,Tung,809,Spain,Female,33,3,0,2,0,1,141426.78,0 +4908,15739931,Yuan,523,France,Male,34,2,161588.89,1,1,1,51358.66,0 +4909,15806256,Jackson,540,France,Male,48,2,109349.29,1,1,0,88703.04,1 +4910,15787258,Ross,596,Spain,Female,29,6,0,2,1,0,116696.77,0 +4911,15706463,Yang,597,France,Female,36,9,0,2,1,1,7156.09,0 +4912,15691004,Yu,407,Spain,Male,37,1,0,1,1,1,49161.12,1 +4913,15792228,Onwumelu,748,France,Male,60,0,152335.7,1,1,0,126743.33,1 +4914,15733447,Gay,562,France,Female,51,1,124662.54,1,1,1,65390.46,1 +4915,15679062,Morrison,734,Germany,Female,47,10,91522.04,2,1,1,138835.91,0 +4916,15594409,Belov,710,France,Male,45,1,0,2,1,1,36154.66,0 +4917,15613816,Mao,539,Spain,Female,39,6,62052.28,1,0,1,59755.14,0 +4918,15681991,Walsh,542,France,Male,32,7,107871.72,1,1,0,125302.64,0 +4919,15796074,Bruno,717,France,Female,36,2,99472.76,2,1,0,94274.72,1 +4920,15625941,Gray,682,Spain,Female,50,10,128039.01,1,1,1,102260.16,0 +4921,15615016,Maurer,515,France,Male,33,2,0,2,1,1,136028.97,0 +4922,15748414,Chiang,526,Spain,Female,33,8,114634.63,2,1,0,110114.38,1 +4923,15751203,Cattaneo,702,France,Male,26,5,56738.47,2,1,1,100442.22,1 +4924,15662658,Grieve,651,Germany,Male,34,2,90355.12,2,0,0,193597.94,0 +4925,15574868,Lowell,792,Germany,Male,36,5,115725.24,2,0,0,1871.25,0 +4926,15790282,Trentino,817,Germany,Male,58,3,114327.59,2,1,1,42831.11,0 +4927,15762927,Sung,674,Germany,Female,36,6,100762.64,1,1,0,182156.86,0 +4928,15803456,Yen,641,France,Female,40,9,0,1,0,0,151648.66,1 +4929,15771857,Philipp,513,Spain,Male,39,7,89039.9,2,1,1,146738.83,0 +4930,15700601,Dynon,561,France,Male,34,1,78829.53,1,1,1,12148.2,0 +4931,15569670,Alexeyeva,627,Germany,Male,30,6,112372.96,1,1,1,118029.09,0 +4932,15772341,Hs?eh,682,Germany,Male,81,6,122029.15,1,1,1,50783.88,0 +4933,15661548,Ferri,683,France,Female,29,0,157829.12,1,0,0,129891.66,0 +4934,15787597,Hsu,420,Germany,Female,31,1,108377.75,2,1,1,9904.63,0 +4935,15806913,Bishop,670,France,Female,54,2,95507.12,1,1,1,63213.31,0 +4936,15804862,Toscani,505,Germany,Male,43,6,127146.68,1,0,0,137565.87,0 +4937,15792986,T'ao,580,Germany,Male,24,1,133811.78,1,1,0,17185.95,1 +4938,15625632,Philip,577,France,Male,36,3,121092.47,2,0,1,143783.46,0 +4939,15727703,Li Fonti,773,Germany,Male,34,10,126979.75,1,0,0,36823.28,0 +4940,15606273,Rene,616,France,Male,37,5,144235.73,2,0,0,154957.66,1 +4941,15799652,Daigle,763,France,Female,38,0,152582.2,2,0,0,31892.82,0 +4942,15715047,Joshua,640,Spain,Male,43,9,172478.15,1,1,0,191084.4,1 +4943,15784687,Simmons,592,France,Male,36,1,126477.42,1,0,0,179718.17,0 +4944,15615322,Jamieson,528,Spain,Male,43,7,97473.87,2,1,1,159823.16,0 +4945,15722072,Hou,630,France,Male,53,5,138053.67,1,0,1,114110.97,0 +4946,15646784,Cochran,529,France,Female,31,2,164003.05,2,1,1,60993.23,0 +4947,15644692,Bibb,546,France,Female,47,8,0,1,1,1,66408.01,1 +4948,15670354,Jen,753,France,Female,62,6,0,2,1,1,136398.9,0 +4949,15716357,Corran,772,Spain,Female,39,4,122486.11,2,1,1,140709.25,0 +4950,15786717,He,567,France,Male,36,1,0,2,0,0,8555.73,0 +4951,15771383,Loggia,628,Germany,Female,45,6,53667.44,1,1,0,115022.94,0 +4952,15649793,Lovely,658,France,Male,20,7,0,2,0,0,187638.34,0 +4953,15731543,Becker,679,Spain,Male,58,9,109327.65,1,1,1,3829.13,0 +4954,15684516,Plascencia,629,Spain,Male,34,1,121151.05,1,0,0,119357.93,0 +4955,15677249,Somadina,731,Spain,Male,42,9,101043.63,1,1,1,192175.52,0 +4956,15581525,Walker,775,Germany,Male,33,3,83501.66,2,1,0,128841.31,0 +4957,15628420,Alekseeva,660,Spain,Male,33,2,80462.24,1,0,0,150422.35,0 +4958,15600478,Watson,752,France,Male,39,3,0,1,1,0,188187.05,0 +4959,15594502,Zotov,655,France,Male,37,6,109093.41,2,1,0,1775.52,0 +4960,15784361,Williamson,543,Spain,Female,46,5,140355.6,1,1,1,85086.78,0 +4961,15767626,Carpenter,811,France,Male,42,10,0,2,1,1,3797.79,0 +4962,15632521,Cattaneo,689,Germany,Male,45,0,130170.82,2,1,0,150856.38,0 +4963,15665088,Gordon,531,France,Female,42,2,0,2,0,1,90537.47,0 +4964,15652084,Boni,515,France,Male,40,0,109542.29,1,1,1,166370.81,0 +4965,15574761,Lynch,466,France,Female,41,3,33563.95,2,1,0,178994.13,1 +4966,15729515,McCarthy,782,France,Male,36,1,148795.17,2,1,1,195681.43,0 +4967,15682070,Davies,611,France,Male,64,9,0,2,1,1,53277.15,0 +4968,15743817,Hargreaves,621,Germany,Male,40,8,174126.75,3,1,0,172490.78,1 +4969,15572158,Blackburn,604,Spain,Male,41,3,0,1,0,0,11819.84,0 +4970,15584477,K?,655,Spain,Female,35,1,106405.03,1,1,1,82900.25,0 +4971,15614893,Meng,689,Spain,Male,38,2,0,1,1,1,82709.8,0 +4972,15665963,Cattaneo,681,Spain,Male,30,2,128393.29,1,1,1,180593.45,0 +4973,15612524,Hunt,643,Germany,Male,41,2,127841.52,1,1,0,172363.41,0 +4974,15596962,Owens,617,France,Female,24,4,137295.19,2,1,1,91195.12,0 +4975,15744942,Steele,638,Spain,Female,55,2,155828.22,1,0,1,108987.25,1 +4976,15573278,Kennedy,743,France,Male,39,6,0,2,1,0,44265.28,0 +4977,15717056,Pan,828,Germany,Female,25,7,144351.86,1,1,0,116613.26,0 +4978,15795881,Alexander,776,Spain,Male,35,8,106365.29,1,1,1,148527.56,0 +4979,15758939,Bray,540,Germany,Male,35,7,127801.88,1,0,1,84239.46,0 +4980,15792250,Nnabuife,616,Germany,Female,45,4,122793.96,1,1,1,62002.04,0 +4981,15740406,Padovesi,628,Germany,Male,38,10,113525.84,1,1,0,46044.48,1 +4982,15768137,Bray,667,Spain,Female,23,6,136100.69,2,0,0,169669.33,1 +4983,15569120,Lucas,615,France,Male,30,7,0,2,1,1,156346.84,0 +4984,15723721,Tinline,543,France,Male,30,4,140916.81,1,1,0,157711.18,0 +4985,15777122,Esomchi,553,France,Female,31,4,0,2,1,1,89087.4,0 +4986,15742681,Liao,554,Germany,Male,26,4,121365.39,1,1,1,8742.36,0 +4987,15582090,Iroawuchi,684,Spain,Female,36,4,0,1,1,0,117038.96,0 +4988,15711254,Retana,452,France,Female,35,7,0,2,1,0,164241.67,0 +4989,15775067,Fang,606,France,Male,47,3,93578.68,2,0,1,137720.56,1 +4990,15602851,Ozioma,629,France,Male,40,9,0,1,1,0,106.67,0 +4991,15802857,Robson,659,Spain,Female,33,8,115409.6,1,0,1,1539.21,0 +4992,15701175,Bruno,493,France,Female,33,8,90791.69,1,1,1,59659.53,0 +4993,15783019,Price,794,France,Female,62,9,123681.32,3,1,0,173586.63,1 +4994,15728912,Swanson,554,France,Female,44,6,92436.86,1,1,0,126033.9,0 +4995,15585580,Chang,796,Germany,Female,52,9,167194.36,1,1,1,62808.93,1 +4996,15583480,Morgan,807,France,Female,36,4,0,2,0,1,147007.33,0 +4997,15620341,Nwebube,500,Germany,Male,44,9,160838.13,2,1,0,196261.64,0 +4998,15613886,Trevisan,722,Spain,Male,43,1,0,1,1,0,44560.17,1 +4999,15792916,Ositadimma,559,Spain,Female,40,7,144470.77,1,1,1,18917.95,0 +5000,15710408,Cunningham,584,Spain,Female,38,3,0,2,1,1,4525.4,0 +5001,15598695,Fields,834,Germany,Female,68,9,130169.27,2,0,1,93112.2,0 +5002,15649354,Johnston,754,Spain,Male,35,4,0,2,1,1,9658.41,0 +5003,15737556,Vasilyev,590,France,Male,43,7,81076.8,2,1,1,182627.25,1 +5004,15671610,Hooper,740,France,Male,36,7,0,1,1,1,13177.4,0 +5005,15625092,Colombo,502,Germany,Female,57,3,101465.31,1,1,0,43568.31,1 +5006,15741032,Tsao,733,France,Male,48,5,0,1,0,1,117830.57,0 +5007,15750014,Chikere,755,Germany,Female,37,0,113865.23,2,1,1,117396.25,0 +5008,15784761,Ballard,554,Spain,Female,46,7,87603.35,3,0,1,96929.24,1 +5009,15768359,Akhtar,534,France,Male,36,4,120037.96,1,1,0,36275.94,0 +5010,15805769,O'Loughlin,656,Spain,Male,33,4,0,2,1,0,116706,0 +5011,15719508,Davis,575,Germany,Male,49,7,121205.15,4,1,1,168080.53,1 +5012,15609011,Barry,480,Spain,Male,47,8,75408.33,1,1,0,25887.89,1 +5013,15703106,K'ung,575,France,Male,40,5,0,2,1,1,122488.59,0 +5014,15626795,Gorman,672,France,Female,40,3,0,1,1,0,113171.61,1 +5015,15773731,John,758,Spain,Female,35,5,0,2,0,0,100365.51,0 +5016,15756196,Tsou,682,France,Male,50,6,121818.84,2,0,1,124151.37,0 +5017,15687903,Okonkwo,501,France,Female,29,8,0,2,1,0,112664.24,0 +5018,15777599,Esposito,746,Germany,Male,34,6,141806,2,1,1,183494.87,0 +5019,15754577,Boni,556,France,Female,51,8,61354.14,1,1,0,198810.65,1 +5020,15584113,Pratt,823,Germany,Female,53,4,124954.94,1,0,1,131259.6,1 +5021,15669589,Page,491,Germany,Female,68,1,95039.12,1,0,1,116471.14,1 +5022,15632793,Wilkinson,638,France,Female,29,9,103417.74,1,1,1,15336.4,0 +5023,15711130,Tseng,734,France,Male,45,2,0,2,1,0,99593.28,0 +5024,15615254,Clark,555,France,Male,40,10,43028.77,1,1,0,170514.21,0 +5025,15720583,Finch,745,Germany,Female,44,0,119638.21,1,1,1,34265.08,1 +5026,15780432,Shen,728,France,Male,37,3,122689.51,2,0,0,106977.53,1 +5027,15673223,Hou,626,France,Male,44,10,0,2,0,0,164287.86,0 +5028,15807989,Wall,681,Germany,Male,37,8,73179.34,2,1,1,25292.53,0 +5029,15761168,Manna,478,France,Female,38,4,171913.87,1,1,0,51820.87,1 +5030,15651272,Reyes,709,France,Male,38,5,0,2,1,1,81452.29,0 +5031,15812832,Jideofor,562,Germany,Male,33,8,92659.2,2,1,0,1354.25,0 +5032,15680517,Sal,769,Germany,Female,34,7,137239.17,1,1,1,71379.92,1 +5033,15750569,Iweobiegbunam,684,Germany,Female,46,3,102955.14,2,1,0,154137.33,0 +5034,15690743,Shao,536,France,Female,61,8,65190.29,1,1,1,64308.49,1 +5035,15627741,Heath,631,Germany,Female,29,2,96863.52,2,1,1,31613.35,0 +5036,15712121,Chidimma,657,Spain,Male,34,5,154983.98,1,1,0,27738.01,0 +5037,15805429,Murray,699,Germany,Male,59,3,106819.65,1,0,1,163570.25,0 +5038,15814923,Sullivan,606,Spain,Male,38,7,128578.52,1,1,1,193878.51,0 +5039,15589230,Wu,612,France,Female,63,2,126473.33,1,0,1,147545.65,0 +5040,15775490,Downie,660,France,Female,38,5,110570.78,2,1,0,195906.59,0 +5041,15749727,Chukwufumnanya,829,Spain,Male,50,7,0,2,0,1,178458.86,0 +5042,15619238,Allan,567,Spain,Male,29,8,0,2,1,0,156125.72,0 +5043,15593468,Findlay,850,France,Female,33,3,0,2,1,1,11159.19,0 +5044,15718454,Ch'eng,712,Spain,Female,44,2,0,2,0,0,45738.94,0 +5045,15789498,Miller,562,France,Male,30,3,111099.79,2,0,0,140650.19,0 +5046,15744691,Tsai,755,France,Female,29,3,0,3,1,0,4733.94,0 +5047,15708289,Graham,793,Spain,Male,25,3,100913.57,1,0,0,10579.72,0 +5048,15790412,Norton,471,Spain,Male,26,8,0,2,1,1,179655.87,0 +5049,15741416,Yegorov,707,France,Male,42,2,16893.59,1,1,1,77502.56,0 +5050,15598894,Holt,784,Spain,Male,38,10,122267.85,1,0,0,145759.93,0 +5051,15663294,Kao,703,France,Male,32,1,125685.79,1,1,1,56246.72,0 +5052,15572728,Ross,704,Spain,Male,36,8,127397.34,1,1,0,151335.24,0 +5053,15706729,Hsiao,662,France,Male,38,0,105271.56,1,0,1,179833.45,0 +5054,15674433,Allan,636,Germany,Female,28,2,115265.14,1,0,0,191627.85,0 +5055,15641170,Liang,640,Spain,Male,36,4,0,1,0,0,173016.46,0 +5056,15806284,Briggs,739,Spain,Male,31,1,0,2,1,1,58469.75,0 +5057,15690958,Cantrell,767,Germany,Male,23,2,139542.82,1,0,1,28038.28,0 +5058,15606386,Wang,753,Germany,Female,46,3,111512.75,3,1,0,159576.75,1 +5059,15682322,Aksenov,714,France,Male,37,9,148466.93,2,0,1,151280.96,0 +5060,15579915,Glennon,707,France,Male,29,4,0,2,1,0,139953.94,0 +5061,15681928,Yancy,577,France,Female,35,4,108155.49,1,1,0,105407.79,0 +5062,15734005,Mazzi,633,France,Female,42,1,0,2,1,0,56865.62,0 +5063,15650432,Liu,849,Germany,Male,41,10,84622.13,1,1,1,198072.16,0 +5064,15592578,Nucci,614,Spain,Female,41,7,146997.64,2,0,0,137791.18,0 +5065,15671243,Y?,558,France,Female,47,9,0,2,1,0,103787.28,0 +5066,15775709,Nucci,832,France,Female,27,10,98590.25,1,1,0,30912.89,0 +5067,15702631,Tang,567,France,Female,26,2,0,2,1,1,78651.55,0 +5068,15602282,Kao,587,Germany,Female,45,8,134980.74,1,1,1,123309.57,1 +5069,15717879,Chen,712,Spain,Female,79,5,108078.56,1,1,1,174118.93,0 +5070,15740878,Yao,655,Spain,Female,29,9,0,2,0,1,85736.26,0 +5071,15794468,Tsou,641,France,Female,42,6,0,2,0,0,121138.77,0 +5072,15773277,Barnes,676,France,Male,35,5,106836.67,2,1,0,84199.78,0 +5073,15572657,H?,472,France,Male,29,8,102490.27,1,0,1,181224.56,0 +5074,15800295,Cruz,644,Germany,Male,34,9,112746.54,2,0,0,141230.07,0 +5075,15672397,Smith,598,France,Male,38,0,125487.89,1,0,0,158111.71,0 +5076,15684921,Onuchukwu,792,Spain,Male,25,8,142862.21,1,1,1,130639.01,0 +5077,15720676,Bukowski,700,France,Female,37,7,0,2,1,0,17040.82,0 +5078,15731829,Simmons,616,France,Male,34,10,0,2,1,0,25662.27,0 +5079,15732672,Stewart,743,Spain,Male,35,6,79388.33,1,1,1,193360.69,0 +5080,15692406,Gow,427,France,Male,37,5,0,2,1,1,121485.1,0 +5081,15764405,Williams,731,France,Male,29,10,0,2,1,1,162452.65,0 +5082,15757537,Francis,610,France,Female,31,6,107784.65,1,1,1,141137.53,0 +5083,15793307,Calabresi,724,Spain,Female,41,4,142880.28,3,0,0,185541.2,1 +5084,15660679,Chimaobim,653,Spain,Female,38,9,149571.94,1,1,0,118383.18,0 +5085,15666856,Chikwendu,774,France,Male,49,1,142767.39,1,1,1,8214.41,0 +5086,15687372,Padovesi,547,Germany,Male,49,8,121537.71,2,1,0,46521.45,1 +5087,15667289,Henderson,719,Spain,Male,50,2,0,2,0,0,10772.13,0 +5088,15624641,Kharlamova,740,Spain,Male,43,9,0,1,1,0,199290.68,1 +5089,15734610,Onio,543,France,Male,42,4,89838.71,3,1,0,85983.54,1 +5090,15631882,Yeh,688,Germany,Male,45,9,103399.87,1,0,0,129870.93,0 +5091,15642709,Feng,474,France,Female,30,9,0,2,0,0,63158.22,0 +5092,15811026,Norman,505,Germany,Male,43,5,136855.94,2,1,0,171070.52,0 +5093,15596303,White,688,France,Female,39,0,0,2,1,0,53222.15,1 +5094,15787255,Manfrin,650,Germany,Female,55,2,140891.46,3,1,1,179834.45,1 +5095,15617166,Ritchie,610,France,Male,37,0,0,1,1,0,114514.64,0 +5096,15742442,Udegbulam,705,Spain,Female,46,5,89364.91,1,0,1,139162.15,0 +5097,15758692,Kao,669,France,Female,29,7,146011.4,1,0,0,50249.16,0 +5098,15568238,Diaz,650,Spain,Male,20,8,0,2,1,1,113469.65,0 +5099,15730353,Olisaemeka,550,Germany,Male,29,9,145294.08,2,1,0,147484.13,0 +5100,15731555,Ross-Watt,595,Germany,Female,45,9,106000.12,1,0,0,191448.96,1 +5101,15582404,Miller,572,Spain,Female,26,5,0,2,1,0,119381.41,0 +5102,15721462,Shubin,622,Spain,Female,58,2,0,2,1,1,33277.31,0 +5103,15632899,Nwankwo,662,Spain,Male,20,9,104508.77,2,0,0,73107.53,0 +5104,15808526,Cartwright,783,Germany,Female,58,3,127539.3,1,1,1,96590.39,1 +5105,15694349,Ngozichukwuka,714,Spain,Male,44,7,0,1,0,1,6923.11,0 +5106,15718465,Sadler,671,Germany,Male,51,3,96891.46,1,1,0,176403.33,1 +5107,15682995,Azuka,600,France,Female,32,1,78535.25,1,1,0,64349.6,0 +5108,15584776,Shen,847,Spain,Female,37,9,112712.17,1,1,0,116097.26,0 +5109,15777772,Whittaker,650,Spain,Male,55,9,119618.42,1,1,1,29861.13,0 +5110,15576156,Abazu,710,Spain,Female,28,6,0,1,1,0,48426.98,0 +5111,15646756,Murphy,682,France,Female,33,8,74963.5,1,1,1,32770.56,0 +5112,15742886,Ford,642,France,Male,26,1,138023.79,2,0,1,117060.2,0 +5113,15586135,Gratwick,536,Spain,Female,28,4,0,1,1,1,136197.65,0 +5114,15616152,Pai,754,France,Female,47,1,185513.67,1,1,0,27438.83,0 +5115,15721460,Lorenzo,678,France,Male,60,8,185648.56,1,0,0,192156.54,1 +5116,15727317,Brady,533,Germany,Female,49,1,102286.6,3,1,0,69409.37,1 +5117,15649536,Wong,741,Germany,Male,38,4,128015.83,1,1,0,58440.43,0 +5118,15754929,Douglas,757,France,Male,31,10,39539.39,2,0,0,192519.39,0 +5119,15572051,Kennedy,721,France,Male,40,3,0,1,1,1,144874.67,0 +5120,15668142,Chang,700,France,Male,37,3,77608.46,2,1,1,175373.46,0 +5121,15701176,Brown,663,France,Male,26,5,141462.13,1,1,0,440.2,0 +5122,15708422,Hsiung,677,Spain,Female,35,0,0,2,0,0,76637.38,0 +5123,15655632,MacDonald,655,France,Male,27,2,131691.33,1,1,0,49480.66,0 +5124,15744606,Davidson,832,Spain,Male,29,8,93833.86,1,0,1,10417.87,0 +5125,15612140,Milano,721,Spain,Female,46,7,137933.39,1,1,1,67976.57,0 +5126,15656086,Bovee,542,Spain,Male,54,8,105770.14,1,0,1,140929.98,1 +5127,15655298,Lewis,654,Spain,Female,54,5,0,2,0,1,47139.06,0 +5128,15644796,Dyer,821,Spain,Female,38,8,0,2,0,1,126241.4,1 +5129,15726250,Hsia,508,France,Female,38,3,166328.65,2,0,1,22614.19,0 +5130,15764432,Hicks,588,Germany,Female,42,2,164307.77,1,1,0,48498.19,0 +5131,15631721,Millar,691,Germany,Male,38,9,163965.69,2,0,1,103511.26,0 +5132,15707479,Fan,664,France,Male,40,7,125608.72,1,1,0,122073.48,0 +5133,15579826,Young,439,France,Female,66,9,0,1,1,0,65535.56,0 +5134,15668104,Kerr,479,Spain,Male,37,6,118433.94,1,0,1,160060.9,0 +5135,15641604,Frolova,850,France,Female,55,10,98488.08,1,1,0,155879.57,1 +5136,15587240,Vasilyev,518,France,Male,40,4,0,2,0,1,194416.58,0 +5137,15680767,Sabbatini,717,Germany,Female,64,10,98362.35,2,1,1,21630.21,0 +5138,15601594,Ifeanacho,698,France,Female,51,6,144237.91,4,1,0,157143.61,1 +5139,15589969,Capon,850,France,Male,34,6,0,1,0,1,52796.31,0 +5140,15703728,Chieloka,700,Spain,Male,47,4,0,1,1,0,121798.52,1 +5141,15617790,Hanson,626,France,Female,29,4,105767.28,2,0,0,41104.82,0 +5142,15662500,Ts'ao,774,Spain,Male,32,9,0,2,1,0,10604.48,0 +5143,15778526,Bradshaw,719,Spain,Female,48,5,0,2,0,0,78563.66,0 +5144,15670584,Nkemakolam,646,Spain,Male,31,2,0,1,1,1,170821.43,1 +5145,15748069,Clunie,485,France,Female,25,3,134467.26,1,1,1,113266.09,0 +5146,15680597,Cover,784,Germany,Male,38,1,138515.02,1,1,1,171768.76,0 +5147,15628992,Esposito,850,Germany,Male,32,2,128647.98,2,0,0,54416.18,0 +5148,15719624,Hodgson,669,France,Female,38,9,121858.98,1,1,0,130755.34,0 +5149,15812767,Harvey,731,Spain,Male,70,3,0,2,1,1,141180.66,0 +5150,15689201,Dobie,721,France,Female,49,1,120108.56,1,0,1,183421.76,0 +5151,15614716,Okwudilichukwu,515,France,Female,37,0,196853.62,1,1,1,132770.11,0 +5152,15683618,Dyer,774,France,Female,35,3,121418.62,1,1,1,24400.37,0 +5153,15799631,Chase,585,Spain,Male,36,10,0,2,1,1,180318.6,0 +5154,15692259,Baresi,695,France,Female,29,9,0,2,1,0,111565.45,0 +5155,15590966,Lo,729,Germany,Female,42,4,97495.8,2,0,0,2002.5,0 +5156,15656426,Tyler,713,France,Female,42,3,0,2,0,0,82565.01,0 +5157,15675256,Ts'ui,555,Spain,Male,33,5,127343.4,1,0,1,121789.3,0 +5158,15751185,Aparicio,699,Spain,Female,50,0,158633.61,1,1,0,193785.87,0 +5159,15789582,Macleod,587,France,Male,55,9,0,1,1,0,64593.07,0 +5160,15651103,Sal,762,Spain,Female,69,9,183744.98,1,1,1,196993.69,0 +5161,15672299,Yeh,510,France,Male,44,6,0,2,1,1,175518.31,0 +5162,15772250,Udegbunam,842,Spain,Male,46,9,0,1,0,0,17268.02,0 +5163,15763922,Alexandrov,608,France,Male,31,7,79962.92,2,1,0,60901.72,0 +5164,15633870,Ozioma,850,France,Female,36,10,0,2,1,1,100750.03,0 +5165,15624323,Atkins,642,France,Male,36,4,0,2,1,1,195224.91,0 +5166,15688612,Campos,850,France,Male,33,7,140956.99,1,0,0,3510.18,0 +5167,15694644,Wood,455,Spain,Female,43,6,0,1,1,1,81250.79,0 +5168,15587174,Kerr,726,France,Male,29,7,0,2,1,1,91844.14,1 +5169,15579559,Chienezie,544,Spain,Male,30,8,145241.63,1,1,1,80676.83,0 +5170,15775430,Tsou,651,Germany,Male,31,7,138008.06,2,1,0,129912.74,0 +5171,15623695,McKinnon,814,France,Female,31,4,0,2,1,1,142029.17,0 +5172,15760849,Nwachukwu,537,France,Male,39,2,0,2,1,1,137651.6,0 +5173,15813095,Nwebube,553,France,Male,37,2,0,2,1,0,33877.29,0 +5174,15705281,Burt,800,Spain,Male,38,9,0,1,1,0,78744.39,0 +5175,15812594,Ross,791,France,Male,34,7,0,2,1,0,96734.46,0 +5176,15626322,Lees,699,Spain,Female,29,9,127570.93,2,1,0,164756.81,0 +5177,15723105,Feetham,756,France,Female,28,6,0,1,1,1,164394.65,0 +5178,15588449,Chuang,591,Spain,Female,27,5,107812.67,1,0,1,162501.83,1 +5179,15794849,Aitken,850,Germany,Male,22,7,91560.58,2,0,0,10541.38,0 +5180,15620000,Chambers,760,Germany,Male,34,6,121303.77,2,1,1,59325.21,0 +5181,15799720,Coburn,569,Spain,Male,43,8,161546.68,2,0,1,178187.28,0 +5182,15711287,Ahmed,661,Spain,Female,35,5,128415.45,1,1,0,142626.49,0 +5183,15613102,Ogochukwu,670,France,Female,31,2,57530.06,1,1,1,181893.31,1 +5184,15621440,Soto,694,France,Male,38,1,0,2,0,1,156858.2,0 +5185,15677146,Obiajulu,728,France,Female,28,4,142243.54,2,1,0,33074.51,0 +5186,15801169,Yegorova,764,Germany,Female,39,9,138341.51,1,1,0,50072.94,1 +5187,15722425,Lucchese,639,France,Male,32,9,0,2,1,0,111340.36,0 +5188,15682421,Talbot,683,France,Female,30,2,0,2,0,1,100496.84,1 +5189,15691910,Lu,663,Spain,Male,30,4,0,3,1,0,101371.05,0 +5190,15721779,Arnold,826,Spain,Male,41,5,146466.46,2,0,0,180934.67,0 +5191,15579548,Nicholson,735,Spain,Male,36,5,0,2,1,0,105152.17,0 +5192,15681075,Chukwualuka,682,France,Female,58,1,0,1,1,1,706.5,0 +5193,15607884,Wallace,663,France,Female,39,8,0,2,1,1,101168.9,0 +5194,15767757,Pisano,562,Spain,Female,29,9,120307.58,1,1,1,6795.61,0 +5195,15791550,Kelly,696,France,Male,27,4,87637.26,2,0,0,196111.35,0 +5196,15658589,Brady,850,Spain,Male,38,2,94652.04,1,1,1,171960.76,0 +5197,15670822,Palmer,719,France,Female,22,7,114415.84,1,1,1,177497.4,0 +5198,15629744,Tan,804,France,Female,71,8,0,2,0,1,147995.96,0 +5199,15660768,L?,604,France,Male,40,1,84315.02,1,0,0,36209.1,0 +5200,15726310,Mordvinova,782,Spain,Female,27,3,0,2,1,0,143614.01,0 +5201,15641298,Corones,512,Germany,Male,42,9,93955.83,2,1,0,14828.54,0 +5202,15625675,Clements,569,France,Male,36,1,67087.69,1,1,0,154775.7,0 +5203,15713354,Morrice,597,Germany,Female,22,6,101528.61,1,1,0,70529,1 +5204,15633866,Hsiung,753,Germany,Male,30,1,110824.52,1,1,1,57896.27,0 +5205,15704231,Barrett,430,France,Female,33,8,0,1,1,1,69759.91,0 +5206,15735400,Kanayochukwu,756,France,Male,28,8,179960.2,1,1,0,89938.08,0 +5207,15632826,Tardent,493,France,Male,38,3,134006.77,1,1,0,89578.32,0 +5208,15751022,Bowhay,777,Germany,Female,37,10,121532.17,2,1,1,73464.88,0 +5209,15664737,Lei,779,Spain,Female,38,7,0,2,1,1,138542.87,0 +5210,15681126,Baker,702,Spain,Female,38,2,0,1,1,1,161888.63,0 +5211,15738954,Pisano,551,France,Male,35,7,129717.3,2,0,0,86937.2,0 +5212,15662263,Castillo,749,Germany,Male,22,4,94762.16,2,1,1,42241.54,0 +5213,15621611,Gibson,742,Germany,Male,55,5,155196.17,1,0,1,121207.66,1 +5214,15783752,Lindsay,752,Germany,Male,29,4,129514.99,1,1,1,102930.46,0 +5215,15709474,Macnamara,740,Germany,Female,57,3,113386.36,2,1,1,65121.63,1 +5216,15701280,Romano,576,France,Male,24,3,0,1,0,1,78498.04,1 +5217,15671104,Aksakova,637,Spain,Male,43,3,172196.23,1,1,1,104769.96,0 +5218,15796434,Farnsworth,724,France,Male,28,5,97612.12,1,1,1,96498.14,0 +5219,15781505,Giordano,685,France,Male,20,4,104719.94,2,1,0,38691.34,0 +5220,15625819,Arnold,625,France,Female,38,7,0,1,1,0,164804.02,0 +5221,15753174,Thompson,571,Germany,Male,37,9,139592.98,3,1,0,104152.65,1 +5222,15654067,Koch,584,Spain,Female,29,4,0,2,1,0,88866.92,0 +5223,15724719,Jones,550,France,Female,22,7,139096.85,1,1,0,129890.94,0 +5224,15624695,Otitodilinna,662,Spain,Female,72,7,140301.72,1,0,1,179258.67,0 +5225,15718216,Fleetwood-Smith,803,Spain,Male,43,3,0,1,1,0,72051.44,0 +5226,15586300,Chinonyelum,615,France,Male,66,7,0,2,1,1,74580.8,0 +5227,15783349,Montague,481,Spain,Male,39,1,111233.09,1,1,1,123995.15,0 +5228,15725767,Milani,701,France,Male,23,3,0,2,1,0,38960.59,0 +5229,15791925,Palermo,751,France,Male,29,10,147737.63,1,0,1,94951.27,0 +5230,15793585,Anderson,675,France,Male,35,8,0,2,1,1,56642.97,0 +5231,15576641,Crawford,733,Germany,Male,40,5,125725.02,2,1,1,50783.1,0 +5232,15749519,Lin,822,France,Male,38,6,128289.7,3,1,0,9149.96,1 +5233,15684960,Yewen,559,France,Female,46,5,0,1,1,0,21006.1,1 +5234,15591286,Simmons,731,Germany,Female,49,4,88826.07,1,1,1,33759.41,1 +5235,15668323,Mbadiwe,678,France,Female,41,1,143443.61,1,1,0,196622.28,1 +5236,15608528,Munro,645,France,Female,68,9,0,4,1,1,176353.87,1 +5237,15645184,Graham,701,France,Male,29,2,0,2,1,0,176943.59,0 +5238,15702566,Lombardo,554,Spain,Male,26,8,149134.46,1,1,1,177966.24,0 +5239,15660840,Kalinin,723,France,Male,30,3,124119.54,1,1,0,162198.32,0 +5240,15750811,Woodward,766,Germany,Male,44,3,116822.7,1,0,0,197643.24,0 +5241,15733842,Pirozzi,597,France,Female,24,1,103219.47,1,1,0,60420.07,0 +5242,15581526,Iweobiegbulam,574,France,Male,41,1,0,2,0,0,70550,0 +5243,15662751,Piazza,655,Germany,Female,40,0,81954.6,1,1,1,198798.44,1 +5244,15684319,Baranova,780,Germany,Female,37,10,95196.26,1,1,0,126310.39,1 +5245,15702190,Fan,672,Spain,Male,43,5,0,2,1,1,64515.5,0 +5246,15588517,Sun,717,France,Male,38,7,0,2,1,1,158580.05,0 +5247,15801863,Marino,521,France,Female,32,2,136555.01,2,1,1,129353.21,0 +5248,15584271,Donaldson,633,France,Male,59,5,0,1,1,1,137273.97,0 +5249,15700366,Burton,669,France,Male,39,3,119452.03,1,1,1,171575.54,0 +5250,15804038,Quinn,740,France,Male,44,9,0,1,0,1,96528,1 +5251,15720820,Sabbatini,462,Germany,Female,24,9,69881.09,2,0,1,64421.02,0 +5252,15743759,Brooks,619,France,Male,39,5,0,2,1,1,158444.61,0 +5253,15749947,Black,665,France,Female,44,7,0,2,1,1,66548.58,0 +5254,15670496,Schwartz,655,Spain,Female,27,9,0,2,0,0,108008.05,0 +5255,15746664,Ts'ui,463,Spain,Male,20,8,204223.03,1,1,0,128268.39,0 +5256,15745533,Sargent,799,France,Female,63,1,110314.21,2,1,0,37464,1 +5257,15761497,Udinesi,713,Spain,Female,48,1,163760.82,1,0,0,157381.14,1 +5258,15628600,Lee,807,Germany,Female,31,1,141069.18,3,1,1,194257.11,0 +5259,15627002,Taylor,728,France,Male,38,1,115934.74,1,1,1,139059.05,0 +5260,15614635,Kepley,582,France,Male,52,2,151457.88,1,0,1,40893.61,0 +5261,15731281,Ozuluonye,704,Germany,Female,35,3,154206.07,2,1,1,40261.49,0 +5262,15814022,Lassetter,714,France,Female,26,9,89928.99,1,1,0,46203.31,0 +5263,15659194,Mishina,628,France,Male,30,8,89182.09,1,1,1,13126.9,0 +5264,15745030,Trevisano,809,Germany,Male,41,1,79706.25,2,1,0,165675.01,0 +5265,15691817,Iloerika,547,Spain,Female,44,5,0,3,0,0,5459.07,1 +5266,15707488,Tan,560,France,Female,27,5,0,2,1,0,131919.48,0 +5267,15784700,Chikelu,811,France,Male,31,7,117799.28,1,1,1,182372.35,0 +5268,15710397,Lin,584,France,Male,26,4,0,2,1,0,147600.54,0 +5269,15687648,Nicholson,691,France,Male,28,1,0,2,0,0,92865.41,0 +5270,15732281,Ugoji,680,Germany,Male,34,6,146422.22,1,1,0,67142.97,1 +5271,15607230,Michel,588,Germany,Male,33,9,150186.22,2,1,1,65611.01,0 +5272,15567630,Bruce,721,Germany,Male,40,6,100275.88,1,1,0,138564.48,1 +5273,15587507,Feng,850,France,Male,47,6,0,1,1,0,187391.02,1 +5274,15733904,McDonald,529,France,Male,32,9,147493.89,1,1,0,33656.35,0 +5275,15709511,Watt,622,France,Male,43,8,0,2,1,0,100618.17,0 +5276,15579616,Goodwin,683,France,Female,42,8,0,2,0,1,198134.9,0 +5277,15694852,Arcuri,575,France,Male,29,4,121823.4,2,1,1,50368.87,0 +5278,15589924,Rapuluolisa,577,Spain,Female,40,1,0,2,1,1,108787,0 +5279,15799300,Kao,510,Germany,Male,31,0,113688.63,1,1,0,33099.41,1 +5280,15731330,Tsui,652,Spain,Female,40,7,100471.34,1,1,1,124550.88,0 +5281,15694129,Summers,569,Germany,Female,28,3,100032.52,1,1,0,5159.21,1 +5282,15620372,Cross,687,Spain,Male,31,3,0,2,0,0,48228.1,0 +5283,15744622,Osorio,822,France,Male,32,8,116358,1,1,0,108798.36,0 +5284,15799815,Bobrov,656,Germany,Female,23,4,163549.63,1,0,1,21085.12,0 +5285,15759250,Barnett,745,Germany,Male,51,3,99183.9,1,1,1,28922.25,0 +5286,15732643,Pike,386,Spain,Female,53,1,131955.07,1,1,1,62514.65,1 +5287,15690540,Gearheart,684,Spain,Female,41,1,134177.06,1,0,0,177506.66,0 +5288,15803078,Bruno,635,Spain,Female,38,1,0,2,1,0,90605.05,0 +5289,15652180,Egobudike,582,France,Male,30,2,0,2,1,1,132029.95,0 +5290,15741195,Okechukwu,613,Spain,Male,19,5,0,1,1,1,176903.35,0 +5291,15743490,Zikoranachidimma,795,Germany,Female,56,9,94348.94,1,1,0,29239.29,1 +5292,15575510,Milanesi,659,France,Female,32,2,155584.21,1,0,1,153662.88,0 +5293,15732610,Ahern,745,France,Female,28,6,0,2,1,0,154389.18,0 +5294,15602909,Dickson,604,Spain,Female,41,10,0,2,1,1,166224.39,0 +5295,15734058,Anayochukwu,509,Germany,Male,32,9,170661.47,1,1,1,21646.2,0 +5296,15801788,McDonald,706,Germany,Female,29,6,185544.36,1,1,0,171037.63,0 +5297,15702462,Fiorentini,619,Spain,Female,44,6,52831.13,1,1,1,112649.22,1 +5298,15683416,Russo,572,Germany,Male,51,8,97750.07,3,1,1,193014.26,1 +5299,15794187,Young,695,France,Male,36,6,114007.5,2,1,0,118120.88,0 +5300,15792989,Bianchi,543,France,Female,71,1,104308.77,1,1,1,25650.04,0 +5301,15613734,Fallaci,640,France,Female,33,6,84719.13,2,1,1,113048.79,0 +5302,15606177,Crawford,672,France,Male,39,2,0,2,1,0,87372.49,0 +5303,15636700,Marsh,701,France,Male,39,9,140236.98,1,0,1,146651.99,0 +5304,15645766,Kosisochukwu,634,Spain,Male,25,9,0,2,1,1,8227.91,0 +5305,15671345,Piccio,531,Spain,Female,42,6,75302.85,2,0,0,57034.35,0 +5306,15652469,Nevels,699,France,Male,27,1,0,2,1,0,93003.21,0 +5307,15749638,Kaodilinakachukwu,605,France,Female,51,9,104760.82,1,1,1,165574.54,1 +5308,15728706,Amaechi,534,France,Female,49,7,0,1,1,0,13566.48,1 +5309,15735439,P'an,449,Spain,Female,31,1,113693,1,0,0,82796.29,0 +5310,15778696,Ikemefuna,684,Spain,Female,36,5,174180.39,1,1,0,119830.08,0 +5311,15624744,Tai,622,Germany,Male,42,9,115766.26,1,0,0,72155.85,1 +5312,15584338,Winn,714,France,Female,40,0,0,2,1,0,62762.12,0 +5313,15726178,Hardy,712,Spain,Female,48,8,0,2,1,0,183235.33,0 +5314,15794939,Chiu,783,France,Female,72,5,121215.9,2,1,1,105206.48,0 +5315,15788068,Lopez,743,Germany,Male,45,10,144677.19,3,1,0,22512.44,1 +5316,15572956,Steen,683,France,Male,36,5,115350.63,1,1,1,122305.91,0 +5317,15780386,Ferri,654,Spain,Male,40,5,105683.63,1,1,0,173617.09,0 +5318,15791114,Yegorova,700,France,Male,37,1,135179.49,1,1,0,160670.37,0 +5319,15708046,Knowles,744,Spain,Male,31,0,117551.23,1,1,0,158958.9,0 +5320,15719779,May,645,Germany,Male,25,1,157404.02,2,1,0,93073.04,0 +5321,15591550,Bianchi,525,Spain,Male,36,3,77910.23,1,1,0,67238.01,0 +5322,15639368,Pipes,732,France,Male,25,0,110942.9,1,0,0,172576.56,0 +5323,15699830,Doherty,721,France,Female,40,7,0,2,1,1,122580.48,0 +5324,15569264,Yobanna,622,France,Male,32,5,179305.09,1,1,1,149043.78,0 +5325,15595158,Hsu,654,Germany,Male,31,5,150593.59,2,1,1,105218.45,0 +5326,15599126,Russell,529,France,Female,43,0,123815.86,1,1,1,78463.99,1 +5327,15650575,Payne,720,Spain,Female,59,6,0,2,1,1,160849.43,1 +5328,15641490,Windsor,850,Germany,Female,25,8,69385.17,2,1,0,87834.24,0 +5329,15680234,Bray,667,Germany,Male,27,2,138032.15,1,1,0,166317.71,0 +5330,15592230,Seleznyov,620,France,Male,41,3,0,2,1,1,137309.06,0 +5331,15626212,Wark,616,France,Male,29,9,0,1,1,1,166984.44,0 +5332,15700627,Y?,637,Germany,Female,46,2,143500.82,1,1,0,166996.46,1 +5333,15782641,Brown,710,Spain,Female,29,3,119670.18,1,1,0,188022.44,0 +5334,15784445,Huang,717,Spain,Male,33,1,99106.73,1,0,0,194467.23,0 +5335,15813681,Zito,786,Germany,Male,24,2,120135.55,2,1,1,125449.47,0 +5336,15596649,Bailey,651,France,Female,39,8,0,1,1,0,137452.57,0 +5337,15700460,Allnutt,530,France,Female,55,4,120905.03,1,0,1,123475.88,1 +5338,15724076,Christie,815,Spain,Female,57,5,0,3,0,0,38941.44,1 +5339,15784000,Pope,715,Germany,Female,34,9,102277.52,1,0,0,177852.57,1 +5340,15733966,Johnstone,496,Germany,Female,55,4,125292.53,1,1,1,31532.96,1 +5341,15612667,Bird,680,Spain,Male,42,0,0,1,1,0,136377.21,0 +5342,15654025,Jones,646,France,Female,51,4,101629.3,1,0,0,130541.1,0 +5343,15589431,Pedder,807,Germany,Male,47,1,171937.27,1,1,1,65636.92,0 +5344,15578238,Calabrese,727,France,Male,47,7,0,2,1,0,193305.35,0 +5345,15566269,Chialuka,787,France,Male,25,5,0,2,1,0,47307.9,0 +5346,15639217,McKenzie,806,France,Male,34,6,0,2,0,0,100809.99,0 +5347,15688644,Holloway,603,France,Male,31,1,129743.75,1,1,0,109145.2,0 +5348,15662426,Tang,649,Spain,Male,32,1,0,1,0,1,91167.19,1 +5349,15720511,Byrne,547,Germany,Male,41,3,151191.31,1,1,0,175295.89,1 +5350,15567246,Selwyn,684,Germany,Male,32,3,102630.13,2,1,1,127433.47,0 +5351,15647965,Genovese,477,France,Female,57,9,114023.64,2,1,1,71167.17,1 +5352,15679048,Koger,558,Germany,Male,41,2,124227.14,1,1,1,111184.67,0 +5353,15675749,Baranov,695,France,Female,23,1,0,2,1,1,141756.32,0 +5354,15782181,Greco,592,Spain,Male,35,6,80285.16,1,1,0,72678.75,1 +5355,15795738,Owens,789,France,Male,31,4,175477.15,1,1,1,172832.9,0 +5356,15773751,Y?,597,France,Female,29,1,132144.35,1,1,0,158086.33,0 +5357,15655436,Kendall,839,Germany,Male,47,2,136911.07,1,1,1,168184.62,1 +5358,15691396,Ko,405,Germany,Male,31,5,133299.67,2,1,1,72950.14,0 +5359,15796958,Tang,658,France,Male,39,7,0,2,1,0,48378.4,0 +5360,15801832,Lombardo,684,Germany,Male,42,1,117691,1,1,1,23135.65,1 +5361,15661349,Perkins,633,France,Male,35,10,0,2,1,0,65675.47,0 +5362,15719265,Feng,589,France,Male,46,9,0,2,1,0,170676.67,0 +5363,15779985,Lo,750,Germany,Female,37,1,133199.71,2,1,1,27366.77,0 +5364,15663410,Piccio,771,Spain,Male,51,5,135506.58,3,1,1,152479.64,1 +5365,15704144,Mazzanti,812,Germany,Male,33,2,127154.14,2,0,1,105383.49,0 +5366,15774104,Chukwualuka,539,Spain,Male,39,2,0,2,1,1,48189.94,0 +5367,15812230,Elliot,670,Germany,Female,42,5,49508.79,3,1,1,100324.01,0 +5368,15742848,Gratton,673,France,Male,41,5,0,1,1,1,65657.29,0 +5369,15745326,Carandini,538,France,Female,62,3,75051.49,1,0,0,17682.02,1 +5370,15674541,Robinson,575,Spain,Male,52,8,123925.23,1,0,0,111342.66,1 +5371,15728564,Lo,682,France,Male,41,6,0,2,0,1,134158.09,1 +5372,15580701,Ma,712,France,Male,33,3,153819.58,1,1,0,79176.09,1 +5373,15688973,Vinogradova,598,Spain,Female,39,5,0,2,1,1,83103.46,0 +5374,15709412,H?,776,Spain,Male,30,6,0,2,0,1,63908.86,0 +5375,15607753,Alexandrova,606,Spain,Female,23,10,70417.79,1,0,1,90896.04,0 +5376,15705352,Yang,686,Spain,Male,38,7,111484.88,1,1,1,76076.2,0 +5377,15602500,Maslova,850,Spain,Male,38,1,146343.98,1,0,1,103902.11,0 +5378,15672437,Buccho,642,France,Male,72,1,160541,2,1,1,142223.94,0 +5379,15720968,Young,606,Germany,Male,27,2,130274.26,2,1,0,147533.09,0 +5380,15730796,Barker,627,France,Female,21,7,98993.02,1,1,1,169156.64,0 +5381,15768219,Sung,850,Spain,Male,36,0,0,2,1,0,141242.57,0 +5382,15663883,Hansen,850,Germany,Male,32,9,141827.33,2,1,1,149458.73,0 +5383,15589296,Brown,724,France,Female,40,6,110054.45,1,1,1,86950.72,0 +5384,15586425,Lo Duca,579,France,Male,28,4,0,2,1,1,176925.69,0 +5385,15679813,Ellis,727,Spain,Male,28,1,0,1,1,0,40357.39,0 +5386,15681410,Korff,813,Germany,Female,36,6,98088.09,1,0,1,26687.22,1 +5387,15668283,Gardiner,642,France,Male,48,9,118317.27,4,0,0,78702.98,1 +5388,15624072,Kiernan,669,Spain,Male,22,10,0,2,1,0,176163.74,0 +5389,15669664,Thompson,574,Germany,Male,54,1,99774.5,1,0,0,4896.11,1 +5390,15682728,Mathews,774,France,Female,32,4,0,2,0,0,114899.13,0 +5391,15573851,Macrossan,735,France,Female,38,1,0,3,0,0,92220.12,1 +5392,15733661,Illingworth,639,Spain,Female,27,8,133806.54,2,1,0,6251.3,0 +5393,15710012,Bowen,738,Spain,Male,44,2,0,2,1,0,43018.82,1 +5394,15763327,Craig,835,France,Male,32,8,124993.29,2,1,1,27548.06,0 +5395,15668853,Menhennitt,637,Spain,Female,44,0,157622.58,1,1,1,120454.2,0 +5396,15639303,Moore,589,Germany,Male,48,5,126111.61,1,0,1,133961.19,0 +5397,15691011,Shoebridge,591,France,Male,42,9,161651.37,2,1,1,131753.97,0 +5398,15638513,Palermo,723,France,Female,40,7,142856.95,2,0,0,38019.74,0 +5399,15648933,Reilly,831,Germany,Male,44,3,111100.98,1,1,1,28144.07,1 +5400,15628904,Bowen,733,Spain,Male,35,8,102918.38,1,1,1,45959.86,0 +5401,15644788,Fyodorov,731,France,Female,30,5,0,2,1,0,189528.72,0 +5402,15598161,Clements,654,France,Male,47,10,0,2,1,0,170481.98,0 +5403,15745624,McKenzie,828,France,Male,37,4,0,2,1,0,94845.45,0 +5404,15733169,Craig,590,Spain,Male,22,7,125265.61,1,1,1,161253.08,0 +5405,15801417,Iloerika,657,France,Male,37,4,82500.28,1,1,1,115260.72,0 +5406,15592707,Dolgorukova,531,Germany,Female,64,2,175754.87,2,1,1,60721.4,0 +5407,15593954,Eva,516,France,Female,47,6,109387.33,1,0,0,121365.45,0 +5408,15714431,Yeh,561,France,Male,37,1,100443.36,2,0,1,101693.73,0 +5409,15638257,P'an,682,Spain,Female,54,0,83102.72,2,1,1,54132.93,0 +5410,15690939,Howe,575,Spain,Male,28,7,0,1,1,1,10666.05,0 +5411,15723613,Jenkins,623,France,Female,28,4,0,2,1,0,41227.67,0 +5412,15813640,Shih,642,France,Female,40,7,0,2,1,0,10712.82,0 +5413,15707322,Nnamdi,779,France,Female,48,2,115290.27,1,0,0,98912.69,1 +5414,15588918,Mitchell,671,France,Female,42,6,0,2,1,0,197202.48,0 +5415,15600357,Findlay,495,France,Female,40,1,140197.71,2,1,0,150720.39,0 +5416,15747014,Pisani,850,France,Female,28,1,105245.34,1,0,1,74780.13,0 +5417,15809830,Belisario,630,France,Male,50,8,0,2,0,1,79377.45,0 +5418,15662245,Pomeroy,588,France,Male,32,1,0,2,1,1,8763.87,0 +5419,15651075,Ibrahimova,562,Germany,Male,35,3,142296.13,1,0,1,177112.7,0 +5420,15594456,K?,740,Spain,Female,56,4,99097.33,1,1,1,85016.64,1 +5421,15583462,Graham,695,France,Male,28,5,171069.39,2,1,1,88689.4,0 +5422,15757661,Trevisano,589,France,Female,39,7,0,2,0,0,95985.64,0 +5423,15729117,Trevisano,607,France,Female,31,1,102523.88,1,1,1,166792.71,0 +5424,15749671,K?,794,France,Male,35,6,0,2,1,1,68730.91,0 +5425,15566253,Manning,580,Germany,Male,44,9,143391.07,1,0,0,146891.07,1 +5426,15595153,Tucker,644,Germany,Female,44,8,106022.73,2,0,0,148727.42,0 +5427,15698572,Schaffer,636,Spain,Female,36,1,0,1,1,0,43134.58,0 +5428,15674149,Esomchi,599,Germany,Male,36,3,128960.21,2,1,1,40318.33,0 +5429,15623082,Ch'ang,507,France,Female,35,2,0,2,1,0,97633.93,0 +5430,15797905,Walker,682,France,Female,48,7,0,2,1,0,65069.03,0 +5431,15746028,Chu,714,France,Female,24,7,0,2,1,0,166335,0 +5432,15582951,Crawford,696,France,Female,25,8,126442.59,1,1,0,121904.44,0 +5433,15616471,Milne,599,Spain,Male,51,0,0,1,1,1,175235.99,0 +5434,15641575,Anenechukwu,577,France,Male,37,2,127261.35,1,1,0,56185.05,0 +5435,15638803,Donaldson,733,Spain,Female,32,5,0,2,1,0,131625.14,0 +5436,15808283,Kelly,647,France,Female,33,4,0,1,1,0,152323.04,0 +5437,15811200,Ts'ao,831,France,Female,34,2,0,2,0,0,165840.94,0 +5438,15733476,Gonzalez,543,Germany,Male,30,6,73481.05,1,1,1,176692.65,0 +5439,15633274,Tai,679,France,Male,34,7,160515.37,1,1,0,121904.14,0 +5440,15582168,Muravyova,713,Germany,Female,61,4,149525.34,2,1,0,123663.63,0 +5441,15807269,Milanesi,690,Germany,Male,43,2,166522.78,1,0,0,119644.59,1 +5442,15602979,Lin,751,France,Male,29,1,135536.5,1,1,0,66825.33,0 +5443,15660417,Lambert,613,Germany,Female,43,10,120481.69,1,0,0,94875.03,1 +5444,15590199,Temple,701,Spain,Male,28,1,103421.32,1,0,1,76304.73,0 +5445,15641794,Ridley,698,France,Male,33,5,135658.73,2,0,1,39755,0 +5446,15779174,Young,451,France,Female,36,2,0,2,1,1,180142.42,0 +5447,15785547,Slye,665,France,Male,28,8,191402.82,2,1,0,83238.4,0 +5448,15795124,Pan,726,Germany,Male,50,9,94504.35,1,0,1,5078.9,0 +5449,15718912,Hsueh,608,Germany,Female,44,5,126147.84,1,0,1,132424.69,1 +5450,15592028,Roberts,549,France,Female,46,7,0,1,1,1,109057.56,0 +5451,15580227,Moss,803,France,Male,33,6,0,2,1,0,115676.61,0 +5452,15657830,Andrews,663,France,Male,43,4,87624.03,2,1,0,149401.33,0 +5453,15798256,Takasuka,558,France,Female,45,1,153697.53,2,0,0,89891.4,1 +5454,15643819,Dawson,714,France,Female,25,4,0,2,0,0,82500.84,0 +5455,15754301,Bruche,704,France,Male,39,5,0,1,1,0,6416.92,0 +5456,15726855,Oliver,805,Germany,Female,45,9,116585.97,1,1,0,189428.75,1 +5457,15755225,Ryan,659,Germany,Male,34,9,134464.58,2,1,0,178833.34,0 +5458,15725221,Sabbatini,738,Germany,Male,62,10,83008.31,1,1,1,42766.03,0 +5459,15789055,Watt,635,Spain,Male,35,2,113635.16,1,1,0,90883.12,0 +5460,15617507,Wilson,530,Spain,Female,36,7,0,2,1,0,80619.09,0 +5461,15668894,Abramova,661,Germany,Male,41,5,122552.48,2,0,1,120646.4,0 +5462,15589563,Purdy,531,Spain,Male,31,2,118899.45,2,0,0,41409.36,0 +5463,15693162,Higgins,694,France,Female,29,5,99713.87,1,0,0,112317.89,0 +5464,15750099,Marshall,731,France,Female,36,6,0,1,0,0,152128.36,0 +5465,15795540,Reye,556,France,Female,36,2,134208.22,1,0,1,177670.57,0 +5466,15794941,Chibueze,647,Germany,Female,41,1,85906.65,3,1,0,189159.97,0 +5467,15611848,Kwemtochukwu,850,Germany,Male,32,3,137714.25,1,0,1,159403.68,0 +5468,15581237,Biryukova,573,Spain,Male,33,1,160777.9,1,1,1,149536.15,0 +5469,15738150,Chidozie,591,France,Male,45,5,0,2,1,1,155492.87,0 +5470,15678571,Barber,723,France,Male,21,4,0,2,0,0,24847.02,0 +5471,15736124,Thompson,617,France,Male,25,1,102585.88,2,1,1,115387.4,0 +5472,15623202,Maslov,704,Germany,Female,39,10,102556.18,2,1,0,171971.25,1 +5473,15804201,Jones,457,Germany,Male,42,4,126772.57,1,0,1,126106.4,0 +5474,15596863,Chidumaga,787,Germany,Female,38,3,158373.23,1,1,1,28228.35,0 +5475,15696277,Hs?,651,France,Female,34,9,0,2,1,0,138113.71,0 +5476,15748608,Trentini,612,Germany,Male,42,5,141927.1,1,1,1,43018.98,0 +5477,15723864,Lucas,828,Spain,Male,47,1,109876.82,2,1,0,83611.45,1 +5478,15802390,Willoughby,724,France,Female,34,2,0,2,1,1,118863.38,0 +5479,15774336,Jamieson,648,Germany,Male,44,9,111369.79,2,1,1,91947.74,0 +5480,15648766,Robertson,569,Spain,Male,35,3,116969.35,1,0,0,94488.82,0 +5481,15659094,Ojiofor,765,Germany,Female,34,8,136729.51,2,0,0,47058.21,0 +5482,15606397,Cameron,577,Germany,Female,44,1,152086.15,1,0,1,44719.5,1 +5483,15642619,Mayne,603,Spain,Male,46,2,0,2,1,0,174478.54,0 +5484,15666032,Mancini,568,Spain,Male,28,1,127289.28,1,0,0,45611.51,0 +5485,15595842,Paramor,748,Germany,Male,45,2,119852.01,1,0,0,73853.94,1 +5486,15753837,Young,573,Spain,Male,38,4,0,2,1,1,196517.43,0 +5487,15783882,Daly,771,Spain,Female,41,5,0,2,0,1,92914.67,0 +5488,15799790,Carter,763,France,Male,35,9,0,1,1,1,31372.91,0 +5489,15628155,Dike,410,France,Female,35,7,117183.74,1,1,1,109733.73,0 +5490,15703778,Hughes,728,France,Male,33,8,129907.63,1,0,1,36083.96,0 +5491,15722322,Green,655,Spain,Female,78,2,0,2,0,1,188435.38,0 +5492,15639278,Chinomso,580,Germany,Female,36,6,145387.32,2,1,1,169963.2,1 +5493,15568487,Gorshkov,712,France,Male,35,7,124616.23,1,1,1,69320.97,0 +5494,15682084,Chinomso,680,France,Male,31,9,0,2,1,0,36145.53,0 +5495,15642821,Ijendu,383,Spain,Female,48,8,95808.19,1,0,0,137702.01,1 +5496,15601387,Yen,721,France,Male,35,10,0,2,1,0,71594.26,0 +5497,15642515,Arcuri,620,France,Female,42,1,0,2,0,1,65565.92,0 +5498,15710421,Baresi,774,Spain,Female,36,8,117152.3,1,0,0,101828.39,0 +5499,15726774,Field,563,France,Male,35,3,106250.72,1,0,0,39546.32,0 +5500,15649078,Christian,850,Germany,Female,27,8,111837.78,2,1,1,110805.79,0 +5501,15641877,Ross,681,France,Male,47,9,97023.21,1,1,1,2168.13,0 +5502,15796496,Trevisani,631,France,Female,31,8,137687.72,1,1,0,190067.12,0 +5503,15815690,Akabueze,614,Spain,Female,40,3,113348.5,1,1,1,77789.01,0 +5504,15631739,Dunn,704,Spain,Male,24,10,122109.78,1,1,1,127654.37,0 +5505,15625584,Martin,786,France,Male,32,2,120452.4,2,0,0,79602.86,0 +5506,15802466,Donaldson,534,France,Female,53,7,0,2,1,1,80619.17,0 +5507,15697028,McClinton,590,Spain,Male,34,0,65812.35,2,0,1,160346.3,0 +5508,15575759,Bentley,583,Spain,Female,40,3,54428.37,1,1,0,109638.78,1 +5509,15567442,Ibezimako,656,France,Female,75,3,0,2,1,1,1276.87,0 +5510,15746805,Thomson,597,France,Male,33,9,0,2,1,0,49374.82,0 +5511,15636330,Ch'in,588,Germany,Female,48,1,143279.58,2,1,0,31580.8,1 +5512,15714970,Holbrook,667,Germany,Male,32,0,103846.65,1,1,0,20560.69,0 +5513,15653784,Solomina,627,France,Male,37,2,125190.86,1,0,1,84584.69,0 +5514,15693543,McDonald,708,France,Female,33,8,0,2,0,1,15246.83,0 +5515,15773283,Dennis,641,France,Male,65,6,38340.02,1,1,0,32607.77,1 +5516,15742534,Faulk,527,Germany,Female,28,2,123802.98,2,1,1,155846.69,0 +5517,15569878,Dale,592,France,Male,37,3,96651.03,1,1,1,3232.82,0 +5518,15729454,Gorbunov,465,France,Male,33,8,0,2,1,0,177668.55,0 +5519,15578375,Farrell,628,France,Male,39,6,0,2,0,0,134441.6,0 +5520,15785559,De Luca,678,France,Male,43,1,133237.21,1,1,0,111032.79,1 +5521,15649414,Walker,570,France,Female,61,6,142105.35,1,1,1,45214.04,0 +5522,15701605,Forster,815,France,Male,37,1,166115.42,1,1,0,67208.3,0 +5523,15686696,Brown,817,France,Female,37,6,81070.34,2,1,0,80985.88,0 +5524,15625586,Monaldo,717,France,Male,35,4,0,1,1,1,167573.06,0 +5525,15654975,Wu,641,France,Female,53,0,123835.52,2,0,1,160110.65,0 +5526,15782993,Pan,624,France,Male,51,10,123401.43,2,1,1,127825.25,0 +5527,15774382,Longo,579,Germany,Male,49,4,169377.31,1,1,1,123535.05,0 +5528,15689602,Findlay,698,France,Male,38,2,130015.24,1,1,1,41595.3,0 +5529,15756155,Fu,645,France,Male,32,4,0,2,0,1,97628.08,0 +5530,15812647,Yin,691,France,Male,34,8,133936.04,2,1,0,91359.79,0 +5531,15736043,Hamilton,638,France,Male,34,6,114543.27,1,1,1,97755.29,0 +5532,15696744,Miller,705,France,Female,31,3,119794.67,1,0,0,182528.44,0 +5533,15602572,Hsing,720,France,Male,33,9,0,2,1,1,142956.48,0 +5534,15674765,Mitchell,553,Spain,Male,44,4,0,1,1,0,10789.3,0 +5535,15678725,Chamberlin,658,France,Female,29,8,0,2,0,1,130461.09,0 +5536,15694444,Buttenshaw,648,Germany,Female,32,8,157138.99,3,1,0,190994.48,1 +5537,15795878,Anayochukwu,636,Spain,Male,45,3,0,2,1,1,159463.8,0 +5538,15735346,Wallace,527,Germany,Female,41,10,136733.24,1,1,1,57589.29,0 +5539,15687094,Calabresi,717,Germany,Female,28,9,82498.14,2,0,0,40437.67,0 +5540,15790067,Sun,614,Spain,Male,39,3,151914.93,1,0,0,56459.45,0 +5541,15605742,Tuan,737,France,Male,43,0,80090.93,1,1,0,39920,1 +5542,15566740,Nazarova,587,Spain,Male,51,3,83739.32,1,0,1,148798.45,0 +5543,15664897,Bryant,682,France,Female,35,2,181166.44,1,1,1,63737.19,1 +5544,15585777,Pai,710,France,Male,38,3,130588.82,1,1,1,154997.64,0 +5545,15650864,Power,507,France,Male,42,6,0,2,1,0,34777.23,0 +5546,15806709,Hao,609,Germany,Male,33,6,94126.67,1,0,0,93718.16,0 +5547,15633818,McMillan,786,France,Male,32,9,0,2,1,0,133112.41,0 +5548,15713845,Merrett,688,France,Male,38,7,148045.68,1,1,0,175479.92,1 +5549,15639662,Phillips,710,France,Male,38,2,0,2,1,0,96.27,0 +5550,15567013,De Luca,779,Spain,Male,33,3,0,2,1,0,30804.68,0 +5551,15777784,Tu,733,France,Female,44,6,168165.84,1,0,1,197193.49,0 +5552,15800251,Elder,583,Germany,Female,26,10,72835.56,2,1,0,96792.15,0 +5553,15651315,Dilke,627,France,Male,41,3,0,2,1,0,132719.8,0 +5554,15651450,Panicucci,666,Germany,Male,31,3,123212.08,2,1,1,112157.31,0 +5555,15784218,Mason,620,Spain,Male,38,0,0,2,1,1,38015.34,0 +5556,15572398,Townsend,614,Spain,Female,39,6,0,2,1,1,164018.98,0 +5557,15707962,Gunson,606,France,Male,40,6,119501.88,2,1,0,46774.94,0 +5558,15705663,Milano,700,Germany,Female,39,5,144550.83,2,1,1,189664.43,0 +5559,15645355,Macleod,677,Germany,Male,34,3,126729.41,1,1,1,26106.39,1 +5560,15729557,Olisaemeka,850,Germany,Male,36,5,119984.07,1,1,0,191535.11,1 +5561,15631436,Gleeson,564,France,Male,35,4,0,1,1,0,158937.55,0 +5562,15583073,Martin,771,Spain,Female,56,2,0,1,1,1,25222.6,1 +5563,15614361,Liao,620,Spain,Male,42,9,121490.05,1,1,1,29296.74,0 +5564,15724684,Sung,610,Spain,Male,46,5,91897.8,1,1,0,54394.28,0 +5565,15700083,Lai,609,Spain,Male,39,2,139443.75,2,1,0,9234.06,0 +5566,15636541,Cartwright,683,Germany,Male,35,5,144961.97,1,0,1,26796.73,0 +5567,15796015,Wu,633,Germany,Male,42,3,126041.02,1,0,1,11796.89,0 +5568,15787222,Ch'in,676,Germany,Male,28,1,69459.05,2,1,1,128461.29,0 +5569,15594270,Biryukov,693,France,Male,38,7,198338.77,2,1,1,14278.18,0 +5570,15701524,Ting,709,France,Male,36,0,0,2,1,0,46811.77,0 +5571,15645847,P'eng,569,Germany,Male,35,2,109196.66,3,1,0,109393.19,1 +5572,15708867,Niu,684,Spain,Female,38,3,134168.5,3,1,0,3966.5,1 +5573,15613140,Mellor,565,France,Male,34,6,0,1,1,1,63173.64,0 +5574,15628893,Power,681,France,Male,29,8,0,1,1,0,66367.33,0 +5575,15764073,Arcuri,503,Spain,Female,36,9,0,2,1,1,16274.67,0 +5576,15782879,Lang,656,France,Male,40,2,0,2,1,1,180553.48,0 +5577,15635964,Eve,566,Germany,Male,65,4,120100.41,1,1,0,107563.16,1 +5578,15726087,Ch'in,592,France,Female,62,5,0,1,1,1,100941.57,0 +5579,15726313,Napolitani,687,Spain,Female,50,5,0,2,1,0,110230.4,0 +5580,15578073,Barker,686,Spain,Male,22,8,0,2,0,0,142331.85,0 +5581,15786249,Whitfield,616,Spain,Male,30,2,0,2,1,0,199099.51,0 +5582,15812850,Stradford,494,Spain,Male,67,5,0,2,1,1,85890.16,0 +5583,15596972,Brownlow,534,France,Male,38,3,0,1,0,0,143938.27,0 +5584,15620579,Dunn,695,Spain,Female,31,8,0,2,0,1,131644.41,0 +5585,15768270,DeRose,579,Spain,Female,31,9,0,2,1,0,112395.98,0 +5586,15656597,Wang,432,Germany,Male,38,2,135559.8,2,1,1,71856.3,0 +5587,15699446,Hobbs,816,Germany,Female,25,2,150355.35,2,1,1,35770.84,0 +5588,15615004,Anderson,730,France,Female,37,1,0,2,1,1,124364.63,0 +5589,15704771,Ugochukwu,593,France,Female,35,6,133489.12,2,1,1,78101.29,0 +5590,15588372,Kirsova,715,Germany,Female,37,9,105489.31,1,0,0,143096.49,1 +5591,15681439,Tsou,775,Germany,Male,25,10,60205.2,2,1,0,14073.11,0 +5592,15607509,Ozerova,539,France,Male,38,5,0,2,1,0,47388.41,0 +5593,15670343,Li,576,Spain,Male,19,6,0,2,0,0,72306.07,0 +5594,15597968,Fyans,617,Spain,Male,50,7,0,1,1,0,184839.7,1 +5595,15658432,Freeman,688,France,Male,40,6,0,1,1,1,47886.44,0 +5596,15616431,Chiu,608,France,Male,33,4,0,1,0,1,130474.03,0 +5597,15796957,Iadanza,597,Spain,Male,35,9,0,3,0,1,73181.39,1 +5598,15815552,Ferguson,670,France,Female,42,6,112333.63,1,1,1,65706.86,0 +5599,15631871,Kelly,616,Germany,Female,57,7,116936.81,1,1,1,104379.36,0 +5600,15635870,She,579,Germany,Female,50,5,117721.02,1,0,1,192146.63,1 +5601,15596713,Christie,786,France,Male,37,7,165896.22,2,1,1,66977.68,0 +5602,15684211,Creel,704,Spain,Female,44,9,153656.85,1,1,0,158742.81,0 +5603,15760521,Thompson,796,France,Female,50,1,94164,1,1,1,189414.74,0 +5604,15608408,Lazareva,598,Spain,Male,39,1,0,2,1,0,159130.32,0 +5605,15804721,Boni,602,France,Male,49,0,191808.73,1,0,0,97640.2,0 +5606,15730272,Evseev,619,France,Male,58,5,152199.33,1,1,1,86022.09,0 +5607,15741988,Marino,492,Germany,Female,52,8,125396.24,1,1,0,10014.72,1 +5608,15771728,Mackenzie,641,Germany,Male,41,7,104405.54,3,1,0,17384.21,0 +5609,15605113,Sutherland,518,France,Female,27,1,133801.49,1,1,1,143315.57,0 +5610,15661945,Nicolay,623,Spain,Female,40,4,0,3,1,0,31669.18,0 +5611,15783816,Lori,733,France,Female,28,5,0,2,0,0,12761.16,0 +5612,15721207,Piazza,625,Germany,Male,42,6,100047.33,1,1,0,93429.95,0 +5613,15764072,Somerville,759,France,Female,31,1,109848.6,1,1,1,42012.55,0 +5614,15689412,Christie,604,France,Female,32,7,127849.38,1,1,0,15798.7,0 +5615,15798385,Grave,512,Spain,Female,46,3,0,2,1,1,56408.14,0 +5616,15775339,Lori,520,France,Female,29,8,95947.76,1,1,0,4696.44,0 +5617,15585256,Iloerika,805,Spain,Male,26,2,0,2,1,1,25042.1,0 +5618,15797329,Muir,626,France,Male,43,4,137638.69,1,1,0,130442.08,1 +5619,15780220,Pauley,656,France,Male,38,10,0,1,1,1,136521.82,0 +5620,15648951,Kao,785,Spain,Male,41,7,0,2,1,1,199108.88,0 +5621,15752409,Grant,553,France,Male,31,6,0,2,0,0,124596.63,0 +5622,15807524,Chukwuma,569,France,Female,44,4,0,2,0,0,134394.78,0 +5623,15766649,Vincent,670,France,Male,38,10,89416.99,1,0,0,144275.39,0 +5624,15696812,Lazareva,586,Spain,Male,42,6,0,2,1,1,123410.23,0 +5625,15581295,Ch'ien,617,Spain,Female,45,1,0,1,1,0,143298.06,0 +5626,15663234,Bishop,508,France,Female,60,7,143262.04,1,1,1,129562.74,0 +5627,15741417,Chibuzo,624,Spain,Female,35,7,119656.45,2,1,1,4595.05,0 +5628,15695174,Chang,654,France,Male,29,4,132954.64,1,1,1,146715.07,0 +5629,15665168,Calabrese,681,Germany,Female,44,3,105206.7,2,1,1,163558.36,0 +5630,15601503,Tokaryev,578,Spain,Male,28,4,0,2,0,0,6947.09,0 +5631,15706131,Logan,621,Spain,Female,37,9,83061.26,2,1,0,9170.54,0 +5632,15782758,Ozerova,632,France,Male,40,5,147650.68,1,1,1,199674.83,0 +5633,15591091,Goering,644,France,Male,44,5,73348.56,1,1,0,157166.79,1 +5634,15715877,Lo,821,France,Male,28,2,0,2,1,0,46072.52,0 +5635,15756918,Simmons,754,France,Female,38,2,0,2,0,0,3524.69,0 +5636,15746662,Maduabuchim,568,Spain,Female,27,1,116320.68,1,0,1,45563.94,0 +5637,15626679,Linger,584,France,Male,33,3,0,2,0,1,59103.13,0 +5638,15793343,Yeh,549,France,Female,29,8,0,2,1,1,189558.44,0 +5639,15576774,Stevenson,729,France,Female,38,7,0,2,0,0,45779.9,0 +5640,15801316,Ifeatu,523,France,Male,61,8,66250.71,1,1,1,21859.06,0 +5641,15800514,Kenechukwu,477,Germany,Female,24,2,95675.62,2,0,0,162699.7,1 +5642,15662232,Learmonth,675,Germany,Male,42,2,92616.64,2,1,0,8567.18,0 +5643,15737778,Dickson,782,Spain,Female,41,4,0,1,1,0,132943.88,0 +5644,15782096,Volkova,616,Spain,Female,36,6,0,1,1,1,12916.32,1 +5645,15783522,Mitchell,738,Spain,Female,37,8,100565.94,1,1,1,128799.86,0 +5646,15785373,Wong,717,Spain,Female,42,5,190305.78,1,1,0,99347.8,1 +5647,15756272,James,526,Germany,Female,35,9,118536.4,1,1,0,40980.87,1 +5648,15615245,Shao,660,France,Male,19,5,127649.64,1,1,1,40368.65,0 +5649,15600174,Walton,525,France,Male,35,7,165358.77,1,0,1,94738.54,0 +5650,15752956,Stanley,629,Spain,Male,29,6,0,2,1,1,88842.8,0 +5651,15644882,Watson,616,Germany,Female,36,10,78249.53,1,1,0,136934.91,0 +5652,15766272,Folliero,521,Germany,Female,61,0,125193.96,1,1,1,109356.53,0 +5653,15800620,Fitzgerald,691,France,Female,29,9,0,2,0,0,199635.93,0 +5654,15569764,Garner,687,Germany,Female,41,2,154007.21,1,1,0,158408.23,0 +5655,15747458,Folliero,677,Spain,Female,43,3,133214.88,2,1,1,95936.84,0 +5656,15573171,Liao,695,Spain,Male,63,1,146202.93,1,1,1,126688.83,1 +5657,15736769,Lucchesi,663,France,Female,27,9,0,2,1,0,150850.29,0 +5658,15763381,Chan,496,France,Male,30,0,90963.49,1,0,1,27802,0 +5659,15814430,Ma,747,Spain,Male,41,9,0,1,1,0,32430.94,1 +5660,15638607,Nwabugwu,546,France,Female,52,2,0,1,1,0,137332.37,1 +5661,15737133,P'eng,706,Spain,Male,68,4,114386.85,1,1,1,28601.68,0 +5662,15613945,Andrews,472,France,Female,26,5,0,2,1,0,108411.66,0 +5663,15659937,Otutodilinna,703,France,Female,40,7,0,2,0,1,122518.5,0 +5664,15765287,Grant,850,France,Female,38,2,0,2,1,0,9015.07,0 +5665,15661723,Abramovich,667,Spain,Male,71,4,137260.78,1,0,1,94433.08,1 +5666,15766064,Komarova,559,France,Male,33,9,111060.05,2,1,0,110371.84,0 +5667,15649616,Otutodilichukwu,636,Spain,Male,60,7,124447.73,1,1,1,141364.62,1 +5668,15719017,Donaldson,672,France,Female,34,8,0,2,1,1,16245.25,0 +5669,15720919,Duggan,667,France,Male,42,7,0,1,0,1,108348.94,1 +5670,15706706,Chinwendu,648,Germany,Male,33,7,135310.41,2,0,1,171668.2,0 +5671,15709653,Hamilton,497,France,Male,32,8,0,2,1,0,67364.42,0 +5672,15805104,Smith,743,France,Female,73,6,0,2,0,1,107867.38,0 +5673,15622442,Mazzi,619,France,Male,29,5,0,2,1,0,194310.1,0 +5674,15572801,Krischock,639,Spain,Male,34,5,139393.19,2,0,0,33950.08,0 +5675,15767598,Kent,540,Spain,Male,28,8,0,2,0,0,197588.32,0 +5676,15757897,Binder,766,France,Female,26,3,104258.8,1,1,1,428.23,0 +5677,15568104,Zubarev,749,France,Female,26,6,0,2,0,1,34948.77,0 +5678,15763414,Degtyarev,655,Germany,Male,32,9,113447.01,1,1,0,82084.3,0 +5679,15732265,Obialo,630,France,Male,33,9,0,2,1,0,64804.59,0 +5680,15621974,Davydova,778,Germany,Female,33,4,111063.73,2,1,0,83556.65,0 +5681,15803947,Teng,757,Germany,Female,30,6,161378.02,1,0,0,71926.28,1 +5682,15720706,Hsing,529,Spain,Female,39,2,82766.43,1,1,1,122925.44,0 +5683,15759290,Coleman,620,Spain,Male,29,9,0,2,1,0,13133.88,0 +5684,15651664,Wilder,615,France,Female,61,1,104267.7,1,1,0,62845.64,1 +5685,15795132,Molineux,735,France,Female,25,3,91718.8,1,0,0,28411.23,0 +5686,15811565,Cocci,705,Spain,Female,47,3,63488.7,1,0,1,28640.92,1 +5687,15713774,Chikwendu,644,Spain,Female,46,6,12459.19,1,0,0,156787.34,1 +5688,15691840,Fraser,505,Germany,Female,37,6,159863.9,2,0,1,125307.87,0 +5689,15682021,Lai,471,Germany,Male,23,6,104592.55,2,1,0,131736.23,0 +5690,15612931,Korovin,722,Spain,Female,50,4,132088.59,1,1,1,128262.14,0 +5691,15676707,Sidorov,577,Spain,Female,39,4,0,2,1,0,91366.42,0 +5692,15601383,Ibrahimova,744,Spain,Male,44,5,120654.68,1,1,0,82290.81,0 +5693,15662662,Duigan,573,France,Female,30,6,0,2,1,0,66190.21,0 +5694,15752694,Taylor,653,France,Female,32,4,83772.95,1,0,1,23920.65,0 +5695,15590683,Donaldson,660,France,Female,31,6,172325.67,1,0,1,45438.38,0 +5696,15773591,Jobson,787,France,Male,46,7,117685.31,2,1,1,93360.35,0 +5697,15723620,Lu,617,France,Male,41,7,0,2,0,1,14496.67,0 +5698,15671779,Nebechi,567,France,Male,39,5,0,2,0,0,168521.72,0 +5699,15672966,Cross,682,Spain,Female,64,9,0,2,1,1,103318.44,0 +5700,15624667,Wallace,684,France,Male,35,6,135871.5,1,1,1,87219.41,0 +5701,15812888,Perreault,447,France,Male,41,3,0,4,1,1,197490.39,1 +5702,15724154,Manna,625,Germany,Female,49,4,128504.76,1,1,0,126812.63,1 +5703,15749540,Hsiung,585,France,Male,36,7,0,2,1,0,94283.09,0 +5704,15621063,Gibbons,516,France,Female,42,8,56228.25,1,1,0,46857.52,0 +5705,15661626,Algeranoff,732,Germany,Female,45,6,98792.4,1,1,0,81491.7,1 +5706,15698703,Doherty,628,Germany,Male,40,5,181768.32,2,1,1,129107.97,0 +5707,15801431,Rowe,682,Spain,Female,48,9,101198.01,1,1,1,49732.9,0 +5708,15649451,Yates,746,France,Male,25,9,0,2,0,1,88728.47,0 +5709,15626156,Galloway,655,France,Female,60,3,0,2,1,1,86981.45,0 +5710,15606158,Genovese,644,France,Female,39,9,0,1,1,0,3740.93,0 +5711,15589496,Arrington,778,France,Male,34,5,139064.06,2,0,0,67949.32,0 +5712,15730345,Miah,617,France,Female,35,2,104508.1,1,1,1,147636.46,0 +5713,15572038,Chijindum,660,Germany,Male,35,9,113948.58,1,1,0,188891.96,1 +5714,15643439,Ferguson,537,France,Male,47,10,0,2,0,1,25482.62,0 +5715,15604158,Smith,554,France,Female,39,10,0,2,1,1,18391.93,0 +5716,15657396,Marshall,806,France,Male,31,9,0,2,0,1,140168.36,0 +5717,15709478,P'an,611,Germany,Male,37,1,117524.72,2,0,1,161064.29,0 +5718,15628824,Burton,665,France,Female,37,5,160389.82,1,0,1,183542.08,0 +5719,15814519,Kamdibe,648,France,Female,37,7,0,2,1,0,194238.92,0 +5720,15636520,Milani,692,France,Male,27,1,125547.53,1,0,0,7900.46,0 +5721,15794414,Forbes,507,Spain,Male,46,6,92783.68,1,1,1,51424.29,0 +5722,15643671,Chiekwugo,696,Germany,Male,49,5,97036.22,2,1,0,152450.84,1 +5723,15700650,Cousens,681,France,Male,34,3,0,2,0,0,55816.2,0 +5724,15680224,Ross,687,France,Female,26,6,0,2,1,1,32909.13,0 +5725,15784286,Wood,641,Spain,Male,40,5,102145.13,1,1,1,100637.07,0 +5726,15693996,Hawks,507,France,Female,33,1,113452.66,1,0,0,142911.99,0 +5727,15764343,T'ien,688,Spain,Female,46,8,155681.72,1,1,0,26287.21,0 +5728,15704168,Ting,535,Germany,Male,38,8,127475.24,1,0,0,60775.76,1 +5729,15680197,Thynne,701,France,Male,41,10,0,2,1,1,146257.77,0 +5730,15633729,Wang,488,France,Male,43,10,112751.13,1,1,1,28332,0 +5731,15577683,Maclean,539,France,Female,29,4,0,2,1,1,100919.19,0 +5732,15800746,Watson,674,France,Male,45,7,144889.18,1,1,1,102591.9,1 +5733,15788686,Gibson,538,Spain,Male,40,8,0,2,1,1,25554.4,0 +5734,15742798,French,829,France,Female,22,7,150126.44,1,1,0,152107.93,1 +5735,15596647,Henderson,768,France,Male,54,8,69712.74,1,1,1,69381.05,0 +5736,15756070,Greenwood,585,Spain,Female,44,4,0,2,0,1,101728.46,0 +5737,15775116,Anderson,581,France,Male,31,3,0,2,0,0,89040.61,0 +5738,15575428,Mistry,682,Germany,Female,35,2,117438.92,2,1,1,16910.98,0 +5739,15654074,Tuan,653,France,Male,38,8,119315.75,1,1,0,150468.35,0 +5740,15695872,Fiorentini,712,France,Female,30,1,89571.59,1,1,1,177613.19,0 +5741,15568885,Scott,620,Germany,Female,34,8,102251.57,1,1,0,120672.09,0 +5742,15725036,Jideofor,709,France,Male,42,9,118546.71,1,0,1,77142.85,0 +5743,15632665,Yevseyev,832,France,Male,61,2,0,1,0,1,127804.66,1 +5744,15571476,Kelly,635,Spain,Male,38,0,103257.14,1,0,0,158344.63,0 +5745,15776850,Smith,749,Spain,Female,43,1,124209.02,1,1,1,167179.48,0 +5746,15623649,Ogle,629,Spain,Male,32,3,0,2,1,1,15404.64,0 +5747,15751131,Moss,836,Spain,Female,41,7,150302.84,1,1,1,156036.19,0 +5748,15688128,Loggia,542,Spain,Male,34,8,108653.93,1,0,1,144725.14,0 +5749,15678412,Nwankwo,645,France,Female,45,8,85325.93,1,0,0,22558.74,0 +5750,15770291,Allan,844,France,Female,29,8,0,2,0,0,147342.03,0 +5751,15583392,Woronoff,747,Germany,Male,37,9,135776.36,3,1,0,85470.45,1 +5752,15690731,Wolfe,645,France,Male,40,6,131411.24,1,1,1,194656.11,0 +5753,15697948,Henderson,752,Spain,Female,36,3,0,2,1,1,48505.1,0 +5754,15608328,Sutherland,760,Spain,Female,41,6,0,2,0,0,101491.23,0 +5755,15766378,Marsden,714,Germany,Female,45,9,106431.97,2,1,1,164117.69,0 +5756,15600813,Hyde,717,France,Male,50,9,90305.76,1,1,1,124626.57,0 +5757,15706217,Kao,645,Germany,Male,28,7,117466.03,2,1,1,34490.06,0 +5758,15601417,T'ang,681,France,Male,32,3,148884.47,2,1,1,90967.37,0 +5759,15610972,Crawford,681,Germany,Female,44,4,91115.76,2,0,0,24208.84,1 +5760,15674620,Dilibe,679,Germany,Female,37,8,77373.87,2,0,1,174873.09,0 +5761,15785350,Austin,528,Spain,Male,23,7,104744.89,1,1,0,170262.97,0 +5762,15749119,Santiago,710,France,Female,31,3,0,2,1,1,112289.06,0 +5763,15756535,Chibugo,733,Germany,Male,39,5,91538.51,1,1,1,93783,0 +5764,15700965,Toscano,724,France,Female,32,6,0,2,1,1,150026.79,0 +5765,15791851,Afanasyeva,726,France,Female,34,0,185734.75,1,1,1,102036.82,0 +5766,15717156,Sokolov,520,France,Male,30,3,143396.54,2,1,1,898.51,0 +5767,15740846,Wei,556,France,Male,40,5,125909.85,1,1,1,95124.4,0 +5768,15573284,Olisanugo,579,France,Female,45,2,0,2,0,0,11514.39,0 +5769,15729083,Gorman,674,France,Male,36,2,154525.7,1,0,1,27468.72,0 +5770,15611612,Priestley,570,France,Female,29,0,0,1,1,0,37092.43,0 +5771,15694381,Lloyd,631,France,Male,51,8,100654.8,1,1,0,171587.9,0 +5772,15651737,Salmond,623,Spain,Male,44,1,83325.77,1,0,1,80828.78,0 +5773,15663168,MacDonald,665,France,Male,35,8,110934.54,1,1,0,169287.99,0 +5774,15643426,Robertson,523,Spain,Female,36,8,113680.54,1,0,0,13197.44,0 +5775,15618245,Chukwumaobim,706,Germany,Male,31,1,117020.08,2,1,0,54439.53,0 +5776,15717527,Ifeanacho,619,France,Female,49,9,145359.99,1,1,0,38186.85,0 +5777,15793478,Li Fonti,593,Germany,Female,39,8,151391.68,1,1,0,27274.6,1 +5778,15642248,Ko,608,Spain,Male,66,8,123935.35,1,1,1,65758.19,0 +5779,15640377,Goloubev,526,France,Female,36,0,0,2,1,0,97767.63,0 +5780,15723950,Kruglov,684,Spain,Male,40,2,70291.02,1,1,1,115468.84,1 +5781,15590327,Liao,604,Germany,Female,42,10,166031.45,1,1,0,98293.14,0 +5782,15706199,White,636,Germany,Male,36,6,96643.32,1,0,0,182059.28,0 +5783,15671514,Sinclair,669,Spain,Female,33,8,0,2,0,1,128538.05,0 +5784,15727041,Fiorentini,624,France,Male,71,7,0,2,1,1,108841.83,0 +5785,15738063,Shen,631,France,Male,29,2,0,2,1,1,18581.84,0 +5786,15711733,Rapuokwu,753,France,Male,48,4,0,2,0,1,146821.42,0 +5787,15652320,Woronoff,588,France,Male,40,5,0,2,0,0,100727.68,0 +5788,15634180,Holden,729,Germany,Male,26,4,97268.1,2,1,0,39356.38,0 +5789,15694566,Roberts,602,France,Female,42,10,0,2,0,0,169921.11,1 +5790,15726103,Tsou,689,Germany,Female,55,1,76296.81,1,1,0,42364.75,1 +5791,15646351,Somerville,486,Spain,Male,27,7,0,2,1,0,28823.04,0 +5792,15730044,Greco,809,Germany,Female,42,6,64497.94,3,0,1,182436.81,1 +5793,15795186,Leonard,562,France,Male,38,5,0,1,1,0,115700.2,0 +5794,15784890,McKenzie,763,Spain,Female,32,8,0,2,1,0,16725.53,0 +5795,15694125,McElhone,669,France,Male,57,5,0,2,1,1,56875.76,0 +5796,15565891,Dipietro,709,France,Male,39,8,0,2,1,0,56214.09,0 +5797,15674254,Kerr,554,Spain,Female,45,4,0,2,1,1,193412.05,0 +5798,15775206,Hunter,699,France,Male,37,10,0,2,0,0,83263.04,0 +5799,15797627,Niehaus,732,Spain,Male,54,0,134249.7,1,0,1,13404.4,0 +5800,15649853,Craig,625,France,Female,45,3,0,1,1,1,184474.15,1 +5801,15610379,Barclay-Harvey,599,France,Male,30,9,105443.68,1,1,1,121124.53,0 +5802,15659800,Teng,584,Spain,Female,50,1,0,1,0,1,152567.75,1 +5803,15716236,Milani,499,France,Male,35,10,0,2,1,0,10722.54,0 +5804,15672053,Mistry,526,Spain,Male,38,2,0,2,0,0,58010.98,0 +5805,15663933,Jamieson,625,Germany,Female,35,5,86147.46,2,1,0,163440.8,1 +5806,15814236,Kay,537,Spain,Female,38,1,96939.06,1,1,1,102606.92,0 +5807,15583597,Ikedinachukwu,696,Spain,Male,47,1,106758.6,1,1,1,80591.18,0 +5808,15607395,Holt,679,France,Female,33,9,112528.65,2,1,0,177362.45,0 +5809,15694556,Nkemakolam,684,France,Male,60,2,116563.58,1,1,0,120257.7,1 +5810,15744109,Hartung,850,France,Male,32,4,0,1,1,1,180622.02,0 +5811,15800688,Ch'en,495,Spain,Female,42,7,0,2,0,0,130404.53,0 +5812,15810878,Baker,537,Spain,Female,38,6,141786.78,1,0,1,147797.54,0 +5813,15587835,Osinachi,850,France,Male,41,3,136416.82,1,0,1,57844.26,0 +5814,15763515,Shih,513,France,Male,30,5,0,2,1,0,162523.66,0 +5815,15725882,Feng,618,Germany,Female,40,1,133245.52,2,1,1,54495.82,0 +5816,15788022,Sternberg,802,Germany,Female,41,4,90757.64,2,0,1,169183.66,0 +5817,15663917,Adams,547,France,Male,43,1,92350.36,1,0,1,80262.91,0 +5818,15656865,Gray,613,Germany,Male,69,9,78778.49,1,0,1,8751.59,0 +5819,15667971,Shepherd,592,Germany,Female,34,6,102143.93,2,1,1,102628.98,0 +5820,15800366,Walton,546,France,Male,29,5,0,1,1,1,94823.95,0 +5821,15717231,Yang,721,Germany,Male,37,4,98459.6,1,0,0,90821.66,0 +5822,15643188,Barnett,671,Germany,Female,47,7,114603.76,2,1,0,153194.32,1 +5823,15671351,Romani,624,Spain,Male,35,2,0,2,1,0,87310.59,0 +5824,15573628,Greene,751,Germany,Female,51,7,148074.79,1,1,0,146411.41,1 +5825,15698953,Hart,636,Spain,Male,36,1,0,3,1,1,74048.1,1 +5826,15753888,Johnston,607,Spain,Female,62,8,108004.64,1,1,1,23386.77,1 +5827,15737961,Miller,509,Germany,Female,29,0,107712.57,2,1,1,92898.17,0 +5828,15801701,Robson,653,Spain,Male,35,9,0,2,1,1,45956.05,0 +5829,15684419,Wallace,709,Spain,Female,37,8,0,3,1,0,71738.56,0 +5830,15794266,Cross,559,France,Male,32,9,145303.52,1,1,0,103560.98,0 +5831,15810711,Marcum,684,Germany,Male,37,4,138476.41,2,1,1,52367.29,0 +5832,15771270,North,635,France,Female,27,8,127471.56,1,1,1,152916.05,1 +5833,15607786,Mao,709,France,Male,26,6,156551.63,1,0,1,4410.77,0 +5834,15624519,Calabrese,656,Germany,Female,49,9,97092.87,1,1,0,74771.22,1 +5835,15799910,Martin,793,France,Male,32,2,0,2,1,0,193817.63,1 +5836,15602479,Fleming,609,Spain,Male,37,5,129312.79,1,1,1,26793.82,0 +5837,15617419,Roberts,618,Germany,Female,29,10,100315.1,2,1,1,32526.64,0 +5838,15657603,Finch,850,France,Female,35,6,81684.97,1,1,0,824,0 +5839,15570379,Whitelegge,669,Spain,Male,51,3,88827.53,1,0,0,85250.77,1 +5840,15772996,Rooke,594,Germany,Male,40,0,152092.44,2,1,1,83508.93,0 +5841,15729574,Lu,616,Spain,Male,71,4,0,2,1,1,173599.38,0 +5842,15737267,Marcelo,676,France,Female,49,1,0,1,1,0,79342.31,1 +5843,15799128,Matthews,608,Spain,Female,38,9,102406.76,1,0,1,57600.66,0 +5844,15813327,Romani,710,France,Male,21,4,109130.96,2,1,1,56191.99,0 +5845,15711921,Scott,695,France,Male,29,5,0,2,1,1,6770.44,0 +5846,15654300,Mao,530,Germany,Male,33,9,75242.28,1,0,1,101694.67,0 +5847,15569945,Horsley,509,Spain,Male,29,1,0,2,1,0,69113.14,0 +5848,15569666,Goddard,517,France,Female,45,4,0,1,0,0,172674.36,1 +5849,15681887,Eskridge,758,Germany,Male,33,0,129142.54,2,1,1,26606.28,0 +5850,15608873,Smith,665,France,Male,51,2,0,1,0,0,53353.36,0 +5851,15762091,Simpson,631,Germany,Female,22,6,139129.92,1,1,1,63747.51,0 +5852,15722053,Oguejiofor,576,Spain,Male,33,3,0,2,0,1,190112.05,0 +5853,15782100,Holloway,544,Spain,Male,22,3,66483.32,1,0,1,110317.39,0 +5854,15765300,L?,596,Germany,Male,40,5,62389.03,3,1,0,148623.43,1 +5855,15743570,Feng,481,France,Female,34,5,0,2,1,1,125253.46,0 +5856,15608541,Claiborne,498,France,Male,46,1,91857.66,1,1,0,101954.78,1 +5857,15750671,Egobudike,512,Spain,Male,31,6,0,2,1,0,168462.26,0 +5858,15813659,Folliero,594,France,Female,56,7,0,1,1,0,26215.85,1 +5859,15757867,Bray,570,France,Female,30,10,176173.52,1,1,0,97045.32,1 +5860,15652914,Ibrahimov,721,Spain,Male,38,7,0,1,0,1,53534.8,0 +5861,15723818,Carpenter,453,France,Female,37,4,131834.76,2,1,0,8949.2,0 +5862,15713819,Walsh,562,France,Male,48,3,92347.96,1,1,1,163116.75,0 +5863,15656484,Woods,682,France,Male,40,4,0,2,1,1,140745.91,0 +5864,15778515,Wu,748,France,Male,40,3,95297.11,1,0,0,171515.84,0 +5865,15803840,Forbes,729,France,Female,32,9,0,2,0,0,150803.44,0 +5866,15735339,Lynch,663,France,Male,39,4,0,1,1,0,76884.05,0 +5867,15600392,Amaechi,735,France,Female,53,8,123845.36,2,0,1,170454.93,1 +5868,15625740,Enriquez,627,Germany,Male,62,3,143426.34,2,1,1,143104.3,0 +5869,15663817,Y?an,713,France,Male,46,5,0,1,1,1,55701.62,0 +5870,15734461,Brooks,562,Germany,Male,31,2,112708.2,1,0,1,186370.3,0 +5871,15780142,Wang,632,France,Male,43,2,100013.51,1,1,0,24275.32,0 +5872,15709920,Burke,479,France,Female,33,2,208165.53,1,0,0,50774.81,1 +5873,15684248,Meng,658,Spain,Male,21,7,0,2,0,1,154279.87,0 +5874,15643158,Chiganu,598,France,Female,40,9,0,1,1,0,68462.59,1 +5875,15693902,Hunt,597,France,Male,19,2,0,2,1,1,91036.74,0 +5876,15578307,Lucchese,512,France,Female,33,6,121685.31,2,1,1,83681.97,0 +5877,15585379,Humphries,704,France,Male,39,2,111525.02,1,1,0,199484.96,0 +5878,15758510,Frolova,474,France,Male,26,6,0,2,0,0,152491.22,0 +5879,15692918,Hsing,604,Germany,Male,36,10,113546.3,1,1,1,134875.37,0 +5880,15705301,Parkes,683,France,Male,41,6,95696.52,2,1,1,184366.14,0 +5881,15718231,Gregory,537,France,Male,28,0,88963.31,2,1,1,189839.93,0 +5882,15567991,Obiuto,794,Spain,Male,31,0,144880.34,2,0,1,175643.44,0 +5883,15772650,Longo,732,France,Male,55,9,136576.02,1,0,1,3268.17,1 +5884,15574795,Lombardo,495,France,Female,38,2,63093.01,1,1,1,47089.72,0 +5885,15706036,Lombardo,552,Germany,Male,38,10,132271.12,2,1,1,46562.02,0 +5886,15723856,Gonzalez,602,France,Female,29,3,88814.4,2,1,1,62487.97,0 +5887,15812920,Nwabugwu,607,Germany,Male,40,5,90594.55,1,0,1,181598.25,0 +5888,15691287,Ford,675,Germany,Female,33,0,141816.25,1,1,0,64815.05,1 +5889,15804797,Gilleland,443,France,Female,54,3,138547.97,1,1,1,70196.23,1 +5890,15708650,Fullwood,727,France,Female,31,2,52192.08,2,0,1,160383.47,0 +5891,15712777,Kao,482,France,Male,38,4,124976.19,1,1,0,35848.12,0 +5892,15786469,Montalvo,686,France,Female,34,1,0,2,1,0,87278.48,0 +5893,15669219,Wilson,588,Germany,Male,35,3,104356.38,1,1,0,94498.82,0 +5894,15641004,Doyne,605,Spain,Female,48,10,150315.92,1,0,1,133486.36,0 +5895,15648067,Onwuamaeze,583,France,Male,39,1,129299.28,2,1,0,73107.6,0 +5896,15704014,K'ung,738,Germany,Male,37,7,140950.92,2,1,0,195333.98,0 +5897,15645136,O'Donnell,744,Spain,Male,30,1,128065.12,1,1,0,121525.48,0 +5898,15709604,McMillan,781,France,Male,23,2,107433.48,1,1,0,173843.21,0 +5899,15713637,Chinedum,699,France,Male,34,2,117468.67,1,1,0,185227.42,0 +5900,15793901,Capon,639,France,Female,27,2,0,2,0,0,125244.18,0 +5901,15569759,Rawling,583,France,Female,27,4,0,3,1,0,163113.41,0 +5902,15712930,Duncan,587,France,Male,42,1,0,1,0,0,123006.91,0 +5903,15586504,Trevisani,694,France,Male,40,9,0,2,1,0,40463.03,0 +5904,15677317,Ankudinova,570,France,Female,29,4,153040.03,1,1,1,131363.57,1 +5905,15664270,Balsillie,692,Germany,Male,45,6,142084.04,4,1,0,188305.85,1 +5906,15731519,Kerr,511,France,Female,30,5,0,2,1,0,143994.86,0 +5907,15745623,Worsnop,788,France,Male,32,4,112079.58,1,0,0,89368.59,0 +5908,15813862,Yevseyev,526,Spain,Male,66,7,132044.6,2,1,1,158365.89,0 +5909,15641934,Manna,749,Spain,Female,46,9,66582.81,1,1,0,78753.12,1 +5910,15713043,Siciliani,691,France,Female,33,6,0,2,1,1,100408.31,0 +5911,15700749,Powell,481,France,Female,39,6,0,1,1,1,24677.54,0 +5912,15697567,Bazarova,752,France,Male,33,4,0,2,1,1,39570.78,0 +5913,15715414,White,658,France,Female,38,6,102895.1,1,0,0,155665.76,0 +5914,15639530,Buda,679,Spain,Male,42,2,0,1,1,1,168294.27,0 +5915,15726058,Cattaneo,754,Germany,Male,27,7,117578.35,2,0,1,87908.01,0 +5916,15725665,Lo,679,France,Male,47,10,198546.1,2,1,0,191198.92,1 +5917,15698872,Brown,633,Spain,Female,39,2,0,2,0,0,191207.03,0 +5918,15812184,Rose,674,France,Female,31,1,0,1,1,0,128954.05,0 +5919,15742609,Lombardo,600,Germany,Male,28,2,116623.31,1,0,1,59905.29,0 +5920,15815043,McMillan,645,Spain,Male,49,8,0,2,1,0,162012.6,0 +5921,15640648,Howe,698,France,Male,36,6,0,2,0,1,19231.98,0 +5922,15627203,Hsu,508,Spain,Male,54,10,0,1,1,1,175749.36,0 +5923,15786196,Han,555,France,Female,44,3,105770.7,3,1,0,60533.96,1 +5924,15612095,Calabrese,751,France,Female,48,9,0,1,1,0,137508.42,1 +5925,15674368,Riley,738,France,Female,39,1,94435.45,2,0,1,189430.86,0 +5926,15783477,Biryukov,706,Germany,Female,39,8,112889.91,1,0,1,6723.66,0 +5927,15757559,Broadhurst,595,France,Female,53,7,0,2,1,0,41371.68,1 +5928,15591036,Genovesi,577,Germany,Female,43,3,127940.47,1,0,0,125140.72,1 +5929,15761241,Hsieh,578,Germany,Female,36,8,129745.1,1,1,1,143683.75,0 +5930,15695078,Kemp,699,France,Male,32,3,0,2,1,1,170770.44,0 +5931,15645744,Chukwudi,826,France,Female,30,5,0,2,0,1,157397.57,0 +5932,15566988,Iqbal,656,Germany,Female,46,7,141535.52,1,1,0,50595.15,1 +5933,15749300,Teng,556,France,Female,47,2,139914.27,1,1,1,50390.98,0 +5934,15594340,Tao,569,France,Male,41,4,120243.49,1,1,0,163150.03,1 +5935,15607065,Chinedum,765,France,Male,34,9,91835.16,1,0,0,138280.17,0 +5936,15778089,Stevenson,544,Spain,Male,37,2,0,2,0,0,135067.02,0 +5937,15773723,Duncan,588,Spain,Female,22,9,67178.19,1,1,1,163534.75,1 +5938,15697035,Garrett,740,Spain,Female,31,8,0,2,0,0,86657.48,0 +5939,15679668,Yao,850,Spain,Male,38,7,115378.94,1,0,1,162087.82,0 +5940,15709861,He,766,Germany,Male,30,4,127786.28,2,1,1,28879.3,0 +5941,15791958,Mazzi,849,France,Female,41,6,0,2,1,1,169203.51,1 +5942,15791030,Edwards,612,France,Female,33,0,64900.32,2,1,0,102426.12,0 +5943,15695339,Lucchesi,517,Germany,Male,53,0,109172.88,1,1,0,54676.1,1 +5944,15658813,Siciliani,645,France,Female,55,7,0,2,1,1,18369.33,0 +5945,15715709,Shih,696,Germany,Male,43,4,114091.38,1,0,1,159888.1,0 +5946,15722533,Logue,716,France,Female,40,3,0,2,0,1,167636.15,0 +5947,15683118,Rechner,590,France,Male,32,9,0,2,1,0,138889.15,0 +5948,15672798,O'Brien,656,France,Female,45,7,145933.27,1,1,1,199392.14,0 +5949,15680112,Stewart,473,Germany,Female,35,7,131504.73,1,1,0,189560.43,0 +5950,15714575,Batt,742,Germany,Female,44,8,107926.02,1,0,1,17375.27,1 +5951,15806808,Hope,834,Germany,Female,57,8,112281.6,3,1,0,140225.14,1 +5952,15590637,Ahmed,721,France,Male,41,7,0,2,0,1,61018.85,0 +5953,15657535,Pearson,590,Spain,Male,29,10,0,1,1,1,51907.72,1 +5954,15696141,Kruglov,516,Spain,Female,31,7,0,1,1,0,47018.75,0 +5955,15811947,Gordon,850,France,Male,33,0,124781.67,1,0,1,33700.52,0 +5956,15649024,Trujillo,748,France,Female,39,9,132865.56,1,1,1,59636.43,1 +5957,15594928,Pagnotto,798,Germany,Female,38,4,129055.13,1,1,0,157147.59,0 +5958,15765532,Horton,612,Germany,Male,76,6,96166.88,1,1,1,191393.26,0 +5959,15741719,DeRose,540,France,Female,40,3,165298.12,1,0,1,199862.75,0 +5960,15665629,Chiang,719,Spain,Female,33,7,0,2,1,0,20016.59,0 +5961,15728917,Gill,598,France,Male,48,6,120682.53,1,1,0,30635.52,1 +5962,15762993,Trevisano,796,Spain,Male,32,5,102773.15,2,0,1,117832.88,0 +5963,15571193,Morrison,579,Germany,Male,42,0,144386.32,1,1,1,22497.1,1 +5964,15653521,Onuora,850,Germany,Female,40,7,104449.8,1,1,1,747.88,0 +5965,15802220,Ikenna,599,Spain,Male,35,6,137102.65,1,0,0,76870.81,0 +5966,15644132,Mancini,724,France,Female,30,9,142475.87,1,1,1,107848.24,0 +5967,15600832,Moss,508,France,Female,43,9,0,1,1,0,103726.71,0 +5968,15797919,Ting,773,Spain,Male,37,2,103195.2,2,1,0,178268.36,0 +5969,15603743,Tai,526,France,Male,28,1,112070.44,1,0,1,126281.83,0 +5970,15579714,Pan,542,France,Female,29,7,0,2,0,1,196651.72,0 +5971,15634295,Wilson,470,France,Male,35,1,96473.59,1,0,0,5962.3,0 +5972,15786680,Bianchi,805,Spain,Male,37,5,0,2,1,0,21928.81,0 +5973,15623499,Holman,548,Germany,Male,49,9,108437.89,1,0,0,127022.87,1 +5974,15691823,Obidimkpa,672,France,Male,37,5,153195.59,1,1,1,162763.01,0 +5975,15809279,Wallace,773,France,Male,45,8,96877.21,1,1,1,113950.51,0 +5976,15758039,Ash,614,France,Male,44,6,0,2,0,1,104930.46,0 +5977,15807163,Ku,537,France,Female,38,10,0,1,0,0,52337.97,1 +5978,15631639,Uspensky,704,France,Female,40,6,95452.89,1,0,1,179964.55,0 +5979,15713770,Shih,586,Spain,Male,41,3,63873.56,1,1,0,83753.64,0 +5980,15698167,Kumm,677,France,Female,24,0,148298.59,2,0,0,182913.95,0 +5981,15781710,Carey,558,Spain,Female,31,7,0,2,1,0,166720.28,0 +5982,15801296,Farber,634,Germany,Female,37,7,143258.85,2,1,0,192721.98,0 +5983,15704378,Calabrese,655,Germany,Male,37,9,121342.24,1,1,1,180241.44,0 +5984,15767891,Findlay,619,Germany,Female,28,6,99152.73,2,1,0,48475.12,0 +5985,15640667,Yu,662,France,Female,41,4,0,2,1,0,126551.48,0 +5986,15702145,Edments,705,Spain,Male,33,7,68423.89,1,1,1,64872.55,0 +5987,15679738,Brown,527,Spain,Female,35,8,0,1,1,0,98031.53,1 +5988,15636634,Lindon,630,Germany,Female,25,7,79656.81,1,1,0,93524.22,0 +5989,15809227,Chukwudi,850,France,Male,35,2,0,2,1,1,56991.66,0 +5990,15601811,Caldwell,668,France,Female,53,10,110240.04,1,0,0,183980.56,1 +5991,15625494,Li Fonti,573,France,Female,32,9,125321.84,2,1,1,130234.63,0 +5992,15723737,Pitcher,680,France,Male,27,3,0,1,1,0,32454.26,0 +5993,15682955,Capon,758,France,Female,32,2,84378.9,1,1,1,75396.43,0 +5994,15758856,Kable,597,France,Male,45,7,0,2,0,0,167756.45,0 +5995,15746065,Lo Duca,580,Germany,Male,35,10,136281.41,2,1,1,24799.47,0 +5996,15783865,Kulikova,622,France,Male,59,5,119380.37,1,1,1,60429.43,0 +5997,15745455,Navarrete,638,Germany,Male,62,4,108716.59,2,1,1,74241.09,0 +5998,15583033,Huguley,640,France,Female,20,4,0,2,0,1,78310.82,0 +5999,15644212,Han,644,Spain,Male,28,0,0,2,1,0,119419.37,0 +6000,15735688,Horsley,753,France,Female,31,6,106596.29,1,0,0,91305.77,0 +6001,15658577,Massie,629,France,Female,37,10,99546.25,3,0,1,25136.95,1 +6002,15606887,Singh,775,France,Female,30,5,0,1,1,0,193880.6,1 +6003,15783026,H?,701,France,Female,41,2,0,1,1,0,47856.78,0 +6004,15579892,Doyle,708,Spain,Male,19,7,112615.86,1,1,1,4491.77,0 +6005,15802088,Grant,521,Spain,Female,22,10,0,1,1,1,101311.95,0 +6006,15589323,Law,636,France,Female,24,9,0,2,0,1,38830.72,0 +6007,15636395,King,529,France,Female,31,5,0,2,1,0,26817.23,0 +6008,15712772,Onwubiko,757,France,Male,28,3,75381.15,1,1,1,199727.72,0 +6009,15700937,Romano,767,Spain,Female,24,5,0,2,1,1,67445.85,0 +6010,15766659,Okwudilichukwu,525,Spain,Male,33,5,0,2,1,0,161002.29,0 +6011,15814033,Milano,759,Spain,Male,38,1,0,2,1,0,20778.39,0 +6012,15783007,Parker,520,Germany,Female,45,1,123086.39,1,1,1,41042.4,1 +6013,15654183,Aitken,738,France,Female,26,3,0,2,1,0,67484.16,0 +6014,15609899,Obiora,548,Spain,Male,37,4,0,1,1,0,121763.68,0 +6015,15747323,Vasilyeva,535,Spain,Male,48,9,109472.47,1,1,0,157358.43,1 +6016,15582591,Chiabuotu,615,Spain,Male,59,4,155766.05,1,1,1,110275.17,0 +6017,15738835,Slater,850,Germany,Male,38,7,101985.81,2,0,0,43801.27,0 +6018,15782404,Hughes,487,France,Female,34,2,96019.5,1,0,0,9085,0 +6019,15697480,Menkens,731,France,Male,30,7,0,2,0,1,143086.09,0 +6020,15697045,Pisani,726,Spain,Female,35,9,0,2,0,1,100556.98,0 +6021,15781234,Y?an,609,France,Female,35,2,147900.43,1,1,0,140000.29,0 +6022,15579891,Milani,714,France,Male,52,4,100755.66,1,1,1,186775.25,0 +6023,15805690,Chin,694,Spain,Female,35,7,0,1,1,0,133570.43,1 +6024,15612139,Fu,786,France,Female,33,0,83036.05,1,0,1,154990.58,1 +6025,15568834,Howells,698,Spain,Male,27,6,125427.37,2,0,0,27654.44,0 +6026,15709917,Ni,601,France,Female,46,3,98202.76,1,0,0,137763.93,0 +6027,15718843,Maslova,769,Spain,Male,41,1,72509.91,1,1,0,25723.73,0 +6028,15799494,Forster,850,Germany,Male,44,3,140393.65,2,0,1,186285.52,0 +6029,15673439,Sun,646,Spain,Female,50,5,142644.64,2,1,1,142208.5,1 +6030,15669011,Bocharova,659,France,Female,44,9,23503.31,1,0,1,169862.01,1 +6031,15581388,Y?an,487,Spain,Male,33,8,145729.71,1,1,0,41365.85,0 +6032,15743153,Singh,740,Germany,Female,40,2,122295.17,2,1,1,30812.84,0 +6033,15579787,Nkemakonam,686,France,Male,39,4,0,2,1,0,155023.93,0 +6034,15759966,Chiemenam,612,Spain,Female,36,5,119799.27,2,1,0,159416.58,0 +6035,15601045,Angelo,655,Spain,Male,37,8,163708.58,2,0,0,76259.23,0 +6036,15764021,Frolov,617,France,Male,34,1,61687.33,2,1,0,105965.25,0 +6037,15687218,West,674,France,Female,27,4,79144.34,1,0,1,50743.83,0 +6038,15626452,Beatham,711,Spain,Male,32,5,0,2,1,1,147720.27,0 +6039,15700964,Pollard,624,Germany,Female,27,7,104848.68,1,1,1,167387.36,0 +6040,15768887,Hsing,597,Spain,Male,26,5,0,2,0,1,95159.13,0 +6041,15735358,Dowse,682,Spain,Male,46,4,0,1,1,1,4654.28,0 +6042,15749472,Lucciano,775,France,Male,45,8,0,1,1,0,130376.68,0 +6043,15685872,Godfrey,727,France,Female,29,1,146652.01,1,1,1,173486.39,0 +6044,15760851,Gratton,629,France,Male,31,6,0,2,1,0,93881.75,0 +6045,15734588,Manning,684,France,Male,46,0,0,2,1,1,36376.97,0 +6046,15784594,Mazzi,549,Germany,Female,37,1,130622.34,2,1,1,128499.94,0 +6047,15606435,Wall,593,Germany,Male,69,2,187013.13,2,0,1,105898.69,0 +6048,15790247,Sims,536,Spain,Male,40,9,0,2,1,1,11959.03,0 +6049,15676433,Allan,707,France,Female,36,6,0,1,0,0,98810.78,0 +6050,15625905,Griffen,592,Spain,Male,41,0,0,2,1,0,65906.07,0 +6051,15626414,Russell,703,France,Male,44,6,98862.54,1,1,0,151516.7,0 +6052,15623220,Brown,723,Spain,Female,45,4,0,2,1,0,37214.39,0 +6053,15752857,Palerma,452,Germany,Male,52,1,98443.14,2,0,0,92033.98,0 +6054,15677908,Gilbert,552,Spain,Male,42,4,0,2,0,0,195692.3,0 +6055,15773013,Uvarov,633,France,Female,47,0,0,1,1,1,6342.84,1 +6056,15623972,Wisdom,479,Germany,Female,23,9,123575.51,1,0,1,95148.28,0 +6057,15738627,Hussain,768,France,Male,25,6,0,2,1,1,21215.67,0 +6058,15643392,Woods,742,France,Male,31,4,105239.1,1,1,1,19700.24,0 +6059,15684868,Cameron,668,Germany,Male,56,9,110993.79,1,1,0,134396.64,1 +6060,15627854,Mai,707,Spain,Male,44,3,0,2,1,1,135077.01,0 +6061,15669253,Gibson,754,Spain,Male,39,7,157691.98,2,1,0,133600.89,1 +6062,15758023,Grigoryeva,544,Germany,Male,47,5,105245.21,1,0,0,99922.08,1 +6063,15574558,Gunter,718,Spain,Male,32,8,0,2,1,1,41399.33,0 +6064,15635256,Arcuri,762,France,Male,31,7,117687.35,1,1,1,159344.43,0 +6065,15680399,Tung,772,France,Male,23,2,0,2,1,0,18364.19,0 +6066,15674720,Smith,691,Germany,Female,37,7,123067.63,1,1,1,98162.44,1 +6067,15580249,Lori,502,France,Male,45,0,0,1,0,0,84663.21,0 +6068,15675431,Chidimma,563,France,Female,34,6,0,2,0,0,36536.93,0 +6069,15698285,Ting,676,France,Female,41,4,101457.14,1,1,1,79101.67,0 +6070,15810775,Tsao,576,Spain,Male,52,2,100549.43,2,1,1,16644.16,0 +6071,15678173,Collee,629,Spain,Male,35,4,174588.8,2,0,1,158420.14,0 +6072,15665222,Lettiere,625,Spain,Male,52,8,121161.57,1,1,0,48988.28,0 +6073,15803908,Fu,628,France,Male,45,9,0,2,1,1,96862.56,0 +6074,15586039,Bergamaschi,471,Germany,Female,36,5,90063.74,2,1,1,96366.7,0 +6075,15802570,Dyer,811,France,Female,45,5,0,2,1,1,146123.19,0 +6076,15781451,Buccho,504,France,Male,42,3,134936.97,2,0,0,135178.91,0 +6077,15721019,Jones,687,France,Female,24,3,110495.27,1,1,0,158615.41,0 +6078,15738588,Nebechi,660,Germany,Female,37,2,133200.09,1,0,0,71433.88,0 +6079,15730657,Ibekwe,548,France,Female,41,4,82596.8,1,0,1,55672.09,0 +6080,15739292,Gorshkov,609,Germany,Male,31,9,103837.75,1,1,1,150218.11,0 +6081,15725945,Nweke,659,Spain,Female,42,2,0,1,0,0,162734.31,1 +6082,15813159,Hairston,526,France,Male,52,8,93590.47,1,0,1,21228.71,1 +6083,15636820,Loggia,725,Germany,Male,40,8,104149.66,1,1,0,62027.9,0 +6084,15603880,Morgan,519,Germany,Male,38,1,114141.64,1,1,1,60988.21,1 +6085,15619494,Abdulov,562,Germany,Female,31,9,117153,1,1,1,108675.01,0 +6086,15596992,Norris,482,Germany,Male,45,7,156353.46,1,1,0,72643.95,1 +6087,15735025,Clark,535,Spain,Male,37,3,175534.78,2,1,1,9241.52,0 +6088,15730759,Chukwudi,561,France,Female,27,9,135637,1,1,0,153080.4,1 +6089,15752912,Perkin,661,France,Female,30,7,0,2,1,0,72196.57,0 +6090,15711316,Ch'ang,771,France,Male,27,2,0,2,1,1,199527.34,0 +6091,15738785,Kang,545,France,Male,26,7,0,2,0,1,156598.23,0 +6092,15777896,Chukwudi,850,Germany,Female,33,2,83415.04,1,0,1,74917.64,0 +6093,15628963,Frolova,601,Germany,Male,43,3,141859.12,2,1,1,111249.62,0 +6094,15742126,Chiu,712,Germany,Male,38,7,132767.66,2,1,1,59115.77,0 +6095,15575623,Simpson,589,France,Female,31,10,110635.32,1,1,0,148218.86,0 +6096,15741652,McLean,600,Spain,Male,37,8,177657.35,1,1,1,77142.32,0 +6097,15738884,Hu,642,Germany,Male,41,4,157777.58,1,1,0,67484.6,0 +6098,15615050,Savage,575,Germany,Male,47,9,107915.94,2,1,1,63452.18,1 +6099,15803005,Wallace,570,Germany,Female,57,5,86568.75,1,0,1,103660.31,0 +6100,15743498,Winter,532,Germany,Male,52,9,137755.76,1,1,0,163191.99,1 +6101,15720463,Ho,796,France,Male,30,2,137262.71,2,1,0,62905.29,0 +6102,15588695,Su,833,Spain,Male,32,6,0,1,1,1,44323.22,1 +6103,15665802,Li Fonti,642,Spain,Female,36,6,0,2,1,1,97938.59,0 +6104,15571144,Ives,655,France,Male,28,10,0,2,0,1,126565.21,0 +6105,15750731,Trevisani,736,Germany,Male,50,9,116309.01,1,1,0,185360.4,1 +6106,15605134,Bond,617,France,Female,34,0,131244.65,2,1,0,183229.02,0 +6107,15626044,Lettiere,762,Germany,Male,28,3,125155.83,2,1,1,106024.02,0 +6108,15737910,Houghton,703,Germany,Male,35,5,140691.08,2,1,0,167810.26,0 +6109,15761076,Lei,507,France,Male,41,3,58820.32,2,1,1,138536.09,0 +6110,15710105,Stirling,581,Germany,Female,26,3,105099.45,1,1,1,184520,1 +6111,15577402,Grant,593,France,Male,31,9,0,2,0,1,20492.16,0 +6112,15803337,Baresi,648,France,Male,23,9,168372.52,1,1,0,134676.72,0 +6113,15654372,Pearce,462,Germany,Male,34,1,94682.56,2,1,0,138478.2,0 +6114,15585867,Rutledge,596,Spain,Male,36,2,0,2,0,1,125557.95,0 +6115,15662488,Udegbunam,627,France,Female,44,5,0,2,1,0,82969.61,1 +6116,15604813,Zaytseva,494,France,Male,40,7,0,2,0,1,158071.69,0 +6117,15611644,Onyemauchechukwu,627,France,Male,73,0,146329.73,1,0,1,43615.67,0 +6118,15674928,Mullah,850,Spain,Male,37,2,0,2,1,0,119969.99,0 +6119,15656100,Candler,632,France,Female,49,5,167962.7,1,0,0,140201.21,0 +6120,15764293,Konovalova,490,France,Male,33,1,0,2,1,1,80792.83,0 +6121,15636423,Lei,715,France,Male,40,7,0,1,1,1,141359.11,0 +6122,15607629,Hollis,679,France,Male,48,8,0,2,1,0,23344.94,0 +6123,15577313,Lionel,619,France,Male,44,3,116967.68,1,1,0,5075.17,1 +6124,15714493,Francis,465,Spain,Female,33,6,0,2,1,1,95500.98,0 +6125,15643359,Carter,736,Spain,Male,32,7,0,1,0,1,79082.62,0 +6126,15687913,Mai,501,Germany,Female,34,7,93244.42,1,0,1,199805.63,0 +6127,15790935,Johnson,535,France,Female,29,5,0,2,0,1,52709.55,0 +6128,15708693,Sherman,759,France,Female,33,2,0,2,1,0,56583.88,0 +6129,15672016,Sabbatini,819,France,Male,35,1,0,2,0,1,3385.04,0 +6130,15727605,Shih,533,Germany,Male,43,4,80442.06,2,0,1,12537.42,0 +6131,15651144,Yao,632,Germany,Female,35,2,150561.03,2,0,0,64722.61,0 +6132,15749401,Ko,686,France,Male,60,9,0,3,1,1,75246.21,1 +6133,15691874,Kazakova,687,France,Female,34,9,125474.44,1,1,0,198929.84,0 +6134,15620735,Chiganu,667,Germany,Female,33,4,127076.68,2,1,0,69011.66,0 +6135,15769781,Nucci,699,Spain,Female,25,8,0,2,1,1,52404.47,0 +6136,15624611,Marsden,497,Spain,Male,37,8,128650.11,2,1,1,163641.53,0 +6137,15773071,Serena,780,Spain,Female,33,6,145580.61,1,1,1,154598.56,0 +6138,15720371,McLean,652,France,Female,51,3,0,1,1,0,173989.47,1 +6139,15717984,Longo,477,France,Male,47,9,144900.58,1,1,0,61315.37,1 +6140,15806407,Wilson,652,France,Female,37,4,0,2,1,0,143393.24,0 +6141,15785042,Hsiung,488,France,Female,31,8,97588.6,1,0,0,124210.53,0 +6142,15809302,Wright,572,France,Male,24,1,0,2,1,1,151460.84,0 +6143,15677550,Folliero,755,France,Female,38,1,0,2,1,0,20734.81,0 +6144,15654096,Johnston,779,Germany,Female,24,10,122200.31,2,1,0,43705.56,0 +6145,15617320,Palermo,693,Spain,Female,46,3,151709.33,1,1,0,180736.24,0 +6146,15653065,Nwabugwu,530,Spain,Female,22,7,0,2,1,0,104170.48,0 +6147,15649112,Endrizzi,738,Spain,Female,33,3,122134.4,2,0,1,27867.59,0 +6148,15690526,Tuan,690,Germany,Male,31,2,137260.45,2,1,0,55387.28,0 +6149,15806945,Udobata,611,France,Female,30,9,88594.14,1,1,0,196332.45,0 +6150,15670066,Ibezimako,643,Spain,Male,34,6,0,2,1,1,116046.22,0 +6151,15625761,Maclean,632,Germany,Male,41,8,127205.32,4,1,0,93874.87,1 +6152,15761525,Shaw,727,Spain,Female,31,10,96997.09,2,0,0,76614.04,0 +6153,15735080,Cummins,508,France,Female,64,2,0,1,1,1,6076.62,0 +6154,15619537,Lavrentiev,550,France,Male,31,5,142200.19,2,1,1,122221.71,0 +6155,15598162,Saunders,754,Germany,Female,39,3,160761.41,1,1,1,24156.03,0 +6156,15694300,Fiorentino,759,France,Male,26,4,0,2,1,0,135394.62,0 +6157,15637235,Knight,794,Spain,Male,33,8,0,2,0,0,91340.02,0 +6158,15612444,Manfrin,549,France,Male,29,3,0,2,1,0,146090.38,0 +6159,15626457,Zetticci,671,France,Male,31,0,116234.61,1,1,0,172096.08,0 +6160,15627995,Angelo,756,Germany,Female,26,5,155143.52,1,0,1,135034.57,1 +6161,15706128,Zhdanov,632,France,Female,21,1,0,2,1,0,84008.66,0 +6162,15666430,Peck,579,France,Male,38,8,0,2,0,0,91763.67,0 +6163,15627385,Uwaezuoke,748,France,Male,34,5,84009.47,1,1,1,137001.1,0 +6164,15581323,White,488,Germany,Female,28,7,139246.22,2,1,0,106799.49,0 +6165,15608109,Greco,710,Germany,Male,58,7,170113,2,0,1,10494.64,0 +6166,15801942,Chu,619,Spain,Female,41,8,0,3,1,1,79866.73,1 +6167,15567431,Kodilinyechukwu,773,France,Male,64,2,145578.28,1,0,1,186172.85,0 +6168,15810167,Scott,657,Spain,Male,75,7,126273.95,1,0,1,91673.6,0 +6169,15644501,Enyinnaya,579,France,Female,26,10,162482.76,1,1,1,18458.2,0 +6170,15785290,Hao,542,France,Male,29,9,0,1,1,0,8342.35,0 +6171,15611157,McElhone,709,France,Female,32,2,87814.89,1,1,0,138578.37,0 +6172,15673837,Ko,617,Spain,Male,61,3,113858.95,1,1,1,38129.22,0 +6173,15656822,Day,568,Germany,Male,43,5,87612.64,4,1,1,107155.4,1 +6174,15580560,Harris,769,France,Female,73,1,0,1,1,1,29792.11,0 +6175,15760641,Gerald,608,Germany,Male,26,1,106648.98,1,0,1,7063.6,0 +6176,15587584,Nebeuwa,503,Spain,Male,31,4,0,2,1,1,21645.06,0 +6177,15604146,Kaodilinakachukwu,608,Germany,Female,38,8,103653.51,2,1,1,137079.86,0 +6178,15813974,Maruff,731,Germany,Male,37,3,116880.53,1,0,0,172718.35,1 +6179,15746986,Howe,850,Germany,Female,40,4,97990.49,2,0,0,106691.02,0 +6180,15759741,Knepper,591,Germany,Female,34,4,150635.3,1,1,1,72274.84,0 +6181,15734892,Fennell,579,Spain,Male,37,4,0,2,1,1,32246.63,0 +6182,15797194,T'ao,570,France,Male,39,10,129674.89,2,1,0,80552.36,0 +6183,15723786,Morris,709,France,Female,37,9,0,2,1,0,16733.59,0 +6184,15642726,Holmes,611,France,Male,53,3,83568.26,1,0,0,1235.49,0 +6185,15664339,Yu,775,Spain,Male,48,4,178144.91,2,0,0,50168.41,1 +6186,15754526,Walker,699,Germany,Male,36,6,147137.74,1,1,1,33687.9,0 +6187,15703037,Edwards,618,France,Male,37,5,0,1,0,1,178705.45,1 +6188,15751412,Harvey,704,France,Male,36,3,114370.41,1,0,1,66810.48,0 +6189,15609558,McDonald,835,Germany,Female,47,5,108289.28,2,1,1,45859.55,1 +6190,15572408,Chambers,714,Germany,Male,39,3,149887.49,2,1,0,63846.36,0 +6191,15613923,Reed,581,Spain,Female,43,4,170172.9,1,0,1,100236.02,0 +6192,15747000,Shih,592,France,Male,27,3,0,2,1,1,19645.65,0 +6193,15731781,Onyemachukwu,551,France,Male,43,7,0,2,1,0,178393.68,0 +6194,15727198,Teng,689,Germany,Female,28,2,64808.32,2,0,0,78591.15,0 +6195,15794273,Hand,604,France,Female,56,0,62732.65,1,0,1,124954.56,0 +6196,15804950,Onyemauchechukwu,514,France,Female,41,7,0,2,1,1,3756.65,0 +6197,15576304,Bailey,698,France,Male,29,5,95167.55,1,1,1,152723.23,0 +6198,15645200,Chiang,581,Germany,Female,54,2,152508.99,1,1,0,187597.98,1 +6199,15779627,Maclean,573,Germany,Male,31,0,134644.19,1,1,1,70381.49,0 +6200,15750755,Yobachi,449,Spain,Female,33,8,0,2,0,0,156792.89,0 +6201,15569654,Munro,850,Germany,Female,31,3,51293.47,1,0,0,35534.68,0 +6202,15753079,Chidi,612,France,Male,41,5,0,3,0,0,151256.22,0 +6203,15684995,Chamberlain,690,Spain,Male,49,8,116622.73,1,0,1,51011.29,0 +6204,15790763,Trujillo,599,Spain,Female,49,2,0,2,1,0,111190.53,0 +6205,15766458,Tang,498,France,Male,33,1,198113.86,1,1,0,69664.35,0 +6206,15616221,Wilson,497,France,Female,29,4,85646.81,1,0,0,63233.02,1 +6207,15776124,Mann,802,Spain,Male,51,7,0,1,0,1,40855.79,0 +6208,15665811,Parry,644,France,Male,33,9,141234.98,1,1,0,95673.05,0 +6209,15729804,Manfrin,714,France,Male,34,10,0,2,1,1,80234.14,0 +6210,15714062,Millar,690,France,Female,40,9,77641.99,1,0,0,189051.59,1 +6211,15592197,Simmons,522,Spain,Male,30,3,0,2,1,0,145490.85,0 +6212,15793116,Beneventi,502,Germany,Female,40,7,117304.29,1,0,0,196278.32,0 +6213,15638231,Chung,730,Spain,Female,62,2,0,2,1,1,162889.1,0 +6214,15697678,Maxwell,590,Germany,Male,36,6,92340.69,2,1,1,174667.58,0 +6215,15800412,Dale,458,Germany,Male,35,9,146780.52,2,1,1,3476.38,0 +6216,15597610,Stevens,553,Spain,Male,41,6,144974.55,1,1,1,19344.92,0 +6217,15726634,Wei,479,France,Male,47,1,0,1,1,0,95270.83,0 +6218,15670866,Chiu,693,France,Male,31,2,0,2,1,1,107759.31,0 +6219,15667462,Duncan,707,Spain,Male,43,10,0,2,1,0,118368.2,0 +6220,15662574,Brady,636,Spain,Male,37,1,115137.26,1,1,0,52484.01,0 +6221,15716926,Macleod,807,France,Male,33,10,101952.97,2,1,0,178153.65,0 +6222,15603554,Berkeley,513,France,Female,45,0,164649.52,3,1,0,49915.52,1 +6223,15716800,Kaur,582,France,Male,31,2,0,2,1,1,33747.03,0 +6224,15679429,Bell,694,France,Male,32,0,91956.49,1,1,1,59961.81,0 +6225,15616122,Nwokike,777,France,Male,39,8,0,2,1,1,18613.52,0 +6226,15742172,Williamson,598,Germany,Male,32,9,123938.6,2,1,0,198894.42,0 +6227,15792305,Mountgarrett,762,Germany,Male,46,6,123571.77,3,0,1,57014.17,1 +6228,15636016,Wreford,588,France,Female,34,3,120777.88,1,1,1,131729.52,0 +6229,15733138,Paterson,663,Germany,Male,42,5,90248.79,1,1,1,79169.73,0 +6230,15669741,Hou,777,France,Male,36,7,0,1,1,0,106472.34,0 +6231,15616954,Smith,592,France,Male,71,4,0,2,0,1,17013.54,0 +6232,15729238,Peng,631,Germany,Male,48,1,106396.48,1,1,1,150661.42,1 +6233,15718242,Wollstonecraft,725,Germany,Female,47,1,104887.43,1,0,0,86622.56,1 +6234,15682914,Bolton,850,France,Male,34,2,72079.71,1,1,1,115767.93,0 +6235,15654274,Corrie,540,France,Male,37,6,0,2,1,0,141998.89,0 +6236,15691457,Boyle,674,Spain,Male,36,2,0,2,1,1,182787.17,0 +6237,15719649,Lambie,553,France,Male,38,3,99844.68,1,0,0,187915.7,0 +6238,15778897,Cartwright,630,France,Female,28,1,0,2,1,1,133267.78,0 +6239,15589437,Lu,466,France,Male,26,3,156815.71,1,1,1,137476.09,0 +6240,15682369,Pisano,613,France,Male,47,6,146034.74,1,1,1,77146.14,0 +6241,15626507,Chukwubuikem,558,France,Male,27,1,152283.39,1,1,0,183271.15,0 +6242,15571995,Harper,775,Germany,Female,33,1,118897.1,2,1,1,26362.4,0 +6243,15673333,Wilson,698,Germany,Male,52,8,96781.39,1,1,1,153373.71,0 +6244,15748752,Ch'in,608,Germany,Male,33,1,102772.67,2,1,0,70705.58,0 +6245,15725302,Streeton,670,Spain,Female,20,4,0,2,1,0,119759.24,0 +6246,15722083,Ch'ang,591,Spain,Male,39,8,0,2,0,0,42392.24,0 +6247,15771442,Pennington,633,France,Male,40,4,150578,1,0,1,34670.62,1 +6248,15803633,T'ien,678,France,Female,46,1,0,2,0,0,82106.19,0 +6249,15672185,Liu,590,France,Male,47,3,0,2,1,0,171774.5,0 +6250,15806486,Cunningham,705,France,Female,48,0,0,2,0,0,149772.61,0 +6251,15570895,Ch'in,608,France,Male,42,10,163548.07,1,1,0,38866.85,0 +6252,15614520,Smith,682,France,Female,37,8,148580.12,1,1,0,35179.18,0 +6253,15687492,Anderson,596,Germany,Male,32,3,96709.07,2,0,0,41788.37,0 +6254,15675337,Forbes,395,Germany,Female,34,5,106011.59,1,1,1,17376.57,1 +6255,15721047,Ansell,578,Germany,Male,37,1,135650.88,1,1,0,199428.19,0 +6256,15589017,Chiu,547,Germany,Male,55,4,111362.76,3,1,0,16922.28,1 +6257,15611186,Yevdokimova,609,France,Male,37,1,39344.83,1,1,1,178291.89,1 +6258,15617301,Chamberlin,774,Germany,Male,36,9,130809.77,1,1,0,152290.28,0 +6259,15726046,Johnston,712,France,Female,27,2,133009.51,1,1,0,126809.15,0 +6260,15585748,McDonald,585,Germany,Female,28,9,135337.49,2,1,1,40385.61,0 +6261,15672826,Chen,666,France,Female,32,10,112536.57,2,1,1,34350.54,0 +6262,15595162,Cattaneo,708,Spain,Female,35,8,122570.69,1,0,0,199005.88,0 +6263,15650026,Barclay-Harvey,513,France,Male,44,1,63562.02,2,0,1,52629.73,1 +6264,15745826,Dawson,445,France,Male,37,3,0,2,1,1,180012.39,0 +6265,15708610,Costa,690,Germany,Male,44,9,100368.63,2,0,0,35342.33,0 +6266,15624471,Chikwado,850,France,Male,37,6,0,2,1,0,109291.22,0 +6267,15590097,Ch'eng,537,Spain,Female,33,7,136082,1,1,0,62746.54,0 +6268,15689328,Harrison,705,Germany,Male,48,9,114169.16,1,0,0,173273.2,1 +6269,15582154,Crawford,670,France,Female,45,5,47884.92,1,1,1,54340.24,0 +6270,15734626,Gibson,652,Spain,Female,36,1,0,2,1,1,19302.78,0 +6271,15702806,Martin,696,Spain,Male,24,9,0,1,0,0,10883.52,0 +6272,15620756,Stokes,747,France,Male,49,6,202904.64,1,1,1,17298.72,1 +6273,15611331,Niu,511,France,Female,46,1,0,1,1,1,115779.48,1 +6274,15576935,Ampt,743,Spain,Male,43,2,161807.18,2,0,1,93228.86,1 +6275,15661275,Wynn,532,Germany,Male,52,3,110791.97,1,1,0,148704.77,1 +6276,15814940,Lawrence,642,Spain,Female,33,9,0,2,1,1,150475.14,0 +6277,15768471,Wagner,554,Germany,Female,54,6,108755,1,1,0,40914.32,1 +6278,15697391,Argyle,604,Spain,Female,34,3,0,2,1,0,38587.7,0 +6279,15793346,Ofodile,602,France,Female,72,3,0,2,1,1,171260.66,0 +6280,15608338,Chiemenam,757,Spain,Female,55,9,117294.12,4,1,0,94187.47,1 +6281,15578546,Akobundu,491,Germany,Male,26,4,102251.14,1,1,1,145900.89,0 +6282,15656921,Locke,850,France,Male,31,4,0,2,0,0,152298.28,0 +6283,15761340,Bullen,521,France,Male,22,5,0,2,1,1,99828.45,0 +6284,15591135,Forster,726,France,Male,37,2,132057.92,2,1,0,34743.98,0 +6285,15623219,Smith,596,France,Male,33,8,0,1,1,0,121189.3,1 +6286,15655229,Craig,850,Germany,Female,35,7,114285.2,1,0,1,129660.59,0 +6287,15805884,Archer,637,France,Female,41,9,0,2,1,0,145477.36,0 +6288,15668289,McWilliams,690,Spain,Male,32,2,76087.98,1,0,1,151822.66,0 +6289,15568562,Moss,689,France,Male,40,8,160272.27,1,1,0,49656.24,0 +6290,15773276,Townsend,633,Spain,Male,63,4,114552.6,1,1,0,73856.28,1 +6291,15622801,Brown,555,France,Female,27,8,102000.17,1,1,1,116757,0 +6292,15779886,Munson,563,Spain,Male,24,7,0,2,0,0,16319.56,0 +6293,15713673,T'ien,494,France,Female,33,1,137853,1,0,1,90273.85,0 +6294,15783083,Shubin,534,France,Male,27,9,0,2,1,0,161344.13,0 +6295,15742824,Isayeva,696,Germany,Male,42,7,162318.61,1,1,0,121061.89,0 +6296,15621550,Hung,535,Spain,Female,50,1,140292.58,3,0,0,69531.22,1 +6297,15799480,Webb,600,France,Male,34,0,0,2,0,1,3756.23,0 +6298,15625247,Scott,807,France,Female,34,1,0,1,0,0,114448.13,0 +6299,15755241,Rahman,714,France,Female,52,2,0,1,0,1,144045.08,1 +6300,15575679,Lori,590,France,Male,24,7,126431.54,1,1,0,58781.11,0 +6301,15668235,Cooke,614,France,Female,41,3,123475.04,1,1,1,179227.52,0 +6302,15683183,Volkova,766,Germany,Female,45,6,97652.96,1,1,0,127332.33,0 +6303,15684592,Lamb,557,Spain,Male,42,4,0,2,0,1,86642.38,0 +6304,15591169,Hawes,788,Germany,Female,49,4,137455.99,1,1,0,184178.29,1 +6305,15653455,Smith,648,France,Female,38,2,0,2,0,1,9551.49,0 +6306,15732563,Swanton,726,Germany,Female,33,7,99046.31,2,1,1,56053.06,0 +6307,15656471,Mitchell,773,France,Male,33,9,0,2,1,1,1118.31,0 +6308,15598510,Colombo,583,Germany,Male,27,4,105907.42,2,1,1,195732.04,0 +6309,15766427,Shaw,565,Germany,Male,52,5,97720.35,2,1,0,175070.94,1 +6310,15785342,Shipp,705,France,Male,25,9,0,2,0,1,112331.19,0 +6311,15641595,Jonathan,685,Spain,Male,43,4,97392.18,2,1,0,43956.83,0 +6312,15798429,Hernandez,741,France,Male,29,8,0,2,1,1,115994.52,0 +6313,15648136,Green,658,Germany,Female,28,9,152812.58,1,1,0,166682.57,0 +6314,15812482,Young,575,France,Male,27,3,139301.68,1,1,0,99843.98,0 +6315,15790810,Han,844,France,Female,41,10,76319.64,1,1,1,141175.18,1 +6316,15687421,Highland,559,Spain,Male,67,9,125919.35,1,1,0,175910.95,1 +6317,15765643,Hamilton,725,France,Male,37,6,124348.38,2,0,1,176984.34,0 +6318,15654878,Yobanna,450,France,Male,29,7,117199.8,1,1,1,43480.63,0 +6319,15686835,Crawford,738,Germany,Female,57,9,148384.64,1,0,0,155047.11,1 +6320,15768340,Beavers,642,Germany,Female,19,3,113905.48,1,1,1,176137.2,0 +6321,15673599,Williamson,618,Spain,Male,32,5,133476.09,1,0,1,154843.4,0 +6322,15689096,Beneventi,590,France,Male,47,0,117879.32,1,1,1,8214.46,0 +6323,15684294,Chidumaga,735,France,Male,50,2,0,2,0,1,147075.69,0 +6324,15615828,Mitchell,550,France,Male,34,8,122359.5,1,0,0,116495.55,0 +6325,15746012,Chibugo,729,Spain,Female,28,0,0,2,1,1,31165.06,1 +6326,15615797,Hyde,743,Germany,Male,59,5,108585.35,1,1,1,192127.22,1 +6327,15788494,Alekseeva,555,France,Male,31,8,145875.74,1,1,0,137491.23,0 +6328,15793856,Abdulov,667,Spain,Female,36,3,121542.57,2,1,1,186841.71,0 +6329,15629545,Buckley,790,Spain,Female,41,7,109508.68,1,0,0,86776.38,0 +6330,15661198,Howard,727,Germany,Male,34,2,146407.11,1,1,1,72073.72,0 +6331,15715117,Peel,744,France,Female,39,6,0,1,0,0,10662.58,0 +6332,15701074,Herz,629,Germany,Male,35,8,112330.83,1,1,1,91001.02,0 +6333,15793046,Holden,619,France,Female,35,4,90413.12,1,1,1,20555.21,0 +6334,15623744,McLean,634,France,Male,34,8,105302.66,1,1,1,123164.97,0 +6335,15611329,Findlay,608,Spain,Female,35,6,0,2,1,1,143463.28,0 +6336,15740428,Wyatt,507,France,Female,35,1,0,2,0,0,92131.54,0 +6337,15781534,Rapuluolisa,536,Germany,Female,35,4,121520.36,1,0,0,77178.42,0 +6338,15618243,Buckland,730,Spain,Female,43,1,103960.38,1,1,1,193650.16,0 +6339,15784161,Hargreaves,583,Germany,Male,39,8,102945.01,1,0,0,52861.89,0 +6340,15700325,Onyeoruru,644,France,Female,24,8,92760.55,1,1,0,35896.75,0 +6341,15659064,Salas,790,Spain,Male,37,8,0,2,1,1,149418.41,0 +6342,15658364,Laney,807,Germany,Female,40,1,134590.21,1,1,1,46253.65,0 +6343,15704340,Fu,581,France,Female,37,10,104255.03,1,1,0,86609.37,0 +6344,15793455,Tien,627,Spain,Female,55,6,0,1,0,0,91943.94,1 +6345,15579777,Sazonova,850,France,Male,41,3,0,2,1,0,128892.36,0 +6346,15632345,Tuan,754,France,Female,35,4,0,2,1,0,44830.71,0 +6347,15814468,Wei,551,Germany,Male,50,1,121399.98,1,0,1,84508.44,1 +6348,15754820,Bergamaschi,637,Germany,Male,35,8,147127.81,2,1,1,84760.7,0 +6349,15707505,Taylor,699,Spain,Male,31,8,125927.51,2,1,0,147661.47,0 +6350,15699507,Messersmith,542,France,Female,25,7,0,2,0,1,82393.08,0 +6351,15799600,Coles,640,Germany,Male,48,1,111599.32,1,0,1,135995.58,0 +6352,15794472,Brookes,553,France,Female,27,3,0,2,0,0,159800.16,0 +6353,15646632,Reid,741,France,Male,38,9,0,2,1,0,14379.01,0 +6354,15676353,Etheridge,598,France,Male,35,8,114212.6,1,1,1,74322.85,0 +6355,15566312,Jolly,660,Spain,Female,42,5,0,3,1,1,189016.24,1 +6356,15570414,Chizoba,618,Spain,Male,41,4,115251.64,1,0,0,136435.75,0 +6357,15776743,Eberegbulam,647,France,Male,43,9,0,2,1,1,78488.39,0 +6358,15674637,Pagnotto,491,France,Female,68,3,107571.61,1,0,1,113695.99,0 +6359,15730418,Lucchesi,652,France,Female,32,2,0,2,1,0,54628.11,0 +6360,15739972,Hughes,650,Germany,Female,45,9,152367.21,3,1,0,150835.21,1 +6361,15661591,Panicucci,413,Germany,Male,39,1,130969.77,2,1,1,158891.79,0 +6362,15675585,Burns,416,Germany,Female,25,0,97738.97,2,1,1,160523.33,0 +6363,15814750,Ricci,629,Spain,Male,34,8,0,2,1,1,180595.02,0 +6364,15593454,Lambert,678,Spain,Female,40,4,113794.22,1,1,0,16618.76,0 +6365,15663421,Esposito,527,Spain,Male,28,6,128396.33,2,1,0,79919.97,0 +6366,15576196,Benson,743,Spain,Female,48,5,118207.69,2,0,0,186489.14,1 +6367,15677324,Botts,683,Germany,Male,73,9,124730.26,1,1,1,51999.5,0 +6368,15568742,Parkes,536,France,Female,41,9,0,1,1,0,121299.14,0 +6369,15693764,Mai,663,Spain,Male,52,0,136298.65,1,1,0,144593.3,1 +6370,15714260,Castiglione,646,France,Female,38,2,0,2,0,0,178752.73,0 +6371,15798200,Manna,707,France,Male,35,2,0,3,1,1,94148.3,0 +6372,15656627,Lin,602,France,Male,34,5,0,2,1,1,77414.45,0 +6373,15791111,Fink,635,France,Female,47,2,125724.95,2,1,0,63236.97,0 +6374,15638269,Baresi,597,France,Male,67,2,0,2,0,1,108645.85,0 +6375,15807473,Morehead,503,France,Male,38,1,0,2,1,1,95153.24,0 +6376,15708534,Afamefuna,524,Spain,Female,64,5,0,1,1,0,136079.64,1 +6377,15640686,Greco,700,France,Male,46,5,95872.86,1,1,0,98273.01,1 +6378,15588904,Balashova,692,France,Male,33,9,0,1,1,0,113505.93,1 +6379,15768763,Bogdanov,562,France,Male,37,2,0,1,0,1,52525.15,1 +6380,15770543,Lowe,679,France,Male,37,7,74260.03,1,1,0,194617.98,0 +6381,15642162,Ponce,603,Germany,Male,35,1,123407.69,1,1,0,152541.89,1 +6382,15714046,Trevisano,720,Spain,Male,33,3,123783.91,2,1,1,142903.44,0 +6383,15575060,Gardner,797,France,Male,24,5,0,2,1,0,182257.61,0 +6384,15812040,Lorenzo,594,France,Male,36,6,153880.15,1,0,0,135431.72,0 +6385,15812073,Palmer,529,France,Female,31,7,0,2,1,1,175697.87,0 +6386,15706810,Zuyeva,606,Germany,Female,32,1,106301.85,2,0,1,59061.25,0 +6387,15584090,Jen,621,Spain,Female,40,7,0,2,0,1,131283.6,1 +6388,15810807,Alekseeva,513,France,Female,43,9,0,2,1,0,152499.8,0 +6389,15582033,Manfrin,753,Germany,Male,44,3,138076.47,1,1,0,15523.09,1 +6390,15687607,Chiemenam,605,France,Female,30,9,135422.31,1,0,1,186418.85,0 +6391,15588406,Chiemenam,574,Spain,Female,37,7,0,2,1,0,32262.28,0 +6392,15784099,Clark,726,France,Female,38,5,126875.62,1,1,0,128052.29,0 +6393,15701352,Fanucci,611,Spain,Female,28,3,96381.68,2,1,0,181419.29,0 +6394,15789371,Cattaneo,593,Germany,Female,41,4,119703.1,2,1,1,109783.29,0 +6395,15602845,Udinesi,466,Germany,Male,41,2,152102.18,2,1,0,181879.56,0 +6396,15707918,Bentley,741,Germany,Female,36,0,127675.39,2,1,0,74260.16,0 +6397,15602812,Holmes,684,Germany,Female,44,2,133776.86,2,0,1,49865.04,0 +6398,15675888,Austin,550,Spain,Female,33,9,72788.03,1,1,1,103608.06,0 +6399,15591822,Mackenzie,593,Spain,Male,26,9,76226.9,1,1,0,167564.82,0 +6400,15738501,Booth,601,Germany,Male,48,9,163630.76,1,0,1,41816.49,1 +6401,15585907,Collier,676,Spain,Female,30,5,0,2,0,0,179066.58,0 +6402,15579040,Hs?,556,France,Female,46,10,0,2,0,0,109184.24,0 +6403,15804211,Oluchukwu,719,France,Male,36,3,155423.17,1,1,1,199841.32,0 +6404,15736126,Sung,850,Germany,Male,55,0,98710.89,1,1,1,83617.17,1 +6405,15745399,Marino,649,Spain,Female,49,2,0,1,1,0,84863.85,1 +6406,15760749,Vinogradov,509,Spain,Male,41,7,126683.8,1,0,1,114775.53,0 +6407,15637118,Burns,684,France,Male,33,4,140700.61,1,1,0,103557.93,0 +6408,15657829,Fanucci,806,Germany,Male,30,8,168078.83,1,1,0,85028.36,1 +6409,15738497,Chukwujamuike,729,Spain,Male,44,4,107726.93,2,1,0,153064.87,0 +6410,15690695,Flynn,683,France,Female,33,9,0,2,1,1,38784.42,0 +6411,15762351,Chao,689,Spain,Female,63,1,0,2,1,1,186526.12,0 +6412,15791172,Yeh,672,Germany,Female,21,1,35741.69,1,1,0,28789.94,0 +6413,15598982,Klein,602,Germany,Female,53,5,98268.84,1,0,1,45038.29,1 +6414,15734765,Mahmood,739,France,Female,20,4,133800.98,1,0,1,150245.81,0 +6415,15642912,Tu,618,France,Female,21,2,125682.79,1,0,0,57762,0 +6416,15769516,Shcherbakov,674,France,Female,42,9,0,2,1,0,4292.72,0 +6417,15789379,Zetticci,762,France,Male,26,6,130428.78,1,1,0,173365.89,0 +6418,15695103,Carr,790,Spain,Male,37,6,0,2,1,1,119484.01,0 +6419,15801924,Browne,754,Spain,Female,27,8,0,2,0,0,121821.16,0 +6420,15767804,Feng,729,France,Male,44,6,0,2,1,0,151733.43,0 +6421,15718039,Ferguson,606,Germany,Female,47,0,137138.2,2,0,1,53784.22,0 +6422,15579994,Shaw,616,France,Male,23,8,73112.95,1,1,1,62733.05,0 +6423,15595037,Palermo,772,France,Male,47,9,152347.01,1,0,1,17671.78,0 +6424,15600720,Moore,652,Spain,Male,41,8,115144.68,1,1,0,188905.43,0 +6425,15782608,Huang,743,France,Male,43,5,0,2,0,0,113079.19,1 +6426,15566894,Gray,793,France,Male,39,3,137817.52,1,0,0,83997.79,0 +6427,15749123,Sokolova,743,Spain,Male,45,7,157332.26,1,1,0,125424.42,0 +6428,15668943,Henderson,746,France,Male,37,2,0,2,1,0,143194.05,0 +6429,15577423,Mosley,627,Germany,Female,39,5,124586.93,1,1,0,93132.61,1 +6430,15623102,Nnaemeka,713,Spain,Male,38,6,116980.78,2,0,1,76038.38,0 +6431,15728012,Everett,678,Spain,Female,40,3,128398.38,1,1,0,168658.3,0 +6432,15683363,Goddard,540,Spain,Male,39,1,0,1,0,1,108419.41,0 +6433,15699335,Kuo,615,Germany,Female,33,3,137657.25,2,1,1,171657.57,0 +6434,15574369,Bianchi,415,Spain,Male,53,5,167259.44,1,1,1,22357.25,0 +6435,15703167,Rouse,628,France,Female,45,8,0,2,1,0,193903.06,0 +6436,15754874,Nwoye,700,France,Male,26,4,119009.57,1,1,0,141926.43,0 +6437,15723216,Greco,623,Germany,Male,33,2,80002.33,1,1,1,104079.62,0 +6438,15725094,Fang,623,France,Female,37,4,140211.88,1,1,1,93832.33,0 +6439,15647974,Chiemenam,679,France,Female,44,3,118742.74,2,1,0,1568.91,0 +6440,15583371,Artemiev,632,Spain,Male,37,1,138207.08,1,1,0,60778.11,1 +6441,15772559,Burrows,790,France,Female,47,10,148636.21,1,0,1,16119.96,1 +6442,15711251,Chizuoke,514,France,Male,45,1,178827.79,1,1,0,60375.18,0 +6443,15719212,T'ien,491,France,Male,33,5,83134.3,1,1,0,187946.55,0 +6444,15764927,Rogova,753,France,Male,92,3,121513.31,1,0,1,195563.99,0 +6445,15731412,Trevisano,693,Germany,Female,37,6,95900.04,1,1,1,38196.24,0 +6446,15719170,Sagese,679,France,Female,30,1,112543.42,1,1,1,179435.21,0 +6447,15596011,Artyomova,529,Spain,Male,34,9,0,1,1,1,93208.22,0 +6448,15614834,Long,619,Spain,Female,31,3,141751.82,1,0,1,61531.86,0 +6449,15600510,Hsueh,680,Spain,Female,37,6,124140.57,2,1,0,92826.35,0 +6450,15625706,White,693,Germany,Male,45,2,116546.59,2,0,0,23140.28,1 +6451,15781409,Lazarev,834,France,Female,28,6,0,1,1,0,74287.53,0 +6452,15722583,Benjamin,636,Spain,Female,29,6,157576.47,2,1,1,101102.39,0 +6453,15677243,Wan,538,Spain,Male,43,5,0,2,1,0,126933.73,0 +6454,15815070,Romano,566,Germany,Female,44,5,141428.99,2,0,0,68408.74,0 +6455,15705899,Craig,597,Spain,Male,35,0,127510.99,1,1,1,155356.34,0 +6456,15701522,Yermolayeva,711,France,Female,29,9,0,2,0,1,3234.8,0 +6457,15755978,Tseng,606,France,Male,31,10,0,2,1,0,195209.4,0 +6458,15722090,Tseng,615,Spain,Male,51,6,81818.49,1,1,1,169149.38,0 +6459,15783526,Le Hunte,589,France,Male,36,1,100895.54,1,1,1,68075.14,0 +6460,15632125,Blake,606,Germany,Male,45,5,63832.43,1,1,1,93707.8,0 +6461,15688395,Lane,582,France,Male,29,4,0,2,0,0,156153.27,0 +6462,15666975,Sparks,710,France,Female,36,4,116085.06,1,1,0,58601.61,0 +6463,15682211,Tu,467,France,Male,57,1,0,2,1,1,114448.77,0 +6464,15637411,Tochukwu,749,France,Male,30,1,0,2,0,1,126551.65,0 +6465,15591512,Whittaker,564,Germany,Female,33,2,115761.51,1,0,1,112350.21,1 +6466,15606855,Wang,730,Spain,Male,26,6,0,2,1,1,185808.7,0 +6467,15763683,Northern,678,Germany,Male,32,4,139626.01,1,1,1,118235.52,1 +6468,15641782,Humphries,540,France,Female,31,7,0,1,0,1,183051.6,1 +6469,15677184,Cremonesi,767,France,Female,35,6,115576.44,1,0,1,27922.45,0 +6470,15775042,Ku,615,France,Female,23,4,0,2,1,0,196476.19,0 +6471,15616630,Tobenna,583,Germany,Female,41,5,77647.6,1,1,0,190429.52,0 +6472,15800233,Okwuadigbo,850,France,Female,40,5,0,2,1,0,35034.15,0 +6473,15588419,Johnston,651,Germany,Female,34,10,148962.46,1,1,0,66389.43,1 +6474,15595557,Li,798,France,Male,22,8,0,2,1,0,107615.43,0 +6475,15626143,Talbot,695,France,Male,37,2,0,2,1,1,99692.65,0 +6476,15566030,Tu,497,Germany,Male,41,5,80542.81,1,0,0,88729.22,1 +6477,15701412,T'ien,739,France,Male,40,4,0,2,0,0,173321.65,0 +6478,15702464,Ross,549,France,Female,34,4,0,2,0,0,139463.57,0 +6479,15573348,Maclean,850,France,Male,35,9,102050.47,1,1,1,3769.71,0 +6480,15704160,Wan,648,Spain,Male,49,5,0,1,1,0,149946.43,1 +6481,15693704,Tsou,679,France,Female,24,6,114948.76,2,0,1,135768.25,0 +6482,15664752,Jack,606,Germany,Male,39,8,136000.45,2,1,0,31708.53,0 +6483,15628292,Lucchesi,850,France,Male,32,4,156001.68,2,1,1,151677.31,0 +6484,15621195,Ch'eng,619,Germany,Male,41,3,147974.16,2,1,0,170518.83,0 +6485,15668629,Saunders,719,Spain,Male,44,2,0,2,1,0,196582.19,0 +6486,15635197,Glover,640,Germany,Male,26,5,90402.77,1,1,1,3298.65,0 +6487,15592761,Tung,710,France,Male,40,5,0,2,0,0,162878.96,0 +6488,15574283,Padovano,580,France,Male,31,2,0,2,0,1,64014.24,0 +6489,15598097,Johnstone,550,France,Male,44,9,0,2,1,0,26257.01,0 +6490,15711352,Endrizzi,841,France,Female,31,3,162701.65,2,1,1,126794.56,0 +6491,15620751,Secombe,760,France,Male,34,2,0,2,1,0,164162.44,0 +6492,15656717,Elewechi,687,France,Female,30,6,0,2,0,0,179206.92,0 +6493,15643121,Chu,753,Germany,Female,35,5,82453.96,2,0,0,18254.75,0 +6494,15723671,Lucciano,661,France,Male,35,9,100107.99,1,1,0,83949.68,0 +6495,15752846,Pinto,699,France,Male,28,7,0,2,1,1,22684.78,0 +6496,15640852,McGregor,617,Germany,Female,39,5,83348.89,3,1,0,7953.62,1 +6497,15789313,Ugorji,595,Germany,Female,44,4,96553.52,2,1,0,143952.24,1 +6498,15793688,Bancks,669,France,Male,50,9,201009.64,1,1,0,158032.5,1 +6499,15770405,Warlow-Davies,613,France,Female,27,5,125167.74,1,1,0,199104.52,0 +6500,15702561,Dale,782,France,Male,32,9,0,1,1,1,87566.97,0 +6501,15625964,Buckley,582,France,Female,43,5,153313.67,1,0,0,170563.73,0 +6502,15761364,Nkemjika,679,France,Male,30,9,0,2,1,0,157871.55,0 +6503,15590286,Fairley,611,France,Female,40,2,125879.29,1,1,0,93203.43,0 +6504,15587978,Boothby,455,Germany,Female,37,6,170057.62,1,0,1,54398.56,0 +6505,15773242,Chukwuhaenye,621,France,Male,32,1,0,2,1,1,168779.47,0 +6506,15761053,Lock,596,Germany,Male,48,2,131326.47,1,0,0,1140.02,1 +6507,15702095,Clarke,585,Spain,Female,56,1,128472.8,1,1,0,186476.91,1 +6508,15764253,Ramsey,742,France,Male,32,6,160485.16,1,1,0,29023.03,0 +6509,15700801,Eipper,850,Germany,Male,42,6,84445.68,3,0,1,60021.34,1 +6510,15730590,Ko,738,Germany,Female,40,1,115409.18,2,0,0,180456.8,0 +6511,15643916,Munro,619,Spain,Male,46,8,62400.48,1,1,1,132498.39,1 +6512,15720636,McGregor,628,France,Female,50,4,143054.56,1,0,1,109608.81,1 +6513,15795429,Henderson,487,France,Male,24,7,133628.09,2,1,1,98570.01,0 +6514,15609254,Fernandez,513,Spain,Female,41,9,107135.04,2,1,1,160546.58,0 +6515,15625141,Porter,563,Spain,Male,26,7,0,2,0,0,6139.74,0 +6516,15810898,Pan,803,France,Female,65,2,151659.52,2,0,1,6930.17,0 +6517,15775797,Esposito,607,Spain,Female,32,7,0,3,0,1,10674.62,0 +6518,15795246,Kaeppel,628,Germany,Female,51,9,155903.82,2,1,1,71159.84,0 +6519,15795275,Lamb,521,Spain,Female,49,4,82940.25,2,0,0,62413.01,1 +6520,15571869,Lei,669,Germany,Female,50,4,112650.89,1,0,0,166386.22,1 +6521,15694143,Conti,686,France,Female,41,10,0,1,1,0,133086.45,0 +6522,15748231,Hargreaves,700,Germany,Male,35,4,95853.39,2,1,0,192933.37,0 +6523,15632185,Yermolayev,663,France,Female,42,1,82228.67,2,1,0,71359.78,0 +6524,15806249,Kerr,671,Spain,Female,31,4,0,2,0,1,79270.02,0 +6525,15743293,Waters,651,Germany,Female,35,1,163700.78,3,1,1,29583.48,1 +6526,15598157,Onyeorulu,728,France,Male,34,4,106328.08,1,1,0,88680.65,0 +6527,15700946,Kolesnikova,574,France,Female,34,7,152992.91,1,1,1,134691.2,0 +6528,15722692,Kazakova,464,France,Male,38,3,116439.65,1,1,0,75574.48,0 +6529,15696506,MacDonald,604,Spain,Male,27,9,101352.78,1,0,0,30252.3,0 +6530,15728823,Sharwood,836,Spain,Female,37,10,0,2,1,0,111324.41,0 +6531,15808851,Bufkin,511,Germany,Female,75,9,105609.17,1,0,1,105425.18,0 +6532,15675231,Nwankwo,518,France,Female,45,8,0,2,1,1,36193.07,0 +6533,15732299,Boniwell,756,France,Male,67,4,0,3,1,1,93081.87,0 +6534,15706269,Willis,489,France,Female,47,8,103894.38,2,1,1,107625.46,0 +6535,15590078,Burns,622,Spain,Male,27,9,139834.93,1,1,1,152733.89,0 +6536,15776985,Kung,652,France,Female,36,6,112518.71,2,0,1,110421.31,0 +6537,15756743,Howells,625,France,Female,37,7,115895.42,1,1,0,48486.25,0 +6538,15782364,Bevan,521,Spain,Female,39,3,146408.68,1,0,0,72993.67,0 +6539,15604093,Neitenstein,546,France,Male,34,4,165363.31,2,1,1,25744.13,1 +6540,15749328,Johnson,697,France,Female,45,1,0,2,1,0,46807.62,1 +6541,15656322,Sandover,571,Germany,Male,33,3,71843.15,1,1,0,26772.04,0 +6542,15685564,Nnamutaezinwa,748,Spain,Male,35,5,105492.53,1,1,1,150057.2,0 +6543,15785831,Sinclair,591,France,Male,35,7,183027.25,1,1,1,56028.79,0 +6544,15796218,Wei,814,Germany,Male,29,1,131968.57,2,1,1,147693.92,0 +6545,15716218,Higgins,709,France,Female,45,3,104118.5,1,0,1,174032,0 +6546,15572735,Chang,433,Spain,Male,27,2,0,2,1,1,153698.65,0 +6547,15633840,Henderson,781,France,Male,20,0,125023.1,2,1,1,108301.45,0 +6548,15608760,Cox,656,France,Female,30,4,74323.2,1,1,1,22929.08,0 +6549,15627848,Tsui,683,France,Male,38,7,109346.13,2,1,0,102665.92,0 +6550,15792029,Lee,620,France,Male,32,6,0,2,1,0,56139.09,0 +6551,15617331,Sergeyeva,637,Germany,Female,39,3,109698.41,1,1,1,88391.29,1 +6552,15651740,Napolitani,525,Spain,Female,30,5,0,2,0,1,149195.44,0 +6553,15636407,Beatham,793,Germany,Female,34,5,127758.09,1,1,0,143357.03,0 +6554,15607526,Lu,638,Germany,Male,50,1,102645.48,1,1,0,168359.98,1 +6555,15632576,Yashina,520,France,Male,31,4,93249.4,1,1,0,77335.75,0 +6556,15581505,Bales,641,France,Male,35,5,0,2,1,0,93148.93,0 +6557,15612207,Hill,840,Germany,Female,51,1,87779.83,1,0,1,36687.11,1 +6558,15707242,Ibeamaka,504,Spain,Male,40,5,0,2,0,0,146703.36,0 +6559,15721937,Romilly,686,France,Male,38,0,138131.34,1,0,1,115927.85,0 +6560,15773852,Hayes,533,Germany,Male,38,4,70362.52,2,1,1,104189.46,0 +6561,15719778,Chiu,577,France,Female,32,1,0,2,1,0,9902.39,0 +6562,15650538,Sun,445,Germany,Female,48,7,168286.58,1,1,0,16645.77,1 +6563,15797475,Brennan,720,France,Male,44,3,86102.27,1,1,0,180134.88,1 +6564,15780359,Storey,643,Germany,Male,25,4,115142.9,1,1,1,148098.95,0 +6565,15737104,Lawson,652,Germany,Female,47,0,126597.89,2,1,1,38798.79,1 +6566,15789936,T'ao,663,France,Female,33,2,0,2,1,0,153295,0 +6567,15709523,Yao,525,Germany,Female,30,0,157989.21,2,1,1,100687.67,0 +6568,15593425,Bracewell,662,Spain,Female,54,1,187997.15,1,0,0,111442.71,1 +6569,15776725,Kerr,724,Germany,Male,54,8,172192.49,1,1,1,136902.01,0 +6570,15604706,Blake,581,Germany,Male,38,1,133105.47,1,1,0,105732.9,1 +6571,15790958,Sanders,685,Spain,Male,38,4,0,2,1,1,35884.91,0 +6572,15747534,Torkelson,595,France,Male,46,10,0,1,1,0,73489.15,1 +6573,15574237,Hsueh,588,France,Female,21,8,0,2,1,1,110114.19,0 +6574,15690332,Wang,647,Germany,Male,35,3,192407.97,1,1,1,40145.28,0 +6575,15661290,Hightower,785,Germany,Female,38,9,107199.75,1,0,0,146398.51,0 +6576,15651883,Genovesi,794,Germany,Female,55,6,115796.7,1,1,0,160526.36,1 +6577,15808905,Levan,823,France,Male,37,5,164858.18,1,1,1,173516.71,0 +6578,15715532,Lai,687,Germany,Male,38,4,117633.28,1,0,1,88396.6,0 +6579,15786078,Loginov,850,France,Female,28,9,0,2,1,0,185821.41,0 +6580,15652401,Lafleur,496,France,Female,36,7,0,2,0,0,108098.28,0 +6581,15673074,Obidimkpa,527,Germany,Female,30,6,126663.51,1,1,1,162267.91,0 +6582,15598744,Ch'ang,576,Germany,Female,71,6,140273.47,1,1,1,193135.25,1 +6583,15785975,Mason,525,Spain,Female,60,7,0,2,0,1,168034.9,0 +6584,15613180,Miranda,727,Germany,Male,21,8,153344.72,1,1,1,163295.87,0 +6585,15584229,Simon,671,Germany,Female,23,9,123943.18,1,1,1,159553.27,0 +6586,15773804,Golubeva,625,France,Male,39,5,0,1,1,0,99800.87,0 +6587,15699515,Manfrin,643,Germany,Male,33,7,98630.31,2,1,1,40250.82,0 +6588,15705313,Stange,707,France,Female,33,2,58036.33,1,1,1,83335.78,0 +6589,15693817,Ferrari,539,Spain,Male,28,5,0,2,1,0,48382.4,0 +6590,15673790,Taylor,498,Germany,Male,45,7,109200.74,2,0,1,165990.44,0 +6591,15674868,Wei,696,Spain,Female,30,0,0,2,1,1,9002.8,0 +6592,15692110,Ch'eng,758,France,Female,33,7,0,1,1,0,188156.34,0 +6593,15645904,Parsons,685,France,Female,33,6,0,2,0,1,186785.01,0 +6594,15581332,Pan,655,Germany,Female,30,1,83173.98,2,1,1,184259.6,0 +6595,15808544,Cameron,747,France,Female,40,3,0,1,0,0,57817.84,1 +6596,15734948,Igwebuike,601,Spain,Male,24,7,0,2,0,0,144660.42,0 +6597,15654531,Tuan,477,France,Male,22,5,82559.42,2,0,0,163112.9,1 +6598,15637774,Fraser,558,France,Male,32,5,73494.21,1,0,0,136301.1,0 +6599,15677141,Turnbull,586,Spain,Male,29,2,132450.24,1,1,1,36176.63,0 +6600,15739578,Chiazagomekpere,850,France,Male,49,6,128663.9,1,1,0,65769.3,1 +6601,15697360,Yudina,505,France,Female,36,2,79951.9,1,0,1,174123.16,1 +6602,15655213,Udinese,591,Germany,Female,51,8,132508.3,1,1,1,161304.68,1 +6603,15580872,Chinweike,761,Germany,Female,38,1,120530.13,2,1,0,109394.62,0 +6604,15683213,Bergamaschi,554,France,Female,35,10,74988.59,2,0,1,190155.13,0 +6605,15801188,Milliner,774,France,Female,47,6,94722.88,1,0,1,61450.96,0 +6606,15645029,Knowles,771,Spain,Female,33,5,0,2,1,0,8673.43,0 +6607,15633181,Swinton,792,France,Male,31,6,71269.89,2,0,1,125912.77,0 +6608,15598259,Gregory,673,Germany,Female,41,9,98612.1,1,1,0,151349.35,0 +6609,15576000,Chibueze,765,France,Male,40,6,138033.55,1,1,1,67972.45,0 +6610,15766047,Sukhorukova,748,France,Female,41,2,91621.69,1,1,1,71139.31,0 +6611,15596339,French,422,France,Male,54,3,140014.42,1,0,1,86350.97,0 +6612,15715199,Estrada,568,Spain,Male,27,5,126815.97,2,0,1,118648.12,0 +6613,15615938,Fleming,502,France,Female,64,3,139663.37,1,0,1,100995.11,0 +6614,15679991,Kennedy,524,France,Female,28,7,0,2,0,1,147100.72,0 +6615,15626135,Combes,689,France,Male,34,1,165312.27,1,1,0,155495.63,0 +6616,15792934,Carruthers,661,France,Male,26,8,0,2,0,0,196875.87,0 +6617,15744046,Andrejew,606,Spain,Male,33,8,0,2,1,1,63176.77,0 +6618,15700826,Ko,678,Germany,Female,54,1,123699.28,2,0,1,105221.76,0 +6619,15756301,Daniels,636,Germany,Female,29,3,97325.15,1,0,1,131924.38,0 +6620,15586517,Toscano,647,France,Male,32,5,97041.16,1,1,1,23132.73,0 +6621,15751297,Wilson,732,France,Male,36,5,0,2,1,0,161428.25,0 +6622,15710365,Thomson,646,France,Male,50,0,104129.24,2,1,0,181794.86,1 +6623,15679307,Kazantseva,559,France,Female,43,1,0,1,0,1,86634.3,0 +6624,15610753,Cremonesi,581,France,Male,28,3,104367.5,1,1,1,29937.75,0 +6625,15811036,Ferri,565,France,Male,46,7,135369.71,1,0,1,140130.22,0 +6626,15610912,Ferri,657,Spain,Female,41,6,112119.48,1,1,0,17536.82,0 +6627,15619932,Lombardi,847,France,Male,66,7,123760.68,1,0,1,53157.16,0 +6628,15746199,Eluemuno,558,France,Female,41,6,0,1,1,1,143585.29,1 +6629,15584967,Chiganu,596,Spain,Male,57,6,0,2,1,1,72402,0 +6630,15734365,Hsueh,579,France,Male,39,5,0,2,0,1,39891.84,0 +6631,15726960,O'Brien,741,France,Female,36,3,0,2,1,1,89804.83,0 +6632,15665177,Booth,613,France,Male,44,3,0,2,0,1,136491.72,0 +6633,15779915,O'Loghlin,694,Spain,Male,31,5,0,1,1,0,35593.18,0 +6634,15729110,Lavrov,729,Spain,Female,42,7,0,2,1,0,58268.2,1 +6635,15575399,Somadina,480,France,Female,42,1,152160.21,2,1,0,101778.9,0 +6636,15678374,Colombo,666,France,Female,59,5,0,2,1,1,185123.09,0 +6637,15792679,Troupe,575,France,Male,24,2,0,2,1,1,119927.81,0 +6638,15668767,Kenenna,850,France,Male,36,3,0,2,1,0,195033.07,0 +6639,15761886,Franklin,740,France,Male,36,4,172381.8,1,1,1,86480.29,0 +6640,15583076,Deleon,588,Germany,Male,41,6,106116.56,2,1,0,198766.61,0 +6641,15815615,Kung,681,France,Male,36,5,141952.07,1,1,1,185144.08,0 +6642,15591942,Zito,611,Spain,Female,33,7,0,2,1,1,3729.89,0 +6643,15724924,Giordano,589,France,Female,37,6,138497.84,1,0,1,18988.58,0 +6644,15762123,Davide,717,Spain,Female,34,1,0,2,1,0,119313.74,0 +6645,15567893,Lei,556,Germany,Male,33,3,124213.36,2,1,0,62627.55,0 +6646,15648989,Moss,850,France,Male,37,4,126872.6,1,1,0,197266.58,0 +6647,15662021,Lucciano,685,Spain,Female,42,2,0,2,0,0,199992.48,0 +6648,15691627,Tai,713,France,Female,37,8,0,1,1,1,16403.41,0 +6649,15731751,Osinachi,437,France,Female,26,1,120923.52,1,0,1,78854.57,0 +6650,15635277,Coates,605,Spain,Male,47,7,142643.54,1,1,0,189310.27,0 +6651,15655252,Larionova,758,Germany,Male,41,10,79857.64,1,1,1,78088.17,0 +6652,15803941,Seleznev,600,France,Male,46,10,95502.21,1,0,0,19842.18,0 +6653,15714380,Butcher,827,France,Male,38,5,0,2,0,0,103305.01,0 +6654,15666559,Gould,608,Germany,Male,23,8,197715.93,2,1,1,116124.28,0 +6655,15799998,Cunningham,608,France,Female,30,8,85859.76,1,0,0,142730.27,0 +6656,15703763,Sanderson,554,France,Male,44,7,85304.27,1,1,1,58076.52,0 +6657,15795640,Mai,683,Germany,Female,35,1,132371.3,2,0,0,186123.57,0 +6658,15780056,Reid,660,Spain,Male,33,4,0,1,1,0,29664.45,0 +6659,15777873,Downer,628,France,Female,31,5,0,1,0,0,147963.07,1 +6660,15584749,Humphries,668,Germany,Male,39,4,79896,1,1,0,38466.39,0 +6661,15765258,Bochsa,776,France,Female,29,5,0,2,1,1,143301.49,0 +6662,15623346,Czajkowski,820,France,Male,36,4,0,2,1,0,31422.69,0 +6663,15614054,Pankhurst,665,France,Male,36,1,0,2,0,1,121505.61,0 +6664,15766185,She,850,Germany,Male,31,4,146587.3,1,1,1,89874.82,0 +6665,15667632,Birdseye,703,France,Female,42,7,0,2,0,1,72500.68,0 +6666,15599024,Hope,506,Spain,Male,32,8,0,2,0,1,182692.8,0 +6667,15798709,Gill,588,Spain,Male,32,3,109109.33,1,0,1,4993.94,0 +6668,15741921,Moon,622,Spain,Female,26,8,0,2,1,1,124964.82,0 +6669,15793671,Watt,606,France,Male,34,5,0,1,1,0,161971.42,0 +6670,15797900,Chinomso,517,France,Male,56,9,142147.32,1,0,0,39488.04,1 +6671,15667932,Bellucci,758,Spain,Female,43,10,0,2,1,1,55313.44,0 +6672,15795933,Barese,677,France,Female,49,3,0,2,1,1,187811.71,0 +6673,15660403,Fleming,827,Spain,Female,35,0,0,2,0,1,184514.01,0 +6674,15736299,Bell,729,France,Female,36,8,109106.8,1,0,0,121311.12,0 +6675,15759034,Li Fonti,654,France,Male,36,2,112262.84,1,1,0,12873.39,0 +6676,15724663,Christmas,654,Spain,Female,36,5,0,2,0,0,157238.05,0 +6677,15594556,Chuter,619,Spain,Male,52,8,0,2,1,1,123242.11,0 +6678,15737169,Johnson,642,Spain,Male,26,8,144238.7,1,1,1,184399.76,0 +6679,15632472,Scott,472,Spain,Female,32,1,159397.75,1,0,1,57323.18,0 +6680,15722813,Byrne,470,Spain,Male,30,4,125385.01,1,1,0,68293.93,0 +6681,15588450,Chukwudi,633,France,Female,60,8,69365.25,1,1,1,10288.24,0 +6682,15736717,Ma,602,France,Male,31,7,155271.83,1,1,1,179446.31,0 +6683,15680683,Simmons,640,Spain,Male,29,5,197200.04,2,1,0,141453.62,0 +6684,15710316,Fang,454,Spain,Female,48,5,144837.79,1,1,1,93151.77,0 +6685,15746333,Blake,562,France,Female,57,3,0,3,1,0,6554.97,1 +6686,15606861,Tien,636,France,Male,34,8,0,2,1,0,38570.13,0 +6687,15641285,Yusupova,621,Spain,Male,50,3,163085.79,1,0,1,131048.36,0 +6688,15662908,Davidson,795,Germany,Male,38,7,125903.22,2,1,1,127068.92,0 +6689,15814267,Zhdanova,550,France,Male,22,6,154377.3,1,1,1,51721.52,0 +6690,15614923,Nielson,630,Spain,Male,41,7,107511.52,1,0,1,46156.87,0 +6691,15579223,Niu,573,Germany,Male,30,8,127406.5,1,1,0,192950.6,0 +6692,15651389,Kay,561,Spain,Male,24,8,143656.55,1,0,1,180932.46,0 +6693,15677087,Green,662,France,Female,39,5,138106.75,1,0,0,19596.73,0 +6694,15665784,She,637,France,Male,27,9,128940.24,1,1,0,46786.92,0 +6695,15576706,Ajuluchukwu,651,Germany,Male,37,9,114453.58,1,0,1,175820.91,0 +6696,15615473,Sabbatini,646,France,Female,33,2,0,2,0,0,198208,0 +6697,15587299,Board,567,France,Female,48,3,0,1,1,0,55362.45,0 +6698,15655389,Leckie,638,France,Male,41,1,131762.94,1,1,1,47675.29,0 +6699,15784491,Ho,725,France,Female,31,6,0,1,0,0,61326.43,0 +6700,15809999,Gordon,709,France,Female,41,3,150300.65,2,1,0,71672.86,0 +6701,15681115,Iroawuchi,787,Spain,Male,39,10,108935.39,1,1,1,101168.3,0 +6702,15629390,Liao,653,France,Male,37,7,135847.47,1,1,0,144880.81,0 +6703,15792668,Hamilton,661,Germany,Male,37,7,109908.06,2,1,0,115037.67,1 +6704,15583863,Chimaobim,681,Germany,Male,49,8,142946.18,1,0,0,187280.51,1 +6705,15681878,Fan,436,Germany,Male,45,3,104339.11,2,1,1,183540.22,1 +6706,15782875,Cayley,663,France,Male,33,5,157274.36,2,1,1,28531.81,0 +6707,15732235,Kuykendall,662,France,Male,64,0,98848.19,1,0,1,42730.12,0 +6708,15735909,McDonald,607,Germany,Female,39,8,105103.33,1,1,0,104721.5,1 +6709,15653448,Duncan,754,France,Male,34,7,0,2,1,1,65219.85,0 +6710,15587647,Browne,850,Germany,Female,66,0,127120.62,1,0,1,118929.64,1 +6711,15701037,Barton,578,France,Male,39,2,0,2,1,0,70563.9,0 +6712,15727499,Boyle,666,Germany,Female,36,3,129118.5,2,0,0,139435.12,0 +6713,15724838,Moretti,599,France,Female,43,4,0,1,1,0,170347.1,0 +6714,15666711,Ukaegbulam,586,France,Female,46,0,0,3,0,1,131553.82,1 +6715,15588933,Nwankwo,825,France,Female,36,3,146053.66,1,1,1,138344.7,0 +6716,15763111,Niu,808,Spain,Female,67,10,124577.15,1,0,1,169894.4,0 +6717,15805676,Hsu,515,Spain,Male,29,4,151012.55,2,1,0,9770.97,0 +6718,15586674,Shaw,663,Spain,Female,58,5,216109.88,1,0,1,74176.71,1 +6719,15744553,Ho,444,France,Male,34,2,144318.97,1,1,0,112668.06,0 +6720,15776629,Christie,650,France,Female,39,4,0,2,0,0,186275.7,0 +6721,15647207,Onwuemelie,609,France,Male,26,7,0,2,1,0,98463.99,0 +6722,15715638,Ch'ang,824,Germany,Male,77,3,27517.15,2,0,1,2746.41,0 +6723,15750602,Clendinnen,662,France,Male,29,5,147092.65,1,1,0,10928.3,0 +6724,15766810,Onyemauchechi,699,Germany,Female,51,2,92246.14,2,0,1,91346.03,0 +6725,15756625,Crawford,752,France,Female,41,8,0,2,1,0,139844.04,1 +6726,15639552,Mellor,603,Germany,Female,40,8,148897.02,1,0,0,105052.9,0 +6727,15633213,Rizzo,628,Spain,Male,50,8,0,1,0,0,144366.83,1 +6728,15610416,Christie,745,France,Female,36,9,0,1,1,0,19605.18,1 +6729,15715208,Watkins,804,Germany,Female,33,10,138335.96,1,1,1,80483.76,0 +6730,15619608,Ojiofor,454,Germany,Female,50,10,92895.56,1,1,0,154344,1 +6731,15628697,Tung,631,Spain,Male,46,9,160736.63,1,0,1,93503.02,0 +6732,15643826,McKay,503,France,Male,32,4,0,2,1,1,153036.97,0 +6733,15718588,Meng,548,France,Female,37,9,0,2,0,0,98029.58,0 +6734,15709741,Hussain,668,France,Male,28,4,107141.27,1,1,0,193018.71,0 +6735,15723318,Mactier,619,France,Female,55,0,0,3,0,0,60810.64,1 +6736,15717328,Hsueh,842,France,Female,37,4,132446.08,2,1,0,87071.18,1 +6737,15771299,Nnachetam,707,France,Female,57,1,92053,1,1,1,164064.44,1 +6738,15706223,Barnes,715,Spain,Male,38,2,96798.79,2,1,1,4554.67,0 +6739,15612358,Christie,573,Germany,Male,35,9,134498.54,2,1,1,119924.8,0 +6740,15769191,Lipton,509,France,Male,55,8,132387.91,2,1,1,170360.11,0 +6741,15618816,Yu,670,Germany,Female,40,2,147171.2,1,0,1,69850.04,0 +6742,15730810,Storey,613,Spain,Male,44,9,100524.69,1,1,1,47298.95,0 +6743,15783463,Read,678,France,Female,26,1,0,2,1,0,45443.68,0 +6744,15616213,Levy,555,Germany,Female,51,9,138214.5,1,1,0,198715.27,1 +6745,15611287,Chiu,777,France,Female,30,4,0,2,0,1,115611.97,0 +6746,15786454,Moore,552,Spain,Male,55,3,0,1,1,1,40333.94,0 +6747,15768682,Amies,640,Spain,Male,39,3,0,1,1,1,105997.25,0 +6748,15766172,Tsao,541,France,Male,34,3,128743.55,1,1,0,134851.12,0 +6749,15637646,Rowley,756,France,Male,31,10,122647.32,1,0,0,61666.87,0 +6750,15653404,Aliyev,684,Spain,Female,24,9,79263.9,1,0,1,196574.48,0 +6751,15690546,Riley,618,France,Female,42,2,0,4,0,0,111097.39,1 +6752,15735636,Toscano,604,France,Female,53,2,121389.78,1,1,1,48201.64,1 +6753,15605424,Oluchukwu,624,Spain,Male,38,7,123906.55,1,1,0,135096.78,0 +6754,15568449,Fu,661,Spain,Male,38,7,143006.7,1,1,1,15650.89,0 +6755,15688085,Warner,627,Spain,Female,28,3,157597.61,1,0,1,34097.22,0 +6756,15683483,Fleming,812,Spain,Male,38,3,127117.8,2,1,1,174822.74,0 +6757,15659567,Ch'iu,473,France,Female,39,9,117103.26,2,1,1,85937.52,1 +6758,15766667,Langler,717,Spain,Male,36,2,102989.83,2,0,1,49185.57,0 +6759,15624975,Angelo,693,Spain,Male,28,1,145118.83,1,0,1,77742.38,0 +6760,15660878,T'ien,705,France,Male,92,1,126076.24,2,1,1,34436.83,0 +6761,15586557,Milani,661,France,Male,41,5,0,1,0,1,88279.6,0 +6762,15746183,Pye,573,France,Female,27,4,0,2,1,1,157549.6,0 +6763,15631457,Asher,639,France,Male,37,5,98186.7,1,0,1,173386.95,0 +6764,15754053,Chung,718,France,Female,67,7,0,3,1,1,82782.08,0 +6765,15645839,Yudin,570,France,Male,37,6,0,1,1,1,187758.5,0 +6766,15689955,Arcuri,461,France,Female,40,7,0,2,1,0,176547.8,0 +6767,15593510,Capon,638,Germany,Female,33,5,129335.65,1,1,1,56585.2,1 +6768,15654964,Piccio,608,Spain,Male,48,7,75801.74,1,1,0,125762.95,0 +6769,15594039,Lung,599,Spain,Male,42,6,0,2,1,0,113868.4,0 +6770,15625929,Trevisan,762,France,Female,44,7,159316.64,1,0,0,24780.13,0 +6771,15815295,John,662,France,Female,38,2,96479.81,1,1,0,120259.41,0 +6772,15621818,Anayolisa,747,Germany,Male,29,7,117726.33,1,1,1,175398.34,0 +6773,15652700,Ritchie,539,France,Male,39,6,0,2,1,1,86767.48,0 +6774,15636860,Ch'eng,625,France,Male,43,4,122351.29,1,1,0,71216.6,0 +6775,15569432,Macleod,656,France,Female,48,9,0,2,1,1,85240.61,1 +6776,15751455,Boyle,469,France,Female,48,5,0,1,1,0,160529.71,1 +6777,15800583,Chukwuemeka,621,Spain,Female,43,8,0,1,0,0,102806.6,0 +6778,15770214,Bryant,754,France,Female,27,7,0,2,1,0,144134.64,0 +6779,15613463,Hackett,679,Germany,Female,50,6,132598.38,2,1,1,184017.98,0 +6780,15587066,Kovaleva,535,France,Male,38,2,119272.29,1,0,0,195896.59,1 +6781,15693752,Reed,487,France,Male,37,2,0,2,1,1,126722.57,0 +6782,15714874,Major,850,France,Female,42,3,0,2,1,1,176883.42,0 +6783,15657809,Lo,585,France,Male,55,10,106415.57,3,1,1,122960.98,1 +6784,15651955,Hanson,603,France,Male,31,4,0,2,0,1,9607.1,0 +6785,15570912,Ogbonnaya,728,Germany,Female,32,9,127772.1,2,1,1,152643.48,0 +6786,15640266,Windsor,621,Spain,Male,41,5,104631.67,1,1,1,95551.22,0 +6787,15652069,Calabrese,833,France,Male,30,1,0,2,1,0,141860.62,0 +6788,15596074,Keating,502,France,Male,37,10,0,1,1,1,76642.68,0 +6789,15800268,Costa,825,Germany,Male,37,6,118050.79,1,0,1,52301.15,0 +6790,15809847,Tan,668,France,Male,46,0,0,2,0,0,29388.02,0 +6791,15599074,Ma,487,Spain,Female,40,6,136093.74,1,0,1,193408.43,0 +6792,15599591,Martin,600,Germany,Female,39,7,88477.36,2,1,0,58632.37,0 +6793,15776096,Halpern,606,Spain,Male,34,3,161572.24,1,0,1,191076.22,0 +6794,15611669,Nyhan,623,Germany,Male,50,7,126608.37,1,0,1,645.61,1 +6795,15694098,Jackson,575,France,Female,54,9,68332.96,1,1,1,144390.75,0 +6796,15713347,Reynolds,577,Spain,Male,48,6,179852.26,1,1,0,193580.32,0 +6797,15713094,Tai,651,France,Female,25,8,0,2,1,1,126761.2,0 +6798,15811978,Trevisani,693,Germany,Male,46,2,104763.41,1,1,1,62368.33,0 +6799,15799925,Uwakwe,800,France,Male,60,6,88541.57,2,1,1,131718.12,0 +6800,15692575,Kerr,760,France,Male,38,6,162888.73,1,1,0,91098.76,1 +6801,15743149,Findlay,711,France,Female,35,8,0,1,1,1,67508.01,0 +6802,15776947,Ugorji,637,Spain,Male,43,8,0,1,1,0,12156.93,1 +6803,15700656,Balashova,662,France,Male,32,9,0,2,0,0,65089.38,0 +6804,15594515,Cheng,568,France,Female,44,7,0,2,0,0,62370.67,1 +6805,15787884,Martin,692,France,Female,30,7,0,2,1,1,18826.34,0 +6806,15577988,Skinner,614,France,Female,35,1,0,2,1,1,3342.62,0 +6807,15795586,McDonald,478,France,Male,35,1,92474.05,1,1,0,178626.07,0 +6808,15677739,Dellucci,562,France,Male,36,6,0,2,1,0,32845.32,0 +6809,15720134,Reynolds,709,Germany,Male,30,9,115479.48,2,1,1,134732.99,0 +6810,15688868,Birdsall,684,France,Female,26,5,87098.91,1,0,0,106095.82,0 +6811,15642996,Tsai,546,Germany,Female,42,9,86351.85,2,1,0,57380.13,0 +6812,15771222,Oguejiofor,779,France,Female,42,5,0,2,0,0,25951.91,0 +6813,15605059,Mackie,576,Germany,Male,63,3,148843.56,1,1,0,69414.13,1 +6814,15568088,Jamieson,481,Germany,Male,44,3,163714.52,1,1,0,96123.72,0 +6815,15665943,Mai,445,France,Male,25,6,0,2,1,0,119425.94,0 +6816,15795571,Patterson,606,Spain,Male,36,0,94153.56,1,0,1,120138.27,0 +6817,15662243,Taylor,559,France,Male,50,5,162702.35,1,0,0,150548.5,1 +6818,15593128,Vinogradoff,608,France,Female,56,10,129255.2,2,1,0,142492.04,1 +6819,15589739,North,698,France,Male,41,3,90605.29,1,1,1,14357,0 +6820,15787602,Carter,568,Spain,Male,39,5,0,2,1,1,129569.92,0 +6821,15685019,Graham,528,France,Male,29,3,102787.42,1,1,0,55972.56,0 +6822,15704209,Noble,802,France,Female,39,7,120145.96,2,0,1,59497.01,1 +6823,15605264,Walker,669,Germany,Male,47,0,63723.78,2,1,1,181928.25,0 +6824,15708265,Chibugo,581,Spain,Female,24,10,159203.71,1,1,1,102517.83,1 +6825,15740264,Yobachi,640,France,Male,38,9,0,2,1,0,88827.67,0 +6826,15615477,Ignatyeva,529,Spain,Female,44,1,0,2,0,0,14161.3,0 +6827,15727361,Chiemela,547,France,Female,51,1,0,2,1,1,56908.41,0 +6828,15760216,Pokrovskaya,718,France,Female,49,10,0,1,1,0,184474.72,1 +6829,15806134,Storey,707,Germany,Male,34,9,162691.16,2,1,0,94912.78,0 +6830,15601351,Moroney,735,France,Male,43,9,127806.91,1,1,1,73069.59,0 +6831,15669262,Maslov,765,France,Male,43,9,157960.49,2,0,0,136602.8,0 +6832,15696989,Chukwueloka,469,Germany,Female,52,8,139493.25,3,0,0,150093.32,1 +6833,15688498,Chu,594,Germany,Female,21,2,87096.82,2,1,0,168186.11,0 +6834,15686964,Spence,675,France,Female,34,10,84944.58,1,0,0,146230.63,0 +6835,15625035,Mills,703,France,Male,50,8,160139.59,2,1,1,79314.1,0 +6836,15618391,Doyle,810,France,Male,33,6,0,2,1,1,77965.67,0 +6837,15591344,Donnelly,715,Spain,Male,42,6,0,2,1,1,128745.69,0 +6838,15605455,Tai,664,France,Male,40,9,0,2,1,0,194767.3,0 +6839,15680804,Abbott,850,France,Male,29,6,0,2,1,1,10672.54,0 +6840,15768282,Perez,724,Germany,Male,36,6,94615.11,2,1,1,10627.21,0 +6841,15685826,Hsiung,563,France,Male,30,7,90727.79,1,1,0,122268.75,0 +6842,15793491,Cherkasova,714,Germany,Male,26,3,119545.48,2,1,0,65482.94,0 +6843,15797787,Denisov,614,France,Male,36,1,118311.76,1,1,0,146134.68,0 +6844,15611171,Fowler,740,France,Male,33,1,129574.98,1,1,1,123300.38,0 +6845,15601627,Siciliano,587,France,Male,33,8,148163.57,1,0,0,122925.4,0 +6846,15734085,Crocker,465,Germany,Male,24,5,117154.9,1,1,1,127744.02,0 +6847,15809309,Longo,689,Spain,Female,40,5,154251.67,1,0,1,118319.5,0 +6848,15809462,Polyakova,656,France,Male,30,3,0,2,0,1,17104,0 +6849,15634628,Brown,579,France,Female,33,1,65667.79,2,0,0,164608.98,0 +6850,15775678,Uspensky,716,France,Female,44,1,0,1,1,1,152108.47,0 +6851,15579526,O'Meara,551,France,Male,42,1,50194.59,1,1,1,23399.58,0 +6852,15779103,Cantamessa,527,Germany,Female,39,9,96748.89,2,1,0,94711.43,0 +6853,15738715,Alexander,600,France,Female,37,4,0,3,1,0,7312.25,1 +6854,15593943,Chinagorom,685,France,Female,43,1,132667.17,1,1,1,41876.98,0 +6855,15754574,Tomlinson,738,Spain,Male,36,5,0,2,1,1,96881.32,0 +6856,15737814,Lo,622,France,Male,41,2,127087.06,1,1,0,102402.91,1 +6857,15670889,Nwachukwu,528,France,Male,34,1,125566.9,1,1,1,176763.27,0 +6858,15629299,Yang,546,Germany,Female,52,1,106074.89,1,1,1,23548.45,1 +6859,15771569,Bage,576,Germany,Male,46,4,137367.94,1,1,1,33450.11,0 +6860,15811927,Marcelo,733,France,Female,38,3,157658.36,1,0,0,19658.43,0 +6861,15785654,Ofodile,727,Germany,Male,45,6,114422.85,2,1,1,104678.78,1 +6862,15665524,Savage,605,Spain,Male,41,5,103154.66,1,0,0,143203.78,0 +6863,15736287,Piccio,586,France,Male,33,9,0,1,1,0,6975.02,0 +6864,15765732,Simmons,564,Spain,Female,24,6,149592.14,1,1,1,153771.8,0 +6865,15797381,DeRose,593,Germany,Female,48,3,133903.12,2,1,1,85902.39,1 +6866,15598536,Onuchukwu,736,Germany,Female,26,0,84587.9,1,0,1,188037.76,0 +6867,15664506,Goodwin,675,Spain,Male,32,8,197436.82,1,1,1,52710.7,0 +6868,15575619,Teakle,656,Spain,Female,32,1,104254.27,1,1,1,17034.37,0 +6869,15587394,Thomson,462,France,Male,39,4,140133.08,2,0,0,131304.45,0 +6870,15654457,Cross,685,Spain,Female,30,2,0,3,1,1,172576.43,1 +6871,15762793,Jones,850,Germany,Female,36,0,136980.23,2,1,1,99019.65,0 +6872,15658067,Walker,636,Germany,Female,48,3,120568.41,1,1,0,190160.04,1 +6873,15642816,De Salis,850,France,Female,27,7,43658.33,2,1,1,3025.49,0 +6874,15693088,Oliver,628,France,Female,37,9,0,2,1,1,34689.77,0 +6875,15793883,Lo Duca,798,France,Male,28,3,0,2,1,0,2305.27,0 +6876,15665283,Brookes,610,France,Female,57,7,72092.95,4,0,1,113228.82,1 +6877,15680421,Challis,591,France,Female,42,10,0,2,0,0,171099.22,0 +6878,15695148,Ibeabuchi,614,Spain,Female,37,9,0,2,1,1,62023.1,0 +6879,15636592,Iroawuchi,651,France,Male,35,0,181821.96,2,0,1,36923.67,1 +6880,15772618,Tyler,665,France,Male,25,7,90920.75,1,0,1,112256.57,0 +6881,15724453,Fan,570,France,Male,23,2,0,1,0,0,198830.98,0 +6882,15565878,Bates,631,Spain,Male,29,3,0,2,1,1,197963.46,0 +6883,15609160,Marsden,586,France,Male,32,1,0,2,0,0,31635.99,0 +6884,15678460,Dodgshun,691,France,Male,30,9,0,1,1,0,49594.02,0 +6885,15662571,Maclean,639,France,Male,35,8,0,2,1,0,170483.9,0 +6886,15606849,Blackall,698,France,Female,27,1,94920.71,1,1,1,40339.9,0 +6887,15670738,Mazzanti,733,Germany,Male,45,2,113939.36,2,1,0,3218.71,0 +6888,15662641,Amadi,850,France,Male,19,8,0,1,1,1,68569.89,0 +6889,15727539,Schoenheimer,618,France,Female,31,4,0,2,1,0,29176.04,0 +6890,15651020,Fiorentino,473,France,Female,25,6,110666.42,2,0,0,46758.42,0 +6891,15673877,Murray,490,France,Male,39,1,0,3,1,0,171060.01,1 +6892,15760865,Fan,754,Germany,Female,48,7,141819.02,1,1,0,93550.53,1 +6893,15705009,Cartwright,649,France,Female,56,8,156974.26,1,1,0,89405.26,1 +6894,15657540,Cremonesi,578,France,Male,50,5,151215.34,2,1,0,169804.4,0 +6895,15707441,White,690,Spain,Male,26,8,116318.23,1,1,1,83253.05,0 +6896,15694765,Sabbatini,610,Germany,Male,49,6,113882.33,1,1,0,195813.81,1 +6897,15649086,Patterson,596,France,Male,42,7,0,2,1,1,121568.37,0 +6898,15650488,Bromley,492,France,Female,48,6,127253.98,1,1,1,92144.09,1 +6899,15760924,Doherty,575,Spain,Male,41,2,100062.39,1,0,0,126307.25,0 +6900,15700263,Ifeatu,569,France,Male,66,2,0,1,1,0,130784.2,1 +6901,15806922,Bergamaschi,674,Spain,Female,41,4,126605.14,1,1,1,166694.93,0 +6902,15637522,Shubina,507,France,Female,31,0,106942.08,1,0,1,44001.11,0 +6903,15636548,Lung,457,Spain,Male,44,7,0,2,0,0,185992.36,0 +6904,15566891,Kinder,584,Germany,Female,41,3,88594.93,1,1,0,178997.89,0 +6905,15627185,Terry,744,Germany,Male,29,6,123737.04,2,1,0,141558.04,0 +6906,15754012,Shepherdson,687,France,Female,35,1,110752.15,2,1,1,47921.22,0 +6907,15627514,Short,688,Spain,Female,46,3,0,2,0,1,104902.68,0 +6908,15661433,Zetticci,519,France,Male,34,5,0,1,1,0,68479.6,0 +6909,15610653,Belov,733,Spain,Female,38,5,0,2,1,1,1271.51,0 +6910,15667002,Knight,666,Spain,Male,43,5,0,2,1,0,29346.1,0 +6911,15709199,Burson,511,Spain,Female,40,1,0,1,1,1,184118.73,0 +6912,15710087,Nicholls,705,Germany,Female,54,3,125889.3,3,1,0,96013.5,1 +6913,15679884,Hs?eh,544,France,Male,48,10,78314.63,3,1,1,103713.93,1 +6914,15784180,Ku,564,France,Female,36,7,206329.65,1,1,1,46632.87,1 +6915,15808849,T'ien,702,France,Male,40,7,145536.9,1,0,1,135334.24,0 +6916,15751549,H?,658,Germany,Male,31,2,77082.65,2,0,0,13482.28,0 +6917,15588235,Vasilieva,654,France,Female,24,8,145081.73,1,1,1,130075.07,0 +6918,15640418,Omeokachie,649,Germany,Female,41,4,115897.73,1,1,0,143544.48,0 +6919,15721116,Napolitano,597,Spain,Male,24,0,108058.07,2,1,1,187826.11,0 +6920,15599084,Hopwood,782,France,Male,33,7,191523.09,1,1,1,167058.75,0 +6921,15773394,Bergamaschi,644,France,Male,38,3,0,2,1,1,79928.41,0 +6922,15625713,Lindeman,679,Spain,Female,39,7,91187.9,1,0,1,6075.36,0 +6923,15766417,McKinley,678,France,Female,60,2,0,2,1,1,43821.56,0 +6924,15622578,Sergeyev,806,France,Male,34,5,113958.55,1,0,1,32125.98,0 +6925,15799924,Sanchez,668,Spain,Male,43,1,147167.25,1,0,0,141679.73,0 +6926,15618363,Muomelu,659,Germany,Male,29,9,82916.48,1,1,1,84133.48,0 +6927,15637138,Murray,660,France,Male,34,1,0,2,1,0,9692.58,0 +6928,15781665,Ibekwe,601,France,Female,37,5,0,1,0,0,20708.6,0 +6929,15804853,McVey,781,France,Female,48,0,57098.96,1,1,0,85644.06,1 +6930,15651627,White,628,Germany,Male,39,1,115341.19,1,1,1,107674.3,1 +6931,15680685,Patterson,751,France,Male,30,3,165257.2,1,0,0,134822.05,0 +6932,15808930,Mai,531,France,Female,37,1,0,1,1,0,4606.97,0 +6933,15570970,Han,647,France,Female,42,9,0,2,1,1,51362.82,0 +6934,15679961,Davidson,708,Spain,Male,46,7,68799.72,1,1,1,39704.14,0 +6935,15705458,Parkin,550,Spain,Male,39,2,116120.19,2,1,1,195638.13,0 +6936,15750396,McKissick,670,France,Male,33,1,0,2,1,1,86413.11,0 +6937,15679928,Horsfall,592,France,Female,31,2,84102.11,2,0,1,116385.24,0 +6938,15711181,Clapp,589,France,Female,50,4,0,2,0,1,182076.97,0 +6939,15698324,Azikiwe,725,France,Female,33,4,0,1,1,1,67879.8,0 +6940,15807433,Zubarev,570,France,Female,43,9,0,2,0,1,11417.26,0 +6941,15636590,Pisano,575,France,Male,46,1,0,2,1,1,65998.26,0 +6942,15628950,Coates,501,Germany,Male,25,6,104013.79,1,1,0,114774.35,0 +6943,15617206,Trentino,431,Germany,Male,42,8,120822.86,2,1,0,126153.24,0 +6944,15603741,MacDonnell,719,Spain,Male,40,4,128389.12,1,1,1,176091.31,0 +6945,15742607,Ermakov,850,Germany,Male,36,7,102800.72,1,1,1,87352.43,0 +6946,15747821,K?,554,Germany,Female,31,6,135470.9,1,1,0,107074.81,0 +6947,15612043,Hammonds,418,France,Male,36,7,90145.04,1,1,1,69157.93,0 +6948,15809558,Peppin,715,Spain,Male,31,7,0,1,1,1,149970.59,0 +6949,15803750,Ball,750,Spain,Female,33,3,161801.47,1,0,1,153288.97,1 +6950,15704681,Yeh,766,Germany,Male,37,2,99660.13,2,0,1,147700.78,0 +6951,15667392,L?,652,Spain,Female,38,6,123081.84,2,1,1,188657.97,0 +6952,15738889,Shih,658,France,Male,42,8,102870.93,1,0,1,103764.55,1 +6953,15598838,Greco,659,France,Female,37,1,151105.68,1,1,1,140934.57,0 +6954,15579109,Napolitano,574,Germany,Male,35,5,163856.76,1,1,1,15118.2,0 +6955,15799042,Zaytseva,611,France,Male,38,7,0,1,1,1,63202,0 +6956,15697042,Genovesi,738,Spain,Male,35,8,127290.61,1,1,0,16081.62,0 +6957,15696605,Angelo,571,France,Male,49,4,180614.04,1,0,0,523,0 +6958,15802274,Waters,686,France,Female,44,7,55053.62,1,1,0,181757.19,0 +6959,15596808,Maclean,679,Spain,Male,33,4,96110.22,1,1,0,1173.23,0 +6960,15705403,Seleznyova,617,Spain,Female,46,3,106521.49,1,0,1,86587.37,0 +6961,15732903,Fontenot,673,France,Male,39,7,82255.51,2,1,0,109545.56,0 +6962,15581968,Reid,745,France,Female,33,1,0,2,1,1,174431.01,0 +6963,15683892,Fraser,677,Germany,Female,26,3,102395.79,1,1,0,119368.99,0 +6964,15595447,Tuan,613,Spain,Male,39,8,118201.41,1,1,0,23315.59,0 +6965,15569249,Howarth,576,France,Female,55,6,44582.07,3,0,1,67539.85,1 +6966,15656188,Davis,584,Spain,Female,30,5,0,2,1,1,185201.58,0 +6967,15689661,Gorbunov,663,France,Male,22,6,0,2,0,1,131827.15,0 +6968,15644934,Gentry,466,France,Male,26,9,105522.06,1,1,0,10842.46,0 +6969,15721793,Chiu,510,Germany,Female,50,7,123936.54,1,1,1,23768.01,0 +6970,15687413,Sunderland,619,Spain,Female,38,6,0,2,1,1,117616.29,0 +6971,15761286,Fan,696,Germany,Female,66,7,119499.42,2,1,1,174027.3,0 +6972,15658240,Parry,554,France,Female,44,9,135814.7,2,0,0,115091.38,0 +6973,15706232,Niu,595,France,Male,52,9,0,1,1,1,106340.66,1 +6974,15583394,Zuyev,659,Germany,Male,39,8,106259.63,2,1,1,198103.32,0 +6975,15715643,Ijendu,662,France,Male,44,8,0,2,1,1,175314.87,0 +6976,15644856,Bird,556,Spain,Male,38,2,115463.16,1,1,0,150679.65,0 +6977,15785488,Palmer,701,Spain,Female,39,9,0,2,1,1,110043.88,0 +6978,15711571,Y?,587,Spain,Male,42,5,120233.83,1,1,0,194890.33,0 +6979,15778604,Nicholson,571,France,Female,47,7,0,2,0,0,112366.98,0 +6980,15751180,Adams,539,France,Female,40,7,81132.21,1,1,0,167289.82,0 +6981,15748360,Cocci,644,Germany,Female,34,10,122196.99,2,1,1,182099.71,0 +6982,15770039,Kuo,572,Germany,Male,39,4,112290.22,1,1,0,49373.97,1 +6983,15685096,Trevisani,753,France,Female,50,4,0,2,1,1,861.4,0 +6984,15669501,Kuo,706,France,Male,35,5,0,2,1,1,81718.37,0 +6985,15622631,H?,588,France,Male,44,8,154409.74,1,1,0,49324.03,1 +6986,15586699,Thomson,825,France,Male,32,9,0,2,0,0,9751.03,0 +6987,15702377,Knorr,627,Spain,Male,48,1,132759.8,1,1,0,78899.22,0 +6988,15577170,Manfrin,532,France,Male,60,5,76705.87,2,0,1,13889.73,0 +6989,15769451,Hayes,764,France,Female,44,1,0,2,1,1,11467.38,0 +6990,15811877,Shao,700,France,Female,36,4,0,2,1,0,130789.15,0 +6991,15648725,Sinclair,660,France,Male,41,3,0,2,1,1,108665.89,0 +6992,15752801,Bradshaw,518,Germany,Male,29,9,125961.74,2,1,0,160303.08,1 +6993,15808175,Castiglione,557,France,Female,39,7,49572.73,1,1,0,115287.99,1 +6994,15681342,Hurst,639,France,Female,35,1,103015.12,2,1,1,139094.12,0 +6995,15589210,Adamson,557,France,Female,24,4,0,1,0,0,20515.72,0 +6996,15696826,James,633,France,Female,32,1,104001.38,1,0,1,36642.65,0 +6997,15614962,Pavlova,623,Spain,Female,50,2,87116.71,1,1,1,104382.11,0 +6998,15689061,Davey,611,France,Male,68,5,82547.11,2,1,1,146448.01,0 +6999,15640074,Barrett,666,Spain,Female,47,5,0,1,0,0,166650.9,1 +7000,15776156,Dolgorukova,521,France,Male,27,4,121325.84,1,1,1,164223.7,1 +7001,15739548,Johnson,775,France,Male,28,9,111167.7,1,1,0,149331.01,0 +7002,15662854,Manna,681,Germany,Male,48,5,139714.4,2,0,0,73066.72,0 +7003,15687688,Hou,564,Germany,Female,32,10,139875.2,2,1,0,15378.23,0 +7004,15715750,Okeke,646,Germany,Female,44,2,113063.83,1,0,0,53072.49,1 +7005,15571121,Kodilinyechukwu,670,France,Female,50,8,138340.06,1,0,1,3159.15,0 +7006,15726466,Esposito,751,France,Male,43,1,114974.24,1,1,0,125920.54,0 +7007,15660390,Boyle,544,France,Female,33,6,0,2,1,1,124113.04,0 +7008,15663942,Hsiung,639,France,Female,38,5,0,2,0,0,93716.38,0 +7009,15638610,Kennedy,635,Germany,Female,65,5,117325.54,1,1,0,155799.86,1 +7010,15644446,Norton,672,France,Female,28,6,0,1,0,1,8814.69,0 +7011,15585892,Zakharov,639,France,Female,35,8,0,1,0,0,164453.98,0 +7012,15609356,Chimaraoke,697,France,Female,25,1,0,2,0,0,87803.32,0 +7013,15803378,Small,850,Spain,Male,44,8,0,2,1,1,183617.32,0 +7014,15599440,McGregor,748,France,Female,34,8,0,2,1,0,53584.03,0 +7015,15692408,Brown,463,Spain,Female,35,2,0,2,1,1,1950.93,0 +7016,15683168,Frederickson,572,France,Female,30,6,0,1,0,1,175025.27,0 +7017,15790254,Wood,741,Spain,Male,50,1,78737.61,1,1,1,13018.96,0 +7018,15767729,Smith,646,Spain,Male,25,5,182876.88,2,1,1,42537.59,1 +7019,15768600,Harris,805,Germany,Male,50,9,130023.38,1,1,0,62989.82,1 +7020,15699839,Hall,637,France,Male,36,2,152606.82,1,1,1,71692.8,0 +7021,15786237,Pickworth,651,France,Male,28,7,0,2,1,0,823.96,0 +7022,15694530,Porter,672,France,Male,28,4,167268.98,1,1,1,169469.3,0 +7023,15796813,Storey,493,France,Male,54,3,167831.88,2,1,0,150159.95,1 +7024,15605791,Li,524,Germany,Male,29,9,144287.6,2,1,0,32063.3,0 +7025,15714087,McGill,624,Germany,Female,45,5,151855.33,1,1,0,68794.15,0 +7026,15711446,Sinclair,569,Spain,Female,51,3,0,3,1,0,75084.96,1 +7027,15588123,Horton,677,France,Female,27,2,0,2,0,1,114685.92,0 +7028,15748552,Sal,464,Germany,Male,37,4,155994.15,1,0,0,143665.44,0 +7029,15618410,Murray,718,Germany,Male,26,7,147527.03,1,0,0,51099.56,0 +7030,15672432,Giles,594,France,Female,53,4,0,1,1,0,5408.74,1 +7031,15610042,Brown,574,France,Male,33,8,100267.03,1,1,0,103006.27,0 +7032,15580914,Okechukwu,478,Spain,Male,48,0,83287.05,2,0,1,44147.95,1 +7033,15583680,White,615,Spain,Male,41,4,0,1,0,1,149278.96,0 +7034,15813718,Kirillova,651,Spain,Male,45,4,0,2,0,0,193009.21,0 +7035,15767264,Lawson,465,Germany,Male,53,1,117438.17,1,0,0,74898.8,1 +7036,15686461,Sarratt,558,France,Female,56,7,121235.05,2,1,1,116253.1,0 +7037,15678882,Hay,540,Germany,Male,37,3,129965.18,1,0,0,19374.08,0 +7038,15789611,Lin,568,Germany,Male,46,8,150836.92,1,0,0,64516.8,1 +7039,15668679,Ozerova,630,France,Male,31,0,0,2,1,1,34475.14,0 +7040,15631685,Lambert,523,Germany,Male,60,1,163894.35,1,0,1,57061.71,0 +7041,15655658,Bulgakov,678,France,Female,48,2,0,2,1,1,32301.88,0 +7042,15753591,He,438,France,Male,38,2,0,2,1,0,136859.55,0 +7043,15617348,Uchechukwu,544,France,Male,44,1,0,2,0,0,69244.24,0 +7044,15704581,Robertson,595,Germany,Male,34,2,87967.42,2,0,1,156309.52,0 +7045,15738487,Leworthy,678,France,Male,26,3,0,2,1,0,4989.33,0 +7046,15648069,Onyemachukwu,850,France,Female,36,6,0,2,1,1,190194.95,0 +7047,15737627,Rivero,589,Germany,Female,20,2,121093.29,2,1,0,3529.72,0 +7048,15731586,Lai,785,Spain,Female,31,2,121691.54,2,0,0,81778.72,0 +7049,15757467,Feng,563,Spain,Male,57,6,0,2,1,1,39297.48,0 +7050,15597709,Hornung,602,France,Female,39,6,154121.32,2,1,0,176614.86,1 +7051,15720529,Schiavone,591,France,Male,29,6,0,2,1,1,108684.65,0 +7052,15596797,Barnet,643,Spain,Male,43,1,0,2,1,1,145764.4,0 +7053,15681755,Dennys,605,France,Female,32,5,0,2,1,1,42135.28,0 +7054,15815271,Ritchie,755,Germany,Male,43,6,165048.5,3,1,0,16929.41,1 +7055,15682860,Lo,769,Spain,Male,38,6,0,2,0,0,104393.78,0 +7056,15621546,Yuriev,620,France,Female,33,9,127638.35,1,1,1,192717.57,0 +7057,15705918,Howarth,725,France,Male,31,8,0,2,1,1,59650.42,0 +7058,15684512,Gibson,818,Germany,Female,72,8,135290.42,2,1,1,63729.72,0 +7059,15671769,Zikoranachidimma,624,France,Female,71,4,170252.05,3,1,1,73679.59,1 +7060,15642934,Mason,669,Germany,Female,35,4,108269.2,2,1,0,174969.92,0 +7061,15594305,Rizzo,712,France,Female,32,1,0,2,1,0,1703.58,0 +7062,15789201,Thomson,603,Germany,Female,35,9,145623.36,1,1,0,163181.62,0 +7063,15706762,Ignatyev,597,France,Female,41,4,145809.53,2,1,1,52319.26,0 +7064,15766183,Ferguson,580,Germany,Male,76,2,130334.84,2,1,1,51672.08,0 +7065,15777994,Woods,718,France,Female,39,3,0,2,1,1,145355.11,0 +7066,15568162,Sung,527,Spain,Male,53,8,0,1,1,1,51711.57,0 +7067,15680643,Lo,729,Spain,Female,42,1,0,2,1,1,149535.97,0 +7068,15761854,Burn,746,France,Female,24,4,0,1,0,1,94105,0 +7069,15730793,Russell,699,Germany,Female,54,3,111009.32,1,1,1,155905.79,1 +7070,15692137,Jen,759,France,Female,46,2,0,1,1,1,138380.11,0 +7071,15608595,Lo Duca,748,France,Female,39,3,157371.54,1,0,1,97734.3,0 +7072,15709459,Oluchi,698,Spain,Female,63,5,0,1,1,1,173576.71,0 +7073,15775750,Yao,686,France,Male,37,9,134560.62,1,1,0,27596.39,0 +7074,15585855,Gould,679,France,Male,40,1,0,1,1,1,16897.19,0 +7075,15752139,Salter,682,Germany,Male,36,5,72373.62,2,1,0,36895.99,0 +7076,15768295,Warner,778,France,Female,34,7,109564.1,1,0,1,113046.81,0 +7077,15766906,Salier,742,France,Female,25,4,132116.13,2,1,0,129933.5,0 +7078,15725776,Lazar,649,Germany,Male,24,7,101195.23,1,0,0,133091.32,0 +7079,15682576,Onyenachiya,763,France,Male,67,1,149436.73,2,0,1,106282.74,0 +7080,15704081,Findlay,595,Germany,Male,30,9,130682.11,2,1,1,57862.88,0 +7081,15719940,Gibbons,628,Germany,Female,51,10,115280.49,2,0,0,12628.61,1 +7082,15672894,McCawley,625,France,Female,36,8,129944.39,2,0,0,198914.8,0 +7083,15667451,Taylor,733,France,Male,36,5,0,2,1,1,109127.54,0 +7084,15636767,Yang,665,Spain,Female,32,10,0,1,1,1,22487.45,0 +7085,15571415,Okwudiliolisa,805,Germany,Male,56,6,151802.29,1,1,0,46791.09,1 +7086,15575605,Napolitano,725,France,Male,38,6,0,2,1,1,158697.28,0 +7087,15649160,Vavilov,554,France,Female,38,3,138731.95,1,1,1,194138.36,0 +7088,15615832,Teague,675,Spain,Female,35,8,155621.08,1,0,1,35177.31,0 +7089,15600975,Chiemenam,556,France,Female,54,4,150005.38,1,1,0,157015.5,1 +7090,15690772,Hughes,635,Spain,Female,48,2,0,2,1,1,136551.25,0 +7091,15565714,Cattaneo,601,France,Male,47,1,64430.06,2,0,1,96517.97,0 +7092,15763108,Davis,600,Germany,Male,53,7,106261.63,1,1,0,93629.66,1 +7093,15723884,Nekrasova,758,Spain,Male,40,3,0,2,0,0,96097.65,0 +7094,15644453,Loggia,606,Germany,Female,41,4,132670.53,1,1,0,156476.36,1 +7095,15655464,Combes,640,France,Female,67,3,0,1,0,1,42964.63,0 +7096,15783883,Onwuka,753,Germany,Female,38,1,117314.92,1,1,0,122021.33,1 +7097,15787693,Kharlamov,559,Spain,Male,38,3,145874.35,1,1,0,56311.39,1 +7098,15664793,Scott,754,Spain,Female,50,7,146777.44,2,0,1,150685.52,0 +7099,15642391,Lettiere,621,Germany,Male,51,4,109978.83,1,0,0,177740.58,1 +7100,15756538,Osonduagwuike,654,France,Female,37,5,0,1,0,1,71492.28,0 +7101,15668830,Wan,650,Spain,Male,24,8,108881.73,1,1,0,104492.83,0 +7102,15796569,Donaldson,831,Spain,Female,44,10,0,1,0,1,47729.33,0 +7103,15677112,Chukwufumnanya,519,France,Male,39,2,112957.26,2,1,0,97593.16,0 +7104,15815040,Ma,552,Germany,Female,42,8,103362.14,1,0,1,186869.58,1 +7105,15590434,Alexander,577,Spain,Male,41,4,89015.61,1,0,1,135227.23,0 +7106,15597536,Nkemjika,576,Spain,Male,45,5,133618.01,1,0,0,135244.87,0 +7107,15723989,Carroll,646,France,Male,40,5,93680.43,2,1,1,179473.26,0 +7108,15767358,Obioma,711,Germany,Female,45,1,97486.15,2,1,0,50610.62,0 +7109,15594812,Campbell,806,Spain,Female,37,2,137794.18,2,0,1,75232.02,0 +7110,15688210,Sims,670,France,Female,39,8,101928.51,1,0,0,89205.54,0 +7111,15681509,McKay,679,Spain,Female,28,9,0,2,0,1,61761.77,0 +7112,15572390,Huang,850,Spain,Female,39,6,0,2,1,0,103921.43,0 +7113,15801441,Campbell,670,Germany,Female,35,2,79585.96,1,0,1,198802.9,0 +7114,15783859,Boni,733,France,Female,24,3,161884.99,1,1,1,9617.24,0 +7115,15575243,Gorbunova,764,France,Female,39,1,129068.54,2,1,1,187905.12,0 +7116,15773421,Genovese,673,France,Female,42,4,0,2,1,0,121440.8,0 +7117,15788776,Landor,588,Germany,Male,49,6,132623.76,3,1,0,36292.94,1 +7118,15765257,Meng,564,Spain,Male,31,5,121461.87,1,1,1,20432.09,1 +7119,15661412,Wardell,715,France,Male,32,8,175307.32,1,1,0,187051.23,0 +7120,15636478,Williams,621,France,Male,31,7,136658.61,1,1,1,148689.13,0 +7121,15603683,Ofodile,796,Spain,Female,23,3,146584.19,2,0,0,125445.8,0 +7122,15651868,Clark,672,France,Male,34,6,0,1,0,0,22736.06,0 +7123,15815443,Lo,527,Spain,Female,46,10,131414.76,1,1,0,54947.51,0 +7124,15682686,Chukwuemeka,722,France,Female,38,3,0,2,0,1,167984.72,0 +7125,15697460,Lai,596,Germany,Male,34,4,99441.21,2,0,1,4802.27,0 +7126,15748432,Arcuri,746,France,Female,32,4,0,2,1,1,72909.75,0 +7127,15698271,Graham,523,France,Female,26,4,0,2,1,0,185488.81,0 +7128,15808662,Krylov,624,France,Male,44,3,0,2,1,0,88407.51,0 +7129,15690372,Henry,553,Spain,Male,38,1,181110.13,2,1,0,184544.59,0 +7130,15781875,Jamieson,850,Spain,Male,33,3,100476.46,2,1,1,136539.13,0 +7131,15801473,Moore,599,Germany,Male,33,2,51949.95,2,1,0,85045.92,0 +7132,15704509,Tan,492,France,Male,35,8,121063.49,1,0,0,85421.48,0 +7133,15694666,Thornton,707,Spain,Male,48,8,88441.64,1,1,1,119903.2,1 +7134,15731166,Macleod,743,France,Female,30,1,127023.39,1,1,1,138780.89,0 +7135,15728523,Rizzo,522,France,Male,41,5,144147.68,1,1,1,14789.9,0 +7136,15788442,Chukwukadibia,681,Spain,Female,57,2,173306.13,1,0,1,131964.66,0 +7137,15689781,Ts'ai,826,France,Female,49,0,0,1,0,0,178709.98,1 +7138,15764226,Lu,630,Germany,Female,28,8,106425.75,1,1,1,20344.84,0 +7139,15809837,Kent,430,Germany,Female,66,6,135392.31,2,1,1,172852.06,1 +7140,15805212,Black,806,France,Female,67,1,0,2,0,1,103945.58,0 +7141,15716082,Chukwubuikem,703,Spain,Male,39,6,152685.4,1,0,0,183656.12,0 +7142,15643056,McMillan,755,Germany,Female,38,1,82083.52,1,0,1,10333.78,0 +7143,15654859,Ngozichukwuka,612,Spain,Female,63,2,131629.17,2,1,0,122109.58,1 +7144,15761158,Y?an,719,France,Female,54,7,0,2,1,1,125041.52,0 +7145,15577515,Sung,554,Germany,Female,55,0,108477.27,1,0,1,140003,1 +7146,15723827,Macartney,683,France,Male,30,4,114779.35,1,0,0,183171.47,0 +7147,15646594,Ali,749,France,Male,41,5,57568.94,1,1,1,61128.29,0 +7148,15712877,Morley,724,Spain,Male,36,1,0,2,1,0,52462.25,0 +7149,15598802,Martin,770,Spain,Male,30,8,0,2,0,1,50839.85,0 +7150,15699340,Okorie,680,France,Male,37,4,0,2,1,0,61240.87,0 +7151,15691150,Ku,699,France,Female,32,4,110559.46,1,1,1,127429.56,0 +7152,15608688,Andreyeva,442,France,Male,34,4,0,2,1,0,68343.08,0 +7153,15737998,Cheng,529,France,Male,46,8,0,1,0,0,126511.94,1 +7154,15735837,Hsia,574,Spain,Male,36,3,0,2,1,1,8559.66,0 +7155,15659100,Lane,605,France,Male,33,9,128152.82,1,0,0,147822.81,0 +7156,15609070,Findlay,515,Germany,Male,45,7,120961.5,3,1,1,39288.11,1 +7157,15650313,Okonkwo,632,Germany,Male,65,6,129472.33,1,1,1,85179.48,0 +7158,15627699,Pirogova,558,France,Male,32,10,105000.23,1,1,0,190019.61,0 +7159,15591010,McDonald,434,Germany,Male,55,8,109339.17,2,1,0,96405.88,1 +7160,15798895,Okonkwo,525,France,Female,59,6,55328.4,1,1,0,83342.73,1 +7161,15745375,Nnanna,640,Germany,Male,23,3,72012.76,1,1,0,161333.13,0 +7162,15775235,Ku,690,France,Female,36,6,110480.48,1,0,0,81292.33,0 +7163,15780088,Porter,607,Spain,Male,34,9,132439.99,1,1,0,177747.72,0 +7164,15649379,Somayina,850,France,Female,46,3,0,2,1,1,187980.21,0 +7165,15713983,Mao,780,Germany,Male,34,5,94108.54,2,1,0,177235.21,0 +7166,15709252,Fuller,616,Germany,Female,28,10,105173.99,1,0,1,29835.37,1 +7167,15699238,Craig,618,Spain,Female,40,8,0,2,1,0,80204.38,0 +7168,15732884,Trevisano,676,France,Male,29,7,131959.86,1,0,0,189268.81,0 +7169,15587297,Ruiz,507,France,Male,33,7,0,2,1,1,85411.01,0 +7170,15684722,Fraser,490,France,Male,34,5,122952.9,2,0,0,154360.97,0 +7171,15621244,Gallo,678,France,Male,36,0,107379.68,1,1,1,84460.18,0 +7172,15744273,Waterhouse,637,Germany,Male,30,6,122641.56,2,1,0,65618.01,0 +7173,15682540,Cremonesi,602,France,Female,33,8,0,2,1,1,112928.74,0 +7174,15636521,Feng,744,Spain,Female,30,1,124037.28,1,1,1,142210.94,0 +7175,15785339,H?,640,France,Female,50,9,117565.03,2,0,0,82559.77,0 +7176,15638983,Jara,684,France,Female,38,5,133189.4,1,0,0,127388.06,0 +7177,15654625,Wilson,495,Germany,Male,39,8,120252.02,2,1,1,10160.23,0 +7178,15697310,O'Callaghan,559,Germany,Female,28,3,152264.81,1,0,0,64242.31,0 +7179,15678210,Robson,684,France,Male,38,5,105069.98,2,1,1,198355.28,0 +7180,15575438,Pease,613,France,Male,42,7,115076.06,1,1,1,79323.61,0 +7181,15632789,Maclean,794,France,Male,30,8,0,2,1,1,24113.91,0 +7182,15621423,Lavrentyev,736,France,Female,42,7,117280.23,3,0,0,41921.06,1 +7183,15573520,Rhodes,692,Germany,Male,49,6,110540.43,2,0,1,107472.99,0 +7184,15740458,Murphy,703,Spain,Male,36,7,135095.47,1,1,0,143859.66,0 +7185,15762799,Alexander,720,Germany,Male,23,0,187861.18,2,1,1,104120.17,0 +7186,15686885,Nekrasov,777,Germany,Male,44,3,124655.59,2,0,1,79792.3,0 +7187,15565996,Arnold,653,France,Male,44,8,0,2,1,1,154639.72,0 +7188,15662152,Trevisan,552,France,Female,38,9,134105.01,1,0,0,57850.1,0 +7189,15711742,Mason,708,France,Female,34,4,0,1,1,1,62868.33,0 +7190,15701885,Tucker,647,France,Female,40,9,0,2,0,1,92357.21,0 +7191,15774262,Hobson,597,Germany,Male,52,8,83693.34,2,1,1,161083.53,0 +7192,15567839,Gordon,501,France,Male,42,9,114631.23,1,0,1,91429.74,0 +7193,15644400,Anderson,709,France,Male,44,9,128601.98,1,1,0,117031.2,0 +7194,15797246,Terry,621,Germany,Female,34,2,91258.52,2,1,0,44857.4,0 +7195,15778290,Lappin,799,France,Male,70,8,70416.75,1,1,1,36483.52,0 +7196,15708714,Santiago,675,France,Female,33,6,0,2,1,0,34045.61,0 +7197,15586183,Wallace,561,France,Female,35,5,0,2,1,0,59981.62,0 +7198,15761733,King,707,France,Female,42,10,0,2,1,1,152944.39,0 +7199,15773934,Fang,670,France,Male,33,6,88294.6,1,1,0,66979.06,0 +7200,15705343,May,649,Spain,Female,32,7,0,1,1,0,28797.32,0 +7201,15593959,Travis,524,France,Male,28,1,93577.3,1,1,1,51670.82,0 +7202,15664615,Nnachetam,689,Germany,Female,30,5,136650.89,1,1,1,41865.72,1 +7203,15671014,Zhdanova,573,Spain,Female,72,8,98765.84,1,1,1,96015.53,0 +7204,15657778,Jefferson,657,France,Male,33,1,84309.57,2,0,0,103914.4,0 +7205,15585192,Cremonesi,686,Spain,Male,39,10,136258.06,1,0,0,89199.51,0 +7206,15592914,Fang,683,France,Female,29,9,0,2,1,1,48849.89,0 +7207,15770995,Sinclair,753,Germany,Female,47,1,131160.85,1,1,0,197444.69,0 +7208,15570990,Begley,520,Spain,Female,30,4,145222.99,2,0,0,145160.96,0 +7209,15596165,Degtyarev,547,Germany,Male,25,4,98141.57,2,1,1,52309.8,0 +7210,15788131,Atkins,653,France,Male,47,6,0,1,1,0,50695.93,1 +7211,15800773,Ikenna,648,Spain,Female,28,9,102282.61,1,1,1,157891.11,0 +7212,15690153,Sun,639,France,Female,37,4,116121.84,2,0,1,181850.74,0 +7213,15638989,Lettiere,711,France,Female,25,5,190066.54,1,0,0,51345.39,1 +7214,15623210,Smith,484,Germany,Female,55,8,149349.58,3,0,0,137519.92,1 +7215,15652658,Finch,721,France,Male,36,1,155176.83,2,1,1,49653.37,0 +7216,15684440,Monaldo,548,Germany,Male,32,2,98986.28,1,1,1,55867.38,0 +7217,15730287,Ugonna,679,France,Male,41,8,147726.98,3,1,0,172749.4,1 +7218,15720353,Chiang,553,France,Male,41,1,0,2,1,0,90607.31,0 +7219,15767231,Sun,757,France,Male,36,7,144852.06,1,0,0,130861.95,0 +7220,15761554,Blackburn,581,France,Male,54,4,89299.81,1,0,0,5558.47,1 +7221,15706637,Chang,718,Spain,Male,40,9,0,2,0,0,121537.91,0 +7222,15690492,Palermo,625,France,Male,41,6,97663.16,2,1,0,57128.78,0 +7223,15694237,McEwan,744,Spain,Male,39,4,95161.75,1,1,0,19409.77,0 +7224,15729771,Davide,799,Germany,Male,31,9,154586.92,1,0,1,88604.89,1 +7225,15609823,Chieloka,751,Spain,Female,34,8,127095.14,2,0,0,479.54,0 +7226,15793366,Humphreys,781,Germany,Male,35,7,92526.15,2,1,1,173837.54,0 +7227,15614813,Cocci,777,Germany,Female,46,0,107362.8,1,1,0,487.3,0 +7228,15566495,Hanson,704,Spain,Female,24,2,0,1,1,0,35600.25,1 +7229,15707602,Macleod,539,France,Female,47,2,127286.04,2,1,1,166929.43,1 +7230,15635244,Ritchie,716,France,Female,29,6,0,2,1,1,98998.61,0 +7231,15805627,Nebechukwu,670,France,Male,37,2,0,2,1,1,54229.74,0 +7232,15607986,Nnamutaezinwa,555,France,Male,40,10,139930.18,1,1,1,105720.09,0 +7233,15799785,Ikemefuna,679,Germany,Female,30,4,77949.69,1,1,1,121151.46,0 +7234,15699963,Scott,571,France,Male,38,1,121405.04,1,1,1,154844.22,0 +7235,15624595,Chiang,512,Spain,Female,35,5,124580.69,1,1,1,18785.48,0 +7236,15629750,Artyomova,697,France,Male,35,5,133087.76,1,1,0,64771.61,0 +7237,15651460,Hsieh,424,Spain,Male,34,7,0,1,1,1,16250.61,0 +7238,15753550,Levien,684,France,Female,43,7,0,2,1,0,131093.99,0 +7239,15594133,Erskine,697,Spain,Male,62,7,0,1,1,0,129188.18,1 +7240,15772329,Fiorentino,580,Germany,Male,45,8,103741.14,1,1,0,47428.73,1 +7241,15591552,Okonkwo,600,France,Female,32,7,98877.95,1,1,0,132973.21,0 +7242,15750921,Monds,521,France,Male,37,5,105843.26,2,1,1,84908.2,0 +7243,15701687,Campbell,664,Spain,Male,44,7,77526.66,3,0,0,57338.56,1 +7244,15728906,Ibekwe,634,France,Male,77,5,0,2,1,1,161579.85,0 +7245,15670029,Marcelo,445,France,Female,33,7,0,2,1,0,122625.68,0 +7246,15763579,Castro,702,Germany,Female,36,2,105264.88,2,1,1,52909.87,0 +7247,15728010,Capon,485,France,Male,37,5,0,2,0,1,170226.47,0 +7248,15663194,Voronova,582,Germany,Female,40,3,110150.43,1,1,1,191757.65,1 +7249,15736510,Loggia,605,Spain,Female,57,2,0,3,1,0,66652.75,1 +7250,15745804,Law,628,France,Male,25,7,0,2,1,1,195977.75,0 +7251,15631451,Grant,604,Spain,Female,28,6,0,2,1,1,69056.26,0 +7252,15746995,Greco,724,Germany,Male,31,9,138166.3,1,1,0,12920.43,0 +7253,15730673,Dietz,567,Germany,Male,40,7,122265.24,1,1,0,138552.74,0 +7254,15734649,Martel,779,Spain,Female,55,0,133295.98,1,1,0,22832.71,1 +7255,15701081,Jarvis,785,France,Male,36,2,0,1,0,1,61811.1,0 +7256,15632503,Meng,563,France,Female,32,0,148326.09,1,1,0,191604.27,1 +7257,15585928,Hay,821,Germany,Female,31,2,68927.57,1,1,1,25445,0 +7258,15648681,Voronoff,747,France,Female,47,5,139914.6,4,0,1,129964.56,1 +7259,15747757,Trevascus,600,Germany,Female,58,8,118723.11,1,0,0,6209.51,1 +7260,15718921,Ho,625,Spain,Male,32,7,106957.28,1,1,1,134794.02,0 +7261,15571081,Hansen,773,France,Female,41,7,190238.93,1,1,1,57549.65,0 +7262,15734578,Craig,726,France,Female,53,1,113537.73,1,0,1,28367.21,0 +7263,15579583,Hall,641,Spain,Female,40,4,101090.27,1,1,1,51703.09,0 +7264,15622729,Sun,649,France,Female,46,2,0,2,1,1,66602.7,0 +7265,15662189,Durant,434,Spain,Male,33,3,0,1,1,1,2739.71,0 +7266,15692718,Jackson,738,France,Female,38,7,0,2,0,0,69227.42,0 +7267,15762716,Chigozie,762,Spain,Female,60,10,168920.75,1,1,0,31445.03,1 +7268,15724851,Farmer,507,Germany,Male,31,9,111589.67,1,1,0,150037.19,0 +7269,15587266,Douglas,606,Germany,Female,27,6,172310.33,1,0,1,111448.92,0 +7270,15675926,Ardis,655,Germany,Male,34,7,118028.35,1,1,0,51226.32,1 +7271,15706268,Smith,697,Germany,Male,51,1,147910.3,1,1,1,53581.14,0 +7272,15581871,Butler,504,Germany,Male,42,7,131287.36,2,1,1,149697.78,0 +7273,15666166,Pettry,653,France,Female,74,0,121276.32,1,1,1,160348.31,0 +7274,15671582,John,660,Spain,Male,38,6,109869.32,1,1,1,154641.91,0 +7275,15680901,Potter,652,France,Female,34,6,97435.85,2,1,1,104331.76,0 +7276,15642336,Shaw,669,France,Female,42,9,0,2,0,0,135630.32,0 +7277,15653147,Boyle,594,France,Male,35,2,133853.27,1,1,1,65361.66,0 +7278,15571284,Elmore,756,Germany,Male,32,0,109528.16,2,1,1,56176.31,0 +7279,15591360,Udinesi,642,France,Female,33,4,84607.34,2,0,1,60059.47,0 +7280,15810485,Sun,486,Germany,Male,37,1,101438,1,0,0,51364.56,0 +7281,15611973,Tuan,804,France,Male,55,7,0,2,1,1,118752.6,0 +7282,15735572,Lawrence,629,France,Male,59,9,113657.83,1,1,1,116848.79,1 +7283,15567860,Burrows,581,Spain,Female,44,7,189318.16,2,1,0,45026.23,1 +7284,15795690,Shao,667,France,Male,31,3,99513.91,1,1,1,189657.26,0 +7285,15706464,White,667,Spain,Male,35,4,97585.32,2,0,0,57213.46,0 +7286,15725028,Chialuka,679,France,Male,29,3,0,2,1,1,63687.06,0 +7287,15751167,Toscano,680,France,Female,43,4,0,2,1,1,58761.33,0 +7288,15633944,McKay,644,Spain,Male,32,3,136659.74,1,1,1,14187.78,0 +7289,15672637,Voronkov,571,France,Female,30,4,85755.86,1,1,0,145115.95,0 +7290,15680895,Sal,627,Spain,Female,35,7,0,1,1,0,187718.26,0 +7291,15793825,Ikechukwu,536,France,Male,39,4,0,2,1,0,27150.35,0 +7292,15611318,Kruglova,599,Spain,Male,33,4,51690.89,1,1,0,111622.76,1 +7293,15768474,Clements,744,Spain,Male,34,3,0,2,1,0,27244.35,0 +7294,15716276,Kennedy,709,France,Female,34,2,111669.68,1,1,0,57029.66,0 +7295,15623668,Johnson,653,Germany,Male,31,2,154741.45,2,0,0,25183.01,0 +7296,15696361,Chung,648,Germany,Male,31,7,125681.51,1,0,1,129980.93,0 +7297,15607988,Garland,663,Germany,Female,37,8,155303.71,1,1,0,118716.63,0 +7298,15637891,Docherty,613,Germany,Female,43,4,140681.68,1,0,1,20134.07,0 +7299,15789865,Nnaife,620,France,Male,28,9,71902.52,1,0,1,190208.23,0 +7300,15627190,Lettiere,661,France,Male,51,6,146606.6,1,1,1,68021.9,0 +7301,15788224,Sanderson,669,Germany,Male,45,1,123949.75,1,0,0,110881.56,0 +7302,15702149,Fomin,767,Germany,Female,33,1,144753.21,1,1,1,132480.75,0 +7303,15708236,Wright,491,France,Female,72,6,91285.22,1,1,1,7032.95,0 +7304,15568469,Buckley,653,France,Male,43,0,0,2,1,0,27862.58,0 +7305,15764444,Pan,679,Germany,Male,58,8,125850.53,2,1,1,87008.17,0 +7306,15794204,Manna,687,France,Male,28,7,108116.66,1,1,1,27411.19,0 +7307,15807546,Chinwendu,837,France,Female,38,2,0,2,1,1,46395.21,0 +7308,15782159,Ndubuagha,850,France,Male,28,8,67639.56,2,1,1,194245.29,0 +7309,15618703,White,663,Spain,Female,53,6,150200.23,1,0,1,151317.27,1 +7310,15793317,Hale,547,Spain,Female,22,7,141287.15,1,1,0,118142.79,0 +7311,15740487,Ross,627,France,Female,41,6,0,3,1,1,138700.75,1 +7312,15722479,Ikenna,707,France,Male,37,1,0,2,0,1,6035.51,0 +7313,15688264,Nkemdilim,629,France,Female,43,0,0,2,1,1,41263.69,0 +7314,15583067,McMillan,687,France,Female,36,4,97157.96,1,0,1,63185.05,0 +7315,15686670,Duke,588,France,Female,36,2,0,2,1,0,92536,1 +7316,15593345,Bradbury,502,Germany,Female,33,6,125241.17,2,1,1,158736.07,0 +7317,15811690,Bayley,793,Germany,Male,54,2,128966.13,1,0,0,18633.4,1 +7318,15734008,Bartlett,727,Germany,Male,59,5,152581.06,1,1,0,71830.1,1 +7319,15771856,Cremin,632,Spain,Female,32,1,0,2,1,0,19525.65,0 +7320,15762045,Gilchrist,474,Germany,Female,37,5,142688.57,2,1,1,110953.33,0 +7321,15778142,Shih,850,Germany,Female,31,1,130089.56,2,1,1,4466.21,0 +7322,15689268,Fitzpatrick,584,France,Male,36,9,0,1,1,1,105818.51,0 +7323,15721507,Pagan,713,France,Female,32,1,117094.02,1,0,0,149558.83,1 +7324,15750476,Hendrick,742,Spain,Male,24,8,0,2,1,0,4070.28,0 +7325,15810723,Sanderson,607,France,Female,39,10,0,3,1,0,132741.13,1 +7326,15787229,Samsonova,761,Spain,Female,34,2,0,2,1,0,61251.25,0 +7327,15570508,Azubuike,600,France,Male,49,7,90218.9,1,1,0,91347.76,0 +7328,15617065,Pan,650,Spain,Male,42,4,194532.66,1,1,0,171045.31,1 +7329,15689786,Massie,850,Germany,Male,56,1,169743.83,1,0,0,155850.4,1 +7330,15648876,Sandover,501,France,Female,34,5,0,1,1,0,27380.99,0 +7331,15802106,Craig,418,France,Male,34,8,155973.88,1,1,0,154208.96,0 +7332,15773869,Onwudiwe,797,Spain,Male,59,4,129321.44,1,1,1,93624.55,0 +7333,15711635,Chu,788,Germany,Female,42,6,138650.49,2,1,0,64746.07,0 +7334,15795527,Zetticci,699,Spain,Male,43,2,136487.86,2,1,0,82815.93,0 +7335,15759133,Vaguine,616,France,Male,18,6,0,2,1,1,27308.58,0 +7336,15679394,Owen,651,France,Female,41,4,38617.2,1,1,1,104876.8,0 +7337,15801072,Hurst,654,France,Female,28,7,0,2,1,0,151316.37,0 +7338,15646082,Harding,676,France,Female,34,8,82909.14,1,1,0,91817.38,1 +7339,15796111,Smith,708,Germany,Female,54,8,145151.4,1,0,1,125311.17,1 +7340,15670646,Moore,499,Spain,Female,42,0,147187.84,1,1,1,14868.94,1 +7341,15578722,Bradley,689,France,Male,39,4,0,2,1,0,196112.45,0 +7342,15815095,Burfitt,850,Spain,Male,54,7,108185.81,2,0,0,24093.4,1 +7343,15730360,Mackenzie,502,France,Male,30,4,0,2,1,1,66263.87,0 +7344,15763194,Milanesi,643,France,Male,34,7,0,2,0,1,100304.13,0 +7345,15720725,Shubin,762,France,Male,28,2,0,2,1,0,167909.52,0 +7346,15567834,Nieves,719,France,Male,49,5,105918.1,1,1,1,16246.59,0 +7347,15720644,Martin,789,France,Male,27,6,0,2,1,0,103603.65,0 +7348,15811742,Jen,553,Spain,Male,42,7,0,2,1,0,7680.23,0 +7349,15813363,Woods,448,Spain,Male,25,2,0,2,0,0,95215.73,0 +7350,15717629,Docherty,632,Germany,Male,42,6,59972.26,2,0,1,148172.94,0 +7351,15713160,Lin,669,Spain,Male,25,7,157228.61,2,1,0,124382.9,0 +7352,15568878,Cheng,654,Spain,Male,34,5,0,2,1,0,159311.46,0 +7353,15809800,Korovina,726,France,Female,38,4,0,2,0,0,6787.48,0 +7354,15736420,Macdonald,596,France,Male,21,4,210433.08,2,0,1,197297.77,1 +7355,15757933,Hardy,733,Germany,Female,30,1,102452.71,1,1,0,21556.95,0 +7356,15623072,Shaw,529,Spain,Female,35,5,0,2,1,0,56518,0 +7357,15683993,Knight,493,France,Female,37,8,142987.46,2,1,0,158840.99,0 +7358,15570947,Bruny,615,Spain,Female,29,7,143330.56,2,1,1,126396.01,0 +7359,15797767,Ikedinachukwu,600,France,Female,49,6,0,1,0,1,148087.88,1 +7360,15731989,Moran,666,France,Male,36,4,120165.4,2,1,0,33701.5,0 +7361,15591035,Macleod,644,Spain,Male,54,6,0,1,0,1,84622.37,0 +7362,15586479,Yin,692,France,Female,36,4,0,1,1,0,185580.89,1 +7363,15605872,Felix,707,France,Male,73,6,66573.17,1,1,1,62768.8,0 +7364,15666012,Rippey,603,France,Male,40,4,102833.46,2,1,1,38829.11,0 +7365,15641733,Mishina,671,France,Female,34,5,164757.56,1,1,0,110748.88,0 +7366,15593178,Graham,568,Spain,Female,36,10,153610.61,1,1,1,54083.8,1 +7367,15649183,Johnston,598,Spain,Female,35,8,0,3,0,1,88658.73,0 +7368,15736399,Korovin,606,Spain,Male,42,10,0,2,1,0,177938.52,0 +7369,15751137,Lei,850,Germany,Female,36,3,169025.83,1,1,0,174235.06,0 +7370,15757188,Chimaijem,644,Spain,Female,26,4,153455.72,2,1,1,82696.84,0 +7371,15726167,Scott,655,France,Male,37,4,0,2,1,1,142415.97,0 +7372,15624850,Grant,850,France,Male,30,10,153972.89,2,1,0,62811.03,0 +7373,15717700,McIntyre,683,Spain,Male,34,9,114609.55,2,0,1,25339.29,0 +7374,15716347,Griffin,663,Germany,Male,37,7,143625.83,2,0,1,176487.05,0 +7375,15696287,Converse,682,Germany,Female,38,1,116520.28,1,1,1,49833.5,1 +7376,15638871,Ch'ang,639,France,Male,77,6,80926.02,2,1,1,55829.25,0 +7377,15765093,Coates,704,France,Male,23,6,166594.78,1,1,1,155823.2,0 +7378,15592999,Reid,691,France,Female,40,0,115465.98,1,1,1,60622.61,0 +7379,15641715,Ts'ui,599,France,Male,34,8,0,2,1,1,174196.68,0 +7380,15607746,Belstead,573,France,Female,36,1,0,1,1,1,56905.38,0 +7381,15625311,Dickinson,589,Germany,Female,41,7,92618.62,1,1,1,101178.85,0 +7382,15573077,Nwora,620,Germany,Female,25,8,141825.88,1,1,1,73857.94,1 +7383,15735106,Bishop,647,Spain,Male,28,6,149594.02,2,1,0,102325.19,0 +7384,15672912,Loggia,737,Spain,Female,39,7,130051.66,2,0,0,55356.39,1 +7385,15589881,Rowe,634,France,Female,41,7,0,2,1,1,131284.93,0 +7386,15660144,Balashov,660,France,Male,38,4,0,2,0,0,88080.43,0 +7387,15664083,Ulyanova,666,Germany,Female,37,2,158468.76,1,0,1,93266.01,0 +7388,15690898,Bogolyubova,696,France,Male,44,8,161889.79,1,0,0,75562.47,0 +7389,15808023,Remington,836,France,Female,29,9,133681.78,1,1,1,153747.73,0 +7390,15676909,Mishin,667,Spain,Female,34,5,0,2,1,0,163830.64,0 +7391,15764922,Tu,596,Spain,Male,20,3,187294.46,1,1,0,103456.47,0 +7392,15766734,Castiglione,430,France,Male,31,5,0,1,1,0,95655.16,0 +7393,15795079,Nnaife,596,Spain,Male,67,6,0,2,1,1,138350.74,0 +7394,15757434,Yang,599,France,Male,28,7,119706.22,1,0,0,31190.42,0 +7395,15673747,Ayers,519,France,Female,22,8,0,1,0,1,167553.06,0 +7396,15808386,Cocci,721,Germany,Female,45,7,138523.2,1,0,0,59604.45,1 +7397,15603565,Mackenzie,603,Spain,Female,56,5,90778.76,2,1,0,162223.67,1 +7398,15744044,Fiorentini,572,Germany,Male,47,4,99353.42,1,1,0,196549.85,1 +7399,15577771,Akabueze,453,Germany,Female,40,1,111524.49,1,1,1,120373.84,1 +7400,15769548,Hyde,668,France,Female,37,7,128645.67,1,1,0,92149.64,0 +7401,15802071,Levi,762,Germany,Male,35,1,117458.51,1,0,1,178361.48,1 +7402,15677395,Nwabugwu,633,France,Female,39,9,129189.15,2,0,0,170998.83,0 +7403,15632010,Chia,647,Spain,Male,33,7,121260.19,2,1,0,77216.48,0 +7404,15779492,Trevisano,796,Spain,Male,56,6,94231.13,1,0,0,121164.6,1 +7405,15694677,Bennetts,733,France,Male,39,1,0,2,1,1,141841.31,0 +7406,15704315,Teng,556,France,Male,34,8,163757.06,1,1,1,104000.06,0 +7407,15742009,Hsueh,489,Spain,Male,58,4,0,2,1,1,191419.32,0 +7408,15766663,Mahmood,639,France,Male,22,4,0,2,1,0,28188.96,0 +7409,15742297,Sinclair,715,France,Male,35,2,141005.47,1,1,1,60407.93,0 +7410,15688059,Chin,807,Germany,Female,42,9,105356.09,2,1,1,130489.37,0 +7411,15752344,She,714,Spain,Male,34,5,0,2,1,0,193040.32,0 +7412,15698749,He,626,Germany,Female,23,6,85897.95,1,1,0,109742.8,0 +7413,15631693,Hill,697,France,Male,36,7,0,2,1,1,74760.32,0 +7414,15604536,Vachon,850,Germany,Female,31,4,164672.66,1,0,1,61936.1,0 +7415,15802869,Ball,737,Germany,Female,45,2,99169.67,2,1,1,78650.95,0 +7416,15635598,Hsieh,812,France,Male,29,6,0,2,0,0,168023.6,0 +7417,15592326,Baker,583,France,Male,36,8,0,2,0,1,5571.59,0 +7418,15736533,Monaldo,730,Germany,Female,37,5,124053.03,1,1,0,118591.67,0 +7419,15647191,Lucchesi,677,France,Male,36,4,0,2,1,0,7824.31,0 +7420,15622507,Hamilton,748,Germany,Female,40,3,103499.09,2,0,0,38153.19,0 +7421,15765487,Kuo,753,Germany,Female,38,9,151766.71,1,1,1,180829.99,0 +7422,15646521,Fan,634,Spain,Female,36,1,0,1,1,1,143960.72,0 +7423,15746258,Wright,622,France,Male,29,7,101486.96,1,1,1,8788.35,0 +7424,15692430,Milano,699,Germany,Male,36,2,123601.56,2,1,0,103557.85,0 +7425,15625501,Wall,570,Germany,Male,38,1,127201.58,1,1,0,147168.28,1 +7426,15640521,Chidumaga,552,Germany,Male,33,3,144962.74,1,1,0,58844.84,1 +7427,15790630,Olisaemeka,619,France,Female,48,4,0,1,0,0,18094.96,1 +7428,15664720,Kovalyova,714,Spain,Male,33,8,122017.19,1,0,0,162515.17,0 +7429,15750055,Onio,503,Spain,Male,32,9,100262.88,2,1,1,157921.25,0 +7430,15644878,Hill,685,Spain,Female,43,6,117302.62,1,0,0,68701.73,0 +7431,15754578,Okeke,606,France,Female,35,0,135984.15,2,1,0,186778.89,0 +7432,15705379,Upjohn,678,France,Male,38,3,0,2,1,0,66561.6,0 +7433,15761047,H?,724,Germany,Male,31,2,160997.54,2,0,1,64831.36,0 +7434,15671293,Marcus,779,Germany,Female,37,2,128389.63,1,1,1,6589.16,1 +7435,15687527,Yobachukwu,638,Spain,Male,35,1,0,2,1,0,165370.66,0 +7436,15647898,Russell,610,Spain,Female,50,5,130554.51,3,1,0,184758.17,1 +7437,15671534,Hovell,646,Germany,Female,57,6,90212,1,1,0,13911.27,1 +7438,15591248,Chukwumaobim,628,France,Female,29,9,71996.29,1,1,1,34857.46,0 +7439,15676156,Boyle,528,France,Female,32,4,85615.66,2,1,0,156192.43,0 +7440,15812918,Scott,432,France,Female,27,6,62339.81,2,0,0,53874.67,0 +7441,15604130,Johnstone,622,Spain,Female,47,6,142319.03,1,0,0,100183.05,0 +7442,15700549,Alvares,721,France,Male,54,5,0,2,1,1,4493.12,0 +7443,15715519,McDavid,614,Spain,Male,36,5,0,2,1,0,130610.78,0 +7444,15707042,Dellucci,634,France,Female,24,2,87413.19,1,1,0,63340.65,0 +7445,15605276,Brothers,742,France,Female,29,4,0,2,1,1,180066.59,0 +7446,15630592,Sanders,516,France,Female,45,4,0,1,1,0,95273.73,1 +7447,15636626,Morrison,718,France,Male,35,3,97560.16,1,1,1,53511.74,0 +7448,15740411,Molle,636,Germany,Male,30,8,141787.31,2,1,1,109685.61,0 +7449,15593834,Genovese,691,Spain,Male,36,7,129934.64,1,0,0,75664.56,1 +7450,15804235,Zetticci,698,France,Female,37,2,166178.02,2,1,1,71972.95,0 +7451,15679801,Hsueh,712,Spain,Female,39,5,163097.55,2,1,1,23702.42,0 +7452,15673907,Alexander,659,France,Male,20,8,0,2,0,0,112572.02,0 +7453,15636562,Muravyova,573,Spain,Male,44,8,0,2,0,0,62424.46,0 +7454,15702571,Wright,778,Germany,Female,35,1,151958.19,3,1,1,131238.37,1 +7455,15627365,Calabresi,732,France,Male,46,0,0,2,1,1,184350.78,0 +7456,15748499,Johnson,550,Germany,Male,33,4,118400.91,1,0,1,13999.64,1 +7457,15598614,Lucchesi,790,Spain,Male,20,8,0,2,1,0,168152.76,0 +7458,15668889,Galgano,665,Germany,Female,43,2,116322.27,4,1,0,35640.12,1 +7459,15800049,Grigoryeva,728,Spain,Female,43,5,0,1,1,1,120088.17,0 +7460,15583724,Raymond,645,Spain,Female,29,4,0,2,1,1,74346.11,0 +7461,15622083,Paterson,647,Germany,Male,30,6,143138.91,2,1,0,2955.46,0 +7462,15645571,Genovese,596,Spain,Male,32,4,0,2,0,1,146504.35,0 +7463,15598266,Martin,610,France,Male,40,9,0,1,1,1,149602.54,0 +7464,15667934,Moretti,512,France,Male,36,0,129804.17,1,1,0,53020.9,0 +7465,15569682,Leckie,768,Germany,Male,37,9,108308.11,1,1,0,41788.25,1 +7466,15772941,Lane,666,Germany,Male,30,3,110153.27,1,0,1,74849.46,0 +7467,15586174,Brodney,700,Germany,Female,30,4,116377.48,1,1,1,134417.31,0 +7468,15803682,Angelo,651,Germany,Female,37,10,117791.06,2,1,1,75837.58,0 +7469,15627328,Millar,542,Spain,Female,26,2,0,2,1,1,54869.54,0 +7470,15717065,Balashov,686,France,Female,35,8,105419.73,1,1,0,35356.46,0 +7471,15602456,Afanasyev,850,Germany,Female,47,4,99219.47,2,1,1,122141.13,0 +7472,15721569,Chialuka,658,Germany,Female,55,8,119327.93,1,0,1,119439.66,0 +7473,15573798,Yermolayev,448,France,Female,36,6,83947.12,2,1,0,81999.53,0 +7474,15638272,Tien,609,Spain,Male,32,4,99883.16,1,1,1,120594.85,0 +7475,15799859,Lucchesi,704,France,Male,50,4,165438.26,1,1,0,120770.75,1 +7476,15599152,Lai,698,France,Male,31,1,156111.24,1,0,0,134790.74,0 +7477,15737909,Bates,759,France,Male,44,2,111095.58,2,1,0,100137.7,0 +7478,15646190,Saunders,677,France,Female,56,0,119963.45,1,0,0,158325.87,1 +7479,15711249,Chukwuemeka,544,Spain,Male,22,4,0,2,1,0,70007.67,0 +7480,15671987,Meagher,567,Spain,Male,35,8,153137.74,1,1,0,88659.07,0 +7481,15812766,Golubeva,490,Spain,Male,40,6,156111.08,1,0,0,190889.13,0 +7482,15778589,Collier,626,France,Male,34,7,113014.7,2,1,1,56646.28,0 +7483,15750104,Chan,718,Germany,Male,43,5,132615.73,2,1,0,32999.1,0 +7484,15784526,Chen,616,France,Male,44,5,102016.38,1,0,1,178235.37,1 +7485,15646563,Wright,772,France,Female,35,9,0,1,0,1,25448.31,0 +7486,15744423,Cocci,561,France,Male,32,5,0,2,1,0,84871.99,0 +7487,15593694,Williams,814,France,Male,49,8,0,2,0,0,157822.54,0 +7488,15785367,McGuffog,651,France,Female,56,4,0,1,0,0,84383.22,1 +7489,15687765,Chukwujamuike,538,Germany,Female,42,4,80380.24,1,1,0,119216.46,0 +7490,15789014,Scott,600,France,Female,26,6,108909.12,1,1,0,82547.01,0 +7491,15703177,Bell,654,France,Female,35,2,90865.8,1,1,1,86764.46,0 +7492,15660263,Olisaemeka,622,France,Male,40,4,99799.76,2,1,0,197372.13,0 +7493,15776545,Napolitani,682,France,Male,28,10,200724.96,1,0,1,82872.64,1 +7494,15683276,Sargood,610,Spain,Female,37,10,140363.95,2,1,1,129563.86,0 +7495,15599272,Harrington,795,France,Female,36,1,151844.64,1,1,1,135388.89,0 +7496,15589541,Sutherland,557,France,Female,27,2,0,2,0,1,4497.55,0 +7497,15608804,Allan,824,Germany,Male,49,8,133231.48,1,1,1,67885.37,0 +7498,15645820,Folliero,698,France,Male,27,7,0,2,1,0,111471.55,0 +7499,15659031,Mordvinova,630,France,Female,36,8,126598.99,2,1,1,134407.93,0 +7500,15790113,Schofield,609,Germany,Female,71,6,113317.1,1,1,0,108258.22,1 +7501,15652289,Williams,694,France,Male,47,4,0,2,1,0,197528.62,0 +7502,15605341,Baird,681,France,Female,58,8,93173.88,1,1,1,139761.25,0 +7503,15697844,Whitehouse,721,Spain,Female,32,10,0,1,1,0,136119.96,1 +7504,15652048,Thompson,563,Germany,Male,44,7,105007.31,2,1,1,197812.16,0 +7505,15587038,Ogochukwu,654,Spain,Female,32,2,0,1,1,1,51972.92,1 +7506,15660528,Niu,659,Spain,Male,27,4,0,2,1,0,99341.87,0 +7507,15700300,Okoli,674,Germany,Female,44,4,131593.85,1,0,1,171345.02,1 +7508,15642001,Lorenzen,576,Germany,Male,44,9,119530.52,1,1,0,119056.68,1 +7509,15580366,Okechukwu,566,Germany,Male,54,4,118614.6,2,1,1,172601.62,0 +7510,15657228,Anderson,545,Germany,Male,37,9,95829.13,2,0,1,104936.88,0 +7511,15729377,Ku,798,France,Male,36,1,0,2,1,1,159044.1,0 +7512,15686913,Kung,757,France,Male,38,0,0,1,1,0,83263.06,0 +7513,15631267,Lu,641,France,Male,50,6,153590.73,2,1,1,130910.78,0 +7514,15632275,Trevisano,718,France,Male,29,2,0,1,1,0,126336.72,0 +7515,15715907,Onwubiko,699,France,Male,64,9,113109.52,1,1,0,27980.8,1 +7516,15764841,Vidler,623,France,Female,35,0,130557.24,1,1,1,47880.71,0 +7517,15748649,Shen,644,France,Male,40,8,93183.19,1,1,0,73882.49,0 +7518,15771409,McGregor,586,France,Male,58,7,151933.63,1,1,0,162960.05,1 +7519,15779207,Nnamdi,500,Germany,Male,30,2,125495.64,2,1,1,68807.47,0 +7520,15814116,Castiglione,583,France,Female,42,7,0,2,1,0,144039.05,0 +7521,15665087,Bergamaschi,595,Germany,Female,26,8,118547.72,1,1,1,151192.18,0 +7522,15611189,Allingham,670,Spain,Male,43,1,97792.21,1,0,0,120225.62,0 +7523,15729718,Stelzer,610,France,Male,41,6,0,3,0,0,56118.81,1 +7524,15733602,Rubin,814,Spain,Female,72,2,0,2,0,1,130853.03,0 +7525,15620103,Ho,660,France,Female,40,8,167181.01,1,1,1,185156.94,0 +7526,15770406,Watson,580,Germany,Male,35,9,121355.19,1,0,1,35671.45,0 +7527,15800554,Perry,850,France,Female,81,1,0,2,1,1,59568.24,0 +7528,15611409,Sun,676,Spain,Male,35,0,0,2,0,0,139911.58,0 +7529,15646535,Harrell,578,France,Male,46,5,113226.47,1,1,0,56770.76,0 +7530,15575430,Robson,579,France,Female,33,1,118392.75,1,1,1,157564.75,0 +7531,15711299,Wilson,711,Germany,Female,52,8,145262.54,1,0,1,131473.31,0 +7532,15642063,Kelechi,692,France,Male,40,6,163505.16,1,0,0,90424.09,0 +7533,15706602,Bates,760,Spain,Female,33,1,118114.28,2,0,1,156660.21,0 +7534,15592773,Eberegbulam,630,Germany,Female,51,0,108449.23,3,0,0,88372.69,1 +7535,15786539,Olisaemeka,808,France,Male,32,1,0,2,1,1,46200.71,0 +7536,15737542,Davey,611,Germany,Female,36,10,103294.56,1,1,0,160548.12,0 +7537,15590234,De Luca,697,France,Female,42,1,0,1,1,0,1262.83,1 +7538,15773776,Ho,655,France,Female,38,6,0,1,1,1,188639.28,0 +7539,15728082,Vasiliev,601,Spain,Male,28,6,0,2,1,0,14665.28,0 +7540,15609987,Smith,755,France,Male,42,2,119919.12,1,1,0,156868.21,0 +7541,15735330,Sung,553,France,Male,37,1,0,1,1,0,30461.55,0 +7542,15649430,White,723,France,Male,28,4,0,2,1,1,123885.88,0 +7543,15768777,Wang,507,Spain,Female,34,4,0,2,1,1,60688.38,0 +7544,15777893,Davide,777,France,Male,43,1,0,2,1,0,21785.91,0 +7545,15791326,Nnamdi,566,France,Male,34,3,0,1,0,0,188135.69,0 +7546,15615176,Welsh,732,France,Male,26,7,0,2,1,0,154364.66,0 +7547,15735221,Sousa,697,France,Female,42,10,0,2,1,0,61312.15,0 +7548,15617991,Andrews,555,France,Male,29,4,128744.04,1,1,1,47454.93,0 +7549,15658504,Chiawuotu,584,Germany,Female,62,9,137727.34,2,0,1,121102.9,0 +7550,15785705,Thomson,705,Germany,Female,44,10,106731.58,1,1,0,137419.87,1 +7551,15801817,Carpenter,688,France,Female,38,7,123544.21,1,1,1,157664.02,0 +7552,15752578,Yefimova,626,France,Female,37,2,133968.96,2,1,0,148689.65,0 +7553,15781574,Ma,636,Spain,Male,76,9,126534.6,1,1,1,39789.62,0 +7554,15792107,Black,719,Spain,Female,35,8,0,1,1,1,165162.4,0 +7555,15569917,Obijiaku,706,Spain,Male,30,6,87609.68,2,0,0,137674.55,1 +7556,15721504,King,731,Spain,Male,41,3,0,2,1,0,101371.72,0 +7557,15757306,Miller,738,Spain,Male,49,3,0,3,1,1,65066.48,1 +7558,15647295,Chin,426,France,Male,34,9,0,2,1,0,107876.91,0 +7559,15642098,Cox,622,Spain,Female,36,0,108960,2,1,0,111180.3,1 +7560,15696120,Wallace,701,Spain,Female,30,2,0,2,1,0,115650.63,0 +7561,15675176,Price,512,France,Male,51,6,144953.31,1,1,1,165035.17,0 +7562,15700046,Yuan,635,France,Male,41,4,103544.88,2,1,0,193746.55,0 +7563,15782089,Mullen,685,France,Male,33,6,0,1,1,0,58458.26,0 +7564,15706394,Howell,609,France,Male,53,7,0,2,0,1,52332.85,0 +7565,15759387,McIntosh,598,Germany,Male,38,1,101487.18,1,1,1,75959.1,1 +7566,15623369,Clifton,708,France,Male,52,10,105355.81,1,1,0,123.07,1 +7567,15732943,Okwuoma,574,Spain,Male,36,4,77967.5,1,1,0,167066.95,1 +7568,15750545,Chidiebere,629,France,Male,44,5,0,4,0,0,117572.59,1 +7569,15809909,Fan,422,Spain,Female,54,4,0,2,1,1,7166.71,0 +7570,15642448,Onyemauchechukwu,656,Spain,Male,28,8,120047.77,1,1,1,137173.39,0 +7571,15791944,Harker,697,France,Male,32,7,175464.85,3,1,0,116442.42,1 +7572,15768342,Bolton,718,France,Male,52,8,79475.3,3,1,1,32421.32,1 +7573,15567919,Lazarev,586,Germany,Male,37,8,167735.69,2,0,1,104665.79,0 +7574,15674750,Alexeyeva,481,Spain,Female,37,8,0,2,1,0,44215.86,0 +7575,15778345,Stevens,749,France,Female,33,1,74385.98,1,1,0,20164.47,0 +7576,15687634,Glover,561,Germany,Male,49,5,94754,1,1,1,26691.31,0 +7577,15666096,Ibekwe,676,Spain,Male,27,4,0,1,0,1,107955.67,0 +7578,15581700,Paterson,615,Germany,Male,43,3,86920.86,1,1,1,150048.37,0 +7579,15656417,Marsh,582,France,Female,39,1,132077.48,2,1,0,192255.15,0 +7580,15649101,Reeves,601,France,Male,40,10,127847.86,1,0,0,173245.68,0 +7581,15781975,Rees,708,France,Male,34,3,0,1,0,1,121457.88,1 +7582,15700511,Hanson,708,Germany,Male,42,9,176702.36,2,1,1,104804.74,0 +7583,15770255,Onwughara,797,Germany,Female,33,10,83555.58,1,0,0,69767.14,0 +7584,15643574,Odinakachukwu,682,France,Male,26,8,0,2,1,0,178373.43,0 +7585,15595010,Huang,694,Spain,Female,39,9,0,2,0,0,99924.04,0 +7586,15580579,Trevisani,490,France,Female,40,1,0,1,1,1,49594.19,1 +7587,15748532,Dale,828,Spain,Male,42,10,0,1,1,1,186071.14,0 +7588,15773789,Pavlova,594,Spain,Female,38,7,96858.35,1,1,0,77511.45,0 +7589,15600027,Meng,579,Spain,Male,33,1,0,2,1,1,54816.57,0 +7590,15620832,Dean,723,France,Female,35,0,0,2,0,1,61290.99,0 +7591,15568819,Chiganu,619,Germany,Female,42,8,132796.04,3,1,1,191821.35,1 +7592,15748691,Lung,794,Spain,Female,30,1,154970.54,1,0,1,156768.45,0 +7593,15583552,Donaldson,674,Germany,Male,44,3,88902.21,1,1,0,73731.32,0 +7594,15588019,Li Fonti,418,France,Male,28,7,98738.92,1,1,0,122190.22,0 +7595,15713250,Izmailova,502,France,Male,33,8,0,2,1,1,123509.01,0 +7596,15569595,Walker,678,France,Female,50,6,0,1,1,0,8199.5,0 +7597,15794868,Nnonso,599,Germany,Male,40,10,137456.28,2,1,1,14113.11,0 +7598,15576680,Stevenson,736,France,Male,29,4,0,2,0,0,51705.01,0 +7599,15613699,Schnaars,430,France,Female,60,7,73937.02,1,1,0,161937.62,1 +7600,15609758,Geoghegan,537,France,Female,45,7,158621.04,1,1,0,120892.96,1 +7601,15762392,Ilyina,683,Spain,Male,30,1,113257.2,1,1,1,65035.02,0 +7602,15693382,Muir,828,France,Male,31,9,0,1,0,1,164257.37,0 +7603,15791769,Gardener,691,France,Female,29,9,116536.43,1,1,0,51987.99,0 +7604,15712483,Chidi,608,Spain,Female,28,4,0,2,1,0,10899.63,1 +7605,15636454,Fu,691,France,Female,60,6,101070.69,1,1,0,177355.8,1 +7606,15710138,Sun,718,Spain,Male,39,6,0,2,0,1,63889.1,0 +7607,15571571,Ting,680,Germany,Female,31,3,127331.46,3,1,1,176433.6,0 +7608,15638751,Ashton,838,Spain,Female,41,5,0,2,1,0,81313.51,0 +7609,15598574,Uwakwe,695,Spain,Female,31,5,0,2,0,1,13998.88,0 +7610,15796787,Vassiliev,681,France,Male,46,0,105969.42,1,1,0,5771.56,0 +7611,15615670,Kazakova,762,France,Male,36,5,119547.46,1,1,1,42693.65,0 +7612,15705506,Perry,751,Spain,Male,38,7,0,2,0,0,90839.61,0 +7613,15599535,Howell,678,Spain,Male,28,5,138668.18,1,1,1,54144.01,0 +7614,15768449,Ricci,634,France,Female,37,7,51582.5,2,1,1,184312.88,0 +7615,15725002,Smith,749,France,Male,37,7,0,2,1,0,20306.79,0 +7616,15611682,Rossi,590,Spain,Male,37,6,169902.92,1,1,1,128256.18,0 +7617,15749964,Jones,610,France,Female,27,4,87262.4,2,1,0,182720.07,0 +7618,15678779,Quezada,502,France,Male,33,7,0,2,0,1,4082.52,0 +7619,15752601,McCulloch,578,France,Female,40,7,0,2,0,0,102233.73,0 +7620,15758477,Tobeolisa,547,France,Female,32,2,0,2,1,0,132002.83,0 +7621,15629133,Black,579,France,Female,27,9,0,2,1,0,126838.7,0 +7622,15604963,Fraser,661,France,Male,39,5,0,2,0,0,181461.46,0 +7623,15796413,Green,794,France,Male,46,6,0,2,1,0,195325.74,0 +7624,15812470,Allan,719,France,Male,61,5,0,2,0,1,29132.43,0 +7625,15587443,Akudinobi,728,France,Female,69,1,0,2,1,1,131804.86,0 +7626,15689692,Walker,598,Germany,Male,19,3,150348.37,1,1,1,173784.04,0 +7627,15779586,Olisaemeka,822,Germany,Female,46,3,115074.02,2,1,0,26249.86,0 +7628,15667588,Arcuri,670,Spain,Female,40,3,0,1,1,1,182650.15,0 +7629,15624423,Liu,850,France,Male,28,8,99986.98,1,1,0,196582.55,0 +7630,15591107,Flemming,723,Germany,Female,68,3,110357,1,0,0,141977.54,1 +7631,15748986,Bischof,705,Germany,Male,42,8,166685.92,2,1,1,55313.51,0 +7632,15793896,John,677,Spain,Male,40,7,95312.8,1,1,1,62944.75,0 +7633,15620570,Sinnett,736,France,Male,43,4,202443.47,1,1,0,72375.03,0 +7634,15727811,Ts'ui,661,Germany,Female,47,0,109493.62,1,0,0,188324.01,1 +7635,15707681,Pokrovsky,501,Germany,Male,38,9,88977.39,2,0,1,133403.07,0 +7636,15702030,Azarov,516,France,Female,29,2,104982.57,1,1,0,157378.5,0 +7637,15673238,McCarthy,517,Germany,Female,59,8,154110.99,2,1,0,101240.08,1 +7638,15604196,Simpson,766,France,Male,32,6,185714.28,1,1,1,102502.5,0 +7639,15769356,Stevenson,520,Germany,Female,23,3,116022.53,2,1,1,37577.66,0 +7640,15665590,Moore,541,France,Male,46,6,0,2,1,1,83456.67,0 +7641,15572361,Chill,790,Germany,Female,34,2,164011.48,1,1,0,199420.41,0 +7642,15667460,Moore,797,France,Male,31,9,0,2,1,1,24748.89,0 +7643,15654760,Su,811,France,Male,40,1,101514.89,1,1,1,121765,0 +7644,15632669,Rees,722,Spain,Female,32,4,0,2,1,1,113666.48,0 +7645,15613673,Lung,675,France,Male,28,9,0,1,1,0,134110.93,0 +7646,15698522,Thomas,660,Germany,Male,39,9,134599.33,2,1,0,183095.87,0 +7647,15741633,Fuller,566,Spain,Male,32,10,147511.26,1,1,1,159891.03,0 +7648,15674583,Trevisani,768,France,Male,25,0,78396.08,1,1,1,8316.19,0 +7649,15665374,Dumolo,610,Spain,Female,31,5,0,2,0,0,63736.36,0 +7650,15588854,Wu,715,France,Female,31,3,110581.29,1,1,1,94715.24,0 +7651,15810716,Kerr,750,Germany,Male,42,8,151836.36,2,1,0,68695.38,0 +7652,15776921,Geoghegan,431,Germany,Male,45,5,83624.55,2,0,0,36899.62,0 +7653,15569394,Bailey,704,France,Male,24,2,148197.15,2,1,0,182775.08,0 +7654,15788215,Hsia,535,Spain,Female,30,5,122924.75,1,0,0,62390.59,1 +7655,15641007,Holden,614,France,Female,38,4,72594,1,1,1,76042.48,0 +7656,15594651,Milani,748,France,Male,38,4,115221.36,1,0,1,70956.75,0 +7657,15575146,Jamieson,492,Germany,Male,51,8,117808.74,2,1,1,67311.12,0 +7658,15608916,Ndubueze,573,France,Male,40,7,147754.68,1,1,1,110454.46,0 +7659,15666297,Abramova,706,Spain,Female,53,3,0,3,0,0,88479.02,1 +7660,15598586,Wetherspoon,680,France,Male,31,10,113292.17,1,1,1,122639.73,0 +7661,15665014,Middleton,458,Spain,Male,36,5,0,2,1,0,79723.78,0 +7662,15701738,Arcuri,612,Germany,Male,44,2,115163.38,1,1,1,97677.52,1 +7663,15650591,Calabrese,809,Germany,Male,50,10,118098.62,1,1,1,100720.02,1 +7664,15652667,Hampton,590,France,Male,39,9,0,2,1,1,104730.52,0 +7665,15679622,Clayton,602,France,Male,35,8,0,1,1,1,22499.29,0 +7666,15730150,Otutodilichukwu,540,Spain,Male,37,0,120825.7,1,1,0,28257.89,0 +7667,15813192,Chukwuemeka,494,France,Male,25,6,0,2,0,1,109988.09,0 +7668,15606554,Douglas,797,France,Male,29,1,0,1,0,1,149991.32,0 +7669,15611794,Galloway,526,Germany,Male,61,6,133845.28,2,1,1,45180.8,0 +7670,15672357,Sochima,631,Spain,Male,38,7,0,2,1,0,181605.85,0 +7671,15711759,Wilkins,576,France,Female,29,5,108541.04,1,1,1,126469.09,0 +7672,15615296,Rice,405,France,Male,39,10,0,1,1,0,160810.85,1 +7673,15699294,Pope,555,France,Male,30,1,0,2,0,0,88146.86,0 +7674,15788634,Romani,750,Spain,Female,37,2,113817.06,1,0,0,88333.74,0 +7675,15660871,Ch'ang,665,France,Male,28,8,137300.23,1,1,0,90174.83,0 +7676,15618258,Chizuoke,640,Spain,Male,37,5,158024.38,1,1,0,81298.09,0 +7677,15722535,Ireland,457,France,Female,33,7,127837.54,1,0,1,60013.17,0 +7678,15711977,Finch,695,France,Male,36,4,161533,1,1,0,100940.91,0 +7679,15690169,Meng,645,France,Male,31,7,161171.7,2,1,0,12599.94,1 +7680,15790689,Hibbins,647,Spain,Male,32,9,80958.36,1,1,1,128590.73,0 +7681,15665181,Chung,808,Spain,Male,25,7,0,2,0,1,23180.37,0 +7682,15633608,Black,641,France,Male,33,2,146193.6,2,1,1,55796.83,1 +7683,15805261,Balashov,700,Spain,Male,29,8,0,2,0,1,152097.02,0 +7684,15740356,Palmer,660,Germany,Male,26,4,115021.76,1,0,1,162443.05,0 +7685,15808223,Lea,615,Spain,Male,41,1,126773.43,1,1,1,55551.26,0 +7686,15769980,Singleton,705,Germany,Female,40,3,92889.91,1,1,1,109496.69,0 +7687,15675450,Burt,718,France,Male,48,9,0,2,1,1,72105.63,0 +7688,15776494,Siciliano,754,France,Male,61,5,146622.35,1,1,1,41815.22,1 +7689,15592412,Sun,713,Germany,Male,45,4,131038.14,1,1,0,74005.04,1 +7690,15777452,Sauve,587,France,Female,46,6,88820.29,1,0,0,70224.34,0 +7691,15692258,Thompson,569,Spain,Male,31,1,115406.97,1,0,0,145528.22,0 +7692,15791045,Boni,568,France,Female,38,3,132951.92,1,0,1,124486.28,0 +7693,15807889,Wood,634,Germany,Male,74,5,108891.7,1,1,0,10078.02,0 +7694,15602043,Buccho,770,Germany,Female,46,5,141788.63,2,0,0,164967.21,0 +7695,15807335,Spencer,676,Spain,Female,64,4,116954.32,1,1,1,91149.48,0 +7696,15629985,Eidson,723,Germany,Female,47,10,90450,2,0,0,103379.31,1 +7697,15679453,Hung,614,Germany,Female,39,8,125997.22,1,1,1,128049.34,1 +7698,15637315,Melvin,601,Spain,Female,41,3,0,2,1,0,54342.83,0 +7699,15691513,Dawkins,592,France,Male,60,9,0,4,1,1,13614.01,1 +7700,15622289,Rizzo,605,Spain,Female,36,9,0,2,0,1,35521.63,0 +7701,15715184,Capon,752,Spain,Female,31,4,144637.86,2,1,0,40496.72,0 +7702,15702801,Ts'ao,677,France,Female,29,3,86616.35,1,0,0,91903.9,1 +7703,15719931,Johnstone,850,France,Male,31,8,0,2,1,0,178667.7,0 +7704,15806081,Fleming,608,Germany,Female,48,2,127924.25,2,1,0,32202.61,0 +7705,15796336,Chang,786,Spain,Female,34,9,0,2,1,0,117034.32,0 +7706,15647306,Gibbs,777,France,Female,29,9,131240.61,1,1,1,163746.09,1 +7707,15742369,Rita,667,Spain,Male,31,5,0,2,1,1,20346.69,0 +7708,15655859,Munro,848,Spain,Male,35,5,120046.74,2,1,0,84710.65,0 +7709,15675650,Duncan,486,France,Female,39,8,97819.36,1,0,1,120531.31,0 +7710,15574119,Okwuadigbo,598,Spain,Female,64,1,62979.93,1,1,1,152273.57,0 +7711,15754168,McIntosh,506,France,Female,40,3,0,1,1,1,144345.58,0 +7712,15763029,Ch'iu,612,Germany,Male,46,9,161450.03,1,1,1,96961,1 +7713,15765048,Watt,545,France,Male,30,3,0,2,1,0,170307.43,0 +7714,15786215,Udinese,793,France,Male,56,8,119496.25,2,1,0,29880.99,0 +7715,15707559,Clark,682,France,Female,30,9,0,2,1,1,195104.91,0 +7716,15582129,Hsia,517,France,Male,62,1,43772.66,3,1,0,187756.24,1 +7717,15687540,Obiuto,684,France,Male,32,9,100249.41,2,0,1,67599.69,0 +7718,15787196,T'ien,692,Spain,Male,46,2,0,2,1,1,105983.09,0 +7719,15670898,McKenzie,740,France,Female,60,5,108028.08,2,0,0,25980.42,1 +7720,15775433,Tang,666,Germany,Male,71,1,53013.29,2,1,1,112222.64,0 +7721,15700693,Tu,693,France,Male,68,2,0,2,1,1,59864.96,0 +7722,15677955,Tsui,757,Germany,Male,33,1,122088.67,1,1,0,42581.09,0 +7723,15570086,Lynch,684,Germany,Male,18,9,90544,1,0,1,4777.23,0 +7724,15794875,Hung,691,Spain,Male,35,6,0,2,0,1,178038.17,0 +7725,15673591,Oluchukwu,842,France,Male,44,3,141252.18,4,0,1,128521.16,1 +7726,15631756,Tuan,482,France,Female,35,5,147813.05,2,0,0,109029.72,0 +7727,15757617,Lewis,735,France,Male,55,6,134140.68,1,1,0,2267.88,0 +7728,15612729,Chidiebere,681,France,Female,63,7,0,2,1,1,55054.48,0 +7729,15637857,Woolacott,616,France,Female,31,8,0,1,0,1,76456.17,0 +7730,15681007,Yen,850,France,Female,35,2,128548.49,4,1,0,75478.95,1 +7731,15593622,Service,635,France,Male,43,10,122198.21,2,0,1,179144.54,0 +7732,15629273,Lin,638,Germany,Male,42,8,145177.84,1,1,0,193471.74,1 +7733,15765846,Chuang,820,Spain,Female,31,2,94222.53,1,1,0,103570.8,0 +7734,15596013,Akhtar,694,Germany,Female,58,1,143212.22,1,0,0,102628.56,1 +7735,15722473,Faulkner,713,France,Male,41,3,0,2,1,0,55772.04,0 +7736,15774936,Liang,543,Germany,Male,41,6,143350.41,1,1,1,192070.16,1 +7737,15685640,Dancy,649,France,Female,41,3,130931.83,1,1,1,144808.37,0 +7738,15566563,Duigan,777,France,Female,30,4,137851.31,1,1,0,5008.23,1 +7739,15768746,McLean,561,France,Male,33,6,0,2,0,0,173680.39,0 +7740,15689952,Zuyeva,724,Spain,Male,41,5,0,1,0,1,115753.94,0 +7741,15725906,Hankinson,665,Spain,Female,51,8,0,1,1,1,38928.48,1 +7742,15634501,Wei,441,France,Male,60,1,140614.15,1,0,1,174381.23,0 +7743,15571940,Afamefula,579,Spain,Male,22,3,118680.57,1,1,1,49829.8,0 +7744,15741643,Chiang,777,Germany,Male,35,7,122917.69,1,1,1,76169.68,0 +7745,15806822,Myers,739,France,Female,36,0,0,2,0,0,133465.57,0 +7746,15701166,Chinedum,660,France,Male,40,5,131754.11,2,1,1,38761.61,0 +7747,15718531,Ukaegbunam,554,France,Female,35,8,0,2,1,1,176779.46,0 +7748,15628308,Akubundu,850,France,Female,24,6,0,2,1,1,13159.9,0 +7749,15585287,Sal,842,Germany,Female,35,9,119948.09,1,1,0,48217.97,1 +7750,15781619,Stevenson,785,France,Female,38,1,0,1,1,0,134964.85,1 +7751,15805162,Sutherland,550,France,Male,25,0,0,2,1,1,184221.11,0 +7752,15588535,Ts'ao,750,Spain,Female,39,6,0,2,0,0,19264.33,0 +7753,15775307,Sung,490,Spain,Female,38,3,97266.1,1,1,1,92797.23,0 +7754,15777616,Pisani,605,Germany,Male,28,10,113690.83,1,1,0,33114.24,0 +7755,15692291,Hs?eh,563,Spain,Female,42,6,99056.22,2,1,0,154347.95,1 +7756,15680843,Sherrod,675,France,Male,34,8,0,2,1,1,184842.21,0 +7757,15606232,Holloway,621,Spain,Female,36,7,116338.68,1,1,1,155743.48,0 +7758,15641585,Newton,850,France,Male,40,6,97339.99,1,0,1,88815.25,0 +7759,15684358,Kang,711,France,Male,41,3,0,2,1,1,193747.57,0 +7760,15806389,Walton,549,Germany,Female,55,1,137592.31,2,0,1,116548.02,1 +7761,15641860,Bradley,764,Germany,Male,34,6,108760.27,2,1,0,166324.79,1 +7762,15814237,Watkins,627,Germany,Male,30,3,128770.88,2,1,1,40199.01,0 +7763,15808780,Tien,850,France,Female,34,2,0,2,0,0,51919.04,0 +7764,15767064,Davide,614,Spain,Female,36,1,44054.84,1,1,1,73329.08,0 +7765,15751177,Milne,685,Germany,Female,44,2,119657.53,1,1,0,145387.05,1 +7766,15613427,Barling,683,Germany,Female,49,7,108797.63,2,0,0,140763.18,0 +7767,15647259,Barnett,643,Spain,Male,35,2,0,2,0,0,67979.35,0 +7768,15748660,Ellis,561,Germany,Female,49,1,102025.32,1,1,0,133051.64,1 +7769,15726695,Hsia,601,Spain,Female,20,9,122446.61,2,1,0,86791.9,0 +7770,15757473,Chukwujamuike,766,France,Female,27,7,158786.67,2,0,1,47579.25,0 +7771,15809509,Venables,699,France,Male,29,3,125689.29,1,1,1,151623.71,0 +7772,15715512,Hsia,850,Germany,Male,29,1,154640.41,1,1,1,164039.51,0 +7773,15614168,Alexander,792,Germany,Female,50,4,146710.76,1,1,0,16528.4,1 +7774,15679818,Yuan,636,Germany,Male,67,7,136709.35,1,0,1,66753.1,1 +7775,15609928,Johnston,850,Germany,Male,43,5,129305.09,2,0,1,19244.58,0 +7776,15731246,Hobler,628,Spain,Male,40,10,0,2,1,0,103832.58,0 +7777,15685243,Jamieson,736,France,Female,63,10,0,2,0,1,502.7,0 +7778,15638730,Macleod,711,France,Female,21,0,82844.33,2,0,1,1408.68,0 +7779,15697034,Norris,583,Spain,Female,22,2,0,2,0,1,5985.36,0 +7780,15699225,Pirozzi,757,France,Male,46,0,0,2,1,0,37460.05,0 +7781,15677387,Folliero,749,Germany,Female,33,10,76692.22,1,0,1,30396.43,0 +7782,15759184,Russell,705,France,Male,34,7,117715.84,1,1,0,2498.67,0 +7783,15595991,Hsiung,585,France,Male,54,8,87105.32,1,1,1,55346.14,0 +7784,15681332,Tate,437,France,Female,43,6,0,1,1,0,148330.97,1 +7785,15756299,Davis,741,France,Female,64,2,69311.16,1,1,1,59237.72,0 +7786,15750547,Bair,738,France,Male,26,9,0,2,1,1,48644.94,0 +7787,15566380,Drury,586,Spain,Female,33,10,66948.67,2,1,1,140759.03,0 +7788,15675963,Padovano,627,France,Female,57,9,0,2,1,1,107712.42,0 +7789,15674671,Conway,551,Spain,Male,76,2,128410.71,2,1,1,181718.73,0 +7790,15621466,Waters,606,Germany,Male,38,3,99897.53,1,0,0,37054.65,0 +7791,15607176,Kang,674,France,Male,22,3,0,1,1,1,173940.59,0 +7792,15570299,Martin,584,Germany,Female,31,6,152622.34,1,1,0,99298.8,0 +7793,15613197,Ugochukwutubelum,590,France,Male,40,8,0,2,1,0,62933.03,0 +7794,15798885,Burns,585,France,Male,56,4,138227.19,2,1,1,55287.84,0 +7795,15714883,Genovese,508,France,Female,25,2,111395.53,1,0,1,48197.06,0 +7796,15604497,Beale,458,Germany,Male,44,7,84386.57,1,1,0,178642.73,0 +7797,15773949,Cherkasova,692,France,Female,36,3,0,2,1,1,8282.22,0 +7798,15774164,Coles,502,Germany,Male,33,5,174673.65,2,1,0,33300.56,0 +7799,15774127,Potter,518,France,Male,46,3,0,2,1,0,76515.79,0 +7800,15619016,McMinn,660,Germany,Male,46,5,109019.65,2,1,1,33680.56,0 +7801,15795759,Bergamaschi,698,Germany,Female,52,1,107906.75,1,1,0,168886.39,1 +7802,15798844,Chijindum,678,France,Male,54,7,128914.97,1,0,0,191746.23,1 +7803,15717962,Ch'iu,773,Spain,Male,63,9,111179.83,1,1,1,93091.02,0 +7804,15691504,Yusupova,619,Germany,Female,52,8,124099.13,1,0,0,23904.52,0 +7805,15693893,Davis,684,Germany,Male,59,9,122471.09,1,0,1,15807.07,0 +7806,15672499,Iadanza,635,France,Male,34,3,134692.4,2,1,1,83773.02,0 +7807,15750410,Jordan,680,France,Female,25,4,123816.5,1,1,1,90162.35,0 +7808,15568904,Kruglova,608,Germany,Male,34,3,106288.54,1,1,1,36639.25,0 +7809,15649033,Echezonachukwu,603,Germany,Female,55,7,127723.25,2,1,0,139469.11,1 +7810,15780989,Hajek,579,Spain,Male,43,2,145843.82,1,1,1,198402.37,1 +7811,15771059,Welch,756,Germany,Female,34,2,148200.72,1,0,0,194584.48,0 +7812,15687852,Vinogradoff,611,France,Male,30,2,104145.65,1,0,0,159629.64,0 +7813,15695280,Hung,532,Germany,Male,24,8,142755.25,1,0,0,34231.48,0 +7814,15592751,Okwudiliolisa,684,Germany,Female,63,3,81245.79,1,1,0,69643.31,1 +7815,15598338,Mays,647,Germany,Female,33,3,168560.46,2,0,0,90270.16,0 +7816,15735784,Gardner,583,France,Male,38,8,0,1,1,0,47848.56,0 +7817,15629128,Mamelu,774,Germany,Male,42,2,132193.94,2,1,1,162865.52,0 +7818,15642870,Ross,677,France,Male,58,9,0,1,0,1,168650.4,0 +7819,15637977,Barese,542,Germany,Male,25,8,139330.1,1,0,0,54372.37,0 +7820,15600792,Swayne,613,Spain,Male,29,0,0,2,0,1,133897.32,0 +7821,15576131,Phillips,666,France,Male,40,5,0,2,1,0,147878.05,0 +7822,15686588,Manfrin,777,France,Female,28,2,134571.5,1,0,1,118313.38,0 +7823,15761018,Tan,581,Germany,Male,50,2,143829.2,2,1,0,181224.24,1 +7824,15616029,Adams,705,France,Male,32,7,0,2,1,0,7921.57,0 +7825,15761149,Teng,673,France,Female,44,8,133444.97,1,0,1,5708.19,0 +7826,15802758,Chinwendu,594,Germany,Female,23,4,104753.84,2,1,0,56756.52,1 +7827,15647838,Davison,648,Germany,Female,51,2,116574.84,1,1,0,4121.04,1 +7828,15735968,Hsing,605,France,Male,41,10,0,2,0,1,97213.09,0 +7829,15581286,Castro,734,France,Female,40,9,176914.8,1,1,1,12799.23,0 +7830,15625445,Parkin,572,France,Female,36,8,68348.18,2,0,1,50400.32,0 +7831,15600173,Manna,595,France,Female,33,9,0,2,1,1,41447.86,0 +7832,15635143,Fennescey,749,France,Male,42,2,56726.83,2,0,1,185543.35,0 +7833,15664849,Colon,573,Spain,Male,46,3,65269.23,1,0,1,189988.65,1 +7834,15762455,Yeh,624,Spain,Male,33,6,66220.17,1,0,1,170819.01,0 +7835,15797165,Bergamaschi,703,France,Male,56,9,0,1,0,0,85547.33,1 +7836,15788189,Matveyeva,665,France,Female,41,8,96147.55,1,1,0,137037.97,0 +7837,15780492,Ignatyeva,648,France,Male,42,4,0,2,1,0,19283.14,0 +7838,15678497,Lederer,850,Spain,Male,48,2,0,1,1,0,169425.3,1 +7839,15588560,Nwabugwu,569,Germany,Female,32,8,145330.43,1,1,1,132038.65,0 +7840,15606003,Abramowitz,566,France,Female,21,3,0,2,1,1,3626.47,0 +7841,15611756,Chapman,537,Germany,Female,47,4,124192.28,2,1,1,50881.51,0 +7842,15789563,Fiorentino,706,Germany,Female,46,7,111288.18,1,1,1,149170.25,1 +7843,15702416,Cecil,734,France,Male,43,7,107805.67,1,0,0,182505.68,0 +7844,15766288,Ikechukwu,586,Germany,Female,36,5,103700.69,1,1,0,194072.56,1 +7845,15667633,Allen,612,France,Female,38,1,0,2,1,1,9209.21,0 +7846,15622774,Kao,648,France,Male,34,0,0,1,1,1,167931.81,0 +7847,15755416,Hart,557,France,Female,27,3,87739.08,1,1,1,123096.56,0 +7848,15769915,Charlton,643,Spain,Female,20,0,133313.34,1,1,1,3965.69,0 +7849,15643908,Turnbull,433,France,Female,49,10,0,1,1,1,87711.61,0 +7850,15627395,Manners,643,Germany,Male,41,7,154902.66,1,1,1,49667.28,0 +7851,15679663,Chiazagomekpere,488,France,Female,36,0,0,2,1,0,136675.22,0 +7852,15651581,Lavrentyev,758,Germany,Male,68,6,112595.85,1,1,0,35865.44,1 +7853,15596379,Wallace,743,Germany,Male,39,3,119695.75,1,0,1,26136.13,0 +7854,15746674,Miller,730,France,Female,47,7,0,1,1,0,33373.26,1 +7855,15801256,Bazhenov,746,Spain,Male,49,7,0,2,0,1,10096.25,0 +7856,15663808,Ifesinachi,666,Germany,Female,59,8,152614.51,2,1,1,188782.3,0 +7857,15598521,Ma,580,Germany,Female,33,7,131647.01,2,0,0,79775.19,0 +7858,15621457,Chu,850,France,Male,27,6,96654.72,2,0,0,152740.16,0 +7859,15764726,Kerr,563,France,Male,22,3,137583.04,1,0,1,5791.85,0 +7860,15646374,Wynne,766,Germany,Female,28,3,62717.84,2,1,1,13182.43,0 +7861,15716501,Moon,659,France,Male,32,9,95377.13,1,0,1,187551.24,0 +7862,15589948,Disher,607,Spain,Male,28,1,135936.1,2,1,1,110560.14,0 +7863,15811343,Cattaneo,644,Germany,Male,35,5,161591.11,3,1,1,63795.62,0 +7864,15659677,Beluchi,746,France,Male,47,8,142382.03,1,1,1,62086.62,0 +7865,15594436,Mazzi,588,Spain,Male,33,2,0,2,1,1,12483.56,0 +7866,15748995,Ifeajuna,691,Spain,Male,30,9,0,2,0,1,10963.04,0 +7867,15677062,Howe,666,France,Female,38,6,127043.09,1,1,1,8247,0 +7868,15697201,Yocum,640,Spain,Female,46,3,0,1,1,1,156260.08,0 +7869,15666453,Moore,611,Germany,Female,29,4,78885.88,2,1,1,26927.69,0 +7870,15693771,Y?an,651,Spain,Female,45,8,95922.9,1,1,0,84782.42,1 +7871,15569867,Chinweuba,529,France,Female,29,8,0,2,1,0,19842.11,0 +7872,15711602,Lowrie,676,France,Female,36,3,91711.59,1,1,1,95393.43,0 +7873,15717736,Shen,639,Germany,Female,46,10,110031.09,2,1,1,133995.59,0 +7874,15750441,Lavarack,782,France,Male,36,5,81210.72,2,0,1,108003.38,0 +7875,15732791,Davide,641,Germany,Male,32,5,122947.92,1,1,1,99154.86,0 +7876,15775104,Gomes,697,France,Female,38,1,182065.85,1,1,0,49503.5,0 +7877,15757607,Matveyeva,623,France,Male,45,0,0,1,1,0,196533.72,1 +7878,15793070,Fiorentino,494,Spain,Female,41,2,69974.66,2,1,0,188426.13,1 +7879,15760456,Eberechukwu,731,France,Female,38,10,123711.73,2,1,0,171340.68,1 +7880,15665385,Gibney,657,France,Male,44,6,76495.04,1,1,0,79071.89,0 +7881,15612418,Virgo,744,France,Female,38,9,0,2,0,0,20940.76,0 +7882,15727138,Kulikova,774,Spain,Male,46,9,0,2,1,1,34774.26,0 +7883,15732061,Liu,850,Germany,Female,45,1,121874.89,1,0,0,6865.41,1 +7884,15776051,Kao,551,France,Female,45,6,0,2,1,1,51143.43,0 +7885,15616530,Foran,638,France,Male,36,6,188455.19,1,0,0,47031.4,1 +7886,15632344,Jones,792,France,Female,42,0,99045.93,2,1,0,47160.01,0 +7887,15744979,Fowler,666,France,Female,36,8,0,1,0,1,158666.99,0 +7888,15745433,Conti,716,Germany,Female,30,2,205770.78,2,0,0,65464.66,0 +7889,15683657,Stephenson,594,France,Female,31,0,79340.95,1,1,0,78255.86,0 +7890,15718572,Willis,600,Germany,Male,57,9,138456.03,2,1,1,103548.25,0 +7891,15665783,Ts'ui,565,France,Male,49,7,0,2,1,1,89609.26,0 +7892,15652782,Chibuzo,678,Germany,Male,48,2,101099.9,2,0,1,193476.04,0 +7893,15707025,Fang,648,Spain,Female,31,5,0,2,1,1,5199.02,0 +7894,15647807,Wyckoff,642,France,Male,40,8,109219.83,1,1,0,52827.51,0 +7895,15718281,Muir,706,Germany,Male,67,1,123276.69,2,1,1,86507.88,1 +7896,15660571,Halpern,668,Spain,Male,43,10,113034.31,1,1,1,100423.88,0 +7897,15727857,Flynn,635,Spain,Male,41,1,0,2,1,0,175611.5,0 +7898,15639252,Shao,603,Spain,Male,30,6,129548.5,2,1,1,19282.85,0 +7899,15628144,Soares,635,France,Female,72,4,74812.84,1,0,1,27448.33,0 +7900,15683560,Gallo,642,France,Female,40,7,0,2,1,0,183963.34,0 +7901,15653275,Lei,785,Spain,Female,54,1,0,2,1,0,45113.92,1 +7902,15622182,Daniels,628,Germany,Female,28,3,153538.13,2,1,0,110776.01,0 +7903,15613962,Kenechi,499,France,Female,38,9,0,2,0,1,183042.2,0 +7904,15618437,Singleton,567,Spain,Male,34,10,0,2,0,1,161571.79,0 +7905,15783338,Williams,449,Spain,Male,32,0,155619.36,1,1,1,166692.03,0 +7906,15764491,Greece,701,Spain,Male,35,10,159693.9,2,1,1,71173.64,0 +7907,15712960,Olisanugo,613,Spain,Male,37,3,171653.17,1,0,1,5353.12,0 +7908,15688157,Padovano,683,Germany,Female,39,2,47685.47,2,1,1,86019.48,0 +7909,15579287,Rossi,581,France,Male,35,4,0,2,0,1,86383.82,0 +7910,15570931,Grant,620,France,Male,61,5,0,1,0,0,31641.52,1 +7911,15615177,Ebelegbulam,561,Spain,Male,28,6,123692,1,1,1,70548.96,0 +7912,15809906,Mitchell,558,Germany,Male,26,1,148853.29,2,1,1,24411.02,0 +7913,15652169,Buckley,642,France,Male,35,2,133161.95,1,0,1,122254.86,0 +7914,15649450,Repina,805,Germany,Male,24,6,143221.35,2,1,0,186035.72,0 +7915,15777179,Ellis,687,France,Male,35,9,0,2,0,1,73133.82,0 +7916,15803538,Douglas,695,Spain,Male,56,1,0,3,1,0,187734.49,1 +7917,15610936,Becher,562,France,Male,33,6,0,2,1,0,111590.35,0 +7918,15590094,Nwachukwu,613,Germany,Male,38,9,126265.88,2,0,0,15859.95,0 +7919,15572706,Smith,589,France,Male,37,5,0,1,1,0,61324.87,0 +7920,15634564,Aksyonov,593,Spain,Male,31,8,112713.34,1,1,1,176868.89,0 +7921,15684296,Artyomova,714,France,Male,34,5,141173.03,1,0,1,98896.06,0 +7922,15702293,Medvedeva,588,Spain,Female,35,7,0,2,1,1,108739.15,0 +7923,15642099,Tsui,679,Spain,Male,39,6,0,2,1,0,12266.06,0 +7924,15773273,Runyon,730,Spain,Male,38,5,118866.36,1,1,1,163317.5,0 +7925,15613337,Gallo,833,France,Male,47,2,0,2,1,1,182247.77,0 +7926,15800482,Bradshaw,586,Spain,Female,33,7,0,2,1,1,168261.4,0 +7927,15732644,Evans,567,Spain,Female,54,5,92316.31,2,1,0,158590.66,1 +7928,15713426,Hancock,637,Germany,Male,30,1,122185.53,1,1,0,102566.46,1 +7929,15640789,Butler,711,France,Male,38,4,123345.85,1,1,0,141827.83,0 +7930,15598892,Bradshaw,828,France,Male,30,4,73070.18,2,0,0,161671.15,0 +7931,15606436,Bergamaschi,500,Spain,Male,38,7,0,2,0,0,192013.23,0 +7932,15751227,Ebelegbulam,807,France,Male,47,1,95120.59,1,0,0,127875.1,0 +7933,15812365,Greco,850,France,Male,40,8,102800.65,1,1,0,60811.56,0 +7934,15616088,Lucas,782,France,Female,70,7,97072.42,1,0,1,131177.22,0 +7935,15803886,Barber,629,Spain,Male,31,6,132876.55,1,1,1,130862.11,0 +7936,15587311,Dobbs,582,Spain,Male,33,6,0,2,0,1,72970.93,0 +7937,15617401,Thomson,468,France,Male,22,2,0,2,1,0,28123.99,0 +7938,15775886,Su,670,France,Male,36,3,0,1,1,0,140754.19,1 +7939,15807305,Watkins,805,France,Male,39,2,0,1,0,0,166650.32,0 +7940,15761717,Ch'ien,720,France,Male,26,10,51962.91,2,1,0,45507.24,0 +7941,15628008,Monds,781,Spain,Female,29,6,98759.89,1,0,0,112202.64,0 +7942,15583755,McClemans,592,Germany,Male,33,2,156570.86,1,1,1,37140.2,0 +7943,15661409,Shen,542,France,Female,42,1,0,1,1,1,178256.58,1 +7944,15774250,Gallo,532,France,Male,42,1,159024.71,1,1,0,100982.93,1 +7945,15681476,Foveaux,520,France,Female,39,1,73493.17,1,0,1,109626.13,1 +7946,15654870,Longo,759,France,Female,45,8,0,2,1,1,99251.24,0 +7947,15790448,Calabresi,473,France,Female,35,6,69617.36,1,1,0,143345.69,0 +7948,15785326,Randall,639,Spain,Female,35,5,136526.26,2,1,0,59653.03,0 +7949,15592854,Garcia,705,France,Male,25,3,113736.27,1,0,1,196864.61,0 +7950,15617486,Sullivan,530,France,Male,52,1,106723.28,1,0,0,109960.4,1 +7951,15806796,Higgins,516,Germany,Female,33,10,138847.9,1,1,1,127256.7,0 +7952,15644699,Crawford,850,France,Female,40,0,0,2,1,0,1099.95,0 +7953,15622305,Martin,746,Germany,Female,33,2,107868.14,2,1,1,146192.4,0 +7954,15608209,Currey,622,Germany,Male,33,3,96926.12,2,1,0,48553.77,0 +7955,15626898,Teng,743,France,Male,30,7,77599.23,1,0,0,144407.1,0 +7956,15644297,Austin,732,Germany,Male,38,5,178787.54,1,1,1,195760.53,0 +7957,15731569,Hudson,850,France,Male,81,5,0,2,1,1,44827.47,0 +7958,15582149,Ts'ui,850,Germany,Female,34,3,129668.43,2,1,1,88743.99,0 +7959,15802483,Hancock,686,France,Male,34,6,146178.13,2,1,1,88837.11,0 +7960,15686999,Nicholas,556,France,Female,40,8,0,2,1,0,62112.7,0 +7961,15772479,Napolitano,673,France,Male,37,4,0,2,0,0,163563.07,0 +7962,15778884,Jamieson,809,France,Female,38,2,154763.21,2,1,1,174800.31,0 +7963,15623630,Foster,634,Germany,Female,56,3,116251.24,1,0,1,42429.88,1 +7964,15774316,Moretti,630,France,Male,37,6,0,2,1,1,82647.65,0 +7965,15695097,Chiedozie,564,Germany,Female,30,0,100954.88,2,0,0,134175.15,0 +7966,15645404,Okwukwe,625,France,Female,51,4,124620.01,2,1,0,92243.94,1 +7967,15750574,Lumholtz,677,Spain,Female,34,4,0,2,1,1,6175.53,0 +7968,15636812,Rose,583,France,Male,40,9,112701.04,1,0,0,29213.63,0 +7969,15712068,Wan,592,Spain,Male,45,8,84692.5,1,0,1,67214.02,0 +7970,15652030,De Bernales,637,Germany,Male,49,2,108204.52,1,1,0,169037.84,1 +7971,15577398,Ch'eng,850,France,Male,30,6,86449.39,1,1,1,188809.23,0 +7972,15756848,Edmondson,633,Spain,Male,42,10,0,1,0,1,79408.17,0 +7973,15806929,Ch'ien,751,Germany,Male,36,5,73194.99,1,1,1,89222.66,0 +7974,15656005,Millar,592,Germany,Male,31,7,124593.23,1,1,0,86079.67,0 +7975,15722632,Dickson,716,Germany,Male,50,2,119655.77,1,1,1,12944.17,1 +7976,15794356,Toscani,641,Germany,Male,42,3,121765.37,2,1,1,166516.84,0 +7977,15659656,Pan,849,France,Male,35,4,110837.73,1,0,0,126419.8,0 +7978,15588341,Chigozie,647,Spain,Male,47,10,99835.17,1,0,1,89103.05,0 +7979,15709142,Sagese,608,Germany,Female,30,2,91057.37,2,1,0,132973.17,0 +7980,15627042,Reilly,555,France,Female,26,7,0,2,1,0,93122.41,0 +7981,15627517,Taylor,497,Spain,Male,27,7,149400.27,1,0,0,167522.19,0 +7982,15803032,Yen,599,Germany,Male,38,9,89111.63,1,0,0,157239.6,0 +7983,15665129,Kapustin,545,Germany,Male,33,1,132527.9,2,0,1,107429.71,0 +7984,15628272,Singh,774,France,Female,36,9,114997.42,1,1,0,75304.09,0 +7985,15678206,Yeh,464,France,Male,46,6,161798.53,1,1,0,182944.47,0 +7986,15678427,Genovese,696,Germany,Female,27,2,96129.32,2,1,1,5983.7,0 +7987,15678067,Boyle,667,Spain,Male,45,3,0,2,0,0,163655.01,0 +7988,15793331,Blair,812,France,Male,32,5,133050.97,2,1,0,89385.92,0 +7989,15699532,Okagbue,516,France,Male,51,8,120124.35,2,0,1,168773.54,0 +7990,15605827,Khan,645,France,Male,39,8,0,2,0,0,96864.36,0 +7991,15643635,Robertson,664,Spain,Male,32,5,133705.74,1,0,0,134455.84,0 +7992,15787710,Tikhonov,427,Spain,Female,39,9,0,2,1,0,28368.37,0 +7993,15614137,MacDonald,685,France,Female,40,7,0,2,1,0,103898.59,0 +7994,15754494,Ah Mouy,585,France,Female,33,4,152805.05,1,1,0,63239.65,0 +7995,15713440,Barese,519,Germany,Female,21,1,151701.45,3,1,1,170138.68,1 +7996,15803479,Winter-Irving,708,France,Female,67,1,0,2,0,1,3837.08,0 +7997,15709639,Wilson,717,France,Female,22,5,112465.06,1,1,1,92977.75,0 +7998,15601719,Fiorentino,465,Germany,Male,24,6,156007.09,1,1,0,191368.37,0 +7999,15772482,Iloerika,829,Germany,Male,28,3,132405.52,3,1,0,104889.2,1 +8000,15591489,Davison,826,France,Male,26,5,142662.68,1,0,0,60285.3,0 +8001,15629002,Hamilton,747,Germany,Male,36,8,102603.3,2,1,1,180693.61,0 +8002,15798053,Nnachetam,707,Spain,Male,32,9,0,2,1,0,126475.79,0 +8003,15753895,Blue,590,Spain,Male,37,1,0,2,0,0,133535.99,0 +8004,15595426,Madukwe,603,Spain,Male,57,6,105000.85,2,1,1,87412.24,1 +8005,15645815,Mills,615,France,Male,45,5,0,2,1,1,164886.64,0 +8006,15632848,Ferrari,634,France,Female,36,1,69518.95,1,1,0,116238.39,0 +8007,15703068,Nixon,716,Germany,Male,41,8,126145.54,2,1,1,138051.19,0 +8008,15791513,Manfrin,647,France,Male,41,4,138937.35,1,1,1,101617.64,1 +8009,15587210,McCartney,591,Germany,Female,44,10,113581.98,1,1,0,1985.41,0 +8010,15793803,Robinson,574,France,Male,34,1,112572.39,1,0,0,165626.6,0 +8011,15787756,Nkemdirim,467,Germany,Male,51,10,114514.71,2,1,0,177784.68,1 +8012,15723437,Sal,701,France,Female,35,2,0,2,1,1,65765.22,0 +8013,15702715,Kao,747,France,Female,34,10,0,2,1,1,50759.8,0 +8014,15809872,Ikechukwu,650,France,Male,32,2,84906.45,1,1,0,163216.48,0 +8015,15644295,Hargreaves,731,Spain,Female,39,2,126816.18,1,1,1,74850.93,0 +8016,15778694,Sievier,638,Germany,Female,26,1,105249.76,2,1,1,23491.09,0 +8017,15759555,Murphy,569,Spain,Male,41,2,0,2,1,0,134272.57,0 +8018,15631406,Munro,459,Germany,Male,50,5,109387.9,1,1,0,155721.15,0 +8019,15616676,Donnelly,632,Germany,Male,23,3,122478.51,1,1,0,147230.77,1 +8020,15771154,North,683,France,Female,73,8,137732.23,2,1,1,133210.44,0 +8021,15669491,Cruz,850,France,Female,46,2,157866.77,1,1,1,18986.12,0 +8022,15697691,Sinclair,512,France,Female,41,6,0,1,1,1,100507.81,0 +8023,15665180,Vasiliev,616,France,Female,31,3,136789.14,1,1,0,59346.4,1 +8024,15752588,Vasilyeva,664,France,Male,36,1,0,2,1,1,95372.64,0 +8025,15743051,Hamilton,694,France,Male,30,10,144684.03,1,1,1,31805.49,0 +8026,15571873,Sung,655,France,Male,24,9,107065.31,1,1,1,51959.82,0 +8027,15679743,Genovesi,607,France,Female,33,8,91301.72,1,0,1,130824.57,0 +8028,15769412,Atkinson,684,Spain,Male,39,4,207034.96,2,0,0,157694.76,1 +8029,15775124,Watterston,763,Spain,Male,37,8,0,2,1,1,933.38,0 +8030,15732113,Butters,671,Spain,Male,50,8,0,1,0,1,2560.11,0 +8031,15578141,Chien,592,Spain,Male,38,3,0,1,1,1,12905.89,1 +8032,15595874,Gorbunova,666,Spain,Female,36,6,0,2,1,0,176692.87,0 +8033,15755642,Bulgakov,667,France,Male,34,5,0,2,1,1,102908.63,0 +8034,15576526,Steele,850,Spain,Male,36,6,0,2,0,1,41291.05,0 +8035,15792489,Polyakova,622,Spain,Male,42,9,0,2,1,0,119127.06,0 +8036,15733705,Bull,577,France,Female,30,8,92472.1,2,0,1,126434.61,0 +8037,15807221,Weaver,555,Spain,Male,21,1,0,2,0,0,103901.35,0 +8038,15573045,Earl,547,France,Male,62,10,127738.75,2,1,1,85153,0 +8039,15756824,Giordano,613,Germany,Female,50,5,101242.98,2,1,0,12493.61,0 +8040,15773520,Begg,672,France,Female,43,4,92599.55,2,1,1,167336.78,0 +8041,15627439,Pickering,624,Spain,Female,36,10,0,2,0,1,186180.42,0 +8042,15701439,Fanucci,698,Spain,Female,50,1,0,4,1,0,88566.9,1 +8043,15785352,Chang,606,France,Male,37,6,82373.94,1,0,0,172526.9,1 +8044,15616525,Sopuluchi,720,Spain,Male,31,4,141356.47,1,0,0,137985.69,0 +8045,15717489,Martin,835,France,Male,23,9,0,1,1,0,19793.73,1 +8046,15795737,McNaughtan,771,Spain,Female,47,3,72664,2,1,1,107874.39,0 +8047,15693877,Stewart,811,France,Female,47,3,123365.34,2,0,0,171995.34,0 +8048,15576111,Reagan,734,Germany,Male,33,5,121898.58,1,1,0,61829.89,0 +8049,15595713,Heller,548,Spain,Male,33,6,0,1,1,1,31728.35,0 +8050,15808868,Nwokeocha,652,France,Female,31,3,103696.97,3,0,0,155221.05,1 +8051,15708193,Liu,707,France,Male,33,2,0,2,0,0,130866.95,0 +8052,15697801,Sokolova,605,Germany,Female,56,1,74129.18,2,1,1,62199.78,1 +8053,15770121,Bancroft,623,France,Female,34,9,0,1,1,0,24255.21,0 +8054,15800524,Nnanna,686,Germany,Male,29,3,185379.02,1,1,0,64679.07,0 +8055,15686236,Trevisani,525,Germany,Female,47,1,118087.68,1,1,0,88120.78,1 +8056,15659807,Nwachinemelu,657,Spain,Male,41,8,109402.13,1,1,1,66463.62,0 +8057,15736078,Ting,730,Germany,Female,33,7,130367.87,1,1,0,15142.1,1 +8058,15620836,Lo Duca,816,Germany,Female,34,2,108410.87,2,1,0,102908.91,0 +8059,15698184,Marshall,484,France,Female,50,2,90408.16,2,0,0,48170.57,0 +8060,15717643,Band,728,France,Female,34,6,90425.15,2,1,1,11597.69,0 +8061,15776596,Ferri,730,Spain,Female,39,6,140094.59,1,1,0,172450.04,1 +8062,15814757,Carter,477,Spain,Male,31,9,0,2,0,1,184061.17,0 +8063,15812607,Wilson,663,Germany,Female,46,6,95439.4,1,1,1,21038.58,1 +8064,15663888,Connor,549,Germany,Male,34,6,204017.4,2,1,0,109538.35,0 +8065,15748882,Reid,714,Spain,Male,29,9,0,2,1,0,129192.55,0 +8066,15690829,Sandefur,430,Germany,Male,49,3,137115.16,1,1,0,146516.86,1 +8067,15695819,Bidwill,504,Germany,Male,43,5,134740.19,2,1,0,181430.91,0 +8068,15696834,Cone,530,France,Female,29,5,0,2,0,0,121451.21,0 +8069,15797710,Saunders,619,Germany,Male,29,4,98955.87,1,0,1,131712.51,0 +8070,15700654,Liardet,617,Germany,Male,44,9,49157.09,2,1,0,53294.17,0 +8071,15583764,Wilkes,791,Germany,Male,31,1,130240.33,1,0,0,96546.55,0 +8072,15688849,Martin,609,France,Male,48,1,108019.27,3,1,1,184524.65,1 +8073,15661473,Boni,780,Germany,Male,51,4,126725.25,1,1,0,195259.31,1 +8074,15601030,Patel,777,Germany,Female,34,5,96693.66,1,1,1,172618.52,0 +8075,15789557,Howell-Price,817,Germany,Female,27,7,129810.6,1,1,1,59259.44,0 +8076,15745250,Simpson,850,France,Male,58,8,156652.13,1,0,0,25899.21,1 +8077,15590349,Rowland,732,France,Female,36,9,0,1,0,0,3749,1 +8078,15741693,Barnard,693,France,Male,40,4,130661.96,1,1,1,101918.96,0 +8079,15618446,Nnonso,576,France,Female,50,8,0,2,1,1,57802.62,0 +8080,15766552,Rossi,643,France,Male,37,6,0,2,0,0,142454.77,0 +8081,15668775,Pendred,757,France,Male,47,3,130747.1,1,1,0,143829.54,0 +8082,15757895,Martin,569,Germany,Male,30,6,106629.49,1,0,1,44114.88,0 +8083,15774551,K?,772,Spain,Male,36,3,112029.83,1,1,1,186948.35,0 +8084,15684011,Miller,576,Germany,Male,29,7,130575.26,1,0,1,173629.78,0 +8085,15736146,Afamefula,608,Germany,Male,28,4,96679.71,1,1,1,49133.45,0 +8086,15656286,Sims,794,France,Male,33,0,0,2,0,0,178122.71,0 +8087,15774847,Knight,593,France,Male,50,6,171740.69,1,0,0,20893.61,0 +8088,15619340,Obijiaku,597,Spain,Male,38,1,0,2,1,0,41303.29,0 +8089,15815656,Hopkins,541,Germany,Female,39,9,100116.67,1,1,1,199808.1,1 +8090,15623357,Onio,692,Germany,Male,24,2,120596.93,1,0,1,180490.53,0 +8091,15601324,Black,697,France,Female,48,1,0,2,1,1,87400.53,0 +8092,15715510,Eluemuno,768,France,Male,29,2,95984.69,2,1,1,73686.75,0 +8093,15663770,Doyle,802,France,Male,38,1,142557.11,1,1,1,172497.73,0 +8094,15779267,Onyemere,584,France,Male,47,5,0,2,1,0,89286.29,0 +8095,15597957,Rahman,614,Spain,Male,66,2,0,2,0,1,180082.7,0 +8096,15584620,Su,850,Germany,Female,36,6,143644.16,1,1,0,22102.25,1 +8097,15750772,Walker,671,France,Female,38,6,132129.72,1,0,1,76068.95,0 +8098,15706557,Ferguson,626,France,Female,52,0,0,2,1,0,32159.46,1 +8099,15594391,Samaniego,770,France,Female,68,2,183555.24,1,0,0,159557.28,1 +8100,15661656,Onwumelu,633,France,Male,38,2,91902.56,2,1,1,107673.35,0 +8101,15631217,Young,663,France,Male,40,6,156218.19,1,0,1,33607.72,0 +8102,15588955,Mazzi,581,Germany,Female,43,5,93259.57,3,1,0,141035.65,1 +8103,15758252,Toscano,561,Germany,Female,45,2,168085.38,2,0,1,115719.08,0 +8104,15740223,Walton,479,Germany,Male,51,1,107714.74,3,1,0,86128.21,1 +8105,15805413,Chiang,769,France,Female,31,6,117852.26,2,1,0,147668.64,0 +8106,15635116,Burgos,659,Spain,Male,60,2,0,1,1,0,177480.45,1 +8107,15764892,Spinelli,590,Spain,Female,51,10,84474.62,2,1,1,190937.09,0 +8108,15795936,Lung,560,France,Male,50,3,0,2,1,0,84531.79,0 +8109,15655232,Noble,437,Germany,Male,35,6,126803.34,2,1,1,161133.4,0 +8110,15640133,Pai,661,France,Female,34,0,0,2,1,0,185555.63,0 +8111,15751524,Chigozie,677,Germany,Female,36,10,68806.84,1,1,0,33075.24,0 +8112,15670552,Peavy,560,France,Female,31,3,115141.18,1,1,0,39806.75,0 +8113,15623966,Yermakov,578,France,Female,35,2,0,2,0,1,26389.92,0 +8114,15752193,Burton,421,Spain,Male,34,6,90723.36,1,1,1,12162.76,0 +8115,15607269,Costa,492,Germany,Female,49,2,151249.45,2,1,1,167237.94,0 +8116,15700752,Pugliesi,545,France,Female,32,6,0,2,1,1,52067.37,0 +8117,15777901,Lindell,640,Germany,Female,43,9,94752.49,1,1,0,184006.36,1 +8118,15639117,Sorenson,624,Spain,Female,34,6,0,1,1,0,582.59,1 +8119,15720203,Arcuri,577,Spain,Male,28,7,0,1,1,0,143274.41,0 +8120,15586236,Banks,704,France,Male,31,5,132084.66,3,1,1,54474.48,1 +8121,15676645,Parry,523,France,Male,45,5,0,2,1,1,121428.2,0 +8122,15715988,Cockett,793,France,Male,35,2,0,2,1,1,79704.12,0 +8123,15603749,Galkina,564,France,Female,53,2,45472.28,1,1,1,41055.71,1 +8124,15608956,Su,711,France,Male,33,1,0,1,0,0,41590.4,0 +8125,15733872,Marino,791,Germany,Female,33,10,130229.71,2,0,0,54019.93,1 +8126,15666982,Spears,629,Germany,Female,38,9,123948.85,1,1,0,76053.07,0 +8127,15602647,Cunningham,729,Germany,Male,39,6,127415.85,1,1,1,184977.2,1 +8128,15623063,Taylor,651,Germany,Male,35,8,110067.71,1,1,0,127678.95,1 +8129,15682928,Chiazagomekpere,695,Spain,Male,39,4,65521.2,1,1,1,1243.97,0 +8130,15729246,Hardacre,847,Spain,Male,31,5,0,2,1,1,76326.67,0 +8131,15588928,Maslow,704,France,Male,47,5,0,2,1,1,145338.61,0 +8132,15803352,Scott,613,Germany,Male,33,3,155736.42,2,1,1,57751.21,0 +8133,15607485,Wakelin,692,Spain,Female,29,4,0,2,0,0,138880.24,0 +8134,15656249,Esposito,720,France,Female,34,3,118307.57,2,1,1,136120.29,0 +8135,15761783,Shah,577,France,Male,41,6,0,1,1,1,167621.18,0 +8136,15716605,Chukwufumnanya,710,Germany,Female,24,7,103099.17,2,1,0,173276.62,0 +8137,15757425,Fleming,716,France,Female,38,1,0,2,1,1,99661.46,0 +8138,15603096,Lori,410,France,Male,33,6,125789.69,1,0,0,66333.56,1 +8139,15588580,Kennedy,584,Germany,Female,36,4,109646.83,1,1,1,70240.79,0 +8140,15770539,Walters,792,France,Male,30,1,127187.86,1,1,1,113553.42,0 +8141,15572022,Han,605,France,Female,36,6,0,1,0,1,690.84,0 +8142,15571843,Lawrence,486,Spain,Male,24,1,0,1,1,0,98802.76,0 +8143,15752502,Cooke,615,France,Male,41,4,130385.82,1,0,1,130661.95,0 +8144,15609058,Wan,676,France,Male,23,1,107787.47,1,0,1,116378.82,0 +8145,15775108,Lo Duca,571,France,Male,34,1,99325.04,2,0,1,186052.15,0 +8146,15708904,Yermakova,850,France,Female,37,9,0,1,0,0,100101.06,0 +8147,15600086,Combs,717,France,Male,48,7,123764.95,1,1,1,169952.82,0 +8148,15814675,Chien,642,Germany,Female,39,8,128264.03,1,1,0,61792.76,1 +8149,15572777,Meng,780,Spain,Male,47,7,86006.21,1,1,1,37973.13,0 +8150,15585106,Calabresi,492,Germany,Female,38,8,57068.43,2,1,0,188974.81,0 +8151,15738936,Stevenson,760,Germany,Male,29,5,103607.24,2,0,1,86334.64,0 +8152,15750970,Davidson,500,Spain,Male,40,1,99004.24,1,1,1,152845.99,0 +8153,15725772,Ch'in,654,Spain,Female,36,2,0,2,1,1,146652.11,0 +8154,15692106,Rose,606,Spain,Female,25,3,147386.72,3,1,0,45482.04,1 +8155,15791533,Ch'ien,367,Spain,Male,42,6,93608.28,1,1,0,168816.73,1 +8156,15715715,Artyomova,799,Spain,Male,38,2,0,2,1,1,59297.34,0 +8157,15785576,Mayrhofer,434,Germany,Male,71,9,119496.87,1,1,0,125848.88,0 +8158,15798834,Yefremov,719,Spain,Female,32,7,0,1,0,0,76264.27,0 +8159,15744127,Kosovich,641,France,Female,37,2,0,2,1,0,3939.87,0 +8160,15637427,Lu,461,Spain,Female,25,6,0,2,1,1,15306.29,0 +8161,15576990,Taplin,790,Germany,Female,25,5,152885.77,1,1,0,58214.79,0 +8162,15615352,Ebelechukwu,588,France,Male,31,4,99607.37,2,0,1,35877.03,0 +8163,15647333,Fleming,621,France,Male,27,4,137003.68,1,1,0,21254.06,0 +8164,15572050,Yefimov,768,Germany,Male,48,3,122831.58,1,1,1,24533.89,1 +8165,15581370,Andreyeva,681,Spain,Male,38,2,99811.44,2,1,0,23531.5,0 +8166,15813503,Pickering,606,Spain,Male,37,8,154712.58,2,1,0,89099.18,0 +8167,15769783,Allan,542,Spain,Male,37,8,0,1,1,1,807.06,0 +8168,15793135,Wang,713,Germany,Female,24,7,147687.24,1,1,1,121592.5,0 +8169,15599182,Reynolds,597,Spain,Female,33,2,0,2,1,1,4700.66,0 +8170,15689517,Hales,635,France,Male,27,3,127009.83,1,1,0,161909.95,0 +8171,15641366,Y?an,599,Germany,Male,61,1,124737.96,1,0,1,90389.61,1 +8172,15588859,Rowley,496,Spain,Female,44,0,179356.28,2,1,0,2919.21,1 +8173,15732293,Chia,759,Spain,Male,31,8,0,2,1,1,99086.74,0 +8174,15568032,Moore,757,Germany,Male,31,1,127320.36,3,1,0,163170.32,0 +8175,15623525,Copeland,564,Spain,Male,31,0,125175.58,1,1,1,72757.33,0 +8176,15606601,Rishel,561,France,Female,22,6,186788.96,2,1,0,73286.8,0 +8177,15800811,Wan,702,France,Male,40,3,148556.74,1,0,1,146056.29,0 +8178,15610711,Eluemuno,678,Germany,Female,40,8,128644.46,1,0,0,167673.37,0 +8179,15809654,Hsia,707,France,Female,46,7,127476.73,2,1,1,146011.55,0 +8180,15576077,Kelly,610,France,Female,27,9,159561.93,1,0,1,103381.47,0 +8181,15643378,Muir,744,France,Male,42,1,112419.92,1,1,1,83022.92,0 +8182,15566790,McIntyre,598,France,Male,28,8,129991.76,2,0,1,46041.08,0 +8183,15774402,Donaldson,562,Spain,Male,36,5,0,1,0,1,182843.24,0 +8184,15694641,Wright,621,Spain,Female,59,2,0,2,1,1,171364.18,0 +8185,15605916,Uvarova,659,France,Female,50,3,0,1,1,0,183399.12,1 +8186,15812356,Doherty,722,Germany,Female,40,6,89175.06,2,0,1,152883.95,0 +8187,15644179,Allen,606,France,Female,39,3,0,2,1,0,50560.45,1 +8188,15771674,Ma,603,Spain,Female,39,5,162390.52,2,1,0,54702.66,0 +8189,15623314,Tucker,506,Germany,Female,59,3,190353.08,1,1,0,78365.75,0 +8190,15613292,Ch'eng,715,France,Male,21,8,0,2,1,0,68666.63,0 +8191,15813871,Hs?,690,France,Male,47,2,0,2,1,0,151375.73,0 +8192,15759480,H?,644,France,Female,40,10,139180.97,1,1,1,19959.67,0 +8193,15587712,Chimaijem,589,France,Male,36,8,114435.47,1,1,0,26955.72,0 +8194,15671165,Esomchi,592,France,Female,66,5,149950.19,1,1,1,76267.59,0 +8195,15620746,Lorenzo,632,France,Male,42,4,126115.6,1,1,0,100998.5,0 +8196,15706537,Pirogov,577,Germany,Female,59,7,111396.97,1,0,1,191070.01,0 +8197,15589312,Larkin,588,France,Male,30,3,115007.08,1,0,0,176858.5,0 +8198,15741180,Eddy,617,France,Male,54,6,102141.9,1,1,1,45325.26,0 +8199,15733888,Sells,668,Spain,Female,36,3,133686.52,1,1,0,190958.48,1 +8200,15798532,Crawford,810,France,Male,32,9,120879.73,2,0,1,78896.59,0 +8201,15577359,Bezrukov,767,Spain,Male,47,5,0,1,1,0,121964.46,1 +8202,15614936,Mancini,718,Spain,Female,49,10,82321.88,1,0,1,11144.4,0 +8203,15747647,Iadanza,589,Spain,Female,27,4,0,2,1,0,144181.48,0 +8204,15588566,Wilkinson,778,Spain,Male,33,5,116474.28,2,1,1,32757.55,0 +8205,15570141,P'eng,724,France,Female,34,3,132352.69,1,1,0,80320.3,0 +8206,15800793,St Clair,477,Germany,Female,39,4,182491.57,1,1,0,185830.72,0 +8207,15572415,Preston,580,France,Male,34,6,0,2,1,1,160095.31,0 +8208,15635125,Findlay,566,Spain,Male,63,2,120787.18,2,1,1,52198.84,0 +8209,15636551,Nixon,711,France,Female,29,3,130181.47,2,1,0,31811.44,0 +8210,15600912,Gorshkov,706,Germany,Male,32,5,88348.43,2,1,1,104181.78,0 +8211,15768476,Chukwubuikem,703,Spain,Male,31,6,0,2,1,1,67667.19,0 +8212,15650266,Medvedeva,679,Germany,Male,39,2,146186.28,2,1,1,193974.47,0 +8213,15621004,Chukwuhaenye,603,France,Male,32,7,0,1,1,0,198055.94,1 +8214,15748352,Endrizzi,598,Spain,Male,34,0,104488.17,1,0,1,43249.67,0 +8215,15788920,Ch'ang,836,Germany,Female,32,4,109196.67,2,1,0,55218.02,0 +8216,15743236,Piccio,687,France,Female,61,7,80538.56,1,1,0,131305.37,1 +8217,15637717,Lockington,704,Germany,Male,41,4,109026.8,2,1,1,43117.1,0 +8218,15635500,Seleznyov,605,Germany,Male,75,2,61319.63,1,0,1,186655.11,0 +8219,15634792,Weston,516,France,Female,40,9,0,2,0,1,33266.29,0 +8220,15607560,Groom,572,France,Female,39,2,0,2,1,1,555.28,0 +8221,15727177,Manfrin,557,France,Male,42,6,177822.03,1,1,0,150944.31,1 +8222,15774358,Robertson,443,Germany,Male,59,4,110939.3,1,1,0,72846.58,1 +8223,15791304,Ch'ang,604,Germany,Male,25,7,165413.43,1,1,1,35279.74,0 +8224,15603328,Lucchesi,483,France,Male,27,1,77805.66,1,1,1,2101.89,0 +8225,15804937,Cambage,702,France,Male,50,3,0,2,0,0,94949.84,0 +8226,15804142,Tan,670,Spain,Female,57,3,175575.95,2,1,0,99061.75,1 +8227,15608845,Tao,804,Spain,Female,38,3,124197.22,1,1,0,74692.06,0 +8228,15702434,Hsieh,850,France,Female,30,3,0,2,1,0,116692.8,0 +8229,15632609,Burdekin,554,France,Female,39,10,160132.75,1,1,0,32824.15,0 +8230,15603550,Longo,588,Germany,Female,37,7,70258.88,2,1,0,139607.61,0 +8231,15755239,Maughan,758,Germany,Male,32,4,162657.64,2,1,1,115525.13,0 +8232,15670528,Franz,787,Germany,Male,43,0,132217.45,1,1,0,20955.03,1 +8233,15732704,Piazza,582,Spain,Male,25,9,148042.97,2,1,0,52341.15,0 +8234,15589019,Morant,633,Spain,Female,33,4,92855.02,1,1,1,159813.18,0 +8235,15677796,Becher,766,Germany,Male,47,9,129289.98,1,1,0,169935.46,1 +8236,15760177,Lombardi,564,Spain,Male,37,9,100252.18,1,1,1,146033.52,0 +8237,15636595,Loton,602,Spain,Male,37,3,107592.89,2,0,1,153122.73,0 +8238,15737275,Conti,649,France,Male,39,3,113096.41,1,1,1,60335.24,0 +8239,15672905,Sani,679,Spain,Female,40,7,0,2,1,1,163757.29,0 +8240,15753955,Lori,639,Spain,Male,34,7,149940.04,2,0,0,156648.81,0 +8241,15708504,Wong,790,Germany,Male,50,8,121438.58,1,1,1,176471.78,1 +8242,15592451,Lombardi,565,France,Male,32,9,0,2,1,0,5388.3,0 +8243,15790455,Obialo,478,France,Female,50,2,0,1,0,1,93332.64,1 +8244,15572174,Mazzi,825,France,Male,29,3,148874.01,2,0,1,71192.82,0 +8245,15656330,Von Doussa,528,Spain,Female,32,0,68138.37,1,1,1,170309.19,0 +8246,15569626,Miller,577,Spain,Male,35,5,110080.3,1,1,1,109794.31,0 +8247,15608726,Miracle,663,France,Male,24,7,0,2,1,1,166310.82,0 +8248,15637366,Su,505,Germany,Female,25,5,114268.85,2,1,1,126728.27,0 +8249,15778049,Wyatt,633,Germany,Male,29,6,117412.35,1,0,0,30338.94,0 +8250,15727421,Anayolisa,586,France,Female,38,6,0,2,1,1,37935.83,0 +8251,15688865,Wade,850,France,Female,35,9,0,2,0,0,25329.48,0 +8252,15751032,Enemuo,629,Germany,Female,37,1,35549.81,2,0,0,49676.33,0 +8253,15734737,Bruno,744,France,Male,56,9,0,2,1,1,169498.61,0 +8254,15746515,Greece,750,France,Male,36,7,136492.92,3,1,1,26500.29,1 +8255,15664311,Yang,637,Germany,Male,28,3,123675.69,1,1,1,166458.41,0 +8256,15708139,Brown,575,France,Female,40,1,139532.34,1,1,0,181294.39,0 +8257,15768574,Anderson,671,Spain,Male,58,1,178713.98,1,1,1,21768.21,0 +8258,15738018,Johnston,571,France,Male,40,5,0,2,0,0,72849.29,0 +8259,15699753,Zakharov,590,France,Male,41,1,89086.31,1,1,0,24499.97,0 +8260,15703199,Golibe,619,Spain,Male,38,3,96143.47,1,0,0,98994.92,0 +8261,15627830,Nikitina,640,Germany,Female,30,5,32197.64,1,0,1,141446.01,0 +8262,15570855,Leonard,670,France,Male,38,7,0,2,1,1,77864.41,0 +8263,15772503,Burns,737,France,Female,33,4,0,2,1,0,115115.32,0 +8264,15584453,Burtch,555,Spain,Male,32,10,0,2,0,1,168605.96,0 +8265,15710111,Clark,742,France,Male,33,6,0,2,0,0,38550.4,0 +8266,15618562,Woodward,618,Germany,Female,40,0,140306.38,1,1,0,160618.61,1 +8267,15706764,Spencer,560,France,Female,35,1,0,2,1,0,3701.63,0 +8268,15798737,Chao,654,France,Male,38,8,0,2,1,0,88659.44,0 +8269,15712608,Costa,787,Germany,Female,42,2,74483.97,2,0,1,44273.91,0 +8270,15636736,McLachlan,611,France,Female,53,7,0,2,0,1,156495.39,1 +8271,15703544,Hung,559,Spain,Male,34,0,0,1,1,0,182988.94,0 +8272,15815645,Akhtar,481,France,Male,37,8,152303.66,2,1,1,175082.2,0 +8273,15705739,Toscani,753,Germany,Male,32,5,159904.79,1,1,0,148811.14,0 +8274,15709643,Gray,675,France,Male,32,1,0,3,1,0,85901.09,0 +8275,15669805,Warren,748,Germany,Female,31,1,99557.94,1,1,0,199255.32,0 +8276,15737489,Ramsden,610,Spain,Female,46,5,116886.59,1,0,0,107973.44,0 +8277,15775131,Bartlett,580,Spain,Male,32,9,142188.2,2,0,1,128028.6,0 +8278,15765283,Wenz,624,Germany,Female,40,3,149961.99,2,1,0,104610.86,0 +8279,15628715,Kisch,709,France,Female,36,8,0,2,1,1,69676.55,0 +8280,15813283,Mai,605,France,Female,34,2,0,1,0,0,35982.42,0 +8281,15745716,McGregor,706,Spain,Male,53,7,0,2,0,1,117939.17,0 +8282,15598485,Pinto,567,Spain,Male,40,8,28649.64,1,1,1,95140.62,0 +8283,15696552,Newman,747,France,Female,21,4,81025.6,2,1,0,167682.57,0 +8284,15754569,Pagnotto,664,France,Male,57,1,0,2,1,1,56562.57,0 +8285,15701741,Williams,711,France,Female,39,3,152462.79,1,1,0,90305.97,0 +8286,15572631,Ndubuisi,609,France,Male,25,10,0,1,0,1,109895.16,0 +8287,15636069,Plummer,632,Spain,Male,28,7,155519.59,1,1,0,1843.24,0 +8288,15682467,Chimezie,725,France,Female,36,1,118851.05,1,1,1,102747.02,0 +8289,15790744,Nash,850,France,Female,34,9,92899.27,2,1,0,97465.89,0 +8290,15625023,Onochie,682,France,Male,40,4,0,1,0,1,105352.55,0 +8291,15731267,Rizzo,797,France,Male,37,4,75263.7,1,1,0,85801.77,0 +8292,15742879,Boni,668,Spain,Male,38,1,147904.31,1,1,1,69370.05,0 +8293,15757015,Davies,783,Germany,Female,41,5,106640.5,1,1,0,176945.96,0 +8294,15770711,Lu,766,Germany,Female,28,4,90696.78,1,0,1,21597.2,0 +8295,15569430,Burrows,704,Spain,Female,36,2,175509.8,2,1,0,152039.67,0 +8296,15617304,Ershova,722,France,Male,40,6,0,2,1,1,111893.09,0 +8297,15704466,Udokamma,692,France,Female,34,7,0,2,1,0,195074.62,0 +8298,15664681,Aitken,584,France,Female,35,2,114321.28,2,0,0,15959.01,0 +8299,15605534,Turnbull,644,Germany,Female,51,4,95560.04,1,0,0,72628.84,1 +8300,15792473,Reilly,598,Germany,Female,50,5,88379.81,3,0,1,64157.24,1 +8301,15802625,Hardy,733,Germany,Male,48,7,85915.52,1,1,1,23860.5,0 +8302,15766017,Brookman,615,Germany,Male,58,3,72309.3,1,1,1,85687.09,1 +8303,15762172,Kerr,850,France,Female,39,2,0,2,1,0,179451.42,0 +8304,15728333,McBurney,521,France,Male,43,8,0,1,1,1,93180.09,0 +8305,15792868,Mickey,675,France,Male,69,1,0,2,1,0,157097.09,0 +8306,15605698,Harrison,746,France,Male,58,3,0,3,1,1,80344.96,1 +8307,15777060,Olszewski,770,France,Female,33,4,0,1,1,0,26080.54,1 +8308,15626243,Chijioke,618,France,Male,30,3,133844.22,1,1,1,31406.93,0 +8309,15719898,Young,556,France,Male,36,7,154872.08,2,1,1,32044.64,0 +8310,15599976,Bellasis,749,France,Female,27,9,0,2,1,0,132734.87,0 +8311,15752809,De Mestre,702,Spain,Male,43,6,116121.67,1,1,0,61602.42,0 +8312,15589698,De Luca,555,Germany,Male,42,6,107104.5,1,1,1,41304.44,1 +8313,15609977,Mundy,587,France,Male,47,6,71026.77,1,1,0,57962.41,0 +8314,15750121,Tung,639,France,Male,38,3,0,1,1,0,42862.82,0 +8315,15734177,Donahue,643,France,Male,33,4,0,2,1,1,152992.04,0 +8316,15781347,Okagbue,600,France,Female,41,1,0,2,1,1,91193.65,0 +8317,15592025,Nnaemeka,651,France,Male,53,7,0,2,1,1,130132.41,0 +8318,15670163,Verjus,666,France,Female,27,4,0,2,0,0,88751.45,0 +8319,15765402,H?,520,France,Female,39,6,145644.05,1,0,0,104118.93,0 +8320,15624343,Napolitani,650,Spain,Female,50,7,129667.77,1,0,0,42028.16,0 +8321,15602354,Ginikanwa,564,Germany,Male,33,3,109341.87,1,1,0,75632.78,0 +8322,15579183,Spaull,586,France,Male,64,1,0,2,1,1,53710.23,0 +8323,15584899,Siciliani,617,France,Female,35,5,0,2,0,1,13066.3,0 +8324,15723658,Voronina,712,Spain,Female,30,6,0,2,1,0,152417.97,0 +8325,15803965,Tang,654,France,Male,55,3,87485.67,1,1,1,3299.01,0 +8326,15682489,Crumbley,605,France,Male,27,9,0,2,1,0,198091.81,0 +8327,15813645,Hamilton,491,France,Female,36,0,53369.13,1,1,1,103934.12,0 +8328,15766787,Piazza,707,France,Female,35,9,0,2,1,1,70403.65,0 +8329,15687171,Birch,638,Spain,Male,34,5,146679.77,1,1,0,102179.86,0 +8330,15690744,Custance,683,France,Male,43,2,112499.42,2,1,0,30375.18,0 +8331,15707974,Anayochukwu,815,Spain,Female,38,2,48387,1,1,0,184796.84,0 +8332,15673084,Galkin,645,Spain,Male,38,1,68079.8,1,0,1,166264.89,0 +8333,15814772,Adams,645,Germany,Male,49,4,160133.88,1,0,1,88391.97,0 +8334,15743709,Toomey,683,France,Male,30,4,66190.33,1,1,1,115186.97,0 +8335,15610343,Marshall-Hall,705,France,Female,37,10,0,2,1,1,13935.53,1 +8336,15737414,Shen,647,France,Male,35,4,123761.68,1,1,0,83910.4,0 +8337,15788480,Pagnotto,786,Germany,Female,33,0,122325.58,1,0,0,34712.34,1 +8338,15568519,Wood,534,France,Male,41,9,0,2,1,0,13871.34,0 +8339,15792453,More,602,Spain,Female,42,1,138912.17,1,1,1,139494.75,0 +8340,15658100,Piccio,695,France,Female,42,0,0,2,0,1,140724.64,0 +8341,15695197,Tochukwu,553,Germany,Female,25,7,128524.19,2,1,0,20682.46,0 +8342,15749807,Graham,516,Spain,Female,31,3,0,2,1,0,124202.26,0 +8343,15773876,Tung,655,France,Female,34,3,0,2,1,0,159638.77,0 +8344,15591698,P'eng,849,Germany,Female,49,9,132934.89,1,1,0,171056.65,1 +8345,15712813,Nevzorova,520,Germany,Male,43,3,150805.17,3,0,1,25333.03,1 +8346,15763898,Toscani,568,Spain,Female,46,3,0,2,1,1,29372.62,0 +8347,15793324,McKenzie,695,Spain,Male,32,9,0,3,0,1,38533.79,0 +8348,15757759,Okwuoma,807,Spain,Female,28,7,165969.26,3,1,0,156122.13,1 +8349,15796230,Morley,642,Germany,Female,36,2,124495.98,3,1,1,57904.22,1 +8350,15611729,Kerr,703,Germany,Male,39,1,141559.5,1,1,1,31257.1,1 +8351,15709531,Harding,556,France,Male,38,2,114756.14,1,1,0,193214.05,0 +8352,15650751,Butler,585,France,Female,30,6,0,2,1,1,137757.69,0 +8353,15641413,Crawford,587,Germany,Female,49,7,155393.98,2,1,0,13308.2,1 +8354,15753840,Brown,524,Spain,Female,32,6,0,1,1,1,132861.9,1 +8355,15669994,Greece,556,Germany,Female,31,1,128663.81,2,1,0,125083.29,0 +8356,15695301,Matthews,504,Spain,Male,44,4,113522.64,1,1,1,12405.2,0 +8357,15792004,Heath,731,Spain,Female,26,3,0,2,1,0,37697.29,0 +8358,15603035,Vincent,651,France,Male,34,3,0,2,1,1,105599.65,0 +8359,15717286,Sal,675,Spain,Female,40,8,79035.95,1,1,0,142783.98,1 +8360,15577107,Milne,657,Spain,Female,22,6,0,3,0,1,168412.07,1 +8361,15754747,Bazile,686,Germany,Male,33,9,141918.09,2,0,1,184036.47,0 +8362,15705676,Wardle,690,France,Female,35,9,107944.33,2,0,0,48478.47,0 +8363,15751912,Lilly,567,France,Male,36,7,0,2,0,1,3896.08,0 +8364,15677336,Aitken,557,Germany,Male,57,1,120043.13,1,1,0,132370.75,1 +8365,15684395,Enderby,446,Spain,Female,45,10,125191.69,1,1,1,128260.86,1 +8366,15659949,Chiu,850,France,Male,31,1,96399.31,2,1,0,106534.15,0 +8367,15812422,Ugorji,637,France,Male,41,2,0,2,0,1,102515.42,0 +8368,15806941,Sharpe,499,France,Male,60,7,76961.6,2,1,1,83643.87,0 +8369,15637690,Houghton,622,Germany,Female,34,7,98675.74,1,1,0,138906.85,1 +8370,15632882,Konovalova,684,Germany,Male,37,1,126817.13,2,1,1,29995.83,1 +8371,15807107,Patel,612,France,Male,32,3,121394.42,1,1,0,164081.42,0 +8372,15661034,Ngozichukwuka,813,Germany,Female,29,5,106059.4,1,0,0,187976.88,1 +8373,15811958,Medland,850,Germany,Male,44,2,112755.34,2,0,0,158171.36,0 +8374,15785167,Padovano,795,Spain,Male,29,4,0,2,0,0,155711.64,0 +8375,15646720,Tsui,628,Spain,Female,55,7,0,3,1,0,85890.75,1 +8376,15658614,H?,565,Germany,Female,38,7,145400.69,2,1,1,83844.79,0 +8377,15704657,Denman,601,France,Male,39,3,72647.64,1,1,0,41777.9,1 +8378,15567147,Ratten,802,Spain,Male,40,4,0,2,1,1,81908.09,0 +8379,15701319,Baxter,614,Germany,Female,37,6,96340.81,2,1,1,139377.24,1 +8380,15745266,Norman,434,Spain,Male,55,6,0,1,0,1,73562.05,1 +8381,15650437,Shen,522,Germany,Male,32,8,124450.36,2,1,1,165786.1,0 +8382,15764314,Reilly,550,Germany,Male,36,2,113877.23,2,1,0,174921.91,0 +8383,15612594,Ifeanacho,599,Spain,Male,25,3,0,2,1,1,120790.02,0 +8384,15593501,Graham,493,France,Female,36,5,148667.81,2,1,0,56092.51,0 +8385,15804150,Lysaght,755,France,Male,34,3,0,2,1,1,158816.03,0 +8386,15649297,T'ang,605,France,Female,62,4,111065.93,2,0,1,125660.99,0 +8387,15641110,Abron,708,France,Male,41,0,0,1,1,0,128400.62,0 +8388,15660608,Chimaraoke,699,France,Male,44,8,158697.61,1,1,0,107181.22,0 +8389,15806570,Y?an,763,France,Female,53,4,0,1,1,0,77203.72,1 +8390,15715345,Sergeyeva,743,Spain,Male,25,6,0,2,1,0,129740.11,0 +8391,15755521,Ma,660,France,Female,48,0,90044.32,2,0,1,187604.97,1 +8392,15579074,Obiajulu,619,Germany,Male,38,10,84651.79,1,1,1,184754.26,0 +8393,15641158,Belcher,739,Germany,Male,32,3,102128.27,1,1,0,63981.37,1 +8394,15752507,K?,769,Germany,Male,60,9,148846.39,1,1,0,192831.67,1 +8395,15597983,Brown,692,France,Male,69,10,154953.94,1,1,1,70849.47,0 +8396,15586069,Abernathy,560,France,Female,30,0,108883.29,1,1,0,27914.95,0 +8397,15655082,Pape,607,France,Female,48,4,112070.86,3,1,0,173568.3,1 +8398,15720155,Tao,630,Germany,Male,29,6,131354.39,1,0,1,9324.31,1 +8399,15582116,Ma,767,Germany,Female,45,7,132746.2,2,1,0,26628.88,1 +8400,15749365,Earle,543,France,Female,34,8,0,2,0,1,145601.8,0 +8401,15632069,Kazantsev,776,France,Male,39,8,125211.55,2,1,0,144496.07,0 +8402,15663134,Uspenskaya,535,Spain,Male,58,1,0,2,1,1,11779.98,1 +8403,15766683,Coombes,549,Germany,Male,36,6,139422.37,1,0,0,83983.39,1 +8404,15707219,Hopman,844,France,Female,28,4,0,2,0,1,123318.37,0 +8405,15709232,McKay,586,Germany,Female,47,5,157099.47,2,1,1,65481.86,0 +8406,15801351,Milanesi,583,France,Male,40,3,0,2,1,0,47728,0 +8407,15578747,Chineze,701,Spain,Male,26,5,83600.24,1,0,1,59195.05,0 +8408,15675626,Dawson,726,France,Male,28,2,0,1,0,0,98060.51,0 +8409,15583736,Shih,829,Germany,Male,36,4,81795.74,2,1,0,90106.94,0 +8410,15590011,Hughes,749,Spain,Male,38,9,129378.32,1,1,1,13549.34,0 +8411,15609913,Clark,743,France,Female,46,9,0,1,1,0,113436.08,0 +8412,15719479,Chukwuhaenye,619,Spain,Female,56,7,0,2,1,1,42442.21,0 +8413,15575147,Wall,699,France,Male,22,9,99339,1,1,0,68297.61,1 +8414,15597309,Howell,749,Spain,Male,36,7,0,2,0,0,80134.65,0 +8415,15648367,Lo,600,Germany,Female,29,6,74430.1,2,1,1,96051.1,0 +8416,15758031,Lazarev,760,Spain,Male,38,3,91241.85,1,0,1,80682.35,0 +8417,15751771,Lowe,528,Germany,Male,32,2,99092.45,1,0,1,111149.98,0 +8418,15689288,Folliero,630,France,Female,26,5,0,2,1,0,182612.38,0 +8419,15731026,Han,683,Germany,Female,39,2,100062.16,2,1,0,109201.43,0 +8420,15775809,Holloway,677,Germany,Female,26,6,98723.67,1,0,1,151146.67,0 +8421,15743076,Pai,669,Spain,Male,29,9,0,1,1,1,93901.61,0 +8422,15658258,Trejo,693,France,Male,43,6,128760.32,1,1,0,36342.79,0 +8423,15756321,Johnston,612,Spain,Female,52,5,144772.69,1,0,0,98302.57,1 +8424,15706799,Macknight,719,Spain,Male,44,4,0,1,0,0,84972.9,1 +8425,15775703,Lo,702,France,Male,26,2,71281.29,1,1,1,108747.12,1 +8426,15642636,Glossop,755,France,Male,29,9,117035.89,1,1,1,21862.19,0 +8427,15704651,Bishop,514,France,Male,26,1,0,2,0,0,121551.93,0 +8428,15806771,Yefremova,753,France,Female,40,0,3768.69,2,1,0,177065.24,1 +8429,15566735,Obialo,548,Germany,Female,36,2,108913.84,2,1,1,140460.01,0 +8430,15681671,Nkemjika,850,Germany,Male,28,2,101100.22,2,1,1,35337.31,0 +8431,15775949,Trevisani,612,France,Female,38,7,110615.47,1,1,1,193502.93,0 +8432,15586752,Parkes,628,Germany,Male,33,8,152143.89,1,1,1,32174.03,0 +8433,15582519,Seleznyov,479,France,Male,47,6,121797.09,1,0,1,5811.9,1 +8434,15658233,Naylor,724,France,Female,41,5,109798.25,1,0,1,149593.61,0 +8435,15755330,Forbes,512,Germany,Male,41,7,122403.24,1,0,1,37439.9,1 +8436,15605072,Douglas,638,France,Female,43,3,145860.98,1,1,1,142763.51,1 +8437,15617538,Nwankwo,834,Spain,Male,40,7,0,2,0,0,45038.74,0 +8438,15591428,Myers,781,France,Male,29,9,0,2,0,0,172097.4,0 +8439,15692142,Rogova,707,Germany,Female,48,7,105086.74,1,1,1,180344.69,1 +8440,15692931,Hsing,670,France,Male,22,2,114991.45,1,1,1,37392.56,0 +8441,15781127,Giordano,663,Spain,Female,33,8,96769.04,1,1,1,36864.05,0 +8442,15677136,Okwukwe,624,France,Female,23,5,0,2,0,0,132418.59,0 +8443,15677828,Chalmers,598,France,Female,34,4,0,2,0,0,60894.26,0 +8444,15567897,Chiazagomekpere,619,Germany,Male,23,5,132725.1,1,1,1,143913.33,0 +8445,15793641,Evseyev,792,France,Female,70,3,0,2,1,1,172240.27,0 +8446,15678333,Parry-Okeden,683,France,Female,26,7,0,2,1,0,86619.77,0 +8447,15630511,Picot,691,France,Female,33,6,0,2,1,0,164074.89,0 +8448,15792627,Reid,765,Spain,Female,33,5,84557.82,1,1,1,69039.43,0 +8449,15717191,Ferri,508,France,Male,49,1,93817.41,2,1,1,132468.76,1 +8450,15625716,Genovesi,637,France,Female,33,9,113913.53,1,0,1,65316.5,0 +8451,15710053,Neumayer,667,Germany,Female,44,5,140406.68,2,0,1,57164.19,0 +8452,15580043,Murray,575,Spain,Female,22,8,105229.34,1,1,1,34397.08,0 +8453,15601410,Tien,744,Spain,Female,46,1,0,3,1,1,177431.59,1 +8454,15684669,Parkes,567,France,Female,41,9,137891.35,1,1,0,142009.46,1 +8455,15619083,Yip,502,France,Female,35,6,0,2,1,1,80618.47,0 +8456,15692207,Ingle,609,France,Female,53,6,0,2,1,1,124218.27,0 +8457,15730705,Chidubem,715,France,Male,37,9,165252.52,1,1,0,85286.3,0 +8458,15749688,Lu,541,France,Male,32,8,0,2,0,0,40889.14,0 +8459,15728542,Vorobyova,850,France,Female,71,4,0,2,1,1,107236.87,0 +8460,15760063,Chiedozie,595,Spain,Male,23,7,0,2,1,1,168085.97,0 +8461,15658982,Napolitani,650,Germany,Female,28,5,122034.4,3,0,1,146663.43,1 +8462,15758769,Coffey,625,France,Female,44,7,0,1,1,0,4791.8,0 +8463,15778481,Chigbogu,817,France,Male,59,1,118962.58,1,1,1,120819.58,0 +8464,15661162,Akabueze,526,Spain,Male,49,2,0,1,1,0,114539.67,1 +8465,15568164,Istomin,850,France,Female,34,4,71379.53,2,1,1,154000.99,0 +8466,15601569,Ndubueze,598,France,Female,40,2,171178.25,1,1,0,137980.58,1 +8467,15772383,Toscani,613,France,Male,36,9,131307.11,1,0,0,83343.73,0 +8468,15667456,Ross,709,Spain,Male,62,3,0,2,1,1,82195.15,0 +8469,15672983,Fernando,678,Spain,Female,27,5,87099.85,2,1,0,149550.95,0 +8470,15799534,McClaran,720,France,Male,71,5,183135.39,2,1,1,197688.5,0 +8471,15582847,Yermakova,662,France,Male,26,0,0,2,0,1,72929.96,0 +8472,15612478,Somadina,525,France,Male,51,10,0,3,1,0,171045.35,1 +8473,15709621,Wan,662,France,Male,31,3,0,2,0,1,27731.05,0 +8474,15802009,Mazzi,770,France,Female,33,6,0,2,1,1,126131.9,0 +8475,15698816,Tuan,721,Spain,Female,33,4,72535.45,1,1,1,103931.49,0 +8476,15574830,Townsley,633,Germany,Male,58,2,128137.42,2,1,0,147635.33,1 +8477,15603082,Yashina,701,France,Male,51,9,0,2,0,0,61961.57,0 +8478,15685947,Henderson,556,Germany,Male,42,0,115915.53,2,0,1,125435.47,1 +8479,15643048,Mueller,639,France,Male,66,0,0,2,0,1,42240.54,0 +8480,15807568,Wright,632,France,Male,50,2,0,2,0,0,57942.88,0 +8481,15597591,Lung,456,France,Male,29,5,107000.49,1,1,1,153419.62,0 +8482,15747558,Bryant,729,Spain,Female,38,10,0,2,1,0,189727.12,0 +8483,15756655,Madukaife,632,France,Female,34,2,0,2,0,0,165385.55,0 +8484,15589949,Maclean,433,Spain,Male,34,9,152806.74,1,1,0,19687.99,0 +8485,15601012,Abdullah,802,France,Female,60,3,92887.06,1,1,0,39473.63,1 +8486,15724269,Yao,670,France,Male,25,7,0,2,1,1,144723.38,0 +8487,15567506,Cheatham,738,Germany,Female,40,6,114940.67,2,1,1,194895.57,1 +8488,15791877,Gallagher,706,Germany,Male,34,0,140641.26,2,1,1,77271.91,0 +8489,15794360,Hao,592,Germany,Female,70,5,71816.74,2,1,0,105096.82,1 +8490,15686538,Nixon,522,France,Female,41,7,0,2,0,1,176780.39,0 +8491,15585985,Wang,746,France,Male,48,5,165282.42,1,1,0,153786.46,1 +8492,15699257,Kerr,651,Spain,Male,42,2,143145.87,2,1,0,43612.06,0 +8493,15804104,Romani,494,France,Male,28,9,114731.76,2,0,1,79479.74,0 +8494,15727619,Lock,753,Germany,Female,46,9,113909.69,3,1,0,92320.37,1 +8495,15740237,Millar,671,Germany,Male,36,2,116695.27,1,0,0,193201.86,0 +8496,15801436,K'ung,696,France,Male,42,4,0,1,0,0,126353.13,1 +8497,15705735,Onyekachi,577,Spain,Male,43,3,0,2,1,1,135008.92,0 +8498,15649359,Somayina,587,France,Male,36,1,0,2,0,1,17135.6,0 +8499,15624892,Dennis,712,Germany,Male,37,7,93978.96,2,1,0,60651.77,0 +8500,15784918,Brown,498,Germany,Male,35,2,121968.11,2,0,1,188343.05,0 +8501,15584785,Ogochukwu,660,France,Male,37,2,97324.91,1,1,0,23291.83,0 +8502,15797197,Macleod,678,Spain,Male,29,6,0,2,1,0,64443.75,0 +8503,15574858,Page,530,France,Male,37,8,0,2,1,1,287.99,0 +8504,15794101,Barese,559,France,Female,48,2,0,2,0,1,137961.41,0 +8505,15743245,Agafonova,624,France,Male,42,3,145155.37,1,1,0,72169.95,1 +8506,15791535,Caraway,592,France,Male,28,5,137222.77,1,0,0,39608.58,0 +8507,15605215,Stevenson,767,France,Male,48,9,0,2,0,1,175458.21,0 +8508,15771749,Duncan,653,Germany,Female,38,5,114268.22,2,1,1,89524.83,0 +8509,15616833,Wang,678,Spain,Male,27,2,0,2,1,1,13221.25,0 +8510,15750728,Kaur,586,Spain,Female,42,2,0,1,1,0,102889.34,0 +8511,15769353,Jenkins,550,France,Female,40,8,150490.32,1,0,0,166468.21,1 +8512,15770091,Edwards,643,Germany,Male,28,9,160858.13,2,1,0,27149.27,0 +8513,15716420,Kelly,612,Spain,Male,39,5,170288.38,1,1,1,59601.15,0 +8514,15740602,Boyle,674,Germany,Female,27,4,111568.01,1,0,1,22026.18,0 +8515,15796071,Loane,657,Spain,Male,29,7,83889.03,1,1,0,153059.62,0 +8516,15811389,Padovano,724,Germany,Female,35,0,171982.95,2,0,1,167313.07,0 +8517,15783875,Li Fonti,500,France,Female,34,4,0,2,1,0,12833.96,0 +8518,15671800,Robinson,688,France,Male,20,8,137624.4,2,1,1,197582.79,0 +8519,15677288,Geach,599,France,Male,50,3,121159.65,1,0,0,4033.39,1 +8520,15633525,Payne,631,France,Male,29,7,0,2,0,1,125877.22,0 +8521,15634606,Chinonyelum,634,Spain,Male,52,1,0,2,1,1,176913.42,0 +8522,15579207,Watkins,545,France,Male,37,3,91184.01,1,1,0,105476.65,0 +8523,15619892,Page,644,Spain,Male,18,8,0,2,1,0,59172.42,0 +8524,15567778,Genovese,690,Germany,Female,54,1,144027.8,1,1,1,108731.02,1 +8525,15711750,Watson,711,France,Female,34,6,0,2,1,1,175310.38,0 +8526,15751084,Mancini,712,France,Female,29,8,140170.61,1,1,1,38170.04,0 +8527,15768945,Chibueze,627,France,Male,27,1,62092.9,1,1,1,105887.04,0 +8528,15586931,Hunter,694,Spain,Male,39,3,0,1,1,1,95625.03,0 +8529,15636353,Buchi,534,Spain,Male,35,4,0,2,0,0,9541.15,0 +8530,15623858,Charteris,603,France,Male,45,9,0,1,0,0,148516.79,0 +8531,15703354,Aksenov,808,France,Female,33,2,103516.87,1,1,0,113907.8,0 +8532,15663987,Wright,723,Spain,Male,30,1,0,3,1,0,164647.72,1 +8533,15780805,Lu,585,France,Female,35,2,0,2,1,0,98621.04,1 +8534,15768566,K?,706,France,Male,34,8,0,2,1,1,37479.97,0 +8535,15643229,Hou,671,France,Female,31,6,0,2,1,1,15846.42,0 +8536,15754940,Descoteaux,597,Spain,Male,43,2,85162.26,1,0,1,5104.08,1 +8537,15676576,Stephenson,646,France,Female,43,8,143061.88,1,1,0,61937.6,0 +8538,15800068,Cooper,801,Spain,Female,46,6,0,2,1,1,170008.74,0 +8539,15648030,Crump,731,Spain,Female,33,5,137388.01,2,1,0,165000.68,0 +8540,15668594,Diggs,620,Germany,Female,25,1,137712.01,1,1,1,76197.05,0 +8541,15728709,Shih,484,Germany,Male,40,7,106901.42,2,0,0,118045.98,0 +8542,15724181,Hudson,647,Spain,Male,47,5,105603.21,2,1,1,157360.9,0 +8543,15647546,Carvosso,688,Germany,Female,40,8,150679.71,2,0,1,196226.38,0 +8544,15702601,Wyatt,680,Germany,Male,30,4,108300.27,2,0,1,44384.57,1 +8545,15567725,Kodilinyechukwu,689,France,Female,46,7,52016.08,2,1,1,72993.65,0 +8546,15674179,Vorobyova,513,Germany,Male,34,7,60515.13,1,0,0,124571.09,0 +8547,15686957,Piccio,553,Germany,Male,35,2,158584.28,2,1,0,43640.16,0 +8548,15607690,Hsing,689,Germany,Male,47,2,118812.5,2,0,0,31121.42,0 +8549,15806546,Lucas,517,Spain,Male,46,4,0,1,1,0,22372.78,0 +8550,15632850,T'ang,731,France,Male,37,8,0,2,1,1,170338.35,0 +8551,15709016,North,687,Germany,Female,47,1,91219.29,1,0,0,158845.49,1 +8552,15638068,Thompson,507,Spain,Male,32,7,0,2,1,0,67926.18,0 +8553,15749345,Simpson,468,France,Female,22,1,76318.64,1,1,1,194783.12,0 +8554,15791321,Nwora,682,Spain,Female,58,4,0,1,1,0,176036.01,0 +8555,15699095,Chandler,603,France,Female,24,3,0,1,1,1,198826.03,1 +8556,15638329,Uspensky,522,Germany,Male,25,1,111432.13,1,1,1,168683.57,0 +8557,15575445,Ferguson,629,Spain,Male,41,10,150148.51,1,0,0,6936.27,0 +8558,15752622,Kerr,729,France,Female,32,7,38550.06,1,0,1,179230.23,0 +8559,15774507,Furneaux,574,France,Female,39,5,119013.86,1,1,0,103421.91,0 +8560,15570857,Kambinachi,677,Germany,Female,39,0,111213.64,2,1,1,147578.26,0 +8561,15599386,Black,627,Germany,Male,28,5,71097.23,1,1,1,130504.49,0 +8562,15744913,Chizoba,788,Spain,Male,36,10,109632.85,1,1,1,16149.13,0 +8563,15647292,Peng,697,France,Male,63,7,148368.02,1,0,0,118862.08,1 +8564,15728838,Leach,578,France,Male,45,1,148600.91,1,1,0,143397.14,1 +8565,15584704,Chiazagomekpele,519,France,Male,48,10,71083.98,1,1,0,137959,0 +8566,15749068,Nickson,632,France,Female,40,9,139625.34,1,1,0,93702.96,1 +8567,15622985,Lin,679,France,Female,39,4,0,1,0,0,172939.3,1 +8568,15587676,Alexeieva,699,France,Male,30,9,0,1,1,1,108162.13,0 +8569,15779496,Sykes,615,France,Male,64,0,81564.1,2,0,1,35896.09,0 +8570,15733460,Martin,622,Spain,Male,36,9,0,2,1,1,104852.6,0 +8571,15711457,Herz,755,France,Female,28,7,124540.28,1,0,1,188850.89,0 +8572,15795290,Nikitina,767,France,Female,42,2,133616.39,1,1,0,28615.8,0 +8573,15611223,Ko,752,Germany,Female,38,10,101648.5,2,1,0,172001.44,0 +8574,15794159,Highett,633,France,Female,26,8,124281.84,1,1,1,60116.57,0 +8575,15780677,Jackson,717,France,Female,59,4,0,2,1,1,170528.63,0 +8576,15690175,Ball,585,Spain,Male,45,0,0,2,0,0,189683.7,0 +8577,15722599,Nelson,751,France,Female,37,9,183613.66,2,0,0,49734.94,0 +8578,15569976,Woronoff,754,Germany,Male,65,1,136186.44,1,1,1,121529.59,1 +8579,15707011,Morrison,495,France,Male,47,10,137682.68,1,1,0,71071.47,0 +8580,15702277,Smith,650,France,Male,34,4,106005.54,1,0,1,142995.32,0 +8581,15801915,Rendall,529,France,Female,31,6,152310.55,1,1,0,13054.25,0 +8582,15580213,McIntyre,585,France,Female,43,2,0,2,1,0,89402.54,0 +8583,15637947,Wei,668,Spain,Male,32,1,134446.04,1,0,1,111241.37,0 +8584,15715888,Allardyce,591,France,Female,38,2,142289.28,1,0,1,119638.85,0 +8585,15732967,Cremonesi,731,France,Male,19,6,0,2,1,1,151581.79,0 +8586,15737047,Weatherford,754,France,Female,45,6,0,1,1,0,73881.68,1 +8587,15694039,Jen,650,Germany,Female,46,9,149003.76,2,1,0,176902.83,0 +8588,15649457,Macleod,588,Germany,Male,41,2,131341.46,2,0,1,7034.94,0 +8589,15742809,Mironova,712,Spain,Female,29,7,77919.78,1,1,0,122547.58,0 +8590,15637829,Sharpe,691,France,Female,34,7,0,2,0,1,161559.12,0 +8591,15633194,Osborne,771,France,Female,41,10,108309,4,1,1,137510.41,1 +8592,15611635,Chu,678,Spain,Female,39,6,0,1,0,1,185366.56,0 +8593,15638774,Chong,719,Spain,Female,40,9,0,2,1,0,182224.14,0 +8594,15722037,Alvarez,610,Germany,Male,36,7,115462.02,1,0,1,42581.04,0 +8595,15672930,Palerma,722,Spain,Male,37,9,0,2,1,0,31921.95,0 +8596,15668774,Chiemenam,758,Germany,Female,23,5,122739.1,1,1,0,102460.84,1 +8597,15780966,Pritchard,709,France,Female,32,2,0,2,0,0,109681.29,0 +8598,15659694,Wallis,634,Germany,Female,53,3,113781.5,2,1,1,106345.05,1 +8599,15624424,Palerma,678,Spain,Female,49,1,0,2,1,1,102472.9,0 +8600,15708713,Hill,633,France,Male,35,3,0,2,1,1,36249.76,0 +8601,15755405,Hudson,710,France,Male,43,9,128284.45,1,1,0,32996.89,1 +8602,15647570,Chung,640,Germany,Male,45,8,120591.19,1,0,0,195123.94,0 +8603,15684348,Zhdanova,656,France,Male,63,8,0,2,0,1,57014.43,0 +8604,15702541,Fraser,551,France,Female,59,2,166968.28,1,1,0,159483.76,1 +8605,15646942,Meng,786,Spain,Female,39,7,0,2,0,0,100929.59,0 +8606,15748920,Cherkasova,561,France,Female,49,8,0,2,1,1,12513.07,0 +8607,15694581,Rawlings,807,Spain,Male,42,5,0,2,1,1,74900.9,0 +8608,15643215,Jen,602,Germany,Male,38,2,71667.97,2,0,0,137111.89,0 +8609,15649060,Chien,727,Germany,Female,31,3,82729.47,2,1,0,60212.51,0 +8610,15774258,Gorbunov,678,France,Male,40,1,0,2,1,1,187343.4,0 +8611,15731553,Lucas,730,France,Male,23,8,0,2,1,0,183284.53,0 +8612,15617029,Young,596,Spain,Female,30,1,0,2,1,0,8125.39,0 +8613,15780716,Colombo,686,Germany,Male,39,3,129626.19,2,1,1,103220.56,0 +8614,15577018,Tsao,684,Germany,Female,26,2,114035.39,1,0,0,96885.19,0 +8615,15809515,Lewis,797,Germany,Male,32,1,151922.94,1,1,0,8877.06,0 +8616,15789924,Hussain,658,France,Female,39,4,0,1,1,1,147530.06,0 +8617,15725076,Anderson,653,Spain,Female,27,6,107751.68,2,1,1,33389.42,0 +8618,15672481,Ulyanov,641,France,Male,37,6,0,2,1,0,45309.24,0 +8619,15574115,Shaw,656,Spain,Female,41,6,101179.23,2,1,1,35230.61,0 +8620,15661830,Lucciano,750,Spain,Female,36,6,0,2,1,1,59816.41,0 +8621,15665879,Gordon,768,France,Female,40,8,0,2,0,1,69080.46,0 +8622,15673820,Woodward,568,France,Male,33,7,0,2,1,0,143450.61,0 +8623,15747772,Cunningham,706,Germany,Male,36,9,58571.18,2,1,0,40774.01,0 +8624,15666197,Boni,430,Germany,Female,38,8,153058.64,1,1,0,99377.27,0 +8625,15773639,Truscott,745,Germany,Male,35,4,98270.34,1,1,0,133617.43,0 +8626,15581893,Ginikanwa,747,France,Male,43,1,130788.71,1,0,1,101495,1 +8627,15672447,Bailey,657,Germany,Male,40,7,99165.84,1,0,1,119333.95,1 +8628,15777830,Hutchinson,639,France,Female,42,4,0,2,0,0,167682.37,0 +8629,15713890,Maclean,704,France,Male,44,3,0,2,0,1,152884.85,0 +8630,15577598,Chiang,651,Spain,Male,23,4,115636.05,2,1,0,70400.86,0 +8631,15786042,Willmore,706,Germany,Female,44,2,185932.18,2,1,0,65413.41,0 +8632,15753462,Godson,632,Germany,Male,30,2,72549,2,0,1,182728.8,0 +8633,15759690,Smith,751,France,Male,42,4,0,2,1,1,81442.6,0 +8634,15801414,Bitter,767,France,Female,35,2,0,2,0,0,144251.38,0 +8635,15656141,Ts'ao,741,France,Male,39,5,0,1,0,1,40207.06,0 +8636,15608701,Chialuka,651,Germany,Male,29,3,121890.06,1,1,0,54530.51,1 +8637,15582892,Scott,601,France,Male,46,2,99786.07,1,1,1,32683.88,1 +8638,15632967,Feng,520,France,Male,34,3,0,2,1,1,104703.96,0 +8639,15587573,Castiglione,626,Germany,Male,27,4,115084.53,2,0,1,26907.43,0 +8640,15654891,He,811,France,Male,30,6,0,2,1,1,180591.32,0 +8641,15611365,Fanucci,730,France,Female,32,9,127661.69,1,0,0,60905.51,0 +8642,15749103,Ginikanwa,604,Germany,Female,47,4,118907.6,1,0,1,47777.15,1 +8643,15810203,Manning,499,Germany,Female,44,6,77627.33,2,1,0,108222.68,0 +8644,15813660,Forlonge,754,Spain,Male,40,2,160625.17,1,0,1,3554.63,0 +8645,15605673,Liang,716,Spain,Female,29,8,0,2,0,0,78616.92,0 +8646,15669282,Uchechukwu,636,France,Female,20,10,124266.86,1,0,0,100566.81,0 +8647,15792726,Sung,470,France,Female,25,8,127974.06,2,1,1,183259.35,0 +8648,15593241,Tochukwu,444,France,Male,43,3,0,2,1,1,159131.21,0 +8649,15683053,Reyna,809,Spain,Female,48,2,0,1,1,0,160976.85,1 +8650,15632736,Liang,850,Germany,Female,30,3,104911.35,2,1,1,42933.26,0 +8651,15731865,Unwin,637,France,Male,27,1,0,2,1,0,91291.2,0 +8652,15760450,Rutherford,512,France,Male,43,1,0,2,1,1,52471.36,0 +8653,15787204,Howe,774,Spain,Female,43,1,110646.54,1,0,0,108804.28,0 +8654,15650454,Tran,641,France,Male,57,5,0,2,1,1,122449.18,0 +8655,15573730,Thompson,586,Germany,Male,42,6,126704.49,2,1,0,41682.3,0 +8656,15705050,Linger,611,France,Male,30,9,0,2,1,1,148887.69,0 +8657,15791342,Johnston,660,Spain,Male,31,1,84560.04,1,1,1,137784.25,0 +8658,15684316,Udokamma,532,France,Male,43,9,0,2,0,0,190573.91,1 +8659,15700540,Barrera,557,Germany,Female,38,2,129893.56,1,0,0,102076.03,0 +8660,15770631,Sutherland,730,Spain,Male,25,5,167385.81,1,1,1,56307.51,0 +8661,15790594,Bednall,535,France,Female,27,6,0,2,0,1,49775.58,0 +8662,15604020,Otoole,773,Germany,Female,36,4,105858.71,1,0,1,4395.45,0 +8663,15637599,Cremonesi,510,Germany,Female,44,4,123070.89,1,1,0,28461.29,1 +8664,15736578,Hamilton,539,France,Male,39,1,0,1,1,1,28184.7,0 +8665,15666332,Donaldson,690,Spain,Female,48,2,0,2,1,1,3149.1,0 +8666,15727291,McKay,821,France,Female,40,1,0,2,1,0,194273.12,0 +8667,15785920,Black,687,Germany,Male,35,1,125141.24,2,1,1,148537.07,0 +8668,15658987,Kane,557,France,Female,46,4,96173.17,2,1,1,116378.31,0 +8669,15687719,She,532,Spain,Female,37,5,0,2,0,1,6761.84,0 +8670,15799641,Bruno,540,Spain,Male,39,2,0,2,1,0,81995.92,0 +8671,15758702,Watson,705,France,Female,55,8,0,2,1,1,14392.68,0 +8672,15689526,Shih,542,Germany,Female,35,9,127543.11,2,1,0,468.94,1 +8673,15586848,Rose,706,France,Male,38,1,0,2,1,0,122379.54,0 +8674,15707637,Zikoranachukwudimma,765,France,Female,56,1,0,1,1,0,13228.93,1 +8675,15719426,Cole,529,France,Male,67,8,103101.56,2,1,1,154002.02,1 +8676,15639265,Isaacs,714,France,Male,54,7,126113.28,1,1,0,112777.38,0 +8677,15576124,Muravyova,582,France,Male,41,1,40488.76,1,1,0,128528.83,0 +8678,15757829,Timperley,609,Germany,Female,40,10,137389.77,2,1,0,170122.22,0 +8679,15633227,Kenechukwu,518,France,Female,28,9,85146.36,1,0,0,2803.89,0 +8680,15753092,He,791,Germany,Male,35,5,129828.58,1,1,1,181918.26,1 +8681,15782939,Storey,747,France,Male,42,4,80214.36,1,1,0,115241.96,1 +8682,15746338,Onyekachukwu,565,France,Female,40,2,0,2,1,1,129956.13,0 +8683,15590676,Kharlamova,735,France,Male,34,1,141796.43,1,1,0,45858.49,0 +8684,15599329,Christopher,697,France,Female,49,7,195238.29,4,0,1,131083.56,1 +8685,15783097,Lombardo,813,Germany,Male,27,6,111348.15,1,1,0,46422.46,0 +8686,15597885,Kerr,772,France,Male,43,6,0,2,1,1,57675.88,0 +8687,15597467,Duncan,606,France,Female,71,8,0,2,1,1,169741.96,0 +8688,15724764,Lawley,667,Germany,Female,42,10,64404.26,2,0,0,26022.37,0 +8689,15778418,Burns,637,Germany,Male,40,9,154309.67,1,1,1,125334.16,1 +8690,15684769,Whitson,542,France,Male,67,10,129431.36,1,0,1,21343.74,0 +8691,15756167,Doyne,762,Spain,Female,43,5,134204.67,1,1,1,139971.01,0 +8692,15632439,Pinto,698,France,Female,39,4,0,2,0,1,47455.82,0 +8693,15755138,Chin,850,France,Female,32,8,0,2,1,1,55593.8,0 +8694,15659092,Davide,621,France,Female,50,5,0,2,1,0,191756.54,1 +8695,15742116,Torres,671,Germany,Female,48,9,116711.06,2,0,0,76373.38,0 +8696,15801994,Buccho,775,France,Male,31,9,0,2,1,0,169278.51,0 +8697,15647572,Greece,504,Spain,Male,34,0,54980.81,1,1,1,136909.88,0 +8698,15644551,Wimble,751,Spain,Female,37,3,99773.85,2,1,0,54865.92,0 +8699,15709135,Pirozzi,691,Germany,Male,30,7,101231.77,2,0,0,156529.44,0 +8700,15684469,Hsiung,841,Germany,Male,32,2,117070.21,1,1,0,113482.2,0 +8701,15627637,Obioma,709,Germany,Male,23,8,73314.04,2,1,0,63446.47,0 +8702,15667093,Onio,673,France,Male,37,2,0,1,1,1,13624.02,0 +8703,15690589,Udinesi,541,France,Male,37,9,212314.03,1,0,1,148814.54,0 +8704,15595350,Fermin,661,France,Female,31,3,136067.82,2,1,0,65567.91,0 +8705,15777586,Moss,784,Spain,Female,42,2,109052.04,2,1,0,6409.55,0 +8706,15804064,Docherty,742,France,Female,35,2,79126.17,1,1,1,126997.53,0 +8707,15717770,Marcelo,850,Spain,Female,55,7,0,1,0,0,171762.87,1 +8708,15754443,Fadden,443,France,Female,35,9,108308,1,1,0,129031.19,1 +8709,15776939,Zox,778,Germany,Female,48,3,102290.56,2,1,0,182691.31,0 +8710,15713517,Otitodilinna,529,France,Male,39,6,102025.08,2,1,0,12351.01,0 +8711,15683522,Kennedy,678,Germany,Female,37,2,113383.07,1,1,1,135123.96,0 +8712,15673995,Tu,516,Spain,Female,65,9,102541.1,1,1,0,181490.42,0 +8713,15771054,Barnes,469,Spain,Male,35,5,0,2,1,0,186490.37,0 +8714,15578788,Bibi,786,Spain,Male,40,6,0,2,0,0,41248.8,0 +8715,15737408,L?,703,France,Female,41,6,109941.51,1,1,0,116267.28,0 +8716,15750837,Landseer,579,Germany,Male,41,0,141749.68,1,0,1,9201.53,0 +8717,15576022,Nwachinemelu,565,France,Male,38,5,0,2,0,1,80630.32,0 +8718,15635502,Ch'iu,443,France,Male,44,2,0,1,1,0,159165.7,0 +8719,15627298,Vinogradova,589,France,Male,37,7,85146.48,2,1,0,86490.09,1 +8720,15811415,Jenks,691,France,Female,44,6,134066.1,2,1,1,197572.41,0 +8721,15645059,Crace,711,France,Female,28,8,0,2,0,0,105159.89,0 +8722,15689671,Packham,775,Spain,Male,27,4,0,1,1,1,40807.26,0 +8723,15718667,T'ien,621,France,Male,35,7,87619.29,1,1,0,143.34,0 +8724,15803202,Onyekachi,350,France,Male,51,10,0,1,1,1,125823.79,1 +8725,15593683,Solomina,668,Spain,Female,30,8,0,2,1,0,138465.7,0 +8726,15703394,Hawes,633,Spain,Male,27,3,0,2,1,0,44008.91,0 +8727,15570289,Benson,697,Germany,Male,43,8,103409.16,1,1,0,66893.28,1 +8728,15567437,Emenike,734,Germany,Female,30,7,123040.38,1,1,1,76503.06,0 +8729,15711687,Nero,434,France,Male,41,4,108128.52,1,0,1,56784.11,0 +8730,15656592,Toscano,646,Germany,Male,48,8,169023.33,2,1,1,175657.55,0 +8731,15634373,Yang,764,France,Male,30,5,0,2,0,1,105155.66,0 +8732,15769125,Palerma,727,Spain,Female,41,10,0,2,0,1,47468.56,0 +8733,15711386,Trentini,724,France,Female,29,6,0,2,0,1,64729.51,0 +8734,15714241,Haddon,749,Spain,Male,42,9,222267.63,1,0,0,101108.85,1 +8735,15642530,Coates,706,Germany,Female,47,10,144090.42,1,1,0,140938.95,1 +8736,15713599,Castiglione,728,France,Male,30,10,114835.43,1,0,1,37662.49,0 +8737,15744770,Stone,636,France,Male,44,2,0,2,0,0,86414.41,0 +8738,15780498,Maynard,634,France,Male,34,3,145030.92,1,1,1,41820.65,0 +8739,15624397,Moore,627,France,Male,43,8,71240.3,1,0,1,127734.16,0 +8740,15615219,Obielumani,518,France,Male,59,5,138772.15,1,0,1,123872,0 +8741,15570908,Harding,687,Spain,Female,29,7,93617.07,1,0,1,113050.92,0 +8742,15762855,Hill,622,Spain,Female,23,8,0,2,1,1,131389.39,0 +8743,15661827,Brown,693,Spain,Female,45,4,0,2,1,1,26589.56,0 +8744,15746035,Pagnotto,450,Spain,Male,25,9,74237.2,2,0,1,195463.35,0 +8745,15691906,Esposito,664,Germany,Female,49,5,127421.78,2,1,0,108876.75,1 +8746,15793424,Tan,663,Spain,Female,28,8,61274.7,2,1,0,136054.45,0 +8747,15577905,Hammond,660,France,Male,34,8,106486.66,2,0,1,182262.66,0 +8748,15667216,Chung,579,France,Female,29,10,73194.52,2,1,1,129209.09,0 +8749,15673971,Houghton,655,Germany,Female,44,6,146498.76,1,1,0,64853.51,1 +8750,15701238,Chia,683,France,Male,47,1,0,2,1,0,148989.15,0 +8751,15644849,Zikoranachidimma,655,France,Female,32,2,0,1,1,1,71047.51,0 +8752,15635531,Boag,575,Spain,Female,30,8,0,2,1,0,185341.63,0 +8753,15632263,Pagnotto,574,Spain,Male,30,5,120355,1,1,0,137793.35,0 +8754,15720110,Oluchukwu,795,France,Male,32,2,117265.21,1,1,1,198317.23,0 +8755,15619045,Baxter,776,France,Female,43,4,0,2,0,1,162137.5,0 +8756,15697510,Tien,707,Spain,Female,52,7,0,1,1,0,109688.82,1 +8757,15784923,Chimezie,705,Germany,Female,37,3,109974.22,1,1,1,36320.87,1 +8758,15567383,Slone,678,Germany,Female,44,2,98009.13,2,0,1,31384.86,0 +8759,15732621,Martin,663,France,Male,34,10,0,1,1,1,114083.73,0 +8760,15757981,Loggia,748,France,Male,66,8,0,1,1,1,163331.65,0 +8761,15727819,Hartley,677,Spain,Female,34,10,171671.9,1,1,1,50777.77,0 +8762,15738088,Parkin,634,Spain,Male,63,10,0,2,1,0,30772.86,1 +8763,15765173,Lin,350,France,Female,60,3,0,1,0,0,113796.15,1 +8764,15665159,Brooks,727,France,Male,61,0,128213.96,2,1,1,188729.08,1 +8765,15618203,Tien,773,Germany,Male,51,8,116197.65,2,1,1,86701.4,0 +8766,15791452,Dann,675,France,Male,39,1,0,2,1,0,153129.22,0 +8767,15638159,Trentino,649,Spain,Female,36,6,86607.39,1,0,0,19825.09,0 +8768,15585466,Russo,552,France,Male,29,10,0,2,1,0,12186.83,0 +8769,15677310,Christie,761,Germany,Male,62,5,98854.34,1,0,0,86920.97,1 +8770,15646262,Ross,622,France,Male,31,7,0,1,1,0,35408.77,0 +8771,15656901,Nnonso,615,France,Male,59,8,0,2,1,1,165576.55,0 +8772,15621093,Teng,681,Germany,Male,31,4,97338.19,2,0,0,48226.76,0 +8773,15592123,Buccho,768,France,Male,30,6,0,2,1,1,199454.37,0 +8774,15589200,Madukaife,617,Spain,Male,34,9,0,2,1,0,118749.58,0 +8775,15602934,Dunn,452,France,Female,33,6,131698.57,2,1,0,151623.91,0 +8776,15812720,Hooker,807,Germany,Male,37,10,130110.45,2,0,1,172097.95,0 +8777,15695383,Griffin,567,Spain,Male,44,9,0,2,1,0,87677.15,0 +8778,15723064,Kistler,603,Spain,Male,24,1,165149.13,2,1,0,21858.28,0 +8779,15761606,Law,617,Spain,Female,37,9,101707.8,1,1,0,123866.28,0 +8780,15650322,Grigoryeva,701,France,Female,34,3,105588.66,1,0,1,74694.41,0 +8781,15669782,Chu,820,Germany,Male,39,9,111336.89,1,1,0,16770.31,1 +8782,15751628,Onyemachukwu,438,France,Male,60,7,78391.17,1,0,1,49424.6,0 +8783,15809057,Lu,600,Spain,Female,27,6,0,2,1,1,172031.22,0 +8784,15617052,Watson,782,France,Male,34,9,0,1,1,0,183021.06,1 +8785,15590810,Fallaci,638,Germany,Female,41,9,144326.09,1,1,0,73979.85,1 +8786,15801293,Ni,850,Germany,Male,27,1,101278.25,2,1,1,26265.18,0 +8787,15770968,Leason,741,Germany,Female,19,8,108711.57,2,1,0,24857.25,0 +8788,15572356,Tsai,689,Spain,Male,73,1,108555.07,1,0,1,167969.15,0 +8789,15603247,Bruner,743,Germany,Female,35,1,146781.24,1,1,0,189307.7,0 +8790,15619116,Wallace,493,France,Female,36,2,0,2,0,1,99770.3,0 +8791,15691792,Young,416,Spain,Male,35,8,0,1,0,0,119712.78,0 +8792,15783276,Forbes,725,France,Female,25,9,0,2,1,1,168607.74,0 +8793,15766137,Muir,497,France,Male,34,2,0,2,1,1,83087.13,0 +8794,15574554,Pugh,537,Germany,Male,66,8,103291.25,2,1,1,130664.79,0 +8795,15578671,Webb,706,Spain,Female,29,1,209490.21,1,1,1,133267.69,1 +8796,15716608,Walker,651,Spain,Male,38,2,0,3,1,0,67029.82,1 +8797,15690670,Cox,720,France,Male,33,2,0,2,0,1,141031.08,0 +8798,15630466,Maclean,797,France,Male,45,8,0,1,0,0,125110.02,0 +8799,15630349,Hollis,543,Spain,Male,23,5,0,2,1,0,117832.39,0 +8800,15803801,Jamieson,454,France,Male,34,4,0,2,1,0,198817.72,0 +8801,15647890,Su,691,France,Male,37,9,149405.18,1,1,1,146411.6,0 +8802,15606115,P'eng,510,France,Female,52,6,191665.21,1,1,1,131312.56,1 +8803,15714642,Hawkins,792,Spain,Female,40,7,0,1,1,0,141652.2,0 +8804,15741181,Ndubuagha,721,France,Male,41,6,135071.12,1,1,1,64477.25,0 +8805,15773973,Hill,765,France,Male,41,2,0,2,0,1,191215.61,0 +8806,15758546,Norton,850,Spain,Male,39,8,0,2,1,1,37090.44,0 +8807,15598940,Achebe,681,Germany,Male,38,6,181804.34,2,1,1,57517.71,0 +8808,15669783,Simpson,586,France,Female,60,3,47020.65,2,0,1,63241.21,1 +8809,15624993,Chiang,753,France,Female,36,7,128518.98,1,1,1,44567.83,1 +8810,15760568,Dalrymple,593,Germany,Female,38,5,142658.04,2,0,1,135337.11,0 +8811,15699047,Chukwuemeka,674,France,Female,21,9,120150.39,2,1,1,33964.03,0 +8812,15616168,Ojiofor,610,France,Female,35,7,81905.95,1,1,1,61623.19,0 +8813,15773146,Rubeo,652,France,Male,26,3,137998.2,2,0,1,168989.77,0 +8814,15770375,Fanucci,850,Germany,Female,26,8,123126.29,1,1,0,74425.41,0 +8815,15589725,Zubarev,740,France,Female,51,4,0,2,1,1,178929.84,0 +8816,15710034,T'ao,637,Germany,Male,43,1,135645.29,2,0,1,101382.86,1 +8817,15800806,Pai,685,Spain,Male,31,7,122449.31,2,1,1,180769.55,0 +8818,15570485,Udegbunam,558,Spain,Male,40,4,161766.87,1,0,0,92378.54,0 +8819,15575391,Claypool,677,France,Female,37,3,0,2,1,1,38252.25,0 +8820,15790750,Manfrin,592,Germany,Male,36,10,123187.51,1,0,1,146111.35,0 +8821,15714832,Baker,652,Germany,Male,36,9,150956.71,1,0,0,72350.17,0 +8822,15619953,Efremov,662,Spain,Female,42,6,105021.28,1,1,0,48242.38,0 +8823,15673929,Chin,543,France,Male,64,4,0,2,1,1,148305.82,0 +8824,15578835,Brookes,675,Spain,Female,50,1,133204.91,1,0,1,8270.06,0 +8825,15752388,Doyle,643,Spain,Female,35,6,0,2,1,1,41549.64,0 +8826,15797081,Ajuluchukwu,611,Germany,Female,49,9,115488.52,2,1,1,138656.81,1 +8827,15570194,Ikemefuna,412,France,Male,29,5,0,2,0,0,12510.53,0 +8828,15580149,Fowler,638,Spain,Male,41,7,0,2,1,0,43889.41,0 +8829,15777708,Liao,824,Spain,Female,38,3,0,2,1,0,192800.25,0 +8830,15769955,Onuora,683,France,Female,40,1,0,2,0,0,75762,0 +8831,15810444,Aksenov,562,Germany,Female,39,6,130565.02,1,1,0,9854.72,1 +8832,15645593,Trevisani,599,France,Female,41,2,91328.71,1,1,0,115724.78,0 +8833,15765345,Wood,753,France,Male,35,4,0,2,1,1,106303.4,0 +8834,15760873,Lombardo,594,France,Male,50,7,81310.34,1,1,1,183868.01,0 +8835,15794178,Walpole,657,France,Male,34,3,107136.6,1,1,0,153895.46,0 +8836,15589361,Chikwendu,716,Spain,Male,34,9,0,1,1,1,66695.71,0 +8837,15662483,Ko,850,France,Male,43,7,0,2,1,1,173851.11,0 +8838,15809736,Steigrad,664,France,Male,46,2,0,1,1,1,177423.02,1 +8839,15731148,Isayeva,558,France,Male,33,0,108477.49,1,1,1,109096.71,1 +8840,15774328,Boni,606,Germany,Male,40,1,144757.97,2,1,1,166656.18,0 +8841,15646969,Anayolisa,776,Spain,Male,33,2,0,2,1,1,176921,0 +8842,15718769,Fallaci,557,Spain,Male,36,1,113110.26,1,1,0,98413.1,0 +8843,15610226,Fenton,614,France,Female,27,9,106414.57,2,0,0,77500.81,0 +8844,15616270,Chao,620,Spain,Male,42,4,106920.91,1,0,1,119747.08,0 +8845,15790717,Osinachi,695,Spain,Male,35,7,0,2,1,0,160387.98,0 +8846,15635703,Chu,729,Germany,Female,39,1,131513.26,1,1,1,193715,0 +8847,15616365,Obiuto,571,France,Female,53,2,0,2,1,0,28045.77,0 +8848,15630244,Chu,457,France,Male,40,10,134320.23,2,1,0,150757.35,0 +8849,15734714,Nash,559,France,Female,29,3,79715.36,1,1,0,82252.28,0 +8850,15721433,Hixson,664,France,Female,38,4,74306.19,2,1,0,154395.56,0 +8851,15590201,Fiorentini,500,Spain,Female,50,5,0,4,1,1,83866.35,1 +8852,15590828,Chidimma,782,Germany,Male,42,7,126428.38,1,1,0,39830.1,0 +8853,15752097,Chiazagomekpere,708,Spain,Male,38,8,99640.89,1,1,0,12429.22,0 +8854,15800031,Laura,681,France,Male,43,3,66338.68,1,1,1,18772.5,1 +8855,15630857,Wu,674,Spain,Female,39,6,0,2,1,1,9574.83,0 +8856,15689953,Toscani,697,Spain,Male,43,10,128226.37,1,0,0,188486.94,0 +8857,15759733,McMillan,774,France,Female,26,5,0,2,1,1,64716.08,0 +8858,15810826,Chiekwugo,624,France,Male,36,6,0,2,0,0,84749.96,0 +8859,15668009,Hendley,747,Spain,Male,37,1,0,2,0,1,180551.76,0 +8860,15743456,Birnie,715,France,Female,32,10,0,2,1,0,60907.49,0 +8861,15725762,Kemp,808,France,Male,24,4,122168.65,1,1,0,174107.04,0 +8862,15761713,Johnstone,678,France,Female,43,7,178074.33,1,0,0,110405.9,0 +8863,15769246,Lo Duca,813,Germany,Male,59,2,135078.41,1,1,0,187636.06,1 +8864,15781129,Montgomery,687,Spain,Male,38,8,69434.4,2,1,1,66580.13,1 +8865,15599124,Miller,832,France,Female,29,5,0,2,1,0,178779.52,0 +8866,15639004,Chiemezie,668,France,Male,72,2,0,2,1,1,70783.61,0 +8867,15810995,Wright,526,Germany,Male,34,3,122726.56,1,1,1,46772.36,0 +8868,15653773,Shaw,457,France,Female,38,7,164496.99,1,1,1,163327.27,0 +8869,15708357,Chapman,649,Spain,Female,38,8,0,1,1,0,103760.53,0 +8870,15733597,Y?an,669,France,Female,41,0,150219.41,2,0,0,107839.03,0 +8871,15789560,Clark,668,France,Male,42,8,187534.79,1,1,1,32900.41,1 +8872,15699524,Howells,466,France,Female,30,3,0,1,1,0,193984.6,0 +8873,15626475,Gamble,685,France,Male,30,2,0,2,1,1,140889.32,0 +8874,15810839,Rogers,610,France,Male,34,0,103108.17,1,0,0,125646.82,0 +8875,15684318,McMillan,582,Germany,Female,50,6,96486.57,2,1,1,20344.02,0 +8876,15768120,Brown,702,Germany,Male,36,9,90560.48,2,1,0,174268.87,0 +8877,15712807,Robertson,556,Spain,Male,46,3,131764.96,1,1,1,108500.66,1 +8878,15696371,Thomas,812,Spain,Female,24,1,92476.88,1,0,0,83247.14,0 +8879,15675794,Hsing,645,Germany,Male,47,9,152076.93,1,1,0,121840.2,1 +8880,15774277,Chiu,809,France,Male,43,2,0,2,1,1,132908.07,0 +8881,15603764,Chang,560,France,Male,49,4,0,1,1,1,100075.1,1 +8882,15618647,Kornilova,744,France,Male,29,1,43504.42,1,1,1,119327.75,0 +8883,15614643,Chifo,731,Spain,Female,39,2,0,2,1,0,136737.13,0 +8884,15707696,Lu,471,Spain,Female,28,5,0,2,1,1,22356.97,0 +8885,15749583,Bellucci,686,Germany,Female,38,2,93569.86,3,0,0,10137.34,1 +8886,15815125,Michael,668,Spain,Male,45,4,102486.21,2,1,1,158379.25,0 +8887,15779620,Sinclair,575,France,Male,36,1,0,1,0,1,94570.56,0 +8888,15768233,Chukwuebuka,435,Germany,Male,37,8,114346.3,1,0,1,980.93,1 +8889,15637788,Schmidt,743,France,Male,23,3,110203.77,1,1,0,95583.45,0 +8890,15777046,Parry,580,France,Female,39,9,128362.59,1,1,0,86044.98,0 +8891,15788723,McIntyre,599,Germany,Female,49,10,143888.22,2,1,1,166236.38,1 +8892,15790489,Lo Duca,534,Spain,Male,34,5,170600.78,1,0,1,5240.53,0 +8893,15739476,Ferrari,680,France,Female,32,5,0,1,1,1,150684.23,0 +8894,15612670,Berry,631,Spain,Female,46,10,0,2,1,1,129508.96,0 +8895,15631222,Cattaneo,485,France,Female,39,2,75339.64,1,1,1,70665.16,0 +8896,15658972,Foster,699,France,Female,40,8,122038.34,1,1,0,102085.35,0 +8897,15724691,Gordon,712,France,Male,34,1,0,2,1,1,195052.12,0 +8898,15740442,May,603,France,Male,51,8,186825.57,1,1,0,93739.71,1 +8899,15760427,Cameron,850,France,Male,40,6,124788.18,1,1,0,65612.12,0 +8900,15677939,Ch'eng,584,France,Female,41,3,0,2,1,1,160095.48,0 +8901,15611599,Curtis,604,France,Female,71,2,0,2,1,1,49506.82,0 +8902,15633474,Whitehead,586,France,Male,51,2,138553.57,1,1,1,92406.22,0 +8903,15671973,Chukwuemeka,467,Spain,Male,39,5,0,2,1,1,7415.96,0 +8904,15790019,Onwughara,520,France,Male,35,9,105387.89,1,1,1,25059.06,0 +8905,15737735,Grant,683,Spain,Male,40,4,95053.1,1,1,1,116816.54,1 +8906,15661745,Browne,557,France,Male,36,3,0,1,0,1,144078.02,0 +8907,15797065,Goloubev,613,Spain,Female,32,0,0,2,0,1,126675.62,0 +8908,15710671,Gordon,786,France,Male,34,3,137361.96,1,0,0,183682.09,0 +8909,15656522,Sutherland,593,Spain,Male,32,10,158537.42,1,1,0,166850.57,0 +8910,15705085,Quesada,670,Spain,Female,29,9,0,2,1,0,27359.19,0 +8911,15744873,Wright,657,Germany,Female,48,5,143595.87,1,0,0,101314.65,1 +8912,15781914,Simmons,718,Germany,Male,32,9,169947.41,2,1,1,27979.16,0 +8913,15637354,Yobachukwu,623,France,Female,24,7,148167.83,2,1,1,109470.34,0 +8914,15717307,Read,496,France,Male,31,5,0,2,1,0,93713.13,0 +8915,15746695,Wunder,429,France,Female,39,6,48023.83,1,1,0,74870.99,0 +8916,15804962,Nnaife,606,France,Male,36,1,155655.46,1,1,1,192387.51,1 +8917,15665378,Shen,499,France,Female,46,6,0,2,1,0,73457.55,0 +8918,15757865,Powell,642,France,Male,62,7,0,2,1,1,61120.75,0 +8919,15578787,Goddard,641,France,Female,52,4,0,1,1,0,90964.54,1 +8920,15794323,Buckley,673,France,Male,32,8,121240.76,1,1,0,116969.73,0 +8921,15697546,McIntyre,570,France,Female,36,3,0,2,1,0,92118.75,0 +8922,15629519,Yen,472,France,Female,37,1,0,2,1,1,48357.9,0 +8923,15624703,Okonkwo,550,Germany,Male,35,9,129847.75,2,1,0,197325.4,0 +8924,15570002,Burlingame,625,Germany,Female,55,8,118772.71,4,0,0,135853.62,1 +8925,15808566,Hs?,516,France,Male,46,2,0,2,1,1,169122.54,0 +8926,15805463,Board,682,Germany,Male,32,2,105163.88,2,1,1,164170.46,0 +8927,15709136,Adams,620,France,Male,28,8,0,2,1,1,199909.32,0 +8928,15801605,Rizzo,626,France,Female,39,0,0,2,1,1,83295.09,0 +8929,15567855,Chukwufumnanya,623,France,Female,29,1,0,2,0,0,39382.06,0 +8930,15675141,Fraser,569,France,Female,35,4,93934.63,1,1,0,184748.23,0 +8931,15665759,Russell,724,France,Female,69,5,117866.92,1,1,1,62280.91,0 +8932,15761487,Yefimova,678,France,Female,55,5,0,1,0,1,196794.11,1 +8933,15700394,Palermo,713,Spain,Female,26,4,122857.46,2,1,0,144682.17,1 +8934,15631162,Bergamaschi,631,France,Male,32,10,0,2,0,1,196342.66,0 +8935,15630641,Shao,846,France,Female,37,6,127103.97,1,1,1,41516.44,0 +8936,15585066,Chimaraoke,660,France,Female,43,1,0,1,0,1,112026.1,1 +8937,15722991,McGregor,567,France,Male,54,9,96402.96,1,0,0,52035.29,1 +8938,15737404,Kesteven,731,France,Male,31,1,132512.26,1,1,1,185466.85,0 +8939,15722409,Ritchie,693,Spain,Male,47,8,107604.66,1,1,1,80149.27,0 +8940,15806420,Jenks,772,France,Male,34,9,0,2,1,0,170980.86,0 +8941,15658148,Udokamma,657,France,Male,38,7,0,2,1,0,185827.74,0 +8942,15810660,Boyle,774,Germany,Male,34,4,120875.23,2,0,1,113407.26,0 +8943,15709780,Azuka,667,France,Female,37,9,71786.9,2,1,1,67734.79,0 +8944,15727350,Pai,516,France,Female,37,8,113143.12,1,0,0,3363.36,0 +8945,15752312,Howells,551,Spain,Male,49,1,150777.72,2,1,1,135757.27,0 +8946,15616745,Hs?,542,Spain,Male,35,2,174894.53,1,1,1,22314.55,0 +8947,15572294,Kelly,623,France,Male,28,7,0,1,0,0,129526.57,0 +8948,15674110,Walton,701,France,Female,43,2,160416.56,1,0,1,37266.43,0 +8949,15662501,Ebelechukwu,583,France,Male,48,3,91246.53,1,1,0,60017.46,1 +8950,15649239,Vasilieva,731,Spain,Male,46,10,0,2,1,0,153015.42,0 +8951,15700424,Hsiao,461,France,Female,35,5,0,1,1,1,54209.02,0 +8952,15636388,Abrego,702,Germany,Female,23,7,98775.23,1,1,0,114603.96,0 +8953,15713975,Gibson,565,Germany,Female,47,10,139756.12,1,1,0,165849.49,1 +8954,15592925,Giordano,711,Spain,Male,42,3,177626.77,3,0,1,16392.72,1 +8955,15581626,Mancini,664,France,Male,54,8,0,1,1,1,162719.69,1 +8956,15641319,Afanasyeva,518,Spain,Male,50,4,0,1,0,0,107112.25,1 +8957,15723481,Wright,728,Spain,Male,42,8,0,2,0,1,41823.22,0 +8958,15787825,Okwudiliolisa,585,Germany,Male,37,6,152496.82,1,1,1,99907.29,0 +8959,15710726,Hughes,573,France,Male,52,8,0,2,0,1,178229.04,0 +8960,15627195,Parrott,568,Germany,Male,26,1,112930.28,2,1,0,22095.73,0 +8961,15657957,Hughes,602,Germany,Female,26,8,113674.2,1,1,0,197861.16,1 +8962,15676117,Zinachukwudi,603,France,Male,44,9,0,1,1,0,138328.24,0 +8963,15607874,Keane,687,France,Male,38,0,144450.58,1,0,1,137276.83,0 +8964,15796993,McCollum,741,France,Male,52,1,171236.3,2,0,0,21834.4,1 +8965,15649858,Simpson,469,Spain,Male,37,9,96776.49,1,1,1,119890.86,0 +8966,15811032,Gambrell,477,Germany,Female,58,8,145984.92,1,1,1,24564.7,0 +8967,15679963,Moretti,737,Germany,Male,43,8,96353.8,1,0,0,10209.8,0 +8968,15579131,Ricci,835,France,Male,25,7,0,2,1,1,83449.65,0 +8969,15572428,Rieke,717,Germany,Female,33,0,115777.23,1,1,1,81508.1,0 +8970,15622461,Ndubuagha,562,France,Female,51,7,122822,2,0,0,32626.21,0 +8971,15636105,Chung,758,Spain,Male,61,2,0,2,1,1,43982.41,0 +8972,15583849,Ts'ai,408,France,Male,40,3,0,2,0,0,124874.23,0 +8973,15718780,Cox,650,Spain,Female,32,4,79450.09,1,1,1,118324.75,0 +8974,15739271,Lei,582,Germany,Male,33,2,122394,1,1,1,22113.93,0 +8975,15697129,Ulyanova,706,Spain,Female,43,1,0,2,1,0,31962.77,0 +8976,15763415,Gray,567,Germany,Male,41,0,134378.89,1,1,1,105746.94,0 +8977,15796617,McGregor,720,France,Male,29,2,0,2,1,0,39925.52,0 +8978,15626628,Tretiakova,631,Spain,Female,31,2,88161.85,2,1,0,127630.88,0 +8979,15765857,Genovesi,623,Spain,Male,41,2,142412.13,1,1,0,28778.98,0 +8980,15742511,Gordon,514,France,Male,35,3,121030.9,1,1,0,10008.68,0 +8981,15786433,Aitken,650,Germany,Female,35,3,165982.43,2,1,1,24482.16,0 +8982,15685805,Ginikanwa,673,Spain,Female,35,6,0,2,1,0,98618.79,0 +8983,15627971,Coates,504,France,Female,32,8,206663.75,1,0,0,16281.94,0 +8984,15783025,Piazza,723,Germany,Male,37,3,94661.53,2,1,0,121239.65,0 +8985,15726289,Cawood,645,France,Male,25,0,174400.36,1,1,0,42669.37,0 +8986,15802118,Ignatieff,664,Spain,Male,41,7,123428.69,1,1,1,164924.11,0 +8987,15607990,Gallo,760,Spain,Male,43,6,175735.5,1,1,1,157337.29,0 +8988,15695932,Yelverton,766,Spain,Male,36,5,78381.13,1,0,1,153831.6,0 +8989,15812279,William,634,France,Male,37,5,115345.86,2,0,0,168781.8,0 +8990,15687558,Mault,640,Germany,Female,31,10,118613.34,1,1,0,168469.65,0 +8991,15729065,Mackay,784,Germany,Male,28,2,109960.06,2,1,1,170829.87,0 +8992,15698902,McIntyre,547,Germany,Female,42,1,142703.4,1,1,0,86207.49,1 +8993,15570192,Henry,608,Germany,Female,40,8,121729.42,1,0,0,61164.45,0 +8994,15809265,Kao,547,France,Female,35,4,0,1,1,1,133287.73,0 +8995,15745201,Frewin,612,France,Female,43,4,139496.35,2,1,1,77128.23,0 +8996,15580623,Yefremova,573,Spain,Male,28,8,0,2,0,0,77660.03,0 +8997,15578156,Anenechukwu,615,Spain,Male,32,5,138521.83,1,1,1,56897.1,0 +8998,15631063,Trentino,710,France,Female,33,2,0,2,1,0,72945.32,0 +8999,15692577,Tomlinson,674,Germany,Female,38,10,83727.68,1,1,0,45418.12,0 +9000,15810910,Royston,702,Spain,Female,38,9,0,2,1,1,158527.45,0 +9001,15723217,Cremonesi,616,France,Male,37,9,0,1,1,0,111312.96,0 +9002,15733111,Yeh,688,Spain,Male,32,6,124179.3,1,1,1,138759.15,0 +9003,15610727,Ch'in,605,France,Male,36,7,128829.25,1,1,0,190588.59,0 +9004,15792720,Martinez,676,France,Male,33,6,171490.78,1,0,0,79099.64,0 +9005,15723153,Wearing,708,Spain,Male,33,3,0,2,1,0,138613.21,0 +9006,15802823,Maclean,745,Spain,Female,38,7,0,2,1,1,194230.82,0 +9007,15756118,T'ao,661,Spain,Male,20,8,0,1,1,0,110252.53,0 +9008,15684934,Rose,726,France,Male,31,9,0,2,1,1,106117.3,0 +9009,15776936,Whitworth,475,France,Male,40,7,160818.08,1,0,1,169642.13,1 +9010,15729087,Suttor,751,Germany,Male,54,9,156367.6,2,0,1,116179.92,0 +9011,15786463,Hsing,645,Germany,Female,59,8,121669.93,2,0,0,91.75,1 +9012,15717498,Boni,775,France,Male,42,6,133970.22,2,0,1,187839.9,0 +9013,15718406,Marshall,540,France,Male,41,3,0,2,1,0,121098.65,0 +9014,15799468,Catchpole,591,France,Female,34,3,96127.27,1,0,0,30972.06,0 +9015,15626383,Tang,596,Spain,Male,60,7,121907.97,1,0,1,30314.04,0 +9016,15597385,Siddons,573,Spain,Male,41,5,0,2,0,1,14479.29,0 +9017,15570271,Wan,577,Spain,Male,31,6,0,1,1,1,196395.25,0 +9018,15690330,Efimov,830,Germany,Female,40,8,77701.64,1,0,1,19512.38,0 +9019,15680611,Rose,663,France,Male,67,9,0,3,1,1,72318.77,0 +9020,15810227,Fanucci,421,France,Male,34,2,0,2,1,1,96615.23,0 +9021,15807194,Iweobiegbulam,718,Spain,Male,34,5,113922.44,2,1,0,30772.22,0 +9022,15712199,Ijendu,655,Germany,Female,61,2,183997.7,2,1,1,161217.18,0 +9023,15694995,O'Sullivan,712,France,Male,23,2,0,2,0,1,66795.78,0 +9024,15723400,Hutchinson,663,France,Male,28,4,0,2,1,1,123969.64,0 +9025,15654772,Kwemto,640,France,Female,47,6,89799.46,2,0,1,13783.77,1 +9026,15574743,Chiu,577,Spain,Male,29,2,0,1,1,1,168924.41,0 +9027,15807593,Berry,546,Spain,Female,36,7,85660.96,1,0,0,134778.01,0 +9028,15686718,Hung,802,Germany,Male,37,9,115569.21,1,0,1,119782.89,0 +9029,15695299,Mordvinova,590,France,Female,45,2,81828.22,1,1,0,52167.97,0 +9030,15722701,Bruno,594,Germany,Male,18,1,132694.73,1,1,0,167689.56,0 +9031,15799635,Arbour,577,Spain,Male,51,2,108867,1,0,0,140800.66,1 +9032,15742323,Barese,541,France,Male,39,7,0,2,1,0,19823.02,0 +9033,15658435,Hingston,781,France,Female,27,5,0,2,0,0,72969.9,0 +9034,15586029,Davis,806,Germany,Male,34,2,96152.68,2,1,0,143711.02,0 +9035,15772337,Lawrence,723,Germany,Female,49,0,153855.52,1,1,1,180862.26,1 +9036,15807555,Chung,535,France,Male,45,2,0,2,1,0,125658.28,0 +9037,15603378,Padovano,768,France,Female,36,3,141334.95,1,0,1,125870.5,0 +9038,15792862,Blinova,653,Germany,Male,41,1,104584.11,1,1,0,15126.32,1 +9039,15657349,Carter,803,Germany,Female,50,8,98173.02,1,0,0,22457.25,1 +9040,15777614,Webb,545,Spain,Female,44,1,0,2,1,1,82614.89,0 +9041,15653952,T'an,581,Germany,Female,38,3,135157.05,1,1,1,32919.42,0 +9042,15724336,Yates,513,Germany,Female,49,5,171601.27,1,1,0,126223.84,0 +9043,15689594,Su,731,France,Male,29,5,179539.2,1,0,0,112010.02,0 +9044,15801920,Christian,727,Germany,Male,39,5,80615.46,2,0,0,180962.32,0 +9045,15653347,Chiu,560,Spain,Male,47,1,0,1,0,0,128882.66,1 +9046,15749951,Sacco,766,Germany,Male,27,5,126285.73,1,1,0,177614.17,1 +9047,15648178,Lettiere,630,Germany,Female,23,4,137964.51,1,0,1,174570.55,0 +9048,15738662,Daluchi,652,Germany,Male,41,9,159434.03,1,1,0,178373.93,0 +9049,15640855,T'ien,729,Germany,Male,40,5,113574.61,2,1,0,103396.08,0 +9050,15584288,Hung,629,France,Female,33,6,0,2,1,1,59129.72,0 +9051,15760988,Liu,667,Germany,Male,33,9,124573.33,2,0,0,683.37,0 +9052,15569624,Feng,671,Germany,Female,31,6,105864.6,2,1,0,145567.34,0 +9053,15597949,Gilbert,768,Germany,Female,47,5,104552.61,1,1,0,48137.08,1 +9054,15604551,Robb,732,France,Female,35,3,0,2,1,0,90876.95,0 +9055,15617476,Manfrin,546,France,Female,30,5,0,2,0,1,198543.09,0 +9056,15645323,Chinwenma,630,France,Male,55,2,0,1,1,1,106202.07,1 +9057,15793311,Smith,765,Germany,Female,46,8,119492.88,2,0,1,166896.01,1 +9058,15764153,Rowe,704,France,Female,33,0,130499.09,2,1,1,74804.36,0 +9059,15802560,Moran,470,Spain,Female,48,6,140576.11,1,1,1,116971.05,0 +9060,15728608,Walker,688,Germany,Female,34,9,91025.58,2,0,1,163783,0 +9061,15770474,Myers,685,France,Female,33,1,0,3,0,1,70221.13,1 +9062,15724444,Wall,567,France,Female,38,1,125877.65,2,1,1,107841.77,0 +9063,15753110,McKay,720,Spain,Male,64,3,45752.78,2,1,0,79623.28,1 +9064,15711521,Egobudike,609,France,Male,39,3,121778.71,1,1,1,138399.67,0 +9065,15632816,Williams,521,Germany,Female,49,2,127948.57,1,1,1,182765.14,0 +9066,15693637,Ochoa,556,France,Female,30,7,0,2,1,1,186648.19,0 +9067,15725509,Otutodilinna,662,Germany,Male,30,5,115286.68,2,1,1,149587.92,0 +9068,15684645,Ajuluchukwu,704,Germany,Male,41,9,62078.21,2,1,0,129050.67,0 +9069,15692235,Bellucci,750,France,Female,38,1,0,2,1,0,47764.99,0 +9070,15777459,Gordon,619,Spain,Female,32,4,175406.13,2,1,1,172792.43,1 +9071,15656937,Johnston,468,Spain,Male,26,1,131643.25,1,1,0,64436.16,0 +9072,15610643,De Luca,435,Germany,Male,44,3,151739.65,1,1,0,167461.5,0 +9073,15777315,Hill,529,France,Male,43,6,93616.35,2,0,0,98348.66,0 +9074,15611058,Eluemuno,702,Germany,Female,60,5,138597.54,2,1,1,41536.59,1 +9075,15630413,Howarth,608,France,Female,41,5,0,2,1,1,72462.25,0 +9076,15635942,Thomson,576,France,Male,40,9,0,2,1,0,112465.19,1 +9077,15648858,King,666,France,Female,27,1,85225.21,1,0,1,64511.44,0 +9078,15810732,Grant,730,France,Female,36,8,148749.29,2,1,0,91830.75,0 +9079,15705448,Gilbert,647,Germany,Male,52,7,130013.12,1,1,1,190806.36,1 +9080,15730488,Richmond,516,Spain,Female,27,1,0,1,0,1,112311.15,0 +9081,15620443,Fiorentino,711,France,Female,81,6,0,2,1,1,72276.24,0 +9082,15741078,Greece,736,France,Male,54,7,111729.47,2,0,1,84920.49,0 +9083,15753161,Dickson,768,France,Female,36,5,180169.44,2,1,0,17348.56,0 +9084,15711396,Henderson,427,Spain,Male,40,8,0,2,1,1,82870.75,0 +9085,15593499,Stevens,686,Spain,Female,47,6,0,1,1,0,32080.69,1 +9086,15579189,Mitchell,690,France,Female,42,5,0,2,0,1,120512.08,0 +9087,15743545,Nworie,647,Spain,Female,29,2,0,2,1,0,179032.68,0 +9088,15791316,Boni,714,France,Male,35,3,0,2,1,1,95623.28,0 +9089,15608246,Wentcher,736,Germany,Female,36,8,103914.17,1,1,1,110035.88,1 +9090,15676526,Bentley,608,France,Female,34,4,88772.87,1,1,1,168822.01,0 +9091,15813911,Hayes-Williams,809,France,Female,39,5,0,1,1,0,77705.75,0 +9092,15630195,Johnstone,745,France,Female,40,6,131184.67,1,1,1,49815.62,0 +9093,15736250,Johnstone,781,France,Male,38,2,117810.79,1,0,1,65632.33,1 +9094,15671334,Nixon,527,France,Male,31,4,0,1,1,0,169361.89,0 +9095,15574169,Trevisano,595,Germany,Female,32,0,92466.21,1,1,0,4721.3,0 +9096,15718839,Tsui,850,Germany,Female,38,2,102741.15,2,0,1,23974.85,0 +9097,15762331,Moss,569,France,Male,37,9,178755.84,1,1,0,199929.17,0 +9098,15606901,Graham,728,France,Male,43,7,0,2,1,0,40023.7,0 +9099,15713559,Onyemauchechukwu,473,Germany,Female,32,5,146602.25,2,1,1,72946.95,0 +9100,15768881,Saunders,738,France,Male,29,2,0,2,1,1,170421.13,0 +9101,15743075,Ko,659,France,Male,35,6,0,2,1,1,58879.11,0 +9102,15660980,Cairns,597,Spain,Male,38,6,115702.67,2,1,1,25059.05,0 +9103,15810942,Chiemela,445,Germany,Female,61,2,137655.31,1,0,1,29909.84,0 +9104,15728362,Robertson,671,France,Female,29,3,0,2,1,0,158043.11,0 +9105,15683339,P'eng,656,Spain,Female,34,6,59877.33,1,1,0,14032.62,1 +9106,15685476,Tseng,658,France,Male,31,5,100082.14,1,0,1,49809.88,0 +9107,15663650,Russell,698,Germany,Male,52,10,107304.39,3,1,0,28806.32,1 +9108,15617434,Yen,655,Spain,Male,38,9,0,1,0,1,90490.33,0 +9109,15622470,Yeh,772,Spain,Male,41,10,96032.22,1,1,1,75825.57,0 +9110,15703682,Kalinina,681,Spain,Male,33,10,0,1,0,0,158336.36,0 +9111,15727391,Collier,688,Germany,Male,29,9,144553.5,2,1,0,143454.95,0 +9112,15711062,Thomas,633,Germany,Male,40,5,86172.81,2,1,1,117279.49,0 +9113,15567339,Shaw,735,France,Male,73,9,0,1,1,1,114283.33,0 +9114,15760662,Francis,521,Germany,Female,29,2,87212.8,1,1,1,994.86,0 +9115,15605737,George,541,France,Male,36,5,0,2,1,0,124795.84,0 +9116,15692977,Ikenna,612,Germany,Female,36,2,130700.92,2,0,0,77592.8,0 +9117,15672082,Schatz,562,France,Male,62,3,0,2,1,0,105986.01,0 +9118,15600280,Tao,703,France,Female,32,6,0,2,0,0,33606.52,0 +9119,15804052,Scott,710,Spain,Male,23,6,0,2,1,1,134188.11,0 +9120,15576065,Sims,731,Spain,Female,40,5,171325.98,1,1,1,159718.27,1 +9121,15796838,Chibugo,703,Spain,Male,58,4,92930.92,1,0,1,85148.78,0 +9122,15693526,Ku,618,France,Female,40,0,0,1,1,0,119059.13,0 +9123,15748595,Stanton,689,France,Female,29,1,77556.79,2,1,1,122998.26,0 +9124,15679029,Kung,718,France,Male,33,7,102874.28,1,0,0,117841.06,0 +9125,15753639,Gibson,608,France,Male,37,5,146093.39,2,0,0,160593.41,0 +9126,15604138,Iheanacho,749,Spain,Male,34,2,0,1,0,0,174189.04,1 +9127,15666095,Costa,753,Spain,Male,51,4,79811.72,2,0,1,68260.27,1 +9128,15643487,Sal,630,Spain,Male,39,10,105473.74,1,0,0,58854.88,1 +9129,15764033,Lin,693,Germany,Female,43,1,121927.92,1,1,0,87994.95,1 +9130,15747288,Ferri,838,Spain,Female,40,6,61671.19,1,0,1,150659.35,1 +9131,15790599,Yin,756,Germany,Female,39,5,149363.12,2,1,1,109098.39,0 +9132,15737705,Avdeyeva,775,France,Female,27,4,152309.37,1,1,0,104112,0 +9133,15737194,Tu,635,France,Female,33,5,0,2,1,0,122949.71,0 +9134,15726776,Donnelly,705,Spain,Male,36,1,111629.29,1,1,1,21807.16,0 +9135,15804357,Loggia,481,France,Male,40,3,0,1,1,1,32319.93,0 +9136,15664432,Chao,727,Spain,Female,49,7,96296.78,1,1,0,190457.87,1 +9137,15688984,Belonwu,595,France,Male,20,4,95830.43,1,1,0,177738.98,0 +9138,15583026,Welch,535,France,Female,38,0,135919.33,1,1,0,80425.65,0 +9139,15771668,Henderson,578,France,Male,59,10,185966.64,1,0,0,9445.42,1 +9140,15779904,Yobanna,597,France,Female,29,5,0,2,1,1,174825.57,0 +9141,15784323,Gallo,449,France,Female,21,7,0,2,0,0,175743.92,0 +9142,15756277,Wilson,850,Germany,Female,43,8,92244.83,2,1,0,54949.73,0 +9143,15663312,Marino,494,France,Female,35,9,112727.06,2,1,0,183752.91,0 +9144,15793197,Bailey,676,France,Female,34,8,100359.54,1,0,0,46038.28,0 +9145,15731463,Gboliwe,818,Germany,Male,43,10,105301.5,1,1,1,78941.59,0 +9146,15621768,Chukwuhaenye,712,Spain,Male,45,6,112994.65,1,0,0,198398.68,0 +9147,15691323,Bianchi,672,Germany,Male,40,4,89025.88,2,1,0,188892.19,0 +9148,15781326,Ford,636,France,Male,35,9,95478.17,1,0,0,169286.74,0 +9149,15595640,Rizzo,698,France,Male,37,8,0,2,0,0,145004.39,0 +9150,15814331,Lung,597,Germany,Female,43,7,119127.46,2,1,0,55809.92,0 +9151,15602030,Ramirez,717,France,Male,28,4,128206.79,1,1,1,54272.12,0 +9152,15747974,Sabbatini,614,France,Male,49,1,0,2,1,0,192440.54,0 +9153,15611315,Ts'ao,708,Germany,Female,23,4,71433.08,1,1,0,103697.57,0 +9154,15636977,Trevisan,507,Germany,Male,36,9,118214.32,3,1,0,119110.03,1 +9155,15690337,Chinwenma,581,France,Female,27,5,102258.11,2,1,0,194681.6,0 +9156,15680666,Berry,579,Spain,Female,39,2,151963.26,2,1,0,158948.63,0 +9157,15679551,Colombo,504,Spain,Female,46,2,163764.84,1,1,1,165122.55,1 +9158,15778915,Harris,737,France,Female,32,7,128551.36,2,0,1,189402.71,0 +9159,15568849,Bryan,540,Spain,Female,31,10,118158.74,1,1,1,158027.57,0 +9160,15747762,Chigozie,609,France,Male,32,7,118520.41,1,0,0,3815.48,0 +9161,15753679,Mullawirraburka,778,France,Male,24,4,0,2,1,1,162809.2,0 +9162,15750049,Steele,621,France,Male,40,10,163823.37,1,0,0,89519.47,0 +9163,15606097,Zakharov,665,Germany,Male,63,7,104469.58,1,1,1,25165.36,1 +9164,15802368,Ch'eng,608,France,Female,47,6,0,1,1,1,126012.57,0 +9165,15767488,Berry,680,Spain,Male,36,7,0,2,1,0,20109.21,0 +9166,15669946,Jen,663,Germany,Female,46,2,141726.88,1,1,1,58257.23,0 +9167,15612103,Wang,627,Germany,Female,35,2,137852.96,1,1,1,172269.21,1 +9168,15645353,Chubb,607,France,Male,26,1,0,1,1,0,29818.2,0 +9169,15650018,Chen,681,France,Female,43,8,154100.3,1,0,0,114659.81,0 +9170,15659002,Mazzanti,766,France,Female,45,6,0,2,0,0,147184.74,0 +9171,15616028,T'ao,694,France,Male,30,2,0,3,0,1,15039.41,0 +9172,15660475,Ndubueze,411,France,Female,54,9,0,1,0,1,76621.49,0 +9173,15652615,Ferri,742,France,Male,39,8,140004.96,1,1,1,92985.78,0 +9174,15653572,Thornton,673,Spain,Male,43,8,127132.96,1,0,1,6009.27,1 +9175,15628059,DeRose,529,France,Male,61,1,0,2,1,1,191370.97,0 +9176,15703413,Montes,519,France,Female,38,7,125328.56,1,1,0,188225.67,0 +9177,15610433,Kwemto,573,France,Male,35,9,0,2,1,0,11743.89,0 +9178,15770548,Lucchese,453,Germany,Female,28,3,139986.65,1,1,0,136846.75,0 +9179,15645637,Huggins,798,Germany,Female,39,6,119787.76,1,1,1,164248.33,0 +9180,15590888,Wade,693,Spain,Female,34,10,107556.06,2,0,0,154631.35,0 +9181,15568326,Kenenna,637,France,Female,44,2,0,2,1,0,149665.65,0 +9182,15655368,Wheeler,672,France,Male,47,1,0,1,0,0,91574.92,0 +9183,15665579,Cartwright,597,France,Female,28,0,142705.95,1,1,0,127233.39,0 +9184,15676091,Iloerika,543,France,Male,42,7,0,1,1,1,56650.47,0 +9185,15716984,Palermo,695,Spain,Female,56,4,0,2,1,0,84644.76,0 +9186,15715078,Nkemakolam,584,France,Male,35,6,161613.94,2,1,1,148238.16,0 +9187,15569452,Butler,652,Germany,Female,58,3,116353.2,2,0,1,193502.9,0 +9188,15628863,Calabresi,601,France,Male,38,4,60013.81,1,1,1,38020.05,0 +9189,15778192,Nkemdilim,628,Spain,Male,28,4,0,2,1,1,176750.81,0 +9190,15793723,Ch'iu,607,Germany,Male,32,9,144272.07,2,1,0,176580.63,0 +9191,15798943,Alexander,646,France,Female,46,8,0,2,1,0,133059.15,0 +9192,15764708,Chiabuotu,572,France,Male,30,6,117696.67,1,1,0,100843.82,0 +9193,15791040,Vasilyeva,801,Spain,Male,58,1,79954.61,2,1,1,30484.19,0 +9194,15631512,Schneider,597,France,Female,26,8,149989.39,1,1,0,42330.58,0 +9195,15640106,Mason,613,France,Male,40,7,124339.9,1,0,0,193309.58,0 +9196,15710315,Chukwukadibia,529,Germany,Male,29,4,135759.4,1,0,0,112813.79,1 +9197,15771535,Tsui,794,Spain,Female,37,9,0,2,1,0,68008.85,0 +9198,15611947,Banks,557,France,Male,34,3,83074,1,1,0,132673.22,0 +9199,15670266,Shih,499,France,Female,28,4,141792.61,1,1,1,22001.91,0 +9200,15609083,Tretiakova,544,France,Female,26,6,0,1,1,0,100200.4,1 +9201,15567923,Barese,739,France,Female,30,6,0,1,0,0,122604.44,0 +9202,15788183,Longo,458,Germany,Female,43,1,106870.12,2,1,0,100564.37,0 +9203,15735782,MacDonald,528,France,Male,31,9,120962.59,1,1,0,5419.31,0 +9204,15774401,Chambers,773,Spain,Male,51,4,0,2,0,0,123587.83,1 +9205,15737971,Cowen,646,France,Female,30,5,0,2,1,0,13935.32,0 +9206,15758750,Iweobiegbunam,564,France,Male,31,0,110527.17,1,1,1,87060.77,0 +9207,15611767,Mai,624,Germany,Female,52,0,133723.43,1,0,0,4859.59,1 +9208,15643770,Yu,682,France,Female,52,5,112670.48,1,1,0,21085.17,1 +9209,15744717,Duffy,726,France,Female,44,2,0,2,1,1,26733.86,0 +9210,15570681,Chiang,560,France,Male,24,1,116084.32,1,1,0,89734.7,0 +9211,15792650,Watts,382,Spain,Male,36,0,0,1,1,1,179540.73,1 +9212,15605531,Daly,457,Spain,Female,38,6,0,2,1,0,173219.09,0 +9213,15605339,Baker,673,France,Female,37,10,0,2,1,1,37411.35,0 +9214,15672216,Uvarov,584,France,Female,40,4,82441.75,1,0,0,80852.11,0 +9215,15812893,Costa,629,France,Female,39,10,0,2,1,1,43174.49,1 +9216,15624180,Genovesi,584,Germany,Female,37,10,134171.8,4,1,1,70927.11,1 +9217,15701364,Doherty,724,France,Male,30,10,0,2,1,1,54265.55,0 +9218,15762588,Kaleski,644,France,Male,31,5,0,2,1,1,41872.17,0 +9219,15806318,Wright,676,Germany,Female,48,2,124442.38,1,1,0,15068.53,1 +9220,15712596,Huang,499,France,Male,31,4,0,1,1,0,25950.49,0 +9221,15600399,Trentino,598,France,Male,60,4,0,1,1,0,197727.14,1 +9222,15576216,Chienezie,655,Germany,Female,37,4,108862.76,1,1,0,79555.08,1 +9223,15620750,Sugden,559,France,Male,28,3,141099.43,1,1,1,15607.27,0 +9224,15623489,Tu,543,France,Female,67,0,128843.67,1,1,1,134612.48,0 +9225,15667944,Onuchukwu,679,France,Male,39,0,86843.61,1,0,1,159830.58,0 +9226,15584928,Ugochukwutubelum,594,Germany,Female,32,4,120074.97,2,1,1,162961.79,0 +9227,15779913,Davidson,586,France,Male,27,5,130231.8,2,1,1,192427.16,0 +9228,15644977,Goddard,776,France,Female,31,5,0,2,1,0,92647.94,0 +9229,15749679,Beck,699,France,Male,39,2,109724.38,1,1,1,180022.39,0 +9230,15629010,Beam,847,Germany,Female,35,5,111743.43,1,1,1,183584.14,0 +9231,15768465,Sheppard,582,Germany,Male,35,8,121309.17,2,1,1,28750.67,0 +9232,15767781,Godfrey,648,France,Male,38,10,82697.28,1,1,0,74846.67,0 +9233,15635364,Gray,618,France,Female,49,9,44301.43,3,1,1,89729.3,1 +9234,15722004,Hsiung,543,France,Female,31,4,138317.94,1,0,0,61843.73,0 +9235,15766044,Cameron,642,Germany,Male,49,4,120688.61,1,1,0,24770.22,1 +9236,15586680,Fleming,462,France,Male,27,4,176913.52,1,1,0,80587.27,0 +9237,15635388,Austin,640,Spain,Male,47,6,89047.14,1,1,0,116286.25,0 +9238,15655175,Wallace,740,Germany,Male,40,4,114318.78,2,1,0,129333.69,1 +9239,15639133,Ku,773,France,Female,50,4,0,2,1,0,129372.94,0 +9240,15799653,Fiorentino,583,Germany,Female,32,7,94753.55,2,1,1,18149.03,0 +9241,15723872,Buccho,589,Spain,Female,46,10,0,2,0,1,168369.37,0 +9242,15775627,Gordon,509,France,Male,35,8,0,2,0,1,67431.28,0 +9243,15630704,Haworth,612,Germany,Male,32,9,106520.73,2,1,0,177092.16,0 +9244,15815534,Guidry,505,Spain,Male,37,0,134006.39,1,1,1,93736.69,0 +9245,15697249,Lettiere,546,Germany,Female,25,3,132837.7,1,1,0,131647.31,0 +9246,15681316,Tai,681,France,Female,41,0,120549.29,2,1,0,175722.31,0 +9247,15682523,Chigozie,762,France,Male,20,1,139432.55,1,1,1,85606.83,0 +9248,15650244,Bezrukov,786,Spain,Male,29,7,80895.44,2,1,0,64945.57,0 +9249,15648638,Chia,629,Spain,Male,34,6,0,2,1,0,190347.72,0 +9250,15795747,Sheppard,787,Spain,Female,39,7,171646.76,1,0,1,100791.36,0 +9251,15607330,Vasilyev,713,Spain,Male,42,0,109121.71,1,0,1,167873.49,0 +9252,15624013,Maxwell,541,France,Female,39,6,109844.81,1,1,0,25289.23,0 +9253,15800805,Maher,451,France,Female,31,7,140931.82,1,0,1,20388.77,0 +9254,15667321,Cocci,644,Spain,Male,49,10,0,2,1,1,145089.64,0 +9255,15601116,P'an,686,France,Male,32,6,0,2,1,1,179093.26,0 +9256,15622033,Rapuluchukwu,847,Germany,Female,41,3,101543.51,4,1,0,16025.17,1 +9257,15758451,Azuka,765,Germany,Male,37,7,102708.77,1,1,0,9087.81,0 +9258,15688689,Esposito,678,Germany,Female,37,8,149000.91,2,1,1,21472.42,0 +9259,15652674,Hou,539,France,Male,20,0,83459.86,1,1,1,146752.67,0 +9260,15806327,Cyril,800,France,Female,40,3,75893.11,2,1,0,132562.23,0 +9261,15649618,Tomlinson,799,Germany,Female,39,7,167395.6,2,0,1,139537.43,0 +9262,15677117,Crawford,629,France,Female,61,6,0,2,1,1,133672.61,0 +9263,15751445,Chikwado,734,Germany,Female,52,6,71283.09,2,0,1,38984.37,0 +9264,15749669,Hargreaves,542,France,Female,31,3,0,2,1,1,115217.59,0 +9265,15656351,Laidley,414,Spain,Male,60,3,0,2,1,1,93844.82,0 +9266,15667438,Ferguson,675,France,Female,38,1,104016.88,1,0,0,22068.83,1 +9267,15682273,Burns,683,France,Female,38,5,127616.56,1,1,0,123846.07,0 +9268,15580912,McNeill,748,France,Male,32,5,154737.88,2,1,1,172638.13,0 +9269,15785183,Chukwuebuka,596,Spain,Male,29,2,0,2,1,1,1591.19,0 +9270,15705383,Shen,642,France,Male,35,4,125476.31,1,1,1,91775.51,0 +9271,15712903,Diaz,499,France,Female,21,3,176511.08,1,1,1,153920.22,0 +9272,15774285,Kentish,649,Spain,Female,47,8,110783.28,1,1,1,71420.16,0 +9273,15583138,Persse,739,France,Male,42,2,141642.92,2,1,0,172149.76,0 +9274,15740160,Okwukwe,616,France,Male,31,1,0,2,1,1,54706.75,0 +9275,15793425,Watt,560,Spain,Female,33,9,0,1,0,1,183358.21,0 +9276,15749265,Carslaw,427,Germany,Male,42,1,75681.52,1,1,1,57098,0 +9277,15623989,Griffin,435,France,Male,54,3,0,1,1,0,156910.46,1 +9278,15604832,Hsia,633,France,Male,29,7,0,1,1,1,130224.73,0 +9279,15584580,Fyodorova,443,France,Male,35,6,161111.45,1,0,0,13946.66,0 +9280,15573854,Chukwujekwu,727,France,Male,62,5,0,2,0,1,38652.96,0 +9281,15614847,Townsend,674,France,Female,45,6,72494.69,1,0,1,140041.78,0 +9282,15679966,Marsh,661,France,Female,31,3,133964.3,1,1,1,166187.1,0 +9283,15799435,Hayes,619,Spain,Male,34,1,0,1,1,0,139919.38,0 +9284,15752186,Padovano,562,France,Female,27,3,0,2,1,0,28137.03,0 +9285,15705544,Ma,633,France,Male,61,3,157201.48,1,0,1,50368.63,0 +9286,15713632,Ham,551,Spain,Female,48,5,95679.29,1,0,0,94978.1,0 +9287,15586523,Paten,720,Germany,Female,29,7,106230.92,1,1,1,69903.93,1 +9288,15609176,Cawthorne,688,France,Female,32,5,0,2,0,1,177607.77,0 +9289,15769308,Herbert,635,Germany,Female,36,9,81231.85,2,1,0,196731.08,0 +9290,15676810,Jen,561,France,Female,31,1,81480.27,2,1,1,65234.6,0 +9291,15634591,Saunders,850,France,Male,33,8,73059.38,1,1,1,186281,0 +9292,15679804,Esquivel,636,France,Male,36,5,117559.05,2,1,1,111573.3,0 +9293,15677764,Chao,461,Germany,Female,74,1,186445.31,2,1,1,196767.83,0 +9294,15571917,Eluemuno,771,Germany,Female,38,5,137657.71,2,1,0,72985.61,0 +9295,15574608,Sidorova,713,France,Male,36,8,133889.35,1,1,1,143265.65,0 +9296,15740868,Pirogova,658,Germany,Female,45,9,134562.8,1,1,1,159268.67,0 +9297,15702442,Benson,586,Germany,Female,56,9,100781.75,2,1,1,54448.41,0 +9298,15699797,Santana,737,France,Male,30,8,174356.13,1,0,0,31928.5,0 +9299,15648047,Williamson,742,Germany,Male,27,5,190125.43,2,0,0,21793.59,0 +9300,15766826,North,824,France,Male,26,7,146266,1,1,0,21903.62,1 +9301,15591628,Davies,701,Germany,Male,41,9,164046.1,1,1,0,49405.93,0 +9302,15583857,Siciliano,623,Spain,Female,43,4,123536.52,2,0,0,154908.52,0 +9303,15752534,Mironov,744,France,Male,36,10,0,2,1,1,182867.84,0 +9304,15741403,Amechi,698,Spain,Female,38,1,171848.38,1,0,0,16957.45,0 +9305,15783589,Toscano,616,France,Male,40,9,0,2,0,0,93717.55,0 +9306,15598046,Su,662,France,Female,39,5,139562.05,2,1,0,61636.22,0 +9307,15643330,Chukwuemeka,594,France,Male,37,2,0,2,0,1,95864.5,0 +9308,15680405,P'eng,685,France,Male,40,2,168001.34,2,1,1,167400.29,0 +9309,15728683,Lombardo,742,France,Male,27,0,0,2,0,1,131534.96,0 +9310,15621644,Lombardi,678,Germany,Male,83,6,123356.63,1,0,1,92934.41,0 +9311,15733032,Butler,651,Spain,Male,47,2,0,2,1,1,119808.64,0 +9312,15608381,Dean,585,Germany,Male,50,2,125845.66,1,1,0,9439.31,1 +9313,15658946,Piccio,579,Germany,Male,40,10,45408.85,2,1,0,18732.91,0 +9314,15757912,Bradley,722,Germany,Female,37,0,125977.81,1,0,0,160162.42,0 +9315,15645371,Cameron,613,Germany,Female,51,7,147262.11,1,1,1,53630.9,1 +9316,15653110,Chan,694,France,Male,42,8,133767.19,1,1,0,36405.21,0 +9317,15766355,Lettiere,550,Germany,Male,49,0,108806.96,3,1,0,61446.92,1 +9318,15585249,Mironova,741,France,Male,42,6,106036.52,1,1,0,194686.78,1 +9319,15611786,Tsui,668,Spain,Female,69,9,0,1,0,1,134483.07,0 +9320,15575486,Okoli,529,France,Female,27,1,0,2,1,1,37769.98,0 +9321,15780215,Berry,636,France,Male,31,6,0,2,1,1,2382.61,0 +9322,15686099,Ruse,563,Spain,Male,61,1,82182.1,1,1,0,106826.92,1 +9323,15739042,Bogolyubov,767,France,Female,35,9,0,2,1,0,39511.61,0 +9324,15815316,Kennedy,644,France,Male,50,9,76817,4,1,0,196371.13,1 +9325,15778489,Bolton,780,Germany,Male,71,9,142550.25,2,1,1,122506.78,0 +9326,15786389,Chuang,635,Spain,Female,41,10,0,2,1,1,61994.2,0 +9327,15601787,Greco,641,Germany,Male,35,2,103711.56,1,0,1,192464.21,1 +9328,15624715,Ma,593,Spain,Female,40,2,0,1,1,1,5194.95,0 +9329,15763093,Nucci,540,Germany,Female,35,7,128369.75,2,1,0,198256.15,0 +9330,15572073,Yao,663,Spain,Male,35,5,0,2,1,1,62634.94,0 +9331,15780256,Palfreyman,630,France,Male,34,9,0,2,1,1,114006.35,0 +9332,15659305,Webster,605,Germany,Male,19,8,166133.28,1,1,1,107994.99,0 +9333,15638882,Cardell,710,Germany,Female,62,9,148214.36,1,1,0,48571.14,1 +9334,15714680,Bianchi,755,France,Female,78,5,121206.96,1,1,1,76016.49,0 +9335,15777217,Somadina,641,Spain,Male,25,10,0,2,1,1,180808.39,0 +9336,15739123,Mellor,737,Germany,Male,50,4,127552.85,2,1,0,4225.11,0 +9337,15594450,Tomlinson,695,France,Male,49,9,159458.53,1,1,0,135841.35,0 +9338,15797751,Pai,466,Germany,Female,47,5,102085.72,1,1,1,183536.24,1 +9339,15691543,Lennox,558,Germany,Male,58,2,142537.18,1,1,1,88791.83,0 +9340,15722845,Meldrum,665,Spain,Male,29,1,182781.74,2,1,1,63732.9,0 +9341,15605804,Watson,737,France,Male,45,10,0,2,1,0,1364.54,0 +9342,15702061,Findlay,654,France,Male,29,7,0,2,1,1,149184.15,0 +9343,15694321,Su,619,France,Female,28,3,0,2,1,0,53394.12,0 +9344,15798749,Davidson,845,Germany,Female,43,3,152063.59,2,1,0,97910.06,0 +9345,15720050,Barrett,727,France,Female,28,2,110997.76,1,1,0,101433.76,0 +9346,15758048,Miah,582,France,Male,50,2,148942,1,1,1,116944.3,0 +9347,15805681,Chamberlain,716,France,Male,41,9,0,1,1,1,113267.48,0 +9348,15802809,Vidal,660,Spain,Female,36,0,84438.57,1,1,1,181449.51,0 +9349,15807239,Lung,664,France,Female,34,7,93920.47,1,0,0,179913.98,0 +9350,15749093,Tretyakova,801,France,Male,43,4,158713.08,2,0,0,98586.14,0 +9351,15689344,Montgomery,615,Spain,Male,42,4,0,3,0,1,120321.09,0 +9352,15606076,Golubev,718,Germany,Male,63,7,123204.88,1,1,1,100538.8,0 +9353,15610090,Han,667,France,Male,40,8,72945.29,2,1,0,98931.5,0 +9354,15693926,Pan,670,Spain,Male,37,0,178742.71,1,1,1,194493.57,0 +9355,15791501,Carroll,590,France,Male,43,8,0,2,1,1,143628.31,0 +9356,15621870,Hawkins,739,Spain,Female,40,8,0,1,1,0,167030.51,0 +9357,15734711,Loggia,373,France,Male,42,7,0,1,1,0,77786.37,1 +9358,15814405,Chesnokova,418,France,Female,46,9,0,1,1,1,81014.5,1 +9359,15729359,Chambers,837,France,Female,29,9,0,2,1,1,41866.26,0 +9360,15606944,Fleming,645,Germany,Male,43,9,140121.17,1,1,0,11302.7,1 +9361,15671934,Veale,552,Germany,Male,39,2,132906.88,1,0,1,149384.43,0 +9362,15641773,Browne,580,Germany,Male,45,2,179334.83,2,1,1,169303.65,0 +9363,15701972,Parsons,684,France,Male,35,3,137179.39,1,1,1,37264.11,0 +9364,15749114,Bailey,634,Spain,Male,35,3,0,2,1,1,19515.48,0 +9365,15780362,Ferrari,607,France,Female,49,9,119960.29,2,1,0,103068.22,0 +9366,15753229,Genovese,802,France,Male,29,9,127414.55,1,1,1,134459.12,0 +9367,15656009,McIntyre,736,France,Female,36,6,0,1,1,0,70496.66,0 +9368,15785024,Warner,629,France,Female,40,9,137409.19,1,1,0,175877.7,1 +9369,15670492,Gordon,737,France,Male,28,8,0,2,1,0,106390.01,0 +9370,15795458,McMillan,718,Spain,Female,39,2,0,1,1,1,52138.49,0 +9371,15732438,Cheng,561,France,Male,43,4,0,4,0,0,18522.91,1 +9372,15781987,Akhtar,641,France,Male,31,9,112494.99,1,1,1,32231.6,0 +9373,15775826,Iadanza,677,France,Male,30,1,78133.15,1,0,1,174225.88,0 +9374,15807457,Abernathy,641,Spain,Female,36,1,0,2,1,0,102021.39,0 +9375,15632538,Watson,658,Spain,Female,32,5,145553.07,1,1,1,31484.76,0 +9376,15641389,Shen,659,Germany,Male,48,4,123593.22,2,1,0,82469.06,1 +9377,15657306,Kershaw,567,France,Female,47,2,0,1,0,0,110900.43,1 +9378,15709447,Reed,584,France,Female,26,0,146286.22,1,1,0,105105.35,0 +9379,15762682,Mitchell,709,Spain,Female,35,1,111827.27,2,1,0,12674.68,0 +9380,15626042,Webb,690,Spain,Female,26,2,0,2,1,1,93255.85,0 +9381,15597109,Vanzetti,627,France,Male,70,1,94416.78,1,0,1,145299.5,0 +9382,15756148,Nnanna,765,Spain,Male,45,2,91549.78,1,1,1,47139.44,0 +9383,15665634,Campbell,645,France,Female,38,7,59568.57,1,1,1,167723.25,0 +9384,15739997,Capon,716,France,Female,23,2,94464.81,2,0,1,185900.88,0 +9385,15686242,Otutodilichukwu,771,France,Female,57,4,0,1,0,0,85876.67,1 +9386,15759244,Boone,687,Germany,Male,44,8,95368.14,2,1,1,1787.85,0 +9387,15672027,McIntyre,717,Germany,Female,33,10,102185.42,2,1,0,23231.93,0 +9388,15594576,Zhdanov,524,France,Male,32,1,144875.71,1,0,0,187740.04,0 +9389,15707138,Nagy,679,Spain,Male,39,5,0,2,1,1,100060.54,0 +9390,15756954,Lombardo,538,France,Female,32,2,0,1,1,1,80130.54,0 +9391,15619130,Simpson,752,Germany,Female,37,5,113291.05,2,1,1,132467.54,0 +9392,15639665,Herbert,846,Spain,Male,61,0,0,2,1,1,96202.44,0 +9393,15571065,Lehr,532,Spain,Female,39,0,0,2,1,0,94977.3,0 +9394,15686060,Chou,670,Germany,Male,43,9,111677.88,1,1,0,178827.3,1 +9395,15615753,Upchurch,597,Germany,Female,35,8,131101.04,1,1,1,192852.67,0 +9396,15800961,Ugorji,627,Germany,Male,52,1,76101.81,2,0,1,177238.35,0 +9397,15763065,Palerma,700,Spain,Female,40,2,0,2,1,0,199753.97,0 +9398,15672467,Coles,766,France,Female,52,7,92510.9,2,0,1,66193.61,0 +9399,15752915,Hsueh,488,France,Female,34,2,0,2,1,1,181270.84,0 +9400,15744695,Tu,694,France,Male,39,5,77652.4,1,1,1,25407.59,0 +9401,15584897,Kuo,639,France,Female,31,3,98360.03,1,0,0,20973.8,0 +9402,15601857,Woodhouse,705,Germany,Female,46,4,115518.07,1,0,0,76544.9,1 +9403,15674156,Tretiakova,810,Germany,Male,69,3,27288.43,1,1,1,110509.9,0 +9404,15695465,Gibson,638,France,Female,36,6,0,1,1,0,164247.51,0 +9405,15792232,Moss,595,Spain,Female,43,5,0,2,0,0,105149.8,0 +9406,15807900,Chineze,575,France,Male,36,7,0,1,1,1,55868.97,1 +9407,15743760,Davidson,850,France,Male,31,6,131996.66,2,1,1,178747.43,0 +9408,15652835,Liang,419,Spain,Female,27,2,121580.42,1,0,1,134720.51,0 +9409,15767818,Graham,640,France,Male,55,10,132436.34,1,1,0,978.66,0 +9410,15591150,Nwebube,570,Spain,Male,34,10,0,2,0,1,183387.12,0 +9411,15734659,Sozonov,640,Germany,Female,46,5,107978.4,2,1,0,155876.06,0 +9412,15796115,Forbes,689,Germany,Female,40,4,78119.59,4,1,0,119259.34,1 +9413,15724648,Chikezie,725,France,Male,26,6,98684.15,1,0,0,133720.57,0 +9414,15737732,Onwuemelie,751,France,Female,44,10,0,2,1,0,170634.49,0 +9415,15632280,Toth,544,Spain,Female,53,9,0,1,1,0,125692.07,1 +9416,15750407,Hunt,768,Germany,Female,43,2,129264.05,2,0,0,19150.14,0 +9417,15795370,Mazure,648,Germany,Male,37,6,131753.41,1,1,0,86894.67,0 +9418,15656829,Hughes,577,Spain,Female,33,6,0,2,1,0,57975.8,0 +9419,15643794,Bennett,639,Spain,Female,27,2,0,1,1,1,82938.99,0 +9420,15798605,Tien,686,Germany,Male,26,1,57422.62,1,1,1,79189.4,0 +9421,15637324,Kay,657,France,Female,28,7,0,2,0,1,5177.62,0 +9422,15589589,Bryan,613,France,Male,34,5,144094.2,1,1,0,44510.26,0 +9423,15778936,Ingamells,701,France,Male,33,9,147510.34,1,1,0,190611.92,0 +9424,15757385,Milne,578,Spain,Female,28,8,161592.76,1,1,0,177834.79,0 +9425,15666200,Lombardo,689,France,Female,40,1,0,2,1,1,119446.64,0 +9426,15683977,Owens,687,Spain,Female,72,4,0,2,1,1,50267.69,0 +9427,15675518,Charlton,499,Spain,Female,53,1,75225.53,2,0,0,144849.1,1 +9428,15584812,Overby,693,Spain,Female,39,0,0,2,0,0,81901.6,0 +9429,15752984,Chifley,737,France,Female,70,9,87542.89,2,1,1,42576.86,0 +9430,15577913,Oliver,651,France,Female,32,8,144581.96,1,1,1,87609.5,0 +9431,15591980,Hill,753,France,Male,33,5,122568.05,2,1,1,82820.85,0 +9432,15598948,DeRose,523,Spain,Female,24,5,172231.93,1,0,1,155144.12,0 +9433,15574142,Chuang,458,Germany,Female,28,2,171932.26,2,1,1,9578.24,0 +9434,15582903,Edwards,643,France,Male,39,7,0,2,1,1,170392.59,0 +9435,15733229,Rodriguez,638,Spain,Female,34,7,0,2,0,0,3946.29,0 +9436,15635752,Lo,685,Germany,Male,38,4,111798.06,2,1,1,102184.66,0 +9437,15771000,Powell,684,France,Male,38,4,0,3,1,0,75609.84,0 +9438,15804864,Chu,670,France,Female,27,5,79336.61,1,1,1,26170.08,0 +9439,15641175,Munro,701,Germany,Male,63,3,120916.52,3,0,0,144727.45,1 +9440,15692226,Onwumelu,705,France,Female,31,3,142905.51,1,1,1,58134.97,0 +9441,15584156,Siciliani,593,Spain,Male,27,10,0,3,0,0,94620,1 +9442,15702656,Yobachi,651,France,Female,33,1,96834.78,1,1,0,108764.69,0 +9443,15606552,Akabueze,741,France,Male,37,9,105261.76,2,1,1,149503.54,0 +9444,15687001,Chiemenam,596,Germany,Male,54,1,123544,1,1,1,120314.75,1 +9445,15781903,Odinakachukwu,581,Germany,Male,41,2,127913.71,2,1,1,44205.95,0 +9446,15731951,Reilly,689,Spain,Female,28,5,95328.6,1,1,0,6129.61,1 +9447,15580953,Forbes,544,France,Male,30,4,73218.89,1,0,1,126796.69,0 +9448,15810390,Amadi,718,France,Female,41,1,0,2,0,1,27509.52,1 +9449,15628274,Ferri,583,Germany,Male,35,8,149995.72,2,1,0,42143.55,0 +9450,15615444,Y?an,663,Germany,Male,28,8,123674.28,2,1,1,87985.2,0 +9451,15784010,Williamson,666,Germany,Male,33,2,124125.26,1,1,0,81884.8,0 +9452,15571586,Briggs,524,Spain,Male,29,3,159035.45,1,1,0,2705.31,1 +9453,15748616,Napolitani,599,France,Male,27,5,0,2,1,0,30546.4,0 +9454,15769402,Carpenter,667,France,Male,27,7,156811.74,1,1,1,149402.59,0 +9455,15739248,Lin,727,France,Male,52,4,0,2,1,1,118429.02,0 +9456,15603481,Robinson,689,Spain,Female,55,4,0,2,1,1,58442.25,0 +9457,15723604,Collins,639,France,Male,39,6,150555.83,1,1,0,30414.17,0 +9458,15797822,Kingsley,678,France,Male,28,2,109137.12,1,1,1,58814.41,0 +9459,15665064,Harvey,523,France,Male,36,8,158351.02,2,1,0,155304.53,0 +9460,15640580,Obiora,650,France,Female,47,9,0,1,1,0,187943.6,0 +9461,15581089,Knight,744,Spain,Male,35,7,0,2,1,1,43036.6,0 +9462,15728605,Hung,697,France,Male,40,4,0,2,0,1,26543.28,0 +9463,15737385,Curtis,800,Spain,Female,46,6,0,2,1,0,171928.04,0 +9464,15714789,Perez,664,France,Male,24,7,0,1,0,1,35611.35,0 +9465,15786035,Gosnell,740,France,Male,39,9,0,2,1,0,19047.23,0 +9466,15815259,Fang,835,France,Female,56,2,0,2,1,1,39820.13,0 +9467,15592716,Clarke,559,France,Male,52,2,0,1,1,0,129013.59,1 +9468,15734850,Milanesi,676,Spain,Male,36,1,82729.49,1,1,0,113810.12,0 +9469,15638047,Chia,613,Germany,Female,45,9,142765.24,2,1,0,34749.65,0 +9470,15674573,Gearhart,713,France,Female,25,4,121172.97,1,1,1,56268.98,0 +9471,15694859,McLean,751,Germany,Female,28,10,132932.14,2,1,1,46630.47,0 +9472,15776404,Williamson,523,France,Male,22,8,123374.46,1,1,1,124906.59,0 +9473,15579345,Murphy,775,Germany,Female,74,0,161371.5,1,1,1,134869.93,0 +9474,15690733,Angelo,608,Spain,Male,45,4,0,2,0,0,36697.48,1 +9475,15631481,Thomson,673,France,Male,51,8,79563.36,2,1,1,172200.91,0 +9476,15620988,Murray,616,France,Male,46,2,0,2,1,0,137136.46,0 +9477,15571529,Kirby,650,Germany,Female,48,7,138232.24,1,1,0,57594.78,0 +9478,15592104,Lane,655,France,Female,41,5,0,1,0,0,36548,1 +9479,15651900,Bergamaschi,782,Germany,Female,53,1,81571.05,1,1,0,182960.46,1 +9480,15596212,Yang,781,Spain,Male,35,1,0,2,0,0,42117.9,0 +9481,15710687,Mills,593,France,Female,33,0,95927.04,1,1,0,199478.05,0 +9482,15613787,Chidubem,505,Spain,Male,35,8,116932.59,1,1,0,91092.84,0 +9483,15599211,Findlay,707,France,Male,40,1,0,2,1,0,14090.4,1 +9484,15675983,Wood,692,France,Female,36,3,79551.12,1,0,1,178267.07,0 +9485,15622370,Boyle,813,Germany,Male,30,1,116416.94,1,0,1,85808.22,0 +9486,15656319,Toscano,850,Spain,Male,37,4,88141.1,1,1,0,109659.12,0 +9487,15605130,Seccombe,753,France,Male,32,6,177729.13,1,1,1,161642.08,0 +9488,15672574,Uspenskaya,850,Spain,Female,32,5,0,1,1,1,3830.59,0 +9489,15659355,McKenzie,671,Spain,Male,32,6,123912.78,2,1,1,146636.44,0 +9490,15777907,Liang,791,France,Female,33,3,0,1,1,1,144413.92,1 +9491,15655171,Yermakova,624,France,Male,80,3,0,1,1,1,65801.44,0 +9492,15619674,White,649,France,Female,35,4,108306.44,1,1,1,192486.24,0 +9493,15775192,Rounsevell,732,Germany,Female,48,4,102962.62,1,1,0,120852.85,1 +9494,15617657,Ts'ai,664,France,Female,36,0,103502.22,1,1,1,146191.82,0 +9495,15688951,Stoneman,789,Germany,Male,43,8,119654.44,2,0,1,148412.24,1 +9496,15763460,Yao,680,France,Male,33,10,183768.47,1,1,0,164119.35,0 +9497,15756992,Chukwukere,701,France,Male,37,1,0,2,1,0,163457.55,0 +9498,15617454,Ifeatu,684,France,Female,25,1,0,2,0,1,144978.47,0 +9499,15701932,Millar,586,France,Female,52,6,140900.97,1,1,1,67288.89,0 +9500,15700813,Igwebuike,522,Germany,Female,25,5,94049.92,2,1,0,103269,0 +9501,15645600,Obidimkpa,739,Spain,Female,27,8,98926.4,1,1,1,106969.98,0 +9502,15634146,Hou,835,Germany,Male,18,2,142872.36,1,1,1,117632.63,0 +9503,15686743,Moody,790,Spain,Male,29,3,46057.96,2,1,1,189777.66,0 +9504,15698792,Keldie,671,France,Female,48,6,119769.77,1,0,1,66032.65,0 +9505,15591724,Liu,560,France,Female,44,5,143244.97,1,1,0,98661.27,0 +9506,15571281,Ts'ao,651,France,Male,28,10,79562.98,1,1,1,74687.37,0 +9507,15661380,Walker,682,France,Male,69,6,0,2,0,1,149604.18,0 +9508,15728885,Defalco,808,France,Male,41,0,0,1,1,1,79888.78,0 +9509,15618950,Lo Duca,644,Spain,Male,26,8,96659.64,2,1,1,138775.69,0 +9510,15609804,Hyde,688,France,Male,29,1,0,2,1,0,154695.57,0 +9511,15735849,Kanayochukwu,617,France,Female,26,2,165947.99,2,0,1,168834.38,0 +9512,15652948,Yen,738,France,Male,33,4,92676.3,1,1,0,105817.63,0 +9513,15618155,Ts'ui,663,France,Male,45,5,83195.12,1,1,1,48682.1,0 +9514,15566378,Tillman,515,France,Male,48,5,129387.94,1,0,1,147955.91,1 +9515,15565879,Riley,845,France,Female,28,9,0,2,1,1,56185.98,0 +9516,15792922,Tu,639,Spain,Male,38,9,130233.14,1,1,1,81861.1,0 +9517,15770567,Ruiz,557,France,Female,32,3,123502.53,1,1,1,69826.8,0 +9518,15738042,Goliwe,543,Germany,Male,37,8,140894.06,2,1,1,118059.19,0 +9519,15714920,Balashov,585,Germany,Male,44,7,163867.86,1,1,1,112333.22,0 +9520,15782121,Leonard,610,France,Female,27,2,0,2,1,0,14546.76,0 +9521,15673180,Onyekaozulu,727,Germany,Female,18,2,93816.7,2,1,0,126172.11,0 +9522,15660636,Carpenter,540,Spain,Female,40,8,0,2,1,0,3560,0 +9523,15664504,Beede,418,France,Male,35,7,0,2,1,1,88878.15,0 +9524,15790322,Beneventi,660,France,Female,32,0,114668.89,1,1,0,84605,0 +9525,15739847,Sadlier,850,Germany,Male,38,5,146756.68,1,1,0,78268.61,0 +9526,15699415,Lewis,618,France,Female,46,6,150213.71,1,1,0,120668.46,1 +9527,15665521,Chiazagomekpele,642,Germany,Male,18,5,111183.53,2,0,1,10063.75,0 +9528,15682868,Elliott,850,France,Female,40,9,99816.46,1,1,1,163989.66,1 +9529,15584462,Liang,739,France,Male,34,9,0,1,1,0,60584.33,0 +9530,15661708,She,508,France,Female,41,5,0,2,1,1,94170.84,0 +9531,15584452,Bozeman,667,France,Male,41,6,0,2,0,0,167181.77,0 +9532,15717010,Yu,741,France,Female,60,5,0,1,1,1,38914.51,0 +9533,15643828,Teng,592,France,Male,29,7,0,2,1,1,91196.67,0 +9534,15733361,Davide,651,Germany,Female,45,6,86714.06,1,1,0,85869.89,1 +9535,15795488,Beneventi,773,Spain,Male,52,2,0,2,1,0,57337.79,0 +9536,15581551,Yobachukwu,850,Spain,Male,41,8,132838.07,1,1,1,175347.28,0 +9537,15632051,Douglas,550,Germany,Female,42,10,128707.31,1,1,0,63092.65,1 +9538,15780409,Egobudike,783,France,Male,40,6,0,2,1,0,109742.55,0 +9539,15572767,Shelby,777,France,Male,29,2,0,2,1,0,124489.88,0 +9540,15590337,Golubov,659,France,Male,29,6,123192.12,1,1,1,56971.41,1 +9541,15634551,Williamson,727,Germany,Male,46,3,115248.11,4,1,0,130752.01,1 +9542,15669290,Fan,603,France,Male,38,8,59360.77,1,1,1,191457.06,0 +9543,15621140,Nwebube,644,Spain,Male,37,9,0,2,1,1,96442.86,0 +9544,15613518,Bellucci,647,France,Female,35,6,112668.7,1,0,1,122584.29,0 +9545,15728043,Udinese,648,Germany,Female,37,7,138503.51,2,1,0,57215.85,0 +9546,15570073,Marian,721,Spain,Male,57,1,0,1,1,1,195940.96,0 +9547,15777033,Chizoba,524,France,Male,29,7,0,2,1,1,105448.74,0 +9548,15682454,McFarland,626,France,Female,34,3,0,2,1,1,37870.29,0 +9549,15758513,McDonald,569,France,Male,43,7,0,2,1,0,52534.81,0 +9550,15772604,Chiemezie,578,Spain,Male,36,1,157267.95,2,1,0,141533.19,0 +9551,15721715,Fane,769,France,Female,40,9,133871.05,1,1,1,50568.02,0 +9552,15688563,Marchesi,694,Germany,Male,31,4,141989.27,2,1,0,26116.82,0 +9553,15772009,Scott,664,France,Female,41,5,0,1,1,1,152054.33,0 +9554,15809585,H?,646,France,Male,38,7,0,2,1,0,1528.4,0 +9555,15593778,Craig,779,France,Female,29,3,46388.16,3,1,0,127939.26,1 +9556,15655360,Chikelu,782,Germany,Female,72,5,148666.99,1,1,0,2605.65,1 +9557,15780909,Caffyn,769,Germany,Male,34,7,115101.5,1,0,0,57841.89,1 +9558,15757310,Otitodilichukwu,655,Germany,Male,67,6,148363.38,1,1,1,186995.17,0 +9559,15801411,Green,623,Spain,Male,46,4,0,1,1,0,5549.11,1 +9560,15761706,Y?an,705,Spain,Female,39,8,144102.32,1,1,1,11682.36,0 +9561,15658409,Mao,686,France,Male,41,5,128876.71,3,1,1,106939.34,1 +9562,15810010,Dahlenburg,678,Germany,Male,36,6,118448.15,2,1,0,53172.02,0 +9563,15627027,Shih,738,France,Male,39,5,0,2,1,1,114388.98,0 +9564,15624374,Maclean,703,France,Male,28,9,0,2,0,1,2151.17,0 +9565,15720083,Fiorentino,554,Spain,Male,42,1,0,2,0,1,183492.9,0 +9566,15752294,Long,582,France,Female,38,9,135979.01,4,1,1,76582.95,1 +9567,15743193,Olson,644,France,Male,37,6,117271.8,2,1,0,104217.96,1 +9568,15696733,McKenzie,724,France,Male,29,4,0,1,1,0,8982.75,0 +9569,15677522,Rossi,593,France,Male,33,1,0,2,0,0,9984.4,0 +9570,15643523,Power,710,Spain,Female,30,10,0,2,1,0,19500.1,0 +9571,15624936,Yen,631,France,Male,35,8,129205.49,1,1,1,79146.36,0 +9572,15716085,Norris,739,Spain,Female,41,8,0,1,1,0,191694.77,1 +9573,15641688,Collier,644,Spain,Male,18,7,0,1,0,1,59645.24,1 +9574,15796834,Rivers,652,Germany,Male,35,7,104015.54,2,1,1,55207.88,0 +9575,15720123,Hudson,554,Spain,Male,37,3,0,2,1,0,166177.3,0 +9576,15604732,Milani,483,France,Female,30,9,0,2,0,0,136356.97,0 +9577,15723484,Hunt,669,Germany,Female,42,1,103873.39,1,1,0,148611.52,0 +9578,15807120,Oluchukwu,841,Germany,Female,52,3,112383.03,1,1,0,85516.37,1 +9579,15810891,Lorenzo,662,France,Male,34,2,117731.79,2,0,1,55120.79,0 +9580,15640407,Chidiegwu,821,Germany,Male,45,0,135827.33,2,1,1,131778.58,0 +9581,15778838,Warren,783,France,Male,38,9,114135.17,1,1,0,153269.98,0 +9582,15709256,Glover,850,France,Female,28,9,0,2,1,1,164864.67,0 +9583,15742285,Andersen,559,France,Male,62,6,118756.62,1,1,1,20367.68,0 +9584,15729019,Arcuri,602,Spain,Male,34,8,98382.72,1,1,0,39542,0 +9585,15608588,Mackinlay,563,Germany,Male,41,2,100520.92,1,1,1,19412.8,1 +9586,15610557,McCarthy,695,Spain,Female,35,7,79858.13,2,1,1,127977.66,0 +9587,15786418,Chiu,546,France,Female,20,6,0,1,0,1,20508.85,0 +9588,15653050,Norriss,719,Germany,Female,76,10,95052.29,1,1,0,176244.87,0 +9589,15744914,Moore,539,Germany,Male,42,1,177728.55,1,1,0,105013.63,0 +9590,15669611,Mott,632,France,Male,71,3,83116.68,1,1,1,27597.76,0 +9591,15594786,Ts'ai,772,Germany,Male,34,7,111565.91,1,1,1,121073.23,0 +9592,15649211,Fokina,708,Spain,Male,40,8,83015.71,1,1,0,101089.76,0 +9593,15766066,Nikitina,668,Germany,Female,28,1,124511.01,1,0,0,114258.18,0 +9594,15772216,Henry,738,France,Female,67,1,130652.52,1,0,1,22762.23,0 +9595,15619898,Chiefo,785,France,Male,55,5,0,2,1,1,7008.65,0 +9596,15724543,Mao,597,France,Male,61,5,0,2,1,1,81299.17,0 +9597,15755084,Bezrukova,531,France,Male,37,7,121854.45,1,1,0,147521.35,0 +9598,15730441,Dodd,509,France,Male,26,10,0,2,1,1,6177.83,0 +9599,15666767,Lori,508,France,Male,35,1,86893.28,1,0,0,59374.82,0 +9600,15690456,Yudina,749,Germany,Female,32,7,79523.13,1,0,1,157648.12,0 +9601,15570533,Conti,621,Germany,Female,55,7,131033.76,1,0,1,75685.59,1 +9602,15797692,Volkova,659,France,Female,33,7,89939.62,1,1,0,136540.09,0 +9603,15603135,Boni,634,Germany,Female,59,3,95727.05,1,0,0,97939.4,1 +9604,15698927,Ritchie,675,France,Male,39,7,0,2,0,1,36267.21,0 +9605,15687363,McMillan,770,France,Male,31,3,155047.56,2,1,1,186064.34,0 +9606,15733444,Phillips,736,France,Female,29,9,0,2,0,0,176152.7,0 +9607,15678057,Lombardi,524,France,Male,44,10,118569.03,2,0,0,82117.2,0 +9608,15806918,Ireland,674,France,Male,28,5,0,1,1,1,151925.25,0 +9609,15638247,Boan,700,Spain,Male,44,9,0,2,1,0,142287.65,0 +9610,15674833,Shao,741,France,Female,35,1,0,2,1,0,36557.55,0 +9611,15812534,Chiemenam,455,France,Male,40,1,0,3,0,1,129975.34,0 +9612,15586522,Hunter,608,Spain,Male,37,2,130461.02,1,1,0,21967.15,0 +9613,15794297,McKay,776,France,Male,36,1,0,2,1,0,53477.76,0 +9614,15737025,Roberts,635,France,Male,33,1,0,3,0,0,178067.33,1 +9615,15615931,Aitken,746,France,Female,37,4,0,2,0,1,171039.56,0 +9616,15664860,Chao,692,Spain,Female,47,3,0,2,1,0,150802.41,1 +9617,15664539,Bruce,683,Spain,Male,35,9,61172.04,1,0,0,82951.12,0 +9618,15583692,Chan,591,Germany,Female,35,2,90194.34,2,1,0,57064.57,0 +9619,15693131,Watts,581,France,Female,24,3,95508.2,1,1,1,45755,0 +9620,15779973,Gibbons,684,Germany,Male,35,3,99967.76,1,1,1,176882.08,0 +9621,15620557,Ni,561,Spain,Male,37,4,101470.29,1,0,1,88838.14,0 +9622,15639549,Jen,718,Germany,Female,33,4,70541.06,1,0,0,88592.8,0 +9623,15618750,Phillips,590,France,Male,31,8,112211.61,1,1,0,26261.42,0 +9624,15796790,Amaechi,573,France,Female,47,8,154543.98,1,1,0,29586.73,0 +9625,15668309,Maslow,350,France,Female,40,0,111098.85,1,1,1,172321.21,1 +9626,15732437,Rowley,504,Germany,Female,44,0,131873.07,2,1,1,158036.72,1 +9627,15665158,Chukwuemeka,813,Spain,Male,27,1,137275.36,1,0,1,115733.16,0 +9628,15689322,Bevan,641,Spain,Male,31,3,153316.14,1,1,0,59927.99,0 +9629,15596624,Topp,662,France,Female,22,9,0,2,1,1,44377.65,0 +9630,15601977,Burgoyne,497,Spain,Male,44,2,121250.04,1,0,1,79691.4,0 +9631,15801462,Yermakov,716,France,Male,31,8,109578.04,2,1,1,51503.51,0 +9632,15566139,Ts'ui,526,France,Female,37,5,53573.18,1,1,0,62830.97,0 +9633,15791006,Kodilinyechukwu,760,Germany,Female,34,6,58003.41,1,1,0,90346.1,0 +9634,15668057,K?,669,France,Female,31,6,113000.66,1,1,0,40467.82,0 +9635,15580805,Marino,655,France,Male,27,10,0,2,1,0,51620.94,0 +9636,15658768,Lucas,547,France,Female,49,2,0,1,0,0,65466.93,1 +9637,15613048,Anderson,648,Germany,Female,40,5,139973.65,1,1,1,667.66,1 +9638,15803654,Wei,790,France,Female,31,2,151290.16,1,1,1,172437.12,0 +9639,15662337,Baldwin,744,Germany,Female,50,1,121498.11,2,0,1,106061.47,1 +9640,15650924,Foster,761,Spain,Female,32,4,103515.39,2,1,1,177622.38,0 +9641,15647203,Gebhart,750,France,Female,35,3,0,1,1,0,191520.5,0 +9642,15682778,Fedorov,680,France,Male,34,9,0,2,1,1,95686.6,0 +9643,15579820,Robertson,704,Spain,Male,38,6,106687.76,1,1,0,173776.5,0 +9644,15709354,Tudawali,521,France,Female,41,2,0,2,1,1,113089.43,0 +9645,15728480,Iloerika,452,France,Female,35,8,0,2,1,1,149614.81,0 +9646,15641091,Onyemauchechukwu,695,France,Female,31,5,106089.2,1,0,0,99537.68,0 +9647,15603111,Muir,850,Spain,Male,71,10,69608.14,1,1,0,97893.4,1 +9648,15679693,Walker,625,France,Male,31,5,0,2,0,1,90.07,0 +9649,15797190,Charlton,608,Germany,Female,40,7,96202.32,1,0,0,161154.85,0 +9650,15788025,Tseng,715,France,Female,38,0,0,2,1,1,332.81,0 +9651,15646168,Ifeatu,834,Spain,Male,33,5,0,2,1,0,66285.18,0 +9652,15580493,Chin,469,France,Male,33,1,127818.52,1,1,0,163477.22,0 +9653,15726720,Blinova,480,France,Female,40,7,0,1,1,0,170332.67,1 +9654,15735799,Maconochie,527,Germany,Male,58,3,137318.42,1,1,1,126144.96,0 +9655,15773098,Ch'in,834,Spain,Male,34,5,0,2,0,0,53437.1,0 +9656,15668971,Nicholson,583,France,Female,40,4,55776.39,2,1,0,26920.43,0 +9657,15603221,Burgess,696,Germany,Male,32,4,84421.62,1,0,1,52314.71,0 +9658,15740043,Young,606,France,Male,32,5,83161.65,1,1,1,116885.59,0 +9659,15712264,Plumb,713,France,Female,39,10,0,2,1,1,126263.97,0 +9660,15751926,Trentino,821,Germany,Male,42,3,87807.29,2,1,1,64613.81,0 +9661,15589401,Allen,550,France,Female,30,4,0,2,1,0,89216.29,0 +9662,15742019,Benford,675,France,Female,39,6,0,2,0,0,83419.15,0 +9663,15660611,Gallo,748,Spain,Male,39,3,0,2,1,1,123998.52,0 +9664,15607634,Cobb,606,Germany,Male,40,9,95293.86,2,0,1,96985.58,0 +9665,15595036,Doherty,726,Germany,Male,30,7,92847.59,1,1,0,146154.06,0 +9666,15745794,Cocci,547,France,Male,30,6,0,2,1,1,18471.86,0 +9667,15781689,Macadam,758,Spain,Male,35,5,0,2,1,0,95009.6,0 +9668,15696054,Tychonoff,596,France,Male,37,2,0,1,0,1,121175.86,0 +9669,15752467,Johnson,720,Spain,Male,34,3,0,2,1,1,77047.78,0 +9670,15597739,Tu,674,France,Male,37,3,0,1,1,0,158049.9,0 +9671,15651336,Chidiebere,756,France,Female,32,4,0,2,1,0,147040.25,0 +9672,15636061,Pope,649,Germany,Male,78,4,68345.86,2,1,1,142566.75,0 +9673,15723013,Sutherland,613,Germany,Male,28,7,76656.4,2,1,1,185483.24,0 +9674,15784148,Beneventi,643,France,Male,62,9,0,2,0,0,155870.82,0 +9675,15578098,Jamieson,600,France,Male,31,8,0,2,1,1,121555.51,0 +9676,15638621,Simmons,735,Spain,Male,39,1,60374.98,1,1,0,40223.74,0 +9677,15720924,Chijioke,585,France,Female,34,1,0,1,1,1,75503.6,0 +9678,15566531,Iloerika,724,Germany,Male,33,4,88046.88,1,0,1,186942.49,1 +9679,15718064,Chia,635,Spain,Male,29,2,0,2,0,0,117173.8,0 +9680,15605067,Nwachinemelu,472,France,Male,19,9,0,2,1,0,3453.4,0 +9681,15655335,Becher,590,France,Male,36,1,0,2,1,0,48876.84,0 +9682,15607301,Romano,651,Spain,Female,63,8,129968.67,1,1,1,11830.53,0 +9683,15694628,Walker,686,Germany,Female,39,4,157731.6,2,1,0,162820.6,0 +9684,15607112,Chiawuotu,606,France,Male,32,6,0,2,0,1,36540.63,0 +9685,15635775,Watt,781,France,Male,33,3,89276.48,1,1,0,6959,0 +9686,15644280,Udegbunam,593,France,Male,45,4,138825.19,1,0,0,10828.78,0 +9687,15708362,Watson,793,France,Male,63,4,103729.79,2,1,1,80272.06,0 +9688,15771997,Bryant,791,France,Female,31,10,75499.24,1,1,0,22184.14,0 +9689,15730579,Ward,850,France,Male,68,5,169445.4,1,1,1,186335.07,0 +9690,15728005,Urban,698,France,Female,57,9,111359.55,2,1,0,105715.01,0 +9691,15791674,Sutherland,846,France,Female,34,10,142388.61,2,0,1,68393.64,1 +9692,15754599,K'ung,765,France,Male,42,4,123311.39,2,1,1,82868.34,0 +9693,15693690,Iweobiegbunam,574,Spain,Male,52,7,115532.52,1,1,0,196257.67,0 +9694,15728963,Wei,617,Germany,Female,51,10,167273.71,1,0,0,93439.75,1 +9695,15659710,Lascelles,581,France,Male,25,5,77886.53,2,1,0,150319.49,0 +9696,15658675,Ts'ao,710,Germany,Male,37,6,135795.63,1,0,1,46523.6,0 +9697,15638788,Mack,550,France,Male,32,8,97514.07,1,1,1,199138.84,0 +9698,15609735,Campbell,533,Germany,Male,51,6,127545.56,2,0,0,79559.02,1 +9699,15771477,Fiorentini,779,France,Male,49,9,106160.37,1,0,0,116893.87,0 +9700,15570145,Long,763,France,Female,23,2,0,2,1,0,153983.99,0 +9701,15797149,Lloyd,563,Spain,Female,36,4,143680.47,2,1,1,63531.19,0 +9702,15636912,Sneddon,678,Spain,Male,38,3,124483.53,1,1,0,126253.31,0 +9703,15687828,Gorshkov,644,Spain,Female,31,5,86006.3,1,1,1,73922.95,0 +9704,15667424,Forbes,682,Germany,Female,43,7,111094.05,2,1,1,64679.3,0 +9705,15759872,L?,625,France,Male,22,9,0,2,1,0,157072.91,0 +9706,15572374,Hopetoun,733,Spain,Male,36,1,0,2,0,1,108377.82,0 +9707,15754926,Lucchesi,512,France,Female,30,6,0,2,1,0,88827.31,0 +9708,15687431,Faria,642,France,Female,41,7,115171.71,1,1,1,37674.47,0 +9709,15604515,Yefremov,737,Germany,Female,22,10,111543.26,2,0,0,106327.85,0 +9710,15682839,Genovesi,575,France,Female,57,8,137936.94,1,1,1,84475.13,0 +9711,15624677,Marquez,543,Germany,Female,37,3,122304.65,2,0,0,33998.7,0 +9712,15646366,Trevisani,521,Germany,Male,41,8,120586.54,1,0,1,20491.15,0 +9713,15701768,Tung,637,France,Male,32,3,0,2,1,1,197827.06,0 +9714,15623566,Barnhill,714,France,Male,40,9,46520.69,1,1,1,96687.25,0 +9715,15681274,Marshall,726,Spain,Female,56,2,105473.74,1,1,1,46044.7,0 +9716,15762573,Bednall,680,Spain,Female,34,7,0,2,1,0,98949.85,0 +9717,15706458,Pan,812,Germany,Male,39,5,115730.71,3,1,1,185599.34,1 +9718,15654222,Ogg,757,Spain,Male,30,3,145396.49,1,0,1,198341.15,0 +9719,15704053,T'ang,710,Spain,Male,62,3,131078.42,2,1,0,119348.76,1 +9720,15724321,Baresi,516,Germany,Female,47,9,128298.74,1,0,0,149614.17,1 +9721,15621815,Obiajulu,803,France,Female,40,6,165526.71,1,1,0,12328.08,0 +9722,15724876,McGregor,560,France,Female,38,5,83714.41,1,1,1,33245.97,0 +9723,15696588,Lung,679,France,Female,36,3,0,2,1,1,2243.41,0 +9724,15612832,Jamieson,526,France,Male,32,7,125540.05,1,0,0,86786.41,0 +9725,15804295,Pinto,485,France,Male,41,2,100254.76,2,1,1,12706.67,0 +9726,15712536,Fallaci,625,France,Female,36,3,0,2,1,0,41295.1,1 +9727,15662494,Goliwe,773,Spain,Male,43,7,138150.57,1,1,1,177357.16,0 +9728,15807728,Ferri,530,France,Female,45,1,0,1,0,1,190663.89,1 +9729,15764916,Rowley,616,Germany,Female,43,7,95984.21,1,0,1,115262.54,1 +9730,15615330,Tretiakova,651,France,Male,23,10,0,2,1,1,170099.23,0 +9731,15638487,She,586,Germany,Male,38,2,136858.42,1,0,1,189143.94,0 +9732,15627859,Nebeolisa,607,Germany,Male,29,7,102609,1,1,0,163257.44,0 +9733,15622192,Young,724,Spain,Male,39,3,0,2,0,1,95562.81,0 +9734,15789413,Fitzgerald,733,France,Male,64,3,0,2,1,1,75272.63,0 +9735,15583221,Arnold,667,Germany,Male,70,3,77356.92,2,1,1,20881.96,0 +9736,15768495,Chidimma,700,France,Female,32,8,110923.15,2,1,1,161845.81,1 +9737,15644103,Wells,659,Spain,Male,78,2,151675.65,1,0,1,49978.67,0 +9738,15741197,Calzada,710,Spain,Male,22,8,0,3,1,0,107292.91,0 +9739,15664547,Black,760,France,Male,37,7,0,1,0,0,32863.24,1 +9740,15797293,Sopuluchukwu,677,France,Female,25,3,0,2,1,0,179608.96,0 +9741,15572021,Ts'ao,798,Germany,Female,29,8,80204.11,2,1,0,70223.22,0 +9742,15637461,Ukaegbunam,758,France,Male,35,7,0,2,1,0,77951.84,0 +9743,15620577,Wood,715,France,Male,45,4,0,2,1,1,55043.93,0 +9744,15609643,Furneaux,752,Germany,Male,32,9,115587.49,2,0,1,101677.46,0 +9745,15785358,Gresswell,586,Germany,Male,46,8,106968.96,1,1,1,79366.98,1 +9746,15603883,Ch'in,818,France,Male,36,4,0,2,1,1,8037.03,0 +9747,15782550,Ma,490,Germany,Female,41,0,139659.04,1,1,1,176254.12,0 +9748,15775761,Iweobiegbunam,610,Germany,Female,69,5,86038.21,3,0,0,192743.06,1 +9749,15680201,Marcelo,627,Germany,Male,24,5,102773.2,2,1,0,56793.02,1 +9750,15767594,Azubuike,533,France,Female,35,8,0,2,1,1,187900.12,0 +9751,15591985,Stewart,708,France,Female,51,8,70754.18,1,1,1,92920.04,1 +9752,15789339,Yen,681,France,Male,59,4,122781.51,1,0,1,140166.95,0 +9753,15781530,Hsieh,690,France,Male,21,8,0,2,1,1,155782.89,0 +9754,15705174,Chiedozie,656,Germany,Male,68,7,153545.11,1,1,1,186574.68,0 +9755,15572114,Shih,673,Spain,Male,40,1,121629.22,1,1,1,3258.6,0 +9756,15804009,Amechi,806,Germany,Male,36,8,167983.17,2,1,1,106714.28,0 +9757,15662698,Ko,648,Spain,Female,43,7,81153.82,1,1,1,144532.85,1 +9758,15696047,Chimezie,501,France,Male,35,6,99760.84,1,1,1,13591.52,0 +9759,15701160,Azubuike,556,Germany,Female,43,4,125890.72,1,1,1,74854.97,0 +9760,15790093,Aguirre,627,France,Female,27,2,0,2,1,0,125451.01,0 +9761,15632143,Lung,652,France,Male,31,2,119148.55,1,0,0,149740.22,0 +9762,15736778,Adams,807,Germany,Female,60,1,72948.58,2,1,1,17355.36,0 +9763,15734917,Castiglione,708,Germany,Male,21,8,133974.36,2,1,0,50294.09,0 +9764,15643903,Yao,619,France,Male,27,1,154483.98,1,1,0,156394.74,0 +9765,15569526,Morales,601,France,Male,40,10,98627.13,2,0,0,77977.69,0 +9766,15777067,Thomas,445,France,Male,64,2,136770.67,1,0,1,43678.06,0 +9767,15795511,Vasiliev,800,Germany,Male,39,4,95252.72,1,1,0,13906.34,0 +9768,15610419,Chukwueloka,554,France,Male,33,3,117413.95,1,1,1,12766.74,0 +9769,15644994,Ko,714,Germany,Male,54,4,137986.58,2,0,1,51308.54,1 +9770,15703707,Atkins,656,France,Male,44,10,143571.52,1,0,0,127444.14,0 +9771,15659327,Moffitt,520,France,Male,49,5,121197.64,1,1,0,72577.33,1 +9772,15771323,Panicucci,480,Spain,Male,39,5,121626.9,1,1,1,82438.13,0 +9773,15750549,Akobundu,660,Germany,Male,30,1,84440.1,2,1,1,60485.98,0 +9774,15698462,Chiu,532,France,Male,36,4,0,2,1,1,132798.78,0 +9775,15739692,Tsui,679,France,Male,42,1,0,2,0,0,71823.15,0 +9776,15744041,Yobanna,780,France,Female,26,3,140356.7,1,1,0,117144.15,0 +9777,15700714,Hollis,747,France,Male,29,7,0,2,1,1,141706.43,0 +9778,15777743,Cattaneo,705,France,Female,39,3,92224.56,1,1,1,54517.25,0 +9779,15623143,Lung,732,France,Female,43,9,0,2,1,0,183147.17,0 +9780,15712568,Angelo,515,Spain,Male,40,10,121355.99,1,1,0,138360.29,0 +9781,15617432,Folliero,816,Germany,Female,40,9,109003.26,1,1,1,79580.56,0 +9782,15650424,Bryant,641,France,Female,48,3,147341.43,1,1,1,157458.61,1 +9783,15728829,Weigel,509,France,Male,18,7,102983.91,1,1,0,171770.58,0 +9784,15680430,Ajuluchukwu,601,Germany,Female,49,4,96252.98,2,1,0,104263.82,0 +9785,15687626,Zhirov,527,France,Male,39,4,0,2,1,0,167183.07,1 +9786,15609187,Cox,455,France,Female,27,5,155879.09,2,0,0,70774.97,0 +9787,15609521,Chimaraoke,803,Germany,Male,34,4,142929.16,2,1,1,114869.56,0 +9788,15752626,Genovese,553,France,Male,32,7,64082.09,1,0,1,109159.58,0 +9789,15571756,Ohearn,724,France,Female,28,5,0,1,1,0,59351.68,0 +9790,15814040,Munroe,610,France,Female,45,1,0,2,1,1,199657.46,0 +9791,15658211,Morrison,559,Spain,Female,39,2,0,2,1,1,121151.1,0 +9792,15742091,Parkhill,825,Germany,Female,35,6,118336.95,1,1,0,26342.33,1 +9793,15787168,Y?,819,Spain,Female,28,8,168253.21,1,1,1,102799.14,0 +9794,15772363,Hilton,772,Germany,Female,42,0,101979.16,1,1,0,90928.48,0 +9795,15659364,Thompson,685,Spain,Male,23,5,164902.43,1,0,0,141152.28,0 +9796,15738980,Yobanna,506,France,Male,43,2,0,2,1,0,105568.6,0 +9797,15794236,Thorpe,642,Germany,Male,22,10,111812.52,2,1,1,183045.46,0 +9798,15721383,Harvey,627,Spain,Male,40,10,0,2,1,1,194792.42,0 +9799,15652981,Robinson,600,Germany,Male,30,2,119755,1,1,1,21852.91,0 +9800,15722731,Manna,653,France,Male,46,0,119556.1,1,1,0,78250.13,1 +9801,15640507,Li,762,Spain,Female,35,3,119349.69,3,1,1,47114.18,1 +9802,15578878,Hancock,569,Spain,Female,30,3,139528.23,1,1,1,33230.37,0 +9803,15744295,Hao,756,France,Male,40,1,94773.11,1,1,0,114279.63,0 +9804,15776558,Nicholls,673,France,Male,31,1,108345.22,1,0,1,38802.03,0 +9805,15596136,Folliero,637,France,Female,36,9,166939.88,1,1,1,72504.76,0 +9806,15704597,Trumbull,644,France,Male,33,7,174571.36,1,0,1,43943.09,0 +9807,15648272,Medvedeva,658,Spain,Male,35,9,71829.34,1,1,1,68141.92,0 +9808,15594915,Crist,649,France,Female,36,8,0,2,0,1,109179.89,0 +9809,15581115,Middleton,603,France,Female,39,9,76769.68,1,0,0,48224.72,0 +9810,15763907,Watts,820,France,Female,39,1,104614.29,1,1,0,61538.43,1 +9811,15705994,Udinese,712,Spain,Male,27,10,0,1,1,0,94544.88,0 +9812,15772421,Tretiakov,645,Germany,Female,31,1,128927.93,1,1,1,2850.01,0 +9813,15711572,O'Kane,705,Germany,Female,31,9,110941.93,2,1,0,163484.8,0 +9814,15691170,Vasilyeva,590,Spain,Female,29,10,99250.08,1,1,1,129629.41,0 +9815,15600106,Wei,631,France,Male,36,1,0,2,0,0,133141.34,0 +9816,15745431,Chinonyelum,604,France,Male,34,7,0,2,1,1,188078.55,0 +9817,15649508,Chin,643,Spain,Male,48,8,0,2,1,0,174729.3,0 +9818,15812611,Lorimer,690,Spain,Female,30,5,0,2,0,1,78700.03,0 +9819,15619699,Yeh,558,France,Male,31,7,0,1,1,0,198269.08,0 +9820,15813946,Duffy,637,Germany,Male,51,1,104682.83,1,1,0,55266.96,1 +9821,15762762,Onyekachukwu,648,Germany,Female,45,5,118886.55,1,0,0,51636.7,0 +9822,15629793,Banks,652,Spain,Male,28,8,156823.7,2,1,0,198251.52,0 +9823,15781298,Hughes,808,Germany,Male,39,3,124216.93,1,0,1,171442.36,0 +9824,15622658,Lai,551,France,Female,26,2,144258.52,1,1,0,49778.79,0 +9825,15658980,Matthews,711,Germany,Male,26,9,128793.63,1,1,0,19262.05,0 +9826,15701936,Bell,467,Germany,Male,28,10,126315.26,1,1,0,32349.29,1 +9827,15686917,Tu,789,Spain,Female,40,4,0,2,1,0,137402.27,0 +9828,15807312,Hsia,602,Spain,Male,33,5,0,2,0,1,64038.34,0 +9829,15574523,Cheng,576,France,Male,39,1,0,2,1,1,68814.23,0 +9830,15724200,Cheng,584,France,Male,38,1,115341.55,1,0,1,173632.92,0 +9831,15738224,Lin,593,France,Male,32,6,99162.29,1,1,0,128384.11,0 +9832,15593283,Higgins,705,Germany,Female,48,1,156848.13,2,1,1,99475.95,1 +9833,15814690,Chukwujekwu,595,Germany,Female,64,2,105736.32,1,1,1,89935.73,1 +9834,15807245,McKay,699,Germany,Female,41,1,200117.76,2,1,0,94142.35,0 +9835,15799358,Vincent,516,France,Female,46,6,62212.29,1,0,1,171681.86,1 +9836,15616172,Ubanwa,838,France,Male,31,2,0,2,1,0,8222.96,0 +9837,15777958,Ch'ien,587,France,Male,39,10,0,2,1,1,170409.45,0 +9838,15809124,T'ien,750,France,Male,38,5,151532.4,1,1,1,46555.15,0 +9839,15616367,Ricci,581,Germany,Male,39,1,121523.51,1,0,0,161655.55,1 +9840,15687385,McDowell,484,France,Male,41,5,0,1,1,1,74267.35,0 +9841,15607877,Maclean,576,Spain,Male,26,8,0,2,0,1,34101.06,0 +9842,15736327,Manna,567,Germany,Female,46,1,68238.51,2,1,1,109572.58,0 +9843,15746704,Jibunoh,638,Spain,Male,30,9,136808.53,2,1,1,106642.97,0 +9844,15778304,Fan,646,Germany,Male,24,0,92398.08,1,1,1,18897.29,0 +9845,15588456,Hsieh,658,France,Female,40,5,143566.12,1,1,1,189607.71,0 +9846,15664035,Parsons,590,Spain,Female,38,9,0,2,1,1,148750.16,0 +9847,15596405,Udinese,546,Spain,Male,25,7,127728.24,2,1,1,105279.74,0 +9848,15815097,Root,603,France,Female,34,9,0,2,1,0,167916.35,0 +9849,15762708,Chiemezie,619,Spain,Female,38,10,119658.49,1,1,1,8646.58,0 +9850,15776211,Toscani,678,France,Female,34,6,0,2,1,1,124592.84,0 +9851,15626012,Obidimkpa,459,France,Male,26,4,149879.66,1,0,0,50016.17,0 +9852,15792077,Degtyaryov,671,Germany,Male,28,8,119859.52,2,1,0,125422.66,0 +9853,15718765,Maclean,501,Spain,Male,43,6,104533.24,1,0,0,81123.59,1 +9854,15576615,Giordano,719,Spain,Male,37,10,145382.61,1,1,0,80408.59,0 +9855,15752650,Saad,681,Spain,Female,37,6,121231.39,1,1,1,146366.08,0 +9856,15797502,Lord,706,Spain,Male,24,2,141078.57,1,1,1,24402.87,0 +9857,15687329,Hope,763,Germany,Female,32,1,108465.65,2,1,0,60552.44,1 +9858,15779423,K?,716,France,Male,39,1,70657.61,2,1,1,76476.05,0 +9859,15619514,Bull,507,Germany,Male,40,3,120105.43,1,1,0,92075.01,1 +9860,15615430,Adams,678,Germany,Male,55,4,129646.91,1,1,1,184125.1,1 +9861,15716431,Brookes,775,France,Female,30,10,191091.74,2,1,1,96170.38,0 +9862,15798341,Victor,544,France,Male,38,8,0,1,1,1,98208.62,0 +9863,15651958,Giles,756,France,Male,27,8,0,2,1,1,157932.75,0 +9864,15726179,Ferrari,757,Germany,Female,43,5,131433.33,2,1,1,3497.43,1 +9865,15652999,Milne,742,Germany,Male,33,1,137937.95,1,1,1,51387.1,0 +9866,15691950,Parry,591,France,Male,49,3,0,2,1,0,50123.44,0 +9867,15632446,Allan,667,France,Male,24,4,0,2,0,0,180329.83,0 +9868,15620936,Warren,787,France,Male,32,4,0,2,1,1,13238.93,0 +9869,15587640,Rowntree,718,France,Female,43,0,93143.39,1,1,0,167554.86,0 +9870,15782231,Andrejew,521,France,Male,38,6,0,2,1,0,51454.06,0 +9871,15580462,Corby,607,Spain,Male,40,1,112544.45,1,1,1,19842.22,0 +9872,15736371,Kennedy,633,France,Female,34,3,123034.43,2,1,1,38315.04,0 +9873,15648032,Young,588,Spain,Male,37,2,0,2,0,1,187816.59,0 +9874,15610454,Poole,724,Germany,Female,33,9,119278.44,1,1,1,197148.24,0 +9875,15671358,Fletcher,720,France,Male,44,4,0,2,1,0,163471.01,0 +9876,15747130,Tsao,521,France,Male,39,7,0,2,0,1,653.58,0 +9877,15578374,Gilroy,620,Spain,Male,36,7,169312.72,1,1,0,45414.09,0 +9878,15572182,Onwuamaeze,505,Germany,Female,33,3,106506.77,3,1,0,45445.78,1 +9879,15770041,Manna,728,Spain,Female,43,8,128412.61,1,0,1,139024.31,0 +9880,15669414,Pisano,486,Germany,Male,62,9,118356.89,2,1,0,168034.83,1 +9881,15777054,Thorpe,584,Germany,Male,42,3,137479.13,1,1,0,25669.1,0 +9882,15621021,Dwyer,687,Spain,Female,40,1,0,2,1,0,8207.36,0 +9883,15785490,Okeke,771,France,Male,50,3,105229.72,1,1,1,16281.68,1 +9884,15577695,Zito,678,France,Male,41,2,148088.11,1,1,0,14083.12,0 +9885,15686974,Sergeyeva,751,France,Female,48,4,0,1,0,1,30165.06,1 +9886,15574584,Fang,670,France,Male,33,8,126679.69,1,1,1,39451.09,0 +9887,15719541,Flannagan,675,Spain,Male,31,2,90826.27,2,1,0,60270.87,0 +9888,15646310,Mao,684,Spain,Male,24,8,143582.89,1,1,1,22527.27,0 +9889,15697606,Sturdee,637,France,Female,21,10,125712.2,1,0,0,175072.47,0 +9890,15711489,Azikiwe,760,Spain,Female,32,2,0,1,1,1,114565.35,0 +9891,15670427,Chidi,662,Spain,Male,37,4,155187.3,1,1,0,48930.8,0 +9892,15731755,Hull,680,France,Male,49,10,0,2,1,0,187008.45,0 +9893,15796370,Shah,604,Spain,Male,40,5,155455.43,1,0,1,113581.85,0 +9894,15598331,Morgan,764,France,Female,40,9,100480.53,1,1,0,124095.69,0 +9895,15704795,Vagin,521,France,Female,77,6,0,2,1,1,49054.1,0 +9896,15796764,Bruno,684,Germany,Female,56,3,127585.98,3,1,1,80593.49,1 +9897,15589420,Osinachi,795,France,Female,40,2,101891.1,1,1,1,183044.86,0 +9898,15810563,Ho,678,Spain,Female,61,8,0,2,1,1,159938.82,0 +9899,15746569,Tsui,589,France,Male,38,4,0,1,1,0,95483.48,1 +9900,15811594,Gordon,660,Spain,Female,28,3,128929.88,1,1,1,198069.71,0 +9901,15645896,Duncan,646,Germany,Male,39,6,121681.91,2,0,1,61793.47,0 +9902,15802909,Hu,706,Germany,Female,56,3,139603.22,1,1,1,86383.61,0 +9903,15797665,Docherty,730,France,Female,27,7,0,2,1,0,144099.48,0 +9904,15778959,Brookes,606,France,Female,36,10,0,2,0,1,155641.46,0 +9905,15722532,Angelo,690,Spain,Female,36,10,91760.11,1,1,1,135784.94,0 +9906,15784124,Emenike,645,Germany,Male,41,2,93925.3,1,1,0,123982.14,1 +9907,15776518,Pugh,579,France,Female,38,4,175739.36,1,1,1,193130.55,0 +9908,15611247,McKenzie,481,France,Female,28,10,0,2,1,0,145215.96,0 +9909,15721469,Mach,492,Germany,Male,45,9,170295.04,2,0,0,164741.81,0 +9910,15773338,Endrizzi,739,France,Male,58,2,101579.28,1,1,1,72168.53,0 +9911,15784042,L?,624,France,Male,55,7,118793.6,1,1,1,95022.02,1 +9912,15776229,MacPherson,682,France,Male,44,3,115282.3,1,0,0,23766.4,0 +9913,15655903,Michael,701,Spain,Female,34,6,107980.37,1,1,1,119374.74,0 +9914,15590177,Chiedozie,718,France,Female,44,1,133866.22,1,0,1,139049.24,0 +9915,15568876,Hughes,496,France,Female,34,1,102723.35,2,1,0,180844.81,0 +9916,15813140,Taylor,543,Spain,Male,41,5,0,2,0,1,143980.29,0 +9917,15770516,Evdokimov,616,Spain,Female,44,7,193213.02,2,1,1,137392.77,0 +9918,15755731,Davis,635,Germany,Male,53,8,117005.55,1,0,1,123646.57,1 +9919,15574480,Ubanwa,652,Spain,Male,31,1,132862.59,1,0,0,158054.49,0 +9920,15798084,Murray,688,France,Male,26,0,0,2,1,0,105784.85,0 +9921,15673020,Smith,678,France,Female,49,3,204510.94,1,0,1,738.88,1 +9922,15643575,Evseev,757,Germany,Male,36,1,65349.71,1,0,0,64539.64,0 +9923,15596811,Mitchell,667,France,Male,36,8,139753.35,1,1,0,79871.16,0 +9924,15786789,Ni,725,France,Female,29,6,0,2,1,1,190776.83,0 +9925,15578865,Palerma,632,Germany,Female,50,5,107959.39,1,1,1,6985.34,1 +9926,15605672,Yuan,694,France,Female,38,5,195926.39,1,1,1,85522.84,0 +9927,15603674,Knight,803,France,Male,36,1,0,2,1,1,149370.93,0 +9928,15759915,Rapuokwu,814,France,Female,31,6,87772.52,1,1,0,188516.45,0 +9929,15686219,Wan,611,France,Male,38,4,71018.6,2,1,0,2444.29,0 +9930,15696388,Artamonova,755,Germany,Male,38,4,111096.91,1,1,1,19762.88,0 +9931,15713604,Rossi,425,Germany,Male,40,9,166776.6,2,0,1,172646.88,0 +9932,15647800,Greco,850,France,Female,34,6,101266.51,1,1,0,33501.98,0 +9933,15813451,Fleetwood-Smith,677,Spain,Male,18,8,134796.87,2,1,1,114858.9,0 +9934,15765375,Butusov,797,France,Female,46,8,0,1,0,0,162668.33,0 +9935,15774586,West,692,Germany,Female,43,10,118588.83,1,1,1,161241.65,1 +9936,15603454,Sanders,735,Germany,Male,28,5,160454.15,2,0,1,114957.22,0 +9937,15653037,Parks,609,France,Male,77,1,0,1,0,1,18708.76,0 +9938,15782475,Edith,700,France,Female,42,8,0,2,1,1,105305.72,0 +9939,15593496,Korovin,526,Spain,Female,36,5,91132.18,1,0,0,58111.71,0 +9940,15808971,Lajoie,693,Spain,Female,57,9,0,2,1,1,135502.77,0 +9941,15791972,Bergamaschi,748,France,Female,20,7,0,2,0,0,10792.42,0 +9942,15676869,T'ien,657,Spain,Male,36,8,0,2,0,1,123866.43,0 +9943,15683007,Torode,739,Germany,Female,25,5,113113.12,1,1,0,129181.27,0 +9944,15659495,Fu,784,Spain,Male,23,2,0,1,1,1,6847.73,0 +9945,15703923,Cameron,744,Germany,Male,41,7,190409.34,2,1,1,138361.48,0 +9946,15674000,Cattaneo,645,France,Male,44,10,0,2,0,1,166707.22,0 +9947,15618171,James,669,France,Female,33,9,0,2,0,1,107221.03,0 +9948,15732202,Abramovich,615,France,Male,34,1,83503.11,2,1,1,73124.53,1 +9949,15735078,Onwughara,724,Germany,Female,53,1,139687.66,2,1,1,12913.92,0 +9950,15798615,Wan,850,France,Female,47,9,137301.87,1,1,0,44351.77,0 +9951,15638494,Salinas,625,Germany,Female,39,10,129845.26,1,1,1,96444.88,0 +9952,15763874,Ho,635,Spain,Male,46,8,0,2,1,1,60739.16,0 +9953,15696355,Cleveland,724,Germany,Male,37,6,125489.4,1,1,0,118570.53,0 +9954,15655952,Burke,550,France,Male,47,2,0,2,1,1,97057.28,0 +9955,15739850,Trentino,645,France,Male,45,6,155417.61,1,0,1,3449.22,0 +9956,15611338,Kashiwagi,714,Spain,Male,29,4,0,2,1,1,37605.9,0 +9957,15707861,Nucci,520,France,Female,46,10,85216.61,1,1,0,117369.52,1 +9958,15672237,Oluchi,633,France,Male,25,1,0,1,1,0,100598.98,0 +9959,15657771,Ts'ui,537,France,Male,37,6,0,1,1,1,17802.42,0 +9960,15677783,Graham,764,Spain,Male,38,4,113607.47,1,1,0,91094.46,0 +9961,15681026,Lucciano,795,Germany,Female,33,9,104552.72,1,1,1,120853.83,1 +9962,15566543,Aldridge,573,Spain,Male,44,9,0,2,1,0,107124.17,0 +9963,15594612,Flynn,702,Spain,Male,44,9,0,1,0,0,59207.41,1 +9964,15814664,Scott,740,Germany,Male,33,2,126524.11,1,1,0,136869.31,0 +9965,15642785,Douglas,479,France,Male,34,5,117593.48,2,0,0,113308.29,0 +9966,15690164,Shao,627,Germany,Female,33,4,83199.05,1,0,0,159334.93,0 +9967,15590213,Ch'en,479,Spain,Male,35,4,125920.98,1,1,1,20393.44,0 +9968,15603794,Pugliesi,623,France,Male,48,5,118469.38,1,1,1,158590.25,0 +9969,15733491,McGregor,512,Germany,Female,40,8,153537.57,2,0,0,23101.13,0 +9970,15806360,Hou,609,France,Male,41,6,0,1,0,1,112585.19,0 +9971,15587133,Thompson,518,France,Male,42,7,151027.05,2,1,0,119377.36,0 +9972,15721377,Chou,833,France,Female,34,3,144751.81,1,0,0,166472.81,0 +9973,15747927,Ch'in,758,France,Male,26,4,155739.76,1,1,0,171552.02,0 +9974,15806455,Miller,611,France,Male,27,7,0,2,1,1,157474.1,0 +9975,15695474,Barker,583,France,Male,33,7,122531.86,1,1,0,13549.24,0 +9976,15666295,Smith,610,Germany,Male,50,1,113957.01,2,1,0,196526.55,1 +9977,15656062,Azikiwe,637,France,Female,33,7,103377.81,1,1,0,84419.78,0 +9978,15579969,Mancini,683,France,Female,32,9,0,2,1,1,24991.92,0 +9979,15703563,P'eng,774,France,Male,40,9,93017.47,2,1,0,191608.97,0 +9980,15692664,Diribe,677,France,Female,58,1,90022.85,1,0,1,2988.28,0 +9981,15719276,T'ao,741,Spain,Male,35,6,74371.49,1,0,0,99595.67,0 +9982,15672754,Burbidge,498,Germany,Male,42,3,152039.7,1,1,1,53445.17,1 +9983,15768163,Griffin,655,Germany,Female,46,7,137145.12,1,1,0,115146.4,1 +9984,15656710,Cocci,613,France,Male,40,4,0,1,0,0,151325.24,0 +9985,15696175,Echezonachukwu,602,Germany,Male,35,7,90602.42,2,1,1,51695.41,0 +9986,15586914,Nepean,659,France,Male,36,6,123841.49,2,1,0,96833,0 +9987,15581736,Bartlett,673,Germany,Male,47,1,183579.54,2,0,1,34047.54,0 +9988,15588839,Mancini,606,Spain,Male,30,8,180307.73,2,1,1,1914.41,0 +9989,15589329,Pirozzi,775,France,Male,30,4,0,2,1,0,49337.84,0 +9990,15605622,McMillan,841,Spain,Male,28,4,0,2,1,1,179436.6,0 +9991,15798964,Nkemakonam,714,Germany,Male,33,3,35016.6,1,1,0,53667.08,0 +9992,15769959,Ajuluchukwu,597,France,Female,53,4,88381.21,1,1,0,69384.71,1 +9993,15657105,Chukwualuka,726,Spain,Male,36,2,0,1,1,0,195192.4,0 +9994,15569266,Rahman,644,France,Male,28,7,155060.41,1,1,0,29179.52,0 +9995,15719294,Wood,800,France,Female,29,2,0,2,0,0,167773.55,0 +9996,15606229,Obijiaku,771,France,Male,39,5,0,2,1,0,96270.64,0 +9997,15569892,Johnstone,516,France,Male,35,10,57369.61,1,1,1,101699.77,0 +9998,15584532,Liu,709,France,Female,36,7,0,1,0,1,42085.58,1 +9999,15682355,Sabbatini,772,Germany,Male,42,3,75075.31,2,1,0,92888.52,1 +10000,15628319,Walker,792,France,Female,28,4,130142.79,1,1,0,38190.78,0 diff --git a/5.1 Deep Learning/notebooks/Um-neuron.png b/5.1 Deep Learning/notebooks/Um-neuron.png new file mode 100644 index 0000000..6ceb3a6 Binary files /dev/null and b/5.1 Deep Learning/notebooks/Um-neuron.png differ diff --git a/5.1 Deep Learning/notebooks/detectando bordas.png b/5.1 Deep Learning/notebooks/detectando bordas.png new file mode 100644 index 0000000..8435f02 Binary files /dev/null and b/5.1 Deep Learning/notebooks/detectando bordas.png differ diff --git a/5.1 Deep Learning/notebooks/part1 - redes neurais.ipynb b/5.1 Deep Learning/notebooks/part1 - redes neurais.ipynb new file mode 100644 index 0000000..9d07aca --- /dev/null +++ b/5.1 Deep Learning/notebooks/part1 - redes neurais.ipynb @@ -0,0 +1 @@ +{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"nn.ipynb","provenance":[],"collapsed_sections":[]},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.6.7"},"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"}},"cells":[{"cell_type":"markdown","metadata":{"id":"dGYEB3wu01rh","colab_type":"text"},"source":["# Redes Neurais Artificiais"]},{"cell_type":"markdown","metadata":{"tags":["remove_cell"],"id":"A8ksqCDU01rj","colab_type":"text"},"source":["## Preparando os dados"]},{"cell_type":"markdown","metadata":{"id":"wRKKNfl801rk","colab_type":"text"},"source":["Vamos criar uma rede neural simples para prever *churn* de clientes. \n","\n","Vamos começar pela leitura dos dados:"]},{"cell_type":"code","metadata":{"id":"dQBGMhka01rl","colab_type":"code","colab":{}},"source":["import pandas as pd"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"8D6e8mbB01ro","colab_type":"code","colab":{}},"source":["df = pd.read_csv('Churn_Modelling.csv')\n","df.head()"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"lZmlsHwT01rt","colab_type":"code","colab":{}},"source":["df['Exited'].value_counts()"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"scrolled":true,"id":"aCqt05at01rw","colab_type":"code","colab":{}},"source":["df['Geography'].value_counts()"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"0IyE5ePm01ry","colab_type":"code","colab":{}},"source":["df['Gender'].value_counts()"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"F55WS_t401r1","colab_type":"text"},"source":["Para este exemplo vamos fazer um tratamento simples dos dados, apenas convertendo as variáveis categoricas em dummies:"]},{"cell_type":"code","metadata":{"id":"oGs6BI9s01r1","colab_type":"code","colab":{}},"source":["df = pd.get_dummies(df, columns=['Geography', 'Gender'])\n","df.columns"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"Z_dg-Si001r5","colab_type":"text"},"source":["Vamos separar os dados de teste e treinamento:"]},{"cell_type":"code","metadata":{"id":"zyu-8JLl01r6","colab_type":"code","colab":{}},"source":["X = df[['CreditScore', 'Age', 'Tenure', 'Balance', 'NumOfProducts', 'HasCrCard', 'IsActiveMember','EstimatedSalary', \n"," 'Geography_France', 'Geography_Germany', 'Geography_Spain', 'Gender_Female']]\n","\n","y = df['Exited']"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"SeBizmWM01r8","colab_type":"code","colab":{}},"source":["from sklearn.model_selection import train_test_split\n","\n","X_train, X_test, y_train, y_test = train_test_split(X , y, test_size = 0.1)\n","X_train, X_val, y_train, y_val = train_test_split(X , y, test_size = 0.1)\n","\n","print(X_train.shape)"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"-DJrD5LK01r_","colab_type":"code","colab":{}},"source":["from sklearn.preprocessing import StandardScaler\n","sc = StandardScaler()\n","X_train = sc.fit_transform(X_train)\n","X_test = sc.transform(X_test)\n","X_val = sc.transform(X_val)"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"_G1rFBZZ01sB","colab_type":"text"},"source":["## Construindo o modelo"]},{"cell_type":"markdown","metadata":{"id":"R-YJYGJs01sC","colab_type":"text"},"source":["Agora com o dados prontos vamos montar a nossa rede neural. Vamos usar a library [Keras](https://keras.io) rodando em cima do [TensorFlow](https://tensorflow.org/)\n","\n","\n","1. Definição da arquitetura\n","\n","2. Compilação\n","\n","3. Treinamento\n","\n","4. Avaliação"]},{"cell_type":"markdown","metadata":{"id":"xyW6ePju01sC","colab_type":"text"},"source":["### 1. Definição da arquitetura: \n","Definir a arquitetura da rede"]},{"cell_type":"code","metadata":{"id":"kQPVavi-01sD","colab_type":"code","colab":{}},"source":["import keras\n","from keras.models import Sequential\n","from keras.layers import Dense\n","from keras.optimizers import Adam"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"c3vTyK8M01sF","colab_type":"code","colab":{}},"source":["def build_model():\n"," model = Sequential()\n"," \n"," # primeira camada adiciona o shape do input\n"," # adiciona a funcao de ativacao\n"," # quantidade de units (neurônios)\n"," # também é possível alterar a inicializacao, bias, entre outros -- https://keras.io/layers/core/\n"," model.add(Dense(units=10, input_dim=12, activation='relu'))\n"," model.add(Dense(10, activation='relu'))\n"," \n"," #Camada de saida com o resultado de 1 classe e a ativação sigmoid -- outras funções de ativação: https://keras.io/activations/\n"," model.add(Dense(1, activation='sigmoid'))\n"," return model"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"dd61j62S01sI","colab_type":"text"},"source":["### Vamos entender melhor as funções de ativação:"]},{"cell_type":"markdown","metadata":{"id":"qnut6mXL01sI","colab_type":"text"},"source":["Em cada neurônio da rede há uma função de ativação, que decide se o neurônio deve ser *ativado*, e transmitir informações para a próxima camada.\n","\n","![](https://i1.wp.com/deeplearningbook.com.br/wp-content/uploads/2018/02/act.png?w=406)\n","\n","A função mais comum nas camadas intermediárias é a relu:\n","\n","![](https://cdn-images-1.medium.com/max/937/1*oePAhrm74RNnNEolprmTaQ.png)\n","\n","Na camada de saída a rede precisa nos retornar a probabilidade do cliente fazer o cancelamento.\n","\n","Por ser uma probabilidade (de 0 a 1), nós usamos a função sigmoid:\n","\n","![as vezes a função sigmóide é simplesmente representada pela curva S](https://sabedoriararefeita.files.wordpress.com/2016/02/ann_sigmoid.png?w=615)\n","\n","\n","Outras funções comuns:\n","\n","Softmax -> Usada na camada de output para problemas de multiclasse, a soma das probabilidades de todas as classes dará 1.\n","\n","elu -> para ser usada nas camadas intermediarias no lugar da relu, uma exponencial é aplicada nos valores menores que 0.\n","\n","> Em regressão não há função de ativação na camada de output\n","\n","outras funções de ativação: https://keras.io/activations/\n","explicações extras: http://deeplearningbook.com.br/funcao-de-ativacao/"]},{"cell_type":"code","metadata":{"id":"GqBxWWSX01sJ","colab_type":"code","colab":{}},"source":["model = build_model()"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"scrolled":true,"id":"R2-4sNUG01sL","colab_type":"code","colab":{}},"source":["model.summary()"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"2F6w5JCt01sP","colab_type":"text"},"source":["> Podemos ver que na primeira camada 130 parâmetros (pesos) serão aprendidos ((12 inputs x 10 layers) + (1 bias * 10 layers))"]},{"cell_type":"markdown","metadata":{"id":"pGR3b2Sw01sP","colab_type":"text"},"source":["### 2. Compilar o modelo:\n","\n","Definer como a rede irá aprender. Qual o otimizador com os parâmetros de learning rate, função e parametros específicos da função e a loss function.\n"]},{"cell_type":"code","metadata":{"id":"3_XHomw-01sQ","colab_type":"code","colab":{}},"source":["# outras funções de loss: https://keras.io/losses/\n","# outros optimizers: https://keras.io/optimizers/\n","adam = Adam(lr=0.01)\n","model.compile(loss='binary_crossentropy', \n"," optimizer=adam,\n"," metrics=['accuracy'])"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"1xuR3OIU01sT","colab_type":"text"},"source":["### Vamos entender como a rede aprende:"]},{"cell_type":"markdown","metadata":{"id":"1IDh89q001sU","colab_type":"text"},"source":["Para aprender os parâmetros $w$ e $b$ é preciso uma **função de custo**. Primeiro, vamos definir uma função de perda ou $Loss Function$ de modo que quanto mais próximo da resposta certa, menor seja o valor dessa função:\n","\n","$L(\\hat{y},y)=-(y\\log{\\hat{y}} + (1-y)\\log{(1-\\hat{y})})$ (binary_crossentropy)\n","\n","> Se uma instância tem label 1, então $(1-y)$ é $0$, deixando apenas o lado esquerdo da equação. Pra que ele seja o menor possível, $\\hat{y}$ precisa ser o maior possível, no caso o mais próximo de 1. O oposto também se aplica para quando o label é 0.\n","\n","Com isso, temos a funcão de custo:\n","\n","$J(w,b)=\\frac{1}{m}\\sum_{i=1}^{m}L(\\hat{y}^i,y^i)$\n","\n","Dado nosso custo, queremos encontrar $w$ e $b$ que minimize esse custo. Para isso utilizamos o **Gradiente Descendente**. A função de custo é uma funcão convexa, como uma bacia, então o que o gradiente faz é ir descendo o mais rápido possível até chegar no fundo da bacia, no menor ponto, independente do ponto inicial.\n","\n","![enter image description here](https://blog.paperspace.com/content/images/2018/05/68747470733a2f2f707669676965722e6769746875622e696f2f6d656469612f696d672f70617274312f6772616469656e745f64657363656e742e676966.gif)\n","\n","Para fazer essa \"decida\", utilizaremos a derivada do custo e uma taxa de aprendizado ou *learning rate*, da seguinte forma:\n","\n","A cada iteração do algoritmo temos $w = w - \\alpha \\frac{\\mathrm{d}J}{\\mathrm{d}w}$, sendo $\\alpha$ o learning rate.\n","\n","De modo geral, atualizamos w e b a cada iteração, sendo a velocidade controlada pelo learning rate, até chegarmos no ponto mínimo de custo."]},{"cell_type":"markdown","metadata":{"id":"W4RwH9Jb01sV","colab_type":"text"},"source":["**Mas o que é o Adam então?**"]},{"cell_type":"markdown","metadata":{"id":"oTnbH0jp01sX","colab_type":"text"},"source":["Algoritmo de otimização da taxa de aprendizado adaptável que foi projetado especificamente para o treinamento de redes neurais profundas, pode ser usado em vez do procedimento clássico de descida de gradiente estocástico (SGD) para atualizar os pesos da rede de forma iterativa com base nos dados de treinamento.\n","\n","![](https://cdn-images-1.medium.com/max/1600/1*X9gB3l_Wh5owNPCUsaYQVQ.png)\n","\n","Mais informações: [artigo original](https://arxiv.org/abs/1412.6980), [post explicativo](https://towardsdatascience.com/adam-latest-trends-in-deep-learning-optimization-6be9a291375c), [outros otimizadores](http://ruder.io/optimizing-gradient-descent/)\n","\n"]},{"cell_type":"markdown","metadata":{"id":"eKEsEXn401sX","colab_type":"text"},"source":["> **Importante**: quando estiverem fazendo experimentos com NN, testem com SGD e Adam e com diferentes **LEARNING RATES**.\n"]},{"cell_type":"markdown","metadata":{"id":"jwITCmDi01sY","colab_type":"text"},"source":["### 3. Treinamento"]},{"cell_type":"code","metadata":{"id":"RyxaBoNB01sZ","colab_type":"code","colab":{}},"source":["model.fit(x=X_train, y=y_train, validation_data=(X_val,y_val), batch_size=16, epochs=10)"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"xhYl1kcL01sb","colab_type":"text"},"source":["> Percebemos que só com 10 épocas a rede ainda não tinha convergido, o loss ainda estava caindo, então poderíamos treinar por mais épocas!"]},{"cell_type":"markdown","metadata":{"id":"qQGY_Rjt01sb","colab_type":"text"},"source":["Temos dois parâmetros importantes no treinamento:\n","- Número de épocas: Quantas vezes a rede vai passar por todos as instâncias\n","- Tamanho do batch: Qual o tamanho do bloco que ela vai usar, ou seja, quantas instâncias por vez passarão pela rede\n"]},{"cell_type":"markdown","metadata":{"id":"kOFC_EIE01sb","colab_type":"text"},"source":["### 4. Avaliação"]},{"cell_type":"code","metadata":{"id":"usQeizWV01sc","colab_type":"code","colab":{}},"source":["y_pred = model.predict(X_test)\n","y_pred = (y_pred > 0.5)"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"r67tho6C01sf","colab_type":"code","colab":{}},"source":["from sklearn.metrics import confusion_matrix, accuracy_score, recall_score, precision_score"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"YSurd8ry01sg","colab_type":"code","colab":{}},"source":["accuracy_score(y_test, y_pred)"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"Vtobs9R401si","colab_type":"code","colab":{}},"source":["cm = confusion_matrix(y_test, y_pred)\n","print(cm)"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"FIgnuVeTGKhU","colab_type":"code","colab":{}},"source":["recall_score(y_test, y_pred)"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"TY1vt9AyHOFE","colab_type":"code","colab":{}},"source":["precision_score(y_test, y_pred)"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"YMEwIDCUGnNb","colab_type":"text"},"source":["Perceba que apesar da nossa acurácia ser alta, a qualidade do modelo é ruim com baixa sensibilidade. Vamos retreinar o mesmo modelo, desta vez passando peso para as classes."]},{"cell_type":"code","metadata":{"id":"ThkZfU-KG4xS","colab_type":"code","colab":{}},"source":["model = build_model()\n","model.compile(loss='binary_crossentropy', \n"," optimizer=adam,\n"," metrics=['accuracy'])\n","\n"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"fEZGp8ilG45A","colab_type":"code","colab":{}},"source":["model.fit(x=X_train, y=y_train, validation_data=(X_val,y_val), batch_size=16, epochs=10, class_weight={0:0.2,1:0.8})"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"SMbh_RJVHcIS","colab_type":"code","colab":{}},"source":["y_pred = model.predict(X_test)\n","y_pred = (y_pred > 0.5)\n","\n","cm = confusion_matrix(y_test, y_pred)\n","print(cm)"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"MahBjtzVEJ8B","colab_type":"text"},"source":["## Exercício:\n","Crie uma nova arquitetura de rede para o mesmo dataset. Mude também o learning rate e a quantidade de épocas e compare os resultados\n"]},{"cell_type":"code","metadata":{"id":"_YaUW3OvFYv9","colab_type":"code","colab":{}},"source":["def build_model2():\n"," model = Sequential()\n"," \n"," ## TODO defina a arquitetura da rede\n"," \n"," return model"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"1-omt5xgFY3x","colab_type":"code","colab":{}},"source":["model2 = build_model2()\n","model2.summary()"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"eYwBkuuBFY_f","colab_type":"code","colab":{}},"source":["## TODO defina o learning rate\n","adam = Adam(lr= )\n","model2.compile(loss='binary_crossentropy', \n"," optimizer=adam,\n"," metrics=['accuracy'])"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"b7ghlANBFZHY","colab_type":"code","colab":{}},"source":["## TODO defina o total de épocas\n","model2.fit(x=X_train, y=y_train, validation_data=(X_val,y_val), batch_size=16, epochs= )"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"ULu15NUQFZS_","colab_type":"code","colab":{}},"source":["y_pred = model2.predict(X_test)\n","y_pred = (y_pred > 0.5)\n","cm = confusion_matrix(y_test, y_pred)\n","print(cm)"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"Zof3PBhF01sk","colab_type":"text"},"source":["## Por que o crescimento de Deep Learning?\n","\n","\"drawing\"\n","\n","Algoritmos tradicionais tendem a estabilizar a performance apartir de uma certa quantidade de dados, enquanto redes neurais tendem a ficar cada vez melhores quanto mais dados são utilizados para o aprendizado.\n","\n","Portanto, o principal motivo que faz com que as NN cresçam nos últimos anos é o grande aumento na quantidade de **dados** disponíveis. Além disso, o poder **computacional** também é muito maior nos dias atuais, principalmente com a utilização de GPU's. O que também permitiu o desenvolvimento de **algoritmos** mais complexos e potentes.\n"]},{"cell_type":"markdown","metadata":{"id":"WfkXMpe601sl","colab_type":"text"},"source":["Neural Networks, mais especificamente Deep Learning, tem grande aplicações em datas não-estruturados, como: Imagens, Aúdios e Textos."]}]} \ No newline at end of file diff --git a/5.1 Deep Learning/notebooks/part2 - cnn.ipynb b/5.1 Deep Learning/notebooks/part2 - cnn.ipynb new file mode 100644 index 0000000..167bf4e --- /dev/null +++ b/5.1 Deep Learning/notebooks/part2 - cnn.ipynb @@ -0,0 +1,908 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "name": "deep-learning-part2.ipynb", + "provenance": [], + "collapsed_sections": [] + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + }, + "accelerator": "GPU" + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "rLLmnh67DocC", + "colab_type": "text" + }, + "source": [ + "# configurando drive" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "TJ9Gozb4CLEh", + "colab_type": "code", + "colab": {} + }, + "source": [ + "!apt-get install -y -qq software-properties-common python-software-properties module-init-tools\n", + "!add-apt-repository -y ppa:alessandro-strada/ppa 2>&1 > /dev/null\n", + "!apt-get update -qq 2>&1 > /dev/null\n", + "!apt-get -y install -qq google-drive-ocamlfuse fuse\n", + "from google.colab import auth\n", + "auth.authenticate_user()\n", + "from oauth2client.client import GoogleCredentials\n", + "creds = GoogleCredentials.get_application_default()\n", + "import getpass\n", + "!google-drive-ocamlfuse -headless -id={creds.client_id} -secret={creds.client_secret} < /dev/null 2>&1 | grep URL\n", + "vcode = getpass.getpass()\n", + "!echo {vcode} | google-drive-ocamlfuse -headless -id={creds.client_id} -secret={creds.client_secret}" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "8Y80l37cCWwJ", + "colab_type": "code", + "colab": {} + }, + "source": [ + "!mkdir -p drive\n", + "!google-drive-ocamlfuse drive" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "JQU0xXfqtA_Y" + }, + "source": [ + "# Deep Learning - parte 2: Convolutional Neural Network" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "m9fA1rJytAWm" + }, + "source": [ + "Redes convolucionais são usadas principalmente para classificação de imagens.\n", + "\n", + "## Como elas funcionam?\n", + "\n", + "Filtros convolucionais são usados para extrair features de imagens. Vamos olhar um exemplo de como extrair bordas de imagens:\n", + "\n", + "\"drawing\"\n", + "\n", + "Nas redes convolucionais esses filtros são aplicados em várias camadas:\n", + "\n", + "\n", + "\n", + "Os valores dos filtros são aprendidos, portanto a própria rede aprende quais características são relevantes.\n", + "\n", + "![](https://adeshpande3.github.io/assets/deconvnet.png)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "trJkG4PzRY4J" + }, + "source": [ + "## Construindo uma CNN pra predizer lateralidade do raio-X" + ] + }, + { + "cell_type": "code", + "metadata": { + "colab_type": "code", + "id": "0RVx7UjzRnuQ", + "colab": {} + }, + "source": [ + "# Primeiro vamos definir os imports\n", + "\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "\n", + "import time\n", + "import os\n", + "import datetime\n", + "\n", + "\n", + "from keras import datasets, Model\n", + "from keras.layers.convolutional import Conv2D\n", + "from keras.layers.convolutional import MaxPooling2D\n", + "from keras.layers import Flatten, GlobalAveragePooling2D\n", + "from keras.layers.core import Dropout\n", + "from keras.layers.core import Dense\n", + "from keras.optimizers import Adam\n", + "from keras import Sequential\n", + "from keras.utils import to_categorical\n", + "from keras.callbacks import ModelCheckpoint, EarlyStopping\n", + "from keras.applications import VGG16\n", + "from keras.preprocessing.image import ImageDataGenerator\n", + "from keras.models import load_model\n", + "from keras import backend\n", + "import tensorflow as tf\n", + "from random import randint\n", + "\n", + "from keras.preprocessing.image import load_img, img_to_array\n", + "\n", + "import glob" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "y7sgifiKLzP7", + "colab_type": "text" + }, + "source": [ + "Nosso desafio é criar uma rede para aprender se um raio X é lateral ou de frente:\n", + "\n", + "![alt text](https://github.com/jessica-santos/qcon_notebook/raw/066adc30051b0a5b6e6a3cbab31b00fb6b75dbd5/lateral.png)\n", + "\n", + "** O ideal é sempre visualizar uma amostra das imagens de cada classe e, assim como fazemos feature engineering em variáveis, também podemos ver se é necessário fazer alguma transformação ou normalização nas imagens." + ] + }, + { + "cell_type": "code", + "metadata": { + "colab_type": "code", + "id": "DfkwmsT3YJtO", + "colab": {} + }, + "source": [ + "!ls /content/drive/images-chest-orientation" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "gz7TRoSNB4hr", + "colab_type": "code", + "colab": {} + }, + "source": [ + "!ls /content/drive/images-chest-orientation/train" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "nI79O6avMaSz", + "colab_type": "code", + "colab": {} + }, + "source": [ + "files_frente = glob.glob('drive/images-chest-orientation/train/frente/*.jpg')\n", + "for i in range(5):\n", + " plt.figure(figsize=(2,2))\n", + " indx = randint(0,len(files_frente))\n", + " im = plt.imread(files_frente[indx])\n", + " plt.imshow(im)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "7r73dBUiM4Ix", + "colab_type": "code", + "colab": {} + }, + "source": [ + "files_lateral = glob.glob('drive/images-chest-orientation/train/lateral/*.jpg')\n", + "for i in range(5):\n", + " plt.figure(figsize=(2,2))\n", + " indx = randint(0,len(files_lateral))\n", + " im = plt.imread(files_lateral[indx])\n", + " plt.imshow(im)\n" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "MkXsrXz_SgcQ" + }, + "source": [ + "## Input de dados\n", + "\n", + "Existem várias formas de inputar os dados para treinamento, vamos usar o `Image Data Generator` para ler as imagens a partir do disco" + ] + }, + { + "cell_type": "code", + "metadata": { + "colab_type": "code", + "id": "PxMQU9KBT_LK", + "colab": {} + }, + "source": [ + "# aqui definimos as transformações que serão aplicadas na imagem e a % de dados \n", + "# que serão usados para validação\n", + "\n", + "#estamos nesse caso apenas normalizando a imagem dividindo por 255\n", + "\n", + "data_generator = ImageDataGenerator(rescale=1./255, validation_split=0.30)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab_type": "code", + "id": "TdFCG_SUUe91", + "colab": {} + }, + "source": [ + "# para criar os generators precisamos definir o path da pasta raiz com as imagens e o tamanho da BATCH SIZE\n", + "\n", + "path = '/content/drive/images-chest-orientation/train/'\n", + "BATCH_SIZE = 50\n", + "\n", + "\n", + "train_generator = data_generator.flow_from_directory(path, shuffle=True, seed=13, classes=['frente', 'lateral'],\n", + " class_mode='categorical', batch_size=BATCH_SIZE, subset=\"training\")\n", + "\n", + "validation_generator = data_generator.flow_from_directory(path, shuffle=True, seed=13, classes=['frente', 'lateral'],\n", + " class_mode='categorical', batch_size=BATCH_SIZE, subset=\"validation\")" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "gnO2vFANY-A_" + }, + "source": [ + "Vamos dar uma olhada em como ficaram as imagens:" + ] + }, + { + "cell_type": "code", + "metadata": { + "colab_type": "code", + "id": "ht2Dtb7GYY29", + "colab": {} + }, + "source": [ + "plt.imshow(train_generator[3][0][0])\n", + "shape = train_generator[3][0][0].shape" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab_type": "code", + "id": "cyl9SIuoZV4u", + "colab": {} + }, + "source": [ + "plt.imshow(validation_generator[1][0][2])" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "76JMntETaCK5" + }, + "source": [ + "## Definindo a arquitetura:\n", + "\n", + "Vamos criar uma rede pequena que consiga identificar corretamente essas imagens:" + ] + }, + { + "cell_type": "code", + "metadata": { + "colab_type": "code", + "id": "O7bAtj5HZ0zS", + "colab": {} + }, + "source": [ + "def build_model(shape):\n", + " '''\n", + " Constroi as camadas da rede\n", + " :return: modelo construido\n", + " '''\n", + " \n", + " model = Sequential()\n", + "\n", + " # primeira camada adiciona o shape do input\n", + " # adiciona a funcao de ativacao\n", + " # padding define o output da camada, \"same\" eh mesmo tamanho\n", + " # tamanho do kernel (mascara)\n", + " # quantidade de filtros (neurônios)\n", + " # também é possível alterar a inicializacao, bias, entre outros -- https://keras.io/layers/convolutional/#conv2d\n", + " model.add(Conv2D(filters=64, kernel_size=2, padding='same', activation='relu', input_shape=shape, kernel_initializer='glorot_uniform'))\n", + " #Tamanho do downsampling\n", + " model.add(MaxPooling2D(pool_size=2))\n", + " # Fracao das unidades que serao zeradas\n", + " model.add(Dropout(0.3))\n", + "\n", + " # Segunda camada\n", + " model.add(Conv2D(filters=128, kernel_size=2, padding='same', activation='relu', kernel_initializer='glorot_uniform'))\n", + " model.add(MaxPooling2D(pool_size=2))\n", + " model.add(Dropout(0.3))\n", + "\n", + " # Da um reshape no output transformando em array\n", + " model.add(Flatten())\n", + "\n", + " # Camada full-connected \n", + " model.add(Dense(256, activation='relu'))\n", + " model.add(Dropout(0.5))\n", + "\n", + " #Camada de saida com o resultado das classes\n", + " model.add(Dense(2, activation='sigmoid'))\n", + "\n", + " return model" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "YicO_oLbB4iJ", + "colab_type": "text" + }, + "source": [ + "Outros tipos de camadas utilizadas:\n", + "\n", + "MaxPooling:\n", + "Realiza o downsampling pós convolução.\n", + "\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "AbFXboJXB4iK", + "colab_type": "text" + }, + "source": [ + "Dropout:\n", + "Em cada época desativa aleatoriamente um % de neurônios. Evita overfitting\n", + " \n", + "" + ] + }, + { + "cell_type": "code", + "metadata": { + "colab_type": "code", + "id": "bXwTN58aao4k", + "scrolled": true, + "colab": {} + }, + "source": [ + "model = build_model(shape)\n", + "model.summary()" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab_type": "code", + "id": "El7wzNoCatdU", + "colab": {} + }, + "source": [ + "# Compila o modelo definindo: otimizador, metrica e loss function\n", + "model.compile(loss='binary_crossentropy',\n", + " optimizer='adam',\n", + " metrics=['accuracy'])" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "INt1TltSb0Ot" + }, + "source": [ + "## Treinamento\n", + "\n", + "Como lemos os dados usando um generator, o fit do keras também será usando um `fit_generator`.\n", + "\n", + "Também usaremos alguns `callbacks`: \n", + " - ModelCheckPoint para salvar o modelo que tiver o melhor loss durante o treinamento e,\n", + " - EarlyStop para interromper o treinamento caso a rede pare de aprender (convergiu)." + ] + }, + { + "cell_type": "code", + "metadata": { + "colab_type": "code", + "id": "hkByiwpGd5P3", + "colab": {} + }, + "source": [ + "# aqui definimos as transformações que serão aplicadas na imagem e a % de dados \n", + "# que serão usados para validação\n", + "\n", + "#estamos nesse caso apenas normalizando a imagem dividindo por 255\n", + "\n", + "data_generator = ImageDataGenerator(rescale=1./255, validation_split=0.30)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab_type": "code", + "id": "y5IvExyrd5P9", + "colab": {} + }, + "source": [ + "# para criar os generators precisamos definir o path da pasta raiz com as imagens e o tamanho da BATCH SIZE\n", + "\n", + "path = '/content/drive/images-chest-orientation/train/'\n", + "BATCH_SIZE = 50\n", + "\n", + "\n", + "train_generator = data_generator.flow_from_directory(path, shuffle=True, seed=13, classes=['frente', 'lateral'],\n", + " class_mode='categorical', batch_size=BATCH_SIZE, subset=\"training\")\n", + "\n", + "validation_generator = data_generator.flow_from_directory(path, shuffle=True, seed=13, classes=['frente', 'lateral'],\n", + " class_mode='categorical', batch_size=BATCH_SIZE, subset=\"validation\")" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab_type": "code", + "id": "KffsfxWgbyDb", + "colab": {} + }, + "source": [ + "checkpoint = ModelCheckpoint('chest_orientation_model.hdf5', \n", + " monitor='val_loss', \n", + " verbose=1, mode='min', \n", + " save_best_only=True)\n", + "\n", + "early_stop = EarlyStopping(monitor='val_loss',\n", + " min_delta=0.001,\n", + " patience=2, # geralmente colocamos no mínimo 5 epocas\n", + " mode='min',\n", + " verbose=1)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab_type": "code", + "id": "Ca5UO7sNc28i", + "colab": {} + }, + "source": [ + "model.fit_generator(generator=train_generator,\n", + " steps_per_epoch = train_generator.samples//BATCH_SIZE,\n", + " validation_data=validation_generator,\n", + " validation_steps=validation_generator.samples//BATCH_SIZE,\n", + " epochs= 50,\n", + " callbacks=[checkpoint, early_stop]\n", + " )" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "yta0wNPbm334" + }, + "source": [ + "## Avaliação:\n", + "\n", + "Sempre importante separar uma quantidade de dados para testar o modelo no final" + ] + }, + { + "cell_type": "code", + "metadata": { + "colab_type": "code", + "id": "zqDb2-f3dbiV", + "colab": {} + }, + "source": [ + "import glob" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab_type": "code", + "id": "1rctpVhgd20q", + "colab": {} + }, + "source": [ + "test_set = glob.glob('/content/drive/images-chest-orientation/test/**/*.jpg', recursive=True)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab_type": "code", + "id": "CQa1Xc_SjUFx", + "colab": {} + }, + "source": [ + "test_set" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab_type": "code", + "id": "x34Idp6pkDfm", + "colab": {} + }, + "source": [ + "# temos que fazer o load do model que teve o melhor loss\n", + "model = load_model('chest_orientation_model.hdf5')" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab_type": "code", + "id": "vG5SpxO3keQZ", + "colab": {} + }, + "source": [ + "image_test = np.array([img_to_array(load_img(image_name, target_size=(256, 256), color_mode='rgb'))/255 for image_name in test_set])" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab_type": "code", + "id": "Uy5jPu5Hj4LF", + "colab": {} + }, + "source": [ + "y_pred = model.predict(image_test)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab_type": "code", + "id": "3jSi0qLEjVdw", + "colab": {} + }, + "source": [ + "y_true = [1,1,1,1,1,0,0,0,0,0]\n", + "labels = ['Frente', 'Lateral']\n", + "figure = plt.figure(figsize=(20, 8))\n", + "for i in range(10):\n", + " ax = figure.add_subplot(3, 5, i + 1, xticks=[], yticks=[])\n", + " # Display each image\n", + " im = plt.imread(test_set[i])\n", + " ax.imshow(im)\n", + " predict_index = np.argmax(y_pred[i])\n", + " true_index = y_true[i]\n", + " # Set the title for each image\n", + " ax.set_title(\"{} ({})\".format(labels[predict_index], \n", + " labels[true_index]),\n", + " color=(\"green\" if predict_index == true_index else \"red\"))" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "ZvZ5YY5RnWk9" + }, + "source": [ + "## Transfer Learning" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "02FZWBmzB4iv", + "colab_type": "text" + }, + "source": [ + "Nem sempre precisamos definir a arquitetura da nossa rede do zero. Para reconhecimento de imagens existem arquiteturas já definidas e pré-treinadas com o Imagenet - um dataset com 1.2 milhões de imagens e 1000 categorias.\n", + "\n", + "![](https://cdn-images-1.medium.com/max/1400/1*n16lj3lSkz2miMc_5cvkrA.jpeg)\n", + "[referência](https://towardsdatascience.com/neural-network-architectures-156e5bad51ba)\n", + "\n", + "Para usar essas redes utilizamos **transfer learning**, transferir os pesos já aprendidos nessas redes para uma tarefa." + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "TUuc45kLfiU9", + "colab_type": "code", + "colab": {} + }, + "source": [ + "data_generator = ImageDataGenerator(samplewise_center=False, \n", + " samplewise_std_normalization=False, \n", + " horizontal_flip=True, \n", + " vertical_flip=False, \n", + " height_shift_range=0.1, \n", + " width_shift_range=0.1, \n", + " brightness_range=[0.7, 1.5],\n", + " rotation_range=3, \n", + " shear_range=0.01,\n", + " fill_mode='nearest',\n", + " zoom_range=0.125,\n", + " rescale = 1./255, validation_split=0.30)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "DtQhaWnYfkb0", + "colab_type": "code", + "colab": {} + }, + "source": [ + "path = '/content/drive/images-chest-orientation/train/'\n", + "BATCH_SIZE = 50\n", + "\n", + "\n", + "train_generator = data_generator.flow_from_directory(path, shuffle=True, seed=13, classes=['frente', 'lateral'],\n", + " class_mode='categorical', batch_size=BATCH_SIZE, subset=\"training\")\n", + "\n", + "validation_generator = data_generator.flow_from_directory(path, shuffle=True, seed=13, classes=['frente', 'lateral'],\n", + " class_mode='categorical', batch_size=BATCH_SIZE, subset=\"validation\")" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "qmCm_subB4iv", + "colab_type": "code", + "colab": {} + }, + "source": [ + "from keras.applications import MobileNet" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Kxo16tQDe6Z4", + "colab_type": "text" + }, + "source": [ + "### **Usaremos a MobileNet**\n", + "\n", + "\n", + "\n", + "![alt text](https://i.ytimg.com/vi/onKT9OwMiMU/maxresdefault.jpg)" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "ps1nh5oxB4i2", + "colab_type": "code", + "colab": {} + }, + "source": [ + "def build_model(shape):\n", + " '''\n", + " Constroi as camadas da rede\n", + " :return: modelo construido\n", + " '''\n", + " \n", + " base_model = MobileNet(weights = \"imagenet\", include_top=False, input_shape = shape)\n", + " # congelando camadas que não iremos treinar.\n", + " # para congelar alguns layers específicos basta passar o indice: for layer in mobile.layers[:5]:\n", + " for layer in base_model.layers[:3]:\n", + " layer.Trainable=False\n", + " \n", + " x = base_model.output\n", + " x = GlobalAveragePooling2D()(x)\n", + " predictions = Dense(2, activation='sigmoid')(x)\n", + " \n", + " model = Model(input = base_model.input, output = predictions)\n", + "\n", + " return model" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "qx314mPXB4i5", + "colab_type": "code", + "colab": {} + }, + "source": [ + "model = build_model(shape)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "eT3z2d8BB4i7", + "colab_type": "code", + "colab": {} + }, + "source": [ + "model.summary()" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "TJearDCHB4i9", + "colab_type": "code", + "colab": {} + }, + "source": [ + "model.compile(loss='binary_crossentropy',\n", + " optimizer='adam',\n", + " metrics=['accuracy'])" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "OAQpT8XSB4i-", + "colab_type": "code", + "colab": {} + }, + "source": [ + "model.fit_generator(generator=train_generator,\n", + " steps_per_epoch = train_generator.samples//BATCH_SIZE,\n", + " validation_data=validation_generator,\n", + " validation_steps=validation_generator.samples//BATCH_SIZE,\n", + " epochs= 50,\n", + " callbacks=[checkpoint, early_stop]\n", + " )" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "K1BpB2tSB4jB", + "colab_type": "text" + }, + "source": [ + "- Vamos visualizar algumas classificações" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "c8T7DZeGCXsP", + "colab_type": "code", + "colab": {} + }, + "source": [ + "y_pred = model.predict(image_test)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "MluovNpwCO2o", + "colab_type": "code", + "colab": {} + }, + "source": [ + "y_true = [1,1,1,1,1,0,0,0,0,0]\n", + "labels = ['Frente', 'Lateral']\n", + "figure = plt.figure(figsize=(20, 8))\n", + "for i in range(10):\n", + " ax = figure.add_subplot(3, 5, i + 1, xticks=[], yticks=[])\n", + " # Display each image\n", + " im = plt.imread(test_set[i])\n", + " ax.imshow(im)\n", + " predict_index = np.argmax(y_pred[i])\n", + " true_index = y_true[i]\n", + " # Set the title for each image\n", + " ax.set_title(\"{} ({})\".format(labels[predict_index], \n", + " labels[true_index]),\n", + " color=(\"green\" if predict_index == true_index else \"red\"))" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "k7J_7jIVB4jB", + "colab_type": "text" + }, + "source": [ + "## Razões de porque sua rede pode não estar funcionando:\n", + "\n", + "https://blog.slavv.com/37-reasons-why-your-neural-network-is-not-working-4020854bd607" + ] + } + ] +} \ No newline at end of file diff --git a/5.1 Deep Learning/notebooks/usages_dl.png b/5.1 Deep Learning/notebooks/usages_dl.png new file mode 100644 index 0000000..2996d23 Binary files /dev/null and b/5.1 Deep Learning/notebooks/usages_dl.png differ diff --git a/5.1 Deep Learning/slides/Machine Learning Parte 2 - Deep Learning.pdf b/5.1 Deep Learning/slides/Machine Learning Parte 2 - Deep Learning.pdf new file mode 100644 index 0000000..312a4ca Binary files /dev/null and b/5.1 Deep Learning/slides/Machine Learning Parte 2 - Deep Learning.pdf differ diff --git a/5.1 Deep Learning/slides/Machine Learning Parte 2 - Deep Learning.pptx b/5.1 Deep Learning/slides/Machine Learning Parte 2 - Deep Learning.pptx new file mode 100644 index 0000000..a41268a Binary files /dev/null and b/5.1 Deep Learning/slides/Machine Learning Parte 2 - Deep Learning.pptx differ diff --git a/5.2 NLP/aula_nlp_topic_modeling_text_classification-a-preencher.ipynb b/5.2 NLP/aula_nlp_topic_modeling_text_classification-a-preencher.ipynb new file mode 100644 index 0000000..302d0e1 --- /dev/null +++ b/5.2 NLP/aula_nlp_topic_modeling_text_classification-a-preencher.ipynb @@ -0,0 +1,453 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Processamento de Linguagem Natural" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "O objetivo do PLN é fornecer aos computadores a capacidade de entender e compor textos. “Entender” um texto significa reconhecer o contexto, fazer análise sintática, semântica, léxica e morfológica, criar resumos, extrair informação, interpretar os sentidos, analisar sentimentos e até aprender conceitos com os textos processados.\n", + "\n", + "\n", + "Neste notebook, exploraremos dois problemas clássicos de PLN: `classificação de texto` e `agrupamento de tópicos`;" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Bibliotecas Auxiliares" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[nltk_data] Downloading package stopwords to\n", + "[nltk_data] /Users/thaisalmeida/nltk_data...\n", + "[nltk_data] Package stopwords is already up-to-date!\n" + ] + }, + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import pandas as pd\n", + "from re import sub\n", + "\n", + "from numpy import asarray\n", + "import matplotlib.pyplot as plt\n", + "\n", + "from nltk.corpus import stopwords\n", + "from nltk.tokenize import RegexpTokenizer\n", + "from nltk.stem import PorterStemmer \n", + "from nltk import download\n", + "\n", + "from sklearn.model_selection import StratifiedKFold\n", + "from sklearn.ensemble import RandomForestClassifier\n", + "from sklearn.cluster import KMeans\n", + "from sklearn.metrics import classification_report\n", + "from sklearn.feature_extraction.text import TfidfVectorizer\n", + "\n", + "from warnings import filterwarnings\n", + "\n", + "filterwarnings('ignore')\n", + "download('stopwords')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Prática I : Identificação de Fake News" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Carregando base de dados" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "fake_set = pd.read_csv('datasets/fakenews_silverman.csv')\n", + "real_set = pd.read_csv('datasets/realnews_silverman.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "|fake news| = 467 samples \n", + "|legitimate news| = 467 samples\n" + ] + } + ], + "source": [ + "print(f'|fake news| = {fake_set.shape[0]} samples \\n|legitimate news| = {real_set.shape[0]} samples')" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " headline \\\n", + "0 Apple’s next major Mac revealed: the radically... \n", + "1 Report: A Radically Redesigned 12-Inch MacBook... \n", + "2 Apple may launch 12-inch MacBook Air with Reti... \n", + "\n", + " main_content label \n", + "0 Apple is preparing an all-new MacBook Air for ... 1 \n", + "1 Everyone's been waiting years and years for a ... 1 \n", + "2 Apple would never lower itself to rubbing elbo... 1 " + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "real_set.head(3)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "|corpus| = 934 samples\n" + ] + } + ], + "source": [ + "news_list = pd.concat([fake_set['headline'],real_set['headline']], axis=0, ignore_index=True)\n", + "target_list = pd.concat([fake_set['label'],real_set['label']], axis=0, ignore_index=True)\n", + "\n", + "print(f'|corpus| = {news_list.shape[0]} samples')" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "scrolled": false + }, + "outputs": [], + "source": [ + "# Limpeza de dados + Engenharia de Atributos..." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Engenharia de Atributos + Classificação de Texto...." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Desafio:\n", + "\n", + "- Criar um modelo de identificação de notícias falsas utilizando o `conteúdo` das notícias representado por `bigramas` ponderados por TF-IDF." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Prática II : Agrupamento em Tópicos" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Carregando base de dados" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "fake_set = pd.read_csv('datasets/fakenews_silverman.csv')\n", + "real_set = pd.read_csv('datasets/realnews_silverman.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "|fake news| = 467 samples \n", + "|legitimate news| = 467 samples\n" + ] + } + ], + "source": [ + "print(f'|fake news| = {fake_set.shape[0]} samples \\n|legitimate news| = {real_set.shape[0]} samples')" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "|corpus| = 934 samples\n" + ] + } + ], + "source": [ + "news_list = pd.concat([fake_set['headline'],real_set['headline']], axis=0, ignore_index=True)\n", + "target_list = pd.concat([fake_set['label'],real_set['label']], axis=0, ignore_index=True)\n", + "\n", + "print(f'|corpus| = {news_list.shape[0]} samples')" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "# Limpeza de dados + Engenharia de Atributos..." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "# Visualização...." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "# Agrupamento de tópicos..." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Referências:\n", + "\n", + "- https://www.amazon.com.br/Express%C3%B5es-Regulares-Uma-Abordagem-Divertida/dp/8575223372\n", + "- Baeza-Yates, Ricardo, and Berthier Ribeiro-Neto. Recuperação de Informação-: Conceitos e Tecnologia das Máquinas de Busca. Bookman Editora, 2013.\n", + "- https://medium.com/botsbrasil/o-que-%C3%A9-o-processamento-de-linguagem-natural-49ece9371cff" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.4" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/5.2 NLP/aula_nlp_topic_modeling_text_classification.ipynb b/5.2 NLP/aula_nlp_topic_modeling_text_classification.ipynb new file mode 100644 index 0000000..43dfb00 --- /dev/null +++ b/5.2 NLP/aula_nlp_topic_modeling_text_classification.ipynb @@ -0,0 +1,714 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Processamento de Linguagem Natural - Gabarito" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "O objetivo do PLN é fornecer aos computadores a capacidade de entender e compor textos. “Entender” um texto significa reconhecer o contexto, fazer análise sintática, semântica, léxica e morfológica, criar resumos, extrair informação, interpretar os sentidos, analisar sentimentos e até aprender conceitos com os textos processados.\n", + "\n", + "\n", + "Neste notebook, exploraremos dois problemas clássicos de PLN: `classificação de texto` e `agrupamento de tópicos`;" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Bibliotecas Auxiliares" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[nltk_data] Downloading package stopwords to\n", + "[nltk_data] /Users/thaisalmeida/nltk_data...\n", + "[nltk_data] Package stopwords is already up-to-date!\n" + ] + }, + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import pandas as pd\n", + "from re import sub\n", + "\n", + "from numpy import asarray\n", + "import matplotlib.pyplot as plt\n", + "\n", + "from nltk.corpus import stopwords\n", + "from nltk.tokenize import RegexpTokenizer\n", + "from nltk.stem import PorterStemmer \n", + "from nltk import download\n", + "\n", + "from sklearn.model_selection import StratifiedKFold\n", + "from sklearn.ensemble import RandomForestClassifier\n", + "from sklearn.cluster import KMeans\n", + "from sklearn.metrics import classification_report\n", + "from sklearn.feature_extraction.text import TfidfVectorizer\n", + "\n", + "from warnings import filterwarnings\n", + "\n", + "filterwarnings('ignore')\n", + "download('stopwords')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Prática I : Identificação de Fake News" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Carregando base de dados" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "fake_set = pd.read_csv('datasets/fakenews_silverman.csv')\n", + "real_set = pd.read_csv('datasets/realnews_silverman.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "|fake news| = 467 samples \n", + "|legitimate news| = 467 samples\n" + ] + } + ], + "source": [ + "print(f'|fake news| = {fake_set.shape[0]} samples \\n|legitimate news| = {real_set.shape[0]} samples')" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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0Apple’s next major Mac revealed: the radically...Apple is preparing an all-new MacBook Air for ...1
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" + ], + "text/plain": [ + " headline \\\n", + "0 Apple’s next major Mac revealed: the radically... \n", + "1 Report: A Radically Redesigned 12-Inch MacBook... \n", + "2 Apple may launch 12-inch MacBook Air with Reti... \n", + "\n", + " main_content label \n", + "0 Apple is preparing an all-new MacBook Air for ... 1 \n", + "1 Everyone's been waiting years and years for a ... 1 \n", + "2 Apple would never lower itself to rubbing elbo... 1 " + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "real_set.head(3)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "|corpus| = 934 samples\n" + ] + } + ], + "source": [ + "news_list = pd.concat([fake_set['headline'],real_set['headline']], axis=0, ignore_index=True)\n", + "target_list = pd.concat([fake_set['label'],real_set['label']], axis=0, ignore_index=True)\n", + "\n", + "print(f'|corpus| = {news_list.shape[0]} samples')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Limpeza de dados + Engenharia de Atributos" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "scrolled": false + }, + "outputs": [], + "source": [ + "def remove_stopwords_and_normalize(doc_text, stopwords_hash):\n", + " content = []\n", + " stemmer = PorterStemmer() \n", + " \n", + " for word in doc_text:\n", + " word_clean = word.lower().strip()\n", + " if(stopwords_hash.get(word_clean) == None):\n", + " word_clean = stemmer.stem(word_clean) \n", + " content.append(word_clean)\n", + " return content\n", + "\n", + "def tokenizer(text):\n", + " tokenizer = RegexpTokenizer(r'\\w+')\n", + " tokens = tokenizer.tokenize(text)\n", + " \n", + " return tokens\n", + "\n", + "def data_cleaning(news_list, target_list):\n", + " X_clean, Y_clean = [], []\n", + " \n", + " stopwords_dict = {word:0 for word in stopwords.words('english')} \n", + " \n", + " for idx, news in enumerate(news_list):\n", + " text = sub(r'[^\\w\\s]',' ', news)\n", + " text = sub(r'[^\\D]',' ', text)\n", + " text = tokenizer(text)\n", + " text = remove_stopwords_and_normalize(text, stopwords_dict)\n", + " text = ' '.join(text).strip()\n", + " \n", + " if(len(text) > 0):\n", + " X_clean.append(text)\n", + " Y_clean.append(target_list[idx])\n", + " return X_clean, Y_clean " + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "X, y = data_cleaning(news_list, target_list)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Engenharia de Atributos + Classificação de Texto" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Fold: 1\n", + " precision recall f1-score support\n", + "\n", + " fake 0.82 0.87 0.85 94\n", + " legitimate 0.86 0.81 0.84 94\n", + "\n", + " accuracy 0.84 188\n", + " macro avg 0.84 0.84 0.84 188\n", + "weighted avg 0.84 0.84 0.84 188\n", + " \n", + "\n", + "\n", + "Fold: 2\n", + " precision recall f1-score support\n", + "\n", + " fake 0.77 0.82 0.79 94\n", + " legitimate 0.81 0.76 0.78 94\n", + "\n", + " accuracy 0.79 188\n", + " macro avg 0.79 0.79 0.79 188\n", + "weighted avg 0.79 0.79 0.79 188\n", + " \n", + "\n", + "\n", + "Fold: 3\n", + " precision recall f1-score support\n", + "\n", + " fake 0.79 0.86 0.82 93\n", + " legitimate 0.85 0.77 0.81 93\n", + "\n", + " accuracy 0.82 186\n", + " macro avg 0.82 0.82 0.82 186\n", + "weighted avg 0.82 0.82 0.82 186\n", + " \n", + "\n", + "\n", + "Fold: 4\n", + " precision recall f1-score support\n", + "\n", + " fake 0.81 0.80 0.80 93\n", + " legitimate 0.80 0.82 0.81 93\n", + "\n", + " accuracy 0.81 186\n", + " macro avg 0.81 0.81 0.81 186\n", + "weighted avg 0.81 0.81 0.81 186\n", + " \n", + "\n", + "\n", + "Fold: 5\n", + " precision recall f1-score support\n", + "\n", + " fake 0.80 0.81 0.80 93\n", + " legitimate 0.80 0.80 0.80 93\n", + "\n", + " accuracy 0.80 186\n", + " macro avg 0.80 0.80 0.80 186\n", + "weighted avg 0.80 0.80 0.80 186\n", + " \n", + "\n", + "\n" + ] + } + ], + "source": [ + "X, y = asarray(X), asarray(y)\n", + "\n", + "kfold = StratifiedKFold(n_splits=5, random_state=42, shuffle=True)\n", + "\n", + "iteration = 1\n", + "for train_index, test_index in kfold.split(X, y):\n", + "\n", + " X_train, X_test = X[train_index], X[test_index]\n", + " Y_train, Y_test = y[train_index], y[test_index]\n", + "\n", + " vectorizer = TfidfVectorizer(use_idf=True, ngram_range = (1,1),\\\n", + " min_df = 5, max_df = 0.70)\n", + "\n", + " X_train = vectorizer.fit_transform(X_train)\n", + " X_test = vectorizer.transform(X_test)\n", + "\n", + " classifier = RandomForestClassifier(random_state=5)\n", + " classifier.fit(X_train, Y_train)\n", + " predictions = classifier.predict(X_test)\n", + " \n", + " print(f'Fold: {iteration}')\n", + " print(classification_report(Y_test, predictions, target_names=['fake','legitimate']),'\\n\\n')\n", + " iteration+=1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Desafio:\n", + "\n", + "- Criar um modelo de identificação de notícias falsas utilizando o `conteúdo` das notícias representado por `bigramas` ponderados por TF-IDF." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Prática II : Agrupamento em Tópicos" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Carregando base de dados" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "fake_set = pd.read_csv('datasets/fakenews_silverman.csv')\n", + "real_set = pd.read_csv('datasets/realnews_silverman.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "|fake news| = 467 samples \n", + "|legitimate news| = 467 samples\n" + ] + } + ], + "source": [ + "print(f'|fake news| = {fake_set.shape[0]} samples \\n|legitimate news| = {real_set.shape[0]} samples')" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "|corpus| = 934 samples\n" + ] + } + ], + "source": [ + "news_list = pd.concat([fake_set['headline'],real_set['headline']], axis=0, ignore_index=True)\n", + "target_list = pd.concat([fake_set['label'],real_set['label']], axis=0, ignore_index=True)\n", + "\n", + "print(f'|corpus| = {news_list.shape[0]} samples')" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "def top_cluster_terms(km, tfidf_vectorizer, number_of_clusters):\n", + " order_centroids = km.cluster_centers_.argsort()[:, ::-1]\n", + " terms = tfidf_vectorizer.get_feature_names()\n", + " dist = clusters_distribution(km)\n", + " \n", + " top_ten_list, dist_list = [],[]\n", + " for i in range(number_of_clusters):\n", + " top_ten_words = [terms[ind] for ind in order_centroids[i, :7]]\n", + " print(\"Cluster \",i,f'| Total: {dist[i]}|',' '.join(top_ten_words),)\n", + " \n", + "def clusters_distribution(km):\n", + " clusters_count = {}\n", + " for i in km.labels_:\n", + " if(clusters_count.get(i)!=None):\n", + " clusters_count[i]+=1\n", + " else:\n", + " clusters_count[i]=1\n", + " return clusters_count" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "def remove_stopwords(doc_text, stopwords_hash):\n", + " content = []\n", + " \n", + " for word in doc_text:\n", + " word_clean = word.lower().strip()\n", + " if(stopwords_hash.get(word_clean) == None):\n", + " content.append(word_clean)\n", + " return content\n", + "\n", + "def tokenizer(text):\n", + " tokenizer = RegexpTokenizer(r'\\w+')\n", + " tokens = tokenizer.tokenize(text)\n", + " \n", + " return tokens\n", + "\n", + "def data_cleaning(news_list):\n", + " X_clean = []\n", + " \n", + " stopwords_dict = {word:0 for word in stopwords.words('english')} \n", + " \n", + " for idx, news in enumerate(news_list):\n", + " text = sub(r'[^\\w\\s]',' ', news)\n", + " text = sub(r'[^\\D]',' ', text)\n", + " text = tokenizer(text)\n", + " text = remove_stopwords(text, stopwords_dict)\n", + " text = ' '.join(text).strip()\n", + " \n", + " if(len(text) > 0):\n", + " X_clean.append(text)\n", + " return X_clean " + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "X_clean = data_cleaning(news_list)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Cluster 0 | Total: 179| banksy arrested argentina president batmobile stolen stolen detroit turning werewolf identity revealed president adopts\n", + "Cluster 1 | Total: 508| boko haram third breast bank hank big bank sugarhill gang vladimir putin jose canseco\n", + "Cluster 2 | Total: 24| justin bieber bear attack bieber ringtone russian fisherman saves man saves russian mauled bear\n", + "Cluster 3 | Total: 26| rescue attempt luke somers attempt yemen yemen rescue british born rescue bid killed rescue\n", + "Cluster 4 | Total: 76| apple watch macbook air inch macbook watch edition gold apple steel apple stainless steel\n", + "Cluster 5 | Total: 47| islamic state james foley killed us us journalist missing american journalist james american journalist\n", + "Cluster 6 | Total: 26| james wright wright foley journalist james american journalist beheads american isis beheads islamic state\n", + "Cluster 7 | Total: 24| isis fighters contracted ebola fighters contracted isis militants iraqi media media reports reports isis\n", + "Cluster 8 | Total: 15| hewlett packard two companies split two plans break packard plans break companies packard split\n", + "Cluster 9 | Total: 9| brian williams brokaw wants wants brian tom brokaw williams fired meteorologist peeing williams meteorologist\n" + ] + } + ], + "source": [ + "vectorizer = TfidfVectorizer(use_idf=True, sublinear_tf=False, ngram_range=(2,2))\n", + "X = vectorizer.fit_transform(X_clean)\n", + "\n", + "kmeans = KMeans(n_clusters=10, random_state = 42).fit(X)\n", + "\n", + "top_cluster_terms(kmeans, vectorizer, 10)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Cluster 0 | Total: 390| banksy hoax woman isis saudi caught arrested\n", + "Cluster 1 | Total: 29| haram boko nigeria ceasefire girls kidnapped schoolgirls\n", + "Cluster 2 | Total: 153| batmobile president werewolf argentina stolen boy million\n", + "Cluster 3 | Total: 42| killed rescue yemen attempt al hostage us\n", + "Cluster 4 | Total: 90| apple watch gold macbook air inch cost\n", + "Cluster 5 | Total: 66| claims isis islamic state weapons airdrop us\n", + "Cluster 6 | Total: 76| ebola bear bieber justin contracted isis man\n", + "Cluster 7 | Total: 46| journalist james foley american wright video beheaded\n", + "Cluster 8 | Total: 23| companies two packard hewlett split hp break\n", + "Cluster 9 | Total: 19| bank gang hank sugarhill big canadian captured\n" + ] + } + ], + "source": [ + "X_clean = data_cleaning(news_list)\n", + "\n", + "vectorizer = TfidfVectorizer(use_idf=True, sublinear_tf=False)\n", + "X = vectorizer.fit_transform(X_clean)\n", + "\n", + "kmeans = KMeans(n_clusters=10, random_state = 42).fit(X)\n", + "\n", + "top_cluster_terms(kmeans, vectorizer, 10)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Referências:\n", + "\n", + "- https://www.amazon.com.br/Express%C3%B5es-Regulares-Uma-Abordagem-Divertida/dp/8575223372\n", + "- Baeza-Yates, Ricardo, and Berthier Ribeiro-Neto. Recuperação de Informação-: Conceitos e Tecnologia das Máquinas de Busca. Bookman Editora, 2013.\n", + "- https://medium.com/botsbrasil/o-que-%C3%A9-o-processamento-de-linguagem-natural-49ece9371cff" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.4" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/5.2 NLP/datasets/fakenews_silverman.csv b/5.2 NLP/datasets/fakenews_silverman.csv new file mode 100644 index 0000000..0e1a90a --- /dev/null +++ b/5.2 NLP/datasets/fakenews_silverman.csv @@ -0,0 +1,10338 @@ +"headline","main_content","label" +"AUSTRALIA: 600-POUND WOMAN GIVES BIRTH TO 40-POUND BABY","Perth | A 600-pound woman has given birth to a 40-pound baby at Perth’s King Edward Memorial Hospital, a record breaking weight that could possibly make the newborn the largest baby ever born, reports the Western Australian Herald this morning. +The baby of gigantic size surprised doctors and staff members who were not fully prepared for such an event but miraculously managed to give birth to the 40-pound (18 kilos) baby who remains in a healthy state, has confirmed a hospital spokesman. + +The single mother who’s delivery necessitated a surgical incision in the mother’s abdomen and uterus was done to prevent any harm to the baby and mother’s health and was undergone without any complications. + +pregnant-woman-600 +The 600-pound woman was brought in emergency by ambulance, her family unable to carry her in an automobile +The doctor who practiced the cesarean section first believed the woman to be pregnant with twins or even triplets. + +“I have dealt with other women suffering from obesity before but this birth will stick with me until I die” he told reporters with a large grin. “I truly believed there was two or even three babies in there” he commented laughingly, “but no, it was just one big sturdy guy. He obviously has a career as a future rugby player” he added with humor. +The largest recorded baby in the world was previously thought to be a South African baby who is believed to have weighted 38 pounds (17.2 kilos) and was born in 1839. The young boy of Zulu origin is reported to have grown to an impressive 7’6 feet or 2.28 meters high before he reached his 18th birthday.","0" +"Jonathan S. Geller","Apple has been hard at work on multiple upcoming iOS versions simultaneously, and we’ve been told that iOS 8.2 is finally moving to the release stage. Barring any last minute problems, I would expect to see iOS 8.2 released this coming Monday, or the following week at the absolute latest. + +DON’T MISS: Is the Galaxy S6 really an iPhone ripoff? Leaked comparison photo lets you be the judge + +Additionally, we were told there might be as many as four iOS 8.3 beta versions. Apple released iOS 8.3 beta 2 earlier this week, so that leaves two more versions before the company makes it publicly available to customers. + +iOS 8.3 adds support for multiple new features and is filled with improvements in the operating system, though the biggest addition is support for the upcoming Apple Watch, which is slated to be released in early April. Apple’s event on March 9th should answer our remaining questions on pricing and other details. + +Additionally, stay tuned for the first The Boy Genius Report podcast coming later today with some thoughts on Apple Watch, the Apple Car, my struggle with the iPhone 6 Plus, and other interesting topics.","0" +"Amazon Is Opening a Brick-and-Mortar Store in Manhattan","Amazon, the cyber store that sells everything, plans to open its first physical store at 7 W 34th Street in Midtown Manhattan just in time for the holiday season. The experimental store will work as a mini-warehouse for some same day deliveries in New York. It'll surely serve as a nice little billboard, too. + +The new brick-and-mortar shop is actually across the street from the Empire State Building, so it's clearly primo real estate. That's surely why analysts think that Amazon is opening the space as a marketing effort. It doesn't hurt that the company will be able to show off its (now sizable) lineup of products, including Kindles of all kinds and the new Fire phone. The store will also handle pick-ups and returns. + +This is not the first time that Amazons's toyed with the idea of a physical presence, however. Rumors were rampant a couple of years ago that the company was going to open a similar-sounding store in Seattle. But hey, why open a store in a small city, when you can open a warehouse at the foot of the Empire State Building. [WSJ] + +Image by Michael Hession","0" +"Amazon is opening its first physical store","Digital retail company Amazon announced Thursday it plans to open its first brick-and-mortar store in midtown Manhattan in time for holiday shopping season. + +The company's first physical location will function as more of a warehouse than a big-box store. The location will have a limited supply of items available for same-day delivery in the city, and will process returns, exchanges, and pickup orders, according to The Wall Street Journal. + +Amazon did not immediately say how long the experimental store would remain open, nor whether it was preparing to open similar physical locations elsewhere in the country. + +- - Jon Terbush","0" +"Amazon.com to open first physical store in Manhattan: DJ","Amazon.com announced plans for its first brick-and-mortar store, Dow Jones reported. It will open on 34th Street in Manhattan across the street from the Empire State Building, just in time for this year's holiday season. + +The experimental pop-up store will function as a small warehouse, holding limited inventory for same-day deliveries only in New York. The store may also host tech showcases for items such as Kindle e-readers, Fire phones and Fire TVs. + +A customer may order an item online and then pick it up that same day in the store. + +Amazon stock was down 2 percent in midafternoon trading Thursday. + +The company risks increasing costs related to retailing such as paying leases and hiring workers. But if the store is successful, it may set a precedent for additional stores in other cities. + +Amazon has been researching and scouting a possible store for several years, said a person familiar with the project. Two years ago, the company went as far as scouting spots in Seattle, where it is headquartered. + +""Same-day delivery, ordering online and picking up in-store are ideas that are really catching on. Amazon needs to be at the center of that,"" Matt Nemer, a Wells Fargo analyst, told Dow Jones. + +Other companies such as Wal-Mart and Home Depot have already incorporated this order-online, pick-up in-store model. Clothing company Bonobos opened 10 stores in 2011 and plans to expand to 40 stores by 2016. + +Amazon tried brick-and-mortar experiments before, such as Kindle vending machines that sold tablets and e-readers in malls.","0" +"Amazon's first brick-and-mortar store said to open in Manhattan","It's hardly a secret that Amazon wants to be your go-to store for everything, but despite it's big pushes for same-day delivery there's still nothing like trudging into a physical store when you need something in a rush. Amazon seems to understand that all too well -- according to reports from CNBC and the Wall Street Journal, the e-commerce titan is gearing up to open its first brick-and-mortar store in midtown Manhattan in time for the holidays. + +The move might seem a little out of character for a company like Amazon, but this isn't the first time it's thought about moving off of the internet and into meatspace. Two years ago, rumor had it that Amazon was going to open a physical shop in Seattle devoted to Amazon-exclusive books and its slew of Kindle gadgets. Oh, and who could forget those Amazon lockers you could choose to route your goodies to? Amazon's vision for its role in the real world has evolved a bit since then -- the Journal notes that the New York outpost could act as a way to highlight its own products like Fire TV, but the bigger draw is the space's role as a same-day product pickup location/customer service hub. Think about it: you'd be able to purchase something from Amazon and schlep down to the store on 34th Street to pick it up. Not exactly what you expected? You'd be able to return it to that very same spot. That sense of physical immediacy is something that Amazon has always lacked -- now we'll just have to wait and see if it's enough to warrant opening more of these things. + +Source: WSJ, CNBC","0" +"Amazon to launch first brick-and-mortar store, report says","Amazon may be venturing beyond the world of online retail to set up its first brick-and-mortar shop, according to a report from Bloomberg News. + +The store will be in Seattle and its focus will be pricier merchandise such as tablet computers, the report says. And its footprint won’t be nearly as large as that of big box retailers such as Barnes & Noble. + +The single store is a test run for Amazon to see whether a chain of retail outlets could be profitable. If so, it could be a way for the company to make up for the declines they’ve seen in profits due to the manufacturing costs of the Kindle Fire. + +The blog Good E Reader reports that Amazon has hired a designer to begin work on the store’s look and layout and that it is aiming to open its doors later this year in time for the holiday shopping season. + +There would be certain advantages to Amazon having retail stores — namely that some items could be picked up immediately instead of going through shipping once they were purchased online. + +Over at Forbes, Eric Savitz notes that this isn’t the first time that there have been rumors about Amazon opening a chain of stores — in 2009 similar rumors surfaced after the Sunday Times reported the online retailer was looking at properties. Amazon quickly refuted the report. + +More from The Washington Post: + +iPhone leads jump in global smartphone shipments + +Facebook’s monster mobile numbers + +Google removes content in India","0" +"Obama Orders Fed To Adopt Euro Currency","(WASHINGTON, DC) – In the boldest takeover of Presidential authority in history, Barack Obama ordered the Federal Reserve to adopt the euro beginning October 1, 2015, the start of the next fiscal year. The US will soon share the single monetary system used by 18 European Union member states, including Greece, France, Germany, and Slovakia. + +The surprise announcement resulted from secret overseas deals between Obama, foreign finance ministers and the Federal Reserve System. “This step forward,” announced Obama, “will make it easier for Americans and Wall Street to compare prices, stabilize the economy, and set us up to again become leaders on the world economic stage.” The President revealed the changeover during the worldwide economic summit held in Beijing, where alongside Chinese premier Li Keqiang, he worked out a climate accord agreement, also developed in secrecy. + +Criticism has been swift and severe. “Obama’s given up entirely on our US economy after single-handedly destroying it,” said Rep. Kevin Brady (R-TX 8th District), Chairman of the Congressional Joint Economic Committee. + +“It’s like breaking all the toys in the toybox and then saying I don’t want to play with those broken products anymore,” said former Alaska Governor Sarah Palin. “This is the most abusive power grab witnessed on the worldwide stage. He needs to consider staying over in China while he’s there,” she added. + +To help with the conversion to the euro, a new whitehouse.gov website will launch in early 2015, complete with downloadable conversion calculators and apps. Printable vouchers will be provided for discounts toward government manufactured cash registers. A children’s website featuring ‘Yuri the Happy Euro‘ will help prepare youngsters for the new system. + +For the first 3 months of the conversion, euro notes and coins will circulate jointly with US currency, owing to overlap with the 2015 holiday season. “We don’t want to add any extra stress to an already hectic time of year,” said the President. “My economic team predicts everything will go smoothly, and holiday shopping should be stronger than ever.” + +Many unanswered questions remain. Will vendors take advantage of the new system to gouge consumers? What about ATMs? Will small businesses who can’t afford to make the changeover right away close up shop and further weaken an increasingly unstable Obama economy? + +“I think it’s a good idea, said Washington DC shop owner Vonda Miller. “I spend too much time counting pennies all day long making change. They tell me my taxes will be easier to do, so I’m for whatever the President wants.” + +National Report will keep readers informed with updates about the anticipated massive fallout over this latest political bombshell, occurring during the last days of Obama’s increasingly emboldened administration.","0" +"Rumor: Apple to hold event this month to unveil Retina MacBook Air & finalize Apple Watch specs","Apple may be planning to hold a media event in late February to showcase the final version of its upcoming Apple Watch, and also debut a newly redesigned MacBook Air, potentially with a Retina display, according to a new report. + +Word of a potential late-February event was reported on Wednesday by French Apple publication iGen, citing unnamed sources. Specifically, it was said that Tuesday, Feb. 24, could be a likely date for such an event to unveil upcoming products. + +Rumors have suggested that Apple will launch an all-new 12-inch MacBook Air with a thinner chassis this quarter, which concludes at the end of March. A late February event could set Apple up to debut the new MacBook Air within that timeframe. + +It's expected that the redesigned MacBook Air will sport a high-resolution 12-inch Retina display. There have also been claims that the device will feature the new, smaller, reversible USB 3.0 port. + +As for the Apple Watch, although Apple offered a preview of the device and its appearance last September, the company has been working behind the scenes to finalize the hardware and software ahead of its launch in April. A February event could give Apple an opportunity to offer more specifics on the upcoming wearable device, such as battery life. + +Another potential product unveiling could be a so-called ""iPad Pro,"" rumored to feature a 12.2-inch display. However, it's been reported that the device may not launch until the second quarter of 2015, making it potentially a candidate for WWDC. + +Apple hasn't held a major event early in the year in a few years, instead waiting to unveil new products at its annual Worldwide Developers Conference in June. The last time Apple held a major product unveiling event in the first quarter of the calendar year was for the third-generation iPad in 2012. + +iGen has a respectable track record in predicting Apple's future plans. Last fall, the site got its hands on Foxconn schematics that showed the final design of the iPhone 6, and the site also predicted the launch details for Apple's latest-generation handsets.","0" +"Apple’s next big event reportedly set for late February","Apple’s next media event might be less than three weeks away. French Apple fan site iGen has received information from its sources which indicates that Apple will take the stage during the last week of February, most likely on Tuesday, February 24th. + +DON’T MISS: The stupidest thing you’ll read today: ‘The Apple Watch will flop’ + +Apple typically holds it events within a few weeks of launching a new product, but as we learned during the company’s recent earning call, the Apple Watch won’t start shipping until April. That said, it’s been quite some time since Apple held an event this early in the year, so it’s worth tempering any expectations for what the company has in store. + +If the event does end up taking place in February, it’s likely that we’ll be seeing a lot more than just the wearable. The latest version of the MacBook Air might make an appearance as well — possibly the 12-inch model about which rumors have been circulating for months. + +This isn’t definitive confirmation, but it would honestly be more surprising to see the company miss out on another huge opportunity to get consumers excited about a brand new product. If Apple does have an event planned for this month, the invitations should start arriving before too long. We’ll know for sure within a matter of days. + +UPDATE: According to 9to5Mac’s sources, Apple currently has no plans to hold an event in February: + +“While it’s highly likely that Apple will hold an advance event to officially launch the Apple Watch and begin preorders ahead of shipping, the actual date remains a question mark,” writes 9to5Mac’s Jordan Kahn.","0" +"Apple could make a Special Event in late February","Apple would hold its first media event in 2015 towards the very end of February . This date was mentioned by members of Apple and we were then reported. This is not a direct confidence, but has not been assigned to anyone and let us take a moment to cash. +Officially known that Apple will sell his watch in April, remains to intervene when it was launched to the media. In this, the last week of February (Tuesday 24 fleet also in air) defends. + +In technical terms, it would allow developers to tweak their apps having the ultimate instructions on the possibilities of the product. This echoes elsewhere to a request made ​​by Apple with its partners handpicked for it to submit its app in mid-February. + +There are also waiting around at all the new MacBook Air that we would see the market in the wake of this conference. Thus, the following month or month and a half, Apple could focus all its communication around the clock. + +Apple has already done so in the past, the iPhone is not the best example in this case, but yes iPad. Another product that has created a new category. The first version of the tablet was unveiled on January 27th and marketing has started two months later, on 29 March. + +The only false note in this scenario is that we would have seen Apple play spoilsport in full Mobile World Congress in Barcelona, ​​which will gather all its competitors. She loves to remind their good memory in such circumstances. But the fair is held between 2 and 5 March. As for the big event of his best Samsung enemy, it takes place on March 1 . To be continued ...","0" +"Apple could make a Special Event in late February [Update]","Apple would hold its first media event in 2015 towards the very end of February . This date was mentioned by members of Apple and we were then reported. This is not a direct confidence, but has not been assigned to anyone and let us take a moment to cash. + +[Update] : according to 9to5mac the suggestion of a keynote late February (suggestions, as outlined in the introduction, but these shades have been forgotten in the times of this rumor here and there) does not match what is expected from Apple . No other date offered in exchange, however, when the next keynote remains shrouded in mystery. + + +Officially known that Apple will sell his watch in April, remains to intervene when it was launched to the media. In this, the last week of February (Tuesday 24 fleet also in air) defends. + +In technical terms, it would allow developers to tweak their apps having the ultimate instructions on the possibilities of the product. This echoes elsewhere to a request made ​​by Apple with its partners handpicked for it to submit its app in mid-February. + +There are also waiting around at all the new MacBook Air that we would see the market in the wake of this conference. Thus, the following month or month and a half, Apple could focus all its communication around the clock. + +Apple has already done so in the past, the iPhone is not the best example in this case, but yes iPad. Another product that has created a new category. The first version of the tablet was unveiled on January 27th and marketing has started two months later, on 29 March. + +The only false note in this scenario is that we would have seen Apple play spoilsport in full Mobile World Congress in Barcelona, ​​which will gather all its competitors. She loves to remind their good memory in such circumstances. But the fair is held between 2 and 5 March. As for the big event of his best Samsung enemy, it takes place on March 1 . To be continued ...","0" +"Apple Media Event Rumored for Late February, Apple Watch and 12"" MacBook Air Likely Topics [Updated]","Apple may be planning to hold a special event during the month of February, according to French Apple-focused website iGen [Google Translate] (via iDownloadBlog). The site's sources, which are often reliable, suggest that the event might take place during the last week of February, potentially on Tuesday, February 24. + +The event may see Apple once again showcasing the Apple Watch, which is set to debut in April, and it may also see the launch of the 12-inch MacBook Air. KGI Securities analyst Ming-Chi Kuo recently predicted that the upcoming notebook will debut in March, which is in line with a late-February unveiling. + +Rendering of the 12-inch MacBook Air by Martin Hajek +Apple's 12-inch MacBook Air is rumored to feature a new ultrathin design that does away with fans and introduces a revamped trackpad. It may include a low-power Core-M processor and it may be the first device to take advantage of the new reversible USB Type-C connector, which is much smaller and allows a USB cable to be inserted into a notebook in any orientation. + +Apple may also use the event to unveil additional details on the Apple Watch, such as pricing and battery life. An event showing off the Apple Watch could explain why Apple has been asking some developers to have their apps ready to launch in the App Store in mid-February, as we reported last week. It's possible that Apple will use apps from these developers to demonstrate additional capabilities of the watch. + +Though rumored, a February event is by no means confirmed at this point, and it is unclear what else Apple might cover in addition to the Apple Watch and the 12-inch MacBook Air. + +Update 12:23 PM: Sources speaking to 9to5Mac have indicated Apple will not be holding a late February media event. + +Related roundup: Apple Watch , Tag: igen.fr","0" +"Apple May Or May Not Hold An Event On The 24th Of February [Rumor]","The Apple Watch has been scheduled to begin shipping in April according to Apple’s CEO Tim Cook. Now presumably Apple might want to make some kind of announcement regarding the prices and the finalized specs of the device, and given that it is their first wearable, it doesn’t seem like a stretch. +That being said, a report from French Apple website iGen (via AppleInsider) claims to have heard from their sources that this event could be held on the 24th of February in which Apple is expected to share the finalized specs and launch plans for the Apple Watch, and will also be announcing the rumored 12-inch MacBook Air. +Previously we have heard rumors that the 12-inch MacBook Air could be launched in Q1 2015 so an announcement either in February or by the end of March would coincide with the rumors. However we should also note that the folks at 9to5Mac have heard from their own sources that the 24th of February event will not be happening. +9to5Mac does not dispute the possibility of Apple holding a special event to launch their new products, but rather the actual date which their sources have told them will not be the 24th of February. Given that both websites have been pretty reliable when it comes to Apple rumors, it’s hard to say who’s right. Either way we will be keeping our eyes and ears peeled for a possible invite, but in the meantime try not to get your hopes up just yet. +Filed in Apple >Computers >Gadgets >Rumors. Read more about Apple Watch and macbook air.","0" +"Report claims steel Apple Watch to start at $500, gold model between $4-5K","French website iGen.fr, which has provided reliable information in the past, reported on Tuesday that the steel Apple Watch will start at $500 alongside a gold model that will retail for between $4,000 and $5,000. Apple previously claimed at its September event that the Apple Watch would start at $349, but did not disclose further pricing information. + +The report claims that the stainless steel Apple Watch in polished steel or black will cost $500, while the gold Apple Watch Edition will be the more expensive version at between $4,000 and $5,000. That price range would be nearly half the estimated $10,000 price that some other reports have suggested. + + + + +In terms of a launch date, the report claims that the Apple Watch will launch in time for Valentine’s Day, but that was the most specific date given. We previously shared an internal memo from Apple retail chief Angela Ahrendts in which she wrote that the Apple Watch will launch in the “Spring” following the Chinese New Year. + +iGen.fr accurately reported that Apple would launch both the 4.7-inch and 5.5-inch iPhone 6 at its September event and has also provided information that proved true regarding an iPod touch update in the past. + +Apple announced last month that its WatchKit SDK will be available in November.","0" +"Rumor: Gold Apple Watch Edition priced up to $5,000, steel version at $500, will debut on Feb. 14","A rumor on Tuesday claims Apple's upcoming Apple Watch will be priced at $500 for the mid-tier steel model and up to $5,000 for top-end gold ""Edition"" versions, a number much higher than previous estimates. + +Citing an unnamed source, French website iGen reports Apple is looking to field the Apple Watch at a proposed retail cost of $500 for versions with stainless steel cases and between $4,000 and $5,000 for Apple Watch Edition models. This leaves the Apple Watch Sport version as Apple's lowest-priced option, which the company said would come in at $350. + +While the website has been accurate in predicting recent Apple product launches, the claims are unverifiable and should be taken with a grain of salt. + +Previous estimates from jewelers and industry analysts pegged high-end Apple Watch Edition models at $1,200. Edition versions are crafted from 18-karat gold, feature sapphire crystal and come with a variety of luxurious strap options. Apple has not commented on whether the entire chassis is solid gold, or merely gold plated, but the company apparently developed a variant of the metal twice as strong as the standard. + +Additionally, the source claims Apple is still shooting for a launch on Valentine's Day. + +Prior to the Apple Watch announcement, noted analyst Ming-Chi Kuo accurately predicted that the device would come in two sizes and multiple models spread across a wide range of price points. At the time, he speculated the wearable could cost into the ""thousands of dollars."" + +Apple announced its anticipated first foray into the wearables market in September, saying only that pricing would start at $350. Given that the Apple Watch Sport is made from relatively low-cost materials — aluminum, elastomer band and non-sapphire window — many believe it to be the entry-level model.","0" +"Rumor: Stainless Steel Apple Watch Will Cost $500, Gold $4,000","While Apple announced that the base model of its forthcoming smartwatch would cost $350, it's remained tight-lipped about the pricing of the rest of the range. Now, a new report suggests that the stainless steel version will start at $500, and the gold at somewhere between $4,000 and $5,000. + +The report comes from sources at Apple via French website iGen.fr. As MacRumors points out, the site has been reliable in the past, accurately reporting the dimensions of both the iPhone 6 and 6 Plus. + +It's thought that the $350 price applies to the aluminum model of the watch. Certainly, $500 for the stainless steel version feels about right by comparison. The cost of the gold model, though; well, quite simply it depends on how much gold there is. We'll have to wait to find out, but such high pricing would indeed make it very much a luxury item. + +The iGen.fr sources also claim that Apple is hoping to release the watch as soon as possible—though other rumors claim we may have to wait until Spring of 2015. Either way, we have longer to wait before we find out more than we'd like. [iGen.fr via MacRumors]","0" +"Report: Apple Watch to start at $500 in stainless steel, thousands for gold model","When Apple introduced its Apple Watch in September, the company said there would be three editions along with various face options and bands. Customers will literally have dozens of watch configurations to choose from. Only the base model got an official price of $349, however. Now a report claims to have pricing information on other editions. + +MacRumors spotted a French blog whose sources suggest the stainless steel Apple Watch variant will start at $500 while gold models could cost $4,000 and up. The iGen blog has been credible in the past, correctly predicting the size of the iPhone 6 and 6 Plus. + +If you take the view that Apple Watch is simply another smartwatch or gadget, the prices may not make that much sense. Look at the device as a fashion statement with smarts, though, and the anticipated costs sound viable. Apple has designed the watch and will market it as a modern timepiece that adds smartwatch functions to your wrist. It’s already considered a luxury brand by many and people are clearly willing to pay premium prices for that brand. + +The stainless steel pricing is certainly believable to me. Look at Pebble to see why. + +Pebble Steel fashion + + + + +You can buy a plastic Pebble smartwatch for as little as $99 now, recently discounted from its $149 price. The same watch and functionality in a more aesthetically pleasing stainless steel case will cost you $199, or double the plastic model’s price. It’s reasonable to assume an Apple Watch with stainless steel casing will cost $500 based on that. I wouldn’t be at all surprised to see that come with a leather strap, with an additional $50 to $100 cost for a matching stainless steel strap. + +Unfortunately, we’re not likely to know the official retail costs until this coming spring, as Apple won’t be selling the Apple Watch until then. For now, potential customers have time to save up for Apple’s timepiece — something they may need to do if they want an Apple Watch in gold.","0" +"Apple Watch Stainless Steel variant reportedly priced at $500, $4,000 for the gold variant","Along with unveiling the Apple Watch earlier this year, the company also announced that the prices for the wearable device will start at $349. French website iGen.fr now claims to have an idea about the pricing of the stainless steel variant, as well as the gold variant. + +According to the publication, the stainless steel variant of the Apple Watch will be priced around $500, while the gold variant will be priced between $4,000 to $5,000. This is in line with earlier rumors, which claimed that the top-end variant of the Apple Watch will be priced above $1,000. While Apple didn’t announce which variant would be priced $350, it is widely believed to be the entry-level aluminum variant of the Apple Watch. + +RELATED: All you want to know: Apple Watch specifications, features and price + +As for the availability, the publication claims that the first Apple Watch will start shipping by Valentine’s Day 2015. While this is in line with earlier rumors, it is in contrast with what Apple Retail SVP Angela Ahrendts hinted yesterday. In a video message to the company’s retail employees, she hinted that the Apple Watch will launch in spring next year. She said, “We’re going into the holidays, we’ll go into Chinese New Year, and then we’ve got a new watch launch coming in the spring.”","0" +"Stainless steel Apple Watch could cost just $499, but gold will be 10 times as pricey","Although Apple has given us our first peek at the Apple Watch, so far we don’t know much about it, including when it will be released or how much its many versions will cost. + +A new report, however, provides some possible answers to these questions. According to a French website, the Apple Watch will start at around $500 for the steel model. And gold? Gold will be even more expensive. + +According to iGen.fr, the stainless steel Apple Watch in polished steel or black will cost $500 when it debuts close to Valentine’s Day of 2015. This would be a $150 premium over the anodized aluminum Sports Model, which Apple said last month would start at a price of $349. + +For the gold model, expect to spend 10 times as much. According to iGen.fr’s sources, the gold Apple Watch in yellow or pink gold would cost between $4,000 and $5,000 when it goes on sale in January. + +iGen.fr also suggests that the Apple Watch will rank low on the iFixIt repairability scale. They claim the only thing on the Apple Watch that will be user-replaceable is the strap, so don’t expect to be able to repair an Apple Watch the way you would a normal timepiece. + +As for shipping date, iGen.fr’s sources say the Apple Watch is still on track for a February 2015 release date. That pink gold Apple Watch is looking like a pretty good Valentine’s Day present right now, isn’t it?","0" +"Info iGen: $ 500 for Apple Watch, February 14?","Despite a presentation in due form in September and a few public appearances (at Colette in Paris, in particular), Apple Watch is still shrouded in mystery: what are the prices of the different versions? And at what point will we be able to equip his wrist? To these questions, Apple has made piecemeal responses: prices officially start at $ 349 (for the Sport model anodized aluminum), with availability set for early next year. + +All this is still very vague. After cooking one of our contacts among the most reliable - who obviously wishes to remain anonymous - we can lift a corner of the veil on the prices of stainless steel versions and the gold (Edition ). Keep in mind that it is impossible to be absolutely certain of the truth of these indiscretions. + + +A cheese cover? No, one of the many third-party accessories that will be available for the Apple Watch! This object can support the show with its magnets and will act as a backdrop in an office, for example (photomontage) - Click to enlarge +The Apple Watch Stainless steel (polished or black sidereal) would be proposed $ 500. The Edition model in yellow or rose gold would be sold between $ 4,000 and $ 5,000. No part of the Watch casing (not the bracelet, so) can not be removed easily, replace the battery or other component. Nothing says that the operation can not be supported in an Apple Store, but of what comprises, Apple watches might well be as closed as an iPad. + +Regarding availability, our contact says the date of Valentine's Day is still relevant, despite the declaration of Angela Ahrendts announcing a spring launch . Operators (resellers and distributors) would in any case in the starting blocks for mid-February ... In addition, three major French would strongly positioned in the accessory market for the Apple Watch. So we seem to believe, but also upstream of the production chain, from manufacturers and from distributors. We'll go into more detail on the accessories and other gadgets for Apple Watch.","0" +"Apple Watch Pricing to Reportedly Start at $500 for Stainless Steel, $4,000 for Gold","French Apple website iGen.fr is reporting [Google Translate] that pricing for the stainless steel Apple Watch may start at $500, while the gold Apple Watches' pricing could start between $4,000 and $5,000. iGen.fr has been reliable in the past, most recently reporting the dimensions of both the iPhone 6 and 6 Plus. + +While Apple had announced that the Apple Watch would start at $350, which was widely assumed to be the price of the aluminum model, and estimates pegged the price of the gold Apple Watch at prices as low as $1,000 or as high as $5,000, there has been little information regarding the pricing of the stainless steel option. + +The site's sources also indicate that Apple still aims to release the Apple Watch by Valentine's Day 2015, which somewhat echoes an earlier report that said the company would be ""lucky"" to release the device by that timeframe. iGen.fr also mentions that manufacturers and resellers are preparing as if the Watch would release in mid-February 2015. Previously, Apple Senior Vice President of Retail and Online Stores Angela Ahrendts said the Watch would release in Spring 2015.","0" +"Report: Stainless steel Apple Watch will be priced $500, gold at $5,000","Citing an anonymous source, the French website iGen.Fr reports that stainless steel versions of the Apple Watch will retail for $500 while the gold models may retail for as high as $5,000. + +FEATURED RESOURCE + +PRESENTED BY SCRIBE SOFTWARE +10 Best Practices for Integrating Data +Data integration is often underestimated and poorly implemented, taking time and resources. Yet it +LEARN MORE +Apple, of course, has been rather quiet on Apple Watch pricing, aside from indicating that lower-tier pricing will begin at $349 for the Apple Watch Sport models. That being the case, a $150 bump for stainless steel models isn't outside the realm of reason. + +See also: The many looks of the Apple Watch + +Interestingly, iGen.Fr also relays that Apple may still be trying to push for a release before Valentine's Day. This however is at odds with a previous report claiming that Apple is planning to release its highly anticipated wearable device this spring. + +As with any anonymous rumor, the aforementioned pricing matrix should be taken with a grain of salt, especially because pricing is one of the few details prone to changing at any time. Still, because iGen.Fr has a rather solid track record with respect to Apple rumors, we felt it was worth passing this particular tidbit along. + +On a related note, Tim Cook just last week confirmed that the Apple Watch will most likely have to be charged nightly. + +Lastly, make sure to check out the many different looks of the Apple Watch over here. The stainless steel options look really great, and if the $500 price point is accurate, it may very well prove to be the most popular model.","0" +"Piper Jaffray pegs stainless steel Apple Watch price at $499, Edition at $4,999","Investment firm Piper Jaffray issued a report on Monday breaking down expected Apple Watch average selling prices, saying an aggregate of consumers will likely spend closer to $550 on the device, considering case and internal storage options. + +Building off Apple's quoted starting price of $349, analyst Gene Munster anticipates combined Apple Watch ASPs to fall closer to $550, or $575 to $600 including additional bands. + +Apple Watch will come in three separate price tiers — Apple Watch Sport, Apple Watch and Apple Watch Edition — each series including two display sizes and a variety of strap choices. + +Starting with Apple Watch Sport, the aluminum and glass version widely thought to be the least expensive model, Munster expects an ASP of $450 after factoring in configuration alternatives like case and internal storage options. + +The stainless steel Apple Watch model, which also features a more expensive sapphire glass cover, is expected to start at $499 to $549, again depending on customizable features. Munster sees an overall ASP at around $650 for the mid-tier Watch series. + +On the high end, the analyst forecasts base model Apple Watch Edition devices to start at $4,999, but classifies segment ASP closer to $7,500 after adding in straps made from precious metals. + +Based on current pricing for Apple's silicon iPhone 6 cases, which come in at $35, Munster sees elastomer Apple Watch straps to start in a similar $29 to $35 range, while leather bands could be priced between $49 to $59. Pricing for metal bands like the link bracelet and Milanese loop are more difficult to determine, but the analyst believes steel versions will come in at $99, while gold bands could be priced into the thousands of dollars. + +""If you assume that 55 percent of bands purchased are elastomer, 35 percent leather, 10 percent steel, and about 5,000 total gold bands are sold, the average band ASP could be around $50,"" Munster writes. + +He added that if half of all Watch buyers purchase a band — assuming 8 million Watches are sold in 2015 — the accessory range would add $25 to Apple's watch category, equating to a $575 ASP. If every Watch customer purchases an extra strap, it would tack on $50, bringing ASP up to $600. + +The lower-cost Sport model is expected to make up 55 percent of overall Watch sales, while the mid-tier Apple Watch will take another 45 percent. That leaves very little room for Apple Watch Edition, but Munster believes Apple might sell roughly 10,000 units this year. In an interesting comparison, the firm calculates that Apple Watch Edition business could equate to about two percent of luxury watchmaker Rolex, which moves between 600,000 to 750,000 units each year. + +Finally, Munster expects Apple to reveal a better sense of device pricing at its March 9 event, as well as highlight ""special features"" to drum up consumer interest ahead of release. + +AppleInsider will be covering the ""Spring forward"" event live from San Francisco's Yerba Buena Center next week.","0" +"High-end Apple Watch to start at $5,000 -- analyst","Would you pay five grand for the high-end luxury edition of the Apple Watch? That's the starting price that Piper Jaffray analyst Gene Munster sees in his crystal ball. + +On March 9, Apple is expected to finally unveil the finer details of its Apple Watch, including the price tags and launch date. The company's first smartwatch will be available in three versions: Apple Watch Sport, Apple Watch and Apple Watch Edition. Apple has already revealed that the entry-level Sport model will start at $349 in the US. But the company has been mum about the prices of the other two models. + +In an investors note released late Monday, Munster said he expects that the price for the Sport model could reach as high as $450 depending on different case and storage options. The mid-tier Apple Watch could start at anywhere from $499 to $549 and likely will come closer to an average selling price of $650, according to Munster. But the top-of-the-line Apple Watch Edition could break the bank, starting at $4,999 and potentially reaching closer to $7,500 by factoring in high-end, expensive bands. + +That $4,999 price lines up with a projection from Apple observer John Gruber, who forecast the cost of the high-end version last September. + +Apple is a latecomer to a smartwatch market already crowded with entries from Samsung, LG, Motorola, Microsoft, Sony, Pebble and other players. Apple's product will be part smartwatch and part fitness and activity tracker, a combination the company is counting on to bring in buyers. But by offering the watch in a luxury edition, Apple is also presenting it as a piece of fine jewelry to further distinguish it from rival products. + +Munster remains bearish on Apple Watch sales, estimating 8 million in unit sales this year, compared with Wall Street forecasts of 14 million. But the analyst believes next Monday's event ""will finally highlight the special features of the watch and start to excite the public."" + +Apple will offer interchangeable bands for each of its watches, a factor that will determine the ultimate price. Munster said he believes the elastomer bands for the Apple Watch Sport will range in price from $29 to $39. Leather bands could be priced from $49 to $59. Steel bands could run around $99. And the gold bands for the higher-end edition may run into the thousands of dollars. + +How might the three different versions of the watch play out in terms of sales? Munster said he expects the entry-level Sport edition to account for around 55 percent of all units sold this year, while the Apple Watch will contribute around 45 percent. That leaves the luxury Apple Watch Edition contributing pretty much nothing, at least in terms of percentage. + +""The Apple Watch Edition is the more difficult to predict, but we believe that with the watch likely starting at $4,999, Apple might sell around 10,000 units in CY15 [calendar year 2015] of our total 8 million estimate, Munster said. ""To put the 10k units in perspective, Piper analyst Erinn Murphy, in conjunction with industry estimates, believes that Rolex sells 600-750K watches per year, thus Apple at 10K in the first year would be about 2 percent the size of Rolex. We believe this is a reasonable potential first year size as high-end consumers weigh the power of the Apple brand vs. other luxury watches and the trade-off of quickly depreciating technology in an Apple Watch vs. other more traditional luxury watches that may hold value better."" + +A spokeswoman for Apple said the company had no comment at this time.","0" +"Gene Munster Predicts $499 Steel Apple Watch, $4,999 for 18k Gold Edition","Piper Jaffray’s Gene Munster has issued a new report to investors, breaking down expected Apple Watch average selling prices. The analyst predicts that the stainless steel Apple Watch will be priced at $499, while the 18k Gold Edition will sell for $4,999, AppleInsider reports. He also said that on average, consumers will spend closer to $550 on the device, considering case and internal storage options. + +Apple watch versions + +Apple Watch will be released in three separate price tiers i.e. Apple Watch Sport, Apple Watch and Apple Watch Edition, with each series including two display sizes and a variety of strap choices. Starting with Apple Watch Sport, Munster expects an ASP (average selling price) of $450 including configuration choices like case and internal storage options. The stainless steel Apple Watch model is expected to start at $499 to $549, with an overall ASP at around $650. Regarding the Apple Watch Edition, the analyst forecasts the base model to start at $4,999, while classifying segment ASP at $7,500. + +Based on current pricing for Apple’s silicon iPhone 6 cases, which come in at $35, Munster sees elastomer Apple Watch straps to start in a similar $29 to $35 range, while leather bands could be priced between $49 to $59. Pricing for metal bands like the link bracelet and Milanese loop are more difficult to determine, but the analyst believes steel versions will come in at $99, while gold bands could be priced into the thousands of dollars. + +“If you assume that 55 percent of bands purchased are elastomer, 35 percent leather, 10 percent steel, and about 5,000 total gold bands are sold, the average band ASP could be around $50,” Munster writes. + +Lastly, Munster expects the Sport model to make up 55% of overall Watch sales, while the mid-tier Apple Watch will take 45%. As for Apple Watch Edition, Munster believes Apple might sell roughly 10,000 units this year. + +Based on what we know so far about the Apple Watch, which model do you plan on getting?","0" +"Chinese rumor suggests Apple Watch to launch in February, sapphire to blame for low supply","Chinese site Feng is reporting that Taiwanese media is saying that Apple wants to launch the smartwatch sometime in February. Most recently, The Information said Apple would be “lucky” to release the Apple Watch by Valentine’s Day. Officially, Apple has only quoted ‘early 2015′ as a launch window for the Apple Watch. + +According to the report, Apple is supply constrained by the sapphire output of GTAT, which will mean the Apple Watch will hit in limited quantities. However, it is important to note that the low-end Apple Watch, the Apple Watch Sport, does not use sapphire at all, which will make that model easier to source. The higher end versions, Apple Watch and Apple Watch Edition are the SKU’s that will be impacted by sapphire shortages. + + + + +Most notably, right now the limiting factor on Apple Watch isn’t really component availability. First things first, Apple needs to finish the development of the Apple Watch software and hardware internally. + +To date, all of the Apple Watch’s handled by press have been non-functional, showing only non-interactive videos of the user interface. This means that Apple still has a long way to go before the device is in any kind of shippable state. It has been previously rumored that Apple is working hard to improve battery longevity, for example. + +Moreover, although Apple has announced WatchKit, which will enable third-party developers to create interactive notifications for the Watch, no SDK has been released to actually allow development. Apple Watch integration may come as part of iOS 8.2 for example, which is currently in development.","0" +"New rumor backs up reports that the Apple Watch will launch in February","The much-anticipated Apple Watch — which was recently unveiled to Apple fans everywhere — may just be getting a February launch date according to a rumor that originated on a Taiwanese news site. + +This rumor would clearly fit right into the “early 2015″ release timeframe stated by Apple executives during the device’s unveiling. Apple CEO Tim Cook and Senior VP of Operations Jeff Williams explained the situation to Bloomberg BusinessWeek. + +“We want to make the best product in the world,” Williams said, with Cook adding, “One of our competitors is on their fourth or fifth attempt, but nobody is wearing them. We could have done the watch much earlier, honestly, but not at the fit and finish and quality and integration of these products. And so we are willing to wait.” + +anigif_enhanced-2741-1410388337-5 + +When the watch is finally released, it may be in short supply due to constraints attributed to the sapphire output at Apple’s supplier GTAT, not to mention the company is still working on perfecting the design, software and manufacturing of the watches themselves. + +The Apple Watch Sport seems like it will not be affected by the rumored limited release like the Apple Watch Edition version will. Unlike the pricier models, the Apple Watch Sport doesn’t use Sapphire at all. + +We’ll have to see if this rumor turns out to be true, but for the time being all we know for sure is that the watch will be released in “early 2015.”","0" +"New Rumour Suggests Apple Watch to Launch in February","Rumors have been circulating that the Apple Watch will launch in February.","0" +"Are Rumors of the Apple Watch in Feb True?","When Tim Cook finally announced the long-awaited Apple Watch on September 9, the company promised an “early 2015” release. Since then, it’s really been anybody’s guess as to when, exactly, that might end up being. A few new rumors, however, suggest that we’ll get the Apple Watch sometime in February…but it’s likely that it’ll be later than that. + +Today, a post on 9to5Mac points the way back to a report from Chinese site Feng, which itself cites “Taiwanese media” as saying that the Apple Watch is likely to hit sometime in February, though not without a fair bit of challenges to overcome. The reports say that the supply of sapphire crystal – which will compose the displays of the highest-end Apple Watch units – has led to some difficulties in manufacturing. + +However, it should be noted that if sapphire is the biggest problem facing the Apple Watch, then Apple’s in good shape. The software itself is still in development, and as the 9to5Mac post points out, the company has yet to release the WatchKit SDK for developers to start making all the cool apps that’ll run on the device. + +Another report from Asia this week claims that production on the Apple Watch isn’t set to start at manufacturing partner Quanta until sometime in January – and with only a month of actual production, it seems doubtful that Apple would truly be ready to sell the Watch by February. And last week, an unnamed Apple insider was quoted as saying that the company would be “lucky to ship it by Valentine’s Day.” If that quote is true, then February seems like a tall order. + +That said, March doesn’t seem too out of the question. Nor does April. In fact, considering that Motorola promised the Moto 360 smartwatch by “summer 2014,” and didn’t launch it until early September, it would seem that OEMs are pretty loose about their definitions for launch windows. “Early 2015” is simply anything before the very last day in June. And barring any major disasters, we should start to see Apple Watches on consumers’ wrists long before then. + +The main question, though, is what cool stuff will the competition cook up between then and now…","0" +"Apple Watch launch has new timetable: Analyst","After multiple delays, the launch of the Apple Watch will be put off until early next year, Rosenblatt Securities Senior Research Analyst Brian Blair said Friday. + +""There's really no right time of the year for this product to come out because really hasn't existed yet,"" said Blair. ""It is kind of a strange period, but the more production gets pushed back, the later it's going to launch. It looks like right now February is the best shot they have."" + +On CNBC's ""Fast Money,"" Blair said that the majority of the issues Apple is addressing with the delay are internal, one of which is battery life. + +""The word is that the battery lasts for about a day,"" he said. ""That's going to be a problem for a lot of consumers. + +""If they can talk about two days, three days, where you don't have to charge it every single night when you go to bed, that will ultimately bring more consumers to the product.""","0" +"Apple Watch launch reportedly planned for February with limited supply","The Apple Watch is on track for a February release, according to supply chain sources in China. A February launch echoes an earlier report from The Information, which said Apple will be “lucky” to ship by Valentine’s Day. + +While mass manufacturing of the Apple Watch hasn’t begun yet, there are already concerns that sapphire production won’t be able to meet initial demand. The constraints will likely result in making more expensive Apple Watch models harder to come by. + +All sapphire for the Apple Watch is coming from Apple’s plant with GT Advanced (GTAT) in Arizona. Because of Apple’s very stringent quality specifications, GTAT will reportedly be unable to meet the level of output Apple had hoped. + +Not all Apple Watch models use a sapphire display, however. The lowest-end Apple Watch Sport uses strengthened Ion-X glass, while the mid-level Apple Watch and higher-end gold Apple Watch Edition use sapphire. + +Initial supply constraints are not uncommon for Apple products, especially entirely new product categories like the Watch. If lines to see the Watch in person during Paris Fashion Week are any indication, demand will be extremely high when it goes on sale. + +Since the Apple Watch was unveiled last month, it’s been clear that the product is unfinished on multiple levels. Demo units shown to the press have been running videos on continuous loops, and Apple hasn’t said anything about pricing. All Apple has said about availability is that it plans to ship by “early 2015.” + +Via: G4Games","0" +"Apple Watch delayed for February in limited quantity","The Apple Watch will not be produced until January 2015 at the earliest.","0" +"Apple Watch mass production kicks off in January: Report","According to a news source from Taiwan, the mass production stage of the Apple Watch will not begin until January. +In addition to the delay in start of mass production, the G for Games blog also reported that the Apple Watch will instead be assembled by only one supplier, as opposed to the two suppliers that was previously rumored. +The information about the January start of mass production was revealed [in Chinese] by AppleDaily, which adds that the reported time frame of the start of mass production will make questionable Apple's statements that the Apple Watch will become available to the public by early 2015. +The Apple Watch was unveiled by Apple on Sept. 9, in the same event where the company unveiled the iPhone 6 and iPhone 6 Plus. The device is Apple's first entry into the wearable technology market, wherein rivals such as Samsung and LG and startup companies such as Pebble have already established their presence. +In the event, Apple said that the Apple Watch will begin to be sold to the public in early 2015 without specifying a definite time frame. However, if Apple really does intend to release the device early next year, mass production should already have started. +AppleDaily's report of a January start date for the Apple Watch's mass production could mean that the delay was due to the suppliers that Apple tapped for the device. +Earlier rumors suggested that two suppliers will be assembling the Apple Watch, namely Quanta Computer and Inventec. However, AppleDaily's report specifies that Quanta will be the only supplier to Apple for the device, with Inventec being removed from the process due to reasons that have not been made clear. +Quanta has started its preparations for the mass production of the Apple Watch, increasing its workforce to a total of 4 million employees, reported G for Games. There is also said to be an agreement between Apple and Quanta that the Chinese supplier will not be manufacturing smartwatches for Apple's rival companies in the industry. +The delayed mass production start, coupled with the sudden departure of a supplier, will make it difficult for Apple to keep its promise of an early-2015 release for the Apple Watch. +The delay will only add to the conservative expectations that Piper Jaffray investment firm analyst Gene Munster has on the sales forecasts for the Apple Watch. +""Overall, we believe that the Apple Watch is light years ahead of any other smartwatch on the market, but consumer application may be limited initially until developers begin to create useful applications for the watch,"" Munster wrote. +Munster forecasts 10 million Apple Watches sold in 2015, with a selling price of an average of $500.","0" +"Apple: Citi Sees $550 and $950 Apple Watches, Accessory Plethora","Jim Suva with Citigroup this evening weighs in with what to expect from the March 9th media event in San Francisco that Apple (AAPL) announced today, an event that is likely focused on Apple Watch, given that, as he points out, Daylight Savings Time starts the day before, March 8th, so the tag line of the event, “Spring Forward,” is an apt time reference. + +Suva, who has a Buy rating on Apple, and a $135 price target, lays out the prospects for details about the watch, including pricing: + +We expect Apple to give specifics on the launch time, price, and geographic locations, which we estimate as: Launch date: April 16th; Price points: $350, $550 and $950; with a launch limited to the U.S., followed by Europe and Asia in the subsequent months. A flurry of fashionable accessories including various colors and materials (plastic, leather, and metal, including high-end metals such as gold, silver and platinum), starting at $29 and ranging over several hundred dollars. We expect features to include Apple Pay, adjustable notifications due to personal frequency and preferences, Apple Health, variable haptic feedback, and battery life of one day (under normal use). Purchase locations to be Apple retail stores and Apple online store only. Hundreds of applications immediately available upon release, ranging from social, financial, health, sports and news etc. + +Apple is more likely to benefit from continued iPhone 6 sales, Suva opines. Still, the WTch is among things that expand its addressable market: + +We do note Apple is actively expanding its total available market (watches, payments, automotive etc). We expect Apple to sell 3.1M watch units in the June qtr, with a F12M est of 17.1M watch units. + +Apple stock on Thursday closed up $1.62, or 1.3%, at $130.41.","0" +"Citi sees Apple Watch price points of $550 and $950; myriad accessories","Citigroup Jim Suva on Apple Watch: + +We expect Apple to give specifics on the launch time, price, and geographic locations, which we estimate as: Launch date: April 16th; Price points: $350, $550 and $950; with a launch limited to the U.S., followed by Europe and Asia in the subsequent months. A flurry of fashionable accessories including various colors and materials (plastic, leather, and metal, including high-end metals such as gold, silver and platinum), starting at $29 and ranging over several hundred dollars. We expect features to include Apple Pay, adjustable notifications due to personal frequency and preferences, Apple Health, variable haptic feedback, and battery life of one day (under normal use). Purchase locations to be Apple retail stores and Apple online store only. Hundreds of applications immediately available upon release, ranging from social, financial, health, sports and news etc. + +Read more in the full article here.","0" +"Analyst: Apple Watch Edition to Cost $950","Citigroup analyst Jim Suva weighed in with his expectations for Apple Watch pricing following the news that Apple is hosting a media event on March 9. Apple already announced pricing will start at US$349—presumably for the Apple Watch Sport—and he thinks Apple Watch will cost $550 while the Apple Watch Edition will be priced at $950. He's also pegging April 16 as the smartwatch's official release date. + +Citigroup analyst thinks Apple Watch Edition will cost $950, not $5,000Citigroup analyst thinks Apple Watch Edition will cost $950, not $5,000 + +On Apple's March 9 media event he said, + +We expect Apple to give specifics on the launch time, price, and geographic locations, which we estimate as: Launch date: April 16th; Price points: $350, $550 and $950; with a launch limited to the U.S., followed by Europe and Asia in the subsequent months. +Setting Apple Watch Sport at $350 and the standard Apple Watch at $550 falls in line with the general consensus, but the $950 price point he's targeting for Apple Watch Edition comes in well below expectations. Apple Watch Edition ships with a gold body instead of aluminium or stainless steel, and is generally expected to start somewhere between $5,000 and $10,000. + +Mr. Suva said he expects Apple will offer a wide variety of accessories for Apple watch with bands starting at $29 and topping out in the hundreds of dollars. He also thinks hundreds of apps will be available on launch day. + +He offered up his thoughts on which features we'll see in Apple Watch when it launches saying, ""We expect features to include Apple Pay, adjustable notifications due to personal frequency and preferences, Apple Health, variable haptic feedback, and battery life of one day (under normal use)."" + +Shoppers hoping to be the first to get an Apple Watch will be able to buy theirs in Apple's own retail stores and through the company's online store. Mr. Suva expects Apple's smartwatch won't be available through other retailers. + +Apple sent out media invitations on Thursday for a March 9 event teased as ""Spring forward,"" which is a play on the Day Light Saving change happening on March 8, and likely a thinly veiled hint that we'll be getting more Apple Watch news. + +When Apple first showed off its smartwatch last September, we saw three models with a wide selection of bands, support for tracking basic fitness activity such as steps and distance walked, along with heart rate logging. Apple Watch will also offer Apple Pay support, and will require an iPhone to perform many of its tasks. + +Mr. Suva has a ""Buy"" rating on Apple's stock along with a $135 target price. Apple is currently trading at $129.59, down 0.82 (0.63%). + +[Thanks to Barrons for the heads up] + +The Mac Observer Spin +Mr. Suva's $950 price point for the gold Apple Watch Edition is surprisingly low compared to the general consensus that it won't start below $5,000 and could cost more than $10,000. We'll have to wait until Apple's March 9 media event where Apple Watch pricing is expected to be announced to see how close he really is.","0" +"Will Apple hit a Valentine’s Day 2015 target for the Apple Watch’s release?","You may remember Apple CEO Tim Cook teasing major new product categories for Apple to be released in 2014. Technically, that will happen with Apple Pay next month, Apple’s first foray into the mobile payments category, but it is far more likely that Cook had been focusing his teases on the Apple Watch. Earlier this month, Apple debuted the fashion and fitness-oriented smart watch to the same crowd that saw the debut of the iPhone 6 and iPhone 6 Plus. While the Watch was demonstrated, it is obviously not a finished product: it’s not shipping until “early 2015,” according to Apple. + +How early in 2015? Nobody knows for sure, but a new profile from The Information says “that Apple would be lucky to ship it by Valentine’s Day.” At 9to5, we’ve been hearing similar whispers. Valentine’s Day is in February, and this could be a great target for Apple to try to hit for the Watch’s launch. That Hallmark Holiday isn’t as strong as a shopping season as the December holidays, but it is still a time that many people seek out expensive or fashionable gifts. So why not the Apple Watch Edition, too? Apple has done product launches around that timeframe before, releasing new iOS device storage capacities and pink-colored models on multiple occasions. + +Valentine’s Day aside, the bigger picture here is that many signs indicate Apple missed its own 2014 launch target. As The Information says: + + + + +Earlier this year, Apple executives indicated to some employees and others involved in the product that it was expected launch for the holidays. After all, since 2011, Apple has configured itself for once-a-year launches of new versions of its flagship hardware, the iPhone, in time for the Western world’s peak shopping season. But at some point in recent months that changed, according to these people, who surmised that Apple wanted more time on the software and the apps. The Information previously reported some development hiccups, including consideration of a new screen. The inside chatter parallels a shift among analysts as well; in the months before the announcement, many shifted their forecasts from this year to next. + +Seemingly confirming this is commentary from Cook and Apple Senior VP of Operations Jeff Williams (who supervised the Apple Watch software and hardware engineering groups) in an interview with Bloomberg BusinessWeek. Asked why the Apple Watch missed a 2014 target, the executives responded: + +Williams is unapologetic about the Apple Watch missing the 2014 holiday season. “We want to make the best product in the world,” he says. “One of our competitors is on their fourth or fifth attempt, but nobody is wearing them.” Cook also preaches patience. “We could have done the watch much earlier, honestly, but not at the fit and finish and quality and integration of these products,” he says. “And so we are willing to wait.” + +So it seems fairly clear that 2014 was the original, missed target, but Apple is unapologetic about the entire situation. After all, this makes sense. Apple has been teasing a new category for years during the post-Steve Jobs-era, and they need to get it mostly right on version 1.0. Cook has even hinted that his own Apple Watch has yet-to-be-introduced functionality, and we don’t even know the pricing or exact details about the device (beyond the Sport model), so perhaps Apple will announce everything else related to the Watch on their website or at an event early next year.","0" +"Apple Watch Likely Be Launched On Valentine’s Day; Plus First Apple Watch Accessory To Be Showcased In CES 2015","At CES 2015 event scheduled between Jan. 6 and Jan. 9, a potential company named Standzout will be showcasing its prototype of the Apple Watch accessory. The accessory in focus is the ""Bandstand Apple Watch dock."" The aforesaid company calls it the first great Apple Watch accessory ever. + +The dock apparently makes use of an ""induction charging plate to power the gadget"" and by doing so, it holds the smartwatch in place. In addition, there are two USB ports housed on the device to enable the user to charge other devices like Apple iPhones and iPads, notes Phone Arena. Interested readers can check out the Bandstand Apple Watch dock prototype from Gigaom. + +When it comes to Apple Watch release date, reports state that the Cupertino-headquartered company might launch its gadget on Valentine's Day. Meanwhile, the sales predictions for the Apple Watch are as high as 30 million units and the demand is assumed to grow further, according to the same site. In contrast to other smartwatches available in the market, Apple will reportedly be marketing the Watch as a fashion accessory than a tech gear. + +When it comes to key features of the Apple Watch, the company is believed to be working on two different models, namely 38 mm and 42 mm versions of the smartwatch. Moreover, the gadget with high focus on fashion will be offered in six different casing options. In addition, the smartwatch's band can reportedly be interchanged as required. As far as the pricing details go, the base variant of the Apple Watch i.e. the sports model will reportedly be priced at $349. But then, the high-end variants especially the solid gold/diamond model will go as high as several thousand dollars, says MacRumors. + +Moving on to the higher-end Apple Watch, Apple is planning to release a $30,150 priced model of the smartwatch, adorned in diamonds and sapphire. The sapphire and diamond-clad gadget will reportedly come with eight rows of ""high-grade 15 carat diamonds"" and it is considered to be the ""luxury edition"" of the smartwatch. Apparently, this device will also come equipped with sapphire glass display for extra protection, notes Phone Arena.","0" +"Your Apple Watch might be ready just in time for Valentine’s Day","The Apple Watch was Apple’s “one more thing” announcement during its iPhone 6 event, but the company still left many questions about the device unanswered. One of them is the device’s actual release date, as Apple simply said during the keynote that the device is coming in early 2015. Meanwhile, The Information has learned from sources familiar with the matter that Apple employees and partners were expecting “until recently” to see the Watch in stores this year. + +“Earlier this year, Apple executives indicated to some employees and others involved in the product that it was expected launch for the holidays,” the publication writes. “But at some point in recent months that changed, according to these people, who surmised that Apple wanted more time on the software and the apps. The Information previously reported some development hiccups, including consideration of a new screen.” + +Apparently, “Apple would be lucky to ship it by Valentine’s Day” next year, although an actual launch date for the device is still not available. + +For what it’s worth, 9to5Mac says it heard similar whispers about a tentative Valentine’s Day launch for the smartwatch. + +In a recent interview with Bloomberg Businessweek, Apple senior vice president of operations Jeff Williams basically confirmed that Apple needs more time refining the device before it’s ready to sell it to customers, taking a hit at Samsung in the process. “We want to make the best product in the world,” he said. “One of our competitors is on their fourth or fifth attempt, but nobody is wearing them.” + +TAGS:","0" +"Rumor: Apple Watch Production Gearing Up For Valentine's Day Release With High Prices","Production is ""gearing up"" for the upcoming launch of the Apple Watch, according to a fresh report from Digitimes. + +Industry sources indicate that as many as 40 million units of Apple's custom chip have been ordered to prepare for initial shipments. These numbers suggest that the Cupertino tech giant is expecting high global demand for its innovative smartwatch. + + +Along with those high production stats, however, come potentially high prices for consumers. When the Apple Watch was first revealed in September, the base model was announced at a $350 for an aluminum band. This is well over $100 more than similar products from competitors like Sony and Motorola. The ever-looming Apple tax doesn't stop there either. + +Apple Watch stainless steel bands could start as high as $500, says French Apple blog iGen.fr, while wealthy buyers hoping to purchase a solid gold band for their Apple smartwatch may have to shell out as much as $5,000. French pricing schemes may vary widely from what we see on day one in the United States, so the accuracy of these figures is still up for debate. Fans of Apple products are used to paying higher prices for premium goods, and that trend seems to be alive and well in the company's latest product. + +For those wondering when the Apple Watch hits store shelves, a recent rumor report from Business Insider pegs a release as soon as Valentine's Day 2015. That date is supposedly an optimistic one, however, so officials at Apple are more inclined to stick to a tentative spring 2015 time frame. + +As production enters its heaviest phases, Apple seems ready to tackle the watch industry in full force. What remains to be seen, is if the company's first massive chip order will be enough to satisfy consumer demand. + +Is the Apple Watch high on your wish list? Would you pay thousands of dollars for a top-tier band? Tell us your thoughts in the comments!","0" +"Valentine’s Day 2015 May Be The Apple Watch Release Target","Almost throughout the entire year we constantly heard rumors that Apple’s smartwatch will be released later this year. A couple of weeks back the Apple Watch was formally unveiled but the company also revealed that it won’t hit the market until early 2015. There has already been much speculation about why Apple missed its 2014 launch target for this wearable device but what most people are now interested is when it’ll finally be available? If recent reports are to be believed then Valentine’s Day 2015 may be the Apple Watch release target. +Every year Apple releases its new iPhones and iPads around the holiday season which is one of the most lucrative shopping seasons of the year. Probably why it was assumed from the very start that Apple’s smartwatch too would be released around the same time. +But recently rumors about production issues starting cropping up, hinting that the release may have been pushed back as a result of these delays. While Apple hasn’t confirmed if production issues really did play a part in pushing the smartwatch’s release into 2015 CEO Tim Cook did remark in an interview with Bloomberg BusinessWeek that Apple “could have done the watch much earlier, honestly, but not at the fit and finish and quality and integration of these products.” +Valentine’s Day doesn’t see shopping frenzy that can rival the lucrative holiday season but its still that time of the year when people are a bit loose with their wallets. The Information reports on the possibility of Apple shipping the smartwatch by Valentine’s Day 2015 and 9to5mac has been hearing whispers about the same, still there no confirmation on this from Cupertino. +Whenever the Apple Watch ultimately go on sale it will start from $349.","0" +"The Apple Watch Will Debut by Late March [Report]","While hype around the Apple Watch has remained steady, one factor has hurt consumers' interest: No one has known when it's arriving. All that Apple revealed was that the device — its first foray into wearables — would be unveiled sometime in early 2015. Does that mean right after New Year's? Or early Spring? Now, we're getting a clearer idea on the release date for the Apple Watch. + +Sources familiar with the product’s development told 9to5Mac that the device is on track to ship by the end of March. Additionally, multiple sources revealed that Apple is planning a comprehensive testing program to train retail store employees on the new product between Feb. 9-16. + +The program will entail sending one to two associates from each U.S. store to the company's offices in Cupertino, California or Austin, Texas. There, employees will be familiarized with all the features of the watch first-hand. Those employees will then train the staff at their respective stores. + +While the plan is reportedly to release the wearable in March, 9to5Mac noted that unexpected delays are always a possibility. If there are any setbacks in terms of software development or manufacturing, the Apple Watch may not hit stores until April or later. + +As I wrote in December: + +Apple certainly made some smart decisions for the firm’s foray into wearables. For one, the company refused to describe the product as a “smartwatch” — something that separated their gadget from competitors’. On the other hand, the tech giant also opted not to hold any big press events about the watch after their initial announcement, and marketing efforts have been relatively weak in comparison to their other products. +While Apple analyst Gene Munster has pointed to waning interest in the Apple Watch, analysts such as Trip Chowdhry of Global Equities Research has still been arguing that the Apple Watch will be a smash success, Barron’s reported. (Chowdhry even argued that every iPhone user will also be an Apple Watch user, according to Barron's.)","0" +"Report: Apple Watch to Ship in March","Rumors about a spring launch for the Apple Watch might be true; the latest reports tip a March arrival. +Cupertino is reportedly planning to hold ""extensive testing programs"" between Feb. 9 and 16 to acquaint Apple Store employees with the new product category. Citing anonymous sources, 9to5Mac suggested that store representatives will be sent to Apple offices in Cupertino or Austin for hands-on experience, which they will then pass on to in-store employees. +Apple unveiled its long-awaited smartwatch in early September, showing off the device, which comes in three variants with different bands: Apple Watch, Apple Watch Sport, and Apple Watch Edition. + VIEW ALL PHOTOS IN GALLERY +Available in a 38mm or 42mm watch face, the device requires it be connected to an iPhone (5, 5c, 5s, 6, or 6 Plus). To juice it up, attach the circular, magnetic charger onto the back of the face. Press the dial, or digital crown, to access Siri, and just raise your wrist to call on apps, look at photos, follow turn-by-turn directions, and communicate with friends and family. +By November, reports were tipping a springtime ship date—after the Chinese New Year, according to the leaked transcript of a voice message shared by retail chief Angela Ahrendts with retail employees. +Apple review, Apple commentary, Apple news... Everything AppleNow that the holiday shopping season is over, overseas employees must prepare for the company's Chinese New year sale, which begins Feb. 19. Then, the Apple Watch. +Apple Chief Designer Jony Ive spoke about the future of the Apple Watch during a recent event at the San Francisco Museum of Modern Art, saying that he unequivocally believes that the watch will help ""establish a new category of computing device."" +But how can advertisers take advantage of Apple's wearable? Mobile marketing firm TapSense is providing a glimpse of its Apple Watch ad-buying service during this week's CES 2015 in Las Vegas. According to Reuters, TapSense's product would allow businesses to use the watch's applications to notify customers of special deals—but only in already-open apps, avoiding annoying pop-up ads. +For more, see PCMag's Hands On With the Apple Watch and the slideshow above. Also check out 5 Reasons the Apple Watch Is a Winner and 5 Wearables More Interesting Than the Apple Watch, as well as Understanding Apple's Watch Strategy.","0" +"KGI: iPhone sales forecast at 73M for Q4 ahead of Apple Watch debut in March, 12"" MacBook Air in Q1","Apple is forecast to have shipped a whopping 73 million iPhones over the 2014 holiday quarter on strong iPhone 6 demand, according to one well-connected analyst who also expects a busy start to 2015 for the company, with Apple Watch sales in March and a rumored 12-inch MacBook Air coming sometime before April. + +In a research note from well-connected KGI analyst Ming-Chi Kuo obtained by AppleInsider, Apple's latest iPhone 6 and iPhone 6 Plus models led a charge to 73 million overall unit sales for the quarter ending December. The analyst estimates the 4.7-inch iPhone 6 to hit more than 42 million, while the larger 5.5-inch iPhone 6 ""phablet"" contributed with just over 16 million unit sales. + +If the numbers hold up, Apple is in for a record-smashing holiday quarter. Kuo's estimates are well above expectations from other leading investment banks including UBS, which earlier this month forecast Apple to sell 69 million iPhones. + +Momentum from Apple's iPhone 6 lineup will spill into the first quarter, driving overall iPhone shipments to an about 61.7 million unit sales. A performance of that caliber would buffer seasonally slow sales. + +Consistent with the latest reports, Kuo also expects the highly anticipated Apple Watch to launch in March. While Apple has stayed mum on exact specifications, the company could fill in the blanks with a special announcement prior to the device's debut, the analyst said. + +Assuming a March launch, Apple Watch is expected to sell 2.8 million units in the first quarter, meaning those sales will be spread across a relatively short one-month span. Kuo says most component suppliers will see shipments in the 4 million to 5 million unit range through the March quarter, but a few manufacturers are seeing low yields on key parts, slowing down final assembly and shipping. + +On Apple's rumored 12-inch MacBook Air with Retina display, Kuo is forecasting a ship-by date sometime this quarter. The all-new thin-and-light, said to sport a Retina display, ultra-thin form factor and Intel's latest mobile chips, will help fuel a 2.6-percent quarter-over-quarter increase in Mac shipments. Kuo expects Mac sales to hit 6 million units for the first three months of 2015, up slightly from 5.9 million forecast for Q4 2014. + +Aside from industry scuttlebutt, not much is known about Apple's ultraportable newcomer. A set of photos posted online yesterday purportedly show the laptop's display assembly, which boasts edge-to-edge glass with black bezels and eschews the usual translucent Apple logo for a polished insert more in line with the latest iOS devices. + +Finally, Kuo sees drooping sell through for iPad as Apple's recently released iPad Air 2 and iPad mini 3 models largely failed to move the needle during the holiday season. For the December quarter, estimates put iPad shipments down 17.8 percent year-over-year to 21.4 million units. Moving into the first quarter of 2015, iPad could hit 10.1 million unit sales, but the number is still weak, down 38 percent compared to the same time last year. + +Interestingly, Kuo models a rise in shipments for older iPad versions during the March quarter while at the same time revising down previous estimates of iPad Air 2 and iPad mini 3. The analyst adjusted his numbers to reflect challenges Apple's tablet is facing with shifting market headwinds.","0" +"APPLE WATCH MAY GO ON SALE IN MARCH ACCORDING TO ANALYST","The Apple Watch may hit shelves in March, claims KGI Securities analyst Ming Chi Kuo, who also predicts 5 million sales in its first quarter. + +Earlier reports, according to MacRumors, support the possible March release date. + +Apple first unveiled the Apple Watch last September, a 64-bit smartwatch officially scheduled for an early 2015 release. It will cost $350. + +Everything You Need to Know About the Apple Watch +03:45 +According to Kuo, Apple will reveal more information about the smartwatch before its launch, including details on pre-ordering. + +Three separate collections – Watch, Sport, and Edition – will be available, each running on an iOS-based software called Watch OS. + +Read more about the Apple Watch in our previous coverage. IGN Logo","0" +"The World's Most Accurate Apple Analyst Says The Apple Watch Is Coming In March","KGI Securities' Ming Chi Kuo, one of the most accurate analysts when it comes to predicting Apple's product lineup, says the Apple Watch will be released in March, according to MacRumors. + +And, Apple is expected to make some announcements about the watch soon. + +This follows previous reports from 9to5Mac's Mark Gurman that also said Apple's first wearable will hit store shelves in March. + +Although Apple detailed most of the watch's features back in September, Kuo thinks we'll learn even more about the Apple Watch shortly before its release. Apple will offer more specifics on battery life, Kuo says, which has been a point of contention since the watch was announced. + +The company previously said you'd have to charge it nightly, but didn't reveal an exact battery life estimate. Gurman reports that Apple is targeting between 2.5 and 4 hours of active use and 19 hours of mixed standby and active use. + +This, however, is just a target and could change by the time the watch is actually released. + +Apple will also release information regarding Apple Watch preorders before March, according to Kuo, and the company is expected to ship 2.8 million units in the first quarter of 2015. + +SEE ALSO: One Of Google's Earliest Android Employees Explains Where It Loses To The iPhone","0" +"Apple Reported to Begin Shipping Apple Watch in March, 12-Inch MacBook Air in Early 2015","Apple will begin shipping the Apple Watch in March and will also look to launch its new 12-inch MacBook Air during this quarter, according to a new report by KGI Securities analyst Ming Chi Kuo. The analyst also predicted that iPhone shipments would beat expectations for Q1 2015 with over 61 million units shipped, while iPad shipments are expected to total to 10 million units. + +Kuo notes that Apple may reveal more details about the Apple Watch before its official launch, revealing specifics on battery life and the start of pre-orders. Most components of the Apple Watch will see high shipments during the quarter, but other key components are expected to see low production yields which may cause a constrained supply. Kuo predicts that Apple will ship 2.8 million Apple Watch units in Q1 2015, and his estimate for a March launch falls in line with previous reports. + +Rendering of 12-inch MacBook Air done by Martin Hajek +Kuo's estimate for a Q1 2015 launch of the new 12-inch MacBook Air falls in line with a report earlier this month which stated that Apple supplier Quanta Computer was ramping up production of the notebook for a release this quarter. The 12-inch MacBook Air is expected to feature a new ultra-thin, fan-less design with a high resolution Retina display and a low-power Intel Core M processor. The notebook is also said to be one of the first to take advantage of the new reversible USB Type C connector, which may also be used for charging. + +Related roundups: MacBook Air, Apple Watch , Tags: KGI Securities, Ming-Chi Kuo","0" +"Apple Watch to go on sale in March, claims analyst","The Apple Watch will go on sale in March, and though component shortages may be an issue, about 5 million of the devices are likely to be sold in the first quarter, according to KGI Securities analyst Ming Chi Kuo. + +Apple hasn’t given a launch date for its first smartwatch, which it unveiled in September, only saying to expect the device in early 2015. In addition to Kuo’s research note, however, other reports also have said the watch will be generally available in March. + +Before the device becomes available, Apple will reveal additional information on the watch, including battery specifics and pre-order details, said Kuo, according to a story on the website MacRumors. Apple has said the smartwatch will need nightly recharging, but hasn’t offered other battery information. + +Component issues may cause supply problems for the watch, Kuo said. Even with possible component shortages, Apple will sell 2.8 million Apple Watches in March and go on to sell 5 million devices in the first quarter of 2015, he said. Kuo called for iPhone shipments for that quarter to exceed 61 million units and iPad shipments to come in at 10 million units. + +Apple will also launch a 12-inch MacBook Air that quarter, said Kuo. The ultra-thin notebook will run Intel’s Core M chip and feature the high resolution Retina display.","0" +"New report tips Apple Watch release in March, 12in MacBook Air in Q1","Our 2015 calendars are about to turn over to February and there's still no confirmed launched date for the Apple Watch. As a result, speculation on when the touchscreen wearable will hit shelves is beginning to reach a fervor. Fear not, however, as Ming-Chi Kuo, the analyst with a mostly reliable track record, is here to contribute to the prediction that the Apple Watch will begin shipping in March. Even more, Kuo says the much-discussed 12-inch MacBook Air will launch before the end of 2015's first quarter. + +As an analyst for KGI Securities, Kuo's latest report says that before the Apple Watch's official release, Apple may announce additional details about the device (that's a big ""no duh""), including battery life specifics and when pre-orders will begin. He predicts that while components for the Apple Watch will see high shipments throughout the first quarter, initial production numbers will be low and a high customer demand will make the product hard to find. Kuo forecasts there will be 2.8 million Apple Watch shipments during the first quarter of 2015. + +As for the new 12-inch MacBook Air, the analyst says the ultra-thin laptop will make its debut before the end of the current quarter, with additional information saying that Quanta Computer, an Apple supplier, has already begun increasing production. As a brand new entry to the MacBook Air line, the 12-inch model has long been suggested to feature a Retina display and an even thinner design, while recent rumors have pegged the notebook to ship with only a headphone jack and a single new reversible USB Type-C connector that will be used for charging. + +A release date for the new MacBook Air within the current quarter definitely seems soon, but an alleged leak of the laptop's display only days ago could back up Kuo's claim of production having already begun. As for his prediction of a March release for the Apple Watch, that seems like a pretty safe bet, since Apple's own website says the device is ""coming early 2015."" We'll just have to wait to see if the wearable actually ships that month, of if that's just when pre-orders will begin. + +SOURCE MacRumors","0" +"Apple Watch on Your Wrist in March, 12-inch MacBook Air Set for Q1 Launch: Analyst","iFans can look forward to the much-awaited smartwatch from Apple making its debut this March if analysts' predictions prove true. That's not all: the 12-inch MacBook Air is also gearing up to launch in the first quarter. + +According to a research note from Ming-Chi Kuo, analyst with KGI Securities, the Apple Watch will begin shipping by March. Kuo's forecast is in keeping with recent reports that predict the same release date. He also noted that Apple may hold a special event to unveil the details of the smartwatch, whose specifications are not yet clearly known. + +Kuo also predicted that Apple will release the new 12-inch MacBook Air in Q1 2015. + +The Apple Watch is also anticipated to sell 2.8 million units in the first quarter -- that is the first month alone -- in the event that there is a March launch. + +According to Kuo, shipments in the range of 4 million to 5 million will be seen by most component suppliers in March. However, a few components may also see low production yields, which could affect the assembly and shipping. + +Kuo also forecast that the much-rumored 12-inch MacBook Air with Retina display will also ship in the same quarter, which is in synergy with other rumors. A report earlier inJanuary suggested that Quanta Computer, an Apple supplier, was beefing up production of the notebook to meet the Q1 2015 release deadline. The ultra-thin MacBook Air is rumored to tout a fan-less design and pack in the latest low-power processor from Intel (Core M). It is also expected to boast a high resolution Retina display and may be the first to incorporate the USB Type C connector which is reversible. This may also be used for charging the device. + +Per Kuo, MacBook Air sales will likely touch the 6 million units sales mark (for the first three months of 2015), which is an increase from the 5.9 million forecast in Q1 2014. + +The analyst sees iPhone shipments touch 61.7 million unit sales in Q1 2015. Kuo also anticipates a drop in demand for the iPad as the latest iPad Air 2 and iPad mini 3 tablets did not create much of a stir in the holiday season.","0" +"Analyst “Confirms” Apple Watch And 12-inch MacBook Air’s Q1 2015 Launch","In Q1 2015, we expect that Apple could very well release at least two new products – the Apple Watch and the 12-inch MacBook Air. We have heard two separate rumors that the former will be launched in March and the latter will see a general Q1 2015 release, but if you’re still a little skeptical, analyst Ming-Chi Kuo has basically “confirmed” it. +Kuo has been known for his pretty accurate predictions regarding Apple’s product lineup and their release timeframes, so there could be some truth in his claims. According to Kuo, he confirms that Apple will indeed be releasing the Apple Watch in March and the upcoming 12-inch MacBook Air later on in the quarter as well, but no specific dates were provided. +According to Kuo, the Apple Watch could see some supply constraint. This is due to key components of the wearable having low production yields, but Kuo notes that this is not an issue for the other components which should see high shipments in this quarter. He also expects that Apple will ship 2.5 million Apple Watch units in Q1 2015 alone. +Kuo also predicts that Apple will reveal more details about the Apple Watch ahead of its release and offer up more detailed information about its battery life and when pre-orders will begin, which we guess sounds pretty probable. However as is the case with all rumors, they’re best taken with a grain of salt for now, but do check back with us in the coming weeks/months where hopefully we will have more details for you.","0" +"Werewolf Legend Leads To Jewish Godson's 'Adoption' by Argentina President","Argentina’s president adopted a Jewish godson under a law intended to counteract an old legend about werewolves. +President Christina Fernandez described in seven tweets her meeting with her new godson, Yair Tawil, a member of a Chabad-Lubavitch family. +He was adopted as a godson under a law passed in the 1920s. The law was passed in order to counteract a legend that led to the death of Argentine boys. According to the legend, the seventh son, born after six boys without any girls in-between, becomes a werewolf whose bite can turn others into a werewolf. +The belief in the legend was so widespread that families were abandoning, giving up for adoption and even killing their own sons. +The law only applied to the biological children of Catholic families until the enacting of a presidential decree in 2009, which allows children from other religions to qualify. +The boys receive presidential protection, a gold medal and a scholarship for all studies until his 21st birthday. +Shlomo and Nehama Tawil, parents of seven boys, in 1993 wrote a letter to the president asking for the honor and were denied. But this year Yair wrote a letter to the president citing the 2009 decree, and asking for the designation of godson. +Yair Tawil on Tuesday became the first Jewish godson of a president in Argentina’s history. Fernandez received the Yair, his parents and three of his brothers in her office, where they lit Hanukkah candles together on a Hanukkah menorah from Israel presented to the president by the Tawil family. +The president in her tweets and photos described to her 3.4 million Twitter followers the “magical moment” with a “marvelous family.” She described Yair as “a total sweety,” and his mother a “Queen Esther.” +She tweeted that the Tawils “are a very special family. They have a sort of peace, happiness and a lot of love that is not common.” The tweet included a link to the presidential blog, which includes more photos from the meeting. +Shlomo Tawil is the director of the Chabad House in Rosario, located in central Argentina","0" +"President of Argentina adopts godson to stop him from turning into a werewolf","The President of Argentina, Cristina Fernandez de Kirchner, has adopted a Jewish godson – to prevent him from becoming a werewolf. + +Although this sounds like something straight out of a fantasy novel, the President last week met Yair Tawil and his family for the unusual ceremony, which dates back more than 100 years and is based on Argentinian folklore. + +According to the legend, the seventh son of a family will transform into ‘El Lobison’, a werewolf like creature, on the first Friday after the boy’s 13th Birthday, and will continue to turn into a blood-thirsty, baby eating werewolf every full moon. + +The fear of the creature was so fervent in 19th century Argentina that many families murdered or abandoned their seventh born son, forcing the Argentinian government to implement the process of Presidential adoption. + +The tradition was established in 1907, and was extended to baby girls in 1973. + +Although having seven children is now much rarer than 100 years ago, seventh sons or daughters can now expect to gain the President as their official godparent, as well as a gold medal and educational scholarship. + +The President has said that Yair is the first Jewish boy to take part in the ceremony, as the tradition was exclusive to Catholic children until 2009.","0" +"Argentina's President Just Adopted a Son So He Won't Turn into a Werewolf","Argentinian President Cristina Fernandez de Kirchner wants to put an end to werewolf bar mitzvahs once and for all. + +Kirchner adopted Argentinian teen Yair Tawil as her godson as part of a folktale that says the seventh-born son in a family will turn into a werewolf and eat unbaptized babies, the New York Daily News reports. + +This may sound familiar to fans of 30 Rock: + +Source: YouTube + +Wait, what? According to Argentinian folklore, the seventh son born to a family turns into the feared ""el lobizon,"" the Independent explains. The werewolf-like beast ""shows its true nature on the first Friday after boy's 13th birthday, the legend says, turning the boy into a demon at midnight during every full moon, doomed to hunt and kill before returning to human form."" + +The legend seems ridiculous, but the Independent reports that fear of the creature was so widespread in 19th century Argentina that some families even murdered their babies. Fear and panic gave rise to the unusual practice of adoption by Argentina's president in 1907, which is meant to quell the deadly stigma ad demystify the folklore that was causing the abuse of children. Now a time-honored tradition, any family with seven sons or daughters today gets the president as their official godparent, a gold medal and a full educational scholarship. + + +The boy's parents, Shlomo and Nehama Tawil, had written the president's office requesting the adoption in 1993, the Jewish Telegraphic Agency reported. President Kirchner reportedly described the adoption as a ""magical moment,"" calling the Tawils a ""marvelous family."" + +But are they more marvelous than this? + + +Source: Giphy +h/t New York Daily News","0" +"Argentina’s President Adopted A Jewish Godson To Stop Him From Turning Into A Werewolf","Argentina’s president, Cristina Fernandez de Kirchner, announced on Dec. 23 that she had adopted a young Jewish man as her godson to prevent him from turning into a werewolf-like creature. + +According to Argentine folklore, the seventh son of a family will turn into a werewolf-like creature called “el lobizón” when he turns 13. The lobizón feeds on excrement and unbaptized babies. + +The Argentine president will now become the official godparent of any family that has seven sons or daughters. The tradition dates back to 1907. In 1973, the Argentine government extended it to baby girls. + +Mágico fue recibir a Iair Tawil, 1er ahijado presidencial de nuestra historia que profesa la fe judía. + +Yair Tawil, Kirchner’s newest godson, is the first Jewish person to be adopted, however. Kirchner said the tradition only included Catholics until 2009. + +Yo no lo sabía, pero su visita coincidía con la celebración de Hanukkah. El papá, decía que no era una casualidad… + +The ceremony began in 1907 in an effort to demystify the folklore and prevent the abuse of children, but has since become a time-honored tradition. The anti-lobizón adoption ceremony also includes a gold medal and a full educational scholarship. + +Tenía razón. Me trajeron de regalo un candelabro de Israel. Me pidieron que encendiera las velas… + +The boy’s parents, Shlomo and Nehama Tawil, had written the president’s office requesting the adoption in 1993, the Jewish Telegraphic Agency reported. + +Y a Iair, que hiciera el rezo. Un momento muy especial. Después me dijeron que tenía que apagarlas y pedir un deseo…","0" +"Werewolf legend leads Argentine president to adopt","The world's werewolf population likely will have one less member to add to its rolls, thanks to the benevolence of Argentine President Christina Fernandez de Kirchner. + +Under a law the country has followed since the 1920s to counteract a generations-old legend, Fernandez adopted Yail Tawil, her godson who was destined, as the seventh son of his family, to become a werewolf, according to various published reports and the president's own tweets. + +The happy family: + +Argentina passed the law because the belief in the curse became so widespread that families were abandoning, putting up for adoption and in some cases killing their seventh sons, according to The Jerusalem Post. + +Tawil's parents wrote Fernandez a letter asking her to take on Tawil as her godson, to which she agreed in a ceremony she described to her Twitter followers as ""magical."" + +Many media reports described Tawil as a boy, but The Guardian said he's 21. + +Editor's note: This story was updated to include The Guardian report that Tawil is 21 years old.","0" +"Argentina's President Adopts Young Boy so He Won't Turn Into Werewolf","What did you do this weekend? Argentinian President Cristina Fernandez de Kirchner adopted a young boy as her godson so he wouldn't turn into a werewolf and eat babies. Yes, really! (Kind of.) + +It's actually part of a long-standing tradition stemming from Argentinian folklore that says the seventh son in families with no girls are doomed to turn into ""el lobison,"" a werewolf who feeds on unbaptized babies and whose bites could turn others into werewolves. Belief in the legend was once reportedly so widespread that families were abandoning their seventh sons, giving them up for adoption, or killing them. + +A law was passed in the 1920s to counteract the effect (the law was expanded in 2009 to include girls and non-Catholic children), and now, every year, the president formally adopts a boy or girl as his or her godchild, awarding him or her a medal, ""presidential protection,"" and a scholarship to study until the godchild turns 21. + +This year, Fernandez de Kirchner formally adopted Yair Tawil, a member of a Chabad-Lubavitch family, according to the Jewish Telegraphic Agency. In 1993, Yair's parents reportedly wrote to the president asking for the honor and were denied, but this year, Yair wrote to Fernandez de Kirchner himself and got his wish, making him the first Jewish boy in Argentina to be officially adopted by the president. + + +WE RECOMMEND +The 121 Best Celebrity Selfies +Fernandez de Kirchner posted a photo of herself with Yair and his family lighting Hanukkah candles together (below) with a menorah, which Fernandez de Kirchner tweeted was a gift from Yair's family.","0" +"Argentina president adopts Jewish godson for first time in country's history","Argentina’s president has accepted an official Jewish godson for the first time in the country’s history. + +President Christina Fernandez described in seven tweets her meeting with her new godson, Yair Tawil, a member of a Chabad-Lubavitch family. + +He was adopted as a godson under a law passed in the 1920s. The law was passed in order to counteract a legend that led to the death of Argentine boys. According to the legend, the seventh son, born after six boys without any girls in-between, becomes a werewolf whose bite can turn others into a werewolf. + +The belief in the legend was so widespread that families were abandoning, giving up for adoption and even killing their own sons. + +The law only applied to the biological children of Catholic families until the enacting of a presidential decree in 2009, which allows children from other religions to qualify. + +The boys receive presidential protection, a gold medal and a scholarship for all studies until his 21st birthday. + +Shlomo and Nehama Tawil, parents of seven boys, in 1993 wrote a letter to the president asking for the honor and were denied. But this year Yair wrote a letter to the president citing the 2009 decree, and asking for the designation of godson. + +Yair Tawil on Tuesday became the first Jewish godson of a president in Argentina’s history. Fernandez received the Yair, his parents and three of his brothers in her office, where they lit Hanukkah candles together on a Hanukkah menorah from Israel presented to the president by the Tawil family. + +The president in her tweets and photos described to her 3.4 million Twitter followers the “magical moment” with a “marvelous family.” She described Yair as “a total sweety,” and his mother a “Queen Esther.” + +She tweeted that the Tawils “are a very special family. They have a sort of peace, happiness and a lot of love that is not common.” The tweet included a link to the presidential blog, which includes more photos from the meeting. + +Shlomo Tawil is the director of the Chabad House in Rosaria, located in central Argentina.","0" +"Argentina's President Cristina Kirchner Adopts Jewish Godson To Prevent Him Turning Into A Werewolf","The president of Argentina, Cristina Kirchner, has adopted a Jewish grandson in order to prevent him becoming a werewolf. + +Tenía razón. Me trajeron de regalo un candelabro de Israel. Me pidieron que encendiera las velas… pic.twitter.com/DVWewmZera + +— Cristina Kirchner (@CFKArgentina) December 23, 2014 + +Hmmm, let us explain. + +According to an old Argentinian legend, the seventh son born after six boys with no girls in between is liable to turn into one of the mythical creatures. + +Fear was so rife in the country that families would often give up their seventh-born sons for adoption or even kill them. + +In the 1920s a law was passed to counteract the legend. It offered presidential protection, a gold medal and a scholarship for all studies until their 21st birthday but only for Catholic families. + +Y a Iair, que hiciera el rezo. Un momento muy especial. Después me dijeron que tenía que apagarlas y pedir un deseo… pic.twitter.com/31ThMLjULn + +— Cristina Kirchner (@CFKArgentina) December 23, 2014 + +In 2009 a decree was passed to extend the law to other religions. + +Shlomo and Nehama Tawil, parents of seven boys, had written to the then- president in 1993 but were turned down. After the updated law was passed they tried again and Kirchner agreed. + +She said: ""It was magical to receive Iair Tawil, the first presidential godson in national history to profess the Jewish faith. Iair, 21, is completely sweet. + +Yo no lo sabía, pero su visita coincidía con la celebración de Hanukkah. El papá, decía que no era una casualidad… pic.twitter.com/o3y5E17Gew + +— Cristina Kirchner (@CFKArgentina) December 23, 2014 + +""His family, marvelous. His mother Reina Ester. His father, Salomón, a rabbi. His brothers: Rafael, Eliel, Eitan. I didn’t know, but his visit coincided with the celebration of Hanukkah. His father said it was no coincidence. He was right. They brought me the gift of a menorah. + +""They asked me to light the candles, and for Lair to say the prayer. A very special moment. Later, they told me to blow them out and make a wish. Don’t even dream I’m going to tell you what it was.""","0" +"President of Argentina adopts Jewish boy to stop him turning into werewolf","As traditions go this may be the most unbelievable tale you may ever read - the President of Argentina has adopted a Jewish boy as her godson to stop him turning into a werewolf. + +Christina Fernandez de Kirchner met Yair Tawil and his family last week at her office to mark the 100-year-old Argentine custom. + +According to legend the seventh son born to a family turns into a ferocious ""el lobison"" or werewolf – on the first Friday after his 13th birthday. + +The country began to introduce adoption procedures to quell the fear of the people in the 19th century who believed their sons could turn into werewolfs (the fear was so extreme in some cases people murdered their baby boys). + +It has become customary since 1907 but formally established in 1973 for the president to adopt their seventh sons and daughters who also receive a gold medal and full educational scholarship. + +Tawil's parents wrote to the president in 1993 for their son to be the first Jewish boy to be adopted and they got their wish this year, according to the Jewish Telegraphic Agency. + +Until 2009, the tradition only applied to Catholic children. + +Last week's unusual ceremony between the president and Tawil, witnessed by his parents and three brothers, happened at the same time as Hanukkah - the eight-day Jewish festival that commemorates the rededication of the holy Temple in Jerusalem in 165 BC. + +Fernandez de Kirchner tweeted: ""I didn't know it but his visit coincided with the Hanukkah celebration. The father said it wasn't a coincidence."" + +She added the meeting with him and his family was a ""magical moment"".","0" +"Argentina’s president adopts Jewish godson to counteract werewolf legend","BUENOS AIRES, Argentina (JTA) — Argentina’s president adopted a Jewish godson under a law intended to counteract an old legend about werewolves. +President Christina Fernandez described in seven tweets her meeting with her new godson, Yair Tawil, a member of a Chabad-Lubavitch family. +Tawil was adopted under a law passed in the 1920s to counteract a legend that a seventh son born after six boys with no girls in between becomes a werewolf whose bite can turn others into a werewolf. Belief in the legend was once so widespread that families were abandoning, giving up for adoption and even killing their own sons. +Under the law, the boys receive presidential protection, a gold medal and a scholarship for all studies until their 21st birthday. Until 2009, the law only applied to Catholic boys. +Shlomo and Nehama Tawil, parents of seven boys, in 1993 wrote a letter to the president asking for the honor and were denied. But this year, Yair wrote a letter to the president citing the 2009 decree and asking for the designation of godson. +On Tuesday, he became the first Jewish godson of a president in Argentina’s history. Fernandez received Yair, his parents and three of his brothers in her office, where they lit Hanukkah candles together. +The president in her tweets and photos described to her 3.4 million Twitter followers a “magical moment” with a “marvelous family.” She described Yair as “a total sweety,” and his mother a “Queen Esther.” +She tweeted that the Tawils “are a very special family. They have a sort of peace, happiness and a lot of love that is not common.” The tweet included a link to the presidential blog, which includes more photos from the meeting. +CORRECTION: The original brief stated incorrectly that Shlomo Tawil was the director of the Chabad House in Rosario, located in central Argentina. The sentence has been deleted.","0" +"Argentina's President Adopts Boy to End Werewolf Curse","Argentina's President Christina Fernández de Kirchner had a ""magical moment"" last week when she ended a young man's werewolf curse — that is, if you believe South American folklore. + +Kirchner shared photos from a Hanukkah candle-lighting ceremony on her blog, and described ""adopting"" a young man named Yair Tawil. He is the seventh son of his family, and because of that, was supposedly cursed to become a werewolf on every full moon after his 13th birthday — unless he is adopted by another family. According to legend, seventh daughters become witches. + +Enter Argentina's presidents, who since 1907 have been adopting — symbolically, anyway — seventh children so that their families can avoid the superstitious stigma of having a ""cursed"" child. The practice has traditionally involved Catholic children, but that was changed by presidential decree in 2009. + +Under Argentine law, seventh children adopted by the president receive a gold medal and an education scholarship until they turn 21. Last Tuesday's ritual was the first time someone of the Jewish faith was adopted by a president. Yair's parents, Shlomo and Nehama Tawil, had first written a letter asking that their seventh son be adopted in 1993, when he was born, reported the Jewish Telegraphic Agency. + +In a series of tweets, Kirchner called the ceremony ""magical"" and the Tawils a ""marvelous family.""","0" +"Argentina president adopts young Jewish boy as godson to prevent him from turning into werewolf","President Cristina Fernandez de Kirchhner adopted Yair Tawil as her godson, due to an Argentine folktale that says the seventh born son in a family will turn into a werewolf, and eat unbaptized babies. + +Argentina's president has adopted a young Jewish boy as her godson to stop him turning into a werewolf. + +Yair Tawil was adopted in a ceremony which took place because of Argentinian folklore, reports the Independent. + +He is the first Jewish boy to be adopted, as the practice only applied to Catholics until 2009. + +According to tradition in the country, the seventh son born to a family turns into a werewolf, a feared ""el lobison"". + +The creature only shows its true nature on the first Friday after the boy's 13th birthday, turning the teenager into a demon at midnight during every full moon. + +Legend has it that the lobison feeds on unbaptized babies. + +Although the story may now seem fanciful, fear of the werewolf-like creature was so widespread in 19th century Argentina that some families even murdered their babies. + +To stop the practice happening the Argentine president began adopting babies. + +Any family now which has seven sons or daughters get the president as their official godparent, a gold medal and a full educational scholarship, reports the Independent. + +President Cristina Fernandez de Kirchhner described the adoption as a ""magical moment"" and called the Tawils a ""marvelous family"".","0" +"Argentina's President Adopts Jewish Boy to Keep Him from Turning into a Werewolf","Argentina's President Christina Fernández de Kirchner has a pretty solid plan for keeping her country safe from werewolves: She's going to adopt them. + +There's apparently an obscure bit of Argentinian folklore that states the seventh son born to a family will turn into the feared el lobison on the first Friday after the boy's 13th birthday. The myth predicts the child will transform into a creature at midnight during each full moon, eternally damned to ravage the countryside before returning to human form. + +Other fun bits of el lobison trivia, per The Independent: They feed on excrement, unbaptized babies and the flesh of the recently dead; they're unnaturally strong; and they can spread their curse by biting. + +The fear of el lobison's curse was so strong in Argentina that families abandoned – or in some cases murdered – their seventh son in the 19th century, which is how the tradition of the sitting president adopting one of these children came to pass in 1907. It was formally decreed in 1973 by then-president Juan Domingo Perón, and extended to baby girls at that time. Those adopted gain the sitting president as their official godparent, a gold medal and a full educational scholarship. + + + + +This year, Kirchner adopted the first Jewish seventh son, Yair Tawil. The practice had extended only to Catholic children until 2009. Kirchner met with Yair and his parents, Shlomo and Nehama, on Dec. 23. She called the family ""marvelous,"" described Yair as ""a total sweetie,"" and bestowed the presidential nickname of ""Queen Esther"" on Nehama. (Shlomo and Nehama had sent in their request back in 1993.)","0" +"Argentina Has a Superstition That Seventh Sons Will Turn into Werewolves","Christina Fernández de Kirchner, the president of Argentina, got a new addition to her family last week when she adopted a 13-year-old Jewish boy named Yair Tawil as her godson, the Independent reports. Her motivations for doing so are based on a centuries-old legend that seventh sons will transform into werewolves. + +In Argentina, the werewolf is referred to as el lobison; in Paraguay it goes by the name Luison, and in Brazil it's called the Lobisomem. The Independent elaborates on the South American legend: + +The werewolf-like creature shows its true nature on the first Friday after boy’s 13th birthday, the legend says, turning the boy into a demon at midnight during every full moon, doomed to hunt and kill before returning to human form. + +As well as feeding on excrement, unbaptized babies, and the flesh of the recently dead, the lobison was said to be unnaturally strong and able to spread its curse with a bite. + +In Guaraní mythology, the lobison is the offspring of Tau, an evil spirit, and Kerana, a mortal woman. In the cultures that believe in the lobison, that creature acts as a sort of Grim Reaper, whose mere presence means that death will soon befall those it comes into contact with. As the Independent explains, by the 19th century, fear of this creature was so acute in Argentina that families sometimes murdered their seventh sons to prevent the legend from coming true. So in 1907, in an attempt to stop this practice, the Argentinean president began adopting seventh sons, which the president insisted would stop the curse. In 1973, the Independent adds, the presidential adoption tradition was also extended to seventh daughters. + +In addition to being able to say he's the president's godson, Tawil will receive a gold medal and enjoy a full educational scholarship. In modern times, the curse, it seems, is more aptly described as a blessing.","0" +"Argentinian President Cristina Kirchner adopts Jewish boy to protect him from werewolf stigma","BUENOS AIRES, Dec. 29 (UPI) -- Argentinian President Cristina Kirchner adopted Jewish boy Yair Tawil as her godson to protect him from the stigma of a folk tale prophesying he will turn into a werewolf. +In Argentina, there is a legend the seventh son born to a family with no daughters will turn into ""el lobison"" or a werewolf upon his 13th birthday. The legend became so feared that families would abandon or kill their sons. To counteract this stigma, the president of Argentina began in 1907 to adopt one of the boys as their godson. + +Tawil is the first Jewish godson as the honor only applied to Catholic boys until 2009. His parents asked for the honor in 1993 but were denied. He appealed to Kirchner, citing the 2009 decree and was accepted as the candidate. + +The family met with Kirchner and presented her with a menorah they lit for Hanukkah.","0" +"Adopting Potential Werewolves Is Routine Business for Argentine Presidents","Last week, President Cristina Kirchner adopted a Jewish teenager named Yair Tawil and posted pictures of the event on her Twitter feed. Outlets around the world ran with the story, explaining the move by citing lingering local superstition about werewolves. In Western folklore, only a werewolf can create another werewolf with its bite, but in Argentina, the story's a little different: the creature is born when a couple gives birth to their seventh son in a row. According to said folklore, seventh sons turn into el lobizon on their 13th birthday if nothing is done about the hereditary curse. Thus, the need for presidential action is pretty clear. + +""The notion of animal shifting came from different Native American traditions,"" Oscar Chamosa, a folklorist at the University of Georgia, told me. ""The idea of el lobison comes from uturunco—or the were-jaguar—which mixed with the European notion of the werewolf."" Chamosa says he's not sure how the idea was first associated with teenaged boys. + +But even if someone who's devoted his entire life to studying Argentine folklore can't explain it, the teen werewolf thing had become pervasive by the early 20th century, and Catholics in Argentina were producing enough seventh children, that the myth became a public policy problem. After all, terrified parents were (according to legend, at least) regularly committing infanticide. + +""In order to counteract the myth, Argentine presidents have traditionally godfathered any child born into the same family,"" Chamosa explains, adding that the governor of a province or mayor of a village would sometimes officiate for practical reasons. ""The rationale is that the godson of a president would be respected throughout his life despite the suspicion his seventh-male birth position would bring with it."" + +This idea apparently prevented people from murdering their own babies, so it was a smart move on part of the Argentine government. But if it's surprising people believed in such a curse a century ago, it's downright bizarre that they're still entertaining the notion of it today. + +As per a decree that came out in 1973, adoptees receive a gold medal and a college scholarship. And Argentina is apparently still making new rules about werewolf children, because in 1999 the adoption ceremony was extended to non-Catholics. As the Independent noted, Tawil is the first Jewish boy to receive the honor. So while a werewolf Bar Mitzvah might be a joke on 30 Rock, it's also apparently a real thing that just happened in South America. + +The boy's parents first applied for the medal and scholarship in 1993, but were denied. They applied again after the rules changed to include Jews in 2009. A tweet from President Kirchner's account shows her lighting a menorah with the Tawils, quite the gesture given that the Jewish population of Argentina is less than half of one percent. + +Jewishpublications are making a big deal out of the historic event, and angry commenters are freaking out about a Jew being adopted—even symbolically—by a non-Jew and the blasphemous concept of a Jewish family taking part in something involving werewolves. (In Jewish folklore, people don't turn into werewolves, and whatever they were before beasthood is never really discussed.) + +But most observers have been glossing over the absolutely fucking strange juxtaposition between a groundbreaking event and an ancient superstition. Like, for instance, that's it's kind of a weird move to progressively bequeath a privilege to a religious minority while tacitly legitimizing the belief that human beings have the ability to transform into mythical creatures that feast on unbaptized babies. + +Stories about the adoption would also have us believe the president of an industrialized nation believes in werewolves, which is clearly not the case. Although presidents in our own country's recent memory believed they were chosen by God, Chamosa describes Argentina's Kirchner as a nominal Catholic who's a ""progressive left-wing president—more like a Marxist and a secular person in general."" Much as our Dear Leader pardons a turkey every year, this is an Argentine ritual that's basically a national inside joke. + +Chamosa says that the werewolf thing has stuck around out of quaint tradition and that the average family in the country today has only two children. For that reason, anyone who achieves an unbroken chain of seven same-sex children is rewarded with the prize. + +Of course, that doesn't mean there aren't some people in Latin America who still believe in el lobizon. + +""Belief in the healing powers of folk saints and withcraft are pretty much shared across the territory, especially—but not only—in rural areas,"" Chamosa says. ""I would say that only old people still believe [in el lobison]. But you really don't know."" + +Follow Allie Conti on Twitter.","0" +"Did Argentina’s president ‘adopt’ a Jewish boy to save him from life as a ‘werewolf’?","Last week, Argentine President Cristina Fernández de Kirchner ""adopted"" a boy as her godson to prevent him from turning into a werewolf, according to multiple news reports. A report in the Guardian subsequently deemed the story spurious. + +Kirchner tweeted images of a small ceremony conducted with the family of Yair Tawil, the seventh child of an Argentine Jewish family, during which the Tawils met with the president and lit candles on a menorah. She was adopting the child as her godson, a symbolic gesture made by generations of Argentine leaders over the years. + +Tenía razón. Me trajeron de regalo un candelabro de Israel. Me pidieron que encendiera las velas… pic.twitter.com/DVWewmZera + +— Cristina Kirchner (@CFKArgentina) December 23, 2014 + +According to the Independent, tradition holds that the seventh son of a family is doomed to turn into a werewolf — known as ""el lobison"" in Argentina — after his 13th birthday and will stalk the night in its beastly form. The legend stems from indigenous folklore and melded with superstitions of European settlers in the 19th century. The fear of this werewolf-child was so pronounced that many seventh sons were killed after they were born, which started the practice in 1907 of Argentine leaders taking these children symbolically under their wing. + +In the past half-century, the ceremonies have been opened up to girls and now, for the first time, Jews. The Tawil family appealed to the Argentine government as early as the 1990s to have the practice extended to non-Catholic families. The boy's new status as the president's godson wins him a gold medal as well as a full educational scholarship, according to the Independent. + +Tales of shape-shifting demons and feral monsters slaughtering livestock can be found in many parts of Latin America. This Argentine iteration can be traced to a local Guarani story of the seven cursed spawn of Tau, an evil mythological spirit, and Kerana, a beautiful woman he seduced and kidnapped. The seventh son was ""Luison,"" who appears sometimes in the shape of a small dog and feeds on corpses. + +But, citing an Argentine historian, the Guardian disputes the connection between beliefs about this folk horror and the presidential act of adopting a seventh son as a godson, and says the latter is a distinct custom brought over by Eastern European migrants. In updates posted to their Web sites, both the Independent and Buzzfeed say European folklore surrounding seventh sons included fears of the child turning into a monster. + +In any case, Americans should not be so quick to scoff at the tradition and its embrace by Argentina's head of state, in whatever form. After all, the U.S. president participates in the ritual pardoning of a fluffy and presumably bewildered animal every year. + +Update: This post has been updated to reflect new skepticism around initial media reports.","0" +"Boy, 16, secretly films sex with teacher then uploads it to WhatsApp","A female teacher who slept with a 16-year-old male pupil was rumbled after he sent a secret WhatsApp video of the encounter to his friends. + +Lucita Sandoval, 26, was apparently unaware the unnamed student was using a camera phone to document the incident until after they had started having sex. + +He later promised he’d deleted the 23 minute video but had actually sent it around on the app, with it soon making its way on to a porn site in Argentina. + +In the video the 16-year-old boy who was wearing a soccer shirt is seen smiling enthusiastically and giving the camera the thumbs up symbol before panning around to show he is having sex with the teacher. + +Sandoval had previously faced disciplinary hearings at her school in the city of Santiago del Estero over inappropriate relationships with students. + +Until now there had been no consequences as nothing had been proven but she now faces the sack. + +The woman who is teaching English at the school has so far not commented on the scandal and is currently on suspension from work. + +Update: It has now been discovered that the woman in the video is not a teacher and the ‘boy’ featured in it is actually a university student in his 20s. + +MORE: It turns out the ‘teacher secretly filmed having sex with student’ story is fake","0" +"Has this Argentine woman fallen victim to a cruel online hoax? Adult video claiming to show teacher having sex with pupil isn't all it seems","A teacher who reportedly had sex with a 16-year-old pupil who secretly took a video of the tryst may have been the victim of a vicious internet prank. + +Various media reported that Lucita Sandoval, a 26-year-old teacher from the city of Santiago del Estero, in north-central Argentina, was facing disciplinary action over the video. + +It now emerges the teacher in the video isn't Sandoval, but an entirely different woman from the city of Corrientes. + +Thumbs up: It was widely reported that Lucita Sandoval (right) was filmed having sex with a student (left). But the man in the video is actually in college and the woman in the footage is not Sandoval + +Nuevo Diario tracked down the man in the video, who isn't an underage student but is actually in college. + +It was also falsely reported the 'teacher' has several times faced disciplinary hearings over inappropriate relationships with pupils. + +The video was posted on a pornography site in September. + +Mystery still surrounds where the story emerged from, and why Sandoval was targeted in this way. + +It now emerges the teacher in the video isn't Sandoval (pictured), but an entirely different woman from the city of Corrientes","0" +"Female teacher facing sack after making SEX TAPE with teenager","Curvy Lucita Sandoval, 26, has been accused on several occasions of romping with students but until now nothing had been proven. + +In the explicit video the teen is seen grinning wildly and giving the camera a thumbs up before panning around to show he is having sex with his teacher. + +The boy, who has not been identified, allegedly told Sandoval he had deleted the video. + +EXPLICIT: The teacher may lose her job over the leaked video [CEN] +ACCUSED: It is not the first time Sandoval has been accused of improper conduct [CEN] +BETRAYED: The teacher reportedly asked the teen to delete the video but he ended up sharing it on the web [CEN] +But instead he shared the 23-minute-long clip with friends on WhatsApp after which it quickly went viral. + +School officials in the city of Santiago del Estero, Argentina, have said now there is clear proof of Sandoval's abuse they will be forced to act. + +The 26-year-old brunette has yet to comment on the scandal. + +ROMP: A screenshot of the viral video which may cost the English teacher her job [CEN] +The English teacher is currently suspended from work pending an investigation. + +Argentina's age of consent is 18 although there are several separate laws regarding sexual relations with adolescents between the ages of 13 and 16.","0" +"Teacher suspended after sex session with teen pupil ends up on hardcore porn website","Lucita Sandoval was apparently filmed having sex with a teenage pupils who films himself smiling and giving a thumbs up + +A teacher is facing the sack after she was secretly filmed having sex with one of her pupils - and the video ended up on a porn site. + +Argentinian beauty Lucita Sandoval was unwittingly recorded having sex with a 16-year-old pupil who switched camera phone on after asking the teacher to turn around. + +The teenager, who wear a football shirt throughout the 23 minute long video, is then seen giving the thumbs up and smiling before panning round to show his naked teacher engaging in sexual acts with him. + +CEN Lucita Sandoval + +According to newspapers in Argentina, 26-year-old Miss Sandoval realises later on that she is being filmed, but appears to do nothing about it. + +It has been reported that the pupil told the teacher he had deleted the footage, but instead he shared it with his friends on WhatsApp . + +The graphic footage was then shared hundreds of times around the country and even ended up on a pornographic website. + +Miss Sandoval has allegedly faced previous disciplinary hearings at the school in Santiago del Estro over inappropriate relationships with pupils, but nothing was done due to lack of evidence. + +CEN Lucita Sandoval + +With the emergence of the video, education authorities have now said they will be forced to act against the teacher. + +Miss Sandoval, who teaches English at the school, has not commented but is suspended from work.","0" +"Sources: Guns N' Roses Frontman Axl Rose Found Dead in West Hollywood Home at Age 52","Sources are reporting that music legend Axl Rose, last remaining original member of the Rock And Roll Hall Of Fame band Guns N' Roses, has been found dead at the age of 52. + +Unconfirmed reports say Rose was found dead Tuesday late afternoon in his West Hollywood home after police were called around 3:30 pm for a welfare check. + +A neighbor has confirmed the residence belongs to Rose but police have not confirmed the man's identity at this time. + +""The home was entered by police through an open back door where a body was found in the foyer area. We have found no signs of abuse or foul-play and have turned the case over to the coroner's office to make a final ruling on the cause of death,"" said Ofc. William Tenpenny, a Hollywood Police spokesperson. + +Born William Bruce Rose, Jr. on February 6, 1962, Rose has been named one of the greatest singers of all time by various media outlets, including Rolling Stone and NME. + +This story is still developing. More details will be made available once they emerge.","0" +"Graffiti Artist Banksy Arrested In London; Identity Revealed","London, England — The elusive graffiti artist, political activist, film director, painter and long time fugitive that for years has gone by the pseudonymous name of Banksy, was arrested early this morning by London’s Metropolitan Police. After hours of questioning and a raid of his London art studio, his true name and identity have finally been revealed. + +The City of London Police say Banksy’s real name is Paul Horner, a 35-year old male born in Liverpool, England. The BBC has confirmed this information with Banky’s PR agent Jo Brooks along with Pest Control, a website that acts as a handling service on behalf of the artist. + +London Police Chief Lyndon Edwards held a press conference to answer questions about Banksy and how Horner was finally apprehended after all these years on the run. + +“We had a 24-hour Anti-Graffiti Task Force monitoring different groups where Banksy was known to frequent. We received word that around 2am a group of individuals left a flat speculated to be one of Banky’s art studios. This group was followed by agents and once vandalism had occurred, we then arrested the group, 5 men total. These individuals all had ID on them except for one, and that is the one we believed to be Banksy,” Edwards said. “We then raided the studio where this group was last seen leaving from. Inside we found thousands of dollars of counterfeit money along with future projects of vandalism. We also found a passport and ID of a Paul Horner who matched the description of the man that we are currently holding.” Edwards continued, “Horner is currently being held without bail on charges of vandalism, conspiracy, racketeering and counterfeiting. We are also holding the other four individuals whose names we are not releasing at this time.” + +Horner was arrested by London Police in Watford, a town and borough in Hertfordshire, England, about 17 miles northwest of central London. + +The graffiti artist that goes by the name Space Invader told reporters he does not agree with the arrest or outing of Banksy’s identity. + +“He’s just doing art, spreading joy and making political statements the best way he knows how. That is what he was doing and I hope that is what he’ll continue to do,” Invader said. “For the London Police to setup some 24-hour task force just to catch Banksy is ridiculous. I hope we hear plenty of noise from the good tax-paying citizens of London about this.” + +After today’s arrest it is unclear who else will be sought in connection with Banksy’s arrest. CNN spoke with John Hawes who is a project manager for Banksy says he is worried that charges could be brought against him also. + +“If they spent this many man-hours and brought this many charges against Banksy, I can’t imagine that he’ll be the only one to go down in all of this,” Hawes said. “All the beauty Paul Horner brought to this world, unfortunately the London Police just see it as vandalism and want to lock him up. It’s such a shame.” + +Banksy’s identity was long speculated to be Robin Gunningham, a man born in Bristol, England in 1973. Known for his contempt for the government in labeling graffiti as vandalism, Banksy displays his art on public walls and even goes as far as to build physical prop pieces. He does not sell his work directly; however, art auctioneers have been known to attempt to sell his street art on location and leave the problem of its removal in the hands of the winning bidder. + +Police apprehended the famous street artist while in the middle of finishing a piece about a mascot for a Christian organization named Fappy The Anti-Masturbation Dolphin. + +“I’m just happy to be a part of this whole thing,” Fappy told CNN. “I’m not familiar with this Banksy character, honestly if it’s not in the Bible I probably haven’t heard of it, but if this arrest spreads awareness of the harmful effects of self-rape, then that is a good thing. Hopefully news of this ordeal will bring the much needed attention to the dangers and consequences of playing with your sin stick or ringing the Devil’s doorbell. Hopefully, God willing, one day, masturbation will be illegal and people will finally be free of playing on the Devil’s playground.” + +Local resident 27-year old Matthew Williams told reporters he was disgusted when he heard news of the arrest. + +“What a waste of taxpayers money. Wouldn’t it be better spent fighting the war against drugs or violence ? What harm has this man done except produce beautiful thought provoking artwork? The counterfeit money thing has either been planted or its part if his art and not actual real counterfeit cash.” Williams continued, “This is just another move by the Five-Oh to crush anything good and free. People need to work out what side they’re on and if they’re on the side of beauty and freedom, they need to start fighting back. There are simply not enough heroes like Banksy to do it for you. I hope this blows up in the cops’ faces and the rest of the government as well.” + +“People are taking the piss out of you everyday. They butt into your life, take a cheap shot at you and then disappear. They leer at you from tall buildings and make you feel small. They make flippant comments from buses that imply you’re not sexy enough and that all the fun is happening somewhere else. They are on TV making your girlfriend feel inadequate. They have access to the most sophisticated technology the world has ever seen and they bully you with it. They are The Advertisers and they are laughing at you.You, however, are forbidden to touch them. Trademarks, intellectual property rights and copyright law mean advertisers can say what they like wherever they like with total impunity. + +F*ck that. Any advert in a public space that gives you no choice whether you see it or not is yours. It’s yours to take, re-arrange and re-use. You can do whatever you like with it. Asking for permission is like asking to keep a rock someone just threw at your head. + +You owe the companies nothing. Less than nothing, you especially don’t owe them any courtesy. They owe you. They have re-arranged the world to put themselves in front of you. They never asked for your permission, don’t even start asking for theirs.” + +In 2011, Banksy was a no-show to accept his Oscar for his documentary Exit The Gift Shop, though his artwork was seen all over Hollywood in days leading up to the awards. + +As soon as news of the arrest was made, the City of London Police say they began receiving dozens of phone calls from people either claiming to be Banksy, or claiming to be with him. As of 6 PM London time, hundreds of people were gathered outside the London Police Department chanting “I’m Banksy!” and holding signs demanding his release. Various local news stations have reported witnessing the crowd parting for a blind woman who attempted to turn herself into authorities claiming that she was in fact the real Banksy. + +Horner was born in Liverpool is a city in Merseyside, England, on the eastern side of the Mersey Estuary. Horner is currently being held without bail on charges of graffiti, public vandalism, criminal mischief, public indecency, resisting arrest, money laundering, criminal conspiracy and racketeering. More charges may follow. For anyone with more information on criminal charges that could be used against Horner, London working alongside the United States have setup a 24-hour hotline at (785) 273-0325.","0" +"Graffiti Artist Banksy Arrested In London; Identity Revealed - See more at: http://nationalreport.net/banksy-arrested-identity-revealed/#sthash.JBpE0Utc.DSzOJ8Zl.dpuf","London, England — The elusive graffiti artist, political activist, film director, painter and long time fugitive that for years has gone by the pseudonymous name of Banksy, was arrested early this morning by London’s Metropolitan Police. After hours of questioning and a raid of his London art studio, his true name and identity have finally been revealed. +The City of London Police say Banksy’s real name is Paul Horner, a 35-year old male born in Liverpool, England. The BBC has confirmed this information with Banky’s PR agent Jo Brooks along with Pest Control, a website that acts as a handling service on behalf of the artist. +London Police Chief Lyndon Edwards held a press conference to answer questions about Banksy and how Horner was finally apprehended after all these years on the run. +“We had a 24-hour Anti-Graffiti Task Force monitoring different groups where Banksy was known to frequent. We received word that around 2am a group of individuals left a flat speculated to be one of Banky’s art studios. This group was followed by agents and once vandalism had occurred, we then arrested the group, 5 men total. These individuals all had ID on them except for one, and that is the one we believed to be Banksy,” Edwards said. “We then raided the studio where this group was last seen leaving from. Inside we found thousands of dollars of counterfeit money along with future projects of vandalism. We also found a passport and ID of a Paul Horner who matched the description of the man that we are currently holding.” Edwards continued, “Horner is currently being held without bail on charges of vandalism, conspiracy, racketeering and counterfeiting. We are also holding the other four individuals whose names we are not releasing at this time.” +Horner was arrested by London Police in Watford, a town and borough in Hertfordshire, England, about 17 miles northwest of central London. + + + +The graffiti artist that goes by the name Space Invader told reporters he does not agree with the arrest or outing of Banksy’s identity. +“He’s just doing art, spreading joy and making political statements the best way he knows how. That is what he was doing and I hope that is what he’ll continue to do,” Invader said. “For the London Police to setup some 24-hour task force just to catch Banksy is ridiculous. I hope we hear plenty of noise from the good tax-paying citizens of London about this.” +After today’s arrest it is unclear who else will be sought in connection with Banksy’s arrest. CNN spoke with John Hawes who is a project manager for Banksy says he is worried that charges could be brought against him also. +“If they spent this many man-hours and brought this many charges against Banksy, I can’t imagine that he’ll be the only one to go down in all of this,” Hawes said. “All the beauty Paul Horner brought to this world, unfortunately the London Police just see it as vandalism and want to lock him up. It’s such a shame.” +Banksy arrested by London Police +Banksy, AKA Paul Horner, seen here being taken into police custody.(AP Photo/Dennis System, File) / AP + + + +Banksy’s identity was long speculated to be Robin Gunningham, a man born in Bristol, England in 1973. Known for his contempt for the government in labeling graffiti as vandalism, Banksy displays his art on public walls and even goes as far as to build physical prop pieces. He does not sell his work directly; however, art auctioneers have been known to attempt to sell his street art on location and leave the problem of its removal in the hands of the winning bidder. +Police apprehended the famous street artist while in the middle of finishing a piece about a mascot for a Christian organization named Fappy The Anti-Masturbation Dolphin. +“I’m just happy to be a part of this whole thing,” Fappy told CNN. “I’m not familiar with this Banksy character, honestly if it’s not in the Bible I probably haven’t heard of it, but if this arrest spreads awareness of the harmful effects of self-rape, then that is a good thing. Hopefully news of this ordeal will bring the much needed attention to the dangers and consequences of playing with your sin stick or ringing the Devil’s doorbell. Hopefully, God willing, one day, masturbation will be illegal and people will finally be free of playing on the Devil’s playground.” +Banksy's artwork tribute to Pulp Fiction +Banksy’s take on Quentin Tarantino’s cult classic Pulp Fiction was well known in the area and amongst collectors of his work. Transport for London ordered it to be painted over because of their strict policy against graffiti. (AP Photo/Dennis System, File) / AP +Local resident 27-year old Matthew Williams told reporters he was disgusted when he heard news of the arrest. +“What a waste of taxpayers money. Wouldn’t it be better spent fighting the war against drugs or violence ? What harm has this man done except produce beautiful thought provoking artwork? The counterfeit money thing has either been planted or its part if his art and not actual real counterfeit cash.” Williams continued, “This is just another move by the Five-Oh to crush anything good and free. People need to work out what side they’re on and if they’re on the side of beauty and freedom, they need to start fighting back. There are simply not enough heroes like Banksy to do it for you. I hope this blows up in the cops’ faces and the rest of the government as well.” +One Of The More Memorable Quotes By Banksy +“People are taking the piss out of you everyday. They butt into your life, take a cheap shot at you and then disappear. They leer at you from tall buildings and make you feel small. They make flippant comments from buses that imply you’re not sexy enough and that all the fun is happening somewhere else. They are on TV making your girlfriend feel inadequate. They have access to the most sophisticated technology the world has ever seen and they bully you with it. They are The Advertisers and they are laughing at you.You, however, are forbidden to touch them. Trademarks, intellectual property rights and copyright law mean advertisers can say what they like wherever they like with total impunity. +F*ck that. Any advert in a public space that gives you no choice whether you see it or not is yours. It’s yours to take, re-arrange and re-use. You can do whatever you like with it. Asking for permission is like asking to keep a rock someone just threw at your head. +You owe the companies nothing. Less than nothing, you especially don’t owe them any courtesy. They owe you. They have re-arranged the world to put themselves in front of you. They never asked for your permission, don’t even start asking for theirs.” +Banksy arrested, real name is Paul Horner +Police confiscated this image from Horner’s residence which was seen in the Oscar winning documentary, “Exit Through The Gift Shop”. Up until today, the face had always been blacked out.(AP Photo/Dennis System, File) / AP +In 2011, Banksy was a no-show to accept his Oscar for his documentary Exit The Gift Shop, though his artwork was seen all over Hollywood in days leading up to the awards. +As soon as news of the arrest was made, the City of London Police say they began receiving dozens of phone calls from people either claiming to be Banksy, or claiming to be with him. As of 6 PM London time, hundreds of people were gathered outside the London Police Department chanting “I’m Banksy!” and holding signs demanding his release. Various local news stations have reported witnessing the crowd parting for a blind woman who attempted to turn herself into authorities claiming that she was in fact the real Banksy. +Horner was born in Liverpool is a city in Merseyside, England, on the eastern side of the Mersey Estuary. Horner is currently being held without bail on charges of graffiti, public vandalism, criminal mischief, public indecency, resisting arrest, money laundering, criminal conspiracy and racketeering. More charges may follow. For anyone with more information on criminal charges that could be used against Horner, London working alongside the United States have setup a 24-hour hotline at (785) 273-0325. +- See more at: http://nationalreport.net/banksy-arrested-identity-revealed/#sthash.JBpE0Utc.DSzOJ8Zl.dpuf","0" +"Graffiti Artist Banksy Arrested In London; Identity Revealed In A Reddit AMA","London, England — The elusive graffiti artist, political activist, film director, painter and long time fugitive that for years has gone by the pseudonymous name of Banksy, was arrested early this morning by London’s Metropolitan Police. After hours of questioning and a raid of his London art studio, his true name and identity have finally been revealed. + +The City of London Police say Banksy’s real name is Paul Horner, a 35-year old male born in Liverpool, England. The BBC has confirmed this information with Banky’s PR agent Jo Brooks along with Pest Control, a website that acts as a handling service on behalf of the artist. + +London Police Chief Lyndon Edwards held a press conference to answer questions about Banksy and how Horner was finally apprehended after all these years on the run. + +“We had a 24-hour Anti-Graffiti Task Force monitoring different groups where Banksy was known to frequent. We received word that around 2am a group of individuals left a flat speculated to be one of Banky’s art studios. This group was followed by agents and once vandalism had occurred, we then arrested the group, 5 men total. These individuals all had ID on them except for one, and that is the one we believed to be Banksy,” Edwards said. “We then raided the studio where this group was last seen leaving from. Inside we found thousands of dollars of counterfeit money along with future projects of vandalism. We also found a passport and ID of a Paul Horner who matched the description of the man that we are currently holding.” Edwards continued, “Horner is currently being held without bail on charges of vandalism, conspiracy, racketeering and counterfeiting. We are also holding the other four individuals whose names we are not releasing at this time.” + +Horner was arrested by London Police in Watford, a town and borough in Hertfordshire, England, about 17 miles northwest of central London. + +The graffiti artist that goes by the name Space Invader told reporters he does not agree with the arrest or outing of Banksy’s identity. + +“He’s just doing art, spreading joy and making political statements the best way he knows how. That is what he was doing and I hope that is what he’ll continue to do,” Invader said. “For the London Police to setup some 24-hour task force just to catch Banksy is ridiculous. I hope we hear plenty of noise from the good tax-paying citizens of London about this.” + +After today’s arrest it is unclear who else will be sought in connection with Banksy’s arrest. CNN spoke with John Hawes who is a project manager for Banksy says he is worried that charges could be brought against him also. + +“If they spent this many man-hours and brought this many charges against Banksy, I can’t imagine that he’ll be the only one to go down in all of this,” Hawes said. “All the beauty Paul Horner brought to this world, unfortunately the London Police just see it as vandalism and want to lock him up. It’s such a shame.” + +Banksy’s identity was long speculated to be Robin Gunningham, a man born in Bristol, England in 1973. Known for his contempt for the government in labeling graffiti as vandalism, Banksy displays his art on public walls and even goes as far as to build physical prop pieces. He does not sell his work directly; however, art auctioneers have been known to attempt to sell his street art on location and leave the problem of its removal in the hands of the winning bidder. + +Police apprehended the famous street artist while in the middle of finishing a piece about a mascot for a Christian organization named Fappy The Anti-Masturbation Dolphin. + +“I’m just happy to be a part of this whole thing,” Fappy told CNN. “I’m not familiar with this Banksy character, honestly if it’s not in the Bible I probably haven’t heard of it, but if this arrest spreads awareness of the harmful effects of self-rape, then that is a good thing. Hopefully news of this ordeal will bring the much needed attention to the dangers and consequences of playing with your sin stick or ringing the Devil’s doorbell. Hopefully, God willing, one day, masturbation will be illegal and people will finally be free of playing on the Devil’s playground. To find out more about finding a cure to this deadly disease, please visit STOP Masturbation NOW.” + +Local resident 27-year old Matthew Williams told reporters he was disgusted when he heard news of the arrest. + +“What a waste of taxpayers money. Wouldn’t it be better spent fighting the war against drugs or violence ? What harm has this man done except produce beautiful thought provoking artwork? The counterfeit money thing has either been planted or its part if his art and not actual real counterfeit cash.” Williams continued, “This is just another move by the Five-Oh to crush anything good and free. People need to work out what side they’re on and if they’re on the side of beauty and freedom, they need to start fighting back. There are simply not enough heroes like Banksy to do it for you. I hope this blows up in the cops’ faces and the rest of the government as well.” + +“People are taking the piss out of you everyday. They butt into your life, take a cheap shot at you and then disappear. They leer at you from tall buildings and make you feel small. They make flippant comments from buses that imply you’re not sexy enough and that all the fun is happening somewhere else. They are on TV making your girlfriend feel inadequate. They have access to the most sophisticated technology the world has ever seen and they bully you with it. They are The Advertisers and they are laughing at you.You, however, are forbidden to touch them. Trademarks, intellectual property rights and copyright law mean advertisers can say what they like wherever they like with total impunity. + +F*ck that. Any advert in a public space that gives you no choice whether you see it or not is yours. It’s yours to take, re-arrange and re-use. You can do whatever you like with it. Asking for permission is like asking to keep a rock someone just threw at your head. + +You owe the companies nothing. Less than nothing, you especially don’t owe them any courtesy. They owe you. They have re-arranged the world to put themselves in front of you. They never asked for your permission, don’t even start asking for theirs.” + +In 2011, Banksy was a no-show to accept his Oscar for his documentary Exit The Gift Shop, though his artwork was seen all over Hollywood in days leading up to the awards. + +As soon as news of the arrest was made, the City of London Police say they began receiving dozens of phone calls from people either claiming to be Banksy, or claiming to be with him. As of 6 PM London time, hundreds of people were gathered outside the London Police Department chanting “I’m Banksy!” and holding signs demanding his release. Various local news stations have reported witnessing the crowd parting for a blind woman who attempted to turn herself into authorities claiming that she was in fact the real Banksy. + +Horner was born in Liverpool is a city in Merseyside, England, on the eastern side of the Mersey Estuary. Horner is currently being held without bail on charges of graffiti, public vandalism, criminal mischief, public indecency, resisting arrest, money laundering, criminal conspiracy and racketeering. More charges may follow. For anyone with more information on criminal charges that could be used against Horner, London working alongside the United States have setup a 24-hour hotline at (785) 273-0325.","0" +"Popular 'Banksy' Instagram account offers powerful message of perseverance after Paris attack","Editors' note: This image, which is unique according to a reverse image search done on Tin Eye, was posted on the @Banksy Instagram account to its nearly 1 million followers. It is not, however, confirmed to be an official account operated by the artist. It could be Banksy, but the artist's real accounts are unclear. We've changed the headline and story below to reflect that. + +A popular Banksy Instagram account weighed in on Wednesday with a powerful homage to the murdered journalists at the French newspaper Charlie Hebdo, victims of a horrific terror attack. + +Take a look: + +A photo posted by Banksy (@banksy) on Jan 1, 2015 at 3:02pm PST + +The account, which has nearly one million followers — though it is not known to be an official Banksy Instagram account — posted a picture on featuring three pencils — the pencil fully intact is next to the word ""yesterday,"" a broken pencil represents ""today,"" and the resharpened shard shows there will be two pencils ""tomorrow."" + +It adds: ""RIP,"" joining scores of other cartoonists and artists who have been sharing tributes throughout the day. + +Twelve people were killed in what France's president called a ""terror attack"" on satirical magazine Charlie Hebdo in Paris on Wednesday, leading authorities to launch a massive manhunt for the gunmen, who remain at large. No arrests have been confirmed in the hunt for the attackers, though an ""anti-terror raid"" is reportedly underway in the northeastern city of Reims. + +The brothers, caught on tape by an eyewitness, shouted ""Allahu akbar!"" as they walked outside the building carrying large guns and dressed entirely in black. The magazine staff was in an editorial meeting, around lunchtime in Paris, when the gunmen opened fire. Eleven others were wounded; four of those injuries are serious. + +Witnesses described the gunmen as speaking perfect French. + +Charlie Hebdo has frequently drawn condemnation from Muslims. In 2011, the magazine was firebombed after it ran a cartoon depicting the Prophet Muḥammad. + +The editor in charge of the paper was one of those killed on Wednesday. There was no immediate claim of responsibility, though supporters of militant groups like the Islamic State and al-Qaeda praised the attack online. World leaders condemned it as an attack on freedom of expression. + +Additional reporting by Mashable staff. Have something to add to this story? Share it in the comments.","0" +"'Banksy' Reacts To Paris Attack With Poignant Drawing","Banksy appears to have shared a message of sorrow and hope Wednesday after an attack on the Paris office of the satirical newspaper Charlie Hebdo left 12 people dead. + +The drawing was shared from an Instagram account and Facebook page that many believe are associated with the enigmatic street artist. Both posts carried only the message ""RIP"". + +banksy paris charlie hebdo + + +That said, there is debate about the authenticity of the image. The page the drawing was shared from was initially verified by Facebook, but that verification was later removed. Banksy's publicist Jo Brooks told Animal New York that the page is ""100 per cent fake"" and the artist's website says Banksy is ""not on Facebook and has never used Twitter."" + +Many have speculated, however, that the denials are all part of cultivating Banksy's puzzling persona. + +The Guardian and Mashable both identified the Instagram post as being authentic, but Mashable later updated its story to reflect doubts about the image's authenticity. In 2013 The New York Times identified a different Instagram account as being linked to the artist. + +Regardless of whether the real Banksy is behind the drawing, there's no denying it's a powerful image.","0" +"Holy Theft! Batmobile Stolen from 'Batman v Superman'???","Ok, this is all still rumor, but there’s a chance a Batmobile was stolen from the set of Batman v Superman set in Detroit. My former employer Bleeding Cool posted this: +The scuttlebutt from sources in Detroit is that one of the Batmobile models being used in the filming of Batman Vs. Superman has gone missing, believed stolen. + +It would not be the first time a Batmobile has been nicked in Detroit. Though that was just a $200 replica of the TV Series version back in 2o10. + +So far we have no clue or confirmation, but if this is true, we should quickly form a list of suspects. My money is on King Tut. + +Stay tuned for updates, rumors, or the dispelling of rumors! + +We want to hear from you! As always leave us your thoughts and opinions in the comments below! + +Want more Batman? Download the Fansided.com app for more Batman news! Don’t forget to like Caped Crusades on Facebook and follow us on Twitter! +Really love Batman? Caped Crusades is always looking for volunteer writers! Leave us a comment, email me at capedcrusades@gmail.com, or apply on Fansided.com!","0" +"Batmobile Rumored To Have Been Stolen From Batman V. Superman: Dawn Of Justice Set","Rumors have hit social media that the Batmobile has been stolen from the Batman V. Superman: Dawn of Justice set in Detroit. While on the face of it the idea that someone could actually make off with a Batmobile from the heavily-secured set seem somewhat ludicrous, the local Michigan media seems to be taking the reports seriously enough that the police department has been contacted to look into it. + +CBS Detroit notes in their report, “Does this person — if the rumor is true (we don’t know how credible the source is) — think that he or she can just go cruising around in this car no one will notice?” WWJ950 tweets, “Was The Batmobile Stolen In #Detroit? Unconfirmed Rumors Are Swirling, And Police Tell WWJ They'll Look Into It.” + +Of course, it’s a little unclear from the tweet if the police department is actually looking into the disappearance of the Batmobile or is just looking into the source of the unconfirmed rumors. Most sites seem to be pointing to Bleeding Cool as the source of the rumors, which they report as having heard from sources in Detroit. + +Batman V. Superman: Dawn of Justice is scheduled to be released in movie theaters on March 25, 2016.","0" +"Was The Batmobile Stolen In Detroit?","Only in Detroit? Holy stolen Batmobile, Batman… +A website is reporting that the Batmobile, from the upcoming Batman v. Superman flick, has gone missing in Detroit… and is presumed stolen. +If this is true I could only imagine seeing it driving down 696 in rush hour. +Seriously, how the heck could someone steal this car? It’s not like it’s a 2008 Sebring that you could mix up with just about any other Sebring. No, it’s the BATMOBILE! It has machine guns in the front. +Does this person — if the rumor is true (we don’t know how credible the source is) — think that he or she can just go cruising around in this car no one will notice? +If I see the Batmobile driving around anywhere I am taking photos. Even funnier: Could you imagine getting pulled over for going too slow in this car? No way right? +How would the cops catch it with all the Bat devices that come standard? Does Alfred come to your rescue? Is the Batcave set in the GPS? If so you would be safe from the cops, I presume… +Our brother station WWJ put a call into the Detroit Police Department to see if there is any truth to this. (Update! As of 4 p.m., police were saying they hadn’t heard about this, but were looking into it). +I hope Commissioner Gordon is on the case, too. +Earlier this week photos of the Batmobile surfaced. You think if the photos didn’t surface than people would just think it’s a Corvette rolling down the street? Maybe not.","0" +"REPORT: The Batmobile Might Have Been Stolen In Detroit","It can't be possible. I refuse to believe it. But there are reports circling that the Batmobile has been stolen from the set of Batman Vs. Superman in Detroit. +Details are scarce and nothing is confirmed. Bleeding Cool, which first reported on the caped crusader's missing machine, reached out to Warner Bros. but the studio hasn't responded. CBS in Detroit has contacted the local police department and they're looking into it. + +Again, this is probably bogus, but if it isn't, keep your eyes peeled for something dark, menacing, and with freaking machine guns on its nose.","0" +"BATMAN VS. SUPERMAN BATMOBILE STOLEN","It's being reported that one of the Batmobiles that are currently in Detroit for Batman Vs. Superman has been stolen. + +Details are slim as Bleeding Cool mentions they heard it, but not from whom, and they state WB hasn't responded to inquires. + +It's known that there are at two versions of the Batmobile in Detroit as two were spotted recently under a tarp. + +Cosmic Book News will update when more becomes available. + +This isn't the first time the film has had issues in Detroit as reportedly Henry Cavill almost got into a fight with a bunch of Detroit locals at a bar that dub themselves the ""Deaf Wolfpack."" +""Batman v Superman: Dawn of Justice"" has a March 25, 2016 release starring Ben Affleck as Batman, Henry Cavill as Superman, Gal Gadot as Wonder Woman, Amy Adams as Lois Lane, Laurence Fishburne as Perry White, Diane Lane as Martha Kent, Jeremy Irons as Alfred, Jesse Eisenberg as Lex Luthor, Ray Fisher as Cyborg with Callan Mulvey, Holly Hunter and Tao Okamoto in new character roles for the film. Justice League is to follow directed by Zack Snyder as well. + +For more news on the ""Man of Steel"" and related movies head on over to the Cosmic Book News Superman movie hub.","0" +"Has The Batman Vs. Superman Batmobile Been Stolen In Detroit?","The scuttlebutt from sources in Detroit is that one of the Batmobile models being used in the filming of Batman Vs. Superman has gone missing, believed stolen. + +It would not be the first time a Batmobile has been nicked in Detroit. Though that was just a $200 replica of the TV Series version back in 2o10. + +Anyway, if you are driving around and get overtaken by this… +…do get in touch. + +Warner Bros representatives did not respond to inquiries.","0" +"At CBS Detroit, Fan Site 'Scuttlebutt' Is Enough to Publish Batmobile Rumor","Holy crap, Batman -- look what happened to a a once-distinguished news organization. + +The CBS Detroit broadcast group's website posts a 10-paragraph article, if that's the right word, about something that may or may not have happened: + +A website is reporting that the Batmobile, from the upcoming Batman v. Superman flick, has gone missing in Detroit and is presumed stolen. + +Sounds serious and dramatic. And yet no other local media outlet has a word about it. + +Further reading suggests why. + +""Presumed stolen"" refers to a presumption by the anonymous writer of a four-paragraph post at Bleeding Cool, an Illinois site for comic book fans. Its brief item begins: + +The scuttlebutt from sources in Detroit is that one of the Batmobile models being used in the filming of Batman Vs. Superman has gone missing, believed stolen. + +That site adds: ""Warner Bros representatives did not respond to inquiries."" +The CBS Detroit writer, Evan Jankens, also makes a nod to verification: + +Our brother station WWJ put a call into the Detroit Police Department to see if there is any truth to this. (Update! As of 4 p.m., police were saying they hadn’t heard about this, but were looking into it). + +Members of the broadcast group are WWJ-TV (Channel 62), WWJ Newsradio 950 and two sports radio stations. + +Absent any confirmation, Jankens riffs speculatively on the notion of a possible Batmobile-jacking: + +If this is true I could only imagine seeing it driving down 696 in rush hour. +Seriously, how the heck could someone steal this car? . . . No, it’s the BATMOBILE! It has machine guns in the front. +Does this person — if the rumor is true (we don’t know how credible the source is) — think that he or she can just go cruising around in this car no one will notice? +Hey, we like Friday afternoon playfulness as much as the next keyboard jockey, but stay on the other side of publishing a story from someone else's anonymous source that requires disclaimers such as ""if the rumor is true"" and ""we don't know how credible the source is."" + +That wouldn't slide past a high school student publication adviser and it seems like a disservice to readers of CBS Detroit, which didn't share the wispy piece on its Facebook pages and presumably not on its newscasts. + +The contrasting tweets below show two approaches to the Bleeding Cool short. The first was sent by CBS Detroit's writer to the film director after publication, while the second was posted instead of a preliminary article.","0" +"Batmobile Stolen From 'Batman V Superman: Dawn Of Justice' Set? Report Claims That One Of The Batmobile Models Is Missing! Detroit Locals Responsible?","In a bizarre twist during the filming of ""Batman V Superman: Dawn of Justice"" in Detroit, the Batmobile (or at least one of the models) is missing! The initial assumption based on the report is that Detroit locals may have stolen it! +All initial reports point to Bleeding Cool as the primary source of the report. They did not give any specific details: +""The scuttlebutt from sources in Detroit is that one of the Batmobile models being used in the filming of 'Batman Vs. Superman' has gone missing, believed stolen. +Warner Bros representatives did not respond to inquiries."" +The website is one of the known super hero movie sites and has been accurate in some of their scoops. However, there is no way to determine the accuracy of this claim except through the police. +One of the local radio stations affiliated with CBS Detroit Local did just that. The result along with CBS Detroit's report: +""Does this person - if the rumor is true (we don't know how credible the source is) - think that he or she can just go cruising around in this car no one will notice? +If I see the Batmobile driving around anywhere I am taking photos. Even funnier: Could you imagine getting pulled over for going too slow in this car? No way right? +How would the cops catch it with all the Bat devices that come standard? Does Alfred come to your rescue? Is the Batcave set in the GPS? If so, you would be safe from the cops, I presume... +Our brother station WWJ put a call into the Detroit Police Department to see if there is any truth to this. (Update! As of 4 p.m., police were saying they hadn't heard about this, but were looking into it)."" +We'll keep you posted on further developments. In the meantime, be on the lookout for the Batmobile. It looks like this.","0" +"LOL: RICH JOHNSTON SAYS THE BATMOBILE HAS BEEN STOLEN IN DETROIT","Source: Bleeding Cool + +This news shouldn't bring me so much joy, but Bleeding Cool rumormonger Rich Johnston is reporting that the Batmobile, or at least one of the Batmobiles used for filming Superman v. Batman: Paths of Glory, has been stolen. The movie is being filmed in Detroit, which hasn't been going through the best times of late. There's no official confirmation yet, but hey, maybe somebody needed it to drive out of town to get some fucking water. + +Hey, their tax dollars paid for the breaks Warner Bros. gets for shooting in the state anyway, so when you look at it that way, the thieves were just taking back what was rightfully theirs! + +But don't worry! The Outhouse has it on good authority that the theft wasn't at all malicious. It was just some people trying to win the prize in MTV's Steal the Batmobile contest from 1989!","0" +"Boston.com pulls story accusing prof of sending ‘racist’ emails","The Boston Globe’s Boston.com last night pulled a story off its website that alleged a Harvard Business School professor had sent “racist” emails to the owner of a Chinese restaurant with whom he had a dispute over $4 on his bill. + +Boston.com has taken professor Ben Edelman to task over the dispute in a series of stories. Last night, the website posted a story headlined: “Ben Edelman Appears to Have Sent Racist Email to Chinese Restaurant Owner. Today.” + +“Could it be Harvard Business School Professor Ben Edelman has a problem with people of Asian descent?” the story said. It also included what purported to be the text of emails from Edelman containing a racial slur, which Boston.com said had been provided to the website by the restaurant owner. + +Edelman has reportedly denied sending such an email. + +He could not be reached for comment by the Herald last night. + +The Boston.com story, which gained significant traction on the Internet, was replaced by an editor’s note that reads: “Earlier tonight, Boston.com published a piece suggesting Harvard Business School Professor Ben Edelman sent an email with racist overtones to Sichuan Garden. We cannot verify that Edelman, in fact, sent the email. We have taken the story down.”","0" +"Justin Bieber Helps Defend Russian Fisherman From Bear","Fisherman Igor Vorozhbitsyn is lucky to be alive - after his Justin Bieber ringtone went off while he was being attacked by a bear. + +Igor, 42, thought he was a goner when the brown bear pounced on him as he was walking to a favourite fishing spot in northern Russia's Yakutia Republic. + +But as the bear began to claw at him, Igor's mobile went off and the beast turned tail and fled back into the forest. + +Wildlife experts believe the ringtone - according to local media the singer's hit 'Baby' - must have startled the bear into halting its attack. + +""Sometimes a sharp shock can stop an angry bear in its tracks and that ringtone would be a very unexpected sound for a bear,"" explained one. + +Igor suffered from cuts and severe bruises to his face and chest and was rescued when he was found by other fishermen after using the phone to call for help. + +Igor - now recovering from his mauling - explained: ""I had parked my car and was walking towards the spot I'd marked out when there was a tremendous impact on my back and the bear was on top of me."" + +""I couldn't believe my luck when the phone went off and he fled. + +""I know that sort of ringtone isn't to everyone's taste but my granddaughter loaded it onto my phone for a joke,"" he added.","0" +"Justin Bieber Saved A Guy Getting Mauled By A Bear Read more: http://dailycaller.com/2014/08/05/justin-bieber-saved-a-guy-getting-mauled-by-a-bear/#ixzz39YVg3eSm","A 42-year-old Russian fisherman was being mauled by a brown bear when his Justin Bieber “Baby” ringtone saved his life, he believes. + +The Daily Mail reports that Igor Vorozhbitsyn had parked his car and was walking towards his favorite fishing spot when the bear attacked him and began clawing his face and chest, but then his phone rang, playing the annoying crescendo of “baby, baby, baby, baby oooh,” and the bear did what any creature with ears would do when it heard Justin Bieber: it fled. + +“I couldn’t believe my luck when the phone went off and he fled,” he said. + +The man, who sustained cuts and bruises on his face and chest and was taken to the hospital after other fisherman found him, said he firmly believes if his phone hadn’t rang he would have been killed, marking the first time in written history that someone has been thankful for Justin Bieber’s existence.","0" +"Justin Bieber Saved A Guy Getting Mauled By A Bear","A 42-year-old Russian fisherman was being mauled by a brown bear when his Justin Bieber “Baby” ringtone saved his life, he believes. + +The Daily Mail reports that Igor Vorozhbitsyn had parked his car and was walking towards his favorite fishing spot when the bear attacked him and began clawing his face and chest, but then his phone rang, playing the annoying crescendo of “baby, baby, baby, baby oooh,” and the bear did what any creature with ears would do when it heard Justin Bieber: it fled. + +“I couldn’t believe my luck when the phone went off and he fled,” he said. + +The man, who sustained cuts and bruises on his face and chest and was taken to the hospital after other fisherman found him, said he firmly believes if his phone hadn’t rang he would have been killed, marking the first time in written history that someone has been thankful for Justin Bieber’s existence. (RELATED: Justin Bieber Used A Wheelchair At Disneyland So He Could Cut Lines)","0" +"A Justin Bieber Ringtone Just Saved A Man’s Life Who Was Being Attacked By A Bear","Justin Bieber recently saved the life of a 42-year-old Russian man. + +No, the Biebs didn’t do anything heroic. When Igor Vorozhbitsyn was en route to his favorite fishing spot in northern Russia’s Yakutia Republic, he was attacked by a huge brown bear. + +But then, his cell phone rang and the ringtone, “Baby,” scared off the animal. + +As the bear started clawing violently at Vorozhbitsyn, the Biebs’ pre-pubescent vocals made the bear’s ears bleed, and it ran off. + +Wildlife experts believe it was the fact that the ringtone sounding off was so unexpected that it spooked the bear, but it’s more fun to say the bear just really, really, hated that song. + +Vorozhbitsyn suffers from severe bruises on his chest and face and cuts on his neck. Other fishermen found him after he was attacked, and used his phone to call for help. + +Vorozhbitsyn says he knows the ringtone “isn’t to everyone’s taste,” but it was his granddaughter that loaded “Baby” onto his phone “for a joke.” + +I think, however, that’s just code for “I’m honestly just a true Belieber.” + +via Daily Mail","0" +"Man Mauled By Bear Says He's Only Alive Thanks to Justin Bieber","A Russian fisherman says the only thing that prevented a brown bear from killing him was Justin Bieber—specifically, a ringtone of Bieber's first big hit, ""Baby."" + +Igor Vorozhbitsyn, 42, had parked his car and started walking toward the fishing spot he'd marked out for that day when the bear jumped him from behind. + +""There was a tremendous impact on my back and the bear was on top of me,"" he said, according to the Daily Mail. + +The bear mauled Vorozhbitsyn's face and chest, inflicting serious cuts and bruises. He believes it probably would have killed him if his phone hadn't gone off in the nick of time, blaring ""Baby"" loudly enough to drive the bear away. + +After narrowly escaping death, he also escaped a lifetime of being known as a Belieber. + +""I know that sort of ringtone isn't to everyone's taste but my granddaughter loaded it onto my phone for a joke,"" the fisherman said. + +The Mail quotes a bear expert as saying there wasn't anything about Bieber's music in particular that bears find offensive, but ""sometimes a sharp shock can stop an angry bear in its tracks, and that ringtone would be a very unexpected sound for a bear."" + +""What's up, bitch?"" Bieber said, albeit earlier and in a completely non-bear-related context.","0" +"Justin Bieber's 'Baby' Saves Man From Violent Bear Attack","The melodic warbling of Justin Bieber is credited with saving a man's life in Europe. + +Igor Vorozhbitsyn told the Austrian Times he was fishing in northern Russia's Yakutia Republic when a bear attacked him. The man thought he was done for, but when the bear clawed at him, his cellphone went off. The ringtone, Justin Bieber's ""Baby,"" caused the bear to run away. + +Wildlife experts believe the ringtone - according to local media the singer's hit 'Baby' - must have startled the bear into halting its attack. + +""Sometimes a sharp shock can stop an angry bear in its tracks and that ringtone would be a very unexpected sound for a bear,"" explained one. + +Igor suffered from cuts and severe bruises to his face and chest and was rescued when he was found by other fishermen after using the phone to call for help. +The bear's actions are completely understandable. Who among us hasn't ran, screeching in a state of panic from the room when Bieber's ""Baby"" is played? I often use ""Baby"" to scare away annoying door-to-door salesman or pesky types like my landlord with her annoying questions about why I haven't paid my rent or what the smell coming from my apartment is. I hear the Pentagon is currently experimenting with using the song in place of a missile defensive system for the United States. Bieber could save this country billions in national defense. + +Vorozhbitsyn said his granddaughter put the ringtone on his phone as a ""joke."" It's OK, dude. You can admit to being a Belieber. We will not judge you.","0" +"Justin Bieber saves man from bear attack","Even bears can’t stand Justin Bieber’s music. + +A fisherman in Russia was being attacked by a brown bear and escaped death when his Justin Bieber ringtone went off and sent the beast fleeing into the forest. + +Igor Vorozhbitsyn was heading to a local fishing spot in northern Russia’s Yakutia Republic when the Bieber-hating bear suddenly appeared and pounced on him, Central European News reports. + +The 42-year-old was saved when Bieber’s popular hit song “Baby” started playing on his phone. + +“I couldn’t believe my luck when the phone went off and he fled,” Vorozhbitsyn said. + +“I know that sort of ringtone isn’t to everyone’s taste, but my granddaughter loaded it onto my phone for a joke.” + +Wildlife experts said it was the music’s volume that scared the bear away — not the quality of the music. + +“Sometimes a sharp shock can stop an angry bear in its tracks and that ringtone would be a very unexpected sound for a bear,” an expert told Central European News. + +Vorozhbitsyn suffered several cuts and large bruises around his face and chest and is currently recovering from his vicious attack.","0" +"Justin Bieber ringtone saves man being mauled by bear","When faced with the choice of feasting on a fine meal of human while listening to Justin Bieber's music or fleeing to blessed — but hungry — quiet, one bear in Russia decided that silence is indeed golden. + +A report in the Daily Mail details Russian fisherman Igor Vorozhbitsyn's unfortunate encounter with the brown bear, who attacked him from behind as he was walking to his favorite fishing spot in the Yakutia Republic. But as the bear was beginning to inflict serious injury on Vorozhbitsyn, his cellphone rang, and the ringtone of Justin Bieber hit ""Baby"" startled the animal, causing it to beat a hasty retreat. + +""I know that sort of ringtone isn't to everyone's taste but my granddaughter loaded it onto my phone for a joke,"" Vorozhbitsyn said. Nice work, kid — you just saved Grandpa's life with nothing more than a tween anthem.","0" +"Justin Bieber ringtone saved a Russian fisherman during a bear attack","Are you a fan of Justin Bieber’s music? If not, you may want to convert yourself into a “Belieber” because it may save your life one day. + +According to the New York Post , a fisherman in Russia was attacked by a brown bear, but was able to escape death when his Justin Bieber ringtone went off and scared the bear. + +Igor Vorozhbitsyn, 42, was heading toward his favorite fishing spot in Russia’s Yakutia Republic when a bear started clawing at him, according to The Austrian Times . + +The man told the news agency that his granddaughter had downloaded the hit song “Baby” onto his phone as a joke. As funny as the joke may be, it was lifesaving when his phone rang during the attack and Bieber’s melody scared the bear. + +According to the report, the man said the bear halted the attack and fled back into the forest. + +The man said he “couldn’t believe” his luck. + +According to wildlife experts who spoke with The Austrian Times, a “sharp shock can stop an angry bear in its tracks” as the ringtone was a “very unexpected sound for a bear”. + +In a photo of the man, bruises and injuries can be seen on his hands, head and chest. + +Vorozhbitsyn called for help, but was rescued by a fellow fisherman who found him.","0" +"Bieber ringtone scares bear, saves man's life","A Russian fisherman says a Justin Bieber ringtone on his phone scared away a bear that was mauling him near his favorite fishing spot, according to video from Newsy. + +Igor Vorozhbitsyn says a brown bear jumped on him and began mauling him before his mobile phone went on and began playing the Bieber tune Baby. The victim, who had already suffered severe cuts and bruises, said the bear ran off in fear once the tune began playing. + +He was found by other fisherman, who used his phone to call for help, Newsy says. + +Scientists explain that it wasn't necessarily a Bieber tune that scared off the bear off - it could have been any unexpected loud noise. However, the victim felt a need to explain why he had the Bieber song as a ringtone, telling news outlets that his granddaughter uploaded it as a joke.","0" +"A Russian Guy Says His Justin Bieber Ringtone Saved Him From A Bear Attack","A Russian fisherman says that Justin Bieber saved his life…sort of. + +Igor Vorozhbitsyn was on his way to a northern Russia fishing spot when he was suddenly attacked by a bear. + +“I had parked my car and was walking towards the spot I’d marked out when there was a tremendous impact on my back and the bear was on top of me,” Vorozhbitsyn told Central European News. + +But then, with what turned out to be extremely fortuitous timing, the 42-year-old man’s cell phone started ringing. The Justin Bieber song “Baby” started playing, and the bear — who was either frightened by the sound or who perhaps is a Bieber fan himself and wanted to go easy on a fellow Belieber — fled. + +“I couldn’t believe my luck when the phone went off and he fled,” Vorozhbitsyn said. “I know that sort of ringtone isn’t to everyone’s taste, but my granddaughter loaded it onto my phone for a joke.” + +After the bear fled, Vorozhbitsyn called for help and was rescued by fishermen. He is now recovering from the attack, which left him with cuts and bruises around his face and chest. + +cen.at + +cen.at + +Vorozhbitsyn posted these pictures after the attack. + +So remember, the next time you’re trying to fend off a bear attack and this doesn’t work… + +Or this… + +Try this! + +And especially this! + +Thanks for being terrifying to bears, Justin!","0" +"Justin Bieber Saved This Guy From a Bear Attack","Justin Bieber may not have been able to take on Orlando Bloom, but he sure as hell was able to take on a bear. + +No, PETA, Bieber didn’t beat down a bear, he just scared one away in Russia's Yakutia Republic. + +It all went down when 42-year-old fisherman Igor Vorozhbitsyn’s attack by a brown bear was interrupted by a Justin Bieber ringtone. + +The fisherman explains: + +""I had parked my car and was walking towards the spot I'd marked out when there was a tremendous impact on my back and the bear was on top of me."" +That’s when Vorozhbitsyn’s phone went off and “Baby” started blaring, causing the bear to run off. + +He also justified his surprising ringtone: ""I know that sort of ringtone isn't to everyone's taste,” he said, “but my granddaughter loaded it onto my phone for a joke.” + +Living with embarrassment is a small price to pay for your life.","0" +"Finally, proof that Justin Bieber IS unbearable: Russian fisherman saved from bear attack when ringtone featuring one of the pop brat's songs scares it away","var twitterVia = 'MailOnline'; DM.has('shareLinkTop', 'shareLinks', { 'id': '2716479', 'title': 'Fisherman saved from bear attack by Justin Bieber ringtone', 'url': 'http://www.dailymail.co.uk/news/article-2716479/Fisherman-saved-bear-attack-Justin-Bieber-ringtone-went-mauled-scared-bear-away.html', 'eTwitterStatus': ' http://dailym.ai/1oajoHS via @' + twitterVia, 'articleChannelFollowButton': 'MailOnline', 'isChannel': false, 'hideEmail': true, 'placement': 'top', 'anchor': 'tl'}); 9,199 shares 190 View comments","0" +"Man saved from bear attack - thanks to his Justin Bieber ringtone","FISHERMAN Igor Vorozhbitsyn is lucky to be alive - after his Justin Bieber ringtone went off while he was being attacked by a bear. + +Mr Vorozhbitsyn, 42, thought he was a goner when the brown bear pounced on him as he was walking to a favourite fishing spot in northern Russia's Yakutia Republic. + +But as the bear began to claw at him, Mr Vorozhbitsyn's mobile went off and the beast turned tail and fled back into the forest. + +Wildlife experts believe the ringtone - according to local media the singer's hit Baby - must have startled the bear into halting its attack. + +""Sometimes a sharp shock can stop an angry bear in its tracks and that ringtone would be a very unexpected sound for a bear,"" explained one. + +Mr Vorozhbitsyn suffered from cuts and severe bruises to his face and chest and was rescued when he was found by other fishermen after using the phone to call for help. + +Mr Vorozhbitsyn - now recovering from his mauling - said: ""I had parked my car and was walking towards the spot I'd marked out when there was a tremendous impact on my back and the bear was on top of me. + +""I couldn't believe my luck when the phone went off and he fled. + +""I know that sort of ringtone isn't to everyone's taste but my granddaughter loaded it onto my phone for a joke,"" he added.","0" +"Fisherman Saved from Deadly Bear Attack by His Justin Bieber Ringtone","In a story straight out of a Russian folk tale, Igor Vorozhbitsyn was walking to his favorite fishing spot in Northern Russia when a bear leaped out of the woods and pinned him down, swiping and clawing at him. Mauled and bleeding, Vorozhbitsyn thought he was about to die. + +And then Justin Bieber‘s “Baby” started playing on his phone. + +“‘I couldn’t believe my luck when the phone went off and he fled,” Vorozhbitsyn said, according to the Daily Mail. “‘I know that sort of ringtone isn’t to everyone’s taste.” (Okay, this isn’t the most romantic Russian folk tale.) + +According to bear experts, bears are easily scared away by sudden, loud noises, ideally made with air horns, yelling, or, apparently, the tinny screeches emitted by douchebag teenyboppers allegedly “singing.” + +Vorozhbitsyn survived after he used his phone to call for help, and has made a full recovery. As to why a burly, 42-year-old Russian man has “Baby” as his ringtone: “My granddaughter loaded it onto my phone for a joke.” Uh huh. + +[h/t Inquisitr] [Image via Shutterstock] + +– + +>> Follow Tina Nguyen (@Tina_Nguyen) on Twitter","0" +"Justin Bieber scares off GRIZZLY BEAR and saves fisherman from a mauling","Biebs may not be able to take Orlando Bloom in a bare knuckle fight but a grizzly bear poses no such problem to the pint sized pugilist + +Orlando Bloom may be glad to know he is not the only one who can’t stomach Justin Bieber. + +The Lord of the Rings star’s latest ally in his fallout with the pop loudmouth is a wild Russian Bear - who found the singer truly unbearable. + +The beast had pounced on fisherman Igor Vorozhbitsyn and would have certainly have killed him .... until Igor’s phone went off and played Bieber’s hit Baby. So grisly did the mighty grizzly find the ringtone tune that it turned tail and fled back into the forest. + +Recounting his terrifying experience in northern Russia’s Yakutia Republic, badly mauled Igor said: “I was walking to my fishing spot when there was a tremendous impact on my back and the bear was on top of me. I couldn’t believe my luck when the phone went off and he fled. My granddaughter had loaded the ringtone onto my phone for a joke.” + +Wildlife experts believe it must have startled the bear into halting its attack. “That ringtone would be a very unexpected sound for a bear,” said one. + +Perhaps lifesaver Bieber should now dub himself Lord of the Ringtones.","0" +"Justin Bieber Basically Saves A Russian Man From A Bear","Bears might be the #1 threat to America, but what’s the #1 threat to bears? Justin Bieber, apparently. + +Here’s the deal: Russian fisherman Igor Vorozhbitsyn was on his way to his favorite fishing spot in Russia’s Yakutia Republic on August 5 when he was attacked by a brown bear. Just then, the 42-year-old’s ringtone, which was set to Bieber’s “Baby,” started blasting, and the ursine predator fled into the woods. + +“Sometimes a sharp shock can stop an angry bear in its tracks and that ringtone would be a very unexpected sound for a bear,” a wildlife expert told the Austrian Times. + +OK, so the next time I’m attacked by bears, I’ve gotta play some Justin Bieber. But the next time I’m attacked by pirates, I’ve gotta crank that Britney Spears. Got it. + +Thanks to JB’s breakout 2010 single, Vorozhbitsyn survived with only cuts and severe bruises to his face and chest, although I don’t think the ordeal has made him a Belieber. “I know that sort of ringtone isn’t to everyone’s taste but my granddaughter loaded it onto my phone for a joke,” he told the AT. Yep, that story definitely checks out.","0" +"Man saved from bear attack when his Justin Bieber ringtones goes off, sending bear fleeing","A MAN was saved from a vicious bear attack thanks to his Justin Bieber ringtone. + +Russian man Igor Vorozhbitsyn, 41, was walking to his favourite fishing spot when a brown bear attacked him. + +As the bear clawed him, Mr Vorozhbitsyn’ mobile phone went off, setting off his ringtone, Justin Beiber’s ‘Baby’, reports The Austrian Times. + +At the sound of the hit Beiber track, the bear turned and fled back into the forest. + +“I had parked my car and was walking towards the spot I’d marked out when there was a tremendous impact on my back and the bear was on top of me.” + +“I couldn’t believe my luck when the phone went off and he fled.” + +“I know that sort of ringtone isn’t to everyone’s taste but my granddaughter loaded it onto my phone for a joke,” he said. + +Wildlife experts said a sudden noise can frighten animals, even in mid-attack. + +“Sometimes a sharp shock can stop an angry bear in its tracks and that ringtone would be a very unexpected sound for a bear,” a wildlife experts told The Austrian Times. + +After the animal fled Mr Vorozhbitsyn used his phone to call for help. + +He suffered cuts and bruises from the attack and is now recovering.","0" +"Justin Bieber Ringtone Startles Bear","A man fishing in northern Russia was attacked by a bear. But the bear fled when the men's cellphone rang. The ringtone was Bieber's song ""Baby.""","0" +"Justin Bieber ringtone saves Russian fisherman from bear attack","Igor Vorozhbitsyn was going fishing in Yakutia Republic when the bear began to maul him. But Bieber’s ‘Baby’ had been installed as a ringtone on his phone — and caused the bear to stop and flee after he got a call. + +Justin Bieber saved a Russian fisherman from the clutches of a killer bear. + +The deadly beast bolted after hearing the pop brat's smash hit ""Baby"" blasting out of Igor Vorozhbitsyn's cellphone. + +The 42-year-old was walking to his favorite angling spot in the Yakutia Republic when the animal pounced. + +As it clawed his face, the rodman feared he was about to be killed. + +But then his cell phone started to ring and the Bieber tone installed by his granddaughter startled his attacker, who fled back into the forest. + +Vorozhbitsyn, who suffered deep cuts and bruises to his face and chest, then used his cell to call for help. + +""I couldn't believe my luck when the phone went off and he fled,"" he told the Croatian Times. + +""I know that sort of ringtone isn't to everyone's taste but my granddaughter loaded it onto my phone for a joke,"" he added. + +On a mobile device? Click here to watch video.","0" +"Justin Bieber ringtone saves Russian man from bear attack","Justin Bieber at amfAR's 21st Cinema Against AIDS Gala. Photo: Getty + +Justin Bieber’s song has saved a Russian man from being mauled by a bear. + +Fishing in the Yakutia Republic, Russia, Igor Vorozhbitsyn is lucky to be alive after his Justin Bieber ringtone, Baby, scared off a bear that was attacking him. + +""I couldn't believe my luck when the phone went off and he fled,” Vorozhbitsyn told the Croatian Times. + +Vorozhbitsyn, 42, was walking to his angling spot when a bear ambushed him from behind. + +""I had parked my car and was walking towards the spot I'd marked out when there was a tremendous impact on my back and the bear was on top of me,"" he said. + +But as the bear clawed Vorozhbitsyn’s face and back his mobile phone rang, the ringtone selected was Justin Bieber’s hit song Baby. Rightly startled, the bear retreated back into the forest. + +Vorozhbitsyn was able to call for help on his phone and was rescued by fishermen. + +Vorozhbitsyn said he has his granddaughter to thank for his ringtone selection. + +“I know that sort of ringtone isn't to everyone's taste but my granddaughter loaded it onto my phone for a joke,"" he said. + +Wildlife experts believe the ringtone must have startled the bear enough to halt its attack, reports the Croatian Times. + +""Sometimes a sharp shock can stop an angry bear in its tracks and that ringtone would be a very unexpected sound for a bear,"" an expert said. + +Vorozhbitsyn suffered cuts and bruises to his face and chest and is now recovering.","0" +"Unbearable: Man fends off bear attack by playing Justin Bieber song","A Russian man was recently able to fend off a bear attack with a Justin Bieber song. + +Forty-two year old Igor Vorozhbitsyn was recently fishing in Russia's Yakutia Republic when he was attacked by a bear. + +During the ordeal Vorozhbitsyn's phone -- which has Bieber's ""Baby"" as the ringtone -- went off, causing the startled bear to run away. + +While some might argue the pop song has the ability to repel animals, wildlife experts say the bears might not have anything against Justin Bieber, per se. + +The volume of the ringtone is probably what stopped the attack. + +One expert told Central European News that an unexpected noise, like a ringtone, can stop an angry bear in its tracks.","0" +"Justin Bieber ringtone scares bear, saves Russian fisherman","A Russian fisherman was saved from a savage bear attack when his phone ringtone went off and a Jusin Bieber track scared the assailant back into the forest. + +Igor Vorozhbitsyn’s was besieged by a brown bear on the way to his favourite fishing spot in northern Russia’s Yakutia Republic. Luckily he was saved from the near-fatal attack when his phone rang, playing Justin Bieber’s Baby, reported Mail Online. + +Wildlife experts believe that the ringtone must have startled the bear into halting its assault. + +Vorozhbitsyn suffered cuts and bruises to his face and chest, he used the phone to call other fishermen to help him to the hospital. + +“I couldn’t believe my luck when the phone went off and he [the bear] fled. I know that sort of ringtone isn’t to everyone's tastes but my granddaughter put it onto my phone as a joke,” he said. + +The brown bear (Ursus arctos) is the largest land based predator in the world. Adult males can reach up to 635 kgs.","0" +"According to some Russians this dark figure stumbling through the snowy woods is a Yeti - and they even have a footprint. Hmmmmm","This is the moment a group of Russians captured video footage of what they believed was a Yeti walking through the woods. + +The footage shows a 'bear-like' figure covered in hair emerging from an area of snow-covered trees in the south-western Adygeya Republic before disappearing again seconds later. + +A team had set out in search of the mysterious creature after local television reported that it had been sighted in a remote region an hour's drive away from the city of Adygeisk. + +Scroll down for video + +Sighting: A team of Russians believe they have captured footage of the elusive Yeti in a remote patch of woodland + +Footage shows a 'bear-like' figure covered in hair emerging from an area of snow-covered trees in the south-western Adygeya Republic before disappearing again seconds later + +They said they had questioned residents at a mountainside lodge who claimed to have seen it - and on speaking to others in the area managed to secure reports of several independent sightings. + +The group claim they heard the crunching of snow as they headed out to investigate before capturing footage of the creature, which they describe as covered in hair. + +Afterwards, they took a plaster cast of a large footprint they said they found in the snow. + +Eyewitness Ludmila Hristoforova who spoke to local television said: 'The creature was big, looking like a bear, but not a bear. From the door we've seen something big and shaggy.' + +Homeowner Andrei Kazarian said: 'I heard footsteps and we were pretty sure there was no one else around because we knew for sure everyone else was inside the house. + +'Although we didn't see anyone we saw its huge footprints. They were five to six centimetres deep and couldn't come from a human foot. + +The group claim they heard the crunching of snow as they headed out to investigate before capturing footage of the creature, which they describe as covered in hair + +After capturing the creature on camera, the team claim to have taken a plaster cast of its footprint + +The plaster cast and the footage have now been handed to local scientists and will go to the local council by the end of the month + +Big foot? Some have suggested the video was just a stunt to bring in tourists while others are convinced this was the first proof that the yeti exists in the area + +'We took a plaster cast of them and we estimate that it probably would have taken about 200 kilos to press the snow down that much.' + +The plaster cast and the footage have now been handed to local scientists and will go to the local council by the end of the month. + +The footage has already sparked debate with some suggesting it was just a stunt to bring in tourists and others convinced this was the first proof that the yeti exists in the area.","0" +"Bigfoot Strolls Through A Russian Forest -- At Least That's The Claim [VIDEO]","A video has emerged with claims that it shows a large, hairy figure walking swiftly through a snowy, wooded area in Russia. Key details about the incident are missing. But the visuals are remarkable. + +Watch it here: + +According to Mirror online, some Russian adventurers went in search of the elusive Yeti -- that's what many call Bigfoot in Russia -- after reports of creature sightings emerged from a remote region of the southwestern Adygea Republic in the foothills of the Caucasus Mountains. The map below shows Adygea's capital city of Maykop. + +The research team spoke to local residents who said they saw the unusual animal. + +The Daily Mail reports that one eyewitness, Ludmila Hristoforova, told a local television station, ""The creature was big, looking like a bear, but not a bear. From the door we've seen something big and shaggy."" + +Another resident, Andrei Kazaryan (who Mysterious Universe suggests was one of the investigators), said, ""I heard footsteps and we were pretty sure there was no one else around because we knew for sure everyone else was inside the house. Although we didn't see anyone, we saw its huge footprints."" + +The researchers claimed they captured that video footage -- seen above -- of the hairy Yeti. They also made a plaster cast of a large footprint found in the snow. + +Both the video footage and the footprint cast are now reportedly in the hands of local scientists. Oddly, the names have not been revealed of those scientists or of the original researchers who say they took the video. + +This story brings up other dubious questions: + +Why no exact date or time of the alleged video encounter? + +Why is it that, after the ""Yeti"" moves quickly through the snow from right to left, seeming to elude the research group as fast as it can, it suddenly stops its forward motion and casually turns to the right, not appearing to be in a hurry, almost as if it/he was waiting for further cinematic direction from those who were doing the videotaping? + +This story is hot on the heels of two other Bigfoot tales we've reported on so far in January, including one that set off a huge controversy about a reported Skunk Ape photographed in Tampa, Florida. + +There was also the one about how the Arizona Department of Transportation posted an image on its Facebook page, purporting to show ""a family of Sasquatches"" standing in snow next to a highway on Jan. 1. That turned out to be a little joke played on the public by Arizona state transportation officials. + +We have a feeling 2015 hasn't seen the last of Bigfoot. + +@media only screen and (min-width : 500px) {.ethanmobile { display: none; }} + +Like Us On Facebook | Follow Us On Twitter | Contact The Author","0" +"Russian Yeti Or Bigfoot Hoax? New Footage Sparks Debate","New footage of the elusive yeti, captured amid the snowfields of Russia, is sparking renewed debate about the creature’s existence, as some see definitive proof while others claim the video is nothing more than a publicity stunt. + +A group of Russian researchers set out after the yeti, traveling to the south-western Adygeya Republic after local news detailed sightings of the creature, according to the Daily Mail. The yeti had reportedly been spotted just an hour’s drive away from the city of Adygeisk. After arriving in the area, the team interviewed witnesses at a local mountainside lodge who claimed to have seen the yeti. + +“I heard footsteps and we were pretty sure there was no one else around because we knew for sure everyone else was inside the house,” local witness Andrei Kazarian recalled. “Although we didn’t see anyone, we saw its huge footprints. They were 5 to 6 centimeters deep and couldn’t come from a human foot. We took a plaster cast of them and we estimate that it probably would have taken about 200 kilos to press the snow down that much.” + +Eyewitness Ludmila Hristoforova described the yeti as bearlike, though markedly different. + +“The creature was big, looking like a bear, but not a bear. From the door we’ve seen something big and shaggy.” + +The Yeti Exists, And It’s In Russia – http://t.co/n2VoITsJ3M pic.twitter.com/9i0JciJbmB + +— Regardt Stander (@XstremeArt) January 14, 2015 + +Setting out to investigate, the group were stunned to hear crunching snow, before spotting the yeti moving through the trees. As the Mirror reports, they claim to have then captured footage of the yeti, evidence that has since been handed over to local scientists for analysis. + +The yeti video has already proven to be controversial, with some observers claiming that the sighting is nothing more than a stunt designed to bring tourists into the Russian town. Others, however, have asserted that the clip represents genuine proof of the yeti’s existence. + +Watch the shocking new footage that claims to PROVE the existence of the YETI http://t.co/nQXMWXBz5s pic.twitter.com/YNRkabIOzS — Daily Express (@Daily_Express) January 14, 2015 + +Last year, a DNA study conducted by Oxford professor Bryan Sykes failed to identify definitive proof of the yeti from hair samples. As the Inquisitr previously reported, however, Sykes was quick to assert that the study was meant to systematically examine yeti evidence, not pass judgement on its existence. + +Hairy human-like beasts have been reported the world over, most famously in the United States, where the creatures are known as Bigfoot (or Sasquatch). In Russia, they are called either Almas or Yeti, names which may denote two distinct species. + +[Image: EuroPics (CEN) via the Daily Mail]","0" +"Is this proof of bigfoot? New 'yeti' video shows giant hairy beast walking through forest","There has long been speculation about the mythical creature but latest clips could reveal the truth once and for all + +Video loading Watch next Watch this video again Watch Next + +A group of Russians claim to have captured the best footage of bigfoot. + +The adventurers spotted what they described as a hairy bear-sized humanoid that marched out of the woods before disappearing seconds later. + +The recording came when a group of people from the city of Adygeisk set off in search of the mysterious creature after a local TV station reported that it had been sighted in a remote region. + +They said they had questioned the people at a mountainside lodge who claimed to have seen the creature, and managed to get several independent confirmations that there was something out there. + +CEN Conclusive proof: A group claim to have spotted the beast in the woods + +Eyewitness Ludmila Hristoforova who spoke to local TV station said: ""The creature was big, looking like a bear, but not a bear. From the door we’ve seen something big and shaggy."" + +Another homeowner Andrei Kazarian said: ""I heard footsteps and we were pretty sure there was no one else around because we knew for sure everyone else was inside the house. Although we didn't see anyone, we saw its huge footprints. + +7 terrifying mystery beasts that never existed + +""They were 5 to 6 centimetres deep and couldn't come from a human foot. We took a plaster cast of them and we estimate that it probably would have taken about 200 kilos to press the snow down that much."" + +The local team then set off to investigate, and as they headed off into the forest said they were stunned when they heard the crunching of snow, and managed to grab footage of a hairy creature as it emerged from the trees. + +After taking a plaster cast of the alleged footprint, the group have now handed their findings to local scientists for analysis. + +The footage has already attracted a lot of interest with some suggesting it was just a stunt to bring in tourists, and others convinced that this was the first form of conclusive proof that the yeti exists in the area. + +Poll loading …","0" +"Bird defecates on Vladimir Putin during speech (video)","Vladimir Putin spoke at the dedication of a new monument to the First World War in Moscow on Friday. The Russian president said that the lessons of the war, which began a century ago this summer, were that peace is fragile, that military aggression is dangerous and that violence can generate more violence in turn. + +Putin has supported the separatists in Ukraine who apparently shot down a Malaysian airliner last month, killing all 298 people on board. A bird defecated on Putin during his speech, as shown in the footage above. + +European countries have been observing the centenary of the war this weekend, which claimed some 16 million lives, both soldiers and civilians.","0" +"Here's video of a bird pooping on Vladimir Putin in the middle of a speech","Russian President Vladimir Putin was pooped on by a bird while giving a speech unveiling a World War One monument in Moscow on Friday. You can see the freedom bombs land at 0:11 into the above video or you can watch it on repeat, forever, in the gif below. + +The Moscow bird poop incident of 2014 is a small but symbolically satisfying comeuppance for Putin's involvement in Ukraine, where fighting with Russia-backed separatists has killed hundreds of Ukrainians and, two weeks ago, 298 civilians flying overhead in Malaysian Airlines flight 17. Europe and the US have punished Russia with economic sanctions meant to deter further aggression, but on Friday this unknown bird launched some targeted sanctions against the man himself. + +Rn0eaqx + +This being Russia, getting pooped on by a bird wasn't even the most ridiculous part of Putin's WWI speech. Putin warned that the lesson of WWI was — fair warning, irony is going to die forever at the end of this sentence — to avoid excessive ambitions in war. ""Humankind should grasp one truth: violence generates violence,"" said the man whose overt and ongoing support for separatist rebels in Ukraine, which he also invaded to annex Crimea, has helped claim hundreds of lives and stirred up months of crisis. + +""It was on the eve of WWI when Russia did everything possible to solve the conflict peacefully, without bloodshed, between Serbia and Austria-Hungary,"" Putin said, repeating an old Russian complaint that only it really wants peace but is ignored by an aggressive West. ""But Russia wasn't heard. And it had to respond to the challenge in order to protect the [fellow] Slavic nation."" + +I'm not sure whether Putin means this as an explicit nod to his involvement in Ukraine, but Russia's meddling there has often been internally premised on the idea that Russia must save the Russian-speakers in Ukraine's east. So there would seem to be a parallel. More ironically, the Ukrainians who are fighting and dying to keep Putin out of their country are themselves Slavic, but must have forgotten to thank Putin for his peace-seeking, pan-Slavic magnanimity.","0" +"Terrorist Plot Targeting Black Friday Shoppers Uncovered","The Department of Homeland Security has received serious and credible information indicating that an extremist splinter group of Al Qaeda, now going by the name Bhakkar Fatwa, is planning multiple attacks against American consumers as they wait in line for stores to open on November 28th: the day known as Black Friday. + +Bhakkar Fatwa is a small, relatively unknown group of Islamic militants and fanatics that originated in Bhakkar Pakistan as the central leadership of Al Qaeda disintegrated under the pressures of U.S. military operations in Afghanistan and drone strikes conducted around the world. The group has since branched out and begun aggressively recruiting throughout the Middle East, Africa and Europe. Within the last year the group has come under increased scrutiny by both the CIA and the Department of Homeland Security as they have begun actively recruiting on American soil. + +Jeh Johnson, Director of the Department of Homeland Security, has referred to Bhakkar Fatwa as the number one growing problem on the domestic terrorism front in America. Their presence is felt in many mosques and islamic centers across the country: always quietly and out of sight, and previously without any violent operations. Officials at both the CIA and Homeland Security think that may be about to change. + +Jack Phillips, agent in charge of monitoring Bhakkar Fatwa’s American operation detailed the agencies recent findings. “Working with both the CIA and the NSA we were able to access conversations and communications between members of Bhakkar Fatwa’s domestic organization and their leadership in Pakistan which indicate that several attacks are planned against American citizens at retail operations on the 28th of November”, said Phillips. “The instructions sent from Pakistan detailed a broad plan of attacks using both firearms and homemade explosives against large crowds gathered outside of stores waiting for the sales that have become the hallmark of the day. The leadership of Bhakkar Fatwa views the American religion as one worshiping money and possessions. They commanded these attacks as being against the ‘holiest temples’ that the Americans serve.” + +“We have taken several actions based off of this information”, stated Phillips. “We have detained three individuals who were in active communication with Pakistani leadership regarding these planned terror attacks. All three are undergoing interrogation as we speak so that we may hopefully determine the scope and extent of attacks that have been planned. The names of those detained will not be immediately released. They have been deemed enemy combatants and releasing their identities could impact our operational ability at this point. Everything conceivable is being done to unmask and deal with this new threat.” + +“If you are going out shopping early on Friday please keep your eyes open”, Phillips advised. ” At this juncture we are unsure as to how great the threat from these attacks is going to be. We are working as quickly as we can to resolve this situations, but this terrorist group is savvy. They utilize a small closed cell structure, and we may not be able to identify all of them in time. I urge all Americans to strongly consider whether the sales are worth the risk. And if you do go out take particular caution while waiting in line for the store to open. Intelligence points to the time spent waiting outside of the store as the time of greatest vulnerability. I am sure we will resolve this issue, but I still recommend taking adequate precautions.”","0" +"Accused Boston Marathon Bomber Severely Injured In Prison, May Never Walk Or Talk Again","FORT DEVENS, Massachusetts - + +Infamous Boston Marathon bombing suspect Dzhokhar Tsarnaev, 21, was the victim of an “unfortunate accident” yesterday at Ft. Devens Detention Center in Massachusetts, just weeks after his high-profile trial began, according to warden Paul Jacobson. + +Corrections officers reportedly found the alleged terror suspect face down in a pool of his own blood in his cell; a banana peel was found on the floor nearby. + +“It initially appeared as though Tsarnaev slipped on a discarded banana peel and hit the floor with such force that his head bounced off the hard tile surface, probably 16 or 17 times. There was blood everywhere – all over the walls, the floor, even the toilet. The injuries have caused massive brain trauma,” said prison investigator Joe Goldsmith. “We determined though, through expert analysis, that it would be impossible for these injuries to have occurred through a fall. Our investigation has shown that that it was the Aryan Brotherhood who initiated an attack on Tsarnaev.” + +“Yes, it was the brotherhood who took care of that bomber,” said Miles Smith, head of the Aryan Nation inside Devens. “The other gangs, they wanted him, too. We paid the guards the most money to have a shot. They stood aside, and let us do what we do. On the way out, they shook our hands, told us ‘Thank you.’ Well, You’re welcome. You’re welcome, Boston. You’re welcome, America!” + +“Normally, an attack this violent, this cruel, on another inmate would get any offending party more time added to their sentence,” said warden Jacobson. “Because of the nature of Tsarnaev’s crimes, though, we have decided to actually reduce the sentences of the Aryan members who were involved. They have done our prison and our country a great service, and we appreciate it immensely. They are heroes in the eyes of not only this institution, but also in the eyes of the people of the Commonwealth of Massachusetts.” + +Dzhokhar Tsarnaev and his older brother Tamerlan Tsarnaev were both suspected of perpetrating the Boston Marathon bombings on April 15, 2013. The bombings killed three people and reportedly injured as many as 264 others. Shortly after the FBI named the two suspects and released images of them, the two brothers reportedly killed an MIT police officer and carjacked an SUV in a shootout with police. During the shootout, the elder brother, Tamerlan was captured but was killed when his brother drove over him with the SUV. On the evening of April 20, 2013, the wounded Dzhokhar was found unarmed and hiding in a boat on a trailer in Watertown, Massachusetts. + +On January 30, 2014, United States Attorney General Eric Holder announced that the federal government would seek the death penalty against Tsarnaev. The trial had just begun on January 5, 2015, as Tsarnaev pleaded not guilty to all thirty charges filed against him.","0" +"Source: Tom Brokaw Wants Brian Williams Fired","According to the New York Post's Page Six, an NBC source says that Tom Brokaw wants Brian Williams' ""head on a platter"" after the anchor recanted his story about taking incoming fire in Iraq on Wednesday. + +""He is making a lot of noise at NBC that a lesser journalist or producer would have been immediately fired or suspended for a false report,"" said the source. + +The Post reports that Williams' fabrication was long-known at NBC, but at least one employee thinks the Nightly News anchor is unlikely to be punished. + +""He is not going to be suspended or reprimanded in any way,"" a network source told the paper. ""He has the full support of NBC News."" + +[Image via AP Images]","0" +"Tom Brokaw 'wants Brian Williams out': NBC legend 'furious' at Iraq war lie, as it's claimed executives warned anchor to stop exaggerating the story in the past","As a series of ex-soldiers come forward to criticize Brian Williams for his ‘stolen valor’ Iraq war story, it is being reported that top level executives at NBC News had known the tale was fake and had been begging the newscaster for years to stop repeating it. + +Williams is at a center of a media firestorm after he was found out for embellishing an old war story about being in a helicopter hit by a grenade during the Iraq war in 2003. + +The newscaster acted swiftly on Wednesday night to attempt to diffuse the situation by apologizing during his Nightly News show, but since then a series of ex-soldiers have come forward to criticize Williams ‘half-hearted’ apology. + +Brian Williams is at the center of a media firestorm over his embellished war story and now it transpires that NBC News executives - and Tom Brokaw - had known for years that the story was false + +To make matters worse there are also now reports that senior executives at NBC News, including legendary anchor Tom Brokaw who Williams replaced in 2004, knew the story was false. + +‘Tom Brokaw and [former NBC News President] Steve Capus knew this was a false story for a long time and have been extremely uncomfortable with it,’ an insider told the New York Post. + +Now Brokaw, 74, has had it and wants Williams fired, the Post claims. + +Senior executives had in the past asked Williams to stop telling the story in public, reports Variety. + +Despite his credibility being called into question, Williams still took the anchor’s seat for his Nightly News broadcast on Thursday evening but unlike on Wednesday he didn't address the issue during the broadcast. + +'Brokaw wants Williams’ head on a platter. He is making a lot of noise at NBC that a lesser journalist or producer would have been immediately fired or suspended for a false report,' said the source. + +Retraction: NBC anchor Brian Williams has been forced to admit that he wasn't aboard a helicopter hit and forced down by enemy fire during the 2003 invasion of Iraq, as he claimed in a broadcast on Friday, pictured + +However a separate source says that isn't going to happen. 'He is not going to be suspended or reprimanded in any way. He has the full support of NBC News,' said the source. + +On Thursday the pilot of the army chinook that was attacked by rocket-propelled grenades told the Omaha World-Herald that he had contacted NBC News not long after their initial broadcast. Don Helus said he saw Williams’ initial report not long after its original broadcast after someone emailed him a clip. + +NBC’s Tom Brokaw introduced the report with the words: 'Our colleague Brian Williams is back in Kuwait City tonight after a close call in the skies over Iraq.' + +Helus said he contacted Williams’ producer and asked for a retraction, but didn't get a reply. + +'My crew was a little upset about that - somebody trying to make a claim to inflate their career,' Helus said. + +Williams was forced to apologize on air and on Facebook on Wednesday and admit that he wasn't aboard a helicopter that was hit, but had been traveling in a separate aircraft more than half an hour behind that landed without incident. + +'He was actually on my aircraft and we came in behind [the other helicopter] about 30-45 minutes later,' Sgt. 1st Class Joseph Miller, the flight engineer on the helicopter that carried the journalists, wrote on Facebook after NBC shared a link to Williams' story. + +Williams pictured in Iraq in 2003 with Command Sgt. Major Tim Terpack: In a lengthy Facebook post on Wednesday, Williams admitted his mistake and blamed the 'fog of memory over 12 years' for his error + +'He had the audacity to tell me the whole thing was like 'Saving Private Ryan' and that the whole army would be out looking for him. I called him an idiot in front of his camera crew and he didn't come back to my bird for the next three days.' + +Pate Butler, another soldier, confirmed on Facebook: 'He flew with the Savannah birds in a totally different flight. Never was shot at. That aircraft was out of Germany and we were all in that flight.' + +Lance Reynolds, another soldier who had actually been on the 159th Aviation Regiment's Chinook that was hit, also lashed out at Williams on Facebook. + +'Sorry dude, I don't remember you being on my aircraft,' he wrote. 'I do remember you walking up about an hour after we had landed to ask me what had happened. + +'Then I remember you guys taking back off in a different flight of Chinooks from another unit and heading to Kuwait to report your 'war story' to the Nightly News. + +'The whole time we were still stuck in Iraq trying to repair the aircraft and pulling our own Security.' + +Speaking to Stars and Stripes, Reynolds recalled how he had been aboard the helicopter when it was hit by two rocket-propelled grenades and small arms fire. + +The damaged Chinook made a rolling landing at an Iraqi airfield, skidded off the runway and came to a stop in the desert. Reynolds and other crew members were unhurt. + +Called out: Lance Reynolds, left, and Pate Butler, right, who were both part of the crews flying that day, said that Williams had not been aboard their damaged helicopter and expressed their anger at his lies + +Anger: The day after Williams' report, Reynolds responded to the story on NBC NIghtly News' Facebook and said that he remembered things rather differently + +Another man, Joseph Miller, who claimed to be on Williams' aircraft at the time said he had been 'calling him out on this for a long time with no response' + +'It was something personal for us that was kind of life-changing for me,' he told Stars and Stripes. + +'I know how lucky I was to survive it. It felt like a personal experience that someone else wanted to participate in and didn't deserve to participate in.' + +When Williams approached him and took photos of the damaged aircraft, Reynolds said he dismissed the level of danger because he didn't want his wife to see a news report about it. + +'I wanted to tell her myself everything was all right before she got news of this happening,' he said. + +Another man on the downed aircraft, Mike O'Keeffe, said he had long been bothered by Williams' false claims. + +'Over the years it faded,' he said, 'and then to see it last week it was - I can't believe he is still telling this false narrative.' + +O'Keeffe added that he was satisfied with Williams' apology and didn't want to push the issue any further or 'kick the guy when he is down'. + +Other soldiers have accused Williams of being misleading in his apology and continuing to imply details that are false. + +Denial: Williams denied that he was 'trying to steal anyone's valor' in a message he posted on Wednesday + +Since the 2003 incident, Williams' Chinook story has been recounted countless times and gradually the reporter's role seems to have grown. + +NBC reported the incident on March 26, 2003, with the headline, 'Target Iraq: Helicopter NBC's Brian Williams Was Riding In Comes Under Fire.' + +However when the incident was reported the next day by the New York Daily News it stated that a 'chopper was hit and forced to land. Then the one carrying Williams landed.' + +Three days later USA Today carried a similar report that stated: 'NBC's Brian Williams was stranded in the Iraqi desert for three days after a Chinook helicopter ahead of his was attacked by a man who fired a rocket-propelled grenade. + +'The grenade just missed, but it forced the group to make an emergency landing. Luckily, a U.S. tank platoon was there and surrounded the helicopters, killing four Iraqis.' + +In a 2007 entry from his blog Williams recounts how he was part of a 'flotilla of four twin-rotor Chinook helicopters'. + +'Some men on the ground fired an RPG through the tail rotor of the chopper flying in front of ours. + +'There was small arms fire. … All four choppers dropped their heavy loads and landed quickly and hard on the desert floor,' he recalled. + +By the next year Williams was claiming on his blog that 'all four of our low-flying Chinooks took fire.' + +'The Chinook helicopter flying in front of ours (from the 101st Airborne) took an RPG to the rear rotor, as all four of our low-flying Chinooks took fire,' he wrote. + +'We were forced down and stayed down -- for the better (or worse) part of 3 days and 2 nights.' + +The tale takes a more dramatic twist during a 2013 appearance on The Late Show With David Letterman. By now Williams is recalling that two helicopter were hit - including his. + +'Two of our four helicopters were hit by ground fire including the one I was in,' he told Letterman. + +Then during his report on January 30, Williams once again told an inaccurate version of events so that now 'the helicopter we were travelling in was forced down after being hit by an RPG.' + +For example, army flight crews told Stars and Stripes that Williams implied he was flying with the same company that the downed helicopter belonged to - but he was actually flying with a different company in a different direction, and only linked to the unit by radio. + +He also suggested that his aircraft was forced to land because of the attack, but soldiers said it was landed due to deteriorating weather conditions. + +After Williams' apology, there were cries for him to be terminated. + +'Brian Williams has to go,' Brent Bozell, the founder and president of the Media Research Center, wrote on Twitter. 'NBC's credibility is completely shot.' + +The Nightly News anchor has often repeated the war story over the past 12 years about how the aircraft he was on was forced down by enemy fire. + +He repeated his old war story on Friday when he presented a segment about a public tribute at a hockey game in New York for Command Sgt. Major Tim Terpack, a retired soldier who had provided security for the grounded helicopters. + +During the report, Williams went further and said that the aircraft he was on had actually been hit - and the soldiers expressed their anger on Facebook afterwards. + +'I would not have chosen to make this mistake,' Williams told Stars and Stripes. 'I don't know what screwed up in my mind that caused me to conflate one aircraft with another.' + +On the Nightly News broadcast on Wednesday evening, Williams told viewers that his mistake was a 'bungled attempt' to honor a soldier who had helped protect him. + +'I made a mistake in recalling the events of 12 years ago. I want to apologize,' he said. + +In a lengthy Facebook post on Wednesday Williams admitted his mistake and blamed the 'fog of memory over 12 years' for his error. + +'I feel terrible about making this mistake, especially since I found my OWN WRITING about the incident from back in '08, and I was indeed on the Chinook behind the bird that took the RPG in the tail housing just above the ramp,' he wrote. + +'Because I have no desire to fictionalize my experience (we all saw it happened the first time) and no need to dramatize events as they actually happened, I think the constant viewing of the video showing us inspecting the impact area - and the fog of memory over 12 years - made me conflate the two, and I apologize.' + +Williams went on to strenuously deny that he was 'trying to steal anyone's valor'. + +'I was and remain a civilian journalist covering the stories of those who volunteered for duty. This was simply an attempt to thank Tim, our military and Veterans everywhere -- those who have served while I did not.' + +All the credit: After his apology, Twitter users joked about Williams inserting himself in other historic events + +One of the top trending topics on Twitter on Wednesday night was #BrianWilliamsMisremembers. + +'#BrianWilliamsMisremembers and then I said look Woodward you and Bernstein are in way over your head,time to follow a real man..lets do this,' tweeted one person. + +'And I just knew we could make a better portable music player. Called it the iPod.' #BrianWilliamsMisremembers,' wrote another. + +Since the 2003 incident, Williams' Chinook story has been recounted countless times and gradually the reporter's role seems to have grown. + +NBC reported the incident on March 26, 2003, with the headline, 'Target Iraq: Helicopter NBC's Brian Williams Was Riding In Comes Under Fire.' + +However when the incident was reported the next day by the New York Daily News it stated that a 'chopper was hit and forced to land. Then the one carrying Williams landed.' + +Original report: In 2003, Williams reported that another helicopter had been shot at - not the one he was on + +Damage: The original report shows the damage suffered by the Chinook after it was shot at in 2003 + +Three days later USA Today carried a similar report that stated: 'NBC's Brian Williams was stranded in the Iraqi desert for three days after a Chinook helicopter ahead of his was attacked by a man who fired a rocket-propelled grenade. + +'The grenade just missed, but it forced the group to make an emergency landing. Luckily, a U.S. tank platoon was there and surrounded the helicopters, killing four Iraqis.' + +In a 2007 entry from his blog Williams recounts how he was part of a 'flotilla of four twin-rotor Chinook helicopters'. + +'Some men on the ground fired an RPG through the tail rotor of the chopper flying in front of ours. + +'There was small arms fire. … All four choppers dropped their heavy loads and landed quickly and hard on the desert floor,' he recalled. + +By the next year Williams was claiming on his blog that 'all four of our low-flying Chinooks took fire.' + +'The Chinook helicopter flying in front of ours (from the 101st Airborne) took an RPG to the rear rotor, as all four of our low-flying Chinooks took fire,' he wrote. + +Williams appeared nonplussed about the scandal on Wednesday evening as he enjoyed a New York Rangers game with his good friend Tom Hanks + +Actor Tom Hanks and Brian Williams pictured together at the Boston Bruins game at Madison Square Garden + +The two shared plenty of laughs and thrills at the game only hours after Williams apologized for his 'mistake' + +'We were forced down and stayed down -- for the better (or worse) part of 3 days and 2 nights.' + +The tale takes a more dramatic twist during a 2013 appearance on The Late Show With David Letterman. By now Williams is recalling that two helicopter were hit - including his. + +'Two of our four helicopters were hit by ground fire including the one I was in,' he told Letterman. + +Then during his report on January 30, Williams once again told an inaccurate version of events so that now 'the helicopter we were travelling in was forced down after being hit by an RPG.' + +Williams has anchored NBC Nightly News - the nation's highest rated news program - since December 2004 when he replaced Tom Brokaw. + +His reporting from inside the New Orleans Superdome in the immediate aftermath of Hurricane Katrina the next year helped earn NBC a Peabody Award. + +DailyMail.com has reached out to NBC News for comment.","0" +"Tom Brokaw Wants Brian Williams Fired Over Iraq Helicopter Story: Report","Famed NBC journalist Tom Brokaw thinks that Nightly News anchor Brian Williams should be fired, according to a report from the New York Post's Page Six, which cited NBC insiders. Brokaw's ire was prompted by Williams' admission that a story he has often repeated about being in a helicopter, which was shot down during the 2003 Iraq war, was untrue. + +“Brokaw wants Williams’ head on a platter,” the source told the paper. “He is making a lot of noise at NBC that a lesser journalist or producer would have been immediately fired or suspended for a false report.” + +The source also said that both Brokaw and former NBC News President Steve Capus were aware that the story was untrue ""for a long time and have been extremely uncomfortable with it."" + +Williams had repeatedly claimed that he had been traveling on a U.S. military helicopter that was downed by RPG fire during the 2003 invasion of Iraq, most recently on a Jan. 30 broadcast. He also told the story during an appearance on David Letterman's show. + +NBC shared a clip of Williams recounting the story on Facebook, “Sorry dude, I don't remember you being on my aircraft. I do remember you walking up about an hour after we had landed to ask me what had happened,” Lance Reynolds, the flight engineer for the helicopter that was struck, wrote in response, prompting Williams' on-air apology Thursday. + +Speculation has been rife about whether Williams will, or should, lose his job or face some kind of sanction for the misrepresentation. Williams argued that it did not represent dishonesty, saying rather that he “made a mistake in recalling the events of 12 years ago.” + +Thus far, NBC News has made no official statement about the incident, and has announced no investigations or possible disciplinary measures, suggesting that the company is supporting the anchor, and hopes to ride out the wave of criticism he is currently attracting, the Washington Post reported. + +“You could say it’s business as usual,” an anonymous NBC executive told the paper. “He has the whole support of NBC.” + +In addition to the apparent support of NBC, Williams also has the support of his esteemed colleague Dan Rather, who defended Williams Thursday. + +""I don't know the particulars about that day in Iraq. I do know Brian,"" Rather said in a statement provided to The Huffington Post. ""He's a longtime friend and we have been in a number of war zones and on the same battlefields, competing but together. Brian is an honest, decent man, an excellent reporter and anchor -- and a brave one. I can attest that -- like his predecessor Tom Brokaw -- he is a superb pro, and a gutsy one.""","0" +"Report: Tom Brokaw Wants Brian Williams Fired","Former “NBC Nightly News” anchor Tom Brokaw wants his replacement Brian Williams fired, the New York Post’s Page Six reported Thursday night, citing sources. + +“Brokaw wants Williams’ head on a platter,” an NBC source told Page Six. “He is making a lot of noise at NBC that a lesser journalist or producer would have been immediately fired or suspended for a false report.” + +ournalist Brian Williams speaks on stage at The New York Comedy Festival and The Bob Woodruff Foundation present the 8th Annual Stand Up For Heroes Event at The Theater at Madison Square Garden on November 5, 2014 in New York City. (Monica Schipper/Getty Images for New York Comedy Festival) + +Williams, on Wednesday, recanted a 2003 war story in which he claimed that he was aboard a helicopter in Iraq that was forced down because of RPG fire. The story, which had been repeated throughout the years, had been recently challenged on social media. + +An NBC source told Page Six that Brokaw and former NBC News president Steve Capus “knew this was a false story for a long time and have been extremely uncomfortable with it.” + +Nevertheless, a network source told the newspaper that the network is firmly behind Williams. + +“He is not going to be suspended or reprimanded in any way. He has the full support of NBC News,” a network source told Page Six. + +— + +Follow Oliver Darcy (@oliverdarcy) on Twitter","0" +"DNA Results Confirm Michael Jackson Is Biological Father Of Bruno Mars","NEW YORK, New York - + +Vladimir Kershov, publicist of R&B singer Bruno Mars, has been fired today after he revealed a shocking secret regarding the pop and R&B singer. Kershov leaked private information that revealed that Michael Jackson is Mars’ biological father. + +In a statement emailed to news and media outlets across the world, Kershov revealed that he was told by the singer that DNA testing had proven that Jackson, known across the world as the King of Pop, was without a doubt his biological father. After pleading with Mars, born under the name Peter Hernandez, to go public with the revelation, Mars refused to do so. Kershov insisted that it be made known to the public, and that the news would catapult the singer’s fame and boost record sales. Mars remained adamant that the information not be released. According to Kershov, he then took it upon himself and emailed the shocking news to media sources all over the world. + +“DNA testing has proven that Michael Jackson is the biological father of Bruno Mars,” Kershov said in the statement. “Against his wishes, I have decided to relay this message for the greater good and betterment of Bruno’s life and extravagant music career.” + +In a statement released by Mars’ new publicist, Jacqueline Pryor, it has been announced that Kershov was immediately fired by the singer, and may seek legal action against his former publicist. “The job of a publicist is indeed to better the career of their clients by persuading them to take part in things that cause their popularity to grow, however, the client must trust their publicist. The artist has the final say, no matter what.” + +When asked about the validity of Kershov’s statement, Pryor surprisingly made it clear that the information is accurate. “It is true. Doesn’t mean he was right in saying so, but it is true. When it comes to 29-year-old Bruno Mars, Michael Jackson is the father!”","0" +"Someone painted a graffiti dick on a $2.5 million car","Some might say that no matter how rich you are, spending $2.5 million on a car makes you a total dick. + +Apparently a vandal in Seattle sought to communicate this message quite literally, branding a Bugatti Veyron 16.4 Grand Sport—the world’s most expensive production car—with a graffiti penis while it was parked on the street. + +The car boasts 1,200 horse power, tops out at 252.97 miles per hour, and was named car of the decade in 2010 by BBC show “Top Gear.” + +If you can afford one of these, you can probably afford a new paint job. Still, guy must be pissed. +grafitti penis 2 million car Someone painted a graffiti dick on a $2.5 million car + +images: Metro","0" +"Penis Drawn On Bugatti Veyron Could Be World's Most Expensive Car Vandalism","To be fair, if you've spent £1.5 million on a Bugatti Veyron you probably should put a bit of thought into where you leave it. + +But that's still no excuse for this... + +Yup, a big old cock and balls was apparently spray-painted on the bonnet of one of the 1200hp supercars in Seattle. + +Reaction has been mixed to say the least. + +Some were filled with praise. + +vandal painted a brilliantly simple penis on a $2 Million Bugatti Veyron pic.twitter.com/oKrCZRt5u0 (via @digg) + +— Stef Stivala (@stefstivala) October 9, 2014 + +More of this kind of thing please http://t.co/j4mQhispYe + +— Toby Amies (@TobyAmies) October 8, 2014 + +Others horrified. + +You've taken it too far this time @Phishtitz http://t.co/entLDNIcJg pic.twitter.com/wN5I3iMN0w + +— Adam Morland (@adammorland) October 8, 2014 + +best believe if someone spray painted a penis on my 2.4 million dollar bugatti veyron BITCHES WOULD GET SWUNG ON QUICK AF JUST KNOW + +— Haley. (@haleythoe) October 8, 2014 + +Accusations abounded. + +Clarkson again? http://t.co/4DZT7oTuHY via @MetroUK + +— Emmarse (@Ganninforrit) October 8, 2014 + +While others thought it was part of a bigger plan. + +Humble beginnings for a war on the rich. http://t.co/9fxsgJx4Iy + +— Michael J Dolan (@MichaelJDolan) October 8, 2014 + +Although this is probably pushing it a bit far... + +Whoever Spray-Painted A Penis On This $2.5 Million Bugatti Veyron Should Be Charged With Treason --- http://t.co/5x4gAgpu7B + +— BroBible (@BroBible) October 8, 2014","0" +"Cheeky vandals paint giant penis on bonnet of £1.5 million Bugatti Veyron sportscar","Twitter users are suggesting the phallic daubing could have been the handiwork of a jilted lover or jealous rival + +The owner of a £1.5 million Bugatti Veyron supercar could be left with a £500,000 dent in their pocket after crude vandals painted a huge penis on its bonnet. + +Yobs targeted the silver-coloured car which was parked in a street in Seattle, US. + +The Bugatti Veyron 16.4 Grand Sport is the world’s most expensive production car and is capable of going from 0 to 60mph in just 2.6 seconds. + +But its flashy owner will be reeling, as the graffiti is set to slash a whopping half a million pounds off the racing car's retail value. + +The image was posted on Reddit this week, with some users condemning the graffiti artists for vandalism and other suggesting it was the handiwork of a jilted lover. + +One Twitter user even suggested it could be a sign of activism by the culprit. + +The spray can artist who drew a penis on a Bugatti Veyron - activist or vandal? Shame to damage a great car, but accurate comment on owner?— Trefor Patten (@treftwit) October 9, 2014 + +A spoof account for Iron Man Tony Stark also claimed to be the owner, tweeting: ""Yes they were in good condition, besides the fact there was a penis on my Bugatti Veyron..."" + +Yes they were in good condition, besides the fact there was a penis on my Bugatti Veyron...— Tony Stark (@TonyStarkTweets) October 6, 2014 + +Poll loading …","0" +"The famous “Dog whisperer” Cesar Millan died of a heart attack this morning.","The 45 year old Mexican/American, born in De la Cruz, Sinaloa, who made a name for himself with his incredible rehabilitation and training technics wit dogs, duty in which he professionally wrote three books on the topic “Cesar’s way” “Be the pack leader” and “Member of the family”, he reach worldwide popularity with his TV series “The dog Whisperer”, this name would be the new way people knew him, he died this morning in Santa Clarita hospital in California. + +Millan was hospitalize yesterday afternoon, the medical reports indicate that he suffered a fulminate heart attack, which paralyze his heart unavailable for the blood to reach his brain, and other vital organs, situation witch cause the death of this humanitarian man, who years before open his foundation “Cesar Millan Foundation”, where Jada Pinkett Smith, wife of Will Smith, is Vice-president. + + + +The sad news of Millan’s death was given by his wife Jahira Dar in a news conference, a couple of hours ago, where se said to the media, “I hope you can understand my lost, and I would appreciate if you can give us our space for our mourning”. + +Until now, it’s uncertain de details of the funeral, never the less, the body of Cesar Millan is expected to be shipped back to Mazatlan, Sinaloa. He will be buried next to his grandfather, who planted in him the love for animal, especially dogs. + +Definitely it’s a big lost, for ever more, rest in peace Cesar Millan…","0" +"Chinese State Media Warns People To Stop Calling Themselves Dumbledore","This week CCTV News, the state-run broadcaster, came up with these tips for any Chinese people considering an English name – one of which is to steer clear of “Dumbledore”. +This week CCTV News, the state-run broadcaster, came up with these tips for any Chinese people considering an English name – one of which is to steer clear of ""Dumbledore"". +Warner Bros. Entertainment +It’s common for Chinese people to choose an English name, partly to make conversation with non-Chinese speakers easier. Many Chinese students in western colleges go by an English name, for example. +But as CCTV points out, some people are choosing names that might sound odd to English speakers. +The article says: “While native English speakers are stuck with whatever happy or unhappy names they’ve been given, Chinese and other ‘non-natives’ get the lucky choice of picking their own English name. +“However these choices can mean more than you think!” +Religious, mythical, and fictional characters such as Vampire, Satan, Medusa, and Edward Cullen are a no-no. +Religious, mythical, and fictional characters such as Vampire, Satan, Medusa, and Edward Cullen are a no-no. +Getty Images/iStockphoto Hlib Shabashnyi +“Unique names like these aren’t just very amusing to English speakers, it also suggests you have some connection to that name,” the article warns. +“So if you call yourself Satan, you might get a few foreigners thinking you’re anti-Christian, or possibly a member of a heavy metal band.” +CCTV says Harry is OK, if you’re a Harry Potter fan, but only because it was a common name to start with. +Also on the “no” list are common everyday words that aren’t used as names in English, such as Lawyer. +Also on the ""no"" list are common everyday words that aren't used as names in English, such as Lawyer. +Getty Images/iStockphoto IuriiSokolov +Other examples include Surprise, Dragon, and Fish – things that might be related to the characters in someone’s Chinese name. +“Sure, have fun and pick a random object or word as a name, but avoid them if you want a call back from that serious law firm in America.” CCTV says. +CCTV closes the article with this advice for anyone thinking of an English name: + +A good way to work out the ‘feeling’ of a name is to watch a bunch of American movies and sitcoms. They’re full of name stereotypes – you’ll find the good girls’ are all ‘Janes’, the jock boys are still ‘Buds’ and the geeks are called ‘Sheldon’.","0" +"Tips for Chinese choosing an English name","您所访问的资源已不存在。 +查看更多请返回网站主页。 +» cctvnews.cn","0" +"Chinese advised to choose British-sounding names to get ahead","Chinese people have been given state advice on the adoption of English sounding names – being urged to avoid those that make them sound like a “stripper” and instead opt for ones that imply the bearer is from “a fancy or conservative family”. + +A report published on the website of CCTV, a state broadcaster, offered readers practical advice on the selection of their Western-style name, a rite of passage for most young Chinese. + +“Take heed,” the article said. “English names come with different connotations…A name can come with a 'feeling’ or idea about what sort of person you are.” + +Names “with a distinct feeling of Britishness” such as Elizabeth, William and Catherine were considered as “safe” by the article, which was illustrated with a picture of the Royal family. + +But other, less desirable name types were also listed, such as those derived from “suggestive” foods such as Candy, Lolly and Sugar which were “typically thought of as 'non-smart girl’ names, or 'stripper’ names.” + +Picking the distinctive name of a world leader of celebrity such as Obama or Madonna, or that of a religious figure (“Satan”), was not advised. + +In a discussion about the article on Observer, a news portal, one user suggested that the tradition could be short-lived. “Why get an English name?” Xiao Weixia wrote. “Just wait, everyone will get a Chinese name in the future.”","0" +"The Chinese Guide to Avoiding a Bad English Name","Years ago, I had a job in China where I evaluated the spoken English of college students. One bright young woman introduced herself to me with her Chinese name. Then she added: ""You can call me 'Easy.' That's my English name."" + +I paused, thought for a moment, and then decided to say something. ""You might want to consider changing your name,"" I said, explaining—as delicately as possible—that ""easy"" was an unfortunate name for a woman. Mortified, she thanked me for the tip. ""I'm going to go and change my name now,"" she said. + +People in China have adopted English names for decades. Many choose ones that resemble their birth names: Chinese boys named ""Da Wei,"" a common name, almost invariably become ""David."" Others find inspiration from singers, athletes, politicians, or movie stars. In my first year in China, I taught five different boys called ""Tom Hanks,"" thanks in part to Castaway's success. + +Most of the ""English"" names I encountered were conventional, though others—like the aforementioned ""Easy""—were less than appropriate. (I also taught a boy named ""Fish"" who, perhaps inspired by a certain musical artist, preferred to render his name by drawing it.) + +Sweets-inspired names are ""typically thought of as ‘non-smart girl’ names, or ‘stripper’ names."" +CCTV, China's state-run broadcaster, wants to solve this problem. In an article published by its English-language channel, the network laid out a series of guidelines for how not to name yourself. For example, avoid naming yourself after a food item (""Candy""), a famous person (""Obama""), or a very old person (""Gertrude""). If you name yourself ""Satan,"" says CCTV, people might think you're anti-Christian, or worse, a ""member of a heavy metal band."" Proper and traditional names, like ""Michael,"" ""William,"" and ""Elizabeth,"" on the other hand, imply you're from a fancy and conservative family. Sweets-inspired names are ""typically thought of as ‘non-smart girl’ names, or ‘stripper’ names."" + +One wonders if certain American celebrities might not also benefit from these guidelines. For instance, here's what CCTV has to say about using food as a name: + +""Food is very hit or miss. And usually miss. One of the issues here is that food names can be 'very' suggestive."" + +Gwyneth Paltrow, take note.","0" +"Comcast blocks Tor","""Users who try to use anonymity, or cover themselves up on the internet, are usually doing things that aren’t so-to-speak legal; we have the right to terminate, fine, or suspend your account at anytime due to you violating the rules -- Do you have any other questions? Thank you for contacting Comcast."" + +That's from a Comcast customer, who says it's a transcript of a conversation s/he had with a Comcast rep after noticing that Tor, an online privacy- and anonymity-enhancing tool loathed by the NSA, was blocked on her/his Internet connection. + +Comcast Declares War on Tor? [Nathan Wold/Deep Dot Web] (Thanks, Alan!)","0" +"Comcast Declares War on Tor?","If you needed another reason to hate Comcast, the most hated company in America, they’ve just given it to you: they’ve declared war on Tor Browser. +Reports have surfaced (Via /r/darknetmarkets and another one submitted to us) that Comcast agents have contacted customers using Tor and instructed them to stop using the browser or risk termination of service. A Comcast agent named Jeremy allegedly called Tor an “illegal service.” The Comcast agent told its customer that such activity is against usage policies. +The Comcast agent then repeatedly asked the customer to tell him what sites he was accessing on the Tor browser. The customer refused to answer. +The next day the customer called Comcast and spoke to another agent named Kelly who reiterated that Comcast does not want its customers using Tor. The Comcast agent then allegedly told the customer: +Users who try to use anonymity, or cover themselves up on the internet, are usually doing things that aren’t so-to-speak legal. We have the right to terminate, fine, or suspend your account at anytime due to you violating the rules. Do you have any other questions? Thank you for contacting Comcast, have a great day. +How did Comcast know its customers were using Tor in the first place? Because Tor Browser provides online anonymity to its users, This would mean that Comcast is monitoring the online activities of its users, to (among other things) check if they are following their Acceptable Use Policy. +Comcast has previously been listed by the Tor project as a Bad ISP. The users of the Tor project listed Comcast as a bad ISP that is not friendly to Tor. The Tor project cited Comcast’s Acceptable Use Policy for its residential customers which claims to not allow servers or proxies under “technical restrictions.”: +use or run dedicated, stand-alone equipment or servers from the Premises that provide network content or any other services to anyone outside of your Premises local area network (“PremisesLAN”), also commonly referred to as public services or servers. Examples of prohibited equipment and servers include, but are not limited to, email, web hosting, file sharing, and proxy services and servers; +A Comcast spokesperson told DeepDotWeb that: +We respect customer privacy and security and would only investigate the specifics of a customer’s account with a valid court order. And if we’re asked by a court to provide customer information, then we ask for a reasonable amount of time to notify the customer so they can decide if they would like to hire a lawyer and if they do, then we turn the case over to them and they proceed with the judge directly and we step away. +However, this statement appears to be at odds with Comcast’s treatment of Ross Ulbricht, alleged Dread Pirate Roberts. +Comcast previously corroborated with the FBI by providing information on alleged Silk Road mastermind Ross Ulbricht’s internet usage. Ulbricht’s legal defense without a warrant. Ulbricht was most certainly never given a warning by Comcast or given time to contact a lawyer before he was arrested in a San Francisco library last October. +Comcast already monitors its customers internet usage to prevent them from downloading pirated media in violation of copyright laws. Under the “Six Strikes” plan, Comcast customers who are caught by Comcast pirating copy-written material are emailed by Comcast and told to cease the activity. Comcast will continue monitoring them, and if they violate the “Six Strikes” plan five more times, their internet service will be terminated. +EDIT: Removed a sentence that was wrong. Added link.","0" +"50 foot crab : Is this a Crabzilla spotted in the UK?","“The aerial shot enables viewers to see the full body of the crab, including its pinchers and legs,” says the AOL article. +The article also mentions a man who runs a website devoted to the weird and unusual. He reportedly thought the creature in question was initially driftwood with a striking resemblance to a crab, but then later explained he now thinks the crab is real. +By the way, the largest known crab in the world is the Japanese spider crab. But even that one only measures up to about one-fourth the size of this alleged “Crabzilla.” They can measure 12 feet across from claw to claw and weigh up to 40 pounds. +Agencies/Canadajournal","0" +"‘Crabzilla’ a 50-foot colossal conundrum","AUSTIN (KXAN) — This giant news is a colossal conundrum. That’s because a photo of a “Crabzilla” has people asking if it could be real, according to AOL. The creature in question: a 50-foot-long crab. The picture is reportedly an aerial image taken in the United Kingdom. + +“The aerial shot enables viewers to see the full body of the crab, including its pinchers and legs,” says the AOL article. + +The article also mentions a man who runs a website devoted to the weird and unusual. He reportedly thought the creature in question was initially driftwood with a striking resemblance to a crab, but then later explained he now thinks the crab is real. + +By the way, the largest known crab in the world is the Japanese spider crab. But even that one only measures up to about one-fourth the size of this alleged “Crabzilla.” They can measure 12 feet across from claw to claw and weigh up to 40 pounds.","0" +"Crabzilla! Photo appears to show giant CRAB measuring at least 50ft across lurking in the waters off Whitstable","The seaside town might be famed for its oysters, but this incredible image could soon have visitors flocking to Whistable in the hope of catching Britain's biggest crab. + +The photograph, which has been shared online, appears to show a crustacean that is at least 50ft-wide lurking in shallow water. + +While some insist it is proof of 'Crabzilla', others argue that the shadowy figure is nothing more than an unusually-shaped sandbank - or is simply a playful hoax. + +Crabzilla: The photograph, above, which has been shared online, appears to show a crustacean that is at least 50ft wide lurking in the shallow water. It dwarfs the fishing boasts resting on the nearby pier + +The image shows the outline of a crab in the mouth of the Kent harbour - dwarfing the fishing boats resting on the nearby pier. + +It is shaped like an edible crab, a species that is commonly found in British water and grows to an average of five inches. + +The photograph was posted on a website called Weird Whitstable - an online collection of strange and unusual sightings in the town. + +Its curator, Quinton Winter, said that at first he thought the image - sent to him by a follower - showed an unusual sand formation, but that he is now convinced it is a monster of the deep. + +Speaking to the Daily Express, he claimed that he saw the giant creature close to the shore when he took his son crabbing last summer. + +He said: 'At first all I could see was some faint movement, then as it rose from the water I thought, ""that’s a funny looking bit of driftwood"". + +Hoax? It is shaped like an edible crab, a species that is commonly found in British water but normally grows to no more than 10 inches. Some claim that the incredible image is simply a playful hoax + +'It had glazed blank eyes on stalks, swivelling wildly and it clearly was a massive crab with crushing claws. + +'Before this incident I thought the aerial photo showed an odd-shaped sand bank. Now I know better.' + +The largest known species of crab is the Japanese spider crab, which can measure more than 12ft.","0" +"Is this Crabzilla? 'Giant crab' measuring 50ft spotted off British coast","IS it Crabzilla or Claws? This aerial image of a giant crab lurking at a British resort has become an internet sensation. + +People have been flocking to a website to judge for themselves whether this picture shows a huge crustacean in shallow water at a harbour mouth in Kent or is just an elaborate hoax. + +Quinton Winter, who collates strange and spooky sightings for his Weird Whitstable website, at first thought the image sent to him by a follower showed an unusual sand formation in the shape of a crab but is now convinced it’s a true monster of the deep. + +**CLICK HERE TO SEE MORE CREATURES IN DIGUISE** + +He believes he saw the giant lurking close to the shore when he took his son crabbing last summer in the harbour at Whitstable, which is famed for its oysters. + +He said: “At first all I could see was some faint movement, then as it rose from the water I thought, ‘that’s a funny looking bit of driftwood’. + +“It had glazed blank eyes on stalks, swivelling wildly and it clearly was a massive crab with crushing claws. + +“Before this incident I thought the aerial photo showed an odd-shaped sand bank. Now I know better.” + +The picture appears to show an edible crab, scientific name cancer pagurus, a species commonly found in British water but which normally only grows to 10 inches, weighing six pounds. + +The biggest known crab species is the Japanese spider crab, which can measure more than 12ft.","0" +"Crabzilla: Photo Appears To Show Giant, 50-Foot Crab Lurking In British Waters","An astonishing image appears to show a giant crab, nearly 50 feet across, lurking in the harbor at Whitstable, Kent, and while some assert that it is a playful hoax, others believe they have found evidence of a genuine aquatic monster. + +The aerial image reveals the outline of a crab at the mouth of Kent harbor, yet the size of the animal dwarfs fishing boats on a nearby pier, as the Daily Mail notes. The giant animal is shaped like an edible crab, a species commonly found in British waters, but which only grows to be ten inches across, on average. + +People have flocked to the website Weird Whitstable since the image was first posted there, to judge its authenticity for themselves. Quinton Winter, who curates Weird Whitstable, asserted that the image of the giant crab was sent to him by a follower. At first, he believed that it showed only an unusually shaped sand formation, though he is now convinced that there truly is a strange animal lurking in the harbor. + +While crabbing with his son in Whitstable harbor last year, Winter claims to have spotted the giant crab near shore, as he related to The Daily Express. + +Save yourselves, Crabzilla has arrived in Whitstable http://t.co/W2NgcmJP24 pic.twitter.com/7RuUxSBUhB + +— Sara Nelson (@SaraCNelson) October 13, 2014 + +“At first all I could see was some faint movement, then as it rose from the water I thought, ‘that’s a funny looking bit of driftwood,’ Winter said. “It had glazed blank eyes on stalks, swiveling wildly and it clearly was a massive crab with crushing claws… Before this incident I thought the aerial photo showed an odd-shaped sand bank. Now I know better.” + +In July of last year, another image emerged, depicting a giant crab lurking underneath a pier. + +Another image, said to be taken in July of last year and posted on Winter’s Weird Whitstablog, purports to show a giant, albeit smaller, crab hiding under a pier. + +“This shocking image of a giant crab under a popular crabbing spot in Whitstable was taken last weekend,” claims Winter’s website, adding “The boys were unaware of the danger, but as several passersby shouted to them, the crab slipped silently away under the water, into the dark, sideways.” + +Graphic artist Ashley Austen noted his skepticism of the aerial image while speaking to Kent Online, describing the way in which such a photograph could be easily manufactured. + +“The image of the giant crab can be quite easily recreated in Photoshop,” he said. “All the ‘artist’ had to do is find a suitable image of a crab, overlay it on to the satellite picture of the harbor and apply a few filters to it to get the realistic look.” + +Meet Crabzilla, a giant Japanese spider crab http://t.co/irhM1m5fiT pic.twitter.com/mPOHNhQySN — Sir Arnold Robinson (@uk_expat) August 26, 2014 + +Earlier this year, another photograph of an unknown creature emerged from England, appearing to show “Bownessie,” an animal similar to the Loch Ness Monster. As The Inquisitr noted at the time, the surprisingly clear image was met with claims that it had been similarly created in Photoshop. + +The largest known species of crustacean is the Japanese Spider Crab. Giant in comparison to other known species of crab, adults can grow to be 12 feet across. + +[Images: Quinton Winter via The Daily Express and Weird Whitstablog]","0" +"Mystery of 50ft giant crab caught on camera in Kent harbour","Is it a bird? Is it a plane? Or is it a giant crab? + +Aerial images of a giant sea creature in Kent have appeared on the website Weird Whitstable which features all manner of supernatural stories and pictures. + +The site was set up by artist Quinton Winter and features this image taken from Whitstable Harbour + +The website reads: ""Crabbing is a popular activity for children during the summer. + +""Does this satellite photo of the harbour reveal a giant crab or unusual sand formation?"" + +The jury is out on whether the image genuinley does show a giant crustaction and if there really is claws for concern. + +Some say it could be a spoof but you would be shellfish to stop somebody having a bit of fun + Attack of the giant crab?? +Is a giant crab patrolling a Kent harbour? Credit: Weird Whitstable +Last updated Mon 13 Oct 2014","0" +"Is this Crabzilla? Giant Monster Crab Caught on Camera","Does crabzilla really exist? A Mysterious 50ft giant monster crab was caught on camera yards from British harbour. + +Visitors are flocking to the British seaside town of Whistable in the hopes of catching a supposed 50 foot crab whose photo has gone viral in recent days.","0" +"Is this a Crabzilla spotted in the UK? Monster crab measures about 50 feet","The picture of a possible ""Crabzilla"" measuring about 50 feet has surfaced after such creature was allegedly spotted at a harbor in the United Kingdom. The oddity has led many to ask: could this be real or simply a hoax? + +The photograph of the monster crab first came out in the website Weird Whitstable, which collects exciting and unusual pictures of sightings reported in the town of Whitstable, Kent. + +Quinton Winter, the curator of the website, reveals that a follower sent him the picture of the giant crab lurking at the Kent harbor. The satellite image of the crab shows the creature to be about 50 feet in size, more than four times bigger than the biggest crabs alive on the planet. Winter initially thought the crab-like image was due to some sort of sand formation; however, he now believes that it is an actual crab. + +Winter says that he may have also seen the gigantic crab when he went for crabbing with his son in the summer of 2013. + +""At first all I could see was some faint movement, then as it rose from the water I thought, 'that's a funny looking bit of driftwood,"" said Winter. ""It had glazed blank eyes on stalks, swiveling wildly and it clearly was a massive crab with crushing claws. Before this incident I thought the aerial photo showed an odd-shaped sand bank. Now I know better."" + +Japanese spider crabs, found in the waters around Japan, are the biggest known living crab species is the world. The Japanese spider crab can weigh up to 12 kilograms (26.45 pounds) and its leg span can reach up to 3.8 meters (about 12 feet). + +Even though some people believe that the giant crab image is real, there are some who believe it is a hoax and may be the result of computer image manipulation. The image could be an enlarged picture of an edible crab with the scientific name of Cancer pagurus, which is generally found in the waters surrounding the British Isles. However, this crab species is not as big as 50 feet but measures just about 10 inches and weighs just around six pounds. + +Check out the picture of the giant crab of Weird Whitstable and decide for yourself: is it real or a hoax?","0" +"Weatherman caught peeing live on camera","There’s getting caught short and then there is this guy. + +Weather forecaster Mike Seidel obviously thought he had enough time to answer a quick call of nature, but clearly he was wrong. + +In a video uploaded to YouTube by Kris Tatum, NBC Nightly news reader Lester Holt cuts to Seidel ready for the forecast. + +Holt says: ‘Let’s bring in Weather Channel meteorologist Mike Seidel he’s in Sugar Mountain, North Carolina. Hi Mike.’ + +But then there is an awkward pause until Seidel eventually says ‘Why?’ + +Holt adds: ‘Well, obviously Mike’s not ready for us.’","0" +"Did NBC Nightly News Go Live To A Man Who Was Taking A Piss?","It sure looks like Weather Channel meteorologist Mike Seidel was relieving himself when Lester Holt threw to him during his coverage of the storms in North Carolina. What else could he have been doing?","0" +"Watch moment TV weatherman is caught urinating in the bushes LIVE on camera","There was a light sprinkling of showers on the ground as weatherman Mike Seidel was supposed to be giving an outdoor forecast but decided to relieve himself instead + +Video loading + +A TV weatherman was caught with his trousers down - literally - when a news report cut to him ""using the bathroom."" + +NBC Nightly anchorman Lester Holt in the New York studio cut to an outdoor weather forecast but his man in the field was busy having a crafty wee in the bushes. + +Weatherman Mike Seidel obviously thought he had enough time to have a quick tinkle before presenting his segment, but when a cameraman shouted for him to look lively he just turned round, muttering ""why?"" + +Seidel is seen doing up his flies and putting his gloves back on (we're sure he usually washes his hands) as the all professional news reader diplomatically tells viewers that the weatherman isn't quite ready yet. + +Seidel was supposed to be doing an outdoor forecast in Sugar Mountain, North Carolina. + +The original viral clip was uploaded to Youtube by Kris Tatum. + +Poll loading …","0" +"SEE IT: NBC meteorologist Mike Seidel appears to relieve himself during broadcast; network says he was looking for phone","The weather man was reporting from Sugar Mountain N.C. Saturday night when anchor Lester Holt said he was going to give a live report. But Seidel’s back was facing the camera and it appeared to many viewers he was answering Mother Nature’s call instead of reporting on it. But the network said he had dropped his phone in the snow and was looking for it. + +The TV news weather forecast appeared to call for yellow snow — but the network says it was not so. + +NBC weatherman Mike Seidel missed a live report from snow-blanketed North Carolina on Saturday night because his back was to the camera. And the way he turned around while also on camera — appearing to zip up the fly of his pants before putting his gloves back on — suggested to viewers that he had been relieving himself. + +During the telecast anchor Lester Holt said hello to the No. 1 Weather Channel meteorologist who was in Sugar Mountain, but his back was turned to the camera. + +Seidel's body was slightly hunched over and he was looking downward near some trees. + +After a few pauses Seidel can be heard asking ""Why?"" as he starts to turn around. The weather man is holding his gloves in his hands despite the cold temperature. + +As he turns he slightly moves his arm, which may have been an attempt to close an open zipper. He then hurriedly puts his gloves back on. + +A network official told the Daily News that Seidel had dropped his cell phone in the snow and had turned around to find it. + +Seidel has tweeted pictures of the snowstorm on his Twitter account, but did not make any mention of the incident. + +jlandau@nydailynews.com Follow on Twitter @joelzlandau + +USING A MOBILE DEVICE? CLICK HERE TO SEE THE VIDEO.","0" +"Weather Reporter Mike Seidel Was Caught Off Guard on Live TV and Appeared to Be Urinating in the Snow -- Watch!","And we're live! Weather Channel meteorologist Mike Seidel was caught off guard on live TV during a segment on NBC Nightly News over the weekend. Like, really off guard! +PHOTOS: Celebrity flubs! +After Lester Holt tossed to Seidel, who was covering the storms in North Carolina, the camera showed the back of the weather man, who appeared to be relieving himself in the snow. + +While the camera focuses on Seidel's back for a couple seconds, a voice off-camera can be heard yelling, ""Mike, turn around!"" A seriously unaware Seidel then turns while appearing to zip up his pants and asks ""Why?"" +PHOTOS: More stars who messed up on live TV +Holt, who looks hilariously shocked once he realizes what may have happened, then calmly says: ""Well obviously Mike is not quite ready for us. Let's turn to some other news we are following this Saturday night."" +PHOTOS: Funniest Internet moments +Watch the hilarious clip above and decide for yourself!","0" +"Man With Ebola-Like Symptoms Claims Contact With 'Patient Zero' in Texas","A patient in Frisco, Texas, walked into an urgent care facility on Wednesday exhibiting signs and symptoms of Ebola, and told health-care workers he had had contact with ""patient zero"" in Dallas, local officials said in a statement, referring to Thomas Eric Duncan, who died Wednesday of the virus. + +The Texas Department of State Health Services refuted that claim to CNN, however, saying ""no indication"" the man had contact with Duncan. + +It is not known if the patient is one of the 48 being monitored by Texas health officials. A patient who saw the man at the facility told NBCDFW's Ray Villeda that the man arrived with his wife, appearing ""flush, slouched but walking."" + +A spokesperson for CareNow confirmed the news to Mashable, saying that the man ""checked yes"" to one of the screening questions regarding travel to West Africa. ""We are being very cautious,"" she said, adding that while the facility remains open, ""we are not currently seeing any patients."" + +""We are working with the Health Deptartment, the CDC and multiple other municipalities to follow protocol,"" the spokesperson said. + +A reporter on the scene, however, said CareNow is sealed off from the public. + +#Breaking #Frisco police have sealed off Care Now clinic where patient exhibited signs of #Ebola pic.twitter.com/iMWc52TOjc + +— J.D. Miles (@jdmiles11) October 8, 2014 + +A car that was left at the facility was cordoned off with red tape on Wednesday afternoon. + +RIGHT NOW: car outside CareNow clinic taped off with red ""DANGER"" tape @NBCDFW pic.twitter.com/47FkA0vRCN + +— Ray Villeda (@RayVilleda) October 8, 2014 + +And officials in protective suits were spotted walking around inside. + +LOOK: inside staff at CareNow wearing masks and protective gear @NBCDFW pic.twitter.com/hReAuab7z0 + +— Ray Villeda (@RayVilleda) October 8, 2014 + +The patient is being taken by ambulance — complete with police escort — to Dallas Presbyterian Hospital, where he will be evaluated for Ebola. + +#BREAKING Frisco Ambulance transporting patient from CareNow http://t.co/W8SguwjskA pic.twitter.com/8wNaPjdQwy + +— NBC DFW (@NBCDFW) October 8, 2014 + +WFAA said the vehicle is registered to a deputy who ""was very vocal about not wearing protective gear"" during a previous visit to Duncan's apartment. NBC 5 believes the patient is an employee with the Dallas County Sheriff's Office. + +Officials have planned a media briefing for 3:30 p.m. local time. + +Have something to add to this story? Share it in the comments.","0" +"BREAKING: Texas sheriff's deputy rushed to hospital with Ebola symptoms after attending apartment of 'patient zero' who died today","A Dallas County sheriff's deputy has been hospitalized today with Ebola symptoms, a week after he went unprotected into the apartment of first patient Thomas Duncan. + +Sgt Michael Monning went on Wednesday to an urgent-care facility in Frisco, Texas with his wife, after complaining of stomach problems. + +The deputy presented at the clinic a week after he visited the Dallas home where Duncan was staying when he developed Ebola symptoms. Sgt Monning was at the home to deliver a quarantine order to family members. + +Neither Sgt Monning, nor the other two health officials, Zachary Thompson and Christopher Perkins with him, were wearing protective clothing or masks. + +Mr Duncan, 42, died on Wednesday morning at Texas Health Presbyterian Hospital, two weeks after developing symptoms of the virus. + +Scroll down for video + +A possible Ebola patient, believed to be Dallas County Sheriff's Deputy Michael Monning, is brought to the Texas Health Presbyterian Hospital on Wednesday in Dallas, Texas + +The sheriff's deputy arrives at Texas Health Presbyterian Hospital today via ambulance after attending an urgent-care clinic with symptoms + +Sgt Monning walked into Texas Presbyterian Hosptial today accompanied by medics in hazmat suits + +Sgt Monning, pictured, went to an urgent-care facility in Frisco, Texas on Wednesday with Ebola-like symptoms. His family said he was simply taking precautions + +Sgt Monning told medics at the Frisco clinic today that he had been in contact with first victim Mr Duncan and had not been wearing protective clothing. + +The CareNow clinic was immediately placed in lock-down because Monning was exhibiting signs of the deadly virus - including feeling sick and appearing flushed with a fever. + +The CDC told MailOnline today that the person is not one of the 48 contacts being monitored, and there is no indication of any direct contact with the initial patient, Mr Duncan. + +None of the 48 individuals with verified or possible contact with the patient has shown symptoms, the CDC said today. + +Sgt Monning's son, Logan Monning, told CBS that his father had woken up with 'stomach issues' and had gone to the clinic as a precaution. + +Logan said their family was told by the CDC that their father was not at risk of the virus, as he had only been in the apartment for 30 minutes and had not come in contact with bodily fluids. + +A firefighter removes red tape from a vehicle parked outside a CareNow clinic in Frisco, Texas on Wednesday. Frisco Fire Chief Mark Piland says the deputy is being treated 'out of an abundance of caution' + +A medical team in hazmat suits along with law enforcement rushed to the scene at a CareNow clinic in Frisco, Texas on Wednesday after a man turned up with Ebola-like symptoms + +The person, reportedly a Dallas County sheriff's deputy, was exhibiting Ebola symptoms today and claimed to have had contact with patient Thomas Duncan, who died from the virus on Wednesday morning + +An ambulance, driven by a firefighter-paramedic wearing a hazmat suit, carries an individual, believed to be a Dallas County sheriff's deputy, with Ebola symptoms to a hospital in Frisco, Texas on Wednesday afternoon after the person turned up at an urgent care clinic + +A father who had taken his teenage son to the clinic to get a flu shot on Wednesday told WFAA that the man entered the clinic with his wife, appeared flushed and was hunched over. + +Chuck Moreno said that he and his son had self-quarantined in an exam room, put on surgical masks and sprayed themselves with disinfectant. + +Sgt Monning answered yes in a screening questionnaire to a question about travel to West Africa and is said to have contact with Duncan, referred to as ‘patient zero’. + +The Frisco patient was rushed to Texas Health Presbyterian Hosptial by ambulance after turning up at the urgent care clinic on Main Street. + +Medics at the clinic called 911 at around 12.30pm to request an ambulance for the patient. A team in hazmat suits and face masks transported the law enforcement officer. + +A hospital spokesman said: 'Texas Health Presbyterian Dallas can confirm today that a patient has been admitted to the Emergency Room after reporting possible exposure to the Ebola virus. + +'Right now, there are more questions than answers about this case. Our professional staff of nurses and doctors is prepared to examine the patient, discuss any findings with appropriate agencies and officials. + +A second person is exhibiting Ebola symptoms in Texas today and claimed to have had contact with Thomas Duncan who died from Ebola today + +A sign on the door of the apartment where Thomas Eric Duncan stayed with family warns that the unit has been quarantined by the commissioner of health on Wednesday + +Where it began: Neither Sgt Monning, nor the other two health officials, Zachary Thompson (left) and Christopher Perkins (right) with him, were wearing protective clothing or masks. The two other men are seen here leaving the apartment where Patient Zero stayed while ill. Neither Thompson nor Perkins have reported any worrisome symptoms + +'We are on alert with precautions and systems in place. At the same time, we are caring for routine cases which are completely separate in operations.' + +The clinic was keeping everyone at the center until they are checked out by the CDC - it is unknown how many people were exposed to the patient. + +All those at the clinic will be transferred to a hospital but it is unclear which medical facility. + +Mr Duncan, a 42-year-old Liberian national, exposed nearly 50 people to the disease in America before he was put in isolation at Texas Presbyterian. + +A patient attended CareNow clinic in Frisco, Texas today and was rushed to a nearby hospital after presenting with Ebola symptoms. The clinic was placed on lockdown until everyone inside can be checked by the CDC + +His fiancee Louise Troh is currently in quarantine with her 13-year-old son and two nephews and under constant monitoring by health officials over fears that they, too, could develop symptoms during a 21-day incubation period. + +Ten people, including seven healthcare workers and three family members, are considered at high risk for Ebola after they were exposed to Duncan after he became contagious. + +Another 38 more are being monitors by the CDC for possible risk of the disease. + +Duncan's fiancee Louise Troh, who is perhaps highest at risk of catching the disease after she cared for him at her Dallas apartment while he sweated and vomited through the early staged of the disease, says she does not blame him for possibly exposing her. + +The White House said on Wednesday that extra screening for fever will be carried out for arriving aircraft passengers from West Africa, where the virus has killed nearly 4,000 people in three countries. + +The screening will start at New York's John F. Kennedy airport from the weekend, and later at Newark Liberty, Washington Dulles, Chicago O'Hare and Hartsfield-Jackson Atlanta. + +Authorities will use a non-invasive device to take the temperature of passengers and have them fill out a questionnaire created by the U.S. Centers for Disease Control and Prevention (CDC) asking for detailed information about their activities. + +A cleaning crew in bio-hazard suits decontaminated the Dallas apartment where Ebola patient Thomas Duncan fell ill almost two weeks ago. He died from the deadly virus on Wednesday + +President Obama participates in a conference call with state and local officials to discuss domestic preparedness response to the Ebola epidemic in West Africa, at the White House today","0" +"Texas sheriff's deputy rushed to hospital with Ebola symptoms after attending apartment of 'patient zero' who died today","A Dallas County sheriff's deputy has been hospitalized today with Ebola symptoms, a week after he went unprotected into the apartment of first patient Thomas Duncan. + +Sgt Michael Monnig went on Wednesday to an urgent-care facility in Frisco, Texas with his wife, after complaining of stomach problems. + +The deputy presented at the clinic a week after he visited the Dallas home where Duncan was staying when he developed Ebola symptoms. Sgt Monnig was at the home to deliver a quarantine order to family members. + +Neither Sgt Monnig, nor the other two health officials, Zachary Thompson and Christopher Perkins with him, were wearing protective clothing or masks despite being in the apartment as cleaning crews were going about their work in full protective gear. + +A possible Ebola patient, believed to be Dallas County Sheriff's Deputy Michael Monnig, is brought to the Texas Health Presbyterian Hospital on Wednesday in Dallas, Texas + +The sheriff's deputy arrives at Texas Health Presbyterian Hospital today via ambulance after attending an urgent-care clinic with symptoms + +Sgt Monnig walked into Texas Presbyterian Hosptial today accompanied by medics in hazmat suits + +Sgt Monnig, pictured, went to an urgent-care facility in Frisco, Texas on Wednesday with Ebola-like symptoms. His family said he was simply taking precautions + +The day after going into the apartment, Monnig and his fellow officers were told to bag up the clothes they'd been wearing. Their police cars were also taken out of commission. + +'That starts putting question marks in your mind,' Monnig told WFAA in an October 3 report. 'You know when you go home and then the next day you start hearing that equipment is being quarantined or asked to be bagged up, that you had on or were driving. + +'Then your question is, ""well, what about me?"" And so those were the questions that were raised.' + +Now the question is: Why wasn't Monnig warned before entering the home completely without protection? + +'There should be some kind of protocols as far as what kind of a response we're going to have and what kind of safety equipment we're going to have,' Dyer said in the WFAA interview. 'Those kinds of things didn't happen.' + +Mr Duncan, 42, died on Wednesday morning at Texas Health Presbyterian Hospital, two weeks after developing symptoms of the virus. + +Sgt Monnig told medics at the Frisco clinic today that he had been in contact with first victim Mr Duncan and had not been wearing protective clothing. + +The CareNow clinic was immediately placed in lock-down because Monnig was exhibiting signs of the deadly virus - including feeling sick and appearing flushed with a fever. + +The CDC told MailOnline today that the person is not one of the 48 contacts being monitored, and there is no indication of any direct contact with the initial patient, Mr Duncan. + +None of the 48 individuals with verified or possible contact with the patient has shown symptoms, the CDC said today. + +Sgt Monnig's son, Logan Monnig, told CBS that his father had woken up with 'stomach issues' and had gone to the clinic as a precaution. + +Logan said family were told by the CDC that their father was not at risk of the virus, as he had only been in the apartment for 30 minutes and had not come in contact with bodily fluids. + +A firefighter removes red tape from a vehicle parked outside a CareNow clinic in Frisco, Texas on Wednesday. Frisco Fire Chief Mark Piland says the deputy is being treated 'out of an abundance of caution' + +A medical team in hazmat suits along with law enforcement rushed to the scene at a CareNow clinic in Frisco, Texas on Wednesday after a man turned up with Ebola-like symptoms + +The person, reportedly a Dallas County sheriff's deputy, was exhibiting Ebola symptoms today and claimed to have had contact with patient Thomas Duncan, who died from the virus on Wednesday morning + +An ambulance, driven by a firefighter-paramedic wearing a hazmat suit, carries an individual, believed to be a Dallas County sheriff's deputy, with Ebola symptoms to a hospital in Frisco, Texas on Wednesday afternoon after the person turned up at an urgent care clinic + +'We are not expecting him to' test positive for Ebola, said Logan. + +A father who had taken his teenage son to the clinic to get a flu shot on Wednesday told WFAA that the man entered the clinic with his wife, appeared flushed and was hunched over. + +Chuck Moreno said that he and his son had self-quarantined in an exam room, put on surgical masks and sprayed themselves with disinfectant. + +Sgt Monnig answered yes in a screening questionnaire to a question about travel to West Africa and is said to have contact with Duncan, referred to as ‘patient zero’. + +The Frisco patient was rushed to Texas Health Presbyterian Hosptial by ambulance after turning up at the urgent care clinic on Main Street. + +Medics at the clinic called 911 at around 12.30pm to request an ambulance for the patient. A team in hazmat suits and face masks transported the law enforcement officer. + +A hospital spokesman said: 'Texas Health Presbyterian Dallas can confirm today that a patient has been admitted to the Emergency Room after reporting possible exposure to the Ebola virus. + +'Right now, there are more questions than answers about this case. Our professional staff of nurses and doctors is prepared to examine the patient, discuss any findings with appropriate agencies and officials. + +A second person is exhibiting Ebola symptoms in Texas today and claimed to have had contact with Thomas Duncan who died from Ebola today + +A sign on the door of the apartment where Thomas Eric Duncan stayed with family warns that the unit has been quarantined by the commissioner of health on Wednesday + +Where it began: Neither Sgt Monnig, nor the other two health officials, Zachary Thompson (left) and Christopher Perkins (right) with him, were wearing protective clothing or masks. The two other men are seen here leaving the apartment where Patient Zero stayed while ill. Neither Thompson nor Perkins have reported any worrisome symptoms + +'We are on alert with precautions and systems in place. At the same time, we are caring for routine cases which are completely separate in operations.' + +The clinic was keeping everyone at the center until they are checked out by the CDC - it is unknown how many people were exposed to the patient. + +All those at the clinic will be transferred to a hospital but it is unclear which medical facility. + +While no doubt in a fearful and nearvous state now, Mr. Monnig's career has often hinged largely on his physical toughness, even more so than most cops. + +The large-framed Monnig once worked as a sort of human punching bag for incoming Dallas County police recruits who learned how to use batons by beating Monnig. + +At least that was his job until 2008, when Monnig was temporarily terminated from the police force after getting seriously injured during one of his brutal training sessions. + +He was unable to work in active duty and the force was apparently not interested in giving him a desk job. + +Concerned son: Monnig's son Logan (pictured) spoke to reporters outside the family home not long after his father checked himself in with doctors Wednesday. Logan Monnig said he and his family are worried about Mr. Monnig but said 'we are not expecting him to' test positive for Ebola + +A patient attended CareNow clinic in Frisco, Texas today and was rushed to a nearby hospital after presenting with Ebola symptoms. The clinic was placed on lockdown until everyone inside can be checked by the CDC + +'Your job is basically to get beaten up by recruits,' CBS DFW said in a 2008 interview about his firing. + +'Part of it is,' he replied. 'I want it to be as realistic as possible.' + +Thanks in part to the 2008 broadcast, Monnig was rehired by the force. + +Mr Duncan, a 42-year-old Liberian national, exposed nearly 50 people to the disease in America before he was put in isolation at Texas Presbyterian. + +His fiancee Louise Troh is currently in quarantine with her 13-year-old son and two nephews and under constant monitoring by health officials over fears that they, too, could develop symptoms during a 21-day incubation period. + +Tough guy: Part of Monnig's job, at least back before 2008, was to take the physical blows dealt by Dallas county police recruits learning how to use batons + +Fired: After sustaining an injury during his extreme training sessions that kept him off his beat, Monnig was fired. However, a local CBS report that cast light on the apparent unfair treatment got Monnig his job back + +Ten people, including seven healthcare workers and three family members, are considered at high risk for Ebola after they were exposed to Duncan after he became contagious. + +Another 38 more are being monitors by the CDC for possible risk of the disease. + +Duncan's fiancee Louise Troh, who is perhaps highest at risk of catching the disease after she cared for him at her Dallas apartment while he sweated and vomited through the early staged of the disease, says she does not blame him for possibly exposing her. + +The White House said on Wednesday that extra screening for fever will be carried out for arriving aircraft passengers from West Africa, where the virus has killed nearly 4,000 people in three countries. + +The screening will start at New York's John F. Kennedy airport from the weekend, and later at Newark Liberty, Washington Dulles, Chicago O'Hare and Hartsfield-Jackson Atlanta. + +Authorities will use a non-invasive device to take the temperature of passengers and have them fill out a questionnaire created by the U.S. Centers for Disease Control and Prevention (CDC) asking for detailed information about their activities. + +A cleaning crew in bio-hazard suits decontaminated the Dallas apartment where Ebola patient Thomas Duncan fell ill almost two weeks ago. He died from the deadly virus on Wednesday + +President Obama participates in a conference call with state and local officials to discuss domestic preparedness response to the Ebola epidemic in West Africa, at the White House today","0" +"'What about me?': Texas sheriff's deputy rushed to hospital with symptoms of deadly Ebola complained about lack of safety when he was sent to 'patient zero's' apartment","A Dallas County sheriff's deputy has been hospitalized today with Ebola symptoms, a week after he went unprotected into the apartment of first patient Thomas Duncan. + +Sgt Michael Monnig went on Wednesday to an urgent-care facility in Frisco, Texas with his wife, after complaining of stomach problems. + +The deputy presented at the clinic a week after he visited the Dallas home where Duncan was staying when he developed Ebola symptoms. Sgt Monnig was at the home to deliver a quarantine order to family members. + +Neither Sgt Monnig, nor the other two health officials, Zachary Thompson and Christopher Perkins with him, were wearing protective clothing or masks despite being in the apartment as cleaning crews were going about their work in full protective gear. + +A possible Ebola patient, believed to be Dallas County Sheriff's Deputy Michael Monnig, is brought to the Texas Health Presbyterian Hospital on Wednesday in Dallas, Texas + +The sheriff's deputy arrives at Texas Health Presbyterian Hospital today via ambulance after attending an urgent-care clinic with symptoms + +Sgt Monnig walked into Texas Presbyterian Hosptial today accompanied by medics in hazmat suits + +Sgt Monnig, pictured, went to an urgent-care facility in Frisco, Texas on Wednesday with Ebola-like symptoms. His family said he was simply taking precautions + +The day after going into the apartment, Monnig and his fellow officers were told to bag up the clothes they'd been wearing. Their police cars were also taken out of commission. + +'That starts putting question marks in your mind,' Monnig told WFAA in an October 3 report. 'You know when you go home and then the next day you start hearing that equipment is being quarantined or asked to be bagged up, that you had on or were driving. + +'Then your question is, ""well, what about me?"" And so those were the questions that were raised.' + +Now the question is: Why wasn't Monnig warned before entering the home completely without protection? + +'There should be some kind of protocols as far as what kind of a response we're going to have and what kind of safety equipment we're going to have,' Dyer said in the WFAA interview. 'Those kinds of things didn't happen.' + +Monnig's wife Lisa echoed his sentiment. + +'It was pretty scary,' Lisa Monnig said about the day her husband entered the apartment. 'I was awake until he got home that night.' + +No doubt Monnig is now feeling that pit in her stomach again as she and her family are forced to wait out the next two days it will take to determine whether Monnig managed to catch the dreaded virus. + +Mr Duncan, 42, died on Wednesday morning at Texas Health Presbyterian Hospital, two weeks after developing symptoms of the virus. + +Sgt Monnig told medics at the Frisco clinic today that he had been in contact with first victim Mr Duncan and had not been wearing protective clothing. + +A firefighter removes red tape from a vehicle parked outside a CareNow clinic in Frisco, Texas on Wednesday. Frisco Fire Chief Mark Piland says the deputy is being treated 'out of an abundance of caution' + +A medical team in hazmat suits along with law enforcement rushed to the scene at a CareNow clinic in Frisco, Texas on Wednesday after a man turned up with Ebola-like symptoms + +The person, reportedly a Dallas County sheriff's deputy, was exhibiting Ebola symptoms today and claimed to have had contact with patient Thomas Duncan, who died from the virus on Wednesday morning + +An ambulance, driven by a firefighter-paramedic wearing a hazmat suit, carries an individual, believed to be a Dallas County sheriff's deputy, with Ebola symptoms to a hospital in Frisco, Texas on Wednesday afternoon after the person turned up at an urgent care clinic + +The CareNow clinic was immediately placed in lock-down because Monnig was exhibiting signs of the deadly virus - including feeling sick and appearing flushed with a fever. + +The CDC told MailOnline today that the person is not one of the 48 contacts being monitored, and there is no indication of any direct contact with the initial patient, Mr Duncan. + +None of the 48 individuals with verified or possible contact with the patient has shown symptoms, the CDC said today. + +Sgt Monnig's son, Logan Monnig, told CBS that his father had woken up with 'stomach issues' and had gone to the clinic as a precaution. + +Logan said family were told by the CDC that their father was not at risk of the virus, as he had only been in the apartment for 30 minutes and had not come in contact with bodily fluids. + +'We are not expecting him to' test positive for Ebola, said Logan. + +A father who had taken his teenage son to the clinic to get a flu shot on Wednesday told WFAA that the man entered the clinic with his wife, appeared flushed and was hunched over. + +Chuck Moreno said that he and his son had self-quarantined in an exam room, put on surgical masks and sprayed themselves with disinfectant. + +Sgt Monnig answered yes in a screening questionnaire to a question about travel to West Africa and is said to have contact with Duncan, referred to as ‘patient zero’. + +The Frisco patient was rushed to Texas Health Presbyterian Hosptial by ambulance after turning up at the urgent care clinic on Main Street. + +Medics at the clinic called 911 at around 12.30pm to request an ambulance for the patient. A team in hazmat suits and face masks transported the law enforcement officer. + +A hospital spokesman said: 'Texas Health Presbyterian Dallas can confirm today that a patient has been admitted to the Emergency Room after reporting possible exposure to the Ebola virus. + +'Right now, there are more questions than answers about this case. Our professional staff of nurses and doctors is prepared to examine the patient, discuss any findings with appropriate agencies and officials. + +A second person is exhibiting Ebola symptoms in Texas today and claimed to have had contact with Thomas Duncan who died from Ebola today + +A sign on the door of the apartment where Thomas Eric Duncan stayed with family warns that the unit has been quarantined by the commissioner of health on Wednesday + +Where it began: Neither Sgt Monnig, nor the other two health officials, Zachary Thompson (left) and Christopher Perkins (right) with him, were wearing protective clothing or masks. The two other men are seen here leaving the apartment where Patient Zero stayed while ill. Neither Thompson nor Perkins have reported any worrisome symptoms + +'We are on alert with precautions and systems in place. At the same time, we are caring for routine cases which are completely separate in operations.' + +The clinic was keeping everyone at the center until they are checked out by the CDC - it is unknown how many people were exposed to the patient. + +All those at the clinic will be transferred to a hospital but it is unclear which medical facility. + +While no doubt in a fearful and nearvous state now, Mr. Monnig's career has often hinged largely on his physical toughness, even more so than most cops. + +The large-framed Monnig once worked as a sort of human punching bag for incoming Dallas County police recruits who learned how to use batons by beating Monnig. + +At least that was his job until 2008, when Monnig was temporarily terminated from the police force after getting seriously injured during one of his brutal training sessions. + +He was unable to work in active duty and the force was apparently not interested in giving him a desk job. + +Concerned son: Monnig's son Logan (pictured) spoke to reporters outside the family home not long after his father checked himself in with doctors Wednesday. Logan Monnig said he and his family are worried about Mr. Monnig but said 'we are not expecting him to' test positive for Ebola + +A patient attended CareNow clinic in Frisco, Texas today and was rushed to a nearby hospital after presenting with Ebola symptoms. The clinic was placed on lockdown until everyone inside can be checked by the CDC + +'Your job is basically to get beaten up by recruits,' CBS DFW said in a 2008 interview about his firing. + +'Part of it is,' he replied. 'I want it to be as realistic as possible.' + +Thanks in part to the 2008 broadcast, Monnig was rehired by the force. + +Mr Duncan, a 42-year-old Liberian national, exposed nearly 50 people to the disease in America before he was put in isolation at Texas Presbyterian. + +His fiancee Louise Troh is currently in quarantine with her 13-year-old son and two nephews and under constant monitoring by health officials over fears that they, too, could develop symptoms during a 21-day incubation period. + +Tough guy: Part of Monnig's job, at least back before 2008, was to take the physical blows dealt by Dallas county police recruits learning how to use batons + +Fired: After sustaining an injury during his extreme training sessions that kept him off his beat, Monnig was fired. However, a local CBS report that cast light on the apparent unfair treatment got Monnig his job back + +Ten people, including seven healthcare workers and three family members, are considered at high risk for Ebola after they were exposed to Duncan after he became contagious. + +Another 38 more are being monitors by the CDC for possible risk of the disease. + +Duncan's fiancee Louise Troh, who is perhaps highest at risk of catching the disease after she cared for him at her Dallas apartment while he sweated and vomited through the early staged of the disease, says she does not blame him for possibly exposing her. + +The White House said on Wednesday that extra screening for fever will be carried out for arriving aircraft passengers from West Africa, where the virus has killed nearly 4,000 people in three countries. + +The screening will start at New York's John F. Kennedy airport from the weekend, and later at Newark Liberty, Washington Dulles, Chicago O'Hare and Hartsfield-Jackson Atlanta. + +Authorities will use a non-invasive device to take the temperature of passengers and have them fill out a questionnaire created by the U.S. Centers for Disease Control and Prevention (CDC) asking for detailed information about their activities. + +A cleaning crew in bio-hazard suits decontaminated the Dallas apartment where Ebola patient Thomas Duncan fell ill almost two weeks ago. He died from the deadly virus on Wednesday + +President Obama participates in a conference call with state and local officials to discuss domestic preparedness response to the Ebola epidemic in West Africa, at the White House today","0" +"'What about me?': Texas sheriff's deputy hospitalized with symptoms of deadly Ebola complained along with his terrified wife about lack of safety when he was sent to 'patient zero's' apartment","A Dallas County sheriff's deputy has been hospitalized today with Ebola symptoms, a week after he went unprotected into the apartment of first patient Thomas Duncan. + +Sgt Michael Monnig went on Wednesday to an urgent-care facility in Frisco, Texas with his wife, after complaining of stomach problems. + +The deputy presented at the clinic a week after he visited the Dallas home where Duncan was staying when he developed Ebola symptoms. Sgt Monnig was at the home to deliver a quarantine order to family members. + +Neither Sgt Monnig, nor the other two health officials, Zachary Thompson and Christopher Perkins with him, were wearing protective clothing or masks despite being in the apartment as cleaning crews were going about their work in full protective gear. + +A possible Ebola patient, believed to be Dallas County Sheriff's Deputy Michael Monnig, is brought to the Texas Health Presbyterian Hospital on Wednesday in Dallas, Texas + +The sheriff's deputy arrives at Texas Health Presbyterian Hospital today via ambulance after attending an urgent-care clinic with symptoms + +Sgt Monnig walked into Texas Presbyterian Hosptial today accompanied by medics in hazmat suits + +Sgt Monnig, pictured here with his family, went to an urgent-care facility in Frisco, Texas on Wednesday with Ebola-like symptoms. His family said he was simply taking precautions + +'It was pretty scary': Monnig's wife recalled the fear she had after learning her husband was in the apartment where Duncan took ill and likely relived that fear Wednesday + +The day after going into the apartment, Monnig and his fellow officers were told to bag up the clothes they'd been wearing. Their police cars were also taken out of commission. + +'That starts putting question marks in your mind,' Monnig told WFAA in an October 3 report. 'You know when you go home and then the next day you start hearing that equipment is being quarantined or asked to be bagged up, that you had on or were driving. + +'Then your question is, ""well, what about me?"" And so those were the questions that were raised.' + +Now the question is: Why wasn't Monnig warned before entering the home completely without protection? + +'There should be some kind of protocols as far as what kind of a response we're going to have and what kind of safety equipment we're going to have,' Christopher Dyer, president of the Dallas County Sheriff's Association, said in the WFAA interview. 'Those kinds of things didn't happen.' + +Monnig's wife Lisa echoed his sentiment. + +'It was pretty scary,' Lisa Monnig said about the day her husband entered the apartment. 'I was awake until he got home that night.' + +No doubt Monnig is now feeling that pit in her stomach again as she and her family are forced to wait out the next two days it will take to determine whether Monnig managed to catch the dreaded virus. + +Mr Duncan, 42, died on Wednesday morning at Texas Health Presbyterian Hospital, two weeks after developing symptoms of the virus. + +Sgt Monnig told medics at the Frisco clinic today that he had been in contact with first victim Mr Duncan and had not been wearing protective clothing. + +A firefighter removes red tape from a vehicle parked outside a CareNow clinic in Frisco, Texas on Wednesday. Frisco Fire Chief Mark Piland says the deputy is being treated 'out of an abundance of caution' + +A medical team in hazmat suits along with law enforcement rushed to the scene at a CareNow clinic in Frisco, Texas on Wednesday after a man turned up with Ebola-like symptoms + +The person, reportedly a Dallas County sheriff's deputy, was exhibiting Ebola symptoms today and claimed to have had contact with patient Thomas Duncan, who died from the virus on Wednesday morning + +An ambulance, driven by a firefighter-paramedic wearing a hazmat suit, carries an individual, believed to be a Dallas County sheriff's deputy, with Ebola symptoms to a hospital in Frisco, Texas on Wednesday afternoon after the person turned up at an urgent care clinic + +The CareNow clinic was immediately placed in lock-down because Monnig was exhibiting signs of the deadly virus - including feeling sick and appearing flushed with a fever. + +The CDC told MailOnline today that the person is not one of the 48 contacts being monitored, and there is no indication of any direct contact with the initial patient, Mr Duncan. + +None of the 48 individuals with verified or possible contact with the patient has shown symptoms, the CDC said today. + +Sgt Monnig's son, Logan Monnig, told CBS that his father had woken up with 'stomach issues' and had gone to the clinic as a precaution. + +Logan said family were told by the CDC that their father was not at risk of the virus, as he had only been in the apartment for 30 minutes and had not come in contact with bodily fluids. + +'We are not expecting him to' test positive for Ebola, said Logan. + +A father who had taken his teenage son to the clinic to get a flu shot on Wednesday told WFAA that the man entered the clinic with his wife, appeared flushed and was hunched over. + +Chuck Moreno said that he and his son had self-quarantined in an exam room, put on surgical masks and sprayed themselves with disinfectant. + +Sgt Monnig answered yes in a screening questionnaire to a question about travel to West Africa and is said to have contact with Duncan, referred to as ‘patient zero’. + +The Frisco patient was rushed to Texas Health Presbyterian Hosptial by ambulance after turning up at the urgent care clinic on Main Street. + +Medics at the clinic called 911 at around 12.30pm to request an ambulance for the patient. A team in hazmat suits and face masks transported the law enforcement officer. + +A hospital spokesman said: 'Texas Health Presbyterian Dallas can confirm today that a patient has been admitted to the Emergency Room after reporting possible exposure to the Ebola virus. + +'Right now, there are more questions than answers about this case. Our professional staff of nurses and doctors is prepared to examine the patient, discuss any findings with appropriate agencies and officials. + +A second person is exhibiting Ebola symptoms in Texas today and claimed to have had contact with Thomas Duncan who died from Ebola today + +A sign on the door of the apartment where Thomas Eric Duncan stayed with family warns that the unit has been quarantined by the commissioner of health on Wednesday + +Where it began: Neither Sgt Monnig, nor the other two health officials, Zachary Thompson (left) and Christopher Perkins (right) with him, were wearing protective clothing or masks. The two other men are seen here leaving the apartment where Patient Zero stayed while ill. Neither Thompson nor Perkins have reported any worrisome symptoms + +'We are on alert with precautions and systems in place. At the same time, we are caring for routine cases which are completely separate in operations.' + +The clinic was keeping everyone at the center until they are checked out by the CDC - it is unknown how many people were exposed to the patient. + +All those at the clinic will be transferred to a hospital but it is unclear which medical facility. + +While no doubt in a fearful and nearvous state now, Mr. Monnig's career has often hinged largely on his physical toughness, even more so than most cops. + +The large-framed Monnig once worked as a sort of human punching bag for incoming Dallas County police recruits who learned how to use batons by beating Monnig. + +At least that was his job until 2008, when Monnig was temporarily terminated from the police force after getting seriously injured during one of his brutal training sessions. + +He was unable to work in active duty and the force was apparently not interested in giving him a desk job. + +Concerned son: Monnig's son Logan (pictured) spoke to reporters outside the family home not long after his father checked himself in with doctors Wednesday. Logan Monnig said he and his family are worried about Mr. Monnig but said 'we are not expecting him to' test positive for Ebola + +A patient attended CareNow clinic in Frisco, Texas today and was rushed to a nearby hospital after presenting with Ebola symptoms. The clinic was placed on lockdown until everyone inside can be checked by the CDC + +'Your job is basically to get beaten up by recruits,' CBS DFW said in a 2008 interview about his firing. + +'Part of it is,' he replied. 'I want it to be as realistic as possible.' + +Thanks in part to the 2008 broadcast, Monnig was rehired by the force. + +Mr Duncan, a 42-year-old Liberian national, exposed nearly 50 people to the disease in America before he was put in isolation at Texas Presbyterian. + +His fiancee Louise Troh is currently in quarantine with her 13-year-old son and two nephews and under constant monitoring by health officials over fears that they, too, could develop symptoms during a 21-day incubation period. + +Tough guy: Part of Monnig's job, at least back before 2008, was to take the physical blows dealt by Dallas county police recruits learning how to use batons + +Fired: After sustaining an injury during his extreme training sessions that kept him off his beat, Monnig was fired. However, a local CBS report that cast light on the apparent unfair treatment got Monnig his job back + +Ten people, including seven healthcare workers and three family members, are considered at high risk for Ebola after they were exposed to Duncan after he became contagious. + +Another 38 more are being monitors by the CDC for possible risk of the disease. + +Duncan's fiancee Louise Troh, who is perhaps highest at risk of catching the disease after she cared for him at her Dallas apartment while he sweated and vomited through the early staged of the disease, says she does not blame him for possibly exposing her. + +The White House said on Wednesday that extra screening for fever will be carried out for arriving aircraft passengers from West Africa, where the virus has killed nearly 4,000 people in three countries. + +The screening will start at New York's John F. Kennedy airport from the weekend, and later at Newark Liberty, Washington Dulles, Chicago O'Hare and Hartsfield-Jackson Atlanta. + +Authorities will use a non-invasive device to take the temperature of passengers and have them fill out a questionnaire created by the U.S. Centers for Disease Control and Prevention (CDC) asking for detailed information about their activities. + +A cleaning crew in bio-hazard suits decontaminated the Dallas apartment where Ebola patient Thomas Duncan fell ill almost two weeks ago. He died from the deadly virus on Wednesday + +President Obama participates in a conference call with state and local officials to discuss domestic preparedness response to the Ebola epidemic in West Africa, at the White House today","0" +"'What about me?' Texas Sheriff's deputy who has Ebola symptoms was sent into patient zero's apartment WITHOUT protection and started growing concerned when his squad car was quarantined","A Dallas County sheriff's deputy has been hospitalized today with Ebola symptoms, a week after he went unprotected into the apartment of first patient Thomas Duncan. + +Sgt Michael Monnig went on Wednesday to an urgent-care facility in Frisco, Texas with his wife, after complaining of stomach problems. + +The deputy presented at the clinic a week after he visited the Dallas home where Duncan was staying when he developed Ebola symptoms. Sgt Monnig was at the home to deliver a quarantine order to family members. + +Neither Sgt Monnig, nor the other two health officials, Zachary Thompson and Christopher Perkins with him, were wearing protective clothing or masks despite being in the apartment as cleaning crews were going about their work in full protective gear. + +A possible Ebola patient, believed to be Dallas County Sheriff's Deputy Michael Monnig, is brought to the Texas Health Presbyterian Hospital on Wednesday in Dallas, Texas + +The sheriff's deputy arrives at Texas Health Presbyterian Hospital today via ambulance after attending an urgent-care clinic with symptoms + +Sgt Monnig walked into Texas Presbyterian Hosptial today accompanied by medics in hazmat suits + +Sgt Monnig, pictured here with his family, went to an urgent-care facility in Frisco, Texas on Wednesday with Ebola-like symptoms. His family said he was simply taking precautions + +'It was pretty scary': Monnig's wife recalled the fear she had after learning her husband was in the apartment where Duncan took ill and likely relived that fear Wednesday + +The day after going into the apartment, Monnig and his fellow officers were told to bag up the clothes they'd been wearing. Their police cars were also taken out of commission. + +'That starts putting question marks in your mind,' Monnig told WFAA in an October 3 report. 'You know when you go home and then the next day you start hearing that equipment is being quarantined or asked to be bagged up, that you had on or were driving. + +'Then your question is, ""well, what about me?"" And so those were the questions that were raised.' + +Now the question is: Why wasn't Monnig warned before entering the home completely without protection? + +'There should be some kind of protocols as far as what kind of a response we're going to have and what kind of safety equipment we're going to have,' Christopher Dyer, president of the Dallas County Sheriff's Association, said in the WFAA interview. 'Those kinds of things didn't happen.' + +Monnig's wife Lisa echoed his sentiment. + +'It was pretty scary,' Lisa Monnig said about the day her husband entered the apartment. 'I was awake until he got home that night.' + +No doubt Monnig is now feeling that pit in her stomach again as she and her family are forced to wait out the next two days it will take to determine whether Monnig managed to catch the dreaded virus. + +Mr Duncan, 42, died on Wednesday morning at Texas Health Presbyterian Hospital, two weeks after developing symptoms of the virus. + +Sgt Monnig told medics at the Frisco clinic today that he had been in contact with first victim Mr Duncan and had not been wearing protective clothing. + +A firefighter removes red tape from a vehicle parked outside a CareNow clinic in Frisco, Texas on Wednesday. Frisco Fire Chief Mark Piland says the deputy is being treated 'out of an abundance of caution' + +A medical team in hazmat suits along with law enforcement rushed to the scene at a CareNow clinic in Frisco, Texas on Wednesday after a man turned up with Ebola-like symptoms + +The person, reportedly a Dallas County sheriff's deputy, was exhibiting Ebola symptoms today and claimed to have had contact with patient Thomas Duncan, who died from the virus on Wednesday morning + +An ambulance, driven by a firefighter-paramedic wearing a hazmat suit, carries an individual, believed to be a Dallas County sheriff's deputy, with Ebola symptoms to a hospital in Frisco, Texas on Wednesday afternoon after the person turned up at an urgent care clinic + +The CareNow clinic was immediately placed in lock-down because Monnig was exhibiting signs of the deadly virus - including feeling sick and appearing flushed with a fever. + +The CDC told MailOnline today that the person is not one of the 48 contacts being monitored, and there is no indication of any direct contact with the initial patient, Mr Duncan. + +None of the 48 individuals with verified or possible contact with the patient has shown symptoms, the CDC said today. + +Sgt Monnig's son, Logan Monnig, told CBS that his father had woken up with 'stomach issues' and had gone to the clinic as a precaution. + +Logan said family were told by the CDC that their father was not at risk of the virus, as he had only been in the apartment for 30 minutes and had not come in contact with bodily fluids. + +'We are not expecting him to' test positive for Ebola, said Logan. + +A father who had taken his teenage son to the clinic to get a flu shot on Wednesday told WFAA that the man entered the clinic with his wife, appeared flushed and was hunched over. + +Chuck Moreno said that he and his son had self-quarantined in an exam room, put on surgical masks and sprayed themselves with disinfectant. + +Sgt Monnig answered yes in a screening questionnaire to a question about travel to West Africa and is said to have contact with Duncan, referred to as ‘patient zero’. + +The Frisco patient was rushed to Texas Health Presbyterian Hosptial by ambulance after turning up at the urgent care clinic on Main Street. + +Medics at the clinic called 911 at around 12.30pm to request an ambulance for the patient. A team in hazmat suits and face masks transported the law enforcement officer. + +A hospital spokesman said: 'Texas Health Presbyterian Dallas can confirm today that a patient has been admitted to the Emergency Room after reporting possible exposure to the Ebola virus. + +'Right now, there are more questions than answers about this case. Our professional staff of nurses and doctors is prepared to examine the patient, discuss any findings with appropriate agencies and officials. + +A second person is exhibiting Ebola symptoms in Texas today and claimed to have had contact with Thomas Duncan who died from Ebola today + +A sign on the door of the apartment where Thomas Eric Duncan stayed with family warns that the unit has been quarantined by the commissioner of health on Wednesday + +Where it began: Neither Sgt Monnig, nor the other two health officials, Zachary Thompson (left) and Christopher Perkins (right) with him, were wearing protective clothing or masks. The two other men are seen here leaving the apartment where Patient Zero stayed while ill. Neither Thompson nor Perkins have reported any worrisome symptoms + +'We are on alert with precautions and systems in place. At the same time, we are caring for routine cases which are completely separate in operations.' + +The clinic was keeping everyone at the center until they are checked out by the CDC - it is unknown how many people were exposed to the patient. + +All those at the clinic will be transferred to a hospital but it is unclear which medical facility. + +While no doubt in a fearful and nearvous state now, Mr. Monnig's career has often hinged largely on his physical toughness, even more so than most cops. + +The large-framed Monnig once worked as a sort of human punching bag for incoming Dallas County police recruits who learned how to use batons by beating Monnig. + +At least that was his job until 2008, when Monnig was temporarily terminated from the police force after getting seriously injured during one of his brutal training sessions. + +He was unable to work in active duty and the force was apparently not interested in giving him a desk job. + +Concerned son: Monnig's son Logan (pictured) spoke to reporters outside the family home not long after his father checked himself in with doctors Wednesday. Logan Monnig said he and his family are worried about Mr. Monnig but said 'we are not expecting him to' test positive for Ebola + +A patient attended CareNow clinic in Frisco, Texas today and was rushed to a nearby hospital after presenting with Ebola symptoms. The clinic was placed on lockdown until everyone inside can be checked by the CDC + +'Your job is basically to get beaten up by recruits,' CBS DFW said in a 2008 interview about his firing. + +'Part of it is,' he replied. 'I want it to be as realistic as possible.' + +Thanks in part to the 2008 broadcast, Monnig was rehired by the force. + +Mr Duncan, a 42-year-old Liberian national, exposed nearly 50 people to the disease in America before he was put in isolation at Texas Presbyterian. + +His fiancee Louise Troh is currently in quarantine with her 13-year-old son and two nephews and under constant monitoring by health officials over fears that they, too, could develop symptoms during a 21-day incubation period. + +Tough guy: Part of Monnig's job, at least back before 2008, was to take the physical blows dealt by Dallas county police recruits learning how to use batons + +Fired: After sustaining an injury during his extreme training sessions that kept him off his beat, Monnig was fired. However, a local CBS report that cast light on the apparent unfair treatment got Monnig his job back + +Ten people, including seven healthcare workers and three family members, are considered at high risk for Ebola after they were exposed to Duncan after he became contagious. + +Another 38 more are being monitors by the CDC for possible risk of the disease. + +Duncan's fiancee Louise Troh, who is perhaps highest at risk of catching the disease after she cared for him at her Dallas apartment while he sweated and vomited through the early staged of the disease, says she does not blame him for possibly exposing her. + +The White House said on Wednesday that extra screening for fever will be carried out for arriving aircraft passengers from West Africa, where the virus has killed nearly 4,000 people in three countries. + +The screening will start at New York's John F. Kennedy airport from the weekend, and later at Newark Liberty, Washington Dulles, Chicago O'Hare and Hartsfield-Jackson Atlanta. + +Authorities will use a non-invasive device to take the temperature of passengers and have them fill out a questionnaire created by the U.S. Centers for Disease Control and Prevention (CDC) asking for detailed information about their activities. + +A cleaning crew in bio-hazard suits decontaminated the Dallas apartment where Ebola patient Thomas Duncan fell ill almost two weeks ago. He died from the deadly virus on Wednesday + +President Obama participates in a conference call with state and local officials to discuss domestic preparedness response to the Ebola epidemic in West Africa, at the White House today","0" +"Texas deputy showing Ebola symptoms was sent into patient zero's apartment WITHOUT protection but started growing concerned when his squad car and his uniform were quarantined","A Dallas County sheriff's deputy has been hospitalized today with Ebola symptoms, a week after he went unprotected into the apartment of first patient Thomas Duncan. + +Sgt Michael Monnig went on Wednesday to an urgent-care facility in Frisco, Texas with his wife, after complaining of stomach problems. + +The deputy presented at the clinic a week after he visited the Dallas home where Duncan was staying when he developed Ebola symptoms. Sgt Monnig was at the home to deliver a quarantine order to family members. + +Neither Sgt Monnig, nor the other two health officials, Zachary Thompson and Christopher Perkins with him, were wearing protective clothing or masks despite being in the apartment as cleaning crews were going about their work in full protective gear. + +A possible Ebola patient, believed to be Dallas County Sheriff's Deputy Michael Monnig, is brought to the Texas Health Presbyterian Hospital on Wednesday in Dallas, Texas + +The sheriff's deputy arrives at Texas Health Presbyterian Hospital today via ambulance after attending an urgent-care clinic with symptoms + +Sgt Monnig walked into Texas Presbyterian Hosptial today accompanied by medics in hazmat suits + +Sgt Monnig, pictured here with his family, went to an urgent-care facility in Frisco, Texas on Wednesday with Ebola-like symptoms. His family said he was simply taking precautions + +'It was pretty scary': Monnig's wife recalled the fear she had after learning her husband was in the apartment where Duncan took ill and likely relived that fear on Wednesday + +The day after going into the apartment, Monnig and his fellow officers were told to bag up the clothes they'd been wearing. Their police cars were also taken out of commission. + +'That starts putting question marks in your mind,' Monnig told WFAA in an October 3 report. 'You know when you go home and then the next day you start hearing that equipment is being quarantined or asked to be bagged up, that you had on or were driving. + +'Then your question is, ""well, what about me?"" And so those were the questions that were raised.' + +Now the question is: Why wasn't Monnig warned before entering the home completely without protection? + +'There should be some kind of protocols as far as what kind of a response we're going to have and what kind of safety equipment we're going to have,' Christopher Dyer, president of the Dallas County Sheriff's Association, said in the WFAA interview. 'Those kinds of things didn't happen.' + +Monnig's wife Lisa echoed his sentiment. + +'It was pretty scary,' Lisa Monnig said about the day her husband entered the apartment. 'I was awake until he got home that night.' + +No doubt Monnig is now feeling that pit in her stomach again as she and her family are forced to wait out the next two days it will take to determine whether Monnig managed to catch the dreaded virus. + +Mr Duncan, 42, died on Wednesday morning at Texas Health Presbyterian Hospital, two weeks after developing symptoms of the virus. + +Sgt Monnig told medics at the Frisco clinic today that he had been in contact with first victim Mr Duncan and had not been wearing protective clothing. + +A firefighter removes red tape from a vehicle parked outside a CareNow clinic in Frisco, Texas on Wednesday. Frisco Fire Chief Mark Piland says the deputy is being treated 'out of an abundance of caution' + +A medical team in hazmat suits along with law enforcement rushed to the scene at a CareNow clinic in Frisco, Texas on Wednesday after a man turned up with Ebola-like symptoms + +The person, reportedly a Dallas County sheriff's deputy, was exhibiting Ebola symptoms today and claimed to have had contact with patient Thomas Duncan, who died from the virus on Wednesday morning + +An ambulance, driven by a firefighter-paramedic wearing a hazmat suit, carries an individual, believed to be a Dallas County sheriff's deputy, with Ebola symptoms to a hospital in Frisco, Texas on Wednesday afternoon after the person turned up at an urgent care clinic + +The CareNow clinic was immediately placed in lock-down because Monnig was exhibiting signs of the deadly virus - including feeling sick and appearing flushed with a fever. + +The CDC told MailOnline today that the person is not one of the 48 contacts being monitored, and there is no indication of any direct contact with the initial patient, Mr Duncan. + +None of the 48 individuals with verified or possible contact with the patient has shown symptoms, the CDC said today. + +Sgt Monnig's son, Logan Monnig, told CBS that his father had woken up with 'stomach issues' and had gone to the clinic as a precaution. + +Logan said family were told by the CDC that their father was not at risk of the virus, as he had only been in the apartment for 30 minutes and had not come in contact with bodily fluids. + +'We are not expecting him to' test positive for Ebola, said Logan. + +A father who had taken his teenage son to the clinic to get a flu shot on Wednesday told WFAA that the man entered the clinic with his wife, appeared flushed and was hunched over. + +Chuck Moreno said that he and his son had self-quarantined in an exam room, put on surgical masks and sprayed themselves with disinfectant. + +Sgt Monnig answered yes in a screening questionnaire to a question about travel to West Africa and is said to have contact with Duncan, referred to as ‘patient zero’. + +The Frisco patient was rushed to Texas Health Presbyterian Hosptial by ambulance after turning up at the urgent care clinic on Main Street. + +Medics at the clinic called 911 at around 12.30pm to request an ambulance for the patient. A team in hazmat suits and face masks transported the law enforcement officer. + +A hospital spokesman said: 'Texas Health Presbyterian Dallas can confirm today that a patient has been admitted to the Emergency Room after reporting possible exposure to the Ebola virus. + +'Right now, there are more questions than answers about this case. Our professional staff of nurses and doctors is prepared to examine the patient, discuss any findings with appropriate agencies and officials. + +A second person is exhibiting Ebola symptoms in Texas today and claimed to have had contact with Thomas Duncan who died from Ebola today + +A sign on the door of the apartment where Thomas Eric Duncan stayed with family warns that the unit has been quarantined by the commissioner of health on Wednesday + +Where it began: Neither Sgt Monnig, nor the other two health officials, Zachary Thompson (left) and Christopher Perkins (right) with him, were wearing protective clothing or masks. The two other men are seen here leaving the apartment where Patient Zero stayed while ill. Neither Thompson nor Perkins have reported any worrisome symptoms + +'We are on alert with precautions and systems in place. At the same time, we are caring for routine cases which are completely separate in operations.' + +The clinic was keeping everyone at the center until they are checked out by the CDC - it is unknown how many people were exposed to the patient. + +All those at the clinic will be transferred to a hospital but it is unclear which medical facility. + +While no doubt in a fearful and nearvous state now, Mr. Monnig's career has often hinged largely on his physical toughness, even more so than most cops. + +The large-framed Monnig once worked as a sort of human punching bag for incoming Dallas County police recruits who learned how to use batons by beating Monnig. + +At least that was his job until 2008, when Monnig was temporarily terminated from the police force after getting seriously injured during one of his brutal training sessions. + +He was unable to work in active duty and the force was apparently not interested in giving him a desk job. + +Concerned son: Monnig's son Logan (pictured) spoke to reporters outside the family home not long after his father checked himself in with doctors Wednesday. Logan Monnig said he and his family are worried about Mr. Monnig but said 'we are not expecting him to' test positive for Ebola + +A patient attended CareNow clinic in Frisco, Texas today and was rushed to a nearby hospital after presenting with Ebola symptoms. The clinic was placed on lockdown until everyone inside can be checked by the CDC + +'Your job is basically to get beaten up by recruits,' CBS DFW said in a 2008 interview about his firing. + +'Part of it is,' he replied. 'I want it to be as realistic as possible.' + +Thanks in part to the 2008 broadcast, Monnig was rehired by the force. + +Mr Duncan, a 42-year-old Liberian national, exposed nearly 50 people to the disease in America before he was put in isolation at Texas Presbyterian. + +His fiancee Louise Troh is currently in quarantine with her 13-year-old son and two nephews and under constant monitoring by health officials over fears that they, too, could develop symptoms during a 21-day incubation period. + +Tough guy: Part of Monnig's job, at least back before 2008, was to take the physical blows dealt by Dallas county police recruits learning how to use batons + +Fired: After sustaining an injury during his extreme training sessions that kept him off his beat, Monnig was fired. However, a local CBS report that cast light on the apparent unfair treatment got Monnig his job back + +Ten people, including seven healthcare workers and three family members, are considered at high risk for Ebola after they were exposed to Duncan after he became contagious. + +Another 38 more are being monitors by the CDC for possible risk of the disease. + +Duncan's fiancee Louise Troh, who is perhaps highest at risk of catching the disease after she cared for him at her Dallas apartment while he sweated and vomited through the early staged of the disease, says she does not blame him for possibly exposing her. + +The White House said on Wednesday that extra screening for fever will be carried out for arriving aircraft passengers from West Africa, where the virus has killed nearly 4,000 people in three countries. + +The screening will start at New York's John F. Kennedy airport from the weekend, and later at Newark Liberty, Washington Dulles, Chicago O'Hare and Hartsfield-Jackson Atlanta. + +Authorities will use a non-invasive device to take the temperature of passengers and have them fill out a questionnaire created by the U.S. Centers for Disease Control and Prevention (CDC) asking for detailed information about their activities. + +A cleaning crew in bio-hazard suits decontaminated the Dallas apartment where Ebola patient Thomas Duncan fell ill almost two weeks ago. He died from the deadly virus on Wednesday + +President Obama participates in a conference call with state and local officials to discuss domestic preparedness response to the Ebola epidemic in West Africa, at the White House today","0" +"Ebola Frisco 2014: Patient Shows Virus Symptoms After Apparent Thomas Eric Duncan Contact","Someone displaying symptoms of Ebola, who apparently had contact with Thomas Eric Duncan, showed up at a Care Now facility in Frisco, Texas, Wednesday afternoon, the Dallas Morning News reported. As of now, it's not a confirmed Ebola case. + +“The patient claims to have had contact with the Dallas ‘patient zero.’ Frisco firefighter-paramedics are in the process of transporting the patient,” a statement from Dana Baird-Hanks, a spokeswoman with the city of Frisco, said. + +Paramedics are reportedly transporting the patient, who has not yet been identified, to Presbyterian Hospital in Dallas, the Morning News reported. Staff and patrons of the facility are being examined for the deadly virus. + +A campaign to save the dog of a Spanish woman infected with the Ebola virus is heating up. Reuters + +Since Duncan was diagnosed with Ebola, there have been 5,000 false alarms in the U.S., Forbes wrote Wednesday. The Centers for Disease Controls said it received more than 800 calls a day regarding the deadly disease -- a drastic jump from the 50 calls a day it received before Duncan’s infection was known. + +Duncan, the first person in the U.S. to become sick with virus, died Wednesday. “It is with profound sadness and heartfelt disappointment that we must inform you of the death of Thomas Eric Duncan,” said a statement from Texas Health Presbyterian Hospital, where he was being treated. “He fought courageously in this battle.” + +More than 3,400 people in West Africa have been killed by the latest outbreak. The virus might have been spread through handling “bushmeat,” which is the meat of African wild animals, and contact with infected bats. + +Follow me on Twitter @mariamzzarella","0" +"Frisco: Sick patient claims to have had contact with Ebola victim","FRISCO, Texas - A patient exhibiting symptoms of Ebola who claims to have had contact with Thomas Eric Duncan showed up at a Care Now facility in Frisco Wednesday afternoon. + +City officials confirmed a significant medical response at the clinic located in the 300 block of Main Street. + +Paramedics are said to be in the process of transporting the patient, but it is unclear where. + +All staff and patrons at the facility are also being examined, officials said. + +The city has scheduled a news conference for 3:30 p.m. to release more information about the incident.","0" +"Ebola Scare in Kansas City","At about 9:30 Saturday night, a Kansas City apartment building was sealed off as a seriously ill person was taken to Research Medical Center for treatment. A source close to the situation said ""all or part of the medical facility was then quarantined."" +According to KCTV-5, the Kansas City Health Department is monitoring the patient who may have contracted a contagious virus. At this point, health officials are saying Ebola is unlikely,. +Spokesman Jeff Hershberger said it is extremely unlikely that this person has Ebola because of their travel history and lack of symptoms. It is unknown at this time what the patient is suffering from or if anyone else is sick. + + Gateway Pundit is reporting that the patient is a Nigerian woman who became ill with Ebola-like symptoms. +UPDATE: +Via KSHB -41, Dr. Rex Archer, director of Health at the Kansas City Health Department said, ""this person was supposedly in Nigeria and had come here from there but we have no evidence that they were actually where any of the other cases were."" +The patient had a 102-degree fever on Saturday night. +Nigeria has only had 20 cases of Ebola during the current outbreak according to the CDC.","0" +"Report: Nigerian Woman Quarantined in KC with Ebola-Like Symptoms (Video)","A Kansas City apartment building in the 3600 block of East Meyer Boulevard was sealed off because a person who lives there is sick with something that may be contagious, a source close to KCTV5 News says. (KCTV) + +A Kansas City TV station, KCTV-5 reported Saturday night someone was being quarantined at Rockhill Research Hospital (Research Medical Center), according to their sister station in Wichita, KWCH. + +A source in Kansas City confirmed the story to the Gateway Pundit and added some details. + +A Nigerian woman was taken to the hospital with a high fever and Ebola like symptoms. Her apartment building was quarantined, though that may have been lifted later. + +The source added the Nigerian woman initially tested negative for Ebola and was released (or set to be released) but was called back to the hospital. The source said parts of the hospital may be quarantined but the hospital is not confirming anything. + +The CDC is reportedly on the way, according to the source.","0" +"Texas Town Quarantined After Family Of Five Test Positive For The Ebola Virus","The small town of Purdon, Texas has been quarantined after a family of five tested positive for the Ebola virus. + +Purdon is located just 70 miles from Dallas, Texas, and the hospital that has cared for both American Ebola patients, Thomas Eric Duncan, and Texas nurse, Nina Pham. + +It has been verified that Jack Phillips returned from Dallas last week while on business. Shortly after arriving home, Mr. Phillips began exhibiting flu-like symptoms, but did not immediately go to the hospital. At this time his wife and children began showing similar symptoms, which provoked the family to get tested. Doctors then learned that Phillips, his wife, and three children had contracted Ebola haemorrhagic fever. + +Facts About Purdon, Texas And The Ebola Quarantine + +133 residents + +Unincorporated community in Navarro County + +Originally Known As Belle Point + +Ebola is spread through contact with bodily fluids of an infected individual + +Ebola has a 90% casualty rate in areas such as West Africa. In America the mortality rate is 50/50 + +Five people are confirmed to have the Ebola Virus in Pardon County + +CDC quarantined the area, erecting road blocks and disallowing anyone in or out of the area + +A staff member at the Texas Health Presbyterian Hospital contacted National Report with a short statement about the Ebola situation in Texas. The individual wished to remain anonymous for their own safety, and told us the following, + +“As far as we know, Jack Phillis had not come in contact with neither the late Thomas Duncan or Mrs. Phan. It is perhaps possible that he was within a close proximity of the infected parties, but it is otherwise unknown as to how Phillips was infected with Ebola. + +The CDC wasted no time sealing up the rest of the town’s denizens, and has stopped all traffic entering and exiting Purdon, TX. As of 10 Pm, Oct. 13th area has been surrounded with police and CDC officials. Communications with the locals seems to have been cut off, and press is currently awaiting an official statement from local authorities.","0" +"Ghost Ship Filled with Ebola-Ridden Rats Heading for Florida","The ship left Sierra Leone on July 13 2014 in destination of the Mexican city of Tampico. Six days after leaving the port of Freetown, the captain of the ship reported in a radio communication that three of the crew members were beginning to show distressing symptoms that suggested they could be infected with ebola, and that the ship was changing course to head towards Cape Verde to get some medical help. This was the last time that the crew was heard of, and all 17 men on board are presumed to have died in only a few days later. + +The ship could now pose an important threat to the American public, as the ship is believed to be infested with thousands of starving rats possibly carrying the ebola virus. Many of the witnesses who came across the ship over the last months, have indeed reported seeing the rodents feeding off the crew’s bodies as the ship went by. Experts fear that these animals could now spread the disease to humans and other animals on the continent, creating an uncontrolable ebola pandemic in the United States. + +The ship is believed to be infested with thousands of ebola-ridden rats, fear local health authorities + +The Guinean Luck has been reported multiple times in the Atlantic Ocean, drifting away slowly along the North Equatorial Current towards the American continent. It has been sighted almost a dozen times since November 2014, by various ships sailing north of the Antilles. It was last reported to have been seen by fishermen, only a few nautical miles North of the territorial waters of Bahamas. + +Despite their efforts, the American authorities have not been able to locate the ghost ship, but some recent satellite pictures showing the ship have enabled them to narrow the search area to approximately 400 square nautical miles (nearly 1375 km² or 530 square mile). A total of 324 coast guard ships and 32 helicopters have already been affected to the search operations, forming the largest search force ever created by the U.S. coast guard. + +Ships and officers of the U.S. Coast Guard from the entire East Coast have been mobilized in a desperate attempt to find and sink the ship before it reaches America. + +Experts and analysts estimate that the ship’s actual course and speed will bring it to land or be washed ashore in Southern Florida over the next weeks, probably near the densely populated Miami area. The authorities remain confident however, that the ship will be found and sunk before it reaches the coast.","0" +"University Bans Word ‘Freshman’ Because It’s Sexist and Promotes Rape","Elon University in North Carolina banned the word “freshman” from its website and student orientation, claiming it’s sexist and suggests that the young women might make good rape victims. + +It’s replacing the term with “first-year.” + +“The term has often been felt to refer to the vulnerableness of young women in college for the first time,” Leigh-Anne Royster, the school’s “Inclusive Community Wellbeing Director” told the College Fix. + +“Given the rates of sexual violence perpetrated against women on college campuses, it is useful to examine any use of a term that suggests that a group of people just entering college might be targets for such violence in any way,” she added. + +In fact, the word is apparently so dangerous that any orientation leader who dared to use it was immediately corrected. + +“They engrained over and over in our brains that it was supposed to be ‘first-year,’ not ‘freshman,’” sophomore orientation leader Alaina Schukraft told the Fix. “They were very adamant . . . and stressed the importance of using language that would make the new students feel comfortable.” + +Ironically, Schukraft said that multiple students approached her and said they were actually more comfortable with the word “freshman.” + +But no matter. Greg Zaiser, vice president of admissions and financial planning, insists that it will make the school a better place for women — telling the Fix that people consider “freshman” to be a “sexist” word. + +“As an inclusive community, Elon strives to incorporate language that is current and reflective of our student body,” Zaiser said in an e-mail to the Fix. + +No public announcement was made about the word switch. According to the Fix, administrators relied “largely on word of mouth.” + +— Katherine Timpf is a reporter at National Review Online.","0" +"UNIVERSITY DROPS TERM ‘FRESHMAN,’ REPLACES IT WITH ‘FIRST-YEAR’","OFFICIAL: Celebrates wider range of identities and expressions, protects young women from sexual violence + +ELON, N.C. – Elon University has dropped the term “freshman” from its vocabulary and replaced it with “first-year,” a move made official this fall and implemented in everything from its website to orientation workshops. + +The change at the small, private liberal arts college in North Carolina was done to promote inclusivity, celebrate diversity, and ensure the campus did not promote sexist stereotypes or create a hostile and unsafe environment for female students, campus officials said in interviews with The College Fix. + +Leigh-Anne Royster, director of Elon’s “Inclusive Community Wellbeing,” said in an email to The College Fix that she has been told by some that they believe the term “freshman” is outdated, and that replacing “freshman” with “first year” is a “celebration of diversity.” + +Royster stated the word “freshman” naturally insinuates a hierarchy among students on campus. She said she believes that students are viewed as younger and less experienced when referred to as “freshman.” With that, Royster stated “freshman” may contribute to sexual violence on campus because it labels the youngest students, causing them to be targets. + +“The term has often been felt to refer to the vulnerableness of young women in college for the first time,” Royster said. “Given the rates of sexual violence perpetrated against women on college campuses, it is useful to examine any use of a term that suggests that a group of people just entering college might be targets for such violence in any way.” + +Royster said she believes this change will positively impact future students at Elon and foster progress in inclusivity related to gender. + +“Using language that allows for a more inclusive understanding of gender will be important in our culture moving forward,” she said. “Moving away from language, including pronouns, that denote a gender binary will be something we see more and more as our culture evolves to celebrate a wider range of identities and expressions.” + +At this semester’s student orientation leader training, administrators made it clear that incoming students must be called “first-years.” No public announcement was made regarding this change — administrators relied largely on word of mouth to carry the news. + +Elon sophomore Alaina Schukraft, an orientation leader, told The Fix that each time an orientation leader said “freshman” in training, he or she was immediately corrected. + +“They engrained over and over in our brains that it was supposed to be ‘first-year,’ not ‘freshman,’” Schukraft said. “They were very adamant about using the correct terminology and stressed the importance of using language that would make the new students feel comfortable.” + +But when the new wording was rolled out, not all incoming students were comfortable with this change. Schukraft said multiple incoming students approached her saying they were more comfortable with the term “freshman.” + +But Greg Zaiser, vice president of admissions and financial planning, said in an email to The College Fix that the change improves the campus environment. + +Zaiser said administrators believe the change keeps with Elon’s core values, and is a more appropriate description for new students. He added some believe “freshmen” is a “sexist” term, and Elon is attempting to move away from gendered stereotypes. + +“As an inclusive community, Elon strives to incorporate language that is current and reflective of our student body,” Zaiser said in an email to The College Fix. “ ‘Freshman’ isn’t necessarily wrong, but it’s not completely applicable to Elon’s entire population, which includes internationals, transfers, spring admits, along with traditional students beginning their first year on a college campus.” + +College Fix contributor Diana Stancy is a student at Elon University and president of the Network of enlightened Women (NeW) chapter at Elon. + +Like The College Fix on Facebook / Follow us on Twitter + +IMAGE: Facebook screenshot","0" +"ESPN's Domestic Violence Panel Is Missing Something Important","Actual women. + +With ongoing outrage over the NFL's recent slew of scandals, it made perfect sense when ESPN announced it will hold a panel on domestic violence Monday night. But as the two organizations geared up this discussion about women and abuse in the world of sports, it quickly became painfully clear that women had been completely excluded from the table. + +As Esquire's Ben Collins pointed out last week, the panel will consist entirely of male commentators, while female reporters will be literally sidelined in the discussion. + +""Up to 11 men, all between the ages of 39 and 74 will sit at the table for a domestic violence discussion on ESPN. Zero women. Victims of domestic violence in America are most likely to be women aged 20-24,"" Collins wrote. + +""When the show has updates from the field — brief reports about injuries and the upcoming game — they'll cut to female sideline reporters, Lisa Salters and, on some weeks, Suzy Kolber. These people are not allowed at the table."" + +What an oversight. The utter failure to include a single woman in a discussion about domestic violence has already attracted a ton of criticism online: + + + + + + +But that's not all. While it might be easy to dismiss an incident like this as unintentional, Collins rightly points out that ESPN's track record on holding the NFL accountable is not that great. And why should it be, given the lucrative, multibillion-dollar partnership the two organizations enjoy? + +""You will not hear these words because ESPN is not a company in the business of journalism. It is an entertainment outlet that sometimes reports convenient, timely information to drive interest in future programming,"" Collins writes. ""There are 11 seats at the table at ESPN. All of them go to men. Women get their own table, but only sometimes — and ESPN has placed that table where no one can hear them."" + +This scandal has given ESPN the chance to decide whether it wants to be an outlet for responsible sports journalism or a profit-driven hype man for the NFL. And we may already have the answer.","0" +"Doubts raised over authenticity of Charlie Hebdo footage.","The killing of the french policeman is also being called into question, due to the ‘lack of blood spatter consistent with that of a close range shooting’. As shown in the freeze frame below, smoke is shown to emit from the weapon, with no impact or trauma appearing to register on the body of the victim. The decision of many news outlets to blur out the victim is being debated as evidence of complicity in what many are now calling a hoax. Forensic and ballistics expert David Mayhew commented; “If the video shows events as they actually occurred, then in my opinion it is most likely that the firearm shown is discharging blanks rather than conventional ammunition”.","0" +"Missouri Pig Brothel Dismantled During FBI Raid","Suspected for sometime by local authorities of running a pig farm functioning as an underground pig brothel, where clients paid for sexual services with the farm animals, the 67-year old farm owner was arrested with two of his sons and some 30 guests who were present to celebrate the New Year’s Eve. + +Caught in full action during the night of New Year’s Eve, the FBI raid engaged more than 16 agents in what local officials believe to be the biggest crack down on an animal brothel in American history. + +Hundreds of piglets were forced into sexual acts with clients of the pig brothel + +Local authorities fear a recrudescence in sexual deviant behavior with animals in the region since this is the third animal brothel to be closed down in recent months in the area. + +The farmer and his sons could spend up to five years in prison expect legal experts.","0" +"Fidel Castro Rumors Sweep Internet, but No Sign in Cuba","Social media around the world have been flooded with rumors of Fidel Castro's death, but there was no sign Friday that the reports were true, even if the 88-year-old former Cuban leader has not been seen in public for months. + +Similar speculation has swept across Cuban expatriate communities repeatedly over the decades, particularly after a serious illness forced him to step down from duties as president in 2006, handing over leadership to his younger brother Raul. + +The new wave was prompted in part by Fidel Castro's failure to comment after the U.S. and Cuba declared on Dec. 17 that they would move to restore full diplomatic relations broken a half century ago. + +The chatter appeared to pick up when some media noted Thursday that Castro had not been seen in public in a year. He last appeared on Jan. 8, 2014, at an art exhibition in Havana, ending nine months out of public view. + +The most recent official photographs of Castro came out of a private meeting with Venezuelan President Nicolas Maduro on Aug. 21. He was also photographed with the Chinese and Russian presidents in July. Castro was last heard from on Oct. 18, when he published an editorial about Ebola. + +By Friday, Cuba-related Twitter accounts were ablaze with speculation, fueled in large part by reports on news websites such as Diario de Cuba and Diario las Americas that Cuba had scheduled a news conference, possibly to discuss Castro's health. + +The rumors were further stoked when respected Italian newspaper Corriere Della Sera reported on its website that Castro had died. It quickly pulled the report back, however. + +Cuban officials told news media in Havana that no press conference had been called, and there were no obvious signs of official preparations for mourning.","0" +"Fidel Castro Is Dead, According to Viral Twitter Rumors","No one has died more times than Fidel Castro. +But yesterday, rumors began flying anew in the Cuban-American community -- and, of course, on Twitter -- that the Cuban leader has finally bitten the dust and that a possible news conference will announce his demise today. Could the speculation finally be true this time? + +The reports began circulating late yesterday around Twitter: + + +So far there's nothing substantiating all the buzz. Cuban media outlets have denied any news conference is scheduled, and the hype also comes ""suspiciously close"" to the actual death of Fidel Castro Odinga, the 41-year-old son of a Kenya opposition leader, as the Daily Mail reports. + +There is another reason the rumors may be swirling: According to Fox News Latino, yesterday marked one year since the 88-year-old revolutionary was last seen in public. + +Let's hope Fidel himself jumps on Twitter soon to deny -- or confirm? -- the rumors.","0" +"WATCH: Twitter catches fire amid rumors of Fidel Castro’s death","Fidel Castro was pronounced dead on Twitter sometime around 3:59 p.m. on Thursday. It was an unconfirmed rumor, of course, but it was announced confidently so many folks assumed it was true — or at least worthy of retweet. + +Then separate rumors started about Raul Castro calling a press conference at 9 a.m. or 11 a.m. today, allegedly to announce his brother’s death. + + +As South America’s Twittersphere caught fire, some started questioning whether the users in their feed were even talking about the right Fidel Castro. After all, Al Jazeera reported on Jan. 4 that the Fidel Castro Odinga, the son of Kenya’s main opposition leader, died in Nairobi last weekend after a night of drinking with friends. Could it be that Twitter users were confusing the dead Kenyan man with his Cuban namesake? + + +Twitter heatmap shows mention of “Fidel Castro” from 10 a.m. Thursday- 8 a.m today (GMT). + +An overly excited Wikipedian edited the entry for Cuba’s Fidel Castro to say “this article is about a person who has recently died.” Moments later, the Castro’s Wikipedia entry was reverted back and to his undead version. + +By 8 p.m., media outlets around Latin America were reporting “strong rumors” about Castro’s death and the alleged forthcoming announcement by Cuban officials. + + +But on the island, where folks are more accustomed to rumors of Castro’s death, the situation seemed less urgent. Journalists in Havana said they were aware of the rumors, but weren’t finding echo on the streets of Cuba. It’s true Castro hasn’t been seen in public in a year, but rumors of his death — as Mark Twain might have said — appeared to be greatly exaggerated. + + +As journalists turned to each other for answers, Cuba watchers tuned into state television.When Castro dies, that’s where it will be announced unequivocally.","0" +"#RIPFidel fuels false rumors of Cuban leader's death after another Fidel Castro dies","Rumors of the death of former Cuban leader Fidel Castro, who has not been spotted in months, went into overdrive on Friday night due in part to an unrelated death thousands of miles away. + +As the #RIPFidel hashtag began to spread online, it became clear that rumors of Castro's death were being fueled by the high-profile death of a different man with the same name, half a world away. + +Fidel Castro Odinga, the son of prominent Kenyan politician and former prime minister Raila Odinga, reportedly died on Jan. 4. His Cuban namesake, however, still appears to be very much alive. + +It is with profound sorrow that my wife Ida and I announce the untimely passing of our eldest son, Fidel Castro Odinga. + +— Raila Odinga (@RailaOdinga) January 4, 2015 + +Thousands of mourners took to social media with the hashtag #RIPFidel, as they paid their final respects to the Kenyan Fidel ahead of his funeral Saturday, likely fueling rumors about Cuban Fidel's death. + +Mourners flock at Jaramogi Odinga Oginga University to give Fidel a send off #RIPFIDEL #FarewellFidelCastro pic.twitter.com/gZYa4joWjH + +— EBRU AFRICA NEWS (@ebruafricanews) January 10, 2015 + +Today, we as the Odinga family held a requiem mass for our late son Fidel Castro at the All Saints Cathedral. pic.twitter.com/pCawAqVWwR + +— Raila Odinga (@RailaOdinga) January 8, 2015 + +Fidel Castro Odinga is a high-profile person in Kenya because of his father's political status, so many used social media in the wake of his death to express their condolences, including current Kenyan President Uhuru Kenyatta. + +My condolences go out to the former PM @RailaOdinga and his family. This is a big loss not only to you & your family but the entire country + +— Uhuru Kenyatta (@UKenyatta) January 4, 2015 + +Reports of Fidel Castro's death have been a staple of the international rumor mill for years, with speculation on the former Cuban leader's status bubbling up every few months. + +There is no indication that the 88-year-old Castro is on his deathbed. However, he last appeared in public on Jan. 8, 2014 at an art exhibition in Havana, ending nine months out of public view. + +The most recent official photographs of Castro came out of a private meeting with Venezuelan President Nicolas Maduro on Aug. 21, 2014. He was also photographed with the Chinese and Russian presidents in July. Castro was last heard from on Oct. 18, when he published an editorial about Ebola. + +In 2006, a serious illness forced him to step down from duties as president, and hand over leadership to his younger brother Raul Castro. + +Some of the speculation was prompted by Castro's failure to comment after the U.S. and Cuba declared on Dec. 17 that they would move to restore full diplomatic relations broken a half century ago. + +On Friday, Cuba-related Twitter accounts were ablaze with speculation, fueled in large part by reports on news websites, such as Diario de Cuba and Diario las America, that Cuba had scheduled a news conference, possibly to discuss Castro's health. + +One CNN journalist added fuel to the fire, tweeting that a speech from Raul was imminent, although he later retracted the information, citing ""bad info from Reuters."" + +Intervención de Raúl Castro. Estamos verificando información + +— Patricia Janiot (@patriciajaniot) January 9, 2015 + +Raul Castro expected to address Cuba soon amid speculation about the health of #FidelCastro. + +— Mark Bixler (@CNNmarkbixler) January 9, 2015 + +UPDATE - not expecting a Castro announcement - bad info from Reuters. + +— Mark Bixler (@CNNmarkbixler) January 10, 2015 + +Cuban officials told news media in Havana that no press conference had been called, and there were no obvious signs of official preparations for mourning. + +Additional reporting by The Associated Press + +Have something to add to this story? Share it in the comments.","0" +"FIDEL CASTRO DEATH WATCH: RUMORS HEAT UP, CUBA DENIES","Cuban dissidents and Cuban-American media are reporting that Havana is plagued with the most serious rumors in months that former dictator Fidel Castro has died, after the one-year anniversary of Castro’s last public appearance transpired without fanfare on Thursday. + +The rumors began to circulate almost immediately after President Barack Obama announced that the United States would yield major concessions to the Cuban government in exchange for the freedom of USAID worker Alan Gross, jailed for attempts to bring Internet services to Jewish Cubans. As Fox News Latino reports, Fidel Castro made no public comments on the matter, triggering a wave of rumors in Cuban dissident media. Castro has previously commented on a number of current events, including blaming the United States and the Mossad, the Israeli intelligence service, of creating the Islamic State terrorist group in September. + +One dissident blogger in particular, Yusnaby Pérez, exacerbated rumors by writing about them in a Spanish-language post titled “Has Fidel Died?“, in which he detailed changes in behavior from neighborhood communists who had previously been loud and fervent in their displays of support for the Castros, particularly on January 1, the anniversary of the Revolution: + +This January 1st, my neighbor Mercy did not hang her “VIVA LA REVOLUCIÓN” sign, as usual, at the entrance to her house. How strange! It is the first year since I can remember that neither Fidel nor my neighbor’s odious sign–with Soviet font–appears. + +Pérez tweeted that, almost immediately after publishing the blog post, the Cuban government shut down his entire page, at least within Cuba. His Twitter account appeared unscathed, however, where he posted images of Cubans wearing American flag leggings after the announcement of President Obama’s concessions to the Castros. + +Rumors strengthened this week, however, as the anniversary of Castro’s last appearance approached. News outlets in Miami, the de facto capital of the Cuban diaspora, reported this week that the Cuban government had called for a press conference today to follow up Castro’s year-long absence with an update, many speculating that they would announce Castro’s death. The Cuban Foreign Ministry denied that any such press conference was scheduled for today, however, or that they had any major news to break. Instead, they noted that there was no record of an email or text message sent out to convene reporters, as is customary. + +But dissidents continue to report strange incidents that give fuel to the rumor that, if not dead, Castro is close to death. Miami media professor Carlos Peñalosa reported that rumors had not been abated by the Cuban government message, and that “[Venezuelan President Nicolás] Maduro must be on his way to Havana”: + + +Yusnaby Pérez also reports that there are “strong” rumors that Raúl Castro called the socialist Venezuelan president urgently to Havana, another alleged sign that Castro has died: + + +Maduro had traveled to China to ask the Chinese government for financial aid, as the Venezuelan economy is collapsing under his socialist price controls and suffering due to the extremely low international prices of crude oil. And despite the rumors, Venezuelan state media reported that he landed in Iran today, with no apparent emergencies to attend to on the Western Hemisphere. Nonetheless, Venezuelan opposition media are reporting that his departure from China was indicative enough of a route back to Cuba. + +While there are no concrete answers to whether the Cuban government is hiding either the impending or already occurring death of the leader of the communist revolution, the Daily Mail has a theory: that Cuban dissident media has confused the former dictator with Fidel Castro Odinga, the son of a prominent Kenyan politician who died this week.","0" +"Hundreds mourn the 'death' of Fidel Castro after rumours sweep Twitter (but are they confusing him with recently departed Fidel Castro Odinga from Nairobi?)","Twitter is abuzz with rumours that Cuba's former communist leader Fidel Castro has died, although the timing is suspiciously close to the death of another high-profile person who shares his name. + +While reports of the death of Cuba's 88-year-old former leader could be true, there has been no official confirmation and his death has been mistakenly claimed on social media many times in the past. + +Also casting doubt on today's rumours is the possibility it has been confused with the recent death of the son of Nairobi's opposition leader, named Fidel Castro Odinga, 41, who died only days ago. + +Former Cuban leader Fidel Castro, pictured during a speech in 2003. Twitter is abuzz with rumours he has died, but it remains to be seen if they are correct + +However, speculation is rife that the former leader of Cuba has died after Venezuelan media reports the Cuban Government has called for a press conference with the international media today. Venezuela and Cuba have fostered a close relationship for decades. + +The report in the Diario de Cuba, didn't specify a time or subject for the press conference, saying that the Cuban government's press office wouldn't give out the information.. + +It has also been claimed Venezuelan president Nicolas Maduro has rushed to Havana, adding some substance to the rumours that Castro's death could be announced. + +Castro, who passed on Cuba's leadership to his brother Raul in 2008, was announced Prime Minister of Cuba after overthrowing the government in 1959 and under his rule turned it into a one-party state. + +Fidel Castro, dressed his famous green military uniform, pictured during a public meeting in Havana in 1990 + +Fidel Castro smokes a cigar during a news conference in Havana in 1961 - two years after he overthrew the Batista government + +Cuba's Fidel Castro (pictured left in 1976 and right in 1978) ushered in a long period of communism to the tiny island in what developed into a highly antagonistic relationship with the U.S. + +He has lived in increasing seclusion from the outside world ever since he retired from the leadership amid speculation that his health was suffering. + +It is understood he was recently being cared for by his wife and by a team of nurses. Once an enthusiastic food connoisseur, he has long since stopped visiting Havana restaurants. + +Today his former Lieutenant Colonel Hugo Perez Silva told various outlets: 'Fidel is waiting for the right moment, because he is a great prophet who knows the right moment to say what needs to be said.'","0" +"Rumors Of Fidel Castro's Death Circulate After Prolonged Absence From Public Life","Once again rumors of the death of former Cuban leader Fidel Castro have spread across the exile community and across social media. + +El Diario de las Américas, a Florida-based publication read mostly by Cuban exiles, reported Thursday that the Cuban government had called a press conference amid speculation about Castro’s health. The Cuban government later disputed the report, saying no such press event had been planned, according to AFP’s correspondent in Havana. + +The Cuban government’s lack of transparency and the lack of an independent mass media on the island have long provided fertile ground for rumor’s of 88-year-old Castro’s death since he fell ill in 2006. + +Since the reports on Thursday Twitter has been abuzz with rumors of his death, though they have not yet been confirmed. + +Twitter is saying #FidelCastro is dead. Twitter says people are dead all the time though. Let me not get my hopes up. #CubanAmerican + +— MISS JESS™ (@M1SS_J3SS) January 9, 2015 + +As Univision news anchor Jorge Ramos warned, this is not the first time Fidel Castro’s alleged death has taken over the internet. In 2012 rumors of his death began circulating after news that Venezuelan doctor, Jose Rafael Marquina, said the former leader had suffered cardiac arrest and was in a vegetative state. + +“Careful. Remember that here in Miami, almost like a ritual, Fidel Castro is killed several times a year” Ramos wrote on Twitter. + +Thursday marked one year since Castro’s last public appearance, according to Fox News Latino. His absence at major events like the 56th anniversary this week of Castro’s entry into Havana after the victory of the Cuban Revolution or the return last month of three Cubans convicted of spying in the U.S. have led some to believe that his health has worsened. Castro has yet to comment on the historic resumption of diplomatic relations with the United States for the first time since 1961, announced by both governments last month. The most recent ""Reflection,"" as Fidel Castro's columns are called, appeared in October 2014. + +Venezuelan President Nicolás Maduro was the last head of state to meet with Castro in August 2014 and published photos of their meeting. Maduro stated that he found Castro had an “impressive lucidity, an impressive train of thought and exceptional wisdom.” + +Adding to the confusion, Kenyan opposition leader Raila Odinga’s son, Fidel Castro Odinga, was found dead in his home in Nairobi on Jan. 4. + +Correction: An earlier version of this article stated that Fidel Castro's last column was published in August 2013. It was actually published in October 2014.","0" +"Rumors about Fidel Castro’s death again circulate on the Internet","MEXICO CITY — Rumors about the death of Fidel Castro — an age-old ritual for Cuba-watchers — once again began circulating on and off the island this week. + +It’s true that Castro hasn't been seen in public in about a year, and it’s been a few months since one of his last columns were published. Castro, 88, has not said one public word about the historic announcement by President Obama last month about his goal of moving toward normal relations with Cuba after a half-century Cold War stand-off. + +Twitter went wild Thursday night with speculation about his demise. Why? There are rumors about that, too. One of them is that another Fidel Castro, this one the son of a prominent Kenyan politician, died a few days ago (Fidel Castro Odinga of Nairobi), and maybe this was all a social media mash-up of mistaken identity. + +Also, an Argentine Web site reported that foreign press in Havana had been summoned to a news conference — presumably to announce the huge news — but this turned out to be false. On the island, there was more talk this morning that Fidel’s brother, current President Raul Castro, would be speaking today at noon, but that came and went in silence. + +Instead, Cuban state media has been promoting a round-table interview with the three members of the “Cuban 5” who were released from U.S. custody as part of the prisoner swap. + +The Cuban government hasn’t spoken one way or the other about Fidel Castro’s health in recent days.","0" +"Insiders Claim Steel Apple Watch to Start at $500, Gold at $4,000","When Apple unveiled its Apple Watch, the company said the starting price would come in at US$349, but insider sources are claiming the stainless steel version will start at $500. Those sources also say the high-end gold Apple Watch Edition will start between $4,000 and $5,000, which is lower than many have been expecting. + +Apple's mid-range smartwatch will likely start at $500Apple's mid-range smartwatch will likely start at $500 + +Assuming the sources are correct, that pegs the anodized aluminum Apple Watch Sport as the lower-priced $349 model. + +The anonymous sources, speaking with the French site iGen (English translation), also said Apple will ship its smartwatch in time for Valentine's Day in February. While a February release would be nice because it would get Apple Watch on consumer's wrists earlier, doesn't fit with Apple Senior Vice President of Retail Angela Ahrendts comments saying the smartwatch will ship in Spring 2015. + +Apple Watch is a smartwatch device with sensors for tracking fitness activities and heart rate. It links to your iPhone to display alerts and messages, lets you reply to messages, shows turn-by-turn directions, learns your fitness routine and offers suggestions for improvement, and more. Three models in two sizes with multiple band options will be available when Apple Watch ships. + +Hopefully Apple will release Apple Watch earlier in the year instead of some time in Spring, because even though products like Microsoft's new Band and Fitbit's just announced Surge aren't direct competitors, they are enticing enough to draw away some sales. Waiting until Spring could cost Apple some momentum, too. + +iGen has been accurate in the past with Apple information, so they may be right on the pricing, but we're going with Angela Ahrendts on the release time frame because she's clearly in a good position to know when her own company's products will ship.","0" +"Bin Laden Shooter Rob O’Neill Mistakenly Attacked By Street Thugs Seeking To Collect Debt From Neighbor","BUTTE, Montana - + +Robert O’Neill, the former United States Navy SEAL who shot and killed Osama Bin Laden, had his home mistakenly invaded by members of a street gang this morning shortly after 1AM. O’Neill was uninjured, the five intruders all suffered injuries and remain hospitalized, but are expected to make a full recovery. Their names were not released in anticipation of the oncoming media storm. + +Butte Police Commissioner Bartholomew S. Harrington told members of the Associated Press in a brief press conference that the five men, part of a local street gang connected with the infamous Crips, were seeking to collect on a drug debt and invaded the wrong house, with the intended target just so happening to be the next door neighbor of O’Neill’s. + +“Mr. O’Neill had just turned in for the night, but was awoken by a loud crash when his backdoor was abruptly kicked in. As the five thugs ran aimlessly through the home, Mr. O’Neill used silent hand-to-hand combat tactics to individually disarm them of their weapons. Once Mr. O’Neill had taken down the five men and secured his home, he brewed a pot of coffee and called the police station. Those boys sure did find the wrong house!” commissioner Harrington said as he chuckled. + +O’Neill had little to say on the matter when Butte Daily Times journalist Kevin Williamson interviewed the celebrated war hero. + +“It was nothing really. Those kids didn’t have their mission planned out properly and hit the wrong target. I hated to break their wrists and dislocate each of their knees like I did, but it was necessary in order to immobilize the invasion. I hope they get the money that is owed to them once they get out of jail and decide to live better lives. My main concern is getting my back door fixed. Those boys really did a number on the door jamb,” O’Neill stated. + +The neighbor who was the intended target seems to have abandoned home and has not been found by police. According to the men in custody, the debt was over a $50 bag of marijuana.","0" +"Missing Nuke In Colorado Sparks Intense Russian Fears","The Foreign Intelligence Service (SVR) is reporting today that President Putin’s order to begin deploying tactical nuclear weapons throughout the Crimean Federal District is “intensely/directly related” to a “missing”, and believed stolen, low-yield atomic cannon shell from its storage bunker in Fort Carson, Colorado, which is a United States Army installation located near the city of Colorado Springs. + +According to the SVR, the atomic weapon missing from Fort Carson has been identified as a W48 nuclear artillery shell that measures 155 mm (6.1 inches) in diameter and 845.82 mm (33.3 inches) long. + +This report notes that the W48 was produced in two models, Mod 0 and Mod 1, which weighed 53.5 and 58 kg (118 and 128 pounds) respectively and have an explosive yield equivalent to 0.072 kiloton (72 tons of TNT). + +Though the US had reported that all of their W48 nuclear shells had been “retired” by 1992, this report says, the SVR has long noted their continued “use for training” by US Army 4th Infantry Division forces headquarter at Fort Carson and under the command of North American Aerospace Defense Command (NORAD) forces operating from the Cheyenne Mountain nuclear bunker complex, all of whom are located in El Paso County, Colorado. + +The specific US weapons platform designed to fire the W48, this report notes, is the Paladin M109A6 155mm Artillery System [3rd photo left] which is currently operated by forces belonging to the 1st Brigade Combat Team of the 4th Infantry Division. + +Over the past few days when this W48 nuclear shell “disappeared”, this report continues, the forces of the 1st Brigade Combat Team were involved in training exercises with the 1st Battalion of the 66th Armored Regiment at Fort Carson ahead of their planned deployment in the next few weeks to the Fort Irwin National Training Center, in California, which will span much of November, after which they will be prepared to deploy to combat worldwide. + +US media reports about this missing W48 nuclear shell are “nonexistent”, this report further notes, other than their noting that Fort Carson has been put on a “total lockdown” as US military forces there continue their search for what they call a lost ""sensitive item"", a term they use that refers to gear including weapons, ammunition and night vision goggles - items that cause high-level concern when missing. + +These media reports further report that whatever is missing, it must be small enough to fit in a car causing Fort Carson security officers to spend about two hours inspecting all vehicles leaving Fort Carson's gates yesterday and their spokesman stating: “As part of random searches at the gate, we are conducting outbound vehicle searches in order to prevent the unauthorized removal of government property from the installation.” + +Of critical concern to the Kremlin regarding this missing W48 nuclear shell, SVR intelligence analysts in this report state, is that if fits nearly exactly to the strange and mysterious war game sprung on world leaders this past March by President Barack Obama that he named “nukes on the loose” and involved a terrorist attack with an atomic “dirty bomb” that takes place in the financial heart of an unnamed but Western metropolis. + +London’s Telegraph News Service in their report on this “nukes on the loose” war game further noted: + +“David Cameron joined Barack Obama, Angela Merkel and Xi Jinping and other world leaders to play a ""nukes on the loose"" war game to see how they would cope with a terrorist nuclear attack. The German chancellor grumbled at being asked to play games and take tests with the Prime Minister, US and Chinese presidents around a table with dozens of heads of state at a nuclear summit in The Hague. Her complaints were overruled because Mr Obama was keen on the idea and in on the surprise.” + +Of equal concern to the Kremlin, this report continues, are that these events are occurring as predicted by former US Assistant Treasury Secretary Dr. Paul Craig Roberts who this past June warned that Obama regime was planning for a preemptive nuclear attack. + +In his warning Dr. Roberts stated: “Washington not only has war plans for launching a preemptive nuclear attack on Russia, and also possibly China, but Washington has a cadre of people who advocate nuclear war. We have people running around Washington saying things such as ‘What’s the good of nuclear weapons if you can’t use them.” + +With the “suicidal tendencies” of the Obama regime becoming more apparent by the day, the SVR in this report grimly concludes, Russia’s near record de-Dollarization efforts, when coupled with the “secret deal” between the US and Saudi Arabia to destroy Syria, point towards a truly tragic global outcome as the American-backed Western economy is near collapse…and all who oppose them will surely suffer their wrath….including the 1.2 million of their own citizens they currently have under surveillance and targeted for destruction. + +October 12, 2014 © EU and US all rights reserved. Permission to use this report in its entirety is granted under the condition it is linked back to its original source at WhatDoesItMean.Com. Freebase content licensed under CC-BY and GFDL. + +[Ed. Note: Western governments and their intelligence services actively campaign against the information found in these reports so as not to alarm their citizens about the many catastrophic Earth changes and events to come, a stance that the Sisters of Sorcha Faal strongly disagrees with in believing that it is every human beings right to know the truth. Due to our missions conflicts with that of those governments, the responses of their ‘agents’ against us has been a longstanding misinformation/misdirection campaign designed to discredit and which is addressed in the report “Who Is Sorcha Faal?”.]","0" +"Saudi Arabia's national airline planning to introduce gender segregation on flights","After a number of complaints from passengers about ""random males"" being seated next to their wives, Saudi Arabia's national airline is looking in to segregating their flights. + +Saudi Arabia's national airline, Saudia, will order its staff to keep men and women seated separately on flights from now on after passengers complained about the lack of segregation on their flights. + +The Emirates247 news website reported that the airline, which already complies with many of the religious practices of Islam including not offering alcohol or dishes that contain pork on their flights, have decided to separate men and women on board, unless they are close relatives. + + +Abdul Rahman Al Fahd, Saudia's assistant manager for marketing, said that ""there are solutions to this problem…we will soon enforce rules that will satisfy all passengers"". According to RT.com, Saudia is not the first airline to encounter these issues after Israeli carrier El Al faced delays to a flight back in October as Orthodox Jews refused to be seated next to women on the plane, while Delta have also faced a similar issue, both occurring on flights between Tel Aviv and New York.","0" +"Saudi Arabia May Be Taking Misogyny to the Skies","The calendar may have just flipped to 2015, but Saudi Arabia is partying like it's 1755. + +The Daily Mail reports that Saudia, the kingdom's national airline, will introduce gender-segregated flights. Except close relatives, men and women flying on Saudia can reportedly look forward to assigned seating based on their naughty bits. + +The discriminatory practice stems from multiple complaints lodged by male fliers who were unhappy that other men were allowed to sit next to their wives and female family members. Some men also objected to the conduct of a female flight attendant, which they deemed too ""flirty."" + +The change was first reported by Gulf media outlets, according to the Daily Mail. ""There are solutions to this problem,"" Saudia assistant manager for marketing Abdul Rahman Al Fahd told Ajel, a Saudi Arabian newspaper. ""We will soon enforce rules that will satisfy all passengers."" + +The airline will apparently include orders for flight-booking staff on the ground to make sure men and women are separated, Emirates247 reports. According to Mashable, however, a marketing manager for the airline is denying their plans to segregate passengers. + +Saudia already follows a variety of religious practices onboard, including the prohibition of alcohol and pork dishes and reading a Quran verse before takeoff. The airline also chooses not to hire Saudi women to work as cabin crew. + + +Source: Getty +Similar complaints have been heard on flights traveling to Israel. In September, a flight headed to Tel Aviv from New York was delayed because several ultra-Orthodox Jewish men wouldn't sit next to women who weren't family members; more recently, a Delta flight was delayed for half an hour because ultra-Orthodox men refused to be seated next to women, and other passengers wouldn't change seats with them. + +One Chicago woman started a petition on Change.org to stop the practice of forcing women to change seats, arguing that ""one person's religious rights do not trump another person's civil rights."" + +She's right, and the same could be said of discriminatory rules like those that Saudia reportedly plans to introduce. But given its already troubled history of the treatment of women — it was ranked the third-worst country in the Arab world for women — these new guidelines unfortunately appear to be more of the same. + +Mic has reached out to Saudia for comment but received a message indicating that the company's inbox was full. We'll update if we hear back.","0" +"Saudi Airline Considering Separating Passengers By Gender","Saudi Arabia still doesn’t know what year it is. + +Saudi Arabia’s national airline, Saudia is allegedly considering seating male and female passengers apart from each other, according to Emirates247. The airline has cited complaints from male passengers who don’t like unknown men being seated next to their wives when they fly. Saudia assistant manager for marketing Abdul Rahman Al Fahd said, “There are solutions to this problem…we will soon enforce rules that will satisfy all passengers.” The airline will supposedly begin having airport staff assign separate seating for men and women, unless they are closely related. + +It’s not only Muslims that are concerned over seating assignments, but also Orthodox Jews. An El Al Airlines flight in September from New York to Israel was delayed because some men refused to be seated next to women… + +According to a post on Mashable, a marketing manager for the airline is denying their plans to segregate passengers. However, we should be cautions here — companies often deny they’re working on a new product or procedure, and then all of a sudden it’s introduced as a “surprise.”","0" +"Saudi national airline may introduce gender segregation on its flights","Saudi Arabia’s national airline carrier is planning to introduce gender segregation aboard its flights following complaints from passengers who refused to have random males seated next to their wives, the Kingdom’s media report. + +Airline company Saudia will order its staff to keep men and women separated onboard, unless they are close relatives, the Emirates247 news website reported. + +“There are solutions to this problem…we will soon enforce rules that will satisfy all passengers,” Saudia assistant manager for marketing Abdul Rahman Al Fahd said, according to Saudi daily Ajel. + + +Saudia's traveling policies are already in accord with the strict Islam practices of Saudi Arabia. For instance, in addition to the routine boarding announcements at the Kingdom’s airports, a prayer or verse from the Quran is read prior to take off. Furthermore, international flights usually have a specially designated men’s prayer area to accommodate 5 daily prayers. In addition, the airline does not offer any beverages or dishes which contain alcohol or pork products. And the onboard entertainment menu does not offer any movies with adult content. + + +The Kingdom itself is infamous for gender segregation in everyday matters of society. For instance, women typically require male guardian approval to travel or work outside of the home. Saudi women are also not employed as stewardesses on Saudi Arabia’s national carrier. That role is reserved for women of other nationalities. + +Ironically enough, Israel too is battling the same problem, as many ultra-orthodox Jews refuse to share their transit time with female companions. A flight from New York to Tel Aviv was delayed by half an hour in late December after a group of male Jewish passengers onboard a Delta flight refused to sit next to women. + + +In October, on the eve of the Jewish festival Rosh Hashana, ultra-Orthodox (Haredi) men left the plane before take-off, also between New York and Tel Aviv, again refusing to sit next to women. In an incident in September, Israeli carrier El Al flight was postponed by 11-hours after a group of Haredi passengers refused to sit next to women. + +READ MORE: Israeli airline criticized over Orthodox Jews ‘bullying’ women passengers + +Last September an Israeli campaign, seeking to put a stop to the segregation stalemate started an online campaign on Change.org, entitled, ""Ultra-Orthodox passengers refuse to sit next to women on El Al flights"" + +""Why does El Al Airlines permit female passengers to be bullied, harassed, and intimidated into switching seats which they rightfully paid for and were assigned to by El Al Airlines? One person's religious rights does not trump another person's civil rights,"" the petition said.","0" +"Saudi airline, Saudia, to ban gender-mixing","Saudi Arabia’s national carrier Saudia intends to ban gender-mixing aboard all its flights in line with rules enforced by the conservative Gulf kingdom. + +The airlines said it decided to act following recurrent complaints from passengers objecting to have males seated next to their wives and other female family members. + +“There are solutions to this problem…we will soon enforce rules that will satisfy all passengers,” Saudia assistant manager for marketing Abdul Rahman Al Fahd said, quoted by the Saudi Arabic language daily ‘Ajel’. + +He did not elaborate, but the paper said it would include instructions to flight booking staff at the Gulf kingdom’s airports to ensure males and females are separated aboard Saudia’s flights unless they are closely related.","0" +"Saudi Arabia airline segregation: Saudi airlines to assign seats based on gender","Saudi Arabia airlines has a new passenger plan: Segregation. The Arab state’s national airlines plans to introduce the gender segregation, proving just how far behind the western Asian nation is when it comes to human rights. Complaints were reportedly received by the airlines of men sitting next to their spouses. In Saudi Arabia, one of the very few countries that have rejected adoption of the UN's Universal Declaration of Human Rights, it’s customary for a female to walk a few feet behind her male counterpart. + +Writes RT.com on Jan. 2: “Airline company Saudia will order its staff to keep men and women separated onboard, unless they are close relatives, the Emirates247 news website reported. ‘There are solutions to this problem…we will soon enforce rules that will satisfy all passengers,’ Saudia assistant manager for marketing Abdul Rahman Al Fahd said, according to Saudi daily Ajel.” + +The proposed rule from the Gulf kingdom is in line with strict interpretations of Islamic practices. The complaints were allegedly aired by single, Saudi men who saw other married men sitting directly next to their spouses or female strangers. The airlines has issued an updated set of regulations “to flight booking staff at Gulf airports to keep these new rules in place,” writes the Daily Mail. + +The carrier already has number of Islamic guidelines in place – the airline does not offer alcohol (or pork dishes), a prayer from the Quran is uttered before the flight leaves the tarmac, and some flights have an area on the plane designated as a “male prayer zone.” The airlines also will not hire any women from Saudi Arabia – they are employed from surrounding countries only. + +The Daily Mail picks up the story: The country is known for its gender segregation, with women requiring a male guardian approval to travel or work outside of the home. In public spaces such as restaurants, beaches, amusement parks or banks, women are required to enter and exit through special doors. Women who are seen socializing with a man who is not a relative can even be charged with committing adultery, fornication or prostitution. + +UK’s ""The Week,"" in September, published an article entitled Eleven things women in Saudi Arabia can't do. While not the case in all parts of the country, the article says women are unable to walk without a male chaperone, vote, swim, drive, or try on clothes in a store, among other restrictions.","0" +"Gill Rosenberg, Canadian citizen, reportedly captured by ISIS in Syria","The federal government is working to confirm reports that Gill Rosenberg, a Canadian citizen, has been captured by Islamist extremists in Syria. + +According to the Jerusalem Post, websites ""known to be close"" to ISIS extremists reported the capture of the Israeli-Canadian woman, who joined Kurdish fighters overseas, on Sunday. + +""Canada is pursuing all appropriate channels"" to seek further information and is in touch with local authorities, a spokesman for the foreign ministry said on Sunday. + +The newspaper said the websites give few details on the alleged capture, only that it occurred after three suicide attacks on sites where Kurdish fighters were holed up. + +Clashes between ISIS and Kurdish troops have largely focused on the Syrian city of Kobani, near the Turkish border. + +The now-notorious al-Qaeda splinter group is currently in control of large swaths of territory in both Syria and Iraq. + +Messages of concern were posted Sunday on a Facebook profile belonging to a Gill Rosenberg. An earlier message asked for advice on joining the Kurdish army.","0" +"Unconfirmed reports claim Canadian-Israeli Gill Rosenberg captured by ISIS","A Canadian-Israeli woman who has joined the ranks of the Kurdish militias fighting Islamic State in northern Syria has been taken captive by ISIS fighters, blogs and Islamist websites thought to be close to the militant group reported. + +A blog considered to be one of the Islamic State's media arms reported that several female fighters who fought alongside the Kurds have been captured, among them Gill Rosenberg. According to the report, prior to their capture Islamic State fighters made three suicide bombing attacks against Kurdish outposts, killing some and capturing many others. + +According to Israel Radio, Kurdish sources denied the reports, saying Rosenberg wasn't in the area when it was attacked. + +Gill Rosenberg, 31, a resident of Tel Aviv, joined the Kurdish troops against Islamic State in northern Syria earlier this month. According to reports, Rosenberg said she had contacted Kurdish fighters over the Internet before traveling through Iraq to train at one of their camps on the Syrian border. + +According to Walla, Rosenberg immigrated to Israel from Canada in 2006, leaving behind a career as a civilian pilot, and served for two years in the Israel Defense Forces. In 2009, she was extradited to the United States and jailed over an international phone scam, one of her former lawyers said. + +Israel Radio aired an interview with Rosenberg earlier in November in which she said she had travelled to Iraq, was training with Kurdish guerrillas and would fight in neighbouring Syria. + +""They are our brothers. They are good people. They love life, a lot like us, really,"" she told Israel Radio, explaining her decision to enter the combat zone in northern Syria. + +A source in the Kurdistan region said Rosenberg, known in Israel by her Hebraised first name Gila, was the first foreign woman to join Syrian Kurds in battle, in addition to several Western men who are fighting in their ranks. + +""After me"" + +A Facebook page registered to Rosenberg showed photographs of her in settings marked as Kurdish areas of Iraq and Syria. + +""In the IDF (Israeli army), we say 'aharai', After Me. Let's show ISIS (Islamic State) what that means,"" read a Nov. 9 post. + +Rosenberg had consented to extradition and served around three years in a U.S. prison under a plea bargain, her lawyer said. A 2009 FBI statement on the case names her as Gillian Rosenberg, among 11 people arrested in Israel ""in a phony 'lottery prize' scheme that targeted victims, mostly elderly"". + +Israel's NRG news site reported at the time that Rosenberg turned to crime after running short on money, that she was estranged from her parents and had tried in vain to join the Mossad spy service. + +""She is incredibly strong, both in mind and in body,"" said long-time friend Daniel Lieber in Massachusetts. ""She has always been someone interested in politics and is very pro-Israel."" + +Discreet ties + +Israel has maintained discreet military, intelligence and business ties with the Kurds since the 1960s, seeing in the minority ethnic group a buffer against shared Arab adversaries. The Kurds are spread through Syria, Iraq, Turkey and Iran. + +Worried about spillover from the Syrian war, Israel has been cracking down on members of its 20-percent Arab minority who return after volunteering to fight with Islamic State or other rebels opposed to Syrian President Bashar Assad's rule. + +Israel bans its citizens from travelןng to enemy states, among them Syria and Iraq, and officials did not respond to a Reuters inquiry about whether the woman could face prosecution if she returns to Israel. + +Photos by LiveLeak:","0" +"Canadian-Israeli Woman May Have Been Captured In Syria: Reports","OTTAWA, Nov 30 (Reuters) - Canada is trying to confirm reports that a Canadian citizen has been captured in Syria, a foreign ministry spokesman said on Sunday. ""Canada is pursuing all appropriate channels"" to seek further information and is in touch with local authorities, the spokesman said in a statement. Israeli media reports, including Haaretz newspaper quoting a website associated with Islamic State, said a Canadian-Israeli woman, Gil Rosenberg, has been captured. The reports cited jihadist websites and have not been confirmed by Israeli officials. ""I cannot confirm that and I hope that it isn't true,"" Israeli Defense Minister Moshe Ya'alon told an Israeli television channel when asked about the reports. Rosenberg, 31, told Reuters that she was in Syria in November. A source linked to the YPG, the Kurds' dominant fighting force in northern Syria, said earlier this month that she was their first female foreign recruit and had crossed into Syria to fight Islamic State militants. (Reporting by Randall Palmer; Additional reporting by Allyn Fisher-Ilan in Jerusalem; Writing by Amran Abocar; Editing by Kevin Liffey and Eric Walsh)","0" +"ISIS Claims It Kidnapped Gill Rosenberg, The First Western Woman To Fall Into The Group's Hands","A 31-year-old Canadian-Israeli woman who traveled to Iraq to join the Kurdish fight against the Islamic State group reportedly has been abducted by ISIS. Gill Rosenberg, 31, a former Israeli soldier, was captured after three suicide bombings near Kobani, the Times of Israel reported. + +The SITE Intelligence Group said jihadists are discussing ideas for executing her or using her for a prisoner exchange. The capture was reported Sunday on the Islamic State-associated blog Samoach al-Islam and other Islamist websites. The Israeli Foreign Ministry said it is investigating the claim, which was not backed by any evidence, the Jerusalem Post said. The Israeli security service Shin Bet told the Post it had “no further details” about the reported abduction. + +Israeli Jill Rosenberg joined Kurdish forces in Iraq is a @NyMets_ fan! Via @isin669 pic.twitter.com/vpGmXKlB1o + +— Yaron Melman (@NrouteHQ) November 25, 2014 + +The Canadian government said it is looking into the report, according to CTV News. The Department of Foreign Affairs told the media outlet in an email it was “pursuing all appropriate channels” in seeking to determine Rosenberg's whereabouts, but declined to release any other information. + +Quoting two Kurdish fighters, Israel Radio reported Rosenberg was not near Kobani. + +The Post noted if the claim is true, it would make Rosenberg, who was born in Vancouver, British Columbia, and moved to Israel in 2006, the first Western female to fall into the Islamic State group’s hands and her Israeli citizenship could complicate the situation even further. Steven Sotloff, who was executed by ISIS in August, had dual U.S.-Israeli citizenship.","0" +"'No hard evidence' of Isis claims it kidnapped Canadian-Israeli woman Gill Rosenberg","Gill Rosenberg is reported to have been captured with several other women fighting with Kurds + +There is “no hard evidence” that Isis has captured a Canadian-Israeli woman fighting with the Kurds in Syria, an expert has said, as officials struggle to discover the truth of militants’ claims the woman is just one of a group of female fighters to have been kidnapped near Kobani. + +Gill Rosenberg, 31, is a Canadian-born woman and resident of Tel Aviv who volunteered to fight alongside Kurdish fighters in Syria. + +According to a blog linked to Isis (also known as Islamic State), which has been quoted by Israeli media reports, Ms Rosenberg was captured alongside several female fighters near Kobani. These reports have not yet been confirmed by Israeli officials, and the Canadian foreign ministry has said it is “pursuing all appropriate channels” to confirm Ms Rosenberg’s whereabouts. + +“I cannot confirm that and I hope that it isn’t true,” Israeli Defence Minister Moshe Ya’alon told an Israeli television channel when asked about the reports. + +Charlie Winter, a researcher at counter-extremism think tank Quilliam, said that while the rumours swirl around the state of Ms Rosenberg’s capture, there is “no hard evidence” to show that she has been taken by Isis. + +“No photos of her have been circulated by Isis,” Mr Winter said, “which means there is no hard evidence that she has actually been captured. At the same time, the YPG have denied the rumours, and the Free Syrian Army’s representatives in Kobani said the rumours haven’t been confirmed to them either.” + +Mr Winter said despite the lack of physical evidence, the YPG and the Free Syrian Army are “not above deliberate obfuscation to make Isis look weaker,” but that it is impossible to know the truth without any official pictures or statements. + +Others have refuted rumours of Ms Rosenberg’s kidnap however, claiming that she simply has no internet access and will be updating her status on Facebook as soon as she had a connection. + +Oliver Brimo, who appears to be a friend of Ms Rosenberg, posted on her Facebook profile on Monday: “To those who are concerned about Gill Rosenberg’s safety. Gill is safe and she is not active on Facebook cause she has no internet access. Once she has internet access she will be updating her status [sic].” + +He added: “Isis’s supporters launched a rumour on social media that she was captured in #Kobani which is not true, simply because Gill is at least 300km from Kobani [sic].” + +Mr Brimo told The Independent on Monday that his source claims to have seen Ms Rosenberg ""in person hours ago"". + +On 20 November, Ms Rosenberg posted that her Facebook page and friend requests were to be managed by someone else until she had access again, which she expected to happen approximately two weeks later, around the second week of December. + +Messages of concern have flooded her Facebook page since the claims emerged of her kidnapping. + +Ms Rosenberg is a former member of the Israel Defence Force. A source linked to the YPG, the Kurds’ dominant fighting force in northern Syria, told Reuters News Agency in November that Ms Rosenberg was their first female foreign recruit and had crossed into Syria to fight Isis. + +Additional reporting by Reuters","0" +"Gill Rosenberg, former IDF soldier, possibly captured by ISIS while fighting with Kurds","Canadian national and former Israel Defense Forces (IDF) soldier Gill Rosenberg, 31, revealed to the Israeli media earlier this month that she had traveled to Iraq to help the Kurdish People's Protection Units (YPG) fight off ISIS. +""They are our brothers,"" she told Israel Radio of the Kurds. ""They are good people. They love life, a lot like us, really."" +Now, just three weeks later, there are rumors she may be in ISIS custody. Posts on ISIS-affiliated web forums, including Al Platform Media, claim the ""Zionist soldier"" was captured while fighting with the Kurds against ISIS in Kobane, a small majority-Kurdish town along Syria's northern border with Turkey. +There has indeed been intense fighting in Kobane between ISIS and the YPG over the past 24 hours. However, YPG sources have strongly denied to the Journal and other outlets that Rosenberg was captured. +So far, neither group has provided evidence either way, and ISIS has yet to release an official statement. + +A spokesperson at the IDF news desk told the Journal that the IDF is not keeping track of Rosenberg, and ""does not have a way of knowing"" if she's been captured by ISIS. Minister of Defense Moshe Ya'alon, too, told Channel 2 that he had no information on Rosenberg's whereabouts. +Rosenberg, formerly a resident of Tel Aviv, did post to Facebook on Nov. 20 that she would be taking a short leave from social media. +""My Facebook account and friend requests are being managed by someone else until I have access again in apx 2 weeks time on or around week of 12/8,"" she wrote. ""Please do not message as this is not me. Thank you."" +A couple weeks before that, right around her 31st birthday, Rosenberg posted photos of herself on the Iraqi-Syrian border, and wrote: ""In the IDF, we say אחריי - After Me. Let's show ISIS what that means."" + + + + + +A friend of hers from the IDF told the Journal that he remembered Rosenberg as ""a cute lady with a strong ideology."" On Twitter, her tagline is: ""On a spiritual journey and a quest for authenticity."" +Her attraction to foreign battlgrounds aside, the IDF-turned-YPG warrior has a pretty bizarre backstory. She reportedly served a few years in U.S. prison for a phone scam that she ran out of Israel, in which elderly Americans were ""bilked out of millions of dollars, collectively,"" according to the FBI. +Since news of her possible capture broke, friends and supporters have filled her Facebook wall with respects, prayers and side-by-side photos of the Israeli and Kurdish flags. + +ISIS members writing on the Al Platform Media forum urged leaders to use Rosenberg as a bargaining chip for a prisoner exchange with Israel. +In a phone interview with the Journal, Emmanuel Nachshon, spokesman for the Israel Ministry of Foreign Affairs, distanced the government from Rosenberg. ""She’s her own person,"" he said. ""As an individual, she’s free to do whatever she wants. We're not in a position to tell her what to do. ... Remember, she didn’t go there as an Israeli. She never said, 'I’m representing Israel.'"" +Nachshon said the foreign ministry was aware Rosenberg was fighting for the Kurds, but has not been able to confirm the kidnapping rumors. ""Our researchers are looking into it,"" he said. (CBC News in Canada reports that the Canadian foreign ministry is likewise ""pursuing all appropriate channels"" to locate Rosenberg.) +Asked if Israel was expecting ISIS to try and negotiate, Nachshon said: ""I hear they are more in the business of cutting heads."" +Updates to come as story develops.","0" +"Report: ISIS kidnaps Canadian-Israeli, former IDF soldier who went to fight with the Kurds","Gill Rosenberg, 31,said last week on Facebook that she was no longer updating her page because she was headed to an area without internet. + +Uncertainty abounds concerning the fate of Israeli-Canadian Gill Rosenberg, who was apparently captured by ISIS. + +Islamist websites – some of them known to be close, or even serving as a front for ISIS – reported Sunday that the 31-year-old was captured by their warriors during fierce battles with Kurdish fighters in unspecified areas. + +According to the websites, Rosenberg was taken hostage following three suicide attacks on sites where Kurdish fighters had barricaded themselves. The websites gave no further details regarding the circumstances of the capture, nor did they provide any proof of it. + +The ISIS claims do not make clear whether Rosenberg was captured in Iraq or in Syria. The main lines of battle between Kurds and ISIS are in the Syrian-Turkish border town of Kobani – but Kurdish sources approached by Israel Radio reporter Eran Cicorel expressed doubt over the ISIS report. They said Rosenberg was not in Kobani. In the assessment of these Kurdish sources, the reports of Rosenberg's capture are probably ISIS propaganda. + +The Shin Bet, Israel's general security service, told The Jerusalem Post that ""there are no further details at this stage."" + +Rosenberg wrote on her Facebook page on November 20 that she was handing over management of her account to ""someone else"" and would be without internet access for at least two weeks, until December 8, she wrote. It is not clear where she went at this time. + +If the websites' reports are true, Rosenberg would likely be the first Western female to fall into ISIS captivity. Holding Israeli citizenship would complicate her situation even further. + +Unlike the United States and the United Kingdom, which refused to negotiate with ISIS over their captured nationals, thus giving the impression of laissez faire interest, Israel invests intense concern into the fate of its citizens captured by terrorists. + +This does not mean that Israel would negotiate with ISIS over Rosenberg, if she has indeed been captured – or that ISIS would agree to talk Israel, chalking her nationality up to Canadian alone. + +It is worth mentioning that if Rosenberg was captured, she would be the second Israeli – of dual nationality – in this position. Steven Sotloff, a freelance American journalist who also held Israeli citizenship and filed for The Jerusalem Report from the Syrian Civil War, was captured by ISIS last year shortly after crossing the Syrian border and beheaded by the Islamist group this past August. + +It is also worth noting that Rosenberg breached Israeli law by flying to Iraq, an enemy country which Israeli citizens are forbidden to enter. No matter what has happened to her since joining the Kurdish forces – whether safe or in ISIS captivity – there is no doubt that upon return to Israel, she will be arrested and prosecuted, as was the case of several Israeli Arab who joined ISIS and returned. + +This is not Rosenberg's first tryst with adventurism – in 2009 she was arrested in an American con scandal and sentenced to four years in jail. This is however, her first serious choice encounter with death. + +Rosenberg was born in Vancouver, Canada, and experienced a family crisis after her parents divorced. In an interview with Ma’ariv in 2009, she said that already at the age of 22 she was pursuing a promising career as a pilot of Boeing passenger planes, but decided to leave everything behind and make aliya in 2006. In Israel, she joined the IDF, serving as an instructor for Kenyan soldiers who came to Israel for home front search and rescue training. + +Rosenberg said that she had ambitions to join the Mossad, but was hurt during her military training and afterward had money problems. + +She met an American friend in ulpan (Hebrew language school) who led her into crime, she claimed. She joined a group of Israelis who were accused of setting up a ring to cheat elderly Americans and steal their money through a fake lottery scheme. According to the indictments filed against them, they stole hundreds of thousands of dollars, and perhaps even millions, from the unknowing pensioners. + +After a number of complaints were filed, a joint Israel Police and FBI investigation was launched. The probe led to the arrest of several suspects and their extradition to the US, where they were tried. Rosenberg served four years in jail.","0" +"BREAKING Gill Rosenberg former IDF soldier was captured by ISIS","BREAKING: Gill Rosenberg (31) from Tel Aviv former IDF soldier was captured by ISIS after going to Iraq to join Kurds & fight ISIS - Ch 2","0" +"Canadian-Israeli woman reportedly kidnapped by ISIS: Jerusalem Post","A Canadian-Israeli woman who joined Kurdish fighters battling Islamic State militants earlier this month has been kidnapped by the group, Israeli media reported Sunday morning. + +Gill Rosenberg's kidnapping was reported by The Jerusalem Post as well as ynetnews.com, the English-language edition of Ynet, Israel's largest and most popular news website. + +""The reports began surfacing on jihadi and Palestinian social media and forums, and claim Rosenberg was taken while fighting with the Peshmerga forces in Kobani, Syria,"" ynetnews.com said on its site. + +The Post said that in an interview with Israel Radio in early November, Rosenberg said she had decided to join the fighters for humanitarian and ideological reasons and “because they are our brothers” who are fighting Islamic State. + +Friends of Rosenberg posted messsages on her Facebook page shortly after the news of her possible kidnapping broke. + +""Hope this is wrong and you come back safely. Gila bat Avraham,"" Ed-Malki Dvir wrote. + +And Chris Levy posted: ""I hope this isn't true but if it is then I am praying for you and your other captured hevals in your darkest hours."" Heval means friend in Kurdish. + +Haaretz.com, the online edition of Israel's oldest daily newspaper, said ""the pro-Islamic State blog Samoach al-Islam reported that several female fighters who fought alongside the Kurds have been captured, among them Gill Rosenberg. + +""According to the report, prior to their capture, Islamic State fighters made three suicide bombing attacks against Kurdish outposts, killing some and capturing many others."" + +Haaretz says, Samoach al-Islam is considered to be one of the media arms of ISIS. + +According to ynet.com, Rosenberg immigrated to Israel from Canada in 2006, after studying at British Columbia Institute of Technology and left behind a promising career as a pilot.","0" +"Islamist websites claim Israeli-Canadian woman kidnapped by IS: report","An Israeli newspaper report says Islamist websites are claiming extremists have kidnapped an Israeli-Canadian woman who joined Kurdish fighters overseas. + +The Jerusalem Post says reports of Gill Rosenberg’s capture surfaced Sunday on websites “known to be close” to Islamic State extremists. + +The newspaper says the websites give few details on the alleged kidnapping, only that it occurred after three suicide attacks on sites where Kurdish fighters were holed up. + +Clashes between ISIL and Kurdish troops have largely focused on the Syrian city of Kobani, near the Turkish border. + +The now-notorious al-Qaeda splinter group is currently in control of large swaths of territory in both Syria and Iraq. + +Messages of concern were posted Sunday on a Facebook profile belonging to a Gill Rosenberg. An earlier message asked for advice on joining the Kurdish army. + +“Canada is pursuing all appropriate channels” to seek further information and is in touch with local authorities, a foreign ministry spokesman said on Sunday in a statement + +With a file from Reuters","0" +"Ottawa investigating reports that IS has captured a Canadian-Israeli woman","The federal government is investigating reports a Canadian-Israeli woman has been captured by Islamic State militants after joining Kurdish forces in Syria. + +Israeli newspapers reported on the weekend that IS-linked websites claimed Gill Rosenberg, 31, was taken prisoner in Kobani after suicide attacks by members of the radical religious movement. + +Other reports, however, said she was safe and sound in Rojava, the Kurdish-controlled region of northern Syria, where peshmerga fighters are holding out against IS. + +“She is in Rojava and safe,” Kader Kadandir, who said he is a member of a Kurdish group battling IS, wrote on Ms. Rosenberg’s Facebook page Sunday. He also posted several photographs of Ms. Rosenberg holding rifles and pistols. + +A relative of Ms. Rosenberg said her family had not heard anything from her over e-mail and she had not signed into her Facebook page. + +“She’s a very brave girl. She knew what she was doing. She did it for a reason. She knew the consequences,” said the relative, who asked not to be identified. + +A spokesman for the Department of Foreign Affairs and International Trade said the government is aware of the reports. + +“Canada is pursuing all appropriate channels to seek further information,” Nicolas Doire wrote in an e-mail. + +Ms. Rosenberg, who lists White Rock, B.C., near Vancouver, as her hometown, has been living in Israel for several years. She gave a radio interview in Israel several weeks ago indicating she was planning to join Kurdish forces.","0" +"Ottawa investigates reports that Isis has captured Canadian-Israeli woman","The Canadian government said on Sunday it was investigating reports that a Canadian-Israeli woman who joined Kurdish militias fighting in northern Syria has been captured by Islamic State (Isis) fighters. + +According to a blog linked to Isis, several female fighters who fought alongside the Kurds have been taken prisoner, including Gill Rosenberg, a Canadian-born resident of Tel Aviv. Israel Radio reported Kurdish sources denying the claims, saying Rosenberg was not in the area when it was attacked. + +A Canadian government spokesman said in a statement his country was “pursuing all appropriate channels” as it sought further information and was in touch with local authorities. + +Asked by an Israeli television station about the reports, the Israeli defence minister, Moshe Ya’alon, said: “I cannot confirm that and I hope that it isn’t true.” The Shin Bet, Israel’s general security service, told the Jerusalem Post: “There are no further details at this stage”. + +Rosenberg, 31, joined Kurdish troops fighting Isis earlier this month. A former pilot who served in the Israeli Defence Force (IDF), she reportedly contacted Kurdish fighters over the internet before travelling through Iraq to train at one of their camps on the Syrian border. + +In an interview with Israel Radio aired in November, Rosenberg said she was training with Kurdish guerrillas with the intention of fighting in Syria. “They are our brothers. They are good people. They love life, a lot like us, really,” she said. + +On 20 November, a message posted to a Facebook page in Rosenberg’s name said: “My Facebook account and friend requests are being managed by someone else until I have access again in apx [sic] 2 weeks time on or around week of [8 December]. Please do not message as this is not me. Thank you.” + +Messages of concern were being posted on the Facebook page this weekend. + +Isis, which has killed five western hostages, is believed to be holding 39 Indian construction workers captive. Last week the group was reported to have executed two Iraqi women who were former parliamentary candidates.","0" +"Female Israeli fighter said abducted by Islamic State Read more: Female Israeli fighter said abducted by Islamic State","An Israeli-Canadian woman who traveled to Iraq to fight alongside the Kurds there earlier this month has been abducted by Islamic State fighters, Hebrew media reported Sunday, citing Syrian jihadist-linked media. + +Gill Rosenberg, 31, was captured by jihadists near the flashpoint city of Kobani in the past few days, reports said. The former IDF soldier and Canada native was taken after the jihadists launched three suicide bombings in the area, and her condition is unknown. + + +The reports were not initially confirmed by the Islamic State group. In Israel, the Foreign Ministry said it was looking into the reports while stressing that the websites that carried the information were “of dubious credibility.” + +Two Kurdish fighters quoted by Israel Radio cast doubt on the reports. One, an American fighter, said Rosenberg was never in Kobani. Another soldier on the ground said that he had heard nothing of her alleged abduction. + +In her last Facebook post to date, Rosenberg wrote on November 20 that someone would be managing her profile for two weeks, and asked that people not message her “as this is not me.” + +IS launched an attack Saturday on the Syrian border town of Kobani from Turkey, a Kurdish official and activists said, although Turkey denied that the fighters had used its territory for the raid. + +The assault began when a suicide bomber driving an armored vehicle detonated an explosive device on the border crossing between Kobani and Turkey, said the Britain-based Syrian Observatory for Human Rights and Nawaf Khalil, a spokesman for Syria’s powerful Kurdish Democratic Union Party. + +The Islamic State group “used to attack the town from three sides,” Khalil said. “Today, they are attacking from four sides.” + +The Islamic State group claimed three suicide attacks in Kobani’s border crossing point, the SITE Intelligence Group reported. The group, quoting Twitter accounts linked to the militants, said the suicide attacks were carried out by a Saudi and a Turkmen, adding that one of them was driving a Humvee. + +The first foreign woman to join the Kurdish forces, Rosenberg set out from her home in Tel Aviv on November 2, stopping in Amman before flying to Erbil, the capital of the autonomous Kurdistan Region of Iraq. + +Rosenberg told Israel Radio that she wanted to do her part for the Kurdish national struggle, and that she was hopeful her experience in the Israel Defense Forces would be useful to the Kurds. + +According to Rosenberg’s Facebook page, she served in the IDF’s Home Front Command. + +Rosenberg has posted pictures of herself in mountains of Iraq and Syrian Kurdistan. + +“In the IDF, we say Aharai – After Me. Let’s show ISIS what that means,” she wrote, using an alternate acronym for Islamic State. + +In 2009, Rosenberg was arrested in a joint Israeli police and FBI operation on suspicion that she had been part of a ring that cheated elderly American citizens out of their money by posing as lottery officials and convincing the unsuspecting seniors to pay for fictive services, according to the Walla news site. The members of the ring, which included 11 other Israeli citizens aside from Rosenberg, were said to have stolen up to $25 million. + +Rosenberg was later convicted of the crime and sentenced to four years in a US prison, though her term was eventually shortened and she was deported to Israel instead, Channel 10 reported. + +The Islamic State group began its Kobani offensive in mid-September, capturing parts of the town as well as dozens of nearby villages. The town later became the focus of airstrikes by the US-led coalition against the militants. + +Kurdish fighters slowly have been advancing in Kobani since late October, when dozens of well-armed Iraqi peshmerga fighters joined fellow Syrian Kurds in the battles. The fighting has killed hundreds of fighters on both sides over the past two months. + +If confirmed, Rosenberg would be the second Israeli captive held by the jihadist group. Israeli-American journalist Steven Sotloff was beheaded by the Islamic State group in early September. Sotloff went missing in Syria in August 2013, and the jihadists were reportedly unaware of his Jewish heritage and Israeli citizenship until after his death. + +Lazar Berman and AP contributed to this report.","0" +"Conflicting reports on alleged IS capture of Canadian woman","KOBANE , Syria, Dec. 1 (UPI) -- There are conflicting reports whether Gill Rosenberg, a Canadian-Israeli woman who claims to have joined the fight against the Islamic State, has been captured. +Rosenberg, 31, told Israeli radio she traveled from Israel to Iraq in November to join a Kurdish militia, the only anti-IS group encouraging women to enter combat. IS-affiliated websites claimed over the weekend she was captured near locations where Kurdish and IS forces were engaged in battle, but Kurdish sources told the Jerusalem Post the reports of her capture were merely IS propaganda. + +Two messages have appeared on the Facebook social media website since Sunday night, indicating Rosenberg was not taken prisoner. Facebook user Oliver Bruno wrote ""Gill is safe and she is not active on Facebook cause (sic) she has no internet access. ISIS's supporters launched a rumor on social media that she was captured in ‪#‎Kobani which is not true, simply because Gill is at least 300 km. from Kobani."" + +The message would imply Rosenberg left Israel to fight but was some 186 miles away from Kobane, a town on the Syria-Turkey border and the scene of two months of fighting. + +A later message from Bruno said the head of the YPG Kurdish forces in Kobane ""categorically refuted these allegations."" + +Another message from Facebook user Emanuela Siyar Barzani, citing a ""qualified"" source, noted ""Everything is fine with Gill."" + +On Saturday, an online form posted a message from a pro-IS contributor, claiming a ""female Zionist soldier"" was captured in Kobane by IS forces, the SITE Intelligence Group reported. Speculation began that the soldier in question was Rosenberg, but there has been no confirmation. + +The Canadian government's Department of Foreign Affairs said it was investigating the reports, but did not confirm Rosenberg, who is from White Rock, B.C., had been captured.","0" +"Report: Israeli-Canadian woman fighting Islamic State has been kidnapped by terror group","Online reports in jihadi and Palestinian forums claim Gill Rosenberg was captured by Islamic State group in embattled town of Kobani. + +Gill Rosenberg, the Israeli-Canadian who joined Kurdish forces in their battles against the radical Islamic State terror group has been reportedly taken captive by the group, unconfirmed reports claimed. + +Rosenberg, 31, is a civil aviation pilot who enlisted in an Israeli army search-and-rescue unit before being arrested in 2009, extradited to the United States and jailed over an international phone scam, one of her former lawyers said. + +Rosenberg said that she had made contact with the Kurds through Facebook, asking them to allow her to join the Kurdish People's Protection Units, commonly known as the YPG. + +On her Facebook page, Rosenberg shared her plans for her mission in Syria two months in advance, when she uploaded a picture from Jerusalem showing an Israeli flag next to an Islamic State flag, and continued posting images until her November 1, her final day in Israel. + +She later posted pictures from Queen Alia International Airport in Amman, Jordan, and then from Erbil International Airport in Kurdistan. On November 9, she uploaded images from the Kurdish region of Syria and wrote, ""In the IDF (Israeli army), we say 'aharai', After Me. Let's show ISIS (Islamic State) what that means."" A friend wrote, ""Take care of yourself, friend. You are one strong woman, and you'll destroy the Islamic State."" + +A source in the Kurdistan region with knowledge of the issue said Rosenberg was the first foreign woman to join YPG, the Kurds' dominant fighting force in northern Syria. She has crossed into Syria and is one of around 10 Westerners recruited by YPG, the source said. + +Rosenberg could not be reached by Reuters for comment. A source provided an Iraqi Kurdistan cellphone number for her, but it was turned off on Tuesday. + +Michal Margalit contributed to this report","0" +"The Gold Apple Watch Could Cost As Much As $1,200","A jewelry contact familiar with the matter told TechCrunch that the gold, 18-karat version of the Apple Watch could cost around $1,200 retail when it launches in January. This has been corroborated, based on size and weight, by jewelers familiar with the material Apple is using to make its Apple Watch Edition pieces. It should be noted that this is an estimate and the piece could come in well below that price. + +Although there is still some confusion as to whether the watch will be gold plated or actually made of gold, the jeweler suggested that it would be sub-optimal not to make the watch out of solid gold alloy, a decision that will drive up the price. The estimate is based on the leaked design images of the iWatch that appeared this weak. + +Chad Rickicki, a watch expert in Pittsburgh, Pennsylvania said that a case the size and shape of the Apple Watch in 18 carat gold would cost about $600 to make. The rest – the electronics and markup could double that price. + +That doesn’t mean that all of the Apple Watches will rest in the rarified air of haute horlogerie. The lower end sport versions will start at $349 and presumably the standard versions, simply called Apple Watch, will receive a premium over that. The Edition watches, however, are expensive because gold is expensive, even at 18K and intermixed with Apple’s alloys. + +What does this mean? It suggests an interesting move by the company to turn Apple Stores into luxury destinations. While I’m sure Prada and Louis Vuitton are clamoring to be given access to Apple’s unique band connectors, the upside for a more fashionable, luxury-leaning Apple Watch display in stores means the company will control quality and, more important, control profits on band upgrades. + +Apple is entering a fascinating new world of potential partnerships as is, to some degree, the makers of Android Wear devices. Now consumers are going to have to get used to armed guards standing over cases of (tastefully) blinged-out Apple Watches.","0" +"Apple Watch Gold Edition rumored to be priced at $1200: Will you buy?","Apple has remained mum as to its pricing strategy for the three versions of the Apple Watch to be made available next year, only saying that the price will start at $350 for the entry-level version, likely to be the Apple Watch Sport, which features light aluminum and a sweat-resistant band made from a rubbery material. + +But jewelry industry experts believe the Apple Watch Edition, which comes with 18-karat yellow gold or rose gold, a sapphire crystal display and Venetian leather for its bands, will cost around $1,200, with other jewelers estimating that Apple's fanciest smartwatch could be priced as much as $10,000. + +Watch expert Chad Rickicki of Pittsburgh, Penn. told TechCrunch that an 18-karat gold case that is the size and shape of the Apple Watch could rack up as much as $600 for the raw material. That does not even include the smartwatch's electronic components and the profit margin Apple plans to tack on to the device. All in all, consumers can expect to pay $1,200 for a gold smartwatch, says Rickicki. + +However, other jewelers are not as optimistic, saying that we need to understand the materials Apple used for its smartwatch to be able to peg it at a more accurate price. Ariel Adams, founder and editor of watch blog aBlogtoWatch, says Apple adopted watch industry terminology for the Apple Watch. The term ""18-karat gold,"" he says, likely means the watch is made of solid gold, not gold-plated. Otherwise, Apple would have used the term ""gold-plated."" + +The current market price for gold is $1,200 per ounce. If, for example, the Apple Watch weighs two ounces, that is already $2,400 just for the gold. That is not even considering the special process Apple's own metallurgists invented to create gold that is ""twice as hard as standard gold."" Adams says Apple has cheaper manufacturing centers in China than the facilities used by Swiss-based watchmakers, but gold is gold and it is expensive wherever it is crafted. + +Adams also points out that there is also the cost of sapphire glass to contend with, estimating that Apple has to pay around $30 to $40 for the sapphire crystal case of the Edition smart watch. Sapphire manufacturing, Adams says, is a long and expensive process where the crystals are synthetically grown in large chambers and then cut into rectangles that are then laminated. Adams thinks the high-end Apple Watch will not cost anything less than $5,000 and could go up as much as $10,000. + +""The Edition is going to be far, far less mass-produced than the steel version,"" he says. ""I think it's going to have a much different type of distribution. It'll be a much more exclusive product.""","0" +"Gold Apple Watch Edition Could Cost As Much As $1,200","When Apple unveiled the Apple Watch, the unveiled three different editions: the Apple Watch, the Apple Watch Sport, and the Apple Watch Edition. The latter model appears to be catered to those who are more interested in fashion and luxury as the watch will be given an 18-karat gold treatment. +Sure, we guess it looks good but at the same time, have you ever wondered how much it will cost? Apple has declined to state a price of the Apple Watch Edition but according to the folks at TechCrunch, it is possible that the gold Apple Watch could retail for as much as $1,200. This is according Chad Rickicki, a watch expert who claims that the 18-karat gold Apple Watch would cost $600 just for the case, size, and shape alone, and that combine it with the electronics and markup, could end up being in the $1,200 range. +This is a significant leap over the base Apple Watch which Apple has said would be priced starting at $349, so safe to say it is an interesting direction that Apple is headed if they do indeed price the Edition at over $1,000. Given how Apple’s recent hires have come from the high-end fashion industry, we can’t say this is too surprising. +In fact a rumor earlier this year had even suggested that Apple could be preparing an Apple Watch that could cost thousands, thus making these claims slightly more believable. Either way we expect Apple will announce the prices in the near future as the Apple Watch has currently been pegged for a release in 2015.","0" +"Results: 80% expect the 18-karat gold Apple Watch Edition to cost under $4500, but will it?","In a poll of 9to5Mac readers, nearly 80% of people think Apple’s 18-karat gold Apple Watch Edition will cost under $4500. Only 16% expect the gold Apple Watch Edition to cost between $5000-$10,000, and 3.8% expect a price tag over $10,000. The biggest group at 29.68% expect the gold model to cost between $1500-$2500. But how much will the gold Apple Watch really cost? + + + +Apple-watch-gold-survey-01 + +It depends on how much gold, in terms of weight, is actually in the Apple Watch. Apple itself described the model as solid 18-karat gold, but we still don’t know for sure. + +We have at least an estimate, however, with Greg Koenig (via Forbes) creating a 3D render of the Apple Watch (above) and estimating around 29.16g, or approximately $1200, worth of gold. Factor in everything else included in manufacturing the watch and Apple’s usual markup and Koenig thinks the watch won’t come in below $5000. Compare that with the hint of a price point close to the entry-level $4000 Mac Pro from the WSJ in recent weeks. + +We’ll have to wait to know for sure how Apple decides to price the device (like an iPhone + gold or like a traditional, high-end timepiece), but it appears most consumers are expecting (or at least hoping) for the former. + +Our poll included nearly 10,000 votes.","0" +"Could Gold Apple Watch cost $5,000?","My wrists and I have had a troubled relationship since last week. + +Ever since Apple revealed its vast array of watches, my lower forearms have looked up at me and hissed: ""Well? You're going to leave us naked?"" + +So I spent some time yesterday browsing Apple's site and perusing all the different types of watches that will soon be available. + +The fancier model -- the so-called Apple Watch Edition -- does look relatively lovely on tiny female forms. But how much might it cost? All Tim Cook offered last week was that the watches -- the cheapest presumably being the sporty ones you'll sweat all over -- will start at $349. + +Then along comes influential Apple observer John Gruber to insert a little informed perspective. + +""Apple Watch is not a product from a tech company, and it will not be understood, at all, by the tech world,"" he said. + +This incites a kaleidoscope of optimism for those who find tech minds frightfully insular. For Gruber, the higher-end watches -- the Apple Watch made of stainless steel and the Watch Edition adorned with 18-karat gold -- will be competing directly with fancy watches. + +What they will offer is a (hopefully) gorgeous watch with some fancy gizmos attached. + +It's a persuasive concept, one that makes your standard Rolexy thing a klutzy lump of gold that can merely tell the time and make you look like something of a exhibitionist half-wit. + +However, if you want your artistic creation to seem valuable, you have to price it as such. So Gruber wagers that the stainless steel Apple watch will start at around $999. The Edition, however, he places at $4,999. + +In his words: ""I think Apple Watch prices are going to be shockingly high -- gasp-inducingly, get-me-to-the-fainting-couch high -- from the perspective of the tech industry. But at the same time, there is room for them to be disruptively low from the perspective of the traditional watch and jewelry world."" + +The thing that's missing currently is the full gamut of what Apple's watches will be capable of doing. We've seen the basic hardware, but we don't know that much about the software. + +Between now and their launch -- some time in 2015 -- Apple's team has time, surely, to develop and keep in secrecy all sorts of amusing functionality. This functionality will keep your first date enthralled for hours as you waft your Apple Watch before his or her mesmerized eyes. + +Not only will you seem to be a person of means, but one who means to know where the world is at. + +Even if the fanciest of its watches costs $4,999, Apple still has the problem of obsolescence and general pain-in-the-buttness. + +Do you really want an extra item to charge every night? Do you really want to replace your watch every couple of years? Or might there, as Gruber suggests, be a nifty software-update solution so that you don't have to toss it in the drawer next to all your old iPhones? + +What's most important here, though, is that Apple is proving ever more that what is conventionally called tech is not its main domain. + +We humans are posers, as much if not more than we're thinkers. We sift the world through imagery, rather than substance. Somehow, substance is a more shifty essence than is our world of impressions. + +Impressions are instant, substance takes time. There are too many demands on our time for us to bother to dig deep into the substance of everything (or even anything much at all). So we sift our world by looking at it and absorbing impressions. + +MORE TECHNICALLY INCORRECT + +Man demands iPhone 6 as dowry, report says +GoDaddy makes very funny ad (no, really) +Samsung hires Kristen Bell to help you forget about Apple +Apple's watches will exist first to make certain impressions. Buried a little deeper, however, will likely be a certain substance that is unique to these fashion accessories. This is what Apple means when it says these are the most ""personal"" devices it's ever made. + +It's like any relationship. You're first moved by looks. Then you hope that there's something more behind them, something that will be the glue that creates a deeper, longer-lasting bond. + +You might choose to pay $4,999 or even more for a gold Apple Watch Edition. But you'll need it to be more than just a pretty face. And that's where Apple hopes to make a killing.","0" +"The gold Apple Watch Edition could set you back a whopping $4,999","The Apple Watch Sport may start at a mere $349, but the product line’s price point could well soar from there! + +According to Daring Fireball‘s John Gruber, Apple’s 18-karat gold Apple Watch Edition may sell for as much as $4,999. + +“Most people think I’m joking when I say the gold ones are going to start at $5,000,” Gruber writes in a new blog post. “I couldn’t be more serious.” + +Gruber notes that the device might cost $1,999 at a bare minimum, but this is unlikely since the components alone would cost more than this. + +While $4,999 would give the Apple Watch Edition the dubious distinction of being both one of the company’s most expensive products and its smallest, Gruber points out that the device will not just be gold-plated, but actually manufactured using 18-karat gold. + +With that said, is anyone going to want to regularly upgrade a solid gold watch that costs them the same as a Swiss watch which could conceivably stay in a person’s family for a lifetime? + +For the record, Gruber thinks the stainless steel/sapphire Apple Watch will set customers back $999. + +Guess we’ll find out for sure in early 2015, when the Apple Watch finally ships. + +Hey, at least the gold Apple Watch Edition comes with a snazzy charging case.","0" +"Apple Watch Gold Edition may cost as much as $5,000","You want a gold Apple Watch, you say? Then it's going to cost you... a lot. + +The vanilla variant of Apple's newest wrist-worn wearable device only costs $349. However, if you're willing to spend big cash on something that has the Apple logo on it, the company would be more than willing to accommodate. + +According to analyst John Gruber, the gold version of the upcoming device may cost about as much as the monthly salary of a middle-class worker in the United States. Gruber predicts that the gold Apple Watch would cost $5,000. The figure is basically just a guess. However, it's not an uneducated one. + +""Most people think I'm joking when I say the gold ones are going to start at $5,000. I couldn't be more serious,"" Gruber wrote in a blog post. ""The lowest conceivable price I could see for the Edition models is $1,999 -- but the gold alone, just as scrap metal, might in fact be worth more than that."" + +Gruber claims that Apple told him that the gold version of the Apple Watch is made of solid 18-karat gold. It is not gold-plated. This caused him to revise his guess on the price of the device. + +He based his estimate on the going rate for solid gold watches from other manufacturers. Challenging people to find a solid gold watch that costs less than $20,000, he cited a leaked price list for Rolex from 2012. Luxury watch companies don't set prices for their products; they leave that to their authorized dealers. This means that the products on the price list may have ended up being sold for a higher price. In the list, an 18-karat gold Rolex had a price tag of $34,250. + + +Gruber suspects that the reason Apple has been mostly silent about the specs for the device is that they don't know what the capabilities of the finished product would be. + +""What does Apple Watch actually do? Or, rather, what does WatchKit allow? We don't know. And Apple is not talking, even off the record. One factor is that the software (and perhaps the hardware internals remain a work in progress). It is far from a finished product,"" he said. + +Aside from the gold version, Gruber also predicts a stainless steel version of the device that costs $999. It's not clear whether fancier variants of the device would be available with the sport version at launch. Nonetheless, the Apple Watch is expected to ship in early 2015.","0" +"Analyst: Apple Watch Edition Could Cost $5,000","The Apple Watch has garnered its fair share of opinions ever since its existence was made official to the masses last week, and it will be the beginning of next year before we see the very first Apple Watch being worn on the wrists of everyday consumers. The thing is, while there were several different versions of the Apple Watch mentioned, only one price was stated – which pointed to the $349 starting price, and we still have zero idea on how long the battery is going to last, and neither do we have a bucket list of its features. Analyst John Gruber has rolled up his sleeves and figured out that the Apple Watch Edition might just cost $4,999, coming in 18-karat gold/sapphire to boot. +As for the other estimates that analyst John Gruber has come up with, the normal aluminum/glass Apple Watch Sport ought to be the one that sports a $349 price tag, while those with three times more disposable income can settle for the predicted $999 price tag for the Apple Watch with stainless steel/sapphire. +But how did Gruber arrive at the $4,999 price point for the Apple Watch Edition with 18-karat gold/sapphire? Simply because he thinks it will be a solid gold piece, and not gold-colored. Those who have seen the Watch Edition and touched it purportedly claimed that it is heavier compared to the stainless steel version, which means the materials used within could cost a bomb – as reflected in the possible price tag. What do you think of Gruber’s estimates?","0" +"New Twist: Charlie Hebdo Police Investigator Turns Up Dead, ‘Suicided’","BREAKING: INFORMANT? Paris Terror Suspect on US Watch List Met With French President Sarkozy in 2009 + +21st Century Wire says… + +As the dust settles from this week’s terror extravaganza in France, more loose ends are turning up (or being tied up), with this latest bizarre bombshell which is already fueling speculation as to the covert nature of the Charlie Hebdo false flag affair. + +A police commissioner from Limoges, France, Helric Fredou, aged 45 (photo, below), turned up dead from a gun shot to the head on Thursday amid the Charlie Hebdo affair. A high-ranking official within the French law enforcement command-and-control structure, Fredou was also a former deputy director of the regional police service. + + +At the time of his death, police claim to have not known the reason for his alleged suicide. This was reflected in their official statements to the media: “It is unknown at this time the reasons for his actions”. However, a back story appears to have been inserted simultaneously, most likely from the very same police media liaisons, who then told the press that Fredou was ‘depressed and overworked’. For any law enforcement officer in France, it would seem rather odd that anyone would want to miss the biggest single terror event in the century, or history in the making, as it were. + +Here is a link to the original report in the French media, which confirms that Commissioner Fredou was indeed working on the Charlie Hebdo case: + +“The Fredou Commissioner, like all agents SRPJ, worked yesterday on the case of the massacre at the headquarters of Charlie Hebdo. In particular, he was investigating the family of one of the victims. He killed himself before completing its report. A psychological ‘cell’ was set up in the police station.” + +Helric-Fredou-3 +EDITOR’S NOTE: It is not yet known to 21WIRE exactly how the fatal gun shot occurred, but if any other past political and high-profile ‘suicided’ cases are anything to go by, authorities will claim that this victim either shot himself in the back of the head, with his non-shooting hand. In addition, if that were the case, there would also be a lack of gun powder burns on the hands according to the autopsy. + +UK-based investigative reporter Morris108, interviews ‘Phil in France’ regarding this new development: + + + + +Even more bizarrely, an almost identical event took place just over one year earlier, November 2013 in Limoges, when the number 3 ranked SRPJ officer had killed himself in similar circumstances, with his weapon in the police hotel. Allegedly, his colleague discovered his body. The prosecution ruled that case was a suicide too, and the police officer had left a suicide note to his family in which he expressed “personal reasons” for his surprising action. + +Stay tuned for more updates on this story at 21WIRE. + +Sputnik News + +Police commissioner, who had been investigating the attack on the Charlie Hebdo magazine committed suicide with his service gun on Thursday night. + +Police commissioner Helric Fredou, who had been investigating the attack on the French weekly satirical magazine Charlie Hebdo, committed suicide in his office. The incident occurred in Limoges, the administrative capital of the Limousin region in west-central France, on Thursday night, local media France 3 reports. +Helric Fredou, 45, suffered from ‘depression’ and experienced ‘burn out’ [according to the official statement]. Shortly before committing suicide, he met with the family of a victim of the Charlie Hebdo attack and killed himself preparing the report. + +Fredou began his career in 1997 as a police officer at the regional office of the judicial police of Versailles. Later he returned to Limoges, his hometown. Since 2012 he had been the deputy director of the regional police service. +“We are all shocked. Nobody was ready for such developments”, a representative of the local police union told reporters. +On January 7, 2015, two gunmen burst into the editorial office of Charlie Hebdo magazine, known for issuing cartoons, ridiculing Islam. The [suspected] attackers, later identified as brothers Said and Cherif Kouachi, killed 12 people and injured 11, and escaped from the scene. Following two days of nationwide manhunt, the suspects were killed on Friday by French police some 20 miles northeast of Paris.","0" +"Charlie Hebdo investigator took own life hours after attack: report","A French police officer who was in charge of investigating last week’s attack on satirical magazine Charlie Hebdo that left 12 people dead took his own life after the massacre, French television channel France 3 reported. + +Helric Fredou reportedly shot himself on Wednesday in his police office in the west-central city of Limoges with his service weapon. + +The 45-year-old commissioner was found dead by one of his colleagues shortly after he had met with the family of a victim of the Charlie Hebdo attack. + +He reportedly killed himself while preparing the report. + +According to France 3, the senior police officer suffered from “depression” and “burn out.” + +In 2013, Fredou discovered the body of one of his colleagues who had also committed suicide. + +Last week, France was in shock following the killing of 12 people in an attack on satirical newspaper Charlie Hebdo, avowedly in retaliation for the magazine’s defiant stance in publishing cartoons they deemed offensive to Islam. + + +Last Update: Monday, 12 January 2015 KSA 17:31 - GMT 14:31","0" +"Charlie Hebdo top cop Helric Fredou kills himself hours after magazine massacre","The 45-year-old was investigating the devastating terrorist attack at Charlie Hebdo magazine when he killed himself + +VIEW GALLERY + +A senior French police officer investigating the Charlie Hebdo magazine massacre killed himself just hours after the horrific terror attack. + +Commissioner Helric Fredou, 45, shot himself in his police office in Limoges last Wednesday night, France 3 reported. + +His body was found by a colleague at 1am on Thursday, hours after the terror attack at the satirical magazine's office which left 12 people dead. + +It has been reported that shortly before committing suicide Commissioner Fredou had met with the family of one of the victims of the Charlie Hebdo attack massacre. + +Speaking to Mirror Online, the Union of Commissioners of the National Police confirmed Mr Fredou had committed suicide. + +In a statement released after his death, a spokesman for the union said: ""It is with great sadness that we were informed this morning of the death of our colleague Helric Fredou, assigned as Deputy Director of the Regional Service Judicial Police in Limoges. + +Getty Firefighters carry a victim on a stretcher at the scene of the Charlie Hebdo shooting + +""On this particular day of national mourning, police commissioners are hit hard by the tragic death of one of their own. + +""The Union of Commissioners of the National Police would like to present its most sincere condolences to the relatives of Helric. + +""In these difficult times, we have a special thought for all his colleagues."" + +Mr Fredou - who was single and had no children - began his career as a police officer in 1997, working in Versailles. + +He eventually returned to his home town of Limoges and in 2012 became deputy director of the regional police service. + +French media reports suggest he was depressed and was suffering from burnout. + +Brothers Said and Cherif Kouachi launched last Wednesday's devastating attack at the office's of the French satirical magazine. + +The attack left 12 people dead. On Friday, the pair were shot dead by police after taking a man hostage at a family-run printing press in Dammartin-en-Goele . + +In a separate incident on Friday, Amedy Coulibaly, 32, took about 15 people hostage in a Paris supermarket. + +Four hostages were killed in the incident along with Coulibaly. + +Video loading","0" +"Police officer in Charlie Hebdo investigation 'shot himself dead hours after the attack'","A top police officer involved in the Charlie Hebdo investigation killed himself within hours of the massacre. + +Helric Fredou, 45, shot himself with his police-issued gun after meeting relatives of one of the 12 victims of the terror attack at the magazine's Paris office, according to reports. + +Mr Fredou was Deputy Director of the Regional Service Judicial Police in Limoges, south of the French capital, and is believed to have been one of the leading figures in the investigation into the attack. + + +French media reported that the single police officer, who had no children, had complained of being ""depressed” and overworked before the massacre. + +His body is thought to have been discovered in his office at Limoges by a colleague at around 1am on Thursday morning. + + +Tribute: flowers, candles and a placard which reads ""I am Charlie"" are displayed during a gathering at the Place de la Republique in Paris (Picture: Reuters) +The Commissioners' Union of the National Police confirmed Mr Fredou's death. + +It said in a statement: ""It is with great sadness that we were informed this morning of the death of our colleague Helric Fredou , assigned as Deputy Director of the Regional Service Judicial Police in Limoges. + +""On this particular day of national mourning , police commissioners are hit hard by the tragic death of one of their own . + + +The two gunmen open fire in the street during the attack +""The Union of Commissioners of the National Police would like to present its most sincere condolences to the relatives of Helric."" + +Mr Fredou had been a police officer since 1997 and was appointed Deputy Director in 2012. + +His death came within hours of brothers Said and Cherif Kouachi shooting 12 people dead in Paris.","0" +"Police Chief In Charge of Paris Attacks Commits Suicide","Commissioner Helric Fredou, the person in charge of the Charlie Hebdo investigation, committed suicide on Thursday night in his office using his service weapon. The reasons behind the suicide are as yet unknown. + +According to an article on ‘Uprooted Palestinians’ blog: + +He was deputy director of the regional police service since 2012. His father was a former police officer, his mother was a nurse in the emergency context CHU Limoges. He was single and had no children. + +Advertisement + + + +According to the police union commissioner was depressed and experiencing burnout . In November 2013, the Commissioner Fredou had discovered the lifeless body of his colleague, number 3 of SRPJ Limoges, who had also committed suicide with his service weapon in his office. He was also 44 years old. + +The Commissioner Fredou, like all agents SRPJ worked yesterday on the case of the massacre at the headquarters of Charlie Hebdo. In particular, he surveyed the family of one of the victims. He killed himself before completing its report. A psychological cell was set up in the police station. + +Source: https://uprootedpalestinians.wordpress.com/2015/01/09/another-mossad-victim-police-chief-helric-fredou-investigating-charlie-hebdo-commits-suicide/ + +This story has received very little coverage in the media as yet. Are the circumstances around his death suspicious? We will keep you updated with this story as it progresses. + +- See more at: http://yournewswire.com/police-chief-in-charge-of-paris-attacks-commits-suicide/#sthash.JzwB16lg.dpuf","0" +"Teen Made $72 Million Trading Stocks, Confirms Teen Dominance Worldwide","If we've learned anything in 2014, it's that teenagers are to be both feared and revered. In a profile published over at New York magazine, one 17-year-old New Yorker confirms that he made $72 million trading stocks during his lunch break at his high school. Someone please send help!!!! + +Mohammed Islam is the son of Bengali immigrants who live in Queens. He attends Stuyvesant High School in downtown Manhattan. And now he is richer than all of us by an unfathomable margin. The profile of Islam doesn't seem willing to explain where he got the money to begin investing (there is a mention of earning tutoring money when he was nine) but it does show that teens are just as ridiculous and spunky whether they have a few bucks allowance or $72 million in investments: + +Mo, a cherubic senior with a goatee and slight faux-hawk, smiled shyly. ""He's quiet today,"" said Patrick Trablusi, who was seated with Mo and Damir at a table littered with empty glasses. ""Humble."" And tired: ""This is our third meeting of the day,"" Damir said, signaling to the waitress for another round. ""We saw a real-estate agent, a lawyer, you …"" + +""Next we're going to see a hedge-fund guy,"" Patrick said. The friends locked eyes and started to giggle. + +""He basically wants to give us $150 million,"" Mo explained, a blush like a sunset creeping over his cheeks. + +The waitress arrived with a tray of green drinks. ""Freshly squeezed apple juice,"" Damir said, passing them around. ""It's very good. Do you like caviar?"" + +New York magazine confirmed that Islam's net worth is in the high eight figures. The teen made his money trading in oil and gold but he won't stop there. Though his parents won't let him move into his rented Manhattan apartment and he can't drive his newly purchased BMW (no driver's license just yet), Islam and his team of three teen Wall Street JV investors plan on starting a hedge fund together in a few months. + +As they nobly point out, teens get the money: + +""Money never sleeps!"" Damir added. ""That's from the Wall Street movie."" + +""It all comes down to this,"" Mo continued. ""What makes the world go round? Money. If money is not flowing, if businesses don't keep going, there's no innovation, no products, no investments, no growth, no jobs."" + +What were you doing as a teenager hey don't answer that. + +[Image via LinkedIn]","0" +"The Story Of The High School Trader Who Made $72 Million Is A Rumor Spun Out Of Control","A lot of folks are buzzing about 17-year-old Stuyvesant High School senior Mohammed ""Mo"" Islam who is rumored to have made $72 million from trading. + +New York Magazine's Jessica Pressler profiled him in a recent issue. + +But a number of folks who know Islam told Business Insider that they strongly believe that the $72 million figure is just a rumor - a rumor that Islam hasn't denied. + +In the article, he acknowledged to Pressler over caviar and apple juice that his net worth was in the ""high eight figures."" + +A source familiar with the story told Business Insider that Islam is not worth $72 million. The source believes it's a rumor started by Islam's friends or partners that was perpetuated by the New York Magazine article. + +Pressler has also defended the story. She Tweeted that she saw a bank statement with the eight figures and is comfortable with what's in the piece. She also Tweeted that New York Magazine ""is not a financial publication."" + +Business Insider actually featured Islam on our list of ""20 Under 20"" in finance just over a year ago. He was nominated by his peers. + +In a phone interview on Monday Islam's partner Damir Tulemagabetov, who was also in the New York Magazine article, said the $72 million figure isn't necessarily completely accurate. + +""Let me put it this way...it's stated as a rumor,"" Tulemaganbetov told us when we asked him if he would deny the $72 million figure. He was with Islam in a car headed to CNBC's studios in New Jersey. + +""All the hype, [Islam] deserves it,"" Tulemaganbetov said. Adding that he is ""pretty sure"" Islam is a ""a great trader"" and that he's a ""genius."" + +Business Insider asked for audited numbers or P&L statements to prove that Islam's networth is close to $72 million. Tulemaganbetov refused. + +Islam himself did not respond to our email this morning requesting the numbers. He also would not get on the phone when Business Insider learned he was riding in the car to CNBC. + +The investment club for young traders, of which Islam is a member, sent Business Insider this statement regarding the $72 million figure: + +It has been brought to the attention of the Leaders Investment Club that Mohammed Islam has been rumored to have made $72,000,000 through making trades in the stock market. After performing due diligence and talking with Mohammed Islam himself, we have determined that these claims are false and simply been blown up by the media in the interests of sensationalism. + +Islam's partner Tulemaganbetov, however, would not be that clear in his coversation with Business Insider. + +""We can't just talk about the numbers. It's not just about the money,"" Tulemaganbetov said. ""We're on the verge of a lot of great things in our lives so we can't just focus on providing you the statements. We're on the verge of a lot of great things. We are going to talk to CNBC."" + +Again, Business Insider pressed the issue of the P&L statements. + +""All those statements...that's good for you. We know what we're doing. We're managing this whole hype and everything. We are trying to work with it. We were never expecting it and never denied. You have no proof."" + +Tulemaganbetov told us that Islam didn't expect all the attention. He just expected a magazine article. + +""The guy became famous all over the world in 24 hours. He's all over the world. The next thing we wake up and he's famous. This guy is a celebrity all over the world right now."" + +Tulemaganbetov told us that they were going to ""make it clear on CNBC."" + +We'll be watching.","0" +"New York schoolboy 'made $72million trading stocks on his lunch breaks' - and now takes his friends out to dine on $400 caviar, drives a BMW and has definitely made his immigrant parents proud","He has not yet reached his 18th birthday. + +But Mohammed Islam, from Queens, New York, has already made a fortune estimated at as much as $72million - from trading stocks on his lunch breaks at school, according to New York magazine's Monday issue. + +The 17-year-old, who started dabbling in penny stocks at the tender age of nine, spends most of his breaks at Stuyvesant High School trading oil and gold futures, and small to mid-cap equities. + +SCROLL DOWN FOR VIDEO + +Multi-millionaire: Mohammed Islam (pictured in a Facebook photo), 17, from Queens, New York, has already made an estimated $72million - from trading stocks on his lunch breaks at Stuyvesant High School + +Professional: The teenager (center, in glasses), who started dabbling in penny stocks at the tender age of nine, spends most of his school breaks trading oil and gold futures, and small to mid-cap equities + +Life of luxury: Outside of school, Mohammed (left, in an Instagram shot) often takes his friends out to dine at Morimoto on 10th Avenue, where they feast on $400 caviar, expensive dishes and fresh-squeezed apple juice + +Outside of school, he often takes his friends out to dine at Morimoto on 10th Avenue, where they feast on $400 caviar, expensive dishes and freshly-squeezed apple juice. + +During an interview for the magazine's 10th annual 'Reasons to Love New York issue', Mohammed refused to disclose his exact net worth, but he admitted it was in 'the high eight figures' and provided bank and financial paperwork to back that up. + +The successful teenager revealed he had used his incredible wealth to purchase a BMW - which he does not yet have a license to drive - and rent a Manhattan apartment. + +However, his parents, who are immigrants from the Bengal region of South Asia, will not yet allow him to move out of their family home in Queens, according to the New York Post. + +Mohammed has also taken to social media to show off his well-funded, lavish lifestyle - regularly posting videos of him partying, playing poker and dancing with numerous women on Instagram. + +His hard-earned cash has certainly been beneficial to his parents. 'My dad doesn't work now and I tend to help out with things, and futures gives me that incentive,' said the student. + +School: During an interview for New York magazine, Mohammed refused to disclose his exact net worth, but he admitted it was in 'the high eight figures'. Above, Stuyvesant High School, where he traded stocks + +Lavish: Mohammed has also taken to social media to show off his well-funded, lavish lifestyle - regularly posting videos of him partying, playing poker (pictured) and dancing with numerous women on Instagram + +Birthday fun: The teenager revealed he had used his wealth to purchase a BMW - which he does not yet have a license to drive - and rent a Manhattan apartment. Above, a clip from a video on Mohammed's Instagram + +This photo, also posted on the student's Instagram, shows two women holding up bottles of champagne + +But despite its advantages, Mr and Mrs Islam are not overly keen on their son's interest in trading. + +'My dad doesn't like [finance] that much,' Mohammed, who has written the phrase, 'More money, less problems', on his Instagram profile, said in an ISSUU interview. + +'He says he is ok with me trading, but my mom is skeptical about the market. But they see it as, if I am good at it, then why not?' + +A year after he started experimenting with penny stocks, Mohammed was introduced to further financial markets by his cousin. He has since developed a 'life-long passion' for trading. + +'What makes the world go round? Money,' he said. 'If money is not flowing, if businesses don’t keep going, there’s no innovation, no products, no investments, no growth, no jobs.' + +On his LinkedIn profile, the student said he rose to success while trading stocks during his lunch breaks because he 'followed the market, hunted for opportunities and used everything from fundamental analysis to technical analysis and price action to speculate in the markets'. + +After having high returns in penny stocks, he moved on to small-mid cap equities, then derivatives, before feeling out the futures market and specializing in oil and gold, he said. + +He added he has now developed 'a passion for understanding the markets and a passion for making money', and trades 'mainly based on volatility and volume'. + +Let me take a selfie: Mohammed has the phrase, 'More money, less problems', written on his Instagram profile. Above, a female reveller is pictured taking a selfie in another video on Mohammed's Instagram + +Speech: Speaking of his passion for trading stocks, Mohammed (pictured giving a speech), who trades 'mainly based on the volatility and volume' of gold and oil, said: 'What makes the world go round? Money' + +During his interview with New York magazine's, Mohammed revealed his biggest inspiration in the finance world has been Paul Tudor Jones. + +Jones, 60, the billionaire founder of Tudor Investment Corporation, a private asset management firm and hedge fund, ranks as the 108th-richest American, according to Forbes. + +Mohammed said that while he had been 'paralyzed' by his losses when he first started trading, he quickly learned from Connecticut-based Jones's ability to get back into the game again and again. + +'I had been paralyzed by my loss,' he said. 'But [Jones] was able to go back to it, even after losing thousands of dollars over and over.' + +Inspiration: Mohammed revealed his biggest inspiration in the finance world has been Paul Tudor Jones (pictured), the founder of Tudor Investment Corporation, a private asset management firm and hedge fund + +Speaking to Business Insider, he added: 'Jones’s personality and technique are what make him so successful and I aspire to become even one per cent of the man he is. + +'He went through obstacles, yet still came out on top' + +And despite his massive fortune, Mohammed has no plans to give up trading just yet. + +The teenager said he and his trader friends hope to start a hedge fund in June - when he is old enough to get his broker-dealer license - and intend to make a billion dollars by next year. + +This, of course, will all be done while attending college. + +'It’s not just about the money,' said Mohammed, whose ultimate goal is to pave a path in the financial industry that will enable him to become a reputable hedge fund manager. + +'We want to create a brotherhood. Like, all of us who are connected, who are in something together, who have influence.'","0" +"Did This Kid Really Make $72 Million During Lunch?","Money makes the world go round, right? + +Editor’s Note: Less than 24 hours after this story went viral, Islam admitted to the New York Observer that he’d made it all up and that he merely runs an investment club at his school but has not made any money in the stock market. + +Lunchtime: it’s that essential break in the day when you get to catch up with friends, check your feeds, eat some crappy lunch line food and, oh, if you’re 17-year-old Mohammed “Teen Wolf” Islam, allegedly rake in $72 million playing the stock market. + +New York magazine reported that the Queens, New York, teen made millions of dollars during his lunch breaks, which he used to buy a new BMW (which he can’t drive yet because he doesn’t have a license right now) and rent an apartment in the city. And though his parents won’t let him move out of their house just yet, the president of Stuyvesant High School’s Investment Club seems set for life before he even walks at graduation. + +The quiet son of Bengali immigrants has been profiled in his school paper and landed on a list of young money hustlers to watch in the Business Insider. When New York recently caught up with him and pal Damir Tulemaganbetov, the pair chowed down on caviar and green drinks as revealed that they were weighing an offer from a “hedge fund guy” who they said wanted to give them $150 million to invest. + +Now, along with two friends, Mohammed plans to launch his own hedge fund in June, when he turns 18 and can officially get his broker-dealer license. The trio also plan to go to college next year, but they’re not worried about Psych 101 getting in the way of their ultimate goal: $1 billion. “By next year!” said pal Damir Tulemaganbetov. “But it’s not just about money. We want to create a brotherhood. Like, all of us who are connected, who are in something together, who have influence, like the Koch brothers …” + +Damir likened Mohammed to “Wolf of Wall Street” anti-hero Jordan Belfort, who, coincidentally, also got his start in penny stocks. After a cousin showed Mohammed how to trade the stocks, the teen got hooked on it, but got spooked after losing a bunch of money he’d made tutoring… as a 9 year-old. + +“I had been paralyzed by my loss,” said Mohammed, who went on to study hedge fund managers and try to learn their secrets. He graduated to trading oil and gold and while he wouldn’t confirm the widely reported $72 million figure, Islam said his net worth is in the “high eight figures.” + +“It all comes down to this,” he said. “What makes the world go round? Money. If money is not flowing, if businesses don’t keep going, there’s no innovation, no products, no investments, no growth, no jobs.”","0" +"Teen Makes $72 Million on the Stock Market","Kids these days. + +New York Magazine recently profiled Mohammed Islam, a 17-year-old senior at Manhattan's Stuyvesant High School who decided to start trading stocks during his lunch break and found himself all the richer for it. + +$72 million richer, to be precise. + +Islam, the son of Bengali immigrants from Queens, is the president of the school's Investment Club and has been profiled by Business Insider for his financial acumen. Mo, as he's known, won't disclose his full net worth but says it's in ""the high eight figures."" + + + + +Mo's got an apartment in Midtown Manhattan, though his parents won't let him move out of their house until he's 18. He bought a BMW, but he doesn't have a license to drive it – his dad drives him on inspirational tours past the home of his idol, billionaire Paul Tudor Jones, a hedge-funder and private asset manager who's ranked the 108th richest American, according to Forbes. + +Islam recalls that, when he first experimented with penny stocks (at the tender age of 9), he lost some of the money he'd saved up from tutoring, which caused him to swear off trading briefly. But he was reinvigorated by Jones's story and quotes his idol: ""You learn more from your losses than from your gains."" + +From all appearances, Islam's learned plenty.","0" +"Doctors confirmed the first case of death from ingesting GMOs","Madrid | The doctors of the Hospital Carlos III confirmed this morning in a press conference, the first human death caused by eating genetically modified food. Juan Pedro Ramos died of anaphylaxis after eating recently developed tomatoes with fish genes, causing a violent and deadly allergic reaction. + +This surprising announcement comes after the autopsy of the Spanish man of 31, who died at the hospital in Madrid in early January. The health of the young man quickly deteriorated after suffering an allergic reaction unexplained, and all drugs used to contain anaphylaxis have been totally ineffective. The team of experts claims to have been able to determine that genetically modified tomatoes that the victim ingested at lunch, were the cause of the allergic reaction that caused his death. + +Mr. Ramos was working as a secretary in a Madrid warehouse on January 7, and began to feel sick just after lunch. A number of symptoms occurred, including a rash with violent itching, severe swelling of the throat and a drastic drop in blood pressure. The man, who was known to have allergies, quickly injected a degree add'rénaline but his health continued to deteriorate. + +The young man was quickly taken to hospital by colleagues, but the medical staff could not identify the cause of the allergic reaction in the time and no treatments or conventional medications seemed to work. Mr. Ramos was pronounced dead a little over an hour after arriving at the hospital. + +The young man seemed happy and healthy when this photo was taken by his roommate, less than 24 hours before his death. +The young man seemed happy and healthy when this photo was taken by his roommate, less than 24 hours before his death. +Forensic scientists and experts from the hospital Carlos III had to perform a wide battery of tests and analysis before we can accurately determine what caused the death of Mr. Ramos, and this because of an allergic reaction to seafood, because the only things he had swallowed before his death were bacon, lettuce and tomato sandwich accompanied by a cocacola light. They were surprised when they discovered that the tomato he had ingested allergens contained not only related to fish, but also some antibiotic resistance genes that had prevented the white blood cells of M. Ramos to save his life. + +""At first we thought there had been some form of contamination of food, contact with fish or seafood during the preparation"" , explained Dr. Rafael Pérez-Santamarina. ""It ' is that when we tested the tomato itself, we noticed that it contained certain allergens commonly found in seafood. We did a lot of different analyzes and they all confirmed that the tomato was indeed the source of allergens that killed Mr. Ramos. "" + +Several experiments on GMOs produced horrible tumors and even killed rats in laboratories, but most of GM products on the market were considered harmless to humans. +Several experiments on GMOs produced horrible tumors and even killed rats in laboratories, but most of GM products on the market were considered harmless to humans. + + +Mr. Ramos is the first human death officially confirmed linked to the ingestion of genetically modified foods. It contradicts most studies on GMOs that have concluded that genetically modified current market crops were edible and without dangers. + +A team of scientists led by the University of Nebraska had anticipated this problem in 1996, when they found that the protein of a walnut in Brazil, introduced to improve the nutritional quality of GM soy was able to cause an allergic reaction in Brazil. However, this problem has been rejected by most scientists as unlikely as it could easily be avoided with appropriate safety tests. Soybean genes injections in Brazil nuts were effectively abandoned during development, but it seems that the genetically modified tomato that caused the death of Mr. Ramos was not enough to be tested and risk of death had not been identified before marketing. + +The Spanish Ministry of Health, Social Services and Equality, which placed the order of Portuguese origin tomatoes that have infected the young man, demanded that they be repatriated and removed from shops and markets for reasons security. More than 7,000 tons of tomatoes will be seized across the country by ministry inspectors and officials of public safety. + +The ministry also made ​​a public announcement about the death of Mr. Ramos in which he offers his condolences to his family and added that ""immediately request further research on the subject, to determine if other food products GM on the European market could represent a risk for the Spanish population. ""","0" +"PICTURES: Shocking Pictures Comparing US School Lunches to Other Countries Goes Viral","Since the program’s inception, Michelle Obama’s Healthy Hunger-Free Kids Act has offended the sensibilities of the entire nation. + +Conservatives found the program to be invasive, thrusting D.C.’s hand into local education matters. Educators found the program wasted enormous amounts of food and money. Parents found the lunches far too light to be considered “meals.” And school children everywhere took to the Internet with pictures of the gruesome dishes the program sloshed onto their cafeteria trays every day. + +Those pictures did massive amounts of damage to Michelle’s pet program, but now an even worse PR disaster rears its head. This week the U.K. Daily Mail ran pictures of what other countries feed their school children. The comparison is stark … and humiliating for the United States. + +The “meal” above featuring an orange slice, a puddle of either apple sauce or a pulverized slice of peach or pear, and what looks like lumpy chipped beef without the toast is one of the dishes that complies with Michelle’s totalitarian program. + +Compare this insult to parents, palettes and taxpayers alike with what other nations feed their school children. The contrast below is striking to say the least. + +There you have it. Those are samples from a bankrupt Mediterranean nation, a former second-world nation, a financially stricken European nation, a favela-ridden South American nation and some of our other allies. + +Every single one manages to feed their schoolchildren in a more thorough, appetizing and seemingly humane way than the world’s lone remaining superpower (H/T U.K. Daily Mail). + +What Michelle Obama has done to our children’s food is a national disgrace, and she should hang her head in shame. + +Please like and share this article on Facebook and Twitter if you agree that Michelle Obama and her husband are both national disgraces.","0" +"The school lunches that shame America: Photos reveal just how meager US students' meals are compared to even the most cash-strapped of nations","Mouthwatering photos of school lunches served around the world reveal even children in Ukraine, Estonia and Greece are treated to delectable meals each day. School children in America, meanwhile, aren't nearly so lucky. + +Whereas a kid in France might be treated to a juicy steak and a hunk of brie, the richest country in the world's youths are more likely to receive unidentified meat served alongside little more than a starch like white pasta, fries or a roll. + +The contrasts between America's school meals and those in far less fortunate economies are stark and suggest Michelle Obama's push for more healthful lunches nationwide may not be enough. + +What is it? School lunches in the United States stand in stark contrast to the wholesome and in some cases even decadent meals served to kids in other markedly less fortunate nations + +The first new school lunch standards championed by Michelle Obama have been phased in over the last several school years. + +In addition to whole grain requirements, the rules set fat, calorie, sugar and sodium limits on foods in the lunch line and beyond. While many schools have had success putting the rules in place, others have said they are too restrictive and costly. + +Backlash against the rules have spawned a wave of social media photos along with the tag #thanksMichelleObama. If these pictures are any indication, schools have responded to the rules by cutting down on portions to reduce fat and calories rather than by using potentially more costly ingredients. + +Meanwhile, the widely different meals from Spain, Ukraine, Greece, South Korea, Brazil, France, Finland and Italy are all fresh and wholesome, with fish, steak and vegetables featuring prominently. + +Photos of the meals appear on Sweetgreen.com. + +But in the UK and US, lunch trays feature processed foods such as popcorn chicken, frankfurters, cookies, and beans from a tin. + +What children in other countries eat (clockwise from top left): Ukraine's version of sausage and mash; Brazil's plantains, rice and black beans; beetroot salad and pea soup in Finland and steak with beans and carrots in France (photo courtest Sweetgreen) + +South Indian school children eat off a thali plate which has white rice, sambar (dhal), smoked gourd vegetable stir-fry, curd, buttermilk and kesari, a type of sweet dessert made from semolina + +The school lunch comparisons were revealed by Sweetgreen, a chain of US restaurants, and website Never Seconds, run by Scottish schoolgirl Martha Payne, who logs her thoughts and experiences of eating school meals at her primary school in Lochgilphead, Scotland. + +The 12-year-old launched the blog in 2012 as a school writing project with assistance from her father, David, + +Written under the pseudonym 'VEG' (Veritas Ex Gustu – truth from tasting), with the subtitle 'One primary school pupil's daily dose of school dinners', the blog features daily entries on the $3 school meal that Martha/ 'VEG' has chosen that day, her thoughts on the food and its quality, a count of the number of hairs, a health rating, a picture, and marks out of 10 based on a 'Food-o-Meter'. + +Martha, who has been invited to talk in international conferences is currently raising money for Scottish charity Mary's Meals, through her JustGiving page. + +Mary's Meals - which began in 2002 as a one-off school feeding programme - currently provides daily life changing meals to over 989,000 hungry children in Africa, Asia, the Caribbean, Eastern Europe and South America. + +The surprising pictures show just how the UK and US measures up to the rest of the world when it comes to feeding schoolchildren. + +While the majority of lunches feature fresh foods, US tray is packed with processed items. + +Similarly the typical UK school lunch is sadly lacking in fresh vegetables, featuring a baked potato, sausage and beans from a tin, and a half corn on the cob with a melon slice to follow. + +Lunch in an Estonian school is rice with a piece of meat and purple cabbage. They also have bread and a get a cup of chocolate drink + +UK school dinner of frankfurters and beans, a baked potato, corn on the cob, slice of melon and a box drink + +Balanced diet: Italian children get pasta, fish, two kinds of salad, rocket and caprese, a bread roll and grapes (courtesy Sweetgreen) + +In Finland lunch is mainly a vegetarian affair of pea soup, carrots, beetroot salad, crusty roll and sweet pancake with berries to finish + +School lunch in Alba, Spain (left): white flesh peaches, strawberries and yogurt melts, cous-cous, broccoli, cucumbers and roasted salmon; (right): Poached apple pears, strawberries and blue berries, boiled swede and fresh garden peas + +In France, children start their meal with a generous slab of Brie. + +This is followed by a hearty portion of rare steak, served with two types of vegetables - carrots and green beans. + +And you won't find sweets on this lunch tray. The healthy theme continues into dessert, with the young ones tucking into kiwi fruit and apples. + +The South Korean lunch is equally as impressive. + +A milky fish soup to start followed by a serving of stir fried rice with tofu, broccoli and peppers. On the side is kimchi, the traditional Korean condiment of fermented cabbage. + +In Scandinavia, Finnish schools dish up a vegetarian lunch of pea soup, beetroot salad, carrots and a roll. For pudding there is pannakkau, a sweet pancake served with strawberries and blueberries. + +Naked man appears to climb out of Buckingham Palace window + +'Depraved' or 'hilarious'? You decide. Dakota Johnson's ISIS... + +WARNING GRAPHIC CONTENT: Homeless man shot dead by police + +Students dress as monkeys & banana to taunt black players + +Snake Vs spider! Redback traps Brown Snake in its web + +That'll teach him! Hilarious moment thief hits himself with... + +Jermaine Hopkins stars in 1989 classic Lean on Me + +Can you spot the ghost at Disneyland on CCTV? + +Sarah has sent $1.4 MILLION dollars to a man shes never met + +Watch terrifying moment skydiver has seizure while free... + +Best moments: Leonard Nimoy stars in classic Star Trek... + +Driver vs cyclist: Road rage incident caught on head cam + +South Korean children tuck into broccoli and peppers, fried rice with tofu, fermented cabbage and fish soup + +Brie, green beans, carrot, rare steak and pudding of kiwi fruit and apples is served in French schools + +A meal of traditional flavours: Brazil's rice and black beans, baked plantain, pork with peppers and coriander, green salad and a seeded roll + +Rice, a chicken croquette, a piece of taro root and yellow pea soup is the school lunch in Old Havana, Cuba + +In Japan, school children tuck into fried fish, dried seaweed, tomatoes, miso soup with potatoes, rice (in the metal container), and milk + +A plump portion of lightly fried fish sits atop rocket salad in the Italian lunch tray. This is accompanied by a small portion of pasta, a simple caprese salad of tomatoes, mozzarella and basil, a crusy roll and a bunch of grapes. + +Most of the schools have kept to traditional foods for the school lunch. + +Children in Spain start their meal with cold tomato soup, gazpacho, served with shrimp and brown rice. This is served with a seeded roll, peppers with red cabbage and half an orange for dessert. + +Children in Greece have baked chicken with orzo, stuffed grape leave, cucumber and tomato salad, yoghurt with pomegranate seeds and oranges. + +Wholesome: Seeded roll, shrimp with brown rice, gazpacho and tri-colour peppers. Dessert is half an orange + +A serving of borscht (beetroot soup) with pickled cabbage, sausages and mash. Dessert is a sweet pancake + +Greek school lunches feature baked chicken with orzo, stuffed grape leaves, salad of cucumber and tomatoes, yogurt with pomegranate seeds and two oranges + +Thanks Michelle Obama? New school lunch rules backed by FLOTUS have students nationwide tweeting '#thanksMichelleObama' along with photos of meals like these + +Traditional South American food such as rice with black beans, baked plantains and pork with vegetables are on offer for Brazilian children. They also had a side serving of salad and bread with their meal. + +In Ukraine children feast on mashed potato, sausages, borscht, cabbage and syrniki, a type of dessert pancake. + +US school lunches feature fried popcorn chicken with ketchup, mashed potatoes, peas, a fruit cup and a chocolate chip cookie. + +Bowls of salad are ready to be served at Delcare Edu Center, a local kindergarten and child care center in the business district of Singapore + +A healthier UK school dinner: Two trays at a primary school in London. The meal at right consists of pasta with broccoli and slices of bread, and fruit. At left are vegetable chili with rice and broccoli, sponge cake with custard, and a banana + +In France, school lunch is an art form: hot, multi-course and involving vegetables. A meal of rice, salmon, ratatouille, a slice of bread, a salad with celery and carrots, and an orange and donut at the Anne Franck school in Lambersart, northern France + +Naked man appears to climb out of Buckingham Palace window + +'Depraved' or 'hilarious'? You decide. Dakota Johnson's ISIS... + +WARNING GRAPHIC CONTENT: Homeless man shot dead by police + +Students dress as monkeys & banana to taunt black players + +Snake Vs spider! Redback traps Brown Snake in its web + +That'll teach him! Hilarious moment thief hits himself with... + +Jermaine Hopkins stars in 1989 classic Lean on Me + +Can you spot the ghost at Disneyland on CCTV? + +Sarah has sent $1.4 MILLION dollars to a man shes never met + +Watch terrifying moment skydiver has seizure while free... + +Best moments: Leonard Nimoy stars in classic Star Trek... + +Driver vs cyclist: Road rage incident caught on head cam","0" +"Iraq shoots down 2 UK planes delivering weapons to ISIL","Iraq's army has shot down two British planes as they were carrying weapons for the ISIL terrorists in Al-Anbar province, a senior lawmaker disclosed on Monday. + +""The Iraqi Parliament's National Security and Defense Committee has access to the photos of both planes that are British and have crashed while they were carrying weapons for the ISIL,"" Head of the committee Hakem al-Zameli said, according to a Monday report of the Arabic-language information center of the Islamic Supreme Council of Iraq. + +He said the Iraqi parliament has asked London for explanations in this regard. + +The senior Iraqi legislator further unveiled that the government in Baghdad is receiving daily reports from people and security forces in al-Anbar province on numerous flights by the US-led coalition planes that airdrop weapons and supplies for ISIL in terrorist-held areas. + +The Iraqi lawmaker further noted the cause of such western aids to the terrorist group, and explained that the US prefers a chaotic situation in Anbar Province which is near the cities of Karbala and Baghdad as it does not want the ISIL crisis to come to an end. + +Earlier today, a senior Iraqi provincial official lashed out at the western countries and their regional allies for supporting Takfiri terrorists in Iraq, revealing that US and Israeli-made weapons have been discovered from the areas purged of ISIL terrorists. + +""We have discovered weapons made in the US, European countries and Israel from the areas liberated from ISIL's control in Al-Baqdadi region,"" the Al-Ahad news website quoted Head of Al-Anbar Provincial Council Khalaf Tarmouz as saying. + +He noted that the weapons made by the European countries and Israel were discovered from the terrorists in the Eastern parts of the city of Ramadi. + +Al-Zameli had also disclosed in January that the anti-ISIL coalition's planes have dropped weapons and foodstuff for the ISIL in Salahuddin, Al-Anbar and Diyala provinces. + +Al-Zameli underlined that the coalition is the main cause of ISIL's survival in Iraq. + +""There are proofs and evidence for the US-led coalition's military aid to ISIL terrorists through air(dropped cargoes),"" he told FNA in January. + +He noted that the members of his committee have already proved that the US planes have dropped advanced weaponry, including anti-aircraft weapons, for the ISIL, and that it has set up an investigation committee to probe into the matter. + +""The US drops weapons for the ISIL on the excuse of not knowing about the whereabouts of the ISIL positions and it is trying to distort the reality with its allegations. + +He noted that the committee had collected the data and the evidence provided by eyewitnesses, including Iraqi army officers and the popular forces, and said, ""These documents are given to the investigation committee ... and the necessary measures will be taken to protect the Iraqi airspace."" + +Also in January, another senior Iraqi legislator reiterated that the US-led coalition is the main cause of ISIL's survival in Iraq. + +""The international coalition is only an excuse for protecting the ISIL and helping the terrorist group with equipment and weapons,"" Jome Divan, who is member of the al-Sadr bloc in the Iraqi parliament, said. + +He said the coalition's support for the ISIL is now evident to everyone, and continued, ""The coalition has not targeted ISIL's main positions in Iraq."" + +In late December, Iraqi Parliamentary Security and Defense Commission MP disclosed that a US plane supplied the ISIL terrorist organization with arms and ammunition in Salahuddin province. + +MP Majid al-Gharawi stated that the available information pointed out that US planes are supplying ISIL organization, not only in Salahuddin province, but also other provinces, Iraq TradeLink reported. + +He added that the US and the international coalition are ""not serious in fighting against the ISIL organization, because they have the technological power to determine the presence of ISIL gunmen and destroy them in one month"". + +Gharawi added that ""the US is trying to expand the time of the war against the ISIL to get guarantees from the Iraqi government to have its bases in Mosul and Anbar provinces."" + +Salahuddin security commission also disclosed that ""unknown planes threw arms and ammunition to the ISIL gunmen Southeast of Tikrit city"". + +Also in Late December, a senior Iraqi lawmaker raised doubts about the seriousness of the anti-ISIL coalition led by the US, and said that the terrorist group still received aids dropped by unidentified aircraft. + +""The international coalition is not serious about air strikes on ISIL terrorists and is even seeking to take out the popular (voluntary) forces from the battlefield against the Takfiris so that the problem with ISIL remains unsolved in the near future,"" Nahlah al-Hababi told FNA. + +""The ISIL terrorists are still receiving aids from unidentified fighter jets in Iraq and Syria,"" she added. + +Hababi said that the coalition's precise airstrikes are launched only in those areas where the Kurdish Pishmarga forces are present, while military strikes in other regions are not so much precise. + +In late December, the US-led coalition dropped aids to the Takfiri militants in an area North of Baghdad. + +Field sources in Iraq told al-Manar that the international coalition airplanes dropped aids to the terrorist militants in Balad, an area which lies in Salahuddin province North of Baghdad. + +In October, a high-ranking Iranian commander also slammed the US for providing aid supplies to ISIL, adding that the US claims that the weapons were mistakenly airdropped to ISIL were untrue. + +“The US and the so-called anti-ISIL coalition claim that they have launched a campaign against this terrorist and criminal group - while supplying them with weapons, food and medicine in Jalawla region (a town in Diyala Governorate, Iraq). This explicitly displays the falsity of the coalition's and the US' claims,” Deputy Chief of Staff of the Iranian Armed Forces Brigadier General Massoud Jazayeri said. + +The US claimed that it had airdropped weapons and medical aid to Kurdish fighters confronting the ISIL in Kobani, near the Turkish border in Northern Syria. + +The US Defense Department said that it had airdropped 28 bundles of weapons and supplies, but one of them did not make it into the hands of the Kurdish fighters. + +Video footage later showed that some of the weapons that the US airdropped were taken by ISIL militants. + +The Iranian commander insisted that the US had the necessary intelligence about ISIL's deployment in the region and that their claims to have mistakenly airdropped weapons to them are as unlikely as they are untrue.","0" +"Iraqi Army Downs 2 UK Planes Carrying Weapons for ISIL","TEHRAN (FNA)- Iraq's army has shot down two British planes as they were carrying weapons for the ISIL terrorists in Al-Anbar province, a senior lawmaker disclosed on Monday. +""The Iraqi Parliament's National Security and Defense Committee has access to the photos of both planes that are British and have crashed while they were carrying weapons for the ISIL,"" Head of the committee Hakem al-Zameli said, according to a Monday report of the Arabic-language information center of the Islamic Supreme Council of Iraq. + +He said the Iraqi parliament has asked London for explanations in this regard. + +The senior Iraqi legislator further unveiled that the government in Baghdad is receiving daily reports from people and security forces in al-Anbar province on numerous flights by the US-led coalition planes that airdrop weapons and supplies for ISIL in terrorist-held areas. + +The Iraqi lawmaker further noted the cause of such western aids to the terrorist group, and explained that the US prefers a chaotic situation in Anbar Province which is near the cities of Karbala and Baghdad as it does not want the ISIL crisis to come to an end. + +Earlier today, a senior Iraqi provincial official lashed out at the western countries and their regional allies for supporting Takfiri terrorists in Iraq, revealing that US and Israeli-made weapons have been discovered from the areas purged of ISIL terrorists. + +""We have discovered weapons made in the US, European countries and Israel from the areas liberated from ISIL's control in Al-Baqdadi region,"" the Al-Ahad news website quoted Head of Al-Anbar Provincial Council Khalaf Tarmouz as saying. + +He noted that the weapons made by the European countries and Israel were discovered from the terrorists in the Eastern parts of the city of Ramadi. + +Al-Zameli had also disclosed in January that the anti-ISIL coalition's planes have dropped weapons and foodstuff for the ISIL in Salahuddin, Al-Anbar and Diyala provinces. + +Al-Zameli underlined that the coalition is the main cause of ISIL's survival in Iraq. + +""There are proofs and evidence for the US-led coalition's military aid to ISIL terrorists through air(dropped cargoes),"" he told FNA in January. + +He noted that the members of his committee have already proved that the US planes have dropped advanced weaponry, including anti-aircraft weapons, for the ISIL, and that it has set up an investigation committee to probe into the matter. + +""The US drops weapons for the ISIL on the excuse of not knowing about the whereabouts of the ISIL positions and it is trying to distort the reality with its allegations. + +He noted that the committee had collected the data and the evidence provided by eyewitnesses, including Iraqi army officers and the popular forces, and said, ""These documents are given to the investigation committee ... and the necessary measures will be taken to protect the Iraqi airspace."" + +Also in January, another senior Iraqi legislator reiterated that the US-led coalition is the main cause of ISIL's survival in Iraq. + +""The international coalition is only an excuse for protecting the ISIL and helping the terrorist group with equipment and weapons,"" Jome Divan, who is member of the al-Sadr bloc in the Iraqi parliament, said. + +He said the coalition's support for the ISIL is now evident to everyone, and continued, ""The coalition has not targeted ISIL's main positions in Iraq."" + +In late December, Iraqi Parliamentary Security and Defense Commission MP disclosed that a US plane supplied the ISIL terrorist organization with arms and ammunition in Salahuddin province. + +MP Majid al-Gharawi stated that the available information pointed out that US planes are supplying ISIL organization, not only in Salahuddin province, but also other provinces, Iraq TradeLink reported. + +He added that the US and the international coalition are ""not serious in fighting against the ISIL organization, because they have the technological power to determine the presence of ISIL gunmen and destroy them in one month"". + +Gharawi added that ""the US is trying to expand the time of the war against the ISIL to get guarantees from the Iraqi government to have its bases in Mosul and Anbar provinces."" + +Salahuddin security commission also disclosed that ""unknown planes threw arms and ammunition to the ISIL gunmen Southeast of Tikrit city"". + +Also in Late December, a senior Iraqi lawmaker raised doubts about the seriousness of the anti-ISIL coalition led by the US, and said that the terrorist group still received aids dropped by unidentified aircraft. + +""The international coalition is not serious about air strikes on ISIL terrorists and is even seeking to take out the popular (voluntary) forces from the battlefield against the Takfiris so that the problem with ISIL remains unsolved in the near future,"" Nahlah al-Hababi told FNA. + +""The ISIL terrorists are still receiving aids from unidentified fighter jets in Iraq and Syria,"" she added. + +Hababi said that the coalition's precise airstrikes are launched only in those areas where the Kurdish Pishmarga forces are present, while military strikes in other regions are not so much precise. + +In late December, the US-led coalition dropped aids to the Takfiri militants in an area North of Baghdad. + +Field sources in Iraq told al-Manar that the international coalition airplanes dropped aids to the terrorist militants in Balad, an area which lies in Salahuddin province North of Baghdad. + +In October, a high-ranking Iranian commander also slammed the US for providing aid supplies to ISIL, adding that the US claims that the weapons were mistakenly airdropped to ISIL were untrue. + +“The US and the so-called anti-ISIL coalition claim that they have launched a campaign against this terrorist and criminal group - while supplying them with weapons, food and medicine in Jalawla region (a town in Diyala Governorate, Iraq). This explicitly displays the falsity of the coalition's and the US' claims,” Deputy Chief of Staff of the Iranian Armed Forces Brigadier General Massoud Jazayeri said. + +The US claimed that it had airdropped weapons and medical aid to Kurdish fighters confronting the ISIL in Kobani, near the Turkish border in Northern Syria. + +The US Defense Department said that it had airdropped 28 bundles of weapons and supplies, but one of them did not make it into the hands of the Kurdish fighters. + +Video footage later showed that some of the weapons that the US airdropped were taken by ISIL militants. + +The Iranian commander insisted that the US had the necessary intelligence about ISIL's deployment in the region and that their claims to have mistakenly airdropped weapons to them are as unlikely as they are untrue.","0" +"IRAQ ACCUSES BRITAIN OF DELIVERING WEAPONS TO ISLAMIC STATE","“The Iraqi Parliament’s National Security and Defense Committee has access to the photos of both planes that are British and have crashed while they were carrying weapons for the ISIL,” Head of the committee Hakem al-Zameli said, according to the Arabic-language information center of the Islamic Supreme Council of Iraq. + +The incident was reported by foreign and alternative media but not mentioned by the establishment media in the U.S. Europe. + + +Hakem al-Zameli, a senior Iraqi legislator, added that the current government in Baghdad is receiving daily reports from security forces in al-Anbar province about flights airdropping weapons to ISIS. + +He said the U.S. wants to promote chaos in Iraq and does this by supporting the Islamic State. + +Other Iraqi lawmakers are complaining about the situation. + +“We have discovered weapons made in the US, European countries and Israel from the areas liberated from ISIL’s control in Al-Baqdadi region,” the al-Ahad news website quoted the head of the al-Anbar Provincial Council Khalaf Tarmouz as saying. + +Weapons made in Europe and Israel were also discovered in Ramadi, Tarmouz said. + +“The US drops weapons for the ISIL on the excuse of not knowing about the whereabouts of the ISIL positions and it is trying to distort the reality with its allegations,” he said. + +In December Iranian state media claimed U.S. military aircraft dropped weapons in areas held by the Islamic State for a second time. + +Infowars.com reported: + +Iraqi volunteers fighting against IS in the Yathrib and Balad districts in Iraq’s Salahuddin Province reported the air drops. + +Iraq claims it now has the upper hand in the battle to regain territory from the terrorist group. + +In October a purported errant airdrop of weapons fell into the hands Islamic State fighters outside Kobani in Syria. + +In November Iraqi intelligence sources said the U.S. is actively supplying ISIS with weapons. + +“The Iraqi intelligence sources reiterated that the US military planes have airdropped several aid cargoes for ISIL terrorists to help them resist the siege laid by the Iraqi army, security and popular forces,” a report stated. + +“What is important is that the US sends these weapons to only those that cooperate with the Pentagon and this indicates that the US plays a role in arming the ISIL.” +In July, Infowars.com reported on the large amount of U.S. weapons captured by ISIS. + +In addition to combat ground vehicles and artillery previously acquired from the Iraqi military, the trove taken form U.S. bases included more than 50 155mm M-198 artillery batteries and 4,000 PKC machine guns. + +The acquisition of sophisticated weapons converted ISIS from a terrorist group into an army capable of waging conventional war in Iraq and Syria.","0" +"Iraqi Army Downs Two UK Planes Carrying Weapons for ISIS","There have already been been numerous reports that US led coalition planes have been air dropping supplies and weapons to Islamic State terrorists…. + +From Fars News Agency: + +Iraq’s army has shot down two British planes as they were carrying weapons for the ISIL terrorists in Al-Anbar province, a senior lawmaker disclosed on Monday. + +Advertisement + + + +Iraqi Army Downs Two UK Planes Carrying Weapons for ISIS + +Advertisement + +“The Iraqi Parliament’s National Security and Defense Committee has access to the photos of both planes that are British and have crashed while they were carrying weapons for the ISIL,” Head of the committee Hakem al-Zameli said, according to a Monday report of the Arabic-language information center of the Islamic Supreme Council of Iraq. + +He said the Iraqi parliament has asked London for explanations in this regard. + +The senior Iraqi legislator further unveiled that the government in Baghdad is receiving daily reports from people and security forces in al-Anbar province on numerous flights by the US-led coalition planes that airdrop weapons and supplies for ISIL in terrorist-held areas. + +The Iraqi lawmaker further noted the cause of such western aids to the terrorist group, and explained that the US prefers a chaotic situation in Anbar Province which is near the cities of Karbala and Baghdad as it does not want the ISIL crisis to come to an end. + +Earlier today, a senior Iraqi provincial official lashed out at the western countries and their regional allies for supporting Takfiri terrorists in Iraq, revealing that US and Israeli-made weapons have been discovered from the areas purged of ISIL terrorists. + +“We have discovered weapons made in the US, European countries and Israel from the areas liberated from ISIL’s control in Al-Baqdadi region,” the Al-Ahad news website quoted Head of Al-Anbar Provincial Council Khalaf Tarmouz as saying. + +He noted that the weapons made by the European countries and Israel were discovered from the terrorists in the Eastern parts of the city of Ramadi. + +Al-Zameli had also disclosed in January that the anti-ISIL coalition’s planes have dropped weapons and foodstuff for the ISIL in Salahuddin, Al-Anbar and Diyala provinces. + +Al-Zameli underlined that the coalition is the main cause of ISIL’s survival in Iraq. + +“There are proofs and evidence for the US-led coalition’s military aid to ISIL terrorists through air(dropped cargoes),” he told FNA in January. + +He noted that the members of his committee have already proved that the US planes have dropped advanced weaponry, including anti-aircraft weapons, for the ISIL, and that it has set up an investigation committee to probe into the matter. + +“The US drops weapons for the ISIL on the excuse of not knowing about the whereabouts of the ISIL positions and it is trying to distort the reality with its allegations. + +He noted that the committee had collected the data and the evidence provided by eyewitnesses, including Iraqi army officers and the popular forces, and said, “These documents are given to the investigation committee … and the necessary measures will be taken to protect the Iraqi airspace.” + +Also in January, another senior Iraqi legislator reiterated that the US-led coalition is the main cause of ISIL’s survival in Iraq. + +“The international coalition is only an excuse for protecting the ISIL and helping the terrorist group with equipment and weapons,” Jome Divan, who is member of the al-Sadr bloc in the Iraqi parliament, said. + +He said the coalition’s support for the ISIL is now evident to everyone, and continued, “The coalition has not targeted ISIL’s main positions in Iraq.” + +In late December, Iraqi Parliamentary Security and Defense Commission MP disclosed that a US plane supplied the ISIL terrorist organization with arms and ammunition in Salahuddin province. + +MP Majid al-Gharawi stated that the available information pointed out that US planes are supplying ISIL organization, not only in Salahuddin province, but also other provinces, Iraq TradeLink reported. + +He added that the US and the international coalition are “not serious in fighting against the ISIL organization, because they have the technological power to determine the presence of ISIL gunmen and destroy them in one month”. + +Gharawi added that “the US is trying to expand the time of the war against the ISIL to get guarantees from the Iraqi government to have its bases in Mosul and Anbar provinces.” + +Salahuddin security commission also disclosed that “unknown planes threw arms and ammunition to the ISIL gunmen Southeast of Tikrit city”. + +Also in Late December, a senior Iraqi lawmaker raised doubts about the seriousness of the anti-ISIL coalition led by the US, and said that the terrorist group still received aids dropped by unidentified aircraft. + +“The international coalition is not serious about air strikes on ISIL terrorists and is even seeking to take out the popular (voluntary) forces from the battlefield against the Takfiris so that the problem with ISIL remains unsolved in the near future,” Nahlah al-Hababi told FNA. + +“The ISIL terrorists are still receiving aids from unidentified fighter jets in Iraq and Syria,” she added. + +Hababi said that the coalition’s precise airstrikes are launched only in those areas where the Kurdish Pishmarga forces are present, while military strikes in other regions are not so much precise. + +In late December, the US-led coalition dropped aids to the Takfiri militants in an area North of Baghdad. + +Field sources in Iraq told al-Manar that the international coalition airplanes dropped aids to the terrorist militants in Balad, an area which lies in Salahuddin province North of Baghdad. + +In October, a high-ranking Iranian commander also slammed the US for providing aid supplies to ISIL, adding that the US claims that the weapons were mistakenly airdropped to ISIL were untrue. + +“The US and the so-called anti-ISIL coalition claim that they have launched a campaign against this terrorist and criminal group – while supplying them with weapons, food and medicine in Jalawla region (a town in Diyala Governorate, Iraq). This explicitly displays the falsity of the coalition’s and the US’ claims,” Deputy Chief of Staff of the Iranian Armed Forces Brigadier General Massoud Jazayeri said. + +The US claimed that it had airdropped weapons and medical aid to Kurdish fighters confronting the ISIL in Kobani, near the Turkish border in Northern Syria. + +The US Defense Department said that it had airdropped 28 bundles of weapons and supplies, but one of them did not make it into the hands of the Kurdish fighters. + +Video footage later showed that some of the weapons that the US airdropped were taken by ISIL militants. + +The Iranian commander insisted that the US had the necessary intelligence about ISIL’s deployment in the region and that their claims to have mistakenly airdropped weapons to them are as unlikely as they are untrue.","0" +"HORROR: ISIS Fighters Have Reportedly Contracted Ebola","The World Health Organization is looking into reports that ISIS fighters in Iraq have been showing up at hospitals with Ebola symptoms. + +According to the pro-government Iraqi newspaper al Sabaah, an unknown number of ISIS militants have shown up at a hospital in the militant-controlled city of Mosul, about 250 miles north of Baghdad. The paper reported that foreign terrorists brought the disease into Mosul from “several countries” in Africa. (RELATED: ISIS Massacred Every Man And Boy Over 15 In Muslim Town) + +It’s not yet clear whether the ISIS extremists actually have Ebola or another disease. Ebola symptoms include fever, vomiting, diarrhea and unexplained bleeding and bruising — problems which could also be attributed to malaria or yellow fever. And doctors in Mosul might be unable to even test for Ebola. + +WHO spokeswoman Christy Feig said the organization is reaching out to officials in the ISIS-held area to offer help if the disease does turn out to be Ebola. However, United Nations workers are not allowed to work in ISIS-controlled areas in either Iraq or Syria, so a UN operation to help either ISIS militants or any civilians in the areas who contract Ebola is unlikely. + +Feig told Mashable that there’s been no official notification from the Iraqi government that the terrorists’ disease is, in fact, Ebola. + +ISIS is against western science and medicine as a rule, but apparently several militants have taken to hospitals with Ebola-like symptoms anyway. Since taking control of Mosul in June 2014, ISIS has taken to executing doctors that refuse to treat them. + +Kurdish news website Rudaw reported in Nov. 2014 that ISIS executed six doctors in Mosul for refusing to treat wounded fighters, in addition to kidnapping six merchants for failing to pay a monthly tax to ISIS. The group reportedly executed two more doctors just last week. + +The U.S. has been hitting ISIS with air strikes since mid-November and the Pentagon confirmed in December that the strikes have killed around 1,000 fighters, including three senior ISIS officials. + +An Ebola outbreak, however unlikely, probably wouldn’t help matters much. + +Follow Sarah on Twitter","0" +"Iraqi media says ISIS militants have contracted Ebola","Reports that Islamic State militants in Mosul have contracted Ebola swirled though Iraqi media sources on Wednesday. World Health Organization officials said they haven't confirmed the cases, but the organization has reached out to offer assistance. + +Three outlets reported that Ebola showed up at a hospital in Mosul, a city 250 miles north of Baghdad that's been under ISIS control since June 2014. The reports, however, have perpetuated mostly in pro-government and Kurdish media. + +""We have no official notification from [the Iraqi government] that it is Ebola,"" Christy Feig, WHO's director of communications told Mashable. + +Feig added that WHO is in the process of reaching out to government officials in Iraq to see if they need help investigating the cases, a task that could be a challenge, given the restrictions that would come with operating in ISIS-controlled territory. + +It's unclear if any disease experts or doctors in Mosul are even able to test for the Ebola virus. A Kurdish official, who was convinced the cases are Ebola, told the Kurdish media outlet Xendan that the militants' symptoms were similar to those of the Ebola virus. + +However, Ebola symptoms — nausea and vomiting, diarrhea, bleeding and bruising — are also similar to those associated with a number of other diseases, including malaria, Lassa fever, yellow fever viruses and the Marburg virus. Also, most confirmed Ebola cases in this recent outbreak have originated in West Africa. + +Citing an unnamed source in a Mosul hospital, Iraq's official pro-government newspaper, al Sabaah, said the disease arrived in Mosul from ""terrorists"" who came ""from several countries"" and Africa. + +While ISIS has recruited foreign fighters, very few of them — if any at all — are believed to have traveled from West Africa. + +The majority of the Islamic State's African fighters came from Tunisia, according to a Washington Post report. Others came from Morocco, Libya, Egypt, Algeria, Sudan and Somalia — none of which reported any Ebola cases in 2014. + +If the cases in Mosul turn out to be Ebola — a scenario that, at this point, seems highly unlikely — it would mark the first time the virus had been detected in an area controlled by ISIS, a group that doesn't embrace science and modern medicine. + +Over the past few weeks, militants affiliated with ISIS have executed more than a dozen doctors in Mosul, according to Benjamin T. Decker, an intelligence analyst with the Levantine Group, a Middle East-based geopolitical risk and research consultancy. + +""U.N. workers have thus far been prohibited from entering ISIS-controlled territory in both Iraq and Syria,"" Decker, who specializes in Iraq, told Mashable. + +""In this context,"" he said, ""the lack of medical infrastructure, supplies and practitioners in the city suggests that the outbreak could quickly lead to further infection of both ISIS fighters and residents of Mosul."" + +Have something to add to this story? Share it in the comments.","0" +"WHO ‘probing’ whether ISIS fighters got Ebola","Islamic State fighters are no match for Ebola. + +The World Health Organization is investigating whether some ill jihadists have contracted the killer disease, two sources at the agency told The Post. + +Agency officials are checking if there are Ebola patients at a Mosul hospital 250 miles north of Baghdad, sources said. + +Al-Sabah, an Iraqi pro-government newspaper, reported this week that the fighters were being treated for Ebola, while some of their comrades have come down with HIV brought by foreign extremists “coming from many countries, particularly those in Africa.” + +“The Ebola virus could be in any area in the world, including Mosul, where they don’t have the measures or techniques to diagnose the virus,” ministry spokesman Ahmed Rudaini told Iraqi media Thursday. “They are incapable to detect it.”","0" +"ISIS cracks down on five confirmed Ebola cases among fighters: official","BAGHDAD, Iraq – The Islamic State (ISIS) incinerated the corpses of five militants who were suspected of contracting Ebola, an Iraqi health official indicated. + +Faisal Ghazi, member of the Health Committee in Iraq’s council of ministries, said the five were incinerated in Mosul, the ISIS stronghold in Iraq. + +“The Islamic State organization incinerated five militants infected with Ebola to prevent further spread of the disease in Mosul,” he said. + +“ISIS had proof that these militants were infected with Ebola,” he added, without giving details of whether the fighters died of the disease or were killed and incinerated by the group. + +The UN’s World Health Organization (WHO) had been investigating cases of Ebola in Mosul, following reports that some militants with Ebola symptoms had reported to a hospital in the city. + +ISIS volunteers have poured into Iraq and Syria from around the world, including countries in Africa.","0" +"IRAQI AND KURDISH MEDIA REPORTS: ISIS FIGHTERS HAVE CONTRACTED EBOLA","Multiple Iraqi and Kurdish media sources have claimed that some Islamic State (ISIS) militants in Mosul, Iraq, have contracted the deadly Ebola virus, Mashable reports. + +The Iraqi outlets reportedly claimed that Ebola had started to spread in a Mosul hospital. The city, known as ISIS’s most important strategic stronghold in Iraq, has been under the control of the Islamic State since June. + +Christy Feig, the World Health Organization (WHO) director of communications, told Mashable, “We have no official notification from the Iraqi government that it is Ebola.” She said that WHO had reached out to authorities and asked if they needed help investigating the matter. + +Kurdish media network Xendan reported that ISIS jihadists’ symptoms were similar to those shown by someone who has contracted Ebola. However, it is highly uncertain whether Mosul health authorities have the means, tools, or skill-set necessary to test for Ebola, given the current hostile environment in the area. + +In late December, the Islamic State reportedly executed doctors who refused to treat their militant jihadis. The Washington Post said of the ongoing situation in Mosul, “Services are collapsing, prices are soaring, and medicines are scarce in towns and cities across the ‘caliphate’ proclaimed in Iraq and Syria by ISIS.” + +Iraq’s pro-government Al Sabaah (The Morning) daily newspaper reported that Ebola made its way into Mosul through Africa-based Islamist “terrorists” who then linked up with ISIS. Mashable notes, however, that the majority of ISIS recruits in Africa have come from countries that have not reported any Ebola cases, such as Tunisia, Egypt, Morocco, Libya, and others. + +Meanwhile, Mosul’s liberation remains a strategic priority for Iraqi forces and the U.S.-led coalition. Mosul has been described as ISIS’s de facto capital in Iraq. While under ISIS control, many of the city’s one million residents have lived under fear of severe punishment or execution should they not comply with the jihadists’ mandates.","0" +"IRAQI HEALTH OFFICIAL: EBOLA HAS KILLED 5 ISIS FIGHTERS","The Islamic State terror group has burned the corpses of five of its fighters due to the belief that they had contracted the deadly Ebola virus, according to an Iraqi health official who told Kurdish paper Rudaw. + +“The Islamic State organization incinerated five militants infected with Ebola to prevent further spread of the disease in Mosul (Iraq),” said Faisal Ghazi, who is part of Iraq’s Health Committee in its council of ministries. He added, “ISIS had proof that these militants were infected with Ebola.” + +On New Year’s Day, Breitbart News reported that multiple Iraqi and Kurdish news outlets had claimed that Islamic State fighters in Mosul, Iraq had contracted the deadly virus. Iraqi news outlets claimed at the time that Ebola had started to spread in a Mosul hospital. + +A World Health Organization (WHO) official told Mashable at the time, “We have no official notification from the Iraqi government that it is Ebola. + +Kurdish news site Xendan elaborated further, reporting that the ISIS fighters’ symptoms were similar to those who had contracted Ebola. An Iraqi paper claimed that the virus had made its way into Mosul through jihadists who were recruited out of Africa. + +However, most of the Islamic State’s Africa-based recruits have come from countries where Ebola has not had a documented presence. It also remains unclear whether Mosul health officials would even have the means, training or education necessary to test for Ebola. Furthermore, an Iraqi government spokesman, Ahmed Rudaini, told Al-Maalomah News that Mosul simply doesn’t have the technology available to confirm an Ebola case.","0" +"Is Ebola Virus Spreading Among ISIS Militants? Reports Claim Jihadists Seeking Cure at Mosul Hospital","The World Health Organization is investigating reports that ISIS militants have contracted the deadly Ebola virus and are seeking help at a hospital in Mosul in Iraq. The virus, which has claimed thousands of lives in West Africa, is believed to have been brought to the city by jihadists from several different countries. + +WHO spokesman Christy Feig confirmed that the health agency is reaching out to ISIS officials in the region to gather more information, The Daily Mail noted on Friday. Feig said that the Iraqi government hasn't yet responded to the news of possible Ebola cases in the country. + + +Free Sign Up CP Newsletter! + + + + +Want to build your credit? Start with us. + +Apply for a Capital One® MasterCard® in just a few clicks. It’s fast, easy and secure. + +Sponsored by Capital One + + +RELATED + +Iraqi Soldier Turned Baghdad Cab Driver Reveals How Iraq's 50,000 Ghost Soldiers Operate Their Scam + + +Boko Haram's Bloodiest Year Yet: Over 9,000 Killed, 1.5 Million Displaced, 800 Schools Destroyed in 2014 + + +ISIS Releases Interview With Captive Jordanian Pilot, Tweet Requests for Ways to Kill Hostage + + +ISIS Executes Nearly 2,000 People in Syria in Six Months + +An unconfirmed number of jihadists apparently sought treatment at the hospital in Mosul, which was captured by ISIS earlier this year. Local newspaper al Sabaah has claimed that the virus was brought to Mosul by terrorists arriving from several countries in Africa. + +As of the end of 2014, the total death count from the largest Ebola outbreak in history stands at 7,890 people, while over 20,000 have been diagnosed with the disease, for which there is no cure. + +The West African countries of Guinea, Liberia and Sierra Leone have been the hardest hit. While the former two have seen the transmission rate go down significantly in the past couple of months, Sierra Leone remains in a fierce battle to contain the virus. + +ISIS captured several cities across Iraq and Syria in 2014, and has been seeking to establish an Islamic caliphate in the region. + +Confirmation of Ebola cases will likely be difficult, however, as U.N. workers are prohibited from entering militant-controlled areas. + +The militants have become known for executing prisoners, including women and children, and giving Christians and other religious minorities an option to convert to Islam, pay a tax or be killed. Over a dozen doctors have reportedly been executed by ISIS in recent weeks for refusing to treat their injured fighters. + +The Daily Mail pointed out that there is no information on whether doctors still working in Mosul are trained or equipped to fight a possible Ebola outbreak. + +Since Ebola shares symptoms with other diseases including malaria and yellow fever, it is also possible that the cases so far have been misdiagnosed. + +It is also not know how many fighters from West African countries could have joined ISIS, though tens of thousands of foreigners and several other jihadist groups have reportedly rallied under the Islamic State banner. + +Nigerian terror group Boko Haram also pledged allegiance to ISIS in 2014 — Nigeria experienced its own scare with Ebola after a number of cases of the virus were reported, but the country was declared Ebola-free by October.","0" +"ISIS fighters 'have contracted Ebola': World Health Organisation investigating reports militants showed up at Iraqi hospital with lethal disease","The World Health Organisation is investigating reports that ISIS militants have been showing up at an Iraqi hospital with Ebola. + +According to three media outlets an undisclosed number of militants displaying signs of the disease attended a hospital in the ISIS-held city of Mosul, 250 miles north of Baghdad. + +While the reports, from Kurdish and pro-Iraqi sources, remain unconfirmed, WHO spokesman Christy Feig said the group are trying to reach out to officials in ISIS-held areas to offer help. + +Infection: Several ISIS militants have arrived at a hospital in Mosul displaying signs of Ebola according to unconfirmed reports + +UN workers are currently banned from entering ISIS-controlled areas in both Iraq and Syria so it is unlikely an operation in the region could be carried out. + +Ms Feig told Mashable: 'We have no official notification from [the Iraqi government] that it is Ebola.' + +The symptoms of ebola are similar to those of other diseases including malaria and yellow fever + +Mosul has been under control of ISIS since June 2014 and over the past few weeks militants have reportedly executed more than a dozen doctors for refusing to treat injured fighters. + +According to a report in Iraq's pro-government newspaper, al Sabaah, the disease was brought to Mosul by 'terrorists' arriving 'from several countries' and Africa. + +The symptoms of Ebola, which include nausea and vomiting, diarrhea, bleeding and bruising, are similar to those of other diseases including malaria and yellow fever meaning it could easily have have been misdiagnosed. + +In addition, very few ISIS fighters are believed to have travelled up from West Africa where the Ebola outbreak originated with most coming from areas where there have been no reports of the disease. + +The reports have appeared in pro-government and Kurdish media but if true it could have catastrophic implications for people in ISIS-held areas as the group is against western science and medicine. + +It is not known if any of the surviving doctors in Mosul are equipped to test for Ebola or trained to treat patients and prevent the spread of the disease. + +ISIS fighters pictured in June 2014, when the extremist group swept through Iraq seizing territory including the city of Mosul + +Yesterday the United States and its allies staged 29 air strikes on Islamic State targets in Syria and Iraq on Wednesday, the Combined Joint Task Force said. + +The action in Syria included 17 strikes near the cities of Al Raqqah, Dayr az Zawr and Kobani. A variety of Islamic State buildings, fighting positions and units were hit. + +In Iraq, 12 strikes targeted Islamic State buildings, fighting positions and units near the cities of Mosul, Fallujah and Sinjar. + +Fighters, bombs and remotely controlled aircraft were used.","0" +"WHO investigates media reports ISIS fighters contracted Ebola","Several Iraqi news sources, including Al Sabah and the website al-Maalomah, reported on Wednesday that several ISIS fighters sought help at a hospital in Mosul, 250 miles north of the city of Baghdad, after developing symptoms of Ebola virus infection. +Citing anonymous sources in a hospital in Mosul, Al-Sabah reported that two cases of Ebola and 26 cases of HIV/AIDS were confirmed by health authorities in Mosul. The newspaper also claimed that ISIS recruits from some African countries brought the virus to Iraq. +The International Business Times UK also carried a similar report, quoting Iraqi news sources. +But a spokesperson for the Iraqi health ministry, Ahmed Rudaini, has denied reports that two cases of Ebola virus infection were diagnosed among ISIS militants in Mosul. The Iraqi health ministry spokesperson said the infection couldn't have been confirmed in Mosul because none of the hospitals in the city have the diagnostic facilities. He said only the Central Laboratory of Public Health in Baghdad has the ability to confirm cases of Ebola virus infection. +Responding to inquiries from Mashable, a WHO spokesperson, Christy Feigh, said, ""We have no official notification that it is Ebola."" +Feigh said the WHO was investigating the reports and would give assistance if needed. But because UN workers are banned from entering ISIS-held areas in Iraq and Syria, it is unclear how the organization would be able to confirm the report or render assistance in suspected cases. +Mashable, however, reports that a Kurdish official who appeared convinced that the reports were accurate told the Kurdish news outlet Xendan that the militants reported at the hospital in Mosul with symptoms of Ebola virus infection. +While Iraqi health officials are probably not taking the reports seriously, an outbreak of Ebola among ISIS militants could have serious consequences due to lack of access to the ISIS-held areas. It is also feared that ISIS militants could use the presence of the virus among its militants as a terror weapon against opponents, further complicating the prosecution of the war against the extremist group. +However, the symptoms of Ebola virus, including vomiting, diarrhea and bleeding in the late stages of the disease are similar to those of several other diseases, including malaria, yellow fever and typhoid fever. Thus, it is possible that the militants who reported at the hospital in Mosul were suffering from other diseases that have symptoms similar to Ebola. +Given the fact that the reports were carried exclusively on pro-government newspapers, it is not possible to rule out that they were designed to cause confusion among ISIS fighters and discourage new recruits from joining the group. It is not known that ISIS has a significant number of recruits from West African countries where the epidemic has been reported. Thousands of foreign recruits to ISIS arrived mostly from North African countries such as Tunisia, Libya, Egypt, Algeria and Somalia where there have been no reports of Ebola outbreak. +The Ebola virus epidemic has claimed thousands of lives in the West African countries of Sierra Leone, Liberia and Guinea. +Recently, Nigerian news sources reported that ISIS was making efforts to recruit fighters from the country. The report led the Nigerian government to issue a statement urging some Middle Eastern countries to carry out thorough background checks on Nigerians applying for visas. +The report that some ISIS militants might have contracted Ebola comes a few weeks after Benjamin T. Decker, intelligence analyst and Iraq specialist with the Middle East research firm Levantine Group, said that ISIS executed about 11 doctors in Mosul for refusing to treat wounded militants. +Mosul was among several cities ISIS fighters captured earlier in the year 2014. The militants declared an Islamic caliphate in the areas they captured. Mosul, in particular, has been under ISIS control since June 2014. The city has reportedly suffered food, water and power shortages since extremist militants took over. Residents have suffered brutal treatment with reports of executions and enslavement of minorities women and children. +On Wednesday, the US and its allies carried out 17 airstrikes in Syria and 12 in Iraq. The airstrikes in Syria targeted ISIS facilities in Al Raqqah, Dayr az Zawr and Kobani, while the strikes in Iraq hit ISIS buildings and positions around Mosul, Fallujah and Sinja.","0" +"Fears Islamic State could launch EBOLA attack on Britain after fighters 'contract virus'","FEARS have been raised that Islamic State could target Britain with an EBOLA attack after two of the terror group's fighters reportedly contracted the deadly virus. + +Sources at a hospital in the northern Iraqi city of Mosul say they have seen suspected cases involving two IS fighters. + +They are believed to have unknowingly travelled from their African homelands with Ebola. + +The news will spark fears that the jihadists could use the killer virus to hit Britain with so-called ""human-bug bombs"". + +Intelligence experts have already urged authorities to be ready for members of the extremist outfit deliberately trying to spread Ebola in the West. + +Even if a calculated plot does not emerge, experts fear Ebola could be accidentally spread by IS — also known as ISIS and ISIL — should it tear through the group's ranks. + +The World Health Organisation (WHO) was last night scrambling to uncover more information about the Iraqi infection claims. + +WHO officials have offered to assist the Iraqi government in investigating any potential outbreak. + +However, experts are concerned that the lack of resources and doctors — caused by IS's bloody campaign in Syria and Iraq — could make cases impossible to probe and treat. + +IS fighters have reportedly killed more than a dozen doctors, who may have been able to confirm the diagnoses, in Mosul. + +Meanwhile Western medics, who would normally travel to the Middle East to help, face terrifying risks of kidnap and beheading by IS. + +Ebola's potential appearance in Mosul was reported by three separate media outlets yesterday. + +Mosul is 250 miles north of Baghdad and has been controlled by IS since June, 2014. + +Al-Sabaah, an Iraqi newspaper, said two cases of Ebola and 26 of AIDS were reported in the city. + +Citing medical sources, it claimed the virus had been transported from ""terrorists"" who came ""from several countries"" in Africa. + +WHO director of communications Christy Feig said there has been ""no official notification"" from the Iraqi government that Ebola has been confirmed. + +The organisation is trying to contact Iraqi officials to see if help can provided to investigate any suspected cases in rebel-controlled areas of the country. + +Meanwhile a Kurdish official told media outlet Xendan the fighters’ symptoms were similar to those experienced by Ebola sufferers. + +However, the effects of Ebola can resemble those caused by a number of illnesses, including malaria and Lassa and Yellow Fever. + +They include nausea and vomiting, diarrhoea, bleeding and bruising. + +Middle East-based intelligence analyst Benjamin Decker said IS's killing of medics and its decision to ban Westerners from its territory could allow Ebola to spread rapidly. + +He said: ""United Nations workers have thus far been prohibited from entering ISIS-controlled territory in both Iraq and Syria. + +""In this context the lack of medical infrastructure, supplies and practitioners in the city suggests that the outbreak could quickly lead to further infection of both ISIS fighters and residents of Mosul."" + +Hundreds of Britons are believed to have to travelled to join IS forces, with some already heading home. + +Security and intelligence services monitor those who come back to see if they have renounced the terror network’s barbaric regime or whether they remain suspected terrorists plotting UK atrocities. + +However, the current system may not equip security services for motoring symptoms of the Ebola, according to the WHO, has killed around 8,000 people in West Africa and affected areas so far. + +IS is a hardline jihadist group, which formerly had ties to al-Qaeda. + +It seized vest swathes of Iraq and Syria in August in a bid to create a so-called caliphate. + +brightcove.createExperiences();","0" +"Has Ebola infected Isis militants in Mosul?","Islamic State (Isis) militants in Mosul may have contracted Ebola, according to Iraqi media reports of suspected cases at an IS-controlled hospital in the city. + +The government and Kurdish media reported that militants were displaying symptoms similar to those of Ebola. The World Health Organization has not been able to confirm this but has offered assistance to Iraqi officials. + +Iraq's official pro-government newspaper, al Sabaah, said Ebola arrived in Mosul from ""terrorists"" who came ""from several countries and Africa"", reports Mashable. + +However, it is uncertain if any IS recruits came from the Ebola-hit regions of West Africa. Most have come from Tunisia, Morocco, Libya, Egypt, Algeria, Sudan and Somalia. + +A number of other illnesses could be to blame for the fighters' symptoms. Malaria, Lassa fever, yellow fever and the Marburg virus could all be confused with Ebola as they can also cause fever, nausea, vomiting and diarrhoea. + +IS, a group that has been known to dismiss some aspects of science and modern medicine, recently executed a number of Iraqi doctors in Mosul for refusing to treat militants. UN workers have also been prohibited from entering their territory, an intelligence analyst who specialises in Iraq told Mashable. + +RelatedEbola patient Pauline Cafferkey receives experimental drug and blood from survivorsEbola outbreak: Setback to Liberia, as fresh cases reportedSyria: Isis publicly whips three drug addicts and burns vast supply of cannabisIsis militants flog man for watching porn in Syria","0" +"ISIS Militants In Mosul Have Contracted Ebola, Iraqi Media Sources Claim","With the threat of an ISIS terror attack becoming ever more real, Iraqi media reported yesterday that some of the group’s militants have contracted the deadly Ebola virus, although World Health Organization officials have yet to confirm the reports. + +An International Business Times article from today confirms that three Iraqi news outlets reported that Ebola showed up at a hospital in Mosul, a city 250 miles north of Baghdad which has been under ISIS control since June 2014. + +Christy Feig, WHO’s director of communications, casted doubt on the report though, telling reporters, “We have no official notification from [the Iraqi government] that it is Ebola.” + +On top of that, it isn’t clear whether any disease experts or doctors in Mosul are even able to test for the Ebola virus. A Kurdish official, who was convinced the cases are Ebola, told the Kurdish media outlet Xendan that the militants’ symptoms were similar to those of the Ebola virus. + +Nonetheless, Ebola symptoms, like nausea and vomiting, diarrhea, and bleeding, are also similar to those associated with a number of other diseases, including malaria, Lassa fever, yellow fever viruses, and the Marburg virus. + +Iraq’s pro-government newspaper, al Sabaah, reported that the disease arrived in Mosul from “terrorists” who came “from several countries” in Africa. + +According to a Washington Post report, the majority of the ISIS’ African fighters came from Tunisia, while others came from Morocco, Libya, Egypt, Algeria, Sudan, and Somalia — none of which reported any Ebola cases in 2014. + +Benjamin T. Decker, an intelligence analyst with the Levantine Group, said that over the past few weeks, militants affiliated with ISIS have executed more than a dozen doctors in Mosul. + +“U.N. workers have thus far been prohibited from entering ISIS-controlled territory in both Iraq and Syria,” he said. + +Decker added, “In this context, the lack of medical infrastructure, supplies and practitioners in the city suggests that the outbreak could quickly lead to further infection of both ISIS fighters and residents of Mosul.”","0" +"Ebola Outbreak 2015 Update: ISIS Fighters May Have Contracted Deadly Virus","Sick jihadis are being tested for Ebola. +ISIS fighters are being evaluated by the World Health Organization for the deadly virus. WHO is also checking a Mosul hospital 250 miles north of Baghdad for others who may be infected, according to the New York Post. +Mosul has been under ISIS control since June 2014. +However, Iraqi newspaper Al-Sabah reported the fighters do have Ebola and are being treated. +ISIS Terror News: Political Official Reveals India's Ban on Vimeo, Github, Imgur and 29 Other Websites Is Due to 'Jihadi Propaganda' From Terrorist Group + +Pope Francis Christmas Speech Compares ISIS Refugees to Jesus +""The Ebola virus could be in any area in the world, including Mosul, where they don't have the measures or techniques to diagnose the virus,"" ministry spokesman Ahmed Rudaini said. ""They are incapable to detect it.""  +Though some Iraqi news outlets have confirmed cases of Ebola, the country's health ministry has denied the reports. +""We have no official notification from [the Iraqi government] that it is Ebola,"" WHO director Christy Feig told Mashable. +If the ill patients are determined to have Ebola, it would be the first time an ISIS-controlled area has the virus. ISIS does not believe in modern medicine or science, making it a potentially problematic situation. +""U.N. workers have thus far been prohibited from entering ISIS-controlled territory in both Iraq and Syria,"" said Benjamin T. Decker, an intelligence analyst for Levantine Group. ""In this context, the lack of medical infrastructure, supplies and practitioners in the city suggests that the outbreak could quickly lead to further infection of both ISIS fighters and residents of Mosul."" +In late December, more than a dozen Centers for Disease Control and Prevention workers were being evaluated for the disease. A sample of the pathogen was taken from one lab to another, and mistakes made by technicians possibly exposed workers, according to the CDC.","0" +"Iraqi and Kurdish media reports cases of Ebola among Islamic State fighters in Mosul","THERE are unconfirmed reports that jihadists fighting for the Islamic State have contracted Ebola. + +Local media outlets reported that cases of Ebola have showed up at a hospital in the IS-controlled city of Mosul, in Iraq, Mashable reported. + +Iraq’s official pro-government newspaper, al Sabaah, claimed that the disease had arrived in Mosul from jihadists “from several countries” including Africa. + +An official told the Kurdish media outlet Xendan that the militants’ symptoms were similar to those of the Ebola virus. Although the symptoms of Ebola, which include nausea, vomiting and diarrhoea, can easily be mistaken for many other illnesses such as malaria. + +The World Health Organisation (WHO) has been unable to confirm the cases. + +Christy Feig, WHO’s director of communications told Mashable they were in the process of reaching out to government officials in Iraq to see if help was needed investigating the cases. + +IS counts fighters from a number of African countries among its ranks though few, if any, are known to have come from areas hit by Ebola.","0" +"ISIS Militants Have Contracted Ebola: Iraqi, Kurdish Media Reports","Several Iraqi media sources stated Wednesday that some of the Islamic State militants in Mosul have contracted Ebola. + + +Three Iraqi media outlets reported that two cases of Ebola have been 'recorded' in Mosul, which is considered to be the jihadist group's stronghold.","0" +"ISIS Militants Allegedly Contracted Ebola","A group of ISIS militants in Iraq have allegedly gone to a local hospital to be treated for what is believed to be Ebola. + +Three local media outlets reported this week that a number of ISIS fighters have shown signs of the deadly disease and were taken to a hospital in Mosul to be treated. The reports are currently unconfirmed, but the World Health Organization says that they are investigating the claims and that they are attempting to reach out to officials in the area to offer help. + +“We have no official notification from [the Iraqi government] that it is Ebola,” WHO’s director of communications Christy Feig told Mashable in a statement. + +Feig reportedly went on to acknowledge that, despite their best efforts to offer help to area officials, if Ebola has in fact reached them, having an impact in an ISIS-controlled area could prove to be challenging. + +Ebola reached epidemic levels last year in parts of Africa, and fear that the virus would spread in the United States took over the headlines for weeks this past fall. However, so far, the disease has yet to make any serious impact in the states. + +Iraq’s pro-government newspaper al Sabaah claims that the disease has spread to Mosul through “terrorists” coming from “several countries” in Africa. + +Symptoms of Ebola include nausea and vomiting, diarrhea, bruising, and severe bleeding, but any of those ailments could be attributed to a number of other conditions, so it’s not entirely clear if the reported Ebola diagnoses are accurate. + +Sources: Daily Mail, Mashable / Photo Sources: Mashable, Daily Mail","0" +"Biological Warfare on the Horizon? ISIS Soldiers May Be Infected With Ebola","It's what national security organizations have feared since day one-the World Health Organization (WHO) announced last week that they are evaluating jihadist militants associated with ISIS, who may have contracted the virus responsible for Ebola. While the WHO has yet to confirm whether or not the fighters are exhibiting symptoms, the current evaluations of a Mosul hospital 250 miles north of Baghdad are prompting concerns that the fringe extremist group ISIS may in fact be able to obtain a biological weapon unlike anything the world has seen before. + +Like Us on Facebook + +Though Mosul has been under ISIS control since late last June, the Iraqi health ministry has issued a press release denying reports from Iraqi news outlets that claim the soldier are definitively infected and seeking treatment in Mosul. + +""The Ebola virus could be in any area in the world, including Mosul, where they don't have the measures or techniques to diagnose the virus"" spokesperson for the health ministry Ahmed Rudaini says. ""They are incapable to detect it."" + +Over the past several months, the world has watched as threats from extremist group ISIS have come true, from the beheadings of captured prisoners of war to the mass murder of children's schools. And with the possibility of a global pandemic looming over our heads, many are demanding action be taken to isolate the potential vectors as a worst case scenario. Yet, as conflicting reports abound, international health organizations and the WHO are unable to assess the health concern on site, and treat the patients as their own. + +WHO director Christy Feig told reporters early this weekend that "" We [the WHO] have no official notification from the Iraqi government that it is Ebola."" + +While that may be true, the possibility that the militants may have contracted the virus causes a problematic situation for the WHO, in that ISIS does not believe in modern medicine and an outbreak in an ISIS-controlled area like Mosul could be a breeding ground for the ever-mutating virus. But worst of all, aside from the possibility of possible infection of Iraq, should ISIS isolate the virus for themselves, the entire western world may find soon enough that the Ebola virus could be the worst weapon known to man. + +""U.N. workers have thus far been prohibited from entering ISIS-controlled territory in both Iraq and Syria,"" intelligence analyst for Levantine Group, Benjamin T. Decker says. ""In this context, the lack of medical infrastructure, supplies and practitioners in the city suggests that the outbreak could quickly lead to further infection of both ISIS fighters and residents of Mosul.""","0" +"ISIS fighters ‘have contracted Ebola’","The World Health Organisation is investigating reports that ISIS militants have been showing up at an Iraqi hospital with Ebola, repots Mail Online. + +According to three media outlets an undisclosed number of militants displaying signs of the disease attended a hospital in the ISIS-held city of Mosul, 250 miles north of Baghdad. + +While the reports, from Kurdish and pro-Iraqi sources, remain unconfirmed, WHO spokesman Christy Feig said the group are trying to reach out to officials in ISIS-held areas to offer help. + +UN workers are currently banned from entering ISIS-controlled areas in both Iraq and Syria so it is unlikely an operation in the region could be carried out. + + +Feig told Mashable: 'We have no official notification from [the Iraqi government] that it is Ebola.' + +Mosul has been under control of ISIS since June 2014 and over the past few weeks militants have reportedly executed more than a dozen doctors for refusing to treat injured fighters. + +According to a report in Iraq's pro-government newspaper, al Sabaah, the disease was brought to Mosul by 'terrorists' arriving 'from several countries' and Africa. + +Advertisement + +The symptoms of Ebola, which include nausea and vomiting, diarrhea, bleeding and bruising, are similar to those of other diseases including malaria and yellow fever meaning it could easily have been misdiagnosed. + +In addition, very few ISIS fighters are believed to have travelled up from West Africa where the Ebola outbreak originated with most coming from areas where there have been no reports of the disease. + +The reports have appeared in pro-government and Kurdish media but if true it could have catastrophic implications for people in ISIS-held areas as the group is against western science and medicine. + +It is not known if any of the surviving doctors in Mosul are equipped to test for Ebola or trained to treat patients and prevent the spread of the disease. Yesterday the United States and its allies staged 29 air strikes on Islamic State targets in Syria and Iraq on Wednesday, the Combined Joint Task Force said. + +ISIS fighters pictured in June 2014, when the extremist group swept through Iraq seizing territory including the city of Mosul. Photo-AFP +ISIS fighters pictured in June 2014, when the extremist group swept through Iraq seizing territory including the city of Mosul. Photo-AFP +The action in Syria included 17 strikes near the cities of Al Raqqah, Dayr az Zawr and Kobani. A variety of Islamic State buildings, fighting positions and units were hit. + +In Iraq, 12 strikes targeted Islamic State buildings, fighting positions and units near the cities of Mosul, Fallujah and Sinjar. + +Fighters, bombs and remotely controlled aircraft were used.","0" +"Iraqi media: ISIS militants have contracted Ebola","(Mashable) Reports that Islamic State militants in Mosul have contracted Ebola swirled though Iraqi media sources on Wednesday. World Health Organization officials said they haven’t confirmed the cases, but the organization has reached out to offer assistance. + +Three outlets reported that Ebola showed up at a hospital in Mosul, a city 250 miles north of Baghdad that’s been under ISIS control since June 2014. The reports, however, have perpetuated mostly in pro-government and Kurdish media. + +“We have no official notification from [the Iraqi government] that it is Ebola,” “We have no official notification from [the Iraqi government] that it is Ebola,” Christy Feig, WHO’s director of communications told Mashable.","0" +"Weaponized Ebola? ISIS Militants Said To Contract Deadly Virus","Forget targeted US airstrikes, ISIS faces a new existential threat. Citing an unnamed source in a Mosul hospital, Iraq's official pro-government newspaper, al Sabaah, said Ebola arrived in Mosul from ""terrorists"" who came ""from several countries"" and Africa. Mashable further confirms, three outlets reported that Ebola showed up at a hospital in Mosul. For now, it's unclear if any disease experts or doctors in Mosul are even able to test for the Ebola virus; but it would mark the first time the virus had been detected in an area controlled by ISIS, a group that doesn't embrace science and modern medicine. + + + +As Mashable reports, + +Reports that Islamic State militants in Mosul have contracted Ebola swirled though Iraqi media sources on Wednesday. World Health Organization officials said they haven't confirmed the cases, but the organization has reached out to offer assistance. + +... + +""We have no official notification from [the Iraqi government] that it is Ebola,"" Christy Feig, WHO's director of communications told Mashable. + +Feig added that WHO is in the process of reaching out to government officials in Iraq to see if they need help investigating the cases, a task that could be a challenge, given the restrictions that would come with operating in ISIS-controlled territory. + +It's unclear if any disease experts or doctors in Mosul are even able to test for the Ebola virus. A Kurdish official, who was convinced the cases are Ebola, told the Kurdish media outlet Xendan that the militants' symptoms were similar to those of the Ebola virus. + +... + +Citing an unnamed source in a Mosul hospital, Iraq's official pro-government newspaper, al Sabaah, said the disease arrived in Mosul from ""terrorists"" who came ""from several countries"" and Africa. + +... + +If the cases in Mosul turn out to be Ebola — a scenario that, at this point, seems highly unlikely — it would mark the first time the virus had been detected in an area controlled by ISIS, a group that doesn't embrace science and modern medicine. + +Over the past few weeks, militants affiliated with ISIS have executed more than a dozen doctors in Mosul, according to Benjamin T. Decker, an intelligence analyst with the Levantine Group, a Middle East-based geopolitical risk and research consultancy. +* * * +The question now is - will Nobel Peace Prize winning President Obama send his humanitarian non-boots-on-the-ground military advisors to help? + +* * * + +However, as The International Business Times reports, officials are denying the reports... + +Iraq's Ministry of Health also denied that anyone in Mosul had contracted the Ebola virus, which broke out in March in West Africa. + +Spokesman Ahmed Rudaini told news site Al-Maalomah that Mosul doesn't even have the technological capability to diagnose Ebola cases -- only Baghdad does. Therefore, he said, the reports that Ebola has infected anyone in Mosul are ""incorrect"" and ""unfounded."" +But, perhaps most concerning, + +In the event ISIS does have Ebola, the militants could use it as a biological terror technique, Forbes reported in October. Members could contract the virus on purpose and then go to foreign countries to infect others. + +“The individual exposed to the Ebola virus would be the carrier,” national security professor Al Shimkus told Forbes. “In the context of terrorist activity, it doesn’t take much sophistication to go to that next step to use a human being as a carrier.” +* * *","0" +"Report: 4 ISIS Terrorists Caught at Southern Border in 36 Hrs","A report from Judicial Watch stated that four ISIS members were apprehended at the Mexican border.","0" +"GOP Rep: ‘At Least Ten ISIS Fighters Have Been Caught Coming Across The Mexican Border’","WASHINGTON (CBS DC) – Rep. Duncan Hunter, R-Calif., says that at least ten fighters for the Islamic State of Iraq and Syria have been apprehended while attempting to enter the southern U.S. border. +The California Republican claims that “at least ten ISIS fighters have been caught coming across the Mexican border in Texas,” in a conversation with Fox News on Tuesday. Hunter says that the Islamic terrorists are slipping into the U.S. through the porous southern border as several have already been captured. +“There’s nobody talking about it,” Rep. Hunter told Fox. “If you really want to protect Americans from ISIS, you secure the southern border. It’s that simple…They caught them at the border, therefore we know that ISIS is coming across the border. If they catch five or ten of them then you know there’s going to be dozens more that did not get caught by the border patrol.” +In August, Chairman of the Joint Chiefs of Staff, Gen. Martin Dempsey, warned that the open border posed an “immediate threat” for terrorist activity infiltrating the country. The government watchdog group, Judicial Watch, said ISIS terrorists were “planning to attack the United States with car bombs or other vehicle born [sic] improvised explosive devices.” +Hunter, a member of the House Armed Services Committee, said that the 1,933-mile southern border with Mexico is the obvious entry point for Islamic State terrorists. He says that information regarding the capture of Islamic State terrorists crossing the border comes directly from U.S. Customs and Border Protection. +“ISIS doesn’t have a navy, they don’t have an air force, they don’t have nuclear weapons. The only way that ISIS is going to harm Americans is by coming through the southern border – which they already have,” he added. +“They aren’t flying B-1 bombers, bombing American cities,” said Hunter. “But they are going to be bombing American cities coming across from Mexico…All you have to do is ask the border patrol.” +The Department of Homeland Security released a statement on Wednesday that claims alleging Islamic State militants have been apprehended at the Mexican border are “categorically false.” +“The suggestion that individuals who have ties to ISIL have been apprehended at the Southwest border is categorically false, and not supported by any credible intelligence or the facts on the ground,” a DHS spokesman said in a statement today. “DHS continues to have no credible intelligence to suggest terrorist organizations are actively plotting to cross the southwest border.” +After Hunter’s comments to Fox, one of his sources nuanced their claims, saying that some of those apprehended at the border might be ISIS-affiliated or possibly Americans who fought with the Syrian Free Army – one of many ISIS enemies. +In a statement to ABC News, a spokesperson for Hunter said he was not backing down on the claims. +“The Congressman was conveying what he knows — and what he was told,” the spokesperson told ABC. “It makes sense that the left hand of DHS doesn’t know what the right hand is doing — it’s been that way for a long time and we don’t expect that to change.” +– Benjamin Fearnow","0" +"Two GOP Congressmen Say Suspected Terrorists Caught Crossing U.S.–Mexico Border","A Texas National Guard soldier scans the Mexican side of the U.S.–Mexico border in Havana, Texas. John Moore / Getty Images + +Two Republican lawmakers told BuzzFeed News Wednesday suspected terrorists have infiltrated the U.S.–Mexico border and as many as 10 fighters have been captured, but Homeland Security officials deny any such thing has happened. + +Rep. Jason Chaffetz, a Republican from Utah, said four alleged terror suspects were captured on Sept. 10 in Texas. In an interview Wednesday, Chaffetz said the men flew from a Middle Eastern country to Mexico City, where they paid a smuggler to take them to and across the border. From there, the men ended up in a safe house for immigrants. They were en route to New York City, Chaffetz said, when they were captured. + +Chaffetz would not reveal his source of the information, but said he confirmed it with government officials. “I had an informant tell me about it and then I questioned the Secretary of Homeland Security,” he said. “I have no doubt about its authenticity.” + +The four alleged terror suspects had affiliations with groups other than the Islamic State in Iraq and Syria (ISIS), Chaffetz said. He added that they were still being held in Texas as of Wednesday. + +youtube.com + +California Rep. Duncan Hunter, a Republican who represents San Diego County, made headlines Tuesday when he said to Fox News’ Greta Van Susteren that he had “asked Border Patrol” about terrorists and learned that several had been captured. + +Hunter claimed 10 terror suspects had been caught near the border, including four people allegedly captured in September. + +“I know at least 10 ISIS fighters have been caught coming across the Mexican border in Texas,” he said on the program. + +Hunter’s spokesman Joe Kasper told BuzzFeed News the congressman’s assertion that 10 terror suspects had been captured along the border included the same four people described by Chaffetz. Kasper claimed four other suspects had been captured within the last 36 hours, and pointed to a Judicial Watch story that allegedly “confirmed” the most recent captures to back up his assertion. + +Two additional suspects were picked up sometime after the first group in September, but before this week, Kasper said. + +The Department of Homeland Security strongly denied Hunter’s claim that terror suspects had been caught near the border. + +When reached for comment, Customs and Border Protection referred BuzzFeed News to the Department of Homeland Security (DHS), which did not respond to emails Wednesday. However, DHS released an identical statement to both The New Republic and ABC News denying that there were terrorists coming across the border: + +The suggestion that individuals who have ties to ISIL have been apprehended at the Southwest border is categorically false, and not supported by any credible intelligence or the facts on the ground. DHS continues to have no credible intelligence to suggest terrorist organizations are actively plotting to cross the southwest border. + +But Hunter isn’t buying that explanation. His spokesman told BuzzFeed News Wednesday that they have evidence from reliable sources about “foreign nationals” being captured along the border. Kasper said those foreign nationals may not technically be ISIS fighters, but do have suspected terror group affiliations. Kasper did not identify his sources but said that Hunter’s office remains convinced that the lawmaker was correct. + +A U.S. Border Patrol vehicle drives by the 18-foot rusty steel barrier along the U.S.–Mexico border in Brownsville, Texas. Rick Wilking / Reuters + +The issue of terrorists coming over the U.S.–Mexico border has been a contentious and increasingly politicized one. + +Among the other claims about terrorists using the border to enter the country, Rep. Tom Cotton, a Republican from Arkansas, said ISIS may be teaming up with Mexican drug cartels. Audio recorded at a town hall apparently showed Cotton saying that ISIS could potentially attack people in Arkansas, the Washington Post reported Tuesday. + +w.soundcloud.com + +Cotton did not respond to BuzzFeed News’ request for comment Wednesday, but when the Post asked about the statements his spokesman pointed to a series of conservative websites. And like many of the claims about the border and terrorism, the story goes back months and relies on sources who are not named — making it difficult to verify.","0" +"This Is Why Rumors That ISIS Is Crossing The Border Into The U.S. Aren’t Going Away","Border Patrol agents detain immigrants who crossed from Mexico into the United States near McAllen, Texas, June 27, 2014. The state’s Rio Grande Valley has been the epicenter of a surge illegal immigration in recent months. Molly Hennessy-Fiske/Los Angeles Times / MCT + +The Department of Homeland Security has repeatedly said that the assertion that ISIS-affiliated terrorists were arrested while crossing the U.S.-Mexico border is “categorically false and not supported by any credible intelligence or facts on the ground.” + +But the vice president of the largest union representing Border Patrol agents told BuzzFeed News on Thursday that DHS — which oversees the Border Patrol — is incorrect. And he said, the incident highlights the need for more funding for the Border Patrol, + +“I haven’t been able to outright confirm that it happened, but from what I have heard it sounds very credible,” said Shawn Moran, the vice-president of the National Border Patrol Council, which represents some 17,000 Border Patrol employees, “From what people have read to me, from what they say they have seen in documents, it seems pretty legit.” + +Moran admitted he had not seen the document himself. He added that he did not know the name of the official who prepared the report, or what agency did that official work for, but that his “instincts told” him the official was with the Border Patrol. He also declined to tell BuzzFeed News who had told him about the report in the first place. + +When asked what would be the appropriate response to the alleged incident, Moran said that the Border Patrol needs more funding and more people to do its job and prevent ISIS from entering the U.S. again. + +A spokeswoman with the Department of Homeland Security declined to discuss Moran’s specific statements, but insisted that “DHS continues to have no credible intelligence to suggest terrorist organizations are actively plotting to cross the southwest border.” + +Moran’s statements Thursday followed allegations from two Republican lawmakers who told BuzzFeed News on Wednesday that suspected terrorists have infiltrated the U.S.–Mexico border and as many as 10 fighters have been captured. + +The persistence of these rumors may stem from the arrests in September of four people with suspected ties to terrorism that were later found to be unfounded, Secretary of Homeland Security Jeh Johnson said in a speech Thursday. + +“Four individuals were arrested, their supposed link to terrorism was thoroughly investigated and checked, and in the end amounted a claim by the individuals themselves that they were members of the Kurdish Worker’s Party – an organization that is actually fighting against ISIL and defended Kurdish territory in Iraq,” said Johnson. “Nevertheless, these individuals have been arrested for unlawful entry, they are detained, and they will be deported.” + +Reports that terrorists affiliated with Islamist groups have tried to enter the United States through the southern border have circulated around the web for months, even before ISIS became a household term. + +In July, for example, members of a volunteer armed militia told Breitbart News they were concerned because they had found what they thought was a “Muslim Prayer Rug” in the Arizona desert. + +Thus far, the threat embodied by that alleged rug has failed to materialize.","0" +"Congressman: ‘At least 10 ISIS fighters’ caught trying to cross into US","mboxCreate('FoxNews-Politics-Autoplay-Videos-In-Articles'); + +A Republican congressman claimed Tuesday that ""at least 10"" Islamic State ""fighters"" have been caught trying to cross the U.S.-Mexico border into Texas, though an administration official denied it. + +Rep. Duncan Hunter, R-Calif., said he learned the information from the Border Patrol, warning that the alleged attempts to cross into the U.S. raise serious security concerns. + +""ISIS is coming across the southern border,"" he told Fox News. ""They aren't flying B1 bombers bombing American cities, but they are going to be bombing American cities coming across from Mexico."" + +Hunter continued: ""I know that at least 10 ISIS fighters have been caught coming across the Mexican border in Texas."" + +He claimed Border Patrol ""caught them,"" but ""you know there's going to be dozens more that did not get caught by the Border Patrol."" + +The Department of Homeland Security on Wednesday denied Hunter's claim. + +""The suggestion that individuals who have ties to ISIL have been apprehended at the Southwest border is categorically false, and not supported by any credible intelligence or the facts on the ground,"" a senior DHS spokesman said. ""DHS continues to have no credible intelligence to suggest terrorist organizations are actively plotting to cross the southwest border."" + +But Hunter spokesman Joe Kasper said the information -- that about 10 individuals with ""known ISIS affiliations"" -- came from a ""high-level source within the Border Patrol."" + +""The congressman was conveying what he knows -- and what he was told,"" Kasper said. ""It makes sense that the left hand of DHS doesn't know what the right hand is doing -- it's been that way for a long time and we don't expect that to change."" + +Obama administration officials previously have downplayed the threat of Islamic State militants infiltrating the U.S. through the southern border, as warnings about that possibility have circulated. + +Homeland Security Secretary Jeh Johnson, in an interview with Fox News last week, acknowledged reports that four men with suspected terror ties had been apprehended at the southern border in Texas and questioned. But Johnson said they were ""scrutinized very, very carefully"" and officials found ""no evidence that these individuals were tied to terrorism."" + +Border Patrol and Homeland Security sources also told Fox News that they have not been able to substantiate Hunter's claim. They said between Sept. 23 and Oct. 6, only five illegal immigrants from ""special interest"" countries were arrested at the Texas border -- and they were from Bangladesh. + +The four men that Johnson referred to were actually Kurds, Fox News is told. + +Johnson, at a hearing last month, stressed that the government had ""no specific intelligence or evidence to suggest at present that ISIL is attempting to infiltrate this country though our southern border."" + +At the same hearing, National Counterterrorism Center head Matthew Olsen also said: ""There has been a very small number of sympathizers with ISIL who have posted messages on social media about this, but we've seen nothing to indicate there is any sort of operational effort or plot to infiltrate or move operatives from ISIL"" into the U.S. through the southern border. + +Still, Johnson said the U.S. needs to be ""vigilant"" and aware of the possibility of ""potential infiltration by ISIL or any other terrorist group."" + +The union representing America's immigration caseworkers also sounded an urgent warning last month about the threat. Kenneth Palinkas, president of the National Citizenship and Immigration Services Council, alleged the administration has made it easier for terrorists to ""exploit"" the country's visa policies and enter the homeland. + +He complained that the administration has ""widened the loophole"" they could use through the asylum system, and has restricted agents from going after many of those who overstay their visas. + +Further, he warned that executive orders being contemplated by President Obama would ""legalize visa overstays"" and raise ""the threat level to America even higher."" He said there is ""no doubt"" many are already being ""targeted for radicalization."" + +FoxNews.com's Judson Berger and Fox News' Jennifer Griffin and William La Jeunesse contributed to this report.","0" +"GOP Rep. Duncan Hunter Claims 'At Least' 10 ISIS Fighters Apprehended On Texas Border","Rep. Duncan Hunter (R-Calif.) claimed Tuesday that ""at least"" 10 Islamic State fighters were apprehended while attempting to enter the U.S. at its southern border. + +The San Diego Republican said U.S. Border Patrol ""sources"" told him that ""at least 10 ISIS fighters have been caught coming across the Mexican border in Texas."" + +""If you really want to protect Americans from ISIS, you secure the southern border -- it’s that simple,"" he said. ""They caught them at the border, therefore we know that ISIS is coming across the border. If they catch five or 10 of them then you know there’s going to be dozens more that did not get caught by the border patrol,"" he said on Fox News’ ""On the Record with Greta Van Susteren."" + +""ISIS doesn’t have a navy, they don’t have an air force, they don’t have nuclear weapons,"" he added. ""The only way that ISIS is going to harm Americans is by coming through the southern border -- which they already have."" + +Two of the country's top intelligence officials said last month they had no credible evidence to support the theory that militants are operating next door, nor that they are plotting to sneak across the border. + +A spokesperson for the Department of Homeland Security said Wednesday that Hunter's claim otherwise was ""categorically false."" + +""The suggestion that individuals who have ties to ISIL have been apprehended at the Southwest border is categorically false, and not supported by any credible intelligence or the facts on the ground,"" DHS spokeswoman Marsha Catron told The Huffington Post. ""DHS continues to have no credible intelligence to suggest terrorist organizations are actively plotting to cross the southwest border."" + +Hunter, who sits on the House Armed Services Committee, isn't the first member of Congress to raise the alarm about the prospect of extremists crossing the border. Sen. Marco Rubio (R-Fla.) suggested last month that such infiltration was possible, and Rep. Jeff Duncan (R-S.C.) said it was already happening. Texas Gov. Rick Perry (R) has also sounded similar notes about terrorists crossing his state's border from Mexico. GOP Rep. Tom Cotton, who is running for the U.S. Senate in Arkansas, claimed Tuesday that extremists were actively collaborating with Mexican drug cartels to infiltrate the U.S. border and attack Arkansans. + +Asked for comment on Wednesday, a spokesman for Hunter said the information came for a ""high level source"" and that DHS was ""actively discouraging any talk of IS on the border."" + +""The congressman was conveying what he knows -- and what he was told,"" Hunter spokesman Joe Kasper told The Huffington Post. ""And as for DHS’ statement, it makes sense that the left hand of DHS doesn’t know what the right hand is doing -- it’s been that way for a long time and we don’t expect that to change. No surprise there.""","0" +"ISIS Fighters Getting Caught Coming Across the U.S.-Mexican Border?","From the midweek edition of the Morning Jolt: + +Say What? ‘At Least Ten ISIS Fighters Have Been Caught Coming Across the Border’ + +Rep. Duncan Hunter, Republican of California, does not seem like a nut job or prone to wild exaggerations. But last night he said something that should make jaws drop: + +Van Susteren: Hold on. Stop for one second. + +Hunter: They are going to be bombing American cities coming across from Mexico. + +Van Susteren: Let me ask a question. You say that they are coming in the southern border, which changes all the dynamics Do you have any information that they are coming in through the southern border now? + +Hunter: Yes. + +Van Susteren: Tell me what you know. + +Hunter: At least ten ISIS fighters have been caught coming across the border in Texas. + +Van Susteren: How do you know that? + +Hunter: Because I’ve asked the border patrol, Greta. + +Van Susteren: And the border patrol just let’s ISIS members come across the border? + +Hunter: No. They caught them at the border. Therefore, we know that ISIS is coming across the border. If they catch five or ten of them, you know that there are going to be dozens more that did not get caught by the border patrol. That’s how you know. That’s where we are at risk here, is from ISIS and radical Islamists coming across the border. Once again, they don’t have a navy, air force, nuclear weapons. The only way that Americans are going to be harmed by radical Islam — Chairman Dempsey said the same thing. He said that’s where the major threat is here, that’s how these guys are going to infiltrate through America and harm Americans. + +Then add this comment by a House Democrat: + +Rep. Tim Bishop (D., N.Y.) warned during a recent speech that up to 40 radicalized U.S. citizens who have fought alongside the Islamic State of Iraq and Levant (ISIL or ISIS) have already returned to the United States, where they could pose a terrorist threat. + +Bishop claims that of the 100 or so Americans who have traveled to the Middle East to join ISIL’s ranks, some 40 have returned and are currently being surveilled by the FBI, according to his remarks, which were filmed and uploaded to YouTube last week. + +“One of the concerns is the number of U.S. citizens who have left our country to go join up with ISIS,” Bishop said during the speech. “It is believed there have been some number up to 100 that have done that.” + +“It is also believed that some 40 of those who left this country to join up with ISIS have now returned to our country,” Bishop said, eliciting shocked responses from some in the crowd. + +Is the threat of ISIS terrorists crossing our southern border no longer theoretical? Could the administration really successfully cover up something as big as this?","0" +"Rep. Duncan Hunter: 'At Least 10' ISIS Fighters Caught at Mexican Border","""At least 10"" Islamic State (ISIS) fighters were captured trying to cross the Mexico border into Texas, Rep. Duncan Hunter of California claims, but the Department of Homeland security has called his statements ""categorically false."" + +Hunter told Fox News he learned the information from the Border Patrol, saying ""they aren't flying B1 bombers bombing American cities, but they are going to be bombing American cities coming across from Mexico."" +Vote Now: +Story continues below video. + + + +The Border Patrol ""caught them,"" Hunter said, but ""you know there's going to be dozens more that did not get caught by the Border Patrol."" + +A senior Department of Homeland Security spokesman said Wednesday that suggestions that people with ties to ISIS have been apprehended at the southwest border are ""not supported by any credible intelligence or the facts on the ground."" +Special: +The spokesman also said there is no credible intelligence suggesting any terrorist organizations are ""actively plotting to cross the southwest border."" + +Hunter spokesman Joe Kasper said the information about the individuals ""with known ISIS affiliations"" came from a ""high-level source within the Border Patrol,"" and the congressman is merely ""conveying what he knows, and what he was told."" + +Kasper said ""the left hand of DHS doesn't know what the right hand is doing. It's been that way for a long time and we don't expect that to change."" + +Hunter is not alone in saying the Islamic State agents have crossed the border. Last month, former CIA agent Bob Baer told CNN that there are already ISIS cells in the United States, and he has learned from intelligence services that some of the extremist group's agents have crossed the Mexican border. + +While DHS maintains there is no evidence that anyone with terrorist ties has come across from Mexico, Homeland Security Secretary Jeh Johnson acknowledged to Fox News last week that four men with suspected ties were stopped at the border and questioned, although officials found ""no evidence that these individuals were tied to terrorism."" + +Johnson also emphasized at a hearing last month that there was ""no specific intelligence or evidence"" showing the Islamic State is trying to come across the Mexican border. + +National Counterterrorism Center head Matthew Olsen, during the same meeting, said there have been some ISIS sympathizers posting social media messages, but ""we've seen nothing to indicate there is any sort of operational effort or plot to infiltrate or move operatives"" across the border.","0" +"Judicial Watch's Farrell: ISIS Terrorists Did Cross Mexican Border","Judicial Watch has reported that ISIS members crossed the Mexican border.","0" +"SEE IT: ISIS militants caught trying to cross border into Texas, Congressman claims","Rep. Duncan Hunter said Border Patrol agents have captured ‘at least 10 ISIS fighters’ trying to enter the U.S. from Mexico. The California congressman’s bombshell on Fox News Tuesday also claims more militants may already be here. + +ISIS may already be here. + +In an alarmist bombshell statement that intersects both America’s war on terror and its fight to secure the border with Mexico, Rep. Duncan Hunter said ISIS fighters have been caught attempting to cross into the U.S. + +Hunter, a California Republican and former Marine major, told Fox News Channel’s Greta Van Susteren on Tuesday that Border Patrol agents have captured Islamic State in Iraq and Syria militants trying to get into Texas from Mexico. + +“ISIS is coming across the southern border,” said Hunter, whose district includes much of San Diego. “They aren’t flying B-1 Bombers bombing American cities, but they are going to be bombing American cities coming across from Mexico. + +“At least 10 ISIS fighters have been caught coming across the Mexican border in Texas,” Hunter continued. “There’s nobody taking about it.” + +When Van Susteren pressed him for his source, the Congressman replied: “I’ve asked the Border Patrol.” + +“They caught them at the border,” Hunter said. “Therefore, we know ISIS is coming across the border. If they catch five or 10 of them you know there are going to be dozens more that did not get caught by the Border Patrol.” + +jmolinet@nydailynews.com Follow on Twitter @jmolinet + +ON A MOBILE DEVICE? CLICK HERE TO WATCH THE VIDEO.","0" +"Lawmaker Says ‘At Least 10′ Islamic State Fighters Have Been Captured at the Southern U.S. Border","Rep. Duncan Hunter (R-Calif.) said Tuesday night that U.S. border officials have caught “at least 10″ Islamic State fighters or people with ties to the group as they tried to enter the U.S. through Mexico, a claim that was immediately disputed by the Obama administration. + +“I know that at least 10 ISIS fighters have been caught coming across the Mexican border in Texas,” Hunter said on Fox News Tuesday night. “There’s nobody talking about it.” + +When asked by host Greta Van Susteren how he knows this, Hunter said, “Because I’ve asked the Border Patrol, Greta.” + +The Department of Homeland Security spokeswoman disputed Hunter’s claim on Wednesday morning. + +“The suggestion that individuals who have ties to ISIL have been apprehended at the southwest border is categorically false, and not supported by any credible intelligence or the facts on the ground,” said Marsha Catron. “DHS continues to have no credible intelligence to suggest terrorist organizations are actively plotting to cross the southwest border.” + +But Hunter’s office replied by saying Hunter was told directly by a senior official that people with ties to the Islamic State have in fact been apprehended. + +“A high level source within the Border Patrol told the congressman otherwise,” said Hunter spokesman Joe Kasper. “The congressman was conveying what he knows — and what he was told. It makes sense that the left hand of DHS doesn’t know what the right hand is doing — it’s been that way for a long time and we don’t expect that to change.” + +Hunter said Tuesday that the biggest risk that the Islamic State poses to Americans is by trying to enter the U.S. illegally and committing acts of terrorism. + +“If you really want to protect Americans from ISIS, you secure the southern border,” he said. “It’s that simple.” + +“ISIS doesn’t have a navy, they don’t have an air force, they don’t have nuclear weapons,” he added. “The only way that ISIS is going to harm Americans is by coming in through the southern border, which they already have.” + +The Obama administration has come under increased scrutiny about border enforcement in light of fears that Islamic State fighters could try to enter the U.S. through Mexico. Officials were already under fire for its effort to ease immigration rules, which many Republicans say has created even more incentive for people to try entering the country illegally. + +— This story was updated at 10:37 a.m.","0" +"US Lawmaker: Ten ISIS Fighters Have Been Apprehended Coming Across Southern Border (Video)","Rep. Duncan Hunter (R-CA) told Greta Van Susteren tonight that ten ISIS fighters have crossed the border from Mexico into America. + +Greta Van Susteren: You say they’re coming in the southern border which changes the dynamics. Do you have any information or any evidence that they are actually coming in the southern border now? + +Rep. Hunter: Yes. + +Greta: Tell me what you know? + +Rep. Hunter: I know that at least ten ISIS fighters have been caught coming across the southern border in Texas. + +Via On the Record: + +In September Rep. Jason Chaffetz (R-UT) also said four known terrorists were apprehended at the the US border in Texas and were still being held.","0" +"ISIS leader dead?","A Sept. 8 U.S. Department of Defense news article talking about the success of airstrikes in Iraq mentions a question from the media — and answer — about the leader of ISIS, Abu Bakr al-Baghdadi. + +From the article: + +In response to a question about the reported deaths of ISIL leader Abu Bakr al-Baghdadi and some of his advisors in an air strike, (Pentagon spokesman Army Col. Steve) Warren said the U.S. has not conducted any targeted airstrikes against specific ISIL personnel. + +“I hope he’s dead. We certainly hope he’s dead, but we haven’t conducted any strikes against him,” he said. + +“With every terrorist that we kill from the air, that is one less terrorist on the ground,” the colonel added. + +Warren also said this in talking about the airstrikes against ISIS: + +Certainly, ISIL forces realize that when American airpower is deployed, their chance of survival goes to nil.” + +You can read the whole article here. + +And an article by The Associated Press on The Gazette’s website says U.S. President Barack Obama will address his nation Wednesday night to outline plans for an expanded U.S. effort to confront ISIS in Iraq and Syria. + +– Jillian","0" +"Report: ISIS Leader Abu Bakr Al-Baghdadi Assassinated In U.S. Airstrike","An unverified photo claims to show the body of ISIS leader Abu Bakr al-Baghdadi after he was purportedly killed by US air strikes against three senior members of ISIS. An aide to al-Baghdadi were also killed by US air strikes. + +The ISIS leader was reportedly killed during an air strike in the city of Mosul, which ISIS forces took over this summer. + +Pentagon Spokesman Col. Steve Warren could not confirm the deaths and said ISIS leaders had not been targeted. But he added that if ISIS leaders were embedded “inside troop formations they are likely to be killed.” + +A number of news outlets and websites have published the unverified photo and news about the death of al-Baghdadi by US airstrikes. IraqiNews.com has been unable to verify the photo and claim that al-Baghdadi was killed.","0" +"Iraqi airstrike kills key ISIL leader","An Iraqi airstrike on Thursday (September 4th) killed Abu Hajar al-Souri, a top aide to ""Islamic State of Iraq and the Levant"" (ISIL) leader Abu Bakr al-Baghdadi, the Iraqi Ministry of Defence said. +""The Iraqi army air hawks were able to make a direct hit on one of ISIL's main strongholds in Tal al-Rumman, west of Mosul, killing Abu Hajar al-Souri, the right arm of ISIL leader Abu Bakr al-Baghdadi, and those with him,"" the ministry said in a statement released by Al-Iraqiya state television. + +The airstrike killed ""seven prominent leaders in the group, most of them Arab and foreign fighters"", ministry spokesman Maj. Gen. Mohammed al-Askari told Mawtani. + +""Abu Hajar is considered a key leader in the group and the second-in-command for planning and executing terrorist operations,"" the spokesman said. ""He used to move between Iraq and Syria on an on-going basis to follow up on the group's members."" + +The army plans to release additional details about the operation after carrying out the necessary investigations, he added. + +CITIZENS' CO-OPERATION KEY +Deputy Air Force Commander Lt. Gen. Hamed Attia said the air raid ""took place after days of surveillance, information-gathering and communications intercepted by locals about the presence of al-Souri in the region"". + +Attia said the attack was the fruit of security co-operation with citizens. + +Iraqi MP Hassan al-Sunaid described the air raid as a positive step. + +""The death of Abu Hajar al-Souri will be welcome news for the thousands of families of terrorism victims, and hundreds of thousands of Iraqis displaced because of ISIL,"" he said. + +Co-operation between civilians and the security forces is continuously increasing, al-Sunaid said. + +Iraqis in Mosul and its suburbs also are welcoming the news, said Ibrahim al-Hassan, deputy chairman of the Ninawa tribal council. + +""This criminal did not stop at what he did in his own country and came to our country to continue his crimes,"" al-Hassan said. + +""He received what he deserves and others should expect a similar fate,"" he added.","0" +"ISIS leader ‘killed’ in US airstrikes","Thousands of social media users are distributing an unverified photo which claims to show the body of ISIS leader Abu Bakr al-Baghdadi after he was purportedly killed by US airstrikes after three senior members of ISIS, including an aide to al-Baghdadi were also killed by US air strikes. +Talking to NBC News, a senior Iraqi official confirmed the deaths on Thursday. The strike on the ISIS stronghold of Mosul killed Abu Hajar al-Sufi, an aide to al-Baghdadi, as well as an explosives operative and the military leader of nearby Tal Afar, the source said. Al Arabiya cited the Iraqi Defence Ministry as saying that Baghdadi’s aide had been killed. +Pentagon Spokesman Col Steve Warren could not confirm the deaths and said ISIS leaders had not been targeted. But he added that if ISIS leaders were embedded “inside troop formations they are likely to be killed”. The US has been carrying out airstrikes across north Iraq after the brutal terrorists of ISIS gained ground in a murderous sweep in June. +A number of news outlets and websites have published the unverified photo and news about the death of al-Baghdadi by US airstrikes.","0" +"ISIS Leader Killed: Abu Bakr Al-Baghdadi Reportedly Killed By U.S. Airstrike","ISIS leader Abu Bakr al-Baghdadi has reportedly been killed by a U.S. airstrike, an attack that left three other senior members of the militant group dead. + +The ISIS leader was killed during an air strike in the city of Mosul, which ISIS forces took over this summer. A Pentagon spokesperson did not confirm the death, but thousands of social media users have passed around an unverified photo claiming to be the ISIS leader’s body. It was also reported by Iraqi News. + +Pentagon spokesman Col. Steve Warren did say that any ISIS leaders “inside troop formations they are likely to be killed.” + +Abu Bakr al-Baghdadi was known as the world’s “most powerful jihadi leader” and “the new Bin Laden.” + +“The true heir to Osama bin Laden may be ISIS leader Abu Bakr al-Baghdadi,” wrote The Washington Post’s David Ignatius. + +Many believe that as the leader of ISIS, Abu Bakr al-Baghdadi helped the group eclipse al-Qaeda both in power and relevance in the region. + +“For the last 10 years or more, [al-Qaeda leader Ayman al-Zawahiri ] has been holed up in the Afghanistan-Pakistan border area and hasn’t really done very much more than issue a few statements and videos,” Richard Barrett, a former counterterrorism chief with the British foreign intelligence service, told Agence France-Presse. “Whereas Baghdadi has done an amazing amount — he has captured cities, he has mobilized huge amounts of people, he is killing ruthlessly throughout Iraq and Syria…. If you were a guy who wanted action, you would go with Baghdadi.” + +The reported killing of ISIS leader Abu Bakr al-Baghdadi comes after the United States just took out a leader of the group al-Shabaab, a Somali terrorist group. The leader killed, Ahmed Abdi Godane, was responsible for a the attack in a Kenyan mall last year that killed 68 people and left 200 more injured.","0" +"URGENT: ISIS leader Abu Bakr al-Baghdadi allegedly killed by US airstrikes","(IraqiNews.com) Thousands of social media users are distributing an unverified photo which claims to show the body of ISIS leader Abu Bakr al-Baghdadi after he was purportedly killed by US air strikes after three senior members of ISIS, including an aide to al-Baghdadi were also killed by US air strikes. The death of the three senior members and aide to al-Baghdadi were confirmed by a senior Iraqi security official when interviewed by NBC News on Thursday. + +The strike on the ISIS stronghold of Mosul killed Abu Hajar Al-Sufi, an aide to Abu Bakr al-Baghdadi, as well as an explosives operative and the military leader of nearby Tal Afar, the source said on condition of anonymity. Al Arabiya cited the Iraqi Defense Ministry saying Baghdadi’s aide had been killed. + +Pentagon Spokesman Col. Steve Warren could not confirm the deaths and said ISIS leaders had not been targeted. But he added that if ISIS leaders were embedded “inside troop formations they are likely to be killed.” The U.S. has been carrying out airstrikes across north Iraq after the brutal terrorists of ISIS gained ground in a murderous sweep in June. + +A number of news outlets and websites have published the unverified photo and news about the death of al-Baghdadi by US airstrikes. IraqiNews.com has been unable to verify the photo and claim that al-Baghdadi was killed.","0" +"Iraqi social-media rumors claim IS leader slain","Rumors that Islamic State leader Abu Bakr al-Baghdadi was killed in an airstrike circulated on Iraqi social media Sunday, along with a photograph purportedly showing the bloodied jihadi leader. + +The speculation was backed by several unconfirmed Iraqi media reports, which maintained that Baghdadi was slain in a US airstrike several days ago. However, later Iraqi reports said the IS leader was severely wounded in the chest near the Syrian border and was receiving medical treatment. + +The reports could not be independently confirmed. + +Washington expanded its month-long air campaign to Iraq’s Sunni Arab heartland, hitting Islamic State fighters west of Baghdad as troops and allied tribesmen launched a ground assault on Sunday. + +The new strikes deepen Washington’s involvement in the conflict and were a significant escalation for President Barack Obama, who made his political career opposing the war in Iraq and pulled out US troops in 2011. + +Previous strikes — since the US air campaign began on August 8 — had been mainly in support of Kurdish forces in the north. + +US warplanes bombed IS fighters around a strategic dam on the Euphrates River in an area that the jihadists have repeatedly tried to capture from government troops and their Sunni militia allies. + +“We conducted these strikes to prevent terrorists from further threatening the security of the dam, which remains under control of Iraqi security forces, with support from Sunni tribes,” Pentagon spokesman Rear Admiral John Kirby said. + +“The potential loss of control of the dam, or a catastrophic failure of the dam — and the flooding that might result — would have threatened US personnel and facilities in and around Baghdad, as well as thousands of Iraqi citizens,” he added. + +AFP contributed to this report. + + + +Read more: Iraqi social-media rumors claim IS leader slain | The Times of Israel http://www.timesofisrael.com/iraqi-social-media-rumors-claim-is-leader-slain/#ixzz3CemgIdtk +Follow us: @timesofisrael on Twitter | timesofisrael on Facebook","0" +"Israel opens dams, floods Gaza","GAZA, Feb. 22 (Xinhua) -- A Palestinian minister lashed out at Israel on Sunday after it opened its dams near the border with the Gaza Strip, flooding the central area of the besieged enclave with huge amounts of water. + +Mufid al-Hasaynah, minister of Housing and Public Works in the Palestinian unity government, told Xinhua that Israel deliberately increases the suffering of the Gazans. + +""Dozens of houses were filled with water of the Israeli dams, which were largely opened this morning towards the Gaza Strip. These actions double the people's suffering who live under a tight Israeli siege,"" said the minister. + +Early on Sunday, rescue teams and firefighters rushed to the central area of the Gaza Strip to rescue dozens of Palestinians who were stuck in their houses after Israel opened the dams. + +Witnesses said that bulldozers were bringing sands to reduce the amounts of water that covered the houses in the area and that several main roads and streets were closed due to the floods. + +The Gaza-based Ministry of Interior said in an emailed press statement that the civil defense teams rescued 18 families after their homes were fully covered with water that came from the Israeli side. + +Mohamed Abu Shamallah, head of the Gaza civil defense, said that the level of water in the area in central Gaza Strip grew up to three meters and a half.","0" +"Palestine accuses Israel of opening dams, flooding Gaza, forcing evacuations","Palestinian officials say hundreds of Gazans were forced to evacuate after Israel opened the gates of several dams on the border with the Gaza Strip, and flooded at least 80 households. Israel has denied the claim as “entirely false.” + +In the wake of a recent severe winter storm in the region, Israeli authorities opened the floodgates to discharge the accumulated water, Palestinian officials say. Residents of eastern Gaza reported injuries as well as deaths of livestock and poultry, caused by the Israeli action which allegedly came without prior notification, Gaza's Civil Defense Directorate (CDD) said Sunday. + +Photos of the Gaza Strip flood have appeared in social networks, but the date when they were taken can't be independently verified as yet. + + +“The [Israeli] army opened the floodgates of a canal leading to central Gaza, which resulted in the removal of sand mounds along the border with Israel,” the CDD announced, according to Palestinian News Agency WAFA. + +“Opening the levees to the canal has led to the flooding of several Palestinian homes, and we had to quickly evacuate the afflicted citizens.” + +No casualties were reported as a result, but more than 80 families had to flee after their homes filled with water levels sometimes reaching more than three meters, the Gaza Ministry of Interior said in a statement. + +In a letter to RT regarding the issue, Israel’s Coordinator of Government Activities in the Territories (COGAT) maintained that“the claim is entirely false."" + +""Southern Israel does not have any dams. Due to the recent rain, streams were flooded throughout the region with no connection to actions taken by the State of Israel,” COGAT said. + +The flood reportedly forced the closure of the main road connecting al-Mughraqa district and Nusseirat refugee camp south of Gaza city, leaving hundreds of Palestinians trapped in the floods, a difficult prospect for approximately 110,000 Palestinians left homeless by Israel’s assault last summer. + +Evacuated families were taken to UNRWA-sponsored (UN Relief and Works Agency) shelters in the al-Bureij refugee camp and the al-Zahra neighborhood. + + +""Israel opened water dams, without warning, last night, causing serious damage to Gazan villages near the border. More than 40 homes were flooded and 80 families are currently in shelters as a result,” chief of the civil defense agency in Gaza, Brigadier Gerneral Said Al-Saudi, told Al Jazeera. + +Local agriculture was also affected, Al-Saudi said. “We are appealing to human rights organizations and international rights organizations to intervene to prevent further such action.” + +Further harm could be caused if Israel opens up more dams, warned Gaza Civil Defense Services (CDD) spokesman Muhammad al-Midana, as cited by the Ma'an news agency. A fast-moving water stream is currently flowing from the Israel border through the Gaza valley and into the Mediterranean Sea, he said. + + +The Gaza Valley (Wadi Gaza) used to be a unique wetland ecosystem located in the central Gaza Strip between al-Nuseirat refugee camp and al-Moghraqa. It flowed from two streams, one running from near Beersheba, and the other from vicinity of Hebron. There’s not much water left in Wadi Gaza, as water being mostly used upstream in Israel and the stream running through the Gaza Strip consists mainly of untreated waste from Gaza City, which pumps up millions of liters of sewage into the riverbed. + +Wadi Gaza overflowing with untreated sewage (image from www.ewash.org)Wadi Gaza overflowing with untreated sewage (image from www.ewash.org) + +According to media reports, this is not the first time Israeli authorities have opened the floodgates to their Gaza Valley dams to discharge massive quantities of excessive water that accumulated during heavy rains or snowfall.","0" +"Hundreds of Palestinians flee floods in Gaza as Israel opens dams","Hundreds of Palestinians were evacuated from their homes Sunday morning after Israeli authorities opened a number of dams near the border, flooding the Gaza Valley in the wake of a recent severe winter storm. + +The Gaza Ministry of Interior said in a statement that civil defense services and teams from the Ministry of Public Works had evacuated more than 80 families from both sides of the Gaza Valley (Wadi Gaza) after their homes flooded as water levels reached more than three meters. + +Gaza has experienced flooding in recent days amid a major storm that saw temperatures drop and frigid rain pour down. + +The storm displaced dozens and caused hardship for tens of thousands, including many of the approximately 110,000 Palestinians left homeless by Israel's assault over summer. + +The suffering is compounded by the fact that Israel has maintained a complete siege over Gaza for the last eight years, severely limiting electricity and the availability of fuel for generators. It has also prevented the displaced from rebuilding their homes, as construction materials are largely banned from entering. + +Gaza civil defense services spokesman Muhammad al-Midana warned that further harm could be caused if Israel opens up more dams in the area, noting that water is currently flowing at a high speed from the Israel border through the valley and into the Mediterranean sea. + +Evacuated families have been sent to shelters sponsored by UNRWA, the UN agency for Palestinian refugees, in al-Bureij refugee camp and in al-Zahra neighborhood in the central Gaza Strip. + +The Gaza Valley (Wadi Gaza) is a wetland located in the central Gaza Strip between al-Nuseirat refugee camp and al-Moghraqa. It is called HaBesor in Hebrew, and it flows from two streams -- one whose source runs from near Beersheba, and the other from near Hebron. + +Israeli dams on the river to collect rainwater have dried up the wetlands inside Gaza, and destroyed the only source of surface water in the area. + +Locals have continued to use it to dispose of their waste for lack of other ways to do so, however, creating an environmental hazard. + +This is not the first time Israeli authorities have opened the Gaza Valley dams. + +In Dec. 2013, Israeli authorities also opened the dams amid heavy flooding in the Gaza Strip. The resulting floods damaged dozens of homes and forces many families in the area from their homes. + +In 2010, the dams were opened as well, forcing 100 families from their homes. At the time civil defense services said that they had managed to save seven people who had been at risk of drowning.","0" +"Hundreds of Palestinians flee as Israel opens dams into Gaza Valley","GAZA CITY (Ma'an) -- Hundreds of Palestinians were evacuated from their homes Sunday morning after Israeli authorities opened a number of dams near the border, flooding the Gaza Valley in the wake of a recent severe winter storm. + +The Gaza Ministry of Interior said in a statement that civil defense services and teams from the Ministry of Public Works had evacuated more than 80 families from both sides of the Gaza Valley (Wadi Gaza) after their homes flooded as water levels reached more than three meters. + +Gaza has experienced flooding in recent days amid a major storm that saw temperatures drop and frigid rain pour down. + +The storm displaced dozens and caused hardship for tens of thousands, including many of the approximately 110,000 Palestinians left homeless by Israel's assault over summer. + +The suffering is compounded by the fact that Israel has maintained a complete siege over Gaza for the last eight years, severely limiting electricity and the availability of fuel for generators. It has also prevented the displaced from rebuilding their homes, as construction materials are largely banned from entering. + +Gaza civil defense services spokesman Muhammad al-Midana warned that further harm could be caused if Israel opens up more dams in the area, noting that water is currently flowing at a high speed from the Israel border through the valley and into the Mediterranean sea. + +Evacuated families have been sent to shelters sponsored by UNRWA, the UN agency for Palestinian refugees, in al-Bureij refugee camp and in al-Zahra neighborhood in the central Gaza Strip. + + + + + +The Gaza Valley (Wadi Gaza) is a wetland located in the central Gaza Strip between al-Nuseirat refugee camp and al-Moghraqa. It is called HaBesor in Hebrew, and it flows from two streams -- one whose source runs from near Beersheba, and the other from near Hebron. + +Israeli dams on the river to collect rainwater have dried up the wetlands inside Gaza, and destroyed the only source of surface water in the area. + +Locals have continued to use it to dispose of their waste for lack of other ways to do so, however, creating an environmental hazard. + +This is not the first time Israeli authorities have opened the Gaza Valley dams. + +In Dec. 2013, Israeli authorities also opened the dams amid heavy flooding in the Gaza Strip. The resulting floods damaged dozens of homes and forces many families in the area from their homes. + +In 2010, the dams were opened as well, forcing 100 families from their homes. At the time civil defense services said that they had managed to save seven people who had been at risk of drowning.","0" +"KANYE WEST BARRED FROM ALL FUTURE AWARDS SHOWS","LOS ANGELES, California ( The Adobo Chronicles) – He did it again. Rapper Kanye West reprised his most infamous stunt at Sunday night’s Grammy awards, taking the stage as Beck was accepting the album of the year award. West popped up on stage and moved toward Beck as if he was about to take the trophy from him. Instead, West turned away and quickly jumped down. + +Beck beat out both the night’s top winner, Sam Smith, and the category’s expected winner, Beyoncé. + +The incident was a repeat of the 2009 MTV Video Music Awards, when West accosted Taylor Swift during her acceptance speech after Swift’s “You Belong With Me” beat Beyoncé’s “Single Ladies” for Female Video of the Year. + +“Yo, Taylor, I’m really happy for you, I’ma let you finish,” West said after taking the microphone at Radio City Music Hall, “but Beyoncé had one of the best videos of all time! One of the best videos of all time!” + +West was roundly criticized for his action and was even called a “jackass” by no less than President Obama. + +After this latest incident, organizers of the major awards shows like the Grammys, MTV Video Music Awards, People’s Choice Awards and the Oscars have unanimously agreed to disinvite and bar West from their respective ceremonies. The television networks that air these awards programs also joined in the ‘West boycott.’ + +No more Kanye West on live TV! And Beyoncé just lost her most loyal cheerleader.","0" +"Have Kanye & Kim Been Banned From Future Grammy Ceremonies?","Rumors are circulating that are too delicious to overlook. Has Kanye West been banned from future Grammy Awards shows? +Some sources on the World Wide Interweb are reporting that the infamous stage crasher and his wife, Kim Kardashian have been forever banned from attending future Grammy Awards. However, the rapper is still eligible to win a Grammy. +» More Kim Kardashian: The 31 Best Instagram Posts By Celebs At The Grammys +West, who is more famous for his marriage and storming the stage to protest when Beyoncé doesn’t win than for his music these days first caused this kind of controversy back in 2009. Yeezus stormed the stage at the MTV Video Music Awards when Taylor Swift was given the Video of The Year for “You Belong With Me,” over Beyoncé’s “Single Ladies.” +“Yo, Taylor, I’m really happy for you, I’ma let you finish,” West said while interrupting her acceptance speech, “but Beyoncé had one of the best videos of all time! One of the best videos of all time!” +On Sunday night, Kanye again took to the stage, this time when Beck beat out Beyoncé for Album of the Year. He left before he could say anything, but after the broadcast he made his feelings on that particular award very clear. +Kanye very angrily spouted off about “true artistry” and said “Beck should respect true artistry and give his award to Beyoncé.” +After those disrespectful comments, Kanye was allegedly called to task by the powers that be at the Grammys and he and his sex tape famous wife were permanently banned. +Whether this is true or not remains to be seen. It would be delightful if it was true and send a message to Kanye that he is, in fact, not the guy who gets to say who wins the awards. Beyoncé is great, but she isn’t the only artist out there","0" +"Kei Nishikori Highest-Paid Tennis player in the World","It's been a rough year for the tennis player, but at least he has his millions of dollars to ease the pain. 25-year-old Kei Nishikori has taken the No. 1 spot on People With Money’s top 10 highest-paid tennis players for 2015 with an estimated $46 million in combined earnings. + +UPDATE 26/01/2015 : This story seems to be false. (read more) + +Kei Nishikori tops annual list of highest-paid tennis players + +In 2012 it looked like the tennis player’s spectacular career was winding down. Suddenly, he was back on top. People With Money reports on Sunday (January 25) that Nishikori is the highest-paid tennis player in the world, pulling in an astonishing $46 million between December 2013 and December 2014, a nearly $20 million lead over his closest competition. + +People With Money’s factors + +In compiling this yearly list, the magazine considers factors such as upfront pay, profit participation, residuals, endorsements and advertising work. + +The Japanese tennis player has an estimated net worth of $145 million. He owes his fortune to smart stock investments, substantial property holdings, lucrative endorsement deals with CoverGirl cosmetics. He also owns several restaurants (the “Fat Nishikori Burger” chain) in Tokyo, a Football Team (the “Matsue Angels”), has launched his own brand of Vodka (Pure Wondernishikori - Japan), and is tackling the juniors market with a top-selling perfume (With Love from Kei) and a fashion line called “Kei Nishikori Seduction”. + +The ranking is significant for many Kei fans, who have been waiting for his triumphant return to the glory days for what seems like a lifetime.","0" +"$YUM Serving Up #Marijuana & Fried Chicken","KFC (NYSE:YUM) Gets Occupational Business License To Sell Marijuana In Colorado Restaurants. + +In the state of Colorado, cannabis clinics are big industry – earning some retailers nearly $1 million per year. + +Those numbers made an impact on the KFC Corporation, they made the decision to include a pot dispensary to be a part of their Colorado franchise restaurants. + +Franchisees have the chance to build a foundation into the business for an additional $35,000 setup fee. + +The KFC Corporation was able to get approval on February 3, 2015 for their Cannabis Retail Recreational Marijuana / Medical Cannabis Occupational Business License. + +So far, 42 of the almost 100 KFC franchises that are located in the state Colorado have made this “option” an addition to their menu. + + Their is actually a humorous comparison due to the south park episode “medicinal fried chicken” having to do with KFC selling marijuana with there famous fried chicken + +In the midst of all this a major crisis happens for cartman when his favorite foods at KFC are all replaced with medicinal marijuana stores. Though KFC isn’t going out of business they are adapting to a new trend. + +“In order to be successful, a deep understanding of the market is critical to success,” says KFC spokesperson William Rausch. “It’s all about evolution and we are ready to serve the needs of the people of Colorado.” + +For the people choosing to buy marijuana they must provide a picture ID showing that they are 21 years or older in order to make a purchase + +Coloradans are only allowed to purchase 28 grams at one time, while people who are not citizens of colorado are limited on their purchase only be allowed to buy a quarter at a time + +Due to banking restrictions, when making a purchase in dispensaries it is a cash only business . Ounces usually start at a price of 200 and only go up along with a pot tax of 25 % + +In addition to making a profit from the “leafy green” they also have some delectable edibles in stock. They are offering Smashed Potatoes, Macaroni Munchies andBong Time Biscuits – all made with their tasty cannabis butter + +KFC is anticipating to get all 100 franchisees ready to go with the new inventory by March 2016. #KushForCure","0" +"KFC Locations In Colorado To Begin Selling Marijuana","(ANTIMEDIA) The KFC Corporation just acquired a Colorado licence to legally sell cannabis within the state. +According to some reports, nearly half of the KFC franchises in the state Colorado began selling cannabis last month. +“In order to be successful, a deep understanding of the market is critical to success. It’s all about evolution and we are ready to serve the needs of the people of Colorado,” KFC spokesperson William Rausch said in a statement. + + +Customers who want to buy cannabis with their genetically modified fried chicken will still need to prove that they are at least 21 years of age, with a valid government issued ID. +Interestingly enough, this weird phenomenon is something that “South Park” predicted years ago. In one episode of the hit comedy show, Randy Marsh gives himself testicular cancer with a microwave in order to get a prescription for medical marijuana. In the episode, all of the KFC locations in the town become marijuana dispensaries. +With this bold move, KFC becomes one of the first major fast food chains to offer this extra service, and it is possible that many others will follow in their footsteps. Fast food has been suffering financially in recent years, as consumers become more health conscious. While KFC may not be the best place to eat, the addition of cannabis to their menu definitely signals the beginning of a new era.","0" +"KFC Gets Occupational Business License To Sell Marijuana In Colorado Restaurants KFC Gets Occupational Business License To Sell Marijuana In Colorado Restaurants","The Racket Report – KFC Gets Occupational Business License To Sell Marijuana In Colorado Restaurants. + +In the state of Colorado, marijuana dispensaries are big business – earning some retailers nearly $1 million per year. + +Those numbers were so appealing to the KFC Corporation, they decided to incorporate a marijuana dispensary with their Colorado franchise restaurants. + +Franchisees have the opportunity to expand into the business for an additional $35,000 setup fee. + + + +The KFC Corporation was approved on February 3, 2015 for their Marijuana Retail Recreational Pot / Medical Marijuana Occupational Business License. + +Currently, 42 of the nearly 100 KFC franchises in the state of Colorado have added this “option” to their menu. + + fc,550x550,white.u1“In order to be successful, a deep understanding of the market is critical to success,” says KFC spokesperson William Rausch. “It’s all about evolution and we are ready to serve the needs of the people of Colorado.” + + + + + +Marijuana may be purchased only by adults 21 years or older, and a picture ID is required. + +Coloradans may buy 1 ounce at a time, while out-of-state residents are limited to a quarter ounce. + +Due to banking restrictions, all sales are required to be cash transactions. Prices begin around $200 and up per ounce along with a 25% marijuana tax. + +potshop-400x404 + +In addition to selling the “leafy green” they also have some yummy edibles available. They are offering Smashed Potatoes, Macaroni Munchies and Bong Time Biscuits – all made with their savory marijuana butter (sold in small amounts). + +KFC is hoping to get all 100 franchisees on board with the new product by March 2016. #KushForCure","0" +"Jordan Vs ISIS: Reports Say King Abdullah II Could Personally Lead Airstrikes After Pilot’s Death","While other global leaders rant their exasperations and anger towards the extremists ISIS fighters and its entire caliphate, one leader may just take matters in his own hands. Jordan's King Abdullah II, visibly shaken and angered over the death of one of his kingdom’s military pilots, has vowed to exact revenge. Reports in Arabic-language newspapers hinted he may don his pilot suit and drop the bombs himself. + +Photos have emerged over the Internet of a poker-faced Jordan King Abdullah II who was wearing a fatigue green army uniform. The reports emerged after the Jordanian leader vowed a relentless war against the ISIS right on their own territory. The portal dailycaller said the king leader, a trained pilot, “may fly a bomber himself on Thursday.” + +The news of the burning of Jordanian pilot First Lieutenant Moaz al-Kasasbeh by the ISIS happened while the king was in the U.S. King Abdullah is a strong ally of Washington and London. Al-Kasasbeh got captured when the F-16 fighter he was flying crashed over the jihadi Syrian headquarters in Raqqa in December. He had been burned alive in a cage by the terrorist army. In a closed-door meeting with U.S. lawmakers following the video’s release, King Abdullah II said the ISIS will see a retribution it hasn’t seen before. + +Safi al-Kaseasbeh, the pilot's father, said earlier the 53-year-old monarch had personally attended to the coordination for the release of his son, which had ended in vain. “The King told me that he was following up personally on Muath’s case,"" the grieving father told the Jordan Times. ""He said Crown Prince Hussein, may God protect him, is no dearer to me than Muath.” The younger al-Kaseasbeh had graduated from King Hussein Air College, the academy named for Abdullah's father. + +King Abdullah said they will pursue the black-clad terrorist army until they ran “out of fuel and bullets.” Quoting lines from the ‘Unforgiven,’ a movie led by American actor Clint Eastwood, he said the death of one of Jordan’s sons will call not only for the death of his killers, but also their “wives and all their friends, and burn his damn house down.” + +Duncan Hunter, California Republican Rep., told the Washington Examiner that King Abdullah II has called his officials to arrange “more sorties than they've ever had. They're starting tomorrow.” Mohammad Momani, Jordanian government spokesman, quoted by Fox News, said the country’s response to the assassination “...will be swift. Jordanians’ wrath will devastate Daesh’s ranks.” + +""All the State's military and security agencies are developing their options. Jordan's response will be heard by the world at large but this response on the security and military level will be announced at the appropriate time,"" Momani said. + +Jon Alterman, director of the Center for Strategic & International Studies' Middle East Program, told Fox News that Jordan’s words were not just mere lip service or emotional outbursts. ""Their ability to do difficult things with small numbers of highly trained people is up there with some of the best militaries in the world."" + +David Schenker, former adviser to Defense Secretary Donald Rumseld and director of the Arab politics program at The Washington Institute, said Jordan's military force, ""regionally speaking, they are people of high quality."" + +To report problems or to leave feedback about this article, e-mail: e.misa@ibtimes.com.au.","0" +"Jordan’s King May Participate Personally In ISIS Raids","Jordan’s King Abdullah ibn al-Hussein, who has trained as a pilot, may fly a bomber himself on Thursday in the country’s retaliation against the ISIS. + +Several Arabic-language newspapers reported late Wednesday that the monarch would personally participate in bombing raids on the terrorist group, citing his vow Tuesday to “strike them in their strongholds.” + +The king was in Washington when news broke Tuesday of pilot Muadh al-Kasasbeh’s demise at the hands of ISIS extremists. Meeting with the House Armed Services Committee shortly before leaving for Amman, he reportedly quoted the Clint Eastwood’s film “Unforgiven” and said that Jordan would pursue the jihadis until it ran “out of fuel and bullets.” + +Rep. Duncan Hunter, who was in the meeting, told Fox News that given the ruler’s immediate and vehement reaction, “King Abdullah is not President Obama.” + +Jordan, which has been a key American ally in the air war against ISIS, killed a number of ISIS-affiliated prisoners early Wednesday, as it had promised should Kasasbeh turn out to be dead, prior to the news of his immolation. Some have warned that the terrorist group deliberately deployed news of Kasasbeh’s fate in order to provoke a Jordanian overreaction. But public outcry in Jordan before and after the news seems to have pressured the government into a strong response, regardless of strategy. (RELATED: Jordan To Retaliate For Pilot Killed By ISIS) + +Meanwhile, Pentagon spokesman John Kirby said Tuesday that “nothing’s going to change” in U.S. policy toward ISIS as a result of Kasasbeh’s murder. + +Follow Ivan Plis on Twitter + +Content created by The Daily Caller News Foundation is available without charge to any eligible news publisher that can provide a large audience. For licensing opportunities of our original content, please contact licensing@dailycallernewsfoundation.org.","0" +"REPORTS: JORDANIAN KING PERSONALLY FLYING SORTIES AGAINST ISIS","Jordan’s King Abdullah is reportedly personally involved in executing air strikes against Islamic State positions in the aftermath of the terrorist group’s brutal execution of Jordanian pilot 1st Lt. Moaz Kasasbeh. + +Shafaqna news and Iraqinews.com claimed to have confirmed with their sources that King Abdullah is personally involved in conducting the air strikes. What remains unclear is whether Abdullah is personally suiting up and flying a plane, or instead commanding units involved in the mission. + +“The Jordanian King Abdullah II will participate personally on Thursday in conducting air strikes against the shelters of the terrorist ISIL organization to revenge the execution of the Jordanian pilot [Kasasbeh] by the ISIL,” said the IraqiNews report. + +Others on social media have reported similar statements. + +Jordanian Author Waleed Abu Nada Tweeted on Wednesday afternoon, “Local reports here in Jordan say that King Abdullah will personally fly and lead the airstrikes against ISIS tomorrow.” + +Middle East commentator Joseph Braude wrote on Twitter: “Reports that Jordanian King Abdullah, himself a pilot, will fly sorties on ISIS targets.” + +Before assuming the throne, Abullah II was a Major General in charge of Jordanian Special Forces. Abdullah is also certified as a Cobra Attack Helicopter Pilot. In 1980, he joined the UK’s Royal Military Academy Sandhurst and was commissioned as a 2nd Lt. in the British Army. + +Jordanian air strikes on Wednesday neutralized at least 55 Islamic State jihadists, including a top Islamic State commander who was known as the “Prince of Nineveh,” according to reports.","0" +"Will King of Jordan lead airstrikes on ISIS HIMSELF? Reports say trained pilot plans to take part in attack after quoting Clint Eastwood's Unforgiven to Congressmen","Jordan's King Abdullah, a trained pilot, could lead revenge airstrikes on Islamic State himself, it has been revealed. + +The monarch may personally take part in bombing raids on extremist strongholds on Thursday, according to reports in Arabic-language newspapers. + +It comes after the former general told members of Congress that he was ready to exact a blistering revenge against the ISIS terror army for the brutal execution of military pilot Moaz al-Kassasbeh - and he quoted a Clint Eastwood movie character to make his point. + +Scroll down for videos + +Jordan's King Abdullah (pictured), a trained pilot, could lead revenge airstrikes on Islamic State himself, it has been revealed + +Uncompromising language; King Abdullah of Jordan, (center), is hurried into a meeting with leaders of the Senate Foreign Relations Committee at the Capitol in Washington after shocking footage of a Jordanian pilot being burned alive was released online Tuesday + +According to the dailycaller, reports have emerged suggesting he could take part in airstrikes on ISIS targets today. + +California Republican Rep. Duncan Hunter told the Washington Examiner that the king quoted the scene where Eastwood's character announces his plan for retribution. + +'Any man I see out there, I'm gonna kill him,' Eastwood's William Munny says in 'Unforgiven.' + +'Any son of a bitch takes a shot at me, I'm not only going to kill him, I'm going to kill his wife and all his friends and burn his damn house down.' + +'He said there is going to be retribution like ISIS hasn't seen,' Hunter said. 'He's angry. 'They're starting more sorties tomorrow than they've ever had. They're starting tomorrow. And he said, ""The only problem we're going to have is running out of fuel and bullets"".' + +'He's ready to get it on. He really is. It reminded me of how we were after 9/11. We were ready to give it to them.' + +Return home: King Abdullah of Jordan arrives as Jordanians stand along the way between Amman and Queen Alia airport waiting to greet him upon his arrival on Wednesday + +REVENGE: 'Any son of a bitch takes a shot at me, I'm not only going to kill him, I'm going to kill his wife and all his friends and burn his damn house down,' Clint Eastwood says in 'Unforgiven,' and the King of Jordan quoted him Tuesday in response to ISIS + +Last-minute meeting: Jordan's King Abdullah II (left) met with President Obama at the White House on Tuesday after video emerged showing the brutal execution of one of his country's pilots by the ISIS terrorist group + +Brutal: Footage titled 'Healing the Believers Chests' appears to show captured airman Moaz al-Kassasbeh wearing an orange jumpsuit as a trail of petrol leading up to the cage is set alight + +Hunter told the Examiner that no one in the king's meeting on Tuesday with members of the House Armed Services Committee made any mention of President Obama, who is seen by some anti-ISIS coalition partners as a weak and indecisive actor. + +South Carolina Republican Sen. Lindsey Graham said after a separate meeting with the king that Jordan would have a 'strong and forceful' response to the the fiery execution. + +'The Jordanian response will be more engaged, not less engaged, when it comes to destroying ISIL,' Graham said. + +'The king feels that the gloves are off and that it now is time if you can't negotiate with these people, you're going to have to take it to them, and I think it's going to be more than Jordan.' + +Obama and Abdullah met Tuesday evening in a hastily arranged meeting just hours after a grisly video emerged showing al-Kassasbeh, who was 26 years old, being burned alive in a cage by ISIS. + +They emerged from the meeting, vowing to continue their fight of the extremist group gaining control over large swathes of Iraq and Syria. + +In addition, the State Department said Tuesday that the administration will increase its annual aid to Jordan to $1 billion from $660 million to help it pay for the cost of housing refugees from Iraq and Syria – and provide new resources to fight ISIS. + +An agreement on the aid will require congressional approval. + +In a brief statement, the U.S. State Department said it planned to provide $1 billion per year to Jordan for each of the U.S. fiscal years for 2015, 2016 and 2017. The U.S. fiscal year ends on Sept. 30. + +Activists carry pictures of Jordanian pilot Moaz al-Kassasbeh in Amman on February 3, 2015 + +Captured: Muath al-Kasasbeh (centre in white) was captured by the Islamic State after after crashing near its HQ in the Syrian city of Raqqa in December. ISIS is now believed to brutally murdered him + +Al-Kassasbeh was captured in December when his F-16 jet crashed over northern Syria, a mission that was part of the U.S.-led coalition campaign against the jihadists. + +During the meeting, President Obama offered 'his deepest condolences' to the king over the pilot's death + +'The president and King Abdullah reaffirmed that the vile murder of this brave Jordanian will only serve to steel the international community's resolve to destroy ISIL,' said White House spokesman Alistair Baskey. + +Obama earlier decried the 'cowardice and depravity' of the Islamic State, saying the brutal killing would only strengthen international resolve to destroy the extremists. + +The White House would not speculate on whether the video was released to coincide with Abdullah's visit to Washington, where he was not scheduled to meet Obama. + +The president said First Lieutenant Kassasbeh's 'dedication, courage and service to his country' represented 'universal human values that stand in opposition to the cowardice and depravity of ISIL.' + +'Today, we join the people of Jordan in grieving the loss of one of their own,' the president added, as his administration reaffirmed its intention to give Jordan $3 billion in security aid over the next three years. + +'As we grieve together, we must stand united, respectful of his sacrifice to defeat this scourge,' Obama said after the latest in a wave of grizzly filmed murders. + +Jordanian state television said that Kassasbeh was killed on January 3. + +The slaying would redouble international commitment to ensure the Islamic State group 'are degraded and ultimately defeated,' said Obama. + +The extremists seized swathes of territory in Iraq and Syria last year, declaring an Islamic 'caliphate' and committing a wave of atrocities. + +Countries as diverse as the United States, Saudi Arabia and Jordan responded with 'Operation Inherent Resolve,' an air-led campaign to pummel the jihadist group. + +US Central Command meanwhile admitted that the Islamic State still had the ability 'to conduct small-scale operations,' despite months of air strikes. + +But, it said, 'their capacity to do so is degraded and their momentum is stalling.' + +Attacks have hit the group's 'ability to command and control forces; recruit, train and retain fighters, produce revenue from oil sales, and maintain morale.' + +Islamic State had offered to spare Kassasbeh's life and free a Japanese journalist in return for the release of a female would-be suicide bomber on death row in Jordan. + +Jordanian officials announced the female bomber and other jihadists would be executed on Wednesday.","0" +"Robert Plant Literally Ripped Up An $800 Million Contract To Reunite Led Zeppelin","You can purchase a lot of things for $800 million. Ten Matthew McConaughey’s, eighty-billion pieces of penny candy, my dignity. But the one thing it can’t buy: a Led Zeppelin reunion. Also, a cure for AIDS, probably, but also the Led Zeppelin thing. Jimmy Page and John Paul Jones agreed to a “35 dates in three cities” tour, but Robert Plant was having none of it, and like a poorly written character in an Aaron Sorkin script, he literally ripped up a contract. + +[Plant] and the other living founding members of legendary hard-rock band Led Zeppelin were about to ink an $800 million contract with Virgin Atlantic billionaire Richard Branson to play a reunion tour, but the iconic band’s singer ripped the contract to shreds in the final moments, a report said. + +Branson was left stunned when the 66-year-old Plant tore the agreement to pieces right in front of the concert promoters, the newspaper said. + +“There was an enormous sense of shock,” a source told the Mirror. “He said no and ripped up the paperwork he had been given.” (Via) + +Branson’s dream of a Zeppelin reunion crashed as horribly as the VSS Too Soon. Nothing’s going right for that handsome, charismatic billionaire lately…","0" +"Robert Plant Reportedly Tears Up $800 Million Led Zeppelin Reunion Contract","Sorry to disappoint, fans of Led Zeppelin, but it doesn’t look like a reunion will be happening any time soon. + +According to a report from UK publication The Mirror, the group’s famed lead singer Robert Plant literally tore up a contract to reunite the band worth almost $800 million, saying the timing just wasn’t right for a reunion tour. + +Sir Richard Branson of the Virgin brand fame was apparently behind the entire thing, offering the band an obscene amount of money just to reunite for a few dozen shows. The contract was reportedly for 35 shows in three cities: London, Berlin, and an unnamed location in New Jersey. Each of the three remaining original members would have earned somewhere over $200 million each just for performing, while another $100 million in merchandising profits was to be shared between the group members. + +English: Robert Plant of Led Zeppelin +Robert Plant of Led Zeppelin (Photo credit: Wikipedia) + +Branson was reportedly also ready to supply the group with their own private jet for the tour. The mogul was prepared to take one of his airline’s planes and rebrand it “The Starship”. The contract also had an extension option to add 45 more shows in additional venues should the band agree. + +The other two original members of the group apparently signed on immediately, and Jason Bonham, the son of late drummer John Bonham, was set to step in for his father. Plant apparently met with conert promoters to discuss the deal, and during the meeting actually ripped the contract in two, ending any chance of a regrouping. + + +While $800 million is certainly a lot of money, it’s not like Robert Plant (or any of the other members for that matter) really need it. Led Zeppelin are one of the most successful groups of all time, having sold around 112 million records in the United States alone (that figure is three or four times that when the entire planet is counted). In fact, they are the fourth best-selling music act in American history, right behind The Beatles, Elvis Presley, and Garth Brooks. + +Robert Plant has also had an incredibly successful career outside of Led Zeppelin. He has released fourteen albums, selling additional millions and making his chart history that much more impressive. His collaborative album Raising Sand with bluegrass/country singer Alison Krauss may not have been his most commercially successful, but it was adored universally by critics, and won he, Alison, and producer T-Bone Burnett five Grammys back in 2009, including Record of the Year and Album of the Year. + +While the band’s last album of original music, Coda, was released back in 1982, the band has continued to sell well throughout the years, making millions in repackagings, reissues and live album releases. The group’s last show together was in London back in December of 2007, which was a tribute to legendary music executive Ahmet Ertegün. The concert is thought to have had the most-desired tickets of any show in history, as when it was announced, 20 million requests were submitted online for passes.","0" +"Led Zeppelin Reunion: Robert Plant Rips Up $300 Million Contract, Refuses To Rejoin Legendary Band","A Led Zeppelin reunion tour, backed by an astonishing amount of money put up by British billionaire Richard Branson, will never happen — because singer Robert Plant ripped up a contract that would have paid him about $300 million to play 35 concerts with the the legendary band in just three cities. + +The information about the aborted Led Zeppelin reunion tour came from an exclusive report in Britain’s Daily Mirror newspaper, which said that the 66-year-old Plant — who during the 1970s heyday of Zeppelin was one of the world’s most successful and recognizable rock stars — simply didn’t believe it was “the right thing to do.” + +“They have tried to talk him round but there is no chance,” said an anonymous source said by The Mirror to be close to Robert Plant. “His mind is made up and that’s that.” + +According to the Mirror story, the other two surviving members of Led Zeppelin — guitarist Jimmy Page, 70, and 68-year-old bass player/musical arranger John Paul Jones — had already signed their mega-contracts and were ready to set out on the tour, which would have taken them to London’s O2 Arena as well as Berlin and New Jersey. + +But Plant just wasn’t into it. + +Jason Bonham, the 48-year-old son of original Led Zeppelin drummer John Bonham, has also signed on to play drums as a salaried musician on the Zep reunion tour. + +Led Zeppelin formed in 1968 and were considered the biggest rock act in the world through the early and mid-1970s. But they broke up in 1980 after John Bonham died in his sleep at age 32 following a heavy drinking binge. + +Jason Bonham played drums with Led Zeppelin for the band’s one-off reunion performance during the Ahmet Ertugun Tribute Concert in 2007. Ertugun was the record label boss who signed Led Zeppelin to Atlantic Records, sight unseen, launching the then-unknown band’s meteoric career. + +Branson, according to the Mirror, guaranteed the band more than $900 million to be split among the three original members, for the proposed Led Zeppelin reunion tour. + +Plant’s share alone would have nearly tripled his current, already-formidable net worth, which is reported at $170 million. + +According to the Mirror’s source, Page, Jones, and Bonham were stunned by Plant’s refusal to take part in the tour. + +“It was a no-brainer for them but Robert asked for 48 hours to think about it. When he said no and ripped up the paperwork he had been given, there was an enormous sense of shock,” The Mirror quotes the source as saying. “There is no way they can go ahead without him.” + +Led Zeppelin fans can still get their dose of the legendary band through an ongoing series of remastered reissues of the original Led Zeppelin albums, a project being coordinated by Page.","0" +"Purported Lisa Bonet Twitter Account Suspended After Cryptic Cosby Tweet","After sending a tweet that many observers said they believed was directed at Bill Cosby, a Twitter account claiming to be that of “The Cosby Show” actress Lisa Bonet was suspended. The account was suspended Saturday following a Nov. 21 tweet directed to no one in particular that piqued the attention of many in the media, including the New York Post and Fox News. + +“According to the karma of past actions, one’s destiny unfolds, even though everyone wants to be so lucky… Nothing stays in the dark 4ever!” the tweet said. + +Bonet starred as Denise Huxtable on “Cosby” and many said they believed the tweet was directed at her former on-screen father, who has of late suffered a devastating blow to his public persona. Public anger prompted numerous partners to sever relationships with the embattled actor and comedian as a result of allegations he raped more than a dozen women during his career that were reignited by comedian Hannibal Buress last month. + +The account is no longer on Twitter, but it featured the Twitter handle @Lilakoi_Moon and used “Lisa Bonet” in its full name field. It also included a photo of the actress. Bonet changed her name to Lilakoi Moon while still acting under the name Lisa Bonet. + +Cosby and Bonet were rumored to have had a falling out during the 1980s because Cosby did not approve of her decision to shoot a sexually explicit scene in the 1987 R-rated film “Angel Heart” or to pose topless for a photoshoot with Interview magazine. Bonet left “The Cosby Show” to shoot the spin-off “A Different World” but returned after giving birth. She parted ways with the show again in 1991 and chose not to be part of a reunion special. + +The @Lilakoi_Moon account had been on the social networking service for a number of months, and before being shut down had garnered thousands of followers. The user sent tweets to verified Twitter accounts belonging to actor Kadeem Hardison and other members of the “Different World” cast. Representatives of Twitter did not immediately respond to requests from International Business Times to explain why the account was suspended. + +An account said to be that of Cree Summer, the actress who played Winifred ""Freddie"" Brooks on “A Different World,” told followers that the @Lilakoi_Moon was fake in a tweet July 10. + +I have to let everyone know that @Lilakoi_Moon is not a real account Lisa Bonet , my sister Lilakoi Moon is NOT on Twitter . Please do not + +— Cree Summer (@IAmCreeSummer) July 10, 2014 + +Bonet's reps have reported confirmed that the Twitter account does not belong to the actress and requested it be taken down. “I can assure you that is not her Twitter account and I have had the account suspended,” talent manager Jillian Neal told TheWrap Sunday.","0" +"McDonald’s Will Stop Serving Overweight Customers Beginning 1/1/15","Obesity rates in America have more than doubled over the last 2 decades and has become the leading public health issue in the U.S. With more than two-thirds of the adult population overweight, McDonald’s has decided to become part of the obesity rate solution – not the problem. + +According to reports, beginning January 1, 2015, McDonald’s will no longer serve customers who show risks of being overweight. They will define overweight by these standards: Over 170 lbs for women and 245 lbs for men. Children’s weight restrictions will vary depending on age and height. + +McDonald’s is currently running campaigns to shake its “junk food” image, insisting they sell nothing but good quality food. They are are branding themselves from “A dining experience of fast food” to “Good food served fast.” They want people to understand the risks of being overweight. + +So how will they know if you are overweight ? Will they ask you what you weigh and trust your answer? NO + +They are implementing scales at the from of every register just like the one in the photo below. You must stand on the scale when ordering or you will not be served. They also plan on posting signs to let customers know that they have the legal “Right to refuse service to anyone.” + +For drive-thru patrons it may be a bit more difficult to enforce. However, if the person looks like they exceed the weight restrictions, they will be refused service at the drive-thru window.","0" +"Official: Houthis take U.S. vehicles, weapons in Yemen","Sanaa, Yemen (CNN)Houthi rebels took all U.S. Embassy vehicles parked at the Yemeni capital's airport and wouldn't let departing U.S. Marines take their weapons with them, a top Sanaa airport official said about the latest evidence of unrest in an Arab nation long seen as key in America's fight against terrorists. + +The actions come after the United States, along with Britain, suspended operations at their embassies and moved out staffers because of the instability in Yemen. + +According to the official, the Houthis seized many U.S. Marines' weapons at the airport, and the American troops also handed over some to random airport officials. + +However, a senior U.S. military official told CNN the Marines disabled their weapons and gave them to a Yemeni security detail, which had escorted them to the airport, because the Marines were flying commercial. + +The U.S. Marine Corps sharply denied the allegations. + +""All crew served weapons were destroyed at the embassy prior to movement. None of them were 'handed over' in any way to anyone. The destruction of weapons at the embassy and the airport was carried out in accordance with an approved destruction plan,"" the statement read. + +The statement continued: ""To be clear: No Marine handed a weapon to a Houthi, or had one taken from him."" + +The previous night, embassy officials burned tens of thousands of documents and destroyed weapons that were inside the Sanaa embassy's storage warehouses, Yemeni employees of the embassy said. + +What you need to know about Yemen + +Yemen has been an important country to the United States as the home of al Qaeda in the Arabian Peninsula, one of the most feared, influential and operational terrorist organizations in the world. U.S. officials have had a long relationship with Yemeni leaders, working with them to target AQAP militants. + +But now, Yemen's latest leader, President Abdu Rabu Mansour Hadi, is gone, having resigned after Houthi rebels seized control of key government facilities, dissolved parliament and placed him under house arrest. + +All this movement has left the Houthis -- Shiite Muslims who have long felt marginalized in the majority Sunni country -- as the pre-eminent power in Yemen. + +Their takeover hasn't been smooth and it's not clear whether it will ever be complete. There has already been resistance to their attempted takeover of national government institutions from different groups in Yemen, particularly in the south, where there's a long-running secessionist movement, and in the oil-rich province of Marib to the east of Sanaa. + +Then there's the question of what it means for the United States and its anti-terrorism efforts. + +U.S. special forces stay in Yemen + +As of last month, U.S. officials hadn't engaged in talks with the Houthis, though there were discussions about whether to talk to them. + +Still, even amid the turmoil, the U.S. military remains active in Yemen. + +Take, for instance, the killing of senior AQAP cleric Harith bin Ghazi al-Nadhari and three other people in a drone strike on their vehicle on January 31. + +""They are still capable of conducting counterterrorism operations in Yemen, and frankly ... there's some counterterrorism training that's still ongoing ... with Yemeni security forces,"" said Rear Adm. John Kirby, a Pentagon spokesman. + +""I'd be less than honest if I said that there hadn't been some adjustments already made because of the political uncertainty,"" he said. ""We're just going to have to watch this closely going forward."" + +Yemen's government has been a key ally in the fight against AQAP, which has been tied to the failed attempt by ""underwear bomber"" Umar Farouk AbdulMutallab and Fort Hood shooter Maj. Nidal Hasan. More recently, the terror group has been linked to the slaughter at French magazine Charlie Hebdo. + +""They are a very dangerous group,"" said Kirby. ""They do want to threaten Western interests, including U.S. interests, and we do consider them a threat to the United States of America. We're watching them very closely."" + +Journalist Hakim Almasmari reported from Yemen, and CNN's Greg Botelho wrote in Atlanta. CNN's Jim Sciutto and Jamie Crawford contributed.","0" +"Pete Hegseth: Marines Exit Yemen Forced to Surrender Dignity, Weapons","Central Command reportedly is furious over a State Department order that Marines guarding the U.S. Embassy in Yemen were told by the State Department to turn their rifles over to Yemeni officials before boarding a private plane to evacuate the country, Fox News reports. + +The order is humiliating to Marines, who are essentially being told to break an oath they take during training, Pete Hegseth, CEO of Concerned Veterans for America, told Fox News Channel's ""The Kelly File."" +Special: The Emergency Radio Every Family Must Have — Special Offer +""We're surrendering our embassy. And now we're asking U.S. Marines to surrender their dignity, give up oaths they made, creeds that they lived by, and surrender their rifle,"" Hegseth said. ""I'm no Marine, but I know a lot of them and fought alongside a lot of them. Without their rifle they are nothing. They are taught you never give that up."" + +The Rifleman's Creed reads, in part, ""My rifle, without me, is useless. Without my rifle, I am useless."" +Latest News Update + +Get Newsmax TV At Home » + + +Special: Doctors Reversing Diabetes With Magnesium +""This is a mindless stupid bureaucrat making a decision like that offensive to military culture, offensive to procedures,"" Retired Four-Star Gen. Jack Keane told Kelly. ""I'm sure people at central command are furious."" + +Kelly said that Fox News' reporting has indicated that CENTCOM is indeed furious. + +Fox News later reported that the Marine Corps clarified that no ""crew-served weapons"" were turned over to anyone, but were destroyed at the embassy before the evacuation. ""They say their personal weapons were not destroyed at the embassy. They were instead 'rendered inoperable' at the airport and the destroyed components were left behind at the airport,"" Megyn Kelly said. +Special: US Intelligence Adviser Exposes Covert Plan to Destroy the US Economy +""They do not dispute, in this statement, the reporting that we have earlier tonight that CENTCOM is outraged over this entire incident about weapons being rendered inoperable at the direction of the State Department.""","0" +"Yemen’s Houthi rebels seize U.S. Marines’ weapons at airport","Yemen’s Houthi rebels seized weapons from U.S. Marines as well as several vehicles used by Americans stationed at the now-closed U.S. Embassy in Sana’a. + +It wasn’t immediately clear what types of weapons and vehicles were seized. + +An unidentified Sana'a airport official confirmed that the rebel forces took control of the U.S. Embassy vehicles, which were parked at the airport, United Press International reported. The same official also said that the Houthi rebels seized several weapons used by U.S. Marines who were trying to abide by a White House order and leave the country. + +U.S. State Department spokeswoman Jen Psaki said in a widely reported statement: “The Department of State has decided to suspend our embassy operations and our embassy staff have been temporarily relocated out of Sana'a. Recent unilateral actions disrupted the political transition process in Yemen, creating the risk that renewed violence would threaten Yemenis and the diplomatic community in Sana'a.” + +British and French embassies have been temporarily closed, with Germany, perhaps, not far behind. + +Houthi rebels are tied to Iran and regard Americans as enemies.","0" +"Mexico checks if 43 missing students in mass grave","Iguala de la Independencia (Mexico) (AFP) - More bodies were being pulled out of a mass grave in southern Mexico Sunday as authorities worked to determine if 43 students who vanished after a police shooting were among the dead. + +At least 15 bodies have so far been dug out of pits discovered Saturday on a hill outside the town of Iguala, 200 kilometers (125 miles) south of Mexico City, two police officers at the scene told AFP. + +The grim find came a week after the students disappeared when a protest turned deadly. Witnesses in Iguala say municipal police officers whisked several of the students away. + +Inaky Blanco, chief prosecutor for the violence-plagued state of Guerrero, declined to say how many bodies were buried in the pits. + +""We still can't talk about an exact number of bodies. We are still working at the site,"" Blanco told a news conference late Saturday in the state capital, Chilpancingo. + +The site was was cordoned off and guarded by scores of troops and police. + +View galleryForensic personnel unload bodies at the Iguala morgue … +Forensic personnel unload bodies at the Iguala morgue from a mass grave in Pueblo Viejo, in the outs … +More bodies were being recovered on Sunday, another officer said. + +Juan Lopez Villanueva, an official from the National Human Rights Commission, said that six pits were found up a steep hill probably inaccessible by car. + +Four forensic services vans left for the morgue late Saturday carrying nine bodies in silver bags. Authorities are conducting DNA analysis to identify the victims. + +The graves were found after some of the 30 suspects detained in the case told authorities about their location, Blanco said. The detainees include 22 police officers and gang members. + +If the bodies are confirmed to be those of the students, it would be one of the worst slaughters that Mexico has witnessed since the drug war intensified in 2006, leaving 80,000 people dead to date. + +View galleryPolicemen stand guard at Pueblo Viejo, in the outskirts … +Policemen stand guard at Pueblo Viejo, in the outskirts of Iguala, Guerrero state, Mexico, where a m … +- Police linked to gang - + +The students from a teacher training college disappeared last weekend after Iguala police officers shot at buses that the group had seized to return home after holding fundraising activities on September 26. Three students were killed. + +Another three people died when police and suspected gang members shot at another bus carrying football players on the outskirts of town. + +A survivor said in an interview that the officers took away 30 to 40 students in patrol cars. + +Blanco said investigators had confirmed suspicions that a criminal organization, the Guerreros Unidos, was involved in last week's crimes and that local police officers belong to the gang. + +View galleryMexican marines patrol at Pueblo Viejo, in the outskirts … +Mexican marines patrol at Pueblo Viejo, in the outskirts of Iguala, Guerrero state, Mexico, where a … +Authorities have issue an arrest warrant for Iguala's mayor, who has fled. + +In Pueblo Viejo, a hamlet surrounded by forests and mountains, a resident said the region is dominated by a drug gang and that he had seen municipal police officers going up the hill in recent days. + +""They were going up there back and forth,"" said the resident, Jose Garcia, pointing to a location between two mountains where the graves were found. + +- 'Savagely massacred' - + +Governor Angel Aguirre appealed for calm in his state, which is mired in poverty, gang violence and social unrest. + +""I call on all (Guerrero state residents) to maintain harmony, non-confrontation, and avoid violence,"" he said, offering his support to the families of those who were ""savagely massacred."" + +The missing students are from a teacher training college near Chilpancingo known as a hotbed of protests. + +Thousands of students and teachers blocked the highway between Chilpancingo and Acapulco for hours on Thursday, demanding help from federal authorities to find the missing. + +The police's links to organized crime has raised fears about the fate of the students in a country where drug cartels regularly hide bodies in mass graves. + +Around 30 bodies were found in mass graves in Iguala alone this year. + +""We are very worried. The families are very anxious,"" said Vidulfo Rosales, a human rights lawyer representing relatives of the missing. + +The United Nations has called the case ""one of the most terrible events of recent times.""","0" +"Bodies found in Mexico town where students vanished","Iguala de la Independencia (Mexico) (AFP) - Authorities were investigating whether several bodies found in clandestine graves in southern Mexico are those of 43 students who disappeared after a deadly police shooting last week. + +Inaky Blanco, chief prosecutor for the violence-plagued state of Guerrero, declined to say how many bodies were buried in the pits outside Iguala, 200 kilometers (125 miles) south of Mexico City. + +""We still can't talk about an exact number of bodies. We are still working at the site,"" Blanco told a news conference in the state capital, Chilpancingo. + +But two police officers at the scene in the community of Pueblo Viejo told AFP that at least 15 bodies were exhumed from the site, which was cordoned off and guarded by scores of troops and police. + +Juan Lopez Villanueva, an official from the National Human Rights Commission, said that six pits were found up a steep hill probably inaccessible by car. + +View galleryParents and relatives of missing students leave the … +Parents and relatives of missing students leave the Interior Ministry building after a meeting to pr … +Four forensic services vans left for the morgue late Thursday carrying bodies in silver bags. Authorities are conducting DNA analysis to identify the victims. + +The graves were found after some of the 30 suspects detained in the case told authorities about their location, Blanco said. The detainees include 22 police officers and gang members. + +If the students are in those pits, it would be one of the worst slaughters that Mexico has witnessed since the drug war intensified in 2006, leaving 80,000 people dead to date. + +The students from a teacher training college disappeared last weekend after Iguala police officers shot at buses that the group had seized to return home after holding fundraising activities on September 26. Three students were killed. + +Another three people died when police and suspected gang members shot at another bus carrying football players on the outskirts of town. + +View galleryA Mexican marine and a policeman guard the site where … +A Mexican marine and a policeman guard the site where bodies were found in unmarked graves on the ou … +A survivor said in an interview that the officers took away 30 to 40 students in patrol cars. + +Blanco said investigators had confirmed suspicions that a criminal organization, the Guerreros Unidos, was involved in last week's crimes and that local police officers belong to the gang. + +Authorities have issue an arrest warrant for Iguala's mayor, who has fled. + +- 'Savagely massacred' - + +Governor Angel Aguirre appealed for calm in his state, which is mired in poverty, gang violence and social unrest. + +""I call on all (Guerrero state residents) to maintain harmony, non-confrontation, and avoid violence,"" he said, offering his support to the families of those who were ""savagely massacred."" + +The missing students are from a teacher training college near Chilpancingo known as a hotbed of protests. + +Thousands of students and teachers blocked the highway between Chilpancingo and Acapulco for hours on Thursday, demanding help from federal authorities to find the missing. + +The police's links to organized crime has raised fears about the fate of the students in a country where drug cartels regularly hide bodies in mass graves. + +Around 30 bodies were found in mass graves in Iguala alone this year. + +""We are very worried. The families are very anxious,"" said Vidulfo Rosales, a human rights lawyer representing relatives of the missing. + +The United Nations has called the case ""one of the most terrible events of recent times.""","0" +"Are missing students in mass graves found near Iguala, Mexico?","Read this story in Spanish at CNNMexico.com + +(CNN) -- Gunmen opened fire at buses carrying students and soccer players in southern Mexico. + +It's been more than a week since that violent night of shootouts in Iguala, Mexico. Authorities say three students were among six people killed in the September 26 violence, and 43 students remain missing. + +Where are they? Authorities and witnesses fear they may be close to unraveling the mystery. + +Along a dirt road in a remote part of Mexico's Guerrero state, authorities turned up unmarked graves full of human remains on Saturday. + +Investigators found the remains of at least 28 people inside the graves, Guerrero State Attorney General Iñaky Blanco Cabrera told reporters Sunday. The bodies were covered in gasoline and burned before they were buried, he said, and it could take between two weeks and two months to identify them. + +A tip from suspects detained after the shootouts led them to the grave sites, authorities said. + +The missing students, who were studying to become school teachers at Escuela Normal Rural de Ayotzinapa, were mostly young men in their 20s, according to a website state government officials have set up to help in the search. + +""Help us find them!"" the website says, offering a reward of 1 million pesos ($74,000) for information leading to the missing students. + +State officials, who've faced sharp criticism over the students' disappearance, released a statement Sunday detailing their investigative efforts. So far more than 30 people have been detained, including 22 local police officers. + +The police have denied attacking anyone, according to a government statement on their detention. + +But protesters from the school have said officials aren't doing enough. + +""NOW IT IS MORE DANGEROUS TO BE A STUDENT THAN A CRIMINAL,"" one post on a Facebook page dedicated to the school said. + +Witnesses have accused police of orchestrating and participating in the shootings. + +""The goal of the police was to kill any person that was inside the perimeter they had,"" one student from the school told CNN en Español. + +Guerrero state Gov. Angel Aguirre has defended his government's response and called for calm in the face of protests. + +""To the family and friends of those who were savagely massacred, I offer all my solidarity and support,"" he said in a series of Twitter post Saturday. ""It would be highly condemnable, those who want to take advantage or politically profit from a situation like the one that today overwhelms and saddens us."" + +A bus carrying members of the third division Chilpancingo Hornets soccer club was also among those ambushed in what authorities described as three attacks on September 26. A 15-year-old player on the team was killed. + +Omar Sanchez, one of his teammates, described the ambush to CNN en Español. + +""We were just watching a movie and we saw the bullets come in and then it was like we were going off a cliff and the bus tipped over. And it was then that they started firing at us with machine guns,"" he said. ""It sounded so ugly, the gunshots and my teammates screaming, 'Help, leave us alone, we are injured.' A teacher said, 'you have already blinded me, please, we are the team from Chilpancingo."" + +The armed men said they weren't going anywhere, ordering the team to open the door. + +""Now you are going to be taken, we are going to kill all of you,"" the gunmen said, according to Sanchez. + +When the teacher refused to open the door, Sanchez said, the men opened fire again. + +The case has left many troubling questions unanswered. Key among them: Who gave the orders to open fire, and what was their motive? + +State prosecutors first said last week that the violence started after the college students commandeered three buses, and city police opened fire. + +Since then, evidence has tied the Guerreros Unidos criminal group, and police connected with them, to the shooting and the students' disappearance, Blanco told reporters Saturday. + +In 2013: 54 bodies found in mass graves in Mexico + +For years Guerrero state, which includes Iguala and the well-known resort city of Acapulco, has ranked among the Mexican states with the highest homicide rates, a crime statistic regularly used by officials and analysts when discussing the overall security situation. + +Figures released by Mexico's National Statistics and Geography Institute last year painted a grim picture of kidnapping throughout the country. + +A survey revealed that there were more than 105,000 kidnappings nationwide in 2012, the institute said, but only about 1,300 of them were reported to authorities. + +CNNMexico.com contributed to this report.","0" +"Police find mass graves with at least '15 bodies' near Mexico town where 43 students disappeared after police clash","Police in Mexico have found mass graves containing at least 15 charred bodies near where 43 students disappeared after a deadly police shooting last week. + +The burial pits were found Saturday on a hill in a community outside Iguala, Southern Mexico, the town where the students were last seen. + +Witnesses claimed that they had last been seen being led away by police. Twenty-two police officers were arrested in Guerrero today, accused of killing two students during the clashes last week. + +Scroll down for video + +Mexican authorities are investigating a mass grave discovered on the outskirts of Iguala, the same city where 43 students have been missing for a week + +A Mexican navy marine guards the road that leads to the site. Witnesses claimed that the students had last been seen being led away by police + +A car from the forensic technician service Servicio Medico Forense (SEMEFO) is seen in the area where a mass grave was found, in Colonia las Parotas on the outskirts of Iguala, in Guerrero + +Teen felled with killer punch after picking fight with... + +Dana Vulin unveils her horrific burns after being set on... + +HILARIOUS! Boy thinks Beyonce lied to him after wisdom tooth... + +He's alive! Moment 'dead' Ebola victim nearly sent to... + +Couple shares their fertility journey in heartwarming video + +Adorable baby elephant needs rescuing after going belly up + +Katy Perry living it up at a bar in Oxford, Mississippi + +Health officials issue order to Ebola patient family to stay... + +British jihadi challenges Cameron to put troops on the... + +Adorable bear cub gets rescued after he gets head stuck in... + +Peter Kassig's parents make plea to ISIS for son's return + +Oklahoma City Panhandler is busted when caught in 2013 car + +Inaky Blanco, is chief prosecutor for the violence-plagued state of Guerrero. + +He told a news conference in the state capital, Chilpancingo: 'We still can't talk about an exact number of bodies. We are still working at the site.' + +Reports from the scene in the community of Pueblo Viejo said at least 15 bodies were exhumed from the site. + +Iguala is about 120 miles (193 km) south of Mexico City in the increasingly violent state of Guerrero, the site of clashes involving students, police and armed men last week. At least six people were killed in a spate of incidents. + +Guerrero Governor Angel Aguirre said earlier this week that photos showed police had taken some of the students away. + +Several hundred students protested on Saturday night in front of Aguirre's residence in the state capital of Chilpancingo, expressing anger that some of their classmates may be among the bodies found in the graves. + +A car was overturned and several petrol bombs were hurled at the residence perimeter, where security outposts were lightly damaged. + +Authorities found the mass grave as police are scouring the area for nearly four dozen people missing after a rash of violence. Guerrero was the site of clashes involving students, police and armed men, which started in late September + +The graves were found up a steep hill after some of the 30 suspects detained in the case told authorities about their location + +If the students are in those pits, it would be one of the worst slaughters that Mexico has witnessed since the drug war intensified in 2006, leaving 80,000 people dead to date + +The pits were found Saturday on a hill in a community outside Iguala, Southern Mexico, the town where the students were last seen. Policemen stand guard at the site where the mass grave was found + +Policemen and forensic personnel holding white bags for the bodies arrive at Pueblo Viejo, in the outskirts of Iguala, Guerrero state, Mexico. + +Four forensic services vans left for the morgue late on Thursday carrying bodies in silver bags + +A police official said on Saturday that there was video footage of eight to 10 students being put into police trucks earlier in the week. + +Twenty-two police officers were arrested in Guerrero on Sunday, accused of killing two students during the clashes last week. + +Aguirre said on Saturday that a total of 30 individuals have now been detained in connection with the incidents. + +Local government officials criticized the police for showing an excessive use of force with the students in Guerrero, where gangs have evolved from a fragmented drug cartel and are fighting turf wars. + +Thirteen of an original group of 57 missing people re-emerged this week. Some had hidden, others had gone home. Dozens are still unaccounted for. + +Many mass graves have been found across Mexico in recent years and months, the legacy of drug gang violence that has killed around 100,000 people since 2007. + +Thousands of students and teachers blocked the highway between Chilpancingo and Acapulco for hours on Thursday, demanding help from federal authorities to find the missing + +Ayotzinapa Teacher Training College students shout slogans during a demonstration in downtown Chilpancingo. The missing students are from a teacher training college near Chilpancingo known as a hotbed of protests + +Governor Angel Aguirre appealed for calm in his state, which is mired in poverty, gang violence and social unrest + +The missing students are from a teacher training college near Chilpancingo known as a hotbed of protests. + +Thousands of students and teachers blocked the highway between Chilpancingo and Acapulco for hours on Thursday, demanding help from federal authorities to find the missing. + +The police's links to organized crime has raised fears about the fate of the students in a country where drug cartels regularly hide bodies in mass graves. + +Around 30 bodies were found in mass graves in Iguala alone this year. + +'We are very worried. The families are very anxious,' said Vidulfo Rosales, a human rights lawyer representing relatives of the missing. + +The United Nations has called the case 'one of the most terrible events of recent times.' + +life is random, meaningless, and grim.","0" +"Mexico finds 4 more graves at site of suspected student massacre","Four bodies have been found at the suspected massacre site of missing students.","0" +"6 hidden mass graves may hold missing Mexican students","Mexican authorities have discovered six hidden graves that may contain the bodies of more than 40 university students who went missing a week ago after clashing with local police in the violent state of Guerrero. + +The semiofficial National Human Rights Commission said Sunday that experts will conduct DNA tests in an attempt to identify bodies found in the graves. It was not yet clear how many bodies were present. + +Mexican police enter La Parota colony, on the outskirts of Iguala, Mexico, where a mass grave was found Saturday. (European Pressphoto Agency) +Guerrero state Health Minister Lazaro Mazon said nine bodies, burned beyond recognition, were recovered from the muddy pits in the first series of exhumations. He said it could take two weeks before identifications are made. Later, state prosecutor Inaky Blanco said 28 bodies had been recovered, in various conditions. + +Frantic parents who have been demanding the return of their children attempted to reach the site of the makeshift graves, near a slum on the outskirts of the city of Iguala, about 80 miles south of Mexico City. They and supporters blocked major highways in the area for several hours. + +“You took them alive, we want them returned alive,” read a huge banner unfurled across the highway that leads from Mexico City to Acapulco. + +On Sept. 26-27, Iguala city police attacked a group of students rallying against government policies. Six people were killed, more than two dozen injured and more than 50 students vanished. About 15 students eventually were found hiding in their homes, but 43 remained missing. Within days, 22 police officers were arrested for what prosecutors said was use of excessive force. + +Parents and surviving students have said they last saw some of the missing being taken away by police. Several parents offered up license plates of the police vehicles that took away their children. + +Guerrero Gov. Angel Aguirre said the local police corps was thoroughly penetrated by criminal organizations, at whose behest the police may have been acting. He said that after the discovery of the graves, an additional eight people were arrested. He did not identify them. + +If the graves turn out to contain the students, it will suggest that they were summarily executed by their captors, be they police or cartel criminals. And if that proves true, it would constitute the most egregious human rights atrocity in the 2-year-old government of President Enrique Peña Nieto and one of the worst in recent years. + +The students were from a special kind of rural university in the town of Ayotzinapa, near Iguala. They had a contentious relationship with authorities and often spearheaded demonstrations. + +After they went missing late last month, the federal government dispatched army, navy and national police to take over the search. The federal prosecutor’s office took charge of the case as soon as the graves were discovered late Saturday. + +“Mexico cannot let such a serious incident go unpunished,” Tomas Zeron, head of investigations from the federal attorney general’s office, said. + +More than 20,000 people are registered as having disappeared in Mexico in the last eight years, giving rise to an intense citizens’ movement to find them. Most never reappear.","0" +"Mass Graves Found In Mexico, Near Place Where 43 Students Went Missing","Police in the Mexican town of Iguala have found mass graves near the same place where 43 students went missing last month. + +The Mexican newspaper El Proceso says authorities have begun digging up bodies and are trying to determine their identities. + +The Wall Street Journal quotes Guerrero State Prosecutor Inaky Blanco as saying the graves were linked to the disappearance of the students but that it would ""irresponsible"" to jump to conclusions and say the bodies are those of the students. + +The Journal adds: + +The AP reports that the The Aytozinapa Normal school, where the missing students attended, is ""known for militant and radical protests that often involve hijacking buses and delivery trucks."" + +The AFP reports that Governor Angel Aguirre appealed for calm. + +""I call on all [Guerrero state residents] to maintain harmony, non-confrontation, and avoid violence,"" he said. + +El Universal reports that family members and other students reacted to the news violently, ""launching 10 molotov cocktails and flipping a car.""","0" +"Mexico police find mass grave near site 43 students vanished","Authorities unearthed on Saturday unmarked graves containing a number of bodies on the outskirts of a southern Mexico town where 43 students disappeared after a deadly police shooting last week. + +Inaky Blanco, chief prosecutor for the violence-plagued state of Guerrero, told reporters ""pits with bone remains"" had been found outside Iguala, 125 miles south of Mexico City. + +""It's hard to be sure that it's the missing students because we must conduct expert tests and find similarities with the people being searched,"" a state police agent at the scene told AFP on condition of anonymity. + +The graves were in rough terrain in a hillside community that is part of the Iguala municipality. Police kept reporters far from the site. + +The 43 students disappeared last weekend after Iguala municipal officers shot at buses that the group had seized to return to their teacher training college near the state capital Chilpancingo. + +Three students were killed. Another three people died when police and suspected gang members shot at another bus carrying football players on the outskirts of town. + +Witnesses told AFP that the officers took away several students in patrol cars after the shooting. One witness said he saw 30 to 40 people taken away. + +The officers are suspected of having links to criminal gangs, raising fears about the students' fate in a country where drug cartels often bury their victims in mass graves. + +Around 30 bodies were found in mass graves in Iguala alone this year. + +Another police official said the pits on the outskirts of Iguala were found thanks to an anonymous phone tip. + +""We are very worried. The families are very anxious,"" said Vidulfo Rosales, a human rights lawyer representing relatives of the missing. + +Authorities have detained 22 Iguala officers over the shootings and issued arrest warrants for the town's mayor and security chief, both of whom have disappeared. + +The United Nations has urged Mexican authorities to conduct an ""effective and diligent"" search for the missing, calling the case ""one of the most terrible events of recent times."" + +Dozens of police officers, soldiers and investigators were deployed to the area after the graves were found. + +Guerrero is one of the most violent states in Mexico, with gangs known as ""Guerreros Unidos"" and ""Los Rojos"" engaged in bloody turf wars.","0" +"Mexican investigators fear mass grave might hold 43 missing students","Security forces investigating the role of municipal police in clashes in this southern city a week ago found a mass grave on the edge of town, raising fears the pits might hold 43 students missing since the violence that also resulted in six shooting deaths. + +Guerrero Gov. Angel Aguirre said the victims had been “savagely slaughtered.” + +Jesus Lopez, the father of one of the missing students, told The Associated Press that a delegation of family and school representatives would come to Iguala on Sunday to get information about developments in the case from authorities. + +“We cannot say anything. We are very nervous, but until they inform us, there is nothing,” said Lopez, whose 19-year-old son, Giovani, hasn’t been seen since the violence last weekend. + +Separately, a group of students and relatives of the missing young people said they planned to march Sunday from Aytozinapa Normal school to the state capital of Chilpancingo to demand information in the case. + +Anger over the discovery of the graves exploded Saturday night when a group of young people from the school protested outside the governor’s Chilpancingo residence. They threw Molotov cocktails and overturned a car after state authorities told them they would not allow them to travel to the graves to determine if the bodies are those of their missing classmates. + +Guerrero State Prosecutor Inaky Blanco did not say Saturday night how many bodies were in the burial pits uncovered on a hillside on Iguala’s outskirts, and he declined to speculate about whether the dead were the missing students. + +“It would be irresponsible” to jump to conclusions before tests to identify the bodies, Blanco said. Officials said the federal Attorney General’s Office and the National Human Rights Commission had sent teams of experts to aid state authorities in identifying the remains. + +About 100 soldiers, marines and federal and state police on Saturday cordoned off the area where the grave site was found in the poor Pueblo Viejo district of Iguala, which is about 120 miles (200 kilometres) south of Mexico City. + +Blanco said eight more people had been arrested in the case, adding to the 22 Iguala city police officers detained after a police confrontation with student protesters last weekend set off a series of violent incidents in the city. + +The prosecutor has said state investigators had obtained videos showing that local police arrested an undetermined number of students after the initial clash and took them away. + +He said some of the eight newly arrested people were members of an organized crime gang, adding that some of them had given key clues leading to the discovery of the mass grave. + +Blanco said his investigators had found that “elements of the municipal police are part of organized crime.” He also said his office was searching for Iguala Mayor Jose Luis Abarca and had alerted officials across Mexico to be on the lookout for him. + +The governor had charged earlier in the week that organized crime had infiltrated the city government. + +State prosecutors have said the first bloodshed occurred when city police shot at buses that had been hijacked by protesting students from a teachers college, killing three youths and wounding 25. A few hours later, unidentified masked gunmen shot at two taxis and a bus carrying a soccer team on the main highway, killing two people on the bus and one in a taxi. + +Violence is frequent in Guerrero, a southern state where poverty feeds social unrest and drug gangs clash over territory. + +The Aytozinapa Normal school attended by the missing students, like many other schools in Mexico’s “rural teachers college” system, is known for militant and radical protests that often involve hijacking buses and delivery trucks. + +In December 2011, two students from Aytozinapa died in a clash with police on the highway that leads to the Pacific coast resort of Acapulco. Students had allegedly hijacked buses and blocked the road to press demands for more funding and assured jobs after graduation. Two state police officers were charged in the shootings. + +During that confrontation, students apparently set fire to pumps at a gas station on the highway when federal and state police moved in to quell the protest, and a gas station employee later died of burns suffered in the attack.","0" +"Mass grave found after 40 students disappear in Mexican protest","Soldiers searching for dozens of students missing after clashes with police at a demonstration in southern Mexico have found a mass grave full of bodies too burned or disfigured to be identified, officials said. +The mass murder near the rural town of Iguala, in the crime-hot state of Guerrero, may be one of the worst massacres since the clampdown on Mexico’s drugs gangs began eight years ago, and suspicion has fallen on local police links to a gang known as Guerrero Unido.","0" +"McDonald’s Removing Big Mac, Apple Pies And Eliminating Large Size Options","McDonald’s Removing Big Mac, Apple Pies And Eliminating Large Size Options. + +McDonald’s has just announced that it will be phasing out 8 menu items the beginning of next year and most McDonald’s customers are not happy. + +With McDonald’s profits tanking over the recent months, the company has had to make some tough decisions to find adequate solutions for their financial distress by shrinking menu sizes. “Our intent is to have a cleaner menu board that is easier for customers to absorb,” spokeswoman Lisa McComb said in a statement. “To do so we must simplify our current menu. + +This means the end of the Big Mac, apple pie and large size menu items. Currently, the Big Mac has a whopping 550 calories and 29g of fat. The Apple pie contains 250 cal, and it would take a full 69 minute to walk that off! With that being said, those two menu items were not a tough decision for elimination. + +McDonald’s is currently testing out a new version of their slim down menu in Delaware, Little Rock, Waco, Bakersfield, Macon and Knoxville. They plan a full nationwide rollout beginning February 1, 2015. + +One notable “ingredient” – preservatives – might also be eliminated from the menu altogether. Mark Andrés, President of McDonald’s USA, sparked widespread speculation when he asked investors, “Why do we need to have preservatives in our food?” And then answered himself with a “We probably don’t.” + +What do you think about this new menu transformation at McDonald’s? In an attempt to make America healthier, do you think it will work?","0" +"You can still order a McPizza at these two McDonald’s locations","Over the years, countless food items have come and gone from McDonald’s finely-tuned menu, but one franchise owner in the Midwest decided that the McPizza was more than just a fad. That’s right — the McDonald’s pizza that you knew (and loved?) in the ’90s is still on the menu, but only at two U.S. locations. + + +FROM EARLIER: Video: McDonald’s explains that its McNuggets are really made from chicken and contain no beaks + +As reported by Canada.com, one McDonald’s on the Ohio River and another in Spencer, West Virginia, both owned by Greg Mills, still serve piping hot McPizzas day in and day out. + +“According to employee Judy Norman, it’s the same pizza as they sold when she started there 11 years ago and it’s presumably the same that children everywhere enjoyed throughout the 1990s,” writes Canada.com’s Ashley Csanady. + +Norman tells Canada.com that there are “days when everyone wants pizza and there are days where just every so often you get a pizza [order].” + +So if you were planning on making a cross-country road trip any time soon, it might be worth altering your route just to make sure you pass through Spencer, West Virginia on your way. After all, McDonald’s should have the pizza ready for you in under 5 minutes:","0" +"Attention children of the ’90s: you can still get McDonald’s pizza","Remember the crunch of the cornmeal crust? And the stringy cheese, with a slightly sweeter-than normal marinara underneath? + +Maybe you shoved french fries in it like birthday candles. Or ate it crust first, as was the style at the time. + +In any case, if you’re a child of the nineties, you remember it well: McDonald’s pizza. + + + +And, like pogs and Beanie Babies, it too disappeared with the innocence of your childhood. + +Except, in two magical locations in Ohio and West Virginia, where one hero owner has kept the McDonald’s pizza ovens burning all these years later. + +So bust out a gel pen to jot down these directions, because I’m about to tell you where you can still buy McDonald’s pizza. + + +Neslted on the banks of the Ohio River, along the border with West Virginia sits the village of Pomeroy, population 1,852 in the 2010 census. And its McDonald’s, located along Main Street on the riverbank, still pumps out pizza — in five minutes or less, of course. + + + +It’s just a seven-and-a-half hour drive from Toronto in zero traffic, according to Google Maps. + +And, thanks to owner Greg Mills, there’s another McD’s where you can still get a slice, just over ninety kilometres away, across the state border. Spencer, West Virginia also boasts a McDonald’s that’s still lighting the pizza fires — or electrical coils, as the case may be. + +According to employee Judy Norman, it’s the same pizza as they sold when she started there 11 years ago and it’s presumably the same that children everywhere enjoyed throughout the 1990s. She said the location sold 13 pizzas yesterday, but there are “days when everyone wants pizza and there are days where just every so often you get a pizza [order].” + +Mills, who it’s pretty safe to call an American hero for preserving this very unique pizza, couldn’t not be immediately reached for comment, but this post will be updated should he return our calls. + + + +Whatever actually happened to McDonald’s pizza, you ask? + +Well, for starters, it turned out adult palates didn’t quite take to it the same way kids did. When McDonald’s first launched its pizza in the Canadian market in the early ’90s, it was tapping into a growing appetite for pizza as burger sales dwindled. It even launched hockey-themed TV ads. + + + +The market for the savoury pie topped $2 billion in the early 90s, according to a 2004 National Post article on the death of McDonald’s pizza. And the company poured $25 million into the ovens alone across Canada, to moderate success throughout the decade. Then the-drive through took over — remember waiting for your pizza to be delivered with a plastic number on top of your car? — and pizza slowed things down as its own sales were dragging. + +So the ovens were scrapped and McDonald’s turned its sights on other gimmicky productions — like the Arch Deluxe, which I think we can blame for Jessica Biel becoming a thing.","0" +"There Are Still Two McDonald’s That Serve McPizza From the ’90s","Domino's was still killing it with the Noid in the '90s when McDonald's rolled out McPizzas to get in on ""the dinnertime business."" The fast-food chain made clever signs by tipping Golden Arches sideways into serviceable Zs, and Pizza Hut's copywriters predicted, ""Every place you see a McDonald's pizza, you're going to see a war."" Formidable as all that seemed, that war never came and McPizza became a nostalgic slice for countless millennials, which is why it's insane that two locations owned by a guy along the Ohio–West Virginia border are still cranking out the ""pizza you won't believa."" + + + +Two decades ago, the chain's ""patented"" ovens needed five and a half minutes to bake pizzas — time-consuming McPizzas were the the McWraps of their day — so most were gone by 2000. It's not clear where Greg Mills's locations in the very small towns of Pomeroy, Ohio, and Spencer, West Virginia, are getting their raw materials for the discontinued menu items, but mysteriously, they're still selling. Judy Norman, an employee who's been at the West Virginia spot for 11 years, tells Canada.com ""it’s the same pizza as they sold when she started there 11 years ago and it’s presumably the same that children everywhere enjoyed throughout the 1990s."" In other words, there may be a way to tap into all that nostalgia, but that doesn't mean it's not freezer-burnt. + +[Canada.com]","0" +"DISCONTINUED '90S MCPIZZA STILL EXISTS AT THESE MCDONALD'S LOCATIONS","Gone are the days when Jason Alexander danced on the streets to celebrate McDonald's McDLT, and -- SO WE THOUGHT -- gone are the days when the McPizza (""The pizza you won't believa!"") was hawked to awed fast-food patrons. Because, as it turns out, there are still two McDonald's locations selling the long-since-discontinued Italian-ish treat. So maybe there's still hope for Jason Alexander. + +It's not quite public knowledge how the two locations (located on the Ohio-West Virginia border in the towns of Pomeroy, OH and Spencer, WV) still have access to the McPizza; an employee at the West Virginia location has said that ""it’s the same pizza as they sold when [she] started there 11 years ago and it’s presumably the same that children everywhere enjoyed throughout the 1990s,"" according to Canada.com. + +Fans of the five-minute meal need only travel to one of the two tiny border towns to indulge their decades-old craving. Just know that -- if you do go -- you're most likely diminishing a stockpile of nostalgic food that might not ever be replenished. + +Adam Lapetina is a Food/Drink staff writer for Thrillist, and despite being born during its heyday, has never eaten a McPizza. Read his musings at @adamlapetina.","0" +"Newly-Found Document Holds Eyewitness Account of Jesus Performing Miracle","Rome| An Italian expert studying a first century document written by the Roman historian Marcus Velleius Paterculus that was recently discovered in the archives of the Vatican, found what is presumed to be the first eyewitness account ever recorded of a miracle of Jesus Christ. The author describes a scene that he allegedly witnessed, in which a prophet and teacher that he names Iēsous de Nazarenus, resuscitated a stillborn boy and handed him back to his mother. + +Historian and archivist Ignazio Perrucci, was hired by the Vatican authorities in 2012, to sort, analyze and classify some 6,000 ancient documents that had been uncovered in the gigantic archive vaults. He was already very excited when he noticed that the author of the text was the famous Roman historian Velleius, but he was completely stunned when he realized the nature of the content. + +Professor Perrucci found the text in the archives of the Vatican, while searching amongst a bundle of personal letters and other trivial documents dating from the Roman era. + +The text as a whole is a narrative of the author’s return journey from Parthia to Rome that occurred in 31 AD, recorded in a highly rhetorical style of four sheets of parchment. He describes many different episodes taking place during his trip, like a a violent sandstorm in Mesopotamia and visit to a temple in Melitta (modern day Mdina, in Malta). + +The part of the text that really caught M. Perrucci’s attention is an episode taking place in the city of Sebaste (near modern day Nablus, in the West Bank). The author first describes the arrival of a great leader in the town with a group of disciples and followers, causing many of the lower class people from neighbouring villages to gather around them. According to Velleius, that great man’s name was Iēsous de Nazarenus, a Greco-Latin translation of Jesus’ Hebrew name, Yeshua haNotzri. + +Upon entering town, Jesus would have visited the house of a woman named Elisheba, who had just given birth to a stillborn child. Jesus picked up the dead child and uttered a prayer in Aramaic to the heavens, which unfortunately the author describes as “immensus”, meaning incomprehensible. To the crowd’s surprise and amazement, the baby came back to life almost immediately, crying and squirming like a healthy newborn. + +Marcus Velleius Paterculus, being a Roman officer of Campanian origins, seems to perceive Jesus Christ as a great doctor and miracle man, without associating him in any way to the Jewish concept of Messiah. + +Many tests and analysis have been realized over the last weeks to determine the authenticity of the manuscript. The composition of the parchment and ink, the literary style and handwriting have all been carefully scrutinized and were considered to be entirely legitimate. The dating analysis also revealed that the sheepskin parchment on which the text is written, does indeed date from the 1st century of this era, more precisely from between 20-45 AD. + +This new text from an author known for his reliability, brings a brand new perspective on the life of the historical character that is Jesus of Nazareth. It comes to confirm the Gospels on the facts that he was known for accomplishing miracles and that his sheer presence in a town was enough to attract crowds of people. + +A complete and official translation of the document should be made available online in many different languages over the next few weeks, but the impact of the discovery is already felt in the scientific community. Many scholars have already saluted the finding as one of the greatest breakthrough ever realized in the study of the historical life of Jesus, while others have expressed doubts about the conclusions of Professor Perrucci and demand for more tests to be performed by other scientific institutions before drawing any conclusions.","0" +"NHL expansion to include Toronto, Quebec City, Seattle and Las Vegas: Report","The NHL may be set to expand in a big, big way. + +Sports Business News reported late Tuesday the league is preparing to add four teams by 2017 in Toronto, Quebec City, Seattle and Las Vegas. + +Expansion fees could reach a combined $1.4 billion. + +The number of NHL teams would increase to 34, including nine Canadian clubs. + +Earlier Tuesday, a report in the Vancouver Province, citing sources close to the situation, said an expansion team in Sin City was a “done deal” and the only thing yet to be determined is who will front the ownership group. + +The report also indicated any expansion plans might include more than two teams. + +In May, Las Vegas officials broke ground on the building of a 20,000-seat multi-sport arena to be completed in spring 2016. + +Construction on a $400 million, 18,000-seat arena in Quebec City is underway with a projected opening date of Sept. 2015. The rink is being built as part of a public-private partnership between the city and Quebecor Media, owner of QMI Agency, Sun Media and Sun News Network.The league has routinely denied any plans for expansion in recent years. + +In spite of that, NHL commissioner Gary Bettman and deputy commissioner Bill Daly have reportedly had several meetings with city officials and potential ownership groups in Seattle. + +Bettman has in the past admitted to receiving interest from groups in Seattle, Las Vegas, Kansas City and Quebec City. + +“We’re listening, and that’s all we’re doing,” Bettman said in March. “We haven’t decided to engage in a formal expansion process at this point, but we’re listening. There is a lot of interest, and some of that’s a testament to the state of the game right now.” + +The league last expanded in 2000 with the addition of the Columbus Blue Jackets and Minnesota Wild.","0" +"Four new NHL expansion teams? Vegas, Seattle, Toronto and Quebec by 2017: Report","There are few topics in the NHL that get people buzzing like expansion and relocation do. Drop some morsel of news in the dead of August, and it’s like tossing the last bite of a Shake Shack burger to a flock of pigeons in Central Park. + +On Tuesday, Tony Gallagher and Howard Bloom chucked their meat and the flock went crazy. Gallagher said that NHL expansion to Las Vegas was a “done deal,” and then Bloom upped the ante by claiming that the NHL will add Vegas, Seattle, a second Toronto franchise and Quebec City by 2017, the 100th anniversary of the League. + +(No word on whether the League will begin an aggressive cloning program to fill out those rosters with NHL-level talent. Protect your comb, Jonathan Toews, they’re coming for DNA samples!) + +Bill Daly of the NHL said the four-team expansion is ""not in"" the NHL's plans. Because what else is he supposed to say... + +Gallagher of The Province wrote with finality that the NHL was coming to Las Vegas through expansion: + +Sources close to the situation have indicated Las Vegas is a done deal, the only thing to be determined being which owner will be entitled to proclaim that he brought the first major league sports franchise to Sin City. + +And given how dead set against a team in the gambling haven the commissioner was 10 years ago, this move into another player friendly state-tax-free zone represents a considerable about-face indeed. + +You know, we started getting an inkling that Bettman had changed his tune on Las Vegas when he moved one of the league’s signature promotional events there in 2009, but yes, this is a considerable about-face indeed! + +So, in summary, expansion to Las Vegas is a “done deal” except for the fact that there isn’t an ownership group that’s been approved by the Board of Governors; nor is there an expansion fee established for the market that would, in theory, determine who’s willing to buy-in (oooh, Vegas parlance!). + +Look, we’re all in total squee-mode for a team in Vegas. Or really any declaration that expansion is going to happen. But the proliferation of this “done deal” report – by Tony Gallagher, no less – is the most Hockey August moment in the history of Hockey August. + +For the love of Balsillie, he actually writes “the only thing to be determined” is the group actually owning the team. That’s like writing, “The Penguins are going to trade for a first-line winger. They just need to find a team that will trade them one.” + +Is Vegas a done deal? Of course not. + +Is it likely? Connecting the dots, one could draw that conclusion. + +MGM Grand and AEG aren’t building a $375 million arena to house a Carrot Top repertoire. The NHL didn’t structure its realigned conferences with 16 in the East and 14 in the West to make things easier for Winnipeg. And with the NHL pulling in record revenue, attendance and ratings, the iron hasn’t been hotter to strike for expansion. + +But as we’ve noted previously about Vegas: It’s unlike any other market in professional sports. There’s unrivaled competition for entertainment dollars. Many of the people who would attend the games as local fans are working while the games are being played. The largest target audience for the team would be the casinos who fill the considerable luxury box space in the new arena and tourists who pop in to see a game while in Sin City – or, perhaps, get comp’d for one. + +It wouldn’t surprise us in the least to see the NHL dive into the market, despite those mysteries, just to be first ones in and because Bettman obviously believes an association with Vegas brings some level of prestige to the League. + +But what about the other three teams? + +Bloom, of Sports Business News, reported later on Tuesday that the NHL was going full-on expansiongasm by adding every city that it’s considering adding for the last several years. Four new franchises, none through relocation: + +“NHL expansion – four teams added by 2017, Quebec City, Toronto, Seattle, and Las Vegas $1.4b in expansion fees” + +If you’ve been following the Seattle angle, you know the situation: Chris Hansen – the billionaire, not the predator catcher – has an arena construction deal with the city that hangs on attracting an NBA team; the only hope for an NHL team there first is if Hansen has a change of heart, and Vancouver billionaire Victor Coleman is working with him to that end. + +Then comes the real fight: Convincing a city council that has otherwise been apathetic to hockey to turn on the funding faucet for an NHL team’s arena. + +Then there’s Quebec City, which will have an NHL-ready arena next year and has no shortage of financial powerhouses ready to step up for an expansion franchise. It’s also been the most public and hubristic bid for a team, otherwise known as the opposite of how Gary Bettman likes to operate. + +Then there’s a second team in Toronto, which remains the best idea out of all of these options. Then again, what media conglomerates are left to own a team there? The Score app? + +And what level of bribery to the Leafs would it take to even crack that market? + +Bloom believes this will happen because the NHL won’t be able to keep itself from collecting that expansion franchise windfall, and that’s as solid a theory as any. It makes sense that the League would expand quickly before losing that expansion money to another relocation (/casts an eye at Florida and Arizona). + +All of this makes sense from a timing perspective and, of course, because we understand the League’s avarice. There are still significant obstacles in a couple of these markets, but it’s not outrageous to think it could happen. + +Which leaves us with the biggest decisions of all: The nicknames! Seattle Sasquatch, Las Vegas Craps, Quebec Nordiques (‘natch) and Toronto Rakes (the sworn enemy of Leafs)!","0" +"NHL expansion plans in the works: reports","The NHL is considering expanding by as many as four teams, according to a pair of reports, with Toronto and Quebec City in the mix to land new franchises. + +Howard Bloom of Sports Business News tweeted that the league will add four franchises ""by 2017"" in Toronto, Quebec City, Las Vegas and Seattle. + +Bloom added that the NHL would take in $1.4 billion in expansion fees with the deals. + +Also on Tuesday, Tony Gallagher of the Province, based in Vancouver, reported that an NHL team in Las Vegas is a ""done deal,"" according to ""sources close to the situation."" + +However, French-language TVA Sports reported that NHL deputy commissioner Bill Daly denied the league is looking to expand. + +""It's not in our plans,"" TVA Sports quoted Daly as saying in French. ""There is absolutely nothing new on that."" + +The NHL hasn't expanded since the Columbus Blue Jackets and the Minnesota Wild joined for the 2000-01 season. + +NHL commissioner Gary Bettman, who has previously dismissed talk of expanding beyond the league's 30 teams, visited Seattle in May for an update on a proposed new arena. + +In July, former NHL great Wayne Gretzky's agent denied a report that his client is among a group of investors looking to bring a team to the city. + +Toronto and Quebec City have long been considered candidates if the NHL decides to expand beyond the seven Canadian-based clubs in operation. + +Quebec City hasn't had an NHL team since the Nordiques moved to Denver in 1995. + +Toronto, of course, is already home to the Maple Leafs, but it's possible that Canada's most populous city could support a second team, whether in the city proper or the surrounding suburbs. + +Markham, Ont., just north of Toronto, has flirted with the idea of funding the construction of an NHL-sized arena, but those plans have stalled. + +Arid Las Vegas may seem like an odd place for a hockey team, but the Twitter account attributed to Panthers goalie Roberto Luongo suggested a sizable home-ice advantage could be enjoyed against weary visitors to Sin City. + +""Gonna be unreal when Las Vegas goes undefeated at home every year,"" tweeted @strombone1.","0" +"Reports: NHL expansion could include Las Vegas, others","The odds of bringing a big-league franchise to the city of Las Vegas have always seemed long for a lot of reasons, but that may soon change and it might just be the NHL that brings top-level professional sports to Sin City. A recent report suggests that an NHL team coming to Las Vegas isn't so much a pipe dream as it is a certainty. + +Tony Gallagher of the Vancouver Province reported that commissioner Gary Bettman, who has so often said “we're not looking to expand” or “we have no plans for expansion” so many times over the last decade, is changing his tune on expansion. + +More from the Province: + +…Recently the nature of the rhetoric has changed so much that the question is becoming not if, but when [the league will expand]. + +And then the ultimate question. Will they be able to limit the number of new teams to just two? + +Sources close to the situation have indicated Las Vegas is a done deal, the only thing to be determined being which owner will be entitled to proclaim that he brought the first major league sports franchise to Sin City. + +“Done deal.” Sounds almost too good to be true and it may be, but there has been movement on the expansion front recently. + +UPDATE: NHL deputy commissioner Bill Daly denied the report Wednesday morning in comments to TVA Sports: + +""[Expansion to Las Vegas is] not in our plans, there is absolutely nothing new in that,"" he has admitted to TVASports.ca. + +And if it were an organization struggling with financial difficulties, as the Florida Panthers, who moved rather in the ""Sin City""? + +""We have no move in sight, whether in the case of the Panthers, or any other team besides,"" replied Daly. + +Even in light of the league's denial, there's still reason to believe the NHL will have to soon expand and cities like Las Vegas and another rumored candidate Seattle would help expand the league's footprint. + +Here's why it's not completely outlandish to envision Vegas as a future NHL city. For one, they have two open spots in the Western Conference to even things out and bring some competitive balance. The Eastern Conference currently has 16 teams, while the West has 14. If the NHL expanded to the most long-rumored top candidate of Seattle, that would help even things out. It's definitely not as simple as that, though. + +Another barrier for Las Vegas would have been an arena, but that may no longer be an issue. The city has been home to minor-league hockey for years, but now Vegas is in the process of building a new arena however with the aim of bringing either an NHL or NBA team to Vegas. + +MGM and AEG, owner of the Los Angeles Kings, are teaming up on the project that broke ground in Las Vegas in May. The new arena is due to open in 2016 and will have 20,000 seats, but a projected capacity of 17,500 for hockey. The company building the arena, ICON, is also building the Edmonton Oilers' new arena. Kings great Luc Robitaille was on hand at the ground-breaking. + +There has long been a desire for Las Vegas to finally get a major league franchise and there are likely more than a few individuals out there that would be willing to bet on Sin City to support a big team. + +But here are the issues that make it seem a little less likely. There are other markets like Quebec City or Southern Ontario, that have long been pushing for NHL teams and would appear safer bets than Las Vegas. Putting teams in Seattle and Las Vegas would help even out the Western conference, but there could be an uproar if the NHL goes to two more non-traditional markets while strong Canadian markets exist to make money hand over fist. + +A recent report from CBC suggested that Canada could support three more NHL teams. The league undoubtedly knows that they could get a lot out of more Canadian markets and also have that new TV rights deal with Rogers, a company that would no doubt love more Canadian markets. + +That's where a second report comes in regarding expansion. Howard Bloom of SportsBusinessNews.com reported that the NHL will expand by four teams including Las Vegas, Seattle, Quebec City and Toronto. + +Update: In light of Daly's comments, the timeline sure doesn't seem to add up on this one, but it is hardly surprising that the league would come out in strong denial. With expansion ""not in the plans"" now, it doesn't mean it can't be eventually, and possibly soon. + +A $1.4 billion figure for combined expansion fees seems a bit high. The last time the NHL expanded between 1997 and 2000, expansion fees were a reported $80 million, which was a $30 million difference from the previous high. In the 14 years since, you better believe that number is way up from $80 million. Either way, the NHL stands to gain quite the influx of cash if they can expand. + +The Winnipeg Jets paid a $60 million relocation fee on top of the reported $170 million True North paid to purchase the Atlanta Thrashers. The relocation fee likely wouldn't be in the same range as an expansion fee, but it offers a more recent point of reference. + +Talk of widespread expansion is a big step away from what commissioner Gary Bettman told the Las Vegas Review-Journal in June: + +“Right now, we're not looking to expand. I know Las Vegas is an important city. Whether or not it's a city for the NHL to put a team in is still to be determined. We have not done any investigating as to whether or not the city could support the NHL or looked at potential ownership groups. If the owners were to approve expansion, we would certainly begin looking more closely at Las Vegas and other potential markets.” +It doesn't shut the door, but there's a lot of moving parts to expansion and you'll never hear the NHL commissioner get ahead of himself. It's clear that the gears are in motion on some level, though. + +Quebec City is already building an arena that is set to be completed by 2015. The Vegas arena will be ready by 2016. Investors have interest in putting an arena in Markham, Ont., and Hamilton, Ont., has also long been a possible expansion/relocation target. + +Seattle meanwhile has yet to break ground on an a new arena, but there has been some movement recently as real estate mogul Victor Coleman is adding some weight to a potential ownership group. He recently met with Chris Hansen, who is working towards bringing an NBA team to Seattle and has promised the city an arena if successful. There were reportedly talks of building the arena if the city secures an NHL team first. Coleman told KING5 News in Seattle that there is a ""clear path"" to bringing the NHL to the city. + +A possible 34-team league by 2017 is a bit concerning, however. Could the international talent pool support it? It seems to be a stretch. Diluting the competition should be a major fear as there are a lot of NHL players right now that are just barely scraping by in a 30-team league. You don't have to look any further than a lot of the fourth lines in the league. Thirty-two teams may even be a stretch at that point, but adding 50 new players wouldn't be as straining as trying to add 100. + +There are a lot of questions left to be answered and the fact that none of the hockey insiders that are usually on top of the big stories like this have backed up the reports yet certainly takes a little air out of these exciting developments. + +Expecting the NHL to expand by 2017 without relocating current teams seems a bit overly-optimistic, but the league is making more money than it ever has and is enjoying growing popularity. More expansion is probably at its most likely since 2000 when the Minnesota Wild and Columbus Blue Jackets entered the league and that offers some serious excitement for some possibly hockey-hungry markets.","0" +"Report: Toronto, Seattle, Quebec City to join Vegas in 2017 NHL expansion","Apparently Las Vegas isn't the only city on the National Hockey League's expansion team radar: Seattle, Toronto and Quebec City will add franchises as well with a target date of 2017, according to a tweet from SportsBusinessNews' Howard Bloom. + +Bloom said the four-fold expansion, which would increase the number of NHL teams to 34 and the number of Canadian team to nine, could raise $1.4 billion in expansion fees. + +A report Tuesday in Canada's The Province revealed the finalization of an NHL franchise in Las Vegas, with only the new team's ownership left to determine. The move would entitle Las Vegas to a professional sports franchise in one of the four major sports league's for the first time in the city's history. NHL commissioner Gary Bettman has previously voiced disapproval of such a move out of concern over the city's potentially damaging connection to the sports betting industry. +On Wednesday morning, Deputy Commissioner Bill Daly publicly denied that anything was imminent in Las Vegas. + +Seattle has been at the center of expansion rumors for more than a year and Quebec City has a new arena that is slated to open in 2015. A new team in Toronto would mean a second franchise for the city. The Maple Leafs are the NHL's highest grossing and most valuable franchise by net worth. + +- Will Green","0" +"NHL expansion rumors: This time, Las Vegas is about to get a team","Item: Vancouver Province columnist Tony Gallagher wrote Tuesday that the NHL will expand soon, and that a franchise in Las Vegas is a lock. + +Well, we all know about Las Vegas and locks. + +Hey, a team in Vegas would be nice because, well, the Seattle Metropolitans are getting ready for their first season in the Western Conference, and Vegas would make 16 teams in the West to balance out the 16 in the East and ... + +Oh, wait, you say there's no team in Seattle? But, but, but ... we thought it was getting a franchise this year, too. + +Yeah, the crickets are still competing with all the chirping about that, about how the NHL is increasing from 30 ... to 32 ... to 34 ... or more clubs. + +Gallagher wrote that NHL commissioner Gary Bettman has changed his mind about expansion and is now ready to take the plunge — and that he doesn't have to stop at just two teams. + +The NHL adding more than two fits historically. This is how the league has operated the past 40-plus years: + +1967: Next Six, to join with the Original Six. + +1970-74: Six, to continue Western expansion and to compete with the WHA. + +1979: Four, as the league absorbed the surviving teams of the dying WHA. + +1991-93: Five, as the Sun Belt strategy took hold. + +1998-2000: Four, as part of the league's reunion tour (Atlanta, Minnesota, Ohio). + +There are enough worthwhile markets outside Seattle and Las Vegas (Quebec City, Kansas City, Toronto, Hamilton, Portland) to go to 36. Also, Bettman and the owners know they can tap an easy revenue stream (aka franchise fees) if they want/need to pad their cash reserves.","0" +"Gallagher: Bettman has changed his tune on NHL expansion","It wasn’t very long ago that NHL commissioner Gary Bettman was treating talk of expansion as though he was being asked if he’d like an epidemic of Ebola. + +But recently the nature of the rhetoric has changed so much that the question is becoming not if, but when. + +And then the ultimate question. Will they be able to limit the number of new teams to just two? + +Sources close to the situation have indicated Las Vegas is a done deal, the only thing to be determined being which owner will be entitled to proclaim that he brought the first major league sports franchise to Sin City. + +And given how dead set against a team in the gambling haven the commissioner was 10 years ago, this move into another player friendly state-tax-free zone represents a considerable about-face indeed. + +But people have been betting on hockey games for years and to pretend games couldn’t be fixed just as easily anywhere as in Vegas is pretty ridiculous, so that posturing has fallen by the wayside. + +A new team close to the newly renamed Arizona squad and California’s big three is all but assured, the only question being when and with which other city. Or should that be plural? + +With all the activity going on in the Seattle area in the last little bit it would be quite a stretch to imagine that much time and effort being spent by so many wealthy men being frittered away for nothing. + +At the moment there are no surefire plans to build a new rink, but that could change at any time with Vancouver billionaire Victor Coleman among many reportedly showing interest in putting an NHL team into the city. + +And Bettman hasn’t been visiting there to see if it really does rain a lot. + +It’s been 15 years since the NHL expanded — and given there are 16 teams in the east and just 14 in the west, taking in two more teams would certainly seem to make a lot of sense, the same amount of sense it made when realignment was first announced. + +And expanding without the players getting their mitts on any of the money other than the increase in payrolls is surely tempting, at least to those owners who remember the hefty cheques they cashed for Columbus and Minnesota. + +Whereas before the commissioner balked at expansion, this is a sample of his more recent verbal footwork: + +“There’s a lot of interest. We’re hearing from multiple groups in Seattle and in Vegas and Kansas City and Quebec City,” Bettman said to the Tribune while scoping out Target field in Minny for yet another trip to the well of outdoor games. + +“We have not decided to engage in a formal expansion process but we listen to expressions of interest. It’s not something we’ve seriously considered yet.” + +Like hell it isn’t. They’d have to be nuts not to be thinking about it seriously. + +And since then things have changed for a commissioner who hates to move teams in his league no matter how dire the circumstances might appear — one of the most likable aspects of his regime for most hockey fans. Once the league comes to your area, it is going to stay through thick, thin and the almost impossible, as seems to be the case in Phoenix. + +But could that long-standing policy and loyalty change with the Florida situation? True there’s a lease until 2028, but with the Panthers bleeding money, even the city of Sunrise can’t seem to see the point of carrying on much longer, so perhaps one of these new cities could get an existing team after all. + +And while Kansas City isn’t really likely to be a serious contender in this expansion soup unless they’re going to stretch it to four teams, saying no to Quebec City in favour of two more U.S. cities with no proven NHL backgrounds is almost certainly not going to happen. + +Going back to Minnesota has been a success, and there’s no question there’s more money and corporate backing than ever before in Quebec. Even an expansion team there in a new arena would be virtually assured of sellouts into perpetuity. + +There will be all manner of bleating about there being insufficient talent, of course, but even if it’s true, after such a long wait this trivial detail — which only troubles the fans — isn’t going to get in the way of a financial windfall like this. + +And any time the league decides it could use talent, they can start doing away with most of the coaches they employ whose chief calling in life is to devise ways to stop offensive players and choke the very life out of the game that’s paying their salaries. + +Expansion will be happening, and soon. The only question is how many new cities will be involved.","0" +"Report: NHL expansion to Las Vegas 'a done deal'","The Commissioner of the National Hockey League, Gary Bettman, has repeatedly insisted that the league is not engaged in an active ""expansion process,"" but reports insisting otherwise continue to crop up. + +The latest is from veteran Vancouver Province columnist Tony Gallagher, who suggested on Tuesday that the NHL will expand to Las Vegas, Nev. sooner rather than later: + +Sources close to the situation have indicated Las Vegas is a done deal, the only thing to be determined being which owner will be entitled to proclaim that he brought the first major league sports franchise to Sin City. + +Gallagher also insists that there's fire behind all of the NHL-related smoke emanating out of Seattle, Wash. and reports that Vancouver-born billionaire Victor Coleman would be among the bidders interested in bringing a second NHL club to the Pacific Northwest. + +While rumors about Las Vegas expansion continue to swirl, to the consternation of players like Chicago Blackhawks nofunnick Jonathan Toews, NHL brass has been steadfast in their insistence that nothing is imminent for the league on the expansion front. + +""We're not ready to expand,"" Bettman said in early May, addressing rumors of potential NHL expansion in Las Vegas. ""We, as I repeatedly have said, have received expressions of interest from people who might want to own a franchise in Las Vegas - as we have from a number of other cities - but we're not involved in any expansion process."" + +[H/T Kukla's Korner]","0" +"Boko Haram Denies Ceasefire, Says Kidnapped Girls Are Now Married","In a video released late Friday night, the leader of Islamist militant group Boko Haram claimed Nigeria's kidnapped schoolgirls have all been converted to Islam and married off. + +In the video, obtained by Agence France-Presse, Boko Haram leader Abubakar Shekau also denied having agreed to a ceasefire with the Nigerian government. + +""Don't you know the over 200 Chibok schoolgirls have converted to Islam? They have now memorized two chapters of the Koran,"" he said. + +Laughing, he dashed hope that a deal might be reached in exchange for the girls' release, saying, ""The issue of the girls is long forgotten because I have long ago married them off."" + +[image via AP]","0" +"Continuing Violence Puts Boko Haram Ceasefire In Jeopardy","The reported ceasefire between the Nigerian government and Boko Haram, the terrorist group still holding more than 200 girls captive, does not appear to be working out, as violence over the weekend put the possibility of the girls' return on even more tenuous ground. + +As Reuters reports, while the Nigeria's Air Chief Marshal Alex Badeh announced the deal last Friday, it was not confirmed by Boko Haram. At least five attacks have occurred since the announcement. + +From CNN: + +In one attack, militants ambushed travelers in the Borno state village of Shaffa, residents of the area said, killing eight people and abducting others. + +Boko Haram gunmen also stormed the village of Waga in Adamawa state, abducting a number of residents, including women, residents there told CNN. + +Insurgents also occupied the town of Abadam, near Niger, after killing an unknown number of residents in their attack, residents said. + +According to Reuters, negotiations between the government and the insurgency are expected to continue in Chad on Monday, but family members of those kidnapped are skeptical of whether they will be productive. + +[Image via AP]","0" +"More than 200 kidnapped Nigerian girls to be released after deal reached with Boko Haram","More than 200 girls who were kidnapped in Nigeria will be released after the country’s government agreed an immediate cease-fire with their captors Boko Haram. + +Air Marshal Alex Badeh, who is chief of defence staff, ordered his troops to immediately comply with the agreement. + +‘A ceasefire agreement has been concluded between the Federal Government of Nigeria and the Jama’atu Ahlis Sunna Lidda’awati wal Jihad (Boko Haram),’ he said. + +MORE: Brave or shameless PR stunt? Nigerian singer offers virginity to Boko Haram in exchange for kidnapped schoolgirls + +The news comes as another official confirmed there had been direct negotiations this week in neighboring Chad about the release of the 219 girls who were taken in April. + +An initial 300 students were kidnapped from a boarding school in northeast Chibok town but a number of them had already managed to escape. + +Boko Haram had been demanding the release of detained extremists in exchange for the girls. + +MORE: Military force ‘an option’ to rescue girls kidnapped by Boko Haram in Nigeria","0" +"Nigeria claims deal with Boko Haram on ceasefire, kidnapped girls","Abuja (AFP) - Nigeria on Friday claimed to have reached a deal with Boko Haram militants on a ceasefire and the release of more than 200 kidnapped schoolgirls but doubts immediately surrounded the purported breakthrough. + +Related Stories + +Nigeria says reaches deal with Boko Haram over abducted girls Reuters +Nigeria, extremists agree to immediate cease-fire Associated Press +Why Nigeria Was Able to Beat Ebola, but Not Boko Haram The Atlantic +Six months after girls abducted, Nigerians protest near president's house Reuters +Nigeria And Boko Haram Reportedly Reach Cease-Fire Huffington Post +Chief of Defence Staff Air Marshal Alex Badeh told senior military officials from Nigeria and Cameroon meeting in Abuja that a ""ceasefire agreement"" had been concluded between the government and the insurgents. + +""I have accordingly directed the service chiefs to ensure immediate compliance with this development,"" he added. + +Badeh's announcement came after a senior aide to President Goodluck Jonathan, Hassan Tukur, told AFP that an agreement to end hostilities had been reached following talks, as well as for the release of 219 girls held captive since April. + +But a precedent of previous claims from the government and military about an end to the deadly five-year conflict and the fate of the missing teenagers left many observers urging caution. + +Jonathan is also expected to declare his bid for re-election in the coming weeks, with positive news about the hostages and the violence likely to give him a political boost. + +Multiple analysts cast doubt over the credibility of a man called Danladi Ahmadu, whom Tukur claimed represented Boko Haram at the two meetings in neighbouring Chad. + +""I have never heard of such a man (Ahmadu) and if Boko Haram wanted to declare a ceasefire it would come from the group's leader Abubakar Shekau,"" said Shehu Sani, a Boko Haram expert who has negotiated with the group before on behalf of the government. + +Ralph Bello-Fadile an advisor to Nigeria's National Security Advisor (NSA), told a conference on Monday that the NSA has been inundated with fraudsters claiming to represent Shekau. + +""Government wants to negotiate,"" he told a Chatham House event in Abuja, ""but so far nobody has come forward who speaks for Shekau."" + +View galleryBoko Haram +A screengrab taken on October 2, 2014 from a video released by Boko Haram and obtained by AFP shows … +- Chad talks - + +Tukur said he represented the government at two meetings with the Islamists in Chad, which were mediated by the country's President Idriss Deby. + +""Boko Haram issued the ceasefire as a result of the discussions we have been having with them,"" said Tukur, adding that Ahmadu made the announcement on Thursday evening. + +""They have agreed to release the Chibok girls,"" he continued, referring to the girls seized in northeast Nigeria on April 14, causing global outrage. + +Ndjamena refused to comment but security sources in the country said Chad, which Jonathan visited for talks with Deby early last month, had been involved in the discussions. + +The source also said a ceasefire agreement was reached as well as the release of 27 hostages, 10 of them Chinese nationals, who were kidnapped in northern Cameroon earlier this year. + +The release of the hostages last weekend was ""a first strong signal"" from Boko Haram to prove their good faith, the source added but did not mention the schoolgirls. + +- Discrepancies - + +Ahmadu gave an interview broadcast on Friday on the Hausa language service of Voice of America radio in which he claimed to be the group's ""chief security officer"" and in charge of publicity. + +He made no mention of an end to hostilities and was vague on details of the apparent talks, even claiming not to have met Shekau. + +He also referred to the jihadi group as Boko Haram, a name that means 'Western education is forbidden' which was imposed on the Islamist radicals by outsiders. The insurgents themselves never use the term. + +The group's known leaders have exclusively used the name Jama'atu Ahlis Sunna Lidda'awati wal-Jihad, which means ""People Committed to the Propagation of the Prophet's Teachings and Jihad"". + +He made no reference to the Chibok girls and did not list the creation of an Islamic state in Nigeria's mainly Muslim north -- the core, unwavering Boko Haram demand since the uprising began. + +Shekau has in a series of video messages since 2012 ruled out talks with the government and said northern Nigeria will never know peace until sharia (Islamic law) is strictly enforced. + +Envoys from Nigeria's presidency have made similar ceasefire claims in the past, notably Jonathan's Minister for Special Duties Taminu Turaki, who led a so-called amnesty commission in 2013 that was tasked with brokering peace. + +Turaki on several occasions maintained that he was negotiating with legitimate Boko Haram commanders, including Shekau's immediate deputies, and that a ceasefire was at hand. + +But nothing materialised from Turaki's protracted negotiations. Shekau said that he never sent delegates to any talks and attacks continued at a relentless pace.","0" +"Nigeria Claims Boko Haram Will Release the Kidnapped Schoolgirls","The Nigerian military says it has reached a cease-fire with the violent militant group Boko Haram and that the more than 200 young women kidnapped by the group earlier this year will be freed, the BBC reports. ""They've assured us they have the girls and they will release them,"" said an aide to President Goodluck Jonathan, who hopes to be reelected in early 2015. ""I am cautiously optimistic."" + +A spokesperson and self-proclaimed secretary general for Boko Haram confirmed to Voice of America Danladi Ahmadu that the girls will be released on Monday in Chad. Ahmadu said the kidnapping victims are ""in good condition and unharmed."" + +The Nigerian government would not reveal its concessions to the Islamist insurgents. ""We are inching closer to release of all groups in captivity, including the Chibok girls,"" said a government spokesperson. Fingers crossed. + +We are monitoring the news with huge expectations http://t.co/L01FrUFKwz #BringBackOurGirls","0" +"Nigeria Says Boko Haram Cease-Fire May Lead to Release of Kidnapped Girls","More than 200 schoolgirls were kidnapped in April, sparking the #BringBackOurGirls campaign + +A top military official in Nigeria was reported Friday to have announced a cease-fire between the government and the military group Boko Haram, igniting both skepticism and hopes that more than 200 schoolgirls who were kidnapped in April would be released. + +The truce was said to be announced by Air Marshall Alex Badeh, Nigeria’s chief of defense, the Associated Press reports. The release of the girls is still being negotiated, Maj. Gen. Chris Olukolade added, but the cease-fire would begin immediately and could take take several days to reach the groups of militants. + +“Already, the terrorists have announced a cease-fire in furtherance of their desire for peace. In this regard, the government of Nigeria has, in similar vein, declared a cease-fire,” said Mike Omeri, a government spokesman on Boko Haram, at a news conference. The AP adds that Omeri confirmed negotiations about the girls’ potential release were held throughout the week. + +Reports of the deal were met with hesitation by those who have followed the saga since the girls were abducted from their school in Chibok on April 14. There was neither an official statement quickly released by the government, nor an announcement made by the insurgent group, the New York Times reports. + +Boko Haram, which released a video in May that claimed responsibility for the girls’ abductions and vowed to “sell them on the market, by Allah,” has previously demanded the release of rebel prisoners in exchange for their freedom. But Nigerian President Goodluck Jonathan, who has faced intense global pressure to free the students, said that’s a trade he will not make. The Nigerian government has in the past misled the public about the girls’ status; its fight against Boko Haram has been fraught with challenges since the militant group rose up in 2009, from inefficiency and corruption in the military to lax local support in the northern communities that are threatened most. + +In August, the Wall Street Journal reported that American surveillance planes spotted groups that appeared to be the missing girls, suggesting that not all of them had been sold into marriage or slavery — as feared — and that some were perhaps being kept as a bargaining tactic.","0" +"Nigeria says ceasefire agreed with Boko Haram","Nigeria's official news agency says the government fighters from Boko Haram have agreed to an immediate ceasefire. + +It quoted the chief of defence staff, Air Marshal Alex Badeh, as ordering his troops to immediately comply with the agreement on Friday. + +The news came as another official confirmed there had been direct negotiations this week in neighbouring Chad about the release of more than 200 schoolgirls abducted six months ago. + +Al Jazeera's Haru Mutasa, reporting from Lagos, said details of the deal have yet to emerge. + +""Both sides have agreed there will be no more attacks, no more bombs and no more attacks on Boko Haram.The government will not attack any Boko Haram strongholds for the moment."" Mutasa said. + +""We do know Boko Haram wanted certain conditions met, for example they wanted their senior commanders released from government captivity."" Mutasa added. + +Abducted schoolgirls + +Sources told Al Jazeera that substantial progress had been reached in negotiations about the abducted girls but that no definite deal had been agreed. + + +Inside Story - Who are Nigeria's Boko Haram? +A senior adviser to Nigeria's President Goodluck Jonathan told Al Jazeera that the deal reached on Friday included the release of the girls, but that no date had been set and that the release was part of an ""ongoing process"". + +Doyin Okupe said the government had agreed to ""some concessions"" but did not give any details. + +Boko Haram has been demanding the release of detained fighters in exchange for the girls. + +The group attracted international condemnation with the April abduction of nearly 300 girls from a boarding school in northeast Chibok town. Dozens escaped but 219 remain missing. + +Nigeria's president has been criticised at home and abroad for his slow response to the abducted and for his inability to quell the violence by the group, seen as the biggest security threat to Africa's biggest economy. + +Jonathan is expected to announce he will run for a second term in office on Saturday. + +Boko Haram, whose name roughly translates as ""Western education is sinful"", has killed thousands of people in a five-year insurgency aimed at creating an Islamic caliphate in the country's northeast.","0" +"Nigeria and Boko Haram 'agree ceasefire and girls' release'","Nigeria's military says it has agreed a ceasefire with Islamist militants Boko Haram - and that the schoolgirls the group has abducted will be released. + +Nigeria's chief of defence staff, Alex Badeh, announced the truce. Boko Haram has not made a public statement. + +The group has been fighting an insurgency since 2009, with some 2,000 civilians reportedly killed this year. + +Boko Haram sparked global outrage six months ago by abducting more than 200 schoolgirls. + +The girls were seized in the north-eastern town of Chibok in Borno state, and their continued captivity has led to criticism of the Nigerian government's efforts to secure their release. + +Members of the Bring Back Our Girls campaign said in a tweet on Friday: ""We are monitoring the news with huge expectations."" + +'Cautiously optimistic' + +Air Chief Marshal Badeh revealed the truce at the close of a three-day security meeting between Nigeria and Cameroon. He said Nigerian soldiers would comply with the agreement. + +Nigerian presidential aide Hassan Tukur told BBC Focus on Africa that the agreement was sealed after a month of negotiations, mediated by Chad. + +As part of the talks, a government delegation twice met representatives of the Islamist group. + +Mr Tukur said Boko Haram had announced a unilateral ceasefire on Thursday and the government had responded. + +""They've assured us they have the girls and they will release them,"" he said. + +""I am cautiously optimistic."" + +He said arrangements for their release would be finalised at another meeting next week in Chad's capital, Ndjamena. + +The negotiations are said to have the blessing of Boko Haram leader Abubakar Shekau, reports the BBC's Chris Ewokor in Abuja. + +Speaking to the BBC, Nigerian government spokesman Mike Omeri said Boko Haram would not be given territory under the ceasefire agreement - and that the government would not reveal what concessions it would make. + +""We are inching closer to release of all groups in captivity, including the Chibok girls,"" he said. + +Analysis: Will Ross, BBC News, Lagos + +Nigerian officials had not given any indication that negotiations with Boko Haram were taking place. Even though there had been rumours of talks in neighbouring Chad, this is a very surprising development. + +Many Nigerians are extremely sceptical about the announcement especially as there has been no definitive word from the jihadists. + +The military has in the past released statements about the conflict in north-east Nigeria that have turned out to be completely at odds with the situation on the ground. + +So many here will only celebrate when the violence stops and the hostages are free. + +In May 2013, President Goodluck Jonathan imposed a state of emergency in the northern states of Borno, Yobe and Adamawa, vowing to crush the Islamist insurgency. + +But Boko Haram increased its attacks this year. + +The group promotes a version of Islam which makes it ""haram"", or forbidden, for Muslims to take part in any political or social activity associated with Western society. + +It frequently attacks schools and colleges, which it sees as a symbol of Western culture. + +Who are Boko Haram? + +Who are Boko Haram? + +Profile: Boko Haram leader Abubakar Shekau + +Human Rights Watch has reported that 2,053 civilian were killed in the first half of the year, while Amnesty International estimated that 4,000 people were killed in violence - including Nigerian military operations - in the first seven months of 2014. + +Boko Haram is seeking to establish an Islamist state in Nigeria, but its fighters often cross the long and porous border with Cameroon. + +Eight Cameroon soldiers and more than 100 Boko Haram militants were killed in fighting in the far north of Cameroon on Friday, Reuters quoted the country's defence ministry as saying. + +In July, Cameroon, Nigeria, Chad and Niger agreed to form a 2,800-strong regional force to tackle Boko Haram militants.","0" +"Nigeria Boko Haram blamed for raids despite truce claim","Suspected militant Islamists have shot and slaughtered people in three villages in north-east Nigeria, despite government claims that it had agreed a truce with them, residents say. + +Boko Haram fighters raided two villages on Saturday, and raised their flag in a third, residents said. + +The government said it would continue negotiating with Boko Haram, despite the alleged breach of the truce. + +It hopes the group will this week free more than 200 girls it seized in April. + +Boko Haram has not commented on the announcement made on Friday that a truce had been agreed, and that the militants would release the schoolgirls abducted from the remote north-eastern town of Chibok. + +'Promise honoured' + +Boko Haram is reportedly represented in the talks, taking place in neighbouring Chad, by Danladi Ahmadu. + +However, Mr Ahmadu was ""bogus"" and an ""imposter"", said Ahmad Salkida, a Nigerian journalist with good contacts in Boko Haram. + +The abduction of the girls sparked a global campaign to pressure the government to secure their release. + +Government negotiator Hassan Tukur said Boko Haram had ""honoured its first promise"" by releasing 27 Cameroonian and Chinese nationals on 11 October, after capturing them in separate raids in May and July, Nigeria's privately owned This Day newspaper reports. + +""Since it delivered on its promise to Cameroon, we expect Boko Haram to deliver on the release of the Chibok girls and the cessation of hostilities in north-eastern Nigeria,"" he said. + +Chad's President Idris Deby is mediating between the two sides, Nigeria's government says. + +'Friend killed' + +However, Saturday's attacks have caused many Nigerians to doubt whether the government has really negotiated a truce with Boko Haram, especially as no statement has been issued by its leader Abubakar Shekau, says BBC Nigeria analyst Bilkisu Babangida. + +Who are Boko Haram? + +Who are Boko Haram? + +Profile: Boko Haram leader Abubakar Shekau + +Will 'truce' with Boko Haram free Chibok girls? + +Boko Haram fighters burnt homes and killed many people during raids on the villages of Grata and Pina in Adamawa state, a resident told BBC Hausa. + +As they marched from Grata to Pina, they also slit the throats of villagers whom they came across, he added. + +In a separate attack, the militants raided Abadam village in neighbouring Borno state, and raised their flag over the village, a resident who fled the area told the BBC. + +His friend was among those who had been killed by the militants, the resident said. + +Many people had fled across the border to Niger, he added. + +Mr Tukur said the government was trying to ""verify where the attacks are coming from"". + +""As you know, it is difficult to have a ceasefire in an organisation that has many members and cells/units,"" he is quoted by This Day as saying. + +In May 2013, President Goodluck Jonathan imposed a state of emergency in the northern states of Borno, Yobe and Adamawa, vowing to crush the Islamist insurgency. + +But Boko Haram has increased its attacks this year. + +The group promotes a version of Islam which makes it ""haram"", or forbidden, for Muslims to take part in any political or social activity associated with Western society. + +It frequently attacks schools and colleges, which it sees as a symbol of Western culture.","0" +"Nigerian Claims of Boko Haram Cease-Fire Hurt by Violence","Persistent violence in northeast Nigeria is undermining the government’s claims to have brokered a cease-fire with Islamist militant group Boko Haram. + +A lack of detail about the agreement the Nigerian military announced on Oct. 17 and complaints of exclusion from the process by community leaders in the worst-hit areas are fueling skepticism about prospects of an end to the five-year rebellion. + +“If there is any genuine cease-fire, people from the three affected states should have been invited,” Bulama Mali Gubio, spokesman for the Borno Elders Forum, said yesterday from Maiduguri, the state capital. “But for the Federal Government just to come out and say soldiers should lay down their arms, there is a cease-fire -- it means they are giving us to Boko Haram.” + +Borno, Yobe and Adamawa, states in the northeast of Nigeria, about 1,600 kilometers (1,000 miles) from the oil-producing southern coast and commercial capital Lagos, have borne the brunt of the Boko Haram insurgency. + +Their populations have experienced near daily gun and bomb attacks on villages, schools, mosques and markets, and have been living under emergency rule since May 2013. President Goodluck Jonathan said last month that the rebels had killed more than 13,000 people since 2009. + +‘Very Sketchy’ + +The agreement as announced by Chief of Defence Staff Alex Badeh “is very sketchy because nothing is spelled out,” Gubio from the Borno Elders Forum said. + +As part of the cease-fire announcement, Nigerian authorities said the Islamist militant group had indicated it’s willing to discuss the release of more than 200 schoolgirls it abducted from the town of Chibok in April. + +“We are aware of reports that the Nigerian authorities have agreed a truce with Boko Haram, and are making urgent enquiries to establish the facts,” the British High Commission in the capital, Abuja, said in an e-mailed response to questions today. “It is not yet clear what impact this might have on the missing Chibok girls.” + +There was more fighting in Borno yesterday, as soldiers in the town of Damboa repelled an insurgent attack, leaving many dead, according to Hassan Ibrahim, leader of a pro-government vigilante group in the area. + +Village Raids + +“Boko Haram has yet to confirm whether it had entered into a cease-fire, and the emerging accounts of village raids and clashes with the military have raised more doubts on the credibility of the cease-fire claim,” Poole, U.K.-based security consultancy Drum Cussac said in e-mailed comments today. “There is speculation that the Federal Government may have negotiated a truce with only one faction of the sect, as violence has continued unabated in the northeast.” + +The media attention the Chibok kidnap drew brought international scrutiny and criticism of Jonathan’s track record on national security. The 56-year-old president is widely expected to stand for re-election in a vote set for Feb. 14. + +To contact the reporters on this story: Daniel Magnowski in Abuja at dmagnowski@bloomberg.net; Mustapha Muhammad in Kano at mmuhammad10@bloomberg.net + +To contact the editors responsible for this story: Nasreen Seria at nseria@bloomberg.net John Viljoen, Karl Maier","0" +"Boko Haram Could Release Kidnapped Girls, Nigerian Officials Say","Protesters march in support of the girls kidnapped by members of Boko Haram in front of the Nigerian Embassy in Washington on May 6. + +The Nigerian government said Friday that it reached a cease-fire agreement with Boko Haram, the jihadist organization that kidnapped 219 girls in April, according to the AFP. + +“A ceasefire agreement has been concluded between the Federal Government of Nigeria and Boko Haram,” said Air Marshal Alex Badeh, Nigeria’s top military officer. + +A second Nigerian official told AFP that the ceasefire would include provisions for the release of the kidnapped girls. + +“They have agreed to release the Chibok girls,” said Hassan Tukur, a secretary to President Goodluck Jonathan who served as the government’s representative in talks with Boko Haram. + +But some experts questioned the credibility of the officials’ claims, in part because news of the agreement comes as President Jonathan prepares to launch a re-election bid. Announcing the return of the girls, whose abduction inspired the hashtag #BringBackOurGirls, could help Jonathan’s electoral aspirations — even if the claim turns out not to be entirely true. + +The Nigerian government has lied about the girls several times in the past. The government even once claimed to have rescued the girls. + +In particular, experts questioned the credibility of Danladi Ahmadu, who the government said was Boko Haram’s representative in the talks. + +“I have never heard of Ahmadu, and if Boko Haram wanted to declare a ceasefire it would come from the group’s leader Abubakar Shekau,” Shehu Sani, a Boko Haram expert who has negotiated with the group before on behalf of the government, told AFP. + +The Nigerian military has been fighting Boko Haram since 2009. Multiple attempts at reaching a cease-fire have proven unsuccessful.","0" +"Nigeria, Boko Haram reach ceasefire deal, kidnapped girls to go free, official says","(CNN) -- Nigeria has reached a ceasefire agreement with the Islamist terror group Boko Haram that includes the release of more than 200 kidnapped schoolgirls, Nigerian officials said Friday. + +The deal came Thursday night after a month of negotiations with representatives of the group, said Hassan Tukur, principal secretary to President Goodluck Jonathan. + +""We have agreed on the release of the Chibok schoolgirls, and we expect to conclude on that at our next meeting with the group's representative next week in Chad,"" Tukur said. + +Officials provided few details about the release. + +Doyin Okupe, a government spokesman, did not specify when the girls would be freed. He said not all would be let go at once, but a ""significant number"" would be released soon. + +""A batch of them will be released shortly, and this will be followed by further actions from Boko Haram,"" he said. ""It is a process. ... It is not a question of hours and days."" + +The Nigerian government consented to some demands by Boko Haram, but Okupe declined to provide details. + +The government, he said, ""is looking beyond the girls. We want to end the insurgency in this country."" + +""On the war front,"" he added, ""we can say there is peace now."" + +The agreement was first reported by Agence France-Presse. + +What is Boko Haram? + +The terrorist group abducted an estimated 276 girls in April from a boarding school in Chibok in northeastern Nigeria. Dozens escaped, but more than 200 are still missing. + +Nigerian officials met with Boko Haram in Chad twice during talks mediated by Chadian President Idriss Deby, according to Tukur. + +""The group has shown willingness to abide by the agreement which ‎it demonstrated with the release of the Chinese and Cameroonian hostages few days ago,"" Tukur said. + +In cross-border attacks by Boko Haram this week, eight Cameroonian soldiers and 107 group members were killed in heavy fighting that lasted two days in northern Cameroon, the country's defense ministry said Friday, according to state broadcaster CRTV. + +The militants led an incursion near Limani, close to the border with Nigeria, on Wednesday, equipped with heavy weapons, including at least one tank, CRTV said, citing information from the defense ministry. + +The fighting lasted two hours and resumed on Thursday, when Cameroonian soldiers forced the militants back across the border into Nigeria. Seven Cameroonian soldiers were injured. A Boko Haram tank and other vehicles were destroyed and weapons and ammunition were seized by Cameroonian forces, according to CRTV. + +A source involved in talks with the militants told CNN last month that Nigerian government officials and the International Committee of the Red Cross had discussions with Boko Haram about swapping imprisoned members of the group for the more than 200 schoolgirls. It is unclear, however, whether the deal includes a prisoner swap. + +Where are the missing girls? + +The name ""Boko Haram"" translates to ""Western education is sin"" in the local Hausa language. The militant group is trying to impose strict Sharia law across Nigeria, the most populous country in Africa. + +In recent years, its attacks have intensified in an apparent show of defiance amid the nation's military onslaught. Its ambitions appear to have expanded to the destruction of the Nigerian government. + +The militant group has bombed schools, churches and mosques; kidnapped women and children; and assassinated politicians and religious leaders alike. + +The group has said its aim is to impose a stricter enforcement of Sharia law across Nigeria, which is split between a majority Muslim north and a mostly Christian south. + +Boko Haram was founded 12 years ago by Mohammed Yusuf, a charismatic cleric who called for a pure Islamic state in Nigeria. Police killed him in 2009 in an incident captured on video and posted to the Internet. + +CNN's Robyn Turner contributed to this report.","0" +"Despite ceasefire announcement, new Boko Haram attacks reported","(CNN) -- Despite government claims of a ceasefire, gunmen believed to be Boko Haram fighters attacked two villages and a town near the border with Niger, killing at least 8 and kidnapping others, residents told CNN Saturday. + +Boko Haram has not yet responded to the government's announcement Thursday of a ceasefire, which an official said heralded peace in the country after some five years of conflict with the Islamic extremist group. + +In one attack, militants ambushed travelers in the Borno state village of Shaffa, residents of the area said, killing eight people and abducting others. + +Boko Haram gunmen also stormed the village of Waga in Adamawa state, abducting a number of residents, including women, residents there told CNN. + +Insurgents also occupied the town of Abadam, near Niger, after killing an unknown number of residents in their attack, residents said. + +Nigerian officials said Friday that the government had reached a ceasefire agreement with Boko Haram, which has been waging an insurgency in the country's north since 2009. + +The deal, the government said, includes the release of more than 200 kidnapped girls whose abduction from their boarding school shocked the world in April. + +The deal, first reported by Agence France-Presse, came Thursday night after a month of negotiations with representatives of the group, said Hassan Tukur, principal secretary to President Goodluck Jonathan. + +Nigerian officials met with Boko Haram in Chad twice during talks mediated by Chadian President Idriss Deby, according to Tukur. + +""We have agreed on the release of the Chibok schoolgirls, and we expect to conclude on that at our next meeting with the group's representative next week in Chad,"" Tukur said. + +Doyin Okupe, a government spokesman, said the ceasefire deal was meant not only to free the girls but also to end the insurgency. + +""On the war front, we can say there is peace now,"" he said Friday. + +What is Boko Haram? + +A source involved in talks with the militants told CNN last month that Nigerian government officials and the International Committee of the Red Cross had discussions with Boko Haram about swapping imprisoned members of the group for the more than 200 schoolgirls. It is unclear, however, whether the deal includes a prisoner swap. + +The name ""Boko Haram"" translates to ""Western education is sin"" in the local Hausa language. The militant group is trying to impose strict Sharia law across Nigeria, which is split between a majority Muslim north and a mostly Christian south. + +As part of its insurgency, the militant group has bombed schools, churches and mosques; kidnapped women and children; and assassinated politicians and religious leaders alike. + +Where are the missing girls? + +CNN's Ray Sanchez contributed to this report.","0" +"Boko Haram leader denies ceasefire deal, says 200 abducted girls married off ","(CNN) -- Boko Haram laughed off Nigeria's announcement of a ceasefire agreement, saying there is no such deal and schoolgirls abducted in spring have been converted to Islam and married off. + +Nigerian officials announced two weeks ago that they had struck a deal with the Islamist terror group. + +The deal, the government said, included the release of more than 200 girls whose kidnapping in April at a boarding school in the nation's north stunned the world. + +In a video released Saturday, the Islamist group's notorious leader fired off a series of denials. + +""Don't you know the over 200 Chibok schoolgirls have converted to Islam?"" Abubakar Shekau said. ""They have now memorized two chapters of the Quran."" + +Shekau slammed reports of their planned release. + +""We married them off. They are in their marital homes,"" he said, chuckling. + +The group's leader also denied knowing the negotiator with whom the government claimed it worked out a deal, saying he does not represent Boko Haram. + +""We will not spare him and will slaughter him if we get him,"" he said of the negotiator. + +It wasn't clear when the video was made. + +Mike Omeri, coordinator of Nigeria's National Information Centre, told CNN on Saturday that all these claims contradict those made in conversations in which the Nigerian government has been involved. + +Omeri said Nigeria's government will do everything possible to verify the claims made in the video. + +Nigerian officials met with Boko Haram in Chad twice during talks mediated by Chadian President Idriss Deby, according to the aide. + +The ceasefire deal announced October 17 followed a month of negotiations with representatives of the group, said Hassan Tukur, an aide to Nigerian President Goodluck Jonathan. + +After the deal was announced, the aide said final negotiations on the girls' release would be completed at a meeting a week later in Chad. + +That day passed without any signs of the girls. + +Boko Haram a growing challenge + +In the video, Shekau talked not of peace but of more violence -- promising more ""war, striking and killing with gun."" + +This strategy appears to be playing out in parts of Nigeria, where Boko Haram fighters have continued deadly attacks on villages despite government claims of a ceasefire. More people have been abducted and scores killed in recent weeks, including one attack a day after the ceasefire that left eight dead. + +Days later, members of the Islamist terror group abducted at least 60 young women and girls from Christian villages in northeast Nigeria, residents said Thursday. + +Heavily armed fighters left 1,500 naira, or about $9, and kola nuts as a bride price for each of the women abducted, residents said. + +For its part, the Nigerian government isn't backing down. + +Rather, it is stepping up its military campaign against militants and criminals in some parts of the West African nation, Nigeria's defense ministry said on Saturday. + +The military claimed its airstrikes and ground operations have repelled attacks against civilians in Adamawa and Borno, two of the states in northeastern Nigeria that have been strongholds and frequent targets for Boko Haram. + +Officials are ""studying"" the latest video, even as the military continues to recognize the talks aimed at assuring the release of the kidnapped schoolgirls, the ministry said. + +Boko Haram, whose name translates to ""Western education is sin"" in the Hausa language, is trying to impose strict Sharia law across Nigeria, which is split between a majority Muslim north and a mostly Christian south. Like ISIS, it has ambitions for a caliphate, or religious state. + +The group's attacks have intensified in recent years in an apparent show of defiance for the nation's military onslaught. Its ambitions appear to have expanded to the destruction of the government. + +As part of its insurgency, it has bombed schools, churches and mosques, kidnapped women and children and assassinated politicians and religious leaders alike. + +CNN's Isha Sesay, Lillian Leposo, Christabelle Fombu, Greg Botelho and Nana Karikari-apau contributed to this report.","0" +"Boko Haram ceasefire ignored as violence flares in Borno state","A ceasefire agreement between Boko Haram and the Nigerian government was expected to lead to the liberation of more than 200 school girls kidnapped by the militants six months ago. That was not the case. + +At least 25 suspected Boko Haram militants were killed as they battled with Nigerian soldiers on Monday, following a ceasefire between the Nigerian government and Islamists in the lawless northern region. +An army officer, speaking anonymously, said the militants tried to enter the town of Damboa late on Sunday through Alagarno, a Boko Haram hideout, but that soldiers had fought them off. +""Our men gunned down 25 of the insurgents because they would have entered Damboa and unleashed more terror on the town that is just picking up from its ruins,"" the officer said. +Damboa, near the border with Cameroon, has been the site of fierce fighting between the militants and Nigerian forces for months. The insurgents sacked the town in July but were driven out by a military counter-offensive. +Ceasefire 'incomplete' +The Borno Elders Forum, made up of retired Nigerian civilian and military officials from the Borno state, said attacks in recent days indicated that not all Boko Haram fighters were aware of the deal. +""I don't think they would continue attacking innocent people if they are aware and they are in agreement that there is a ceasefire,"" said spokesman Bulama Mali Gubio. +The Borno Elders Forum, which last month warned that Boko Haram was preparing preparing to take over key sites in Borno, suggested the government had not negotiated with the entire group. +""If the federal government does not know who the real Boko Haram is, I think they should come here to find out from us,"" Gubio said. +""The real Boko Haram who are killing us, who are burning our towns and villages, are not the Boko Haram that a peace deal was reached with."" +The government claimed a deal was reached after talks in Chad, which included provisions for the release of more than 200 schoolgirls kidnapped from the Borno town of Chibok in April. +glb/sb (Reuters, AFP)","0" +"Nigeria Says It Struck A Cease-Fire With Boko Haram, But Are They Talking To The Right Guy?","Nigeria says it has struck a cease-fire deal with Boko Haram, raising hopes that over 200 schoolgirls who were kidnapped by the militant group will be released. But mystery continues to surround the identity of the interlocutor on the other side of the negotiations. + +Nigerian officials said the deal was reached in Chad on Friday in talks with a Saudi Arabia-based Boko Haram representative named Danladi Ahmadu. + +The name took many by surprise, including people who have been involved in previous negotiations with Boko Haram. “I have failed to find anyone who has ever heard of him,” BBC’s Nigeria correspondent wrote. “We've tried verifying the authenticity of the person from sources traditionally close to Boko Haram militants and we are getting negative feedback,” the editors of Nigerian news site Sahara Reporters told The WorldPost by email. + +Ahmad Salkida, a Nigerian journalist who is considered close to Boko Haram's leaders, said he does not believe Ahmadu is part of the group’s leadership or that he speaks for the group. “I challenge Danladi Ahmadu to an open debate if he has d [sic] interest of Nigeria at heart. Who is he?"" Salkida wrote on Twitter. + +But Mike Omeri, the Nigerian government's spokesperson on the Boko Haram insurgency, told The WorldPost Saturday that the government is confident it has been negotiating with the right guy. + +“These talks did not just happen one sunny morning ... They approached the president of Chad, and if he wasn’t confident [of Ahmadu’s identity] he wouldn’t have connected him with the president of Nigeria,” Omeri said. ""The fact that this contact comes from Nigeria’s neighbor gives us confidence."" + +Chad has confirmed it is acting as a mediator in the talks to free the girls, who were kidnapped in the Nigerian village of Chibok in April. Since Nigerian President Goodluck Jonathan visited Chad last month, rumors have grown that Nigeria's government was quietly negotiating the girls' release via its neighbor. It was not immediately clear how long the talks have been taking place. + +Boko Haram's leadership has not commented on the cease-fire. Meanwhile, Ahmadu himself has purportedly made at least two statements in recent days. On Friday, he gave an interview with Voice of America’s Hausa-language service in which he didn’t mention the kidnapped schoolgirls and was vague on the details of the cease-fire, Agence France-Presse reported. The news agency also noted that Ahmadu referred to the militant group as Boko Haram, a name used by outsiders but not by the insurgents themselves. + +On Saturday, Sahara Reporters said its correspondent in the northeastern Nigerian city of Maiduguri had obtained a CD recording of another statement by Ahamdu. This time, he was more precise. + +“On the girls that we took from Chibok, all that we want before we free the girls is to get justice from the Nigerian state because there are many of our members that their business premises were destroyed, some killed and others in detention and many other oppression,” Ahmadu said, according to a translation from Hausa by Sahara Reporters. The news site’s editors said they remain skeptical about his identity. + +As part of the deal, Omeri said, the talks taking place in Chad this week will address the release of the schoolgirls. + +Omeri added that the militants are motivated by a wish to reintegrate into society. “They are working towards peace in order to have a chance for them to return to normal things -- for example, many have businesses, "" he said. + +Asked whether Nigeria would consider releasing captured Boko Haram militants in exchange for the girls, Omeri said “every asset"" will be directed towards the girls' release. ""Everything possible is being done until the day they are freed,"" he said. + +""Boko Haram want peace, they are ready for it and intend to have it implemented,"" he added. + +After the cease-fire was announced, suspected Boko Haram militants continued to attack communities in northeast Nigeria, leaving several dozen dead over the weekend. + +But Omeri insisted that the violence would not deter the negotiations. He suggested that militants in remote areas may not have heard about the cease-fire, or that the attacks could have been perpetrated by criminal opportunists, rather than Boko Haram members. + +Boko Haram is ""deeply fractured,"" according to the risk consultancy Stratfor, quoted in Reuters Sunday. Nigeria's government had a ""difficult time identifying a Boko Haram representative who could make compromises and guarantee the entire group will observe them,"" Stratfor said. + +""It is quite possible that Abuja has reached an agreement with a legitimate representative of a specific cell ... that holds the kidnapped schoolgirls captive,"" the group added. + +In the kidnapped girls’ hometown, the community hardly dared to hope that the girls might be finally returned. ""We don't know how true it is until we prove it,"" said Bana Lawan, chairman of Chibok Local Government Area, told The Associated Press.","0" +"Boko Haram Cease-Fire: Abducted Nigerian Schoolgirls To Be Released, Officials Say","Boko Haram has reportedly agreed to a cease-fire with the Nigerian military as well as the release of hundreds of schoolgirls who were abducted by the terrorist group earlier this year, officials said Friday. The jihadist militia has not yet made a public statement about the decision, which could confirm the arrangement, according to the BBC. + +""They've assured us they have the girls and they will release them,"" Nigerian presidential aide Hassan Tukur told the BBC. ""I am cautiously optimistic."" The announcement of the release and cease-fire comes after a month of negotiations between the Nigerian government and Boko Haram, which has killed more than 2,000 civilians in 2014 alone. + +The little-known al Qaeda offshoot gained national attention in April when they abducted some 300 schoolgirls from a school in Chibok, northern Nigeria, to be sold as slaves. The abduction sparked international outrage and the social media campaign #BringBackOurGirls that enlisted the likes of U.S. first lady Michelle Obama and countless celebrities. Human rights organizations are watching the ongoing deals closely for any developments. + +We are monitoring the news with huge expectations http://t.co/L01FrUFKwz #BringBackOurGirls + +— #BringBackOurGirls (@BBOG_Nigeria) October 17, 2014 + +In August, Boko Haram declared an “Islamic state” in northeastern Nigeria, the Washington Post reported. Authorities believe the group is hiding the girls somewhere in that area. Jennifer Cook, the director of the Africa Program at the Center for Strategic and International Studies, said the longer the girls stay in captivity, the harder it would be to bring them home. + +“With hostage situations with this many people, to bring one set back without endangering another set is very difficult,” Cooke told Time. “In some cases, there’s a pretty good idea of where they are, but extricating them from a group of armed criminals who have so little respect for life is a difficult negotiation process. And the longer they’re there, the greater likelihood they become dispersed, and the more difficult they are to track down.” + +It's unclear how the girls have been treated during their captivity, raising questions about their health. “These girls are being held under absolutely horrific circumstances, subjected to sexual violence and rape, forced into servitude,” Cooke said. “There are reports that some have become pregnant.”","0" +"Kidnapped Nigerian schoolgirls: Government claims ceasefire deal with Boko Haram that will bring missing girls home","Relatives of the more than 200 girls taken by militant group Boko Haram in Chibok, northern Nigeria expressed hope yesterday that a ceasefire deal said to have been signed between the Nigerian government and the Islamist group will end their nightmare and bring their families home. + +However, restraint appeared to be the order of the day, with the details of any deal still hazy and no word yet from Boko Haram's leader, Abubakar Shekau. Wild celebrations might have been expected at the apparent end of an ordeal that has lasted more than six months but they were not in evidence, with many cautious about what might happen. But officials have made clear that the return of the girls is part of the deal. + +""We will know the negotiations were successful when we see the girls physically. And then we will know it is true. And then we will celebrate,"" said Bana Lawan, chairman of Chibok's local government, told the Associated Press. + +Another resident, community leader Pogu Bitrus, told the news agency that ""people rejoiced, but with caution"". + +Some reports on Friday night suggested the girls, taken from a school in Chibok back in April, could be released as early as tomorrow in neighbouring Chad – but Reuters reported yesterday, citing two senior government sources, that the Nigerian government would be looking to secure the release of the girls by Tuesday. + +Yesterday Mike Omeri, a government spokesman, said the authorities are ""inching closer to the release of the Chibok girls"". He later told Reuters that ""discussions will continue in Chad next week, and on the basis of those discussions we'll have more details"" on the girls' release. + +The second source quoted by Reuters said that there might need to be further meetings in Nigeria or the Chadian capital N'Djamena to iron out the rest of the details for the deal. ""We have confidence in those we are negotiating with, but we are still doing it with considerable caution. Boko Haram has grown into such an amorphous entity that any splinter group could... disown the deal,"" he reportedly said. + +During its 12-year existence – the past five have seen the group trying to create an Islamic state in the north of the country – Boko Haram has been split. Doubts have been raised by some analysts about Danladi Ahmadu, the self-proclaimed ""secretary general"" of Boko Haram who was named by President Goodluck Jonathan's principal secretary, Hassan Tukur, as the Boko Haram's representative in the talks. Ahmadu gave an interview to Voice of America in which he confirmed the ceasefire that was officially announced by Air Chief Marshal Alex Badeh, the head of Nigeria's military forces, on Friday. + +In the interview Ahmadu appeared to say that he had not even met Abubakar Shekau. + +This is not the first time a ceasefire has been called, hence the trepidation on the part of families in Chibok. In July 2013, when a government minister announced an agreement, Shekau quickly denied it using a video message – his preferred means of communication. He said that whoever the government negotiated with did not speak for him, and that he would never talk to infidels. + +Leaders of the #BringBackOurGirls campaign, which gained the backing of politicians and public figures worldwide – including the US First Lady, Michelle Obama – summed up the mood. + +""We are really cautious because there have been many times that such optimism has been expressed but did not materialise,"" Obi Ezekwesili, a former education minister said in a TV interview on Saturday. ""But all the same, we are hopeful,"" she said, according to the AFP news agency. + +Quoted by the Leadership newspaper yesterday, the headteacher of the school from where the girls were taken, Asabe Kwambura, said she would be the ""happiest person in the world"" if the girls were to return + +President Jonathan has faced criticism over his response to the abduction of the girls – and Boko Haram's continuing insurgency. He was set to attend a rally in Abuja yesterday where he was expected to officially announce his candidacy for presidential elections next year, leaving some to question the timing of the ceasefire announcement. + +Publically, the President has also always said he would not release Boko Haram prisoners, a central demand of the group – but there has been speculation about such a deal. + +Other than the girls, some of whom have escaped back to their families in the months since they were taken, many in the northern provinces where Boko Haram have killed thousands during their insurgency will be hoping the ceasefire holds. However, yesterday there were reports that suspected Boko Haram militants had killed several people in a number of attacks on Nigerian villages that occurred after the ceasefire announcement, security sources and witnesses told Reuters.","0" +"Nigeria announces truce with Boko Haram; fate of schoolgirls unclear","Nigerian officials Friday announced they had agreed to a cease-fire with Boko Haram, but their statements left confusion over the fate of 219 schoolgirls kidnapped by the militant group in April. + +Defense chief of staff Alex Badeh announced the truce, saying all Nigerian military units had been instructed to abide by the accord. + +Women attend a demonstration in Lagos, Nigeria, calling on the government to rescue schoolgirls kidnapped by the radical Islamist group Boko Haram. +Hassan Tukur, an aide to Nigerian President Goodluck Jonathan, said there was also an agreement for the release of the captive girls following talks with Boko Haram representatives mediated by officials from Chad, new agencies reported. + +But Nigerian Defense Ministry spokesman Maj. Gen. Chris Olukolade said the schoolgirls' release was still under negotiation, the Associated Press reported. + +Nigerian officials haven’t commented on what was being offered to Boko Haram in return for the girls’ freedom. The group has previously demanded the release of prisoners as a condition for freeing the hostages. + +Nigeria’s military announced months ago it knew the location of the girls but said it would not launch a military operation to recover them because of the risk of casualties. + +A government spokesman, Mike Omeri, told a new conference Friday that Boko Haram representatives said during negotiations that the girls were in good health. + +Analysts were cautious about the news, with Nigerian officials reporting countless false dawns in its long confrontation with the militant group -- and with Nigeria facing presidential and parliamentary elections in February. Jonathan is expected to announce in coming weeks that he will run for a second term. + +There have been several efforts in recent years to negotiate peace with Boko Haram, which has battled the army for control of northern Nigeria and sought to impose a strict form of Islam in the region. None of the attempts has come to anything. + +Jonathan, desperately in need of some good news, has faced harsh criticism over his slow response to the girls’ abduction. His supporters accuse the #BringBackOurGirls campaign of being opposition stooges, using the girls’ fate for political mileage. + +Hundreds more women and girls have been abducted by Boko Haram in recent years – and dozens of schoolboys and teachers were killed by the group that opposes secular education and other aspects of Western culture. But the mass kidnapping in April and the BringBackOurGirls hashtag coined by Nigerian activists attracted global attention to the schoolgirls’ plight. + +The schoolgirls had gathered at a lightly guarded boarding school on the outskirts of the town of Chibok for their final exams when the attack happened. Gunmen loaded 276 girls into trucks and drove away. Parents and local officials accused Nigeria’s military of failing to pursue and recover the girls. + +According to Nigerian officials, 57 escaped and 219 remain in custody. + +Boko Haram leader Abubakar Shekau later released a video describing the girls as slaves and threatening to “sell them in the market.” A video of the girls reciting the Koran and dressed in Islamic clothing was also released. + +Nigeria, a country of 170 million, is roughly divided between the north, which is predominantly Muslim, and the mostly Christian south. + +Boko Haram emerged over a decade ago in response to Nigeria’s corrupt ruling class and opposes what it sees as the taint of Western influences such as taxation, democracy and automatic teller machines. It has become increasingly fragmented in recent years, with some factions opposed to the group’s violent attacks on Muslims. + +Boko Haram’s assaults initially focused on police stations and military posts. In recent years, the group has stepped up its violence, killing thousands of people in attacks on villages, churches, schools, markets, open-air video entertainment venues, bus stations and other crowded public places.","0" +"Nigeria's missing girls 'to be released by Boko Haram', government aide claims","Nigeria’s government and Boko Haram have agreed a ceasefire that brings closer the release of more than 200 schoolgirls kidnapped in the north of the country more than six months ago. + +Secret meetings held between the authorities in Abuja, the Nigerian capital, and representatives of the al-Qaeda-linked militia have led to an temporary agreement to lay down arms. + +Part of the deal includes “the need to rescue all the captives of the terrorists, including the students of Government Girls’ Secondary School, Chibok”, said Mike Omeri, anti-terrorism spokesman of the president’s national information centre. + +There would also be an immediate ceasefire, with Boko Haram apparently saying it would suspend its bombing and kidnap campaign, and the Nigerian army agreeing not to target suspected militant camps. + +“From the discussions, [Boko Haram’s representatives] indicated their desire for, and willingness to discuss and resolve all associated issues,” Mr Omeri said. “They also assured that the school girls and all other people in their captivity are all alive and well.” + +The announcement came days after protesters marched in Abuja to mark the six-month anniversary of the girl’s abduction. Close to 300 teenage girls were kidnapped by armed gunmen as they were driven back to their school in coaches after an excursion. + +Some managed to escape, but an estimated 219 are still being held captive, reportedly in Nigeria’s neighbour, Cameroon, whose military was involved in the ceasefire talks. + +There was immediate scepticism, however. One Western diplomat in Lagos, Nigeria’s coastal commercial capital, pointed out that Goodluck Jonathan, the president, is in the middle of campaigning for the presidential elections due next year. + +“He’s having a tough run with Boko Haram, and he needs a boost,” the diplomat said. “It’s the main thing that people are concerned about, security. If he can score a ceasefire, great. If he can bring the girls back, even better. + +“But we’ve not yet heard from Boko Haram. Until then, we’re taking this with a little salt.” + +Aid groups working to secure the release of the schoolgirls welcomed the news, but also remained cautious. + +“This ceasefire is incredibly promising, but we aren’t there yet,” said Hussaini Abdu, country director for ActionAid Nigeria. “Until every girl is released negotiations must continue. + +“We are excited about the possibility of restoring peace in the country, but these girls must remain a priority and we therefore urge the government to ensure that the safety of all of them is guaranteed as part of any truce.” + +Britain is among several nations that has offered assistance to the Nigerian government and its military to help find the missing schoolgirls. + +Privately, Western security sector sources in the country report exasperation among those coming to help over the slow pace of the Nigerians’ reactions to the kidnap crisis. + +The girls are understood to have been separated into several groups, making an armed rescue far more complicated and dangerous, leaving talks as the only likely route to their release. + +Boko Haram has in the past insisted that it would only release the teenagers if Nigeria freed several of the group’s senior commanders, who have been captured and are in jail. There were no immediate details of what Boko Haram will get out of the ceasefire deal. + +The group has been blamed for hundreds of killings in bomb or gun attacks, and it is increasingly choosing targets over an ever wider area of northern Nigeria. + +It began as a local militia targeting people who broke strict Islamic regulations such as drinking alcohol. But it recently linked with al-Qaeda’s franchise in West Africa, al-Qaeda in the Islamic Maghreb, and appears to have taken on far more ambitious aims, including ridding northern Nigeria of Christians. + +Boko Haram’s leader, Abubakar Shekau, frequently justifies attacks on Christians as revenge for killings of Muslims in Nigeria’s volatile “Middle Belt”, where the largely Christian south and mostly Muslim north meet. + +The Telegraph revealed last month that the International Committee of the Red Cross had become involved in a secret prisoner swap deal that would ensure the schoolgirls' return. + +Officials from the Geneva-based organisation sat in on talks between the Nigerian government and a senior Boko Haram leader that was being held in one of the country's maximum security prisons. + +The Red Cross officials also visited a number of other jails, identifying a list of 16 senior commanders that Boko Haram wants freed in exchange for the 219 hostages kidnapped from the north-east town of Chibok. + +The ICRC's role in the talks represented the first official confirmation that the Nigerian government was actively engaged in talks with Boko Haram. + +Publicly, Nigeria's president, Goodluck Jonathan, has previously maintained that the government would never agree to any kind of negotiations.","0" +"Insurgents killed in Nigeria despite alleged truce with Boko Haram","At least 25 suspected Boko Haram insurgents were killed in clashes between soldiers and the Islamist militants in northeast Nigeria and five civilians were killed in fighting elsewhere in the region, a military source and residents said on Monday. + +A ceasefire agreement between Boko Haram and the Nigerian government was expected to lead to the liberation of more than 200 schoolgirls kidnapped by the militants six months ago, and talks were due to continue in neighbouring Chad on Monday. + +Boko Haram has not confirmed the truce and there have been at least six attacks over the weekend – blamed by security sources on the insurgents – that have killed several dozen people since the announcement of the ceasefire. + +A government spokesman has said that the fighting on Sunday may be the work of criminal gangs in the lawless region. + +An army officer, who requested anonymity, said the militants tried to enter the town of Damboa late on Sunday through Alagarno, a Boko Haram hideout, but soldiers fought them off. “Our men gunned down 25 of the insurgents because they would have entered Damboa and unleashed more terror on the town that is just picking up from its ruins,” the officer said. + +He said an armoured vehicle and some arms were recovered from the insurgents. + +Damboa, a garrison town near the border with Cameroon, has been the site of fierce fighting between the militants and Nigerian forces for months. The insurgents sacked the town in July but were driven out by an army counter-offensive. + +A member of pro-government Civilian Joint Task Force vigilantes, Mohammed Haruna, said of clashes on Sunday, “Two of our members came to [the town of] Biu this morning from Damboa and said the soldiers engaged Boko Haram yesterday and the battle lasted till about midnight.” + +Separately, Maiduguri resident Andrew Tada, said the insurgents killed five people in Gava, a hilly town in Gwoza Local Government Area not far from Damboa. + +Tada said his brother in Gava was lucky to have escaped to the top of a mountain. + +“My brother is still there now with other relatives, women and children,” he told Reuters after speaking with his brother on the phone. + +“They [the militants] came yesterday [Sunday] while people were scouting for food at the foot of the mountain. When the insurgents sighted our people, they pursued them and slaughtered five,” Tada said.","0" +"Nigeria says it has deal with Boko Haram to release kidnapped girls","Nigeria said on Friday it had agreed a ceasefire with Islamist militants Boko Haram and reached a deal for the release of more than 200 schoolgirls kidnapped by the group six months ago. + +There was no immediate confirmation from the rebels, who have brought five years of havoc in Africa’s top oil producer and triggered an international outcry by seizing the girls from the northeast town of Chibok in April. + +“I wish to inform this audience that a ceasefire agreement has been concluded,” said the head of Nigeria’s military, Air Chief Marshal Alex Badeh, adding the deal had followed three days of talks with the militant sect. + +Government spokesman Mike Omeri said the deal covered the release of the captives and Boko Haram had given assurances “that the schoolgirls and all other people in their captivity are all alive and well.” + +Their release would be a huge boost for President Goodluck Jonathan, who faces an election next year and has been pilloried at home and abroad for his slow response to the kidnapping and his inability to quell the violence, the biggest security threat to Africa’s biggest economy. + +Apart from one appearance on a Boko Haram video, the girls have not been seen since the brazen nighttime raid on the town near the Cameroon border, although police and a parent said last month that one of the victims had been released. + +Boko Haram, whose name roughly translates as “Western education is sinful,” has killed thousands of people in its fight to create an Islamic caliphate in the vast scrubland of Nigeria’s impoverished northeast. + +A senior Nigerian security source confirmed the existence of talks, but said it remained unclear whether Abuja was negotiating with self-proclaimed movement leader Abubakar Shekau, or another faction within the group. + +“Commitment among parts of Boko Haram and the military does appear to be genuine. It is worth taking seriously,” the security source told Reuters. + +Several rounds of negotiations have been attempted in recent years but they have never achieved a peace deal, partly because the group is believed to be deeply divided. + +“There are some talks but it depends on the buy-in of the whole group. I would be surprised if Shekau had suddenly changed his mind and is ready for a ceasefire,” the source added. + +The government was negotiating with Danladi Ahmadu, a man calling himself the secretary-general of Boko Haram, a presidency source said. It was not clear if Ahmadu is part of the same faction as Shekau. + +Security sources in neighbouring Chad said Chadian mediators had been involved in the discussions, which were part of a larger deal that led to the release a week ago of 27 hostages, including 10 Chinese workers, kidnapped in Cameroon. + +Separately, Cameroon’s defence ministry said eight soldiers and 107 Boko Haram militants had been killed in fighting in the far north on Wednesday and Thursday, a region that has suffered regular cross-border raids.","0" +"Boko Haram agrees to release schoolgirls, Nigeria says","Nigeria said on Friday it had agreed to a ceasefire with Islamist militants Boko Haram and reached a deal for the release of more than 200 schoolgirls kidnapped by the group six months ago. + +There was no immediate confirmation from the rebels, who have wreaked five years of havoc in Africa’s top oil producer and triggered an international outcry by seizing the girls from the northeast town of Chibok in April. + +“I wish to inform this audience that a ceasefire agreement has been concluded,” said the head of Nigeria’s military, Air Chief Marshal Alex Badeh, adding the deal had followed three days of talks with the militant sect. + +The U.S. State Department said it “could not independently confirm” a deal had been struck between Nigeria and Boko Haram. The United States is among several Western allies helping Nigeria’s military with training and intelligence support to tackle Boko Haram. + +But French President François Hollande welcomed the “good news” and told a news conference in Paris that the girls’ release “could happen in the coming hours and days.” France has been involved in negotiations that led to the release of several of its citizens kidnapped by Boko Haram in Cameroon. + +Neither Mr. Hollande nor Nigerian government officials gave any details. + +Nigerian government spokesman Mike Omeri said the deal covered the release of the captives and Boko Haram had given assurances “that the schoolgirls and all other people in their captivity are all alive and well.” + +But a precedent of previous government and military claims about an end to the deadly five-year conflict and the fate of the missing teenagers left many observers cautious. + +Nigerian President Goodluck Jonathan is expected to declare his bid for re-election in coming weeks, and positive news about the hostages and the violence would likely give him a political boost. He has been pilloried at home and abroad for his slow response to the kidnapping and his inability to quell the violence, the biggest security threat to Africa’s biggest economy. + +Apart from one appearance on a Boko Haram video, the Chibok girls have not been seen since the brazen night-time raid on the town near the Cameroon border, although police and a parent said last month that one of the victims had been released. + +Boko Haram, whose name roughly translates as “Western education is sinful,” has killed thousands of people in its fight to create an Islamic state in the vast scrubland of Nigeria’s impoverished northeast. A senior Nigerian security source confirmed the existence of talks but said it remained unclear whether Abuja was negotiating with self-proclaimed movement leader Abubakar Shekau, or another faction within the group. + +“Commitment among parts of Boko Haram and the military does appear to be genuine. It is worth taking seriously,” the security source told Reuters. + +Several rounds of negotiations have been attempted in recent years but they have never achieved a peace deal, partly because the group is believed to be deeply divided. + +“There are some talks but it depends on the buy-in of the whole group. I would be surprised if Shekau had suddenly changed his mind and is ready for a ceasefire,” the source added. + +With reports from Associated Press and Agence France-Presse","0" +"Boko Haram denies it has agreed ceasefire","The Islamist group Boko Haram has denied claims by Nigeria’s government that it has agreed to a ceasefire and will release more than 200 abducted schoolgirls. + +The announcement came in a video sent to Agence France-Presse on Saturday in which the militant group’s leader, Abubakar Shekau, ruled out future talks with the government and said the girls had converted to Islam and been married off since being kidnapped more than six months ago. + +Some 276 schoolgirls were seized from the remote north-eastern town of Chibok in Borno state in April. Many escaped in the first couple of days but 219 remain missing. + +More than 500 women and girls aged from infancy to 65 have been kidnapped by Boko Haram and held in militant camps since 2009, Human Rights Watch said this week, including 60 reportedly kidnapped from two towns in north-eastern Nigeria last week. Many have been targeted because they are Christians or attending school. + +Girls and women abducted by the Islamist group and later released have spoken of life in captivity that included forced marriage and labour, rape, torture, psychological abuse and coerced religious conversion. + +Shekau said in the latest video that all of the Chibok schoolgirls had become Muslims. “They have now memorised two chapters of the Qur’an,” he said. + +Speaking in Hausa, he said: “We have married them off. They are in their marital homes.” + +Families of the Chibok schoolgirls said they were shocked but not surprised at the marriage claims. + +Pogo Bitrus, the head of the Chibok Elders Forum, said: “We were sceptical about the talks to release our girls and we never took the ceasefire seriously because since the announcement, they have never stopped attacking communities. Therefore the information that our girls have been married off is not surprising to us.” + +Bitrus has four nieces among the hostages. “We are only hoping the government will step up whatever efforts it is making to quell the insurgency,” he said. + +Enoch Mark, a Christian pastor in Chibok whose daughter and niece are among the hostages, said the girls’ families were “lost for words”. + +“Since they were kidnapped we have no certainty about the situation they are in. We keep getting conflicting information,” he said. “We only keep hoping that they will be returned to us.” + +Daniel Bekele of Human Rights Watch said the Chibok kidnappings and the #BringBackOurGirls campaign had focused global attention on the vulnerability of girls in north-eastern Nigeria. + +“Now the Nigerian government and its allies need to step up their efforts to put an end to these brutal abductions and provide for the medical, psychological and social needs of the women and girls who have managed to escape,” he said.","0" +"Nigeria: hopes for return of kidnapped schoolgirls rise after ceasefire reported","Questions surrounded purported deal between Nigerian government and Boko Haram for release of missing schoolgirls + +The Nigerian government says it has agreed a ceasefire with the Islamist militant group Boko Haram and is negotiating for the release of 219 schoolgirls kidnapped six months ago. + +The deal would mark a huge breakthrough after a five-year insurgency by extremists seeking to create an Islamic state in the north of Africa’s most populous country. It has left thousands dead and a worldwide outcry was prompted when the girls were abducted in April from the north-eastern town of Chibok. + +Members of the Bring Back Our Girls campaign tweeted: “We are monitoring the news with huge expectations.” + +But questions surrounded the purported agreement on Friday. Similar claims from the government and military have failed to bear fruit. The Nigerian president, Goodluck Jonathan, is expected to declare that he is standing for re-election, and positive news about the hostages and insurgency could deflect criticism of his handling of the crisis. + +Mike Omeri, a government spokesman, told a press conference in the capital, Abuja: “Already, the terrorists have announced a ceasefire in furtherance of their desire for peace. In this regard, the government of Nigeria has, in similar vein, declared a ceasefire.” + +Omeri claimed that there had been direct negotiations this week about the release of the missing girls. Boko Haram negotiators “assured that the schoolgirls and all other people in their captivity are all alive and well”, he said. + +The truce was announced on Friday by Nigeria’s chief of defence staff, Air Marshal Alex Badeh, who ordered his troops to comply immediately with the agreement. Boko Haram has not made a public statement. + +The group had been demanding the release of detained extremists in exchange for the girls. Jonathan had said he could not countenance a prisoner swap. + +The failure of Jonathan’s government to rescue the girls has prompted an international campaign and daily Bring Back Our Girls rallies in Abuja to highlight the girls’ plight. There was further anger when posters calling for Jonathan’s re-election in February by using the hashtag BringBackGoodluck2015 appeared until he ordered them to be torn down. + +In July, Jonathan met for the first time parents of the girls and dozens of classmates who managed to escape. It followed months of controversy in which the parents had sought a meeting. He finally agreed to the meeting after a request from Malala Yousafzai, the 17-year-old Pakistani schoolgirl who was shot by Taliban militants in 2012 and won the Nobel peace prize this month for her campaigning for girls’ right to an education. + +Jonathan’s principal secretary, Hassan Tukur, told Agence France-Presse on Friday that an agreement to end hostilities had been reached following talks, as well as a deal to release the 219 girls. + +Tukur said he had represented the government at two meetings with the Islamist extremists in neighbouring Chad, mediated by that country’s president, Idriss Déby. “Boko Haram issued the ceasefire as a result of the discussions we have been having with them,” said Tukur. “They have agreed to release the Chibok girls,” he added. + +But there was uncertainty about the identity of Boko Haram’s representative at the talks, named by Tukur as Danladi Ahmadu. + +Multiple analysts cast doubt on Ahmadu’s credibility as a Boko Haram envoy. Shehu Sani, a Boko Haram expert who has negotiated with the group before on behalf of the government, told AFP: “I have never heard of such a man, and if Boko Haram wanted to declare a ceasefire, it would come from the group’s leader, Abubakar Shekau.” + +Ralph Bello-Fadile, an assistant to Nigeria’s national security adviser (NSA), told a conference on Monday that it had been inundated with fraudsters claiming to represent Shekau. “Government wants to negotiate, but so far nobody has come forward who speaks for Shekau,” he told a Chatham House event in Abuja. + +Ahmadu gave an interview broadcast on Friday yesterday on the Hausa language service of Voice of America radio in which he claimed to be the group’s chief security officer and in charge of publicity. He made no mention of an end to hostilities and was vague on details of the apparent talks, even claiming not to have met Shekau. + +He also referred to the jihadi group as Boko Haram, a name that means “western education is forbidden”. The name was imposed on the Islamist radicals by outsiders – the insurgents themselves never use the term. Their leaders have exclusively used the name Jama’atu Ahlis Sunna Lidda’awati wal-Jihad, which means “People Committed to the Propagation of the Prophet’s Teachings and Jihad”. + +Boko Haram stormed the school in Chibok in April and snatched nearly 300 students, of whom 219 remain in captivity. This week about 50 protesters in red shirts tried to march to the presidential villa but were repeatedly diverted by riot police. The president has blamed activists for politicising the abductions and influencing the parents.","0" +"Reports: Boko Haram may release schoolgirls as part of deal","More than 200 missing schoolgirls kidnapped by the Islamic extremist group Boko Haram may be released as part of an immediate cease-fire agreement announced Friday with the Nigerian government, according to multiple media reports. + +Nigerian presidential aide Hassan Tukur told BBC Focus on Africa that the cease-fire agreement came after months of negotiations mediated by Chad. + +The girls were kidnapped by Boko Haram — the group's nickname means ""education is sinful"" — on April 15 while in school in the northeastern town of Chibok. + +""They've assured us they have the girls and they will release them,"" Tukur told the BBC. ""I am cautiously optimistic."" + +Talking to CNN, Tukur said: ""We have agreed on the release of the Chibok schoolgirls, and we expect to conclude on that at our next meeting with the group's representative next week in Chad."" + +Voice of America reported Tukur and Danladi Ahmadu, who calls himself the secretary-general of the militant group, also said the girls would be released. The release was set to happen Monday in Chad, according to VOA's Hausa-language service. + +However, Nigerian Defense Ministry spokesman Maj. Gen. Chris Olukolade told the Associated Press that the girls' release is still being negotiated. + +Boko Haram negotiators ""assured that the schoolgirls and all other people in their captivity are all alive and well,"" Mike Omeri, the government spokesman on the insurgency, told a news conference after the truce was announced. + +Contributing: The Associated Press","0" +"Reports: Boko Haram may release schoolgirls","More than 200 missing schoolgirls kidnapped by the Islamic extremist group Boko Haram may be released as part of an immediate cease-fire agreement announced Friday with the Nigerian government, according to multiple media reports. + +Nigerian presidential aide Hassan Tukur told BBC Focus on Africa that the cease-fire agreement came after months of negotiations mediated by Chad. + +The girls were kidnapped by Boko Haram — the group's nickname means ""education is sinful"" — on April 15 while in school in the northeastern town of Chibok. + +""They've assured us they have the girls, and they will release them,"" Tukur told the BBC. ""I am cautiously optimistic."" + +Talking to CNN, Tukur said, ""We have agreed on the release of the Chibok schoolgirls, and we expect to conclude on that at our next meeting with the group's representative next week in Chad."" + +Voice of America reported Tukur and Danladi Ahmadu, who calls himself the secretary-general of the militant group, said the girls would be released. The release was set to happen Monday in Chad, according to VOA's Hausa-language service. + +Maj. Gen. Chris Olukolade, a Nigerian Defense Ministry spokesman, told the Associated Press the girls' release is still being negotiated. + +Boko Haram negotiators ""assured that the schoolgirls and all other people in their captivity are all alive and well,"" Mike Omeri, the government spokesman on the insurgency, told a news conference after the truce was announced. + +Contributing: The Associated Press","0" +"Boko Haram denies truce, says kidnapped girls married","ABUJA, Nigeria — The leader of Nigeria's Islamist extremist group dashed hopes for the release of 200 kidnapped girls Saturday, denying reports of a truce with the government. + +In a new video message, Boko Haram leader Abubakar Shekau says the schoolgirls have converted to Islam and married off. ""The issue of the girls is long forgotten because I have long ago married them off,"" he says, laughing. + +The news goes counter to what the Nigerian government said nearly two weeks ago when it announced a cease-fire deal with the terrorist organization, raising hopes among the families of the kidnapped girls — who were taken from the northeastern Nigerian town of Chibok in April — that their daughters would soon be released. + +But as the weeks dragged on with no sign of the kidnapped girls, hopes began to fade. + +""I was very excited when I heard the news — I will finally reunite with my daughter,"" said Hamidah Amira, 36, whose 17-year-old daughter was kidnapped. But then desperation set in, especially as Boko Haram abducted dozens of young women and teenagers in northeast Nigeria and continued to launch attacks that forced hundreds to flee. + +Despite those incidents, the government insisted negotiations with the Islamists were ongoing in Chad, as some began to raise doubts a cease-fire was even agreed upon by the group. + +Martin Ewi, senior researcher at the Institute for Security Studies' office in Pretoria, said he didn't think Boko Haram had agreed to a truce, citing the lack of public statements on the issue in the past two weeks. + +""The government might be talking to one faction … and then you have the other factions which might not have bought into the idea of dialogue,"" he said. + +Human Rights Watch estimates Boko Haram, whose name loosely translates as ""Western education is forbidden,"" has abducted around 500 young women over the past five years. + +Although some girls managed to escape from the Islamists, the whereabouts and the fate of the rest of the young women are uncertain. + +A recent Human Rights Watch report, based on interviews with victims and witnesses of Boko Haram abductions, offers rare insight into a series of physical and sexual abuses the girls suffer in captivity, including rape, forced labor and beating. + +""We found that the Nigerian government has never interviewed these girls, never really found out or learned what they've gone through, never attempted to do any kind of investigations,"" said Rona Peligal, Human Rights Watch deputy director for the Africa Division. ""They were kind of left on their own."" + +Chibok resident Solomon Ali is deeply critical of the government's handling of the situation since the beginning. + +""We were disappointed that the government has done nothing to ensure these girls are released,"" he said, adding officials have failed to keep the community informed. + +Outraged by the kidnappings and the atrocities committed by Boko Haram, the international community has urged the Nigerian government to step up its efforts to free the girls. Since April, a campaign under the motto ""Bring Back Our Girls"" went viral on social media. + +Peligal says Nigerian authorities should do a better job responding to the Boko Haram threat and ensuring protection around schools. + +""The government needs to better anticipate and plan for those kinds of abductions because they're continuing,"" she said. ""And the government should respond capably."" + +Ewi worries the girls would not be freed unless the government yields to Boko Haram's demands to release some of their militants. + +""You can't pursue military operations and still be hoping to release the girls alive,"" he said. + +Analysts warn the situation is likely to get worse in the months ahead of the 2015 election. Earlier this week, President Goodluck Jonathan, who is under increasing scrutiny for his failure to locate the girls, confirmed he would be running for re-election. + +""The Boko Haram issue has been indeed politicized, and I expect it would be further politicized as we get closer to the election,"" said Peligal. + +In the meantime, Amira — like other moms — waits, while making a personal appeal to Boko Haram to release her daughter and the other girls. + +""They should sympathize with us, not with the government,"" Amira said. + +Contributing: The Associated Press","0" +"Six months after abducting Nigerian schoolgirls, Boko Haram reportedly wants to free them","On Friday, the Nigerian military reportedly agreed to a truce with the militant group Boko Haram. According to the announcement, more than 200 Nigerian schoolgirls who were abducted this year will be freed. According to CNN, the details of the release are expected to be negotiated next week. + +In August, the militant group Boko Haram declared an ""Islamic state"" in northeastern Nigeria, a territory largely occupied by the fighters. Boko Haram is believed to be hiding the girls somewhere in this area. + +This week marked six months since the mass kidnapping took place. Here's what has happened since. + +On April 14, 276 Nigerian girls were kidnapped by Boko Haram militants from a school in Chibok, northern Nigeria, according to official figures. The mass abduction occurred at night, and it took days before the full scale of the kidnapping became clear. Shortly after the abductions, a military spokesperson claimed that most of the girls had been rescued by Nigerian soldiers, but the remarks turned out to be wrong. Whether or not the Nigerian army is suited to finding the girls has been questioned: Its reputation in the rural north is bad, and it is often accused of lacking transparency and its soldiers of committing crimes. One recent video allegedly showed Nigerian soldiers slitting prisoners' throats, according to Amnesty International. + +In the weeks following the mass kidnapping, criticism of the Nigerian government and the military had quickly grown as they failed to free the girls. In May, Boko Haram leader Abubakar Shekau released a video message claiming that the girls would ""remain slaves with us."" + +Nearly 200 days have passed since the girls were abducted, and according to estimates, more than 200 schoolgirls are still being held by Boko Haram militants. + +Only a few dozen girls have managed to escape over the past months: The Times of London cited an example of four girls who were able to flee from their captors and walked for three weeks through the jungle. Most of the escapes, however, took place shortly after the abductions, as this graph shows. As time passed, hope faded for many parents, and reports of escapes became less frequent. ""The longer they're there, the greater likelihood they become dispersed, and the more difficult they are to track down,"" Jennifer Cook, director of the Africa Program at the Center for Strategic and International Studies, told Time magazine this week, before the reports emerged that Boko Haram was considering freeing them. There are conflicting numbers of how many girls are still in captivity — some say 215, some say 219. + +The numbers used in our graph only refer to the mass kidnapping in April. Other abductions of women and girls have occurred since. + +Boko Haram is predominantly active in the northeast of Nigeria, where the girls were kidnapped, but its sphere of influence extends further into the west and south of the country. + +The militants have conducted an increasing number of attacks over the past few months and are now believed to be active in an area which could be up to 500,000 square kilometers, or 193,000 square miles. Its core area spreads over as much as 250,000 square kilometers, roughly the size of the United Kingdom. However, Boko Haram is not in full control of most of the areas in which it is active. + +Fatalities from non-criminal Nigerian violence — a term that includes attacks by terror groups and communal or political actors — have risen rapidly since 2010, and Boko Haram attacks are the main driver behind this rise. The militant group has killed at least 5,100 Nigerians this year, according to estimates of the Johns Hopkins School of Advanced International Studies. This graph shows how fatalities caused by Boko Haram went up from around zero to more than 5,000 annually within only six years. + +Although the threat posed by Boko Haram had grown steadily, it took until the April abductions for the conflict to make international headlines. The burst of reporting was accompanied by a huge rise in attention to Boko Haram on social media. + +Up until May 13, about 3.3 million tweets were posted, using the hashtag #BringBackOurGirls. According to the BBC, most people who used the hashtag lived in Nigeria (27 percent) and the United States (26 percent). Still, thousands of tweets are being posted each week in an effort to raise awareness about the fate of the Nigerian schoolgirls. + +The social media campaign found prominent supporters: As of Oct. 17, more than 57,000 users had retweeted Michelle Obama's message: ""Our prayers are with the missing Nigerian girls and their families. It's time to #BringBackOurGirls."" + +Our prayers are with the missing Nigerian girls and their families. It's time to #BringBackOurGirls. -mo pic.twitter.com/glDKDotJRt + +— The First Lady (@FLOTUS) May 7, 2014 + +The Obama administration deployed 80 U.S. military personnel to Chad in May. In a letter, the White House said: ""These personnel will support the operation of intelligence, surveillance and reconnaissance aircraft for missions over northern Nigeria and the surrounding area,"" and aid in the search for the missing schoolgirls. Chad is east of Nigeria. Other countries, such as China, France and Britain, have also sent military assistance to the region. + +According to some reports, Boko Haram started to sell some of the kidnapped girls as brides to militants in May. The value of a girl, according to Boko Haram: $12. The Associated Press cited reports of forced mass weddings which had taken place after the abductions. In a video message, Boko Haram leader Shekau had reportedly announced: ""I abducted your girls. I will sell them in the market, by Allah."" + +The hunt for Boko Haram leader Shekau had started well before the mass abductions of the girls. In 2013, the U.S. State Department added Shekau to its ""Rewards for Justice Program,"" offering up to $7 million for information that led to his capture. Those efforts have been unsuccessful. A video which was released this month showed Shekau alive and in freedom. + +Meanwhile, USAID — the international development agency of the United States — has devoted about $150 million to programs aimed at providing education to Nigerian children and teenagers. + +The programs primarily target internally displaced children and others who are affected by the violence in Nigeria. Only 28 percent of primary-age children have ever attended school in Borno, the state in which the kidnappings took place. + +The low attendance rates in an area partially under the sphere of influence of Boko Haram does not seem to be a coincidence. Boko Haram's name can be translated as ""Western education is sin.""","0" +"North Dakota Names Landfill After Obama","The state of North Dakota has named a new publicly-owned landfill after President Barack Obama. + +In an overwhelming 35-10 vote, the state Senate advanced a bill naming a 650-acre site currently under construction after the nation’s 44th president. Governor Jack Dalrymple is expected to sign the measure into law Tuesday. + +When completed, the Barack Obama Memorial Landfill will be the largest waste disposal site in North Dakota, and the 17th largest in the United States. It will be especially rich in toxic waste from the local petroleum and medical industries. + +“We wanted to do something to honor the president,” says Republican State Senator Doug Perlman, who was the lead sponsor of the bill. “And I think a pile of garbage is a fitting tribute to Obama’s presidency. + +“We originally planned on naming it after a nearby mountain. But then someone jokingly suggested we name it after Obama. I never thought and idea like that would actually pass. But I was pleasantly surprised.” + +The president is hardly popular in North Dakota. The most recent poll in December 2013 found that Obama has a 35% approval rating in the state, although that figure may have fallen further in the year since. Yet even considering the political climate, seasoned observers are surprised that two Democratic lawmakers voted for the bill’s passage. + +“I supported Obama because I thought he would end the wars in the Middle East;” says Allison Mitchell, a progressive Democrat from Grand Forks. “But he decided to fight new wars abroad instead of fighting for single-payer health care and jobs here at home. + +“I guess people expected me to oppose this landfill thing because I’m a Democrat. But honestly I don’t really care anymore. Maybe this small act of protest will wake him up.” + +Ordinary citizens in the state also seem to approve of the government’s choice. + +“I can’t think of a better name,” says Joe Blough, a plumber from Minot. “It’s darkly colored and it's full of shit. That pretty much sums up Obama.”","0" +"Is Kim Jong-Un Really Opening a Restaurant in Scotland?","If the past few weeks of nonstop media onslaught about North Korea and The Interview just haven’t quite appeased your insatiable appetite for Kim Jong-Un antics, fear not—there are other things (literally) cooking up his tunic sleeves. + +Everyone’s favorite guilty pleasure, the sometimes-reliable, sometimes-not UK rag The Daily Mail, reports that the dictator is eyeing Scotland as the location for his next business venture—an expansion of the restaurant chain known as Pyongyang, which is owned by the North Korean government and used to generate additional cash flow overseas. There are currently franchises in cities such as Beijing, Shanghai, Kuala Lampur, Jakarta, and more recently, Amsterdam. + +Although the proposed new location may seem a bit random, Scotland has allegedly been singled out for two reasons. The first is that Kim Jong-Un and other elite North Korean officials love drinking Scotch whisky. (His father, the late Kim Jong-Il, was a bigger fan of Hennessy, supposedly spending some £700,000 a year on the cognac.) + +In September of this year when the United Kingdom debated whether or not Scotland should be granted sovereignty, Kim Jong-Un was allegedly a supporter of the country’s independence because—as Choe Kwan-il, managing editor of North Korean paper Choson Sinbo, told UK’s Daily Mirror—“North Korea is rich in natural resources and we like the taste of Scotch whisky, so [Scotland and North Korea] can be beneficial to each other.” + +In terms of the potential new addition to the Pyongyang chain, The Daily Mail claims that the other reason why North Korea might single out Scotland is that they want to make nice with some European countries in hopes of improving diplomacy and their global image. North Korean Leadership Watch editor Michael Madden tells the Mail that Kim Jong-Un has been trying to think of ways to buddy up with Scotland ever since its bid for sovereignty, and has more hope for acceptance there than in those other judgy European countries like England and France. Madden also claims that tourists in North Korea are already encouraged to pay tips in Scotch rather than won (the local currency). + +Jenny Town of the US-Korea Institute is also quoted as arguing, “North Korea is going to support any country struggling for independence and legitimacy, as North Korea itself still continues to seek validation and recognition of its own legitimacy as a sovereign nation.” In this case, that may mean trying to snuggle up with a Pyongyang franchise that will attempt to win over the Scots via dishes such as barbecued cuttlefish, kimchi, pine-nut gruel, dog meat soup, and a mysterious aphrodisiac made out of bears. (Although these foods are served at other Pyongyang restaurants, there is no specific evidence that they’d make their way onto menus in Scotland). + +There has been no official announcement from North Korea confirming that they are opening a restaurant in Scotland—in fact, a Korean embassy official recently denied the story to The Independent. But as it is with many other wealth-generating businesses in North Korea, many critics believe that cash flow from the restaurant chain goes straight to Jong-Un himself and his small group of elites with virtually no trickle-down to the North Korean people. + +Kim Jong-Un, 31, gained quite a bit of attention earlier this year for his diagnosis of gout, a disease commonly caused by overindulgence in rich, fatty foods. It was widely reported that he became ill and developed a limp and facial swelling because he had become literally addicted to Emmental, more commonly called “Swiss cheese.” + +No other details about the new restaurant have yet to be verified, so it’s unclear whether tipping in whisky would be encouraged.","0" +"Could Kim Jong Un open a restaurant in Scotland?","North Korean dictator Kim Jong Un could be opening a restaurant in Scotland and serving national favorites such as dog on the menu, experts said. + +""The Scottish independence referendum catapulted Scotland into the North Korean elite's thoughts,"" Michael Madden, editor of the North Korea Leadership Watch blog, told the Edinburgh Evening News. + +""Despite voting 'No' they'd consider left-leaning Scotland to be more suitable to deal with than England. Plus, North Koreans love whisky. Tourists in North Korea are told to tip people in Scotch instead of the currency."" + +The report comes just months after Scots voted to remain part of the U.K. in an independence referendum. North Korea backed the calls for Scottish Independence, and the historic moment could be behind the controversial leader's potential move to locate his next ""Pyongyang"" restaurant branch in Scotland. + +The North Korean embassy in London declined to comment. The Scottish government said it was looking into the report. + +The regime – which has been accused of severe human rights abuses by the United Nations – opened the first branches of Pyongyang near the border with China in the 1990s. Kim Jong Un's restaurant expansion plans saw a branch open in Amsterdam in 2012. This eventually closed down but reopened under the name of Haedanghwa. + +Pyongyang restaurants are known for being a lavish and expensive experience. Traditional Korean music and entertainment often takes place. Jim Hoare, a Korea expert at the School of Oriental and African Studies (SOAS) in London, has visited the restaurants in Asia. He said the main aim of them is to raise money and up the profile of the regime abroad. + +North Korea has been seen as notoriously closed to the outside world and its reputation took at further battering at the end of last year when U.S. officials blamed Kim Jong Un's regime for the unprecedented hacking of Sony Pictures Entertainment. + +The move into Scotland could be to drum up support for North Korea, but despite Kim Jong Un's love of cheese and whisky, Hoare was surprised by the choice of location. + +""Scottish food is very conservative and the idea of them taking to Korean food…I can't think it is the obvious place to go,"" Hoard said. + +""This type of restaurant is not aimed at the Korean community but aimed at rich foreigners who might want to spend money, and may be more suited to London.""","0" +"Anyone for dog meat soup? Kim Jong-Un considers opening restaurant in Scotland selling North Korean delicacies","Kim Jong-Un could be set to open a state-backed restaurant in Scotland serving North Korean delicacies such as dog meat soup and pine-nut gruel. + +The dictator, who has also opened a diner in Amsterdam, is believed to be interested in opening another in the UK. + +Experts say that Kim is especially keen on opening the restaurant in Scotland due to his love of whisky and its popularity among the communist ruling elite. + +Scroll down for video + +The North Korean leader, pictured, is reportedly keen on opening a restaurant in Scotland offering traditional dishes native to his country + +The 'Pyongyang' chain of restaurants already has branches in China and Asia, with proceeds from the business being funnelled back into North Korea to help prop up the secretive regime. + +Michael Madden, editor of North Korea Leadership Watch, said the country is desperate to build diplomatic ties with European countries, especially those with left-wing leanings. + +He explained: 'It would not surprise me at all if they opted to open a restaurant in Scotland. + +'The Scottish independence referendum catapulted Scotland into the North Korean's elite's thoughts. + +'Despite voting no they'd consider left-leaning Scotland to be more suitable than England, plus North Koreans love whisky. + +'Tourists in North Korea are told to tip people in Scotch instead of the currency.' + +Kim Jong Un pictured visiting a mushroom farm in Pyongyang in a picture released last week. As well as a love for whisky, the North Korean leader is reportedly hooked on Swiss cheese + +The Pyongyang restaurants are run in partnership with Office 39, a secretive branch of the North Korean government, which uses them as a legal way of raising overseas cash. + +Mr Madden, a frequent visitor to North Korea, added: 'They are one of the few ways to experience North Korean culture without having to go there. + +'They are done like a franchise with the state renting the brand out to other Koreans to run.' + +Fellow expert Jenny Town, of the US-Korea Institute, said she too believed Pyongyang had warmed to Scotland in recent months. + +Cold noodles + +Barbecued cuttlefish + +Kimchi - a side dish of vegetables with a variety of seasonings + +Dog meat soup + +Pine-nut gruel + +Gingseng wine + +She added: 'North Korea is going to support any country struggling for independence and legitimacy, as North Korea itself still continues to seek validation and recognition of its own legitimacy as a sovereign nation.' + +The state-run food outlets - which began springing up about 10 years ago - channel up to 30 per cent of takings back to Pyongyang. + +But some critics fear the cash ends up in Jong-Un’s own pockets to fund his lifestyle. + +As well as a love for whisky, the North Korean leader is reportedly hooked on Swiss cheese. + +It’s claimed he imports vast quantities at huge expense - despite millions of his countrymen being malnourished. + +A unhealthy appetite for Emmental is believed to be a key factor in Kim's weight ballooning so much that he now walks with a limp. + +The North Korean Embassy in London did not respond to requests for a comment.","0" +"North Korea dictator Kim Jong-un 'set to open a new restaurant in SCOTLAND'","KIM Jong-un could try and open a restaurant in Scotland serving delicacies such as dog meat soup, North Korea experts claim. + +This comes after the controversial leader brought his chain, The 'Pyongyang' restaurants, over to Europe by launching one in Holland. + +Now North Korea watchers believe Scotland may be the next prime location, largely thanks to the popularity of whisky among the communist ruling elite. + +Michael Madden, editor of the North Korea Leadership Watch, said Jong-un is desperate to build diplomatic ties with European countries with left-wing leanings. + +He added: ""It would not surprise me at all if they opted to open a restaurant in Scotland. + +""The Scottish independence referendum catapulted Scotland into the North Korean elite's thoughts. + +GettyKim Jong-Un +""Despite voting No' they'd consider left-leaning Scotland to be more suitable to deal with than England. Plus, North Koreans love whisky. Tourists in North Korea are told to tip people in Scotch instead of the currency."" + +The chain has begun springing up across China and Asia, with proceeds funnelled back to North Korea to help prop up the secretive regime. + +They are run in partnership with Office 39, a secretive branch of the North Korean government, which uses them as a legal way of raising overseas cash. + +Would you eat at Kim Jong-un's restaurant? + +YES +NO + +Mr Madden, a frequent visitor to Pyongyang, the North Korean capital, said: ""They are one of the few ways to experience North Korean culture without having to go there. + +""They are done like a franchise with the state renting the brand out to other Koreans to run. + +""But they tailor the menus to suit. Customers in Western Europe won't get a plateful of dog!"" + +ReutersKim Jong Un looking at fast food +Fellow expert Jenny Town, of the US-Korea Institute, said she too believed Pyongyang had warmed to Scotland in recent months. + +She said: ""North Korea is going to support any country struggling for independence and legitimacy, as North Korea itself still continues to seek validation and recognition of its own legitimacy as a sovereign nation."" + +The state-run food outlets - which began springing up about 10 years ago - channel up to 30% of takings back to Pyongyang. But some critics fear the cash ends up in Jong-un's own pockets to fund his lifestyle. + +As well as a love for whisky, portly leader Jong-un is reportedly hooked on Swiss cheese. + +It's claimed he imports vast quantities at huge expense - despite millions of his countrymen being malnourished. + +The FBI recently accused North Korea of being behind cyber attacks on the US. The regime is thought to be incensed at a film, The Interview, which centres around the fictional assassination of Kim Jong-un. + +The North Korean Embassy in London did not respond to requests for a comment.","0" +"Is North Korea, world's most secret state, really planning a new restaurant in Scotland?","WATCHERS of North Korea's secretive regime believe it could be planning another surprise move, a restaurant in Scotland. + +The Cambodia eaterie +Leader Kim Jong-Un has already opened a diner in Amsterdam, with the 'Pyongyang' chain of restaurants also having branches in China and parts of Asia. + +It has been reported that the dictator is believed to be interested in opening another in the UK, with claims by observers of North Korea that Kim is especially keen on an eaterie in Scotland. + +His fondness of whisky and the profile of Scotland's referendum have been cited as key reasons for the potential serving of North Korean delicacies such as dog meat soup and pine-nut gruel in Scotland. + +Proceeds from the 'Pyongyang' chain are funnelled back into North Korean government funds. + +Michael Madden, editor of North Korea Leadership Watch, said the country is desperate to build diplomatic ties with European countries, especially those with left-wing leanings. + +He said: ""It would not surprise me at all if they opted to open a restaurant in Scotland. + +""The Scottish independence referendum catapulted Scotland into the North Korean's elite's thoughts. + +""Despite voting no they'd consider left-leaning Scotland to be more suitable than England, plus North Koreans love whisky. + +""Tourists in North Korea are told to tip people in Scotch instead of the currency."" + +The Pyongyang restaurants are run in partnership with Office 39, a branch of the North Korean government, which uses them as a way of raising overseas cash.","0" +"Is Kim Jong-un Opening North Korean Restaurant in Scotland?","Reports in recent days had suggested that North Korean dictator Kim Jong-un may open a restaurant in Scotland, exposing the western world to a variety of delicacies including dog meat. +Reports had suggested that North Korean supreme leader Kim Jong-un may open a restaurant in Scotland.Reuters +""It would not surprise me at all if they opted to open a restaurant in Scotland,"" Edinburgh Evening News quoted Michael Madden, editor of the North Korea Leadership Watch blog, as saying. He further explained that North Koreans consider Scotland, which leans more towards leftist ideals than England, more suitable to ""deal with"". +Moreover, the North Korean leader is said to have been keenly interested in Scottish affairs during the Referendum Debate of September 2014, wherein voters decided ""yes"" or ""no"" on ""Should Scotland be an independent country?"". +""Plus, North Koreans love whisky,"" said Madden, before elaborating, ""Tourists in North Korea are told to tip people in Scotch instead of the currency"". The restaurants, if they did open, would serve all nationally popular delicacies, giving the Scots a chance to experience North Korea, without actually going there. +The dictator already owns over a chain of restaurants ""Pyongyang"", with international branches including one in Amsterdam. Although the possibility is quite intriguing, an official at the North Korean Embassy in the United Kingdom is said to have denied any such plans. + +The official at the North Korean embassy in England denied the claims, saying ""It's a nonsense"", and refusing to comment further, reported Independent.","0" +"Kim Jong-un 'set to open a new restaurant in SCOTLAND'","The North Korean leader already has a restaurant in Holland and is hoping to branch out and build diplomatic ties with European cities + +Kim Jong-un could try and open a restaurant in Scotland serving delicacies such as dog meat soup, North Korea experts claim. + +This comes after the controversial leader brought his chain, The 'Pyongyang' restaurants, over to Europe by launching one in Holland. + +Now North Korea watchers believe Scotland may be the next prime location, largely thanks to the popularity of whisky among the communist ruling elite. + +Michael Madden, editor of the North Korea Leadership Watch, said Jong-un is desperate to build diplomatic ties with European countries with left-wing leanings. + +He added: ""It would not surprise me at all if they opted to open a restaurant in Scotland. + +""The Scottish independence referendum catapulted Scotland into the North Korean elite's thoughts. + +Getty Tasty: Kim Jong-Un is a fan of delicacies such as dog meat soup + +""Despite voting No' they'd consider left-leaning Scotland to be more suitable to deal with than England. + +""Plus, North Koreans love whisky. Tourists in North Korea are told to tip people in Scotch instead of the currency."" + +The chain has begun springing up across China and Asia, with proceeds funnelled back to North Korea to help prop up the secretive regime. + +They are run in partnership with Office 39, a secretive branch of the North Korean government, which uses them as a legal way of raising overseas cash. + +Mr Madden, a frequent visitor to Pyongyang, the North Korean capital, said: ""They are one of the few ways to experience North Korean culture without having to go there. + +""They are done like a franchise with the state renting the brand out to other Koreans to run. + +""But they tailor the menus to suit. Customers in Western Europe won't get a plateful of dog!"" + +Reuters Hungry dictator: Kim Jong Un looking at fast food + +Fellow expert Jenny Town, of the US-Korea Institute, said she too believed Pyongyang had warmed to Scotland in recent months. + +She said: ""North Korea is going to support any country struggling for independence and legitimacy, as North Korea itself still continues to seek validation and recognition of its own legitimacy as a sovereign nation."" + +The state-run food outlets - which began springing up about 10 years ago - channel up to 30% of takings back to Pyongyang. But some critics fear the cash ends up in Jong-un's own pockets to fund his lifestyle. + +As well as a love for whisky, portly leader Jong-un is reportedly hooked on Swiss cheese. + +It's claimed he imports vast quantities at huge expense - despite millions of his countrymen being malnourished. + +The FBI recently accused North Korea of being behind cyber attacks on the US. The regime is thought to be incensed at a film, The Interview, which centres around the fictional assassination of Kim Jong-un. + +The North Korean Embassy in London did not respond to requests for a comment. + +McJONG'S MENU + +STARTERS + +Despotted shrimps + +Dictator and leek soup + +Roast peasant + +MAIN COURSE + +Fried Seoul + +Red herring + +Cottage spy + +Commie chef’s special + +DESSERT + +Don’t or you will be shot","0" +"SNOWDEN: ‘Elf On A Shelf’ Actually Hugely Successful NSA Project Read more: http://www.duffelblog.com/2014/12/elf-on-a-shelf-snowden/#ixzz3MAOziZJf","STOCKHOLM — Speaking via Google Hangout to officials in Sweden last week, former NSA Contractor Edward Snowden dropped a bag of coal on his former employers by revealing the hugely popular “Elf on a Shelf” trend is actually an intelligence gathering operation originating with and run by the National Security Agency. + +“It actually started out as a joke,” Snowden said in his speech. “Someone photocopied a picture of an elf with the caption ‘I’m watching you,’ and it just kept moving from cubicle to cubicle.” + +Snowden said that at some point it occurred to someone that if people as paranoid as NSA staff would play this game, what would happen with civilians? + +“Now, the NSA has an agent inside practically every home with a child in it,” Snowden said. + +“The elves have basic mobility, which isn’t a problem because when one shows up someplace unexpected,” Snowden added, “it’s just assumed to be part of the game.” + +Through these adorable snoops, the NSA has gained access to millions of tax returns, bank statements, and 10-year old boys unwrapping and re-wrapping their presents in the days ahead of Christmas. + +“We would flag those kids for later recruitment to the intelligence community,” Snowden said. “Especially for Tailored Access Operations.” + +In addition, the NSA has uncovered a trove of data about the personal lives of millions of Americans, sources confirmed. + +“The NSA has incorporated advanced sensors into these things that can uncover all kinds of information,” journalist Glenn Greenwald told Duffel Blog in an email. “They can tell things about people’s health — cancer, heart disease, liver disease. They know who’s being naughty, and who’s being really naughty, things that even extensive online snooping couldn’t provide. Dildos, vibrators, chains — all the things stashed in closets and under beds.” + +Sources told reporters these were previously inaccessible to the government’s leading intelligence agency, if the owners paid cash at least. + +“If you want to know why the ‘privacy advocates’ have settled down, and moved on? My guess is, blackmail. These elves have accumulated petabytes of evidence against pretty much everybody,” Snowden said. + +“You wouldn’t believe what perverse things people will do to each other, right in front of these things,” Snowden concluded. “It’s why ‘ElfMonitor’ is such a highly sought after duty assignment.”","0" +"Oil Futures Jump on Rumored Pipeline Explosion in Saudi Arabia","NEW YORK—Oil prices jumped Wednesday on unconfirmed rumors in the market that a pipeline exploded in Saudi Arabia, raising fears that the country’s crude production and exports could be curtailed. + +A spokesperson for Saudi Aramco, Saudi Arabia’s oil company, told The Wall Street Journal that the company has seen the rumors, which circulated on Twitter, but isn’t able to confirm them. + +Prices have been sliding for months on concerns that the market is oversupplied and that Saudi Arabia, the biggest oil exporter, is unlikely to cut production to raise prices. + +Light, sweet oil for December delivery recently traded up $1.84, or 2.4%, to $79.03 a barrel on the New York Mercantile Exchange. + +Brent, the global benchmark, rose $1.52, or 1.8%, to $84.34 on ICE Futures Europe. Earlier in the session, prices were trading lower around $82.50 a barrel. + +Weekly inventory data from the U.S. Energy Information Administration, which showed a smaller-than-expected increase in U.S. crude supplies, also supported prices. + +December gasoline futures recently rose 2.1% to $2.1211 a gallon. December diesel rose 1.5% to $2.4793 a gallon. + +—Summer Said contributed to this article.","0" +"U.S., BRENT CRUDE CRUDE FUTURES EXTEND GAINS ON UNCONFIRMED MARKET RUMOR OF OIL PIPELINE EXPLOSION IN SAUDI ARABIA","U.S., BRENT CRUDE CRUDE FUTURES EXTEND GAINS ON UNCONFIRMED MARKET RUMOR OF OIL PIPELINE EXPLOSION IN SAUDI ARABIA","0" +"U.S., Brent crude jump on rumor of oil pipeline blast in Saudi Arabia","Nov 5 (Reuters) - U.S. and Brent crude futures extended gains on Wednesday on an unconfirmed market rumor of an oil pipeline explosion in Saudi Arabia. + +Oil futures had already been lifted by a government report showing a smaller-than-expected rise in U.S. crude stocks and drops in gasoline and distillate inventories. + +Brent December crude futures were up $1.60 at $84.42 a barrel at 11:02 a.m. EST (1602 GMT), after jumping to $84.45. U.S. December crude was up $2 at $79.19 a barrel, having reached $79.35. (Reporting by Robert Gibbons; Editing by Chizu Nomiyama)","0" +"Hearing Unconfirmed Reports of Saudi Pipeline Explosion","Hearing Unconfirmed Reports of Saudi Pipeline Explosion","0" +"Oil spikes on U.S. inventory data, Saudi explosion rumor","Oil futures extended gains Wednesday on unconfirmed rumors of an oil pipeline explosion in Saudi Arabia after previously spiking on data that showed U.S. crude inventories rose less than expected. + +U.S. crude stocks increased by 460,000 barrels in the last week, data from the U.S. government's Energy Information Administration showed on Wednesday. Analysts had expected a rise of 2.2 million barrels. + +Brent turned positive, popping 61 cents to $83.43 a barrel shortly after the report was released. It previously reached a low of $81.63 for the day, its weakest level since late 2010. + +U.S. crude rose $1.37 to $78.56 a barrel, rebounding off a low of $75.84 hit in the previous session, its weakest since October 2011. + +Earlier on Wednesday weak economic data from top energy consumer China intensified worries about demand as a global supply glut grows. + +Services sector growth in China weakened in October as new business cooled, a private survey showed, coming just days after data revealed sluggish factory growth in the world's second-largest economy. + +""Supply is higher and demand expectations are being cut almost every day,"" said Hans van Cleef, senior energy economist at ABN Amro in Amsterdam. + +Brazil's oil output reached a record 2.358 million barrels per day in September, up nearly 13 percent from a year earlier, national oil regulator ANP said on Tuesday. + +Consistent supply from Libya and Iraq, where many expected production to be disrupted by conflict, has added to the downward pressure on prices. + +Van Cleef added that dollar strength was weighing on oil. Oil, priced in dollars, becomes more expensive to holders of other currencies when the U.S. currency rises, denting demand. + +The dollar index hit a new 4-1/2-year high on Wednesday. + +Oil prices on both sides of the Atlantic lost more than 2 percent on Tuesday after Saudi Arabia cut export prices to the United States, threatening to deepen a global supply glut that has driven crude prices down 30 percent since June. + +A bleak outlook for Europe after the European Commission downgraded its forecast for euro zone economic growth over the next few years also weighed on oil prices. + +Saudi Oil Minister Ali al-Naimi is making his first visits in years to fellow exporters Venezuela and Mexico, although tumbling oil prices are not the stated purpose of the trip, according to officials and sources. + +Still, the travel plans come at a pivotal moment for Saudi Arabia and the Organization of the Petroleum Exporting Countries, which meets later in November to discuss how to respond to the rout in global oil prices. + +CNBC contributed to this report.","0" +"Heads up oil traders: Big pipeline explosion reported in Saudi Arabia","Unconfirmed reports at the moment but a pipeline belonging to Saudi Aramco in Sudair Saudi Arabia. +Coming from the twittersphere just now. +Brent jumped up on the news with futures hitting 84.44 but have since fallen back to 83.88","0" +"Crude Sees a Bid on Reports of Saudi Arabia Pipeline Explosion","Crude, under massive pressure of late, is bidding higher on reports of a major pipeline explosion in Saudi Arabia.","0" +"Loggers Accidentally Cut Down World’s Oldest Tree in Amazon Forest","The giant Samauma tree that is thought to be over 5,800 years old judging on its concentric rings and estimated to be close to 40 meters in height was a major part of the native tribes cultural landscape, countless generations of natives having witnessed the long duration of the tree and having included it in their own culture. + +«It is the Mother spirit of the rainforest, from this spirit-tree came the life force of all things living. They have destroyed Aotlcp-Awak, they have brought darkness upon not only our people, but the whole world» explains local tribesman leader Tahuactep of the Matsés tribe. + +Native communities alarmed local media outlets and conservation groups when Aotlcp-Awak, or Mother tree in local dialects, was reported sawed down by heavy machinery + +Anna Golding, local researcher for non profit organization and conservancy group Rainforest Protection Coalition (RPC), an initiative stemming from Berkeley University in California, believes the ‘incident’ was intentionnal. « There are large portions of this national reserve that are rich in oil and natural gas. There has been committed action by energy corporations to lobby the government to exploit the area for years. The protected zones have been cut in half over the past decade and this is only their latest attempt to get rid of the local populations who are fighting to preserve their cultural heritage and lifestyle» she admits. + +Between 1991 and 2014, the total area of forest lost in the Amazon has more than tripled, with most of the lost forest becoming pasture for cattle. Rainforests are the richest places on earth holding the majority of the planet’s biodiversity, yet 100 acres of rainforests are cleared every minute, estimates a recent 2014 World Resources Institute report.","0" +"Whoa, Paul Rudd Was One of the Airport Heroes Who Took Down the Homophobe","You remember the video we posted about late Friday? When I put that item up, the video had a little more than 10,000 views. Now it’s got more than 1.7 million. + +Well, turns out that one of the onlookers who rushed to the defense of the man attacked by an antigay bigot at Dallas-Fort Worth International Airport was Paul Rudd. The actor. You know, this guy. He was probably on a connecting flight from Kansas City.","0" +"Did Paul Rudd Help Tackle That Dallas Airport Gay-Basher?","On Saturday, the entire Internet watched in horror and then cautious joy as a drunk and/or high man in the Dallas-Forth Worth airport assaulted a random bystander he believed was gay. The attacker was then quickly subdued by a crowd of people. The video, first posted by Raw Story, has been viewed nearly two million times. But only one person, comedian and friend of Jezebel Sarah Benincasa, noticed that one of the guys tackling said gay-basher looks a lot like actor and decent-seeming human being Paul Rudd. + +Here's the video once again, via Raw Story: + + + +As you can see, the glassy-eyed gentleman attacks the guy in the pink shirt because he suspects him of being ""a queer"" and then, when asked why he did that, screams ""Because America!"" (It's great that a crowd of people worked to subdue him; slightly less great that an airport security guard can be seen meandering past him moments before he attacks the pink-shirted man, ignoring him as he screams threats and takes his sweatshirt off.) + +In her viewing of the video, Benincasa noticed that around 1:30, one of the people dog-piling the man really, really looks like Paul Rudd. Like, a lot: + +As Wonkette reported, another Twitter user, @msigs, found a girl who'd tweeted about seeing Paul Rudd that day, and got her to confirm he was wearing what he had on the video: a checked shirt and a sport coat. + + +However, that Twitter user appears to have seen Rudd on a flight out of Savannah, Georgia, and we don't know for sure that he stopped in Dallas. (Do people with Paul Rudd-level money really have layovers?) + +So, the jury is still out on this one, even as the glorious #PaulRuddSavesLives hashtag is engulfing Twitter. But, if confirmed, it's going to be almost as great — and, let's be frank, arousing — as that time Ryan Gosling broke up a street fight. + + +Watch Ryan Gosling, Hero, Break Up A Random Street Fight +Here's amateur footage, taken on the corner of Astor Place in New York City over the weekend,… + +Were you in the Dallas airport the other day? Did you see Paul Rudd tackle a gay-basher? Email me: anna.merlan@jezebel.com.","0" +"Oh Hey, Paul Rudd Was One Of The Dallas Airport Homophobe Heroes, No Big","WONKET EXCLUSIVE MUST CREDIT WONKetTE! So you all saw the video, today or alllll the way back on Saturday, of a bunch of Dallas airport heroes tackling the fuck out of that violent homophobe guy. But you DID NOT know one of the heroes was Paul Rudd, because you are not Internet sleuth Sara Benincasa. + +This is even better than the time Ryan Gosling Hey Girled Laurie Penny from getting hit by a lorrie! + +So here is a thing, about this, for blogging. When we saw the video alllll the way back on Saturday, we said, “that is nice when men choose to be manly by physically — and at risk to themselves — keeping the peace. But we are guessing everyone here is bored and also on the lookout for troublemakers and terrorists. Call us when they stop a gaybashing in front of the Crowing Cock.” But we did not say it out loud. + +Well! Now that Paul Rudd is involved — which we know thanks to Sara Benincasa and also this dude @msigs — we are going to guess that FUCK YEAH they would have stopped that nonsense in the streets too, because we give Paul Rudd more credit than random Dallas cowboys, because we are regionist and also classist and probably racist too, the end. + +paul rudd tweets + +Go ahead! Go back to about a minute twenty and watch Paul Rudd full-on tackle the asshole! + +Good job everybody! Keep calm and keep the nutpunchers down!","0" +"TV show tricks chronic catcallers into harassing their own mothers","The Peruvian TV show ""Harassing Your Mother"" performs secret makeovers on the mothers of habitual catcallers, then uses hidden cameras to record catcallers shouting sexual remarks at their own mothers, who furiously upbraid them in the middle of the busy streets of Lima.","0" +"Watch Two Guys Appear to Get Tricked Into Catcalling Their Own Moms","Now, that is an awkward dinner conversation + +A filmmaker in Peru seems to have come up with an ingenious solution to men sexually harassing women in the street — trick serial offenders into catcalling their own mothers. + +Two moms are shown agreeing to be secretly filmed as they donned flattering disguises and strolled past their unwitting sons. After the men shout out sleazy comments, the women pull off their wigs and confront their red-faced boys with a very loud and very public rebuke. + +One enraged mother is seen hitting her son over the head with her handbag. + +The clip, created by American clothing brand Everlast, was filmed in Peru’s national capital Lima, where the company says 7 out of 10 women report being harassed in the street.","0" +"A Peruvian TV show is tricking men into catcalling their mothers, for feminism","Peruvian Show ‘Whistling At Your Mom’ takes the mothers of men with a history of street harassment and gives them makeovers, so that their sons can’t recognise them. + +The women then walk past their awful sons, and are of course catcalled. + +They respond by giving them hell… + +Whilst we’ve not made our mind up about the gimmicky format, we’re glad that this issue is receiving mainstream attention.","0" +"These Men Freak Out When They Discover The Women They Are Harassing Are Their Moms In Disguise (VIDEO)","Street harassment is something that happens to women all over the globe. It may begin to occur a lot less in Lima, Peru after an extremely creative Public Service Announcement, which was sponsored by Everlast aired. The video shows what happens when men harass an attractive woman in the street, only to soon find out that the woman is in fact their own mother in disguise. The results are nothing short of hilarious. The video is called Harassing Your Mother. + +The host of the video starts out by saying: + +“7 out of 10 women are sexually harassed on the streets of Lima, Peru. Men who do it think it is a minor offense. Let’s show them that they are wrong.” + +They find “repeating offenders” who harass women on the streets, then proceed to get in contact with their mothers. The moms then get a makeover that makes then look fabulous and not immediately recognizable. + +The first man in the video calls out to a woman that he does not know is actually his mother saying (at least according to the translation): + + + +“Tasty panties!” + +The mother then turns around and walks up to her son. The realization that he just catcalled his own mother dawns on him as he says, “Mama?” + +She then wails on him. She says: + +“What’s the matter with you Renzo? What they told me about you is true.” + +The man then tries to desperately rationalize the awful thing he did to his mother telling her that it is, “just a game.” + +They repeat the prank again one more time in the video, just to cement the idea they are trying to put out. Remember, the next woman you decide to harass on the street may turn out to be your mother, so maybe try not to do it. Okay? + +You can watch the video in full, below. + + + + + +Featured Image Credit: Screenshot via YouTube","0" +"The men caught cat-calling and wolf whistling their own MOTHERS: Hilarious TV show disguises women so they can experience their sons' behaviour","A new TV show in Peru has captured the moment unwitting men have been caught wolf-whistling their own mothers. + +The experiment took two mothers, whose sons were identified as repeat cat-callers, and disguised them using make-up, wigs and clothes. The women then women walked past their sons to gauge their reaction. + +The mother wearing a disguise of a wig and sunglasses walks past her unsuspecting son and a friend, before he makes a comment towards her + +The mother then goes over to confront her child, who is still unaware the woman is actually his parent + +The man acts in horror as he realises it is his own mother and she launches into a tirade, accusing him of being dirty + +The mother gets so angry with her son, she then takes off her bag and proceeds to hit him with it due to this behaviour + +In the first case, the mother is dressed in a short black dress and walks past her son and a friend in the street. + +The son then unwittingly makes a comment at his mother saying 'tasty panties' which prompts her to go and confront him. + +She then removes her sunglasses and the man then realises he has just cat-called his own mother. + +The mother then launches into a tirade, accusing him of being dirty and saying she never taught him to talk to women in that manner. + +Another mother, wearing a black wig walks past her son, who is standing working on the streets of Lima + +After making a remark towards his mother, she then turns around and goes over to confront him + +She then takes off her wig to reveal herself and then throws it on the floor in anger after being disgusted by her son's behaviour + +The mother then tells her son he should be ashamed of himself for speaking to her like that, as he pleads with her to calm down + +She then gets so angry with her child that she then removes her bag and hits him with it. + +Meanwhile in the second case, the mother wearing a green dress, walks past her son, who calls her 'piggy'. + +She then calls his name before taking off her wig and confronting her son, hitting him with her hairpiece. + +The man then tries to claim he didn't make the remark but is then forced to apologise to his mother before she walks off + +She too launches into a tirade telling her son to he should be ashamed of himself, while he pleads with his mother to quieten down as he is working. + +He then tries to claim he didn't make the remark and it a man in a nearby car, but he eventually apologises before his mother walks off. + +The video ends with a warning saying men should start respecting women before they unwittingly harass their own mothers. + +It comes after the video claims that seven in 10 women say they have experienced sexual harassment on the streets of the Peruvian capital Lima.","0" +"When Street Harassers Realize The Women They're Catcalling Are Their Moms In Disguise","If you've ever wanted to tell a street harasser to stick it where the sun don't shine, but couldn't find the right words -- don't worry, these mamas got you covered. + +A new PSA about street harassment shows what happens when men realize the women they're catcalling are actually their mothers. Sponsored by Everlast, the PSA takes place in Lima, Peru where, as the video states, seven out of 10 women are harassed on the streets. Everlast found two men who were ""repeat offenders"" and contacted their moms who agreed to dress in disguise and walk past their sons. + +The outcome is highly satisfying. After their sons yell some fairly unsavory things, the horrified moms publicly berate them. One of the women actually repeatedly hits her son over the head with her purse after he calls her ""Tasty panties."" It's everything you've ever wanted a catcaller to hear. + +So street harassers, next time you want to catcall a woman imagine how you would feel if she was your mom. Or just realize she's a human being and keep your mouth shut.","0" +"'Whistling At Your Mom': Video Showing Sons Catcalling their Mothers Goes Viral [VIDEO]","A video showing sons catcalling their mothers in Peru's capital city of Lima has gone viral on the internet. +Cases of sexual harassment, eve teasing and molestation have plagued several cities across the world. +A recent video shows that not only young girls, but middle-aged woman also become the victims of such attacks. +The video stated that seven out of ten women are harassed in the streets of Lima. +A Peruvian TV show found some repeat offenders who harass women in public places in Lima. Following this, the channel asked the offenders' mothers to get a makeover and walk past their sons. However, its climax turned ugly. +In the video titled, ""Harassing Your Mother"", which is sponsored by Everlast, two moms dress up and walk in front of their own sons. +While a pervert is seen catcalling his mother by mentioning ""tasty panties"", the other stalker refers his mom as ""Hello Piggy"". Both the angry mothers yell at the sons after revealing their identity. +? + +""What's the matter with you Renzo? What they told about you was true that you saying such dirty things to women,"" one mother asked. +When the other lady said she was under covering herself just to see if her son was really harassing women, the guy tried to tell her that it wasn't him who teased her. +The viral video ends with the message, ""If you harass women don't wait for us to get you to harass your own mother to start respecting them"". +Watch the video below:","0" +"This Man Kept HARASSING Women On The Streets. Until One Day… MOM!?","November 25th marks the International Day for the Elimination of Violence Against Women. So Everlast created this incredible video, demonstrating how some men disrespect women. A woman might simply be walking along the street before she ends up being harassed. And that’s pretty much what happens in this video. Except there’s a very shocking twist! +Right on! They totally deserved that… absolutely brilliant! + +Share this with your friends and family by clicking the button below.","0" +"These Men Catcalling Their Undercover Mothers Is the Best Payback Ever","Like most other places with people, Lima, Peru has a surplus of men who pass those crucial moments throughout their work day by sexually harassing women in the streets. + +Everlast, the brand you had no clue was this fierce, actually did something about it. + +They filmed men catcalling their own mothers. Everlast tracked down the mothers of their very scummy spawn and got them on board for a worthwhile mission: shame your son by getting him to accidentally catcall you. Everlast gave these moms makeovers, wigs, manicures, the whole thing. Then they sent these women out all dressed up like all the other desperate women who wear dresses out in public so that they could be magnets for pervy lines like “where are you going, can I come?” + +Predictably, this video shows the sons saying dirty stuff to their own mothers in disguise, but it doesn’t stop there. In the typically charming way we’re all so enchanted with, one dude calls his own mom “piggy.” Another says, “tasty panties!” That’s when the most satisfying part happens. The mothers turn around for the reveal and bitch these men out. So this is one chance encounter with a lady in the street they won’t forget. The glorious leader of this effort, who is wearing fingerless Everlast driving gloves, wants the moms to slap these scoundrels, but watching them freak out is even more gratifying. Even if it isn’t real, it’s required viewing for all men with female relatives. + +It could have been trite to have moms help their sons see the light by subjecting them to street harassment. It might have been corny if Everlast gave these dudes a chance to redeem themselves. But these boss women offered no such opportunity. They were on a war path to make their sons pay. In one screaming session, they express all the anger you’ve felt every time you had to deal with sex invites in the morning. + +It’s a pretty genius way to turn the tables on the catcallers. At least it’s definitely more effective than issuing a friendly card explaining why it’s not polite to express interest in a stranger’s underwear. One of the guy’s explains to his mommy that it wasn’t him saying those nasty things. (It was the guy in the car.) Iron-clad alibis like this are best handled by a raging mother in heels. Freud may have already died, but now he’s literally dying over this. + +Watch this glorious victory with the English translation below. + + + +[Reddit]","0" +"Arab woman pilot who is poster girl for Gulf states' blitz on ISIS is 'disowned by her family' for bombing 'Sunni heroes of Iraq and the Levant'","Mariam Al Mansouri's F-16 bombing raids were celebrated in the West + +But a statement purporting to be from her UAE family has 'disowned' her + +It attacks her for 'taking part in the brutal aggression against Syria' + +The female air force pilot whose missions against Isis were dubbed 'boobs on the ground' has reportedly been disowned by her family and labelled an 'ingrate'. + +Mariam Al Mansouri's participation in F-16 bombing raids for the UAE was celebrated in the West, but an anonymous statement claiming to be from her family 'disowned' her for 'taking part in the brutal international aggression' against Syria. + +It also expressed support for the Islamic State, saying 'we are proud of the Sunni heroes in Iraq and the Levant'. The brutal terrorist group's original name was the Islamic State of Iraq and the Levant, or Isil. + +Courageous: Major Mansouri, from Abu Dhabi, made a remarkable rise through the ranks of the UAE air force. She's pictured here in an F-16 Desert Eagle + +Major Al Mansouri's F-16 fighter was one of several from a group of Arab nations that are blitzing Isis + +In the name of God All Merciful. + +'O ye who believe! Take not your fathers or your brethren for friends if they favour disbelief over faith. Those of you who taketh them for friends are wrong-doers.' [Quranic verse] + +'Renouncement of Mariam Al Mansouri: + +'We the Mansouri family in the United Arab Emirates hereby publicly declare that we disown the so-called Mariam Al Mansouri as well as anyone taking part in the brutal international aggression against the brotherly Syrian people, starting with our ingrate daughter Mariam Al Mansouri. + +'We hereby remind the Muslim nation all over the world of its duty to defend the causes of the nation [meaning the Islamic nation], and we urge them to take up the jihad [holy war] for the sake of God to support the blessed Syrian revolution against the descendants of Ibn Al Alqami.' [Sunni Islamist insurgents refer to the Shi'a as 'alqami' - a reference to Mu'ayyad al-Din Muhammad Ibn al-Alqami, a Shi'ite minister in the last Abbasid caliphate, who purportedly assisted the Mongols in conquering Baghdad in 1258.] + +'We call upon all factions and battalions operating on the Syrian battleground to unite and join efforts and forces towards the single objective of overthrowing the monstrous Assad regime perched on the pure and blessed Syrian land. + +'Al Mansouri family, in the UAE and abroad, takes this opportunity to declare its support for the blessed Syrian revolution and to all free men defending their rights everywhere in the world. + +'Our family is proud of all free men who defend their cause and of all those who take up arms to defend the honour of their nation [The Islamic Nation}. We are proud of the Sunni heroes in Iraq and the Levant and all those who take up the banner of righteousness wherever they may be. We may not know them, but God knows them and would champion them. + +'We ask our countrymen not to burden us with the consequences of the actions of the so-called Mariam Al Mansouri. All the honourable members of our family have agreed to this statement. + +'Al Mansouri family.' + +The statement also expressed support for the Syrian revolution, according to the Palestinian Wattan news agency. + +It said: 'We the Mansouri family in the United Arab Emirates hereby publicly declare that we disown the so-called Mariam Al Mansouri as well as anyone taking part in the brutal international aggression against the brotherly Syrian people, starting with our ingrate daughter Mariam Al Mansouri. + +'We ask our countrymen not to burden us with the consequences of the actions of the so-called Mariam Al Mansouri.' + +It continued: 'We call upon all factions... on the Syrian battleground to unite and join efforts and forces towards the single objective of overthrowing the monstrous Assad regime. + +'Our family is proud of all free men who defend their cause and of all those who take up arms to defend the honour of their nation [the Islamic Nation]. We are proud of the Sunni heroes in Iraq and the Levant and all those who take up the banner of righteousness wherever they may be.' + +It's not clear whether the views expressed in the statement represent those of the entire family or indeed if it is genuine. + +The Mansouri tribe has some influential members, including the country's economics minister, but it's also very large – the second biggest in Abu Dhabi, the capital of UAE, so it certainly can't be assumed that the views expressed in the statement are representative of the whole group. + +The statement could well have been made anonymously out of fear of punishment, as voicing dissent against the UAE government can result in imprisonment. + +If true, the statement won't represent the first time the Mansouri family has been linked to extremism. + +In January this year high-profile lawyer Mohammed al-Mansoori was jailed for allegedly trying to set up an 'international' branch of the controversial Muslim Brotherhood in the UAE, according to the BBC. + +Major Mansouri, from Abu Dhabi, made a remarkable rise through the ranks of the UAE air force. She joined it in 2007 and is now a squadron commander. + +She is one of eight children and has a degree in English literature. + +The UAE is known to have the most liberal views on women's rights in the Middle East and Mansouri said that she was treated as an equal by her commanding officers. + +She told Deraa Al Watan magazine: 'Everybody is required to have the same high level of combat competence.' + +She says that her nearest relatives are supportive of her role in the air force. + +There was also no difference between men and women with regards to training and assignments, she said. + +'Everybody is required to have the same high level of combat competence,' + +Earlier this week Fox News host Eric Bolling apologised for calling Major Mansouri's missions as 'boobs on the ground'. + +Major Mansouri, from Abu Dhabi, made a remarkable rise through the ranks of the UAE air forc + +A Fox News host has issued an apology after making a sexist comment about a female fighter pilot earlier this week on The Five. + +During a segment about Maj. Mariam Al Mansouri, a female pilot from the United Arab Emirates who led a mission this week against ISIS in Syria, Eric Bolling referred to her mission as 'boobs on the ground.' + +Now, after outrage from viewers, and even his own wife, following these insensitive remarks, he has apologized. + +'I made a joke and when I got home, I got the look, and realized some people didn't think it was funny at all,' Bolling said on the air today. + +'I said sorry to my wife and I apologize to all of you as well and want to make that very clear.' + +This all began when Bolling's cohost, Kimberly Guilfoyle, praised Maj. Mansouri on the program Wednesday afternoon. + +'Hey ISIS, you were bombed by a woman,' Guilfoyle said. + +'Oh yeah, hell came down on ISIS in Syria, because guess what: the first female pilot piloting for the [United Arab Emirates], there she was, leading the strikes. Dropped the bombs on ISIS Monday night.' + +Maj. Mansouri, 35, was the first woman to join the Emirati Air Force. + +'This is really incredible,' Guilfoyle continued. + +'Major Mariam Al Mansouri is who did this. Remarkable, very excited. I wish it was an American pilot. I'll take a woman doing this any day to them. + +Right after she said this, the men on the panel began making sexist jokes. + +It comes as Britain, Belgium and Denmark on Friday joined the U.S.-led coalition of nations that are launching airstrikes on Isis. + +The European politicians flatly described the moves as critical to security on home soil, arguing that facing down terrorists has become a matter of urgency. + +Prime Minister David Cameron made a passionate plea for action in drastic terms - noting that the militants had beheaded their victims, gouged out eyes and carried out crucifixions to promote goals 'from the Dark Ages.' + +'This is about psychopathic terrorists that are trying to kill us and we do have to realize that, whether we like it or not, they have already declared war on us,' he said. 'There isn't a `walk on by' option. + +There isn't an option of just hoping this will go away.' + +Cameron told a tense House of Commons during more than six hours of debate that the hallmarks of the campaign would be 'patience and persistence, not shock and awe' - a reference to the phrase associated with the invasion of Iraq. + +That unpopular intervention has cast a shadow over the discussions because critics fear that Europe will be drawn into a wider conflict, specifically taking on the Islamic group's fighters in Syria. + +British MPs voted 524-43 for action after being urgently recalled from a recess. Belgian lawmakers also overwhelmingly approved, voting 114-2 to take part, despite widespread concerns that more terrorism may follow in their homeland as a result. + +The White House said in a statement that it welcomed the countries to the coalition. + +'These decisions - along with those by Saudi Arabia, Jordan, the United Arab Emirates, Bahrain, and Qatar to participate in airstrikes against ISIL in Syria - demonstrate the clear commitment of the international community to take action together against these terrorists,' the statement reads.","0" +"NASA: Planetary Alignment On Jan 4, 2015 Will Decrease Gravity For 5 Minutes Causing Partial Weightlessness???","via Daily Buzz Live + +Strange natural occurrences are happening in the world today. But nothing more magnificent than the one you might experience on January 4, 2015 if this story is true. + +According to British astronomer Patrick Moore, at exactly 9:47 PST AM on January 4th, Pluto will pass directly behind Jupiter, in relation to Earth. This rare alignment will mean that the combined gravitational force of the two planets would exert a stronger tidal pull, temporarily counteracting the Earth’s own gravity and making people virtually weightless. Moore calls this the Jovian-Plutonian Gravitational Effect. + +Moore told scientists that they could experience the phenomenon by jumping in the air at the precise moment the alignment occurred. If they do so, he promised, they would experience a strange floating sensation. + +Who is going to try this?? Cause I most definately am! 2 weeks from today folks!","0" +"Planetary Alignment On Jan 4, 2015 Will Decrease Gravity For 5 Minutes Causing Partial Weightlessness","Planetary Alignment On Jan 4, 2015 Will Decrease Gravity For 5 Minutes Causing Partial Weightlessness. + +Strange natural occurrences are happening in the world today. But nothing more magnificent than the one you will experience on January 4, 2015. + +According to British astronomer Patrick Moore, at exactly 9:47 PST AM on January 4th, Pluto will pass directly behind Jupiter, in relation to Earth. This rare alignment will mean that the combined gravitational force of the two planets would exert a stronger tidal pull, temporarily counteracting the Earth’s own gravity and making people virtually weightless. Moore calls this the Jovian-Plutonian Gravitational Effect. + +Moore told scientists that they could experience the phenomenon by jumping in the air at the precise moment the alignment occurred. If they do so, he promised, they would experience a strange floating sensation. + +Astronomers have long been aware that there would be an alignment of the planets on that date, when Mercury, Venus, Earth, Mars, Jupiter, Saturn, Uranus, Neptune and Pluto would be on the same side of the sun, within an arc 95° wide. But now they are guaranteeing the occurrence as the gravitational effect of the other planets on the Earth’s crust is maximum even at their closest approach. + +But don’t get too excited. If you think you’ll be able to float around your house, you’re wrong. But, if you jump in the air at 9:47 AM PST, on January 4, 2015, it should take you about 3 seconds to land back on your feet instead of the usual 0.2 seconds. + +So, mark this date on your calendar and share it with your friends! Zero gravity day is just around the corner!","0" +"Mechanical polar bear ‘threatened with ASBO for singing Christmas songs’","If Asbos weren’t out of control before, they could be now, after a six foot mechanical polar bear was allegedly threatened with one. + +Bernard the polar bear has stood outside The Loft Café, in Shefford, Bedfordshire, since December 1 and has delighted children with his Christmas inspired singing and dancing. + +But staff at the cafe were left stunned on Monday when they got a visit from local council officers. + +MORE: Nelly the neat freak! Elephant picks up litter when nobody is around + +Owners Rob and Teresa Farndon were told there had been complaints of a noise nuisance and they needed to investigate Bernard’s racket. + +Cafe worker Abbie McGee, 19, argued the bear was there for the whole of last December without any complaints but that didn’t seem to make a difference. + +‘The children love him and there’s even one woman who used to put 20p in his pocket every time she went past,’ she said. + +‘I can’t believe there have been complaints, is no-one allowed to have fun anymore? + +Central Bedfordshire Council confirmed they had visited the premises ‘on a number of occasions’ and Bernard was subject to an ‘ongoing investigation’. + +MORE: Man gets tossed, turned and injured after foolishly using closed down ride","0" +"Singing polar bear facing ASBO after noise complaint","A mechanical, singing polar bear could earn its owners an ASBO following complaints that its festive songs were causing a nuisance. + +Central Bedfordshire Council is said to be undertaking an ‘ongoing investigation’ into Bernard the bear, who performs to passers by outside The Loft café in Shefford. + + +An enforcement officer has now visited the café’s owners, warning that Bernard has been causing a public nuisance. + +A shop employee told Bedfordshire on Sunday ‘it seems really silly that someone would moan about a bear when we’re on the high street where there is constant noise from the pubs and traffic’. + +A spokesman for Central Bedfordshire Council said: ‘We have visited the premises on a number of occasions and, while Bernard has not been deemed a nuisance, we have written to both parties, explaining the situation as part of an ongoing investigation.","0" +"NEWS/ All Dogs Go to Heaven! Pope Francis Confirms Paradise Is Open to All of God's Creatures","Finally, Pope Francis confirms what we've always known: All dogs go to heaven! +During his weekly address in St. Peter's Square, the Catholic leader tried to console a little boy who was heartbroken over the death of his beloved pup. According to multiple reports, Pope Francis told the boy, ""One day, we will see our animals again the eternity of Christ. Paradise is open to all of God's creatures."" +Of course, this viewpoint goes against the conservative Catholic ideology that because animals don't have souls (!), they can't go to heaven. Some theologians have cautioned, per the New York Times, that Pope Francis ""had spoken casually, not made a doctrinal statement."" +PHOTOS: The last surviving 9/11 search dog returns to memorial site +Others within the faith, however, took the pontiff's words for what they were. ""He said paradise is open to all creatures,"" Rev. James Martin, a Jesuit persist and editor at large of America, the Catholic Magazine, told the Times. ""That sounds pretty clear to me."" +It's pretty clear, too, that Pope Francis is a friend to the four-legged. In fact, he took his papal name from St. Francis of Assisi, the patron saint of animals. +NEWS: Hero dog saves owner's life after snowmobile crash +But, back to that debate as to whether or not our furry and feathered friends have souls or not—the late Dr. James Herriot, a veterinarian and author, tackled this head-on in his story, ""The Card Over the Bed."" In it, he wrote about an encounter with ""an old woman whose only fear is that she may never be reunited with her animals after death because some people say animals have no soul."" +Dr. Herriot held the old woman's hand and told her reassuringly, ""If having a soul means being able to feel love and loyalty and gratitude, then animals are better off than a lot of humans. You've nothing to worry about there."" +Amen.","0" +"Do all dogs go to heaven? Pope tells grieving boy: 'Paradise is open to all of God’s creatures'","Is there a pet door on the Pearly Gates? + +During his weekly address in St. Peter's Square, Pope Francis comforted a young boy who was distraught over the recent death of his dog by telling him, ""One day, we will see our animals again in the eternity of Christ,"" the 77-year leader of the Roman Catholic Church said, according to Time. ""Paradise is open to all of God’s creatures."" + +The statement by the pope was welcomed by animal rights groups and humane societies across the globe, who see it as a repudiation of traditional Catholic teaching dating back hundreds of years that holds that animals can’t go to heaven because they have no souls. + +""My inbox got flooded,"" Christine Gutleben, senior director of faith outreach at the Humane Society, the largest animal protection group in the United States, told the New York Times. ""Almost immediately, everybody was talking about it."" + +Some Catholic scholars, however, have warned that the Pope’s comment was made casually and should not be taken as official Church doctrine. Others point to earlier comments that seem to suggest that Pope Francis has long held beliefs that animals can go to heaven. + +""He said paradise is open to all creatures,"" Father James Martin, a Jesuit priest and editor at large of the Catholic magazine America, told the Times. ""That sounds pretty clear to me."" + +The statement has also stirred up debate between vegan groups and their counterparts in the meat industry – with groups like People for the Ethical Treatment of Animals (PETA) saying the pope’s statement aligns with the view of heaven as a peaceful place and could convince more Catholics to avoid eating meat. + +""It’s a vegan world, life over death and peace between species,"" said Sarah Withrow King, director of Christian outreach and engagement at PETA. ""I’m not a Catholic historian, but PETA’s motto is that animals aren’t ours, and Christians agree. Animals aren’t ours, they’re God’s."" + +Pope Francis’ statement worried many in the multi-billion dollar meat industry, for whom the idea of Catholics not buying meat – especially those holiday hams and turkeys in the lead up to Christmas – equals a potentially large loss of revenue. + +""As on quite a few other things Pope Francis has said, his recent comments on all animals going to heaven have been misinterpreted,"" Dave Warner, a spokesman for the National Pork Producers Council, told the Times in an email. ""They certainly do not mean that slaughtering and eating animals is a sin.” + +Mr. Warner quoted passages from Genesis that say man is given “dominion over the fish of the sea and over the birds of the heavens and over every living thing that moves on earth."" + +Father Martin couldn't see how the pope's comments could be interpreted as a proclamation about vegetarianism, but, he said, ""[The pope] is reminding us that all cre","0" +"Pope Francis tells boy whose dog had died that heaven is open to all","Pope Francis suggested recently that even animals have a place in heaven, while trying to soothe a young boy during a public appearance at the Vatican's St. Peter's Square. + +""Paradise is open to all of God’s creatures,"" he told the boy whose dog died recently. + +He made the comment during the weekly general audience at the Vatican, in St. Peter's Square + +ANALYSIS | Pope Francis turns up the heat on church's future — behind closed doors +Vatican sparks controversy by saying gay couples have 'gifts and qualities' +ANALYSIS | Has 'rock star' Pope Francis really launched a revolution? +“One day, we will see our animals again in the eternity of Christ,” said the leader of the Catholic Church, according to Italian news sources. + +This is a significant pivot from the position held by Francis's predecessor, Pope Benedict XVI. In 2008, he said that when an animal dies, it “just means the end of existence on Earth.” + +Francis has consistently made headlines with sometimes controversial remarks since assuming the papacy in 2013. + +Vatican observers have called him a ""radical"" because of his open-mindedness and desire to reach out to ""the grassroots of Catholic life."" + +The 77-year-old leader of the world's one billion Roman Catholics has adopted more liberal positions than his predecessor, stirring up tensions with conservative Catholics on issues such as homosexuality and single motherhood. + +In one such instance in July 2013, Francis struck a compassionate tone when speaking about homosexuality. + +""If a person is gay and seeks God and has good will, who am I to judge?"" he said to reporters on a flight returning to the Vatican from Brazil. + +Francis's papal name comes from St. Francis of Assisi, the church's patron saint of animals and the ecology.","0" +"Dogs DO go to heaven… and cats, and horses: Pope assures young boy that there is a place in paradise for animals as well","The leader of the Catholic Church has assured pet lovers across the world that dogs do go to heaven. + +Speaking at his weekly address in the Vatican's St. Peter's Square, Pope Francis confirmed that there is a place in heaven for our furry friends, along with 'all of God's creatures.' + +The head of the Catholic Church had been attempting to console a distraught young boy who was mourning the death of his dog, according to Time magazine. + +Pope Francis confirmed that there is a place in heaven for dogs and 'all of God's creatures' during his weekly address in the Vatican's St. Peter's Square + +The statement is at odds with conservative Roman Catholic theology which states that animals cannot go to heaven because they have no souls. + +Francis was quoted by Italian news media as saying: 'One day, we will see our animals again in the eternity of Christ. Paradise is open to all of God's creatures.' + +The remarks have been warmly welcomed by animal rights groups such as PETA and the Humane Society. + +The issue of whether animals have the chance of an afterlife has been debated for centuries. + +Pet owners will welcome the Pope's remarks that their beloved dogs, cats, horses and other furry friends have a place in heaven + +Pope Francis has refused to meet the Dalai Lama over fears it could impact on the Catholic Church's relationship with China. + +The exiled Tibetan leader requested the meeting during a visit to Rome but it was declined 'for obvious reasons concerning the delicate situation' with China. + +The Catholic Church in China is divided in two; the official Church overseen by the Chinese Communist Party, and an underground community that swears allegiance to the Pope. + +But the main bone of contention is over which side should have the final say in the appointment of bishops. + +A Vatican official said the Pope's decision was 'not taken out of fear but to avoid any suffering by those who have already suffered'. + +The longest serving Pope - Pius IX - who was the leader of the church from 1846 to 1878 believed animals had no consciousness and therefore could not have an afterlife. + +Pope Francis's predecessor, Pope Benedict XVI, had also denied the idea of pets entering heaven and said their death simply meant the end of their existence on Earth + +But it is perhaps unsurprising that Pope Francis, aged 77, supports the idea of pets and animals having a place in paradise as he took his papal name from St. Francis of Assisi, the patron saint of animals. + +It's not the first time Francis, an Argentine Jesuit who took over from Pope Benedict XVI last year, has courted controversy. + +The leader is seen as more liberal than his predecessors and his lenient positions on homosexuality and unwed couples have caused a stir in the conservative members of the church.","0" +"Pope says dogs can go to heaven: ‘Paradise is open to all of God’s creatures’","In an effort to console a grieving boy after the death of his beloved pup, Pope Francis declared that ‘all of God’s creatures’ have a shot of ending up in heaven when they die. New York dog owners and animal lovers everywhere rejoiced at the good news. + +Delighted city dog owners agreed Friday with Pope Francis’ comforting comment to a distraught boy that the lad’s recently departed canine would be welcome in the hereafter. + +“That’s great!” said fashion designer Allina Liu as her pet pooch, Snoopy, hit the Union Square dog run. “All dogs go to heaven, right? There is no hell for dogs. + +“There is hell for people who treat their dogs badly. People who treat their animals poorly just shouldn’t have them.” + +The Pope, speaking earlier this week, offered his assurance of four-legged angels to the grieving child. + +""Paradise is open to all of God’s creatures,"" he said during the weekly papal address. + +“This marvelous plan cannot but involve everything that surrounds us and came from the heart and mind of God,” the pontiff said. + +The Pope’s stance was also hailed by animal-rights activists. Though his dog dogma appeared unexpected, there had been earlier clues to the Pope’s feelings about the animal kingdom. He took his papal name from St. Francis of Assisi, the patron saint of animals. + +Francis’ puppy views reverse opinions from previous popes, who maintained that heaven was just for human believers. + +In a 2008 sermon, Pope Benedict XVI explained that not all creatures “are called to eternity” and when non-humans die, their deaths mean “solely the end of existence on earth.” The move seemingly barred pets from paradise. + +Francis did not say if dogs could go to hell, too. + +The puppy pardon is the latest move in his apparent campaign to make the Catholic church more inclusive and tolerant. + +Earlier this year, he said gay men and women had “gifts” to offer the church, a dramatic shift in tone from the Vatican’s traditional anti-gay views. He also softened the church’s condemnation of premarital sex, cohabitation and divorce. + +Health care worker Sarah Gluck, 26, said she was not religious, but definitely approved the Pope’s words. + +“Dogs are a reflection of their owners; 99% of dogs go to heaven. But there’s always that 1%.” + +Gluck said it’s too soon to know if her 4-month-old Australian shepherd will find eternal salvation. + +“It’s hard to tell right now if Lilly is going to heaven because she’s so young,” said Gluck. “But if she goes to hell, it’ll be my fault.” + +Dog walker Donna Bruno, 32, brought beagle-bulldog Hailey and Wheaten terrier Emma to the park with her. + +She didn’t see how things could get any better for her canine charges. + +“All dogs go to heaven?” Bruno asked as she watched the pair carouse happily with their equally excited pals. + +“They’re already in heaven. Look at these guys,” she said. + +mwagner@nydailynews.com","0" +"Animal lovers abuzz over pope’s comments that 'paradise is open to all of God’s creatures'","Pope Francis has given hope to gays, unmarried couples and advocates of the Big Bang theory. Now, he has endeared himself to dog lovers, animal-rights activists and vegans. +Trying to console a distraught young boy whose dog had died, Francis told him in a recent public appearance on St. Peter’s Square that “paradise is open to all of God’s creatures.” +While it is unclear whether the pope’s remarks helped soothe the child, they were welcomed by groups such as the Humane Society and People for the Ethical Treatment of Animals, which saw them as a repudiation of conservative Catholic theology that says animals cannot go to heaven because they have no souls. +“My inbox got flooded,” said Christine Gutleben, senior director of faith outreach at the Humane Society, the largest animal protection group in the United States. +Charles Camosy, an author and a professor of Christian ethics at Fordham University, said it was difficult to know precisely what Francis meant, since he spoke “in pastoral language that is not really meant to be dissected by academics.” +But asked if the remarks had caused a new debate on whether animals have souls, suffer and go to heaven, Camosy said, “In a word: Absolutely.” +To some extent, it was not a surprise that Francis, an Argentine Jesuit who took his papal name from St. Francis of Assisi, the patron saint of animals, would suggest to a saddened child that his lost pet had a place in the afterlife. +Theologians cautioned that Francis had spoken casually, not made a doctrinal statement. +The Rev. James Martin, a Jesuit priest and editor at large of America, the Catholic magazine, said he believed that Francis was at least asserting that “God loves and Christ redeems all of creation,” even though conservative theologians have said paradise is not for animals. +The question of whether animals go to heaven has been emotionally debated for much of the church’s history. Pope Pius IX, who led the church from 1846 to 1878, strongly supported the doctrine that dogs and other animals have no consciousness. +Laura Hobgood-Oster, professor of religion and environmental studies at Southwestern University in Georgetown, Texas, said: “Historically, the Catholic Church has never been clear on this question; it’s all over the place, because it begs so many other questions. Where do mosquitoes go, for God’s sake?”","0" +"Paradise is open to all, even dogs, Pope tells boy","NEW YORK — Pope Francis has given hope to gays, unmarried couples and advocates of the Big Bang theory. Now, he has endeared himself to dog lovers, animal-rights activists and vegans. + +Trying to console a little boy whose dog had died, Pope Francis told him in a recent public appearance on St Peter’s Square that “paradise is open to all of God’s creatures”. While it is unclear whether the Pope’s remarks helped soothe the child, they were welcomed by groups such as the Humane Society and People for the Ethical Treatment of Animals (PETA). + +In his relatively short tenure as leader of the world’s one billion Roman Catholics since taking over from Benedict XVI, Pope Francis, 77, has repeatedly caused a stir among conservatives in the church. + +He has suggested more lenient positions than his predecessor on issues such as homosexuality, single motherhood and unwed couples. + +Theologians cautioned that Pope Francis had spoken casually, not made a doctrinal statement. + +Reverend James Martin, a Jesuit priest and editor-at-large of America, a Catholic magazine, said he believed that Pope Francis was at least asserting that “God loves and Christ redeems all of creation”, even though conservative theologians have said paradise is not for animals. “He said paradise is open to all creatures,” Rev Martin said. + +The question of whether animals go to heaven has been debated for much of the church’s history. Pope Benedict said during a 2008 sermon that when an animal dies, it “just means the end of existence on earth”. + +Ms Christine Gutleben, senior director of the Humane Society, said Pope Francis’ apparent reversal of his predecessor’s view could be enormous. “If the Pope did mean that all animals go to heaven, then the implication is that animals have a soul. And if that is true, then we ought to seriously consider how we treat them because they mean something to God,” she said. + +Ms Sarah Withrow King, director of Christian outreach and engagement at PETA, one of the most activist anti-slaughterhouse groups, said the Pope’s remarks could move Catholics away from consuming meat. But there are differing views. + +Mr Dave Warner, a spokesman for the National Pork Producers Council, said in an email that it “certainly does not mean that slaughtering and eating animals is a sin”. THE NEW YORK TIMES","0" +"Dead for 48 minutes, this Catholic Priest claims God is female","A Catholic priest from Massachussetts who was officially dead for more than 48 minutes before medics were able to miraculously re-start his heart has revealed a shocking revelation about God. + +According to 71-year-old cleric Father John Micheal O'neal claims that God is a warm and comforting motherly figure, whom he met in the heaven. + +Father John Micheal O'neal was rushed to the hospital on January 29 after a major heart attack, but was declared clinically dead soon after his arrival. + +With the aid of a high-tech machine called LUCAS 2, that kept the blood flowing to his brain, doctors at Massachusetts General Hospital managed to unblock vital arteries and return his heart to a normal rhythm, reported starrfmonline.com + + +He claims that at that point in his experience, he went to heaven and encountered God, which he describes as a feminine, mother-like ""Being of Light"". + +The declarations of the cleric caused quite a stir in the catholic clergy of the archdiocese over the last few days, causing the Archbishop to summon a press conference to try and calm the rumors. + +Despite the disapproval of his superiors, Father O'neal says that he will continue dedicating his life to God and spread the word of the ""Holy Mother"".","0" +"Catholic Priest Claims God Is Female After Clinically Dead Experience","After being officially dead for 48 minutes and having his heart restarted, a 71 year-old Massachusetts Catholic Priest woke up and shared that he went to heaven and met God. +Who he claimed to be a warm and Motherly figure. +Father John Micheal O’neal was rushed to a hospital after suffering a massive heart attack: and was declared clinically dead before he was revived. +Cardinal Sean P. O’Malley, The Archbishop of Boston, has said that Father O’neal suffered hallucinations linked to a near-death experience…and that God clearly isn’t a female. +The full story is here. +It might sound odd, but I don’t have a problem picturing God as a female. +And, no, it has nothing to do with the fact that my wife is a United Methodist Pastor. +But am I the only one picturing Alanis Morissette a la Dogma? +Follow me on Facebook, Twitter, or check out my blog here!","0" +"Catholic Priest Dies for 48 Minutes, Comes Back to Life and Claims God Is Female","A Catholic priest from Massachusetts was officially dead for more than 48 minutes before medics were able to miraculously re-start his heart. During that time, Father John Micheal O’neal claims he went to heaven and met God, which he describes as a warm and comforting motherly figure. + +The 71-year old cleric was rushed to the hospital on January 29 after a major heart attack, but was declared clinically dead soon after his arrival. With the aid of a high-tech machine called LUCAS 2, that kept the blood flowing to his brain, doctors at Massachusetts General Hospital managed to unblock vital arteries and return his heart to a normal rhythm. + +The doctors were afraid he would have suffered some brain damage from the incident, but he woke up less than 48 hours later and seems to have perfectly recovered. + +The elderly man claims that he has clear and vivid memories of what happened to him while he was dead. He describes a strange out-of-body experience, experiencing an intense feeling of unconditional love and acceptance, as well as being surrounded by an overwhelming light. + +He claims that at that point in his experience, he went to heaven and encountered God, which he describes as a feminine, mother-like “Being of Light”. + +“Her presence was both overwhelming and comforting” states the Catholic priest. “She had a soft and soothing voice and her presence was as reassuring as a mother’s embrace. The fact that God is a Holy Mother instead of a Holy Father doesn’t disturb me, she is everything I hoped she would be and even more!” + +The declarations of the cleric caused quite a stir in the catholic clergy of the archdiocese over the last few days, causing the Archbishop to summon a press conference to try and calm the rumors. +Despite the disapproval of his superiors, Father O’neal says that he will continue dedicating his life to God and spread the word of the “Holy Mother”. + +“I wish to continue preaching” says the elderly cleric. “I would like to share my new knowledge of the Mother, the Son and the Holy Ghost with all catholics and even all Christians. God is great and almighty despite being a woman…” + +The Roman Catholic Archdiocese of Boston has not confirmed however, if they will allow Father O’neal to resume his preaching in his former parish in South Boston. + +The Archbishop of Boston, Cardinal Sean P. O’Malley, made a public statement this morning stating that Father O’neal suffered hallucinations linked to a near-death experience and that God clearly isn’t a female.","0" +"NET Extra: Back-from-the-dead Catholic priest claims God is a female","A catholic priest from Masschussetts, who was reported dead for close to an hour before medics were able to revive him, has made a shocking revelation upon his return to life. + +The 71-years old priest, identified as, Father John Micheal O’neal, claims he went to heaven and met God, whom he describes as a warm and comforting motherly figure. + +‘Her presence was both overwhelming and comforting, she had a soft and soothing voice and her presence was as reassuring as a mother’s embrace. + +‘The fact that God is a Holy Mother instead of a Holy Father doesn’t disturb me, she is everything I hoped she would be and even more!’ + +Despite the shocking revelation, which is being received with a bit of confusion in the Catholic world, Father O’neal says he still wishes to continue dedicating his life to God and spread the word of the ‘Holy Mother’. + +‘I wish to continue preaching. I would like to share my new knowledge of the Mother, the Son and the Holy Ghost with all Catholics and even all Christians. God is great and almighty despite being a woman,’ he said. + +With his new outlook, the Roman Catholic Archdiocese of Boston is yet to confirm if Father O’neal will be permitted to resume preaching in his former parish in South Boston or not. + +Father John Micheal O’neal, who was rushed to Massachusetts General Hospital on Thursday, January 29, 2015, was revived through the aid of a high-tech machine called LUCAS 2, which kept the blood flowing to his brain as doctors managed to unblock vital arteries and return his heart to a normal rhythm, after a major heart attack. + +© NET Newspapers 2014. All Rights Reserved. Please use sharing tools. Do not cut, copy or lift any content from this website without our consent.","0" +"Catholic priest dies for 48 mins, wakes up claiming God is a woman","A 71-yr-old Catholic priest, John Micheal O’neal has claimed that God is a woman, with a warm and with a comforting motherly figure. +John Micheal O’neal from Massachussetts was said to have been declared dead for more than 48 minutes, he was miraculously revived by medics and had woken up with a shocking revelation that he had gone to heaven and met God. +Reports say Father O'neal was rushed to the hospital on January 29 after a major heart attack, but was declared clinically dead soon after his arrival. +But with the aid of high-tech machine called LUCAS 2, that kept the blood flowing to his brain, doctors at Massachusetts General Hospital managed to unblock vital arteries and return his heart to a normal rhythm. +It was gathered that doctors were afraid he would have suffered some brain damage from the incident, but he woke up less than 48 hours later and seems to have perfectly recovered. +The elderly priest claims that he has clear and vivid memories of what happened to him while he was dead. He describes a strange out-of-body experience, experiencing an intense feeling of unconditional love and acceptance, as well as being surrounded by an overwhelming light. +He claims that at that point in his experience, he went to heaven and encountered God, which he describes as a feminine, mother-like “Being of Light”. +“Her presence was both overwhelming and comforting” states the Catholic priest. “She had a soft and soothing voice and her presence was as reassuring as a mother’s embrace. The fact that God is a Holy Mother instead of a Holy Father doesn’t disturb me, she is everything I hoped she would be and even more!” +It was learnt that declarations of the cleric caused quite a stir in the catholic clergy of the archdiocese over the last few days, causing the Archbishop to summon a press conference to try and calm the rumors. +Despite the disapproval of his superiors, Father O’neal says that he will continue dedicating his life to God and spread the word of the “Holy Mother”. +The Roman Catholic Archdiocese of Boston has not confirmed however, if they will allow Father O’neal to resume his preaching in his former parish in South Boston.","0" +"Etats-Unis: Mort pendant 48 minutes, un prêtre affirme que Dieu est une femme","Et si Dieu était une femme? C'est ce qu'affirme le père John Micheal O’neal, prêtre de 71 ans dans le Massachusetts. Le 29 janvier dernier, il est amené d’urgence à l’hôpital, victime d'une crise cardiaque. Quelques minutes après son arrivée, il est déclaré cliniquement mort. Les médecins parviennent finalement à le «ramener à la vie en redémarrant son cœur, 48 minutes après qu’il s’est arrêté, rapportent plusieurs médias américains. +Le religieux américain a prétendu avoir des souvenirs clairs de ce qui lui était arrivé pendant ces longues minutes de mort clinique. Il explique avoir eu la sensation d’être sorti de son corps, entouré par une lumière écrasante, et éprouvé un sentiment d’intense amour autour de lui. Des sensations souvent évoquées par ceux qui ont fait l’expérience de mort imminente (EMI). +Dieu, une «figure maternelle chaleureuse et réconfortante» +Mais John Micheal O’neal va plus loin. Il affirme être monté au ciel et avoir rencontré le Tout-puissant. Celui-ci serait un «être de lumière», mais surtout, une «figure maternelle chaleureuse et réconfortante». +«Sa présence était à la fois immense et réconfortante», déclare le prêtre catholique. «Elle avait une voix douce et apaisante et sa présence était aussi rassurante que l'étreinte d'une mère. Le fait que Dieu soit une Sainte=Mère au lieu d'un Saint-Père ne me dérange pas, elle est tout ce que j'espérais et même plus encore». +Ces déclarations ont provoqué l’émoi dans le clergé catholique de l'archidiocèse, obligeant le cardinal Sean P. O’Malley à faire une déclaration publique, pour expliquer que Dieu n’était pas une femme et que le père O’neal avait subi des hallucinations.","0" +"Catholic Priest Dead For 48 Minutes, Is Miraculously Revived – His Revelations About God Are Even More Shocking","A Catholic priest from Massachusetts had been dead for 48 minutes before he was miraculously resuscitated. However, it is his description about God that is bound to spark a hot debate about the almighty. + +Father John Michael O’Neal was officially declared dead for more than 48 minutes, but medics were able to miraculously re-start his heart. According to the 71-year-old man of God, the supreme entity isn’t a man, as is popularly assumed and believed. Father O’Neal claims he met God during the brief time he was officially dead and God is a woman. + +The catholic father claims God is a warm and comforting motherly figure. The revelation will undoubtedly have a profound bearing on the teachings of Christianity, which firmly believes and even implies that God is a male figure who has watched over us with love and devotion. Though the love and devotion part is corroborated by Father O’Neal, he differs from the church’s teachings about the gender of God. + +Father John Micheal O’neal had the chance to meet with the divine when he was rushed to a hospital late last month owing to a massive heart attack. However, Father O’Neal was declared clinically dead shortly after his arrival. Not one to give up hope so easily, doctors at Massachusetts General Hospital kept the blood flowing to his brain with the aid of a high-tech machine called LUCAS 2. + +While the blood flowed with the help of modern science, doctors worked tirelessly to unblock vital arteries and return his heart to a normal rhythm. Consistent with near-death experiences, Father O’Neal entered heaven through a gate made of bright light and encountered God. However, instead of the all-mighty father figure, the priest claims he was warmly greeted by a motherly figure. Father O’Neal describes the divine entity as “mother-like ‘Being of Light.'” + +“Her presence was both overwhelming and comforting. She had a soft and soothing voice and her presence was as reassuring as a mother’s embrace. The fact that God is a Holy Mother instead of a Holy Father doesn’t disturb me, she is everything I hoped she would be and even more!” + +As expected, the priest’s claims about the gender of God has created quite a stir amidst devote Catholics. The intense discussion between the catholic clergy of the archdiocese about the “experience” of the father and the ramifications of his revelations persuaded the Archbishop to summon a press conference to try and calm the rumors. + +Though his superiors have disapproved, Father O’Neal says that he will continue dedicating his life to God and spread the word of the “Holy Mother.” + +“I wish to continue preaching. I would like to share my new knowledge of the Mother, the Son and the Holy Ghost with all Catholics and even all Christians. God is great and almighty despite being a woman…” + +Given the potency of Father O’Neal’s alleged experience, it is quite likely he might face some resistance and criticism. However, he is prepared, assures the priest. + +[Image Credit | India Today]","0" +"God is a woman- Priest who died for 48 minutes claims","Boston| +A Catholic priest from Massachussetts was officially dead for more than 48 minutes before medics were able to miraculously re-start his heart. During that time, Father John Micheal O’neal claims he went to heaven and met God, which he describes as a warm and comforting motherly figure. + +The 71-year old cleric was rushed to the hospital on January 29 after a major heart attack, but was declared clinically dead soon after his arrival. With the aid of a high-tech machine called LUCAS 2, that kept the blood flowing to his brain, doctors at Massachusetts General Hospital managed to unblock vital arteries and return his heart to a normal rhythm. + +The doctors were afraid he would have suffered some brain damage from the incident, but he woke up less than 48 hours later and seems to have perfectly recovered. + +The elderly man claims that he has clear and vivid memories of what happened to him while he was dead. He describes a strange out-of-body experience, experiencing an intense feeling of unconditional love and acceptance, as well as being surrounded by an overwhelming light. + +He claims that at that point in his experience, he went to heaven and encountered God, which he describes as a feminine, mother-like “Being of Light”. + +“Her presence was both overwhelming and comforting” states the Catholic priest. “She had a soft and soothing voice and her presence was as reassuring as a mother’s embrace. The fact that God is a Holy Mother instead of a Holy Father doesn’t disturb me, she is everything I hoped she would be and even more!” + +The declarations of the cleric caused quite a stir in the catholic clergy of the archdiocese over the last few days, causing the Archbishop to summon a press conference to try and calm the rumors. +Despite the disapproval of his superiors, Father O’neal says that he will continue dedicating his life to God and spread the word of the “Holy Mother”. + +“I wish to continue preaching” says the elderly cleric. “I would like to share my new knowledge of the Mother, the Son and the Holy Ghost with all catholics and even all Christians. God is great and almighty despite being a woman…” + +The Roman Catholic Archdiocese of Boston has not confirmed however, if they will allow Father O’neal to resume his preaching in his former parish in South Boston. + +The Archbishop of Boston, Cardinal Sean P. O’Malley, made a public statement this morning stating that Father O’neal suffered hallucinations linked to a near-death experience and that God clearly isn’t a female. + +This article was first published in world news daily report","0" +"God Is A Woman – Resurrected Father Narated","A 71 years old cleric Father John Micheal O’neal who was officially dead for more than 48 minutes, was re-started by medics. He claims he went to heaven and met God, which he describes as a warm and comforting motherly figure. + +Father John Micheal O’neal was rushed to the hospital on January 29 after a major heart attack, but was declared clinically dead soon after his arrival. With the aid of a high-tech machine called LUCAS 2, that kept the blood flowing to his brain, doctors at Massachusetts General Hospital managed to unblock vital arteries and return his heart to a normal rhythm. + +However, doctors were afraid he would have suffered some brain damage from the incident, but he woke up less than 48 minutes later and seems to have perfectly recovered. + +The Father also claims that he has clear and vivid memories of what happened to him while he was dead.","0" +"‘Evocative shape': Is Vladimir Putin trolling the world with his motorcade formation?","Last year, a Vine from President Obama’s trip to Israel showed just how ridiculously large his motorcade can grow. Assuming that this still really does show Russian President Vladimir Putin’s motorcade, he might not have such a large escort, but there is something a bit suggestive about the formation. + + + + + + +Please, that sort of language isn’t necessary. Besides, it’s obviously a rocket.","0" +"Putin’s motorcade looks suspiciously like a massive…","Source @reitschuster +We hope all the president’s men are trolling Putin hard here, letting their feelings known with a margin of plausible deniability. + +Although he should get that left ball-bag looked at, not sure it should be that baggy","0" +"Vladimir Putin’s Motorcade Looks Like A Massive Knob","VLADIMIR Putin’s Motorcade looks like a massive knob: +Spotter: UsVThem","0" +"Joan Rivers' doctor denies 'unauthorized procedure,' selfie before cardiac arrest","(CNN) -- Joan Rivers' personal throat doctor denies ""performing an unauthorized procedure"" before the comedian suffered cardiac arrest, a source close to the doctor told CNN. + +Dr. Gwen Korovin also ""categorically denies"" taking a selfie photo while Rivers was under anesthesia at a medical clinic, the same source said Thursday. + +The statement disputes what a source close to the Rivers death investigation told CNN -- that staff members at the clinic told investigators Korovin snapped the selfie and also performed an unauthorized procedure on Rivers. + +Rivers, 81, died a week after suffering cardiac arrest during an appointment at Manhattan's Yorkville Endoscopy clinic. + +CNN's source close to the investigaton also provided new details Thursday, including that a sedated Rivers was visible in Korovin's procedure room selfie. + +Clinic workers told investigators they heard Korovin make a statement to the effect that Rivers ""will think this is funny"" or ""would love this"" as she took the photo, the source said. + +Investigators do not have access to the phone Korovin used to take the photo, the source said. + +The source also provided more specific information about what procedures were done on Rivers. + +Several clinic workers told investigators that it began with Korovin performing a laryngoscopy, which involves using a device to view a patient's vocal folds. + +Gastroenterologist Dr. Lawrence Cohen, who was the medical director of the clinic until resigning in the wake of Rivers' death, then performed an endoscopy intended to diagnose why she was suffering a sore and hoarse throat, the source said. + +Cohen detected something of concern, the source said.. + +Korovin then began a second laryngoscopy to again view River's vocal cords, the source said. It was at that time that her vocal cords began to swell, leading to a cut off of oxygen to her lungs and ultimately to cardiac arrest, according to the source. + +Rivers was rushed by paramedics from Yorkville Endoscopy to New York's Mount Sinai Hospital a mile away, where she was kept on life support until she died a week later. + +Korovin was only authorized to observe Cohen, who performed the procedure since she was not certified by Yorkville Endoscopy clinic, as required by New York health law, the source said. + +Investigators have found no prior consent form signed by Rivers authorizing a procedure by Korovin, the source said. It was unclear if Rivers had given verbal consent to the biopsy before being sedated. + +Korovin is well known for helping an impressive list of celebrities with voice trouble. The list of famous patients who have sung her praises include actors Hugh Jackman and Nathan Lane and singers Celine Dion, Lady Gaga and Ariana Grande. + +The walls of Korovin's Manhattan medical office are covered with autograph photos, including from operatic tenor Luciano Pavarotti, Broadway star Barbara Cook and actress-singer Julie Andrews. + +""I've always been fascinated by the human voice and music,"" Korovin, 55, is quoted telling the New York Daily News in a profile story last year. + +Korovin's lawyer sent a statement to CNN Thursday in response to the reports: + +""Gwen S. Korovin, M.D. is a highly experienced, board certified otolaryngologist. She maintains privileges at one of the city's most prestigious hospitals. She is respected and admired by her peers in the medical community and she is revered by her patients. + +""As a matter of personal and professional policy, Dr. Korovin does not publicly discuss her patients or their care and treatment. Further, Dr. Korovin is prohibited by state and federal confidentiality laws from discussing her care and treatment of any particular patient. + +""For these reasons, neither Dr. Korovin nor her attorneys will have any public comment on recent press reports regarding her practice. We ask that the press please respect Dr. Korovin's personal and professional policy of not discussing her patients, as well as the privacy of her patients."" + +The clinic is still open, although an accreditation group is calling for it to suspend procedures and surgeries, according to letters obtained by CNN. Patients were seen in the clinic's waiting room Wednesday. + +The American Association for Accreditation of Ambulatory Surgery Facilities (AAAASF) sent representatives for an unscheduled visit to the clinic after hearing about Rivers' cardiac arrest, according to letters from the group. + +The letters cited two ""deficiencies"" found by the representatives, declared the clinic to be in ""immediate jeopardy"" and placed it on ""emergency suspension."" The accreditation group said the clinic should stop procedures and surgeries ""until accreditation questions are settled."" + +The clinic sent CNN a statement Wednesday night in response to questions about the accreditation association's letter putting the facility under ""emergency suspension."" + +""Yorkville Endoscopy continues to maintain its federal, state and Quad A (AAAASF) authorization to be operational and provide patient care. Yorkville Endoscopy is committed to adhering to the standards established by Quad A (AAASF),"" the statement said. + +While the accreditation agency has no power to shut a clinic down, the state of New York does. State health investigators also found deficiencies in Rivers' treatment, according to a source close to the death investigation. These include the participation of River's personal throat doctor. + +Timeline emerges in Joan Rivers' death + +Yorkville Endoscopy issued a statement last Thursday denying reports that any vocal cord biopsy has ever been done at the clinic, although federal privacy law prevented any patient information from being released. + +The day after the denial was issued, the clinic confirmed that Cohen ""is not currently performing procedures. ... Nor is he currently serving as medical director."" + +The source said that at this time neither Cohen nor the ear, nose and throat doctor have been accused of wrongdoing by investigators. + +The clinic declined to respond to the source's comments about a biopsy or a selfie, citing federal privacy law. + +As my son Cooper and I mourn the loss of my mother, we want to thank everyone for the beautiful cards and flowers co... http://t.co/FKPejY4nQz + +Melissa Rivers has been silent since her mother's death on September 4, although she did post an online message thanking friends and fans Wednesday evening. + +""As my son Cooper and I mourn the loss of my mother, we want to thank everyone for the beautiful cards and flowers conveying heartfelt messages and condolences, which continue to arrive from around the world and through social media. My mother would have been overwhelmed by the scope and depth of the love that people have expressed for her. It is certainly helping to lift our spirits during this time. + +""We are forever grateful for your kindness and support in continuing to honor my mother's legacy, and for remembering the joy and laughter that she brought to so many."" + +CNN's Lena Jakobsson contributed to this report.","0" +"'Throat specialist to the stars' allegedly involved in fatal Joan Rivers procedure denies taking selfie with star as she releases statement saying she will not comment on tragic incident","Dr Gwen Korovin was inside Yorkville Endoscopy clinic when the star died + +Is alleged to have taken a selfie with her before she went into cardiac arrest + +Sources close to the doctor, 56, say reports she took photo are 'lies' + +Statement by her attorneys says she's 'respected and admired by peers' + +56-year-old ENT was not supposed to be in the room during the procedure + +'Lies': Dr Gwen Korovin insists reports she took a selfie with Joan Rivers before she went into cardiac arrest are not true + +Joan Rivers' personal doctor has said reports she took a selfie with the star before the procedure that allegedly killed the comedienne are 'lies'. + +Dr Gwen Korovin - who was not authorized to be in the room at the time of the fatal treatment - has also released a statement saying she has 'no comment' to make about the tragic incident. + +Reports suggest the 'throat specialist to the stars' took a photo of the 81-year-old inside Yorkville Endoscopy clinic on August 28 before the star stopped breathing while undergoing a procedure on her vocal cords. + +However sources close to the ENT have accused CNN - who originally published the story - of 'making up lies'. + +According to TMZ she has also denied performing a biopsy on Joan. However it is unknown whether she performed any other procedure while in the room. + +Attorneys from Abrams and Fensterman acting on behalf of the medical professional released a statement today, saying she is 'respected and admired' in the medical community, but will not be discussing the incident. + +It read: 'Gwen S. Korovin M.D. is a highly experienced, board certified otolaryngologist. She maintains priveleges at one of the city's most prestigious hospitals. She is respected and admired by her peers in the medical community and she is revered by her patients. + +'As a matter of personal and professional policy, Dr Korovin does not publicly discus her patients or their care and treatment. Further, Dr Korovin is prohibited by state and federal confidentiality laws from discussing her care and treatment of any particular patient. + +'For these reasons, neither Dr Korovin nor her attorneys will have any public comment on recent press reports regarding her practice. We ask that the press pleases respect Dr Korovin's personal and professional policy of not discussing her patients as well as the privacy of her patients.' + +The doctor who counts Hugh Jackman, Julie Andrews, Lady Gaga, pop princess Ariana Grande and Celine Dion among her celebrity patients, is an esteemed ear, nose and throat specialist based in Manhattan. + +Joan arrived at the Upper East side clinic for an endoscopy with gastroenterologist Dr. Lawrence Cohen, Yorkville's medical director, on the morning on August 28. She died on September 4. + +The procedure was intended to help diagnose her hoarse voice and sore throat, and involved the insertion of a camera down her throat. + +An ear, nose and throat specialist - who was not certified by the clinic, as required by law - then performed a biopsy on the star's vocal cords. + +The doctor was described by the source as Joan's personal ENT specialist who is reported to be Dr Korovin. + +Scroll down for video + +Response: The 56-year-old, pictured outside her Manhattan home this weekend, has released a statement via her lawyers which says she cannot comment on the tragic incident which led to the 81-year-old's death + +'Specialist to the stars': Dr Korovin counts celebrities including Hugh Jackman - who performed at Joan Rivers' funeral, Daniel Radcliffe (pictured in frame), Lady Gaga and Ariana Grande among her clients + +It has been reported that Joan's vocal chords began to swell during the biopsy, cutting off the flow of oxygen to her lungs, which led to cardiac arrest. + +The comedienne was then rushed to nearby Mount Sinai hospital from the clinic. + +However, she never regained consciousness and died days later after being taken off life support and spending her final days with her daughter Melissa Rivers by her side and her loved ones paying their final respects. + +Dr Korovin has been earmarked as one of the top specialists in the country and is the choice of many celebrities. She has even been involved in a documentary with Celine Dion. + +During a clip from the program, Dr Gwen Korovin is seen conducting an laryngoscopy on the Canadian singer, using a camera to examine Dion's vocal chords as she sings a few notes. + +The two go on to share a few laughs in Dr Korovin's clinic room, covered with framed photos of her famous clientele. + +Dr Korovin is pictured with comedienne Joy Behar at the Celebrity Dinner Talkfest held at the New York Friars Club in June 2011","0" +"Doc calls macabre 'selfie' claims completely crazy","If the bizarre story about Joan Rivers' doctor pausing to take a ""selfie"" in the operating room minutes before the 81-year-old comedienne went into cardiac arrest on August 29 sounded outlandish, that's because it was. +So says Dr Gwen Korovin, Rivers' personal physician who on Thursday night shot down a CNN report claiming Korovin was so star-struck she took the opportunity of her celebrity patient being unconscious to snap a souvenir photo of the two of them together. + +CNN, citing sources close to the investigation being carried out by the medical examiner's office, is standing by its claim that a sedated Rivers was clearly visible in Korovin's procedure room selfie - an allegation Korovin's lawyers are calling ""lies"". + +Korovin, (known as the ""patron saint of Broadway singers and actors"" for her work tending to the likes of Lady Gaga, Hugh Jackman, Julie Andrews, Celine Dion, Mick Jagger and Luciano Pavarotti) also ""categorically"" denied performing an unauthorised biopsy on Rivers which, according to multiple published reports, caused the heart attack that killed the beloved New Yorker during what should have been a routine medical procedure. + +Whatever Rivers would have made of the escalating drama surrounding her mysterious death, those close to her say she would be thrilled by the news that Vanity Fair scribe Leslie Bennetts has been signed to write her biography, due out early next year. + +""Joan Rivers' life story was, in every way, a remarkably dramatic roller-coaster ride characterised by triumphant highs and devastating lows, one that is both wildly entertaining and deeply moving,"" Bennetts said in a statement. ""It's hard to imagine a more compelling subject for a book or one that would be more fun."" And lucrative. Within hours of Rivers' death, sales of her latest book (Diary of a Mad Diva) shot up an impressive - and record-breaking - 70,750pc on Amazon. + +Lost in translation + +Garth Brooks seems to think his Irish fans weren't that put out by the Croke Park debacle. In the run-up to his latest seven-performance run, which kicked off in Atlanta on Friday night, the self-effacing singer-songwriter made reference to his cancelled Irish gigs when asked what the secret is behind his ongoing appeal. + +""I wish I could explain it: Of course - I'm beautiful, are you kidding me? I'm talented,"" the 52-year-old joked with reporters. ""But I don't get it...If the Garth guy shows up or not, these guys are still going to have the same great time,"" he said, using his Irish fans as a case in point. ""We saw video footage of people in Ireland, at a bar the night we were supposed to be there, singing Friends in Low Places and they were having the time of their lives... It's like it's their show."" As if. + +Dowd deals with pot shots + +Pulitzer prize-winning journalist Maureen Dowd is on quite a high after learning that she has been cast as the poster girl for a new ""Consume Responsibly"" edible pot publicity campaign. + +The 62-year-old New York Times op-ed columnist, who got (unintentionally) stoned last summer while researching a story about Colorado's recent decision to legalise the use of recreational marijuana, doesn't even mind that the pro-pot brigade are making fun of her nightmare experience with cannabis to warn rookies about the dangers of overdosing. + +Dowd, who decided to test the benefits of pot with a few bites of a weed-infused chocolate bar wrote about the results (""What could go wrong?"") in a column (titled ""Don't Harsh Our Mellow, Dude"") which was published in June, graphically recalling how - an hour after ingesting the bar, things went haywire. + +""I barely made it from the desk to the bed, where I lay curled up in a hallucinatory state for the next eight hours... I was panting and paranoid, sure that when the room-service waiter knocked and I didn't answer, he'd call the police and have me arrested for being unable to handle my candy,"" she wrote. + +""As my paranoia deepened, I became convinced that I had died and no one was telling me."" + +A medical consultant would later tell Dowd that marijuana candy bars ""are supposed to be cut into 16 pieces for novices,"" a point she used to condemn the marijuana industry for promoting the drug without safety precautions for first-time users. + +On Wednesday, the advocacy group Marijuana Policy Project (MPP) responded to Dowd's criticism by unveiling a giant billboard featuring a red-haired woman (who looks exactly like the writer) obviously worse for wear on a hotel room bed. ""Don't let a candy bar ruin your vacation,"" reads the tagline. ""With edibles, start low and go slow."" + +Dowd, who wasn't in the slightest fazed at her likeness or her story being used in the ad said she has her own plans for artwork from the billboard. + +""I'm going to make it my Christmas card. Now,"" she said, adding dryly, ""onto gun control.""","0" +"Joan Rivers Doctor Denies Selfie","In a typical case of he-said-she-said, Joan Rivers’ personal doctor, Gwen Korovin, is disputing the rumors that she took a selfie with the unconscious comedian shortly before her death. A source at Yorkville Endoscopy, the New York clinic where Rivers went for a routine endoscopy, allegedly told CNN that Korovin snapped the selfie before performing an unconsented biopsy that led to respiratory and cardiac arrest. Sources for Korovin claim the statements regarding the photo are completely false and that no biopsy was performed. The doctor, who is the “go-to ENT in NYC,” did not respond when questioned if she performed another procedure instead.","0" +"Joan Rivers’s Personal Doctor Denies Taking Operating-Room Selfie","According to TMZ, Joan Rivers's personal doctor, Gwen Korovin, has denied CNN's allegations that she took a selfie in the operating room while the 81-year-old was under anesthesia, saying that the network's source is ""making up lies."" Korovin also denied performing the unauthorized biopsy that allegedly caused Rivers to go in to cardiac arrest. TMZ claims that it ""pressed to find out if she performed some other procedure"" but did not receive an answer.","0" +"Gwen Korovin, Joan Rivers’s doctor, denies taking selfie","Gwen Korovin, Joan Rivers’s personal ear, nose and throat doctor who allegedly performed an unauthorized procedure on the late comedian while she was under anesthesia for an endoscopy, has denied taking a selfie with Rivers while she was in the procedure room. + +According to a report by CNN, Korovin “categorically denies” taking the selfie, and also denies performing the unauthorized procedure on Rivers. Days ago, CNN reported that clinic employees told investigators the doctor took the photo and performed said procedure. + +Said CNN: + +CNN’s source close to the investigation also provided new details Thursday, including that a sedated Rivers was visible in Korovin’s procedure room selfie. Clinic workers told investigators they heard Korovin make a statement to the effect that Rivers “will think this is funny” or “would love this” as she took the photo, the source said. Investigators do not have access to the phone Korovin used to take the photo, the source said. + +Rivers went to Yorkville Endoscopy on Aug. 28 to find out why she had a sore throat and her voice was hoarse. CNN’s sources maintain Rivers stopped breathing when her vocal cords began to swell, and she went into cardiac arrest. Rivers died Sept. 4 at age 81 after going on life support at Mount Sinai Hospital. + +Previous reports stated Rivers stopped breathing after a botched attempt at a biopsy. CNN is now reporting that she stopped breathing after Korovin attempted a second laryngoscopy following an endoscopy. Korovin also performed a laryngoscopy prior to the endoscopy. + +Here’s the letter Korovin’s lawyer sent to the network: + +Gwen S. Korovin, M.D. is a highly experienced, board certified otolaryngologist. She maintains privileges at one of the city’s most prestigious hospitals. She is respected and admired by her peers in the medical community and she is revered by her patients. As a matter of personal and professional policy, Dr. Korovin does not publicly discuss her patients or their care and treatment. Further, Dr. Korovin is prohibited by state and federal confidentiality laws from discussing her care and treatment of any particular patient. For these reasons, neither Dr. Korovin nor her attorneys will have any public comment on recent press reports regarding her practice. We ask that the press please respect Dr. Korovin’s personal and professional policy of not discussing her patients, as well as the privacy of her patients.","0" +"Here Are Microsoft's New Robot Security Guards","Robots are increasingly replacing humans in a variety of mundane tasks, like bolting a car together or making lollipops, but now they are moving into the security business. + +Microsoft recently installed a fleet of 5-feet-tall, 300-pound robots to protect its Silicon Valley campus. The robots are packed with HD security cameras and sensors to take in their organic, protein-based surroundings. There’s also an artificial intelligence on board that can sound alarms when the robot notices something awry. It can also read license plates and cross-reference them to see if they’re stolen. + +The K5 robots come from a California company called Knightscope, which calls the robots “autonomous data machines” that provide a “commanding but friendly presence.” Sounds like something a robot manufacturer would say. + +Let’s be honest though, the robots look pretty damn cool. They’re like modern versions of R2-D2. + +Thankfully—or sadly, depending on how you look at it—the K5 robots don’t have any weapons on them. All they can do is assess a situation, sound an alarm to defuse it, or call a human security officer to the scene. There are, however, plans equip the robots with tasers sometime in the future. + +Microsoft’s new protectors are fairly autonomous. A single charge will last 24 hours, and if the robot notices that its battery is getting low, it will return to a charging port and plug itself in. It can fully recharge in 20 minutes, which is pretty insane. + +There are plans to one day expand the use of Knightscope’s robots and have them patrol the streets as part of human police units. We can’t even imagine what would happen if Elon Musk heard about this. + +H/T Extreme Tech | Videos/Photos: © Knightscope, Inc. 2014 (www.knightscope.com) + +This article originally appeared at The Daily Dot. Copyright 2014. Follow The Daily Dot on Twitter. + +SEE ALSO: This Terrifying Robot Was Developed By Google","0" +"Robot security guards now patrolling Microsoft's Silicon Valley campus","A California company is hoping to revolutionize the security business with autonomous robots. + +The Knightscope K5 is one of four drones now patrolling Microsoft's Silicon Valley Campus. + +Matt Stambaugh, the Calgary Eyeopener's science and technology columnist, spoke about how the five feet tall robots learn. + +""You take them to an area, apparently an operator has to walk around the perimeter where they're supposed to patrol once, then they go about learning their environments,"" said Stambaugh. ""What they're using is a variety of different sensors essentially to take the role of what a lot of private security contractors do today."" + +According to Stambaugh, the robots are capable of detecting anomalies and making decisions. + +""It's not quite as advanced as what Google is doing with their self-driving car, but they've got different sensors on board to make a map of the area and then they've got code on board to decide what is something that should be reported back."" + +""They've got thermal imaging if you need. They've got chemical sensors, licence plate recognition software [and] facial recognition software,"" said Stambaugh. ""It looks kind of like a large Roomba. And so instead of looking for dust bunnies it's looking for, you know, criminals."" + +K5s to hit the market in 2015 + +According to Stambaugh, the robots will be hitting the market starting 2015. + +""What the company Knightscope is trying to do is to lease these out on a per-hour basis,"" said Stambaugh. ""So $6.25 an hour they'll lease you one of these K5s and that's about half the price of the average security guard."" + +There are many advantages to a robot over a human patrol. + +""They'll work triple shift, 24 hours a day. The battery is supposed to last around a day and when it runs out they go back to a charging carpet and in 20 minutes they are charged up again."" + +Stambaugh also said the robots do not have any weapons, but that may change in the future. + +""Basically what it's doing is calling back to a manned response centre if something is going wrong,"" he said.","0" +"Microsoft Hires Dalek-style Robocops to Guard Silicon Valley HQ","Computing giant Microsoft is one of the Silicon Valley companies that has hired robot security guards to protect and serve the streets around northern California's technology hub. + +The Knightscope K5 robot security guards are fitted with lasers, GPS and heat-detecting technology, and can predict where criminals will strike next and the likelihood of future crimes. + +Unlike human security guards, the egg-like Knightscopes are not armed(Knightscope) + +The 5ft tall robots are designed to operate without human control and are equipped with surveillance cameras and sensors, a thermal imaging system, scanners that can read 300 car registration plates a minute, and odour detectors. It patrols the streets using lasers to gauge distance and a GPS system. + +The robots analyse information from government, businesses and social media sources to predict the likelihood of a crime being committed in a given area, and decide whether the alert authorities it if comes across anything suspicious. + +Four of the robot security guards have been deployed to guard Microsoft's Silicon Valley campus, in the system's first real mission. + +It appears to be going well, although the robots have come unstuck in the face of a seemingly innocent adversary: steps. + +Rachel Metz, a reporter for MIT Technology Review, said: ""I noticed that a K5 in the distance had somehow toppled over the edge of the sidewalk onto the parking-lot asphalt several inches below. A couple of Knightscope folks were needed to pull it upright."" + +Well, if Doctor Who's mortal enemies can't handle stairs, what chance to these youngsters have? + +RelatedUnderwater Robot Dolphins Used to Study How Shrinking Antarctic Glaciers Are MeltingCBI and Ricoh: New World Order of Robots Will Help, Not Steal, British JobsRobots to Steal 10 Million Low Paid UK Jobs by 2034People Not Robots Campaign Aiming to Shut Electronics Industry Death-traps","0" +"Microsoft's Silicon Valley campus now guarded by Daleks","If you ever visit the Microsoft campus in the Silicon Valley and hear a mechanical voice shout ""Ex-ter-min-ate!"", don't be too spooked. It just means some geek humor has gone a little crazy. + +Microsoft's campus in Silicon Valley will be patrolled by a team of five security guard robots from a company called Knightscope. The robot, dubbed K5, is five feet tall, weighs 300 pounds, and looks disturbingly like the Daleks of ""Doctor Who"" fame. + +Fortunately, they are not armed with lasers. They use cameras and sensors to monitor their assigned area and look for suspicious activity. They are armed with high-definition cameras and audio recorders, able to record events and voices, analyze faces, read license plates, and even detect biological and chemical agents. + +The K5s also use laser scanning and GPS for navigation, have weather sensors, and communicate via Wi-Fi. Their batteries run for about 24 hours and the K5 will return to a dock/power station to recharge. + +Should they spot a problem, they call a human security guard. I'm just waiting for Knightscope to decide to cut out the middle man. Or for bored Microsofties to try and hack the thing to play pranks on people. + +That sounds like the plot of a bad SyFy movie, doesn't it?","0" +"Microsoft turns to robotic security guards to watch for trouble","OK, so the robot apocalypse probably won’t happen any time soon, but the new robot sentries guarding Microsoft’s Silicon Valley campus seem like something straight out of a futuristic sci-fi movie. + +According to ExtremeTech, each of the K5 security guard robots from robotics company Knightscope stands 5 feet tall and weighs 300 pounds, so you probably don’t want to mess with one. + +The K5 robots don’t come with any weapons onboard—thankfully—but they use a suite of alarms, sirens, and cameras to monitor and patrol the grounds of Microsoft’s campus. If one spots trouble, it’ll either sound an alarm or dispatch a human security guard to its location. + +ExtremeTech notes that the K5 can run for up to 24 hours on a single charge, and can recharge in only about 20 minutes. Its battery won’t die out in the field, though—these bots will return to the charging station by themselves when their batteries start to run dry. + +The story behind the story: Robots are playing an increasingly large role in security and military operations. Google-owned robotics company Boston Dynamics, for example, has been working with DARPA to develop various robots to aid soldiers in combat settings. Meanwhile, South Korea deployed a robotic sentry to guard its side of the Demilitarized Zone in 2010. Unlike K5, though, South Korea’s guard robot came fully armed.","0" +"Microsoft Tried Out Robot Security Guards on Its Silicon Valley Campus","It seems like robots are everywhere these days, and now they’re rolling around Microsofts Silicon Valley campus R2-D2-style to fight crime and keep everyone safe. At least that’s the idea behind a pilot program the company ran last week to test a fleet of five K5 security guard robots. + +Designed and manufactured by robotics company Knightscope, K5s weigh 300 pounds and are 5 feet tall. They use cameras and sensors to keep track of their surroundings and look for suspcious activity. They can “see” license plate numbers and even analyze faces. While K5s aren’t equipped with weapons (and can’t run or get in someone’s face anyway), they do have onboard alarms and sirens to alert people if something bad is going on. And if they spot something that a person should handle, they can call a human security guard over. The K5s also use laser scanning and GPS for navigating, weather sensors, and, of course, Wi-Fi connectivity. + +Stacy Stephens, Knightscope’s co-founder and vice president of sales and marketing, told MIT Tech Review, “This takes away the monotonous and sometimes dangerous work, and leaves the strategic work to law enforcement or private security, depending on the application.” + +K5s are mostly meant for spotting strange or unusual behavior, but if you’re in trouble you can also use them to call for help. They have battery life of about 24 hours and can automatically bring themselves back to their charging stations when they’re low on juice. And it’s true that there’s artificial intelligence coordinating an A5’s actions and making decisions about where it should go and what it should do next. But reaction to the robots seems kind of alarmist. + +ExtremeTech writes that by testing the robots, Microsoft is “[s]howing a rather shocking disregard for the long-term safety of human civilization.” That and other comments might be meant as tongue-in-cheek, but the A5s don’t seem any different from the robot guards South Korea piloted in prisons in 2012 or even Boston Dynamics’ Atlas robot, which is designed to be used in dangerous situations like natural disaster relief or fire rescues. + +If they were armed, A5s might seem scarier, but as eyes and ears that never get tired and can just endlessly putter around a big campus, A5s seem like a reasonable solution.","0" +"Knightscope Security Robots Are Keeping Microsoft Campuses Safe (and They Look Really Scary)","While Daleks ""know no fear"" and ""must not fear,"" the cold, calculating robots from the Dr. Who series don't exist in the real world yet and Microsoft has had to settle on the next best thing for securing its campuses: the K5. + +Microsoft is the first company in Silicon Valley to dispatch a fleet of the K5 policing robots. Each 5-foot tall, 300-pound K5 is equipped with arrays of high-definition camera, sensors, debilitating sirens, Wi-Fi and artificial intelligence. + +The squat policing robots are the product of Knightscope, a startup firm from Mountain View, Calif. William Santana Li, chairman and CEO of Knightscope, sees a world in which his company's policing robots move out of the private sector and start working alongside law enforcement officers. + +""Technology and robotics are making the concept of Precision Policing -- a systematic, proactive and almost precognitive approach to ensuring public safety -- a real possibility,"" said Li in a March blog post. + +The K5s can use their sensors to track down threats and their Wi-Fi connection to call in bipedal backup, aka security guards. Their AI and camera rigs enable the K5s to do a good deal of profiling, scanning license plates and faces to compare against databases available to them over Wi-Fi. + +The K5 robots are only tools to surveil, assess and report suspicious activity, for now at least. There are plans in the works that could see the K5s brandishing and using Taser guns -- ""you are being neutralized."" + +The K5s sensors enable them to recognize and analyze alphanumeric text, heat signatures, sounds, air quality and infrared light. The robots are equipped with both radar and Lidar to help them make measurements, while GPS helps them maintain their bearing and report their positions. Lidar, which stands for light detection and ranging, is a remote-sensing technology used to measure distance by illuminating a target with a laser and then analyzing the reflected light. + +The robots are fully autonomous and can even refuel at a charging station without the guidance of humans. The K5s leverage their machine learning abilities for predictive analytics, analyzing and accounting for risks in real time. + +To keep people assured that the machines aren't abusing their abilities or beginning to learn too much, Knightscope plans to let people keep an eye on the machines by making the K5s' video feeds available to the public online. + +""I believe robots are the perfect tools to handle the monotonous and sometimes dangerous work in order to free up humans to more judiciously address activities requiring higher-level thinking, hands-on encounters, or tactical planning,"" states Li.","0" +"'Dear Sandwich Thief': Man's hilarious response to passive-aggressive sign posted on his office's fridge door sparks incredible kitchen note war","The anonymous note between office colleagues was posted on Facebook + +It was shared from a New Zealand radio station and went viral + +It is a hilarious note war between the colleagues over a stolen sandwich + +The notes were posted on a fridge door in an office kitchen + +A frustrated office worker's request to a colleague to stop pinching their lunch from the fridge has sparked a hilarious note war between the two. + +The A4 notes pinned to the fridge door of an office kitchen have gone viral on a New Zealand radio Facebook page due to the hilarious content contained on them. + +What starts as a simple request to the 'turkey and Swiss on Rye' owner to the 'sandwich thief' to stop stealing their lunch, soon turns into an anonymous office stand-off with several demands being traded. + +The passive-aggressive note which started the war between the two office workers + +The first demand from the anonymous thief, which infuriates the sandwich thief even further + +A return threat from the owner of the 'Turkey and Swiss on Rye' that they will bring HR in to conversation + +'To the person who keeps stealing my sandwiches (Turkey and Swiss with mayo on Rye)...' the first of many passive-aggressive notes reads. + +'Stop stealing other people's property!!!' + +What follows is one of several demands from the thief to pay $10 and leave it in the fridge in return for the person's lunch - or they'll 'never see it undigested again.' + +The thief, a man, includes a picture of him holding a portion of the 'Turkey and Swiss on Rye' - one of many he posts picture with him holding it to prove he has it in his possession. + +Refusing to take the sandwich owner's advice to be a 'responsible adult' seriously, he further infuriates 'Turkey and Swiss on rye' who threatens the thief with human resources action. + +The conversation loses its professionalism along the way and becomes increasingly personal, before 'Tina from HR' wades in with a note to the sandwich owner. + +'Please return the sandwich to the owner and we won't investigate this any further,' Tina writes. + +To which the thief replies: 'Buy me a pizza.' + +Tina responds: 'No' + +The image of the sandwich thief threatening to continue devouring the person's lunch if they don't put $10 in the fridge + +The defeated sandwich owner asks... + +More evidence that the man is in possession of the sandwich + +The owner follows through on his threat to contact HR and a letter from Tina appears on the fridge door + +The thief takes his demands to the top + +Who would have thought? Tina refuses + +The three-way dialogue continues until the thief posts a lengthy note with an image of an empty plate proving that he has devoured the sandwich in full. + +It is at this point the alleged thief, 'Francis', is finally found out when Tina traces the printed A4 sheets back to his account. + +'Francis we checked the office printer queue and traced the requests back to your desk. Could you please see me at your earliest convenience.' + +The hilarious note war winds up with Francis grovelling for his job with a simple one-line request pleading not to be fired. + +'Please don't fire me.' + +The thief rubs it in even more + +The sandwich owner cracks with their first personal spray at the thief + +The thief devours the sandwich and posts the finished meal + +Caught out: Francis's cover is blown + +In fine print the thief grovels to Tina not to fire him","0" +"Office sandwich thief is caught after hilarious 'note war' reaches fantastic finale","The stand-off between an office worker, known only as 'Turkey and Swiss on Rye' and their colleague, 'Sandwich Thief' has become an internet hit + +This office note battle between a cheeky sandwich thief and their jobsworth nemesis might just be the funniest thing you read all day. + +If you've ever worked in an office, you'll be familiar with those who are possessive about their lunch and partial to a passive-aggressive note. + +And if those people annoy you, this funny note war should give you a giggle. + +The battle breaks out when someone has a sandwich stolen from the office fridge. + +Clearly irked, they leave their light-fingered a note, telling them to stop stealing. + +And the subsequent string of letters between the two doesn't disappoint. + +Check out the hilarious exchanges between the two below. + +(function(d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = ""//connect.facebook.net/en_US/all.js#xfbml=1""; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); Post by MORE FM. + +Then the sandwich thief explained his demands. + +(function(d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = ""//connect.facebook.net/en_US/all.js#xfbml=1""; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); Post by MORE FM. + +But the note-leaver wasn't happy, threatening to call human resources. + +(function(d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = ""//connect.facebook.net/en_US/all.js#xfbml=1""; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); Post by MORE FM. + +So the threats elevated, and Sandwich Thief showed he wasn't going to back down. + +(function(d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = ""//connect.facebook.net/en_US/all.js#xfbml=1""; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); Post by MORE FM. + +The note-leaver was getting desperate. He began pleading for mercy. + +(function(d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = ""//connect.facebook.net/en_US/all.js#xfbml=1""; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); Post by MORE FM. + +The demands become ever more ruthless. It's unclear whether Liam Neeson will hold on to his starring role in Taken 3. + +(function(d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = ""//connect.facebook.net/en_US/all.js#xfbml=1""; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); Post by MORE FM. + +But then... + +(function(d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = ""//connect.facebook.net/en_US/all.js#xfbml=1""; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); Post by MORE FM. + +Sandwich Thief backs down for no-one. Especially not 'Tina from HR'. + +(function(d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = ""//connect.facebook.net/en_US/all.js#xfbml=1""; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); Post by MORE FM. + +Notice the subtle font change. Things are getting serious. + +(function(d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = ""//connect.facebook.net/en_US/all.js#xfbml=1""; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); Post by MORE FM. + +And Sandwich Thief starts to get cocky... + +(function(d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = ""//connect.facebook.net/en_US/all.js#xfbml=1""; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); Post by MORE FM. + +We're back to Comic Sans. You can almost read the note-leaver's tears. + +(function(d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = ""//connect.facebook.net/en_US/all.js#xfbml=1""; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); Post by MORE FM. + +So Sandwich Thief reveals his motives... + +(function(d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = ""//connect.facebook.net/en_US/all.js#xfbml=1""; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); Post by MORE FM. + +But his moment of glory is trampled on. + +(function(d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = ""//connect.facebook.net/en_US/all.js#xfbml=1""; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); Post by MORE FM. + +It turns out you shouldn't mess with Human Resources. + +(function(d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = ""//connect.facebook.net/en_US/all.js#xfbml=1""; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); Post by MORE FM. + +Poll loading …","0" +"Lunch theft prompts ransom note from sandwich thief","CHICAGO (FOX 32 News) - A frustrated office worker recently called out his colleague for stealing his lunch, prompting a response from the ""sandwich thief"" himself. + +The frustrated worker posted a sign on the fridge saying, ""To the person who keeps stealing my sandwiches (turkey and Swiss with mayo on rye), this is ridiculous. We are full grown adults, not children. Please take responsibility for your actions and stop stealing other people's property!"" + +The sandwich thief then came back with a response, asking for ransom money for the stolen turkey and Swiss on rye. + +""Dear turkey and Swiss on rye, I have your precious sandwich. It's safe. For now. Put 10 dollars on the plate in the fridge or you'll never see it undigested again."" + +HR then got involved in the situation and told the alleged thief to give back the sandwich and it won't be investigated. +But it was too late, the sandwich thief already had eaten the coveted lunch! But he didn't get away with it. HR was able to track down the crook. + +Click here for more on this story from the Daily Mail.","0" +"Sandwich thief gets comeuppance in this awesome office note saga","THIS might be the best note scandal ever. + +A hilarious tit-for-tat between an office sandwich thief and its hungry victim is making its way around the internet, with hilarious results. + +We don’t want to give too much away, but let’s just say the office thief gets his comeuppance. + +Post by MORE FM. + +Post by MORE FM. + +Post by MORE FM. + +Post by MORE FM. + +Post by MORE FM. + +Post by MORE FM. + +Post by MORE FM. + +Post by MORE FM. + +Post by MORE FM. + +Post by MORE FM. + +Post by MORE FM. + +Post by MORE FM. + +Post by MORE FM.","0" +"Sushi lover's entire body left riddled with WORMS after eating contaminated sashimi","It is the most expensive - and many would argue delicious - part of a sushi menu. + +But one man's love of sashimi nearly killed him after it led to his body becoming riddled with tapeworm. + +The Chinese man had gone to his doctor complaining of stomach ache and itchy skin. + +To his horror, scans revealed his entire body had been infected with tapeworm after eating too much sashimi - raw slices of fish. + +Scroll down for video + +One man's love of sashimi nearly killed him after it led to his body becoming riddled with tapeworm + +The Chinese man had seen his doctor complaining of stomach ache and itchy skin. Scans revealed his entire body had been infected with tapeworm parasites after eating too much sashimi - raw slices of fish + +Humans contract tapeworm infections from sushi by eating raw fish that has been infected with the worm in its larvae stage. + +When fish eat tapeworm eggs, the hatching larvae attach themselves to the intestinal wall of the fish and the worms infect the fish flesh. + +Because sushi is not cooked, the larvae can in turn transfer into the flesh of any human that eats the fish. + +Once a human is infected, a tapeworm will grow inside the intestine to a length of up to 15metres over a period of weeks. It can survive for years and go undetected for weeks or months, in turn releasing its own eggs that infect other parts of the human body. + +Symptoms include fatigue, constipation and abdominal discomfort - which can be so mild the victim may not notice anything is wrong. + +If larvae begin to migrate to other parts of the body they can start to eat away at the liver, eyes, heart or brain and cause life-threatening conditions. + +Doctors believe some of the uncooked Japanese delicacy of raw meat or fish must have become contaminated. + +He was treated at the Guangzhou No. 8 People's Hospital in Guangdong Province, in eastern China. + +Research has shown that eating raw or undercooked fish can lead to a variety of parasitic infections. + +Tapeworm infections occur after ingesting the larvae of diphyllobothrium, found in freshwater fish such as salmon, although marinated and smoked fish can also transmit the worm. + +While cases have increased in poorer areas due to improved sanitation, cases have increased in more developed countries,. + +This is most likely due to the soaring popularity of sushi, say doctors writing in the journal Canadian Family Physician. + +Study author Nancy Craig wrote: 'The widespread popularity of Japanese sushi and sashimi (slices of raw fish) is a contributor. + +'But other popular dishes might also be implicated, such as raw salted or marinated fillets - which originate from Baltic and Scandinavian countries - carpaccio - very thin slices of raw fish common in Italy, raw salmon and ceviche - lightly marinated fish.' + +Dr Yin, of Guangzhou No. 8 People’s Hospital, told the website that'smags.com that eating uncooked food contaminated with tapeworms' eggs could eventually cause cysticercosis, when the adult worms enters a person’s blood stream. + +This type of infection is life-threatening once it reaches the brain. + +Research has shown that eating raw or undercooked fish can lead to a variety of parasitic infections + +Eating uncooked food contaminated with tapeworms' eggs could eventually cause cysticercosis, when the adult worms enters a person’s blood stream - and can be fatal","0" +"Saudi Arabia's Religious Police Outlaw 'Tempting Eyes'","It's a safe bet that Sheikh Motlab al Nabet, spokesman of Saudi Arabia's religious police, isn't a fan of Cole Porter. ""The lure of you"" is precisely why Nabet announced yesterday that the Committee for the Promotion of Virtue and the Prevention of Vice will cover any women's eyes that are deemed ""tempting."" ""The men of the committee will interfere to force women to cover their eyes, especially the tempting ones"" he said. ""[We] have the right to do so."" +What are ""tempting"" eyes? One Saudi journalist mused on condition of anonymity that they are ""uncovered eyes with a nice shape and makeup. Or even without makeup, if they are beautiful, the woman will be in trouble."" The Orwellian-named committee did not provide a definition of tempting, but if they happen to rely on Merriam-Webster, then it means ""having an appeal."" What is an appeal? According to the dictionary, it is ""arousing a sympathetic response."" And what is sympathetic? ""Showing empathy,"" according to Merriam-Webster. + +So there you have it. To allow a women's eyes to capture the unfettered glory of the world, one must empathize with her very existence. But the religious police--massively funded by King Abdullah--cannot do this. ""It's so stupid,"" the Saudi journalist tells me. ""I don't know what to say. They have to stop this. Many people will oppose this in the country. They won't be silent."" + +Perhaps they won't be, but the Committee for the Promotion of Virtue and the Prevention of Vice has some of the most powerful backers in the country. Prince Naif, recently appointed heir to the throne, has said: ""The committee is supported by all sides ... It should be supported because it is a pillar from Islam. If you are a Muslim, you should support the committee."" No surprise, then, that King Abdullah awarded this draconian body an additional 200 million riyals (about $53 million) in March. + +How should America respond to this latest affront to Saudi women? Perhaps it can sponsor a contest of the most tempting eyes in Saudi Arabia. Women will send in pictures of their most tempting look and the winner will get to accompany President Obama during his next meeting with the Saudi dictator. + +If Congress reconsidered the recent $60 billion U.S.-Saudi arms deal, the religious police might quickly find it ""tempting"" to stop treating women as property.","0" +"Saudi Arabia outlaws ‘tempting eyes’","A new law in Saudi Arabia banning ‘tempting eyes’ has become the latest example of female oppression in the country. + +The law, which states that women with alluring eyes will be forced to wear a full veil, has been branded ‘stupid’ by dissenters and roundly criticised on social media, aina.org reports. + +Sheikh Motlab al Nabet, spokesman of the Saudi Arabian Committee for the Promotion of Virtue and the Prevention of Vice, said they ‘had the right’ to force women to cover their face. + +‘The men of the committee will interfere to force women to cover their eyes, especially the tempting ones,’ he said. + +‘We have the right to do so.’ + +Many commentators wondered how the word ‘tempting’ would be applied. + +MORE: Church ministers and 90-year-old man arrested for feeding the homeless + +MORE: Frederico: Shocking image of street child was taken seven months AFTER he was found + +MORE: Egypt court jails eight men for ‘gay wedding’ video + +One unnamed journalist in the country suggested it referred to ‘uncovered eyes with a nice shape and makeup.’ + +‘Or even without makeup, if they are beautiful, the woman will be in trouble,’ they added. + +Prince Naif, whose impending ascension to the Saudi throne many hoped would spell an end to this kind of draconian oppression, looks likely to be as intolerant as his father King Abdullah after suggesting that any Muslim should support the Committee’s new law. + +‘The committee is supported by all sides,’ he said. + +‘It should be supported because it is a pillar of Islam. If you are a Muslim, you should support the committee.’","0" +"Saudi Women May Have to Cover Up Sexy Eyes","RIYADH, Saudi Arabia – Saudi women with attractive eyes may be forced to cover them up, the news website Bikya Masr reported, in a move that could mark the latest repressive measure taken against women by the Islamic state. + +A spokesperson for Saudi Arabia's Committee for the Promotion of Virtue and the Prevention of Vice (CPVPV), Sheikh Motlab al Nabet, said the committee had the right to stop women revealing ""tempting"" eyes in public. + +Women in Saudi Arabia already have to cover their hair, and, in some regions, their faces while in public. If they do not, they face punishments including fines and public floggings. + +The CPVPV has repeatedly been accused of human rights violations. Founded in 1940, its function is to ensure Islamic laws are not broken in public in Saudi Arabia. + +In 2002 the committee refused to allow female students out of a burning school in Mecca because they were not wearing correct head cover, report said. The decision contributed to the high death toll of 15 people who were killed in the fire.","0" +"‘Tempting Eyes’ Ban: Saudi Women With Pretty Eyes Made To Cover Them Up","A “tempting eyes” ban has just been announced in Saudi Arabia that further represses women more than they already are. In this part of the world, women are known to cover their bodies completely from head-to-toe. The eyes are one of the only parts of their body that are seen in public. + +Opposing Views reports that women who have eyes “with a nice shape and makeup” could be deemed too tempting to other men, and police can make them wear veils. Committee for the Promotion of Virtue and the Prevention of Vice announced this decision a few days ago. It’s one bound to get universal criticism. + +Assyrian International News Agency covered what the Saudi Arabian committee’s spokesman has to say about the new law. Sheikh Motlab al Nabet, explains that Saudi police “have a right” to make a woman cover her eyes. + +“The men of the committee will interfere to force women to cover their eyes, especially the tempting ones. We have the right to do so.” + +This development has sparked the question of what defines “tempting eyes” and how will women be evaluated on having them? An unidentified journalist in the nation best describes what Saudi police are going after. + +“Uncovered eyes with a nice shape and makeup. Or even without makeup, if they are beautiful, the woman will be in trouble.” + +He adds that a lot of people in Saudi Arabia will be very upset about the law. This type of control will outrage citizens of the country, the unnamed journalist says. + +“It’s so stupid. I don’t know what to say. They have to stop this. Many people will oppose this in the country. They won’t be silent.” + +The report notes that no divide between Church and State exists in Saudi Arabia. The bad part is that the Committee for the Promotion of Virtue and the Prevention of Vice has powerful “backers” that include Prince Naif, the heir to the nation’s throne. He announced that the committee “should be supported because it is a pillar from Islam. If you are a Muslim, you should support the committee.” + +If there was any hope among the people that King Abdullah’s son would steer Saudi Arabia in a different direction, it’s lost at this point. By supporting the committee, the prince also supports the “tempting eye ban.” Oppression will continue in the nation, as women are considered nothing more than property. + +[Photo Credit: Hassan Ammar/AP Photo via Assyrian International News Agency]","0" +"If They Are Beautiful, The Woman Will Be In Trouble': Saudi Arabia Religious Police Ban 'Tempting Eyes'","As if women were not subjugated enough already in Saudi Arabia, the nation’s Committee for the Promotion of Virtue and the Prevention of Vice announced yesterday that “tempting eyes” would be subject to veils if deemed inappropriate. + +Sheikh Motlab al Nabet, spokesman of the Saudi Arabian committee, said in the announcement that, ""The men of the committee will interfere to force women to cover their eyes, especially the tempting ones. We have the right to do so."" + +The new ban on well-manufactured facial features is broad enough to lead to some inquiry on the definition of ""tempting eyes."" Moreover, what is the process by which a woman will be found guilty of having “tempting eyes?” A humorous image can only come to mind with long lines of “tempting eyed women” waiting to be brought before the 1984-esque committee. + +According to an unnamed journalist in Saudi Arabia, “tempting eyes” could possibly be defined with these stipulations: ""Uncovered eyes with a nice shape and makeup. Or even without makeup, if they are beautiful, the woman will be in trouble."" + +The unnamed journalist went onto say, ""It's so stupid. I don't know what to say. They have to stop this. Many people will oppose this in the country. They won't be silent."" + +While in most Western nations there is harsh divide between Church and State, in Saudi Arabia no such segmentation exists. In March, King Abdullah awarded the committee more than $53 million to continue enforcing their religious dogma via the estimated 3,500 to 4,000 religious police officers, which patrol the streets. + +As King Abdullah nears the end of his reign, there was hope that a younger and more liberal dictator would follow. Prince Naif was recently appointed as the heir to the throne, but after giving his support to the committee, there is little hope that Saudi Arabia will evolve in the human rights department. + +""The committee is supported by all sides,” Naif said. “It should be supported because it is a pillar from Islam. If you are a Muslim, you should support the committee."" + +The parental “because I told you so” argument lacks logic and rationale, but such is the case when a nation resides under monarch rule. It remains unclear how many women will be found or charged with ""tempting eyes,"" but if there is a great enough dissenting voices, public outcry will hopefully have some bearing on the obscene policy. + +Source: Assyrian International News Agency","0" +"Mom Calls 911 On Masturbating Teenage Son; Boy Arrested, Charged With New ‘Self-Rape’ State Law","Phoenix, AZ — A Phoenix boy is behind bars tonight after his mother called 9-1-1 when she found her son in his room, watching pornography and masturbating. Phoenix Police were quick to respond, arresting 15-year-old Paul Horner, who attends North Valley High School in Phoenix, Arizona. Now the teenager is being held without bail and charged by prosecutors under a new controversial Arizona state law called ‘Self-Rape’, which carries a minimum of 3 years in prison with a maximum of 15 years behind bars depending on that individuals past criminal history. + +This is the first time this new state law has been used since it was put into action last month by Arizona Governor Jan Brewer. Brewer spoke with local news station ABC 15 about the charges against the boy. + +“I applaud the Arizona District court systems here in Phoenix,” Brewer said. “This is exactly why I implemented the state law of ‘Self-Rape’ last month and this is exactly what it is meant to be used for. Before my time as governor is up early next year, I’ll do whatever I can to ensure that tragedies like this don’t happen again. We need to educate our children about the dangers and consequences of masturbation before it’s too late.” + +Horner, after hearing his charges by the Honorable Judge Stevens of the United States District Court in Phoenix, which included the brand new ‘Self-Rape’ state law, Horner immediately broke down into tears and had to be restrained by bailiffs. + +Transcripts of the 9-1-1 call were released to the public: + +“911, what’s your emergency?” + +“Help! My son is watching porn and masturbating! That is not allowed in his house and I don’t know what kind of demons possessed him to degrade his body in such a matter. I’m so shakin’ up! Please send help immediately!” + +32-year-old Adeline Horner, Horner’s mother, who is a self-proclaimed fanatical Baptist follower, told CNN she is still in shock. + +“Up until now, my young, precious boy had no run-ins with the law, no drugs or alcohol, was a straight-A student, was in numerous extra curricular activities and played starting center on the boys Varsity basketball team,” Horner’s mother said. “But somewhere along the way he started playing on the Devil’s playground. Hopefully because of my quick thinking and actions my son will soon be able to get the help he so badly needs. I pray for it; please Jesus, save our family!” + +Winters controversial actions have been applauded by some, for example, Lonnie Childs, president and founder of the federally funded Christian anti-masturbation organization STOP Masturbation NOW. + +“STOP Masturbation NOW ministries have nominated Adeline Horner for our coveted Mother of the Year award,” Childs told reporters. “She really stepped up, provided moral discipline and leadership under such difficult conditions. My prayer app has been activated and I send this brave, courageous woman nothing but the best during these difficult times. I encourage you all all to do the same.” + +A mascot for the Christian organization, Fappy The Ant-Masturbation Dolphin, whose real name is 36-year-old Paul Horner from Phoenix, Arizona, told reporters he is pleased with the justice served today and is confident this will set a precedent for all the would be masturbators out there. + +“Fappy® has helped tens of thousands of adults and children around the world learn to live a masturbation-free lifestyle. During our visits to schools around the world, our organization has collected thousands of signatures from children promising to never masturbate; we have done great things. Our organization is passionate about the great work that we do. The children even have a nickname for Fappy®, they call him the tickle monster. Working side by side with such great women as Jan Brewer, we’re ridding the demons from these heathens pants, one pair of pants at a time. Fappy® vows to stay on this case until justice is served!” + +Tom Downey with the Phoenix Police Department, who took the child into custody, spoke with Arizona news station Fox 10 News about the arrest. + +“We thought at first he was possibly intoxicated or mentally unstable, ya know, talking about how we should leave him alone and just let him watch his filth, makes me sick! It’s a slippery slope my friend, one day it’s masturbating to porn, the next day it’s raping some innocent school girl. Thank God we got this heathen off the streets before another tragedy could have occurred.” Downey continued, “There’s no better feeling than putting the real bad guys behind bars. Nothing better than that. I know I can sleep better at night just knowing another criminal is off the streets.” + +Officers confiscated the pornography and lube found in the teenagers room as evidence. + +Prosecutors told local reporters that based on the severity of the crime, the new Arizona state law of Self-Rape [A.R.S. §§ 29-169 & 48-69] would carry a minimum of 3 years with a maximum of 15 years depending on that criminals past history. + +Horner is currently being held at the Maricopa County Jail in Phoenix, Arizona. He presently has no bond set and the judge has restricted him from seeing visitors. Horner’s next scheduled court appearance is December 2nd. + +Fappy The Anti-Masturbation Dolphin and Stop Masturbation Now are federally funded programs designed to teach both children and adults about the dangers and consequences of masturbation. For more information or if you would like the group to visit your child’s school call (785) 273-0325. To contact Arizona Governor Jan Brewer, call (602) 542-4331. + +VIDEO: Mom Calls 911 On Masturbating Teenage Son; Boy Charged With ‘Self-Rape’","0" +"Was Alleged Audio of Michael Brown Shooting on CNN a Hoax?","Mediaite writes about CNN’s morning show questioning the reporting of one of CNN’s evening shows. + +Monday night, “CNN Tonight” aired an audiotape purported to capture the shooting of Michael Brown. The tape was brought to CNN by St. Louis attorney Lopa Blumenthal, (at right with anchor Don Lemon) who says a former client gave it to her. Lemon repeatedly said that CNN could not verify the authenticity of the tape. + +TVNewser has learned CBS News received the same audio earlier this week from Blumenthal, but chose not to run it because it could not be verified. + +This morning on “New Day,” two guests on CNN doubted the veracity of it. + +“I’ve told your producers that for all I know this is something one of Howard Stern’s punk people had been doing. I look at this and my first inclination is someone is trying to punk CNN,” said former LAPD officer David Klinger. CNN analyst Tom Fuentes also doubted its authenticity: “When I heard this yesterday, I thought the exact same thing: it’s a hoax.” + +WaPo’s Erik Wemple reported yesterday on how CNN got its hands on the audiotape. When asked about its authenticity, a CNN spokesperson told Wemple, “[W]e interviewed the caller’s attorney off camera and she answered key questions that gave us confidence to put her on the air live with Don. And we did confirm the caller lived close enough to the shooting to have heard the shots.” + +Now it appears, there are doubts inside CNN.","0" +"CNN Expert on Brown Audio: At First I Thought ‘Someone’s Trying to Punk CNN’","Former LAPD officer David Klinger and CNN law enforcement analyst Tom Fuentes both told CNN’s New Day Wednesday morning that the recording the network has been airing that allegedly captured the shots fired at Michael Brown could quite easily be a hoax. + +“I have no idea [if it's authentic],” Klinger said. “I’ve told your producers that for all I know this is something one of Howard Stern’s punk people had been doing. …I look at this and my first inclination is someone is trying to punk CNN.” + +RELATED: Limbaugh: CNN ‘Flat-Out Irresponsible’ for Hyping Alleged Mike Brown Audio + +“When I heard this yesterday, I thought the exact same thing: it’s a hoax,” Fuetnes said, explaining: + +“The engineers in the laboratory at Quantico will be trying to determine if there was a dubbing; did we have an original recording of this guy having a conversation no one wants to talk about, and then the shots then dubbed over it; was it the complete tape? All accounts from Brown’s side and the officer’s side say there was a single shot fired initially at the door of the police car. So that shot, followed by Brown trying to flee, and then the officer exiting the car and pursuing him and then firing the series of shots — so we’re missing that first shot. Now, I don’t know, CNN got this tape first. Did they censor it because the guy said something obscene over the first shot and they didn’t want to air that? We just don’t know all that.” + +New Day cohost Michaela Pereira defended the airing of the tape. “It needs to be said the lawyer who is representing the man who gave us the audio gave it to us, she swears it is real,” Pereira said. “We have no reason here at CNN to believe that it’s not true.” + +Watch the clip below, via CNN: + +OO.ready(function() { OO.Player.create('ooyalaplayer-hxdDd3bzrV79UNb455SjJj5g98PqcbOu', 'hxdDd3bzrV79UNb455SjJj5g98PqcbOu'); }); + +Please enable Javascript to watch. + +[Image via screengrab] + +—— >> Follow Evan McMurry (@evanmcmurry) on Twitter","0" +"Is the Alleged Audio of the Gunshots That Killed Michael Brown a Hoax?","At least two experts are questioning the authenticity of an audio file that is purported to have captured the gunshots that killed 18-year-old Michael Brown in Ferguson, Missouri, earlier this month. + +CNN law enforcement analyst Tom Fuentes and former Los Angeles police officer David Klinger both said Wednesday morning that they initially felt the recording alleged to reveal the sequence of shots fired by Officer Darren Wilson was a hoax, according to Mediaite. + +“I’ve told your producers that for all I know this is something that one of Howard Stern’s punk people have been doing … I don’t have a high degree of confidence in it,” Klinger said on CNN’s “New Day.” “I look at this and my first inclination is that someone is trying to punk CNN.” + +He cited the fact that the clip emerged two weeks after the shooting as well as the curious words being voiced by a man in the audio as reasons why he doubted its authenticity, though he said he remains open to seeing whether an investigation finds it legitimate. + +A man’s voice can be heard in the audio telling a woman, “You are pretty. You’re so fine, just going over some of your videos. How could I forget?” The context of the remarks is unclear, though purported gunshots can be heard in the background. + +And Klinger wasn’t alone in his skepticism. Fuentes also said that he has qualms over the authenticity of the audio. + +“When I heard this yesterday, I thought the exact same thing — it’s a hoax, but maybe not. Maybe they’ll be able to authenticate it,” he said. + +Fuentes said that the FBI’s investigation will likely include engineers at Quantico examining the audio to see if there was any dubbing and to examine whether the complete tape was delivered to CNN, Mediaite reported. + +Watch their comments below: + +CNN “New Day” co-host Michaela Pereira noted that an attorney — a woman named Lopa Blumenthal — had delivered the audio to the network, vouching for its authenticity on behalf of her unnamed client. + +TheBlaze first reported about the clip’s emergence in the contentious case on Tuesday.","0" +"NASA Confirms Earth Will Experience 6 Days of Total Darkness in December 2014!","WORLDWIDE - NASA has confirmed that the Earth will experience 6 days of almost complete darkness and will happen from the dates Tuesday the 16 – Monday the 22 in December. The world will remain, during these three days, without sunlight due to a solar storm, which will cause dust and space debris to become plentiful and thus, block 90% sunlight. + +This is the head of NASA Charles Bolden who made the announcement and asked everyone to remain calm. This will be the product of a solar storm, the largest in the last 250 years for a period of 216 hours total. Reporters interviewed a few people to hear what they had to say about the situation with Michael Hearns responding “We gonna be purgin my n*gga, six days of darkness means six days of turnin up fam”. + +Despite the six days of darkness soon to come, officials say that the earth will not experience any major problems, since six days of darkness is nowhere near enough to cause major damage to anything. “We will solely rely on artificial light for the six days, which is not a problem at all”, says NASA scientist Earl Godoy. Visit our website daily for more shocking news! + +What do you plan to do during these six days of darkness? Tweet ‘#6DaysOfDarkness‘ including your plan for these six days!","0" +"Kurt Sutter Announces Plans For ‘Sons Of Anarchy’ Movie Starring Charlie Hunnam, Brad Pitt","NORTH HOLLYWOOD, California - + +Kurt Sutter, creator of the hit FX drama Sons of Anarchy, has announced plans to turn the popular television series into a major motion picture. + +Sutter, who was also a writer, producer, and director on the series, said in an interview with Hollywood Today magazine that he has long contemplated taking S.O.A. to the big screen following its run on television. “People absolutely loved the show, as did I, and I have put a lot of thought into the matter, and we are going forward with turning it into a feature film” Sutter said. + +Sons of Anarchy ran for seven seasons on FX, from 2008-2014, and in the process built a huge following. Sutter said the film will star Charlie Hunnam, who played the lead character Jax Teller, as well as Ryan Hurst who played Opie Winston, and Katey Sagal as Gemma Teller. The film, which is a prequel to the storyline of Sons will also introduce fans to Jax’s father, John, who will be played by Brad Pitt. + +“I am most excited about bringing Brad (Pitt) on as John Teller, he is absolutely perfect for the role. The movie will take place from the day Jax was born, and leads up to the era just before Sons Of Anarchy began as a series.” + +Sutter also said that he is really happy to bring Ryan Hurst back as Opie Winston, and hopes fans will forgive him for killing Opie off. “Man I tell ya, when we killed Opie off, it was like the thing turned real. I’ve never gone public with this, but I’ve had people get really crazy when they see me in public,” said Sutter. “They shout at me, and they get angry - ‘You shouldn’t have killed Ope! I hope you rot in Hell!,’ that sort of thing. I had people try to run me off the road when they recognized me, although that just might be because I’m kind of a dangerous driver. Anyway, my hope is that this film will help them cope.” + +Sutter says pre-production on film will begin in the middle of 2015, and will begin shooting sometime in the fall. “For a movie of this scope, with this much storyline attached, you should expect to see the film by the end of 2016,” said Sutter. “In the mean time, buy all the official Sons of Anarchy merchandise you can. Every dollar goes to helping get this movie completed. Brad Pitt isn’t cheap, you know.”","0" +"Pumpkin Spice Condoms Could Be The Only Thing To Save The World From Basic Children","In a mass influx of basicness, it seems Durex may or may not be hopping on the pumpkin spice bandwagon. + +This past weekend, images of a Starbucks PSL-inspired condom took social media by storm. + +Is this a ploy to get basic bitches of the world to stop procreating? Will they actually be able to convince a potential partner to wrap it up with something as bizarre as this? Is there even a demand for a product like this? + +The image is an altered image of Durex’s flavored “Taste Me” condom line, which just begs me to ask one question: Can your genitals taste flavors? + +Oh, wait… That’s not what they were getting at, is it? + +There have been no official corporate announcements determining if this will be a reality or not. But, after seeing this image spread, why wouldn’t Durex look into this? + +If there’s anything that could get the population on the condom train it would have to be the PSL trend, right? + +Sounds like an easy moneymaker to me, even if it’s just a novelty. + +H/T: Quartz","0" +"Durex is not confirming or denying rumors of a “pumpkin spice” condom","Word that Durex was rolling out a pumpkin-spice-flavored condom swept through social media over the weekend: + +The autumnal-themed birth control may well be just an internet invention, a riff on Starbucks’ wildly popular coffee drink. The photo in the tweet above appears to be an altered version of Durex’s flavored “Taste Me” range of condoms, which come in apple, strawberry, banana and orange, but not (yet) pumpkin. There have been no corporate announcements about any new offering. +Several emails to Durex’s parent company, Reckitt Benckiser, and Virgo Health, the PR company that handles communications for Durex, didn’t yield a conclusive answer. A spokeswoman for Virgo Health said she couldn’t say whether the company was or was not actually developing such a thing. +Reckitt Benckiser has been growing the Durex brand in emerging markets, as Quartz reported earlier, and transforming it into a “sexual well-being brand.” But plans for any holiday-themed contraception remain mysterious, or possibly imaginary, even ones involving a certain cult cinnamon and nutmeg-laced spice flavor.","0" +"Is Durex Planning To Release A Pumpkin Spice Condom?","If you spent enough time on Twitter this weekend, you probably saw this photo on your feed: + +And all the basic white girls were like, does it come with UGG Boots? Anyway, the photo is an obvious fake, but Durex is sitting on a potential (ironic) goldmine if they could make your penis smell like Starbucks in October. So far, they’re playing it cool, neither confirming nor denying the existence of a pumpkin-flavored love glove. + +Several emails to Durex’s parent company, Reckitt Benckiser, and Virgo Health, the PR company that handles communications for Durex, didn’t yield a conclusive answer. A spokeswoman for Virgo Health said she couldn’t say whether the company was or was not actually developing such a thing. (Via) + +There’s a pumpkin creampie joke to be made here, but I refuse to be the one who says it.","0" +"Durex on Rumored ‘Pumpkin Spice’ Condom: No Comment","Happy Monday! It’s now unofficially Fall, which means you’ll see the word “pumpkin” trotted out even more often than the phrase “Apple product launch” this month. + +Brands like Starbucks do not seem to have heeded the “enough with the pumpkin stuff!” warning; as friend of the site Dave Armon of Critical Mention wrote in one of those rare comments worth reading: + +“Like it or not, Starbucks is killing it with this story. We spotted 75 airings on U.S. TV and radio stations today, through 5:45 p.m. ET. Personally, I’ll wait until I can see my breath before ordering anything pumpkin flavored.” + +This point goes a long way toward explaining why Durex and its PR AOR Virgo Health refused to give Quartz a definitive answer on the most absurd trend to emerge from Twitter this weekend: + +If it’s real, the client wins. If it’s fake, the client still wins. Why stop the world from wondering? + +For the record, we’re leaning strongly toward fake and 100% unearned.","0" +"‘Star Wars: The Force Awakens’ May Get An Early Release Date—Report","“Star Wars: The Force Awakens” is one of the most highly anticipated movies of 2015 that is scheduled to be released during winter. The latest reports, however, claim that J.J. Abrams, the director of the seventh episode of the epic space opera, wants an early release date for his movie. + +“Star Wars: The Force Awakens” is currently scheduled to be released on Dec. 18, 2015. Based on YouTuber Votesaxon 07’s video, Movie Pilot reports that J.J. Abrams wants to release “Episode 7” in the summer of 2015. The report by the aforementioned entertainment news publication claims that the 48-year-old director made the announcement at the Visual Effects Society Awards 2015. + +The publication claims that the reason why J.J. Abrams wants to release “Star Wars: The Force Awakens” almost six months before its scheduled date is the alleged plot and images leaks from the sets and script. The moviemaker is now worried that these plot leaks will make the film “predictable and not worth watching” for the audience. + +According to the website, moving the release date forward would be “an extremely brave move,” putting it up against other fan-favourite releases such as “Avengers: Age of Ultron,” “Jurassic World” and “Ant-Man.” However, shifting the release date means a lot of work for the moviemakers and the studio. Meanwhile, Ikwiz reports that Disney is “seriously” considering J.J. Abrams' demand of summer release of “Star Wars: The Force Awakens.” + +Fans must note that these reports lack official comments from the associated parties; thus, the information must be taken with a pinch of salt. However, fans know that Disney is seriously dealing with the issue of image leak. Recently, the studio issued a subpoena over the leak of images from “Star Wars: The Force Awakens.” + +In additional news, J.J. Abrams finally broke his silence on the controversy over the new lightsaber that debuted in “Star Wars: The Force Awakens” trailer. Speaking to Collider at a Hollywood event, the director admitted receiving tons of emails arguing about the new lightsaber and its functionality. + +""It's been the funniest thing to see the arguments that have developed over this thing,” J.J Abrams said. ""This was not done without a lot of conversation. It's fun to see people have the conversation that we had, but in reverse,” the director explained. + +“Star Wars: The Force Awakens” features John Boyega as Finn, Daisy Ridley as Rey, Oscar Isaac as Poe Dameron, Harrison For as Han Solo, Carrie Fisher as Leia, Mark Hamill as Luke Skywalker, and Domhnall Gleeson, Max von Sydow and Adam Driver, all in unspecified roles. Stay tuned for more updates. + +To report problems or leave feedback on this article, email: j.kaur@IBTimes.com.au. + +Read more about “Star Wars: The Force Awakens,” below: + +‘Star Wars: The Force Awakens’ Possible Plot Details On Main Cast Revealed, Luke Skywalker Guarding ‘Ancient Sith Tomb,’ Plus More Spoilers","0" +"Star Wars VII for a New SUMMER Release Date!?","In quite recent news, J J Abrams has reportedly said at the Visual Effects Society Awards (2015) that he may release his extremely anticipated film, Star Wars: Episode VII — The Force Awakens. instead of winter he may move his film down the line for a summer release! This is an extremely brave move (if true) as it puts Star Wars up against films like Avengers 2: Age Of Ultron, Ant-Man and the long awaited Jurassic World but who would win at the summer box office if it were to happen? In my opinion Star Wars has got the strongest chance at the box office if moved to a summer release but why would he do it? All the big films come out in the summer and I mean there's no Hobbit to compete with in December so why move it down to Summer? + +Box office championship. +Box office championship. +J J's biggest reason was reported to be that all of the Star Wars plot leaks and pictures of characters had sent him on a little scare that more and more would be leaked therefore making the film predictable and not worth watching. For example just one photo can give away a lot for instance: (If you don't want spoilers look away!) + +Sorry J J! +Sorry J J! +For instance these 5 figures reveal the character's Kylo Ren, Rey, Fin, BB-8 and shows us what Kylo Ren (ol' crossguard) will look like with his outer cloak removed. I do see that if more of these pictures are leaked we could be seeing what Han, Leia, Luke, C3PO etc. will be like in the film before seeing a company made trailer, which would ruin the surprise. Disney, being the owners of the new Star Wars franchise, have taken J J's thoughts into consideration and deep thought which could get the film released a lot earlier than we thought we were going to see it! There are some bad things about this though... If we do get what we all wish for and we get to see Star Wars 7 about 6 months before we thought we were going to, won't Disney be in a panic? If they thought that their blockbuster was coming in December would they have ordered toy designs, trailers etc. for later on in the year? Perhaps this is just paranoia but Disney and J J will have a lot of work to get done if they want their merchandise etc. to come alongside Star Wars in summer. + +I gathered the basis of this information from Votesaxon07 (part of following the nerd) who's a great youtuber and if you want to see the information for yourself watch this video which also has news for Frozen fever, the A.T.O.M suit, Deadpool movie news and other awesome snip-its: + + + +Thanks for reading guys and I hope you gained some information from this and enjoyed reading through some of my opinions on the topic! (Thanks to Votesaxon07 and following the nerd for the awesome news!)","0" +"Has J.J. Abrams Asked for THE FORCE AWAKENS Release Date to be Moved Up?","Here’s some news that may have slipped under the radar from yesterday, thanks to all of the Spider-Man news. A site called iKwiz is reporting that director J.J. Abrams, has asked Disney for the release date of Star Wars: Episode VII to be moved up from it’s original release date. + +According to the site, Abrams had said it himself while addressing a group of attendees at the 2015 Visual Effects Society Awards about his frustration about the leaked pictures floating around the web. The site also states that Disney is taking Abrams’ request very seriously. + +The site does not specify as to what date Abrams is asking for. Disney has not commented on the rumor. + +As of now, the release date for The Force Awakens is still Dec. 18.","0" +"'Star Wars VII' News, Update: JJ Abrams Pushing for Summer Release?","J.J. Abrams' heavily anticipated ""Star Wars: The Force Awakens"" is currently slated to open in theaters this Dec. 18, 2015. But if there's truth to these recent release date rumors, the sequel could be hitting the cinemas on an earlier schedule. + +An article from The Telegraph cited two separate ""unconfirmed reports"" from Ikwiz and Movie Pilot indicating that instead of winter, Star Wars VII might arrive in theaters ""this summer."" + +""J J's biggest reason was reported to be that all of the Star Wars plot leaks and pictures of characters had sent him on a little scare that more and more would be leaked therefore making the film predictable and not worth watching,"" Movie Pilot wrote. + +Ikwiz meanwhile stated that ""Disney is reportedly taking Abrams' request very seriously, and is looking at a possible summer release."" + +This conclusion was apparently drawn from the statement which the ""Star Trek"" helmer gave off during the Visual Effects Society Awards (2015) event on Feb. 4 where Abrams received the VES Visionary Award. + +John Boyega, who is set to appear in the ""Star Wars"" sequel, recently shared his appreciation for the brilliance Abrams has put in the gigantic film project. + +""It was brilliant,"" Boyega told BBC. ""J.J. Abrams is obviously a passionate guy and does well in this movie and I can't wait for it come out."" + +As for the movie itself, the 22-year-old quipped that fans should really brace themselves when it arrives. + +""I think they should be very excited,"" he added. ""We're going back to the originals, we're staying true to practical effects and we have the original cast back, and it's going to be a great time.""","0" +"'The Force Awakens' Release Date: JJ Abrams Plan for an Early Release of 'Star Wars' Movie?","Fans of ""Star Wars"" may not have to wait until December to watch ""The Force Awakens"", as a new report states that director JJ Abrams wants to release the movie this summer. + + +'Star Wars: The Force Awakens' might hit the theaters in summer along with 'Jurassic World' and 'The Avengers: Age of Ultron'.Facebook/Star Wars +An article appeared on ikwiz claims that the film-maker has approached Disney for an early release of the movie, which is currently scheduled to hit the theatres on 18 December. +As per the report, Abrams made the announcement at the 2015 Visual Effects Society Awards that was held on 4 February. +The website also stated that Disney has taken the request seriously and is looking for a possible release date for ""Star Wars: The Force Awakens"" in summer. +If the reports are true then the seventh instalment of ""Star Wars"" film series will be released in June along with ""Jurassic World"" and there will be a box office clash between the three most anticipated movies of the year. +The main reason for an early release of the film is said to be the alleged leaks of plots and images from the sets and scripts and Abrams believes that it will make the movie predictable and not worthy of watching, according to Movie Pilot.? + + +However, the makers of ""Star Wars: The Force Awakens"" have not released any official statement on the early release date of the movie.","0" +"Star Wars: The Force Awakens to be released this summer?","JJ Abrams is considering releasing his heavily anticipated Star Wars: The Force Awakens this summer, according to unconfirmed reports from Ikwiz and Movie Pilot. The film has a current release date of December 18 2015. + +According to Movie Pilot, the director is losing patience with the constant stream of plot and image leaks from the Star Wars set, and believes that shifting to an earlier release date will mean the film isn't ""ruined"" before fans can see it. The Ikwiz article states: ""Disney is reportedly taking Abrams’ request very seriously, and is looking at a possible summer release."" + +While neither website has an official source for the rumour, Abrams is reported to have made the comments at the 2015 Visual Effects Society Awards on February 4. The director received the VES Visionary Award during the ceremony. + +Last week, Disney appeared to be cracking down on anyone illegally leaking content from Star Wars VII, requesting that a judge issue a subpoena to a website named ImageShack, which was hosting a blurred image of a Sith Lord clutching a red lightsaber – said to be a leaked still from the film. In a declaration to support the issuance of a subpoena, a Disney employee confirmed the image was related to Star Wars: The Force Awakens. + +Keep up with Star Wars VII latest news, rumours and spoilers","0" +"‘Islamic tribunal confirmed in Texas’","Breitbart Texas reports: + +An Islamic Tribunal using Sharia law in Texas has been confirmed by Breitbart Texas. The tribunal is operating as a non-profit organization in Dallas. One of the attorneys for the tribunal said participation and acceptance of the tribunal’s decisions are “voluntary.” + +Breitbart Texas spoke with one of the “judges,” Dr. Taher El-badawi. He said the tribunal operates under Sharia law as a form of “non-binding dispute resolution.” El-badawi said their organization is “a tribunal, not arbitration.” A tribunal is defined by Meriam-Webster’s Dictionary as “a court or forum of justice.” The four Islamic attorneys call themselves “judges” not “arbitrators.” + +El-badawi said the tribunal follows Sharia law to resolve civil disputes in family and business matters. He said they also resolve workplace disputes. + +In matters of divorce, El-badawi said that “while participation in the tribunal is voluntary, a married couple cannot be considered divorced by the Islamic community unless it is granted by the tribunal.” He compared their divorce, known as “Talaq,” as something similar to the Catholic practice of annulment in that the church does not recognize civil divorce proceedings as ending a marriage. + +An Examiner.com article seems troubled by this. + +This, though, is a perfectly normal practice within religious groups in America. El-badawi is right that Catholics have long gone to Catholic authorities to resolve certain questions related to marriage. Orthodox Jews have long gone to Jewish religious courts (such a court is called a “beth din”) both to resolve marital matters and to resolve commercial disputes. Some Protestants sometimes do the same; 1 Corinthians 6:1 is often interpreted as calling for that. + +There are three ways in which these tribunals’ decisions have practical effect. + +1. Parties’ respect for the system: Religious people may often feel personally obligated to follow the judgments of respected authorities on their religious law. For instance, a Catholic who doesn’t get an annulment might feel obligated not to remarry, even if he thinks that he should have gotten the annulment, simply because he feels that God wants him to follow the church’s teachings and decisions. + +2. Social pressure: Would observant Muslims feel pressured to abide by a sharia tribunal’s ruling, when that will affect how their coreligionists, business partners, neighbors, and family members perceive them? You bet. Would Orthodox Jews feel the same? You bet, and I expect that Christians who operate within sufficiently devout and religiously homogeneous communities would have the same reaction. For an interesting, but rare, case of the legal system being asked to intervene to stop such social pressure and refusing to do so, see Paul v. Watchtower Bible & Tract Soc’y (9th Cir. 1987). (I think that, even in the absence of the Free Exercise Clause that were made in that case, but that might be unavailable in many states following Employment Division v. Smith (1990), a campaign urging people to shun the excommunicated would be protected under the Free Speech Clause, see NAACP v. Claiborne Hardware Co. (1982).) + +Indeed, one common argument in favor of religiosity is that community pressure tends to lead people to abide by religious obligations (not to steal, not to commit adultery, and more). The flip side is that community pressure tends to lead people to abide by religious obligations that we might not agree with (stay with a husband who mistreats you, never remarry, and so on). Of course, if there is also the threat of violence and not just community pressure, then the law can step in to punish the violence, and any explicit threats of violence. But the possibility of such violence in rare cases doesn’t allow the legal system to step in to block nonviolent social pressure in other cases. + +3. The parties could also enter into a binding arbitration agreement, under which they agree that the tribunal’s decision would be enforceable in civil court. Such agreements are common with secular commercial arbitration, even when the arbitration is supposed to apply law other than American law (e.g., English law or French law). And they are also permissible for religious arbitration. + +There are interesting questions about whether an arbitral decision is enforceable in secular American court if it applies substantive or procedural rules that discriminate based on race, religion or sex. I discuss this a bit in this post, and the comments to it are also much worth reading. But according to the Breitbart Texas article, El-badawi says that these tribunals do not conduct legally binding arbitrations; rather, their decisions are followed — when they are followed — as a result of the parties’ acquiescence and community pressure. As a result, these interesting questions don’t arise here. + +Religious communities have long had the right to use standard American contract law — coupled with the standard American liberty to exert social pressure on your family members, friends, neighbors and business partners — to have religious decisionmakers decide disputes. That’s especially so when the decisions are enforced just by community members’ own religious feelings, or by social pressure. But that can also be so, subject to some limitations, when the parties to the dispute agree to binding arbitration (which, again, doesn’t seem to be in play with the Texas Islamic tribunal). + +The remedy for those who disapprove of the religious law is leaving the community (or the religion). That is of course often very hard, for personal and economic reasons. It’s hard for Muslims. It’s hard for Orthodox Jews (and especially groups such as the Satmar Hasidim). It’s hard for Mormons, Jehovah’s Witnesses, the Amish, and members of lots of other groups. But that’s a necessary aspect of American social and religious freedom.","0" +"Islamic Tribunal Using Sharia Law In Texas Has Been Confirmed Tribunal members say they will avoid Sharia's ""criminal law.""","Breitbart Texas has confirmed the existence of an Islamic tribunal in Texas that will make judgments in accordance with Sharia law. + +The website for the Islamic tribunal states: “It is with this issue that Muslims here in America are obligated to find a way to solve conflicts and disputes according to the principles of Islamic Law and its legal heritage of fairness and justice in a manner that is reasonable and cost effective.” + +Advertisement-content continues below + +The website states that Sharia’s well known criminal law, which includes things like cutting off hands of offenders, is only a portion of Sharia law. This tribunal would not do such things, but will focus on civil Sharia law rather than criminal Sharia law. + +Breitbart Texas interviewed one of the tribunal’s “judges,” Dr. Taher El-badawi. El-badawi said that the tribunal is done in accordance with Sharia as a form of “non-binding dispute resolution.” He also added that the tribunal is not arbitration. The four Islamic attorneys call themselves “judges” instead of “arbitrators.” He said that the tribunal will resolve civil business and family disputes, as well as workplace disputes. + +El-badawi was asked what would happen if there is conflict between the laws of Texas and Sharia law. He responded that the laws are in agreement most of the time, but said that Sharia would take precedence out of the two in the tribunal. + +There are four judges listed on the tribunal’s website: Imam Yusuf Z.Kavakci, Imam Moujahed Bakhach, Imam Zia ul Haque Sheikh, and Dr. El-badawi.","0" +"Texas Turkey Farm Contaminated With Ebola, Over 250,000 Holiday Turkeys Infected","Texas Turkey Farm Contaminated With Ebola, Over 250,000 Holiday Turkeys Infected. + +A Texas turkey farm employee is now under quarantine after he tested positive for the Ebola virus. Texas Prime Turkey Farm, the largest supplier of turkeys in the United States, has been ordered by the CDC to quarantine over 250,000 holiday turkeys. The CDC has confirmed 3,000 turkeys have tested positive for the virus since Friday’s incident. + +According to investigators, long time employee Philip Canseco was seen vomiting in the facilities restroom three days prior to the incident on Friday. “I was passing by the restroom, when I heard somebody throwing up inside,” said one Texas Prime Turkey Farm employee. “I opened the door and looked inside and saw Canseco throwing up in one of the urinals. I asked him if he was okay, he said yes, and I left. I didn’t want to get close to him and get sick.” + +Management confirmed that Canseco worked three full work days at the facility with flu-like symptoms, before passing out unconscious with a fever of 106°. Due to his symptoms, he was rushed to a local hazmat tent where he tested positive for the Ebola virus. The CDC reports an additional 7 coworkers are being quarantined and tested. However, they have not released those results as of yet. + +The facility has been ordered by the CDC to burn their entire flock of turkeys, over 250,000. Texas Prime Turkey Farm is requesting permission from the state of Texas to send the shipment of incinerated turkey ashes to Veolia’s Port Arthur environmental waste facility. This facility has already accepted one shipment of Ebola waste from household goods where Thomas Eric Duncan had stayed. Duncan was the first man to die of Ebola on US soil. + +Activists are protesting the shipments of contaminated Ebola waste to their community. “We feel every precaution should be taken to protect our community, our children and our elderly. We are not a dumping ground for the nations, or the world’s bio waste.” + +Plant manager Mitch Osborne said on Saturday that even though no contract has yet been signed, the plant will likely receive the second shipment of contaminated Ebola waste. “It is a safe and sound process,” Osborne said. “I am not going to place my employees in harms way, or the community. The company is here to improve the environment and I believe we are doing a pretty darn good job of that. I believe we are doing the right and safe thing.” + +A spokesperson for Texas Prime Turkey Farm said there is a good chance Ebola turkeys may have already shipped out to major suppliers for distribution. Each retailer will have to perform recalls individually if they feel they have received a contaminated shipment.","0" +"Woman Gets Third Boob Implanted, Wants to Be ""Unattractive to Men""","A massage therapist from Tampa, Fla. has spent $20,000 to get a third breast implanted dead center between the right one and the left one as a way to become unattractive to men. She claims that she isn't interested in dating anymore. + +Jasmine Tridevil contacted over 50 doctors before she found a surgeon who was willing to to perform the surgery to add a third breast. In an interview with local radio station Real Radio 104.1, Tridevil explained that ""My mom ran out the door. She won't talk to me. She won't let my sister talk to me. My dad . . . he really isn't happy. He is kind of ashamed of me but he accepted it,"" she said. + +The doctor who performed the surgery couldn't add an areola so Tridevil had one tattooed on instead. As the woman told 104.1, her biggest dream is to have an MTV reality show. + +[Image via Twitter]","0" +"Woman pays $20,000 for third breast to make herself LESS attractive to men","No, you do not need to adjust your sets, you are actually looking at a woman with three breasts. + +Jasmine Tridevil wants to work on TV and in a bid to get there she has spent $20,000 on surgery to get an extra boob. + +It was a bit of an uphill struggle for Jasmine, however, as she says she asked between 50 and 60 doctors but none of them wanted to do it because they would be breaking ethics codes. + +It took two years to save up for the surgery but it has now been finished, topped off with a tattooed nipple. + +She told Real Radio 104.1: My whole dream is to get this show on MTV. + +Scroll down for video + +Her mother and sister are no longer talking to her (Picture: Facebook/Jasmine Tridevil) + +‘I’m dumping every penny I have into this. If this doesn’t work, I’m through. + +She denies that she had the extra breast put on to get fame and fortune. + +Jasmine added: ‘I got it because I wanted to make myself unattractive to men. Because I don’t want to date anymore.’ + +However, her mum and sister will not speak to her and her father is ashamed of her.","0" +"Meet the 3-boobed woman","A woman has spent $20,000 on surgery to get a third breast and her dream is to become a celebrity. + +The Florida massage therapist, who calls herself Jasmine Tridevil, said she had the surgery a few months ago. + +“It was really hard finding someone that would do it, too, because they’re breaking the code of ethics,” Tridevil told Real Radio 104.1. + +“I called like 50 or 60 doctors, nobody wanted to do it.” + +Last month she posted a YouTube video of herself in a bikini while Radiohead’s Creep plays in the background. + +Tridevil said her extra breast felt like her other breasts, “the only difference is the nipple”, which she had to get tattooed on. + +The 21-year-old saved up for two years so she could have the surgery and is also paying for a film crew to follow her around. + +Photo: Faceook“My whole dream is to get this show on MTV,” she said. + +“I’m dumping every penny I have into this. If this doesn’t work, I’m through.” + +Tridevil said that while she wanted fame and fortune, this was not why she had the surgery. + +“I got it because I wanted to make myself unattractive to men. Because I don’t want to date anymore,” she said. + +She has been filmed telling her parents about the third boob and they were not happy. + +“My mum ran out the door. She won’t talk to me. She won’t let my sister talk to me. My dad … he really isn’t happy … he is kind of ashamed of me but he accepted it,” she said. + +While some have criticized Tridevil for her chasing fame, others have described her as “beautiful” and commented that she reminds them of the girl in the sci-fi film “Total Recall.” + +“I love boobs, you have three, what’s not to like … we all loved that girl in Total Recall, now your (sic) the real deal,” said one follower on her Facebook page.","0" +"‘Three-boobed‘ woman: They’re not fake","She made headlines around the world when she revealed she paid thousands of dollars to get a third breast surgically attached to her chest. + +But now Florida woman Jasmine Tridevil is facing claims that the surgery is a fake and she made it all up. + +The claims come as Tampa Bay’s 10 News revealed Tridevil, whose real name is Alisha Jasmine Hessler, had filed an incident report after losing a three-breast prosthesis earlier this month. + +Tridevil filed the report after her bag was stolen from Tampa International Airport on Sept. 16. + +The luggage, which was stolen, allegedly contained a fake breast and 10 News obtained the report which listed the missing contents including a “3 breasts prosthesis.” + +However, Tridevil claims she underwent her surgery a few months ago and it cost $20,000. + +Internet rumor site Snopes also discovered that her JasmineTridevil.com site is registered to Alisha Hessler, someone to whom Tridevil bears a striking resemblance. + +However, when 10 News reporter Charles Bill tracked her down, Tridevil insisted her surgery and third breast were the real deal. + +“I figured people would be skeptical, but it’s true. I recorded the surgery and it will be on my show,” she said. + +Photo: FaceookTridevil insisted the surgery went ahead and she tried 50 to 60 doctors before she found one willing to perform the surgery. + +Surgeons have also dismissed the possibility of it being real. + +New York plastic surgeon Matthew Schulman told The Daily Dot: “[I] believe 100 percent that this is a hoax that everyone is falling for.” + +“I would be happy to go on record claiming that this is a falsified story and essentially not possible.” + +Michigan surgeon Dr. Anthony Youn agreed that while the surgery was possible, it was highly unlikely that anyone would perform it. + +In a YouTube clip, Tridevil said the extra breast felt like her other two but that “the only difference is the nipple,” which she had to get tattooed on. + +The 21-year-old saved up for two years so she could have the surgery and is also paying for a film crew to follow her around. + +She also said her surgery was documented by a film crew and will prove her story is true. + +Tridevil has received plenty of venom on social media and just hours ago posted “Pain is temporary, glory is forever” on her Facebook page. + +Just an hour earlier she wrote: “Don’t be afraid to be different … that’s what makes you beautiful” and also posted a photo of her pre-surgery which won her a host of compliments and questions as to why she would want to change. + +It’s not the first time Hessler has made headlines. + +Last year, she chose to publicly humiliate a man who beat her instead of sending him to prison. + +She said she was introduced to the man when friends of hers invited him out clubbing last December and he beat her after he made unwanted sexual advances. + +She received hospital treatment and a police report was filed. + +But instead of pressing charges, she offered her attacker an ultimatum, telling him, “I can either press charges and have you arrested for a year, or I can have you sit outside at a busy intersection for 8 hours holding up a sign that says ‘I beat women.’” + +This article originally appeared on News.com.au.","0" +"Florida woman claims to have surgically added third breast","A Florida woman — because where else? — claims to have gotten a third breast surgically implanted dead-centre on her chest. + +Jasmine Tridevil (not her birth name) says she spoke with over 50 cosmetic surgeons before she found one willing to break the ethical boundaries of his profession for $20,000. + +“They put a mini-implant to make it look like a nipple poking out,” she told The News Junkie, an Orlando radio show. “And for a while it didn’t have an areola but I got a tattoo.” +The motivation for the third breast was not to pay homage to Total Recall, apparently, but because Tridevil wants to become “unattractive” since she is not interested in dating anymore. This is an explanation that must have made more sense on paper. + +She says she has also hired a camera crew to follow her around in the hopes that MTV will give her a reality TV show. + +“I saved up for two years and I didn’t spend any of that money,” she said. “I’m dumping every penny I have into this so if it doesn’t work, I’m through.” + +She also said relations with her parents were somewhat strained after she revealed her surprise surgery to them. + +There is no way to confirm if Tridevil’s breast implant is real but she has been gaining thousands of Facebook and Twitter fans since the story broke Monday morning. So: mission accomplished, either way.","0" +"Florida woman gets third breast surgically implanted","You've heard of the third nipple — but what about a third breast? + +A Tampa massage therapist, Jasmine Tridevil, underwent surgery to get just that. Tridevil told Orlando radio station Real Radio 104.1 that she spent close to $20,000 on the procedure. + +Tridevil told the station that she contacted more than 50 doctors before finding one who would give her the third breast. ""It was really hard finding someone that would do it too because they're breaking the code of ethics,"" she said. The surgeon she found couldn't create a silicone areola, though, so she had one tattooed onto the implant, which is made from silicone and skin tissue from her stomach. + +While Tridevil's dream is to star in an MTV reality show, she told the radio station she had the surgery to become ""unattractive to men"" in addition to gaining fame. ""I don't want to date anymore,"" she said. + +Tridevil also noted that her parents are displeased with the surgery — her mother no longer speaks to her, and her father ""really isn't happy"" but has ""accepted it,"" she said. --Meghan DeMaria + +#3Boobs #MTV pic.twitter.com/pzAkrsTYpz — Jasmine Tridevil (@JasmineTridevil) September 15, 2014","0" +"Florida woman reportedly gets third breast surgically implanted","You've heard of the third nipple — but what about a third breast? + +A Tampa massage therapist, who goes by Jasmine Tridevil, reportedly underwent surgery to get just that. Tridevil told Orlando radio station Real Radio 104.1 that she spent close to $20,000 on the procedure. + +Tridevil told the station that she contacted more than 50 doctors before finding one who would give her the third breast. ""It was really hard finding someone that would do it too because they're breaking the code of ethics,"" she said, adding that she allegedly signed a non-disclosure agreement, so she couldn't reveal what doctor had performed the surgery. Tridevil reports that the surgeon she found couldn't create a silicone areola, though, so she reportedly had one tattooed onto the alleged implant, which she says is made from silicone and skin tissue from her stomach. + +While Tridevil says her dream is to star in an MTV reality show, she told the radio station she had the surgery to become ""unattractive to men"" in addition to gaining fame. ""I don't want to date anymore,"" she said. + +Tridevil also noted in the interview that her parents are displeased with the surgery — her mother no longer speaks to her, and her father ""really isn't happy"" but has ""accepted it,"" she said. + +Update: Snopes reports that Tridevil's story may be too good to be true, since the only images of Tridevil's implant come from Tridevil herself. Snopes also discovered that the now-defunct domain name JasmineTridevil.com is registered to Tampa massage therapist Alisha Hessler. Meanwhile, in an interview with Tampa's WTSP 10 News, Tridevil maintained that the story was real and that she had recorded her surgery, which would be aired on her show. The story hasn't been officially confirmed as real or fake, but in the age of internet hoaxes, anything is possible. --Meghan DeMaria + +#3Boobs #MTV pic.twitter.com/pzAkrsTYpz — Jasmine Tridevil (@JasmineTridevil) September 15, 2014","0" +"This Woman Claims To Have Had Plastic Surgery To Have A Third Breast","Jasmine Tridevil (not her real name) is a young lady from Tampa, Florida. + +Here is a troubling radio interview with her about why she allegedly got a third breast a few months ago and how hard it was to get one. She said that she was told to “sign a nondisclosure agreement” and had to call scores of doctors before she could find one who would do it because it was such a breach of ethics. She didn’t reveal the name of the doctor who performed the procedure. + +Over the course of the interview, during which the hosts asked some unbelievably inappropriate questions, she said the surgery cost $20,000, that she saved up for two years so that it could happen, that her mum won’t talk to her and won’t let her sister talk to her, and that her dad is unhappy. She said it’s not just about fame. + +On the station, the 21-year-old said: “I got it because I wanted to make myself unattractive to men. Because I don’t want to date anymore.” + +She said a “mini-implant” was put in so it had a nipple, and an areole was tattooed around it. The breasts apparently don’t quite “match up”. + +She told the station: “The reaction has been crazy.” + +Facebook: 510456172418517 + +Facebook: 510456172418517 + +It’s not entirely unsurprising. Thus far she seems to be enjoying the attention, writing on her Facebook page, “So I’m flying to New York to appear on The Inside Edition show this Monday! Then going to be on the news, Jimmy Kimmel show and Vice magazine! oh and a few radio shows!” + +BuzzFeed News has reached out to her for further comment. + +update + +Consultant plastic surgeon and British Association of Aesthetic Plastic Surgeons Nilesh Sojitra told BuzzFeed News: + +“This is a clear case of a patient who should not have had surgery performed on her. Someone making this kind of request may have body dysmorphia disorder, or not have thought through the long-term consequences of such a surgery – she will now be scarred for life – and may have benefited from psychological evaluation rather than surgery. Additionally, the actions of the surgeon are unethical and they have acted in a way where no reasonable plastic surgeon would.” BF_STATIC.timequeue.push(function () { document.getElementById(""update_article_update_time_3863178"").innerHTML = UI.dateFormat.get_formatted_date('2014-09-22 10:32:25 -0400', 'update'); });","0" +"Fake or freak? Woman, 21, claims to have paid $20,000 to surgically add third breast in desperate bid to become a reality TV star","Jasmine Tridevil, 21, 'paid $20,000 to add a breast to become a TV star' + +She was 'rejected by 50 doctors who feared violating ethical codes' + +It took her two years to find willing surgeon who would also add a nipple + +She now has a film crew tracking her 'struggles as a three-breasted woman' + +A 21-year-old woman claims to have paid $20,000 to surgically add a third breast in a desperate bid to become a reality TV star. + +Jasmine Tridevil, not her real name, insists she was rejected by more than 50 doctors who feared violating ethical codes before she found a willing surgeon who would perform the procedure. + +Now, she has hired a camera crew to follow her around Tampa, Florida, documenting the 'struggles' she faces as a three-breasted woman. + +Scroll down for video + +Three-breasted? Jasmine Tridevil, 21, claims she paid $20,000 to have a third breast surgically attached to her chest. She is now filming her own reality show about the struggles she faces as a three-breasted woman + +Surgeons are reluctant to perform unnatural procedures as the ethical code outlined by the American Board of Plastic Surgeons dictates that 'the principal objective of the medical profession is to render services to humanity with full respect for human dignity.' + +Tridevil claims she found a surgeon who agreed to carry out the operation on the grounds that she kept their name a secret. + +The massage therapist, who recently celebrated her 21st birthday, has shared dozens of pictures of her new look in custom made bikinis on her Facebook fan page in a bid to convince followers the surgery was legitimate. + +And she has proudly declared that she been disowned by her mother and sister, who ran out the room in disgust when they saw what she had done. + +'My mum ran out of the door. She won't talk to me. She won't let my sister talk to me,' Tridevil said. + +Dreams of being a star: The massage therapist from Tampa, Florida, said her dream is to have a show on MTV + +'My dad… he really isn't happy. He is kind of ashamed of me but he accepted it.' + +However, Tridevil insists she has no regrets as she prepares to send pilot episodes of her self-produced reality show titled Jasmine's Jugs to MTV. + +'My whole dream is to get this show on MTV,' she told Real Radio 104.1. + +'I'm dumping every penny I have into this. If this doesn't work, I'm through.' + +Despite scheduling interviews, creating a fan page, and hiring a film crew, Tridevil insists her apparent surgery was not an attempt become famous. + +Reminiscent: Her new look is similar to that of the three-breasted prostitute in the 1990 film Total Recall + +Disowned: Tridevil, who recently celebrated her 21st birthday, says she has been disowned by her mother + +'I got it because I wanted to make myself unattractive to men,' she claims. 'Because I don't want to date anymore.' + +The new look is reminiscent of the alluring three-breasted prostitute who parades around semi-topless in the 1990 Arnold Schwarzenegger film Total Recall. + +The bizarre character prompted one of the most famous movie quotes to date, as a man declares: 'Baby, you make me wish I had three hands!'","0" +"Report: Woman claims she had third breast added, hopes to become a TV star","You won’t believe this one. + +According to Buzzfeed, a young woman from Tampa, Fla., has become the latest viral sensation by claiming she had plastic surgery to get a third breast. She even claims her strange look has landed her appearances on “Inside Edition” and “Jimmy Kimmel Live!” + +But so far at least that part of her story isn't panning out. + +The woman, who goes by the name Jasmine Tridevil, wrote on Facebook: “So I'm flying to New York to appear on The Inside Edition show this Monday! Then going to be on the news, Jimmy Kimmel show and Vice magazine! oh and a few radio shows!” + +FOX411 talked to ""Inside Edition,"" and they told us they are not interviewing her. And she's not on the schedule that gets sent out with ""Kimmel'"" guests either. + +But Kimmel is famous for online pranks, including a viral video called ""Worst twerk fail EVER,"" purportedly of a hilarious twerking accident, that turned out to be staged by his show. + +HEALTH: Purported third-breast add raises medical, ethical questions + +In trying to further track down the story, we did find Tridevil's real name and cell phone number, and we gave her a call, but so far have not received a reply to our voice mail message. + +Which is a shame, because we have several questions to ask about her unique tale. + +Tridevil said in a recent radio interview that she got the surgery “a few months ago” and had a very hard time finding a doctor who would agree to her request. + +“They did have an issue with it and it was really hard finding somebody that would do it too because they are breaking the code of ethics to do it,” she said. “I called 50 or 60 doctors and no one would do it.” + +She says when she eventually found a doctor who agreed to do her surgery, she had to sign a confidentiality agreement stating she wouldn’t reveal his identity. She said paid $20,000 for the purported surgery. + +Tridevil also says she is currently filming her own reality show that she hopes will land on MTV. + +Well, she would most likely have a role if they ever decided to do another ""Total Recall"" remake. + +WATCH: Four4Four: Duke porn star next on Vogue cover?","0" +"Jasmine Tridevil Has Surgery 'To Add Third Breast' Total Recall Style","A massage therapist claims to have undergone plastic surgery to obtain a third breast. + +Jasmine Tridevil (not her real name) says she had the surgery “a few months ago” and is now hell bent on starring in her own reality TV show. + +The 21-year-old has hired a camera crew to follow her around and hopes to pitch her show to MTV. Writing on her Facebook page, she says she has upcoming appearances on the Jimmy Kimmel show and the Inside Edition. + +Jasmine Tridevil says she had to contact more than 50 doctors before she found one willing to perform the surgery + +Of the controversial surgery, she told Real Radio 104.1 she had to contact more than 50 doctors before she found a surgeon who agreed to carry out the procedure. + +“It was really hard finding someone that would do it too because they’re breaking the code of ethics.” + +Of the one who agreed to carry out the operation, she claimed: “He made me sign a non-disclosure agreement as he was scared he’d get in trouble.” + +Tridevil dreams of starring in her own reality TV show + +Tampa resident Tridevil, who recently celebrated her 21st birthday, says her parents have not taken the news of her transformation well. + +She said: “My mum ran out of the door. She won’t talk to me. She won’t let my sister talk to me. My dad… he really isn’t happy. He is kind of ashamed of me but he accepted it.” + +Tridevil says the surgery cost $20,000 and that included a “nipple” implant. She claims to have had an areole tattooed around the nipple after the surgery. + +Looks familiar: The three-breasted woman first made an appearance in 1999's Total Recall + +She also revealed: “I got it because I wanted to make myself unattractive to men. Because I don’t want to date anymore. + +“Most guys would think [the extra breast is] weird and gross. But I can still feel pretty because if I wore makeup and cute clothes, I can still, you know… feel pretty.” + +Um, right. + +Tridevil’s bold new look is of course reminiscent of that infamous scene from the 1999 Arnold Schwarzenegger film Total Recall. + +Kaitlyn Leeb reprised the role in the 2012 remake of the film + +Upon meeting a prostitute with three breasts, one enamoured suitor exclaims: “Baby, you make me wish I had three hands!” + +The film was remade in 2012, and yes, the three-breasted woman made another appearance. + +Toronto-based model and actress Kaitlyn Leeb took the role and even decided to display her (prosthetic) triple cleavage at a Comic Con event. + +We think you’ll agree Leeb’s prosthetics are pretty convincing – could it be that Tridevil simply followed suit and hasn’t been under the knife after all?","0" +"Is Jasmine Tridevil's Triple Breasted Tale An Internet Hoax?","It was with a healthy dose of scepticism that we brought you reports of a 21-year-old woman who allegedly had surgery to obtain a third breast. + +The massage therapist from Tampa, Florida claimed to have paid $20,000 for the procedure in an attempt to secure herself a reality show on MTV. + +Using an obvious pseudonym, Jasmine Tridevil told an American radio station she had to contact more than 50 doctors before she found a surgeon willing to operate. + +Jasmine Tridevil says she had to contact more than 50 doctors before she found one willing to perform the surgery + +She claims the one who did agree forced her to sign a non-disclosure agreement in order to protect his anonymity, because he was ""breaking the code of ethics"". + +Tridevil’s dubious story is not helped by the fact that all the available images of her appear to have been taken by herself, with no third parties present, and that the footage she has posted is decidedly grainy. + +And now the internet sleuths of Snopes have weighed in with some pretty convincing research that indicates Tridevil may be playing the media. It points out: + +'...The JASMINETRIDEVIL.COM domain was registered by someone named Alisha Hessler, and Jasmine Tridevil herself bears a striking likeness to Tampa-area massage therapist Alisha Jasmine Hessler (whose ""Alisha's Golden Touch"" massage web site now bears legends identifying her as ""Provider of internet hoaxes since 2014"" and ""Specialist in massage for three breasted women""). Photos on a modeling page linked with Hessler closely matched the circulating images of Jasmine Tridevil, and profile pictures on Hessler's YouTube page strongly resembled the woman in the ""third breast"" photos.' + +Snopes also claims an Alisha Jasmine Hessler was taken into custody in Florida last year and charged with fraudulent use of personal information and that a woman with the same name has had previous brushes with viral fame. + +However Tridevil continues to insist she and her three breasts are the real deal. + +She told The Sun (£): “This is not a fake. I had a procedure done. If people don’t believe it, that’s up to them.” + +Tridevil dreams of starring in her own reality TV show + +She also claims her self-financed film crew recorded footage of her operation, adding: “I plan to release it on my reality TV show and I don’t really care what people think or say about me. + +“I know what I have done. As I say this is not a fake or a hoax.” + +Speaking exclusively to 10 News Tampa, Tridevil obliged the channel with a ""quick flash"" of her third breast, but when asked why she wouldn't allow a closer look, replied with: ""I'm not ready to do that right now because it's in episode six of my show."" + +Meanwhile Jezebel spoke to an attending plastic surgeon at Cedars-Sinai Medical Centre in Los Angeles. + +Looks familiar: A three-breasted woman makes an appearance in 1990's Total Recall + +Kaitlyn Leeb reprised the role in the 2012 remake of the film + +Dr Mossi Salibian, a member of the hospital’s multidisciplinary breast expert team, said such a procedure would be possible, but mercifully added he didn’t believe any doctor would perform such an operation. + +He said: “There are many things that are possible, but that doesn’t mean we would do it.” + +Over to you, dear readers.","0" +"Woman Adds Third Breast by Undergoing Surgery to Participate in Reality Show","In order to become a reality star, a woman from Florida underwent an expensive surgery to implant a third breast on her chest. + +Massage therapist Jasmine Tridevil (not her real name) decided to take the extreme step as she wants her own reality show on MTV, the 9 News reported. + +Tridevil reportedly spent $20,000 to have a third breast. The procedure was done a few months ago and the extra breast was constructed with silicone implants and skin tissues taken from her abdomen, the website reported. + +However, Tridevil's doctors could not create an artificial areola, which she managed on her own by tattooing it. + +Nevertheless, the reality show aspirant had a difficult time finding a doctor who would do the procedure by ignoring medical ethics. + +""I called 50 doctors. It was really hard finding someone who would do it too because they're breaking the code of ethics,"" she told real radio 104.1, via 9News. + +When asked about her family's reaction to the creepy news of her third breast implant, she said: ""My mum ran out of the door. She won't talk to me. She won't let my sister talk to me. My dad, he really isn't happy. He is kind of ashamed of me but he accepted it."" + +Tridevil went on to claim she wanted this to happen to make herself look unattractive as she is not interested in dating anymore. + +""I got it because I wanted to make myself unattractive to men. Because I don't want to date anymore,"" she said. + +""Most guys would think [the extra breast is] weird and gross. But I can still feel pretty because if I wore make-up and cute clothes, I can still, you know, feel pretty."" + +Reality shows on popular networks have always fascinated youngsters who want to grab their 15 minutes of fame and become popular. + +""Reality and fantasy are blurred. The consequences of bad behaviour and poor choices are never questioned. On the contrary, bad behaviour is welcomed because sensationalism attracts more viewers. The danger lies in that they lose sight of their own sense of self-worth and critical thinking,"" a report from NDLA reads. + +RelatedIsis Offers Cash for Babies: Islamic State Luring American Women to Bear Children of MilitantsIndia: Karan Singh is World's Tallest 5-Year-Old at 5ft 7inUS Teenager Faces Two Years In Jail For 'Oral Sex' with Jesus StatueHuge Alien-Like Shrimp Caught by Florida Couple on a Fishing Date","0" +"Woman has surgery to get third breast: The three most statistically unlikely pairs of boobs","After the news that a Floridian woman had an operation to add a third boob to her chest, we decided to look at the world's weirdest breasts + +Jasmine Tridevil, a Floridian massage therapist, has had an operation to give herself a third breast, in what is perhaps the most controversial boob job of 2014. + +We decided to look at the three most statistically unlikely pairs of breasts in the world. + +1. Jasmine Tridevil- Three breasts + +Jasmine had to call 50-60 doctors in order to get her controversial operation. She said: “It was really hard finding someone that would do it, too, because they’re breaking the code of ethics”. + +She did it because she wanted a reality TV show on MTV, but she had another reason, too. + +“I got it because I wanted to make myself unattractive to men. Because I don’t want to date anymore.” + +Average: Most women have two breasts + +2. One of the most extreme boob jobs + +Model Sarah Marie Summer - who's addicted to boob jobs The 23-year-old glamour model who has had three surgeries to go up a whopping 18 bra sizes wants to go even bigger + +We didn't know this was possible. + +Sarah Marie Summer, from Sydney, who is 'addicted to boob jobs' went up 18 cup sizes and has had four boob jobs. + +Her boob jobs, which have got her to an M cup, have won her fans and modelling work. + +This is one of the most extreme possible boob jobs. + +Average: The average UK bra size is a 34 DD. + +3. World's largest natural boobs- 48V + +Annie Hawkins-Turner won the Guinness World Record for the biggest natural breasts. Her boobs started developing at the age of nine. She said: ""I just started growing, and kept right on. I started wearing a bra when I was in third grade, and it was a regular grown-up woman's bra. I don't remember ever wearing a training bra."" + +Average: The average UK bra size is a 34 DD. + +Poll loading …","0" +"Jasmine Tridevil: The woman with three breasts","A WOMAN has spent $20,000 on surgery to get a third breast and her dream is to become a celebrity. + +The Florida massage therapist, who calls herself Jasmine Tridevil, said she had the surgery a few months ago. + +“It was really hard finding someone that would do it, too, because they’re breaking the code of ethics,” Tridevil told Real Radio 104.1. + +“I called like 50 or 60 doctors, nobody wanted to do it.” + +Last month she posted a YouTube video of herself in a bikini while Radiohead’s Creep plays in the background. + +Tridevil said her extra breast felt like her other breasts, “the only difference is the nipple”, which she had to get tattooed on. + +The 21-year-old saved up for two years so she could have the surgery and is also paying for a film crew to follow her around. + +“My whole dream is to get this show on MTV,” she said. + +“I’m dumping every penny I have into this. If this doesn’t work, I’m through.” + +Tridevil said that while she wanted fame and fortune, this was not why she had the surgery. + +“I got it because I wanted to make myself unattractive to men. Because I don’t want to date anymore,” she said. + +She has been filmed telling her parents about the third boob and they were not happy. + +“My mum ran out the door. She won’t talk to me. She won’t let my sister talk to me. My dad ... he really isn’t happy ... he is kind of ashamed of me but he accepted it,” she said. + +While some have criticised Tridevil for her chasing fame, others have described her as “beautiful” and commented that she reminds them of the girl in the sci fi film Total Recall. + +“I love boobs, you have three, what’s not to like ... we all loved that girl in Total Recall, now your (sic) the real deal,” said one follower on her Facebook page. + +@JasmineTridevil Big props to you for doing wtf you want!— Danny Boy Gim (@TugMusic) September 15, 2014 + +@JasmineTridevil Big props to you for doing wtf you want! + +3 boobs are better than 2...I guess. #flawdah #jasminetridevil #crazypants pic.twitter.com/8Y0rqBOzDM— ThingsHeardBackstage (@ThingsheardBS) September 16, 2014 + +3 boobs are better than 2...I guess. #flawdah #jasminetridevil #crazypants pic.twitter.com/8Y0rqBOzDM + +watttttaaaa f... ??!! ""Jasmine Tridevil is a 21 year old woman who got a 3rd breast implant"" what a mad world— Ren Höek (@Raccoon_Ren) September 19, 2014 + +watttttaaaa f... ??!! ""Jasmine Tridevil is a 21 year old woman who got a 3rd breast implant"" what a mad world + +@JasmineTridevil is that really not photoshopped? As long as youre happy, Enjoy It, but take care on yourself, showbiz is a crazy business— hedgehog (@redojame) September 20, 2014 + +@JasmineTridevil is that really not photoshopped? As long as youre happy, Enjoy It, but take care on yourself, showbiz is a crazy business","0" +"Florida woman has surgery to add third breast to make herself 'unatttractive to men'","Jasmine Tridevil, 21, spent $20,000 for the plastic surgery, she told an Orlando radio station. 'To me it just feels like another boob,' she says. 'The only difference is the nipple, that doesn't feel like the other ones.' + +One of these things is not like the others. + +A 21-year-old Florida woman says she spent $20,000 for a third breast to make herself ""unatttractive to men."" + +The admittedly ""crazy"" massage therapist, who goes by the name Jasmine Tridevil, told an Orlando radio station in a bizarre interview that she had the plastic surgery because she doesn't want to date anymore. + +""Well I am crazy,"" she told the ""The News Junkie"" show last week. ""Crazy people don't know they are crazy, so technically since I know I'm crazy I'm not crazy."" + +She said she had to see countless doctors before finding one who would do the surgery. The procedure cost $20,000, she told the radio station. + +Tridevil has aspirations to be a reality star, and hopes to get a show on MTV. + +When asked about her new addition, she told the station that ""to me it just feels like another boob. The only difference is the nipple, that doesn't feel like the other ones."" + +Her parents, though, apparently did not take the news in stride. + +""I told my mom on camera,"" she told the station. ""(She) ran out the door."" + +dboroff@nydailynews.com + +USING MOBILE? CLICK FOR VIDEO","0" +"Florida woman has surgery to add third breast to make herself 'unattractive to men'","Jasmine Tridevil, 21, spent $20,000 for the plastic surgery, she told an Orlando radio station. 'To me it just feels like another boob,' she says. 'The only difference is the nipple, that doesn't feel like the other ones.' + +One of these things is not like the others. + +A 21-year-old Florida woman says she spent $20,000 for a third breast to make herself ""unattractive to men."" + +The admittedly ""crazy"" massage therapist, who goes by the name Jasmine Tridevil, told an Orlando radio station in a bizarre interview that she had the plastic surgery because she doesn't want to date anymore. + +""Well I am crazy,"" she told the ""The News Junkie"" show last week. ""Crazy people don't know they are crazy, so technically since I know I'm crazy I'm not crazy."" + +She said she had to see countless doctors before finding one who would do the surgery. The procedure cost $20,000, she told the radio station. + +Tridevil has aspirations to be a reality star, and hopes to get a show on MTV. + +When asked about her new addition, she told the station that ""to me it just feels like another boob. The only difference is the nipple, that doesn't feel like the other ones."" + +Her parents, though, apparently did not take the news in stride. + +""I told my mom on camera,"" she told the station. ""(She) ran out the door."" + +dboroff@nydailynews.com + +USING MOBILE? CLICK FOR VIDEO","0" +"Breast Chancer","Claim: Florida woman Jasmine Tridevil underwent surgery to add a third breast. + +UNDETERMINED + +Example: [Collected via e-mail, September 2014] + +""A WOMAN has spent $20,000 on surgery to get a third breast and her dream is to become a celebrity."" + +Well, this has 'What does Snopes say?' written all over it! + +Origins: On 22 September 2014, a strange story of body modification appeared on the social web. According to several circulating articles, a Florida woman named Jasmine Tridevil underwent cosmetic surgery to add a ""third breast"" to her body. + +In the initial frenzy of interest in Jasmine Tridevil and her purported third breast, lots of linking and re-posting of the same information and images occurred. However, few looked very deeply at the claims made by the woman shown in the images or her agents, or whether such a modification was even feasible. + +A New York article about the woman's third breast reveals a potentially relevant aspect of Tridevil's claim. According to the site, the Florida woman claims her surgeon forced her to sign a non-disclosure agreement, and therefore the obvious avenue of corroboration for her claim is closed off: + +The 21-year-old massage therapist claims she had to ask over 50 doctors to perform the surgery, which involved taking skin tissue from her abdomen and adding a silicon implant. She also got an areola tattooed on. The procedure cost $20,000, and Tridevil had to sign an NDA so couldn't disclose what doctor performed it. + +As Jasmine Tridevil's claims about a third breast circulate the social web, most information being reported appears to come directly from the subject herself without any external confirmation. Tridevil's Facebook page and YouTube account appear to be the primary source for verification, despite the fact that both host only self-taken videos and photos. In one clip posted by Tridevil, her ""breasts"" appear to be of an entirely different skin tone than her facial skin and limbs: + +Another red flag in Tridevil's tale is her stated motivations. Surgeons are ethically bound to decline performing cosmetic surgery on patients without certain mental health clearances (i.e., ensuring that patients do not have unrealistic expectations or motivations driven by psychological disorders), and in an interview Tridevil made the rather bizarre claim she set out to make herself look less attractive to men by opting to get a third breast implant: + +I got it because I wanted to make myself unattractive to men. Because I don't want to date anymore ... Most guys would think [the extra breast is] weird and gross. But I can still feel pretty because if I wore makeup and cute clothes, I can still, you know ... feel pretty. + +Jasmine Tridevil's third breast tale has a few other potential inconsistencies. Despite claiming to have undergone an incredibly rare procedure, she does not go into detail about the operation or state whether she had her other breasts enhanced to match the third one. No third party images of Tridevil have emerged, and while she claims to have booked appearances on Jimmy Kimmel Live and Inside Edition , no evidence has emerged to suggest that any media sources have vetted the story. + +We have submitted a request for an interview with Jasmine to verify her claim and have not yet received a response. + + + +","0" +"Florida woman gets third breast to become 'unattractive' 32","A Florida massage therapist said she paid $20,000 for a third breast in hopes of becoming less attractive to men + +""I don't want to date anymore,"" Jasmine Tridevil told Orlando's Real Radio 104.1. + +Tridevil, 21, has documented her post-surgery life through photos and videos posted to YouTube, Facebook and other social media sites -- mostly images of her posing in custom-made three-cup bikinis and bras. + +Her desire to repel the opposite sex with her updated anatomy wasn't her only motivation for the surgery: Tridevil also hopes to have her own show on MTV someday. + +She said she contacted more than 50 doctors before she found a surgeon willing to perform the operation.","0" +"Tampa woman claims to add 3rd breast","Tampa, Florida -- She's an Internet sensation: Jasmine Tridevil, the 21-year-old Tampa woman who claims to have had a third breast implanted. Her video on YouTube has almost a million hits and her pictures on Facebook have gone global. + +10 News spoke with her in an exclusive interview. + +""I figured people would be skeptical, but it's true. I recorded the surgery and it will be on my show,"" said Tridevil. + +She agreed to the interview on the condition we only discuss her self-produced show she hopes will be picked up by a cable network, and when we asked to see her third breast, she obliged, but with only a quick flash. When asked her why we couldn't have a longer look Tridevil responded, ""I'm not ready to do that right now because it's in episode six of my show."" + +Some of the comments from the public have been cruel. Tridevil says she predicted that, but she is willing to do whatever it takes to be famous. Dr. Dan Greenwald of Bayshore Plastic Surgery in Tampa says that raises a lot of red flags. + +""I think its very extreme, and that leads me to wonder why she needs this attention. Is there some instability? Is there something psychologically lacking or out of balance for this person,"" said Greenwald. + +And Jasmine's reaction to that. + +""I saw it coming."" + +Other stories you may find interesting...","0" +"Tiger Woods serving secret PED suspension?","A PGA Tour golfer said he has sources who tell him that Tiger Woods is currently serving a one-month suspension for PED use. + +Tiger Woods has had a tough career as of late, plagued with injuries and surgeries that have complicated his strong golf swing, and now that he’s taken “a leave of absence” until his golf game is “tournament ready,” he’s facing criticism. + +MORE FROM GOLF +3/2 - Tiger Woods’ Agent, PGA Refute Claims Of PED Suspension +3/1 - Rickie Fowler And Kid Rock Give Advice To Tiger Woods +2/28 - Ian Poulter’s Caddie Chases A Duck (Video) +2/27 - Rory McIlroy Thinks U.S. Is Desperate For Ryder Cup Win +2/25 - Yahoo Fantasy Golf Picks: The Honda Classic 2015 +This criticism blew up Monday morning when professional, but not well-known PGA Tour golfer Dan Olsen went on a radio interview with David “Mad Dog” DeMarco on 730 WVFN’s The Game in Lansing, MI and claimed that Tiger Woods is serving a suspension for using PEDs. + +“I heard he’s on a month suspension,” Olsen said. “And it’s kind of a strong witness, a credible person that’s telling me this… It’s not testosterone, but it’s something else. I think when it is all said and done, he is going to surpass Lance Armstrong with…a…infamy.” + +WOW. Dan Olsen, who are you? + +Olsen’s dislike for Tiger Woods must be really strong if he’s going to go on radio and make wild claims that haven’t been evidenced by anything or anyone else. + +As if this wild claim wasn’t enough, Olsen went on to basically say that Tiger is just one big cheater and dragged Rory McIlroy into it. + +“Tiger, he’s got some problems now,” Olsen said. “One of the big problems, Nike’s been giving Tiger a ball that I would almost bet hasn’t been tested…Rory played it too. Remember when Rory signed the Nike deal and he played like an amateur for a year? He was going to fail out of the contract unless he got the high-spin ball too… So if you go to Tour events, Nike pays them, pays the Tour staff and the range staff, they pay them to get all those balls back. That’s why Tiger would never sign a golf ball and give it away… He played a ball that nobody else could play.” + +Again, wow. Dan Olsen is going all in on Tiger Woods, staking his reputation (which obviously isn’t much because most people have never heard of him) to call out Tiger as a cheater. + +It’s a tough claim to believe, and one you don’t want to believe, either. Tiger Woods is one of the best golfers to play the game and when he’s done he’ll be remembered as the best. + +Tiger has played two PGA Tour events this year and he missed the cut in Phoenix in January and withdrew from the Farmers Insurance Open in early February after suffering back pain. Because of his back surgery last summer, I guess it wouldn’t be shocking that Tiger would take PEDs, but IF he even has, they certainly haven’t helped him at all. And Tiger is a veteran, he knows about drug testing and he’s gone through it his whole career. + +The claims by Olsen, who has played in 35 PGA Tour events in his career with no top ten finishes, seem farfetched and forced, but you can’t discount them completely. We’ll see if this prompts Tiger Woods or the PGA of America to make a statement denying these facts or coming clean on something that may or may not be true.","0" +"Former PGA Tour player: Tiger Woods suspended for drug test failure","A former PGA Tour player claims Tiger Woods has been suspended for one month under the Tour’s anti-doping program. + +Dan Olsen, who has made 35 career PGA Tour starts and was an exempt player for the 2004 season, made the claim Friday on radio station WVFN to host David DeMarco. + +“I’ve heard that he’s on a month(-long) suspension,” Olsen said, claiming the information came from “exempt Tour players.” Olsen said Woods did not test positive for testosterone but for “something else.” + +Olsen continued, “I think when it’s all said and done, he’s going to surpass Lance Armstrong in infamy.” + +Woods’ agent Mark Steinberg released a statement to Golf News Net, saying, “These claims are absolutely, unequivocally and completely false. They are unsourced, unverified and completely ridiculous. The PGA Tour has confirmed that there is no truth to these claims.” + +PGA Tour media official Joel Schuchmann released a statement on behalf of the Tour, saying, “Regarding the allegations made by Dan Olsen concerning Tiger Woods, there is no truth whatsoever to his claims and the PGA Tour categorically denies them.” + +The Michigan-based pro added he believes Woods was faking the back tightness that Woods cited in withdrawing from the Farmers Insurance Open after just 11 holes. + +Olsen, whose last PGA Tour start was the 2011 PGA Championship, also made several wild accusations concerning Woods’ golf ball, incorrectly identifying dates during which Woods made changes in the ball he uses. Olsen alluded to comments made by Golf Channel analyst Frank Nobilo concerning the advantage he felt Woods had in 2000 (not 1998 or 1999 as Olsen claimed) in switching to Nike’s first solid-core golf ball. After switch in May 2000, Woods went on to win the final three majors that year, just before Titleist introduced its Pro V1. + +Further, Olsen claimed Rory McIlroy wanted out of his Nike contract if he couldn’t have access to the same ball as Woods. + +Switching subjects, Olsen also claimed PGA Tour commissioner Tim Finchem personally visited Dustin Johnson’s home twice in an effort to help the pro with his “personal challenges” before a six-month leave of absence from golf that ended in February. Johnson has disputed a Golf.com report saying he was suspended for that half-year period because of a failed drug test under the Tour’s anti-doping program.","0" +"PGA Tour Pro Claims Tiger Woods Is Currently Suspended For PEDs, Compares Him To Lance Armstrong","For the last few weeks, the general public has assumed that Tiger Woods hasn’t been playing on Tour because of his back and a dog shit golf game, but PGA Tour golfer, Dan Olsen — don’t worry, I haven’t heard of him before either — is saying that’s simply not the case. Olsen went on record, during a radio interview with 730 WVFN’s David “Mad Dog” DeMarco, claiming his sources are telling him that Tiger Woods is currently serving a one month suspension for failing a drug test. Later in the interview, Olsen says his sources are “Tour players that are exempt.” + +Per Olsen’s interview with 730 WVFN: + +“I heard he’s on a month suspension. And it’s kind of a strong witness, a credible person that’s telling me this… It’s not testosterone, but it’s something else. I think when it is all said and done, he is going to surpass Lance Armstrong with…a…infamy.” + +Olsen didn’t stop at PED’s. He even goes as far as claiming Tiger Woods has allegedly been using questionable golf balls since the late 1990s. So questionable, in fact, that Nike has paid PGA Tour staff to pick up all the balls so no one get’s the balls. + +“Tiger, he’s got some problems now. One of the big problems, Nike’s been giving Tiger a ball that I would almost bet hasn’t been tested…Rory played it too. Remember when Rory signed the Nike deal and he played like an amateur for a year? He was going to fail out of the contract unless he got the high-spin ball too… So if you go to Tour events, Nike pays them, pays the Tour staff and the range staff, they pay them to get all those balls back. That’s why Tiger would never sign a golf ball and give it away… He played a ball that nobody else could play.” + +I have personally seen Rory McIlroy throw his golf balls into the stands, so I don’t know how valid this ball claim is. But, WOW. Dan Olsen must have very few fucks left to give if he’s publicly calling out Tiger Woods as a cheater on multiple levels. + +Thanks to BroBible writer and PGA Tour caddie, Pinot Pete, for getting this interview on our radar. And while Pinot Pete could not corroborate Olsen’s claim — nor would he probably want to, because LAWSUITS — he did say, “I’ve known Dan Olsen for 10 years. And in all that time, I’ve never known him to stretch the truth.” So there’s that.","0" +"SHOCK CLAIM: PGA Golfer Says Tiger Woods Is Suspended For Failed Drug Test","PGA golfer Dan Olsen told WVFN that he has learned that Tiger Woods failed a drug test for performance enhancing drugs and has been suspended by the PGA. + +Dan Olsen: “Well, I’ve heard that he’s suspended. I heard he’s on a month’s suspension. And it’s kind of a strong witness. A credible person is telling me this. Well, it’s not testosterone but it’s something else. I think when it’s all said and done he’s going to surpass Lance Armstrong with infamy… + +WVFN host: Well, he’s already put a big dent in his situation with the circumstance he got himself into philandering behind his wife’s back… + +Dan Olsen: That’s nothing though. This is going to be surpass that. The women are going to take a distant second place.","0" +"Tiger Woods selling Swedish villa — island included","Golfers, take note — Tiger Woods’ Swedish luxury island, complete with six tee-off locations, is now up for grabs. + +Located in Lake Mälaren, Sweden, the island was previously home to Woods and his then-wife, Swedish native Elin Nordegren, before their marriage famously collapsed in 2010 due to Woods’ infidelity. + +In addition to being a golfer’s paradise, the 62-acre haven features a villa, hunting lodge, private ferry boat, horse stables and landing strip for propeller planes. + +Sabine Rollinger of Vladi Private Islands, who are listing the island, told Mercury Press Agency that the escape is “unique due to its central location, as the Swedish capital is only about an hour away by boat or car, and from there you have swift access to the Stockholm archipelago.” + +The property is also home to a historic 11th-century Viking stronghold, “a dramatic landscape with approximately 30-meter-high rocks rising out of the lake.” + +Lake Mälaren is an enviable swim destination, as the water temperature reaches up to 79 degrees Fahrenheit in the summer months. + +For more information, visit vladi-private-islands.de. + +Price available only upon application.","0" +"Tiger Woods' luxe Viking island in Sweden is for sale","A luxe Viking island owned by the world's sixth-richest athlete, golfer Tiger Woods, is up for sale, the Telegraph of London reports. +Naturally it has room for putting practice, with half a dozen tee boxes and a golf hole. It also has a private ferry, stables and pasture land, its own protected bay, a ""mini-mansion"" of a villa, a hunting lodge and a landing strip. + +Oh -- and it also has a ""hill fort"" dating back to the Stone, Bronze and Iron ages that was more recently (about a thousand years ago) a Viking stronghold. Visitors can take forest trails up to the top for views like those ancient man might have seen. + +Listing agent Sabine Rollinger of Vladi Private Islands confirmed in the Telegraph report: ""This island was owned by Tiger Woods, but after his divorce he doesn't need an island in Sweden anymore."" + +Called Stora Rullingen, it's on Lake Malaren, about an hour from Stockholm. Three international airports are within 60 miles. + +CLICK PHOTO FOR SLIDESHOW. +CLICK PHOTO FOR SLIDESHOW. +Woods married Elin Nordegren, a former model born and raised in Stockholm, in 2004. They had two children -- daughter Sam in June 2007 and son Charlie in February 2009 -- but their marriage unraveled when Charlie was a baby. Nordegren learned during Thanksgiving 2009 that Woods had been cheating on her, and soon after, his very public one-man SUV crash revealed their marital problems to the world. +Subsequent news reports said his dalliances involved perhaps a dozen women. Their divorce was finalized in August 2010. + +Vladi Private Islands declines to disclose the asking price except upon application, but a listing at Private Islands Online prices the property at 6 million euros, or about $7.1 million at today's exchange rates. The Vladi listing pegs the property at about 62 acres; Private Islands Online says its about 82 acres.","0" +"Tee-off in your own putting paradise: Swedish luxury island owned by Tiger Woods up for sale - and it comes with a villa, a hot tub and a lodge","Keen golfers can have their very own putting paradise if they snap up this luxury island previously owned by Tiger Woods. + +The island in Lake Mälaren, Sweden, was one of the homes shared by the 14-time major winner and his ex-wife, Elin Nordegren, before their six-year marriage fell apart in 2010. + +The 62-acre island features a secluded villa, a hunting lodge, its very own landing strip for propeller planes as well as, of course, six tee-off areas for a custom-made golf hole. + +Very private: The 62-acre island previously home to Tiger Woods and his ex-wife Elin Nordegren + +Riches: The island in Lake Mälaren, Sweden, was just one of the homes shared by golfer and his ex-wife + +Secluded: The island's villa, built from wood cut from the island itself, according to the estate agents + +Serene: The residence on the island is apparently the only home for many miles around + +Rustic: Yet the wooden construction also includes modern conveniences like a hot tub and gas barbecue + +Kitted out: The kitchen, including breakfast bar, wood-burning stove and a disguised extractor fan + +Welcoming: The bedroom. Tiger Woods and his wife split after his infidelity became public + +Room to live: The kitchen and living room share an open plan space with the wood ceiling rising high above + +It also includes a protected quay, a private ferry boat, a historic hill fort, pasture land for horses, stables and two small Skinnpälsarna islands with a water area of around 500 acres. + +But potential buyers will have to bring their own clubs as the main building comes unfurnished. + +Sabine Rollinger of Vladi Private Islands, who are listing the island, told Mercury Press Agency: 'This island was owned by Tiger Woods but after his divorce he doesn't need an island in Sweden any more. + +'This is a unique, exclusive private island with total privacy. + +'It includes a private harbour, untouched woods, beautiful lush parks, open fields, striking lake views and a tastefully designed main residence, a mini-mansion. + +'Also on the island is a landing strip and six tee-off areas for golf practice. + +'The secluded villa, hunting lodge and stables are located on the main island and surrounded by a very large lawn. + +Log cabin: The hunting lodge offers another space away from the main house for times you want to be alone + +Fore! The island includes six teeing off areas for a single custom golf hole + +Neigh: These are the stables on the island which, along with the private pasture, would be great for horses + +Well lit: As darkness falls, you can see the house is tastefully illuminated by a number of external lights + +Is that an outside swimming pool? If so, it's an ambitious choice for Sweden, with its long, chilly winters... + +A luxury yacht on the island: The protected quay catches the evening sun and it's only an hour's boat ride from the island to the Stockholm archipelago and the sights and sounds of the Swedish capital + +Happy times: Tiger bought the place when married to Swede Elin + +'Here you can land your private prop airplane, play soccer, do some riding or enjoy unstructured golfing. + +'A hundred metres from the villa is the private, protected bay, and a 50-metre long quay that provides plenty of space for your own, and your friends' boats. + +'This is the place to begin great fishing trips in your own private fishing waters, take a boat ride out to Mälaren's over 1000 islands or the beautiful archipelago of Stockholm. + +'This island is also unique due to its central location as the Swedish capital is only about an hour away by boat or car, and from there you have swift access to the Stockholm archipelago. + +'The property even has a historical 11th century Viking stronghold, a dramatic landscape with approximately 30 metres high rocks rising out of the lake. + +'The island boasts a variety of wildlife, such as deer, hares and beavers - even elks can be seen on occasion. + +'The protected location, combined with the quay's generous dimensions, make it an ideal place for private parties and outdoor dining. + +'You go for a swim in Lake Mälaren, where the water reaches temperatures of up to 26C in the summer. + +'Apart from the island, the property also includes the two small Skinnpälsarna islands and a water area of around two million square metres.' + +For more information on the listing, visit vladi-private-islands.de. The price is only available on application. + +Tile floors throughout? Really? A log cabin entirel...","0" +"For sale: Tiger's former island in Sweden","Want to buy a private island previously owned by Tiger Woods? Hey, here’s your chance! + +The Telegraph reported Tuesday that Woods' former 62-acre island in Lake Malaren, Sweden, has been put on the market. + +The listing agent for Vladi Private Islands says the island, about an hour from Stockholm, features one golf hole in addition to a “mini mansion,” secluded villa, hunting lodge, private barber and landing strip for propeller planes. How convenient! + +“This island was owned by Tiger Woods,” the listing agent said, “but after his divorce he doesn’t need an island in Sweden anymore. This is a unique, exclusive private island with total privacy. … + +“The protected location, combined with the quay’s generous dimensions, make it an ideal place for private parties and outdoor dining.” + +Interested? The price is only available upon request, but something tells us private islands don't come cheap.","0" +"Tiger Woods Is Selling His Private Island For $7.1 Million","Tiger Woods divorced Swedish model Elin Nordegren in 2010, but he’s only now decided to unload his private island near Stockholm. The Los Angeles Times reports the luxury property has an asking price of $7.1 million. + +The agency searching for a buyer made no secret of Woods’ motivation to sell. Sabine Rollinger, of Vladi Private Islands, said the property is of little practical use to the golf superstar. + +“This island was owned by Tiger Woods but after his divorce he doesn’t need an island in Sweden any more.” + +Nordegren told People in May of 2014 that she and Woods live a 25-minute drive apart in Southern Florida and share custody of their two children, daughter Sam and son Charlie. The children were, at that time, 6 and 5 respectively. + +“I have moved on and I am in a good place. My relationship with Tiger is centered around our children and we are doing really good — we really are — and I am so happy that is the case. He is a great father.” + +Nordegren gave the interview to People as she finally received her psychology degree after nine years of chipping away at courses. She graduated with a 3.96 GPA and gave the commencement address at her institution, Rollins College. Her speech made a silent reference to her marriage to Woods. + +“Education has been the only consistent part of my life the last nine years. And it has offered me comfort. Education is one thing that no one can take away from you.” + +The island is in Sweden’s Lake Mälaren and boasts a villa, hunting lodge, landing strip, stables, woods, lush parks, and tee-off area. There’s also a unique historical artifact: an 11th-century Viking stronghold. But anyone who buys the property will have to ferry in a couch, since the property is listed as unfurnished. + +The Boston Herald reports that after Elin and Tiger’s divorce, they sold their home in Windermere, Florida, to another golf star, left-hander Bubba Watson. Woods’ extensive Florida compound is in Hobe Sound, Florida, and Nordegren’s Florida home is in North Palm Beach. + +Last year, Tiger Woods’ career earnings surpassed the $1.3 billion mark. ESPN quotes a Golf Digest report in stating that 88 percent of those earnings were for endorsements off the green. In 2013, Woods made $12 million playing golf and $71 million in endorsements. + +After revelations came to light about Woods’ infidelity, his endorsement earnings dropped to an all-time low of $62 million in 2011. He made $100 million in endorsements in each of 2008 and 2009.","0" +"Tiger Woods prices private island at $7.1 million","To the victor go the spoils, and for Tiger Woods, winner of 14 major golf championships and one of the richest athletes on the planet, the spoils include, among other things, a private island in Sweden. + +Woods, who is expected to make his 2015 debut at the Phoenix Open later this month, has put the 62-acre island near Stockholm on the market for about $7.1 million. + + Hot Property: Tiger Woods +CAPTION +Hot Property: Tiger Woods +Vladi Private Islands/www.vladi-private-islands.de +CAPTION +Hot Property: Tiger Woods +Vladi Private Islands/www.vladi-private-islands.de +CAPTION +Hot Property: Tiger Woods +Vladi Private Islands/www.vladi-private-islands.de +CAPTION +Hot Property: Tiger Woods +Vladi Private Islands/www.vladi-private-islands.de +CAPTION +Hot Property: Tiger Woods +Vladi Private Islands/www.vladi-private-islands.de +Situated in Lake Mälaren, the private island features a villa, a hunting lodge, guest quarters, horse stables, a dock and a landing strip for propeller planes, as well as a structure of historical significance: an 11th century Viking stronghold. + +The main villa, fashioned in log cabin style, spans about 2,475 square feet with a chef’s kitchen, a dining area and a living room fireplace. Adjacent from the villa is a spa and a pool built around a rock outcrop. + +Elsewhere on the grounds are six golf tee boxes. + +lRelated PGA golfer Jim Furyk asks $6 million for Maui estate +HOT PROPERTY +PGA golfer Jim Furyk asks $6 million for Maui estate +SEE ALL RELATED +8 + +Two smaller islands and a 494-acre water area for hunting and fishing are included in the sale. What’s not included is the furniture; the property is being marketed as unfurnished, according to Vladi Private Islands, the real estate agency that holds the listing. + +Woods, whose career earnings eclipsed the $1.3-billion mark last year, announced that he would take part in the Waste Management Phoenix Open starting Jan. 29, followed by Torrey Pines in La Jolla in February. He was limited to seven PGA Tour events last year due to injury.","0" +"Tiger Woods' former luxury island goes on sale","A luxury island previously owned by Tiger Woods, the golfer, is up for sale. + +The 62-acre island, in Lake Mälaren, Sweden, was the former home of the 14-time major winner and his ex-wife, Elin Nordegren, to whom he was married for six years. + +It boasts six tee-off areas for a custom-made golf hole, features a secluded villa, a hunting lodge and its very own landing strip for propeller planes. + +The island also includes a protected quay, private ferry boat, historic hill fort, pasture land for horses, stables and two small Skinnpälsarna islands with a water area of around 500 acres. + +However, potential buyers will have to bring their own clubs as the main building does not come with furnishing. + +Sabine Rollinger, of Vladi Private Islands, which is listing the island, said: ""This island was owned by Tiger Woods, but after his divorce he doesn't need an island in Sweden any more. + +""This is a unique, exclusive private island with total privacy. It includes a private harbour, untouched woods, beautiful lush parks, open fields, striking lake views and a tastefully designed main residence, a mini-mansion. + +""Also on the island is a landing strip and six tee-off areas for golf practice. The secluded villa, hunting lodge and stables are located on the main island and surrounded by a very large lawn. + +""Here you can land your private prop airplane, play soccer, do some riding or enjoy unstructured golfing. + +""A hundred metres from the villa is the private, protected bay, and a 50-metre long quay that provides plenty of space for your own, and your friends' boats. + +""This is the place to begin great fishing trips in your own private fishing waters, take a boat ride out to Mälaren's over 1,000 islands or the beautiful archipelago of Stockholm. + +Tiger Woods with ex-wife Elin Nordegren in 2010 (Reuters) + +""This island is also unique due to its central location as the Swedish capital is only about an hour away by boat or car, and from there you have swift access to the Stockholm archipelago. + +""The property even has a historical 11th century Viking stronghold, a dramatic landscape with approximately 30 metres high rocks rising out of the lake. + +""The island boasts a variety of wildlife, such as deer, hares and beavers - even elks can be seen on occasion. + +""The protected location, combined with the quay's generous dimensions, make it an ideal place for private parties and outdoor dining. + +""You go for a swim in Lake Mälaren, where the water reaches temperatures of up to 26C in the summer. + +""Apart from the island, the property also includes the two small Skinnpälsarna islands and a water area of around two million square metres."" + +Vladi Private Islands said the island's price would be released on request.","0" +"Country Music Legend Willie Nelson Dies at Age 81","Legendary country music star Willie Nelson was found dead today in his Maui home. He was 81 years old. Rumors of Nelson's death first circulated early February 24, 2015 on social media outlets but was later confirmed by police. + +A groundskeeper scheduled to perform yard maintenance on Nelson's property reportedly found the singer/songwriter unresponsive on the front lawn and immediately called 911. + +""There was no evidence of drug abuse or alcohol and no signs of foul play,"" said Det. Aldeson. + +""Determining an official cause of death could take as long as 3 weeks,"" said County Coroner Frank Shultz. ""It's just too early to tell what caused his tragic death."" + +The shocking news comes just days after a recent ""60 Minutes"" interview where Nelson was quoted as saying ""Life is good and I have never felt better or been happier."" + +This story is still developing and all information is not yet officially verified.","0" +"Elderly Woman Arrested for Kidnapping Neighbor’s Cats & Making Fur Coats","An 85-year-old woman in Waco, Texas has been been arrested for allegedly kidnapping neighbor’s cats and making them into fur coats. + +Local residents couldn’t figure out where their cats were disappearing, so one or more residents decided to hire a private investigator. Some even thought they saw their own cats as a part of her fur coats. Eventually, the investigator successfully videotaped the woman stealing a neighbor’s cat. + +According to World News Daily Report, the woman admitted in court that she tried to raise her own cats, but became too attached to them. + +Prior to being caught on tape, the woman denied all allegations. + +Prosecutors allege that the retired fashion designer skinned the cats in her basement. The following is a photo of the woman wearing one of her fur coats: + +fur coat made of cats + +Investigators estimate that a total of 30 coats were required to make a single jacket. Additionally, they report that 20 skinned cats were found at the crime scene. + +If found guilty, the unnamed woman could spend up to 18 months in prison.","0" +"‘Little old lady’ Arrested for Making Fur Coats with Neighbor’s Cats","The recent disappearance of domestic animals in the neighborhood started to arise suspicion from local residents when some people started to notice the old lady’s particular fur coats, some even recognizing their cats in the coat’s furs, a fact the lady vehemently denied before being caught on videotape by a private detective hired by local residents to follow the suspicious lady. + +It is believed the old lady started at first to raise her own cats but finally decided to capture neighboring cats because she “got too much attached to the little critters”, she admitted in court. + +It is estimated she used over 30 cats to make one single fur coat and over 20 fur coats were found in her house during the arrest + +The retired fashion designer lured neighborhood cats with food and skinned them in her basement where she dried the skins. She also used the meat of the cats to lure other cats who unwittingly were eating their own species, a disgusting and cruel hobby admits local PETA spokeswoman Jane Churchill. + +Legal experts assess the 85-year old woman could spend up to 18 months in jail for her crimes.","0" +"We just found out the #Ferguson Protester who claim she was shot in the eye with a rubber bullet was a false story guys. Smh..","We just found out the #Ferguson Protester who claim she was shot in the eye with a rubber bullet was a false story guys. Smh..","0" diff --git a/5.2 NLP/datasets/realnews_silverman.csv b/5.2 NLP/datasets/realnews_silverman.csv new file mode 100644 index 0000000..e8bee85 --- /dev/null +++ b/5.2 NLP/datasets/realnews_silverman.csv @@ -0,0 +1,12283 @@ +"headline","main_content","label" +"Apple’s next major Mac revealed: the radically new 12-inch MacBook Air","Apple is preparing an all-new MacBook Air for 2015 with a radically new design that jettisons standards such as full-sized USB ports, MagSafe connectors, and SD card slots in favor of a markedly thinner and lighter body with a higher-resolution display. Sources within Apple, who have used internal prototype versions of the upcoming computer, have provided in-depth details about the machine, and our exclusive artist renditions of the revamped MacBook Air provide the first close look at Apple’s first major step in mobile Mac computing since the Retina MacBook Pro launch in 2012. + +The 12-inch MacBook Air will be considerably smaller than the current 13-inch version, yet also slightly narrower than the 11-inch model. The new 12-inch version is approximately a quarter-of-an-inch narrower than the 11-inch version, yet it is also a quarter-of-an-inch taller in order to accommodate the slightly larger display. In order to fit the larger screen into a footprint about the size of the current 11-inch model, the bezels on the display have been reduced on all sides. + +KeyboardSilver copy + +Besides a new look for the front of the computer, the entire unibody has been revamped from the keyboard to the trackpad to the speakers. Taking cues from the 12-inch PowerBook introduced by Steve Jobs over a decade ago, the new keyboard sits edge-to-edge across the width of the laptop. In addition to going edge-to-edge, the entire key set has been subtly redesigned so that each key sits noticeably closer together. Apple has squeezed the keys closer in order for the computer to be as narrow as possible, which can be seen in the rendition below: + +KeyboardSpacing copy + +Apple has also relocated some of the function keys across the top and simplified the arrow key array in order to keep the keyboard as narrow as possible without taking away from overall usability. In addition to the keyboard, the trackpad has been changed. The trackpad is approximately the same width as that on the 11-inch MacBook Air (if not ever-so-slightly wider), but it is apparently slightly taller, nearly touching the bottoms of the keyboard and the frame. In line with earlier rumors, it also appears that the new trackpad does not have the same clicking effect as found on current and earlier MacBook models. + +ProfileCompare copy + +The elimination of physical feedback in the click is part of Apple’s plan to reduce the thickness of the MacBook to a bare minimum. As can be seen in 9to5Mac artist Michael Steeber‘s rendition above, the new 12-inch Air (on the left) is far thinner than the current 11-inch model (on the right). Taking cues from the current Air, the future model has a teardrop-like, tapered design that gets thinner from top to bottom. Above the keyboard are four redesigned speaker grills that actually double as ventilation holes for the fan-less device to keep cool. + +The upcoming laptop is so thin that Apple employees are said to refer to the device as the “MacBook Stealth” internally. In order to reach that new level of portability, Apple not only slimmed down the trackpad and tweaked the speakers but the ports as well: + +ProfileL-R copy + +The upcoming 12-inch Air has the fewest amount of ports ever on an Apple computer, as can be seen in the rendition above. On the right side is a standard headphone jack and dual-microphones for input and noise-canceling. On the left side is solely the new USB Type-C port. Yes, Apple is currently planning to ditch standard USB ports, the SD Card slot, and even its Thunderbolt and MagSafe charging standards on this new notebook. We must note that Apple tests several designs of upcoming products, so Apple may choose to ultimately release a new Air that does include the legacy components, though there is very little space on the edges for them. + +As we’ve reported on multiple occasions, the new USB Type-C connector is smaller, faster, and more capable than the standard USB 2.0 and 3.0 ports on existing computers. The connector is able to replace the Thunderbolt Display port on the current Apple laptops as USB Type-C actually has the technology to drive displays. Additionally, the latest specifications from the USB foundation indicate that USB Type-C can actually be used to power computers, which makes the standard MagSafe plugs unnecessary on this new device. The connector is also reversible like Lightning on iPads and iPhones, which should make the overall experience a bit more intuitive. + +KeyboardGray copy + +As the new MacBook may only have a single port, it would make sense for Apple to create a hub of some sort for users to be able to plug in multiple devices into the new laptop. Apple already ships all sorts of adapters for its Macs and iOS Devices, so adding yet another attachment to the accessory portfolio would not be unprecedented. With Apple moving to a new “Space Gray” color on its iOS devices and on some Macs (such as with the 2013 Mac Pro), it seems possible that this new MacBook may come in a new gray color, as shown off in some of our renditions. + +The latest rumors indicate that the new MacBook Air will ship in mid-2015 (perhaps around WWDC), while other reports have claimed that the new Air is already nearing production. With Intel revealing the latest news on the Broadwell chipset family at CES this week, the ball is likely now in Apple’s court for pushing the future of mobile computing into the world.","1" +"Report: A Radically Redesigned 12-Inch MacBook Air Is Coming","Everyone's been waiting years and years for a meaningful update to the MacBook line. According to a report from 9to5 Mac, this will be the year that a new design will arrive. The blog just published a few renderings based on details from unnamed Apple employees. And if they're correct, this new MacBook looks awesome. + +The report comes from 9to5Mac's Mark Gurman, who tends to be a reliable source on all things Apple. The details also match up with many of the rumors about MacBook upgrades in recent years. Chief among them is how Apple will ditch ports almost altogether to achieve a slimmer, sleeker profile. Sources say that prototypes for a new 12-inch MacBook Air are a quarter inch narrower than the current 11-inch model. They also have fewer ports than any other Apple computer: a headphone jack and a single USB Type-C port. + +Another less dramatic detail is the slimmer keyboard. Apple's designers are channeling the old 12-inch PowerBook by pushing the keys all the way to the edge. They're also evidently narrowing the amount of space in between the keys to squeeze them together a little bit more. Meanwhile, the trackpad will no longer click in order to make the body thinner. It almost sounds like some sort of feature liquidation, all designed to make this machine as sleek as possible. + +It looks pretty amazing, though! If that is what Apple actually does, of course. Click over the 9to5Mac for more on the new laptop design. [9to5Mac] + +Images via 9to5Mac","1" +"Apple may launch 12-inch MacBook Air with Retina Display","Apple would never lower itself to rubbing elbows with the unwashed masses at CES, but it does like to throw out a few announcements during the show to get under everyone’s skin. Cupertino has been quiet thus far, but rumors are swirling about a 12-inch MacBook Air refresh, and this isn’t just a spec bump. Apple is reportedly redesigning the iconic laptop to be even thinner with a higher resolution screen. +Sources inside the company who have used the prototype notebook (code named MacBook Stealth) say it will eschew many of the conventional laptop features in the name of advancing design. The current MacBook Air’s taper toward the front edge, which gives them a very slim profile, but there’s still space near the back for the power connector and full-sized USBs. The new Air, however, won’t be thick enough for a USB port. Instead, Apple will start using the new type-c reversible connectors. There also won’t be an SD card slot or a MagSafe power connector–even Apple’s beloved Thunderbolt is taking a hike. USB will do it all. +MBA +The 12-inch laptop would be substantially smaller and lighter than the 13-inch model, and even slightly smaller than the 11-inch version. This is thanks to slimmer bezels and a slightly more compact keyboard with less separate between keys. 9to5Mac doesn’t have details on exactly how high the resolution will be, but the current Airs are sitting at 1366 x 768 (11-inch) and 1440 x 900 (13-inch). Stepping it up to a Retina Display resolution of 2560 x 1600 (like the 13-inch Pro) would be amazing in the Air’s form factor. +profilel-r-copy +To be clear, all the images of this supposed notebook are renders created by 9to5Mac. This is still thoroughly in the rumor category, but it’s a redesign we’ve been expecting for a long time. The updated MacBook Air could be announced in mid-2015. +Now read: Which is better: Microsoft Surface Pro 3 or Apple MacBook Air?","1" +"Apple's 12-Inch Retina MacBook Air Shown in Artist's Renditions","In a set of artist renditions, 9to5Mac offers a look at Apple's long-rumored 12-inch Retina MacBook Air. The renditions and details shared in the report are consistent with previous reports on the machine, although plans do sometimes change during the development process. + +As previously described in rumors, the next MacBook Air will have roughly the same footprint as the current 11-inch model, but include a 12-inch display nestled inside narrower bezels. The machine's keyboard will also extend from edge to edge while the speakers move to a set of grilles above the keyboard. + +Comparison of 12-inch Retina MacBook Air (left) with current 11-inch MacBook Air (right) +As part of Apple's effort to reduce the thickness of the MacBook Air, the new 12-inch model will do away with nearly all of the ports currently found on the machine, including the usual USB and MagSafe ports. Instead, the machine's sides will include only a headphone jack, a pair of microphones, and a USB Type-C port that appears set to handle both connectivity and charging. + +Apple's new Retina MacBook Air is expected to run on new Broadwell Core M to allow for the thin, fanless design and perhaps come in multiple color options similar to the company's iPhone and iPad lineups. The machine has been rumored to be entering production as soon as this month, although it is unclear whether Apple may wait until its Worldwide Developers Conference in June to launch the device or introduce it earlier in the year. + +Related roundup: Retina MacBook Air","1" +"Apple’s next MacBook could be a 12-inch MacBook Air","If 9to5Mac’s latest findings are true, than Apple’s biggest product of the year could be the MacBook Air. (You know, right behind the Apple Watch.) According to early reports, Apple has completely redesigned the MacBook Air, ditching the full-sized USB port, MagSafe connector, and SD card slots for something entirely different. + +9to5Mac’s Mark Gurman writes: “The 12-inch MacBook Air will be considerably smaller than the current 13-inch version, yet also slightly narrower than the 11-inch model. The new 12-inch version is approximately a quarter-of-an-inch narrower than the 11-inch version, yet it is also a quarter-of-an-inch taller in order to accommodate the slightly larger display. In order to fit the larger screen into a footprint about the size of the current 11-inch model, the bezels on the display have been reduced on all sides.” + +profilecompare copy +9to5Mac's artist Michael Steeber designed renditions of what the new Air could look like. Here's a side view of the rumored 12-inch Air (left) compared to the current 11-inch Air (right). + +Why this matters: We already have an 11-inch MacBook Air... and a 13-inch, too. So, doesn’t a 12-inch just seem unnecessary? To keep up the MacBook Air’s reputation of being ultra-light and ultra-portable, it makes sense to keep the Air’s screen size at 13-inches or less. However, something smaller than 11-inches will just be too small. So, the 12-inch could actually fill that “just right” sweet spot nicely. + +It’s not all about the size +However, if 9to5Mac’s design estimates are correct, this is the start of a new design shift for the MacBook Air. We’ll see features that are slimmer and more compact than before, with an edge-to-edge keyboard, a modified trackpad, and a thinner profile (yes, the Air will actually be getting smaller). + +Apple could also introduce USB Type-C on the new Air, which means it would no longer need a MagSafe port, as reports on USB Type-C indicate that it can be used to power computers. 9to5Mac believes this single port could be used as a sort of hub, allowing users to plug in multiple devices to the Air. + +Of course, this is just speculation at this point—Apple has yet to announce a new MacBook Air officially—but 9to5Mac’s artist renditions are pretty cool. Check out their full report for more details.","1" +"12in Retina MacBook Air release date rumours: All-new 12in MacBook Air design for 2015, launching at WWDC?","Our Retina MacBook Air rumour article brings together everything we know or can plausibly predict about Apple's next MacBook Air laptop: a laptop that we're pretty sure will come with a Retina display. We're also interested in rumours that Apple will be launching its next MacBook Air in a new size: one based on a 12in screen. + +We report on (and analyse for credibility) all the rumours about every aspect of the new MacBook Air with Retina display: its release date, so you'll know exactly when the new Retina MacBook Air will launch; the Retina MacBook Air's specs, features and design; its UK pricing and availability; and all the rest of the clues and hints circulating on the web that could help us work out what to expect, and when to expect it. Finally, we will show you any Retina MacBook Air images that surface online, together with concept and mockup illustrations produced by clever artists with an eye for prediction. + +We'll update this article whenever we hear of new information, clues and rumours about the next MacBook Air, so bookmark this page and check back here regularly for the latest information about the new MacBook Air with Retina display. + +UPDATED: The plot thickens! Apple website 9to5Mac has commissioned an artist to produce detailed images of the next MacBook Air, based (the site says) on information from sources who have used prototypes. More info in the MacBook Air redesign section. + +Read our MacBook Air reviews \ Which Mac laptop? MacBook Air vs MacBook Pro comparative review \ Best Mac 2014 + +Plus, find out what's in store for next year: Apple rumours and predictions for 2015 + +Retina MacBook Air release date rumours: When is the new MacBook Air coming out? +The latest 'word on the street' (not our words) sounds to us like a bit of a long shot, but here goes. It's been suggested by a number of websites that Apple will launch its next range of MacBooks during the Christmas holidays. + +Aside from the obvious problem (which is that this would be an unbelievable nightmare for us poor souls in the media), this seems to be a case of a reasonable article by Boy Genius Report, written back in August, being rehashed and misinterpreted this month. + +For a start, BGR wrote that the next MacBook Air would be ready in time for the Christmas holidays, not launched during them (releasing during the holidays would be a truly bizarre move, denying the products access to the lucrative pre-Christmas shopping period). That nuance seems to have been lost in translation. And beyond this, the article was as we said written in August, at which point a pre-Christmas launch still seemed possible. Now we're pretty much certain that the Retina MacBook Air will have to wait until 2015. + +UPDATE, 7 Jan 2015: Sure enough, no MacBook Air appeared over Christmas. The very idea! The latest rumour suggests instead that a radically slimmed-down 12in MacBook Air will launch in mid-2015, perhaps making an appearance at WWDC 2015. See more details and images in the Design section, below. + +We've been awaiting the launch of a new MacBook Air for some time. Back in summer 2014 Apple made a few tweaks to the MacBook Air line up, but this was mainly to reduce prices; the processor bump was very slight. Read our reviews of the current MacBook Air range here: 11in 2014 MacBook Air review and MacBook Air 2014, 13in, review. + +What people are really waiting for is a new MacBook Air with Intel's (delayed) Broadwell processor, and a Retina display. + +The new MacBook Air line up is said to include a completely new 12-inch model which may replace the 11-inch version, giving customers the option of a slighly bigger screen, or it may replace the 13-inch model, where customers could instead opt for the comparitively priced 13-inch MacBook Pro with Retina display. + +So when will this new MacBook Air arrive? Reports in mid June suggested that Apple would begin production of this 12-inch MacBook Air in the third quarter. According to a DigiTimes report, Quanta Computer was set to begin production of the new 12-inch MacBook Air in July. This may have started, if the new Intel chips arrived in time... + +They may have: Intel has issued a press release regarding the arrival of its new Core M chip that some believe could be used in the new MacBook Air. A number of manufacturers are already said to be using this new chip in their laptops and tablets, and some of these models will be available in October. According to Intel, Acer, Asus, Dell, HP, Lenovo and Toshiba are all using the Core M. + +If this new Intel chip is used by Apple, reports suggest that the new Retina MacBook Air will be available in time for Christmas. + +In an August report on Digitimes, the Taiwan-based site claimed that its sources in the Taiwanese supply chain said that the production of components for the new MacBook had begun and that it may launch before the end of this year, or next year. + +However, there are also reports that suggest the new Retina MacBook Air could be delayed until next year - it may not be using these Core M chips, relying instead on a different series of Intel Core i5 Broadwell processors (more on that below). + +One report even suggests a mid-2015 launch date, claiming that the date has already been pushed back on multiple occasions. + +Read our New Retina iMac release date rumours + +New Retina MacBook Air rumours : Redesign, new colours, thinner design +On 6 January 2015, 9to5Mac posted a series of images that it says show the next MacBook Air's radical new design. + +New 12in MacBook Air design mockups by 9to5mac +Advertisement + +Bear in mind that these are artist's renders rather than photos of the real thing (although we're sure you'll agree that they're extremely well done - the artist is Michael Steeber). 9to5mac commissioned the images based on information it acquired from sources within Apple ""who have used internal prototype versions of the upcoming computer"". + +It isn't entirely clear how much of the design comes from the sources and how much from the artist's imagination, although many of the most major changes (to the keyboard layout, for instance) are obviously in the former category. + +Sure enough, the new design is for a laptop with a new screen size: 12 inches. Yet the slimming process in these designs is so extreme that the new 12in MacBook Air actually has a smaller body than the existing 11in MacBook Air. The screen is a little bigger, but everything around the screen has been shrunk. + +Here (according to the renders, at any rate) is how the new 12in MacBook Air (left) will compare to the current 11in MacBook Air (right): + +New 12in MacBook Air design mockups by 9to5mac + +This also partly illustrates the biggest bombshell in these leaks: the new design finds space for only one port on each side of the laptop. It has a USB port on the righthand edge (the new, smaller and reversible, Type-C USB) and a headphone socket, along with a couple of microphone holes, on the left. If this is right, the MacBook will have to be powered via the USB port - and sure enough, USB Type-C will be perfectly adequate for that purpose. It just means that you won't be able to use a USB hard drive, wired mouse (or wireless mouse dongle) or other USB accessory while the MacBook is plugged in. + +Macworld contributor Kirk McElhearn is one of the sceptics who have pointed out the numerous inconveniences this would impose, and it's possible - likely, we would say - that the eventual layout will be less extreme. We think the MagSafe power connection is likely to survive. + +As we mentioned briefly, the keyboard is also designed differently. The power button now sits next to the Esc key at the top-left corner of the keyboard, and the keys have in general been shrunk down and squeezed together. The trackpad, on the other hand, has been expanded and now comes closer to the keys. + +New 12in MacBook Air design mockups by 9to5mac +Advertisement + +Of course, 9to5mac's images aren't the first apparent leak about the next MacBook Air's design. + +Jack Marsh, a 16-year-old blogger who appears to have a source with plausible information about the new MacBook Air, seems to have become the the go-to blogger for all MacBook Air rumours. There have certainly been other young bloggers who have gained insight into unannounced Apple products, but as yet we can't be sure the claims are legitimate. + +Marsh has a rumour about the MacBook Air to add to an earlier rumour that suggested the new model would come in gold, silver and space grey finishes (more on that below). Now he claims his source has told him that the new design is so thin Apple has had to switch to a new reversible USB Type C connector which is significantly smaller than USB 3 (it's 8.4x2.6mm). + +Apparently the MagSafe port is also getting a redesign for the same reason: the laptop chassis is too thin to accomodate the current MagSafe charger. Indeed the MacBook Air may charge in an entirely new way, although Marsh's source wasn't clear on whether this had been finalised yet. + +The MacBook Air is also said to feature thin bezels with a keyboard that stretches to the edge of the laptop. Marsh also claims his source told him: ""The display bezels are noticeably thinner - quite similar to the current MacBook Pro Retina lineup."" + +Marsh's earlier report claimed that the new MacBook Air will come in iPhone-like space grey and gold finishes, as well as the usual aluminium. + +MacRumors lent some credibility to this inisial report, claiming that they are aware that ""Apple has at least considered launching the 12in notebook with several different 'special edition' colour options"". And it wouldn't be the first time Apple has introduced a range of colour choices on their Mac laptops. + + +Advertisement + +New Retina MacBook Air rumours: 12-inch screen +Many of the new MacBook Air rumours suggest this model will feature a 12in screen. + +Some sources point to evidence that Apple is working with 12in screens, but there have been claims that Quanta Computer will be building a rumoured 12-inch iPad later this year and it could be the iPad Pro that is being referred to here. + +According to a DigiTimes report in June, sources claim Apple wishes to introduce a smaller MacBook Air to make clearer the distinction between the 11-inch MacBook Air and the iPad Air with its 9.7-inch screen. + +Canalys analyst Daniel Matte also believes Apple is working on a new version of the MacBook Air - one with a 11.88in screen. Other rumours place the screen size at 12in (which probably matches Matte's expectations). + +In his blog Matte seems to be suggesting that there may only be one MacBook Air - this new 12-inch model, with the 13-inch model being phased out in favour of the 13-inch MacBook Pro with Retina display. + +KGI Securities analyst Ming-Chi Kuo suggested back in October 2013 that Apple will launch a 12-inch MacBook Air in 2014. Kuo suggested that this new MacBook Air would have an entirely new design. + +The smaller 12in model could still accommodate a reasonably sized screen and keyboard if it had a smaller bezel. + +New Retina MacBook Air rumours: Fanless design +The new MacBook Air is also said to be even thinner than the existing MacBook Air. This is based on the theory that it will use Intel's new Intel Core M processor, a chip that doesn't need fans. By using this processor it is claimed that Apple could make the laptop 9mm thin. The MacBook Air is currently 0.3-1.7cm thick so it could be almost 1cm thinner at its thickest point. + +Apparently the fan assembly is the reason why the MacBook Air is thicker at one end than the other. Removing the fan assembly would enable Apple to make the laptop thinner than ever, according to reports. + +Presumably there will be some sort of cooling system built in, but that may not be necessary. The new Intel processors are said to be efficient enough to make the removal of the fan feasible - indeed there are already laptops on the market that do not feature a fan. + +Even the Core M may still require cooling in a 12in laptop, though. The new Broadwell processor should enable a fanless design for the smaller (up to 11.6in) laptop or mobile device, notes Motley Fool, based on what Intel said at its developer forum in 2013. + +It has been suggested that the MacBook Air could also offer thermal scaling and thermal management. + +Another advantage of a fanless design would be quiet operation. There would also be no moving parts (making it less likely to break), and it could also offer higher battery capacity because the remaining space could be used to house a bigger battery. + +(We can't help but worry that history could repeat itself if the MacBook Air is fan free - Steve Jobs famously refused to include a fan in the Apple III, leading to hardware failure.) + +New Retina MacBook Air rumours: USB Type C +If Marsh's source (above) is correct the new MacBook Air may offer USB Type C support, which is smaller than USB 3 (it's 8.4x2.6mm). USB Type C is able to support 10Gbps data transfers, which is twice as fast as USB 3, but still slower than Thunderbolt 2 (although the same as the older Thunderbolt 1). + +It will also support for up to 100 watts of power, which is apparently enough to power 4K displays, as Apple's Thunderbolt cable does currently. The only problem is that USB Type C isn't backwards-compatible. + +New Retina MacBook Air rumours: Inductive charging +Marsh's source also claims that the MagSafe port may get a redesign and that the MacBook Air may charge in an entirely new way. Perhaps the new MacBook Air will use inductive charging like the Apple Watch does. + + +Advertisement + +New Retina MacBook Air rumours: Trackpad changes +According to a report on Chinese site Weiphone earlier this year, the new MacBook Air will be thinner and lighter, a feat it will achieve by removing the fan and the clicking mechanism in the trackpad. + +The new 12in model will drop the trackpad and introduce ""force and optical sensors"" and new touch gestures, according to this report from BEN Latest News. + +New Retina MacBook Air rumours: Retina display +Will the next MacBook Air feature a Retina display? That's one of the strongest and most persistent rumours, and it's certainly possible. + +Apple may opt to keep prices down (and battery life up) by keeping the screen non-Retina; but we don't think so. According to our own reviews of the MacBook Air, the MacBook Air is currently let down by its display, which has a lower resolution than the competition. + +Canalys analyst Daniel Matte has written a blog claiming that Apple will add a Retina display to the MacBook Air this year. He expects that we will see a 11.88-inch model with a resolution of 2,732x1,536 pixels, the same 264ppi that the iPad Air offers. + +He explains the significance of Apple using the same display technology for the MacBook Air and iPad Air, stating: ""It turns out that an ~11.88"" Retina MacBook Air with a 2732 x 1536 resolution happens to have the exact same pixel density as the 9.7"" 2048 x 1536 Retina iPads: ~264 PPI. It would make sense for Apple to take advantage of the same display technology it has been utilizing for the 9.7"" iPads by cutting their panels to this larger size."" + +Rumours also claim that the new MacBook Air Retina display could have a resolution of 2,304 x 1,440 for a rumoured 12in display (discussed below). That's 226 pixels per inch, compared to 227 pixels per inch for the 13in MacBook Pro (which offers 2,560-by-1,600 resolution). This adds up to a 16:10 aspect ratio like that found on the 13in MacBook Air and MacBook Pro models, rather than the 16:9 aspect ratio currently offered by the 11in MacBook Air. + +The current 11.6-inch MacBook Air offers a 1366 x 768 pixel display. + +The rumours of a MacBook Air with Retina display have been long running. Back in February 2013, rumours suggested that Apple was planning to launch a revamped MacBook Air with a Retina display in the third-quarter of 2013. A separate report in March 2013 also claimed that Apple would introduce a Retina display to the MacBook Air in 2013. Since this didn't happen in 2013, it is perhaps likely for 2014. + +Apple does appear to be moving the whole of its range to Retina display. The company updated the Retina versions of its MacBook Pro in 2013, and also introduced a Retina iPad mini in October 2013. + +Wondering what the Retina display fuss is all about? Read: What's a Retina display, and what's a Retina HD display? + +Apple may use the IGZO display technology for the new display, offering improved power efficiency. The reason for the supposition is that Apple was recruiting for a engineers with experience in LED backlighting and LCD displays, in February, according to CultofMac. In an LCD display the bunches of pixels with wires running behind to connect them. The backlight has to shine though this mesh of wires to light up the pixels. In an IGZO display more light is able to shine though this mesh of wires, so the power requirements are lower, and battery life can be preserved. As a result we could see even longer battery life than the 12 hours currently on offer from the 13in MacBook Air. + + +Advertisement + +Rumours about a Retina MacBook Air with a smaller display have been circulating for some time. KGI Securities analyst Ming-Chi Kuo suggested back in October 2013 that Apple will launch a 12-inch MacBook Air in 2014. Kuo suggested that this new MacBook Air would have an entirely new design. + +Then back in January 2014, Evercore Partners analyst Patrick Wang predicted that a 12in MacBook/iPad hybrid would launch in the autumn of 2014. It is possible that the rumoured Retina display MacBook Air could be this Mac. + +Canalys analyst Daniel Matte also believes Apple will add a Retina display to the MacBook Air this year. + +New Retina MacBook Air rumours: Processor +Intel has announced the new Intel Core M chip. Some expect that this processor may be used by Apple inside the new MacBook Air. As mentioned above, because this chip doesn't need fans, the new MacBook Air could be less than a centimeter thick at its thickest point. Since it uses the 14nm processor, the processor itself it is tiny. + +The Core M processor should also enable the new MacBook to be more power-efficient with better battery life. Intel claims it's the most energy-efficient chip yet. + +The Core M also offers excellent graphics processing power, according to Intel. Intel says it will offer seven times the graphics power of four-year-old machines, and double the graphical and three times the web performance of the current range of high-end tablets. + +However, Intel has not confirmed that Apple will use the new processor. (In the press release regarding the new chip, Intel mentions Acer, Asus, Dell, HP, Lenovo and Toshiba as potentially using the Core M. Some of these models will be available in October, according to Intel.) + +The Core M is designed for small laptops, large tablets and 2-in-1 devices, and Intel is positioning the chips as being for use in laptops of 13.3in, tablets above 10in and dual devices. Apple would traditionally use the Core i5 chips in its MacBook, so it is possible that these processors will never appear in a MacBook Air which may instead use the new U Broadwell processor, which may not ship until 2015. + +Redmond Pie reports that performance with the Core M hasn't been particularly impressive; it was featured in the Lenovo Yogo 3 Pro, which didn't exactly set the world alight: benchmark speed tests and overall reviews rated the device quite poorly. It's therefore been suggested that Apple may give the Core M a miss and go instead for an i5 or i7 chip. + +(On the other hand, some analysts have argued that Lenovo's implementation of the Core M, rather than the innate qualities of the Core M itself, was to blame for the sub-standard performance, and that Apple's engineers would be able to coax solid performance from a Core M-equipped MacBook Air. We shall see.) + +Whichever Broadwell processor Apple does use, it should make the Retina display MacBook Air possible. Broadwell is said to consume 30 percent less power than its predecessor Haswell, and that should be good news for battery life on the portable Macs, especially those with power hungry screens. + +Other features of the Broadwell chip are that it is low power and offers integration with WiDi, 4G WWAN and WiGig networks. + + +Advertisement + +New Retina MacBook Air rumours: May not use Intel chips +This rumour has been floating around for some time. It is possible that Apple will ditch the Intel processor in its range of laptop in favour of its own home-made A-series chips, like those found in the iPad and iPhone. + +Some have even speculated that the new MacBook Air could mark some sort of crossover between the iPad and the MacBook, perhaps an iPad Pro. + +However, rumours that Apple will move from Intel to ARM chips seem unlikely, based on this explaination from Cult of Mac. + +New Retina MacBook Air rumours: UK price +With the price of the MacBook Air and MacBook Pro with Retina display being so close we had expected that Apple would reduce the price of the entry-level MacBook even further. It's currently £749 for the 11in model, which is £100 less than in 2013. This compares to the MacBook Pro Retina starting price of £999. However, the fact that the top-of the range iPhone 6 Plus costs more than the entry level MacBook Air (£789) makes us think that the MacBook Air price is more likely to increase. + +It may be that the 13-inch MacBook Air is discontinued, as that model is similar in price to the 13-inch MacBook Pro with Retina, but not equal in specs. This would leave the cheaper 12-inch MacBook Air models with, potentially, an entry-level price of £800. + +When it first launched in October 2012, the 13-inch MacBook Pro with Retina display started at £1,449. This was reduced to £1,249 a few months later when the range received a processor upgrade. Now, with the April 2014 update to the MacBook Air, the entry-level price of the 13-inch model is a much more compelling £999 which makes the difference between the 13-inch MacBook Pro with Retina display and the 13-inch MacBook Air £250 rather than £150. + +In his predictions last year, KGI Securities analyst Ming-Chi Kuo suggested that the price of this new 12-inch MacBook Air model could be lower than the current line up of Mac laptops. + +Read: Which 13-inch MacBook should I buy? + +Didn't Apple already introduce the 2014 MacBook Air? +Apple unveiled the latest update to the MacBook Air on 29 April 2014. Quietly updating its MacBook Air line-up with improved Haswell processors from Intel. You can read our review of the 2014 11in MacBook Air and the review of the 13in MacBook Air here. + +Aside from the small processor boost and a tiny battery life tweak, the main change for the new MacBook Air models was the price. Each model is now under £1,000, with prices starting at £749, £100 less than the previous models. This helps keep the MacBook Air an attractive option for customers, as the previous price was not much different to the price of the new MacBook Pro with Retina display. + +The range update came as some surprise as the Retina display for the MacBook Air rumour was already in circulation. Prior to the MacBook Air update in April, there were suggestions that the new MacBook Air with Retina display could launch at WWDC, but this was obviously not the case. + +Read our 5 reasons to buy a MacBook Air and 5 reasons NOT to buy a MacBook Air. + +Apple has updated its MacBook Air and Retina MacBook Pros for 2014, read more here: + +2014 13-inch Retina MacBook Pro review +2014 15-inch Retina MacBook Pro review +11in 2014 MacBook Air review +MacBook Air review (13in, 2013) +Why is the Retina MacBook Air delayed? +If there is a delay, the key reason may be the availability of Intel processors, rather than the production of the new design. + +Intel's newest generation of chips - the successor to the Haswell chips currently in the MacBook Air - called Broadwell has been plagued by delays. However, in a conference call about Intel's second-quarter results on 15 July, Intel's chief executive Brian Krzanich confirmed Intel’s hardware partners will have Broadwell systems on store shelves in the run up to Christmas. He said: ""We said we would have products on shelves for the holiday season and we continue to work with our partners and we’re on schedule to have product on shelf in the holiday."" + +As we mention above, some of these new chips are now shipping, however, anyone awaiting the new Retina MacBook Pro, MacBook Air, iMac and Mac mini should note that there are various Broadwell chips being developed by Intel, and the chips that Intel confirmed are shipping now are the M variety, destined for fanless two-in-ones. The new MacBook Air may use the U Broadwell processor, which may not ship until 2015. + +We are sure that Apple is pretty frustrated with Intel. + +Shipment of Skylake – the successor to Broadwell which will offer even more power than that chip - is also delayed. + +New Retina MacBook Air release date: Will the MacBook Air be an iPad Pro? +There are also rumours that Apple could launch a 12in iPad, but this might not arrive until 2015, or the rumours could relate to the 12in MacBook. + +There are also rumours that the new MacBook Air merge with the iPad to create the iPad Pro. You can read more about the iPad Pro rumours here. + +We think that a MacBook Air that offered a dual boot system for iOS 7 and Mac OS X would be very interesting, however, Tim Cook last year ruled out any kind of convergence suggesting that a Toaster Refrigerator wouldn't work. + +Will the old non-Retina MacBook Air remain? +If Apple launches a 12in MacBook Air, will it discontinue the existing models? It's possible that if Apple launches a 12in Retina MacBook Air model it will discontinue both, or either of the existing models. Equally, Apple could maintain one of the existing models as an entry-level model. It seems more likely that it would keep the 11in model on at an even lower price, rather than keep on the bigger 13in model. + +One reason why Apple may keep a lower-priced MacBook Air on is the fact that Apple has just introduced a new entry-level iMac and already the MacBook Air looks superior to that, despite costing less. If Apple wants a low end option, it would appear unlekely that the Retina MacBook Air would be it. + +Read our review of the new £899 iMac and see how it compares to the MacBook Air. + +The new MacBook Air will be solar-powered +Ok, so this is a bit of an out-there rumour, but it really is possible that Apple will one day release a new MacBook Air with a solar powered display. + +In January 2013, Apple was granted a patent that described a method for harnessing sunlight to illuminate a MacBook's display. This patent is actually the seventh solar-related patent Apple has gained in the past two years. + +New Retina MacBook Air leaked images +At present, there are no new MacBook Air leaked images to share with you, but we will update this story as soon as one surfaces on the web. + +We have seen a few concept images, however... + +Perhaps inspired by the Mac Pro, or the Space Grey iPhone 5s, there are calls for a black version of the MacBook Air. TUAW has provided some renders of how such a MacBook Air could look. + + +Advertisement + +Here is our mockup of how a gold MacBook Air could look with an iOS-style operating system. + + +Advertisement + +Read the latest MacBook Air News, Reviews and Features here + +Wondering whether to buy a MacBook or a Mac desktop? Find out if you should buy a Mac laptop or Mac desktop here. Also: read our Best Mac to Buy Mac Buyers Guide where we compare every Mac.","1" +"Report: new 12-inch MacBook Air slims down, has single USB port","According to a new report from 9to5Mac, a new MacBook Air is coming. The new computer is alleged to have a12-inch screen, but remain about the size of the 11-inch model via reduced bezels on all sides. Possibly even cooler than that is the computer is said to be an actual thing, not like the iPad Pro we keep hearing about. Sources inside Apple claim to have been hands-on with the new device, which is also lighter than existing MacBook Airs. + +Aside from sporting a larger screen and lighter design, there are several other interesting nuances, here. The new-look MacBook is sporting a single USB Type-C port, which sounds silly — but isn’t. + +The USB Type-C port can handle things you’ve been relying on other ports to do for years, like external monitors. the new USB standard is also capable of charging, so MagSafes might be dead. + +That also means no multiple USB ports, SD Card slot, Thunderbolt — and you won’t be able to natively charge and use an external monitor. The natural assumption here is that Apple will release some sort of hub alongside the new MacBook Air for those occasions when multitasking is necessary. + +profilel-r-copy + +The trackpad is said to be a touch bigger than the existing MacBook Air models (and get rid of the click), but the keyboard has reportedly been minimized to accommodate the slimmer profile. That means smaller keys, closer together, even though the keyboard is said to go edge-to-edge. + +The report details the device as overall slimmer than the existing MacBook Air 11-inch (which sounds insane), but a touch taller to accommodate the larger 12-inch screen. Speaker grilles toward the top of the keyboard double as vents for the CPU, too. + +What news don’t we get, here? Retina. Sadly, nothing in the report suggest we’ll get a Retina MacBook Air with the refresh. Fans of the dense Apple screens won’t find favor there, but we’ll all still marvel at the thin profile, should this actually come to pass as reported. + +Source: 9to5Mac","1" +"Apple 'working on 12-inch MacBook Air'","Apple is planning to release its slimmest MacBook yet, boasting a single USB port and 12-inch display, according to a new report. + +Rumours site 9to5Mac created artist renditions of the revamped model based on information from sources within the company, which it says in the first major shakeup of the Mac line since the introduction of the Retina MacBook Pro in 2012. + +The 12-inch model would slot neatly into the current range, which is comprised of an 11-inch and 13-inch model. The new version is slimmer than both predecessors, but sports the same 'tapered' design from top to bottom. + +But such a slimline frame comes at a price; as Apple appears to have done away with standard USB ports and SD card slot. A single USB Type-C port remains, and the gaps between keyboard keys narrowed in order to minimise space. + +Four speaker grills positioned between the screen and keyboard double up as ventilation, as the model has no fan. The trackpad is taller than that of the 11-inch model, and the keyboard has been designed to sit edge-to-edge across the width of the laptop, with a notably slimmer margin. + +UK pricing and the release date of the potential new model remain unknown. + +The first MacBook Air was introduced by former chief executive Steve Jobs at the 2008 Macworld Conference and Expo, where he claimed the company had built the world's thinnest notebook. The MacBook Air replacing the white MacBook as the standard entry model after its discontinuation in 2011. + +The news comes as reports circulate that Apple is preparing for the Apple Watch to go on sale by the end of March. + +The 12-inch MacBook Air (L) is much slimmer than its 11-inch counterpart (R) + +The new, thinner keys compared to previous models'","1" +"Is Apple about to launch a totally redesigned, 12-inch MacBook Air?","Every year, Apple does some counterprogramming at CES. This year, whether it meant to or not, it may have some big news: 9to5Mac has some new details that say there's a 12-inch MacBook Air with a completely new design, a higher-resolution display, and few of the trappings we've come to expect from a MacBook Air. + +Here's Mark Gurman at 9to5Mac: + +Apple is preparing an all-new MacBook Air for 2015 with a radically new design that jettisons standards such as full-sized USB ports, MagSafe connectors, and SD card slots in favor of a markedly thinner and lighter body with a higher-resolution display. Sources within Apple, who have used internal prototype versions of the upcoming computer, have provided in-depth details about the machine, and our exclusive artist renditions of the revamped MacBook Air provide the first close look at Apple’s first major step in mobile Mac computing since the Retina MacBook Pro launch in 2012. +According to Gurman's sources, there are a number of other changes as well. The function keys and arrow keys have been redesigned, and the keyboard sits completely edge to edge on the palmrest. It's smaller and narrower, apparently, and the trackpad doesn't have the same clicking feedback. Of course, let's be clear: these are leaks and sources, who are often working with incomplete and occasionally incorrect information. Things also change, a lot, between leaks and release. But also, Mark Gurman has a long history of being right. + +These photos, too, are not real. They are renderings, guesses as to what the Macbook might be. But if these sources are right, confirming rumors we've been hearing for months and years — of a lighter, thinner, higher-res MacBook Air — 2015 could be a big year for Apple's laptops.","1" +"Why the Gold Apple Watch Edition Must Cost $10,000","Get ready for the tech press to flip out when Apple announces the retail price for the gold Apple Watch Edition model. Apple critics have always roasted the company for selling products that are more expensive than they should be, and they frequently use this as a wedge topic to criticize buyers. But the “18-karat gold” Apple Watch Edition will set a whole new bar with a sales price of $10,000. The funny thing in this case is that Apple is perfectly right to be charging that much! + +Do you disagree? Check out my counterpoint, “The Case Against the $10,000 Gold Apple Watch Edition“ + +Gold is Expensive + +Let’s start with a little backgrounder in gold. Everyone has a vague sense that gold is expensive. Even rabid Internet trolls have seen the banner ads and heard about that in the news. But most people don’t understand just how expensive even a little bit of gold is. So this is a good place to begin the discussion. + +Update: My calculations were wrong! Also, this was a bit “back of the envelope.” Now that it has some readership I realize I should go back and fix the calculations in the article to be more realistic… + +Here are the basic facts: + +Gold currently sells for between $1,200 and $1,300 per troy ounce and has been over $1,000 per troy ounce for the last five years. +18-karat gold contains 75% pure gold, and that term is regulated by law. +One ounce of 18k gold occupies about 1.8 cubic centimeters of volume since a typical 18-karat gold alloy weighs about 16.5 grams per cc. +18-karat gold currently sells for $29.11 per gram, $905 per troy ounce, or $480 per cc. +.25 cc of 18k gold is about enough to construct a watch buckle and .75 cc gets you a deployant clasp. It takes a few more to build a watch case, anywhere from 1.5 to 8 cc depending on the size and thickness of the case. So the buckle is worth $120-$360 and the watch case $720 to $3800 just as raw gold. This is why gold watches generally sell for a lot more than $6,000! + +Gold Watches are Expensive + +Let’s apply this to a watch case. Imagine you wanted to create a rectangular case 42 mm high by 36 mm wide by 10 mm deep. If it was solid, this would equal 15.12 cc of volume. But it’s a watch case, so you have to leave room for the movement, dial, case back, etc. So let’s just leave 5 mm of thickness all around, making a hollow rectangle. This equals 6.8 cc (42 x 36 x 10 – 32 x 26 x 10). Therefore, the raw gold to make just the case of this hypothetical watch would cost $3,200 as of this writing. + +A simple 42x36x10 mm rectangle of 5 mm thick 18-karat gold would cost over $8,300 +A simple 42x36x10 mm rectangle of 5 mm thick 18-karat gold would cost more than $3,200 +Now let’s consider the same shape but just 2 mm thick. That’s 2.9 cc of gold, worth $1,400. Pick your thickness and you’re still looking at thousands of dollars worth of gold. + +How does this translate in the real world? Let’s look at the retail price of some watches that are available in both stainless steel and 18-karat gold. + +This Cartier Tank MC is $15,000 more in 18k gold +This Cartier Tank MC is $15,000 more in 18k gold +The Cartier Tank MC measures 44 mm by 34 mm by 9.5 mm thick: $15,000 extra (list) for 18k gold +Cartier Tank MC in stainless steel: $7,000 list, $5,800 street +Cartier Tank MC in 18k pink gold: $22,000 list, $18,200 street +The Jaeger-LeCoultre Reverso Squadra Hometime measures 50.5 mm by 34.9 mm by 14 mm thick: $14,750 extra (list) for 18k gold +Jaeger-LeCoultre Reverso Squadra Hometime in stainless steel: $8,550 list, $6,800 street +Jaeger-LeCoultre Reverso Squadra Hometime in 18k pink gold: $23,300 list, $18,400 street +This list could go on and on, but the gist is simple: 18-karat gold cases cost a lot more than stainless steel. In fact, it’s pretty much impossible to find a gold watch for under $10,000 in any size and from any manufacturer. Even tiny quartz ladies watches like the tiny Chopard Happy Sport Mini sells for $11,000! Most of the bargains commenters have pointed to are either 14-karat or less, very slim and small, or long out of production and with outdated pricing. + +Then there’s the bracelet. Swap a gold bracelet for a leather strap and you are looking at an extra $20,000. Adding a gold bracelet to that Jaeger-LeCoultre bumps the price to $42,900! + +Certainly there is quite a bit of profit in luxury watches, but one simply cannot deny the raw material value in a gold watch case. And the gold market is liquid like stocks and other commodities: There are plenty of buyers and sellers of gold, and plenty of reserves, so no company, no matter how strong, can expect favorable pricing from their suppliers. + +Another reason companies charge so much for gold watches and jewelry is as a hedge against volatility. They can’t price near the commodity price because they have to set a price and stick to it all year long. So they generally price somewhat higher than they would, even taking into consideration all the rest of the materials, labor, distribution, and profit in a watch. + +The Apple Watch Edition Will Cost $10,000 + +There’s a reason I picked those two watches for my comparisons: Both are similar in size and shape to the 42 mm Apple Watch. The Cartier is a little smaller and the Jaeger-LeCoultre is a little larger, but both represent a traditional watchmaker’s gold-cased square-ish offering in the space. And both cost more than $20,000, with much of that price going to the gold case and matching buckle. And Jony Ive recently said that the historic Cartier Tank was one of his inspirations for the Apple Watch design! + +Apple would be crazy to sell the Apple Watch Edition for $20,000, though. That’s not going to happen. So they’re likely to find ways to reduce the cost dramatically. + +First, as we can see, the Apple Watch case is highly rounded in all three dimensions. Although questionable from an esthetic standpoint, this reduces the amount of material required by quite a lot. Second, Apple Watch has a large sapphire crystal front and back with the display, sensors, and such. Third, the interior frame is likely made of steel or aluminum, not gold, to reduce cost and increase commonality with the aluminum and steel versions. + +Could it be gold plated? No. Numerous reports state that it is a solid gold case. Although Apple has not apparently used the word, “solid” in their press releases, they do claim it is “crafted from 18-karat gold” and nowhere does it say it is plated or “gold filled” (the industry term). There are laws covering descriptions of metal content for jewelry and Apple cannot break these any more than Tiffany could. + +Apple says that the Apple Watch will start at $349 for that aluminum Sport model, and many bloggers have reported the price for the steel Apple Watch to be roughly $1,000. It is reasonable to assume that the gold Edition model will sell for substantially more than this, with many suggesting $4,000 or $5,000. But remember that this price would only cover 4 or 5 ounces of gold! Even with thin walls and a steel frame, it’s hard to see how Apple could make a solid 18-karat gold case and buckle for a 42 mm watch with just 3 ounces of gold. + +Gold is soft, but Apple claims that their special gold is twice as hard as “standard gold”. Taking that at face value, perhaps they reduced the thickness of the case commensurately, cutting the amount of gold in half versus a standard rectangular watch. This still leaves a few thousand dollars of material value in the case. The Apple Watch Edition will come in 38 mm and 42 mm sizes, a difference of about 20% in terms of case volume. So the smaller model could sell for 20% less still. + +My prediction is that the 42 mm Apple Watch Edition will retail for $9,999 with the 38 mm Apple Watch Edition retailing for $7,999. This covers the cost of the gold case, the internals, manufacturing, sales, and profit, and yet does not leave Apple subsidizing the world gold market by selling at a discount or cheating with a too-thin or plated case. I will be shocked if the price is $4,999, but I suppose it’s possible with some finagling and if that’s the smaller model. And it will not be any less than that. + +This is a $10,000 product +This is a $10,000 product +Bonus prediction: Given the very high price of the Apple Watch Edition, I predict that availability will be quite limited. Apple will likely create special store-within-a-store spaces in certain Apple Store locations for the Edition. I further expect them to open special standalone Apple Edition Boutiques to sell the Watch Edition, accessories, and perhaps other future high-end products. + +Update! + +Needless to say, many people disagree with me. And now that @Gruber Fireballed this post, I imagine I’ll hear from lots of them real soon! + +The gist of the disagreement lies in the amount of gold needed for the watch case. I assumed it would be quite thick (read sturdy) and would contain upwards of 130 grams of 18k gold. Then there’s the strap lugs and buckle which would likely contain another few dozen grams. But @GAK_PDX (and others, though he was most visually eloquent) suspects it contains much less gold. + + +I think this number is way too low, but it’s a good lower bound if the case was very thin and completely hollow. And it puts the raw gold at about $849 at $29.11 per gram of 18k gold. Although this is admittedly much, much lower than my estimate, it still illustrates my point that the Apple Watch Edition is not going to be cheap. And I think he’s way off but time will tell who is right and who is wrong. + +Another argument is based on this 2006 analysis of a gold Rolex watch. Right off the bat one should point out that gold cost $400/oz when it was written and that watch includes a gold bracelet as well, something Apple is apparently not going to do with the Edition. That Rolex case contained 18.5 grams of gold alloy, but it’s much, much smaller than the Apple watch and it’s circular to boot! A 34mm circle is 107mm in circumference, while the 42mm Apple Watch is 156mm in circumference. Use the magic of math to scale the Rolex up into a 42mm rectangle and we’re at 27.75 grams. But that case is also much thinner since we excluded the bezel, and the Apple Watch is pretty slab-sided. So we can probably double this safely and come out with $1,615 of gold in my mangled square Rolex case. + +So there are lower estimates than mine for the amount and value of the gold. I can accept that. But let’s take a step back and think about the final price. Even if it contained less than $1,500 of gold, how much would it sell for? Certainly not $2,000 or $3,000. You still have to account for the cost of everything else, plus the intangibles of manufacturing and distribution. And profit for Apple (and a hedge against the volatility of the price of gold). So we’re back at the $4,000-$5,000 estimate others have made. As Greg Koenig tweeted, and Forbes reported, “If anyone thinks Apple is charging less than $5k for the Edition, they are smoking crack.” + +Regardless of the total, it’s important to realize that the price of gold is in the driver’s seat when it comes to pricing the Apple Watch Edition. + +I’d love to be wrong, and I look forward to updating this piece. Thanks for reading!","1" +"Why the most expensive Apple Watch will probably cost around $10,000","The most expensive Apple Watch set to go on sale in April will have to cost around $10,000, according to analysis done by the timepiece blog Grail Watch. + +That's mostly because the Apple Watch Edition has a frame made from solid 18-karat gold, which is very expensive. + +Grail Watch notes that gold sells for between $1,200 and $1,300 per ounce these days. By that measure, the Apple Watch Edition's frame would cost around $8,300 for the larger 42mm version, excluding all other costs. + +That's assuming the watch's case is made from solid gold, not gold-plated. But the blog notes that Apple's marketing material never uses ""gold-plated"" or ""gold-filled,"" which is conventional terminology for gold-plated materials, and that Apple must abide by laws governing how jewelry makers describe their products. + +The conventional wisdom so far has been that the Apple Watch Edition will cost $5,000. Apple has only announced the price of the low-end Apple Watch Sport, which will sell for $349. + +But gold-framed luxury watches usually go for well above the $10,000 mark. Cartier's Tank MC lists for $22,000 and Jager-LeCoultre's Reverso Squadra Hometime lists for over $23,000. + +Even if the Apple Watch Edition sells for less than its analog competitors, it will still be Apple's most expensive product. + +Grail Watch predicts the larger Apple Watch Edition will go for $9,999, with the smaller version retailing for $7,999.","1" +"Gold Apple Watch Edition price? Speculators say at least $10,000","The Apple Watch will not be an accessory for your iPhone - but your iPhone will be an accessory for your Apple Watch, claims technology writer John Gruber, who expects the new wearable to cost upwards of $10,000 (£6,500/€8,800). Due to go on sale in April, the Apple Watch will start at $349 for the basic Sport model with a rubber strap, but beyond that no one knows how much the stainless steel and 18-karat gold Edition models will cost. A debate between technology and wristwatch experts is under way to determine how far into uncharted water Apple is willing to sail. First, Stephen Foskett of Grail Watch chimed in, suggesting (although using self-proclaimed ""back of envelope"" maths) the gold Apple Watch Edition will cost at least $10,000, based on the materials used. Foskett points to the huge gap in prices between stainless steel and gold versions of Swiss watches of a similar size and shape to the Apple Watch, noting how the Cartier Tank - a watch praised by Apple design chief Jony Ive - costs $7,000 in steel and $22,000 in pink gold. The Jaeger-LeCoultre Reverso Squadra Hometime, slightly larger than the 42mm Apple Watch, costs $8,550 in steel and $23,000 in gold - and a gold strap is a further $20,000. Apple must also price the Watch so it is protected against the volatility of gold. Foskett said: ""[Watchmakers] can't price near the commodity price because they have to set a price and stick to it all year long. So they generally price somewhat higher than they would, even taking into consideration all the rest of the materials, labour, distribution and profit in a watch."" Will the Apple Watch be gold plated to save costs? Apple Watch will go on sale before the end of April(Apple) Foskett says not. Although Apple doesn't describe the Watch Edition as being ""solid gold,"" it does say it is ""crafted from 18-karat gold,"" and nowhere is the material described as plated or gold filled. Entering the jewellery market means complying with new regulation, Foskett explains. ""There are laws covering descriptions of metal content for jewelry and Apple cannot break these any more than Tiffany could."" Add to this Apple's claims of producing the Watch from gold twice as hard as standard gold, and it is clear that the company will not be scrimping on materials. Foskett believes $9,999 for the 42mm model and $7,999 for the 38mm version of the gold Watch Edition could well be possible. Days later, Apple commentator John Gruber blogged to say he also thinks the price will be $10,000. ""The more I think about it, and the more I learn about the watch industry, the world of luxury goods, and the booming upper class of China, the better I feel about that bet. I don't think I was wrong to place a friendly late night bar bet on a $9,999 starting price [for the gold model]."" Gold straps Gruber says a ""starting price"" because he expects Apple to announce a new gold band when the Watch finally gets a price and release date - and for this he suspects the company will charge an additional $10,000. Looking at how Rolex charges a much higher premium for its gold models over steel - and for watches with identical movements - Gruber says the Apple Watch Edition ""is not a tech product, so don't try to price it like one... Apple's ambitions in this arena, I am convinced, are almost boundless."" Buying the Watch Edition will be unlike buying any other product in Apple's history. Reports claim the company will store the watches in safes, and that it is even considering completely separate boutique stores to sell them. Apple is expected to reveal the Watch's pricing structure and release date at a media event before the end of April 2014. + +RelatedApple Watch features were ditched as executives struggled to define its smartwatch purposeLG targets Apple Watch with premium, all-metal Urbane smartwatchApple installing safes in-store to protect gold Watch EditionApple Watch release date is before the end of April, says CEO Tim CookApple retail boss and ex-Burberry chief Angela Ahrendts paid $73.3m in 2014 beating CEO Tim CookApple Watch battery will last less than three hours of 'active use'Impressed by Apple Watch, Swiss watchmaker Tag Heuer looks to Silicon Valley for smartwatch helpNew Apple Watch features revealed by 'Companion' iPhone app","1" +"Would you pay $10,000 for the Apple Watch?","VENICE BEACH, Calif. --You've probably heard Apple is launching its latest i-device, a new Apple Watch, in April and that it will start at $350. + +But did you know there are three editions of the watch? What no one knows, outside of Apple, is how much the top of the line ""Watch Edition"" will sell for. + +We've seen online reports that it could sell for as much as $4,000. Maybe more. + +So we got to wondering: How much would consumers pay for the top-of-the-line Apple Watch? + +Not much, as we recently found out in chats with consumers here. + +""I'd get the $350 model,"" says Ashlea Fellows of Australia. ""I wouldn't go any higher."" + +Thousands of dollars for a gold watch? Not for Karla Gallegos of Chile. ""Too expensive. I could find a watch made of gold for $2,000,"" she said. + +Juan Frias of New York would drop $1,000. ""I like gold watches,"" he says. ""I'm a teacher, and I wouldn't have to look down at my wrist. My daughter texts me, I can look and nobody can say, `Hey, you're on the phone.'"" + +Apple touts the high-end Apple Watch as sporting a 18-karat gold case, which it says is twice as hard as standard gold. And it's protected by sapphire crystal, advertised as almost impossible to break, unlike the gorilla glass of the iPhone. + +In mid-2014, many analysts expected Apple to use sapphire glass on the iPhone 6, but that didn't happen. Apple wasn't happy with the sapphire being produced by its factory near Phoenix, which has since been shut down. The company hasn't said where its new sapphire is being produced. + +Estimates online for how much Apple will charge for the top-line watch are all over the map. Website Grail-watch.com goes as high as $10,000. ""t's pretty much impossible to find a gold watch for under $10,000 in any size,"" notes the site. + +But even at $4,000 or $5,000, the price tag will make it easily the most expensive item at the Apple Store. It's most expensive computer, the MacPro, starts at around $3,000. + +Apple's high-priced watch will be in good company -- and even if it tops the most optimistic estimates, it will be still be way cheaper than the gold standard of luxury watches, the Rolex. Amazon's Rolex page starts at $4,000 and goes all the way up to $62,000. + +But those watches don't read back texts or control your music. + +With such expensive i-jewelry on display at shopping malls across the world, will it change the way people shop at the Apple Store? Will folks be wary of walking out of the store with a multi-thousand-dollar gold watch on their wrists? + +Paul Wallace of Long Beach, Calif., admits that sporting a gold Apple watch on his wrist would make him a target. ""It would….but you've got to go Gold,"" he said. ""If you've got it, flaunt it."" + +Follow Jefferson Graham on Twitter","1" +"Don’t cancel your ski plans, Apple’s not having an event in Feb.","Contrary to a report from the often-reliable French blog iGen.fr, Apple is apparently not planning a media event late this month to introduce the Apple Watch or other new products, sources tell 9to5Mac. + +Several media reports picked up the rumor today, repeating claims that Apple has planned an event for the last week of February, perhaps February 24. The blog speculated that the event could also include the introduction of the in development 12-inch MacBook we revealed earlier this year. + + + +While it’s highly likely that Apple will hold an advance event to officially launch the Apple Watch and begin preorders ahead of shipping, the actual date remains a question mark. The French report suggested that Apple could use a late February event to begin a major media push ahead of the Apple Watch’s release, informing developers about last-minute details pertinent to app development. Though Tim Cook has confirmed that the Apple Watch will ship in April during the company’s recent earnings call, the specific release date, pricing, and other launch-related details have been left ambiguous. + +An event in February would have been a change for Apple based on recent years, though the last week of the month has often been when invites go out ahead of events held in early March. Apple’s last event in March was its new iPad and third-gen Apple TV event in 2012, while its last event in February was for the iPod Hi-Fi back in 2006. + +Mark Gurman contributed to this report.","1" +"Apple plans relaunched Beats streaming music service for WWDC, skipping March event; Apple TV still coming","Apple won’t take the wraps off of its upcoming Beats-based music streaming service at its March 9 “Spring Forward” event, according to music industry sources briefed on the launch timeline. Instead, Apple currently plans to introduce the service, at least in beta form, at its Worldwide Developers Conference (WWDC) in early June. The WWDC keynote takes place on Monday, June 8th, so that’s when the debut will likely occur. The new iTunes music streaming service is based on technology acquired from Beats Music, including curated playlists, cloud-based libraries, and offerings customized to the musical tastes of individual users. The service will be priced as high as $7.99 per month, which is less expensive than current $9.99 pricing for Beats Music, Spotify, and Rdio… + +The service was initially planned for launch earlier in 2015, but was delayed by the departures of key employees, as well as difficulties integrating Beats human and technology resources into Apple. Some Beats executives such as Bobby Gaza, who was a Senior Vice President at Beats in charge of technology, have departed Apple in recent weeks. The new Apple-made service will also make way for Apple’s first entirely-in-house Android application, but sources say that delays to the Android app are also possible as some of Apple’s Android developers have also left the company. Apple has, not coincidentally, published job listings for Android developers in recent days. + +Apple currently plans to launch the new music service as part of an iOS 8.4 upgrade for the iPhone, iPad, and iPod touch following WWDC, but a final decision has not yet been made. It’s possible that the service will be bundled into iOS 9 this fall, which is expected to have a significant focus on bug fixes and stability improvements. The service will be integrated into the standard iOS Music application and will function similarly to Beats Music for iPhone, but it will have an entirely Apple-designed aesthetic that matches the Music app and iOS. On the Mac side, the new service will be implemented with an iTunes update. + +As for the Apple TV, the new service will be an app that replaces the existing Beats channel. Sources say that Apple is also finishing up work on a slimmer Apple TV set-top-box with a more capable and tactile remote control and a redesigned operating system bundled with an App Store. As of last fall, Apple had hoped to debut a new set top box as soon as this month, but with reports of the discussions between Apple and content providers being in only “early stages”, it seems that, just like last year, content roadblocks could keep the new Apple TV from debuting until another point in the future. As we learned yesterday regarding the larger iPad Pro, Apple will have another busy fall, so perhaps the new Apple TV will launch later in the year. + +While the streaming service won’t debut at the March event, as some had hoped, Apple still has plenty to talk about. The Apple Watch will be the cornerstone of the event, where sources expect Apple to spend a significant amount of time introducing and demonstrating third-party WatchKit applications as selling points for the device. It is also highly likely that Apple will discuss the rest of the price points for the device and its accessories before the April ship date. Apple has a redesigned MacBook Air with Retina display in the works for this year, but it remains unclear whether Apple actually plans to debut the computer at the March event.","1" +"Apple might finally unveil the Retina MacBook Air of your dreams next week","Apple may take time during its upcoming media event on March 9 to talk about more than just the impending Apple Watch launch. According to The Michael Report, Apple next week will finally introduce the long-rumored 12-inch Retina MacBook Air. + +Many are expecting Apple [to] talk more about the Apple Watch. However, sources familiar with the matter within Apple have exclusively told The Michael Report that Apple plans to unveil the long-awaited Retina MacBook Air at the same event. The Michael Report has independently verified this information to be highly credible. + +Related: Stunning renders show 12-inch MacBook Air next to 12-inch iPad Air Plus + +There are few things worth mentioning here. + +First, a Retina MacBook Air has been a long time coming. The first iteration of the Retina MacBook Pro first launched back in June of 2012. Now we’re already well into 2015 and it’s about time that the MacBook Air received some Retina love. Indeed, rumors of a Retina MacBook Air being in the works stretch all the way back to 2013. + +Second, reputed analyst Ming-Chi Kuo (who has an incredibly accurate track record when it comes to Apple rumors) issued a research report last month indicating that Apple has plans to release a Retina MacBook Air sometime during the first quarter of 2015. Further, we reported this past September that Apple was eyeing a mid-2015 release date for a new MacBook Air model. + +Third, the technology to support a Retina Display on such a compact notebook is finally right around the corner. Remember that a Retina Display, with so many pixels in play, naturally drains up more battery power during day to day use, a fact which likely explains why the product was reportedly prone to developmental delays. Apple, after all, prides itself on best in class battery life and it would much rather wait than rush to release a laptop with shoddy battery life. That said, Apple’s upcoming notebooks will likely feature Intel’s next-gen Broadwell processors which promise to deliver a discernible increase in power efficiency. + +Putting all of these factors together, it certainly seems more than plausible that Apple will introduce a new member to its notebook lineup come next Monday. + +Lastly, there are two more details to keep an eye on: First, a tantalizing rumor from a few months ago claimed that Apple’s next-gen MacBook Air will be available in new color options: Space Grey and Gold, to be exact. And second, if a 12-inch Retina MacBook Air is released, some reports have claimed that Apple, in turn, will lower the pricepoints on the 11-inch and 13-inch MacBook Air models.","1" +"EXCLUSIVE: Apple To Unveil The Long-Awaited Retina MacBook Air At Its “Spring Forward” Event","Last week, Apple sent out the invites for its “Spring Forward” event, slated to be held at the Yerba Buena Center for the Arts in San Francisco on March 9th. + +Many are expecting Apple talk more about the Apple Watch. However, sources familiar with the matter within Apple have exclusively told The Michael Report that Apple plans to unveil the long-awaited Retina MacBook Air at the same event. The Michael Report has independently verified this information to be highly credible. + +We should note that this information falls in line with what Apple analysts such as KGI Securities’ Ming-Chi Kuo and Oppenheimer’s Andrew Uerkwitz have been predicting for months. Supply chain sources who spoke to the press have also said that Apple ramped up their production in late 2014 and entered the mass production stage in December, with the goal of producing enough units for an early-2015 debut. + +Apple’s MacBook Air line, which got upgraded in April last year (the only real upgrade being a small speed bump), still features a non-Retina screen with the same screen resolution that hasn’t been updated since late 2010. This is a stark contrast from the rest of the Apple computer lineup, which have been steadily upgraded to a Retina (or at least, a version of it is offered) screen since the first Retina MacBook Pro was unveiled in 2012. + +The upcoming Retina MacBook Air, if earlier reports are to be believed, will come in an ultra slim design that combines the productivity of the current larger-screened 13-inch MacBook Air with the portability of the 11-inch MacBook Air. + +Internally, the new Retina MacBook Air is said to feature Intel’s next-generation Broadwell Core M low-power processors, which would allow Apple to strip the computer of its fan assembly to create an even thinner profile. Other compromises Apple reportedly made in exchange for a thinner and lighter body includes the full-sized USB ports, MagSafe connectors and SD card slots. + +The Retina MacBook Air, currently codenamed “MacBook Stealth” internally, will also come with a modest price decrease according to previous reports.","1" +"Apple could surprise us with 12-inch MacBook Air next week","The Apple Watch is expected to be the main attraction at next week’s “Spring Forward” event, but according to a new report, the long-rumored 12-inch Retina MacBook Air could make a surprise appearance at the Yerba Buena Center for the Arts. + +The sketchy rumor comes from the Michael Report, which claims its sources inside Apple say the company’s long-awaited update to the MacBook Air will be announced March 9. + +“Sources familiar with the matter within Apple have exclusively told The Michael Report that Apple plans to unveil the long-awaited Retina MacBook Air at the same event. The Michael Report has independently verified this information to be highly credible.” + +Obviously, we can’t verify the accuracy of the report. The Michael Report unearthed full details of the iPad Air 2 before the product’s announcement in October of last year, however, the publication also whiffed on some iPhone 6 launch details, including the name of the iPhone 6 Plus, and the Nexus 6. + +We’re not really expecting any hardware other than the Apple Watch at next week’s event, but Cupertino could surprise us. The last time the MacBook Air line was upgraded was April 2014, which was just a small spec bump, so it’s due for an update. + +Hardware leaks of the 12-inch MacBook Air have been scarce, although multiple reports have confirmed that Apple is working on the device. The new Retina MacBook Air will supposedly feature a fan-less design made possible by Intel’s next-gen Broadwell processors. It’s also rumored that the new device will only have one USB-C port and a headphone jack.","1" +"Rumor Suggests 12-Inch Retina MacBook Air Could Launch During March 9 Apple Watch Event","Apple could be planning to introduce the much-rumored 12-inch Retina MacBook Air during its March 9 Apple Watch event, according to one site that claims to have sources within Apple. The Michael Report believes Apple will use the event to debut the ultrathin MacBook, which is rumored to have a Retina display and a redesigned chassis.Many are expecting Apple talk more about the Apple Watch. However, sources familiar with the matter within Apple have exclusively told The Michael Report that Apple plans to unveil the long-awaited Retina MacBook Air at the same event. The Michael Report has independently verified this information to be highly credible.While there have been no concrete rumors from major sites linking the Retina MacBook Air to Apple's March 9 event, previous rumors have indicated that Apple is planning for a spring release. Apple supplier Quanta is said to have begun mass production of the notebook in January, and KGI Securities analyst Ming-Chi Kuo predicted a March launch for the MacBook. + +Rendering of the 12-inch Retina MacBook Air created by Martin Hajek +When taking these rumors into account, along with the fact that the MacBook Air is due for an update, the introduction of the Retina MacBook Air at Apple's March 9 event does seem like a possibility. It's also possible Apple will introduce new models of the existing 11 and 13-inch MacBook Air at the event -- the last update was in April and there was a rumor suggesting an update in February was imminent. Core M Broadwell chips believed to be appropriate for the 12-inch Retina MacBook have been available since November, and chips appropriate for the standard MacBook Air began shipping in January. + +Along with a Retina display, the 12-inch MacBook Air is rumored to come without a fan assembly for silent operation, made possible by the aforementioned Core M chips, and it may also include a revamped trackpad that does not incorporate a mechanical button. It is said to feature smaller bezels in a Retina MacBook Pro-style black, a keyboard that stretches right to the edges of the machine, and speakers that are located above the keyboard. + +The Michael Report has a mixed track record when it comes to rumors. The site accurately predicted some design elements of the iPad Air 2, but its predictions may have been based on dummy models that were circulating around the Internet at the time. The site also shared details on the iPhone 6 and 6 Plus ahead of their launch, inaccurately calling the iPhone 6 Plus the ""iPhone 6L"" and suggesting the iPhones would come with quad-core processors and sapphire displays. + +More details about what Apple plans to unveil at its Monday, March 9 event may come out through the week. Thus far, many sites have agreed that the focal point of the event will be the Apple Watch, with Apple unveiling new details about the device like its price and its official launch date. + +Related roundup: Retina MacBook Air , Tag: themichaelreport.com","1" +"Bloomberg: Apple pushes back 12.9-inch iPad Pro production to September","The 12.9-inch “iPad Pro” that was expected to make its first public appearance around April before being pushed back to Q2 has been postponed yet again, a new Bloomberg report says. The new release date is reportedly some time in September, right around the next-gen iPhone launch. + +This delay is said to be the result of display panel supply problems… + +The larger tablet is expected to include an A8X processor built by Apple, and is far enough along in the development process that we’re already starting to see leaked molds, supposed manufacturing renders, and even manufacturing schematics that claim the device will run on an A9 chip and cite the name as the “iPad Air Plus.” + +Pushing the bigger iPad back to the same time as an iPhone launch makes a lot of sense, especially if both will run on the same A9 processor (as at least one rumor has suggested) or share other features. In fact, Apple hasn’t released an iPad this early in the year since the iPad 3 (“The New iPad”) launched in 2012. The fourth-generation iPad and both models of the iPad Air—as well as all iterations of the iPad mini—have been released near the end of the year.","1" +"Apple to Delay Production of Larger iPads","Apple Inc., which has seen stagnating iPad sales, will delay the start of manufacturing for a larger-screened version of the tablet, people with knowledge of the matter said. + +Production of the 12.9-inch-screen iPad is now scheduled to start around September because of delays involving the supply of display panels, said one of the people, who asked not to be identified because the details aren’t public. Apple had initially planned to begin making the larger version this quarter, people familiar with those plans had said. + +A new big-screen tablet is part of Chief Executive Officer Tim Cook’s effort to reinvigorate the iPad product line, where sales have declined for four straight quarters. IPads are also facing competition from larger iPhones, which were introduced in September and helped Apple deliver record profit in the latest quarter. +Apple, based in Cupertino, California, currently sells the iPad with a 9.7-inch display and the iPad mini, which has a 7.9-inch screen. Apple hasn’t disclosed plans for a bigger iPad. + +Existing suppliers to Apple include Sharp Corp., Japan Display Inc. and LG Display Co., according to the company’s supplier list. LG Display fell 2.5 percent to a four-month low in Seoul. Sharp fell as much as 2.6 percent before closing 0.9 percent higher in Tokyo while Japan Display dropped 2.1 percent. + +Business Tools + +A larger iPad could also bolster Cook’s initiative to make Apple’s products more appealing to business users. Apple announced a partnership last year with International Business Machines Corp. to create mobile software for businesses and for IBM to help sell iPads to corporate customers. + +Even as consumers shift away from tablets in favor of bigger smartphones, businesses remain a growth opportunity for iPads because the devices can be used for field work and as laptop replacements. In total, global sales of tablets to businesses, institutions and governments are projected to jump to 101 million units in 2018 from 19 million in 2013, according to IHS Technology. + +Billionaire activist investor Carl Icahn cited the opportunity to boost iPad sales to businesses as one of the key reasons why he thinks Apple shares are undervalued. Improvements to the iPad and the IBM partnership should help boost revenue from the device by 13 percent in each of the next three fiscal years, Icahn wrote in a public letter to Cook last year.","1" +"REPORT: Apple's 12.9-Inch 'iPad Pro' Has Been Delayed","It looks like Apple's 12.9-inch iPad has been delayed. + +The heavily rumored large-screen iPad, sometimes referred to as an ""iPad Pro,"" was initially reported to be launching in the first quarter of 2015. + +A new report from KGI Securities analyst Ming-Chi Kuo (via Apple Insider) says Apple has faced delays on its 12.9-inch iPad, which will push the launch into the second quarter of 2015. + +It's important to note that Kuo has a stellar track record when it comes to Apple, which means this is likely more than just a rumor. + +The tablet's delay reportedly stems from the type of display that Apple intends to use in the tablet, which will utilize newer LCD technologies for faster response times and higher color saturation, according to Kuo. + +Citing a ""time crunch on component production and assembly,"" Kuo believes the iPad Pro won't enter mass production until the second quarter of 2015, months later than Apple's original plans.","1" +"HBO reportedly in talks to debut $15/month standalone streaming service on Apple TV next month","HBO is reportedly negotiating with Apple to have the Apple TV included as a launch device when the network’s new standalone streaming service launches next month. International Business Times reports Apple has been “aggressive” in pushing to get access to the new service as HBO reportedly plans a launch by mid-April in time for the latest season of hit show Game of Thrones: + + + +HBO is in talks with Apple to make Apple TV one of the launch partners for its highly anticipated streaming service when it debuts next month. HBO and streaming partner Major League Baseball Advanced Media are working to have the standalone service, called “HBO Now,” ready to launch in April in conjunction with the premiere of the fifth season of “Game of Thrones,” according to sources familiar with their plans. + +The much anticipated HBO Now streaming service, first announced back in October, will allow users to access HBO content outside of a subscription from a cable TV provider for the first time. + +While the Apple TV already offers an HBO channel, it and many others currently require users to first authenticate with a cable TV account. The new streaming service, according to today’s report, will cost around $15/month when purchased directly from HBO and could arrive as soon as next month. The report adds that Apple could “add a second app for HBO Now,” which would help distinguish the standalone service from the HBO GO apps already available for cable subscribers. + +HBO hasn’t yet announced an official launch date, pricing or device support for the service.","1" +"Report: HBO Now coming to Apple TV next month","HBO plans to launch its stand-alone Net video service next month on Apple TV and other devices, according to the International Business Times. + +The news generated a bump in Time Warner (TWX) stock, pushing it to $83.80. Shares closed at $83.08, down 0.1%, and were down slightly (0.15%) in after-hours trading at $82.96. + +Sources familiar with HBO’s plans told IBT that Apple TV was among the devices that the streaming service, to be called HBO Now, would be available on at launch. The price for the service, which like Netflix would not require a pay-TV subscription, would be $15 monthly, sources said. + +When contacted, HBO offered this statement: “We know there’s great anticipation around our stand-alone streaming service. And when we have details to share, we will do so.” + +Back in October, HBO CEO Richard Plepler said the network planned to debut a stand-alone streaming service in 2015. Various reports, including IBT‘s Wednesday suggest HBO wants service up and running when its series Game of Thrones returns April 12 for its fifth season. + +“It is time to remove all barriers to those who want HBO,” he said at the time. + +Neither Apple nor MLB Advanced Media, which is reportedly providing the streaming technology for HBO, had comment on the report.","1" +"HBO in talks with Apple to be launch partner for coming web service 'HBO Now'","HBO is in talks with Apple to make Apple TV one of the launch partners for its highly anticipated streaming service when it debuts next month. HBO and streaming partner Major League Baseball Advanced Media are working to have the standalone service, called “HBO Now,” ready to launch in April in conjunction with the premiere of the fifth season of “Game of Thrones,” according to sources familiar with their plans. + +When it launches, consumers will be able to subscribe to “HBO Now” directly from HBO for the first time, rather than through a cable, satellite or telco TV distributor such as Comcast or Verizon. The retail price is expected to be $15 a month when purchased directly from HBO, or about the that consumers pay when they order HBO through their cable, satellite or telco provider. + +With “HBO Now,” HBO’s corporate parent, Time Warner Inc., is looking to a whole new generation of distributors for HBO such as Apple TV, Roku, Xbox, PlayStation, Amazon and others to help market the service to an estimated 10 million U.S. broadband subscribers who do not pay for a cable TV bundle. CEO Jeff Bewkes has said the offering could also help reach some of the 70 million cable TV subscribers who do not subscribe to HBO but might if given the opportunity to subscribe online. + +HBO’s over-the-top service has been cast as the biggest chink yet in the so-called cable bundle, where consumers are required to buy packages of channels, some of which they may never watch. One study claimed the service would lead to a 7 percent drop in pay TV subscribers as users opt of cable and opt-in to HBO Now. + +But some cable providers, such as Cablevision and Cox Communications, have expressed interest in bundling “HBO Now” with broadband for their own subscribers who don’t get cable TV. + +Apple has been most aggressive in courting HBO in a bid to add the service to Apple TV, sources say. Apple TV already carries HBO Go for current HBO subscribers, but it may add a second app for HBO Now. Apple has spent the last several years negotiating for the rights to offer their own linear TV package; in the meantime, HBO Now is seen as an added service to drive adoption of Apple TV. + +While HBO has not confirmed a launch date for HBO Now, internally the target is an April launch, in time for the April 12 debut of “Game of Thrones.” That’s an aggressive timeframe for Major League Baseball Advanced Media, which is building the back-end along with a new front-end separate from HBO Go. HBO is taking care not to launch HBO Now before it can guarantee that the service will work without some of the technical glitches that plagued HBO Go during last fall's debut of ""Game of Thrones."" + +The launch of “HBO Now” will be a milestone for Time Warner’s premium TV channel, which has for most of its 42-year history been distributed as an add-on to a package of cable channels. The web service will allow HBO to sign on a new group of distribution partners, which it sees as no different than when it added satellite TV and, later, telcos like Verizon and AT&T. + +Each of those distributors pays a wholesale price for HBO and then resells it to consumers for anywhere from $13 to $18 a month. Most see HBO as a retention device; those that subscribe are less likely to drop service or switch providers. HBO and Time Warner declined to comment. + +At $15 a month, HBO Now will be significantly more expensive than Netflix, which ranges from $8 to $12 a month for various levels of service, but cheaper than some were predicting. HBO makes the case that it has more original programming than Netflix and a better, more current film library. “It’s a premium product and it will be priced accordingly,” HBO CEO Richard Plepler said during a Time Warner earnings call in February. + +HBO’s push to launch HBO Now comes after years of talking about launching an over-the-top service that bypasses traditional cable TV. It has been met with some resistance from current distributors, such as Time Warner Cable and Comcast, two companies in the midst of a $46 billion merger, according to sources. + +But HBO heard the same misgivings from cable when it first added satellite TV providers and then telcos as distributors. HBO’s strategy is to give early partners a pricing advantage over newer ones; it’s unclear how this will go over with Apple, which has a track record of squeezing advantageous deals out of media, including the 99 cent single, more than a decade ago. + +Time Warner CEO Jeff Bewkes said in December he saw “cord-cutting” accelerate as pay-TV providers dropped subscribers. U.S. pay TV providers lost 125,000 subscribers in 2014, according to Leichtman Research Group. At the same time, HBO and Cinemax its highest number of new subscribers -- 2.8 million -- in 30 years. + +Among the challenges HBO faces to get HBO Now launched is how to avoid confusion with HBO Go, the service that allows HBO’s TV subscribers to access it on the web, smartphones and tablets. The two services will have separate log-in pages and separate apps, but some cable execs are concerned about customer confusion. The explanation might challenge even the best call center employee: HBO Go is for TV subscribers to watch their content on devices; HBO Now for those who don’t subscribe via TV. + +This article originally appeared at International Business Times. Copyright 2015. Follow International Business Times on Twitter.","1" +"HBO Reportedly in Talks with Apple for Launch of New Unbundled Streaming Service","The new season of Game of Thrones starts next month, and you know what that means: Cue the mad dash to secure someone's HBO Go password in time. But for cord cutters (and cord never-getters) who want to tune in online, this year may mark the first time they've been able to do so without breaking the rules. + +HBO is reportedly in talks with Apple to be the launch partner for its highly anticipated streaming service that wouldn't require a cable subscription, according to International Business Times. HBO Now, as it's allegedly being called, would cost $15/month and open up access to HBO's film and TV titles to distributors like Apple TV and Roku. + +HBO's existing streaming app HBO Go is currently available only through a cable subscription. Last year, HBO announced that it would finally unbundle its streaming services from cable in 2015, and the HBO Now launch could be signals that HBO is making good on that promise. + +It's unclear how the HBO Now library would measure up to HBO Go's current offerings, but the companies are reportedly trying to wrap up negotiations in time for the Season 5 premiere of Game of Thrones next month. So it's likely a safe bet that recent HBO content would be available through the Apple service. + +At a price point that's double the monthly fee for both Netflix and Hulu, the new service had better deliver on quantity, as both services offer robust streaming libraries of their own. However, while the quality of the content on those services can vary wildly, the HBO brand is known for its acclaimed original series like The Wire, The Sopranos, and Six Feet Under. + +Fans of HBO's programming, who increasingly occupy a demographic that's moving away from cable, have long craved a cable-free streaming service—but HBO has deflected the matter for years. + +Presumably, the HBO Now launch must navigate the complexities of HBO's longstanding relationship with cable carriers—Time Warner, HBO's parent company, reportedly makes 70% of its profits from cable subscriptions. But if the current negotiations with Apple are successful, the Now service could be HBO's first crack at making good on its promise to cord cutters.","1" +"HBO In Talks With Apple To Be Launch Partner For Coming Web Service 'HBO Now': Exclusive","HBO is in talks with Apple to make Apple TV a launch partner for its highly anticipated streaming service when it debuts next month. HBO and streaming partner Major League Baseball Advanced Media are working to have the standalone service, called “HBO Now,” ready to launch in April in conjunction with the premiere of the fifth season of “Game of Thrones,” according to sources familiar with the plan. + +When it launches, consumers will be able to subscribe to HBO Now directly from HBO for the first time, rather than through a cable, satellite or telco TV distributor such as Comcast or Verizon. The retail price is expected to be $15 a month when purchased directly from HBO, or about what consumers pay when they order HBO through their cable, satellite or telco provider. + +HBO’s corporate parent, Time Warner Inc., will rely on a whole new line of distributors (e.g., Apple TV, Roku, Xbox, PlayStation, Amazon, etc.) to help market HBO Now to an estimated 10 million U.S. broadband subscribers who do not pay for a cable TV bundle. CEO Jeff Bewkes has said the offering could also help reach some of the 70 million cable TV subscribers who do not subscribe to HBO but might if given the opportunity to subscribe online. + +HBO’s over-the-top service has been cast as the biggest challenge yet to the so-called cable bundle, in which consumers are required to buy packages of channels, some of which they may never watch. One study claimed the service would lead to a 7 percent drop in pay TV subscriptions, as users opt out of cable and opt in to HBO Now. + +Some cable providers, however, such as Cablevision and Cox Communications, have expressed interest in bundling HBO Now with broadband for their own subscribers who don’t get cable TV. + +Apple has been most aggressive in courting HBO in a bid to add the service to Apple TV, sources say. Apple TV already carries HBO Go for current HBO subscribers, but it may add a second app for HBO Now. Apple has spent the past several years negotiating for the rights to offer its own linear TV package; in the meantime, HBO Now is seen as an added service to drive adoption of Apple TV. + +While HBO has not confirmed a launch date for HBO Now, internally the target is an April launch, in time for the April 12 debut of “Game of Thrones.” That’s an aggressive time frame for Major League Baseball Advanced Media, which is building the back end along with a new front end separate from HBO Go. HBO is taking care not to launch HBO Now before it can guarantee that the service will work without some of the technical glitches that plagued HBO Go during last year's debut of cult-fave ""Game of Thrones."" + +The launch of HBO Now will be a milestone for Time Warner’s premium TV channel, which has for most of its 42-year history been distributed as an add-on to a package of cable channels. The Web service will allow HBO to sign on a new group of distribution partners, which it sees as no different than when it added satellite TV and, later, telcos such as Verizon and AT&T. + +Each of those distributors pays a wholesale price for HBO and then resells it to consumers for anywhere from $13 to $18 a month. Most see HBO as a retention device; those who subscribe are less likely to drop service or switch providers. HBO and Time Warner declined to comment. + +At $15 a month, HBO Now will be significantly more expensive than Netflix, which ranges from $8 to $12 a month for various levels of service, but cheaper than some were predicting. HBO makes the case that it has more original programming than Netflix and a better, more current film library. “It’s a premium product, and it will be priced accordingly,” HBO CEO Richard Plepler said during a Time Warner earnings call in February. + +HBO’s push to launch HBO Now comes after years of talking about launching an over-the-top service that bypasses traditional cable TV. Understandably, it has been met with some resistance from current distributors, including Time Warner Cable and Comcast, two companies in the midst of a $46 billion merger, according to sources. + +HBO, of course, heard the same misgivings from cable companies when it first added satellite TV providers and then telcos as distributors. HBO’s strategy is to give early partners a pricing advantage over newer ones; it’s unclear how this will go over with Apple, which has a track record of squeezing advantageous deals out of media, including the 99-cent single more than a decade ago. + +Bewkes said in December that he saw “cord-cutting” accelerate as pay TV providers dropped subscribers. U.S. pay TV providers lost 125,000 subscribers in 2014, according to Leichtman Research Group. At the same time, HBO and Cinemax reported their highest number of new subscribers (2.8 million) in 30 years. + +Among the challenges HBO faces to get HBO Now launched is how to avoid confusion with HBO Go, the service that allows HBO’s cable TV subscribers to access it on the Web, smartphones and tablets. The two services will have separate log-in pages and separate apps, but some cable execs are concerned about customer confusion. The explanation might challenge even the best call center employee: HBO Go is for TV subscribers to watch their content on devices; HBO Now for those who don’t subscribe via TV.","1" +"Report: Apple Watch Will Need Charging Every Day","Amidst all the fist-pumping and Bono-goofing yesterday, one piece of information was conspicuously absent: The Apple Watch's battery life. What's the point of strapping a tiny computer to your body if it needs constant charging? According to Re/code, even Apple hasn't quite figured out the battery dilemma yet. + +After Tim Cook mentioned charging Apple Watch ""every night"" on stage, John Paczkowski confirms today that a source within Apple pins the charge-by date at nightly—which would imply that the Apple Watch has a battery life of less than a day. Apparently, Apple is still working to improve that number before release. ""We anticipate that people will charge nightly which is why we designed an innovative charging solution that combines our MagSafe technology and inductive charging,"" an Apple spokesperson told Paczkowski, seemingly confirming the source. + +This isn't just Apple's problem. As a paradigm, smartwatches still have quite a few kinks that need working out before they'll seem truly functional—and battery life is one of the biggest. On Monday, Gizmodo's Brent Rose reported that the Moto 360's battery life, while not as bad as expected, was only about 24 hours. + +That's not terrible, but it does present some problems from a user experience perspective. The main selling point of many smartwatches is that they will constantly track your activity, from sleeping to working out. If your device needs to be charged for even a few hours every day, that's lost data, as information designer Nicholas Felton pointed out yesterday on Twitter: + +Also sad that the watch charging solution means unbroken health stats are impossible. Not necessary for everyone, but important for many. + +— Nicholas Felton (@feltron) September 9, 2014 + +Sure, not everyone cares about tracking things like REM cycles. Not everyone will mind taking off their watch for a few hours every day. But the ideal use case for Apple Watch, just like a regular watch, is effortless omnipresence. It should just work—and for periods of time longer than 12 hours. [Re/code]","1" +"Code/Red: Apple Watch Battery Life — “Charge Nightly”","One More Thing … You Have to Charge It Every Day + +“Bono really should ask Tim Cook about the Apple Watch’s battery life.” I tweeted that yesterday during the U2 frontman’s awkward vaudeville routine with Cook onstage Tuesday at Apple’s biggest event in years. We were clearly moments away from its end and we hadn’t been told how long the company’s first wearable will run on a single charge. Expected battery life was a glaring omission in an otherwise impressive parade of features and specs. And after ignoring it completely during the Apple Watch’s onstage debut, the company stalwartly refused comment on it during the device demos that followed. + +There’s a good reason for that. Sources tell me that Apple isn’t yet happy with the watch’s battery life, which isn’t going to break any industry standards. “It’s about a day right now,” said one, adding that Apple is working on various modifications ahead of the device’s 2015 launch to improve it. Reached for comment, Apple spokeswoman Nat Kerris declined to provide an estimate on expected battery life, but said the company expects users will charge their Apple Watches once daily. “There’s a lot of new technology packed into Apple Watch and we think people will love using it throughout the day,” Kerris said. “We anticipate that people will charge nightly which is why we designed an innovative charging solution that combines our MagSafe technology and inductive charging.” + +And Soil Shorts at Fitbit, Jawbone, Samsung and Motorola +Apple CEO Tim Cook on Apple Watch in an all-hands memo to employees: “This is a product which will change what people expect from wearable technology.” + +BABA Booey +Alibaba kicked off the road show for its initial public offering on Monday, and its IPO order book is already full up. Reuters says the Chinese internet giant has collected enough orders to cover the entire deal, though it’s not clear where they fall in its $60-$66 per share price range. Regardless, Alibaba’s IPO is expected to be among the largest tech offerings ever, topping out at up to $21.1 billion, topping Facebook’s $16 billion listing in 2012 as the largest-ever technology IPO. + +Apple Comms Breathing Easier Today +And not just because it pulled off the company’s biggest event in years yesterday. Looks like former White House Press Secretary Jay Carney, who was being considered for the top communications job at Apple, will not be moving to Cupertino anytime soon. He’s joining CNN as a political commentator. + +Correction: Making a Mockery of Money and Privacy +Leonid Bershidsky, Bloomberg View: “I know what Facebook is about: Making a mockery of money.” + +So the Mixed English/Chinese Soundtrack Wasn’t a Feature? +Dan Rayburn, Streaming Media Blog: “Apple’s live stream of the unveiling of the iPhone 6 and Watch was a disaster … right from the start, with many users like myself having problems trying to watch the event. Apple simply didn’t provision and plan for the event properly.” + +That 8-Digit Calculator Is a Godsend Come Budget Time +Rep. John Dingell (D-Mich.) on the Apple Watch: “I’ve gotten pretty good life out of my Casio watch, to be honest. It tells me the time and even beeps on the hour. What more could you need?” + +“Maybe” Here Being a Euphemism for “Obviously” +Path founder Dave Morin on Path: “Did the experiment fail? Maybe.” + +Off Topic +Mutant giant spider dog and shitty New Yorker cartoon captions.","1" +"REPORT: Apple Isn't Happy With The Battery Life Of Its New Smartwatch","On Tuesday, Apple unveiled its first wearable device, the Apple Watch. During the company's presentation, we learned a lot about what you'll be able to do with the company's new smartwatch. + +But what we didn't learn, however, is how long its battery would last on a single charge. + +That may be because Apple is still working out this detail, as a new report suggests. + +Attributing anonymous sources, Re/code's John Paczkowski reports that Apple isn't happy with the watch's battery life just yet. In its current form, the watch's battery life will not break any industry standards, Paczkowski says. + +Right now, the Apple Watch's battery life is about one day, but Paczkowski's sources say Apple is working on some modifications to make the watch last longer on a charge before its 2015 launch. + +This aligns with what we've heard from Apple as well, since a company representative told us the watch can be charged at night. Apple hasn't offered any further comment on the watch's battery life. + +Battery life has been one of the biggest obstacles facing wearable devices. That's because a lot of smartwatches run on components that are meant for smartphones and aren't properly optimized for wrist-worn gadgets, Chris Jones, vice president and principal analyst with Canalys Insight, told Business Insider in a previous interview. + +""We're expecting so much from these early products in the market when we don't really have dedicated components to go inside these devices,"" Jones said. ""We're nowhere near seeing the best of what can be developed out there."" + +SEE ALSO: Apple Left Out Two Very Important Details About Its New Smartwatch","1" +"REPORT: The Apple Watch will be available outside the US when it launches next month","The Apple Watch will reportedly be available in other countries, including Germany, when it launches in April, according to 9to5Mac's Mark Gurman. + +Apple CEO Tim Cook shared this information with employees at the company's flagship store in Berlin, according to Gurman, who says he spoke with an Apple employee in attendance. + +Specifically, Cook said the watch won't be exclusive to the United States in April. + +It's unclear which markets the Apple Watch will be available in, and whether or not it will be released at exactly the same time in multiple markets. As Gurman points out, it's possible Apple could release the Apple Watch in the US before releasing it to international markets such as Germany later in the month. + +This is a somewhat unusual move for Apple to make with a first-generation product. Both the iPhone and iPad were available exclusively in the US before expanding to other markets. + +Apple has been showing off its watch at boutiques in Paris and in the Paris edition of Vogue, so it seems like the company is making a push to market the watch overseas as well, as Gurman also noted. + +We expect to learn more next week when Apple holds its press event on March 9. + +SEE ALSO: We asked a bunch of fitness experts about the Apple Watch — here's what they had to say","1" +"Apple Watch may be available outside US shortly after launch","Lately, Apple cEO has been making the rounds in Europe, stopping at various stores and chatting with employees. Now and then, we get tidbits of info about his chats. The last time we heard anything about his commentary on Apple Watch, it was that he wore it in the shower, suggesting it’s a bit more water resistant than originally thought. Cook also said the Apple Watch was good for a full day of use. Now, he’s saying it will be available outside the US just after launch. + +According to unnamed employees, Apple’s CEO says the Apple Watch will be available outside the US in April. Cook reportedly said this to Apple Store employees in Berlin, and said, specifically, that the Apple Watch would come to Germany sometime in early April. + +There was no word on if any other countries or regions were specifically mentioned by Cook. + +This is another exciting piece to the puzzle for those anticipating big things from Apple on March 9. Though we’ve got quite a bit of insight on Apple Watch, we don’t know it all. + +So far, Apple is busy erecting a tent just outside the events hall where they’ll (presumably) give us more details on the Apple Watch next week. Though not necessarily confirmed as an Apple Watch hub, the tent is reminiscent of the outdoor space Apple erected last Fall, when they officially announced their wearable. + +Until we know for sure, rumors of Apple Watch coming to more countries than the one I live in is exciting news. In the past, Apple (like most companies) launched stateside before gently rolling their items to other countries. With an expected first-run of 5 million Apple Watches, though, the company might have no reason not to let interested fans slap one on their wrist. + +Source: 9to5Mac","1" +"NYT: Apple Watch includes ‘Power Reserve’ mode, shows only the time but conserves battery life","The New York Times has published a piece about the culmination of the Watch project, as Apple transitions from product development stages to production and marketing to consumers. The piece reiterates that Apple was working on a vast array of health tracking sensors that were later dropped, which 9to5Mac covered extensively at the time. + +However, the post includes one new piece of information about a previously-unannounced mode called ‘Power Reserve’. According to the report, users will be to enable a special low-power state that conserves battery life. In this mode, users will be able to see the time but cannot interact with the ‘smarter’ watch features like other apps. It is likely that other power-sapping features, like the constant connection to an iPhone for notifications, will also be disabled in this mode… + + + + +Apple has said the watch battery is estimated to last a full day, requiring a user to charge it at night, similar to a smartphone. The company also developed a yet-to-be-announced feature called Power Reserve, a mode that will run the watch on low energy but display only the time, according to one employee. + +9to5Mac has previously reported that Apple was targeting to achieve approximately 19 hours of average usage time per day, combining in-app functions with standby time, as well as 2.5 hours of straight heavy app usage. According to many reports, improving battery life has been a key goal of development since the Watch’s initial debut in September. It is unclear exactly what battery life was finally attained, but Tim Cook has repeatedly said that the device will need to be charged every night, implying approximately one day of battery life. Apple may offer more specifics at its event on March 9th, where the company will reveal more details about Apple Watch. + +One more perhaps humorous tidbit from the NYTimes: Supposedly Apple used specialized cases for the AppleWatch which disguised it as a Samsung watch, though we’re not certain how widespread this was since lots of Apple Watch sightings have happened around Cupertino and elsewhere.","1" +"Apple Watch to reportedly offer 'Power Reserve' to help extend battery life","Apple will offer a low power mode on Apple Watch to help boost it through longer days, according to a new report that also takes a stab at dispelling rumors that the company may have elected to all some long-rumored sensors last minute. + +With the exception of Pebble products, most current and upcoming smartwatches - including the Apple Watch - will last no more than a day on a single charge. To help mitigate this issue, Apple has reportedly developed a still unannounced software feature of the Apple Watch called Power Reserve, according to the New York Times. It's said to cut power to all non-essential functions and display only the time, helping to extend the watch's life in cases where a recharge may not be possible. The function is similar in concept to the Battery Saver mode in Android 5.0, which can push smartphone battery life from minutes to hours by reducing processor use. + +Apple previously stated that the Watch's battery should last only a normal day, requiring a fresh charge at night. Although standard among smartwatches, the issue has created controversy, since many had been hoping Apple would solve the smartwatch industry's battery woes with its inaugural effort. + +The report also notes that despite some recent claims to the contrary, Apple's decision to abandon some advanced health tracking features came over 18 months ago, rather than at the last minute. Early experiments in tracking factors like blood pressure and stress are said to have been ditched after the sensors proved unreliable and otherwise unworkable. Instead, the first-generation device only features motion and heart-rate sensors, once again mirroring some competing smartwatches. + +The Times also highlights some of the challenges that faced the Apple Watch's development cycle, noting that Apple not only encountered technical difficulties in achieving its ideal design but was also forced to battle the loss of key engineers, some of whom were poached by Google-owned home automation outfit Nest Labs. Among them was Bryan James, who became an Engineering vice president at Nest early last year. + +Chief among some of the later challenges was keeping a tight lid on secrecy surrounding the product while simultaneously deploying evaluation units into the real world, for which Apple engineers created dummy casing, including some resembling Samsung smartwatches. + +Apple is due to reveal more details about the Watch at a San Francisco press event on March 9th. AppleInsider will be offering live coverage of the event as it progresses.","1" +"Apple Watch Power Reserve feature will save battery life, report says","In the days leading up to Apple's big event next week, which is rumored to be focused on the Apple Watch, a new detail about the company's first wearable has been leaked. Along with all other features mentioned during Tim Cook's unveiling of the smartwatch in September, the device will also come with a feature called Power Reserve, according to The New York Times. + +The report, which cites an anonymous Apple employee, claims that the unannounced feature will allow the watch operate in a mode that only shows the current time on its display, presumably to preserve battery power for other functions. + +A standby mode for a wearable isn't particularly innovative, but given the questions surrounding the battery life of the Apple Watch (about a day, according to Apple), a Power Reserve feature dedicated to preserving battery life could be the device's saving grace. (Particularly when figures like $5,000 are being tossed around the rumor mill as the price for the top tier model.) + +Another surprising detail revealed in the report is that during field testing of the Apple Watch, engineers disguised the device with a fake casing to make it look like a Samsung smartwatch. So if you've seen Apple employees walking around with what looks like a Samsung Gear and wondered why, you now have an answer to the mystery. + +That last detail will probably come as a surprise to Samsung, a company often accused of following Apple's lead when it comes to mobile devices. But it also highlights the fact that Apple is entering a space already packed with smartwatches, so the success of the Apple Watch isn't a foregone conclusion, solid battery life or not. + +Have something to add to this story? Share it in the comments.","1" +"Apple Watch’s Power Reserve feature combats short battery life","The Apple Watch is the most buzzed about wearable to hit the market in a long time, and not all of the buzz is good. We've shared some of th earlier rumblings about the Apple Watch's short battery life. Now we are hearing news of a new feature called Power Reserve, which could be a battery-saving mode that lets the Apple Watch run on low energy while only displaying the time. + +The Apple Watch's battery life is expected to only last a day. This puts it at the bottom of the pack for iOS smartwatches. Even with a Power Reserve function, the battery is significantly lagging behind the Pebble Time's seven day battery life. Even before wearables came on the scene, not everyone is diligent about plugging in their smartphones overnight. One of the most frustrating things in the world is a dead battery when you need to check your email, text, or actually make a call. + +If the expected battery life is only one day, then we must consider what happens with higher than average usage. Imagine if dynamic and draining apps are engaged, then the battery has the possibility of lasting only until midday. This means that the user will have to take his watch off to charge it.The allure of a wearable is its instant notifications while your phone is tucked away in your pocket. If the Apple Watch isn't on your wrist, will you be drawn to look at the notifications? + +Can the new consumers get used to plugging in every night? The Power Reserve feature sounds like it may revert the smartwatch back to an ordinary time piece to save battery life. It's still better than a running out of juice. Without a charge, a dead Apple Watch isn't even a watch. It's just an expensive bracelet. Perhaps the short battery life will be overshadowed by the army of apps and developers Apple has at its disposal. We'll let you know all the emerging details leading up to Apple's big event on March 9th, 2015. + +Source: The NY Times","1" +"Apple Watch reportedly has low-energy 'power reserve' mode","We're just over a week away from learning a whole lot more about the Apple Watch, but The New York Times has just revealed a few more details about the new smartwatch. Apple employees involved with the project tell the paper that there will be a special battery stretch feature called ""Power Reserve."" The low-energy mode will let the Apple Watch continue displaying the time (and nothing else) even with scant battery life left. + +ENGINEERS DISGUISED THE SMARTWATCH AS A SAMSUNG DEVICE + +Battery life has been a major concern for the Apple Watch and other wearables — with current battery technology, there just isn't much space for a battery cell that can keep the device charged for a long time. Reports say that the watch will require nightly charging. + +The article also mentions a few details about the behind-closed doors development of the Apple Watch. Amusingly, Apple engineers who've been putting the device through its paces have kept the Apple Watch in a case that makes it look like one of Samsung's Gear smartwatches. The report also says that designers originally intended to include sensors to monitor stress and blood pressure, but those ideas were dropped after struggles with the sensors.","1" +"Sorry, Argentina's President Didn't Actually Adopt a Jewish Werewolf","If you've been anywhere even remotely near a computer today, you've probably heard that Argentina's president recently adopted a young Jewish man to stop him from turning into a werewolf. And why not—it's internet gold! Also, as it turns out, not even remotely true. + +According to the Washington Post, the story of the day is as follows: + +A tradition holds that the seventh son of a family is doomed to turn into a werewolf — known as ""el lobison"" in Argentina — after his 13th birthday and will stalk the night in its beastly form, feeding on the dead and murdering all before it.... The fear of this werewolf-child was so pronounced that many seventh sons were killed after they were born, which started the practice in 1907 of Argentine leaders taking these children symbolically under their wing. +While, yes, seventh sons and daughters in Argentina are eligible to become the godson or goddaughter (read: not the adopted child) of the country's president, as The Guardian points out, Jewish werewolf-hood has no part in the tradition. Which is fairly evident from Argentinian President Cristina Fernández de Kirchner's tweets depicting the country's newly announced first Jewish godson. + +Top translation: They brought me a menorah. They asked me to light it. Bottom translation: I didn't realize it, but their visit coincided with Hanukkah. + +But, as The Guardian points out, this nice, totally innocuous event somehow got mixed up with an ancient, werewolf-esque myth called the lobizón: + +But somehow, the story became entangled with the ancient legend of the lobizón(Argentina's equivalent to the European werewolf). According to some versions of the myth, the seventh son of the seventh son is particularly prone to fall victim to the curse. + +Evidently, the chance meeting of a Latin American president with a colorful myth too good to fact-check proved irresistible – confirming as it did any number of stereotypes about erratic behavior from national leaders in the continent of magical realism. + +In fact, the only connection between the two tales is that they center around seventh children. There is an actual, century-old tradition in which every seventh child born to an Argentinian family is eligible to become the president's godchild—a practice originating from Czarist Russia. The tale of the lobizón, on the other hand, started amongst Argentina's gauchos and has nothing whatsoever to do with the president's newly minted godson. + +So sorry to burst your bubble, internet—no werewolf Jewish godsons this time. But hey, at least it got us talking about this again. [The Guardian] + +Art by Michael Hession with help from Shutterstock and Michael J. Fox","1" +"People Actually Believed Argentina’s President Adopted A Jewish Boy To Stop His Change Into A Werewolf","The story went like this: a young Argentinian man named Yair Tawil just turned 13 years old and was adopted by the country’s president, Cristina Fernandez de Kirchhner. Why did she do it? It’s simple really. Due to Argentinian folklore, the president was required to adopt the boy in order to prevent him from turning into a werewolf. At least that’s what people believed. From New York Daily News: + +According to tradition in the country, the seventh son born to a family turns into a werewolf, a feared “el lobison”. + +The creature only shows its true nature on the first Friday after the boy’s 13th birthday, turning the teenager into a demon at midnight during every full moon. + +A demon at midnight? Do tell… + +As well as feeding on excrement, unbaptized babies, and the flesh of the recently dead, the lobison was said to be unnaturally strong and able to spread its curse with a bite. + +Fear of the lobison was so rife in 19th Century Argentina that some families abandoned or even murdered baby boys – an atrocity that sparked the unusual Presidential practice of adoption, aimed at stopping the deadly stigma. (Via) + +The problem here is that all of it is bullsh*t. According to The Guardian, it is a nice mixture of folklore and truth that fooled plenty of people and may have had them running for the silver: + +Like all good urban myths, the articles were based on a grain of truth: by tradition, the seventh son (or daughter) born to an Argentine family is eligible to become the godson (or daughter) of the president. Until this month, the honour had only been bestowed on Christian babies, but on Wednesday, Iair Tawil – not a baby, but the strapping 21-year old son of a rabbi – became the country’s first Jewish presidential godson… + +[Somehow], the story became entangled with the ancient legend of the lobizón (Argentina’s equivalent to the European werewolf). According to some versions of the myth, the seventh son of the seventh son is particularly prone to fall victim to the curse. + +That makes the entire thing infinitely less appealing. I’m disappointed now, and not just because I was ready to go get The Monster Squad together to test out my “nards” theory. Stupid facts, ruining a good story yet again. I bet science will be coming along shortly, via UBER no doubt, to add in an annoying truth to make werewolves even less cool. F*cking science.","1" +"Argentina's President Didn’t Adopt A Jewish Child To Avoid Becoming A Werewolf; So What Did She Do?","Seems like the President of Argentina Cristina Fernández Kirchner did not exactly save a Jewish boy from becoming a werewolf. Apparently this is what happens when a tradition and an urban legend get intertwined. The tradition does dictate that the seventh child born to an Argentine family with six consecutive children of the same sex is eligible to become the godchild of the president; and the urban myth says this child’s fate is unlucky as it is meant to become a werewolf sooner or later. So technically Lair Tawil was safe. + +According to the real legend of the ‘lobizón’ (or werewolf) it is only the seventh son of the seventh son who could be potentially cursed. The Guardian reported Argentine historian Daniel Balmaceda said, “The local myth of the ‘lobizón’ is not in any way connected to the custom that began over 100 years ago by which every seventh son (or seventh daughter) born in Argentina becomes godchild to the president.” + +The tradition of the president adopting a seventh child began in 1907 when then-president José Figueroa Alcorta, was asked by Russian immigrants Enrique Brost and Apolonia Holmann to become their son’s godfather. “The couple wanted to maintain a custom from Czarist Russia, where the Tsar was said to become godfather to seventh sons, and Argentina’s president accepted.” + +Although Isabel Perón passed the law in 1974, it’s still so that not every seventh child is eligible to become a presidential godchild; the honor is only given to those in which seven sons are born consecutively, with no daughters in between. The president with most godsons was Juan Perón, who had 1,982 over three terms in office. Kirchner has already become the presidential godmother of almost 700 children since taking office in 2007, and for all we know, she might've saved a few from becoming werewolves.","1" +"Argentine President Takes On Godson — But Not To Keep Werewolf At Bay","Update at 5:38 p.m. + +Did Argentine President Cristina Fernandez de Kirchner take on a godson? Yes. Did she do it, as we and others reported, because of the legend of the werewolf? No. + +The Guardian reports that a tradition that began during mass Russian immigration to Argentina in the early 20th century became conflated with a local legend involving seventh sons and werewolves. + +""The local myth of the [lobison] is not in any way connected to the custom that began over 100 years ago by which every seventh son [or seventh daughter] born in Argentina becomes godchild to the president,"" Argentine historian Daniel Balmaceda told the newspaper. + +The emigres from Russia who asked the Argentine president in 1907 to become the godfather to their seventh son were carrying on a custom from czarist Russia. The practice became law in 1974. + +Our original post is below: + +Silver bullets are believed to be among the few effective weapons against werewolves. In Argentina, add presidential protection to that short list. + +President Cristina Fernandez de Kirchner, in keeping with a long-standing tradition, has embraced a 21-year-old Jewish man as her godson to prevent him from assuming a lycanthropic form. + +The root of the story is the mythology of the Guarani people that says the seventh son in a family of only male children will turn into el lobison — a werewolf. This legend prompted some people to abandon — or kill — their seventh-born sons. So Argentina passed a law in the 1920s that gave the seventh son presidential protection along with a gold medal and a scholarship until his 21st birthday. + +At first, that law covered only Catholic families. But in 2009, a presidential decree broadened the law to cover children of other faiths, too. + +Kirchner's godson is Yair Tawil, the seventh son of a rabbi, and he's the first Jewish godson of an Argentine president. + +The Jewish Telegraphic Agency reports: + +Fernandez received Yair, his parents and three of his brothers in her office in Buenos Aires. They lit Hanukkah candles on a menorah the family presented her. Kirchner publicized the event on Twitter, calling the meeting ""magical"" and the Tawil family ""marvelous.""","1" +"No, Argentina's president did not adopt a Jewish child to stop him turning into a werewolf","Nope. Argentina’s President Cristina Fernández de Kirchner has not become godmother of a Jewish baby to stop him from becoming a werewolf – despite what you may have read in multiple news reports. + +Over the past few days, the story has been reported and unquestioningly re-reported across the echo chamber of the internet, picked up by news organisations around the world including Haaretz, Buzzfeed, The Independent and The Huffington Post. + +Like all good urban myths, the articles were based on a grain of truth: by tradition, the seventh son (or daughter) born to an Argentine family is eligible to become the godson (or daughter) of the president. Until this month, the honour had only been bestowed on Christian babies, but on Wednesday, Iair Tawil – not a baby, but the strapping 21-year old son of a rabbi – became the country’s first Jewish presidential godson. + +In her Twitter account, Kirchner described Tawil, 21, as “completely sweet” and lit Hanukkah candles with his family. + +Tenía razón. Me trajeron de regalo un candelabro de Israel. Me pidieron que encendiera las velas… pic.twitter.com/DVWewmZera + +Yo no lo sabía, pero su visita coincidía con la celebración de Hanukkah. El papá, decía que no era una casualidad… pic.twitter.com/o3y5E17Gew + +But somehow, the story became entangled with the ancient legend of the lobizón (Argentina’s equivalent to the European werewolf). According to some versions of the myth, the seventh son of the seventh son is particularly prone to fall victim to the curse. + +Evidently, the chance meeting of a Latin American president with a colourful myth too good to fact-check proved irresistible – confirming as it did any number of stereotypes about erratic behaviour from national leaders in the continent of magical realism. + +But according to Argentine historian Daniel Balmaceda, there is no link between the two traditions. “The local myth of the lobizón is not in any way connected to the custom that began over 100 years ago by which every seventh son (or seventh daughter) born in Argentina becomes godchild to the president,” he said. + +That custom began in 1907, when Enrique Brost and Apolonia Holmann, Volga German emigrés from south-eastern Russia asked then-president José Figueroa Alcorta to become godfather to their seventh son, said the historian. + +“The couple wanted to maintain a custom from Czarist Russia, where the Tsar was said to become godfather to seventh sons, and Argentina’s president accepted.” + +The practice soon became tradition and was passed into law in 1974 by Isabel Perón, the widow of Argentina’s political strongman General Juan Perón, once she succeeded him in the presidential seat after his death in office. As Argentina’s first woman president, Mrs Perón extended the benefit to seventh daughters as well.“The unconnected myth of the lobizón began among Argentina’s “gauchos,” the cowboys of Argentina’s vast cattle-raising Pampas, adapted from the older European werewolf legends,” said Balmaceda.In the Argentinian version, the lobizón transforms into a mixture of pig and dog every Tuesday and Friday night – not just once every full moon. Unlikely other werewolves of myth, the lobizón transmits its curse not through its bite but by passing between the legs of its unfortunate victims. + +In Catholic Argentina, large familes are not uncommon: over 120,000 families had seven of more children at last count in 2006. Not all qualify to become presidential god-children as the honour is only given to those in which seven sons are born consecutively, with no daughters in between. + +The president with most godsons was Juan Perón, who had 1,982 over three terms in office. He is followed by another Peronist former president, Carlos Menem, who had 1,136 during the 1990s. Fernández has become presidential godmother to some 700 children since taking office in 2007. Earlier this year, she set another precedent, by making the the daughter of a lesbian couple the first presidential godchild.","1" +"This Woman Is Wrongly Being Called A Sexual Predator After Her Private Sex Tape Was Used For A Hoax","A story is currently circulating about a teacher from Santiago del Estero, Argentina, named Lucita Sandoval who allegedly made a sex tape with a 16-year-old student, which then leaked on WhatsApp. + +British tabloids like the Daily Mail picked up the story, going so far as to write that there would be a criminal investigation and that this isn’t the first time Sandoval has had sexual relations with a student. + +The only issue with all of these sites covering the story of Lucita Sandoval, however, is that almost none of it is true, as Gawker points out. + +Local Santiago del Estero newspaper Nuevo Diario debunked the Lucita Sandoval sex tape last week. + +xvideos.com + +xvideos.com + +The sex tape currently going viral is believed to be a private sex tape that was shared to WhatsApp and then uploaded to streaming porn sites. + +To make things weirder, the woman currently misidentified as “Lucita Sandoval” is becoming a celebrity on Facebook and Twitter. A friend of the woman cleared up her identity for Nuevo Diario. + +According to her Facebook, the woman is a teacher, but not in Santiago del Estero — she’s from a different city called Corrientes. The man in the video isn’t 16 years old, either. According to his Facebook, he’s in college. + +So now, not only is a random woman’s private sex tape going viral, news sites all over the world are accusing her of possibly sexually assaulting a student. + +A somewhat similar hoax happened last week, when Chinese dating app Youjia created a fake advertisement for a woman offering to prostitute herself in exchange for travel costs. + +aicool.me + +aicool.me","1" +"Teacher sex tape exposed as a FAKE after internet detectives trace the origin of pornographic clip","Lucita Sandoval was not involved in a sex tape scandal after a newspaper unearthed the truth following internet gossip sites that were filled with reports of the story + +A graphic sex video that has been shared across South America after rumours emerged that it involved a female teacher and her teenage pupil has been exposed as a fake. + +The footage was shared by thousands of people in Argentina after false reports came out that it showed a woman called Lucita Sandoval from the city of Santiago del Estero with a 16-year-old boy. + +Internet gossip sites incorrectly stated that Miss Sandoval was a teacher and was secretly filmed by a grinning pupil of hers. + +It has since emerged that the woman in the video is not Miss Sandoval, but a completely different woman from the city of Corrientes in Argentina. + +And reports that she engaged in sexual antics with a school pupil proved to be false too, after it was revealed the young man in the video is a college student. + +It was also falsely reported that the 'teacher' has several times faced disciplinary hearings over inappropriate relationships with pupils + +An Argentinian newspaper investigated the claims, and found that no such woman exists and the video appears to be a private sex tape that was shared via Whatsapp and then uploaded to a hardcore porn website.","1" +"Lucita Sandoval sex tape hoax: Viral Argentine video features college student ― not 16-year-old boy","The story of English teacher Lucita Sandoval’s affair with a 16-year-old student went viral after video allegedly showing the two having sex leaked. But the video in question is from a porn website, and features a woman and a college student, a local newspaper found. + +A salacious sex tape from an Argentinian teacher’s affair with her 16-year-old student is likely nothing more than an Internet hoax. + +An Argentinian newspaper debunked the racy story. While the actual tape may be real, it features a woman and a college student ― not a teacher and her pupil, Nuevo Diario reported. + +The story of teacher Lucita Sandoval went viral after video allegedly showed the 26-year-old having sex with an underage student from her school in the city of Santiago del Estero. The scandalous story maintained the boy filmed her without her consent and then shared the 23-minute clip with his friends on WhatsApp. + +The story rapidly spread throughout Latin America and picked up even more steam when English wire services reported it. + +But the woman in the video is not a teacher ― and the “boy” is a college student, the Santiago del Estero newspaper found. + +While the tape is real, it appears to be from a porn website. + +The real woman who appears in the clip, identified by a friend, is from a different Argentine city, Corrientes, the newspaper reported. She does have a teaching degree, but was not employed at the school in question. The newspaper tracked down the man in the video, too, who is well over the age of 16 and in college. + +It’s unclear if “Lucita Sandoval” is a real teacher who was the victim of the online hoax or an entirely made-up person.","1" +"“Axl Rose dead 2014” : Guns N' Roses frontman killed by internet death hoax","News of singer Axl Rose’s death spread quickly earlier this week causing concern among fans across the world. However the December 2014 report has now been confirmed as a complete hoax and just the latest in a string of fake celebrity death reports. Thankfully, Guns N' Roses frontman is alive and well. + +UPDATE 03/12/2014 : This story seems to be false. (read more) + +Axl Rose death hoax spreads on Facebook + +Rumors of the singer’s alleged demise gained traction on Monday after a ‘R.I.P. Axl Rose’ Facebook page attracted nearly one million of ‘likes’. Those who read the ‘About’ page were given a believable account of the American singer’s passing: + +“At about 11 a.m. ET on Monday (December 01, 2014), our beloved singer Axl Rose passed away. Axl Rose was born on February 6, 1962 in Lafayette. He will be missed but not forgotten. Please show your sympathy and condolences by commenting on and liking this page.” +Hundreds of fans immediately started writing their messages of condolence on the Facebook page, expressing their sadness that the talented 52-year-old singer, musician and songwriter was dead. And as usual, Twittersphere was frenzied over the death hoax. + +Where as some trusting fans believed the post, others were immediately skeptical of the report, perhaps learning their lesson from the huge amount of fake death reports emerging about celebrities over recent months. Some pointed out that the news had not been carried on any major American network, indicating that it was a fake report, as the death of a singer of Axl Rose's stature would be major news across networks. + +A recent poll conducted for the Celebrity Post shows that a large majority (89%) of respondents think those Axl Rose death rumors are not funny anymore. + +Axl Rose Death Hoax Dismissed Since Singer Is ‘Alive And Well’ + +On Tuesday (December 02) the singer's reps officially confirmed that Axl Rose is not dead. “He joins the long list of celebrities who have been victimized by this hoax. He's still alive and well, stop believing what you see on the Internet,” they said. + +Some fans have expressed anger at the fake report saying it was reckless, distressing and hurtful to fans of the much loved singer. Others say this shows his extreme popularity across the globe.","1" +"Axl Rose Dead? Fans Freak Out Over Death Rumors","Rumors, claiming the Guns N’ Roses frontman allegedly died, started spreading online on Dec. 3, leaving fans shocked and saddened. Could it really be true or have Axl Rose fans fallen for a death hoax? +Axl Rose was allegedly found dead in his West Hollywood home at age 52, according to a crazy new report. Could the Guns N’ Roses frontman really have died? Fans seems to be completely shocked — and confused. + + +Axl Rose Dead — Guns N’ Roses Frontman Dies In West Hollywood Home? +Don’t worry! This report is a hoax. Axl proved he’s not dead by addressing the situation on Twitter a few hours ago. + + +At least he has a sense of humor about the death rumor! + +The fake story came from a site called MSNBC.website.com, which was designed to look like an MSNBC report. However, the two have no connection whatsoever. + +The headline from the bogus story reads: “Sources: Guns N’ Roses Frontman Axl Rose Found Dead in West Hollywood Home at Age 52.” + + +'Pretty Little Liars': Lucy Hale Teases Christmas Special EXCLUSIVE +Hollywood Life + +“Unconfirmed reports say Rose was found dead Tuesday late afternoon in his West Hollywood home after police were called around 3:30 pm for a welfare check,” the story claims. The report then goes on to say a police spokesperson said, “The home was entered by police through an open back door where a body was found in the foyer area.” + +The website pulled a similar prank in November, when it claimed Home Alone star Macaulay Culkin had died. That story also proved to be fake! + +Axl Rose Dies — Fans React On Twitter + +How do YOU feel about death hoaxes, HollywoodLifers? Are they entertaining or just plain scary? Tell us how you feel! + +– Chris Rogers","1" +"The Internet Tried To Make Axl Rose Its Latest Death Hoax Victim","Oh Internet, when will you ever stop killing perfectly healthy celebrities, or at least those that are healthy enough to be alive? Today, one of those ridiculously stupid and fake-looking hoax sites that generates random celebrity death stories once again proved that people are gullible and should have to take IQ tests to use the Internet. Looking like an MSNBC page that stopped loading in 2004, the farticle (that’s my name for these fake articles) claimed that sources were “reporting” that Guns N’ Roses frontman Axl Rose was found dead yesterday from unknown causes in his West Hollywood home. + +“The home was entered by police through an open back door where a body was found in the foyer area,” read the report created by a douchebag with a presumably large, Dorito-speckled smirk on his face. While plenty of people fell for it enough for the link to start spreading on Facebook and Twitter, the sleuths at Gossip Cop quickly proved that it was fake. Probably by looking at it. + +The awful hoax comes from the jerks behind the MSNBC.website URL, which has no affiliation with the real news outlet and tries to fool people into clicking on bogus stories. A new phony report has the headline, “Sources: Guns N’ Roses Frontman Axl Rose Found Dead in West Hollywood Home at Age 52.” + +Enough people have been duped by this story to share it more than 39,000 times on social media like Facebook. Again, this is TOTALLY FAKE. MSNBC.website pulled the same trick last month with a death hoax about Macaulay Culkin. The phony Culkin story is almost identical to the phony Rose story. Don’t believe any report coming from MSNBC.website. (Via Gossip Cop) + +One of these days, Rose might actually pass away and then none of us will believe it because of these stupid hoax reports. And then his funeral will be really sad when it starts raining and Slash plays a guitar solo with no shirt under his leather jacket on top of Rose’s casket, and nobody’s there to appreciate it. + +RELATED: Since we’re talking about GNR, do yourself a favor and go back and read Danger Guerrero’s breakdown of “November Rain.”","1" +"Axl Rose NOT Dead: Fake MSNBC Death Hoax Goes Viral On Facebook","Axl Rose is NOT dead. He’s the victim of a new death hoax, designed to look like an MSNBC report. Do not believe it. Axl Rose is alive and hopefully well. + +The awful hoax comes from the jerks behind the MSNBC.website URL, which has no affiliation with the real news outlet and tries to fool people into clicking on bogus stories. A new phony report has the headline, “Sources: Guns N’ Roses Frontman Axl Rose Found Dead in West Hollywood Home at Age 52.” + +To fill out the 100 percent fake story, the pranksters write, “Unconfirmed reports say Rose was found dead Tuesday late afternoon in his West Hollywood home after police were called around 3:30 pm for a welfare check.” According to a fake quote from a fake police spokesperson, “The home was entered by police through an open back door where a body was found in the foyer area.” + +Enough people have been duped by this story to share it more than 39,000 times on social media like Facebook. Again, this is TOTALLY FAKE. MSNBC.website pulled the same trick last month with a death hoax about Macaulay Culkin. The phony Culkin story is almost identical to the phony Rose story. Don’t believe any report coming from MSNBC.website.","1" +"Axl Rose Dead? Of Course Not — Tiresome Internet Death Hoax Plague Hits Guns N’ Roses Frontman","Axl Rose is not dead, despite internet reports to the contrary — but that should come as no surprise to fans who by now have surely grown tired of the seemingly endless stream of online hoaxes falsely reporting the death of just about every major celebrity, and plenty of minor celebs as well. + +The Axl Rose death hoax started on a bogus site forged to look like a page on the MSNBC website. The authentic looking — at a cursory glance, anyway — story was headlined, “Sources: Guns N’ Roses Frontman Axl Rose Found Dead in West Hollywood Home at Age 52,” and claimed that the “Welcome To The Jungle” singer was found dead after police were called to check on the former rock star’s welfare. + +Perhaps in a vain attempt to add an air of authenticity to the latest death hoax, the phony story on the ersatz MSNBC site claimed the death of Axl Rose remained “unconfirmed.” + +“It’s fake, dude,” wrote the site Mediaite, in its story mocking the Axl Rose death hoax. “You can go ahead and confirm it.” + +The site Gossip Cop, which specializes in debunking rumors about celebrities — dead or alive — was among the first to expose the fakery, which apparently fooled numerous internet users with its convincing-looking URL, “msnbc.website.” + +“The awful hoax comes from the jerks behind the MSNBC.website URL, which has no affiliation with the real news outlet and tries to fool people into clicking on bogus stories,” reported Gossip Cop. “Enough people have been duped by this story to share it more than 39,000 times on social media like Facebook. Again, this is TOTALLY FAKE. MSNBC.website pulled the same trick last month with a death hoax about Macaulay Culkin. The phony Culkin story is almost identical to the phony Rose story. Don’t believe any report coming from MSNBC.website.” + +In addition to Home Alone star Culkin, and today’s hogwash “Axl Rose is dead” prank, other celebrities victimized by death hoaxes recently have included “Dog Whisperer” Cesar Millan, ’80s “Brat Pack” actor Judd Nelson, and TV Incredible Hulk star Lou Ferrigno. + +While Axl Rose and his representatives have not confirmed that the “Paradise City” crooner is actually still living and breathing, but they probably don’t need to. But one thing is certain. Axl Rose may be the latest, but will certainly not be the last “dead” but-not-really celebrity to be the subject of a yet another tiresome online death hoax.","1" +"Posted in: Celebrity News Posted: December 3, 2014 Axl Rose Dead? Of Course Not — Tiresome Internet Death Hoax Plague Hits Guns N’ Roses Frontman","Axl Rose is not dead, despite internet reports to the contrary — but that should come as no surprise to fans who by now have surely grown tired of the seemingly endless stream of online hoaxes falsely reporting the death of just about every major celebrity, and plenty of minor celebs as well. + +The Axl Rose death hoax started on a bogus site forged to look like a page on the MSNBC website. The authentic looking — at a cursory glance, anyway — story was headlined, “Sources: Guns N’ Roses Frontman Axl Rose Found Dead in West Hollywood Home at Age 52,” and claimed that the “Welcome To The Jungle” singer was found dead after police were called to check on the former rock star’s welfare. + +Perhaps in a vain attempt to add an air of authenticity to the latest death hoax, the phony story on the ersatz MSNBC site claimed the death of Axl Rose remained “unconfirmed.” + +“It’s fake, dude,” wrote the site Mediaite, in its story mocking the Axl Rose death hoax. “You can go ahead and confirm it.” + +The site Gossip Cop, which specializes in debunking rumors about celebrities — dead or alive — was among the first to expose the fakery, which apparently fooled numerous internet users with its convincing-looking URL, “msnbc.website.” + +“The awful hoax comes from the jerks behind the MSNBC.website URL, which has no affiliation with the real news outlet and tries to fool people into clicking on bogus stories,” reported Gossip Cop. “Enough people have been duped by this story to share it more than 39,000 times on social media like Facebook. Again, this is TOTALLY FAKE. MSNBC.website pulled the same trick last month with a death hoax about Macaulay Culkin. The phony Culkin story is almost identical to the phony Rose story. Don’t believe any report coming from MSNBC.website.” + +In addition to Home Alone star Culkin, and today’s hogwash “Axl Rose is dead” prank, other celebrities victimized by death hoaxes recently have included “Dog Whisperer” Cesar Millan, ’80s “Brat Pack” actor Judd Nelson, and TV Incredible Hulk star Lou Ferrigno. + +While Axl Rose and his representatives have not confirmed that the “Paradise City” crooner is actually still living and breathing, but they probably don’t need to. But one thing is certain. Axl Rose may be the latest, but will certainly not be the last “dead” but-not-really celebrity to be the subject of a yet another tiresome online death hoax.","1" +"Axl Rose Found Dead of Sh*tty Hoax Website at Age 52","It appears we have the world’s first hoax serial killer on our hands. Only weeks after Judd Nelson was reported dead by a fake Fox News website, a fake MSNBC site is now reporting that Axl Rose was found dead in his home at the age of 52. + +Fetch thee thy magnifying glass to detect the problems with the website below: + +This humble scribe’s favorite bit is that the hoax bothered to call the reports “unconfirmed.” It’s fake, dude; you can go ahead and confirm it. + +On that note Mediaite reached out to Rose’s camp to check on his pulse, and will update accordingly. + +[Image via Nikola Spasenoski / Shutterstock.com] + +—— >> Follow Evan McMurry (@evanmcmurry) on Twitter","1" +"Axl Rose Dies? Guns N’ Roses Singer Dead ‘West Hollywood Home at Age 52′ is Fake","Axl Rose, the singer of Guns N’ Roses, has not died in West Hollywood at the age of 52. + +A hoax news website designed to look like MSNBC was promulgating the false rumors this week. The site says MSNBC.website, which isn’t real. + +Users on social media were questioning whether the “Chinese Democracy” singer was still alive. + +The bogus story reads: “Unconfirmed reports say Rose was found dead Tuesday late afternoon in his West Hollywood home after police were called around 3:30 pm for a welfare check.” + +It also includes fake quotes from police officers. The article has been shared tens of thousands of times on Facebook. + +MSNBC.website was also responsible for a hoax that said Home Alone actor Macaulay Culkin was found dead at age 34 a few weeks ago. That obviously wasn’t true, either. + +Earlier his year, Rose said that Guns N’ Roses has two new albums in the works. The last album the band released was “Chinese Democracy” in November 2008, which was censored in China due to its title track and reference to Falun Gong, a traditional Chinese spiritual practice that has been persecuted in China for the past 15 years. + +“We recorded a lot of things before ‘Chinese’ was out,” Rose told Rolling Stone. + +He added: “We’ve worked more on some of those things and we’ve written a few new things. But basically, we have what I call kind of the second half of Chinese. That’s already recorded. And then we have a remix album made of the songs from Chinese. That’s been done for a while, too. But after Vegas [Guns N’ Roses is performing a residency at the Hard Rock Hotel & Casino that runs through June 7], we’re going to start looking very seriously at what we’re doing in that regard.”","1" +"No, Banksy has not been arrested (sigh)","Let’s clear this one up quickly. + +A US website is carrying a report that the world’s richest street artist Banksy has been identified and arrested. + +It is, of course, completely fake, and the quotes used in the National Report piece were originally ‘issued’ via a press release hosted by a satirical website in 2013. + +Hm…","1" +"Everybody Relax, Banksy Wasn’t Arrested And Exposed As A 35-Year-Old Man","If you’ve seen a story floating around on your Facebook feed about Banksy getting arrested and exposed, don’t worry because Banksy is still anonymous and well. The hoax was the work of a “satirical” news site called The National Report — which I’m not linking because f*ck those guys — that makes up fake stories that sound like they could be ostensibly true, usually without a trace of actual satire, as filthy, filthy clickbait. It’s an awful yet unfortunately effective business model. + +In a story which was published early this morning, The National Report claimed that Banksy was arrested in London by a 24-hour Anti-Graffiti Task Force and revealed to be a 35-year-old man named Paul Horner. The International Business Times did some quick fact checking and exposed the story to be a hoax: + +Paul Horner is the name given to a Facebook spokesperson who said the site will soon be charging users $2.99 a month – another hoax story that comes around every now and again – as well as the name from a hoax story about a 15-year-old Louisiana teen who was sentenced to 25 years to life after he called a SWAT team to another teenager’s house after he beat him while playing Battlefield 4. + +The article is also said to have been written by Dr Darius Rubics, a fake name for a writer who claims to have be a Pulitzer-prize winning reporter but who, unsurprisingly since his previous stories include ‘Obama Declares November National Muslim Appreciation Month’ and ‘Dennis Rodman Leaves US To Talk With Leaders Of Isis’, has never been awarded any prizes for excellence in journalism. + +HAHA get it? It’s funny because it’s not true! I guess there’s some logic in there somewhere. It’s not even entertaining to see people share stories that come from places like the The National Report since they’re designed to trick — unlike when dumb people share stories from The Onion, which are designed to actually be satire. Again, and I cannot stress this enough: F*ck those guys.","1" +"A Bunch Of People Thought Banksy Got Arrested But It Was A Hoax","SHOCK! + +HORROR! + +Here’s the VITAL NEWS REPORT… + +…which bears a startling resemblance to a hoax that went around last year. + +And uses a photo of someone being arrested in the run-up to the Notting Hill Carnival. + +Here’s who Paul Horner is, by the way. + +And that’s the story of Banksy’s arrest, in full.","1" +"Everyone chill! Banksy has NOT been arrested","A hoax report filed by website nationalreport.net claimed the infamous artist had been arrested in London during a raid on his art studio. + +The website – which describes itself as ""America's No.1 independent news source"" – said a man named Paul Horner from Liverpool had been nicked. + +They even had the cheek to say both the BBC and a representative for Bansky had confirmed the news. + +To complete the tale they quoted ""London police chief"" Lyndon Edwards who apparently held a press conference to announce the arrest. A press conference apparently attended by no reporters or TV crews. + +HOAX: The false report claiming Banksy had been arrested [NATIONALREPORT] +Most hilariously of all the article was written by one Darius Rubics who has ""won numerous awards for journalism including a Peabody Award and a Pulitzer Prize"". + +Despite the ludicrous nature of the article some fell for it hook, line and sinker. + +Former Tory MP Louise Mensch, never shy of sharing her opinion with the world, said: ""You have to be kidding me, @metpoliceuk. Banksy? + +""There are so many criminals out there, Banksy? The great artist?"" + +She did later apologise after being duped. + + +There are so many problems with the hoax we've decided to list some of the best ones for you. + +– The article claims Banksy is from Liverpool when all known evidence strongly suggests he is from Bristol. + +– Other articles by Darius Rubics include: Dennis Rodman leaves US to talk with leaders of ISIS and Obama declares November national Muslim appreciation month. + +– London Police Chief Lyndon Edwards doesn't exist. The top cop in London is Sir Bernard Hogan Howe. + +– The article suggests Banksy was nicked in Watford which actually falls under the catchment of the Hertfordshire Police. + +– In Britain police do not release mugshots of people after they have been arrested. + +– Banksy's PR Jo Brooks, despite apparently being quoted in the original story, has tweeted saying it is a hoax.","1" +"Met police denies reports of Banksy arrest","The London Metropolitan Police has denied reports that street artist Banksy has been arrested on Monday after a 24-hour Anti-Graffiti Task Force operation. +A Met spokesperson said the force did not have any information of such arrest and even if they had, it was possible they would not publish a press release about it. +Meanwhile, the fake press release initially published by PR Log has been taken down.","1" +"Once Again, The Banksy 'Arrest' Is A Giant Hoax. Repeat: A Hoax.","Banksy has not been arrested. Let's not bury the lede here, people. The news of his incarceration is, yet again, a hoax. + +If you woke up this morning to a Twitter feed filled with recycled ""OMG BANKSY WAS ARRESTED/WTF BANKSY WAS NOT ARRESTED"" exclamations, here's why. + +This week's fickle rumor started with The National Report, which for those unaware, is an American satire site. A satirical post on the site reported, in a joking fashion lost on many an Internet surfer, that a 35-year-old man had been apprehended by authorities in the London suburb of Watford early Monday morning. It claimed that a press conference had validated that the man was indeed Banksy, that the BBC confirmed the information in their report, and that five men in total had been snagged with counterfeit money and ""future projects of vandalism."" + +So illicit! So false. + +Just to be extra clear, here are a few things that did not happen today: The anonymous British street artist was not caught by a ""24-hour Anti-Graffiti Task Force."" Police did not raid his studio in the middle of the night like a carefully plotted drug bust. His name is not and never will be Paul Horner. + +We do appreciate the fact that someone out there is trying her hardest to make the name ""Paul Horner"" a thing. Remember last year, when some trolly press release tried to convince the masses that a Banksy arrest happened? The name of the apprehended: Paul Horner. + +Stop trying to make ""Paul Horner"" happen, Gretchen. It's not going to happen!","1" +"Banksy 'Arrested & Real Identity Revealed' Is The Same Hoax From Last Year","Elusive graffiti artist Banksy’s cover was blown when he was unceremoniously arrested for vandalism, conspiracy, racketeering and counterfeiting. + +Well that’s what US website the National Report would have you believe. + +The bogus story alleged the infamous street artist was arrested following a raid on his London studio. + +It ‘outs’ him as Paul Horner, a 34-year-old born in Liverpool and says he is being held “without” bail, along with four other, unnamed individuals. + +Banksy's publicist Jo Brooks confirmed to the Independent the now viral story is a hoax. + +Indeed the quotes which accompany the piece date back to an identical spoof in February last year, which claimed Banksy had been arrested on the same charges and outed as, yep, Paul Horner. + +So basically the internet is now recycling its own hoaxes. Lazy.","1" +"Hoax 'Banksy Arrested in London' Story Dupes the Internet Again","A hoax story alleging the British graffiti artist Banksy has been arrested and has had his identity revealed has once again duped thousands of people online. + +According to the highly refutable website National Report, a 'news' website consisting entirely of fake stories, the artist was arrested by Metropolitan Police at his studio and his identity revealed as 35-year-old Paul Horner, originally from Liverpool. + +The article contains all the elements you would expect to see from a news story covering an arrest, including details from police and quotes from those close to Banksy. + +However, it only takes the bare minimum of fact-checking and research to spot that this story is a hoax. + +The article claims the story has been confirmed by the BBC (it hasn't) and that City of London Police Chief Lyndon Edwards held a press conference to answer questions about Banksy's arrest (he never did and Edwards doesn't even exist). + +US news site CNN also did not conduct an interview with Banksy's ""project manager"" John Hawes following his arrest (also because he doesn't exist). + +The 'revealed identity' of Banksy is also suspicious. + +Paul Horner is the name given to a Facebook spokesperson who said the site will soon be charging users $2.99 a month – another hoax story that comes around every now and again – as well as the name from a hoax story about a 15-year-old Louisiana teen who was sentenced to 25 years to life after he called a SWAT team to another teenager's house after he beat him while playing Battlefield 4. + +The article is also said to have been written by Dr Darius Rubics, a fake name for a writer who claims to have be a Pulitzer-prize winning reporter but who, unsurprisingly since his previous stories include 'Obama Declares November National Muslim Appreciation Month' and 'Dennis Rodman Leaves US To Talk With Leaders Of Isis', has never been awarded any prizes for excellence in journalism. + +One final, major clue that the story is a hoax is that the exact same thing has happened before. Last February, a fake press release that again claimed Banksy has been arrested and again claimed his name is Paul Horner did the rounds, with Jezebel being one of the more high-profile websites to publish the hoax before later taking it down. + +Despite this, the latest 'Banksy arrested' story has been shared more than 200,000 times on Facebook and Twitter, proving there are still people who will believe anything they read on the internet. + +RelatedClacton-on-Sea Scrubs 'Racist' £400,000 Banksy Mural off WallKing Robbo: Graffiti Artist and Banksy Rival DiesBanksy Condemns 'Disgusting' Exhibition Featuring His Stolen ArtworkBansky Pokes Fun at GCHQ With Cheltenham MuralAlternative Miss World 2014: Drag Queens, Robots and a PVC Octopus Compete at Shakespeare's Globe","1" +"Banksy arrest hoax: Internet duped by fake report claiming that the street artist's identity has been revealed","Fear not, the street artist is still roaming free, spray can in hand + +Banksy has not been arrested, despite a report stating the contrary. + +“The Banksy arrest is a hoax,” the street artist’s publicist, Jo Brooks, told The Independent. + +However, the prank seems to have duped the internet, with his name quickly trending on Twitter. + +A false story, published on US website National Report, alleged that the identity of the British street artist had finally been revealed and he had been arrested by London’s Metropolitan Police and is being held “without bail on charges of vandalism, conspiracy, racketeering and counterfeiting”. + +The story claimed that Banksy’s London art studio had been raided, where “thousands of dollars of counterfeit money along with future projects of vandalism” were found, along with ID thought to belong to the famed anonymous street artist, which allegedly identified him as Liverpool-born Paul Homer. + +However, a quick google search shows that the quotes were originally published in 2013 on hoax website on PRLog. + +Nonetheless, the joke struck a nerve with Louise Mensch, who fell wholeheartedly for the ‘news’ and chastised the police for arresting the street artist and not focusing on other more pressing issues. + +You have to be kidding me, @metpoliceuk. Banksy? There are so many criminals out there, Banksy? The great artist? + +After she was notified that the report was, in fact, a prank, she quickly apologised to the police. + +OK. Apparently it's bullshit. Sorry @metpoliceuk #Banksy + +Fear not world, Banksy is still roaming free, spray can in hand.","1" +"Banksy arrest hoax: Internet duped by fake online report claiming artist's identity has been revealed","Fear not, the street artist is still roaming free, spray can in hand + +Banksy has not been arrested, despite a report stating the contrary. + +“The Banksy arrest is a hoax,” the street artist’s publicist, Jo Brooks, told The Independent. + +However, the prank seems to have duped the internet, with his name quickly trending on Twitter. + +A false story, published on US website National Report, alleged that the identity of the British street artist had finally been revealed and he had been arrested by London’s Metropolitan Police and is being held “without bail on charges of vandalism, conspiracy, racketeering and counterfeiting”. + +The story claimed that Banksy’s London art studio had been raided, where “thousands of dollars of counterfeit money along with future projects of vandalism” were found, along with ID thought to belong to the famed anonymous street artist, which allegedly identified him as Liverpool-born Paul Homer. + +However, a quick Google search shows that the quotes were originally published in 2013 on hoax website on PRLog. + +Nonetheless, the joke struck a nerve with Louise Mensch, who fell wholeheartedly for the ‘news’ and chastised the police for arresting the street artist and not focusing on other more pressing issues. + +You have to be kidding me, @metpoliceuk. Banksy? There are so many criminals out there, Banksy? The great artist? + +After she was notified that the report was, in fact, a prank, she quickly apologised to the police. + +OK. Apparently it's bullshit. Sorry @metpoliceuk #Banksy + +Fear not world, Banksy is still roaming free, spray can in hand.","1" +"Banksy has not been arrested: Internet duped by fake report claiming artist's identity revealed","Fear not, the street artist is still roaming free, spray can in hand + +Banksy has not been arrested, despite a report stating the contrary. + +“The Banksy arrest is a hoax,” the street artist’s publicist, Jo Brooks, told The Independent. + +However, the prank seems to have duped the internet, with his name quickly trending on Twitter. + +A false story, published on US website National Report, alleged that the identity of the British street artist had finally been revealed and he had been arrested by London’s Metropolitan Police and is being held “without bail on charges of vandalism, conspiracy, racketeering and counterfeiting”. + +The story claimed that Banksy’s London art studio had been raided, where “thousands of dollars of counterfeit money along with future projects of vandalism” were found, along with ID thought to belong to the famed anonymous street artist, which allegedly identified him as Liverpool-born Paul Homer. + +However, a quick Google search shows that the quotes were originally published in 2013 on hoax website on PRLog. + +Nonetheless, the joke struck a nerve with Louise Mensch, who fell wholeheartedly for the ‘news’ and chastised the police for arresting the street artist and not focusing on other more pressing issues. + +You have to be kidding me, @metpoliceuk. Banksy? There are so many criminals out there, Banksy? The great artist? + +After she was notified that the report was, in fact, a prank, she quickly apologised to the police. + +OK. Apparently it's bullshit. Sorry @metpoliceuk #Banksy + +Fear not world, Banksy is still roaming free, spray can in hand.","1" +"No, Banksy hasn’t been arrested","Never fear, Banksy fans: the infamous street-artist has not been unmasked, despite frenzied reports on American websites. + +Online news sites were subject to a hoax on Friday from US ‘media troll extaordinaire’ Paul Horner. + +Sites Complex, Death and Taxes, and Jezebel published online stories stating that Paul Horner, 39, had been identified as the street-artist known as Banksy, and had been arrested by British police in Watford. + +Horner is in fact editor of the cunningly-named Super Official News website, where he makes statements such as: “Until then just remember, if it’s on the internet it must be true”, and that “Paul Horner is an American hero.” + +Website NationalReport said that “London Police Chief Lyndon Edwards” had held a press conference unmasking Banksy after the arrest - but according to the Met, no such officer exists. However, there is a dairy farmer called Lyndon Edwards. + +Other Banksy pretenders incude,‘cap man’ in New York, 2013; Robin Gunningham in Bristol, 2008; Mr Brainwash in 2010; and Rose Biggin, an 89-year-old from Camden, North London, who was touted as the elusive street-artist. The pensioner said of her “I’m Spartacus” moment: “It sure does help to pass the time.” + +Even a Battersea charity shop got in on the act – earlier in October someone from the Fara shop on Northcote Road not pretending to be the artist painted a Banksy-style mural and tweeted it soon after.","1" +"Calm down everyone, Banksy hasn't been arrested: 9 clues that it's a hoax","The rumour that Banksy has been arrested has been circulating on the internet + +An article has started circulating on Twitter today claiming that Banksy has been arrested. + +The story on ""news"" website National Report says that Banksy was arrested in Watford after been tracked by a ""24-hour Anti-Graffiti Task Force"". + +Stories crop up all the time claiming to reveal the true identity of the guerrilla graffiti artist, but this one is particularly ridiculous. + +The National Report have also produced this video which claims to prove his arrest. + +Video loading + +Here's why it's definitely a hoax... + +1. Banksy isn't from Liverpool + +He's from Bristol according to his Wikipedia. + +2. There's no London Police force + +There's the Metropolitan Police and the City of London Police, both used interchangeably in the article. + +3. There's no London Police Chief called Lyndon Edwards + +We call them The Commissioner of Police of the Metropolis. And he is Sir Bernard Hogan Howe. + +4. Police don't release pictures of people being arrested + +Nope. They definitely don't do that. + +5. Met Police don't cover the Watford area. + +That's Hertfordshire Police's job. + +6. The website it comes from is full of spurious stories + +Other headlines on the site include 'Kanye West applies for refugee status' and 'Miley Cyrus replaced by double in 2010'. + +7. The same article was circulating last year as a press release + +Before Banksy was Paul William Horner a 39 year old, rather than Paul Horner, a 35-year old. + +8. The picture of him being arrested is from Notting Hill Carnival 2012 + +Put that picture URL into Google images and you get pictures from Carnival. + +9. And as if you needed any more proof, Banksy's PR has confirmed it is a hoax + +@JDBeauvallet it's a hoax— jo brooks (@brightonseagull) October 20, 2014 + +Nevertheless it looked real enough to fool many people - including former Tory MP Louise Mensch. + +You have to be kidding me, @metpoliceuk. Banksy? There are so many criminals out there, Banksy? The great artist?— Louise Mensch (@LouiseMensch) October 20, 2014 + +But it's definitely a hoax, Banksy's secret is still safe for now. Everyone back in your boxes until the next rumour appears. + +Banksy’s real identity has been a closely kept secret ever since his work emerged in 1992. + +Initially it was rumoured he was born Robin Banks, a former butcher. + +However, more recently people believe he could be Robin Gunningham, who enjoyed a middle-class upbringing in Bristol. + +During a rare interview he was described as “a cross of Jimmy Nail and British rapper Mike Skinner”. + +Banksy has also claimed his parents think he is a painter and decorator. + +VIEW GALLERY","1" +"Banksy arrest hoax: US website claims street artist caught in Watford","A hoax story about street artist Banksy being arrested in Watford has duped internet users. + +US website National Report alleged the Metropolitan Police had held the elusive graffiti artist after he was traced by a ""24-hour Anti-Graffiti Task Force"". + +It claimed his art studio in the capital had been raided and “thousands of dollars of counterfeit money along with future projects of vandalism” found. + +The story also said documents identified the anonymous artist as 35-year-old Paul Homer, from Liverpool. + +He was said to be in custody “without bail on charges of vandalism, conspiracy, racketeering and counterfeiting”. + +However, Scotland Yard confirmed the story - which left Banksy's name trending on Twitter - was fake. + +A spokesman said: ""We are certainly not aware of Banksy being arrested in Watford, or anywhere else for that matter."" + +The story hit a chord with Louise Mensch, the former Conservative MP who is active on Twitter. + +She fell for the scam and criticised the Metropolitan Police for not focusing on the ""so many other criminals out there"". + +But she quickly apologised when she was alerted to the story being a prank. + +The story fooled thousands of others on social media, who expressed shock that the infamous artist had been unmasked at last. + +You have to be kidding me, @metpoliceuk. Banksy? There are so many criminals out there, Banksy? The great artist?— Louise Mensch (@LouiseMensch) October 20, 2014 + +You have to be kidding me, @metpoliceuk. Banksy? There are so many criminals out there, Banksy? The great artist? + +However, there were several clear discrepancies in the National Report story. + +It mentions Banksy was arrested by the Metropolitan Police and the City of London Police, which are different forces. + +The report quotes ""London Police Chief Lyndon Edwards"", which is a fictional name, and uses a picture of an arrest ahead of the Notting Hill Carnival in 2011.","1" +"No, that broken pencil illustration isn't by Banksy","You may have seen a clever Banksy illustration of broken pencils being shared far and wide on social media yesterday. It's a powerful message about optimism and rebuilding after facing adversity. But it's not by Banksy. + +The illustration is actually by Lucille Clerc, a London-based illustrator. After being posted on an Instagram account purporting to be associated with Banksy, the image has been shared over 130,000 times. There are a lot of fake Banksy accounts on social media but the one that scraped Lucille Clerc's image has over a million followers, which explains its wide reach. + +The Independent talked to a spokesperson from Banksy's camp who said ""We can confirm this is not by Banksy."" [Emergent]","1" +"Lucille Clerc's powerful message of perseverance goes viral after a fake Banksy account reposts it","UPDATE, Jan. 8, 8:51 a.m. ET: We now know that the illustration below wasn't by Banksy and was not an original piece of art. It was illustrated by Lucille Clerc, a London-based graphic designer and printmaker, who shared it on social media on Wednesday night. + +Editors' note: This image, which is unique according to a reverse image search done on Tin Eye, was posted on the @Banksy Instagram account to its nearly 1 million followers. It is not, however, confirmed to be an official account operated by the artist. It could be Banksy, but the artist's real accounts are unclear. We've changed the headline and story below to reflect that. + +A popular Banksy Instagram account weighed in on Wednesday with a powerful homage to the murdered journalists at the French newspaper Charlie Hebdo, victims of a horrific terror attack. + +Take a look: + +A photo posted by Banksy (@banksy) on Jan 1, 2015 at 3:02pm PST + +The account, which has nearly one million followers — though it is not known to be an official Banksy Instagram account — posted a picture on featuring three pencils — the pencil fully intact is next to the word ""yesterday,"" a broken pencil represents ""today,"" and the resharpened shard shows there will be two pencils ""tomorrow."" + +It adds: ""RIP,"" joining scores of other cartoonists and artists who have been sharing tributes throughout the day. + +Twelve people were killed in what France's president called a ""terror attack"" on satirical magazine Charlie Hebdo in Paris on Wednesday, leading authorities to launch a massive manhunt for the gunmen, who remain at large. No arrests have been confirmed in the hunt for the attackers, though an ""anti-terror raid"" is reportedly underway in the northeastern city of Reims. + +The brothers, caught on tape by an eyewitness, shouted ""Allahu akbar!"" as they walked outside the building carrying large guns and dressed entirely in black. The magazine staff was in an editorial meeting, around lunchtime in Paris, when the gunmen opened fire. Eleven others were wounded; four of those injuries are serious. + +Witnesses described the gunmen as speaking perfect French. + +Charlie Hebdo has frequently drawn condemnation from Muslims. In 2011, the magazine was firebombed after it ran a cartoon depicting the Prophet Muḥammad. + +The editor in charge of the paper was one of those killed on Wednesday. There was no immediate claim of responsibility, though supporters of militant groups like the Islamic State and al-Qaeda praised the attack online. World leaders condemned it as an attack on freedom of expression. + +Additional reporting by Mashable staff. Have something to add to this story? Share it in the comments.","1" +"The Image That Everyone Is Sharing By 'Banksy' Isn't By Banksy — But It's Awesome","There's an illustration being shared on Facebook, Instagram and Twitter that claims to be a tribute created by street artist Banksy in response to the terrorist attack that killed 12 people near the offices of the French satirical magazine Charlie Hebdo in Paris earlier today. + +While the image does have a touching message, it's almost certainly a fake - not created by Banksy. + +Here's the illustration that everyone is sharing: + +Mashable is reporting that the image was posted by a ""popular 'Banksy' account"" on Instagram. The instagram.com/banksy Instagram isn't run by Banksy at all, and is actually a fan page that shares street art created by a variety of different artists - rarely with any attribution. + +Search on Facebook, Twitter, and Instagram and you'll see plenty of popular accounts that seem to be official Banksy pages. The problem of fake social media accounts is so widespread that Banksy has even posted on his official website to deny he runs any Facebook or Twitter accounts. He does, however, have one Instagram account, which was used during his recent trip to New York. + +Facebook was recently forced to remove the verification checkmark for a Facebook page for a Banksy account with millions of Likes after the artists PR representative denied that he had anything to do with it. + +The Instagram account that the pencil illustration originates from is part of a ring of fake social media profiles. As well as the fake Instagram and Facebook accounts, the administrators behind the Banksy pages also run a YouTube account that re-uploads popular viral videos to capitalize on their popularity. + +Here's an example of a video posted by the fake Banksy YouTube account: + +Another clue that points to the image being fake is its file size. The image uploaded to the fake Banksy social media posts is pixelated and low-resolution. Banksy is an artist who makes a living from exhibiting his work, he wouldn't want his work to be displayed in a way that makes it look bad. + +It's tricky to verify new Banksy work. Because of Banksy's continued anonymity, and the often confusing similarity to other graffiti artists, many works of art end up mistakenly labeled as created by Banksy. A handful of galleries and companies in the UK are, however, experts in his work, meaning that they can verify prints purported to originate from Banksy. + +Nevertheless, given today's tragic events, the sentiment is strong. + +SEE ALSO: ""Vive la France!"": Massive Rallies In Paris After Terrorist Attack","1" +"No, Banksy Didn't Create That 'Charlie Hebdo' Tribute Cartoon, But That Doesn't Mean You Can't Appreciate It","Following the deadly shootings at Charlie Hebdo, a French satirical magazine with a history of lampooning religious extremism, cartoonists came out in droves to support those who were killed Wednesday in the best way they knew how: with their own set of tribute cartoons. Artists from The Independent, The Washington Post, and more published visual depictions of their reaction to the news of the attack, which took the lives of 12 people, a death toll that included four prominent cartoonists. (Charlie Hebdo editor Stephane Charbonnier was perhaps the most high-profile of those killed Wednesday.) And — for those who flocked to Facebook, Instagram, and other forms of social media Wednesday — it appeared that Banksy had dedicated his own cartoon to the tragedy. But, come Wednesday night, fans of the elusive street artist would be disappointed to learn that, no, Banksy likely did not draw the stunning pencil image. + +Though it at first appeared as though the artist was responsible for the cartoon after it surfaced on a Banksy Instagram account, it’s believed that the account does not belong to Banksy himself. Not only because Banksy’s official website insists that the artist keeps off social media — specifically referencing his lack of a Facebook or Twitter account (this short-lived Instagram was the only account that was ever linked to Banksy) — but also, as Business Insider notes, the cartoon image is far too low-res for an artist with Banksy’s notoriety. Writes the site: + +Another clue that points to the image being fake is its file size. The image uploaded to the fake Banksy social media posts is pixelated and low-resolution. Banksy is an artist who makes a living from exhibiting his work, he wouldn’t want his work to be displayed in a way that makes it look bad. +That said, the image itself is striking, and a fitting tribute to those who have passed on following the shootings in Paris. So, though it’s possible Banksy did not design the cartoon (and only leaves you wondering what kind of tribute Banksy would publish), it’s worth digesting, appreciating, and using it to remember that violence will never quell freedom of speech.","1" +"This Powerful Cartoon About The Charlie Hebdo Attack Is Not By Banksy","This post was widely shared over the internet yesterday as being the work of graffiti artist Banksy. + +View on Instagram + +However, it’s by illustrator Lucille Clerc. You can see more of her work here. + +BuzzFeed was also one of several media outlets to mistakenly credit the image to Banksy. A correction has now been issued.","1" +"Did Banksy Post This Poignant Tribute To Paris Shooting Victims? Probably Not","Popular ""Banksy"" social media accounts shared an image of sorrow and hope Wednesday after an attack on the Paris office of the satirical newspaper Charlie Hebdo left 12 people dead. + +The drawing was shared from an Instagram account and Facebook page with a combined following of nearly five million people. + +Both posts carried only the message ""RIP"". + +banksy paris charlie hebdo + +The image quickly went viral, but many have since expressed skepticism about whether Banksy is really behind the image. + +The page the drawing was shared from was initially verified by Facebook, but that verification was removed in early 2014. Banksy's publicist Jo Brooks told Animal New York that the page is ""100 per cent fake"" and the artist's website says Banksy is ""not on Facebook and has never used Twitter."" + +Some have speculated, however, that the denials are all part of cultivating Banksy's puzzling persona. + +The Guardian and Mashable both identified the Instagram post as being authentic, but Mashable later updated its story to reflect doubts about the image's provenance. + +Business Insider points out that @Banksy Instagram account shares work by other artists, often without attribution. In 2013, The New York Times identified a different Instagram account as being linked to the artist. + +Many users on Twitter noticed that similar pictures by different artists were shared before the ""Banksy"" posts. + + +Regardless of whether the real Banksy is behind the drawing, there's no denying it's a powerful image.","1" +"Banksy's illustrated response to the Charlie Hebdo attack isn't by Banksy. But it is striking","The artist posted a poignant image in the wake of the shooting that killed 12 at the offices of the French satirical magazine in Paris yesterday + +Thousands of Banksy fans have shared this strong pictorial response to the terror attack at the offices of French satirical magazine Charlie Hebdo. + +Masked gunmen stormed the offices in Paris, claiming the lives of 12 and leaving five more seriously injured, yesterday. + +Among the dead were four of France’s most celebrated political cartoonists, Jean Cabu, Stephane “Charb” Charbonnier, Bernard “Tignous” Verlhac and Bernard Maris. + +The following image was posted via this Instagram yesterday, which has since been shared by over 100,000 people: + +However, a spokesperson for Banksy told The Independent: ""We can confirm this is not by Banksy."" + +The account is actually one of many fakes (Twitter handles @Banksyofficial and @therealbanksy are also fake) set up in the street artist's name. + +The drawing appears instead to be the work of illustrator Lucille Clerc: + +Break one, thousand will rise #CharlieHebdo #JeSuisCharlie #raiseyourpencilforfreedom pic.twitter.com/3n5fOEmrwJ + +His reaction follows that of Private Eye editor Ian Hislop, who released this statement. + +“Very little seems funny today,” he concluded. + +Gerard Biard, Charlie Hebdo’s editor-in-chief, who was in London at the time of the attack, said: “I don’t understand how people can attack a newspaper with heavy weapons. A newspaper is not a weapon of war.” + +Barack Obama, David Cameron and Angela Merkel have all condemned the “barbaric” killings and vowed to stand up for freedom of expression. + +Seven of the gunmen suspected of being involved in the attack have since been arrested. An 18-year-old accomplice also handed themself in to a police station. + +Charlie Hebdo was firebombed in 2011 after they published a spoof issue “guest edited” by the Prophet Mohamed. + +The magazine has been threatened on numerous occasions for publishing the religious cartoon caricatures.","1" +"A Bogus Banksy","Claim: An illustration created in response to the Charlie Hedbo attack, titled ""Break one, thousand will rise,"" was drawn by graffiti artist Banksy. + +FALSE + +Example: [Collected via Twitter, January 2015] + +Banksy shares simple but beautiful tribute to Charlie Hebdo cartoonists http://t.co/Q7qjsgOKB9 pic.twitter.com/D5PEFmEgtC— HuffPostArts&Culture (@HuffPostArts) January 8, 2015 + +Origins: In the days following the 7 January 2015 terror attack at the headquarters of French satirical magazine Charlie Hedbo in Paris, artists from around the world shared powerful tributes in solidarity with the victims on social media. One of these illustrations, captioned ""Break One, Thousands Will Rise,"" was shared on the @Banksy Instagram page: + +A photo posted by Banksy (@banksy) on Jan 7, 2015 at 3:02pm PST + +The image was shared hundreds of thousands of times on Instagram; and since most viewers first saw the above-displayed artwork on the @Banksy account, many assumed the illustration was created by the infamous graffiti artist. + +The @Banksy Instagram account, however, does not belong to Banksy: it is merely one of many imposter accounts falsely attributed to the mysterious London artist. The ""Break One, Thousands Will Rise"" illustration was actually created by illustrator Lucille Clerc: Break one, thousand will rise #CharlieHebdo #JeSuisCharlie #raiseyourpencilforfreedom pic.twitter.com/3n5fOEmrwJ— Lucille Clerc (@LucilleClerc) January 7, 2015 Clerc, an illustrator based in London, shared her artwork on Facebook , Twitter, and Instagram on 7 January 2015. She also confirmed she created the powerful piece: + +This is irrelevant, I don't want it to turn into polemic and distract people from the real issues. + +There are way more important things to talk about at the moment, and in the end what matters is that this image speaks to people, so the more it spreads the better it is. + +My drawing was a spontaneous reaction, I didn't expect it would have such an echo. Ideas don't break, ideas don't die. Charlie became immortal yesterday and I hope that this terrible day will make us cherish and protect our freedom with even more wit and humour. I can only hope it will inspire people to use their pencils too and that there will be thousands of drawings like this very soon. + + + +","1" +"‘Banksy’ Instagram tribute to Charlie Hebdo victims not posted by artist","A touching tribute to the victims of the Charlie Hebdo shooting posted on an unofficial Banksy Instagram account has been shared more than 100,000 times. + +Many who shared the poignant drawing online believed it was created by the enigmatic street artist. + +However a spokesman for Banksy told the Independent: ""We can confirm this is not by Banksy."" + +The drawing is actually by French illustrator Lucille Clerc, who posted the tribute on her official Twitter page after the shooting, which left 12 dead. + +Several fake Banksy social media accounts have attracted thousands of followers, however the artist has confirmed on his official website that he is not on Facebook or Twitter. + +.embed-container {position: relative; padding-bottom: 120%; height: 0; overflow: hidden;} .embed-container iframe, .embed-container object, .embed-container embed { position: absolute; top: 0; left: 0; width: 100%; height: 100%; } + +Break one, thousand will rise #CharlieHebdo #JeSuisCharlie #raiseyourpencilforfreedom pic.twitter.com/3n5fOEmrwJ— Lucille Clerc (@LucilleClerc) January 7, 2015 + +Break one, thousand will rise #CharlieHebdo #JeSuisCharlie #raiseyourpencilforfreedom pic.twitter.com/3n5fOEmrwJ + +The pencil cartoon being circulated as a Banksy was posted by a Banksy fan account and without credit. It's actually by @LucilleClerc— Liz Buckley (@liz_buckley) January 8, 2015 + +The pencil cartoon being circulated as a Banksy was posted by a Banksy fan account and without credit. It's actually by @LucilleClerc + +Many Instagram users commenting on the post have called for the Banksy Instagram page to credit Ms Clerc and have also shared links to her page. + +#JeSuisCharlie began trending worldwide shortly after the attack, with cartoonists sharing their drawings in solidarity with the victims and in support of free speech. + +Cartoonists show solidarity after #CharlieHebdo attack: http://t.co/8zXyCAeuWB pic.twitter.com/ij29oR0jY3— The Telegraph (@Telegraph) January 8, 2015 + +Cartoonists show solidarity after #CharlieHebdo attack: http://t.co/8zXyCAeuWB pic.twitter.com/ij29oR0jY3","1" +"Detroit Police Issue Statement That The Batmobile Is Safe","Earlier today, the Detroit media reported on rumors that the Batmobile had been stolen from the Batman V. Superman: Dawn of Justice set. It turns out that the rumors were just as absurd as they sounded. + +The ironic part is that the unfounded rumors actually triggered a real police investigation. After receiving inquiries from the Detroit media, the Detroit police department contacted producers of Batman V. Superman: Dawn of Justice to inquire if the Batmobile had indeed been stolen. + +According to the Detroit Free Press, Detroit police spokesman Sgt. Michael Woody issued the statement, “The Batmobile is safe in the Batcave where it belongs.” + +And for those that might claim any type of police cover-up in regards to the theft of the Batmobile, the Detroit Free Press also confirmed with sources close to the production that the Ben Affleck’s ride had not been stolen. + +Batman V. Superman: Dawn of Justice is scheduled to be released in movie theaters on March 25, 2016.","1" +"REPORT: The Batmobile Might Have Been Stolen In Detroit [UPDATE: Nope]","It can't be possible. I refuse to believe it. But there are reports circling that the Batmobile has been stolen from the set of Batman Vs. Superman in Detroit. +Details are scarce and nothing is confirmed. Bleeding Cool, which first reported on the caped crusader's missing machine, reached out to Warner Bros. but the studio hasn't responded. CBS in Detroit has contacted the local police department and they're looking into it. + +Again, this is probably bogus, but if it isn't, keep your eyes peeled for something dark, menacing, and with freaking machine guns on its nose. + +UPDATE 8:53 PM ET: The Freep has been in contact with Detroit police who confirmed that it the Batmobile has not been stolen. ""The Batmobile is safe in the Batcave where it belongs,"" says Sgt. Michael Woody. Moving on...","1" +"Zack Snyder Makes Fun of Stolen Batmobile Rumor with New Image","In case you hadn’t heard, a little movie called Batman v Superman: Dawn of Justice is currently filming in and around Detroit, MI. Since we live in the Golden Age of social media networking, set pictures and videos have fueled all kinds of speculation on what’s going on in this movie, from Ben Affleck’s shoulder injury to Jesse Eisenberg’s hair to Scoot McNairy’s legs. +The most recent set leaks revolved around Batman’s ride. Instagram users posted several pictures of the new, updated Batmobile, which was promptly followed by an official photo released by director Zack Snyder. The exciting design appears to be something of a hybrid between the tank-like vehicle used in Christopher Nolan’s Bat-films and more traditional, hot rod-inspired Batmobiles of old. + +Meanwhile, outlets like Bleeding Cool reported a rumor that one of the Batmobiles from the movie’s set had been stolen. The rumor was picked up by some of the mainstream media (such as the local Detroit CBS affiliate) before being debunked by the Detroit Free Press. + +In response, director Zack Snyder took to Twitter (as he does) to send up not only the stolen-Batmobile rumor, but to reference a competing franchise. Snyder tweeted the following picture: +Is Snyder taking a sly, friendly dig at J.J. Abrams and the currently-filming Star Wars: Episode VII? It would seem so, but what if Snyder had used, say, a Joker or Two-Face lookalike – or at least one of their henchmen? The internet would’ve imploded. This way, Snyder provides fans with a harmless bit of franchise-crossover in the form of this officially-sanctioned bit of fan-fiction. The attention to detail is pretty funny, too – the way the Gotham PD cop nearest the Batmobile is looking at the Stormtrooper’s blaster is priceless. + +Make no mistake, Zack Snyder is following the online fan chatter. He’s not above calling in to a Detroit radio show to defend Aquaman’s badassery and, apparently, will comment on your Instagram video when the mood takes him. + +CBM caught Snyder’s now-deleted comment - “Watching you” - on the following video taken by IG user @danielblane, who was home one night while the Batmobile did burnouts on the neighboring Batman v Superman set: +Snyder, whose Instagram handle is @cruelfilms, has removed his comment, but judging by the reaction of the video’s other commenters, the fact that Snyder has weighed in at all delights them to no end. + +The fact that the director takes the time to interact with his fans is genuinely heartening for audience members who may have questioned the decision to hand Snyder not just an all-new Superman and Batman, but Warner Bros. and DC’s own interconnected movie universe. + +The leaked BvS set pictures and videos still don’t answer any of the bigger questions about the film’s plot and whether or not it will be able to seamlessly integrate multiple superheroes while giving us a satisfying first-time team-up of the World’s Finest, but that won’t stop us from poring over every image from Detroit that we can get our hands on. + +Batman v Superman: Dawn of Justice will open in theaters on March 25, 2016. + +Source: Instagram, Zack Snyder, Bleeding Cool","1" +"At CBS Detroit, Fan Site 'Scuttlebutt' Is Enough to Report False Batmobile Theft","Update: Saturday, 12:15 a.m.: Detroit Police say the Batmobile film vehicle was not stolen, the Detroit Free Press reports. +Friday evening article: + +Holy crap, Batman -- look what happened to a a once-distinguished news organization. + +The CBS Detroit broadcast group's website posts a 10-paragraph article, if that's the right word, about something that may or may not have happened: + +A website is reporting that the Batmobile, from the upcoming Batman v. Superman flick, has gone missing in Detroit and is presumed stolen. + +Sounds serious and dramatic. And yet no other local media outlet has a word about it. + +Further reading suggests why. + +""Presumed stolen"" refers to a presumption by the anonymous writer of a four-sentence post by Rich Johnston at Bleeding Cool, an Illinois site for comic book fans. Its brief item begins: + +The scuttlebutt from sources in Detroit is that one of the Batmobile models being used in the filming of Batman Vs. Superman has gone missing, believed stolen. + +That site adds: ""Warner Bros representatives did not respond to inquiries."" + + +This spectator shot of one Batmobile in Detroit was postedthis week at the website cosmicbooknews.com. +The CBS Detroit writer, Evan Jankens, also makes a nod to verification: + +Our brother station WWJ put a call into the Detroit Police Department to see if there is any truth to this. (Update! As of 4 p.m., police were saying they hadn’t heard about this, but were looking into it). + +Members of the broadcast group are WWJ-TV (Channel 62), WWJ Newsradio 950 and two sports radio stations. + +Absent any confirmation, Jankens riffs speculatively on the notion of a possible Batmobile-jacking: + +If this is true I could only imagine seeing it driving down 696 in rush hour. +Seriously, how the heck could someone steal this car? . . . No, it’s the BATMOBILE! It has machine guns in the front. +Does this person — if the rumor is true (we don’t know how credible the source is) — think that he or she can just go cruising around in this car no one will notice? +Hey, we like Friday afternoon playfulness as much as the next keyboard jockey, but stay on the other side of publishing a story from someone else's anonymous source that requires disclaimers such as ""if the rumor is true"" and ""we don't know how credible the source is."" + +That wouldn't slide past a high school student publication adviser and it seems like a disservice to readers of CBS Detroit, which didn't share the wispy piece on its Facebook pages and presumably not on its newscasts. + +The contrasting tweets below show two approaches to the Bleeding Cool short. The first was sent by CBS Detroit's writer to the film director after publication, while the second was posted instead of a preliminary article. + +.@ZackSnyder did the Batmobile get stolen? http://t.co/zz07zWOxh9 + +— Evan Jankens (@KINGoftheKC) September 12, 2014 +Craziest question I've asked Detroit police in a long time: Did someone steal the Batmobile? Awaiting response. + +— Motor City Muckraker (@MCmuckraker) September 12, 2014","1" +"Batmobile stolen in Detroit? Good one, joker!","Holy Motor City gossip! The rumored theft of the Batmobile in Detroit appears to be a false alarm. + +Detroit police spokesman Sgt. Michael Woody said that police confirmed with producers of “Batman v. Superman: Dawn of Justice” that the vehicle has not been stolen, a rumor that proliferated on the web and social media on Friday. + +“The Batmobile is safe in the Batcave where it belongs,” Woody said. + +Sources close to the production being filmed in metro Detroit also said it wasn’t true that the Caped Crusader’s ride had been stolen. + +Buzz about the supposed theft swirled Friday when at least one comic book website reported on the “scuttlebutt” that one of the Batmobile models had disappeared and was presumed stolen. + +The rumor was greeted and retweeted with smirking skepticism by some — and insert-your-own-Detroit-joke comments by others. + +The Warner Bros. production has been working hard to keep its activities under wraps while filming in and around Detroit. But that’s not always easy when the cast and crew leaves the relative lockdown of the film’s headquarters at Pontiac’s Michigan Motion Picture Studios. + +Unauthorized photos of the Batmobile have been hitting the Web this week – an unwelcome reality for studios in a world where everyone with a smartphone is a potential paparazzi. Director Zack Snyder also tweeted an official photo. + +“Batman v. Superman” stars Ben Affleck and Henry Cavill. It is scheduled to reach theaters on March 25, 2016.","1" +"Zack Snyder’s ‘Batman V Superman: Dawn Of Justice’ Stolen Batmobile Rumor Put To Rest","Over the weekend there was a rumor flying around that someone actually stole the Batmobile off the set of Batman V Superman: Dawn of Justice. How cold something the big and bulky get stolen off a secure set, but stay hidden away in a major city like Detroit? While I may not know the insurance coverage for this, it seems that the stolen Batmobile was nothing more than a publicity stunt. And to add some more fun to this, director Zack Snyder tweeted a photo of the culprit. Hint: Snyder is currently in a twitter war with this movie. Hit the jump to check it out. +So there you have it, it was nothing more than a publicity stunt created by social media. It also a great way to market both films, but more importantly we get to see more of the Batmobile. +Now it’s Bad Robot or Disney’s move. The rivalry all started back last July when Snyder tweeted a shot of Superman (Henry Cavill) donning a Sith robe while wielding a red lightsaber. The director added the #superjedi to rub some salt on the wound. +Of course then Bad Robot responded with the following tweet. They even called out the Batman V Superman: Dawn Of Justice director with “The C3Ped Crusader“:","1" +"Zack Snyder Kills ""Stolen Batmobile"" Rumor With Great Photo","On Friday, a rumor cropped up that one of the new Batmobile vehicles had been stolen in Detroit. The story wasn’t verified, but it did end up at a couple bigger news outlets. Because who can resist the phrase “stolen Batmobile”? Thankfully it was all just a rumor, but the story did give Batman v Superman director Zack Snyder a reason to pull together some of the minor resources at his disposal for a great photo op. + +Bleeding Cool had the original rumor, and also hilariously scolded CBS for picking up the story. In an update, the site even praised the Detroit Free Press for killing the story BC created in the first place. The DFP reports: + +Detroit police spokesman Sgt. Michael Woody said that police confirmed with producers of “Batman v. Superman: Dawn of Justice” that the vehicle has not been stolen, a rumor that proliferated on the web and social media on Friday. + +“The Batmobile is safe in the Batcave where it belongs,” Woody said. + +So the Batmobile isn’t stolen; it hasn’t even lost a wheel. All is right in the world, except for the fact that Bats and Supes are fighting again. + +All of which brings us to Zack Snyder’s most recent tweet. +This is the latest in a set of back and forth tweets between Snyder and Bad Robot that play around with the DC and Star Wars characters. A couple more are below.","1" +"Zack Snyder Responds to Fake Stolen Batmobile Report","A recent report from Cosmic Book News stated that the recently revealed Batmobile had been stolen from the Detroit set of ""Batman v. Superman: Dawn of Justice."" + +Not suprisingly, the story turned out to be completely fake. This is also the same site that posted the fake news story earlier this year that ""Breaking Bad"" actor Bryan Cranston had been confirmed in the role of Lex Luthor. + +In response to the fake article and seeing an opporunity for another crossover image between his film and J.J. Abrams' ""Star Wars"" movie, director Zack Snyder has posted the following mash-up of the new Batmobile and a Stormtrooper from ""Star Wars"" being arrested by Gotham City cops for stealing the vehicle:","1" +"BATMOBILE NOT STOLEN, MTV CONTEST PRIZE REMAINS UNCLAIMED","Source: Detroit Free Press + +Yesterday, we reported on a rumor from Bleeding Cool that someone in Detroit had stolen one of the Batmobiles being used for filming in the city. The rumor took off all over the web, even making its way to Detroit's local CBS affliate. Our article did pretty well, probably because we found that sweet MTV contest video from 1989, showing this plot has been in motion for twenty-five years. + +But there's just one problem... it didn't happen. The Detroit Free press checked with police spokesman Michael Woody, who said, ""The Batmobile is safe in the Batcave where it belongs."" He then exited the room and promptly removed a rubber mask, revealing himself to be The Joker in disguise, and laughed maniacally.","1" +"Batmobile wasn't stolen: Cops","Rumours that the Caped Crusader's ride has been stolen have been greatly exaggerated. + +On Friday, bleedingcool.com said, ""The scuttlebutt from sources in Detroit is that one of the Batmobile models being used in the filming of Batman Vs. Superman has gone missing, believed stolen."" + +Not surprisingly, the Internet went into a tizzy, but later that day, Detroit police said the theft was a rumour. + +Sgt. Michael Woody told the Detroit Free Press that police confirmed with producers of Batman v. Superman: Dawn of Justice that the vehicle has not been stolen. + +“The Batmobile is safe in the Batcave where it belongs,” Woody said. + +The paper also said that sources close to the movie being filmed in D-Town also said the fly ride had not been stolen. + +Unauthorized photos of the Batmobile appeared online this week, and director Zack Snyder tweeted an official photo on Wednesday. + +Batman v. Superman stars Ben Affleck and Henry Cavill, and is scheduled to open in theatres in 2016.","1" +"Boston.com retracts claim about racist email from professor","The tale of the Harvard Business School professor who flipped out because he’d been overcharged $4 by a Chinese restaurant took an ugly turn Wednesday night. The Boston Globe’s free Boston.com site, which first reported the story, posted a follow-up claiming that Ben Edelman had sent a racist email to the restaurant owner — and then replaced the follow-up with an “Editor’s Note,” explaining that the authenticity of the email couldn’t be verified. The Boston Herald has a summary of what went wrong. + +The original story about Edelman, by Boston.com’s Hilary Sargent, had gone viral. Who, after all, can resist reading about a privileged Harvard professor threatening legal action against a hard-working business owner because the prices on his website hadn’t been updated for a while? So when Boston.com retracted its explosive allegation (carrying Sargent and Roberto Scalese’s bylines) that Edelman was not just a contentious jerk but a racist, Twitter exploded. + + +So what did Boston.com publish? It wasn’t long before screen grabs started to make their way around the intertubes. J. Alain Ferry posted a copy here. What happened was that after Edelman apologized to Ran Duan, whose family owns the Sichuan Garden restaurant in Brookline, someone claiming to be Edelman sent another email to the restaurant owner, writing, “You may have won the battle Duan, but at least we can agree your menu is a little less slanty-eyed.” That’s followed up by an apology for accidentally sending what was meant as a private joke, which has the effect of making the mail seem more authentic. + +Edelman’s domain name, benedelman.org, is easily found on the Web, and it’s not difficult to send an email using any address you like. The Sichuan Garden website offers an email form that lets you do exactly that. One clue is that all of the legitimate emails Boston.com has posted from Edelman are marked as coming from “Ben Edelman,” whereas the racist email and subsequent apology were from “ben@benedelman.org.” + +Despite the retraction, Boston.com as of this moment is still all-in on the rest of its Edelman package. We’ll see what, if anything, comes next.","1" +"The Washington Post Is Now Free On Amazon Kindles","The Washington Post is available as a free app in Amazon Kindle Fire tablets.","1" +"Jeff Bezos Is Planning To Make The Washington Post Pre-Loaded On Every Kindle HDX","Amazon founder and CEO Jeff Bezos has a plan to boost the readership of The Washington Post, which he bought last year for $250 million. + +Amazon's newest line of high-end Kindle Fire HDX tablets will come pre-installed with an app curating Post news and photography, Brad Stone reports for Bloomberg. + +The app will be free, at least at first, and will also be available to download on other devices, though with a monthly subscription fee. + +The effort is reportedly called ""Project Rainbow"" internally, and marks Bezos' first move to create ties between the newspaper and Amazon. + +The initiative is being led by the former editor in chief of Salon, Kerry Lauerman, who was one of many new hires brought on since Bezos took charge. + +As Stone points out, this move would not only get the Post to more readers, but also potentially make the Kindle Fire HDX tablet more attractive to buyers. Amazon has made a huge bet on original content, like television shows and video games, to add value to its devices through its subscription service, Amazon Prime, and adding Washington Post's news could align with those efforts. + +Disclosure: Jeff Bezos is an investor in Business Insider through his personal investment company Bezos Expeditions. + +SEE ALSO: This Amazing Twitter Account Curates The Most Hilarious And Cringe-Worthy Movie Reviews On Amazon","1" +"Beast-eater, frightened phone signal, threw the victim and rend in the taiga","Reports of more attacks in Yakutia bears on people 53-year-old Igor Nerungri Vorozhbitsyn ignored, they say, for his life more than once met nose to nose with clumsy and all circuits. So as usual without fear went fishing in the nearby Aldan region. From the road, a man went to the creek to winter quarters where usually stayed fishing. Weapons of a knife on his belt in his hands - rods, behind - the backpack. +To rain at times forced to throw a tight long cloak. A few kilometers left on the old highway. Pereobulsya, Bolotnikov tied to a backpack and walked toward the key Evota to zymes. +Coming in a somewhat macabre silence about three hundred meters, clearly felt that the rear - risk. At the same moment a powerful blow to the backpack knocked him down. Falling, he saw a couple of meters of a huge bear. +Igor himself considerable size, weight under one hundred pounds. But pounce beast with incredible force began to throw it as a toy. Poor fisherman tried to pull a knife, but the bitten hand predator is not obeyed, hanging whip. +What happened next, other than a miracle not to name. Bear attacks in the final chord in the chest and grabbed at the moment mobile fisherman made a sound. +- In the taiga time looked - it was 8:30 pm and put a mobile phone in his breast pocket - recalls that terrible battle Vorozhbitsyn. - I have an older model. Push the first button and the machine tells you how many times. When the bear sank his teeth into my chest and bit this button. ""Eight forty. Forty eight ... ""- said in a metallic voice my machine. Beast scared and ran away. +Still not really understanding what had happened, and waiting for a new attack, Igor few minutes lying on the ground. Everything is quiet. Rose. Oh, the horror! Bear almost took the scalp and the skin on the left side of the face, left deep lacerations on his stomach and chest, broke a vein in his right hand - there was gushing blood. How could, hand tied it with rags, but blood continued to ooze. Wounded and bleeding, being careful of the new bear attack, he moved for some reason in the opposite direction from winter quarters and soon completely lost. Night fell on the taiga. Escaping from the rain, cover the broken beast cloak. Very sick and dizzy. Somehow I pulled out his match. Tried to start a fire, but fingers did not obey. Suddenly spurted from the wound and the blood flooded matches. +Spent the night under a tree, listening to every rustle. At dawn, he went on. When the forces finally left, lay down on the ground and crawled. Sometimes got up and staggered moved on. When before the next overnight lay down to rest, suddenly, not believing himself felt the smoke of a fire ... +Two fishermen from Neryungri standing camp here, just picked up on the hands of out-of-darkness bloody Igor. Without delay, immediately put the wounded man in the car and rushed to the nearest village Khatymov. From there, the ambulance - Neryungri. Four hours of operation, and three surgeons literally collected on parched face bloodied pieces Igor. Then - three operations already in the Republican Hospital in Yakutsk. Fortunately, the fisherman left eye was saved. Igor saved and that the first shot hit on the head is not (bear paw easily cut out the skull), and a backpack. Played a protective role and dense coat. Bear claws and teeth left serious wounds on his stomach and chest fisherman. But by a happy coincidence did not touch the internal organs and even ribs broken. And if not for mobile ... + + Bear claws and teeth left serious wounds on his stomach and chest fisherman. +While doctors saved Igor Vorozhbitsyna hunters looking for a bear attacked him. Evoty literally combed the neighborhood with dogs. And on July 26 shot clumsy 2-3 years old. However, within a few kilometers hunters found more traces of bears. So what killed a man-eating beast or not, no one really can not tell.","1" +"Рыбака от медведя спас мобильник","Сообщения об участившихся в Якутии нападениях медведей на людей 53-летний житель Нерюнгри Игорь Ворожбицын проигнорировал, мол, за свою жизнь не раз встречался нос к носу с косолапыми и все обходилось. Поэтому как обычно без опаски отправился на рыбалку в соседний Алданский район. От дороги мужчина пошел по ручью, к зимовью, где обычно останавливался на рыбалку. Из оружия только нож на поясе, в руках – удочки, за спиной – рюкзак. + +Временами накрапывающий дождь заставил набросить плотный длинный плащ. Через несколько километров вышел на старую автомобильную дорогу. Переобулся, привязал болотники к рюкзаку и пошел в сторону ключа Эвота, к зимовью. + +Пройдя в какой-то жутковатой полной тишине метров триста, ясно почувствовал, что сзади - опасность. В ту же секунду мощный удар по рюкзаку сбил его с ног. Падая, увидел в паре метров огромного медведя. + +Игорь и сам немалых размеров, вес под сто килограммов. Но набросившийся зверь с неимоверной силой начал бросать его как игрушку. Бедный рыбак попытался вытащить нож, но прокушенная хищником рука абсолютно не слушалась, болталась плетью. + +То, что случилось дальше, иначе как чудом не назвать. Медведь в финальном аккорде нападения вцепился в грудь и в этот момент мобильник рыбака издал звук. + +- В тайге посмотрел время – было 8.30 вечера, и положил мобильник в нагрудный карман, - вспоминает ту жуткую схватку Ворожбицын. - У меня старая модель. Нажимаешь первую кнопку, и аппарат говорит, сколько времени. Когда медведь вцепился зубами мне в грудь и прикусил эту кнопку. «Восемь сорок. Восемь сорок...», - сказал металлическим голосом мой аппарат. Зверь испугался и убежал. + +Еще толком не понимая, что произошло, и ожидая нового нападения, Игорь несколько минут лежал на земле. Все тихо. Поднялся. О, ужас! Медведь практически снял скальп и кожу с левой стороны лица, оставил глубокие рваные раны на животе и груди, порвал вену на правой руке - оттуда хлестала кровь. Как смог, перетянул руку тряпками, но кровь продолжала сочиться. Израненный, окровавленный, остерегаясь нового нападения медведя, он двинулся почему-то в обратную сторону от зимовья и вскоре окончательно заблудился. На тайгу опускалась ночь. Спасаясь от дождя, прикрывался разорванным зверем плащом. Сильно болела и кружилась голова. Кое-как достал из кармана спички. Попытался разжечь костер, но пальцы не слушались. Из раны вдруг брызнула кровь и залила спички. + +Ночь провел под деревом, прислушиваясь к каждому шороху. Когда рассвело, пошел дальше. Когда силы окончательно покидали, ложился на землю и полз. Иногда вставал и, шатаясь, шел дальше. Когда перед очередным ночлегом прилег отдохнуть, вдруг, не веря себе, почувствовал дым костра... + +Два рыбака из Нерюнгри, стоявшие здесь лагерем, буквально подхватили на руки вышедшего из тьмы окровавленного Игоря. Не мешкая, мужчины немедленно посадили раненого в машину и помчались в ближайшее село Хатымь. Оттуда, на скорой – в Нерюнгри. Четыре часа операции, и трое хирургов буквально собрали по запекшимся окровавленным кусочкам лицо Игоря. Потом – еще три операции, уже в республиканской больнице в Якутске. К счастью, левый глаз рыбака удалось сохранить. Игоря спасло и то, что первый удар пришелся не на голову (медведь лапой без труда раскраивает череп), а по рюкзаку. Сыграл свою защитную роль и плотный плащ. Медвежьи когти и зубы оставили серьезные раны на животе и груди рыбака. Но по счастливому стечению обстоятельств не задели внутренние органы и даже не переломали ребра. И если бы не мобильник... + +Пока медики спасали Игоря Ворожбицына, охотники искали напавшего на него медведя. Окрестности Эвоты буквально прочесали с собаками. И 26 июля застрелили косолапого 2-3 лет отроду. Однако в радиусе нескольких километров охотники нашли еще следы медведей. Так что убили зверя-людоеда или нет, никто точно сказать не может.","1" +"Bear attack foiled by Justin Bieber’s music: A story too good to check","Just after 12 pm on Tuesday, a story started picking up some serious online momentum. + +In the span of about an hour, it appeared on the websites of The Week, Elite Daily, the Daily Mirror, the New York Post, Mediaite, an ABC affiliate, among others. + +Here’s how the New York Post’s story began: + +Even bears can’t stand Justin Bieber’s music. +A fisherman in Russia was being attacked by a brown bear and escaped death when his Justin Bieber ringtone went off and sent the beast fleeing into the forest. +Animals? Check. A strange and amazing turn of events? Check. Justin Bieber angle when he’s already in the news for a run-in with Orlando Bloom? Check. + +Too good to check? Check. + +But next thing you know, NPR’s “Morning Edition” covers it, and it ends up in a Seth Meyers monologue: + +Here’s the issue: the first story of the bear attack was published in Russian language publication Pravda back on July 31 — and it says nothing about Justin Bieber. + +At some point in making the leap to English, someone added a detail to the story that transformed it into a viral hit. According to Google Translate, the original Russian version said the bear was scared away when Igor Vorozhbitsyn’s phone began speaking out the current time. So, yes, the phone apparently scared off the bear mid-mauling. But no Bieber. + +Did Vorozhbitsyn change his story in a subsequent interview and realize it was Bieber all along? + +Or did someone insert a seemingly false Justin Bieber angle into the story? + +Point of Bieberfication + +The bear-and-Bieber stories all carried the same pictures of Vorozhbitsyn. They had the same quotes of him explaining that his granddaughter had put the ringtone on his phone. + +They quote the same “wildlife expert”: “Sometimes a sharp shock can stop an angry bear in its tracks and that ringtone would be a very unexpected sound for a bear.” + +Hey, thanks for that too-perfect quote to round out the story, anonymous wildlife expert with no credentials! + +The symmetry in the stories is because they all used the information contained in a single English language report from a site called the Austrian Times. It’s led by a Brit named Michael Leidig, who also owns the Central European News agency. (His name is listed in the domain owership records for the sites, as well as for CEN’s affiliate agency, EuroPics.) + +After the Austrian Times/CEN published the story, it spread to MailOnline. + +Once MailOnline had it, the story was off and running. Bieber and the bear was the real deal, and everyone wanted to plant a flag on it. As of this writing, MailOnline’s story has racked up over 13,000 shares. + +The images are the first clue as to where the story really came from. MailOnline cited CEN as the copyright holder of the image it used. But the Austrian Times story credits Pravda with the image on its story. A search on the Pravda website turned up the original article with its images and Bieber-less reporting. + +So how did the Austrian Times learn of the Bieber angle that Pravda apparently missed? + +No answer from Austrian Times/CEN/EuroPics + +I called the offices of the Austrian Times and first asked to speak with David Rogers, who is the only person listed on the site. (He is both its ombudsman and its primary sales contact.) + +I spoke with a woman who said Rogers was not in the office. When I asked about the story, she said she would follow up with their office in Russia to get the details and would call me back. I asked if their office there typically rewrites things from wires and local press. + +“A lot of stories are found on the wire or in local media but also from local interviews on the ground, or we speak to the reporters who wrote them; we speak to police to get things confirmed,” she said. + +I called her again later that day to ask if she had news from the Russian office, and she said they are often hard to get ahold of. She never got back to me. + +I also called and emailed Leidig, owner of both the Austrian Times, CEN and EuroPics. A man who answered the phone at the CEN office said Leidig is on vacation in Romania. + +Leidig, who has lived in Austria for some time, says nothing about himself on the CEN or Times websites, but he has an extensive Wikipedia page. In the section about CEN, it lists MailOnline as one of its clients, though that and much of the page itself offers no citation for the claim. (In 2013, Leidig self-published a book about Ponzi schemer Bernie Madoff.) + +Along with detailing Leidig’s journalistic achievements, the Wikipedia page includes this passage: + +Leidig is also a campaigner for greater support for journalism which he describes as the “coalface of democracy.” He has campaigned in favour of more responsibility from search engines like Google to give credit to original source material and also for payment for originators of news, arguing that if the journalists all go out of business nobody will provide the content worth having. +The sole link in that passage goes to… an article on the Austrian Times. Still, one would hope Pravda is therefore earning some revenue from the story and images that CEN and the Austrian Times plucked from its site. (I contacted Pravda to ask about the images and the story, but have not yet heard back.) + +For their part, the Austrian Times, CEN and EuroPics have stopped talking to me. After receiving no information from their Russian bureau, I sent a detailed email Thursday with questions about the Bieber version of the Pravda story and its use — and possible resale — of Pravda images. No has replied or returned my calls. + +Meanwhile, the irresistibly Bieberfied version of the story continues to spread. Entertainment websites and news organizations give it the quick rewrite treatment and link to each other’s versions, completely obscuring the dubious origins of the story. + +Too good to check, and now, I suspect, too entrenched to ever be really corrected.","1" +"Sugarhill Gang rapper Big Bank Hank dead at 57","(CNN) -- A member of the Sugarhill Gang, whose pioneering hit ""Rapper's Delight"" brought hip hop to mainstream audiences 35 years ago, died Tuesday of complications from cancer. +""Big Bank Hank,"" whose real name was Henry Jackson, died early Tuesday in Englewood, New Jersey, according to David Mallie, who manages the two surviving Sugarhill Gang members. The New York native was 57. +A beefy, boisterous presence onstage, Hank handled vocals in the early to middle portion of ""Rapper's Delight,"" which despite its extended length -- one version was more than 14 minutes long -- became the first rap song to reach the Top 40 on the U.S. Billboard charts. +Jackson traded rhymes with bandmates ""Wonder Mike"" Wright and Guy ""Master Gee"" O'Brien and spoke some of the song's catchiest lines, including ""Ho-tel, mo-tel, Holiday Inn/If your girl starts acting up, then you take her friend."" +Wonder Mike and Master Gee issued a statement Tuesday: +""So sad to hear about our brother's passing. The 3 of us created musical history together with the release of Rapper's Delight. We will always remember traveling the world together and rocking the house. Rest in peace Big Bank."" +The three friends were unknown MCs when producer Sylvia Robinson recruited them to record the song for her rap label, Sugar Hill Records. + +Released in fall 1979, ""Rapper's Delight"" became a novelty hit and a staple at dance clubs well into 1980. It was born from the emerging New York hip-hop scene of the late '70s, in which young rappers gathered in clubs and exchanged rhymes over instrumental breaks from popular songs, most notably Chic's hit ""Good Times."" +""Rapper's Delight"" also borrowed its bass line and other flourishes from ""Good Times,"" prompting threats of legal action by Chic co-founders Nile Rodgers and Bernard Edwards. After a settlement, Rodgers and Edwards were listed as co-writers of the song. +""It felt like a new art form,"" Rodgers said later of ""Rapper's Delight."" +In 2011, Rolling Stone ranked ""Rapper's Delight"" at No. 248 on its list of the 500 Greatest Songs of All Time. +People we've lost in 2014","1" +"Big Bank Hank, US rapper and Sugarhill Gang founder member, dies at 57","Big Bank Hank, the New York rapper who, as part of the Sugarhill Gang, released what is generally regarded as the first rap record, has died at the age of 57. + +The performer, real name Henry Jackson, died from kidney complications due to cancer, according to reports. + +Jackson formed the Sugarhill Gang with Master Gee and Wonder Mic, having a big hit in 1979 with Rapper's Delight. + +The record sold several million copies worldwide and helped establish rap as the genre it is today. + +The full version of Rapper's Delight ran nearly 16 minutes long and was recorded in a single take. + +The song - famous for its ""hip, hip, a hop"" refrain - featured 'Big Bank' introducing himself as ""six foot one and tons of fun"". + +The trio continued to perform together and spent three weeks in the UK singles chart in 1982 with The Lover In You. + +Jackson's death was reported by website TMZ and confirmed to Fox News by David Mallie, who manages the two remaining band members. + +""So sad to hear of our brother's passing,"" said Wonder Mike and Master Gee in a statement. ""Rest in peace Big Bank.""","1" +"Sugarhill Gang rapper Big Bank Hank dies at age 57","Sugarhill Gang founder Henry 'Big Bank Hank' Jackson has died at age 57 from kidney complications due to cancer. + +The rapper was a founding member or Sugarhill Gang, which produced the first mainstream rap hit Rapper's Delight in 1979. + +The manager for the group David Mallie confirmed the musician's untimely passing with Fox News. + +Untimely: Sugarhill Gang founder Henry 'Big Bank Hank' Jackson has died at age 57 from kidney complications due to cancer. pictured with Master Gee (L) and Wonder Mike (far right) in New York City in 2005 + +'[Wonder Mike and Master Gee] had been in contact with him in the past year,' Sugarhill's rep told FOX411. 'They had some great times and created history.' + +Wonder Mike and Master Gee released a statement, communicating their condolences: 'So sad to hear of our brother's passing. Rest in peace Big Bank.' + +History: The rapper was a founding member or Sugarhill Gang, which produced the first mainstream rap hit Rapper's Delight in 1979 + +Henry was born in the Bronx and later graduated from the local community college with an associates degree in oceanography. + +Unable to find a job in his chosen field of oceanography, he began working at a pizza restaurant. + +Soon after he was discovered by music manager Sylvia Robinson after she heard him rapping. + +Stars: Sugarhill's only hit in the US was Rapper's Delight, but they did manage to score a few more chart toppers in Europe + +His turn: Big Bank Hank was known for his competition with Superman for the love of Lois Lane + +Sylvia soon formed Sugarhill Gang with Henry as a member of the group with the moniker Big Bank Hank. + +Sugarhill's only hit in the US was Rapper's Delight, but they did manage to score a few more chart toppers in Europe.","1" +"Sugarhill Gang co-founder Big Bank Hank dies","Sugarhill Gang's Henry 'Big Bank Hank' Jackson has died at the age of 57, confirms David Mallie, who manages the group's two remaining living members. + +Mallie said Jackson died from kidney complications due to cancer. + +“[Wonder Mike and Master Gee] had been in contact with him in the past year,"" Mallie told FOX411. ""They had some great times and created history.” + +The former band members also expressed their condolences. + +""So sad to hear of our brother's passing. Rest in peace Big Bank,"" they said. + +The Sugarhill Gang popularized rap music with the hit single ""Rapper's Delight"" in 1979. + +“Once I step out that door into the entertainment arena, we get crazy love everywhere we go,” Wonder Mike told FOX411 in 2013. “Like one of the Soul Train Awards years ago, Denzel Washington was in the audience, Danny Glover, Jay Z and Beyonce were doing the lyrics, and all of these people are saying the words right back to me.” + +Diana Falzone is a FoxNews.com reporter. You can follow her on Twitter @dianafalzone.","1" +"Sugarhill Gang's Big Bank Hank Dead At 57","Henry Jackson, better known as Big Bank Hank of the Sugarhill Gang, died early Tuesday morning at Englewood Hospital in New Jersey from complications due to cancer. The news -- first reported by TMZ -- was confirmed to HuffPost Entertainment by David Mallie, business manager for Sugarhill Gang members Michael ""Wonder Mike"" Wright and Guy ""Master Gee"" O'Brien. Jackson was 57 years old. + +In a statement to HuffPost Entertainment via Mallie, Wright and O'Brien expressed sorrow and condolences: ""So sad to hear of our brother's passing. The three of us created musical history together with the release of 'Rapper's Delight.' We will always remember traveling the world together and rocking the house. Rest in peace Big Bank."" + +The Sugarhill gang formed in the late '70s and was best-known for the 1979 hit single, ""Rapper's Delight."" + +DJ Funkmaster Flex was among the many people to pay tribute to Jackson: + +Rest in peace... Big Bank Hank... Hip hop pioneer dies of Cancer .... Legend... Sugarhill gang August 5th-1957 / Nov11th-2014 ..... InFlexWeTrust.Com + +A photo posted by DjFunkFlex (@djfunkflex) on Nov 11, 2014 at 6:01am PST","1" +"Big Bank Hank, co-founder of the Sugarhill Gang, has died","His voice served as a call to action, an echo that continues today whenever a kid bellows the word “hip hop” into a microphone. It was in Henry “Big Bank Hank” Jackson’s lyrical wobble, the way he rapped through the Sugarhill Gang’s “Rapper’s Delight,” the singular hit that propelled a movement when it was released in 1979. + +Jackson, 57, died Tuesday morning after complications from cancer, but his influence remains. + +The news was confirmed by David Mallie, the business manager for the two surviving members of the original Sugarhill Gang, Guy “Master Gee” O’Brien and “Wonder Mike” Wright. + +Hank was introducing a flow that in the decades to come would move through culture one boasted rhyme at a time. +- +“They say that miracles never cease, I’ve created a devastating masterpiece,” rapped Big Bank Hank on “Rapper’s Delight,” a boast that codified one of rap’s central themes -- self-aggrandizement. Little did he know at the time how accurate he was, and that through said devastation Hank was introducing a flow that in the decades to come would move through culture one boasted rhyme at a time. + +lRelated Notable deaths of 2014 +OBITUARIES +Notable deaths of 2014 +SEE ALL RELATED +8 + +As seen on a widely circulating YouTube clip in performance on a local dance show, Big Bank Hank performs with a violet Kangol-style hat and a too-tight T-shirt. The hearty emcee grooves as he rhymes (lip-synced though it may be), lost in music with a fluid pelvic wobble. Next to the more restrained Wonder Mike and Master Gee, he is rap-funk personified. Hank embodies his verse as he raps of out-lasting Superman with a funny line belittling the superhero’s manhood. It's no match for Hank’s “super sperm.” + +“I’m here, I’m there, I’m Big Bank Hank, everywhere,” he raps. Again, he had no idea how true that was, though he witnessed the music's evolution over the following decades as the hip-hop style he helped popularize become a form as vital to the ever-evolving story of American music as jazz and country and western. + +Related: 'Big Bank Hank' of trailblazing Sugarhill Gang dies at 57 +Related: 'Big Bank Hank' of trailblazing Sugarhill Gang dies at 57 +Christine Mai-Duc +This line, from the same verse, part of a larger bit involving a sexy reporter, further underscores his import: “She said she’s heard stories and she’s heard fables/That I’m vicious on the mike and the turntables.” That little turn of phrase carved into wax rap’s ongoing love-affair with turntables and microphones. + +In the formative “Apache,” the Gang harnessed the titular brass and bongo breakbeat while they shouted, “Tonto, jump on it! Kemosabe, jump on it!” Big Bank Hank then made another claim: “I’m the one who shot Jesse James!” + +cComments +Got something to say? Start the conversation and be the first to comment. +ADD A COMMENT +0 + +To call the Sugarhill Gang the “big bang” of hip-hop diminishes the contributions of an entire community that imagined the music at its inception. Big Bank Hank, after all, got his start in the business as a bouncer and managing an act that would become the Cold Crush Brothers. He landed a spot in the Sugarhill Gang when the late music executive Sylvia Robinson tapped him to be part of a pop-oriented rap trio she was putting together. + +Jeff Chang’s essential history of hip hop, “Can’t Stop, Won’t Stop,” describes the song as standing out amid party-oriented rap of the time due to the group’s birth as a studio creation. + + +Writes Chang, “Their raps on ‘Rapper’s Delight’ were the stuff that sounded good not in the parties, but on the live bootleg cassettes playing in the OJ cabs and on the boom-boxes --- the funny stories, the hookish slang, the same kind of stuff that would strike listeners around the world as both universal and new, not local and insular.” + +“Rapper’s Delight” is considered the best selling 12-inch single of all time, though that’s tough to confirm in the pre-Soundscan era, which began in 1991 (and various litigation involving the track’s unapproved sampling of Chic’s “Good Times” further blurred the issue of numbers). + +As happened with most first-generation rap teams (and second-, third-, fourth- and fifth-), Sugarhill Gang failed to sustain a bankable post-hit career, and didn’t receive royalty checks equal to its influence. In the years following the track's success, the style morphed in dozens of different directions, though, becoming politicized through Grandmaster Flash and the Furious Five, electro-fied through Afrika Bambaataa and popularized through Run-DMC and the Beastie Boys. + +Reverse engineer virtually any rap song since, and the circuitry leads back to ""Rapper's Delight,"" and by extension, Big Bank Hank. His phrasing, his fluid, funky tone, has endured, passed down from rapper to rapper, an invisible but essential presence. + +Follow Randall Roberts on Twitter: @liledit","1" +"Big Bank Hank of The Sugarhill Gang is dead at 57","The artist whose real name was Henry Jackson passed away at about 2 a.m. Tuesday in the New York City area. A founding member of 1980s revolutionary hip hop group The Sugarhill Gang, Big Bank Hank was best known for his verses on 'Rapper's Delight,' which was No. 248 on Rolling Stone's list of The 500 Greatest Songs of All Time. + +Big Bank Hank, one of the founding members of iconic 1980s hip hop group The Sugarhill Gang, died early Tuesday morning after a battle with cancer. He was 57. + +The news was first reported by music blog InFlexWeTrust.com. TMZ reported that the rapper — born Henry Jackson on Aug. 5, 1957, in the Bronx — died at about 2 a.m. Tuesday in the greater New York City area. + +“So sad to hear of our brother’s passing,” wrote fellow group members Wonder Mike and Master Gee in a statement to TMZ. + +From left, Wonder Mike, Master G and Big Bank Hank perform live circa 1979. + +Big Bank Hank, left, leaves behind fellow group members Wonder Mike, ceinter, and Master G, right. + +The Sugarhill Gang quickly rose to fame in the 1980s with their hit, 'Rapper's Delight,' and left a legacy as one of the greatest hip hop groups of all time. + +Hank’s Sugarhill Gang, which was named after the Sugar Hill neighborood in Manhattan, made music history in 1979 when their single “Rapper’s Delight” became the first hip hop track to be listed in the Top 40 charts in the United States. + +The track is widely considered to be the first song to popularize hip hop. Rolling Stone ranked it No. 248 on its list of The 500 Greatest Songs of All Time, and it came in at No. 2 on VH1’s 100 Greatest Hip Hop Songs. + +Big Bank Hank was born in the Bronx and died in the New York City area. + +Big Bank Hank performs during the Justin Timberlake and Friends Old School Jam concert benefiting Shriners Hospitals for Children at the Planet Hollywood Theater for the Performing Arts in October 2011 in Las Vegas. + +Big Bank Hank poses for a portrait at Sugar Hill Records in January 1984 in Englewood, N.J. + +Henry Jackson loved to rap about trying to steal Lois Lane away from Superman. + +Hank, known in his songs as ""the grandmaster with 3 MCs that shock the house for the young ladies,” rapped in his verses about competing with Superman for Lois Lane. + +The Sugarhill Gang, a seminal hip group in music history, had five studio albums including their 1980 self-titled record. The group released its last one, ""Jump on It!,"" a hip hop children's album, in 1999.","1" +"Sugarhill Gang Rapper Big Bank Hank Dies at 57","Big Bank Hank ... the Sugarhill Gang rapper best know as ""the grandmaster with 3 MCs that shock the house for the young ladies""... died early Tuesday morning ... TMZ has learned. + +Hank ... born Henry Jackson ... had been suffering from cancer. We're told he passed away in the greater NYC area around 2 AM. Hank was one third of the famous Sugarhill Gang ... which had the first mainstream rap hit ""Rappers Delight"" in 1979. + +His group mates Wonder Mike and Master Gee told TMZ ... ""So sad to hear of our brother's passing. Rest in peace Big Bank."" + +Hank was 57 years old.","1" +"Rapper Big Bank Hank of Sugarhill Gang dies at 57","The music world is mourning the death of rapper Big Bank Hank, who delighted fans and changed the course of hip-hop with the Sugarhill Gang's 1979 classic, Rapper's Delight. + +Big Bank Hank, who was born Henry Jackson but was also known as Imp the Dimp, died early Tuesday after a battle with cancer, according to TMZ. + +David Mallie, who manages the group's two remaining living members, told Fox News that Jackson died from kidney complications due to cancer. + +Wrote DJ Funkmaster Flex on Instagram. + +""Rest in peace... Big Bank Hank... Hip hop pioneer dies of Cancer .... Legend... Sugarhill gang August 5th-1957 / Nov11th-2014 ..... InFlexWeTrust.Com,"" wrote Flex. + +Hip Hop Wired.com notes that Rapper's Delight wasn't just a catchy hit song. It was ""the song is considered the moment that hip-hop became commercially viable.""","1" +"Reports: Big Bank Hank of pioneering rap group Sugarhill Gang has died","Henry Jackson, aka Big Bank Hank of the pioneering rap group Sugarhill Gang, has died of cancer, according to TMZ and some of Jackson’s friends on Twitter. David Mallie, who manages the group’s two remaining living members, confirmed Jackson’s death to Fox News. + +R.I.P. Big Bank Hank. One third of the song that made all of this Hip Hop Music possible. Thanx for opening the door. http://t.co/yrXx9dBo8M + +— Dark Gable (@bigdaddykane) November 11, 2014 + +Respect. Prayers up. God Bless. RT @Combat_Jack: RIP Big Bank Hank Aug. 5 1957 – Nov. 11 2014 + +— Bun B (@BunBTrillOG) November 11, 2014 + +RIP Big Bank Hank of the Sugarhill Gang #pioneer + +— QTip (@QtipTheAbstract) November 11, 2014 + +You were one of the guys who inspired me to touch the Mic. Rip Big Bank Hank. #ThankYou. #Tears http://t.co/CRdpjPLBB8 + +— GOAT. (@llcoolj) November 11, 2014 + +Jackson, 57, was best known for this verse in the iconic song, “Rapper’s Delight.” Released in 1979, the track became hip-hop’s first crossover hit and paved the way for rap to enter the mainstream. + +Check it out, I’m the C-A-S-AN, the O-V-A and the rest is F-L-Y You see, I go by the code of the doctor of the mix and these reasons I’ll tell you why You see I’m six foot one and I’m tons of fun and I dress to a tee You see I got more clothes than Muhammad Ali and I dress so viciously I got bodyguards, I got two big cars, that definitely ain’t the whack I got a Lincoln continental and a sunroof Cadillac So after school, I take a dip in the pool, which really is on the wall I got a color TV so I can see the Knicks play basketball Hear me talking ’bout checkbooks, credit cards, more money than a sucker could ever spend But I wouldn’t give a sucker or a bum from the Rucker, not a dime ’til I made it again Everybody go: Hotel, motel, whatcha gonna do today (say what?) Cause I’ma get a fly girl, gonna get some spank and drive off in a def OJ Everybody go: Hotel, motel, Holiday Inn You see, if your girl starts acting up, then you take her friend Uh Master Gee, am I mellow? It’s on you so what you gonna do? + +Here’s the group performing the song during Soul Train: + +“Rapper’s Delight” has since inspired countless wannabe rappers to spit those rhymes — even Brian Williams. Sort of.","1" +"Vladimir Putin gives speech on dangers of military aggression","Correction: A bird did not defecate on Russian President Vladimir Putin during a speech on Friday. The video appears to have been a hoax. +Vladimir Putin spoke at the dedication of a new monument to the First World War in Moscow on Friday. The Russian president said that the lessons of the war, which began a century ago this summer, were that peace is fragile, that military aggression is dangerous and that violence can generate more violence in turn. +Putin has supported the separatists in Ukraine who apparently shot down a Malaysian airliner last month, killing all 298 people on board. In the video above, a bird appears to defecate on Vladimir Putin, but it appears that the footage was altered. +European countries have been observing the centenary of the war this weekend, which claimed some 16 million lives, both soldiers and civilians.","1" +"No, a bird didn't poop on Vladimir Putin","A rogue bird let loose on Vladimir Putin over the weekend as the Russian president delivered a speech opening a World War I monument, according to multiple tittering reports. If that tale of feathered vigilante justice sounds farfetched though, that's because it is: The video purporting to show the airborne assault appears to be a sneaky editing job. + +Here's the clip that got Reddit's attention: + +Yet as another Redditor points out, other footage from the event shows Putin sans poop. (The snippet from the previous video comes around the ninth minute below.) + +Pictures from before and after the speech similarly show no tell-tale white stain, according to The Independent. + +So sorry, President Obama, but the birthday present that was too good to be true was, in fact, too good to be true. At least we'll always have the (admittedly phony) memories. --Jon Terbush + +(Reddit)","1" +"A Bunch Of Folks Are Passing Around This Hoax Video Of A Bird Pooping On Vladimir Putin","Russian President Vladimir Putin last Friday unveiled a World War I monument in Moscow last Friday, ahead of the centennial of the start of the ""Great War."" + +Sometime on Saturday, a video popped up on YouTube purporting to show a bird staging a form of protest — defecating, to be specific, on Putin. The video, which has been passed around on multiple sites only beginning on Monday, appears to be fake. + +Here's the evidence: The Independent points to a side-by-side comparison video clearly showing it's fake. + +The unaltered video also clearly shows Putin laying a wreath after speaking at the ceremony. And wire images show his suit to be perfectly clean during those moments..."" + +...And afterward: + +One of those ""too-good-to-be-true"" stories.","1" +"No, Vladimir Putin did not get pooped on by a bird during a First World War speech","A YouTube video claimed to show the incident in Moscow but was fake + +Monday 04 August 2014 + +A video of Vladimir Putin apparently being pooped on by a passing bird during a speech has proved to be a fake. + +Footage uploaded to YouTube claimed to show the embarrassing incident as the Russian President spoke at the unveiling of a First World War memorial in Moscow on Friday. + +Even by Putin’s ice man standards, he did seem remarkably unfazed by the present on his shoulder – probably because it was never there. + +In all other footage of the event the bird poo is nowhere to be seen and it does not appear on any pictures taken by multiple international agencies. + +If the incident had been real, it would not have been Putin’s first public encounter with an animal’s rear end – in September he drew a cat’s backside for confused Russian pupils on a school visit. + +Russia’s Deputy Prime Minister used a picture of his superior with a leopard to show the “different values” between his country and the US and Putin has also been seen “shaking hands” with a walrus and feeding dolphins. + +The Russian President is known for using photo opportunities with animals to cultivate his “macho” image. + +If his PR is to be believed, he likes nothing more than a holiday horse-riding topless through the wilds of southern Russia, catching huge pike or harpooning whales. + +Unluckily for many for the animals involved, Putin’s publicity stunts can end badly, as with the Siberian tiger that died after being over-sedated so the President could attach a GPS transmitter. + +In pictures: Putin's macho adventures + +Manchester United legend's exclusive new column for The Independent","1" +"Vladimir Putin Bird Poop Video is Fake","A video that appears to a show a bird pooping on Russian President Vladimir Putin’s suit during a speech last week is fake. + +The video–uploaded to YouTube–is going viral. A few media outlets appear to have been tricked by it. The video is titled: “Bird pooped on Putin at opening of WWI monument.” + +The Washington Post and TIME magazine both posted the video, apparently believing it. + +The Post issued a correction, saying that “a bird did not defecate on Russian President Vladimir Putin during a speech on Friday. The video appears to have been a hoax.” + +TIME wrote: “A video shared online made it seem as if Vladimir Putin got some unwelcome love from a feathered friend Sunday during a speech unveiling a monument to Russians who served in World War I.” + +It later updated the post, saying that “The Independent reveals this video to have been falsely doctored to show a bird defecating on Putin.” + +The Associated Press update: + +Obama, Putin discuss Ukraine, missile treaty + +WASHINGTON (AP) — Capping a week of aggressive action against Russia, President Barack Obama pressed Russian President Vladimir Putin Friday for a diplomatic path out of Ukraine’s struggle with Moscow-backed pro-Russian separatists. Putin countered by calling U.S. and European economic sanctions against Russia counterproductive. + +Obama later conceded that pressure from recently imposed U.S. and European measures to squeeze the Russian economy “hasn’t resolved the problem yet.” + +In an Obama-initiated phone call Friday, the U.S. president also raised concerns that Russia violated a key Cold War era nuclear weapons treaty, the White House said. In a letter this week from Obama to Putin and in an administration report released this week, the United States said Russia violated a 1987 treaty that bans all U.S. and Russian missiles of intermediate range, meaning those that can travel between about 300 miles and about 3,400 miles. + +Putin in the call said the sanctions seriously damage bilateral cooperation and general global stability, according to a Kremlin report on the call. + +It was the first conversation between the leaders since the U.S. and Europe slapped the new round of economic sanctions on Russia and since Obama’s letter claiming a breach in the missile treaty. + +“I indicated to him, just as we will do what we say we do in terms of sanctions, we’ll also do what we say in terms of wanting to resolve this issue diplomatically if he takes a different position,” Obama told reporters later. + +The Kremlin said both Obama and Putin underscored the urgency for bringing an end to fighting in eastern Ukraine and spoke positively about a meeting that took place the day before in Minsk, Belarus, among members of a diplomatic “contact group” pursuing an end to hostilities. That group includes representatives from Russia, Ukraine and the Organization for Security and Cooperation in Europe.","1" +"If Only A Bird Really Did Poop on Putin","The ""too good to be true"" cliche is especially accurate when it comes to viral news stories on perfectly formed dollops of bird crap. On Monday some news sites reported on a hoax video of a pigeon pooping on Putin during his speech on the dangers of military aggression while unveiling a monument in Moscow commemorating the 100th anniversary of World War One. The Independent has a good explainer on why the video below is fake. + +But if it had been real, the symbolism would have been spot on. During his speech, Putin emphasized a strong belief in promoting peace, even as Russia's policies have only provoked and perpetuated violence in Ukraine and Crimea, which he invaded. Despite his words, Russia announced on Monday that it will hold military exercises on its border with Ukraine in a show of strength, according to Reuters. The ""war games"" will include 100 fighter jets and missile practice. + +According to RT, he called the memorial ""'a tribute to the great deeds,' but also a warning that 'this peace is fragile.'"" He said that ""a peaceful and quiet life"" is the most valuable thing on Earth and that ""humankind should grasp one truth: violence generates violence. And the way to peace and prosperity is made up of good will and dialogue, and the memory of the lessons of the last wars."" + +On Friday, the same day Putin gave his poop-free speech, President Obama called Putin again to emphasize his concern over Putin's support of pro-Russian separatists in Ukraine. Vice President Joe Biden also announced $8 million in new financial aid to Ukraine to help the country protect its borders.","1" +"The video of a bird pooping on Vladimir Putin is a hoax","Correction: This post originally presented the video of a bird pooping on Putin as real, but comparison with Russian news footage from the event shows it to be a hoax. Putin's unintentionally ironic speech decrying ""excessive ambitions in war,"" though, was very real. + +The video appeared to show Russian President Vladimir Putin getting pooped on by a bird while giving a speech unveiling a World War One monument in Moscow on Friday. You can see the (fake) freedom bombs land at 0:11 into the above video or you can watch it on repeat, forever, in the gif below. + +The Moscow bird poop hoax of 2014 was passed around Western and Russian social media as a small but symbolically satisfying comeuppance for Putin's involvement in Ukraine, where fighting with Russia-backed separatists has killed hundreds of Ukrainians and, two weeks ago, 298 civilians flying overhead in Malaysian Airlines flight 17. Europe and the US have punished Russia with economic sanctions meant to deter further aggression, but this video appeared to show an unknown bird launched some targeted sanctions against the man himself. + +Rn0eaqx + +This being Russia, getting pooped on by a bird wasn't even the most ridiculous part of Putin's WWI speech. Putin warned that the lesson of WWI was — fair warning, irony is going to die forever at the end of this sentence — to avoid excessive ambitions in war. ""Humankind should grasp one truth: violence generates violence,"" said the man whose overt and ongoing support for separatist rebels in Ukraine, which he also invaded to annex Crimea, has helped claim hundreds of lives and stirred up months of crisis. + +""It was on the eve of WWI when Russia did everything possible to solve the conflict peacefully, without bloodshed, between Serbia and Austria-Hungary,"" Putin said, repeating an old Russian complaint that only it really wants peace but is ignored by an aggressive West. ""But Russia wasn't heard. And it had to respond to the challenge in order to protect the [fellow] Slavic nation."" + +I'm not sure whether Putin means this as an explicit nod to his involvement in Ukraine, but Russia's meddling there has often been internally premised on the idea that Russia must save the Russian-speakers in Ukraine's east. So there would seem to be a parallel. More ironically, the Ukrainians who are fighting and dying to keep Putin out of their country are themselves Slavic, but must have forgotten to thank Putin for his peace-seeking, pan-Slavic magnanimity.","1" +"News sites fall for Putin bird-dropping video","Vox.com, the brainy news-explainer site, has announced that it fell for one of the Internet’s many tricks. Allow it to explain: + +Correction: This post originally presented the video of a bird pooping on Putin as real, but comparison with Russian news footage from the event shows it to be a hoax. Putin’s unintentionally ironic speech decrying “excessive ambitions in war,” though, was very real. + +Right here is where a media critic generally hammers the offender for naivete, stupidity and a failure to observe reportorial protocol. All of which applies to this instance, but hey, that fake pooping video looks pretty convincing, in part because the white blotch falls not on Putin’s dome — an obvious landing spot for a hoaxster — but on his left shoulder. + +The Post’s “Know More” blog also fell for it. That post is now titled “Vladimir Putin gives speech on dangers of military aggression.” Its URL reads, “bird-defecates-on-vladimir-putin-during-speech-video.” It, too, has apprised readers that it got taken: “Correction: A bird did not defecate on Russian President Vladimir Putin during a speech on Friday. The video appears to have been a hoax.”","1" +"No joke: 5-year-old billed for missing friend’s birthday party","TORPOINT — No one likes getting bills, but one bill in particular has a family in Torpoint completely shocked. + +According to the Plymouth Herald, it all happened after 5-year-old Alex Nash was invited to a friend’s birthday party at a ski and snowboarding facility. + +After Alex was invited to the bash, Nash’s parents told his friend’s mother he would attend the party. But later, they realized they already had made other plans for that day, so Alex missed the party. + +Several days later, the little boy came home from school with an envelope in his book bag. It contained an invoice from his friend’s mother for a “child’s party no show fee.” + +The total was about $24. + +At first, they thought the bill was a joke and the woman they would not be paying the fee. But then, they say, she threatened to take them to small claims court. + +They also claimed that Alex’s friend will not play with him anymore. + +Alex’s parents are trying to resolve the situation via Facebook.","1" +"“I am lost for words,” 5-year-old boy billed for missing friend’s birthday party","TORPOINT, England – It’s always a shame when a friend can’t make it to a birthday party, but now one family may be paying the price for the no-show. + +According to Sky News, 5-year-old Alex Nash was invited to a friend’s birthday party at Ski Slope and Snowboard Centre. + +The boy’s father, Derek Nash, said that he accepted the invitation, forgetting about a prior family commitment. + +By the time he realized the mistake, Nash said he didn’t have any contact information for the woman. + +When Alex returned to school, he was handed an envelope by a teacher. + +Nash says the envelope contained a bill for a $24 “child’s party no-show fee.” + +“I thought it was a joke to begin with. I am lost for words,” Nash told Sky News. + +Nash says he is sorry for the mistake but will not be paying for a bill. + +The woman has since threatened to take the case to small claims court, and the boy will no longer play with Alex at school.","1" +"Parents billed $29 for a ‘no-show fee’ after five-year-old son misses birthday party","It’s enough to scare someone off of having children. + +Whether it’s gluten or plastics or peanuts, it seems young and new parents have more and more social taboos to navigate. + +The latest parenting taboo? Missing a birthday party — or sending an invoice to the absent child’s parents, depending on how you look at it. + +A pair of British parents are still reeling from the discovery of an invoice for £15.95 (just under $29 Canadian) in their five-year-old son Alex’s backpack. Their crime? Not informing the parents of his classmate their son would not be attending a birthday party in December. + + + +Julie Lawrence, the birthday boy’s mother, has defended the “fee” as necessary to recoup the costs associated with a no-show. She said Alex told her son he would attend the party and took that as proper confirmation. She said the cost covers one ticket to the “child’s party at the ski slope including snow tubing and tobogganing and lunch.” + +Lawrence has also threatened to take the Nash family to small claims court if they don’t pay up. + +Nash has said he understood the financial concerns and said it was the way Lawrence went about it that offended. They have also taken the issue up with the school, because it allowed Lawrence to place the brown envelope in Alex’s backpack, which is against school policy. + +So where was Alex? Out with his grandparents, whom he chose over the party when his parents realized he was double booked for the day and it was the only chance he would have to see them before Christmas. + +Alex’s mom, Tanya Nash, explained this to Lawrence in a Facebook exchange printed by the Plymouth Herald, the local paper that first broke the story. The ensuing Facebook debate between the two mothers now has parents around the world chiming in. + + +If Lawrence’s side of the story seems reasonable — she did have to pay for Alex when he didn’t show up after all — the Facebook conversation takes quite the turn. The moms’ fight about whether or not they had each other’s number and who was ruder in how they approached the other parent. + +“This is not the first time Alex has not turned up to a party that he has been invited to, either. the amicable way round this I believe would be to pay me the money and let a lesson be learnt, I hope this is agreeable,” Lawrence writes. + +Nash responds that she can’t think of another party Alex missed where there was a formal invite, and the pushes back against Lawrence’s tone: “Exactly what lesson would I be learning? I am not a child, so please do not speak to me like I am one. So, to answer your question, unfortunately no. This is not agreeable.”","1" +"Party invoice: Boy sent bill for birthday no-show","A five-year-old was billed for failing to attend a friend's birthday party - resulting in threats of legal action. + +Alex Nash, from Cornwall, was invited to the party just before Christmas. + +An invoice for £15.95 was sent by his schoolfriend's mother Julie Lawrence, who said Alex's non-attendance left her out of pocket and his parents had her details to tell her he was not going. + +Alex's father Derek said he had been told he would be taken to the small claims court for refusing to pay. + +Alex's parents, from Torpoint, had accepted an invitation to the party at a dry ski slope in Plymouth, Devon, just before Christmas. + +However, they realised their son was double-booked and due to spend time with his grandparents, which he did. + +Analysis: Clive Coleman, BBC legal correspondent + +It is all but impossible that Ms Lawrence will be able to recover the £15.95 party ""no show fee"". + +Any claim would be on the basis that a contract had been created, which included a term that a ""no show"" fee would be charged. + +However, for there to be a contract, there needs to be an intention to create legal relations. A child's party invitation would not create legal relations with either the child ""guest"" or its parents. + +If it is being argued that the contract is with the child, it is inconceivable that a five-year-old would be seen by a court as capable of creating legal relations and entering into a contract with a ""no show"" charge. + +It's amusing to imagine what a children's party invitation seeking to create a contract might say: ""I, the 'first party', hereinafter referred to as the 'birthday boy', cordially invite you the 'second party', hereinafter referred to as 'my best friend', to the party of 'the first party'. + +His parents said they had no contact information for Ms Lawrence at that time. + +They found the invoice in a brown envelope in his schoolbag last week. + +Mr Nash said: ""It was a proper invoice with full official details and even her bank details on it. + +""I can understand that she's upset about losing money. The money isn't the issue, it's the way she went about trying to get the money from me. + +""She didn't treat me like a human being, she treated me like a child and that I should do what she says."" + +In a short statement, Ms Lawrence said: ""All details were on the party invite. They had every detail needed to contact me."" + +Mr Nash said he had been told he was being taken to the small claims court because he was refusing to pay. + +The party was held at the Plymouth Ski and Snowboard Centre. + +In a statement, the centre said: ""We would like all our customers to know that this invoice has nothing to do with Plymouth Ski and Snowboard Centre. + +""No invoices are ever sent out from the centre to private individuals. This is a disagreement between the two parents involved and the fact that the centre has been named on the invoice is fraudulent. + +""When booking a party there is a small deposit to pay on booking, confirmation of numbers and final balance are due 48 hours before the party. + +""On the extremely rare occasion that people don't attend parents are generally offered other activities in compensation."" + +The unwritten rules of children's parties? + +Read more from the BBC Magazine on the politics of parties + +Have you ever committed a kids party faux pas? Email England@bbc.co.uk with your tale of breaking the rules","1" +"Boy, 5, billed with 'no show fee' for missing friend's BIRTHDAY PARTY","A FIVE-YEAR-OLD boy has been billed with a ""no show fee"" - for missing his friend's BIRTHDAY party. + +Derek Nash and his partner discovered the invoice - for the sum of £15.95 - after it was slipped into their son Alex's school bag. + +The host of the party gave it to Alex via a teacher after he failed to show up for the get-together at a ski slope and snowboard centre in Plymouth, Cornwall. + +Alex's family confirmed that their son would be attending the party just before the Christmas holidays. + +But Mr Nash, from Torpoint, Cornwall, realised he had arranged for their daughter to go on a day trip with her grandparents. + +He then asked Alex if he wished to join his sister or go to the party, to which he chose to spend time with his grandparents. + +Bemused Mr Nash said he originally thought the invoice ""was a joke"", but the issue has remained unresolved and now the birthday boy's mother has threatened to take him to a small claims court. + +He said: ""She saw me and asked if Alex was coming to the party. At this time I agreed and said that Alex was looking forward to it."" + +However, after Alex had changed his mind about the party, Ms Nash realised he had no way of contacting the birthday boy's mother. + +""So on the day of the party we asked Alex what he wanted to do - he chose to be with his grandparents,"" he said. + +""By this time we did not have a contact number, email or an address to let [the boy's mother] know."" + +Alex returned to Torpoint Nursery and Infant School on January 6, but just over a week later, the family were stunned to receive the bill. + +Mr Nash continued: ""My partner looked out for [the friend's mother] to apologise for Alex not showing up to the party, but didn't see her. + +""But on January 15 she looked in Alex's school bag and found a brown envelope. It was an invoice for 15.95 for a child's party no show fee. + +""I asked Alex's class teacher if [the child's mother] had given anything to her. She said, 'Yes, a brown envelope'. + +""I then visited Alex's school headteacher, who couldn't apologise enough that one of the teachers had passed this on. + +""She said she would remind all staff that this was a breach of protocol."" + +He then went to visit the mother, since named as Julie Lawrence and whose address was on the invoice, and told her that he would not be paying the bill. + +""I told her she should have spoken to me first and not put the invoice in my son's school bag,"" he said. + +""I would have sympathised with her about the cost of Alex not showing up, but I just can't believe the way she has gone around it."" + +The mother has since threatened the family to take the case to a small claims court, while the birthday boy will no longer play with Alex at school. + +Mr Nash added: ""I drive all around the South West for my job and I have talked to quite a few people about this. + +""They're all quite incredulous that this has happened. I thought it was a joke to begin with. I am lost for words."" + +His partner, who does not want to be named, has been in contact with the mum on Facebook and is hoping to resolve the situation. + +In a short statement, Ms Lawrence said she had no regrets about sending the invoice. + +She said: ""All details were on the party invite. They had every detail needed to contact me."" + +Manager of the Plymouth ski and snowboard centre, Louisa Duggan, said they would never send invoices to individuals and were upset at being dragged into the row. + +She said: ""This is nothing to do with us. It is a dispute between two parents. But I really need to clarify that we don't send invoices to private individuals - ever. + +""We don't know the names of the children coming so we would never even be able to. + +""We are upset that we have been dragged into this. We ask families who book with us to pay a small deposit and then 48 hours before we ask them to confirm the numbers. + +""This gives them plenty of time to get responses in. We are quite flexible if any of the party does not turn up. + +""We can put on other activities to compensate or often an adult will take part in place. + +""We do need to know how many people are coming because we have to plan food and reserve activities and spaces. That is how any businesses like ours has to operate.""","1" +"Torpoint: Five-Year-Old Billed For Missing Friend’s Birthday Party In England","A five-year-old boy in Torpoint, England, ended up missing a friend’s birthday party, and he did it without any advance notice. Due to his no-show at his friend’s party, the young child was actually given an invoice and billed for his nonappearance. + +According to the Plymouth Herald, Derek Nash says that his son Alex was given a “child’s party no show fee” invoice for not going to a friend’s birthday party. The bill for £15.95 (approx. $25) was in his son’s school bag last week and Nash “thought it was a joke.” + +The party was scheduled for before the Christmas holidays when Alex was invited to one of his Torpoint Nursery and Infant School classmate’s birthday party. It was being held at the Ski Slope and Snowboard Centre, and the Nash family indicated that Alex would be attending the party. + +“She saw me and asked if Alex was coming to the party. At this time I agreed and said that Alex was looking forward to it.” + +As the Metro stated, Nash informed the classmate’s mother in person that his son would be going to the party. It was after that conversation that Nash realized the family already had a family trip planned for that day. + +Upon trying to cancel Alex’s acceptance to the party, Nash found no way to contact the party-thrower. + +“We did not have a contact number, email or an address to let [the boy’s mother] know. So on the day of the party we asked Alex what he wanted to do – he chose to be with his grandparents.” + +It was a week later that the invoice for Alex’s no-show was received. A teacher at the Torpoint Nursery and Infant School is actually the one who put the notice in the boy’s school bag, and the school has since issued an apology for their involvement in the matter. + +Alex’s teacher said that she would let all staff know that giving the boy an invoice was a “breach of protocol.” + +Derek Nash said he then left the school and went to visit the birthday boy’s mother since her address was now on the invoice. He let her know that he “would not be paying her the money” and that “she should have spoken to me first.” + +The birthday boy’s mother has since threatened the Nash family with legal action and could possibly take them to small claims court to get the money she is owed. + +As for Alex Nash and his classmate at the Torpoint Nursery? He has told his parents that his classmate won’t play with him at school now since he was a no-show to the party and the invoice was given out. + +[Image via Plymouth Herald]","1" +"Five-year-old boy gets a bill for missing school friend's birthday party","Five-year-old Alex Nash and dad Derek holding the invoice + +The professional-looking 'invoice' even contains a space for VAT + +Alex says his friend will no longer play with him at school since the row broke out + +Dad Derek Nash and his partner claim they have been threatened with court action if they don't stump up the cash + +Derek Nash says he thought the invoice was ""a joke"" at first + +Alex was handed the bill in a brown envelope at school + +Pals of the Nash family are ""incredulous"", dad Derek says + +Alex, 5, chose a day out with his grandparents instead of the party at Plymouth's ski slope + +Five-year-old Alex Nash and dad Derek holding the invoice +Previous +Next + Comments (73) +A FIVE-year-old boy has been handed an invoice – for missing his friend’s birthday party. + +And now his parents claim they have been threatened with the possibility of court action if they don’t stump up the cash. + + +Advertisement +Derek Nash and his partner, who live in Torpoint, discovered the ‘no show fee’ invoice for £15.95 in their son’s school bag last week. + +Mr Nash, a delivery driver, said he “thought it was a joke”. + +RELATED CONTENT +Bracelets handed out to primary school children recalled amid safety fears +Booster the dog lived with a belly full of toys - which were only revealed after Quality Street mishap +Big cats, zombies, clowns and potholes - 10 years of Freedom of Information in Plymouth +Drunk in the morning man tells himself to shut up +Plymouth primary school starts teaching pupils Mr Tumble-style sign language +Plymouth ski centre criticises mum for billing boy who missed birthday party + +Digsby +IM, Email, and Social Networks in one easy to use application! +http://kvors.com/click/?s=88377&c=89569&subid=21987 +Alex's parents fear they may be dragged into a court battle - all because their son chose a day out with his grandparents over a pal's birthday party + +Just before the Christmas holidays, Alex, their son, was invited to a classmate’s Birthday party at the Ski Slope and Snowboard Centre. + +Alex, who goes to Torpoint Nursery and Infant School, told his parents he wanted to go and so Mr Nash and his partner confirmed he would be at the celebration. + +Mr Nash said: “She saw me and asked if Alex was coming to the party. At this time I agreed and said that Alex was looking forward to it.” + +But Mr Nash later realised he had arranged for Alex and his sister Lily to out for a day trip with their grandparents. + +“By this time we did not have a contact number, email or an address to let [the boy’s mother] know,” explained Mr Nash. + +“So on the day of the party we asked Alex what he wanted to do; he chose to be with his grandparents.” + +On January 6 Alex went back to school as the new term got under way. + +Mr Nash continued: “My partner looked out for [the friend’s mother] to apologise for Alex not showing up to the party, but didn’t see her. + +“But on January 15 she looked in Alex’s school bag and found a brown envelope. It was an invoice for £15.95 for a child’s party no show fee. + + +Digsby +IM, Email, and Social Networks in one easy to use application! +http://kvors.com/click/?s=88377&c=89569&subid=21987 +The bill Alex brought home. He was not charged VAT on his birthday party no-show... + +“I asked Alex’s class teacher if [the child’s mother] had given anything to her. She said, ‘Yes, a brown envelope’. + +“I then visited Alex’s school headteacher, who couldn’t apologise enough that one of the teachers had passed this on. + +“She said she would remind all staff that this was a breach of protocol.” + +“I left the school and went to see [the birthday boy’s mother] as her address was on the invoice. + +“When she answered the door I told her I had found the invoice in my son’s school bag and that I wasn’t happy about it. + +“I told her I would not be paying her the money. + +“I told her she should have spoken to me first and not put the invoice in my son’s school bag.” + +He added: “I would have sympathised with her about the cost of Alex not showing up, but I just can’t believe the way she has gone around it.” + +The couple claim that the mother of Alex’s friend has threatened the couple with taking the case to the small claims court. + +And five-year-old Alex has told his parents that his classmate will no longer play with him after he didn’t show up to the party. + + +Poor Alex says his friend will no longer play with him at school since the row broke out + +Mr Nash said: “I drive all around the South West for my job and I have talked to quite a few people about this. + +“They’re all quite incredulous that this has happened. + +“I thought it was a joke to begin with. I am lost for words.” + +Mr Nash’s partner has been in contact with the mum via Facebook hoping to resolve the situation. + +The mother of Alex’s friend was unavailable for comment when contacted by The Herald. + + +Full Facebook conversation between Alex's mum Tanya and the birthday boy's mum Julie. + +Tanya Walsh + +Hi Julie. This is Alex's mum. I don't know what has happened between you and my partner, Derek. I was very shocked to see the invoice in Alex's school bag. I did not realise that you had to pay for each child, as you never mentioned anything about money when we spoke. The only reason Alex did not attend the party was because his nan and grandad were going away for christmas and the only day the kids could go see them was on the same day as the party. I did not know this. On the day Alex decided that he wanted to spend time with his nan and grandad. I apologise for not letting you know, but I did not have a phone number or an e-mail for you to let you know the situation(I also didn't know your first name, or I would have looked you up). If I had known that I would have to pay if Alex did not go, then I would have paid you the money, no problem. I do not like fighting with people, and would prefer to settle this amicably. + +Julie Lawrence + +Hi Tanya, I didn't mention the money when we spoke because it was a child's party, it doesn't matter if you have to pay per person or for a group if people agree to going, I confirmed that with all parents on the Thursday before the party that they were going as I had to pay that day, and Derek told me Alex was looking forward to it and would see us there, to me that is confirmation. My phone number was on the invitation that was sent out to Alex. I don't like fighting with people either, and was not best impressed when Derek turned up on my doorstep, and said you won't get any money out of me, rather rudely, I do admit it rattled me. This is not the first time Alex has not turned up to a party that he has been invited to, either. the amicable way round this I believe would be to pay me the money and let a lesson be learnt, I hope this is agreeable ? Julie + +Tanya Walsh + +Hi Julie, who's party is Alex supposed to have gone to? I did speak to another mum about a party but she never got back to me with details, other than that I don't recall any other confirmed invites. The only reason Derek was angry was because of the fact that the envelope was put into Alex's school bag, when it has nothing to do with the school. He spoke to the headteacher about and she said that it's against school policy to do that kind of thing. Birthday invites are fine, but not personal items. Like I said before, no money was mentioned when we spoke, and I feel it would be inappropriate to pay you the money, when I don't know what it's actually paying for. Alex was very excited to go to the party. I didn't know until the day about his nan and grandad, and he decided he would rather spend the day with them. Like I said before I didn't have your number to let you know. And exactly what lesson would I be learning. I am not a child, so please do not speak to me like I am one. So, to answer your question, unfortunately no. This is not agreeable. + +Julie Lawrence + +You are paying for 1 x child's party at the ski slope including snow tubing and tobogganing and lunch, to with you said Alex was attending on the Thursday + +Tanya Walsh + +Just so you know, small claims court cost #60 just to start a claim. Also I'm not paying for something we didn't use. + +Julie Lawrence + +It doesn't cost that much + +Tanya Walsh + +It does. Also I don't think the school are very happy with you involving them in this either. I don't know why you are out for our blood and slandering us. I've told you the reasons why alex didn't go. I also told you why I couldn't call. You also don't seem to understand that I never ran away from you. I didnt hear you calling after me. I have to get to my daughter at carbeile. So if they let alex out last then I have to rush a bit because evie, my 2 year old, walks slow. So maybe that's why you thought I was rushing off. I had no reason to run to run away from you. So please do not state things as truth when you do not have all the facts. Maybe if you actually spoke to me rather than making your own mind up about what happened then none of this would be happening right now. If you had come up to us the first day back and explained about the money, then I could have explained about alex, then maybe we could have sorted something out. Instead you send an invoice.","1" +"Boy, 5, given £15.95 invoice for missing friend's birthday party","A five-year-old has been handed an invoice and his parents threatened with court action - for missing his friend's birthday party. + +Derek Nash and his partner Tanya Walsh discovered the £15.95 ""no show fee"" invoice after it was slipped into their son Alex's school bag. + +Mr Nash said he originally ""thought it was a joke"", but the issue has remained unresolved with the birthday boy's mother, Julie Lawrence, threatening small claims court. + +His partner confronted Ms Lawrence in a series of posts on Facebook in a bid to resolve the situation. + +The family confirmed their son would be attending the party at the Ski Slope and Snowboard Centre just before the Christmas holidays. + +However, Mr Nash, from Torpoint, Cornwall, realised he had already arranged for their daughter to go on a day trip with her grandparents. + +He said: ""She saw me and asked if Alex was coming to the party. At this time I agreed and said that Alex was looking forward to it. + +""By this time we did not have a contact number, email or an address to let [the boy's mother] know. So on the day of the party we asked Alex what he wanted to do - he chose to be with his grandparents."" + +Alex returned to Torpoint Nursery and Infant School on January 6, but the family were shocked to receive the bill just over a week later. + +Mr Nash added: ""My partner looked out for [the friend's mother] to apologise for Alex not showing up to the party, but didn't see her. + +""But on January 15 she looked in Alex's school bag and found a brown envelope. It was an invoice for £15.95 for a child's party no show fee. + +""I asked Alex's class teacher if [the child's mother] had given anything to her. She said, 'Yes, a brown envelope'. + +""I then visited Alex's school head teacher, who couldn't apologise enough that one of the teachers had passed this on. She said she would remind all staff that this was a breach of protocol. + +""I left the school and went to see [the birthday boy's mother] as her address was on the invoice. When she answered the door I told her I had found the invoice in my son's school bag and that I wasn't happy about it. + +""I told her I would not be paying her the money. I told her she should have spoken to me first and not put the invoice in my son's school bag. + +Julie Lawrence and her husband Simon + +""I would have sympathised with her about the cost of Alex not showing up, but I just can't believe the way she has gone around it."" + +Ms Lawrence has since threatened the family that she would take the case to a small claims court, while the birthday boy will no longer play with Alex at school. + +Mr Nash added: ""I drive all around the south west for my job and I have talked to quite a few people about this. They're all quite incredulous that this has happened. I thought it was a joke to begin with. I am lost for words."" + +Ms Lawrence said the boy's non-attendance left her out of pocket and insisted his parents did have details to tell her he was not going. + +She said in a statement: ""All details were on the party invite. They had every detail needed to contact me.""","1" +"Fake-News Report Claims Michael Jackson Is Father Of Bruno Mars","According to this 'news' report, which is circulating via social media, DNA testing has confirmed that Michael Jackson is the biological father of American singer Bruno Mars. + +Supposedly, Bruno's publicist Vladimir Kershov leaked the private information and was subsequently fired for his actions. But, claims the article, Bruno's new publicist has nevertheless confirmed that Michael Jackson is indeed Bruno's father. + +However, the claims in the story are untrue. No such private information was leaked and there are no credible reports that support the claims. + +The bogus story comes from the fake-news website Empire News. Empire News considers itself satirical. The site includes the following disclaimer: + +Empire News is a satirical and entertainment website. We only use invented names in all our stories, except in cases when public figures are being satirized. Any other use of real names is accidental and coincidental. +But, alas, because the site presents its fictional stories in news format, many readers tend to believe them and share them accordingly. + +Given the number of fake-news 'satire' websites that have sprung up in recent years, it is a good idea to verify any 'news' stories that come your way before you share them. Searching a news portal such as Google News will usually reveal if a circulating story is true. + +Example +DNA Results Confirm Michael Jackson Is Biological Father Of Bruno Mars +NEW YORK, New York - DNA Results Confirm Michael Jackson Is Biological Father Of Bruno Mars +Vladimir Kershov, publicist of R&B singer Bruno Mars, has been fired today after he revealed a shocking secret regarding the pop and R&B singer. Kershov leaked private information that revealed that Michael Jackson is Mars’ biological father. + + + + + + +© Depositphotos.com/ Jean_Nelson","1" +"No, Michael Jackson Isn’t Bruno Mars’ Dad","Michael Jackson, legendary as he was as the King of Pop, wasn’t the most the popular dad in showbiz. Ever since the Berlin baby-dangling incident of ’02, the media has tirelessly and unfairly portrayed him as an irresponsible and detached father (before his death, Jackson had shown remorse for the incident). This depiction was unfortunately fueled by his own erratic behavior during the final years of his life, and the sexual abuse charges that chased Jackson a few years before his death certainly didn’t help with his image. + +This week, social media went crazy over a “news” article that had been circulating Facebook and Twitter like wildfire. An article published by Empire News entitled, “DNA Results Confirm Michael Jackson Is Biological Father Of Bruno Mars,” has unsurprisingly shocked and enraged fans of both singers across the internet. + +The story went on to detail how the Billionaire singer allegedly and inadvertently revealed where he got his singing genes. The article wrote that the discovery involved Mars’ firing of a certain Vladimir Kershov, the singer’s reported publicist. + +“Vladimir Kershov, publicist of R&B singer Bruno Mars, has been fired today after he revealed a shocking secret regarding the pop and R&B singer. Kershov leaked private information that revealed that Michael Jackson is Mars’ biological father.” + +Gullible netizens went insane over the Michael Jackson-Bruno Mars story, not realizing that Empire News, an Onion-like website (without the funny), publishes mostly “satirical” and made-up articles. Fact-checking website Snopes has since labelled the story “false”. + +According to Bruno’s Wikipedia page, the half-Filipino singer was born to Peter Hernandez and Bernadette Bayot in 1985 and was born and raised in Honolulu, Hawaii. Meanwhile, Michael was, at the time, not involved with anyone, although he was already beginning to form a relationship with future-wife Lisa Marie Presley. + +While Jackson was often portrayed as a bad dad in tabloids, he was, in reality, an amazing father to his kids Michael Jr, Paris and Prince. Shortly after his death, MTV revealed never-before seen correspondence with people closest to Michael, most of whom attested to the fact that the singer was a caring and loving dad to his children. Producer and Jackson’s friend Teddy Reily recalled, “Michael] read them a book every day. When we were in Virginia during the Invincible [sessions], there was not one day missed reading the children something. So that showed me right there that he was an incredible father.” + +In other news, Michael Jackson’s brothers continue to celebrate his musical legacy through various performances around the world. Inquisitr recently reported about the brothers’ upcoming UAE concert, which is set to be attended by thousands of fans. + +[Image Via fanpop.com and obladoo.se]","1" +"Penis Spray-Painted on a $2.5 Million Car Was Just for a Prank Video","In this week's edition of lies, fakes, pranks and cheats on the Internet, we bring you a spray-painted penis on a very expensive car. Seriously. + +It all began with a picture of a poorly drawn penis on the hood of a $2.5 million Bugatti Veyron that appeared on Reddit. + +Image: Imgur + +But as the automotive blog Car Crushing pointed out, the artwork was most likely done for a planned prank video. + +Instagram user andreysmygov posted a photo of the elementary-level NSFW drawing with the caption, ""How often do [yo]u get to spray paint on a Bugatti lol,"" crediting the TwinzTV YouTube channel and crew, who also posted photos of the vehicle mentioning a prank. + +The proof: + +Loading + +How often do u get to spray paint on a Bugatti lol shoutout to the homie @vgtorious for letting us @twinztv1 @twinztv2 @twinz_tv @nigxl @alexwood66 + +View on Instagram + +Loading + +I got to spray paint this on @vgtorious #buggati today haha #prank #twinztv #youtube #funny #seattle with @_twinztv_ @twinztv2 @andreysmygov + +View on Instagram + +The owner of the vehicle appears to be Instagram user gtorious, who posted another photo of his expensive car last night with the caption, ""Oops I think we pranked the WORLD and the video hasn't aired...yet."" + +Image: @vgtorious on Instagram + +In August, the TwinzTV crew posted another prank video using the same vehicle. + +Believe in nothing, Internet — especially penises. + +Have something to add to this story? Share it in the comments.","1" +"Bugatti Veyron Vandalized With Penis Graffiti? Viral Photo Isn’t What It Seems","Did you see the Bugatti Veyron that was vandalized with penis graffiti in Seattle? Well, it may have not actually been a crime. + +Several people were angry this week when they saw a photo of the $2.5 million car with a big penis drawn across the hood. How could someone vandalize such a beautiful piece of machinery! Well, it doesn’t appear like this was the work of vandals. + +A photo of the car was uploaded to Instagram by AndreysMyGov of VG Productions. Andrey writes that the car was purposefully spray painted for an upcoming music video. + + +Andrey writes: “Yea bro it’s for an upcoming video we working on. It’s gonna be sick stay tuned bro two Bugatti videos coming in the next couple weeks.” Andrey claims that it’s real spray paint but that may not be true. Here’s another photo with a different red mark, “VG,” on the car. + + +The most recent photo from Andrey’s account shows the Bugatti Veyron without any markings. Either VG Productions has a garage full of disposable cars of they are using some sort of paint that is very easy to remove. + + +Regardless, VG Productions did what they wanted to do and created a buzz on the internet. The story has been picked up by dozens of publications and the photos have been shared thousands of time on social media. + +Loading + +A little joke goes a long way haha + +The video featuring the vandalized Bugatti hasn’t been released yet but here’s a look at their previous Bugatti prank video.","1" +"Vandals add rude paint job to $2.5m Bugatti (but luckily for the owner it all turned out to be a hoax)","An image of a gold Bugatti Veyron graffitied with a drawing of a penis may have upset car lovers - but it turns out the vehicle was included in a YouTube hoax. + +Photos from multiple Instagram accounts have revealed the luxury vehicle wasn't permanently damaged. + +Instagram user @andreysmygov uploaded a photo last Friday of the Veyron with a caption that suggested it was painted on as a stunt for TwinzTV, Car Crushing noted. + +Scroll down for video + +Graffitied: A photo of the 'vandalised' Bugatti Veyron was reportedly taken in Seattle, according to a Reddit post + +Busted: This Instagram photo from @andreysmygov included a caption suggesting the car was spray-painted as a stunt with TwinzTV + +'How often do u get to spray paint on a Bugatti lol shoutout to the homie @vgtorious for letting us @twinztv1 @twinztv2 @twinz_tv @nigxl @alexwood66,' he wrote online. + +Brothers Jeremy and Jason Holden run the YouTube pranks channel TwinzTV. + +A Saturday photo @andreysmygov shows user @vgtorious standing next to the Veyron, this time with different graffiti. + +Instead of a drawing of male genitalia, there is graffiti of the initials 'VG' + +A Sunday photo from his account shows both @andreysmygov and @vgotorious leaning on a scrubbed-clean Veyron, suggesting the luxury vehicle no longer features any markings. + +'Filming new vid with @vgtorious this one is going to be sick! #vgproductions #bugatti' @andreysmygov captioned the photograph. + +A photo of the car being waxed - with no graffitti visible - was posted by @vgtorious to Instagram on Saturday, though it is not clear when that took place. + +Different drawing: A second photo @andreysmygov's account shows different graffitti on the hood of the Veyron + +He also re-grammed the photograph showing him next to the with the letters 'VG' on the hood, confirming the hoax. + +'Oops I think we pranked the WORLD and the video hasn't aired...yet �� #bugatti #veyron #vw #youtube #global #news #pranks #funny #bugattifamilyimsorry', he captioned the snap. + +Jeremy Holden also uploaded a snap of the penis drawing on the Veyron on Saturday. + +He wrote, 'I got to spray paint this on @vgtorious #buggati today haha #prank #twinztv #youtube #funny #seattle with @_twinztv_ @twinztv2 @andreysmygov.' + +TwinzTV already featured the Bugatti Veyron in an August YouTube video, Car Crushing pointed out. + +In that clip, a man leans against the Veyron picking up women, with a much less expensive silver car parked behind him. + +When he convinces the women to get food with him, all but one leave when they realize he is not the Veyron's actual owner - and actually owns the silver car.","1" +"Vandals spray a rude drawing on $2.4m Bugatti Veyron (but fortunately for the owner it is all a prank)","An image of a gold Bugatti Veyron graffitied with a drawing of a penis may have upset car lovers - but it turns out the vehicle was included in a YouTube hoax. + +Photos from multiple Instagram accounts have revealed the luxury vehicle wasn't permanently damaged. + +Instagram user @andreysmygov uploaded a photo last Friday of the Veyron with a caption that suggested it was painted on as a stunt for TwinzTV, Car Crushing noted. + +Scroll down for video + +Graffitied: A photo of the 'vandalised' Bugatti Veyron was reportedly taken in Seattle, according to a Reddit post + +Busted: This Instagram photo from @andreysmygov included a caption suggesting the car was spray-painted as a stunt with TwinzTV + +'How often do u get to spray paint on a Bugatti lol shoutout to the homie @vgtorious for letting us @twinztv1 @twinztv2 @twinz_tv @nigxl @alexwood66,' he wrote online. + +Brothers Jeremy and Jason Holden run the YouTube pranks channel TwinzTV. + +A Saturday photo @andreysmygov shows user @vgtorious standing next to the Veyron, this time with different graffiti. + +Instead of a drawing of male genitalia, there is graffiti of the initials 'VG' + +A Sunday photo from his account shows both @andreysmygov and @vgotorious leaning on a scrubbed-clean Veyron, suggesting the luxury vehicle no longer features any markings. + +'Filming new vid with @vgtorious this one is going to be sick! #vgproductions #bugatti' @andreysmygov captioned the photograph. + +A photo of the car being waxed - with no graffitti visible - was posted by @vgtorious to Instagram on Saturday, though it is not clear when that took place. + +Different drawing: A second photo @andreysmygov's account shows different graffitti on the hood of the Veyron + +He also re-grammed the photograph showing him next to the with the letters 'VG' on the hood, confirming the hoax. + +'Oops I think we pranked the WORLD and the video hasn't aired...yet �� #bugatti #veyron #vw #youtube #global #news #pranks #funny #bugattifamilyimsorry', he captioned the snap. + +Jeremy Holden also uploaded a snap of the penis drawing on the Veyron on Saturday. + +He wrote, 'I got to spray paint this on @vgtorious #buggati today haha #prank #twinztv #youtube #funny #seattle with @_twinztv_ @twinztv2 @andreysmygov.' + +TwinzTV already featured the Bugatti Veyron in an August YouTube video, Car Crushing pointed out. + +In that clip, a man leans against the Veyron picking up women, with a much less expensive silver car parked behind him. + +When he convinces the women to get food with him, all but one leave when they realize he is not the Veyron's actual owner - and actually owns the silver car.","1" +"Cesar Millan is Not Dead: Dog Whisperer Death Hoax Circulates","A story circulating online claims that Dog Whisperer Cesar Millan died of a heart attack. That report, however, is false. + +Sponsored links + + + + +Death Hoax + +In a report published by Unam Noticias, we read that Millan died in a Santa Clarita hospital of a heart attack. The story states that Millan’s death was announced by his wife at a press conference. The article, as of this writing, has received nearly 20,000 shares online. + +The report, however, is not true. + +cesar millan + +Some shocked readers shared the sad news on social media, without first verifying the claims in the report. Although as of this writing, neither Millan nor his representatives have responded to the death hoax, there are several factors which indicate the article is not true. + +Consider: + +The original report does not cite any sources. +No legitimate media outlets have reported Millan’s death +There is no evidence that Millan’s wife held a press conference +There has been no such announcement on Millan’s official Facebook page. +The story on Unam Noticias is rife with grammatical and spelling errors (example: “Millan was hospitalize yesterday afternoon, the medical reports indicate that he suffered a fulminate heart attack, which paralyze his heart unavailable for the blood…” +Bottom Line + +The report claiming that Cesar Millan died of a heart attack appears to be yet another celebrity death hoax. The poorly-written source of this report offered no sources and has received no corroboration from trusted media outlets or representatives of Millan.","1" +"Hoax Busted: Report on Popular 'Dog Whisperer' Cesar Millan's Death is False","A report claiming that popular 'dog whisperer' Cesar Millan had died of heart attack on Tuesday morning, is nothing, but a lie. + + A hoax report claimed that 'dog whisperer' Cesar Millan had died of heart attack. +A hoax report claimed that 'dog whisperer' Cesar Millan had died of heart attack. Twitter +The death hoax report was started by a website that claimed to be the popular Spanish news agency - ProcesoMX. The report on the fake website was soon picked by many on social media as thousands of his fans shared it on Facebook and Twitter. +The Cesar Millan death hoax now has gone viral. +The fake death report stated: +The 45 year old Mexican/American, born in De la Cruz, Sinaloa, who made a name for himself with his incredible rehabilitation and training technics wit dogs, duty in which he professionally wrote three books on the topic ""Cesar's way"" ""Be the pack leader"" and ""Member of the family"", he reach worldwide popularity with his TV series ""The dog Whisperer"", this name would be the new way people knew him, he died this morning in Santa Clarita hospital in California. +Millan was hospitalize yesterday afternoon, the medical reports indicate that he suffered a fulminate heart attack, which paralyze his heart unavailable for the blood to reach his brain, and other vital organs, situation witch cause the death of this humanitarian man, who years before open his foundation ""Cesar Millan Foundation"", where Jada Pinkett Smith, wife of Will Smith, is Vice-president. +? + + +The hoax that was circulated as a death notice issued by the grieving family stated that +""the sad news of Millan's death was given by his wife Jahira Dar in a news conference, a couple of hours ago, where she said to the media, 'I hope you can understand my loss, and I would appreciate if you can give us our space for our mourning.'"" +The report, however, was soon rubbished by many. A Mexican news source, Monitor National, stated that the ""misinformation caused great impact and controversy in social networks"" as thousands of his fans started grieving for their favourite dog trainer. +The worried admirers of Cesar Millan can now rest assured that the 'dog whisperer' is safe as he has been seen active, both on his Facebook and Twitter accounts. +A self-taught dog trainer, the Mexican American TV show host, is widely known for his television series, Dog Whisperer with Cesar Millan, which is televised in more than 80 countries worldwide from 2004 to 2012. +Social Media Reactions on Cesar Millan Death Hoax: +An admirer, Susanne Nilsson, commenting on a recent post by Cesar Millan, said:"" I hope u safe and well Cesar. Please comfirm that this News are fake..I only have one idol and thats you..Big hugs from Sweden"" +Meanwhile, Invisible Man ‏@CHADinAMSTERDAM posted: ""RIP to Cesar Millan. Dude always came across as good folks."" +Kerem Soyyilmaz ‏@keremsoyyilmaz said: ""Rest in peace beautiful man, this is sooo early. With love, your dog friend @cesarmillan "" +Another fan, Aimee ‏@AmyL618, said: It's a hoax right? Someone please tell me @cesarmillan is okay and not dead. I love him and he changed my life. I need the truth.","1" +"The news of Cesar Millan's death is false","Celebrity Dog Cesar Millan should have died, according to a post on the site noticiasunam.com. But there are many obvious oddities in the post - Viral Inspector shows why it probably is fake. + +TV Personality and hunduppfostraren Cesar Millan has died of a heart attack, reports the site noticiasunam.com . The news has been widely adopted - just over 17,000 interactions on Facebook accordance sharedcount.com - and shocked many. ""Oh, becomes so sad. Rest in paradise Cesar Millan! ""Writes one of many Swedes who have turned to Facebook to express their condolences. + +But they probably unnecessarily. It is unclear what exactly noticiasumam.com is a kind side, but a reputable news source, it is at least not. + +To begin with, there are many warning signs about the article itself if Millan's death. It is the Hispanic-side single article in English, and has under its byline written by Frank William Abagnale, a famous forger of checks whose lives laid the basis for the movie ""Catch Me If You Can"". And whatever Abagnale do nowadays so it's probably not writing for noticiasumam.com. + +Additionally, it stated the source of the claim to be a press conference with Millan's wife, Jahira Dar. Searches shows that this press conference is not mentioned anywhere else than right on noticiasumam.com, which almost certainly means that the conference never even took place. To make doubly sure is Jahira Dar and Cesar Millan not actually married, at least according to a mingling article in the Daily Mail from November 23. + +According to the article, Millan have been put in the hospital ""yesterday afternoon"", ie on Tuesday. But the night of Wednesday, Swedish time appeared still up happy tweets and status updates on Millans Twitter - and Facebook feeds - the last came as late as an hour before the site's article was published. Cesar Millan has a television program on the National Geographic, nor where there any information about his death. + +If there are rumors about a celebrity death so you should always wait until they are confirmed by a close relative or associate of the person, in an interview with a credible source. In the case of Millan, there is no such confirmed data, and both Indian International Business Times as Dutch De Telegraaf warns that page that published the news is not credible. + +Viral reviewer can therefore conclude that the source of the allegation of Cesar Millan's death is not credible. Although Millan's team have not directly denied the information we dare say he most certainly not dead. We have searched his team for comment.","1" +"Web Portal publishes death of ""Dog Whisperer""","It is not the first time in social networks, some news spreads false information of celebrities. + + + +cesar_MN +Mexico City Social networks do his thing again, the ProcesoMX website announced the tragic news of the death of the famous ""Dog Whisperer"" Cesar Millan, this morning after suffering a cardiac arrest fulminate. +Misinformation caused great impact and controversy in social networks, causing a sad time, while no major media spread such lies. +This part of the note: +""The famous"" Dog Whisperer ""Cesar Millan, died this morning after suffering a cardiac arrest fulminate."" +""The Mexican, 45, a native of La Cruz, Sinaloa, who became famous for his incredible techniques rehabilitation and training of dogs, in their professional work be allowed to write three books on these topics (The Way of Caesar, Be the pack leader and a member of the family), becoming famous for the TV series ""The Dog Whisperer"" whose name was stayed as pseudonym, died this morning at a hospital in Santa Clarita, California "" +It is not the first time in social networks, a note is disseminated false information, celebrity who lost their lives, so before believing a note you must validate the source, to avoid falling into error. +encantador_MN","1" +"China: Satirical site warns citizens over name choices","A satirical website has poked fun at the Chinese practice of choosing alternative English names, in a report urging citizens to think carefully before making their decision. + +The site, which is done in the style of the state-owned CCTV website, warns people against picking a name that could cause offence, or simply make no sense at all. Many Chinese people prefer to use an English name, particularly if they conduct business with the West. But the satirical site suggests people should avoid fictional characters, names with the potential for sexual innuendo, or random words like Dragon, Fish or Lawyer, which could come back and haunt you ""if you want a call back from that serious law firm in America"". + +An English name should ""come with a 'feeling' or idea about what sort of person you are, and where you come from"", so names such as Satan or Dumbledore are out, the website says. Women are told to think carefully about ""food"" names such as Candy, Lolly or Sugar, which might be seen as ""stripper names"". There's also a lengthy warning about names with sexual connotations, especially when used in conjunction with Dong or Wang, which ""are used as slang for male genitalia... so avoid anything like 'Bunny Wang' at all times,"" the website says. Instead, a ""traditional"" name like Elizabeth, Catherine, William or George is considered a good choice. ""Pick one of these if you're looking for a 'safe' English name, often with implications of wealth,"" the website advises. + +Correction 9 December 2014: An earlier version of this story said the post came from the official CCTV website. The post was actually from a satirical news site. + +Use #NewsfromElsewhere to stay up-to-date with our reports via Twitter.","1" +"How did Fake Chinese News Site Dupe Washington Post, Atlantic, BBC?","Multiple news outlets including the Washington Post and the BBC were duped by a fake news site posing as Chinese public broadcaster CCTV. + +The Oct. 19 phony story was headlined ""Tips for Chinese choosing an English name."" + +It lists as good names ""'proper' traditional names"" like Elizabeth, Michael and William. No-no names include ""Surprise, Dragon, Fish [and] Lawyer,"" as well as ""food as a name"" such as Apple or Candy. Other names you may not want to use include ""Obama, Einstein or Madonna,"" but common celebrity names like Nicole (from Nicole Kidman) are OK. Other bad names the site lists are ""Hercules, Satan, Dumbledore or Jesus."" + +A screenshot detail of the article is below + + + +The real CCTV English-language news site is at the web address www.english.cntv.cn. Below see a screenshot. + + + + + +When you go to the Chinese language version of the site and click on English language version, you are taken to that page. + + + + + +The fake site is at: www.cctvnews.cn. See a screenshot below from July in the WayBack Machine. + + + +The About Page for the satire site reads: ""Official website for CCTV NEWS, An English language news channel of China Central Television (CCTV), the nation’s largest national broadcasting network."" + +The satirical site has pubished numerous stories but not nearly as many as the real English-language version of the CCTV site, which is loaded with articles. Other headlines on the fake site include: + +""Hunan 'color ride': another fantastic opportunity for gratuitous flesh"" +""Taiwan cooking oil made from 'kitchen waste' and grease"" +""Does Buddhist music help crops grow"" +""How would it feel dining in a prison restaurant"" +The satire article on English names has apparently been removed. Links for the article and other articles go to an error page. The actual website's homepage says ""Our website is under construction, coming up soon."" + + + + + + + +Only One Duped Outlet Corrected, 2 more Correct after iMediaEthics inquiry + +The Washington Post was duped by the naming story, but posted a correction to acknowledge it was tricked. + +The Oct. 20 Washington Post story's correction reads: ""Correction: An earlier version of this story reported that the original post was from CCTV. It was, in fact, by a satirical news site."" + + + +Its headline now reads ""Satirical news site attacks China’s weird English names"" and the story characterizes the CCTVnews.cn story as ""a humorous report on a satirical Web site done in the style of China's state broadcater CCTV."" + +iMediaEthics has written to the Post reporter to ask how he learned of the error. + +iMediaEthics asked four other outlets if they would follow suit and correct their articles. + +The BBC's Oct. 20 story, ""China: Don't call yourself Dumbledore."" +The Telegraph's Oct. 21 story, ""Chinese advised to choose British-sounding names to get ahead"" +The Atlantic's Oct. 20 story ""The Chinese Guide to Avoiding a Bad English Name"" +Buzzfeed Oct. 21 story, ""Chinese State Media Warns People To Stop Calling Themselves Dumbledore,"" +BuzzFeed told IMediaEthics by e-mail it would correct. The following update is atop the article now: + +""This story was a hoax written by a site which appeared to be the English-language website of the Chinese state-run broadcaster, CCTV. And we fell for it. + +""The original blog post, which was cited by us and other publishers, was published at cctvnews.cn. The fake site used CCTV’s logo and embedded tweets from the official @CCTVNEWS Twitter account. + +""The actual URL of CCTV English is english.cntv.cn. + +""However, an internet directory search shows that the fake CCTVNews site – which is now offline – is based in Hangzhou, 1,300 miles from CCTV’s real headquarters in Beijing. Dec. 8, 2014, at 4:28 a.m."" + +The BBC didn't respond to iMediaEthics' inquiry, but within days of our e-mail asking if the BBC would correct, it did just that. + +The BBC re-wrote its article to be headlined, ""China: Satirical site warns citizens over name choices."" The following correction was added: + +""Correction 9 December 2014: An earlier version of this story said the post came from the official CCTV website. The post was actually from a satirical news site.""","1" +"Satirical news site attacks China’s weird English names","A humorous report on a satirical Web site done in the style of China's state broadcaster CCTV offers advice to Chinese on how to choose their English names. ""English names come with different connotations. It’s not always fair to those people, but they do,"" the article warns. ""A name can come with a ‘feeling’ or idea about what sort of person you are, and where you come from."" + +The adoption of unconventional English names in China and other parts of East Asia is the source of perennial fascination and mirth among expats. Any young Anglophone who teaches English in the region could rattle off a host of perplexing names he or she had to call out during class. + +One friend of WorldViews who taught English and civics in the southern Chinese city of Guangzhou had a number of students whose chosen English names were derived from screen names used during online computer games. There was Orcapm, who was not to be outdone by Skycoolz. + +""Sure, have fun and pick a random object or word as a name, but avoid them if you want a call back from that serious law firm in America,"" the post chides. It offers this guide: + +A good way to work out the ‘feeling’ of a name is to watch a bunch of American movies and sitcoms. They’re full of name stereotypes — you’ll find the good girls’ are all ‘Jane’s, the jock boys’ are still ‘Buds’ and the geeks’ are called ‘Sheldon’. + +The report also lays out a set of rules governing the types of English names typically adopted by Chinese. Be careful about what may sound inappropriate alongside common Chinese family names such as Wang or Dong. In general, it's good to avoid food as a name, it suggests. + +To put bluntly, names like Candy, Lolly, Sugar (think anything sweet), are typically thought of as ‘non-smart girl’ names, or ‘stripper’ names. + +It’s not always right; there are doubtless some very smart Candy’s out there. But it’s the first thing that comes to mind. + +Other instructions include eschewing the names of famous leaders or celebrities. ""Pick any name like Obama, Einstein or Madonna and you’re going to get some stares,"" it says. ""You have some pretty big shoes to fill there."" + +At a McDonald's restaurant in Hong Kong, WorldViews once was served by an employee whose badge confusingly read ""Franco Mussolini."" One hopes he didn't harbor similar dreams of power and domination. + +While it's easy to make fun of such unusual naming conventions, it's also hard not to appreciate the playfulness with which these names get chosen. Often, Chinese people pick an English name as a play of words based on their original given Chinese name. The Atlantic offers a few examples from the Cantonese-speaking city of Hong Kong: + +Many English names mimic the sound of Chinese given names. A solicitor called Tse Kar-son, for example, has Carson as his English name. Singer Lee Hak-kan's English name is Hacken. Another singer, Chan Yik-shun, is called Eason... + +Ho Wai-leuk, a journalist, got his name another way. ""When I was a student, everyone kept saying my Chinese name really fast until it started sounding like 'hoh lok,'"" he said referring to the Cantonese pronunciation for Coca-Cola, ""so Cola stuck."" + +For most people, our names are our names and we have little choice in the matter. But the practice of adopting a new English name can be seen as an exercise in self-expression, especially in societies where larger trends of conformity hold some sway. + +Who wouldn't want to be able to re-brand themselves or be able to highlight some unique part of their identity? Just don't use that power to call yourself ""Bunny Wang,"" the post says. + +Correction: An earlier version of this story reported that the original post was from CCTV. It was, in fact, by a satirical news site.","1" +"Comcast calls rumor that it disconnects Tor users “wildly inaccurate”","Comcast has lately found itself issuing public apologies on a somewhat regular basis as subscribers share tales of horrible customer service. + +But the latest accusation leveled against Comcast—that it is threatening to disconnect customers who use the anonymity-providing Tor browser—hasn't been backed by convincing evidence that it's happening. And Comcast dismisses the rumor as “wildly inaccurate.” + +It began Saturday with a site called DeepDotWeb claiming that Comcast has “declared war on Tor Browser.” + +“Reports have surfaced (Via /r/darknetmarkets and another one submitted to us) that Comcast agents have contacted customers using Tor and instructed them to stop using the browser or risk termination of service,” the article said. “A Comcast agent named Jeremy allegedly called Tor an ‘illegal service.’ The Comcast agent told its customer that such activity is against usage policies. The Comcast agent then repeatedly asked the customer to tell him what sites he was accessing on the Tor browser. The customer refused to answer. The next day the customer called Comcast and spoke to another agent named Kelly who reiterated that Comcast does not want its customers using Tor.” + +“Kelly” allegedly told the customer that “Users who try to use anonymity, or cover themselves up on the Internet, are usually doing things that aren’t so-to-speak legal. We have the right to terminate, fine, or suspend your account at anytime due to you violating the rules.” + +“I think the story is nonsense” + +There was good reason to be skeptical of this report. A search of the subreddit /r/darknetmarkets for Comcast and Tor turned up nothing. (UPDATE: Here is the reddit post quoted by DeepDotWeb.) Any organized Comcast campaign against users of Tor would likely inspire numerous customer complaints, not just a few, as noted by Cato Institute Research Fellow Julian Sanchez and security researcher Robert Graham, who wrote on Twitter: + + +""This story is wildly inaccurate,"" Comcast spokesperson Charlie Douglas told Ars. ""Customers are free to use their Xfinity Internet service to visit any website or use it however they wish otherwise."" + +While Comcast publishes an acceptable use policy, the company ""doesn’t monitor users’ browser software or Web surfing and has no program addressing the Tor browser,"" Douglas said. + +In some previous cases where customers have documented poor customer service, Comcast has admitted fault and said its customer service agents acted in error. In this case, Comcast says it investigated the story and found no evidence that the encounters ever happened. + +""The anecdotal chat room evidence provided is not consistent with our agents’ messages and is not accurate,"" Douglas said. ""Per our own internal review, we have found no evidence that these conversations took place, nor do we employ a Security Assurance team member named Kelly. We respect customer privacy and security and only investigate and disclose certain information about a customer's account with a valid court order or other appropriate legal process."" + +Comcast's Jason Livingood, VP of Internet communications and engineering, also disputed the report in a blog post today. ""Our customers can use Tor at any time, as I have myself. I’m sure many of them are using it right now,"" he wrote. + +The DeepDotWeb report has other problems. It falsely stated that ""Comcast already monitors its customers internet usage to prevent them from downloading pirated media in violation of copyright laws. Under the 'Six Strikes' plan, Comcast customers who are caught by Comcast pirating copy-written material are e-mailed by Comcast and told to cease the activity. Comcast will continue monitoring them, and if they violate the 'Six Strikes' plan five more times, their Internet service will be terminated."" + +In fact, Six Strikes reports are the result of content companies monitoring online activity and notifying Internet service providers of potential violations. Comcast says it uses e-mail and in-browser alerts to ""educate"" customers about copyright violations, but it doesn't cut off service. Nonetheless, the DeepDotWeb report was credulously re-reported by a few other news outlets that didn't seek further confirmation. The stories are being shared by Twitter users, who often add expressions of outrage: + + +Tor isn't for criminals + +Tor Project Executive Director Andrew Lewman told Ars that it doesn't have enough information on the Comcast rumors ""to know whether this is a company-wide practice."" He noted that ""people with uncensored connections to the Internet can use Tor to share their access with human rights defenders and journalists behind national firewalls. We tend to have good relationships with Internet service providers in free societies for this reason."" + +Tor itself was unfairly branded ""the Web browser for criminals"" by one news report: + + +Enlarge +Business Insider +While Tor can be used by criminals, it was created by the US Naval Research Laboratory to protect government communications and is used by many people with privacy concerns, including activists in countries with repressive governments. For anyone hoping to use Tor to mask downloads of pirated material, the Tor Project itself says that ""File sharing (peer-to-peer/P2P) is widely unwanted in the Tor network, and exit nodes are configured to block file sharing traffic by default."" (Comcast was caught interfering with BitTorrent traffic in 2007.) + +If the customers described by DeepDotWeb did have discussions with Comcast employees, it's possible they were being notified of a pending legal action. DeepDotWeb quoted Comcast as saying, ""if we’re asked by a court to provide customer information, then we ask for a reasonable amount of time to notify the customer so they can decide if they would like to hire a lawyer and if they do, then we turn the case over to them and they proceed with the judge directly and we step away."" + +Douglas told Ars that ""it's impossible to speculate"" whether that's what happened in this case, since the reports mentioned no specific customers. + +If any Ars readers are subscribers of Comcast and use the Tor browser, we'd love to hear about your experiences in the comments.","1" +"Setting the record straight on tor","On Monday morning, a report surfaced claiming that Comcast has been discouraging customers from using the Tor Browser, a browsing program designed to allow users to surf the Internet with greater anonymity than most browsers. Monday’s report was repackaged on a number of other sites, stating that Comcast has ""declared war on the Tor Browser."" The report goes on to suggest that Comcast has contacted some users telling them that they risk disconnection if they continue using Tor. The report may have generated a lot of clicks but is totally inaccurate. + +Comcast is not asking customers to stop using Tor, or any other browser for that matter. We have no policy against Tor, or any other browser or software. Customers are free to use their Xfinity Internet service to visit any website, use any app, and so forth. + +Here are the facts: + +Comcast doesn’t monitor our customer’s browser software, web surfing or online history. + +The anecdotal chat room evidence described in these reports is not accurate. + +We respect customer privacy and security and only investigate and disclose certain information about a customer's account with a valid court order or other appropriate legal process, just like other ISPs. More information about these policies can be found in our Transparency Report here. + +We do not terminate customers for violating the Copyright Alert System (aka ""six strikes""), which is a non-punitive, educational and voluntary copyright program. Read more here. + +Our customers can use Tor at any time, as I have myself. I’m sure many of them are using it right now.","1" +"Comcast Denies It Will Cut Off Customers Who Use Tor, The Web Browser For Criminals","Some users of the anonymous web browser Tor have reported that Comcast has threatened to cut off their internet service unless they stop using the legal software. + +Comcast completely denies their claims. In a blog post, the company said ""We have no policy against Tor, or any other browser or software. Customers are free to use their Xfinity Internet service to visit any website, use any app, and so forth."" + +According to a report on Deepdotweb, Comcast customer representatives have branded Tor ""illegal"" and told customers that using it is against the company's policies. + +Tor is a type of web browser that, in theory, makes all your internet activity private. The software routes traffic through a series of other connected internet users, making it difficult for governments and private companies to monitor your internet usage. Up to 1.2 million people use the browser, which became especially popular after Edward Snowden leaked information showing that the NSA was eavesdropping on ordinary citizens. Prior to that, Tor had been popular among people transacting business on Silk Road, the online market for drugs and hitmen. + +The problem is that downloading or using Tor itself isn't illegal. Plenty of people might have legitimate reasons to want to surf the web in private, without letting others know what they were looking at. But Tor has been pretty popular with criminals. + +Some Comcast reps allegedly begun telling users that it is an ""illegal service."" One Comcast representative, identified only as Kelly, warned a customer over his use of Tor software, DeepDotWeb reports: + +Users who try to use anonymity, or cover themselves up on the internet, are usually doing things that aren’t so-to-speak legal. We have the right to terminate, fine, or suspend your account at anytime due to you violating the rules. Do you have any other questions? Thank you for contacting Comcast, have a great day. + +Comcast customers, speaking to Deepdotweb, claimed that Comcast repeatedly asked them which sites they were accessing using Tor. + +In a statement to Business Insider, Comcast refuted the claims made in Deepdotweb, stating that they had launched an internal review into the discussions reported above: + +Customers are free to use their Xfinity Internet service to visit any website or use it however they wish otherwise. Like virtually all ISPs, Comcast has an acceptable use policy or AUP that outlines appropriate and inappropriate uses of the service. Comcast doesn’t monitor users’ browser software or web surfing and has no program addressing the Tor browser. he anecdotal chat room evidence provided is not consistent with our agents’ messages and is not accurate. Per our own internal review, we have found no evidence that these conversations took place, nor do we employ a Security Assurance team member named Kelly. Tor’s own FAQs clearly state: 'File sharing (peer-to-peer/P2P) is widely unwanted on Tor' and 'BitTorrent is NOT anonymous' on Tor. + +Read Comcast's full statement here. + +SEE ALSO: A Comcast Customer Tried To Cancel His Account But Was Put On Hold Until Comcast Closed For The Day","1" +"Comcast Says You Can Keep Your Tor","Reports that Comcast will deny Internet service to users of the Tor Internet browser are false, the company says in a new blog post. The browser lets users surf the web with a higher degree of anonymity, making it more difficult for hackers (or the government) to follow them around the Internet. + +Comcast’s Jason Livingood wrote in today’s post: + +Comcast is not asking customers to stop using Tor, or any other browser for that matter. We have no policy against Tor, or any other browser or software. Customers are free to use their Xfinity Internet service to visit any website, use any app, and so forth. + + +Here are the facts: + +Comcast doesn’t monitor our customer’s browser software, web surfing or online history. + +The anecdotal chat room evidence described in these reports is not accurate. + +We respect customer privacy and security and only investigate and disclose certain information about a customer's account with a valid court order or other appropriate legal process, just like other ISPs. More information about these policies can be found in our Transparency Report here. + +We do not terminate customers for violating the Copyright Alert System (aka ""six strikes""), which is a non-punitive, educational and voluntary copyright program. Read more here. + +Livingood concluded: ""Our customers can use Tor at any time, as I have myself. I’m sure many of them are using it right now.""","1" +"The Whole Internet Is Waiting For This Pic Of A Monster 50-Foot Crab To Be Declared A Hoax","A giant crab photographed in a harbour mouth in Kent, UK, is proving a great drawcard… for the website that’s claiming it’s a giant crab. + +Weird Whitstable curator Quinton Winter believes he lives in the UK’s weirdest town and hosts a collection of pics and reports on his website to prove it. + +But even he couldn’t believe this aerial photograph of a 50-foot crab lurking in the shallows off the harbour: + + +Crab, sandbank, or Photoshopping idiot? Picture: Weird Whitstable +So he went to check it out for himself. + +“At first all I could see was some faint movement, then as it rose from the water I thought, ‘that’s a funny looking bit of driftwood’,” Winter said. + +“It had glazed blank eyes on stalks, swivelling wildly and it clearly was a massive crab with crushing claws. + +“Before this incident I thought the aerial photo showed an odd-shaped sand bank. Now I know better.” + +Oh, internet. As great as it would be for this to be genuine, we’re counting down to the hoax bust in 3… 2… 1… but secretly hoping it’s real.","1" +"Is 'Crabzilla' real or not? Leading marine biologist rules picture of giant crab lurking in shallow waters must be a HOAX","A marine biologist has killed off claims that a giant crab is living on the Kent coast - insisting the image is probably a well-doctored hoax. + +Residents of Whitstable were left shocked when a photo emerged appearing to show a huge crustacean just yards from the coastal town's harbour. + +But sea-life expert Dr Verity Nye, who has worked on logging new species of crab, says it is impossible one of the creatures could grow so big. + +This image of Whistable harbour from above led to claims that a 'Crabzilla' could be living off the Kent coast + +The image (left) appears to show a crustacean the length of five or six boats lurking in the Thames Estuary, but marine biologist Dr Verity Nye (right) says the picture is a hoax + +Dr Nye, an Ocean and Earth Science researcher at the University of Southampton, said: 'The idea of a giant ""crabzilla"" would very exciting. Unfortunately, I think this is a hoax. + +'I don't know what the currents are like around that harbour or what sort of shapes they might produce in the sand, but I think it's more conceivable that someone is playing about with the photo.' + +She added: 'The UK does have large crabs. The biggest is the spider crab which can grow up to 1.2 metres in size, but they tend to stay in much deeper water, about 1,000-metres deep, and are a different shape from the image in this photo. + +'Crabs with a ""pie crust edge"", like the one in the crabzilla image, are known as edible crabs, or Cancer pagarus, but tend only to grow to about 20 to 30 centimetres.' + +Mocked-up photos poking fun at the idea of a Crabzilla were posted on Twitter after the image emerged + +The largest crabs in British waters are spider crabs, which live in waters between 10 and 1,000 metres deep + +Edible crabs, shaped like the one in the aerial photo of Whitstable, grow to only 30 centimetres long + +Dr Nye added: 'The largest crabs in the world are Japanese Spider Crabs, which can grow to about 3.7 metres in size, about as big as a small car, but again, they tend to stay in deep water and don't come ashore. + +'Crabs are amazing because they are so diverse, we have about 60 species around the UK, and it is not inconceivable that new species could be found, but I laughed when I saw this picture.' + +The photograph of the apparent 50ft crustacean was originally posted on a blog called Weird Whistable, a collection of strange and unusual sightings in the town. + +The image has sparked a rash of less believable online images, with Twitter users mocking up their own pictures of giant claws emerging from the water.","1" +"Five reasons 'Crabzilla' is definitely not real","Leading invertebrate researcher says ""a hoax is an understatement"" of photograph appearing to show a colossal crustacean basking off the Kent coastline + +A fifty-foot crab dwelling somewhere off the English coast is a thing of nightmares. + +The shadowy figure of a colossal crustacean, apparently spotted in the murky waters of Whistable, in Kent, dwarfs boats and cars on the pier it lurks besides. + +A satellite picture of the so-called crab, aptly dubbed ‘Crabzilla’, has gone viral after first surfacing on Weird Whitstable, a website for the supernatural curated by illustrator Quinton Winter, which deals in “phantoms, mysteries, tall tales, and artefacts”. + +The creature is depicted in the coastal town’s harbour, which is a popular spot for children to go crabbing in the summer. + +But those suffering from ostraconophobia (that’s fear of shellfish to you and me) needn’t be left gasping for air, because invertebrate expert Paul Clark at the Natural History Museum in London has branded the photo a hoax. + +""I had a good giggle about it - it's ridiculous,"" he said, adding that it ""is definitely not real."" + +Here's why: + +1. The largest crabs in the world are thought to be Japanese spider crabs - also known as Macrocheira kaempferi - which can grow to the size of a small car with an impressive leg span of up to twelve feet. However, these crabs live in deep, cold water around Japan and are a completely different shape. + +2. Another huge crab with a more similar shape to the one in the picture is the Tasmanian giant crab, also known as Pseudocarcinus gigas. These are the world's heaviest crabs but they reside in the southern waters of Australia at depths of 20-820 metres. + +3. Mr Clark did not think that the crab was a representation of Cancer pagurus, also known as the edible crab, either because of a slightly different shape. And anyway, these tend to only grow to a maximum of 30 centimetres. + +4. Instead, he said that the crab looked more to him like a shore crab (Carcinus maenas) - cleverly Photoshopped on to a satellite image. ""A hoax is an understatement. A shore crab gets up to two inches - if you're lucky!"" he said. + +5. Internet hoax debunkers have also been on the case, with a user from ThatsNonsense.com pointing out that the the image of the harbour was taken from Bing maps, sans crustacean in the original satellite photograph, of course.","1" +"Brian Williams Debunks Peeing Meteorologist Report On ‘NBC Nightly News': Video","When a report went viral that NBC meteorologist Mike Seidel got caught on camera peeing in the woods during a live weekend appearance with Lester Holt, NBC News decided Brian Williams needed to discuss it on NBC Nightly News tonight. Yes, it’s come to this.","1" +"Brian Williams Insists NBC News Meteorologist Did Not Pee in the Snow While on Air","For everyone out there who believed NBC Nightly News meteorologist Mike Seidel peed in the snow while on-camera, Brian Williams has some stern words for you and your ""social media."" + +Williams took time out of his broadcast last night to set the record straight, explaining that when Seidel lost communication with the station during a live report from a winter storm in North Carolina, he took his gloves off and dialed his phone. He did not, as some places report, ""write his name in the snow"" in urine. + +Thanks for letting us know, Bri.","1" +"‘Wild Misinformation’: Brian Williams Explains the Mike Seidel Liveshot","Brian Williams took a moment on Monday’s “NBC Nightly News” to push back on a social media dustup over a Saturday night liveshot that didn’t quite happen. Mike Seidel appeared on camera Saturday night with his back turned, leading some to speculate the reporter may have been relieving himself. + +No so, geniuses: + +Social Media owes our friend Mike Seidel an apology. The intrepid and fearless Weather Channel Meteorologist was the victim of some wild misinformation when this happened on the news here Saturday night: Lester Holt threw to Mike’s live report in a snowstorm in North Carolina. Mike had lost cellphone contact with our control room.. so he couldn’t hear through his attached earpiece that he was on the air. He put his back to the storm and the camera.. he had to take off his gloves and re-dial his phone which was tethered to his ear, that’s when the rumors hit the web that he was perhaps writing his name in the snow. It was just Mike working to make it right — which is why we all love working with Mike Seidel.","1" +"Brian Williams: No, Our Meteorologist Was Not Peeing on Live TV","Brian Williams took a moment during Monday’s edition of NBC Nightly News to address a very important issue. As the anchor said, social media, as well as a few news websites, owes meteorologist Mike Seidel an “apology” after some “wild misinformation” circulated about what he was doing during a live appearance with Lester Holt over the weekend. + +Williams explained that Seidel has lost communication with the NBC station and couldn’t hear Holt through his earpiece so he turned his back to the camera, took off his gloves and redialed his phone to connect for the segment. + +“That’s when the rumors hit the web that he was perhaps writing his name in the snow,” Williams said. “It was just Mike working to make it right, which is why we all love working with Mike Seidel.” + +But, of course, that explanation is far less hilarious and would likely generate almost zero clicks. + +Watch video below, via NBC: + +[Photo via screengrab] + +– – + +>> Follow Matt Wilstein (@TheMattWilstein) on Twitter","1" +"Weather Channel’s Mike Seidel was not caught with his pants down","The Weather Channel’s Mike Seidel has taken a lot of ribbing about what he was doing live on network TV this weekend. But he didn’t do what online news sites and YouTubers suggest he did. + + + +Seidel was reporting from Sugar Mountain, North Carolina Saturday where an early season storm dropped 10 inches of snow. NBC Nightly News anchor Lester Holt introduced Seidel while the meteorologist’s back was turned to the camera. Seidel was hunched over fiddling with something. To an awful lot of people who saw Holt dump out of the live shot, it appeared Seidel was zipping up his pants, having answered nature’s call. + + +The NY Daily news headline taunted, “NBC meteorologist Mike Seidel appears to relieve himself during broadcast.” + +But that is not what happened at all, said Shirley Powell, the Weather Channel’s spokesperson. Seidel, she said, was using his cell phone as an IFB (that is short for interruptible feedback) which is how reporters in the field get their cues from the control room. The phone lost its signal just as the anchor was introducing the live shot. Powell told Poynter.org that Seidel yanked off his gloves, turned from the howling wind and was dialing the IFB when Holt tossed to him. Since Seidel didn’t have a phone signal, he didn’t know he was on the air. While he frantically dialed the phone, Seidel tucked his heavy gloves between his knees to keep them from blowing away. When he finished dialing, he yanked his gloves back on and turned to the camera but Holt was already calling off the shot and moving on. Seidel was left hanging in the winter wind. + +“I’m glad for you to tell what really happened,” Powell told me. + +The crew was using a LiveU mobile live system, which is a backpack sized phone based transmitter andSeidel would not have had a live truck engineer who might have alerted the control room of the communication problem. We still don’t know why the producer in the control booth took the shot live on the air with Seidel turned away. + +On his Weather Channel bio page, Seidel is asked, “What is your most embarrassing moment on the air?” He answers “Do you want a list?” Whatever was on that list before now just took a back seat. And sadly for Seidel, the video will live forever online.","1" +"Brian Williams Demands Apology From Social Media Over Erroneous Urination Reports (Video)","The NBC News anchor clears the record on behalf of victimized Weather Channel meteorologist + +There was no urinating on Brian Williams‘ airwaves, and the “Nightly News” anchor asked for an apology from social media critics Monday night. + +See video: Brian Williams on Daughter's Peter Pan Role: ‘I've Listened to Those Damn Songs Since She Was 3' + +Williams explained a segment from the weekend that showed “Weather Channel” meteorologist Mike Seidel with his back to the camera in a position that led to rumors he was urinating while unaware he was on-camera. + +Also read: Nielsen's Colossal Screw-Up Strips ABC's David Muir of Ratings Win Over NBC's Brian Williams + +“Social media owes our friend Mike Seidel an apology,” Williams said. “The intrepid and fearless Weather Channel meteorologist was the victim of some wild misinformation,” he continued. + +Apparently viewers on social media thought Seidel was “writing his name in the snow.” In reality, Williams explained, Seidel lost contact with the NBC control room. He was hunched over dialing NBC–not relieving himself. + +See video: Brian Williams Reveals a Hilarious ‘Bachelorette’ Obsession + +Vindicated, and it feels so good.","1" +"Dog Found Abandoned With Suitcase Filled With His Belongings","A dog was found abandoned at a Scottish train station next to a suitcase filled with it's belongings and now the local animal welfare charity are looking for tips into who is the neglectful owner. + +The dog, a male shar-pei named Kai, was found sitting with a leash attached to a banister at the Ayr railway station on Jan. 2, according to the Scottish Society for Prevention of Cruelty to Animals. + +""Kai is around two to three years old and is a lovely dog with a nice nature,"" Scottish SPCA Inspector Stewart Taylor said in the group's release. + +Amazing Animals From Around the World +The group reported that the suitcase contained a dog bowl, food, a pillow and toy -- although that doesn't clear the owner from wrongdoing. + +Abandoning an animal is an offense in Scotland and, if they are able to determine who left the dog in the station, that person or persons could be banned from owning animals for life. + +""Regardless of the fact Kai was left with his belongings, this was still a cruel incident and we are keen to identify the person responsible,"" Taylor said. + +Officials were able to determine the dog's name because the animal had been microchipped by a previous owner. When they contacted that individual, he reported that he had sold the dog in 2013 but did not have any information on the new owner. + +Taylor said that the group will care for the dog until they find an owner for Kai.","1" +"Dog abandoned at Ayr station with belongings in suitcase","An animal charity is attempting to trace the owner of a dog that was abandoned at a railway station with its belongings in a suitcase. + +The male Shar-Pei crossbreed was discovered tied to a railing outside Ayr station on 2 January. + +The suitcase included the dog's pillow, toy, food bowl and food. + +The Scottish SPCA traced a previous owner through the dog's microchip but were told it was sold in 2013 to someone they did not have details for. + +Inspector Stewart Taylor said: ""The dog is micro-chipped and we were able to find out his name is Kai. + +""We contacted the owner registered to the microchip, who stated they had sold Kai on Gumtree in 2013. + +'Cruel incident' + +""Unfortunately they could not tell us the address of the person who bought him."" + +Insp Taylor said the case highlighted the potential consequences of selling an animal online. + +He said buyers often included people acting on impulse who knew very little about animals. + +He added: ""Regardless of the fact Kai was left with his belongings, this was still a cruel incident and we are keen to identify the person responsible. + +""If anyone can help we would ask them to get in touch as soon as possible. + +""Kai is around two to three years old and is a lovely dog with a nice nature. We will look after him until we can find him a permanent and loving home."" + +The charity reminded pet owners that abandoning an animal is an offence under the Animal Health and Welfare (Scotland) Act 2006.","1" +"This Dog Was Left At A Railway Station With A Suitcase Of His Belongings After He Was Sold On Gumtree","The Scottish SPCA posted this picture to its Facebook page this afternoon. + +The charity said the dog was found on Friday evening tied to railings at Ayr railway station along with a suitcase full of his belongings, which included a pillow, a toy, a food bowl, and food. + +The charity added: “The 2–3-year-old Shar-Pei cross is microchipped and we were able to find out his name is Kai.” + +Scottish SPCA inspector Stewart Taylor said: + +The dog is microchipped and we were able to find out his name is Kai. + +We contacted the owner registered to the microchip, who stated they had sold Kai on Gumtree in 2013. Unfortunately they could not tell us the address of the person who bought him. + +This case highlights the potential consequences of selling an animal online as it often leads to the impulse buying of pets that people know very little about. + +Regardless of the fact Kai was left with his belongings, this was still a cruel incident and we are keen to identify the person responsible. If anyone can help we would ask them to get in touch as soon as possible. + +Kai is around two to three years old and is a lovely dog with a nice nature. We will look after him until we can find him a permanent and loving home.","1" +"Dog abandoned at Scottish rail station with suitcase full of belongings Read more: http://www.ctvnews.ca/world/dog-abandoned-at-scottish-rail-station-with-suitcase-full-of-belongings-1.2175026#ixzz3O9Shc1IO","The Scottish SPCA is appealing to the public for any information related to a dog that was found abandoned at a railway station along with a suitcase full of its belongings. +The dog, a male shar-pei crossbreed was found tied to a railing at Ayr Station, located in southwestern Scotland, last Friday. Next to the dog was a suitcase containing a pillow, toy, food bowl and food, the SPCA said in a statement Tuesday. +Scottish SPCA Insp. Stewart Taylor said the dog was microchipped, so the SPCA found out his name is ""Kai"" and was able to locate the dog's previous owner. +""We contacted the owner registered to the microchip, who stated they had sold Kai on Gumtree in 2013. Unfortunately they could not tell us the address of the person who bought him,"" Taylor said in the statement. +Taylor said the case highlights the many risks of selling an animal online. +""Regardless of the fact Kai was left with his belongings, this was a cruel incident and we are keen to identify the person responsible,"" he said. +The SPCA describes Kai as a ""lovely dog with a nice nature"" and estimates that he is between two to three years old. ""We will look after him until we can find him a permanent and loving home,"" it said in the statement. +Under the Scottish Animal Health and Welfare Act 2006, abandoning an animal is an offence. Anyone found guilty of abandoning an animal can be banned from keeping any animals for a period of time or for life. +Anyone with any information about the case is being asked to contact the Scottish SPCA helpline at 0300 999 999.","1" +"Hundreds of dog-lovers from around the world offer home to pet abandoned at the railway station with a suitcase containing his pillow, toy, bowl and favourite food","Hundreds of dog-lovers from Britain, the U.S., Canada and even the Philippines have offered to re-home a pet who was found abandoned at a train station with his own suitcase. + +Kai the Shar-Pei crossbreed is now the most popular dog in the Scottish SPCA's history after he was found tied to railings outside Ayr station on Friday with a case containing a toy, bowl, food and a pillow. + +The two-year-old is now doing well that the charity's rehoming centre in Glasgow, where staff have had more than 100 phone calls and more than 80 e-mails offering him a new home. + +Scroll down for video + +Lonely: Kai the Shar-Pei crossbreed was found at Ayr station with his toy, food and bowl in a suitcase + +Staff now face days of work to whittle down the flood of applications to find Kai one new owner after poignant photos of him went viral. + +Assistant manager Katrina Cavanagh said: 'We've had offers from America, the Philippines, Canada and England and we're trying to work our way through them. + +'We've had good responses in the past but this is off the scale. We've never had offers from the other side of the world before. + +'What we're saying to people is fill out a questionnaire, and Anna the manager and I will have a wee look through, whittle them down and make a decision. It'll be hard but we'll get there. + +'We just can't believe how big this became, but then, it's not every day you get a dog abandoned with his own suitcase.' + +Kai has been compared to Paddington bear after his ordeal, which has prompted an investigation by the animal welfare charity. + +Until it is complete, he will not be handed over to a new family, so it could be some time before he is adopted. + +He may also need surgery for entropions, inward-curling eyelids, which the charity will pay for. + +Ms Cavanagh added: 'He's loved the attention. He's been in and out of his kennel so many times being filmed and having his picture taken. He's a very happy boy and he's behaved perfectly. + +'We're also seeing a boost in donations. A lot of people have come here in person and mentioned him.' + +Animal welfare experts warned his owners could face a lifetime ban from keeping animals after the 'cruel' incident. + +Scottish SPCA inspector Stewart Taylor said: 'The dog is microchipped and we were able to find out his name is Kai. + +Cared for: Station staff looked after Kai until the Scottish SPCA arrived at the scene on Friday + +'We contacted the owner registered to the microchip, who stated they had sold Kai on Gumtree in 2013. Unfortunately they could not tell us the address of the person who bought him. + +'This case highlights the potential consequences of selling an animal online, as it often leads to the impulse buying of pets that people know very little about. + +'Regardless of the fact Kai was left with his belongings, this was still a cruel incident and we are keen to identify the person responsible. + +'If anyone can help we would ask them to get in touch as soon as possible. + +'Kai is around two to three years old and is a lovely dog with a nice nature. We will look after him until we can find him a permanent and loving home.' + +Station staff looked after Kai until the Scottish SPCA arrived at the scene on Friday. + +Abandoning an animal is an offence under the Animal Health and Welfare (Scotland) Act 2006. + +Anyone found guilty of doing so can be banned from keeping animals for a fixed period or life.","1" +"From the Philippines to Canada: Dog-lovers around the world offer home to abandoned Shar-Pei Kai - but carers say he will stay in Scotland after he turned up at train station","Hundreds of dog-lovers from Britain, the U.S., Canada, Spain and even the Philippines have offered to re-home a pet who was found abandoned at a train station with his own suitcase. + +Kai the Shar-Pei crossbreed is now the most popular dog in the Scottish SPCA's history after he was found tied to railings outside Ayr station with a case containing a toy, bowl, food and a pillow. + +Just like Paddington Bear, he was saved after a human took pity on him - and the two-year-old has since been lapping up the attention at the charity's rehoming centre in Glasgow + +Staff have received more than 100 phone calls and more than 80 e-mails offering him a new home. + +Scroll down for video + +Enjoying the attention: Kai the Shar-Pei crossbreed at the Scottish SPCA's rehoming centre in Glasgow + +Character: The charity has had more than 100 phone calls and 80 emails - but Kai (above) will stay in Scotland + +Assistant manager Katrina Cavanagh said Kai's success had taken staff by surprise. 'We just can't believe how big this became,' she said. 'But then, it's not every day you get a dog abandoned with his own suitcase' + +The delighted staff face days of work to whittle down the flood of applications after poignant photos of Kai went viral - but they insist the new owner will be in Scotland. + +Assistant manager Katrina Cavanagh said: 'We've had offers from America, the Philippines, Canada and England and we're trying to work our way through them. + +'We've had good responses in the past but this is off the scale. We've never had offers from the other side of the world before. + +'What we're saying to people is fill out a questionnaire, and Anna the manager and I will have a wee look through, whittle them down and make a decision. It'll be hard but we'll get there. + +'We just can't believe how big this became, but then, it's not every day you get a dog abandoned with his own suitcase.' + +Kai has been compared to Paddington bear after his ordeal, which has prompted an investigation by the animal welfare charity. + +Until it is complete, he will not be handed over to a new family, so it could be some time before he is adopted. + +Vow: The charity will rehome Kai in the country where he was found abandoned on railings at a train station + +New friends: Kai investigating the characters on a donations bucket for the animal rescue charity + +Hello! Kai in his new lodgings, which he has been in and out of constantly because of all the attention + +Grumpy? Kai needs surgery for entropions - inward-curling eyelids - but his fans have already raised the cash + +He also needs surgery for entropions, inward-curling eyelids, which the charity will pay for. + +There has been an enthusiastic response on social media, with even author Irvine Welsh tweeting: 'If I was in Ayr that boy would be coming home with Welshy. Yes he would! Yes he would!’ + +Seizing on the publicity, the Scottish SPCA set up a JustGiving page yesterday to raise the £1,000 needed for Kai's operation - and it has already raised almost double that. + +All leftover funds will go towards other animals in the care of the charity. + +Ms Cavanagh added: 'He's loved the attention. He's been in and out of his kennel so many times being filmed and having his picture taken. He's a very happy boy and he's behaved perfectly. + +'We're also seeing a boost in donations. A lot of people have come here in person and mentioned him.' + +Animal welfare experts warned his owners could face a lifetime ban from keeping animals after the 'cruel' incident. + +Scottish SPCA inspector Stewart Taylor said: 'The dog is microchipped and we were able to find out his name is Kai. + +Lonely: This photo of Kai the Shar-Pei crossbreed, who was found at Ayr station with his toy, food and bowl in a suitcase last Friday, was shared around the world and prompted an outpouring of generosity + +Cared for: Station staff looked after Kai until the Scottish SPCA arrived at the scene on Friday + +'We contacted the owner registered to the microchip, who stated they had sold Kai on Gumtree in 2013. Unfortunately they could not tell us the address of the person who bought him. + +'This case highlights the potential consequences of selling an animal online, as it often leads to the impulse buying of pets that people know very little about. + +'Regardless of the fact Kai was left with his belongings, this was still a cruel incident and we are keen to identify the person responsible. + +'If anyone can help we would ask them to get in touch as soon as possible. + +'Kai is around two to three years old and is a lovely dog with a nice nature. We will look after him until we can find him a permanent and loving home.' + +Station staff looked after Kai until the Scottish SPCA arrived at the scene on Friday. + +Abandoning an animal is an offence under the Animal Health and Welfare (Scotland) Act 2006. + +Anyone found guilty of doing so can be banned from keeping animals for a fixed period or life. + +Do you know Kai's previous owners? E-mail dan.bloom@mailonline.co.uk + +Good boy! Kai with senior animal expert Alan Grant. Staff hope to find him a new owner later this month + +One staff member said: 'We've had good responses in the past but this is off the scale. We're telling people to ill out a questionnaire, and Anna the manager and I will have a wee look through and whittle them down'","1" +"Hunt for 'cruel' owner who abandoned dog at train station","THE hunt is on to find the owner of a dog who was abandoned at a railway station with its belongings in a suitcase. + +Kai, a male Shar-Pei crossbreed was found tied to a railing outside Ayr station in Scotland on Friday. + +Now animal welfare charity the Scottish SPCA are trying to find who left him there. + +The charity managed to trace a previous owner through his microchip, but were told he had been sold two years ago to someone they did not have details for. + +Scottish SPCA inspector Stewart Taylor said Kai had been sold on classified website Gumtree. + +He said: ""Regardless of the fact Kai was left with his belongings, this was still a cruel incident and we are keen to identify the person responsible. + +""If anyone can help we would ask them to get in touch as soon as possible. + +""Kai is around two to three years old and is a lovely dog with a nice nature. We will look after him until we can find him a permanent and loving home."" + +The charity also said abandoning an animal was a criminal offence. + +Anyone with information is asked to contact the Scottish SPCA Animal Helpline on 03000 999 999.","1" +"Dog found abandoned outside railway station with suitcase of his belongings","The suitcase held a number of the dog's belongings, including a pillow, toy, food bowl and food + +A shar-pei cross has been found abandoned at a railway station along with a suitcase with his belongings. + +The dog, named Kai, was tied to a railing outside Ayr station in Scotland. + +The Scottish SPCA (Scotland’s Animal Welfare Charity) is appealing for information. + +A statement from the SPCA said: ""Regardless of the act Kai was left with his belongings, this was a cruel incident and we are keen to identify the person responsible."" + +The suitcase held a number of the dog's belongings, including a pillow, toy, food bowl and food. + +Inspector Stewart Taylor said: ""The dog is microchipped and we were able to find out his name is Kai. + +""We contacted the owner registered to the microchip, who stated they had sold Kai on Gumtree in 2013. Unfortunately they could not tell us the address of the person who bought him."" + +Abandoning an animal is an offence under the Animal Health and Welfare (Scotland) Act 2006 and anyone found guilty of doing so can expect to be banned from keeping animals for a fixed period or life. + +Inspector Taylor added: ""This case highlights the potential consequences of selling an animal online as it often leads to the impulse buying of pets that people know very little about.""","1" +"Search launched for dog's owner after pooch found dumped next to suitcase filled with belongings","Kai the shar pei-crossbreed was discovered tied to a railing outside Ayr railway station in Scotland with a case containing a pillow, toy, food and bowl + +A dog has been found abandoned at a railway station along with a suitcase filled with his belongings. + +The Scottish SPCA is keen to trace the owner of shar pei-crossbeed Kai, who was discovered tied to a railing outside Ayr station on Friday. + +He was accompanied by a case containing items including a pillow, toy, food and bowl. + +The dog was sold on the Gumtree website in 2013 and the charity is appealing for information to help trace whoever bought him. + +Scottish SPCA inspector Stewart Taylor said: ""The dog is microchipped and we were able to find out his name is Kai. + +""We contacted the owner registered to the microchip, who stated they had sold Kai on Gumtree in 2013. Unfortunately they could not tell us the address of the person who bought him. + +PA Pooch passing through: Kai was found tied to a railing at Ayr station + +""This case highlights the potential consequences of selling an animal online as it often leads to the impulse buying of pets that people know very little about. + +""Regardless of the fact Kai was left with his belongings, this was still a cruel incident and we are keen to identify the person responsible. If anyone can help we would ask them to get in touch as soon as possible. + +""Kai is around two to three years old and is a lovely dog with a nice nature. We will look after him until we can find him a permanent and loving home."" + +Station staff looked after Kai until the Scottish SPCA arrived at the scene on Friday. + +He is now being cared for at the charity's centre in Glasgow. + +The charity said abandoning an animal is an offence under the Animal Health and Welfare (Scotland) Act 2006 and anyone found guilty of doing so can expect to be banned from keeping animals for a fixed period or life.","1" +"Dog abandoned at railway station with suitcase set for happy ending as offers pour in","Offers have been pouring in to re-home a dog found abandoned at a train station along with a suitcase filled with his belongings. + +Kai’s heart-breaking story received media attention around the world after he was discovered tied to a railing outside Ayr station in Scotland. + +The Scottish SPCA has received hundreds of messages online after Wimbledon champion Andy Murray and Trainspotting author Irvine Welsh tweeted about Kai. + +A spokeswoman for the charity said it has received dozens of calls from members of the public offering Kai a new home. + +“The phone’s been ringing off the hook all day. We’ve had over 100 offers to take him on. It’s really unusual to get that sort of interest,” the SSPCA said. + +Dog abandoned at train station with suitcase full of belongings > http://t.co/fKlBh4yX6N pic.twitter.com/5EcNcRTOim— SCOTTISH SPCA (@ScottishSPCA) January 6, 2015 + +Dog abandoned at train station with suitcase full of belongings > http://t.co/fKlBh4yX6N pic.twitter.com/5EcNcRTOim + +It seems a despicable act to leave a dog at a station like that, but remember that many folks are so sad, depressed and desperate right now.— Irvine Welsh (@IrvineWelsh) January 6, 2015 + +It seems a despicable act to leave a dog at a station like that, but remember that many folks are so sad, depressed and desperate right now. + +@ScottishSPCA I would give Kai a loving home which he deserves!! Pls reply— Nathan Fletcher (@ziggy2505) January 6, 2015 + +@ScottishSPCA I would give Kai a loving home which he deserves!! Pls reply + +@ScottishSPCA is Kai still available for adoption? located in Canada but love the breed and will pay any necessary costs to have him come.— brenda chan (@_bchan_) January 7, 2015 + +@ScottishSPCA is Kai still available for adoption? located in Canada but love the breed and will pay any necessary costs to have him come. + +“Normally, when we get an abandonment, it’s usually a staffie and we don’t tend to get many offers to re-home them, but when it’s an unusual breed or a particularly cute one, then we get a lot of interest. + +“I’m sure Kai’s story has tugged at a lot of heartstrings.” + +The Scottish SPCA has asked for anyone with any information about the ‘cruel incident’ to contact them. + +Abandoning an animal is an offence under the Animal Health and Welfare (Scotland) Act 2006.","1" +"Dog found abandoned at Scottish train station with suitcase of belongings","An animal shelter is trying to track down the owner who abandoned a young Shar Pei at a railway station in Scotland, leaving him leashed to a rail with a suitcase full of his belongings. + +The Scottish Society for Prevention of Cruelty to Animals (SPCA), an animal welfare charity, said the wrinkly-faced crossbreed was discovered last Friday at Ayr railway station. His suitcase was packed with a pillow, a toy, some food and a bowl. + +The dog was microchipped, so the charity was able to find the dog’s name, Kai. The group was also able to track Kai’s previous owner whom the microchip was registered to. + +His previous owners said they sold him on the classified ads website, Gumtree, in 2013. The were unable to provide the charity with the address of the person who bought Kai. + +If found, the owner could be charged under Scotland’s Animal Health and Welfare Act. + +Scottish SPCA inspector Stewart Taylor said the case highlights the unfortunate consequences of selling an animal online. + +“Regardless of the fact Kai was left with his belongings, this was still a cruel incident and we are keen to identify the person responsible,” he said “If anyone can help we would ask them to get in touch as soon as possible.” + +The Scottish SPCA said Kai is a “lovely dog with a nice nature”, and estimate that he is between two to three years old. The charity said it will care for the dog until they find him a permanent home. + +Ben Supple, a spokesman with the charity, told the Guardian on Tuesday afternoon that the prospect of Kai finding a loving home looks promising. + +“We haven’t as yet found a home for Kai though we’ve been inundated with offers and will ensure we find him the right owner,” Supple said. + +Anyone with information about Kai is urged to contact the charity’s animal helpline at 03000 999 999.","1" +"Dog abandoned at Scotland train station with suitcase","The Scottish Society for the Prevention of Cruelty to Animals is investigating an incident of a dog abandoned at a train station along with a suitcase. + +The SPCA says the dog was found Jan. 2 tied to a railing at the Ayr railway station in South Ayrshire, Scotland. The suitcase was filled with possessions, including a pillow, a toy, food bowl, and food, according to the SPCA. + +Inspector Stewart Taylor said the dog's name is Kai. + +Officials said the male shar-pei crossbreed, who is 2 or 3 years old, had a microchip and they were able to track down the last registered owner. + +""Unfortunately they could not tell us the address of the person who bought him. This case highlights the potential consequences of selling an animal online as it often leads to the impulse buying of pets that people know very little about,"" according to the SPCA website. + +The SPCA says the society will look after him until a suitable owner is found. + +In the country, abandoning an animal violates the Animal Health and Welfare Act of 2006. The SPCA says, ""Anyone found guilty of doing so can expect to be banned from keeping animals for a fixed period or life."" + +Follow @JessicaDurando on Twitter","1" +"EBay appears to be planning an Apple Watch app","Forget health or messaging. The forthcoming Apple Watch could end up being a lynchpin for e-commerce. + +EBay, whose website allows people to buy and sell all sorts of things both new and old, is seeking an iOS Engineer/Architect who can work on “elegant solutions for the Apple Watch that will complement our core iOS eBay app,” according to a job posting from the company. + +The listing was first published on eBay’s job page in November, but it has been getting more attention thanks to its appearance on LinkedIn this month, according to a report today from AppleInsider. + +E-commerce companies like Flipkart have developed apps for Android Wear watches. Now, as Apple gears up to start shipping the Apple Watch in April, e-commerce companies will presumably develop for it, too. + +Apple first announced the WatchKit software development kit for Apple Watch in November. + +But eBay isn’t only interested in the Apple Watch as a development platform. In addition to an Apple Watch app, eBay’s New Technology Group is planning “solutions” for CarPlay and Apple TV, according to the job posting.","1" +"eBay is planning an Apple Watch app","At least one of the big boys is planning on developing an app for the Apple Watch. eBay has posted an ad listing, looking for a developer to help them come up with a bidding app for Cupertino’s new smartwatch. + +Although the ad was originally posted to eBay’s career page way back in November, it has only recently come to light through an ad posted to LinkedIn. The ad says that it is looking for a dev to join eBay’s New Technology Group, which operates out of Portland with over 200 engineers. + +According to the ad, the ideal candidate will “design and implement elegant solutions for the Apple Watch that will complement our core iOS eBay app.” That seems to indicate that whatever presence the eBay app has on the Apple Watch, it will tie into the core iPhone app. + +What kind of functionality will the eBay Apple Watch app have? That’s up for speculation, although an alert app that lets you know when you’re about to be outbid, when your items have sold, and when a new watched search term pops up on the world’s largest internet auction site are all a good bet.","1" +"Research Medical Center denies reports that a patient has Ebola","KANSAS CITY, Mo. — Research Medical Center is waiting for test results after concern that a patient might have a contagious disease. The hospital says some local reports that the patient has Ebola are false. + +Research Medical Center says that patient came to its Brookside campus emergency department Saturday for treatment. + +“Somebody went to an ER with a high fever and a history of having recently been to Nigeria,” said Jeff Hershberger, the spokesman for the KCMO Health Department. + +He says because Ebola is so high-profile right now, they don’t want to rule it out quite yet. + +“The patient has been isolated, however, at this point, because there’s been no development of new symptoms, it’s highly unlike that Ebola is the diagnosis,” added Hershberger. + +According to a statement from Research Medical Center, like hospitals across the United States, it has standard infectious disease precautions and is well-equipped and well-prepared to implement them as necessary. + +“There’s a wide umbrella of things that it could be,” Hershberger said, “We want to make sure, looking at that entire umbrella, that we are not ignoring something.” + +The hospital does not believe the patient has Ebola, and says the patient is being treated for another illness. Hershberger says regardless, Ebola should not be a big concern. + +“It’s very unlikely they will even be exposed to it, let alone contract it,” Hershberger said, “You cannot catch Ebola unless you touch the bodily fluids of somebody who has Ebola.” + +The health department says it should know the patient’s diagnosis by Monday. It also says that Research Medical Center is taking the appropriate steps when it comes to dealing with infectious diseases.","1" +"Hospital Officials: Kansas City Patient Not Being Treated For Ebola","In response to Ebola Scare in Kansas City : +Via KCTV - 5: +The person who was rushed to Research Medical Center in Kansas City, Missouri Saturday night is a man - not a woman as previously reported, and hospital officials now say the patient is not being treated for Ebola. +HCA Midwest assistant vice president Chris Hamele said that the patient does not have the symptom profile of virus and is being treated appropriately for his condition. +Last night, it was reported that all or part of the medical facility was under quarantine. It is still unknown what the Nigerian man is suffering from or if anyone else is sick. +This afternoon when Breitbart News checked, the apartment building was no longer cordoned off. +Kansas City Health Department spokesman Jeff Hershberger said health department officials are monitoring the situation and and are in a state of awareness because of the recent lone Ebola patient diagnosed in Texas.","1" +"Despite no Ebola case in Kansas City, the rumor goes viral","Rumors of Ebola turned out to be far more contagious than the virus itself this weekend as online media whipped up a feverish story, later disproven, of a suspected Ebola case in Kansas City. + +After appearing on a local blog and a Wichita television website Saturday night, the rumor went viral, spreading to such national outlets as Breitbart.com. + +Then on Sunday afternoon, a spokeswoman for Research Medical Center issued a statement: + +“We have seen online reports that a patient at Research Medical Center is suspected of having Ebola. These reports are inaccurate. Research Medical Center is caring for a patient who presented to our Brookside Campus emergency department, however, the patient does not have the symptom profile of Ebola.” + +That was followed Monday by a statement from the Kansas City Health Department: “The Health Department has ruled out the presence of Ebola in Kansas City.” + +“There was a social media frenzy about the possibility of Ebola in Kansas City,” said Jeff Hershberger, a department spokesman. “We’re still exploring how this happened.” + +Hospitals and the general public have been on edge since an Ebola case was diagnosed last week at a hospital in Dallas. Thomas Eric Duncan is in critical condition at Texas Health Presbyterian Hospital. The hospital’s failure to recognize that Duncan may have had Ebola during an earlier visit to its emergency room has heightened vigilance further. + +Details about what happened Saturday in Kansas City are still unclear, but a feverish man was taken to Research Medical Center’s Brookside Campus on Saturday night. The man apparently was from Nigeria, a country that has had Ebola cases but is not among the three African countries engulfed in the current epidemic. + +The patient’s travel history and fever “triggered them to look at things that included Ebola,” Hershberger said. + +Kansas City police said they received a call Saturday night from a nurse who told them the hospital was under lockdown because of suspicions about the patient. The police decided to block access to the patient’s apartment in the 3600 block of East Meyer Boulevard and to keep the vehicle used to take him to the hospital under observation. + +“Neighbors saw (the police activity) and got worried and contacted the media,” Hershberger said. + +Meantime, the blog TonysKansasCity.com posted the line: “First suspected report of Ebola in Kansas City!!” Tony Botello, who writes the blog, later revised that report. + +KCTV-5 broadcast a story Saturday night about the apartment building being locked down because of a potentially contagious disease but never mentioned Ebola, said Darrin McDonald, the station’s vice president and general manager. + +If a Wichita station reported it was a case of the Ebola virus, “they connected dots that we never did,” McDonald said. + +Gordon Beedle, a news producer at KWCH-12 in Wichita, said the station received information from KCTV about the story and posted its own version online. Beedle said he couldn’t recall exactly what that story said and couldn’t trace it Monday night. + +Sunday night, KCTV reported that Kansas City health officials said it was not Ebola. + +But on Saturday night, others told a different story, said Christine Hamele, a spokeswoman for HCA Midwest Health, which operates Research Medical Center. + +“I was made aware of erroneous reports of a suspected Ebola case in the Kansas City area,” she said. “What was clear to me by 11 p.m. (Saturday) was that none of the information … was accurate.” + +Hamele said the patient was transferred from Research’s Brookside Campus to the main hospital, where he was placed in isolation. He responded well to treatment and was released Monday, she said. + +“A lot of us are on an extra alert because of what happened in Dallas,” Hershberger said. “What happened this weekend was a situation we would prefer to what happened in Dallas. We prefer extra vigilance to not enough vigilance.” + +To reach Alan Bavley, call 816-234-4858 or send email to abavley@kcstar.com. To reach Tim Engle, call 816-234-4779 or send email to tengle@kcstar.com.","1" +"Hospital: Man not being treated for Ebola in Kansas City","KANSAS CITY, MO (KCTV) - +A man rushed to a Kansas City-area hospital Saturday is not being treated for Ebola, hospital officials say. + +HCA Midwest assistant vice president Chris Hamele said that the patient does not have the symptom profile of virus and is being treated appropriately for his condition. + +It is unknown at this time what the patient is suffering from or if anyone else is sick. + +This comes after a Kansas City apartment building in the 3600 block of East Meyer Boulevard was sealed off about 9:30 p.m. Saturday when the man who lived there became seriously ill. + +Paramedics rushed the man to Research Medical Center Brookside Campus about 9:30 p.m. It was then when all or part of the medical facility was quarantined, a source close to the situation told KCTV5 News. + +""Like hospitals across the United States, Research Medical Center has standard infectious disease precautions and we are well-equipped and well-prepared to implement them as necessary,"" Hamele said. ""As healthcare providers, our job is to care for sick patients and we will continue to provide high-quality care to our community as we always have."" + +Kansas City Health Department spokesman Jeff Hershberger said health department officials are monitoring the situation and are in a state of awareness because of the recent lone Ebola patient diagnosed in Texas. + +Chris Hernandez, a spokesperson for the city of Kansas City, said they wanted to take an abundance of caution to avoid a Dallas situation and Sunday he's been told that it's considered ""extremely unlikely"" to be Ebola. + +Hamele said Sunday that the patient has been responding well to treatment that day and was upgraded to good condition.","1" +"KC hospital: Patient does not have symptom profile of Ebola","KANSAS CITY, Mo. —Research Medical Center said a patient who came to its Brookside Campus emergency department for treatment does not have the symptom profile of Ebola. + +The hospital issued the statement to stop rumors and online reports that the patient was being treated for the disease. + +""These reports are inaccurate,"" said HCA Midwest Health spokeswoman Chris Hamele. + +She said the patient was taken to the hospital's main campus, where he being treated appropriately for his illness and is responding well in good condition. The man had one of the symptoms of Ebola and had recently traveled to Nigeria. + +The symptoms of the disease can include a high fever, diarrhea, vomiting, bleeding and bruising. + +Local health officials have said it's extremely unlikely that the patient has Ebola. + +Family members with patients in the emergency room at Research Medical Center said it was business as usual there on Sunday. + +""If it's something we should have been concerned about, I think they would have said something,"" said patient Collette Harvin. + +Marcus Mitchem, who was visiting a patient, said Ebola is a scary thing to think about. + +""The most concerning thing about the Ebola virus is no known cure. You get it, you die. That causes concern for everybody,"" he said. + +Several Americans who contracted Ebola while in Africa have returned to the United States and responded well to treatment, in part due to safety protocols at American hospitals. + +Hamele said Research Medical Center has standard infectious disease precautions, and is well-equipped and well prepared to implement them. + +""As health care providers, our job is to care for sick patients and we will continue to provide high quality care to our community as we always have,"" Hamele said. + +Harvin said she's not really afraid about Ebola. + +""We have measures here. We have medicine,"" she said. ""If we were in Africa or something like that, I'd be a little more worried."" + +The Kansas City Health Department said in a tweet that local hospitals have procedures to protect patients, staff and visitors from infectious diseases. It said it has complete faith that Research Medical Center is taking the appropriate steps. + +""It's important to remember,"" the Health Department tweeted. ""You cannot get Ebola unless you handle bodily fluids of someone who has Ebola."" + +The Centers for Disease Control and Prevention also reminds the public that it's not spread through casual contact or the air. + +More than 3,000 people have died from the outbreak. About 2,000 U.S. troops are already helping Ebola-affected countries. On Friday, the Pentagon announced that number could grow to 4,000.","1" +"Sick Kansas City man said not to have Ebola, U.S. plans new steps to fight virus","KANSAS CITY, Mo. - Kansas City health officials said a man held in isolation at a local hospital over the weekend was not infected with the Ebola virus. Officials hope to sooth nerves as fears about the deadly virus spread across the country, even though the virus itself has not. + +“We have ruled out any Ebola case in Kansas City,” Kansas City Health Department Director Dr. Rex Archer told reporters on Monday. He said the man, who had recently traveled to Nigeria, did not possess the symptom profile for the deadly virus beyond a high fever and had not been in direct contact with anyone who had the disease during his travels. + +No Ebola blood test was done, Dr. Archer said, because the feared symptoms never materialized. + +The case marked the second known Ebola scare in the Kansas City area , as fears of the virus have built while an American fights for his life against it in Dallas. + +At the White House Monday, President Barack Obama urged calm and outlined several steps the administration is taking to contain the virus in Africa and fight it there. + +“The CDC is familiar with dealing with infectious diseases and viruses like this,” the president said. “We know what has to be done, and we have the medical infrastructure to do it.” + +Monday morning, Kansas Senator Jerry Moran sent a letter to the CDC director , urging greater screening at U.S. ports of entry, including airports. + +This afternoon, President Obama said such steps are under consideration. + +“We're also going to be looking at protocols to do additional passenger screening both at the source and here in the United States,” Obama said. “All of these things make me confident that here in the United States, the chances of an outbreak-of an epidemic here- are extraordinarily low.”","1" +"KC Man Does Not Have Ebola","TOPEKA, Kan. (WIBW)- A Kansas City patient is not being treated for ebola after being rushed to a Kansas City hospital Saturday. + +The man's Kansas City apartment building was sealed off when the man became seriously ill. + +He was rushed to Research Medical Center when all or part of the medical facility was quarantined. + +It is unknown what the man is suffering from or if anyone else is sick. + +HCA Midwest Assistant Vice-President Chris Hamele tells KCTV that Research Medical has standard infectious disease precautions and are well prepared to implement them as necessary.","1" +"UPDATE: Internet report of Ebola outbreak in Purdon not true","From Staff Reports +An Internet posting claiming a family of five in Purdon has come down with Ebola is not true. +The website, which has the appearance of a news site, is reporting a the town of Purdon has been sealed off by the CDC and local police. This is not true. +Local Emergency Management officials, the Corsicana/Navarro County Health Department and Navarro County Sheriff Elmer Tanner all report there is no truth to the claim on the website. +Navarro County officials issued the following news release calling the report untrue: +""A release today on at least one website, National Report, stated that “The small town of Purdon, Texas has been quarantined after a family of five tested positive for the Ebola virus.” + ""This report is entirely false."" +""Local authorities, emergency management, and county government have been inundated with calls concerning this false report. Please be assured if this were accurate information, you would have been notified immediately from accurate sources first."" + ""Please ensure that you utilize accurate information sources when looking on social media and any unknown news sources."" + H.M. Davenport, Navarro County Judge + +Sheriff Elmer Tanner +Emergency Management Coordinator, Eric R Meyers +————— +Several questions have been posted on the Daily Sun Facebook page asking about the site — a site that also boasts stories that claim Las Vegas oddsmakers are setting odds on school shootings, and a claim the Obama administration is planning to conduct a sale of all marijuana seized during the Obama administration. +In addition to the source of the first posting, sites that commonly aggregate content from other sites and re-publish it are spreading the rumors to a wider audience.","1" +"Report of quarantined Texas town NOT real; shared on a 'fake' news website","OKLAHOMA CITY —You may have seen an article on social media about a town in Texas being quarantined because of Ebola. + +The story was written on the website NationalReport.net, which is a satire news site. + +The story claimed the town of Purdon was quarantined after a family of five tested positive for the virus. The website also said road blocks had been set up keeping people out of the town. + +Snopes.com, a website that examines rumors and urban myths, created an entry debunking the story after it was shared 79,000 times in nine hours.","1" +"Officials: Report That Area Town Is Under Ebola Quarantine Is False","CORSICANA (October 14, 2014) Navarro County officials Tuesday emphatically rejected as false a posting on the National Report website that said the small town of Purdon was quarantined because a family of five tested positive for the Ebola virus after the father began to exhibit symptoms following a business trip to Dallas. + +The Corsicana Daily Sun reported that local emergency management officials, the Corsicana-Navarro County Public Health District and county officials all say there’s no truth to the claim that federal officials closed down the town of about 130 residents. + +""A release today on at least one website, National Report, stated that “The small town of Purdon, Texas has been quarantined after a family of five tested positive for the Ebola virus. This report is entirely false,” Navarro County Judge H.M. Davenport said in a statement. + +""Local authorities, emergency management, and county government have been inundated with calls concerning this false report. Please be assured if this were accurate information, you would have been notified immediately from accurate sources first,” Davenport said. + +""Please ensure that you utilize accurate information sources when looking on social media and any unknown news sources,” Davenport said.","1" +"Purdon Ebola Hoax: ‘Texas Town Quarantined After Family Of Five Test Positive For The Ebola Virus’ Article is Fake","A report that says a family in the town of Purdon, Texas has got the Ebola virus and the town was quarantined is fake. + +It was posted on the National Report, a satirical website. + +The bogus report says: “The small town of Purdon, Texas has been quarantined after a family of five tested positive for the Ebola virus. Purdon is located just 70 miles from Dallas, Texas, and the hospital that has cared for both American Ebola patients, Thomas Eric Duncan, and Texas nurse, Nina Pham.” + +Thomas Eric Duncan and Nina Pham have in fact be diagnosed with Ebola, with Duncan dying earlier this month. Duncan traveled from Liberia, a country that’s been hard-hit by the virus, to the US and he apparently came into contact with Pham. + +However, the report goes on to say that a man contracted the virus, which is fake. + +The National Report doesn’t currently have a disclaimer since it was taken down a few months ago. + +It used to read: “*DISCLAIMER: National Report is a news and political satire web publication, which may or may not use real names, often in semi-real or mostly fictitious ways. All news articles contained within National Report are fiction, and presumably fake news. Any resemblance to the truth is purely coincidental . The views expressed by writers on this site are theirs alone and are not reflective of the fine journalistic and editorial integrity of National Report. Advice given is NOT to be construed as professional. If you are in need of professional help (and you may be if you are on this page), please consult a professional. National Report is intended for a mature audience and not for children under the age of 18.” + +Hoax-debunking site Snopes.com also has a writeup on the bogus report, which says: “In just a few hours, the Texas quarantine article was shared tens of thousands of times on Facebook. However, National Report is a fake news site that publishes sensational, made-up stories such as “15 Year Old Who ‘SWATTED’ Gamer Convicted of Domestic Terrorism,” “Solar Panels Drain the Sun’s Energy, Experts Say,” and “Vince Gilligan Announces Breaking Bad Season 6.” While the yarn about additional Ebola cases in Texas is not nearly as lighthearted and perhaps more plausible than those japes, it’s still completely fabricated.”","1" +"Purdon Ebola Hoax: ‘Texas Town Quarantined After Family Of Five Test Positive For The Ebola Virus’ Article Totally Fake","A report that says a family in the town of Purdon, Texas has got the Ebola virus and the town was quarantined is fake. + +It was posted on the National Report, a satirical website. + +The bogus report says: “The small town of Purdon, Texas has been quarantined after a family of five tested positive for the Ebola virus. Purdon is located just 70 miles from Dallas, Texas, and the hospital that has cared for both American Ebola patients, Thomas Eric Duncan, and Texas nurse, Nina Pham.” + +Thomas Eric Duncan and Nina Pham have in fact be diagnosed with Ebola, with Duncan dying earlier this month. Duncan traveled from Liberia, a country that’s been hard-hit by the virus, to the US and he apparently came into contact with Pham. + +However, the report goes on to say that a man contracted the virus, which is fake. + +The National Report doesn’t currently have a disclaimer since it was taken down a few months ago. + +It used to read: “*DISCLAIMER: National Report is a news and political satire web publication, which may or may not use real names, often in semi-real or mostly fictitious ways. All news articles contained within National Report are fiction, and presumably fake news. Any resemblance to the truth is purely coincidental . The views expressed by writers on this site are theirs alone and are not reflective of the fine journalistic and editorial integrity of National Report. Advice given is NOT to be construed as professional. If you are in need of professional help (and you may be if you are on this page), please consult a professional. National Report is intended for a mature audience and not for children under the age of 18.” + +Hoax-debunking site Snopes.com also has a writeup on the bogus report, which says: “In just a few hours, the Texas quarantine article was shared tens of thousands of times on Facebook. However, National Report is a fake news site that publishes sensational, made-up stories such as “15 Year Old Who ‘SWATTED’ Gamer Convicted of Domestic Terrorism,” “Solar Panels Drain the Sun’s Energy, Experts Say,” and “Vince Gilligan Announces Breaking Bad Season 6.” While the yarn about additional Ebola cases in Texas is not nearly as lighthearted and perhaps more plausible than those japes, it’s still completely fabricated.”","1" +"Purdon Ebola Hoax: ‘Texas Town Quarantined After Family Of Five Test Positive For The Ebola Virus’ Report Totally Fake","A report that says a family in the town of Purdon, Texas has got the Ebola virus and the town was quarantined is fake. + +It was posted on the National Report, a satirical website. + +The bogus report says: “The small town of Purdon, Texas has been quarantined after a family of five tested positive for the Ebola virus. Purdon is located just 70 miles from Dallas, Texas, and the hospital that has cared for both American Ebola patients, Thomas Eric Duncan, and Texas nurse, Nina Pham.” + +Thomas Eric Duncan and Nina Pham have in fact be diagnosed with Ebola, with Duncan dying earlier this month. Duncan traveled from Liberia, a country that’s been hard-hit by the virus, to the US and he apparently came into contact with Pham. + +However, the report goes on to say that a man contracted the virus, which is fake. + +The National Report doesn’t currently have a disclaimer since it was taken down a few months ago. + +It used to read: “*DISCLAIMER: National Report is a news and political satire web publication, which may or may not use real names, often in semi-real or mostly fictitious ways. All news articles contained within National Report are fiction, and presumably fake news. Any resemblance to the truth is purely coincidental . The views expressed by writers on this site are theirs alone and are not reflective of the fine journalistic and editorial integrity of National Report. Advice given is NOT to be construed as professional. If you are in need of professional help (and you may be if you are on this page), please consult a professional. National Report is intended for a mature audience and not for children under the age of 18.” + +Hoax-debunking site Snopes.com also has a writeup on the bogus report, which says: “In just a few hours, the Texas quarantine article was shared tens of thousands of times on Facebook. However, National Report is a fake news site that publishes sensational, made-up stories such as “15 Year Old Who ‘SWATTED’ Gamer Convicted of Domestic Terrorism,” “Solar Panels Drain the Sun’s Energy, Experts Say,” and “Vince Gilligan Announces Breaking Bad Season 6.” While the yarn about additional Ebola cases in Texas is not nearly as lighthearted and perhaps more plausible than those japes, it’s still completely fabricated.”","1" +"Elon University has not banned the term ‘freshman,’ despite rumors","ELON, N.C. – A recent rumor claims that Elon University has banned the term “freshman” because it’s sexist. But the rumor is not true, according to the university. + +A junior student at Elon University recently wrote an article for the College Fix, a website for students, claiming the school dropped the term and replaced it with “first year.” + +The post claims it was an official move made by the school this fall to promote inclusivity, diversity, and ensure the campus does not promote sexist stereotypes or create a hostile and unsafe environment for female students. The National Review Online also picked up the story. + +The article claimed the school implemented the term “first-year” in everything from its website to orientation workshops. + +But Dan Anderson, vice president of university communications at Elon, told the Burlington Times-News there is no ban or new policy. + +Anderson said the university uses the term “first-year” because it applies to more students than the term “freshman.” + +He said the school uses “first-year” to describe any student in the first year at Elon, as opposed to a recent high school graduate. + +“Elon has done what most schools have done and gone to using ‘first-year’ more frequently because ‘first-year’ encompasses more than just traditional freshmen,” Anderson said. “We still use ‘freshman’ when it refers to traditional students who come right out of high school.” + +The student who wrote the original story said she became curious when she was writing a story for the school newspaper and her editor changed the word “freshman” to first-year.” + +She said she was surprised her story got as much attention as it did and hopes it didn’t put the school in a bad light. + +Read full story: The Burlington Times-News","1" +"At Elon, ‘first-year’ has not replaced ‘freshman,’ university says","Elon University has not banned the use of the word freshman, and there is no policy dictating that the school uses the term “first-year” in place of “freshman,” according to Dan Anderson, vice president of University Communications. + +The university has received national media attention since a student from Elon reported that the school is dropping the word freshman and replacing it with first year. The story, originally published on The College Fix, found its way to FOX News and The National Review Online, where the word “drop” changed to “ban.” + +The university uses first-year in its admissions process because the types of students coming into college are not all traditional students who have graduated from high school. + +“At almost every college, admissions is moving to this term because it encompasses traditional students and also includes transfers, spring admits, gap semester students, part-time students and non-traditional age students,” Anderson said. “It describes people spending their first year at Elon.” + +Anderson explained that the term isn’t Elon’s alone. Duke University, the University of North Carolina system and High Point all use first-year on their admissions websites. They all refer to “The First Year Experience.” The U.S. News and World Report publishes rankings for the schools with the best first-year experience programming. + +While there is no official policy on the word, first-year Blair Foreman said her orientation leader always called the group just that, and most of her professors use the term as well. She understands why the university would use it in place of freshman, but is not offended by the word. + +“I get the intentions behind it,” Foreman said. “Everyone is on the same totem pole, but I don’t mind either way.” + +Sophomore Tyson Glover spent his first semester at Elon in the GAP program and said he enjoyed being called first-year rather than freshman. He said it made his transition into college easier. + +“Coming into Elon January was different,” Glover said. “There’s not a lot going on. First year is an all-encompassing term, and made our transition smoother. It helped us get in the same boat as the rest of our class.” + +According to the original article, Leigh-Anne Royster, director of the Inclusive Community Well-Being, said the term “freshman” may contribute to sexual violence. Anderson said Royster was answering generally why people might not like to use the term “freshman,” not referring to why Elon University does not use the term. + +Greg Zaiser, vice president of admissions and financial planning, corroborated Royster’s comments in the article. + +“The student asked what the primary reason was for changing freshman to first year, presuming there was a change,” Anderson said. Zaiser explained that in general, some consider it a sexist term and that it is not a completely accurate description of the incoming classes. + +There are some students who prefer freshman to first year, though. Firs- years Mackenzie Franklin and Daniel Maclaury prefer the word freshman, saying it is a more traditional term and more natural for them. + +“First year makes it seem like I won’t graduate in four years,” Franklin said. “But I do use them interchangeably.” + +Editor’s note: Diana Stancy, who wrote the original article for College Fix, is a senior reporter for The Pendulum. Stancy did not write the article for The Pendulum.","1" +"No, ESPN is not having an all-male domestic violence panel tonight","The following is one of the most unusual media stories of the last year. + +On Friday, Esquire Magazine posted a blistering piece bashing ESPN written by the publication’s news editor Ben Collins. It was entitled “ESPN has a problem with women.” + +While the column centered on the suspensions of Bill Simmons and Stephen A. Smith, the lead produced some exclusive details about coverage plans for Monday Night Football. Namely, the network would be having a domestic violence panel featuring 11 different voices. All men. Our bold emphasis has been added. + +On Monday night, a panel on a two-hour pregame show for Monday Night Football will, among other things, address domestic abuse. This panel will discuss, once again, the appropriate penalty for hitting a woman. +The panel for that discussion will include the following people: Chris Berman, Cris Carter, Mike Ditka, Adam Schefter, Tom Jackson, Keyshawn Johnson, Jon Gruden, Mike Tirico, Stuart Scott, Steve Young and Ray Lewis. + +Up to 11 men, all between the ages of 39 and 74 will sit at the table for a domestic violence discussion on ESPN. Zero women. Victims of domestic violence in America are most likely to be women aged 20-24. + +When the show has updates from the field—brief reports about injuries and the upcoming game—they’ll cut to female sideline reporters, Lisa Salters and, on some weeks, Suzy Kolber. + +These people are not allowed at the table. + +How Collins got that information, whether through his own sources or ESPN itself, was never shared with Esquire readers. Nevertheless, the “11 men” theme kept coming back throughout his piece as a tentpole of outrage. + +The existence of ESPN’s 11 men domestic violence panel, and the anger towards it, spread slowly throughout the weekend. Deadspin has a nice recap of how far the story reached as it was noticed on Twitter and reblogged across the internet, with one feminist organization even putting the network on blast based on the Esquire article in a press release. + +Of course, ESPN is not having an 11 man domestic violence panel tonight. The network has explicitly and publicly called the Esquire story false as documented below. + +But just examining this story from the outset, there was plenty to be skeptical about in Esquire’s story. + +First of all, ESPN has covered domestic violence and the NFL at length while involving women in the discussion. Jane McManus has been a consistent presence on ESPN airwaves and ESPN has a deep bench of female commentators that have talked about the issue on the air. You can criticize sports networks for not involving women in more prominent ways, but ESPN at least appears to be trying to make an effort here. McManus defended the network on Twitter: + + + +Second, in light of those tweets, there’s no mention of Suzy Kolber – who will be one of the hosts on Monday Night Countdown tonight. If there’s any panel discussion happening tonight, wouldn’t she be involved? + +Third, it’s easy to make fun of ESPN and the gratuitously absurd amount of NFL analysts the network employs. But who in their right mind would conduct an 11 person panel on a topic like domestic violence? That’s not something that even Nancy Grace and the cable news networks would be silly enough to do. + +If we’re to believe this Esquire story, Chris Berman would be moderating an 11 person panel discussion on domestic violence including everyone from the game announcers to reporters. It’s nonsensical. Not even ESPN would be that dense. + +Bristol began the counter-offensive today. The network released their coverage plans for Monday Night Countdown tonight. And in a move straight out of the ESPN PR Playbook, they also highlighted women’s contributions to their coverage of the NFL domestic violence crisis. + +A rare public statement from John Wildhack, one of the highest on the ESPN Executive Food Chain, also disputed the Esquire report/column/rant/guesswork… + +Contrary to published reports in Esquire, there was no panel on domestic violence ever planned for tonight’s Monday Night Countdown. We will present our normal Monday Night Football pre-game show, with Suzy Kolber hosting. ESPN is proud of the work it has done covering the issue of domestic violence, and is committed to continued coverage. Much of that work has been informed by several talented female colleagues from our television and espnW platforms, including Hannah Storm, Jemele Hill, Jane McManus, Kate Fagan, Sarah Spain and more. + +So how did this happen? It’s simple. Haphazard and reckless writing at Esquire gradually began to be taken as fact. + +There never were plans for an 11 men panel to discuss domestic violence on Monday Night Countdown. Collins merely listed the talent that would be working the show and assumed the topic would come up at some point during the evening in an unbelievable failure in communication through the written word. + +Collins explained his position in greater detail on his Twitter page: + + +That’s a pretty far cry from what Collins actually wrote in his article which made it abundantly clear there would be a special domestic violence panel with enough men to field an entire football team. “Up to 11 men, all between the ages of 39 and 74 will sit at the table for a domestic violence discussion on ESPN.” There’s no ambiguity in that statement. + +100 out of 100 people would read that sentence and think ESPN would be televising a large all-male panel discussion specifically focused on domestic violence tonight. How does someone who is a news editor at a major publication blur the lines of truth and fiction so badly? + + + + +Had Collins stuck with that last tweet he would have had the basis for a decent column and a valid criticism worth raising. But because of the overall sloppiness of the Esquire piece, that point was missed entirely. Instead, a lot of people have wasted a lot of time talking about an 11 men domestic violence panel that never existed.","1" +"That ESPN Domestic Violence Panel You Keep Hearing About Isn't Real","On Friday, Esquire.com's Ben Collins wrote a blog post in which some awkward phrasing made it appear as though tonight's episode of Monday Night Countdown on ESPN will feature a special panel discussion on domestic violence. + +Here's how his post starts: + +On Monday night, a panel on a two-hour pregame show for Monday Night Football will, among other things, address domestic abuse. This panel will discuss, once again, the appropriate penalty for hitting a woman. + +The panel for that discussion will include the following people: Chris Berman, Cris Carter, Mike Ditka, Adam Schefter, Tom Jackson, Keyshawn Johnson, Jon Gruden, Mike Tirico, Stuart Scott, Steve Young and Ray Lewis. + +Up to 11 men, all between the ages of 39 and 74 will sit at the table for a domestic violence discussion on ESPN. Zero women. Victims of domestic violence in America are most likely to be women aged 20-24. + +When the show has updates from the field—brief reports about injuries and the upcoming game—they'll cut to female sideline reporters, Lisa Salters and, on some weeks, Suzy Kolber. + +These people are not allowed at the table. +Collins's outrage at ESPN's failure to include any women in a discussion dedicated to domestic violence was shared by many, and word of the ""panel discussion"" began to spread across Twitter: + + + + + + + + + +And then there were a lot of other blogposts, piggybacking off of Collins's, with headlines like these: + +ESPN Doesn't Get It: They Ignore Women's Voices In Public Dialog About Domestic Violence +ESPN's Domestic Violence Panel Is Missing Something Important +11 Men and 0 Women on Tonight's ESPN Domestic Violence Panel +ESPN's Domestic Abuse Tonight Panel Will Be 100% Dudes +ESPN to save NFL's image with all-male domestic abuse discussion +And then feminist organization UltraViolet blasted this press release to various media outlets: + +UltraViolet Calls on ESPN to Include Women in Discussion About Domestic Violence + +Statement from Nita Chaudhary, co-founder of UltraViolet, on ESPN's announcement that a 11 man panel will discuss domestic violence during their Monday Night Football pre-game roundtable: + +""By having a roundtable on domestic violence and not including any women, much less survivors of domestic violence, the panel is the height of ignorance by ESPN. ESPN must be getting their PR advice from their buddies at the NFL. Both the NFL and ESPN seem to greatly misunderstand the problem they are trying to address and the millions of people's lives it effects."" + +While it's good to see ESPN taking on the issue of domestic violence within the NFL tonight, we strongly believe that they should also include the voices of women and survivors of domestic violence at the table. With nearly 45% of NFL fans and viewers being women, including women at the table not only would add to the discussion but would address the realities of their audience and the issue at hand."" +But tonight's episode of Monday Night Countdown is just going to be a regular episode, and will not be featuring any special discussion about domestic violence. We reached out to ESPN PR, who told us that talk of the special panel was ""false info"" and that tonight will feature a ""regular episode of Countdown hosted by Suzy Kolber."" + +There are certainly criticisms to be made of Monday Night Countdown fielding such a dude-heavy panel that is painfully ill-equipped to speak intelligently about any issue of substance, as has been proven in the past. Tonight, however, it's highly unlikely that domestic violence will even come up. + +Update: And here is a statement from ESPN: + +Contrary to published reports in Esquire, there was no panel on domestic violence ever planned for tonight's Monday Night Countdown. We will present our normal Monday Night Football pre-game show, with Suzy Kolber hosting and Lisa Salters reporting. ESPN is proud of the work it has done covering the issue of domestic violence, and is committed to continued coverage. Much of that work has been informed by several talented female colleagues from our television and espnW platforms, including Hannah Storm, Jemele Hill, Jane McManus, Kate Fagan, Sarah Spain and more.","1" +"ESPN’s All-Male “Monday Night Football” Panel On Domestic Violence Is Not Real","On Friday, Esquire published an article titled “ESPN Has A Problem With Women” that suggests the network was planning to host a male-only panel discussion on domestic violence during this week’s “Monday Night Football” broadcast. + +The article begins: + +On Monday night, a panel on a two-hour pregame show for Monday Night Football will, among other things, address domestic abuse. This panel will discuss, once again, the appropriate penalty for hitting a woman. + +The panel for that discussion will include the following people: Chris Berman, Cris Carter, Mike Ditka, Adam Schefter, Tom Jackson, Keyshawn Johnson, Jon Gruden, Mike Tirico, Stuart Scott, Steve Young and Ray Lewis. + +Up to 11 men, all between the ages of 39 and 74 will sit at the table for a domestic violence discussion on ESPN. Zero women. Victims of domestic violence in America are most likely to be women aged 20-24. + +When the show has updates from the field—brief reports about injuries and the upcoming game—they’ll cut to female sideline reporters, Lisa Salters and, on some weeks, Suzy Kolber. + +These people are not allowed at the table. + +The assertion that ESPN would host such a panel discussion and not invite any women to participate sparked outrage. + +THIS IS HORRIFYING http://t.co/lasYPHtbXl + +Utterly speechless. RT @Lahlahlindsey THIS IS HORRIFYING http://t.co/ycDWFvwtfI … + +Chris Berman and Mike Ditka, who are not good at talking about *football,* talking about domestic violence? This has a chance to be A+ TV. + +Several other blogs wrote posts questioning why ESPN would only let men participate in this domestic violence discussion. (H/t Deadspin) + +ESPN Doesn’t Get It: They Ignore Women’s Voices In Public Dialog About Domestic Violence + +ESPN’s Domestic Violence Panel Is Missing Something Important + +11 Men and 0 Women on Tonight’s ESPN Domestic Violence Panel + +Esquire writer Ben Collins who posted the original article took to Twitter to attempt to clarify what he wrote. + +Hi, everybody now reading my ESPN story @Lahlahlindsey's tweet! Note: There's no special panel on tomorrow's Countdown for domestic violence + +...Those are the people on the show every week. They haven't changed it in the last few weeks, either. Don't know if that's better or worse. + +But there was a top sentence left off that tweet that's going around, and I wanted to clarify. ESPN is mad enough at me as it is. Thank you. + +On Monday, ESPN’s John Wildhack, executive vice president of programming and production released a statement refuting Esquire’s original report that the network scheduled any sort of domestic violence panel discussion. + +Contrary to published reports in Esquire, there was no panel on domestic violence ever planned for tonight’s Monday Night Countdown. We will present our normal Monday Night Football pre-game show, with Suzy Kolber hosting. ESPN is proud of the work it has done covering the issue of domestic violence, and is committed to continued coverage. Much of that work has been informed by several talented female colleagues from our television and espnW platforms, including Hannah Storm, Jemele Hill, Jane McManus, Kate Fagan, Sarah Spain and more. + +ESPN published a blog post highlighting reporting on domestic abuse by its female staffers since the Ray Rice scandal broke last month. + +ESPN also posted a list of highlights for tonight’s “Monday Night Football” broadcast, which includes no discussion about domestic violence. + +ESPN reporter Jane McManus took to Twitter to debunk Esquire’s domestic violence panel story. + +ESPN is about to release a statement. I'll go through a few points here. There was never a domestic violence panel planned for MNF tonight. + +Since the Rice story broke, ESPN has featured several women prominently, including myself, @katefagan3, @SarahSpain @jemelehill etc. + +Tonight's regular MNF panel will be hosted by Suzy Kolber. It was never meant to be a single-issue discussion of domestic violence. + +Esquire did not immediately return a request for comment.","1" +"There was never a panel discussion on domestic violence planned for ESPN’s ‘Monday Night Football’ pregame show","ESPN’s “Monday Night Football” will not be featuring a discussion in which an all-male panel discusses domestic violence. + +In fact, the telecast of the game between the New England Patriots and Kansas City Chiefs will feature just a regular pregame show. There was never, the network says, a panel discussion about the topic planned for tonight. + +The network was hammered with calls after an Esquire blog post (“ESPN Has a Problem with Women”) indicated that an all-male lineup would debate the topic, which has been a hot once since the second Ray Rice video surfaced three weeks ago. On Monday, in the third game since the explosive video triggered the NFL’s domestic violence crisis, “it’s a normal lineup for ‘Monday Night Football,’” according to Chris LaPlaca, ESPN’s senior vice-president of corporate communications. + +That lineup, of course, includes Suzy Kolber, who hosts the two-hour “Monday Night Countdown” show, and Lisa Salters, reporter and sideline reporter. In a statement on the matter, John Wildhack, executive vice-president of programming and production, said: + +Contrary to published reports in Esquire, there was no panel on domestic violence ever planned for tonight’s Monday Night Countdown. We will present our normal Monday Night Football pre-game show, with Suzy Kolber hosting and Lisa Salters reporting. ESPN is proud of the work it has done covering the issue of domestic violence, and is committed to continued coverage. Much of that work has been informed by several talented female colleagues from our television and espnW platforms, including Hannah Storm, Jemele Hill, Jane McManus, Kate Fagan, Sarah Spain and more.","1" +"Fake BBC News website set up to carry Charlie Hebdo attack conspiracy theories","A realistic-looking fake BBC News website has been set up carrying conspiracy theories about the Charlie Hebdo massacre. + +A story, headlined: “Doubts raised over Charlie Hebo footage”, appears on the website domain bbc-news.co.uk. + +The rest of the BBC website furniture on the page looks genuine and the links to other BBC content work. + +But the story and video are about a conspiracy theory that the widely broadcast amateur video footage showing the killing of a Paris policeman was faked. + +The story also claims that the Charlie Hebdo attack was a “false flag” operation perpetrated by Western intelligence. + +According to internet registry company Nominet, the bbc-news.co.uk internet domain was registered on 28 December 2014. + +The fake BBC News site site also carries a faked a video news report purporting to be produced by the BBC which has been posted to Youtube. + +Tags:","1" +"Ferguson Protester's Photo Gets Edited Into Racist Meme, Goes Viral","When Jermell Hasson agreed to let Riverfront Times take his photo for a story about Ferguson protesters, he had no idea someone would later turn it into a viral and inflammatory meme. +Hasson carried a sign in front of the Ferguson police station that read: ""No mother should have to fear for her son's life every time he leaves home. #blacklivesmatter #stayhuman"" + +Months later, a doctored photo of him holding a sign that says, ""No mother should have to fear for her son's life every time he robs a store,"" has gone viral. + +""That's slander to my character,"" Hasson tells Daily RFT. ""You can tell it's obviously been photoshopped. It was a horrible job."" + +Imgur user Bdawgid says he's the Photoshop wizard behind the altered photo, which was posted to the photo-sharing site on November 27. Bdawgid writes on Imgur that he created the image because, ""it captured mine, and many others, frustration with this whole situation."" + +More than 28,000 people shared the faked photo after Jim Gleason, a Maplewood native who's owned a south-county sign business for almost twenty years, posted it on Facebook with the (very incorrect) description: ""You can't make this up!!!!!"" + + +racisteditwonames.JPG +Facebook +More than 28,000 people shared this doctored photo. +Gleason wouldn't tell Daily RFT what motivated him to share the photo, which refers to the death of Michael Brown, who was recorded on surveillance cameras stealing from a convenience store and was later fatally shot by then-Ferguson police officer Darren Wilson. +""I certainly didn't mean any harm by it,"" Gleason says. He says he found the doctored image on Facebook and took the image down after getting ""an onslaught of emails"" saying it was fake. ""We absolutely, unequivocally did not edit it."" + +Riverfront Times reporter Mitch Ryals took the original photo of Hasson, 27, in September in front of the police station. + + +mitchphotoorig.JPG +Mitch Ryals +The original photo. +Hasson told Daily RFT in September he'd been sleeping in a parking lot across the street from the police station for weeks to peacefully protest Brown's death. +""We were literally on this lot for 24 hours for that whole month,"" Hasson told Daily RFT in September. ""I'm not saying here for an hour then going home. Twenty-four [hours] we were in this lot peacefully protesting. We've been rained on for a full week on this lot waiting for the sun to come out in the morning to dry us out."" + +This week, Hasson tells Daily RFT he thinks the doctored photo is a sign that Ferguson protests are having an effect on the way people think. + +""It shows that we are making a difference out here,"" Hasson says. ""For someone who has nothing better to do with their life than photoshop a sign, it shows me that we haven't been out here since August for no reason. They're trying to stop the movement, which they can't."" + +Hasson says he has a message for Gleason and the thousands of people who shared the fake photo: ""Remove the hatred out of your heart, and come and see what we're doing for yourself."" + +Gleason says he is surprised and saddened by the backlash to the photo he posted because ""qualified investigators at all levels of government"" concluded that Brown robbed the convenience store before his death. + +""It appears that this young man robbed a store, assaulted a police officer, and it is just surprising to me the uprising when the physical evidence seems to be overwhelmingly in support of the police officer's actions,"" Gleason says. + +People who objected to the provocative photo posted to the Facebook page for Gleason's business, Sign-A-Rama St. Louis, to warn customers. + +""Makes the BEST racist memes on Facebook,"" one person sarcastically wrote on the shop's Facebook page. ""Gives good discounts to whites, charges darkies extra. Highly recommended to any whites in St. Louis looking for a good white pride meme."" + +Mitch Ryals contributed reporting to this story.","1" +"Dumb Racists Photoshop Ferguson Protester Into Awful Viral Meme","Jermell Hasson spent his summer sleeping in a parking lot in Ferguson to join the protests over Michael Brown's shooting by police. Hasson's reward was to become racist America's favorite meme, after a doctored image of him was shared thousands of times across the internet's dark, sticky id-corners. + +Riverfront Times photographer Mitch Ryals snapped an innocuous shot in September of Hasson carrying a sign with fellow protesters that read ""No mother should have to fear for her son's life every time he leaves home,"" with the hashtags ""#blacklivesmatter"" and ""#stayhuman"": + +Dumb Racists Photoshop Ferguson Protester Into Awful Viral Meme + +Opponents of the protests did not take Hasson's advice. Instead, the Times reports, its image of him went viral after his sign was photoshopped to read ""No mother should have to fear for her son's life every time he robs a store"": + +Dumb Racists Photoshop Ferguson Protester Into Awful Viral Meme +EXPAND + +Brown was suspected of helping to knock over a convenience store before the confrontation with Ferguson police officer Darren Wilson that led to the teen's death. + +Riverfront Times caught up with one local man, Jim Gleason, who was apparently one of the first to share the made-up image on Facebook with the note ""You can't make this up!!!!"" (It was subsequently shared more than 28,000 times.) Gleason explained to the Times what was apparently self-evident to him and other fans of the image—that suspected robbers of convenience stores should be summarily shot: + +Gleason says he is surprised and saddened by the backlash to the photo he posted because ""qualified investigators at all levels of government"" concluded that Brown robbed the convenience store before his death. + +""It appears that this young man robbed a store, assaulted a police officer, and it is just surprising to me the uprising when the physical evidence seems to be overwhelmingly in support of the police officer's actions,"" Gleason says. +A handful of critics have taken to the Facebook page of Gleason's St. Louis business—a signmaking business—to express their frustrations. + +Hasson called the image-doctoring a ""slander,"" but he seems to be taking it in stride. ""It shows that we are making a difference out here,"" he told the Times: + +For someone who has nothing better to do with their life than photoshop a sign, it shows me that we haven't been out here since August for no reason. They're trying to stop the movement, which they can't.","1" +"Rumor Fatigue Sets In at False Alarms of Castro’s Death","MIAMI — The bulletin now falls squarely in the pantheon of unconfirmed phenomena, along with U.F.O.s, sightings of the Loch Ness monster and the breakup of Brad Pitt and Angelina Jolie: + +Fidel Castro is dead. + +Sooner or later, it will be true. But on Friday, for the umpteenth time, Miami was distracted by the rumor that Mr. Castro, 88, who has survived revolution, assassination attempts, countless cigars, substantial stress, a fall after leaving a stage and a life-threatening stomach ailment, had finally succumbed. + +“Hope springs eternal,” said James Cason, the former head of the United States Interests Section in Cuba from 2002 to 2005 and now the mayor of Coral Gables, a wealthy enclave in Miami-Dade County. “He must have died 20 times since the time I went to Cuba.” + +Cuban-Americans gathered in the usual spot, the Versailles restaurant on Calle Ocho, and other Cuban establishments to ponder the possibility that this time, maybe, maybe, it would be true. But even here in a city still fixated by Mr. Castro, rumor fatigue was obvious. Versailles had put its Fidel-is-dead game plan into action — assigning some parking spots to local TV and radio stations, but few showed up + +It was no different at La Carreta, a restaurant in Westchester, Fla., a Cuban-American stronghold. + +“There is always doubt about this; the joke is on us,” said Manolo Alvarez, 75, a retired painter, laughing as he held court with his friends in front of the Cuban cafecito counter. “But eventually it will happen. No one is immortal. And he will join the devil.” + +Castro death alerts come fast and frequently these days. His age, ill health, long absence from public view and society’s shift from old-school rumor mill to hyperspeed Twitter feed make even debunked stories effortlessly spreadable. In fact, determining the provenance of each rumor has become a kind of modern-day parlor game. + +In this case, the story probably stemmed from a simple mix-up, the death of a lesser-known namesake in a faraway country: Fidel Castro Odinga, the son of a prominent Kenyan politician, Raila Odinga, died on Sunday and was eulogized on Thursday. A similar mistake occurred in August 1997, when a Cuban revolutionary figure, Rene Orley Sanchez Castro, died in Cuba, spawning a swirl of speculation around the world. + +Like most of the past false reports, the one on Friday was bolstered by tantalizing circumstantial droplets. The last time Mr. Castro was seen in public was Jan. 9, 2014, making Friday the first anniversary of his disappearance. And Mr. Castro, never at a loss for words, had failed to comment about December’s announcements by his younger brother, Raúl, and President Obama that the United States and Cuba would resume diplomatic ties. + +There was also word on Friday of an abruptly scheduled news conference and chatter — true or not — about how the major roads to a famous revolutionary cemetery in Santiago de Cuba, where Mr. Castro reportedly will be buried, were being repaired. + +The likeliest explanation for Mr. Castro’s absence is that he is, in fact, too mentally and physically frail to be seen or to speak. + +“We don’t know what his physical state is because they never let you know,” Mr. Cason said of Cuban officials. “But they want him to be remembered as strong and vigorous. They don’t want him to be seen.” + +Tales of Mr. Castro’s demise have surfaced for decades. In 1986, the State Department had to beat back a flurry of reports and questions from Miami about Mr. Castro’s apparent death. The sources of the speculation were varied and dubious: A ham radio operator in Havana, a nurse in Cuba who telephoned a friend in Miami, a report by an astrologer. + +More rumors followed, off and on, and then accelerated after Mr. Castro vanished for a stretch in 2006 and, once again, after he relinquished power to his brother Raúl in 2008. Through the years, Mr. Castro has been rumored to have been stricken by heart attacks, brain hemorrhages, strokes and cancer. He has alternately delighted in and derided the many attempts to “kill him off early,” as he joked once in 1997. + +“Now that our enemies have prematurely declared me dying or dead, I am happy to send my compatriots and friends around the world this short film material,” Mr. Castro said in 2006, after his absence. + +In Miami, his death, when it is finally confirmed, will be historically momentous and, for most, cause for jubilation. The city will dust off its ever-evolving contingency plans. Even some private schools have early dismissal emails to parents at the ready. + +But, to a certain extent, Mr. Castro’s death will also be anticlimactic. Years ago, his death was seen as the necessary prelude to a democratic Cuba and a return home for tens of thousands of exiles. With Raúl Castro firmly in place, that is no longer the case. + +“If this had happened at the height of his power, or even when he was just fading, it would be different,” said Peter Hakim, a Cuba expert at the Inter-American Dialogue center in Washington. “This was almost a personal battle not to let Fidel win. Now, I think people are beginning to accept that Fidel has won. He will go to his grave with the government intact and the U.S. backing down from its unalterable commitment to unseat the regime he installed.”","1" +"Fidel Castro Dead? Yes, He Is… But The Cuban Leader Is Alive, Death Rumors Proven False","Is Fidel Castro dead? Yes, a man named “Fidel Castro” has died, but he’s not the famous Castro you might be thinking of. The prospect that the leader of Cuba might have died is circulating on the internet, and the rumors claim Fidel Castro’s death was supposed be announced at an official conference, according to the Castro health rumors, but already Cuba has denied these rumors. + +In a related report by the Inquisitr, it’s claimed that Ian Fleming, the author of the famous James Bond series, helped former President Kennedy to hatch a Fidel Castro assassination plot. + +According to the el Nuevo Herald, the rumors claimed Fidel Castro dead because a man named Fidel Castro Odinga, the son of an important politician in Kenya, died over the weekend at the age of 14 years old. + +“Castro Odinga was the son of Raila Odinga, the main opposition leader in Kenya and was considered a possible successor to his father. It is possible that his death and his name have confused many users of Twitter, and these have begun to spread the word about the supposed death of the Cuban leader.” + +Kenyan police are currently investigating Odinga’s death, and these headlines may have encouraged rumors about the Cuban leader. + +According to Laiguana TV, it’s also possible that a blog by Yusnaby Perez may have sparked rumors that claimed Fidel Castro dead because he had not been in public in many months. + +“How strange! It is the first year since I can remember the anniversary of the Revolution that Fidel does not appear.” + +Thursday marked a year since the former Cuban president made a public appearance. Castro has apparently received foreign dignitaries at his home in Havana, but has not commented publicly on the recent changes between Cuba and the United States that was announced on December 17, 2014. + +The rumors were increased even further when Italian newspaper Corriere Della Sera reported on Fidel Castro’s death. The newspaper quickly retracted its report, but not before the alleged “news” about Castro went viral. + +Because of these rumors several media outlets in Venezuela and Cuba claimed the Cuban government planned on calling a press conference to discuss Fidel Castro’s heath condition. But an official from the International Press Centre (CPI), the department Cuban Foreign Ministry serving foreign media, says this rumor is false, saying, + +“That is false. No press conference was convened, no.” + +In addition, Castro’s influential nephew, Alejandro Castro Espin, who is currently in Greece, told a radio station his uncle is “in good health” and there’s no reason to speculate about Castro’s death.","1" +"Rob O'Neill may have killed bin Laden, but didn't take out gangster intruders","BUTTE — Butte Police Commissioner Bartholomew S. Harrington is a wanted man in these parts. Too bad neither the position nor the man exist. + +A satirical story about Rob O’Neill posted on the Internet has prompted everyone from Associated Press reporters to Louisiana law enforcement officers to call local authorities for information. + +Empire News posted a bogus article Monday titled “Bin Laden Shooter Rob O’Neill Mistakenly Attacked by Street Thugs Seeking To Collect Debt From Neighbor.” + +“Nothing in the story has a resemblance of truth,” Butte-Silver Bow Undersheriff George Skuletich said Wednesday. + +Skuletich does exist, for the record. + +What is fabricated in the article includes: the police commissioner, five gang members seeking a drug debt and the Butte Daily Times. Also, O’Neill did not take down the intruders and brew a pot of coffee while awaiting backup. + +“We’ve been getting all kinds of calls from across the country,” Sheriff Ed Lester said. + +The article has been making its rounds on social media sites. This prompted Snopes.com to label it false. + +“Empire News is one of many fake news sites responsible for the frequent hoodwinking of Facebook users. Among previous hoaxes were a yarn about welfare recipients getting free cars, a claim that Colorado legalized meth and a widely shared story about pending ‘snowmageddon,’” Snopes notes. + +The piece claims that members of the Crips gang broke into the home of the former Navy SEAL and Butte native. + +“We don’t have established Bloods or Crips here,” Lester added. + +The story goes: “As the five thugs ran aimlessly through the home, Mr. O’Neill used silent hand-to-hand combat tactics to individually disarm them of their weapons. Once Mr. O’Neill had taken down the five men and secured his home, he brewed a pot of coffee and called the police station. Those boys sure did find the wrong house!” + +While some might find the fake news piece amusing, local police are reminded of another hoax of a girl who reportedly shot intruders: An 11-year-old Butte girl was reported to have taken out two crooks. She was reportedly a clay-shooting champion in Butte who killed one man with a shot to the genitals and the other bled out. + +That bogus story reappears about every year or so, Lester said.","1" +"Missing Fort Carson item not a nuclear weapon - despite Internet rumors","Despite a wild report on a website dedicated to conspiracy theories, local soldiers haven't lost a low-yield nuclear weapon. + +As the lockdown of soldiers in a Fort Carson battalion dragged into its fifth day Monday, the site Whatdoesitmean.com reported that a nuclear artillery shell was missing - an item that hasn't been in the Army inventory for 22 years. That story was translated into several languages, including Russian and spread rapidly on the Internet. + + Photo - The modified M9-Beretta pistol used for the Basic Active Shooter Course fires a powder propelled paint cup to provide the most realistic training possible while maintaining the level of safety required for the scenarios, Jan 26. The course is taught by a 4-man training team from the 610th Security Forces Squadron, Joint Reserve Base Fort Worth, Texas. They came to Dobbins Air Reserve Base to provide this critical training for the 94th Security Forces Squadron and other Dobbins area security personnel. The two day course provides classroom and tactical instruction to first responders covering several shooting spree scenarios. (U.S. Air Force photo/ Brad Fallin) + caption + +Sources at the post told The Gazette that the lockdown involving 100 soldiers from the 1st Battalion of the 66th Armor Regiment is actually for something more mundane - a 9 mm pistol. The Army hasn't officially released details on what spurred the lockdown and search, calling it ""missing government property."" + +The lockdown started with about 800 soldiers confined to the battalion's buildings on the post. That was reduced over the weekend to about 100 soldiers - a company of troops. + +Retired Command Sgt. Maj. Terrance McWilliams, who served as the post's top enlisted soldier, said lockdowns are a common practice commanders use to turn up lost gear. + +""I personally went through it as a 1st sergeant and the longest it took was four days,"" said McWilliams. + +The lockdown was triggered Thursday after the pistol turned up missing in an equipment inventory that followed a training exercise. Post officials ordered a wide search for the missing weapon Thursday, including inspecting cars as they exited the post at gates. + +Retired Command Sgt. Maj. John Kurak, who also held Fort Carson's top enlisted post, said a five-day lockdown isn't close to a record for Fort Carson. + +""In Fort Carson's history there have been lockdowns that have lasted months,"" Kurak said, noting that an infantry battalion on there spent three months on lockdown in the late 1980s after a M-16 rifle was lost. + +McWilliams said the first step in the search for the weapon likely was quizzing the soldier who checked it out from the unit's armory for the training exercise. The battalion's soldiers were returning from a training exercise that spanned a wide swath of the 137,000-acre post. + +When it was determined that the weapon was lost, soldiers were likely sent to scouring training areas in a move called ""hands across Fort Carson"" that sees soldiers walking shoulder-to-shoulder to find the missing weapon. + +When that didn't bear fruit, soldiers were ordered to remain on duty and on post until the weapon was found - a lockdown. + +Long lockdowns like the one that deprived 1st Battalion soldiers of what was a planned four-day weekend, do come to an end. + +""Eventually its going to get to the point where they determine the item is actually lost,"" McWilliams said. ""Then they will determine what actions to take against the person responsible for the item."" + +Losing a weapon can bring stiff consequences in the military, where loss or destruction of government property can be charged as a crime bringing up to a year behind bars. + +The Army spends a lot of time keeping track of pistols, rifles and other ""sensitive"" items. Every training day begins and ends with a sensitive items check, and daily inventories are sent up through the chain of command. + +""If you can't keep track of your equipment, how can you be expected to do more complex tasks?"" Kurak asked. + +In combat, units heading out and returning from stop for a ""boys and toys"" check to make sure all weapons, night vision goggles, laser sights, radios and other items are on hand. + +""Accountability of equipment is a basic and essential function of a unit,"" Kurak said. + +While the battalion may have lost a pistol, scores of web pages carried the nuclear weapon tale Monday. That story, attributed to unnamed Russian intelligence sources, alleged that a 155 mm artillery-fired nuclear warhead is missing at the post. + +The battalion involved, though, doesn't have artillery. And the W-48 artillery warhead alleged to be missing was pulled from Army bases worldwide in 1992. + +While the Pikes Peak region is home to a five military bases, it doesn't house nuclear weapons. The closest nuclear arms are atop Air Force intercontinental ballistic missiles at F.E. Warren Air Force Base in Cheyenne, Wyo.","1" +"The @FoxNewsPress Account Tweeting Lawsuit Threats Is a Fake","Last night, @FoxNewsPress, the Twitter account claiming to be that of the Fox News public relations team, went live. One big problem: It’s a fake. + +They had one mission, they declared: + +The team at @FoxNews have set up this account to manage and dispel all false facts attributed to us through the #foxnewsfacts trend. — Fox News Press Team (@FoxNewsPress) January 12, 2015 + +The hashtag refers to a meme that blew up after a Fox contributor declared that certain British cities had been swallowed whole by Muslim immigrants. “In Britain, it’s not just no-go zones, there are actual cities like Birmingham that are totally Muslim where non-Muslims just simply don’t go in,” said Steve Emerson, whose statement was so absurd that it was actually debunked by British PM David Cameron himself. (For the record, Birmingham’s Christian population is twice the size of the Muslim population.) + +And so, @FoxNewsPress went about trying to stop people from mocking Fox News, with the power of empty legal threats: + +@ScottMacBain we have no record of this in our news lists. Please delete tweet or face legal charges. — Fox News Press Team (@FoxNewsPress) January 12, 2015 + +And the faker responded with anger: + +@Victorialush this false statement is not from our news list. Please delete or face legal action. — Fox News Press Team (@FoxNewsPress) January 12, 2015 + +Fox News confirmed to Mediaite on Monday that this account is, in fact, a fake. + +Though that likely won’t stop the fraudulent tweeters from issuing an empty lawsuit threat against us, like they did to the Washington Examiner: + +We have been made aware that individuals posing as ourselves have been quoted by @dcexaminer. We will be pursuing legal recourse for mis… — Fox News Press Team (@FoxNewsPress) January 12, 2015 + +representation and requesting the article is removed from publication. — Fox News Press Team (@FoxNewsPress) January 12, 2015 + +[Featured Image via screenshot] + +– – >> Follow Tina Nguyen (@Tina_Nguyen) on Twitter","1" +"No - a Fox News Twitter account isn't responding to tweets on the #FoxNewsFacts hashtag","Yes, we wished it were true too, but no, Fox News are not angrily responding on Twitter to the hilarious #FoxNewsFacts hashtag + +Yes, we’ve all been having a good laugh at Fox News’ expense for hosting a “terrorism expert” saying that everybody in Birmingham is a Muslim and the entire city is a no-go area . + +Especially on Twitter, where the #FoxNewsFacts hashtag has been a brilliantly British response to the ludicrous statement. + +And then suddenly it looked like Fox News had got rather upset about the hashtag, and started responding from @FoxNewsPress . + +Except, not really. + +At the time of writing, the account has only made 25 tweets. And it appears it was set up in the middle of last night. Here’s their first ever tweet... + +We can’t quite imagine a Fox News board meeting in the wee hours with someone shouting “Quick! The Brits are laughing at us with a hashtag! Activate a brand new Twitter account for our press team.” + +Or approving of a Twitter account threatening individual users with legal action for making jokes. + +I'm not sure that the Fox News Press Team is entering into the spirit of #foxnewsfacts pic.twitter.com/JL92a3DCpr— Thomas Haynes (@thomashaynes_) January 12, 2015 + +So, until we hear otherwise, we are calling this one a hoax. + +Still, we’ll always have #FoxNewsFacts as the funniest hashtag of the year to date to cheer us up.","1" +"Fake Fox News Twitter account emerges after #FoxNewsFacts goes viral","A Twitter account associating itself with Fox News is issuing legal threats to anyone who posts tweets that mock the cable news outlet. But the account is not official, a Fox News spokesperson told the Washington Examiner media desk. + +""It's a fake account,"" the spokesperson said. + +The account ""@FoxNewsPress"" surfaced over the weekend in response to a hashtag that made fun of a recent segment on Fox News. The segment involved author Steve Emerson, who writes books on terrorism, claiming that there are certain ""no-go"" zones for non-Muslims in Europe, including Birmingham, which he wrongly claimed is a ""totally muslim"" city. + +The segment launched #FoxNewsFacts on Twitter, wherein critics of the news channel attributed sometimes humorous, though false, assertions to Fox. ""You are not allowed to eat anything during daylight in Ramada Inns,"" one person tweeted with the hashtag #FoxNewsFacts. + +Sign Up for the Politics Today newsletter! +MORE STORIES +CNN begins researching use of drones +BY EDDIE SCARRY | 01/12/15 12:35 PM +Drones are often at the center of controversy for their ability to access private areas by air. +Mark Sanford accused of violating House ethics rules +BY SEAN LENGELL | 01/12/15 12:15 PM +CREW says the South Carolina Republican violated ethics rules by accepting more than $100,000 in stock from... +U.Va. fraternity from Rolling Stone article reinstated +BY KELLY COHEN | 01/12/15 11:25 AM +Phi Kappa Psi restored to full status after a police investigation failed to find ""any substantive basis."" +Top House Democrat lays out $1.2 trillion progressive tax plan +BY JOSEPH LAWLER | 01/12/15 11:17 AM +A Maryland Democrat wants to tax high earners and stock trades to transfer money to the middle class. +CNN's Tapper 'ashamed' US did not participate in Paris march +BY EDDIE SCARRY | 01/12/15 10:09 AM +CNN's Jake Tapper wrote in an op-ed for CNN.com on Monday, that ""as an American: I was ashamed."" +WEX TV +John Hoeven touts Keystone XL +John Hoeven touts Keystone XL +Obama takes an economic victory lap +Obama takes an economic victory lap +Obama on community college: 'I want to make it free' +Obama on community college: 'I want to make it free' +Weekly Examiner: Terror in France +Weekly Examiner: Terror in France +The fake @FoxNewsPress account then emerged Sunday to apparently further mock Fox. It began responding to many of the #FoxNewsFacts tweets with legal threats. ""This has not come from @FoxNews team,"" a typical threat would read. ""Remove or face legal recourse."" + +The account was an apparent jab at Fox's reputation among journalists for having a particularly hostile public relations department. + +For his part, Emerson did eventually apologize for his statements on Fox. ""I have clearly made a terrible error for which I am deeply sorry,"" he told the Telegraph. My comments about Birmingham were totally in error.","1" +"AP report: Police say gunman in FSU library shooting, Myron May, was alumnus","TALLAHASSEE, Fla. —Police said the suspected gunman in a shooting at Florida State University was an alumnus, according to a report by the Associated Press. + +The Tallahassee Police Department held a news conference on Thursday morning to discuss a shooting at FSU that left three students injured. The gunman was shot and killed by officers, police said. + +A Florida State University student recalls the terrifying moments when a gunman opened fire on campus on Thursday morning. Jason Derfuss said he later realized the books in his backpack stopped the bullets from striking him. Investigators said three other students were injured and the gunman was shot and killed by police. +MORE +Full video: Student says textbooks stopped bullet + +The report said the shooter, Myron May, graduated from FSU before attending Texas Tech University's law school. + +May was fatally shot early Thursday morning after he shot three people at the Florida State Library, police said. + +Two students were taken to Tallahassee Memorial Hospital with gunshot wounds and a third victim was treated on scene for a grazing wound, according to Tallahassee Police spokesman Dave Northway. The victims' names and conditions were not released. + +Full video: Gov. Scott addresses shooting at FSU + +A campus alert urged people to take shelter and stay away from doors and windows after the gunman opened fire inside Strozier Library just after 12 a.m., according to police. + +""FSU alert dangerous situation main campus-Tallahassee,"" the alert read. ""Seek shelter immediately, away from doors and windows."" + +There were approximately 300 to 400 students inside the library at the time of the shooting. Students shoved tables and book shelves against doors to barricade themselves. + +Full press conference from Tallahassee PD + +As the incident unfolded, anxious students sent tweets and text messages to loved ones. + +""There's a man with a gun in the library,"" Samantha Sillick said in a text to her father. ""I love you."" + +A survivor told WESH 2 News he was there during the terrifying moments when bullets began to fly. + +""I heard what was unmistakably a gunshot behind me, and initially I kind of tried to rationalize it as a firecracker, but I knew exactly what it was,"" said Jason Derfuss, an FSU student. ""He gunned down another student right in front of me about 50 feet away."" + + + +Derfuss said the gunman also fired several gunshots at him, but the books in his backpack stopped the bullets from striking his body. + +Police said the officers rushed the area and shot the gunman when he refused to drop his weapon and fired at officers. + +""Instead of complying with their commands, the gunman, in turn, fired a shot at the officers and they returned fire, killing the suspect,"" said Northway. + +Police said the gunman acted alone, and there is no further threat to the university. Students have been allowed back into the library to retrieve their belongings. + +""If there's any positive news we can take from this occurrence is that the victim count was not greater,"" said the city's Mayor-elect Andrew Gillum. + +On Thursday, Gov. Rick Scott said he is praying for the victims, their families and the entire FSU community. + +""I know every Seminole has a heart of a dreamer and every dreamer is resilient,"" said Scott. + +FSU's new president, John Thrasher, released a statement that said in part: + +""The Florida State University community is extremely saddened by the shootings that took place early this morning at Strozier Library, in the very heart of campus, and our thoughts and prayers are with the families and loved ones of all those who have been affected."" + + +Thrasher also said the university will be increasing security measures and providing strong law enforcement presence on and around campus on Thursday, although the campus will be closed for the day. + +FSU officials also said there will be counselors available for any students or employees in need. + +The five officers involved in the shooting were placed on routine paid administrative leave. + +Abigail Taunton told the AP that May had recently been staying at a guest house she owns in a rural area in the Florida Panhandle. She said police interviewed her husband, David, after the shooting. + +FSU is one of the top research universities in the nation. It has about 40,000 students spread out in various campuses in the city, and is also considered one of the nation's top-ranked football teams. + +The campus will reopen for classes and normal operations on Friday.","1" +"Saudi airline rep denies plan to separate men and women on flights","Saudia Airlines, the state-run airline of Saudi Arabia, does not have plans to separate passengers based on gender, according to an airline source quoted in stories claiming the opposite. + +Several Gulf area and UK media outlets reported that the airline planned to seat unrelated men and women after receiving complaints. + +“There are solutions to this problem,"" Abdul Rahman Al Fahd, an assistant marketing manager for Saudia, was quoted as saying to Saudi Arabia daily Ajel. ""We will soon enforce rules that will satisfy all passengers."" + +Although Ajel reported that those solutions would include separating men and women unless they are closely related, the source of the quote said the story was fabricated, and that his quote was taken out of context. + +@RunwayGirl @JetwayMJ my name was mentioned there, it is a total false and fabrication. + +— عبدالرحمن الفهـد (@ahfahad) January 2, 2015 + +@RunwayGirl a follower asked me how would the airline solve the issue of separate family seating that is a root of most delays, I answered: + +— عبدالرحمن الفهـد (@ahfahad) January 2, 2015 + +@RunwayGirl we are trying a solution and awaiting the outcome(.)It is on how to rearrange splitting family members aboard but got twisted:) + +— عبدالرحمن الفهـد (@ahfahad) January 2, 2015 + +The rumor was perhaps more believable after an incident last week, when ultra-Orthodox Jewish men delayed an Israel-bound Delta flight because they refused to sit next to female passengers. + +And Saudi Arabia has persistent gender disparities: The World Economic Forum ranked Saudi Arabia 127th out of 136 countries for women's rights in its Global Gender Gap Report in 2013. + +There are restrictions on women — for example, they are not permitted to drive in the country — however there have also been signs of recent change. Saudi Arabia’s King Abdullah announced in 2011 that women would be able to vote in 2015 elections. + +Saudia is a member of the SkyTeam alliance. + +Have something to add to this story? Share it in the comments.","1" +"No gender segregation on Saudia","Saudi Arabian Airlines on Sunday dismissed claims made by some local media outlets that the national flag carrier is planning to segregate men and women on its flights. +Denying that such arrangements are being considered, Abdullah Al-Ajhar, the airline’s spokesman, termed the reports as “false” and “misleading.” +Speaking to Arab News, Al-Ajhar asserted that there are no plans to separate passengers based on their gender. +A few days ago, international media, quoting a local daily, reported that Saudia is planning to segregate according to gender, following complaints of uncomfortable journeys by male relatives of female passengers. +According to the report, some passengers complained that females sitting next to non-related male passengers felt uncomfortable. +In the report, the international news organization quoted Abdul Rahman Al-Fahd, airline’s vice president for marketing, as saying that measures would be taken to solve this problem. +However, the official concerned denied having made any statement on segregation. He asserted that his quote was taken out of context. +Al-Fahd tried to clear the air on the matter by tweeting what he claimed was his real response: “I answered: We are trying to find a solution and awaiting the outcome.” +In a significant but unrelated move, Saudia has extended the validity of domestic flight tickets from 6 months to 1 year from Jan. 1. +إعلان +What's this? inRead™ invented by Teads.tv + +According to the new system, passengers will have to purchase tickets while making reservations on domestic flights, with the ticket validity extended to one year to give passengers enough flexibility, a Saudia official said.","1" +"Saudi Arabian Airline Rep Denies Plan to Separate Men and Women on Flights","According to an airline source quoted in stories claiming the opposite, Saudia Airlines, the state-run airline of Saudi Arabia, does not have plans to separate passengers based on gender. Several Gulf","1" +"YPG Confirms: Gill Rosenberg Not Captured in Kobani","Eran Cicurel, an editor at Voice of Israel, has quoted YPG fighters familiar with the situation in Kobani, saying that Gill Rosenberg was not captured by IS. Cicurel's claims contradict IS claims, which made announcements on IS-affiliated websites Samoach al-Islam, al-Platform Media, and Twitter that Rosenberg had been captured. Earlier in the day, IS media sources even alleged that a video was coming soon. Considering the scale of yesterday's IS advance, the story appeared plausible. Close friends, comrades, and supporters also voiced credible concern on Rosenberg's Facebook page. The YPG fighters noted, through Cicurel, that Rosenberg was not in the city of Hoban at the time that IS claims she was abducted. They also called the story ""mere propaganda"". While not a confirmation per se, Cicurel's claims, in addition to circumstantial evidence, have made the story of Rosenberg's capture implausible. Established Israeli sources exclusively ran the story purporting to be primary sources of reporting Rosenberg's capture. The Haaretz Israeli News, the Times of Israel, the Jerusalem Post, and Ynet News almost immediately published similar reports, while media outside Israel have either not reported on the story or quoted the Israeli media. It is illegal for an Israeli citizen to travel to an Israeli-declared hostile state, including Iraq and Syria, for any reason including business and media reporting. Rosenberg, age 31, has become infamous in recent months for joining YPG fighters in Kobani despite the illegality of her endeavor. In the past 24 hours, an IS advance pushed the YPG back on four fronts, including the northern side that borders Turkey. However, the YPG has mitigated many IS gains, due to US airstrikes and the arrival of Turkish forces sealing the border to the north. Despite the new information, little is still publicly known about Rosenberg's status at this time. Pro-IS sources are still claiming that she is captured, while other sources are staying quiet. A link will be added in the comments if the story is officially confirmed or denied. Pictures of Rosenberg (Not a repost! The article is completely original content. These images are merely appended for informational purposes) Kobani map November 28 (credits to @deSyracuse) Kobani map late November 29 (credits to @macroarch). Note: Some IS gains have been pushed back, but claims of a total reversal are untrue.","1" +"Canadian-Israeli Woman Says She Hasn’t Been Captured By ISIS","Gillian Rosenberg, the Canadian-Israeli woman fighting ISIS with Kurdish forces in Syria, has updated her Facebook page to say that, contrary to reports, she has not been captured by militant forces. + +“Guys, I’m totally safe and secure,” she wrote Monday. “I don’t have Internet access or any communication devices with me for my safety and security. I can’t reply regularly and only happened to have a chance to log in and see these buklshit [sik] news stories. Ignore the reports that I’ve been captured.” + +News of Rosenberg’s apparent capture first emerged online on ISIS-affiliated websites early Sunday morning. The websites did not post any proof or state whether she was in Iraq or Syria, The Jerusalem Post reported, only saying that she had been taken hostage following three suicide attacks on Kurdish forces. + +The Canadian and Israeli governments said Sunday that they were looking into reports that a Canadian-Israeli woman had been captured by ISIS in Syria. They have not yet confirmed the news posted on Rosenberg’s page. + +Rosenberg is believed to be the first foreign female fighter to join Syrian Kurds in their fight against ISIS. + +In an interview with Israel Radio earlier this month, Rosenberg claimed to be in Iraq and said she was training with Kurdish guerrillas and planned to battle militants in Syria. When asked about her decision to fight, she said, “[The Kurds] are our brothers. They are good people. They love life, a lot like us, really.” + +Rosenberg left Canada and moved to Israel in 2006 and served for two years in the Israeli Defense Forces. + +In 2009, she was arrested and extradited to the United States for her involvement “in a phony ‘lottery prize’ scheme that targeted victims, mostly elderly.” She served three years in jail for fraud. + +Rosenberg said she communicated with Kurdish fighters online before deciding to join them. According to her Facebook page, she arrived in Iraq on Nov. 2. + +Rosenberg recently wrote about her eagerness to join the Kurdish forces on her Facebook page. + +She also posted pictures of herself, seemingly in Iraq and Syria. + +On Nov. 20, Rosenberg said that she would not have access to the internet for two weeks and that someone else would be managing her account. + +Photos of Rosenberg brandishing a weapon and stepping on an ISIS flag appeared on LiveLeak on Nov. 22. + +liveleak.com + +liveleak.com + +On Monday, in response to the rampant rumors of her capture, she appears to have posted a personal comment on her Facebook page. + +The person running her page also posted a follow-up message.","1" +"Canadian woman 'captured by ISIS in Syria' says she is actually fine and still fighting the jihadists, despite kidnap reports","The Canadian woman who was reportedly kidnapped by ISIS has said she is fine, and that rumors of her capture spread on jihadist websites are untrue. + +Gill Rosenberg, 31, joined the ranks of the Kurdish peshmerga fighting force this year, which has elite all-female units. + +ISIS sources reported Sunday that Rosenberg was captured in the contested town of Kobane, on the Turkish border, and were gleefully debating whether to execute her or try to negotiate a prisoner swap. + +But now Rosenberg, who leaves sporadic updates about her campaign against extremism on Facebook, has posted to clarify that she is in fact alive and well. + +Scroll down for video + +Military history: Rosenberg, pictured in uniform, was formerly a member of the Israeli Defense Force + +On the attack: Rosenberg uploaded pictures of herself, left, dressed for war in Syria in recent weeks + +'Captured': Gill Rosenberg, a Canadian with dual Israeli citizenship, was reportedly captured - but took to social media to dispell the rumor + +Before: Rosenberg, who went to Syria earlier this year, is pictured above before she left + +She wrote: 'Guys, I'm totally safe and secure. I don't have Internet access or any communication devices with me for my safety and security. + +'I can't reply regularly and only happened to have a chance to log in and see these bu*****t news stories. Ignore the reports I've been captured.' + +Sources in the Kurdish militia also confirmed that she is unharmed and was not captured. + +Idris Nassan, an official in Kobane, said he had been told by peshmerga members she is fine, and dismissed the reports of propaganda.. + +Even when the initial reports came out, some sources were sceptical and said Rosenberg was nowhere near Kobane in the first place. + +Rosenberg, a joint citizen of Israel who served in the Israeli Defense Force, went to fight against the so-called Islamic State earlier this month, while they were locked in combat over Kobane, a town on the Turkey-Syria border. + +She had earlier posted on social media explaining her decision to go and fight, declaring she sympathized with the Kurds, whose territory has come under heavy assault. + +Her position in the Israeli military is thought to have been a non-combat role. + +After the reports over the weekend of her capture, Canadian and Israeli government sources said they were investigating the possibility. + +IS jihadists began advancing on Kobane on September 16, hoping to quickly seize the small town and secure its grip on a large stretch of the Syrian-Turkish border, following advances it made in Iraq. + +At one point, it looked set to overrun the town, but Kurdish Syrian fighters, backed by coalition air strikes and an influx of Iraqi Kurdish peshmerga forces, have held back the group. + +Allies: Female peshmerga soldiers are seen preparing for battle in Syria, near the front lines with ISIS + +War-torn: Rosenberg and her allies were captured in Kobane, near the Turkish border, according to jihadist websites","1" +"Israeli Canadian fighting ISIS posts on Facebook: I'm safe and secure","Gill Rosenberg, the Canadian Israeli volunteer fighting with Kurdish forces, posted on Facebook on Monday night that she was ""safe and secure"" and not captured by ISIS guerillas, as had been widely reported in the media. has apparently not been captured by the Islamic State, as widely reported in the media. + +""Guy, I'm totally safe and secure. I don't have Internet access or any communication devices with me for my safety and security,"" the post continued. ""I can't reply regularly and only happened to have a chance to log in and see these bullshit news stories. Ignore the reports I've been captured. Yalla, Acharai [after me]!"" + +Haaretz was unable to verify that Rosenberg herself was responsible for the post. + + + +A second post uploaded to Rosenberg's Facebook page half an hour later read: ""All: On Behalf of Gill Rosenberg - please be advised that she is safe and sound. DO NOT listen to the reports for the past few days about kidnapping. I will update you again when I hear from her. Please keep her in your thoughts and prayers!! Thank you!"" + +Several Islamist blogs and websites reported last week that Rosenberg +had been captured by ISIS. + +A blog considered to be one of the Islamic State's media arms reported that several female fighters who fought alongside the Kurds have been captured, among them Rosenberg. According to the report, prior to their capture Islamic State fighters made three suicide bombing attacks against Kurdish outposts, killing some and capturing many others. + +Kurdish sources denied the reports, saying that Rosenberg wasn't in the area when it was attacked. + +In her previous Facebook post on November 20, Rosenberg wrote that she would be without internet access for at least two weeks. + +""My Facebook account and friend requests are being managed by someone else until I have access again in apx 2 weeks time on or around week of 12/8,"" she wrote at the time. ""Please do not message as this is not me. Thank you."" + +Rosenberg, 31, a resident of Tel Aviv, joined the Kurdish troops against Islamic State in northern Syria earlier this month. According to reports, Rosenberg said she had contacted Kurdish fighters over the +Internet before traveling through Iraq to train at one of their camps on the Syrian border. + +According to Walla, Rosenberg immigrated to Israel from Canada in 2006, leaving behind a career as a civilian pilot, and served for two years in the Israel Defense Forces. In 2009, she was extradited to the United States and jailed over an international phone scam, one of her former lawyers said. + +Israel Radio aired an interview with Rosenberg earlier in November in which she said she had travelled to Iraq, was training with Kurdish guerrillas and would fight in neighboring Syria. + +""They are our brothers. They are good people. They love life, a lot like us, really,"" she told Israel Radio, explaining her decision to enter the combat zone in northern Syria.","1" +"Gill Rosenberg, Canadian-Israeli Woman Feared Kidnapped By ISIS, Says She's Safe","A Canadian-Israeli woman who was feared kidnapped by the Islamic State over the weekend appears to have posted a message on Facebook debunking reports of her capture. + +Gill Rosenberg wrote on her Facebook page on Monday that she is ""safe and secure."" + +Canada's Globe and Mail newspaper also reported earlier on Monday that Kurdish media carried unverified statements from Rosenberg, in which she stated that she was fine. + +A former IDF soldier who joined up with Kurdish militias to fight against the Islamic State, Rosenberg had been the subject of a Canadian government inquiry after rumors circulated on jihadist forums over the weekend that she had been taken prisoner in the Syrian town of Kobani. + +The Israeli newspaper Haaretz reported that the 31-year-old from White Rock, a suburb of Vancouver, served two years in the Israeli army. While in Israel in 2009 she was arrested as part of an international fraud ring and brought to the United States to serve time in jail. Haaretz reports that in the years since, Rosenberg began contacting Kurdish militias via the internet, before traveling to Iraq and Syria to fight alongside them against the extremist militants.","1" +"Israeli-Canadian Woman 'Captured' By ISIS Says She Is 'Safe And Secure'","Gill Rosenberg, a Canadian-Israeli woman, who ISIS had claimed to have abducted, posted on Facebook Monday afternoon that she was “safe and secure.” On Sunday, contributors to a number of jihadist platforms had claimed that the Islamic State group had captured a “female Zionist soldier fighting with the Kurds against the Islamic State” from Kobani. + +A message, allegedly posted by Gill Rosenberg, on her Facebook account Monday afternoon Gill Rosenberg's Facebook profile + +A message posted through Rosenberg's Facebook account Monday Gill Rosenberg's Facebook profile + +International Business Times was unable to verify that Rosenberg herself was responsible for the post. + +Rosenberg, 31, who migrated to Israel from Canada in 2006, is believed to have served for two years in the Israeli military, according to a report by Haaretz. She had earlier claimed, through photos published on the same account, that she had joined Kurdish forces battling ISIS in Iraqi Kurdistan in the country’s north. + +Jihadists believed to be loyal to ISIS had claimed on Sunday that Rosenberg, along with a number of female fighters, had been abducted near Kobani and that the Israeli military was deliberately trying to curb the news of her capture. However, a number of media outlets subsequently raised doubts over the claims, citing Kurdish sources, who said that Rosenberg was nowhere near Kobani. + +""This is false propaganda by IS,” Kurdish sources told The Times of Israel. ""We can say with a high level of certainty that no Israeli volunteer, or any international volunteer for that matter, arrived to fight in the city of Kobani in Syria."" + +The Israeli government, which on Sunday said it was investigating reports of her capture, had also stressed that the information was of “dubious credibility,” according to a report by The Times of Israel. “I cannot confirm that [report of Rosenberg’s capture] and I hope that it isn’t true,” Israel’s Defense Minister Moshe Ya'alon had reportedly said.","1" +"Kurds Deny Gill Rosenberg was in Kobane","Sources in the Kurdish underground in Syria denied Sunday night that Canadian-Israeli Gill Rosenberg, 31, had been in the Kobane region, as claimed by Islamist and Palestinian websites that reported she was captured by ISIS during the fighting in that area. The report about Rosenberg's capture has not been confirmed by ISIS. + +An American who is fighting in the ranks of the Kurds told Voice of Israel that Rosenberg was not in the Kobane region. “She was never in Kobane, that's not reasonable that she was captured,” he said. The head of the station's foreign news desk, Eran Sikorel, said that he, too, had information that Rosenberg had been stationed in eastern Syria and not in the Kobane region, which is in central Syria. + +Yisrael Hayom quotes a senior Kurdish source who confirmed that Rosenberg joined the Kurdish resistance in Syria and said she was the first western woman to join its fighters. The source added that ten other western citizens who are not of Kurdish origin have also joined the Kurdish fighters in recent days. + +Earlier on Sunday, the monitoring group SITE said Islamic State (ISIS) jihadists claimed a ""female Zionist soldier"" had been captured in the embattled Syrian border town. + +Some jihadists said the woman might be Rosenberg, who had served in the Israel Defense Forces and had volunteered to fight with the Kurds, the monitoring group said. + +""The Government of Canada is aware of reports that a Canadian citizen was kidnapped in Syria,"" a foreign ministry statement said, according to AFP. + +""Canada is pursuing all appropriate channels to seek further information and officials are in close contact with local authorities,"" added the statement. + +Israel, too, said it was following reports about Rosenberg.","1" +"Somalia Shebab chief Ahmed Abdi Godane likely dead in US strike: Source","NAIROBI: The death of the leader of Somalia's Al-Qaeda-linked Shebab rebels in a US air strike is a ""very strong probability,"" but still unconfirmed, security sources said today. + +""There is a very strong probability that he is dead.... This requires verification on the ground, which is not simple,"" said a Western security source, who asked not be identified.","1" +"6 Islamist militants killed in US attack in Somalia","MOGADISHU, Somalia — Al-Shabaab’s top leader was traveling in one of two vehicles hit Monday night in a US military strike, a member of the Somali Islamic extremist group said Tuesday. + +The spokesman would not say whether al-Shabaab leader Ahmed Abdi Godane was among the six militants killed. + +The two vehicles were heading toward the coastal town of Barawe, al-Shabaab’s main base, when they were hit, Abu Mohammed told the Associated Press. A witness in Somalia described ground-shaking explosions in the strike. + +Al-Shabaab attacked the upscale Westgate Mall in Nairobi, Kenya, killing at least 67 people, a year ago this month, and the US targeted planners of the bloody assault. US commanders were waiting to determine the attack’s outcome. + +“US military forces conducted an operation in Somalia today against the al-Shabaab network. We are assessing the results of the operation and will provide additional information as and when appropriate,” said Pentagon press secretary Rear Adm. John Kirby. + +After the US strike in a forest south of Mogadishu, masked Islamic militants in the area arrested dozens of residents they suspected of spying for the US and searched nearby homes, a resident said. + +“Mass arrests just started, everyone is being detained,” said Mohamed Ali, who lives in the Sablale district. “They even searched nearby jungles and stopped the nomads transporting milk and grass to the towns for questioning.” + +A senior Somali intelligence official said a US drone targeted Godane as he left a meeting of the group’s top leaders. Godane, also known as Mukhtar Abu Zubeyr, is the group’s spiritual leader under whose direction the Somali militants forged an alliance with al Qaeda. In 2012, the US offered a reward of up to $7 million for information leading to his arrest. + +The Somali official, speaking on condition of anonymity since he was not authorized to speak to the media, said intelligence indicated Godane “might have been killed along with other militants.” The official said the attack took place 105 miles (170 kilometers) south of Mogadishu, where al-Shabaab trains its fighters. + +As government and African Union forces were heading to a town in the district, they heard what sounded like an “earthquake” as the al-Shabaab bases were hit, the governor of Somalia’s Lower Shabelle region, Abdiqadir Mohamed Nor, told the Associated Press. + +“There was an airstrike near Sablale. We saw something,” Nor said. + +The US has carried out several airstrikes in Somalia in recent years. + +A US missile strike in January killed a high-ranking intelligence officer for al-Shabaab, and last October a vehicle carrying senior members of the group was hit in a US strike that killed al-Shabaab’s top explosives expert. + +The latest US action comes after Somalia’s government forces regained control of a high-security prison in the capital that was attacked Sunday. Seven heavily armed suspected al-Shabaab members had attempted to free other extremists held there. + +Somali officials said all seven attackers, three government soldiers and two civilians were killed. Mogadishu’s Godka Jilacow prison is an interrogation center for Somalia’s intelligence agency, and many suspected militants are believed to be held in underground cells there. The attack started when a suicide car bomber detonated an explosives-laden vehicle at the gate of the prison and the gunmen then fought their way into the prison. + +Al-Shabaab had attacked the mall in Nairobi last year in retaliation against Kenya for sending troops into Somalia against the extremists. Godane said at the time that the attack was carried out in retaliation for the West’s support for Kenya’s Somalia intervention and the “interest of their oil companies.” + +Al-Shabaab is now mostly active in Somalia’s rural regions after being ousted from the capital by African Union forces in 2011. + +Somali military officials last week launched a military operation to oust al-Shabaab from its last remaining bases in the southern parts of Somalia. On Saturday the militants withdrew from the town of Bulomarer, about 70 miles (110 kilometers) south of Mogadishu, after hours of fighting.","1" +"Somali terrorist leader dead after US airstrike","WASHINGTON — The Pentagon on Friday confirmed the death of the leader of the al-Shabab terror group, Ahmed Abdi Godane, who was the target of a U.S. airstrike Monday in Somalia. + +The Pentagon’s press secretary, Rear Adm. John Kirby, confirmed the death in a brief written statement. President Barack Obama, speaking at the conclusion of a NATO summit in Newport, Wales, said the successful U.S. strike was an example of his administration’s determination to hit back at terrorists. + +Obama said the U.S. would use the same approach in degrading the Islamic State group in Iraq and Syria. + +“We have been very systematic and methodical in going after these kind of organizations” that threaten U.S. personnel and the homeland, Obama said. “That deliberation allows us to do it right, but have no doubt: We will continue to do what is necessary to protect the American people.” + +The White House declared a counterterrorism success. + +“Godane’s removal is a major symbolic and operational loss to the largest al-Qaida affiliate in Africa and reflects years of painstaking work by our intelligence, military and law enforcement professionals,” a White House statement said. + +“Even as this is an important step forward in the fight against al-Shabab, the United States will continue to use the tools at our disposal – financial, diplomatic, intelligence and military – to address the threat that al-Shabab and other terrorist groups pose to the United States and the American people.” It added. + +U.S. officials had said after the strike on Monday that U.S. special operations forces using manned and drone aircraft had destroyed an encampment and a vehicle using several Hellfire missiles and laser-guided munitions. But they did not confirm that Godane had been killed until Friday. + +The State Department declared al-Shabab a terrorist organization in February 2008. + +Kirby said on Tuesday, before the Pentagon was certain that Godane had died, that the U.S. strike was conducted south of Mogadishu and that it had destroyed the vehicle that was targeted. He noted that in September 2013, Godone had publicly claimed al-Shabab was responsible for the deadly Westgate Mall attack in Nairobi, Kenya. + +“Under the leadership of Godane, al-Shabab has claimed responsibility for many bombings, including suicide attacks in Mogadishu and in central and northern Somalia, typically targeting officials and perceived allies of the federal government of Somalia, as well as the former transitional federal government of Somali,” Kirby said Tuesday.","1" +"US airstrike targets Al Shabaab leader Ahmed Abdi Godane in Somalia","The US is assessing whether an airstrike on an encampment in Somalia killed the leader of the Al Shabaab terrorist group. + +Pentagon spokesman John Kirby said drones and manned aircraft bombed a gathering of Al Shabaab commanders in a camp in south-central Somalia on Monday. + +""US special operations forces using manned and unmanned aircraft destroyed an encampment and a vehicle using several Hellfire missiles and laser-guided munitions,"" he said. + +Mr Kirby confirmed that the attack was aimed at leader Ahmed Abdi Godane, also referred to as Abu-Zubayr, and that the bombs definitely hit the meeting of Shabaab chiefs. + +But he said it was unclear if Godane had been killed in the raid. + +""We are still assessing the results of the operation, and we'll provide additional information when and if appropriate,"" he said. + +The assault did not involve US ground troops, Mr Kirby added. + +He declined to provide details of the special operations forces' unit that took part in the air raid or the nature of the intelligence that led to the strike. + +The militant group is fighting to overthrow the Somali government, regularly launching attacks against state targets and in neighbouring countries that contribute to the African Union force. + +Since taking charge in 2008, Godane has restyled Al Shabaab as a global player in the al Qaeda franchise - a transformation that was highlighted when it killed at least 67 people in an attack on a Kenyan shopping mall last September. + +The US State Department has listed Godane as one of the world's eight top terror fugitives and, if confirmed, his death would mark a serious setback for Al Shabaab forces. + +The bombing raid reflected a commitment by Washington and its allies ""to detect, deter, disrupt and defeat violent extremists who threaten progress in the region, as well as ... threaten to conduct terrorist attacks against innocent people around the world,"" Mr Kirby said. + +ABC/wires","1" +"Al-Shabaab Terror Group Leader Killed in U.S. Airstrike","The Pentagon confirmed today that the U.S. killed Ahmed Abdi Godane, the leader of the al-Shabaab insurgent group in Somalia, in an airstrike this week. + +U.S. special operations forces targeted Godane in southern Somalia in a Sept. 1 attack using manned aircraft and drones to destroy an encampment and a vehicle. It took several days to confirm initial reports that he died in the attack. + +“The United States works in coordination with its friends, allies and partners to counter the regional and global threats posed by violent extremist organizations,” Rear Admiral John Kirby, the Pentagon’s spokesman, said in an e-mailed statement confirming the mission’s success. + +Al-Shabaab, an offshoot of al-Qaeda, was declared a terrorist organization by the U.S. State Department in 2008. Godane claimed responsibility for the attack last year on the Westgate shopping mall in Kenya’s capital of Nairobi, in which at least 67 people died. The U.S. has offered a $7 million reward for information on his whereabouts. + +“Godane’s removal is a major symbolic and operational loss to the largest al-Qaeda affiliate in Africa and reflects years of painstaking work by our intelligence, military and law enforcement professionals,” White House Press Secretary Josh Earnest said in a statement. +Godane was among a number of “high-ranking” al-Shabaab officials who were meeting at Dhaytubako, about 300 kilometers (186 miles) southwest of the capital, Mogadishu, when the attack occurred, Lower Shabelle Governor Abdulkadir Mohamed Nur said in a phone interview Sept. 2. + +Suicide Bombings + +In recent months, al-Shabaab claimed responsibility for a suicide bombing in Djibouti that killed a Turkish national and wounded several Western soldiers as well a car bomb at the Mogadishu airport that targeted and killed members of a United Nations convoy, according to the statement. + +Al-Shabaab was responsible for twin suicide bombings in Kampala, Uganda, on July 11, 2010, that killed more than 70 people, including one American. The group has also been responsible for the assassination of Somali peace activists, international aid workers, numerous civil society figures, and journalists. + +To contact the reporter on this story: Terry Atlas in Washington at tatlas@bloomberg.net + +To contact the editors responsible for this story: John Walcott at jwalcott9@bloomberg.net Larry Liebert, Michael Shepard","1" +"Al-Shabab leader who ordered Kenya mall massacre believed killed in US drone attack in Somalia","Ahmed Abdi Godane is the spiritual leader of al-Shabab + +He is believed among six people killed in a U.S. airstrike on two cars near the al-Shabab stronghold of Barawe + +Godane is believed to have ordered the Westgate Mall massacre in Kenya in September 2013 that killed 67 people + +U.S. officials have not yet confirmed Godane is among the dead + +U.S. drone strikes are believed to have killed the leader of the Somali terrorist group al-Shabab, who ordered the massacre at a Kenyan shopping mall last year that killed 67 people. + +U.S. Intelligence officials believe Ahmed Abdi Godane was traveling in a two-car convoy Monday night near al-Shabab's main base in Barawe when American drone aircraft hit the vehicles with missiles. + +Six people were killed in the attack and Somali authorities say they think Godane is among the dead - though the Pentagon said it is still awaiting confirmation. + +Godane, also known as Mukhtar Abu Zubeyr, is al-Shabab's spiritual leader under whose direction the Somali militants forged an alliance with al-Qaida and became the most high-profile terrorist group in Africa. + +Scroll down for video + +Ahmed Abdi Godane is believed one of six people killed when a drone fired on his two-car convoy in Somalia on Monday night, though U.S. officials have not confirmed the death + +Dangerous as ever: Even though al-Shabab fighters have been kicked out of the capital of Mogadishu, they have continued attacking targets throughout Africa + +Under Godane's orders, the group attacked the upscale Westgate Mall in Nairobi, Kenya, killing at least 67 people a year ago this month. + +The group was also responsible for a suicide bombing at a World Cup watching party in Kampala, Uganda, in 2010 that left 74 dead and 70 injured. + +The U.S. has targeted planners of the bloody Westgate assault, in which four Britons and two Canadians were killed. A month after the attack, Navy SEALs landed at al-Shabab's headquarters in Barawe and attempted to capture another mastermind behind the attack. + +In 2012, the U.S. government put a $7million price on Godane's head - though he has escaped justice until now. + +A witness to Monday's airstrike in Somalia described ground-shaking explosions caused by the missile. Somali government and African Union forces heading to a town in the district heard what sounded like an 'earthquake' as the al-Shabab bases were hit, the governor of Somalia's Lower Shabelle region, Abdiqadir Mohamed Nor, told The Associated Press. + +'There was an airstrike near Sablale. We saw something,' Nor said. + +U.S. commanders said they are waiting to determine the outcome of Monday's attack. + +'U.S. military forces conducted an operation in Somalia today against the al-Shabab network. We are assessing the results of the operation and will provide additional information as and when appropriate,' said Pentagon Press Secretary Rear Adm. John Kirby. + +After the U.S. strike in a forest near Sablale district south of Mogadishu, masked Islamic militants in the area arrested dozens of residents they suspected of spying for the U.S. and searched nearby homes, a resident said. + +Godane is believed to have ordered the Westgate Mall massacre in Nairobi, Kenya, last year that claimed 67 lives in Kenya. He also forged the groups alliance with al-Qaeda + +'Mass arrests just started, everyone is being detained,' said Mohamed Ali, who lives in Sablale district. 'They even searched nearby jungles and stopped the nomads transporting milk and grass to the towns for questioning.' + +The U.S. has carried out several airstrikes in Somalia in recent years. + +A U.S. missile strike in January killed a high-ranking intelligence officer for al-Shabab and last October a vehicle carrying senior members of the group was hit in a U.S. strike that killed al-Shabab's top explosives expert. + +The latest U.S. action comes after Somalia's government forces regained control of a high-security prison in the capital that was attacked on Sunday. Seven heavily armed suspected al-Shabab members had attempted to free other extremists held there. + +Somali officials said all seven attackers, three government soldiers and two civilians were killed. Mogadishu's Godka Jilacow prison is an interrogation center for Somalia's intelligence agency, and many suspected militants are believed to be held in underground cells there. The attack started when a suicide car bomber detonated an explosives-laden vehicle at the gate of the prison and the gunmen then fought their way into the prison. + +Al-Shabab attacked the mall in Nairobi last year to punish Kenya for sending troops into Somalia against the extremists. Godane said at the time that the mall attack was carried out in retaliation for the West's support for Kenya's Somalia intervention and the 'interest of their oil companies.' + +Al Shabab is now mostly active in Somalia's rural regions after being ousted from the capital by African Union forces in 2011. + +Somali military officials last week launched a military operation to oust al-Shabab from its last remaining bases in the southern parts of Somalia. On Saturday the militants withdrew from the town of Bulomarer, located about 110 kilometers (70 miles) south of Mogadishu, after hours of fighting.","1" +"US confirms death of Somalia terror group leader","WASHINGTON (AP) — U.S. airstrikes earlier this week killed the leader of the al-Shabab terrorist group in Somalia, the Pentagon said Friday. President Barack Obama said the death of Ahmed Abdi Godane demonstrated U.S. counterterrorism resolve and was an example of his deliberate approach to dismantling al-Qaida affiliated groups. + +The Pentagon's press secretary, Navy Rear Adm. John Kirby, announced the death in a brief written statement. It took the Pentagon four days to conclusively determine that Godane had not survived Monday's airstrikes. + +Al-Shabab has not publicly confirmed Godane's death. + +Somali President Hassan Sheikh Mohamud urged al-Shabab militants to renounce violence, saying they have an opportunity to embrace peace following Godane's death. + +""While an extreme hardcore may fight over the leadership of al-Shabab, this is a chance for the majority of members of al-Shabab to change course and reject Godane's decision to make them the pawns of an international terror campaign,"" he said in a statement. + +The Somali president said the U.S. operation was carried out ""with the full knowledge and agreement of"" his government and that Somalis ""greatly value the support of our international allies"" in the fight against al-Shabab. + +Obama, speaking at the conclusion of a NATO summit in Newport, Wales, told reporters the success against al-Shabab should leave no doubt about his determination to degrade and eventually destroy the Islamic State group in Iraq and Syria. The U.S. military announced later Friday that a mix of fighter jets, drones, attack planes and bombers launched four airstrikes Thursday and Friday in northern Iraq, destroying a host of Islamic State targets including an observation post, an armed vehicle and three mortar positions. + +Obama faces mounting pressure to take more aggressive military action against the Islamic State, which evolved from an al-Qaida affiliate that sprouted in Iraq in 2004. + +""We have been very systematic and methodical in going after these kinds of organizations"" that threaten U.S. personnel and the homeland, Obama said. ""That deliberation allows us to do it right, but have no doubt: We will continue to do what is necessary to protect the American people."" + +U.S. officials had said after the strike on Monday that U.S. special operations forces using manned and drone aircraft had destroyed an encampment and a vehicle using several Hellfire missiles and laser-guided munitions. But they did not confirm that Godane had been killed until Friday. + +The State Department declared al-Shabab a terrorist organization in February 2008. The implications of the group's loss of Godane are unclear. + +""The individual who takes his place will live in fear,"" said Army Col. Steven Warren, a Pentagon spokesman. + +Because Godane had weakened and effectively dismantled the al-Shabab council of leaders known as the shura, a meeting of regional commanders will have to take place to pick his successor, said Matt Bryden, the head of Sahan Research in Nairobi, Kenya. Bryden predicted the meeting will be difficult and dangerous to organize. + +Terrorism analyst J.M. Berger predicted a significant splintering between al-Shabab's domestically focused insurgents and internationally aspiring terrorists. + +Abdi Aynte, a Somali analyst who runs a Mogadishu-based think tank called the Heritage Institute for Policy Studies, predicted that Godane's death ""will almost certainly be the beginning of the end of the organization."" + +Under Godane's leadership, he said, al-Shabab had gradually become a guerrilla movement that avoided conventional warfare, tactics that suited it amid mounting military pressure from African Union troops and government forces. + +Godane, who was born in 1977 and raised in the town of Hargeisa in the autonomous region of Somaliland, was said to be a quiet boy who was interested in the Quran and Islamic studies in his early years. His relatives there described him as ""a private man"" who was devoted to Islamic teachings at mosques, said Mohamed Hassan, a former senior Somali intelligence official in Somaliland who once was tasked with tracking down Godane over charges the future terror leader stole money when he worked for a local telecommunications company. In Somaliland, he also had been accused of involvement in the murder of foreigners. + +Godane is believed to have settled in Mogadishu in 2004, working at local charities before he joined the Islamic Courts Union, al-Shabab's precursor group that once controlled Mogadishu and many parts of Somalia before it was ousted by Ethiopian forces. + +___ + +Baldor reported from Newport, Wales. Associated Press writers Jason Struziuso in Cairo, Rodney Muhumuza in Uganda, Abdi Guled in Mogadishu, Somalia, and Josh Lederman and Sagar Meghani in Washington contributed to this report. + +Sorry we are not currently accepting comments on this article.","1" +"Terror Leader Ahmed Abdi Godane Killed in U.S. Strike","Ahmed Abdi Godane — the leader of al Shabab, the Islamic militant organization behind the siege on a mall in Kenya last year — was killed in a U.S. military strike earlier this week, an al Shabab source told NBC News on Friday. + +The Pentagon confirmed the death later in the day. + +“Removing Godane from the battlefield is a major symbolic and operational loss to al Shabab,” said Rear Adm. John Kirby, a Pentagon spokesman. “The United States works in coordination with its friends, allies and partners to counter the regional and global threats posed by violent extremist organizations.” + +A U.S. security official also told NBC News earlier in the week that Shabab had been killed by the strike on Monday. U.S. officials had said publicly after the strike that Godane was targeted, but that they were not sure whether he was dead. + +The al Shabab source told NBC News that Godane was among 11 militants killed. Also killed were an operations leader, a financial official and a military strategist for the organization, the source said. + +“It’s a big win,” the U.S. security official said. “He was operationally savvy and ideologically driven, with aspirations off the charts.” The official said that nine Hellfire missiles and one 500-pound guided bomb had been used in the strike. + +The Reuters news agency reported Friday that the Somali prime minister had confirmed the death on Facebook, but Reuters later withdrew that report. A Somali government spokesman told Reuters that the government had not yet commented on whether Godane was dead. + +The siege last September at the Westgate Mall in Nairobi left 67 people dead and about 200 injured. + +The United States in 2012 offered a $7 million reward for his arrest. Godane took leadership of al Shabab after his predecessor was killed in an American airstrike in 2008.","1" +"U.S. airstrike kills Islamic Al Shabab terrorist leader in Somalia","Ahmed Abdi Godane was the 'principal target' of the Monday attack. + +A U.S. airstrike killed the leader of a Somali terrorist group Monday, the Pentagon confirmed Friday. + +Al Shabab head Ahmed Abdi Godane — who was considered one of the world's most wanted men — was the 'the principal target' of the attack, officials said Tuesday when they announced the strike. + +The Pentagon knew immediately that six people were killed in the Monday strike, but Godane was not identified as a victim until Friday. + +The other five victims have not been identified. + +Godane, also known as Mukhtar Abu Zubeyr, was the reviled leader of the Al Qaeda-affiliated group. The State Department desperately wanted to find him and had put a $7 million bounty on his head. + +His death deals a major blow to the Somali terror network, the Pentagon said. + +Rear Adm. John Kirby, the Defense Department’s chief spokesman, said the drone and aircraft attack directly targeted the terrorists. + +Six people, including Godane, were killed. The other five victims have not been named. + +In the strike, missiles destroyed a suspected terrorist compound near the port city of Barawe, a stronghold of the group. The missiles hit Godane as he left a meeting of the group's top leaders. + +President Barack Obama said airstrike was highly calculated and well planned. + +“That deliberation allows us to do it right,” he said at a Friday press conference. + +The airstrike against Al Shabab is part of the U.S.’s larger anti-terrorism campaign. Troops have previously launched strikes against ISIS terrorists in Iraq. + +“The goal has to be dismantle them,” Obama said of ISIS, Al Shabab and other terrorist organizations. + +With News Wire Services","1" +"Pentagon: death of al Shabaab leader in U.S. strike would be major blow","(Reuters) - The Pentagon is assessing whether an airstrike on an encampment in Somalia killed al Shabaab leader Ahmed Abdi Godane, but if confirmed the militant's death would represent a ""very significant"" blow to the group, the Pentagon said on Tuesday. + +Rear Admiral John Kirby told a Pentagon briefing that the U.S. special operations strike conducted on Monday involved manned and unmanned aircraft. Kirby said Hellfire missiles and laser-guided munitions were dropped on the camp in south-central Somalia, but he said it was too soon to say what the results of the strike had been. + +Since taking charge in 2008, Godane has restyled the group as a global player in the al Qaeda franchise - a transformation that was highlighted when it killed at least 67 people in an attack on a Kenyan shopping mall last September. + +(Reporting by Phil Stewart; Editing by Eric Beech)","1" +"Al-Shabaab co-founder confirmed killed by US air strike in Somalia","The Pentagon has confirmed that Ahmed Abdi Godane, the leader of the Islamist militant group al-Shabaab, was killed in a US air strike earlier this week. + +The United States previously said that the strike inside Somalia had targeted Godane, but did not know whether he had been killed. + +“We have confirmed that Ahmed Godane, the co-founder of al-Shabaab, has been killed,” said rear admiral John Kirby, the Pentagon press secretary, describing it as a “major symbolic and operational loss” for the militant group, which aligned itself with al-Qaida. + +Al-Shabaab is fighting to topple Somalia’s western-backed government and regularly launches bombings and gun attacks against state targets and civilians. Godane’s death could now lead to an internal power struggle. + +On Wednesday US officials had said they were still investigating to see whether the strike on an al-Shabaab encampment had killed Godane, 37, who reportedly trained with the Taliban in Afghanistan. + +At least three strikes hit a convoy of al-Shabaab vehicles in southern Somalia on Monday night, according to witnesses and a spokesman for the group who spoke later with the Associated Press. The al-Shabaab representative said that six al-Shabaab fighters had been killed in the strikes. + +The air raid came days after African Union (AU) troops and Somali government forces launched “Operation Indian Ocean”, a major offensive aimed at seizing key ports from al-Shabaab and cutting off one of their key sources of revenue: multi-million dollar exports of charcoal. AU forces were targeting Shabaab on several fronts, with Ugandan troops leading the offensives against the main port of Barawe, south of the capital, Mogadishu. + +The commander of the AU in Somalia has said the death of Godane would be a “proud and happy moment for all Africa”. + +Godane, who has a passion for poetry, seized world attention a year ago with the Westgate mall attack in Nairobi, which left at least 67 dead. He warned Kenya that it would suffer further atrocities unless it withdrew its troops from the AU force in Somalia. + +“You cannot withstand a war of attrition inside your own country,” he said in an audio message posted on a website linked to al-Shabaab. “So withdraw all your forces, or be prepared for an abundance of blood that will be spilt in your country.” + +Washington has carried out a series of drone missile strikes in the past, including attacks reportedly targeting Godane, but rarely confirms this officially. + +Godane took over the leadership of al-Shabaab in 2008 after then chief Adan Hashi Ayro was killed by a US missile strike. + +Also known as Mukhtar Abu Zubeyr, Godane was al-Shabaab’s spiritual leader under whose direction the Somali militants forged an alliance with al-Qaida. In 2012 the US offered a reward of up to $7m (£4.2m) for information leading to his arrest.","1" +"Al-Shabaab leader Ahmed Abdi Godane killed by US air strike in Somalia","The Pentagon has confirmed that Ahmed Abdi Godane, the leader of the Islamist militant group al-Shabaab, was killed in a US air strike earlier this week. + +The United States previously said that the strike inside Somalia had targeted Godane, but did not know whether he had been killed. + +“We have confirmed that Ahmed Godane, the co-founder of al-Shabaab, has been killed,” said rear admiral John Kirby, the Pentagon press secretary, describing it as a “major symbolic and operational loss” for the militant group, which aligned itself with al-Qaida. + +Al-Shabaab is fighting to topple Somalia’s western-backed government and regularly launches bombings and gun attacks against state targets and civilians. Godane’s death could now lead to an internal power struggle. + +On Wednesday US officials had said they were still investigating to see whether the strike on an al-Shabaab encampment had killed Godane, 37, who reportedly trained with the Taliban in Afghanistan. + +At least three strikes hit a convoy of al-Shabaab vehicles in southern Somalia on Monday night, according to witnesses and a spokesman for the group who spoke later with the Associated Press. The al-Shabaab representative said that six al-Shabaab fighters had been killed in the strikes. + +The air raid came days after African Union (AU) troops and Somali government forces launched “Operation Indian Ocean”, a major offensive aimed at seizing key ports from al-Shabaab and cutting off one of their key sources of revenue: multi-million dollar exports of charcoal. AU forces were targeting Shabaab on several fronts, with Ugandan troops leading the offensives against the main port of Barawe, south of the capital, Mogadishu. + +The commander of the AU in Somalia has said the death of Godane would be a “proud and happy moment for all Africa”. + +Godane, who has a passion for poetry, seized world attention a year ago with the Westgate mall attack in Nairobi, which left at least 67 dead. He warned Kenya that it would suffer further atrocities unless it withdrew its troops from the AU force in Somalia. + +“You cannot withstand a war of attrition inside your own country,” he said in an audio message posted on a website linked to al-Shabaab. “So withdraw all your forces, or be prepared for an abundance of blood that will be spilt in your country.” + +Washington has carried out a series of drone missile strikes in the past, including attacks reportedly targeting Godane, but rarely confirms this officially. + +Godane took over the leadership of al-Shabaab in 2008 after then chief Adan Hashi Ayro was killed by a US missile strike. + +Also known as Mukhtar Abu Zubeyr, Godane was al-Shabaab’s spiritual leader under whose direction the Somali militants forged an alliance with al-Qaida. In 2012 the US offered a reward of up to $7m (£4.2m) for information leading to his arrest. + +Mohamed Hassan Hamud, Somalia’s defence minister, said: “The Somalia federal government welcomes the death of the leader of the terrorist group al-Shabaab, Ahmed Godane.” + +He added: The death of Godane is big blow to al-Shabaab and also to the al-Qaida network which al-Shabaab is a member of.”","1" +"Pentagon: Airstrike killed terror leader in Somalia","WASHINGTON — The Pentagon on Friday confirmed that the leader of al-Shabab, an al-Qaeda-linked organization in Africa, was killed in a U.S. airstrike in Somalia this week. + +The leader, Ahmed Abdi Godane, was targeted Monday in an airstrike that hit a vehicle and compound in a militant stronghold south of the capital, Mogadishu. + +Al-Shabab has been linked to a number of attacks in Africa, including the bloody siege at the upscale Westgate Mall in Nairobi, Kenya, in September 2013 that killed 67 people. + +""Removing Godane from the battlefield is a major symbolic and operational loss to al-Shabab,"" Pentagon Press Secretary Rear Admiral John Kirby said in a statement. + +At the time of the strike, the Pentagon said it could not confirm Godane's death. + +Hellfire missiles and laser-guided munitions were used to strike the targets. Both manned aircraft and unmanned drones participated in the attack. + +The Pentagon said no U.S. ground troops were involved in the operation. + +""The United States works in coordination with its friends, allies and partners to counter the regional and global threats posed by violent extremist organizations,"" Kirby said in the statement released Friday. + +The United States has backed the Somali government, which has pushed the terrorist groups out of Mogadishu. Despite the government successes, the terror group has been able to operate in parts of the country that remain out of the reach of the government's influence. + +The White House said it would continue to pursue the organization. + +""Even as this is an important step forward in the fight against al-Shabab, the United States will continue to use the tools at our disposal –- financial, diplomatic, intelligence and military –- to address the threat that al-Shabaab and other terrorist groups pose to the United States and the American people,"" the White House said in a statement.","1" +"Pentagon: Airstrike kills terror leader in Somalia","WASHINGTON — The Pentagon on Friday confirmed that the leader of al-Shabaab, an al-Qaeda-linked organization in Africa, was killed in a U.S. airstrike in Somalia this week. + +The leader, Ahmed Abdi Godane, was targeted Monday in an airstrike that hit a vehicle and compound in a militant stronghold south of the capital, Mogadishu. + +Al-Shabaab has been linked to a number of attacks in Africa, including the bloody siege at the upscale Westgate Mall in Nairobi, Kenya, in September 2013 that killed 67 people. + +""Removing Godane from the battlefield is a major symbolic and operational loss to al-Shabaab,"" Pentagon press secretary Rear Admiral John Kirby said in a statement. + +At the time of the strike, the Pentagon said it could not confirm Godane's death. + +Hellfire missiles and laser-guided munitions were used to strike the targets. Both manned aircraft and unmanned drones participated in the attack. + +The Pentagon said no U.S. ground troops were involved in the operation. + +""The United States works in coordination with its friends, allies and partners to counter the regional and global threats posed by violent extremist organizations,"" Kirby said in the statement released Friday. + +The United States has backed the Somali government, which has pushed the terrorist group out of Mogadishu. Despite the government successes, the terror group has been able to operate in parts of the country that remain out of the reach of the government's influence. + +The White House said it would continue to pursue the organization. + +""Even as this is an important step forward in the fight against al-Shabaab, the United States will continue to use the tools at our disposal — financial, diplomatic, intelligence and military — to address the threat that al-Shabaab and other terrorist groups pose to the United States and the American people,"" the White House said in a statement.","1" +"Pentagon confirms al-Shabab leader killed in airstrike in Somalia","The Pentagon said Friday that it had confirmed the death of a key Somali militant leader allied with al-Qaeda who had been targeted in a U.S. airstrike earlier this week. + +Ahmed Abdi Godane, a co-founder of a network blamed for its brutal tactics in Somalia and for the attack on an upscale Kenyan shopping mall last year, was killed Monday in an attack carried out by U.S. drones and other aircraft, the Pentagon said. + +“Removing Godane from the battlefield is a major symbolic and operational loss to al-Shabab,” Rear Adm. John Kirby, the Pentagon press secretary, said in a statement. + +U.S. military officials had acknowledged that they were trying to kill Godane in Monday’s air assault on a Shabab compound in southern Somalia. But they had been cautious about asserting the mission was successful, mindful of reports of other al-Qaeda leaders who had been killed in drone attacks, only to resurface later. + +The State Department had offered a $7 million reward for information leading to Godane’s arrest. It identified him as a 37-year-old native of northern Somalia who, among other aliases, went by the names Mukhtar Abu Zubeyr and Ahmed Abdi Aw Mohamed. + +Monday’s drone strike was the most aggressive U.S. military operation in Somalia in nearly a year, and it came as the Obama administration was already grappling with security crises in Iraq, Syria and Ukraine. + +Counterterrorism officials and analysts have described Godane as a particularly ruthless jihadi leader who eliminated several rivals within al-Shabab, either by killing them or forcing them to go underground. + +It was unclear who might succeed him as leader of the network. Although al-Shabab often posts comments from the group on social media and gives interviews with journalists in Somalia, it has been mum about whether he survived the airstrike.","1" +"White House confirms al-Shabab leader killed in airstrike in Somalia","The Obama administration said Friday that it had confirmed the death of a key Somali militant leader allied with al-Qaeda who had been targeted in a U.S. airstrike earlier this week. + +Ahmed Abdi Godane, a co-founder of a network blamed for its brutal tactics in Somalia and for the attack on an upscale Kenyan shopping mall last year, was killed Monday in an attack carried out by U.S. drones and other aircraft, according to the White House and the Pentagon. + +Speaking to reporters at the NATO summit in Wales, President Obama cited Godane’s death as the result of the U.S. government’s “very systematic and methodical approach” in combating al-Shabab, al-Qaeda, Islamic State and other radical networks. + +“That deliberation allows us to do it right,” he added. “But, have no doubt, we will continue and I will continue to do what is necessary to protect the American people.” + +U.S. military officials had acknowledged that they were trying to kill Godane in Monday’s air assault on a Shabab compound in southern Somalia. But they had been cautious about asserting the mission was successful, mindful of reports of other al-Qaeda leaders who had been killed in drone attacks, only to resurface later. + +Al-Shabab, which means “the youth” in Arabic, is a jihadist movement that has formally affiliated itself with al-Qaeda. Born in Somalia, a chronically unstable country on the Horn of Africa, it has transformed itself from a domestic insurgency into a regional terrorist group that has carried out attacks in Kenya and Uganda. The network also has cooperated with al-Qaeda’s franchise in Yemen. + +“Removing Godane from the battlefield is a major symbolic and operational loss to al-Shabab,” Rear Adm. John Kirby, the Pentagon press secretary, said in a statement. + +The State Department had offered a $7 million reward for information leading to Godane’s arrest. It identified him as a 37-year-old native of northern Somalia who, among other aliases, went by the names Mukhtar Abu Zubeyr and Ahmed Abdi Aw Mohamed. + +Monday’s drone strike was the most aggressive U.S. military operation in Somalia in nearly a year, and it came as the Obama administration was already grappling with security crises in Iraq, Syria and Ukraine. + +Godane took public responsibility for the Sept. 21, 2013 attack on the Westgate Mall in Nairobi in which Shabab gunmen killed dozens of people and held Kenyan security forces at bay for days. + +Counterterrorism officials and analysts have described Godane as a particularly ruthless jihadi leader who eliminated several rivals within al-Shabab, either by killing them or forcing them to go underground. + +It was unclear who might succeed him as leader of the network. Although al-Shabab often posts comments from the group on social media and gives interviews with journalists in Somalia, it has been silent about whether he survived the airstrike. + +Although Godane had sworn allegiance to al-Qaeda and his group has been a menace in East Africa, U.S. counterterrorism officials have been divided over how much of a direct threat al-Shabab poses to the United States. + +The State Department officially declared al-Shabab a terrorist organization in 2008. In a statement Friday, the White House said that Godane had “continued to oversee plots targeting Westerners, including U.S. persons, in East Africa,” but did not give further evidence of specific attempts to kill Americans.","1" +"Google seals massive Sunnyvale, Redwood City deals","Google leased all 1.9 million square feet of Moffett Place, a Sunnyvale office complex under development by Jay Paul Co. + +Google Inc. has cemented a pair of massive real estate deals in Sunnyvale and Redwood City that boost the company's Silicon Valley footprint by 2.8 million square feet – about the size of the Empire State Building and enough room for more than 10,000 workers. + +Even by Google standards, the latest transactions are blockbusters: In one deal, Google has agreed to lease all of Jay Paul Co.'s Moffett Place, a 1.9 million square foot office campus currently under construction in Sunnyvale. It's a contender for the largest office lease ever signed in Silicon Valley and perhaps the state of California. + +In a separate but no less notable deal, Mountain View-based Google completed the purchase of six buildings from Blackstone Group and Starwood Capital totaling about 934,000 square feet at Redwood City's Pacific Shores office park. It's Google's first entry into that city and a potential game changer for that commercial real estate market. + +""Google is obviously a very strong company and they are in hyper growth mode,"" said Amber Schiada, director of research for real estate services firm JLL. + +The deals — both of which I previously reported were in the works — were confirmed by sources close to the transactions. Google declined to comment for this story. Blackstone didn't return inquiries. Jay Paul's longtime broker Phil Mahoney of Newmark Cornish & Carey, would only say that Moffett Place is off the market. + +Google's expansion on the Peninsula has been the biggest real estate story since the 2008 Great Recession as the world's biggest Web-search advertising company has bought and leased building after building, radiating out from its Mountain View headquarters. Its real estate growth dwarfs even that of Cisco Systems Inc.'s expansion during the 1990s. + +Terms of the latest deals were not disclosed, but sources estimated the Redwood City sale at around $625 per square foot, or $583.75 million. That would make it perhaps Google's single largest real estate acquisition by footprint and dollar amount ever in Silicon Valley. + +""I welcome them to our city and I look forward to working with them,"" said Redwood City Mayor Jeffrey Gee in an interview this afternoon. ""For a long time I would go around and say, 'Redwood City is one of the best kept secrets in the Bay Area. With Google and everything going on, we're not a secret anymore.'"" + +Aside from sheer size, the deals are notable for several reasons. First, they showcase Google's incredibly ambitious growth plans as the company enters new business sectors such as wearable computing, self-driving cars and robotics — all of which could be huge space users on their own. + +Google has not even moved into much of the space it has leased or bought over the last several years. Yet the company continues to bank more elbow room for future expansion, suggesting it is thinking far down the line in terms of its space needs. Google counted 55,030 employees globally as of Sept. 30, according to its most recent quarterly report, up 18 percent — or 8,600 Googlers — from a year ago. + +The transactions also alter the marketplace dynamics in two cities by taking available space off the table. Schiada noted that Moffett Place was the largest speculatively built project under construction in Silicon Valley. In Redwood City's Pacific Shores, which is more than 90 percent leased, I'm told Google will honor all current tenants' leases for now, but will evaluate moving into spaces as they become available in the years ahead. + +""A big question is what does this leave for tenants,"" Schiada said, speaking specifically about the Moffett Place deal. ""It also increases rates, because the supply becomes more limited."" + +Still, that could actually be a good thing for tenants down the line by pushing developers to build more product, she added. + +""This deal essentially eliminates a significant portion of new development, which could prompt more developers to move forward,"" she said. + +Jim Beeger, a veteran broker with Colliers International, said in the short term, the Sunnyvale deal could also push tenants back into the market. + +The transaction could ""cause tenants of all sizes to realize they should have more of a sense of urgency in their search for a new site,"" he said. ""Moffett Place will be difficult to replicate, and those who lingered no longer have this option."" + +Sethena Leiker, senior analyst for Cushman & Wakefield's Silicon Valley office, agreed. + +""There's not a lot of spec development coming,"" she said. ""If you want to take any new space, you're going to have to take something that's proposed."" + +One result, Beeger said, could be a ""trickle-down effect"" of growing tenants moving to other areas of Santa Clara County that have available sites. + +Score for Sunnyvale + +Google's lease at Moffett Place is a huge win for San Francisco-based Jay Paul Co., if one that's not entirely unexpected. Jay Paul already leased 949,000 square feet to Google in Sunnyvale at a nearby campus called Technology Corners, making Google a natural prospect for the new development. + +And while Google has not yet started moving into Technology Corners, the company has also been growing elsewhere in Sunnyvale this year, snapping up the old Juniper Networks headquarters (424,000 square feet) and former head office of Palm Computing Inc. (285,000 square feet). And it's rumored that a fund, CBRE Global Investors, that's buying up land all around Sunnyvale's Moffett Park business district is actually acting on behalf of Google. + +Yet landing Google wasn't guaranteed when Jay Paul started building Moffett Place earlier this year on spec. Other major tech tenants were also making offers on the property, according to sources. The rent Google is paying isn't known, but Jay Paul was asking $3.75 per square foot on a triple-net basis, or not including utilities, taxes and fees. + +Redwood City action + +In Redwood City, Google picks a up a major chunk one of Silicon Valley's marquee office campuses. The 10-building, 1.7-million-square-foot project was built by Jay Paul Co. in the early 2000s and gained notice for its sleek design and swanky amenities including pools, a rock-climbing wall, day spa and baseball diamonds. + +Starwood bought the campus in 2006 for about $833 million, and immediately sold two buildings to Shorenstein, the San Francisco-based landlord. Blackstone came into the picture after acquiring the junior debt on the property a couple of years ago. Informatica also acquired two buildings out of the 10 in 2012 for $525 per square foot. Google's acquisition this week is only for the six Blackstone/Starwood buildings. + +As I reported earlier this month, a new owner could build even more office space at Pacific Shores. New zoning approved about a year ago could allow total build-out of up to 3 million square feet. + +Google — which like many expanding tech companies is focused on reducing its car and shuttle trips as traffic worsens during the current boom — may have been attracted to the project partly for its water transit possibilities beyond freeways. + +Pacific Shores is a half mile from the Port of Redwood City, where a Google pilot project earlier this year tested running ferries from San Francisco and Alameda to the port. + +Mayor Gee said the city would be happy to work with Google on such a plan, should the search company decide to go in that direction. + +""One of the things that's always a challenge with new forms of transportation is, is there enough there there,"" he said. ""With Google, that potentially brings the there there."" + +Check back later for more on this story.","1" +"Google Said to Buy Redwood City Offices for $585 Million","Google Inc. (GOOG) bought six office buildings northwest of its Silicon Valley headquarters from Starwood Capital Group LLC and Blackstone Group LP (BX) in a $585 million deal, two people with knowledge of the matter said. + +The properties are part of the Pacific Shores Center office park in Redwood City, California, about 11 miles (18 kilometers) from Google’s main office in Mountain View, said the people, who asked not to be named because the transaction is private. The company said in its quarterly report filed yesterday that it bought land and buildings for $585 million, without details. + +The acquisition extends a real estate deal spree as Google, owner of the world’s largest search engine, expands hiring and makes acquisitions. This month, the company signed office-lease agreements for a total commitment of about $1 billion through 2028, according to the filing. + +“We expect to continue to hire aggressively for the remainder of 2014,” Google said in the filing. “Acquisitions will also remain an important component of our strategy.” + +The company had 55,030 full-time employees as of Sept. 30, up almost 19 percent from a year earlier, the filing shows. + +Meghan Casserly, a spokeswoman for Google, declined to comment beyond the filing. Tom Johnson, a spokesman for Barry Sternlicht’s Starwood Capital in Greenwich, Connecticut, and Peter Rose, a spokesman for New York-based Blackstone, declined to comment. The Silicon Valley Business Journal reported this month that Google was close to completing a deal at the site. + +Fitness Center + +The properties Google purchased comprise about 934,200 square feet (86,800 square meters) of Class A office space, as well as a 38,000-square-foot fitness center that includes a gym, pool and spa, according to the people with knowledge of the matter. That’s more than half of the 1.7 million square feet of office space at the complex. + +The office building addresses are 1200, 1300, 1600, 1700, 1800, and 1900 Seaport Blvd., the people said. + +Pacific Shores Center is a 106-acre (43-hectare) waterfront campus that was developed by San Francisco-based Jay Paul Co. in the early 2000s. It lies about halfway between San Francisco and San Jose. The campus, which includes sports fields and a park, is next to restored wetlands that are part of the San Francisco Bay Wildlife Refuge. + +Starwood, Blackstone + +Starwood Capital bought Pacific Shores Center in December 2006, near the height of the commercial-property market, from its developer and Walton Street Capital LLC, and immediately resold two of the buildings. Starwood Capital paid about $833 million in the deal, its first office acquisition in the San Francisco Bay area. + +Blackstone in 2011 bought an $80 million junior loan on the office complex at a discount in an effort to gain ownership if Starwood Capital defaulted, two people with knowledge of the purchase said at the time. Blackstone then gained an equity stake in the properties sold to Google through a loan restructuring. + +Blackstone, through its Equity Office unit, has major office holdings in Northern California and is the second-largest U.S. office landlord, after Brookfield Property Partners LP. + +To contact the reporters on this story: Hui-yong Yu in Seattle at hyu@bloomberg.net; Brian Womack in San Francisco at bwomack1@bloomberg.net + +To contact the editors responsible for this story: Kara Wetzel at kwetzel@bloomberg.net Andreea Papuc","1" +"Google Grows With $1.6 Billion in California Office Deals","Google has bought about half of Pacific Shores office park.","1" +"Google said to buy six silicon valley buildings for $585 million","Seattle/ San Francisco: Google Inc. bought six office buildings northwest of its Silicon Valley headquarters from Starwood Capital Group Llc and Blackstone Group Lp in a $585 million deal, two people with knowledge of the matter said. The properties are part of the Pacific Shores Centre office park in Redwood City, California, about 18 kilometres from Google’s main office in Mountain View, said the people, who asked not to be named because the transaction is private. The company said in its quarterly report filed on Thursday that it bought land and buildings for $585 million, without details. The acquisition extends a real estate deal spree as Google, owner of the world’s largest search engine, expands hiring and makes acquisitions. This month, the company signed office-lease agreements for a total commitment of about $1 billion through 2028, according to the filing. “We expect to continue to hire aggressively for the remainder of 2014,” Google said in the filing. “Acquisitions will also remain an important component of our strategy.” The company had 55,030 full-time employees as of 30 September, up almost 19% from a year earlier, the filing shows. Meghan Casserly, a spokeswoman for Google, declined to comment beyond the filing. Tom Johnson, a spokesman for Barry Sternlicht’s Starwood Capital in Greenwich, Connecticut, and Peter Rose, a spokesman for New York-based Blackstone, declined to comment. The Silicon Valley Business Journal reported this month that Google was close to completing a deal at the site. Fitness centre The properties Google purchased comprise about 9,34,200 square feet of Class A office space, as well as a 38,000-square-foot fitness centre that includes a gym, pool and spa, according to the people with knowledge of the matter. That’s more than half of the 1.7 million square feet of office space at the complex. The office building addresses are 1200, 1300, 1600, 1700, 1800, and 1900 Seaport Blvd., the people said. Pacific Shores Centre is a 106-acre waterfront campus that was developed by San Francisco-based Jay Paul Co. in the early 2000s. It lies about halfway between San Francisco and San Jose. The campus, which includes sports fields and a park, is next to restored wetlands that are part of the San Francisco Bay Wildlife Refuge. Starwood Capital bought Pacific Shores Centre in December 2006, near the height of the commercial-property market, from its developer and Walton Street Capital Llc, and immediately resold two of the buildings. Starwood Capital paid about $833 million in the deal, its first office acquisition in the San Francisco Bay area. Blackstone in 2011 bought an $80 million junior loan on the office complex at a discount in an effort to gain ownership if Starwood Capital defaulted, two people with knowledge of the purchase said at the time. Blackstone then gained an equity stake in the properties sold to Google through a loan restructuring. Blackstone, through its Equity Office unit, has major office holdings in Northern California and is the second-largest US office landlord, after Brookfield Property Partners Lp. Bloomberg","1" +"Unconfirmed reports of hand grenade found in a safe at Shortlands property","News Shopper has received unconfirmed reports that a hand grenade has been found in a safe at a property in Shortlands. + +Alex McFee, who works at Curran and Pinner estate agents on Beckenham Lane, has sent in this picture of the road which has been taped off by police. + +The 20-year-old said: “We have been told a hand grenade has been found in a safe directly above the old sweet shop. Everything here has just come to a stand still."" + +More to come.","1" +"Hand grenade found at Beckenham Lane property in Shortlands","An unexploded grenade was found at a property in Beckenham Lane in Shortlands earlier today (September 22). + +Officers were called to the scene at around 1pm. + +Police said nobody was injured but the area was cordoned off and specialist officers attended. + +Alex McFee, aged 20, who works at local estate agent Curran and Pinner said staff from The IT Crowd, a computer repair shop on Beckenham Lane, had found the grenade. + +The 20-year-old, of Ravenscroft Road in Penge, said: ""The police shouted to us to stay inside. Everything here came to a standstill. There was definitely a sense of confusion. + +""The bomb disposal squad went in and brought it out. It was dealt with quite quickly really."" + +Steve Hughes, who works at Kent Fireplace in Beckenham Lane, said he heard police had found a grenade in a safe above one of the shops. + +The 37-year-old, of Farnaby Road, said: ""The police shut the road off for about an hour and a half. + +""There was two police cars and four or five policeman and then two guys from bomb disposal showed up""","1" +"No, that high school kid didn't make $72 million trading stocks","You may have seen the amazing story today about the high school kid who made $72 million trading stocks. There were plenty of red flags in the original New York Magazine article. But now CNBC is reporting that the $72 million figure is totally bogus. + +Mohammed Islam, a 17-year-old high school kid in New York, was profiled as a Wall Street whiz kid who was raking in millions. The New York Magazine piece implies that his wealth ($72 million or not) largely came from trading. + +Mo got into trading oil and gold, and his bank account grew. Though he is shy about the $72 million number, he confirmed his net worth is in the ""high eight figures."" More than enough to rent an apartment in Manhattan—though his parents won't let him live in it until he turns 18—and acquire a BMW, which he can't drive because he doesn't yet have a license. +But the investment club that Islam belongs to sent a statement to Business Insider: + +It has been brought to the attention of the Leaders Investment Club that Mohammed Islam has been rumored to have made $72,000,000 through making trades in the stock market. After performing due diligence and talking with Mohammed Islam himself, we have determined that these claims are false and simply been blown up by the media in the interests of sensationalism. +The journalist who wrote the piece defends it, saying that she saw a bank statement that confirms he's worth eight figures: + + +So what's the real story? We can only speculate at this point, but if history is any guide for Wall Street prodigy stories, most of his wealth could come from an inheritance. Just last month Yahoo Finance had to issue a correction about the story of a 27-year-old ""self-made"" millionaire. It turned out that probably 80 percent of that man's wealth came from an inheritance. + +You can watch video of CNBC discussing the story of Mohammed Islam, the high school millionaire, below: + + +All this doesn't mean that Islam isn't still making decent coin from his trading, nor that he's not incredibly wealthy. He's just not worth $72 million and almost certainly didn't make the majority of his money trading stocks. + +We'll have to wait until the dust settles for the real story on this one, but that could take a while. Islam cancelled an appearance on CNBC after getting spooked by producers in his pre-interview.","1" +"EXCLUSIVE: New York Mag’s Boy Genius Investor Made It All Up","It’s been a tough month for factchecking. After the Rolling Stone campus rape story unraveled, readers of all publications can be forgiven for questioning the process by which Americans get our news. And now it turns out that another blockbuster story is —to quote its subject in an exclusive Observer interview—”not true.” + +Monday’s edition of New York magazine includes an irresistible story about a Stuyvesant High senior named Mohammed Islam who had made a fortune investing in the stock market. Reporter Jessica Pressler wrote regarding the precise number, “Though he is shy about the $72 million number, he confirmed his net worth is in the “’high eight figures.’” The New York Post followed up with a story of its own, with the fat figure playing a key role in the headline: “High school student scores $72M playing the stock market.” + +And now it turns out, the real number is … zero. + +In an exclusive interview with Mr. Islam and his friend Damir Tulemaganbetov, the baby faced boys who dress in suits with tie clips came clean. Swept up in a tide of media adulation, they made the whole thing up. + +Speaking at the offices of their newly hired crisis pr firm, 5WPR and handled by a phalanx of four including the lawyer Ed Mermelstein of RheemBell&Mermelsein, Mr. Islam told a story that will be familiar to just about any 12th grader—a fib turns into a lie turns into a rumor turns into a bunch of mainstream media stories and invitations to appear on CNBC. + +Here’s how it happened. + +Observer: What was your first contact with the New York magazine reporter? + +Mohammed Islam: “My friend’s father worked at New York magazine and he had the reporter contact me. Then she [Jessica Pressler] called me.” + +You seem to be quoted saying “eight figures.” That’s not true, is it? + +No, it is not true. + +The Post trumpeted the boys' investment success, as did New York magazine. (screencap) +The Post trumpeted the boys’ investment success, as did New York magazine. (screencap) + +Is there ANY figure? Have you invested and made returns at all? + +No. + +So it’s total fiction? + +Yes. + +Are you interested in investing? How did you get this reputation? + +I run an investment club at Stuy High which does only simulated trades.” + +If you had been playing with real money, would you have done really well? + +The simulated trades percentage was extremely high relative to the S&P. + +Where did Jessica Pressler come up with the $72 million figure? + +I honestly don’t know. The number’s a rumor. + +She said ‘have you made $72 million’? + +[I led her to believe] I had made even more than $72 million on the simulated trades. + +At this point the PR reps jumped in with Law & Order style objections. A conference outside the room ensued. Back into the room came Mr. Islam. + +All I can say is for the simulated trades, I was very successful. The returns were incredible and outperformed the S&P. + +Damir, tell me where you fit into this. + +Damir Tulemaganbetov: Well, I got excited by this whole trading thing and I said hey, let me get on board. I heard about this article coming out and Mohammed invited me and I met Jessica. + +But you guys are pals outside of this? + +We go to social gatherings and friends’ places. + +Are you into stockpicking as well? + +I haven’t been into it but I’m interested. + +Mohammed, you’re from Queens and you go to this elite public high school. Is this a hobby of your parents as well or would you be the first person in your family to pursue high finance? + +Mohammed Islam: In my immediate family, just me. + +So what did your parents think when they’re reading that you’ve got $72 million? + +Mohammed Islam: Honestly, my dad wanted to disown me. My mom basically said she’d never talk to me. Their morals are that if I lie about it and don’t own up to it then they can no longer trust me. … They knew it was false and they basically wanted to kill me and I haven’t spoken to them since. + +You haven’t? Where did you sleep last night? + +Mohammed Islam: At a friend’s house. But we didn’t sleep. + +Damir Tulemaganbetov: We stayed awake all night. We’ve been checking out news all over the world. + +Are your friends blowing up your phones? + +Damir Tulemaganbetov: He had 297 unread messages and 190 LinkedIn. All the friends shared it. + +Mohammed Islam: It was hyped up beyond belief. + +Damir Tulemaganbetov: We were at CNBC. That’s why we’re dressed up. But we were there and literally in the building stressing out. We had 20 minutes. Then we three times asked them could we have 20 seconds to talk? + +[The boys ended up cancelling the CNBC appearance.] + +Where do you go from here? + +Damir Tulemaganbetov: Socially, people will be mad about it. But we’re sorry. Especially ot our parents. Like my dad would read this and be like ‘Oh My God’ because he’s a very humble man and I portrayed him like a bad father. + +Mohammed Islam: At school, first things first. I am incredibly sorry for any misjudgment and any hurt I caused. The people I’m most sorry for is my parents. I did something where I can no longer gain their trust. I have one sister, two years younger, and we don’t really talk. + + + +So that’s that. There was no $72 million, no “eight figures,” not even one figure. The story is already coming unglued as the commenters on New York’s site hammer the reporter for even thinking this was possible. New York has now altered its headline to back away from the $72 million figure but the story itself remains. Even if this working-class kid had somehow started with $100,000 as a high school freshman on day one at Stuy High, he’d have needed to average a compounded annualized return of something like 796% over the three years since. C’mon, man. + +It’s not hard to see why the story was tough to resist for New York, which placed Mr. Islam’s alleged acumen at No. 12 in its 10th annual “Reasons to Love New York” issue. Ms. Pressler quoted him saying, “It’s not just about money. We want to create a brotherhood. Like, all of us who are connected, who are in something together, who have influence, like the Koch brothers …” Yep, nothing says success—or search engine optimization—quite like “Koch brothers.” + +No one asked for my opinion, but I’m going to provide it anyway, having sat with these kids for a good bit on a tough day. They got carried away. They’re not children. But they’re not quite adults, either, and at least Mr. Islam was literally quaking as we spoke. So yeah, they probably should have known better. But New York and the New York Post probably should have, as well. This story smelled fishy the instant it appeared and a quick dance with the calculator probably would have saved these young men—and a couple reporters—some embarrassment. + +The Stuyvesant High School classmates stayed up all night as the crisis grew. (5WPR) +The Stuyvesant High School classmates stayed up all night as the crisis grew. (5WPR)","1" +"Whiz kid stock picker: I didn't actually make $72M trading","The improbable story making the rounds today of the 17-year old whiz kid of Wall Street who is rumored to have made $72 million trading the markets, while still in high school, is being widely disputed. + +Mohammed Islam, the alleged teenaged prodigy, said he had no idea where that dollar figure came from and that it's not accurate. + +Instead the figure is believed to be a few million dollars, but Mr. Islam declined to be more specific. + +""The attention is not what we expected – we never wanted the hype. This was about friends trying to make something exciting together, "" Mr. Islam said in an exclusive CNBC interview. + +Mr. Islam and one of his colleagues were scheduled to appear on CNBC's ""Halftime Report"" following the publication of a New York Magazine profile. The ensuing publicity however, and pre-interview by CNBC, prompted them to reconsider. + +""We expected a regular article about what we hope to do"" in our career, he said. ""The way we were portrayed is not who we are.""","1" +"Mohammed Islam Denies Making $72 Million From Stock Market Trading","Mohammed Islam, the 17-year-old whose profile has circulated across the nation, says he did not make $72 million from trading stocks. + +Islam, a high school student at Stuyvesant in New York City, was profiled by the New Yorker, which claimed that he made $72 million from the market. + +But Islam told CNBC that the figure is not accurate, although he declined to be more specific other than saying it’s closer to a few million dollars. + +“The attention is not what we expected – we never wanted the hype. This was about friends trying to make something exciting together, ” Islam said. + +“We expected a regular article about what we hope to do” in our career, he said. “The way we were portrayed is not who we are.” + +The New Yorker claimed that it got the figure from rumors. + +“Our story portrays the $72 million figure as a rumor; the initial headline has been changed to more clearly reflect the fact that we did not know the exact figure he has made in trades,” it said in a statement. “However, Mohammed provided bank statements that showed he is worth eight figures, and he confirmed on the record that he’s worth eight figures.” + +Islam says he would like to become a hedge fund manager, and find a mentor who is a great trader. + +His inspiration is Paul Tudor Jones. + +Islam, who trades mainly in Crude Oil futures and Gold futures and small to mid-cap equities, told Business Insider he’s already learned a lot. + +“When I learned that I needed discipline, a strategy that had been back tested, and enough capital, I buckled down and made sure I didn’t make one more trade until I had done that,” he said. + +“I traded using my plan and didn’t go astray and followed the cardinal rule of minimizing losses and maximizing profits. This made me profitable and to this day I look upon that as a major goal I accomplished.”","1" +"Yemen says U.S. man freed, sister says he’s dead","An American hostage in Yemen held by al-Qaeda has been freed, according to statements from the country’s defense ministry on Saturday, however his sister has received information of his death. + +The defense ministry said on its website that an operation by Yemen's armed forces early on Saturday freed photojournalist Luke Somers and led to the killing of 10 members of the militant group holding him, according to Reuters news agency. + +It said the operation took place in the Wadi Abdan Al Daqqar region of Shabwa Province in the southern part of the country. + +But his sister Lucy Somers told The Associated Press that she learned of her 33-year-old brother’s death from FBI agents. There was no immediate comment from Washington, nor from security officials in Yemen's capital, Sanaa. + +Meanwhile another account suggests Somers was wounded during the operation. + +""American soldiers carried away the hostage. He was wounded and we don't know if he is dead or alive,"" the Yemeni official told Agence France-Presse on condition of anonymity. + +Somers was kidnapped in September 2013 in the Yemeni capital of Sanaa, where he had been working as a freelance photographer for the Yemen Times. + +Al-Qaeda posted a video Thursday that showed Somers, 33, and a local al-Qaeda commander threatening that Somers would meet his fate in three days if the United States doesn’t meet the group’s demands, which weren’t specified. + +In a video posted Saturday near London, Lucy Somers describes her older brother as a romantic who “always believes the best in people.” She ends with the plea: “Please let him live.” + +In a statement, Somers’ father, Michael, calls his son “a good friend of Yemen and the Yemeni people” and asks for his safe release. + +“When foreign nationals were advised to leave Yemen, Luke refused to go, saying he felt safe and at home there,” Lucy Somers said in her video. “He felt the Yemeni people would look after him.” + +“Photojournalism has been his way of highlighting the struggles of the Yemeni people,” she said. + +Michael Somers said his son “was confident that no one would harm him for his simplicity and honest friendship to all Yemenis around him.” + +Luke Somers “told all his friends and loved ones stories of Yemenis’ generosity, humility and devoted friendship,” his father said, adding, “Luke’s life in Yemen these past three and a half years should not have ended with a kidnapping but with a great reward. The fact that he chose to live in Yemen and not the United States shows where his sympathies lay. Please bring Luke back to us safe and sound.” + +Somers’ brother, Jordan, and mother, Paula, offered a similar message in an earlier video. + +“My life is in danger,” Luke Somers said in the al-Qaiea footage, which appeared to mimic hostage videos released by al-Qaida’s rival, the Islamic State of Iraq and Syria (ISIS) group. He asked for help. + +In a statement Thursday, Pentagon press secretary Rear Adm. John Kirby acknowledged for the first time that a raid last month had sought to rescue Somers but that he turned out not to be at the site. + +White House spokeswoman Bernadette Meehan also said President Barack Obama had authorized a rescue operation to free Somers and other hostages but “regrettably, Luke was not present.” + +[With agencies]","1" +"US hostage Luke Somers dies after rescue bid","A US journalist held by al-Qaeda in Yemen was killed by militants during an operation to rescue him, US and Yemeni officials say. + +Luke Somers was shot by his captors during a raid by US forces, a US official told the New York Times. + +His sister, Lucy Somers, told the Associated Press that she had been notified by the FBI of his death. + +US Defence Secretary Chuck Hagel confirmed the killing and said a second, non-US hostage, also died. + +Yemen's defence ministry confirmed a ""major operation"" had taken place in Yemen's southern Shabwa province on Saturday. + +Mr Somers, who was kidnapped in Yemen in 2013, had appeared in a video appealing for help. + +""We ask that all of Luke's family members be allowed to mourn in peace,"" Lucy Somers told AP, speaking from London. + +A drone strike believed to have been carried out by the US is reported to have killed nine suspected al-Qaeda militants in the region. + +Mr Somers, 33, worked as a journalist and photographer for local news organisations. His material appeared on international news outlets, including the BBC News website. + +He was kidnapped outside a supermarket in the Yemeni capital Sana'a in September 2013 and is believed to have been sold on to al-Qaeda in the Arab Peninsula (AQAP). + +The video of him released this week showed a member of AQAP threatening to kill Mr Somers unless unspecified demands were met. + +The Pentagon confirmed that an an attempt to rescue Mr Somers last month had failed. + +His family appealed in a video to al-Qaeda militants in Yemen to ""show mercy"" and release him. + +""Luke is only a photojournalist and is not responsible for any actions the US government has taken,"" his brother, Jordan, said in a video. + +AQAP is regarded by the US as one of the deadliest offshoots of al-Qaeda. + +The group is based in eastern Yemen and has built up support amid the unrest which has beset the impoverished country since the overthrow of President Ali Abdullah Saleh in 2011.","1" +"US hostage Luke Somers and SA Pierre Korkie killed during Yemen rescue bid","US journalist Luke Somers and another man held by al-Qaeda in Yemen have been killed by militants during a rescue attempt by US special forces. + +US Defence Secretary Chuck Hagel said the hostages were ""murdered by... terrorists during the mission"". + +He said there were ""compelling reasons"" to believe that Mr Somers's life was in danger. + +The second hostage has been named by a charity as South African teacher Pierre Korkie. + +AQAP is regarded by the US as one of the deadliest offshoots of al-Qaeda. + +The group is based in eastern Yemen and has built up support amid the unrest which has beset the impoverished country since the overthrow of President Ali Abdullah Saleh in 2011. + +Plea to mourn + +Mr Hagel said a number of militants were also killed in the operation in Shabwa province. + +""US Special Operations Forces conducted a mission in Yemen to rescue a US citizen, Luke Somers, and any other foreign nationals held hostage with him by al-Qaeda in the Arabian Peninsula (AQAP) terrorists,"" he said in a statement released during a visit to Kabul. + +""Both Mr Somers and a second non-US citizen hostage were murdered by the AQAP terrorists during the course of the operation."" + +A US official told the New York Times that Mr Somers, 33, was apparently shot by his captors as the raid unfolded and was badly wounded when the US forces reached him. + +By the time he was flown to a US naval ship in the region, he had died from his injuries, the official was quoted as saying. + +Mr Somer's sister, Lucy Somers, told the Associated Press earlier that she had been notified by the FBI of his death. + +""We ask that all of Luke's family members be allowed to mourn in peace,"" Lucy Somers told AP, speaking from London. + +""We received with sadness the news that Pierre was killed in an attempt by American Special Forces, in the early hours of this morning, to free hostages in Yemen,"" the charity Gift of the Givers said in a statement. + +Mr Somers, who was kidnapped in Yemen in 2013, appeared in a video this week appealing for help. + +The footage showed a member of AQAP threatening to kill him unless unspecified demands were met. + +Mr Somers worked as a journalist and photographer for local news organisations. His material appeared on international news outlets, including the BBC News website. + +He was kidnapped outside a supermarket in the Yemeni capital Sana'a in September 2013 and is believed to have been sold on to al-Qaeda in the Arab Peninsula (AQAP). + +Another attempt to rescue Mr Somers last month had failed.","1" +"US hostage killed in rescue bid","UK-born US journalist Luke Somers and South African teacher Pierre Korkie have been killed by al-Qaeda militants in Yemen during a failed rescue bid. + +Saturday's operation was carried out by joint US and Yemeni special forces in the southern, Shabwa region. + +US President Barack Obama condemned Mr Somers's death as a ""barbaric murder"". + +They were being held by militants from al-Qaeda in the Arabian Peninsula (AQAP), regarded by the US as one of the deadliest offshoots of al-Qaeda. + +The group is based in eastern Yemen and has built up support amid the unrest which has beset the impoverished country since the overthrow of President Ali Abdullah Saleh in 2011. + +Analysis: Frank Gardner, BBC Security correspondent + +Luke Somers is believed to have been sold on by his abductors to AQAP, described as the most dangerous of all al-Qaeda's regional affiliates. + +The group has earned itself millions of dollars by ransoming hostages but the US and British governments refuse to pay, leaving them little room for negotiation. + +Experts believe the group may now be looking to compete with Islamic State, in Syria and Iraq, which has gained worldwide notoriety for its extreme violence and cruelty coupled with highly produced videos uploaded on to the internet. + +Imminent danger + +President Obama said he authorised the raid to rescue Mr Somers and other hostages held in the same location. + +He said information had ""indicated that Luke's life was in imminent danger."" + +A number of militants were also killed in the operation. + +""Terrorists who seek to harm our citizens will feel the long arm of American justice,"" Mr Obama said. + +A US official told the New York Times that Mr Somers, 33, was apparently shot by his captors as the raid unfolded and was badly wounded when the US forces reached him. + +By the time he was flown to a US naval ship in the region, he had died from his injuries, the official was quoted as saying. + +Mr Somers' sister, Lucy Somers, told the Associated Press earlier that she had been notified by the FBI of his death. + +""We ask that all of Luke's family members be allowed to mourn in peace,"" Lucy Somers told AP, speaking from London. + +'Devastation' + +Meanwhile there are reports that Mr Korkie was expected to be released on Sunday. + +He was abducted with his wife Yolande in May last year in Yemen's second city, Taiz. + +She was freed on 10 January without ransom and returned to South Africa. + +""We received with sadness the news that Pierre was killed in an attempt by American Special Forces, in the early hours of this morning, to free hostages in Yemen,"" the charity Gift of the Givers said in a statement. + +""The psychological and emotional devastation to Yolande and her family will be compounded by the knowledge that Pierre was to be released by al-Qaeda tomorrow."" + +'Difficult time' + +Mr Somers, who was kidnapped in Yemen in 2013, appeared in a video this week appealing for help. + +Luke Somers emails to the BBC + +23 August 2013 + +I'm still in Yemen, though I plan to depart fairly soon, following the end of the country's National Dialogue Conference [UN-backed reconciliation talks] + +24 August 2013 + +Yemen isn't the most difficult place to live in. Always something to make you smile, you just sometimes have to step outside and find it. I actually feel pretty fortunate, as I'm the only foreigner I know of working directly and regularly in connection with the National Dialogue Conference. But soon enough, I need to depart and spend some time with my mom! + +4 September 2013 + +I'm sure I will return to the Middle East - and with regards to Yemen, it's pretty much a must. It's an emptying thought, imaging rooting yourself so firmly in a place, only to never return. So return I should, return I must. + +Profile: Luke Somers + +The footage showed a member of AQAP threatening to kill him unless unspecified demands were met. + +Mr Somers worked as a journalist and photographer for local news organisations. His material appeared on international news outlets, including the BBC News website. + +He was kidnapped outside a supermarket in the Yemeni capital Sana'a in September 2013 and is believed to have been sold on to AQAP. + +""We are aware of reports of the death of Luke Somers and our thoughts are with his family at this difficult time,"" a BBC spokesperson said on Saturday. + +Another attempt to rescue Mr Somers last month had failed.","1" +"BREAKING NEWS: British-born U.S. photojournalist held hostage by al-Qaeda killed in failed rescue attempt in Yemen","A British-born photojournalist and a South African aid worker held hostage in Yemen by al Qaida were 'murdered' in a failed rescue attempt, the US defence secretary has confirmed. + +Luke Somers had been held hostage since September 2013 in Yemen's capital Sana'a having moved to the country two years earlier. + +The 33-year-old was reportedly shot by his captors as US commandos carried out a dramatic rescue bid in the southern Shabwa province late on Friday night. + +Reports have now emerged that South African hostage Pierre Korkie was also killed during the operation - a day before he was due to be released. + +Scroll down for video + +Lucy Somers said she learned of her 33-year-old brother Luke Somers' death from FBI agents + +Mr Somers was badly wounded when commandos found him and he died from his injuries by the time he had been flown to a naval ship, a U.S. official told the New York Times. + +U.S. President Barack Obama this morning condemned killing as 'barbaric'. + +His sister Lucy Somers told Associated Press that she learned of her brother's death from FBI agents at 5am this morning. + +'We ask that all of Luke's family members be allowed to mourn in peace,' she said from London. + +U.S. Defense Secretary Chuck Hagel this morning confirmed Mr Somers and a second hostage being held by terrorists in Yemen were 'murdered' during a rescue attempt ordered by President Barack Obama. + +Hagel said there were 'compelling reasons to believe Somers' life was in imminent danger.' + +British-born U.S. photojournalist Luke Somers (pictured), who was being held by al-Qaida militants in Yemen, has been killed in a failed rescue attempt, his sister has revealed today + +Luke Somers was kidnapped in September 2013 from Yemen's capital Sana'a (shown in the map above) + +Mr Somers moved from London to Sana'a, Yemen in 2011 to become a teacher, but soon started taking pictures of public demonstrations and established himself as a photojournalist working for the Yemen Times + +He said Mr Somers and a second non-U.S. citizen were 'murdered by AQAP terrorists during the mission.' Hagel said that several terrorists were also killed in the mission carried out by U.S. special forces. + +The humanitarian group Gift of Givers has said today that teacher Pierre Korkie was shot dead in crossfire during the bid to rescue Mr Somers - just a day before he was set to be freed. + +Mr Korkie and his wife Yolande were reportedly captured by militants in May 2013 in Ta'iz, Yemen. But his wife was released after Gift of the Givers helped negotiate her freedom. + +Earlier this week al Qaida in the Arabian Peninsula (AQAP) issued a video with a message aimed at the US government threatening to kill Mr Somers if its demands were not met. + +Last week the U.S. said it had attempted a rescue operation to free a number of hostages, including Mr Somers, but that he had not been at the site of the raid. + +South African Pierre Korkie was killed in the attempted rescue mission by the United States - just a day before he was due to be released + +South African Pierre Korkie was killed in the attempted rescue mission by the United States - just a day before he was due to be released, an aid group says. + +Mr Korkie was killed in the failed effort to release hostages, Imtiaz Sooliman, founder of the Gift of the Givers group told the South African Press Agency. + +Korkie was to be freed by al-Qaida on Sunday, Gift of the Givers said on Twitter. + +'Leaders met in Aden this morning, preparing final security and logistical arrangements 2 bring Pierre 2 safety & freedom,' said tweeted the aid group. + +Mr Korkie and his wife Yolande were taken hostage in Taiz, Yemen, in May 2013, the charity said. + +A team had met in Aden this morning, preparing final security and logistical arrangements 2 bring the hostage to freedom, it claimed. + +'It is even more tragic that the words we used in a conversation with Yolande at 5.59 this morning was ""the wait is almost over"",' the charity tweeted to its 7,500 followers. + +It added: 'All logistical arrangements were in place 2 safely fly Pierre out of Yemen under diplomatic cover.' + +At the time of the kidnapping, Mr Korkie was a teacher in Yemen, while his wife was working in hospitals, News24 reports. + +The family of Mr Somers had earlier pleaded for him to be released. + +In an online video Miss Somers described her older brother as a romantic who 'always believes the best in people.' She added: 'Please let him live.' + +His father Michael said Mr Somers was 'a good friend of Yemen and the Yemeni people'. + +It came after the release of the AQAP video which begins with a reading in Arabic from Nasser bin Ali al Ansi, an AQAP official, before Mr Somers appears and gives a statement in English. + +He said: 'My name is Luke Somers. I'm 33 years old. I was born in England, but I carry American citizenship and have lived in America for most of my life. + +'It's now been well over a year since I've been kidnapped in Sana'a. Basically, I'm looking for any help that can get me out of this situation. I'm certain that my life is in danger. + +'So as I sit here now, I ask if anything can be done, please let it be done. Thank you very much.' + +Al Ansi gave the US government three days to meet the demands or 'otherwise, the American hostage held by us will meet his inevitable fate'. + +Militants released a video on Thursday that showed Mr Somers, threatening to kill him in three days if the United States did not meet the group's demands + +Nasser bin Ali al Ansi, senior official in Al Qaeda in the Arabian Peninsula, pictured, spoke for two minutes and thirty seconds during the video where he threatened to kill Mr Somers within three days + +The three-minute video also features Ansi speaking about American activity in Afghanistan, Somalia and Iraq as well as recent air strikes in Syria. + +It follows similar videos by another extremist militant group, Islamic State (IS), which has already killed two British hostages and three American hostages in videos released on social media. + +IS has posted a series of videos online showing the separate murders of US journalists James Foley and Steven Sotloff, US aid worker Peter Kassig and two British aid workers, David Haines and Alan Henning. + +Footage claiming to show Mr Henning's murder appeared on the internet just days after the UK joined US-led air strikes against the terrorists in Iraq. + +The news of the failed rescue comes after a suspected U.S. drone strike in Yemen killed nine alleged al-Qaida militants early Saturday, a security official said. + +The drone struck at dawn in Yemen's southern Shabwa province, hitting a suspected militant hideout, the official said. + +American commandos tried to rescue Mr Somers in a raid on an AQAP camp late last month, but he had been moved by the time they arrived + +Begging for mercy: Luke's brother, Jordan (left), and his mother, Paula Somers (right), released a video on Thursday asking his al-Qaeda captors to release him + +The official did not elaborate and spoke on condition of anonymity as he wasn't authorised to brief journalists. + +At least six suspected militants were killed in an airstrike in the same province last month. + +Later Saturday, tribal leaders said they saw helicopters flying over an area called Wadi Abdan in Shabwa province. + +American authorities rarely discuss their drone strike campaign in Yemen. + +The strikes are incredibly unpopular in Yemen due to civilian casualties, legitimising for many the attacks on American interests. + +In a statement on Thursday, Pentagon press secretary Rear Admiral John Kirby acknowledged for the first time that a mysterious U.S. raid last month had sought to rescue Mr Somers but that he turned out not to be at the site. + +Kirby did not elaborate on the joint U.S-Yemeni operation to free Mr Somers, saying details remained classified. + +However, officials have said the raid targeted a remote al-Qaida safe haven in a desert region near the Saudi border. Eight captives - including Yemenis, a Saudi and an Ethiopian - were freed. + +Mr Somers, a Briton and four others had been moved days earlier. + +Mr Somers was kidnapped in September 2013 as he left a supermarket in the Yemeni capital, Sana'a, said Fakhri al-Arashi, chief editor of the National Yemen, where Mr Somers worked as a copy editor and a freelance photographer during the 2011 uprising in Yemen. + +The U.S. considers Yemen's al-Qaida branch to be the world's most dangerous arm of the group as it has been linked to several failed attacks on the U.S. homeland.","1" +"British-born U.S. photojournalist is killed by his al-Qaeda captors during failed rescue attempt by American commandos in Yemen","A British-born U.S. photojournalist and a South African aid worker held hostage in Yemen by al Qaida were 'murdered' in a failed rescue attempt, the US defence secretary has confirmed. + +Luke Somers had been held hostage since September 2013 in Yemen's capital Sana'a having moved to the country two years earlier. + +The 33-year-old was reportedly shot by his captors as US commandos carried out a dramatic rescue bid in the southern Shabwa province late on Friday night. + +Reports have now emerged that South African hostage Pierre Korkie was also killed during the operation - a day before he was due to be released. + +Scroll down for video + +Lucy Somers said she learned of her 33-year-old brother Luke Somers' death from FBI agents + +Mr Somers was badly wounded when commandos found him and he died from his injuries by the time he had been flown to a naval ship, a U.S. official told the New York Times. + +Mr Somers' sister Lucy Somers told Associated Press that she learned of her brother's death from FBI agents at 5am this morning. 'We ask that all of Luke's family members be allowed to mourn in peace,' she said from London. + +US president Barack Obama described Mr Somers' murder as 'barbaric' in a statement this morning. + +'On behalf of the American people, I offer my deepest condolences to Luke's family and to his loved ones,' he said in a statement. + +'As this and previous hostage rescue operations demonstrate, the United States will spare no effort to use all of its military, intelligence and diplomatic capabilities to bring Americans home safely, wherever they are located. + +'And terrorists who seek to harm our citizens will feel the long arm of American justice,' he said. + +President Obama said he authorised the raid on Friday to rescue Somers and other hostages held in the same location. He said the United States had used every tool at its disposal to secure Somers' release since his capture 15 months ago. + +He also thanked the Yemen government for its support. + +British-born U.S. photojournalist Luke Somers (pictured), who was being held by al-Qaida militants in Yemen, has been killed in a failed rescue attempt, his sister has revealed today + +Luke Somers was kidnapped in September 2013 from Yemen's capital Sana'a (shown in the map above) + +Mr Somers moved from London to Sana'a, Yemen in 2011 to become a teacher, but soon started taking pictures of public demonstrations and established himself as a photojournalist working for the Yemen Times + +'Luke was a photojournalist who sought through his images to convey the lives of Yemenis to the outside world,' President Obama said. + +'The callous disregard for Luke's life is more proof of the depths of AQAP's depravity, and further reason why the world must never cease in seeking to defeat their evil ideology,"" he said. + +U.S. Defense Secretary Chuck Hagel this morning confirmed Mr Somers and a second hostage being held by terrorists in Yemen were 'murdered' during a rescue attempt ordered by the President. + +Hagel said that several terrorists were also killed in the mission carried out by U.S. special forces. + +The humanitarian group Gift of Givers said today that teacher Pierre Korkie was shot dead during the bid to rescue Mr Somers - just a day before he was set to be freed. + +Mr Korkie and his wife Yolande were reportedly captured by militants in May 2013 in Ta'iz, Yemen. But his wife was released after Gift of the Givers helped negotiate her freedom. + +South African Pierre Korkie was killed in the attempted rescue mission by the United States - just a day before he was due to be released, an aid group says. + +Mr Korkie was killed in the failed effort to release hostages, Imtiaz Sooliman, founder of the Gift of the Givers group told the South African Press Agency. + +Korkie was to be freed by al-Qaida on Sunday, Gift of the Givers said on Twitter. + +South African Pierre Korkie was killed in the attempted rescue mission by the United States - just a day before he was due to be released. His wife Yolande is pictured right + +'Leaders met in Aden this morning, preparing final security and logistical arrangements 2 bring Pierre 2 safety & freedom,' said tweeted the aid group. + +Mr Korkie and his wife Yolande were taken hostage in Taiz, Yemen, in May 2013, the charity said. + +A team had met in Aden this morning, preparing final security and logistical arrangements 2 bring the hostage to freedom, it claimed. + +'It is even more tragic that the words we used in a conversation with Yolande at 5.59 this morning was ""the wait is almost over"",' the charity tweeted to its 7,500 followers. + +It added:'Three days ago we told her ""Pierre will be home for Christmas"". + +'We certainly did not mean it in the manner it has unfolded. + +'All logistical arrangements were in place 2 safely fly Pierre out of Yemen under diplomatic cover.' + +At the time of the kidnapping, Mr Korkie was a teacher in Yemen, while his wife was working in hospitals, News24 reports. + +Yemen's national security chief, Major General Ali al-Ahmadi, said the militants planned to kill Luke Somers on Saturday. + +'Al-Qaida promised to conduct the execution (of Somers) today so there was an attempt to save them but unfortunately they shot the hostage before or during the attack, al-Ahmadi said at a conference in Manama, Bahrain. + +Earlier this week al Qaida in the Arabian Peninsula (AQAP) issued a video with a message aimed at the US government threatening to kill Mr Somers if its demands were not met. + +Last week the U.S. said it had attempted a rescue operation to free a number of hostages, including Mr Somers, but that he had not been at the site of the raid. + +The family of Mr Somers had earlier pleaded for him to be released. + +In an online video Miss Somers described her older brother as a romantic who 'always believes the best in people.' She added: 'Please let him live.' + +His father Michael said Mr Somers was 'a good friend of Yemen and the Yemeni people'. + +It came after the release of the AQAP video which begins with a reading in Arabic from Nasser bin Ali al Ansi, an AQAP official, before Mr Somers appears and gives a statement in English. + +Militants released a video on Thursday that showed Mr Somers, threatening to kill him in three days if the United States did not meet the group's demands + +Nasser bin Ali al Ansi, senior official in Al Qaeda in the Arabian Peninsula, pictured, spoke for two minutes and thirty seconds during the video where he threatened to kill Mr Somers within three days + +He said: 'My name is Luke Somers. I'm 33 years old. I was born in England, but I carry American citizenship and have lived in America for most of my life. + +'It's now been well over a year since I've been kidnapped in Sana'a. Basically, I'm looking for any help that can get me out of this situation. I'm certain that my life is in danger. + +'So as I sit here now, I ask if anything can be done, please let it be done. Thank you very much.' + +Al Ansi gave the US government three days to meet the demands or 'otherwise, the American hostage held by us will meet his inevitable fate'. + +The three-minute video also features Ansi speaking about American activity in Afghanistan, Somalia and Iraq as well as recent air strikes in Syria. + +It follows similar videos by another extremist militant group, Islamic State (IS), which has already killed two British hostages and three American hostages in videos released on social media. + +IS has posted a series of videos online showing the separate murders of US journalists James Foley and Steven Sotloff, US aid worker Peter Kassig and two British aid workers, David Haines and Alan Henning. + +American commandos tried to rescue Mr Somers in a raid on an AQAP camp late last month, but he had been moved by the time they arrived + +Begging for mercy: Luke's brother, Jordan (left), and his mother, Paula Somers (right), released a video on Thursday asking his al-Qaeda captors to release him + +Footage claiming to show Mr Henning's murder appeared on the internet just days after the UK joined US-led air strikes against the terrorists in Iraq. + +The news of the failed rescue comes after a suspected U.S. drone strike in Yemen killed nine alleged al-Qaida militants early Saturday, a security official said. + +The drone struck at dawn in Yemen's southern Shabwa province, hitting a suspected militant hideout, the official said. + +The official did not elaborate and spoke on condition of anonymity as he wasn't authorised to brief journalists. + +At least six suspected militants were killed in an airstrike in the same province last month. + +Later Saturday, tribal leaders said they saw helicopters flying over an area called Wadi Abdan in Shabwa province. + +American authorities rarely discuss their drone strike campaign in Yemen. + +The strikes are incredibly unpopular in Yemen due to civilian casualties, legitimising for many the attacks on American interests. + +In a statement on Thursday, Pentagon press secretary Rear Admiral John Kirby acknowledged for the first time that a mysterious U.S. raid last month had sought to rescue Mr Somers but that he turned out not to be at the site. + +Kirby did not elaborate on the joint U.S-Yemeni operation to free Mr Somers, saying details remained classified. + +However, officials have said the raid targeted a remote al-Qaida safe haven in a desert region near the Saudi border. Eight captives - including Yemenis, a Saudi and an Ethiopian - were freed. + +Mr Somers, a Briton and four others had been moved days earlier. + +Mr Somers was kidnapped in September 2013 as he left a supermarket in the Yemeni capital, Sana'a, said Fakhri al-Arashi, chief editor of the National Yemen, where Mr Somers worked as a copy editor and a freelance photographer during the 2011 uprising in Yemen. + +The U.S. considers Yemen's al-Qaida branch to be the world's most dangerous arm of the group as it has been linked to several failed attacks on the U.S. homeland.","1" +"REVEALED Navy Seals got within 100 yards of Yemen compound where U.S. photojournalist was being held - before al-Qaeda captors realised and shot him dead","A British-born U.S. photojournalist and a South African aid worker held hostage in Yemen by al Qaeda militants have been 'murdered' in a failed rescue attempt. + +American citizen Luke Somers had been held hostage since September 2013 in Yemen's capital Sana'a having moved to the country two years earlier. + +The 33-year-old was reportedly shot by his captors as Navy SEAL Team six, made up of around 40 men, carried out a dramatic rescue bid in the southern Shabwa province late on Friday night - the second attempted extraction by special forces in as many months. + +Another hostage, South African aid worker Pierre Korkie, was also killed during the operation - a day before he was due to be released. + +According to CNN the commandos hiked for six miles to reach the village where he was being held. They were only 100 yards away from the compound when they were spotted - prompting the militants to shoot the pair. + +Two medics involved in the operation tried to revive both of the hostages, but one died at the scene while the other succumbed to his injuries on the operating table inside the USS Makin Island. + +Outgoing U.S. Defense Secretary Chuck Hagel confirmed Mr Somers death this morning as he landed in Afghanistan. + +Scroll down for video + +Lucy Somers said she learned of her 33-year-old brother Luke Somers' death from FBI agents + +In April 2013 he took photos of a protest by Yemenis, demanding the release of Guantanamo Bay trainees + +During a press conference he announced that 1,000 more US troops than expected will be stationed in the country next year following a spike in Taliban attacks. + +Mr Somers was badly wounded when commandos found him and he died from his injuries by the time he had been flown to a naval ship. + +Mr Somers' sister Lucy Somers told Associated Press that she learned of her brother's death from FBI agents at 5am this morning. 'We ask that all of Luke's family members be allowed to mourn in peace,' she said from London. + +An Osprey aircraft took a team of U.S. Navy SEALS to the location, which was close to the site where a previous rescue mission had taken place, officials told CNN. + +A gun fight is understood to have unfolded before the badly injured hostages were taken away on the aircraft, the report says. + +Four Yemeni and CTU agents were wounded during the operation. + +According to the New York Times the forces raided four houses in the village where the attack took place, killed and least two militants but also gunned down eight civilians. + +Mr Somers was kidnapped in September 2013 as he left a supermarket in the Yemeni capital, Sana'a, said Fakhri al-Arashi, chief editor of the National Yemen. + +He had moved to the country in 2010 to teach English as the Arab Spring started to develop but soon became one of the country's only foreign photographers. + +The hostage worked at the paper as a copy editor and a freelance photographer during the 2011 uprising in Yemen. + +There are reports Mr Somers was sold to al-Qaeda in the Arabian Peninsula (AQAP) - one of the most dangerous regional arms of the terrorist group. + +The organisation make millions ransoming hostages - but British and American governments refuse to pay. + +On November 25, U.S Special Forces sent a unit to a cave near the Yemen border with Saudi Arabia in a hope of retrieving Mr Somers. Seven hostages were saved and eight militants were killed but the journalist was not inside. + +The U.S. considers Yemen's al-Qaeda branch to be the world's most dangerous arm of the group as it has been linked to several failed attacks on the U.S. homeland. + +Barack Obama described Mr Somers' murder as 'barbaric' in a statement this morning. + +'On behalf of the American people, I offer my deepest condolences to Luke's family and to his loved ones,' he said in a statement. + +British-born U.S. photojournalist Luke Somers (pictured), who was being held by al-Qaeda militants in Yemen, has been killed in a failed rescue attempt, his sister has revealed today + +Luke Somers was kidnapped in September 2013 from Yemen's capital Sana'a (shown in the map above) + +Mr Somers moved from London to Sana'a, Yemen in 2010 to become a teacher, but soon started taking pictures of public demonstrations and established himself as a photojournalist working for the Yemen Times + +The photojournalist bends down to take a picture during the National Dialogue Conference in Sanaa in July 2013, weeks before he was captured + +'As this and previous hostage rescue operations demonstrate, the United States will spare no effort to use all of its military, intelligence and diplomatic capabilities to bring Americans home safely, wherever they are located. + +'And terrorists who seek to harm our citizens will feel the long arm of American justice,' he said. + +President Obama said he authorised the raid on Friday to rescue Somers and other hostages held in the same location. He said the United States had used every tool at its disposal to secure Somers' release since his capture 15 months ago. + +He also thanked the Yemen government for its support. It is understood that the U.S. personnel who carried out the raid are safe. + +'Luke was a photojournalist who sought through his images to convey the lives of Yemenis to the outside world,' President Obama said. + +'The callous disregard for Luke's life is more proof of the depths of AQAP's depravity, and further reason why the world must never cease in seeking to defeat their evil ideology,' he said. + +Hagel this morning confirmed Mr Somers and a second hostage being held by terrorists in Yemen were 'murdered' during a rescue attempt ordered by the President. + +Hagel said that several terrorists were also killed in the mission carried out by U.S. special forces. + +The outgoing Pentagon head said the raid was 'well-executed' and based on better intelligence forces had received in the last 24 hours. + +He made the announcement just hours before holding a press conference with Afghan President Ashraf Ghani - during which he confirmed 10,800 troops will still be in Afghanistan in 2015. + +The original plan was to cut the number down to 9,800. + +'It's predictable that they would do everything they could and continue to do to try to disrupt and discourage the new government of President Ghani,' he said. + +The news of the hostage's death came as U.S. Secretary of Defense Chuck Hagel made an unannounced visit to Kabul to meet Afghan President Ghani and announce that more troops than expected will be stationed in the country in 2015 + +The outgoing Pentagon head said a recent spike in attacks by the Taliban proved that they were trying to disrupt the transition into the new government + +The Defense Department said the rise in violence did not prompt the decision to keep troops in the country. + +An official statement said it was due to the late signing of the Bilateral Security Agreement, which allows a specified amount of U.S. troops to remain after the combat mission ends this year. + +Hamid Karzai, Ghani's predecessor, refused to sign the deal. + +According to The Pentagon, 99 per cent of Afghan forces are now taking the lead in missions and are performing 'well'. + +By 2016 the number of troops will have decreased to 5,500 before a further transition to power in Kabul by 2017. + +Secretary of State John Kerry issued a statement today saying Somers' murder 'is a reminder of the brutality of the terrorists of al Qaeda in the Arabian Peninsula. They have again demonstrated their cruelty and their disdain for human life, freedom, and the Yemeni people whom they terrorize daily. + +Kerry said he's 'proud of the brave men and women of the U.S. military who twice risked their lives in operations to try and bring Luke home safely. + +'We also appreciate the efforts of the dedicated intelligence, law enforcement, and diplomatic professionals who supported these operations, and we are particularly grateful to the Yemeni government, under the leadership of President Hadi, for their critical and supportive role in trying to liberate this young American from unfathomable captivity, and for their enduring partnership in combating the scourge of AQAP.' + +The AWAP terrorists know 'how to hate, they know how to murder, and now they have robbed a family of an idealistic young photojournalist who went to Yemen to practice his calling and document the lives of ordinary Yemenis,' Kerry said. + +South African Pierre Korkie was killed in the attempted rescue mission by the United States - just a day before he was due to be released, an aid group says. + +Mr Korkie was killed in the failed effort to release hostages, Imtiaz Sooliman, founder of the Gift of the Givers group told the South African Press Agency. + +Korkie was to be freed by al-Qaeda on Sunday, Gift of the Givers said on Twitter. + +South African Pierre Korkie was killed in the attempted rescue mission by the United States - just a day before he was due to be released. His wife Yolande is pictured right + +'Leaders met in Aden this morning, preparing final security and logistical arrangements 2 bring Pierre 2 safety & freedom,' said tweeted the aid group. + +Mr Korkie and his wife Yolande were taken hostage in Taiz, Yemen, in May 2013, the charity said. + +A team had met in Aden this morning, preparing final security and logistical arrangements 2 bring the hostage to freedom, it claimed. + +'It is even more tragic that the words we used in a conversation with Yolande at 5.59 this morning was 'the wait is almost over',' the charity tweeted to its 7,500 followers. + +It added:'Three days ago we told her 'Pierre will be home for Christmas'. + +'We certainly did not mean it in the manner it has unfolded. + +'All logistical arrangements were in place 2 safely fly Pierre out of Yemen under diplomatic cover.' + +At the time of the kidnapping, Mr Korkie was a teacher in Yemen, while his wife was working in hospitals, News24 reports. + +Those close to Mr Korkie said al-Qaeda militants had demanded a $3million ransom for his release. + +British Foreign Secretary, Philip Hammond said: 'My deepest condolences are with the families of both hostages at this time. We utterly condemn AQAP for the brutal murder of these two men. + +'Luke had close links with the UK and his family have spoken about Luke's life and his work, and that is how he should be remembered. + +'I salute the forces involved, who showed great courage in carrying out this mission. We continue to work with our international and Yemeni partners to counter the threat from Al Qaida and other terrorist groups.' + +The humanitarian group Gift of Givers said today that teacher Pierre Korkie was shot dead during the bid to rescue Mr Somers - just a day before he was set to be freed. + +Mr Korkie and his wife Yolande were reportedly captured by militants in May 2013 in Ta'iz, Yemen. But his wife was released after Gift of the Givers helped negotiate her freedom. + +On Friday, a team of local leaders was finalizing arrangements to reunite Pierre Korkie to his wife and children, the statement reads. + +The charity recently told his wife that 'the wait is almost over.' + +Militants released a video on Thursday that showed Mr Somers, threatening to kill him in three days if the United States did not meet the group's demands + +'Three days ago we told her 'Pierre will be home for Christmas,'' the group said. 'We certainly did not mean it in the manner it has unfolded.' + +Yemen's national security chief, Major General Ali al-Ahmadi, said the militants planned to kill Luke Somers on Saturday, meaning the American and Yemeni forces faced a race against time. + +'Al-Qaeda promised to conduct the execution (of Somers) today so there was an attempt to save them but unfortunately they shot the hostage before or during the attack, al-Ahmadi said at a conference in Manama, Bahrain. + +Earlier this week al Qaeda in the Arabian Peninsula (AQAP) issued a video with a message aimed at the US government threatening to kill Mr Somers if its demands were not met. + +Last week the U.S. said it had attempted a rescue operation to free a number of hostages, including Mr Somers, but that he had not been at the site of the raid. + +The family of Mr Somers had earlier pleaded for him to be released. + +In an online video Miss Somers described her older brother as a romantic who 'always believes the best in people.' She added: 'Please let him live.' + +His father Michael said Mr Somers was 'a good friend of Yemen and the Yemeni people'. + +It came after the release of the AQAP video which begins with a reading in Arabic from Nasser bin Ali al Ansi, an AQAP official, before Mr Somers appears and gives a statement in English. + +Nasser bin Ali al Ansi, senior official in Al Qaeda in the Arabian Peninsula, pictured, spoke for two minutes and thirty seconds during the video where he threatened to kill Mr Somers within three days + +He said: 'My name is Luke Somers. I'm 33 years old. I was born in England, but I carry American citizenship and have lived in America for most of my life. + +'It's now been well over a year since I've been kidnapped in Sana'a. Basically, I'm looking for any help that can get me out of this situation. I'm certain that my life is in danger. + +'So as I sit here now, I ask if anything can be done, please let it be done. Thank you very much.' + +Al Ansi gave the US government three days to meet the demands or 'otherwise, the American hostage held by us will meet his inevitable fate'. + +The three-minute video also features Ansi speaking about American activity in Afghanistan, Somalia and Iraq as well as recent air strikes in Syria. + +It follows similar videos by another extremist militant group, Islamic State (IS), which has already killed two British hostages and three American hostages in videos released on social media. + +Luke Somers had been working as a freelance photographer when he was captured, and those who knew him say he had 'wanderlust' and was drawn to new experiences. + +Mr Somers, who was born in Britain, earned a bachelor's degree in creative writing while attending Beloit College in Wisconsin from 2004 through 2007. + +'He really wanted to understand the world,' said Shawn Gillen, an English professor and chairman of Beloit College's journalism program. + +Fuad Al Kadas, who said Somers is one of his best friends, said Somers spent time in Egypt before finding work in Yemen. Somers started teaching English at a Yemen school but quickly established himself as a one of the few foreign photographers in the country, he said. + +'He is a great man with a kind heart who really loves the Yemeni people and the country,' Al Kadas wrote in an email from Yemen. He said he last saw Somers the day before he was kidnapped. + +'He was so dedicated in trying to help change Yemen's future, to do good things for the people that he didn't leave the country his entire time here,' Al Kadas wrote. + +Al Kadas said in Yemen, Somers enjoyed making friends with neighbors, youth activists and ordinary people. + +American commandos tried to rescue Mr Somers (pcitred) in a raid on an AQAP camp late last month, but he had been moved by the time they arrived + +Gillen said Somers wanted to seek out experiences that would matter to him, noting he traveled to Egypt as part of the school's study abroad program. The professor said he wasn't surprised when he heard Somers had moved to Yemen. + +'He'd want to be in places where world events were happening,' the professor said, adding that liberal arts instructors want their students 'to go on and lead meaningful, purposeful lives. Luke was trying to do that. That makes (his capture) all the more horrible for us to ponder.' + +Gillen said Somers was in his advanced non-fiction writing course and a small-group seminar that focused on William Butler Yeats and James Joyce. He said Somers would often stop by his office just to chat. + +'He would come by and say, 'I was walking across campus and I was thinking about something Joyce wrote,' and he'd want to talk about it. In many ways that's a professor's dream come true,' Gillen said. + +Friends of Mr Somers (pictured) said he had 'wanderlust' and was drawn to new experiences + +In 2007, Somers worked as an editor at The Teaching Drum Outdoors School in Three Lakes, Wisconsin. + +Tamarack Song, the school's director, said Somers was hired to edit a book for the school. He came to the school with his girlfriend who also was an editor. + +'He was born in England, raised in America. He had wanderlust,' Song said. 'He wanted to know what made people tick. He has an undying curiosity for human dynamics and for the way people worked. He was constantly doing research.' + +Song said he thought Yemen and the Middle East was a symbol for Somers, and that Somers wanted to be at the epicenter of culture and ideology. + +Song said he speculates that Somers went 'to be where the action was, to get a feel for the pulse of contemporary conflict.' + +'He wanted to be in the center of things, and to get a feel for it. To get closer and closer, to interview people, to research, to write, to get right there,' Song said. + +Penny Bearman, the step-mother of the hostage, paid tribute to her husband's son following his death. + +She told ITV News: 'Luke’s taste for travel grew early on in life. He was born in London to an American Mother who returned to the States with him when he was 7 years old, visiting his father each year in Deal, Kent. + +'As a young man he worked Salmon Fishing in the Arctic, lived for a time in Jamaica, witnessed riots in Cairo and moved to Yemen in 2011. + +'He was a talented photographer with a sensitivity for people and people’s lives and made a considerable contribution as a photo journalist in telling the stories of communities in war-torn areas. + +'Recently he lived in Sana’a the capital city of Yemen, living as a well-loved and respected member of the community there. He has extensive coverage of the area online, illustrating and expressing the struggles of the Yemen people. + +'I think Luke would have wanted issues of extremism and terrorism to be addressed by stepping up the dialogue instead of resorting to conflict between nations.' + +During his time in Trenchtown, a municipality in Jamaica, he was involved in a number of projects where he captured photos of citizens around the town. + +IS has posted a series of videos online showing the separate murders of US journalists James Foley and Steven Sotloff, US aid worker Peter Kassig and two British aid workers, David Haines and Alan Henning. + +Foley, who was beheaded in by the terrorists in August, was reportedly the subject of another failed rescue mission in July. + +Following his death, White House counterterrorism adviser told the press: 'The U.S. government had what we believed was sufficient intelligence, and when the opportunity presented itself, the president authorized the Department of Defense to move aggressively to recover our citizens. + +'Unfortunately, that mission was ultimately not successful because the hostages were not present.' + +The Obama administration was accused of knowing where Foley was five weeks before the extraction attempt in July and questions have been raised as to why they hesitated. + +A former military official told Fox that when the team 'finally did go' into Syria to try and save Foley and a number of other hostages they felt the intelligence was 'drying up'. + +Footage claiming to show Mr Henning's murder appeared on the internet just days after the UK joined US-led air strikes against the terrorists in Iraq. + +The news of the failed rescue comes after a suspected U.S. drone strike in Yemen killed nine alleged al-Qaeda militants early Saturday, a security official said. + +The drone struck at dawn in Yemen's southern Shabwa province, hitting a suspected militant hideout, the official said. + +The official did not elaborate and spoke on condition of anonymity as he wasn't authorised to brief journalists. + +At least six suspected militants were killed in an airstrike in the same province last month. + +Later Saturday, tribal leaders said they saw helicopters flying over an area called Wadi Abdan in Shabwa province. + +Begging for mercy: Luke's brother, Jordan (left), and his mother, Paula Somers (right), released a video on Thursday asking his al-Qaeda captors to release him + +American authorities rarely discuss their drone strike campaign in Yemen. + +The strikes are incredibly unpopular in Yemen due to civilian casualties, legitimising for many the attacks on American interests. + +In a statement on Thursday, Pentagon press secretary Rear Admiral John Kirby acknowledged for the first time that a mysterious U.S. raid last month had sought to rescue Mr Somers but that he turned out not to be at the site. + +Kirby did not elaborate on the joint U.S-Yemeni operation to free Mr Somers, saying details remained classified. + +However, officials have said the raid targeted a remote al-Qaeda safe haven in a desert region near the Saudi border. Eight captives - including Yemenis, a Saudi and an Ethiopian - were freed. + +Mr Somers, and five others had been moved days earlier + +After hearing of Luke Somers' death, friend and colleague Tik Root paid tribute to the photojournalist on PBS. + +He said: 'Luke never wavered from the front lines. He spent countless hours documenting revolutionaries in Sanaa's Change Square and snapped photos ranging from Yemen's former president to children afflicted with malnutrition. + +'His work provides a gripping window into a country rarely on the world's radar. It also reveals his deep and persistent love for the country. + +'I knew Luke. Not particularly well. But during my 15 months as a fellow freelancer in Yemen, we crossed paths on perhaps a dozen or so occasions — both social and professional. Quirky, passionate and thoughtful, he also struck me as a fairly private guy.' + +He also revealed some of the pictures he liked while Mr Somers worked with Demotix. + +Here is a collection of his work while in the Middle East - including striking photos of children, protesters and politicians. + +A young boy from the Home Care Orphanage in Sana'a, Yemen, participates in a drawing competition in July 2012 + +Houthi followers reach the conclusion of a march in Sana'a, with eleven days to go before they celebrate the birthday of the Prophet Mohammed in January 2013 + +Shi'ite Houthis marched in Sana'a in anticipation of the Prophet Mohammed's birthday, 'Mawlid An-Nabi' in Arabic, which in 2013 fell on January 29 + +Women are controlled by security in August 2012 as they enter the residence of a family which, every year during Ramadan, distributes charity in the form of cash to Sana'a's poor and needy + +During a demonstration near Yemeni President Abd Rabbu Mansour Hadi's Sana'a residence in December 2012, a female protester holds up a picture of former president Ibrahim al-Hamdi, a beloved figure for many Yemeni citizens + +Gulf Cooperation Council Secretary General Abdul-Latif Al-Zayani speaks with United States Ambassador to Yemen Gerald Feierstein about Yemen's upcoming National Dialogue in January 2013 + +Tribesmen loyal to the powerful al-Ahmar family stand outside the family compound in Sana'a, Yemen in December 2012","1" +"REVEALED: Navy Seals hiked six miles and got within 100 yards of Yemen compound where executed US hostage was being held - before a 'dog bark' alerted al-Qaeda captors","A British-born U.S. photojournalist and a South African aid worker held hostage in Yemen by al Qaeda militants have been 'murdered' in a failed rescue attempt. + +American citizen Luke Somers had been held hostage since September 2013 in Yemen's capital Sana'a having moved to the country two years earlier. + +The 33-year-old was reportedly shot by his captors as Navy SEAL Team six, made up of around 40 men, carried out a dramatic rescue bid in the Wadi Abdan region of the southern Shabwa province late on Friday night. + +It is the second attempted extraction by special forces in as many months. + +Another hostage, South African aid worker Pierre Korkie, was also killed during the operation - a day before he was due to be released. + +According to the Wall Street Journal the commandos hiked for six miles through a mountain range to reach the village where he was being held. + +Scroll down for video + +Lucy Somers said she learned of her 33-year-old brother Luke Somers' death from FBI agents + +In April 2013 he took photos of a protest by Yemenis, demanding the release of Guantanamo Bay trainees + +They were only 100 yards away from the compound when the terrorists reportedly heard a dog bark - prompting the militants to shoot the pair dead. + +Two medics involved in the operation tried to revive both of the hostages, but one died at the scene while the other succumbed to his injuries on the operating table inside the USS Makin Island. + +Outgoing U.S. Defense Secretary Chuck Hagel confirmed Mr Somers death this morning as he landed in Afghanistan. + +During a press conference he announced that 1,000 more US troops than expected will be stationed in the country next year following a spike in Taliban attacks. + +Mr Somers was badly wounded when commandos found him and he died from his injuries by the time he had been flown to a naval ship. + +Mr Somers' sister Lucy Somers told Associated Press that she learned of her brother's death from FBI agents at 5am this morning. 'We ask that all of Luke's family members be allowed to mourn in peace,' she said from London. + +An Osprey aircraft took a team of U.S. Navy SEALS to the location, which was close to the site where a previous rescue mission had taken place, officials told CNN. + +A gun fight is understood to have unfolded before the badly injured hostages were taken away on the aircraft, the report says. + +Four Yemeni and CTU agents were wounded during the operation. + +According to the New York Times the forces raided four houses in the village where the attack took place, killed six militants but also gunned down eight civilians. + +Mr Somers was kidnapped in September 2013 as he left a supermarket in the Yemeni capital, Sana'a, said Fakhri al-Arashi, chief editor of the National Yemen. + +He had moved to the country in 2010 to teach English as the Arab Spring started to develop but soon became one of the country's only foreign photographers. + +The hostage worked at the paper as a copy editor and a freelance photographer during the 2011 uprising in Yemen. + +There are reports Mr Somers was sold to al-Qaeda in the Arabian Peninsula (AQAP) - one of the most dangerous regional arms of the terrorist group. + +The organisation make millions ransoming hostages - but British and American governments refuse to pay. + +On November 25, U.S Special Forces sent a unit to a cave near the Yemen border with Saudi Arabia in a hope of retrieving Mr Somers. Seven hostages were saved and eight militants were killed but the journalist was not inside. + +The U.S. considers Yemen's al-Qaeda branch to be the world's most dangerous arm of the group as it has been linked to several failed attacks on the U.S. homeland. + +Barack Obama described Mr Somers' murder as 'barbaric' in a statement this morning. + +'On behalf of the American people, I offer my deepest condolences to Luke's family and to his loved ones,' he said in a statement. + +British-born U.S. photojournalist Luke Somers (pictured), who was being held by al-Qaeda militants in Yemen, has been killed in a failed rescue attempt, his sister has revealed today + +Luke Somers was kidnapped in September 2013 from Yemen's capital Sana'a (shown in the map above) + +Mr Somers moved from London to Sana'a, Yemen in 2010 to become a teacher, but soon started taking pictures of public demonstrations and established himself as a photojournalist working for the Yemen Times + +The photojournalist bends down to take a picture during the National Dialogue Conference in Sanaa in July 2013, weeks before he was captured + +'As this and previous hostage rescue operations demonstrate, the United States will spare no effort to use all of its military, intelligence and diplomatic capabilities to bring Americans home safely, wherever they are located. + +'And terrorists who seek to harm our citizens will feel the long arm of American justice,' he said. + +President Obama said he authorised the raid on Friday to rescue Somers and other hostages held in the same location. He said the United States had used every tool at its disposal to secure Somers' release since his capture 15 months ago. + +He also thanked the Yemen government for its support. It is understood that the U.S. personnel who carried out the raid are safe. + +'Luke was a photojournalist who sought through his images to convey the lives of Yemenis to the outside world,' President Obama said. + +'The callous disregard for Luke's life is more proof of the depths of AQAP's depravity, and further reason why the world must never cease in seeking to defeat their evil ideology,' he said. + +Hagel this morning confirmed Mr Somers and a second hostage being held by terrorists in Yemen were 'murdered' during a rescue attempt ordered by the President. + +Hagel said that several terrorists were also killed in the mission carried out by U.S. special forces. + +The outgoing Pentagon head said the raid was 'well-executed' and based on better intelligence forces had received in the last 24 hours. + +He made the announcement just hours before holding a press conference with Afghan President Ashraf Ghani - during which he confirmed 10,800 troops will still be in Afghanistan in 2015. + +The original plan was to cut the number down to 9,800. + +'It's predictable that they would do everything they could and continue to do to try to disrupt and discourage the new government of President Ghani,' he said. + +The news of the hostage's death came as U.S. Secretary of Defense Chuck Hagel made an unannounced visit to Kabul to meet Afghan President Ghani and announce that more troops than expected will be stationed in the country in 2015 + +The outgoing Pentagon head said a recent spike in attacks by the Taliban proved that they were trying to disrupt the transition into the new government + +The Defense Department said the rise in violence did not prompt the decision to keep troops in the country. + +An official statement said it was due to the late signing of the Bilateral Security Agreement, which allows a specified amount of U.S. troops to remain after the combat mission ends this year. + +Hamid Karzai, Ghani's predecessor, refused to sign the deal. + +According to The Pentagon, 99 per cent of Afghan forces are now taking the lead in missions and are performing 'well'. + +By 2016 the number of troops will have decreased to 5,500 before a further transition to power in Kabul by 2017. + +Secretary of State John Kerry issued a statement today saying Somers' murder 'is a reminder of the brutality of the terrorists of al Qaeda in the Arabian Peninsula. They have again demonstrated their cruelty and their disdain for human life, freedom, and the Yemeni people whom they terrorize daily.' + +Kerry said he's 'proud of the brave men and women of the U.S. military who twice risked their lives in operations to try and bring Luke home safely. + +'We also appreciate the efforts of the dedicated intelligence, law enforcement, and diplomatic professionals who supported these operations, and we are particularly grateful to the Yemeni government, under the leadership of President Hadi, for their critical and supportive role in trying to liberate this young American from unfathomable captivity, and for their enduring partnership in combating the scourge of AQAP.' + +The AWAP terrorists know 'how to hate, they know how to murder, and now they have robbed a family of an idealistic young photojournalist who went to Yemen to practice his calling and document the lives of ordinary Yemenis,' Kerry said. + +Vice President Joe Biden said the U.S. would be relentless in its efforts to bring the killers of an American photojournalist to justice. + +Echoing the words of the President he called the killing of Mr Somers a 'despicable crime'. + +He says U.S. special forces soldiers 'inflicted serious damage' on Somers captors. + +Biden commented Saturday during a previously scheduled address to a Washington conference on U.S.-Israeli relations. + +South African Pierre Korkie was killed in the attempted rescue mission by the United States - just a day before he was due to be released, an aid group says. + +Mr Korkie was killed in the failed effort to release hostages, Imtiaz Sooliman, founder of the Gift of the Givers group told the South African Press Agency. + +Korkie was to be freed by al-Qaeda on Sunday, Gift of the Givers said on Twitter. + +South African Pierre Korkie was killed in the attempted rescue mission by the United States - just a day before he was due to be released. His wife Yolande is pictured right + +'Leaders met in Aden this morning, preparing final security and logistical arrangements 2 bring Pierre 2 safety & freedom,' said tweeted the aid group. + +Mr Korkie and his wife Yolande were taken hostage in Taiz, Yemen, in May 2013, the charity said. + +A team had met in Aden this morning, preparing final security and logistical arrangements 2 bring the hostage to freedom, it claimed. + +'It is even more tragic that the words we used in a conversation with Yolande at 5.59 this morning was 'the wait is almost over',' the charity tweeted to its 7,500 followers. + +It added:'Three days ago we told her 'Pierre will be home for Christmas'. + +'We certainly did not mean it in the manner it has unfolded. + +'All logistical arrangements were in place 2 safely fly Pierre out of Yemen under diplomatic cover.' + +At the time of the kidnapping, Mr Korkie was a teacher in Yemen, while his wife was working in hospitals, News24 reports. + +Those close to Mr Korkie said al-Qaeda militants had demanded a $3million ransom for his release. + +British Foreign Secretary, Philip Hammond said: 'My deepest condolences are with the families of both hostages at this time. We utterly condemn AQAP for the brutal murder of these two men. + +'Luke had close links with the UK and his family have spoken about Luke's life and his work, and that is how he should be remembered. + +'I salute the forces involved, who showed great courage in carrying out this mission. We continue to work with our international and Yemeni partners to counter the threat from Al Qaida and other terrorist groups.' + +The humanitarian group Gift of Givers said today that teacher Pierre Korkie was shot dead during the bid to rescue Mr Somers - just a day before he was set to be freed. + +Mr Korkie and his wife Yolande were reportedly captured by militants in May 2013 in Ta'iz, Yemen. But his wife was released after Gift of the Givers helped negotiate her freedom. + +On Friday, a team of local leaders was finalizing arrangements to reunite Pierre Korkie to his wife and children, the statement reads. + +The charity recently told his wife that 'the wait is almost over.' + +Militants released a video on Thursday that showed Mr Somers, threatening to kill him in three days if the United States did not meet the group's demands + +'Three days ago we told her 'Pierre will be home for Christmas,'' the group said. 'We certainly did not mean it in the manner it has unfolded.' + +Yemen's national security chief, Major General Ali al-Ahmadi, said the militants planned to kill Luke Somers on Saturday, meaning the American and Yemeni forces faced a race against time. + +'Al-Qaeda promised to conduct the execution (of Somers) today so there was an attempt to save them but unfortunately they shot the hostage before or during the attack, al-Ahmadi said at a conference in Manama, Bahrain. + +Earlier this week al Qaeda in the Arabian Peninsula (AQAP) issued a video with a message aimed at the US government threatening to kill Mr Somers if its demands were not met. + +Last week the U.S. said it had attempted a rescue operation to free a number of hostages, including Mr Somers, but that he had not been at the site of the raid. + +The family of Mr Somers had earlier pleaded for him to be released. + +In an online video Miss Somers described her older brother as a romantic who 'always believes the best in people.' She added: 'Please let him live.' + +His father Michael said Mr Somers was 'a good friend of Yemen and the Yemeni people'. + +It came after the release of the AQAP video which begins with a reading in Arabic from Nasser bin Ali al Ansi, an AQAP official, before Mr Somers appears and gives a statement in English. + +Nasser bin Ali al Ansi, senior official in Al Qaeda in the Arabian Peninsula, pictured, spoke for two minutes and thirty seconds during the video where he threatened to kill Mr Somers within three days + +He said: 'My name is Luke Somers. I'm 33 years old. I was born in England, but I carry American citizenship and have lived in America for most of my life. + +'It's now been well over a year since I've been kidnapped in Sana'a. Basically, I'm looking for any help that can get me out of this situation. I'm certain that my life is in danger. + +'So as I sit here now, I ask if anything can be done, please let it be done. Thank you very much.' + +Al Ansi gave the US government three days to meet the demands or 'otherwise, the American hostage held by us will meet his inevitable fate'. + +The three-minute video also features Ansi speaking about American activity in Afghanistan, Somalia and Iraq as well as recent air strikes in Syria. + +It follows similar videos by another extremist militant group, Islamic State (IS), which has already killed two British hostages and three American hostages in videos released on social media. + +Luke Somers had been working as a freelance photographer when he was captured, and those who knew him say he had 'wanderlust' and was drawn to new experiences. + +Mr Somers, who was born in Britain, earned a bachelor's degree in creative writing while attending Beloit College in Wisconsin from 2004 through 2007. + +'He really wanted to understand the world,' said Shawn Gillen, an English professor and chairman of Beloit College's journalism program. + +Fuad Al Kadas, who said Somers is one of his best friends, said Somers spent time in Egypt before finding work in Yemen. Somers started teaching English at a Yemen school but quickly established himself as a one of the few foreign photographers in the country, he said. + +'He is a great man with a kind heart who really loves the Yemeni people and the country,' Al Kadas wrote in an email from Yemen. He said he last saw Somers the day before he was kidnapped. + +'He was so dedicated in trying to help change Yemen's future, to do good things for the people that he didn't leave the country his entire time here,' Al Kadas wrote. + +Al Kadas said in Yemen, Somers enjoyed making friends with neighbors, youth activists and ordinary people. + +American commandos tried to rescue Mr Somers (pcitred) in a raid on an AQAP camp late last month, but he had been moved by the time they arrived + +Gillen said Somers wanted to seek out experiences that would matter to him, noting he traveled to Egypt as part of the school's study abroad program. The professor said he wasn't surprised when he heard Somers had moved to Yemen. + +'He'd want to be in places where world events were happening,' the professor said, adding that liberal arts instructors want their students 'to go on and lead meaningful, purposeful lives. Luke was trying to do that. That makes (his capture) all the more horrible for us to ponder.' + +Gillen said Somers was in his advanced non-fiction writing course and a small-group seminar that focused on William Butler Yeats and James Joyce. He said Somers would often stop by his office just to chat. + +'He would come by and say, 'I was walking across campus and I was thinking about something Joyce wrote,' and he'd want to talk about it. In many ways that's a professor's dream come true,' Gillen said. + +Friends of Mr Somers (pictured) said he had 'wanderlust' and was drawn to new experiences + +In 2007, Somers worked as an editor at The Teaching Drum Outdoors School in Three Lakes, Wisconsin. + +Tamarack Song, the school's director, said Somers was hired to edit a book for the school. He came to the school with his girlfriend who also was an editor. + +'He was born in England, raised in America. He had wanderlust,' Song said. 'He wanted to know what made people tick. He has an undying curiosity for human dynamics and for the way people worked. He was constantly doing research.' + +Song said he thought Yemen and the Middle East was a symbol for Somers, and that Somers wanted to be at the epicenter of culture and ideology. + +Song said he speculates that Somers went 'to be where the action was, to get a feel for the pulse of contemporary conflict.' + +'He wanted to be in the center of things, and to get a feel for it. To get closer and closer, to interview people, to research, to write, to get right there,' Song said. + +Penny Bearman, the step-mother of the hostage, paid tribute to her husband's son following his death. + +She told ITV News: 'Luke's taste for travel grew early on in life. He was born in London to an American Mother who returned to the States with him when he was 7 years old, visiting his father each year in Deal, Kent. + +'As a young man he worked Salmon Fishing in the Arctic, lived for a time in Jamaica, witnessed riots in Cairo and moved to Yemen in 2011. + +'He was a talented photographer with a sensitivity for people and people's lives and made a considerable contribution as a photo journalist in telling the stories of communities in war-torn areas. + +'Recently he lived in Sana'a the capital city of Yemen, living as a well-loved and respected member of the community there. He has extensive coverage of the area online, illustrating and expressing the struggles of the Yemen people. + +'I think Luke would have wanted issues of extremism and terrorism to be addressed by stepping up the dialogue instead of resorting to conflict between nations.' + +During his time in Trenchtown, a municipality in Jamaica, he was involved in a number of projects where he captured photos of citizens around the town. + +IS has posted a series of videos online showing the separate murders of US journalists James Foley and Steven Sotloff, US aid worker Peter Kassig and two British aid workers, David Haines and Alan Henning. + +Foley, who was beheaded in by the terrorists in August, was reportedly the subject of another failed rescue mission in July. + +Following his death, White House counterterrorism adviser told the press: 'The U.S. government had what we believed was sufficient intelligence, and when the opportunity presented itself, the president authorized the Department of Defense to move aggressively to recover our citizens. + +'Unfortunately, that mission was ultimately not successful because the hostages were not present.' + +The Obama administration was accused of knowing where Foley was five weeks before the extraction attempt in July and questions have been raised as to why they hesitated. + +A former military official told Fox that when the team 'finally did go' into Syria to try and save Foley and a number of other hostages they felt the intelligence was 'drying up'. + +Footage claiming to show Mr Henning's murder appeared on the internet just days after the UK joined US-led air strikes against the terrorists in Iraq. + +The news of the failed rescue comes after a suspected U.S. drone strike in Yemen killed nine alleged al-Qaeda militants early Saturday, a security official said. + +The drone struck at dawn in Yemen's southern Shabwa province, hitting a suspected militant hideout, the official said. + +The official did not elaborate and spoke on condition of anonymity as he wasn't authorised to brief journalists. + +At least six suspected militants were killed in an airstrike in the same province last month. + +Later Saturday, tribal leaders said they saw helicopters flying over an area called Wadi Abdan in Shabwa province. + +Begging for mercy: Luke's brother, Jordan (left), and his mother, Paula Somers (right), released a video on Thursday asking his al-Qaeda captors to release him + +American authorities rarely discuss their drone strike campaign in Yemen. + +The strikes are incredibly unpopular in Yemen due to civilian casualties, legitimising for many the attacks on American interests. + +In a statement on Thursday, Pentagon press secretary Rear Admiral John Kirby acknowledged for the first time that a mysterious U.S. raid last month had sought to rescue Mr Somers but that he turned out not to be at the site. + +Kirby did not elaborate on the joint U.S-Yemeni operation to free Mr Somers, saying details remained classified. + +However, officials have said the raid targeted a remote al-Qaeda safe haven in a desert region near the Saudi border. Eight captives - including Yemenis, a Saudi and an Ethiopian - were freed. + +Mr Somers, and five others had been moved days earlier + +After hearing of Luke Somers' death, friend and colleague Tik Root paid tribute to the photojournalist on PBS. + +He said: 'Luke never wavered from the front lines. He spent countless hours documenting revolutionaries in Sanaa's Change Square and snapped photos ranging from Yemen's former president to children afflicted with malnutrition. + +'His work provides a gripping window into a country rarely on the world's radar. It also reveals his deep and persistent love for the country. + +'I knew Luke. Not particularly well. But during my 15 months as a fellow freelancer in Yemen, we crossed paths on perhaps a dozen or so occasions — both social and professional. Quirky, passionate and thoughtful, he also struck me as a fairly private guy.' + +He also revealed some of the pictures he liked while Mr Somers worked with Demotix. + +Here is a collection of his work while in the Middle East - including striking photos of children, protesters and politicians. + +A young boy from the Home Care Orphanage in Sana'a, Yemen, participates in a drawing competition in July 2012 + +Houthi followers reach the conclusion of a march in Sana'a, with eleven days to go before they celebrate the birthday of the Prophet Mohammed in January 2013 + +Shi'ite Houthis marched in Sana'a in anticipation of the Prophet Mohammed's birthday, 'Mawlid An-Nabi' in Arabic, which in 2013 fell on January 29 + +Women are controlled by security in August 2012 as they enter the residence of a family which, every year during Ramadan, distributes charity in the form of cash to Sana'a's poor and needy + +During a demonstration near Yemeni President Abd Rabbu Mansour Hadi's Sana'a residence in December 2012, a female protester holds up a picture of former president Ibrahim al-Hamdi, a beloved figure for many Yemeni citizens + +Gulf Cooperation Council Secretary General Abdul-Latif Al-Zayani speaks with United States Ambassador to Yemen Gerald Feierstein about Yemen's upcoming National Dialogue in January 2013 + +Tribesmen loyal to the powerful al-Ahmar family stand outside the family compound in Sana'a, Yemen in December 2012","1" +"US hostage 'murdered' by militants in Yemen, says Hagel","Defense Secretary Chuck Hagel said on Saturday that US journalist Luke Somers was killed by militants during an operation aimed at freeing him from his Al-Qaeda kidnappers in Yemen. + +""US Special Operations Forces conducted a mission in Yemen to rescue a US citizen, Luke Somers, and any other foreign nationals held hostage with him by Al-Qa'ida in the Arabian Peninsula (AQAP) terrorists,"" Hagel said in a statement released during a visit to Kabul. + +""Both Mr. Somers and a second non-US citizen hostage were murdered by the AQAP terrorists during the course of the operation."" + +A grab taken from a propaganda video released by al-Malahem Media on December 4, 2014 purportedly shows US hostage Luke Somers, 33, kidnapped more than a year ago in the Yemeni capital Sanaa, saying that his life is in danger + +A charity that had been involved in negotiations said the second dead hostage was Pierre Korkie from South Africa. + +Hagel added that Friday's operation was undertaken when ""there were compelling reasons to believe Mr. Somers' life was in imminent danger."" + +""Several of the AQAP terrorists holding the hostages captive were killed in the mission,"" he said. + +""The rescue attempt took place in central Yemen and was conducted in partnership with the Government of Yemen. + +""Yesterday's mission is a reminder of America's unrelenting commitment to the safety of our fellow citizens -- wherever they might be around the world. + +""I commend the troops who undertook this dangerous mission."" + +Sorry we are not currently accepting comments on this article.","1" +"US, South African hostages killed in Yemen rescue bid","American journalist Luke Somers and a South African hostage were killed on Saturday during a failed attempt by US forces to rescue them from Al-Qaeda militants in Yemen. + +Somers's death was announced by US Defence Secretary Chuck Hagel, who said the raid was carried out because the photojournalist's life was believed to be ""in imminent danger"". + +Al-Qaeda in the Arabian Peninsula (AQAP) had on Thursday threatened to execute Somers, 33, who was kidnapped more than a year ago in Sanaa. + +A grab taken from a propaganda video released by al-Malahem Media on December 4, 2014 purportedly shows US hostage Luke Somers, 33, kidnapped more than a year ago in the Yemeni capital Sanaa, saying that his life is in danger + +""Both Mr Somers and a second non-US citizen hostage were murdered by the AQAP terrorists during the course of the operation,"" Hagel said in a statement released during a visit to Kabul. + +South African hostage Pierre Korkie was also killed in the raid, according to a charity that had been negotiating his release. + +The Gift of the Givers said that Korkie's death came a day before he was due to be freed after more than a year in captivity. + +""The psychological and emotional devastation to (his wife) Yolande and her family will be compounded by the knowledge that Pierre was to be released by Al-Qaeda tomorrow,"" it said. + +Ten militants were killed in the joint operation in Shabwa province in southeast Yemen, Yemen's defence ministry said. + +A tribal leader said soldiers were seen parachuting into the area. + +Heavy clashes ensued in Nusab, a militant stronghold, according to residents who reported hearing loud explosions. + +Hagel said the rescue attempt was conducted in partnership with the Yemeni government. + +The operation ""is a reminder of America's unrelenting commitment to the safety of our fellow citizens -- wherever they might be around the world,"" he added. + +- Deadliest Qaeda affiliate - + +The United States has said that American and Yemeni forces had already tried unsuccessfully to rescue Somers last month. + +According to Yemen's defence ministry, Al-Qaeda moved hostages, including the US journalist, a Briton and a South African, days before that US-Yemeni raid in southeastern Hadramawt province. + +Yemeni officials said eight other hostages were freed in the earlier operation. + +Yemen is a key US ally in the fight against Al-Qaeda, allowing Washington to conduct a longstanding drone war against the group on its territory. + +AQAP is considered by Washington to be the most dangerous affiliate of Al-Qaeda. + +The execution threat by AQAP followed the murder of five Western hostages since August by the Islamic State group that controls parts of Syria and Iraq. + +Two US journalists, James Foley and Steven Sotloff, American aid worker Peter Kassig and British aid workers Alan Henning and David Haines were all beheaded. + +Al-Qaeda has exploited instability in impoverished Yemen since a 2011 uprising forced president Ali Abdullah Saleh to step down. + +In recent years there has been a growing number of abductions in Yemen by Al-Qaeda. + +The militants remain active in southern and eastern regions of Yemen despite several military campaigns by government forces. + +Al-Qaeda militants have allied with Sunni tribesmen in southern Yemen to halt the advance of Shiite Huthi militias who seized Sanaa in September unopposed, and who have since extended their control to coastal areas and regions south of the capital. + +South African Yolande Korkie, a former hostage and wife of Pierre Korkie, holds a press conference in Johannesburg to appeal for the release of her husband held in Yemen on January 16, 2014 ©Marco Longari (AFP/File) + +US Defense Secretary Chuck Hagel, seen here in Simi Valley, California, on November 15, 2014, said journalist Luke Somers had been killed by Al-Qaeda militants ©Mark Ralston (AFP/File) + +Sorry we are not currently accepting comments on this article.","1" +"US, South African Qaeda hostages killed in Yemen rescue bid","American journalist Luke Somers and a South African hostage were killed on Saturday during a failed attempt by US special forces to free them from Al-Qaeda militants in Yemen. + +President Barack Obama condemned the ""barbaric murder"" of Somers, saying he had authorised the joint rescue operation because the life of the 33-year-old photojournalist was believed to be ""in imminent danger"". + +Al-Qaeda in the Arabian Peninsula (AQAP) had on Thursday threatened to execute Somers, who was kidnapped more than a year ago in the Yemeni capital Sanaa, within three days if Washington failed to meet unspecified demands. + +A grab taken from a propaganda video released by al-Malahem Media on December 4, 2014 purportedly shows US hostage Luke Somers, 33, kidnapped more than a year ago in the Yemeni capital Sanaa, saying that his life is in danger + +""The callous disregard for Luke's life is more proof of the depths of AQAP's depravity, and further reason why the world must never cease in seeking to defeat their evil ideology,"" Obama said in a statement. + +South African hostage Pierre Korkie was also killed in the raid, according to a charity that had been negotiating his release. + +The Gift of the Givers said that Korkie's death came a day before he was due to be freed after more than a year in captivity. + +""The psychological and emotional devastation to (his wife) Yolande and her family will be compounded by the knowledge that Pierre was to be released by Al-Qaeda tomorrow,"" it said. + +The South African couple, who had worked as teachers in Yemen for four years, were seized by Al-Qaeda in May 2013 in the city of Taez. The wife was released in January following mediation by Gift of the Givers. + +The charity said logistical arrangements had already been put in place to fly Pierre Korkie out of Yemen under diplomatic cover after negotiations. + +""It is even more tragic that the words we used in a conversation with Yolande at 5.59 this morning was 'the wait is almost over'. + +""Three days ago we told her 'Pierre will be home for Christmas'. We certainly did not mean it in the manner it has unfolded."" + +Ten militants were killed in the joint operation in Shabwa province in southeast Yemen, Yemen's defence ministry said. + +A tribal leader said soldiers were seen parachuting into the area and residents reported heavy clashes. + +- 'Despicable terrorist organisation' - + +Obama said that since the abduction of Somers 15 months ago, Washington had been using ""every tool at our disposal"" to try to secure his release. + +""Luke was a photojournalist who sought through his images to convey the lives of Yemenis to the outside world,"" Obama added. + +""He came to Yemen in peace and was held against his will and threatened by a despicable terrorist organisation."" + +Washington has a long-standing policy of not negotiating with hostage-takers or paying ransoms. + +The United States has said that American and Yemeni forces had already tried unsuccessfully to rescue Somers last month. + +According to Yemen's defence ministry, Al-Qaeda moved hostages, including the US journalist, a Briton and a South African, days before that US-Yemeni raid in southeastern Hadramawt province. + +The whereabouts of the Briton are unknown. + +Yemeni officials said eight other hostages were freed in the earlier operation. + +Yemen is a key US ally in the fight against Al-Qaeda, allowing Washington to conduct a long-standing drone war against the group on its territory. + +AQAP is considered by Washington to be the most dangerous affiliate of Al-Qaeda. + +The execution threat by AQAP followed the murder of five Western hostages since August by the Islamic State group that controls parts of Syria and Iraq. + +Two US journalists, James Foley and Steven Sotloff, American aid worker Peter Kassig and British aid workers Alan Henning and David Haines were all beheaded. + +Al-Qaeda has exploited instability in impoverished Yemen since a 2011 uprising forced president Ali Abdullah Saleh to step down. + +In recent years there has been a growing number of abductions in Yemen by Al-Qaeda. + +The militants remain active in southern and eastern regions of Yemen despite several military campaigns by government forces. + +Al-Qaeda militants have allied with Sunni tribesmen in southern Yemen to halt the advance of Shiite Huthi militias who seized Sanaa in September unopposed, and who have since extended their control to coastal areas and regions south of the capital. + +An image from a propaganda video released by al-Malahem Media on December 4, 2014 purportedly shows Nasser bin Ali Al-Ansi, of Al-Qaeda in the Arabian Peninsula, reading a message threatening to kill US hostage Luke Somers + +South African Yolande Korkie, a former hostage and wife of Pierre Korkie, holds a press conference in Johannesburg to appeal for the release of her husband held in Yemen on January 16, 2014 ©Marco Longari (AFP/File) + +US Defense Secretary Chuck Hagel, seen here in Simi Valley, California, on November 15, 2014, said journalist Luke Somers had been killed by Al-Qaeda militants ©Mark Ralston (AFP/File) + +Sorry we are not currently accepting comments on this article.","1" +"US, S.African Qaeda hostages killed in Yemen rescue bid","An American and a South African were killed Saturday as US forces tried to free them from Al-Qaeda in Yemen, with President Barack Obama accusing the militants of ""barbaric murder"". + +Obama said he had authorised the joint attempt involving US special forces to rescue American photojournalist Luke Somers because his life was believed to be ""in imminent danger"". + +South African teacher Pierre Korkie was also killed in the raid, which came just a day before he was due to be freed after more than a year in captivity, according to a charity that had been negotiating his release. + +A grab taken from a propaganda video released by al-Malahem Media on December 4, 2014 purportedly shows US hostage Luke Somers, 33, kidnapped more than a year ago in the Yemeni capital Sanaa, saying that his life is in danger + +Al-Qaeda in the Arabian Peninsula (AQAP) had on Thursday threatened to execute Somers, 33, who was kidnapped more than a year ago in the Yemeni capital Sanaa, within three days if Washington failed to meet unspecified demands. + +""The callous disregard for Luke's life is more proof of the depths of AQAP's depravity, and further reason why the world must never cease in seeking to defeat their evil ideology,"" Obama said in a statement. + +Korkie was seized by Al-Qaeda in May 2013 in the city of Taez. He had worked as a teacher in Yemen for four years with his wife Yolande, who was freed in January following mediation by a charity. + +The Gift of the Givers said that Korkie had also been on the brink of release and logistical arrangements had already been put in place to fly him out of Yemen under diplomatic cover after negotiations. + +""The psychological and emotional devastation to Yolande and her family will be compounded by the knowledge that Pierre was to be released by Al-Qaeda tomorrow (Sunday),"" it said. + +""It is even more tragic that the words we used in a conversation with Yolande at 5.59 this morning was 'the wait is almost over'."" + +Ten militants were killed in the joint operation in Shabwa province in southeast Yemen, Yemen's defence ministry said. + +A tribal leader said soldiers were seen parachuting into the area and residents reported heavy clashes. + +The mission ""was extremely well executed"", US Defence Secretary Chuck Hagel said during a visit to Kabul. + +""It was extremely dangerous and complicated,"" he added. ""Like always with these operations, there is risk."" + +- 'Despicable terrorist organisation' - + +Obama said that since Somers was abducted 15 months ago, Washington had been using ""every tool at our disposal"" to try to secure his release. + +""Luke was a photojournalist who sought through his images to convey the lives of Yemenis to the outside world,"" Obama added. + +""He came to Yemen in peace and was held against his will and threatened by a despicable terrorist organisation."" + +Somers's brother Jordan recently described him as a ""good person"", and said he did not know why he was taken hostage. + +""He's a good person and he's only been trying to do good things for the Yemeni population,"" Jordan said in a video earlier this week with his mother Paula. + +The United States has said that American and Yemeni forces had already tried unsuccessfully to rescue Somers last month. + +According to Yemen's defence ministry, Al-Qaeda moved hostages, including the US journalist, a Briton and a South African, days before that joint raid in southeastern Hadramawt province. + +The whereabouts of the Briton are unknown. + +Yemeni officials said eight other hostages were freed in the earlier operation. + +The United States has a long-standing policy of not negotiating with hostage-takers or paying ransoms. + +Yemen is a key US ally in the fight against Al-Qaeda, allowing Washington to conduct a long-standing drone war against the group on its territory. + +AQAP is considered by Washington to be the most dangerous affiliate of Al-Qaeda. + +The execution threat by AQAP followed the murder of five Western hostages since August by the Islamic State group that controls parts of Syria and Iraq. + +Two US journalists, James Foley and Steven Sotloff, American aid worker Peter Kassig and British aid workers Alan Henning and David Haines were all beheaded. + +Al-Qaeda has exploited instability in impoverished Yemen since a 2011 uprising forced president Ali Abdullah Saleh to step down. + +In recent years there has been a growing number of abductions in Yemen by Al-Qaeda which remains active in the south and east despite several campaigns by government forces. + +This undated picture provided on December 6, 2014 by the Gift of the Givers charity shows South African Pierre Korkie before he was kidnapped in Yemen + +South African Yolande Korkie, a former hostage and wife of Pierre Korkie, holds a press conference in Johannesburg to appeal for the release of her husband held in Yemen on January 16, 2014 ©Marco Longari (AFP/File) + +An image from a propaganda video released by al-Malahem Media on December 4, 2014 purportedly shows Nasser bin Ali Al-Ansi, of Al-Qaeda in the Arabian Peninsula, reading a message threatening to kill US hostage Luke Somers + +Yemeni soldiers walks outside the Yemeni Defense Ministry in Sanaa on December 6, 2014 after American journalist Luke Somers and a South African hostage were killed during a failed rescue mission ©Mohammed Huwais (AFP) + +US Defense Secretary Chuck Hagel, seen here in Simi Valley, California, on November 15, 2014, said journalist Luke Somers had been killed by Al-Qaeda militants ©Mark Ralston (AFP/File) + +Sorry we are not currently accepting comments on this article.","1" +"US, S.African Qaeda hostages dead in Yemen rescue bid","An American and a South African were killed Saturday as US forces tried to free hostages from Al-Qaeda in Yemen, with President Barack Obama accusing the militants of ""barbaric murder."" + +Obama said he had authorised the joint attempt involving US special forces to rescue American photojournalist Luke Somers because his life was believed to be ""in imminent danger"". + +South African teacher Pierre Korkie was also killed, just a day before he was due to be freed after more than a year in captivity, said the charity that had negotiated his release. + +A grab taken from a propaganda video released by al-Malahem Media on December 4, 2014 purportedly shows US hostage Luke Somers, 33, kidnapped more than a year ago in the Yemeni capital Sanaa, saying that his life is in danger + +Al-Qaeda in the Arabian Peninsula (AQAP) had threatened Thursday to execute Somers, 33, who was kidnapped 15 months ago in Sanaa. It gave Washington three days to meet unspecified demands. + +""The callous disregard for Luke's life is more proof of the depths of AQAP's depravity,"" Obama said in a statement. + +- Due home for Christmas - + +In May 2013, Al-Qaeda seized Korkie and his wife Yolande, who was released in January. The couple had worked as teachers in Yemen for four years. + +The Gift of Givers charity said logistical arrangements had already been put in place to fly Korkie, 57, out of Yemen under diplomatic cover after negotiations. + +""The psychological and emotional devastation to Yolande and her family will be compounded by the knowledge that Pierre was to be released by Al-Qaeda tomorrow,"" it said. + +""It is even more tragic that the words we used in a conversation with Yolande at 5:59 this morning was 'the wait is almost over.'"" + +""Three days ago we told her 'Pierre will be home for Christmas.' We certainly did not mean it in the manner it has unfolded."" + +Details of the operation were limited, but a tribal leader said soldiers parachuted into the area in the southeastern province of Shabwa. + +Residents reported heavy clashes, and Yemen said 10 militants were killed and four of its own men wounded. + +- Qaeda 'murdered hostages' - + +US Defence Secretary Chuck Hagel said both hostages were ""murdered by the AQAP terrorists during the course of the operation,"" which he described as ""extremely complicated."" + +Imtiaz Sooliman, head of the charity, said US forces intervened to prevent Al-Qaeda from decapitating an American hostage. + +He said he had spoken to his representative in Yemen on Friday about information Al-Qaeda planned to execute a US hostage. + +""I said, that is my greatest fear... and that before they do it, American troops are going to attack and Pierre is going to die in the operation."" + +He said the Americans were probably under pressure from the families of the hostages to act. + +""No one can be blamed for that; it is a hostage-taking, a crisis situation and each one works for his interests,"" he said. + +A State Department official said ""we assessed that there were two hostages at this location,"" including Somers. ""We did not know who the second hostage was."" + +- 'Despicable terrorist organisation' - + +Obama said that since Somers was abducted, Washington had been using ""every tool at our disposal"" to try to secure his release. + +""Luke was a photojournalist who sought through his images to convey the lives of Yemenis to the outside world,"" Obama added. + +""He came to Yemen in peace and was held against his will and threatened by a despicable terrorist organisation."" + +Somers's brother Jordan said he did not know why he was taken hostage. + +""He's a good person and he's only been trying to do good things for the Yemeni population,"" Jordan said in a video earlier this week with his mother Paula. + +The United States has said American and Yemeni forces already tried unsuccessfully to rescue Somers last month. + +According to Yemen's defence ministry, Al-Qaeda moved hostages, including Somers, a Briton and a South African, days before in southeastern Hadramawt province. + +The Briton's whereabouts remain unknown. + +The United States has a long-standing policy of not negotiating with hostage-takers or paying ransoms. Obama has recently ordered a review of policy. + +Reporters Without Borders, reacting to Saturday's news, urged Washington to ""explore all alternatives to the military option and to make every effort to guarantee the safety of the civilians involved."" + +Yemen is a key US ally in the fight against Al-Qaeda, allowing Washington to conduct a long-standing drone war against the group on its territory. + +AQAP is considered by Washington to be the most dangerous affiliate of Al-Qaeda. + +AQAP's threat followed the murder since August of five Western hostages by the Islamic State jihadist group, which controls parts of Syria and Iraq. + +US journalists James Foley and Steven Sotloff, American aid worker Peter Kassig and British aid workers Alan Henning and David Haines were all beheaded. + +Al-Qaeda has exploited instability in impoverished Yemen since a 2011 uprising forced president Ali Abdullah Saleh to step down. + +This undated picture provided on December 6, 2014 by the Gift of the Givers charity shows South African Pierre Korkie before he was kidnapped in Yemen + +An image from a propaganda video released by al-Malahem Media on December 4, 2014 purportedly shows Nasser bin Ali Al-Ansi, of Al-Qaeda in the Arabian Peninsula, reading a message threatening to kill US hostage Luke Somers + +US President Barack Obama speaks in Washington, DC on December 3, 2014 ©Nicholas Kamm (AFP/File) + +Yemeni soldiers walks outside the Yemeni Defense Ministry in Sanaa on December 6, 2014 after American journalist Luke Somers and a South African hostage were killed during a failed rescue mission ©Mohammed Huwais (AFP) + +Sorry we are not currently accepting comments on this article.","1" +"Al-Qaeda kills hostages as US tries dramatic rescue bid","Al-Qaeda militants in Yemen killed two hostages -- an American and a South African -- during a pre-dawn gunfight as US special forces came agonisingly near to springing them free during a rescue attempt. + +American photojournalist Luke Somers and South African teacher Pierre Korkie were both shot but still alive as commandoes tried to rush them to safety, and later died of their wounds, US officials said. + +US President Barack Obama accused the jihadists of ""barbaric murder"", after authorising the operation following the release of an Al-Qaeda video in which Somers pleaded for his life. + +A grab taken from a propaganda video released by al-Malahem Media on December 4, 2014 purportedly shows US hostage Luke Somers, 33, kidnapped more than a year ago in the Yemeni capital Sanaa, saying that his life is in danger + +Vice President Joe Biden said US intelligence had worked ""relentlessly"" to free Somers and bemoaned: ""We came so close."" + +One of the hostages -- it was not clear who -- died en route to a naval ship off Yemen, the USS Makin Island, and the other on the operating table aboard the vessel, officials said. + +The US commandoes dropped by helicopter in the dead of night 10 kilometres (six miles) from where Somers and Korkie were being held in the southeastern Yemeni province of Shabwa. + +They made their way to the Al-Qaeda hideout by foot, but were discovered about 100 metres (yards) away. + +A short but intense firefight -- lasting five to 10 minutes -- erupted, a senior US defence official said. At least five militants were believed killed during the firefight, and there were no casualties among the US personnel. + +""When the element of surprise was lost, and a firefight ensued, we believe that is when (the hostages) were shot,"" the official, who was with US Defense Secretary Chuck Hagel in the Afghan capital Kabul, said. + +- 'Despicable terrorist organisation' - + +Korkie's death came just a day before the 57-year-old was to be freed after more than a year in captivity, according to the charity that had negotiated his release. + +British-born Somers, 33, had worked as a freelance photographer for the BBC and spent time at local newspapers, including the Yemen Times, before he was snatched off Sanaa's streets in September 2013. + +Al-Qaeda in the Arabian Peninsula (AQAP) had threatened in a video Thursday to execute Somers and gave Washington three days to meet unspecified demands. + +AQAP's threat followed the murder since August of five Western hostages by the Islamic State jihadist group, which controls parts of Syria and Iraq. + +The senior US defence official said there were ""good indications"" AQAP had moved the deadline up and ""were preparing to kill him... which is why we moved as fast as we could"". + +""It was either act now and take the risk, or let that deadline pass. And no one was willing to do that."" + +Obama said that since Somers was abducted, Washington had been using ""every tool at our disposal"" to try to secure his release. + +""Luke was a photojournalist who sought through his images to convey the lives of Yemenis to the outside world,"" the president added. + +""He came to Yemen in peace and was held against his will and threatened by a despicable terrorist organisation. + +""The callous disregard for Luke's life is more proof of the depths of AQAP's depravity."" + +- 'Home for Christmas' - + +In May 2013, Al-Qaeda seized Korkie and his wife Yolande, who was released in January. The couple had worked as teachers in Yemen for four years. + +The Gift of Givers charity said logistical arrangements had already been put in place to fly Korkie out of Yemen on Sunday. + +""The psychological and emotional devastation to Yolande and her family will be compounded by the knowledge that Pierre was to be released by Al-Qaeda tomorrow,"" it said on Saturday. + +""Three days ago we told her 'Pierre will be home for Christmas'. We certainly did not mean it in the manner it has unfolded."" + +Imtiaz Sooliman, head of the charity, said he had anticipated on Friday that the Americans, under family pressure after the AQAP video emerged, were going to act and that he feared Korkie would die in the operation. + +""No one can be blamed for that; it is a hostage-taking, a crisis situation and each one works for his interests,"" he said. + +A US State Department official said ""we assessed that there were two hostages at this location"", including Somers. ""We did not know who the second hostage was."" + +The United States has said American and Yemeni forces already tried unsuccessfully to rescue Somers last month. + +Yemen's defence ministry said Al-Qaeda moved hostages, including Somers, a Briton and a South African, days before. + +The Briton's whereabouts remain unknown. + +This undated picture provided on December 6, 2014 by the Gift of the Givers charity shows South African Pierre Korkie before he was kidnapped in Yemen + +An image from a propaganda video released by al-Malahem Media on December 4, 2014 purportedly shows Nasser bin Ali Al-Ansi, of Al-Qaeda in the Arabian Peninsula, reading a message threatening to kill US hostage Luke Somers + +US President Barack Obama speaks in Washington, DC on December 3, 2014 ©Nicholas Kamm (AFP/File) + +Sorry we are not currently accepting comments on this article.","1" +"Hostage 'murdered' in rescue bid","A British-born photojournalist held hostage in Yemen by al Qaida was ""murdered"" in a failed rescue attempt, the US defence secretary has confirmed. + +Chuck Hagel said Luke Somers, an American citizen, was shot by his captors during the raid on Friday night, which was the second attempt by the US to rescue him. + +Mr Somers, 33, was taken hostage in the Yemeni capital Sana'a more than a year ago by the extremist Islamic group, which last week released a video threatening to kill him if its demands were not met by the US authorities. + +Luke Somers was kidnapped over a year ago by al Qaida (AP Photo/Hani Mohammed) + +His sister Lucy said the family were informed of his death by the FBI this morning. + +Sorry we are not currently accepting comments on this article.","1" +"'Barbaric' hostage murder condemned","The US and UK have both condemned the ""barbaric"" murder of a British-born photojournalist by terrorists during a failed rescue attempt in Yemen. + +American citizen Luke Somers, 33, who was held hostage for more than a year by al Qaida, was killed last night by his captors during the second rescue attempt by the US military last night. + +US president Barack Obama said he had sanctioned the night-time operation in Yemen's southern Shabwa state because the reporter was in ""imminent danger"". + +Luke Somers was kidnapped over a year ago by al Qaida (AP Photo/Hani Mohammed) + +On Thursday, a video featuring Mr Somers, who was captured in the capital Sana'a in September last year, was released by the group al Qaida in the Arabian Peninsula (AQAP) who threatened to kill their hostage if the US authorities did not meet their demands in three days. + +In a statement, the US president said: ""The United States strongly condemns the barbaric murder of Luke Somers at the hands of al Qaida terrorists during a rescue operation conducted by US forces in Yemen in partnership with the Yemeni government. + +""On behalf of the American people, I offer my deepest condolences to Luke's family and to his loved ones."" + +Mr Obama added that information ""indicated that Luke's life was in imminent danger"". + +""Based on this assessment, and as soon as there was reliable intelligence and an operational plan, I authorised a rescue attempt."" + +Mr Somers' sister Lucy said the family were informed of his death by the FBI this morning. + +Lucy Somers told the Associated Press: ""We ask that all of Luke's family members be allowed to mourn in peace."" + +A second hostage was also killed in the mission, named by aid charity Gift of Givers as South African teacher Pierre Korkie. + +Foreign Secretary Philip Hammond said he ""salutes"" the forces involved in the mission and offered his condolences to the families of both men. + +""My deepest condolences are with the families of both hostages at this time,"" he said. + +""We utterly condemn AQAP for the brutal murder of these two men. + +""Luke had close links with the UK and his family have spoken about Luke's life and his work, and that is how he should be remembered. + +""I salute the forces involved, who showed great courage in carrying out this mission. + +""We continue to work with our international and Yemeni partners to counter the threat from al Qaida and other terrorist groups."" + +A senior Obama administration official told the Associated Press that militants tried to kill Mr Somers just before the raid, wounding him. + +US commandos then flew Mr Somers to a Navy ship in the region where he died. + +On Thursday, the Pentagon confirmed that last month the US military had sought to rescue Mr Somers, but that he had not been found. + +On the same day, AQAP issued a video on Thursday threatening to kill the hostage within three days if its demands were not met by the US authorities. + +It began with a reading in Arabic from Nasser bin Ali al Ansi, an AQAP official, before Mr Somers gave a statement in English. + +He said: ""My name is Luke Somers. I'm 33 years old. I was born in England, but I carry American citizenship and have lived in America for most of my life. + +""It's now been well over a year since I've been kidnapped in Sana'a. Basically, I'm looking for any help that can get me out of this situation. I'm certain that my life is in danger. + +""So as I sit here now, I ask if anything can be done, please let it be done. Thank you very much."" + +The three-minute video also features Mr Ansi speaking about American activity in Afghanistan, Somalia and Iraq as well as recent air strikes in Syria. + +The family of Mr Somers, who was captured in September 2013, had earlier pleaded for him to be released. + +In an online video, his sister Lucy Somers described her older brother as a romantic who ""always believes the best in people."" She added: ""Please let him live."" + +His father Michael said Mr Somers was ""a good friend of Yemen and the Yemeni people"". + +The SITE Intelligence Group, which monitors Jihadist groups, reported that Yemeni jihadists said on Twitter that they had ""anticipated"" the attack. + +It follows similar videos by another extremist militant group, Islamic State (IS), which has already killed two British hostages and three American hostages in videos released on social media. + +IS has posted a series of videos online showing the separate murders of US journalists James Foley and Steven Sotloff, US aid worker Peter Kassig and two British aid workers, David Haines and Alan Henning. + +Footage claiming to show Mr Henning's murder appeared on the internet just days after the UK joined US-led air strikes against the terrorists in Iraq. + +Sorry we are not currently accepting comments on this article.","1" +"U.S., South African hostages in Yemen killed in rescue attempt","By Mohammed Ghobari and Mohammed Mukhashaf + +SANAA/ADEN, Dec 6 (Reuters) - A U.S. journalist and a South African teacher held by al Qaeda militants in Yemen were killed alongside 10 of their captors during a rescue attempt by U.S. and Yemeni forces in a remote desert village, officials said on Saturday. + +U.S. Secretary of State John Kerry and a Yemeni intelligence official said Luke Somers, 33, and Pierre Korkie were shot by their kidnappers shortly after the dawn raid began in the arid Wadi Abadan district of Shabwa, a province in southern Yemen long seen as one of al Qaeda's most formidable strongholds. + +Kerry said the attempted rescue, the second attempt to free Somers in 10 days, had only been approved because of information that the American's life was in imminent danger. + +However, the Gift of the Givers relief group, who were trying to secure Korkie's release, said it had negotiated for the South African teacher to be freed and had expected that to happen on Sunday and for him to be returned to his family. + +Al Qaeda in the Arabian Peninsula (AQAP) is seen by Washington as one of the movement's most dangerous branches. The United States has worked with the Yemeni government and via drone strikes to attack its leadership in southern and eastern parts of Yemen. + +""The callous disregard for Luke's life is more proof of the depths of AQAP's depravity, and further reason why the world must never cease in seeking to defeat their evil ideology,"" U.S. President Barack Obama said in a statement. + +He said he had authorised the attempted rescue and said the United States would ""spare no effort to use all of its military, intelligence and diplomatic capabilities to bring Americans home safely, wherever they are located"". + +Somers was moved from the scene of the rescue attempt but died later from his wounds, a senior official in the Yemeni president's office said. + +Gift of the Givers said in a statement on its website: ""We received with sadness the news that Pierre was killed in an attempt by American Special Forces, in the early hours of this morning, to free hostages in Yemen."" + +It added: ""The psychological and emotional devastation to (Korkie's wife) Yolande and her family will be compounded by the knowledge that Pierre was to be released by al Qaeda tomorrow ... Three days ago we told her 'Pierre will be home for Christmas'."" + +A South African government spokesman declined to comment. + +There was no new information about three other hostages, a Briton, a Turk and a Yemeni, who had previously been held alongside Somers and Korkie, a Yemeni security official told Reuters. + +Lucy Somers, the photojournalist's sister, told the Associated Press that she and her father learned of her brother's death from FBI agents at 0500 GMT (12 a.m. EST) Saturday. + +""We ask that all of Luke's family members be allowed to mourn in peace,"" she said from London. + +IMMEDIATE DANGER + +Kerry and U.S. Secretary of Defense Chuck Hagel both said the decision to mount the raid was based on fears that AQAP planned to kill Somers. + +""Earlier this week, AQAP released a video announcing that Luke would be murdered within 72 hours. Along with other information, there was a compelling indication that Luke's life was in immediate danger,"" Kerry said. + +Hagel, in Kabul, said: ""There were compelling reasons to believe Mr Somers' life was in immediate danger."" He said Somers and another hostage, who he did not name, had been killed by al Qaeda militants. + +U.S. officials on Thursday said American forces had already attempted to rescue Somers, without giving details. Yemeni officials had previously disclosed the release of six Yemenis, a Saudi and an Ethiopian hostage in a raid on Nov. 25. + +The operation involved an air strike followed by a raid by U.S. and Yemeni forces, a local security official said. It took place in Dafaar village in Shabwa Province and targeted an al Qaeda group headed by Mubarak al-Harad. + +""It's a very small village with only 20-40 houses. There were very quick clashes with the gunmen and then it was all finished,"" a tribal source from the area told Reuters. + +A senior Yemeni intelligence official said: ""When the forces entered the place where the hostages were being held, they called on the kidnappers to give themselves up because they were surrounded on all sides. + +""But the kidnappers immediately killed two hostages, which prompted the forces to open fire on the kidnappers. They tried to give first aid to the hostages but they had lost their lives."" + +AQAP on Thursday released a video showing a man it said was Somers saying: ""I'm looking for any help that can get me out of this situation. I'm certain that my life is in danger"". Reuters was not able to independently verify the authenticity of that video, which was reported on by SITE Monitoring. (Additional reporting by Peter Salisbury in Sanaa, Yara Bayoumy in Manama, Phil Stewart in Kabul; Stella Mapenzauswa in Johannesburg; Writing by Angus McDowall; Editing by Janet Lawrence) + +Sorry we are not currently accepting comments on this article.","1" +"U.S., South African hostages killed in rescue attempt in Yemen","By Mohammed Ghobari and Mohammed Mukhashaf + +SANAA/ADEN, Dec 6 (Reuters) - A U.S. journalist and a South African teacher held by al Qaeda militants in Yemen were killed along with some of their captors during a night rescue attempt by U.S. and Yemeni forces in a remote desert village, officials said on Saturday. + +U.S. Secretary of State John Kerry and a Yemeni intelligence official said Luke Somers, 33, and South African Pierre Korkie were shot by their kidnappers shortly after the raid began in the arid Wadi Abadan district of Shabwa, a province in southern Yemen long seen as one of al Qaeda's most formidable strongholds. + +Kerry said the operation, the second attempt to free Somers in 10 days, had only been approved because of information that the American's life was in imminent danger. + +However, the Gift of the Givers relief group, which was trying to secure Korkie's release, said it had negotiated for the teacher to be freed and had expected that to happen on Sunday and for him to be returned to his family. + +Al Qaeda in the Arabian Peninsula (AQAP) is seen by Washington as one of the movement's most dangerous branches. The United States has worked with the Yemeni government and via drone strikes to attack its leadership in southern and eastern parts of Yemen. + +""The callous disregard for Luke's life is more proof of the depths of AQAP's depravity, and further reason why the world must never cease in seeking to defeat their evil ideology,"" President Barack Obama said in a statement. + +He said he had authorised the attempted rescue and said the United States would ""spare no effort to use all of its military, intelligence and diplomatic capabilities to bring Americans home safely, wherever they are located"". + +Somers was moved from the scene of the rescue attempt but died later from his wounds, a senior official in the Yemeni president's office said. + +Gift of the Givers said on its website: ""We received with sadness the news that Pierre was killed in an attempt by American Special Forces, in the early hours of this morning, to free hostages in Yemen."" + +It added: ""The psychological and emotional devastation to (Korkie's wife) Yolande and her family will be compounded by the knowledge that Pierre was to be released by al Qaeda tomorrow ... Three days ago we told her 'Pierre will be home for Christmas'."" + +A South African government spokesman declined to comment. + +There was no new information about three other hostages, a Briton, a Turk and a Yemeni, who had previously been held alongside Somers and Korkie, a Yemeni security official told Reuters. + +Lucy Somers, the photojournalist's sister, told the Associated Press that she and her father learned of her brother's death from FBI agents at 0500 GMT (12 a.m. EST) Saturday. + +""We ask that all of Luke's family members be allowed to mourn in peace,"" she said from London. + +IMMEDIATE DANGER + +Kerry said the decision to mount the raid was based on fears that AQAP planned to kill Somers. + +""Earlier this week, AQAP released a video announcing that Luke would be murdered within 72 hours. Along with other information, there was a compelling indication that Luke's life was in immediate danger,"" Kerry said. + +U.S. officials on Thursday said American forces had already attempted to rescue Somers, without giving details. Yemeni officials had previously disclosed the release of six Yemenis, a Saudi and an Ethiopian hostage in a raid on Nov. 25. + +There were contradictory accounts of how Saturday's raid unfolded and how many of the kidnappers were killed. A Yemeni official said on Saturday morning that 10 al Qaeda suspects had died in the raid. + +A U.S. official, speaking to Reuters on condition of anonymity, said American special forces had conducted the operation alone at 1 a.m. in Yemen, but that the kidnappers had been alerted to their approach shortly before they arrived. + +The official said the kidnappers then ""executed"" the hostages, who each sustained multiple gunshot wounds. One died during the flight out and another aboard a U.S. ship. + +At no point was there an exchange of fire in the part of the compound where the hostages were being held, the source said, and at no point did U.S. forces shoot into that part of the building. + +A senior U.S. official said Yemen's President Abd Rabbu Mansour Hadi had given his support for the operation. + +Although the United States knew there were two hostages at the location, and that one of them was Somers, it did not know that the other was Korkie, the senior Washington official said. + +The rescue team was made up of about 40 members of Special Operations forces, and the raid lasted about 30 minutes from start to finish, said the U.S. officials. + +Yemen's government said in a statement carried on state media that its security forces had led the raid. It said the security forces had surrounded the house and called on the kidnappers to surrender, but they instead shot the hostages. + +That led to an assault on the building in which four Yemeni security officers were also wounded, it said. The statement said the house belonged to suspected militant Saeed al-Daghaari, which another Yemeni security source told Reuters it was in the village of Dafaar in the Wadi Abadan district of Shabwa. + +""It's a very small village with only 20-40 houses. There were very quick clashes with the gunmen and then it was all finished,"" a tribal source from the area said. + +AQAP on Thursday released a video showing a man it said was Somers saying: ""I'm looking for any help that can get me out of this situation. I'm certain that my life is in danger"". Reuters was not able to independently verify the authenticity of that video, which was reported on by SITE Monitoring. (Additional reporting by Jeff Mason in Washington, Peter Salisbury in Sanaa, Yara Bayoumy in Manama, Phil Stewart in Kabul; Stella Mapenzauswa in Johannesburg; Writing by Angus McDowall; Editing by Janet Lawrence and Mark Trevelyan) + +Sorry we are not currently accepting comments on this article.","1" +"American, South African hostages die in rescue attempt in Yemen","By Mohammed Ghobari and Mohammed Mukhashaf + +SANAA/ADEN, Dec 6 (Reuters) - U.S. special forces stormed a walled compound in a remote Yemeni village early on Saturday in an attempt to free western hostages held by an al Qaeda unit, but an American journalist and a South African teacher were killed by their captors, officials said. + +U.S. Secretary of State John Kerry and a Yemeni intelligence official said Luke Somers, 33, and South African Pierre Korkie, 56, were shot by their kidnappers shortly after the raid began in the arid Wadi Abadan district of Shabwa, a province long seen as one of al Qaeda's most formidable strongholds. + +It was the second U.S. attempt to free Somers in 10 days and Kerry said it had been approved because of information that Somers' life was in imminent danger. ""It was our assessment that that clock would run out on Saturday,"" one U.S. official said. + +However, the Gift of the Givers relief group, which was trying to secure Korkie's release, said it had negotiated for the teacher to be freed and had expected that to happen on Sunday and for him to be returned to his family. + +Al Qaeda in the Arabian Peninsula (AQAP) is seen by Washington as one of al Qaeda's most dangerous branches. The United States has worked with Yemen's government and via drone strikes to attack its leaders in southern and eastern Yemen. + +""The callous disregard for Luke's life is more proof of the depths of AQAP's depravity, and further reason why the world must never cease in seeking to defeat their evil ideology,"" President Barack Obama said in a statement. + +Obama said he had authorised the operation and said the United States would ""spare no effort to use all of its military, intelligence and diplomatic capabilities to bring Americans home safely, wherever they are located."" + +SHOOT-OUT + +A U.S. defense official said about 40 U.S. Special Forces troops, flown in by tilt-rotor CV-22 Osprey aircraft, had advanced to within 100 meters (yards) of the walled compound where the hostages were held before the defenders were alerted and a firefight started. + +U.S. officials said they knew Somers was at the location, partly because of information they gleaned during the earlier rescue attempt, and they were aware that a second hostage was there but did not know in advance who it was. + +The men were each shot several times by at least one of their retreating guards, and not in crossfire, said the officials, who declined to be identified. The men were treated by medics but one died during the flight out and another aboard a U.S. ship. More than five militants were killed and no U.S. troops were hurt, they said. + +The raid lasted about 30 minutes. + +Gift of the Givers said on its website: ""We received with sadness the news that Pierre was killed in an attempt by American Special Forces, in the early hours of this morning, to free hostages in Yemen."" + +It added: ""The psychological and emotional devastation to (Korkie's wife) Yolande and her family will be compounded by the knowledge that Pierre was to be released by al Qaeda tomorrow ... Three days ago we told her 'Pierre will be home for Christmas'."" + +Yolande, who was kidnapped with her husband in mid-2013, was released in January after intervention by Gift of the Givers. + +A South African government spokesman declined to comment. + +There was no new information about three other hostages, a Briton, a Turk and a Yemeni, who had previously been held alongside Somers and Korkie, a Yemeni security official said. + +Lucy Somers, the photojournalist's sister, told the Associated Press that she and her father learned of her brother's death from FBI agents at 0500 GMT (12 a.m. EST) Saturday. ""We ask that all of Luke's family members be allowed to mourn in peace,"" she said from London. + +IMMEDIATE DANGER + +Kerry said the decision to mount the raid was based on fears that AQAP planned to kill Somers. + +""Earlier this week, AQAP released a video announcing that Luke would be murdered within 72 hours. Along with other information, there was a compelling indication that Luke's life was in immediate danger,"" Kerry said. + +U.S. officials on Thursday said American forces had already attempted to rescue Somers, without giving details. Yemeni officials had previously disclosed the release of six Yemenis, a Saudi and an Ethiopian hostage in a raid on Nov. 25. + +A senior U.S. official said Yemen's President Abd Rabbu Mansour Hadi had given his support for Saturday's operation, which a U.S. official said took place at 1 a.m. local time. + +Yemen's government issued a different account of the incident. It said in a statement carried on state media that its security forces had led the raid. It said the security forces had surrounded the house and called on the kidnappers to surrender, but they instead shot the hostages. + +That led to an assault on the building in which four Yemeni security officers were also wounded, it said. The statement said the house belonged to suspected militant Saeed al-Daghaari, which another Yemeni security source told Reuters it was in the village of Dafaar in the Wadi Abadan district of Shabwa. + +""It's a very small village with only 20-40 houses. There were very quick clashes with the gunmen and then it was all finished,"" a tribal source from the area said. + +AQAP on Thursday released a video showing a man it said was Somers saying: ""I'm looking for any help that can get me out of this situation. I'm certain that my life is in danger."" + +Reuters was not able to independently verify the authenticity of that video, which was reported by SITE Monitoring. (Additional reporting by Jeff Mason in Washington, Peter Salisbury in Sanaa, Yara Bayoumy in Manama, Phil Stewart in Kabul; Stella Mapenzauswa in Johannesburg; Writing by Angus McDowall and David Storey; Editing by Janet Lawrence, Mark Trevelyan and Grant McCool) + +Sorry we are not currently accepting comments on this article.","1" +"American hostage killed in rescue attempt in Yemen - senior official","SANAA, Dec 6 (Reuters) - U.S. journalist Luke Somers was killed during a rescue operation in Shabwa in southern Yemen on Saturday, a senior official in the president's office told Reuters. + +He said the government initially believed Somers had been freed but later learnt he had died. Yemen's Defence Ministry said earlier on Saturday that an American hostage had been freed in an operation that killed 10 Islamist militants. + +(Reporting By Peter Salisbury in Sanaa; Writing by Angus McDowall in Riyadh; Editing by Janet Lawrence) + +Sorry we are not currently accepting comments on this article.","1" +"BREAKING: British-born hostage 'KILLED in failed rescue attempt'","The sister of the British-born American photojournalist, Luke Somers, held captive by al-Qaeda's Yemen affiliate, claims he was killed in a failed rescue attempt. + +Lucy Somers told the Associated Press that FBI agents had informed her of the 33-year-old's death. She went on to say: ""We ask that all of Luke's family members be allowed to mourn in peace."" + +There has been no comment by US officials. The news comes after the Yemeni Defence Ministry had stated a joint US-Yemeni armed forces operation had freed ""an American hostage"" in a mission that killed 10 al-Qaeda members, Reuters reported. Luke Somers was kidnapped by militants last September while working for the Yemen Times. On Thursday, the extremist group posted a video threatening to kill Somers in three days if the US did not meet their unspecified demands. Following this, the Pentagon confirmed it had previously launched a failed attempt to rescue Mr. Somers.","1" +"VIDEO: Heartbreaking plea from sister as Brit hostage KILLED in failed rescue attempt","BRITISH-BORN American photojournalist, Luke Somers, held captive by al-Qaeda's Yemen affiliate, has been killed in a failed rescue attempt. + +FBI agents informed his sister Lucy Somers of the 33-year-old's death. She went on to say: ""We ask that all of Luke's family members be allowed to mourn in peace."" + +Meanwhile a senior al-Qaeda operative wanted by the United States for plotting to bomb New York subway has been killed. + +A senior official at the Barack Obama’s office has now confirmed Mr Somers’ death. + +The Yemeni Defence Ministry and US Government first thought Mr Somers had been freed, but later learnt he had died. His death came during a mission that killed 10 al-Qaeda members. + +Luke Somers was kidnapped by militants last September as he left a supermarket in the Yemeni capital Sanaa, where he worked as a copy editor and freelance photographer during the 2011 uprising in Yemen. + +On Thursday, the extremist group posted a video threatening to kill Somers in three days if the US did not meet their unspecified demands. Following this, the Pentagon confirmed it had previously launched a failed attempt to rescue Mr. Somers. + +Before her brother's death, Lucy Somers released an online video describing him as a romantic who ""always believes the best in people."" She ended with the plea: ""Please let him live."" + +In a statement, Somers' father, Michael, also called his son ""a good friend of Yemen and the Yemeni people"" and asked for his safe release. + +Somers, who was born in Britain, earned a bachelor's degree in creative writing while attending Beloit College in Wisconsin from 2004 through 2007. + +English professor Shawn Gillen who taught Mr Somers said: ""He really wanted to understand the world."" + +brightcove.createExperiences(); + +The news comes as top al-Qaeda leader Adnan el Shukrijuma was killed in Pakistan by the country’s army, a statement from its military has confirmed. + +Shukrijumah is wanted in the United States for conspiracy to use weapons of mass destruction and to commit murder in a foreign country. + +He was killed in the remote Shinwarsak, South Waziristan, which borders Afghanistan, today.","1" +"British-born journalist and South African aid worker KILLED in hostage rescue attempt","BRITISH-BORN American photojournalist, Luke Somers, and a South African teacher held captive by al-Qaeda's Yemen affiliate, have been killed in a failed rescue attempt. + +FBI agents informed his sister Lucy Somers of the 33-year-old's death. She went on to say: ""We ask that all of Luke's family members be allowed to mourn in peace."" + +South African teacher Pierre Korkie was due to be released on Sunday, but US President Barack Obama ordered the raid after a video was posted threatening to kill Somers. + +Information ""indicated that Luke's life was in imminent danger,"" Obama said. ""Based on this assessment, and as soon as there was reliable intelligence and an operational plan, I authorized a rescue attempt. ... I also authorised the rescue of any other hostages held in the same location as Luke."" + +The Yemeni Defence Ministry and US Government first thought Mr Somers had been freed, but later learnt he had died. His death came during a mission that killed 10 al-Qaeda members. + +Luke Somers was kidnapped by militants last September as he left a supermarket in the Yemeni capital Sanaa, where he worked as a copy editor and freelance photographer during the 2011 uprising in Yemen. + +brightcove.createExperiences(); + +On Thursday, the extremist group posted a video threatening to kill Somers in three days if the US did not meet their unspecified demands. Following this, the Pentagon confirmed it had previously launched a failed attempt to rescue Mr. Somers. + +Before her brother's death, Lucy Somers released an online video describing him as a romantic who ""always believes the best in people."" She ended with the plea: ""Please let him live."" + +In a statement, Somers' father, Michael, also called his son ""a good friend of Yemen and the Yemeni people"" and asked for his safe release. + +Somers, who was born in Britain, earned a bachelor's degree in creative writing while attending Beloit College in Wisconsin from 2004 through 2007. + +English professor Shawn Gillen who taught Mr Somers said: ""He really wanted to understand the world."" + +Meanwhile a senior al-Qaeda operative wanted by the United States for plotting to bomb New York subway has been killed. + +Adnan el Shukrijuma was killed in Pakistan by the country’s army, a statement from its military has confirmed. + +Shukrijumah is wanted in the United States for conspiracy to use weapons of mass destruction and to commit murder in a foreign country. + +He was killed in the remote Shinwarsak, South Waziristan, which borders Afghanistan, today.","1" +"Luke Somers Dies In Rescue Attempt, Sister Says; Yemeni Defense Ministry Says Unnamed US Hostage Freed","Update as of 04:16 a.m. EST: A senior U.S. official has told the New York Times that Luke Somers was killed in rescue attempt launched late Friday. + +The official was quoted as saying that Somers was shot by his captors, and was gravely wounded by the time U.S. commandos reached him. Despite being transferred to a U.S. naval ship in the region, the offical said Somers died from his injuries. + +The U.S. State Department is expected to issue more details about the raid in the coming hours, according to Al Jazeera. + +Original story below + +The sister of Luke Somers, the American photojournalist held captive by al-Qaeda militants in Yemen, says that he was killed in a failed rescue attempt, Saturday, according to the Associated Press. + +There are conflicting reports however, with the Reuters news agency reporting that Yemen's Defense Ministry said a raid by its forces Saturday freed a U.S. hostage, who was not named. + +Lucy Somers, who said that she had heard the news from FBI agents, said: ""We ask that all of Luke's family members be allowed to mourn in peace,"" according to a report from Sky News. + +A joint military operation to free Somers, conducted by U.S. and Yemeni forces, was launched Saturday, according to a report from NBC News. The network added that Somers' status was unclear. + +The reports come just hours after the Associated Press reported that 9 suspected al-Qaeda fighters were killed in a drone strike in Yemen. + +Somers' mother and brother appeared in an video earlier this week, in which they called on his captors to “show mercy,” to him. + +A video released earlier this week by Somers' captors, al-Qaeda in the Arab Peninsula, showed a militant threatening to kill Somers unless unspecified demands were met. + +There has been no official comment or confirmation of Somers' status. + +This is a breaking story, check back for more updates.","1" +"Luke Somers: British-born photojournalist 'killed by al-Qaeda after failed rescue attempt in Yemen'","There were conflicting reports about the outcome of the operation + +A British-born photojournalist has reportedly been killed by al-Qaeda militants in Yemen during a failed rescue attempt by US special forces. + +Luke Somers, 33, had been held hostage since being kidnapped in the capital, Sana’a, in September 2013 as he left a supermarket. + +There were conflicting reports on Saturday morning about the outcome of a joint US-Yemeni operation to free him. Some said an unnamed American hostage had been rescued while others said Mr Somers was dead. + +His captors had taunted his family after a previous attempt by American and Yemeni forces to free him, saying on Thursday they would execute him within three days if the US did not meet their demands. + +Al-Qaeda released a video statement from Mr Somers, where he said: “I’m looking for any help that can get me out of this situation. I’m certain that my life is in danger."" + +Lucy Somers, his sister, told the Associated Press today that FBI agents informed her he was killed in another failed rescue mission but Washington has not confirmed the claim. + +""We ask that all of Luke's family members be allowed to mourn in peace,"" she said. + +She had released a video pleading with al-Qaeda in the Arabian Peninsula (AQAP) to let him live, describing her older brother as a romantic who ""always believes the best in people"". + +Mr Somers’ father, Michael, called his son ""a good friend of Yemen and the Yemeni people"" and asked for his safe release and his mother and brother appealed to his captors to spare him, saying he ""was only trying to do good"". + +According to a statement on the website of Yemen's defence ministry, a hostage rescue attempt on Saturday morning was successful. + +A drone struck a suspected AQAP hideout at dawn in Yemen's southern Shabwa province, it said, and a subsequent raid freed an unnamed US hostage and killed 10 extremists. It was unclear whether the hostage described was Mr Somers. + +No further details have emerged of Saturday's operation but the Pentagon admitted on Thursday that a secret raid last month had got the wrong location. + +Special forces arrived at the target location, in a remote al-Qaeda safe haven in the desert near Yemen’s border with Saudi Arabia, to find Mr Somers was not there. + +The American government considers AQAP to be the world's most dangerous arm of the international terrorist organisation after linking it to several failed attacks on US soil. + +Mr Somers was born in Britain and holds dual US-UK citizenship. Having spent most of his life in the United States, he worked for two years in Yemen as a freelance photojournalist, sub-editor and interpreter for English language newspapers. + +American authorities rarely discuss their controversial drone strike campaign in Yemen, which are known to cause civilian casualties, legitimising violent resistance against US intervention in the country. + +Al-Qaeda and Islamist militants have gained a foothold in large parts of southern and eastern Yemen, where the government is struggling to exert control outside main cities. + +The Pentagon has not replied to The Independent's request for confirmation. + +Additional reporting by agencies","1" +"Luke Somers: British-born photojournalist killed by al-Qaeda during Yemen rescue attempt","There were conflicting reports about the outcome of the operation + +A British-born photojournalist has been killed by al-Qaeda militants in Yemen during a failed rescue attempt by US special forces. + +Luke Somers, 33, had been held hostage since being kidnapped in the capital, Sana’a, in September 2013 as he left a supermarket. + +There were initially conflicting reports on Saturday morning about the outcome of a joint US-Yemeni operation to free him. Some said an unnamed American hostage had been rescued while others said Mr Somers was dead. + +The White House later confirmed that the photographer had died, despite being taken out of the al-Qaeda base. + +An official told the New York Times that Mr Somers was shot by his captors as the overnight raid unfolded and was badly wounded when the commandos reached him. + +By the time Mr Somers was flown to a United States naval ship in the region, he had died from his injuries, the source said. + +His captors had taunted his family after a previous attempt by American and Yemeni forces to free him, saying on Thursday they would execute him within three days if the US did not meet their demands. + +Al-Qaeda released a video statement from Mr Somers, where he said: “I’m looking for any help that can get me out of this situation. I’m certain that my life is in danger."" + +Lucy Somers, his sister, told the Associated Press that FBI agents informed her he was killed on Saturday. + +""We ask that all of Luke's family members be allowed to mourn in peace,"" she said. + +She had released a video pleading with al-Qaeda in the Arabian Peninsula (AQAP) to let him live, describing her older brother as a romantic who ""always believes the best in people"". + +Mr Somers’ father, Michael, called his son ""a good friend of Yemen and the Yemeni people"" and asked for his safe release and his mother and brother appealed to his captors to spare him, saying he ""was only trying to do good"". + +According to a statement on the website of Yemen's defence ministry, a hostage rescue attempt on Saturday morning was successful. + +A drone struck a suspected AQAP hideout at dawn in Yemen's southern Shabwa province, it said, and a subsequent raid freed an unnamed US hostage and killed 10 extremists. + +It is believed the inconsistency arose because Mr Somers did not die until after he was pulled out and taken into the care of American forces. + +No further details have emerged of Saturday's operation but the Pentagon admitted on Thursday that a secret raid last month had got the wrong location. + +Special forces arrived at the target, in a remote al-Qaeda safe haven in the desert near Yemen’s border with Saudi Arabia, to find Mr Somers was not there. + +The American government considers AQAP to be the world's most dangerous arm of the international terrorist organisation after linking it to several failed attacks on US soil. + +Mr Somers was born in Britain and holds dual US-UK citizenship. Having spent most of his life in the United States, he worked for two years in Yemen as a freelance photojournalist, sub-editor and interpreter for English language newspapers. + +American authorities rarely discuss their controversial drone strike campaign in Yemen, which are known to cause civilian casualties, legitimising violent resistance against US intervention in the country. + +Al-Qaeda and Islamist militants have gained a foothold in large parts of southern and eastern Yemen, where the government is struggling to exert control outside main cities. + +Additional reporting by agencies","1" +"Luke Somers: Al-Qaeda kill British-born photojournalist during Yemen rescue attempt","A second hostage, Pierre Korkie from South Africa, also died during the raid + +A British-born photojournalist has been killed by al-Qaeda militants in Yemen during a failed rescue attempt by US special forces. + +Luke Somers, 33, had been held hostage since being kidnapped in the capital, Sana’a, in September 2013 as he left a supermarket. + +An official told the New York Times that Mr Somers was shot by his captors as the overnight raid unfolded and was badly wounded when the commandos reached him. + +By the time Mr Somers was flown to a United States naval ship in the region, he had died from his injuries, the source said. + +The outgoing US Defence Secretary, Chuck Hagel, said Mr Somers and ""a second non-US citizen hostage were murdered” by al-Qaeda militants. + +Pierre Korkie, a South African teacher, was named as the second captive by disaster relief group Gift of the Givers. He was kidnapped alongside his wife, who was released in January, by militants in Taiz in May last year and was reportedly due to be released on Sunday. + +“Yesterday by the order of the president of the United States, US special operations forces conducted a mission in Yemen to rescue a US citizen Luke Somers and any other foreign nationals held hostage with him,” Mr Hagel said during a visit to Afghanistan. “There were compelling reasons to believe Somers' life was in imminent danger.” + +President Barack Obama described Mr Somers' murder as ""barbaric"" in a statement reported by NBC News. + +""The United States strongly condemns the barbaric murder of Luke Somers at the hands of al-Qaeda terrorists during a rescue operation conducted by US forces in Yemen in partnership with the Yemeni government. + +""On behalf of the American people, I offer my deepest condolences to Luke's family and to his loved ones."" + +His captors had taunted his family after a previous attempt by American and Yemeni forces to free him, saying on Thursday they would execute him within three days if the US did not meet their demands. + +Al-Qaeda released a video statement from Mr Somers, where he said: “I’m looking for any help that can get me out of this situation. I’m certain that my life is in danger."" + +Lucy Somers, his sister, told the Associated Press that FBI agents informed her he was killed on Saturday. + +""We ask that all of Luke's family members be allowed to mourn in peace,"" she said. + +She had released a video pleading with al-Qaeda in the Arabian Peninsula (AQAP) to let him live, describing her older brother as a romantic who ""always believes the best in people"". + +Mr Somers’ father, Michael, called his son ""a good friend of Yemen and the Yemeni people"" and asked for his safe release and his mother and brother appealed to his captors to spare him, saying he ""was only trying to do good"". + +Fuad Al Kadas, who said the journalist was one of his best friends, said he spent time in Egypt before finding work in Yemen first as an English teacher and then as one of the few foreign photographers in the country. + +“He is a great man with a kind heart who really loves the Yemeni people and the country,” Mr Al Kadas said. “He was so dedicated in trying to help change Yemen's future, to do good things for the people that he didn't leave the country his entire time here."" + +According to a statement initially released on the website of Yemen's defence ministry, a hostage rescue attempt on Saturday morning was successful. + +A drone struck a suspected AQAP hideout at dawn in Yemen's southern Shabwa province, it said, and a subsequent raid freed an unnamed US hostage and killed 10 extremists. + +It is believed the inconsistency arose because Mr Somers did not die until after he was pulled out and taken into the care of American forces. + +No further details have emerged of Saturday's operation but the Pentagon admitted on Thursday that a secret raid last month had got the wrong location. + +Special forces arrived at the target, in a remote al-Qaeda safe haven in the desert near Yemen’s border with Saudi Arabia, to find Mr Somers was not there. + +The American government considers AQAP to be the world's most dangerous arm of the international terrorist organisation after linking it to several failed attacks on US soil. + +Mr Somers was born in Britain and holds dual US-UK citizenship. Having spent most of his life in the United States, he worked for two years in Yemen as a freelance photojournalist, sub-editor and interpreter for English language newspapers. + +American authorities rarely discuss their controversial drone strike campaign in Yemen, which are known to cause civilian casualties, legitimising violent resistance against US intervention in the country. + +Al-Qaeda and Islamist militants have gained a foothold in large parts of southern and eastern Yemen, where the government is struggling to exert control outside main cities. + +Additional reporting by agencies","1" +"Luke Somers killed: Barack Obama condemns 'barbaric murder' of British-born photojournalist by al-Qaeda captors","A second hostage, Pierre Korkie from South Africa, also died during the raid + +A British-born photojournalist has been killed by al-Qaeda militants in Yemen during a failed rescue attempt by US special forces. + +Luke Somers, 33, had been held hostage since being kidnapped in the capital, Sana’a, in September 2013 as he left a supermarket. + +An official told the New York Times that Mr Somers was shot by his captors as the overnight raid unfolded and was badly wounded when the commandos reached him. + +By the time Mr Somers was flown to a United States naval ship in the region, he had died from his injuries, the source said. + +The outgoing US Defence Secretary, Chuck Hagel, said Mr Somers and ""a second non-US citizen hostage were murdered” by al-Qaeda militants. + +Pierre Korkie, a South African teacher, was named as the second captive by disaster relief group Gift of the Givers. He was kidnapped alongside his wife, who was released in January, by militants in Taiz in May last year and was reportedly due to be released on Sunday. + +“Yesterday by the order of the president of the United States, US special operations forces conducted a mission in Yemen to rescue a US citizen Luke Somers and any other foreign nationals held hostage with him,” Mr Hagel said during a visit to Afghanistan. “There were compelling reasons to believe Somers' life was in imminent danger.” + +President Barack Obama described Mr Somers' murder as ""barbaric"" in a statement reported by NBC News. + +""The United States strongly condemns the barbaric murder of Luke Somers at the hands of al-Qaeda terrorists during a rescue operation conducted by US forces in Yemen in partnership with the Yemeni government. + +""On behalf of the American people, I offer my deepest condolences to Luke's family and to his loved ones."" + +His captors had taunted his family after a previous attempt by American and Yemeni forces to free him, saying on Thursday they would execute him within three days if the US did not meet their demands. + +Al-Qaeda released a video statement from Mr Somers, where he said: “I’m looking for any help that can get me out of this situation. I’m certain that my life is in danger."" + +Lucy Somers, his sister, told the Associated Press that FBI agents informed her he was killed on Saturday. + +""We ask that all of Luke's family members be allowed to mourn in peace,"" she said. + +She had released a video pleading with al-Qaeda in the Arabian Peninsula (AQAP) to let him live, describing her older brother as a romantic who ""always believes the best in people"". + +Mr Somers’ father, Michael, called his son ""a good friend of Yemen and the Yemeni people"" and asked for his safe release and his mother and brother appealed to his captors to spare him, saying he ""was only trying to do good"". + +Fuad Al Kadas, who said the journalist was one of his best friends, said he spent time in Egypt before finding work in Yemen first as an English teacher and then as one of the few foreign photographers in the country. + +“He is a great man with a kind heart who really loves the Yemeni people and the country,” Mr Al Kadas said. “He was so dedicated in trying to help change Yemen's future, to do good things for the people that he didn't leave the country his entire time here."" + +According to a statement initially released on the website of Yemen's defence ministry, a hostage rescue attempt on Saturday morning was successful. + +A drone struck a suspected AQAP hideout at dawn in Yemen's southern Shabwa province, it said, and a subsequent raid freed an unnamed US hostage and killed 10 extremists. + +It is believed the inconsistency arose because Mr Somers did not die until after he was pulled out and taken into the care of American forces. + +No further details have emerged of Saturday's operation but the Pentagon admitted on Thursday that a secret raid last month had got the wrong location. + +Special forces arrived at the target, in a remote al-Qaeda safe haven in the desert near Yemen’s border with Saudi Arabia, to find Mr Somers was not there. + +The American government considers AQAP to be the world's most dangerous arm of the international terrorist organisation after linking it to several failed attacks on US soil. + +Mr Somers was born in Britain and holds dual US-UK citizenship. Having spent most of his life in the United States, he worked for two years in Yemen as a freelance photojournalist, sub-editor and interpreter for English language newspapers. + +American authorities rarely discuss their controversial drone strike campaign in Yemen, which are known to cause civilian casualties, legitimising violent resistance against US intervention in the country. + +Al-Qaeda and Islamist militants have gained a foothold in large parts of southern and eastern Yemen, where the government is struggling to exert control outside main cities. + +Additional reporting by agencies","1" +"Luke Somers killed: Barack Obama condemns the 'barbaric murder' of British-born photojournalist by al-Qaeda","A second hostage, Pierre Korkie from South Africa, also died during the raid + +A British-born photojournalist has been killed by al-Qaeda militants in Yemen during a failed rescue attempt by US special forces. + +Luke Somers, 33, had been held hostage since being kidnapped in the capital, Sana’a, in September 2013 as he left a supermarket. + +An official told the New York Times that Mr Somers was shot by his captors as the overnight raid unfolded and was badly wounded when the commandos reached him. + +By the time Mr Somers was flown to a United States naval ship in the region, he had died from his injuries, the source said. + +The outgoing US Defence Secretary, Chuck Hagel, said Mr Somers and ""a second non-US citizen hostage were murdered” by al-Qaeda militants. + +Pierre Korkie, a South African teacher, was named as the second captive by disaster relief group Gift of the Givers. He was kidnapped alongside his wife, who was released in January, by militants in Taiz in May last year and was reportedly due to be released on Sunday. + +“Yesterday by the order of the president of the United States, US special operations forces conducted a mission in Yemen to rescue a US citizen Luke Somers and any other foreign nationals held hostage with him,” Mr Hagel said during a visit to Afghanistan. “There were compelling reasons to believe Somers' life was in imminent danger.” + +President Barack Obama described Mr Somers' murder as ""barbaric"" in a statement reported by NBC News. + +""The United States strongly condemns the barbaric murder of Luke Somers at the hands of al-Qaeda terrorists during a rescue operation conducted by US forces in Yemen in partnership with the Yemeni government. + +""On behalf of the American people, I offer my deepest condolences to Luke's family and to his loved ones."" + +His captors had taunted his family after a previous attempt by American and Yemeni forces to free him, saying on Thursday they would execute him within three days if the US did not meet their demands. + +Al-Qaeda released a video statement from Mr Somers, where he said: “I’m looking for any help that can get me out of this situation. I’m certain that my life is in danger."" + +Lucy Somers, his sister, told the Associated Press that FBI agents informed her he was killed on Saturday. + +""We ask that all of Luke's family members be allowed to mourn in peace,"" she said. + +She had released a video pleading with al-Qaeda in the Arabian Peninsula (AQAP) to let him live, describing her older brother as a romantic who ""always believes the best in people"". + +Mr Somers’ father, Michael, called his son ""a good friend of Yemen and the Yemeni people"" and asked for his safe release and his mother and brother appealed to his captors to spare him, saying he ""was only trying to do good"". + +Fuad Al Kadas, who said the journalist was one of his best friends, said he spent time in Egypt before finding work in Yemen first as an English teacher and then as one of the few foreign photographers in the country. + +“He is a great man with a kind heart who really loves the Yemeni people and the country,” Mr Al Kadas said. “He was so dedicated in trying to help change Yemen's future, to do good things for the people that he didn't leave the country his entire time here."" + +According to a statement initially released on the website of Yemen's defence ministry, a hostage rescue attempt on Saturday morning was successful. + +A drone struck a suspected AQAP hideout at dawn in Yemen's southern Shabwa province, it said, and a subsequent raid freed an unnamed US hostage and killed 10 extremists. + +It is believed the inconsistency arose because Mr Somers did not die until after he was pulled out and taken into the care of American forces. + +No further details have emerged of Saturday's operation but the Pentagon admitted on Thursday that a secret raid last month had got the wrong location. + +Special forces arrived at the target, in a remote al-Qaeda safe haven in the desert near Yemen’s border with Saudi Arabia, to find Mr Somers was not there. + +The American government considers AQAP to be the world's most dangerous arm of the international terrorist organisation after linking it to several failed attacks on US soil. + +Mr Somers was born in Britain and holds dual US-UK citizenship. Having spent most of his life in the United States, he worked for two years in Yemen as a freelance photojournalist, sub-editor and interpreter for English language newspapers. + +American authorities rarely discuss their controversial drone strike campaign in Yemen, which are known to cause civilian casualties, legitimising violent resistance against US intervention in the country. + +Al-Qaeda and Islamist militants have gained a foothold in large parts of southern and eastern Yemen, where the government is struggling to exert control outside main cities. + +Additional reporting by agencies","1" +"U.S. Hostage Luke Somers Killed During Yemen Rescue Bid: Family","American photojournalist Luke Somers, held hostage by al Qaeda in Yemen, was killed Saturday in a failed rescue attempt, his sister said. There was no immediate comment from Washington about operation, which Yemeni officials said was conducted jointly by the U.S. and Yemen. + +The British-born hostage's sister, Lucy, told NBC News' partner ITV News and The Associated Press that the FBI had inform the family of the 33-year-old's death. + +The operation took place in Shabwa province, a Yemen interior ministry official told NBC News, adding that 10 militants were also killed. It came two days after the Pentagon acknowledged an earlier U.S. commando mission to rescue Somers had failed. Teacher and photographer Somers, a British-born U.S. citizen, was abducted a year ago in Sanaa where he had been working as a freelance photographer for the Yemen Times. + +Al Qaeda posted a video Thursday that showed Somers and a local militant commander threatening that thwe hostage would meet his fate in three days if the U.S. didn't meet the group's demands. + +This is a breaking news story.","1" +"Luke Somers, American Hostage, Is Killed During Rescue Attempt in Yemen, U.S. Official Says","SANA, Yemen — An American journalist held for more than a year by Al Qaeda’s affiliate in Yemen was killed during a rescue attempt by United States commandos late Friday, a senior United States official said. + +Early reports of the overnight raid were sketchy. The official said that the journalist, Luke Somers, 33, was apparently shot by his captors as the raid unfolded and was badly wounded when the commandos reached him. By the time Mr. Somers was flown to a United States naval ship in the region, he had died from his injuries, the official said Saturday. + +There was no immediate comment from the Obama administration about the raid, which took place in the southern Yemeni province of Shabwa. When asked about the operation at a security conference in Bahrain, Gen. Lloyd J. Austin III, the head of United States Central Command, declined to comment. + +Continue reading the main story +RELATED COVERAGE + +A video posted on YouTube purports to show Luke Somers, 33, a kidnapped American journalist.Qaeda Group in Yemen Threatens to Kill American Journalist by End of This WeekDEC. 4, 2014 +Mr. Somers’ sister, Lucy Somers, told The Associated Press on Saturday that she had been notified by the FBI of her brother’s death. “We ask that all of Luke’s family members be allowed to mourn in peace,” she said. + +Mr. Somers, a freelance journalist, was abducted in the Yemeni capital, Sana, in September 2013. Last month, United States commandos and Yemeni counterterrorism troops made an unsuccessful attempt to rescue him in a remote Yemeni province. + +On Wednesday, Al Qaeda in the Arabian Peninsula, the Yemeni extremist group that was holding Mr. Somers, threatened to kill him by the end of the week if its demands were not met. In the video, a leader of the group spoke of the November raid and warned the United States not to carry out any similar operations. + +There was no immediate word on the fate of other hostages who were believed to have been held with Mr. Somers, including citizens of Britain, Turkey and South Africa.","1" +"Luke Somers, American Hostage, Is Killed During Rescue Attempt in Yemen","SANA, Yemen — Two hostages, including an American journalist, who were being held by Al Qaeda’s affiliate in Yemen were killed during a rescue attempt by United States commandos early Saturday, American officials said. + +In a statement, President Obama said the hostages had been “murdered” by militants belonging to Al Qaeda in the Arabian Peninsula during the rescue operation. A senior United States official said that the American, Luke Somers, 33, was badly wounded when commandos reached him. By the time Mr. Somers was flown to a United States naval ship in the region, he had died from his injuries, the official said Saturday. + +The other hostage was identified as Pierre Korkie, a South African citizen, according to a brief statement posted on the website of Gift of the Givers, a disaster relief organization that was trying to negotiate his release. + +Continue reading the main story +RELATED COVERAGE + +A video posted on YouTube purports to show Luke Somers, 33, a kidnapped American journalist.Qaeda Group in Yemen Threatens to Kill American Journalist by End of This WeekDEC. 4, 2014 +A Yemeni tribal leader who said he was a witness to the raid, in the southern province of Shabwa, said that two Al Qaeda militants and at least eight civilians were killed during firefights as U.S. commandos raided several homes. + +Mr. Obama said in his statement, “It is my highest responsibility to do everything possible to protect American citizens. As this and previous hostage rescue operations demonstrate, the United States will spare no effort to use all of its military, intelligence and diplomatic capabilities to bring Americans home safely, wherever they are located.” + +It was the second failed attempt to rescue Mr. Somers, a freelance photographer who was abducted from a street in the Yemeni capital in September 2013. Last month, United States commandos and Yemeni counterterrorism troops mounted a raid on a remote cave in Yemen near the border with Saudi Arabia, freeing eight other hostages but failing to locate Mr. Somers. + +On Wednesday, Al Qaeda in the Arabian Peninsula, the Yemeni extremist group that was holding Mr. Somers, threatened to kill him by the end of the week if its demands were not met. In the video, a leader of the group spoke of the November raid and warned the United States not to carry out any similar operations. + +Mr. Somers’ family broke its silence after the video appeared, urging his captors to release him in a video of their own and insisting that they had no prior knowledge of the first rescue attempt. “Luke is only a photojournalist, and he is not responsible for any actions the U.S. government has taken,” said his brother, Jordan Somers. + +There was no immediate word on the fate of at least two other hostages who were believed to have been held with Mr. Somers, including citizens of Britain and Turkey. + +The tribal leader who said he witnessed the raid, Tarek al-Daghari al-Awlaki, said helicopters and as many as a hundred troops descended on the village, Wadi Abadan. The U.S. forces deployed concussion grenades as they raided four houses in the village, he said. + +“The shooting caused panic,” Mr. Daghari said. “Nine of the dead are from my tribe. Two of the dead are known to be members of Al Qaeda.” He said that two wounded civilians, a woman and a child, were taken to a nearby hospital.","1" +"Luke Somers 'killed in failed rescue attempt in Yemen'","The sister of British-born American photojournalist Luke Somers has said he has been killed in a failed rescue attempt in Yemen. + +Lucy Somers told The Associated Press on Saturday that she learned of her 33-year-old brother's death from FBI agents. There was no immediate comment from Washington. + +Lucy Somers said: ""We ask that all of Luke's family members be allowed to mourn in peace."" + +However, Yemen's defence ministry released a statement claiming that armed forces early on Saturday freed ""an American hostage"" being held by al-Qaeda and killed 10 members of the militant group holding him, Reuters reported. + +Luke Somers was abducted in September 2013 in Yemen's capital, Sanaa. This week, the Pentagon confirmed it launched an earlier failed raid to rescue him. + +Somers' reported death comes as a Yemeni security official said a suspected US drone strike at dawn Saturday killed nine alleged al-Qaeda militants in the country's southern Shabwa province. + +Tribal leaders said they saw helicopters flying nearby after the strike. + +More to follow.","1" +"Luke Somers' sister says he was killed in failed Yemen rescue attempt","American photojournalist Luke Somers, held by al-Qaeda militants following his abduction in Yemen's capital, Sanaa, in September last year, was killed during a failed rescue attempt early Saturday, according to his sister. + +Lucy Somers said she learned of her brother's death from the FBI. ""We ask that all of Luke's family members be allowed to mourn in peace,"" she said. Lucy Somers gave the comments to the Associated Press. + +The claim nonetheless seemed to contradict a statement on the Yemen defense ministry's website carried by Reuters that suggested Luke Somers had been freed following a suspected U.S. drone strike Saturday in Yemen that killed nine alleged al-Qaeda militants. + +The drone struck at dawn in Yemen's southern Shabwa province, hitting a suspected militant hideout, according to an official who spoke to the AP. The official did not elaborate and spoke to the AP on condition of anonymity as he wasn't authorized to brief journalists. + +There was also no immediate comment from U.S. officials, who rarely discuss their drone campaign in Yemen. + +Following the strike, the Al Arabiya news organization tweeted that ""reports suggest U.S. #journalists held in #Yemen freed,"" but there was no immediate confirmation of that report or the originating source. + +In a YouTube video released Wednesday, Somers, 33, says is certain his ""life is in danger."" + +The video features an al-Qaeda official and a brief message from Somers — dressed in a purple shirt and with a shaved head — at the end. He notes that he was born in England but has American citizenship and lived in America for most of his life. + +Pentagon press secretary Rear Adm. John Kirby said Thursday that during a U.S. raid last month that attempted to free Somers he turned out not to be at the site.","1" +"Hewlett-Packard Announces Plans To Break Up Company","Hewlett-Packard Co. HPQ +6.68% on Monday said it plans to separate its personal-computer and printer businesses from its corporate hardware and services operations, the latest attempt by the technology company to improve its fortunes by breaking itself in two. + +The company will make the split through a tax-free distribution of shares to stockholders by the end of fiscal 2015. + +If the division goes off as planned, it would give rise to two publicly traded companies, each with more than $50 billion in annual revenue. + +H-P also boosted the number of its expected layoffs by 5,000 to 55,000, after identifying “incremental opportunities for reductions.” H-P had previously projected its job cuts to be between 45,000 and 50,000, and it has already shed 36,000 employees under the restructuring program as of the end of the most recent quarter. + +A number of big companies, including eBay Inc. EBAY -0.77% in tech, have chosen to break up lately, in part because of a belief that operations with different growth profiles are best managed as separate entities. H-P, which has suffered sharp sales declines, sees better long-term potential for its corporate hardware and services business than for its printer and PC unit, said one person familiar with the plan. + +The impending move, first reported Sunday by The Wall Street Journal, set off a round of speculation in the industry about whether the separation could lead to more deal making. + +The Journal recently reported that for much of the past year, H-P held talks to merge with data-storage equipment maker EMC Corp. EMC +0.49% , a deal that would have created an industry giant with a market value of roughly $130 billion. Although the talks recently ended, the separation could pave the way for H-P’s corporate hardware and services business to ultimately be combined with EMC, industry observers said. + +The planned breakup is one that Palo Alto, Calif.-based H-P and its investors have long contemplated. H-P came close to hiving off its PC operation in 2011, when it announced the ill-fated acquisition of U.K. software company Autonomy Corp. H-P said then it was exploring a separation of its PC business, only to decide two months later to hold on to it amid pressure from shareholders, which led to the departure of then-Chief Executive Leo Apotheker. + +H-P in 1999 spun off Agilent Technologies, A +1.93% a maker of electronic-testing gear and other hardware. Agilent subsequently announced plans to break itself up. + + +H-P chief Meg Whitman is slated to be chairman of a PC and printer business, while remaining CEO of a separate company selling corporate hardware and services. Associated Press +In 2012, under current H-P Chief Executive Meg Whitman, the company reorganized itself to combine the PC business with its more profitable printer operation, helping pave the way for the current plan. + +Ms. Whitman is slated to be chairman of the PC and printer business, to be known as HP Inc., and CEO of the other company, to be called Hewlett-Packard Enterprise. Current lead independent director Pat Russo will be chairman of the enterprise company, while Dion Weisler, an executive in the PC and printer operation, is to be CEO of that business. + +H-P, which affirmed its guidance for the year ending Oct. 31, said it expects per-share earnings of $3.83 to $4.03 for fiscal 2015. The range doesn’t include one-time charges expected to be connected to the separation. Analysts polled by Thomson Reuters were projecting $3.95 a share. + +In the 2013 fiscal year ended last October, the Printing and Personal Systems Group, as it is known, reported $55.9 billion in revenue, about half of H-P’s total. Sales for the operation dropped 7.1% amid fierce competition, compared with a 6.7% decline for company revenue as a whole. + +Last year, H-P lost its place as the largest PC maker by shipments, slipping to No. 2 behind China’s Lenovo Group Ltd 0992.HK +0.68% , according to industry research firm IDC. + +H-P’s shares have risen sharply since the beginning of last year, but they remain well below their highs in recent years—and the even loftier levels they reached during the 1990s tech boom. H-P shares increased 2% on Friday to $35.20, giving it a market capitalization of nearly $66 billion. + +In response to lower sales and to provide a lift to its shares, H-P has laid off tens of thousands of employees and cut other costs. + +Ms. Whitman has sought to push H-P further into growth pockets such as “cloud” software, but the company has struggled to make headway in such areas. + +The recent wave of breakups and spinoffs at technology companies and in the wider corporate world has been fueled by the idea that companies with a narrower focus perform better. The moves in many cases have been well-received by shareholders—and sometimes actively sought by them. + +Last Tuesday, online-auction pioneer eBay, where Ms. Whitman was once CEO, announced a plan to spin off its PayPal payments-processing unit. Shareholders rewarded eBay’s decision, pushing the company’s shares up about 7.5% that day. + +—Shira Ovide and Michael Calia contributed to this article. + +Write to Joann S. Lublin at joann.lublin@wsj.com, Dana Mattioli at dana.mattioli@wsj.com and Dana Cimilluca at dana.cimilluca@wsj.com","1" +"Report: HP to split into two companies, one focused on PCs/printers and one on enterprise computing","Hewlett Packard plans to split into two companies on Monday, according to a report in The Wall Street Journal. One company will be focused on enterprise computing and services, and the other will build and sell PCs and printers. + +Current HP CEO Meg Whitman will lead the enterprise-focused version of HP (it’s not clear who gets to keep the iconic name) and will be chairman of the PC/printer company, which will be led by Dion Weisler as CEO. Details are still fuzzy as to how this will all work, but WSJ reported that HP plans to announce the move on Monday. + +HP is perhaps the seminal Silicon Valley company, with a rich history of computing breakthroughs and technology leadership since it was founded in 1939. But despite taking in $112 billion in revenue in 2013 (split almost evenly between the groups that will form the two separate companies) it has struggled over the last decade with the decline of the PC market, the rise of mobile computing, and the shift to enterprise cloud computing. A series of at-times comical leadership fiascos hasn’t helped. + +I’ll update this post as more information becomes available, and we’ll certainly cover any announcement HP might make tomorrow.","1" +"HP is better not together — company to split into enterprise and PC/printer businesses","Hewlett-Packard is now forging ahead with plans to split off its PC-and-printer businesses into a separate company, with the rest of the company’s enterprise portfolio staying together in a separate entity to be called Hewlett-Packard Enterprise, the company said early Monday morning. + +The Hewlett-Packard enterprise unit, comprising servers, storage, networking, converged systems, services and software and the OpenStack Helion cloud, will be led by Meg Whitman as president and CEO. Pat Russo will be chairman of that board. + +The PC and printer entity, to be known as HP Inc., will be led by Dion Weisler as president and CEO, with Whitman as chairman. The Wall Street Journal (registration required) was first to report this news Sunday afternoon. + +Get all the news you need about Tech with the Gigaom newsletter +SIGN UP +“Our work during the past three years has significantly strengthened our core businesses to the point where we can more aggressively go after the opportunities created by a rapidly changing market,” Whitman said in a statement. “The decision to separate into two market-leading companies underscores our commitment to the turnaround plan. It will provide each new company with the independence, focus, financial resources, and flexibility they need to adapt quickly to market and customer dynamics, while generating long-term value for shareholders.” + +HP, truly an iconic IT company, has been slammed in the past decade by the shift to mobile devices and cloud and a series of management fiascos including the short-lived tenure of former CEO Leo Apotheker. Under his watch, the company considered selling off its still huge PC business, a plan that was scotched by Whitman when she took the reins in 2011. The rationale behind holding onto the PC business was that it gave HP huge volume buying power advantages in procuring chips and other components for its server business as well. + +Toni Sacconaghi, senior analyst with Bernstein Research, wrote in a note that while a split up of HP is hardly a new topic, his take is that the spin off seems to be “fueled by weakness at HP rather than strength.” He also noted that HP in the past few months “came close” to buying Rackspace for nearly $6 billion; nearly bought EMC and “apparently has shopped various parts of its portfolio PCs, its Unix business, IT Services.” + +In another research report released before the news was official, Wells Fargo analyst Maynard Um wrote: + +We believe a separation may suggest HP could become more active in both divestitures and acquisitions, which we believed would be increasingly necessary in FY2015. While this is somewhat of an about face from its prior stance that it was “better together”, we believe this, if true, is likely to be driven by competitive market dynamics as well as a stabilization in its PC business. +The separation, which HP said will be tax-free to shareholders in terms of federal income taxes, is slated to be done by the end of HP’s 2015 fiscal year, ending October 31, 2015. + +Note: This story was updated several times with additional analyst quotes.","1" +"Hewlett-Packard will reportedly split into two companies","The legendary Hewlett-Packard reportedly is about to become two companies. + +One will focus on the firm’s personal computer and printer business, and the other on its business hardware and services, according to a story in today’s Wall Street Journal. + +The publication, citing “people familiar with the matter,” said the split may be made public as early as tomorrow. + +The Journal said that current CEO Meg Whitman will become CEO of the enterprise-oriented company, and independent director Patricia Russo will be chairman. Whitman will serve as chairman of the PC/printer firm, and exec Dion Weisler will be CEO. + +HP has been struggling with its dual selves of being oriented toward businesses’ high-end needs and toward personal computers and printers. Various company executives have in the past discussed spinning off its PC unit, only to be followed by the company asserting its long-term interest in PCs. + +In 2000, Agilent Technologies split off from HP, taking with it the test and measurement equipment business that was HP’s first line of business. + +The company had long reigned as the top PC maker in the world, although it dropped to second place last year in the rankings of industry research firm IDC, after Lenovo. Its printer/personal systems group rakes in about $56 billion in fiscal 2013, about half the company’s total, but sales are down about seven percent from the previous year. + +Via the Wall Street Journal","1" +"HP confirms plan to split company","Hewlett-Packard confirmed on Monday that it will split the company into two new corporations, one focused on PCs and printers and the other on its enterprise businesses. + +News of the split was first reported by the Wall Street Journal on Sunday. On Monday, HP disclosed in a filing with the U.S. Securities and Exchange Commission that it would proceed with the plan, which is expected to be completed by the end of the fiscal year 2015. + +“Our work during the past three years has significantly strengthened our core businesses to the point where we can more aggressively go after the opportunities created by a rapidly changing market,” said HP chief executive Meg Whitman said in a press release. “The decision to separate into two market-leading companies underscores our commitment to the turnaround plan.” + +HP’s split arrives less than a week after eBay’s decision to spin-off PayPal into a separate, public company. + +More information: + +HP +HP is an American multinational information technology corporation headquartered in Palo Alto, California, USA that provides products, technologies, softwares, solutions and services to consumers, small- and medium-sized businesses (SM... read more » + +Powered by VBProfiles","1" +"Hewlett-Packard to split into two companies","Technology giant Hewlett-Packard, known as HP, is to split itself into two separate companies. + +The US firm will separate its better-performing computer and printer business from its corporate hardware and services operations. + +Shareholders will be given a stake in both businesses. + +The split is part of a radical restructuring plan, which has already resulted in tens of thousands of job cuts in recent years. + +The firm is now in the fourth year of its five-year turnaround plan, aimed at helping the firm adapt to the new era of mobile and online computing. + +Current chief executive Meg Whitman, who has the job of reviving the fortunes of the 75-year-old firm, will head the new spin-off, Hewlett Packard Enterprise. + +This will house the corporate hardware and services operations. + +She will also be chairman of HP's printing and PC business, HP Inc, which last quarter accounted for about half its revenue and profit. + +Ms Whitman said the split would give both firms the ""flexibility they need to adapt quickly to market and customer dynamics"". + +""We can [now] more aggressively go after the opportunities created by a rapidly changing market,"" she added. + +HP said it expected the division to be complete by the end of the 2015 financial year. + +Business pressures + +The division of HP's businesses comes at a time when other large tech firms are being urged to break up. + +Last week, online auction site eBay announced it was splitting off its payments system PayPal into a separate company. + +HP has been under pressure from newer rivals such as Chinese firm Lenovo, which overtook HP as the world's largest PC maker in 2012. Third-ranked US rival Dell was taken private last year. + +Founded by Bill Hewlett and Dave Packard in 1939, HP helped usher in the PC revolution and now has more than 300,000 employees globally.","1" +"Report: Hewlett-Packard plans to break into 2 companies","Hewlett-Packard CEO Meg Whitman reportedly plans to split the company in two, becoming chair of a new company with its PC and printer business and CEO of a new company with its corporate hardware and services businesses. + +Hewlett-Packard plans to break into two companies in a move that would create separate personal computer/printer and corporate hardware/services businesses, the Wall Street Journal reported on Sunday. + +The report cited unnamed sources who said the plan could be announced as early as Monday. + +The split would be done as a tax-free distribution of stock to shareholders next year, one of the Journal's sources said. + +It would be the second big breakup of a Silicon Valley tech powerhouse in a week, following eBay's plan to spin off PayPal. It also comes in the wake of Oracle's announcement that Larry Ellison was handing the CEO reins over to former HP CEO Mark Hurd and Safra Catz. + +The move by HP has long been speculated upon and follows the 2011 exploration of a spinoff of the PC business during Leo Apotheker's stormy and short tenure as CEO. + +Current CEO Meg Whitman reorganized the company to combine the PC and printer units, which are leaders in shrinking businesses. HP was No. 1 in PCs until last year when it slipped behind China's Lenovo Group Ltd. + +The Journal said that Whitman will be chairman of the PC and printer business and CEO of the other enterprise-focused business. Lead independent director Patricia Russo will be chairman of the enterprise company. Dion Weisler, an executive in the PC and printer operation will be CEO of that business. + +HP brought in $55.9 billion in revenue from its printing and personal systems group last year, about half of its total. But sales dropped by about 7.1 percent in the unit, compared to a 6.7 percent drop for the company as a whole.","1" +"Hewlett-Packard plans to break into 2 companies","Hewlett-Packard CEO Meg Whitman plans to split the company in two, becoming chair of a new company with its PC and printer business and CEO of a new company with its corporate hardware and services businesses. + +Hewlett-Packard Co. plans to split into two companies in a move that would create separate personal computer-printer and corporate hardware-services businesses. + +The company on Monday confirmed what the Wall Street Journal reported on Sunday from unnamed sources. + +The split will come as a tax-free distribution of stock to shareholders by the end of next year, HP said. Both will be publicly traded. The current stock was up more than 5 percent in pre-market trading on Monday. + +Meg Whitman will be chairman of HP Inc. — the printer and computer business — and she will be CEO of Hewlett-Packard Enterprise — the other half of the business. + +HP's lead independent director, Pat Russo, will be chairman at the new enterprise company and Chief Financial Officer Cathie Lesjak will CFO at that company. + +Dion Weisler, executive vice president of HP’s printing and computers business, will be HP Inc.'s president and CEO. Whitman be the non-executive chairman of HP Inc.’s board. + +This is the second big breakup of a Silicon Valley tech powerhouse in a week, following eBay's plan to spin off PayPal. It also follows Oracle's announcement that Larry Ellison was handing the CEO reins over to former HP CEO Mark Hurd and Safra Catz. + +The announcement comes a few weeks after talks reportedly broke down about a possible HP merger with EMC, whose CEO Joe Tucci is near retirement and whose leadership in the data-storage industry is being challenged by a group of upstarts. + +The move by HP has long been speculated upon and follows the 2011 exploration of a spinoff of the PC business during Leo Apotheker's stormy and short tenure as CEO.","1" +"IT'S OFFICIAL: HP Is Splitting Into Two Separate Businesses","Hewlett-Packard is planning to split itself into two separate businesses, The Wall Street Journal is reporting. HP confirmed the news on Monday morning. + +Sources tell the WSJ that HP will split its personal-computer and printer segments from its corporate hardware and services business. + +The announcement could come as early as Monday, the sources said. + +The company reorganized itself in 2012 under CEO Meg Whitman. That move combined its computer and printer businesses. + +The PC and computer segment is massive for HP. For the first six months this year, it reported $27.8 billion in revenue. That's about three times the size of HP's next biggest unit, the Enterprise Group, which makes servers, storage, and network hardware. + +Under the new split, Whitman would be chairman of the computer and printer business, and CEO of a separate enterprise company, according to one of the sources. Patricia Russo, who sits on HP's board, would be chairman of the enterprise company. The printer and PC operation would be led by Dion Weisler, a current exec in that division. + +Whitman has said since 2012 that fixing the supply chain is one of HP's biggest priorities to get the company back on track in terms of revenues and profits. HP reported a beat on revenue for its third quarter, and its profits were right in line. + +This isn't the first time HP has been toying with the idea of strategic moves. For almost a year it has contemplated merging with EMC to create what would be one of the biggest enterprise companies in the world. But talks apparently fell through, The WSJ reported. + +And HP isn't the only company that sees benefit in splitting itself to create a more-focused company. eBay announced last week that it was spinning off PayPal into a separate business starting next year. + +HP declined to comment. + +SEE ALSO: This Is What HP Looks Like Without Its Biggest, $56 Billion PC/Printer Business","1" +"IT'S OFFICIAL: HP Is Splitting Into 2 Separate Businesses","Hewlett-Packard is splitting itself into two separate businesses, the company confirmed on Monday. + +HP is splitting its personal-computer and printer segments from its corporate hardware and services business. The PC/printer company will be called HP. The remaining units will be called HP Enterprise. Both will be public companies. The stock split is intended to be a tax-free transaction for existing shareholders. The Wall Street Journal first reported the story. + +The company reorganized itself in 2012 under CEO Meg Whitman. That move combined its computer and printer businesses. + +The PC and computer segment is massive for HP. It accounts for half of the company's revenue. For the first six months this year, it reported $27.8 billion in revenue. That's about three times the size of HP's next biggest unit, the Enterprise Group, which makes servers, storage, and network hardware. + +Under the new split, Whitman is chairman of the computer and printer business, and she remains CEO of the separate HP Enterprise company. Patricia Russo, who sits on HP's board, is chairman of the enterprise company. Dion Weisler, who currently leads the printer and PC operation, is being named CEO of the new printer/PC company. + +Whitman has said since 2012 that fixing the supply chain is one of HP's biggest priorities to get the company back on track in terms of revenues and profits. HP reported a beat on revenue for its third quarter, and its profits were right in line. + +This isn't the first time HP has been toying with the idea of strategic moves. For almost a year it has contemplated merging with EMC to create what would be one of the biggest enterprise companies in the world. But talks apparently fell through, The Journal reported. + +And HP isn't the only company that sees benefit in splitting itself to create a more-focused company. eBay announced last week that it was spinning off PayPal into a separate business starting next year. + +Here is the press release HP issued Monday morning: + +October 06, 2014 06:30 ETHP to Separate Into Two New Industry-Leading Public Companies + +Hewlett-Packard Enterprise Will Define the Next Generation of Technology Infrastructure, Software and Services for the New Style of IT + +HP Inc. Will Be the Leading Personal Systems and Printing Company Delivering Innovations That Will Empower People to Create, Interact and Inspire Like Never Before + +Strategic Step Provides Each New Company With the Focus, Financial Resources and Flexibility to Adapt Quickly to Market and Customer Dynamics While Generating Long-Term Value for Shareholders + +PALO ALTO, CA--(Marketwired - Oct 6, 2014) - HP (NYSE: HPQ) + +Highlights: + +Hewlett-Packard Enterprise will build upon HP's leading position in servers, storage, networking, converged systems, services and software as well as its OpenStack Helion cloud platformMeg Whitman to be President and Chief Executive Officer of Hewlett-Packard Enterprise; Pat Russo to be Chairman of Hewlett-Packard Enterprise BoardHP Inc. will be the leading personal systems and printing company with a strong roadmap into the most exciting new technologies like 3D printing and new computing experiencesDion Weisler to be President and Chief Executive Officer of HP Inc.; Meg Whitman to be Chairman of the HP Inc. BoardCompany reiterates fiscal 2014 non-GAAP diluted net earnings per share (EPS) outlook of $3.70 to $3.74 and updates GAAP diluted net EPS outlook to $2.60 to $2.64Company issues fiscal 2015 non-GAAP diluted net EPS outlook of $3.83 to $4.03 and GAAP diluted net EPS outlook of $3.23 to $3.43 + +HP (NYSE: HPQ) today announced plans to separate into two new publicly traded Fortune 50 companies: one comprising HP's market-leading enterprise technology infrastructure, software and services businesses, which will do business as Hewlett-Packard Enterprise, and one that will comprise HP's market-leading personal systems and printing businesses, which will do business as HP Inc. and retain the current logo. Immediately following the transaction, which is expected to be completed by the end of fiscal 2015, HP shareholders will own shares of both Hewlett-Packard Enterprise and HP Inc. The transaction is intended to be tax-free to HP's shareholders for federal income tax purposes. + +Today's announcement comes as HP approaches the fourth year of its five-year turnaround plan. Over this time, the company has executed successfully against its turnaround objectives, keeping customers and partners at the forefront. HP has reignited its innovation pipeline, strengthened its go-to-market capabilities, rebuilt its balance sheet, and inspired its workforce and management teams. The company is now positioned to accelerate performance, drive sustained growth and demonstrate clear industry leadership in key areas. + +""Our work during the past three years has significantly strengthened our core businesses to the point where we can more aggressively go after the opportunities created by a rapidly changing market,"" said Meg Whitman, Chairman, President and Chief Executive Officer of HP. ""The decision to separate into two market-leading companies underscores our commitment to the turnaround plan. It will provide each new company with the independence, focus, financial resources, and flexibility they need to adapt quickly to market and customer dynamics, while generating long-term value for shareholders. In short, by transitioning now from one HP to two new companies, created out of our successful turnaround efforts, we will be in an even better position to compete in the market, support our customers and partners, and deliver maximum value to our shareholders."" + +Both companies will be well capitalized and expect to have investment grade credit ratings and capital structures optimized to reflect their distinct growth opportunities and cash flow profiles. The separation into independent publicly traded companies will provide each company with its own, more focused equity currency, and investors with the opportunity to invest in two companies with compelling and unique financial profiles well suited to their respective businesses. + +Management StructureMeg Whitman, President and Chief Executive Officer of HP, and Cathie Lesjak, Chief Financial Officer of HP, will hold these positions with Hewlett-Packard Enterprise. When the separation is complete, Whitman will also serve on the Board of Directors of Hewlett-Packard Enterprise, and Pat Russo will move from Lead Independent Director of HP to Chairman of Hewlett-Packard Enterprise. + +Dion Weisler, Executive Vice President of HP's Printing and Personal Systems business, will lead HP Inc. as President and Chief Executive Officer. Whitman will serve as non-executive Chairman of HP Inc.'s Board of Directors. + +Hewlett-Packard EnterpriseHewlett-Packard Enterprise will have a unique portfolio and strong multi-year innovation roadmap across technology infrastructure, software and services to allow customers to take full advantage of the opportunities presented by cloud, big data, security and mobility in the New Style of IT. By leveraging its HP Financial Services capability, the company will be well positioned to create unique technology deployment models for customers and partners based on their specific business needs. Additionally, the company intends for HP Financial Services to continue to provide financing and business model innovation for customers and partners of HP Inc. + +Customers will have the same unmatched choice of how to deploy and consume technology, and with a simpler, more nimble partner. The separation will provide additional resources, and a reduction of debt at the operating company level, to support investments across key areas of the portfolio. The separation will also allow for greater flexibility in completing the turnaround of Enterprise Services and strengthening the company's go-to-market capabilities. + +""Over the past three years, we have reignited our innovation engine with breakthrough offerings for the enterprise like Apollo, Gen 9 and Moonshot servers, our 3PAR storage platform, our HP OneView management platform, our HP Helion Cloud and a host of software and services offerings in security, analytics and application transformation,"" continued Whitman. ""Hewlett-Packard Enterprise will accelerate innovation across key next-generation areas of the portfolio."" + +HP Inc.HP Inc. will be a proven leader in the personal systems and printing markets with exciting new technologies on the horizon. The new company's strong profitability and free cash flow will enable investments in growth markets such as 3-D printing and new computing experiences. At the same time, HP Inc. will continue to execute against a well-defined and established strategic plan, ensuring continuity for customers and consistent value to shareholders. + +""Since assuming responsibility for the Printing and Personal Systems Group, Dion and his leadership team have done an excellent job of building our relationships with customers and channel partners, segmenting the market and driving product innovation,"" added Whitman. ""The creation of HP Inc. will only accelerate the progress the team has made."" + +""This is a defining moment in our industry as customers are looking for innovation to enable workforces that are more mobile, connected and productive while at the same time allowing a seamless experience across work and play,"" said Weisler. ""As the market leader in printing and personal systems, an independent HP Inc. will be extremely well positioned to deliver that innovation across our traditional markets as well as extend our leadership into new markets like 3-D printing and new computing experiences -- inventing technology that empowers people to create, interact and inspire like never before."" + +Transaction DetailsThe separation transaction is intended to be tax-free to HP shareholders for federal income tax purposes. The transaction is currently targeted to be completed by the end of fiscal 2015, subject to certain conditions, including, among others, obtaining final approval from the HP Board of Directors, receipt of a favorable opinion and/or rulings with respect to the tax-free nature of the transaction for federal income tax purposes and the effectiveness of a Form 10 filing with the Securities and Exchange Commission. + +Goldman Sachs & Co. is serving as financial advisor and Wachtell, Lipton, Rosen and Katz is serving as legal advisor to HP. + +For more information, please see here. + +Financial OutlookFor fiscal 2014, HP reaffirms its non-GAAP diluted net EPS outlook range of $3.70 to $3.74, and updates its fiscal 2014 GAAP diluted net EPS outlook to be in the range of $2.60 to $2.64. + +For fiscal 2015, HP estimates non-GAAP diluted net EPS outlook to be in the range of $3.83 to $4.03 and GAAP diluted net EPS outlook to be in the range of $3.23 to $3.43. + +HP's outlook does not include one-time GAAP charges the company is expected to incur in connection with the separation, including advisory and tax costs which will be quantified at a later date. + +Investment Community Conference CallFor webcast details, go to www.hp.com/investor/2014OctAnnouncement/. + +HP Securities Analyst Meeting 2014HP also announced today that, as a result of the announcement of this separation, its October 8, 2014 Securities Analyst Meeting has been postponed. + +About HPHP creates new possibilities for technology to have a meaningful impact on people, businesses, governments and society. With the broadest technology portfolio spanning printing, personal systems, software, services and IT infrastructure, HP delivers solutions for customers' most complex challenges in every region of the world. More information about HP is available at http://www.hp.com. + +Use of non-GAAP financial informationTo supplement HP's historical and forecasted financial results presented on a GAAP basis, HP provides non-GAAP diluted net earnings per share. Non-GAAP diluted net earnings per share is defined to exclude the effects of any restructuring charges, charges relating to the amortization of intangible assets and certain other acquisition-related charges recorded or expected to be recorded during the relevant period. In addition, non-GAAP diluted net earnings per share are adjusted by the amount of additional taxes or tax benefit associated with each non-GAAP item. Fiscal 2014 non-GAAP diluted net EPS estimates exclude after-tax costs of approximately $1.10 per share, related primarily to restructuring charges and amortization of intangible assets. Fiscal 2015 non-GAAP diluted net EPS estimates exclude after-tax costs of approximately $0.60 per share, related primarily to amortization of intangible assets and restructuring charges. + +HP's management uses non-GAAP financial measures, including HP's non-GAAP diluted net earnings per share, to evaluate and forecast HP's performance before gains, losses or other charges that are considered by HP's management to be outside of HP's core business segment operating results. These non-GAAP financial measures may have limitations as analytical tools, and these measures should not be considered in isolation or as a substitute for analysis of HP's results as reported under GAAP. For example, items such as the amortization of intangible assets, though not directly affecting HP's cash position, represent the loss in value of intangible assets over time. The expense associated with this loss in value is not included in HP's non-GAAP diluted net earnings per share and therefore does not reflect the full economic effect of the loss in value of those intangible assets. In addition, items such as restructuring charges that are excluded from HP's non-GAAP diluted net earnings per share can have a material impact on HP's GAAP diluted net earnings per share. Other companies may calculate non-GAAP diluted net earnings per share differently than HP does, which limits the usefulness of that measure for comparative purposes. + +SEE ALSO: This Is What HP Looks Like Without Its $56 Billion PC/Printer Business","1" +"Hewlett-Packard to break into 2 companies","Hewlett-Packard said it would split into two listed companies, separating its computer and printer businesses from its faster-growing corporate hardware and services operations. + +HP said its shareholders would own a stake in both businesses through a tax-free transaction next year. + +Shares of the company, which has struggled to adapt to the new era of mobile and online computing, rose almost 8 percent in premarket trading on Monday. (Get the latest quote here.) + +Each of the two businesses contribute about half of HP's current revenue and profit. + +The move will result in a monumental reshaping of one of technology's most important pioneers, which still has more than 300,000 employees and is on track to book $112 billion in revenue this fiscal year. + +The printing and personal computing business, to be known as HP Inc., will be led by Dion Weisler, currently an executive in that division. + +HP's current chief executive, Meg Whitman, will lead the new Hewlett-Packard Enterprise, which will house the corporate hardware and services operations. She will also be chairman of HP Inc. + +Current HP lead independent director Patricia Russo will be chairman of the enterprise company. + +Founded by Bill Hewlett and Dave Packard in a Palo Alto, California garage in 1939, HP was one of the companies that shaped Silicon Valley and the PC revolution. + +Lately, however, it has struggled to adapt to the shift toward mobile computing, and it has been overshadowed by younger rivals. + +The announcement on Monday confirmed a report of the split in the Wall Street Journal on Sunday. + +HP is the latest in a line of companies, often under shareholder pressure, to spin off operations in an attempt to become more agile and to capitalize on faster-growing businesses. + +Last week online auction company eBay said it would spin off electronic payment service PayPal. + +Up to Friday's close, HP's stock had risen nearly 26 percent this year.","1" +"Hewlett-Packard plans to split into two companies: Report","Hewlett-Packard plans to break in two, separating its computer and printer businesses from its corporate hardware and services operations, the Wall Street Journal reported on Sunday. + +The company plans to announce the move as early as Monday, the Journal said in a report on its web site that cited people familiar with the matter. The division would be made through a tax-free distribution of shares to stockholders next year, according to the report. + +A company spokeswoman declined to comment on the report. + +HP and some of its investors have long considered such a move, the newspaper noted. As one of the older big computer companies, for several years HP directors have discussed ways to restructure to keep up with technology upstarts. + +Company split-ups in which shares of new divisions were spun off to stockholders in the past have resulted in higher stock market returns for investors.","1" +"HP to split into two businesses -- report","Hewlett-Packard may be ready for a breakup. + +HP, the world's second largest PC vendor behind Lenovo, plans to separate its PC and printer businesses from its corporate hardware and other enterprise operations, reported The Wall Street Journal on Sunday, citing ""people familiar with the matter."" The company could announced the move as early as Monday, according to the Journal's sources. + +HP declined to comment. + +CEO Meg Whitman will be chairman of the new PC and printer business and chief executive of the separate ""enterprise company,"" one source told the Journal, while board member Patricia Russo will chairman of the enterprise company. Don Weisler, the current executive vice president of HP's printing and personal systems, will step in as CEO of the PC and printer business, according to the Journal.","1" +"Hewlett-Packard splits off PC, printer businesses","NEW YORK (AP) — Hewlett-Packard is splitting itself into two companies, one focused on its personal computer and printing business and another on technology services, such as data storage, servers and software, as it aims to drive profits higher. + +The company laid off tens of thousands of people in recent years as sales crumbled, with customers shifting to mobile devices like smartphones and computer tablets. That has drastically curbed demand for HP's desktop and laptop computers, as well as its printers. + +The company said Monday that the PC and printer business will use the name HP Inc. The services business will be called Hewlett-Packard Enterprise. + +FILE - In this Aug. 21, 2012, file photo, the Hewlett-Packard Co. logo is seen outside the company's headquarters in Palo Alto, Calif. Hewlett-Packard Co. is splitting itself into two companies, one focused on its personal computer and printing business and another on technology services, such as data storage, servers and software, as it aims to drive stronger profitability. (AP Photo/Paul Sakuma, File) + +HP CEO Meg Whitman will lead the Enterprise business. HP PC and printer chief Dion Weisler will be CEO of HP Inc. + +""The decision to separate into two market-leading companies underscores our commitment to the turnaround plan,"" Whitman said. ""It will provide each new company with the independence, focus, financial resources, and flexibility they need to adapt quickly to market and customer dynamics."" + +The split, if approved by the company board, is expected to close by the end of fiscal 2015. Once complete, HP stockholders will own shares of both companies. + +During its most recent quarter HP reported revenue of $27.6 billion, a 1 percent annual gain. It marked HP's first year-over-year increase in quarterly revenue since late 2011. Printers and computers contributed 51 percent of the company's quarterly revenue, with the rest coming from technology services like consulting, software and financial programs. + +HP is expected to complete the latest round of layoffs, between 11,000 to 16,000 people, this month. That is on top of the 34,000 people it had already jettisoned from its payroll. + +Another tech stalwart announced a split this month. In a bid to drive growth, eBay Inc. said it would spin off its mobile payment service PayPal into a separate and publicly traded company. Investors sent eBay shares up more than 7 percent on the day of the announcement. + +HP maintained its guidance for fiscal 2014 adjusted earnings between $3.70 and $3.74 per share. Analysts polled by FactSet predict earnings of $3.73 per share. + +For fiscal 2015, the company anticipates adjusted earnings in a range of $3.83 to $4.03 per share. Wall Street is looking for $3.96 per share. + +Shares of Hewlett-Packard Co., based in Palo Alto, California, gained $2.85, or 8.1 percent, to $38.05 before the market open. + +Sorry we are not currently accepting comments on this article.","1" +"Hewlett-Packard to split into two public companies","Oct 6 (Reuters) - Hewlett-Packard Co said it would split into two listed companies, separating its computer and printer businesses from its faster-growing corporate hardware and services operations. + +HP said its shareholders would own a stake in both businesses through a tax-free transaction next year. + +Shares of the company, which has struggled to adapt to the new era of mobile and online computing, were up 5.1 percent at $37 in premarket trading on Monday. + +Each of the two businesses contribute about half of HP's current revenue and profit. + +The move will result in a monumental reshaping of one of technology's most important pioneers, which has more than 300,000 employees and is on track to book $112 billion in revenue the fiscal year ending October. + +""Shareholders will now be able to invest in the respective asset groups without the fear of cross-subsidies and inefficiencies that invariably plague large business conglomerates,"" Ralph Whitworth, former HP chairman and founder of Relational Investors LLC, said in a statement. + +Relational owns a 1.49 percent stake in HP, which had a market value of about $66 billion as of Friday. + +Many investors and analysts had called for a break-up of the company, or a sale of the personal computer business, so that HP could focus on the more profitable operations of providing computer servers, networking and data storage to businesses. + +HP is the latest in a line of companies, often under shareholder pressure, to spin off operations in an attempt to become more agile and capitalize on faster-growing businesses. + +Online auction company eBay Inc said last week it would spin off electronic payment service PayPal. + +WHITMAN TO LEAD ENTERPRISE + +HP's current chief executive, Meg Whitman, will lead the new Hewlett-Packard Enterprise, which will house the corporate hardware and services operations. + +Current HP lead independent director Patricia Russo will be chairman of the enterprise company. + +HP's printing and personal computing business, to be known as HP Inc, will be led by Dion Weisler, currently an executive in that division. Whitman will be chairman of HP Inc. + +Founded by Bill Hewlett and Dave Packard in a Palo Alto, California garage in 1939, HP was one of the companies that shaped Silicon Valley and the PC revolution. + +Lately, however, it has struggled to adapt to the shift towards mobile computing, and it has been overshadowed by younger rivals such as Chinese PC maker Lenovo, which is now the world's No. 1 PC maker by shipments. + +Dell Inc, which is HP's closest U.S. competitor and facing similar pressure, was taken private by founder Michael Dell last year. + +HP's PC business has shown signs of life in recent quarters, growing broadly geographically as businesses replace aging machines. + +HP on Monday affirmed its fiscal 2014 adjusted earnings of $3.70 to $3.74 per share. It also forecast 2015 adjusted earnings of $3.83-$4.03 per share, in line with the average analyst estimate of $3.95, according to Thomson Reuters I/B/E/S. + +HP's announcement on Monday confirmed a report of the split in the Wall Street Journal on Sunday. + +Up to Friday's close, HP's stock had risen nearly 26 percent this year. (Reporting by Supantha Mukherjee in Bangalore, David Henry in New York, Edwin Chan in San Francisco and Bill Rigby in Seattle; Editing by Chizu Nomiyama and Savio D'Souza) + +Sorry we are not currently accepting comments on this article.","1" +"Hewlett-Packard to split into two public companies, lay off 5,000","By Supantha Mukherjee and Edwin Chan + +Oct 6 (Reuters) - Hewlett-Packard Co said it would split into two listed companies, separating its computer and printer businesses from its faster-growing corporate hardware and services operations, and eliminate another 5,000 jobs as part of its turnaround plan. + +HP said its shareholders would own a stake in both businesses through a tax-free transaction next year, the details of which still needed to be worked out. + +Each business contributes about half of HP's revenue and profit. + +Shares of the 75-year-old company, which has struggled to adapt to the new era of mobile and online computing, were up 4 percent at $36.60 in early trading on Monday. + +A spinoff of the PC business was last proposed in 2011 by then-Chief Executive Leo Apotheker as the company struggled in the highly competitive PC market. HP later ditched the plan - and Apotheker, replacing him with current CEO Meg Whitman. + +""Make no mistake, one HP was the right thing to do to begin the turnaround of this company,"" Whitman said on a conference call. ""But now ... this is definitely the right tactic."" + +HP said it planned to cut 5,000 more jobs as part of its multi-year restructuring, raising the total under Whitman to 55,000. The company currently has more than 300,000 employees. + +The separation will result in a fundamental reshaping of one of technology's most important pioneers, which is on track to generate $112 billion in revenue in the fiscal year this month. + +Many investors and analysts had called for a break-up of the company, or a sale of the PC business, so that HP could focus on the more profitable operations that sell computer servers and networking gear and data storage to businesses. + +""Shareholders will now be able to invest in the respective asset groups without the fear of cross-subsidies and inefficiencies that invariably plague large business conglomerates,"" Ralph Whitworth, former HP chairman and founder of Relational Investors LLC, said in a statement. + +Relational owns a 1.49 percent stake in HP, which has a market value of almost $70 billion. + +HP is the latest in a line of companies, often under shareholder pressure, to spin off operations in an attempt to become more agile and capitalize on faster-growing businesses. + +Online auction company eBay Inc, which was formerly run by Whitman, said last week it would spin off electronic payment service PayPal. + +WHITMAN TO LEAD ENTERPRISE + +Whitman will lead the new Hewlett-Packard Enterprise, which will house the corporate hardware and services operations. + +Current lead independent director Patricia Russo will be chairman of the enterprise company. + +HP's printing and personal computing business, to be known as HP Inc, will be led by Dion Weisler, currently an executive in that division. Whitman will be chairman of HP Inc. + +Founded by Bill Hewlett and Dave Packard in a Palo Alto, California garage in 1939, HP was one of the companies that shaped Silicon Valley and the PC revolution. + +Goldman Sachs & Co served as financial adviser to HP, while Wachtell, Lipton, Rosen and Katz served as legal adviser. (Reporting by Supantha Mukherjee in Bangalore, David Henry in New York, Edwin Chan in San Francisco and Bill Rigby in Seattle; Editing by Chizu Nomiyama, Savio D'Souza and Ted Kerr) + +Sorry we are not currently accepting comments on this article.","1" +"HP is reportedly splitting into two companies","HP's home-focused and business divisions have frequently seemed at odds with each other, and apparently the company agrees. The Wall Street Journal claims that the tech giant is about to split into two companies, one focused on PCs and the other dedicated solely to corporate hardware and services. If the report is accurate, the separation could be announced as early as Monday. The exact reasoning behind the move hasn't been mentioned, but the PC-centric group would be headed by one of its existing executives, Dion Weisler; current CEO Meg Whitman would run the business group and keep an eye on the other company by serving as its chairman of the board. However true the rumor may be, such a move wouldn't be all that surprising -- much of the computing industry has been restructuring and rescaling to cope with a world where the PC's role is rapidly evolving. + +Source: Wall Street Journal","1" +"HP is reportedly splitting into two companies focused on PCs and business","HP's home-focused and business divisions have frequently seemed at odds with each other, and apparently the company agrees. The Wall Street Journal claims that the tech giant is about to split into two companies, one focused on PCs and the other dedicated solely to corporate hardware and services. If the report is accurate, the separation could be announced as early as Monday. The exact reasoning behind the move hasn't been mentioned, but the PC-centric group would be headed by one of its existing executives, Dion Weisler; current CEO Meg Whitman would run the business group and keep an eye on the other company by serving as its chairman of the board. However true the rumor may be, such a move wouldn't be all that surprising -- much of the computing industry has been restructuring and rescaling to cope with a world where the PC's role is rapidly evolving. + +Source: Wall Street Journal","1" +"HP officially splitting into two companies (update)","HP's home-focused and business divisions have frequently seemed at odds with each other, and apparently the company agrees. The Wall Street Journal claims that the tech giant is about to split into two companies, one focused on PCs and the other dedicated solely to corporate hardware and services. If the report is accurate, the separation could be announced as early as Monday. The exact reasoning behind the move hasn't been mentioned, but the PC-centric group would be headed by one of its existing executives, Dion Weisler; current CEO Meg Whitman would run the business group and keep an eye on the other company by serving as its chairman of the board. However true the rumor may be, such a move wouldn't be all that surprising -- much of the computing industry has been restructuring and rescaling to cope with a world where the PC's role is rapidly evolving. + +Update: Recode also says it's aware of the split, and has an explanation for it. Supposedly, HP had no luck in early talks to sell its PC division to Dell or Lenovo. It had similar problems offloading server and services groups, and a merger with the data storage gurus at EMC also wasn't meant to be. The breakup would effectively revive plans shelved when CEO Leo Apotheker got the boot in 2011; getting rid of less successful products (in this case, PCs) would improve the chances of an EMC merger or similar deals. + +Update 2: HP has now confirmed the news. In a filing with the SEC, the company states that it plans to split into two publicly traded companies. Its consumer-focused PC, tablet, and printing efforts will continue on under the HP banner, while a new company named Hewlett-Packard Enterprise will focus on ""enterprise technology infrastructure"" and ""software and services businesses."" Meg Whitman, the current CEO of HP, will take the reins at Hewlett-Packard Enterprise, while Dion Weisler, the company's EVP for Printing and Personal Systems, will lead the new HP. + +The company also announced an increase in the number of layoffs for this financial year. It had previously estimated 45,000-50,000 employees would be leaving the company, but that figure has now risen to 55,000.","1" +"Hewlett-Packard Plans To Break Into Two Companies: Report","Technology giant Hewlett-Packard will break in two, according to sources cited by The Wall Street Journal on Sunday. + +The company will reportedly be divided between its PC and printers units and its corporate hardware and services operations. Hewlett-Packard will announce the separation as early as Monday, according to WSJ. + +The split is the latest in a series of high-profile technology breakups, following close on the heels of eBay's decision to spin off PayPal last week. Many expect better performance when a large company becomes focused on a more limited number of business lines. + +Meg Whitman will be CEO of the corporate hardware and services company and act as chairman of the PC and printer company, according to the WSJ's sources. Dion Weisler will be CEO of the PC side, and Patricia Russo will be chairman of the corporate side. + +HP has considered splitting up for years. + +An HP spokesperson said the company had no comment when contacted by The Huffington Post.","1" +"Hewlett Packard ‘planning to split into two’","Employer of 300,000 will separate its computer and printer business from its corporate hardware and services operations + +Hewlett-Packard is planning to split into two companies as it looks to put more focus on the faster-growing corporate services market, according to a Wall Street Journal report. + +The move, which could be announced on Monday, would be a monumental reshaping of one of technology’s most important pioneers, which still has more than 300,000 employees and is on track to book $112bn (£70bn) in revenue this fiscal year but has struggled to adapt to the new era of mobile and online computing. + +Under the reported plan, HP will separate its computer and printer businesses from its corporate hardware and services operations and spin the unit off through a tax-free distribution of shares to stockholders next year. + +A company spokeswoman declined to comment on the report. + +HP’s printing and personal computing business accounts for about half its revenue and profit, according to last quarter’s financial results. It is not clear how many of HP’s staff –about 300,000 people – work in each of the planned businesses. + +Founded by Bill Hewlett and Dave Packard in a garage in Palo Alto, California in 1939, HP was one of the companies that shaped Silicon Valley and the personal computer revolution. Lately, however, it has struggled to adapt to the shift towards mobile computing and has been overshadowed by younger rivals. + +HP’s market value of $66bn is dwarfed by Apple Inc’s $596bn and Microsoft Corp’s $380bn. + +It has also been overtaken by aggressive Chinese computer maker Lenovo, which is now the world’s number one, based on shipments. Dell, which is HP’s closest US competitor and facing similar pressure, was taken private by founder Michael Dell last year.","1" +"Sorry - this page has been removed.","This could be because it launched early, our rights have expired, there was a legal issue, or for another reason. + +For further information, please contact:","1" +"HP reportedly plans to split PC and printer business from enterprise unit","HP is set to cleave itself in two, splitting off its PC and printer division from its enterprise and services business. According to The Wall Street Journal, an announcement could come as soon as tomorrow. ""Sources familiar with the matter"" tell the paper that current CEO Meg Whitman will become chairman of the PC and printer operation, and will remain CEO of the split-off enterprise business. Dion Weisler will become CEO of the personal computing business — he is currently a high-ranking executive in the division. + +This is not the first time talk of splitting HP has surfaced. During some of the company's very tumultuous 2011, reports suggested that executives were close to making the very same decision to split off the enterprise division into its own business. After the departure of then-CEO Léo Apotheker, the company decided to keep the units together under the same corporate umbrella. + +The company, based in Palo Alto, has struggled along with the rest of the PC industry as profit margins have slimmed and sales of Windows PC continue to steadily decline. The company's printer business is more lucrative than its PC operation, though the two were combined into the same unit back in 2012. That same year, HP lost the title of top-selling PC manufacturer to Lenovo.","1" +"HP announces plan to split in two","Hewlett-Packard is officially splitting in two. Following rumors over the weekend, HP is announcing today that it will separate its PC and printer division from its enterprise and services business. The split means current CEO Meg Whitman will become the chairman of the PC and printer operation, and continue as CEO of the split-off enterprise business. Dion Weisler, an executive at HP’s PC business, will take over as CEO of the company’s PC and printer operation. + +HP Enterprise is the newly split-off part of the original company, and HP Inc will continue to focus on PCs and printers. ""The decision to separate into two market-leading companies underscores our commitment to the turnaround plan,"" says HP CEO Meg Whitman. ""It will provide each new company with the independence, focus, financial resources, and flexibility they need to adapt quickly to market and customer dynamics, while generating long-term value for shareholders."" HP is planning to complete the split by the end of fiscal 2015, and the structure will mean the company's total planned layoffs will rise to 55,000 from an earlier estimate of 45,000 to 50,000 cuts. + +Today’s split is a significant change for the company, following rumors from 2011 that HP was considering a similar split at the time. Those reports surfaced shortly before HP appointed Meg Witman as CEO, just 11 months after former CEO Leo Apotheker took over from Mark Hurd after he was forced to resign amidst charges of inappropriate business conduct. Apotheker spearheaded a disastrous acquisition of Autonomy, and failed to capitalize on the company’s purchase of webOS. + +Whitman’s era at HP has seen the company struggle to cement a solid position in the industry, leaving Lenovo to dominate PC sales worldwide. Whitman’s initial assessment of the company after around six months left her feeling it was ""too complex and too slow,"" noting it had underinvested in its PC division. Instead of significant investment, Whitman claimed in 2012 that the company had to offer a smartphone, before failing to announce one in 2013. Board members reportedly mulled spinning off the company’s consumer PC business in 2013, but it never happened. HP has recently focused on Android tablets, and even an Android laptop, after describing Microsoft as an ""outright competitor."" + +HP and Microsoft appear to be forming a closer relationship with the launch of new low-cost Stream PCs. Although Lenovo continues to push Windows-based PCs, Microsoft still needs close PC allies as it demonstrated with a $2 billion loan to help Dell go private last year. That particular deal may have angered HP, but the renewed partnership will see Microsoft and HP take on Chromebooks this holiday season. HP is also planning to sell a smartwatch this fall. + +A new HP says it will focus on ""new computing experiences"" and technologies like 3D printing. ""As the market leader in printing and personal systems, an independent HP Inc. will be extremely well positioned to deliver that innovation across our traditional markets as well as extend our leadership into new markets like 3-D printing and new computing experiences -- inventing technology that empowers people to create, interact and inspire like never before,"" says Dion Weisler, head of HP's Printing and Personal Systems business.","1" +"Hugh Hefner Dead? Fans Panic That Playboy Founder Is Gone","Uh oh. A report recently went wild on the internet that 88-year-old ‘Playboy’ founder Hugh Hefner had died of natural causes on Dec. 28. Is Hugh really gone for good? +Oh no! Is Hugh Hefner dead? A shocking report went viral on the internet claiming that the Playboy tycoon had passed away of natural causes at his home in the Playboy Mansion. Fans of the 88-year-old celebrity took to Twitter to sound off on their concerns. + + +Hugh Hefner Dead? New Death Hoax Spread On Internet +Take a huge sigh of relief because Hugh is A-ok! + +The businessman made sure everyone know that he was alive and well on Dec. 29. + + +His wife, Crystal Hefner, also posted a picture of Hugh on the movie night. However, before Hugh’s tweet, fans expressed their worry all over Twitter. + + +It’s easy to see why fans would be freaking out. A website with the URL “nbctoday.co” posted the story, and it went viral across various social media sites. Many probably assumed that the link was the actual NBC TODAY site. + + +Hugh Hefner Found Dead? +Inform + +The site wrote: “Hugh Hefner, Founder and chief creative officer of Playboy Enterprises, was found dead of natural causes Sunday morning at his home, the Playboy Mansion, in the Holmby Hills neighborhood of Los Angeles, according to Los Angeles police officer Jimmy N. Gardner. He was 88.” + +But Hugh is doing fine. He was just another victim of those crazy death hoaxes that are prevalent on social media nowadays. Good to know you’re OK, Hef! + +HollywoodLifers, are you glad that Hugh isn’t dead? Let us know! + +– Avery Thompson","1" +"Hugh Hefner Dead Rumors Not True","Sunday night Facebook went crazy with Hugh Hefner dead rumors — but RumorFix can tell you they are not true. + +A bogus website with the url — nbctoday.co — published a story on Sunday with the headline: “Breaking: Playboy Tycoon Hugh Hefner Passes Away at Age of 88.” By the way, the official website for the Today Show is www.today.com. +hugh hefner dead rumors started by bogus website +By 9:45 p.m. Sunday night, the story was shared 130,000 times and the huge influx of traffic shutdown the site at different times during the evening. +The article looked very authentic including fake quotes from a police officer stating Hef had died Sunday morning. The last four lines from the story were directly lifted from Hugh’s Wikipedia profile. +But on Sunday evening, Hugh was very much alive he even tweeted a photo from the Playboy mansion, where it was movie night. He and wife Crystal Hefner watched American Sniper.","1" +"'Rumours of my death are greatly exaggerated': Relax ladies, Hugh Hefner is alive and kicking","Playboy boss Hugh Hefner has denied reports that he is dead and said the rumours were 'greatly exaggerated'.. + +There were recent rumours on the Internet that the 85-year-old had passed away after suffering a heart attack. + +A story claimed Playboy magazine would be printed as usual after his death and a Playmate even spoke out about his life. + +Love: Hugh Hefner with his then fiancee Crystal Harris who he broke up with just days before his wedding. he has since found a new mate + +But soon after the story started to be picked up by several different news outlets, the Playboy founder took to his Twitter page to confirm he is still alive. + +He wrote: 'The rumours of my death are, as Mark Twain observed in a similar situation, greatly exaggerated. I'm very much alive & kicking.' + +Shera Bechard, 27, French-Canadian model and fledgling actress and now Hef's girlfriend + +And to prove how much alive he was, he added: 'I'm lying in bed next to Shera with a big smile on my face, reading tweets about my unexpected demise.' + +Shera Bechard is his 24-year-old girlfriend. + +Many confused tweeters sent messages about his apparent demise with @WolfesMother writing: 'Weird rumour doing the rounds...Hugh Hefner has gone to the big mansion in the sky?! Prob just a rumour, cause he's immortal right?!' + +Moments after his 'death' was reported, the ageing lothario's name was a trending topic on Twitter. + +Hefner has not been out of the papers of late, more recently for his very public break up with his former fiancée Crystal Harris shortly before their wedding was due to take place. + +Harris cites infidelity on Hefner's part, Hefner said it was the other way around. He has since rebounded with Shera Bechard. + +The eternal bachelor did not seem as if he were about to die from heart break however. + +He has already replaced Crystal with more than one girlfriend and he has openly spoken of his excitement about watching an upcoming programme about his wedding-that-almost was. + +Girlfriends: Hef with Kendra Wilkinson, Bridget Marquardt and Holly Madison while promoting E!'s reality TV show Girls Next Door + +After he confirmed that he was still alive, he wrote: 'The guys and I watched an early edit of Hef's Runaway Bride tonight. The fans are going to love it.' + +Hefner launched the Playboy empire in 1953 which he financed by selling his furniture and gathering about $8000 from 25 investors. + +He has been married twice and has four children. At one point, he had seven girlfriends who all lived in the Playboy mansion with him, spawning the hit E! TV series The Girls Next Door, which starred playmates Holly Madison, Kendra Wilkinson-Baskett and Bridget Marquardt. + +Madison and Wilkinson-Baskett went on to star in Holly's World and Kendra, becoming minor stars of their own. + +Kendra recently appeared on Dancing with the Stars.","1" +"Hugh Hefner is not dead: Playboy founder makes it to film night despite mortality rumours","A report emerged yesterday alleging the businessman has been found dead + +Hugh Hefner is very much still alive, despite a hoax concerning his death. + +The Playboy founder, 88, was pictured on a family film night yesterday evening. His wife Crystal Hefner shared the image, along with a quote about the importance of truth - a version of a Mark Twain quote. + +Movie night with the family pic.twitter.com/65QaTvJDNL + +A lie can run around the world before the truth has got it's boots on. #QuoteOfTheDay + +A fake version of NBC called NBCToday.co published a story yesterday which stated that Hefner’s body had been found in the Playboy Mansion. It cited his cause of death of death as natural causes. The story was shared by 273,000 and liked by 77,000. + +Meanwhile, the businessman was busy watching American Sniper with his family merrily enjoying the festive period. + +Tonight's Mansion movie is ""American Sniper."" + +So fear not world, Hefner’s dinosaur-like vision of women as dehumanised sex objects will reign on.","1" +"Hugh Hefner Found Dead But Still Makes It To Family Movie Night","Hugh Hefner was presumed to be dead of natural causes, Sunday, December 28, 2014. Well, that’s the story which was given from a fake sub-medium of NBC called NBCToday.co. This site can’t be called news satire because once “nbctoday.co” is entered as the URL address, it takes the user straight to the fake story. + +Though the story is fake, it spread like wildfire, seemingly without anyone bothering to research the issue himself or herself. + +As of 11 p.m. PST, the Hugh Hefner fake-death story had over 159,000 Facebook shares, along with over 39,000 Likes. Likewise, it has approximately 1800 Twitter shares. Unfortunately, by sunrise, this fake Hugh Hefner story may be trending. + +The story states that police responded to Hugh Hefner’s estate on December 28 at approximately 9 a.m., where Hefner’s body was identified, and he was pronounced dead. + +However, as can be seen from his wife Crystal Hefner”s Twitter update, Hugh is alive and enjoying his time with family. + +Movie night with the family pic.twitter.com/65QaTvJDNL + +— Crystal Hefner (@crystalhefner) December 29, 2014 + +Fortunately, the entire story is fabricated. The only other possibility is that he died and was revived. However, there is nothing on Crystal Hefner’s social media that indicates any kind of scare of such magnitude. + +However, she does offer a witty quote regarding the Hugh Hefner death story. + +A lie can run around the world before the truth has got it’s boots on. #QuoteOfTheDay + +— Crystal Hefner (@crystalhefner) December 29, 2014 + +This statement, along with the “family night” photo, was made only a few hours ago. Whereas, Hugh Hefner was supposed to have been dead around 9 a.m. And unless Hugh has someone managing his social media profiles, he made his own tweets shortly before his wife. + +Tonight’s Mansion movie is “American Sniper.” + +— Hugh Hefner (@hughhefner) December 29, 2014 + +He also retweeted what his wife tweeted afterwards. So sensibly, had Hugh Hefner passed, there would be a buzzing frenzy coming from the Playmates, let alone the rest of the media world. + +It would benefit many to perform a little research before taking things as they come. + +@crystalhefner Dear Crystal Sorry for your loss, may God bless you and your family! + +— L.S. (@UltraGator) December 29, 2014 + +And that comment was after Crystal stated that the story wasn’t true. + +However, there is one thing the anonymous writer got right. Hugh Hefner is 88 years of age. It seems as though he doesn’t plan on letting go of life just yet.","1" +"Man breaks down in tears when a lost recording of his deceased wife resurfaces","After Stan Beaton's wife, Ruby, passed away in 2003, he saved the ""leave a message after the beep"" recording that they had shared. + +The recording was lost after Virgin Mobile conducted some technical work, but with the help of BBC Radio Leeds, the company was able to retrieve the deleted message for Stan — and captured his reaction to hearing it again. + +Stan, 68, is incredulous when he hears the good news. In the video, a reporter tells Stan that it took 10 people a total of three days to retrieve the message. ""That must have cost a fortune!"" Stan exclaims. + +""It's just a wonderful, wonderful sound that I thought was lost forever,"" Stan says. I suppose it's going to be a bit of a PR job now, but thank you Virgin Media."" + +Matt Damon and Ben Affleck confess to Deflategate + +Steve Buscemi is a natural Jan Brady in Snickers’ Super Bowl ad + +NFL's Marshawn Lynch and Rob Gronkowski play 'Mortal Kombat' with Conan + +Here's a TED Talk about sounding smart in a TED Talk","1" +"Mirfield man's tears of joy after lost voicemail of wife retrieved","A husband who thought he had lost a recording of his late wife's voice he had kept for more than 10 years has described the moment the message was recovered as ""wonderful"". + +Stan Beaton, from Mirfield, had kept the voicemail since his wife Ruby's death in 2003, but technical work by Virgin Media meant it was deleted. + +However, the telecoms company has now managed to recover the message. + +Mr Beaton, 68, said: ""They've made this old age pensioner extremely happy."" + +Listening to the message he said: ""It's just a wonderful, wonderful sound that I thought was lost forever. + +""I'm staggered at the lengths they have gone to."" + +Mr Beaton told BBC Radio Leeds the message he had kept since his wife's death from cancer was lost in December. + +He said: ""I've always resisted changing companies because whenever I mentioned that my wife's voice was our voicemail message and would it be retained and each company said no, so that's why I never changed. + +""Sadly it disappeared. I was absolutely devastated by it, but also extremely angry. + +""In the early days [I listened to it] quite often. Basically it came to the point when if I felt low then I would listen to it. + +""In December I learned that it had disappeared. I just could not tell people how it affected me at that time. It really did devastate me."" + +Mr Beaton contacted Virgin who managed to retrieve the message which has now been permanently saved for him. + +Rob Evans, executive director of engineering at Virgin Media, said finding it ""was like searching for a needle in a haystack"", however a team of 11 engineers spent three days tracking it down. + +""The chances of its recovery were slim"" he said, but the missing file containing Ruby's voice was found on Friday. + +""The next morning we called Stan to deliver the good news,"" he said.","1" +"A Husband Breaks Down In Tears After Lost Voicemail Message By His Late Wife Is Recovered","Stan Beaton had kept a voicemail from his late wife for 14 years when an upgrade to his phone line caused the recording to be deleted. + +Work by Virgin Media caused the message, which was left by Beaton’s wife, Ruby, two years before her death in 2003, to be erased last month, the BBC reported. + +The clip was recorded by Ruby to serve as the message people would hear when they called Beaton’s phone. + +The 68-year-old told BBC Radio Leeds: “I’ve always resisted changing companies because whenever I mentioned that my wife’s voice was our voicemail message and would it be retained and each company said no, so that’s why I never changed. + +“Sadly it disappeared. I was absolutely devastated by it, but also extremely angry. + +“In the early days [I listened to it] quite often. Basically, it came to the point when if I felt low then I would listen to it. + +“In December I learned that it had disappeared. I just could not tell people how it affected me at that time. It really did devastate me.” + +Then, having heard Beaton’s story, a team of 11 engineers decided to try to recover the deleted audio recording. + +Rob Evans, executive director of engineering at Virgin Media, told the BBC the task was like searching for a needle in a haystack. + +“The chances of its recovery were slim,” he admitted. + +But after three days of searching, the team found the message on Friday. + +This is Beaton hearing his late wife’s message after it was recovered: + +He said afterwards: “It’s just a wonderful, wonderful sound that I thought was lost forever.” + +“I’m staggered at the lengths they have gone to.” + +“They’ve made this old-age pensioner extremely happy,” he told the BBC. + +Virgin Media is sending Beaton a CD of the recording and the retired forklift truck driver plans on thanking whoever delivers it in style. + +“I’ve got a nice bottle of Glenfiddich with their name on it,” he told the Huddersfield Examiner. + +Following the incident, Virgin pledged to make a series of donations to charities of Beaton’s choice as an apology.","1" +"""This is the recording you thought you'd lost forever""","LONDON -- Stan Beaton lost his wife a decade ago, so he cherished the simple voicemail greeting she had recorded at their home in northern England. + +Then, without warning, it disappeared; deleted by his phone service provider, Virgin Media. + +When Virgin heard about his story, BBC Radio Leeds reports, they set a team of 10 employees to the task of bringing the audio back, and the radio station was on hand this week to surprise Stan with a sound he believed he'd never hear again. + +""That's her,"" he says choking up as he hears his late wife's voice. ""Wonderful. Wonderful."" + +As Stan himself point's out to the BBC Radio reporter sitting in front of him, ""I suppose it's gonna be a bit of a PR job now, but thank you, Virgin Media."" + +He said he was ""staggered"" at the lengths the company had gone to to retrieve it. + +The full video can be found here, and it's worth watching. + +Not all PR stunts are created equal.","1" +"WATCH: Stan Beaton cries tears of joy when phone engineers find treasured voicemail recording of his late wife he thought was lost forever","Widower Stan Beaton cried tears of joy after telephone engineers found the voicemail recording of his late wife he thought was lost forever. + +Stan, 68, of Mirfield, was left devastated in December when an upgrade of his phone line by Virgin Media wiped the precious greeting he had kept for 14 years. + +The retired forklift truck driver took comfort in the voice of wife Ruby, who died of stomach cancer aged 63 in May, 2003. + +Stan had been assured by the phone company that the recording would be saved after the upgrade and the firm was forced to apologise and offered to make donations to Stan’s favourite charities after the blunder. + +Red-faced bosses, though, didn’t stop there and put a team of 10 engineers on the case until the recording was recovered. + +Stan was overcome with emotion when he was played a recording of the voicemail and said: “I felt pure elation and just couldn’t believe it. I thought the recording was gone forever. + +“I can’t thank Virgin Media enough. Putting 10 people on the job must have cost them a fortune. I am staggered by that.” + +Stan, who was married to Ruby for 20 years, often used to listen to the voicemail when he was feeling down. + +He had previously tried to record the message to ensure it wasn’t lost but said: “All I ended up with were blank tapes.” + +Virgin is planning to send a CD of the recording to Stan and the grateful pensioner has a treat for the engineer who finally retrieved the message. + +“I’ve got a nice bottle of Glenfiddich with their name on it,” he said.","1" +"Widower Cries Tears Of Joy After Hearing Late Wife's Voice Again","Ever since his wife Ruby's death in 2003, widower Stan Beaton has treasured the outgoing voicemail message she recorded on their phone -- so much so that he refused to change phone companies out of fear that he might lose it. It was the only way he could still hear the sound of her voice. + +In December, the message was lost during a service upgrade, which left the 68-year-old Brit ""absolutely devastated"" and also ""extremely angry,"" according to the BBC. So he contacted Virgin Media to see if they could retrieve it and -- with the help of nearly a dozen engineers -- they did. + +In the video above, Beaton receives the news that the recording has been recovered. His emotional, teary-eyed reaction couldn't be more heartwarming. + +""It's just a wonderful, wonderful sound that I thought was lost forever,"" he said. + +H/T BuzzFeed + +Keep in touch! Check out HuffPost Weddings on Facebook, Twitter and Pinterest. Sign up for our newsletter here.","1" +"'A wonderful, wonderful sound': Man breaks down after hearing voicemail from his late wife that was lost for 14 years","'They've made this old age pensioner extremely happy' + +A husband who thought the voicemail message of his late wife he had been saving was lost forever has been reunited with it after 14 years, describing hearing her voice again as ""just a wonderful, wonderful sound"". + +Stan Beaton kept the outgoing voicemail message following his wife Ruby's death in 2003, but technical work carried out by Virgin Media caused it to be deleted. + +The telecoms company managed to restore it however, much to the 68-year-old's delight. + +""They've made this old age pensioner extremely happy,"" he said. ""It's just a wonderful, wonderful sound that I thought was lost forever. I'm staggered at the lengths they have gone to."" + +The moment he was played the message back is in the video above, with the Mirfield man becoming overcome with emotion as what under different circumstances would just be a run of the mill voicemail plays. + +""I've always resisted changing companies because whenever I mentioned that my wife's voice was our voicemail message and would it be retained and each company said no, so that's why I never changed,"" he told BBC Radio Leeds. + +""Sadly it disappeared. I was absolutely devastated by it, but also extremely angry. + +""In the early days [I listened to it] quite often. Basically it came to the point when if I felt low then I would listen to it. + +""In December I learned that it had disappeared. I just could not tell people how it affected me at that time. It really did devastate me.""","1" +"Stop Sharing Those Photos of Fancy International School Lunches","By now, you've probably seen (or even shared) the popular set of photos showing delicious, healthful school lunches from around the world, juxtaposed with a photo of the American equivalent, which of course looks like complete dogshit by comparison. Stop sharing it. The images aren't meant to show actual school lunches, and many versions replaced the original U.S. entry, which didn't seem that bad, with an intentionally gross one. + +Before: + +Stop Sharing Those Photos of Fancy International School Lunches + +After: + +Stop Sharing Those Photos of Fancy International School Lunches + +The photo gallery first appeared on the Tumblr of east coast salad chain Sweetgreen, to promote the company's donations toward healthy food for kids. Sweetgreen arranged and shot the meals themselves, based on the contents international lunches—these pretty, well-lit, probably organic versions of the dishes were never served in an actual cafeteria (as you'd think people would be able to tell from the same tray and background in every photo). + +Stop Sharing Those Photos of Fancy International School Lunches + +The meals aren't ""fake,"" they were just presented as representative of the kinds of dishes you'd find in various countries. But things started to get weird when sites began removing that context, replacing Sweetgreen's USA photo with a different one, and adding rants about Michelle Obama. Curse her and her totalitarian program of produce and whole grains! + +See, for example, the Daily Mail's story ""The School Lunches That Shame America,"" which does nothing to imply that the Sweetgreen photos aren't from actual school lunches, and an even worse Conservative Tribune post that was called out on Snopes. At least the Daily Mail version sources the gross mystery meat photo—it's tater tot casserole, by the way—to its origins on Twitter; the Conservative Tribune piece doesn't bother. + +If America should be ashamed of its school lunches, it's not because they don't live up to a bunch of restaurant-quality food porn shot by an actual restaurant. + +[h/t Snopes]","1" +"iOS 8.2 may launch Monday with new health features","Version 8.2 of Apple's iOS mobile operating system could launch as soon as Monday with new and improved health features in tow. That's the same day the company is expected to unveil more details on its Apple Watch. + +The maker of the iPhone and iPad mobile gadgets was close to releasing iOS 8.2 to the public earlier, blog Boy Genius Report said on Thursday, but instead decided to push out one final build to employees and testers. The change log for that build reveals several new features and enhancements in the health department as well as a host of bug fixes, according to BGR. + +The Apple Watch faces an increasingly competitive market already crowded with devices from other players. To entice a wide range of buyers, Apple designed its first wearable as both a smartwatch and a health and fitness monitor. So the health features baked into iOS 8 need to be solid if Apple hopes to capture the fitness crowd. + +Based on the change log, the new and improved health features in iOS 8.2: + +add the ability to select the unit of measurement for body temperature, weight, height, distance and blood glucose, +improve stability when dealing with large amounts of data, +include the ability to add and visualize workout sessions from third-party apps, +address an issue that may have prevented users from adding a photo in Medical ID, +fix units for vitamins and minerals, +fix an issue where health data wouldn't refresh after changes in data source order, +fix an issue where some graphics showed no data values, and +add a privacy setting that enables turning off tracking of steps, distance and flights climbed. +But iOS 8.2 is also designed as a bug squasher. + +Life hasn't exactly been easy for Apple's iOS 8 since it launched last September. The initial version carried a few bugs that were supposed to be resolved a week later in iOS 8.0.1. But that edition came with even more bugs, prompting Apple to quickly pull it and launch 8.0.2. Since then Apple has rolled out versions 8.1, 8.1.2 and 8.1.3, all with some enhancements and bug fixes. + +The bugs and multiple releases may account for the sluggish adoption of iOS 8, which has trailed that of its predecessor but is finally up to 75 percent of all devices that visited the App Store as of last Monday. + +According to BGR, the bug fixes: + +address an issue in Maps that prevented navigating to some favorite locations, +address an issue where the last word in a quick reply message wasn't autocorrected, +fix an issue where duplicate iTunes purchased content could prevent iCloud restore from completing, +resolve an issue where some music or playlists didn't sync from iTunes to the Music app, +fix an issue where deleted audiobooks sometimes remained on the device, +resolve an issue that could prevent call audio from routing to car speakers while using Siri Eyes Free, +fix a Bluetooth calling issue where no audio is heard until the call is answered, +fix a timezone issue where Calendar events appear in GMT, +address an issue that caused certain events in a custom reoccurring meeting to drop from Exchange calendar, +fix a certificate error that prevented configuring an Exchange account behind a third-party gateway, +fix an issue that could cause an organizer's Exchange meeting notes to be overwritten, and +resolve an issue that prevented some Calendar events from automatically showing as ""busy"" after accepting an invite. +The update also promises greater stability for Mail, Music, the Flyover feature in Maps, VoiceOver reliability, and Connectivity with Made for iPhone Hearing Aids. + +A spokeswoman for Apple declined CNET's request for comment. But you can learn more about the Apple Watch and see if iOS 8.2 really will launch Monday by tuning in to CNET's live blog and show starting at 9 a.m. PT Monday.","1" +"Pentagon: 1 weapons bundle seized by militants","WASHINGTON (AP) — The Pentagon is confirming that Islamic State group militants were able to seize one of the 28 bundles of weapons and medical supplies dropped to Kurdish forces on Monday. + +Army Col. Steve Warren, a Pentagon spokesman, says that two of the bundles went astray. One was destroyed by the U.S. The other fell into enemy hands and included small weapons, hand grenades, medical supplies and ammunition. Warren said it appears the wind caused the parachute to go off course. + +He says the weapons in the bundle are not enough to give the enemy any type of advantage. + +Activists said Tuesday the weapons were seized by the extremist fighters. A video uploaded by a media group loyal to IS militants showed the extremists with the pallet of weapons and other materials.","1" +"U.S. arms airdrop fell into ISIS hands: Pentagon","The Pentagon confirmed that a cache of weapons fell into the hands of ISIS.","1" +"ISIS Claims to Have Intercepted Supplies From U.S. Airdrop","Islamic State (ISIS) militants claim to have captured a supply bundle dropped by U.S. forces near the northern Syrian town of Kobani. Video posted to a YouTube channel associated with ISIS shows them rifling through packages containing dozens of grenades. + +The supply package was apparently one of many intended for Kurdish fighters who have been battling ISIS militants for control of the strategically important town for weeks. The footage has not been independently verified. + +According to Pentagon Press Secretary Rear Adm. John Kirby, the majority of supplies were safely delivered to Kurdish forces, which have been supported by a U.S.-led coalition as they defend the town. However, Kirby said that at least one supply package may have fallen into the hands of the Islamic State. + +""We are aware that one bundle was destroyed [via a video],"" said Kirby. ""Analysts are working as fast as they can to validate it."" + +U.S. forces airdropped a total of 27 bundles containing weapons, ammunition and medical supplies early Monday. The supplies were provided by Kurdish authorities. + +Kobani, located just yards from the Turkish border, has been the scene of an intense battle between Kurdish forces and ISIS militants, who attacked the area in late September. + +Have something to add to this story? Share it in the comments.","1" +"Watch: ISIS Claims to Have Captured U.S. Airdropped Weapons","In a new video, ISIS shows American-made weapons it says were intended for the Kurds but actually were air dropped into territory they control. + +At least one bundle of U.S. weapons airdropped in Syria appears to have fallen into the hands of ISIS, a dangerous misfire in the American mission to speed aid to Kurdish forces making their stand in Kobani. + + + +Source: The Daily Beast. Read full article. (link)","1" +"Video: Islamic State Claims to Have Captured US Weapons Airdrop Near Kobane","Islamic State (IS) fighters may have captured weapons airdropped by the US near the Syrian town of Kobane, intended for the Kurdish forces defending it against the jihadists' onslaught. + +A video posted on YouTube on Tuesday by a group calling itself ""A3maq News"" purports to show airdropped supplies in the hands of the extremist group. The footage shows a masked and armed militant examining a package attached to a parachute. Later, he looks into crates containing various munitions, including RPG rounds and grenades. + +The video could not immediately be independently verified, but A3maq News has previously posted IS-linked content and the some of the weapons seen in the video appear to match those possessed by Iraq's Kurdistan Regional Government (KRG), which supplied the arms. + +The grenades seen at 1:28 in the video are reported to be German-made. Berlin sent 10,000 grenades to Iraqi Kurdistan in August as part of a consignment of military aid provided to the KRG's peshmerga fighters, according to publicly available German government documents. + +Additionally, US Central Command confirmed in a statement on Monday that one airdropped bundle had missed its target,. However, CentCom said it had been destroyed in a follow-up airstrike to stop it falling into enemy hands. + + +American C-130 planes delivered weapons, ammunition and medical supplies provided by the KRG to People's Protection Units (YPG) fighters at dawn on Sunday, according to a CentCom statement. The operation was intended to ""enable continued resistance against ISIL's attempts to overtake Kobane,"" CentCom added, using the former name for the Islamic State. + +YPG spokesperson Redur Xelil told Reuters that the weapons would ""help greatly"" in the fight against IS. ""The military assistance dropped by American planes at dawn on Kobane was good and we thank America for this support,"" he said. + +Kobane is surrounded on three sides by IS and is bordered to the north by Turkey. The Turkish government has thus far refused repeated requests to open a land corridor allowing humanitarian and military supplies into the town, leading to accusations of tacit complicity in the IS assault on the Kurds, whose struggle for greater autonomy has long been a thorn in Ankara's side. However, on Monday it announced that it would allow Iraqi Kurdish fighters to cross the border to the town. + +The airdrops were the first of their kind, but the US launched a series of airstrikes on IS targets in August, then extended operations into Syria in September. American planes have now carried out more than 135 airstrikes against IS in Kobane, according to the Centcom statement, which it says are indicated to have ""slowed ISIL [S] advances into the city, killed hundreds of their fighters and destroyed or damaged scores of pieces of ISIL combat equipment and fighting positions."" + +Follow John Beck on Twitter: @JM_Beck","1" +"ISIS Claims To Have Captured US Airdrop Weapons","A video released by the Islamic State on Tuesday allegedly shows a stray weapons bundle from the United States that missed its target in Kurdish-controlled areas near Kobani, Syria and instead fell into the hands of IS (ISIS or ISIL) militants. + +Sunday evening, the Pentagon confirmed that the U.S. military had conducted a weapons drop to supply Syrian Kurds fighting IS militants in Kobani with small arms and supplies. + +Pentagon Spokesperson Rear Adm. John Kirby also confirmed Monday that one of the bundles had missed its target, but that it had been destroyed so that “ISIL terrorists couldn’t get to it.” + +The video, released by unofficial IS news agency Aamaq, bears the Arabic title: “Arms and ammunition delivered by American planes fell in areas controlled by the Islamic State in Kobani.” + +The video shows an IS militant rifling through the weapons and supplies, which include grenades, explosive canisters, and RPG rounds. + +“Thank God, the Mujahideen have them now,” the masked militant said. + +Here is the full video: + +This article originally appeared at The Washington Free Beacon. Copyright 2014. Follow The Washington Free Beacon on Twitter.","1" +"ISIS: We have our hands on weapons, ammo air-dropped by U.S.","In a new video posted online, the Islamic State of Iraq and Syria (ISIS) claims it has captured weapons and ammunition dropped by the U.S. military that was intended for Kurdish forces defending an embattled Syrian city near the Turkish border. + +The airdrops Sunday were the first of their kind and followed weeks of U.S. and coalition airstrikes in and near Kobani. + +In the video, ISIS claims some of the weapons and ammunition was air-dropped by mistake on its positions in Kobani. + + + +A senior administration official told CBS News on Sunday that the majority - but not necessarily all - of the bundles dropped by U.S. forces appeared to ‎make it to their intended targets. + +""We are still assessing the completion of the mission but every indication that we have is that the vast majority of those bundles were successfully delivered to Kurdish forces,"" the official said. ""We're still working through a complete assessment right now.‎"" + +Because the drops were made overnight, the Pentagon could not say with 100 certainty that they reached their intended destinations. + +Idris Nassan, a senior Kurdish official from Kobani who is now in the Turkish town of Mursitpinar, confirmed the Kurdish fighters received the airdrop and asked for more weapons. + +""We are not in need of fighters. We are able to defeat the terrorists of ISIS if we have weaponry - enough weaponry and enough ammunition,"" he told The Associated Press. + +Kurdish fighters tweeted messages of appreciation along with photos that apparently show that some of the air-dropped cargo - including M-16 guns and medical supplies - did reach its intended recipients.","1" +"Pentagon: ISIS seized materials airdropped to Kurds","The Pentagon has confirmed that the weapons were indeed seized by ISIS.","1" +"Turkish president says American weapons drop for Kurdish fighters was 'wrong' after supplies end up in the hands of ISIS","Turkey's president has said it was wrong for the United States to deliver military supplies to Kurdish fighters defending the Syrian city of Kobane after some of the weapons ended up in ISIS' hands. + +The Pentagon claims the vast majority of the U.S. supplies dropped over the weekend had reached the Kurdish fighters despite an online video showing jihadists in possession of a bundle. + +Tayyip Erdogan today said the mission had been a mistake - adding that he could not understand why the U.S. was so keen to defend Kobane as there were no longer any citizens in the city. + +The weapons drop had been considered a highly sensitive subject for Turkey, who says the Kurdish fighter provided with American weapons are linked to the Kurdish People’s Protection Unit (YPG) – a group Ankara considers to be a terrorist organisation. + +Scroll down for video + +Error: Turkish president Tayyip Erdogan said it was wrong for the United States to deliver military supplies to Kurdish fighters defending the Syrian city of Kobane after some of the weapons ended up in ISIS' hands + +A still from an Islamic State (ISIS) video, purportedly shows an IS militant displaying the content of a crate carrying grenades near the town of Ain al-Arab, known by the Kurds as Kobane, on the Syria-Turkey border + +Speaking at a news conference in Ankara today, Erdogan described the weapons drop as a mistake. + +'What was done here on this subject turned out to be wrong. Why did it turn out wrong? Because some of the weapons they dropped from those C130s were seized by ISIL,’ he said, using an alternative acronym for ISIS. + +Asked about a plan for Turkey to facilitate the passage of Iraqi Kurdish peshmerga fighters to Kobane to help in its defence, Erdogan said he proposed this move in a telephone call with Barack Obama at the weekend. + +'I have difficulty understanding why KobanE is so strategic for them because there are no civilians there, just around 2,000 fighters,' Erdogan said. + +'At first they didn't say yes to peshmergas, but then they gave a partial yes and we said we would help.' + +He added that talks were continuing among officials on the details of the peshmergas' transit through Turkey. + +One Turkish journalist close to the government said on Wednesday some 500 of them were expected to cross into Kobani this weekend + +A U.S. military airdrop of weapons meant for Kurdish fighters fell into the hands of their jihadist foes near the Syrian battleground town of Kobane, the Syrian Observatory for Human Rights said + +Earlier, the US Defense Department said is investigating video footage appearing to show Islamic State fanatics with at least one cache of weapons airdropped by coalition forces that was meant for Kurdish militiamen battling the extremist group in a border town. + +The cache of weapons included hand grenades, ammunition and rocket-propelled grenade launchers, according to a video uploaded by a media group loyal to the Islamic State (ISIS) group. + +The video appeared authentic and corresponded to The Associated Press' reporting of the event. + +The Britain-based Syrian Observatory for Human Rights, which bases its information on a network of activists on the ground, said the militants had seized at least one cache. + +The caches were airdropped early Monday to Kurds in the embattled Syrian town of Kobane that lies near the Turkish border. + +The caches were airdropped early Monday to Kurds in the embattled Syrian town of Kobani that lies near the Turkish border + +A container filled with meals ready to eat and fresh water being dropped from a C-130 Hercules during an operational resupply airdrop near the area of Bayji, Iraq + +The militant group has been trying to seize the town for over a month now, causing the exodus of some 200,000 people from the area into Turkey. While Kurds are battling on the ground, a U.S.-led coalition is also targeting the militants from the air. + +Yesterday ISIS loyalists on social media posted sarcastic thank you notes to the United States, including one image that said 'Team USA.' + +But the lost weapons drop was more an embarrassment than a great strategic loss. + +The Islamic State militants already possess millions of dollars-worth of U.S. weaponry that they captured from fleeing Iraqi soldiers when the group seized swaths of Iraq in a sudden sweep in June. + +On Tuesday, the U.S. Central Command said U.S. military forces conducted four airstrikes near Kobani that destroyed IS fighting positions, an IS building and a large IS unit. + +Also Tuesday, Syrian government airstrikes hit a rebel-held town along the country's southern border with Jordan, killing at least eight people. + +Militant: ISIS has been trying to seize the town for over a month now, causing the exodus of some 200,000 people from the area into Turkey + +Checkpoints: The Islamic State already has millions of dollars-worth of U.S. weaponry that they captured from fleeing Iraqi soldiers when the group seized swaths of Iraq in a sudden sweep in June + +Activists with the Local Coordination Committees and the Observatory said the number of those killed was likely to rise as there are more victims under the rubble. + +The LCC said Syrian government planes dropped crude explosives-laden canisters on the town of Nasib on the Syria-Jordan border. + +The airstrikes are part of battles between Syrian government forces and Islamic rebel groups for control of the area. + +Syrian government forces have been heavily bombing rebel areas in recent weeks, while the U.S-led coalition has been conducting airstrikes against Islamic State militants elsewhere in Syria.","1" +"US probing claims ISIS fighters seized airdropped weapons meant for Kurds","mboxCreate('FoxNews-Politics-Autoplay-Videos-In-Articles'); + +U.S. military officials say they are investigating claims that Islamic State fighters seized a cache of weapons that were airdropped by U.S.-led coalition forces and meant for Kurdish militiamen. + +A video uploaded by a media group loyal to the Islamic State showed a cache of weapons including hand grenades, ammunition and rocket-propelled grenade launchers. Their claims would appear to correspond with those of the Britain-based Syrian Observatory for Human Rights, which said the militants had seized at least one cache. + +U.S. officials said Tuesday they could not confirm the video's authenticity but are looking into the claims. + +""We just don't know. We're still looking at it,"" Pentagon spokesman Rear Adm. John Kirby said when asked about the video, while stressing that the ""vast majority"" of supplies ended up in the right hands. + +The supplies were airdropped early Monday to Kurds in the embattled Syrian town of Kobani that lies near the Turkish border. The militant Islamic State has been trying to seize the town for over a month now, causing the exodus of some 200,000 people from the area into Turkey. While Kurds are battling on the ground, a U.S.-led coalition is also targeting the militants from the air. + +In all, 28 bundles of equipment -- including medical supplies, weapons and ammunition -- were dropped. The Pentagon says 27 bundles were received. + +According to Pentagon spokesman Col. Steve Warren, ""one of those bundles drifted off course."" But he said ""we subsequently destroyed it with an airstrike."" + +On Tuesday, though, Islamic State loyalists on social media posted sarcastic thank you notes to the United States, including one image that said ""Team USA."" + +Kirby acknowledged the conflicting accounts. ""We're aware that one bundle did not make it into the right hands and you saw the CENTCOM release indicating that they destroyed it from the air,"" he said. ""All of that doesn't take away from the notion that this video is out there and that it could in fact be that bundle. We just don't know."" + +The lost weapons drop was more an embarrassment than a great strategic loss. The Islamic State militants already possess millions of dollars-worth of U.S. weaponry that they captured from fleeing Iraqi soldiers when the group seized swaths of Iraq in a sudden sweep in June. + +On Tuesday, U.S. Central Command said U.S. military forces conducted four airstrikes near Kobani that destroyed Islamic State fighting positions, a building and a large Islamic State unit. + +Also Tuesday, Syrian government airstrikes hit a rebel-held town along the country's southern border with Jordan, killing at least eight people. + +Activists with the Local Coordination Committees and the Observatory said the number of those killed was likely to rise as there are more victims under the rubble. + +The LCC said Syrian government planes dropped crude explosives-laden canisters on the town of Nasib on the Syria-Jordan border. + +The airstrikes are part of battles between Syrian government forces and Islamic rebel groups for control of the area. + +Syrian government forces have been heavily bombing rebel areas in recent weeks, while the U.S.-led coalition has been conducting airstrikes against Islamic State militants elsewhere in Syria. + +Fox News' Justin Fishel and Greg Palkot and The Associated Press contributed to this report.","1" +"Isis Syria News: Video Shows US Airdropped Weapons and Grenades 'Captured by Islamic State'","A pro-Isis news agency has released a video purportedly showing military aid airdropped by US forces and meant for Kurdish forces defending Kobani being captured by Islamic State (Isis) militants instead. + +RelatedCanada: Isis 'Lone Wolf' Killer Martin Couture Rouleau Mows Down Soldiers with CarSyria: Isis Stone Woman to Death for Adultery with Father's Help in Hama [GRAPHIC VIDEO]Iraqi PM Haider al-abadi Discusses Isis Threat With Hassan Rohani in TehranAl-Qaida Magazine Resurgence Calls for Terrorist Attacks on Oil Tankers and McDonald's BoycottTurkey to Allow Kurdish Peshmerga Forces Passage to Defend Kobani from Isis + +The two-minute long footage was allegedly filmed in the outskirts of the Syrian Kurdish-majority town, which has been besieged by jihadists after a fierce military assault. + +In the clip, armed Isis fighters show several boxes containing weapons, munitions and grenades that were allegedly airdropped by US C-130 cargo planes and were from the Iraqi Kurdistan government. German-manufactured grenades can be also seen in the video, which was published by pro-Isis Amaq News agency. + +On Sunday, the US military said it had air dropped weapons, ammunition and medical supplies to Kurdish forces defending Kobani. In a statement, the US central command said US C-130 cargo planes made multiple drops of arms and supplies that were provided by Kurdish authorities in Iraq, in order to allow Kurdish forces to resist Isis assault and take full control of Kobani. + +According to Lahur Jangi Talabani, the director of the intelligence agency of the Kurdistan government, 24 tons of small arms and ammunition and 10 tons of medical supplies were delivered to Kurdish forces in three US planes. + +RelatedIsis Syria Photos: Fire Balls Explode in Kobani as the Battle Rages On","1" +"Turkish Leader Says U.S. Airdrop Aided ISIS Militants","Erdogan argued that the Turkish weapons drop has harmed the fight against ISIS.","1" +"Cold Turkey","Turkey expressed dismay that the weapons intended for the Kurds ended up with ISIS.","1" +"ISIS Video: America’s Air Dropped Weapons Now in Our Hands","In a new video, ISIS shows American-made weapons it says were intended for the Kurds but actually were air dropped into territory they control. + +At least one bundle of U.S. weapons airdropped in Syria appears to have fallen into the hands of ISIS, a dangerous misfire in the American mission to speed aid to Kurdish forces making their stand in Kobani. + +An ISIS-associated YouTube account posted a new video online Tuesday entitled, “Weapons and munitions dropped by American planes and landed in the areas controlled by the Islamic State in Kobani.” The video was also posted on the Twitter account of “a3maq news,” which acts as an unofficial media arm of ISIS. The outfit has previously posted videos of ISIS fighters firing American made Howitzer cannons and seizing marijuana fields in Syria. + +ISIS had broadly advertised its acquisition of a broad range of U.S.-made weapons during its rampage across Iraq. ISIS videos have showed its fighters driving U.S. tanks, MRAPs, Humvees. There are unconfirmed reports ISIS has stolen three fighter planes from Iraqi bases it conquered. + +The authenticity of this latest video could not be independently confirmed, but the ISIS fighters in the video are in possession of a rich bounty of American hand grenades, rounds for small rockets, and other supplies that they will surely turn around and use on the Kurdish forces they are fighting in and around the Turkish border city. + +On Monday, White House Deputy National Security Advisor Ben Rhodes said the U.S. government was confident that the emergency airdropped supplies for the Kurdish forces near Kobani were falling into the right hands. + +“We feel very confident that, when we air drop support as we did into Kobani… we’ve been able to hit the target in terms of reaching the people we want to reach,” Rhodes told CNN. “What I can assure people is that, when we are delivering aid now, we focus it on the people we want to receive that assistance. Those are civilians in need. Those are forces that we’re aligned with in the fight against ISIL [the government’s preferred acronym for ISIS], and we take precautions to make sure that it’s not falling into the wrong hands.” + +Rhodes was responding to questions about a Monday report in The Daily Beast that U.S. humanitarian aid was flowing into ISIS controlled areas near Kobani by truck. That aid was mostly food and medical supplies, not the kind of lethal weapons in the new ISIS video. + +Senior administration officials said Sunday that three American planes dropped a total of 27 bundles near Kobani and more U.S. air drops could come as part of the joint U.S.-Iraqi effort to aid Kurdish fighters in the Kobani area. The supplies were provided by Kurdish authorities, the official said. + +In the new footage, the weapons appear to be U.S. made. There have also been at least 135 air strikes against ISIS in the area, according to the State Department. + +The airstrikes and air drops appear to be having an impact. The Daily Beast’s Jamie Dettmer, reporting from the Syrian border, said the morale in Kobani has shifted in the last 24 hours. But ISIS continues to hold major swaths of territory in and around Kobani, despite widespread media reports to the contrary. And the civilians there are suffering, badly. + +“I think what this represents is the President recognizes this is going to be a long-term campaign against ISIL; and that we need to look for whatever opportunity we can find to degrade that enemy and to support those who are fighting against ISIL on the ground,” a senior administration official told reporters.","1" +"Pentagon: ISIS Got U.S. Weapons Package","The Pentagon admitted on Wednesday that ISIS did in fact get its hands on one of the 28 bundles of weapons and medical supplies that the U.S. dropped to Kurdish forces on Monday. Two of the bundles had missed their marks, but one was destroyed by the U.S. According to a Pentagon spokesman, the wind caused the parachute to go off course. The spokesman also stressed that the weapons will not give ISIS any advantage. Past reports have indicated that humanitarian and military aid has made its way into the hands of the terrorist group.","1" +"Isis claims it has US airdrop of weapons","Pentagon investigating claims but admits one load missing and it would be embarrassing if it ended up in terror group’s hands + +A US airdrop of arms to besieged Kurds in Kobani appears to have missed its target and ended up in the hands of Islamic State (Isis) militants. + +Video footage released by Isis shows what appears to be one of its fighters for in desert scrubland with a stack of boxes attached to a parachute. The boxes are opened to show an array of weapons, some rusty, some new. A canister is broken out to reveal a hand grenade. + +The Pentagon said it was investigating the claim but admitted that one of its airdrops had gone missing. If confirmed, it would be an embarrassment for the US, given the advanced precision technology available to its air force. + +The seemingly bungled airdrop comes against a steady stream of US-supplied weapons being lost to Isis forces, mainly from the dysfunctional Iraqi army. Isis is reported to have stolen seven American M1 Abrams tanks from three Iraqi army bases in Anbar province last week. + +The Pentagon spokesman, Rear Admiral John Kirby, told reporters that analysts at Centcom headquarters in Tampa, Florida, were examining the video. “We’re still taking a look at it and assessing the validity of it,” he said. “So I honestly don’t know if that was one of the one dropped.” + +The US began dropping munitions, supplied by Kurdish authorities in the semi-autonomous region of northern Iraq, to their compatriots in Kobani, which sits close to the Iraqi-Turkish border; Isis fighters have encircled much of the town. + +Kirby confirmed the weapons shown in the video were the kind that were dropped. “So it’s not out of the realm of the possibility in that regard,” he said. + +“I do want to add, though, that we are very confident that the vast majority of the bundles did end up in the right hands. In fact, we’re only aware of one bundle that did not.” + +The airdrops were carried out by three C-130 planes. The video shows a man in camouflage clothes and balaclava looking through the boxes of munitions. He says they were dropped by US forces and had been intended for the Kurds. He described them as the spoils of war. + +As well as grenades, the boxes appeared to contain parts for rocket-propelled grenades. Some of the equipment appears to be east European in origin, which might seem odd given the weapons were dropped by Americans, but the munitions were supplied by the Kurdish authorities who had been stocking up. + +Kirby said the situation in Kobani remained tense, with Kurdish forces in control of most of the city. The US-led coalition has mounted more than 130 air strikes round the town in an effort to stop Isis taking complete control. + +While the US has carried out air strikes in Kobani, cloud cover last week prevented them hitting much of the rest of Iraq, particularly around the contested Mosul dam. If the dam was to fall to I, it would provide huge leverage for the group, a strategic loss with potentially catastrophic consequences. + +Britain has been supplying the Kurdish semi-autonomous region with weapons but so far supplies have been limited. The Kurds report receiving about 40 heavy machine guns but say they badly need heavier equipment, in particular armoured vehicles.","1" +"Isis claims it has US airdrop of weapons intended for Kurds","· Pentagon investigating claims but admits one load missing and it would be embarrassing if it ended up in terror group’s hands· Turkey criticises arms airdrops saying the strategy will never lead to desired results + +A US airdrop of arms to besieged Kurds in Kobani appears to have missed its target and ended up in the hands of Islamic State (Isis) militants. + +Video footage released by Isis shows what appears to be one of its fighters for in desert scrubland with a stack of boxes attached to a parachute. The boxes are opened to show an array of weapons, some rusty, some new. A canister is broken out to reveal a hand grenade. + +The Pentagon said it was investigating the claim but admitted that one of its airdrops had gone missing. If confirmed, it would be an embarrassment for the US, given the advanced technology available to its air force. + +The seemingly bungled airdrop comes against a steady stream of US-supplied weapons being lost to Isis forces, mainly from the dysfunctional Iraqi army. Isis is reported to have stolen seven American M1 Abrams tanks from three Iraqi army bases in Anbar province last week. + +A spokesman for the Pentagon, Rear Admiral John Kirby, told reporters that analysts at Centcom headquarters in Tampa, Florida, were examining the video. “We’re still taking a look at it and assessing the validity of it,” he said. “So I honestly don’t know if that was one of the one dropped.” + +Turkey’s president Recep Tayyip Erdogan criticised the US air drops as a whole, saying it was “wrong” that weapons had indeed fallen into the hands of Isis, as well as the Kurdish fighters they were intended for. Turkey’s government sees the fighters as part of the Syrian arm of the Kurdistan Workers Party (PKK), a faction that has battled for self-rule in Turkey for over three decades. + +“It has become clear that this was wrong,” Erdogan told reporters in Ankara. “It’s impossible to achieve results with such an operation,” he added. + +In an abrupt shift, Turkey agreed on Monday to allow Iraqi Kurdish fighters to cross its territory and reinforce fellow Kurds in the besieged town of Kobani, but did not comment on whether it backed the air drops. + +The US has dropped munitions, supplied by Kurdish authorities in the semi-autonomous region of northern Iraq, to their compatriots in Kobani, which sits close to the Iraqi-Turkish border; Isis fighters have encircled much of the town. + +Kirby confirmed the weapons shown in the video were the kind that were dropped. “So it’s not out of the realm of the possibility in that regard,” he said. + +“I do want to add, though, that we are very confident that the vast majority of the bundles did end up in the right hands. In fact, we’re only aware of one bundle that did not.” + +The airdrops were carried out by three C-130 planes. The video shows a man in camouflage clothes and balaclava looking through the boxes of munitions. He says they were dropped by US forces and had been intended for the Kurds. He described them as the spoils of war. + +As well as grenades, the boxes appeared to contain parts for rocket-propelled grenades. Some of the equipment appears to be east European in origin, which might seem odd given the weapons were dropped by Americans, but the munitions were supplied by the Kurdish authorities who had been stocking up. + +Kirby said the situation in Kobani remained tense, with Kurdish forces in control of most of the city. The US-led coalition has mounted more than 130 air strikes round the town in an effort to stop Isis taking complete control. + +While the US has carried out air strikes in Kobani, cloud cover last week prevented them hitting much of the rest of Iraq, particularly around the contested Mosul dam. If the dam was to fall to Isis, it would provide huge leverage for the group. + +Britain has been supplying the Kurdish semi-autonomous region with weapons but so far supplies have been limited. Kurds report receiving about 40 heavy machine guns but say they need heavier equipment, in particular armoured vehicles.","1" +"Isis apparently takes control of US weapons airdrop intended for Kurds","· Pentagon admits one of 28 loads missing and blames wind· Turkey criticises arms airdrops saying the strategy will never lead to desired results + +The Pentagon admitted on Wednesday that one of the airdrops of weapons intended for Kurds in the besieged Syrian town of Kobani almost certainly ended up in the hands of the Islamic State (Isis) fighters. + +The Pentagon blamed the wind for possibly blowing the supplies off course and argued that one cache was not enough to make a significant difference to Isis. + +Video footage released by Isis shows what appears to be one of its fighters in desert scrubland with a stack of boxes attached to a parachute. The boxes are opened to show an array of weapons, some rusty, some new. A canister is broken out to reveal a hand grenade. Other equipment appeared to be parts for rocket-propelled grenades. + +The Pentagon said the pallet of weapons was one of 28 dropped, not six as previously reported. + +US defence spokesman Army Lieutenant Colonel Steve Warren said: “One bundle worth of equipment is not enough equipment to give the enemy any type of advantage at all. It’s a relatively small amount of supplies. This is stuff [Isis] already has.” + +The Pentagon cleared up some confusion about a cache going astray on Sunday that had subsequently been destroyed in a US strike, once it had been realised it was in danger of falling into Isis hands. + +Warren said two caches had gone astray but the air force had managed to destroy one. A steady stream of US-supplied weapons are being lost to Isis forces, mainly from the dysfunctional Iraqi army. Isis is reported to have stolen seven American M1 Abrams tanks from three Iraqi army bases in Anbar province last week. + +A spokesman for the Pentagon, Rear Admiral John Kirby, told reporters that analysts at Centcom headquarters in Tampa, Florida, were examining the video. “We’re still taking a look at it and assessing the validity of it,” he said. “So I honestly don’t know if that [box] was one of the ones dropped.” he said. + +Turkey’s president, Recep Tayyip Erdoğan, criticised the airdrops strategy, saying it was “wrong” that weapons had fallen into the hands of Isis, as well as the Kurdish fighters they were intended for. + +Turkey’s government sees the fighters as part of the Syrian arm of the Kurdistan Workers Party (PKK), a faction that has battled for self-rule in Turkey for over three decades. + +“It has become clear that [the airdrops are] wrong,” Erdoğan told reporters in Ankara. “It’s impossible to achieve results with such an operation,” he added. + +In an abrupt shift, Turkey agreed on Monday to allow Iraqi Kurdish fighters to cross its territory and reinforce fellow Kurds in the besieged town of Kobani, but did not comment on whether it backed the airdrops. + +The US has dropped munitions, supplied by Kurdish authorities in the semi-autonomous region of northern Iraq, to their compatriots in Kobani, which sits close to the Iraqi-Turkish border; Isis fighters have encircled much of the town. + +Kirby confirmed the weapons shown in the video were the kind that were dropped. “So it’s not out of the realm of the possibility in that regard,” he said. + +“I do want to add, though, that we are very confident that the vast majority of the bundles did end up in the right hands. In fact, we’re only aware of one bundle that did not.” + +The airdrops were carried out by three C-130 planes. The video shows a man in camouflage clothes and balaclava looking through the boxes of munitions. He says they were dropped by US forces and had been intended for the Kurds. He described them as the spoils of war. + +As well as grenades, the boxes appeared to contain parts for rocket-propelled grenades. Some of the equipment appears to be east European in origin, which might seem odd given the weapons were dropped by Americans, but the munitions were supplied by the Kurdish authorities who had been stocking up. + +Kirby said that the situation in Kobani remained tense, with Kurdish forces in control of most of the city. The US-led coalition has mounted more than 130 air strikes round the town in an effort to stop Isis taking complete control. + +While the US has carried out air strikes in Kobani, cloud cover last week prevented them hitting much of the rest of Iraq, particularly around the contested Mosul dam. If the dam was to fall to Isis it would provide huge leverage for the group. + +Britain has been supplying the Kurdish semi-autonomous region with weapons but so far supplies have been limited. Kurds report receiving about 40 heavy machine guns but say they need heavier equipment, in particular armoured vehicles.","1" +"U.S. accidentally delivered weapons to the Islamic State by airdrop, militants say","This post has been updated with additional reporting. + +The Islamic State has released a new video in which it brags that it recovered weapons and supplies that the U.S. military intended to deliver to Kurdish fighters, who are locked in a fight with the militants over control of the Syrian border town of Kobane. + +The SITE Intelligence Group, which tracks jihadist social media accounts, drew attention to the video Tuesday. At one point, it appears to show a masked militant raking his hands through a crate filled with hand grenades. + +A U.S. Central Command spokesman said he was looking into the reports. In a news release Monday, U.S. military officials acknowledged launching one airstrike near Kobane that they said destroyed “a U.S. airdrop of Kurdish supplies” to prevent “these supplies from falling into enemy hands.” + +“All other resupply bundles were successfully delivered,” the CENTCOM news release said, without specifying what was in the shipment. + +Rear Adm. John Kirby, the Pentagon press secretary, said Tuesday afternoon that analysts were working to determine what happened. The Defense Department is aware that one bundle didn’t make it into the right hands, and is not sure whether the one that appears in the video is the same one CENTCOM already reported destroying. + +On Tuesday, the U.S. military announced another four airstrikes near Kobane, saying it hit Islamic State fighting positions, a building occupied by the militants, and “a large ISIL unit,” using one of the acronyms for the group. The U.S. has launched dozens of airstrikes around Kobane in the last week, as the militants besiege the town. + +The incident highlights the difficulty in making sure all airdrops are accurate, even with GPS-guided parachutes that the Air Force commonly uses. Airdrops of food and water to religious minorities trapped on mountain cliffs in northern Iraq in August hit the mark about 80 percent of the time, Pentagon officials said at the time. + +The United States began dropping weapons, ammunition, medical supplies and other equipment to fighters defending Kobane on Sunday night, in part because Turkey would not allow Kurdish fighters to cross its borders into Kobane to bolster the town’s defenses. Turkish officials said they changed their mind on Monday, but the deal is tentative and depends on whether separate Kurdish groups can resolve longterm differences to confront the Islamic State. + +Related on Checkpoint: Does this mysterious video show the Islamic State flying a fighter jet? + +U.S. airstrikes in Syria are now dwarfing those in Iraq, thanks to the fight for one town + +Operation against the Islamic State to be called Inherent Resolve + +Islamic State’s shootdown of an Iraqi helicopter amplifies fears of shoulder-fired missiles","1" +"An accidental delivery of arms to the Islamic State and the problem with airdrops","There it was in the middle of a field, baking in the sun: a cache of grenades, rockets and guns. The trove was attached to a big black parachute and, as the camera focused in on the shipment, it seemed for a moment abandoned. Then you see the masked man, who sermonized for the occasion. An American airdrop of arms, he said, which had been intended for Kurdish fighters defending the city of Kobane, had fallen into the hands of the Islamic State. + +“These are some of the American aid [items] that were dropped for the atheists in the” Kurdistan Workers’ Party,” the militant said in a video uploaded to jihadist social media accounts and initially reported by SITE Intelligence Group. “Ammunition, military equipment, additional equipment — these are some of the military weapons. The American forces dropped [them] … Praise be to Allah. Spoils for the mujahideen.” + +News of the accidental airdrop, which the Associated Press corroborated and the Syrian Observatory for Human Rights confirmed, brought fresh criticism to a military tactic — the air drop — officials said has become substantially more accurate in the past few decades, but is still evidently prone to screw-ups. And those screw-ups have popped up several times so far in the battle against the Islamic State in Iraq and Syria, underscoring the dangers of trusting the winds to carry valuable resources to their targets. + +In early August, the U.S. military dropped more than 7,000 gallons of water and 36,000 packaged meals onto a barren mountain near Sinjar, the hiding spot for nearly 40,000 Yazidis who fled the Islamic State under threat of genocide. Many packages reached their intended targets — the Department of Defense estimated 80 percent — but not all of them did. “Iraqi officials said that much of the U.S. aid had been ‘useless’ because it was dropped from 15,000 feet without parachutes and exploded on impact,” wrote journalist Jonathan Krohn, who claimed to be the first Western journalist on the scene. The Washington Post’s Liz Sly agreed, saying the drops “apparently went awry.” + +Then NBC News reported late last month Iraqi military pilots accidentally dropped food, water and weapons to Islamic State fighters instead of to their own soldiers, who were battling to retain control of Anbar province. “Some pilots, instead of dropping these supplies over the area of the Iraqi army, threw it over an area that is controlled by ISIS fighters,” Hakim al-Zamili said, using another name for the Islamic State. “Those soldiers were in deadly need of these supplies, but because of the wrong plans of the commanders in the Iraqi army and lack of experience of the pilots, we in a way or another helped ISIS fighters to kill our soldiers.” + +Another general sheepishly added: “Yes, that’s what had happened.” + +The embarrassing anecdotes feed into the complicated history of the airdrop, which still carries risks despite being honed over decades with technological advancements such as GPS-guided parachutes. “There’s no way you can predict who may end up with those weapons, and who is going to use them, or how they are going to use them,” Greg Myre of the Middle East Institute told the Daily Sabah. “That is one of the risks you have to take.” + +It was a risk Bill Clinton was willing to take in 1993. That was the year he ordered an airdrop of tens of thousands of humanitarian packages over eastern Bosnia, despite the “military consistently arguing against involving U.S. troops in airdrops in hostile zones, given the fact that the accuracy of the drops is questionable,” the Associated Press then reported. The brass turned out to be right. + +One major problem laid bare during that mission, military scientists later said, was what they called “wind drift.” “The problem was identified in the late ’90s,” John McGinley, a scientist who researched the topic, told The Washington Post’s Holly Watt in 2008. “The terrain in Bosnia meant that instead of landing in one valley, the cargo could drift into another valley that was held by the enemy. Wind drift was causing all the problems.” + +So research teams got to work, ultimately unveiling wind-forecast software that the National Oceanic and Atmospheric Administration said increased the drop’s accuracy by 70 percent. “Inaccurate wind forecasts are the main culprit in missed targets for dropping supplies and other items from high altitudes,” the report said. + +It almost immediately went into use in the war in Afghanistan, where far-flung military outposts were separated by stretches of roads pockmarked with insurgents and explosives. There had to be another way to get soldiers the equipment they needed, military officials thought, so they launched a massive increase in airdrops. “We’ve gotten a lot more accurate over the years,” Air Force Gen. Arthur Lichte told USA Today. + +That may true. But following this week’s alleged delivery to the Islamic State, there’s clearly still room for work.","1" +"IS Beheads Briton David Cawthorne Haines, Threatens to Execute Another Briton, Alan Henning","The Islamic State released a video showing the beheading of British aid worker David Haines.","1" +"Unverified video shows beheading of aid worker David Haines","An unverified video shows the beheading of David Haines","1" +"Hostage David Haines' Murder 'Evil', PM Says","UK Prime Minister David Cameron condemned the beheading of David Haines.","1" +"British Aid Worker Confirmed Murdered By ISIS","UK Prime Minister Cameron confirmed Haines' death and stated that the UK government was working to verify the video.","1" +"ISIS Video Claims to Show Beheading of British Hostage","A video released by ISIS claims to show the beheading of British aid worker David Haines.","1" +"Cameron vows to hunt down IS 'monsters' after Haines murder","UK Prime Minister David Cameron denounced the Islamic State (IS) jihadist organisation as “monsters” Sunday after the Foreign Office said a video showing the murder of a British aid worker appeared to be authentic. + +""All the signs are that the video is genuine, we have no reason to believe that it's not,"" a spokesman for the Foreign Office told AFP. + +The video showing the beheading of David Haines, who was abducted in Syria last year, was released by IS militants late Saturday. It was the third beheading of a Western hostage by the group in less than a month. + +After chairing a meeting of the government's emergency Cobra committee Sunday, Cameron condemned IS, which has conquered vast swathes of territory in Iraq and Syria in recent months, as the ""embodiment of evil"" and vowed that the UK would do everything possible to find Haines’s killers. + +""We will hunt down those responsible and bring them to justice, no matter how long it takes,"" the grim-faced premier said in a televised statement from Downing Street. + +He continued: ""Step by step we must drive back, dismantle and ultimately destroy ISIL (IS) and what is stands for. We will do so in a calm, deliberate way but with an iron determination. + +""We will not do so on our own, but by working closely with our allies, not just the United States and in Europe, but with our allies in the region."" + +US President Barack Obama said after the killing that the United States would stand with Britain in an expanded effort against the terror group. + +“We will work with the United Kingdom and a broad coalition of nations from the region and around the world to bring the perpetrators of this outrageous act to justice, and to degrade and destroy this threat to the people of our countries, the region and the world,” he said. + +No comment on air strikes + +Haines, 44, had been taken hostage in Syria in March 2013 while working for the French NGO ACTED, which was helping thousands of Syrians displaced by the fighting between Syrian President Bashar al-Assad’s forces and rebel groups, including IS, seeking to oust him. + +Cameron described 44-year-old Haines as a ""British hero"", saying that ""his selflessness, his decency, his burning desire to help others has today cost him his life"". + +Those who killed him ""are not Muslims, they are monsters"", he said. + +Cameron repeated his support for US air strikes against IS in Iraq, and for President Obama's strategy to build a broad coalition to fight the jihadists. + +But despite growing calls at home for action against IS, Cameron made no commitment to Britain joining the air strikes. + +London began sending arms this week to Kurdish fighters battling IS militants in northern Iraq, but it has faced accusations of confusion over its strategy. + +During a visit to Berlin this week, Foreign Secretary Philip Hammond said Britain would not take part in strikes against IS in Syria, after parliament last year voted against taking military action in that country. + +But just hours later, a spokesman for Cameron's Downing Street office insisted the prime minister was not ruling anything out. + +In the footage of Haines’s murder, a hooded militant blames Cameron for joining forces with the United States and says the alliance will drag the British people into ""another bloody and unwinnable war"". + +‘Barbaric crime must not remain unpunished’ + +In a statement, ACTED said it was “deeply appalled and horrified” by the murder. + +“David was a new member of the ACTED team supporting the emergency humanitarian response for the displaced Syrian people in Atmeh camp near to the Turkish border,” it said. + +“David was appreciated by the ACTED team and all those around him, notably for his generosity, commitment, and his professionalism. + +“The horrible assassination of David, an aid worker, goes against all humanitarian principles and is a crime against humanity. This barbaric crime must not remain unpunished.” + +Before joining ACTED, Haines had also worked for groups such as Handicap International, which helps the disabled during conflicts, and Nonviolent Peaceforce, which sends unarmed peacekeepers into conflict zones. He had previously been in Libya during its civil war and South Sudan. + +His brother, Mike Haines, said he had also worked for the United Nations in the Balkans “helping people in real need”. + +“His joy and anticipation for the work he went to do in Syria is for myself and family the most important element of this whole sad affair,” Mike Haines said. “He was and is loved by all his family and will be missed terribly.” + +(FRANCE 24 with AFP, AP) + +Date created : 2014-09-14","1" +"David Haines Beheaded By ISIS, Execution Video Contains Threats Against UK: Reports","Islamic State militants have released a video which purportedly shows the beheading of British citizen David Haines, multiple unconfirmed reports said. The 44-year-old aid worker was kidnapped in March 2013. + +IS Beheads Briton David Haines, Threatens to Execute Another Briton, Alan Henning http://t.co/GOgalAc1mA + +— SITE Intel Group (@siteintelgroup) September 13, 2014 + +Islamic State releases video showing beheading of British aid worker David Haines + +— SITE Intel Group (@siteintelgroup) September 13, 2014 + +Stills from the purported Haines execution video were released to the Internet Saturday, al-Jazeera reported. In the footage, a masked man claims Haines was killed because the United Kingdom said it would arm Kurdish fighters to combat ISIS in Iraq. + +“This British man has to pay the price for your promise, Cameron, to arm the peshmerga against the Islamic State,” the masked men reportedly said, addressing U.K. Prime Minister David Cameron. The video also contains a threat to second British hostage. + +This time around, the message from the Islamic State is very much aimed at @David_Cameron, with a 2nd British hostage threatened. + +— Brown Moses (@Brown_Moses) September 13, 2014 + +The UK Foreign Office is ""working urgently"" to verify the authenticity of the alleged Haines beheading video, Sky News reports. If verified, the execution would constitute ""another disgusting murder,"" the government organization said. + +Haines’ relatives pleaded Saturday with ISIS to “make contact” and respond to their messages, NBC News reported. “We are the family of David Haines,” the relatives said in a statement. “We have sent messages to you to which we have not received a reply. We are asking those holding David to make contact with us.” + +The British aid worker was identified as ISIS’ next target for beheading in the video which showed the execution of American journalist Steven Sotloff. Militants vowed to kill Haines if the United States military did not end military operations against the Islamic State in Syria and Iraq. + +A father of two, Haines was kidnapped in Syria while working with an organization that assists refugees from the country’s civil war, the New York Daily News reported. He was taken captive near the Turkish border.","1" +"ISIS Extremists Claim to Behead British Hostage David Haines","ISIS released a video purportedly showing the execution of British aid worker David Haines.","1" +"ISIS Video Purports To Show Beheading Of British Aid Worker","Update at 8:50 p.m. EDT + +The militant group that calls itself the Islamic State has released a video that purportedly shows the beheading of British aid worker David Haines. + +The authenticity of the video, which appeared online Saturday, has not been independently confirmed by NPR. + +The organization, also known as ISIS, had threatened to kill Haines just under two weeks ago, in an earlier video that showed the beheading of an American journalist. This weekend, Haines' family had issued a public plea to his captors through the British Foreign and Commonwealth Office. The family asked ISIS to make contact with them. + +Haines, an international aid worker, was abducted in Syria in 2013. ""The British government had managed to keep his kidnapping secret out of concern for his safety until the most recent video Islamic State video identified him as a captive,"" the AP writes. + +The BBC reports that the 44-year-old father of two from Perth, Scotland, was kidnapped shortly after he began working with a French relief agency called ACTED. At his posting there, Haines was ""working in the Atmeh refugee camp ... supplying water, food and tents."" + +Over the past decade and a half he'd worked with a variety of aid agencies, writes the BBC: ""He had worked with a German charity on post-war reconstruction projects in Croatia, including housing and demining. He was also involved in efforts to help displaced people to return to their homes. In 2011 he became Head of Mission in Libya for Handicap International,"" an organization that works to help vulnerable people with disabilities. + +""The following year he joined another agency, the Nonviolence Peaceforce (NP), and went to South Sudan,"" where he worked as an unarmed civilian peacekeeper. + +ISIS previously released two videos showing the beheadings of two American journalists, which were confirmed by U.S. officials to be authentic. The first video, which showed the killing of James Foley, was released on August 20. The second, which showed the beheading of Steven Sotloff and contained the threat directed towards Haines, was released on Sept. 2. + +The newest video, like those previous videos, appears to name another Western hostage as a future target. + +NPR's correspondent Alice Fordham, reporting for our Newscast unit, says the video begins with footage of British prime minister David Cameron. The two previous videos began with footage of President Obama. + +The man identified as Haines, Alice reports, is shown ""kneeling in a featureless desert in an orange robe."" + +The video appears to be recent, Alice says: ""The assailant refers to the bombing of Iraq's Haditha dam a week ago. Another man identified as a British hostage appears at the end as the masked man exhorts Prime Minister Cameron to stop fighting the Islamic State."" + +Cameron has tweeted a response, writing, ""We will do everything in our power to hunt down these murderers and ensure they face justice, however long it takes."" + +President Obama said in a statement that the U.S. ""strongly condemns the barbaric murder of UK citizen David Haines by the terrorist group ISIL,"" and pledged to work with the U.K. and other nations to ""bring the perpetrators of this outrageous act to justice.""","1" +"ISIS Video Shows Execution of David Cawthorne Haines, British Aid Worker","The IS released a video purporting to show the execution of British aid worker David Haines.","1" +"British hostage David Haines beheaded by Islamic State terrorists","Islamic State has released a video showing the beheading of British hostage David Haines. + +It comes just hours after his family issued a public plea for his captors to contact them. + +The Foreign Office said it was ""working urgently to verify"" the video and offering Mr Haines's family support. + +David Cameron, the Prime Minister, said: ""The murder of David Haines is an act of pure evil. My heart goes out to his family who have shown extraordinary courage and fortitude."" + +He added: ""We will do everything in our power to hunt down these murderers and ensure they face justice, however long it takes."" + +Mr Haines, 44, was kidnapped last year as he delivered humanitarian aid in Syria. + +His whereabouts were only revealed this month when he was shown kneeling in the sand, wearing an orange jumpsuit, in a video produced by jihadists of the Islamic State of Iraq and the Levant (Isil) which also showed the murder of Steven Sotloff, an American journalist. + +A masked man, who has become known as “Jihadi John”, said Mr Haines would be next if the West did not halt operations against Isil. + +In the latest video, he is also wearing a orange jumpsuit and is kneeling on the sand. + +It begins with a clip from David Cameron. A man believed to be Mr Haines then looks into the camera and says: ""My name is David Cawthorne Haines. I would like to delcare that I hold you David Cameron entirely responsible for my execution. + +""You entered voluntarily into a coalition with the United States against the Islamic State just as your predecessor Tony Blair did, following a trend against our British prime ministers who can't find the courage to say no to the Americans. + +""Unfortunately it is we the British public that in the end will pay the price for our Parliament's selfish decisions."" + +Twitter: David Cameron - The murder of David Haines is an act of pure evil. My heart goes out to his family who have shown extraordinary courage and fortitude. + +Twitter: David Cameron - We will do everything in our power to hunt down these murderers and ensure they face justice, however long it takes. + +In a statement, the Foreign and Commonwealth said: ""We are aware of the video. + +""We are working urgently to verify the content. If true, this is another disgusting murder. We are offering the family every support possible. + +""They have asked to be left alone at this time."" + +Mr Cameron rushed back to Downing Street for crisis talks with his advisers, officials and intelligence chiefs on Saturday night. He arrived at No 10 just after midnight. + +He chaired a COBRA meeting on Sunday morning. + +In the Haines family’s short statement - which was released earlier on Saturday by the Foreign and Commonwealth Office - the British captive’s relatives said: “We are the family of David Haines. + +“We have sent messages to you to which we have not received a reply.We are asking those holding David to make contact with us.” + +No further details of their messages were released. + +Mr Haines had worked for aid agencies in some of the world’s worst trouble spots, including Libya and South Sudan. + +He was travelling in a car through northern Syria in March last year when he was abducted along with an Italian colleague, who was later released. He was working for a French aid organisation, Agency for Technical Co-operation and Development (Acted). + +Mr Haines is believed to have been kidnapped by a gang which later sold him on to Isil. + +His identity remained a closely guarded secret for 19 months in a bid to increase the chances of a negotiated release. + +But the situation changed dramatically with the execution first of James Foley, another American journalist, and then Mr Sotloff with the subsequent appearance of Mr Haines in the second murder video. + +MPs reacted with horror and anger to the reports on Saturday night. + +Ed Vaizey, a government minister and Conservative MP, said he was “so sad and angry” to hear reports of Mr Haines’s murder. + +Stella Creasy, a Labour MP and shadow minister, said she was “shocked and horrified” to see reports that Mr Haines had been killed. “Hoping mistaken but fear not,” she said. + +Dan Jarvis, another senior Labour MP, said he was “sickened”. + +Tim Farron, President of the Liberal Democrats, said: “My thoughts and prayers are with David Haines' family and friends tonight.” + +Ed Miliband, the Labour leader, said: “I am sickened at the disgusting, barbaric killing of David Haines. + +“He was somebody whose only purpose was to help innocent people, themselves victims of conflict. + +“That ISIL would choose to kill him says everything about their warped logic and murderous ways. + +“Acts like this will not weaken but strengthen the resolve of Britain and the international community to defeat ISIL and their ideology. + +“My deepest condolences and thoughts are with his family as they cope with this terrible crime. And the hearts of the British people will go out to them.” + +Lord Dannatt, the former head of the Army, said the UK should respond by playing its role in the assault against IS promised by US president Barack Obama. + +""What we absolutely need to do is not be cowed in any way by yet another foul murder of a hostage,"" he told Sky News. + +""But to develop the strategy into a sensible military campaign in coalition with regional players such as Saudi Arabia, Jordan and other countries in the area. + +""We can support them to confront, attack and defeat the Islamic State jihadi fighters ... and make sure this cancer is removed from the region before it spreads more widely."" + +The United States also ""strongly condemned"" the killing. + +In a statement, the White House said: ""Our hearts go out to the family of Mr Haines and to the people of the United Kingdom. The United States stands shoulder to shoulder tonight with our close friend and ally in grief and resolve. + +""We will work with the United Kingdom and a broad coalition of nations from the region and around the world to bring the perpetrators of this outrageous act to justice, and to degrade and destroy this threat to the people of our countries, the region and the world.""","1" +"Isis video claims to show beheading of British hostage David Haines","Militants with the Islamic State jihadi group have released a video that appears to show the beheading of a British hostage, David Haines, an aid worker who was captured just days after he arrived in Syria last year. + +British government officials were seeking to authenticate the video which purported to show the final moments of Haines, who was 44. + +In the video, entitled A Message to the Allies of America, a masked man is shown carrying out the beheading of Haines, whose life had earlier been threatened in a film showing the murder of American journalist Steven Sotloff. The video, which runs to two minutes and 28 seconds, ends with a warning that a second British hostage would be the next to die. He has been named in international media and on social media as Alan Henning, a British aid worker. + +Haines is the third western hostage and the first Briton to be killed in this fashion by Isis – the first, US journalist James Foley, was murdered in a video released on 19 August. + +The British prime minister, David Cameron, issued a statement denouncing the killing. “This is a despicable and appalling murder of an innocent aid worker. It is an act of pure evil. My heart goes out to the family of David Haines who have shown extraordinary courage and fortitude throughout this ordeal. + +“We will do everything in our power to hunt down these murderers and ensure they face justice, however long it takes.” + +Cameron will gather senior representatives of the military and security services and the Foreign Office and Home Office in Whitehall to discuss the situation. + +The US president, Barack Obama, also condemned the killing. “The United States strongly condemns the barbaric murder of UK citizen David Haines by the terrorist group Isil,” he said, using his administration’s preferred acronym for Isis. “Our hearts go out to the family of Mr Haines and to the people of the United Kingdom. + +“The United States stands shoulder to shoulder tonight with our close friend and ally in grief and resolve. We will work with the UK and a broad coalition of nations from the region and around the world to bring the perpetrators of this outrageous act to justice, and to degrade and destroy this threat to the people of our countries, the region and the world.” + +The recording features a voiceover delivered by an Isis militant, whose voice and accent closely resembles that of the killer in both the Sotloff and Foley videos. The killer directly addresses Cameron, saying that Haines “has to pay the price for your promise” to arm Kurdish peshmerga fighters against Isis. + +Speaking to the camera, the hostage, composed but clearly under duress, and wearing an orange jumpsuit, reads out a statement in which he says that Cameron is “entirely responsible for my execution” for entering into a coalition with the US. + +Haines, who was in the Royal Air Force for 12 years before moving into aid work, addresses Cameron, saying: “You entered voluntarily into a coalition with the United States against the Islamic State, just as your predecessor, Tony Blair, did, following a trend amongst our British prime ministers who can’t find the courage to say no to the Americans. + +“Unfortunately, it is we, the British public, that will in the end pay the price for our parliament’s selfish decisions.” + +The killer, swathed in black, then makes a statement in which he makes a direct reference to the British government’s aid to Kurdish fighters. + +He says: “This British man has to pay the price for your promise, Cameron, to arm the peshmerga against the Islamic State. Ironically, he has spent a decade of his life serving under the same Royal Air Force that is responsible for delivering those arms. + +“Your evil alliance with America which continues to strike the Muslims of Iraq and most recently bombed the Haditha dam will only accelerate your destruction. And playing the role of the obedient lapdog, Cameron, will only drag you and your people into another bloody and unwinnable war.” + +At the end of the latest video, another hostage, Henning, is paraded. + +The US carried out at least nine air strikes last week on Isis militants threatening the Haditha dam. The bombing was cited by Haines’s killer in the video. + +A spokeswoman for the Foreign Office in London said: “We are aware of the video and are working urgently to verify the contents.” + +Isis had threatened to kill Haines, a father of two, in a video that emerged 11 days ago in which Sotloff was murdered. Less than 24 hours before the latest video emerged, the Haines family had made a plea to the jihadis to respond to their efforts to make contact. + +The family statement, which was released by the Foreign Office and addressed the militants directly, said: “We are the family of David Haines. We have sent messages to you to which we have not received a reply. We are asking those holding David to make contact with us.” + +Haines was born in East Yorkshire but raised in Perthshire, and before his capture was living in Croatia with his second wife Dragana. + +He had a 17-year-old daughter with his first wife Louise, and a four-year-old daughter with Dragana, who has described him as a “fantastic man and father”. He was kidnapped while working for the aid organisation Acted, having previously worked in Libya and South Sudan. + +A meeting of the British government’s emergency committee, Cobra, is expected to be called imminently and the prime minister’s attentions will be diverted from the referendum on Scottish independence, due to take place on Thursday. + +Haines had worked for aid agencies in some of the world’s worst trouble spots, including Libya and South Sudan. + +He was in Libya during its civil war in 2011, working as head of mission for Handicap International, which helps disabled people in poverty and conflict zones around the world.","1" +"British aid worker David Haines beheaded by ISIL","ISIL beheaded British aid worker David Haines as shown on released video.","1" +"Unconfirmed reports saying ISIS UK Hostage David Haines Beheaded","""Multiple unconfirmed sources"" report that Haines has been beheaded by ISIS.","1" +"David Haines beheading video confirmed genuine; UK PM Cameron vows to hunt down ISIS 'monsters'","The UK confirmed the video showing the beheading of aid worker David Haines.","1" +"Does ISIS Have Ebola? Probably Not! Media Reports It Anyway","The New York Post decided that it was a good idea to report that members of ISIS may have been infected with Ebola. In other news, Andy Borowitz has been hired at the New York Post. (Haha, no, kidding. Can you imagine, though?) + +Apparently, the World Health Organization is investigating claims made by Iraqi newspaper Al-Sabah that Ebola and HIV-AIDS are spreading among residents of Mosul, brought there by ""terrorists and expats from different countries, especially Africa."" Mosul is held by ISIS; Al-Sabah is the official Iraqi government newspaper. + +Mashable reports that the story, which originated in Al-Sabah, has spread amongst other pro-government and Kurdish newspapers. Like a virus! Might such outlets have an interest in encouraging the notion that ISIS fighters were stricken with highly-stigmatized diseases? Hmm. + +Meanwhile, Forbes reported in October that ISIS maybe possibly could use Ebola as a weapon: + +So maybe that ridiculous scenario is coming to pass. Maybe! Maybe. There's just no way for us to know for sure. Then again, ""We've seen no specific credible intelligence that [ISIS] is attempting to use any sort of disease or virus to attack our homeland,"" Homeland Security Secretary Jeh Johnson said in October. + +Oh, and also, according to Iraq's Ministry of Health, there are no doctors in Mosul that have the capacity to diagnose Ebola. The reports are ""incorrect"" and ""unfounded,"" a ministry spokesman said. + +[Photo credit: AP Images]","1" +"WHO says reports of suspected Ebola cases in Iraq are untrue","LONDON (Reuters) - No suspected cases of Ebola have been found in Iraq, despite reports to the contrary in Iraqi media in the past week, the World Health Organization (WHO) said on Tuesday. + +Describing reports of suspect cases of the deadly viral infection in Mosul as ""rumor"", the Geneva-based United Nations health agency said it and the Iraqi health ministry had conducted a full investigation. + +""All sources contacted have negated the existence of any suspected cases of Ebola,"" the WHO said in a statement. + +""The (Iraqi) Ministry of Health and the World Health Organization further confirmed that the laboratory facilities in Mosul do not have the necessary capabilities to diagnose and confirm the Ebola virus."" + +Reports of suspected Ebola cases appeared on Dec. 31 in Iraq's Al-Sabah newspaper, Rudaw online newspaper and on the Shafaq news agency and were relayed through other media in and outside Iraq, prompting the WHO and Iraqi authorities to investigate. + +(Reporting by Kate Kelland; Editing by Louise Ireland)","1" +"Officials Refute Iraqi Media Reports That ISIS Members Have Contracted Ebola In Mosul","The two biggest news stories of 2014 collided Wednesday when Iraqi media outlets reported that members of the Islamic State group -- also known as ISIS -- had contracted the deadly virus Ebola. But later updates from the World Health Organization and Iraq's Ministry of Health indicate the stories may be just rumors. + +""We have no official notification ... that it is Ebola,"" Christy Feig, director of communications for WHO, told Mashable, though WHO has contacted Iraqi officials to offer help. + +Iraq's Ministry of Health also denied that anyone in Mosul had contracted the Ebola virus, which broke out in March in West Africa. Spokesman Ahmed Rudaini told news site Al-Maalomah that Mosul doesn't even have the technological capability to diagnose Ebola cases -- only Baghdad does. Therefore, he said, the reports that Ebola has infected anyone in Mosul are ""incorrect"" and ""unfounded."" + +The discussion started with an article in Iraq's official newspaper, Al-Sabah, that said ""terrorists"" brought Ebola to Mosul. ""Many diseases and epidemics have spread among residents of the city of Mosul,"" it read. ""Two Ebola and 26 HIV/AIDS cases were registered."" + +Ebola is primarily a threat in West Africa, where its latest outbreak has killed nearly 8,000 people. Mashable reported ISIS has not recruited fighters from any countries severely affected by the disease. Its African members are primarily from Algeria, Egypt, Morocco, Sudan and Tunisia. + +In the event ISIS does have Ebola, the militants could use it as a biological terror technique, Forbes reported in October. Members could contract the virus on purpose and then go to foreign countries to infect others. “The individual exposed to the Ebola virus would be the carrier,” national security professor Al Shimkus told Forbes. “In the context of terrorist activity, it doesn’t take much sophistication to go to that next step to use a human being as a carrier.” + +ISIS, a body of militants labeled a terrorist group by the United States and European Union (among others), has controlled Mosul since June. Iraq's second-largest city is also ISIS' largest stronghold. The group began spreading across the Middle East last summer, taking over large swaths of Iraq and Syria through brutal tactics.","1" +"WHO: Isis does not have Ebola – but contingency plan being developed for Iraq","The Islamic State (Isis) operating in Iraq does not have Ebola, the World Health Organization has confirmed. + +Last week a number of reports emerged suggesting members of the terrorist organisation had contracted the disease. + +The Daily Mail reported that three media outlets had said a number of militants had shown signs of the deadly virus in the city of Mosul. + +Speaking to Mashable, a WHO spokesperson said they were investigating the reports. ""We have no official notification from [the Iraqi government] that it is Ebola,"" Christy Feig, WHO's director of communications, told the website. + +The organisation has now confirmed there are no suspected cases of Ebola in Iraq as of 5 January. + +""On 31 December, 2014, Al-Sabah newspaper, Shafaq news agency and Rudaw online newspaper reported a rumour of EVD cases in Mosul, Ninewa governorate,"" WHO said in a statement. ""The news was also relayed through other media agencies in and outside of Iraq. + +""Following this rumour, the Ministry of Health and the World Health Organization investigated the allegations through existing surveillance networks, as well as through contacts with health authorities and medical sources in Ibn Sina Hospital in Mosul. + +""All sources contacted have negated the existence of any suspected cases of Ebola. The Ministry of Health and the World Health Organization further confirmed that the laboratory facilities in Mosul do not have the necessary capabilities to diagnose and confirm the Ebola Virus."" + +It said both the Ministry of Health and WHO has scaled up surveillance efforts to ensure early detection of any suspected Ebola cases, and that all precautionary measures are being taken to prevent the disease from entering Iraq. + +""The surveillance efforts have been scaled up at all health facilities to ensure that any imported or suspected cases are promptly detected. + +""A contingency and response plan is currently under development."" + +RelatedHas Ebola infected Isis militants in Mosul?An Ebola survivor's story: How a Sierra Leone orphan pulled off Christmas miracle by cheating deathLiberia Ebola victims can be buried after cremation decree relaxedEbola drug BCX4430 shows promising results in rhesus macaquesEbola recap: A year after the first case and many lessons later, the virus plods on","1" +"Reports Isis fighters have contracted Ebola are 'incorrect', says Iraqi health ministry","A spokesman for the Iraqi health ministry denied reports in a local newspaper that militants in Mosul had Ebola + +Reports that Isis fighters in Iraq have contracted Ebola have been refuted as “incorrect” and “unfounded” by the country’s health ministry. + +Despite reports on Wednesday in the Iraqi paper, al-Sabah, that two cases of Ebola had been reported in Mosul in the north of the country, Ahmed Rudaini, the health ministry’s spokesman dismissed the speculation. + +He said the disease could not have been registered, as only the Central Laboratory of Public Health in Baghdad has the “diagnostic capabilities” to confirm cases of Ebola which was reported by the al-Maalomah news website and the International Business Times. + +The World Health Organisation also confirmed that they had received no confirmation of Ebola cases from Iraq. + +Tarik Jasarevic from the organisation told The Independent: ""WHO is aware of these reports and is working closely with Iraqi MoH to get more information. + +""It is unlikely that this case can be a confirmed Ebola case as there is no laboratory facility in Mosul that could do an Ebola test."" + +WHO’s director of communications, Christy Feig had earlier told Mashable: “We have no official notification from [the Iraqi government] that it is Ebola.” + +The organisation has reached out to the Iraqi government to investigate the claims, should it require assistance, however. + +Al-Sabah initially reported that “terrorists” from several unnamed African countries had brought the virus to the country and claimed that two cases of Ebola and 26 cases of HIV/AIDS had been registered by authorities. + +Although Isis has recruited foreign fighters in the past, it believed that the majority came from Tunisia, according to a Washington Post report. Very few, if any, militants are thought to have travelled from at-risk areas of West Africa, including Liberia, Sierra Leone and Guinea. + +The northern city of Mosul fell to Isis six months ago and residents have suffered brutal repression. People are restricted from leaving the city without first nominating a guarantor, water and food supplies are limited and hospitals have been closed due to a lack of electricity.","1" +"WHO: Reports of Suspected Ebola Cases in Iraq Untrue","No suspected cases of Ebola have been found in Iraq, despite reports to the contrary in Iraqi media in the past week, the World Health Organization (WHO) said on Tuesday. + +Describing reports of suspect cases of the deadly viral infection in Mosul as ""rumor"", the Geneva-based United Nations health agency said it and the Iraqi health ministry had conducted a full investigation. + +""All sources contacted have negated the existence of any suspected cases of Ebola,"" the WHO said in a statement. ""The [Iraqi] Ministry of Health and the World Health Organization further confirmed that the laboratory facilities in Mosul do not have the necessary capabilities to diagnose and confirm the Ebola virus."" + +Reports of suspected Ebola cases appeared on December 31 in Iraq's Al-Sabah newspaper, Rudaw online newspaper and on the Shafaq news agency and were relayed through other media in and outside Iraq, prompting the WHO and Iraqi authorities to investigate.","1" +"No, there aren’t any Ebola cases in Iraq","Iraq has many problems. Ebola isn’t one of them. + +The World Health Organization and the Ministry of Health in Iraq made that clear in a statement late Monday, saying there are no suspected infections from the deadly virus in the country. That came after rumors spread online and through several media outlets on Dec. 31. Most of them cited anonymous medical sources in the city of Mosul, which has been under the control of Islamic State militants since June. + +The virus spreading through Iraq would have raised concerns for both the local population and American troops who recently began training the Iraqi military. According to the discredited reports, the virus was said to have been brought to Iraq by militants and other migrants coming to the country from Africa. + +Health officials said that simply isn’t true. The Ministry of Health and World Health Organization investigated the reports through surveillance networks and contacts with medical sources in Mosul, and found that there were no cases of the virus. + +“The Ministry of Health and the World Health Organization further confirmed that the laboratory facilities in Mosul do not have the necessary capabilities to diagnose and confirm the Ebola Virus,” according to the joint statement–a question that was raised by skeptics when the rumors spread last week. + +Here’s a sampling of tweets on the rumors before the announcement: + +Iraqi News: “Two case of Ebola reported in Mosul”. If true, this is disastrous! #Iraq #ISIS pic.twitter.com/ei2XVqh95v + +— Seloom (@M_Seloom) December 31, 2014 + +#Iraq: Two Ebola cases confirmed in #ISIS controlled Mosul http://t.co/gqUkYTMy0t cc: @alimhaider + +— Patrick Poole (@pspoole) December 31, 2014 + +Whoa if true RT @arabthomness: #Iraq BREAKING: according to Iraqi media there have been 2 confirmed cases of #Ebola in #IS controlled #Mosul + +— Kelsey D. Atherton (@AthertonKD) December 31, 2014 + +#ISIS cracks down on five confirmed cases of #Ebola among fighters: official http://t.co/c4rlvzoGwg + +— Rudaw English (@RudawEnglish) January 4, 2015","1" +"DHS Rebuffs Congressman’s Claim ISIS Infiltrating Southern Border","The Department of Homeland Security is denying a congressman’s assertion that fighters with the militant group Islamic State, also known as ISIL or ISIS, have been caught crossing the southwestern border. + +“The suggestion that individuals who have ties to ISIL have been apprehended at the Southwest border is categorically false, and not supported by any credible intelligence or the facts on the ground,” a DHS spokesman said in a statement today. “DHS continues to have no credible intelligence to suggest terrorist organizations are actively plotting to cross the southwest border.” + +Digital Feature: What Is ISIS? +Perry Warns Terrorists Could Infiltrate US Through Border +Obama Pledges to 'Degrade and Ultimately Destroy' ISIS: What You Need To Know +Rhetoric vs. Reality: 5 Myths About Obama's ISIS Plan Debunked +Rep. Duncan Hunter, R-Calif., told Fox News on Tuesday night that ISIS is sneaking into the U.S. through the southwestern border. + +PHOTO: Rep. Duncan Hunter (R-Calif.) speaks during a news conference held by House Republicans on Protecting Americas Veterans at the U.S. Capitol, May 29, 2014, in Washington.Win McNamee/Getty Images +PHOTO: Rep. Duncan Hunter (R-Calif.) speaks during a news conference held by House Republicans on ""Protecting America's Veterans"" at the U.S. Capitol, May 29, 2014, in Washington. +""I know that at least ten ISIS fighters have been caught coming across the Mexican border in Texas,"" Hunter claimed. ""There's nobody talking about it."" + +""If they catch five or ten of them, then you know there's gonna be dozens more that did not get caught by the border patrol,"" he continued. + +One source close to Hunter worked to walk back the comment, emphasizing that the congressman received a tip from a “high level” source at U.S. Customs and Border Protection who told him that a group of people with “suspected ISIS affiliation” –- even Americans who traveled to Syria to fight with the Free Syrian Army against President Bashar al-Assad –- were apprehended at the border. + +The tip ""was from a confidential source with the Border Patrol,"" the source said in an email. ""[It’s] more accurate to say people with known associations. Not 'fighters' in the sense folks might immediately think."" + +While DHS and several other congressional sources shot down the claim outright, a spokesman for Hunter said that the congressman fears ISIS sympathizers could easily melt into U.S. cities and breed home-grown terrorism. + +“The Congressman was conveying what he knows -- and what he was told,” Joe Kasper, deputy chief of staff to Hunter, wrote in response to the DHS denial. “It makes sense that the left hand of DHS doesn't know what the right hand is doing -- it’s been that way for a long time and we don’t expect that to change.” + +Customs and Border Protection is part of DHS. + +Hunter’s office declined an ABC News request to interview the congressman. + +ABC News’ Jeff Zeleny and Mike Levine contributed to this report.","1" +"""Categorically False"": DHS Debunks Right-Wing Fiction That ISIS Attempted To Cross The U.S.- Mexico Border","The Department of Homeland Security definitively debunked the persistent right-wing media conspiracy theory that Islamic State fighters have attempted to cross the U.S.-Mexico border, saying the rumor is not supported by any ""credible intelligence"" and knocking the claim that the terrorists have been apprehended at the border as ""categorically false."" + +What began early this summer as an unsubstantiated claim from Texas Gov. Rick Perry (R) that ""people that are coming [across the U.S.-Mexico border] from states like Syria that have substantial connections back to terrorist regimes and terrorist operations,"" (a claim PolitiFact Texas rated ""Pants on Fire""), has morphed into a full-blown right-wing conspiracy theory. Conservative media and elected officials are hyping fears that members of the Islamic State (ISIS or ISIL) terrorist group are utilizing the U.S.-Mexico border to enter the U.S. and launch terrorist attacks, a chorus that has only grown louder in the ensuing months to attack immigration reform. + +In September, Rep. Jason Chaffetz (R-UT) claimed to have seen information detailing ""four individuals trying to cross through the Texas border who were apprehended at two different stations that do have ties to known terrorists organizations in the Middle East,"" a story subsequently hyped by Fox News. Nearly a month later, the number had jumped from four terrorists allegedly apprehended to 10. + +Fox News' On The Record provided a platform to Rep. Duncan Hunter (R-CA) who claimed to have first-hand knowledge of the terrorists crossing the border. Host Greta Van Susteren replied to Hunter's allegations by asking, ""Do you have any information, or any evidence, that they are actually coming in the southern border now?"" And Hunter responded, ""Yes. ... I know that at least 10 ISIS fighters have been caught coming across the Mexican border in Texas,"" citing information he'd received from border patrol agents. + + + +But the right-wing talking point is ""categorically false,"" according to the Department of Homeland Security, which oversees border security. On October 8, DHS spokesperson Marsha Catron refuted the rumor that Islamic State terrorists had crossed the U.S.-Mexico border, telling The New Republic: + +""The suggestion that individuals who have ties to ISIL have been apprehended at the Southwest border is categorically false, and not supported by any credible intelligence or the facts on the ground,"" said DHS spokesperson Marsha Catron. ""DHS continues to have no credible intelligence to suggest terrorist organizations are actively plotting to cross the southwest border."" + +It remains to be seen whether DHS's facts permeate the right-wing bubble. After hearing the DHS statement, Sean Hannity claimed on his radio program that the agency could not be trusted and suggested it may be lying.","1" +"Officials shoot down congressman's claims ISIS terrorists are running across US-Mexico border","Federal officials have called a sitting U.S. Representative a liar after he went on national television claiming ISIS militants were crossing into the country through the Mexican border. + +The Department of Homeland Security told AOL News that Rep. Duncan Hunter (R-CA) was telling a tale Tuesday afternoon when he told Fox News that insurgents were traversing the Texas border. + +""The suggestion that individuals who have ties to ISIL have been apprehended at the Southwest border is categorically false, and not supported by any credible intelligence or the facts on the ground,"" spokesperson Marsha Catron told AOL. + +""DHS continues to have no credible intelligence to suggest terrorist organizations are actively plotting to cross the southwest border."" + +Catron's comments came one day after Hunter ranted to host Greta van Susteren about America's pourous southern border. + +""ISIS is coming across the southern border,"" Hunter insisted. ""They aren't flying B-1 Bombers bombing American cities, but they are going to be bombing American cities coming across from Mexico. + +""At least 10 ISIS fighters have been caught coming across the Mexican border in Texas,"" Hunter added. ""There's nobody taking about it."" + +When asked where he got the information, Hunter shot back that he ""asked the Border Patrol."" + +An AOL News attempt to reach Texas Border Patrol officials was not successful. The inquiry was directed to the DHS. + +""They caught them at the border,"" Hunter continued. ""Therefore, we know ISIS is coming across the border. + +""If they catch five or 10 of them you know there are going to be dozens more that did not get caught by the Border Patrol."" + +Hunter's constituency mainly covers the San Diego area. He did not say if terrorists were also running through his neck of the woods. + +When offered the opportunity to respond to DHS comments, a spokesperson for Rep Hunter provided AOL News a link to a blog claiming sources told it four ISIS terrorists have recently been arrested at the border. + +There was no response to a follow up request for comment.","1" +"Homeland Security says terrorists haven't crossed U.S-Mexico border","Homeland Security Secretary Jeh Johnson stated that claims of ISIS members at the Mexican border were false.","1" +"Obama administration DENIES congressman's claim that 'at least ten ISIS fighters have been caught coming across the Mexican border in Texas'","The Department of Homeland Security flatly denied on Wednesday a claim from a California Congressman that the ISIS terror army is quietly slipping into the United States through its porous southern border – and that American border patrol agents have already captured ten of its soldiers. + +Republican Duncan Hunter told a Fox News Channel audience on Tuesday that ISIS, the self-proclaimed Islamic State of Iraq and al-Sham, is actively infiltrating the U.S. + +'I know that at least ten ISIS fighters have been caught coming across the Mexican border in Texas,' he said. 'There's nobody talking about it.' + +But DHS fired back, saying in a statement that Hunter's claim is 'categorically false.' + +SCROLL DOWN FOR VIDEO + +Rep. Duncan Hunter stunned a Fox News audience by saying that the US has apprehended about ten ISIS terrorists as they entered the country through the Mexican border + +Vulnerable: Much of the Texas-Mexico border is essentially undefended, with US Border Patrol agents setting up well on the American side + +'The suggestion that individuals who have ties to ISIL have been apprehended at the Southwest border is categorically false, and not supported by any credible intelligence or the facts on the ground,' a Homeland Security spokesman said in a statement, using the administration's preferred alternative acronym for the group. + +'DHS continues to have no credible intelligence to suggest terrorist organizations are actively plotting to cross the southwest border.' + +CBS News reported Wednesday that one of Hunter's sources 'nuanced their claims' after the Fox broadcast, saying that some of the people he referred to may have been 'ISIS-affiliated or possibly Americans who fought with the Syrian Free Army.' + +The FSA is an ISIS foe, not an ally. + +Hunter's spokesman pushed back, defending his claim. + +“The congressman was conveying what he knows – and what he was told,' the spokesperson said in a statement. + +'It makes sense that the left hand of DHS doesn’t know what the right hand is doing – it’s been that way for a long time and we don’t expect that to change.' + +Hunter, like many in the GOP, has advocated in the past for strengthening America's border security to the south, a demand that has largely fallen on deaf ears during the Obama presidency. + +During a 2013 Senate hearing, then-Homeland Security Secretary Janet Napolitano said that due to the administration's 'significant progress and efforts ... our borders have, in fact, never been stronger.' + +But Hunter, a member of the House Armed Services Committee, claimed Tuesday that the nation's 1,933-mile southern border represents ISIS's best hope of waging war on the U.S. + +'If you really want to protect Americans from ISIS, you secure the southern border,' he said. 'It's that simple.' + +'ISIS doesn't have a navy, they don't have an air force, they don't have nuclear weapons. The only way that ISIS is going to harm Americans is by coming in through the southern border – which they already have.' + +'You're talking about OUR southern border?' Fox host Greta can Susteren was shocked to hear Hunter's claim that ISIS is infiltrating the US + +Host Greta Van Susteren was caught flat-footed. 'Are you talking about ours?' she asked. 'You're talking about our southern border? You're not talking about the southern border of Iraq?' + +'They aren't flying B-1 bombers, bombing American cities,' he replied, 'but they are going to be bombing American cities coming across from Mexico.' + +The three-term congressman cited a similar fear that Joint Chiefs Chairman Gen. Martin Dempsey expressed during an August 21 Pentagon press briefing. + +Dempsey called ISIS 'an immediate threat ... because of open borders and immigration issues.' + +Hunter said his information came directly from U.S. Customs and Border Protection, which has a 20,000-strong army of agents patrolling the borders in Texas, Arizona, New Mexico and California. + +'I've asked the border patrol,' he said, adding that he was told about the ten ISIS fighters who were caught crossing the border. + +'If they catch five or ten of them, then you know there's gonna be dozens more that did not get caught by the border patrol,' he said. 'But that's how you know: All you have to do is ask the border patrol.' + +The government watchdog group Judicial Watch claimed in August that ISIS terrorists were 'planning to attack the United States with car bombs or other vehicle born [sic] improvised explosive devices.' + +The group said a 'warning bulletin for an imminent terrorist attack' had been issued to 'agents across a number of Homeland Security, Justice and Defense agencies,'instructing them 'to aggressively work all possible leads and sources' to prevent the attacks. + +The Department of Homeland Security flatly denied that in a statement to MailOnline. + +'We are aware of absolutely nothing credible to substantiate this claim,' a bewildered DHS spokesman said + +'In Mexico? I haven't seen that at all.' + +Homeland Security Secretary Jeh Johnson said on the same day Judicial Watch made its claims that his agency and the FBI were 'unaware of any specific, credible threat to the U.S. homeland' from the terror network.","1" +"Jeh Johnson: Politicians Shouldn't 'Feed The Flames Of Fear' Over ISIS, Ebola","WASHINGTON -- Homeland Security Secretary Jeh Johnson shot down claims on Thursday that a ""porous"" U.S. southern border is allowing terrorists, Ebola and a surge of unaccompanied minors into the country, despite claims to the contrary by some politicians. + +Johnson tried to dispel rumors and dial back fears during a speech at the Center for Strategic and International Studies, saying there have been improvements to border security. He said the number of unaccompanied minors apprehended in fiscal year 2014 was 68,434 -- considerably lower than a projection of 90,000. Claims that four terrorists had crossed the border were false, he said, and the government is intensifying efforts to keep Ebola out of the U.S. + +But that's not always what people are hearing from politicians or reading in the news, he said. + +""Those of us in public office, and in the media –- whether in describing the border, ISIL or Ebola -- owe the public informed, careful, and responsible dialogue, not overheated rhetoric that is certain to feed the flames of fear, anxiety and suspicion,"" Johnson said. ISIL, the terrorist group that calls itself the Islamic State, also is called ISIS. + +Recent criticism of the Obama administration over border security has stoked fears over ISIS and Ebola, particularly by Republicans campaigning for November elections. Former Sen. Scott Brown (R-Mass.), now running for Senate in New Hampshire, said on Thursday that the border needed to be secured to prevent the spread of diseases into the country. Rep. Duncan Hunter (R-Calif.) said Tuesday that ""at least"" 10 members of the Islamic State were apprehended crossing the U.S.-Mexico border, a claim DHS said was false. Rep. Jason Chaffetz (R-Utah) has said that four men with ties to terrorism were apprehended along the border. + +Johnson said the four individuals were investigated and found to be members of the Kurdish Worker's Party, which he said ""is actually fighting against ISIL and defended Kurdish territory in Iraq."" The men remain in detention for unlawful entry, he said. (Chaffetz, for his part, continued to maintain after Johnson's speech that the men are terrorists, according to interview with CBS News.) + +On Ebola, Johnson said the government is ""heavily engaged"" and is ""enhancing our Ebola screening of air passengers from the three affected African countries, and we are continually evaluating whether more is appropriate."" + +""We very definitely in this country have the capability to deal with the Ebola virus,"" he said. + +Johnson touted border security improvements, but said DHS was still working to improve policies on transparency and internal agency coordination. One change in DHS policy, however, has been receiving considerable pushback from immigration advocates: the increased practice of holding families in detention. The government has expanded facilities for detaining families -- largely mothers with children, many of them seeking asylum -- over the past few months, and plans to add more space. + +Greg Chen of the American Immigration Lawyers Association, which has been critical of family detention, asked Johnson during a question and answer period after the speech why the government is expanding family detention when many of the women and children being held are seeking asylum and have fled horrific violence. + +Johnson said that given the increase this year in families crossing the border -- even though the numbers have dropped recently -- DHS needed to make sure it could detain them. + +""We believe it's necessary to build more of that capability in the event we have another spike like we had last summer,"" he said. + +Although Johnson acknowledged the influx of migrants over the past year was a ""setback,"" he said there have been improvements in border security, from more resources focused on patrol to fewer border-crossings. + +""In recent years, the total number of those who attempt to cross our southwest border has declined dramatically, while the percentage of those who are apprehended has gone up,"" he said. ""Put simply, it’s now much harder to cross our border and evade capture than it used to be -– and people know that.""","1" +"ISIS Border Crisis: DHS Chief Says Terrorists Not Entering US Through Mexico","Homeland Security Secretary Jeh Johnson says Islamic State militants are not entering the U.S. through the southern border. Johnson was responding to a claim made by Rep. Duncan Hunter, R-Calif., that at least 10 Islamic State operatives were detained trying to come in from Mexico. + +“We have no credible, specific intelligence to that effect,” Johnson said on CNN Wednesday evening of the militants also known as ISIS. “And I look at the intelligence reports from overseas from our southern border from our intelligence community virtually every day, numerous times a day, to be on the lookout for something of that nature. So, what I’d say to the American public is we’re vigilant in looking out for individuals of suspicion who may be crossing our border.” + +Johnson never mentioned Hunter by name, but he has called on lawmakers to act responsibly and not frighten Americans. “Let’s not unduly create fear and anxiety in the American public by passing on speculation and rumor,” Johnson said. + +The group Judicial Watch reported late Wednesday that four “Islamic terrorists” had been seized along the southern border within 36 hours. Hunter said in an interview with Fox News on Tuesday that ""at least 10 ISIS fighters have been caught coming across the Mexican border in Texas.""","1" +"DHS: GOP Rep.’s Claim ISIS Members Caught at U.S. Border ‘Categorically False’","Congressional Republicans have been pushing the “ISIS At the Border” line so hard they may now be hearing things. + +Representative Duncan Hunter (R-CA) told Fox News’ Greta van Susteren Tuesday that “at least ten ISIS fighters have been caught coming across the Mexican border in Texas,” saying he received the information from a border patrol source. + +According to the Department of Homeland Security, which has been rebutting similar claims for weeks, that’s bogus. + +RELATED: Geraldo to Fox & Friends: Don’t Mix Up War on Terror with Immigration Debate + +“The suggestion that individuals who have ties to ISIL have been apprehended at the Southwest border is categorically false, and not supported by any credible intelligence or the facts on the ground,” a DHS spokesman said in a statement today. “DHS continues to have no credible intelligence to suggest terrorist organizations are actively plotting to cross the southwest border.” + +One of Hunter’s sources modified the claim after the congressman’s comments, saying that those apprehended might be ISIS-affiliated or even American who fought with the Syrian Free Army, one of ISIS’ many enemies. + +Hunter didn’t back down. “The Congressman was conveying what he knows — and what he was told,” a spokesperson told ABC News. “It makes sense that the left hand of DHS doesn’t know what the right hand is doing — it’s been that way for a long time and we don’t expect that to change.” + +[h/t ABC News] + +[Image via screengrab] + +—— >> Follow Evan McMurry (@evanmcmurry) on Twitter","1" +"No, Islamic State Militants Have Not Been Caught by U.S. Border Patrol","Since the U.S. began airstrikes in Iraq and Syria against the Islamic State, Republicans have frequently connected the terrorist group to border security in the U.S. In August, Texas Governor Rick Perry called it a “very real possibility” that fighters from the Islamic State had already crossed into the U.S. + +On Tuesday night, Representative Duncan Hunter, a Republican from California, took those comments even further. Appearing on ""On the Record with Greta Van Susteren,"" Hunter said, “At least ten ISIS fighters have been caught coming across the border in Texas.” When Van Susteren asked how he knew that, Hunter replied, “Because I’ve asked the border patrol, Greta.” + + + +I asked the Department of Homeland Security if Hunter’s comments were true. They weren't. + +“The suggestion that individuals who have ties to ISIL have been apprehended at the Southwest border is categorically false, and not supported by any credible intelligence or the facts on the ground,” said DHS spokesperson Marsha Catron. “DHS continues to have no credible intelligence to suggest terrorist organizations are actively plotting to cross the southwest border.” + +UPDATE: Hunter isn't backing off his comments, claiming they came from a ""high-level source"" at DHS.""The Congressman was conveying what he knows—and what he was told,"" Hunter's spokesperson told The Huffington Post. ""And as for DHS’ statement, it makes sense that the left hand of DHS doesn’t know what the right hand is doing—it’s been that way for a long time and we don’t expect that to change. No surprise there.""","1" +"Homeland Security: No ISIL fighters on U.S. border","Homeland Security Secretary Jeh Johnson is pushing back against a claim made by Rep. Duncan Hunter that at least 10 Islamic State of Iraq and the Levant fighters were apprehended trying to come into the U.S. from Mexico. + +“We have no credible, specific intelligence to that effect,” Johnson said of ISIL insurgents illegally entering the country from along the southern border on CNN Wednesday evening. “And I look at the intelligence reports from overseas from our southern border from our intelligence community virtually every day, numerous times a day, to be on the lookout for something of that nature. So, what I’d say to the American public is we’re vigilant in looking out for individuals of suspicion who may be crossing our border.” + +The top DHS official didn’t mention Hunter, a California Republican congressman, by name. But on several occasions, Johnson said that public officials have a “responsibility” to not “unnecessarily frighten the American public.” + +“Let’s not unduly create fear and anxiety in the American public by passing on speculation and rumor,” the secretary told host Wolf Blitzer. + +Blitzer asked specifically about comments made Tuesday evening by Hunter, a member of the House Armed Services Committee. “[A]t least 10 ISIS fighters have been caught coming across the Mexican border in Texas,” the congressman said during an interview on Fox News, citing information from source from Customs and Border Protection, which is under DHS authority. Hunter also suggested that it was likely that “dozens” of others linked to the terrorist group that has recently beheaded two American journalists and two British aid workers would likely not get caught by border agents and make their way into the U.S. + +On Wednesday, DHS flatly said that Hunter’s claim was unfounded. “The suggestion that individuals who have ties to ISIL have been apprehended at the southwest border is categorically false, and not supported by any credible intelligence or the facts on the ground,” a DHS spokesperson said. + +Judicial Watch reported later Wednesday that four “Islamic terrorists” had been seized along the southern border in 36 hours. + +Hunter’s deputy chief of staff, Joe Kasper, told POLITICO that the congressman stands by his statement, which came from a conversation with a “high-level” source, but didn’t elaborate when asked about the individuals’ specific ties to ISIL. + +In September, Republican Rep. Jason Chaffetz of Utah claimed that four men linked to terrorist organizations tried to cross the border earlier that month.","1" +"Pants on Fire: Duncan Hunter makes unconfirmed claim Border Patrol caught at least 10 ISIS fighters","U.S. Rep. Duncan Hunter this week declared terrorists have been crossing the Rio Grande. + +The California Republican, speaking to Greta Van Susteren on Fox News Oct. 7, 2014, said he’d learned from the U.S. Border Patrol that Islamic State fighters had been nabbed trying to enter the country from Mexico. ""ISIS is coming across the southern border,"" Hunter said, adding a moment later: ""I know that at least 10 ISIS fighters have been caught coming across the Mexican border in Texas."" + +Border Patrol agents ""caught them,"" Hunter also said, but ""you know there's going to be dozens more that did not get caught by the Border Patrol."" + +Our eyebrows were raised. We sought detail. + +No federal or state confirmation + +No state or federal law enforcement agency confirmed Hunter’s account when we inquired, and Hunter spokesman Joe Kasper declined to reveal the congressman’s sources. + +Fox News, in its original Oct. 8, 2014, online news report on Hunter’s declaration, quoted the Department of Homeland Security disputing his account. + +Homeland Security told PolitiFact Texas that no such apprehensions have occurred. An agency spokeswoman, Marsha Catron, emailed: ""The suggestion that individuals who have ties to ISIL have been apprehended at the Southwest border is categorically false, and not supported by any credible intelligence or the facts on the ground. DHS continues to have no credible intelligence to suggest terrorist organizations are actively plotting to cross the southwest border."" + +And after Hunter spoke, the Texas Department of Public Safety wrote state legislators, saying in an Oct. 8, 2014, email it ""does not have any information to confirm"" statements about Islamic terrorists or ISIS fighters entering the country. A DPS spokesman, Tom Vinger, confirmed the message’s authenticity. + +In the message, a DPS deputy director, Robert Bodisch, mentioned the Hunter interview and an Oct. 8, 2014, news report by Judicial Watch, a conservative news website, stating Islamic terrorists had entered the country from Mexico. According to unidentified Homeland Security sources, Judicial Watch said four terrorists had been apprehended in the previous 36 hours by federal authorities and the DPS in McAllen and Pharr. + +In the message to legislators, Bodisch further wrote: ""An unsecure border is certainly a vulnerability that can be exploited by criminals of all kinds, and it would be naïve to rule out the possibility that any criminal organization would not look for opportunities to take advantage of security gaps along our international border. That said, DPS does not have any information to confirm the specific statements recently reported in the press."" + +On Sept. 17, 2014, PolitiFact in Washington analyzed an August 2014 Judicial Watch story, finding Mostly False another congressman’s claim that ""we know that ISIS is present in Ciudad Juarez,"" which neighbors El Paso. Research did not turn up any law enforcement official or news outlet that independently verified or corroborated the claim, making the declaration that ""we know"" with certainty ISIS is in Juarez a big stretch. + +For this fact check, a terrorism expert said Hunter’s claim doesn’t make much sense. + +""It’s implausible given the way the criminal-justice system works to have 10 ISIS fighters arrested at the border and never charged,"" said Daveed Gartenstein-Ross, director of the Center for the Study of Terrorist Radicalization at the Foundation for Defense of Democracies in Washington. + +Gartenstein-Ross said by phone he knows of ""no reporting coming through DHS suggesting that a large number of ISIS fighters have been intercepted at the border. I’ve talked to a large number of people within the department, and the department has unequivocally denied it. There’s not one shred of evidence this is the case."" + +Kasper, informed we'd not confirmed Hunter's statement, said Hunter stands by what he said. + +Kasper also expressed doubt federal agencies are revealing the facts about fighters getting caught. + +""Problem here is that this is always a zero-sum game,"" Kasper wrote. ""We make the point. Official channels deny. Then, maybe in a few years from now the information will pop up on the front page of the Washington Post,"" much like that newspaper this week reported new details about the Secret Service prostitution scandal, Kasper said. + +Our ruling + +Hunter said ""at least 10 ISIS fighters have been caught coming across the Mexican border in Texas"" and there are ""dozens more that did not get caught by the Border Patrol."" + +No government agency confirms anything remotely close to the idea that at least 10 ISIS fighters have been caught coming across the Mexican border. Notably, too, the lead Texas agency entrusted with public safety alerted legislators of its own lack of confirmation. Similarly, the idea there are ""dozens more that did not get caught by the Border Patrol"" is missing a factual basis. + +All told, this statement strikes us as incorrect and ridiculous. Pants on Fire! + +PANTS ON FIRE – The statement is not accurate and makes a ridiculous claim. + +Click here for more on the six PolitiFact ratings and how we select facts to check.","1" +"Jeh Johnson shoots down Duncan Hunter's assertion IS is entering U.S. via Mexico","WASHINGTON, Oct. 9 (UPI) -- Homeland Security Secretary Jeh Johnson took to CNN to publicly counter claims made by Republican Rep. Duncan D. Hunter that Islamic State militants have been detained attempting to enter the United States from Mexico. +""[A]t least 10 ISIS fighters have been caught coming across the Mexican border in Texas,"" Hunter told Fox News. The California congressman claimed to have obtained the alleged information from Customs and Border Protection. + +Speaking to CNN's Wolf Blitzer, Johnson thoroughly shot down Hunter's claims: ""We have no credible, specific intelligence to that effect"" and calling on American leaders to ""not unduly create fear and anxiety in the American public by passing on speculation and rumor."" + +""I look at the intelligence reports from overseas from our southern border from our intelligence community virtually every day, numerous times a day, to be on the lookout for something of that nature. So, what I'd say to the American public is we're vigilant in looking out for individuals of suspicion who may be crossing our border.""","1" +"Islamic State Leader al-Baghdadi “Not Dead”","The Islamic State (IS) leader Abu Bakr al-Baghdadi has not been killed as has been previously claimed. He is wounded and being treated in the border area of Iraq and Syria. + +A few days ago, it was reported that al-Baghdadi had been killed by a U.S. airstrike near Mosul in Northern Iraq, an attack that left three other senior members of the militant group dead. + +However, a source told Iraqi media that the IS leader and self-proclaimed Caliph has not been killed, but is badly injured as a result of the recent US airstrikes near the Tel Afer and Sinjar areas. + +“This is the second time al-Baghdadi has been injured in the last two months and right now he is being treated in a Syrian location close to the Iraqi border,” the source told Iraqi newspaper al-Sabah. + +When it was reported that al-Baghdadi had been killed, the Pentagon did not confirm the death, but thousands of social media users shared an unverified photo claiming to be the ISIS leader’s body. + +However, Pentagon spokesman Col. Steve Warren did later say that any IS leaders “inside troop formations are likely to be killed.”","1" +"We took a look at the photo said to show the body of Islamic State leader Abu Bakr Al-Baghdadi (right) and found it was really an ethnic Albanian militant killed in 2013","We took a look at the photo said to show the body of Islamic State leader Abu Bakr Al-Baghdadi (right) and found it was really an ethnic Albanian militant killed in 2013 (left) -- with Al-Baghdadi's head and watch added. See a news report on the death of Sami Hafez Al-Abdullah here: http://hournews.net/news.php?id=21302.","1" +"Pentagon Denies It Killed ISIS Chief As Airstrikes Hit Top Extremists","The right-hand man of Abu Bakr Al-Baghdadi was killed by an airstrike in Mosul. +An airstrike in the ISIS stronghold of Mosul killed at least two members of the group, including an aide to ISIS leader Abu Bakr Al-Baghdadi, according to the Iraqi Defense Ministry. +Reports that Baghdadi himself had been killed by a U.S. airstrike circulated in Turkish and Kurdish media Wednesday and were repeated to The Daily Beast by multiple Iraqi sources. But a Pentagon official denied that the ISIS leader was dead. ""There is no validity to the rumor that we've killed Baghdadi,"" a senior defense official told The Daily Beast. + +The Iraqi Defense Ministry announcement, first reported by al Arabayia, did not specify whether the airstrike was carried out by American or Iraqi forces, but NBC News reports that a senior security official confirmed it was a U.S. airstrike. The article does not clarify whether the security official is American or Iraqi but quotes them as saying that three ISIS leaders were killed, including Baghdadi’s aide Abu Hajar Al-Sufi, an explosives specialist and commander in the town of Tal Afar. + +There have been no public statements yet from U.S. officials on the reported airstrikes. + +While the U.S. air war in Iraq has been steadily expanding since it began in early August, Thursday’s reports provide the first public indication that ISIS’s senior leadership is being directly targeted. + +The rumors of Baghdadi’s death that spread through northern Iraq yesterday may have been triggered by uncertainty over who died in the airstrikes that reportedly killed his aide. It’s also possible that claim’s of Baghdadi’s death could have come from ISIS itself as part of a deception campaign to cover the leader’s tracks and obscure his true status and whereabouts. + +Multiple sources, including Kurdish intelligence officials and former Iraqi army officers, told The Daily Beast Wednesday that Baghdadi had died somewhere in Syria after being wounded in a recent airstrike and fleeing Iraq to seek medical treatment. + +This was not the first time that rumors of Baghdadi’s death have surfaced. Without an independent press to verify new information, unverified claims can be spread quickly through Iraq as speculation outpacing facts and gets taken for the truth. + +But the new reports that ISIS leaders were killed by airstrikes in Mosul, coming only a day after a flurry of claims about Baghdadi’s death in Syria, suggests the group’s leadership is increasingly vulnerable and that Baghdadi may be on the run and seeking sanctuary in Syria where President Obama has not yet authorized military intervention. + +With additional reporting by Ford Sypher and Eli Lake.","1" +"‘Photo of slain IS leader’ reported to be doctored","A photo purporting to show the slain body of Islamic State leader Abu Bakr al-Baghdadi appears to be a doctored picture of another slain militant killed in Syria in 2013. +Rumors circulated on social media and Iraqi media over the weekend that Baghdadi was slain in a US airstrike several days ago. +Later Iraqi reports said the IS leader was severely wounded in the chest near the Syrian border and was receiving medical treatment. + +The reports could not be independently confirmed. + +A picture purporting to show Baghdadi’s bloodied body in fatigues also circulated. + +However, the picture appears to actually show Baghdadi’s head pasted onto the body of Sami Hafez Al-Abdullah, an Albanian national killed in Syria in 2013, according to an investigation by Storyful, a social media news agency. +A picture of Abdullah, who reportedly also served as an imam in Germany, and a report on his death appeared on Yemenite news site Hournews.net last year. + +Despite the apparently doctored photo, Baghdadi’s fate, amid continuing American air strikes, remains unclear. + +Washington expanded its month-long air campaign to Iraq’s Sunni Arab heartland, hitting Islamic State fighters west of Baghdad as troops and allied tribesmen launched a ground assault on Sunday. + +The new strikes deepen Washington’s involvement in the conflict and were a significant escalation for President Barack Obama, who made his political career opposing the war in Iraq and pulled out US troops in 2011. + +Previous strikes — since the US air campaign began on August 8 — had been mainly in support of Kurdish forces in the north. + +US warplanes bombed IS fighters around a strategic dam on the Euphrates River in an area that the jihadists have repeatedly tried to capture from government troops and their Sunni militia allies. + +“We conducted these strikes to prevent terrorists from further threatening the security of the dam, which remains under control of Iraqi security forces, with support from Sunni tribes,” Pentagon spokesman Rear Admiral John Kirby said. + +“The potential loss of control of the dam, or a catastrophic failure of the dam — and the flooding that might result — would have threatened US personnel and facilities in and around Baghdad, as well as thousands of Iraqi citizens,” he added. + +AFP contributed to this report.","1" +"Video Appears to Show Beheading of Journalist James Foley, Who Went Missing in Syria","A disturbing video posted online appears to show the beheading of American journalist James Foley, who was kidnapped while covering the Syrian conflict in 2012. + +In the video a man who appears to be Foley, dressed in orange, kneels beside an armed man clad in black. Foley delivers a statement condemning U.S. action in Iraq and says that the U.S. government is his “real killers.” + +“For what will happen to me is only a result of their complacency and criminality,” Foley says in halting speech. “I wish I had more time. I wish I could have the hope of freedom of seeing my family once again, but that ship has sailed. I guess all in all, I wish I wasn’t American.” + +Seconds later, the figure dressed in black brandishes a knife and identifies himself as with the Islamic State, the name the brutal terror group Islamic State of Iraq and Syria took on after its leader, Abu Bakr al-Baghdadi, declared himself the leader of all Muslims. + +“Today your military air force has attacked us daily… Your strikes have caused casualties amongst Muslims,” the figure in black says. He then addresses President Obama directly, saying “any attempt… to deny the Muslims their right to live in safety under the Islamic caliphate will result in the bloodshed of your people.” + +Foley is then killed. The video continues, showing American Steven Sotloff, who has written for national publications like Time, also dressed in orange and on his knees. + +“The life of this American citizen, Obama, depends on your next decision,” the figure in black says. + +A spokesperson for the White House National Security Council said the U.S. intelligence community ""is working as quickly as possible to determine its authenticity."" + +""If genuine, we are appalled by the brutal murder of an innocent American journalist and we express our deepest condolences to his family and friends,"" spokesperson Caitlin Hayden wrote in a statement to reporters. + +The U.S. government offers a $10 million reward for information leading to ISIS leader al-Baghdadi’s capture. + +Foley was on assignment in Syria for the news outlet GlobalPost. The news organization's co-founder Charles Sennott said today there is ""no reliable proof that this execution is authentic"" and that they're working to gather information. + +""If the video is verified, it is just unfathomable darkness to think that a life as bright as Jim Foley's ended that way,"" Sennott said. ""He was an experienced and fearless journalist who believed deeply in reporting from the frontlines."" + +In an interview with The Boston Globe in 2011, Foley spoke about being held captive while covering the uprising in Libya and the importance of his job. + +“I believe that frontline journalism is important,” Foley said. “Without these photos and videos and firsthand experience, we really can’t tell the world how bad it might be.” + +Sen. Kelly Ayotte, R-N.H., had worked with Foley's family and the State Department in their efforts to get Foley back. + +""If confirmed, this barbarous and heinous act shocks the conscience and underscores the truly evil nature of the terrorists we confront, who must be defeated,"" Ayotte said in a statement.","1" +"Another American hostage at risk by Islamic state","In a horrifying act of revenge for U.S. airstrikes in northern Iraq, militants with the Islamic State extremist group have beheaded American journalist James Foley — and are threatening to kill another hostage, U.S. officials say. + +The White House must now weigh the risks of adopting an aggressive policy to destroy the Islamic State against resisting any action that could result in the death of another American. + +It will also confront the potentially necessary step of pursuing the Islamic State in Syria, where President Barack Obama has resisted launching airstrikes or deploying significant American firepower. + +Obama was expected to make a statement Wednesday about Foley's killing. + +U.S. officials confirmed a grisly video released Tuesday showing Islamic State militants beheading Foley. Separately, Foley's family confirmed his death in a statement posted on a Facebook page that was created to rally support for his release, saying they ""have never been prouder of him."" + +""He gave his life trying to expose the world to the suffering of the Syrian people,"" said the statement, which was attributed to Foley's mother, Diane Foley. She implored the militants to spare the lives of other hostages. ""Like Jim, they are innocents. They have no control over American government policy in Iraq, Syria or anywhere in the world."" + +Foley, 40, from Rochester, New Hampshire, went missing in northern Syria in November 2012 while freelancing for Agence France-Presse and the Boston-based media company GlobalPost. The car he was riding in was stopped by four militants in a contested battle zone that both Sunni rebel fighters and government forces were trying to control. He had not been heard from since. + +The beheading marks the first time the Islamic State has killed an American citizen since the Syrian conflict broke out in March 2011, upping the stakes in an increasingly chaotic and multilayered war. The killing is likely to complicate U.S. involvement in Iraq and the Obama administration's efforts to contain the group as it expands in both Iraq and Syria. + +The group is the heir apparent of the militancy known as al-Qaida in Iraq, which beheaded many of its victims, including American businessman Nicholas Berg in 2004. + +The video released on websites Tuesday appears to show the increasing sophistication of the Islamic State group's media unit and begins with scenes of Obama explaining his decision to order airstrikes. + +It then cuts to a balding man in an orange jumpsuit kneeling in the desert, next to a black-clad militant with a knife to his throat. Foley's name appears in both English and Arabic graphics on screen. After the captive speaks, the masked man is shown apparently beginning to cut at his neck; the video fades to black before the beheading is completed. The next shot appears to show the captive lying dead on the ground, his head on his body. The video appears to have been shot in an arid area; there is no vegetation to be seen and the horizon is in the distance where the sand meets the gray-blue sky. + +At the end of the video, a militant shows a second man, who was identified as another American journalist, Steven Sotloff, and warns that he could be the next captive killed. Sotloff was kidnapped near the Syrian-Turkish border in August 2013; he had freelanced for Time, the National Interest and MediaLine. + +One U.S. official said the video appeared to be authentic, and two other U.S. officials said the victim was Foley. All three officials spoke on condition of anonymity because they were not authorized to discuss the killing by name. + +Several senior U.S. officials with direct knowledge of the situation said the Islamic State very recently threatened to kill Foley to avenge the crushing airstrikes over the past two weeks against militants advancing on Mount Sinjar, the Mosul dam and the Kurdish capital of Irbil. + +Both areas are in northern Iraq, which has become a key front for the Islamic State as its fighters travel to and from Syria. + +Since Aug. 8, the U.S. military has struck at least 70 Islamic State targets — including security checkpoints, vehicles and weapons caches. It's not clear how many militants have been killed in the strikes, although it's likely that some were. + +The Islamic State militant group is so ruthless in its attacks against all people they consider heretics or infidels that it has been disowned by al-Qaida's leaders. In seeking to impose its harsh interpretation of Islamic law in the lands it is trying to control, the extremists have slain soldiers and civilians alike in horrifying ways — including mounting the decapitated heads of some of its victims on spikes. + +The New York-based Committee to Protect Journalists estimated Tuesday that about 20 journalists are missing in Syria, and has not released their nationalities. In its annual report in November, the committee concluded that the missing journalists were either being held and threatened with death by extremists, or taken captive by gangs seeking ransom. The group's report described the widespread seizure of journalists as unprecedented and largely unreported by news organizations in the hope that keeping the kidnappings out of public view may help in the captives' release. + +___ + +Associated Press writers Bradley Klapper and Julie Pace in Washington, Rik Stevens in Rochester, New Hampshire, and Zeina Karam in Beirut contributed to this report.","1" +"Obama: US Won't Stop Confronting Islamic state","The United States stood firm Wednesday in its fight with Islamic State militants who beheaded a U.S. journalist in Iraq, pledging to continue attacking the group despite its threats to kill another American hostage. The U.S. military continued its airstrikes against the group as President Barack Obama denounced the group as a ""cancer"" threatening the entire region. + +""We will be vigilant and we will be relentless,"" Obama said. + +Calling for a global response to the group that now controls territory in both Iraq and Syria, Obama condemned the group's execution of journalist James Foley, whose death he said had left the nation heartbroken. In forceful remarks, Obama accused the Islamic State of torturing, raping and murdering thousands of people in ""cowardly acts of violence."" + +""ISIL speaks for no religion,"" Obama said, using an alternative name for the Islamic State. ""Their victims are overwhelmingly Muslim, and no faith teaches people to massacre innocents. No just god would stand for what they did yesterday and what they do every single day."" + +Obama's remarks affirmed that the U.S. would not change its military posture in Iraq in response to Foley's killing. Since the video was released Tuesday, the U.S. military has pressed ahead by conducting nearly a dozen airstrikes on Islamic State targets in Iraq. + +The president said he'd told Foley's family in a phone call Wednesday that the United States joins them in honoring all that Foley did, praising the journalist for his work telling the story of the crisis in Syria, where Foley was captured in 2012. ""Jim Foley's life stands in stark contrast to his killers,"" Obama said. He spoke from Martha's Vineyard in Massachusetts, where the president is on vacation. + +Foley, 40, from Rochester, New Hampshire, went missing in northern Syria in November 2012 while freelancing for Agence France-Presse and the Boston-based media company GlobalPost. The car he was riding in was stopped by four militants in a contested battle zone that both Sunni rebel fighters and government forces were trying to control. He had not been heard from since. + +The beheading marks the first time the Islamic State has killed an American citizen since the Syrian conflict broke out in March 2011, upping the stakes in an increasingly chaotic and multilayered war. The killing is likely to complicate U.S. involvement in Iraq and the Obama administration's efforts to contain the group as it expands in both Iraq and Syria. + +The group is the heir apparent of the militancy known as al-Qaida in Iraq, which beheaded many of its victims, including American businessman Nicholas Berg in 2004. + +The video released on websites Tuesday appears to show the increasing sophistication of the Islamic State group's media unit and begins with scenes of Obama explaining his decision to order airstrikes. + +It then cuts to Foley, kneeling in the desert, next to a black-clad militant with a knife to his throat. After the captive speaks, the militant is shown apparently beginning to cut at his neck; the video fades to black before the beheading is completed. The next shot shows the captive lying dead. The video appears to have been shot in an arid area; there is no vegetation to be seen and the horizon is in the distance where the sand meets the gray-blue sky. + +At the end of the video, a militant shows a second man, who was identified as another American journalist, Steven Sotloff, and warns that he could be the next captive killed. Sotloff was kidnapped near the Syrian-Turkish border in August 2013; he had freelanced for Time, the National Interest and MediaLine. + +___ + +Associated Press writers Lita Baldor, Bradley Klapper, Julie Pace and Josh Lederman in Washington, Ryan Lucas in Beirut, Rik Stevens in Rochester, New Hampshire, and Zeina Karam in Beirut contributed to this report","1" +"ISIL allegedly kills US journalist in video","In a video titled ""A Message to America,"" ISIL militants beheaded a man that they say is American reporter James Wright Foley.","1" +"ISIL kills purported US journalist in video","In a video titled ""A Message to America,"" ISIL militants beheaded a man that they say is American reporter James Wright Foley.","1" +"ISIL kills man who appears to be US journalist James Wright Foley","""As a government you have been at the forefront of the aggression towards the Islamic State. You have plotted against us and gone far out of your way to find reasons to interfere with our affairs… Your strikes have caused casualties amongst Muslims… You are no longer fighting an insurgency. We are an Islamic army."" +SPEAKER IN VIDEO +The person who appears to execute Foley in the video speaks in English with what sounds to be a British accent. The video also shows a man identified as Steven Joel Sotloff, another American journalist. The speaker says Sotloff's life ""depends on Obama's next decision."" +""The intelligence community is working as quickly as possible to determine [the video's] authenticity... We will provide more information when it is available,"" said National Security Council spokesperson Caitlin Hayden. +Foley had last been seen in northwest Syria in Nov. 2012. He'd been working as a freelance reporter and photographer for the news service GlobalPost. +4 +""You don't want to be defined as that guy who got captured in 2011… I believe that front-line journalism is important."" +JAMES WRIGHT FOLEY +Foley worked across the Middle East and North Africa, and was previously held captive for 44 days in Libya. He shared his thoughts on the experience after his release, in a May 2011 interview.","1" +"ISIS Beheads American Journalist James Foley in Video Message to U.S.","ISIS militants released gruesome video footage this afternoon of the beheading of American photojournalist James Wright Foley as a message to the U.S. to stop intervening in Iraq. Foley, a freelancer who contributed to the Global Post, was first captured in Libya in 2012, released, and then kidnapped again around Thanksgiving 2012 by unidentified gunmen in Syria. He was 39 years old. + +The (extremely disturbing) video can be viewed here. @Mujahid4life tweeted stills from it, which are (aside from the one below), sickeningly graphic. + +The Global Post reported the circumstances of his disappearance last year, after attempting to keep the news quiet for fear of Foley's safety: + +Foley had set off toward the border in a car about an hour before his capture. A witness, a Syrian, later recounted over the phone to a journalist in Turkey that an unmarked car intercepted Foley. The witness said men holding kalashnikovs shot into the air and forced Jim out of the car. + +The witness said he noticed nothing that would indicate whether the aggressors were rebel fighters, individuals looking for a ransom, members of a pro-government militia, or a religious-based group with other motivations. +He was held captive for 635 days. + +In 2013, Foley's family set up a Find James Foley website for him, which states that he's the oldest of five children. His friend, journalist Clare Morgana Gillis, wrote about him for Syria Deeply last year: + +Jim sees the good in nearly everything and everyone. He is a master motivator. ""You got this, dude!"" he'll say. ""That story's great, just file it already."" ... + +Everybody, everywhere, takes a liking to Jim as soon as they meet him.","1" +"Islamic Militants Post Video Claiming to Show Beheading of U.S. Journalist","Editors' note: There are images in this post that some readers may find distressing. + +Islamic State militants on Tuesday released a video that purported to show the beheading of James Foley, an American freelance journalist who has been missing since he was kidnapped in Syria in November 2012. + +The authenticity of the video could not be immediately verified. + +When contacted by Mashable, NSC spokesperson Caitlin Hayden said, “We have seen a video that purports to be the murder of U.S. citizen James Foley by ISIL. The intelligence community is working as quickly as possible to determine its authenticity. If genuine, we are appalled by the brutal murder of an innocent American journalist and we express our deepest condolences to his family and friends. We will provide more information when it is available.” + +James Foley in Aleppo, Syria, in November 2012. + +Image: Nicole Tung + +The video opens with a clip of President Barack Obama's remarks announcing the launch of airstrikes on Islamic State positions near Erbil in northern Iraq. A black screen then shows the text, ""A message to America,"" and then Foley appears kneeling in a desert landscape, wearing an orange jumpsuit with a microphone attached. A hooded man wearing all-black clothes and tan military boots is standing behind him with a gun in a leather holster. + +""I call on my friends, family and loved ones to rise up against my real killers, the U.S. government, for what will happen to me is only a result of their complacent criminality,"" Foley says, among other things, in remarks seemingly prepared for him by his captors. + +The video then switches to the man in black, who is now holding a serrated knife. + +""This is James Wright Foley — an American citizen of your country,"" the man says in British-accented English. ""As a government, you have been at the forefront of the aggression towards Islamic State.... Effectively, any aggression towards the Islamic State is an aggression towards Muslims from all walks of life who have accepted the Islamic Caliphate as their leadership. So any attempt by you, Obama, to deny the safety of Muslims living under the safety of the Islamic Caliphate will result in the bloodshed of your people."" + +The man then beheads Foley, using the knife as the video fades to black. After a shot of Foley's lifeless body and decapitated head, the video switches to the executioner now standing behind another man in an orange jumpsuit, identified in text on the screen as Steven Joel Sotloff. + +""The life of this American prisoner, Obama, depends on your next decision."" + +Sotloff, an American freelance journalist who had been working for Time magazine among other publications, was kidnapped near the Syrian-Turkish border on Aug. 4, 2013. + +The video then goes black. + +The video was first reported by Zaid Benjamin, a reporter for the Arabic-language Radio Sawa, who said that it came from Furqan Media, the official outlet for the Islamic State. (Twitter suspended — then reinstated — the account.) + +The video appeared to surface first on the Twitter account @mujahid4life, belonging to someone who described himself in his Twitter bio as 19 years old, ""anti-democracy. Loyal to the Caliphate. Harsh on kuffar. #Revert"" + +It didn't take long before people who had worked with Foley began reacting on Twitter. + +I was w/ James Foley in Aleppo, August 2012 for a day in #Selahaddin. Syrian opposition members were adoring him. He was a kind, brave man + +— ilhan tanir (@WashingtonPoint) August 19, 2014 + +My thoughts are with James Foley’s family. No matter what he faced, he was unfailingly kind, generous, and warm. A wonderful soul. + +— Max Fisher (@Max_Fisher) August 19, 2014 + +There was also anger on Twitter that YouTube didn't immediately take down the video. + +It's lucky that video didn't have a unlicensed Katy Perry song as a soundtrack or it would've been deleted from YouTube in seconds. + +— Tom Gara (@tomgara) August 19, 2014 + +However, within an hour of the first report of the beheading, the video was taken down. + +Images from the video are below, showing Foley before his execution and Sotloff being threatened: + +Shortly after the clip appeared on the web, journalists and observers who watch the region began tweeting a hashtag — #ISISmediaBlackout — pledging to stop sharing Islamic State propaganda. + +""You know what I think? And I know how crazy this sounds, but we need an #ISISmediaBlackout. Amputate their reach. Pour water on their flame,"" said a Tumblr blogger known as LibyaLiberty on Twitter in what appeared to be the first mention of the hashtag. ""From here on out, I won't share any photo or video of violence intentionally recorded & released by ISIS for propaganda,"" she tweeted. Many others, promptly, joined her pledge. + +A statement from a group called Free James Foley said: ""We know that many of you are looking for confirmation or answers. Please be patient until we all have more information, and keep the Foleys in your thoughts and prayers."" + +Post by Free James Foley. + +Foley's parents appeared on the Today show last year, pleading for his release. + +UPDATED 8:28 p.m. ET: GlobalPost CEO Philip Balboni released a statement Tuesday about the video that purportedly shows the beheading of journalist James Foley. + +""On behalf of John and Diane Foley, and also GlobalPost, we deeply appreciate all of the messages of sympathy and support that have poured in since the news of Jim’s possible execution first broke. We have been informed that the FBI is in the process of evaluating the video posted by the Islamic State to determine if it is authentic,"" Balboni said. + +“Although GlobalPost’s investigation at one point led us to believe that James was being held by the Syrian government, we later were given strong reason to believe he was being held by Islamic rebels in Syria,"" he added. ""We withheld this information at the request of the family and on the advice of authorities cooperating in the effort to protect Jim. GlobalPost, working with a private security company, has amassed an enormous amount of information that has not been made public.” + +Foley reported in Syria for GlobalPost as a freelancer. + +Have something to add to this story? Share it in the comments.","1" +"Video showing American journalist beheaded believed real, officials and family say","Two U.S. officials say they believe American journalist James Foley was the victim executed by ISIS militants as shown in a grisly video released Tuesday. + +Separately, Foley’s family confirmed his death in a statement posted on a webpage that was created to rally support for his release. + +In the statement, Foley’s mother, Diane Foley, said the journalist, quote, “gave his life trying to expose the world to the suffering of the Syrian people.” + +One of the U.S. officials said President Barack Obama was expected to make a statement about the killing on Wednesday. + +The U.S. officials spoke on condition of anonymity because they were not authorized to discuss the video by name. + +Foley, a 40-year-old freelance journalist from Rochester, New Hampshire, went missing nearly two years ago in northern Syria while on assignment for Agence France-Press and the Boston-based media company GlobalPost. The car he was riding in was stopped by four militants in a contested battle zone that both Sunni rebel fighters and government forces were trying to control. He had not been heard from since. + +Several senior U.S. officials with direct knowledge of the situation said the Islamic State very recently threatened to kill Foley to avenge the crushing airstrikes over the last two weeks against militants advancing on Mount Sinjar, the Mosul dam and the Kurdish capital of Irbil. + +Both areas are in northern Iraq, which has become a key front for the Islamic State as its fighters travel to and from Syria. + +The officials spoke on condition of anonymity because they were not authorized to discuss the hostage situation by name. + +Since Aug. 8, the U.S. military has struck more than 70 Islamic State targets – including security checkpoints, vehicles and weapons caches. It’s not clear how many militants have been killed in the strikes, although it’s likely that some were. + +The Internet video begins with scenes of President Barack Obama explaining his decision to order airstrikes in Iraq. Then it switches to a balding man in an orange jumpsuit kneeling in the desert, a black-clad Islamic State fighter by his side. Foley’s name appears in both English and Arabic graphics on screen. The video appears to have been shot in an arid area; there is no vegetation in sight and the horizon is in the distance where the sand meets the gray-blue sky. + +The New York-based Committee to Protect Journalists estimated Tuesday that about 20 journalists are missing in Syria, and has not released their nationalities. In its annual report last November, CPJ concluded that the missing journalists are either being held and threatened with death by extremists, or taken captive by gangs seeking ransom. The group’s report described the widespread seizure of journalists as unprecedented and largely unreported by news organizations in the hope that keeping the kidnappings out of public view may help in the captives’ release. + +The Islamic State militant group is so ruthless in its attacks against all people they consider heretics or infidels that it has been disowned by al-Qaida’s leaders. In seeking to impose its harsh interpretation of Islamic law in the lands it is trying to control, the extremists have killed soldiers and civilians alike in horrifying executions – including mounting the decapitated heads of some of its victims on spikes. + +The group is the heir apparent of the militancy known as al-Qaida in Iraq, which beheaded many of its victims, including Americans businessman Nicholas Berg in 2004.","1" +"ISIS Seemingly Beheaded American Journalist James Wright Foley","Islamic State militants appear to have killed missing American journalist James Wright Foley, if a video that surfaced Tuesday is to be believed. + +Foley was a freelancer who frequently reported for the Global Post and Agence France-Presse about ongoing conflicts in the Middle East. When Foley first disappeared in Syria, reports indicated that he had been captured by pro-government forces. Instead, it appears that his captors were members of ISIS. He had previously been kidnapped in Libya. + +The video that surfaced Tuesday first shows a clip from President Obama's press conference calling for air strikes against ""the terrorist group ISIL."" About halfway in, a man believed to be Foley speaks in English to his family. He's on his knees, with an ISIS guard standing over him. In a [likely ISIS-scripted] speech, he blames Obama and the U.S. government for his impending death and implores his family not to take a penny from the government. He then addresses his brother, John, who is in the U.S. Air Force. + +""I died that day, John,"" he says, referring to U.S. air strikes against the militant group. ""When your colleagues dropped that bomb on those people, they signed my death certificate."" + +When the video reorients itself to focus back on Foley and his executioner, the mike previously hooked up to his shirt is gone. The militant spouts off an angry tirade against the United States, and the camera cuts away after the first few seconds of the beheading. + +At the end of the video, ISIS militants parade another captive journalist, Steven Sotloff, who they threaten will be the next victim if the U.S. government's policy toward the militant group doesn't change. + +The video was taken down from Youtube shortly after it was publicized. A HuffPo blogger who claimed to have shared the video apologized for doing so: + +As of November 2013, at least 30 journalists were being held captive in Syria. Many more have been killed in the ongoing conflict.","1" +"ISIS Seemingly Beheaded American Journalist James Wright Foley [Updated]","Islamic State militants appear to have killed missing American journalist James Wright Foley, if a video that surfaced Tuesday is to be believed. + +Foley was a freelancer who frequently reported for the Global Post and Agence France-Presse about ongoing conflicts in the Middle East. When Foley first disappeared in Syria, reports indicated that he had been captured by pro-government forces. Instead, it appears that his captors were members of ISIS. He had previously been kidnapped in Libya. + +The video that surfaced Tuesday first shows a clip from President Obama's press conference calling for air strikes against ""the terrorist group ISIL."" About halfway in, a man believed to be Foley speaks in English to his family. He's on his knees, with an ISIS guard standing over him. In a [likely ISIS-scripted] speech, he blames Obama and the U.S. government for his impending death and implores his family not to take a penny from the government. He then addresses his brother, John, who is in the U.S. Air Force. + +""I died that day, John,"" he says, referring to U.S. air strikes against the militant group. ""When your colleagues dropped that bomb on those people, they signed my death certificate."" + +When the video reorients itself to focus back on Foley and his executioner, the mike previously hooked up to his shirt is gone. The militant spouts off an angry tirade against the United States, and the camera cuts away after the first few seconds of the beheading. + +At the end of the video, ISIS militants parade another captive journalist, Steven Sotloff, who they threaten will be the next victim if the U.S. government's policy toward the militant group doesn't change. + +The video was taken down from Youtube shortly after it was publicized. A HuffPo blogger who claimed to have shared the video apologized for doing so: + +Deleted video sharing #ISIS propaganda. I apologise immensely for sharing it. We must not let them win by sharing their content. + +As of November 2013, at least 30 journalists were being held captive in Syria. Many more have been killed in the ongoing conflict. + +UPDATE: One U.S. official told the Associated Press that the video appears to be authentic, and two other officials identified Foley as the victim. Diane Foley, the journalist's mother, also confirmed the news in a statement posted on Facebook: + +We have never been prouder of our son Jim. He gave his life trying to expose the world to the suffering of the Syrian people. + +We implore the kidnappers to spare the lives of the remaining hostages. Like Jim, they are innocents. They have no control over American government policy in Iraq, Syria or anywhere in the world. + +We thank Jim for all the joy he gave us. He was an extraordinary son, brother, journalist and person. Please respect our privacy in the days ahead as we mourn and cherish Jim. + +President Obama is expected to make a statement about Foley's killing on Wednesday.","1" +"Islamic State claims to have beheaded American journalist","Bloodthirsty militants in Iraq released a horrific video on Tuesday that shows the apparent beheading of American journalist James Wright Foley — with the execution aimed at forcing President Obama to put an end to US airstrikes. + +Foley, a 40-year-old photojournalist kidnapped in 2012, was forced to recite anti-American hatred from his Islamic State in Iraq and Syria captors as his final words before a masked killer put the knife to his neck. + +The video — which was posted on YouTube until the site yanked it down — shows Foley dressed in prisoner orange and on his knees in the desert area. His head is shaved. Behind him is a man covered head to toe in black. It’s titled “A Message to America.” + +“Any attempt by you, Obama, to deny Muslims liberty and safety under the Islamic caliphate, will result in the bloodshed of your people,” an Islamic State of Iraq and Syria terrorist says in reference to US airstrikes in Iraq. + +A stone-faced Foley — who was last seen on Thanksgiving 2012 while working for Agence France-Presse — then bravely reads a clearly coerced statement. + +“I call on my friends family and loved ones to rise up against my real killers, the U.S. government. My message to my beloved parents: Save me some dignity and don’t accept any meager compensation for my death from the same people who effectively put the last nail in my coffin,” he said. + +“I call on my brother who is in the Air Force. I call on you, John. Think about who made the decision to bomb Iraq. Who did they really kill? Did they think about me you and our family when they made that decision? I died that day, John. When your colleagues dropped that bomb, they signed my death certificate. I wish I had more time. I wish I had the hope of seeing my family one more time.” + +As a final insult, his last forced words were, “I guess all-in-all I wish I wasn’t American.” + +The video then shows another American — Time journalist Steven Joel Sotloff — and the group says he is next unless the US backs off. + +He is being held by the collar as he kneels in the desert, also wearing prisoner orange and a shaved head. + +Sotloff was abducted in Syria in August 2013. His last Tweet was about his hometown Miami Heat. + +“The life of this American citizen, Obama, depends on your next decision,” the masked man says. + +White House National Security Council Spokesperson Caitlin Hayden said they’re analyzing the video of the beheading to determine its authenticity. + +“If genuine, we are appalled by the brutal murder of an innocent American journalist and we express our deepest condolences to his family and friends,” Hayden said. + +ISIS had warned the US of the potential murder in an earlier video saying, “We will drown all of you in blood” in retaliation for US airstrikes that have been pounding them. + +Several senior U.S. officials with direct knowledge of the situation said the Islamic State very recently threatened to kill Foley to avenge crushing airstrikes over the last two weeks against militants advancing on Mount Sinjar, the Mosul dam and the Kurdish capital of Irbil. + +US Rep. Peter King (R-NY) said the video reveals ISIS for the true murders they are. + +“ISIS is the worst of the worst,” King said. “These guys are truly animals.… We have to go after them and destroy them.” + +Foley family friend Holly Rene, who lives in their hometown of Rochester, NH, told The Post, “These savages have got to be stopped. It’s coming West.” + +She said the family is “falling apart with grief. + +“I was just so hopeful Jimmy had, if they weren’t going to get any good news, that he would have been dead for a long time now and there was no suffering involved. And to think he went through two years just to have this ending, it’s beyond belief.” + +Foley’s family had set up website to plead for Foley’s return — and urged patience on Tuesday. + +“We know that many of you are looking for confirmation or answers,” the Find James Foley Facebook wrote: “Please be patient until we all have more information, and keep the Foleys in your thoughts and prayers.” + +Foley, one of five children, had been captured previously in Libya for 45 days in 2011. + +He graduated from Marquette University in 1996 and later studied journalism at Northwestern University. + +He penned a letter to Marquette Magazine thanking the community for its prayers when he was captured in Tripoli with two colleagues. He recounted getting to call his mother from prison and learning of the university’s prayer vigil for his release. + +“If nothing else, prayer was the glue that enabled my freedom, an inner freedom first and later the miracle of being released during a war in which the regime had no real incentive to free us,” Foley wrote. “It didn’t make sense, but faith did.”","1" +"Mom’s loving tribute to reporter son murdered by jihadi savages","Bloodthirsty militants in Iraq released a horrific video Tuesday that shows the beheading of American photojournalist James Wright Foley — with the execution aimed at forcing President Obama to end US airstrikes. + +Foley, 40, who was kidnapped in Syria nearly two years ago, was forced to recite anti-American hatred before a masked Islamic State killer put the knife to his neck. + +The video — posted on YouTube before being yanked — shows Foley dressed in prisoner orange and on his knees in the desert. His head is shaved. Behind him is his knife-wielding killer, covered from head to toe in black. Its title is “A Message to America.” + +“Any attempt by you, Obama, to deny Muslims liberty and safety under the Islamic caliphate will result in the bloodshed of your people,” the terrorist says in reference to US airstrikes against the Islamic State. + +Foley — last seen on Thanksgiving 2012 while working for Agence France-Presse — earlier reads a clearly coerced statement. + +“I call on my friends, family and loved ones to rise up against my real killers, the US government. My message to my beloved parents: Save me some dignity and don’t accept any meager compensation for my death from the same people who effectively put the last nail in my coffin,” he says. + +“I call on my brother, who is in the Air Force. I call on you, John. Think about who made the decision to bomb Iraq. Who did they really kill? Did they think about me, you and our family when they made that decision? I died that day, John. When your colleagues dropped that bomb, they signed my death certificate. I wish I had more time. I wish I had the hope of seeing my family one more time.” + +As a final insult, his last forced words were, “I guess, all in all, I wish I wasn’t American.” + +The video then cuts to a gruesome image of Foley’s blood-soaked head, detached from his body and resting on his back near his shackled hands. + +The militants then display another kneeling and shackled American — Time journalist Steven Joel Sotloff — and the group says he is next unless the United States backs off. + +Sotloff was abducted in Syria in August 2013. + +“The life of this American citizen, Obama, depends on your next decision,” the masked man says. + +In a statement posted on a Facebook page affiliated with the Foley family, James’ mother, Diane, said, “We have never been prouder of our son Jim. He gave his life trying to expose the world to the suffering of the Syrian people. + +“We thank Jim for all the joy he gave us. He was an extraordinary son, brother, journalist and person.” + +She also called for an end to Islamic State brutality, saying: “We implore the kidnappers to spare the lives of the remaining hostages. Like Jim, they are innocents.” + +Obama was briefed on Foley’s barbaric murder while flying on Air Force One to Martha’s Vineyard to resume his vacation. + +Two US officials said they believe the video is authentic, although White House National Security Council spokeswoman Caitlin Hayden said US intelligence is still analyzing it. + +“If genuine, we are appalled by the brutal murder of an innocent American journalist and we express our deepest condolences to his family and friends,” Hayden said. + +The Washington Post reported that European officials were going over the video to compare the voice of the executioner — who seemed to have a trace of a British accent — with ex-Guantanamo Bay inmates who had British ties. + +The Islamic State — also known as the Islamic State in Iraq and Syria, or ISIS — had warned the United States of the potential murder in an earlier video, saying, “We will drown all of you in blood” in revenge. + +Senior US officials with direct knowledge of the situation said the Islamic State recently threatened to kill Foley to avenge the airstrikes that freed ethnic Yazidis who had been trapped by the terrorists on Mount Sinjar, and that helped Kurds retake the crucial Mosul dam from the Islamic State. + +Foley family friend Holly Rene, who lives in their hometown of Rochester, NH, told The Post, “These savages have got to be stopped. It’s coming West.” + +She said the family is “falling apart with grief.” + +Foley, one of five children, had been a hostage before, having been held in Libya for 45 days in 2011. + +He graduated from Marquette University in 1996 and later studied journalism at Northwestern. + +He penned a letter to Marquette Magazine thanking the community for its prayers when he was captured in Tripoli with two colleagues. + +“If nothing else, prayer was the glue that enabled my freedom, an inner freedom first and later the miracle of being released during a war in which the regime had no real incentive to free us,” Foley wrote. “It didn’t make sense, but faith did.”","1" +"Jihadi savages: Captured Time journalist is next","Bloodthirsty militants in Iraq released a horrific video Tuesday that shows the beheading of American photojournalist James Wright Foley — with the execution aimed at forcing President Obama to end US airstrikes. + +Foley, 40, who was kidnapped in Syria nearly two years ago, was forced to recite anti-American hatred before a masked Islamic State killer put the knife to his neck. + +The video — posted on YouTube before being yanked — shows Foley dressed in prisoner orange and on his knees in the desert. His head is shaved. Behind him is his knife-wielding killer, covered from head to toe in black. Its title is “A Message to America.” + +“Any attempt by you, Obama, to deny Muslims liberty and safety under the Islamic caliphate will result in the bloodshed of your people,” the terrorist says in reference to US airstrikes against the Islamic State. + +Foley — last seen on Thanksgiving 2012 while working for Agence France-Presse — earlier reads a clearly coerced statement. + +“I call on my friends, family and loved ones to rise up against my real killers, the US government. My message to my beloved parents: Save me some dignity and don’t accept any meager compensation for my death from the same people who effectively put the last nail in my coffin,” he says. + +“I call on my brother, who is in the Air Force. I call on you, John. Think about who made the decision to bomb Iraq. Who did they really kill? Did they think about me, you and our family when they made that decision? I died that day, John. When your colleagues dropped that bomb, they signed my death certificate. I wish I had more time. I wish I had the hope of seeing my family one more time.” + +As a final insult, his last forced words were, “I guess, all in all, I wish I wasn’t American.” + +The video then cuts to a gruesome image of Foley’s blood-soaked head, detached from his body and resting on his back near his shackled hands. + +The militants then display another kneeling and shackled American — Time journalist Steven Joel Sotloff — and the group says he is next unless the United States backs off. + +Sotloff was abducted in Syria in August 2013. + +“The life of this American citizen, Obama, depends on your next decision,” the masked man says. + +In a statement posted on a Facebook page affiliated with the Foley family, James’ mother, Diane, said, “We have never been prouder of our son Jim. He gave his life trying to expose the world to the suffering of the Syrian people. + +“We thank Jim for all the joy he gave us. He was an extraordinary son, brother, journalist and person.” + +She also called for an end to Islamic State brutality, saying: “We implore the kidnappers to spare the lives of the remaining hostages. Like Jim, they are innocents.” + +Obama was briefed on Foley’s barbaric murder while flying on Air Force One to Martha’s Vineyard to resume his vacation. + +Two US officials said they believe the video is authentic, although White House National Security Council spokeswoman Caitlin Hayden said US intelligence is still analyzing it. + +“If genuine, we are appalled by the brutal murder of an innocent American journalist and we express our deepest condolences to his family and friends,” Hayden said. + +The Washington Post reported that European officials were going over the video to compare the voice of the executioner — who seemed to have a trace of a British accent — with ex-Guantanamo Bay inmates who had British ties. + +The Islamic State — also known as the Islamic State in Iraq and Syria, or ISIS — had warned the United States of the potential murder in an earlier video, saying, “We will drown all of you in blood” in revenge. + +Senior US officials with direct knowledge of the situation said the Islamic State recently threatened to kill Foley to avenge the airstrikes that freed ethnic Yazidis who had been trapped by the terrorists on Mount Sinjar, and that helped Kurds retake the crucial Mosul dam from the Islamic State. + +Foley family friend Holly Rene, who lives in their hometown of Rochester, NH, told The Post, “These savages have got to be stopped. It’s coming West.” + +She said the family is “falling apart with grief.” + +Foley, one of five children, had been a hostage before, having been held in Libya for 45 days in 2011. + +He graduated from Marquette University in 1996 and later studied journalism at Northwestern. + +He penned a letter to Marquette Magazine thanking the community for its prayers when he was captured in Tripoli with two colleagues. + +“If nothing else, prayer was the glue that enabled my freedom, an inner freedom first and later the miracle of being released during a war in which the regime had no real incentive to free us,” Foley wrote. “It didn’t make sense, but faith did.”","1" +"Savages! Islamic State executes American journalist","Bloodthirsty militants in Iraq released a horrific video on Tuesday that shows the beheading of American photojournalist James Wright Foley — with the execution aimed at forcing President Obama to end US airstrikes. + +Foley, 40, who was kidnapped in Syria nearly two years ago, was forced to recite anti-American hatred before a masked ISIS killer put the knife to his neck. + +The video — posted on YouTube before being yanked — shows Foley dressed in prisoner orange and on his knees in the desert. His head is shaved. Behind him is his knife-wielding killer, covered head to toe in black. It’s title is “A Message to America.” + +“Any attempt by you, Obama, to deny Muslims liberty and safety under the Islamic caliphate will result in the bloodshed of your people,” the terrorist says in reference to US airstrikes against ISIS. + +Foley — last seen on Thanksgiving 2012 while working for Agence France-Presse — earlier reads a clearly coerced statement. + +“I call on my friends family and loved ones to rise up against my real killers, the US government. My message to my beloved parents: Save me some dignity and don’t accept any meager compensation for my death from the same people who effectively put the last nail in my coffin,” he says. + +“I call on my brother, who is in the Air Force. I call on you, John. Think about who made the decision to bomb Iraq. Who did they really kill? Did they think about me you and our family when they made that decision? I died that day, John. When your colleagues dropped that bomb, they signed my death certificate. I wish I had more time. I wish I had the hope of seeing my family one more time.” + +James Wright Foley As a final insult, his last forced words were, “I guess, all-in-all, I wish I wasn’t American.” + +The video then cuts to a gruesome image of Foley’s blood-soaked head, detached from his body and resting on his back near his shackled hands. + +The militants then display another kneeling and shackled American — Time journalist Steven Joel Sotloff — and the group says he is next unless the United States backs off. + +Sotloff was abducted in Syria in August 2013. + +“The life of this American citizen, Obama, depends on your next decision,” the masked man says. + +In a statement posted on a Facebook page affiliated with the Foley family, James’ mother, Diane, said, “We have never been prouder of our son Jim. He gave his life trying to expose the world to the suffering of the Syrian people. + +“We have never been prouder of our son Jim. He gave his life trying to expose the world to the suffering of the Syrian people,” she said. + +“We thank Jim for all the joy he gave us. He was an extraordinary son, brother, journalist and person.” + +She also called for an end to ISIS brutality, saying “We implore the kidnappers to spare the lives of the remaining hostages. Like Jim, they are innocents.” + +Obama was briefed on Foley’s barbaric murder while flying on Air Force One to Martha’s Vineyard to resume his vacation. + +Two US officials said they believe the video is authentic, although White House National Security Council spokeswoman Caitlin Hayden said US intelligence is still analyzing it. + +“If genuine, we are appalled by the brutal murder of an innocent American journalist and we express our deepest condolences to his family and friends,” Hayden said. + +The Washington Post reported that European officials were going over the video to compare the voice of the executioner — who seemed to have a trace of a British accent — with ex-Guantanamo Bay inmates who had British ties. + +ISIS — the Islamic State in Iraq and Syria — had warned the United States of the potential murder in an earlier video, saying, “We will drown all of you in blood” in revenge. + +Senior US officials with direct knowledge of the situation said ISIS recently threatened to kill Foley to avenge the airstrikes that freed ethnic Yazidis who had been trapped by the terrorists on Mount Sinjar, and that helped Kurds retake the crucial Mosul Dam from ISIS. + +Foley family friend Holly Rene, who lives in their hometown of Rochester, NH, told The Post, “These savages have got to be stopped. It’s coming West.” + +She said the family is “falling apart with grief.” + +Foley, one of five children, had been a hostage before, being held in Libya for 45 days in 2011. + +He graduated from Marquette University in 1996 and later studied journalism at Northwestern. + +He penned a letter to Marquette Magazine thanking the community for its prayers when he was captured in Tripoli with two colleagues. + +“If nothing else, prayer was the glue that enabled my freedom, an inner freedom first and later the miracle of being released during a war in which the regime had no real incentive to free us,” Foley wrote. “It didn’t make sense, but faith did.”","1" +"Pure Evil: Islamic State Beheads American Journalist James Wright Foley","The Islamic State kidnapped American journalist James Foley on November 22, 2012. + +Foley was a freelance photo journalist covering the civil war in Syria at the time. + + +IS has held him ever since, but today they tweeted out video of his beheading. + +They want publicity from this barbaric act, and I’m loathe to give it to them even by writing a few words about it. + +But their barbarity needs to be exposed. + +President Obama is reluctant to do anything about the Islamic State’s spread, other than to order airstrikes. Over the past few days, those airstrikes have helped the Kurdish and Iraqi forces fight IS. Iraqi forces recaptured the strategic Mosul dam. + +But IS is far from broken. They still hold Mosul and several other Iraqi and Syrian cities. They are still capturing Iraqi Christians and Yazidis and reportedly selling captured women into sex slavery. They are murdering people by the dozens, by the hundreds. IS has designs on consolidating its power in Iraq and Syria and using that as a springboard to attack the United States and Europe. Tellingly, the murderer in the IS video of Foley’s execution — which I won’t post here — has a British accent. + +IS is still holding American journalist Steven Sotloff. They have tweeted photos of him kneeling in an orange jumpsuit, next to a probable executioner, and declared that his life depends on what President Obama does next.","1" +"Islamic State militants claim to behead missing American journalist","Islamic State militants have released a graphic video allegedly depicting the beheading of American photojournalist James Wright Foley, who has been missing in Syria since 2012. + +The Islamist group also threatened to kill another American journalist, Steven Joel Sotloff of World Affairs and Time, stating his fate is in the hands of President Barack Obama. + +Foley went missing almost two years ago while covering the conflict in Syria as a freelance photographer. The 39-year-old reporter was working for Agence France-Presse when he disappeared, and his whereabouts were essentially unknown until this recording surfaced. + +His November 22nd disappearance was classified as a kidnapping by the FBI, which stated he “was taken by an organized gang after departing from an internet café in Binesh, Syria.” + +In the new video, the militants proclaimed the violent act as “a message to America” for its decision to launch airstrikes against the Islamic State in Iraq, where it has made rapid territorial conquests over the last few months. + +After stating that President Obama’s decision to authorize military action against the extremist group “effectively [placed] America upon a slippery slope towards a new war front against Muslims,” Foley appears kneeling beside a masked man. He is forced to read a letter which blames the US government for “hammering the final nail into his coffin” before the masked man takes his life. +Sotloff’s life, meanwhile, “depends on Obama’s next decision,” the group claimed. Sotloff has been missing since mid-2013, and his Twitter account indicates his last known location was Libya. + +In a statement, the US National Security Council confirmed it had seen the video, but added that it's still working to determine its authenticity. + +""If genuine, we are appalled by the brutal murder of an innocent American journalist and we express our deepest condolences to his family and friends,"" NSC spokeswoman Caitlin Hayden said. + +The video’s release comes just one day after militants declared they would attack American targets “in any place” if American airstrikes kill any of their members. Militants said, “we will drown all of you in blood” and flashed images of an American was beheading during the United States’ initial invasion of Iraq. + +So far, the Islamic State’s campaign through Iraq has seen numerous reports of beheadings, including those carried out against child victims. The group has regularly threatened Christians and other minorities to either convert to their radical take on Islam or die, and even forced tens of thousands of ethnic Yazidis to flee to Sinjar Mountain with no food or water in order to escape being executed. + +The last event triggered renewed military and humanitarian action by the United States earlier this month, and airstrikes have been used to help Kurdish security forces beat back militant fighters from northern Iraq. On Monday, Obama announced Iraqi and Kurdish forces had retaken control of the Mosul Dam – Iraq’s largest, and a key strategic landmark – marking the most significant victory for Iraqi troops since the US became involved again.","1" +"Islamic State Militants Claim to Have Beheaded US Journalist James Wright Foley","Islamic State militants released a video on Tuesday purporting to show the beheading of American journalist James Wright Foley, who has been missing since he was kidnapped in northwest Syria on November 22, 2012. Foley was abducted by unknown gunmen outside a cafe in Binesh, along with his translator, who was later released. + +Another captive is shown at the end of the video. He is identified as Steven Sotloff, an American journalist who has been missing since August 2013. + +The video has not yet been independently verified. The video and images were released on Twitter by user @mujahid4life. The account has since been suspended. + +A freelancer known for his work covering conflict in Iraq, Afghanistan, Syria, and Libya, Foley had contributed work to GlobalPost, Agence France-Presse, and various other outlets. In 2011, he was kidnapped and held by pro-Qaddafi forces in Libya before being released after 45 days. + +""Captivity is the state most violently opposite his nature,"" his friend Clare Morgana Gillis, a journalist who had been kidnapped with him in Libya in 2011, wrote in a piece last year for Syria Deeply. ""But when we were detained in Tripoli, Jim automatically turned his energies to keeping up our strength and hope."" + +In the video, the man identified as Foley delivers what appears to be a prepared statement. + +""I call on my friends, family, and loved ones to rise up against my real killers, the US government,"" he says. ""For what will happen to me is only a result of their complacency and criminality."" + +He goes on to decry the American aerial operation in Iraq, and ends by saying, ""I wish I could have the hope of freedom and seeing my family once again. But that ship has sailed. I guess all in all I wish I wasn't American."" + +A masked militant attired in black stands beside him. + +""This is James Wright Foley, an American citizen of your country,"" the militant says, brandishing a knife in his left hand. ""As a government, you have been at the forefront of the aggression towards the Islamic State. You have plotted against us and gone far out of your way to find reasons to interfere in our affairs. Today your military air force is attacking us daily in Iraq. Your strikes have caused casualties amongst Muslims. You are no longer fighting an insurgency. We are an Islamic army, and a state that has been accepted by a large number of Muslims worldwide. So effectively any aggression towards the Islamic State is an aggression towards Muslims from all walks of life who have accepted the Islamic caliphate as their leadership. So any attempt by you, Obama, to deny the Muslims their rights of living in safety under the Islamic caliphate will result in the bloodshed of your people."" + +The video then shows the militant begin to cut the man's throat with the knife before fading to black, followed by a graphic image of his body. + +The militant then appears standing beside the man identified as Sotloff. + +""The life of this American citizen, Obama, depends on your next decision,"" he says.","1" +"Video Purports to Show Beheading of American Journalist","James Foley went missing in November 2012 + +A video posted online Tuesday purportedly shows an Islamist extremist beheading James Foley, an American journalist kidnapped in Syria more than 18 months ago. + +A graphic video of the purported killing, whose authenticity could not be immediately verified, was posted online Tuesday and quickly spread on social media. The video, which appears to be the work of the militant group Islamic State of Iraq and Greater Syria, declares the act “A Message to #America (from the #IslamicState)” and retribution for the United States’ intervention against ISIS in Iraq. Some versions of the video and Twitter accounts circulating it were quickly taken offline Tuesday evening, though the video soon appeared on YouTube again. + +TIME is not publishing the video. The video also includes a threat to kill Steven Sotloff, a freelance journalist who has written for TIME among other outlets, and has been missing since August 2013. + +A Facebook page affiliated with the Foley family’s campaign for his release posted a message Tuesday saying it couldn’t confirm the authenticity of the video or Foley’s fate. + +“We know that many of you are looking for confirmation or answers,” the post read. “Please be patient until we all have more information, and keep the Foleys in your thoughts and prayers.” + +A spokesperson for the U.S. National Security Council said the American intelligence community “is working as quickly as possible to determine its authenticity.” + +“If genuine, we are appalled by the brutal murder of an innocent American journalist and we express our deepest condolences to his family and friends,” NSC spokesperson Caitlin Hayden said. “We will provide more information when it is available.” + +Foley “was taken by an organized gang after departing from an internet café in Binesh, Syria,” near the Turkish border, the FBI said in an alert following the Nov. 22, 2012, kidnapping. He was in Binesh covering the Syrian civil war for the GlobalPost website and AFP. + +Foley, 40, grew up in New Hampshire, where his parents live.","1" +"Video Shows Beheading of American Journalist","James Foley went missing in November 2012 + +Updated 11:43 a.m. on Aug. 20 + +A video posted online Tuesday purportedly shows an Islamist extremist beheading James Foley, an American journalist kidnapped in Syria more than 18 months ago. + +A graphic video of the purported killing, which the U.S. government believes to be authentic, was posted online Tuesday and quickly spread on social media. The video, which appears to be the work of the militant group Islamic State of Iraq and Greater Syria, declares the act “A Message to #America (from the #IslamicState)” and retribution for the United States’ intervention against ISIS in Iraq. Some versions of the video and Twitter accounts circulating it were quickly taken offline Tuesday evening, though the video soon appeared on YouTube again. + +TIME is not publishing the video. The video also includes a threat to kill Steven Sotloff, a freelance journalist who has written for TIME among other outlets, and has been missing since August 2013. + +A spokesperson for the U.S. National Security Council said Wednesday morning the American intelligence community believes the video is authentic. + +“The U.S. Intelligence Community has analyzed the recently released video showing U.S. citizens James Foley and Steven Sotloff,” said NSC spokesperson Caitlin Hayden. “We have reached the judgment that this video is authentic.” + +A Facebook page affiliated with the Foley family’s campaign for his release posted a message Tuesday evening from his mother, Diane Foley. + +“We have never been prouder of our son Jim,” she wrote. “He gave his life trying to expose the world to the suffering of the Syrian people…We thank Jim for all the joy he gave us. He was an extraordinary son, brother, journalist and person. Please respect our privacy in the days ahead as we mourn and cherish Jim.” + +White House spokesman Eric Schultz said in a statement Tuesday that President Barack Obama had been briefed on the video and “will continue to receive regular updates.” + +The White House announced that Obama will deliver a statement at 12:45 p.m. Wednesday. + +Foley “was taken by an organized gang after departing from an internet café in Binesh, Syria,” near the Turkish border, the Federal Bureau of Investigation said in an alert following the Nov. 22, 2012, kidnapping. He was in Binesh covering the Syrian civil war for the GlobalPost website and AFP. + +Foley, 40, grew up in New Hampshire, where his parents live.","1" +"Islamic State, in video titled ""A Message to America,"" beheads American journalist James Wright Foley who was kidnapped in 2012","Islamic State, in video titled ""A Message to America,"" beheads American journalist James Wright Foley who was kidnapped in 2012","1" +"BREAKING: Islamic State, in video, beheads American journalist James Wright Foley who was kidnapped in 2012 -@BNONews","BREAKING: Islamic State, in video, beheads American journalist James Wright Foley who was kidnapped in 2012 -@BNONews","1" +"#ISIS beheads photojournalist James Wright Foley in a massage to US to end its intervention in #Iraq.","#ISIS beheads photojournalist James Wright Foley in a massage to US to end its intervention in #Iraq.","1" +"A message from Jim's mom, Diane Foley:","A message from Jim's mom, Diane Foley: +We have never been prouder of our son Jim. He gave his life trying to expose the world to the suffering of the Syrian people. +We implore the kidnappers to spare the lives of the remaining hostages. Like Jim, they are innocents. They have no control over American government policy in Iraq, Syria or anywhere in the world. +We thank Jim for all the joy he gave us. He was an extraordinary son, brother, journalist and person. Please respect our privacy in the days ahead as we mourn and cherish Jim.","1" +"‘Evil straight from the pits of hell': American journalist James Foley reportedly beheaded by ISIS","Absolutely awful news. Media are reporting that journalist James Foley, captured in 2012, has been beheaded by ISIS.","1" +"ISLAMIC STATE BEHEADS MISSING AMERICAN JOURNALIST JAMES WRIGHT FOLEY","The Islamic State released a video of its jihadists beheading American journalist James Wright Foley in Syria. The video is almost five minutes long and includes threats against President Barack Obama and the United States. +In the video, which was temporarily available on YouTube but has since been removed, the terrorists remind the audience Obama authorized military action against IS and replayed Obama’s press conference when he announced the airstrikes. To them the declaration is a “slippery slope towards a new war front against Muslims.” +Foley then appears on his knees in an orange jumpsuit. He relays a message that the US government is his true killer. He addresses his family as well. The message is choppy, which gives the appearance that he is reading off cards placed in front of the camera. +His executioner speaks with what appears to be a British accent, saying many Muslims worldwide accepted IS and a war against IS is, in essence, a war against Muslims. The UK has been one of the Islamic State's most active targets of recruitment. +After he beheads Foley, he presents to the camera another journalist, Steven Joel Soltoff, who worked for Time and The National Interest. Soltoff was reported missing in the middle of last year. The executioner said America’s next move will determine IS’s next move in what appears to be a threat against the second journalist. +Foley was an independent journalist in the Middle East. In 2011, he was one of four journalists kidnapped by Qaddafi’s forces in Libya, of which he said in an interview with the Boston Globe, “You don’t want to be defined as that guy who got captured in 2011... believe that front-line journalism is important.” He spoke at Northwestern University about his experience in Libya. His family had set up a website to help find Foley since his disappearance in Syria on Thanksgiving 2012.","1" +"ISIS Appears To Behead American Photojournalist In YouTube Video","“A Message To America,” a video uploaded Tuesday to YouTube, begins with a clip of President Obama announcing his recent authorization of targeted airstrikes and a humanitarian operation in Iraq. Then, around the two minute mark, a man believed to be James Wright Foley, 40, delivers a statement: + +“I call on my friends, family and loved ones to rise up against my real killers: the U.S. government,” he says, before specifically addressing his brother John, a member of the U.S. Air Force. (A full transcript of his last words was posted online by the blogger Brown Moses and can be found here.) + +About two minutes and 20 seconds later, the man is apparently beheaded. His executioner, whose face is covered, has what sounds like a British accent and threatens that “any attempt by you, Obama, to deny the Muslims their rights of living in safety under the Islamic caliphate will result in the bloodshed of your people.” + +Two people who know Foley said the man in the video appears to be him, and that the voice sounds like his. A Facebook page that is part of the Foley family’s appeal to find and bring Foley home posted the following statement: “We know that many of you are looking for confirmation or answers. Please be patient until we all have more information, and keep the Foleys in your thoughts and prayers.” + +Foley, a freelance photojournalist for the AFP and GlobalPost, and his translator were kidnapped in Binesh, Syria, in November 2012. According to the FBI, his translator was later released. + +The propaganda video ends with a shot of another kneeling man in orange believed to be missing journalist Steven Sotloff. “The life of this American citizen, Obama, depends on your next decision,” the executioner says. + +A version of the clip viewed by BuzzFeed was removed from YouTube after about 20 minutes, though others have been uploaded since. + +“YouTube has clear policies that prohibit content like gratuitous violence, hate speech and incitement to commit violent acts, and we remove videos violating these policies when flagged by our users,” a spokesperson for YouTube said. “We also terminate any account registered by a member of a designated Foreign Terrorist Organization and used in an official capacity to further its interests.” + +“We have seen a video that purports to be the murder of U.S. citizen James Foley by ISIL,” said NSC spokesperson Caitlin Hayden. “The intelligence community is working as quickly as possible to determine its authenticity. If genuine, we are appalled by the brutal murder of an innocent American journalist and we express our deepest condolences to his family and friends. We will provide more information when it is available.” + +FBI + +FBI + +James Wright Foley","1" +"James Foley remembered as 'brave and tireless' journalist","New York (CNN) -- When war reporter James Foley wasn't writing for GlobalPost or recording video for AFP or appearing on the PBS ""NewsHour,"" he occasionally shared stories on his own blog, aptly titled ""A World of Troubles."" + +For a subtitle, he chose the famous Carl von Clausewitz sentence ""War is fought by human beings."" + +And that is exactly what Foley sought to show with his reporting: humanity amid the horror of war. + +Foley was abducted while on a reporting trip in northern Syria in November 2012. He was never heard from again. + +A video published Tuesday by the extremist group ISIS showed Foley being beheaded. It is not known when or where the video was recorded. + +For Foley's family and friends, the recording was the answer they hoped they'd never hear to their questions about his disappearance. + +""We have never been prouder of our son Jim. He gave his life trying to expose the world to the suffering of the Syrian people,"" his mother, Diane, said Tuesday night, + +She called him ""an extraordinary son, brother, journalist and person."" + +Courageous, generous + +Foley was the oldest child of Diane and John Foley of Rochester, New Hampshire. He had four siblings. + +Foley -- Jim to his friends -- had been reporting from war-torn countries for the better part of four years when he disappeared in Syria. + +On Tuesday, fellow journalists remembered him for his courage and his generosity. + +One of his friends, Alex Sherman of Bloomberg News, wrote on Twitter that he was a ""funny, warm, Big Lebowski-loving guy."" + +Another friend, Max Fisher of Vox, praised his ""dedication to truth and understanding."" + +Fisher also wrote that ""Jim's faith was something we all agreed not to discuss publicly while he was held in Syria, but it was the wellspring of his generosity,"" + +He recalled how Foley helped to organize a memorial fund for a photographer, Anton Hammerl, who was killed in Libya in 2011. + +Foley had been traveling with Hammerl and two other journalists at the time, and the three who survived wound up in a Libyan jail. + +Beheading of American journalist James Foley recalls past horrors + +Front-line journalist + +Foley was freed six weeks later. Afterward, in a video interview with the Boston Globe, he hesitated to make the story about himself, remarking at one point that ""you don't want to be defined as 'that guy who got captured in 2011.'"" + +""I believe that front-line journalism is important, you know -- without these photos and videos and first-hand experience, we can't really tell the world how bad it might be,"" he said. + +One of the journalists detained with Foley in Libya, Clare Morgana Gillis, said his fundraising for Hammerl's family was ""the same impulse that compelled him to cut short his much-needed break from reporting in Syria when a colleague went missing last summer, and to raise money for an ambulance for Aleppo's Dar al-Shifa field hospital, where he spent weeks filming the plight of doctors who struggled to save lives with minimal space equipment."" + +His time as a teacher + +For Foley, these were acts of service, not entirely unlike his time spent in the Teach for America program. He began teaching in Phoenix in 1996. + +""He'd promise students that he'd take them to the Castles and Coasters amusement park if they would come to class everyday,"" a fellow Teach for America alum, Sarah Fang, recalled in an essay in 2013. + +Foley later ""taught reading and writing to inmates at the Cook County Sheriff's Boot Camp in Chicago,"" according to a Columbia Journalism Review feature about him. + +Would you watch the video? + +His journalism career + +In the mid-2000s he decided to pursue a journalism career, first by enrolling at Northwestern University's well-respected Medill School of Journalism and then by embedding with American troops in Iraq and Afghanistan. While preparing for his first embed, he started his blog. + +Foley freelanced for a number of news media outlets, including GlobalPost, a world news Web site founded in 2009. + +In 2012, he gravitated toward the spiraling conflict in Syria. + +Fang, who kept in touch with Foley after their years teaching in Phoenix, wrote that his interest in the story there did not surprise her. + +""He's always been willing to step into a zone where no one else wants to go,"" she wrote. ""Jim feels that society needs reporters willing to bear witness and report back the facts of history-in-the-making. And his loyalty to his colleagues meant that he wanted to be there with them on the frontlines."" + +BuzzFeed Middle East correspondent Sheera Frenkel said she last saw Foley about a week before his final trip into Syria. + +Drinking beers at the lobby of a hotel popular among journalists, they talked, she said, about ""how hard it was to move on from this job, into a life which would allow for marriage and family."" + +""He was a generous colleague, never holding back a tip, phone number, or detail that could help, and could spend hours talking over the ins and outs of a story to get it just right,"" Frenkel wrote in an email message. + +""Jim was a great journalist, and I think he'd like to be remembered that way, first and foremost."" + +After the news of Foley's killing spread on Tuesday, CBS News foreign correspondent Clarissa Ward changed her profile picture on Twitter to a photo of Foley wearing a helmet, a flak jacket and holding up a camera. + +This, she said, ""is how I will chose to remember James -- as a brave and tireless journalist with a passion for the Syrian cause."" + +READ: ISIS beheads U.S. journalist, threatens another over Iraq + +READ: Who's Haider al-Abadi, the man who will lead Iraq?","1" +"'American bombing had signed my death certificate': Missing US journalist James Wright Foley goes unflinching to his death as ISIS behead him in horrific video, as a warning to Obama","American photojournalist James Wright Foley has been beheaded by ISIS forces + +Foley has been missing since Thanksgiving 2012 while working in Syria + +ISIS posted the extremely graphic video 'A Message to America' to social media + +Foley speaks to camera before his death and labels the US his killers + +Apparently coerced by his captors into speaking against his country + +A masked and robed member of ISIS speaking English in what is thought to be a British accent addresses the camera too + +After the execution of Foley, the ISIS member says that missing American journalist Steven Joel Sotloff will be killed next + +A man identified as Sotloff in a caption on the video is then paraded in front of the camera + +Beheading comes one day after ISIS threat to America that 'we will drown all you in blood' following the US-aided Kurdish recapture of the Mosul Dam + +Horrific video of American freelance photo-journalist James Wright Foley, 40, being beheaded by ISIS in revenge for US airstrikes in Iraq was posted to the internet Tuesday afternoon. +Foley, has been missing since November, 2012, after being taken hostage at gunpoint while reporting from Taftanaz, in northern Syria, for the agency, GlobalPost. +ISIS posted the extremely graphic video shot at an unknown location, titled 'A Message to America' to social media as proof of their barbaric actions. +In a chilling warning at the end of grisly film, the executioner, who has what sounds like a British accent, paraded another American journalist, Steven Joel Sotloff, who went missing in August 2013, saying: 'The life of this American citizen, Obama, depends on your next decision.' + +The video emerged as President Barack Obama was returning from the White House to his Martha's Vineyard vacation. White House National Security Council spokeswoman Caitlin Hayden says the administration has seen the video. +She says that if it’s deemed genuine by the intelligence community, the US would be ‘appalled by the brutal murder of an innocent American journalist.’ +His family issued a statement through their Free James Foley organization, which has been working to free the journalist. +'We know that many of you are looking for confirmation or answers. Please be patient until we all have more information, and keep the Foleys in your thoughts and prayers.' +As the disturbing video infolds, Foley, dressed in orange and on his knees, is unflinching to the end as he addresses the camera before his death. +It appears the journalist has been coerced into blaming the United States by his brutal captors. His voice strong, but struggling at times to swallow as he battles against fear, he brands the US government his real killers as a man in black robes armed with a gun stands over him. + +Foley who has been missing for almost two years also leaves a haunting message for his brother, John, who is thought to be in the US Air Force. +Referring to US airstrikes launched nearly two weeks ago in Iraq, Foley says: ‘I died that day, John, when your colleagues dropped that bomb on these people. They signed my death certificate’ +As the appalling video unfolds, Foley blames the 'complacency and criminality' of the United States for his impending death. +In his final, awful message to the world, Foley pleads for more time, to have seen his family who fought for his freedom for two years again. In a final insult from his vengeful executioners, Foley is made to deny his birthright as a citizen of the United States. +'I wish I had more time, I wish I could have the hope of freedom and see my family once again, but that ship has sailed. I guess all in all, I wish I wasn’t American,' says Foley before his tragic death. + +The reporter then stops speaking and his executioner steps forward. The masked, armed and black robe-clad man speaks in English in what is thought to be a British accent. +Members of the UK's Associated Press pegged the accent to the South East of England and London, while others have claimed the accent resembles one from North Africa. +‘This is James Wright Foley, an American citizen of your country. As a government you have been at the forefront of the aggression towards the Islamic State,' begins the executioner. +'You have plotted against us and gone far out of your way to find reasons to interfere in our affairs. Today, your military airforce is attacking us daily in Iraq. +'Your strikes have caused casualties amongst Muslims. You are no longer fighting an insurgency. +'We are an Islamic Army and a state that has been accepted by a large number of Muslims worldwide. +'So effectively, any aggression toward the Islamic State is aggression towards Muslims from all walks of life who have accepted the Islamic Caliphate as their leadership. +'So any attempt by you, Obama, to deny the Muslims their rights of living in safety under the Islamic Caliphate will result in the bloodshed of your people.’ + +At this point the executioner beheads Foley, who is kneeling bravely with hands tied behind his back. His body is displayed with the head atop the body. +Then in another chilling warning, the executioner holds another man, on his kness with his hands tied behind his back, by the scruff of the neck. A caption claims it is Steven Joel Soltoff. +The executioner says: ‘The life of this American citizen, Obama, depends on your next decision.’ +GlobalPost's co-founder, Charles Sennott told ABC News that there is 'no reliable proof that this execution is authentic. +'If the video is verified, it is just unfathomable darkness to think that a life as bright as Jim Foley's ended that way,' Sennott said. 'He was an experienced and fearless journalist who believed deeply in reporting from the frontlines.' +The gruesome video clip opens with President Obama announcing the commencement of American air strikes on Iraq against ISIS. +'Today I authorized two operations in Iraq: targeted airstrikes to protect our American personnel, and a humanitarian effort to help save thousands of Iraqi civilians who are trapped on a mountain without food and water, and facing almost certain death,' says Obama in a statement dated, August 7. +ISIS, which has claimed control of most of northern Iraq and parts of Syria is threatening to kill Time journalist Joel Sotloff next unless President Obama ceases attacks on the terror group. +Sotloff has been missing since the middle of 2013 and last tweeted on August 3rd, 2013. +According to his Twitter account he was in Libya at the time of his disappearance. +Foley’s family including parents John and Diane, of Rochester, New Hampshire, have publicly appealed for their son’s release over the past two years. +Foley was previously held captive by pro-Gaddafi forces in Libya. + +The barbaric beheading comes one day after ISIS militants threatened to attack U.S. targets 'in any place' in a chilling video showing a blood-spattered Star and Stripes next to the jihadist flag with the message in English: 'We will drown all of you in blood'. +Unlike Al Qaeda, the Islamic State has so far focused on seizing land in Iraq and Syria for its self-proclaimed caliphate, not spectacular attacks on Western targets. +It came as President Barack Obama on Monday announced that Kurdish peshmerga troops, supported by U.S. jets, had recaptured the strategically important Mosul Dam, hailing the offensive as a 'major step forward'. +The dam had given the militants control over power and water supplies, and any breach of the vulnerable structure would have threatened thousands of lives. +As the U.S. military strikes the Islamic State group in Iraq, Syrian President Bashar Assad's forces also stepped up their own campaign against militant strongholds in Syria. + +Foley, who lived Boston, was previously held captive by pro-Gaddafi forces for six weeks in Libya in 2011. +He was released after 45 days following an international campaign by his friends and family. +The Foley family from Rochester, New Hampshire, had hoped keeping silent could aid his release from Syria, but early last year decided to appeal directly to his kidnappers, increasingly concerned as they grew increasingly concerned. +'We want Jim to come safely home, or at least we need to speak with him to know he's okay,' his father John Foley said in a statement in January 2013 as the Foley family launched a website to publicize his disappearance, 'Jim is an objective journalist and we appeal for the release of Jim unharmed. To the people who have Jim, please contact us so we can work together toward his release.' +James, or Jim as he is known to his family and friends, is one of five children to parents John and Diane Foley. +Foley, who studied at Marquette University, Milwaukee, and later studied journalism at Northwestern University, Chicago, has also reported on the war in Iraq and Afghanistan. +Prior to a career in journalism, he taught reading and writing skills to convicted felons at Cook County Jail in Chicago.","1" +"'Spare the lives of the remaining hostages. Like Jim they are innocents': Brave mother of beheaded American journalist calls on ISIS to cease killing as she pays tribute to her 'extraordinary son'","American photojournalist James Wright Foley has been beheaded by ISIS forces + +Foley has been missing since Thanksgiving 2012 while working in Syria + +ISIS posted the extremely graphic video 'A Message to America' to social media + +Foley speaks to camera before his death and labels the US his killers + +Apparently coerced by his captors into speaking against his country + +A masked and robed member of ISIS speaking English in what is thought to be a British accent addresses the camera as well + +After the execution of Foley, the ISIS member says that missing American journalist Steven Joel Sotloff will be killed next + +A man identified as Sotloff in a caption on the video is then paraded in front of the camera + +Beheading comes one day after ISIS threat to America that 'we will drown all you in blood' for the US-aided Kurdish recapture of the Mosul Dam + +President Obama is expected to comment on the video Wednesday","1" +"Executioner 'with a British accent' beheads US journalist in the name of ISIS: Mother of slaughtered American calls on Islamist group to cease killing and pays tribute to her 'extraordinary son'","Photojournalist James Wright Foley has been beheaded by ISIS forces + +Foley has been missing since Thanksgiving 2012 while working in Syria + +ISIS posted extremely graphic video 'A Message to America' to social media + +Foley speaks to camera before his death and labels the U.S. his killers + +Apparently coerced by his captors into speaking against his country + +Masked and robed executioner speaks English in apparent London accent + +British Foreign Secretary today said 'appalling' video appeared to be genuine + +After the execution of Foley, the ISIS member says that missing American journalist Steven Joel Sotloff will be killed next + +Man identified as Sotloff in caption is then paraded in front of the camera + +News comes day after ISIS threatened Americans over Mosul Dam airstrikes + +Warned 'we will drown all you in blood' as U.S. helped Kurds recapture dam","1" +"ISIS beheads American photo-journalist James Wright Foley, threatens more to come","Iraqi group ISIS beheaded American photo-jornalist James Wright Foley, releasing gruesome pictures and video to the internet on Tuesday. Foley had been missing after being captured in Syria in 2012 while working freelance for AFP. + +A group called Free James Foley had been dedicated to finding and saving Foley since his disappearance. The search met its devastating end on Tuesday when the Iraqi group issued video proof of his murder, and threatened more to come: The Daily Beast reports that Time journalist Steven Sotloff is also shown in the video, and that ISIS threatens he will be next if the U.S. doesn’t cease and desist its operations in Iraq. + +“Any attempt by you, Obama, to deny Muslims liberty & safety under the Islamic caliphate, will result in the bloodshed of your people,” an ISIS member says in the video. + +We’ll update this post as more information becomes available.","1" +"Missing American journalist reportedly beheaded by Islamic State ","AN American journalist who has been missing for almost two years has reportedly been executed by the Islamic State (IS). + +James Wright Foley went missing in on November 22, 2012, while reporting from Syria. + +But a shocking video apparently shows the 40-year-old being beheaded by IS (formerly known as Isis) forces. + +Before the execution a masked man dressed in black stands over Foley as he is forced to read a letter labelling the US government as his killers. + +He says: ""I call on my friends family and loved ones to rise up against my real killers, the US government. For what will happen to me is only a result of their complacency and criminality."" + +The journalist is also then made to address his brother John, who is a member of the US airforce. + +He says: ""I died that day, John, when your colleagues dropped that bomb on these people. They signed my death certificate."" + +The militant group is now also threatening to kill Time journalist Joel Sotloff, unless Barack Obama calls a halt to US attacks. + +Mr Sotloff disappeared in 2013 and last tweeted on August 3 that year, when he was understood to be in Libya. + +The executioner claims Sotloff's fate ""depends"" on President Obama's ""next decision"". + +IS has seized several key Iraqi cities, including the country's second largest city, Mosul.","1" +"Family 'have never been prouder' of journalist beheaded by British-accented IS militant","THE family of an American journalist who was shown in a video being beheaded by an Islamic State (IS) extremist have confirmed his death. + +James Wright Foley, 40, had been went missing on November 22, 2012, while reporting from Syria. + +After a grisly video was released by IS militants last night, his family said they ""have never been prouder of him"". + +In a message posted to a Facebook page created to rally support for his release, his mum Diane said: ""We have never been prouder of our son Jim. + +""He gave his life trying to expose the world to the suffering of the Syrian people."" + +IS, who have captured large swathes of Syria and northern Iraq in recent weeks, described the killing of Mr Foley as retribution for recent US airstrikes in Iraq. + +They are now also threatening to kill Time journalist Joel Sotloff, unless President Barack Obama calls a halt to military action designed to prevent an IS slaughter of religious minorities in the country. + +In the statement, Mrs Foley added: ""We implore the kidnappers to spare the lives of the remaining hostages. + +""Like Jim, they are innocents. They have no control over American government policy in Iraq, Syria or anywhere in the world. + +""We thank Jim for all the joy he gave us. He was an extraordinary son, brother, journalist and person. + +""Please respect our privacy in the days ahead as we mourn and cherish Jim."" + +(function(d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = ""//connect.facebook.net/en_GB/all.js#xfbml=1""; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); + +Post by Free James Foley. + +Foreign Secretary Philip Hammond described the death of Mr Foley, from Rochester in New Hampshire, as an ""appalling example of the brutality of this organisation"". + +In the video Mr Foley, who was a freelancer for Agence France-Presse and the Boston-based media company GlobalPost, is seen kneeling in a desert-like environment at an unknown location as an IS fighter stands by his side dressed in black and with his face covered. + +Mr Hammond said the video had not been verified but ""all the hallmarks point to it being genuine"" and acknowledged that the killer spoke with a British accent. + +The Foreign Secretary told the BBC: ""We have been saying for a long time that there are a significant number of British nationals in Syria and Iraq operating with extremist organisations. + +""That's one of the reasons why this organisation represents such a direct threat to the UK's national security. + +""Many of these people may seek at some point to return to the UK and they would then pose a direct threat to our domestic security."" + +Mr Hammond described the ideology of militant groups as ""a poison"" and ""a cancer"". + +He added: ""We are absolutely aware that there are significant numbers of British nationals involved in terrible crimes, probably in the commission of atrocities, making jihad with IS and other extremist organisations. + +""This is something we have been tracking and dealing with for many, many months, I don't think this video changes anything it just heightens awareness of a situation which is very grave and which we have been working on for many months.""","1" +"PM returns as US journalist and 'extraordinary son' is beheaded by 'British' IS militant","THE family of an American journalist who was shown in a video being beheaded by an Islamic State (IS) extremist have confirmed his death. + +James Wright Foley, 40, disappeared on November 22, 2012, while reporting from Syria. + +After a grisly video apparently showing his execution was released by IS militants last night, his family said they ""have never been prouder of him"". + +David Cameron today is returning to Downing Street today to hold meetings with Home and Foreign Office staff over the murder. + +The Prime Minister, who was on holiday in Cornwall with his family, will meet Foreign Secretary Philip Hammond and senior security forces officials following the release of the video. + +A No 10 spokeswoman said: ""If true, the brutal murder of James Foley is shocking and depraved. + +""The Prime Minister is returning to Downing Street this morning. He will meet with the Foreign Secretary and senior officials from the Home Office, Foreign Office and the agencies to discuss the situation in Iraq and Syria and the threat posed by ISIL (Islamic State) terrorists."" + +In a message posted to a Facebook page created to rally support for Foley's release, his mum Diane said: ""We have never been prouder of our son Jim. + +""He gave his life trying to expose the world to the suffering of the Syrian people."" + +IS, who have captured large swathes of Syria and northern Iraq in recent weeks, described the killing of Mr Foley as retribution for recent US airstrikes in Iraq. + +They are now also threatening to kill Time journalist Joel Sotloff, unless President Barack Obama calls a halt to military action designed to prevent an IS slaughter of religious minorities in the country. + +In the statement, Mrs Foley added: ""We implore the kidnappers to spare the lives of the remaining hostages. + +""Like Jim, they are innocents. They have no control over American government policy in Iraq, Syria or anywhere in the world. + +""We thank Jim for all the joy he gave us. He was an extraordinary son, brother, journalist and person. + +""Please respect our privacy in the days ahead as we mourn and cherish Jim."" + +brightcove.createExperiences(); + +Mr Foley was on assignment for Agence France-Press and the Boston-based GlobalPost in northern Syria when his car was stopped by militants in 2012. + +Around 20 journalists are currently missing in Syria, according to the New York-based Committee to Protect Journalists. + +Mr Foley told the BBC in a 2012 interview that he was ""drawn to the drama of the conflict and trying to expose untold stories"". + +He said: ""There's extreme violence, but there's a will to find who these people really are. And I think that's what's really inspiring about it."" + +Filmmaker Matthew VanDyke, a friend of Mr Foley's, said that the journalist knew his job carried risks but ""believed in what he was doing."" + +He said seeing news reports of his friend's death was ""a complete nightmare"" and urged other reporters in Syria and Iraq to take precautions, saying ""if it can happen to him, it can happen to anybody"". + +Mr VanDyke said: ""He was certainly aware of the dangers, he was very professional. + +""He had a love for what he did and he wanted to tell the story of the Syrian people. And nothing was going to stop him from doing that."" + +Mr VanDyke added that IS did not even exist when Foley was captured in Syria in 2012. + +Philip Balboni, chief executive of GlobalPost, paid tribute to their employee, and thanked the public on behalf of Mr Foley's parents. + +""On behalf of John and Diane Foley, and also GlobalPost, we deeply appreciate all of the messages of sympathy and support that have poured in since the news of Jim's possible execution first broke. + +""We have been informed that the FBI is in the process of evaluating the video posted by the Islamic State to determine if it is authentic. ... We ask for your prayers for Jim and his family."" + +The beheading, if confirmed, will be the first time Islamic State fighters have killed an American since the conflict broke out in Syria in 2011. + +(function(d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = ""//connect.facebook.net/en_GB/all.js#xfbml=1""; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); + +Post by Free James Foley. + +brightcove.createExperiences(); + +Foreign Secretary Philip Hammond described the death of Mr Foley, from Rochester in New Hampshire, as an ""appalling example of the brutality of this organisation"". + +In the video, Mr Foley is seen kneeling in a desert-like environment at an unknown location as an IS fighter stands by his side dressed in black and with his face covered. + +Mr Hammond said the video had not been verified but ""all the hallmarks point to it being genuine"" and acknowledged that the killer spoke with a British accent. + +The Foreign Secretary told the BBC: ""We have been saying for a long time that there are a significant number of British nationals in Syria and Iraq operating with extremist organisations. + +""That's one of the reasons why this organisation represents such a direct threat to the UK's national security. + +""Many of these people may seek at some point to return to the UK and they would then pose a direct threat to our domestic security."" + +Mr Hammond described the ideology of militant groups as ""a poison"" and ""a cancer"". + +He added: ""We are absolutely aware that there are significant numbers of British nationals involved in terrible crimes, probably in the commission of atrocities, making jihad with IS and other extremist organisations. + +""This is something we have been tracking and dealing with for many, many months, I don't think this video changes anything it just heightens awareness of a situation which is very grave and which we have been working on for many months."" + +He also warned that military success against IS in Iraq and Syria could be the trigger for fighters returning to their countries of origin. + +He told BBC Radio 4's Today programme: ""I'm afraid I think it's heads we win, tails we lose in this. If the Islamic State, so-called, becomes established in an area of Syria and Iraq, it will undoubtedly use it as a base for launching attacks on the West. It will undoubtedly send its fighters out to attack Western targets. + +""Equally, if it gets pushed back, some of these people will return to their countries of origin. It's not just the UK, it's all European countries, Australia, the United States, other Arab countries. + +""We will see these people going back and potentially carrying on their fight in our own homelands."" + +A campaign on Twitter, backed by celebrities including Mia Farrow, has been launched to stop people sharing the video of the murder. + +Twitter's chief executive Dick Costolo said the firm was taking action against accounts which spread the video.","1" +"Tougher laws if needed to deal with extremism after 'barbaric' killing, says David Cameron","PRIME Minister David Cameron today condemned the killing of a journalist by what appears to be a British man fighting with Islamic State (IS) militants. + +In a chilling video, US journalist James Wright Foley is shown kneeling next to a IS extremist who appears to speak with a British accent, before he is killed. + +Addressing reporters in Downing Street, Mr Cameron vowed the Government will redouble its efforts to prevent young Britons from travelling to join the group. + +Mr Cameron said it seemed ""increasingly likely"" that a British citizen was the killer, adding: ""Let me condemn the barbaric and brutal act that has taken place and let's be clear what this act is - it is an act of murder, and murder without any justification. + +""We have not identified the individual responsible, but from what we have seen it looks increasingly likely that it is a British citizen. + +""This is deeply shocking. But we know that far too many British citizens have travelled to Iraq and travelled to Syria to take part in extremism and violence. + +""And what we must do is redouble all our efforts to stop people from going. To take away the passports of those contemplating travel, arrest and prosecute those who take part in this extremism and violence. + +""To take extremist material off the internet and do everything we can to keep our people safe. And that is what this Government will do."" + +As well as repeating his stance that Britain will not get involved in another military conflict in Iraq, Mr Cameron also suggested new laws could be introduced to prevent Britons leaving the country to join IS in Syria and Iraq. + +He said: ""I have been very clear that this country is not going to get involved in another Iraq war. We are not putting combat troops, combat boots on the ground, that is not something we should do. + +""We have a clear strategy, we should stick to that strategy, and specifically here at home we have very clear laws, tough laws, and of course we will always look at new proposals for even tougher laws to deal with terrorism and extremism. + +""This is not a time for a knee-jerk reaction. It is time for what Britain always shows in these circumstances, and that is a resolve. We have defeated terrorism, extremism, threats to our country before, and we will defeat them again if we show that resolve, but also patience. + +""This struggle against Islamist extremism - not a struggle of one religion against another - it is of all people and all religions including Islam against a poisonous extremism, we must show patience and resolve in fighting this, here at home in the UK and in other parts of the world where countries have been affected."" + +US President Barack Obama also today vowed that America will continue to confront extremists. + +brightcove.createExperiences(); + +Mr Obama, who met earlier with Mr Foley's family, said that the US will continue to do ""what we must do to protect our people"". + +In a damning speech, Mr Obama said that ""no just God would stand for"" the actions of IS, adding: ""Their ideology is bankrupt"". + +He continued: ""One thing we can all agree on is that Isil has no place in the 21st century. + +""We will continue to confront this hateful terrorism and replace it with a sense of hope and stability. + +""That's what Jim Foley stood for. A man who lived his work, who courageously told the stories of his fellow human beings and who was liked and loved by friends and family."" + +A video showing the murder of Mr Foley was today confirmed by the US officials as authentic. + +The 40-year-old disappeared on November 22, 2012, while reporting from Syria. + +After a grisly video apparently showing his execution was released by IS militants last night, his family said they ""have never been prouder of him"". + +David Cameron has returned to Downing Street today to hold meetings with Home and Foreign Office staff over the murder, which he described as ""shocking and depraved"". + +The Prime Minister, who was on holiday in Cornwall with his family, is meeting Foreign Secretary Philip Hammond and senior security forces officials following the release of the video. + +A No 10 spokeswoman said: ""The Prime Minister is returning to Downing Street this morning. He will meet with the Foreign Secretary and senior officials from the Home Office, Foreign Office and the agencies to discuss the situation in Iraq and Syria and the threat posed by (Islamic State) terrorists."" + +(function(d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = ""//connect.facebook.net/en_GB/all.js#xfbml=1""; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); + +Post by Free James Foley. + +brightcove.createExperiences(); + +In a message posted to a Facebook page created to rally support for Foley's release, his mum Diane said: ""We have never been prouder of our son Jim. + +""He gave his life trying to expose the world to the suffering of the Syrian people."" + +British counter-terrorism police have launched an investigation into the video, and have also warned social media users that sharing it online in the UK may constitute an offence. + +Hammond said British intelligence services would work closely with the United States to try to identify the man and a specialist counter-terrorism police unit launched an investigation into the contents of the video. + +A US National Security spokeswoman said that they believed the video, which also showed another American journalist, Steven Sotloff, was authentic. + +Caitlin Hayden said: ""The US Intelligence Community has analysed the recently released video showing U.S. citizens James Foley and Steven Sotloff. + +""We have reached the judgment that this video is authentic. We will continue to provide updates as they are available."" + +IS, who have captured large swathes of Syria and northern Iraq in recent weeks, described the killing of Mr Foley as retribution for recent US airstrikes in Iraq. + +They are now also threatening to kill Time journalist Joel Sotloff, unless President Barack Obama calls a halt to military action designed to prevent an IS slaughter of religious minorities in the country. + +In the statement, Mrs Foley added: ""We implore the kidnappers to spare the lives of the remaining hostages. + +""Like Jim, they are innocents. They have no control over American government policy in Iraq, Syria or anywhere in the world. + +""We thank Jim for all the joy he gave us. He was an extraordinary son, brother, journalist and person. + +""Please respect our privacy in the days ahead as we mourn and cherish Jim."" + +Mr Foley was on assignment for Agence France-Press and the Boston-based GlobalPost in northern Syria when his car was stopped by militants in 2012. + +Around 20 journalists are currently missing in Syria, according to the New York-based Committee to Protect Journalists. + +Mr Foley told the BBC in a 2012 interview that he was ""drawn to the drama of the conflict and trying to expose untold stories"". + +He said: ""There's extreme violence, but there's a will to find who these people really are. And I think that's what's really inspiring about it."" + +Filmmaker Matthew VanDyke, a friend of Mr Foley's, said that the journalist knew his job carried risks but ""believed in what he was doing."" + +He said seeing news reports of his friend's death was ""a complete nightmare"" and urged other reporters in Syria and Iraq to take precautions, saying ""if it can happen to him, it can happen to anybody"". + +Mr VanDyke said: ""He was certainly aware of the dangers, he was very professional. + +""He had a love for what he did and he wanted to tell the story of the Syrian people. And nothing was going to stop him from doing that."" + +Mr VanDyke added that IS did not even exist when Foley was captured in Syria in 2012. + +Philip Balboni, chief executive of GlobalPost, paid tribute to their employee, and thanked the public on behalf of Mr Foley's parents. + +""On behalf of John and Diane Foley, and also GlobalPost, we deeply appreciate all of the messages of sympathy and support that have poured in since the news of Jim's possible execution first broke. + +""We have been informed that the FBI is in the process of evaluating the video posted by the Islamic State to determine if it is authentic. ... We ask for your prayers for Jim and his family."" + +The beheading, if confirmed, will be the first time Islamic State fighters have killed an American since the conflict broke out in Syria in 2011. + +Foreign Secretary Philip Hammond described the death of Mr Foley, from Rochester in New Hampshire, as an ""appalling example of the brutality of this organisation"". + +In the video, Mr Foley is seen kneeling in a desert-like environment at an unknown location as an IS fighter stands by his side dressed in black and with his face covered. + +Mr Hammond said the video had not been verified but ""all the hallmarks point to it being genuine"" and acknowledged that the killer spoke with a British accent. + +The Foreign Secretary told the BBC: ""We have been saying for a long time that there are a significant number of British nationals in Syria and Iraq operating with extremist organisations. + +""That's one of the reasons why this organisation represents such a direct threat to the UK's national security. + +""Many of these people may seek at some point to return to the UK and they would then pose a direct threat to our domestic security."" + +Mr Hammond described the ideology of militant groups as ""a poison"" and ""a cancer"". + +He added: ""We are absolutely aware that there are significant numbers of British nationals involved in terrible crimes, probably in the commission of atrocities, making jihad with IS and other extremist organisations. + +""This is something we have been tracking and dealing with for many, many months, I don't think this video changes anything it just heightens awareness of a situation which is very grave and which we have been working on for many months."" + +He also warned that military success against IS in Iraq and Syria could be the trigger for fighters returning to their countries of origin. + +He told BBC Radio 4's Today programme: ""I'm afraid I think it's heads we win, tails we lose in this. If the Islamic State, so-called, becomes established in an area of Syria and Iraq, it will undoubtedly use it as a base for launching attacks on the West. It will undoubtedly send its fighters out to attack Western targets. + +""Equally, if it gets pushed back, some of these people will return to their countries of origin. It's not just the UK, it's all European countries, Australia, the United States, other Arab countries. + +""We will see these people going back and potentially carrying on their fight in our own homelands."" + +A campaign on Twitter, backed by celebrities including Mia Farrow, has been launched to stop people sharing the video of the murder. + +Twitter's chief executive Dick Costolo said the firm was taking action against accounts which spread the video.","1" +"PM vows to 'redouble efforts' against Islamic extremism after 'barbaric' IS murder","PRIME Minister David Cameron today condemned the killing of a journalist by what appears to be a British man fighting with Islamic State (IS) militants. + +In a chilling video, US journalist James Wright Foley is shown kneeling next to a IS extremist who appears to speak with a British accent, before he is killed. + +Addressing reporters in Downing Street, Mr Cameron vowed the Government will redouble its efforts to prevent young Britons from travelling to join the group. + +Mr Cameron said it seemed ""increasingly likely"" that a British citizen was the killer, adding: ""Let me condemn the barbaric and brutal act that has taken place and let's be clear what this act is - it is an act of murder, and murder without any justification. + +""We have not identified the individual responsible, but from what we have seen it looks increasingly likely that it is a British citizen. + +""This is deeply shocking. But we know that far too many British citizens have travelled to Iraq and travelled to Syria to take part in extremism and violence. + +""And what we must do is redouble all our efforts to stop people from going. To take away the passports of those contemplating travel, arrest and prosecute those who take part in this extremism and violence. + +""To take extremist material off the internet and do everything we can to keep our people safe. And that is what this Government will do."" + +As well as repeating his stance that Britain will not get involved in another military conflict in Iraq, Mr Cameron also suggested new laws could be introduced to prevent Britons leaving the country to join IS in Syria and Iraq. + +He said: ""I have been very clear that this country is not going to get involved in another Iraq war. We are not putting combat troops, combat boots on the ground, that is not something we should do. + +""We have a clear strategy, we should stick to that strategy, and specifically here at home we have very clear laws, tough laws, and of course we will always look at new proposals for even tougher laws to deal with terrorism and extremism. + +""This is not a time for a knee-jerk reaction. It is time for what Britain always shows in these circumstances, and that is a resolve. We have defeated terrorism, extremism, threats to our country before, and we will defeat them again if we show that resolve, but also patience. + +""This struggle against Islamist extremism - not a struggle of one religion against another - it is of all people and all religions including Islam against a poisonous extremism, we must show patience and resolve in fighting this, here at home in the UK and in other parts of the world where countries have been affected."" + +US President Barack Obama also today vowed that America will continue to confront extremists. + +brightcove.createExperiences(); + +Mr Obama, who met earlier with Mr Foley's family, said that the US will continue to do ""what we must do to protect our people"". + +In a damning speech, Mr Obama said that ""no just God would stand for"" the actions of IS, adding: ""Their ideology is bankrupt"". + +He continued: ""One thing we can all agree on is that Isil has no place in the 21st century. + +""We will continue to confront this hateful terrorism and replace it with a sense of hope and stability. + +""That's what Jim Foley stood for. A man who lived his work, who courageously told the stories of his fellow human beings and who was liked and loved by friends and family."" + +A video showing the murder of Mr Foley was today confirmed by the US officials as authentic. + +The 40-year-old disappeared on November 22, 2012, while reporting from Syria. + +After a grisly video apparently showing his execution was released by IS militants last night, his family said they ""have never been prouder of him"". + +David Cameron has returned to Downing Street today to hold meetings with Home and Foreign Office staff over the murder, which he described as ""shocking and depraved"". + +The Prime Minister, who was on holiday in Cornwall with his family, is meeting Foreign Secretary Philip Hammond and senior security forces officials following the release of the video. + +A No 10 spokeswoman said: ""The Prime Minister is returning to Downing Street this morning. He will meet with the Foreign Secretary and senior officials from the Home Office, Foreign Office and the agencies to discuss the situation in Iraq and Syria and the threat posed by (Islamic State) terrorists."" + +(function(d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = ""//connect.facebook.net/en_GB/all.js#xfbml=1""; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); + +Post by Free James Foley. + +brightcove.createExperiences(); + +In a message posted to a Facebook page created to rally support for Foley's release, his mum Diane said: ""We have never been prouder of our son Jim. + +""He gave his life trying to expose the world to the suffering of the Syrian people."" + +British counter-terrorism police have launched an investigation into the video, and have also warned social media users that sharing it online in the UK may constitute an offence. + +Hammond said British intelligence services would work closely with the United States to try to identify the man and a specialist counter-terrorism police unit launched an investigation into the contents of the video. + +A US National Security spokeswoman said that they believed the video, which also showed another American journalist, Steven Sotloff, was authentic. + +Caitlin Hayden said: ""The US Intelligence Community has analysed the recently released video showing U.S. citizens James Foley and Steven Sotloff. + +""We have reached the judgment that this video is authentic. We will continue to provide updates as they are available."" + +IS, who have captured large swathes of Syria and northern Iraq in recent weeks, described the killing of Mr Foley as retribution for recent US airstrikes in Iraq. + +They are now also threatening to kill Time journalist Joel Sotloff, unless President Barack Obama calls a halt to military action designed to prevent an IS slaughter of religious minorities in the country. + +In the statement, Mrs Foley added: ""We implore the kidnappers to spare the lives of the remaining hostages. + +""Like Jim, they are innocents. They have no control over American government policy in Iraq, Syria or anywhere in the world. + +""We thank Jim for all the joy he gave us. He was an extraordinary son, brother, journalist and person. + +""Please respect our privacy in the days ahead as we mourn and cherish Jim."" + +Mr Foley was on assignment for Agence France-Press and the Boston-based GlobalPost in northern Syria when his car was stopped by militants in 2012. + +Around 20 journalists are currently missing in Syria, according to the New York-based Committee to Protect Journalists. + +Mr Foley told the BBC in a 2012 interview that he was ""drawn to the drama of the conflict and trying to expose untold stories"". + +He said: ""There's extreme violence, but there's a will to find who these people really are. And I think that's what's really inspiring about it."" + +Filmmaker Matthew VanDyke, a friend of Mr Foley's, said that the journalist knew his job carried risks but ""believed in what he was doing."" + +He said seeing news reports of his friend's death was ""a complete nightmare"" and urged other reporters in Syria and Iraq to take precautions, saying ""if it can happen to him, it can happen to anybody"". + +Mr VanDyke said: ""He was certainly aware of the dangers, he was very professional. + +""He had a love for what he did and he wanted to tell the story of the Syrian people. And nothing was going to stop him from doing that."" + +Mr VanDyke added that IS did not even exist when Foley was captured in Syria in 2012. + +Philip Balboni, chief executive of GlobalPost, paid tribute to their employee, and thanked the public on behalf of Mr Foley's parents. + +""On behalf of John and Diane Foley, and also GlobalPost, we deeply appreciate all of the messages of sympathy and support that have poured in since the news of Jim's possible execution first broke. + +""We have been informed that the FBI is in the process of evaluating the video posted by the Islamic State to determine if it is authentic. ... We ask for your prayers for Jim and his family."" + +The beheading, if confirmed, will be the first time Islamic State fighters have killed an American since the conflict broke out in Syria in 2011. + +Foreign Secretary Philip Hammond described the death of Mr Foley, from Rochester in New Hampshire, as an ""appalling example of the brutality of this organisation"". + +In the video, Mr Foley is seen kneeling in a desert-like environment at an unknown location as an IS fighter stands by his side dressed in black and with his face covered. + +Mr Hammond said the video had not been verified but ""all the hallmarks point to it being genuine"" and acknowledged that the killer spoke with a British accent. + +The Foreign Secretary told the BBC: ""We have been saying for a long time that there are a significant number of British nationals in Syria and Iraq operating with extremist organisations. + +""That's one of the reasons why this organisation represents such a direct threat to the UK's national security. + +""Many of these people may seek at some point to return to the UK and they would then pose a direct threat to our domestic security."" + +Mr Hammond described the ideology of militant groups as ""a poison"" and ""a cancer"". + +He added: ""We are absolutely aware that there are significant numbers of British nationals involved in terrible crimes, probably in the commission of atrocities, making jihad with IS and other extremist organisations. + +""This is something we have been tracking and dealing with for many, many months, I don't think this video changes anything it just heightens awareness of a situation which is very grave and which we have been working on for many months."" + +He also warned that military success against IS in Iraq and Syria could be the trigger for fighters returning to their countries of origin. + +He told BBC Radio 4's Today programme: ""I'm afraid I think it's heads we win, tails we lose in this. If the Islamic State, so-called, becomes established in an area of Syria and Iraq, it will undoubtedly use it as a base for launching attacks on the West. It will undoubtedly send its fighters out to attack Western targets. + +""Equally, if it gets pushed back, some of these people will return to their countries of origin. It's not just the UK, it's all European countries, Australia, the United States, other Arab countries. + +""We will see these people going back and potentially carrying on their fight in our own homelands."" + +A campaign on Twitter, backed by celebrities including Mia Farrow, has been launched to stop people sharing the video of the murder. + +Twitter's chief executive Dick Costolo said the firm was taking action against accounts which spread the video.","1" +"Isis claims to behead US journalist","Islamist militants claim to have beheaded a man identified as James Foley, an American journalist kidnapped in Syria in late 2012, in a graphic video posted on the internet. +A spokeswoman for the White House said the intelligence community was trying to determine the video’s authenticity. “If genuine, we are appalled by the brutal murder of an innocent American + +The video entitled “Message to #America (from the #IslamicState)” purporting to show “James Wright Foley” on his knees ahead of his execution by a man whose identity is disguised and who speaks with a distinct British accent. + + +At the end of the video, the same person holds up a second person, who is identified with a caption on the screen as Steven Sotloff, a journalist kidnapped in 2013, and says: “The life of this American citizen, Obama, depends on your next decision.” +Last week, social media accounts controlled by the Islamic State in Iraq and the Levant, or Isis, uploaded videos showing dozens of beheadings of individuals they accused of being sympathisers of the regime of Bashar al-Assad, President of Syria, in the northern Syrian town of Deir Ezzor. +The posting of the latest video by Isis comes days after President Barack Obama ordered an intensifying series of air strikes on the militants in northern Iraq. +The immediate aim of the strikes was to back Kurdish and Iraqi forces in their efforts to retake Mosul Dam, a strategic asset which the militants had gained control of in their recent military surge. +Mr Obama has said that Washington will not send troops to Iraq to engage Isis in combat but administration officials have expanded the US military mission there over the last week to halt and push back the militant’s advance. +“We believe that Isis needs to be taken out,” Marie Harf, a State Department spokeswoman, said this week. +An estimated 500 Britons have travelled to fight with extremist groups in Syria – most from London – and almost all have joined Isis, according to UK security officials. +British intelligence believes that several have travelled into Iraq and that some have almost certainly been involved in the worst of Isis’ atrocities. +The apparent murder of Mr Foley is a violent reminder of some of the most graphic crimes committed by Isis’s predecessor organisation, al-Qaeda in Iraq, which gruesomely beheaded dozens of Iraqis and foreigners, uploading videos of the acts to the internet, under the command of the militant group’s then leader, Abu Musab al-Zarqawi, nearly a decade ago. +The beheading of American citizen Nicholas Berg in 2004 by Mr Zarqawi himself propelled AQI to the forefront of the war on terror and marked the beginning of a new particularly bloody phase in the Iraqi extremist insurgency in the wake of the US-led invasion. +AQI’s other high profile victims included Americans Jack Hensley and Eugene Armstrong, Briton Kenneth Bigley and South Korean Kim Sun Il. +Mr Zarqawi was killed in northern Iraq in 2006 in a US air strike, and AQI was subsequently driven underground by a surge in American troops in Iraq and a groundswell of Sunni support – financed by the West – in fighting the jihadi group. +The core of AQI’s ideological and operational beliefs and practices has survived in Isis however. The group has inherited many of the hallmarks of AQI, and has been posting videos of beheadings of Assad-regime soldiers and Iraqi Shia and Kurds online for months. +Early assessments by many in the Western intelligence community concluded that Isis was primarily a group focused on a violent regional and sectarian struggle. +With Isis’ declaration of a “caliphate” in June, however, and with it a direct challenge to what remains of al-Qaeda, many European and American security officials have grown more worried about its international ambitions. +Since air strikes against the group by the US began, intelligence officials have grown more worried over Isis’ attack planning against the West. +Of the estimated 3,000 Europeans who travelled to Syria to fight against Mr Assad’s regime, the majority have become Isis members and represent a potential terrorist risk to Western states.","1" +"James Foley, Missing American Photojournalist, Reportedly Executed By ISIS In Syria","James Foley, an American journalist who went missing in Syria more than a year ago, has reportedly been executed by the Islamic State, a militant group formerly known as ISIS. + +Video and photos purportedly of Foley emerged on Tuesday. A YouTube video -- entitled ""A Message to #America (from the #IslamicState)"" -- identified a man on his knees as ""James Wright Foley,"" and showed his execution. + +This is a developing story. Check back here for updates.","1" +"James Foley, Missing American Photojournalist, Reportedly Beheaded By ISIS In Syria","James Foley, an American journalist who went missing in Syria more than a year ago, has reportedly been killed by the Islamic State, a militant group formerly known as ISIS. + +A YouTube video and photos purportedly of Foley emerged on Tuesday. The video -- entitled ""A Message to #America (from the #IslamicState)"" -- identified a man on his knees as ""James Wright Foley,"" and showed his beheading. + +""This is James Wright Foley, an American citizen of your country,"" an Islamic State militant says in the video, which has since been removed by YouTube. ""As a government, you have been at the forefront of the aggression towards the Islamic State. You have plotted against us and have gone far out of your way to find reasons to interfere in our affairs. Today, your military air force is attacking us daily in Iraq, your strikes have caused casualties among Muslims."" + +The video also shows another man on his knees who is identified as American journalist Steven Sotloff. The Islamic State member says that Sotloff's future ""depends"" on President Obama's ""next decision."" Sotloff, a freelance journalist, went missing in Syria in August 2013. + +A post on the ""Free James Foley"" Facebook page addressed the reports on Tuesday, saying, ""We know that many of you are looking for confirmation or answers. Please be patient until we all have more information, and keep the Foleys in your thoughts and prayers."" + +Foley was in Syria covering the country's civil war when he went missing in November 2012. A May 2013 report from the Columbia Journalism Review said that he was likely being held near Damascus. + +The National Security Council issued a statement about Foley's apparent murder: + +""We have seen a video that purports to be the murder of U.S. citizen James Foley by ISIL. The intelligence community is working as quickly as possible to determine its authenticity. If genuine, we are appalled by the brutal murder of an innocent American journalist and we express our deepest condolences to his family and friends. We will provide more information when it is available.” + +CORRECTION: This article has been amended to say that Foley was reportedly beheaded, not reportedly executed.","1" +"James Foley, Missing American Photojournalist, Beheaded By ISIS In Syria","James Foley, an American journalist who went missing in Syria more than a year ago, has reportedly been killed by the Islamic State, a militant group formerly known as ISIS. + +A YouTube video and photos purportedly of Foley emerged on Tuesday. The video -- entitled ""A Message to #America (from the #IslamicState)"" -- identified a man on his knees as ""James Wright Foley,"" and showed his beheading. + +Foley was in Syria covering the country's civil war when he went missing in November 2012. A May 2013 report from the Columbia Journalism Review said that he was likely being held near Damascus. + +Foley's mother Diane confirmed his death on the 'Free James Foley' Facebook page: + +""We have never been prouder of our son Jim. He gave his life trying to expose the world to the suffering of the Syrian people. We implore the kidnappers to spare the lives of the remaining hostages. Like Jim, they are innocents. They have no control over American government policy in Iraq, Syria or anywhere in the world. We thank Jim for all the joy he gave us. He was an extraordinary son, brother, journalist and person. Please respect our privacy in the days ahead as we mourn and cherish Jim."" +American officials told the Associated Press that they believe Foley is the person shown in the video. They said President Obama was expected to make a statement about his death on Wednesday. + +The Committee To Protect Journalists condemned the killing, calling it ""barbaric."" The press freedom group estimated that there are still around 20 journalists missing in Syria. + +Foley is at least the 70th journalist killed since the Syrian civil war broke out, the CPJ said. + +The video of the beheading was quickly removed by YouTube, but its horrific contents nevertheless spread widely around the Internet. + +""This is James Wright Foley, an American citizen of your country,"" an Islamic State militant says in the video. ""As a government, you have been at the forefront of the aggression towards the Islamic State. You have plotted against us and have gone far out of your way to find reasons to interfere in our affairs. Today, your military air force is attacking us daily in Iraq, your strikes have caused casualties among Muslims."" + +The video also shows another man on his knees who is identified as American journalist Steven Sotloff. The Islamic State member says that Sotloff's future ""depends"" on President Obama's ""next decision."" Sotloff, a freelance journalist, went missing in Syria in August 2013. + +The National Security Council issued a statement about Foley's apparent murder: + +""We have seen a video that purports to be the murder of U.S. citizen James Foley by ISIL. The intelligence community is working as quickly as possible to determine its authenticity. If genuine, we are appalled by the brutal murder of an innocent American journalist and we express our deepest condolences to his family and friends. We will provide more information when it is available.”","1" +"Obama Denounces James Foley's Execution: 'Today The Entire World Is Appalled'","President Barack Obama spoke Wednesday on the execution of American journalist James Foley at the hands of Islamic State militants, warning the group that they have ""no place in the 21st century."" + +""Today the entire world is appalled by the brutal murder of Jim Foley by the terrorist group ISIL,"" Obama said in a statement from Martha's Vineyard, where he is on vacation. ""James was taken from us in an act of violence that shocks the conscience of the entire world."" + +On Tuesday, the group formerly known as ISIS released a video of militants beheading Foley, claiming it was in retribution for U.S. airstrikes in Iraq. The Federal Bureau of Investigations said Wednesday they believe the video to be authentic. + +Obama said he spoke to Foley's family earlier Wednesday to offer his condolences. + +""Jim Foley's life stands in stark contrast to his killers,"" Obama said. ""Let's be clear about ISIL. They have rampaged across cities and villages killing unarmed citizens in cowardly acts of violence. ... No faith teaches people to massacre innocents. No just God would stand for what they did yesterday and what they do every single day."" + +""Their ideology is bankrupt,"" he said. ""People like this ultimately fail. They fail because the future is won by those who build and not destroy."" + +Obama pledged to continue to ""do what is necessary"" to protect Americans and support the Iraqi forces fighting back the extremist group, despite their threats. + +""We will be vigilant and we will be relentless,"" he said.","1" +"Islamic State releases video apparently showing the beheading of missing US journalist James Foley","The White House is attempting to verify footage released by the Islamic State (IS) purporting to show the killing of an American journalist in retaliation for ongoing US airstrikes against its forces in Iraq. + +The video circulated on Tuesday showed a masked Isis fighter beheading a kneeling man cloaked in an orange jumpsuit who is purported to be James Foley, a photojournalist who went missing in Syria in 2012. The White House said it was working to establish the video's authenticity, but if it was genuine, the US would be “appalled by the brutal murder”. + +Foley has worked in a number of conflict zones in the Middle East, including Syria, Libya and Iraq. He and another journalist were working in the northern province of Idlib in Syria when they were kidnapped in November 2012 near the village of Taftanaz. + +The video opened with a clip of US President Barack Obama saying he had authorised strikes in Iraq. “Obama authorises military operations against the Islamic State effectively placing America upon a slippery slope towards a new war front against Muslims,” words appear in English and Arabic on the screen. It showed black and white aerial footage of air strikes with text saying “American aggression against the Islamic State” + +A person identified as James Foley and wearing an orange outfit is seen kneeling in the desert as a man in black dress with a black mask stands beside him, holding a knife. “I call on my friends family and loved ones to rise up against my real killers, the US government, for what will happen to me is only a result of their complacency and criminality,” the kneeling man says. + +The man in the mask says: “This is James Wright Foley, an American citizen, of your country. As a government, you have been at the forefront of the aggression towards the Islamic State. Today your military air force is attacking us daily in Iraq. Your strikes have caused casualties amongst Muslims. You are no longer fighting an insurgency. We are an Islamic army, and a state that has been accepted by a large number of Muslims worldwide.” + +Following his statement he beheads the kneeling man. + +The video also shows a second man on his knees, who is named as Steven Sotloff, another American journalist, who was kidnapped in Syria in August 2013. After bringing out Sotloff, the masked executioner addresses the US President directly, saying: “The life of this American citizen, Obama, depends on your next decision.” + +The Islamic State had not previously executed American citizens publicly. The video was posted after the United States resumed air strikes in Iraq for the first time since the end of the US occupation in 2011. A Twitter account set up by Mr Foley’s family to help find him said early on Wednesday: “We know that many of you are looking for confirmation or answers. Please be patient until we all have more information, and keep the Foleys in your thoughts and prayers.”","1" +"ISIS Reportedly Beheads U.S. Journalist James Wright Foley on Camera","According to multiple reports, ISIS claims to have executed American freelance journalist James Foley. Politico’s Blake Hounshell was one the first to report the news on Twitter, saying the militant Islamic group is threatening to kill another reporter in retaliation for U.S. strikes on their forces in Iraq: + + +Foley had been missing since November 22, 2012 when he disappeared in Syria.","1" +"James Wright Foley, Kidnapped Journalist, Apparently Executed by ISIS","The Islamic State of Iraq and al-Sham (ISIS) claims to have beheaded an American photojournalist and has threatened the life of another American if President Obama doesn't stop airstrikes in Iraq. + +A graphic video obtained by NBC News purportedly shows James Wright Foley, a freelance reporter for the U.S.-based news service GlobalPost who was kidnapped while reporting from Syria two years ago, reciting threats against America before he is executed by an ISIS militant. + +Foley was kidnapped at gunpoint near the town of Taftanaz in northern Syria on Thanksgiving Day in 2012. He had not been heard from during his time in captivity. ""We’ve heard nothing. Nothing. We last knew that he was abducted on Thanksgiving Day in the Idlib province, but we don’t know who took him or why,"" Foley's father, John, said on TODAY last year. + +Foley traveled extensively in the Middle East and North Africa. He reported about conflicts from Iraq, Afghanistan, and Libya, where he was once held captive for 44 days. + +In May 2011, Foley recorded a video interview with The Boston Globe about his arrest and captivity in Libya. “You don’t want to be defined as that guy who got captured in 2011,” he said. “I believe that front-line journalism is important.” + +In the video, ISIS claims they are holding a second journalist, Steven Joel Soltoff. A man on the video is identified as Soltoff and his life is threatened if the United States does not pull out of Iraq. + +GlobalPost has a partnership with NBC News.","1" +"Fears journalist James Wright Foley beheaded by Islamic State jihadists in ‘message’ to United States","UNCONFIRMED reports indicate a US journalist held captive in Iraq has been beheaded as a “message” to President Obama to end air strikes. +Video and pictures of journalist James Wright Foley’s final moments have been published via Twitter by accounts claiming to be associated with the Islamic State, previously known as the Islamic State in Iraq and Syria (ISIS). +Mr Foley was abducted in Idlib, Iraq, in 2012. Born in New Hampshire, he wrote for a variety of media organisations including the Global Post. +The identity of the man in the high-definition footage, titled “A Message to America”, has not yet been confirmed. +The footage shows a man in orange prisoner fatigues being led to a remote desert location where he is forced to kneel before reciting a message ... stating that his “real killer” was the United States. +He is then beheaded. +The Islamic State has issued a warning with the video: There will be more executions if President Barak Obama does not end air strikes in aid of the embaddled Kurdish and Iraqi Government forces. +“We will drown all of you in blood,” a statement attributed to the Jihadists states. +The video then shows what it claims to be another US captive. +MORE TO COME","1" +"James Foley beheaded: ISIS claims to have killed US journalist","US journalist James Foley, believed held captive in Syria, has reportedly been beheaded as a “message” to President Obama. + +Unconfirmed video and pictures of photojournalist James Wright Foley’s heartbreaking final moments have been published via Twitter by accounts claiming to be associated with the Islamic State, previously known as the Islamic State in Iraq and Syria (ISIS). + +Mr Foley was abducted in Syria, in 2012, while covering the campaign against President Bashar al-Assad. He wrote for a variety of media organisations including the AFP news agency. + +The identity of the man in the high-definition footage, titled “A Message to America”, has not yet been officially confirmed. The YouTube file, originally uploaded on Tuesday, has since been deleted. + +Friends and family of Mr Foley have released a statement saying they are uncertain of what the video shows. “We know that many of you are looking for confirmation or answers. Please be patient until we all have more information”, their Facebook group “Free James Foley” reads. + +EXECUTION’S BRUTAL MESSAGE + +The gruesome video shows a man in orange prisoner fatigues being led to a remote desert location where he is forced to kneel before reciting a message urging Americans to rise against his “real killer” — the United States. + +“I call on my friends, family, and loved ones to rise up against my real killers, the US government,” he is heard to say. “For what will happen to me is only a result of their complacency and criminality. + +The US government has issued a statement saying the intelligence community is working to verify the identity of the men shown in the footage. + +“If genuine, we are appalled by the brutal murder of an innocent American journalist and we express the deepest condolences to his family and friends. We will provide more information when it is available.” + +TERROR PROPAGANDA TARGETS FAMILY + +In the video, the man, who is reported to be Foley, looks calm as he kneels with his hands tied behind his back. Speaking in a level voice with a a microphone attached to his orange robe, he can sometimes be heard swallowing as he bravely continues his speech. + +“I call on my brother John, who is a member of the US air force. Think about what you are doing, think about the lives you destroy, including those of your own family.” + +He goes on to attack the integrity of the US government decision: “Think John, who did they really kill? And did they think about me, you, our family when they made that decision?” + +His statement, which is presumed to have been prepared for him by the militants, ends with: “I guess all in all I wish I wasn’t American.” + +It’s not the first time Foley has been held captive. He was taken by government forces in while covering the 2011 uprising against Libya’s Muammar Gaddafi. He was released after six weeks. + +In the video released today, the man belived to be Foley is beheaded with a knife by a black-masked man who speaks with what sounds to be a British accent. + +“Any attempt by you, Obama, to deny the Muslims their rights of living in safety under the Islamic caliphate will result in the bloodshed of your people,” the executioner intones. + +The Islamic State has issued a warning with the video: There will be more executions if President Obama does not end air strikes in aid of the embattled Kurdish and Iraqi Government forces. + +“We will drown all of you in blood,” the jihadists state. + +TWO MORE CAPTIVES THREATENED + +The propaganda video also shows what it claims to be another US captive, identified as journalist Steven Joel Sotloff. + +The dialogue then states his future depends on President Obama’s “next decision”. + +Mr Sotloff is a freelance journalist who was abducted in Syria in August 2013. + +A third prisoner has been threatened in a separate statement attributed to the Islamic State and addressed to his family. + +Warren Weinstein is named as a prisoner the jihadists wish to exchange for one of their own members held by unnamed Western-affiliated forces. + +The open letter, circulating on Twitter, threatens that if Mr Weinstein’s family do not oppose their government, their son will suffer. + +“Your continued silence on the inaction of your government will only lead to your prisoner dying a lonely death in prison after this deliberate and prolonged neglect on the part of your government,” the document reads. + +“Therefore, if you want Warren Weinstein to be released; do whatever you can to pressurize your government”.","1" +"Video Purports To Show Beheading Of U.S. Journalist By Militants","Extremist group the Islamic State claims to have executed American journalist James Foley, who was abducted in Syria in 2012. The FBI is evaluating a video that was posted online Tuesday, purporting to show Foley's beheading. + +That video was uploaded to YouTube on Tuesday afternoon and later removed. The images show a man resembling Foley kneeling next to a masked militant, reciting comments against the U.S. before being killed. + +U.S. officials tell the Associated Press that Islamic State had recently threatened to kill Foley to avenge U.S. airstrikes that have helped Iraqi forces regain key sites, including the Mosul dam. + +The Islamic State also says it's holding another American journalist, Steven Joel Sotloff, who went missing in Syria last year, and that Sotloff could be the next victim. + +National Security Council spokeswoman Caitlin Hayden says U.S. officials are studying the video to determine whether it's genuine: + +Foley has been missing since November of 2012, when he was kidnapped while reporting in Syria for the news organization GlobalPost. A Facebook page was later created to call for his return; last night, it posted this statement from Foley's mother, Diane: + +GlobalPost notes that, ""The Foley family has not received confirmation of Jim's death from the U.S. government, and acknowledged that there is still a small chance the video of his apparent killing will prove to have been fake."" + +The company's CEO and co-founder, Philip Balboni, says GlobalPost had been working to learn who kidnapped Foley, and where he was being held captive. + +""Although GlobalPost's investigation at one point led us to believe that James was being held by the Syrian government, we later were given strong reason to believe he was being held by Islamic militants in Syria,"" Balboni said. ""We withheld this information at the request of the family and on the advice of authorities cooperating in the effort to protect Jim. GlobalPost, working with a private security company, has amassed an enormous amount of information that has not been made public."" + +Foley was on a freelance assignment for GlobalPost when he was abducted in northern Syria on Nov. 22, 2012. He had been making his way to the Turkish border when he was stopped by a group of armed men, the organization says. + +Back in 2011, Foley was one of three journalists who were held captive for more than a month after being attacked by Gaddafi fighters near Benghazi. A fourth journalist didn't survive the attack. + +Their ordeal led Foley and one of his colleagues, American Claire Gillis, to visit NPR's Talk of the Nation back in 2011. Discussing the uncertain weeks of their captivity, Foley said they ""turned to a lot of prayer"" and exercise. In the end, he was the last of the journalists to be released, after spending a week as the sole Westerner in the prison. + +""I started to have some dark thoughts,"" he said. ""I started to think, you know, maybe they're keeping the American guy as the ace in the hole... I thought maybe I was going to be a bargaining chip.""","1" +"U.S. Authenticates Video Of Militants Beheading American Journalist","This post was updated at 11:45 a.m. ET. + +A video that was released online Tuesday in which the extremist group the Islamic State claimed to behead American journalist James Foley is authentic, according to U.S. intelligence analysts. Foley was abducted in Syria in 2012. + +The video was uploaded to YouTube on Tuesday afternoon and later removed; since then, it has resurfaced elsewhere online. The images show Foley kneeling next to a masked militant and reciting comments against the U.S. before being killed. + +After analyzing the footage, National Security Council spokesperson Caitlin Hayden says, ""We have reached the judgment that this video is authentic."" + +The execution likely will be the focus of remarks by President Obama, who is expected to speak at 12:45 p.m. ET. + +U.S. officials tell The Associated Press that the Islamic State had recently threatened to kill Foley to avenge U.S. airstrikes that have helped Iraqi forces regain key sites, including the Mosul dam. + +In the video, the Islamic State also says it is holding another American journalist, Steven Joel Sotloff, and that he could be the next victim. Sotloff went missing in Syria last year. + +The National Security Council's Hayden said earlier today that the U.S. is ""appalled by the brutal murder of an innocent American journalist, and we express our deepest condolences to his family and friends."" + +Foley has been missing since November 2012, when he was kidnapped while reporting in Syria for the news organization GlobalPost. A Facebook page was later created to call for his return. Last night, it featured this statement from Foley's mother, Diane: + +GlobalPost's CEO and co-founder, Philip Balboni, says the company had been working to learn who kidnapped Foley and where he was being held captive. + +""Although GlobalPost's investigation at one point led us to believe that James was being held by the Syrian government, we later were given strong reason to believe he was being held by Islamic militants in Syria,"" Balboni said. ""We withheld this information at the request of the family and on the advice of authorities cooperating in the effort to protect Jim. GlobalPost, working with a private security company, has amassed an enormous amount of information that has not been made public."" + +Foley was on a freelance assignment for GlobalPost when he was abducted in northern Syria on Nov. 22, 2012. He had been making his way to the Turkish border when he was stopped by a group of armed men, the organization says. + +Back in 2011, Foley was one of three journalists held captive for more than a month after being attacked by Gadhafi fighters near Benghazi. A fourth journalist didn't survive the attack. + +After their ordeal, Foley and an American colleague, Claire Gillis, visited NPR's Talk of the Nation in 2011. Discussing the uncertain weeks of their captivity, Foley said they ""turned to a lot of prayer"" and exercise. In the end, he was the last of the journalists to be released, after spending a week as the sole Westerner in the prison. + +""I started to have some dark thoughts,"" he said. ""I started to think, you know, maybe they're keeping the American guy as the ace in the hole. ... I thought maybe I was going to be a bargaining chip.""","1" +"ISIS militants appear to behead abducted American journalist James Wright Foley in graphic video","WARNING: GRAPHIC IMAGES. A masked militant claims the murder is in retaliation for American airstrikes against the Islamic State militants in Iraq. Missing since Nov. 22, 2012, Foley appears to be forced to read an anti-American statement before he is beheaded in the gruesome five-minute clip. + +An American freelance photojournalist missing since being abducted in Syria some 22 months ago was apparently beheaded by an Islamic State militant in a graphic video released Tuesday. + +Titled “A Message to America,” the gruesome clip shows a masked militant saw away at the neck of James Wright Foley, a 40-year-old New Hampshire native captured in Binesh, Syria on Thanksgiving Day 2012. + +The family, on its ""Free James Foley"" Facebook page, has yet to confirm his death. + +""Please be patient until we all have more information, and keep the Foleys in your thoughts and prayers,"" the statement reads. + +Foley, dressed in orange and kneeling in a desert, reads what appears to be a coerced statement that alludes to recent American airstrikes against the Islamic State in Iraq. + +“I call on my friends, family and loved ones to rise up against my real killers, the U.S. government. For what will happen to me is only a result of their complacency and criminality,” Foley reads as he kneels beside an armed militant, masked and dressed all in black. “My message to my beloved parents: Save me some dignity, and don’t accept some minor compensation for my death from the same people who effectively hit the last nail in my coffin with their recent aerial campaign in Iraq. I call on my brother John, who is a member of the U.S. Air Force: Think about what you are doing. Think about the lives you destroy, including those of your own family … I wish I could have the hope of freedom and seeing my family once again, but that ship has sailed. I guess all in all, I wish I wasn’t American.” + +The militant, speaking English with what appears to a British accent, threatens America and President Obama, directly after Foley finishes speaking. + +“So any attempt by you, Obama, to deny the Muslims their rights of living in safety under the Islamic caliphate will result in the bloodshed of your people,” the man says, gesturing with a knife he then uses to behead Foley. + +The clip begins with a video of President Obama announcing Aug. 7. American intervention in Iraq against the militants. + +“Today I authorized two operations in Iraq: targeted airstrikes to protect our American personnel, and a humanitarian effort to help save thousands of Iraqi civilians who are trapped on a mountain without food and water, and facing almost certain death,” Obama said in the clip. + +The 40-year-old New Hampshire native has been missing since 2012. + +James Foley was reporting in the Middle East when abducted. + +Foley, 40, is a New Hampshire native. He was reporting in the Middle East when abducted. + +Toward the end of the video, the terror group threatens to kill another hostage, Steven Joel Soltoff, a journalist who has contributed to TIME and has been missing since the middle of last year. + +“The life of this American citizen, Obama, depends on your next decision,” the man says as he holds Soltoff by the neck. + +The nearly five-minute clip has since been removed from YouTube. It’s unclear where, exactly, the murder was filmed. + +The White House, in a statement from National Security Council spokeswoman Caitlin Hayden, confirmed they ""have seen a video that purports to be the murder of U.S. citizen James Foley."" + +""The intelligence community is working as quickly as possible to determine its authenticity,"" the statement reads. ""If genuine, we are appalled by the brutal murder of an innocent American journalist and we express our deppest condolences to his family and friends."" + +In 2002, Wall Street Journal reporter Daniel Pearl, 38, was beheaded on video in Pakistan days after being abducted by Al-Qaeda militants. + +sgoldstein@nydailynews.com + +On a mobile device? Click here to watch the video.","1" +"ISIS militants behead abducted American journalist James Wright Foley in graphic video","WARNING: GRAPHIC IMAGES. A masked militant claims the murder is in retaliation for American airstrikes against the Islamic State militants in Iraq. Missing since Nov. 22, 2012, Foley appears to be forced to read an anti-American statement before he is beheaded in the gruesome five-minute clip. His family confirmed his death late Tuesday evening. + +An American freelance photojournalist missing since being abducted in Syria some 22 months ago was beheaded by an Islamic State militant in a graphic video released Tuesday. + +Titled “A Message to America,” the gruesome clip shows a masked militant saw away at the neck of James Wright Foley, a 40-year-old New Hampshire native captured in Binesh, Syria on Thanksgiving Day 2012. + +The man's mother, Diane Foley, confirmed her son's death in a heartbreaking statement on the ""Free James Foley"" Facebook page. + +""We had never been prouder of our son Jim,"" the statement reads. ""He gave his life trying to expose the world to the suffering of the Syrian people. We implore the kidnappers to spare the lives of the remaining hostages. Like Jim, they are innocents. They have no control over American government policy in Iraq, Syria or anywhere in the world."" + +Foley, dressed in orange and kneeling in a desert, reads what appears to be a coerced statement that alludes to recent American airstrikes against the Islamic State in Iraq. + +“I call on my friends, family and loved ones to rise up against my real killers, the U.S. government. For what will happen to me is only a result of their complacency and criminality,” Foley reads as he kneels beside an armed militant, masked and dressed all in black. “My message to my beloved parents: Save me some dignity, and don’t accept some minor compensation for my death from the same people who effectively hit the last nail in my coffin with their recent aerial campaign in Iraq. I call on my brother John, who is a member of the U.S. Air Force: Think about what you are doing. Think about the lives you destroy, including those of your own family … I wish I could have the hope of freedom and seeing my family once again, but that ship has sailed. I guess all in all, I wish I wasn’t American.” + +The militant, speaking English with what appears to a British accent, threatens America and President Obama, directly after Foley finishes speaking. + +“So any attempt by you, Obama, to deny the Muslims their rights of living in safety under the Islamic caliphate will result in the bloodshed of your people,” the man says, gesturing with a knife he then uses to behead Foley. + +The clip begins with a video of President Obama announcing Aug. 7. American intervention in Iraq against the militants. + +“Today I authorized two operations in Iraq: targeted airstrikes to protect our American personnel, and a humanitarian effort to help save thousands of Iraqi civilians who are trapped on a mountain without food and water, and facing almost certain death,” Obama said in the clip. + +Toward the end of the video, the terror group threatens to kill another hostage, Steven Joel Soltoff, a journalist who has contributed to TIME and has been missing since the middle of last year. + +“The life of this American citizen, Obama, depends on your next decision,” the man says as he holds Soltoff by the neck. + +The nearly five-minute clip has since been removed from YouTube. It’s unclear where, exactly, the murder was filmed. + +The 40-year-old New Hampshire native has been missing since 2012. + +James Foley was reporting in the Middle East when abducted. + +Foley, 40, is a New Hampshire native. He was reporting in the Middle East when abducted. + +The White House, in a statement from National Security Council spokeswoman Caitlin Hayden, confirmed they ""have seen a video that purports to be the murder of U.S. citizen James Foley."" + +""The intelligence community is working as quickly as possible to determine its authenticity,"" the statement reads. ""If genuine, we are appalled by the brutal murder of an innocent American journalist and we express our deppest condolences to his family and friends."" + +In 2002, Wall Street Journal reporter Daniel Pearl, 38, was beheaded on video in Pakistan days after being abducted by Al-Qaeda militants. + +sgoldstein@nydailynews.com + +On a mobile device? Click here to watch the video.","1" +"Militant Group Says It Killed American Journalist in Syria","The Islamic State in Iraq and Syria posted a video on Tuesday that it said showed the beheading of James Foley, an American journalist who was kidnapped in Syria nearly two years ago, according to a transcript released by the SITE Intelligence Group. + +The authenticity of the video, which was also posted on YouTube, could not be verified, and a telephone call placed to Mr. Foley’s family was not immediately returned. YouTube later took down the four-minute, 40-second video. + +Continue reading the main story +RELATED COVERAGE + +MEMENTOS FROM CAPTIVITY: Items saved by Harald Ickler, a Swede living in Germany, from his 54 days as a hostage in 2003. He was on what he thought would be a four-week adventure vacation when he was kidnapped in the Algerian desert by jihadists who would soon become an official arm of Al Qaeda.Underwriting Jihad: Paying Ransoms, Europe Bankrolls Qaeda TerrorJULY 29, 2014 +The Lede: Investigation Suggests American Journalist Missing in Syria Is ‘Likely’ Held by GovernmentMAY 3, 2013 +Titled “A Message to America,” the video shows the journalist kneeling in a desert landscape, clad in an orange jumpsuit — an apparent reference to the uniforms worn by prisoners at the American military detention camp in Guantánamo Bay, Cuba. Standing to his left is a masked ISIS fighter, who begins speaking in English, with what sounds like an East London accent. Pulling out a knife, he says that Mr. Foley’s execution is in retaliation for the recent American airstrikes ordered by President Obama against the extremist group in Iraq. + +“I call on my friends, family and loved ones to rise up against my real killers — the U.S. government — for what will happen to me is only a result of their complacent criminality,” Mr. Foley says in the video, which was uploaded to the online account of the al-Furqan Media Foundation, according to SITE, an organization that follows jihadist groups. He ends saying that when American soldiers began dropping bombs on Iraq this month, “they signed my death certificate.” + +On Tuesday night, Mr. Foley’s mother, Diane Foley, issued a statement on the Facebook page the family had created to publicize their son’s disappearance: “We have never been prouder of our son Jim. He gave his life trying to expose the world to the suffering of the Syrian people. We implore the kidnappers to spare the lives of the remaining hostages. Like Jim, they are innocents. They have no control over American government policy in Iraq, Syria or anywhere in the world.” + +Two weeks ago, in the wake of American-led airstrikes against the terrorist group, which was fanning out across Iraq, jihadists had taken to social media to call for attacks on American interests. In the three hours after the graphic video of Mr. Foley’s beheading was uploaded on YouTube, jihadists using the hashtag “#NewMessageFromISIStoUS” surpassed 2,000 tweets, according to a survey by SITE, with many fighters gloating over his death, and calling it just retribution for the air raids. + +Mr. Foley, 40, a freelance journalist who was working for GlobalPost, an online publication based in Boston, as well as for Agence France-Presse, disappeared in Syria on Nov. 22, 2012. He was held alongside several other Americans, whose families have asked for a news blackout. + +The video concludes with the fighter threatening to kill Steven Sotloff, another American freelance journalist, who was being held alongside Mr. Foley. Mr. Sotloff is seen kneeling in the same position, in the same landscape and wearing the same style of orange-colored jumpsuit. “The life of this American citizen, Obama, depends on your next decision,” the fighter says. + +Mr. Obama was briefed about the video by Benjamin J. Rhodes, the deputy national security adviser, on Air Force One as he returned to Martha’s Vineyard, according to Eric Schultz, the deputy White House press secretary. + +In Washington, a National Security Council spokeswoman, Caitlin Hayden, said in a statement: “We have seen a video that purports to be the murder of U.S. citizen James Foley by ISIL. The intelligence community is working as quickly as possible to determine its authenticity. If genuine, we are appalled by the brutal murder of an innocent American journalist,” she said, using an alternative name for ISIS. + +Reached by telephone, Philip Balboni, the chief executive and a founder of GlobalPost, said that the newsroom and Mr. Foley’s family were also trying to establish the veracity of the footage. “We are still evaluating the video at this time,” he said. + +Mr. Foley, who was last seen in Binesh, Syria, was also abducted in Libya in 2011, where he was held for several weeks after running into troops loyal to Col. Muammar el-Qaddafi’s crumbling government. + +He was among dozens of journalists — many of them freelancers without the formal backing of a news organization — who disappeared in 2012 and 2013 in Syria. + +Correction: August 19, 2014 +An earlier version of a summary with this article misstated the location of the airstrikes that ISIS opposed. The terrorist group said it executed James Foley in retaliation for American airstrikes in Iraq, not Syria.","1" +"Obama, Outraged Over Beheading, Vows to Stay on Course","President Obama declared that the entire world was “appalled” by the beheading of an American journalist by militants in Syria, but vowed that America would not change course in Iraq, where the United States has been conducting airstrikes against terrorists, despite threats by the group to kill another reporter in the days ahead. + +“The United States of America will continue to do what we must do to protect our people,” Mr. Obama said in a brief statement from Martha’s Vineyard, where he was vacationing. “We will be vigilant and we will be relentless.” + +Before speaking to reporters, Mr. Obama said he placed a phone call to the parents of James Foley, the slain reporter, telling them that Americans were “are all heartbroken at their loss.” He described Mr. Foley as a “journalist, a son, a brother and a friend who was “taken from us in an act of violence that shocked the conscience of the entire world.” + +But the president’s harshest and most emotional words were reserved for the Islamic State in Iraq and Syria, the militants who released a video of the killing of Mr. Foley on Tuesday. American intelligence agencies on Wednesday verified the authenticity of the video, which shows a masked man decapitating James Foley, an American journalist who was kidnapped in Syria nearly two years ago. It also shows another American captive, the journalist Steven Sotloff, and warns that he would be the next to die. + +The president called ISIS a “cancer” in the region and accused them of having “rampaged across cities and villages, killing unarmed civilians in cowardly acts of violence.” He said it had committed torture and rape against innocent women and children and continued to enslave those they did not kill. + +“No faith teaches people to massacre innocents,” Mr. Obama said. “No just God would stand for what they did yesterday and what they do every single day. People like this ultimately fail. They fail because the future is won by people who build and not destroy.” + +The killing of Mr. Foley triggered a fierce response. The New York Daily News and The New York Post both used the same banner headline on their front pages: “Savages.” Prime Minister David Cameron of Britain released a statement saying “the brutal murder of James Foley is shocking and depraved.” + +At the United Nations, Secretary-General Ban Ki-moon issued a statement condemning ISIS for “the horrific murder of journalist James Foley, an abominable crime.” Mr. Ban said “the perpetrators of this and other such horrific crimes must be brought to justice.” + +The four-minute, 40-second video was posted on YouTube but the website later took it down. Titled “A Message to America,” it shows Mr. Foley kneeling in a desert landscape, clad in an orange jumpsuit in an apparent reference to the uniforms worn by prisoners at the American military detention camp in Guantánamo Bay, Cuba. Standing to his left is a masked ISIS fighter who begins speaking in English, with what sounds like an East London accent. Pulling out a knife, he says that Mr. Foley’s execution is in retaliation for the recent American airstrikes ordered by Mr. Obama against the extremist group in Iraq.","1" +"Video shows ISIL beheading of photojournalist James Foley","Men claiming to be part of terrorist group Islamic State of Iraq and the Levant posted a video showing the beheading of freelance photojournalist James Wright Foley, who disappeared in northwest Syria on November 22, 2012. On Wednesday the National Security Council said the video appears to be authentic. + +The video starts with a clip of President Barack Obama earlier this month making the announcement that he had authorized targeted strikes in Iraq to protect American interests in Irbil. It then cuts to a title scene that says ""Message to America"" before cutting to a desert scene, with Foley in orange clothes on his knees, and a man in all black standing next to him. + +In the video Foley delivers a statement calling on his friends and family to ""rise up against my real killers, the U.S. government."" + +Then the ISIL member makes a statement. Speaking in what may possibly be a British accent, he identifies Foley and says his death is a direct result of American intervention in Iraq. + +""So any attempt by you Obama, to deny the Muslims of living in safety under Islamic caliphate will result in the bloodshed of your people."" + +He then beheads Foley. + +Freelance journalist Steven Joel Sotloff is then shown also in an orange jumpsuit on his knees. The man in black then says ""The life of this American citizen Obama, depends on your next decision."" + +About 20 minutes after posting the video was removed from YouTube. + +According to BuzzFeed, two people who know Foley confirmed that the man in the video looks and sounds like him. A statement attributed to Foley's mother Diane and posted to the ""Free James Foley"" Facebook page said the family has ""never been prouder of our son"" and implored the kidnappers to keep those still captive alive. + +""We have never been prouder of our son Jim. He gave his life trying to expose the world to the suffering of the Syrian people,"" Diane Foley said in the statement. ""We implore the kidnappers to spare the lives of the remaining hostages. Like Jim, they are innocents. They have no control over American government policy in Iraq, Syria or anywhere in the world. We thank Jim for all the joy he gave us. He was an extraordinary son, brother, journalist and person. Please respect our privacy in the days ahead as we mourn and cherish Jim."" + +White House Deputy Spokesperson Eric Schultz said President Barack Obama was briefed on the video Tuesday night by Deputy National Security Advisor Ben Rhodes and will continue to receive regular updates, according to White House pool report. + +In a statement, National Security Council spokesperson Caitlin Hayden said that if the video is genuine they are ""appalled by the brutal murder."" + +""We have seen a video that purports to be the murder of U.S. citizen James Foley by ISIL. The intelligence community is working as quickly as possible to determine its authenticity. If genuine, we are appalled by the brutal murder of an innocent American journalist and we express our deepest condolences to his family and friends. We will provide more information when it is available,"" Hayden said. + +On Wednesday, Hayden said in a statement that the video had been deemed authentic. + +""The U.S. Intelligence community has analyzed the recently released video showing U.S. citizens James Foley and Steven Sotloff. We have reached the judgment that this video is authentic. We will continue to provide updates as they are available,"" Hayden said. + +Foley, 40, grew up in New Hampshire and was originally a teacher, at one point teaching prison inmates in Arizona, before attending the Medill school of journalism at Northwestern University. After graduation, his first assignment was as an embed with the U.S. Army’s 173rd Brigade and 101st Airborne Division in Afghanistan. Foley had been covering the Syria's civil war for GlobalPost and Agence France-Presse (AFP) when he was allegedly pulled from the car he was traveling in to meet with a colleague and abducted at gunpoint. According to the Columbia Journalism Review, GlobalPost hired an international security firm for a ground level investigation in Northern Syria and along the Turkish border to locate him. + +Foley was also detained and held for 44 days in Libya in 2011. + +(6:15 pm): This post has been updated to include the NSC statement. + +(9:45pm): This post has been updated with the Foley family statement. + +(8/20/2014 11:40 am): This post has been updated with the NSC statement that the video is authentic.","1" +"Journalist James Wright Foley reportedly beheaded by ISIS","A video has surfaced purporting to depict American journalist James Wright Foley being beheaded by those who claim to be ISIS rebels. James Wright Foley disappeared in northwest Syria on November 22, 2012. + +The video features text saying “Obama authorizes military operations against the Islamic State effectively placing America upon a slippery slope towards a new war front against Muslims.” It then cuts to a clip of Obama announcing airstrikes against ISIS and then to Foley kneeling in orange, next to a man wearing black with his face covered. In it, Foley is forced to read a letter urging Americans to rise up against his “real killer,” the “U.S. government.” I call on my friends, family and loved ones to rise up against my real killer, the U.S. government. What will happen to me is only a result of their complacency and criminality.” + +According to Time’s Mirren Gidda: + +American airstrikes began earlier this month in an attempt to help thousands of people—members of the Yazidi, an ethnic minority in the region—who were trapped on a mountain range by fighters of the Islamic State of Iraq and Greater Syria (ISIS). President Barack Obama formally told Congress on Sunday that he had sanctioned additional air raids, though he said they would be limited. The new strikes, requested by the Iraqi government, were intended to help Iraqi and Kurdish security forces who had been battling the militants for control of the strategic Mosul Dam. Aided by U.S. air support, these troops successfully recaptured it on Aug. 18. + +The video also shows a man on his knees who is allegedly Steven Sotloff, a freelance journalist who went missing in Syria on Aug. 3, 2013. According to the video, Sotloff’s fate depends on Obama’s “next decision.” + +Salon has chosen not to share the video.","1" +"ISIS Reportedly Beheads American Photojournalist in Iraq","ISIS terrorists have released a video purportedly showing the beheading of American freelance photojournalist James Wright Foley who went missing on Thanksgiving Day in 2012. + +Foley, a 40-year-old New Hampshire native, was kidnapped at gunpoint from an Internet café in Syria. ISIS has threatened that Steven Sotloff—another freelance reporter who has been missing since August 2013 and has written for numerous publications such as Time, Christian Science Monitor, and Foreign Policy—will also be executed depending ""on Obama’s next decision"" regarding U.S. military strikes against ISIS in Iraq. + +In the graphic video, Foley was forced to read a letter encouraging Americans to rise up against his “real killer”—“the U.S. government,” adding that the U.S. airstrikes against ISIS “hammered the final nail into [his] coffin.” Apparently, his executor was heard in the video speaking English with a British accent.","1" +"ISIS Reportedly Beheads American Photojournalist in IraqRunning ScaredWhy Apple Pay Can Succeed Where Google Wallet FailedWhy the Military Treats Male Sexual Assault Victims So HorriblyWhy Google Bought a SpoonWe All Have Certain Words We Use Too Often. What’s Yours?Meatless MondaysThe Beatles. Bob Dylan. Biggie Smalls.How to Fix Gerrymandering and Improve American Politics in One Fell SwoopThe Very Funny Comic Who Just Became SNL’s Next “Weekend Update” Anchor","ISIS terrorists have released a video purportedly showing the beheading of American freelance photojournalist James Wright Foley who went missing on Thanksgiving Day in 2012. + +Foley, a 40-year-old New Hampshire native, was kidnapped at gunpoint from an Internet café in Syria. ISIS has threatened that Steven Sotloff—another freelance reporter who has been missing since August 2013 and has written for numerous publications such as Time, Christian Science Monitor, and Foreign Policy—will also be executed depending ""on Obama’s next decision"" regarding U.S. military strikes against ISIS in Iraq. + +In the graphic video, Foley was forced to read a letter encouraging Americans to rise up against his “real killer”—“the U.S. government,” adding that the U.S. airstrikes against ISIS “hammered the final nail into [his] coffin.” Apparently, his executor was heard in the video speaking English with a British accent.","1" +"ISIS Reportedly Beheads American Photojournalist in IraqRunning ScaredVikings Star Adrian Peterson Reportedly Indicted for Child AbuseWhy the Military Treats Male Sexual Assault Victims So HorriblyWhy Google Bought a SpoonWe All Have Certain Words We Use Too Often. What’s Yours?Meatless MondaysThe Beatles. Bob Dylan. Biggie Smalls.How to Fix Gerrymandering and Improve American Politics in One Fell SwoopThe Very Funny Comic Who Just Became SNL’s Next “Weekend Update” Anchor","ISIS terrorists have released a video purportedly showing the beheading of American freelance photojournalist James Wright Foley who went missing on Thanksgiving Day in 2012. + +Foley, a 40-year-old New Hampshire native, was kidnapped at gunpoint from an Internet café in Syria. ISIS has threatened that Steven Sotloff—another freelance reporter who has been missing since August 2013 and has written for numerous publications such as Time, Christian Science Monitor, and Foreign Policy—will also be executed depending ""on Obama’s next decision"" regarding U.S. military strikes against ISIS in Iraq. + +In the graphic video, Foley was forced to read a letter encouraging Americans to rise up against his “real killer”—“the U.S. government,” adding that the U.S. airstrikes against ISIS “hammered the final nail into [his] coffin.” Apparently, his executor was heard in the video speaking English with a British accent.","1" +"ISIS Beheads American Journalist","In a video posted online Tuesday, ISIS beheads James Wright Foley, an American freelance journalist who was captured in Syria in 2012. The video says the killing is a warning to the U.S. to end its intervention in Iraq. The video also shows Steven Sotloff, a freelance journalist working for Time, and threatens that he will be next. Sotloff's kidnapping seems to have been kept secret until now. Foley was working as a photographer in Syria for AFP when he was taken. The year prior he had been kidnapped in Libya.","1" +"James Foley: American Journalist, James Wright Foley Beheaded in New ISIS Video [Breaking News]","James Wright Foley, an American journalist kidnapped in 2012, was beheaded in an ISIS video released on Tuesday, August 19. + +The video is titled “A Message to America.” + +A figure in a black robe with a gun strapped on his person and a masked hat covering his face, apart from his eyes, appears in the video next to Foley. + +In the video, the Islamic State says that Obama’s authorization of strikes against IS places United States “upon a slippery slope towards a new war front against Muslims,” accordin to BNO. + +“Any attempt by you, Obama, to deny Muslims liberty & safety under the Islamic caliphate, will result in the bloodshed of your people,” the ISIS person added. + +Foley also speaks in the video, saying: “call on my friends, family members and loved ones to rise up against my real killers, the U.S. government.” + +See an Associated Press story below.","1" +"James Foley: American Journalist James Wright Foley Beheaded in New Graphic ISIS Video [Breaking News]","James Wright Foley, an American journalist kidnapped in 2012, was beheaded in an ISIS video released on Tuesday, August 19. + +The video is titled “A Message to America.” + +A figure in a black robe with a gun strapped on his person and a masked hat covering his face, apart from his eyes, appears in the video next to Foley. + +In the video, the Islamic State says that U.S. President Barack Obama’s authorization of strikes against the group places the United States “upon a slippery slope towards a new war front against Muslims,” according to BNO. + +“Any attempt by you, Obama, to deny Muslims liberty & safety under the Islamic caliphate, will result in the bloodshed of your people,” the ISIS fighter added. + +Foley also speaks in the video, saying: “I call on my friends, family members and loved ones to rise up against my real killers, the U.S. government.” + +Foley vanished in northwest Syria on Thanksgiving Day, November 22, in 2012. + +Before that, he had reported independently from the Middle East for about five years, according to the Free James Foley website. Foley was 40 years old. + +James Foley in the video. (YouTube) + +Journalist James Foley, of Rochester, N.H., responds to questions during an interview with The Associated Press, in Boston, Friday, May 27, 2011. (AP Photo/Steven Senne) + +National Security Council spokeswoman Caitlin Hayden said in the first official U.S. reaction to the video: “We have seen a video that purports to be the murder of U.S. citizen James Foley by ISIS. The intelligence community is working as quickly as possible to determine its authenticity. If genuine, we are appalled by the brutal murder of an innocent American journalist and express our deepest condolences to his family and friends. We will provide more information when it is available.” + +The White House later said that President Barack Obama, on Air Force One, was briefed on the video by Deputy National Security Advisor Ben Rhodes. “The President will continue to receive regular updates,” it said. + +The video was later taken down by YouTube for violation of its policies. + +Foley’s parents told AFP last year that they were still hoping for his safe return. + +But there was little indication where Foley had been until the video appeared on Tuesday. ”We haven’t been contacted by anybody asking for anything. No ransom requests,” father John Foley told AFP at the time. + +“We’re staying very hopeful,” mother Diane Foley said. “We’re hearing many rumors but no facts at this point. We’ve just a very strong feeling that Jim is alive.” + +Foley was one of an estimated dozens of journalists missing in Syria’s civil war. + +ISIS is also known as ISIL, or The Islamic State of Iraq and the Levant. The Council of Foreign Relations says that the group “is a predominantly Sunni jihadist group, seeks to sow civil unrest in Iraq and the Levant (region spanning from southern Turkey to Egypt and including Syria, Lebanon, Israel, the Palestinian territories and Jordan) with the aim of establishing a caliphate — a single, transnational Islamic state based on sharia.” + +It added: “The group emerged in the ashes of the U.S.-led invasion to oust Saddam Hussein as al-Qaida in Iraq (AQI), and the insurgency that followed provided it with fertile ground to wage a guerrilla war against coalition forces and their domestic allies.” + +The group was originally launched by Abu Musab al-Zarqawi, who had commanded volunteers in Afghanistan before fleeing to Iraq in 2001. It was there that he joined militant Kurdish separatist movement Ansar al-Islam, which was the precursor to AQI, and led its Arab contingent. + +Zarqawi later pledged support to Osama bin Laden, although they had a disagreement over the types of attacks they should launch. + +Zarqawi was killed in a U.S. air strike in 2006, at which point Eguptian-born explosives expert Abu Ayyub al-Masti took over. The group is currently led by Abu Bakr al-Baghdadi, also known as Abu Du’a, whi changed the group’s name to Islamic State of Iraq and Sham (ISIS), according to the U.S. State Department, which has a $10 million reward for information that helps authorities kill or capture the group’s leader. + +MORE: + +People Share Photos and Memories of James Foley From Before He Was Captured + +Steven Sotloff: Another Missing American Threatened by ISIS? Worked for TIME Magazine (Photos) + +See an Associated Press story below. + +Syria strikes militants as US targets them in Iraq + +This Sunday, Aug. 17, 2014 photo provided by the anti-government activist group Aleppo Media Center (AMC), which has been authenticated based on its contents and other AP reporting, shows a Free Syrian Army fighter aiming his weapon during a battle with Islamic State militants in Aleppo, Syria. Members of the Islamic State group have been marching in the northern province of Aleppo capturing areas under the control of the mainstream Free Syrian Army. Islamic State fighters have overrun nearly a dozen towns and villages in Aleppo province last week crushing what little resistance they have encountered. (AP Photo/Aleppo Media Center AMC) + +BEIRUT—As the U.S. military strikes the Islamic State group in Iraq, Syrian President Bashar Assad’s forces have significantly stepped up their own campaign against militant strongholds in Syria, carrying out dozens of airstrikes against the group’s headquarters in the past two days. + +While the government in Damascus has long turned a blind eye to the Islamic State’s expansion in Syria — in some cases even facilitating its offensive against mainstream rebels — the group’s rapid march on towns and villages in northern and eastern Syria is now threatening to overturn recent gains by government forces. + +While Islamic State militants have so far concentrated their attacks against the Western-backed fighters seeking to topple Assad, they have in the past month carried out a major onslaught against Syrian army facilities in northeastern Syria, capturing and slaughtering hundreds of Syrian soldiers and pro-government militiamen in the process. + +On Monday, Islamic State fighters were closing in on the last government-held army base in the northeastern Raqqa province, the Tabqa air base, prompting at least 16 Syrian government airstrikes in the area in an attempt to halt their advance. + +In the northern city of Aleppo, there is a sense of impending defeat among mainstream rebels as Islamic militants systematically routed them last week in towns and villages only a few kilometers (miles) north of the city. An Islamic State takeover of rebel-held parts of Aleppo also would be disastrous for Syrian government troops who have been gaining ground in the city in past months. + +“I think they (Syrian government) are finally realizing that their Machiavellian strategy of working with the Islamic State group against the moderates did not work so well, and so they have started to fight it,” said Andrew Tabler, a senior fellow at the Washington Institute for Near East Policy. + +But in hitting hard against the Islamic State group, Assad has another motive. His aerial bombardment of militant strongholds in Syria in a way mirrors that of the U.S. military’s airstrikes against extremists across the border in Iraq. + +Analysts say Assad’s strikes aim at sending a message that he is on the same side as the Americans, reinforcing the Syrian government’s longstanding claim that it is a partner in the fight against terrorism and a counterbalance to extremists. That comes after the U.S. itself nearly bombed Syria after it blamed Assad’s forces for a chemical weapons attack on rebel-held areas near Damascus last August. + +“Assad would surely love to regain international acceptance via a ‘war on terror’ and maybe that is his long-term plan, in so far as he has one,” Syria analyst Aron Lund said. + +Even while going against the Islamic State in Iraq, U.S. officials have shown little appetite for striking at the same militants in Syria. + +Asked about Syrian government airstrikes targeting the militants, State Department Deputy Spokeswoman Marie Harf rejected the notion that Washington and Damascus are “on the same page” in their fight against the Islamic State as a common enemy. + +“While we may be looking at some of the same targets, I think the fact … that the Assad regime has allowed ISIS to flourish and grow in the way it has is really one of the main reasons they have grown so strong,” she said, using one of the acronyms for the Islamic State. + +Most of all, however, Assad can simply no longer afford to ignore the growing threat of the Islamic State now that it has started attacking his own forces. + +Since July, following their blitz in Iraq and after they declared a self-styled caliphate straddling the Iraq-Syria border, Islamic State fighters have methodically gone after isolated government bases in northern and eastern Syria, killing and decapitating army commanders and pro-government militiamen. + +The attacks started with a devastating onslaught on the al-Shaer gas field in Homs province in which more than 270 Syrian soldiers, security guards and workers were killed. Last month, the jihadis overran the sprawling Division 17 military base in Raqqa province, killing at least 85 soldiers. Two weeks later, Islamic State fighters seized the nearby Brigade 93 base after days of heavy fighting. + +They now are closing in on Tabqa air base. Activists on Monday reported intense clashes between government troops and Islamic State fighters on the edge of the villages of Ajil and Khazna near Tabqa. The Raqqa Media Center, an activist collective, said the Islamic State captured four villages near the air base, including Ajil. + +“They will stop at nothing. If things continue the same way it’s only a matter of time before the Islamic State seizes Aleppo,” said Abu Thabet, an Aleppo rebel commander. He said the jihadis were now looking to take the rebel stronghold of Marea, to be followed by the Bab al-Salama border crossing with Turkey, which would be a major prize and source of money. + +Oubai Shahbandar, a Washington-based senior strategist for the Western-backed opposition Syrian National Coalition group, called Assad’s airstrikes against the Islamic States superficial, saying the Western-backed rebels were the only force truly confronting the jihadis. + +He also shrugged off any suggestion that Assad and the West share a common enemy in the Islamic State group. + +“The choice for the West is clear,” he said. “Assad turned Syria into a springboard for terror, while the opposition leads the anti-Islamic State resistance.”","1" +"James Foley: American Journalist James Wright Foley Beheaded in New Terrorist Video [Breaking News]","James Wright Foley, an American journalist kidnapped in 2012, was beheaded in an ISIS video released on Tuesday, August 19. + +The video is titled “A Message to America.” + +A figure in a black robe with a gun strapped on his person and a masked hat covering his face, apart from his eyes, appears in the video next to Foley. + +In the video, the Islamic State says that U.S. President Barack Obama’s authorization of strikes against the group places the United States “upon a slippery slope towards a new war front against Muslims,” according to BNO. + +“Any attempt by you, Obama, to deny Muslims liberty & safety under the Islamic caliphate, will result in the bloodshed of your people,” the ISIS fighter added. + +Foley also speaks in the video, saying: “I call on my friends, family members and loved ones to rise up against my real killers, the U.S. government.” + +Foley vanished in northwest Syria on Thanksgiving Day, November 22, in 2012. + +Before that, he had reported independently from the Middle East for about five years, according to the Free James Foley website. Foley was 40 years old. + +James Foley in the video. (YouTube) + +Journalist James Foley, of Rochester, N.H., responds to questions during an interview with The Associated Press, in Boston, Friday, May 27, 2011. (AP Photo/Steven Senne) + +National Security Council spokeswoman Caitlin Hayden said in the first official U.S. reaction to the video: “We have seen a video that purports to be the murder of U.S. citizen James Foley by ISIS. The intelligence community is working as quickly as possible to determine its authenticity. If genuine, we are appalled by the brutal murder of an innocent American journalist and express our deepest condolences to his family and friends. We will provide more information when it is available.” + +The White House later confirmed that the video was authentic. + +The video was later taken down by YouTube for violation of its policies. + +Foley’s parents told AFP last year that they were still hoping for his safe return. + +But there was little indication where Foley had been until the video appeared on Tuesday. ”We haven’t been contacted by anybody asking for anything. No ransom requests,” father John Foley told AFP at the time. + +“We’re staying very hopeful,” mother Diane Foley said. “We’re hearing many rumors but no facts at this point. We’ve just a very strong feeling that Jim is alive.” + +Foley’s parents also confirmed the death in a statement, saying they “have never been prouder of him.” + +“He gave his life trying to expose the world to the suffering of the Syrian people,” said Diane Foley. She implored the militants to spare the lives of other hostages. “Like Jim, they are innocents. They have no control over American government policy in Iraq, Syria or anywhere in the world.” + +Foley was one of an estimated dozens of journalists missing in Syria’s civil war. + +ISIS is also known as ISIL, or The Islamic State of Iraq and the Levant. The Council of Foreign Relations says that the group “is a predominantly Sunni jihadist group, seeks to sow civil unrest in Iraq and the Levant (region spanning from southern Turkey to Egypt and including Syria, Lebanon, Israel, the Palestinian territories and Jordan) with the aim of establishing a caliphate — a single, transnational Islamic state based on sharia.” + +It added: “The group emerged in the ashes of the U.S.-led invasion to oust Saddam Hussein as al-Qaida in Iraq (AQI), and the insurgency that followed provided it with fertile ground to wage a guerrilla war against coalition forces and their domestic allies.” + +The group was originally launched by Abu Musab al-Zarqawi, who had commanded volunteers in Afghanistan before fleeing to Iraq in 2001. It was there that he joined militant Kurdish separatist movement Ansar al-Islam, which was the precursor to AQI, and led its Arab contingent. + +Zarqawi later pledged support to Osama bin Laden, although they had a disagreement over the types of attacks they should launch. + +Zarqawi was killed in a U.S. air strike in 2006, at which point Eguptian-born explosives expert Abu Ayyub al-Masti took over. The group is currently led by Abu Bakr al-Baghdadi, also known as Abu Du’a, whi changed the group’s name to Islamic State of Iraq and Sham (ISIS), according to the U.S. State Department, which has a $10 million reward for information that helps authorities kill or capture the group’s leader. + +MORE: + +People Share Photos and Memories of James Foley From Before He Was Captured + +Steven Sotloff: Another Missing American Threatened by ISIS? Worked for TIME Magazine (Photos) + +See Associated Press stories below. + +American journalist killed in Syria aware of risks + +A ribbon is tied to a tree outside the home of American freelance journalist James Foley, on Tuesday Aug. 19, 2014, in Rochester, N.H. (AP Photo/Jim Cole) + +ROCHESTER, N.H.—Journalist James Foley had worked in a number of conflict zones in the Middle East, but the danger didn’t stop him from doing the job he loved. + +Captured and held for six weeks while covering the uprising in Libya, he knew the risks when he went to Syria two years ago to cover the escalating violence there. + +Foley was snatched again in Syria in November 2012 when the car he was riding in was stopped by four militants in a battle zone that Sunni rebel fighters and government forces were trying to control. + +Foley’s family confirmed his death on a webpage created to rally support for him. His mother, Diane Foley, said in a statement on the webpage he “gave his life trying to expose the world to the suffering of the Syrian people.” + +At Foley’s family home in Rochester, a light burned yellow in a center upstairs window and a yellow ribbon adorned a tree at the foot of the driveway. The Rev. Paul Gousse, of Our Lady of the Holy Rosary, where the Foleys are parishioners, spent about 45 minutes at the house but left without commenting. + +Foley, 40, and another journalist were working in the northern province of Idlib in Syria when they were kidnapped near the village of Taftanaz. + +After Foley disappeared, while contributing video for Agence France-Presse and the media company GlobalPost, his parents became fierce advocates for him and all those kidnapped in war zones. They held regular prayer vigils and worked with the U.S. and Syrian diplomatic corps to get whatever scraps of information they could. + +Diane Foley, asked in January 2013 if her son had reservations about going to Syria, said softly: “Not enough.” + +She wrote Tuesday on the family’s webpage, “We thank Jim for all the joy he gave us. He was an extraordinary son, brother, journalist and person.” + +Foley had seen the dangers to journalists up close. + +Upon his release from Libya and return to the United States, he recalled in an interview with The Associated Press seeing a colleague, South African photographer Anton Hammerl, killed by forces loyal to Libyan leader Moammar Gadhafi. He tried to pull his friend’s body out of harm’s way but was turned back by heavy fire. + +“I’ll regret that day for the rest of my life. I’ll regret what happened to Anton,” Foley said. “I will constantly analyze that.” + +Foley also covered the war in Afghanistan but called the Libyan fighting the worst he had ever experienced to that point. + +Foley grew up in New Hampshire and studied history at Marquette University. He later taught in Arizona, Massachusetts and Chicago before switching careers to become a journalist, which he viewed as a calling. + +“Journalism is journalism,” Foley said. “If I had a choice to do Nashua (New Hampshire) zoning meetings or give up journalism, I’ll do it. I love writing and reporting.” + +British fighter appears to have role in beheading + +This September 2012 file photo posted on the website freejamesfoley.org shows journalist James Foley in Aleppo, Syria. (AP Photo/freejamesfoley.org, Manu Brabo, File) + +LONDON—The black-clad Islamic militant fighter filmed in the beheading of American journalist James Foley appears to be British, the U.K. foreign minister said Wednesday — a development that underscores the insurgents’ increasingly sophisticated use of Western fighters to mobilize recruits and terrorize enemies. + +Foreign Secretary Philip Hammond said the man in the video with Foley ”appears to have been a British person.” + +The masked militant in the clip speaks fluent English with what Lancaster University linguist Claire Hardaker said sounds like a London accent. + +Hammond told the BBC that Britain was aware that U.K. nationals were involved in committing atrocities with Islamic State extremists and other organizations. + +Hammond says the possible involvement of a Briton underscored the risks that those now fighting with Islamic militants could return to Britain and carry out attacks at home. + +British officials have said that several hundred people from Britain have traveled to Syria to join the battle against President Bashar Assad, and some may have crossed into Iraq as part of the rapid advance of the Islamic State group. French and German officials have recently put the combined total of those countries around 1,300. + +Shiraz Maher of the International Center for the Study of Radicalization at King’s College London, said the video was evidence that British jihadis were “some of the most vicious and vociferous fighters” in Syria and Iraq. + +“Unfortunately the British participation in the conflicts now raging in both Syria and Iraq has been has been one of full participation, one that has seen them at the front lines, taking part in the conflict in every way,” Maher told BBC radio. “So we have seen British fighters out there operating as suicide bombers, we have seen them operating as executioners.” + +The group has previously used Western fighters in its recruitment videos. In June, it released a video showing British and Australian militants exhorting compatriots to join them in violent jihad. + +Nigel Inkster, a terrorism expert at the International Institute for Strategic Studies, said the videos reflected an increasingly sophisticated media strategy designed to energize recruits and deliver to Western governments and citizens a message “of fear and a perception of inevitability.”","1" +"James Foley: American Journalist James Wright Foley Beheaded in New ISIS Terrorist Video [Breaking News]","James Wright Foley, an American journalist kidnapped in 2012, was beheaded in an ISIS video released on Tuesday, August 19. + +The video is titled “A Message to America.” + +A figure in a black robe with a gun strapped on his person and a masked hat covering his face, apart from his eyes, appears in the video next to Foley. + +In the video, the Islamic State says that U.S. President Barack Obama’s authorization of strikes against the group places the United States “upon a slippery slope towards a new war front against Muslims,” according to BNO. + +“Any attempt by you, Obama, to deny Muslims liberty & safety under the Islamic caliphate, will result in the bloodshed of your people,” the ISIS fighter added. + +Foley also speaks in the video, saying: “I call on my friends, family members and loved ones to rise up against my real killers, the U.S. government.” + +Foley vanished in northwest Syria on Thanksgiving Day, November 22, in 2012. + +Before that, he had reported independently from the Middle East for about five years, according to the Free James Foley website. Foley was 40 years old. + +James Foley in the video. (YouTube) + +Journalist James Foley, of Rochester, N.H., responds to questions during an interview with The Associated Press, in Boston, Friday, May 27, 2011. (AP Photo/Steven Senne) + +National Security Council spokeswoman Caitlin Hayden said in the first official U.S. reaction to the video: “We have seen a video that purports to be the murder of U.S. citizen James Foley by ISIS. The intelligence community is working as quickly as possible to determine its authenticity. If genuine, we are appalled by the brutal murder of an innocent American journalist and express our deepest condolences to his family and friends. We will provide more information when it is available.” + +The White House later confirmed that the video was authentic. + +Foley’s parents also confirmed the death in a statement, saying they “have never been prouder of him.” + +“He gave his life trying to expose the world to the suffering of the Syrian people,” said Diane Foley. She implored the militants to spare the lives of other hostages. “Like Jim, they are innocents. They have no control over American government policy in Iraq, Syria or anywhere in the world.” + +The video was later taken down by YouTube for violation of its policies. + +Foley’s parents told AFP last year that they were still hoping for his safe return. + +But there was little indication where Foley had been until the video appeared on Tuesday. ”We haven’t been contacted by anybody asking for anything. No ransom requests,” father John Foley told AFP at the time. + +“We’re staying very hopeful,” mother Diane Foley said. “We’re hearing many rumors but no facts at this point. We’ve just a very strong feeling that Jim is alive.” + +Foley was one of an estimated dozens of journalists missing in Syria’s civil war. + +ISIS is also known as ISIL, or The Islamic State of Iraq and the Levant. The Council of Foreign Relations says that the group “is a predominantly Sunni jihadist group, seeks to sow civil unrest in Iraq and the Levant (region spanning from southern Turkey to Egypt and including Syria, Lebanon, Israel, the Palestinian territories and Jordan) with the aim of establishing a caliphate — a single, transnational Islamic state based on sharia.” + +It added: “The group emerged in the ashes of the U.S.-led invasion to oust Saddam Hussein as al-Qaida in Iraq (AQI), and the insurgency that followed provided it with fertile ground to wage a guerrilla war against coalition forces and their domestic allies.” + +The group was originally launched by Abu Musab al-Zarqawi, who had commanded volunteers in Afghanistan before fleeing to Iraq in 2001. It was there that he joined militant Kurdish separatist movement Ansar al-Islam, which was the precursor to AQI, and led its Arab contingent. + +Zarqawi later pledged support to Osama bin Laden, although they had a disagreement over the types of attacks they should launch. + +Zarqawi was killed in a U.S. air strike in 2006, at which point Eguptian-born explosives expert Abu Ayyub al-Masti took over. The group is currently led by Abu Bakr al-Baghdadi, also known as Abu Du’a, who changed the group’s name to Islamic State of Iraq and Sham (ISIS), according to the U.S. State Department, which has a $10 million reward for information that helps authorities kill or capture the group’s leader. + +MORE: + +People Share Photos and Memories of James Foley From Before He Was Captured + +Steven Sotloff: Another Missing American Threatened by ISIS? Worked for TIME Magazine (Photos) + +See Associated Press stories below. + +American journalist killed in Syria aware of risks + +A ribbon is tied to a tree outside the home of American freelance journalist James Foley, on Tuesday Aug. 19, 2014, in Rochester, N.H. (AP Photo/Jim Cole) + +ROCHESTER, N.H.—Journalist James Foley had worked in a number of conflict zones in the Middle East, but the danger didn’t stop him from doing the job he loved. + +Captured and held for six weeks while covering the uprising in Libya, he knew the risks when he went to Syria two years ago to cover the escalating violence there. + +Foley was snatched again in Syria in November 2012 when the car he was riding in was stopped by four militants in a battle zone that Sunni rebel fighters and government forces were trying to control. + +Foley’s family confirmed his death on a webpage created to rally support for him. His mother, Diane Foley, said in a statement on the webpage he “gave his life trying to expose the world to the suffering of the Syrian people.” + +At Foley’s family home in Rochester, a light burned yellow in a center upstairs window and a yellow ribbon adorned a tree at the foot of the driveway. The Rev. Paul Gousse, of Our Lady of the Holy Rosary, where the Foleys are parishioners, spent about 45 minutes at the house but left without commenting. + +Foley, 40, and another journalist were working in the northern province of Idlib in Syria when they were kidnapped near the village of Taftanaz. + +After Foley disappeared, while contributing video for Agence France-Presse and the media company GlobalPost, his parents became fierce advocates for him and all those kidnapped in war zones. They held regular prayer vigils and worked with the U.S. and Syrian diplomatic corps to get whatever scraps of information they could. + +Diane Foley, asked in January 2013 if her son had reservations about going to Syria, said softly: “Not enough.” + +She wrote Tuesday on the family’s webpage, “We thank Jim for all the joy he gave us. He was an extraordinary son, brother, journalist and person.” + +Foley had seen the dangers to journalists up close. + +Upon his release from Libya and return to the United States, he recalled in an interview with The Associated Press seeing a colleague, South African photographer Anton Hammerl, killed by forces loyal to Libyan leader Moammar Gadhafi. He tried to pull his friend’s body out of harm’s way but was turned back by heavy fire. + +“I’ll regret that day for the rest of my life. I’ll regret what happened to Anton,” Foley said. “I will constantly analyze that.” + +Foley also covered the war in Afghanistan but called the Libyan fighting the worst he had ever experienced to that point. + +Foley grew up in New Hampshire and studied history at Marquette University. He later taught in Arizona, Massachusetts and Chicago before switching careers to become a journalist, which he viewed as a calling. + +“Journalism is journalism,” Foley said. “If I had a choice to do Nashua (New Hampshire) zoning meetings or give up journalism, I’ll do it. I love writing and reporting.” + +British fighter appears to have role in beheading + +This September 2012 file photo posted on the website freejamesfoley.org shows journalist James Foley in Aleppo, Syria. (AP Photo/freejamesfoley.org, Manu Brabo, File) + +LONDON—The black-clad Islamic militant fighter filmed in the beheading of American journalist James Foley appears to be British, the U.K. foreign minister said Wednesday — a development that underscores the insurgents’ increasingly sophisticated use of Western fighters to mobilize recruits and terrorize enemies. + +Foreign Secretary Philip Hammond said the man in the video with Foley ”appears to have been a British person.” + +The masked militant in the clip speaks fluent English with what Lancaster University linguist Claire Hardaker said sounds like a London accent. + +Hammond told the BBC that Britain was aware that U.K. nationals were involved in committing atrocities with Islamic State extremists and other organizations. + +Hammond says the possible involvement of a Briton underscored the risks that those now fighting with Islamic militants could return to Britain and carry out attacks at home. + +British officials have said that several hundred people from Britain have traveled to Syria to join the battle against President Bashar Assad, and some may have crossed into Iraq as part of the rapid advance of the Islamic State group. French and German officials have recently put the combined total of those countries around 1,300. + +Shiraz Maher of the International Center for the Study of Radicalization at King’s College London, said the video was evidence that British jihadis were “some of the most vicious and vociferous fighters” in Syria and Iraq. + +“Unfortunately the British participation in the conflicts now raging in both Syria and Iraq has been has been one of full participation, one that has seen them at the front lines, taking part in the conflict in every way,” Maher told BBC radio. “So we have seen British fighters out there operating as suicide bombers, we have seen them operating as executioners.” + +The group has previously used Western fighters in its recruitment videos. In June, it released a video showing British and Australian militants exhorting compatriots to join them in violent jihad. + +Nigel Inkster, a terrorism expert at the International Institute for Strategic Studies, said the videos reflected an increasingly sophisticated media strategy designed to energize recruits and deliver to Western governments and citizens a message “of fear and a perception of inevitability.”","1" +"ISIL video claims beheading of kidnapped journalist James Foley","Islamic State insurgents released a video on Tuesday purportedly showing the beheading of U.S. journalist James Foley, who had gone missing in Syria nearly two years ago, and images of another American journalist whose life they said depended on U.S. action in Iraq. + +The video, titled “A Message To America,” was posted on social-media websites. It was not immediately possible to verify its authenticity. + +Mr. Foley, who has reported in the Middle East for five years, was kidnapped on Nov. 22, 2012, by unidentified gunmen. Steven Sotloff, who appeared at the end of the video, went missing in northern Syria while he was reporting in July, 2013. + +A Twitter account set up by Mr. Foley’s family to help find him said early on Wednesday: “We know that many of you are looking for confirmation or answers. Please be patient until we all have more information, and keep the Foleys in your thoughts and prayers.” + +The White House said that U.S. intelligence agents were working to verify the authenticity of the video. + +Islamic State, an al-Qaeda offshoot, had not previously executed American citizens publicly. The Sunni militant group has declared a caliphate in parts of Iraq and Syria in areas it controls. + +The video, which was posted after the United States resumed air strikes in Iraq for the first time since the end of the U.S. occupation in 2011, opened with a clip of U.S. President Barack Obama saying he had authorized strikes in Iraq. + +“Obama authorizes military operations against the Islamic State effectively placing America upon a slippery slope toward a new war front against Muslims,” words appear in English and Arabic on the screen. + +It showed black-and-white aerial footage of air strikes with text saying “American aggression against the Islamic State” + +A person identified as James Foley and wearing an orange outfit is seen kneeling in the desert as a man in black dress with a black mask stands beside him, holding a knife. + +“I call on my friends, family and loved ones to rise up against my real killers, the U.S. government, for what will happen to me is only a result of their complacency and criminality,” the kneeling man says. + +The man in the mask speaks in a British accent and says: “This is James Wright Foley, an American citizen, of your country. As a government, you have been at the forefront of the aggression toward the Islamic State. + +“Today your military air force is attacking us daily in Iraq. Your strikes have caused casualties amongst Muslims. You are no longer fighting an insurgency. We are an Islamic army, and a state that has been accepted by a large number of Muslims worldwide.” + +Following his statement, he beheads the kneeling man. + +At the end of the video, words on the side of the screen say “Steven Joel Sotloff” as another prisoner in an orange jumpsuit is shown on screen. + +“The life of this American citizen, Obama, depends on your next decision,” the masked man says. + +Mr. Foley, a freelance reporter, had been covering Syria’s civil war for GlobalPost. In 2011, he was held for 45 days by forces loyal to former Libyan leader Moammar Gadhafi. + +Mr. Sotloff is also a freelancer journalist with published stories in Time Magazine and Foreign Policy. He has worked in Syria, Libya and Yemen. + +Islamic State has executed hundreds of people in Syria and Iraq during its advance. Its members follow a hard-line interpretation of Sunni Islam but target all those who oppose it, including Sunni Muslims. + +The Syrian Observatory for Human Rights, a monitoring group, said Islamic State militants had executed 700 members of a Sunni tribe in eastern Syria in two weeks, the majority of them civilians. + +“We have seen a video that purports to be the murder of U.S. citizen James Foley by ISIL,” White House spokeswoman Caitlin Hayden said, referring to the militant group by an earlier name, the Islamic State of Iraq and the Levant. + +“If genuine, we are appalled by the brutal murder of an innocent American journalist, and we express our deepest condolences to his family and friends.” + +Islamic State also released another video on Tuesday that gave the strongest indication yet it might attempt to strike American targets. + +The video with the theme “breaking of the American cross” boasts Islamic State will emerge victorious over “crusader” America. + +It follows a video posted on Monday, warning of attacks on American targets if Washington struck against its fighters in Iraq and Syria. + +The latest footage spoke of a holy war between Islamic State and the United States, which occupied Iraq for nearly a decade and faced stiff resistance from al-Qaeda. + +Unlike al-Qaeda, Islamic State has so far focused on territorial gains designed to eventually establish a full-blown Islamist empire.","1" +"The Globe and Mail","Islamic State insurgents released a video on Tuesday purportedly showing the beheading of U.S. journalist James Foley, who had gone missing in Syria nearly two years ago, and images of another American journalist whose life they said depended on U.S. action in Iraq. + +The video, titled “A Message To America,” was posted on social-media websites. It was not immediately possible to verify its authenticity. + +Mr. Foley, who has reported in the Middle East for five years, was kidnapped on Nov. 22, 2012, by unidentified gunmen. Steven Sotloff, who appeared at the end of the video, went missing in northern Syria while he was reporting in July, 2013. + +A Twitter account set up by Mr. Foley’s family to help find him said early on Wednesday: “We know that many of you are looking for confirmation or answers. Please be patient until we all have more information, and keep the Foleys in your thoughts and prayers.” + +The White House said that U.S. intelligence agents were working to verify the authenticity of the video. + +Islamic State, an al-Qaeda offshoot, had not previously executed American citizens publicly. The Sunni militant group has declared a caliphate in parts of Iraq and Syria in areas it controls. + +The video, which was posted after the United States resumed air strikes in Iraq for the first time since the end of the U.S. occupation in 2011, opened with a clip of U.S. President Barack Obama saying he had authorized strikes in Iraq. + +“Obama authorizes military operations against the Islamic State effectively placing America upon a slippery slope toward a new war front against Muslims,” words appear in English and Arabic on the screen. + +It showed black-and-white aerial footage of air strikes with text saying “American aggression against the Islamic State” + +A person identified as James Foley and wearing an orange outfit is seen kneeling in the desert as a man in black dress with a black mask stands beside him, holding a knife. + +“I call on my friends, family and loved ones to rise up against my real killers, the U.S. government, for what will happen to me is only a result of their complacency and criminality,” the kneeling man says. + +The man in the mask speaks in a British accent and says: “This is James Wright Foley, an American citizen, of your country. As a government, you have been at the forefront of the aggression toward the Islamic State. + +“Today your military air force is attacking us daily in Iraq. Your strikes have caused casualties amongst Muslims. You are no longer fighting an insurgency. We are an Islamic army, and a state that has been accepted by a large number of Muslims worldwide.” + +Following his statement, he beheads the kneeling man. + +At the end of the video, words on the side of the screen say “Steven Joel Sotloff” as another prisoner in an orange jumpsuit is shown on screen. + +“The life of this American citizen, Obama, depends on your next decision,” the masked man says. + +Mr. Foley, a freelance reporter, had been covering Syria’s civil war for GlobalPost. In 2011, he was held for 45 days by forces loyal to former Libyan leader Moammar Gadhafi. + +Mr. Sotloff is also a freelancer journalist with published stories in Time Magazine and Foreign Policy. He has worked in Syria, Libya and Yemen. + +Islamic State has executed hundreds of people in Syria and Iraq during its advance. Its members follow a hard-line interpretation of Sunni Islam but target all those who oppose it, including Sunni Muslims. + +The Syrian Observatory for Human Rights, a monitoring group, said Islamic State militants had executed 700 members of a Sunni tribe in eastern Syria in two weeks, the majority of them civilians. + +“We have seen a video that purports to be the murder of U.S. citizen James Foley by ISIL,” White House spokeswoman Caitlin Hayden said, referring to the militant group by an earlier name, the Islamic State of Iraq and the Levant. + +“If genuine, we are appalled by the brutal murder of an innocent American journalist, and we express our deepest condolences to his family and friends.” + +Islamic State also released another video on Tuesday that gave the strongest indication yet it might attempt to strike American targets. + +The video with the theme “breaking of the American cross” boasts Islamic State will emerge victorious over “crusader” America. + +It follows a video posted on Monday, warning of attacks on American targets if Washington struck against its fighters in Iraq and Syria. + +The latest footage spoke of a holy war between Islamic State and the United States, which occupied Iraq for nearly a decade and faced stiff resistance from al-Qaeda. + +Unlike al-Qaeda, Islamic State has so far focused on territorial gains designed to eventually establish a full-blown Islamist empire.","1" +"Isis militants claim to have killed US journalist James Foley","Militants from Islamic State (Isis) claimed to have killed an American journalist long held captive in Syria in retaliation for ongoing US airstrikes against its forces in Iraq. + +A propaganda video circulated on Tuesday showed a masked Isis fighter beheading a kneeling man dressed in an orange jumpsuit who is purported to be James Wright Foley, a photojournalist who went missing in Syria in 2012. + +The masked executioner spoke in English, with what sounded like a British accent, and said that the slaying came in response to the airstrikes ordered by President Barack Obama against Isis 12 days ago. + +Isis, whose chief spokesman came under State Department sanctions on Monday, warned of further revenge – including on another man purported to be a captured US journalist, Steven Sotloff – and in the video, the victim was made to read a statement blaming the US for his own murder. + +Foley has been missing in Syria since November 2012, where he went to report on the bloody struggle to overthrow dictator Bashar al-Assad. He was initially thought to have been captured by forces loyal to the Assad regime. + +A Facebook message from a support group, Free James Foley, urged patience “until we all have more information,” and asked that readers “keep the Foleys in your thoughts and prayers.” + +YouTube took down the gruesome video, but not before it sparked a debate on social media about the ethics of sharing it, adding a metatextual debate to a depiction of a man’s violent death. + +Foley, 40, a former Stars and Stripes reporter, was captured in November 2012 near the Syrian town of Taftanaz. It was not his first detention while reporting: in 2011, he was taken while reporting on the uprising against Libyan dictator Muammar Gaddafi. Gaddafi’s forces ultimately released him after six weeks in captivity. + +A friend of Foley’s and his fellow captive in Libya, journalist Clare Morgana Gillis, wrote in a 2013 essay that captivity was “the state most violently opposite his nature.” Gillis described Foley as gentle, friendly, courageous and impatient with “anything that slows his forward momentum.” + +In a January 2013 interview with local television news near her Rochester, New Hampshire home, Foley’s mother Diane said her son was “passionate about covering the story in Syria, passionate about the people there.” + +Caitlin Hayden, the spokeswoman for the National Security Council, said US intelligence was working to determine the authenticity of the video. + +“If genuine, we are appalled by the brutal murder of an innocent American journalist and we express our deepest condolences to his family and friends,” Hayden said in a statement. + +Messages left with the Foley family were not returned. + +A day after Obama declared that Iraqi and Kurdish forces backed by US warplanes had broken Isis’ hold on the critical Mosul Dam, US Central Command announced two strikes near it on Monday, to “further expand control of the area.” One strike was said to have destroyed an Isis checkpoint while the other was “not successful.” + +Obama has offered no timeframe for the length of his campaign against Isis. The US military has bombed over 90 targets attributed to Isis, including vehicle convoys, mobile artillery and fixed positions, since 8 August. Most of the strikes have come in the past few days, near the dam. The other strikes have occurred either to blunt an Isis advance on the Kurdish regional capital of Irbil or to lift an Isis siege on Mount Sinjar, where it chased thousands of Iraqi Yazidis whom it threatened to kill unless they converted to Islam. The US considers the siege broken.","1" +"Islamic State militants claim to have killed US journalist James Foley","Militants from Islamic State (Isis) claimed to have killed an American journalist long held captive in Syria in retaliation for ongoing US air strikes against its forces in Iraq. + +A propaganda video circulated on Tuesday showed a masked Isis fighter beheading a kneeling man dressed in an orange jumpsuit who is purported to be James Wright Foley, a photojournalist who went missing in Syria in 2012. + +The masked executioner spoke in English, with what sounded like a British accent, and said the slaying came in response to the air strikes ordered by President Barack Obama against Isis 12 days ago. + +Isis, whose chief spokesman came under US state department sanctions on Monday, warned of further revenge – including on another man purported to be a captured US journalist, Steven Sotloff – and in the video the victim was made to read a statement blaming the US for his own murder. + +Foley has been missing in Syria since November 2012, where he went to report on the bloody struggle to overthrow dictator Bashar al-Assad. He was initially thought to have been captured by forces loyal to the Assad regime. + +Foley’s mother later released a statement saying her son gave his life to expose the suffering of the Syrian people. Diane Foley asked his kidnappers to release their other captives. + +“He was an extraordinary son, brother, journalist and person,” she said. + +“We implore the kidnappers to spare the lives of the remaining hostages. Like Jim, they are innocents. They have no control over American government policy in Iraq, Syria or anywhere in the world. + +“We have never been prouder of our son Jim. He gave his life trying to expose the world to the suffering of the Syrian people.” + +YouTube took down the gruesome video, but not before it sparked a debate on social media about the ethics of sharing it. + +Philip Hammond, the British foreign secretary, said the video appeared to be genuine, and that the killer could well be a Briton. + +He said that although further analysis would need to be carried out, the man “on the face of it appears to have been a British person” and that this would not be surprising given the “significant number” of Britons fighting with Isis in Syria and Iraq. + +Foley, 40, a former Stars and Stripes reporter, was captured in November 2012 near the Syrian town of Taftanaz. It was not his first detention while reporting: in 2011, he was taken while reporting on the uprising against Libyan dictator Muammar Gaddafi. Gaddafi’s forces ultimately released him after six weeks in captivity. + +A friend of Foley’s and his fellow captive in Libya, journalist Clare Morgana Gillis, wrote in a 2013 essay that captivity was “the state most violently opposite his nature.” Gillis described Foley as gentle, friendly, courageous and impatient with “anything that slows his forward momentum.” + +In a January 2013 interview with local television news near her Rochester, New Hampshire home, Foley’s mother Diane said her son was “passionate about covering the story in Syria, passionate about the people there.” + +Caitlin Hayden, the spokeswoman for the National Security Council, said US intelligence was working to determine the authenticity of the video. + +“If genuine, we are appalled by the brutal murder of an innocent American journalist and we express our deepest condolences to his family and friends,” Hayden said in a statement. + +A day after Obama declared that Iraqi and Kurdish forces backed by US warplanes had broken Isis’ hold on the critical Mosul Dam, US Central Command announced two strikes near it on Monday, to “further expand control of the area.” One strike was said to have destroyed an Isis checkpoint while the other was “not successful.” + +Obama has offered no timeframe for the length of his campaign against Isis. The US military has bombed over 90 targets attributed to Isis, including vehicle convoys, mobile artillery and fixed positions, since 8 August. Most of the strikes have come in the past few days, near the dam. The other strikes have occurred either to blunt an Isis advance on the Kurdish regional capital of Irbil or to lift an Isis siege on Mount Sinjar, where it chased thousands of Iraqi Yazidis whom it threatened to kill unless they converted to Islam. The US considers the siege broken.","1" +"Obama: murder of James Foley 'shocks the conscience of the entire world'","President Barack Obama denounced Islamic State (Isis) militants for murdering an American journalist in retaliation for US air strikes in Iraq, showing an anger he has rarely displayed in remarks about the Iraq conflict. + +“No just god would stand for what they did yesterday and every single day,” Obama said Wednesday in brief remarks from Edgerton, Massachusetts, where he is vacationing. + +Hours after US intelligence authenticated a gruesome Isis videotape showing the execution of captive journalist James Foley, an act committed with the goal of deterring future US strikes on Isis, Obama said that Isis “has no place in the 21st century,” and called on allies to help defeat a “cancer so it does not spread.” + +Obama did not announce any intensification of his bombing campaign, now in its thirteenth day. US Central Command has yet to announce any new strikes since the Tuesday appearance of the social-media-borne Foley video, although sporadic reports from Iraq have indicated some may have taken place Wednesday. + +An emotional Obama ran through a litany of Isis human-rights abuses, from rape to enslavement, calling them “cowardly acts of violence.” In a vague reference to Americans held captive by Isis or near its path in Iraq, Obama said the US would “do everything we can to protect our people,” a formulation that has preceded US military action in the past. + +With the death of the first American in Iraq since the US military withdrew in 2011, pressure is mounting on Obama to expand his already growing and amorphous air war against Isis. + +The stated purpose of nearly two weeks of bombing has moved from the rescue of mostly Yazidi Iraqi civilians at risk of genocide to providing air cover for Kurdish and Iraqi forces wresting the strategically vital Mosul Dam away from Isis. Aides to Obama pointed out from the start that threats to critical infrastructure would likely prompt a US reprisal. + +Buffeted between calls to destroy Isis and criticism of their shifting rationale, Obama and the Pentagon have strenuously objected to a charge of mission creep. They point out the consistency of the goals Obama has articulated since 8 August: preventing humanitarian catastrophe and protecting US personnel in Iraq. + +Yet both are broad enough to encompass aerial protection of Iraqi Kurdistan and the destruction of Isis vehicles, artillery and fixed positions from Mount Sinjar to the Mosul Dam. The murder of Foley – delivered after he gave a statement at knifepoint blaming the US for his death – and Isis’s threat to kill another American journalist, Steven Sotloff, is also testing Obama’s goal of safeguarding US nationals in a country overrun by Isis. + +National Security Council spokeswoman Caitlin Hayden said Wednesday that the video showed both Foley and Sotloff. + +Leaders from the UK, France and other countries lined up to excoriate Isis for the slaying. British prime minister David Cameron called it “shocking” and cut short his summer holiday to chair meetings on a response. A particularly acute concern for the UK government is the British accent heard from Foley’s masked killer. US intelligence believes hundreds of westerners, including Americans, have joined Isis. + +In the UK, Scotland Yard’s counter-terrorism command, SO15, launched an investigation into the video as leading linguistics experts said the man sounded like he was from London or the south-east of England. + +The British foreign secretary, Philip Hammond, said of the video: “All the hallmarks point to it being genuine. We’re very concerned by the apparent fact that the murderer in question is British and we are urgently investigating – agencies on both sides of the Atlantic – are first of all looking to authenticate the video, to make sure that it is genuine, and sadly it appears to be, and then to see if we can identify the individual in question.” + +A spokesman for German chancellor Angela Merkel called Foley’s murder barbaric. Laurent Fabius, the French foreign minister, said it exposed Isis as the “caliphate of barbarism”. French president Francois Hollande told Le Monde that a global effort “beyond the traditional debate of intervention or non-intervention” was necessary to confront Isis, and proposed an international meeting next month. + +With a brutality so severe it prompted al-Qaida to divorce it from the terrorist franchise, Isis has fulfilled a jihadist aspiration to carve out a state. It flies a flag, sets up internal police to govern its subjects’ adherence to its interpretation of Islamic laws and customs, and maintains financial viability through the control of seized oil assets. While other jihadist entities employ terrorist and insurgent tactics, for which infiltration of another’s populace is central, Isis has mustered a highly mobile army that seizes and holds territory. + +Foley’s killer emphasized in a propaganda video that Isis is a state, not a terrorist group, a distinction that is fundamental to the group’s prestige. On Wednesday, Obama repeatedly called Isis “terrorists.” + +The Committee to Protect Journalists said the murder of Foley, 40, who went missing during a reporting trip to Syria in 2012, “sickens all decent people”. + +“Foley went to Syria to show the plight of the Syrian people, to bear witness to their fight, and in so doing to fight for press freedom,” Sandra Mims Rowe, the group’s chair, said in a statement. + +In a Facebook message attributed to her, Foley’s mother Diane said: “We have never been prouder of our son Jim. He gave his life trying to expose the world to the suffering of the Syrian people.” She also asked the media and the public to respect her family’s privacy. + +Obama hailed Foley, who he called Jim, and said he had called Foley’s parents. + +Foley’s murder, Obama said, was “an act of violence that shocks the conscience of the entire world.”","1" +"ISIL Claims to Behead an American Photojournalist","A video posted by ISIL terrorists on Tuesday purported to the show the beheading of an American photojournalist who has been missing since 2012. The group claims the beheading is a message to President Obama to end the American intervention in Iraq. The incident is reminiscent of the murder of journalist Daniel Pearl in 2002. Pearl was a reporter for the Wall Street Journal, taken hostage and killed by Al-Qaeda. + +James Foley was a photojournalist who has worked for a variety of news organizations. He was working for GlobalPost when he went missing while covering the conflict in Syria in 2012. His disappearance was ruled a kidnapping by the FBI. Before Foley was killed, he was forced to give an anti-American speech. + +In the video, the group also shows journalist Steven Joel Soltoff, a journalist who worked for Time, The National Interest, and Media Line. He last tweeted on August 3, 2013. Soltoff went missing on August 4, 2013 outside of Aleppo, Syria. His family was aware of the situation and was advised not to publicize the information for his safety. He was held in Raqqa. + +This new information may indicate that Foley was detained by the Syrian government alongside Soltoff in 2013. GlobalPost's CEO Phil Balboni gave this comment in May 2013 to NPR, ""Jim [Foley] is now being held by the Syrian government in a detention facility in the Damascus area. We further believe that the facility is under the control of the Syrian air force intelligence service. Based on what we have learned it is likely that Jim is being held with one or more Western journalists, including most likely at least one other American journalist."" At that time, Balboni would not disclose the name, or names, of the ""other American journalist"" citing a ""sensitive and complex"" situation. If this is the case, it is unclear how Foley and Soltoff changed hands from the Syrian government to ISIL. + +ISIL claims that Sotloff’s life “depends on Obama’s next decision,"" specifically if the United States continues attacking them in Iraq. + +(Note: Just after 6 p.m., @zaidbenjamin was suspended from Twitter. Benjamin was the first prominent Twitter account to share images of Foley's death (the image of Foley after the beheading was censored by Benjamin.) At 6:30 p.m., his account was reactivated. ) + +The location at which the beheading took place is unknown. Zaid Benjamin, Radio Sawa's Washington Correspondent, has speculated that the executioner's (pictured left) accent indicates he is North African, rather than Iraqi or Syrian. Richard Venalls, a journalist with the Press Association, believes the accent is British, specifically from the South East/Greater London area. Michael Weiss of Interpret Mag also pegged the accent as British. + +The video of the beheading was posted on ISIL's go-to media outlet, AlFurqan Media and on YouTube. It was quickly removed from YouTube as ""a violation of YouTube's policy on violence."" The video remains on AlFurqan. The site been loading extremely slowly as users watch the tragic incident. It was uploaded to YouTube using RapidLeech, which allows users to download files from blocked websites and upload them elsewhere. + +Remembering James Foley + +Almost immediately, tributes began pouring in from Foley's friends and colleagues: + + + +The response + +The White House is working to confirm the authenticity of the video, as there are often questions about the validity of these execution videos, and some observers have noted suspicious edits to this video. A U.S. official anonymously told the Associated Press they believe it is, in fact, Foley in the video. White House National Security Council spokesperson Caitlin Hayden issued this statement to reporters around 6:15 p.m.: + +We have seen a video that purports to be the murder of U.S. citizen James Foley by ISIL. The intelligence community is working as quickly as possible to determine its authenticity. If genuine, we are appalled by the brutal murder of an innocent American journalist and we express our deepest condolences to his family and friends. We will provide more information when it is available."" + +Free James Foley, an organization dedicated to finding him, offered this statement: + +We know that many of you are looking for confirmation or answers. Please be patient until we all have more information, and keep the Foleys in your thoughts and prayers."" + + +Foley Family via @flyoverangel. +Diane Foley, his mother, posted this statement on the 'Free James Foley' Facebook: + +We have never been prouder of our son Jim. He gave his life trying to expose the world to the suffering of the Syrian people. + +We implore the kidnappers to spare the lives of the remaining hostages. Like Jim, they are innocents. They have no control over American government policy in Iraq, Syria or anywhere in the world. + +We thank Jim for all the joy he gave us. He was an extraordinary son, brother, journalist and person. Please respect our privacy in the days ahead as we mourn and cherish Jim.","1" +"Islamic State claims it executed American photojournalist James Foley","The Islamic State militant group claimed Tuesday to have beheaded an American photojournalist in retaliation for U.S. airstrikes in Iraq. + +A video posted on YouTube, later removed, purported to show the execution of James Foley after he recited a statement in which he called the U.S. government “my real killers.” A second prisoner, said to be Steven Joel Sotloff, like Foley an American journalist who disappeared while covering Syria’s civil war, then appears in the video. + +The masked executioner, speaking in English with what sounds like a British accent, identifies Sotloff and says that “the life of this American citizen, Obama, depends on your next decision.” + +U.S. intelligence officials said they were still evaluating the video and could not immediately authenticate it. + +A White House statement said, “We have seen a video that purports to be the murder of U.S. citizen James Foley by ISIL,” one of several acronyms associated with the militants. + +“The intelligence community is working as quickly as possible to determine its authenticity,” said the statement by National Security Council spokeswoman Caitlin Hayden. “If genuine, we are appalled by the brutal murder of an innocent American journalist and we express our deepest condolences to his family and friends. We will provide more information when it is available.” + +President Obama was briefed on the video aboard Air Force One as he returned to his Martha’s Vineyard vacation and will be updated on further developments, the White House said. + +“If true, the murder of James Foley is shocking and depraved,” British Prime Minister David Cameron said on Twitter. His office said Wednesday he was cutting short a family vacation and returning to London to chair emergency meetings on Iraq and Syria. + +In an interview with the BBC, Foreign Secretary Philip Hammond acknowledged that the apparent executioner spoke with a British accent and said the video seemed to be genuine. + +Hundreds of Britons are believed to have traveled to Syria to fight in the country’s civil war, including many who have joined the Islamic State. + +“We’re absolutely aware that there are significant numbers of British nationals involved in terrible crimes, probably in the commission of atrocities,” Hammond said. “Many of these people may seek at some point to return to the U.K., and they would then pose a direct threat to our domestic security.” + +A European intelligence official said the British government was examining the video, and the speech of the purported executioner, to compare it with former Guantanamo Bay prisoners and other British residents believed to have joined the Islamic State. + +Both prisoners in the video are wearing orange shirts and pants, similar to orange jumpsuits worn by detainees at the U.S. military prison at Guantanamo Bay, Cuba. A similar outfit, believed to be a jihadist symbol of the prison, was worn by Nicholas Berg, an American businessman kidnapped in Iraq in 2004 whose execution by an Islamic State precursor organization was recorded on video and posted online. + +Foley, 40, was working in Syria for the Boston-based news Web site Global­Post when he disappeared on Thanksgiving in 2012. + +Philip Balboni, GlobalPost’s chief executive and co-founder, said in a statement: “On behalf of John and Diane Foley, and also GlobalPost, we deeply appreciate all of the messages of sympathy and support that have poured in since the news of Jim’s possible execution first broke. We have been informed that the FBI is in the process of evaluating the video posted by the Islamic State to determine if it is authentic. Until we have that determination, we will not be in a position to make any further statement. We ask for your prayers for Jim and his family.” + +In a statement Tuesday night on a Facebook page dedicated to his freedom, Foley’s mother appeared to accept that the video was authentic. “We have never been prouder of our son Jim,” Diane Foley wrote. “He gave his life trying to expose the world to the suffering of the Syrian people. + +“We implore the kidnappers to spare the lives of the remaining hostages. Like Jim, they are innocents. They have no control over American government policy in Iraq, Syria or anywhere in the world.” + +Praising James Foley as “an extraordinary son, brother, journalist and person,” she asked that the family’s privacy be respected. + +Sotloff, a freelancer who worked for several news organizations, disappeared in Syria in August 2013. + +In addition to Foley and Sotloff, at least three other Americans are believed to be captives in Syria, including Austin Tice, a freelance journalist whose articles appeared in McClatchy publications and The Washington Post before his disappearance in August 2012, according to a 2013 GlobalPost article. No one has claimed to be holding them. + +According to the Committee to Protect Journalists, at least 66 journalists, all but 10 of them Syrian, have been killed covering the Syrian war. If the video is authenticated, Foley would be the first American journalist known to be executed since the conflict began in early 2011. The video evoked the 2002 taped execution in Pakistan of Wall Street Journal correspondent Daniel Pearl by al-Qaeda. + +The Islamic State, an offshoot of al-Qaeda, is the most powerful among a number of extremist organizations that have emerged during the Syrian civil war, which began as a popular uprising against President Bashar al-Assad. Fighting against both Assad and U.S.-backed rebels, the militants now control much of eastern Syria and claim to have established an Islamic caliphate spanning Syria and neighboring Iraq. + +As the group has grown, it has merged with the group formerly known as al-Qaeda in Iraq, under the leadership of Abu Bakr al-Baghdadi. According to U.S. intelligence, it numbers in the thousands, including foreign fighters from Europe and the United States. + +In April, Islamic State fighters swept across the border into northern Iraq, taking over the city of Mosul before moving southward to within 60 miles of Baghdad. Extensive reports of executions, including beheadings and crucifixions, have emerged from areas under the group’s control. + +This month, amid reports of stranded and besieged Iraqi minorities threatened with execution, the militants advanced eastward toward Irbil, the capital of the semiautonomous Kurdish region of Iraq. + +On Aug. 7, Obama authorized U.S. airstrikes to rescue stranded minorities and protect U.S. personnel and facilities in Irbil and Baghdad. On Monday, after a total of 68 strikes from jets, bombers and drones, Obama announced that Iraqi and Kurdish forces, with U.S. air support, had retaken a strategic dam north of Mosul from the militants and that they had been pushed back from Irbil. + +Within hours of that announcement, the Islamic State posted an online message warning it would attack Americans “in any place” in response to the airstrikes. “We will drown all of you in blood,” it said. + +The title of the video posted Tuesday was “A Message to America” and was produced by the Islamic State’s media arm, according to the Site Intelligence Group, which monitors extremist Web sites. + +A masked man dressed in black is shown standing in an unidentified desert location beside a prisoner kneeling beside him with his hands behind his back. “Obama authorized military operations against the Islamic State effectively placing America upon a slippery slope towards a new war against Muslims,” the masked man says. + +The video then shows a clip of Obama’s Aug. 7 announcement, followed by a statement from the prisoner. + +“I call on my friends, family and loved ones to rise up against my real killers, the U.S. government, for what will happen to me is only a result of their complacent criminality,” he says. He asks his parents not to accept “any meager compensation from the same people who effectively hit the last nail in my coffin with the recent aerial campaign in Iraq.” + +The prisoner also appeals to “my brother John, who is a member of the U.S. Air Force,” to “think about what you are doing.” + +“I wish I had more time,” he says. “I wish I could have the hope for freedom to see my family once again, but that ship has sailed. I guess all in all, I wish I wasn’t an American.” + +The masked man then identifies the prisoner as “James Wright Foley, an American citizen of your country.” He then reaches down with a large knife and begins the apparent beheading of the prisoner; the screen fades to black and the next image is of a body with a head placed upon its chest. + +The masked man then appears with another prisoner, identified as Sotloff, in a similar kneeling position. + +Foley reported from some of the most dangerous recent crises and was imprisoned for 44 days in Libya in 2011 by forces loyal to deposed leader Moammar Gaddafi. According to Global­Post, two eyewitnesses saw his interception by a group of armed men in a silver-colored van on a road near the town of Taftanaz in northern Syria on Nov. 22, 2012. + +Since then, Global­Post “has mounted an extensive international investigation . . . to determine who kidnapped Foley and where he was being held,” Global­Post said in an article on its Web site late Tuesday. + +Julie Tate, Greg Miller and Dan Lamothe in Washington, Griff Witte in London and Souad Mekhennet in Frankfurt, Germany, contributed to this report.","1" +"Obama denounces killing of journalist James Foley and pledges ‘justice’","President Obama said Wednesday that the United States “will be vigilant and we will be relentless” against Islamic State militants and would “do what’s necessary to see that justice is done” following the videotaped execution of an American journalist. + +“Today the entire world is appalled at the brutal murder of James Foley by the terrorist group ISIL,” Obama said, using one of several acronyms for the group. The militants, who posted the video on YouTube Tuesday, said Foley’s killing was in retaliation for U.S. airstrikes in Iraq. + +Obama, who spoke Wednesday morning to Foley’s parents, offered no new policy measures to confront Islamic State. Referring to neighboring countries and U.S. allies, he said “there has to be a common effort to extract this cancer so that it does not spread.” + +Asked whether the United States might consider suspending its airstrikes, one U.S. official said the “only question is if we do more.” Officials said that attacks against the Islamic State would continue in Iraq under an authorization Obama signed early this month. + +Obama could face pressure to escalate the air campaign in Iraq and increase support to U.S.-backed rebels in Syria who are fighting against the Islamic Front, as well as Syrian President Bashar al-Assad. Obama has resisted pleas from the Syrian rebels for U.S. heavy weapons, including portable surface-to-air missiles, as well as for American air support. + +In a statement issued after the president’s remarks, Rep. Ed Royce (R-Calif.), chairman of the House Foreign Affairs Committee, said, “We must get serious about confronting this force, including by aggressively arming those battling it.” + +The White House confirmed early Wednesday that U.S. intelligence had deemed the video authentic. Obama spoke in Martha’s Vineyard, where he is vacationing with his family. + +Foley, a 40-year-old New Hampshire native and a photojournalist working for the Boston-based Web site Global­Post, was kidnapped in northern Syria nearly two years ago while covering the civil war in Syria. + +In Britain Wednesday, Prime Minister David Cameron cut short a family vacation and returned to London to chair emergency meetings on Iraq and Syria, amid indications that a British citizen was involved in Foley’s killing. In the video, his masked executioner speaks in English with what sounds like a British accent. + +After beheading Foley, the executioner is pictured with a second captive, identified as U.S. freelance journalist Steven Joel Sotloff, who disappeared last year in Syria. “The life of this American citizen, Obama, depends on your next decision,” the executioner says. + +In an interview with the BBC, British Foreign Secretary Philip Hammond acknowledged that the executioner spoke with a British accent and said the video seemed to be genuine. Hundreds of Britons are believed to have traveled to Syria to fight in the country’s civil war, including many who have joined the Islamic State. + +“We’re absolutely aware that there are significant numbers of British nationals involved in terrible crimes, probably in the commission of atrocities,” Hammond said. “Many of these people may seek at some point to return to the U.K., and they would then pose a direct threat to our domestic security.” + +A European intelligence official said the British government was examining the video, and the speech of the purported executioner, to compare it to the speech of former Guantanamo Bay prisoners and other British residents believed to have joined the Islamic State. + +Both prisoners in the video are wearing orange shirts and pants, similar to orange jumpsuits worn by detainees at the U.S. military prison at Guantanamo Bay, Cuba. A similar outfit, believed to be a jihadist symbol of the prison, was worn by Nicholas Berg, an American businessman kidnapped in Iraq in 2004 whose execution by an Islamic State precursor organization was recorded on video and posted online. + +Foley, 40, was working in Syria for the Boston-based news Web site Global­Post when he disappeared on Thanksgiving in 2012. + +In a statement Tuesday night on a Facebook page dedicated to his freedom, Foley’s mother wrote: “We have never been prouder of our son Jim,” Diane Foley wrote. “He gave his life trying to expose the world to the suffering of the Syrian people. + +“We implore the kidnappers to spare the lives of the remaining hostages. Like Jim, they are innocents. They have no control over American government policy in Iraq, Syria or anywhere in the world.” + +Praising James Foley as “an extraordinary son, brother, journalist and person,” she asked that the family’s privacy be respected. + +In addition to Foley and Sotloff, at least three other Americans are believed to be captives in Syria, according to a 2013 Global­Post article, including Austin Tice, a freelance journalist whose articles appeared in McClatchy publications and The Washington Post before his disappearance in August 2012. No one has claimed to be holding them. + +According to the Committee to Protect Journalists, at least 66 journalists, all but 10 of them Syrian, have been killed covering the Syrian war. If the video is authenticated, Foley would be the first American journalist known to be executed since the conflict began in early 2011. The video evoked the 2002 taped execution in Pakistan of Wall Street Journal correspondent Daniel Pearl by al-Qaeda. + +The Islamic State, an offshoot of al-Qaeda, is the most powerful among a number of extremist organizations that have emerged during the Syrian civil war, which began as a popular uprising against President Bashar al-Assad. Fighting against both Assad and U.S.-backed rebels, the militants now control much of eastern Syria and claim to have established an Islamic caliphate spanning Syria and neighboring Iraq. + +As the group has grown, it has merged with the group formerly known as al-Qaeda in Iraq, under the leadership of Abu Bakr al-Baghdadi. According to U.S. intelligence, it numbers in the thousands, including foreign fighters from Europe and the United States. + +In April, Islamic State fighters swept across the border into northern Iraq, taking over the city of Mosul before moving southward to within 60 miles of Baghdad. Extensive reports of executions, including beheadings and crucifixions, have emerged from areas under the group’s control. + +This month, amid reports of stranded and besieged Iraqi minorities threatened with execution, the militants advanced eastward toward Irbil, the capital of the semiautonomous Kurdish region of Iraq. + +On Aug. 7, Obama authorized U.S. airstrikes to rescue stranded minorities and protect U.S. personnel and facilities in Irbil and Baghdad. On Monday, after a total of 68 strikes from jets, bombers and drones, Obama announced that Iraqi and Kurdish forces, with U.S. air support, had retaken a strategic dam north of Mosul from the militants and that they had been pushed back from Irbil. + +Within hours of that announcement, the Islamic State posted an online message warning it would attack Americans “in any place” in response to the airstrikes. “We will drown all of you in blood,” it said. + +The title of the video posted Tuesday was “A Message to America” and was produced by the Islamic State’s media arm, according to the Site Intelligence Group, which monitors extremist Web sites. + +A masked man dressed in black is shown standing in an unidentified desert location beside a prisoner kneeling beside him with his hands behind his back. “Obama authorized military operations against the Islamic State effectively placing America upon a slippery slope towards a new war against Muslims,” the masked man says. + +The video then shows a clip of Obama’s Aug. 7 announcement, followed by a statement from the prisoner. + +“I call on my friends, family and loved ones to rise up against my real killers, the U.S. government, for what will happen to me is only a result of their complacent criminality,” he says. He asks his parents not to accept “any meager compensation from the same people who effectively hit the last nail in my coffin with the recent aerial campaign in Iraq.” + +The prisoner also appeals to “my brother John, who is a member of the U.S. Air Force,” to “think about what you are doing.” + +“I wish I had more time,” he says. “I wish I could have the hope for freedom to see my family once again, but that ship has sailed. I guess all in all, I wish I wasn’t an American.” + +The masked man then identifies the prisoner as “James Wright Foley, an American citizen of your country.” He then reaches down with a large knife and begins the apparent beheading of the prisoner; the screen fades to black and the next image is of a body with a head placed upon its back. + +The masked man then appears with another prisoner, identified as Sotloff, in a similar kneeling position. + +Foley reported from some of the most dangerous recent crises and was imprisoned for 44 days in Libya in 2011 by forces loyal to deposed leader Moammar Gaddafi. According to Global­Post, two eyewitnesses saw his interception by a group of armed men in a silver-colored van on a road near the town of Taftanaz in northern Syria on Nov. 22, 2012. + +Since then, Global­Post “has mounted an extensive international investigation . . . to determine who kidnapped Foley and where he was being held,” Global­Post said in an article on its Web site late Tuesday. + +Julie Tate and Dan Lamothe in Washington, Griff Witte in London and Souad Mekhennet in Frankfurt, Germany, contributed to this report.","1" +"The “Flood Libel” Propagandists of 2015","The proliferation of online news outlets has democratized newsgathering, but it’s also updated the famous adage that “there’s a sucker born every minute” for the Internet age. And no circus attracts the suckers quite like the Arab-Israeli conflict. Not only will people believe anything about Israel; their editors will let them write it. And as we learned yesterday, pretty much every year someone will fall for the impossibly preposterous accusation known as the “flood libel.” + +There are moments when biased coverage of Israel goes beyond mere opinion. Last year, the good folks at Vox, a notoriously error-ridden site, declared the existence of a bridge connecting the West Bank and Gaza. It was not a maddening mistake; it was, rather, kind of endearing. It was adorable, in its own way. But that such a bridge does not exist is an easily verifiable fact. + +Same goes for New York Times Jerusalem bureau chief Jodi Rudoren’s claim in 2012 that prospective Jewish construction in the West Bank would bisect the West Bank and make physical contiguity impossible. As was subsequently pointed out (and corrected accordingly), this was not even close to being true and Rudoren would have known as much had she glanced at a map. + +And this week we were treated to another version of this story, though it’s one we hear often enough. It’s a bit of a hazing ritual: the Palestinians find someone they haven’t yet sold this particular lie to and watch the magic unfold. The lie is this: that flooding in Gaza was caused by Israel opening dams in the South. Easily the most important part of this story is the fact that there are no such dams. They are the Gaza-West Bank bridge of this story. And yet, the story just keeps appearing because the Palestinians never run out of Western suckers. + +One of the suckers this year was Vice News. To try to hide its ignorance, Vice offered up several paragraphs of false accusations from the Palestinians followed by this attempt at “balance”: “Israeli officials categorically denied they were to blame while speaking to VICE News on Monday.” + +Other outlets were more honest and ethical in the aftermath of publishing the flood libel. As HonestReporting notes, the Daily Mail went with a bit of false balance but also, crucially, added a straight correction and admission of error: “An earlier version of this article stated that Israel had opened river dams in the south of the country, causing flooding in the Gaza strip. In fact, there are no dams in southern Israel and the flooding was caused by rain and drainage issues. We are happy to clarify this.” + +According to HonestReporting, the Daily Mail piece also contained the following amazing sentence: “The flooding was today compounded after an Israeli power company cut electricity to two of Gaza’s major West Bank cities.” + +And according to CAMERA, both Agence France Presse and Al Jazeera (shocking, I know) passed along the flood libel. AFP pulled its video, and Al Jazeera went the Vice route by pretending the existence of magical dams is somehow in dispute. + +The flood libel is proof that sometimes people refuse to learn from others’ mistakes. See this post from Jonathan Tobin in December 2013 for a reminder that the flood libel is neither new nor surprising. IDF spokeswoman Libby Weiss understandably would rather news organizations first locate their unicorns before blaming those unicorns for goring the neighbor’s ox: + + +So why does this keep happening? Part of the frustration with reporters stems from their absolute laziness. The Internet has put so much information within arm’s reach, and yet reporters are taught that when it comes to Israel, the facts are optional. And that’s because the facts favor Israel. + +If you were to draw a map of Israel, using Western news organizations’ reporting, you’d have one that showed Israel bisecting the West Bank while connecting it to Gaza via a bridge and holding parliamentary meetings in its capital of Tel Aviv. None of that is true, but that’s the picture that emerges from the media’s “reporting.” + +There also appears to be a kind of modified Stockholm Syndrome at work. These reporters and the outlets they represent are constantly made to look like fools by Palestinian propaganda. But they also seem not to mind, because they sympathize so strongly with what the propagandists and terrorists are telling them. + +If what I’m describing to you sounds an awful lot like an activist, not a journalist, well–that’s about right. And such activists play a key role in disseminating grist for the anti-Semitic mill. The first headline is the one that makes waves, especially in the Arab world and in Europe. If the follow-up is not a full retraction or correction, but rather a “balanced” piece in which Israel is permitted to deny the existence of things that plainly don’t exist, then it casts the Israeli government as a powerful entity engaged in a cover-up. + +It would be bad enough if we were forced to admit that our media just can’t get the story right. But that’s naïve. The truth is, much of the time our media just won’t get it right. And that’s why the flood libel returns, year after year.","1" +"Israel denies causing Gaza floods by opening dams","Israel has rejected allegations by government officials in the Gaza strip that authorities were responsible for released storm waters flooding parts of the besieged area. +""The claim is entirely false, and southern Israel does not have any dams,"" said a statement from the Coordinator of Government Activites in the Territorities (COGAT). +""Due to the recent rain, streams were flooded throughout the region with no connection to actions taken by the State of Israel."" +At least 80 Palestinian families have been evacuated after water levels in the Gaza Valley (Wadi Gaza) rose to almost three meters, . +The Gaza Ministry of Interior said in a statement on Sunday that civil defence services had worked alongside teams from the Minsitry of Public Works to evacuate families to shelters in al-Bureij refugee camp and in al-Zahra neighbourhood sponsored by UNRWA, the UN Relief and Works Agency. +Brigadier Gerneral Said Al-Saudi, chief of the civil defence agency in Gaza, told Al Jazeera: ""More than 40 homes were flooded and 80 families are currently in shelters as a result."" +He added that the flooding would adversely affect local agriculture as the area included Gazan poultry and animal farms. +A major storm in the region has brought freezing rain to Gaza and snow across parts of the Occupied Territories and Israel.","1" +"Italian fisherman catches monstrous 280-pound catfish","Italian fisherman Dino Ferrari landed what could potentially be a world record wels catfish in Italy’s Po Delta. Ferrari’s fish measured an incredible 8.7 feet in length and weighed 280 pounds. The current weight record for a wels catfish is over 300 pounds, but according to the Daily Mirror, Ferrari may have set a record for the largest catfish to be caught with a rod and reel. + +Here’s photographic proof that this thing could just swallow an adult if it wanted to. It’s enormous. + +Sportex Italia/Facebook +Sportex Italia/Facebook","1" +"Caught a catfish record in Po: 127 kg and 2.67 meters","The news has gone around the world, including fishing enthusiasts and more: Dino Ferrari and the twin brother Dario, who scored a record-fishing along the river Po. On February 19, in the province of Mantua, have in fact captured a huge torpedo from the weight of 127 kg and a length of 267 centimeters. +shadow carouselCatfish in the Guinness book +Catfish in the Guinness book +Catfish in the Guinness book +Catfish in the Guinness book +Catfish in the Guinness book +Catfish in the Guinness book +Catfish in the Guinness book +Catfish in the Guinness book +Catfish in the Guinness book +Catfish in the Guinness book +Catfish in the Guinness book +Catfish in the Guinness book +Catfish in the Guinness book +Catfish in the Guinness book +Catfish in the Guinness book +Catfish in the Guinness book +Catfish in the Guinness book +Catfish in the Guinness book +Catfish in the Guinness book +Prev Next +Giant River +""It was a fight that lasted 40 minutes,"" says Dino. Before now no one had ever managed to capture a prey so great with the technique of spinning, a type of fishing with artificial bait. When they felt the appropriate time, have pulled it towards the boat and then, with great difficulty by the torpedo, they hooked and towed to shore. Although destroyed by fatigue are happy for the company: the brothers win it a mention in the Guinness Book of Records. ""To fish these giants of the river, you must have patience but also a lot of physical strength,"" says the fisherman. In truth, the two are quite well-known in the catfish fishing for making other exceptional catches in the past: ""In 20 years we have caught about 1,800."" The joy for this sensational blow was so great that Dino wanted to embrace the mighty fish for the usual photos. It is thought that the torpedo can achieve even four feet long, although so far there is no evidence. And the prey, what happened? The giant is still in the Po. After a few shots have thrown back into the water. ""Who am I to take his life?"" Says Dino Ferrari. Maybe in a year will be able to catch them again. However, at that point it will be even more gigantic","1" +"Giant 8ft 9in catfish weighing 19 stone caught in Italy is thought to be the biggest ever reeled in with a rod and line","A fisherman has caught a giant 8ft 9in long catfish weighing 19 stone - and it could be the biggest ever caught with the humble rod and line. + +Dino Ferrari hooked the huge wels catfish, which was 2.67m in length, last week in the Po Delta in Italy. + +The cannibalistic wels catfish, also known as the sheatfish, is native to Europe and can grow as long as 13ft and up to 62st - but it is exceedingly rare to catch one that is over two metres long. + +Scroll down for video. + +Dino Ferrari hooked the huge wels catfish, which was 2.67m in length, last week in the Po Delta in Italy + +But while Mr Ferrari's fish might set a new record for the biggest ever caught on a line, it is not the heaviest ever hooked - that award goes to catfish which weighed 22st and was 9ft long, and was caught in the Po Delta, reports The Mirror. + +In December schoolboy Sam Lee, 14, caught an 8ft 14 stone catfish while on a fishing holiday in Spain with his father Peter. + +The giant catfish immediately bolted 100 metres downstream, but Sam, from Chester, hung on and after a 35 minute battle finally landed the 2.5 metre-long fish. + +In time honoured tradition, he then posed for a photo to secure bragging rights before letting the creature swim back into the water at the River Ebro in Catalonia. + +Mr Ferrari (pictured) poses with his monster catch. Wels catfish can grow as long as 13ft and weigh up to 62st + +In October a Cornish pensioner caught an 8ft-long, 15 stonepart-albino catfish, thought to be the biggest of its kind ever caught. + +The aptly named Tom Herron, 68, from Launceston, battled the cream-coloured monster fish in the River Segre, Mequinenza, Spain, for 40 minutes before finally hauling it in. + +The wels catfish is scaleless and lives in fresh and brackish water. + +It is recognisable by its broad, flat head and wide mouth. + +The wels catfish can live for thirty years and live off annelid worms, gastropods, insects, crustaceans and fish including other catfish; the larger ones also eat frogs, mice, rats, and even ducks. + +Recently, wels catfish have been spotted in non-native habitats lunging out of the water to grab pigeons on land.","1" +"Italian catches huge wels catfish; is it a record?","Italian fisherman Dino Ferrari, an expert at catching big wels catfish, outdid himself on Thursday when he landed an enormous 280-pounder in the Po Delta, a part of the famous Po River, the longest river in Italy at more than 400 miles. + +The wels catfish was put in a sling and weighed out at 280 pounds. Photo is from Sportex Italia Facebook page +The wels catfish was put in a sling and weighed out at 280 pounds. Photo is from the Sportex Italia Facebook page + +The Po River and Delta are known for massive wels catfish, but anything bigger than 6.5 feet is considered extremely rare, and this one measured 8.8 feet. + +The U.K. Mirror reported that Ferrari’s fish could possibly be the world’s biggest wels catfish caught with a rod and reel, though records of this sort are difficult to confirm. + +The Mirror and NT News reported that the biggest wels catfish ever recorded was a 9.1-footer from the Po Delta, but they differ on its weight—one reporting it as 308 pounds, the other as 317 pounds. The method of that catch is uncertain. + +Sportex Italia, Ferrari’s sponsor, called his fish the “world record spinning torpedo,” which might mean it’s a world record for a Torpedo spinning rod made by an Italian manufacturer, though it also simply says it’s a “world record in the spin fishing for catfish.” + +Regardless, Ferrari’s fish is one of the biggest wels catfish recorded in recent history. + +After weighing the wels catfish, Dino and Dario Ferrari released the beast back into the Po Delta. Photo is from the Sportex Italia Facebook page +After weighing the wels catfish, Dino and Dario Ferrari released the beast back into the Po Delta. Photo is from the Sportex Italia Facebook page + +Any wels catfish over 6 1/2 feet is considered extremely rare. This one was 8.8 feet. Photo from the Sportex Italia Facebook page +Any wels catfish bigger than 6.5 feet is considered extremely rare. This one was 8.8 feet. Photo from the Sportex Italia Facebook page + +The wels catfish is the second-largest freshwater fish in its region, ranking behind the beluga sturgeon. The largest beluga sturgeon on record is reportedly 3,463 pounds. + +Ferrari told GrindTV that the fish took an artificial bait on the surface, and the fight from a boat lasted 40 minutes. + +The best part about Ferrari’s catch is that after he and his brother, Dario, weighed the fish, they released it back into the delta so it could fight again another day. + +Follow David Strege on Facebook.","1" +"Enormous 20-stone catfish caught with fishing rod in Italy after 40-minute boat battle","The wels catfish, which was set free, could be one of the largest ever caught + +An enormous catfish weighing 20 stone has been caught in Italy using only a fishing rod. + +Dino Ferrari told GrindTV that he and his brother, Dario, lured it in with artificial bait and then battled the giant fish from their small boat for 40 minutes on Thursday. + +After staying in the water to weigh and measure the specimen, which is one of the largest ever caught, they released it back into the river to swim another day. + +Rod manufacturer Sportex Italia, which sponsors Mr Ferrari, claimed that the 2.67m wels catfish was a world record size to be caught with its Torpedo spinning rod. + +It was found in the Po Delta, which is known for having the perfect living conditions for giant wels to flourish. + +According to a British wels catfish website, they have hundreds “velcro-like teeth” used to hold prey before passing food to “crushing pads” at the back of the throat. + +It records the UK record dating back to 1997 as a four-and-a-half stone fish caught in Bedfordshire. + +The fish are not fussy eaters and have reportedly been known to feed on ducks, rats and even pigeons.","1" +"280 Pound Catfish: Fisherman Makes Huge Catch In Italy, Catfish Could Set Record","A 280 pound catfish was caught by a fisherman in Italy. According to USA Today Sports, Dino Ferrari caught the huge fish in Po Delta. While the catfish caught by Ferrari was 8.7 feet in length and weighed 280 pounds, the largest catfish ever caught weighed 300 pounds. That does not mean that this wasn’t a record-breaking fish, however. According to the report, this might be the largest catfish ever caught using a generic fishing rod. + +According to the San Antonio Express-News, any catfish over 6.5 feet is considered extremely rare. Ferrari isn’t some small time fisherman, either. According to Grind TV, the Italy native is a pro at catching big Wels catfish, and many of these fish frequent the waters where Ferrari casts his line. + +“The wels catfish is the second-largest freshwater fish in its region, ranking behind the beluga sturgeon. The largest beluga sturgeon on record is reportedly 3,463 pounds.” + +The 280 pound catfish is certainly a sight to see, as it looks as if it could swallow Ferrari whole. He posed for photos with the fish, clearly very proud of his catch (even appearing to hug it while his brother took some pictures), which took him a tiring 40 minutes to reel in. It is almost hard to believe that catfish can get that big! + +Animal lovers may be happy to know that Ferrari did not keep the catfish, nor did he sell it for money. After his brother took a couple of pictures of the creature, the guys released it back into the river, where it swam off, happy to live another day. + +As previously reported by the Inquisitr, these Wels catfish aren’t exactly harmless; this certainly is not the type of sea creature that you would want to swim into. And it is definitely not a “gentle giant” by any means. + +“Dino’s monster catch is not the sort of fish you’d want to accidentally swim into while skinny dipping. The fish has a ferocious appetite and will consume anything that happens to cross its path. These surly catfish have even been filmed eating pigeons after our feathery friends happened to fly too close to these cold-blooded killers.” + +Pictures of the 280 pound catfish are making waves on the internet today. Have you ever seen a catfish so big? Would you want to see a Wels catfish in person? + +[Photo courtesy of Sportex /Facebook]","1" +"Fisherman lands 19 STONE catfish which could be biggest in world to be hooked","Dino Ferrari hooked the whopper wels catfish, which was 2.67m in length, last week in the Po Delta in Italy + +A fisherman has reeled in a monster 19 stone catfish, which could be the biggest in the world caught with a rod and reel. + +Dino Ferrari hooked the whopper wels catfish, which was 2.67m in length, last week in the Po Delta in Italy. + +While the fish might set a new record for the biggest caught on a line, it is far from the heaviest ever landed. The biggest was 22st and 2.78m long, and was also from the Po Delta. + +Wels catfish can grow as long as 4m and up to 62st. However, it is rare to catch one that is over two meters long. + +Facebook Hooked: Dino caught the fish in the Po Delta in Italy where the biggest catfish ever caught was 22 stone + +The fish has a ferocious appetite and will consume anything it comes across. They have been filmed eating pigeons that get too close. + +In December 14-year-old Sam Lee caught a 15st catfish while on holiday in Spain. + +The Chester schoolboy was with dad Peter when the 2.5m carnivorous fish snatched the live bait at the end of his line. + +It immediately bolted 100m downstream, but Sam hung on - and eventually landed it after a 35 minute battle. + +He then posed for a traditional photo to secure bragging rights before letting the creature swim back into the water at the River Ebro in Catalonia.","1" +"Monster catfish which looks big enough to swallow a man whole caught in Italy","With its huge, gaping mouth, it looks big enough to swallow a person whole. + +This giant catfish, which weighed 20 stone (127kg) was caught by twin brothers Dino and Dario Ferrari in the Po River of northern Italy. + +Dino Ferrari caught the 127 kg catfish in the Po delta of Italy (Sportex Italia) + +Believed to be one of the largest of its kind ever caught, the creature was pulled from the river on Feb 19 with a rod and line after a battle lasting 40 minutes. + +The nine foot-long creature, a wels catfish, has been dubbed “the monster of the Po” by the Italian media. + +The fish was released after the trophy photos (Sportex Italia) + +After catching, weighing and photographing it, the brothers released it back into the river, which flows across northern Italy to the Adriatic. + +“It’s a silurus glanis [the Latin name for the species],” Dino Ferrari said. “The American catfish doesn’t grow to such large dimensions – at most it can weigh 50kg.” He estimated the fish to be about 30 years old, based on its size, adding that the species can live for up to 50 years. + +“They don’t range over very large distances, they tend to live in the same stretch of river, moving just a few kilometres either way. They eat all types of fish. + +""To catch them you need a lot of patience but also physical strength. We fought for 40 minutes to reel it in. We tired it out and then lifted it out of the water.” + +The wels catfish, also known as the sheatfish, lives in fresh and brackish water. + +It is native to eastern Europe and parts of Asia but was introduced to western Europe. + +The fish prey on other fish, as well as worms, crustaceans, frogs and water fowl. + +“Who knows, maybe we will manage to catch it again in a year’s time, and it will be even more gigantic,” said Mr Ferrari.","1" +"Surreal Photos of Fisherman’s Jaw-Dropping Catch Will Likely Have People Wondering If It’s Real","A fisherman is claiming to have caught a massive catfish — measuring almost 9 feet and weighing roughly 266 pounds — in the Po Delta in Italy. The picture of the giant sea creature is so surreal, many will certainly question if it’s a fake. + +Dino Ferrari posted several photos on Facebook of himself posing with the wels catfish, also known as the sheatfish. + +(Facebook) + +(Facebook) + +Surprisingly, it’s not the heaviest or longest catfish ever caught on a rod and line. The Mirror reports a 9-foot, 308-pound catfish was previously caught in the Po Delta. + +Wels catfish can apparently grow to be over 13 feet long and nearly 900 pounds, but it’s rare to catch one over about 6 feet. + +(H/T: Daily Mail)","1" +"Jose Canseco Shot in the Hand During Accidental Shooting at Vegas Home","Six-time MLB All-Star Jose Canseco shot himself in the hand on Tuesday afternoon at his Las Vegas residence and is recovering at a hospital in the area. + +Spencer Lubitz of KTNV in Las Vegas added specifics about Canseco's condition: + + +Natalie Cullen of CBS 8 News Now got confirmation through police that an accidental shooting had occurred at Canseco's home. + +Canseco, 50, enjoyed many of the best years of his career with the Oakland Athletics, winning an American League MVP award in 1988 and his first of two World Series titles in 1989. + +The slugger hit 462 total home runs, but discredited the power element of his game to a degree in publicly admitting to extensive steroid use.","1" +"Jose Canseco Accidentally Shoots Self in the Hand at Vegas Home","ix-time MLB All-Star Jose Canseco accidentally shot himself in the hand on Tuesday afternoon at his Las Vegas residence and is recovering at a hospital in the area. + +Spencer Lubitz of KTNV in Las Vegas added specifics about Canseco's condition: + + +Natalie Cullen of CBS 8 News Now received confirmation through police that an accidental shooting had occurred at Canseco's home. + +Canseco's daughter Josie tweeted an update on her dad's status: + + +Canseco, 50, enjoyed many of the best years of his career with the Oakland Athletics, winning an American League MVP award in 1988 and his first of two World Series titles in 1989. + +The slugger hit 462 total home runs but discredited the power element of his game to a degree by publicly admitting to extensive steroid use.","1" +"Report—Jose Canseco accidentally shot at his home tonight","(Source) A neighbor tells 8 News NOW former baseball star Jose Canseco was hurt in an accidental shooting Tuesday afternoon at his house on the eastside of the Las Vegas valley. Metro Police confirm there was an accidental shooting at the address, but would not confirm the former player was hurt. However, records show Canseco owns the home where the shooting happened. + + + + + +Vintage Canseco. World Series Game 6, NBA opening night, the Boz On ESPN, all eyes not on Jose Canseco, whoops there I go shooting myself and stealing the show, clumsy me, can’t believe that happened! + + + +You can tell me it was accidental but I know better than that. The consummate showman, that’s what Canseco is. + +UPDATE – Shot or Drone attack?","1" +"Jose Canseco shoots self in hand","LAS VEGAS -- Former major league slugger Jose Canseco is recovering after shooting himself in the hand at his Las Vegas home. + +Metro police Lt. Mark Reddon says officers responded to a call of an accidental shooting shortly after 2:30 p.m. Tuesday. + +Reddon says Canseco told police he was cleaning his gun in the kitchen when it fired, shooting a finger on his left hand. He was taken to University Medical Center of Southern Nevada. + +Canseco's fiancee, Leila Knight, tweeted from his account late Tuesday night, saying he was still in surgery and would be OK. + +Canseco played 17 years in the major leagues, starring for the Oakland Athletics as one of the ""Bash Brothers"" in the late 1980s. He was part of the A's 1989 World Series championship team and last played for the Chicago White Sox in 2001. + +The right-handed outfielder and designated hitter had 462 career home runs and was a six-time All-Star. He also played for Texas, Boston, Toronto, Tampa Bay and the New York Yankees. + +He later admitted to performance-enhancing drug use, with his 2005 book, ""Juiced: Wild Times, Rampant 'Roids, Smash Hits & How Baseball Got Big,"" amplifying MLB's doping issues. + +The Associated Press contributed to this report.","1" +"Report: Jose Canseco accidentally shot","KLAS-TV in Las Vegas is reporting that Jose Canseco was accidentally shot in his home: + +A neighbor tells 8 News NOW former baseball star Jose Canseco was hurt in an accidental shooting Tuesday afternoon at his house on the eastside of the Las Vegas valley. Metro Police confirm there was an accidental shooting at the address, but would not confirm the former player was hurt. However, records show Canseco owns the home where the shooting happened. + +His post-playing career has been nothing if not weird and random. Here’s hoping he’s OK, because weird and random is one thing, tragic is another, and no one wants that at all. + +(h/t to Chad Reno)","1" +"Jose Canseco Accidentally Shot Himself in the Hand [UPDATE - Shot Off Middle Finger]","Jose Canseco certainly lives an interesting life. Reports are beginning to circulate Tuesday night that the former slugger injured himself in a shooting at his Las Vegas home earlier in the day. Details are developing, but it appears the former Oakland Athletics outfielder accidentally shot himself in the hand, possibly while cleaning a gun. + + + +An avid social media user, Canseco hasn’t filed a tweet since Monday when he posted a picture of his dogs. It will be interesting to see what he says about the incident. + +UPDATE: TMZ reports Canseco shot his right middle finger “clear off” according to his fiancée and is now in surgery.","1" +"Baseball star Jose Canseco hurt in accidental shooting","LAS VEGAS -- Metro Police confirms former baseball star Jose Canseco was hurt in an accidental shooting Tuesday afternoon at his house on the far eastside of the Las Vegas valley. + +According to police, the former player accidentally shot himself in the left hand while he was cleaning his .45 caliber handgun. He was taken to University Medical Center. + +Neighbors heard the commotion at around 3 p.m. + +""I just heard some sirens and I walked outside, saw a couple of ambulances and then cops started coming in."" neighbor Taven Swain said. + +There is no word on the seriousness of the injury but he did have to go through surgery. His girlfriend has said through Canseco's Twitter account that doctors are hoping to save his finger from amputation. + +Canseco was a hitting star in the 80s and played for several teams, including the Oakland A's and the Texas Rangers. He retired from baseball in 2001. In 2005, he admitted he used performance-enhancing drugs during much of his career. + +He has been arrested six times for aggravated battery and other offenses. Just last year, he was accused of rape. He vigorously defended himself on social media and was later cleared of the crime.","1" +"Report: Former Baseball Star Jose Canseco Accidentally Shot At Home","Jose Canseco was injured in an accidental shooting at his home, 8 News Now is reporting. + +The former Oakland Athletics slugger was at his house in east Las Vegas when the shooting occurred. + +This story is developing... + +SEE ALSO: Police Are Investigating Sexual Assault Allegations Against Jose Canseco After A Series Of Bizarre Tweets","1" +"Jose Canseco injured in accidental shooting, per reports","Former Major League Baseball outfielder Jose Canseco was injured in an accidental shooting at his home in Las Vegas, Nev., according to KLAS-TV's Natalie Cullen. + +Canseco allegedly shot himself in the hand and is now recovering at a local hospital, reports KTNV's Spencer Lubitz. Police have confirmed that a shooting took place at Canseco's home on the east side of the Las Vegas valley, per the KLAS-TV story. + +In 17 major league seasons, Canseco hit .266/.353/.515 with 462 home runs for seven teams including the Athletics, with whom he broke into the league as a 20-year-old slugger in 1985. Since his final MLB season in 2001, Canseco has attempted to remain in the spotlight by playing in various independent leagues, appearing on reality television shows and writing a book that detailed his and other players' performance-enhancing drug use. Canseco has also participated professionally in mixed martial arts, owning an 0-1 record.","1" +"Don't Worry, 'The Breakfast Club' Star Judd Nelson Is Not Dead","In a welcome break from a slow weekend of news filled with violence and murders, a report that actor Judd Nelson—best known for playing ""The Criminal"" John Bender in The Breakfast Club—had died turned out to be false. +The false report came from the site ""foxnews.es"" which somehow manages to beat the real FOX News in reporting fake information. Nelson's agent Gregg Klein denied the report to the LA Times today and even provided a photo of the alive-and-well ""Brat Pack"" actor holding up a copy of today's Sunday Times with the note, ""Reports of Judd Nelson's death are not accurate please see attached photo."" +The phony report mentions that Nelson died last night in his condo at the Sierra Towers in West Hollywood. Nelson does not live in that building, according to Klein. +With John Bender alive and well, let us enjoy this montage of his best moments in The Breakfast Club:","1" +"Judd Nelson rebuffs Internet rumors that he died of a drug overdose.","Judd Nelson rebuffs Internet rumors that he died of a drug overdose. Rumors swirled on Twitter that the ""Breakfast Club"" actor had found dead in his apartment of an apparent drug overdose. His agent Gregg Klein tweeted out a photo of Nelson holding today's paper","1" +"80's Brat Pack star Judd Nelson forced to deny that he's dead after fake news story starts trending on social media","Actor Judd Nelson, 55, has been forced to confirm that he is alive and well after rumors swept the internet on Sunday morning that he had died overnight. + +Nelson's 'death' was reported by Foxnews.es, a hoax website which has no affiliation with the television news network. + +The fake story claimed that the actor, best known for his roles in 80's classics The Breakfast Club and St. Elmo’s Fire, had been found dead on Saturday night at Sierra Towers, a West Hollywood condominium block. + +I'm alive! Judd Nelson, 55, poses with front page of today's L.A. Times to confirm that he is alive despite internet rumors circulating about his death + +Nelson made the big time after his role as John 'The Criminal' Bender in The Breakfast Club, left, while in recent years he has starred in TV shows including Two And A Half Men + +By Sunday morning Nelson’s name had become a trending topic on Facebook and his agent was prompted to issue a denial. + +Gregg Klein even issued a photo of the actor holding up a copy of Sunday's L.A. Times along with a note, ‘Reports of Judd Nelson's death are not accurate please see attached photo.’ + +It isn't known how or why the fake reports emerged. + +Nelson's longtime manager Jean-Pierre Henraux told the Times that the actor doesn’t even live at the reported address. + +Nelson, top, starred in The Breakfast Club, the 1985 coming-of-age comedy-drama film written, produced, and directed by John Hughes + +Nelson rose to fame in the mid-1980's as a member of the Brat Pack, a group of young actors who broke though at the same time and also included the likes of Rob Lowe, far left, Andrew McCarthy, far right, and Demi Moore, third from the left + +Nelson rose to fame in the mid-1980's as a member of the Brat Pack, a group of young actors who broke though at the same time and also including the likes of Rob Lowe, Andrew McCarthy and Demi Moore. + +Nelson's film career dried up in the 1990's and in recent years he has found work in TV shows including CSI and Two And A Half Men. + +The actor has also been signed up to voice Hot Rod/Rodimus Prime in the live action movie Transformers 5, after having previously voiced the character in The Transformers: The Movie and Transformers: Animated. + +Nelson's 'death' was reported by Foxnews.es, a hoax website which has no affiliation with the television news network","1" +"Judd Nelson Death Hoax: FOX News Impersonator Claims Actor Found Dead In Los Angeles Condo","A Judd Nelson death hoax struck on Sunday as a FOX News impostor website posted a false report stating that the “Brat Pack” actor was found dead in his condo. It was all a hoax. Judd Nelson is not dead. The fake news site even created an elaborate story surrounding Judd Nelson’s alleged death, writing that the Los Angeles County Department of Medical Examiner-Coroner was trying to determine his cause of death as investigators attempted to rule out foul play. In a report called “BREAKING: “Brat Pack” Judd Nelson Found Dead in Los Angeles Condo,” the hoaxer wrote the following untrue tale of Nelson’s demise. + +“Multiple unconfirmed reports say Nelson was found dead Saturday evening in his Los Angeles condo, Sierra Towers after police responded to a 911 call for an unconscious man around 9:25 p.m. Although police have not yet released the man’s identity, multiple occupants of the 31-story West Hollywood high-rise have confirmed that it was Nelson’s condo police responded to and a single body was carried out of the apartment on a stretcher.” + +Judd Nelson doesn’t even live in a Los Angeles condo located in a 31-story West Hollywood high-rise building. That little detail was fabricated along with the news of his death. + +The actor’s agent and his manager both confirmed that the news of his death was premature. Agent Gregg Klein even visited Nelson to snap a photo of the 55-year-old actor, producer and screenwriter clutching a copy of today’s newspaper in his hands, according to Los Angeles Times. As visible in the photo at the top of the page, the actor is still alive. Klein forwarded a copy of the pic to Los Angeles Times along with a message that was short and to the point. + +“Reports of Judd Nelson’s death are not accurate please see attached photo.” + +Nelson’s manager, Jean-Pierre Henraux, also confirmed that the actor was a victim of a death hoax, calling his condition “perfect” and noting that he recently filmed an episode of the upcoming television series Empire, a family drama set in a hip-hop empire. The show’s stars include Terrence Howard, Taraji P. Henson, Jim Cantafio and Jackie Dallas. + +As previously reported by The Inquisitr, a cruel death hoax involving Zayn Malik made headlines when it was incorrectly reported that his younger cousin had died. Little Arshiya Malik underwent surgery for a brain tumor, and someone on Twitter started #RIP Arshiya, which quickly began trending worldwide. Arshiya is not dead. However, she is very ill, and her family is praying for her recovery. + +[Judd Nelson Death Hoax Image via Gregg Klein]","1" +"Judd Nelson Proof Of Life After Death Hoax: FOX News Impersonator Claims Actor Found Dead In Los Angeles Condo [Updated]","Judd Nelson proof of life followed hot on the heels of a death hoax that struck on Sunday. It all began when a FOX News impostor website posted a false report stating that the “Brat Pack” actor was found dead in his condo. It was all a hoax. Judd Nelson is not dead. As proof of life, Judd Nelson even offered a photo of himself holding the day’s Los Angeles Times. + +The fake news site even created an elaborate story surrounding Judd Nelson’s alleged death, writing that the Los Angeles County Department of Medical Examiner-Coroner was trying to determine his cause of death as investigators attempted to rule out foul play. In a report called “BREAKING: “Brat Pack” Judd Nelson Found Dead in Los Angeles Condo,” the hoaxer wrote the following untrue tale of Nelson’s demise. + +“Multiple unconfirmed reports say Nelson was found dead Saturday evening in his Los Angeles condo, Sierra Towers after police responded to a 911 call for an unconscious man around 9:25 p.m. Although police have not yet released the man’s identity, multiple occupants of the 31-story West Hollywood high-rise have confirmed that it was Nelson’s condo police responded to and a single body was carried out of the apartment on a stretcher.” + +The actor doesn’t even live in a Los Angeles condo located in a 31-story West Hollywood high-rise building. That little detail was fabricated along with the news of his death. That’s what prompted Judd Nelson to offer proof of life that he was still among the living. He is. + +The actor’s agent and his manager both confirmed that the news of his death was premature. Agent Gregg Klein even visited Nelson to snap a photo of the 55-year-old actor, producer and screenwriter clutching a copy of today’s newspaper in his hands, according to Los Angeles Times. As visible in the photo at the top of the page, the actor is still alive. Klein forwarded a copy of the Judd Nelson proof of life pic to Los Angeles Times along with a message that was short and to the point. + +“Reports of Judd Nelson’s death are not accurate please see attached photo.” + +Nelson’s manager, Jean-Pierre Henraux, also confirmed that the actor was a victim of a death hoax, calling his condition “perfect” and noting that he recently filmed an episode of the upcoming television series Empire, a family drama set in a hip-hop empire. The show’s stars include Terrence Howard, Taraji P. Henson, Jim Cantafio and Jackie Dallas. + +As previously reported by The Inquisitr, a cruel death hoax involving Zayn Malik made headlines when it was incorrectly reported that his younger cousin had died. Little Arshiya Malik underwent surgery for a brain tumor, and someone on Twitter started #RIP Arshiya, which quickly began trending worldwide. Arshiya is not dead. However, she is very ill, and her family is praying for her recovery. + +[Judd Nelson Proof Of Life/Death Hoax Image via Gregg Klein]","1" +"Judd Nelson isn't dead; report is a hoax","ports of Judd Nelson’s death have been greatly exaggerated. + +Despite rumors that swept the Internet on Sunday morning, the “Breakfast Club” star is alive and well, his manager and agent told the Los Angeles Times. + +Agent Gregg Klein even hustled to Nelson’s home Sunday morning -- which he said is not in the building mentioned in the original false report -- to take a photo of the actor with the front page of today's newspaper. + +Klein was to the point when he answered The Times' query about Nelson's status: ""Reports of Judd Nelson's death are not accurate please see attached photo.""","1" +"Fake Fox News Website Reports Judd Nelson’s Death for Some Reason","Early Sunday morning, Fox News’ website broke the news of the death of 80s actor Judd Nelson: + +Or did it? That’s not actually Fox News, but foxnews.es: + +Per Snopes the website features just that one post. ‘Twas enough to turn the internet to grief mode, however. + +The Los Angeles Times followed up and find Nelson alive and well and reading that morning’s edition. Could it have been Photoshopped? Is it a false flag? Is that actually latimes.es? + +#JuddNelson alive and reading @latimes!! pic.twitter.com/5JHqL8fiVY — patricelatimes (@patricelatimes) October 26, 2014 + +Rumors that after you die that’s it, it’s just nothing remain unconfirmed. + +[Image via screengrab] + +—— >> Follow Evan McMurry (@evanmcmurry) on Twitter","1" +"Fowler Falls For Fake Website, Makes Crazy Claims About Tennis Star","Tonight's Australian Open coverage on ESPN2 featured announcer Chris Fowler explaining to the audience that Japanese pro Kei Nishikori is, among other things, the highest-paid tennis player in the world and the owner of a restaurant chain, a soccer team, and clothing and perfume lines. None of those things are true, and they all come from notorious satire site MediaMass. + +Fowler cited Nishikori as having earned $46 million in 2014. The actual number is $11 million, according to Forbes. That makes him the ninth-highest paid player—not the richest. + +That's okay, Chris. It happens to the best of us.","1" +"Satire Website Fools ESPN, Kei Nishikori isn't highest paid tennis star","ESPN host Chris Fowler was duped by a fake website, MediaMass, because he failed to check his facts. + +Fowler reported a series of wrong facts about Japanese tennis star Kei Nishikori, including that he is the world's highest-paid tennis star and has his own vodka line, soccer team and restaurant chain, USA Today reported. In the segment: + +""You're looking at the highest paid tennis player in the male side in the world. That might be a surprise to Roger Federer fans, but Nishikori has signed up lots of companies. According to published reports, made about 46 million last year...How's he doing it? He owns Fat Nishikori burger restaurant, a football team which is soccer, his own brand of vodka, he's got a perfume, he's got a clothing line...He's got a whole lot of deals with Japanese companies."" + + + +Despite Fowler's claim, Deadspin reported, citing Forbes magazine, that Nishikori didn't make $46 million last year but just $11 million, which ""makes him the ninth-highest paid player -- not the richest."" Forbes breaks that down as $9 million in endorsements and $2 million in prize money. + +The satire site, Media Mass, had reported that Nishikori was the top paid player making $46 million, based on the (fictional) People with Money magazine. + +""He owes his fortune to smart stock investments, substantial property holdings, lucrative endorsement deals with CoverGirl cosmetics. He also owns several restaurants (the “Fat Nishikori Burger” chain) in Tokyo, a Football Team (the “Matsue Angels”), has launched his own brand of Vodka (Pure Wondernishikori - Japan), and is tackling the juniors market with a top-selling perfume (With Love from Kei) and a fashion line called “Kei Nishikori Seduction,'"" Media Mass reported. + +Within the article, however, in red letters, was a note saying the story was false, linking to a 2012 page describing Media Mass's project. The update, which iMediaEthics highlighted below, says it was posted Jan. 25, 2015, but it was posted when iMediaEthics viewed the story Jan. 24, so we are unsure when it was published. + + + + +That update linked to a page on Media Mass' website. ""The website mediamass.net is the medium of our satire to expose with humour, exaggeration and ridicule the contemporary mass production and mass consumption that we observe,"" Media Mass' website states. + +In ESPN's defense, USA Today noted, ""None of the information was completely absurd — it’s not as if they said he owned four castles or slept upside down in a hyperbaric chamber or plans on being one of those people who want to take a one-way trip to Mars."" + +Fowler apologized for the error on Twitter, Sports Grid noted. + + +ESPN pointed iMediaEthics to Fowler's tweets.","1" +"Sorry, KFC isn't going to be selling weed in Colorado restaurants","At least not anytime soon + +The internet has been salivating at the prospect of getting stoned and eating fried chicken this week, after reports circulated that KFC is to become a marijuana dispensary as well as a restaurant. + +A story on Racket Report claimed that with tax revenue from sales of the drug being so high in Colorado, KFC wanted a piece of the action, with the added benefit that its chicken would see a boost in sales thanks to the munchies. + +It looks to be false for several reasons however: + +- Racket Report has carried a lot of hoax stories in the past + +- KFC hasn't mentioned marijuana on its official news page + +- Marijuana sales are currently cash only which would make things tricky for the chain + +- Marijuana is still in somewhat of a legal grey area and probably not crystal clear enough for a giant brand to start slinging it + +- KFC doesn't even sell alcohol, so they'd really be jumping in at the deep end + +While weed might not be hitting KFC any time soon, with sweeping legalisation in the US this sort of thing is inevitable. + +Only yesterday, Ben & Jerry's said they'd be up for creating cannabis-infused ice-cream once it's completely legal. + +Update: KFC confirmed it. Not happening.","1" +"KFC Marijuana Sales To Begin In Colorado? It’s Unbelievable — Literally","KFC: Marijuana on the menu? Not likely. A story that began circulating on Tuesday afternoon created a bit of a frenzy, but the fact is, there’s no sign KFC will really be selling marijuana in its stores. + +The story began at the Racket Report, where it was announced that marijuana profits were hitting such high levels that the fast food restaurant chain had decided to get in on the game. While the idea may appeal to pot lovers who think they can get the munchies and a bucket full of munchables in a single stop, there are a few problems. + +First and foremost, Racket Report appears to be a mostly satirical website, carrying multiple stories, such as the Fetal Ink Syndrome story, that have been debunked by fact-checking site Snopes. (Here‘s Snopes debunking the Fetal Ink Syndrome tale.) + +KFC also doesn’t mention any marijuana sales on its official news page — a thing you’d think they’d mention if they were hoping to drum up sales. + +Another concern is banking. While marijuana shops were assured early in 2014 that they could have access to banks, many report still having difficulties. Though the original story claims that KFC’s pot sales will be cash only, in order to protect the restaurant’s funds, this would be no protection. + +If marijuana sales are understood to be federally illegal (a question that is in limbo at the moment, with government officials calling on law enforcement to make pot arrests a very low priority, but laws still on the books) then no funds collected by a facility could reasonably be protected. That is, if the government elected to seize funds illegally procured, they could still freeze bank accounts and seize the contents — even if all illegal dealings were handled in cash. + +This could not only be a concern for KFC, but for its parent company, YUM Brands. + +Notably, a KFC turned into a marijuana dispensary is a plot point in a South park episode, and there is another KFC that does indeed sell marijuana — but it’s not the fried chicken chain. Instead, it’s a shop called Kind For Cures, a California pot shop based on that same South Park episode, that assures on its website, “This ain’t no chicken joint!” + +Calls to YUM Brands and to KFC Tuesday evening were not immediately returned, but there are no signs that KFC marijuana will be available in the bucket next to your extra crispy any time soon. + +[Photo by: Justin Sullivan/Getty Images]","1" +"Jordan’s King Abdullah Did Not Personally Fly Airstrikes On ISIS","Jordan’s King Abdullah announced he was cutting short a visit to the U.S. following the brutal death of a Jordanian fighter pilot captured by ISIS with this photo. + +The king, a former military pilot himself, joined Jordanian leaders in calling Lt. Muath al-Kaseasbeh, who was burned alive, a martyr. The government also vowed revenge and an “earth-shaking” response. facebook.com + +Sometimes called the “Warrior King,” it wasn’t long before rumors began spreading that his majesty was going to take care of business — personally. + +Via Twitter: @josephbraude + +عاجل ⭕️| ضربة جوية اردنية على معاقل #داعش الآن يشارك فيها ملك #الاردن ""عبدالله الثاني"" + +The images spread on social media… + +Photos of King Abdullah's first personal air attack on ISIS! + +…and prompted some meme-based political commentary. + +Because King Abdullah is a WARRIOR!! + +Obama after James Foley beheading vs. King Abdullah after burning of Jordanian pilot: + +It made a great story, but it wasn’t true, the Jordanian government said. Airstrikes did hit targets in Syria, but the king was not in the pilot’s seat. + +A bomb with Koranic verses is pictured on a Royal Jordanian Air Force plane at an air base before its launch to strike the Islamic state in the Syrian city of Raqqa on Thursday. Petra / Reuters + +Jordanian Foreign Minister Nasser Judeh told CNN Thursday the rumors of the king personally launching airstrikes on ISIS targets were “creative,” but untrue. + +Actually, the king was involved in some more conventional leadership. He met with officials and security leaders. + +صورة: جلالة القائد الأعلى يجتمع مع كبار المسؤولين وقادة الاجهزة الأمنية في القيادة العامة للقوات المسلحة #الأردن #JO + +And he offered condolences to the family of the slain pilot. + +facebook.com + +The cockpit image appears to be from an October charity event, when he piloted a helicopter for children with cancer. + +youtube.com + +Which, is actually pretty cool too. + +Via youtube.com","1" +"No, Jordan's King Abdullah II is not personally flying planes against Isis","A Jordanian government spokesman has denied rumours that the Jordanian King Abdullah II, a trained pilot, is personally conducting airstrikes against the Islamic State (Isis). + +Mohammed al-Momani said in a statement that reports about the personal involvement of the King in combat missions on IS targets is unfounded and baseless. + +Rumours on King Abdullah spread after the he promised to fight back hard against IS, saying that the death of Jordanian pilot Moaz al-Kasasbeh ""will not be in vain"". + +""We are waging this war to protect our faith, our values and human principles and our war for their sake will be relentless and will hit them in their own ground,"" he said on state television. + +Momani had revealed earlier that Jordan will intensify its efforts with an US-led coalition against IS. + +Later on Wednesday, Abdullah vowed ""relentless"" war against IS, saying Jordan will ""hit them on their own ground"". + +Iraqi news outlets cited unofficial sources saying that the king was personally flying a plane. Jordanian author Waleed Abu Anada tweeted: + +BREAKING: Local reports here in Jordan say that King Abdullah will personally fly and lead the airstrikes against ISIS tomorrow. #IAmMoath— Waleed Abu Nada (@waleedabunada) February 4, 2015 + +Before becoming king, Abdullah II was a general in charge of Jordanian special forces and a certified Cobra Helicopter pilot. In 1980 he joined the UK's Royal military academy Sandhurst. + +After the barbaric video of Kasasbeh burning to death emerged, The Royal Hashemite Court's Facebook page published a picture of the King in pilot gear: + +The picture was retweeted several times and used by some as a proof that the Jordanian king was gearing up to fight IS in person. + +So hardcore. Jordan's King Abdullah is seen now in combat gear, with rumors of him leading a battalion against #ISIS pic.twitter.com/Z0SQsB4Feb""— Brennan Mancil (@BrennanMancil) February 5, 2015 + +Others used an old picture of the King on the cockpit of a plane to wrongly suggest Abdullah had carried out his first airstrike on IS. + +عاجل ⭕️| ضربة جوية اردنية على معاقل #داعش الآن يشارك فيها ملك #الاردن ""عبدالله الثاني"" pic.twitter.com/7Z1hDUKunp— عاجل المملكة (@KsaBrk) February 4, 2015","1" +"Rumors of King Abdullah Flying in Airstrikes Not True, Fox Excited Anyway","Fox & Friends got very excited Thursday morning over rumors, which they credited to Jordanian TV, that King Abdullah of Jordan had potentially participated in retaliatory airstrikes against ISIS after the immolation death of Jordanian pilot Muath al-Kasaesbeh. + +“What a statement that would make,” Steve Doocy said. + +“He is stepping up with strong leadership and clarity,” Elisabeth Hasselbeck said. “What is our president doing? + +Fox aired photos of of King Abdullah in flight gear, which had been making the rounds on Twitter since Wednesday evening: + +Reports that Jordanian King Abdullah, himself a pilot, will fly sorties on ISIS targets. pic.twitter.com/mZetDARLOI — Joseph Braude (@josephbraude) February 4, 2015 + +عاجل ⭕️| ضربة جوية اردنية على معاقل #داعش الآن يشارك فيها ملك #الاردن ""عبدالله الثاني"" pic.twitter.com/7Z1hDUKunp — عاجل المملكة (@KsaBrk) February 4, 2015 + +This got conservative Twitter all riled up: + +Looking forward to Brian Williams sharing his memories of flying today's combat mission against ISIL with King Abdullah. — Drew McCoy (@DrewMTips) February 4, 2015 + +The photos were eventually revealed to be from a video last year in which Abdullah took several young cancer patients on a flight. Doocy acknowledged the photos were old before adding, “But he is a pilot.” + +Alas, no hero warrior head of state today: + +Photos of Jord King RT'ed from @KsaBrk appear to be old and misleading. Arabic reports of a planned attack are numerous but unverifiable. — Joseph Braude (@josephbraude) February 5, 2015 + +From @RenaNetjes, Arabic press reports of Jordanian king's flight sortie have been denied by an official spokesperson. @deborahamos — Joseph Braude (@josephbraude) February 5, 2015 + +Al Arabiya confirmed that Abdullah did not take part in any air strikes, and contradicted Doocy’s statement that he was a pilot: + +Meanwhile, a Jordanian government official on Thursday told Al Arabiya News that King Abdullah was not flying missions against ISIS himself, after local media reports – also taken by some international outlets – indicated he is set to do so. The official also noted that observers should refrain from calling King Abdullah a fighter pilot as he does not officially hold the title. He is, however, the commander-in-chief of the Jordanian Air Force. The king is a trained combatant, part of the parachute brigade and flies civilian planes and helicopters, the official added. + +Doocy quietly corrected he record at the end of the next segment. “By the way, I should point out we understand that so far the king has not taken part in any of the raids,” Doocy said. “But he may going forward.” What a statement that would make. + +Watch the video below, via Fox News: + +OO.ready(function() { OO.Player.create('ooyalaplayer-Z3dGc2czrQVCoEqaakHjo4uzs7nqtSWv', 'Z3dGc2czrQVCoEqaakHjo4uzs7nqtSWv'); }); + +Please enable Javascript to watch. + +[Image via screengrab] + +—— >> Follow Evan McMurry (@evanmcmurry) on Twitter","1" +"Korean Housewife’s Hair Sucked Up into Robot Vacuum","SEOUL, Feb. 5 (Korea Bizwire) – A powerful robot vacuum cleaner caused an unlikely accident involving a Korean housewife, and required the intervention of a couple of paramedics. On January 3, a woman in her fifties had her hair sucked up into a robot vacuum at her home in the city of Changwon, South Korea. + +On the day of the accident, she turned on her robot vacuum as usual, and laid down flat on the floor to rest, leaving the robot to do its job. The robot vacuum came around her relaxing on the floor, and suddenly sucked her hair into its nozzle. The vacuum stopped running one to two minutes after the sudden hair intake. + +The startled housewife called 119, Korea’s emergency telephone number. Fortunately, paramedics quickly arrived at the scene, and successfully disjoined her hair from the nozzle. The housewife suffered only minor injuries. + +The problematic robot vacuum had a nozzle with a roller inside, which sweeps and vacuums floors. The Changwon Fire Service Headquarters presumed that the vacuum’s sensors identified the woman’s hair as dust. + +The likelihood of this type accident occurring is undoubtedly more significant in countries with a “sitting-on-the-floor” culture. Since Koreans love to rest or relax on a toasty, cleanly swept floor, exercising caution on using a robot vacuum is probably a good idea.","1" +"Robot vacuum cleaner 'ate' a woman's hair [Google Translate]","20:00 43 minutes three days Changwon, Masan Fire Department Fire Station 119 is a desperate rescue request came from a woman in the situation room to report. Your report is that it does not fall into the hair of the b seed (52) sucked into the unmanned robot vacuum cleaner. b Mr. While no one in the house the day lying alone art the changes in the robot cleaner to myself there was no way I was asking for help. + + + + + + +Masanhoewon-gu, Changwon, Gyeongnam three days 119 nine trillion won a dispatch to a house that has a gloved female hair structure. | Changwon Fire Department offers + + +Dispatched a nine trillion won, four were absurd because these things first. rescuers had hair that holds the b seed in the inlet dust wipe out the results to determine the circumstances involved much intertwined into 5㎝. + + + +Rescuers broke loose hair cleaner and address. Nolan b said, ""thank you"" to the crew members said they had a greeting.","1" +"Robot vacuum cleaner 'attacks' South Korea housewife's hair","A robotic vacuum cleaner ""attacked"" a South Korean woman while she slept by attempting to suck up the hair on her head. + +The woman, a 52-year-old resident of Changwon who has not been named, was awoken by the pain and, unable to extricate herself from the robot, called the fire department for help. + +She was eventually freed by paramedics, escaping serious injury but losing several strands of hair. + +It required two paramedics to remove her hair from the machine's nozzle, Korea Biz Wire reported. + +The incident, which took place on January 3, highlighted the potential risk of this type of accident in South Korea, where sitting and sleeping on the floor is common practice. + +The vacuum only stopped running more than a minute after initially ingesting the woman's hair. + +She was still unable to free herself from the vacuum and made a ""desperate rescue request"" call to 119, South Korea's emergency telephone number. + +Robotic vacuum cleaners are equipped with sensors allowing them to clean surfaces by detecting dirt while avoiding obstacles such as stairs, people and cables - but not, seemingly, human hair that is still attached. + +Too close to home + +While a person's home is his or her castle, it can also the source of seriously painful and embarrassing accidents that require medical attention. + +Doctors in Saudi Arabia got quite a shock when they x-rayed a toddler and saw that he had swallowed a metallic SpongeBob SquarePants pendant. + +Doctors couldn't believe their eyes when they saw this familiar face on the x-ray + +The item, seen in stunning detail in the image above, was removed from the 16-month-old baby boy's oesophagus without complications. + +A closer look at the hairball doctors removed Picture: EUROPICS + +A teen in Kyrgyzstan was rushed to hospital unable to eat and when doctors cut open the 18-year-old's swollen stomach they discovered this giant hairball, which had formed over many years of the girl compulsively eating her own hair and locks she picked up off the floor. + +Statistically speaking, most British people are more likely to be injured at home than anywhere else. + +Don't whatever you do, let the kids anywhere near a trampoline, with the device accounting for around half of all domestic sports injuries requiring hospital treatment among children. Safety experts say children jumping on one with an adult or a crowded trampoline, are the most likely to end in tears and a trip to an A&E unit. + +Barbequing at home can cause unfortunate accidents, with a quarter of us admitting to cooking with one, that is operating a large open flame, while drunk. Gazebos, wooden furniture and sheds are often accidentally set alight in the warmer months, safety experts say. Tipsy grillers could explain the 2,000 individuals admitted to A&E units each year with barbeque-related injuries. + +Depending on the damage, it seems some of us nurse our wounds in silence. + +Around a third of UK adults will feel more than a slight ache or pain as a direct result of bedroom antics, with carpet burns, cricked necks and bruised shoulders among the nation's most common sex injuries. + +For more stories, like the Telegraph's Facebook page by clicking on the link below:","1" +"South Korean woman's hair 'eaten' by robot vacuum cleaner as she slept","When a South Korean woman invested in a robot vacuum cleaner, the idea was to leave her trustworthy gadget to do its work while she took a break from household chores. + +Instead, the 52-year-old resident of Changwon city ended up being the victim of what many believe is a peek into a dystopian future in which supposedly benign robots turn against their human masters. + +The woman, whose name is being withheld, was taking a nap on the floor at home when the vacuum cleaner locked on to her hair and sucked it up, apparently mistaking it for dust. + +The agony of having her hair entangled in the bowels of the contraption roused the woman from her slumber. + +Unable to free herself, she called the fire department with a “desperate rescue plea” and was separated from the robot’s clutches by paramedics, according to the South Korean newspaper the Kyunghyang Shinmun. + +She escaped serious injury, although it is not known whether she has retained the autonomous cleaner’s services. + +Robot vacuum cleaners have grown in popularity in recent years, with US firm iRobot’s circular Roomba selling well over 10 million units in the 12 years since its debut in 2002. + +Panasonic recently unveiled Rulo, a triangular rival to Roomba that the Japanese firm says is more adept at sucking up dust from corners. + +The wheeled gadgets are equipped with sensors that enable them to steer clear of obstacles, avoid tumbling down stairs, and detect dust and other debris on the floor. They can also be programmed to seek out a recharging dock. + +Korean Biz Wire pointed out, however, that people from cultures in which it’s commonplace to sit or nap on the floor - such as Japan and South Korea – may be more vulnerable to vacuum robot rage.","1" +"Rumor Robert Plant Ripped Up $800 Million Contract To Reunite Led Zeppelin Called 'Rubbish'","A rumor that Robert Plant ripped up an $800 million contract offer to reunite Led Zeppelin has been called ""rubbish"" by Plant's publicist. + +As reported by the Daily Mirror, Plant, as well as former bandmates Jimmy Page and John Paul Jones, and Jason Bonham, son of the late drummer John Bonham, were offered $800 million by Virgin mogul Sir Richard Branson to perform a 35-date, three-city reunion tour. The story went that while Page, Jones and Bonham reportedly signed up immediately, Plant ripped up the papers right in front of his colleagues. Plant's publicist later debunked the report to The Guardian. + +If the news was real, it would have been a treat for Zeppelin fans. Each of the three original members were scheduled to make over $200 million just for performing, and another $100 million in merchandise split between them all. Scheduled to perform in London, Berlin and New Jersey, Branson was preparing to rename one of his jumbo jets ""The Starship,"" in order to fly the band to each of its destinations. He also wanted rebrand the jet's staircase as the ""Stairway to Heaven,"" and had an optional 45-date tour extension should the band agree. + +HuffPost Entertainment contacted representatives for Plant and Branson to see if they had any further comment on the story. This post will be updated if and when they provide a response. + +For more, head to The Guardian.","1" +"It's 'rubbish' that Robert Plant turned down £500m Led Zeppelin reformation offer, says publicist","Robert Plant’s publicist has described as “rubbish” a Daily Mirror report that he rejected a £500m Led Zeppelin reunion. The paper claims Jimmy Page and John Paul Jones had both signed on for the tour deal, bankrolled by Richard Branson, which would have featured John Bonham’s son Jason on drums. + +Branson had proposed 35 concerts spanning just three cities, according to the Mirror. The band would fly from London to Berlin to New Jersey in a specially outfitted jet: Branson wanted to recreate The Starship, from Led Zep’s heyday, selling tickets for the plane’s back rows at £100,000 per seat. + +“Branson tried to pull out all of the stops,” claimed the Mirror’s source, who claimed it was enough to convince Page, Jones, and Bonham to reprise their 2007 Celebration Day show, and that the band was even considering a further 45-night tour across five more venues. “But even [Branson’s] money was not enough to get Plant to sign up,” the source said. “[He] asked for 48 hours to think about it,” then ripped up the contract in front of a group of promoters. “His mind is made up and that’s that.” + +Rumours were rife earlier this year that Zeppelin would be reforming, and Page seemed newly furious at his former bandmate. “Everyone would love to play more concerts for the band,” Page said. “[Robert]’s just playing games, and I’m fed up with it, to be honest with you.” + +At the end of September, Page said a reunion was no longer “a possibility or on the cards”. He told journalists at an event to promote the reissues of Led Zeppelin IV and Houses of the Holy: “I’m not going to give a detail-by-detail account of what one person says or another person says, so there’s not much more I can say about that.” The guitarist explained that he is instead planning to revisit Led Zeppelin material on a 2015 solo tour. + +This story was amended on 10 November, following a comment from Robert Plant’s publicist","1" +"No, Robert Plant Didn’t Rip Up an $800 Million Contract","Led Zeppelin fans will be disappointed to learn that there’s no reunion tour and a story that appeared in the Daily Mirror suggesting that Robert Plant ripped up an $800 contract for such a gig is false, according to the Guardian. + +The reported tour was supposedly financed by Virgin founder Richard Branson, who wanted to turn one of his Virgin planes into a new iteration of “The Starship,” the jet​ the band used to tour in the 1970s. The group was to play 35 dates in three locales-- London, Berlin and New Jersey. + +Guitarist Jimmy Page and bassist John Paul Jones had signed on. And the late drummer John Bonham’s son Jason was to play drums for the band. “It was a no-brainer for them but Robert asked for 48 hours to think about it,” a source told the Daily Mirror. “When he said no and ripped up the paperwork he had been given, there was an enormous sense of shock. There is no way they can go ahead without him.” + +Turns out, the entire tale is “rubbish,” said Plant’s publicist to the Guardian, backing up what Page had said to the publication in September - a Zeppelin reunion was “[not] very likely.”","1" +"That powerful Lego letter to parents from the 1970s? It's real","A powerful message from Lego to parents from 1974 went viral over the weekend - and now the company has confirmed that it is indeed authentic. + +It was first posted on Reddit by user fryd_ first and informed parents the “urge to create is equally strong in all children: Boys and girls”. + +Speaking to i100.co.uk, Emma Owen of Lego UK and Ireland said the letter was part of a pamphlet showing a variety of Lego doll house products targeted at girls aged four and up from the 1970s. + +Null + +Commenting on the message, fryd_ first said “it seems like we’ve taken a step backwards” in forty years but Lego disagree. + +The text remains relevant to this day – our focus has always been, and remains to bring creative play experiences to all children in the world, based on the Lego brick and the Lego system – ultimately enabling children to build and create whatever they can imagine. + +Emma Owens of Lego +The letter from 1974 in full: + +To Parents + +The urge to create is equally strong in all children. Boys and girls. + +It’s the imagination that counts. Not skill. You build whatever comes into your head, the way you want it. A bed or a truck. A dolls house or a spaceship. + +A lot of boys like dolls houses. They’re more human than spaceships. A lot of girls prefer spaceships. They’re more exciting than dolls houses. + +The most important thing is to put the right material in their hands and let them create whatever appeals to them. + +It’s not the first time an old message from Lego has gone viral. This 1981 advert from the company was aimed at all children and shared widely online in January 2014. + +Null + +At the time, several commentators contrasted the image with the more feminised marketing for Lego Friends, which is aimed specifically at girls.","1" diff --git a/6. Data Visualization/Aula Power BI/Data/Background.jpg b/6. Data Visualization/Aula Power BI/Data/Background.jpg new file mode 100644 index 0000000..4201d5a Binary files /dev/null and b/6. 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Data Engineering/spark/README.md @@ -0,0 +1,156 @@ +# Aula de Spark (04/11) + +## Notebooks + +### Demo + +* `demo_jupyter_kernel_python.ipynb`: sobre como usar Spark dentro de um kernel Python. + +* `demo_pandas_vs_spark.ipynb`: sobre como o Spark têm performance inferior quando usado para processar um dataset pequeno. + +### Exercícios + +A seguinte ordem é sugerida para fazer os exercícios: + +* `exercicio_acoes_transformacoes.ipynb`: sobre a diferença entre transformações e ações. + +* `exercicio_livros_populares.ipynb`: sobre um pipeline de processamento de dados para selecionar os livros mais populares. Têm exemplos de uso de Spark SQL e DataFrame API. + +* `exercicio_spark_udfs.ipynb`: mostra exemplos simples de construção de user-defined-functions (`udf`s). + +* `exercicio_tags_co_ocorrentes.ipynb`: sobre um pipeline de processamento de dados para mostrar quais tags co-correm mais. Têm exemplos de joins e uso de `udf`s. + +## Instalação do Spark + +Atenção :warning:: Instruções válidas para sistema operacional Ubuntu 18.04. Podem haver variações para outros sistemas. + +```bash +sudo apt-get install openjdk-8-jdk-headless -qq > /dev/null +wget -q http://www-eu.apache.org/dist/spark/spark-2.4.4/spark-2.4.4-bin-hadoop2.7.tgz +sudo mv spark-2.4.4-bin-hadoop2.7 /opt +``` + +Adicionar ao arquivo `~/.bashrc`: +```bash +export PATH=$PATH:/opt/spark-2.4.4-bin-hadoop2.7/bin +export SPARK_HOME=/opt/spark-2.4.4-bin-hadoop2.7 +``` + +Em seguida, recarregar as configurações recém inseridas com o comando: `source ~/.bashrc`. + +De acordo com a [documentação atual](https://spark.apache.org/docs/latest/), Spark roda usando a versão 8 do Java. + +Caso você tenha uma versão do Java mais nova já instalada (você pode checar executando o comando `java -version`), rode o comando `sudo update-alternatives --config java` e selecione a versão correta. Aparecerá algo assim: + +![java_version](figs/java_version_manually_selection.png) + +## Instalação do kernel pyspark para uso no `jupyter notebook` + +Instale a biblioteca para python `pyspark` na mesma versão que o Spark: +```bash +pip install pyspark==2.4.4 +``` + +Crie um arquivo que conterá a configuração do seu kernel, com o seguinte conteúdo: +``` +{ + "display_name": "pyspark-kernel", + "language": "python", + "argv": [ + "", + "-m", + "IPython.kernel", + "-f", + "{connection_file}" + ], + "env": { + "SPARK_HOME": "/opt/spark-2.4.4-bin-hadoop2.7", + "PYTHONPATH": ":/opt/spark-2.4.4-bin-hadoop2.7/python/lib/py4j-2.4.4-src.zip", + "PYTHONSTARTUP": "/opt/spark-2.4.4-bin-hadoop2.7/python/pyspark/shell.py", + "PYSPARK_SUBMIT_ARGS": "--master local[*] --driver-memory 4G --conf spark.driver.maxResultSize=2G pyspark-shell", + "PYSPARK_PYTHON": "" + } +} +``` + +Note que você precisará substituir `` pelo caminho até o python (ex. `/usr/bin/python3`). É possível descobrir esse endereço, executando `which python` (ou `which python3`) no terminal. + +Pronto! Caso tudo tenha dado certo, você deve ser capaz de selecionar o kernel `pyspark-kernel` no jupyter notebook e o Spark deve estar configurado lá. + +![spark_ok](figs/spark_install_successful.png) + +### SETUP para Colab Notebook + +Na primeira célula, faça a instalação do Spark e da biblioteca `findspark`: +``` +!apt-get install openjdk-8-jdk-headless -qq > /dev/null +!wget -q http://www-eu.apache.org/dist/spark/spark-2.4.4/spark-2.4.4-bin-hadoop2.7.tgz +!tar xf spark-2.4.4-bin-hadoop2.7.tgz +!pip install -q findspark +``` + +Em outra célula, defina as variáveis de ambiente necessárias: +``` +import os +os.environ["JAVA_HOME"] = "/usr/lib/jvm/java-8-openjdk-amd64" +os.environ["SPARK_HOME"] = "/content/spark-2.4.4-bin-hadoop2.7" +``` + +Carregue a sessão do Spark e é só começar a usar! +```python +import findspark +from pyspark.sql import SparkSession + +findspark.init("spark-2.4.4-bin-hadoop2.7") +spark = SparkSession \ + .builder \ + .master("local[*]") \ + .getOrCreate() +``` + +### Setup Databricks + +#### Crie uma conta para usar o notebook da Databricks Community Edition + +Acesse [databricks](https://community.cloud.databricks.com/login.html). + +#### Importar notebooks + +No menu lateral esquerdo: +> Workspace > Shared > Import (clique na setinha) e digite um a um os endereços abaixo: + +* https://github.com/WoMakersCode/data-science-bootcamp/blob/master/7.%20Data%20Engineering/spark/demo_jupyter_kernel_python.ipynb + +* https://github.com/WoMakersCode/data-science-bootcamp/blob/master/7.%20Data%20Engineering/spark/demo_pandas_vs_spark.ipynb + +* https://github.com/WoMakersCode/data-science-bootcamp/blob/master/7.%20Data%20Engineering/spark/exercicio_acoes_transformacoes.ipynb + +* https://github.com/WoMakersCode/data-science-bootcamp/blob/master/7.%20Data%20Engineering/spark/exercicio_livros_populares.ipynb + +* https://github.com/WoMakersCode/data-science-bootcamp/blob/master/7.%20Data%20Engineering/spark/exercicio_tags_co_ocorrentes.ipynb + +#### Faça download dos arquivos necessários + +* https://github.com/zygmuntz/goodbooks-10k/blob/master/book_tags.csv + +* https://github.com/zygmuntz/goodbooks-10k/blob/master/books.csv + +* https://github.com/zygmuntz/goodbooks-10k/blob/master/ratings.csv + +* https://github.com/zygmuntz/goodbooks-10k/blob/master/tags.csv + +Agora, faça upload dos arquivos para o seu workspace do Databricks. + +> Data > Add Data (canto superior do menu) > Upload files. + +Selecione ou arraste os arquivos para a caixa cinza. + +**Observação:** caso prefira, você pode fazer download dos datasets [em versão reduzida neste link](https://github.com/cimarieta/goodbooks-10k/tree/master/reduced): `books.csv` e `ratings.csv`. + +#### Como acessar os arquivos que fizemos uploads no Databricks + +O caminho até eles será um pouco diferente. Exemplos: + +* `data/books.csv` --> `dbfs:/FileStore/tables/books.csv` + +* `data/ratings.csv` --> `dbfs:/FileStore/tables/ratings.csv` diff --git a/7. Data Engineering/spark/demo_jupyter_kernel_python.ipynb b/7. Data Engineering/spark/demo_jupyter_kernel_python.ipynb new file mode 100644 index 0000000..0230752 --- /dev/null +++ b/7. Data Engineering/spark/demo_jupyter_kernel_python.ipynb @@ -0,0 +1,120 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# import os\n", + "# os.environ['PYSPARK_SUBMIT_ARGS'] = '--packages ' \\\n", + "# 'org.apache.hadoop:hadoop-aws:2.7.2,mysql:mysql-connector-java:5.1.45,com.facebook.presto:presto-jdbc:0.210 ' \\\n", + "# '--driver-memory 3G ' \\\n", + "# '--conf \"spark.driver.maxResultSize=10g\" '\\\n", + "# 'pyspark-shell'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Descomente a linha abaixo e coloque o caminho onde o Spark foi instalado, caso você não tenha setado a variável de ambiente `$SPARK_HOME`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# import os\n", + "# os.environ['SPARK_HOME'] = '/opt/spark-2.4.4-bin-hadoop2.7'" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "from pyspark.sql import SparkSession" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "spark = SparkSession \\\n", + " .builder \\\n", + " .appName(\"MyFirstSparkSession\") \\\n", + " .getOrCreate()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
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" + ], + "text/plain": [ + " nome idade\n", + "0 fulanoA de tal 15\n", + "1 fulanoB de tal 20\n", + "2 fulanoC de mal 12" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "spark_df = spark.createDataFrame(df)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+--------------+-----+\n", + "| nome|idade|\n", + "+--------------+-----+\n", + "|fulanoA de tal| 15|\n", + "|fulanoB de tal| 20|\n", + "|fulanoC de mal| 12|\n", + "+--------------+-----+\n", + "\n" + ] + } + ], + "source": [ + "spark_df.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Comparação de tempo para cálculo da média de idade" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 176 µs, sys: 92 µs, total: 268 µs\n", + "Wall time: 273 µs\n" + ] + }, + { + "data": { + "text/plain": [ + "15.666666666666666" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "df['idade'].mean()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 7.07 ms, sys: 35 µs, total: 7.11 ms\n", + "Wall time: 330 ms\n" + ] + }, + { + "data": { + "text/plain": [ + "15.666666666666666" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "spark_df.select('idade').groupBy().mean().collect()[0][0]" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pyspark-kernel", + "language": "python", + "name": "spark" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.4" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/7. Data Engineering/spark/exemplo_spark_submit/demo_script.py b/7. Data Engineering/spark/exemplo_spark_submit/demo_script.py new file mode 100644 index 0000000..b3a48d4 --- /dev/null +++ b/7. Data Engineering/spark/exemplo_spark_submit/demo_script.py @@ -0,0 +1,15 @@ +import pandas as pd +from pyspark.sql import SparkSession + + +spark = SparkSession \ + .builder \ + .getOrCreate() + +data = {'nome': ['fulanoA de tal', 'fulanoB de tal', 'fulanoC de mal'], 'idade': [15, 20, 12]} + +df = pd.DataFrame(data) + +spark_df = spark.createDataFrame(df) + +spark_df.show() diff --git a/7. Data Engineering/spark/exercicio_acoes_transformacoes.ipynb b/7. Data Engineering/spark/exercicio_acoes_transformacoes.ipynb new file mode 100644 index 0000000..de51e3b --- /dev/null +++ b/7. Data Engineering/spark/exercicio_acoes_transformacoes.ipynb @@ -0,0 +1,574 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Verifique o que é **ação** e o que é **transformação**\n", + "\n", + "Você pode acessar a Spark UI para conferir também. Em geral, basta acessar o endereço `localhost:4040` em seu browser favorito, caso esteja executando o Spark localmente." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.DataFrame([('amarelo', 1), ('vermelho', 2), ('amarelo', 3)], columns=['cor', 'id'])" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " cor id\n", + "0 amarelo 1\n", + "1 vermelho 2\n", + "2 amarelo 3" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "spark_df = spark.createDataFrame(df).repartition(1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Ação ou Transformação?\n", + "\n", + "Se tiver dúvidas sobre o que cada função está fazendo, você pode consultar a [documentação](https://spark.apache.org/docs/latest/api/python/pyspark.sql.html)." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+--------+---+\n", + "| cor| id|\n", + "+--------+---+\n", + "| amarelo| 1|\n", + "|vermelho| 2|\n", + "| amarelo| 3|\n", + "+--------+---+\n", + "\n" + ] + } + ], + "source": [ + "spark_df.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "`show`\n", + "\n", + "Resposta: Ação" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "DataFrame[cor: string, id: bigint]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "spark_df.filter('cor = \"amarelo\"')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "`filter`\n", + "\n", + "Resposta: Transformação" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[Row(cor='amarelo', id=1), Row(cor='amarelo', id=3)]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "spark_df.filter('cor = \"amarelo\"').collect()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "`collect`\n", + "\n", + "Resposta: Ação" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "DataFrame[cor: string, count: bigint]" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "spark_df.groupBy('cor').count()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "`groupBy` + `count` (função de agregação)\n", + "\n", + "Resposta: Transformação" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "3" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "spark_df.count()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "`count`\n", + "\n", + "Resposta: Ação" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "DataFrame[cor: string]" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "spark_df.select('cor')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "`select`\n", + "\n", + "Resposta: Transformação" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[Row(cor='amarelo'), Row(cor='vermelho')]" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "spark_df.select('cor').take(2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "`take`\n", + "\n", + "Resposta: Ação" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "DataFrame[color: string, id: bigint]" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "spark_df.withColumnRenamed('cor', 'color')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "`withColumnRenamed`\n", + "\n", + "Resposta: Transformação" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Row(color='amarelo', id=1)" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "spark_df.withColumnRenamed('cor', 'color').first()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "`first`\n", + "\n", + "Resposta: Ação" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " color english_color\n", + "0 amarelo yellow\n", + "1 vermelho red" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "english_colors_pandas_df = pd.DataFrame([\n", + " {'color': 'amarelo', 'english_color': 'yellow'},\n", + " {'color': 'vermelho', 'english_color': 'red'}])\n", + "display(english_colors_pandas_df)\n", + "\n", + "english_colors_df = spark.createDataFrame(english_colors_pandas_df)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "DataFrame[color: string, id: bigint, english_color: string]" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "spark_df.withColumnRenamed('cor', 'color') \\\n", + " .join(english_colors_df, on='color', how='inner')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "`join`\n", + "\n", + "Resposta: Transformação" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "spark_df.withColumnRenamed('cor', 'color') \\\n", + " .join(english_colors_df, on='color', how='inner') \\\n", + " .write.mode('overwrite').csv('data/minha_tabela_de_cores', header=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "`write`\n", + "\n", + "Resposta: Ação" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+--------+---+-------------+\n", + "| color| id|english_color|\n", + "+--------+---+-------------+\n", + "| amarelo| 1| yellow|\n", + "| amarelo| 3| yellow|\n", + "|vermelho| 2| red|\n", + "+--------+---+-------------+\n", + "\n" + ] + } + ], + "source": [ + "spark.read.csv('data/minha_tabela_de_cores', header=True).show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## caso deseje, apague o arquivo csv gerado anteriormente\n", + "#!rm -rf data/minha_tabela_de_cores" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Desafio:** Encontre mais algum exemplo de ação e um de transformação" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Finalmente\n", + "\n", + "O uso no dia-a-dia vai te trazer a noção de quais métodos são ações e quais são transformações.\n", + "\n", + "Leia um pouco mais sobre ações e transformações [aqui](https://training.databricks.com/visualapi.pdf). Na página 7, há um slide com vários métodos divididos em ações e transformações. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pyspark-kernel", + "language": "python", + "name": "spark" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.4" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/7. Data Engineering/spark/exercicio_livros_populares.ipynb b/7. Data Engineering/spark/exercicio_livros_populares.ipynb new file mode 100644 index 0000000..6654370 --- /dev/null +++ b/7. Data Engineering/spark/exercicio_livros_populares.ipynb @@ -0,0 +1,665 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Exercício: livros populares \n", + "\n", + "Dado um dataset com avaliações de livros, vamos encontrar os mais populares por dois critérios:\n", + "\n", + "1. pela quantidade de avaliações\n", + "\n", + "2. pela média da nota da avaliação\n", + "\n", + "Motivação: construir um recomendador de livros populares." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Baixando o dataset\n", + "\n", + "Vamos usar o dataset `goodbooks-10k` criado para ser usado em problemas de recomendação. Ele contém cerca de 6 milhões de avaliações para os 10 mil livros mais populares.\n", + "\n", + "Leia mais no [fast-ml](http://fastml.com/goodbooks-10k-a-new-dataset-for-book-recommendations/).\n", + "\n", + "Se tiver erro na execução da célula abaixo, baixe manualmente os arquivos do [github](https://github.com/zygmuntz/goodbooks-10k) e coloque os arquivos `books.csv` e `ratings.csv` em uma pasta chamada `data` neste diretório." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# !mkdir -p data\n", + "# !wget -P data https://github.com/zygmuntz/goodbooks-10k/raw/master/books.csv\n", + "# !wget -P data https://github.com/zygmuntz/goodbooks-10k/raw/master/ratings.csv" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "path = 'data' # se local\n", + "#path = 'dbfs:/FileStore/tables' # se usar notebook databricks" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Leitura dos dados" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "books_df = spark.read.csv(f'{path}/books.csv', inferSchema=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "books_df.show(n=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### O que aconteceu aqui?\n", + "\n", + "Parece que os nomes das colunas não foram lidos propriamente" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "help(spark.read.csv)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Corrigindo o problema\n", + "\n", + "Se olharmos a documentação com calma, vamos ver esse pedaço:\n", + "\n", + "```\n", + " :param header: uses the first line as names of columns. If None is set, it uses the\n", + " default value, ``false``.\n", + "```\n", + "\n", + "**Exercício:** Inclua esses parâmetro (para lermos a primeira linha como `header`) e efetue novamente a leitura" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "books_df = ###" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "books_df.show(n=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Exercício:** Agora, faça a leitura do arquivo `data/ratings.csv`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ratings_df = ###" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ratings_df.show(n=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "É comum encontrar outros formatos de dados ao trabalhar com Spark. Saiba mais [aqui](https://eng.uber.com/hdfs-file-format-apache-spark/)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Dica para os próximos exercícios\n", + "\n", + "Para as próximas manipulações, é provável que usemos métodos do módulo `pyspark.sql.functions`, assim vamos importá-lo, juntamente com o módulo `pyspark.sql.types`.\n", + "\n", + "A documentação do módulo `pyspark.sql` pode ser encontrada [neste endereço](https://spark.apache.org/docs/2.4.4/api/python/pyspark.sql.html)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pyspark.sql.functions as F\n", + "import pyspark.sql.types as T" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Inspecionando os tipos de cada coluna\n", + "\n", + "É possível verificar o chamado `schema` do dataframe usando o método `printSchema`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ratings_df.printSchema()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note que, se não tivéssemos passado o parâmetro `inferSchema=True`, então, os tipos das colunas seriam diferentes:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "spark.read.csv(f'{path}/ratings.csv', header=True).printSchema()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Em nosso caso, o Spark conseguiu inferir corretamente os tipos de cada uma das colunas, mas caso ele não tivesse conseguido, poderíamos tentar forçar a conversão através do uso da função [cast](https://spark.apache.org/docs/2.4.4/api/python/_modules/pyspark/sql/column.html#Column.cast).\n", + "\n", + "Por exemplo, para transformar a coluna `string` em inteiro, faríamos:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "spark.read.csv(f'{path}/ratings.csv', header=True).select('user_id', 'book_id', F.col('rating').cast('int')).printSchema()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Parte 1: quantidade de avaliações de cada um dos livros" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "count_reviews_df = ratings_df \\\n", + " .select('book_id', 'rating') \\\n", + " .groupBy('book_id') \\\n", + " .count()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "count_reviews_df.show(n=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Maneiras alternativas para fazer o mesmo cálculo\n", + "\n", + "```python\n", + "count_reviews_df = ratings_df \\\n", + " .groupBy('book_id') \\\n", + " .agg(F.count('rating').alias('count'))\n", + "```\n", + "\n", + "Também é possível usar Spark SQL:\n", + "```python\n", + "ratings_df.createOrReplaceTempView('ratings')\n", + "\n", + "count_reviews_query = \"\"\"\n", + " select book_id,\n", + " count(rating) as count\n", + " from ratings\n", + " group by book_id\n", + "\"\"\"\n", + "\n", + "count_reviews_df = spark.sql(count_reviews_query)\n", + "```" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Parte 2: média das notas de avaliações de cada um dos livros\n", + "\n", + "**Exercício:** calcule essa média a partir do dataframe `ratings_df`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "avg_ratings_df = ###" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "avg_ratings_df.show(n=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Exercício:** faça o mesmo cálculo usando Spark SQL" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ratings_df.createOrReplaceTempView('ratings') # se você já rodou essa linha anteriormente, não é necessário rodá-la novamente" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "avg_ratings_query = ###" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "spark.sql(avg_ratings_query).show(n=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note que `spark.sql(avg_ratings_query)` é um Spark DataFrame, assim como `avg_ratings_df`." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Parte 3: junção dos dados de quantidade de avaliações e médias das notas das avaliações\n", + "\n", + "Queremos um dataframe que contenha `book_id`, `count` e `mean_rating`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "count_avg_ratings_df = count_reviews_df \\\n", + " .join(avg_ratings_df, on='book_id', how='inner')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "count_avg_ratings_df.show(n=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Parte 4: junção dos dados de título e imagem\n", + "\n", + "Gostaríamos agora de incluir no dataframe `count_avg_ratings_df` as colunas `title` e `image_url`.\n", + "\n", + "**Exercício:** faça outra operação de `join`, desta vez utilizando os dataframes `count_avg_ratings_df` e `books_df` para incluir no dataframe as colunas desejadas." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "books_df.printSchema()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "count_avg_ratings_df = ###" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "count_avg_ratings_df.show(n=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Parte 5: visualização dos livros mais populares " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from pyspark.sql.window import Window" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "count_ordered_window = Window.orderBy(F.desc('count'))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "count_avg_ratings_df = count_avg_ratings_df \\\n", + " .withColumn('count_rank', F.row_number().over(count_ordered_window))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Exercício:** da mesma forma, crie uma coluna chamada `avg_rank`, que calcula o rank segundo a coluna `mean_rating`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "avg_ordered_window = ###" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "count_avg_ratings_df = ###" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "count_avg_ratings_df.orderBy('count', ascending=False).show(n=2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "count_avg_ratings_df.orderBy('mean_rating', ascending=False).show(n=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Exercício:** formate a tabela de modo a ver os dez livros mais populares de acordo com cada método\n", + "\n", + "Ao final, sua tabela deve ser como a abaixo:\n", + "\n", + "|rank|according_to_count |according_to_avg |\n", + "|----|-----------------------------------------------------------|-----------------------------------------------------------------|\n", + "|1 |The Hunger Games (The Hunger Games, #1) |The Complete Calvin and Hobbes |\n", + "|2 |Harry Potter and the Sorcerer's Stone (Harry Potter, #1) |ESV Study Bible |\n", + "|3 |To Kill a Mockingbird |Attack of the Deranged Mutant Killer Monster Snow Goons |" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "top_10 = ###" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "top_10.show(truncate=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Extra: visualização das capas dos livros\n", + "\n", + "Para essa seção, é necessário ter instalado a biblioteca [ipywidgets](https://ipywidgets.readthedocs.io/en/latest/user_install.html)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from ipywidgets import widgets, Layout\n", + "from IPython.display import clear_output, HTML, Markdown, display\n", + "import requests" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "top_10_imgs = count_avg_ratings_df.select(F.col('count_rank').alias('rank'), F.col('image_url').alias('according_to_count')) \\\n", + " .join(\n", + " count_avg_ratings_df.select(F.col('avg_rank').alias('rank'), F.col('image_url').alias('according_to_avg')),\n", + " on='rank') \\\n", + " .filter('rank <= 10')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "top_10_imgs.cache()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "top_10_imgs.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def get_recommended_products(method, n):\n", + " imgs = top_10_imgs.select('rank', F.col(f'according_to_{method}').alias('url')).limit(n).collect()\n", + " return [(img.rank, img.url) for img in imgs]\n", + "\n", + "def printmd(string):\n", + " display(Markdown(string))\n", + "\n", + "def make_horizontal_box(children): return widgets.HBox(children)\n", + "\n", + "def make_vertical_box(children, width='auto', height='600px'):\n", + " return widgets.VBox(children, layout=Layout(width=width, height=height))\n", + "\n", + "def image_widget(url, layout=Layout(height='250px', width='150px', display='flex', align_items='center', border='solid white')):\n", + " img_content = requests.get(url).content\n", + " return widgets.Image(value=img_content, layout=layout)\n", + "\n", + "def widgets_to_render(method, n):\n", + " layout = Layout(height='250px', width='150px', display='flex', align_items='center', border='solid orchid')\n", + " return [image_widget(elem[1]) if i > 0 else image_widget(elem[1], layout=layout) \n", + " for i, elem in enumerate(get_recommended_products(method, n))]\n", + "\n", + "def print_on_button(string, color='lightblue'):\n", + " button = widgets.Button(description=string, layout=Layout(width='300px'))\n", + " button.style.button_color = color\n", + " return button\n", + "\n", + "def display_both_recommendations(n=3):\n", + " boxes = [\n", + " print_on_button('highest_count', color='lightblue'),\n", + " make_horizontal_box(widgets_to_render('count', n))\n", + " ]\n", + " boxes += [print_on_button('highest_avg', color='lightpink'),\n", + " make_horizontal_box(widgets_to_render('avg', n))]\n", + " display(make_vertical_box(boxes))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "display_both_recommendations(n=5)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pyspark-kernel", + "language": "python", + "name": "spark" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.4" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/7. Data Engineering/spark/exercicio_livros_populares_gabarito.ipynb b/7. Data Engineering/spark/exercicio_livros_populares_gabarito.ipynb new file mode 100644 index 0000000..8207f14 --- /dev/null +++ b/7. Data Engineering/spark/exercicio_livros_populares_gabarito.ipynb @@ -0,0 +1,1085 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Exercício: livros populares \n", + "\n", + "Dado um dataset com avaliações de livros, vamos encontrar os mais populares por dois critérios:\n", + "\n", + "1. pela quantidade de avaliações\n", + "\n", + "2. pela média da nota da avaliação\n", + "\n", + "Motivação: construir um recomendador de livros populares." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Baixando o dataset\n", + "\n", + "Vamos usar o dataset `goodbooks-10k` criado para ser usado em problemas de recomendação. Ele contém cerca de 6 milhões de avaliações para os 10 mil livros mais populares.\n", + "\n", + "Leia mais no [fast-ml](http://fastml.com/goodbooks-10k-a-new-dataset-for-book-recommendations/).\n", + "\n", + "Se tiver erro na execução da célula abaixo, baixe manualmente os arquivos do [github](https://github.com/zygmuntz/goodbooks-10k) e coloque os arquivos `books.csv` e `ratings.csv` em uma pasta chamada `data` neste diretório." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# !mkdir -p data\n", + "# !wget -P data https://github.com/zygmuntz/goodbooks-10k/raw/master/books.csv\n", + "# !wget -P data https://github.com/zygmuntz/goodbooks-10k/raw/master/ratings.csv" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "path = 'data' # se local\n", + "#path = 'dbfs:/FileStore/tables' # se usar notebook databricks" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Leitura dos dados" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "books_df = spark.read.csv(f'{path}/books.csv', inferSchema=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+-------+-----------------+------------+-------+-----------+---------+-----------------+---------------+--------------------+----------------+--------------------+-------------+--------------+-------------+------------------+--------------------+---------+---------+---------+---------+---------+--------------------+--------------------+\n", + "| _c0| _c1| _c2| _c3| _c4| _c5| _c6| _c7| _c8| _c9| _c10| _c11| _c12| _c13| _c14| _c15| _c16| _c17| _c18| _c19| _c20| _c21| _c22|\n", + "+-------+-----------------+------------+-------+-----------+---------+-----------------+---------------+--------------------+----------------+--------------------+-------------+--------------+-------------+------------------+--------------------+---------+---------+---------+---------+---------+--------------------+--------------------+\n", + "|book_id|goodreads_book_id|best_book_id|work_id|books_count| isbn| isbn13| authors|original_publicat...| original_title| title|language_code|average_rating|ratings_count|work_ratings_count|work_text_reviews...|ratings_1|ratings_2|ratings_3|ratings_4|ratings_5| image_url| small_image_url|\n", + "| 1| 2767052| 2767052|2792775| 272|439023483|9.78043902348e+12|Suzanne Collins| 2008.0|The Hunger Games|The Hunger Games ...| eng| 4.34| 4780653| 4942365| 155254| 66715| 127936| 560092| 1481305| 2706317|https://images.gr...|https://images.gr...|\n", + "+-------+-----------------+------------+-------+-----------+---------+-----------------+---------------+--------------------+----------------+--------------------+-------------+--------------+-------------+------------------+--------------------+---------+---------+---------+---------+---------+--------------------+--------------------+\n", + "only showing top 2 rows\n", + "\n" + ] + } + ], + "source": [ + "books_df.show(n=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### O que aconteceu aqui?\n", + "\n", + "Parece que os nomes das colunas não foram lidos propriamente" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Help on method csv in module pyspark.sql.readwriter:\n", + "\n", + "csv(path, schema=None, sep=None, encoding=None, quote=None, escape=None, comment=None, header=None, inferSchema=None, ignoreLeadingWhiteSpace=None, ignoreTrailingWhiteSpace=None, nullValue=None, nanValue=None, positiveInf=None, negativeInf=None, dateFormat=None, timestampFormat=None, maxColumns=None, maxCharsPerColumn=None, maxMalformedLogPerPartition=None, mode=None, columnNameOfCorruptRecord=None, multiLine=None, charToEscapeQuoteEscaping=None, samplingRatio=None, enforceSchema=None, emptyValue=None) method of pyspark.sql.readwriter.DataFrameReader instance\n", + " Loads a CSV file and returns the result as a :class:`DataFrame`.\n", + " \n", + " This function will go through the input once to determine the input schema if\n", + " ``inferSchema`` is enabled. To avoid going through the entire data once, disable\n", + " ``inferSchema`` option or specify the schema explicitly using ``schema``.\n", + " \n", + " :param path: string, or list of strings, for input path(s),\n", + " or RDD of Strings storing CSV rows.\n", + " :param schema: an optional :class:`pyspark.sql.types.StructType` for the input schema\n", + " or a DDL-formatted string (For example ``col0 INT, col1 DOUBLE``).\n", + " :param sep: sets a single character as a separator for each field and value.\n", + " If None is set, it uses the default value, ``,``.\n", + " :param encoding: decodes the CSV files by the given encoding type. If None is set,\n", + " it uses the default value, ``UTF-8``.\n", + " :param quote: sets a single character used for escaping quoted values where the\n", + " separator can be part of the value. If None is set, it uses the default\n", + " value, ``\"``. If you would like to turn off quotations, you need to set an\n", + " empty string.\n", + " :param escape: sets a single character used for escaping quotes inside an already\n", + " quoted value. If None is set, it uses the default value, ``\\``.\n", + " :param comment: sets a single character used for skipping lines beginning with this\n", + " character. By default (None), it is disabled.\n", + " :param header: uses the first line as names of columns. If None is set, it uses the\n", + " default value, ``false``.\n", + " :param inferSchema: infers the input schema automatically from data. It requires one extra\n", + " pass over the data. If None is set, it uses the default value, ``false``.\n", + " :param enforceSchema: If it is set to ``true``, the specified or inferred schema will be\n", + " forcibly applied to datasource files, and headers in CSV files will be\n", + " ignored. If the option is set to ``false``, the schema will be\n", + " validated against all headers in CSV files or the first header in RDD\n", + " if the ``header`` option is set to ``true``. Field names in the schema\n", + " and column names in CSV headers are checked by their positions\n", + " taking into account ``spark.sql.caseSensitive``. If None is set,\n", + " ``true`` is used by default. Though the default value is ``true``,\n", + " it is recommended to disable the ``enforceSchema`` option\n", + " to avoid incorrect results.\n", + " :param ignoreLeadingWhiteSpace: A flag indicating whether or not leading whitespaces from\n", + " values being read should be skipped. If None is set, it\n", + " uses the default value, ``false``.\n", + " :param ignoreTrailingWhiteSpace: A flag indicating whether or not trailing whitespaces from\n", + " values being read should be skipped. If None is set, it\n", + " uses the default value, ``false``.\n", + " :param nullValue: sets the string representation of a null value. If None is set, it uses\n", + " the default value, empty string. Since 2.0.1, this ``nullValue`` param\n", + " applies to all supported types including the string type.\n", + " :param nanValue: sets the string representation of a non-number value. If None is set, it\n", + " uses the default value, ``NaN``.\n", + " :param positiveInf: sets the string representation of a positive infinity value. If None\n", + " is set, it uses the default value, ``Inf``.\n", + " :param negativeInf: sets the string representation of a negative infinity value. If None\n", + " is set, it uses the default value, ``Inf``.\n", + " :param dateFormat: sets the string that indicates a date format. Custom date formats\n", + " follow the formats at ``java.text.SimpleDateFormat``. This\n", + " applies to date type. If None is set, it uses the\n", + " default value, ``yyyy-MM-dd``.\n", + " :param timestampFormat: sets the string that indicates a timestamp format. Custom date\n", + " formats follow the formats at ``java.text.SimpleDateFormat``.\n", + " This applies to timestamp type. If None is set, it uses the\n", + " default value, ``yyyy-MM-dd'T'HH:mm:ss.SSSXXX``.\n", + " :param maxColumns: defines a hard limit of how many columns a record can have. If None is\n", + " set, it uses the default value, ``20480``.\n", + " :param maxCharsPerColumn: defines the maximum number of characters allowed for any given\n", + " value being read. If None is set, it uses the default value,\n", + " ``-1`` meaning unlimited length.\n", + " :param maxMalformedLogPerPartition: this parameter is no longer used since Spark 2.2.0.\n", + " If specified, it is ignored.\n", + " :param mode: allows a mode for dealing with corrupt records during parsing. If None is\n", + " set, it uses the default value, ``PERMISSIVE``. Note that Spark tries to\n", + " parse only required columns in CSV under column pruning. Therefore, corrupt\n", + " records can be different based on required set of fields. This behavior can\n", + " be controlled by ``spark.sql.csv.parser.columnPruning.enabled``\n", + " (enabled by default).\n", + " \n", + " * ``PERMISSIVE`` : when it meets a corrupted record, puts the malformed string \\\n", + " into a field configured by ``columnNameOfCorruptRecord``, and sets other \\\n", + " fields to ``null``. To keep corrupt records, an user can set a string type \\\n", + " field named ``columnNameOfCorruptRecord`` in an user-defined schema. If a \\\n", + " schema does not have the field, it drops corrupt records during parsing. \\\n", + " A record with less/more tokens than schema is not a corrupted record to CSV. \\\n", + " When it meets a record having fewer tokens than the length of the schema, \\\n", + " sets ``null`` to extra fields. When the record has more tokens than the \\\n", + " length of the schema, it drops extra tokens.\n", + " * ``DROPMALFORMED`` : ignores the whole corrupted records.\n", + " * ``FAILFAST`` : throws an exception when it meets corrupted records.\n", + " \n", + " :param columnNameOfCorruptRecord: allows renaming the new field having malformed string\n", + " created by ``PERMISSIVE`` mode. This overrides\n", + " ``spark.sql.columnNameOfCorruptRecord``. If None is set,\n", + " it uses the value specified in\n", + " ``spark.sql.columnNameOfCorruptRecord``.\n", + " :param multiLine: parse records, which may span multiple lines. If None is\n", + " set, it uses the default value, ``false``.\n", + " :param charToEscapeQuoteEscaping: sets a single character used for escaping the escape for\n", + " the quote character. If None is set, the default value is\n", + " escape character when escape and quote characters are\n", + " different, ``\\0`` otherwise.\n", + " :param samplingRatio: defines fraction of rows used for schema inferring.\n", + " If None is set, it uses the default value, ``1.0``.\n", + " :param emptyValue: sets the string representation of an empty value. If None is set, it uses\n", + " the default value, empty string.\n", + " \n", + " >>> df = spark.read.csv('python/test_support/sql/ages.csv')\n", + " >>> df.dtypes\n", + " [('_c0', 'string'), ('_c1', 'string')]\n", + " >>> rdd = sc.textFile('python/test_support/sql/ages.csv')\n", + " >>> df2 = spark.read.csv(rdd)\n", + " >>> df2.dtypes\n", + " [('_c0', 'string'), ('_c1', 'string')]\n", + " \n", + " .. versionadded:: 2.0\n", + "\n" + ] + } + ], + "source": [ + "help(spark.read.csv)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Corrigindo o problema\n", + "\n", + "Se olharmos a documentação com calma, vamos ver esse pedaço:\n", + "\n", + "```\n", + " :param header: uses the first line as names of columns. If None is set, it uses the\n", + " default value, ``false``.\n", + "```\n", + "\n", + "**Exercício:** Inclua esses parâmetro (para lermos a primeira linha como `header`) e efetue novamente a leitura" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "books_df = spark.read.csv(f'{path}/books.csv', inferSchema=True, header=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+-------+-----------------+------------+-------+-----------+---------+----------------+--------------------+-------------------------+--------------------+--------------------+-------------+--------------+-------------+------------------+-----------------------+---------+---------+---------+---------+---------+--------------------+--------------------+\n", + "|book_id|goodreads_book_id|best_book_id|work_id|books_count| isbn| isbn13| authors|original_publication_year| original_title| title|language_code|average_rating|ratings_count|work_ratings_count|work_text_reviews_count|ratings_1|ratings_2|ratings_3|ratings_4|ratings_5| image_url| small_image_url|\n", + "+-------+-----------------+------------+-------+-----------+---------+----------------+--------------------+-------------------------+--------------------+--------------------+-------------+--------------+-------------+------------------+-----------------------+---------+---------+---------+---------+---------+--------------------+--------------------+\n", + "| 1| 2767052| 2767052|2792775| 272|439023483|9.78043902348E12| Suzanne Collins| 2008.0| The Hunger Games|The Hunger Games ...| eng| 4.34| 4780653| 4942365| 155254| 66715.0| 127936| 560092| 1481305| 2706317|https://images.gr...|https://images.gr...|\n", + "| 2| 3| 3|4640799| 491|439554934|9.78043955493E12|J.K. Rowling, Mar...| 1997.0|Harry Potter and ...|Harry Potter and ...| eng| 4.44| 4602479| 4800065| 75867| 75504.0| 101676| 455024| 1156318| 3011543|https://images.gr...|https://images.gr...|\n", + "+-------+-----------------+------------+-------+-----------+---------+----------------+--------------------+-------------------------+--------------------+--------------------+-------------+--------------+-------------+------------------+-----------------------+---------+---------+---------+---------+---------+--------------------+--------------------+\n", + "only showing top 2 rows\n", + "\n" + ] + } + ], + "source": [ + "books_df.show(n=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Exercício:** Agora, faça a leitura do arquivo `data/ratings.csv`" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "ratings_df = spark.read.csv(f'{path}/ratings.csv', inferSchema=True, header=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+-------+-------+------+\n", + "|user_id|book_id|rating|\n", + "+-------+-------+------+\n", + "| 1| 258| 5|\n", + "| 2| 4081| 4|\n", + "+-------+-------+------+\n", + "only showing top 2 rows\n", + "\n" + ] + } + ], + "source": [ + "ratings_df.show(n=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "É comum encontrar outros formatos de dados ao trabalhar com Spark. Saiba mais [aqui](https://eng.uber.com/hdfs-file-format-apache-spark/)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Dica para os próximos exercícios\n", + "\n", + "Para as próximas manipulações, é provável que usemos métodos do módulo `pyspark.sql.functions`, assim vamos importá-lo, juntamente com o módulo `pyspark.sql.types`.\n", + "\n", + "A documentação do módulo `pyspark.sql` pode ser encontrada [neste endereço](https://spark.apache.org/docs/2.4.4/api/python/pyspark.sql.html)." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "import pyspark.sql.functions as F\n", + "import pyspark.sql.types as T" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Inspecionando os tipos de cada coluna\n", + "\n", + "É possível verificar o chamado `schema` do dataframe usando o método `printSchema`" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "root\n", + " |-- user_id: integer (nullable = true)\n", + " |-- book_id: integer (nullable = true)\n", + " |-- rating: integer (nullable = true)\n", + "\n" + ] + } + ], + "source": [ + "ratings_df.printSchema()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note que, se não tivéssemos passado o parâmetro `inferSchema=True`, então, os tipos das colunas seriam diferentes:" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "root\n", + " |-- user_id: string (nullable = true)\n", + " |-- book_id: string (nullable = true)\n", + " |-- rating: string (nullable = true)\n", + "\n" + ] + } + ], + "source": [ + "spark.read.csv('data/ratings.csv', header=True).printSchema()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Em nosso caso, o Spark conseguiu inferir corretamente os tipos de cada uma das colunas, mas caso ele não tivesse conseguido, poderíamos tentar forçar a conversão através do uso da função [cast](https://spark.apache.org/docs/2.4.4/api/python/_modules/pyspark/sql/column.html#Column.cast).\n", + "\n", + "Por exemplo, para transformar a coluna `string` em inteiro, faríamos:" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "root\n", + " |-- user_id: string (nullable = true)\n", + " |-- book_id: string (nullable = true)\n", + " |-- rating: integer (nullable = true)\n", + "\n" + ] + } + ], + "source": [ + "spark.read.csv('data/ratings.csv', header=True).select('user_id', 'book_id', F.col('rating').cast('int')).printSchema()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Parte 1: quantidade de avaliações de cada um dos livros" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "count_reviews_df = ratings_df \\\n", + " .select('book_id', 'rating') \\\n", + " .groupBy('book_id') \\\n", + " .count()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+-------+-----+\n", + "|book_id|count|\n", + "+-------+-----+\n", + "| 471| 2725|\n", + "| 148| 5171|\n", + "+-------+-----+\n", + "only showing top 2 rows\n", + "\n" + ] + } + ], + "source": [ + "count_reviews_df.show(n=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Maneiras alternativas para fazer o mesmo cálculo\n", + "\n", + "```python\n", + "count_reviews_df = ratings_df \\\n", + " .groupBy('book_id') \\\n", + " .agg(F.count('rating').alias('count'))\n", + "```\n", + "\n", + "Também é possível usar Spark SQL:\n", + "```python\n", + "ratings_df.createOrReplaceTempView('ratings')\n", + "\n", + "count_reviews_query = \"\"\"\n", + " select book_id,\n", + " count(rating) as count\n", + " from ratings\n", + " group by book_id\n", + "\"\"\"\n", + "\n", + "count_reviews_df = spark.sql(count_reviews_query)\n", + "```" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Parte 2: média das notas de avaliações de cada um dos livros\n", + "\n", + "**Exercício:** calcule essa média a partir do dataframe `ratings_df`" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "avg_ratings_df = ratings_df \\\n", + " .select('book_id', 'rating') \\\n", + " .groupBy('book_id') \\\n", + " .agg(F.avg('rating').alias('mean_rating'))" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+-------+------------------+\n", + "|book_id| mean_rating|\n", + "+-------+------------------+\n", + "| 471| 3.757798165137615|\n", + "| 148|3.7745116998646298|\n", + "+-------+------------------+\n", + "only showing top 2 rows\n", + "\n" + ] + } + ], + "source": [ + "avg_ratings_df.show(n=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Exercício:** faça o mesmo cálculo usando Spark SQL" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "ratings_df.createOrReplaceTempView('ratings') # se você já rodou essa linha anteriormente, não é necessário rodá-la novamente" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "avg_ratings_query = \"\"\"\n", + " select book_id,\n", + " avg(rating) as mean_rating\n", + " from ratings\n", + " group by book_id\n", + "\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+-------+------------------+\n", + "|book_id| mean_rating|\n", + "+-------+------------------+\n", + "| 471| 3.757798165137615|\n", + "| 148|3.7745116998646298|\n", + "+-------+------------------+\n", + "only showing top 2 rows\n", + "\n" + ] + } + ], + "source": [ + "spark.sql(avg_ratings_query).show(n=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note que `spark.sql(avg_ratings_query)` é um Spark DataFrame, assim como `avg_ratings_df`." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Parte 3: junção dos dados de quantidade de avaliações e médias das notas das avaliações\n", + "\n", + "Queremos um dataframe que contenha `book_id`, `count` e `mean_rating`." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "count_avg_ratings_df = count_reviews_df \\\n", + " .join(avg_ratings_df, on='book_id', how='inner')" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+-------+-----+------------------+\n", + "|book_id|count| mean_rating|\n", + "+-------+-----+------------------+\n", + "| 148| 5171|3.7745116998646298|\n", + "| 463| 2472|4.1549352750809065|\n", + "+-------+-----+------------------+\n", + "only showing top 2 rows\n", + "\n" + ] + } + ], + "source": [ + "count_avg_ratings_df.show(n=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Parte 4: junção dos dados de título e imagem\n", + "\n", + "Gostaríamos agora de incluir no dataframe `count_avg_ratings_df` as colunas `title` e `image_url`.\n", + "\n", + "**Exercício:** faça outra operação de `join`, desta vez utilizando os dataframes `count_avg_ratings_df` e `books_df` para incluir no dataframe as colunas desejadas." + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "root\n", + " |-- book_id: integer (nullable = true)\n", + " |-- goodreads_book_id: integer (nullable = true)\n", + " |-- best_book_id: integer (nullable = true)\n", + " |-- work_id: integer (nullable = true)\n", + " |-- books_count: integer (nullable = true)\n", + " |-- isbn: string (nullable = true)\n", + " |-- isbn13: double (nullable = true)\n", + " |-- authors: string (nullable = true)\n", + " |-- original_publication_year: double (nullable = true)\n", + " |-- original_title: string (nullable = true)\n", + " |-- title: string (nullable = true)\n", + " |-- language_code: string (nullable = true)\n", + " |-- average_rating: string (nullable = true)\n", + " |-- ratings_count: string (nullable = true)\n", + " |-- work_ratings_count: string (nullable = true)\n", + " |-- work_text_reviews_count: string (nullable = true)\n", + " |-- ratings_1: double (nullable = true)\n", + " |-- ratings_2: integer (nullable = true)\n", + " |-- ratings_3: integer (nullable = true)\n", + " |-- ratings_4: integer (nullable = true)\n", + " |-- ratings_5: integer (nullable = true)\n", + " |-- image_url: string (nullable = true)\n", + " |-- small_image_url: string (nullable = true)\n", + "\n" + ] + } + ], + "source": [ + "books_df.printSchema()" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "count_avg_ratings_df = count_avg_ratings_df \\\n", + " .join(books_df.select('book_id', 'title', 'image_url'), on='book_id')" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+-------+-----+------------------+--------------------+--------------------+\n", + "|book_id|count| mean_rating| title| image_url|\n", + "+-------+-----+------------------+--------------------+--------------------+\n", + "| 148| 5171|3.7745116998646298|Girl with a Pearl...|https://images.gr...|\n", + "| 463| 2472|4.1549352750809065|Dragonfly in Ambe...|https://images.gr...|\n", + "+-------+-----+------------------+--------------------+--------------------+\n", + "only showing top 2 rows\n", + "\n" + ] + } + ], + "source": [ + "count_avg_ratings_df.show(n=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Parte 5: visualização dos livros mais populares " + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "from pyspark.sql.window import Window" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "count_ordered_window = Window.orderBy(F.desc('count'))" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "count_avg_ratings_df = count_avg_ratings_df \\\n", + " .withColumn('count_rank', F.row_number().over(count_ordered_window))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Exercício:** da mesma forma, crie uma coluna chamada `avg_rank`, que calcula o rank segundo a coluna `mean_rating`" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "avg_ordered_window = Window.orderBy(F.desc('mean_rating'))" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [], + "source": [ + "count_avg_ratings_df = count_avg_ratings_df \\\n", + " .withColumn('avg_rank', F.row_number().over(avg_ordered_window))" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+-------+-----+------------------+--------------------+--------------------+----------+--------+\n", + "|book_id|count| mean_rating| title| image_url|count_rank|avg_rank|\n", + "+-------+-----+------------------+--------------------+--------------------+----------+--------+\n", + "| 1|22806|4.2797070946242215|The Hunger Games ...|https://images.gr...| 1| 794|\n", + "| 2|21850| 4.351350114416476|Harry Potter and ...|https://images.gr...| 2| 440|\n", + "+-------+-----+------------------+--------------------+--------------------+----------+--------+\n", + "only showing top 2 rows\n", + "\n" + ] + } + ], + "source": [ + "count_avg_ratings_df.orderBy('count', ascending=False).show(n=2)" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+-------+-----+-----------------+--------------------+--------------------+----------+--------+\n", + "|book_id|count| mean_rating| title| image_url|count_rank|avg_rank|\n", + "+-------+-----+-----------------+--------------------+--------------------+----------+--------+\n", + "| 3628| 482|4.829875518672199|The Complete Calv...|https://images.gr...| 2634| 1|\n", + "| 7947| 88|4.818181818181818| ESV Study Bible|https://images.gr...| 9735| 2|\n", + "+-------+-----+-----------------+--------------------+--------------------+----------+--------+\n", + "only showing top 2 rows\n", + "\n" + ] + } + ], + "source": [ + "count_avg_ratings_df.orderBy('mean_rating', ascending=False).show(n=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Exercício:** formate a tabela de modo a ver os dez livros mais populares de acordo com cada método\n", + "\n", + "Ao final, sua tabela deve ser como a abaixo:\n", + "\n", + "|rank|according_to_count |according_to_avg |\n", + "|----|-----------------------------------------------------------|-----------------------------------------------------------------|\n", + "|1 |The Hunger Games (The Hunger Games, #1) |The Complete Calvin and Hobbes |\n", + "|2 |Harry Potter and the Sorcerer's Stone (Harry Potter, #1) |ESV Study Bible |\n", + "|3 |To Kill a Mockingbird |Attack of the Deranged Mutant Killer Monster Snow Goons |" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [], + "source": [ + "top_10 = count_avg_ratings_df.select(F.col('count_rank').alias('rank'), F.col('title').alias('according_to_count')) \\\n", + " .join(\n", + " count_avg_ratings_df.select(F.col('avg_rank').alias('rank'), F.col('title').alias('according_to_avg')),\n", + " on='rank') \\\n", + " .filter('rank <= 10')" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+----+-----------------------------------------------------------+-----------------------------------------------------------------+\n", + "|rank|according_to_count |according_to_avg |\n", + "+----+-----------------------------------------------------------+-----------------------------------------------------------------+\n", + "|1 |The Hunger Games (The Hunger Games, #1) |The Complete Calvin and Hobbes |\n", + "|2 |Harry Potter and the Sorcerer's Stone (Harry Potter, #1) |ESV Study Bible |\n", + "|3 |To Kill a Mockingbird |Attack of the Deranged Mutant Killer Monster Snow Goons |\n", + "|4 |Twilight (Twilight, #1) |The Indispensable Calvin and Hobbes |\n", + "|5 |The Great Gatsby |The Revenge of the Baby-Sat |\n", + "|6 |Catching Fire (The Hunger Games, #2) |There's Treasure Everywhere: A Calvin and Hobbes Collection |\n", + "|7 |Mockingjay (The Hunger Games, #3) |The Authoritative Calvin and Hobbes: A Calvin and Hobbes Treasury|\n", + "|8 |Harry Potter and the Prisoner of Azkaban (Harry Potter, #3)|It's a Magical World: A Calvin and Hobbes Collection |\n", + "|9 |Harry Potter and the Chamber of Secrets (Harry Potter, #2) |Harry Potter Boxed Set, Books 1-5 (Harry Potter, #1-5) |\n", + "|10 |The Hobbit |The Calvin and Hobbes Tenth Anniversary Book |\n", + "+----+-----------------------------------------------------------+-----------------------------------------------------------------+\n", + "\n" + ] + } + ], + "source": [ + "top_10.show(truncate=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Extra: visualização das capas dos livros\n", + "\n", + "Para essa seção, é necessário ter instalado a biblioteca [ipywidgets](https://ipywidgets.readthedocs.io/en/latest/user_install.html).\n", + "\n", + "A ideia é ao que final, vejamos algo assim:\n", + "\n", + "![recomendacoes](figs/recommendations_display.png)" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [], + "source": [ + "from ipywidgets import widgets, Layout\n", + "from IPython.display import clear_output, HTML, Markdown, display\n", + "import requests" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [], + "source": [ + "top_10_imgs = count_avg_ratings_df.select(F.col('count_rank').alias('rank'), F.col('image_url').alias('according_to_count')) \\\n", + " .join(\n", + " count_avg_ratings_df.select(F.col('avg_rank').alias('rank'), F.col('image_url').alias('according_to_avg')),\n", + " on='rank') \\\n", + " .filter('rank <= 10')" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "DataFrame[rank: int, according_to_count: string, according_to_avg: string]" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "top_10_imgs.cache()" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+----+--------------------+--------------------+\n", + "|rank| according_to_count| according_to_avg|\n", + "+----+--------------------+--------------------+\n", + "| 1|https://images.gr...|https://images.gr...|\n", + "| 2|https://images.gr...|https://images.gr...|\n", + "| 3|https://images.gr...|https://images.gr...|\n", + "| 4|https://images.gr...|https://s.gr-asse...|\n", + "| 5|https://images.gr...|https://images.gr...|\n", + "| 6|https://images.gr...|https://s.gr-asse...|\n", + "| 7|https://images.gr...|https://images.gr...|\n", + "| 8|https://images.gr...|https://images.gr...|\n", + "| 9|https://images.gr...|https://s.gr-asse...|\n", + "| 10|https://images.gr...|https://s.gr-asse...|\n", + "+----+--------------------+--------------------+\n", + "\n" + ] + } + ], + "source": [ + "top_10_imgs.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [], + "source": [ + "def get_recommended_products(method, n):\n", + " imgs = top_10_imgs.select('rank', F.col(f'according_to_{method}').alias('url')).limit(n).collect()\n", + " return [(img.rank, img.url) for img in imgs]\n", + "\n", + "def printmd(string):\n", + " display(Markdown(string))\n", + "\n", + "def make_horizontal_box(children): return widgets.HBox(children)\n", + "\n", + "def make_vertical_box(children, width='auto', height='600px'):\n", + " return widgets.VBox(children, layout=Layout(width=width, height=height))\n", + "\n", + "def image_widget(url, layout=Layout(height='250px', width='150px', display='flex', align_items='center', border='solid white')):\n", + " img_content = requests.get(url).content\n", + " return widgets.Image(value=img_content, layout=layout)\n", + "\n", + "def widgets_to_render(method, n):\n", + " layout = Layout(height='250px', width='150px', display='flex', align_items='center', border='solid orchid')\n", + " return [image_widget(elem[1]) if i > 0 else image_widget(elem[1], layout=layout) \n", + " for i, elem in enumerate(get_recommended_products(method, n))]\n", + "\n", + "def print_on_button(string, color='lightblue'):\n", + " button = widgets.Button(description=string, layout=Layout(width='300px'))\n", + " button.style.button_color = color\n", + " return button\n", + "\n", + "def display_both_recommendations(n=3):\n", + " boxes = [\n", + " print_on_button('highest_count', color='lightblue'),\n", + " make_horizontal_box(widgets_to_render('count', n))\n", + " ]\n", + " boxes += [print_on_button('highest_avg', color='lightpink'),\n", + " make_horizontal_box(widgets_to_render('avg', n))]\n", + " display(make_vertical_box(boxes))" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(Button(description='highest_count', layout=Layout(width='300px'), style=ButtonStyle(button_colo…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "display_both_recommendations(n=5)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pyspark-kernel", + "language": "python", + "name": "spark" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.4" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/7. Data Engineering/spark/exercicio_spark_udfs.ipynb b/7. Data Engineering/spark/exercicio_spark_udfs.ipynb new file mode 100644 index 0000000..a06905c --- /dev/null +++ b/7. Data Engineering/spark/exercicio_spark_udfs.ipynb @@ -0,0 +1,375 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Spark UDFs\n", + "\n", + "UDF (User Defined Function) são funções customizadas que podemos aplicar sobre colunas do Spark DataFrame." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Vamos criar um DataFrame de exemplo" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "pandas_df = pd.DataFrame({\n", + " 'id': [1, 2, 3, 4],\n", + " 'age': [14, 15, 16, 16],\n", + " 'name': ['Barbara Maria', 'Barbara Beatriz', 'Cris', 'Danielle']})\n", + "\n", + "df = spark.createDataFrame(pandas_df)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+---+---+---------------+\n", + "| id|age| name|\n", + "+---+---+---------------+\n", + "| 1| 14| Barbara Maria|\n", + "| 2| 15|Barbara Beatriz|\n", + "| 3| 16| Cris|\n", + "| 4| 16| Danielle|\n", + "+---+---+---------------+\n", + "\n" + ] + } + ], + "source": [ + "df.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "root\n", + " |-- id: long (nullable = true)\n", + " |-- age: long (nullable = true)\n", + " |-- name: string (nullable = true)\n", + "\n" + ] + } + ], + "source": [ + "df.printSchema()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Exemplos" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Idade no ano que vem\n", + "\n", + "Vamos criar uma `udf` que retorna a idade no ano seguinte (ou seja, a idade somada a um)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Primeiro, definimos uma função `soma_um`, que soma 1 a um número" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "def soma_um(num):\n", + " return num + 1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Para criar a UDF, basta passar dois parâmetros para a função `udf`: a função e o tipo de retorno dela. Como idade é um campo inteiro, sabemos que o retorno dessa função será um número inteiro (`T.IntegerType()` - ou poderia também ser `T.LongType()`, que também é um tipo inteiro, mas para números maiores)." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "import pyspark.sql.functions as F\n", + "import pyspark.sql.types as T" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "soma_um_udf = F.udf(soma_um, T.IntegerType())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Aplicando `soma_um_udf` na coluna `age`, criamos uma nova coluna chamada `age_plus_one`:" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "df = df.withColumn('age_plus_one', soma_um_udf('age'))" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+---+---+---------------+------------+\n", + "| id|age| name|age_plus_one|\n", + "+---+---+---------------+------------+\n", + "| 1| 14| Barbara Maria| 15|\n", + "| 2| 15|Barbara Beatriz| 16|\n", + "| 3| 16| Cris| 17|\n", + "| 4| 16| Danielle| 17|\n", + "+---+---+---------------+------------+\n", + "\n" + ] + } + ], + "source": [ + "df.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Observação**: Note que, neste caso, não precisaríamos (e **não deveríamos**) construir uma `udf` para fazer essa operação. Conseguimos fazer essa operação de adicionar 1 a um número da seguinte forma:" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+---+---+---------------+------------+\n", + "| id|age| name|age_plus_one|\n", + "+---+---+---------------+------------+\n", + "| 1| 14| Barbara Maria| 15|\n", + "| 2| 15|Barbara Beatriz| 16|\n", + "| 3| 16| Cris| 17|\n", + "| 4| 16| Danielle| 17|\n", + "+---+---+---------------+------------+\n", + "\n" + ] + } + ], + "source": [ + "df.withColumn('age_plus_one', F.col('age') + 1).show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Primeiro nome\n", + "\n", + "Vamos criar uma coluna chamada `first_name` que conterá o primeiro nome, segundo a coluna `name` de cada um dos registros." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "def get_first_name(name):\n", + " return name.split(' ')[0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Nesse caso, nossa função retorna uma `string`, assim vamos utilizar `T.StringType()` como segundo parâmetro da `F.udf`." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "get_first_name_udf = F.udf(get_first_name, T.StringType())" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "df = df.withColumn('first_name', get_first_name_udf('name'))" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+---+---+---------------+------------+----------+\n", + "| id|age| name|age_plus_one|first_name|\n", + "+---+---+---------------+------------+----------+\n", + "| 1| 14| Barbara Maria| 15| Barbara|\n", + "| 2| 15|Barbara Beatriz| 16| Barbara|\n", + "| 3| 16| Cris| 17| Cris|\n", + "| 4| 16| Danielle| 17| Danielle|\n", + "+---+---+---------------+------------+----------+\n", + "\n" + ] + } + ], + "source": [ + "df.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Observação**: Note que, neste caso, também, não precisaríamos (e **não deveríamos**) construir uma `udf` para fazer essa operação. Conseguimos fazer essa operação de capturar o primeiro nome da seguinte forma:" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+---+---+---------------+------------+----------+\n", + "| id|age| name|age_plus_one|first_name|\n", + "+---+---+---------------+------------+----------+\n", + "| 1| 14| Barbara Maria| 15| Barbara|\n", + "| 2| 15|Barbara Beatriz| 16| Barbara|\n", + "| 3| 16| Cris| 17| Cris|\n", + "| 4| 16| Danielle| 17| Danielle|\n", + "+---+---+---------------+------------+----------+\n", + "\n" + ] + } + ], + "source": [ + "df.withColumn('first_name', F.split('name', ' ')[0]).show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Exercício: crie e aplique uma udf que conta a quantidade de caracteres de cada nome" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "###" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Assim como nos outros casos, existe uma função pronta do spark que já faz essa operação. Você consegue descobrir qual é e checar se ela realmente tem o mesmo comportamento da udf criada?" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "###" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pyspark-kernel", + "language": "python", + "name": "spark" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.4" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/7. Data Engineering/spark/exercicio_spark_udfs_gabarito.ipynb b/7. Data Engineering/spark/exercicio_spark_udfs_gabarito.ipynb new file mode 100644 index 0000000..563485c --- /dev/null +++ b/7. Data Engineering/spark/exercicio_spark_udfs_gabarito.ipynb @@ -0,0 +1,428 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Spark UDFs\n", + "\n", + "UDF (User Defined Function) são funções customizadas que podemos aplicar sobre colunas do Spark DataFrame." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Vamos criar um DataFrame de exemplo" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "pandas_df = pd.DataFrame({\n", + " 'id': [1, 2, 3, 4],\n", + " 'age': [14, 15, 16, 16],\n", + " 'name': ['Barbara Maria', 'Barbara Beatriz', 'Cris', 'Danielle']})\n", + "\n", + "df = spark.createDataFrame(pandas_df)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+---+---+---------------+\n", + "| id|age| name|\n", + "+---+---+---------------+\n", + "| 1| 14| Barbara Maria|\n", + "| 2| 15|Barbara Beatriz|\n", + "| 3| 16| Cris|\n", + "| 4| 16| Danielle|\n", + "+---+---+---------------+\n", + "\n" + ] + } + ], + "source": [ + "df.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "root\n", + " |-- id: long (nullable = true)\n", + " |-- age: long (nullable = true)\n", + " |-- name: string (nullable = true)\n", + "\n" + ] + } + ], + "source": [ + "df.printSchema()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Exemplos" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Idade no ano que vem\n", + "\n", + "Vamos criar uma `udf` que retorna a idade no ano seguinte (ou seja, a idade somada a um)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Primeiro, definimos uma função `soma_um`, que soma 1 a um número" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "def soma_um(num):\n", + " return num + 1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Para criar a UDF, basta passar dois parâmetros para a função `udf`: a função e o tipo de retorno dela. Como idade é um campo inteiro, sabemos que o retorno dessa função será um número inteiro (`T.IntegerType()` - ou poderia também ser `T.LongType()`, que também é um tipo inteiro, mas para números maiores)." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "import pyspark.sql.functions as F\n", + "import pyspark.sql.types as T" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "soma_um_udf = F.udf(soma_um, T.IntegerType())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Aplicando `soma_um_udf` na coluna `age`, criamos uma nova coluna chamada `age_plus_one`:" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "df = df.withColumn('age_plus_one', soma_um_udf('age'))" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+---+---+---------------+------------+\n", + "| id|age| name|age_plus_one|\n", + "+---+---+---------------+------------+\n", + "| 1| 14| Barbara Maria| 15|\n", + "| 2| 15|Barbara Beatriz| 16|\n", + "| 3| 16| Cris| 17|\n", + "| 4| 16| Danielle| 17|\n", + "+---+---+---------------+------------+\n", + "\n" + ] + } + ], + "source": [ + "df.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Observação**: Note que, neste caso, não precisaríamos (e **não deveríamos**) construir uma `udf` para fazer essa operação. Conseguimos fazer essa operação de adicionar 1 a um número da seguinte forma:" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+---+---+---------------+------------+\n", + "| id|age| name|age_plus_one|\n", + "+---+---+---------------+------------+\n", + "| 1| 14| Barbara Maria| 15|\n", + "| 2| 15|Barbara Beatriz| 16|\n", + "| 3| 16| Cris| 17|\n", + "| 4| 16| Danielle| 17|\n", + "+---+---+---------------+------------+\n", + "\n" + ] + } + ], + "source": [ + "df.withColumn('age_plus_one', F.col('age') + 1).show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Primeiro nome\n", + "\n", + "Vamos criar uma coluna chamada `first_name` que conterá o primeiro nome, segundo a coluna `name` de cada um dos registros." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "def get_first_name(name):\n", + " return name.split(' ')[0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Nesse caso, nossa função retorna uma `string`, assim vamos utilizar `T.StringType()` como segundo parâmetro da `F.udf`." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "get_first_name_udf = F.udf(get_first_name, T.StringType())" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "df = df.withColumn('first_name', get_first_name_udf('name'))" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+---+---+---------------+------------+----------+\n", + "| id|age| name|age_plus_one|first_name|\n", + "+---+---+---------------+------------+----------+\n", + "| 1| 14| Barbara Maria| 15| Barbara|\n", + "| 2| 15|Barbara Beatriz| 16| Barbara|\n", + "| 3| 16| Cris| 17| Cris|\n", + "| 4| 16| Danielle| 17| Danielle|\n", + "+---+---+---------------+------------+----------+\n", + "\n" + ] + } + ], + "source": [ + "df.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Observação**: Note que, neste caso, também, não precisaríamos (e **não deveríamos**) construir uma `udf` para fazer essa operação. Conseguimos fazer essa operação de capturar o primeiro nome da seguinte forma:" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+---+---+---------------+------------+----------+\n", + "| id|age| name|age_plus_one|first_name|\n", + "+---+---+---------------+------------+----------+\n", + "| 1| 14| Barbara Maria| 15| Barbara|\n", + "| 2| 15|Barbara Beatriz| 16| Barbara|\n", + "| 3| 16| Cris| 17| Cris|\n", + "| 4| 16| Danielle| 17| Danielle|\n", + "+---+---+---------------+------------+----------+\n", + "\n" + ] + } + ], + "source": [ + "df.withColumn('first_name', F.split('name', ' ')[0]).show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Exercício: \n", + "\n", + "Crie e aplique uma udf que conta a quantidade de caracteres de cada primeiro nome (coluna `first_name`), criando uma nova coluna chamada `first_name_size`." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "def count_chars(text):\n", + " return len(text)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "count_chars_udf = F.udf(count_chars, T.IntegerType())" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+---+---+---------------+------------+----------+---------------+\n", + "| id|age| name|age_plus_one|first_name|first_name_size|\n", + "+---+---+---------------+------------+----------+---------------+\n", + "| 1| 14| Barbara Maria| 15| Barbara| 7|\n", + "| 2| 15|Barbara Beatriz| 16| Barbara| 7|\n", + "| 3| 16| Cris| 17| Cris| 4|\n", + "| 4| 16| Danielle| 17| Danielle| 8|\n", + "+---+---+---------------+------------+----------+---------------+\n", + "\n" + ] + } + ], + "source": [ + "df.withColumn('first_name_size', count_chars_udf('first_name')).show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Assim como nos outros casos, existe uma função pronta do spark que já faz essa operação. Você consegue descobrir qual é e checar se ela realmente tem o mesmo comportamento da udf criada?" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+---+---+---------------+------------+----------+---------------+\n", + "| id|age| name|age_plus_one|first_name|first_name_size|\n", + "+---+---+---------------+------------+----------+---------------+\n", + "| 1| 14| Barbara Maria| 15| Barbara| 7|\n", + "| 2| 15|Barbara Beatriz| 16| Barbara| 7|\n", + "| 3| 16| Cris| 17| Cris| 4|\n", + "| 4| 16| Danielle| 17| Danielle| 8|\n", + "+---+---+---------------+------------+----------+---------------+\n", + "\n" + ] + } + ], + "source": [ + "df.withColumn('first_name_size', F.length('first_name')).show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pyspark-kernel", + "language": "python", + "name": "spark" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.4" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/7. Data Engineering/spark/exercicio_tags_co_ocorrentes.ipynb b/7. Data Engineering/spark/exercicio_tags_co_ocorrentes.ipynb new file mode 100644 index 0000000..01bfb55 --- /dev/null +++ b/7. Data Engineering/spark/exercicio_tags_co_ocorrentes.ipynb @@ -0,0 +1,696 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Exercício: tags que mais co-ocorrem\n", + "\n", + "Dado um dataset com avaliações de usuários sobre livros, vamos checar que tags co-ocorrem.\n", + "\n", + "Motivação: ser capaz de dizer que tags têm afinidade entre si." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pyspark.sql.functions as F\n", + "import pyspark.sql.types as T" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Baixando o dataset\n", + "\n", + "Vamos continuar usando o dataset `goodbooks-10k` criado para ser usado em problemas de recomendação. Só para lembrar, ele contém cerca de 6 milhões de avaliações para os 10 mil livros mais populares.\n", + "\n", + "Leia mais no [fast-ml](http://fastml.com/goodbooks-10k-a-new-dataset-for-book-recommendations/).\n", + "\n", + "Dessa vez, vamos baixar os arquivos `book_tags.csv` e `tags.csv`.\n", + "\n", + "Novamente, se tiver erro na execução da célula abaixo, baixe manualmente os arquivos do [github](https://github.com/zygmuntz/goodbooks-10k) e coloque os arquivos `book_tags.csv` e `tags.csv` em uma pasta chamada `data` neste diretório." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# !wget -P data https://github.com/zygmuntz/goodbooks-10k/raw/master/book_tags.csv\n", + "# !wget -P data https://github.com/zygmuntz/goodbooks-10k/raw/master/tags.csv" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "path = 'data' # se local\n", + "#path = 'dbfs:/FileStore/tables' # se usar notebook databricks" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Leitura dos datasets" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Exercício:** leia os arquivos `books.csv`, `ratings.csv`, `book_tags.csv` e `tags.csv`\n", + "\n", + "Lembre-se de colocar o caminho usando a variável `path`. Ex. `\"{path}/books.csv\"`" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "books_df = ###\n", + "ratings_df = ###\n", + "book_tags_df = ###\n", + "tags_df = ###" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Remoção de tags que não desejamos no dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "tags_df = tags_df.filter('tag_name not rlike \"(read|own|favorit)\"')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Estrutura dos dataframes `book_tags_df` e `tags_df`" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "root\n", + " |-- goodreads_book_id: integer (nullable = true)\n", + " |-- tag_id: integer (nullable = true)\n", + " |-- count: integer (nullable = true)\n", + "\n" + ] + } + ], + "source": [ + "book_tags_df.printSchema()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "root\n", + " |-- tag_id: integer (nullable = true)\n", + " |-- tag_name: string (nullable = true)\n", + "\n" + ] + } + ], + "source": [ + "tags_df.printSchema()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Parte 1: tag mais popular para cada livro\n", + "\n", + "**Exercício:** una os dataframes `books_tags_df` e `tags_df`. Atenção: pela estrutura acima, é possível saber qual é a coluna que deve ser utilizada na operação de `join`." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "book_tags_df = ###" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Exercício:** filtre o dataset para que ele só permita linhas em que a coluna `tag_name` tenha tamanho estritamente maior do que 3." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "book_tags_df = ###" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Agora, basta ranquearmos as tags de acordo com sua popularidade para cada livro. Para isso, vamos usar novamente uma `Window`." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "from pyspark.sql import Window" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "w = Window.partitionBy('goodreads_book_id').orderBy(F.desc('count'))" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "book_tags_df = book_tags_df \\\n", + " .withColumn('rank', F.row_number().over(w)) \\\n", + " .filter('rank = 1') \\\n", + " .drop('rank')" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+------+-----------------+-----+-----------------+\n", + "|tag_id|goodreads_book_id|count| tag_name|\n", + "+------+-----------------+-----+-----------------+\n", + "| 7563| 1591| 410| clàssics|\n", + "| 11743| 2122| 3692| fiction|\n", + "| 7116| 2142| 56|christian-fiction|\n", + "| 7457| 4900| 8128| classics|\n", + "| 11305| 7993| 1290| fantasy|\n", + "+------+-----------------+-----+-----------------+\n", + "only showing top 5 rows\n", + "\n" + ] + } + ], + "source": [ + "book_tags_df.show(n=5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Extra: remoção de acentos\n", + "\n", + "É possível ver que algumas tags têm acentos e gostaríamos de removê-los. Para isso, vamos utilizar uma função customizada, a chamada `UDF` no Spark." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "from unicodedata import normalize" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "def strip_accents(text):\n", + " return normalize('NFKD', text).encode('ascii', 'ignore').decode('utf-8')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Exercício:** crie a UDF para aplicarmos a função `strip_accents`.\n", + "\n", + "Dica: veja um exemplo [aqui](https://gist.github.com/zoltanctoth/2deccd69e3d1cde1dd78).\n", + "\n", + "Note que, em nosso caso, já temos importados os módulos `pyspark.sql.functions` como `F` e `pyspark.sql.types` como `T`." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "strip_accents_udf = ###" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Exercício:** sobrescreva a coluna `tag_name` aplicando a UDF `strip_accents_udf` nela mesma." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "book_tags_df = book_tags_df \\\n", + " .withColumn('tag_name', ###)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+------+-----------------+-----+--------+\n", + "|tag_id|goodreads_book_id|count|tag_name|\n", + "+------+-----------------+-----+--------+\n", + "| 7563| 1591| 410|classics|\n", + "| 11743| 2122| 3692| fiction|\n", + "+------+-----------------+-----+--------+\n", + "only showing top 2 rows\n", + "\n" + ] + } + ], + "source": [ + "book_tags_df.show(n=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Parte 2: identificação dos livros avaliados pelas tags" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Execício:** adicione a coluna `book_id` no dataframe `book_tags_df`.\n", + "\n", + "Dica: faça uma operação de `join` com o dataframe `books_df` usando como chave (o argumento do parâmetro `on`) uma coluna que ambos os dataframes têm em comum." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "book_tags_df = ###" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Execício:** crie um novo dataframe `user_ratings_tags_df`, que é o dataframe `ratings_df`, com a adição da coluna `tag_name`.\n", + "\n", + "Dica: faça uma operação de `join` com o dataframe `book_tags_df` usando como chave (o argumento do parâmetro `on`) a coluna `book_id`. Note que queremos manter o total de linhas do dataset `ratings_df`, assim, é aconselhado que o método do join (parâmetro `how`) seja `left` (caso coloque o `ratings_df` primeiro)." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "user_ratings_tags_df = ratings_df \\\n", + " .join(###)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Caso um livro não tenha tags em `book_tags_df`, queremos que ele fique com a tag `unknown`." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "user_ratings_tags_df = user_ratings_tags_df \\\n", + " .withColumn('tag_name', F.coalesce('tag_name', F.lit('unknown')))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Parte 3: criação dos pares de tags de cada usuário" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "O primeiro passo é a agregação, para cada usuário, de todas as tags.\n", + "\n", + "**Exercício:** agrupe o dataframe `user_ratings_tags_df` por usuário e use uma função de agregação que liste todas as `tag_name` com as quais esse usuário interagiu. Dê a essa coluna o nome de `tags`.\n", + "\n", + "Dica: existem duas funções que listam todos valores para cada chave de agregação: `collect_set` e `collect_list`. Neste caso, estamos interessados em uma lista com objetos únicos, assim, `collect_set` é a função mais indicada." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "user_tags_df = ###" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Agora, vamos montar os pares usando a função `combinations` do módulo `itertools`." + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "from itertools import combinations" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "def make_pairs(list_objs):\n", + " return list(combinations(sorted(list_objs), 2))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Como é uma função customizada, precisamos criar uma UDF para aplicá-la!\n", + "\n", + "Nesse caso, o retorno é uma lista de tuplas de `string` e, por isso, vamos criar um tipo especial para tupla.\n", + "\n", + "(Alternativamente, poderíamos modificar o retorno para que ele fosse lista de lista de `string`. Quer tentar?)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "tuple_type = T.StructType([\n", + " T.StructField('pair_1', T.StringType(), nullable=False),\n", + " T.StructField('pair_2', T.StringType(), nullable=False)])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Exercício:** crie a UDF `make_pairs_udf`. Note que o tipo do retorno será dado por `T.ArrayType(tuple_type)`." + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "make_pairs_udf = ###" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Alternativamente, a chamada abaixo cria a UDF `make_pairs_df` e também registra a função para uso dentro de uma query Spark SQL.\n", + "\n", + "```python\n", + "make_pairs_udf = spark.udf.register('make_pairs_udf', make_pairs, T.ArrayType(tuple_type))\n", + "```" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Exercício:** aplique `make_pairs_udf` na coluna `tags`, criando uma coluna chamada `pairs`. Ao final, delete a coluna `tags`, usando o comando `drop`." + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "pairs_df = ###" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+-------+--------------------+\n", + "|user_id| pairs|\n", + "+-------+--------------------+\n", + "| 148|[[africa, audiobo...|\n", + "| 463|[[adventure, chic...|\n", + "+-------+--------------------+\n", + "only showing top 2 rows\n", + "\n" + ] + } + ], + "source": [ + "pairs_df.show(n=2)" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "root\n", + " |-- user_id: integer (nullable = true)\n", + " |-- pairs: array (nullable = true)\n", + " | |-- element: struct (containsNull = true)\n", + " | | |-- pair_1: string (nullable = false)\n", + " | | |-- pair_2: string (nullable = false)\n", + "\n" + ] + } + ], + "source": [ + "pairs_df.printSchema()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Parte 4: contagem dos pares" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "O primeiro passo aqui é transformar nosso dataframe, de forma que cada um dos elementos da lista contida na coluna `pairs` esteja em uma linha. Isso pode ser facilmente feito através do método `explode`:" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [], + "source": [ + "one_pair_per_row_df = pairs_df \\\n", + " .select('user_id', F.explode('pairs').alias('pair'))" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+-------+-------------------+\n", + "|user_id|pair |\n", + "+-------+-------------------+\n", + "|148 |[africa, audiobook]|\n", + "|148 |[africa, book-club]|\n", + "+-------+-------------------+\n", + "only showing top 2 rows\n", + "\n" + ] + } + ], + "source": [ + "one_pair_per_row_df.show(n=2, truncate=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Exercício:** para cada par, conte a quantidade de usuários que interagiram com ele. Ao final, faça uma ordenação decrescente do valor da coluna `count`." + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [], + "source": [ + "pair_count_df = ###" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Parte 5: os pares mais comuns são..." + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+-----------------------------+-----+\n", + "|pair |count|\n", + "+-----------------------------+-----+\n", + "|[fantasy, fiction] |48531|\n", + "|[classics, fiction] |47076|\n", + "|[classics, fantasy] |44802|\n", + "|[fiction, non-fiction] |43409|\n", + "|[fiction, young-adult] |43322|\n", + "|[fantasy, young-adult] |42684|\n", + "|[fantasy, non-fiction] |40720|\n", + "|[classics, non-fiction] |40696|\n", + "|[fiction, historical-fiction]|39634|\n", + "|[classics, young-adult] |39549|\n", + "+-----------------------------+-----+\n", + "only showing top 10 rows\n", + "\n" + ] + } + ], + "source": [ + "pair_count_df.show(n=10, truncate=False)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pyspark-kernel", + "language": "python", + "name": "spark" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.4" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/7. Data Engineering/spark/exercicio_tags_co_ocorrentes_gabarito.ipynb b/7. Data Engineering/spark/exercicio_tags_co_ocorrentes_gabarito.ipynb new file mode 100644 index 0000000..7ad4711 --- /dev/null +++ b/7. Data Engineering/spark/exercicio_tags_co_ocorrentes_gabarito.ipynb @@ -0,0 +1,707 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Exercício: tags que mais co-ocorrem\n", + "\n", + "Dado um dataset com avaliações de usuários sobre livros, vamos checar que tags co-ocorrem.\n", + "\n", + "Motivação: ser capaz de dizer que tags têm afinidade entre si." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pyspark.sql.functions as F\n", + "import pyspark.sql.types as T" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Baixando o dataset\n", + "\n", + "Vamos continuar usando o dataset `goodbooks-10k` criado para ser usado em problemas de recomendação. Só para lembrar, ele contém cerca de 6 milhões de avaliações para os 10 mil livros mais populares.\n", + "\n", + "Leia mais no [fast-ml](http://fastml.com/goodbooks-10k-a-new-dataset-for-book-recommendations/).\n", + "\n", + "Dessa vez, vamos baixar os arquivos `book_tags.csv` e `tags.csv`.\n", + "\n", + "Novamente, se tiver erro na execução da célula abaixo, baixe manualmente os arquivos do [github](https://github.com/zygmuntz/goodbooks-10k) e coloque os arquivos `book_tags.csv` e `tags.csv` em uma pasta chamada `data` neste diretório." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# !wget -P data https://github.com/zygmuntz/goodbooks-10k/raw/master/book_tags.csv\n", + "# !wget -P data https://github.com/zygmuntz/goodbooks-10k/raw/master/tags.csv" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "path = 'data' # se local\n", + "#path = 'dbfs:/FileStore/tables' # se usar notebook databricks" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Leitura dos datasets" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "def read(filename):\n", + " return spark.read.csv(f'{path}/{filename}', inferSchema=True, header=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "books_df = read('books.csv')\n", + "ratings_df = read('ratings.csv')\n", + "book_tags_df = read('book_tags.csv')\n", + "tags_df = read('tags.csv')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Remoção de tags que não desejamos no dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "tags_df = tags_df.filter('tag_name not rlike \"(read|own|favorit)\"')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Estrutura dos dataframes `book_tags_df` e `tags_df`" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "root\n", + " |-- goodreads_book_id: integer (nullable = true)\n", + " |-- tag_id: integer (nullable = true)\n", + " |-- count: integer (nullable = true)\n", + "\n" + ] + } + ], + "source": [ + "book_tags_df.printSchema()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "root\n", + " |-- tag_id: integer (nullable = true)\n", + " |-- tag_name: string (nullable = true)\n", + "\n" + ] + } + ], + "source": [ + "tags_df.printSchema()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Parte 1: tag mais popular para cada livro\n", + "\n", + "**Exercício:** una os dataframes `books_tags_df` e `tags_df`. Atenção: pela estrutura acima, é possível saber qual é a coluna que deve ser utilizada na operação de `join`." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "book_tags_df = book_tags_df \\\n", + " .join(tags_df, on='tag_id', how='inner')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Exercício:** filtre o dataset para que ele só permita linhas em que a coluna `tag_name` tenha tamanho estritamente maior do que 3." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "book_tags_df = book_tags_df \\\n", + " .filter('LENGTH(tag_name) > 3')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Agora, basta ranquearmos as tags de acordo com sua popularidade para cada livro. Para isso, vamos usar novamente uma `Window`." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "from pyspark.sql import Window" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "w = Window.partitionBy('goodreads_book_id').orderBy(F.desc('count'))" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "book_tags_df = book_tags_df \\\n", + " .withColumn('rank', F.row_number().over(w)) \\\n", + " .filter('rank = 1') \\\n", + " .drop('rank')" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+------+-----------------+-----+-----------------+\n", + "|tag_id|goodreads_book_id|count| tag_name|\n", + "+------+-----------------+-----+-----------------+\n", + "| 7563| 1591| 410| clàssics|\n", + "| 11743| 2122| 3692| fiction|\n", + "| 7116| 2142| 56|christian-fiction|\n", + "| 7457| 4900| 8128| classics|\n", + "| 11305| 7993| 1290| fantasy|\n", + "+------+-----------------+-----+-----------------+\n", + "only showing top 5 rows\n", + "\n" + ] + } + ], + "source": [ + "book_tags_df.show(n=5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Extra: remoção de acentos\n", + "\n", + "É possível ver que algumas tags têm acentos e gostaríamos de removê-los. Para isso, vamos utilizar uma função customizada, a chamada `UDF` no Spark." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "from unicodedata import normalize" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "def strip_accents(text):\n", + " return normalize('NFKD', text).encode('ascii', 'ignore').decode('utf-8')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Exercício:** crie a UDF para aplicarmos a função `strip_accents`.\n", + "\n", + "Dica: veja um exemplo [aqui](https://gist.github.com/zoltanctoth/2deccd69e3d1cde1dd78).\n", + "\n", + "Note que, em nosso caso, já temos importados os módulos `pyspark.sql.functions` como `F` e `pyspark.sql.types` como `T`." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "strip_accents_udf = F.udf(strip_accents, T.StringType())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Exercício:** sobrescreva a coluna `tag_name` aplicando a UDF `strip_accents_udf` nela mesma." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "book_tags_df = book_tags_df \\\n", + " .withColumn('tag_name', strip_accents_udf('tag_name'))" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+------+-----------------+-----+--------+\n", + "|tag_id|goodreads_book_id|count|tag_name|\n", + "+------+-----------------+-----+--------+\n", + "| 7563| 1591| 410|classics|\n", + "| 11743| 2122| 3692| fiction|\n", + "+------+-----------------+-----+--------+\n", + "only showing top 2 rows\n", + "\n" + ] + } + ], + "source": [ + "book_tags_df.show(n=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Parte 2: identificação dos livros avaliados pelas tags" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Execício:** adicione a coluna `book_id` no dataframe `book_tags_df`.\n", + "\n", + "Dica: faça uma operação de `join` com o dataframe `books_df` usando como chave (o argumento do parâmetro `on`) uma coluna que ambos os dataframes têm em comum." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "book_tags_df = book_tags_df \\\n", + " .join(books_df.select('book_id', 'goodreads_book_id') , on='goodreads_book_id', how='inner')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Execício:** crie um novo dataframe `user_ratings_tags_df`, que é o dataframe `ratings_df`, com a adição da coluna `tag_name`.\n", + "\n", + "Dica: faça uma operação de `join` com o dataframe `book_tags_df` usando como chave (o argumento do parâmetro `on`) a coluna `book_id`. Note que queremos manter o total de linhas do dataset `ratings_df`, assim, é aconselhado que o método do join (parâmetro `how`) seja `left` (caso coloque o `ratings_df` primeiro)." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "user_ratings_tags_df = ratings_df \\\n", + " .join(book_tags_df.select('book_id', 'tag_name'), on='book_id', how='left')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Caso um livro não tenha tags em `book_tags_df`, queremos que ele fique com a tag `unknown`." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "user_ratings_tags_df = user_ratings_tags_df \\\n", + " .withColumn('tag_name', F.coalesce('tag_name', F.lit('unknown')))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Parte 3: criação dos pares de tags de cada usuário" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "O primeiro passo é a agregação, para cada usuário, de todas as tags.\n", + "\n", + "**Exercício:** agrupe o dataframe `user_ratings_tags_df` por usuário e use uma função de agregação que liste todas as `tag_name` com as quais esse usuário interagiu. Dê a essa coluna o nome de `tags`.\n", + "\n", + "Dica: existem duas funções que listam todos valores para cada chave de agregação: `collect_set` e `collect_list`. Neste caso, estamos interessados em uma lista com objetos únicos, assim, `collect_set` é a função mais indicada." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "user_tags_df = user_ratings_tags_df \\\n", + " .groupBy('user_id') \\\n", + " .agg(F.collect_set('tag_name').alias('tags'))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Agora, vamos montar os pares usando a função `combinations` do módulo `itertools`." + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "from itertools import combinations" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "def make_pairs(list_objs):\n", + " return list(combinations(sorted(list_objs), 2))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Como é uma função customizada, precisamos criar uma UDF para aplicá-la!\n", + "\n", + "Nesse caso, o retorno é uma lista de tuplas de `string` e, por isso, vamos criar um tipo especial para tupla.\n", + "\n", + "(Alternativamente, poderíamos modificar o retorno para que ele fosse lista de lista de `string`. Quer tentar?)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "tuple_type = T.StructType([\n", + " T.StructField('pair_1', T.StringType(), nullable=False),\n", + " T.StructField('pair_2', T.StringType(), nullable=False)])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Exercício:** crie a UDF `make_pairs_udf`. Note que o tipo do retorno será dado por `T.ArrayType(tuple_type)`." + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "make_pairs_udf = F.udf(make_pairs, T.ArrayType(tuple_type))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Alternativamente, a chamada abaixo cria a UDF `make_pairs_df` e também registra a função para uso dentro de uma query Spark SQL.\n", + "\n", + "```python\n", + "make_pairs_udf = spark.udf.register('make_pairs_udf', make_pairs, T.ArrayType(tuple_type))\n", + "```" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Exercício:** aplique `make_pairs_udf` na coluna `tags`, criando uma coluna chamada `pairs`. Ao final, delete a coluna `tags`, usando o comando `drop`." + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "pairs_df = user_tags_df \\\n", + " .withColumn('pairs', make_pairs_udf('tags')) \\\n", + " .drop('tags')" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+-------+--------------------+\n", + "|user_id| pairs|\n", + "+-------+--------------------+\n", + "| 148|[[africa, audiobo...|\n", + "| 463|[[adventure, chic...|\n", + "+-------+--------------------+\n", + "only showing top 2 rows\n", + "\n" + ] + } + ], + "source": [ + "pairs_df.show(n=2)" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "root\n", + " |-- user_id: integer (nullable = true)\n", + " |-- pairs: array (nullable = true)\n", + " | |-- element: struct (containsNull = true)\n", + " | | |-- pair_1: string (nullable = false)\n", + " | | |-- pair_2: string (nullable = false)\n", + "\n" + ] + } + ], + "source": [ + "pairs_df.printSchema()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Parte 4: contagem dos pares" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "O primeiro passo aqui é transformar nosso dataframe, de forma que cada um dos elementos da lista contida na coluna `pairs` esteja em uma linha. Isso pode ser facilmente feito através do método `explode`:" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [], + "source": [ + "one_pair_per_row_df = pairs_df \\\n", + " .select('user_id', F.explode('pairs').alias('pair'))" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+-------+-------------------+\n", + "|user_id|pair |\n", + "+-------+-------------------+\n", + "|148 |[africa, audiobook]|\n", + "|148 |[africa, book-club]|\n", + "+-------+-------------------+\n", + "only showing top 2 rows\n", + "\n" + ] + } + ], + "source": [ + "one_pair_per_row_df.show(n=2, truncate=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Exercício:** para cada par, conte a quantidade de usuários que interagiram com ele. Ao final, faça uma ordenação decrescente do valor da coluna `count`." + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [], + "source": [ + "pair_count_df = one_pair_per_row_df \\\n", + " .groupBy('pair') \\\n", + " .count() \\\n", + " .orderBy(F.desc('count'))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Parte 5: os pares mais comuns são..." + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+-----------------------------+-----+\n", + "|pair |count|\n", + "+-----------------------------+-----+\n", + "|[fantasy, fiction] |48531|\n", + "|[classics, fiction] |47076|\n", + "|[classics, fantasy] |44802|\n", + "|[fiction, non-fiction] |43409|\n", + "|[fiction, young-adult] |43322|\n", + "|[fantasy, young-adult] |42684|\n", + "|[fantasy, non-fiction] |40720|\n", + "|[classics, non-fiction] |40696|\n", + "|[fiction, historical-fiction]|39634|\n", + "|[classics, young-adult] |39549|\n", + "+-----------------------------+-----+\n", + "only showing top 10 rows\n", + "\n" + ] + } + ], + "source": [ + "pair_count_df.show(n=10, truncate=False)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pyspark-kernel", + "language": "python", + "name": "spark" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.4" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/7. 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Data Engineering/spark/slides/Spark - WoMakersCode_DSB.pdf new file mode 100644 index 0000000..e230599 Binary files /dev/null and b/7. Data Engineering/spark/slides/Spark - WoMakersCode_DSB.pdf differ diff --git a/README.md b/README.md index 21165bf..7b48c82 100644 --- a/README.md +++ b/README.md @@ -3,7 +3,7 @@ ## 1. Introdução a Análise de Dados, Data Science, BI e Big Data Instrutoras: TBD -## 2.0 Estatística Descritiva +## 2. Estatística Descritiva Instrutoras: Bárbara e Thais ## 2.1 Análise de Dados em Python @@ -12,14 +12,14 @@ Instrutoras: Bárbara e Thais ## 3. Modelos regressivos Instrutoras: Gisely Alves -## 4.0 Modelos de classificação -Instrutoras: Mirelle, Vivian e Gisely +## 4. Modelos de classificação +Instrutoras: Priscilla e Vivian ## 4.1 Clustering -Instrutoras: Mirelle, Vivian e Gisely +Instrutoras: Jéssica e Vivian ## 5. Algoritmos de Machine Learning e aplicações em larga escala -Instrutoras: Jéssica, Vivian e Gisely +Instrutoras: Jéssica, Vivian e Thais ## 6. Data Visualization Instrutoras: Camila e Thais