From 5d922c5eef463bc1a0944f9181eab451abc429f6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arturo=20Filast=C3=B2?= Date: Fri, 23 Aug 2024 12:57:44 +0200 Subject: [PATCH 1/8] Get rid of all the dataviz that isn't the analysis visualizer --- oonipipeline/pyproject.toml | 7 +- .../src/oonipipeline/dataviz/dependencies.py | 25 + oonipipeline/src/oonipipeline/dataviz/main.py | 100 + .../src/oonipipeline/dataviz/react/.gitignore | 2 - .../src/oonipipeline/dataviz/react/Readme.md | 10 - .../oonipipeline/dataviz/react/package.json | 65 - .../oonipipeline/dataviz/react/src/App.tsx | 54 - .../react/src/components/DNSAnalysis.tsx | 204 - .../dataviz/react/src/components/Dataviz.tsx | 422 -- .../oonipipeline/dataviz/react/src/index.tsx | 15 - .../src/oonipipeline/dataviz/react/yarn.lock | 4476 ----------------- .../oonipipeline/dataviz/templates/react.html | 18 - .../oonipipeline/dataviz/templates/vega.html | 21 - oonipipeline/src/oonipipeline/dataviz/viz.py | 1055 ---- oonipipeline/src/oonipipeline/dataviz/web.py | 201 - .../temporal/to_port/response_archiver.py | 2 +- 16 files changed, 130 insertions(+), 6547 deletions(-) create mode 100644 oonipipeline/src/oonipipeline/dataviz/dependencies.py create mode 100644 oonipipeline/src/oonipipeline/dataviz/main.py delete mode 100644 oonipipeline/src/oonipipeline/dataviz/react/.gitignore delete mode 100644 oonipipeline/src/oonipipeline/dataviz/react/Readme.md delete mode 100644 oonipipeline/src/oonipipeline/dataviz/react/package.json delete mode 100644 oonipipeline/src/oonipipeline/dataviz/react/src/App.tsx delete mode 100644 oonipipeline/src/oonipipeline/dataviz/react/src/components/DNSAnalysis.tsx delete mode 100644 oonipipeline/src/oonipipeline/dataviz/react/src/components/Dataviz.tsx delete mode 100644 oonipipeline/src/oonipipeline/dataviz/react/src/index.tsx delete mode 100644 oonipipeline/src/oonipipeline/dataviz/react/yarn.lock delete mode 100644 oonipipeline/src/oonipipeline/dataviz/templates/react.html delete mode 100644 oonipipeline/src/oonipipeline/dataviz/templates/vega.html delete mode 100644 oonipipeline/src/oonipipeline/dataviz/viz.py delete mode 100644 oonipipeline/src/oonipipeline/dataviz/web.py diff --git a/oonipipeline/pyproject.toml b/oonipipeline/pyproject.toml index c5aa3381..93cb5547 100644 --- a/oonipipeline/pyproject.toml +++ b/oonipipeline/pyproject.toml @@ -26,17 +26,17 @@ dependencies = [ "tabulate ~= 0.9.0", "warcio ~= 1.7.4", "msgpack ~= 1.0.4", - "statsd ~= 4.0.1", "click-loglevel ~= 0.5.0", - "dask ~= 2023.3.2", "altair ~= 4.2.0", "numpy ~= 1.23.5", "pandas ~= 2.0.0", - "flask ~= 2.2.0", "jupyterlab ~= 4.0.7", "temporalio ~= 1.7.0", "temporalio[opentelemetry] ~= 1.7.0", "opentelemetry-exporter-otlp-proto-grpc ~= 1.18.0", + "bokeh ~= 3.5.2", + "uvicorn ~= 0.25.0", + "pydantic-settings ~= 2.1.0", ] [tool.hatch.build.targets.sdist] @@ -68,6 +68,7 @@ path = "src/oonipipeline/__about__.py" [tool.hatch.envs.default.scripts] oonipipeline = "python -m oonipipeline.main {args}" +dataviz = "uvicorn oonipipeline.dataviz.main:app {args}" test = "pytest {args:tests}" # --full-trace --log-level=INFO --log-cli-level=INFO -v --setup-show -s test-cov = "pytest --cov=./ --cov-report=xml --cov-report=html --cov-report=term {args:tests}" diff --git a/oonipipeline/src/oonipipeline/dataviz/dependencies.py b/oonipipeline/src/oonipipeline/dataviz/dependencies.py new file mode 100644 index 00000000..1208b37e --- /dev/null +++ b/oonipipeline/src/oonipipeline/dataviz/dependencies.py @@ -0,0 +1,25 @@ +from functools import lru_cache +from typing import Annotated + +from fastapi import Depends +from clickhouse_driver import Client as Clickhouse + +from pydantic_settings import BaseSettings + + +class Settings(BaseSettings): + clickhouse_url: str = "clickhouse://localhost" + data_dir = "tests/data/datadir" + + +@lru_cache +def get_settings() -> Settings: + return Settings() + + +def get_clickhouse_session(settings: Annotated[Settings, Depends(get_settings)]): + db = Clickhouse.from_url(settings.clickhouse_url) + try: + yield db + finally: + db.disconnect() diff --git a/oonipipeline/src/oonipipeline/dataviz/main.py b/oonipipeline/src/oonipipeline/dataviz/main.py new file mode 100644 index 00000000..efa2ea46 --- /dev/null +++ b/oonipipeline/src/oonipipeline/dataviz/main.py @@ -0,0 +1,100 @@ +from dataclasses import asdict +import json +import os +from pathlib import Path + +from fastapi import Depends, FastAPI, Request +from fastapi.templating import Jinja2Templates + +from oonidata.dataclient import load_measurement +from oonidata.apiclient import get_measurement_dict_by_uid +from oonipipeline.dataviz.dependencies import get_settings + +from ..analysis.control import ( + BodyDB, + WebGroundTruthDB, + iter_ground_truths_from_web_control, +) +from ..analysis.web_analysis import make_web_analysis +from ..analysis.website_experiment_results import make_website_experiment_results + +from ..fingerprintdb import FingerprintDB +from ..netinfo import NetinfoDB + +from ..transforms.observations import measurement_to_observations + +app = FastAPI() + +current_dir = os.path.dirname(os.path.abspath(__file__)) +templates = Jinja2Templates(directory=f"{current_dir}/templates") + + +@app.get("/analysis/m/{measurement_uid}") +def analysis_by_msmt( + request: Request, + measurement_uid: str, + settings=Depends(get_settings), +): + data_dir = Path(settings.data_dir) + + fingerprintdb = FingerprintDB(datadir=data_dir, download=False) + netinfodb = NetinfoDB(datadir=data_dir, download=False) + raw_msmt = get_measurement_dict_by_uid(measurement_uid) + msmt = load_measurement(msmt=raw_msmt) + web_observations, web_control_observations = measurement_to_observations( + msmt, netinfodb=netinfodb + ) + web_ground_truth_db = WebGroundTruthDB() + web_ground_truth_db.build_from_rows( + rows=iter_ground_truths_from_web_control( + web_control_observations=web_control_observations, + netinfodb=netinfodb, + ), + ) + + web_ground_truths = web_ground_truth_db.lookup_by_web_obs(web_obs=web_observations) + web_analysis = list( + make_web_analysis( + web_observations=web_observations, + web_ground_truths=web_ground_truths, + body_db=BodyDB(db=None), # type: ignore + fingerprintdb=fingerprintdb, + ) + ) + + # assert len(web_analysis) == len( + # web_observations + # ), f"web_analysis != web_obs {len(web_analysis)} != {len(web_observations)}" + # for wa in web_analysis: + # print_nice_vertical(wa) + + website_er = list(make_website_experiment_results(web_analysis)) + assert len(website_er) == 1 + + wer = website_er[0] + analysis_transcript_list = wer.analysis_transcript_list + + # wer.analysis_transcript_list = None + # print_nice_vertical(wer) + # for loni in loni_list: + # pprint(loni.to_dict()) + # print(analysis_transcript_list) + + return templates.TemplateResponse( + request=request, + name="analysis.html", + context=dict( + website_experiment_result=asdict(wer), + analysis_transcript_list=analysis_transcript_list, + loni_list=wer.loni_list, + raw_msmt=raw_msmt, + measurement_uid=measurement_uid, + web_analysis=list(map(lambda x: asdict(x), web_analysis)), + web_observations=list(map(lambda x: asdict(x), web_observations)), + loni_blocked_dict=dict(zip(wer.loni_blocked_keys, wer.loni_blocked_values)), + loni_blocked_value=sum(wer.loni_blocked_values), + loni_down_dict=dict(zip(wer.loni_down_keys, wer.loni_down_values)), + loni_down_value=sum(wer.loni_down_values), + loni_ok_value=wer.loni_ok_value, + ), + ) diff --git a/oonipipeline/src/oonipipeline/dataviz/react/.gitignore b/oonipipeline/src/oonipipeline/dataviz/react/.gitignore deleted file mode 100644 index 59dc1f7c..00000000 --- a/oonipipeline/src/oonipipeline/dataviz/react/.gitignore +++ /dev/null @@ -1,2 +0,0 @@ -node_modules/ -.parcel-cache/ diff --git a/oonipipeline/src/oonipipeline/dataviz/react/Readme.md b/oonipipeline/src/oonipipeline/dataviz/react/Readme.md deleted file mode 100644 index 20d56760..00000000 --- a/oonipipeline/src/oonipipeline/dataviz/react/Readme.md +++ /dev/null @@ -1,10 +0,0 @@ -To build the react component do -``` -yarn install -yarn run build -``` - -During development do -``` -yarn run watch -``` diff --git a/oonipipeline/src/oonipipeline/dataviz/react/package.json b/oonipipeline/src/oonipipeline/dataviz/react/package.json deleted file mode 100644 index 3d6dc320..00000000 --- a/oonipipeline/src/oonipipeline/dataviz/react/package.json +++ /dev/null @@ -1,65 +0,0 @@ -{ - "name": "oonidataviz", - "version": "1.0.0", - "license": "MIT", - "scripts": { - "build": "parcel build src/index.tsx", - "watch": "parcel watch src/index.tsx" - }, - "targets": { - "default": { - "isLibrary": false, - "scopeHoist": false, - "outputFormat": "global", - "context": "browser", - "distDir": "../static/dist/" - } - }, - "devDependencies": { - "@babel/core": "^7.16.5", - "@babel/preset-react": "^7.17.12", - "@parcel/reporter-bundle-analyzer": "^2.6.0", - "@parcel/transformer-svg-react": "^2.5.0", - "buffer": "^6.0.3", - "gh-pages": "^3.2.3", - "parcel": "2.6.0", - "prettier": "^2.6.2", - "process": "^0.11.10", - "typescript": "^4.2.4" - }, - "dependencies": { - "@fontsource/fira-sans": "^4.5.10", - "@rebass/forms": "^4.0.6", - "ooni-components": "^0.5.0-alpha.5", - "prop-types": "^15.8.1", - "rc-progress": "^3.2.1", - "rc-util": "^5.16.1", - "react": "^16.0.0 || ^17.0.0", - "react-dom": "^17.0.2", - "react-hook-form": "^7.31.1", - "react-icon-base": "^2.1.2", - "react-icons": "^4.4.0", - "react-intl": "^5.24.0", - "react-json-view": "^1.21.3", - "react-lottie-player": "^1.4.1", - "react-router-dom": "6", - "react-spinners": "^0.13.7", - "react-table": "^7.8.0", - "react-vega": "^7.6.0", - "rehype-react": "^7.0.3", - "remark-parse": "^10.0.1", - "remark-rehype": "^10.1.0", - "styled-components": "^5.3.3", - "unified": "^10.1.1", - "vega": "^5.22.1", - "vega-lite": "^5.6.0" - }, - "resolutions": { - "ansi-regex": "^5.0.1", - "postcss": "^7.0.36", - "json-schema": "^0.4.0", - "minimist": "^1.2.3", - "path-parse": "^1.0.7", - "ws": "^7.4.6" - } -} diff --git a/oonipipeline/src/oonipipeline/dataviz/react/src/App.tsx b/oonipipeline/src/oonipipeline/dataviz/react/src/App.tsx deleted file mode 100644 index 1e52424b..00000000 --- a/oonipipeline/src/oonipipeline/dataviz/react/src/App.tsx +++ /dev/null @@ -1,54 +0,0 @@ -import * as React from "react"; - -import { createGlobalStyle, ThemeProvider } from "styled-components"; - -import { Container, theme } from "ooni-components"; - -import { Routes, Route, Outlet, Link } from "react-router-dom"; - -import DataViz from './components/Dataviz' -import DNSAnalysis from "./components/DNSAnalysis"; - -const GlobalStyle = createGlobalStyle` - * { - text-rendering: geometricPrecision; - box-sizing: border-box; - } - body, html { - margin: 0; - padding: 0; - font-family: "Fira Sans"; - font-size: 14px; - height: 100%; - background-color: #ffffff; - } -`; - -const Layout = () => ( - - - - - - - -) - -const Home = () => ( -
Hello home
-) - -const App = () => { - return ( - - }> - } /> - } /> - } /> - } /> - - - ); -}; - -export default App; diff --git a/oonipipeline/src/oonipipeline/dataviz/react/src/components/DNSAnalysis.tsx b/oonipipeline/src/oonipipeline/dataviz/react/src/components/DNSAnalysis.tsx deleted file mode 100644 index 20b8ce13..00000000 --- a/oonipipeline/src/oonipipeline/dataviz/react/src/components/DNSAnalysis.tsx +++ /dev/null @@ -1,204 +0,0 @@ -import * as React from "react"; - -import { useEffect, useState, useMemo } from "react"; - -import { Flex, Box, Text, theme, Heading, Button } from "ooni-components" - -import styled from 'styled-components' - -import ReactJson from 'react-json-view' -import PacmanLoader from "react-spinners/PacmanLoader"; - - -const DataSectionTitle = styled.p` - font-weight: bold; - padding: 8px 0 0; - margin: 0; -` -const DataSectionValue = styled.p` - font-weight: normal; - padding: 0; - margin: 0; - width: 50%; - white-space: nowrap; - overflow: hidden; - text-overflow: ellipsis; -` - -const DataSectionContainer = styled.div` - background-color: ${props => props.theme.colors.gray3}; - padding: 16px; - margin-bottom: 16px; -` - -const AnalysisTableName = styled.td` - font-weight: bold; - padding-right: 8px; -` - -const DNSAnswersList = styled.ul` - padding: 0px; - margin: 0; - list-style: none; -` - -const DataSection = ({ keys, data }) => { - console.log(data) - return ( - - {keys.map((k) => ( - - {k} - {data[k]} - - ))} - - ) -} - -const AnalysisTable = ({ keys, data }) => { - return ( - - - {keys.map((key) => ({key}))} - -
{data[key]}
- ) -} - -const AnalysisElement = ({ data }) => { - const metaKeys = [ - 'report_id', 'input', 'measurement_uid', 'probe_cc', 'probe_asn', - 'measurement_start_time', 'resolver_ip', 'resolver_asn', 'resolver_cc', - 'resolver_as_org_name', 'resolver_as_cc', 'resolver_is_scrubbed', - 'resolver_asn_probe', 'resolver_as_org_name_probe', - 'dns_engine_resolver_address', 'dns_engine' - ] - - const analysisKeys = [ - 'exp_dns_failure', 'exp_dns_answers', 'exp_dns_answers_count', - ] - - const analysisTableBoolsKeys = [ - 'exp_answer_contains_bogon', - 'exp_answer_contains_matching_probe_cc', - 'exp_answer_contains_matching_probe_asn', - 'exp_answer_contains_matching_probe_as_org_name', - ] - - const analysisTableAnswersKeys = [ - 'dns_answers_all_asn_count', - 'dns_answers_ip_match_all_count', - 'dns_answers_ip_match_tls_consistent_count', - 'dns_answers_ip_match_tls_consistent_include_probe_count', - 'dns_answers_ip_match_ctrl_count', - 'dns_answers_asn_match_all_count', - 'dns_answers_asn_match_tls_consistent_count', - 'dns_answers_as_org_name_match_all_count', - 'dns_answers_as_org_name_match_tls_consistent_count', - ] - - const analysisTableFailureKeys = [ - 'failure_asn_count', - 'nxdomain_asn_count', - 'ok_asn_count', - 'ctrl_matching_failures_count', - 'ctrl_failure_count' - ] - - const [loading, setLoading] = useState(false); - const [rawData, setRawData] = useState(null); - - const loadRawData = async () => { - setRawData(null) - setLoading(true) - try { - let response = await fetch(`/api/_/data/dns_analysis_raw?measurement_uid=${data.measurement_uid}`); - let json = await response.json(); - setLoading(false) - setRawData(json) - } catch (error) { - console.log(error); - setLoading(false) - return { success: false }; - } - } - - return ( - - {data.hostname} - -
- - - exp_dns_answers - - {data['exp_dns_answers'].map((answer) => (
  • {answer[0]} - {answer[1]} - {answer[2]}
    • ))} -     -     - - exp_dns_answers_count - {data['exp_dns_answers_count']} - - - exp_dns_failure - {data['exp_dns_failure']} - -     - - - - - - - - - - - - - - - {rawData && } -     - ) -} - -const DNSAnalysis = () => { - const [analysisData, setAnalysisData] = useState([]); - const [loading, setLoading] = useState(false); - - const fetchData = async () => { - setLoading(true) - try { - let response = await fetch(`/api/_/data/dns_analysis`); - let json = await response.json(); - setLoading(false) - return { success: true, data: json }; - } catch (error) { - console.log(error); - setLoading(false) - return { success: false }; - } - } - - useEffect(() => { - (async () => { - let res = await fetchData(); - if (res.success) { - setAnalysisData(res.data); - } - })(); - }, []); - - return ( - <> - {analysisData.length == 0 && } - {analysisData && - analysisData.map((data) => ) - } - - ) -} - -export default DNSAnalysis \ No newline at end of file diff --git a/oonipipeline/src/oonipipeline/dataviz/react/src/components/Dataviz.tsx b/oonipipeline/src/oonipipeline/dataviz/react/src/components/Dataviz.tsx deleted file mode 100644 index a18673e5..00000000 --- a/oonipipeline/src/oonipipeline/dataviz/react/src/components/Dataviz.tsx +++ /dev/null @@ -1,422 +0,0 @@ -import * as React from "react"; -import { useState, useEffect, useMemo } from "react"; -import { Vega } from 'react-vega'; - -import PacmanLoader from "react-spinners/PacmanLoader"; - -import styled from 'styled-components' - -import { MdExpandMore, MdExpandLess, MdArrowUpward, MdArrowDownward } from "react-icons/md"; - -import { useTable, useSortBy, useGroupBy, useExpanded } from 'react-table' - -import { Flex, Box, Heading, Text, theme } from "ooni-components"; - -const vegaEmbedDefaults = { - actions: { - export: true, - source: true, - editor: false, - compiled: false, - } -} - -const ChartDomainBlockingByASN = ({ probeCC, domainName, onClick }) => { - const [data, setData] = useState({}); - const [dataLoaded, setDataLoaded] = useState(false); - - const fetchData = async () => { - try { - let response = await fetch(`/api/_/viz/chart/blocking_of_domain_by_asn?probe_cc=${probeCC}&domain_name=${domainName}`); - let json = await response.json(); - return { success: true, data: json }; - } catch (error) { - console.log(error); - return { success: false }; - } - } - - useEffect(() => { - (async () => { - setDataLoaded(false); - let res = await fetchData(); - if (res.success) { - setData(res.data); - setDataLoaded(true); - } - })(); - }, [probeCC, domainName]); - - - const handleNewView = (view) => { - view.addEventListener("click", (_, item) => { - if (item) { - onClick(item.datum.probe_asn) - } - }) - } - - return ( - dataLoaded ? - - : Loading data... - ) -} - -const ChartDomainBlockingInASN = ({ probeCC, domainName, probeASN }) => { - const [data, setData] = useState({}); - const [dataLoaded, setDataLoaded] = useState(false); - - const fetchData = async () => { - try { - let response = await fetch(`/api/_/viz/chart/blocking_of_domain_in_asn?probe_cc=${probeCC}&domain_name=${domainName}&probe_asn=${probeASN}`); - let json = await response.json(); - return { success: true, data: json }; - } catch (error) { - console.log(error); - return { success: false }; - } - } - - useEffect(() => { - (async () => { - setDataLoaded(false); - let res = await fetchData(); - if (res.success) { - setData(res.data); - setDataLoaded(true); - } - })(); - }, [probeCC, domainName, probeASN]); - - return ( - dataLoaded ? - - : Loading data... - ) -} - -const ChartWorldMap = ({ data, onClick }) => { - const [spec, setSpec] = useState({}); - const [dataLoaded, setDataLoaded] = useState(false); - - const fetchSpec = async () => { - try { - let response = await fetch(`/api/_/viz/chart/world_map`); - let json = await response.json(); - return { success: true, data: json }; - } catch (error) { - console.log(error); - return { success: false }; - } - } - - useEffect(() => { - (async () => { - setDataLoaded(false); - let res = await fetchSpec(); - if (res.success) { - setSpec(res.data); - setDataLoaded(true); - } - })(); - }, [data]); - - - const handleNewView = (view) => { - view.addEventListener("click", (_, item) => { - if (item) { - onClick({ "cc": item.datum.probe_cc, "name": item.datum.name }) - } - }) - } - - return ( - dataLoaded ? - - : Loading data... - ) -} - -const StyleCountryTable = styled.div` - padding: 1rem; - - table { - border-spacing: 0; - border: 1px solid black; - - tr { - :last-child { - td { - border-bottom: 0; - } - } - } - - th, - td { - margin: 0; - padding: 0.5rem; - border-bottom: 1px solid black; - border-right: 1px solid black; - - :last-child { - border-right: 0; - } - } - } -` - -const CountryTable = ({ data, onDomainSelected }) => { - const columns = useMemo(() => [ - { - id: 'category_code', - Header: 'Category Code', - accessor: 'category_code' - }, - { - id: 'domain_name', - Header: 'Domain', - accessor: 'domain_name', - aggregate: 'count', - Aggregated: ({ value }) => `${value} domains`, - }, - { - id: 'blocked_asns', - Header: 'Blocked ASNS', - accessor: 'blocked_asns', - aggregate: 'average', - Aggregated: ({ value }) => `${value} (avg)`, - }, - { - id: 'ok_asns', - Header: 'OK ASNS', - accessor: 'ok_asns', - aggregate: 'average', - Aggregated: ({ value }) => `${value} (avg)`, - }, - ], []) - - const initialGroupBy = useMemo(() => ["category_code"], []) - const initialSortBy = useMemo(() => [{ "id": "category_code" }], []) - - const { - getTableProps, - getTableBodyProps, - headerGroups, - rows, - prepareRow, - state: { groupBy, expanded }, - } = useTable( - { - initialState: { - groupBy: initialGroupBy, - sortBy: initialSortBy - }, - columns, - data, - }, - useGroupBy, - useSortBy, - useExpanded - ) - - const onClickCell = (cell) => { - if (!cell.isAggregated && cell.column.id == "domain_name") { - onDomainSelected(cell.value) - } - } - - return ( - - - - {headerGroups.map(headerGroup => ( - - {headerGroup.headers.map(column => ( - // Add the sorting props to control sorting. For this example - // we can add them into the header props - - ))} - - ))} - - - {rows.map( - (row, i) => { - prepareRow(row); - return ( - - {row.cells.map(cell => { - return ( - - ) - })} - - ) - } - )} - -
    - {column.render('Header')} - {/* Add a sort direction indicator */} - - {column.isSorted - ? column.isSortedDesc - ? - : - : ''} - -
    onClickCell(cell)} - {...cell.getCellProps()} - style={{ - background: cell.isGrouped - ? theme.colors.gray2 - : cell.isAggregated - ? theme.colors.gray1 - : cell.isPlaceholder - ? 'white' - : 'white', - }} - > - {cell.isGrouped ? ( - // If it's a grouped cell, add an expander and row count - <> - - {row.isExpanded ? : } - {' '} - {cell.render('Cell')} ({row.subRows.length}) - - ) : cell.isAggregated ? ( - // If the cell is aggregated, use the Aggregated - // renderer for cell - cell.render('Aggregated') - ) : cell.isPlaceholder ? null : ( // For cells with repeated values, render null - // Otherwise, just render the regular cell - cell.render('Cell') - )} -
    -     - ) - -} - -const StyleLoader = styled.div` - position: fixed; - left: 0px; - top: 0px; - width: 100%; - height: 100%; - z-index: 9999999999; - overflow: hidden; -` - -const GeneralLoader = ({ loading }) => { - return ( - loading ? - - - - - - - ...loading... - - - - : null - ) -} - -const DataViz = () => { - const [selectedASN, setSelectedASN] = useState(null); - const [selectedCC, setSelectedCC] = useState(null); - const [selectedCountry, setSelectedCountry] = useState(""); - const [selectedDomainName, setSelectedDomainName] = useState(null); - - const [worldMapData, setWorldMapData] = useState([]); - const [loading, setLoading] = useState(false) - - const [tableData, setTableData] = useState(null); - - const fetchData = async () => { - try { - let response = await fetch(`/api/_/viz/data/world_map`); - let json = await response.json(); - return { success: true, data: json }; - } catch (error) { - console.log(error); - return { success: false }; - } - } - - useEffect(() => { - (async () => { - setLoading(true); - let res = await fetchData(); - if (res.success) { - setWorldMapData(res.data); - setLoading(false); - } - })(); - }, []); - - const onSelectedASN = (probe_asn) => { - setSelectedASN(probe_asn) - } - - const onSelectedCountry = ({ cc, name }) => { - setSelectedDomainName(null) - setSelectedASN(null) - - setSelectedCountry(name) - setSelectedCC(cc) - } - - useEffect(() => { - if (selectedCC !== null) { - const tableData = worldMapData.filter((d) => d.probe_cc == selectedCC) - console.log("setting table data", tableData, worldMapData) - setTableData(tableData) - } - }, [selectedCC]) - - const onDomainSelected = (domainName) => { - if (domainName == selectedDomainName) { - return - } - setSelectedASN(null) - setSelectedDomainName(domainName) - } - - return ( - - - - - - - {selectedCountry} - - - {tableData && } - - - - - {selectedASN !== null && } - - - {selectedDomainName !== null && } - - - - - - - ) - -} - -export default DataViz \ No newline at end of file diff --git a/oonipipeline/src/oonipipeline/dataviz/react/src/index.tsx b/oonipipeline/src/oonipipeline/dataviz/react/src/index.tsx deleted file mode 100644 index e3ed545e..00000000 --- a/oonipipeline/src/oonipipeline/dataviz/react/src/index.tsx +++ /dev/null @@ -1,15 +0,0 @@ -import * as React from "react"; -import * as ReactDOM from "react-dom"; -import { HashRouter } from "react-router-dom"; -import "@fontsource/fira-sans"; - -import App from "./App"; - -document.addEventListener("DOMContentLoaded", (event) => { - ReactDOM.render( - - - , - document.getElementById("root") - ); -}); diff --git a/oonipipeline/src/oonipipeline/dataviz/react/yarn.lock b/oonipipeline/src/oonipipeline/dataviz/react/yarn.lock deleted file mode 100644 index d276b91d..00000000 --- a/oonipipeline/src/oonipipeline/dataviz/react/yarn.lock +++ /dev/null @@ -1,4476 +0,0 @@ -# THIS IS AN AUTOGENERATED FILE. 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-yargs@~17.6.0: - version "17.6.2" - resolved "https://registry.yarnpkg.com/yargs/-/yargs-17.6.2.tgz#2e23f2944e976339a1ee00f18c77fedee8332541" - integrity sha512-1/9UrdHjDZc0eOU0HxOHoS78C69UD3JRMvzlJ7S79S2nTaWRA/whGCTV8o9e/N/1Va9YIV7Q4sOxD8VV4pCWOw== - dependencies: - cliui "^8.0.1" - escalade "^3.1.1" - get-caller-file "^2.0.5" - require-directory "^2.1.1" - string-width "^4.2.3" - y18n "^5.0.5" - yargs-parser "^21.1.1" diff --git a/oonipipeline/src/oonipipeline/dataviz/templates/react.html b/oonipipeline/src/oonipipeline/dataviz/templates/react.html deleted file mode 100644 index fae496c6..00000000 --- a/oonipipeline/src/oonipipeline/dataviz/templates/react.html +++ /dev/null @@ -1,18 +0,0 @@ - - - - - - OONI Data Viz - - - {% block css %}{% endblock %} - - - -
    - - {% block js %}{% endblock %} - - - diff --git a/oonipipeline/src/oonipipeline/dataviz/templates/vega.html b/oonipipeline/src/oonipipeline/dataviz/templates/vega.html deleted file mode 100644 index ab592e4d..00000000 --- a/oonipipeline/src/oonipipeline/dataviz/templates/vega.html +++ /dev/null @@ -1,21 +0,0 @@ - - - - - - - - - - - -
    - - - - - diff --git a/oonipipeline/src/oonipipeline/dataviz/viz.py b/oonipipeline/src/oonipipeline/dataviz/viz.py deleted file mode 100644 index c15bac8e..00000000 --- a/oonipipeline/src/oonipipeline/dataviz/viz.py +++ /dev/null @@ -1,1055 +0,0 @@ -# This is currently enabled due to: https://github.com/altair-viz/altair/pull/2681 -# type: ignore - -import numpy as np -import pandas as pd -import altair as alt - -from .theme import OONI_COLOR_SCHEME -from .utils import click_query - -from urllib.parse import urlparse -import requests - -world_100m = requests.get( - "https://cdn.jsdelivr.net/npm/vega-datasets@v1.29.0/data/world-110m.json" -).json() -alt_data_world_110m = alt.Data( - values=world_100m, format={"type": "topojson", "feature": "countries"} -) - -country_centers = pd.read_csv( - "https://raw.githubusercontent.com/albertyw/avenews/master/old/data/average-latitude-longitude-countries.csv" -) -country_centers = country_centers[ - ["ISO 3166 Country Code", "Latitude", "Longitude"] -].set_index("ISO 3166 Country Code") - -country_meta = pd.read_json( - "https://raw.githubusercontent.com/ooni/country-util/master/data/country-list.json" -) -country_meta = country_meta[["name", "iso3166_alpha2", "iso3166_num"]].set_index( - "iso3166_alpha2" -) - -citizenlab_global_tl = pd.read_csv( - "https://raw.githubusercontent.com/citizenlab/test-lists/master/lists/global.csv" -) -citizenlab_global_tl["domain_name"] = citizenlab_global_tl["url"].apply( - lambda x: urlparse(x).netloc -) - - -def get_df_dns_analysis_raw( - measurement_uid, start_day="2023-01-01", end_day="2023-01-02" -): - params = { - "start_day": start_day, - "end_day": end_day, - "measurement_uid": measurement_uid, - } - q = """ - SELECT * FROM ( - SELECT - report_id, - input, - measurement_uid, - probe_cc, - probe_asn, - probe_as_org_name, - measurement_start_time, - resolver_ip, - resolver_asn, - resolver_cc, - resolver_as_org_name, - resolver_as_cc, - resolver_is_scrubbed, - resolver_asn_probe, - resolver_as_org_name_probe, - dns_engine_resolver_address, - dns_engine, - dns_query_type, - hostname, - any(dns_failure) as exp_dns_failure, - any(ip_is_bogon) OR 0 as exp_answer_contains_bogon, - any(ip_as_cc = probe_cc) OR 0 as exp_answer_contains_matching_probe_cc, - any(dns_answer_asn = probe_asn) OR 0 as exp_answer_contains_matching_probe_asn, - any(lower(ip_as_org_name) = lower(probe_as_org_name)) OR 0 as exp_answer_contains_matching_probe_as_org_name, - groupArrayIf( - tuple(dns_answer, dns_answer_asn, dns_answer_as_org_name, ip_as_cc), - dns_answer IS NOT NULL - ) as dns_answers - FROM obs_web - WHERE - measurement_start_time > %(start_day)s - AND measurement_start_time < %(end_day)s - AND measurement_uid = %(measurement_uid)s - AND test_name = 'web_connectivity' - AND (dns_answer IS NOT NULL OR dns_failure IS NOT NULL) - GROUP BY report_id, - input, - measurement_uid, - probe_cc, - probe_asn, - probe_as_org_name, - measurement_start_time, - resolver_ip, - resolver_asn, - resolver_cc, - resolver_as_org_name, - resolver_as_cc, - resolver_is_scrubbed, - resolver_asn_probe, - resolver_as_org_name_probe, - dns_engine_resolver_address, - dns_engine, hostname, dns_query_type -) as exp -LEFT JOIN ( - SELECT - hostname, - answers, - failure_asns, - nxdomain_asns, - ok_asns, - ctrl_answers, - ctrl_failures - FROM ( - SELECT - hostname, - - groupArrayIf(tuple(dns_answer, ip_as_org_name, ip_asn, answer_asns, tls_consistent_asns), dns_answer IS NOT NULL) as answers, - - anyIf(failure_asns, dns_answer IS NULL) as failure_asns, - - anyIf(nxdomain_asns, dns_answer IS NULL) as nxdomain_asns, - - arrayReduce('groupUniqArray', arrayFlatten(groupUniqArray(answer_asns))) as ok_asns - FROM ( - SELECT - hostname, - dns_answer, - ip_as_org_name, - ip_asn, - groupUniqArrayIf(tuple(probe_cc, probe_asn), tls_is_certificate_valid = 1) as tls_consistent_asns, - groupUniqArrayIf(tuple(probe_cc, probe_asn), dns_failure IS NULL) as answer_asns, - groupUniqArrayIf(tuple(probe_cc, probe_asn), dns_failure IS NOT NULL) as failure_asns, - groupUniqArrayIf(tuple(probe_cc, probe_asn), dns_failure = 'dns_nxdomain_error') as nxdomain_asns - FROM obs_web - WHERE - measurement_start_time > %(start_day)s - AND measurement_start_time < %(end_day)s - AND (dns_answer IS NOT NULL OR dns_failure IS NOT NULL) - GROUP BY hostname, dns_answer, ip_as_org_name, ip_asn - ) GROUP BY hostname - ) as obs - FULL OUTER JOIN ( - SELECT - hostname, - groupUniqArrayIf(tuple(ip, ip_count), dns_failure IS NULL) as ctrl_answers, - groupArrayIf(tuple(dns_failure, failure_count), dns_failure IS NOT NULL) as ctrl_failures - FROM ( - SELECT - hostname, - ip, - COUNT() as ip_count, - dns_failure, - COUNT() as failure_count - FROM obs_web_ctrl - WHERE - measurement_start_time > %(start_day)s - AND measurement_start_time < %(end_day)s - AND ( - dns_success = 1 - OR dns_failure IS NOT NULL - ) - GROUP BY hostname, ip, dns_failure - ) GROUP BY hostname - ) as ctrl - USING hostname -) as dns_gt -USING hostname - """ - return click_query(q, **params) - - -def get_df_dns_analysis(start_day="2023-01-01", end_day="2023-01-02", limit=100): - params = {"start_day": start_day, "end_day": end_day} - q = """WITH -arrayDistinct(arrayMap(x -> x.1, exp.dns_answers)) as exp_dns_answers_ips, -arrayDistinct(arrayMap(x -> x.2, exp.dns_answers)) as exp_dns_answers_asns, -arrayDistinct(arrayMap(x -> lower(x.3), exp.dns_answers)) as exp_dns_answers_as_org_names, - --- tuple(dns_answer, ip_as_org_name, ip_asn, answer_asns, tls_consistent_asns) -flatten(arrayMap( - asn -> arrayFilter( - y -> y.3 IS NOT NULL AND asn IS NOT NULL AND assumeNotNull(y.3) = assumeNotNull(asn), - dns_gt.answers - ), - exp_dns_answers_asns -)) as dns_answers_asn_match, - --- tuple(dns_answer, ip_as_org_name, ip_asn, answer_asns, tls_consistent_asns) -arrayMap( - x -> tuple( - x.1, - x.2, - x.3, - -- all answers_asns, except probe_asn - arrayFilter( - y -> y.1 != exp.probe_cc OR y.2 != exp.probe_asn, - x.4 - ), - -- all tls_consistent_asns, except probe_asn - arrayFilter( - y -> y.1 != exp.probe_cc OR y.2 != exp.probe_asn, - x.5 - ) - ), - dns_answers_asn_match -) as dns_answers_asn_match_no_asn, - -arrayMap( - x -> tuple( - x.2, - x.3, - length(x.4), - length(x.5) - ), dns_answers_asn_match_no_asn -) as dns_answers_asn_match_no_asn_counts_tup, - --- dns_answers in the ground_truth that match the AS ORG name of the answers in the experiment --- tuple(dns_answer, ip_as_org_name, ip_asn, answer_asns, tls_consistent_asns) -flatten(arrayMap( - asorgname -> arrayFilter( - y -> y.2 IS NOT NULL AND asorgname IS NOT NULL AND lower(assumeNotNull(y.2)) = lower(assumeNotNull(asorgname)), - dns_gt.answers - ), - exp_dns_answers_as_org_names -)) as dns_answers_as_org_name_match, - --- filter the sub-lists in the answers to exclude the ones from the VP of the probe --- tuple(dns_answer, ip_as_org_name, ip_asn, answer_asns, tls_consistent_asns) -arrayMap( - x -> tuple( - x.1, -- dns_answer - x.2, -- ip_as_org_name - x.3, -- ip_asn - -- all answers_asns, except probe_asn - arrayFilter( - y -> y.1 != exp.probe_cc OR y.2 != exp.probe_asn, - x.4 - ), - -- all tls_consistent_asns, except probe_asn - arrayFilter( - y -> y.1 != exp.probe_cc OR y.2 != exp.probe_asn, - x.5 - ) - ), - dns_answers_as_org_name_match -) as dns_answers_as_org_name_match_no_asn, - --- tuple(dns_answer, ip_as_org_name, ip_asn, answer_asns, tls_consistent_asns) -arrayMap( - ip -> arrayFirst( - y -> y.1 IS NOT NULL AND ip IS NOT NULL AND assumeNotNull(y.1) = assumeNotNull(ip), - dns_gt.answers - ), - exp_dns_answers_ips -) as dns_answers_match, - --- tuple(dns_answer, ip_as_org_name, ip_asn, answer_asns, tls_consistent_asns) -arrayMap( - x -> tuple( - x.1, -- dns_answer - x.2, -- ip_as_org_name - x.3, -- ip_asn - -- all answers_asns, except probe_asn - arrayFilter( - y -> y.1 != exp.probe_cc OR y.2 != exp.probe_asn, - x.4 - ), - -- all tls_consistent_asns, except probe_asn - arrayFilter( - y -> y.1 != exp.probe_cc OR y.2 != exp.probe_asn, - x.5 - ) - ), - dns_answers_match -) as dns_answers_match_no_asn, - -arrayMap( - x -> tuple( - x.2, -- ip_as_org_name - x.3, -- ip_asn - length(x.4), -- all_answers - length(x.5) -- tls_consistent - ), dns_answers_match_no_asn -) as dns_answers_match_no_asn_counts_tup, - -arrayFilter( - x -> indexOf(exp_dns_answers_asns, x.2) != 0, - dns_answers_asn_match_no_asn_counts_tup -) as dns_answer_matching_asn, - -arrayFilter( - x -> indexOf(exp_dns_answers_as_org_names, lower(x.1)) != 0, - dns_answers_as_org_name_match_no_asn_counts_tup -) as dns_answer_matching_as_org_name, - -arrayMap( - x -> tuple( - x.2, -- ip_as_org_name - x.3, -- ip_asn - length(x.4), - length(x.5) - ), dns_answers_as_org_name_match_no_asn -) as dns_answers_as_org_name_match_no_asn_counts_tup - - -SELECT - exp.report_id, - exp.input, - exp.measurement_uid, - exp.probe_cc, - exp.probe_asn, - exp.measurement_start_time, - exp.resolver_ip, - exp.resolver_asn, - exp.resolver_cc, - exp.resolver_as_org_name, - exp.resolver_as_cc, - exp.resolver_is_scrubbed, - exp.resolver_asn_probe, - exp.resolver_as_org_name_probe, - exp.dns_engine_resolver_address, - exp.dns_engine, - exp.hostname, - exp.exp_dns_failure, - - -- tuple(dns_answer, dns_answer_asn, dns_answer_as_org_name) - exp.dns_answers as exp_dns_answers, - - length(exp_dns_answers) as exp_dns_answers_count, - exp.exp_answer_contains_bogon, - - exp.exp_answer_contains_matching_probe_cc, - exp.exp_answer_contains_matching_probe_asn, - exp.exp_answer_contains_matching_probe_as_org_name, - - arraySum(arrayMap(x -> length(x.4), dns_gt.answers)) as dns_answers_all_asn_count, - - arraySum( - arrayMap( - x -> x.3, - dns_answers_match_no_asn_counts_tup - ) - ) as dns_answers_ip_match_all_count, - - --dns_answers_asn_match_tls_consistent_include_probe_count, - --dns_answers_as_org_name_match_tls_consistent_include_probe_count, - - arraySum( - arrayMap( - x -> x.4, - dns_answers_match_no_asn_counts_tup - ) - ) as dns_answers_ip_match_tls_consistent_count, - - arraySum( - arrayMap( - x -> length(x.5), - dns_answers_match - ) - ) as dns_answers_ip_match_tls_consistent_include_probe_count, - - arraySum( - arrayMap( - x -> x.2, - arrayFilter( - x -> indexOf(exp_dns_answers_ips, x.1) != 0, - dns_gt.ctrl_answers - ) - ) - ) as dns_answers_ip_match_ctrl_count, - - arraySum( - arrayMap( - x -> x.3, - dns_answer_matching_asn - ) - ) as dns_answers_asn_match_all_count, - - arraySum( - arrayMap( - x -> x.4, - dns_answer_matching_asn - ) - ) as dns_answers_asn_match_tls_consistent_count, - - arraySum( - arrayMap( - x -> x.3, - dns_answer_matching_as_org_name - ) - ) as dns_answers_as_org_name_match_all_count, - - arraySum( - arrayMap( - x -> x.4, - dns_answer_matching_as_org_name - ) - ) as dns_answers_as_org_name_match_tls_consistent_count, - - -- tuple(probe_cc, probe_asn) - --dns_gt.failure_asns, - - length(arrayFilter( - x -> x.1 != exp.probe_cc OR x.2 != exp.probe_asn, - dns_gt.failure_asns - )) as failure_asn_count, - - -- tuple(probe_cc, probe_asn) - --dns_gt.nxdomain_asns, - - -- All ASNS with NXDOMAIN != (probe_cc, probe_asn) - length(arrayFilter( - x -> x.1 != exp.probe_cc OR x.2 != exp.probe_asn, - dns_gt.nxdomain_asns - )) as nxdomain_asn_count, - - -- tuple(probe_cc, probe_asn) - --dns_gt.ok_asns, - - -- All ASNS with NXDOMAIN != (probe_cc, probe_asn) - length(arrayFilter( - x -> x.1 != exp.probe_cc OR x.2 != exp.probe_asn, - dns_gt.ok_asns - )) as ok_asn_count, - - -- tuple(ip, ip_count) - --dns_gt.ctrl_answers, - - -- tuple(dns_failure, failure_count) - --dns_gt.ctrl_failures, - - --dns_answers_ip_match_ctrl_count, - --ctrl_failures_count - - - arraySum( - arrayMap( - x -> x.2, - arrayFilter( - x -> exp_dns_failure IS NOT NULL AND x.1 = exp_dns_failure, - dns_gt.ctrl_failures - ) - ) - ) as ctrl_matching_failures_count, - - arraySum( - arrayMap( - x -> x.2, - arrayFilter( - x -> x.1 IS NOT NULL, - dns_gt.ctrl_failures - ) - ) - ) as ctrl_failure_count - -FROM ( - SELECT - report_id, - input, - measurement_uid, - probe_cc, - probe_asn, - probe_as_org_name, - measurement_start_time, - resolver_ip, - resolver_asn, - resolver_cc, - resolver_as_org_name, - resolver_as_cc, - resolver_is_scrubbed, - resolver_asn_probe, - resolver_as_org_name_probe, - dns_engine_resolver_address, - dns_engine, - dns_query_type, - hostname, - any(dns_failure) as exp_dns_failure, - any(ip_is_bogon) OR 0 as exp_answer_contains_bogon, - any(ip_as_cc = probe_cc) OR 0 as exp_answer_contains_matching_probe_cc, - any(dns_answer_asn = probe_asn) OR 0 as exp_answer_contains_matching_probe_asn, - any(lower(ip_as_org_name) = lower(probe_as_org_name)) OR 0 as exp_answer_contains_matching_probe_as_org_name, - groupArrayIf( - tuple(dns_answer, dns_answer_asn, dns_answer_as_org_name, ip_as_cc), - dns_answer IS NOT NULL - ) as dns_answers - FROM obs_web - WHERE - measurement_start_time > %(start_day)s - AND measurement_start_time < %(end_day)s - AND test_name = 'web_connectivity' - AND (dns_answer IS NOT NULL OR dns_failure IS NOT NULL) - GROUP BY report_id, - input, - measurement_uid, - probe_cc, - probe_asn, - probe_as_org_name, - measurement_start_time, - resolver_ip, - resolver_asn, - resolver_cc, - resolver_as_org_name, - resolver_as_cc, - resolver_is_scrubbed, - resolver_asn_probe, - resolver_as_org_name_probe, - dns_engine_resolver_address, - dns_engine, hostname, dns_query_type -) as exp -LEFT JOIN ( - SELECT - hostname, - answers, - failure_asns, - nxdomain_asns, - ok_asns, - ctrl_answers, - ctrl_failures - FROM ( - SELECT - hostname, - - groupArrayIf(tuple(dns_answer, ip_as_org_name, ip_asn, answer_asns, tls_consistent_asns), dns_answer IS NOT NULL) as answers, - - anyIf(failure_asns, dns_answer IS NULL) as failure_asns, - - anyIf(nxdomain_asns, dns_answer IS NULL) as nxdomain_asns, - - arrayReduce('groupUniqArray', arrayFlatten(groupUniqArray(answer_asns))) as ok_asns - FROM ( - SELECT - hostname, - dns_answer, - ip_as_org_name, - ip_asn, - groupUniqArrayIf(tuple(probe_cc, probe_asn), tls_is_certificate_valid = 1) as tls_consistent_asns, - groupUniqArrayIf(tuple(probe_cc, probe_asn), dns_failure IS NULL) as answer_asns, - groupUniqArrayIf(tuple(probe_cc, probe_asn), dns_failure IS NOT NULL) as failure_asns, - groupUniqArrayIf(tuple(probe_cc, probe_asn), dns_failure = 'dns_nxdomain_error') as nxdomain_asns - FROM obs_web - WHERE - measurement_start_time > %(start_day)s - AND measurement_start_time < %(end_day)s - AND (dns_answer IS NOT NULL OR dns_failure IS NOT NULL) - GROUP BY hostname, dns_answer, ip_as_org_name, ip_asn - ) GROUP BY hostname - ) as obs - FULL OUTER JOIN ( - SELECT - hostname, - groupUniqArrayIf(tuple(ip, ip_count), dns_failure IS NULL) as ctrl_answers, - groupArrayIf(tuple(dns_failure, failure_count), dns_failure IS NOT NULL) as ctrl_failures - FROM ( - SELECT - hostname, - ip, - COUNT() as ip_count, - dns_failure, - COUNT() as failure_count - FROM obs_web_ctrl - WHERE - measurement_start_time > %(start_day)s - AND measurement_start_time < %(end_day)s - AND ( - dns_success = 1 - OR dns_failure IS NOT NULL - ) - GROUP BY hostname, ip, dns_failure - ) GROUP BY hostname - ) as ctrl - USING hostname -) as dns_gt -USING hostname - """ - if limit > 0: - params["limit"] = limit - q += "LIMIT %(limit)d" - - return click_query(q, **params) - - -def get_df_blocking_of_domain_by_asn( - domain_name, probe_cc, start_time="2022-11-03", end_time="2022-12-03" -): - q_args = { - "domain_name": domain_name, - "probe_cc": probe_cc, - "start_time": start_time, - "end_time": end_time, - } - - df = click_query( - """ - SELECT - domain_name, - probe_cc, - probe_asn, - probe_as_org_name, - any(max_blocked) as max_blocked, - any(max_blocked_label) as blocked_label, - any(max_down) as max_down, - any(max_down_label) as down_label, - any(max_ok) as max_ok, - - (max_blocked / (max_ok + max_down + max_blocked)) as blocked, - (max_down / (max_ok + max_down + max_blocked)) as down, - (max_ok / (max_ok + max_down + max_blocked)) as ok, - SUM(cnt) as count - FROM ( - SELECT - domain_name, - probe_cc, - probe_asn, - probe_as_org_name, - max(ema_avg_blocked) OVER (PARTITION BY probe_cc, probe_asn, domain_name) as max_blocked, - any(outcome_label) OVER (PARTITION BY probe_cc, probe_asn, domain_name ORDER BY ema_avg_blocked DESC) as max_blocked_label, - max(ema_avg_down) OVER (PARTITION BY probe_cc, probe_asn, domain_name) as max_down, - any(outcome_label) OVER (PARTITION BY probe_cc, probe_asn, domain_name ORDER BY ema_avg_down DESC) as max_down_label, - max(ema_avg_down) OVER (PARTITION BY probe_cc, probe_asn, domain_name) as max_down, - max(IF(outcome_category == 'http' OR outcome_category == 'https', ema_avg_ok, 0)) OVER (PARTITION BY probe_cc, probe_asn, domain_name) as max_ok, - cnt - FROM ( - SELECT - domain_name, - probe_cc, - probe_asn, - probe_as_org_name, - outcome_category, - outcome_detail, - outcome_label, - avgWeighted(ema_blocked, cnt) OVER (PARTITION BY probe_cc, probe_asn, domain_name, outcome_category) as ema_avg_blocked, - avgWeighted(ema_down, cnt) OVER (PARTITION BY probe_cc, probe_asn, domain_name, outcome_category) as ema_avg_down, - avgWeighted(ema_ok, cnt) OVER (PARTITION BY probe_cc, probe_asn, domain_name, outcome_category) as ema_avg_ok, - cnt - FROM ( - SELECT - domain_name, - probe_cc, - probe_asn, - probe_as_org_name, - outcome_category, - outcome_detail, - IF(outcome_category = 'ok', 'ok', concat(outcome_category, '.', outcome_detail)) as outcome_label, - exponentialMovingAverage(1)(blocked_score, t) as ema_blocked, - exponentialMovingAverage(1)(down_score, t) as ema_down, - exponentialMovingAverage(1)(ok_score, t) as ema_ok, - toFloat64(Count()) as cnt - FROM ( - SELECT - domain_name, - probe_cc, - probe_asn, - probe_as_org_name, - outcome_category, - IF(startsWith(outcome_detail, 'failure.unknown_failure') OR startsWith(outcome_detail, 'unknown_failure'), - 'failure.unknown', - outcome_detail - ) as outcome_detail, - blocked_score, - ok_score, - down_score, - row_number() OVER (PARTITION BY domain_name, probe_asn, outcome_category, outcome_detail) as t - FROM experiment_result - WHERE timestamp > %(start_time)s AND timestamp < %(end_time)s - AND domain_name = %(domain_name)s AND probe_cc = %(probe_cc)s - ) GROUP BY probe_cc, probe_asn, probe_as_org_name, domain_name, outcome_category, outcome_detail - ) - ) - ) GROUP BY probe_cc, probe_asn, probe_as_org_name, domain_name - """, - **q_args, - ) - return df[ - [ - "domain_name", - "probe_cc", - "probe_asn", - "probe_as_org_name", - "blocked_label", - "down_label", - "count", - "ok", - "blocked", - "down", - ] - ].melt( - [ - "domain_name", - "probe_cc", - "probe_asn", - "probe_as_org_name", - "blocked_label", - "down_label", - "count", - ], - var_name="stat", - value_name="stat_value", - ) - - -def plot_blocking_of_domain_by_asn( - df=None, - domain_name=None, - probe_cc=None, - start_time="2022-11-03", - end_time="2022-12-03", -): - if df is None: - df = get_df_blocking_of_domain_by_asn( - domain_name, probe_cc, start_time=start_time, end_time=end_time - ) - - color_scale = alt.Scale( - domain=["blocked", "down", "ok"], - range=[ - OONI_COLOR_SCHEME["red7"], - OONI_COLOR_SCHEME["orange6"], - OONI_COLOR_SCHEME["green8"], - ], - ) - - base_chart = ( - alt.Chart(df) - .mark_bar() - .encode( - y=alt.Y("probe_asn:O", axis=alt.Axis(labels=False, title=None)), - ) - ) - - bars = base_chart.encode( - x="stat_value:Q", - color=alt.Color("stat", scale=color_scale, title="status"), - tooltip=[ - alt.Tooltip("probe_as_org_name:N", title="Network name"), - alt.Tooltip("probe_asn:N", title="ASN"), - alt.Tooltip("stat_value:Q", title="value"), - alt.Tooltip("blocked_label:N", title="blocked_label"), - alt.Tooltip("down_label:N", title="down_label"), - alt.Tooltip("count:Q", title="count"), - ], - order=alt.Order("stat_value", sort="descending"), - ) - - text = ( - base_chart.mark_text( - align="center", - ) - .transform_filter( - "indexof(datum.blocked_label, 'ok') == -1 & datum.stat == 'blocked'" - ) - .encode(color=alt.value(OONI_COLOR_SCHEME["gray9"]), text="blocked_label:N") - ) - - bar_count = base_chart.encode( - y=alt.Y("probe_asn:O", axis=alt.Axis(labels=True, title="ASN")), - x="count:Q", - ).properties(width=30) - - return alt.hconcat(bar_count, (bars + text)).properties( - title=f"Blocking of {domain_name} in {probe_cc} by ASN" - ) - - -def get_df_blocking_of_domain_in_asn( - domain_name, - probe_cc, - probe_asn, - start_time="2022-11-03", - end_time="2022-12-03", -): - q_args = { - "domain_name": domain_name, - "probe_cc": probe_cc, - "probe_asn": probe_asn, - "start_time": start_time, - "end_time": end_time, - } - return click_query( - """ - SELECT - domain_name, - probe_cc, - probe_asn, - probe_as_org_name, - outcome_category, - outcome_detail, - IF(outcome_category = 'ok', 'ok', concat(outcome_category, '.', outcome_detail)) as outcome_label, - exponentialMovingAverage(1)(blocked_score, t) as ema_blocked, - exponentialMovingAverage(1)(down_score, t) as ema_down, - exponentialMovingAverage(1)(ok_score, t) as ema_ok, - toFloat64(Count()) as cnt - FROM ( - SELECT - domain_name, - probe_cc, - probe_asn, - probe_as_org_name, - outcome_category, - IF(startsWith(outcome_detail, 'failure.unknown_failure') OR startsWith(outcome_detail, 'unknown_failure'), - 'failure.unknown', - outcome_detail - ) as outcome_detail, - blocked_score, - ok_score, - down_score, - row_number() OVER (PARTITION BY domain_name, probe_asn, outcome_category, outcome_detail) as t - FROM experiment_result - WHERE timestamp > %(start_time)s AND timestamp < %(end_time)s - AND domain_name = %(domain_name)s AND probe_cc = %(probe_cc)s - AND probe_asn = %(probe_asn)d - ) GROUP BY probe_cc, probe_asn, probe_as_org_name, domain_name, outcome_category, outcome_detail - """, - **q_args, - ) - - -def plot_blocking_of_domain_in_asn( - df=None, - data_name=None, - domain_name=None, - probe_cc=None, - probe_asn=None, - start_time="2022-11-03", - end_time="2022-12-03", -): - if df is None and data_name: - df = alt.NamedData(data_name) - - if df is None: - df = get_df_blocking_of_domain_in_asn( - domain_name=domain_name, - probe_cc=probe_cc, - probe_asn=probe_asn, - start_time=start_time, - end_time=end_time, - ) - - return ( - alt.Chart(df) - .mark_bar() - .encode( - x=alt.X("outcome_detail:O", title=None), - y=alt.Y("cnt:Q", title="Count"), - color=alt.Color( - "ema_blocked:Q", scale=alt.Scale(scheme="redyellowgreen", reverse=True) - ), - tooltip=[ - alt.Tooltip("cnt:N", title="Measurement count"), - alt.Tooltip("outcome_label:N", title="Outcome"), - alt.Tooltip("ema_blocked:Q", title="Blocked EMA"), - alt.Tooltip("ema_ok:Q", title="OK EMA"), - alt.Tooltip("ema_down:Q", title="Down EMA"), - ], - ) - .properties(height=250) - .facet( - column=alt.Column( - "outcome_category:N", - sort=["dns", "tcp", "tls", "https", "http"], - title=None, - ), - ) - .resolve_scale(x="independent") - .properties( - title=f"{domain_name} in AS{probe_asn} ({probe_cc}) from {start_time} to {end_time}" - ) - ) - - -def get_df_blocking_world_map(blocking_threshold=0.7): - q_args = {"blocking_threshold": blocking_threshold} - df = click_query( - """SELECT - probe_cc, - CountIf(max_blocked > %(blocking_threshold)f) as blocked_asns, - CountIf(max_ok > 0.5) as ok_asns, - domain_name - FROM ( - SELECT - domain_name, - probe_cc, - probe_asn, - any(max_blocked) as max_blocked, - any(max_blocked_label) as max_blocked_label, - any(max_down) as max_down, - any(max_down_label) as max_down_label, - arrayMax([0, 1 - max_blocked - max_down]) as max_ok, - COUNT() - FROM ( - SELECT - domain_name, - probe_cc, - probe_asn, - max(ema_avg_blocked) OVER (PARTITION BY probe_cc, probe_asn, domain_name) as max_blocked, - any(outcome_label) OVER (PARTITION BY probe_cc, probe_asn, domain_name ORDER BY ema_avg_blocked DESC) as max_blocked_label, - max(ema_avg_down) OVER (PARTITION BY probe_cc, probe_asn, domain_name) as max_down, - any(outcome_label) OVER (PARTITION BY probe_cc, probe_asn, domain_name ORDER BY ema_avg_down DESC) as max_down_label - FROM ( - SELECT - domain_name, - probe_cc, - probe_asn, - outcome_category, - outcome_detail, - outcome_label, - avgWeighted(ema_blocked, cnt) OVER (PARTITION BY probe_cc, probe_asn, domain_name, outcome_category) as ema_avg_blocked, - avgWeighted(ema_down, cnt) OVER (PARTITION BY probe_cc, probe_asn, domain_name, outcome_category) as ema_avg_down, - avgWeighted(ema_ok, cnt) OVER (PARTITION BY probe_cc, probe_asn, domain_name, outcome_category) as ema_avg_ok - FROM ( - SELECT - domain_name, - probe_cc, - probe_asn, - outcome_category, - outcome_detail, - IF(outcome_category = 'ok', 'ok', concat(outcome_category, '.', outcome_detail)) as outcome_label, - exponentialMovingAverage(1)(blocked_score, t) as ema_blocked, - exponentialMovingAverage(1)(down_score, t) as ema_down, - exponentialMovingAverage(1)(ok_score, t) as ema_ok, - toFloat64(Count()) as cnt - FROM ( - SELECT - domain_name, - probe_cc, - probe_asn, - outcome_category, - IF(startsWith(outcome_detail, 'failure.unknown_failure') OR startsWith(outcome_detail, 'unknown_failure'), - 'failure.unknown', - outcome_detail - ) as outcome_detail, - blocked_score, - ok_score, - down_score, - row_number() OVER (PARTITION BY domain_name, probe_asn, outcome_category, outcome_detail) as t - FROM experiment_result - WHERE timestamp > '2022-11-03' AND timestamp < '2022-12-03' - ) GROUP BY probe_cc, probe_asn, domain_name, outcome_category, outcome_detail - ) - ) - ) GROUP BY probe_cc, probe_asn, domain_name - ) GROUP BY probe_cc, domain_name - """, - **q_args, - ) - df_blocked_cat = df[df["blocked_asns"] > 0].merge( - citizenlab_global_tl[["category_code", "category_description", "domain_name"]], - how="left", - on="domain_name", - ) - df_final = ( - df_blocked_cat[(~df_blocked_cat["category_code"].isnull())] - .join(country_centers, on="probe_cc") - .join(country_meta, on="probe_cc") - ) - df_final.loc[:, "asn_blocking_perc"] = df_final["blocked_asns"] / ( - df_final["blocked_asns"] + df_final["ok_asns"] - ) - return df_final - - -def plot_blocking_world_map(df=None, data_name=None, blocking_threshold=0.7): - if df is None and data_name: - df = alt.NamedData(data_name) - - if df is None: - df = get_df_blocking_world_map(blocking_threshold=blocking_threshold) - - world_background = alt.Chart(alt_data_world_110m).mark_geoshape( - fill="lightgray", stroke="white" - ) - - world_foreground = ( - alt.Chart(df) - .transform_filter((alt.datum.asn_blocking_perc > 0.2)) - .transform_aggregate( - blocked_sites_in_cat="distinct(domain_name)", - groupby=[ - "probe_cc", - "category_code", - "name", - "Latitude", - "Longitude", - "iso3166_num", - ], - ) - .transform_joinaggregate( - blocked_sites="sum(blocked_sites_in_cat)", - blocked_categories="count()", - blocked_category_array="values(category_code)", - groupby=["probe_cc"], - ) - .transform_calculate( - blocked_category_names="pluck(datum.blocked_category_array, 'category_code')", - ) - .transform_lookup( - lookup="iso3166_num", - from_=alt.LookupData(alt_data_world_110m, "id"), - as_="geom", - default="Other", - ) - .transform_calculate(geometry="datum.geom.geometry", type="datum.geom.type") - .mark_geoshape() - .encode( - color=alt.Color( - "blocked_categories:Q", - scale=alt.Scale(scheme="reds"), - ), - tooltip=[ - alt.Tooltip("name:N", title="Country"), - alt.Tooltip("blocked_categories:Q", title="blocked_categories"), - alt.Tooltip("blocked_sites:Q", title="blocked_sites"), - alt.Tooltip("blocked_category_names:N", title="blocked_category_names"), - ], - ) - ) - - circles = ( - alt.Chart(df) - .transform_filter((alt.datum.asn_blocking_perc > 0.2)) - .transform_aggregate( - blocked_sites_in_cat="distinct(domain_name)", - groupby=["probe_cc", "category_code", "name", "Latitude", "Longitude"], - ) - .transform_joinaggregate( - blocked_sites="sum(blocked_sites_in_cat)", - blocked_categories="count()", - blocked_category_array="values(category_code)", - groupby=["probe_cc"], - ) - .transform_calculate( - blocked_category_names="pluck(datum.blocked_category_array, 'category_code')", - ) - .mark_circle() - .encode( - latitude="Latitude:Q", - longitude="Longitude:Q", - size=alt.Size("blocked_sites:Q", title="blocked_sites"), - tooltip=[ - alt.Tooltip("name:N", title="Country"), - alt.Tooltip("blocked_categories:Q", title="blocked_categories"), - alt.Tooltip("blocked_sites:Q", title="blocked_sites"), - alt.Tooltip("blocked_category_names:N", title="blocked_category_names"), - ], - ) - ) - - return ( - (world_background + world_foreground + circles) - .configure_view(strokeWidth=0) - .properties(width=900, height=600) - .project("naturalEarth1") - ) diff --git a/oonipipeline/src/oonipipeline/dataviz/web.py b/oonipipeline/src/oonipipeline/dataviz/web.py deleted file mode 100644 index 7cb342a7..00000000 --- a/oonipipeline/src/oonipipeline/dataviz/web.py +++ /dev/null @@ -1,201 +0,0 @@ -from dataclasses import asdict -import json -from pathlib import Path - -from flask import Flask, request, render_template - -from oonidata.dataclient import load_measurement -from oonidata.apiclient import get_measurement_dict_by_uid - -from ..analysis.control import ( - BodyDB, - WebGroundTruthDB, - iter_ground_truths_from_web_control, -) -from ..analysis.web_analysis import make_web_analysis -from ..analysis.website_experiment_results import make_website_experiment_results - -from .viz import ( - plot_blocking_world_map, - plot_blocking_of_domain_in_asn, - plot_blocking_of_domain_by_asn, -) -from .viz import ( - get_df_blocking_world_map, - get_df_blocking_of_domain_in_asn, - get_df_blocking_of_domain_by_asn, - get_df_dns_analysis, - get_df_dns_analysis_raw, -) -from ..fingerprintdb import FingerprintDB -from ..netinfo import NetinfoDB - -from ..transforms.observations import measurement_to_observations - -app = Flask(__name__) - - -def to_pretty_json(value): - return json.dumps( - value, sort_keys=True, indent=4, separators=(",", ": "), default=str - ) - - -app.jinja_env.filters["tojson_pretty"] = to_pretty_json - - -@app.route("/analysis/m/") -def analysis_by_msmt(measurement_uid): - data_dir = Path("tests/data/datadir/") - - fingerprintdb = FingerprintDB(datadir=data_dir, download=False) - netinfodb = NetinfoDB(datadir=data_dir, download=False) - raw_msmt = get_measurement_dict_by_uid(measurement_uid) - msmt = load_measurement(msmt=raw_msmt) - web_observations, web_control_observations = measurement_to_observations( - msmt, netinfodb=netinfodb - ) - web_ground_truth_db = WebGroundTruthDB() - web_ground_truth_db.build_from_rows( - rows=iter_ground_truths_from_web_control( - web_control_observations=web_control_observations, - netinfodb=netinfodb, - ), - ) - - web_ground_truths = web_ground_truth_db.lookup_by_web_obs(web_obs=web_observations) - web_analysis = list( - make_web_analysis( - web_observations=web_observations, - web_ground_truths=web_ground_truths, - body_db=BodyDB(db=None), # type: ignore - fingerprintdb=fingerprintdb, - ) - ) - - # assert len(web_analysis) == len( - # web_observations - # ), f"web_analysis != web_obs {len(web_analysis)} != {len(web_observations)}" - # for wa in web_analysis: - # print_nice_vertical(wa) - - website_er = list(make_website_experiment_results(web_analysis)) - assert len(website_er) == 1 - - wer = website_er[0] - analysis_transcript_list = wer.analysis_transcript_list - - # wer.analysis_transcript_list = None - # print_nice_vertical(wer) - # for loni in loni_list: - # pprint(loni.to_dict()) - # print(analysis_transcript_list) - - return render_template( - "analysis.html", - website_experiment_result=asdict(wer), - analysis_transcript_list=analysis_transcript_list, - loni_list=wer.loni_list, - raw_msmt=raw_msmt, - measurement_uid=measurement_uid, - web_analysis=list(map(lambda x: asdict(x), web_analysis)), - web_observations=list(map(lambda x: asdict(x), web_observations)), - loni_blocked_dict=dict(zip(wer.loni_blocked_keys, wer.loni_blocked_values)), - loni_blocked_value=sum(wer.loni_blocked_values), - loni_down_dict=dict(zip(wer.loni_down_keys, wer.loni_down_values)), - loni_down_value=sum(wer.loni_down_values), - loni_ok_value=wer.loni_ok_value, - ) - - -@app.route("/api/_/viz/data/world_map") -def data_world_map(): - blocking_threshold = float(request.args.get("blocking_threshold", 0.7)) - return get_df_blocking_world_map(blocking_threshold=blocking_threshold).to_json( - orient="records" - ) - - -@app.route("/api/_/viz/chart/world_map") -def chart_world_map(): - return plot_blocking_world_map(data_name="data").to_json() - - -@app.route("/viz/world_map") -def viz_world_map(): - return render_template("vega.html", endpoint="chart_world_map") - - -@app.route("/api/_/viz/data/blocking_of_domain_in_asn") -def data_blocking_of_domain_in_asn(): - return get_df_blocking_of_domain_in_asn( - domain_name=request.args.get("domain_name", None), - probe_cc=request.args.get("probe_cc", None), - probe_asn=int(request.args.get("probe_asn", 0)), - start_time=request.args.get("start_time", "2022-11-03"), - end_time=request.args.get("start_time", "2022-12-03"), - ).to_json(orient="records") - - -@app.route("/api/_/viz/chart/blocking_of_domain_in_asn") -def chart_blocking_of_domain_in_asn(): - return plot_blocking_of_domain_in_asn( - domain_name=request.args.get("domain_name", None), - probe_cc=request.args.get("probe_cc", None), - probe_asn=int(request.args.get("probe_asn", 0)), - start_time=request.args.get("start_time", "2022-11-03"), - end_time=request.args.get("start_time", "2022-12-03"), - ).to_json() - - -@app.route("/viz/blocking_of_domain_in_asn") -def viz_blocking_of_domain_in_asn(): - return render_template( - "vega.html", - endpoint="chart_blocking_of_domain_in_asn", - query_args=request.args.to_dict(), - ) - - -@app.route("/api/_/viz/chart/blocking_of_domain_by_asn") -def chart_blocking_of_domain_by_asn(): - return plot_blocking_of_domain_by_asn( - domain_name=request.args.get("domain_name", None), - probe_cc=request.args.get("probe_cc", None), - start_time=request.args.get("start_time", "2022-11-03"), - end_time=request.args.get("start_time", "2022-12-03"), - ).to_json() - - -@app.route("/viz/blocking_of_domain_by_asn") -def viz_blocking_of_domain_by_asn(): - return render_template( - "vega.html", - endpoint="chart_blocking_of_domain_by_asn", - query_args=request.args.to_dict(), - ) - - -@app.route("/api/_/data/dns_analysis") -def data_dns_analysis(): - return get_df_dns_analysis( - start_day="2023-01-01", end_day="2023-01-02", limit=100 - ).to_json(orient="records") - - -@app.route("/api/_/data/dns_analysis_raw") -def data_dns_analysis_raw(): - return get_df_dns_analysis_raw( - measurement_uid=request.args["measurement_uid"], - start_day="2023-01-01", - end_day="2023-01-02", - ).to_json(orient="records") - - -@app.route("/") -def index(): - return render_template("react.html") - - -if __name__ == "__main__": - app.run(debug=True) diff --git a/oonipipeline/src/oonipipeline/temporal/to_port/response_archiver.py b/oonipipeline/src/oonipipeline/temporal/to_port/response_archiver.py index f40688e5..9547342c 100644 --- a/oonipipeline/src/oonipipeline/temporal/to_port/response_archiver.py +++ b/oonipipeline/src/oonipipeline/temporal/to_port/response_archiver.py @@ -25,7 +25,7 @@ from oonidata.dataclient import date_interval, iter_measurements, load_measurement from oonidata.models.nettests.web_connectivity import WebConnectivity -from ..fingerprintdb import FingerprintDB, Fingerprint +from ...fingerprintdb import FingerprintDB, Fingerprint log = logging.getLogger("oonidata.processing") From 2c93783b0dffe2b6d4b3b7b2a4032d9323acd3c7 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arturo=20Filast=C3=B2?= Date: Fri, 23 Aug 2024 14:31:01 +0200 Subject: [PATCH 2/8] Add an observations viewer --- .../src/oonipipeline/dataviz/dependencies.py | 2 +- oonipipeline/src/oonipipeline/dataviz/main.py | 47 ++++++++++ .../dataviz/templates/observations.html | 89 +++++++++++++++++++ 3 files changed, 137 insertions(+), 1 deletion(-) create mode 100644 oonipipeline/src/oonipipeline/dataviz/templates/observations.html diff --git a/oonipipeline/src/oonipipeline/dataviz/dependencies.py b/oonipipeline/src/oonipipeline/dataviz/dependencies.py index 1208b37e..7a3674bc 100644 --- a/oonipipeline/src/oonipipeline/dataviz/dependencies.py +++ b/oonipipeline/src/oonipipeline/dataviz/dependencies.py @@ -9,7 +9,7 @@ class Settings(BaseSettings): clickhouse_url: str = "clickhouse://localhost" - data_dir = "tests/data/datadir" + data_dir: str = "tests/data/datadir" @lru_cache diff --git a/oonipipeline/src/oonipipeline/dataviz/main.py b/oonipipeline/src/oonipipeline/dataviz/main.py index efa2ea46..483792c5 100644 --- a/oonipipeline/src/oonipipeline/dataviz/main.py +++ b/oonipipeline/src/oonipipeline/dataviz/main.py @@ -98,3 +98,50 @@ def analysis_by_msmt( loni_ok_value=wer.loni_ok_value, ), ) + + +@app.get("/observations/m/{measurement_uid}") +def observations_by_msmt( + request: Request, + measurement_uid: str, + settings=Depends(get_settings), +): + data_dir = Path(settings.data_dir) + + netinfodb = NetinfoDB(datadir=data_dir, download=False) + raw_msmt = get_measurement_dict_by_uid(measurement_uid) + msmt = load_measurement(msmt=raw_msmt) + web_observations, web_control_observations = measurement_to_observations( + msmt, netinfodb=netinfodb + ) + + def extract_meta(orig_obs_list): + obs_list = [] + + measurement_meta = {} + probe_meta = {} + processing_meta = {} + for obs in orig_obs_list: + wo_dict = asdict(obs) + measurement_meta = wo_dict.pop("probe_meta", None) + probe_meta = wo_dict.pop("measurement_meta", None) + processing_meta = wo_dict.pop("processing_meta", None) + obs_list.append(wo_dict) + return obs_list, measurement_meta, probe_meta, processing_meta + + web_observations_list, probe_meta, measurement_meta, processing_meta = extract_meta( + web_observations + ) + web_control_observations, _, _, _ = extract_meta(web_control_observations) + return templates.TemplateResponse( + request=request, + name="observations.html", + context=dict( + measurement_uid=measurement_uid, + web_observations=web_observations_list, + web_control_observations=web_control_observations, + probe_meta=probe_meta, + measurement_meta=measurement_meta, + processing_meta=processing_meta, + ), + ) diff --git a/oonipipeline/src/oonipipeline/dataviz/templates/observations.html b/oonipipeline/src/oonipipeline/dataviz/templates/observations.html new file mode 100644 index 00000000..dd66ecd0 --- /dev/null +++ b/oonipipeline/src/oonipipeline/dataviz/templates/observations.html @@ -0,0 +1,89 @@ + + + + + + + + + + +
    +
    +
    +
    +

    Observations viewer

    +
    +
    +
    + +
    + +

    Web Observations

    +
    + + + + {% for key in web_observations[0].keys() %} + + {% endfor %} + + + + {% for wo in web_observations %} + + {% for value in wo.values() %} + + {% endfor %} + + {% endfor %} + +
    {{ key }}
    {{value}}
    +
    + +

    Web Control Observations

    +
    + + + + {% for key in web_control_observations[0].keys() %} + + {% endfor %} + + + + {% for wo in web_control_observations %} + + {% for value in wo.values() %} + + {% endfor %} + + {% endfor %} + +
    {{ key }}
    {{value}}
    +
    + +

    Measurement Meta

    +
    + {% for key, value in measurement_meta.items() %} +
    +
    {{ key }}
    +
    {{ value }}
    +
    + {% endfor %} +
    + +

    Probe Meta

    +
    + {% for key, value in probe_meta.items() %} +
    +
    {{ key }}
    +
    {{ value }}
    +
    + {% endfor %} +
    + +
    + + + From a49787280bf7b5d844d406547ec21e56bbed8b85 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arturo=20Filast=C3=B2?= Date: Fri, 23 Aug 2024 14:53:24 +0200 Subject: [PATCH 3/8] Tidy up the layout of the analysis viewer --- oonipipeline/src/oonipipeline/dataviz/main.py | 41 ++++++----- .../dataviz/templates/analysis.html | 71 ++++++++----------- 2 files changed, 56 insertions(+), 56 deletions(-) diff --git a/oonipipeline/src/oonipipeline/dataviz/main.py b/oonipipeline/src/oonipipeline/dataviz/main.py index 483792c5..9657fd70 100644 --- a/oonipipeline/src/oonipipeline/dataviz/main.py +++ b/oonipipeline/src/oonipipeline/dataviz/main.py @@ -2,6 +2,7 @@ import json import os from pathlib import Path +from typing import Dict, List, Tuple from fastapi import Depends, FastAPI, Request from fastapi.templating import Jinja2Templates @@ -29,6 +30,21 @@ templates = Jinja2Templates(directory=f"{current_dir}/templates") +def extract_meta(orig_obs_list) -> Tuple[List, Dict, Dict, Dict]: + obs_list = [] + + measurement_meta = {} + probe_meta = {} + processing_meta = {} + for obs in orig_obs_list: + wo_dict = asdict(obs) + measurement_meta = wo_dict.pop("probe_meta", None) + probe_meta = wo_dict.pop("measurement_meta", None) + processing_meta = wo_dict.pop("processing_meta", None) + obs_list.append(wo_dict) + return obs_list, measurement_meta, probe_meta, processing_meta + + @app.get("/analysis/m/{measurement_uid}") def analysis_by_msmt( request: Request, @@ -80,6 +96,10 @@ def analysis_by_msmt( # pprint(loni.to_dict()) # print(analysis_transcript_list) + web_analysis_list, _, _, _ = extract_meta(web_analysis) + web_observations_list, measurement_meta, probe_meta, processing_meta = extract_meta( + web_observations + ) return templates.TemplateResponse( request=request, name="analysis.html", @@ -89,8 +109,11 @@ def analysis_by_msmt( loni_list=wer.loni_list, raw_msmt=raw_msmt, measurement_uid=measurement_uid, - web_analysis=list(map(lambda x: asdict(x), web_analysis)), - web_observations=list(map(lambda x: asdict(x), web_observations)), + web_analysis=web_analysis_list, + web_observations=web_observations_list, + measurement_meta=measurement_meta, + probe_meta=probe_meta, + processing_meta=processing_meta, loni_blocked_dict=dict(zip(wer.loni_blocked_keys, wer.loni_blocked_values)), loni_blocked_value=sum(wer.loni_blocked_values), loni_down_dict=dict(zip(wer.loni_down_keys, wer.loni_down_values)), @@ -115,20 +138,6 @@ def observations_by_msmt( msmt, netinfodb=netinfodb ) - def extract_meta(orig_obs_list): - obs_list = [] - - measurement_meta = {} - probe_meta = {} - processing_meta = {} - for obs in orig_obs_list: - wo_dict = asdict(obs) - measurement_meta = wo_dict.pop("probe_meta", None) - probe_meta = wo_dict.pop("measurement_meta", None) - processing_meta = wo_dict.pop("processing_meta", None) - obs_list.append(wo_dict) - return obs_list, measurement_meta, probe_meta, processing_meta - web_observations_list, probe_meta, measurement_meta, processing_meta = extract_meta( web_observations ) diff --git a/oonipipeline/src/oonipipeline/dataviz/templates/analysis.html b/oonipipeline/src/oonipipeline/dataviz/templates/analysis.html index 8b801e61..a3e84264 100644 --- a/oonipipeline/src/oonipipeline/dataviz/templates/analysis.html +++ b/oonipipeline/src/oonipipeline/dataviz/templates/analysis.html @@ -20,8 +20,7 @@
    -

    OONI Data Kraken Analysis

    -

    When data krakens and LoNIs join forces!

    +

    Analysis viewer

    @@ -126,8 +125,11 @@

    Experiment result

    Individual LoNIs

    + +
    {% for loni in loni_list %} -
    +
    +

    Loni #{{loop.index}}

    ok_final: {{loni["ok_final"]}}
    @@ -166,71 +168,60 @@

    Loni #{{loop.index}}

    Analysis transcript

    - 
    +            
      
             {% for analysis_line in analysis_transcript_list[loop.index0] %}
-{{ analysis_line }}
+              
    • {{ analysis_line }}
      • 
             {% endfor %}
-
    +
    +
    {% endfor %} - +

    Analysis output

    - -{% for wa in web_analysis %} -
    -
    -

    Analysis #{{loop.index}}

    -
    - +
    - - + {% for key in web_analysis[0].keys() %} + + {% endfor %} - - {% for key, value in wa.items() %} - - - + + {% for wa in web_analysis %} + + {% for value in wa.values() %} + + {% endfor %} {% endfor %}
    keyvalue{{ key }}
    {{key}}{{value}}
    {{value}}
    -
    -
    -{% endfor %}

    Web Observations

    -{% for wo in web_observations %} -
    -
    -

    Observation #{{loop.index}}

    - +
    - - + {% for key in web_observations[0].keys() %} + + {% endfor %} - - {% for key, value in wo.items() %} - - - + + {% for wo in web_observations %} + + {% for value in wo.values() %} + + {% endfor %} {% endfor %}
    keyvalue{{ key }}
    {{key}}{{value}}
    {{value}}
    -
    -
    -
    -{% endfor %} +

    Experiment results raw

    From 0d1c6550207a95c4199e820c7dc360ed25a880bb Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arturo=20Filast=C3=B2?= Date: Fri, 23 Aug 2024 15:10:58 +0200 Subject: [PATCH 4/8] Add simple redirector --- oonipipeline/src/oonipipeline/dataviz/main.py | 23 +++++++++- .../dataviz/templates/redirect.html | 43 +++++++++++++++++++ 2 files changed, 64 insertions(+), 2 deletions(-) create mode 100644 oonipipeline/src/oonipipeline/dataviz/templates/redirect.html diff --git a/oonipipeline/src/oonipipeline/dataviz/main.py b/oonipipeline/src/oonipipeline/dataviz/main.py index 9657fd70..6ed6309b 100644 --- a/oonipipeline/src/oonipipeline/dataviz/main.py +++ b/oonipipeline/src/oonipipeline/dataviz/main.py @@ -2,7 +2,7 @@ import json import os from pathlib import Path -from typing import Dict, List, Tuple +from typing import Dict, List, Optional, Tuple from fastapi import Depends, FastAPI, Request from fastapi.templating import Jinja2Templates @@ -45,12 +45,31 @@ def extract_meta(orig_obs_list) -> Tuple[List, Dict, Dict, Dict]: return obs_list, measurement_meta, probe_meta, processing_meta +@app.get("/analysis/") +def analysis_index( + request: Request, +): + return templates.TemplateResponse( + request=request, name="redirect.html", context={"scope": "analysis"} + ) + + +@app.get("/observations/") +def observations( + request: Request, +): + return templates.TemplateResponse( + request=request, name="redirect.html", context={"scope": "observations"} + ) + + @app.get("/analysis/m/{measurement_uid}") def analysis_by_msmt( request: Request, - measurement_uid: str, + measurement_uid: Optional[str], settings=Depends(get_settings), ): + data_dir = Path(settings.data_dir) fingerprintdb = FingerprintDB(datadir=data_dir, download=False) diff --git a/oonipipeline/src/oonipipeline/dataviz/templates/redirect.html b/oonipipeline/src/oonipipeline/dataviz/templates/redirect.html new file mode 100644 index 00000000..fdfc0a05 --- /dev/null +++ b/oonipipeline/src/oonipipeline/dataviz/templates/redirect.html @@ -0,0 +1,43 @@ + + + + + + + + + + +
    + +
    +
    +

    {{ scope }}: enter measurement UID

    +
    +

    You will be redirected to the relevant {{ scope }} page.

    +
    +
    +
    + + +
    + +
    +
    +
    +
    + + + \ No newline at end of file From 678d321a099d6ea336852bdf3f41a111ade1166c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arturo=20Filast=C3=B2?= Date: Sat, 24 Aug 2024 17:06:48 +0200 Subject: [PATCH 5/8] Start experimenting bayes network based approach --- notebooks/bn-notes.md | 7 + notebooks/msmt_feedback_clean.csv | 287 +++++++++ notebooks/pyproject.toml | 46 ++ notebooks/web-analysis-bn-simple.ipynb | 794 +++++++++++++++++++++++++ notebooks/web-analysis-bn.ipynb | 711 ++++++++++++++++++++++ notebooks/web-analysis.bif | 98 +++ notebooks/web_analysis.png | Bin 0 -> 160818 bytes notebooks/web_analysis_simple.png | Bin 0 -> 43022 bytes 8 files changed, 1943 insertions(+) create mode 100644 notebooks/bn-notes.md create mode 100644 notebooks/msmt_feedback_clean.csv create mode 100644 notebooks/pyproject.toml create mode 100644 notebooks/web-analysis-bn-simple.ipynb create mode 100644 notebooks/web-analysis-bn.ipynb create mode 100644 notebooks/web-analysis.bif create mode 100644 notebooks/web_analysis.png create mode 100644 notebooks/web_analysis_simple.png diff --git a/notebooks/bn-notes.md b/notebooks/bn-notes.md new file mode 100644 index 00000000..b3829e00 --- /dev/null +++ b/notebooks/bn-notes.md @@ -0,0 +1,7 @@ +Useful links: + +- https://maucher.pages.mi.hdm-stuttgart.de/artificial-intelligence/05aBayesNetGarage.html +- https://github.com/paulgovan/BayesianNetwork?tab=readme-ov-file +- https://www.cs.washington.edu/dm/vfml/appendixes/bif.htm +- https://pgmpy.org/models/bayesiannetwork.html +- https://erdogant.github.io/bnlearn/pages/html/index.html diff --git a/notebooks/msmt_feedback_clean.csv b/notebooks/msmt_feedback_clean.csv new file mode 100644 index 00000000..38de02bf --- /dev/null +++ b/notebooks/msmt_feedback_clean.csv @@ -0,0 +1,287 @@ +,measurement_uid,status,outcome +0,20240821111652.275207_RU_telegram_98b717d97593636f,blocked,blocked +1,0120191024c9bee71f54e22e25cdbb7007cb825c,down.unreachable,down 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+requires-python = ">=3.8" +license = "MIT" +keywords = [] +authors = [ + { name = "Arturo Filastò", email = "arturo@filasto.net" }, +] +classifiers = [ + "Development Status :: 4 - Beta", + "Programming Language :: Python", + "Programming Language :: Python :: 3.8", + "Programming Language :: Python :: 3.9", + "Programming Language :: Python :: 3.10", + "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", + "Programming Language :: Python :: Implementation :: CPython", + "Programming Language :: Python :: Implementation :: PyPy", +] +dependencies = [ + "jupyterlab", + "pandas", + "numpy", + "bnlearn", + "d3blocks", + "pygraphviz" +] + +[tool.hatch.envs.types] +extra-dependencies = [ + "mypy>=1.0.0", +] + +[tool.coverage.report] +exclude_lines = [ + "no cov", + "if __name__ == .__main__.:", + "if TYPE_CHECKING:", +] diff --git a/notebooks/web-analysis-bn-simple.ipynb b/notebooks/web-analysis-bn-simple.ipynb new file mode 100644 index 00000000..9f85e4df 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"cell_type": "code", + "execution_count": 93, + "id": "a6346742-dc39-40e3-8673-686b25fb7d87", + "metadata": {}, + "outputs": [], + "source": [ + "web_analysis_bn = BayesianNetwork([\n", + " ('DNS Ctrl Failure', 'DNS Outcome'),\n", + " ('DNS Ctrl Failure', 'DNS Answer Meta'),\n", + " #('Resolver config', 'DNS Outcome'),\n", + " ('DNS Consistency', 'DNS Outcome'),\n", + " ('DNS Answer Meta', 'DNS Consistency'),\n", + " ('DNS Answer Meta', 'DNS TLS Consistency'),\n", + " ('DNS TLS Consistency', 'DNS Consistency'),\n", + "])" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "id": "f78e3c55-3826-4622-b720-74452c7c13a2", + "metadata": {}, + "outputs": [], + "source": [ + "#web_analysis_bn.save('web_analysi.bif')" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "id": "3d63e9c3-0430-4bc1-a5e3-583ae71f3405", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "" + ] + }, + "execution_count": 95, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "viz = web_analysis_bn.to_graphviz()\n", + "viz.draw('web_analysis_simple.png', prog='dot')\n", + "Image('web_analysis_simple.png')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "832d93dd-4cfa-459a-8e1e-01a66cbee2d9", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "13312638-208f-4798-8eae-268fb29a817c", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "57082d9d-01d0-43ec-91af-2a54e85ae0a2", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fb31f020-28d9-4f3c-9d72-1ed687623fea", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 57, + "id": "b3cad79a-bce8-4efb-b811-80f6458fb16c", + "metadata": {}, + "outputs": [], + "source": [ + "def print_boilerplate():\n", + " cpd_list = []\n", + " for x in list(web_analysis_bn.nodes):\n", + " var_name = x.lower().replace(' ', '_')\n", + " var_name = f\"cpd_{var_name}\"\n", + " s = f\"{var_name} = TabularCPD('{x}', variable_card=2, values=[\\n\"\n", + " parents = web_analysis_bn.get_parents(x)\n", + " padding = \" \"*(int(len(s)/2))\n", + " for _ in range(2):\n", + " s += padding + \"[\"\n", + " s += \",\".join(\"0.\" for x in range(len(parents)))\n", + " s += \"],\\n\"\n", + " s += padding + f\"],\\n\" \n", + " s += padding + f\" # parents={parents}\\n\"\n", + " s += padding + f\"evidence={parents},\\n\"\n", + " s += padding + f\"evidence_card=[],\\n\"\n", + " s += padding + \"state_names = {\\n\"\n", + " for p in parents:\n", + " s += padding + f\"'{p}': [],\\n\"\n", + " s += \"}\\n\"\n", + " s += padding + \")\"\n", + " print(s)\n", + " cpd_list.append(var_name)" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "id": "509c45ee-b22d-461a-998b-a701c5090580", + "metadata": {}, + "outputs": [], + "source": [ + "cpd_resolver_config = TabularCPD(\n", + " \"Resolver config\",\n", + " variable_card=3,\n", + " values=[\n", + " # These values were estimated based on a query against the OONI dataset from 2024-01-01 to 2024-08-10\n", + " # with this query:\n", + " # -- ## quad_resolvers\n", + " # -- 15169, # Google LLC\n", + " # -- 13335, # Cloudflare Inc\n", + " # -- 42, # WoodyNet, Inc. | quad9\n", + " # -- 36692, # Cisco OpenDNS, LLC\t\n", + " # SELECT \n", + " # CountIf(resolver_asn IN (15169, 13335, 42, 36692)) as quad_external_count,\n", + " # CountIf( \n", + " # (resolver_asn = probe_asn OR resolver_as_cc = probe_cc) \n", + " # AND NOT (resolver_asn IN (15169, 13335, 42, 36692)) \n", + " # ) as provider_vp_consistent,\n", + " # CountIf( \n", + " # (resolver_asn != probe_asn AND resolver_as_cc != probe_cc) \n", + " # AND NOT (resolver_asn IN (15169, 13335, 42, 36692)) \n", + " # ) as provider_non_vp_consistent,\n", + " # COUNT() as total_count\n", + " # FROM obs_web\n", + " # WHERE \n", + " # measurement_start_time > '2024-01-01' \n", + " # AND measurement_start_time < '2024-08-10'\n", + " [0.56],\n", + " [0.08],\n", + " [0.36],\n", + " ],\n", + " state_names={\n", + " # provider_vp_consistent: means the resolver is consistent with the country and/or AS of the probe and is \n", + " # not a quad (eg. 8.8.8.8, 9.9.9.9, etc.) or third party resolver\n", + " # provider_non_vp_consistent: means the resolver is not a quad resolver, \n", + " # but is not consistent with the metadata of the probe\n", + " # quad_external: means the resolver is something like quad9, google, cloudflare, etc.\n", + " \"Resolver config\": [\"provider_vp_consistent\", \"provider_non_vp_consistent\", \"quad_external\"]\n", + " },\n", + ")\n", + "cpd_dns_ctrl_failure = TabularCPD(\n", + " \"DNS Ctrl Failure\",\n", + " variable_card=3,\n", + " values=[\n", + " [0.994],\n", + " [0.004],\n", + " [0.002],\n", + " ],\n", + " state_names={\n", + " \"DNS Ctrl Failure\": [\"none\", \"nxdomain\", \"server_failure\"]\n", + " },\n", + ")\n", + "cpd_dns_answer_meta = TabularCPD(\n", + " \"DNS Answer Meta\",\n", + " variable_card=7,\n", + " # These values were calculated using the following query.\n", + " # WITH\n", + " # (dns_answer IS NOT NULL \n", + " # AND ip_asn IN (13335, 209242, 20940, 9002, 16625, 63949, 16509, 14618, 15169, 396982, 54113, 8075, 8068)\n", + " # ) as is_cloud_provider\n", + " # SELECT \n", + " # CountIf(is_cloud_provider) as cloud_provider,\n", + " # CountIf(\n", + " # dns_answer IS NOT NULL AND ip_is_bogon AND NOT is_cloud_provider\n", + " # ) as answer_is_bogon,\n", + " # CountIf(\n", + " # dns_answer IS NOT NULL AND ip_asn = probe_asn AND NOT is_cloud_provider\n", + " # ) as answer_matches_probe_asn,\n", + " # CountIf(\n", + " # dns_answer IS NOT NULL AND (ip_cc = probe_cc AND NOT ip_asn = probe_asn AND NOT is_cloud_provider)\n", + " # ) as answer_matches_probe_cc,\n", + " # CountIf(\n", + " # dns_answer IS NOT NULL AND (ip_cc != probe_cc AND ip_asn != probe_asn AND NOT ip_is_bogon AND NOT is_cloud_provider)\n", + " # ) as answer_ok,\n", + " # COUNTIf(dns_failure IS NOT NULL) as dns_failure,\n", + " # COUNT() as total_count\n", + " # FROM obs_web\n", + " # WHERE \n", + " # test_name = 'web_connectivity'\n", + " # AND measurement_start_time > '2024-01-01' \n", + " # AND measurement_start_time < '2024-08-10'\n", + " ## The list of cloud providers was manually curated\n", + " # CLOUD_PROVIDERS_ASNS = [\n", + " # 13335, # Cloudflare: https://www.peeringdb.com/net/4224\n", + " # 209242, #\tCloudflare London, LLC\t\n", + " # 20940, # Akamai: https://www.peeringdb.com/net/2\n", + " # 9002, # Akamai RETN\n", + " # 16625, # Akamai Technologies, Inc.\t\n", + " # 63949, # Akamai Technologies, Inc.\t\n", + " # 16509, #\tAmazon.com, Inc.\n", + " # 14618, #\tAmazon.com, Inc.\t\n", + " # 15169, #\tGoogle LLC\n", + " # 396982, # Google Cloud: https://www.peeringdb.com/net/30878\n", + " # 54113, #\tFastly, Inc\n", + " # 8075, # Microsoft Corporation\n", + " # 8068, #\tMicrosoft Corporation\n", + " # ]\n", + " values=[\n", + " # \"none\", \"nxdomain\", \"server_failure\"\n", + " [0.0238, 0.9, 0.015],\n", + " [0.01, 0.03, 0.91],\n", + " [0.003745, 0.014, 0.015],\n", + " [0.004537, 0.014, 0.015],\n", + " [0.060217, 0.014, 0.015],\n", + " [0.19626, 0.014, 0.015],\n", + " [0.700935, 0.014, 0.015]\n", + " ],\n", + " # parents={parents}\n", + " evidence=[\"DNS Ctrl Failure\"],\n", + " evidence_card=[3],\n", + " state_names={\n", + " \"DNS Answer Meta\": [\n", + " \"answer_failure_nxdomain\",\n", + " \"answer_failure_other\",\n", + " \"answer_is_bogon\", \n", + " \"answer_matches_probe_asn\", \n", + " \"answer_matches_probe_cc\",\n", + " \"answer_is_cloud_provider\",\n", + " \"answer_ok\"\n", + " ],\n", + " \"DNS Ctrl Failure\": [\"none\", \"nxdomain\", \"server_failure\"]\n", + " },\n", + ")\n", + "cpd_dns_tls_consistency = TabularCPD(\n", + " \"DNS TLS Consistency\",\n", + " variable_card=3,\n", + " values=[\n", + " # answer_failure_nxdomain, answer_failure_other, answer_is_bogon, \n", + " # answer_matches_probe_asn, answer_matches_probe_cc, \n", + " # answer_is_cloud_provider, answer_ok,\n", + " [0.96, 0.96, 0.0, 0.05, 0.05, 0.9, 0.94], # tls_consistent\n", + " [0.02, 0.02, 0.02, 0.8, 0.8, 0.08, 0.04], # tls_inconsistent\n", + " [0.02, 0.02, 0.98, 0.15, 0.15, 0.02, 0.02], # tls_connection_failed\n", + " # [0.96],\n", + " # [0.02],\n", + " # [0.02]\n", + " ],\n", + " evidence=[\"DNS Answer Meta\"],\n", + " evidence_card=[7],\n", + " state_names={\n", + " \"DNS TLS Consistency\": [\"tls_consistent\", \"tls_inconsistent\", \"tls_connection_failed\"],\n", + " \"DNS Answer Meta\": [\n", + " \"answer_failure_nxdomain\",\n", + " \"answer_failure_other\",\n", + " \"answer_is_bogon\", \n", + " \"answer_matches_probe_asn\", \n", + " \"answer_matches_probe_cc\",\n", + " \"answer_is_cloud_provider\",\n", + " \"answer_ok\"\n", + " ],\n", + " },\n", + ")\n", + "cpd_dns_consistency = TabularCPD(\n", + " \"DNS Consistency\",\n", + " variable_card=2,\n", + " values=[\n", + " # answer_failure_nxdomain, answer_failure_other, answer_is_bogon, answer_matches_probe_asn, \n", + " # answer_matches_probe_cc, answer_is_cloud_provider, answer_ok\n", + " # tls_consistent, tls_inconsistent, tls_connection_failed\n", + " \n", + " # answer_failure_nxdomain, tls_consistent, tls_inconsistent, tls_connection_failed\n", + " [0.01, 0.001, 0.001,\n", + " # answer_failure_other, tls_consistent, tls_inconsistent, tls_connection_failed\n", + " 0.01, 0.001, 0.001,\n", + " # answer_is_bogon, , \n", + " 0.03, 0.01, 0.01,\n", + " # answer_matches_probe_asn\n", + " 0.999, 0.001, 0.3,\n", + " # answer_matches_probe_cc\n", + " 0.999, 0.001, 0.2,\n", + " # answer_is_cloud_provider\n", + " 0.98, 0.001, 0.1,\n", + " # answer_ok\n", + " 0.9999, 0.01, 0.2 \n", + " ],\n", + " [0.99, 0.999, 0.999,\n", + " # answer_failure_other, tls_consistent, tls_inconsistent, tls_connection_failed\n", + " 0.99, 0.999, 0.999,\n", + " # answer_is_bogon,\n", + " 0.97, 0.99, 0.99,\n", + " # answer_matches_probe_asn\n", + " 0.001, 0.999, 0.7,\n", + " # answer_matches_probe_cc\n", + " 0.001, 0.999, 0.8,\n", + " # answer_is_cloud_provider\n", + " 0.02, 0.999, 0.9,\n", + " # answer_ok\n", + " 0.0001, 0.99, 0.8\n", + " ],\n", + " ],\n", + " # parents={parents}\n", + " evidence=[\"DNS Answer Meta\", \"DNS TLS Consistency\"],\n", + " evidence_card=[7, 3],\n", + " state_names={\n", + " \"DNS Answer Meta\": [\n", + " \"answer_failure_nxdomain\",\n", + " \"answer_failure_other\",\n", + " \"answer_is_bogon\", \n", + " \"answer_matches_probe_asn\", \n", + " \"answer_matches_probe_cc\",\n", + " \"answer_is_cloud_provider\",\n", + " \"answer_ok\"\n", + " ],\n", + " \"DNS TLS Consistency\": [\"tls_consistent\", \"tls_inconsistent\", \"tls_connection_failed\"],\n", + " \"DNS Consistency\": [\n", + " \"consistent\",\n", + " \"inconsistent\"\n", + " # TODO(consistent UP and consistent DOWN)\n", + " ],\n", + " },\n", + ")\n", + "cpd_dns_outcome = TabularCPD(\n", + " \"DNS Outcome\",\n", + " variable_card=3,\n", + " values=[\n", + " # none, nxdomain, server_failure (ctrl failure)\n", + " # consistent, inconsistent (consistency)\n", + " # none, consistent, inconsistent\n", + " [0.1, 0.9, 0.2, 0.8, 0.1, 0.7],\n", + " [0.9, 0.1, 0.0, 0.0, 0.8, 0.1],\n", + " [0.0, 0.0, 0.8, 0.2, 0.1, 0.2],\n", + " ],\n", + " evidence=[\n", + " \"DNS Ctrl Failure\",\n", + " \"DNS Consistency\",\n", + " ],\n", + " evidence_card=[3, 2],\n", + " state_names={\n", + " \"DNS Outcome\": [\n", + " \"blocked\",\n", + " \"ok\",\n", + " \"down\"\n", + " ],\n", + " \"DNS Ctrl Failure\": [\"none\", \"nxdomain\", \"server_failure\"],\n", + " \"DNS Consistency\": [\n", + " \"consistent\",\n", + " \"inconsistent\"\n", + " ],\n", + " },\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "id": "85d58bf9-eb93-48fb-96ba-927657cfd1ef", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:pgmpy:Replacing existing CPD for DNS Ctrl Failure\n", + "WARNING:pgmpy:Replacing existing CPD for DNS Answer Meta\n", + "WARNING:pgmpy:Replacing existing CPD for DNS TLS Consistency\n", + "WARNING:pgmpy:Replacing existing CPD for DNS Consistency\n", + "WARNING:pgmpy:Replacing existing CPD for DNS Outcome\n" + ] + } + ], + "source": [ + "web_analysis_bn.add_cpds(cpd_dns_ctrl_failure, cpd_dns_answer_meta, cpd_dns_tls_consistency, cpd_dns_consistency, cpd_dns_outcome)" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "id": "6eebd10f-58da-41a8-b2ef-520a1733607c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 82, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "web_analysis_bn.check_model()" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "id": "21c4346f-4c39-47fc-9378-306b1bb05d58", + "metadata": {}, + "outputs": [], + "source": [ + "from pgmpy.inference import VariableElimination" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "id": "89546053-4dbb-47af-a81d-1ad5bf41f95c", + "metadata": {}, + "outputs": [], + "source": [ + "infer = VariableElimination(web_analysis_bn)" + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "id": "cb364bad-0321-4cba-9df6-c6a1cdb9ec05", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+----------------------+--------------------+\n", + "| DNS Outcome | phi(DNS Outcome) |\n", + "+======================+====================+\n", + "| DNS Outcome(blocked) | 0.2299 |\n", + "+----------------------+--------------------+\n", + "| DNS Outcome(ok) | 0.7688 |\n", + "+----------------------+--------------------+\n", + "| DNS Outcome(down) | 0.0013 |\n", + "+----------------------+--------------------+\n" + ] + } + ], + "source": [ + "print(infer.query(['DNS Outcome']))" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "id": "a5b30d21-a4c8-4170-ba42-c1727f5131cd", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+----------------------+--------------------+\n", + "| DNS Outcome | phi(DNS Outcome) |\n", + "+======================+====================+\n", + "| DNS Outcome(blocked) | 0.2176 |\n", + "+----------------------+--------------------+\n", + "| DNS Outcome(ok) | 0.7812 |\n", + "+----------------------+--------------------+\n", + "| DNS Outcome(down) | 0.0013 |\n", + "+----------------------+--------------------+\n" + ] + } + ], + "source": [ + "print(g_dist)" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "id": "870bd68f-7969-42c8-9c41-4f8710975497", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+----------------------+--------------------+\n", + "| DNS Outcome | phi(DNS Outcome) |\n", + "+======================+====================+\n", + "| DNS Outcome(blocked) | 0.8890 |\n", + "+----------------------+--------------------+\n", + "| DNS Outcome(ok) | 0.1064 |\n", + "+----------------------+--------------------+\n", + "| DNS Outcome(down) | 0.0046 |\n", + "+----------------------+--------------------+\n" + ] + } + ], + "source": [ + "print(infer.query(\n", + " ['DNS Outcome'], \n", + " evidence={\n", + " #'DNS TLS Consistency': 'tls_inconsistent',\n", + " \"DNS Answer Meta\": \"answer_is_bogon\", \n", + " }\n", + "))" + ] + }, + { + "cell_type": "code", + "execution_count": 90, + "id": "8bd01e2f-1baf-4f63-a851-e318f8cb687b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+----------------------+--------------------+\n", + "| DNS Outcome | phi(DNS Outcome) |\n", + "+======================+====================+\n", + "| DNS Outcome(blocked) | 0.8991 |\n", + "+----------------------+--------------------+\n", + "| DNS Outcome(ok) | 0.1008 |\n", + "+----------------------+--------------------+\n", + "| DNS Outcome(down) | 0.0001 |\n", + "+----------------------+--------------------+\n" + ] + } + ], + "source": [ + "print(infer.query(\n", + " ['DNS Outcome'], \n", + " evidence={\n", + " 'DNS TLS Consistency': 'tls_inconsistent',\n", + " \"DNS Answer Meta\": \"answer_is_cloud_provider\", \n", + " }\n", + "))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "02b703c0-429b-4a6f-ae21-2134bbb9a3e4", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.12.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/web-analysis-bn.ipynb b/notebooks/web-analysis-bn.ipynb new file mode 100644 index 00000000..383eb0c0 --- /dev/null +++ b/notebooks/web-analysis-bn.ipynb @@ -0,0 +1,711 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 7, + "id": "99aba231-cfe4-4ecb-8233-b34c90515fe9", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "from IPython.display import Image\n", + "from pgmpy.models import BayesianNetwork" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "c76afe2b-1a36-494f-aa99-c9ae037b39be", + "metadata": {}, + "outputs": [], + "source": [ + "msmt_feedback = pd.read_csv(\"msmt_feedback.csv\", delimiter='\\t', names=['measurement_uid', 'user_id', 'status', 'comment'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ce851a49-6dab-472d-a5a7-78c41395acca", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1b64f651-0707-4bb9-9205-2df6658ed0eb", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "23fff868-7e7f-4961-9fbb-f2857e4cb899", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['blocked', 'down.unreachable', 'ok', 'blocked.blockpage.dns',\n", + " 'blocked.dns.nxdomain', 'blocked.dns.inconsistent',\n", + " 'blocked.blockpage.server_side', 'blocked.tcp', 'blocked.tls',\n", + " 'blocked.blockpage.http', 'down.misconfigured',\n", + " 'blocked.blockpage', 'down', 'blocked.dns'], dtype=object)" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "msmt_feedback['status'].unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "8bd8a640-3e6d-4d54-b971-eb3332abcd89", + "metadata": {}, + "outputs": [], + "source": [ + "def map_outcome(status):\n", + " if status.startswith('ok'):\n", + " return 'ok'\n", + " elif status.startswith('blocked'):\n", + " return 'blocked'\n", + " elif status.startswith('down'):\n", + " return 'down'\n", + "msmt_feedback['outcome'] = msmt_feedback['status'].apply(map_outcome)" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "c736483d-b280-4972-aa38-70d272c077a8", + "metadata": {}, + "outputs": [], + "source": [ + "msmt_feedback[['measurement_uid', 'status', 'outcome']].to_csv('msmt_feedback_clean.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d625a231-d3f6-4f05-93be-5710392437fd", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "a6346742-dc39-40e3-8673-686b25fb7d87", + "metadata": {}, + "outputs": [], + "source": [ + "web_analysis_bn = BayesianNetwork([\n", + " ('DNS VP Failures', 'DNS Outcome'),\n", + " ('DNS VP Failures', 'VP State'),\n", + " ('DNS Ctrl Failures', 'DNS Outcome'),\n", + " ('DNS Ctrl Failures', 'DNS VP Failures'),\n", + " ('Resolver config', 'DNS Outcome'),\n", + " ('DNS Consistency', 'DNS Outcome'),\n", + " ('DNS Answer Meta', 'DNS Consistency'),\n", + " ('DNS TLS Consistency', 'DNS Consistency'),\n", + " ('DNS VP Got Answer', 'DNS Outcome'),\n", + " ('Resolver Config', 'DNS Consistency'),\n", + " ('Resolver Config', 'VP State'),\n", + " ('DNS Outcome', 'TCP VP Failures'),\n", + " ('TCP VP Failures', 'TCP Outcome'),\n", + " ('TCP Ctrl Failures', 'TCP Outcome'),\n", + " ('TCP Outcome', 'TLS VP Failures'),\n", + " ('TCP Outcome', 'HTTP Failure'),\n", + " ('TLS VP Failures', 'TLS Outcome'),\n", + " ('TLS VP Failures', 'VP State'),\n", + "\n", + " ('TLS Ctrl Failures', 'TLS Outcome'),\n", + " ('TLS Outcome', 'HTTP Failures'),\n", + " ('HTTP Failures', 'HTTP Outcome'),\n", + " ('HTTP Failures', 'VP State'),\n", + " ('HTTP Body Consistency', 'HTTP Response is plaintext'),\n", + " ('HTTP Response is plaintext', 'HTTP Outcome'),\n", + "])" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "f78e3c55-3826-4622-b720-74452c7c13a2", + "metadata": {}, + "outputs": [], + "source": [ + "#web_analysis_bn.save('web_analysi.bif')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "3d63e9c3-0430-4bc1-a5e3-583ae71f3405", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "viz = web_analysis_bn.to_graphviz()\n", + "viz.draw('web_analysis.png', prog='dot')\n", + "Image('web_analysis.png')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "832d93dd-4cfa-459a-8e1e-01a66cbee2d9", + "metadata": {}, + "outputs": [], + "source": [ + "cpd_dns_ctrl_failure = TabularCPD('A', 2, [[0.2], [0.8]])" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "id": "13312638-208f-4798-8eae-268fb29a817c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'DNS VP Failures'" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(web_analysis_bn.nodes)[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "id": "57082d9d-01d0-43ec-91af-2a54e85ae0a2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'DNS VP Failures'" + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "child = list(web_analysis_bn.nodes)[0]\n", + "child" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "id": "fb31f020-28d9-4f3c-9d72-1ed687623fea", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['DNS Ctrl Failures']" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "web_analysis_bn.get_parents(child)" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "id": "b3cad79a-bce8-4efb-b811-80f6458fb16c", + "metadata": {}, + "outputs": [], + "source": [ + "def print_boilerplate():\n", + " cpd_list = []\n", + " for x in list(web_analysis_bn.nodes):\n", + " var_name = x.lower().replace(' ', '_')\n", + " var_name = f\"cpd_{var_name}\"\n", + " s = f\"{var_name} = TabularCPD('{x}', variable_card=2, values=[\\n\"\n", + " parents = web_analysis_bn.get_parents(x)\n", + " padding = \" \"*(int(len(s)/2))\n", + " for _ in range(2):\n", + " s += padding + \"[\"\n", + " s += \",\".join(\"0.\" for x in range(len(parents)))\n", + " s += \"],\\n\"\n", + " s += padding + f\"],\\n\" \n", + " s += padding + f\" # parents={parents}\\n\"\n", + " s += padding + f\"evidence={parents},\\n\"\n", + " s += padding + f\"evidence_card=[],\\n\"\n", + " s += padding + \"state_names = {\\n\"\n", + " for p in parents:\n", + " s += padding + f\"'{p}': [],\\n\"\n", + " s += \"}\\n\"\n", + " s += padding + \")\"\n", + " print(s)\n", + " cpd_list.append(var_name)" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "id": "509c45ee-b22d-461a-998b-a701c5090580", + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'TabularCPD' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[68], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m cpd_dns_ctrl_failures \u001b[38;5;241m=\u001b[39m \u001b[43mTabularCPD\u001b[49m(\n\u001b[1;32m 2\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDNS Ctrl Failures\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 3\u001b[0m variable_card\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m3\u001b[39m,\n\u001b[1;32m 4\u001b[0m values\u001b[38;5;241m=\u001b[39m[\n\u001b[1;32m 5\u001b[0m [\u001b[38;5;241m0.8\u001b[39m],\n\u001b[1;32m 6\u001b[0m [\u001b[38;5;241m0.15\u001b[39m],\n\u001b[1;32m 7\u001b[0m [\u001b[38;5;241m0.05\u001b[39m],\n\u001b[1;32m 8\u001b[0m ],\n\u001b[1;32m 9\u001b[0m state_names\u001b[38;5;241m=\u001b[39m{\n\u001b[1;32m 10\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDNS Ctrl Failures\u001b[39m\u001b[38;5;124m\"\u001b[39m: [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnone\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnxdomain\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mserver_failure\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m 11\u001b[0m },\n\u001b[1;32m 12\u001b[0m )\n\u001b[1;32m 13\u001b[0m cpd_dns_vp_failures \u001b[38;5;241m=\u001b[39m TabularCPD(\n\u001b[1;32m 14\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDNS VP Failures\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 15\u001b[0m variable_card\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m3\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 26\u001b[0m },\n\u001b[1;32m 27\u001b[0m )\n\u001b[1;32m 28\u001b[0m cpd_resolver_config \u001b[38;5;241m=\u001b[39m TabularCPD(\n\u001b[1;32m 29\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mResolver config\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 30\u001b[0m variable_card\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 37\u001b[0m },\n\u001b[1;32m 38\u001b[0m )\n", + "\u001b[0;31mNameError\u001b[0m: name 'TabularCPD' is not defined" + ] + } + ], + "source": [ + "cpd_dns_ctrl_failures = TabularCPD(\n", + " \"DNS Ctrl Failures\",\n", + " variable_card=3,\n", + " values=[\n", + " [0.8],\n", + " [0.15],\n", + " [0.05],\n", + " ],\n", + " state_names={\n", + " \"DNS Ctrl Failures\": [\"none\", \"nxdomain\", \"server_failure\"]\n", + " },\n", + ")\n", + "cpd_dns_vp_failures = TabularCPD(\n", + " \"DNS VP Failures\",\n", + " variable_card=3,\n", + " values=[\n", + " [0.8],\n", + " [0.15],\n", + " [0.05],\n", + " ],\n", + " evidence=[\"DNS Ctrl Failures\"],\n", + " evidence_card=[3],\n", + " state_names={\n", + " \"DNS VP Failures\": [\"none\", \"nxdomain\", \"server_failure\"],\n", + " \"DNS Ctrl Failures\": [\"none\", \"nxdomain\", \"server_failure\"],\n", + " },\n", + ")\n", + "cpd_resolver_config = TabularCPD(\n", + " \"Resolver config\",\n", + " variable_card=3,\n", + " values=[\n", + " # These values were estimated based on a query against the OONI dataset from 2024-01-01 to 2024-08-10\n", + " # with this query:\n", + " # -- ## quad_resolvers\n", + " # -- 15169, # Google LLC\n", + " # -- 13335, # Cloudflare Inc\n", + " # -- 42, # WoodyNet, Inc. | quad9\n", + " # -- 36692, # Cisco OpenDNS, LLC\t\n", + " # SELECT \n", + " # CountIf(resolver_asn IN (15169, 13335, 42, 36692)) as quad_external_count,\n", + " # CountIf( \n", + " # (resolver_asn = probe_asn OR resolver_as_cc = probe_cc) \n", + " # AND NOT (resolver_asn IN (15169, 13335, 42, 36692)) \n", + " # ) as provider_vp_consistent,\n", + " # CountIf( \n", + " # (resolver_asn != probe_asn AND resolver_as_cc != probe_cc) \n", + " # AND NOT (resolver_asn IN (15169, 13335, 42, 36692)) \n", + " # ) as provider_non_vp_consistent,\n", + " # COUNT() as total_count\n", + " # FROM obs_web\n", + " # WHERE \n", + " # measurement_start_time > '2024-01-01' \n", + " # AND measurement_start_time < '2024-08-10'\n", + " [0.56],\n", + " [0.08],\n", + " [0.36],\n", + " ],\n", + " state_names={\n", + " # provider_vp_consistent: means the resolver is consistent with the country and/or AS of the probe and is \n", + " # not a quad (eg. 8.8.8.8, 9.9.9.9, etc.) or third party resolver\n", + " # provider_non_vp_consistent: means the resolver is not a quad resolver, \n", + " # but is not consistent with the metadata of the probe\n", + " # quad_external: means the resolver is something like quad9, google, cloudflare, etc.\n", + " \"Resolver config\": [\"provider_vp_consistent\", \"provider_non_vp_consistent\", \"quad_external\"]\n", + " },\n", + ")\n", + "cpd_dns_answer_meta = TabularCPD(\n", + " \"DNS Answer Meta\",\n", + " variable_card=6,\n", + " # These values were calculated using the following query.\n", + " # WITH\n", + " # (dns_answer IS NOT NULL \n", + " # AND ip_asn IN (13335, 209242, 20940, 9002, 16625, 63949, 16509, 14618, 15169, 396982, 54113, 8075, 8068)\n", + " # ) as is_cloud_provider\n", + " # SELECT \n", + " # CountIf(is_cloud_provider) as cloud_provider,\n", + " # CountIf(\n", + " # dns_answer IS NOT NULL AND ip_is_bogon AND NOT is_cloud_provider\n", + " # ) as answer_is_bogon,\n", + " # CountIf(\n", + " # dns_answer IS NOT NULL AND ip_asn = probe_asn AND NOT is_cloud_provider\n", + " # ) as answer_matches_probe_asn,\n", + " # CountIf(\n", + " # dns_answer IS NOT NULL AND (ip_cc = probe_cc AND NOT ip_asn = probe_asn AND NOT is_cloud_provider)\n", + " # ) as answer_matches_probe_cc,\n", + " # CountIf(\n", + " # dns_answer IS NOT NULL AND (ip_cc != probe_cc AND ip_asn != probe_asn AND NOT ip_is_bogon AND NOT is_cloud_provider)\n", + " # ) as answer_ok,\n", + " # COUNTIf(dns_failure IS NOT NULL) as dns_failure,\n", + " # COUNT() as total_count\n", + " # FROM obs_web\n", + " # WHERE \n", + " # test_name = 'web_connectivity'\n", + " # AND measurement_start_time > '2024-01-01' \n", + " # AND measurement_start_time < '2024-08-10'\n", + " ## The list of cloud providers was manually curated\n", + " # CLOUD_PROVIDERS_ASNS = [\n", + " # 13335, # Cloudflare: https://www.peeringdb.com/net/4224\n", + " # 209242, #\tCloudflare London, LLC\t\n", + " # 20940, # Akamai: https://www.peeringdb.com/net/2\n", + " # 9002, # Akamai RETN\n", + " # 16625, # Akamai Technologies, Inc.\t\n", + " # 63949, # Akamai Technologies, Inc.\t\n", + " # 16509, #\tAmazon.com, Inc.\n", + " # 14618, #\tAmazon.com, Inc.\t\n", + " # 15169, #\tGoogle LLC\n", + " # 396982, # Google Cloud: https://www.peeringdb.com/net/30878\n", + " # 54113, #\tFastly, Inc\n", + " # 8075, # Microsoft Corporation\n", + " # 8068, #\tMicrosoft Corporation\n", + " # ]\n", + " values=[\n", + " [0.034306],\n", + " [0.003745],\n", + " [0.004537],\n", + " [0.060217],\n", + " [0.19626],\n", + " [0.700935]\n", + " ],\n", + " # parents={parents}\n", + " evidence=[],\n", + " evidence_card=[],\n", + " state_names={\n", + " \"DNS Answer Meta\": [\n", + " \"answer_failure\", \n", + " \"answer_is_bogon\", \n", + " \"answer_matches_probe_asn\", \n", + " \"answer_matches_probe_cc\",\n", + " \"answer_is_cloud_provider\",\n", + " \"answer_ok\"\n", + " ],\n", + " },\n", + ")\n", + "cpd_dns_tls_consistency = TabularCPD(\n", + " \"DNS TLS Consistency\",\n", + " variable_card=2,\n", + " values=[\n", + " [],\n", + " [],\n", + " ],\n", + " # parents={parents}\n", + " evidence=[],\n", + " evidence_card=[],\n", + " state_names={\n", + " \"DNS TLS Consistency\": [\"\"]\n", + " },\n", + ")\n", + "cpd_dns_consistency = TabularCPD(\n", + " \"DNS Consistency\",\n", + " variable_card=2,\n", + " values=[\n", + " [0.0, 0.0, 0.0],\n", + " [0.0, 0.0, 0.0],\n", + " ],\n", + " # parents={parents}\n", + " evidence=[\"DNS Answer Meta\", \"DNS TLS Consistency\", \"Resolver Config\"],\n", + " evidence_card=[],\n", + " state_names={\n", + " \"DNS Consistency\": [],\n", + " \"DNS Answer Meta\": [\n", + " \"answer_failure\", \n", + " \"answer_is_bogon\", \n", + " \"answer_matches_probe_asn\", \n", + " \"answer_matches_probe_cc\",\n", + " \"answer_is_cloud_provider\",\n", + " \"answer_ok\"\n", + " ],\n", + " \"DNS TLS Consistency\": [],\n", + " \"Resolver config\": [\"provider_vp_consistent\", \"provider_non_vp_consistent\", \"quad_external\"]\n", + " },\n", + ")\n", + "cpd_dns_outcome = TabularCPD(\n", + " \"DNS Outcome\",\n", + " variable_card=2,\n", + " values=[\n", + " [0.0, 0.0, 0.0, 0.0, 0.0],\n", + " [0.0, 0.0, 0.0, 0.0, 0.0],\n", + " ],\n", + " # parents={parents}\n", + " evidence=[\n", + " \"DNS VP Failures\",\n", + " \"DNS Ctrl Failures\",\n", + " \"Resolver config\",\n", + " \"DNS Consistency\",\n", + " \"DNS VP Got Answer\",\n", + " ],\n", + " evidence_card=[],\n", + " state_names={\n", + " \"DNS VP Failures\": [\"none\", \"nxdomain\", \"server_failure\"],\n", + " \"DNS Ctrl Failures\": [\"none\", \"nxdomain\", \"server_failure\"],\n", + " \"Resolver config\": [\"provider_vp_consistent\", \"provider_non_vp_consistent\", \"quad_external\"]\n", + " \"DNS Consistency\": [],\n", + " \"DNS VP Got Answer\": [],\n", + " },\n", + ")\n", + "cpd_vp_state = TabularCPD(\n", + " \"VP State\",\n", + " variable_card=2,\n", + " values=[\n", + " [0.0, 0.0, 0.0, 0.0],\n", + " [0.0, 0.0, 0.0, 0.0],\n", + " ],\n", + " # parents={parents}\n", + " evidence=[\"DNS VP Failures\", \"Resolver Config\", \"TLS VP Failures\", \"HTTP Failures\"],\n", + " evidence_card=[],\n", + " state_names={\n", + " \"DNS VP Failures\": [],\n", + " \"Resolver Config\": [],\n", + " \"TLS VP Failures\": [],\n", + " \"HTTP Failures\": [],\n", + " },\n", + ")\n", + "cpd_dns_vp_got_answer = TabularCPD(\n", + " \"DNS VP Got Answer\",\n", + " variable_card=2,\n", + " values=[\n", + " [],\n", + " [],\n", + " ],\n", + " # parents={parents}\n", + " evidence=[],\n", + " evidence_card=[],\n", + " state_names={},\n", + ")\n", + "cpd_tcp_vp_failures = TabularCPD(\n", + " \"TCP VP Failures\",\n", + " variable_card=2,\n", + " values=[\n", + " [0.0],\n", + " [0.0],\n", + " ],\n", + " # parents={parents}\n", + " evidence=[\"DNS Outcome\"],\n", + " evidence_card=[],\n", + " state_names={\n", + " \"DNS Outcome\": [],\n", + " },\n", + ")\n", + "cpd_tcp_outcome = TabularCPD(\n", + " \"TCP Outcome\",\n", + " variable_card=2,\n", + " values=[\n", + " [0.0, 0.0],\n", + " [0.0, 0.0],\n", + " ],\n", + " # parents={parents}\n", + " evidence=[\"TCP VP Failures\", \"TCP Ctrl Failures\"],\n", + " evidence_card=[],\n", + " state_names={\n", + " \"TCP VP Failures\": [],\n", + " \"TCP Ctrl Failures\": [],\n", + " },\n", + ")\n", + "cpd_tcp_ctrl_failures = TabularCPD(\n", + " \"TCP Ctrl Failures\",\n", + " variable_card=2,\n", + " values=[\n", + " [],\n", + " [],\n", + " ],\n", + " # parents={parents}\n", + " evidence=[],\n", + " evidence_card=[],\n", + " state_names={},\n", + ")\n", + "cpd_tls_vp_failures = TabularCPD(\n", + " \"TLS VP Failures\",\n", + " variable_card=2,\n", + " values=[\n", + " [0.0],\n", + " [0.0],\n", + " ],\n", + " # parents={parents}\n", + " evidence=[\"TCP Outcome\"],\n", + " evidence_card=[],\n", + " state_names={\n", + " \"TCP Outcome\": [],\n", + " },\n", + ")\n", + "cpd_http_failure = TabularCPD(\n", + " \"HTTP Failure\",\n", + " variable_card=2,\n", + " values=[\n", + " [0.0],\n", + " [0.0],\n", + " ],\n", + " # parents={parents}\n", + " evidence=[\"TCP Outcome\"],\n", + " evidence_card=[],\n", + " state_names={\n", + " \"TCP Outcome\": [],\n", + " },\n", + ")\n", + "cpd_tls_outcome = TabularCPD(\n", + " \"TLS Outcome\",\n", + " variable_card=2,\n", + " values=[\n", + " [0.0, 0.0],\n", + " [0.0, 0.0],\n", + " ],\n", + " # parents={parents}\n", + " evidence=[\"TLS VP Failures\", \"TLS Ctrl Failures\"],\n", + " evidence_card=[],\n", + " state_names={\n", + " \"TLS VP Failures\": [],\n", + " \"TLS Ctrl Failures\": [],\n", + " },\n", + ")\n", + "cpd_tls_ctrl_failures = TabularCPD(\n", + " \"TLS Ctrl Failures\",\n", + " variable_card=2,\n", + " values=[\n", + " [],\n", + " [],\n", + " ],\n", + " # parents={parents}\n", + " evidence=[],\n", + " evidence_card=[],\n", + " state_names={},\n", + ")\n", + "cpd_http_failures = TabularCPD(\n", + " \"HTTP Failures\",\n", + " variable_card=2,\n", + " values=[\n", + " [0.0],\n", + " [0.0],\n", + " ],\n", + " # parents={parents}\n", + " evidence=[\"TLS Outcome\"],\n", + " evidence_card=[],\n", + " state_names={\n", + " \"TLS Outcome\": [],\n", + " },\n", + ")\n", + "cpd_http_outcome = TabularCPD(\n", + " \"HTTP Outcome\",\n", + " variable_card=2,\n", + " values=[\n", + " [0.0, 0.0],\n", + " [0.0, 0.0],\n", + " ],\n", + " # parents={parents}\n", + " evidence=[\"HTTP Failures\", \"HTTP Response is plaintext\"],\n", + " evidence_card=[],\n", + " state_names={\n", + " \"HTTP Failures\": [],\n", + " \"HTTP Response is plaintext\": [],\n", + " },\n", + ")\n", + "cpd_http_body_consistency = TabularCPD(\n", + " \"HTTP Body Consistency\",\n", + " variable_card=2,\n", + " values=[\n", + " [],\n", + " [],\n", + " ],\n", + " # parents={parents}\n", + " evidence=[],\n", + " evidence_card=[],\n", + " state_names={},\n", + ")\n", + "cpd_http_response_is_plaintext = TabularCPD(\n", + " \"HTTP Response is plaintext\",\n", + " variable_card=2,\n", + " values=[\n", + " [0.0],\n", + " [0.0],\n", + " ],\n", + " # parents={parents}\n", + " evidence=[\"HTTP Body Consistency\"],\n", + " evidence_card=[],\n", + " state_names={\n", + " \"HTTP Body Consistency\": [],\n", + " },\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "85d58bf9-eb93-48fb-96ba-927657cfd1ef", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6eebd10f-58da-41a8-b2ef-520a1733607c", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.12.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/web-analysis.bif b/notebooks/web-analysis.bif new file mode 100644 index 00000000..cccf8eb2 --- /dev/null +++ b/notebooks/web-analysis.bif @@ -0,0 +1,98 @@ +dns_ground_truth_nxdomain_count +dns_ground_truth_failure_count +dns_ground_truth_ok_count +dns_ground_truth_ok_cc_asn_count +dns_ground_truth_failure_cc_asn_count +dns_ground_truth_nxdomain_cc_asn_count + +dns_consistency_system_answers +dns_consistency_system_success +dns_consistency_system_failure +dns_consistency_system_answer_count +dns_consistency_system_is_answer_tls_consistent +dns_consistency_system_is_answer_tls_inconsistent +dns_consistency_system_is_answer_ip_in_trusted_answers +dns_consistency_system_is_answer_asn_in_trusted_answers +dns_consistency_system_is_answer_asorg_in_trusted_answers +dns_consistency_system_is_answer_cloud_provider +dns_consistency_system_is_answer_probe_asn_match +dns_consistency_system_is_answer_probe_cc_match +dns_consistency_system_is_answer_bogon +dns_consistency_system_answer_fp_name +dns_consistency_system_answer_fp_scope +dns_consistency_system_is_answer_fp_match +dns_consistency_system_is_answer_fp_country_consistent +dns_consistency_system_is_answer_fp_false_positive +dns_consistency_system_is_resolver_probe_asn_match +dns_consistency_system_is_resolver_probe_cc_match +dns_consistency_system_answer_ip_ground_truth_asn_count +dns_consistency_system_answer_asn_ground_truth_asn_count +dns_consistency_other_answers +dns_consistency_other_success +dns_consistency_other_failure +dns_consistency_other_answer_count +dns_consistency_other_is_answer_tls_consistent +dns_consistency_other_is_answer_tls_inconsistent +dns_consistency_other_is_answer_ip_in_trusted_answers +dns_consistency_other_is_answer_asn_in_trusted_answers +dns_consistency_other_is_answer_asorg_in_trusted_answers +dns_consistency_other_is_answer_cloud_provider +dns_consistency_other_is_answer_probe_asn_match +dns_consistency_other_is_answer_probe_cc_match +dns_consistency_other_is_answer_bogon +dns_consistency_other_answer_fp_name +dns_consistency_other_answer_fp_scope +dns_consistency_other_is_answer_fp_match +dns_consistency_other_is_answer_fp_country_consistent +dns_consistency_other_is_answer_fp_false_positive +dns_consistency_other_is_resolver_probe_asn_match +dns_consistency_other_is_resolver_probe_cc_match +dns_consistency_other_answer_ip_ground_truth_asn_count +dns_consistency_other_answer_asn_ground_truth_asn_count + +tls_success +tls_failure +tls_is_tls_certificate_valid +tls_is_tls_certificate_invalid +tls_handshake_read_count +tls_handshake_write_count +tls_handshake_read_bytes +tls_handshake_write_bytes +tls_handshake_time +tls_ground_truth_failure_count +tls_ground_truth_failure_asn_cc_count +tls_ground_truth_ok_count +tls_ground_truth_ok_asn_cc_count +tls_ground_truth_trusted_failure_count +tls_ground_truth_trusted_ok_count + +tcp_address +tcp_success tcp_failure +tcp_ground_truth_failure_count +tcp_ground_truth_failure_asn_cc_count +tcp_ground_truth_ok_count +tcp_ground_truth_ok_asn_cc_count +tcp_ground_truth_trusted_failure_count +tcp_ground_truth_trusted_ok_count + +http_success +http_failure +http_is_http_request_encrypted + +http_response_body_proportion +http_response_body_length +http_response_status_code + +http_ground_truth_failure_count +http_ground_truth_failure_asn_cc_count +http_ground_truth_ok_count +http_ground_truth_ok_asn_cc_count +http_ground_truth_trusted_ok_count +http_ground_truth_trusted_failure_count +http_ground_truth_body_length + +http_fp_name +http_fp_scope +http_is_http_fp_match +http_is_http_fp_country_consistent +http_is_http_fp_false_positive \ No newline at end of file diff --git a/notebooks/web_analysis.png b/notebooks/web_analysis.png new file mode 100644 index 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zVgPs4{yiAt!OZp4-`LaElgx9!nbO&iEgJ8Q<1!X_!7e^NKc)TN-9IzlwfUoF&RIW5 zs)>^(EzIYY6funO*Cdnhxo_gDKhH7D1r=R`2N$>10s(R5d2tMR<;y;|;bcYF8~}WHqn@G(AV&m1 zl+Hq?1ptUL#gE$U(nn(;#Jg?3-DH(i`}_DL=Z>pp9Ax=q1A1jgeN85#K1f68C;w=B z5SX@d?Tfca>*eyvoB{THBiS%s$9%lK=WI5!w24Ys;MFC4%B_GWb(!5ncL4;-m<|g5 zs};V~Q6iTzir(C)b*?CGi$1wbo7ODUdVksx!=f0Ye*GR#_M(@Q2^BaGPoMK_8?$TI z;nbR#VF+l=J~tb#s^hRGJ5 Date: Sun, 25 Aug 2024 14:06:47 +0200 Subject: [PATCH 6/8] Implement full web analysis bayes net --- notebooks/bayes-net-editor.ipynb | 158 ++++++ notebooks/pyproject.toml | 4 +- notebooks/web-analysis-bn-simple.ipynb | 651 ++++++++++++++++--------- notebooks/web-analysis-full.bif | 151 ++++++ 4 files changed, 726 insertions(+), 238 deletions(-) create mode 100644 notebooks/bayes-net-editor.ipynb create mode 100644 notebooks/web-analysis-full.bif diff --git a/notebooks/bayes-net-editor.ipynb b/notebooks/bayes-net-editor.ipynb new file mode 100644 index 00000000..206df489 --- /dev/null +++ b/notebooks/bayes-net-editor.ipynb @@ -0,0 +1,158 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "bc83eb2c-32c1-4d5a-9e4f-9e0e0378c8a6", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "7f87d42c453a4d27aaa170c18f9036f2", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Box(children=(FloatSlider(value=0.2, continuous_update=False, description='answer_is_bogon', max=1.0, step=0.0…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import ipywidgets as widgets\n", + "from ipywidgets import VBox, Box, Layout\n", + "from IPython.display import display\n", + "\n", + "slider_map = {}\n", + "\n", + "values = [\n", + "\"answer_is_bogon\", \n", + "\"answer_matches_probe_asn\", \n", + "\"answer_matches_probe_cc\",\n", + "\"answer_is_cloud_provider\",\n", + "\"answer_other\"\n", + "]\n", + "\n", + "class Changer:\n", + " change_in_progress = False\n", + " \n", + " def callback(self, value):\n", + " if self.change_in_progress:\n", + " return\n", + " self.change_in_progress = True\n", + " changed_slider = value['owner'].description\n", + " other_slider_sum = 0\n", + " for k, s in slider_map.items():\n", + " if k == changed_slider:\n", + " continue\n", + " other_slider_sum += s.value\n", + " new_other_slider_sum = 1 - value['new']\n", + " mult_factor = new_other_slider_sum/other_slider_sum\n", + " for k, s in slider_map.items():\n", + " if k == changed_slider:\n", + " continue\n", + " s.value = mult_factor * s.value\n", + " self.change_in_progress = False\n", + " \n", + "changer = Changer()\n", + "slider_values = {v: 1.0/len(values) for v in values}\n", + "\n", + "for v in values:\n", + " slider = widgets.FloatSlider(\n", + " value=1/len(values), \n", + " min=0.0,\n", + " max=1.0,\n", + " description=v,\n", + " step=0.001,\n", + " continuous_update=False\n", + " )\n", + " slider.observe(changer.callback, names='value')\n", + " slider_map[v] = slider\n", + "\n", + "display(\n", + " Box(children=list(slider_map.values()), layout=Layout(display='flex', flex_flow='column', align_items='stretch'))\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "97cc09d2-c71b-49a5-9a1c-3f6ace5e6b1f", + "metadata": {}, + "outputs": [], + "source": [ + "def validate_matrix(matrix):\n", + " cols = len(matrix[0])\n", + " rows = len(matrix)\n", + " valid = True\n", + " for col_idx in range(cols):\n", + " col_data = []\n", + " for row_idx in range(rows):\n", + " col_data.append(matrix[row_idx][col_idx])\n", + " if sum(col_data) != 1:\n", + " print(f\"col #{col_idx} INVALID ({sum(col_data)}!=1)\")\n", + " print(col_data)\n", + " valid = False\n", + " if valid:\n", + " print(\"ALL OK\")" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "fee25b03-eec8-4db4-9021-ce92eee94dbf", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ALL OK\n" + ] + } + ], + "source": [ + "validate_matrix([\n", + " # consistent inconsistent\n", + " # \"none\", \"connection_reset\", \"timeout\", \"other\", \"down\"\n", + " [0.02, 0.95, 0.90, 0.85, 0.01, 0.07, 0.07, 0.07, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02], # blocked\n", + " [0.95, 0.01, 0.01, 0.01, 0.08, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01], # ok\n", + " [0.02, 0.03, 0.07, 0.09, 0.01, 0.07, 0.07, 0.07, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05], # down\n", + " [0.01, 0.01, 0.02, 0.05, 0.90, 0.85, 0.85, 0.85, 0.92, 0.92, 0.92, 0.92, 0.92, 0.92, 0.92, 0.92], # unknown\n", + " ])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1f8a25ac-80fe-4124-af4e-d5455faf71d2", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.12.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/pyproject.toml b/notebooks/pyproject.toml index f49a1fae..94cdc333 100644 --- a/notebooks/pyproject.toml +++ b/notebooks/pyproject.toml @@ -30,7 +30,9 @@ dependencies = [ "numpy", "bnlearn", "d3blocks", - "pygraphviz" + "pygraphviz", + "bokeh", + "ipywidgets" ] [tool.hatch.envs.types] diff --git a/notebooks/web-analysis-bn-simple.ipynb b/notebooks/web-analysis-bn-simple.ipynb index 9f85e4df..dd9a2eb0 100644 --- a/notebooks/web-analysis-bn-simple.ipynb +++ b/notebooks/web-analysis-bn-simple.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 11, + "execution_count": 1, "id": "99aba231-cfe4-4ecb-8233-b34c90515fe9", "metadata": {}, "outputs": [], @@ -15,7 +15,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 174, "id": "c76afe2b-1a36-494f-aa99-c9ae037b39be", "metadata": {}, "outputs": [], @@ -25,7 +25,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 175, "id": "ce851a49-6dab-472d-a5a7-78c41395acca", "metadata": {}, "outputs": [ @@ -169,7 +169,7 @@ "[286 rows x 4 columns]" ] }, - "execution_count": 5, + "execution_count": 175, "metadata": {}, "output_type": "execute_result" } @@ -194,6 +194,14 @@ "outputs": [], "source": [] }, + { + "cell_type": "code", + "execution_count": null, + "id": "dfc9bfb1-8a39-4278-a072-1fb96ed1d2bf", + "metadata": {}, + "outputs": [], + "source": [] + }, { "cell_type": "code", "execution_count": null, @@ -212,15 +220,61 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "id": "d625a231-d3f6-4f05-93be-5710392437fd", "metadata": {}, "outputs": [], - "source": [] + "source": [ + "web_analysis_bn_full = BayesianNetwork([\n", + " ('DNS Ctrl Failure', 'DNS VP Failure'),\n", + " ('DNS Ctrl Failure', 'DNS Failure Consistency'),\n", + " #('Resolver config', 'DNS Outcome'),\n", + " ('DNS Answer', 'DNS Answer Consistency'),\n", + " ('DNS Answer', 'DNS Answer TLS Consistency'),\n", + " ('DNS Answer TLS Consistency', 'DNS Answer Consistency'),\n", + " ('DNS Answer Consistency', 'DNS Outcome'),\n", + "\n", + " ('DNS VP Failure', 'DNS Failure Consistency'),\n", + " ('DNS Failure Consistency', 'DNS Outcome'),\n", + "\n", + " ('TCP Ctrl Failure', 'TCP VP Result'),\n", + "\n", + " ('DNS Answer Consistency', 'TCP Outcome'),\n", + " ('TCP VP Result', 'TCP Outcome'),\n", + "\n", + " ('TLS Ctrl Failure', 'TLS VP Result'),\n", + " ('TLS VP Result', 'TLS Outcome'),\n", + " ('DNS Answer Consistency', 'TLS Outcome'),\n", + "])" + ] }, { "cell_type": "code", - "execution_count": 93, + "execution_count": 20, + "id": "94f26d5a-7d07-406f-ab76-a44706e5fee7", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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GNDU1MXLkSJSUlHAdqcHMnj0bmpqaOHHiRKMXT4DmtX+XlJTgu+++w/nz5+v999AaKCgo4PDhwzA2Nsa0adO4jkMIIYQQQkjdMNV49uwZw+PxmL/++qu6b3NKV1eXadeuXZXl/v7+jLGxMaOiosIEBgbKfK9du3YMAGbq1KnVvuaxY8eY1atXs48XLlzIdOjQgamoqJBZb968ecx33333zox//vkno6ioyNy7d6/K90pKShgXFxfm4MGD7LIlS5YwEonkna+bk5PDAGC2bNnyznVVVVUZZ2fnKsvT0tKY77///p3Pr48MLUl8fDyjo6PDLFmyhOsoDcLPz48BwAQEBHCaozns3wzDMPv372cAMP3796/T+qR6gYGBjLy8POPr68t1FEIIIYQQQt7Fq9oWKD/++CO6dOmChQsXNl4lp46UlJSqXT5gwAAcOHAApaWlGDt2rMzVaHV1dbi5ueHQoUP466+/qn1NaSsLAHj8+DGUlZUhJycns96KFSuqLHubl5cXvv/+e2zYsKHa8WJUVFSwbds2vH79GgAQFhaG3bt31/qaUu/TVUBFRaXa5SYmJpg/f36dX+djMrQkbdq0wYYNG7Bjxw6kpaVxHafebd++Hf369UPfvn05zdHU92+pvXv3ok+fPrh58yZevHhRp+eQqlxcXDBs2DBs27aN6yiEEEIIIYS8U5UCyuvXr3HlyhUsXry4zicTTcXw4cMxYMAAduyRynx8fGBubo6lS5fC39+/1tfp0KEDnj9/jgULFqC8vJxdbmlpiaFDh9b63I0bN7JZatK9e3f07t0b9+/fx8iRI1FUVISTJ0+ymV++fIk1a9ZAIpHg4sWL+O233yASiT767xEUFISKigqZ6UNjY2Px999/Y/369bhy5YrM+qWlpTh69CiuX7/OLns7w7///gsvLy94e3uzy7y9veHl5YVz586xy2raJgDIz8/Hvn37sHjxYmzfvh2FhYUftZ0NZebMmVBWVsaZM2e4jlKvysvL4e/vj6+//prrKLVqCvs3ANy5cwcdOnTAmjVrAAA7duyocd24uDisXr0aFRUViI2NxaZNm7Bv374qXeDu3buHVatWYffu3di7dy8A4Pz58/Dy8oKXlxcePXqE3Nxc9rGXlxfb3Sg5OZldlpqaCqD2faq2fZELEydOxO3bt1FUVMRZBkIIIYQQQurk7TYpAQEBDAAmMzOTiyYx72RsbFxtE3+p1atXMwCY6dOns8u6dOnCMAzDPHnyhFFVVWV0dXWZuLg49vunTp1iNm/ezD6OjY1l9PX1GQCMvb09c+XKlTpli42NZQAwPB6PKSsre+f6d+/eZSZOnMgAYC5evMhcu3aNOXz4MGNsbMwAYA4dOsR07tyZAcDcv3+fEQqFde4+o6OjI9OFRyQSMSNHjmTKy8vZZQsWLGB69+7N5OTkMNevX2fk5OTY38OLFy+Y0aNHMwCYX3/9lX3O2xny8/MZd3d3RktLi10nLS2NcXJyYoyNjRmGYWrdppiYGMbDw4O5du0a8/z5c8bR0ZFp27Ytk5eX985t5MLw4cOZKVOmcB2jXsXExDAAmKdPn3IdpUnv31Ljxo1jgoODGYZhmA4dOjCamppMfn5+lfUOHTrEGBkZMQCY8+fPM2PGjGFGjBjBAGDWrFnDrrd8+XLm+PHjTFFREePl5cVoaGgwDMMwkZGRjL6+PmNoaMgUFhYyDPOmKxOPx2Pc3d3ZfUQikTDffvst8/333zMikajWfaq2fZEr0v+/Z8+ecZaBEEIIIYSQOqjahSc/Px8AoK2t3aCFm4Zib28P4M1V2bd17doVBw4cwOvXr/HZZ5+hoKCg2tewtbXFzZs34ezsjJiYGAwbNgzDhw9HbGxsrT87ISGBfX5NXREq69WrF5t3+PDhGDx4MDw9PTFjxgx2nadPnyIqKgpubm7vfL23vXz5En369EGfPn1gYmKCixcvynz/yJEjGDJkCPT09DBo0CB06NCBbTXSvn37Wq+sS2lqaqJz584yy0xMTODi4sI+rm2b5s+fj+nTp2Pw4MHo1KkTtmzZgpcvX2Lr1q3vvb2Ngc/nQyAQcB2jXkmv/Ffu5tJUcbl/S39uTk4OunTpAgCYN28eCgoKcPTo0SrrTpkyBVOmTAHwZlazM2fO4OLFi+jXrx/+/fdfAIBIJMKBAwfQrVs3qKmp4csvv2T3lQ4dOmDZsmXIyclh35cHDBiA0aNHIyUlBVpaWgDezC6Unp6OTZs2gcfj1bpP1ef7S32R/t811ZZnhBBCCCGESFUpoJiamgL4XzGguZGeDBoYGFT7/a+++go//PADIiIiMGnSJDDVz+IMJycnBAcH4++//4aOjg6uXLmCTp06yXRneVt9jQ+iqqrKZgWAdu3afVD3nbZt2+L27du4ffs2UlNTMWHCBJnvX7p0Cd988w2AN917GIaRmWWmrifU8vJVh9J5e1l125SRkQE/Pz88ePAAK1euxMqVK3Hp0iV069YNxcXFdd/QRhQfHw8zMzOuY9Qr6b6Snp7OcZJ343L/BoBdu3Zh3rx57OMpU6ZAQ0MDO3furHZ9dXV1ALJd+hwdHZGSkgIAUFRUhKamJgYOHMh2oVu1ahW7rqenJ+Tl5WWmeNbR0UFiYiL8/PwAAImJiTAxMYGqqirS09PfuU/V1/tLfZGOKWRoaMhZBkIIIYQQQuqiyhn/J598Aj09Pfj4+GDlypVcZPoo0dHRAAAHB4ca19m0aRPCw8Nx/vx5rF27Fs7OztWux+PxsHDhQkycOBGLFy/GkSNH8MUXXyAhIaHaFjp2dnYA3owrUlJSwp6ovK+GOJlRUlLCvHnzZAob7u7uOHv2LHx8fDBkyBC0adOGHUMBqL4w8qGq2ybpFf/ly5dDX1+/3n5WQ0lJSUFQUBCWLVvGdZR6ZWZmBnNzcwQEBODTTz/lOk6tuNy/S0tLcezYMURGRrItSABAT08PERERuHXrVpVBeKvbh9TV1SEWi9nH27dvx+TJkzF8+HB2MFxpgcjY2BjDhg3D4cOHsWzZMmRmZgIArKyssG/fPgwZMgSHDx9mpwKuyz7V1Ma2CggIgJ6eHmxtbbmOQgghhBBCSK2qHN3zeDzMnj0bW7duZWeKaS7Ky8tx8eJF8Hg8fP755zWuJy8vj+PHj6NDhw7YuHFjlQEpf/31V5nHenp6OHz4ML766isIBALcv3+/2tc1MzNDx44dIZFIEB4eXmvWmq6MN6Q+ffpAQUGBfbx8+XIcPHgQ+/btw6RJk6CsrNyoeaTdnJ4+fVrlezV1v+DS2rVrYWFhUesAwc3VhAkTcPDgQZlBVZsarvdvLy8vzJkzB+fOnYO3tzd7O3v2LIDaB5OtzYgRIxAXF4fvvvsOwcHB6Natm8zMPtOnT0dERASePHmC7du3Y+HChZgxYwbOnz+PjIwMhISEsF2Kmts+JZFIsG/fPowfP75eC7aEEEIIIYQ0hGqPWJcvXw4VFRVMnz4dFRUVjZ3pg23ZsoU9EantCjUAaGlp4fz589DR0alygnX37l1kZGRUec6YMWMA1N61Zf369QDe/A5rOhnNzs7GP//8I7NMIpHUmvdD1FakCQ4OxpYtWzB//nyZKY8/pLCjpaUlM62s9HXetU3t2rWDgoICfvzxR5nfVXZ2No4fP/7eORrSmTNncOjQIfz++++NXmhqDAsXLkR2dna10wA3FVzv33v27MHs2bOrLO/cuTNcXV1x7tw5tmtOXRUVFWHfvn3Q1dXFn3/+iVu3bqGwsBBeXl7sOiNGjIChoSF27tyJ+Ph4ODo6Ytq0aZBIJJg+fTr69+/Prtuc9ikA2L17NxISErB48WKuoxBCCCGEEPJO1RZQ+Hw+vLy8cPXqVcybN4+T1hLVEYlEyM7OrrK8rKwM33//PdavX4+VK1eyUwlLpaamVjumhq2tLU6dOiXTKgMAKioq4OnpWWVQw+PHj8PZ2Rmurq41Zhw7diw2btyI27dvY9asWVWm5kxKSsLmzZsxefJkAP8byyE4OBh3795FaWkpO6Vobm6uzHOled413WdFRQWKiopqHexUTU0NAHDu3DmIxWL4+/sjJCQEeXl5iI2NRXx8fLU/r7plVlZWKCsrg5+fHxiGwb///osHDx5AKBRCKBRCIpFUu006OjqYO3cuAgMD0adPH5w4cQKHDh3CxIkT2fEZmgJ/f39MmjQJ8+fPx9ixY7mO0yCsrKywevVqrF27Fk+ePOEkQ1Pev8+fPw9tbe0ax14ZPXo0xGIxNm/eLLNc2oqv8thCYrEYIpEIZWVlqKiowI8//ojS0lIAgJubG+zs7GR+jqKiIiZNmoR//vkH06dPBwCYm5tj6NChCAgIwMSJE9l167JP1fT+0thCQ0OxfPlyLFu2jO3+SAghhBBCSJNW2xw9vr6+jJKSEjNu3DimqKioYScEqoOxY8ey0wR37tyZ+fzzz5mxY8cyI0eOZObOnctOLSr19OlTZubMmQwAZvz48Yyfn1+1r/vXX3/JTHM6ceJEZuzYsUznzp2ZadOmMf/5z3+Yjh07Mn379mXi4+PrlNXb25txdHRkVFVVmT59+jDz589nZs2axaxbt05miuNXr14xRkZGjI6ODrN//37G29ubadeuHZs5JCSEYZg3UwN/8803DADGwcGBOXfuXLU/99atW8yECRMYAIycnByzZMkSJigoqNp1J0+ezMjLyzNGRkbM7t27mY0bNzLy8vLM0qVLmaSkJJmfd+XKlRozFBUVMY6OjgwAxsjIiDl8+DAze/ZsRkdHh1m6dCmzZ8+eardJ+lxPT08GAAOA0dLSYs6ePVun33FjOHz4MKOsrMxMmjSJkUgkXMdpUBKJhBkyZAhjbGzMxMTENPrPb6r7944dOxgDAwPG0NCQ2bx5MyMWi2W+f+vWLaZnz57sPjdjxgwmNTWVOXfuHNOmTRsGALNo0SLm1atXzMmTJxlra2sGALNs2TImLi6OUVVVZZycnJj//ve/zLp165hp06bJTDfOMAwTHh7OdO3aVWaZj48P8/XXX1fJW9s+VdP7S2N79eoVY25uzvTp04cRiUScZCCEEEIIIeQ9eckxTO3NS+7fv48xY8ZAQ0MD+/fvR79+/RqkkMO1nJwcdtDF1NRUmJmZgWEYhIeHIzc3F23btoWFhcV7v25RURHCwsJga2tb46COIpEIYrH4gwed/RjZ2dng8/lQVFQEAOTl5UFHR+e9X0f6u2rbti3U1NQQGxsLc3PzOm9TTk4OkpKS0KFDB05+D28TCARYsWIF9u7di4ULF+LPP/9sFWM0FBQUYNCgQUhISMCZM2fg7u7OdaR60VD798di/n/mK4lEgtjYWNjb29fYhSg5OVkmo1gsRlZWFjtz2tua2j4lFRQUhM8//xxGRka4efMm+Hw+15EIIYQQQgipi5PvLKAAQEZGBubNm4dz585h1qxZ+OOPP+o8xS0hzc3Fixcxd+5cSCQS7Nq1C6NHj+Y6UqMqLCzElClTcPHiRezcuRMzZszgOhJpIU6ePIkZM2agd+/eOHnyJBVPCCGEEEJIc3KyTpfUjY2N4ePjg8OHD8Pb2xsODg7YtWtXk56xg5D39eDBAwwZMgSjRo3C0KFDERUV1eqKJ8CbQVS9vb2xYsUKzJo1C5MmTWKnzyXkQ+Tm5mL69On4+uuvMW/ePFy6dImKJ4QQQgghpNl5rz4JkydPRmRkJD777DMsXrwYtra22LlzZ5UZWAhpTu7fv4/BgwfD3d0dxcXFuHnzJvbv3w9tbW2uo3FGTk4OP/30Ey5cuIB79+6hQ4cO2Lt3b7OalYtwj2EYHDp0CO3bt8f169fh7e2NLVu2VBnYlxBCCCGEkObgvQd1MDIywrZt2xAXF4fRo0djyZIlsLGxwY8//oikpKSGyEhIvSstLcWxY8fw6aefolevXigrK8ONGzdw9+5d9O3bl+t4TcaIESMQERGBGTNmYP78+XB1dcWlS5e4jkWagWvXrsHd3R0zZ87E119/jcjISHaqaEIIIawKy/kAACAASURBVIQQQpqjDx4V08zMDP/973/x8uVLeHp6Yu/evbC2tsbw4cNx9uxZdqpMQpqS8PBwLFq0CKamppg+fToMDQ0REBCA27dvo3///lzHa5LU1dWxZcsWBAcHw9jYGB4eHujevTvOnz/fZKY4J03H5cuX4ebmhqFDh4LP5yMoKAh///03tLS0uI5GCCGEEELIR6nTILJ1IRKJcOHCBezbtw/Xr1+Hvr4+Pv/8c4wZMwb9+vVjZ3khpLFFR0fDx8cHZ86cQXBwMGxtbTFjxgxMnToVxsbGXMdrdp4+fYoNGzbA19cXjo6OmDNnDiZNmtSquzy1dgUFBThx4gR2796NkJAQjBgxAmvWrEGPHj24jkYIIYQQQkh9qdssPO8rMTERx44dg4+PD54+fQodHR14eHhgzJgxGDx4cJOaUpO0TM+ePcPZs2fh4+ODiIgIGBgYYPTo0fjyyy/Rr18/yMnJcR2x2QsJCcG2bdtw8uRJMAyDL7/8ErNnz4aLiwvX0UgjefLkCfbu3QsvLy9IJBJMmDABCxcuRJcuXbiORgghhBBCSH1rmAJKZYmJiTh37hwuXryIW7duQVFREV26dEGvXr0wcOBA9OnTh1qnkI+WmZmJO3fuwN/fH1evXkVSUhIsLCwwbNgwjBw5EkOHDqX/swaSn5+PkydPYvfu3Xj27BnatGmDUaNGYfz48XB3d6diVQsTERGB06dP4/Tp04iMjET79u0xdepUzJw5E3p6elzHI4QQQgghpKE0fAGlsvT0dFy9ehX+/v64ceMGMjMzoauri379+mHAgAFwd3dHx44daYYG8k7p6ekIDAxEQEAA/P398eLFCygrK6Nnz54YMGAABg8ejG7dutHJeyN7/PgxTp06BW9vbyQkJKBt27YYN24cRo0ahR49eoDH43EdkbwniUSCJ0+e4MKFC/D29kZ0dDQsLCwwbtw4TJgwAa6urlxHJIQQQgghpDE0bgGlMoZhEB4ejhs3bsDf3x+3b99GYWEhNDU10a1bN7i5ucHFxQUuLi4wMjLiIiJpIkpLS/H06VM8evQIjx49wsOHD5GUlAR5eXl88sknGDBgAAYOHIhevXpBTU2N67jk/z1+/Bje3t7w9vbGq1evoK2tjf79+2PQoEEYNGgQbG1tuY5IahAfHw8/Pz/4+fnhxo0byMvLg5WVFcaOHYvx48fDxcWFipOEEEIIIaS14a6A8jaJRILw8HAEBgbi0aNHCAwMRHR0NCoqKmBtbY0uXbrAyckJTk5O6NSpE2xsbOgAvgV6/fo1QkJCEBYWhrCwMDx//hyhoaEoLy+HgYEBW1RzdXVFjx49aGaPZiI6Ohp+fn64fv06AgICUFhYCGtra/Tu3Rtubm7o2bMntT7jSEVFBSIjI/Hw4UM8ePAA9+7dQ1xcHNTV1dGnTx8MHjwYgwYNgoODA9dRCSGEEEII4VLTKaBURygUsq0OQkNDERISgpcvX6KiogIaGhpwdHSEs7MznJycYG9vDzs7O1haWtJJWDOQm5uL2NhYxMbGIiIiAqGhoQgLC0NKSgoAQF9fH506dYKTkxO6desGV1dXtG3bluPUpD6IRCI8fPgQ/v7+ePDgAYKCglBQUABNTU24uLigZ8+e6NKlC5ydnWFtbc113BYnMTERoaGhePr0KR4+fIjAwEAIhUJoaGige/fucHd3R//+/eHu7g4lJSWu4xJCCCGEENJUNO0CSnWKiooQEREh00ohLCwMubm5AABlZWXY2NiwBRXpzcrKCubm5nRC0IgyMjKQlJSEV69eITY2FjExMWzR5PXr1wDe/L3at28PJycnODs7szcTExOO05PGIm199uDBAwQGBuLhw4eIi4sDwzDQ1tZm/zekBTV7e3sarLQOXr9+jdjYWISGhsrcBAIB5OTkYGNjAzc3N7i6uqJnz55wcnKiMWoIIYQQQgipWfMroNREerIQFxeH6Oho9kQ9Li4OQqEQACAnJwdjY2NYWlrCwsICFhYWsLKygqWlJUxNTWFqagoDAwOoqKhwvDVNW0VFBbKzs5GdnY3U1FQkJycjOTkZCQkJ7P3k5GSUlZUBABQVFWFtbQ07OzuZwpatrS0sLS0hLy/P8RaRpqagoADh4eFsyzNpC6X8/HwAgK6uLmxtbWX+p9q2bQsLCwsYGRm1iv8phmGQkZGBlJQUvHz5EnFxcYiJiUF0dDRevnzJFpU1NDRkilDSVnvU/Y0QQgghhJD30nIKKLXJyspCYmJijSf66enpMutramrCxMQEBgYGMDAwgImJCQwNDWFgYAAdHR3w+Xxoa2uDz+ezN3V1dY627uOIRCIIBAIIBAIIhUIIBALk5eVBIBCwRZLs7GxkZGQgMzOTfVxRUcG+hqamJiwtLastTFlYWMDS0pKubJOPxjAMEhMTERcXxxZIpa2a4uPjIRKJALwp2JmYmMDCwgLm5uYwNTWFpaUlDAwMoKenB319fRgYGEBfX79J7rdFRUXIzc1FdnY2cnJy2FtSUhLS0tKQnJyMlJQUpKeno7y8HMCbbW7Tpg309fXx7NkzjB49GlOnToW9vT3atGlD40URQgghhBDy8VpHAeVdysrKkJaWhoyMDGRnZyMrK4u9n52djfT0dPZ+Xl4ee6JWmaKiIltU0dbWhrKyMtTU1KCmpgZlZWVoamqCx+OBz+dDXl4efD6ffa70e2+/noaGhswykUiEwsLCKj9bKBSyBY2SkhKUlpaisLAQIpEIQqEQEokEAoEAEokE+fn5KCkpYYslRUVF1f5O+Hw+9PT0YGRkBAMDAxgaGsLY2LjKfRMTE+jo6Lz375yQ+iQWi9nCQnJyMlJTU6vcz8nJYQsOUioqKmxRRU1NDerq6uDz+VBVVYWqqip0dHSgqqrKtkrT0tKSGWNJRUUFqqqq7OPS0lKUlJSwjysqKtgWcNLv5eXloaSkBCUlJRAIBCguLmaLJrm5uTLPB968F+jr68Pc3BxmZmYyhSErKyt2maKiIoqLi/Hbb7/hl19+gaOjI3bs2EHTDBNCCCGEEFI/qIDyIYqKithWGytWrMCNGzfw+++/Q15enm3JUV5ejqKiIhQXF6OsrAwFBQUQi8UQCAQQi8VsVwQAyMvLq/IzpIWQyuTk5GQKL1Lq6urs2C4qKiqQk5MDj8eDgYEBtLW1oaCgAD6fDx6PB01NTaiqqlbbikb6mAoipKXKz89HTk4OsrOz2YJFTk4OcnNzcebMGfB4PDg4OKCkpATFxcVsgaOsrAwMw0AgEMi8XlFRkUxRprrCp7a2NuTl5aGkpFRtgUZaaNXX14eenh5b0NHT04OhoeEHdbWJiYnBt99+C39/f0yaNAlbt26Fvr7+h/3SCCGEEEIIIQAVUD7ODz/8gK1bt8LX1xfDhg3jOg5r2rRpuHPnDl68eEGD5hJSB6GhoejcuTP+/fdfjBs3jus49ebChQuYP38+ioqKsHbtWixYsKBVjA9DCCGEEEJIA6ACyofauXMnvv32Wxw4cADTpk3jOo6M1NRU2Nvb45dffsHChQu5jkNIkzd06FC8fv0ajx49anHjhRQVFWHDhg34448/0KlTJ+zcuRM9evTgOhYhhBBCCCHNzUm6FPkBvLy8sGDBAmzZsqXJFU8AwMzMDPPnz8eGDRvY8RcIIdW7ffs2rl27hs2bN7e44gnwpovf5s2bERwcDBUVFbi5ucHT05OdpYcQQgghhBBSN9QC5T0FBARg6NChWLBgAX7//Xeu49RIIBDA1tYWc+fOxcaNG7mOQ0iTxDAMXFxcoK+vj8uXL3Mdp8ExDIOjR49i+fLlEIvFWLNmDXXrIYQQQgghpG6oBcr7iIqKwtixY/HZZ5/ht99+4zpOrfh8PjtGS0pKCtdxCGmSfH198eTJE/zyyy9cR2kUcnJy8PT0RFRUFCZOnIglS5agb9++CA0N5ToaIYQQQgghTR61QKmj3NxcuLm5gc/n49atW1BTU+M60juVlpaiffv2GDx4MPbu3ct1HEKaFIZh0LlzZ9jZ2eH06dNcx+HE8+fPMX/+fAQFBWHevHnYsGHDB836QwghhBBCSCtALVDqorS0FKNGjYJIJMKFCxeaRfEEeDOl8U8//YSDBw8iIiKC6ziENCk+Pj4IDQ3FmjVruI7CmU8++QT37t3DgQMH4OXlhXbt2uHIkSOgujohhBBCCCFVUQuUd2AYBp6enjh//jzu378PR0dHriO9l4qKCnTr1g2WlpY4d+4c13EIaRKkrU/at2+PkydPch2nScjLy8O6deuwY8cOuLu7Y8eOHc3u/Y4QQgghhJAGRC1Q3uWnn37Cv//+i7NnzzbLkwl5eXn8/PPP8PX1xb1797iOQ0iTcPr0aYSFhWHVqlVcR2kydHR08PfffyMoKAjl5eXo3LkzFi1ahIKCAq6jEUIIIYQQ0iRQC5Ra+Pr6YsyYMdi5cyfmzJnDdZyPMmjQIBQUFODhw4ctcqpWQuqKYRh06tQJHTt2hJeXF9dxmqSKigocO3YMS5YsgZKSEn755Rd4enpyHYsQQgghhBAuUQuUmkRFRWHKlCnw9PRs9sUTANiyZQseP35M3XhIq3fp0iWEh4djxYoVXEdpsuTl5eHp6Yno6GiMGzcO06ZNQ79+/RAZGcl1NEIIIYQQQjhDLVCqkZeXBxcXF+jr6yMgIADKyspcR6oXX331FZ4+fYrw8HAoKipyHYcQTvTq1Qs6Ojq4cOEC11GajSdPnmD+/Pl49uwZvvnmG2zatAkaGhpcxyKEEEIIIaQxUQuUt1VUVGDSpEkoLCyEt7d3iymeAMDPP/+MxMREHDx4kOsohHDi7t27uH//PrU+eU/dunXDw4cPsX//fhw/fhzt27fHkSNHuI5FCCGEEEJIo6ICyltWrVqFmzdv4ty5czA1NeU6Tr2ytrbGnDlzsHbtWhoYkrRKmzdvhqurK3r16sV1lGancreeESNGYOrUqRgwYABevHjBdTRCCCGEEEIaBRVQKrl8+TJ+/fVXbN++HT169OA6ToNYs2YNysrK8Ndff3EdhZBGFRYWhitXrtDMOx9JT08Pe/bswe3bt5GdnY1OnTph0aJFKCws5DoaIYQQQgghDYrGQPl/KSkp6Ny5MwYNGoQTJ05wHadBbdq0CZs3b0ZcXByMjIy4jkNIo5gxYwYCAwMRHh5OM1HVE7FYjB07dmDt2rXQ0tLC1q1bMX78eK5jEUIIIYQQ0hBoDBTgzUnAV199BV1dXezZs4frOA1u8eLF4PP52LRpE9dRCGkUOTk58PLywoIFC6h4Uo94PB4WLVqEqKgo9OvXD1988QU8PDwQHx/PdTRCCCGEEELqHRVQAKxevRpPnjzBqVOnoKmpyXWcBqeqqoo1a9Zg9+7diIuL4zoOIQ1u7969UFZWxuTJk7mO0iKZmJjgyJEjCAgIQEJCAjp27Ih169ahtLSU62iEEEIIIYTUm1bfhefKlSsYOXIk9u/fj2nTpnEdp9FIJBI4OzvDyckJJ0+e5DoOIQ1GLBbDxsYGX3zxBbZs2cJ1nBZPJBJh586dWLNmDQwNDfHf//4Xw4cP5zoWIYQQQgghH6t1d+HJzMzElClTMGnSpFZVPAEABQUFbNq0CadOnUJgYCDXcQhpMD4+PkhNTcU333zDdZRWQVFRke3W07NnT4wYMQIeHh5ISEjgOhohhBBCCCEfpVW3QPHw8EBERARCQkJaRded6vTq1Qs8Hg+3bt3iOgohDaJPnz7Q0dHBuXPnuI7SKgUEBODbb79FQkICli1bhpUrV0JZWZnrWIQQQgghhLyv1tsCZe/evbh8+TL++eefVls8AYA//vgDd+7cwZUrV7iOQki9i46Oxt27d6n1CYf69euH58+f4+eff8Yff/wBJycnXL16letYhBBCCCGEvLdWWUCJj4/H0qVLsWLFCvTp04frOJxycXHBZ599hhUrVkAikXAdh5B6deDAAZiZmWHgwIFcR2nVKnfrcXV1xbBhw+Dh4YGkpCSuoxFCCCGEEFJnra6AUlFRgalTp6Jt27ZYt24d13GahM2bN+PFixc4duwY11EIqTdisRjHjh3DjBkzoKCgwHUcAsDMzAxHjhyBv78/4uLi0KFDB6xbtw7l5eVcRyOEEEIIIeSdWl0B5ddff8WjR49w9OhRKCkpcR2nSWjXrh2mT5+OVatWobi4mOs4hNSLCxcuIDMzs9UNEN0cDBgwACEhIfj555/x+++/w8nJCdevX+c6FiGEEEIIIbVqVQWUqKgorF+/Hhs3boSjoyPXcZqUdevWQSAQYMeOHVxHIaReHDhwAIMGDYKVlRXXUUg1lJSUsGjRIoSGhsLe3h5DhgyBh4cHkpOTuY5GCCGEEEJItVpNAYVhGMyfPx/t27fHd999x3WcJsfExATff/89fv75Z+Tm5nIdh5CPkpaWhqtXr2LGjBlcRyHvYGNjgwsXLuD8+fOIiIigbj2EEEIIIaTJajUFlIMHD+L27ds4cOAAeDwe13GapBUrVkBZWRmbN2/mOgohH+XUqVPQ1NTEqFGjuI5C6kg6rfzSpUvx66+/wtnZGf7+/lzHIoQQQgghhNUqCig5OTn44YcfsHDhQnTt2pXrOE2WhoYGVq1ahe3btyMxMZHrOIR8sJMnT2L06NFQVlbmOgp5D6qqqli3bh3Cw8PRtm1bDB48GJ6ensjMzOQ6GiGEEEIIIa2jgPLdd99BVVUV69ev5zpKkzd37lyYm5tj7dq1XEch5IMkJSUhKCgIX3zxBddRyAdq27YtLl26BF9fX9y5cwft27fH33//TVOtE0IIIYQQTrX4Aoqfnx+OHz+O7du3Q1NTk+s4TZ6ioiI2btyIY8eO4dmzZzLfE4lEuHz5MkfJCKkbLy8v8Pl89O/fn+so5CN5eHggMjISixYtwooVK9CtWzc8ePCA61iEEEIIIaSVkmMYhuE6REMRiURwdnZGhw4d4OPjw3WcZoNhGPTs2RN8Ph9XrlwBwzDw8fHBsmXLkJubC6FQyHVEQmrUpUsXdOvWDXv37uU6CqlHsbGxWLBgAa5fv45Jkybh999/h6GhIdexCCGEEEJI63GyRbdA2bNnD169eoXffvuN6yjNipycHDZv3oyrV6/izz//RI8ePTB+/HgkJiYiPz8f6enpXEckpFqxsbF49uwZJkyYwHUUUs/s7Oxw9epV+Pr64vbt29SthxBCCCGENLoWW0ARCARYv349Fi1aBFtbW67jNDtGRkYwMjLC4sWL8fz5czAMg4qKCgDAixcvOE5HSPV8fX2hp6eHfv36cR2FNBAPDw+8ePECCxcuxPLly9GjRw8EBgZyHYsQQgghhLQCLbaAsmnTJlRUVOCHH37gOkqzkpqaitmzZ8PR0RG5ubkAALFYzH5fUVGRCiikybp8+TKGDh0KBQUFrqOQBqSmpoZ169YhLCwMenp66NmzJzw9PZGdnV3r8x4/foxXr141UkpCCCGEENLStMgCSnx8PLZt24b169dDV1eX6zjNQkVFBVavXg0bGxscOnQIEolEpnBSWWRkZCOnI+Td8vPzcf/+fQwfPpzrKKSR2Nvb4/r16/D19cWtW7fYbj3S1nKVSSQSTJ8+HcOGDUN+fj4HaQkhhBBCSHPXIgsoK1asQJs2bTBnzhyuozQb8vLycHZ2lumqUx2RSITQ0NBGTEZI3Vy/fh0SiQRDhgzhOgppZNJuPQsWLGC79QQFBcmss2vXLkRGRuLVq1f48ssva32fI4QQQgghpDotroDy9OlTeHt747fffoOioiLXcZqVCRMm4Nq1a1BWVgaPx6txPWqBQpqiK1euwMXFBXp6elxHIRxQV1fHunXr8PjxY6ioqMDNzQ2enp7Izc1FZmYmVq5ciYqKCojFYly/fh0rV67kOjIhhBBCCGlmWtw0xmPGjEFCQgKCg4MhJyfHdZxmKSwsDAMGDEBeXl6N3Xhyc3OpexRpMhiGgbm5OebNm4dVq1ZxHYdwjGEYHD16FMuXL4dYLIa1tTVCQkIgEolk1tu/fz9mzJjBUUpCCCGEENLMtKxpjCMjI+Hr64u1a9dS8eQjODk54dGjRzA3N6+xFU9UVFQjpyKkZmFhYUhLS8OwYcO4jkKaADk5OXh6eiIqKgr9+vXDkydPqhRPAGDu3Lm4c+cOBwkJIYQQQkhz1KIKKBs3bkT79u0xatQorqM0e9bW1ggMDET79u2rFFF4PB514yFNyt27d6GlpYVOnTpxHYU0IRoaGoiMjKyxSyLDMPj888+RnJzcyMkIIYQQQkhz1GIKKC9fvsTp06exevVqyMu3mM3ilJGRER48eIBPP/1UZlpYeXl5msqYNCn3799Hz549afpiImPbtm2IioqqsSuiRCJBQUEBhg0bhqKiokZORwghhBBCmpsWU2nYtGkTrKysMH78eK6jtCgaGhq4fPkyxowZwxamysvLER4eznEyQv7n/v37cHd35zoGaULS09OxevXqd862IxKJEB0djcmTJ6OFDQlGCCGEEELqWYsooCQnJ+PYsWNYtWpVrbPHkA+jpKSEkydPYs6cOezYMmFhYRynIuSN1NRUJCUlUQGFyFi5ciWKi4vB4/He+bkgFovh6+uL9evXN1I6QgghhBDSHLWIWXjWrl2LvXv3IikpCUpKSlzHadE2bNjADtKbn58PDQ0NriORVu7kyZOYPHky8vLy6P+RsMRiMaKjoxEcHIzg4GA8fPgQT58+hUQiAY/HA8MwkEgkMs+Rk5PDiRMn8OWXX3KUmhBCCCGENGEnm30BRSwWo02bNpgyZQo2bdrEdZxWYe/evZg3bx4CAwPRrVs3ruOQVm7RokV4+PAhgoKCuI5CmrjCwkIEBwfj8ePHePToER4+fIjU1FQAgIqKCkpLS6GsrIwHDx6gS5cuHKclhBBCCCFNTPMvoPj4+GD8+PGIi4uDtbU113FahaKiIpw7dw5CoRADBw5EQUEBu7y8vFxm3YqKCgiFwiqvoaCgAC0trSrL1dTUoKysDDk5OfD5fCgpKUFdXR3q6urUuohU69NPP4WjoyN27tzJdRTSDGVnZyMoKAiPHz9GYGAggoKCoK6ujsePH8PY2LjOr1NSUoLS0lIAQGlpKUpKSgAAZWVlKC4ulllXKBS+c2wWhmEgEAjq9LNVVVWhoqLyzvU0NTVlujPxeDxoamoCkH1PlpeXh7a2dp1+NiGk+RGJRCgsLGTft/Lz8yGRSCCRSJCfn19l/crvb5UpKytDTU2tynLpe430fUW6Hh3LkdZGem4kFAohFovZc6Ka9qmajg/e/vwGZD+rVVRUoKqqyq6no6PTAFtD/l/zL6AMGTIECgoKuHz5MtdRmo2cnBxkZWUhKysLubm5EAgEyMvLq/FraWkphEIhysvLOZ+pgs/ng8fjQUtLC+rq6tDR0QGfz6/xq56eHoyMjGBiYgJ1dXVOs5OGoaenh59++gnz58/nOgppIqQnAUKhEAUFBSgsLERRURF7kpCXl8euI31fkx7MFBQUQCgUQiAQQEVFBUKhkD3ZAGQLxcXFxSgrK+NyUxuctJgtxefzIScnB0VFRWhoaLDFGw0NDSgqKkJbWxsKCgrg8/nsOtIDO+nJk/SESlNTEzo6OtDQ0ICmpiZUVVU53FJCmo/c3FxkZmYiOzubPY6r7SZ9/xOLxXUuzDYkbW1t8Hg8aGtrQ01NDXw+v9qb9FhOV1cXBgYGMDIygr6+PtfxSSshFouRlZXF7mvSc6PK50lv36QFyeounjQ26UUS6WdwTftZ5Zv0vMnY2JjOm2rWvAsor169gp2dHXx8fPDZZ59xHYdzBQUFSExMREJCAhITE5GRkYH09HRkZmYiMzMT6enpyMrKqtJKREtLq9ZChIqKCrS1tatcQdDW1oaioiJ71bKmKxHa2tpVppauqRgjrbxKW65I34AqV3BFIhHy8/NRVFRUa+FHegVYSl1dHSYmJjAyMoKRkRFMTU1hYGAACwsLWFlZwcrKChYWFnR1pBlJS0uDmZkZbt26hT59+nAdh9SD8vJyvH79Gnl5eexX6f2CggIUFBRAIBCw9wsLC1FQUIC8vDz2/tv7fmXSgoD0yqi0lVtthYDKLTUqt/aQHpQAsu9/0tcEwBYRKqv8vNpIs7yLQCB45wxC1V1Zrvw+XLlIJBaL2ZaFlZ9XuUWh9L1ZWkQqKChgT84kEgl7ta2goKDKujWR/k34fD5bVNHQ0IC2tja0tLTYx9LPLF1dXZmvOjo67N+JkOYoJycHSUlJSE5OljmOy87ORkZGBjIyMpCdnV3lOE5TU7PWAoSamlq1xc233/eA/xVJK6vufQyovuUxAOTl5QH433uJtFVedVfji4uLqz0RlR7PSd+LKmcxNDRkT/IMDQ1hbGwMY2NjWFpasjcDA4OP+luQlksikSAtLQ2JiYlITExEamoqu59Jz5uys7ORlZUl8zzp8YP086a6fU5FRaXaVldaWlrg8XjsBYma9qmaWmlJ96nKKn+Gv/1ZnJeXV+UzWCgU1lj4kRZ/3s5ibGwMIyMjGBoawsTEBIaGhjAzM4OFhQUsLS3Rpk2bas/9WrjmXUBZsWIFjh07hsTExFYx+45YLEZCQgKio6MRHR3NFkuSkpKQmJgos3Pp6urC1NQUJiYm7AeMqakpuwMYGxvDwMAA+vr6VYobLUVZWRlycnLYg46srCykpaUhKyuLPSjJyspCUlISe8IlJycHExMTtGnTBlZWVrC0tIS1tTXatWuH9u3bv1eTftLwrl+/jiFDhiArK4sOlpqgwsJC9qAkOzsbmZmZyMnJqVIYqfy1usKqiooKdHV1oaWlBQ0NDfD5fPa+9KRaevIsXSY9oZAuk55AtNT3u+ZEekJVuRgmLX693XKosLAQAoEA+fn5Muvk5eVV2z1UUVGxSlGlcqFFeiVb+hkovdH/BWkMhYWFiImJQUxMDOLi4pCUlMQWTBISEmSuWFe+2CMtGJiYmLD/nYQTxAAAIABJREFUv9JjOz09PSgoKHC4VQ1LIpEgNzeX/QyRHrtlZGQgMzOTPbbLzMxERkYG+zxVVVX2OE56s7W1hb29Pezt7anY2sJlZGQgOjoaMTEx7LmS9GtaWhrEYjGAN58ZJiYm7H4m3bcMDAzYi67S/a+ld20tKSnB69ev2SJSVlZWlftZWVlISUmRKWzq6+vD0tJS5oK0nZ0d2rVrB2tr6zpdCGpmmm8BhWEYWFpaYurUqdiwYQPXcepVcXExwsPD8eLFC7ZYEhUVhbi4OLbSb2JiAhsbG/ZDQfohIT3xp9lI3k9WVhYSExPZgxlpK57ExETEx8ezB+ra2tpo164dW1Bp164dHBwcYG9v36IPYJqqrVu3YsuWLUhPT+c6SqshEAiQmprKHrBKr9JkZGSw3QOlV0nfbgnC5/NhYGBQY+uBt5dJv1LXDlIdaXesmlos1fQ1OzubPXgG3vQjlxZSpCet0sfSE1YjIyOYm5vDyMiI3uvJOyUmJiIyMhJRUVFswSQ6OpodtFpRUVGm5evbJ/qWlpZ1GteIyCorK5MpSkmP46T3ExISIBKJAACmpqZo164dW1CRHs/ReIrNh0gkwosXL/DixQt2H5Pub9Ljdk1NTVhbW1fZxywsLNCmTRuYmJhQAf0DCAQC9gK+dB+T7nfx8fFIS0sD8Oa9TnohWrq/tWvXDk5OTs15nJbmW0AJCgqCi4sLnj9/jk6dOnEd54MJBAKEh4ezU21GRkYiLCwM5eXlUFJSgrm5ORwcHNCxY0fY2NjAwcEBzs7O1Q7AShpOXl4eXr16hYiICERGRrL3o6OjIZFIoKSkBFtbW3Tt2pW9de7cmfoPNrAZM2YgKSkJfn5+XEdpEfLy8pCWlob09HS8evWKvS/9GhcXV+Wqv46ODkxMTKCjo8O2eqvuvrm5OXWPI01GSUkJ+7+dl5cnc//txxkZGTJdpHR0dGBjY8NetZR+lS6zsLCgz+hWQiQSISYmhj1+i4iIQFBQENv0X/q/Uvk4TvqYCsONTywWIykpCa9evapyTBcfHw+GYaClpQUnJyd07NgRDg4O6Pp/7J13VFTX9/YfuvQiVZQm0gQErIhYomBPNALGJGjsJbEl1pRvYtTExMQYe0libMGCiqhRBDWKgIWqoFKkSRWkDB0G9vuHv7kvI6C0YRg8n7VmMXPn3HMe7p197j77tP794eTk9DZOU+hUFBcX4+HDh0K2FhkZiYqKCsjKysLIyEjIvgT2Zmpq2mBKGkP0VFVVISkpibMvgb09fPiQmxZsYGAgZGf9+/eHtbW1JAS0JDeAsn79epw4cQIpKSniltJsampqEBERgbCwMNy+fRt3797leiMMDQ3h4ODAvRwdHWFqaioJP6K3mqqqKsTFxSE6Opp7xcTEgMfjQUZGBpaWlnB2dsawYcPg7OwMS0tLcUvuUri6usLBwQE7d+4Ut5ROT11dHTIyMpCSkiL0Sk5ORmpqKnJzc4V65QXDxXv27AlDQ0P06NEDvXr14oIhBgYG0NLSEuN/xGB0DBUVFcjJyUFmZiYyMjKQlZWFZ8+eISsrizuWnZ0ttBaElpYWevXqBVNTU6GXwKFnjWfJJD4+Hnfu3EFoaCjCwsLw+PFj8Pl8KCkpwdbWFg4ODujXrx/s7e1hZ2fX5Yf8dyV4PB5iY2Px4MEDzpd7+PAhysrKICsrCysrKwwZMgRDhw7FkCFDYGVlxRrmIqKqqgqRkZEICwtDaGgo7t69i4yMDAAvfRN7e3s4OjrC3t4e/fr1g6WlZVecJtJlycjIwMOHDxETE8PZWmJiImpra6GiogJHR0cMHTqUszVdXV1xS34VyQ2gWFtbY/z48di2bZu4pTRJWVkZbt68iZCQENy+fRv3799HRUUFdHR0MHToUDg7O8PJyQkODg5s/YYuBBEhOTkZUVFRiIiIQEhICMLDw4XuvYuLC4YPH44BAwaw4eBtwMzMDAsXLsTatWvFLaVTUFFRwQ1hfTVQkpaWxjXwFBUVhRpzJiYmMDQ0hKGhIRccUVBQEPN/w2BIFoK1tTIyMpCRkcENZRYEKvPy8ri0+vr6nP0JXr1794a1tXVndBbfSmpqanDnzh3cvn0bYWFhCAsLQ35+Prp164YBAwbA2dkZAwYMQL9+/WBubs6e5V2Quro6JCUlISYmhusAFfjyWlpacHZ2xpAhQ+Dq6gpnZ2c2yrKVFBQUcO2lsLAwREREoKqqCrq6utw1dnR0RL9+/dhahF2UiooKxMbGIjo6Gvfu3eMC1HV1dTA3N4ezszOcnZ0xcuRIWFtbi1uuZAZQEhISYGlpiVu3bsHV1VXccoRITk7GhQsXcPHiRQQHB6OqqgpmZmZwcXHBsGHD4OLiAhsbGxa1fsvg8/mIj4/ngmm3bt1CWloaVFRUMHLkSEyePBnjxo2DkZGRuKVKFEpKSti3bx9mzpwpbikdypumlAH/f+h4Yy8TExM2uo3B6GCqqqqQmZnJDWeu/0pMTOSGNWtoaKB3794NhqL37duXrYshYpKTkxEUFISgoCAEBgaiqKgIBgYG6N+/P+fDDRgwgN2Ht5hX/TnBlBIlJSUMHToUY8aMwZgxY+Dk5MR8/Sbg8/mIiYnhbO3mzZuoq6uDpaWlkK2x9tLbTUlJCWJiYjhbCwkJQWFhIfT09DB8+HCMGTMGkyZNQo8ePTpammQGUH788Uds374dWVlZYo/4V1ZWIiAgAGfPnkVAQAByc3Ohp6cHNzc3jB07Fm5ubtDT0xOrRkbn5PHjxwgICEBAQABu3ryJiooK9O3bF+PHj4enpycGDhzIHhyvoaCgAN27d0dgYCDGjBkjbjkigcfjITo6GlFRUXjw4AEePXqE+Ph4bsctNTU1WFpawtramlvU2NraGr1792Y9YQyGhJGZmYknT54gPj5eaBH59PR0AODW2rKysoKtrS0cHR3h6OgIY2NjMSuXXKqrqxEUFISzZ8/i6tWrePbsGdTV1TFq1Ci4ubnBzc0Nffr0EbdMRicnOTkZgYGBCAoKwrVr11BYWAhDQ0OMHTsWU6ZMgbu7+1s/qjMvLw/nzp2Dv78/bt68idLSUpiZmXF29s4770jyoqKMDqC2thb3799HYGAgAgMDERYWhrq6Ojg4OGD8+PGYNm0aHB0dO0KKZAZQhg4dChsbG/zxxx9iKb+6uhpXr17FqVOncP78eZSWlsLFxQUTJ06Eu7s7HBwcWMOX0SIqKysRHByMgIAA+Pv7IzExESYmJvDy8sL06dPh5OQkbomdjri4ONja2iIuLg42NjbiltNmcnJyEBUVhaioKERHRyMyMhLJyckgImhra8PBwQHW1tawtrbmdoESQ9SdwWB0MKWlpVwwRRBEffDgAZKSklBXVwdNTU1uOrAgqGJpaSn2DqbOSlVVFQIDA+Hr64vz58+juLgYAwcOxIQJE+Dm5oZBgwZBVlZW3DIZEkptbS3Cw8MRGBiIy5cv486dO1BVVcXkyZPh6ekJd3f3t2YE0/Pnz3H27Fn4+vriv//+g4KCAsaOHQt3d3e4ubmhd+/e4pbIkGBKSkpw48YNBAYG4sKFC0hLS4O5uTk8PDzg6ekpyraT5AVQSktLoaWlhWPHjsHLy6tDy46JicHevXtx6tQpFBUVwdnZGV5eXvD09GQNGUa7EhUVhZMnT+LUqVNISUmBubk5Zs+ejXnz5rH58f9HYGAg3N3dUVBQIHG9FpWVlQgPD+eGJEZERHBbMRsbG8PR0VGoMdSrVy8xK2YwGJ0NwfBmwSi1qKgoxMXFobq6GkpKSrC3t+fWZ3BxcXnrR8Pev38f+/fvh6+vL3g8HoYMGQIPDw94eHiw6bMMkZGZmYkzZ87A19cXISEhUFFRwdSpU7Fw4UI4OzuLW167U11djXPnzuHgwYNc0GTixInw8PDAxIkT2e6UDJFARAgPD8fp06fh6+uLlJQUmJmZYdasWZg3b157t9MlL4ASEBCAcePGITMzs0OCFlVVVThz5gx2796N0NBQWFlZYd68efDy8mKNGkaHcO/ePfj4+ODIkSMoLS2Fh4cHlixZAhcXF3FLEytHjx7FggULUF5e3ulHfBUWFiIkJERoQemqqir06NEDw4YNw8CBA7lgCdvZhsFgtJbq6mrExcUhKioKkZGRCAkJwcOHD1FbWwsLCwu4uLhwARULCwtxyxU5paWl8PHxwb59+xAZGQk7OzvMmTMH06ZNYz4co8PJysrC2bNncejQIURGRqJfv35YuHAhPvroI4nf+jw5ORkHDhzAoUOHUFBQgIkTJ+Ljjz/GhAkT2BbQjA4nPDwcJ0+exJEjR1BQUIDJkydj0aJFGDNmTHusASh5AZQvv/wSZ86cQXx8vEjLKSsrw44dO7B9+3YUFBTgvffew5IlSzBq1KhO31hjdE0qKipw4sQJ7NmzB+Hh4XBwcMD//vc/TJky5a38Te7duxf/+9//hHa26Czw+Xzcvn0bly5dwpUrV/Do0SMQEaytrbkFpYcNGwYzMzNxS2UwGF0cHo+H0NBQhISEIDg4GPfv30d5eTn09PQwcuRITJo0CePHj0f37t3FLbXdyMvLw88//4wDBw6guroanp6eWLRoEYYOHSpuaQwGgJedY/v27cPJkychLS2NuXPnYt26dRK3y8z9+/exYcMGXL58GT169MDcuXMxf/58GBoailsag4Hq6mqcPXsW+/btw82bN9G7d2+sXbsWn3zySVu2vj4BkjDGjBlDn3zyicjyr6qqop07d5K+vj6pqqrSV199RRkZGSIrj8FoDXfv3iUvLy+SkpKigQMH0tWrV8UtqcP5/fffycDAQNwyOPLz8+no0aM0ffp00tDQIABkZWVFX3zxBZ0/f57y8/PFLZHBYDCourqaQkNDaevWreTm5kby8vIkIyNDLi4u9OOPP9KDBw/ELbHVFBQU0FdffUUqKiqkr69PW7dupRcvXohbFoPRJIWFhfTbb7+RoaEhKSkp0erVqykvL0/cst5ITEwMvffeeyQlJUXOzs7k5+dHfD5f3LIYjCZ59OgRLVq0iOTl5al37950+PDh1v5mfSQugKKtrU07duwQSd5+fn5kYmJC3bp1o5UrV9Lz589FUg6D0V5ERkbShAkTCAC98847FB8fL25JHcbWrVvJ2NhYrBpycnJo+/bt5OLiQjIyMiQvL09jxoyh7du3U1JSkli1MRgMRnPg8Xjk6+tLs2fPJl1dXQJAxsbGtHz5crp375645TULPp9Pv/zyC2loaJC2tjb99NNPVFZWJm5ZDEazKS8vp23btpGuri6pqqrS5s2bqaamRtyyGpCTk0MzZswgaWlpcnJyoosXL4pbEoPRIlJTU2nu3LkkKytLVlZWremElqwASmpqKgGg27dvt2u+xcXFNHv2bAJA3t7elJ6e3q75MxiiJjg4mJycnEhJSYl2795NdXV14pYkcn744QcyNzfv8HL5fD6dPXuWJkyYQLKysqSqqkre3t50+vRpKi4u7nA9DAaD0V7U1tbS3bt36euvvyZLS0tuJN2PP/7YaTuVnjx5Qs7OzqSgoEDffvst8Xg8cUtiMFpNaWkp/fDDD6SoqEgDBgyg2NhYcUviOHnyJGlra5OpqSmdPXv2rfA1GV2XxMREmjZtGklJSdGiRYuopKSkuaf6tHkVlY4kNjYWAGBnZ9dueYaEhMDe3h6XLl2Cn58fjhw5whYWY0gcw4YNw507d/DFF19g+fLlGDduHHJzc8UtS6RUV1e3Zf5ii+HxeNiyZQvMzMzg4eEBIsKRI0eQm5uLI0eOwMPDQ+IXgWMwGG830tLSGDRoEDZu3IgnT57g7t27cHNzw88//4xevXph1qxZePjwobhlcuzYsQOOjo6oqalBREQEvvvuO6iqqopbFoPRapSVlbF+/XpER0dDTk4O/fv3x9atW0FiXLKyqKgIXl5e+OCDD+Dh4YEHDx5g6tSpb+X6e4yug7m5OXx9fXHixAn4+vrC3t4eISEhzTpXogIoiYmJ0NPTa7dGyunTpzF69GjY29sjNjYW7733Xrvky2CIAzk5OXz//fcICQlBcnIyhg4disTERHHLEhk1NTUdEkApLy/H5s2bYWpqii1btsDT0xMJCQn4999/MWPGDCgqKopcA4PBYIiDQYMGYceOHcjIyMCuXbsQFRUFBwcHeHl54fHjx2LTxefzMX/+fHz++edYv349wsLC0LdvX7HpYTDaGwsLCwQHB+P777/Hl19+iU8++QQ1NTUdriMtLQ0uLi4IDQ3F1atXsXfvXqioqHS4DgZDVHh5eSE2NhZ9+/bF6NGj4ePj88ZzZDtAV7vx9OlTmJubt0te/v7++PDDD/Hpp59i27Zt7bGlUas5duyY0GdZWVmoq6tDS0sLdnZ2Qtt/5eXlISAggPvs5uYGPT09ofOrqqpw9uxZ1NbWAnjZozRu3DhoaWmhqqoKhw8fRkxMDAwNDTFs2DAMGjQIgYGBmDx5cgNtFy9eRFFRkdCxV1frj4yMxKNHj7jPioqKqKio4D5LSUlBV1cXpqamMDY2brLRGxwcjLS0tCavEwDY29vD3t7+tWmAl9vGuri4YO3atZg1axb4fD7Onz+PvXv3YvLkyVi+fPkb85BUBg0ahNDQUEyaNAmjR49GSEhIlx1VJerej3///RefffYZXrx4gRUrVmDlypXQ0NAQaZmipjPXN41x9OhRzJgxA7KyEvW4ahaZmZm4cePGG9NpaWlBW1sbCQkJQsdlZWXxwQcfNHlee1z/zMxMnD59GomJiejevTtGjhwJZ2dnpKeno7a2FjY2Ns3Kp628WqczOhYlJSXMmzcPc+fOxblz57BhwwY4ODhg1apV+Prrrzs0kExEmD9/Pk6dOoVz5841+7csKlpixxMmTGhw7uvsq6CgAKmpqVz65vpTjWlsLzturj/FfLq2IyMjgzVr1qBfv37w9PREdXU1jh8/3mFtlpycHIwePRrKysq4c+cOevbs2SHlNsWr/ktjdJXnJbOzjkVPTw/nz5/H6tWr4e3tDWlpaUyfPr3J9BI1AiU5Obldtv188uQJZsyYgblz52L79u1iDZ4AgI6ODmbOnImlS5ciMTERlZWViIqKwpYtW9C9e3dMmDABT5484dK6u7sjODgY3t7emDJlCqqqqoTyU1BQwPjx4xEYGIi9e/di+PDh0NLSQlFREZycnHDv3j3MmjULAwcOxP79+6GiooLr1683qs3V1RV37tyBt7c3Fi9eDAcHhwZbHdrY2CAuLg6zZs2CgoICpkyZgu7du8Pb2xsrV65EdnY2QkND8e6778LIyAhXr15ttKxhw4ahR48e8Pb2xtdffw0VFRWoqKigW7duePHiBTZu3Ih//vmnWddUVlYW3bt356LkGRkZyMrKwrVr18QSwe9odHR0cOXKFWhoaGDq1Kmorq4Wt6R2R0lJCWVlZSLJm8/nY926dZg4cSL69u2LuLg4bNiwQeKDJ0Dnrm9epaKiAitWrIC/v3+7X4fOQGhoKFasWIGEhAQUFRUhISEB3t7eOHDgAHg8HrKzs3H06FF88cUXGDRoEIyNjTFnzhx4e3tDTU0N7777bpN5t8f1//HHHzFkyBBUVVVhwYIFWL58OWpqajB+/Hi4uro2cFBFyat1enN49bfKaDtSUlJ4//33ERUVhZ07d2LXrl0YMmQIkpOTO0zD1q1bcfz4cZw5c0bswROgZXZcn+bYl4uLS6v8qZaWI6A5NtNcf4r5dO3H2LFjcf78efj5+WHDhg0dUiafz8fUqVMhKyuLoKAgsQdPAHSZ5yWzs86JtLQ0fv31VyxbtgwzZ85ERERE04lFtjKLCOjfvz+tWbOmzfk4OzvT4MGDqbq6uh1UtQ9aWlpkaWnZ4HhQUBDp6+tTt27d6M6dO0LfCRZ4a2pb52PHjtHXX3/NfV62bBlZW1s3WPRpyZIltGLFiia1lZeXk56eHsnKylJBQUGjabZv305Lly4VOqampkZ9+/blPr948YLMzc1JSkqKoqKimixPUVGR7O3tGxzPysqilStXNnnem8jPzycAtHXr1lbnIWkkJCSQiooKbdy4UdxS2p3t27eLZBtjPp9P7777LikrK9M///zT7vl3BjpzfVOfP/74g9thqivy119/0c2bN7nPjx8/JgC0ePFi7lhdXZ3QNTcxMaHu3bu/Me+2Xv/ffvuN5OTkGl20vaKiggYPHkx//fXXG/MRJ1988QXV1taKW0aXJiUlhRwdHUlbW5sePXok8vIePXpEcnJy9Msvv4i8rObSGjtuqX211p9qaTnNtZmW+FPMp2s/9uzZQzIyMhQZGSnysn744QdSUlLqELtuLl3lecnsrHNTW1tLo0ePJhsbm6a2OZasRWTz8vKgo6PTpjwCAgJw584d7Nmzp0MXoHwT8vLyjR4fPXo0/vzzT1RWVmLatGlCUUtlZWU4Ozvj77//xvbt2xvNs35v3f3796GgoNBg2sPatWtfOxVCUVERixcvBp/Px9mzZxtN4+/vj9WrVzcov36+WlpamD59OogIJ06caLK8bt26NXrcwMAAn376aZPnvYmuOAXgTfTp0wdr167Fr7/+itLSUnHLaVfU1NTA4/HaPd81a9bg2rVrCAoKwowZM9o9/85AZ65v6nPgwAGMGDEC169fF+t6C6Kib9++GDZs2GvTSElJYdGiRdxneXn5Ju9ffdpy/X18fLBy5Ups3LgRLi4uDb7v1q0bdu7ciYKCgjfqEBcPHz7Evn37xC2jy2NiYoLbt2/DysoK48ePR0lJiUjL27hxI6ytrbFy5UqRltMSWmrHrbGv1vhTLS2nJTbTEn+K+XTtx+LFizFgwAB89913Ii2ntLQUW7duxdq1a2FtbS3SslpCV3heMjvr/EhLS2P//v1ITExscj0UiQqgvHjxAtra2m3K49SpU3B2doaTk1M7qRI9EyZMwOjRo7m5dfU5e/YsevbsiVWrViEoKOi1+VhbWyM6OhpLly4VmtJhZGSEcePGvfbcRYsWQUFBATt37mzw3ZMnT6CmptasdTYECwBnZGS8MW197t27h7q6OvTu3Zs7lpiYiN9//x0bNmzA5cuXhdJXVlbi6NGjQsNbX60ET548CR8fH/j6+nLHfH194ePjAz8/P+7Y06dP8c0336C2thYXL17Ezz//zA1l4/F4OHjwID7//HPs2rWrUwYpFi9ejNLSUly5ckXcUtoVXV1dlJWVtes1T0pKws6dO7Fjxw4MGTKk3fKVJDpDfQMAt27dgrW1Nb755hsAwO7du5tMm5SUhK+//hp1dXVITEzE5s2bcfDgwQZDTm/fvo2vvvoK+/btw4EDBwC8DP76+PjAx8cHd+/exYsXL7jPPj4+3PDdZ8+ecccyMzMBvN7+X1dvCBg0aFCzppAOHjz4jWlepS3Xf9OmTQDQYL2G+gwcOBCurq7c56qqKly9ehVfffUVdu/ejadPnwqlb8s9Ahqv05tKHxISgkmTJqGsrAwnTpwQ+h2/7p41V6NAy7p163D+/Hluza/z589zv5H6jdq4uDju+IsXL5q8ppKKkpIS/Pz8UFJSgl9//VVk5VRUVOD8+fNYunSp2Kde16eldtwa+2qMN/lTLSmnKZtpqh5r6/pjzKdrPcuXL8fly5cbrE/Ynly5cgUlJSVtaniLAkl/XjI7kxw76927NyZNmtT0grIdOyim9dTV1ZGUlBSdPn26Tfk4OjrSunXr2klV+6Gvr9/okHoBX3/9NQGgOXPmcMecnJyIiCg8PJwUFRVJS0uLkpKSuO9PnTpFW7Zs4T4nJiaStrY2ASALCwu6fPlyizTOmjWLANCNGzeEjq9YsYKuXLnSIL22tjbZ2toKHXNwcCAArx36rampKTQMraamhiZNmiQ05Wrp0qXk6upK+fn5dPXqVZKSkuL+18ePH9OUKVMIAP3000/cOcXFxULD0Hg8Hrm4uJCamhqXJisri+zs7EhfX5+IiA4fPkz6+voEgP7++29ydHQkABQSEkIJCQk0efJkCggIoOjoaLK1taXevXtTYWHhmy5lh9OvXz/68ssvxS2jXQkPDycAlJiY2G55/v7776Srq9vUkL0ugyTUNx4eHhQREUFERNbW1qSqqko8Hq9Bur///pv09PQIAPn7+9P7779PEydOJAD0zTffcOnWrFlDx48fp7KyMvLx8SEVFRUiejklQFtbm3R1dam0tJSIXk5lkpWVJRcXF86ea2tr6bPPPqOVK1dSTU3Na+3/dfXG62hsSPKrWFhYNGvqWmuvf2JiIgEgWVlZqqqqatY5FRUVNHLkSDpx4gQVFhbSzp07SVVVlc6cOUNEbb9HTdXpTaUPDg6mjz76iADQxYsXKSAggIjotfesuRpTU1PJ1dWVDh48SM+ePaPRo0eTmZkZVVRU0OPHj8nAwKBBvSQYDrxr164GQ8S7EqtXryYHBweR5R8ZGUkAKD4+XmRltAevs+PW2BdRy/2plpbTmM28rh571Z96Hcyna18yMzMJAAUHB4usjC+//JL69esnsvzbA0l8XjI7kxw7I3q5VIDgf3oFH4kJoFRWVnKOTVvo3bs3/fjjj+2kqv14U4PmyJEjBIDc3Ny4Y4IGDRHRP//8QwCob9++XCPj1QYNEdGDBw/I3t6eABAAGj9+PCUkJDRLo8B5mTJlCnesvLycBgwY0KhTqK2tTcbGxnT//n26ffs2ffDBB9waCq9zIjU1NUlZWZmGDx9Ow4cP5yq1+pWAuro6bdq0iftsY2NDQ4YM4T4LHjCvqwSIiD777DOhSoCIaN68eUIG89VXX3GVABHRkydPqK6ujtzc3OjcuXNcusuXLzdwtjsLw4cPp08//VTcMtoVwT2uPye2raxfv54cHR3bLb/OSmevb9LT02nkyJHc5507dxIA2r17d6Pp16xZQwDo/Pnz3LFRo0aRhYUFERFVV1dT9+7dhRpey5cv597/9NNPJC3uxGvCAAAgAElEQVQtTVlZWdwxDw8PMjY2FpqnPG3aNCovLycieqP9N1VvvI72dAiJWnf9AwMDCQBZWVk1qwwiog8//JBmz54tdMzDw4MUFRXp2bNnRNT2e/Rqnf6m9Bs2bCAAQtf8TffsTRoFeSxYsID7fPHiRZKSkqKzZ88SEdHx48cJABe0EWgdMGBAlw/M7ty5k/T09ESW/3///UcAKCcnR2RltAevs+PW2BdRy/2p1pTTmM00VY+1tGHHfLr2o6ysjGuAi4rPPvuMhg8fLrL82wNJfV4yO5MMOyN62fmjqKjY2FeSswaKYC5+c+ayvQ4DA4M3bvfUGRHsNtLUGjAzZszAunXrEBcXh48//hhE1Gg6Ozs7RERE4Pfff4empiYuX76Mfv36NWsld0dHR7i6usLf3x8pKSkAXg7l8vT0bHKYmYyMDNLS0nD//n24u7sjOjoahw4deuOwtN69e+PmzZu4efMmMjMz4eXlJfT9pUuXsHjxYgAvh6gRkdDWyc3dqaGx4YCvHhNszyhYD8PS0hI5OTkIDAxEaGgo1q9fj/Xr1+PSpUsYMGAAysvLm1V2R5KWlgZDQ0Nxy2hXDAwMoKio2K67P9jY2ODJkyfIz89vtzwlEXHXN3v37sWSJUu4z7NmzYKKigr27NnTaHplZWUAwkNobW1tuaHtcnJyUFVVxZgxY7ghq1999RWXdubMmZCWlhbaIlFTUxNpaWkIDAwE8NKGBL+57OzsN9p/Y/WGqLfdfpXWXP+WzncuLy/H6dOn4ejoKHR88eLFqKiowKFDhwC0/R69Wqe/Kf2rNOeevUljUlISAgMDMWXKFO77iRMnIicnB1OnTgUATJ8+Hebm5vjll1+4NOfOncOUKVMgIyPTpL6uwK1bt9C3b1+R5d+jRw8AQHp6usjKEDVtWU+gJf5Ue61b0F71GPPp2g/BttYCexAFktpWagsd8bxsCmZnnc/OgJe21lTbSeJWhmnKUW8uo0aNwuHDh1FbWytRzkx8fDwAvHYP8c2bNyM2Nhb+/v743//+1+Se37Kysli2bBk++ugjfP755zhy5AimT5+O1NRUqKurv1bH8uXLERwcjF27duHXX3/FoUOHcObMmSbTKykpYdq0ac34D5tGXl4eS5YsETJOFxcXnDt3DmfPnsXYsWNhYmLCrUsANG+eZHNprBJLTEwE8HLB0bauyyNqYmJikJaWhpEjR4pbSrsiJSUFMzMzJCUltVue77//PtasWYPVq1dzDb+3EXHWN5WVlTh27BgePXqEkydPcse7d++OuLg4/Pfffw1+y43Zu7KyMvh8Pvd5165d8Pb2xoQJE7jFcAUBIn19fYwfPx6HDx/G6tWrkZubCwAwNjbGwYMHMXbsWBw+fBizZ88G0Dz77+hgSVO09Pr36dMHwMv/saKignOCmiI0NBQ1NTUNHElBPoKtG9t6jxo7/3XpX6U59+xNGgULGb/qZOrq6nLvZWRksHbtWsyfPx/37t3DoEGD8Oeff+Lw4cONltlVuHHjBs6cOdNg3aT2xNzcHL169YKfnx8GDhwosnJESUvtqz4t8afaUk59RFGPMZ+ubfj5+UFbW7vJZ257MGrUKHz11VeIjo6Gg4ODyMrpbIj6edkUzM46J+fPn8c777zT6HcSMwJFSUkJAIQiZa3hk08+QXZ2tkQ5M9XV1bh48SJkZWW5Xq7GkJaWxvHjx2FtbY1NmzY1cGR++uknoc/du3fH4cOHMWPGDBQVFSEkJOSNWqZMmQJjY2P8+eefCA4ORq9evTrECEaMGCEU8FqzZg3++usvHDx4EB9//DEUFBRErqE+gpFQkZGRDb4T9S4ELeX777+Hvb19qxbW6uxYWFhwDbT2QElJCQcOHMDRo0exfv36NgdsJRFx1zc+Pj5YuHAh/Pz84Ovry73OnTsH4PWLyb6OiRMnIikpCStWrEBERAQGDBggtLPPnDlzEBcXh/DwcOzatQvLli3D3Llz4e/vj5ycHMTExHCLj3dm+xc4KK29/oaGhujbty9qa2sRGxv72rKICLW1tQBeBlLqI3guWFhYNFv7m+5RW9K3xz0TOMcBAQENvsvLy+Pez5w5E4aGhti8eTPi4+OhoaEBfX39ZpUhiYSFheH999+Hh4fHa+uMtiIlJYUFCxZg9+7dQtdbkmipfXX2cloL8+laR1FREbZv34558+aJtBN4yJAhcHBwEPluP+Kmo5+XHQ2zs9bj5+eH6OhoLFiwoNHvJSaAIisrCzk5uTYHUMzMzLB48WKsWrVKYoanbd26lXMSX9cjDLxcld3f3x+ampoNGjTBwcHIyclpcM77778PoHlDt2RkZPDZZ5+huLgYXl5e3FCwxiCiVlcYrzsvIiICW7duxaeffiq0bVdrylJTUxPaqlWQj6BR0BSWlpaQkZHBt99+K7Rid15eHo4fP95iHaLCx8cH586dw9atWzvVrgXthb29PaKjo9s1z0mTJuGPP/7Atm3bMHXq1LduOo+465v9+/c3+sBydHTEkCFD4Ofn1+JdvMrKynDw4EFoaWnht99+w3///YfS0lKh1dUnTpwIXV1d7NmzBykpKbC1tcXs2bNRW1uLOXPmCPVCiMr+BXXYm+qypr6vq6vDwYMHAbStvt+wYQOAl85W/f+vPnl5eTh06BAcHR2hoKDQwMEUNHDftJOIgObco9akF9Tl7XHPbGxsIC0tjQsXLgg9I54+fYrw8HDus7y8PFatWoULFy5gxYoVQttqdiWICHv37sWoUaPg6uqKI0eOiHzk1fLly6GpqYk5c+agrq5OpGW1ljfZcUvsq36eLfVxWlMOgDf6P62B+XRth4iwYMECyMnJYc2aNSItS0pKCr/88gsuXLiAv//+W6RltRZJfF7Wh9lZ57QzAMjJycHixYvx8ccfo3///o2mkagWlbq6OoqLi9ucz5YtW2BkZITx48d3isZRTU1No70pVVVVWLlyJTZs2ID169dzW2UJyMzMbHTOmLm5OU6dOtUgOl1XV4eZM2c22C7q+PHjsLe3b/a2rfPmzYOysjJ0dHQa3fMceNmLXVhYCB6P16w862ssKyt77fZsgtFIfn5+4PP5CAoKQkxMDAoLC5GYmIiUlBTufxSs5QCg0WPGxsaoqqpCYGAgiAgnT55EaGgoiouLUVxcjNraWm7brfrbT2pqamLRokW4c+cORowYgX/++Qd///03PvroI26+n7i5desW5s6di2XLlsHd3V3cckRC//79kZSU1O7b+X3yySe4fv06IiIiYGVlhT///FMkDztx0JnrG39/f6irqzc5DWPKlCng8/nYsmWL0PGCggIAwiMU+Xw+ampqUFVVhbq6Onz77beorKwEADg7O6NPnz5C5cjJyeHjjz/GoUOHMGfOHABAz549MW7cONy4cQMfffQRl7Y59t9YvfEmBA7c67b0y87ORn5+fgPnpaqqCsuWLYOJiQmAttX306ZNw6ZNm3Dz5k3Mnz9fqM4EXq5BsWXLFnh7e0NXVxdLly5FSkoKbty4waXx8/ODp6cnRowYAaDt9+jV+vtN6QV/IyIiEBwcDEVFxTfeszdp7NGjB2bOnIkHDx7A09MT169fx+7du/HNN9802Opy/vz56N69O1JSUjBq1Kgmr7WkEh0dDVdXVyxbtgxr166Fn59fh/Rmqqqq4p9//kFgYCCWLl3aKUcJvsmOW2JfQOv9qZaW86rNVFZWNlmPNeZPNQbz6dqP1atXw8/PD0ePHoWmpqbIyxs9ejTWrFmDhQsXNjrqTtxI4vMSYHbW2e2ssLAQ48aNg5qaGnbt2tV0wvZbq1b02NnZtdsqvZmZmWRmZkZWVlaUkpLSLnm2lmnTpnHbYDk6OtLUqVNp2rRpNGnSJFq0aBG3laeAyMhImjdvHgEgT09PCgwMbDTf7du3C+2K8dFHH9G0adPI0dGRZs+eTV9++SX17duXRo4c2eJrsHjxYtqzZ0+j3928eZPef/99biXrxYsX0717996Y53///UdeXl4EgKSkpOiLL75o8jxvb2+SlpYmPT092rdvH23atImkpaVp1apVlJ6eTosXLyYAZGNjQ5cvX6asrCyhY35+fkT0cjVzW1tbAkB6enp0+PBhWrBgAWlqatKqVato//79ZGlpyV3rmJgYTkNZWRnNnDmT+z/V1NSEVpYWJ/7+/qSkpEReXl5deueHjIwMAkDXr18XSf48Ho9WrFhBsrKyZGlpSceOHaOamhqRlNVRdNb6Zvfu3aSjo0O6urq0ZcuWBr/b//77j4YOHcrVD3PnzqXMzEzy8/MjExMTAkDLly+n5ORkOnHiBJmamhIAWr16NSUlJZGioiLZ2dnRjh076LvvvqPZs2cLrU5PRBQbG0v9+/cXOnb27Fn68MMPG+h9nf37+vo2WW80xfHjx2ngwIEEgDQ0NGjTpk3cDjZERHfu3OG2PwRAPXv2pIEDB9KgQYPI3t6eVFVVSUpKijIyMlp1/RvD19eXbG1tSVFRkUaMGEGffvopzZ8/n7777juhLRtra2vp888/Jx0dHVq7di3NmjWLvLy8qKKigoiozfeosTqdx+O99p4mJyeTnp4eaWpq0h9//PHGe9Ycjbm5uVRcXExTp07l8jAxMaH79+83ev3WrFlD27Zta9a1lhRiYmJo2rRpJCUlRUOGDKGoqCix6Dh79izJycmRt7c3VVZWikVDY7zJjuvTHPtqrT/V0nKIGtpMU/VYU/7UqzCfrn2orq6mefPmkYyMDPn4+HRo2XV1dTRr1ixSUFCgY8eOdWjZr0OSn5fMzjqnnRERpaSkkI2NDRkZGVFaWtrrkkrONsZERGPHjqW5c+e2W37Z2dnk5ORE6urqdOTIkXbLtzORl5fHvRdUFHV1dfTgwQO6ceMGpaentyrf3NxcKisraxeNreX58+dCDaCCgoJW5SO4HoL/JyEhgduqtDnk5eVRREREi84RFdXV1fTtt9+SjIwMzZ49W+Ib+83BxMSEvvvuO5GWkZCQQDNnziQZGRnq1asXbd68mXJzc0VapiQiqvqmrdTV1VFZWRnxeDyKiIigkpKSJtO+qrGmpoYyMzObTN+Z7L8+7Xn9S0tLKSwsTOj+NkZ5eTlFRkZygZOW0JJ71Nz01dXVjd6X9rhnmZmZFB0d3SAIV58JEya0+rnUmaipqSFfX18aNWoUAaB+/frRuXPn3rgtt6gJCgoidXV1srW1bRD4lSSaa18dUU5TNtMRMJ+uIXFxcTRw4EBSVlYmf39/sWioq6ujb7/9lmsMd4U67VU6+nnJ7Kxz2RkR0alTp6h79+5kZ2fXnHsvWQGUOXPmkJubW7vmWV5eTmvXriVpaWny9PSk/Pz8ds2fwegoHj58SA4ODqSmpkb79+8Xt5wOY/bs2TRixIgOKSs5OZlWrVpFWlpaJCcnR++++y6dPn26VQ1GBoPRdQkJCaGFCxeKW0abiIyMpBUrVpCenh5JS0vTpEmT6MqVK2IPnNQnJSWFRo0aRbKysrR27drXBrQYDEmhtraW9u/fT0pKSjR48GB6/PixuCXRpUuXqEePHmRkZNTkSFQGQ9LIzc2l999/n6SkpGjBggVUWlranNMkK4Dy008/Uc+ePUWS95UrV6hHjx6kp6dHO3bsEBpuxWB0ZrKzs+mzzz4jeXl5Gj58uNinpHU0R48eJXl5+eZWeu1CeXk5HT16lNzd3UlGRobU1NTIw8OD/v77bzYyhcF4S7l79y65uLjQggULaNiwYVRUVCRuSS2iurqagoKCaOXKldSnTx8CQObm5vTdd99RcnKyuOU1SW1tLW3bto0UFRXJ1taWzp4926mCPAxGS/D39ycHBwdSUFCgH3/8sVNNw37+/Dl5enqSlJQUTZ8+nR49eiRuSQxGqygtLaUff/yRtLS0yMTEhG7cuNGS0yUrgHLp0iUCQC9evBBJ/i9evKAVK1ZQt27dyNjYmA4dOtSpKi4Goz4vXrygdevWkZKSEhkaGtK+ffuotrZW3LI6nNzcXJKRkSFfX1+xlJ+ZmUk7duwgd3d3UlBQIGlpaRoyZAht2rRJbOsDMBiMjufu3bukq6tLY8aMofDwcHHLaRa5ubn0999/k4eHB6mpqXFz3desWUMhISESFYhISEggLy8vkpaWJicnJ7p48aK4JTEYzSYgIIAGDx5MUlJSNGXKFIqLixO3pCbx8/MjW1tbkpGRIW9vb0pMTBS3JAajWZSXl9O2bdtIV1eXVFVV6auvviIej9fSbHykiDrhEuZN8OzZMxgZGeHWrVvN3hqxteVs3LgRhw4dgqmpKT799FPMmjULGhoaIiuTwWguCQkJ2LdvH/766y/Iyclh3bp1WLJkCRQVFcUtTWyMHDkShoaGYt8GraysDFevXsW///6LS5cuITs7Gz169MCIESPg4uICV1dX2NradsktpRkMRucnOzsbISEhuH37NoKDgxEdHQ15eXmMGDECkyZNwsSJE2FqaipumW3iwYMH+N///gd/f384OTlh8eLF+OCDD6CsrCxuaQyGEBUVFTh16hT27t2Lu3fvYsKECfj++++b3Dq1M1FXV4dTp07hu+++w9OnTzFt2jQsWrQII0aMEPl25gxGS3n27Bn++OMPHDhwADweD59++inWrFkDbW3t1mR3QqICKABgaGiIpUuXYt26dSIvKzExEdu2bcOxY8dARPjwww+xZMkSODg4iLxsBqM+tbW1uHDhAvbs2YOgoCAYGxtj0aJFWLJkCVRVVcUtT+zs2LED33zzDXJzc4X2txcnRITIyEgEBATg9u3b3BZv6urqcHFx4QIqAwcO7DSaGQxG1+LJkycICQlBcHAwQkJCkJSUBBkZGfTr1w+urq4YNWoUxowZ0yWDCxEREfjtt9/g6+sLRUVFeHt7Y+HChejbt6+4pTHecuLj47F//34cPnwYpaWlmDp1KlasWPHa7XI7K7W1tThx4gR2796NsLAwWFlZYeHChZg1a1aHbLfMYDRFXV0dAgICsH//fly8eBE6OjqYM2cOli1bBj09vbZkLXkBlBkzZoDH4+HSpUsdViaPx8ORI0ewZ88ePH78GAMGDMD06dPh6ekJY2PjDtPBeLsgIty7dw+nTp3CqVOnkJWVBXd3dyxZsgQTJ05koxjqkZ2dDSMjIxw5cqTT7CX/KnV1dXj48CHXkAkODkZmZibk5eVhZ2cHJycnODg4wNHREfb29l2yQcNgMERDXV0dEhMTERUVhejoaERGRiIqKgr5+flQUlLC4MGD4erqChcXFzg7O79Vgff8/HwcOnQIBw4cQFJSEgYPHgxPT094eHgwH47RYTx79gxnzpyBr68vQkNDYWJiggULFmD27Nltbcx1GmJiYrBv3z4cP34cfD4fEydOhIeHByZOnAgVFRVxy2O8BQjaTqdPn4avry/S09MxatQoLFy4EFOmTIG8vHx7FCN5AZS9e/di3bp1ePHiBWRlZTu0bCLCf//9h2PHjsHPzw+FhYUYPHgwvLy84OnpiZ49e3aoHkbXJDw8HKdOncLp06eRmpqKPn36wMvLC5988gnMzc3FLa/T8t5776G8vByBgYHiltJsUlNTcfv2bURERCA6OhrR0dEoKiqCjIwM+vTpA0dHRzg4OHDBlVYONWQwGF2IqqoqxMbGcsGSqKgoPHjwAKWlpZCVlYWNjQ0XjHV2doaTkxPk5OTELVvsEBGCgoLg4+OD8+fPo7CwEAMHDoSHhwc8PDwkfuoSo/ORlpbGBU3u3LkDdXV1vPvuu5gxYwbc3d27bEdYSUkJTp48iVOnTuHGjRuQk5PD+PHj4eHhgUmTJr1VAVyG6Kmrq8OdO3fg6+uLM2fOID09HRYWFvDw8MDMmTNhaWnZ3kVKXgDl6dOnMDc3x7Vr1/DOO++ITUdtbS3CwsJw+vRp+Pj4IC8vD2ZmZpg0aRImT54MV1dXKCgoiE0fQ3IoKCjAtWvXEBQUhCtXriA9PR3GxsZ477334OnpCRcXFzaftBlcuHAB7733HhISEiQ60JSVlYWIiAhERETg0aNHiIuLw6NHjwAAmpqaMDMzg42NDfr27cu9t7KygoyMjJiVMxiM9qSoqAhPnz5FcnIyVw/ExcUhPj4etbW1kJeXh7m5Ofr37y/0epvXw2ou9X24kydPIjc3F2ZmZhgzZgzGjBkDd3d3qKuri1smQ8KoqKhASEgIgoKCEBQUhMjISKirq2Py5Mnw9PSEu7v7W9c2KCwsxIULF3D69GlcvXoVdXV16NevH2drI0aMYAFeRovJzc3FrVu3EBQUhEuXLiEzMxOmpqacrQ0bNkyUxUteAAUAHBwc4OLigt27d4tbCoCXvUHXr1/HlStXEBAQgPj4eCgrK2PUqFFwd3fHiBEj2MKRDI7y8nKEh4fj2rVrCAgIQHh4OKSkpDBkyBCMHTsW48ePl4gFxDobfD4fFhYWGD9+fKepG9qL58+fIyYmBk+ePMHjx48RHx+Px48fIzs7GwDQrVs3WFpawtLSElZWVrCysoKpqSlMTU27zNBgBqMrUl5ejpSUFKSkpCAhIQHx8fGcnefl5QEAlJWVOfu2sbGBpaUl7Ozs0KdPHxY4bQf4fD5u3ryJq1evIjAwENHR0ZCVlcXQoUPh5uaGESNGsMAUo1GqqqoQERGBW7du4erVqwgNDUV1dTXs7Ozg7u4Od3d3jBw5kgUI/o+CggJcuXKFs7WsrCx0794d77zzDtzc3DBs2DBYWVmxTkNGA/Lz8xEWFobr16/j6tWrePToEbp16wZXV1e4u7tj/PjxHbm+lWQGUL7//nvs27cPGRkZnTIokZaWhoCAAAQEBODatWsoLi6GmpoanJ2dMXToUAwdOhRDhgxh8wHfErKyshASEoLQ0FCEhoYiKioKNTU1MDExgbu7O8aOHYvRo0ez3q52YPfu3Vi1ahVSUlKgr68vbjkip7i4mGtsPXnyBPHx8Xj06BFSUlJQU1MDAFBSUuKCKWZmZtx7wYsNpWUwRAefz0d6ejoXJHn1lZuby6XV19eHtbU1LC0tYW1tDSsrK1haWsLIyIg1KDqQ58+fIygoSKiRJycnBycnJzg7O3O+HJu2/faRlZWFsLAwhIaGIiwsDJGRkaiqqoK+vj43csnNze2t8D/ag9jYWM7Obt26hfLycmhqasLZ2RlDhgzB0KFDMWjQIOanvGXU1dUhLi6Os7OwsDAkJCRASkoKdnZ2cHNzg7u7O1xdXcUV2JbMAMqTJ09gY2ODf//9F+PGjRO3nNdSW1uLuLg4bheOkJAQpKamQkZGRmjhSAcHB/Tr1w9qamrilsxoA5mZmdxaFtHR0bh//z7S0tIgKysLe3t7LoDm4uICIyMjccvtcpSXl8PExATz5s3DDz/8IG45YoPP5yMjI6PJRptg5AoAaGtrw8TEBD169ICRkREMDAzQs2dP9OzZEwYGBjAyMmIL2jIYjVBTU4Pc3Fykp6cjKysLmZmZyMjIQHZ2NtLT0/Hs2TNkZGSAz+cDAFRUVISCl68GNJmddU6Sk5M5Jz40NBQPHz4En89Hz549MWDAAPTr1497mZqasmBXFyElJQUxMTF48OABYmJiEB4ejvT0dMjIyMDW1hZDhw7lGvp9+vQRt1yJp6amBtHR0UK2Vv96C9pJ/fr1g4ODA7S0tMQtmdEOVFdX49GjR4iJieFe4eHh4PF4UFFRwaBBg7iBB87Ozp3lvktmAAUARowYAS0tLZw7d07cUlpMVlYWQkNDcefOHW4BuIKCAkhJScHMzIxbOFLQA2Vubt5eqwYz2oni4mLEx8cjPj5eaDE/wZBrU1NTbhG/oUOHYvDgwWzEUQfxyy+/4Ntvv0ViYiJ69OghbjmdksrKSqGASmpqKtfoEzQEKysrufRqamoNgip6enowMDCAjo4OdHR0oKenx7YsZHQJKioqkJeXh5ycHOTl5SEvLw9ZWVkNbCQ3Nxd1dXUAAGlpaejp6cHQ0JALRvbs2VMoQMIWge4alJWV4f79+wgLC0NUVBRiYmKQlJSEuro6qKmpcY08Ozs7WFhYwNLSEgYGBuKWzWiCnJwcxMfHIyEhAQ8fPuSCJkVFRZCWloaZmRnX0ens7IyBAweyEREdhGDEz927dxEdHY2YmBg8f/4cANCrVy/O1vr27QsLCwtYWFiwe9NJ4fP5SElJQWJiIh4/fswFJh89eoSamhp069aNC5Q5OTlh6NChsLW17azTVCU3gOLj44OZM2ciNTUVhoaG4pbTZtLT04VGLkRHRyMtLQ11dXWQkZGBiYkJt76BpaUlLCwsYGpqCkNDww7fjehtoaKiAqmpqUhOTsaTJ0+E5qcLhl0rKCjAysqKe7gKXhoaGmJW//ZSXV0Na2trvPPOOzh48KC45Ugs+fn5yMrKwrNnz7gGo+B9RkYGcnJykJ+fL3SOvLw8F1AxMDCAtrY2dHR0oK+vD11dXe47TU1NaGlpdZaeBEYXp6ysDAUFBSgsLERBQQFycnLw/Plz5Ofnc+/z8vLw/Plz5OTkoLS0VOh8JSUl6Ovrw9DQEL169YKBgQF69erFBUt69eoFfX19ts7BW0xZWRnX+BY09OLi4sDj8QAAqqqqXANPEFQxNzfngtEM0fL8+XOkp6cjKSmJ8+USEhKQkJAgdI8EO1jVD4KxBnnnIjs7mxupEB0djQcPHiAxMZGbtmxgYMC1k/r06QNLS0uYmZnB2NiYdWSKGD6fj8zMTKSmpnL2JbC35ORk7h716NEDdnZ2QrZmYWEhSe1ZyQ2gVFVVwdjYGDNnzsTPP/8sbjkiobKyUqiSf/z4MfdDFFT4srKyMDQ0hJGREUxMTGBiYgIjIyMYGxvD0NAQenp66N69u5j/k84Hn8/nehgFUx3S09ORlpbGvQRRbuClsQsq5PqBLGNj484aHX2rOXbsGD755BPcu3cPTk5O4pbTZRHYkcCW6jdEc3Nzue+ys7ORl5eHioqKBnkIAsWpTQEAACAASURBVCmCoEr94Mqr79XU1KCqqgoNDQ2oqKiwkXlvEYWFhSgtLUVpaSl4PB4XDBH8bep9YWEhqqqqhPKSkZHhgnm6urrQ09MTCvzVH1Wlq6vLptYwWk390Q1NNSa6desGY2NjGBkZcS+BL6evrw99fX3WKfMaeDwesrOzkZOTw/lv6enp3CstLY179sjJycHU1JTz5eo3stmIVclFMLrh1eBYQkICMjMzuXRaWloNbEwwWtDQ0BA6OjpssegmqKur43y8Z8+eNbCxtLQ0ZGVloba2FkDjQWOBvXWB5SokN4ACAFu3bsWGDRuQkpICHR0dccvpUHJycpCamirU4E9LS0NqaipSU1NRVlbGpZWXl4euri4MDAw4h7BHjx7Q1dXlGiYaGhpCf7t16ybG/67llJSUoKioCIWFhSgsLOTeFxQUIDMzk2vgCRpyz58/R/2fvo6ODoyNjYVepqamMDY2homJSVcw9rcKIsKYMWPw4sUL3L9/n/UMdxJKS0uRn5/PNXJfbeg2dax+fVYfeXl5qKqqQl1dHWpqalBRUYGKigpUVVWhqanJfVZRUYG6ujq6desGRUVFKCsrQ15eHmpqapCRkYGmpiZkZGSgpqYGeXl51mBuJXw+HyUlJaiqqkJ5eTnKy8tRVVWFkpIS8Pl8FBYWora2FjweD5WVlSgpKeHqbkFwpKSkBMXFxeDxeELHGkNOTq7RgNvrgnGamprQ0dFh61QwxIpgcWFB4yM1NVWoQZKeni40jVJBQYHz43R1dTk/TkdHB1paWtDQ0BDy4zQ0NCSyHisvL+d8OMFL4Nc9f/4c2dnZeP78OZ4/f46srCzk5eU1uE71A1ECf07w3sjIiPkDbxmlpaVc2+hVGxNMXxZMxQReNvwFtlV/qrKuri40NTWFbExgc5L4m6pvX/Xt7cWLF1xbKTc3V6jdVP86aWhoNGljJiYmXX0hZckOoJSVlcHMzAzz5s3D5s2bxS2nUyEYmpydnY3c3FzuYSPoGRY8hAoLC1FdXd3gfEVFRa5iUFRUhLq6OmRlZaGurs41MASNEHV1dW43JBUVlQYViaKiYoOAjMChro/A2QbAOeBlZWWorq5GUVER+Hw+eDwe952gF1Lw3asoKytDU1OTCxYJKkJdXV2uV0dXVxe9evWCkpJSm643o/Px5MkTODg4YPPmzfjiiy/ELYfRBqqqqlBYWIiSkhLweDwUFxejpKSEa2AXFRVxjXFBg1vQKBccKy4u5uqO5iCot1RVVSErKwsNDQ1ISUlBSkpKqDdYcByAUF0oCM4A4PKojyBg8zpeLasx6tebTdHU/83j8bjeovp1cmlpKdc7LqiDXy1LkKa4uBi1tbUoKip6rQYBsrKyUFVVhaKiIhfs0tDQgKqqqlCwSzDaSHBMEBBTVVXlAmRsaD2jKyMY1ScIFLz6vr4f11gdIAgwCuxLSUkJCgoKQoFjgT0KgstA03VT/foNeNlR0Zjd169LKioqUFlZydUX9X256upqlJWVobS0lPPlGvNH5eXloaWlxU0HFXQECvw5HR0dzs/T19dnwVFGi6iurkZ2djZnT7m5udz6Vzk5OUJrYRUUFKCxZrOysjIXUOnWrRs0NDQgIyMj1GZ61acAGm8fCWzyVY2vdiS9an88Hg98Ph9FRUWoqalBaWkpKisrUVFRgdLSUq4tJQhINobgWSuwJ4FtCQJIApszNDR82zuWJTuAAgA///wzNm7ciISEBLZIVyspKytrdPSG4G9FRQV4PB7nLDcW3BD8jOq/F9BYsKSxSqN+z6/gveCBr66uDjk5OaipqXEPejU1tUZHzwjes+H9jE2bNuGHH37A/fv3O3J/eEYnRxAIEAQQCgsLG4yeENRv9dMA4EZQAC+HtBYXFwNo6MzUd1AaqxfbEvioT2PO1qs0FYipH/AWBMQBcPUuIFxX129kva4xpqCgACUlpUbTMBiM9qeioqLR3mTBsZKSEi6YUVJSwgUzBA0twXeAcL1DRODz+ZCWlubqvfrUDxQLqF9nCOoCQV2joaEBWVlZqKmpcd8Jgqiv9uoL3rMOLkZnori4uIF91f9cWVmJ4uJi8Pl8FBcXc8EPwTO/uLiYG8lRv30k6MyoqalpMN25OUFNQWCm/rO4ftCmfkC1sVE0AttkNAvJD6BUVlbC2toao0aNwl9//SVuOYzX4OTkhHHjxr3V28syOhY+n48RI0aguLgY9+/fZ3NbGRLNDz/8gEOHDiExMVHcUhgMxltAcHAwhg8fjvT0dPTq1UvcchiMLsvy5ctx7949hIWFiVsK482ckH5zms5Nt27d8MMPP+Dw4cMIDw8XtxwGg9GJkJWVxYkTJ5CVlYV169aJWw6DwWAwGBJDbGws1NXV0bNnT3FLYTC6NLGxsbC1tRW3DEYzkfgACgB88MEHGDx4MFauXNno3DQGg/H20qtXL+zfvx87d+7EhQsXxC2HwWAwGAyJIC4uDra2tmxdEQZDxMTGxrKp5hJElwigSElJYd++fbh79y7++OMPccthMBidDE9PT3h7e2Pu3LlIT08XtxwGg8FgMDo9rFecwRA9+fn5eP78ObM1CaJLBFAAwN7eHkuXLsXq1auRnZ0tbjkMBqOTsWfPHujr6+O9995r9k4sDAaDwWC8rTx69Ij1ijMYIubhw4cAwAIoEkSXCaAAwIYNG6Curo6lS5eKWwqDwehkKCsrw9/fHxkZGViwYIG45TAYDAaD0WkRbN/KAigMhmiJjY2FlpYW9PX1xS2F0Uy6VABFRUUFR44cgZ+fH9uRh8FgNMDExAT//PMPTpw4gd9//13cchgMBoPB6JTExsYCYL3iDIaoiYuLg52dnbhlMFpAlwqgAMCIESPw+eefY9myZYiPjxe3HAaD0clwc3PDxo0bsWrVKgQEBIhbDoPBYDAYnY7Y2Fhoa2tDV1dX3FIYjC4NW2tI8uhyARQA2Lx5M/r27YuPPvoI1dXV4pbDYDA6GevWrcMHH3wAT09PREdHi1sOg8FgMBidiri4ONjb24tbBoPR5YmLi2NT5SSMLhlAkZOTw/Hjx5GQkIBvv/1W3HIYDEYnQ0pKCn/99ReGDBmCCRMmIC0tTdySGAwGg8HoNLBecQZD9Dx79gxFRUXM1iSMLhlAAQBzc3P8+uuv+Pnnn3H9+nVxy2EwGJ0MOTk5+Pr6Qk9PDxMmTEBhYaG4JTEYDAaDIXaIiO3Aw2B0AIK1hpitSRZdNoACAPPnz8eUKVPg7e2NzMxMccthMBidDDU1NVy4cAE8Hg+TJ09GWVmZuCUxGAwGgyFW0tPTwePxWK84gyFiYmNjYWhoCC0tLXFLYbSALh1AAYBDhw5BS0uLNY4YDEaj9OzZE9euXcPTp08xbtw4Vk8wGAwG461G0CtuY2MjZiUMRtcmLi6OBSolkC4fQFFTU4O/vz8yMjIwc+ZM1NXViVsSg8HoZFhYWODq1at4/Pgxpk6disrKSnFLYjAYDAZDLMTGxqJXr17Q0NAQtxQGo0vD1hqSTLp8AAUATE1NcebMGVy8eBEbNmwQtxwGg9EJsbOzw5UrV3Dv3j188MEHqKmpEbckxv9j777DmjrbP4B/AwlD9lCGCiLKRkUREVRUBHH1dWFFcdXWam1dtVprh1ZbsbRWa9W2to63ta6KWwRcqIiKWwFlCgpiQdmbcP/+8JfzEgh7nADP57pyAScn5E7guXPO/YzDMAzDtDjWK84wza+8vByPHz9m65+0Qu2igAIAgwcPxi+//IJ169Zh3759fIfDMIwccnR0xJkzZ3DhwgVMnDiRjURhGIZh2h3WK84wzS8hIQH5+fmsrbVC7aaAAgBz5szBkiVL8O677+L69et8h8MwjBxycXHBhQsXEB4eDi8vL+Tk5PAdEsMwDMO0CLFYzHrFGaYFPHr0CAoKCrC2tuY7FKae2lUBBQD8/f3h4eGBMWPG4MGDB3yHwzCMHHJ0dMTly5cRGxsLd3d3vHr1iu+QGIZhGKbZxcXFobCwkPWKM0wze/ToEbp16wZ1dXW+Q2Hqqd0VUBQVFXH48GE4OTlhxIgRiIqK4jskhmHkkI2NDS5evIh///0Xw4cPZ5dCZxiGYdo8Sa+4lZUV36EwTJvG1hpqvdpdAQUAlJWVceTIEVhbW8PT0xMJCQl8h8QwjByysLDAlStXUFZWBmdnZzZqjWEYhmnTIiMj0b17d6ipqfEdCsO0aWytodarXRZQAKBDhw44efIkjIyMMGzYMCQlJfEdEsMwcsjExARhYWHo2bMnXF1dcebMGb5DYhiGYZhmwXrFGab5lZaWIiYmhq011Eq12wIKAGhqaiIkJAR6enrw8PDAixcv+A6JYRg5pK2tjbNnz2LChAkYP348/vjjD75DYhiGYZgmx3rFGab5PXnyBCUlJayttVLtuoAC/O/ESCgUYvjw4UhOTuY7JIZh5JCSkhL27t2LTz/9FO+99x4WLVqEsrIyvsNiGIZhmCZRUlKC2NhY1ivOMM3s0aNHEAqFsLS05DsUpgHafQEFADp16oQLFy5ARUUFzs7OePjwId8hMQwjhwQCAb7++mscO3YMe/fuxbBhw5CWlsZ3WAzDMAzTaI8fP0ZpaSnrFWeYZhYZGQkLCwsoKyvzHQrTAKyA8v8MDQ1x8eJFmJubY+jQoQgPD+c7JIZh5NRbb72FGzduICMjA46Ojrh58ybfITEMwzBMozx69AgikQgWFhZ8h8IwbRqbKte6sQJKBdra2ggKCoKzszM8PDwQHBzMd0gMw8gpKysrhIWFwdbWFm5ubti+fTvfITEMwzBMg0VGRsLS0hJKSkp8h8IwbdqjR4/YVLlWjBVQKunQoQOOHz8Ob29vjBs3DocOHeI7JIZh5JSuri7OnDmDlStXYtGiRZg8eTKysrL4DothGIZh6o31ijNM8yssLERiYiJra60YK6DIIBQKsWvXLixcuBBTp07FmjVr+A6JYRg5paioiDVr1uD8+fO4fv06evfujbCwML7DYhiGYZh6Yb3iDNP8oqKiIBaLWVtrxVgBpRoCgQCbNm3CL7/8gm+++QbTpk1DYWEh32ExDCOn3NzccPfuXdja2mLYsGFYt24du0oPwzAM0yoUFBTg6dOn7KSOYZrZo0ePoKKigh49evAdCtNArIBSi3nz5uHUqVMIDAyEu7s7u+IGwzDV6tixI06fPo3vvvsOGzZsgKurKx4/fsx3WAzDMAxTo8jISJSXl7NpBQzTzCIjI2FtbQ1FRUW+Q2EaiBVQ6mDkyJG4efMmMjMz4ejoiFu3bvEdEsMwckogEGDJkiV4+PAhRCIRHBwcsHHjRpSXl/MdGsMwDMMgMjISv//+O27cuIHc3FwAb3rFVVVV0b17d56jY5i2IyAgAIcPH0Z0dDQ3KpmtNdT6CYiI+A6itXj9+jXefvtthIeHY/fu3fD29uY7JLn17bff4uDBg1InjYmJiVBTU0OnTp24bUKhEJs2bcKwYcP4CJNhmlVZWRk2bNiAdevWwdnZGb/99husrKz4DotpBSIiIjBv3jypaWCvXr1CVlYWzM3NuW0CgQBvvfUW1q9fz0eYDMO0QhEREXBycuJ+NjY2hrKyMgoLC+Hv7w9bW1vY2NhAWVmZxygZpvVbsWIF/P39Abw55+nRoweSk5MxePBgfPDBB7Czs4OZmRkEAgHPkTL1cIAVUOqprKwMy5Ytw9atW/HRRx/B39+ffcDIcPbsWYwaNarW/VRUVJCRkQE1NbUWiIph+HHv3j28++67ePToEVatWoVVq1axy0QyNSotLYW+vj5ycnJq3ffQoUOsoM8wTJ3l5+dDQ0MDFU8BBAIBhEIhxGIxysvLoaioCFNTU6xbtw7Tpk3jMVqGab327t2Ld955R6pDWUFBAUKhECUlJQAAVVVV2NjY4NixY+jSpQtfoTJ1d4BN4aknoVCIn376CQEBAfjzzz/h4uKCuLg4vsOSOyNGjICurm6N+wiFQowfP54VT5g2r0+fPrhx4wa+/fZb+Pv7w8HBAVevXuU7LEaOiUQi+Pj41FpoU1VVxdixY1soKoZh2gI1NTUYGxtLbSMilJaWcid6YrEYaWlpGDFiBB8hMkybYGtrW2UKd3l5OVc8AYDi4mJ06tSJFU9aEVZAaaAJEybg3r17EIlE6Nu3Lw4cOMB3SHJFKBTCx8cHIpGo2n3EYjGmT5/eglExDH8UFRWxbNkyPHr0CCYmJhgyZAimTJmCZ8+e8R0aI6d8fHykDrIqE4lE8Pb2hqqqagtGxTBMW2Bvb1/jtAGhUIjVq1dLTbtmGKZ+bGxs6jQ9RzLNh2kdWAGlEUxNTREaGoo5c+bAx8cHM2fOREFBQY2PaU+jVXx8fFBaWlrt/erq6vD09GzBiBiGf926dUNgYCCOHz+OiIgIWFtbY82aNSguLuY7NEbODB48GAYGBtXeX1payobWMwzTIL179662k0sgEEBXVxdLlixp4agYpm3p0KFDldFeFYlEIrz//vvs8uGtDCugNJKysjK2bNmCw4cP48SJE3B2dsa9e/dk7nvhwgU4Ojq2m8uauri4VJs06jo8nWHaqnHjxiEyMhLLli3Dxo0b4eDggLNnz/IdFiNHFBQU4OvrW22e1NbWhru7ewtHxTBMW2Brayu1SHVFAoEA/v7+6NChQwtHxTBtT+/evasdhSIUCvHll1+2cERMY7ECShOZPHky7t69Cx0dHQwYMADr16+X+mAqLS3F/PnzkZ2dDS8vL7x69YrHaFuGQCDAjBkzZPZwsJ5ThnnTM/H1118jMjISVlZWGDVqFDw9PastwjLtT3XTeEQiEaZPnw6hUMhDVAzDtHay1mYA3kw3tbKygq+vLw9RMUzbY29vL/NcSCgU4vPPP4ehoSEPUTGNwQooTcjMzAyXLl3C1q1b4efnBxcXF0RHRwMAtmzZgvj4eABAamoqxo0bV+Pc9raiumk8HTt2xKBBg3iIiGHkT/fu3REQEIDw8HAUFhaib9++mDJlChITE/kOjeFZv3790KNHjyrbS0tL4ePjw0NEDMO0BdbW1lBQqHoaIBaLsWXLFpn3MQxTf7JGe7Fpcq0by45NTCAQYN68ebh//z6UlZXRt29ffP7551izZg1X6S8tLUVERATmzZvHc7TNr3fv3rC0tJTapqSkhFmzZkFRUZGnqBhGPjk7O+Py5cvYv38/bt++DRsbGyxevBgpKSl8h8bwyNfXt0rvlZGREVxcXHiKiGGY1k5VVRWdO3eW2iYSiTBq1Ch25R2GaUKyRnuxaXKtGyugNBNzc3NcvHgRq1evhp+fX5UFIsvKyvDf//4Xmzdv5inCllN5Gk9JSQnrOWWYaggEArz99tuIjo6Gv78/AgICYG5ujg8//JBdsaedmj59utRIPpFIhFmzZtVpZX+GYZjqVF6bQSwWs6uBMEwTs7GxkRrRxabJtX6sgNKMhEIhhg4dCrFYLHOhLiLCsmXLcOrUKR6iazk+Pj5Sr9/U1BR9+/blMSKGkX9KSkr48MMPER8fj99++w1nz55Fjx49MHPmTG46INM+9OjRA7169eJOdNj0HYZhmoK9vT23SLVIJMJ7773HrgbCME1MRUVFarQXmybX+rG/XDMSi8WYP39+jYv8SXqbHz582IKRtazu3bvDwcEBAoEASkpKmDNnDt8hMUyroaSkhJkzZyI6Oho7d+5EeHg4rK2tMXPmzHpfFp2ImilKprnNnDmTm/YoKagwDMM0hq2tLTe6TSgUYs2aNfwGxDBtVJ8+fSAQCNg0uTaCFVCa0c8//4zo6OhqLxMHAOXl5SgpKcGoUaPw77//tmB0LWvmzJkA3kzfmTp1Ks/RMEzrIxKJMHPmTERFRWHHjh0ICwuDjY0N5s6di9jY2Dr9js8//xy7du1q5kiZ5jB16lSIxWIAwKxZs3iOhmGYtsDOzg7l5eUQCAT47LPP2NVAGKaZ2NvbA3jTuf7999/zHA3TWKyA0kxevnxZ5+t6l5WV4d9//8WECRPa7JV53n77bQgEAvTq1avKorIMw9SdSCTC3Llz8eTJE/z222+4fPkyrKysMHbsWAQHB1c7ykQsFuO3337D3LlzsXTpUu5knGkdOnfuDFdXVwgEAjZ9h2GYJmFpaQkFBQV07NgRy5Yt4zschmmzbG1tQUR49913YWNjw3c4TCOxAkoz2rJlCxYsWAAHBwdujqlQKOS+r6i0tBQ3btzA+++/39JhtghDQ0MMGzaMG4nCMEzjCIVCzJ49G0+ePEFQUBAEAgG8vLxgaWmJLVu2IC8vT2r/c+fOISMjAwCwdetWeHp6IjMzk4/QmQaaMWMG+vfvD3Nzc75DYRimDVBRUUGPHj2wceNGdjUQhmlGtra20NDQwNdff813KEwTEBCbFN8iSktL8ejRI9y6dQu3bt1CeHg4oqKiIBaLIRQKIRAIuHmo/v7+WL58Oa/x5uXlobS0FOXl5cjOzgYAFBQUSF1NKDc3t8bpSZX3v3TpEuzt7aGnp8dtU1dXr3J5zopUVVWhoqJSZX9FRUVoamoCADp06ABlZeX6v0iGaWOePHmC7du3448//oCioiKmTp2KpUuXwsrKCtOnT8fhw4e5PCMSiWBkZITAwEDWG9IMJPlRLBYjJycHAFBYWIiioiJun/z8/BpHHZaWlkoVwvLz83Ht2jV4eHhw20QiEdTV1WuMRVtbm1uAViAQQFtbG8CbkydVVVUAgKamJru0PMO0IpLcIskrWVlZIKIqeQaomksk1NTUcPDgQfj6+nI5QllZGR06dOByheRnliOY9qq4uBgFBQXIzc1FcXEx95ku6zyo8rmPhLq6Oo4cOSK1jIGkTUk+izU1NaGsrAwNDY3mfUFMYx1gBRQeFRcX4/79+1xRJSwsDPHx8SAiHD9+HGPHjq32sXl5ecjKyuJu+fn5yMnJQX5+PgoLC7nvi4qKkJ2djYKCAu4DtuL3AJCTkwOxWFztB2xroqOjA+B/JwZCoRAaGhpQV1eHqqoq972Kigo0NTWhpqYGFRUVaGlpSX2voaEBbW1t7sYKNExr8urVK/z+++/Yvn07nj9/jtGjRyM4OLjKybpkRNz+/fvx1ltv8RRtyysrK0NWVhays7ORlZWFzMxMqXwpOQHJzMxEUVERCgsLkZWVheLiYi7XFhUVcflSMpJHcpDVmklyJvC/4rSSkhLU1NSkDu4q51FlZWVoa2tzRW8dHR2oqalBS0uLy6Osh5thpBUWFuLFixd48eIFMjIykJmZidevXyMzM1Pqe8nXgoIC7kSupg6s5iLpvFJVVUWHDh2go6MDXV3dar/q6enByMgIxsbGXLGWYfhQUFCA58+f4+XLl8jIyKjStl6/fs3dJOdKxcXFvI3UVVNTg5KSEnR0dNChQweZ7avi90ZGRjAwMECnTp14ibedYQUUPpWXlyMjI0Pq9uzZM0RFRSE5ORmdO3dGTk4OMjMzpYolWVlZ1X5w1uWgVlJckPRKSkZ1KCgoQEtLC4D0qA5JUULSCyFR+efKKh6Iy0JEXBGnOtnZ2SgvL6/yc8Vij2S0TMWeXkniKykpqXLCk5ubi6KiIuTm5lYpMsmqGgPg3q/qbjo6OtDX15e6GRgYcKNkGIYP5eXlOH36ND799FNER0fLXB9Fchm9b7/9FitXrmzpEBslMzMT6enpVfJoxVwpKZJIvkoKzrJIcmDFfCnJc1paWlBWVoa6ujo0NDSgrKzMtW8tLS0oKChI5TzJwQ9QfQ6VFCZqInlsdeo7iqWsrAy5ubkApHvKJAeJkpwJ/K93TVJEys7ORlFREfLz86V64vLz81FcXIysrCyZvd8SIpEI2traUkWVijctLS0ul3bq1Ekqn9Y0UpFh5FFOTg4SExPx9OlTPH36FM+fP0daWhpSU1O5r5WPgdTU1GosSnTo0AEdOnSAhoYGlJSUoKWlJdV7raioKHNUWsWRZxVVPsYC/pdTJCOQJe0/JycHJSUl3KiXgoICqRPPyiejlfOslpYWjI2NYWhoiM6dO8PAwABdunSBqakpunXrBjMzM5kxMkxtsrKykJiYiMTERCQlJXGFEsnXlJQU7nNPQkNDQ2YxQk9PD9ra2lIFDMlndcV2B1QdJQ/IPjeq+LkrUfEcSPK5mZ2djZKSEu78pKSkhCucVi70VPy+YhtWUlJCp06d0KVLF66NGRgYwNTUFGZmZjAzM4OxsTG7hHLjsAJKUystLcXLly/x7NkzvHjxAs+fP0dGRgbS09Px77//VjnYr/z26+npQVdXt8rJeU0n79ra2txBPdM4koSWm5tbpWhV0y0zMxMZGRlVRvAoKSlxJwCdOnWSOikwNDSEsbExunTpAkNDQxgYGPD0qpm2zs3NDWFhYTUuHKugoIDJkydjz549vPUUlpSUcAc9aWlpXP7MyMjg8uerV6+4bZULyerq6tDX1+dyZsUTdVnfS77q6OjUOp2QqZ+srCzk5eXJLGBV/D4zM1NqH0kurXxSp6WlVaWoIilUGxgYoHPnzjA0NESXLl3YZyHTYjIyMhAZGYno6GjEx8fj6dOnXNHk1atX3H6SooGRkRE3IkNyDCC5T19fv02Ndi0pKUFGRgZSU1O5UTYVv3/x4gVSUlLw4sUL7jE6OjpcMcXMzAzm5uawsrKCra0t61lv5yq3NUnBJDExkesAEAgEMDIy4tpaxfZV8WtbK8pnZmYiLS0NaWlpSElJ4b5WPJ5KTk7mOkyUlZWlCipmZmawsrKCjY0NzMzM2FS92rECSn0UFBRw1U3JwX1qaipSUlKQmpqK1NRUvHz5UqooYmBggI4dO3IHepLv9fX10bFjR6kDwo4dO7J/2lauqKiIK5hJhglKbi9fvpQqoKWmpkpVpJWUlLjEb2xsjM6dO3MfApJemq5du0IoFPL4CpnWJiUlBSYmJlVOSGURCoWwtrbG6dOn0bVr1yaNIzMzk+uFlRw0Sz7oJR/wL1++lHqMgYGBJ85QDQAAIABJREFUzHypp6cnM4e2pZOP9oyIpHLnq1evZHZASDomXr58KTUKR01NjStMy/pqamoKY2Nj9nnL1Nnr169x584dREdHIyoqCtHR0YiMjOQW5tbS0kKPHj24k//KX9n0leoVFRVJFZ4qfo2Li+N66fX09GBjYwNra2vY2NjAxsYGffr0QceOHXl+BUxTysrK4tqapGASGRmJ9PR0AP9raxVP/iu2t8ojQpg3iAipqalShaeKt+TkZABvlkCwsrKCtbU17OzsYGVlhd69e7PF66WxAkpFJSUleP78ORISEpCQkMBVyiU/JyYmcsURFRUVGBsbcxVOWV+7detW6/Bspn0rKiriim8Ve2cqfk1KSpIaCqujo4Pu3bvLvJmamrKTAkaKn58fvvjiizrPlxcKhdDR0cGpU6fg5ORU5+eRzOWX5MuKt/j4eKmh6ix/Mk0tMzOzxjz64sULJCcnc+1AJBJBX18fxsbGMnOpiYkJK1a3U9nZ2Xj48CFu377N3SRTILW1tWFubg4bGxvY2tpyX83MzLhFWJmmlZmZicjISERFRXFfJZ8tAGBkZIR+/fpxNycnJzait5XIzc3F/fv3pdra48ePUV5eztpaCysuLkZcXJxUO4uMjOT+HpqamrC3t5dqazY2Nu31b9H+CihEhKSkJDx58gSPHz/G48eP8eTJE8TExCA1NZUrkGhpaaFbt24yexNMTU25+W8M09yICC9fvkRSUpLUfGrJ90lJSdywPCUlJZiamsLS0hJWVlbcVysrK+jr6/P8Shg+WFlZITY2VuZwVVmjUsrKykBEEIlE2L17N6ZPn87dl5ubi5iYGMTExEjlzvj4eG79IQBcAURyk8xxNzU1hYmJCVtMlOGFWCxGWloal0Mlt6SkJDx9+lRqiLNIJIKJiQl69uzJ5VILCwtYWlqic+fOPL8SpinFxMTgypUrCA0NxdWrV5GYmAgA6NKli9TJQt++fWFoaMhztIxEeno67ty5I3XynZSUBAAwMTHB4MGDMXjwYAwZMgTW1tY8R8sAwLNnz3Dp0iWurcXExICIpIpgjo6O6Nu3L4yNjfkOl8GbNZEePHiAW7du4fbt27h16xYeP34MsVgMXV1duLi4wM3NDW5ubnBwcGgvHQ9tt4BSVlaGJ0+e4OHDh1KFkidPnqCwsBAA0LFjR1hbW8PKygoWFhZcgaRbt27Q1dXl+RUwTN1IhuVJiioJCQlSJ7eSdVn09PS4YoqlpSWsra3Rq1cvmJiY8PwKmOaSl5eHbdu2AZC92KjkClwVSa48I1kLqFu3bsjJycGTJ0+QkpIC4M3JpWRuuoWFBczNzaUKJWwqDdMaERFevHghVaiWHDfExMRwo6g0NDS4YorkZmdnB0tLy/Zy8NiqxcXFISQkBJcvX0ZoaChevHiBDh06wNnZGUOGDEH//v3Rr18/NoqhFcrIyMDt27dx8+ZNXLlyBeHh4cjLy4OBgQFXTPHw8ICVlRXfobYLqampCA4OxqVLl3D58mUkJiZCSUkJTk5OGDJkCAYMGIB+/fqxonQrk5+fj3v37uHWrVu4cuUKLl++jPT0dGhoaGDQoEEYMmQI3N3d0a9fv7a6WG3bKKBIekUjIyO5KvTdu3dRUFAAoVAIExMTdO/enRv+1b17d9jZ2bGeBKZdqDj8NSEhgfv+6dOnKC8vh5aWFuzs7NCvXz9umKSjoyObR9oOSArNkqGakvwpWdRPMl2sYu7s3r07bG1t2f8H0+5kZmZK5VDJNILIyEgUFRVBJBKhZ8+eUrl0wIABbPFLnonFYoSHh+PUqVM4d+4cbt++DTU1NQwcOBCurq4YNGgQBg8ezAq/bZBYLMa9e/dw9epVhIWF4fz583j9+jXMzMzg4eGBsWPHwtPTk/3tm1BkZCROnTqFkydP4tq1a1BUVETv3r0xYsQIuLq6ws3NjV2hsg1KSEjAuXPncPXqVYSGhiI5ORn6+voYNmwYxo4di//85z9tafZG6yugFBUV4datW7h27Rpu3ryJe/fuISEhAUQEHR0d9OnTB3369EHv3r3Rp08f2NjYtKmVlhmmqeTk5OD+/fu4f/8+7t27h3v37uHRo0coLi6GkpIS7Ozs0KdPHzg7O8PFxQXW1tZttZLcLpSVleHhw4dc7nzw4AGioqJQUlICZWVl2Nraonfv3ujVqxd69+6N3r17s5F4DFMHJSUliIqKwoMHD3D//n08ePAA9+7d4xYYNTExQa9eveDo6AhnZ2c4Ozu3pQNJuVRYWIiTJ0/i0KFDCAkJQU5ODmxtbTFmzBiMHj0arq6ubLRQOyQWi3H9+nWcPn0aZ86cwf3796GmpgYPDw9MnjwZ48ePZ2tv1ZNYLMbFixexf/9+nD59Gi9fvoSpqSlGjx6NsWPHYtiwYWwR5XbowYMHOH36NE6dOoUbN25AKBRiyJAhmDx5Mry9vaGjo8N3iI0h/wWUtLQ0XLt2DWFhYQgPD8ft27dRUlICIyMjODs7SxVMTE1N+Q6XYVq1srIyREdHc0WVO3fuICIiAnl5edDW1oaLiwvXa+fk5MQONOTYq1evEB4ejuvXr+PatWvc31FLSwtOTk5wcHDgCiZWVlbsZIJhmlhqaipXpL5//z4iIiIQHx8PBQUF2NjYYODAgdzN0tKyvS7G12TKy8tx8eJF/PXXXwgICEBBQQHc3d3x1ltvYfTo0ejWrRvfITJy5tmzZzhz5gxOnDiBkJAQKCsrY8KECZg2bRo8PDzYovw1ePDgAf7880/s378fKSkpcHJywoQJEzB69Gj06tWL7/AYOZKRkYHAwEBuZFJ5eTnGjBkDX19fjB49ujWOAJO/AkpmZibOnTuHoKAgXLp0CfHx8VBUVISdnR1cXV25kzczMzO+Q2WYdqGsrAz379/HtWvXuGLms2fPIBQKuWGZI0eOhKurK5SUlPgOt93KysrC+fPnERwcjNDQUDx58gQCgQCWlpbcKKKBAwfCxsaGjSRiGJ68fPkS4eHhuHbtGtcpVFhYCF1dXbi6usLDwwOenp6wtLTkO9RWIy0tDdu3b8euXbuQkpICR0dH+Pr6YurUqWwdE6bOMjIycPDgQezbtw/h4eEwNDTE7Nmz8eGHH7I1Ov5fYWEh/vvf/2L79u148OABunfvjunTp8PX1xcWFhZ8h8e0Ajk5OQgICMCff/6JS5cuQVtbG76+vli8eDG6d+/Od3h1xX8BRSwW49atWwgKCsLZs2dx8+ZNCAQCDBgwgJsv5+zsDA0NDT7DZBimgmfPniEsLAxXr15FcHAwYmNjoa6ujuHDh8PLywsjR45sTYmwVRKLxbh58yaCg4MRFBSEmzdvAgAcHR3h7u4OFxcXODs7Q09Pj+dIGYapTmlpKe7evYvw8HCEhobiwoULyM7ORrdu3eDp6QlPT0+4u7tDW1ub71Dlzr1797B582YcOHAAmpqaeO+99zBjxgy2QCjTaHFxcfjrr7/w66+/4tWrV/D29sbSpUvh6OjId2i8ePHiBbZt24Zff/0VeXl5mD59OubMmQMXFxc2co5psOfPn2Pfvn3YsWMHnj17hvHjx2Pp0qUYNGgQ36HVhp8Cilgsxvnz5/H333/j1KlTePXqFbp27YqRI0di5MiRGDFiBDtYYJhWJCEhgSuCXrhwAXl5ebCwsMDkyZMxbdo02Nra8h1im1BSUoKzZ8/iwIEDOHv2LDIzM2FiYiJ1osXWLWGY1qusrAw3btxAUFAQQkJCEBERAQBwdnaGt7c3pkyZAiMjI56j5NetW7ewatUqnDt3DnZ2dli8eDF8fX3ZwtZMkyspKcGBAwewefNm3L17F0OGDIGfnx8GDhzId2gtIi0tDV999RX27NkDHR0dLFiwAAsWLGALYzNNqqysDEePHsWmTZtw/fp1ODk5wc/PD8OGDeM7tOq0bAElIiIC+/btw8GDB5GWloYBAwbA29sbXl5e7ASLYdqIkpIShIWF4cyZMzh48CCePXuG3r17Y9q0afDx8UHXrl35DrFVEYvFuHTpEvbv34+AgABkZ2dj0KBBmDhxIkaOHMl6WxmmDcvMzMT58+dx8uRJHDt2DPn5+XBzc4OPjw8mTZrU2hfiq5fk5GSsXr0a+/btg6urK7766iu4u7uzHnCmRVy6dAnr1q3DxYsXMXnyZPj5+bXZkbaFhYXYtGkT/Pz8oKOjg6+++gq+vr6tca0KppUJDw/HunXrEBgYiLfeegvfffedPE5pPQBqZhkZGbRhwwaysLAgAGRpaUlr166l2NjY5n5qhmF4JhaLKTQ0lObNm0e6urqkoKBAbm5u9Pfff1NJSQnf4cm1uLg4+vjjj8nIyIgAUN++fen777+n5ORkvkNjGIYHhYWFdOTIEZo8eTKpqqqSkpISvfXWW3TmzBkSi8V8h9dsSktLae3ataSqqko9evSgf/75h++QmHbs5MmTZG1tTUpKSrRq1SoqLi7mO6QmdfLkSeratStpaGjQ+vXrqaCggO+QmHYoKCiI7O3tSSQS0ccff0xFRUV8h1TR/mYroMTFxdG7775LqqqqpK2tTYsXL6aIiIjmejqGYeRccXExHTt2jCZOnEiKiopkbGxMGzZsoJycHL5DkyuXL1+mMWPGkIKCApmYmNCaNWvo8ePHfIfFMIwcyc7Opr1795K7uzsJBALq0aMHbd26lQoLC/kOrUklJSWRq6srqaqq0g8//NDmTlaZ1qm0tJS2bdtG6urq1L9/f4qLi+M7pEYrLi6mJUuWkEAgoBkzZtCLFy/4Dolp58rKyujXX38lTU1NcnBwoCdPnvAdkkTTF1CeP39Oc+bMIaFQSD179qQdO3ZQXl5eUz8NwzCtWFJSEq1YsYI0NTVJT0+P/Pz85K263OLCwsJo6NChBIDc3NwoICCAysrK+A6LYRg5FxUVRR988AGpqqqSkZERbdmypU2M8Dt27Bjp6OiQnZ0dPXr0iO9wGKaKJ0+eUN++fUlTU5MOHjzIdzgNlpiYSP369SMNDQ3666+/+A6HYaTExcWRo6MjaWho0N9//813OERE+5vsWpZlZWXw9/eHlZUVQkND8fvvvyMqKgrz58+HmppaUz0NwzBtgImJCTZu3IjExETMnz8f69atg52dHYKCgvgOrcWlpaVhxowZGDRoEAQCAUJDQ3Hp0iVMmDABioqKfIfHMIycs7a2xrZt25CQkAAfHx+sXLkSvXv3xvnz5/kOrcF+//13TJo0CZMmTcLNmzfZOnmMXLKwsMC1a9cwc+ZMTJ06FT///DPfIdXb48ePMWjQIJSVleH27duYPn063yExjBRzc3OEhYXhnXfewfTp07F161a+Q0KTLCKbkpKCadOmISIiAqtWrcInn3zSKlZDDwsLQ2JiotQ2oVAILS0t6Orqwt7eHh06dODuS09PlzrB8/DwgIGBgdTji4uLERAQALFYDABQUFCAl5cXdHV1UVxcjL179+L+/fvo3LkzBg0aBCcnJ4SEhGDcuHEyY7xy5QqSkpJqfB29evVCr169an29mZmZcHV1xcqVKzFr1iyUlZXh+PHj2LFjB8aNG4fFixfX+juaW0pKCg4fPozY2Fjo6elh6NChGDhwIJKTkyEWi2FjY9MicVR+r5jm9ezZMyxbtgxHjhzBkiVL4OfnByUlJb7DanZnz57FrFmz0KFDB2zatAkTJkzgO6Q6++uvv6R+lrfcWdmff/4JHx8fCIXChr7kVoXl0vYrMTERS5cuxYkTJ7B06VJs2LChVeXTo0ePYvLkyfj888+xdu1aXmJISUnBxYsXa91PV1cXo0ePrvLYmtre69ev8fTpU25/gUCATp06wczMDKamphCJRDKf69SpU8jKypLaNmrUKKlL1d+5cwdRUVHcz5qamsjJyan3c1U+PhYIBFBWVoampibs7OxgbGxc63vTlOTxeLUyPz8/fPbZZ/jrr78wbdo0vsOpE8kFPbp06YIzZ85AS0urxWOoT1vT19dHTEyM1HahUIipU6dW+7j6Hj+wdibf7Wzjxo1YtWoV3+2s8YvIRkdHU5cuXcjS0pLu3bvX+EExLai8vJzOnj1LAoGAtLW16csvv6Tdu3fTN998Q+PHjycVFRUaNWoURUdHc495+fIlzZs3jwCQs7OzzGkHmZmZNHPmTHJxcaFnz55x22xsbGju3Ll048YNCg4OpmnTppGioiItWbKkxhjPnz9PAMjU1JSOHj1KR48epcOHD9PmzZvJwsKCVq5cWafXm5OTQ4MGDeIWYEtMTKSffvqJAJC/v3993rpm8e2331KXLl3Iz8+P7t27RxkZGXT27Flyc3Ojjh070tGjR1sslsrvVV209ykoTeHw4cOkra1NQ4cOpdzcXL7DaVbbt28nBQUF8vb2pszMTL7DqTd5z50VFRQUkK6uLh05cqRpXrycY7mUISI6dOgQl0+zs7P5DqdO4uPjSV1dnRYsWMBrHIcOHSI9PT364osvaOvWrfTFF18QABo8eDBt27aNvvvuO/L09CQrKyupx9Wl7ZWXl9OZM2cIAOnr65O/vz+tWbOGrK2tydDQkIKCgmTGlJWVRQsXLiQApK6uTg8fPqyyT2FhIX366aekoKBAhw4dorKysgY9V8XjY319ffrpp5/oxx9/pH79+pGCggItXbq0RRcXrel4VZ7yxccff0wqKioUFRXFdyi1Ki8vp2HDhpGFhQW9evWKtzjq29YuX75MIpGIANDx48cpPz+/2t/dkOMH1s5aTzureIzZwhq3Bsrz58+pU6dONHjw4Fbz4SyLrq4uWVpaVtl+7tw5MjQ0JBUVFbp+/brUfZaWlgSAZs+eLfN3/vXXX/T5559zPy9atIisra2pvLxcar8PPvigTicBqqqq1KtXryrbU1NTaenSpbU+vjoZGRlyUUD58ccfSSQS0dWrV6vcV1hYSAMGDKBdu3bxEFndffzxx236Sggt5c6dO9SxY0fy8vJqs+/nzp07SSAQ0IYNG/gOpVFaQ+4kIvr9998JAA0fPrxO+7dmLJcyFd2/f58MDQ1p6NChVFpaync4tRo1ahT16tWL98Vid+3aRaGhodzP0dHRBECqsFNeXi6Vx+rb9jQ1NcnW1pb7+dWrV9SjRw8SCAR09+5dmXEVFBSQgYEBCYVCev36tcx9Nm/eTB999JHUtoY8F9GbHG9tbS21bdq0aQSA1q5dW+3jmkN1x6vylC9KS0vJycmJ3Nzc+A6lVrt37yahUEi3bt3iNY6GtLVu3bqRnp5erb+7occPrJ3Jfzvr378/DRs2jK8QGrcGyqxZs6Cnp4fAwEBoamo25lfxqrqhre7u7vjjjz9QVFSESZMmobi4mLtPTU0NAwcOxJ49e7B582aZv1NdXZ37OSIiAsrKyhAIBFL7rVy5sso2WaqbEmVkZISFCxfW+vjqyMNw9v3792Pp0qVYt24dXF1dq9yvoqKCrVu34vXr1zxEVzcPHz7EL7/8wncYbYKDgwPOnDmDixcvymxbrd2TJ0/w0UcfYfXq1fj000/5DqdRWkPuBIDffvsNbm5uuHDhAqKjo+v0mNaI5VKmsl69eiE4OBg3b97EN998w3c4Nbp//z4CAwPh7+/P+5QjW1tbDBo0qMZ9BAIB5s+fD6BhbU9JSUkqh+nq6uLtt98GEeHAgQMyn1NVVRULFixAWVkZAgICZO5z4sQJfPLJJ1LbGvJcksdVNnfuXACo8XHNQdbxqrzlC6FQiE2bNiE0NBTXrl3jO5wabdy4EbNmzUK/fv14jaO+bQ14839ZlxzR0OMH1s6kyWM7++GHH3Dx4kVcv36dnxga+sDw8HCcP38eV69ebdOLxI4ePRru7u44f/48Dh8+DF9fX+6+gIAA9O/fH8uXL4ednR1GjBhR7e+xtrbGrl278NFHH+GHH37gGouJiQm8vLwaFNvNmzfh6OgIc3NzbltsbCzOnDmDrKwsODk5YdSoUdx9RUVFOHz4MAwMDODp6QkAVRLIwYMHUV5eDpFIhMmTJwMA/vnnH5SWlkJVVRXjx48HAMTHx2PPnj1Ys2YNAgMDERUVhaVLl0IkEiEnJwcHDx5EdHQ0unfvjtmzZ0udEFW2fv16AKgyj7ii/v37gyos11NcXIzQ0FCEhobC2NgYXl5eUu9DXFwc9uzZg6+//hrx8fE4dOgQOnXqhNmzZ0vNRbx69SoCAwPRtWtXKCgoYN68edW+V9XtHxYWhmnTpiE/Px8HDhyASCSCt7c3ANT4XtQ1RkkskZGRGDhwIDw9PaGqqorjx4+joKCA+ztK5oBGRkbiwYMHAABPT0+peZuthaOjIz7++GP4+/tj4cKFUFZW5jukJuPv74/u3btjzZo1fIfSrOQld16+fBnW1taYMWMGQkNDsW3btmoX+mtM3jhx4gTy8/MBAN27d0ePHj0QHBzMPcbAwADDhw/Hs2fPcPXqVQDAkCFD0Llz5xrzRE25tjKWS1kulcXe3h5ffvklNmzYgGXLlkFDQ4PvkGQ6cuQIunXrJvV/whcnJ6c67TdgwAAADWt7skg6I58/f17tPvPnz8eGDRuwdetW7iRL4vHjx9DU1ETXrl1rjb0uz1XT48zMzKrcV9vxn6x2X9fjzsrHqzXlCz65urrCxsYGR44cgYuLC9/hyBQVFYXHjx9j9+7dfIdS77ZWH405fmDt7A15bWeDBw+GlZUVAgIC4Ozs3PIBNHTsytq1a6lnz55NMxCGZ4aGhjKHoUt8/vnnBIDeeecdblvfvn2JiOjWrVukqqpKurq6UteBP3ToEPn5+XE/x8bGkr6+PgEgCwsLCgwMrFeMOjo6UlN4SktLaezYsVKXKvzoo49o8ODBlJGRQcHBwSQQCLgYoqOjafz48QSANm7cyD0mOztbaqhWTk4Oubq6kqamJrdPamoq2dvbk6GhIRER7d27lwwNDQkA7dmzhxwcHAgAhYWFUUxMDI0bN46CgoLo3r17ZGdnR+bm5tWu8RAbG0sASCgU1nnIbmFhIQ0dOpQOHDhAmZmZtHXrVtLQ0ODWN9izZw8ZGBgQADpx4gRNnDiRxowZQwDoiy++4H7PihUraN++fZSfn0/79+8ndXX1Gt+r6va/cuUKTZ8+nQDQqVOnuLmONb0XdY3x6dOnNHjwYNq5cyc9e/aM3N3dqXv37lRYWEjR0dFkZGREACg2NpZ7jFgsJnd3d/r555+rDFtsTST/GxEREXyH0qRMTEyk/q9as9aQOydPnky3b98mIiJra2vS0NCgnJycKvs1Nm9ERUWRvr4+derUifLy8ojozVQmoVBIrq6uXA4Ui8X04Ycf0tKlS6m0tLTGPFFTrq2M5VKWS2vy77//EgAKCQnhO5Rq/ec//yEfHx++w5BJ1rQCiYa0PSIifX19srOzk9rWp08fAlDrNLtZs2YRALp48aLU9iVLltDZs2eb7LkMDQ2lphaIxWKaMGECAaiyllJtx3/Vtfu6HHcSVT1erS5fyIP33nuP3N3d+Q6jWvv37yehUEhlZWV8h1JFTW1NwsLCgoyMjGr9XY09fmDtTL7b2Zw5c2jkyJF8PHXD10D56KOPaNCgQU0ZDG9qOwn473//SwDIw8OD2yY5CSAi+vvvvwkA2dracgfmlU8CiIgePHhAvXr1IgAEgEaNGkUxMTF1ilFHR4fU1NRoyJAhNGTIEC4hVCygaGlp0fr167mfbWxsyNnZmfs5JSWl1gIKEdGHH34o1cCIiN59912pBrZ69WruoJ6I6PHjx1ReXk4eHh5SjT0wMLDKgWxFISEhBKDKQmw1mTZtGs2ZM0dq2+TJk0lVVZVbeHLFihXcAlMSksWyiIhKSkpIT0+Pnjx5wt2/ePFi7vvK71Vt+69du5YASB1k1/Ze1Baj5HfMmzeP+/nUqVMkEAgoICCAiIj27dtHAKQSWklJCTk6OsrlB2N95ObmEgA6ffo036E0KVVVVdq7dy/fYTQJec+dycnJNHToUO7nrVu3EgDatm2bzP0bmzc2btxICgoKlJqaym2bPHkymZqaSs0dnjRpErcwXG15orpcWxnLpSyX1kQsFpOSkhLt27eP71CqNXz4cHr//ff5DkOmmk7qGtL2iN6cbJmamlJERARdvXqVpk6dyq0PVVvB7s6dOwSAxo8fz20rKCggR0dHmY9t6HMZGhpS586dac+ePbRu3TqysbGhAQMG0OHDh6vsW1M7ra3d1+W4U9bxqqx8IQ+WL19OTk5OfIdRrZ07d5KWlhbfYcjUlAUUosade7F29oa8trMlS5aQi4sLH0/d8DVQzM3NER0dLTW3va2SDMvu2LGjzPt9fHzw6aefIjIyEr6+vtUO0bS3t8ft27exZcsW6OjoIDAwEL1795Ya5l0Tc3Nzbqh1SkoKpkyZInX/6dOnsWDBAgBvpvcQEQoLC7n7a5pGU5GCQtV/i8rbVFVVAbx57QBgaWmJtLQ0hISE4Nq1a1i1ahVWrVqF06dPw9HRkRseXVl912ApKCjA4cOH4eDgILV9wYIFKCws5IYjSqaVVRxOa2dnxw2hE4lE0NDQwIgRIxAYGAgAWL16Nbdv5feqtv0re/HiRa3vRW0xxsXFISQkhBtWBwBjxoxBWload7nbt99+Gz169MD333/P7XP06FGMHz8eioqK1cbXGty9excA0LNnT54jaVrm5ua4c+cO32G0CL5z544dO/DBBx9wP8+aNQvq6urYvn27zP0bmzdmzpwJBQUFqUs86+joICkpCSEhIQCApKQkGBkZQVVVtU55QlaulTV3m+VSlktr8vDhQ5SUlMDCwoLvUKplaGhY72Hu8qAxa8kpKioiKSkJERER8PT0xL1797B79+5a13dycHDA4MGDceLECe4yqAcPHoS3t3e1j23oc4lEIvTo0QN3795FVFQUvvzyS24KgERt7bS2dl+X487WJDk5GYaGhnyHUS0DAwPk5ORIXXq3rWrMuRdrZ/Lt2bNnMDAw4OfJG1p6SU1NJWWX1xbmAAAgAElEQVRlZfrpp5+arJzDl9p6UZcsWUIApEZ3VOxFJXrTuzN27FgCQJ9//rnMXtSKMjIyaObMmQSAtLW1KSsrq8YYK0/hISK6dOlSlZ6xgIAA8vX1pT///JNbzV5C0qNf2wiURYsWValQzps3T6pC+c033xAAqeGqoaGhBIDS09NrfC0VPX/+nACQoqJinS7VJenp2b59u9T25ORkAkC+vr5ERLRu3ToCIHXVgU8//ZSUlJS4n0+dOkU6OjoEgAYOHChVsZX1XtW0f+XqbF3ei9piPHHiBAGgy5cv1/ie7Ny5kwDQjRs3iIjI09OTXrx4UeNj5F15eTmNGjVKagRVW/Hdd9+RlpYWPX/+nO9QGk2ec2dhYSF17dqV/vOf/9CkSZO4m6mpqcwhuUSNzxtEROPGjeNW4U9LS6P33nuPTE1NadKkSUT0JldIphTVJU/IyrWysFzKcmlNJk+eTLa2tnLXg1jRjh07SENDg5sCJ09q6hWvb9uTkDXcvz7++ecfAkDLli0jIqIhQ4ZU204a+lwVpxZkZmaSqakpdezYsUq7qEs7rand1+W4s7X0jBcVFZGenh59//33fIdSrfT0dO4SvPKmqUegVFTfcy8i1s6I5LOdFRYWkq6uLm3atImPp2/4CBQjIyOsWLECK1euxM2bNxv6a+ReSUkJTp06BaFQyPVUyaKgoIB9+/bB2toa69evx+HDh6Xu37hxo9TPenp62Lt3L3x8fJCVlYWwsLB6x+bm5ibVM7ZixQrs2rULO3fuhK+vb4svvClZnElW73pubq7Mx3Tu3Bm2trYQi8V49OhRjb+fiCAWiwGgyurm+vr6AFCv3rUxY8YgLi4OS5Yswe3bt+Ho6FjjFTrqs39D3ovKJD3PQUFBVe5LT0/nvp85cyY6d+6Mb775Bk+ePIG2trZc93zUxcaNGxESEgJ/f3++Q2lyCxYsgJGREd5++21uhEZbxHfu3L9/P95//30cO3YM//zzD3c7evQoAGDbtm0Nel215YF33nkHkZGRuHXrFn7++WcsWrQIc+fOxYkTJ5CWlob79++jb9++AJomT0iwXFq99pxLAWDLli0ICAjApk2b6nzlKj54e3ujvLxcrq72UBf1bXtNZfz48TA1NcUff/yBK1euoGvXrlz7bQ7a2trYt28fXr9+jVmzZkm9lrq00/rmidZq9+7dyMvL40YNyiN9fX2MHTsWP/zwQ5P+T8qL2NhYAE1z7sXamXzatWsXCgoKuEXfW1qjxu189dVXGD58ODw8PHDx4sWmikmu+Pv7c/+INjY2Ne6rqamJEydOQEdHp8pJwJUrV5CWllblMRMnTgRQt+k1NSW527dvc1csqXjJ44YkRk1NzSpTsyoecFfH0tISioqK+Oqrr1BSUsJtT09Px759+6p93Nq1awG8KQBVfFxF6enp2L17NxwcHKCsrFwl6UkOggcPHlxjjBL5+fnYuXMndHV18eOPP+LSpUvIy8vD/v37G7W/5D1q6HtRkY2NDRQUFHDy5Emp9z4+Ph63bt3iflZSUsLy5ctx8uRJLFmyROpSb60NEWH9+vX47LPPsGnTplovbdcaqaur48iRI4iNjYWnp6fUCVxbwnfu/PXXX7krwVTk4OAAZ2dnHDt2rN7TBeqSB8aMGYNOnTph+/btSExMhJ2dHebMmQOxWIx33nkHw4cP5/ZtijxREculsrXHXAq8yafffvstli5dio0bN8rF1W1qoqenh2XLlmHt2rXccHl5ITmWqu6Yqj5tr+LvbMzJq6KiIj788ENkZ2djypQp3BRuWRr7XBKurq748ssvERwcLDXdrbZ2Wlu7b+hxp0Rd92tuKSkp+Oyzz7Bw4UIYGxvzHU6N1q5di9u3b2PHjh18hyKltrZWeb/KysvLsXPnTgBNc+7F2tn/yEs7e/78OVavXo0PP/wQRkZG/ATR2DEsxcXFNHXqVFJUVKSvv/5aaghta1BSUkKKiopVhqEXFRXRkiVLSCQS0apVq6ioqEjqfgMDA8rPz5f5O0NCQkhRUVFqGPqoUaPIw8ODcnNzpfYdP3489erVq8bh2ZLF37p27VrtPlFRUQSA3n//fSotLaWQkBAyMzOjLl26UExMDCUkJNCLFy8IAH355Zfc4yQL/K1Zs4bbJhnGHBwcTOXl5XTgwAGytbUlJSUlysrKorKyMlqzZg0BkFoskYho4cKFBICcnZ1p3759tHv3bvLw8Kh1mNz69etJIBDQzJkzqwzfTUpKomXLlnEL5i5fvpwA0IULF7h9tmzZQt7e3tzwsqVLlxIAqattLF++nAQCARUVFVFOTg4ZGRlRYWEhd7+FhQU3Ja3ye1Xb/tu3bycAdP36dbp8+TIVFhbW+l7UFiMR0ezZswkATZgwgc6fP08///wz+fj4VBlGl5eXR/r6+jVOp5B3L1++pLFjx5JQKKQdO3bwHU6ze/z4MZmZmZGRkZFcrWpeV/KcO48fP06enp7Vxu7n50cAaOHChVLbG5s3JJYtW0YA6Pz589y20aNHk4qKSpUrktWWJ6rLtdVhubRqjETtK5cSvXnfR48eTUKhkH7++We+w6mzoqIi6tOnD9nZ2dVpeH1LuXDhgtTUNlnq0/aKi4tJQUGhxuO6usjMzCQ1NTWyt7evdp+GPldpaSkJhULq3Lmz1PaysjIaPHgwKSoq0qlTp7jtNbXT2tp9XY47ZR2vysoXfMnNzaV+/fqRtbV1tZ9x8uarr74iZWVlCg0N5TsUTl3amoaGBgmFwirHF0VFRbRw4UJuofjGnHtVxNoZa2eVNPwqPJVt3bqVVFRUyM7OTubccnl0+fJlmjRpEgFvLj/n4OBAEyZMoEmTJtHYsWNp/vz53Fx1iTt37tC7775LAMjb27vaSwJu3rxZ6iRg+vTpNGnSJHJwcKA5c+bQZ599Rra2tjR06FBKTEysNsZLly7RlClTCAAJBAL6+OOP6ebNmzL3nTFjBikoKJCBgQH98ssvtH79elJQUKDly5dTcnIyLViwgACQjY0NBQYGUmpqqtS2Y8eOERFRfn4+2dnZEQAyMDCgvXv30rx580hHR4eWL19Ov/76K1laWnLvwf3797kY8vPzufmFAEhTU7PKJbiq888//5CdnR2pqqqSm5sbLVy4kN577z1as2aNVJITi8W0bNky6tixI61cuZJmzZpFU6ZM4Rr0sWPHqFu3bgSAFi9eTAkJCXTgwAEyMzMjAPTJJ59QXFwcqaqqkr29Pf3000+0Zs0amjNnDpWUlMh8r3Jycqrdn4goISGBDAwMSEdHh37//fda34u6xPjy5UvKzs7mLmUGgLp161btZX1XrFjB11zARiktLaWff/6ZdHR0yNTUlK5du8Z3SC0mKyuLW6Xd29ubnj59yndIdSavuXPbtm3UsWNH6tSpE/n5+VVZJ+rSpUvk4uLC5dS5c+dSSkpKo/NGRY8ePaJ+/fpJbQsICKBp06ZVibemPPHPP/9Um2trwnJp+8ylRG8O4r///nvS1NQkMzMzCg8P5zukektOTqbOnTuTo6NjvdZUay779u2j/v37c+smrF+/nrtKVWV1aXuhoaE0ceJE7n9xwYIF1R7X1cWCBQuqrGUk0dDnqnh8DIDmz58v9bjk5GTS0dEhoVBI48ePp5CQkBrbaW3tvrbjzsjISJnHq7LyBR8yMzPJxcWFDAwMKD4+nrc46kssFtPkyZNJQ0NDLs7damtr169f5y6pC4C6dOlC/fv3JycnJ+rVqxdpaGiQQCDg1phr6LmXLKyd8d/OsrKyyNXVVR7aWdMVUIiI4uLiaMyYMQSAXF1d5aIx8qniB7+kMZeXl9ODBw/o4sWLlJyc3OTP+e+//0odzL9+/bpBv0cSp6S6FxMTU6/F0dLT0+n27dv1eoxEXl4ehYeH13rgVFBQQHfu3GlQJbS8vJzy8/MpJyeHbt++XaU63ZD9S0pKZL7exrwXEikpKXTv3r0qJ2oVjR49usF/bz6IxWI6dOgQWVhYkEgkokWLFkn1ILcn586d43oBZsyYQbGxsXyHxCs+cmdd1CdvVI6xtLSUUlJSqt2/KfJEZSyXVtUWcynRm8LJ3r17ydzcnJSUlGjRokW1/i3kWVxcHJmZmZGpqSmFhYXxHU691bXtNYWXL1/K1YgHWe20Lu2+oced1eWLlhIREUE9evSgLl26UHR0NG9xNFRJSQlNmTKFlJSU6Mcff5SrhUIbqymPH1g747ed3blzh3r27EmdO3eWh3bWtAUUiZCQEHJ1dSUANGTIEPrnn3+q9AIyDNN0wsLC6P333+c7jDrJysqi77//nszMzEgoFNLs2bMpLi6O77B4V1xcTL/99hv3vnh7e9d61RCGYZpWa8qlRG+uiPjll1+SgYEBqaio0MKFC3krMDa19PR0GjduHAmFQvrqq6/YcSQjV8rLy2nz5s2kpKREw4cPr7FALu8kr0UkEpGHhwelpaXxHRLDcPbu3Uuqqqo0dOhQeWlnzVNAkTh//jy99dZbpKCgQF26dKHly5fTnTt3mvMpGabduHHjBrm6utK8efNo0KBBcjVfvLKSkhI6deoUTZs2jdTU1EhDQ4MWLVrECicylJSU0F9//UUDBgwgAGRtbU1r166lmJgYvkNjmDapNeVSojfDtP/8808aM2YMiUQi6tSpE61evVpeDiyblOTETllZmZydnVvlaBSm7YmIiCA3NzcSCoW0YcMGEovFfIfUJK5evUomJiZkZGREv//+e5t5XUzrdPfuXXJ3d+fWWZWj/8eGX8a4LoYPH47jx48jJiYGs2fPRkBAAPr27QsbGxusX78eCQkJzfn0DNPmxcbGIiEhAZs3b4aWlhbf4UghIly9ehUffPABjI2NMW7cOCQnJ8Pf3x/Pnz/Hli1bYG5uzneYckckEmH69Om4fv06bt68iREjRmDHjh2wsLBA//798cMPP9T76jEMw9RMnnMpABQVFSEgIABTpkyBgYEB5s6dC4FAgD179iA5ORnr16+X+6t+NIRAIMDixYtx8+ZNdOjQAYMGDYK3tzfi4+P5Do1ph5KSkuDr6wsnJyeIxWKEh4fj008/hYJCs55OtRhXV1fcvXsXEydOxPz589G3b1+cO3eO77CYdiY1NRXvvPMO+vXrh9zcXFy5cgVffPGFXLUzAVHLXQCciHDjxg38/fffOHjwINLT09G3b194eXnBy8sLzs7OEAqFLRUOwzBNLDs7G+fPn0dQUBACAwPx7Nkz2NvbY9q0afDx8YGpqSnfIbZKYrEYFy9exP79+3H06FFkZ2fDyckJnp6eGDlyJJycnFjuZJg2JjExEcHBwQgODsa5c+eQn58PNzc3TJ06FZMmTYKuri7fIba406dPY8WKFYiLi4Ovry+WLFkCe3t7vsNi2rjo6Ghs2bIFe/fuRdeuXeHn58ddCretevz4MT755BOcOnUK7u7u+Pjjj+Hl5QWBQMB3aEwbFR8fj59++gl//PEH9PX1sWHDBkydOlUe/+cOtGgBpaKysjKcO3cOJ06cQFBQEBISEqCtrQ13d3d4eXlh5MiR6Nq1Kx+hMQxTR0SEO3fuICgoCEFBQbh27RrKy8vRv39/eHl5YdKkSezgtokVFxcjKCgIp0+fRlBQEJKSkqClpQV3d3d4enrC09MTZmZmfIfJMEw95eXl4eLFiwgODkZQUBBiY2OhpqaGYcOGwcvLCxMnToSRkRHfYfKurKwMe/fuxaZNmxAVFYURI0ZgyZIlGDVqlFz1UDKtGxEhJCQEmzdvxtmzZ9GzZ08sXboUc+fOhUgk4ju8FnPx4kX4+fkhJCQEVlZWWLJkCWbMmAFVVVW+Q2PaiKtXr+LHH3/EsWPHYGJigsWLF2P+/PlQUVHhO7Tq8FdAqSwmJgZBQUE4e/YsLl26hIKCAlhZWWHgwIEYNGgQBg4cCCsrK3msQjFMu1FcXIxbt27h2rVrCAsLw7Vr15Ceng5DQ0OMHDkSXl5e8PDwgJ7e/7F352FRlvv/wN8sw76LAoKiqAyLiiiLMGyWSwmoJ/NkueSpc9UJlwwtzAVB1NBMPSlWZp7c0lPqMYVcIhUZQHZQ2VQ2kVUWWWZg9t8ffuf5MUJmpjwsn9d1zcUwDPDBmnvu+/3cyyC2Sx0wioqKmAHX1atXIRAIYGdnB29vb3h5ecHb2xtjx46lGSqE9DKVlZVITk5GSkoKrl+/joyMDEilUkyYMAEzZszA9OnTwePxoKWlxXapvZJCocClS5ewa9cuXLp0CaNGjcLChQuxYMECjB49mu3ySB9VVlaGY8eO4ejRoygsLMRLL72ElStXIjAwcEAHdLdu3cKuXbtw7NgxGBoaYv78+Vi4cCE8PT3ZLo30QdXV1Thx4gQOHz6MnJwcTJ48GaGhoXjttdegoaHBdnl/pPcEKJ11dHQgMTERCQkJ4PP5SE9Ph1AohJmZGTMo4PF4cHNzg76+PtvlEtJv1dbWIiUlBXw+HykpKcjMzIRIJIKFhQXzOnz55ZcxYcIECjd7AbFYjKSkJFy9ehUpKSlITU1FS0sLDAwM4O7uDm9vb0yePBleXl4UchHSg8RiMbKzs3H9+nWkpKQgOTkZFRUV0NDQwNixY8Hj8eDt7Y1p06ZhyJAhbJfb5+Tl5eHAgQM4ceIEampqMHnyZCxYsABvvPEGBg8ezHZ5pJdrbGzEjz/+iGPHjiEpKQnm5uZ444038M9//hMuLi5sl9er1NbW4uDBgzhy5AgKCgowZswYJrikfe3Ik7S1teHMmTM4evQo4uPjYWBggNdffx3vvvsuvLy82C7vz+idAcrjZDIZCgsLkZSUBD6fDz6fj9LSUgCAlZUVJk2axNzc3Nxoiishz6CqqgqZmZnMLT8/n9no2c7ODjweDz4+PuDxeHBycqLApI8oKSkBn89n2s/CwkLI5XJYWVnB2dkZTk5OTPvp4ODQF5J/Qnq1hw8f4tatW0w7mpeXh8zMTHR0dMDIyAgeHh7g8XiYNGkSfHx8YGpqynbJ/YZcLkdycjKOHDmC48ePQygUYsKECQgKCkJwcDAmTpxI710EwKP3xnPnziE2NhbXrl2Duro6pk6disWLF2POnDkDapnOs8rLy8ORI0dw6NAh1NTUwM7OjnmtBQQE0MxXgtraWly8eBGxsbE4f/482tvbMWXKFCxatAhz587tqxMh+kaA0p2KigqkpqYiJycHubm5yMnJYU6msLKywoQJEzBhwgS4uLiAy+WCy+XSej1CADQ0NKCwsBAFBQXIyclBTk4Obty4gdbWVmhoaIDL5cLFxQUTJkyAq6srPDw8euWpFOTZNDY2Ii0tjWk3b9y4gdu3b0MqlUJfXx/jxo1j/vs7ODiAy+VSKE1INwQCAW7fvo2ioiLk5ubixo0byM3NRWVlJQDA0tISLi4uzG3SpEmwt7enAXwPEQqF+OWXXxAXF4dffvkFdXV1sLW1xcyZM/Hqq69SeDXAtLS0gM/n48KFC4iLi0NJSQnMzc3x6quvIjAwEIGBgTAwMGC7zD5JJpPh8uXLiI2NRWxsLEpKSjB48GC8+uqrmDlzJvz9/WFpacl2maQHdHR0IC0tjdmrLzc3FwYGBpg+fToCAwMxe/bs/jADuu8GKN2pr69nBoTKW1FREaRSKdTU1GBrawt7e3s4ODgwAwMulwtra2u2SyfkuZJKpSgtLUVBQQGKiopQVFSEwsJCFBUVob6+HgBgYGCAcePGMWHjhAkTMG7cOAoaB6D29nbk5eUxgYpyMPjw4UMAgJGREezt7Zn2k8vlMp/r6emxXD0hL45MJkN5eTkTlBQVFeH27du4ffs2KioqADw6elwZPCvDx/Hjx8PCwoLl6omSXC5HRkYGYmNjERcXh+zsbKipqWHcuHHw8/ODn58ffH196b9ZP1JfX4/ExERcu3YN165dQ25uLmQyGVxcXDBz5kwEBQXB09OTZl2+APn5+cxrLTk5GVKpFA4ODsxrzd/fHzY2NmyXSZ4DgUCAlJQUXLt2DQkJCUhLS0NHRwdGjhyJoKAgBAUFwd/fH9ra2myX+jz1rwClO2KxGMXFxczgsaioiBlUdh4cjBkzBiNHjsSIESO6fKQBJemNGhsbUVZWhtLSUpWPxcXFKC4uhkQiAQAMGzYM9vb24HK5cHR0ZILDYcOG0ZVQ8kQ1NTUoLCxkBozK+6WlpUwwPWzYMNjZ2WHEiBFMu2lra4sRI0bA2tqapvCSXq+hoQFlZWXMrby8HKWlpSgtLcXdu3chEokAAEOGDIGDgwMTHnK5XDg4OGDkyJE03b+Pqa+vB5/PR0JCgsrg2sHBAe7u7syyRldX1746xXxAEQqFyMnJYZYgp6eno6CggAnJ/P39mZCM9hjqWa2trUhKSmIG2Onp6ZBIJBg5ciQ8PT3h5uaGSZMmYeLEiTAyMmK7XPIEMpkM+fn5yMzMREZGBjIyMpCVlQWJRIJRo0Yx4Zifn19/Pw2y/wcoT1JXV8eEKXfu3GE6TGVlZWhsbGSeZ2lpqRKqDB8+HEOHDoW1tTWGDh0KCwsLGoiS50osFqO6uhqVlZWoqqpCZWVll7CkpaUFAKCmpoahQ4di5MiRzE0ZknC5XJqSSp47sViMkpISJlApKSlRGXx2dHQAADQ1NWFjY8OEKyNGjMDw4cNhaWkJGxsbWFpa0gaP5IUSCoWorKxETU0N7t+/j6qqKpSXl+POnTu4d+8e7t27h7a2NgD/vy3tfAFlzJgxTGhiYmLC8l9DXhTl8o6kpCRkZGQgMzMTDQ0NzLJWZaDi7OwMBwcHunrOourqauTn5yM/Px9ZWVnIzMxEQUEBpFIpTE1NMXHiRLi5ucHHxwc+Pj70uu1lhEIhUlJSkJiYiPT0dGRmZqK2thbq6uoYM2YM3NzcMHHiRIwdOxaOjo4YNmwY2yUPSC0tLSgsLGRmJ2dmZiI7OxtCoRA6OjpwcXGBm5sbvLy8EBAQMNBWcwzsAOVJmpubuwxYlffv3buH5uZm5rkcDgcWFhYYNmwYMzCwsrJiAhZLS0uYm5vD3NycrsYOcO3t7aivr0ddXR2qq6tRVVXFBCTV1dW4f/8+ampqUFtby3yPmpoaLCwsmKv6j8+QsrW17W9T40gfV11drXJFXxmslJWVoaKiAkKhkHmutrY2LC0tYW1tzbSbVlZWGDp0KBNQK9tPuspPlBobG/HgwQPU19czYXPnNlX5WOf3ag0NDVhYWGDkyJFoa2vDjRs3YGlpCVdXVwQEBGDWrFngcrks/lWkNykrK2OutCoHD8olsMbGxnBwcGACFScnJ4wePRojRoyg9+PnQCwWMzNq8/LyUFhYiPz8fBQUFDCzx83MzODq6qpykASdAtM3VVRUqLzWsrKyUFdXB+DRKgEHBweMHTuWec2NHj2a+r7PSVVVFbNSo6CggHm93bt3DwCgq6uLsWPHMjOFJk2ahLFjxw708SwFKM9KKBSioqKCuarVebZA5wGx8kqs0qBBgzB48GBmQGBhYYHBgwczjw0ZMgRmZmYwMTGBqakpTExMaHZLLyUWi/Hw4UM8fPgQTU1NqK+vZ241NTXM/QcPHqCurg51dXUQCAQqP8PIyKhL4Kac3WRlZYVhw4bBwsKCBo6kX2lublYZ8HYe+HYeAD/efhobG6sEKso2s3Obam5uDhMTE5iYmMDY2Jg6WH1AU1MTHj58iObmZjQ1NaG2tlalPVW2oZ0fk0qlzPcrQ+bHA7jOQZwyjFNXVwfwKORLSEhAcnIykpOTkZubC6lUiuHDh4PH4zHHtI8fP36gdxRJJ/X19cjLy0NBQQEKCgqYQb1y4+DuZoQqb8r3dto36tHFJGVbr7xAWVJSwtyvqqqCXC4H8OhgCCcnJ5XAytnZmZbi9HMNDQ3Ma00546jza01dXZ15rdnZ2TGvMzs7O6b9H+hbMMjlctTW1qK6uppZmtr5dVZaWsr0swwMDODo6AgnJyfmo5OTE0aOHMm8bxIGBSgvmnK2QXcD6/r6etTW1jJX0err65l9KzozNjaGsbExMyjoPDhQ3jcwMICxsTF0dHSgr68PIyMj6OrqMvd1dHRoKcf/aWpqQkdHB9rb2/Hw4UO0t7cz9zs6OiAUCpkOvbJTr7zf+bHOV9GVdHV1MXjwYAwZMgRDhgxRGeR1/nzw4MEYOnQodaQIeYKGhgaV9lM5kG5oaFBpQ5X329vbu/wMXV1dpq18Uluqp6fHtJfa2towNDSEgYEBtLW1ma9TGPOIQqFg2ktl2ykSiSAQCNDS0oKOjg60tbWhpaVFpQ3t7mPnGSJK6urqKoGY8mJD58+V7azya3815BAIBMjOzkZmZiaSkpJw+fJlNDQ0QF9fHxMmTGCOcPf29u4PJwiQ56S+vh67du3Cnj17YGdnh/DwcJXByeODFAAwNDSEtbU1hgwZAhsbG1hYWMDa2hrm5uYwNTWFmZkZzMzMmPt9od0Ri8VobGxEY2MjmpqamPsNDQ24f/8+6urqUFlZidraWlRWVjJLkIFHsxCVs2ofv40aNYqW4BAVzc3NKC4u7jYMKCsrY/asAgATExNmJYDyo7W1NQYNGqTyGlPe+kJY3tzczLy+Or/O6urqmItPylttbS1kMhnzvY8HTp2DJ1oq9adQgNLbKN98lLMa/mgQr7zf1taG5uZmJrH/PYaGhtDR0WEGBxwOBxwOhwlXlI9paGgwmzkpBw5qampd3si0tLSeuMGa8ud1RygUqjR0j3v48CE6/+8plUrR2toKAGhra4NEIoFcLmc64J1/XlNTE/NYR0cHE5Q8fkX7cdra2tDT02Nm/zweVD3pMXNzc9psjhAWCQQC1NfXd2kjlQP1zo81NjaiuLgY7e3tUCgUaG9vZ/bC+D3KNlBHRwe6urrMDEHl58CjWWUaGhrQ1NSEoaEhAEBfXx9aWloA0OXY1M7P646yTeqOTCZTGYg8TiQSdQl6u2snOz+vtbUVUqlU5We3tbVBJBI0OigAACAASURBVBIxwfGT2m0AzHtK58Dq8fudH1O2t8rHzc3Ne8XMy5KSEmZfDD6fj4KCAigUCtjZ2YHH4zGhipOTU6+ol/ScBw8eICYmBrt37waHw8HSpUuxcuXK3x3sdx7Y1NTUoKqqivlYW1uL+/fvo7GxsdsLM3p6eswAT0dHh7lApqOjA2NjY2hpacHQ0FAl5O0u8H28P9a5T6UkFouZmbLK+21tbcyMW2Vb0draivb2diYseXx2LfAovB40aBCsra1hYWHBDGCtrKxgZWWlsnSTXj/keZDL5cyKgM6vs86hQlVVFRobG7sdDxgZGTGhiq6uLvT09GBoaAgtLS3mIrWuri7zPg88usjdeYZGd2Ol7t43le+1yvsikQgtLS3MWKW5uRlisRitra1obW1lXmudAxHl7xs0aBCGDBnCzLrsHBgpPw4fPhw6OjrP5d+ZUIDS7yjf8JQvwu7ud746KJPJVDrPyhBGIpEwgwllWNFdZ10gEEAsFv9uPcoOenc6BzfdebwDoK6uDmNj4y5fUw5IOg80lA2asrEzNTVVGfTo6upCV1cXBw8exNdff423334bO3bsgJmZ2e/WQwjp+yQSCb7//nts2bIFNTU1+PTTT7Fx40bm662trejo6EBrayva2trQ0dGBlpYWCAQCplPTOZgFug8lOg9ElB2lzoGv0h8FEsr29/c83nnrrLuOXOewx9jYGAKBgNlBH+g+7NHT04OOjg7Tduro6HRpU7W1tZkZPP31WNCWlhakpaUxoUpSUhLa29thbGwMd3d3lVBloE8d76/q6uqwc+dO7NmzB/r6+ggJCUFoaOhzOz2ko6ODGSh1nsmhvK8MMjsPskQiEdra2lT6Y8r+XWePX5QCuga6nftZyj6avr4+tLW1mde5np4eM7NZOdh8/KMy7CGktxIKhczrq7y8HB988AFmzJgBR0dHJmARCARobW2FWCxWed0pX0vdvad3F0x2d7FZ+V4KQGW2q/J9VbkE2cDAAIaGht3OTlPeJz2OAhRCzp07h5CQEAiFQoSHh2P58uW03o+QfkYul+PUqVNYu3YtysvLMX/+fERERMDOzo7t0lgVGhqKr7/+GvHx8fD29ma7nD5FKpUiNzcXfD4fmZmZuHbtGsrLy6GpqQkXFxfweDxMmjQJ/v7+sLW1Zbtc8hfcu3cPX3zxBb799lsYGRnho48+wooVKygoI6SPa29vx7Rp01BeXo6UlBQ6YYs8DQpQCAEezbwJDw9HTEwMvLy8sG/fPowbN47tsgghf5EyOFm/fj1KS0sxf/58bNy4kU5r+D9yuRzz5s1DQkIC+Hw+HBwc2C6pT6uqqmKW/GRmZiItLQ0SiQRWVlbM7BQfHx+4urpSUN8HlJWVYdeuXdi/fz+GDBmC0NBQvP/++zS7gpB+QPn+d/XqVSQlJdH7H3laFKAQ0llOTg5CQkKQnp6OkJAQREVFPbepuYSQnqMMTjZs2IA7d+5g7ty52Lp1K0aPHs12ab1Oe3s7pk6diqqqKqSkpMDS0pLtkvqNtrY25OTkMKFKcnIyGhsbYWBgABcXF5VQhaZi9x6lpaWIjo7GwYMHYWNjg5UrV+Jf//pXn9jQlRDydD788EPs378fv/76K3x8fNguh/QdFKAQ8jiFQoEjR45g1apV4HA4iI6OxuLFi9kuixDyFBQKBWJjYxEeHo4bN25g7ty52Lx5M+zt7dkurVdraGgAj8eDlpYWEhMTmX0QyPMlk8lQWFjInPaj3JxWXV0dXC4XkyZNYkIVZ2dntssdcPLz8xEdHY3jx49j+PDhCAsLwzvvvNMnTucghDy96OhorFu3Dj/++CPmzp3Ldjmkb6EAhZDf09jYiMjISOzduxf+/v6IiYmBo6Mj22URQrqhDE4iIiKQk5ODuXPnIioqClwul+3S+ozS0lJ4e3vDyckJ58+fZzaTJS9WTU0N0tPTVUKVjo4OWFpaws3NjQlU3NzcaOnIC3Lr1i1s374dP/zwAxwcHPDJJ59gwYIF/XZDZEIGshMnTmDBggXYuXMnPvzwQ7bLIX0PBSiE/BE+n4+QkBAUFhbigw8+wNatW+m4YkJ6kfj4eKxZswZZWVkIDAxEVFQUJkyYwHZZfVJmZiYCAgIwe/ZsHDlyhI4XZYFEIsGNGzeY034SEhJQV1cHDoeD8ePHM0t+AgICMHjwYLbL7dNyc3OxZcsWnDx5EmPHjsXq1aspOCGkH7t69SpeeeUVrFixAtu3b2e7HNI3UYBCyNOQSqWIiYlBeHg4zM3NsWfPHsycOZPtsggZ0OLj47F27VpkZGQgMDAQkZGRmDhxIttl9Xnnz5/HrFmz8Omnn2LTpk1sl0OgujltUlISsrOzIZfLaXPaZ5SSkoKtW7ciLi4O48ePx7p16/D6669TYEhIP3br1i34+vpixowZ+OGHH6itJM+KAhRC/ozq6mqEhYXhyJEjCAoKwt69e+l4SkJ6WHx8PNavX4/U1FRMnToV0dHRmDRpEttl9Svfffcd/vnPf2Lv3r1YunQp2+WQx7S2tiI1NZU57YfP5+Phw4cwNDSEp6cnc4Syn58f7WfTCZ/Px7Zt2xAbGwtvb2+sWbMGQUFBFJwQ0s9VVlbCy8sLdnZ2uHjxIm0ITf4KClAIeRZXrlzB0qVLUV5ejo8//hiffvopNcaEvGB8Ph8bNmzA1atXMXXqVGzduhXu7u5sl9VvRUREYPPmzTh58iTmzJnDdjnkCZSb03Y+Qjk/Px8aGhrgcrkqs1Ts7OzYLrfHdQ5OeDwewsLCEBwczHZZhJAe0NLSAl9fX8hkMiQmJtKJZ+SvogCFkGclkUiwb98+rFu3DtbW1ti7dy+mTZvGdlmE9DtJSUkIDw/H5cuXMXXqVGzevBmenp5slzUgLF26FP/5z3/w22+/wcvLi+1yyJ9QXV2NjIwMJlTJyMiASCSClZWVymk/Hh4e/XbDYD6fj/DwcFy5cgU8Hg+RkZF4+eWX2S6LENJDxGIxZs6ciYKCAqSkpGD48OFsl0T6PgpQCPmrSkpKsGLFCsTFxWHevHnYs2cPLCws2C6LkD4vOTkZn332GXPVePPmzQgICGC7rAFFJpNh7ty5SEpKQlJSEh0H3YcJhUJkZWUxp/1cuXIF9fX10NfXx4QJE5hQ5aWXXsKgQYPYLvcviY+Px7p165CWloapU6ciKioKkydPZrssQkgPUigUWLx4Mc6ePYtr167BxcWF7ZJI/0ABCiHPy7lz57B8+XI0NzcjIiICy5Yto538CXkG169fx5YtW5jgZNOmTXjppZfYLmvAEgqFePnll1FXV4fk5GQKiPuRkpISZmNaPp+PgoICKBQK2NnZMUt+eDwenJycev0+IcqjzDdt2oTMzEwEBgYiPDyclvkRMkCtWrUKe/bsQVxcHM0QJ88TBSiEPE9CoRDbt29HdHQ0HB0d8dVXX9FVL0Ke0o0bN7B582b89NNPzAaPtE9B7/DgwQPweDyYmJjgypUrdJR7P9XS0oK0tDQmVElKSkJ7ezuMjY3h7u6uEqro6uqyXS4AQC6XIy4uDhs3bkRubi5mzpyJiIgI2liakAHsq6++wtKlS3Ho0CEsWrSI7XJI/0IBCiEvwu3bt7Fs2TLEx8dj4cKF2LlzJ8zNzdkui5Be6ebNm4iKisLJkyfh6emJtWvXUnDSCxUXF8Pb2xvu7u44c+YMNDU12S6JvGBSqRRFRUXMDJXExESUlZVBU1MTLi4uzGk//v7+PX4inVwux6lTpxAeHo7bt29j7ty5iIyMhKOjY4/WQQjpXc6ePYvXXnsN0dHRWL16NdvlkP6HAhRCXqRz584hJCQEQqEQ4eHhWL58OZ07T8j/uXXrFjZt2oSTJ09i3LhxWL9+PebNm8d2WeQJ0tPTMWXKFLz11lvYv38/2+UQFlRVVamc9pOWlgaJRAIrKytmdsqkSZPg6ekJDofz3H+/RCLB8ePHsWXLFty9exdz585FVFQUuFzuc/9dhJC+JTExEdOnT8eSJUvw1VdfsV0O6Z8oQCHkRWtubkZ4eDhiYmLg5eWFffv2Ydy4cWyXRQhr8vPzER0djWPHjsHZ2RkbNmzA66+/3uv3WCCPxMbG4m9/+xsiIyOxdu1atsshLGtra0NOTg4TqiQnJ6OxsREGBgZwcXFhQhUejwczM7Nn/j1isRgnTpxAVFQUysvLMX/+fGzYsAFjxox5jn8NIaSvKigoYNqb//3vf7QPIXlRKEAhpKfk5OQgJCQE6enpCAkJQVRUFIyMjNgui5AeU1BQgM8++ww//PADHB0dER4eTsFJH7V//37861//wsGDB7FkyRK2yyG9iEwmQ2FhIXPaj3JzWnV1dXC5XJUjlJ9mc1qRSIRDhw4hKioKdXV1eOONN7Bx40aMGjWqh/4iQkhvV11dDS8vL1haWuLy5cvQ09NjuyTSf1GAQkhPUigUOHLkCFatWgUOh4Po6GgsXryY7bIIeaFKS0sRHR2N7777DlwuF2FhYVi4cCEtZ+vjPv30U3zxxRc4d+4cZsyYwXY5pBerra1FWlqaSqjS0dEBS0tLuLm5MYGKm5sbdHR0AAACgQAHDhzA9u3b0dDQgLfffhvh4eGwtrZm+a8hhPQmra2t8Pf3R2trK5KTkzF48GC2SyL9GwUohLChsbERkZGR2Lt3L/z9/RETE0Mb35F+p7y8HFu3bsXBgwcxZswYrFmzBgsWLKBptf2EQqHAP/7xD5w+fRoJCQlwdXVluyTSR0ilUuTm5jKn/SQkJKCurg4cDgdjx46FoaEhbty4AbFYjH/+859Ys2YNrKys2C6bENLLSCQSBAUFITs7G8nJyRg9ejTbJZH+jwIUQtjE5/MREhKCwsJCfPDBB9i6dSsdD0r6vHv37mHLli04ePAghg0bhjVr1uDdd9+l4KQfUnZeb968ieTkZIwYMYLtkkgfdfv2bWzatAmnTp2CWCyGQqGAQqFQ2ZzWx8cHrq6uNHuNEAKFQoF33nkHp06dwtWrVzFx4kS2SyIDAwUohLBNKpUiJiYG4eHhMDc3x549ezBz5ky2yyLkT6uoqMCOHTvwzTffwNLSEmvXrsU777xDx932c62trfDz84NIJAKfz/9LG4WSgaehoQF79uzBv//9b8jlcnzwwQcICwuDpqYmcnNzmSU/fD4fDx8+hKGhITw9PZnTfnx9fWFiYsL2n0EI6WFr167Fjh07aBkp6WkUoBDSW1RXVyMsLAxHjhxBUFAQ9u7dC1tbW7bLIuQP1dXVYefOnfj3v/+NIUOGYN26dRScDDBVVVXw9vamDfzIU6uvr8fevXuxe/duaGpqYtmyZVi5cuXvhiHKzWk7H6Gcn58PDQ0NcLlclSOUnZ2de/ivIYT0JOVG5t999x3+8Y9/sF0OGVgoQCGkt7ly5QqWLl2K8vJyfPzxx/j000+hra3NdlmEdPHgwQN88cUX+PLLL2Fubo5Vq1bhX//6F/3/OkDl5+fDx8cHvr6+OH36NC3ZIt1SBq579uyBvr4+QkJC8NFHH8HY2PhP/6zq6mpkZGQwoUpGRgZEIhGsrKxUTvtxd3endomQfiIuLg5z5szBxo0bsX79erbLIQMPBSiE9EYSiQT79u3DunXrYG1tjb1792LatGlsl0UIgEdXjnfs2IE9e/bAwMAAoaGh+PDDD5nTM8jAde3aNcyYMQP/+Mc/sG/fPrbLIb2Iconft99+C0NDQ4SGhmL58uXPdbaSUChEVlYWc9rPlStXUF9fDz09Pbi6ujKhypQpU2Bubv7cfi8hpGekp6djypQpePPNN/Htt9+yXQ4ZmChAIaQ3KykpwYoVKxAXF4d58+Zhz549sLCwYLssMkAp9yrYtWsXtLW1sWrVKqxYsQK6urpsl0Z6kZ9++gnz58/H9u3bsWrVKrbLISwrLy/Hzp07sX//fgwZMgShoaF47733eqzdKCkpYZb8JCUlISsrCwqFAnZ2dszGtDweD05OTlBTU+uRmgghf15xcTG8vb3h7u6OM2fO0DJhwhYKUAjpC86dO4fly5ejubkZERERWLZsGU2PJz2msbERX375JXbv3g0Oh4PVq1c/9yvHpH/ZuXMnVq9ejUOHDmHRokVsl0NYUFpait27d+Obb76BlZUVVq5ciffff5/1mWotLS1IS0tjjlBOSkpCe3s7jIyM4OHhoRKqUDhMSO9QX18Pb29vGBsb4+rVq3RiJWETBSiE9BVCoRDbt29HdHQ0HB0d8dVXX2Hy5Mlsl0X6sdbWVuzbtw/R0dHQ0NDAsmXLEBoaCiMjI7ZLI31AaGgoYmJiEBcXh6lTp7JdDukhxcXF2L59u8ox5r15U2mpVIqioiJmH5XExESUlZVBU1MT9vb2TJji7+9PG7sTwgKhUIipU6eitrYWycnJNBObsI0CFEL6mtu3b2PZsmWIj4/HwoULsXPnTlrLTZ6rtrY2xMTEYNu2bVBTU8Py5cufeZNHMnApFAosXrwYZ8+exbVr1+Di4sJ2SeQFunXrFrZv344ffvgBXC4XYWFheOutt3ptcPIkVVVVKqf9pKenQywWw8rKSuW0H09PT3A4HLbLJaTfkslkmDt3LjNbzN7enu2SCKEAhZC+6ty5cwgJCYFQKER4eDiWL18OdXV1tssifZgyONm+fTskEglCQkKwZs2a3z1WlJA/IhaLMXPmTBQWFiI5ORnDhw9nuyTynN24cQM7duzAsWPH4OTkhI8//hgLFizoV8tMBQIBsrOzmVAlOTkZjY2NMDAwgIuLCxOq8Hg8mJmZsV0uIf3G0qVL8Z///Ae//fYbvLy82C6HEIACFEL6tubmZoSHhyMmJgZeXl7Yt28fxo0bx3ZZpI8RCAQ4cOAAPvvsMwgEAixduhRhYWEwNTVluzTSDzQ3N8PPzw8ymQyJiYn0/1U/kZOTg61bt+LkyZMYP3481q1bh9dff33AbMSq3JxWGaoUFBRAXV0dXC5X5Qhl2pyWkGcTGRmJqKgonDx5EnPmzGG7HEKUKEAhpD/IyclBSEgI0tPTERISgqioKNqngvwhkUiEQ4cOYePGjWhra8PSpUvxySef0BVU8txVVlbCy8sLdnZ2uHjxIrS1tdkuiTyjpKQkREdHIzY2Fl5eXvj0008RFBQ04EOC2tpapKWlMaf98Pl8dHR0wMLCAu7u7kyo4uPjw/pGuoT0dseOHcOiRYvw5ZdfYtmyZWyXQ0hnFKAQ0l8oFAocOXIEq1atAofDQXR0NBYvXsx2WaQXEovF+P777xEZGYnm5ma8++67WLt2LW3MRl6oW7duwdfXF6+88gqOHTtGSw77GD6fj23btiE2NhY8Hg9hYWEIDg5mu6xeSyqVIjc3l5mlkpCQgLq6OnA4HIwfP5457cff3x9Dhgxhu1xCepRcLv/d94DLly/j1VdfxSeffIKoqKgeroyQP0QBCiH9TWNjIyIjI7F37174+/sjJiYGjo6ObJdFegFlcLJp0ybU19fj7bffRmRkJCwtLdkujQwQV69exSuvvIIPP/wQ27ZtU/maVCrFunXrEBkZSVfoexE+n4+NGzfi8uXLFJz8RZ03p01KSkJ2djbkcrnK5rQ+Pj5wdXWlgJH0a9u2bUN7ezsiIiJUHs/MzERAQABmzZqFo0ePDviZbaRXogCFkP6Kz+cjJCQEhYWF+OCDD7B161bo6+uzXRZhgUQiwfHjxxEZGYn79+9jyZIl2LhxI4YOHcp2aWQAOnHiBN566y3s3r0bK1asAPBoH5558+bh/PnzOHz4MBYtWsRylSQ+Ph7r169HamoqeDweoqKiMGXKFLbL6ldaW1uRm5vLhCp8Ph8PHz6EoaEhPD09mdN+fH19aTNv0m/I5XKMGDECFRUVWL58OXbv3g11dXWUlpbC29sbjo6OuHDhArS0tNgulZDuUIBCSH8mlUoRExOD8PBwmJubY8+ePZg5cybbZZEeogxONm3ahIqKCixZsgTh4eGwtrZmuzQywH322WdYv349fvzxR/j5+eGVV17BzZs3IZVK4ebmhrS0NLZLHJAUCgViY2MRFRWF9PR0TJ06FVu2bIGHhwfbpQ0IMpkMhYWFKkco5+fnQ0NDA1wuV+UIZWdnZ7bLJeSZnD9/numLqqurY9asWYiJicHLL78MDoeDxMREGBsbs1wlIb+LAhRCBoLq6mqEhYXhyJEjCAoKwt69e2Fra/vE76mvr4e5uXkPVUieJ7lcjlOnTmHdunUoKyvD/PnzERERATs7O7ZLI4SxYsUK7N+/H2ZmZqivr4dEImG+lpWVBVdXVxarG1jkcjni4uIQERGB7OxsBAYGYuPGjXBzc2O7tAGvuroaGRkZTKiSkZEBkUgEKysrldN+3N3daXNm0icEBQXh0qVLTJuvqakJHR0dmJqaIjU1FVZWVixXSMgTnaAFloQMAFZWVjh8+DAuX76M4uJiODk5ISIiAiKRqNvnCwQCeHh44Ndff+3hSslfIZfL8dNPP8HR0RELFizA5MmTUVBQgMOHD1N4QnqdBQsWQC6Xo7a2ViU80dLSwjfffMNiZQOHss0YO3Ys5syZg6FDhyIzMxPnzp2j8KSXsLKyQnBwMKKjo8Hn89HY2IjExESEhYVBV1cXO3bsgK+vL8zMzODj44MPP/wQP/30E+rr69kunZAuKioqcP78eZU2XyqVor29HXK5HAKBgMXqCHk6NAOFkAFGIpFg3759WLduHaytrbF3715MmzZN5Tlr1qzBtm3bYGhoiMzMTIwZM4alage2srIySCSSP/z3V844CQ8Px+3btzF37lxs2bKF/ruRXuvSpUuYM2cOJBIJpFJpl6/r6uqipqaGjmP/E0Qi0VPPQFAu79u6dSvu3LmDuXPnYtOmTXBwcHjBVZIXoaSkhFny03lzWjs7O2bJj4+PDyZOnEibchJWbdiwAdu2bVMJUJQ4HA6MjIxw6dIlTJw4kYXqCHkqtISHkIGqpKQEK1asQFxcHObNm4c9e/bAwsIC+fn5GD9+PGQyGTQ1NTF8+HBkZmbSBnY9rLKyEl5eXvDy8sJ///vfbp+j3K8gPDwcN27cwNy5c7F582bY29v3cLWEPL39+/fjgw8+APAo/OuOhoYG9uzZwzyPPFlbWxteffVV7Ny5E+7u7r/7PLFYjBMnTiAqKgrl5eWYP38+1q9fT21GP9PS0oK0tDTmtJ/k5GQIhUIYGRnBw8ODOe2Hx+NBV1eX7XLJACGRSDB06NAnzo7S0NCAtrY2zpw50+XiHiG9BAUohAx0586dw/Lly9Hc3IyIiAicPn0aKSkpzNUBDocDf39/XLhwARoaGixXOzDU1taCx+OhrKwMcrkcN2/eVNkwUBmcREREICcnh64ekz4jISEBL7/8MuRyOZ7U/VBXVweXy0V+fn4PVtc3CQQCTJ8+HcnJyZg5cybi4uK6PEd5hPnmzZtRW1uLN954A+Hh4Rg9ejQLFZOeJpVKUVRUxOyjkpiYiLKyMmhqasLe3p4JU/z8/DBixAi2yyX91MmTJ/H3v//9iW2/hoYGZDIZgoODcerUKXA4nB6skJCnQgEKIeRRB3zTpk344osvIJPJunxdQ0MDoaGh2L59OwvVDSwPHz6En58fCgsLIZFIwOFwmI4E8Oho0TVr1iArKwuBgYGIiorChAkTWK6akKdXUFCA0NBQXLhwAerq6r87CwUAkpKS4O3t3YPV9S1CoRAzZsxAamoqJBIJ1NTUkJWVxbQJAoEABw4cwOeff476+nq8/fbb2LBhA2xsbFiunLCtqqqKWfLD5/ORnp4OsVgMKysrldN+PDw86DhZ8lz4+/sjKSmp234m8Cg4t7Ozw65duxAUFNTD1RHy1ChAIYQ80tLSghEjRuDhw4e/e3Xgu+++wzvvvNPDlQ0cLS0tCAgIwK1bt1TWB6upqeHrr7/GgQMHkJGRgcDAQERGRtIaYdKnxcfHY8WKFSgqKoJCoejS7nA4HPz973/H0aNHWaqwd2tvb8err76KpKQkZh8ZDoeDwMBAHDlyBN999x22bduGlpYWvPvuuwgLC8PQoUNZrpr0VgKBANnZ2UygkpKSgoaGBujr62PChAlMqMLj8WBmZsZ2uaSPuXv3Luzt7bvtX2pqasLAwAARERFYtmwZzXYmvR0FKISQR5YuXYr9+/d3u6GjEofDQWJiIjw9PXuwsoFBKBRi2rRpSE9P77K5mqamJqRSKWbNmoXIyEiacUL6DblcjqNHjyI0NBTNzc1d2h8Oh4PKykoMHjyYpQp7J7FYjNmzZyM+Pr7bNtvExARyuRxLly5FaGgoHUlPnolyc1plqFJQUACFQsFsTqsMVZycnGhzWvJEoaGh2Lt3r0r/hsPhQF1dHStXrsTatWtp03DSV1CAQggBMjMz4eHh8cSp9MCjpTwmJibIycmhKeDPkVgsRmBgIK5evfrEACstLe2JG0QS0lcJBAJ8/vnniI6OhlwuZzrZmpqa+Oyzz7B69WqWK+w9xGIx5syZg19//bXb9kJTUxNcLhfXrl2jmQLkuaqtrUVaWprK0p+Ojg5YWFjA3d2dOe3Hx8cHOjo6bJdLeon29nZYWlqipaUFwKM2SiaT4bXXXsMXX3wBW1tblisk5E+hAIWQgU4ul8PT0xOZmZlP3NhLicPhwNnZGcnJybR7/3MgkUgwe/bs3x0MKWlqamL69OndbhBJSH9RUVGBNWvW4Pjx49DU1IREIoGtrS1KS0vpCjcehSd/+9vfcOnSpSe2F+rq6sjPzweXy+3B6shAI5VKkZubyxyhnJCQgHv37kFTUxMuLi7MLBV/f38MGTKE7XIJS77//nv84x//gJqaGhQKBfz8/LB79264urqyXRohz4ICFEIGutbWVhw9ehRpaWlITk7GnTt3oFAooKWlBZlM1u1mX5qamnj99ddx/PhxFiruP2QyGd58803873//e+JgqLPU1FR4eHi84MoIYVdGRgZWrlyJpKQkAMDFSJP39AAAIABJREFUixcxffp0lqtil0QiwWuvvYYLFy78YXvB4XDwxhtv4MiRIz1UHSGPVFVVMbNTkpKSkJ2dDblcrrI5rY+PD1xdXaGurs52uaQHuLu7IyMjA6NGjcKuXbsQHBzMdkmE/BUUoBBCVLW0tCA9PR2pqam4fv06rl+/jgcPHkBNTQ1aWloQiUTMc6OjoxEWFvZC6pBIJGhra0NbWxtEIhGam5sBAG1tbV32CBEKhSp1AY82XjUxMenyc42NjaGurg5dXV3o6OjAxMQE2tra0NfXfyF/x++Ry+VYtGgR/vvf//7ujvSPU1NTw/Tp03HhwoUXXB0hvcOZM2ewevVqjB8/HqdPn+72OVKpFK2trRAIBOjo6GDaipaWli6vre4e09HR6TKbTvmYhoYGjIyMoK+vD21t7W7blJ4gkUgwd+5cnD9//qnDVnV1dRQVFdFRxYRVbW1tyMnJUQlVmpqaYGhoiPHjxzOhiq+v73N7fcXExGD69OkYM2bMc/l5fVV7ezs6OjrQ1NSEjo4OtLe3QyaTMUtplLp7DAAMDQ2hqamp8piRkRE0NDRU+lA6OjrQ09Prtobs7GzMmDEDEREReO+997r8PEL6IApQCCF/rKKiAqmpqUhNTWWuKHV0dEBdXR1nz55FYGBgt98nEolQU1ODyspK1NfXo6mpCY2NjWhsbFS5r/xcKBSivb0dzc3Nf7gfy4tgaGgIbW1tGBkZwcDAAGZmZszN1NRU5XNzc3NYWFhg6NChMDY2/lO/R6FQ4L333sOBAwe6fE25+7xykKeuro7BgwfDzs4Ozs7OsLOzQ2hoKLS1tf/6H0xIL9LY2Ijq6mpUV1ejvr6eaRsePHiA1NRUmJqaoqWlBY2NjRAIBGhra0Nra+tTBwrPi3LgYGpqCj09PQwaNEilbRg0aBDz2ODBg2FpaQkbG5tnXvIolUoxb948xMbG/u7fqqGhwWw23TkgWrVqFXbs2PFMv5eQF0Emk6GwsJAJVDIzM5Gfnw8NDQ1wuVyVI5SdnZ2f6XcMHz4cNTU12LBhA8LCwvr0McwymQy1tbWorKxEXV0dGhoaVPpOjY2NKo8JBAKIRCI8fPiwx2s1NjaGjo4O9PX1YWJiwmxePXz4cFhaWqq0lYMHD4aNjQ0sLCwoVCF9DQUohJA/TyaTITs7G+fPn0d2djZ4PB4aGxtRWVnJBCY1NTWor69X+T49Pb1uwwjl5/r6+tDR0YGxsTG0tbVhYGAAfX19aGlpwdTUFED3V4u1tLS6zCBRXpXuTC6XM1enlbNWmpqaIBaLIRAI0NraCrFYjObmZrS1tXXppDQ1NaGhoaFLx0RPTw9Dhw6FpaUlrK2tmQGTra0tRo4ciZEjR2LQoEHM81euXIl///vfKt9va2sLLpeL0aNHw87OjrnZ2tr26c4fIcCjq9AlJSUoKSlBWVkZ7t27h5qaGty/fx/V1dWorKxEe3s783x1dfVugwnlfX19fRgYGKiEnnp6eswVUeDR6+rxoFHZnnQmEAggFou71CuRSJh2pPNMOOVV3YcPH3ZpJxoaGpjb41d0TU1NMXToUFhbW8PKygo2NjawsbFRea1zOByV75FKpXjzzTdx8uRJqKurqxz3rKmpCQsLC4wYMQKjRo2Cra0thg8fztxsbW1pnyrSJ1RXVyMjI4MJVTIyMiASiWBlZcVsTMvj8eDu7v6HFw9qampgZWUF4FGwaGdnh4MHD8LHx6cn/pQ/rba2VqVtrK6uRkVFBdM+1tbWqoSiOjo6XdrDzp93ni33ezNtTUxMuuwp1d1jTU1NKp8rFAqm/9O5D6Wc3dLc3AyRSIS2tjamv9RdyPN4W29hYQFra2sMHToUNjY2sLS0xIgRI2BnZ4dRo0bB0tLyuf6bE/IXUYBCCPl9HR0dKCgoQEFBAW7fvo2SkhKUlpaipKQE1dXVTEfe1NSUGQxYWFgwH4cNG4YhQ4Zg2LBhMDc37ze78svlctTX1zNXhTp3dJQfKyoqUFVVxcykMTIygp2dHUxNTSEWi8HlcjFp0iS89NJLcHBwYPkvIuSvE4lEKCgoQF5eHoqKiphBQUlJCWprawE8WoZmZWWFYcOGwdLSEsOGDYOVlRXTeVYGkZ0Dx75KKpXiwYMHTEBUVVWFqqoqVFZWorq6Gvfv30dFRQUzSNHQ0MCwYcMwatQoJlTJy8tDVVUVHBwcVAKSESNGwNLSkvaQIP2SRCLBjRs3mCU/V69exYMHD6CnpwdXV1cmVJkyZUqXI7pPnTqFefPmMf0TDQ0NyOVyLFiwALt27WLlSO/GxkbcvHkT+fn5uHPnjkrbKBAIADy6EGRra6vSPtrY2Ki0j5aWlr+7VKYvEQqFqK2t7dIe1tTUoKKiAtXV1SgvL2eWZuvp6alcWBozZgwcHR0xbtw4OqKdsIECFELIo45+Xl4e8wafn5+PvLw8lJaWQiaTgcPhMJ165YyKzje29gXo7cRiMcrLy1FaWtrldufOHeZKjrm5OcaOHQtHR0c4OzvDyckJrq6u9O9KeiWFQoG7d+8iJycHeXl5TNtRXFwMqVQKLS0tjBo1imkzOgcCdnZ2/SZIfV6amppQXFzMDKiU94uLi3Hv3j0oFAro6enByckJY8eOhbOzM8aNGwdXV1c62YQMGCUlJcySn86b09rZ2TFLfnx8fHDs2DHExMR0mVXG4XBgaGiIXbt2YfHixS+kRpFIhNzcXNy4cQN5eXm4desW8vLyUF1dDeDRLI8xY8Z0aRdHjRoFGxsbCkQ7kcvlqKysVGkTlffv3LnDBM8WFhZMuzh27FiMGzcOEyZMoPcZ8iJRgELIQKNcf5yZmcncsrOzIRQKweFwMGzYMDg5OTEDeWdnZzg7O9Ob0QvQ1NSEvLw8JrDKz8/HzZs3mav1yunLyhuPx4OZmRnLVZOBRjm9XtlepKam4sGDBwD+//+j1F68GCKRCHfv3mX2iVC2E6WlpVAoFF3aCB8fH2a5IyH9WUNDA1JSUpCSkoKkpCSkp6dDKBQyewF1R7lExdfXF99++y3s7e3/Ug2dQx3lraOjA1paWhg9ejTTLirbyJEjR9Jx7M/J4/2nzMxM5Obmoq2tDZqamrC3t1dpGz08PGg5NHleKEAhpL/r6OjA9evXcfXqVSQkJCA9PR0CgQA6OjpwcXGBm5sb3NzcMGnSJDg6OtJmXr1AVVUVMjMzmUFrRkYGamtroa6uDgcHB/j7+8PPzw/+/v7MWm9CnpeysjJcvnwZV65cQUJCAioqKqCmpgZ7e3t4eHjA3d0d7u7ucHFxoT02WNLQ0ID09HSVW01NDTQ0NODs7IwpU6ZgypQp8Pf3p5lsZECQSCRITU1FQEDAH55sp6mpCXV1dXz66adYu3btUw2sZTIZMjMzmbYxJSUFra2t0NXVxYQJE5h20cPDA6NHj6bZJCxQKBQoLi5GWloa0y4qLxAaGBhg8uTJTNvo7u5O/V3yrChAIaS/kUql4PP5uHLlCq5evYrU1FSIRCLY2toiICCA2YjN2dm5y4aFpPeqqKhAZmYmrl+/joSEBGRkZEAqlYLL5cLf3x/+/v6YPn06rQcmf1p9fT0uXrzIDAxKS0uhq6sLHo+HgIAATJ48GW5ubn/6tCnSs+7du4f09HQkJSXhypUruHHjBtTU1ODq6oopU6bg5ZdfRkBAAJ3gRfqtxMRE+Pn5PfXz1dXVweVycfDgQUyePLnL1/Py8nDp0iVcvnwZ165dQ0tLC6ysrDBlyhT4+vrC09MTY8eOpb5ULyaVSnHr1i2kpaUhMTERly9fRlVVFQwNDeHr64spU6Zg2rRpcHFxYbtU0ndQgEJIf9DY2IjffvsN586dQ2xsLJqammBlZQUfHx9MnToVPB7vmY8DJL2TQCBASkoKs8leYmIiJBIJXF1dERQUhODgYEycOJGmC5NulZaW4uzZs4iNjUVCQgIUCgVcXFwwdepUTJ06FT4+PrQMp49rbW1Famoq4uPjER8fj6ysLOjq6uKll15CcHAwZs+eDQsLC7bLJOS52b59O9avXw+JRPKnvk9NTQ1Lly7Fpk2bkJeXh9jYWPz8888oLCyEoaEhPD09mbaR3lf7vpKSEsTHxzMXG+/fvw9bW1vMmDEDQUFBmDFjBi33IU9CAQohfVVtbS1OnDiBU6dOITk5GRoaGvDz80NgYCCCgoIwevRotkskPai1tRWXLl1CXFwc4uLiUFdXh5EjR2LWrFl466234OHhwXaJhGW3b9/G4cOHcfr0aRQUFMDMzAyBgYGYPXs2ZsyYAQMDA7ZLJC/Q/fv3ce7cOZw5cwZXr16FXC6Hr68v5s2bh/nz59PeKaTPCw4ORlxcHHMCj7q6OjQ1NSGTyVSW9Whra2Po0KEYMWIEbG1tIZPJUFxcjLy8PDQ3N8PR0RGzZ8/GrFmz4OnpSctx+jGFQoGMjAycOXMGZ8+exa1bt2BqaoqZM2diwYIFmD59OjQ0NNguk/QuFKAQ0pe0t7fj559/xpEjR3Dp0iXo6elhzpw5CA4OxvTp02FkZMR2iaQXkMvlSE9Px7lz53Dq1CkUFhbCwcEBCxcuxMKFC2Fra8t2iaSHtLS04Mcff8T333+PpKQkWFtb4+9//ztmzZoFHx8fWgM+QLW0tOD8+fPMoEEul2P27NlYsmQJpk2bRgMG0ucoFAoMGTIELS0tsLCwwPDhwzFq1CgMGzYMNjY2sLGxga2tLWxsbGBqaoo7d+7g0KFDOHz4MCoqKjB58mS89tprmDNnDsaMGcP2n0NYUlxcjLNnzzIXJ62srLBo0SIsWbIEDg4ObJdHegcKUAjpC4qKirB792788MMPEAqFmDFjBhYuXIjZs2fTJo7kD6Wnp+Po0aM4fvw46uvrERAQgOXLl2P27Nl0Za2fysvLwxdffIH//ve/NDgmT9Q5ZEtOTsbQoUPx/vvvIyQkBIMGDWK7PEKeilwuR319/ROP9pbL5Thz5gx2794NPp9Pg2PyRI+HbF5eXli5ciXmzp1L76MDGwUohPRmV65cwc6dO/HLL79g1KhRCAkJwZtvvknr1skzkUgkuHjxIr799lvExsbCzs4OK1euxJIlS6Cvr892eeQ5SExMxPbt2xEXFwcHBwcsX76clmeQp3bnzh0cPHgQ+/fvh0gkwrvvvovQ0FCatUb6NJFIhMOHD2PHjh24e/cugoOD8f7779PyDPJU5HI5fvvtN+zfvx+nT5/GyJEjsWrVKixZsoQuYg5MFKAQ0hvFx8cjLCwMWVlZ8PPzQ2hoKIKDg2m2AHlubt++jV27duHw4cPQ0dHBqlWr8NFHH1FnoI+6fv06Vq1aheTkZPB4PHzyyScICgqiNoM8k7a2Nhw4cAC7du1CVVUVFi1ahC1bttCx6aRPkclk+PbbbxEZGYmmpiYsXLgQq1evptkm5JndvXsXO3bswKFDh2BkZIR169YhJCSElsMOLCeoZ0VIL1JUVITg4GBMmzYN1tbWSE9PR0JCAi21IM+dvb09vvrqK5SXl2P58uX47LPP4ODggOPHj4Ny9b6juroaS5Ysgbe3N7S1tZGUlAQ+n49Zs2ZRm0GemYGBAVauXIm7d+/i4MGDuHz5MrhcLj7//HOIxWK2yyPkD127dg1ubm5YsWIF3nzzTZSWluLAgQMUnpC/ZPTo0fj6669RVlaGJUuW4JNPPsGECRPw22+/sV0a6UHUuyKkFxCJRPj4448xbtw4VFRUID4+HmfPnoWbmxvbpZF+ztzcHBEREbh9+zamTp2KhQsXwtvbG4WFhWyXRv5ATEwMuFwurl69ih9//BGXL1+Gt7c322WRfoTD4WDRokUoKCjAqlWrEBERgXHjxiE5OZnt0gjpVnNzMxYsWICAgABYWlri5s2b2LlzJ82eIs+VhYUFtm3bhry8PIwaNQpTp07FvHnz0NjYyHZppAdQgEIIy+7evQsej4f9+/dj7969yMzMxMsvv8x2WWSAsbKywnfffYeMjAzI5XK4u7vj8OHDbJdFutHa2oo33ngDH374IVauXImCggK8/vrrbJdF+jFdXV1s3LgRBQUFsLe3R0BAAHbt2kWz1UivkpOTAzc3N1y9ehVnz57F+fPnweVy2S6L9GOjRo3Czz//jIsXLyItLQ0TJ05EWloa22WRF4wCFEJY9NNPP2HSpEkAgMzMTLz33nu0oRlhlaurK/h8Pt5//30sWbIES5YsgUgkYrss8n8KCgrg7u6OhIQE/Prrr9i0aRPtW0N6zPDhw3H27Fls3rwZn3zyCebNmweBQMB2WYTg+++/h5eXF4YPH46srCwEBQWxXRIZQKZPn46srCw4OTnB19cXX3/9NdslkReIAhRCWPLNN99g/vz5WLx4MZKSkjB69Gi2SyIEwKNp+zt27MC5c+fw888/Izg4GEKhkO2yBrybN28iICAAgwYNQnZ2NqZMmcJ2SWQAUlNTwyeffILffvsN165dw8yZMylEIaz68ssv8c477+Cjjz7CpUuX6KRCwopBgwYhNjaW2Vh2+/btbJdEXhA6hYcQFpw+fRrz5s1DZGQk1q9fz0oNSUlJKC0tVXlMU1MTxsbGMDMzw7hx46Cnp8d87cGDB7h48SLz+bRp07p0UkQiEU6fPg2ZTAYAUFdXxyuvvAIzMzOIRCIcOnQIubm5sLa2ho+PDzw8PPDrr78iODj4qWouKCjAtWvXcOvWLZiZmcHNzQ1Tp06lK/AvUHZ2NqZNmwY/Pz+cPHmSNiZlSU1NDdzd3TFq1CjExcWxcuz00aNH//A5ZmZmmDlzpspjlZWV+Omnn3Dnzh0MGjQIAQEB8PLywr179yCTydDY2IiysjLm+WpqahgyZAhGjhwJW1tbcDicp6qP2oeel5eXhylTpoDH4+HUqVPUPpAed+rUKcybNw/btm3Dxx9/zEoNT9s2mpub4/bt2yqPa2pqYv78+b/7fdR36pv27t2LFStW4PDhw1i4cCHb5ZDn6wQUhJAeVVJSojAwMFCEhISwWodcLldcuHBBoaampjAxMVGEh4cr/vOf/yi2bNmimDNnjkJHR0fx6quvKgoKCpjvqa2tVbz33nsKAIrJkycrOjo6uvzcpqYmxeLFixXe3t6KiooK5jEnJyfFu+++q0hNTVVcunRJ8dZbbyk0NDQUK1eu/MNa29raFCtXrlRMnDhR8euvvyoePHigyM7OVnz00UcKR0dHRVZW1jP9G3RXP+kqMTFRoa2trdi+fTvbpQxIcrlcMW3aNMWYMWMUjY2NrNUxaNAgxYYNGxR79uxRbNiwQQFA4evrq4iJiVFs375dMX36dIWDg4PK92zdulVhY2OjiI6OVuTk5Cjq6+sVFy5cUPj7+ysGDx6s+N///qeQy+WKX375RQFAYW5urvj8888VERERCkdHR4WlpaXi4sWLT6yL2gd2JSYmKrS0tBS7du1iuxQywJSXlysMDQ1Z70/9mbbx2rVrCg6HowCg+PnnnxUCgeB3fy71nfq21atXK3R1dRV37txhuxTyfB2nAIWQHhYcHKwYO3Zsr3kDMjMzU3C53C6Px8fHKywtLRU6Ov+vvTuPiuLK/gD+BZp9kU0bEESQqKwKso5G3A8SDW7EoLiNiSNRsxizmHGMJsTJNpPJGDzxOEcDJyYGjJEtiRJliQsCGqM0YEAQAYUICjQNdEtzf3/kR4UWFE2UYrmfczjVXVVdfVuby3u3Xr0yoOzsbI1tY8aMIQC0cuXKbo/5+eef05YtW4Tnzz//PLm6ulJ7e7vGfs8999x9NQJCQ0PJxcWFmpubu2x76623SE9Pj86cOdPjce708ssvk1qtfuDXDUbvvPMOGRoaCkUx1nvi4+NJR0eHTp8+LWocmZmZwuPCwkICQFFRUcK69vZ2jZzw0Ucfka6uLp04caLLsVpaWiggIID27t0rrDMzMyN3d3fheV1dHbm4uJCWlhb99NNPd42L84P43nzzTTIxMaFff/1V7FDYIBIeHk5jx46llpYWUeN40Nw4cuRIsrKy6vG43Hbq31QqFY0bN46eeOIJsUNhDxcXUBjrTTKZjLS0tCglJUXsUAQ2NjbdFlCIiFJTUwkADR8+XKPg4+PjQ0FBQQSg27OO8fHx9O677wrPg4KCaPz48V32Ky8vp5deeume8cXExBAA+uyzz7rd3tjYSBYWFuTp6Ukqleqex+rswoULZGxszI2A+6RUKsne3p5eeeUVsUMZdAICAig8PFzsMDR+V7rrJBCRUGz94osvCIBGHrhTTk4Offjhh8Jza2tr8vDw0Njn73//OwGg1157rdtjcH7oGxQKBVlbW9P27dvFDoUNEqWlpaSjo0MJCQlih/JAuZGIaPTo0WRra9vjcbnt1P+lpqaSlpYWyWQysUNhD8+Xkl6/aoixQeybb76Bra1tlzkC+qrQ0FBMnz4dx44dQ0JCgsZ1nIcOHYKfnx82bdoEDw8PzJgx467HcXV1xd69e7Fhwwb861//gp6eHoDf7ugQEhJyzxi2bdsGbW1tREREdLvd1NQU8+fPx969e5GQkAAdHR20t7dDV1dXuLXrwYMHcfv2bRgaGmLevHk4efIklixZAoVCgQMHDkBXVxfh4eEAgNbWViQkJEAmkyEoKAizZs3SuE5YqVQiMzMTmZmZsLOzQ0hICEaNGiVsv3LlCvbt24fXX38dNTU1+OyzzyCVShEREQFzc3NcvnwZCQkJ0NPTw6pVq2BhYaHxeRobG/HVV1+hsLAQzs7OWLlyJUxMTO75b9Qb9PT0sHz5csTHx/PEaL2opqYGOTk52Lp1q9ih3Nf8FgEBAQCA6OhoALhnrvPz8+vxNrhmZmYAgMrKym63c37oG/nByMgIixcvRlJSUp/4rrKBLzU1Faamppg3b57YoTxQbnwQ3Hbq/7lx9uzZkEqlSEpKgpubm9jhsIeEZ/tirBdduHABgYGB0NLSEjuU+xYUFAQASE9P11hvY2ODw4cPQ09PD4sXL8bly5fveozNmzfD2toan3zyCTw9PfH9998L22bNmnXX1127dg03btyAra2t0HDojqOjIwDg/PnzCA0NRUxMDFavXi1snzhxIv75z38iKioKAEBEePzxxwEAQ4YMwZAhQwAA5eXlmDVrFpRKJdavX4+dO3fCw8MDra2tAH5rIISEhODWrVt45ZVXQETw9vbGoUOHAAAHDhzA448/jrfeegupqanYunUrSkpKsGHDBqxevRpZWVnYsmUL8vPz8dprr3WZWKy4uBiRkZFwdHTEihUrsHv3bowfPx719fV3/ey9KSgoCCUlJXzHjV6Un58PIvpDjW+xlJSUoKCgABKJBGPGjLnnvv7+/vfc/uWXXwIApk+f3mUb54e+lR8CAgKE7ytjj1p+fj58fHwgkQzcc8Hcdur/uVFLSwv+/v7Iz88XOxT2MIk2+IWxQSg0NJRWrFghdhga7nUJDxFRXFwcAaCZM2cK63x8fITHHUP13d3dqbGxkYi6XsJD9NuwTy8vLwJAAGj27Nn0yy+/3DO27777Tpiw9l727t1LAITrTNevX09mZmYa+zzzzDNkY2MjPN++fTsB0Li2eObMmbRmzRrheUpKCmlpadGhQ4eIiGjJkiW0atUqjeMuWrRIY26QjuMmJiYK+zz33HMEgOLi4oR1W7ZsIQDU0NCg8f7ffPNNl8//j3/8456fv7dkZmYSALp+/brYoQwahw8fJgCkVCrFDkXD3YapExGlpaURgC4TyvbE2tqaHB0dKTc3l06cOEFPP/20MNfSnXMAEHF+6Gv5ITExkQD0mfm92MC2ZMkSCgsLEzuMLu6VGzvc7yU8RNx2Ggi5MTIykubOnSt2GOzh+ZJHoDDWi6RSKaqqqsQO44F0jDYYOnRot9sjIiLw+uuvQyaTITIy8q5nHz09PXH27Fl8/PHHsLCwwHfffYdx48bh6NGjd33vjrMbjY2N94yx4z2trKwAdD+ctqchtiUlJUhLS9MYDvzEE0+guroa8+fPR3NzMxISEuDt7a3xuqioKLS0tGDfvn0AIAwZnTx5srDPuHHjAACTJk0S1o0dOxYAhO/D9evXkZaWhlOnTmHz5s3YvHkzUlNT4evri+bm5nvG3lsqKiogkUhgbW0tdiiDxrBhwwCgX+WNP3NGWEdHB+Xl5cjNzcWsWbNw/vx57Nu3r9tRe5wf+l5+sLCwgL6+vtihsEGgP7an/ghuO/X/3FhZWQkbGxuxw2AP0cAd98ZYHzRp0iSsX78ecrkcpqamYodzXy5dugQA97x285133kF+fr5w/buXl1e3+0kkEjz//PNYunQpNm7ciLi4OCxevBhXrlwR/uB31vGe5eXl94yxY34EDw+P+/pM3SksLASALtfMdnRgT506hdu3b3fpHD722GMAgF9++QXA742Nzh2+7joUHcNqb9++DeC3IagA8Oqrr/bZAsX333+PwMDAAT1kuq/x9vaGoaEh0tLSsGbNGrHDuS8dvxPFxcVoaWnRuA6+J0ZGRli4cOF97cv5oW9JS0vDX/7yF7HDYINEUFAQdu7cidra2j77O/GwcNvpd/0tNzY2NiI7OxsrV64UOxT2EPEIFMZ60YIFCyCRSLBr1y6xQ7kvKpUKKSkpkEgkmD9//l3309bWxv79++Hq6oro6GgkJCRobH/vvfc0nltZWSE2NhYRERGor6/HyZMnuz3ukCFD4O3tDYVCcc85VoqKiqCtrY2ZM2c+wKfT1NHJO3LkSJdtN27cgFqtBvBbY6Czjj/Yo0eP/sPvDfzeKDh37lyXbXK5/E8d+2GoqKhAQkICVqxYIXYog4qBgQEWLVqETz75BO3t7WKHc1+GDx8Od3d3qNXqHq/7vtuItfvB+eE3fSE/lJSUICUlpcvcBIw9KqGhoTAzM0NMTIzYoTx0HUUBbjv1rK/nxt27d0NXVxdhYWFih8IeIi6gMNaLzM3NsXHjRkRHR6O0tFTscHr0wQcfoKSkBC+++GKPs4fzrlcxAAAVOklEQVSbmZkhKSkJFhYWXQooP/74I6qrq7u8ZsGCBQC6nrnobNeuXdDS0rrrnV8qKyvx9ddfY/369Rg/frwQi1Kp1NiPiIQ/5J11rHNzc4O2tjaSk5M19rt8+TLy8vLg7e0NfX39Lg2WGzduAIAwsdofNWbMGOjo6ODNN9+ESqXSOP7+/fv/1LH/LCJCVFQUHB0dsWzZMlFjGYw2b96MS5cu4b///a/YoQg6Ch93K4Bs374dwG9nBTt/nzu7ceOGMHy741gPWlDh/NA38sO6deswduxY4e4djD1qxsbG2LRpE95//32UlJSIHY6gp9x45353am9vx549ewBw2+l+9OXcWFFRgejoaLzwwgswNzcXNRb2kPX6tCuMDXJKpZLGjx9Pnp6eGpNgiUGlUpGOjk6XSWRbW1vpxRdfJF1dXdq8eXOXSQGlUikpFIpuj5mWlkY6Ojoak8jOnj2bZs6cSXK5XGPfefPmkZeXV48TZEZHR5OBgQGlp6drrG9oaKCQkBCaPHmyxrH37NlDAOjo0aPU3t5OBw4cIHd3d9LT06P6+npqa2ujXbt2EQDKzs6mrKwsamlpoZUrVxIAmj9/Ph07dow++eQTioiIECZL27RpEwGg48ePC+/18ccfU3h4uLDP22+/TQCoqqqqSzwymUxY1zH57qlTp4R169atEyZ+279/P+3bt49mzpxJ9fX19/z3edS2bt1Kurq6dOLECVHjGMzeeust0tfX7zP/B8ePHycAFBkZedd9oqOjSUtLi5YvX05NTU0a28rLy2njxo2kUqmI6Le8qK2tTQ4ODg8cC+cHcfPDtm3bSFdXl06fPi1qHGzwUalU5O3tTV5eXl3aF2K5n9xoampKEomkS9uqtbWV1q1bRzExMUTEbaf+nBubm5vJ19eX3NzcqKWlRbQ42CPxJRdQGBPB1atXyc7OjgICAujmzZuixJCVlUULFy4kACSRSMjb25vmz59PCxcupDlz5tDatWvp7NmzGq85d+4cPfPMMwSAwsPDKS0trdtj/+c//9EooCxdupQWLlxI3t7etGrVKnrjjTfI3d2dpkyZQmVlZfcVb3p6Oo0bN47++te/0s6dO2nTpk0UEBBAO3bsILVarbGvQqEgDw8PAkBSqZRiY2NpzZo1ZGFhQZs2baLa2loqLS0lqVRKFhYW9L///Y+IfmtUzJ8/X5jtfuTIkZSbmyscV61W08aNG2no0KH02muv0YoVK+ipp54S/jgePXpUeN+1a9fSpUuX6NtvvyU/Pz+hQXXhwgU6fvw4TZo0iQDQokWLqKCgQIh7+fLlwvubmZlpzCwvhnfeeYe0tLSEfyMmDrVaTfPmzSNzc3M6c+aMqLHs379f+E6bm5tTdHS0cCeFOx08eJA8PDzI0NCQgoODad26dfTss8/Stm3bhMZ/ZmYmLViwQPjeR0VFUU5OzgPFxPlBHB999BFpaWnRp59+KmocbPC6cuUKSaVSevzxx4U7AYqlp9yYnZ1NS5cuFX6H7e3tyc/Pj/z9/cnLy4tMTU1JS0uLKisriYjbTv01NyoUCpoxYwZZWVlRcXGxaHGwR+ZLLaI/cQEyY+wPKy4uxowZM6Crq4uvvvoKEyZMEDukh6rzxG5VVVUYPnw4iAj5+fmoq6vDqFGj4ODg8MDHbWhogEwmg729PUaMGHHX/Trea9SoUTAyMkJxcTHs7e01JrS8ffs22traukxyee3aNdy4cQNubm7Q1dXtcuyWlhYUFRXB1dUVBgYGD/wZelJbW4urV6/C1dX1gSbgfJiampoQFRWFL774AjExMVi7dq0ocbDfKZVKLFy4EBkZGdi9ezeWLl0qdkj3TaFQ4OLFi3BxcXmkE/1xfugdKpUKL7/8MmJiYvDhhx9i48aNosTBGAAUFBRg+vTpsLa2xsGDBzFmzBixQ3oouO30YPpCbiwtLUV4eDiuXr2KtLQ04fIoNqAc4AIKYyK6ceMGli9fjmPHjuHtt9/Gq6++2u3tOhnrTQUFBVi8eDGqq6sRGxuL0NBQsUNi/6+trQ1btmzB+++/j8jISOzevVu0hiIbnCorK/HUU08hPz8fe/bsweLFi8UOiTH+XjLRpaamYtmyZXB0dMTBgwcxatQosUNij8YBnkSWMRENHToUqamp2Lp1K7Zs2YKZM2fi559/FjssNkjJ5XK88cYbmDBhAqysrPDzzz9z8aSPkUgkePfdd3Hw4EEkJSUhICAA6enpYofFBoG2tjbExMRg3LhxkMvlyMvL404q6zPs7e2RkZGBFStWICIiAsuWLUNVVZXYYbFBoKamBqtXr8bcuXOxcOFCnD59mosnAxwXUBgTmba2NrZs2YIff/wRcrkcEyZMwLPPPtvtzOuMPQpqtRp79uzBY489hk8//RQ7duzAsWPHYGdnJ3Zo7C4WLFiAc+fOwdHREdOmTUN4eDiuXLkidlhsgDp27Bi8vb2xceNGPPPMMzhz5syfvv0oYw+bnp4edu7cicOHD+PUqVMYO3YsduzYgdbWVrFDYwOQSqXChx9+iNGjR+OHH35AfHw89uzZ80guT2J9CxdQGOsjAgMDkZ2djdjYWBw5cgSjR4/Gyy+/jPLycrFDYwOUUqnE3r174eXlhXXr1mHx4sUoLi7GSy+9BB0dHbHDYz1wdnZGcnIyvv32W1y8eBFubm7YsGEDysrKxA6NDRCZmZkIDQ3FjBkz4OTkBJlMhvfeew9GRkZih8bYXT355JOQyWTYvHkzduzYAVdXV8TExKC5uVns0NgA0Nrait27d8PNzQ1bt27FSy+9hMLCQr6N+yDCBRTG+hAtLS0sXboUly5dwtatWxEfHw8XFxdEREQgNzdX7PDYAFFbW4vo6Gg4OjoiKioKfn5+uHjxIj7++GNYWVmJHR57QLNnz8bFixfx/vvvIzk5GaNHj8aSJUvw008/iR0a64fa29tx6NAhBAYGYsqUKVAoFDh69CiSkpLg4uIidniM3RcDAwO88cYbuHTpEmbPno1XXnkFjo6O2L59O2pra8UOj/VDt27dwo4dOzBy5Ei88MILmDZtGgoLC7Ft2zYuKg8yPIksY33Y7du3ER8fj3//+984d+4cAgMDERkZiaeffpo7uuyBqNVqpKWl4fPPP8ehQ4dgaGiIv/3tb9iwYQNsbW3FDo89JG1tbfjqq6/wwQcf4Oeff8bkyZOxatUqLFq0CCYmJmKHx/qwq1evIjY2FrGxsSgrK0NYWBheffVVBAYGih0aY3/ar7/+ip07d2LXrl1obW3FokWLsGrVKgQHB/Pk/eyuiAgnTpzAZ599hvj4eEgkEqxduxYvvPACbGxsxA6PiYPvwsNYf5GRkYG9e/fim2++gUqlwuzZs7Fs2TLMmTMH+vr6YofH+qjz588jLi4OBw4cQHV1NYKCgrB8+XJERkbC2NhY7PDYI0JEOHr0KPbs2YOUlBRIJBIsWrQIK1euxOTJk6GtzQNQGdDc3Iyvv/4asbGxSE9Ph5WVFZYsWYKoqKgBcytYxjprampCbGws9u3bh7Nnz2LkyJFYsWIFli9fDmdnZ7HDY31EeXk54uLiEBcXh5KSEowfPx6rVq3CypUrYWZmJnZ4TFxcQGGsv2lpaUFKSgri4uLw/fffQ09PD9OmTcPcuXMxZ84cnvhzkFOr1Th9+jRSUlKQmJiIoqIijBgxAhEREVi9ejUee+wxsUNkvay+vh7x8fGIi4vDyZMnMXToUISEhCA8PByzZs3iAuwgc/PmTRw7dgzJyck4fPgwmpubMXXqVKxZswZhYWHQ09MTO0TGekVhYaEw6qq6uhpubm5CW2rixIk8MmWQKS0tRXJyMhISEnDq1CmYm5sjPDwca9aswYQJE8QOj/UdXEBhrD+7du0aEhMTkZycjPT0dKhUKvj7+2Pu3LmYMWMGfHx8IJFIxA6TPWIVFRU4fvw4UlNTceTIETQ2NsLDwwNz5sxBWFgYAgICuCHIAAAymQyHDh1CYmIizp07BxMTE4SEhGDu3LmYPn06F2AHICKCTCbDkSNHkJSUhJMnT0JXVxfTpk1DWFgY5s+fj6FDh4odJmOiaWtrww8//IDDhw8jOTkZ165dg5OTE5588kk88cQTmDhxIs9xMQC1tLTg9OnT+Pbbb3H48GFcvnwZUqkUTz75JMLCwjBr1izo6uqKHSbre7iAwthAoVAokJaWhpSUFKSmpqK6uhqmpqaYNGkSJk+ejODgYPj5+XFBZQAoKytDVlYWMjIykJmZibKyMujp6SE4OFg4e+bk5CR2mKyPq6ioQHJyMhITE5GRkQGVSoWxY8di6tSpmDp1KoKDgzFs2DCxw2R/QFFREdLT05GRkYGMjAz8+uuvsLS0RGhoKMLCwhASEsJz4jDWDSJCbm4uEhMTkZSUhPz8fOjp6SEgIADTpk3D1KlTERgYyCP3+iGVSoUzZ87g+PHjyMjIQHZ2NlpbWzF27FiEhYUJJ5z4ElfWAy6gMDYQEREKCgqQmZmJrKwsZGZmorq6GsbGxvD394efnx98fX3h6+vLHe0+rqGhAWfPnkVeXh7y8vKQnZ2NiooKGBgYwN/fH1OmTEFwcDACAwP5DBn7wxQKBU6ePCl0uvPy8qBWq+Hu7o6AgAD4+fnB398fnp6eXITtY+RyOc6ePYucnBzk5OTg1KlTuH79OkxNTTF58mRMmTIFU6dOxfjx4/n25Iw9oGvXruH48eNIT09Heno6ysrKYGhoCH9/f+HHz88Pjo6OYofK7lBRUYHc3FwhN545cwbNzc1wdHQUThRMnToVDg4OYofK+hcuoDA2WBQVFSErKwunT59GXl4eCgsLoVarYWVlJRRTvLy84ObmhtGjR/N18CKoqKhAYWEh8vPzhaJJcXExiAi2trbw9fWFn58fgoOD4e/vDwMDA7FDZgOUXC5HVlYWsrKykJOTg7Nnz0Iul8PQ0BDe3t7w8/ODj48P3N3d4ebmBkNDQ7FDHhTq6upw8eJFyGQy5OXlIScnB0VFRWhvb4ednR38/f0RGBiI4OBg+Pr6crGLsYesvLwc6enpOHHiBHJzcyGTyaBWqzFs2DChmOLl5QVPT084OTnxaIZe0N7ejitXriA/Px8XLlwQiibV1dXQ0dGBq6sr/P39MXHiREyZMoUnC2Z/FhdQGBusFAoFzp8/L4xsOHv2LH755Reo1WpIJBK4uLjA3d0drq6ucHd3x5gxY+Dk5ARzc3OxQ+/XVCoVysvLUVJSAplMhqKiIuTn56OwsBCNjY0AAKlUCh8fH6GwNWHCBAwfPlzkyNlgplarUVRUhJycHKFxevHiRahUKmhra8PZ2RkeHh5wc3ODp6cnxo4di1GjRsHU1FTs0PulmpoalJSUoKCgAPn5+ZDJZMjPz0dNTQ0AwNzcHD4+PhpnwTlHMNb7FAoFzp07J+TG3NxclJWVgYhgZGQktKHc3d3h4eGB0aNHw9HRkefW+APa2tpQXl6O4uJiXLx4UciPhYWFUCgUAICRI0fC19dXGDk5YcIEvlyRPWxcQGGM/U6pVKKoqEijUy+TyXD58mXcvn0bAGBpaQknJyc4OztrLB0cHGBnZ4chQ4aI/CnEpVQqUVNTg8rKSly5cgWlpaUoLS1FWVkZSktLUVVVBbVaDQCwtbWFm5sb3NzcNIpVVlZWIn8KxnrW1taGkpISoYPf0ckvLi5GW1sbAGDo0KEYNWqU8OPs7IxRo0bB3t4etra2g3YeAblcjsrKSlRUVKC0tBSXL18WfkpLS9HU1AQAMDExgaurKzw9PYXilJubG+zt7UX+BIyxu2lqakJBQYFGJ18mk6GqqgoAIJFI4ODg0CUvOjk5wc7ODlKpdFBO/E5EqKmpwfXr13HlyhWNvHj58mVcvXpV+Ntia2sLDw8PjeKUm5sb32KY9QYuoDDGeqZSqYQCQMey8+OOkRMAYGhoiOHDh8PGxkZY2tnZYdiwYbC0tISFhQUsLS2Fn77egSIi3Lx5E7du3cLNmzeFn7q6OlRXV6OqqkpjWVtbK7xWV1cXI0aMgLOzc5eCk4uLC4/mYQOSSqUSCgF3LktLS9Ha2irsa21tDVtbW9jb20MqlcLBwQFSqRTW1tawsrKClZUVLC0tYWVl1efPItbV1Wnkh5s3b6K2thaVlZWorq7WWHacLQUACwsLjU5U5+WIESMGZUeKsYGovr4eJSUl3ebHyspKtLe3A/itwCKVSmFvbw8bGxs4ODjAxsYGNjY2GjmxP7SjVCqVRk7sWFZXV6O6uhoVFRWoqakRlh0n67S0tGBvb99tXnRxcYGlpaXIn4wNYlxAYYz9eXV1dbh27RoqKyuF0Rc1NTWoqqoSlrW1tRqdhg7GxsZCI8DAwACmpqYwNjaGnp4eLCwsoK+vDyMjI5iamgrX85uZmXWZDNHCwkLjeXNzM5RKpca6xsZGYfRHQ0MDVCoV5HK5sO+tW7egUqmgUCjQ0NAgdIbupKurC0tLS6GB07EcNmyYxnM7OzuetJGxTogI169fF4oJFRUVXYoLNTU1qKurEzoTHfT09ISOg6GhIczNzWFoaAgDAwOYm5tDX18fxsbGGrnC3NxcowChq6vbpRBz69YtjecdOQAAWltb0dLSgvr6eiiVSigUCsjlcrS2tkIul0MulwudgjubU/r6+rCyssLw4cNha2srLDs6Rfb29rC3t++Suxhjg49KpcLVq1fvmh+vX7+OmpoayOXyLq81MTHRyI1GRkYwMzODgYEBTExMYGJiAn19fWGEcHd50MjISKMQ0zkPdmhqahIKHI2NjVAqlZDL5WhqaoJSqURDQwNaWlrQ3Nws5MWO0XR3xiuVSrvkw87FIkdHxz5dGGKDGhdQGGO9R6lUCkWJO0d03Lx5U+iUKBQKKJVK1NfXCx2YjuIHEaG+vl7juG1tbV0aFR2Fl846NxBMTU2hr68PMzMzYX3ngs2QIUM0Rsp0/uF5HRh79O4czdH5cUdRo6WlBa2trUKuaG5uRkNDA9rb26FWqzVGxwG/F0Q6u7Mgq62tLXQ0OucDfX19mJiYwNTUVCj2mpqaCh2XziNmLC0t+/yIGcZY/3P79u1uc2LH444CRmNjI1pbW9HU1KRR9AW6z4OdTzABmnmwg4GBgTBheOc2lLGxMQwMDDBkyBAYGRnB0NBQyIOdc2LHY75JAevnuIDCGGOMMcYYY4wx1oMDfG8txhhjjDHGGGOMsR5wAYUxxhhjjDHGGGOsB1xAYYwxxhhjjDHGGOuBBECC2EEwxhhjjDHGGGOM9WFn/g/6Q2U/uGQZrgAAAABJRU5ErkJggg==", + "text/plain": [ + "" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "viz = web_analysis_bn_full.to_graphviz()\n", + "viz.draw('web_analysis_full.png', prog='dot')\n", + "Image('web_analysis_full.png')" + ] + }, + { + "cell_type": "code", + "execution_count": 21, "id": "a6346742-dc39-40e3-8673-686b25fb7d87", "metadata": {}, "outputs": [], @@ -238,7 +292,7 @@ }, { "cell_type": "code", - "execution_count": 94, + "execution_count": 180, "id": "f78e3c55-3826-4622-b720-74452c7c13a2", "metadata": {}, "outputs": [], @@ -248,7 +302,7 @@ }, { "cell_type": "code", - "execution_count": 95, + "execution_count": 181, "id": "3d63e9c3-0430-4bc1-a5e3-583ae71f3405", "metadata": {}, "outputs": [ @@ -259,7 +313,7 @@ "" ] }, - "execution_count": 95, + "execution_count": 181, "metadata": {}, "output_type": "execute_result" } @@ -336,50 +390,32 @@ }, { "cell_type": "code", - "execution_count": 80, + "execution_count": null, + "id": "5c1d1232-ed7a-4539-82bf-e43fd52b8f23", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 62, "id": "509c45ee-b22d-461a-998b-a701c5090580", "metadata": {}, "outputs": [], "source": [ - "cpd_resolver_config = TabularCPD(\n", - " \"Resolver config\",\n", - " variable_card=3,\n", - " values=[\n", - " # These values were estimated based on a query against the OONI dataset from 2024-01-01 to 2024-08-10\n", - " # with this query:\n", - " # -- ## quad_resolvers\n", - " # -- 15169, # Google LLC\n", - " # -- 13335, # Cloudflare Inc\n", - " # -- 42, # WoodyNet, Inc. | quad9\n", - " # -- 36692, # Cisco OpenDNS, LLC\t\n", - " # SELECT \n", - " # CountIf(resolver_asn IN (15169, 13335, 42, 36692)) as quad_external_count,\n", - " # CountIf( \n", - " # (resolver_asn = probe_asn OR resolver_as_cc = probe_cc) \n", - " # AND NOT (resolver_asn IN (15169, 13335, 42, 36692)) \n", - " # ) as provider_vp_consistent,\n", - " # CountIf( \n", - " # (resolver_asn != probe_asn AND resolver_as_cc != probe_cc) \n", - " # AND NOT (resolver_asn IN (15169, 13335, 42, 36692)) \n", - " # ) as provider_non_vp_consistent,\n", - " # COUNT() as total_count\n", - " # FROM obs_web\n", - " # WHERE \n", - " # measurement_start_time > '2024-01-01' \n", - " # AND measurement_start_time < '2024-08-10'\n", - " [0.56],\n", - " [0.08],\n", - " [0.36],\n", - " ],\n", - " state_names={\n", - " # provider_vp_consistent: means the resolver is consistent with the country and/or AS of the probe and is \n", - " # not a quad (eg. 8.8.8.8, 9.9.9.9, etc.) or third party resolver\n", - " # provider_non_vp_consistent: means the resolver is not a quad resolver, \n", - " # but is not consistent with the metadata of the probe\n", - " # quad_external: means the resolver is something like quad9, google, cloudflare, etc.\n", - " \"Resolver config\": [\"provider_vp_consistent\", \"provider_non_vp_consistent\", \"quad_external\"]\n", - " },\n", - ")\n", + "dns_answer_states = [\n", + "\"answer_is_bogon\", \n", + "\"answer_matches_probe_asn\", \n", + "\"answer_matches_probe_cc\",\n", + "\"answer_is_cloud_provider\",\n", + "\"answer_other\"\n", + "]\n", + "dns_failure_states = [\n", + " \"none\",\n", + " \"nxdomain\",\n", + " \"server_failure\"\n", + "]\n", + "tls_consistency_states = [\"tls_consistent\", \"tls_inconsistent\", \"unknown\"]\n", "cpd_dns_ctrl_failure = TabularCPD(\n", " \"DNS Ctrl Failure\",\n", " variable_card=3,\n", @@ -389,194 +425,124 @@ " [0.002],\n", " ],\n", " state_names={\n", - " \"DNS Ctrl Failure\": [\"none\", \"nxdomain\", \"server_failure\"]\n", + " \"DNS Ctrl Failure\": dns_failure_states\n", " },\n", ")\n", - "cpd_dns_answer_meta = TabularCPD(\n", - " \"DNS Answer Meta\",\n", - " variable_card=7,\n", - " # These values were calculated using the following query.\n", - " # WITH\n", - " # (dns_answer IS NOT NULL \n", - " # AND ip_asn IN (13335, 209242, 20940, 9002, 16625, 63949, 16509, 14618, 15169, 396982, 54113, 8075, 8068)\n", - " # ) as is_cloud_provider\n", - " # SELECT \n", - " # CountIf(is_cloud_provider) as cloud_provider,\n", - " # CountIf(\n", - " # dns_answer IS NOT NULL AND ip_is_bogon AND NOT is_cloud_provider\n", - " # ) as answer_is_bogon,\n", - " # CountIf(\n", - " # dns_answer IS NOT NULL AND ip_asn = probe_asn AND NOT is_cloud_provider\n", - " # ) as answer_matches_probe_asn,\n", - " # CountIf(\n", - " # dns_answer IS NOT NULL AND (ip_cc = probe_cc AND NOT ip_asn = probe_asn AND NOT is_cloud_provider)\n", - " # ) as answer_matches_probe_cc,\n", - " # CountIf(\n", - " # dns_answer IS NOT NULL AND (ip_cc != probe_cc AND ip_asn != probe_asn AND NOT ip_is_bogon AND NOT is_cloud_provider)\n", - " # ) as answer_ok,\n", - " # COUNTIf(dns_failure IS NOT NULL) as dns_failure,\n", - " # COUNT() as total_count\n", - " # FROM obs_web\n", - " # WHERE \n", - " # test_name = 'web_connectivity'\n", - " # AND measurement_start_time > '2024-01-01' \n", - " # AND measurement_start_time < '2024-08-10'\n", - " ## The list of cloud providers was manually curated\n", - " # CLOUD_PROVIDERS_ASNS = [\n", - " # 13335, # Cloudflare: https://www.peeringdb.com/net/4224\n", - " # 209242, #\tCloudflare London, LLC\t\n", - " # 20940, # Akamai: https://www.peeringdb.com/net/2\n", - " # 9002, # Akamai RETN\n", - " # 16625, # Akamai Technologies, Inc.\t\n", - " # 63949, # Akamai Technologies, Inc.\t\n", - " # 16509, #\tAmazon.com, Inc.\n", - " # 14618, #\tAmazon.com, Inc.\t\n", - " # 15169, #\tGoogle LLC\n", - " # 396982, # Google Cloud: https://www.peeringdb.com/net/30878\n", - " # 54113, #\tFastly, Inc\n", - " # 8075, # Microsoft Corporation\n", - " # 8068, #\tMicrosoft Corporation\n", - " # ]\n", + "cpd_dns_vp_failure = TabularCPD(\n", + " \"DNS VP Failure\",\n", + " variable_card=3,\n", " values=[\n", - " # \"none\", \"nxdomain\", \"server_failure\"\n", - " [0.0238, 0.9, 0.015],\n", - " [0.01, 0.03, 0.91],\n", - " [0.003745, 0.014, 0.015],\n", - " [0.004537, 0.014, 0.015],\n", - " [0.060217, 0.014, 0.015],\n", - " [0.19626, 0.014, 0.015],\n", - " [0.700935, 0.014, 0.015]\n", + " # \"none\", \"nxdomain\", \"server_failure\"\n", + " [0.994, 0.02, 0.02],\n", + " [0.004, 0.98, 0.01],\n", + " [0.002, 0.01, 0.98],\n", " ],\n", - " # parents={parents}\n", " evidence=[\"DNS Ctrl Failure\"],\n", " evidence_card=[3],\n", " state_names={\n", - " \"DNS Answer Meta\": [\n", - " \"answer_failure_nxdomain\",\n", - " \"answer_failure_other\",\n", - " \"answer_is_bogon\", \n", - " \"answer_matches_probe_asn\", \n", - " \"answer_matches_probe_cc\",\n", - " \"answer_is_cloud_provider\",\n", - " \"answer_ok\"\n", - " ],\n", - " \"DNS Ctrl Failure\": [\"none\", \"nxdomain\", \"server_failure\"]\n", + " \"DNS VP Failure\": dns_failure_states,\n", + " \"DNS Ctrl Failure\": dns_failure_states\n", " },\n", ")\n", - "cpd_dns_tls_consistency = TabularCPD(\n", - " \"DNS TLS Consistency\",\n", + "cpd_dns_failure_consistency = TabularCPD(\n", + " \"DNS Failure Consistency\",\n", " variable_card=3,\n", " values=[\n", - " # answer_failure_nxdomain, answer_failure_other, answer_is_bogon, \n", - " # answer_matches_probe_asn, answer_matches_probe_cc, \n", - " # answer_is_cloud_provider, answer_ok,\n", - " [0.96, 0.96, 0.0, 0.05, 0.05, 0.9, 0.94], # tls_consistent\n", - " [0.02, 0.02, 0.02, 0.8, 0.8, 0.08, 0.04], # tls_inconsistent\n", - " [0.02, 0.02, 0.98, 0.15, 0.15, 0.02, 0.02], # tls_connection_failed\n", - " # [0.96],\n", - " # [0.02],\n", - " # [0.02]\n", + " # \"none\", \"nxdomain\", \"server_failure\"\n", + " [0.99, 0.01, 0.01, 0.94, 0.01, 0.01, 0.94, 0.01, 0.01], # ok\n", + " [0.01, 0.05, 0.05, 0.01, 0.98, 0.92, 0.01, 0.92, 0.98], # expected_not_ok\n", + " [0.01, 0.94, 0.94, 0.05, 0.01, 0.07, 0.05, 0.07, 0.01] # unexpected_not_ok\n", " ],\n", - " evidence=[\"DNS Answer Meta\"],\n", - " evidence_card=[7],\n", + " evidence=[\"DNS Ctrl Failure\", \"DNS VP Failure\"],\n", + " evidence_card=[3, 3],\n", " state_names={\n", - " \"DNS TLS Consistency\": [\"tls_consistent\", \"tls_inconsistent\", \"tls_connection_failed\"],\n", - " \"DNS Answer Meta\": [\n", - " \"answer_failure_nxdomain\",\n", - " \"answer_failure_other\",\n", - " \"answer_is_bogon\", \n", - " \"answer_matches_probe_asn\", \n", - " \"answer_matches_probe_cc\",\n", - " \"answer_is_cloud_provider\",\n", - " \"answer_ok\"\n", + " \"DNS Failure Consistency\": [\n", + " \"ok\", \n", + " \"expected_not_ok\",\n", + " \"unexpected_not_ok\"\n", " ],\n", + " \"DNS VP Failure\": dns_failure_states,\n", + " \"DNS Ctrl Failure\": dns_failure_states\n", + " },\n", + ")\n", + "\n", + "cpd_dns_answer = TabularCPD(\n", + " \"DNS Answer\",\n", + " variable_card=5,\n", + " values=[\n", + " [0.004],\n", + " [0.006],\n", + " [0.06],\n", + " [0.73],\n", + " [0.2],\n", + " ],\n", + " state_names={\n", + " \"DNS Answer\": dns_answer_states,\n", + " },\n", + ")\n", + "cpd_dns_answer_tls_consistency = TabularCPD(\n", + " \"DNS Answer TLS Consistency\",\n", + " variable_card=3,\n", + " values=[\n", + " # \"answer_is_bogon\", \"answer_matches_probe_asn\", \"answer_matches_probe_cc\", \"answer_is_cloud_provider\", \"answer_other\"\n", + " [0.01, 0.80, 0.75, 0.90, 0.94], # tls_consistent\n", + " [0.05, 0.15, 0.20, 0.08, 0.04], # tls_inconsistent\n", + " [0.94, 0.05, 0.05, 0.02, 0.02], # unknown\n", + " ],\n", + " evidence=[\"DNS Answer\"],\n", + " evidence_card=[5],\n", + " state_names={\n", + " \"DNS Answer TLS Consistency\": tls_consistency_states,\n", + " \"DNS Answer\": dns_answer_states,\n", " },\n", ")\n", - "cpd_dns_consistency = TabularCPD(\n", - " \"DNS Consistency\",\n", + "cpd_dns_answer_consistency = TabularCPD(\n", + " \"DNS Answer Consistency\",\n", " variable_card=2,\n", " values=[\n", - " # answer_failure_nxdomain, answer_failure_other, answer_is_bogon, answer_matches_probe_asn, \n", - " # answer_matches_probe_cc, answer_is_cloud_provider, answer_ok\n", - " # tls_consistent, tls_inconsistent, tls_connection_failed\n", - " \n", - " # answer_failure_nxdomain, tls_consistent, tls_inconsistent, tls_connection_failed\n", - " [0.01, 0.001, 0.001,\n", - " # answer_failure_other, tls_consistent, tls_inconsistent, tls_connection_failed\n", - " 0.01, 0.001, 0.001,\n", - " # answer_is_bogon, , \n", - " 0.03, 0.01, 0.01,\n", - " # answer_matches_probe_asn\n", - " 0.999, 0.001, 0.3,\n", - " # answer_matches_probe_cc\n", - " 0.999, 0.001, 0.2,\n", - " # answer_is_cloud_provider\n", - " 0.98, 0.001, 0.1,\n", - " # answer_ok\n", - " 0.9999, 0.01, 0.2 \n", - " ],\n", - " [0.99, 0.999, 0.999,\n", - " # answer_failure_other, tls_consistent, tls_inconsistent, tls_connection_failed\n", - " 0.99, 0.999, 0.999,\n", - " # answer_is_bogon,\n", - " 0.97, 0.99, 0.99,\n", - " # answer_matches_probe_asn\n", - " 0.001, 0.999, 0.7,\n", - " # answer_matches_probe_cc\n", - " 0.001, 0.999, 0.8,\n", - " # answer_is_cloud_provider\n", - " 0.02, 0.999, 0.9,\n", - " # answer_ok\n", - " 0.0001, 0.99, 0.8\n", - " ],\n", + " # \"answer_is_bogon\", \"answer_matches_probe_asn\", \"answer_matches_probe_cc\", \"answer_is_cloud_provider\", \"answer_other\"\n", + " # tls_consistent\", \"tls_inconsistent\", \"unknown\n", + " [0.99, 0.001, 0.001, 0.999, 0.01, 0.3, 0.999, 0.001, 0.3, 0.999, 0.01, 0.8, 0.999, 0.001, 0.2], # consistent\n", + " [0.01, 0.999, 0.999, 0.001, 0.99, 0.7, 0.001, 0.999, 0.7, 0.001, 0.99, 0.2, 0.001, 0.999, 0.8], # inconsistent\n", " ],\n", " # parents={parents}\n", - " evidence=[\"DNS Answer Meta\", \"DNS TLS Consistency\"],\n", - " evidence_card=[7, 3],\n", + " evidence=[\"DNS Answer\", \"DNS Answer TLS Consistency\"],\n", + " evidence_card=[5, 3],\n", " state_names={\n", - " \"DNS Answer Meta\": [\n", - " \"answer_failure_nxdomain\",\n", - " \"answer_failure_other\",\n", - " \"answer_is_bogon\", \n", - " \"answer_matches_probe_asn\", \n", - " \"answer_matches_probe_cc\",\n", - " \"answer_is_cloud_provider\",\n", - " \"answer_ok\"\n", - " ],\n", - " \"DNS TLS Consistency\": [\"tls_consistent\", \"tls_inconsistent\", \"tls_connection_failed\"],\n", - " \"DNS Consistency\": [\n", + " \"DNS Answer\": dns_answer_states,\n", + " \"DNS Answer TLS Consistency\": tls_consistency_states,\n", + " \"DNS Answer Consistency\": [\n", " \"consistent\",\n", " \"inconsistent\"\n", - " # TODO(consistent UP and consistent DOWN)\n", " ],\n", " },\n", ")\n", + "\n", "cpd_dns_outcome = TabularCPD(\n", " \"DNS Outcome\",\n", " variable_card=3,\n", " values=[\n", - " # none, nxdomain, server_failure (ctrl failure)\n", - " # consistent, inconsistent (consistency)\n", - " # none, consistent, inconsistent\n", - " [0.1, 0.9, 0.2, 0.8, 0.1, 0.7],\n", - " [0.9, 0.1, 0.0, 0.0, 0.8, 0.1],\n", - " [0.0, 0.0, 0.8, 0.2, 0.1, 0.2],\n", + " # Consistent, inconsistent\n", + " [0.01, 0.01, 0.40, 0.8, 0.20, 0.90], # blocked\n", + " [0.99, 0.01, 0.40, 0.2, 0.05, 0.01], # ok\n", + " [0.00, 0.98, 0.20, 0.0, 0.75, 0.09], # down\n", " ],\n", " evidence=[\n", - " \"DNS Ctrl Failure\",\n", - " \"DNS Consistency\",\n", + " \"DNS Answer Consistency\",\n", + " \"DNS Failure Consistency\",\n", " ],\n", - " evidence_card=[3, 2],\n", + " evidence_card=[2, 3],\n", " state_names={\n", " \"DNS Outcome\": [\n", " \"blocked\",\n", " \"ok\",\n", " \"down\"\n", " ],\n", - " \"DNS Ctrl Failure\": [\"none\", \"nxdomain\", \"server_failure\"],\n", - " \"DNS Consistency\": [\n", - " \"consistent\",\n", - " \"inconsistent\"\n", + " \"DNS Answer Consistency\": [\"consistent\", \"inconsistent\"],\n", + " \"DNS Failure Consistency\": [\n", + " \"ok\", \n", + " \"expected_not_ok\",\n", + " \"unexpected_not_ok\"\n", " ],\n", " },\n", ")" @@ -584,8 +550,156 @@ }, { "cell_type": "code", - "execution_count": 81, - "id": "85d58bf9-eb93-48fb-96ba-927657cfd1ef", + "execution_count": 63, + "id": "710b4561-7b8f-47fd-a742-dd88e697a1bc", + "metadata": {}, + "outputs": [], + "source": [ + "tcp_failure_states = [\n", + " \"none\",\n", + " \"connection_reset\",\n", + " \"timeout\",\n", + " \"other\"\n", + "]\n", + "\n", + "cpd_tcp_ctrl_failure = TabularCPD(\n", + " \"TCP Ctrl Failure\",\n", + " variable_card=4,\n", + " values=[\n", + " [0.980],\n", + " [0.001],\n", + " [0.014],\n", + " [0.005]\n", + " ],\n", + " state_names={\n", + " \"TCP Ctrl Failure\": tcp_failure_states\n", + " },\n", + ")\n", + "\n", + "cpd_tcp_vp_result = TabularCPD(\n", + " \"TCP VP Result\",\n", + " variable_card=5,\n", + " values=[\n", + " # \"none\", \"connection_reset\", \"timeout\", \"other\"\n", + " [0.980, 0.02, 0.01, 0.01], # none\n", + " [0.001, 0.14, 0.02, 0.06], # connection_reset\n", + " [0.010, 0.05, 0.10, 0.06], # timeout\n", + " [0.009, 0.07, 0.02, 0.12], # other\n", + " [0.009, 0.72, 0.85, 0.75], # down\n", + " ],\n", + " evidence=[\"TCP Ctrl Failure\"],\n", + " evidence_card=[4],\n", + " state_names={\n", + " \"TCP VP Result\": tcp_failure_states + [\"down\"],\n", + " \"TCP Ctrl Failure\": tcp_failure_states\n", + " },\n", + ")\n", + "\n", + "cpd_tcp_outcome = TabularCPD(\n", + " \"TCP Outcome\",\n", + " variable_card=4,\n", + " values=[\n", + " # consistent inconsistent\n", + " # \"none\", \"connection_reset\", \"timeout\", \"other\", \"down\"\n", + " [0.02, 0.95, 0.90, 0.85, 0.01, 0.07, 0.07, 0.07, 0.07, 0.05], # blocked\n", + " [0.95, 0.01, 0.01, 0.01, 0.08, 0.01, 0.01, 0.01, 0.01, 0.01], # ok\n", + " [0.02, 0.03, 0.08, 0.09, 0.01, 0.07, 0.07, 0.07, 0.07, 0.09], # down\n", + " [0.01, 0.01, 0.01, 0.05, 0.90, 0.85, 0.85, 0.85, 0.85, 0.85], # unknown\n", + " ],\n", + " evidence=[\"DNS Answer Consistency\", \"TCP VP Result\"],\n", + " evidence_card=[2, 5],\n", + " state_names={\n", + " \"DNS Answer Consistency\": [\"consistent\", \"inconsistent\"],\n", + " \"TCP VP Result\": tcp_failure_states + [\"down\"],\n", + " \"TCP Outcome\": [\"blocked\", \"ok\", \"down\", \"unknown\"]\n", + " },\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "id": "61234ff3-5e13-48e3-8264-e1966fdd2dc1", + "metadata": {}, + "outputs": [], + "source": [ + "tls_ctrl_failure_states = [\n", + " \"none\",\n", + " \"bad_certificate\",\n", + " \"other\"\n", + "]\n", + "\n", + "tls_vp_result_states = [\n", + " \"none\",\n", + " \"bad_certificate\",\n", + " \"connection_reset_after_ch\",\n", + " \"timeout_after_ch\",\n", + " \"timeout\",\n", + " \"connection_reset\",\n", + " \"other\",\n", + " \"down\"\n", + "]\n", + "\n", + "cpd_tls_ctrl_failure = TabularCPD(\n", + " \"TLS Ctrl Failure\",\n", + " variable_card=3,\n", + " values=[\n", + " [0.980],\n", + " [0.005],\n", + " [0.015],\n", + " ],\n", + " state_names={\n", + " \"TLS Ctrl Failure\": tls_ctrl_failure_states\n", + " },\n", + ")\n", + "\n", + "cpd_tls_vp_result = TabularCPD(\n", + " \"TLS VP Result\",\n", + " variable_card=8,\n", + " values=[\n", + " # \"none\", \"bad_certificate\", \"other\"\n", + " [0.97, 0.02, 0.01], # none\n", + " [0.005, 0.10, 0.01], # bad_certificate\n", + " [0.005, 0.01, 0.05], # connection_reset_after_ch\n", + " [0.005, 0.01, 0.05], # timeout_after_ch\n", + " [0.005, 0.01, 0.05], # timeout\n", + " [0.005, 0.01, 0.05], # connection_reset\n", + " [0.004, 0.02, 0.12], # other\n", + " [0.001, 0.82, 0.66], # down\n", + " ],\n", + " evidence=[\"TLS Ctrl Failure\"],\n", + " evidence_card=[3],\n", + " state_names={\n", + " \"TLS VP Result\": tls_vp_result_states,\n", + " \"TLS Ctrl Failure\": tls_ctrl_failure_states\n", + " },\n", + ")\n", + "\n", + "cpd_tls_outcome = TabularCPD(\n", + " \"TLS Outcome\",\n", + " variable_card=4,\n", + " values=[\n", + " # consistent inconsistent\n", + " # \"none\", \"connection_reset\", \"timeout\", \"other\", \"down\"\n", + " [0.02, 0.95, 0.90, 0.85, 0.01, 0.07, 0.07, 0.07, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02], # blocked\n", + " [0.95, 0.01, 0.01, 0.01, 0.08, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01], # ok\n", + " [0.02, 0.03, 0.07, 0.09, 0.01, 0.07, 0.07, 0.07, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05], # down\n", + " [0.01, 0.01, 0.02, 0.05, 0.90, 0.85, 0.85, 0.85, 0.92, 0.92, 0.92, 0.92, 0.92, 0.92, 0.92, 0.92], # unknown\n", + " ],\n", + " evidence=[\"DNS Answer Consistency\", \"TLS VP Result\"],\n", + " evidence_card=[2, 8],\n", + " state_names={\n", + " \"DNS Answer Consistency\": [\"consistent\", \"inconsistent\"],\n", + " \"TLS VP Result\": tls_vp_result_states,\n", + " \"TLS Outcome\": [\"blocked\", \"ok\", \"down\", \"unknown\"]\n", + " },\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "id": "4a7dff9b-4851-435e-941d-de3e736bc577", "metadata": {}, "outputs": [ { @@ -593,21 +707,44 @@ "output_type": "stream", "text": [ "WARNING:pgmpy:Replacing existing CPD for DNS Ctrl Failure\n", - "WARNING:pgmpy:Replacing existing CPD for DNS Answer Meta\n", - "WARNING:pgmpy:Replacing existing CPD for DNS TLS Consistency\n", - "WARNING:pgmpy:Replacing existing CPD for DNS Consistency\n", - "WARNING:pgmpy:Replacing existing CPD for DNS Outcome\n" + "WARNING:pgmpy:Replacing existing CPD for DNS VP Failure\n", + "WARNING:pgmpy:Replacing existing CPD for DNS Failure Consistency\n", + "WARNING:pgmpy:Replacing existing CPD for DNS Answer\n", + "WARNING:pgmpy:Replacing existing CPD for DNS Answer TLS Consistency\n", + "WARNING:pgmpy:Replacing existing CPD for DNS Answer Consistency\n", + "WARNING:pgmpy:Replacing existing CPD for DNS Outcome\n", + "WARNING:pgmpy:Replacing existing CPD for TCP Ctrl Failure\n", + "WARNING:pgmpy:Replacing existing CPD for TCP VP Result\n", + "WARNING:pgmpy:Replacing existing CPD for TCP Outcome\n", + "WARNING:pgmpy:Replacing existing CPD for TLS Ctrl Failure\n", + "WARNING:pgmpy:Replacing existing CPD for TLS VP Result\n", + "WARNING:pgmpy:Replacing existing CPD for TLS Outcome\n" ] } ], "source": [ - "web_analysis_bn.add_cpds(cpd_dns_ctrl_failure, cpd_dns_answer_meta, cpd_dns_tls_consistency, cpd_dns_consistency, cpd_dns_outcome)" + "cpd_list = [\n", + " cpd_dns_ctrl_failure, \n", + " cpd_dns_vp_failure, \n", + " cpd_dns_failure_consistency, \n", + " cpd_dns_answer, \n", + " cpd_dns_answer_tls_consistency,\n", + " cpd_dns_answer_consistency, \n", + " cpd_dns_outcome,\n", + " cpd_tcp_ctrl_failure,\n", + " cpd_tcp_vp_result,\n", + " cpd_tcp_outcome,\n", + " cpd_tls_ctrl_failure,\n", + " cpd_tls_vp_result,\n", + " cpd_tls_outcome\n", + "]\n", + "web_analysis_bn_full.add_cpds(*cpd_list)" ] }, { "cell_type": "code", - "execution_count": 82, - "id": "6eebd10f-58da-41a8-b2ef-520a1733607c", + "execution_count": 66, + "id": "a2299f85-a607-4198-a0eb-5af82f7317e9", "metadata": {}, "outputs": [ { @@ -616,18 +753,44 @@ "True" ] }, - "execution_count": 82, + "execution_count": 66, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "web_analysis_bn.check_model()" + "web_analysis_bn_full.check_model()" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "id": "73120bce-721a-4965-8a76-a4f37f7be905", + "metadata": {}, + "outputs": [], + "source": [ + "web_analysis_bn_full.save('web-analysis-full.bif')" ] }, { "cell_type": "code", - "execution_count": 83, + "execution_count": null, + "id": "85d58bf9-eb93-48fb-96ba-927657cfd1ef", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6eebd10f-58da-41a8-b2ef-520a1733607c", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 68, "id": "21c4346f-4c39-47fc-9378-306b1bb05d58", "metadata": {}, "outputs": [], @@ -637,17 +800,17 @@ }, { "cell_type": "code", - "execution_count": 84, + "execution_count": 69, "id": "89546053-4dbb-47af-a81d-1ad5bf41f95c", "metadata": {}, "outputs": [], "source": [ - "infer = VariableElimination(web_analysis_bn)" + "infer = VariableElimination(web_analysis_bn_full)" ] }, { "cell_type": "code", - "execution_count": 85, + "execution_count": 70, "id": "cb364bad-0321-4cba-9df6-c6a1cdb9ec05", "metadata": {}, "outputs": [ @@ -658,11 +821,11 @@ "+----------------------+--------------------+\n", "| DNS Outcome | phi(DNS Outcome) |\n", "+======================+====================+\n", - "| DNS Outcome(blocked) | 0.2299 |\n", + "| DNS Outcome(blocked) | 0.0874 |\n", "+----------------------+--------------------+\n", - "| DNS Outcome(ok) | 0.7688 |\n", + "| DNS Outcome(ok) | 0.8945 |\n", "+----------------------+--------------------+\n", - "| DNS Outcome(down) | 0.0013 |\n", + "| DNS Outcome(down) | 0.0181 |\n", "+----------------------+--------------------+\n" ] } @@ -673,9 +836,17 @@ }, { "cell_type": "code", - "execution_count": 86, + "execution_count": null, "id": "a5b30d21-a4c8-4170-ba42-c1727f5131cd", "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 74, + "id": "870bd68f-7969-42c8-9c41-4f8710975497", + "metadata": {}, "outputs": [ { "name": "stdout", @@ -684,23 +855,29 @@ "+----------------------+--------------------+\n", "| DNS Outcome | phi(DNS Outcome) |\n", "+======================+====================+\n", - "| DNS Outcome(blocked) | 0.2176 |\n", + "| DNS Outcome(blocked) | 0.7836 |\n", "+----------------------+--------------------+\n", - "| DNS Outcome(ok) | 0.7812 |\n", + "| DNS Outcome(ok) | 0.2031 |\n", "+----------------------+--------------------+\n", - "| DNS Outcome(down) | 0.0013 |\n", + "| DNS Outcome(down) | 0.0133 |\n", "+----------------------+--------------------+\n" ] } ], "source": [ - "print(g_dist)" + "print(infer.query(\n", + " ['DNS Outcome'], \n", + " evidence={\n", + " #'DNS TLS Consistency': 'tls_inconsistent',\n", + " \"DNS Answer\": \"answer_is_bogon\", \n", + " }\n", + "))" ] }, { "cell_type": "code", - "execution_count": 87, - "id": "870bd68f-7969-42c8-9c41-4f8710975497", + "execution_count": 78, + "id": "8bd01e2f-1baf-4f63-a851-e318f8cb687b", "metadata": {}, "outputs": [ { @@ -710,11 +887,11 @@ "+----------------------+--------------------+\n", "| DNS Outcome | phi(DNS Outcome) |\n", "+======================+====================+\n", - "| DNS Outcome(blocked) | 0.8890 |\n", + "| DNS Outcome(blocked) | 0.0168 |\n", "+----------------------+--------------------+\n", - "| DNS Outcome(ok) | 0.1064 |\n", + "| DNS Outcome(ok) | 0.9646 |\n", "+----------------------+--------------------+\n", - "| DNS Outcome(down) | 0.0046 |\n", + "| DNS Outcome(down) | 0.0186 |\n", "+----------------------+--------------------+\n" ] } @@ -723,16 +900,16 @@ "print(infer.query(\n", " ['DNS Outcome'], \n", " evidence={\n", - " #'DNS TLS Consistency': 'tls_inconsistent',\n", - " \"DNS Answer Meta\": \"answer_is_bogon\", \n", + " 'DNS Answer TLS Consistency': 'tls_consistent',\n", + " \"DNS Answer\": \"answer_matches_probe_cc\", \n", " }\n", "))" ] }, { "cell_type": "code", - "execution_count": 90, - "id": "8bd01e2f-1baf-4f63-a851-e318f8cb687b", + "execution_count": 79, + "id": "02b703c0-429b-4a6f-ae21-2134bbb9a3e4", "metadata": {}, "outputs": [ { @@ -742,11 +919,11 @@ "+----------------------+--------------------+\n", "| DNS Outcome | phi(DNS Outcome) |\n", "+======================+====================+\n", - "| DNS Outcome(blocked) | 0.8991 |\n", + "| DNS Outcome(blocked) | 0.7913 |\n", "+----------------------+--------------------+\n", - "| DNS Outcome(ok) | 0.1008 |\n", + "| DNS Outcome(ok) | 0.1955 |\n", "+----------------------+--------------------+\n", - "| DNS Outcome(down) | 0.0001 |\n", + "| DNS Outcome(down) | 0.0133 |\n", "+----------------------+--------------------+\n" ] } @@ -755,8 +932,8 @@ "print(infer.query(\n", " ['DNS Outcome'], \n", " evidence={\n", - " 'DNS TLS Consistency': 'tls_inconsistent',\n", - " \"DNS Answer Meta\": \"answer_is_cloud_provider\", \n", + " 'DNS Answer TLS Consistency': 'tls_inconsistent',\n", + " \"DNS Answer\": \"answer_matches_probe_cc\", \n", " }\n", "))" ] @@ -764,7 +941,7 @@ { "cell_type": "code", "execution_count": null, - "id": "02b703c0-429b-4a6f-ae21-2134bbb9a3e4", + "id": "ce7f6e84-e728-475c-b075-73404497bd61", "metadata": {}, "outputs": [], "source": [] diff --git a/notebooks/web-analysis-full.bif b/notebooks/web-analysis-full.bif new file mode 100644 index 00000000..4eb90444 --- /dev/null +++ b/notebooks/web-analysis-full.bif @@ -0,0 +1,151 @@ +network unknown { +} +variable DNS Answer { + type discrete [ 5 ] { answer_is_bogon, answer_matches_probe_asn, answer_matches_probe_cc, answer_is_cloud_provider, answer_other }; +} +variable DNS Answer Consistency { + type discrete [ 2 ] { consistent, inconsistent }; +} +variable DNS Answer TLS Consistency { + type discrete [ 3 ] { tls_consistent, tls_inconsistent, unknown }; +} +variable DNS Ctrl Failure { + type discrete [ 3 ] { none, nxdomain, server_failure }; +} +variable DNS Failure Consistency { + type discrete [ 3 ] { ok, expected_not_ok, unexpected_not_ok }; +} +variable DNS Outcome { + type discrete [ 3 ] { blocked, ok, down }; +} +variable DNS VP Failure { + type discrete [ 3 ] { none, nxdomain, server_failure }; +} +variable TCP Ctrl Failure { + type discrete [ 4 ] { none, connection_reset, timeout, other }; +} +variable TCP Outcome { + type discrete [ 4 ] { blocked, ok, down, unknown }; +} +variable TCP VP Result { + type discrete [ 5 ] { none, connection_reset, timeout, other, down }; +} +variable TLS Ctrl Failure { + type discrete [ 3 ] { none, bad_certificate, other }; +} +variable TLS Outcome { + type discrete [ 4 ] { blocked, ok, down, unknown }; +} +variable TLS VP Result { + type discrete [ 8 ] { none, bad_certificate, connection_reset_after_ch, timeout_after_ch, timeout, connection_reset, other, down }; +} +probability ( DNS Answer ) { + table 0.004, 0.006, 0.06, 0.73, 0.2 ; +} +probability ( DNS Answer Consistency | DNS Answer, DNS Answer TLS Consistency ) { + ( answer_is_bogon, tls_consistent ) 0.99, 0.01; + ( answer_is_bogon, tls_inconsistent ) 0.001, 0.999; + ( answer_is_bogon, unknown ) 0.001, 0.999; + ( answer_matches_probe_asn, tls_consistent ) 0.999, 0.001; + ( answer_matches_probe_asn, tls_inconsistent ) 0.01, 0.99; + ( answer_matches_probe_asn, unknown ) 0.3, 0.7; + ( answer_matches_probe_cc, tls_consistent ) 0.999, 0.001; + ( answer_matches_probe_cc, tls_inconsistent ) 0.001, 0.999; + ( answer_matches_probe_cc, unknown ) 0.3, 0.7; + ( answer_is_cloud_provider, tls_consistent ) 0.999, 0.001; + ( answer_is_cloud_provider, tls_inconsistent ) 0.01, 0.99; + ( answer_is_cloud_provider, unknown ) 0.8, 0.2; + ( answer_other, tls_consistent ) 0.999, 0.001; + ( answer_other, tls_inconsistent ) 0.001, 0.999; + ( answer_other, unknown ) 0.2, 0.8; + +} +probability ( DNS Answer TLS Consistency | DNS Answer ) { + ( answer_is_bogon ) 0.01, 0.05, 0.94; + ( answer_matches_probe_asn ) 0.8, 0.15, 0.05; + ( answer_matches_probe_cc ) 0.75, 0.2, 0.05; + ( answer_is_cloud_provider ) 0.9, 0.08, 0.02; + ( answer_other ) 0.94, 0.04, 0.02; + +} +probability ( DNS Ctrl Failure ) { + table 0.994, 0.004, 0.002 ; +} +probability ( DNS Failure Consistency | DNS Ctrl Failure, DNS VP Failure ) { + ( none, none ) 0.99, 0.01, 0.01; + ( none, nxdomain ) 0.01, 0.05, 0.94; + ( none, server_failure ) 0.01, 0.05, 0.94; + ( nxdomain, none ) 0.94, 0.01, 0.05; + ( nxdomain, nxdomain ) 0.01, 0.98, 0.01; + ( nxdomain, server_failure ) 0.01, 0.92, 0.07; + ( server_failure, none ) 0.94, 0.01, 0.05; + ( server_failure, nxdomain ) 0.01, 0.92, 0.07; + ( server_failure, server_failure ) 0.01, 0.98, 0.01; + +} +probability ( DNS Outcome | DNS Answer Consistency, DNS Failure Consistency ) { + ( consistent, ok ) 0.01, 0.99, 0.0; + ( consistent, expected_not_ok ) 0.01, 0.01, 0.98; + ( consistent, unexpected_not_ok ) 0.4, 0.4, 0.2; + ( inconsistent, ok ) 0.8, 0.2, 0.0; + ( inconsistent, expected_not_ok ) 0.2, 0.05, 0.75; + ( inconsistent, unexpected_not_ok ) 0.9, 0.01, 0.09; + +} +probability ( DNS VP Failure | DNS Ctrl Failure ) { + ( none ) 0.994, 0.004, 0.002; + ( nxdomain ) 0.02, 0.98, 0.01; + ( server_failure ) 0.02, 0.01, 0.98; + +} +probability ( TCP Ctrl Failure ) { + table 0.98, 0.001, 0.014, 0.005 ; +} +probability ( TCP Outcome | DNS Answer Consistency, TCP VP Result ) { + ( consistent, none ) 0.02, 0.95, 0.02, 0.01; + ( consistent, connection_reset ) 0.95, 0.01, 0.03, 0.01; + ( consistent, timeout ) 0.9, 0.01, 0.08, 0.01; + ( consistent, other ) 0.85, 0.01, 0.09, 0.05; + ( consistent, down ) 0.01, 0.08, 0.01, 0.9; + ( inconsistent, none ) 0.07, 0.01, 0.07, 0.85; + ( inconsistent, connection_reset ) 0.07, 0.01, 0.07, 0.85; + ( inconsistent, timeout ) 0.07, 0.01, 0.07, 0.85; + ( inconsistent, other ) 0.07, 0.01, 0.07, 0.85; + ( inconsistent, down ) 0.05, 0.01, 0.09, 0.85; + +} +probability ( TCP VP Result | TCP Ctrl Failure ) { + ( none ) 0.98, 0.001, 0.01, 0.009, 0.009; + ( connection_reset ) 0.02, 0.14, 0.05, 0.07, 0.72; + ( timeout ) 0.01, 0.02, 0.1, 0.02, 0.85; + ( other ) 0.01, 0.06, 0.06, 0.12, 0.75; + +} +probability ( TLS Ctrl Failure ) { + table 0.98, 0.005, 0.015 ; +} +probability ( TLS Outcome | DNS Answer Consistency, TLS VP Result ) { + ( consistent, none ) 0.02, 0.95, 0.02, 0.01; + ( consistent, bad_certificate ) 0.95, 0.01, 0.03, 0.01; + ( consistent, connection_reset_after_ch ) 0.9, 0.01, 0.07, 0.02; + ( consistent, timeout_after_ch ) 0.85, 0.01, 0.09, 0.05; + ( consistent, timeout ) 0.01, 0.08, 0.01, 0.9; + ( consistent, connection_reset ) 0.07, 0.01, 0.07, 0.85; + ( consistent, other ) 0.07, 0.01, 0.07, 0.85; + ( consistent, down ) 0.07, 0.01, 0.07, 0.85; + ( inconsistent, none ) 0.02, 0.01, 0.05, 0.92; + ( inconsistent, bad_certificate ) 0.02, 0.01, 0.05, 0.92; + ( inconsistent, connection_reset_after_ch ) 0.02, 0.01, 0.05, 0.92; + ( inconsistent, timeout_after_ch ) 0.02, 0.01, 0.05, 0.92; + ( inconsistent, timeout ) 0.02, 0.01, 0.05, 0.92; + ( inconsistent, connection_reset ) 0.02, 0.01, 0.05, 0.92; + ( inconsistent, other ) 0.02, 0.01, 0.05, 0.92; + ( inconsistent, down ) 0.02, 0.01, 0.05, 0.92; + +} +probability ( TLS VP Result | TLS Ctrl Failure ) { + ( none ) 0.97, 0.005, 0.005, 0.005, 0.005, 0.005, 0.004, 0.001; + ( bad_certificate ) 0.02, 0.1, 0.01, 0.01, 0.01, 0.01, 0.02, 0.82; + ( other ) 0.01, 0.01, 0.05, 0.05, 0.05, 0.05, 0.12, 0.66; + +} From 8c84390f29fe9484d55fa0322c43293a1f4136f7 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arturo=20Filast=C3=B2?= Date: Mon, 26 Aug 2024 14:40:42 +0200 Subject: [PATCH 7/8] Move bayes net analysis notebook to pipeline --- oonipipeline/notebooks/datadir | 1 + .../notebooks}/msmt_feedback_clean.csv | 0 .../notebooks/web-analysis-bn.ipynb | 632 ++++++++++++------ oonipipeline/notebooks/web-analysis-full.bif | 151 +++++ 4 files changed, 579 insertions(+), 205 deletions(-) create mode 120000 oonipipeline/notebooks/datadir rename {notebooks => oonipipeline/notebooks}/msmt_feedback_clean.csv (100%) rename notebooks/web-analysis-bn-simple.ipynb => oonipipeline/notebooks/web-analysis-bn.ipynb (66%) create mode 100644 oonipipeline/notebooks/web-analysis-full.bif diff --git a/oonipipeline/notebooks/datadir b/oonipipeline/notebooks/datadir new file mode 120000 index 00000000..25c0bf37 --- /dev/null +++ b/oonipipeline/notebooks/datadir @@ -0,0 +1 @@ +../tests/data/datadir \ No newline at end of file diff --git a/notebooks/msmt_feedback_clean.csv b/oonipipeline/notebooks/msmt_feedback_clean.csv similarity index 100% rename from notebooks/msmt_feedback_clean.csv rename to oonipipeline/notebooks/msmt_feedback_clean.csv diff --git a/notebooks/web-analysis-bn-simple.ipynb b/oonipipeline/notebooks/web-analysis-bn.ipynb similarity index 66% rename from notebooks/web-analysis-bn-simple.ipynb rename to oonipipeline/notebooks/web-analysis-bn.ipynb index dd9a2eb0..20dbf0d8 100644 --- a/notebooks/web-analysis-bn-simple.ipynb +++ b/oonipipeline/notebooks/web-analysis-bn.ipynb @@ -5,7 +5,16 @@ "execution_count": 1, "id": "99aba231-cfe4-4ecb-8233-b34c90515fe9", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/art/repos/ooni/data/oonipipeline/.venv/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", + " from .autonotebook import tqdm as notebook_tqdm\n" + ] + } + ], "source": [ "import pandas as pd\n", "from IPython.display import Image\n", @@ -15,7 +24,7 @@ }, { "cell_type": "code", - "execution_count": 174, + "execution_count": 2, "id": "c76afe2b-1a36-494f-aa99-c9ae037b39be", "metadata": {}, "outputs": [], @@ -25,179 +34,90 @@ }, { "cell_type": "code", - "execution_count": 175, + "execution_count": 3, "id": "ce851a49-6dab-472d-a5a7-78c41395acca", "metadata": {}, "outputs": [ { "data": { - "text/html": [ - "
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blocked.dns.inconsistent blocked \n", - "\n", - "[286 rows x 4 columns]" + "'20240818234433.791006_VE_webconnectivity_8fac03865551a8eb'" ] }, - "execution_count": 175, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "msmt_feedback" + "msmt_feedback.iloc[283]['measurement_uid']" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, + "id": "f9393b66-f6af-4d17-884d-ffda1683b8f3", + "metadata": {}, + "outputs": [], + "source": [ + "# 20231129041111.939896_NP_webconnectivity_32105af63774eabf" + ] + }, + { + "cell_type": "code", + "execution_count": 5, "id": "1b64f651-0707-4bb9-9205-2df6658ed0eb", "metadata": {}, "outputs": [], - "source": [] + "source": [ + "from pathlib import Path\n", + "from oonidata.dataclient import load_measurement\n", + "from oonidata.apiclient import get_measurement_dict_by_uid\n", + "\n", + "from oonipipeline.netinfo import NetinfoDB\n", + "from oonipipeline.transforms.observations import measurement_to_observations" + ] }, { "cell_type": "code", - "execution_count": null, - "id": "23fff868-7e7f-4961-9fbb-f2857e4cb899", + "execution_count": 53, + "id": "9605bec3-2993-4520-b810-aed279284d00", "metadata": {}, "outputs": [], - "source": [] + "source": [ + "possible_states = {\n", + " 'DNS Ctrl Failure': ['none', 'nxdomain', 'server_failure'],\n", + " 'DNS VP Failure': ['none', 'nxdomain', 'server_failure'],\n", + " 'DNS Answer': [\n", + " 'answer_is_bogon',\n", + " 'answer_matches_probe_asn',\n", + " 'answer_matches_probe_cc',\n", + " 'answer_is_cloud_provider',\n", + " 'answer_other'\n", + " ],\n", + " 'DNS Answer TLS Consistency': [\n", + " 'tls_consistent',\n", + " 'tls_inconsistent',\n", + " 'unknown'\n", + " ],\n", + " 'TCP Ctrl Failure': ['none', 'connection_reset', 'timeout', 'other'],\n", + " 'TCP VP Result': ['none', 'connection_reset', 'timeout', 'other', 'down'],\n", + " 'TLS Ctrl Failure': ['none', 'bad_certificate', 'other'],\n", + " 'TLS VP Result': ['none',\n", + " 'bad_certificate',\n", + " 'connection_reset_after_ch',\n", + " 'timeout_after_ch',\n", + " 'timeout',\n", + " 'connection_reset',\n", + " 'other',\n", + " 'down'],\n", + "}" + ] }, { "cell_type": "code", "execution_count": null, - "id": "dfc9bfb1-8a39-4278-a072-1fb96ed1d2bf", + "id": "83d5ed8f-569b-4345-a09e-c5c388dc31f4", "metadata": {}, "outputs": [], "source": [] @@ -205,22 +125,102 @@ { "cell_type": "code", "execution_count": null, - "id": "8bd8a640-3e6d-4d54-b971-eb3332abcd89", + "id": "23fff868-7e7f-4961-9fbb-f2857e4cb899", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 113, + "id": "dfc9bfb1-8a39-4278-a072-1fb96ed1d2bf", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "WebControlObservation(measurement_meta=MeasurementMeta(measurement_uid='20240804233508.181041_TR_webconnectivity_9a7272e520f3d836', input='https://www.instagram.com/', report_id='20240804T233501Z_webconnectivity_TR_47331_n1_ZXMtX88TjWN1oGmK', measurement_start_time=datetime.datetime(2024, 8, 4, 23, 35, 7), software_name='ooniprobe-android-unattended', software_version='3.8.8', test_name='web_connectivity', test_version='0.4.3', bucket_date='1984-01-01'), processing_meta=ProcessingMeta(processing_start_time=datetime.datetime(2024, 8, 25, 12, 54, 49, 976211, tzinfo=datetime.timezone.utc), processing_end_time=datetime.datetime(2024, 8, 25, 12, 54, 49, 978491, tzinfo=datetime.timezone.utc)), hostname='www.instagram.com', observation_id='20240804233508.181041_TR_webconnectivity_9a7272e520f3d836_0', created_at=datetime.datetime(2024, 8, 25, 12, 54, 49, 976177), ip='157.240.0.174', port=443, ip_asn=32934, ip_as_org_name='Facebook, Inc.', ip_as_cc='US', ip_cc='DE', ip_is_bogon=False, dns_failure=None, dns_success=True, tcp_failure=None, tcp_success=True, tls_failure=None, tls_success=True, tls_server_name='www.instagram.com', http_request_url=None, http_failure=None, http_success=None, http_response_body_length=None)" + ] + }, + "execution_count": 113, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "web_control_observations[1].ip" + ] + }, + { + "cell_type": "code", + "execution_count": 117, + "id": "8bd8a640-3e6d-4d54-b971-eb3332abcd89", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "WebObservation(measurement_meta=MeasurementMeta(measurement_uid='20240804233508.181041_TR_webconnectivity_9a7272e520f3d836', input='https://www.instagram.com/', report_id='20240804T233501Z_webconnectivity_TR_47331_n1_ZXMtX88TjWN1oGmK', measurement_start_time=datetime.datetime(2024, 8, 4, 23, 35, 7), software_name='ooniprobe-android-unattended', software_version='3.8.8', test_name='web_connectivity', test_version='0.4.3', bucket_date='1984-01-01'), probe_meta=ProbeMeta(probe_asn=47331, probe_cc='TR', probe_as_org_name='TTNet A.S.', probe_as_cc='TR', probe_as_name='20160401', network_type='wifi', platform='android', origin='autorun', engine_name='ooniprobe-engine', engine_version='3.22.0', architecture='arm64', resolver_ip='207.211.215.145', resolver_asn=60068, resolver_cc='TR', resolver_as_org_name='Datacamp Limited', resolver_as_cc='GB', resolver_is_scrubbed=False, resolver_asn_probe=60068, resolver_as_org_name_probe='Datacamp Limited'), processing_meta=ProcessingMeta(processing_start_time=datetime.datetime(2024, 8, 25, 12, 54, 49, 974157, tzinfo=datetime.timezone.utc), processing_end_time=datetime.datetime(2024, 8, 25, 12, 54, 49, 976062, tzinfo=datetime.timezone.utc)), observation_id='20240804233508.181041_TR_webconnectivity_9a7272e520f3d836_1', created_at=datetime.datetime(2024, 8, 25, 12, 54, 49), processing_time=None, target_id=None, hostname='www.instagram.com', transaction_id=None, ip='2a03:2880:f223:e5:face:b00c:0:4420', port=443, ip_asn=32934, ip_as_org_name='Facebook, Inc.', ip_as_cc='US', ip_cc='IE', ip_is_bogon=False, dns_query_type='AAAA', dns_failure=None, dns_engine='system', dns_engine_resolver_address='', dns_answer_type='AAAA', dns_answer='2a03:2880:f223:e5:face:b00c:0:4420', dns_answer_asn=32934, dns_answer_as_org_name='Facebook, Inc.', dns_t=0.027259692, tcp_failure='network_unreachable', tcp_success=False, tcp_t=0.468265846, tls_failure=None, tls_server_name=None, tls_version=None, tls_cipher_suite=None, tls_is_certificate_valid=None, tls_end_entity_certificate_fingerprint=None, tls_end_entity_certificate_subject=None, tls_end_entity_certificate_subject_common_name=None, tls_end_entity_certificate_issuer=None, tls_end_entity_certificate_issuer_common_name=None, tls_end_entity_certificate_san_list=[], tls_end_entity_certificate_not_valid_after=None, tls_end_entity_certificate_not_valid_before=None, tls_certificate_chain_length=None, tls_certificate_chain_fingerprints=[], tls_handshake_read_count=None, tls_handshake_write_count=None, tls_handshake_read_bytes=None, tls_handshake_write_bytes=None, tls_handshake_last_operation=None, tls_handshake_time=None, tls_t=None, http_request_url=None, http_network=None, http_alpn=None, http_failure=None, http_request_body_length=None, http_request_method=None, http_runtime=None, http_response_body_length=None, http_response_body_is_truncated=None, http_response_body_sha1=None, http_response_status_code=None, http_response_header_location=None, http_response_header_server=None, http_request_redirect_from=None, http_request_body_is_truncated=None, http_t=None, probe_analysis='http-failure')" + ] + }, + "execution_count": 117, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "web_observations[1]" + ] + }, + { + "cell_type": "code", + "execution_count": 97, "id": "c736483d-b280-4972-aa38-70d272c077a8", "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "WebControlObservation(measurement_meta=MeasurementMeta(measurement_uid='20240804233508.181041_TR_webconnectivity_9a7272e520f3d836', input='https://www.instagram.com/', report_id='20240804T233501Z_webconnectivity_TR_47331_n1_ZXMtX88TjWN1oGmK', measurement_start_time=datetime.datetime(2024, 8, 4, 23, 35, 7), software_name='ooniprobe-android-unattended', software_version='3.8.8', test_name='web_connectivity', test_version='0.4.3', bucket_date='1984-01-01'), processing_meta=ProcessingMeta(processing_start_time=datetime.datetime(2024, 8, 25, 12, 54, 49, 976254, tzinfo=datetime.timezone.utc), processing_end_time=datetime.datetime(2024, 8, 25, 12, 54, 49, 978492, tzinfo=datetime.timezone.utc)), hostname='www.instagram.com', observation_id='20240804233508.181041_TR_webconnectivity_9a7272e520f3d836_1', created_at=datetime.datetime(2024, 8, 25, 12, 54, 49, 976177), ip='185.60.218.174', port=443, ip_asn=32934, ip_as_org_name='Facebook, Inc.', ip_as_cc='US', ip_cc='RO', ip_is_bogon=False, dns_failure=None, dns_success=None, tcp_failure=None, tcp_success=True, tls_failure=None, tls_success=True, tls_server_name='www.instagram.com', http_request_url=None, http_failure=None, http_success=None, http_response_body_length=None)" + ] + }, + "execution_count": 97, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "find_relevant_control(web_observations[0], web_control_observations)" + ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 104, + "id": "f4dc4093-fdfc-410e-b5fa-ea5fada37159", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[WebControlObservation(measurement_meta=MeasurementMeta(measurement_uid='20240804233508.181041_TR_webconnectivity_9a7272e520f3d836', input='https://www.instagram.com/', report_id='20240804T233501Z_webconnectivity_TR_47331_n1_ZXMtX88TjWN1oGmK', measurement_start_time=datetime.datetime(2024, 8, 4, 23, 35, 7), software_name='ooniprobe-android-unattended', software_version='3.8.8', test_name='web_connectivity', test_version='0.4.3', bucket_date='1984-01-01'), processing_meta=ProcessingMeta(processing_start_time=datetime.datetime(2024, 8, 25, 12, 54, 49, 976211, tzinfo=datetime.timezone.utc), processing_end_time=datetime.datetime(2024, 8, 25, 12, 54, 49, 978491, tzinfo=datetime.timezone.utc)), hostname='www.instagram.com', observation_id='20240804233508.181041_TR_webconnectivity_9a7272e520f3d836_0', created_at=datetime.datetime(2024, 8, 25, 12, 54, 49, 976177), ip='157.240.0.174', port=443, ip_asn=32934, ip_as_org_name='Facebook, Inc.', ip_as_cc='US', ip_cc='DE', ip_is_bogon=False, dns_failure=None, dns_success=True, tcp_failure=None, tcp_success=True, tls_failure=None, tls_success=True, tls_server_name='www.instagram.com', http_request_url=None, http_failure=None, http_success=None, http_response_body_length=None),\n", + " WebControlObservation(measurement_meta=MeasurementMeta(measurement_uid='20240804233508.181041_TR_webconnectivity_9a7272e520f3d836', input='https://www.instagram.com/', report_id='20240804T233501Z_webconnectivity_TR_47331_n1_ZXMtX88TjWN1oGmK', measurement_start_time=datetime.datetime(2024, 8, 4, 23, 35, 7), software_name='ooniprobe-android-unattended', software_version='3.8.8', test_name='web_connectivity', test_version='0.4.3', bucket_date='1984-01-01'), processing_meta=ProcessingMeta(processing_start_time=datetime.datetime(2024, 8, 25, 12, 54, 49, 976254, tzinfo=datetime.timezone.utc), processing_end_time=datetime.datetime(2024, 8, 25, 12, 54, 49, 978492, tzinfo=datetime.timezone.utc)), hostname='www.instagram.com', observation_id='20240804233508.181041_TR_webconnectivity_9a7272e520f3d836_1', created_at=datetime.datetime(2024, 8, 25, 12, 54, 49, 976177), ip='185.60.218.174', port=443, ip_asn=32934, ip_as_org_name='Facebook, Inc.', ip_as_cc='US', ip_cc='RO', ip_is_bogon=False, dns_failure=None, dns_success=None, tcp_failure=None, tcp_success=True, tls_failure=None, tls_success=True, tls_server_name='www.instagram.com', http_request_url=None, http_failure=None, http_success=None, http_response_body_length=None),\n", + " WebControlObservation(measurement_meta=MeasurementMeta(measurement_uid='20240804233508.181041_TR_webconnectivity_9a7272e520f3d836', input='https://www.instagram.com/', report_id='20240804T233501Z_webconnectivity_TR_47331_n1_ZXMtX88TjWN1oGmK', measurement_start_time=datetime.datetime(2024, 8, 4, 23, 35, 7), software_name='ooniprobe-android-unattended', software_version='3.8.8', test_name='web_connectivity', test_version='0.4.3', bucket_date='1984-01-01'), processing_meta=ProcessingMeta(processing_start_time=datetime.datetime(2024, 8, 25, 12, 54, 49, 976315, tzinfo=datetime.timezone.utc), processing_end_time=datetime.datetime(2024, 8, 25, 12, 54, 49, 978494, tzinfo=datetime.timezone.utc)), hostname='www.instagram.com', observation_id='20240804233508.181041_TR_webconnectivity_9a7272e520f3d836_2', created_at=datetime.datetime(2024, 8, 25, 12, 54, 49, 976177), ip='2a03:2880:f223:e5:face:b00c:0:4420', port=443, ip_asn=32934, ip_as_org_name='Facebook, Inc.', ip_as_cc='US', ip_cc='IE', ip_is_bogon=False, dns_failure=None, dns_success=None, tcp_failure=None, tcp_success=True, tls_failure=None, tls_success=True, tls_server_name='www.instagram.com', http_request_url=None, http_failure=None, http_success=None, http_response_body_length=None),\n", + " WebControlObservation(measurement_meta=MeasurementMeta(measurement_uid='20240804233508.181041_TR_webconnectivity_9a7272e520f3d836', input='https://www.instagram.com/', report_id='20240804T233501Z_webconnectivity_TR_47331_n1_ZXMtX88TjWN1oGmK', measurement_start_time=datetime.datetime(2024, 8, 4, 23, 35, 7), software_name='ooniprobe-android-unattended', software_version='3.8.8', test_name='web_connectivity', test_version='0.4.3', bucket_date='1984-01-01'), processing_meta=ProcessingMeta(processing_start_time=datetime.datetime(2024, 8, 25, 12, 54, 49, 976362, tzinfo=datetime.timezone.utc), processing_end_time=datetime.datetime(2024, 8, 25, 12, 54, 49, 978495, tzinfo=datetime.timezone.utc)), hostname='www.instagram.com', observation_id='20240804233508.181041_TR_webconnectivity_9a7272e520f3d836_3', created_at=datetime.datetime(2024, 8, 25, 12, 54, 49, 976177), ip='2a03:2880:f277:1e8:face:b00c:0:4420', port=443, ip_asn=32934, ip_as_org_name='Facebook, Inc.', ip_as_cc='US', ip_cc='IE', ip_is_bogon=False, dns_failure=None, dns_success=True, tcp_failure=None, tcp_success=True, tls_failure=None, tls_success=True, tls_server_name='www.instagram.com', http_request_url=None, http_failure=None, http_success=None, http_response_body_length=None),\n", + " WebControlObservation(measurement_meta=MeasurementMeta(measurement_uid='20240804233508.181041_TR_webconnectivity_9a7272e520f3d836', input='https://www.instagram.com/', report_id='20240804T233501Z_webconnectivity_TR_47331_n1_ZXMtX88TjWN1oGmK', measurement_start_time=datetime.datetime(2024, 8, 4, 23, 35, 7), software_name='ooniprobe-android-unattended', software_version='3.8.8', test_name='web_connectivity', test_version='0.4.3', bucket_date='1984-01-01'), processing_meta=ProcessingMeta(processing_start_time=datetime.datetime(2024, 8, 25, 12, 54, 49, 978475, tzinfo=datetime.timezone.utc), processing_end_time=datetime.datetime(2024, 8, 25, 12, 54, 49, 978496, tzinfo=datetime.timezone.utc)), hostname='www.instagram.com', observation_id='20240804233508.181041_TR_webconnectivity_9a7272e520f3d836_4', created_at=datetime.datetime(2024, 8, 25, 12, 54, 49, 976177), ip='', port=None, ip_asn=None, ip_as_org_name=None, ip_as_cc=None, ip_cc=None, ip_is_bogon=None, dns_failure=None, dns_success=None, tcp_failure=None, tcp_success=None, tls_failure=None, tls_success=None, tls_server_name=None, http_request_url='https://www.instagram.com/', http_failure=None, http_success=True, http_response_body_length=280298)]" + ] + }, + "execution_count": 104, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "web_control_observations" + ] + }, + { + "cell_type": "code", + "execution_count": 2, "id": "d625a231-d3f6-4f05-93be-5710392437fd", "metadata": {}, "outputs": [], @@ -250,7 +250,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 3, "id": "94f26d5a-7d07-406f-ab76-a44706e5fee7", "metadata": {}, "outputs": [ @@ -261,7 +261,7 @@ "" ] }, - "execution_count": 20, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -274,7 +274,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 10, "id": "a6346742-dc39-40e3-8673-686b25fb7d87", "metadata": {}, "outputs": [], @@ -292,7 +292,7 @@ }, { "cell_type": "code", - "execution_count": 180, + "execution_count": 11, "id": "f78e3c55-3826-4622-b720-74452c7c13a2", "metadata": {}, "outputs": [], @@ -302,20 +302,26 @@ }, { "cell_type": "code", - "execution_count": 181, + "execution_count": 12, "id": "3d63e9c3-0430-4bc1-a5e3-583ae71f3405", "metadata": {}, "outputs": [ { - "data": { - "image/png": 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T636trKzg5OQEqVSKiIiIerOyppuAuE4DBw6Um1tr9erV2Lt3L3bv3o1p06ZBQ0PjneapvvT56NGjGuvquuTKpw0bNsDGxqbezi6EkMZR66nx6tWroampiTlz5kAmk73rTG9sy5YtiIuLw/Lly185+oKenh7Onj0LQ0PDGsUpMDAQmZmZNV4zceJEAPVf7tq4cSOA53/DF3v6vSgnJwf79u2TW1Y9SkVjqq8AhoSEYMuWLViyZIlct/M3KZp6eno1vkjMGHvlMXXq1Alqamr49ttv5f5WOTk58PHxee0cTenkyZPYv38/fvnll3dexAlpiWotTgYGBvD19cXFixexePFiXs7yayORSJCTk1NjuVgsxooVK7Bx40asWbOG685dLS0trdZ7GO3bt8exY8dqzNQrk8kwY8aMGl2afXx84OLigr59+9aZ0cvLC5s2bcLNmzcxf/587h5YNaFQiM2bN3P3f6rvjYWEhCAwMBAVFRVcF+u8vDy511bneXmfL5PJZCgtLa33xn31UE+nT59GVVUVAgICEBoaioKCAsTGxiIxMbHW96ttWdu2bSEWi3HlyhUwxnD06FHcvXsXhYWFKCwshFQqrfWYDA0NsWjRIgQFBWHgwIE4fPgw9u/fj6lTp3L3phRBQEAApk2bhiVLlsDLy4vvOIS0DPV15Ttz5gxr1aoVmzRpEistLW3yroOv4uXlxXXV7t69O5swYQLz8vJinp6ebNGiRSwkJERu+0ePHrF58+YxAGzy5MnsypUrte5369atcl3Jp06dyry8vFj37t3Z7Nmz2dq1a5mTkxMbNGgQS0xMbFDWEydOsC5dujAtLS02cOBAtmTJEjZ//nz23XffyXUzT0hIYObm5szQ0JDt2bOHnThxghvRYvLkySw0NJQx9rx79qeffsoAMEdHR3b69Ola3/fGjRvsww8/ZACYiooKW7lyJbt//36t206fPp2pqqoyc3NztmvXLrZp0yamqqrKVq1axYRCodz7Xbhwoc4MpaWlrEuXLgwAMzc3Z97e3mzBggXM0NCQrVq1iv3999+1HlP1a2fMmMEAMABMT0+PnTp1qkF/43fB29ubaWhosGnTpjVoFA9CSON45XxOd+7cwcSJE9G6dWvs2bMHgwcPbtJiyZfc3FzupnxaWhqsrKzAGENERATy8vJgb2//RoN+lpaWIjw8HO3bt6/zpr9EIkFVVRUvU9vn5OTAwMAA6urqAJ4P9mpoaPja+6n+W9nb20NbWxuxsbGwtrZu8DHl5uZCKBTCwcGBl7/Dy0QiEb766iv8888/WLZsGX7//fdG7SBCCKlfgyYbzMzMxOLFi3H69GnMnz8fv/76a4O7GRPS3Pj7+2PRokWQSqXYuXMnxo8fz3ckQlqcBp0KWlhYwM/PD97e3jhx4gQcHR2xc+fOOm/4E9Ic3b17FyNGjMAHH3yAkSNHIjo6mgoTITx5resU06dPR1RUFMaNG4cvvvgC7du3x44dOxo05QMhiurOnTsYPnw43NzcUFZWhmvXrmHPnj3NdpQUQpTBa19ENzc3x7Zt2xAXF4fx48dj5cqVsLOzw7fffguhUNgUGQlpdBUVFTh06BAGDBgAd3d3iMViXL16FYGBgRg0aBDf8Qhp8Rp0z6k+6enp2LZtG/bv34/s7GyMGDEC8+fPh6enJ3eTnRBFERERgd27d+PgwYMoKSnBBx98gM8++4wKEiEK5q2LUzWJRIL//vsPu3fvxuXLl2FiYoIJEyZg4sSJGDx4MBUqwpuYmBj4+fnh5MmTCAkJQfv27TF37lzMmjULFhYWfMcjhNSi0YrTi5KTk3Ho0CH4+fnh0aNHMDQ0xNixYzFx4kQMHz5cIboKE+X2+PFjbtzAyMhImJqaYvz48fj4448xePDgZjdXGSEtTZMUpxclJyfj9OnT8Pf3x40bN6Curo4ePXrA3d0dQ4cOxcCBA6lVRd5aVlYWbt26hYCAAFy8eBFCoRA2NjYYNWoUPD09MXLkSPrvjJBmpMmL04syMjJw8eJFBAQE4OrVq8jKyoKRkREGDx6MIUOGwM3NDU5OTjWGEyLkZRkZGQgKCsL169cREBCAp0+fQkNDA/3798eQIUMwfPhw9OrVi1pIhDRT77Q4vah6RIGrV68iICAAN2/eRElJCXR1ddGrVy/069cPffr0QZ8+fWBubs5HRKIgKioq8OjRIwQHByM4OBj37t2DUCiEqqoqunXrhiFDhmDo0KFwd3fnxgwkhDRvvBWnl1VPMxEUFITg4GAEBQUhJiYGMpkM7733Hnr06AFnZ2c4Ozuja9eusLOzo7NiJZSfn4/Q0FCEh4cjPDwcT548QVhYGCorK2FqasqdsPTt2xeurq7Q09PjOzIhpAkoTHGqTWFhIXe2HBYWhtDQUMTHx0Mmk6F169bo0qULXFxc4OzsjI4dO6JDhw6wtbWly4LNQF5eHmJjYxEbG4vIyEiEhYUhPDwcqampAAATExN07doVzs7O6NWrF/r27Qt7e3ueUxNC3hWFLk61KS0tRWRkpNzZdXh4ODcVg4aGBuzs7LhiVf1o27YtrK2tuQnuSNPLzMyEUChEQkICYmNj8ezZM64gVU9kqaGhgc6dO8PZ2RkuLi7cw9LSkuf0hBA+NbviVJf8/HzExsYiLi4OMTEx3IdgXFwcCgsLATyfKtzCwgK2trawsbGBjY0N2rZtC1tbW7Rp0wZt2rSBqamp3OR7pCaZTIacnBzk5OQgLS0NKSkpSElJQVJSEvd7SkoKN6yVuro63nvvPXTo0EHupKF9+/awtbWl0b4JITUoTXGqT3Z2NpKTk+v8EM3IyJDbXldXF5aWljA1NYWpqSksLS1hZmYGU1NTGBoawsDAAPr6+jAwMOAeOjo6PB3d25FIJBCJRBCJRCgsLIRIJEJBQQFEIhFXgHJycpCZmYmsrCzu+YszJOvq6sLW1rbWom9jYwNbW1sIBAIej5IQ0ty0iOL0KmKxGOnp6cjMzEROTg6ys7O533NycpCRkcH9XlBQwM3q+iJ1dXXo6+tDW1sbpqam0NDQgLa2NrS1taGhoQFdXV0IBAIYGBhAVVUVBgYG3Gur1728v5enJZFIJDVm5wWe35urLhbl5eWoqKhASUkJJBIJNxOtSCTiXl9eXs4Vorpm1TUwMICxsTHMzc1hamoKMzMzWFhY1Pjd0tLyjeZ/IoSQ+lBxegPVU6BXf8BX/x4QEIB9+/Zhzpw50NPTQ2lpKcrKyiAWi1FcXIyqqiqIRCJUVVWhqKiI219BQUGN96guMi9SUVGRK2rVdHR0uHtpmpqa0NLS4pbp6+tDTU0NJSUluHPnDmbMmAFjY+NaW3/Vz6nYEEL4RsWpkYSHh6Nfv35YsGABfvvtN77j1CASidC7d2+Ym5vj+vXrNFoCIUShUXFqBMXFxXB1dYWRkRGuX7+usD0CqwvookWL8Msvv/AdhxBC6kTdpN4SYwyzZs2CSCTC8ePHFbYwAYCzszN2796N3377DceOHeM7DiGE1Im6UL2lzZs347///sO1a9fQpk0bvuO80pQpUxAUFIS5c+fC0dERXbp04TsSIYTUQJf13sLt27cxePBgbNmyBcuXL+c7ToNVVVVhyJAhyMjIwIMHD2g6ckKIwqHi9IZEIhG6desGJycn+Pv7N7tx/rKystCzZ0/06NEDZ86caXb5CSHKje45vaE5c+agqqoK3t7ezfKD3dzcHMePH8elS5fwv//9j+84hBAih4rTG/jrr79w5swZHDhwACYmJnzHeWP9+vXDL7/8gvXr1+PChQt8xyGEEA5d1ntNERERcHV1xerVq/Hdd9/xHadRzJ49G2fPnsWDBw9gZ2fHdxxCCKHi9DoqKirQs2dPmJiY4Nq1a0ozNUd5eTnc3d0hlUpx9+5dmrCPEMI7uqz3GtauXYu0tDQcPHhQaQoTAGhpacHPzw+pqalYuHAh33EIIYSKU0Pdvn0bf/75J/744w/Y2tryHafRtW3bFr6+vvD19cWuXbv4jkMIaeHosl4DlJaWomvXrnBycsKZM2f4jtOkNm7ciB9++AHXrl2Du7s733EIIS0UFacGmDdvHs6cOYPw8HBYWFjwHadJMcbg5eWFoKAghISE0Iy0hBBeUHF6hXPnzsHT0xMnTpyAl5cX33HeCRrBnBDCNypO9SgqKoKjoyMGDhwIHx8fvuO8UzSCOSGET9Qhoh7r1q1DRUUFfv/9d76jvHMvjmB+9OhRvuMQQloYGpW8Dg8ePMCOHTvw77//wszMjO84vHhxBHMnJycawZwQ8s7QZb1aVFVVwdXVFXp6erh+/XqzHDuvsdAI5oQQPtBlvVps3boVUVFR2LlzZ4suTAAgEAhw7NgxlJWVYfr06aBzGULIu0DF6SVCoRAbN27EN998AwcHB77jKAQawZwQ8q7RZb2XeHl5ISoqCk+ePIGGhgbfcRTKtm3bsHz5cvj7+2PUqFF8xyGEKDEqTi+4ceMGBg8ejAsXLmDkyJF8x1FIs2fPxpkzZ/Dw4UMawZwQ0mSoOP0/MpkMrq6uMDc3x7lz5/iOo7AqKirg5uZGI5gTQpoU3XP6f/bu3YvQ0FD8/PPPfEdRaJqamjSCOSGkyVFxAlBcXIwNGzZg8eLFcHJy4juOwqMRzAkhTY2KE4Aff/wRFRUV2LBhA99Rmo1hw4Zh/fr1WLZsGW7fvs13HEKIkmnx95xSUlLQsWNHbN68GZ9//jnfcZoVGsGcENJUWnxxWrx4Mc6dO4fY2Fi0atWK7zjNDo1gTghpCi36sl5KSgr27t2Lb775hgrTGzIwMICfnx+ePHmCr7/+mu84hBAl0aJbTp9++inOnz9PraZG4Ovri6lTp8LX1xcfffQR33EIIc1ci205CYVC7Nu3D+vWraPC1AimTJmCpUuXYu7cuYiIiKixnjGGmJgYHpIRQpqjFttyWrhwIS5evEitpkZU1wjmhYWFmDp1KvLy8nDv3j2eUxJCmoMWWZySk5PRsWNH/PXXX5g/fz7fcZRKVlYWevbsiR49euDMmTOIjIzEuHHjkJSUBMYYkpOTYWNjw3dMQoiCa5GX9bZt2wZzc3PMmjWL7yhK58URzD/++GP07t0bQqEQMpmMm36DEEJepcW1nMrKymBjY4Mvv/ySepc1kaqqKowaNQoBAQFQUVHh5oBSUVGBi4sLnjx5wnNCQoiia3Etp/3796O8vJwu5zWR3NxcDB06FNevXwcAuckJGWMIDQ1FbGwsX/EIIc1EiypOjDH89ddfmDZtGoyNjfmOo3SCgoLg7OyMe/fuQSqV1rqNuro6jh8//o6TEUKamxZ1We/SpUsYOXIkQkND4eLiwnccpZKZmQkXFxfk5OS8ctvOnTvj6dOn7yAVIaS5alEtp23btmHw4MFUmJqAhYUFwsLC8MknnwAAVFXr/k8rOjoaUVFR7yoaIaQZajHFKSkpCRcuXMDSpUv5jqK0LCws4OPjg//++w9mZmYQCAS1bqeurk699ggh9WoxxcnHxwfGxsYYO3Ys31GUnqenJ2JiYvDpp59CRUWlRpGSSCQ4cOAAT+kIIc1BiylOR44cwYcffljn2TxpXHp6evjzzz9x+/Zt2NnZQU1NTW59YmIidSknhNSpRRSn8PBwREREYMqUKXxHaXH69++PiIgI/PDDD1BXV+dODlq1aoWjR4/ynI4QoqhaRG+9tWvXwsfHB0lJSVBRUeE7TosVGRmJOXPm4OHDh5DJZLCyskJKSgr9mxBCalD6lhNjDEeOHMGUKVPoQ5BnTk5OuHfvHv78809oa2sjLS0N9+/f5zsWIUQBKX3L6e7du3Bzc8OTJ0/QtWtXvuOQ/yc1NRVLliyBvb09tmzZgqKiIkilUhQVFaGqqgrFxcUAnneeKCkpqXUfhYWFkMlkNZarqKjAwMCg1tfo6Ohwo9C3bt0a6urq0NXVhUAg4H4SQvin9MVp5cqVOH/+PH3pswmIRCJkZ2cjNzcXBQUFKC4uRlFREQoKClBUVMQ9qpeLRCIUFom4uUoAACAASURBVBaiqqoKhYWFXDFSNHp6elBTU4Oenh4EAgEMDAygr68PPT097qGrqwt9fX0YGBhwywwMDGBiYgJTU1MYGRnxfRiENGtKf5r433//YeLEiXzHaBYYY8jMzER6ejrS09ORmpqKrKws5OXlIScnhytE1Q+JRCL3+uoPdENDQ7kPcj09PZibm3Mf5gKBQK4AvPxTVVWVmwsKAAwNDWvN+2Ir6EX1tbZEIhE33t+LrTWpVIri4mKu1Vb9UyKRcEW1uLgYBQUFSE5ORlFREQoLCyESibjW3osEAgFMTEy4h5mZGUxNTbniZWNjgzZt2sDKygrm5ub1fmmZkJZIqVtO0dHRcHBwQGBgINzd3fmOw7v8/HwkJCQgISEBSUlJSEtLQ1paGjIyMiAUCpGVlSVXcIyMjGBhYQFjY2OYmprKfcBWP8zNzWFiYgJDQ0Noa2vzeHT8KisrQ0FBAXJzc5GdnY2cnBy5Qp6VlSX3e15eHvdagUAAc3Nz2NjYwNLSkitc7dq1g52dHezs7GgsSNLiKHVx+uWXX/C///0PWVlZLeZeQkpKCmJiYrgilJCQgPj4eCQkJEAkEgF4/mFoZWUFa2trWFlZoU2bNrC2tuY+GC0tLWFlZQUtLS2ej0Z5VVRUIC0tjWuhZmRkICUlBRkZGUhLS0NqaipSU1O5Fpm+vj5XqF58dOrUCW3btuX5aAhpfEpdnAYOHIi2bdsq5WgE6enpiIqKQmRkJKKiopCQkIDQ0FBu4FVNTU20adOm1g80R0dHKjzNQFVVFYRCodyJxosnHNUnGxoaGrC3t4eTkxMcHR25n507d67x5WdCmgulLU4FBQUwMzODj48PPvzwQ77jvDGJRIKIiAiEhIRwj8jISJSVlQEArKys4ODgAEdHRzg6OnK/m5iY8JycNLW8vDw8ffoUUVFRcj9TUlIAAFpaWnB0dETPnj25h7Ozc6336QhRNEpbnA4fPoxZs2YhOzu7zm7FioYxhqioKNy7d48rRGFhYRCLxdDR0UG3bt3Qs2dPuLi4wMnJCQ4ODnIdBwgBnnf0iI6ORkREBMLDwxESEoLHjx+jpKQErVq1grOzM1es+vXrBycnJ+qQQRSO0hanKVOmICcnBwEBAXxHqZNUKkV0dDTu3LmDgIAAXL9+Hbm5uVBXV0eHDh3kznhdXV3pjJe8lfT0dLkW+N27d5Gfnw9dXV306dMHbm5ucHd3h4eHBzQ0NPiOS1o4pSxOVVVVMDMzw4YNG7B8+XK+48iJjIzEuXPncPXqVdy9exclJSUwMTGBu7s7BgwYAA8PD3Tr1q3FdOAg/JFKpQgLC8OtW7cQGBiIwMBAZGdnQ0dHB3379sWQIUMwZswYmv+M8EIpi9ONGzcwePBgPHv2DB06dOA1S0VFBa5fv45z587h3LlzSEpKgqmpKYYNG8YVIwcHBxpaiSiE6OhorlBdvnwZWVlZsLGxwZgxYzBmzBi8//77LforA+TdUcritGrVKpw/f5632VYrKirg7+8PHx8fXL58GeXl5ejWrRtGjx4NT09PuLq60jV+ovBkMhlCQkK4E6uQkBBoampi6NCh+OSTTzBu3Djq9UmajFIWp06dOmHcuHH4+eef39l7ymQyBAYG4uDBgzh58iSKi4sxdOhQeHl5YfTo0bCysnpnWQhpCpmZmTh//jxOnjyJy5cvQ1tbGxMnTsS0adMwePBgOuEijUrpilNcXBw6dOiAW7duwcPDo8nfr6CgALt27cKuXbsgFArRo0cPTJs2DR9//DEsLS2b/P0J4UN2djaOHDmCQ4cO4cGDB7C2tsaCBQuwePFiGs2CNAqlK06//vorfvzxxyYfFSI5ORlbt27Fnj17IBAIMH/+fMyaNQuOjo5N9p6EKKKYmBh4e3vj77//RkVFBWbPno0VK1bA3t6e72ikGVO64jR48GBYWVnh0KFDTbL/1NRUrFmzBkeOHEGbNm2wfPlyzJs3D7q6uk3yfoQ0F6Wlpdi7dy9+//13CIVCTJo0CZs3b0a7du34jkaaIaW6SFxYWIg7d+7A09Oz0fddWVmJn376CZ07d0ZQUBD279+PuLg4rFixggoTIXg+SvzSpUsRGxsLHx8fhIaGwtHREd9//z0qKir4jkeaGaVqOfn6+mLGjBnIzs6uc5qFN3Hjxg0sWrQIKSkpWLt2LVatWkVfUiTkFSQSCbZu3Yr/83/+D8zNzbFz504MGzaM71ikmVCqlpO/vz88PDwarTAxxvDjjz9i6NCh6Ny5M6KiovDNN99QYSKkAdTV1fHll18iOjoaPXr0wMiRI/Hdd99Bic6HSRNSmmEIpFIpLl68iLVr1zbK/mQyGT777DPs3r0bv/76Kz7//PNG2W9juHPnDhITE+WWCQQC6Ovrw8jICM7OznJflMzJycGlS5e458OGDYO5ubnc68ViMfz8/CCVSgEAqqqqGDlyJIyMjCAWi+Ht7Y3Q0FBYWVnB3d0drq6uuHLlCsaOHdugzAcPHsSUKVOUduSLmzdvcgOuVnexrk9CQgLu3r0L4PnfetSoUY3a2lckVlZWOHbsGP7++28sW7YMQqEQu3fvphHTSf2Ykrh37x4DwKKiohplf1999RXT0NBgp06dapT9NSaZTMYuXrzIVFRUmIGBAduwYQPbt28f++GHH9j48eOZpqYmGzVqFHv69Cn3mqysLLZgwQIGgPXt25dVVFTU2G9BQQGbMWMG69+/P0tJSeGWOTo6srlz57Lg4GB2+fJl9sknnzA1NTW2fPnyBuUtKytjRkZG7OTJk43zB1BAYrGYHT16lAFgANj9+/fr3X78+PEMAHN3d+f+1g1V279dc3HhwgWmpaXFPvvsM76jEAWnNMXpu+++Y9bW1o2yL39/f6aiosK8vb0bZX9NxcjIiHXq1KnG8oCAAGZhYcE0NTVZUFCQ3LpOnToxAGzWrFm17vPQoUNs3bp13PNly5YxBwcHJpPJ5LZbvHhxg4vTnj17GAD2/vvvN2j75qqqqorp6+szAMzLy6vO7WJiYpiOjg4DwL799tvXfp+VK1cyqVT6Fkn5dfz4caaiosKOHTvGdxSiwJTmntOlS5cwcuTIt96PTCbDihUr8NFHH2HGjBmNkKzp1DVK+ZAhQ/Dvv/+ioqICXl5eEIvF3DodHR3069cP+/fvx9atW2vdZ+vWrbnnDx48gIaGRo2x/7766qsGjwf4zz//YODAgbh27RqePn3aoNc0R2pqarC3t8fw4cNx6tQpxMbG1rrdr7/+yv239eLfuiHCw8Oxa9eut87Kp0mTJmH27NlYuXIlJBIJ33GIglKK4iQSifDgwQOMGDHirfcVGBiI2NhYbNiwoRGS8Wf06NEYMmQI0tLScPz4cbl1fn5+sLa2xqpVq145pYiDgwOePHmCpUuXorKykltua2vboJOBW7duwcHBAevXrwcAbN++vc5t4+LisG7dOshkMsTGxuKHH37A7t27a3yA3b59G9988w127dqFf/75BwBw9uxZ+Pr6wtfXF8HBwcjLy+Oe+/r64tq1awCeT2NfvSwtLQ3A8/mPdu/ejS+++AJ//fUXSkpKuPeKj4/H+vXrIZVK4e/vj59//vmVH6irV6+GTCbDL7/8UmNddnY2QkJCMHr06DpfX1ee6q9JlJaW4siRI3L/rrGxsfjjjz+wceNGXLhwod58imDDhg1ITU3FlStX+I5CFBXfTbfGcPz4caampsby8vLeel8//fQTa9u27duHegcsLCxqvaxXbd26dQwAmzNnDresR48ejDHGHj58yLS0tJiRkRGLi4vj1h87doxt3ryZex4bG8tMTEwYANaxY0d24cKF18o4adIkFhISwhhjzMHBgenq6rKioqIa2+3fv5+Zm5szAOzs2bNs4sSJbMyYMQwAW79+Pbfd6tWrmY+PDystLWW+vr6sdevWjDHGoqKimImJCTMzM2MlJSWMseeXNwUCAXNzc2MFBQWMMcakUin77LPP2IoVK5hEImHPnj1jY8eOZZcuXWJPnjxhXbp0Yfb29qygoIB5e3szCwsLBoDt37+fde/enQFgd+7cqfN4q/++3bt3ZxoaGiwjI0Nu/fr169m+ffuYv78/A8C2bNkit76+PIGBgWzq1KkMAPP392eXLl1ijDG2dOlS5uHhwXJzc9nly5eZioqK3L+honJycmIbNmzgOwZRUEpRnObNm8f69evXKPtau3Yt69atW6Psq6m9qjgdOHCAAWDDhg3jllV/eDLG2OHDhxkA5uTkxBWMl4sTY4yFhYUxFxcX7mb/qFGj2LNnz16ZTygUskGDBnHPt23bxgCw7du317r96tWrGQB25swZbtngwYNZx44dGWOMVVZWMmNjYxYTE8Ot//zzz7nff/rpJ6aqqsrS09O5ZZMmTWJt27aVu0fj5eXFysrKGGOMDRs2TK7Ty4ULF+QK4jfffMMVJ8YYi46OrnH/7UXVf19fX18GgK1Zs4ZbV1paylxcXJhYLK6zOL0qz8aNGxkAuQz6+vps06ZN3HNHR0fWt2/fOjMqCnd3d7Z06VK+YxAFpRSX9S5fvtwol/SA591ek5KSUFVV1Sj741NpaSkAwNTUtNb1U6ZMwddff43IyEhMmzatzu+fODs7IyQkBH/88QcMDQ1x4cIFdO3aFZcvX673/Xfu3InFixdzz2fOnInWrVtjx44dtW6vo6MDAHKXvLp06YLU1FQAz783o6uri6FDh3KXrr755htu2xkzZkBVVVVu6CpDQ0MkJydzl4+Sk5NhaWkJLS0tZGRk4MqVK7h79y7WrFmDNWvW4Ny5c+jVqxfKysoAgJsSYsqUKQCej3jfkHttkydPRrt27bBz504UFxcDAPbu3Ytp06bVea+wIXlqc+7cOXz66acAgPv374MxhvLy8ldm5BNjDPHx8bC1teU7ClFUPBfHtxYVFcUAsHv37jXK/hISEpiKiorc2buielXLafny5QyA3Fn1iy0nxp5f5vL09GQA2Lp162ptOb0oNzeXzZgxgwFgBgYGTCQS1bpdeXk5s7GxYePGjWNeXl7co23btgwAu379eo3XfP/99wwAk0gk3LKvv/6atWrVinvu7+/PDA0NGQDWr18/uVYUY4yNHTuWOTk5McYYy8zMZPPnz2dt27bles9t3LiRu8x48+ZNBoDl5OTUebw//PADA8DEYnGd27zoxb/vn3/+ybWOqqqqWLdu3VhhYSF3HHip5dSQPLW1nBhjzM/Pj02bNo0dPHiQjRo1irm4uDQoL18CAgIYABYREcF3FKKgmn3L6dKlSzA0NETv3r0bZX/vvfceJkyYgK+//lrhzz7rU1lZCX9/fwgEAkyYMKHO7VRVVeHj4wMHBwds2rSpRueJn376Se65sbExvL29MWXKFIhEIty5c6fW/fr6+mLhwoU4ffo0Tpw4wT1OnToFoP6OEfUZM2YM4uLisHz5coSEhKBXr15yPQDnzJmDyMhIPHz4EH/99ReWLVuGuXPn4uzZs8jMzERoaCh69OgB4P/3dnz06FGN96lu7byNOXPmwMjICFu3bsWRI0cwdOhQ6Onp1bn9m+ZZvXo19u7di927d2PatGkKP4JJZWUlVq1ahREjRsDJyYnvOERBKUVxGjp0aKN+2/y3335DVlYW5s6dC5lM1mj7fZe2bNnCfYi/ahoPPT09nD17FoaGhjWKU2BgIDIzM2u8pnoEhLq6Qv/9999YsGBBjeXdu3dH3759cfr0ae5yXUOVlpZi9+7dMDIywu+//44bN26gpKQEvr6+3DZjxoyBmZkZduzYgcTERHTp0gWzZ8+GVCrFnDlz8P7773PbdurUCWpqavj222/leiLm5OTAx8fntbLVRkdHB0uWLEFaWhqWLl2K5cuX17v96+SpHskjJCQEW7ZswZIlS6CpqcmtZwo6RBBjDIsXL0ZCQgK2bdvGdxyiwJp1caqoqMCtW7ca7X5TtbZt2+LYsWPw8/PDzJkzFfK7GBKJBDk5OTWWi8VirFixAhs3bsSaNWuwadMmufVpaWm13r9o3749jh07VqPIy2QyzJgxQ657NQD4+PjAxcUFffv2rbGvs2fPQl9fv857XePHj0dVVRU2b94stzw/Px8A5FqsVVVVkEgkEIvFkMlk+Pbbb7kRrvv164cOHTrIvY+6ujqmTZuGffv2Yc6cOQAAa2trjBw5EtevX8fUqVO5bQ0NDbFo0SIEBQVh4MCBOHz4MPbv34+pU6dy95iq/+3z8vJqPZYXlZWVcd3Tqy1duhSampr44IMP5GZDzsjIACDfImpInupjDQkJQWBgIDf77OnTp1FVVYWAgACEhoaioKAAsbGxNYa54pNUKsXChQtx4MAB+Pj4oEOHDnxHIoqM7+uKb+Py5csMAEtOTm6y/evo6DB3d3eWlpbWJO/xJm7dusW8vLwYACYQCFj37t3ZhAkTmJeXF/P09GSLFi3i7qtUe/ToEZs3bx4DwCZPnsyuXLlS6763bt0qd89p6tSpzMvLi3Xv3p3Nnj2brV27ljk5ObFBgwaxxMTEGq/fvn07MzU1ZWZmZmzz5s2sqqpKbv2NGzdY//79GQCmoqLC5s6dy9LS0tjp06dZu3btGAD2+eefs4SEBHbkyBH23nvvMQDsyy+/ZHFxcUxLS4s5OzuzP//8k3333Xds9uzZrLKyUu49IiIiWM+ePeWW+fn5sU8++aRG3tLSUu4eGgCmp6fH9ZY7ceIEN6LG5MmTWWhoaJ3/Jjdu3GATJ05kANiiRYtYcHAwt+7TTz9l4eHhjLHno0hs376d26+1tTX79ddfWX5+/ivzMPb8nqi5uTkzNDRke/bsYYwxNn36dKaqqsrMzc3Zrl272KZNm5iqqipbtWpVnXnftczMTDZ48GCmpaXFzp49y3cc0gw06+K0cuVK5ujo2KTv8fTpU+bk5MQMDAzY1q1b5W7WK6sXb8inpqYyxp6P5xcWFsauX7/OhEIhL7lkMhkrLS1lRUVFLCQkhBUXF9e57csZJRJJvScYOTk5LCQkhOtizrf68lRWVtZYnp2dLVekq4sd32QyGfP29mampqbM1tb2lWMOElKtWc/n5OzsjGHDhuG3335r0vcpLy/HTz/9hM2bN6Nz587466+/4O7u3qTvSUhz9+jRIyxZsgQPHz7E4sWL8f3339fbIYSQFzXbe04ZGRmIjIzE8OHDm/y9tLS08N133yEsLAzm5uYYMGAAxo4di5s3bzb5exPS3Ny9exdeXl7o3bs3tLS0EBoaij/++IMKE3ktzbY4Xbx4ERoaGhgwYMA7e8+OHTvi0qVLOHPmDEQiEQYNGgRXV1ccP36c6z1FSEskk8lw6tQpuLm5wc3NDWlpaThx4gSuXbv2yt6ihNSm2RanK1euwMPDQ25SvXdl7NixCAwMxL1792Bra4uPP/4Y9vb2WL9+PWJiYt55HkL4EhcXh40bN6JDhw6YNGkSTE1NERgYiKCgoHq/X0fIqzTbe05WVlZYunQpvv76a76jID4+Hn///TcOHz6MtLQ0uLq6Ytq0afjoo49gZmbGdzxCGlVeXh6OHj2KQ4cO4d69e7C0tMSUKVOwcOFCdOzYke94REk0y+IUHR0NBwcH3Lt3r9bv2fBFJpPh+vXrOHjwIPz8/FBeXo4BAwZgzJgxGDNmDDp16sR3RELeSFxcHM6dO4dz587h5s2bUFdXx4QJEzBt2rRG/xI8IUAzLU67du3Cl19+ifz8fKirq/Mdp1bl5eU4e/Yszp49i4sXLyI/Px/29vZcoRo4cKDCDzNDWq7KykoEBgbi/Pnz8Pf3x7Nnz2BgYIARI0Zg7NixGD9+PDdQLyFNoVkWp+px3ZrDpGrA82/GP3nyBP/99x/8/f3x6NEjCAQCuLi4YOjQoXBzc4OHhwcMDAz4jkpaqLKyMjx69Ah37tzB7du3cevWLRQVFcHOzg6enp4YO3YsBgwYUOeI6oQ0tmZZnBTpftObEAqFuHbtGm7evInAwEDEx8dDIBCgZ8+e8PDwgJubG3r27AkbGxu+oxIllZ6ejpCQENy5cweBgYF48OABJBIJ2rVrhwEDBmDAgAF4//338d577/EdlbRQza44Ker9preRnp7OFapbt24hKioKjDGYmZmhZ8+ecg8qWOR1paWlISQkRO6RmZkJFRUVdO7cGR4eHlxBov++iKJodsWpOdxveltFRUV49OgRHj16xH2YxMbGQiaTwdTUFF27doWjoyMcHR3h4OAAJycnGBsb8x2b8Cw/Px9RUVGIiorC06dPERkZibCwMGRlZUFFRQXt27dHz5490aNHD+4nXUomiqrZFafmdr+psRQXF+Px48cICQlBREQEIiMj8fTpUxQVFQEAzMzM4OTkhM6dO8PR0RF2dnaws7PDe++9Rx0vlIhYLEZSUhISExORkJDAFaKoqChuahNdXV107twZTk5O6NKlC3r27Inu3btDX1+f5/SENFyzK07N/X5TY0tJSeE+nKof0dHR3BQPKioqsLKy4orVi0XLxsYGFhYWStsCbY4kEgmysrIgFAqRlJSEhIQEuUdaWho3x5iRkRE6deoEJycnrgXduXNntG3bluejIOTtNaviFBMTg86dOyvV/aamUlRUVOODLSEhAYmJiUhKSuIms1NRUYG5uTmsrKzQpk0b2NjYwNLSkvtpaWkJExMTmJiYUBF7CxKJBHl5ecjNzUVmZibS09ORkpKCjIwMpKSkID09HWlpacjKyuKKT6tWrWBra1vjxKL65IIuyRFl1qyK099//41Vq1Yp9f2md0EmkyEjIwNCoRAZGRlITU1FWloa0tPT5Za9PE29vr4+zMzMuGJlYmICU1NTmJmZQV9fH/r6+jAwMICenp7cQ1dXl6cjbXwlJSUoKiqSexQUFKCoqAgikQg5OTnIyclBbm4u98jJyUFBQYHcfjQ1NWFtbQ1LS0vY2trC0tIS1tbW3ElC9TL6citpqZpVcfrkk0+Qn5+Pixcv8h2lRcjPz0dWVpbch2xtH7w5OTkoLCxEYWFhrftRUVGBgYEB9PX1oaenB3V1dejr60NVVbXGTz09PaipqXE/AXDPXyYQCGotfCUlJbXOXlxcXIyqqioAzwt0YWFhnT8ZYxCJRKiqquIKT/X62ujp6XGz/1YXcGNjY7kCXv28ej0hpG4CvgO8jps3b+Kzzz7jO0aLYWRkBCMjo9d6jUgkqtGyePHDvaioCBKJBEVFRZBKpdxPoVAoVyCys7MhFovRunVriMXiWqeWr6ioqNG6A563SrS0tGos19LSgqamJoD/XzCrf1YXSIFAADs7O7nnenp6XHGtqKjAypUrYWBggH379qFLly4wNDR8rb8RIeTVmk3Lqfp+0927d9GvXz++45AmNn36dERERODx48d8R6khPT0d48ePR3x8PE6cOIHBgwfzHYkQpdNspsy4ceMGWrdujV69evEdhTSx3NxcnDhxQmFbyW3atMGtW7cwcuRIDB8+HNu3b+c7EiFKp9lc1gsMDET//v2pI0QLsGfPHmhqauLjjz/mO0qdNDU1cejQIbi4uGDp0qUICwvD9u3bIRA0m/+lCFFozablFBQUhP79+/MdgzQxmUyGf/75B3PmzFH4Ua9VVFTw1VdfcXMbeXp6QiQS8R2LEKXQLIpTXl4eEhIS0KdPH76jkCbm7++PpKQkLFy4kO8oDTZ58mTcvn0bUVFR6NOnD82GTEgjaBbFKTg4GADQu3dvnpOQprZjxw4MHz682c2o2r17dwQFBUFfXx/9+/fH9evX+Y5ESLPWbIpT+/btaXBTJRcfH48rV65g8eLFfEd5I9RRgpDG0yzu3gYHB9MlvRZgx44dsLa2xpgxY/iO8saoowQhjUPhW06MMTx8+BCurq58RyFNqLy8HPv378eiRYua/ZA9tXWUqGv0DEJI7RS+OMXGxiIvL49aTkru8OHDKCkpwZw5c/iO0mhe7Cjh6upKHSUIeQ0KX5yCg4OhoaGBrl278h2FNKF//vkHkyZNgrm5Od9RGlV1Rwk9PT3qKEHIa2gWxalbt240YZ4Si4yMxP379zFv3jy+ozSJNm3aIDAwkDpKEPIaFP4ubXBwMH35Vsnt3bsX7dq1w8CBA/mO0mSoowQhr0ehW05isRjh4eF0v0mJVVVV4fDhw5g9ezZUVRX6P8e3Rh0lCGk4hf40ePz4McRiMRUnJXb27FlkZ2dj5syZfEd5Z17uKPHs2TO+IxGicBS6OAUHB8PY2Bh2dnZ8RyFNZN++fRg6dCjatm3Ld5R3ijpKEFI/hS9Offr0gYqKCt9RSBPIzs7GxYsXMWvWLL6j8KK6o8SIESOoowQhL1Ho4vTw4UMaT0+JHT16FBoaGvjggw/4jsKb6o4SmzZtwtKlS7Fw4UJuKnlCWjKF7SpUXFyM+Ph49OjRg+8opIkcPnwYEydOVPipMZpadUcJOzs7zJo1C8nJyTh69Cj09fX5jkYIbxS25RQWFgaZTEZfvlVS8fHxCA4OxieffMJ3FIVBHSUI+f8Utjg9efIEBgYGsLW15TsKaQKHDx+GiYkJhg4dyncUhUIdJQh5TmGLU2hoKLp160adIZTUkSNH8PHHH9OXUGtBHSUIUeB7TqGhoejXrx/fMUgTCA0NRVRUFPbs2cN3FIVFI0qQlk4hW05SqRQRERF0v0lJnThxAtbW1ujbty/fURRadUeJI0eO0IgSpMVRyOIUFxeHsrIyuLi48B2FNIGTJ0/Cy8uLLtk20IcffkgdJUiLo5DFKTIyEqqqqnBwcOA7CmlkUVFRePr0Kby8vPiO0qxQRwnS0ihkcXr69Cnatm0LbW1tvqOQRnby5EmYm5vTSPNvgDpKkJZEIe+uPn36FI6OjnzHIE3g5MmTmDhxYrOfip0v1FGCtBQK23KiS3rKJzExEaGhoZg4cSLfUZo16ihBWgKFK04ymQwxMTFUnJTQuXPnoKenhwEDBvAdRSlQRwmihgdqmQAAIABJREFUzBSuOCUnJ6O0tJSKkxI6f/48hg0bhlatWvEdRWlQRwmirBSuOEVHRwMAOnfuzHMS0pjKy8tx8+ZNjB49mu8oSufljhI7duzgOxIhb03h7qLGxcXBxMQEhoaGfEchjejatWsoLy/HyJEj+Y6ilF7sKPHZZ58hNDS03o4SEokE6urq7zglIQ2ncC2n+Ph4tG/fnu8YpJGdP38e3bt3R5s2bfiOorQa2lGiuLgYHh4eSEpKevchCWkghStOcXFxVJyU0IULF+iS3jtSX0cJmUyGjz76CMHBwVi+fDmPKQmpn8IVp/j4eNjb2/MdgzSihIQEJCYmYtiwYXxHaTHq6ijx9ddf4/LlywCAM2fO4NKlS3zGJKROClWcZDIZEhMTqeWkZK5fvw5NTU24urryHaVFebmjxMyZM7FlyxZIpVIAgJqaGhYuXAixWMxzUkJqUqjilJKSArFYTC0nJXPjxg24ublBU1OT7ygtTnVHialTp+LAgQNy66RSKVJTU/Hbb7/xlI6QuilUcUpMTAQA2NnZ8ZyENKZbt25h8ODBfMdosYRCIf77779ah4ySSqXYuHEjdY4gCkehipNQKISmpibMzMz4jkIaSVxcHIRCIQYNGsR3lBappKQEo0aNQnFxMXc572UymQxffPHFO05GSP0UrjhZW1vTPD9K5MaNG9DR0UHv3r35jtLiVPfMe/bsGSQSSZ3bSSQSnDp1CleuXHmH6Qipn0IVp5SUFNjY2PAdgzSiu3fvok+fPjRkEQ/Cw8ORnJwMqVT6yr+/mpoaFi1ahMrKyneUjpD6UXEiTer+/fvUS48nXbt2RUREBCIiIrBixQoYGRlBRUWl1lEjpFIpkpOT8fvvv/OQlJCaqDiRJlNWVobo6Gj06tWL7ygtmpOTEzZv3ozs7GxcvnwZ48aNg0AggJqamtwldKlUim+//RbJyck8piXkOYUqTqmpqbC2tuY7BmkkISEhkEqldL9JQaipqWHo0KE4ceIE0tPT8csvv3CTelZf9pNIJNQ5gigEhSlO5eXlEIlEsLKy4jsKaSQPHjyAqakpbG1t+Y5CXmJqaorly5cjIiICT548weLFi2FkZASZTAY/Pz8EBATwHZG0cCqMMcZ3COD5d5zs7Oxw//59OtNWElOmTEFxcTH8/f35jkIaQCKR4Pz589i3bx8SExPx4MGDejtSiEQiMMZQWlqKyspKSCQSlJSUcOsLCwshk8lqfW1FRQXKy8vr3Lempia0tLRqXaeiogIDAwPuuY6ODlq1aoVWrVpBR0cHAGhWAyWgMFNmZGdnAwB9x0mJPHnyBJMmTeI7RotXWlqKgoIC5OfnIz8/H8XFxSgtLUVRURGKiopQVlaG0tJSiEQirrgYGhqiT58+EIvFEIvFKCsrg1gsRlVVFYqLi3k+ooZr3bo11NXVucJV/dPQ0BA6OjrQ1taGrq4u9PX1oaOjAx0dHejp6UFXV5f73dDQEEZGRjAyMuKKH2l6ClOcsrKyAFBxUhYSiQTx8fHcPQ3SOEpLS5GZmYmsrCxkZ2cjMzMTubm5yM/PlytALz6vbew8NTU16OnpQU9PD9ra2tDW1pb7wDY3N4e+vj60tbWhpaXFtWRUVVWhr68PANDT04Oamhq3rnqf1bS1taGhoVHrcby87cuKi4tRVVVV67rqYvnyttWtMZlMxk0VUlRUBKlUivLy8v/L3nuHRXH17//30nvvICBVpNgoIhYQNCoWCIrxMWKJMZo8llQ0atREHzXJNzGxJNFYEkM0alSwRVGwAEYQRVBQFlBpIov0sssue35/+GF+roCgLszucl7XNZc7M2fO3Dsuc8858z7vAz6fDz6fj8bGRsaIGxsbwePxUF1dzZh0bW1th+dXU1NjjOpZ02pdNzY2hpWVFUxNTWFubg4LCwvo6Oh0+D0pHSNT5qSnp9dhU54iX+Tl5UEoFMLNzY1tKXJBTU0NioqK8PDhQxQVFTEG9OjRI/B4PGa9oaFB4jgjIyOYmppK3Cjt7Oza3DSf/ayvr9+hacgKurq6bEuAQCBAbW1th6bf+rmiogK5ubmorKxERUUFnjx5IlFPq9lbWFjAzMwMFhYWzHqfPn1gZ2eHPn36SHRVUmTInMrLy2Fubs62DIqUyMnJgZKSElxcXNiWwjpisRjFxcUoKChAYWEhCgsLUVRUhOLiYsaMamtrmfIGBgawsrKCmZkZrKysYG9vDzMzM1haWsLMzEziRkcHN3cf6urqMDU1hamp6Usd19zcDB6Ph8ePH6OsrIxp4ba2dnNzc5GUlITS0lJUVVUxx+no6MDW1ha2trbo06ePhHE5ODigT58+UFKSmRi2bkdmzInH4730j4Aiu9y9exd2dnbQ0tJiW0qPUVpaiuzsbBQUFEgsd+/eZVo8ampqsLGxgaWlJaysrDBx4kTms4ODAxwdHekTtJyjpqYGa2vrLkUe8/l8lJaWoqCgAKWlpXj06BHz+caNG8jNzWXe8amqqjJG9fzi7u6ucFn/ZcacKisrYWxszLYMipTgcrlwdXVlW4bUEYlE4HK5TOaFO3fu4Pbt27h//z6T+sfQ0BBOTk5wcnLC+PHjsXjxYjg7O8PR0ZH2DlAk0NDQYAymI8rLy5Gfn4+8vDxmycjIwJEjR1BZWQngqXHZ29vDw8MD7u7u8PT0hLu7O1xcXKCqqtpTX0eqyIw51dTUMC9aKfLPw4cP5b5Lr6ysDOnp6cjKymKMKDs7G83NzVBWVoaDgwO8vLwQGRkJV1dXxpDoQxZFmpiZmcHMzAz+/v5t9lVWViIvLw/5+fm4d+8e7ty5gyNHjmDTpk0QiURQU1ODq6srY1geHh7w9vaGlZUVC9/k5ZAZc6qurqaDNRWI4uJijB49mm0ZXaaurg63bt1Ceno6s2RnZwMALC0t4e7ujpEjR2LRokXo378/Bg0aRMOKKaxjZGQEX1/fNvkrhUIhcnNzkZ2dzTxUxcTE4O7duxCLxbC0tMSQIUOYZejQoTL3WkVmzKmmpob2tSsQJSUlMp2KKjc3FxcvXsSVK1eQlpaG3NxcEEJgY2MDb29vzJw5Ez4+PvD29qYDOilyh6qqKtzd3eHu7o5p06Yx22tqapCeno60tDSkpaVh7969WLduHQDA2dkZPj4+GD58OIKCgtCvXz+25AOQIXOqrq6m3XoKQkVFBRobG2UqiW9BQQESExNx8eJFJCYmoqSkBDo6OggICEBkZCRjRJaWlmxLpVC6DX19fYwePVqiV+Px48e4fv060tLSkJqaiujoaNTV1cHS0hKBgYEIDAxEUFAQnJ2de1SrzJgTfeekOJSWlgIAq3kS+Xw+Lly4gNjYWJw9exaFhYXQ0tJCQEAA3n//fQQGBsLX17fd6SMolN6Eubk5QkNDERoaCuBp0E96ejrzIPfxxx+jvr4e1tbWeOONNzB58mSMHTu228ekykxuPVVVVezfvx9vvfUW21Ior8mFCxcQEhKCioqKHg0OqKysxKlTpxhDamhogI+PD0JDQzF69Gj4+vrScUEUyksiFAqRlpaGxMREnD59Gv/++y80NDQwduxYTJkyBRMnToSJiYnUzysT5iQUCqGmpobjx49jypQpbMuhvCZHjhzB9OnTmai27oTP5+Po0aPYu3cvLl68CGVlZQQFBWHKlCmYPHmyXEQlUSjyxOPHjxEXF4fY2FhcuHABQqEQI0aMwNy5czFt2jSptahkYrhxa3ZiRRtE1luprKyEvr5+txpTVlYWli5dCmtra8yZMwc6OjqIiYlBeXk5zpw5g4ULF1JjolC6AXNzc7z77rs4efIkeDweDh48CBMTE7z77ruwsrLCBx98gJs3b772eWTKnGhePcWgsrKyWyLcWlpa8Ndff2Ho0KHw8vLC6dOn8emnn6KwsBDHjh1DZGTkC5OJUigU6aKjo4OpU6fi8OHDKCoqwqpVq5CQkIDBgwfD29sbf/zxR4cJfDtDJsyJz+cDoC0nRaG6ulqq5iQWi7F//364ublh5syZsLW1RUJCAnJzc7F8+XJYWFhI7VwUCuXVMDMzw8cff4ycnBxcuXIFrq6umDt3LlxcXLB79260tLS8VH0yYU605aRY1NfXS22agOTkZPj4+GDu3LkYPnw4cnJycOjQIQQFBYHD4UjlHBQKRboMHz4cMTExyM3NxZgxY7Bo0SIMGjQIiYmJXa5DJsypteUk62n8KV1DIBC89v9lU1MTli1bhpEjR8LY2BgZGRnYs2dPj4+1oFAor07fvn3xyy+/IDMzE3Z2dggODsb777/fZuqX9pCJQR6tzT065kQx4PP5r9VFW1pairCwMHC5XOzZswezZ8+WojrpkpycjPv370tsU1FRgb6+PoyMjODp6SmRmZ3H4+Hs2bPM+pgxY9okgxUIBDh69Cjzd6GkpIRx48bByMgIAoEAv/32G27dugVra2sMHz4cvr6+iI+Px6RJk9roKykp6dLTqpGREUxMTJCbm9vmu7xoeMfL6mmPkpISHD58GFwuF8bGxggMDIS/vz8KCwvR0tLSYxNWVlVVISAgANHR0TL9m5NH+vXrhxMnTuDgwYP473//i6tXr+L48eOws7Pr8BiZaDmJxWIAoN00CsLrtJxKSkowYsQIVFdX4+rVqzJ/kxg2bBhMTU0RFRWFxYsXg8vlgs/n4+bNm9i0aROMjY0xYcIE3L17FwBgamqKsWPH4sqVK5g1axbCwsLazFSrrq6O8ePHIz4+Hj/99BNGjhwJIyMjVFdXY/DgwUhNTcXs2bPh4+ODX375BTo6OkhISGhXX0pKCpYtW4bc3FxUV1cjNzcXs2bNws6dO1FbW4tHjx5h//79+Pjjj+Hr6ws7OzvMmzcPs2bNgp6eHiZPntzhd38VPc+zceNGDB06FAKBAAsWLMDSpUshFAoxfvx4jBgxoo1ZdicqKiowNjZ+qS7p9mYZpnTMW2+9hYyMDCgrKyMgIKDNg50ERAa4du0aAUAePHjAthSKFJg0aRJ5++23X/o4Pp9PPD09ibu7O+HxeN2grPswMjIirq6ubbafP3+eWFhYEA0NDfLvv/9K7HN1dSUAyJw5c9qt848//iCrVq1i1pcsWULc3NyIWCyWKPf++++TZcuWtVvHnj17yKVLl5j1nJwcAoAsWrSI2SYWiyU02NvbE2Nj4xd821fX8yzff/89UVVVJUlJSW32NTU1ET8/P7Jnz55O62GTjz/+mLS0tLAtQ+6orq4mgwcPJq6urqS+vr7dMrTlRJE6IpHolbpoN27ciAcPHuDUqVPdMuK8O+ko80RwcDB2794NPp+PiIgIiSdtbW1t+Pv7Y9++fdiyZUu7dT77FJ+WlgZ1dfU2fyfR0dEd/u24u7tj+PDhL9TO4XCwcOFCifN2JZPGq+hp5cCBA/jwww/x1VdfISAgoM1+DQ0NbN26lZmvSBbJysrCzz//zLYMuURfXx8nTpwAj8fDmjVr2i0jE+ZE/i9JRW+agliR4XA4zP9pVxEIBNixYwc+/fTTF/ZDyyMTJkxAcHAw827lWY4ePQobGxt88sknOH/+/AvrcXNzQ0ZGBhYvXsxMbAgAtra2GDduXLvH+Pr6dunvys/Prwvf5PX1tLJ+/XoAT69NR/j4+GDEiBHMukAgwLlz57By5Ups374d+fn5EuXz8vKwatUqiMVicLlcbNiwAbt27YJQKJQol5SUhJUrV+Lnn3/Gzp07me18Ph/79+/HuXPnOi2fnJyMiRMnoqGhAQcPHpT4f62trcWuXbvw0UcfYdu2baivr39pja1ali9fjtjYWCaiOTY2FgcOHMCBAwdw8OBBpvydO3eY7U+ePOnwmsoSVlZWWLVqFXbt2iVxjRh6tC3XAcnJyQQAKS4uZlsKRQqEhoaSqKiolzrm5s2bBADJycnpJlXdi4WFRbvdeq2sWrWKACDz5s1jtg0ePJgQQsj169eJpqYmMTIyInl5ecz+Q4cOkU2bNjHrXC6XmJiYEADExcWFnDlz5qV1ttet9zwuLi7E0tKy07peVQ+XyyUAiIqKChEIBF06pqmpiQQGBpKDBw+SqqoqsnXrVqKrq0v+/vtvQggh+/btI+bm5gQAiYuLI2+++SYJDQ0lAMjq1auZej777DMSExNDGhoayIEDB4iOjg4h5Ol1CQsLIwDI5s2bOy1/5coVMnPmTAKAnDx5kpw9e5YQQkhubi6ZNGkSOXv2LMnIyCAeHh7E0dGRVFVVdVnjgwcPyIgRI8iuXbtIUVERCQ4OJg4ODqSpqYnk5OQQS0tLAoBwuVzmmJaWFhIcHEy2bdvWpptVlikuLiYAyOXLl9vskwlzSklJIQBIYWEh21IoUmDSpElk1qxZL3XMhQsXCABSUVHRTaq6l87M6ffffycAyJgxY5htreZECCF//vknAUDc3d1JbW0tIaStORFCSGZmJvHy8iIACAAyfvx4kpub22Wd0jSnV9UTHx9PAJB+/fp1Wfd//vMfMnfuXIltU6dOJZqamqSoqIgQ8tRIAJDY2FimTFBQEHFxcSGEENLc3EyMjY3JvXv3mP1Lly5lPpeUlEiYU2fl161bRwBImMGYMWPIsWPHmPUzZ85ImE9nGlvrWLBgAbN+8uRJwuFwyNGjRwkhhMTExBAAjCG2avX29iYikegFV1H2EAgEBIDENWtFJvrRWue4f75pS5FPOBwO8x6xq9jb2wMAM/usotE6rqOj2UZnzJiB5cuX486dO3j77bc77Bb19PREeno6fvjhBxgaGuLMmTMYMGBAm66onuJV9Lzs+8jGxkYcPnwYgwYNkti+aNEiNDU1Ye/evQDAzEz8bFehh4cHiouLATy9z+jq6iIkJARnzpwBAKxcuZIp+3yUXmfln+fRo0eIj49HSkoKVqxYgRUrVuDUqVPw9vZGY2NjlzTm5eUhPj4eYWFhzP7Q0FCUlZUhPDwcADB9+nQ4OTnh22+/ZcocO3YMYWFh3Z5oWdrcuXMHwNPxUM9DzYkidZSVlV86VYmDgwMGDx6Mbdu2dZMqdrl37x4AvHDMzoYNGzBx4kTExcXhiy++6LCciooKlixZAi6Xi6ioKDQ1NWH69OmoqamRuu6u8LJ6WgdSc7lc5l3Ki0hJSYFQKGxjaq31tIabt/duTVtbWyK3W+s7oAkTJmDYsGGoqqpi9rV3/IvKPw+XywUAfPbZZ9i4cSM2btyIrVu3Ii0tjTGSzjTm5OQAaGuUZmZmzGdlZWVER0cjPj4eqampAIDdu3fjnXfe6VCbrLJ161a4urrCy8urzT6ZMKfWyCBqToqBpqYmk/XjZfjyyy9x6NChNkED8k5zczNOnjwJFRUV5um3PZSUlBATEwM3NzesX7++zXXYvHmzxLqxsTF+++03zJgxA9XV1UhOTu4W/c/TehN+VT3W1tZwd3dHS0sLbt++/cJzEUKYB52UlBSJfa0RnS4uLl3WHhoairy8PCxbtgzp6enw9vZmDOF1y7fex27cuNFmX11dXZf0taZwe3agdis8Ho/5HBUVBWtra2zYsAH37t2DgYGB3OWYPHXqFPbt24cvv/yy3ehOmTAn2nJSLLS0tJhujJchNDQUixcvRlRUFP75559uUMYO33zzDXOD6yzbgZ6eHuLi4mBoaNjGnK5cuYKysrI2x7z55psA2j5tt0drd2FH3YbPl3sesViMXbt2vbaedevWAXjayng20u9ZeDwe9u7di0GDBkFdXb2N2bXerJ+N6HsRDQ0N2LVrF4yMjPD999/j4sWLqK+vx4EDB16rfKt5urq6QllZGWvWrJH4TjweDzExMV3S2L9/fygpKeHEiRMSvQ/5+fm4fv06s66mpoZPPvkEJ06cwLJlyySGAsgDly5dwvTp0zF37lxERka2W0amzKmjHylFvtDS0upSd017bNmyBW+99RYmTZqEH3/88aVD0tlAKBRKPNW2IhAI8OGHH2LdunVYsWIFEz7dSklJSbsm7uTkhEOHDrV5fyAWixEVFdUm7DYmJgZeXl4YOnRop1pbzaTd0N3/49GjR6ioqGiT/UAgEGDJkiXM+8HX0RMREYH169fj0qVLePfdd9vkWissLMSmTZswa9YsmJmZYfHixbh//75EKqbjx49j2rRpGDVqFAAwY6Ke/e2JRCIIhUIIBAKIxWKsWbOGadX7+/vD2dmZeQ/Y+j1atXRWvvXf9PR0XLlyBZqamli4cCH+/fdfjBo1Cn/++Sf27duHmTNnYsaMGV3SaGVlhaioKGRmZmLatGlISEjA9u3bsXr16jbh+e+++y6MjY1x//59BAUFdXitZY2dO3di7NixCA0NxS+//NJxwR4NzeiA0tLSDsMJKfLH8uXLyZAhQ175eLFYTP73v/8RZWVl8sYbb5CHDx9KUZ10uXz5MomIiGBCowcNGkTCw8NJREQEmThxIlm4cCFJT0+XOObGjRtk/vz5BACZNm0aiY+Pb7fuLVu2SETrzZw5k0RERJBBgwaRuXPnks8//5y4u7uTwMBAcv/+/U61xsTEEB8fHwKAGBgYkPXr1zORboQQ8u+//zLh0QCIjY0N8fHxIb6+vsTLy4vo6uoSDofDDPl4XT2EEHLkyBHi4eFBNDU1yahRo8gHH3xA3n33XbJ27VqJMPOWlhby0UcfEVNTUxIdHU1mz55NIiMjSVNTEyGEkOPHjxN7e3sCgCxdupQUFBSQgwcPkr59+xIA5NNPPyV5eXlEU1OTeHp6kh9//JGsXbuWzJ07lzQ3N5PCwkKyaNEiAoD079+fnDlzhtTW1nZYnhBCCgoKiLm5OTE0NCS//vorIYSQhoYGEhUVxVxDPT09JhKtKxofP35MampqSHh4OFOHvb09SUtLa/f6ffbZZ+S7777r0rVmm5KSEjJp0iSipKREVq9e3WlmDZkwp5qaGgLglcZtUGSPL7/88qXChDvi6tWrxM3NjWhpaZHo6GhSU1MjBXXyxbNpnFpNQSwWk8zMTJKYmMjq8Atp6qmvrydXr17tNG1VY2MjuXHjBmNKL4NYLCYNDQ2ktraWpKenk7q6utcu39zcTBobG9ts5/F4JD09vd19XaWkpIRkZGQwZtgeEyZMIJWVla98jp6goaGBbNq0iejp6ZG+ffuShISELh0nE+bU0tJCOBwOOXz4MNtSKFLghx9+6PI4mc5obm4mW7ZsIQYGBsTExISsWbNG5v8YKZSeIDk5mbz33ntsy+iQuro6smXLFmJlZUW0tbVJdHR0pw8EzyIT75yUlJSgpaXV5YgWimxjZGQktRQqqqqqWLp0KfLy8vDee+9hy5YtsLe3x8KFC5GWliaVc1Ao8kJqaiqGDx+O9957D9HR0W0iJmWB1pRWffr0werVq/H222+joKAAmzZteqmM7zJhTsDTyJ4XvaSlyA+GhoZobm7u0oRiXcXY2Bjr16/Hw4cPsXbtWly5cgW+vr4YOHAgtm3b9sLxJxSKIsHlclFQUIAtW7ZAX1+fbTkAgJqaGvz888/w8fHBoEGDEB8fj88//xwPHjzA5s2bJcZpdRUOIbIRDuXs7Ix58+ZhxYoVbEuhvCZXr17FsGHDUFhYiD59+nTreX799VccOnQIIpEI48aNw5QpUzBx4kS5y2pOocgblZWVOH36NGJjY3H69GkAwNSpUzF//nwMHz78tWeZkKmWkzSftCnsYWRkBADd3prx9/fH7t27UVpaim3btqG5uRmLFi2ChYUFAgMD8f3336OgoKBbNVAovYmHDx9i69atCAkJgbm5Od555x3U1dXh+++/R2lpKX777TeMGDFCKtMfyUzLKSgoCP3798f27dvZlkJ5TZ48eQITExPEx8cjJCSkR89dX1+Pf/75B7GxsTh16hSqqqrQv39/BAUFITAwEKNGjeowvx2FQpHkyZMnuHz5Mi5evIjExERkZWVBX18f48ePR1hYGMaPHw89Pb1uOffLzwjXTUjzJTqFXYyMjKChoYFHjx71+Ll1dHQwdepUTJ06FSKRCJcuXcK5c+dw8eJF/PzzzxCLxXB3d8fo0aMRGBiIkSNHwtjYuMd1UiiySFVVFa5cuYLExETGjDgcDgYOHIixY8fi22+/RWBgYJcmo3xdZMacWkc6U+QfDocDc3NzVszpWVRUVBAcHIzg4GAAT0f+X716FefPn0dSUhJ++uknCIVCWFpaYsiQIRgyZAiGDx8Of39/Jns0haKoCIVC5ObmIjk5GUlJSUhPT8fdu3chFovh4OCAkJAQrFy5EsHBwUxXfU8iU+b0bO4oinxjaWnJujk9j7a2NkJCQpiuxtbkpGlpaUhLS8OOHTuwbt06qKiooH///vDx8YG3tzcGDBgAd3f3buu+oFC6m7q6OuTk5ODWrVvM7/327dsQiUQwNjaGj48PIiIi4OPjg4CAAFbM6Hlkypxot57iIIvm9DwGBgYIDQ1FaGgos+3BgwdITU1l/oAPHTrEjL+zs7ND//794enpCXd3d3h4eMDNzY3JJE2hsI1AIEB2djbu3LmD27dv486dO7hz5w4ePHgAQgi0tbUxePBgjB49GtHR0fDx8YGjoyPbstuFmhOlW7C2tsbNmzfZlvHS2Nvbw97ensmUTAjBgwcPmD/0rKwsnDt3Dlu2bEFzczOUlZXh4OAAFxcXODs7w8nJiVns7OxeemI9CqUzWlpa8PDhQ+Tl5Uks9+7dQ35+PlpaWqCmpgZXV1e4u7tj/vz5zMNU3759251TShaRmWi9uLg4TJkyBU1NTdDQ0GBbDuU1+e677/Dtt9+itLSUbSndgkgkQl5eHmNaXC6XuUm0PmSpqqrC3t6eMStHR0fY2dnBxsYGffr0gbm5OcvfgiKrlJeXo7i4GEVFRXj48CHy8/OZ39eDBw+YGRwMDQ2Z35ezszNjQs7OzsxsD/KKzJhTamoq/Pz8UFBQ0O6UvRT5IjY2FuHh4airq+t1wQVVVVVtnmrz8vJQUFAgMf+Ruro6+vTpAxsbG9ja2sJCEmOCAAAgAElEQVTW1hY2NjaMeZmamsLMzEzupt6mdIxYLEZ5eTl4PB5jPsXFxXj48CGzXlRUJDFZp7m5Ofr27csY0LOtc1l4N9RdyIw5FRcXo0+fPkhKSkJAQADbciivye3bt+Hp6YmsrCx4eHiwLUdmEAgEzE2osLAQhYWFKC4uZm5QRUVFEtObKykpMSZlaWkJc3NzmJqawsrKCmZmZjA3N4eZmRkMDQ1hZGQEXV1dFr9d76S+vh6VlZWoqqoCj8dDWVkZysvL8ejRIzx+/Jj5XF5ejvLycojFYuZYPT099OnTB7a2tsyDip2dHfO5T58+vbYnSWY6xC0sLKCsrKyw3UC9DQcHB3A4HOTn51NzegZ1dXU4Ojq+8CV0XV0dSkpKUF5ejrKyMuYGV1paivLycty7dw+lpaXg8XhtJgRUVVVljKqjf3V1daGjowN9fX1oa2tDW1sbenp60NXVhba2NrS0tLr7MsgMTU1NaGhoQG1tLWpra9HY2IiGhgZUV1ejvr5ewnie/ffZz8/P4K2mpgYzMzNYWFjAwsICVlZW8Pb2Zh4mLC0tYWpqCmtraxoB+gJkxpxUVFRgYmJCzUlB0NLSgoWFBU0f9Aro6uqiX79+6NevX6dlq6qqUFFR0ekN9MGDB8x6fX19pzMAGBoaMsalo6MDDocDAwMDRp+Kigo0NDSgqakJJSUlJgGpnp6eRDeklpYW1NXV2z2HtrZ2u4M5hUJhh0mgn08oLBaLmZZmbW0tWlpa0NTUBD6fj5aWFtTW1gJ4mphULBajvr4ejY2NqK+vR3V19QtnWtbR0YGOjo6EsRsZGcHJyalD4zcxMVHorraeRGbMCQCsrKxkPvyY0nUcHR2Rn5/PtgyFxtDQEIaGhq90bE1NDRoaGpiWQ1VVFbZt24YrV65g7dq1EAqFzH6RSMQYWuuNvrKyEgKBQGLf8zf81rLt8SJz6Og7PWuSz5fV0dGBqqoq1NTUoK2tDRUVFTg4OEjs09LSgra2NnR1daGvr8+s6+vrMy1HbW3tNueg9DwyZ0605aQ4UHOSbfT19ZkWD4/Hw2effYarV6/ip59+wuzZs1lWR+ntyJQ5WVtbg8vlsi2DIiUcHR1x9epVtmVQOuH69euIiIiAmpoarl27Bk9PT7YlUSiyM2UG8HQE/sOHD9mWQZESjo6OePDgAVpaWtiWQumAnTt3IiAgAJ6enkhNTaXGRJEZZM6cioqK6M1MQXB0dERzczMKCwvZlkJ5Dj6fj/nz52PhwoX48MMPERcX98rvriiU7kCmuvXs7e0hFApRWlrarTOoUnqG/v37g8Ph4Pbt23RgtQxRVFSEiIgI3Lt3D8eOHcOUKVPYlkShtEGmWk729vYAnibfpMg/urq66Nu3LzIzM9mWQvk/EhMT4e3tjebmZty8eZMaE0VmkSlzsrS0hLq6OjUnBcLLywu3bt1iW0avhxCCzZs3Y8yYMQgJCUFKSgoTZk2hyCIyZU5KSkqwtbWlQREKxIABA6g5sUxdXR2mTZuGVatWYcOGDYiJielVWSAo8olMmRPwNO0NHRujOAwYMAB5eXkdjvindC93796Fn58frly5gnPnziE6OpptSRRKl5A5c3JxcUFubi7bMihSwsvLC2KxGHfu3GFbSq8jNjYWfn5+MDY2RkZGBoKCgtiWRKF0GZkzJ2dnZ2pOCoSDgwP09PRo114PIhKJsHz5coSHh+Ott97ChQsXYGlpybYsCuWlkKlQcuBpy6k1kSVNoCj/cDgceHh40Ii9HqKiogJvvfUWkpOTsXv3bsydO5dtSRTKKyFzLScXFxcAoK0nBYIGRfQM6enp8Pb2BpfLxZUrV6gxUeQamTMnOzs7aGhoUHNSILy8vJCZmfnC6Qkor8fOnTsxbNgwuLu7IyMjA97e3mxLolBeC5kzJyUlJTg4OODevXtsS6FICR8fH9TW1uLu3btsS1E4BAIB3n33XSYN0YkTJ2gaIopCIHPvnADA3d2dRncpEAMGDIC2tjauXr0KNzc3tuUoDEVFRZg6dSru3r2Lv//+G+Hh4WxLolCkhsy1nADA09OTvkBXIFRUVDBkyBA6fYYUuXjxIry9vcHn83Hjxg1qTBSFQybNycvLCw8ePGCmWKbIP/7+/khJSWFbhtzTmoYoJCQEwcHBSElJgaOjI9uyKBSpI7PmRAjB7du32ZZCkRL+/v7IyclBVVUV21Lklrq6OkRGRjJpiP78809oa2uzLYtC6RZk0pzs7e2hp6dHu/YUCH9/fxBCkJqayrYUueTevXsYOnQoLl26hLNnz9I0RBSFRybNicPhwNPTE1lZWWxLoUgJMzMzOm37KxIXFwc/Pz8YGhoiIyMDo0ePZlsShdLtyKQ5Af//2BiK4kDfO70cLS0tWL58OcLCwjB9+nQkJCTAysqKbVkUSo8gs+bU2nKiAzcVB39/f1y7dg0tLS1sS5F5KioqMG7cOPzwww/49ddf8csvv0BNTY1tWRRKjyGz5uTl5YWamhoUFhayLYUiJYYNG4ba2loa6NIJN27cgI+PD3Jzc3H58mXMmzePbUkUSo8js+bk6ekJDodDu/YUCC8vL5iYmCAxMZFtKTLL77//juHDh6Nfv364efMmfHx82JZEobCCzJqTnp4e7OzsaFCEAqGkpISRI0ciISGBbSkyh0AgwIIFCzBnzhwsWbIEJ0+epFn5Kb0amUxf1IqXlxc1JwUjODgYy5cvh1AohKqqKttyZILi4mJMnToV2dnZOHLkCN588022JVEorCOzLSeARuwpIqNHj0ZdXR3S09PZliITXLp0Cd7e3qipqcG1a9eoMVEo/4dMm5Onpydyc3PB5/PZlkKREv369YONjU2v79ojhOCHH35ASEgIgoKCcP36dZoUl0J5Bpk2p8GDB0MkEiEjI4NtKRQpEhQU1K451dXVsaCm56mvr8f06dPxySefYP369TQNEYXSDjJtTo6OjjAxMcG1a9fYlkKRIqNHj0ZycjKamppw9+5dfP311/D39+8VkWm5ubkYOnQoEhMT8c8//yA6OhocDodtWRSKzCHTAREcDgc+Pj40H5sCIRKJoKOjAz6fDwcHB5SVlUFVVRUikUjhu7VOnDiBWbNmwcnJCdevX4ednR3bkigUmUWmW04A4OfnR1tOck5DQwNOnDiBBQsWwNzcHNOmTYOSkhLKysoAAEKhEIQQ6Orqsqy0e2hpacHatWuZNEQpKSnUmCiUTpALcyooKEBFRQXbUiivyPr16zF58mTs2bMHlZWVAACxWNymnI6OTk9Le234fP4LpwF58uQJJkyYgE2bNuGXX36haYgolC4i8+bk6+sLALRrT4758ssvMXjwYCgpvfjnpqen10OKpMdXX32FGTNmtGu2rRkecnJycPnyZcyfP58FhRSKfCLz5mRkZAQnJyfatSfHqKqq4vDhw1BTU+vw5b+ysrLcdetlZmZi8+bNOHv2LNauXSuxb//+/QgICICdnR2uX7/OPGRRKJSuIfPmBDxtPVFzkm8cHBywZ8+eDrPMKykpyVU4tVgsxvz585nW4Pr163H06FEIBAIsXboUs2fPxpIlS3D+/HmYmZmxrJZCkT/kwpz8/PyQlpZGp8+QcyIjIxEVFQUVlbZBohwOR67M6ccff0R6ejqEQiGzbebMmfDz88PevXtx+PBhbNq0CcrKyiyqpFDkF7kxp8rKSuTl5bEthfKa7NixA3Z2dm0MSp7MqbCwEJ9//rnEeyZCCEQiEe7du4fExERERESwqJBCkX/kwpwGDhwIdXV12rWnAGhra+PYsWNt3j0RQuTGnBYtWgSRSNRmu0gkQktLC7766ivayqdQXhO5MCc1NTUMHDiQmpOC4OnpiW+++UbCoOTFnP7880+cPn1aojvvWYRCIeLi4rBly5YeVkahKBZyYU4AHYyraCxZsgQTJ05kps0Qi8Uyb05PnjzBf//7307TDRFC8Mknn+DSpUs9pIxCUTzkxpx8fX1x69YtmqFcQeBwONizZw8MDQ2hrKyMlpYWaGlpsS3rhXz00Ueor69/YZddq9nq6enhwoULPSWNQlE45Mac/Pz80NzcTDOUKxAmJiY4dOgQc7OX5QwRFy9exP79+9vtzlNVVQWHw4GWlhYiIyMRFxeH8vJyfPnllywopVAUA7kxJ0dHR5ibmyMpKYltKRQpMmrUKHz++ecAILMtp6amJsyZM0ciw4WysjKUlJSgpqaGMWPGYN++feDxePjjjz8wadIkOssvhfKayI05cTgcjBgxApcvX2ZbCkXKrFmzBgEBATLbclq7di0ePnwIQgiUlJSgqqqK0NBQHDhwAFVVVTh16hSioqJk1lwpFHmEQ+Qo5nXr1q1YvXo1njx5Qgc3yim1tbVoaWlBdXU1WlpaUFNTA+Dp2CE+nw9TU1OJ8s3NzWhoaGi3LgMDg3aDE1q3KysrQ09PD2pqatDW1oaGhgY0NTVfSm9rfjwOh4OQkBD85z//wZQpU+QyDyCFIk/IlTndunULAwcOREZGBgYMGMC2nF5Fc3MzeDwes1RXV6O6uho1NTXM8vx6bW0tmpqawOfz0dDQgObmZra/BoCnY63U1NSgq6sLNTU16Ovrw9DQEPr6+jAwMIC+vj709fWhp6eH8+fPw87ODuPGjYODgwNMTU1hampKJwikULoZuTInsVgMU1NTrFmzBkuWLGFbjkLw5MkTlJSUoLCwEEVFRXj8+DF4PB4ePXrEGNHjx49RXV3d5thnb+TPfn725q6lpQV1dXXo6OhAVVUVenp6UFZWhr6+PpSUlGBoaAjgabetgYFBm3MoKSlBX1+/zfaWlhbU1ta22S4SiZjp3oVCIerr6yEQCNDY2Ag+n4+mpiY0NjZCIBAw+2pqalBVVdWh0T7fclNWVoapqSlMTExgZmYGCwsLxrRsbGxgY2MDa2tr2Nra0q4+CuUVkStzAoDJkydDXV0dhw8fZluKXFBSUoK8vDzk5eXh4cOHKCwsRHFxMYqLi1FYWIimpiamrKGhISwtLWFqagoLCwuYmZnB1NQUZmZmMDc3Z27AZmZm7RqJoiISiVBZWcmYdVlZmYRxtxp6eXk5SkpKJK6psbExY1R9+vSBtbU1HB0d4eTkBCcnp151HSmUl0HuzOnbb7/F119/jcePH9Oulf+joqICt2/fZkyIy+UynxsbGwE8DdO2t7eHra0trK2tYWNjA1tbW+Yp387Ojj7lS4mKigoUFxejqKgIRUVFKCkpQVFREfNgUFhYyISkm5iYwMnJCc7OznB2dmY+9+/fn/5/UHo1cmdOqamp8PPzQ3Z2Ntzc3NiW06M0NzeDy+UiPT0d2dnZuHPnDrKzs1FQUAAAUFdXh7W1Nfr37w93d3c4ODgwi729faeT/VF6BpFIhMLCQhQUFLRZsrOzmZaXpaUlhgwZAnd3d+b/1MPDA+rq6ix/Awql+5E7cxKJRDAyMsI333yD9957j2053YZAIMDNmzeRmprKLPn5+RCLxdDU1ET//v3h4eEBDw8PeHl5wd3dHdbW1mzLprwmIpEI+fn5yMrKQlZWFu7cuYPMzEwUFBSgpaUFGhoa8PT0hK+vL7O4urrSXgSKwiF35gQA48aNg4mJCf744w+2pUiNwsJCXL58GdeuXUNqaioyMjLQ3NwMQ0ND+Pn5wcfHBwMGDICnpyccHR1pKH0vo6mpCdnZ2cjKysKNGzeY34hAIICBgQFjVH5+fhgxYkS7QSQUijwhl+a0YcMG/PzzzygqKmJbyitTXl6OS5cu4fz580hKSkJ2djZUVFTg4uKCIUOGYPjw4QgICICbmxvtjqO0S+v8Uenp6UhOTkZSUhLu3r0LDoeDgQMHIiAgAMOHD8fYsWOpWVHkDrk0p6SkJIwYMQL5+flwcHBgW06XEAqFuHTpEuLi4nDhwgVkZ2dDVVUVvr6+GD16NIKCguDv7w8NDQ22pVLkmIqKCly8eBGJiYlISEjA3bt3oaamBj8/P4wdOxZhYWHw8PBgWyaF0ilyaU6t3V3bt2/HnDlz2JbTIQ0NDfjnn39w/PhxnDp1ClVVVRg4cCDGjh2LoKAgjBgxQuaniaDIN6WlpYxRnTlzBo8ePYKjoyPCw8MxZcoUDBs2jLbMKTKJXJoTAAQFBaFv377Ys2cP21IkEIlEOHXqFPbt24d//vkHQqEQAQEBCAsLQ1hYGPr27cu2REovRSwWIzU1FcePH8exY8eQm5sLc3NzTJ06FfPmzcPgwYPZlkihMMitOa1ZswYxMTHIy8tjWwoA4O7du9izZw/279+P8vJyjB49GjNmzMCkSZPa5IujUGSBnJwcHDt2DPv378fdu3cxcOBAzJs3DzNnzoSRkRHb8ii9HLk1p4SEBAQHB6OoqAg2NjasaCCE4NSpU9i8eTOSkpJga2uLuXPnYs6cObC3t2dFE4XyKiQnJ2PPnj04dOgQhEIhIiMjsWLFil43lpAiO8htZ/OwYcOgoaGBhISEHj+3WCzG0aNHMWTIEEyePBmGhoY4e/Ys7t+/j7Vr11JjosgdAQEB2L17Nx49eoTt27cjPT0dHh4eiIyMxK1bt9iWR+mFyK05aWhoYNiwYT0+Ffa5c+cwYMAATJs2DY6Ojrhx4wbi4uIwduxY+mKZIvfo6OjgnXfeQVZWFg4dOgQul4tBgwYhPDwc9+/fZ1sepRch13fT4OBgnD9/Hj3RM1lRUYGoqCi88cYbcHV1RVZWFg4fPoyBAwd2+7kplJ5GSUkJERERzMNXXl4ePD098d1336GlpYVteZRegNybU2lpKXJycrr1PH/99Rfc3NyQmJiI2NhYHDlyBP379+/Wc1IosgCHw8HEiRORnp6O6OhofP755/Dz88OdO3fYlkZRcOTanLy9vWFoaNhtXXtisRiffvopZsyYgcjISGRnZ2Py5Mndci4KRZZRU1PD6tWrkZGRAXV1dfj7+yMuLo5tWRQFRm6j9VoJDw8HIQTHjx+Xar2EECxYsAD79+/Hr7/+irfffluq9b8KycnJbfr9VVRUoK+vDyMjI3h6ekpMs8Dj8XD27FlmfcyYMTA3N5c4XiAQ4OjRo0xXjZKSEsaNGwcjIyMIBAL89ttvuHXrFqytrTF8+HD4+voiPj4ekyZN6pLmkpISHD58GFwuF8bGxggMDIS/vz8KCwvR0tLSYy3QqqoqBAQEIDo6GrNnz+6RcyoqQqEQH3zwAfbu3YuYmBhERkayLYmigMh1ywl42rWXkJDAzI8jLb788kv8/vvvOHLkiEwYE/A0QtHU1BRRUVFYvHgxuFwu+Hw+bt68iU2bNsHY2BgTJkzA3bt3AQCmpqYYO3Ysrly5glmzZiEsLAwCgUCiTnV1dYwfPx7x8fH46aefMHLkSBgZGaG6uhqDBw9GamoqZs+eDR8fH/zyyy/Q0dHpcoTkxo0bMXToUAgEAixYsABLly6FUCjE+PHjMWLECOTm5kr9GnWEiooKjI2NoaOj0+Vjnr9WlKeoqqpi586d+O9//4u3334bKSkpbEuiKCJEzsnJySEASEpKitTqvHr1KlFSUiI7duyQWp3SxMjIiLi6urbZfv78eWJhYUE0NDTIv//+K7HP1dWVACBz5sxpt84//viDrFq1illfsmQJcXNzI2KxWKLc+++/T5YtW9apxu+//56oqqqSpKSkNvuampqIn58f2bNnT6f1sMnHH39MWlpa2JYhs4jFYjJx4kRia2tLGhsb2ZZDUTDkvuXUr18/2NjYSPW908qVKzFq1CgsWrRIanVKEzU1tXa3BwcHY/fu3eDz+YiIiJB48tfW1oa/vz/27duHLVu2tFvns62KtLQ0qKurt5knKDo6utO5gw4cOIAPP/wQX331FQICAtrs19DQwNatW1FZWfnCetgkKysLP//8M9syZBoOh4Nff/0VVVVV2L59O9tyKAqG3JsT8PSmLC1zKi4uRmJiIj799FOp1NfTTJgwAcHBwcy7nmc5evQobGxs8Mknn+D8+fMvrMfNzQ0ZGRlYvHgxmpubme22trYYN27cC49dv349o6UjfHx8MGLECGZdIBDg3LlzWLlyJbZv3478/HyJ8nl5eVi1ahXEYjG4XC42bNiAXbt2tenOTUpKwsqVK/Hzzz9j586dzHY+n4/9+/fj3LlznZZPTk7GxIkT0dDQgIMHD0pcx9raWuzatQsfffQRtm3bhvr6+pfW2Kpl+fLliI2NZWa+jY2NxYEDB3DgwAEcPHiQKX/nzh1m+5MnTzq8pmxgbm6O2bNnY//+/WxLoSgabDfdpMHvv/9O1NTUSH19/WvXdfz4ccLhcEhTU5MUlHUPFhYW7XbrtbJq1SoCgMybN4/ZNnjwYEIIIdevXyeamprEyMiI5OXlMfsPHTpENm3axKxzuVxiYmJCABAXFxdy5syZLmnjcrkEAFFRUSECgaBLxzQ1NZHAwEBy8OBBUlVVRbZu3Up0dXXJ33//TQghZN++fcTc3JwAIHFxceTNN98koaGhBABZvXo1U89nn31GYmJiSENDAzlw4ADR0dEhhDzt+g0LCyMAyObNmzstf+XKFTJz5kwCgJw8eZKcPXuWEEJIbm4umTRpEjl79izJyMggHh4exNHRkVRVVXVZ44MHD8iIESPIrl27SFFREQkODiYODg6kqamJ5OTkEEtLSwKAcLlc5piWlhYSHBxMtm3b1qabVRY4evSozP/NUOQPhTCn0tJSwuFwunwDfRG//fYb0dTUlIKq7qMzc/r9998JADJmzBhmW6s5EULIn3/+SQAQd3d3UltbSwhpa06EEJKZmUm8vLwIAAKAjB8/nuTm5r5QW3x8PAFA+vXr1+Xv85///IfMnTtXYtvUqVOJpqYmKSoqIoQ8NRIAJDY2likTFBREXFxcCCGENDc3E2NjY3Lv3j1m/9KlS5nPJSUlEubUWfl169YRABJmMGbMGHLs2DFm/cyZMxLm05nG1joWLFjArJ88eZJwOBxy9OhRQgghMTExBABjiK1avb29iUgkesFVZI/ExEQCgDx+/JhtKRQFQiG69SwtLeHm5iaVrj0rKys0NTWhrKxMCsrYoaGhAQA6zIY+Y8YMLF++HHfu3MHbb7/dYYYNT09PpKen44cffoChoSHOnDmDAQMGtOkaexYVFZWX0trY2IjDhw9j0KBBEtsXLVqEpqYm7N27FwCYea+e7Sr08PBAcXExgKcRZLq6uggJCcGZM2cAPH132MrzUXqdlX+eR48eIT4+HikpKVixYgVWrFiBU6dOwdvbG42NjV3SmJeXh/j4eISFhTH7Q0NDUVZWhvDwcADA9OnT4eTkhG+//ZYpc+zYMYSFhUFZWblDfWxSUFAADQ0NmJiYsC2FokAohDkBQEhIiFTMadiwYdDW1saRI0ekoIod7t27BwAvHEO0YcMGTJw4EXFxcfjiiy86LKeiooIlS5aAy+UiKioKTU1NmD59Ompqatot7+zsDADgcrnMu5QXkZKSAqFQ2MbUWutpDTdvL2+htrY2RCIRs976DmjChAkYNmwYqqqqmH3tHf+i8s/D5XIBAJ999hk2btyIjRs3YuvWrUhLS2OMpDONrZlMnjdKMzMz5rOysjKio6MRHx+P1NRUAMDu3bvxzjvvdKiNbY4cOYLg4GCaW5IiVRTm1xQcHIyMjAzweLzXqkdLSwvz5s3Dxo0bUVtbKyV1PUdzczNOnjwJFRUV5mm8PZSUlBATEwM3NzesX7++TfDE5s2bJdaNjY3x22+/YcaMGaiurkZycnK79VpbW8Pd3R0tLS24ffv2C7USQpjBv8+PlWl9CndxcXlhHc8SGhqKvLw8LFu2DOnp6fD29n5haquXKd8aIXnjxo02++rq6rqkT1NTEwAkBka38uzvNioqCtbW1tiwYQPu3bsHAwMDWFhYdOkcPc3Fixdx5swZLF68mG0pFAVDYcwpKCgIKioqUplCY/Xq1SCEYO7cuRCLxVJQ13N88803zA23s+wLenp6iIuLg6GhYRtzunLlSrtdm2+++SaAtk//z7Ju3ToAT1sZz0b6PQuPx8PevXsxaNAgqKurtzG71pv1sxF9L6KhoQG7du2CkZERvv/+e1y8eBH19fU4cODAa5VvNU9XV1coKytjzZo1Et+Jx+MhJiamSxr79+8PJSUlnDhxQiJ5an5+Pq5fv86sq6mp4ZNPPsGJEyewbNkyLFy4sEv19zSPHz/GrFmzMGXKFLzxxhtsy6EoGiy/85Iq/v7+ZP78+VKp69KlS0RdXZ3Mnz9fpgZiNjc3E2Vl5TYBEXw+nyxbtoyoqqqSFStWED6fL7Hf3NycNDQ0tFtnfHw8UVZWlgiIGD9+PBkzZgypq6uTKBsWFka8vLw6jcRbv3494XA4JCoqqk0U5cOHD8lHH31EmpubCSGEfPLJJwQASUhIYMr88MMPZNq0aUxAwocffkgAMAEcrcdxOBzC5/NJbW0tsbS0lIgYc3FxIT/++CMhhJBHjx4RAOSLL74ghJBOy+/YsYMAIP/++y+5fPkyaWpqIh988AEBQIYOHUpiYmLI3r17yZgxY0h1dXWXNBJCyJw5cwgAEh4eTi5cuEC2bdtGZsyY0SYKr76+npiYmLww8IVNysvLiaenJ3F2diaVlZVsy6EoIAplTl988QWxsbGRWn0nT54k6urqZOLEiaSmpkZq9b4qly9fJhEREUyo9qBBg0h4eDiJiIggEydOJAsXLiTp6ekSx9y4cYPMnz+fACDTpk0j8fHx7da9ZcsWCXOaOXMmiYiIIIMGDSJz584ln3/+OXF3dyeBgYHk/v37XdJ75MgR4uHhQTQ1NcmoUaPIBx98QN59912ydu1aCXNraWkhH330ETE1NSXR0dFk9uzZJDIykjGO48ePE3t7ewKALF26lBQUFJCDBw+Svn37EgDk008/JXl5eURTU5N4enqSH3/8kaxdu5bMnTuXNDc3k8LCQrJo0SICgPTv35+cOXOG1IHL1eIAACAASURBVNbWdlieEEIKCgqIubk5MTQ0JL/++ishhJCGhgYSFRXFRC/q6ekx0Xtd0fj48WNSU1NDwsPDmTrs7e1JWlpau9fvs88+I999912XrnVPkpmZSfr27UscHR1JYWEh23IoCopCmVNycjIBQLKzs6VW59WrV4mlpSWxsrJiwn0VFR6Px3wuLi4mhDxNUZOZmUkSExNf+UZUX19Prl69KlF/ezQ2NpIbN2680ngZsVhMGhoaSG1tLUlPT2/T4nuV8s3Nze2m5eHxeCQ9Pf21UvaUlJSQjIwMxgzbY8KECTLVKhEKhWTLli1EW1ubBAQE0NBxSreiUOYkEomIkZGR1J82nzx5QhYsWMC0PugfJaW7SU5OJu+99x7bMhhu3rxJvL29iaamJlmzZk2XB1hTKK+K3E+Z8TytYc7//POP1Os+ffo0Fi1ahLq6OixduhRLliyBoaGh1M9D6Z2kpqbio48+gru7O7Kzs3Hy5Eno6+uzqik7Oxv/+9//cPDgQYwcORI7d+6Ek5MTq5oovQOFidZr5Y033sClS5eYgZHSZMKECbh9+zaWLVuGH3/8EXZ2dlixYgXKy8ulfi5K74TL5aKgoABbtmxh1Zhu3ryJqVOnwtPTEzdv3sT+/ftx4cIFakyUHkPhWk6PHj2CtbU1Tp8+3WmC0tehrq4OO3bswHfffYf6+npMnz4d8+bNw/Dhw7vtnBRKd8Ln83Hs2DHs3r0bCQkJGDhwIFauXInw8HA6wJbS4yjcL87S0hIeHh7tDnSUJrq6uoiOjsb9+/fx9ddf4+bNmxgxYgT69euHr7/+Wq7TH1F6F63Z562srBAVFQUtLS2cOnUK6enpiIiIoMZEYQWFazkBTwd/njhx4oXZAbqDGzduYM+ePfjzzz9RV1eHoKAghIeHY/LkybC2tu5RLRTKi7hx4wZiY2Nx7NgxZGVlwdXVFXPnzkVUVBQsLS3ZlkehKKY5XbhwASEhIcjPz4eDg0OPn5/P5yM2NhZ///03zpw5g4aGBnh7eyM8PBxTpkzpNHMDhSJtRCIRLl++jNjYWMTGxuLhw4fo06cPpkyZgunTp9PuaIrMoZDm1NzcDGNjY3zzzTesp37h8/lISkrCiRMncOTIEZSWlsLCwgIjRoxASEgIxo4dC3t7e1Y1UhSTgoICnD9/nlmqqqrg4OCAiRMnYtq0aQgICOh0VmMKhS0U0pwAYPLkyVBWVsaxY8fYlsIgFotx7do1nD9/HgkJCbh69SoEAgGcnZ0xevRojBo1Cv7+/tSsKC+NSCTC7du3kZKSgsTERFy8eBEVFRUwNjZGYGAgRo8ejTfeeAOOjo5sS6VQuoTCmtP27duxYsUKPHnyBKqqqmzLaZempiakpKQgISEBiYmJSEtLg0gkgpmZGXx9feHr6wsfHx/4+vrCyMiIbbkUGeL+/ftITU1llhs3bqCxsRG6uroYNWoUgoKCMHr0aHh5edGABopcorDmdP/+fTg4OODixYsYNWoU23K6RGNjI27cuMHccK5du4YHDx4AeDq/0YABA+Dh4QEPDw94eXnBwcFBZiego0iHpqYmZGdnIysrC3fu3EFmZiZu3rwJHo8HFRUVeHh4wM/Pj3mYcXNzo78JikKgsOYEPL2hT5s2Df/73//YlvLKlJeXIzU1FWlpacjKykJmZibu378PsVgMTU1NuLu7w9PTE+7u7nBxcYGzszP69u0LdXV1tqVTXoKamhrk5eUhLy8Pd+/exe3bt5GZmYn8/Hy0tLRAXV0d/fv3h6enJwYMGABfX18MHjwYWlpabEunULoFhTanxYsXIzk5ud0J4uSZhoYGZGdnIzMzE7dv32aW1rFVSkpKsLW1hZOTE7M4OzvDwcEBNjY2MDAwYPkb9D4IISgrK0NhYSEKCgoYI+JyucjLy2Pmr1JRUYG9vT08PT3h4eEBT09PeHp6wsnJqc1swRSKIqPQ5nTy5ElMnjwZJSUlvWLsRl1dHfLz85kb37NLSUkJU05bWxt2dnawsbGBjY0N+vTpA1tbW9jY2MDKygqmpqYwMTGh3UNdhM/no6KiAmVlZXj06BEePnyI4uJiFBcXo7CwEEVFRSgtLWUmKVRVVYW9vb3Ew0Pr0rdvX5l9R0qh9CQKbU4NDQ0wNjbGzp07ERUVxbYcVmlsbMSDBw9QVFSE4uJiFBUVobCwkLmJPnz4UCIfIYfDgampKWNUFhYWMDMzg4mJCUxNTWFoaAh9fX0YGBhAX1+fWV40Q648UFVVhZqaGmaprq5GTU0NqqqqwOPxUF5ejsePH4PH46GiogKPHj1qM027iYlJG9O3sbFhHgj69OlDW0EUSicotDkBQEhICMzNzbs8lXZvprKyEmVlZeDxeHj8+DHKy8slbsIVFRXg8Xjg8Xiorq6WmGq8FRUVFcaoDA0NoaqqCh0dHaipqUFbWxsaGhrQ1NSElpYW1NXVoaOjw7QUWss+z7NlWmlsbIRAIGhTtqqqqk2Z+vp6CIVC1NXVQSQSoaamBmKxGFVVVRAKhRJG1B4aGhowMDCAqakpzMzMYG5u3q5pm5mZwdraGpqami913SkUSlsU3pz+3//7f9i4cSPKysro06qUqa+vZ1oWHbU2RCIRcnJykJSUhMDAQIjFYvD5fDQ0NKC5uRm1tbWMyTU1NYHP57c5T3V1NZ7/mbaa3fPo6uoy/8+tRqitrQ01NTVmn4GBAZSUlGBgYABVVVWJFmBri7B1MTAwoMElFAoLKLw55efnw8nJCQkJCQgKCmJbTq+jrKwMgwYNwsiRI/HXX3+xLYdCocgJCj86z9HRER4eHjh+/DjbUnodIpEIkZGR0NXVxa5du9iWQ6FQ5AiFNycACA8Px/Hjx9t0DVG6l1WrViEtLQ2HDh2Cnp4e23IoFIoc0SvMKSwsDIWFhbh58ybbUnoNp0+fxtdff40dO3Zg4MCBbMuhUChyhsK/cwKeDoB0dnZGWFgYvv32W7blKDxFRUUYPHgwxo4dS6MkKRTKK9ErWk4cDgdvv/02/vjjD4hEIrblKDRCoRBvvfUWLCws6HsmCoXyyvQKcwKA2bNno7y8HOfPn2dbikLz6aefIjMzE4cOHaJ53ygUyivTa8ypb9++CAgIwO+//862FIXlxIkT+PHHH7Fjxw64ubmxLYdCocgxvcacACAqKgrHjx+XyCJAkQ75+fmYNWsW3nvvPcyaNYttORQKRc7pFQERrdTX18Pa2hpr167Fhx9+yLYchUEgECAgIABCoRD//vsvTd9DoVBem17VctLR0cGsWbOwfft2iMVituUoDMuWLUNubi4OHTpEjYlCoUiFXmVOAPDBBx+goKAA8fHxbEtRCP766y/88ssv2Lt3L1xdXdmWQ6FQFIRe1a3XSlBQEHR1dREXF8e2FLmGy+XC29sb8+bNw/fff8+2HAqFokD0SnP6+++/ERkZiZycHLi4uLAtRy7h8/nw9/eHmpoarly5AjU1NbYlUSgUBaLXdesBT3PtOTo60mwRr8Gi/6+9O4+Lqt7/B/6aGQYQBGRRdg01kUUUWcJU8JFianAVzWsUblezNCxDyuxLLhmF3fsw9yxvmuRCqRgKpSAqqLiBK5uiICEGgSwOwzAzMJ/fH/44l2lAAYEzyvv5eMxjnHPOnPMe6jGv+ZzzOZ/PwoUoLCxETEwMBRMhpMN1y3ASCoUIDw9HdHQ07t+/z3c5z5ydO3di165d2LlzJxwcHPguhxDyHOqW4QQ8GjHCzMwMGzdu5LuUZ0pmZiZCQ0Px8ccfY/LkyXyXQwh5TnXLa06NoqKiEBUVhbt376JXr158l6P1ampq4O3tDRMTE6SmpmpMnU4IIR2l27acAGDRokUQiUTU06yVFi1ahPLychw4cICCiRDSqbp1OBkbGyMsLAzr169HRUUF3+VotW+//RZ79uzBTz/9BFtbW77LIYQ857p1OAHABx98AD09Paxbt47vUrTW9evXsXTpUnz22Wd49dVX+S6HENINdOtrTo3Wrl2LyMhI5Ofnw8LCgu9ytIpEIoGXlxdsbGyQlJQEkUjEd0mEkG6g27ecACA0NBQGBgaIjIzkuxStM3fuXFRVVWHPnj0UTISQLkPhBMDQ0BArVqzA1q1bcefOHb7L0Rrr16/HoUOHsHv3blhbW/NdDiGkG6HTev9ffX093NzcMGzYMOzdu5fvcnh38eJFjB49GitXrsSnn37KdzmEkG6GwqmJgwcPYvr06UhLS4OPjw/f5fCmsrISHh4eGDx4MOLj4yEUUgObENK1KJyaYIxh5MiREIvFOHXqFAQCAd8ldTnGGIKCgpCRkYErV65QBxFCCC/oJ3ETAoEAmzZtwpkzZ7rtqb21a9ciISEBMTExFEyEEN5Qy6kZ77zzDuLi4nDz5k2YmJjwXU6XOXfuHPz8/BAVFYWwsDC+yyGEdGMUTs2oqKiAo6MjZs6c2W1uzi0rK4O7uzvc3d1x+PDhbnlKkxCiPei0XjPMzMwQGRmJTZs24dq1a3yX0+lUKhVmzpwJkUiEH3/8kYKJEMI7CqcWzJ8/H56enggNDUXTxmVdXR0++eQTJCcn81hd+5w+fbrZ5WvWrMGJEycQExMDc3PzLq6KEEI0UTi1QCgUYvPmzTh37hx2794NALhw4QJcXFywdu1aHDt2jOcK20Ymk2HChAmYPn06Hj58yC0/efIk1qxZg2+++QYjRozgsUJCCPkfuub0BAsXLkRsbCxmzpyJ9evXQyAQoL6+Hs7OzsjKyuK7vFb79ddfMXXqVIhEItjb2+PQoUOwsrKCu7s7Ro8ejZ9//pnvEgkhhEPh9ARpaWnw8/ODSqWCSqXilgsEApSUlKBPnz48Vtd6ISEh+OWXX6BUKqGjowOBQAAHBweoVCpkZGTA2NiY7xIJIYRDp/VaoFKpsGHDBowZM4Z73ZRAIHhmrjsplUocPnwYSqUSwKOhmpRKJW7duoUXX3yRBnQlhGgdCqdm3LlzBy+//DKWLl0KpVKJ+vp6jW1EIhESExN5qK7tkpOTIZFIml13/PhxDB06FDdu3OjiqgghpGUUTn+jUqkQGhqKCxcuoKGhocXtlEolfv/99y6srP1iY2NbnFZdqVSisLAQ3t7eXMcPQgjhG4XT3wiFQsTHx2PlypUQCoWPPeVVWlqKmzdvdmF1bdfQ0IADBw5wp/SaU19fj7q6OuzcuVOtJx8hhPCFwqkZIpEIq1atQnJyMszNzVtsdYjFYiQlJXVxdW1z5swZVFZWtrheLBZDT08PUVFRSEpKoo4RhBCtQOH0GGPGjEFWVhbGjh3b7LQRKpUKR48e5aGy1ouNjYWurm6z6wQCATw9PZGZmYlly5bR1BiEEK1BXclbgTGGjRs3Ijw8HIwxtWtRPXr0QHV1dYutKz4xxmBjY4OSkhK15WKxGGKxGN988w3efvttGq6IEKJ16KdyKwgEAnzwwQc4d+4c7OzsoKOjw62TyWS4ePEij9W17OLFixrBJBAIMHr0aOTk5GDBggUUTIQQrUTh1Aaenp64fv06pk2bxi3T5utOTXvpicViGBgYYNu2bTh+/Dj69u3Lc3WEENIyOq3XTt9//z0WL14MhUIBLy8vrWw9vfDCCygsLIRAIMDYsWOxY8cO2Nvb810WIYQ8EYXTU8jMzMTUqVORn5+PBw8eaNXEhDdu3ICbmxt69uyJjRs3Yu7cuXyXRAghrUbh9JTq6uqwbNkyvPLKK5g8ebLaOqVSiZqaGtTU1EAul6O6uhoAUFNTo3HfUW1tLeRyudoygUCAXr16aRzTxMQEQqEQPXr0gL6+Pnr16gU9PT0YGhpy26xevRoXL17E999/D1tb2476uIQQ0iUonJ5ALpejpKQExcXFKC8vR2VlJSoqKlBRUaH277/++gsSiQS1tbWQyWSorq7WGI+vKxgZGUFPTw96enowNzeHmZkZ9zA1NVV7bWFhAUtLS9jY2GhVq48QQrp1OMnlchQUFHCP4uJiFBcXc2FUUlKC8vJytfcYGBg0+0Xf+NrQ0BD6+vowMTGBnp4eevbsCUNDQ+jq6sLU1BQAoK+vjx49eqjtV1dXV63lAzwaueHvY+KpVCquBdbY2qqsrIRCoYBUKoVEIoFCoUB1dTVqamq48GwaqA8ePEBVVZXG57KxsYGVlRVsbW1hZWUFOzs79OvXDw4ODnBwcKCJCAkhXea5D6e6ujrk5OQgJycHt27dQn5+PgoKCpCfn48///yTm+XW1NQUdnZ2sLOzg6WlJfdsb2+PPn36wN7eHhYWFtDX1+f5E3UMlUqF8vJylJaWckF87949lJaWcs9FRUW4f/8+1wI0NjZG//79ubAaOHAgBg8eDFdXV/Tu3ZvnT0QIeZ48N+FUX1+PrKws3LhxA9nZ2cjOzkZWVhYKCgrQ0NAAsViMAQMGqH25Nn00d22HAAqFAoWFhWotzMZHXl4e1wKzsLCAq6srnJyc4OLiAmdnZ7i7u9PflRDSLs9kODU0NCA3NxcZGRnc48qVK6itrYVYLIa9vT2cnZ25L0kXFxe4uLg8N60ebVJZWYmsrCzux0B2djZu3LiB0tJSAIC1tTU8PDy4x8iRI2FmZsZz1YQQbfdMhFNdXR3Onz+PU6dOISUlBZcuXYJUKoW+vj6GDh0KT09PeHp6wsPDA05OTmojOBB+3L9/HxkZGUhPT+eeS0tLIRQKMXjwYPj5+cHX1xd+fn6wtrbmu1xCiJbRynCqr6/HmTNncPLkSZw6dQoXLlyAXC5Hv379MGbMGIwcORJeXl5wcXHRyjHtSPOKioqQkZGB8+fPIyUlBenp6aivr4ejoyP8/Pzg5+eH8ePHw8LCgu9SCSE805pwqqioQHJyMo4cOYL4+HhUVlbC2toao0aNwrhx4zBy5Ei4uLjwXSbpQFKpFOfOncOZM2dw9uxZnD59GkqlEu7u7ggICEBgYCCGDx9O4/8R0g3xGk6lpaWIiYnBwYMHkZaWBpFIBF9fX7z22msICAjAwIED+SqN8EAikSAxMREJCQlISEjAX3/9BQcHB/zjH//Am2++CW9vb75LJIR0kS4PJ5lMhri4OPz0009ITEyEgYEBpkyZgsDAQIwfP54muyMAHnV1v3TpEo4cOYKDBw8iNzcXgwcPRkhICEJCQtCvXz++SySEdKIuC6ebN29i/fr12Lt3L2pra/Hqq68iJCQEkydP1rghlZC/u3TpEnbv3o19+/ahvLwcY8aMweLFizF58mSaJJGQ51Cnh9PJkyexbt06/PbbbxgwYAAWLVqE4OBgWFpaduZhyXNKqVTi2LFj2L59O+Lj49G/f38sWbIEc+bM0RhhgxDy7Oq0cDp+/DiWLVuGy5cvw9fXF2FhYQgMDKRfuaTD3Lp1C9988w2io6Ohr6+PpUuX4sMPP6SWOCHPgQ5Pips3byIwMBD+/v6wtbXFpUuXkJKSQqdfSIcbNGgQvv32WxQWFmLx4sX46quvMHjwYOzbtw9a0gmVENJOHZYWcrkcH330EYYMGYKioiIcP34chw8fhqenZ0cdgpBmWVhYYNWqVbh16xbGjRuHkJAQvPzyy8jNzeW7NEJIO3VION2+fRsjR47E999/j82bNyMjIwNjx47tiF0T0mrW1tb44YcfkJ6eDpVKBS8vL0RHR/NdFiGkHZ46nPbv3w8PDw8AQEZGBhYsWACRSPTUhRHSXu7u7jhz5gzeeecdzJkzB3PmzNGYyJEQot2eKpy+++47vPHGG5g1axbOnj1LN80SrSEWi/Gf//wHR44cQVxcHAIDA1FbW8t3WYSQVmp3b73Y2FhMnz4dq1evRkREREfX1Spnz55FQUGB2jIdHR2YmJjAzMwMQ4YMgYGBAbeurKwMx44d4177+/trdGmXy+WIjY1FQ0MDAEAoFGLChAkwMzODXC7Hrl27cO3aNdja2mLUqFHw9vZGUlISAgMDW1VzTk4OUlNTkZmZCTMzM3h6emLcuHHUw6wTXblyBf7+/vD19cWBAweoYw4hzwLWDvn5+axnz55s0aJF7Xl7h1GpVOzo0aNMIBCwXr16sRUrVrCdO3eyyMhINmXKFKavr88mTpzIcnJyuPeUlpayBQsWMADMx8eH1dXVaey3srKSzZo1i7388susqKiIW+bs7MzmzZvHLly4wBITE9mbb77JRCIRW7JkyRNrrampYUuWLGHDhw9nSUlJrKysjF25coV9+OGHzMnJiV2+fLldf4Pm6ieaTp8+zfT09NjXX3/NdymEkFZoVzgFBgYyV1dXrfliNDMzY46OjhrLjx8/zqysrJi+vj47f/682jpHR0cGgM2ZM6fZfe7evZtFRERwr99//33m5OTEVCqV2naLFi1qVThNmjSJDRw4kNXW1mqs+/zzz5muri67cOHCE/fzd0uXLmUNDQ1tfl93FBkZyXr06MH94CCEaK82n9/Izs5GfHw8oqKioKen1/FNuXbQ1dVtdvnYsWPxww8/oK6uDtOmTVO7KG5oaIgRI0bgxx9/xPr165vdZ8+ePbnXly5dgp6ensYI2cuWLXviqNlbt27Fb7/9hoiIiGZP3y1ZsgSGhoaYP38+lErlY/fV1I0bN7Bt27ZWb9/dhYeHw9zcHBs3buS7FELIE7Q5nA4dOgRra2tMmjSpM+rpcJMmTcLYsWNRXFyM/fv3q62LjY2FnZ0dwsPDcfz48cfux8nJCVevXsXixYuhUCi45X379sWECRMe+95Vq1ZBKBQiODi42fVGRkYICgrCjRs3sH//fvz888/Yt28fDhw4wG1z4MAB7Nu3D7/++iuAR9fbAgICIJVKERMTo/bZ6urq8NNPP+GTTz5BXFwcZDKZ2vHkcjkSExPxf//3f9iyZQvu3Lmjtv7u3btYuXIlZDIZ7t69i1WrVuHbb7/lpmS/c+cOoqKisG7dOlRWVmp8nocPH2L79u0ICwvD5s2bUVNT89i/T1fR1dXFrFmzcOjQIb5LIYQ8QZvD6fr16/Dx8Xmm5tgZMWIEgEfj/DVlZWWFX3/9Fbq6upgxY4bGl3RTy5cvh4WFBTZv3owhQ4bg6NGj3Lrx48e3+L779++jrKwM1tbWLbbwAHCjbF+9ehWTJk3Cli1bMG/ePG79yJEj8dVXX2HhwoUAAMYYRo8eDQAwMTGBiYkJAKCwsBDjx4+HXC5HaGgoNm3aBFdXV9TV1QF4FFwTJkxAZWUlPvroIzDG4O7ujtjYWABATEwMRo8ejc8//xwJCQlYsWIFbt++jcWLF2PevHlITU1FREQEMjMzsWzZMoSEhKh9jry8PG7U8NmzZ+O7777DsGHDuGDj24gRI3D79m1IpVK+SyGEPE5bzwNOmjSJzZ49u8PPLz4NKyurZq85NYqOjmYAmL+/P7ds+PDh3L/37t3LADAXFxf28OFDxhhjv/zyC4uKilLbz/Xr15mbmxsDwACwiRMnslu3bj22tt9//53rfPE4O3bsYADYa6+9xhhjLDQ0lBkbG6ttM3/+fGZlZcW9Xr16NQOgdh3M39+fLViwgHsdHx/PBAIBi42NZYwx9uabb7K5c+eq7ff1119XuxbTuN+4uDhum0WLFjEALDo6mlsWERHBALDq6mq14x86dEjj83/22WeP/fxdJSUlhQFgf/75J9+lEEIeo80tJ0tLSxQXF3dUNnaJxl/JvXv3bnZ9cHAwPvnkE2RlZSEkJKTFcdmGDBmCjIwMbNiwAaampvj9998xdOhQJCYmtnjsxhbNw4cPH1tj4zHNzc0BoNnuzk/qAn379m0kJSVhypQp3LLXXnsNJSUlCAoKQm1tLfbv3w93d3e19y1cuBAymQw7d+4EAO5am6+vL7fN0KFDAQCjRo3ilg0ePBgAuP8f/vzzTyQlJSEtLQ3Lly/H8uXLkZCQAE9PT625x6ioqAg6Ojo0FTwhWk6nrW8YNWoUQkNDIZFIYGRk1Bk1dbibN28CAJydnVvcJjIyEpmZmTh8+DBWrFgBNze3ZrfT0dHB+++/j7feegthYWGIjo7GjBkzcPfuXS6Immo8ZmFh4WNrvHfvHgDA1dW1VZ+pOTk5OQCg1pEDAPr06QMASEtLg1KphI6O+n/2F198EcCjUb6B/4Vg01O3zXV+aTxN2diJIy8vDwDw8ccfa+2X/9GjR+Hj46PxNyCEaJc2t5ymTp0KHR0dbN26tTPq6XAKhQLx8fHQ0dFBUFBQi9sJhULs2bMHTk5O+OKLLzQ6T6xdu1bttbm5OXbt2oXg4GBUVVXh7Nmzze7XxMQE7u7ukEqlj72mlZubC6FQCH9//zZ8OnWNPQGb3mjcqKysjLuxOC0tTW1dY5AMGjSo3ccG/hdWly9f1lgnkUieat8doaioCPv378fs2bP5LoUQ8gRtDqdevXohLCwMX3zxBfLz8zujpg7173//G7dv38aSJUse23ICAGNjYxw+fBimpqYa4XT69GmUlJRovGfq1KkANFsrTW3duhUCgQBff/11s+vv3buHgwcPIjQ0FMOGDeNq+ft4cIwxLmCaalzm7OwMoVCII0eOqG13584dpKenw93dHXp6ehpBWlZWBgBcB4v2cnR0hEgkwsqVK9V6NJaVlWHPnj1Pte+nxRjDwoUL0a9fP8ycOZPXWgghrdCeC1VyuZwNGzaMDRkyRO1iOB8UCgUTiUQaHSLq6urYkiVLmFgsZsuXL9e4YdjS0pJJpdJm95mUlMREIpFah4iJEycyf39/JpFI1LadMmUKc3NzY3K5/LF1fvHFF0xfX5+dPHlSbXl1dTWbMGEC8/X1Vdv39u3bGQCWmJjIVCoVi4mJYS4uLkxXV5dVVVWx+vp6tnXrVgaAnT9/nqWmpjKZTMbmzJnDALCgoCCWnJzMNm/ezIKDg7lOE+Hh4QwAO3HiBHesDRs2sOnTp3PbrFmzhgFgxcXFGvVkZWVxyxo7kqSlpXHL3nvvPa4DyJ49e9jOnTuZv78/q6qqeuzfp7OtWLGCicVidubMGV7rZixZZQAAB4dJREFUIIS0TrvCiTHG/vjjD2ZjY8NeeuklVlFR0ZE1tVpqaiqbNm0aA8B0dHSYu7s7CwoKYtOmTWMBAQHs3XffZRkZGWrvuXz5Mps/fz4DwKZPn86SkpKa3ff69evVwumtt95i06ZNY+7u7mzu3Lns008/ZS4uLmzMmDGsoKCgVfWePHmSDR06lP3rX/9imzZtYuHh4eyll15iX375pcYoD1KplLm6ujIAzNLSku3atYstWLCAmZqasvDwcFZeXs7y8/OZpaUlMzU1Zf/9738ZY4/CLigoiOtR+MILL7BLly5x+21oaGBhYWGsd+/ebNmyZWz27Nnsn//8J5PJZIwxxhITE7njvvvuu+zmzZvst99+Y15eXgwACwkJYdevX2cnTpxgo0aNYgDY66+/zrKzs7m6Z82axR3f2NhYrfceHyIjI5lAIOD+RoQQ7fdU07Tn5eVh3LhxEIvF+Pnnn7mpM54X5eXl3PWY4uJi2NragjGGzMxMPHjwAAMGDIC9vX2b91tdXY2srCzY2dmhb9++LW7XeKwBAwbAwMAAeXl5sLOzUxtlQqlUor6+XmPkicb7q5ydnSEWizX2LZPJkJubCycnJ+jr67f5MzxJeXk5/vjjDzg5OfE2qG1NTQ0WLlyIvXv3YsuWLXj33Xd5qYMQ0nZPFU7Ao+sJs2bNQnJyMtasWYOPP/74mbpBlzyfsrOzMWPGDJSUlGDXrl3PzIgmhJBHnnrugN69e3MjCURERMDf3x/Xrl3riNoIaTOJRIJPP/0UHh4eMDc3x7Vr1yiYCHkGdcjENkKhEBERETh9+jQkEgk8PDzw9ttvN9u7jZDO0NDQgO3bt+PFF1/Etm3b8OWXXyI5ORk2NjZ8l0YIaYcOnXXNx8cH58+fx65du3Ds2DEMGjQIS5cufeINqIS0l1wux44dO+Dm5ob33nsPM2bMQF5eHj788EOIRCK+yyOEtNNTX3NqiUwmw5YtW7BhwwaUlJTg9ddfR1hYGLy8vDrjcKSbKS8vx7Zt27B582ZUVlYiODgYy5cvh6OjI9+lEUI6QKeFUyOlUolffvkF69atw+XLl+Hj44OQkBC88cYb3DhyhLRGQ0MDkpKSsHv3bsTGxqJHjx545513sHjxYlhbW/NdHiGkA3V6ODV16tQp7NixA4cOHYJCocDEiRMxc+ZMBAQEaM3EhUT7XL16FdHR0YiJiUFJSQlGjBiBWbNmISQkBIaGhnyXRwjpBF0aTo1kMhni4+MRHR2No0ePQldXF6+88goCAwMREBBAF7G7uYaGBpw7dw7x8fGIi4tDbm4u+vbti+DgYMybN48bqJYQ8vziJZyaun//PuLi4nDkyBGcPHkSCoUC3t7eCAwMxLhx4zB8+HAaQbobKCoqwokTJ5CQkIBjx47h4cOHcHV1RUBAACZPnoyXXnqJ7p8jpBvhPZyakkqlSEpKQnx8PBISElBSUgIjIyOMGjUKvr6+8PPzg5eXF4XVc6CgoACpqak4deoUUlJSUFBQAF1dXfj5+XEtaAcHB77LJITwRKvCqSnGGLKzs5GSkoLU1FSkpKSgpKQEhoaG8Pb2hpeXFzw9PeHp6UlfYlquuroaGRkZSE9PR3p6Os6fP4+ioiLo6+vD29sbY8aMgZ+fH3x8fGBgYMB3uYQQLaC14dSc3NxcpKam4ty5c0hPT0dOTg4aGhpgbm7OBZWbmxucnZ0xaNAgbn4h0nWKioqQk5ODzMxMLpDy8vLAGIO1tTU8PT3h5eUFPz8/eHt7d8q4foSQZ98zFU5/J5VKcfXqVe4XeUZGBm7duoWGhgbo6Ohg4MCBcHFxgZOTE1xcXODo6AgHBwf06tWL79KfaQqFAoWFhbh9+zaysrKQm5uLzMxM5OTkcNPRW1paYvjw4dyPBg8PD9ja2vJcOSHkWfFMh1Nz5HI5cnNz1b4ws7KycOfOHW46cTMzMzg4OKB///5qz/b29rCxsWl2uvXuRC6Xo7S0FPfu3cPdu3eRn5+P/Px8FBQUID8/H8XFxdxkhtbW1nB2doazs7PaDwG6h40Q8jSeu3BqiUKh4L5cG5+b/rvxFz/waLpzW1tbWFlZcc82Njbo06cPzMzMYGpqCjMzM+6h7fdoMcZQUVGByspKVFRUcI8HDx6gpKQExcXFas/l5eXce8ViMfr27Yv+/ftrhPnAgQOpFUoI6RTdJpye5MGDB7h//z7u3bvHtRpKS0tRXFzMPZeXl0MqlWq819DQkAsqfX19GBkZwdDQELq6ujA1NYWenh4MDAxgZGTE9TQ0NjbWGPvN1NRU7XVtba3GVO0PHz7kWi3V1dVQKBSQSCTctpWVlVAoFJBKpaiuruaC6O/EYjHMzMxgaWkJOzs77rlPnz5qr21sbGiMOkJIl6NwaiO5XM594f+9JVJRUYG6ujpIJBJIpVLI5XJUVVWhrq4OMpmMCxbGGKqqqtT2W19fD4lEorasMdSaMjAw4FpqRkZG0NPTg7GxMbe8aRiamJiotfCaPoyMjDr3D0UIIU+BwokQQojW6dApMwghhJCOQOFECCFE61A4EUII0To6APbzXQQhhBDS1P8DrJBa2OAIMxYAAAAASUVORK5CYII=", - "text/plain": [ - "" - ] - }, - "execution_count": 181, - "metadata": {}, - "output_type": "execute_result" + "ename": "ImportError", + "evalue": "requires pygraphviz http://pygraphviz.github.io/", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", + "File \u001b[0;32m~/repos/ooni/data/oonipipeline/.venv/lib/python3.11/site-packages/networkx/drawing/nx_agraph.py:134\u001b[0m, in \u001b[0;36mto_agraph\u001b[0;34m(N)\u001b[0m\n\u001b[1;32m 133\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 134\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpygraphviz\u001b[39;00m\n\u001b[1;32m 135\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mImportError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n", + "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'pygraphviz'", + "\nThe above exception was the direct cause of the following exception:\n", + "\u001b[0;31mImportError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[12], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m viz \u001b[38;5;241m=\u001b[39m \u001b[43mweb_analysis_bn\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto_graphviz\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2\u001b[0m viz\u001b[38;5;241m.\u001b[39mdraw(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mweb_analysis_simple.png\u001b[39m\u001b[38;5;124m'\u001b[39m, prog\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdot\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 3\u001b[0m Image(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mweb_analysis_simple.png\u001b[39m\u001b[38;5;124m'\u001b[39m)\n", + "File \u001b[0;32m~/repos/ooni/data/oonipipeline/.venv/lib/python3.11/site-packages/pgmpy/base/DAG.py:1082\u001b[0m, in \u001b[0;36mDAG.to_graphviz\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1069\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mto_graphviz\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m 1070\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 1071\u001b[0m \u001b[38;5;124;03m Retuns a pygraphviz object for the DAG. pygraphviz is useful for\u001b[39;00m\n\u001b[1;32m 1072\u001b[0m \u001b[38;5;124;03m visualizing the network structure.\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1080\u001b[0m \u001b[38;5;124;03m >>> model.draw('model.png', prog='neato')\u001b[39;00m\n\u001b[1;32m 1081\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m-> 1082\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mnx\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mnx_agraph\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto_agraph\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/repos/ooni/data/oonipipeline/.venv/lib/python3.11/site-packages/networkx/drawing/nx_agraph.py:136\u001b[0m, in \u001b[0;36mto_agraph\u001b[0;34m(N)\u001b[0m\n\u001b[1;32m 134\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpygraphviz\u001b[39;00m\n\u001b[1;32m 135\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mImportError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n\u001b[0;32m--> 136\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mImportError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrequires pygraphviz http://pygraphviz.github.io/\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n\u001b[1;32m 137\u001b[0m directed \u001b[38;5;241m=\u001b[39m N\u001b[38;5;241m.\u001b[39mis_directed()\n\u001b[1;32m 138\u001b[0m strict \u001b[38;5;241m=\u001b[39m nx\u001b[38;5;241m.\u001b[39mnumber_of_selfloops(N) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m N\u001b[38;5;241m.\u001b[39mis_multigraph()\n", + "\u001b[0;31mImportError\u001b[0m: requires pygraphviz http://pygraphviz.github.io/" + ] } ], "source": [ @@ -358,7 +364,7 @@ }, { "cell_type": "code", - "execution_count": 57, + "execution_count": 13, "id": "b3cad79a-bce8-4efb-b811-80f6458fb16c", "metadata": {}, "outputs": [], @@ -398,7 +404,7 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 14, "id": "509c45ee-b22d-461a-998b-a701c5090580", "metadata": {}, "outputs": [], @@ -550,7 +556,7 @@ }, { "cell_type": "code", - "execution_count": 63, + "execution_count": 15, "id": "710b4561-7b8f-47fd-a742-dd88e697a1bc", "metadata": {}, "outputs": [], @@ -618,7 +624,7 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": 16, "id": "61234ff3-5e13-48e3-8264-e1966fdd2dc1", "metadata": {}, "outputs": [], @@ -680,11 +686,11 @@ " variable_card=4,\n", " values=[\n", " # consistent inconsistent\n", - " # \"none\", \"connection_reset\", \"timeout\", \"other\", \"down\"\n", - " [0.02, 0.95, 0.90, 0.85, 0.01, 0.07, 0.07, 0.07, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02], # blocked\n", - " [0.95, 0.01, 0.01, 0.01, 0.08, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01], # ok\n", - " [0.02, 0.03, 0.07, 0.09, 0.01, 0.07, 0.07, 0.07, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05], # down\n", - " [0.01, 0.01, 0.02, 0.05, 0.90, 0.85, 0.85, 0.85, 0.92, 0.92, 0.92, 0.92, 0.92, 0.92, 0.92, 0.92], # unknown\n", + " # \"none\", \"bad_certificate\", \"connection_reset_after_ch\", \"timeout_after_ch\", \"timeout\" \"connection_reset\" \"other\" \"down\"\n", + " [0.02, 0.95, 0.90, 0.85, 0.55, 0.65, 0.07, 0.07, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02], # blocked\n", + " [0.95, 0.01, 0.01, 0.01, 0.02, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01], # ok\n", + " [0.02, 0.03, 0.07, 0.09, 0.40, 0.25, 0.07, 0.07, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05], # down\n", + " [0.01, 0.01, 0.02, 0.05, 0.03, 0.09, 0.85, 0.85, 0.92, 0.92, 0.92, 0.92, 0.92, 0.92, 0.92, 0.92], # unknown\n", " ],\n", " evidence=[\"DNS Answer Consistency\", \"TLS VP Result\"],\n", " evidence_card=[2, 8],\n", @@ -698,30 +704,10 @@ }, { "cell_type": "code", - "execution_count": 65, + "execution_count": 17, "id": "4a7dff9b-4851-435e-941d-de3e736bc577", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "WARNING:pgmpy:Replacing existing CPD for DNS Ctrl Failure\n", - "WARNING:pgmpy:Replacing existing CPD for DNS VP Failure\n", - "WARNING:pgmpy:Replacing existing CPD for DNS Failure Consistency\n", - "WARNING:pgmpy:Replacing existing CPD for DNS Answer\n", - "WARNING:pgmpy:Replacing existing CPD for DNS Answer TLS Consistency\n", - "WARNING:pgmpy:Replacing existing CPD for DNS Answer Consistency\n", - "WARNING:pgmpy:Replacing existing CPD for DNS Outcome\n", - "WARNING:pgmpy:Replacing existing CPD for TCP Ctrl Failure\n", - "WARNING:pgmpy:Replacing existing CPD for TCP VP Result\n", - "WARNING:pgmpy:Replacing existing CPD for TCP Outcome\n", - "WARNING:pgmpy:Replacing existing CPD for TLS Ctrl Failure\n", - "WARNING:pgmpy:Replacing existing CPD for TLS VP Result\n", - "WARNING:pgmpy:Replacing existing CPD for TLS Outcome\n" - ] - } - ], + "outputs": [], "source": [ "cpd_list = [\n", " cpd_dns_ctrl_failure, \n", @@ -743,7 +729,7 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": 121, "id": "a2299f85-a607-4198-a0eb-5af82f7317e9", "metadata": {}, "outputs": [ @@ -753,7 +739,7 @@ "True" ] }, - "execution_count": 66, + "execution_count": 121, "metadata": {}, "output_type": "execute_result" } @@ -764,7 +750,7 @@ }, { "cell_type": "code", - "execution_count": 67, + "execution_count": 19, "id": "73120bce-721a-4965-8a76-a4f37f7be905", "metadata": {}, "outputs": [], @@ -778,7 +764,9 @@ "id": "85d58bf9-eb93-48fb-96ba-927657cfd1ef", "metadata": {}, "outputs": [], - "source": [] + "source": [ + "from oonipipeline" + ] }, { "cell_type": "code", @@ -790,7 +778,7 @@ }, { "cell_type": "code", - "execution_count": 68, + "execution_count": 122, "id": "21c4346f-4c39-47fc-9378-306b1bb05d58", "metadata": {}, "outputs": [], @@ -800,7 +788,7 @@ }, { "cell_type": "code", - "execution_count": 69, + "execution_count": 123, "id": "89546053-4dbb-47af-a81d-1ad5bf41f95c", "metadata": {}, "outputs": [], @@ -810,7 +798,7 @@ }, { "cell_type": "code", - "execution_count": 70, + "execution_count": 124, "id": "cb364bad-0321-4cba-9df6-c6a1cdb9ec05", "metadata": {}, "outputs": [ @@ -940,10 +928,244 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 145, "id": "ce7f6e84-e728-475c-b075-73404497bd61", "metadata": {}, "outputs": [], + "source": [ + "CLOUD_PROVIDERS_ASNS = [\n", + " 13335, # Cloudflare: https://www.peeringdb.com/net/4224\n", + " 209242, #\tCloudflare London, LLC\t\n", + " 20940, # Akamai: https://www.peeringdb.com/net/2\n", + " 9002, # Akamai RETN\n", + " 16625, # Akamai Technologies, Inc.\t\n", + " 63949, # Akamai Technologies, Inc.\t\n", + " 16509, #\tAmazon.com, Inc.\n", + " 14618, #\tAmazon.com, Inc.\t\n", + " 15169, #\tGoogle LLC\n", + " 396982, # Google Cloud: https://www.peeringdb.com/net/30878\n", + " 54113, #\tFastly, Inc\n", + " 8075, # Microsoft Corporation\n", + " 8068, #\tMicrosoft Corporation\n", + "]\n", + "def is_cloud_provider(as_number):\n", + " return as_number in CLOUD_PROVIDERS_ASNS\n", + " \n", + "def find_relevant_control(wo, web_ctrl_observations):\n", + " for ctrl in web_ctrl_observations:\n", + " if wo.ip == ctrl.ip:\n", + " return ctrl\n", + "\n", + "def observations_to_features(web_obs, web_ctrl_observations):\n", + " for wo in web_observations:\n", + " ctrl = find_relevant_control(wo, web_control_observations)\n", + " yield produce_state(wo, ctrl)\n", + "\n", + "def produce_state(wo, ctrl):\n", + " state = {\n", + " 'DNS Ctrl Failure': None,\n", + " 'DNS VP Failure': None,\n", + " 'DNS Answer': None,\n", + " 'DNS Answer TLS Consistency': None,\n", + " 'TCP Ctrl Failure': None,\n", + " 'TCP VP Result': None,\n", + " 'TLS Ctrl Failure': None,\n", + " 'TLS VP Result': None\n", + " }\n", + " if wo.dns_failure is not None:\n", + " if wo.dns_failure in ('dns_nxdomain_error', 'android_dns_cache_no_data'):\n", + " state['DNS VP Failure'] = 'nxdomain'\n", + " else:\n", + " state['DNS VP Failure'] = 'server_failure'\n", + " elif wo.dns_answer is not None:\n", + " state['DNS VP Failure'] = 'none'\n", + "\n", + " if ctrl:\n", + " if ctrl.dns_failure is not None:\n", + " if wo.dns_failure == 'dns_nxdomain_error':\n", + " state['DNS Ctrl Failure'] = 'nxdomain'\n", + " else:\n", + " state['DNS Ctrl Failure'] = 'server_failure'\n", + " elif ctrl.dns_success:\n", + " state['DNS Ctrl Failure'] = 'none'\n", + "\n", + " if wo.dns_answer is not None:\n", + " if wo.ip_is_bogon:\n", + " state['DNS Answer'] = 'answer_is_bogon'\n", + " elif wo.ip_asn == wo.probe_meta.probe_asn:\n", + " state['DNS Answer'] = 'answer_matches_probe_asn'\n", + " elif wo.ip_as_cc == wo.probe_meta.probe_cc:\n", + " state['DNS Answer'] = 'answer_matches_probe_cc'\n", + " elif is_cloud_provider(wo.ip_asn):\n", + " state['DNS Answer'] = 'answer_is_cloud_provider'\n", + " else:\n", + " state['DNS Answer'] = 'answer_other'\n", + "\n", + " if ctrl:\n", + " tcp_ctrl_state = None\n", + " if ctrl.ip and (ctrl.tcp_failure is not None or ctrl.tcp_success):\n", + " if ctrl.tcp_failure is None:\n", + " tcp_ctrl_state = 'none'\n", + " elif ctrl.tcp_failure == 'connection_reset':\n", + " tcp_ctrl_state = 'connection_reset'\n", + " elif ctrl.tcp_failure in ('generic_timeout_error', 'timed_out'):\n", + " tcp_ctrl_state = 'timeout'\n", + " else:\n", + " tcp_ctrl_state = 'other'\n", + "\n", + " tls_consistency_state = None\n", + " if wo.ip == ctrl.ip and (ctrl.tls_success or ctrl.tls_failure is not None):\n", + " if ctrl.tls_failure is None:\n", + " tls_consistency_state = 'tls_consistent'\n", + " elif ctrl.tls_failure.startswith(\"ssl_\"):\n", + " tls_consistency_state = 'tls_inconsistent'\n", + " else:\n", + " tls_consistency_state = 'unknown'\n", + " else:\n", + " tls_consistency_state = 'unknown'\n", + "\n", + " if (tcp_ctrl_state and tcp_ctrl_state != 'none'):\n", + " tls_consistency_state = 'tls_inconsistent'\n", + " state['DNS Answer TLS Consistency'] = tls_consistency_state\n", + " state['TCP Ctrl Failure'] = tcp_ctrl_state\n", + " \n", + " if wo.ip and (wo.tcp_failure is not None or wo.tcp_success):\n", + " tcp_vp_result = None\n", + " if wo.tcp_failure is None:\n", + " tcp_vp_result = 'none'\n", + " elif wo.tcp_failure == 'connection_reset':\n", + " tcp_vp_result = 'connection_reset'\n", + " elif wo.tcp_failure in ('generic_timeout_error', 'timed_out'):\n", + " tcp_vp_result = 'timeout'\n", + " else:\n", + " tcp_vp_result = 'other'\n", + " if tcp_vp_result != 'none' and tcp_vp_result == state['TCP Ctrl Failure']:\n", + " tcp_vp_result = 'down'\n", + " state['TCP VP Result'] = tcp_vp_result\n", + "\n", + " if ctrl:\n", + " if ctrl.ip and (ctrl.tls_failure is not None or ctrl.tls_success):\n", + " if ctrl.tls_failure is None:\n", + " state['TLS Ctrl Failure'] = 'none'\n", + " elif ctrl.tls_failure.startswith('ssl_'):\n", + " state['TLS Ctrl Failure'] = 'bad_certificate'\n", + " else:\n", + " state['TLS Ctrl Failure'] = 'other'\n", + " \n", + " if wo.ip and (wo.tls_failure is not None or wo.tls_failure):\n", + " tls_vp_result = None\n", + " if wo.tls_failure is None:\n", + " tls_vp_result = 'none'\n", + " elif wo.tls_failure.startswith('ssl_'):\n", + " tls_vp_result = 'bad_certificate'\n", + " elif wo.tls_failure == 'connection_reset':\n", + " tls_vp_result = 'connection_reset'\n", + " if wo.tls_handshake_last_operation and wo.tls_handshake_last_operation == 'write_1':\n", + " tls_vp_result = 'connection_reset_after_ch'\n", + " elif wo.tcp_failure in ('generic_timeout_error', 'timed_out'):\n", + " tls_vp_result = 'timeout'\n", + " if wo.tls_handshake_last_operation and wo.tls_handshake_last_operation == 'write_1':\n", + " tls_vp_result = 'timeout_after_ch'\n", + " else:\n", + " tls_vp_result = 'other'\n", + " if tls_vp_result != 'none' and state['TLS Ctrl Failure'] != 'none':\n", + " tls_vp_result = 'down'\n", + " state['TLS VP Result'] = tls_vp_result\n", + " return state" + ] + }, + { + "cell_type": "code", + "execution_count": 146, + "id": "0a4480e9-3c4c-43b7-bb8a-6fb34df5348c", + "metadata": {}, + "outputs": [], + "source": [ + "netinfodb = NetinfoDB(datadir=Path(\"datadir\"), download=False)\n", + "# 20231129041111.939896_NP_webconnectivity_32105af63774eabf\n", + "#raw_msmt = get_measurement_dict_by_uid(\"20240804233508.181041_TR_webconnectivity_9a7272e520f3d836\")\n", + "raw_msmt = get_measurement_dict_by_uid(\"20231129041111.939896_NP_webconnectivity_32105af63774eabf\")\n", + "msmt = load_measurement(msmt=raw_msmt)\n", + "web_observations, web_control_observations = measurement_to_observations(\n", + " msmt, netinfodb=netinfodb\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 147, + "id": "6ce969b6-548e-4602-963e-9baeff98c8d9", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'DNS Ctrl Failure': None, 'DNS VP Failure': 'none', 'DNS Answer': 'answer_is_cloud_provider', 'DNS Answer TLS Consistency': 'tls_inconsistent', 'TCP Ctrl Failure': 'other', 'TCP VP Result': 'down', 'TLS Ctrl Failure': None, 'TLS VP Result': None}\n", + "+----------------------+--------------------+\n", + "| TLS Outcome | phi(TLS Outcome) |\n", + "+======================+====================+\n", + "| TLS Outcome(blocked) | 0.0202 |\n", + "+----------------------+--------------------+\n", + "| TLS Outcome(ok) | 0.0189 |\n", + "+----------------------+--------------------+\n", + "| TLS Outcome(down) | 0.0498 |\n", + "+----------------------+--------------------+\n", + "| TLS Outcome(unknown) | 0.9111 |\n", + "+----------------------+--------------------+\n", + "+----------------------+--------------------+\n", + "| DNS Outcome | phi(DNS Outcome) |\n", + "+======================+====================+\n", + "| DNS Outcome(blocked) | 0.7872 |\n", + "+----------------------+--------------------+\n", + "| DNS Outcome(ok) | 0.2044 |\n", + "+----------------------+--------------------+\n", + "| DNS Outcome(down) | 0.0084 |\n", + "+----------------------+--------------------+\n", + "{'DNS Ctrl Failure': None, 'DNS VP Failure': None, 'DNS Answer': None, 'DNS Answer TLS Consistency': None, 'TCP Ctrl Failure': None, 'TCP VP Result': None, 'TLS Ctrl Failure': None, 'TLS VP Result': None}\n", + "+----------------------+--------------------+\n", + "| TLS Outcome | phi(TLS Outcome) |\n", + "+======================+====================+\n", + "| TLS Outcome(blocked) | 0.0405 |\n", + "+----------------------+--------------------+\n", + "| TLS Outcome(ok) | 0.8216 |\n", + "+----------------------+--------------------+\n", + "| TLS Outcome(down) | 0.0275 |\n", + "+----------------------+--------------------+\n", + "| TLS Outcome(unknown) | 0.1103 |\n", + "+----------------------+--------------------+\n", + "+----------------------+--------------------+\n", + "| DNS Outcome | phi(DNS Outcome) |\n", + "+======================+====================+\n", + "| DNS Outcome(blocked) | 0.0874 |\n", + "+----------------------+--------------------+\n", + "| DNS Outcome(ok) | 0.8945 |\n", + "+----------------------+--------------------+\n", + "| DNS Outcome(down) | 0.0181 |\n", + "+----------------------+--------------------+\n" + ] + } + ], + "source": [ + "for features in observations_to_features(web_observations, web_control_observations):\n", + " evidence = {k: v for k,v in features.items() if v is not None}\n", + " print(features)\n", + " print(infer.query(\n", + " ['TLS Outcome'],\n", + " evidence=evidence\n", + " ))\n", + " print(infer.query(\n", + " ['DNS Outcome'],\n", + " evidence=evidence\n", + " ))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "886eb036-3fa0-4084-9a7c-6c048f0634ee", + "metadata": {}, + "outputs": [], "source": [] } ], @@ -963,7 +1185,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.5" + "version": "3.11.7" } }, "nbformat": 4, diff --git a/oonipipeline/notebooks/web-analysis-full.bif b/oonipipeline/notebooks/web-analysis-full.bif new file mode 100644 index 00000000..8255ee41 --- /dev/null +++ b/oonipipeline/notebooks/web-analysis-full.bif @@ -0,0 +1,151 @@ +network unknown { +} +variable DNS Answer { + type discrete [ 5 ] { answer_is_bogon, answer_matches_probe_asn, answer_matches_probe_cc, answer_is_cloud_provider, answer_other }; +} +variable DNS Answer Consistency { + type discrete [ 2 ] { consistent, inconsistent }; +} +variable DNS Answer TLS Consistency { + type discrete [ 3 ] { tls_consistent, tls_inconsistent, unknown }; +} +variable DNS Ctrl Failure { + type discrete [ 3 ] { none, nxdomain, server_failure }; +} +variable DNS Failure Consistency { + type discrete [ 3 ] { ok, expected_not_ok, unexpected_not_ok }; +} +variable DNS Outcome { + type discrete [ 3 ] { blocked, ok, down }; +} +variable DNS VP Failure { + type discrete [ 3 ] { none, nxdomain, server_failure }; +} +variable TCP Ctrl Failure { + type discrete [ 4 ] { none, connection_reset, timeout, other }; +} +variable TCP Outcome { + type discrete [ 4 ] { blocked, ok, down, unknown }; +} +variable TCP VP Result { + type discrete [ 5 ] { none, connection_reset, timeout, other, down }; +} +variable TLS Ctrl Failure { + type discrete [ 3 ] { none, bad_certificate, other }; +} +variable TLS Outcome { + type discrete [ 4 ] { blocked, ok, down, unknown }; +} +variable TLS VP Result { + type discrete [ 8 ] { none, bad_certificate, connection_reset_after_ch, timeout_after_ch, timeout, connection_reset, other, down }; +} +probability ( DNS Answer ) { + table 0.004, 0.006, 0.06, 0.73, 0.2 ; +} +probability ( DNS Answer Consistency | DNS Answer, DNS Answer TLS Consistency ) { + ( answer_is_bogon, tls_consistent ) 0.99, 0.01; + ( answer_is_bogon, tls_inconsistent ) 0.001, 0.999; + ( answer_is_bogon, unknown ) 0.001, 0.999; + ( answer_matches_probe_asn, tls_consistent ) 0.999, 0.001; + ( answer_matches_probe_asn, tls_inconsistent ) 0.01, 0.99; + ( answer_matches_probe_asn, unknown ) 0.3, 0.7; + ( answer_matches_probe_cc, tls_consistent ) 0.999, 0.001; + ( answer_matches_probe_cc, tls_inconsistent ) 0.001, 0.999; + ( answer_matches_probe_cc, unknown ) 0.3, 0.7; + ( answer_is_cloud_provider, tls_consistent ) 0.999, 0.001; + ( answer_is_cloud_provider, tls_inconsistent ) 0.01, 0.99; + ( answer_is_cloud_provider, unknown ) 0.8, 0.2; + ( answer_other, tls_consistent ) 0.999, 0.001; + ( answer_other, tls_inconsistent ) 0.001, 0.999; + ( answer_other, unknown ) 0.2, 0.8; + +} +probability ( DNS Answer TLS Consistency | DNS Answer ) { + ( answer_is_bogon ) 0.01, 0.05, 0.94; + ( answer_matches_probe_asn ) 0.8, 0.15, 0.05; + ( answer_matches_probe_cc ) 0.75, 0.2, 0.05; + ( answer_is_cloud_provider ) 0.9, 0.08, 0.02; + ( answer_other ) 0.94, 0.04, 0.02; + +} +probability ( DNS Ctrl Failure ) { + table 0.994, 0.004, 0.002 ; +} +probability ( DNS Failure Consistency | DNS Ctrl Failure, DNS VP Failure ) { + ( none, none ) 0.99, 0.01, 0.01; + ( none, nxdomain ) 0.01, 0.05, 0.94; + ( none, server_failure ) 0.01, 0.05, 0.94; + ( nxdomain, none ) 0.94, 0.01, 0.05; + ( nxdomain, nxdomain ) 0.01, 0.98, 0.01; + ( nxdomain, server_failure ) 0.01, 0.92, 0.07; + ( server_failure, none ) 0.94, 0.01, 0.05; + ( server_failure, nxdomain ) 0.01, 0.92, 0.07; + ( server_failure, server_failure ) 0.01, 0.98, 0.01; + +} +probability ( DNS Outcome | DNS Answer Consistency, DNS Failure Consistency ) { + ( consistent, ok ) 0.01, 0.99, 0.0; + ( consistent, expected_not_ok ) 0.01, 0.01, 0.98; + ( consistent, unexpected_not_ok ) 0.4, 0.4, 0.2; + ( inconsistent, ok ) 0.8, 0.2, 0.0; + ( inconsistent, expected_not_ok ) 0.2, 0.05, 0.75; + ( inconsistent, unexpected_not_ok ) 0.9, 0.01, 0.09; + +} +probability ( DNS VP Failure | DNS Ctrl Failure ) { + ( none ) 0.994, 0.004, 0.002; + ( nxdomain ) 0.02, 0.98, 0.01; + ( server_failure ) 0.02, 0.01, 0.98; + +} +probability ( TCP Ctrl Failure ) { + table 0.98, 0.001, 0.014, 0.005 ; +} +probability ( TCP Outcome | DNS Answer Consistency, TCP VP Result ) { + ( consistent, none ) 0.02, 0.95, 0.02, 0.01; + ( consistent, connection_reset ) 0.95, 0.01, 0.03, 0.01; + ( consistent, timeout ) 0.9, 0.01, 0.08, 0.01; + ( consistent, other ) 0.85, 0.01, 0.09, 0.05; + ( consistent, down ) 0.01, 0.08, 0.01, 0.9; + ( inconsistent, none ) 0.07, 0.01, 0.07, 0.85; + ( inconsistent, connection_reset ) 0.07, 0.01, 0.07, 0.85; + ( inconsistent, timeout ) 0.07, 0.01, 0.07, 0.85; + ( inconsistent, other ) 0.07, 0.01, 0.07, 0.85; + ( inconsistent, down ) 0.05, 0.01, 0.09, 0.85; + +} +probability ( TCP VP Result | TCP Ctrl Failure ) { + ( none ) 0.98, 0.001, 0.01, 0.009, 0.009; + ( connection_reset ) 0.02, 0.14, 0.05, 0.07, 0.72; + ( timeout ) 0.01, 0.02, 0.1, 0.02, 0.85; + ( other ) 0.01, 0.06, 0.06, 0.12, 0.75; + +} +probability ( TLS Ctrl Failure ) { + table 0.98, 0.005, 0.015 ; +} +probability ( TLS Outcome | DNS Answer Consistency, TLS VP Result ) { + ( consistent, none ) 0.02, 0.95, 0.02, 0.01; + ( consistent, bad_certificate ) 0.95, 0.01, 0.03, 0.01; + ( consistent, connection_reset_after_ch ) 0.9, 0.01, 0.07, 0.02; + ( consistent, timeout_after_ch ) 0.85, 0.01, 0.09, 0.05; + ( consistent, timeout ) 0.55, 0.02, 0.4, 0.03; + ( consistent, connection_reset ) 0.65, 0.01, 0.25, 0.09; + ( consistent, other ) 0.07, 0.01, 0.07, 0.85; + ( consistent, down ) 0.07, 0.01, 0.07, 0.85; + ( inconsistent, none ) 0.02, 0.01, 0.05, 0.92; + ( inconsistent, bad_certificate ) 0.02, 0.01, 0.05, 0.92; + ( inconsistent, connection_reset_after_ch ) 0.02, 0.01, 0.05, 0.92; + ( inconsistent, timeout_after_ch ) 0.02, 0.01, 0.05, 0.92; + ( inconsistent, timeout ) 0.02, 0.01, 0.05, 0.92; + ( inconsistent, connection_reset ) 0.02, 0.01, 0.05, 0.92; + ( inconsistent, other ) 0.02, 0.01, 0.05, 0.92; + ( inconsistent, down ) 0.02, 0.01, 0.05, 0.92; + +} +probability ( TLS VP Result | TLS Ctrl Failure ) { + ( none ) 0.97, 0.005, 0.005, 0.005, 0.005, 0.005, 0.004, 0.001; + ( bad_certificate ) 0.02, 0.1, 0.01, 0.01, 0.01, 0.01, 0.02, 0.82; + ( other ) 0.01, 0.01, 0.05, 0.05, 0.05, 0.05, 0.12, 0.66; + +} From 8d58d2a294e7f94bdc2b5a35f0332d421bbef085 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arturo=20Filast=C3=B2?= Date: Wed, 28 Aug 2024 16:29:18 +0200 Subject: [PATCH 8/8] Add WIP files for bayesian network modelling --- notebooks/bayes-net-editor.ipynb | 18 +- notebooks/web-analysis-bn.ipynb | 712 +--- notebooks/web-analysis-full.bif | 4 +- notebooks/web-analysis.bif | 159 +- notebooks/web_analysis_complex.png | Bin 0 -> 79345 bytes notebooks/web_analysis_full.png | Bin 0 -> 79345 bytes oonipipeline/notebooks/.gitignore | 2 + oonipipeline/notebooks/DNS BN Analysis.ipynb | 3335 +++++++++++++++++ oonipipeline/notebooks/DNS Similarity.ipynb | 416 ++ oonipipeline/notebooks/dns_analysis_bn.png | Bin 0 -> 53986 bytes oonipipeline/notebooks/estimated.png | Bin 0 -> 72700 bytes .../estimated_extra_pc_stable_1M.png | Bin 0 -> 209387 bytes .../notebooks/estimated_hillclimb_1M.png | Bin 0 -> 72700 bytes .../notebooks/estimated_pc_stable_1M.png | Bin 0 -> 95670 bytes oonipipeline/notebooks/sql-analysis.sql | 114 + oonipipeline/notebooks/web-analysis-bn.ipynb | 335 +- oonipipeline/pyproject.toml | 2 + 17 files changed, 4190 insertions(+), 907 deletions(-) mode change 100644 => 120000 notebooks/web-analysis-bn.ipynb create mode 100644 notebooks/web_analysis_complex.png create mode 100644 notebooks/web_analysis_full.png create mode 100644 oonipipeline/notebooks/.gitignore create mode 100644 oonipipeline/notebooks/DNS BN Analysis.ipynb create mode 100644 oonipipeline/notebooks/DNS Similarity.ipynb create mode 100644 oonipipeline/notebooks/dns_analysis_bn.png create mode 100644 oonipipeline/notebooks/estimated.png create mode 100644 oonipipeline/notebooks/estimated_extra_pc_stable_1M.png create mode 100644 oonipipeline/notebooks/estimated_hillclimb_1M.png create mode 100644 oonipipeline/notebooks/estimated_pc_stable_1M.png create mode 100644 oonipipeline/notebooks/sql-analysis.sql diff --git a/notebooks/bayes-net-editor.ipynb b/notebooks/bayes-net-editor.ipynb index 206df489..3b1369d6 100644 --- a/notebooks/bayes-net-editor.ipynb +++ b/notebooks/bayes-net-editor.ipynb @@ -2,14 +2,14 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "id": "bc83eb2c-32c1-4d5a-9e4f-9e0e0378c8a6", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "7f87d42c453a4d27aaa170c18f9036f2", + "model_id": "660a13e6881c4d69b018e42528d36b35", "version_major": 2, "version_minor": 0 }, @@ -79,7 +79,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 3, "id": "97cc09d2-c71b-49a5-9a1c-3f6ace5e6b1f", "metadata": {}, "outputs": [], @@ -102,7 +102,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 10, "id": "fee25b03-eec8-4db4-9021-ce92eee94dbf", "metadata": {}, "outputs": [ @@ -117,11 +117,11 @@ "source": [ "validate_matrix([\n", " # consistent inconsistent\n", - " # \"none\", \"connection_reset\", \"timeout\", \"other\", \"down\"\n", - " [0.02, 0.95, 0.90, 0.85, 0.01, 0.07, 0.07, 0.07, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02], # blocked\n", - " [0.95, 0.01, 0.01, 0.01, 0.08, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01], # ok\n", - " [0.02, 0.03, 0.07, 0.09, 0.01, 0.07, 0.07, 0.07, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05], # down\n", - " [0.01, 0.01, 0.02, 0.05, 0.90, 0.85, 0.85, 0.85, 0.92, 0.92, 0.92, 0.92, 0.92, 0.92, 0.92, 0.92], # unknown\n", + " # \"none\", \"bad_certificate\", \"connection_reset_after_ch\", \"timeout_after_ch\", \"timeout\" \"connection_reset\" \"other\" \"down\"\n", + " [0.02, 0.95, 0.90, 0.85, 0.55, 0.65, 0.07, 0.07, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02], # blocked\n", + " [0.95, 0.01, 0.01, 0.01, 0.02, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01], # ok\n", + " [0.02, 0.03, 0.07, 0.09, 0.40, 0.25, 0.07, 0.07, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05], # down\n", + " [0.01, 0.01, 0.02, 0.05, 0.03, 0.09, 0.85, 0.85, 0.92, 0.92, 0.92, 0.92, 0.92, 0.92, 0.92, 0.92], # unknown\n", " ])" ] }, diff --git a/notebooks/web-analysis-bn.ipynb b/notebooks/web-analysis-bn.ipynb deleted file mode 100644 index 383eb0c0..00000000 --- a/notebooks/web-analysis-bn.ipynb +++ /dev/null @@ -1,711 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 7, - "id": "99aba231-cfe4-4ecb-8233-b34c90515fe9", - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd\n", - "from IPython.display import Image\n", - "from pgmpy.models import BayesianNetwork" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "c76afe2b-1a36-494f-aa99-c9ae037b39be", - "metadata": {}, - "outputs": [], - "source": [ - "msmt_feedback = pd.read_csv(\"msmt_feedback.csv\", delimiter='\\t', names=['measurement_uid', 'user_id', 'status', 'comment'])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ce851a49-6dab-472d-a5a7-78c41395acca", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1b64f651-0707-4bb9-9205-2df6658ed0eb", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "23fff868-7e7f-4961-9fbb-f2857e4cb899", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array(['blocked', 'down.unreachable', 'ok', 'blocked.blockpage.dns',\n", - " 'blocked.dns.nxdomain', 'blocked.dns.inconsistent',\n", - " 'blocked.blockpage.server_side', 'blocked.tcp', 'blocked.tls',\n", - " 'blocked.blockpage.http', 'down.misconfigured',\n", - " 'blocked.blockpage', 'down', 'blocked.dns'], dtype=object)" - ] - }, - "execution_count": 26, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "msmt_feedback['status'].unique()" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "8bd8a640-3e6d-4d54-b971-eb3332abcd89", - "metadata": {}, - "outputs": [], - "source": [ - "def map_outcome(status):\n", - " if status.startswith('ok'):\n", - " return 'ok'\n", - " elif status.startswith('blocked'):\n", - " return 'blocked'\n", - " elif status.startswith('down'):\n", - " return 'down'\n", - "msmt_feedback['outcome'] = msmt_feedback['status'].apply(map_outcome)" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "c736483d-b280-4972-aa38-70d272c077a8", - "metadata": {}, - "outputs": [], - "source": [ - "msmt_feedback[['measurement_uid', 'status', 'outcome']].to_csv('msmt_feedback_clean.csv')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d625a231-d3f6-4f05-93be-5710392437fd", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "a6346742-dc39-40e3-8673-686b25fb7d87", - "metadata": {}, - "outputs": [], - "source": [ - "web_analysis_bn = BayesianNetwork([\n", - " ('DNS VP Failures', 'DNS Outcome'),\n", - " ('DNS VP Failures', 'VP State'),\n", - " ('DNS Ctrl Failures', 'DNS Outcome'),\n", - " ('DNS Ctrl Failures', 'DNS VP Failures'),\n", - " ('Resolver config', 'DNS Outcome'),\n", - " ('DNS Consistency', 'DNS Outcome'),\n", - " ('DNS Answer Meta', 'DNS Consistency'),\n", - " ('DNS TLS Consistency', 'DNS Consistency'),\n", - " ('DNS VP Got Answer', 'DNS Outcome'),\n", - " ('Resolver Config', 'DNS Consistency'),\n", - " ('Resolver Config', 'VP State'),\n", - " ('DNS Outcome', 'TCP VP Failures'),\n", - " ('TCP VP Failures', 'TCP Outcome'),\n", - " ('TCP Ctrl Failures', 'TCP Outcome'),\n", - " ('TCP Outcome', 'TLS VP Failures'),\n", - " ('TCP Outcome', 'HTTP Failure'),\n", - " ('TLS VP Failures', 'TLS Outcome'),\n", - " ('TLS VP Failures', 'VP State'),\n", - "\n", - " ('TLS Ctrl Failures', 'TLS Outcome'),\n", - " ('TLS Outcome', 'HTTP Failures'),\n", - " ('HTTP Failures', 'HTTP Outcome'),\n", - " ('HTTP Failures', 'VP State'),\n", - " ('HTTP Body Consistency', 'HTTP Response is plaintext'),\n", - " ('HTTP Response is plaintext', 'HTTP Outcome'),\n", - "])" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "f78e3c55-3826-4622-b720-74452c7c13a2", - "metadata": {}, - "outputs": [], - "source": [ - "#web_analysis_bn.save('web_analysi.bif')" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "3d63e9c3-0430-4bc1-a5e3-583ae71f3405", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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g4GA8fPgQSUlJkJCQgLm5OZycnDB16lQ4OTnRcdb/v9LSUnh7e8Pb2xv3799HRUUFBg4cCGdnZzg7O2P8+PH0GI0SicfjISIiAnfu3MGdO3fw5MkT8Pl8WFlZYdq0aZg/fz5NKFEURVHdAU0SdLbKykr4+fnBx8cHvr6+KC4uhrGxMZydnTFu3DiMGTOGnj1GdZny8nKmI/TOnTuIj4+HiooKpk2bhlmzZmHKlCm084LqEcrKyhAUFISAgAAEBAQgLi4OEhISsLS0xOjRo5mEwLBhw+hQQVSPUlNTg+joaERERCA8PBxBQUF4+fIl5OTkmISBk5MTbG1t6f00AMTExMDX1xe+vr4IDQ1F79694ejoiLFjx2LMmDGwtbWFjIwM22FSFF69esUkDO7fv4/Y2FjIy8tj4sSJmD59OqZNmwZdXV22w+xSZWVl8PHxwZUrV+Dv7w9JSUlMmjQJU6ZMgbOzM4yMjNgOkeqGKioqcP/+fdy5cwc+Pj7IycmBqakp5s+fjwULFsDY2JjtECmKoihKFJok6Ax1dXW4efMmzp49i7t374LD4cDOzg4uLi5wcXHB4MGD2Q6RogAAz58/h4+PD3x8fBAUFIRevXphwoQJWLJkCWbPnk07Nqj3SnR0NLy9veHr64vo6GgQQpgzKsePHw9HR0eatKUoETIyMhAQEIDAwEAEBAQgOzsb8vLycHR0xKxZszBr1qwe1bkYFhaGCxcuwMvLC9nZ2dDW1sa0adMwbdo0ODs7Q0FBge0QKapFWVlZ+O+//+Dr64t79+6hpqYGI0aMwEcffYRPPvkE/fv3ZzvETsHn83Hnzh38+eefuH37NgDA2dkZ8+fPh4uLCz1ZhupQfD4fjx49wpUrV/DPP/8gNzcX5ubmcHNzw7Jly+jVKRRFUZQ4oUmCjhQVFYUzZ87g4sWLKCsrw6RJk7BgwQLMmDGD3jiWEnvFxcXw9fXFlStX4OfnBwUFBSxcuBDLli2Dra0t2+FRVJtxuVw8ePAA3t7e8PHxwcuXL6Gnp4eZM2diwoQJGDt2LB2bmaLeQWpqKnNF2u3bt1FVVQVra2vMnj0bLi4u7+WwCunp6fD09MSFCxfw7NkzDBs2DB9//DFmzJiBkSNH0vs3UN1aTU0NAgMD4e3tjatXr6KsrAxjx46Fq6sr5s6d+150nL969QqnT5+Gh4cH0tPT4eTkhKVLl8LFxYV21FJdgs/nIzg4GBcvXsTFixfB4/GwcOFCrF27FlZWVmyHR1EURVE0SdBeXC4XFy9exOHDhxEbG4uhQ4di2bJlcHV17VFn1VHvl7y8PHh6euL06dNITEyEqakpNm3ahMWLF9MxqSmx9/jxY5w8eRJeXl4oLS2FhYUFcyUX7cyjqI5VW1uL+/fvM8m4/Px8GBkZYfHixXBzc4Oenh7bIb4zPp+PGzdu4MiRIwgODoaGhgY+/vhjLF68GNbW1myHR1Gdor6+Hrdu3cKFCxfw77//QkJCAnPnzsXmzZsxfPhwtsNrs8zMTOzZswcXLlyAtLQ0li5dijVr1tAhXyhWvX79GufPn8exY8cQHx+PUaNG4dtvv8XUqVPZDo2iKIrquWiS4F3V1tbi9OnTOHDgAHJycrBw4UKsXr0ao0ePZjs0iupQYWFhOH78OM6fPw9NTU1s2bIFK1asgJycHNuhURSjuLgY58+fx8mTJ5GQkABLS0vmDEF6o2GK6hp8Ph+hoaH4559/cOHCBRQVFWHy5MlYsWIFZs6c2W3uYVBTU4OzZ8/ip59+Qnp6OlxcXLBy5UpMmjQJUlJSbIdHUV2mrKwMV69exdGjRxEbG4uJEydiy5YtcHZ2FvuEe0FBAfbt2wcPDw/o6uriq6++wieffAJ5eXm2Q6MoIUFBQTh06BB8fHzg4OCAvXv3YuzYsWyHRVEURfU8NEnQVnw+Hx4eHvj+++9RVlYGNzc3fPnllzAwMGA7NIrqVNnZ2Th06BBOnjwJOTk5fP3113B3d0evXr3YDo3qwWJiYnDw4EH8888/6NOnDxYuXIgVK1bAxsaG7dAoqkfjcDi4efMmTp48CT8/P6irq2PFihX44osvxHYIxvr6evzyyy84ePAgXr9+jaVLl2LTpk0YMmQI26FRFKsIIfD398ehQ4fg7+8PCwsL/O9//8O0adPYDq0RDoeDffv24eDBg1BSUsLOnTuxYsWKbpOkpHqu0NBQ7Ny5E3fv3sXkyZPxxx9/0BNdKIqiqK5EkwRtERcXh9WrVyMyMhLu7u748ssvoaWlxXZYFNWlioqK8PPPP+Pw4cMwNTWFh4cHHXaB6nLR0dH45ptv8N9//8HCwgLu7u746KOP6A1DKUoMZWZm4tSpU/jjjz9QVVWFVatWYceOHVBTU2M7NIa/vz/Wr1+PzMxMbNy4EevXr4eGhgbbYVGU2ImJicEPP/yAa9euYdasWThy5AgGDhzIdlgAgPj4eCxduhTJycnYtWsXPv/8c8jKyrIdFkW1SUBAADZs2ID09HQcOnQIq1atEvsrdyiKoqj3QoUk2xF0B/X19fjqq69gZWWFXr16ISoqCj/99BNNEFA9krq6Ovbt24fY2FgoKSlh1KhR2LBhA2pra9kOjeoBCgsLsXz5clhbW6OoqAg3b95EdHQ0Pv30U5ogoCgxpa+vj127duHFixfYt28fLl++jMGDB+PQoUPgcrmsxpafn4958+bB2dkZxsbGSExMxN69e2mCgKKaMHz4cFy9ehX37t1DWloaTE1NsXfvXtb35Z9++gnW1taQkZFBTEwMvvzyS5ogoLqlcePGITw8HO7u7li3bh2mTZuGwsJCtsOiKIqiegB6JUELCgoKMHfuXMTFxeHQoUNYsWIFJCVpboWigDeXn587dw4bNmzAkCFDcP36dXrDbqrTXLlyBevWrYOcnBx+/PFHfPTRR/TMKorqhiorK3HgwAEcPHgQZmZmOHv2LExMTLo8juDgYCxYsABycnI4evQoJk+e3OUxUFR3xuFw8Msvv+C7776Dra0t/v777y5PsHG5XKxevRrnzp3Dnj178OWXX9KhMKn3xuPHj7F48WJISEjg1q1bGDx4MNshURRFUe8vOtxQc/Lz8zFu3DhwuVx4e3uzcgAryoULF4TeS0lJQUlJCf369YO5ubnQDWWLiorg5+fHvJ80aRI0NTWFvl9XV4fr16+Dx+MBACQlJTFlyhT069cPdXV1OHv2LGJjY6GrqwsHBwfY2trC398fM2fObFW8OTk5uHr1KlJTU6GqqgonJyfY2dkhMzMTPB6vTb+r4G9x7NgxzJw5E1988YXI+YKCgvDy5ctml2VhYQELC4sW11laWgp7e3ts27YNS5cubXUMPUlqaipcXFxQX1+PgIAA6OnpsR0S9R7h8XjYtm0bDh8+jFWrVuHgwYPo27cv22GJFBISgoyMDKFp4lRG5+TkICAgoMXt6NevH9TU1PDs2bNG2/Lxxx83+T1xqzPa4+2yn+p4ycnJWL58OeLj43H+/HnMnj27y9bt6+uLefPmYfLkyTh79iyUlJS6bN3NEfcyRJTz589j4cKF7+1NnR88eICsrCwAgJycHObMmdPs/Onp6Xj06BGAN7/11KlToaKi0ulxsikuLg5z586FpKQk/P39oa+v3yXrJYTg008/xZUrV3DlyhXW75HQ8BhNQkIC0tLSUFRUhJmZGXR0dLo0FnE8XmGjfi8sLMSZM2cQGhqKuro6LF68GN9//323qtuLioowY8YM5OXlISQkhB5nURRFUZ2FDjfUlJqaGkyfPh0A8PDhQ7FJEABvhntZsmQJ3N3dkZqaitraWkRHR2P//v1QVVXFtGnTkJyczMzr7OyMoKAguLq6Yvbs2airqxNanrS0NKZOnQp/f38cO3YMY8aMQb9+/VBWVoaRI0ciLCwMS5cuhY2NDTw8PKCgoID79++3Ktb//e9/GDVqFOrq6rBq1Sp88cUX4HA4mDp1KhwdHYU6oN6OS5Ts7Gzk5ubi3r174HA4Tc7n4OAAHR0duLq6YufOnVBQUICCggJkZGRQXFyMPXv24OLFi63aBikpKaiqqjJDmbQ2hp5k8ODBePDgAeTl5TFlyhRUVlayHRL1niCEYPXq1fj9999x5swZ/Pnnn2KbIACA0aNHi3UZ/ejRI2zYsAHPnj1DWVkZnj17BldXVxw/fhwVFRXIy8vD+fPnsXnzZtja2mLAgAFwc3ODq6srFBUVMWvWrCa3vavrjM72dtnfGq2px6j/M2zYMAQFBWHdunWYM2cOTp061SXrffToEebOnYvFixfj+vXrYpMgAMS/DHlbTU0NNmzYAB8fnw7/LcSFnZ0d+vTpA1dXV8ydOxfh4eHNzr9582a4urrCw8MDY8aMaVOCoLuWIRYWFggODoaMjAwmTZqEsrKyLlnv4cOHceHCBVy9epX1BAHwf8doGzduRElJCbKzs/H1119DT08PmzZtQk1NTZfFIm7HK2zU79XV1ZgzZw4WL16MK1euQEpKCgsXLkTfvn271RCV6urq8PPzg7KyMnNSFkVRFEV1CkKJtH79eqKiokKeP3/Odigi9evXjwwdOrTR9Lt37xItLS0iIyNDnjx5IvTZ0KFDCQCybNkykcu8cOEC2blzJ/N+/fr1xNjYmPD5fKH5PvvsM7Jhw4YWY/z5559J7969SXBwcKPPampqyAcffEBOnTrFTNu8eTPh8XgtLvfVq1cEADl48GCL88rKyhILC4tG03Nzc8nGjRtb/H5HxNCTZGdnEw0NDfLpp5+yHQr1ntixYweRkZEh/v7+bIfSJuJaRp86dYo8ePCAeZ+UlEQAkLVr1zLT+Hy+UAwGBgZEVVW1ma1993gaamudIY5aW49RjW3bto1ISUmRhw8fdup6ysrKiLa2NnFxcRHrv5W4liFvO3nyJAFAxo8f36r5uysul0uUlJQIADJ37twm50tJSSHy8vIEAPnuu+/avJ7uXobk5uYSXV1dMm/evE5f17Nnz0ifPn3I/v37O31dbdGvXz9ibGwsNO2TTz4hAMju3bu7NBZxOV5hq3739PQk/fv3F1pXSEhIh6+nq6SmppK+ffuSXbt2sR0KRVEU9X4qp1cSiJCRkYFjx47hwIEDMDQ0ZDsckfr06SNy+oQJE/DXX3+htrYWc+fOFTojSV5eHnZ2djhz5gyOHDkicpkNz6oIDw+HtLR0ozG/t23b1uI44JcuXcLGjRuxZ88e2NvbN/pcRkYGv/32G0pKSgAAT58+xZ9//tnsMgXacjm7jIyMyOna2tpYt25dq5fTnhh6El1dXfzyyy84ffo0EhIS2A6H6uZiY2Px448/4siRI5g4cSLb4bSJuJbRpqamcHBwaDZ2CQkJrFmzRmi9TW1PQ11ZZ4ijttRjVGP79+/HtGnTsHz58k4963X//v3gcDg4ffq0WN9jSlzLkLcdP34cY8eOxf3795GUlNSq73RHvXr1wqBBg+Ds7AwvLy+kpqaKnO+nn37CkiVLAKDNZyq/D2WItrY2/vrrL1y7dg0PHz7s1HXt27cPgwYNwpYtWzp1PW0lat/99NNPAQCXL1/u0ljE4XiFzfo9Ojpa6FhQRkYGo0eP7vD1dBUjIyNs374dhw8fRnl5OdvhUBRFUe8h8T06YtHFixehqqqK5cuXsx3KO5k2bRomTJjAjPvY0PXr19G/f39s2bIFd+/ebXY5xsbGiImJgbu7u9Bljfr6+pgyZUqz3927dy8TS1NsbGzg6OiIkJAQzJgxA1VVVbh8+TIT8/Pnz/HNN9+Ax+Ph33//xYEDB8DhcNp9o9KwsDDw+XwMGjSImZaamopffvkFu3fvxq1bt4Tmr62txfnz53Hnzh1m2tsx/P3337h06RKuXbvGTLt27RouXbqEGzduMNOa2iYAqKiowIkTJ7Bp0yb8/vvvjYbsCQ4Oxo4dO/Dnn3/i+PHj7foNOtNHH30EAwMDeHp6sh0K1c399ttvMDExwapVq9gOpUOxWUbb2tq2qmP0gw8+aMWWtD8egbbUGUR5BBIAACAASURBVAJ1dXW4c+cOduzYgaNHj+L58+dC86elpWHnzp3g8/lITU3FDz/8gBMnTjTqgG6qbBVV9jc1f1P1GNB82d7aGAWxfPXVV/D29maGrPD29salS5dw6dIloc6nhIQEZnpxcXGTv6m4+fXXX/HixQvcvHmzU5bP4/Fw9uxZrF+/vluPES8O7TzgzXCcxsbG+OabbwAAR48ebXLe9uyPPj4+zP9zaGgoiouLmfeXLl1ihkbKyspipuXk5ABofv9rrk3WlK1bt4LP5+PQoUONPissLERkZGSz5VhT8TRXhjTXRhVHkydPxqhRo3D69OlOWweHw4GXlxc+++yzbnGTYkVFRQDAwIEDG33WnvZ/S/Xg28crvr6+QnWGIMkYFRXFTK+oqGgxrrbsO2zU73l5ebh06RJCQkJQVVXFbBvQdN1eXV0NDw8P7NmzB9euXUNpaSl4PB6ImN2+ce3ataipqekWZQFFURTVDbF9LYM4cnFxIR9//DHbYTRLS0tL5GXoAjt37iQAiJubGzNt5MiRhBBCIiIiiKysLOnXrx9JS0tjPr9y5YrQJbupqalETU2NACBDhgwht27dalVsqampBACRkpIidXV1Lc4fFBREFi1aRACQf//9l/j5+ZGzZ88SLS0tAoCcOXOGjBgxggAgISEhpLy8vNWXzqqoqAgNN8ThcMiMGTNIfX09M83d3Z04OjqSV69ekTt37hAJCQnmd0hKSiKzZ88mAMiPP/7IfOftGCoqKoi9vT1RVFRk5snNzSXm5uZES0uLEEKa3aZnz56RmTNnEj8/PxITE0PMzMzIoEGDSGlpKSGEkK1btxJPT09SVVVFLl26RBQUFFrcdjatWrWKTJgwge0wqG5u8ODBZM+ePWyH8U7EuYxuSNRwQ28bMmQI0dbWbnFZXVVnEPJmyAAnJydy+fJlUlpaSn777TfSt29f8s8//xBCCDlz5gzR1NQkAIiPjw+ZM2cOmT59OgFAvvnmG2Y5TZWtTZX9Tc0vqh4jhDRbtrc2xhcvXhBHR0dy4sQJkpWVRSZMmEAMDQ1JTU0NSUpKItra2gQASU1NZb7D4/HIhAkTyO+//95oKBlxN3r0aOLu7t4py05PTycASFhYWKcsvyN1hzJk3rx5JDIykhBCiLGxMenbty+pqKhoNF9798fExESipqZGNDQ0SGVlJSHkzbBLUlJSxN7enmkr8Xg88vnnn5ONGzcSDofT7P7XXJusKYLfd8SIEURaWprk5eUJff7NN9+Q06dPk3///VdkO7W5eJoqQ5pro4qz3bt3k2HDhnXa8gV1V2xsbKet411paWkJDTfE4/HIhx9+SAAQLy8voXnb0/5vqR4kpPHxSl5eHrGysiIAhIb+4fP5ZNq0aeTSpUstxtWWfYet+r2wsJB4e3sTBwcHoqurS7y9vYm3t3eTdXtRUREZNGgQOXv2LKmvrydbt24lAIiBgQFxcHBoVdxdycrKimzdupXtMCiKoqj3TzlNEojg5OTUbIeJOGjp4PHcuXMEAJk0aRIzTXBwQwghFy9eJACIqakpc0D39sEjIYTExcURCwsLAoAAIFOnTiXPnj1rNjZ/f38CoE0HB7t37yYAhDozduzYwTRACSEkOTmZ8Pn8NicJ5OXlyZgxY8iYMWOYg+GGSQIlJSWyd+9e5r2JiQkZNWoU8z4nJ6fFJAEhhHz++edCSQJCCFmxYgWTJGhumyZNmiR04HDr1i2msVtfX09UVVVJSkoK8/kXX3zR4razaevWrcTKyortMKhurl+/fuTYsWNsh/FOxLmMbqgjkwTvGs+71BmffPIJWb58udC0efPmEVlZWZKVlUUIIcxBvre3NzPPuHHjyJAhQwghpMWy9e2yv6X5RdVjzZXtrYlRsIxVq1Yx7//9918iISFBrl+/Tgh5M+YyAKZTURCrtbU14XK5zfyK4snFxYV88sknnbLsqKgoAqBN+whbxL0MyczMJE5OTsz73377jQAgR48eFTl/e/fHH3/8kUhKSpLc3Fxm2rx588iAAQOExvCfO3cuqa6uJoS0vP811SZriuD3vXTpEgFAtm/fznxWVVVFLCwsSF1dXZNJgpbiEVWGtNRGFVe//vor0dTU7LTlh4aGEgAkIyOj09bxrrS0tIiuri45c+YM2bNnDzExMSEffPABuXr1aqN529P+b009KOp4RVDnenp6MtPq6urInDlzWhUXIa3fd9iq3wU++uijRuWoqOO6DRs2EEVFRcLhcAghhGRlZREA5Ouvv2513F1p/PjxZPXq1WyHQVEURb1/6D0JRNHV1UV6ejrbYbRLVVUVAEBdXV3k5wsXLsRXX32FhIQELF68uMlLKc3NzREZGYlffvkFKioquHXrFiwtLRtdotlQR41/KSsry8QKAEOHDn2noYYGDRqEBw8e4MGDB8jJycGCBQuEPvf19cXatWsBvBmKiBDCDOUAtH5MWVFDeLw9TdQ25efnw9/fH48ePcL27duxfft2+Pr6wtraGtXV1ejduzf69u2LiRMnMpeW7tixo5Vbz47nz5+jf//+bIdBdXMDBw5EYmIi22F0CjbL6M7UFXVGdXU1rl69ihEjRghNF1yCLxjiQl5eHoDwEAdmZmbIzs4GgBbL1rfL/raWxXl5ec2W7a2JMS0tDf7+/pg9ezbz+fTp05Gfn48PP/wQwJsh3oyMjISGP/Hy8sLs2bO7xTAcDRFCkJCQ0Gn3g9LV1QWARkNXdEdslyHHjh3DZ599xrxfunQpFBQU8Mcff4icv73745IlSyApKYkLFy4w01RUVPDy5Uv4+/sDAF6+fAltbW3Iysq2av9713bm/PnzYWBggGPHjuH169cAgFOnTmHx4sVN3kuiNfGI0lIbVVylpaVBX1+/05avo6MDAMjMzOy0dbRH7969YWRkhOjoaCQmJuLbb7/FvHnzhOZp6X+iuX2itfWgKBMnToSxsbHQ/S+uX7+O+fPntyouoPX7Dlv1e3NEHdelpqZCUlKS2Yb+/fvDyMgIwcHBbYq/q7x8+ZKpzyiKoiiqI7F/NyMx5OzsjFWrVqGwsBAaGhpsh/NOUlJSAAAmJiZNzvPDDz8gPj4ePj4++Pbbb2FhYSFyPikpKaxfvx6LFi3Cpk2bcO7cOXz00Ud48eIFlJSUGs0/ePBgAG8aXDU1NUxDsq3ae+8BUfr06YPPPvtMqPPe3t4eXl5euH79OiZPngwDAwNmLFtAdOf/uxK1TYKb323duhVqamoiv/f777/D1dUV06ZNY25K2FTHANvKysrg5+eHAwcOsB0K1c3NmzcPhw4dwu7du7v1+OGisFlGd7bOrjMePXoEDofTqPNBsJxnz54BEF12y8vLg8vlMu+bK1tFfb8tZXFryvaWYhTcCPbtTo2GbZNevXph27ZtWLlyJcLCwmBra4u//voLZ8+eFblOcXb79m2kpaU16kzrKBoaGrC2toanp2erxtwXZ2yWIbW1tbhw4QISExPx999/M9NVVVWRkJCAwMBAODk5CX2nvfujlpYWpk6dirNnz+LLL79EQUEBAGDAgAE4ceIEJk+ejLNnzzL3E2vN/veu7cxevXph06ZNWL9+PTw8PLBx40b89ddfePDgQZPfaU08orTURhVHtbW1uHbtGlasWNFp6xB04vr4+GDMmDGdtp53JSsrC3t7e5iamiIyMhLLli1DXFwctLS0mHna0/5vbT3YlM8//xzr1q1DXFwcLCws4OXlhfPnz7c6rtbuO2zW700R9V0HBwf4+voiLCwMdnZ2qKurQ25uLmbMmNHi8rpaQkICnj9/3qiMpSiKoqiOQK8kEGHevHlQVVXFzp072Q7lndTX1+Pff/+FlJQUc6ahKJKSkvD09ISxsTH27t3b6OZ3P/74o9B7VVVVnD17FgsXLkRZWRlCQkJELldXVxempqbg8XiIj49vNtamzmzrTGPHjhU6u3Lr1q04deoUTpw4gcWLF0NaWrpL4xGcdRYVFdXoM8EZatOnT0daWho2bNiAyMhIWFtbM51H4ub777+HjIwMc3YRRb2r1atXQ1paGmvXrhW7G8e1B9tldEcTdCh0VZ3B4/EAvOlMaEjQmTFkyJBWx97WsrUt87embG+JoEPFz8+v0WdFRUXM6yVLlkBXVxc//PADUlJSoKysLNQZ1R28evUKa9euxbx582Bpadlp69m0aRMuXryI0NDQTltHZ2O7DLl06RJWr16NGzdu4Nq1a8zDy8sLQPM3MG5OS/uXm5sbEhISEBERgd9//x3r16/Hp59+Ch8fH+Tn5yM2NhYjR44E0DH7X3Pc3NzQr18/HDlyBJcvX8bEiROZm9OK8q7xsN1GfRf79+9HRUUFVq1a1anrWblyJY4fP478/PxOXU97KCsrw9PTEyUlJVi6dKlQW6Y97f/21oNLliyBoqIifv/9dyQlJWHw4MFMPB2577BZv7fFxo0bMW/ePGzduhV3797Fli1bMHr0aHz//fedsr722L17N0xNTWFvb892KBRFUdR7iCYJRJCTk8PPP/+MkydP4vLly2yH02YHDx5kGpTNnWEGAIqKivDx8YGKikqjg8egoCCRDe85c+YAaH4Ynt27dwN4c3BTX18vcp6ioqJGl8MKGocdqbnOxcjISBw8eBDr1q2DjIxMq77TFEVFRdTV1TVad0vbNHToUPTq1Qvfffed0G9VVFQET09PVFVV4cSJE+jXrx9+/vlnBAYGorKyEpcuXWpzjJ3Nx8cHv/zyCw4cOABlZWW2w6G6ORUVFZw7dw5eXl5Yv349+Hw+2yF1CHEoowUEZV1LZV5Tn/P5fJw4caLd8bSlzhgxYgSkpaUbdWAKOs0dHR2b3RaBtpatrZ1fUOa3VLa3homJCSQlJXHz5k2huuT58+eIiIhg3vfp0wdbtmzBzZs3sWHDBqxZs6ZVyxcXxcXFmDJlCnr16tXkcDUd5eOPP4azszPmz5+P3NzcTl1XZ2G7DPHw8BDZATxixAiMGjUKN27caNWwHw21Zv+aPn06NDQ08McffyAjIwNmZmZYvnw5eDwe3NzcMH78eGbejtj/miMvL49169YhJycH7u7u2LBhQ7PztyUewb7ekW3UrvLff/9h79692LdvX6cPh7Ju3Tqoq6vDzc1NrNsH9vb2+Pbbb3Hnzh2hYeHa0/5vbz2ooKCApUuXwtPTEwcPHhTanzt632Gjfm8rCQkJ6Ojo4Oeffwafz8e6devg7++Pvn37dsr63tXly5dx7do1HDx4sEOvdKcoiqIoAVq7NGHBggXYtGkTli5dypwZJS44HI7QGYQCdXV12LhxI3bv3o3t27dj7969Qp/n5OSIHPfUyMgIV65caTR2MZ/Px5IlS1BZWSk03dPTExYWFhg1alSTMc6dOxd79+7FgwcPsHLlSmbsXIHMzEzs378frq6uAP5vTN3IyEgEBQWhtrYWHA4HwJvOg4YE8by9zLfx+XxUVVWhrKysyXnk5OQAADdu3ACXy8Xdu3cRGxuL0tJSpKamIiMjQ+T6RE0bMGAA6urq4O/vD0II/v77bzx69Ajl5eUoLy8Hj8cTuU0qKipYs2YNnjx5grFjx+LixYs4c+YMFi1ahIULF4LP5+O7775DbW0tAMDOzg6DBw8Wu+GG/vvvP3z00UdYuXIlc7k/RbXXhAkTcPHiRZw4cQIffvghysvL2Q6pRd2hjBYQdBC+vYyG8vLy8OrVq0ZJ0Lq6Oqxfvx4GBgbtjqctdYaGhgbc3d2RkZGBgIAAZp4bN25g/vz5GDt2LACgpKQEAITG7+ZyueBwOKirq2uxbH27nG9p/rfrMVlZ2WbL9tbEqKOjgyVLliAuLg7z58/H/fv3cfToUXzzzTeNhstZuXIlVFVVkZGRgXHjxjX5W4ubuLg42Nra4tWrV7h7926n120SEhK4ePEi+vbti7FjxyIjI6NT1/cuxLkM8fHxgZKSUpN/p9mzZ4PL5WL//v1C09u7PwJvxnlfvHgxTp8+DTc3NwBvhp2ZMmUKAgICsGjRImbeltpWAJpsZ4pSXV3daJgfd3d3yMjIYNasWUId4nl5eQCEz7puTTxvlyGCTsDm2qjixNvbG3PmzMGyZcvg7u7e6euTl5eHp6cnAgIC4O7uLhbJEy6Xi1evXqGiokJo+o4dO+Do6MiM7w+0r/3f2nqwuWOmdevWoaamBsXFxUL3j+jofYeN+l2gtLS0UbtR1G9y4MABPHjwAFlZWejduzfKy8uRmJjYquGLusrDhw/h5uYGd3d3TJ06le1wKIqiqPdV194ouXvh8/lk3bp1pFevXmT//v2Ez+ezHRIhhJC5c+cSAERKSoqMGDGCfPjhh2Tu3LlkxowZZM2aNSQyMlJo/qioKLJixQoCgMyfP5/4+/uLXO6RI0fI/v37mfeLFi0ic+fOJSNGjCDLly8nX3/9NTE1NSVOTk4kIyOjVbFeu3aNmJmZEVlZWTJ27Fiybt06snLlSrJr1y5SV1fHzJeenk40NTWJiooKOXnyJLl27RoZOnQoE3NsbCwhhJDc3Fyydu1aAoCYmJiQGzduiFxvYGAgWbBgAQFAJCQkyObNm0lYWJjIeV1dXYmkpCTR1NQkf/75J9m7dy+RlJQkW7ZsIZmZmULru3XrVpMxVFVVETMzMwKAaGpqkrNnz5JVq1YRFRUVsmXLFuLh4SFymwTfXbJkCQFAABBFRUXi5eVFCCGkoqKCyMrKEnNzc/Lrr7+SXbt2keXLl5P6+vpW/Q26wpEjR4iUlBRxc3MjPB6P7XCo91BwcDDR0tIienp65NatW2yH06SHDx92mzLa09OT2NjYEABEWVmZ7N27l2RlZTGfP3nyhCxatIgpl/r3709sbGyIra0tsbCwIH379iUSEhIkOzu7Q+IhpPV1Bo/HI5s2bSLq6upk27ZtZOnSpWTBggWkpqaGEELIjRs3iIGBAQFAvvjiC5Kenk4uX75MBg4cSACQL7/8kqSlpTVZtooq+1sqi9+uxwhpvmxvTYwFBQWkvLycfPjhh8wyDAwMSHh4uMjfb+vWreTw4cOt+q3ZxuFwyL59+4i0tDQZM2YMKSgo6NL1FxQUkOHDhxM1NTVy+/btLl13c8S5DDl69ChRV1cnGhoaZP/+/YTL5Qp9HhgYSEaPHs20vT799FOSk5PT7v2xofj4eGJlZSU07fr16+STTz5pFG9z+19T7UxRAgMDyZw5cwgAsmbNGhIaGsp8tnbtWvL06VNCCCFcLpccPXqUWW7//v3JTz/9REpKSlqMhxDRZUhzbVRxwePxyK5du4ikpCRZs2ZNl7cDr1+/TqSkpMiyZctYbxsL9l3B/0rDY4/MzEyioqJCpKSkyOzZs4m/v3+72v8t1YOtOWZydnYWWf511L7TUFfW70lJSeTw4cNEWlqamS8wMFBk3U4IITdv3iQyMjLM9goe+vr65M6dO63avs5048YNIicnR+bPn9+o3KUoiqKoDlROkwSt4OHhQXr37k0cHR1JQkIC2+F0qqKiIua1oOOHz+eTuLg4EhAQQDIzM99puZWVleTx48dCy39bfX09qa6ufqflt1dhYaHQgYXggK6tBL9VVVUVIYSQZ8+etWmbioqKSGRkpNB3+Hw+qaqqIhUVFSQyMpK8fv36nWLrDOnp6WTy5MlEQkKCfPfdd2KTSKPeTyUlJWTVqlUEAJk4cSLTMdOTdFYZ3RG6us4ghJDq6moSFRXFdB60RVvL1tbM31Q9Jqpsb6ucnBwSExPTbCfYtGnT3rn+6kr+/v7E3NycyMjIiOxs7irV1dXEzc2NSEhIEFdXV5Kfn89KHF1JXMuQtuyPb8fI4XBITk5Ok/N3xP7XkZqLR1QZ0lFt1M4QGRlJRo0aRaSlpcmRI0dYi8Pf358oKioSCwsLEhMTw1oc76o97f/21IOZmZnNtt07Y9/pivq9ra5evUouXbpEXr16RVJSUkhUVBQJCAggv/32G3Fycur09TelpqaGbNu2jUhKShI3NzfC4XBYi4WiKIrqEcolCBGDazO7gZiYGKxevRrR0dHYtGkTdu/e3S1uHkZRnYHL5eLo0aPYuXMnBg4cCA8PD9jZ2bEdFtVD3Lt3D1u2bEFcXBymTZuG3bt3MzerpKie6tGjRzh37hz+/PNPtkNp0t27d/HNN9/gyZMnmDFjBo4cOYJBgwaxHRZu3ryJ9evXo6ysDLt27cK6desgJSXFdlgUJbZKS0uxa9cuHD16FA4ODvj9999hZmbGakzp6elYtmwZwsPDsWvXLmzZsqXREFsU9ba0tDTY29sjJyenUblfWFiILVu24Ny5c10eV1xcHJYsWYKMjIxG942gKIqiqE5SQe9J0ErDhw9HSEgI9u/fj6NHj8LExAQeHh6NxmimqPdZfX09Tp8+DVNTU2zfvh1ff/01IiMjaYKA6lITJkxAREQEzp07h4yMDNjY2MDZ2RlXrlxp8qZ4FPU+CgsLg4ODA1avXo1t27bhxx9/ZDukRoqKinD48GGYmJjA2dkZ6urqCA0Nxc2bN8UiQQAAM2fOREJCAtauXYutW7fCzMwMJ06cYMYCpyjqjby8PGzfvh2Ghoa4du0azp8/j8DAQNYTBABgaGiI+/fvY+fOnfj2229hZ2eHO3fusB0WJeaysrJQWFgIV1dXPHz4EFlZWcjKysLdu3exfv16fPfdd10aT3Z2NtasWQNra2uoqanh6dOnNEFAURRFdRmaJGgDKSkpbNq0CQkJCXB2dsYXX3wBQ0ND/PTTT83e9JGiurvq6mr8+uuvMDIywpo1a+Dg4ID4+Hhs374dvXv3Zjs8qgfq1asXFi1ahLi4OHh5eUFaWhqffPIJdHV1sXnzZiQlJbEdIkV1idTUVKSnp+PIkSNQUlJiOxwAb26I6+fnhwULFqB///74/vvv4eTkhJiYGPj4+MDW1pbtEBuRk5PDvn37EB8fD3t7e7i7u8PAwAB79+5t1c05Kep9lpCQADc3NwwcOBBnzpzBli1bkJyczNzIVlxISUlhx44diIiIgIaGBiZPnoyxY8ciODiY7dAoMTVu3Dj4+flBXV0da9aswZAhQzB9+nT4+fnh+PHjXZbMLiwsxMaNGzF48GDcvn0bHh4e8Pf3F7qpNEVRFEV1NjrcUDvk5eXh8OHD8PDwgJSUFBYvXoxly5bRYS+o90ZcXBzOnDmD8+fPo6amBitWrMDmzZuhp6fHdmgU1UhOTg5Onz6NU6dOMVcYzJ49Gy4uLjA1NWU7PIp6r3G5XDx8+BDe3t7w8vJCVlYWHB0dsWLFCsybNw9ycnJsh9gm+fn5+O233/Dnn3+irq4Oc+fOxeLFizF+/Hg6hAnVI1RUVOD69es4f/48AgICMGzYMGzevBmLFy/uNkOuPnr0CDt27EBgYCDGjRuHzz77DC4uLvQEF6pJhBBISEh02fqePn2KY8eO4dy5c1BUVMTXX3+NVatWoU+fPl0WA0VRFEX9fxU0SdABSkpKcPz4cZw5cwYpKSmwsLDA8uXLsWjRIqirq7MdHkW1SXFxMS5evIgzZ84gKioKgwYNwrJly7B69Wr6/0x1C3w+H/fv38eVK1fg4+ODgoICGBkZMQkDOzs72slHUR2gsrISfn5+8Pb2hq+vL0pKSmBubo7Zs2dj0aJFGDp0KNshtltlZSXOnTuH8+fP48mTJ9DR0cHChQvh6uoKS0tLtsOjqA7F5XLh5+eHCxcuwNvbG3w+HzNmzICbmxumTp3apZ2nHenevXs4cuQI/vvvP2hpaWHlypVYuXIldHV12Q6N6oHq6+tx/fp1/PHHHwgKCsKQIUPw2WefYeXKld0uoU5RFEW9V2iSoKOFhITgzJkzuHLlCmpqajBu3Di4uLhg5syZ9OxrSmzl5ubi5s2b8Pb2xv3799G7d2/MmzcPy5cvh6OjY7c9KKQoPp+PJ0+ewNvbG97e3khJSYG6ujqcnJzg5OSEcePGwdjYmO0wKapbqK+vR1hYGAICAhAYGIhHjx6Bw+HA3t4eLi4umD17NgwNDdkOs9OkpqbiwoUL8PT0xPPnzzFs2DDMmDED06dPh4ODA73ZMdUtlZWV4c6dO/D19cV///2H4uJiODg4wNXVFfPmzYOKigrbIXaYFy9e4Pjx4/jrr79QUlKCSZMmYf78+Zg9e/Z7tZ2U+OHxeAgKCsKVK1dw7do1lJaWYtasWVi7di0mTJhAj7UoiqIocUCTBJ2luroaXl5euHHjBm7fvo2qqiqMHDkSs2bNwqxZszB8+HC2Q6R6uKdPn8LHxwfe3t6IiIiAnJwcnJ2dMXv2bMyZMwcKCgpsh0hRHS45ORm+vr4ICAhAUFAQKioqoKWlxSQNnJyc3ouznymqI3A4HISHhyMwMBCBgYEICQlBdXU19PT0MG7cOIwfPx7Tp0+Hmpoa26F2KUIIHj9+jOvXr8PX1xfJyclQUlKCs7Mzpk+fjqlTp0JDQ4PtMCmqSYmJiUxSQDBe/+jRozF9+nQsWLAABgYG7AbYyerr6+Hl5YVLly7Bz88PfD4fEydOxIIFC+Di4gJlZWW2Q6TeAzweD8HBwbhy5QquX7+O/Px8WFpaYv78+Vi2bBm9koWiKIoSNzRJ0BW4XC6ePHmCq1ev4vr168jOzoaGhgbGjh0Le3t7ODg4YOTIkfQMAqpTpaenIzg4GCEhIbh9+zYyMzOhpqaGqVOnYubMmZg6dSpNDFA9Co/HQ0xMDLNf+Pv7o6ysDEpKSjAzM4OVlRUcHBzg4OAAbW1ttsOlqE6Xm5uLkJAQBAcHIzIyElFRUaipqYGWlhYcHR0xceJE2Nvb03t8vCUjIwP+/v64efMm/P39UVdXB0NDQ6aN5+zs/N53ulLiLT09HXfv3kVwcDAePnyIly9fQlVVFePHj8eMGTMwc+bMHnsmfXV1Ne7du4erV6/in3/+QV1dHYYPH46JEydi4sSJGDt2LL2HAdVqBQUFePjwIe7evYubN28iFwA8PQAAIABJREFULy8PJiYmmD9/Pj7++GMMGzaM7RApiqIoqik0SdDVCCGIiorCvXv3EBgYiKCgIFRWVkJHR4c5i3XUqFEwMTGhY2ZT74zH4yE5ORmhoaEIDAxEQEAAsrOzIS8vD3t7ezg5OWHChAmwtraGpKQk2+FSlFjgcrmIiIhAaGgoIiIiEB4ejmfPnoEQgv79+8PGxgY2NjYYOXIkTExM6BByVLfF5XKRlpaGp0+fIjIyEuHh4YiIiEBFRQWkpaVhaWnJ/L/b2dlhyJAhbIfcbVRVVSEgIAAPHz5EUFAQIiIiwOVyYWhoCEdHR4wZMwbW1tYwMTGhwxNRnaKyshIxMTEIDQ3FgwcPEBISgpKSEigqKsLBwQGOjo5wcnKCjY0NPdZ4S3l5OW7fvo07d+7Az88POTk5UFVVxYQJE+Ds7AwHBwd6tSElpKSkBI8fP8a9e/dw584dJCQkQFZWFmPGjGGuLqP/MxRFUVQ3QZMEbBN0SgnG9w0JCUFVVRXk5eUxcuRIWFtbMwfqRkZGbIdLiamMjAyEh4czj8jISFRWVkJOTg52dnbM2Ou2trb0bCiKaoOysjImYSB4ZGdnAwCUlZVhamoKMzMzmJmZwdTUFObm5j1u6BVKfBFCkJGRgYSEBMTHxyM+Ph4JCQlISkpCfX09evXqhWHDhjHtDBsbG1haWqJPnz5sh/7eqKqqwuPHjxEUFISHDx8iNDQUNTU1kJWVhaWlJaysrJgHTRxQbfX69WvExMQgMjKSeaSkpIDP50NdXZ1JTDk6OsLS0pImBdooPj6eSRgEBQWhpqYGampqsLOzg729PUaPHg1ra2vIysqyHSrVBQghSElJwePHjxESEoLHjx8jKSkJhBCYmZnB2dkZkydPhqOjI/2foCiKorojmiQQN1wuF4mJiQgPD0dYWBjCw8Px9OlTcLlc9OvXDyNGjBDqjDIxMYGioiLbYVNd5PXr10hKSkJcXBwSExPx9OlTxMTE4NWrV5CSkoKpqSnT0WNrawszMzPa4UBRHaykpARPnz5FYmIisy/Gx8ejpKQEAKChoQETExMYGRnByMgIgwYNYl7TIb2ozlBYWIi0tDSkpaUhNTUVz58/R2pqKpKTk1FZWQkAGDBgAJPUEjwbGxvTjowuxuVykZCQgKioKKZTNzY2lkkcCJKOw4YNg6mpKYyNjWFgYECv+uvh6urqkJycjOTkZCbRFx8fj2fPnoHP50NNTY1JNo0cORJWVlZ0iKsOVl9fj6ioKKaD+NGjR8jLy0Pv3r0xfPhwjBgxAsOHD8fw4cNhbm5O6/tujs/nIzU1FTExMcwjIiICr169gqysLKytrTF69GiMHj0adnZ2UFdXZztkiqIoimovmiToDmpqahAdHY3w8HDExcUxnVNVVVUAhA/8jY2NmQ4pOoZ291VQUMB0+CQnJzNnf7548QKEEMjJycHExARmZmawsLBghkCRk5NjO3SK6rFyc3ORkJCAp0+f4tmzZ8w+nJWVBT6fDwDQ1tZmEgZGRkYYMGAA9PX1oaenB11dXXqlDyVSVVUVXr58iezsbGRlZSE9PZ35/0pLS0NFRQUAQFpaGoaGhhg8eDCMjIwwbNgwekJBN8DlcpGUlMQkDASdwIKrluTk5DBs2DCYmJgwCUhDQ0MYGhr22HHk30eEEOTm5iI9PR3p6elISUlBUlISEhISkJ6eDh6PBykpKRgZGTH/C4KEgL6+Ptvh90gvXrxASEgIwsLCEBMTg9jYWJSXl0NSUhJGRkZM0sDY2BhDhw7FoEGD6JVaYignJwf/j737DovqWt8G/NARpLehSRMUEBRQQUFFwKCGsWM0RY01xhhP9ERNYmyxJcc0NRqNP6MklgOi4kwsgB07oIKAFOl1hjb0MuX7I9/sA4qJsbAZeO/rmmuKAzwD7r3XXu9aa6enpyMjIwMPHjzA/fv3kZycjPr6eqiqqqJ///4YNGgQvLy8MGzYMHh6elJ7jRBCSHdERQJFJV9CQN55LC8cpKeno6mpCQCgra3NFAza3ltbW8Pa2ppGD7KoqakJhYWFyM/Px+PHj/H48WNkZWUx9/KRnxoaGnBycoKLiwvc3d3h4uICNzc32NnZ0ahCQhREc3PzU5268lthYSFaWloAAMrKyuBwOOjTpw+srKxgbW3droBgbm4OU1NT2nd3MyKRCCUlJRAIBO0KAXl5eSgoKEBRUREzSwX489hub2/frtgkP8ZbW1vTsaEbEYlETCdx2xHkBQUFkEgkAAADAwOmYND2Jt+HaGtrs/wpSFtCoRAlJSXIzc1ligHyW05ODtOG19TUZIoBzs7OTFHAycmJOpm7uOzsbKaj+f79+0hKSkJeXh5kMhlUVVVha2uLfv36MTcnJyfY2trCysqKZv++RkKhEPn5+cjMzER6ejpTFMjIyEBtbS2AP5eRHDBgAFPcGTRoEAYMGAANDQ2W0xNCCCGdgooE3Y1MJkNRURHT4dy28/nx48cQiUTMe42NjWFpackUDdo+NjMzg7GxMUxMTKCkpMTiJ1I8QqEQ5eXlKCsrQ0FBAdPJU1BQgMLCQhQVFUEgEDDv19HRYTp52hZzHBwcYGVlRR0+hHRjMpkMJSUlzL6isLCQ6RyWFxJLS0vR9lCtq6vLFAw4HA44HA5MTExgbm4OMzMzmJqawtDQEIaGhjAwMKB9SCdrbm5GVVUVKisrUVlZibKyMqYIUFpaitLSUgiFQhQXF0MgEDCdggCgrq4OKysrWFlZobm5GYmJiejfvz9GjhyJ0NBQuLu708hxgpaWFuTl5T3VwSx/3Latp6urCysrK1haWsLCwgLW1tYwNzeHlZUVOBwO096jYsLLqaysZNp/RUVFKC4uRkFBAbN/Ly4uRlFREZqbm5mvMTc3f6q4Y2dnB3t7e1hYWFD7uxtpaGhgOqQzMjLw6NEjppNaPhNMRUUFFhYWsLGxga2tLTPT0MbGBlZWVjAxMYGpqSnLn6Rrqq+vZ46veXl5zC0/Px95eXnIzc1FQ0MDAEBNTQ12dnbtijT9+vVD//796fdLCCGkp6MiQU9TXl7ervOpqKjoqcdtOyyUlZVhYmLCFAzMzMxgYmLCvGZgYAA9PT3o6elBV1eXeaynp8fip3w1ampqIBKJnrpVV1czJ4Ll5eVMh095eTmEQiEzug/4cyaApaUlLC0tYWNjA0tLS1hZWaFPnz5MUYYapISQv9LS0oLS0lKmU7msrAylpaUQCAQoKSlBWVkZ0+ksHw3Xlr6+PgwMDGBkZAQDAwOmeCC/19XVhb6+PrS1taGlpQVdXV3o6upCS0sL2tra0NfXZ+FTs0MsFqO2thY1NTWor69HfX09RCIR6urqUF9fj9raWqYA8OS9/LF8KUA5JSUlpnPHzMwM5ubm7Yo6JiYmsLS0hImJCTgcDtMxWFhYiJMnT+L06dO4cuUKZDIZRo4ciQkTJmDChAmws7Nj41dEFEBFRQUzOEHeOV1YWIiSkhLk5+ejpKQEFRUV7b6mV69eMDY2hrGxMczMzGBkZMQ8NzY2hr6+PrNvkN/09PSgr6/fbTqzW1paUFNTg5qaGlRVVTGPa2pqUF1dzbT7hEJhu3ZgeXk5xGIx831UVFRgZmYGKysrpjBjYWHBtAHNzc1hY2NDs8IIAKC0tBS5ubl4/PgxTp48iTt37sDd3Z3p6G57XFdTU2POx54cLGBoaMgc79veK1oBUCwWo6qqClVVVaiurmbuKysrIRAIIBQKUVRUBKFQyBTh2x531dTUYGVlxRRZ7OzsmGKL/EZLBRFCCCEdoiIBeZpAIIBAIOiwA7y0tLTdSVJ1dXW7E6O22hYQVFVVYWBgACUlJejq6kJVVZV5XUdHB2pqau0u8KWrqwsVFZV2309ZWbnD4kNNTU27jnkAkEgkzMgc4M8RJi0tLaitrYVYLGa+RiQSQSqVMp9DXgSorq5GR5uGqqoq9PX1mZPmjgonbZ9zOJx/9LsnhJCX0djYCIFA8Jed2E/eyzvA/qo50Lt3b2hpaaF3795Mp6COjg5UVVWhoaEBLS2tdvto+T5cU1OzXUfYk/v6ttTV1Z/ZmfFX+aqqqto9l+/fm5qa0NjY2O54IN/nNzY2oqmpCS0tLaivr0dVVRUaGhrajfLtKJ+Ojk6HhZa/ujc1NX3pJSTq6+tx8eJFREREgMfjobq6Gvb29ggJCUFoaCiGDx9OM0bIP9LY2MgUG9t2dnfUAV5RUYHq6uqn2lpyOjo67YqLvXr1Yrb9ju6f3C901OYDAD09vaf+Xzc3NzMjgtuSb+9y8v2AvN33rHuRSMQUAtoOkmlLU1MT+vr6TOFEXvQzNjbu8DUzMzNaNoY8t5aWFhw4cABbtmyBUCjEBx98gM2bNzPXGauqqkJxcTHTIS4/H2s7WEB+3O/o/7C6ujpTNOjduze0tbWhrq7OnIfp6ekxx3H5vwFgXmtLft7WVkfb5JPnYVVVVcx2J99W6+rq0NraiurqajQ3NzMFAfmSq20pKyvDwMAApqamMDExgYWFBUxNTWFqagoLCwvmnMvc3BwcDqfD/QkhhBBC/hYVCcjLk4+0fHLkfVVVFfO6vBGYn5+Pa9euwd/fH01NTUyDUd5RA/y5/EZ1dfVTP6fte9rS0tLqcK3ItieX8veoqqqitLQUnp6eTIe/kpISDAwMmIaynp4eM7q27cwIPT09hRuNQwghz6uhoQENDQ1Mh1nbkfS1tbXMc/n+Wd7hLu9cl+/Pgf916j/Z8S7vnH/Wz39WJ33bjosn9e7du92oQPlzedFBSUmJmQ0h/zd554e8w0O+f9fW1mY6O+UzK/T19Z/6GWySSCS4efMm+Hw+Tp06hfT0dBgbG2PcuHHgcrkYN27cMwsxhLyM+vp6Zv9QW1uL6urqdp3s8v2GvBNQvr0/ed92W5dKpe2WR5J71usqKiodXoRb/rq8CGhmZsYUJdXU1JiipvxeXpjoaIaEfHaV/DFdA4C8Dq2trTh69Cg2btyIgoICzJkzB2vXroWlpeULf8+mpqanRuC3vZfPimtpaYFIJEJraytqamqYjv66ujrU1NRAKpUCAHPNJLmOCgLP2ibbzjLS19dntjt5kVC+bRoYGEBdXZ2Z+dDRbIjuMEOdEEIIUQBUJCCdp6ysDIMGDcLIkSPx3//+l5UM9+/fx9ChQ7F9+3Z8/PHHrGQghBBCXpXs7GzweDxERETg5s2b0NDQQGBgILhcLrhcLszNzdmOSEiniYqKwuTJkxEfHw9PT0+24xDyFKlUisjISHzxxRfIzc3FjBkzsH79etjb27MdDQAQGBgIQ0NDREREsB2FEEIIIZ2LigSkc0ilUgQHByM3NxcJCQkdjjjpLOvXr8d//vMf3Lt3D05OTqzlIIQQQl4loVCIs2fPgs/n4+zZs2hoaICHhwdCQkLA5XLh5eXFdkRCXiuZTIbBgwejb9++rA1IIaQj8uLAmjVrkJOTgxkzZmDdunVwcHBgOxqjuLgYffr0QUREBCZPnsx2HEIIIYR0LioSkM6xYcMGbN26FTdu3GB9ZJdYLMawYcOgpqaGa9eu0bqVhBBCup3GxkbExsaCz+eDx+OhpKSEuY4Bl8vFqFGjuswSSoS8SuHh4Zg5cyaSkpLg6urKdhzSw8mLA19++SUyMzMxdepUbN68GY6OjmxHe8q3336LjRs3oqysDJqammzHIYQQQkjnoiIBef2uXr2KgIAA/PDDD/joo4/YjgMASE1NhZeXFzZt2oQVK1awHYcQQgh5baRSKe7duwcejwc+n4+EhAQYGhoiMDAQISEhmDRpEqsz/Ah5laRSKdzd3eHp6YmwsDC245AeSiaTgc/nY+3atUhKSsLUqVOxadOmLj2L2cvLCx4eHti/fz/bUQghhBDS+ahIQF4voVAIDw8PeHh44PTp08wFrLqCzZs346uvvkJCQgKNNCOEENJjyK9jwOfzceXKFaioqMDPzw8hISGYOnUqrKys2I5IyEsJCwvD3LlzkZaW1iVHbJPuS14cWL9+Pe7fv4+pU6fiq6++Qr9+/diO9pcePXoEZ2dnXLhwAQEBAWzHIYQQQkjnoyIBeX1kMhkmTpyI+/fv4/79+zA0NGQ7UjtisRi+vr4Qi8W4desWLbtACCGkx6moqMDFixfB4/EQFRWFmpoauLi4gMvlIiQkBL6+vl2qwE/I85BIJHB2doa/vz/27dvHdhzSQ8TGxmL16tVITEzEm2++ia+++gqDBg1iO9ZzWbduHX755RcUFBTQUqyEEEJIz1SjzHYC0n19/fXXOHfuHI4dO9blCgQAoKqqikOHDiE1NRXbt29nOw4hhBDS6YyMjBAaGoqwsDCUlZUhJiYGQUFBOHz4MEaMGAE7OzssWrQIPB4PLS0tbMcl5LmoqKjg008/xcGDB5GXl8d2HNLNxcbGYujQoXjjjTdgbm6O+Ph48Hg8hSkQAMCxY8cwc+ZMKhAQQgghPRjNJCCvxZ07d+Dn54etW7d2+TX/v/nmG6xduxZ3796Fm5sb23EIIYSQLiElJQURERHg8/lITEyElpYWRo8ejdDQUEyYMAH6+vpsRyTkmVpbW+Ho6Agul4udO3eyHYd0Q3Fxcfjiiy9w9epVBAUFYdu2bfDy8mI71j92+/Zt+Pj4ID4+XiHzE0IIIeSVoOWGyKtXVVUFT09PODs7448//ujyyxRIpVKMGjUKdXV1uHPnDi07RAghhDwhLy8P58+fB4/HQ3R0NCQSCXx8fMDlcjFp0qQuv9426Zl27dqFTz/9FI8fP4aFhQXbcUg3ERcXhy+//BKXL19GUFAQtmzZgiFDhrAd64UtW7YMZ86cQWZmJttRCCGEEMIeWm6IvFoymQxz586FWCxGWFhYly8QAICysjL279+P9PR0bNmyhe04hBBCSJdjY2ODhQsXgsfjobKyEidPnoS9vT22bduG/v37w8HBAcuWLUNcXBykUinbcQkBAMyfPx+Ghob47rvv2I5CuoHr168jMDAQI0aMQGtrK65cuYKYmBiFLhBIJBKEh4fjvffeYzsKIYQQQlhGRQLySv3www/g8Xg4dOgQjI2N2Y7z3Pr164etW7di06ZNuH37NttxCCGEkC5LW1sbXC4XYWFhKC8vx7Vr1xAaGopz585hxIgR4HA4mDVrFiIiIlBXV8d2XNKDaWpq4pNPPsHPP/8MoVDIdhyioG7cuAEulws/Pz80Nzfj0qVLiIuLw8iRI9mO9tIuXLiA0tJSzJgxg+0ohBBCCGEZLTdEXpn4+Hj4+vpi7dq1+OKLL9iO84/JZDK8+eabyMjIwL1796Cjo8N2JEIIIUShpKSkgM/ng8fj4caNG9DU1ERgYCC4XC64XC7Mzc3Zjkh6mPr6etjZ2WHhwoXYtGkT23GIArl16xY2b94MPp8PX19fbNy4EQEBAWzHeqXmzJmDtLQ0GiRFCCGEELomAXk1amtrMXjwYFhaWiImJgYqKipsR3ohxcXFcHd3x7Rp0/Dzzz+zHYcQQghRWEKhEGfPngWfz8eZM2fQ2NgIDw8PhISEgMvl0gUySafZvHkzvvnmG+Tm5sLAwIDtOKSLS0pKwqZNm3D8+HEMGzYMq1evBpfLZTvWK9fU1AQOh4MNGzZg2bJlbMchhBBCCLvomgTk1fjggw8gEolw+PBhhS0QAICFhQV++eUX7Nu3Dzwej+04hBBCiMIyMTHBrFmzEB4eDqFQiFOnTsHLywt79+7F4MGDmesYxMbGorW1le24pBtbunQpVFRUsHPnTrajkC4sOTkZ06dPx6BBg1BQUICoqChcv369WxYIAOD06dOora1FaGgo21EIIYQQ0gXQTALy0vbs2YOPPvoI586dw5gxY9iO80rMnj0bZ8+eRVJSEjgcDttxCCGEkG5DKpXi3r174PF4iIiIQGpqKoyMjBAQEICQkBBMmjQJurq6bMck3czatWvx008/ITc3l5aUJO2kpKRgw4YNOH78ONzc3LBmzRpMmzYNSkpKbEd7raZNmwaRSISYmBi2oxBCCCGEfbTcEHk5ycnJ8Pb2xqeffooNGzawHeeVqaurg4eHB/r27YszZ850+5MEQgghhC3Z2dng8Xjg8/m4fPkyVFVV4efnh5CQEEydOhVWVlZsRyTdQGVlJWxtbbFmzRqsXLmS7TikC0hNTcW2bdtw5MgRuLi44Msvv+wRxQEAaGhogKmpKb777jssXLiQ7TiEEEIIYR8VCciLq6+vx+DBg2FqaoqLFy8q9DJDHbl+/TpGjRqF3bt3U+OZEEII6QQVFRW4ePEieDweTp06hdraWri4uCA0NBRcLheenp49ogOPvB6rVq3CwYMHkZOTAy0tLbbjEJakpaVh69atOHLkCPr3749169b1mOKAXEREBGbOnIni4mKYmpqyHYcQQggh7KMiAXlxs2bNwrlz53Dv3j1YWlqyHee1+Oyzz7Bz504kJibCycmJ7TiEEEJIj9HU1IS4uDjweDxERkaiqKgINjY2CA4ORkhICIKDg6Gurs52TKJAysrKYG9vjy1bttCFWnugnJwcbNu2Df/3f/+Hfv36YdWqVXjnnXe63UCn5zFjxgwIBAJcvHiR7SiEEEII6RqoSEBezIEDBzB//nxERUV124t5AUBrayt8fX0hlUpx8+ZNqKmpsR2JEEII6ZFSUlIQEREBPp+PxMREaGlpYfTo0QgNDcWECROgr6/PdkSiAJYtW4aIiAhkZ2dDU1OT7TikE+Tl5WHLli04cOAAHB0dsXr16h5bHAD+LMCamZlhy5YtWLJkCdtxCCGEENI1UJGA/HMpKSkYOnQoli5dim3btrEd57VLS0uDl5cXVq1ahXXr1rEdhxBCCOnxcnNzER0dDR6Ph+joaEgkEvj4+IDL5WLy5Mk0+488U0lJCezt7fH999/jgw8+YDsOeY3y8/Px7bffYu/evbCwsMDq1asxb968HlsckDt16hSmTp2KgoICWFhYsB2HEEIIIV0DFQnIP9PU1AQfHx9oaGjg2rVrPWaa/86dO7F8+XLExcXB29ub7TiEEEII+f+qqqoQGxsLHo8HHo+H6upquLi4gMvlIiQkBL6+vj1qrXHy9z744AOcPXsWmZmZPaYt25MUFBRg+/bt2Lt3LzgcDj7//HPMnTsXqqqqbEfrEt577z3k5OQgLi6O7SiEEEII6TqoSED+mfnz5yMyMhL37t2Dra0t23E6jUwmw7hx45CZmYnExETo6emxHYkQQgghT5BIJLh58yb4fD5OnjyJjIwMmJiYYOzYseByuRg/fjy0tbXZjklYlp+fD0dHR+zduxdz5sxhOw55RQQCAb777jv8+OOPMDU1xfLly/HBBx9AQ0OD7WhdRmtrK8zMzPDll1/ik08+YTsOIYQQQroOKhKQ5xceHo4ZM2YgMjISkydPZjtOpxMIBBg0aBD8/PwQHh7OdhxCCCGE/I2UlBTw+XzweDzcuHEDmpqaCAwMBJfLxYQJE8DhcNiOSFjy/vvv49q1a3j06BGNMFdwQqEQ3377LXbs2AFjY2OsWLGCigPPcObMGYSEhCAnJwc2NjZsxyGEEEJI10FFAvJ8srKy4OXlhblz5+L7779nOw5rLl26hKCgIPzyyy+YO3cu23EIIYQQ8pwEAgHOnTuHiIgIxMTEoLW1FR4eHggJCcH06dPh4uLCdkTSibKystC/f3/89ttvmDlzJttxyAsoLy/H9u3bsXPnTvTu3RvLly/HsmXL6ILUf2HevHl4+PAhbt++zXYUQgghhHQtVCQgf6+5uRnDhw+HkpISrl+/3uNH5axevRq7du3C3bt34ezszHYcQgghhPxDDQ0NuHDhAvh8Pk6fPo3S0lLY29sjJCQEXC4X/v7+NLq8B5g5cyaSkpKQnJwMZWVltuOQ51RRUYGdO3fi+++/h4aGBlasWIGPP/4YvXr1YjtalyYWi2Fubo5PP/0UK1euZDsOIYQQQroWKhKQv7dkyRKEhYUhISEBTk5ObMdhnVgsxsiRI1FbW4s7d+7QCQkhhBCiwCQSCe7fvw8ej4fw8HCkpaXByMgIAQEBCAkJweTJk6Gjo8N2TPIapKamws3NDREREZgyZQrbccjfqKysxI4dO/DDDz9ATU0N//73v7F06VJoaWmxHU0hxMTE4I033kBWVhYcHBzYjkMIIYSQroWKBOSvRUZGYtq0aTh8+DDefvtttuN0Gfn5+Rg0aBDefvtt7Nq1i+04hBBCCHlFsrOzwePxwOfzcfnyZaiqqsLPzw8hISGYNm0aLC0t2Y5IXqEpU6YgJycHiYmJUFJSYjsO6UBtbS12796Nbdu2QUVFBR999BGWL18OXV1dtqMplA8++AB37txBYmIi21EIIYQQ0vVQkYA8W35+Pjw8PDB9+nTs2bOH7ThdzvHjxzF9+vQeeyFnQgghpLurqKjAH3/8AT6fj3PnzqG2thYuLi4IDQ0Fl8uFp6cndSwruHv37sHLywt8Ph/jx49nOw5po66uDj/99BO+/vprKCkpYenSpfjkk0+gp6fHdjSFI5VKYWVlhSVLluCLL75gOw4hhBBCuh4qEpCOtba2YtSoUbSkzt9YsGABjh8/jvv378PGxobtOIQQQgh5TZqamhAXFwcej4fIyEgUFRXBxsYGwcHBCAkJQXBwMNTV1dmOSV7Am2++iYqKCty6dYvtKAT/Kw588803aG1txYcffojVq1dDX1+f7WgK6/Llyxg9ejTS0tLQv39/tuMQQgghpOuhIgHp2PLly7Fv3z66OO/faGpqgre3N3R1dXHp0iW6yCEhhBDSQ6SkpCAiIgJ8Ph8JCQnQ1tbG6NGjERoaigkTJlCHpgK5desWhg0bhtjYWAQGBrIdp8eqr6/H/v37sXXrVtTX12PJkiVYtWoVDAwM2I6m8JYuXYrLly8jOTmZ7SiEEEII6ZqoSECedubMGYSEhODgwYOYNWsW23G6vJSUFAwZMgT//ve/sXHjRrZDOIVuAAAgAElEQVTjEEIIIaST5ebmIjo6GjweD9HR0ZBIJPDx8QGXy8XkyZPh5OTEdkTyNwIDAyGVSnHp0iXmNYlEgvDwcAwbNgy2trbshevmmpubcejQIaxfvx61tbVYsmQJVq5cCUNDQ7ajdQsymQw2NjaYO3cu1q9fz3YcQgghhHRNVCToqfLy8lBfXw8XF5d2rxcWFsLDwwNcLhcHDhxgKZ3i2bNnDz766CNER0fTCDRCCCGkB6uqqkJsbCx4PB5Onz4NkUgEFxcXcLlchISEwNfXl65j0AVdunQJAQEBuHr1Knx8fHDkyBFs2LABOTk54PF4CAkJYTtit9PS0oKDBw9iw4YNEIlEmDdvHj7//HOYmZmxHa1buXnzJoYPH44HDx7A3d2d7TiEEEII6ZqoSNBTff3111i/fj12796N999/HwAgFosxevRoCAQCxMfHQ0dHh+WUimXmzJm4dOkSHjx4QCc3hBBCCIFEIsHNmzfB5/Nx4sQJZGZmwsTEBGPHjkVoaCjeeOMNaGhosB2T/H++vr4QiUSoqalBUVERZDIZVFRUsGPHDixevJjteN2GvDiwceNGlJeXY/bs2diwYQM4HA7b0bql1atX4/jx48jKymI7CiGEEEK6rhplthMQdhw/fhxNTU2YO3cu3nnnHdTV1WHt2rWIj49HeHg4FQhewO7du6GpqYnZs2dDKpWyHYcQQgghLFNRUYGfnx+2bduGjIwMPHz4ECtWrEB2djYmTpwIQ0NDcLlc7Nu3D6WlpWzH7bGam5uxb98+pKWlITU1FYWFhZBKpUyRoKCggO2I3UJrayvCwsLg7OyMpUuX4s0330R2djb27t1LBYLXKCoqChMnTmQ7BiGEEEK6OJpJ0AOVlZXB3Nwc8j+9mpoajIyMIBAIsHfvXsyfP5/lhIrr7t27GDFiBD777DOsW7eO7TiEEEII6aIEAgHOnTuHiIgIxMTEQCwWY9CgQQgJCcFbb70FZ2dntiN2e3V1ddizZw++/vprVFdXM4WBtpSVlTFz5kz8/vvvLKVUfK2trTh69Cg2btyIgoICzJkzB2vXroWlpSXb0bq9rKwsODo64tKlS/D392c7DiGEEEK6LppJ0BOdOnUKysr/+9O3trZCIBAAAOrr69mK1S0MGTIE3333HTZu3Ihz586xHYcQQgghXZSpqSlmzZoFHo+HyspKnDx5El5eXvj555/h4uICBwcHLFu2DLGxsRCLxWzH7ZY+++wzrFy5EhUVFZBIJE8VCABAKpXi8ePHLKRTfFKpFBEREXB1dcX8+fMxfPhwpKWlYe/evVQg6CSnTp2CoaEh/Pz82I5CCCGEkC6OZhL0QMHBwbhw4QIkEslT/6akpAQul4uDBw/CwMCAhXTdw+zZs8Hn8xEfHw87Ozu24xBCCCFEQbS9jsHp06eRlpYGIyMjjB8/HlwuF2PHjqVlIV8RiUSCOXPm4MiRI3+5VKS5uTmKi4s7MVnXlJWVhb59+/7t+6RSKSIjI7FmzRrk5ORgxowZWLduHRwcHDohJWlr1KhRsLGxQVhYGNtRCCGEENK10YWLe5ra2loYGRmhtbX1me9RU1MDh8PBiRMnMHjw4E5M133U19fD29sb2trauHr1Kl2UkBBCCCEvJDs7GzweD3w+H5cvX4aqqir8/PwQEhKCadOm0YjslySRSPD+++/j8OHDzywUqKiooLm5GSoqKp2cruu4desWxowZg9jYWHh7e3f4HnlxYO3atcjIyMDUqVOxefNmODo6dnJaAgAVFRXgcDg4cuQIQkND2Y5DCCGEkK6Nlhvqac6ePftcU9ZFIhFNrX4J2traOHnyJB49eoQVK1awHYcQQgghCsre3h7Lli1DTEwMSkpKsHfvXhgYGODLL7+ElZUVXF1dsX79eiQkJLAdVSGpqKjg4MGDeO+999otx9mWRCJBSUlJJyfrOu7du4cxY8agvr4ea9aseerfZTIZeDwevLy8MGPGDLi5uSEtLQ3h4eFUIGARn8+HsrIygoOD2Y5CCCGEEAVARYIe5sSJE385CkpJSQn+/v5ITU3FW2+91YnJuh9HR0eEhYVh9+7dNMWXEEIIIS/N2NgYs2bNQnh4OAQCAWJiYhAUFIRffvkFgwcPhp2dHRYtWgQej4eWlha24yoMZWVl/Prrr1iwYMEzCwUFBQWdnKprSE9PR1BQEBobGyGTyRAbG4tr164B+F9xYPDgwZg0aRIcHR2RkpKC8PBwODk5sZyc8Hg8jB49Grq6umxHIYQQQogCoCJBD9La2oo//vijw5kEampq0NLSws8//4zz58/T1PVXZOLEifj444/x4YcfIiUlhe04hBBCCOkmNDU1ERQUhB9//BEFBQWIj4/H7NmzkZCQgAkTJoDD4WD69OkICwuDSCRiO26Xp6SkhD179mDhwoVPFQqUlJSQn5/PUjL2ZGVlYcSIEaipqWGuZaaqqop169YhNjYWQ4YMwcSJE2FhYYGEhASEh4ejf//+LKcmANDc3Izo6GhwuVy2oxBCCCFEQdA1CXqQ8+fPY+zYsU+9rqysjBEjRiAsLAx9+vRhIVn31traioCAAAgEAty9e5dG8xBCCCHktcrNzUV0dDR4PB7Onz8PqVQKHx8fcLlcTJky5YWXgGloaEBqamq3vmaVTCbDkiVLsHfvXuYaBerq6ti0aRM+/fRTltN1noKCAgwbNgwCgaDDa5kpKSlh8uTJWL9+Pdzc3FhISP6K/LwvLy+Pzu8IIYQQ8jzomgQ9SVRUFNTV1ZnnampqUFdXx5YtW3Dx4kVqQL4mampqiIiIQG1tLRYsWMB2HEIIIYR0c7a2tli4cCF4PB7Kyspw9OhR2NvbY+vWrXBycoKrqytWr16NuLg4/JPxQjExMRg+fDi+//77f/R1ikRJSQk//fQTFi1a1G5GQU9abqioqAh+fn7PLBCoqqpiwIABiIyMpAJBF3X27Fm4ubnR+R0hhBBCnhsVCXoImUyGyMhIZn1aZWVlDBo0CMnJyVi1atUz118lrwaHw8Hhw4cRGRmJHTt2sB2HEEIIIT2EgYEBQkNDERYWhoqKCly7dg1BQUE4cuQIRowYAQ6Hg1mzZoHH46G5ufkvv1dUVBQkEglWrFiBcePGoby8vJM+ReeSFwrmz58PZWVltLS0IC8vj+1YnUIoFGL06NEoKSnpsEAAAGKxGMnJybh06VInpyPP68yZMxg/fjzbMQghhBCiQGi5oR7i7t27GDp0KJSVlaGqqoqtW7fiX//6FxUHOtnmzZuxYcMGXLx4EX5+fmzHIYQQQkgPlpKSAj6fDx6Phxs3bqBXr14ICAgAl8vFxIkTYWZmxrxXKpXCxMQElZWVAP6cKamrq4sjR47gjTfeYOsjvFYymQyLFy/G3r174erqiocPH7Id6bWqrq7GyJEjkZ6e/rcXvlZVVYWXlxdu3brVSenI88rOzoaDgwMuX76MUaNGsR2HEEIIIYqhhooEPcSaNWuwefNmeHp64vDhw3RRMZZIpVJMmDABDx48QEJCAkxNTdmORAghhBACgUCAc+fOISIiAjExMRCLxcx1DCZMmIDKysqnBjioqKhAKpVi6dKl2L59O9TU1FhK//rIr1EQHh7ebWdOAEBNTQ38/f3x8OHDZ84g6Eh0dDTGjBnzGpORf+rHH3/E2rVrUV5e3i23SUIIIYS8FlQk6AwymQzV1dUQi8Wora1FU1MTGhsbAQC1tbUQi8VPfU11dXWHa71qa2u3u66AnJ6eHpSVlaGiogJdXV2oq6tDW1sbWlpa0NDQgKenJ6ZNm4aVK1dCVVX11X9I8twqKysxZMgQWFpa4sKFC9R4Jx2qqqpCS0sL6uvrUV9fj5aWFkgkEtTU1Dz13rq6ug5P6OX7hbY0NTXRq1cvAH8uQaGmpobevXsz+wpCyPOpqamBRCJBQ0MDmpub0dzcjIaGBgB45rYKgGkLPEvv3r2feVzQ0dFhjuG9evWCpqYmc7yXH/8JeRVqampw/vx5REVF4ezZs6isrISRkRFqamo6PN6oqKhg0KBBiIiIgJ2dHQuJXz15e72hoQFNTU1Yu3YtPvzwQ2hqaqKqquqp98vb+x151jG27evyY7aBgUGnb8/19fUICgpCfHz8U+cl8lnIEokEEokEwJ9/b3Nzczg6OiI0NBSLFy/utKzk740dOxa6uroIDw9nOwohhBBCFAcVCf6ORCKBUChkbpWVlaiuroZIJOrwvrq6GnV1dUynnkgkglQqZftjMMUFfX19aGhoQF9fH3p6esy9gYEB9PX1271uaGgIc3NzmJiYMJ2K5NVIS0uDj48Ppk6digMHDrAdh7wG5eXlKCsrg0AgQEVFBaqqqtrdqqur2z1vampCfX39Mzv8O4u+vj7U1NSgo6MDHR0dZt9gYGDw1E1fXx8mJiawsLCAqakpFbxIlyWRSFBRUYGKigpUVlZCJBKhrq4O1dXVqK2tRV1dHWpra1FbW8scx+W36urqdp3+HXUOdjUGBgYA/ldU0NPTQ+/evaGjo4PevXtDX1+fedy7d2/o6uoy79HT04ORkREMDQ1hZGREAwsIxGIxrl27hsmTJ0MkEj3zfWpqalBXV8eBAwcwffr0Tkz4tLZt96qqqnbt9bY3edtdJBKhpaWFKYLU1dWxml9OXsiXF/jl2+qzbgYGBtDT04OxsTHMzMxgbGz8twMAmpqaEBISggsXLrR7XUdHB7a2tujfvz8cHBxgb2/P3KytrWnf0EU1NjbCyMgIP/30E95//3224xBCCCFEcfTcIkFLSwsKCwtRWFiIvLw8FBUVoaysDEKhEKWlpcxjoVD4VCe/rq7uUx3qbR/LT7rV1NSgp6cHFRUV6OvrQ1VVFTo6OsyoP+B/IwGf9KyRhB0VHaRSKXPSJh+hKB/RKB/hKJ+xIBKJ0NTU9NSJkbzTUv78yVFEvXv3hrm5OUxNTWFiYsI85nA4sLa2ho2NDaytraGnp/dSf5eeJCoqClOmTMGuXbtoBJYCaWpqQl5eHnJzc5l9R2lpKUpKSlBWVobi4mIIBIKn1vJt29HeUad7r169oKWlxWz7zxrlr6+vDyUlpXbfu6P9SNv9QlvyIoR8xOOTsxWqq6vR2trKdJh2VNCQ354sZpiamsLU1BTm5ubgcDgwMzODpaUl+vTpAxsbG9ja2sLIyOhV/BlID9fU1NRueysqKkJ5eTlTBGhbEBAKhR1uC0pKSs/sLNfW1mY61eXbnLzjXVdXFyoqKkzxXd55J99e5TqaySPX0XYs96wixJOjlOXbrHy0s7xjs+22L5+VWFVV1a7wIRKJUFNTwxQma2pqnjmoQV40MDY2ZgoH8iKCsbExLC0tYWpqCgsLC3A4nA7bNETxZWVlwdHR8W/fp6ysDKlUinfffRd79+6FlpbWK8vQ2NiIgoICpv1eWFgIgUDAFOXbtt3lI97ltLS0mLZ621vbNryGhka7drp825Yfg9u2zdvO6mnrWa/LZx49qe12V11dDalU2q4wKd+u5e362tradgWOJ4seHe0/9PT0wOFwYGJiAmNjY3A4HJiamsLMzAzW1ta4du0aBAIBXFxc2hUC9PX1X+jvRNjF5/MxYcIEFBYWwsLCgu04hBBCCFEc3bdI0NraitzcXGRkZCArKwu5ubkoLCxEQUEB8vPzUVpayizno6GhAXNzc2bUvJmZGdOYbvvYxMQERkZGzzyx707q6upQUVGBkpISCIVCCASCDh8XFxe367TQ1dVligZWVlawtrZG37594ejoCEdHR1oK4QlfffUVvvrqK5w/fx6jR49mOw75/wQCAdLS0vDo0SPk5OQwBYG8vDyUlJQw79PR0YG1tTXMzMyY0fSWlpYwMzNjOspNTU1hbGzcLfcbdXV1zP6gbYdtcXExysrKUFJSwtzk+9vevXvDxsYGdnZ2TOHAyckJzs7OsLOzo5GJBGVlZcz2VlBQwBTx2/6/erIjzMjIiDlGt+3ElnduP/mavBBA2mtoaIBIJGpXZKmoqGAKME8WYcrLyyEUCtt9D319fZibmzNFQvl+Ud42sLGxAYfDYekTkhe1fft2fPbZZx0ukdkRVVVVODg44Pjx4xgwYMBzfY1IJEJWVhaysrKQnZ3NtNvlhYG21wPQ1NSEhYUFzMzMYGJiwgxckbfX2z42NDTsUTPdRCIRBAIBUzB5soBSWloKoVCIkpIS5iLUwJ8DDqytrWFlZQUrKyv06dMHffr0YdrxlpaW3bIt090sWbIEt2/fRnx8PNtRCCGEEKJYFL9IUFpaiocPHyIzMxOZmZlIT09HZmYmcnNzmVGuHA4Htra2TKe1fNS7/DmHw6FG70uora1Ffn4+8vPzmRM6eeeO/LH8b2FmZgYnJyc4OTkxhQNnZ2c4Ojr2yM5BmUyGmTNnIjY2Frdv34aDgwPbkXqU3NxcJCcn49GjR0hPT2cKA/KTZl1dXdjb28PW1rZdx7b8ZmhoyPInUAzNzc1Mp2/bm7wAU1hYCABQV1eHo6Mj+vfvj/79+8PZ2RnOzs4YMGBAh9diIYqpvLwcGRkZyMnJQX5+frv/E7m5ucw1e5SVlWFubt6u8CbvfJZ3Dso7oel6GuxpaWlhZnO0LQ62nWFVWFiI0tJSZiS1pqZmu32p/GZnZwcnJyeYmJiw/KnIk4YPH45bt251eL2sv9KrVy/8/PPPmDVrFoA/ZwGlpqYyg3iysrKQmZmJrKwsCAQCAH8WGPr06cN0VLfttLaysmK2e/LyGhoakJ+fj6KiIhQWFjJt+aKiIma/LL+GSq9evdC3b992N0dHR7i6utLfowtxcHDAO++8g40bN7IdhRBCCCGKRXGKBK2trcjIyEBCQgJSU1ORkpKChIQEZlSvgYFBuymy9vb2cHFxgbu7O41eZ5lYLEZ+fj6ys7OZW0pKClJTU5GXlweJRAI1NTXmRMPFxQVeXl4YPHgwzM3N2Y7/2jU2NmLEiBFobGzEzZs36f/ra1JcXIyEhATmdufOHaZDwsDAAC4uLnB1dWX2Ha6urrCzs6MCYidobm5GVlYWUlNT2+0f0tLS0NDQAFVVVTg5OcHLywteXl5wdXWFp6cnFWm6MPmSfvK/Zdt9v/y4raamBmNjY1hYWDx1/DY3N4ednd0rXaqEsKu1tZUZvdy2PZCdnY3i4mLk5eWhvr4ewJ+zEdqugS7fJzs5OUFHR4flT9LzVFRUwMzM7KnlcuTLbOno6DBL88ivfWVoaAiZTIba2lo0NjZCR0cHOTk5SE9Ph0QiYQoBT2778r83XQur66iqquqwDZ+Zmclcq6VtO0rejh80aFC7JdjI6/fo0SM4Ozvjxo0bGDZsGNtxCCGEEKJYumaRQCKRICUlBTdv3sStW7dw584d5qRCS0sLLi4uGDhwINzc3ODu7g43NzcYGxuzHZu8gObmZqSlpSEpKQnJycl48OABkpOTUVpaCuDPWSCDBw+Gt7c3hg0bhiFDhnTLTvS8vDwMHToUvr6+iIyMpI7plyQSiXD9+nVcv34d165dQ2JiIurr66GmpgZXV1d4eHjAw8MDnp6ecHd3p06nLkosFiMzMxP37t1jbomJiaiqqoKysjKcnJwwfPhwjBgxAr6+vs+1XjZ5tSQSCTIzM5GUlIT79+8jKSkJDx8+RH5+PmQyGVRUVGBjYwMnJyf069ePmUnm5OQEKyurZ67ZT3oeqVSKoqIiZGRkICMjA5mZmXj06BEzO1QsFkNJSQnW1tZwdXXFwIEDMXDgQLi7u8PJyalHzkbsLLW1tSgpKYG6ujr09PSYgkBbmZmZuH37Nu7cuYM7d+4gKSkJjY2NUFZWhp2dHdzd3eHq6go3Nze4ubmhb9++PWoJoO6quLgYKSkpSE5OxsOHD5GcnIzU1FQ0NDQwf/uhQ4cyN09PT7puyWu0Y8cOrFu3DuXl5VBRUWE7DiGEEEIUS9coEohEIly9epUpCty9exd1dXXQ0dHBkCFD4OPjAw8PD7i7u8PBwYEaPT2AUCjEgwcPkJSUhDt37uDmzZvIz8+HsrIyXFxc4OPjAx8fH4wcObLbdAxev34dAQEB+OKLL7B27Vq24ygUoVCICxcuIC4uDteuXcPDhw8hlUrRv39/+Pr6YtiwYfDw8KBla7qJ3Nxc3Lt3D/Hx8YiLi8Pdu3fR2NgIDocDX19fjBgxAv7+/nB3d6eC2yvU1NSEhIQE3Lt3jykKpKSkMLM9+vXr167Ttl+/fujbty9tc+SltbS0IDs7G+np6UhPT2cGFTx69Aitra3Q1NSEq6srBg0aBHd3d3h4eMDLy4tmorwmtbW1iIuLw+3bt5nCQGVlJdTU1DBo0CB4e3vDw8MDbm5ucHFxoet/9DBSqRTZ2dlISkpi2vF37txBRUUF1NTUMHDgQAwdOhTe3t4YMWIE7Ozs2I7cbXC5XGhoaOD48eNsRyGEEEKI4mGnSCAWi/HgwQPExsYiNjYWV69eRUtLC+zt7eHr68ssKeHt7U2jjAijtLQUd+/eZZaLiYuLQ3V1NTgcDkaMGIGgoCCMGzcO1tbWbEd9Yb/++ivmzZuHY8eOYfr06WzH6bIkEgnu37+P2NhY8Hg83Lx5E0pKSujXrx/8/PwQFBQEf39/Wte6h5AfU+Li4nD9+nVcunQJ5eXlMDU1xahRoxASEgIulwsDAwO2oyoU+RJd169fR1xcHBISEtDU1AQ9PT0MGDCg3bISnp6e1CFLOp18Kcq2y1DGx8ejtLQUKioq6NevH7y8vODn5wdfX1+4uLhQ4fAFNDY2MvuCtu12c3Pzdr9fLy8vWiaIPNOTx5TExEQ0NjbC3NycabsFBwfDxsaG7agKqaWlBUZGRti+fTsWLVrEdhxCCCGEKJ7OKxLk5eXh5MmTOHPmDOLi4tDY2Ii+ffsiMDAQgYGBGD16NC0ZRP6R1tZW3L59GxcuXMCFCxdw69YttLa2YsCAAXjjjTcwefJkDB8+XOGWs1i8eDF+//133LhxA25ubmzH6TIaGhrA5/MRGRmJmJgYVFVVwdbWFmPHjsXYsWMRGBhIa98SAH9eEDwxMRHnzp3DuXPnmItt+vj4gMvlYsaMGdQJ8QSZTIaHDx8iJiYGV65cwe3bt1FWVsaMDJbP3vLx8YG9vT3bcQn5S3l5eczs1Fu3buHevXtoaWmBiYkJMwsxKCgIAwcOpKLBM6SlpeHUqVM4f/48bt26hebmZjg6OiIgIACjR4+Gv78/zMzM2I5JFFhzczNu376Nixcv4uLFi7h9+zZaWlrQr18/BAYGYsKECRg9ejTNRntOV65cgb+/Px4/fkzHaUIIIYS8iNdbJMjIyMCJEycQGRmJhIQE6OnpYezYsQgKCkJgYCBsbW1f148mPVBdXR2uXr2KCxcu4MyZM3j06BE4HA4mTZqEKVOmwN/fXyFmprS2tiI4OBg5OTm4c+dOjx4N39LSgujoaBw7dgxRUVFobGzE6NGj8eabb2Ls2LHo378/2xGJAqiqqkJsbCzOnTuHqKgoVFZWYtiwYZgxYwZCQ0PB4XDYjsiK4uJixMTEMLP6SktLYWRkhFGjRmH48OHw9vamkcGkW2hubkZCQgJu376NGzdu4MqVKxAKhTA1NUVgYCDGjBmDoKAghZ6J+LKkUinu3LmDU6dO4dSpU0hPT4epqSnGjx+P0aNHIyAgAFZWVmzHJN1YQ0MDrl+/josXLyI6OhqJiYnQ09PD+PHjMWnSJIwbN46uIfUX1qxZg2PHjiErK4vtKIQQQghRTK++SCAQCHDo0CGEhYXh4cOHMDExwcSJEzFlyhQEBgbSaBDSaVJTU3HixAmcOHEC9+7dg6GhIaZOnYr58+dj6NChbMf7SxUVFfD29oaFhQViY2N73HaTlpaGn376CUePHkVVVRV8fX2ZDl1TU1O24xEF1traipiYGKbwVF9fj4CAACxevBgTJkzo9te8SUhIwPHjx3H69GmkpqZCQ0MDvr6+CAoKwpgxY+Dp6alws68I+aekUimzZF1MTAzi4uLQ1NSE/v37g8vlIjQ0FIMHD+4RswySkpJw4MABhIeHo6SkBA4ODpg8eTImTpyokLMxSfeRl5eHqKgonDp1CteuXYOKigrGjBmDOXPmgMvl9ri28d+RF/Z3797NdhRCCCGEKKZXUySQSqWIjY3F/v37ERUVBS0tLbz99tsIDQ3FiBEjun2nC+n6cnJyEBkZiUOHDuHhw4cYOHAgFixYgHfeeQf6+vpsx+vQgwcP4Ovrizlz5mDXrl1sx3ntJBIJ+Hw+du3ahQsXLqBv375YsGABZsyY0aNHd5LXp6mpCX/88QcOHjyIM2fOwMrKCosXL8b8+fO71fJ3d+/exfHjx3H8+HFkZ2fD1tYWkydPxhtvvIGRI0fStQRIj9fY2Ii4uDjExMQgMjIS2dnZsLGxwbRp0zBt2jR4e3t3q4JBdXU1jh49igMHDiA+Ph59+/bFe++9h8mTJ9Myh6RLqqioAJ/Px7FjxxAdHQ0jIyO8++67mDdvHlxdXdmOx7qqqiqYmJggIiICkydPZjsOIYQQQhTTyxUJmpubsX//fnz77bfIycmBn58fFixYgNDQUFqegHRZN2/exC+//ILw8HDIZDK89957WL16dZdc/urEiRMIDQ3Fd999h2XLlrEd57UQi8X49ddfsWXLFuTn52Ps2LH46KOPEBwcTCMYSafJzs7G7t278X//939oamrCnDlz8OWXX8LCwoLtaC+kpKQE+/btw8GDB5Gbmwt7e3umw7OnjJAm5EUlJiYyhbXMzExYW1tj9uzZWLRokUIvuZOZmYlt27bh6NGjUFJSwrRp0zB37lyMHDmS9glEYRQUFODgwYM4ePAgsrOz4ePjg1WrVmHixIk99v9xREQEZs6cCaFQCAMDA7bjEEIIIUQxvViRQF4c2LZtG8rLyzF//nx8+OGHcHZ2fh0hCXktampqcPjwYWzfvh2FhYWYPXs2Pv/88y5XLKZXuJoAACAASURBVPjmm2/w2Wef4cSJE5g4cSLbcV4ZmUyGEydOYM2aNcjOzsaCBQvwr3/9C3379mU7GunB6uvr8fvvv2PLli0oLy/HsmXLsHLlyi474+hJV65cwe7du3Hy5Eno6+vj/fffx1tvvQVPT0+2oxGikB48eID//ve/+PXXX1FeXo4JEybgww8/REBAgMJ0SKampmLz5s3473//CwcHByxfvhwzZsyAnp4e29EIeWEymQyXLl3Crl27cOrUKQwYMABffPEFQkNDe9wgk4ULF+Lhw4e4ceMG21EIIYQQorhq/nEL6vfff0ffvn3x73//G1OmTMHjx4+xc+dOKhAQhaOrq4vFixfj0aNH2LNnDy5cuAAnJycsWbIEIpGI7XiMlStXYtGiRXj77bdx584dtuO8EsnJyRg2bBhCQ0Ph4eGB1NRU7Nq1iwoEhHXa2tpYtGgR0tPTsXHjRuzbtw8ODg74+eef8Yov4fPKyGQyHDt2DG5ubvD390d+fj4OHDiAgoICfP3111QgIOQlDBw4EFu2bEFeXh5+++03CAQCBAUFwcXFBWFhYZBKpWxHfKbCwkK89dZbcHNzQ1JSEn777TekpqZi0aJFVCAgCk9JSQkBAQE4ceIEkpKSMGDAALzzzjtwdXUFn89nO16niomJwZgxY9iOQQghhBAF99xFgsLCQoSEhGD27Nngcrl4/PgxfvzxR4VdioEQOTU1NcydOxfp6enYu3cvTpw40eVOMHbs2AE/Pz9MmjQJ+fn5bMd5YTKZDN999x2GDh0KVVVVxMfH48iRI3BwcGA7GiHtaGpqYsWKFXj8+DHmz5+Pjz76CFwuF2VlZWxHa+fSpUsYOnQo3nnnHXh4eCAhIQE3b97Eu+++Cw0NDbbjEdJtqKurY8aMGbh27RpzzaB58+bBy8sL0dHRbMdrRyqVYteuXXBxccH9+/cRERGBBw8eYObMmXSdMNItDRgwAEeOHEFqaio8PDzA5XLx1ltvobS0lO1or112djZyc3MRGBjIdhRCCCGEKLjnKhIcOHAAAwYMQFZWFq5evYrdu3dTcYB0O6qqqnj//feRkpKCgIAAcLlcvPfee6ipqWE7GlRVVXH8+HGYmJhg/PjxXWqmw/MqKyvDmDFjsHr1anz55Ze4cuUKjXAmXZ6enh6+/vprXL16FWlpaXB3d8fZs2fZjoXMzEy8+eabCAgIgImJCe7fv4+wsDDapgjpBO7u7ti/fz+SkpJgY2OD4OBgBAcHIy0tje1oyMjIgJ+fH5YvX46PP/4YDx48wJQpU3rc8iukZ3JycsKRI0dw7tw53L17l5nx051dunQJvXr1gre3N9tRCCGEEKLg/vKMQSKR4OOPP8b8+fOxaNEi3L9/H76+vp2VjRBWGBoaIiwsDH/88QcuXLgAX19f5OXlsR0LOjo6OH36NCoqKvD2229DLBazHem5PX78GMOHD0d+fj5u3ryJzz//nEYzEoUyfPhw3L9/H8HBwZgwYQIOHDjAWpb9+/fDw8MDRUVFiI2NxZkzZ+Dm5sZaHkJ6KmdnZ5w6dQpXr15FZWUlvLy8sHv3btbynD9/Ht7e3mhtbUVCQgI2bdoETU1N1vIQwpbg4GAkJydjzpw5mDNnDpYuXQqJRMJ2rNfi8uXLGD58OM0eJIQQQshLe+aFi2UyGebPn4+jR48iLCwM06ZN6+xsT/n999/bPVdVVYWenh4MDQ3h5uYGLS0t5t+EQiHOnz/PPB8zZgzMzMzafX1zczNOnDjBNBqVlZUxduxYGBoaorm5GYcOHcKDBw9gaWkJPz8/DB06FDExMeByuU9l4/P5qK6ubvfauHHjYGRkxDxPTExEamoq87xXr15obGxknispKcHU1BR2dnawsbGBmppah7+Ha9eu/W2ntbu7O9zd3f/yPQBQVVUFX19frFq1CrNnz4ZYLEZUVBT27NkDLpeLZcuW/e336M7ky2yJRCJcvXoV1tbWbEfC3bt34e/vj3fffRd79+5lO87fKi0txbBhw2BkZISzZ8/CxMSEtSxt9yFKSkrQ0NCArq4uBgwY0Omzo3rqtiYQCHDw4EHcvn0bzc3NePfdd7Fx40ZmH6QI1q5di82bN+Pw4cOYMWNGp/1cqVSKTz75BLt27cLKlSuxYcMGqKurd9rPf150rO6YWCxGfHw8Ll++jMePH6NPnz4YP348PD09ER0djeDg4Of6Pi/qt99+w8yZM6Gqqvpaf05PJRaLsWnTJmzatAnz5s3DTz/91Km/az6fj6lTp+Ktt97Cvn37ukRxoCvvCzpSVFSEiIgIZGZmwsjICP7+/hg2bBjy8/MhkUjg4uLyor+Kf+TJtjl5OcePH8fs2bMxefJkHDp0qNsNUrGxscGCBQuwZs0atqMQQgghRLHVQPYMmzZtkqmrq8v++OOPZ72l0507d06mpKQk09fXl61du1b266+/yjZv3iybNGmSTFNTUzZu3DhZWloa8/6ysjLZwoULZQBkPj4+sqampqe+Z1VVlWzWrFmy4cOHywoKCpjXXFxcZPPmzZPdvn1bFh0dLXv77bdlKioqsn/9618dZquurpYtWbJEBkDWu3dvWXJy8lPvaWxslK1evVqmrKwsCw8Pl4nFYtmZM2dkAGTGxsay//znP7L169fLnJ2dZRwOR3b+/PkOf5ZUKpVduHBBBkBmY2MjO3nypOzkyZOyiIgI2Q8//CBzcnKSrVq16rl+pzU1NTI/Pz/Z8ePHZTKZTJaTkyPbsWOHDIDsP//5z3N9j+6uvLxc5ubmJnN3d5c1NDSwHUcmk8lkfD5fpqqqKlu/fj3bUf6SWCyW+fn5yZycnGRCoZDtOMw+xNjYWLZjxw7Z999/L/Py8pIpKyv/P/buOy6K4/8f+ItyFOlVmgpIxwaoqNhFDdEoKNiiGBvWGDVGE/1EjZrEVBuJBRuWoILYSCwgVhQLoChKUVGQrvQOx/v3h7/bLydVBZYyz8fjHsLe3u378GZmd96zM7R06dIm/f9ti2WtoKCAHBwcKCkpicrLy2ns2LEEgHr37s3VQS3FsmXLSFZWliIjI5vsmIsWLSJZWVn6559/muyYH4K11VX99ttvpKWlRX/88QeFh4dTfn4+3b9/n2bNmkUqKir09ddf1/fPy6nu71STwsJCUldXpxMnTrz3cZj3c/78eVJSUqLJkydTRUVFkxwzPDyc5OTkaM6cOU12zPpoznXBu3766ScyMDCgTZs20f379+n169d0/vx5GjRoEGlpadHJkycb5o9SD++em9fH+9QHbVFgYCDJy8vTN998w3coDSouLo4A0I0bN/gOhWEYhmGYli+n2iRBREQESUtL05YtW5o6oDqpq6uTubl5le1BQUGko6NDcnJyFBoaKvacubk5AaAvvvii2vc8fPgw/e9//+N+X7x4MVlaWla50FqwYEGtFxuFhYXUvn17kpaWpszMzGr32bJlC3355Zdi25SVlcna2pr7/c2bN2RiYkISEhIUERFR4/Hk5eWpW7duVbYnJyfT0qVLa3xdXV6/ft2mOi7rIz4+ntTU1D6oI6exeHl5EQD666+/+A6lRtu2bWvyjtS6qKurk6Wlpdi2KVOmEAD64YcfmjSWtlbWjhw5QgYGBtzvRUVFFBISwmNEH668vJwcHByoV69eTdIpt337dpKWlqYzZ840+rEaAmur/8+SJUtIWVmZrl+/Xu3zy5cvJ3d39xpfX5Ovv/6ahEJhvfbds2cPAaChQ4e+93GY93fx4kUSCAT0yy+/NPqxSkpKyMzMjBwdHam8vLzRj/e+mnNdILJ582YSCATVdrQWFRWRvb097du3r8734dP71Adt1YEDB0hCQoKCg4P5DqXB7N69m9q1a0clJSV8h8IwDMMwTMuXU+2aBGvXroWtrS0WL17cmLcxfJCaplYYNmwY9u7di+LiYowfPx4lJSXccwoKCujbty8OHDiALVu2VPueioqK3O93796FrKwsJCQkxPZbuXJllW2VycvLY/78+SgvL4e/v3+1+5w5cwbffPNNleNXfl91dXVMnDgRRISjR4/WeLyabiXX1dXFwoULa3xdXdhUBFUZGhpiw4YN+Ouvv5CcnMx3OACA2bNnY+3atVi8eDFOnTrFdzhVlJeXY9OmTVi4cGGzmi+9ujpk1qxZAFBreWsMba2sRUREiNVbcnJy6NevH48RfTgpKSl4enri3r17OH/+fKMeKy0tDatWrcKqVavqPW0G31hb/da5c+ewZcsWLFu2DP379692nw+ZIuLhw4fYuXNnvfffvXs3Bg0ahODg4GaxuG5rN3z4cKxfvx7r1q1DQkJCox5r3759SEhIwL59+5rlNCrNuS4AAB8fHyxduhQbNmyodt01OTk5bN++HZmZmbW+D5/etz5oq6ZPnw4nJyd89913fIfSYK5cuQIHB4dmOfUgwzAMwzAtT5UkQWZmJs6dO4dly5bVeWLd3Hz66acYNmwYN6doZf7+/jAwMMDy5csRFBRU6/tYWlri/v37+PLLL1FaWspt79ixIz755JNaXztv3jzIyspi+/btVZ6Ljo6GsrJyvea1V1ZWBvB2Tvz3cefOHVRUVKBz587ctri4OGzduhU//PADzp07J7Z/cXExDh06hIsXL3Lb3v1/P3bsGHx8fODn58dt8/Pzg4+Pj1jn9LNnz/D9999DKBQiICAAv/76K8rKygAAubm58PLywrJly+Dp6Yn8/HyxY9y4cQOrV6/Gzp07sXv37vf6zE1l9uzZkJWVxYkTJ/gOhbNu3TrMnTsXU6ZMwc2bN/kOR0xISAiSk5Mxf/58vkOpk6i8GRkZVXnuY767JSUluHjxIlavXo2//voLz549E3v+3bL277//wsfHBz4+Pjh69CjXaRIeHs5tz83NrTOu2spidUT1wLfffovTp0+Lzb9en8/x9OlT/O9//0NFRQXi4uLw448/wsvLiztmSkoKfHx8EBISgoKCAu6zVD525ToIAAoLC7Fr1y5s2LABfn5+yMrKglAoBFW/jA4vevToAQcHhyrtTUM7ePAgBAJBq+nYaEtt9fbt2yEhIYEFCxbU+B4qKirYtGmT2LbaylxISAhGjx6NgoICHD16tM7v37Vr12BpaYnvv/8eAPDXX3/VuG9dZVmkunrvzJkzXNm+ffs23rx5w/3u4+OD4OBgAEBiYiK3LSkpCUDD1mfNxddffw1VVVXs37+/UY9z6NAhTJo0qVmsmfS+mkNdsHHjRi6WmvTq1QsDBgzgfv/YNlGkpvOHmtrF6vavrT6orVzVN8aazg9Onz4tdr4iEhUVxW1/8+ZNjX9TvqxYsQK3b99GTEwM36E0iKtXr2Lw4MF8h8EwDMMwTGvx7r0Fly9fJgCUlpbW5Pc11IeOjk61ty2L/O9//yMANHPmTG6bra0tERHdu3eP5OXlSV1dnZ4+fco9f/z4cdq0aRP3e1xcHGlqahIAMjMzo3Pnzr1XjNOnTycAdPnyZbHtS5YsofPnz1fZX1NTk7p06SK2rUePHgSg1tub1dTUxKYbKisro9GjR1NpaSm37csvv6QBAwbQ69ev6eLFiyQhIcF91idPnpCzszMBELslPicnR2wKlNzcXHJwcCBlZWVun+TkZOratSvp6OgQEZG3tzfp6OgQADpw4ADZ2NgQAAoJCaHY2Fj67LPP6MKFC3T//n3q0qULde7cmbKysoiIaMWKFXTkyBEqKCggHx8fUlRUrPXvy6dPP/2Upk+fzncYYsrLy8nZ2Zk0NTUpOjqa73A4W7Zs4b4fzYmOjo7YdENCoZBcXFwIQJU5hz/mu1tUVESDBw+mo0ePUlZWFm3fvp2UlJTE5gR/t6ylpKSQnZ1dlfllKyoq6NNPPyUfH58646qtLFbnxYsXNGDAAPLy8qLExEQaNmwYGRsbU1FRUb0+x4EDB6h9+/YEgM6cOUPjxo2jUaNGEQD6/vvviYgoPT2dTp8+Tf379yd9fX06ffo0nT59usY6KCMjgzp37kze3t5UWlpKK1asIABkaGhI/fv3f8//8cb17bffko2NTaMeY+zYsTR58uRGPUZDY2312zZZSUmJ9PT03iuuusrc9evX6fPPPycAFBAQUOeaCK6urhQWFkZERJaWlqSkpES5ublV9qtPWSaqud57/PgxaWpqkra2NuXn5xPR2yllpKWlycHBgas3hUIhLVq0iJYuXUplZWUNWp81N7Nnz6Zhw4Y12vtXVFSQrKwsHTx4sNGO8bGac10gms9dWlq63tO1NESbSFRzOaqpXaxp/5rqg9rKVX1jrO384MmTJ6Srq0sAKC4ujnuNUCikYcOGkaenZ7NaH0OkvLycZGVl6fDhw3yH8tFiYmIIAN28eZPvUBiGYRiGaR2qrklw+vRpAtBsF8Cq62Lj4MGDBICGDx/ObRNdbBAR/fPPPwSArK2tuYvkdy82iIgiIyOpW7duBIAAkJOTE8XGxtYrxvDwcAJAzs7O3LbCwkLq2bNntSfMmpqa1KlTJ7p79y7duHGDJk2axM3FWtsJtpqaGikoKNDAgQNp4MCB3AVS5SSBiooKbdy4kfvdysqK+vTpw/2elJRUZ5KA6O2CmZWTBERvL34rdwKvXr2au5AnIoqOjqaKigoaPny4WOfruXPnuAuR0tJS0tDQoJiYGO75r776qsbPzLcpU6bQ2LFj+Q6jivz8fOrduzcZGxtTcnIy3+EQEdGGDRvIzMyM7zCq0NHRIX19fTpw4ABt2LCBrKysyN7ennx9favs+zHf3SlTptCMGTPE3s/V1ZXk5eW5xRarK2uBgYEEgI4cOcJtKykpoXHjxtUrLqKay2J1hg8fTh4eHtzvAQEBJCEhQf7+/vX+HKJO/NOnT3P7DBkypMr//8SJE6vU39XVQaI53MvKyoiIKDExkQDQqlWrqv0MfPr555/J2Ni4UY8xYMAAWrRoUaMeo6GxtpooNDSUAFCvXr2qPf6tW7do4cKFNGTIEBoyZAgtWrSIXr9+Xa8y98MPPxCAOjvhEhISaPDgwdzv27dvr3Utm7rKcl313i+//EKSkpJi7ZCrqyt16tRJbL708ePHcwvFN2R91tw0dhKxsLCQ6+htrppzXSBqby0sLOr9eRqiTayrHL3bLta1f3X1QV3lqj7tdl3nB0eOHCEAYonK0tJS6tmzZ7NcH0NES0uLPD09+Q7jo+3cuZMUFRXFrvsYhmEYhmE+QtU1CfT09AAAL168qP0WhGaqoKAAAKClpVXt85MnT8a3336LqKgoTJ06tcapK7p27YqwsDBs3boVampqOHfuHLp3717l1t/q2NjYYMCAAThz5gzi4+MBvJ2yx83NrcYpnKSkpPDy5UvcvXsXI0aMwP3797F///46p3zq3Lkzrl69iqtXryIpKQkTJkwQe/7ff//lpnu5c+cOiEhsKpHKc7rWRlKy6vIV726Tl5cH8PZvDADm5uZITU1FYGAgbt68ie+++w7fffcd/v33X/Ts2ROFhYUQCARQUlKCo6MjNxXS6tWr6xUTH+Lj46Gvr893GFUoKCggICAAMjIyGDFiRLOYO1dHRwfJyckoLy/nO5QqBAIBTExMEBERgcePH2PNmjVwdXUV2yclJeWDv7uFhYXw9fWFjY2N2HvOnz8fRUVFtU4/4ejoCEtLS7H5hf39/eHm5lavuIDqy2J1dcnTp08RGBgIZ2dnbtuoUaOQmpoKFxeXen8OBQUFAOLTNXTp0qVe06VVVwfFxcVBUlKSi9nAwAAmJia4ceNGne/X1F6+fAldXd1GPUanTp0QHR3dqMdoam2hrRZN7REXF1dt/H369MGGDRtw+fJl3L17F9u2bYO8vPwH1x3V2bFjh9hUR9OnT4eioiL+/vvvavevqyzX1Wa7u7tDUlIShw8f5rapqanh5cuXCAwMBPB/ZUZeXr5B67Pm6MmTJzA0NGy095eXl4e6ujr3/W2J+KwL3nddoIZqE+sqR++2i+97rlyfclVXjHWdHwDAxIkTYWJigt9//53b5+TJk3B2dm6W62MAQE5ODt68eQMDAwO+Q/loovUIBAIB36EwDMMwDNNKVDk77tGjBzQ0NODv798i5z8WzTFpZWVV4z4//vgjHj16hDNnzmDNmjXo1q1btftJS0tj8eLF+Pzzz7Fs2TIcPHgQEydOxIsXL6CiolJrHF999RWuX78OT09P/PHHH9i/f3+tc9m3a9cO48ePr8cnrJmMjAwWLFgg1nnv4OCAkydPwt/fHyNHjoShoSE3BzBQfef/h6ruoj0uLg7A2zlANTU1q32dp6cnpk2bhk8//ZRbqK6mi0U+vXr1Cnfu3KmymGVzoaWlhaCgIPTv3x9OTk64dOlSvZNAjWHQoEHIz8/H1atXMWzYMN7iqI68vDwcHBxgbW2NsLAwfPHFF4iMjISOjg63z8d8d2/evImysrIqHRCmpqYAgNjY2FrjW7RoERYuXIjIyEh069YNJ0+exKFDh+odV3070EQLmL77PdHW1gaAen+O6uoRBQWFeiWIqntt//798e+//+LOnTvo27cvSkpKkJycjNGjR9fjUzUdoVCIc+fOYerUqY16HGdnZ0ycOBHPnj0TW2+mJWsLbbXos2VnZyMuLg5mZmZV9lFTU4OCggIMDAwgISHx0XVHZcXFxTh8+DAeP36MY8eOcds1NDQQFRWFK1euVJnLuj5lubY2W0dHB05OTvD29sY333yDtLQ0AG8TXV5eXhg5ciS8vb0xY8YMAA1bnzU3r169wvnz5xt9naXhw4fDz88PixcvbtTjNBY+6wJRuYqLi0NRURGXkKpJQ7aJtZWj6l7/PufK9SlXdcVY1/kB8DZpunLlSsyZMwd37txB7969sXfvXnh7e1d7zObA398f0tLSGDRoEN+hfLTr16/Xut4NwzAMwzDM+6pyhigtLQ0PDw/8+eefzWI08vsoLS1FQEAApKWluVEu1ZGUlMSRI0dgaWmJjRs3Vlks7ZdffhH7XUNDA97e3pg8eTKys7MREhJSZyzOzs7o1KkT9u7di+vXr6NDhw41nqg3pEGDBomN3lmxYgX27dsHLy8vTJ06FbKyso0eQ2UyMjIA3i68+q68vDwAb0cmPX36FEuWLEFYWBh69uzJXZw0J2vWrEGHDh1qXdyOb/r6+ggMDERCQgLGjh3LLXzLB1NTUwwcOBA///wzbzHURVVVFUeOHEFmZiamT58uNkLxY767QqEQAKosJi2qA6rrLKzM3d0dysrK8PT0xJMnT2BqasrFU5+46kvUIXLhwoUqz2VkZHz05/hQS5cuhaurK1asWIGgoCAsX74c/fr1w/r16xvleB/qyJEjSEpKwvTp0xv1OGPGjIGVlRXmzp3L/Z+0ZG2lrdbV1YW9vT0AIDQ0tMb9JCUluXa7Icucj48P5s6di1OnTsHPz497nDx5EkDtCxjXpq42e+bMmYiKisK9e/fg6emJxYsXY9asWThz5gxSU1Px4MED2NraAmjY+qw5qaiowLx589CpU6cqd3g2tEWLFuH69ev477//GvU4jYHvukBfXx/W1tYQCoV49OhRrbESUYOWz/c9932f/RuiXNV1fiDi7u4OfX19/Pjjj4iJiYGqqqrYgIvmpKCgAOvXr8e0adOgqqrKdzgfJT4+HklJSWILajMMwzAMw3ysaoeRr1ixAnJycpg5cyYqKiqaOqYP9ttvv3En0LWNSAIAZWVlnDlzBmpqalUuNq5fv47U1NQqrxk3bhyA+k3RIyUlhUWLFiEnJwcTJkzgpvypDhHVePt0XWp7XVhYGH777TcsXLgQcnJy9XpNTZSVlat0OFe+YKqJubk5pKSksHbtWpSWlnLbMzIycOTIERQUFMDLywvq6urYvHkzrly5gvz8fPj4+Lx3jI3pxIkTOHDgAH7//fcmT7S8LxMTE1y4cAERERGYNGkSr9P9/PTTT7h8+TK8vLx4i6EuDg4OWLNmDS5evCh2y/zHfHdtbGwgKytbpWNCdGFd10WdoqIipk+fjiNHjuC3336Dh4dHveN6H1ZWVpCUlMTZs2fFyvKzZ89w7969j/4cH0pCQgJ6enrYvHkzKioqsHDhQgQGBkJJSalRjvchkpOT8fXXX2POnDncKNLGIhAIsH//fty6dQvz589vUe1yddpSW71582YAb6cGqS7Wd71vmautDd61a5dY3VH5GH369MGpU6fqNSVYZfVps0eNGgVtbW38/fffiI+PR5cuXTBjxgwIhULMnDkTQ4cO5fZtyPqsuSAiLF26FEFBQdi/f7/Y+Vdj6N+/P6ZMmYKZM2e+9/8n35pDXfDDDz8AeHvtU/k7WFlGRgb279/fYG3i+5771nd/UX3QEOWqrvMDERkZGSxfvhxnz57FkiVLMG/evHq9f1MjIsydOxf5+fnNbsDBhwgJCYGMjAzs7Oz4DoVhGIZhmNakptUKrl+/TrKysjR37txms0BcaWkpSUlJVVkArbi4mJYsWUICgYC+++67Kosut2/fngoKCqp9z8DAQJKSkhJbAM3JyYmGDx9OeXl5Yvs6OztTt27dqKSkpF7xZmVlkYKCAnXt2rXGfUpKSkhSUpI6dOhQr/cUEQqFJCMjU+vrHj9+TABo7ty5VFZWRoGBgWRkZEQGBgYUGxtLz58/p5SUFAJAa9as4V4nWjBt3bp13DYvLy8CQBcvXqSKigo6evQoWVtbk4yMDGVnZ1N5eTmtW7eOAFRZOHfhwoUEgPr06UNHjhyh/fv30/Dhwyk7O5tyc3NJV1eXioqKuP3NzMxo27Zt7/X3aEyBgYEkJyfX4hYOvXnzJikoKJC7uzuvZXj16tUkIyNDQUFBvMUgUlZWRtLS0qSvry+2vby8nAYMGEBSUlIUEBDAbf+Y7+7y5csJAAUHB3PPb926ldzc3Lj/j+rKmkh0dDRJSEjQmDFjqjxXW1xEVGNZrM4XX3xBAMjFxYUuXbpEnp6eNHnyZC7G+nyOpUuXf/tZXQAAIABJREFUEgBuUUnR6yQkJMTq4xEjRogtdk5E1dZBGzZsoO7du5O/vz8FBwdTaGgoRUVFcQsZ8y0nJ4d69OhBFhYWVdqJxnTmzBmSlZUlNzc3btHX5oi11eL8/PxIRUWFevfuXe3/m5KSEllbW3O/16fM/f333wSAQkND6dq1a2L1EBHR6dOnacSIETXGtGnTJgJACxcuFNteV1mub5u9bNkyAkCXLl3itn366ackJydHWVlZYvs2ZH3Gt6KiIpo6dSoJBAI6fvx4kx03NzeXrK2tyczMjJKSkprsuHVpKXXBxo0bSUJCgtzd3Sk/P1/suZcvX9KyZcu4xWEbok2sqxy92y7WtX919UFd5ao+7XZd5wci+fn5pKmpWesC1XyqqKigL7/8kgQCgdgiyy3ZvHnzqG/fvnyHwTAMwzBM65JTY5KA6O1FpoyMDLm6utZ4st6Uxo8fTwBIWlqabGxsyMXFhcaPH0+jR4+mefPmUVhYmNj+4eHhNHv2bAJAbm5uFBgYWO37btmyRexi4/PPP6fx48eTjY0NzZgxg1atWkXW1tY0ePBgio+Pf6+Y58+fT3///Xe1z129epXGjRtHAAgAzZ8/n+7cuVPne165coUmTJhAAEhCQoK+/vrrGl83bdo0kpSUpPbt29POnTtp48aNJCkpScuXL6eEhASaP38+ASArKys6d+4cJScni207deoUEREVFBRQly5dCAC1b9+evL29ycPDg9TU1Gj58uW0a9cuMjc35/7WDx484GIoKCggd3d37nMqKyvTyZMniejthY+8vDx17dqVtm3bRuvWraMZM2ZwF2N88/b2JllZWZo6dSoJhUK+w3lvAQEBJBAI6Ouvv+YtBqFQSFOmTCF5eXk6c+YMb3EQ/V8dAoDmzZsnVm4SEhJITU2NpKWlydnZmQIDAz/quysUCmnZsmWkpaVFK1eupOnTp9OECRO4i/yaylplI0aMoPPnz1fZXltcfn5+NZbF6uTk5JCLiwv3XoaGhnT37l3u+bo+x6lTp8jQ0JAA0FdffUXPnz+no0ePkpGREQGgb775hp48eUJ//vknycrKcvtduXKl2jqIiOjs2bMkJyfHxSR6dOzYkS5evFjv/+/GkJqaSra2tqSvr//e7UFDuHLlCqmrq5OlpWWVNq+5YG11Vc+ePaNRo0aRhYUFTZs2jby8vOjnn38me3t7GjlypFhysq4yR0T0/Plzat++PampqdGePXvEjvXXX3+RlpYWaWtr06ZNm6i8vFzs+StXrlC/fv24c4hZs2ZRUlJSvcry06dP69VmP3r0iOzs7MS2+fv705QpU6r8bRqyPuPTgwcPqEuXLqSiosJLR2RqaipZWlqSgYEB3bt3r8mPX52WVBf4+flRly5dSF5engYNGkQLFy6kOXPm0Lp168SSDA3RJtZWjqprF+s636iuPqitXNUnxrS0tDrPDypbsWIF/fnnn/X6Wzel/Px8cnV1JYFAQH5+fnyH02C6dOlC33zzDd9hMAzDMAzTutSeJCAiunHjBmlra5OxsbHYqJnWJiMjg/v51atXRPR25ElkZCRdvnyZEhISPuh909LSeE+wpKeni13AZ2ZmftD7iP4eos8TGxv7XqNZMzIyKCwsTOw1FRUVVFBQQLm5uRQWFtako3Jrk5WVRR4eHgSAFi9e3CITBCL//PMPSUlJ0erVq3mLoby8nObOnUsSEhK0ePHieo/wbS4+5rtbWFhI4eHhVUb61kdCQkKtd4FUF9eHSkpKovv379eYoPuYz/G+fH19ycfHh16/fk0xMTEUHh5Oly9fpu3bt9PgwYMb/fg1CQoKIn19fTI2Nqa4uDje4khJSSEnJyeSlJQkNzc3evHiBW+xNLXW0FYnJyfT1atXKSoqqtY2r64yV1pa2uR3lLxPm/3u/0VZWVmto9wbsj5rShkZGbRy5UqSkZGhPn368Fo35OTk0OjRo0kgENDKlSurjNBvTRqrLsjPz6dbt26JvX91PqZNfN9z3/rsX1N90BDlqq7zA6K3dwp96PVFY7l69SqZm5uThoZGq7qGzcrKIklJyWoHlzAMwzAMw3yEupMERG87JFxcXEhCQoI8PDyaTUcuwzSGs2fPkr6+Puno6HCjrlq6AwcOkKSkJK1fv57XOLy9vUlRUZG6du1KkZGRvMbCNE9xcXGkra1d7dRCaWlpNG3atCaPqbi4mFauXEmSkpLk6upKb968afIY3lVRUUHHjx8nY2NjateuHa1cuZKbRoJhmMZXUFBAmzZtImVlZdLX16ddu3ZVuWuDD0KhkHbt2kVKSkpkYmLSqjpHmeYpJCSE5s6dy3cYHNFAHwkJCRo9ejQlJibyHVKDCggIIAkJCUpLS+M7FIZhGIZhWpecahcufpeOjg78/f3h7e0NPz8/WFlZYceOHTUu8MUwLdHNmzcxcuRIjBkzBp988gmio6Ph7OzMd1gNYvr06fDy8sLatWvx888/8xaHu7s7wsPDIS8vD3t7e3z33XfIzs7mLR6m+UlMTER6ejqmTZuGa9euITExEYmJiQgKCsLixYuxdu3aJouFiHDixAl0794dO3bswIEDB+Dr6wt1dfUmi6EmEhIScHNzQ1RUFH744Qfs3r0bnTt3xsqVK/H8+XO+w2OYVishIQGrV6+GkZERfvrpJ6xcuRKxsbHw8PCAlJQU3+FBUlISHh4eePjwIUxNTeHo6IiJEyciMjKS79CYVuTOnTvo378/5s6di5UrV+KXX37hOyTk5OTgxx9/hKmpKQICAnDixAmcPXsWBgYGfIfWoEJCQmBmZgZtbW2+Q2EYhmEYppWpV5JAZNq0aXj8+DHGjh2LZcuWwcTEBH///TdKSkoaKz6GaXQhISEYMWIEHBwcUFhYiODgYOzZswcqKip8h9agZs6cia1bt2LVqlX49ddfeYvD1NQUISEh2LhxI7y8vNC5c2f89ttvKCoq4i0mpvkYMmQILly4AC0tLcybNw9mZmYYNWoULly4wHWEN4Xg4GDY29tjwoQJsLOzQ2RkJKZNm9Ykx34fcnJyWL58OZ4+fYolS5bAx8cHpqamGD16NP777z9UVFTwHSLDtHhEhIsXL8LZ2RnGxsbYv38/5s2bh6dPn2LVqlVo164d3yFW0alTJ/z333/w9fVFTEwMevTogbFjx+LOnTt8h8a0EnFxcXj+/Dm2bNnC6znzmzdv8P3338PQ0BC//fYb5s6di6ioKLi4uPAWU2O6ceMG+vfvz3cYDMMwDMO0QhJERB/ywqSkJPzyyy/w8vKCuro6Zs+ejVmzZqFjx44NHSPDNLji4mL4+flh9+7duH79OgYOHIi1a9di6NChfIfW6LZs2YJly5bB09MTCxYs4DWWnJwc/P7779i8eTNUVFSwcOFCzJ49m42OYjhEBAkJiSY5llAoxOnTp7Ft2zZcvXoVTk5O+Omnn9CjR48mOX5DKC8vx9mzZ/H333/j0qVL6NixIyZMmABXV1f06tWryf6WDNMahIWFwc/PD8ePH8fz588xePBgLFiwAM7OzhAIBHyHV29EhICAAGzcuBF37tzBoEGDMGvWLLi6ukJeXp7v8Bjmg4SGhmLv3r04evQoZGVlsWTJEnz55ZetbpBPZaWlpVBTU4OnpydmzJjBdzgMwzAMw7QuuR+cJBBJTk7G9u3bceDAAaSnp2PkyJGYM2cORo8e3aIuoJi24dGjR/Dy8sKhQ4eQn5+PMWPGYNGiRRg8eDDfoTWpH3/8Ed9//z127dqFOXPm8B0OUlNT8eeff2Lv3r0oKCjAxIkTsWjRIvTq1Yvv0Jg24PXr19izZw927NiBV69eYdSoUVi+fDkGDhzId2gfJSYmhpsi6dmzZ+jUqRPGjx8PV1dX9OnThyUMGOYdRIR79+7B19cXfn5+iI+Ph5GREVxdXfHFF1/AysqK7xA/WmBgIHbs2IGAgAC0a9cOkydPxsyZM1l7y7QI6enpOHz4MPbu3YvHjx+ja9eumD17NmbOnAlFRUW+w2t0t27dQr9+/RAbGwtTU1O+w2EYhmEYpnX5+CSBSFlZGc6ePQsvLy9cvHgRmpqacHFxwbhx4zBkyBCWMGB4ExMTA39/f5w4cQJhYWEwMTHBrFmz8MUXX0BHR4fv8Hizbt06rF+/Hn/99Rfmz5/PdzgAgKKiIvzzzz/w9PTE/fv3YWtri8mTJ2PixIno0KED3+ExrUhRURH+++8/HD16FAEBAZCXl8fMmTOxYMECGBsb8x1eg4uIiICfnx98fX0RFxcHPT09jBgxAo6OjnB0dET79u35DpFheJGRkYFLly4hMDAQgYGBSExMhLGxMdzc3ODq6oqePXvyHWKjSE9Px6FDh7Bv3z48fvwYVlZWcHZ2houLC+zs7FgSkWk2UlJScObMGZw6dQrBwcGQl5dvs8mtzZs346effkJ6ejorowzDMAzDNLSGSxJU9vLlSxw+fBj+/v4IDw+HmpoaPvvsM4wbNw4jRoxgtzYzjS4iIgInT56Ev78/oqKioKWlBWdnZ0yaNAlDhgxhJ9b/36+//opvv/0Wf/75J5YsWcJ3OGJu3LgBb29v+Pv7IysrCw4ODpg0aRJcXV1ZhybzQcrKyhAYGIijR4/i9OnTKCgowODBgzFlyhRMmjSpWc4r3hgePHiAM2fOICgoCLdu3UJ5eTm6du2K4cOHw9HREQMGDICCggLfYTJMoygqKsKNGzcQGBiIoKAg3L9/H1JSUrC3t8fw4cPx2WefwdbWlu8wm1RoaCiOHTuGU6dO4cWLFzAwMMDYsWPh7OyMQYMGsYE+TJOLiYnBqVOncPr0ady+fRvy8vIYOXIkxo0bh3HjxrXZa8nJkycjLy8PAQEBfIfCMAzDMEzr0zhJgspevnyJU6dOISAgAFeuXIFAIICtrS369+8PR0dHdvHBNIi0tDRcu3YNQUFBOH/+PBISEtChQwc4OTlh9OjR+OSTT9j3rAZ//PEHli9fjo0bN2L16tV8h1OFUCjE5cuXcfDgQZw6dQoFBQWwsbHhRkAPHjwY0tLSfIfJNFNpaWm4cOECAgICEBgYiOzsbFhZWcHd3R3u7u7Q1dXlO0ReFRYW4ubNmwgKCkJQUBDCw8MhKSkJc3Nz2NnZoX///nBwcICVlRVLrjItUnJyMsLCwhASEoIbN27g3r17KCkpgbGxMdeODB8+HKqqqnyH2ixERUUhICAAZ8+exc2bNyEvL49+/frB0dERDg4OsLe3Z+dTTIOrfB4fGBiI+Ph4qKurY9SoUfjss8/g5OTUJqYTqkvnzp3h7u6OtWvX8h0KwzAMwzCtT+MnCSpLSUnB+fPnERQUhEuXLiEtLQ3q6uoYMmQIhg0bBgcHB1hbW0NKSqqpQmJaqJSUFISGhuLy5csICgrCkydPICsri379+mHYsGEYMWIEevbsyTq16mnnzp1YsGAB1q1bhzVr1vAdTo2Kiopw/vx57pGQkABNTU0MHz4cn3zyCQYOHAhDQ0O+w2R4lJeXh1u3bnEJw4cPH6Jdu3YYMmQIlzTs1KkT32E2WykpKbh69SpCQ0MRGhqKiIgIlJaWQltbG3369EGfPn3Qs2dPdO/enS0wzjQ7r1+/xoMHDxAWFoZbt24hNDQUqampEAgE6NGjB/cdHjhwIAwMDPgOt1nLz8/HuXPn4Ofnhzt37iA9PR2FhYVQU1PD4MGDMWTIEPTr1w/dunVjSQPmvSUkJCA0NBRXr15FcHAwoqOjISMjA3t7ewwdOhSOjo7o27cvuyas5M2bN9DS0sK///4LJycnvsNhGIZhGKb1adokQWVEhEePHuHSpUsICgrC1atXkZ+fDyUlJfTs2RN9+/aFvb097O3t2dQibVxxcTHCw8Nx+/Zt3L59G7du3UJCQgIkJSXRo0cPDBs2DI6Ojujfv3+bmS6kMezevRvz58/HN998g02bNvEdTr1ERUXh3LlzOH/+PG7cuIGSkhLo6+tzo58HDBiArl27sovMViw5ORk3btzgRgk/ePAAQqEQFhYW+OSTT+Dk5ISBAwdCTk6O71BbJFH9GxoaynW6vnr1CgCgo6ODbt26oUePHujWrRu6desGCwsL1mHINLry8nLExMQgMjISDx48wIMHDxAZGYnk5GQAgJ6eHuzt7dGvXz/06dMHdnZ2bXZ6kvrIyclBREQEwsPDER4ejrCwMMTGxqKiogKampqwtbWFk5MThg0bhuDgYAQHB+PatWvIzs6GnJwcbG1t0atXL/Tu3Ru9e/eGiYkJ3x+JaUays7Nx9+5d3Llzh3ukpqZCSkoKdnZ2GDJkCIYOHcrO4+tw7tw5fPrpp0hPT4eWlhbf4TAMwzAM0/rwlyR4l1AoxKNHjxAaGorbt28jNDQUMTExqKiogJGREWxtbdG1a1d07doV3bt3h7GxMRsl3gplZmbiwYMHePjwIR4+fIj79+8jMjISpaWl0NLS4hJHffr0Qe/evaGsrMx3yK2Kl5cX5s2bh+XLl2PTpk0tqowVFxfj7t27uH79OkJCQnDz5k1kZ2dDWVkZvXr1gq2tLWxsbGBjYwMzMzNISkryHTLznjIyMriOrIiICNy9exfx8fGQlpZG9+7d0b9/fy5B1NanEWpMGRkZXKesqL6OiopCaWkpZGRkYGVlBTMzM5iZmcHc3Jz7mU3nwryv3NxcxMbGIjY2FjExMdy/jx8/RklJCQQCASwtLbkklShhxQaX1Cw3NxeRkZEICwvjHtHR0aioqICqqiqsra1hZ2fHPWqaaqyiogLR0dFiHb+RkZEoKyuDhoYGd95ubW2Nbt26wcrKinUAt3IVFRWIj49HZGQkHj16hIcPH+LBgweIi4sDEaFjx46wt7fnkkl2dnZs/Zv38MMPP+DgwYN49uwZ36EwDMMwDNM6NZ8kQXVycnK40eOizohnz56hoqICioqK6NKlC7p164auXbvCzMwMpqam6NixIxs13AK8efMGcXFxiIuLQ1RUFCIjI/Hw4UNuhKqmpia6d++Orl27omfPnujTpw86d+7Mc9Rtw6FDhzBz5kx88cUX2LlzZ4stTxUVFYiKisL169dx7949REREICoqCmVlZVBUVET37t1hY2OD7t27w8LCAhYWFtDU1OQ7bAZASUkJYmJiEBMTg0ePHiEiIgIRERFc/dChQwfY2NjA1tYWDg4O6NOnD5urmGdlZWWIjo7m6nJRZ+6zZ89QUlICANDW1hZLGhgZGaFjx47o1KkTdHR0eP4EDF/S0tKQkJCAly9f4sWLF2JJgdTUVACAjIwMjI2NYWFhATMzM+78z9LSEjIyMjx/guYrOzsbjx49EksIPHnyBEQEXV1d2NnZwdraGlZWVtzPH6OoqAgRERG4c+cOl0B8/PgxioqKICkpCWNjY3Tr1g1dunSBhYUFTExMYGJiAjU1tQb6xExTKC0tRXx8PJ4+fcol7SIjI/H48WMUFBRAQkICRkZG3OAu0V0mrJ7/OKNHj4aSkhJ8fHz4DoVhGIZhmNapeScJqlNQUICoqCix0eYPHz7EmzdvAACysrIwNjbmkgaiR6dOnWBgYMAuJptQamoqEhIS8Pz5c8TFxSE2NpZLDGRmZgJ4+/+loqICeXl5DBo0CK6urujZsycbBcyzgIAATJgwASNGjMDRo0dbzVQtJSUlePToETcSPSIiAo8ePUJ+fj4AQENDAxYWFrC0tIS5uTksLCzQuXNnGBoasqkqGlhFRQWSk5Px/PlzLiHw5MkTREdH4+XLlxAKhZCSkkLnzp25O0BEd4OwZE7LIRQK8fLlS67TVzQaPC4uDklJSRAKhQAAOTk5dOrUiXuIkgeGhobQ0dGBnp4eG3HaAhUWFiI5ORmpqal48eIFXr58ySUERI+ioiIAgKSkJPT19WFqasolkiwsLGBqagpDQ0O2QH0dsrKyEBUVVWtCQPTo1atXk3XYCoVCPHv2jBtd/ujRI0RGRiI+Ph7l5eUA3g4MESUMTE1NYWJiAmNjY3Ts2BE6Ojrszj8e5OTkIDExkUsGxMXF4enTp3j69CkSEhK4ultbWxtdunRBly5duKSAtbU1S9w3gvbt22PlypVYtmwZ36EwDMMwDNM6tbwkQU0yMzO5E9iYmBiuM/rp06fIyckBAEhISEBHRwcdO3ZEhw4d0KFDB64zQk9PD3p6etDS0mo1HaKNpaKiAhkZGcjIyEBSUhISExORmJiIFy9ecD8nJiZyo0cFAgGMjIy4C39R4sbExAQdO3aEj48PvLy8cP36dSgoKGDMmDGYMGECRo4cCVlZWZ4/bdt17do1jBkzBra2tjh16lSrntopMTERMTExiI6OxpMnT7ifk5KSuH3at28PQ0NDruNS9HPHjh2hra3NFnF9R0FBAVJSUpCSkoIXL15wD9Fo4cTERJSWlgIAlJSUYG5uDnNzc7EEjampKasDWrGysjK8evWK6ywWfT9EHckJCQncdwQAFBUVoa+vj/bt23P/6unpQUdHB7q6utDW1oa6ujo0NDRYUq8RFRcX482bN8jMzER6ejqSk5ORlpaGpKQkpKen49WrV0hPT0dSUhLy8vK418nIyMDAwEAsGVS5Hu3QoQMbyFFPycnJYsmAx48f4/nz5wBQJSFgb2/fLNunsrIyvHz5kut4rtwR/eLFC67sCwQC6OnpoUOHDujYsSMMDAxgYGDAnbvr6Oiwc/f3IDqHf/36NZKTk/Hq1SskJCQgMTERSUlJ3M+Vy66uri6XxHn30ZrPDZuTFy9ewMjICNevX0f//v35DodhGIZhmNap9SQJapOeno6XL1/W2JmdkpIitr+SkhJ0dXWhpaUFLS0trvNBS0sLampqUFVVhYqKClRVVblHSx3hWFZWhuzsbGRnZyMnJwfZ2dnIyspCdnY2lwjIyMhAamoq0tLSuN8rKiq491BSUkLHjh2rTb6ILurqMwLw9evX+O+//3Do0CEEBwdDSUkJY8aMgZubG0aOHMk6D3jw6NEjjBw5Enp6ejh37lybG8Gdl5eH58+f4+XLl4iPj6/S0Z2VlcXtKxAIoK2tDV1dXejo6HAdmKKOSzU1tSqPlrTAa05ODrKyssQemZmZSEtLQ3p6OlJSUrh6Ijk5GQUFBdxrZWVl0bFjxypJFkNDQxgZGUFPT4/HT8Y0V0TEJZpSUlLw9OlT/PfffwgPD4e9vT2ysrKQlJSEtLQ0LiktIi8vDw0NDWhoaHCJA01NTe5nZWVlqKioQFlZGYqKilBUVISSkhJUVVWhqKjYqtub0tJS5OfnIzs7G3l5ecjPz0d+fj5yc3ORk5OD3NxcZGZm4s2bN2IP0bbCwkKx95ORkakxcSOqD0Xb2Ijw9/duQuDevXvcNEzvJgT69u3bKtppoVCIV69eITExEQkJCXj16hWXUBT9nJ6eLvYaRUVF6OjoQFtbG5qamtDW1oaOjg40NTXFzt1FD1VV1RY/zVFBQQF37p6Tk8M9srKyqpzDixID757Dy8vLc3dbi5J4lRMxnTp1arHXOK3J8ePHMWXKFOTk5LD/D4ZhGIZhGkvbSBLUpaSkhLsdPiMjA+np6dzPGRkZSElJ4X7OyspCWVlZlfcQCATcRYeKigpkZWXRrl07tGvXDrKyslBSUoK0tDRUVVUhKSkptoCj6Ll33+/dW3XLysq4aVEqy8nJ4U74i4qKUFxcjPz8fJSVlSEnJwdCoRDZ2dkQCoXIzc1FUVERd1FRuSOvMlVVVWhoaKB9+/bQ0tLiLrbe/VlXV7dRLrJevXqFEydOwNfXFzdv3oSKigo+++wzuLm54ZNPPmlRnastXVxcHEaMGIF27drhwoULMDAw4DukZiMnJ4frpExOThYbVZuamoqUlBSkp6cjMzOTm1ahMkVFRS5hICcnB2VlZcjJyUFeXh6KiooQCARcMkFUH0hLS0NJSUnsfSQlJaGioiK2rbi4mJvGQ6SkpITr4BPVJ4WFhSgpKUFOTg7KysqQm5vLvbZyYqByp4KIiooKtLW10b59e7HR3KLkiKiTUFdXt0Utgs00H0SEq1evYufOnTh58iQUFBQwffp0rF69Wqwz9M2bN8jIyOA6sjMzM6vt6BY9J+oQr4mMjAwUFRWhqqrKtdGiMikvLw85OTnIyMhAQUEBUlJS3Gjad9vDmtpHUTl/V3XlViQ7OxuVT9lEScrc3FwIhUIUFBSgtLSUew9RGS8vL0deXh6ys7ORn58vdnfGu1RUVKCkpFRjcuXdfzU1NVtFp3RzQER4+vQpwsPDuUdYWBiysrIgJSUFCwsL2Nracg8bG5sqbUFbUlxczLW31XWGixLYGRkZyM7OrrFcVU4cyMjIiJ2ni8q2qA0WnduLVFe+390HAFcG3yUqs5X3KS0tRUFBAVeORW206Ly+8qCe6s4rJCUloaamBk1NTW6wk+ic/d3kiY6ODjQ0NN7r787w45tvvkFQUBAiIiL4DoVhGIZhmNaLJQk+REFBgdhJenU/i07yRSf3eXl5KC8v507qc3NzuferPBpZRNTZX5mEhIRYckFEQUGBG/Uo6ngQbVNRUYGUlBRUVVVRVlaGO3fuYNSoUdDT06tyN0RzHVmVmJgIf39/LmGgqqqK0aNHs4RBE0pKSsLIkSORk5ODgIAAdO/ene+QWpy8vDyuw110x07lh6ijXtSRn5eXx3UIVO7cr/yziKi+qay6ZELlzkzR86IOTxUVFQgEAigrK4ttq+4OCNGDjQpmGktOTg6OHTsGT09PPHz4EHZ2dvDw8MDnn3/eoKMoc3NzuZH0oo70yqPrRSPrRUn22jrjiQjZ2dnce9eU2AfAnRO8q7pyKyJKUoioqKhAUlKySvJC1KEpSh6K/hXdNaGkpMQlKCvfRcGmDWk6QqEQMTExYgmBiIgI5ObmQlpamltIWJQQ6N69Oxs9/JFEbazoITpnrzwKv7S0tNrBNe923AM1d/yLzvvfVVdC4d2EhOh8/t3BRmpqamKJjcoDlERJPqa/xaEYAAAgAElEQVT1GTJkCExMTODl5cV3KAzDMAzDtF4sSdCWZGVlwdbWFlZWVggICGiRI3tfvnyJU6dOwdfXFyEhIdDQ0MCnn34KNzc3ODk5sYUNG1FeXh4mTJiAGzduwMfHB6NHj+Y7JKYGW7duxaZNm6pMpcYwzV1YWBh2796NI0eOQFJSEpMnT8a8efNgY2PDd2gM80HKy8sRExMjNmXQ/fv3UVBQAIFAAFNTU7Epg2xtbauMRGcYpu0iIqirq+Onn37C/Pnz+Q6HYRiGYZjWiyUJ2po7d+5gwIABWL9+PVauXMl3OB/lxYsXOH36NJcw0NTUhJOTE9zd3TF06FA2yrkRlJeXY9GiRdizZw+2bt2KhQsX8h0SUw0fHx9MmzYNpaWlrBwwzV5xcTGOHz+OLVu2ICIiApaWlpg+fTo8PDya3Z1tDFObsrIyxMbGiiUEwsPDUVRUVG1CoGfPnmzBXYZhahUfHw9jY2PcvHkTffv25TschmEYhmFaL5YkaIv++OMPfPvttwgODsaAAQP4DqdBxMfH4/jx4/D29saTJ09gYGCAcePGwc3NDQ4ODi3yronmbOvWrVi2bBkWLVqEzZs3s47oZubSpUtwdHRERkYGmy+cabaio6Nx4MAB7N69G4WFhRgzZgw8PDzg6OjId2gMU6fS0lLExcVVWVS4pKQESkpK6NatG5cMsLa2RteuXVv1gtgMwzSOkydPwtXVFTk5OVXWq2MYhmEYhmlALEnQFhERxo8fj1u3biEiIgI6Ojp8h9SgoqKi4Ovri2PHjiE6OhodOnSAi4sLSxg0MF9fX7i7u8PJyQmHDx9m0yM0Iw8fPkS3bt0QFRUFKysrvsNhGE5JSQnOnDmD3bt3IygoCKamppg1axZmzZrFElpMs5WXl4cHDx6IJQRiYmIgFAqhoqKCLl26iN0hYGlpyZLnDMM0iHXr1sHHxwcxMTF8h8IwDMMwTOvGkgRtVXZ2Nuzs7GBoaIiLFy9CSkqK75AahShh4OPjg9jYWHTq1Aljx46Fm5sb+vfvz3d4Ld61a9fg4uICMzMznD59Gtra2nyHxABIS0uDjo4OLl++jMGDB/MdDsMgLi4Oe/fuxd69e5GVlQUnJyd89dVXGDZsGEvcMs1KTk4OHj58KJYQiI6ORkVFBVRVVWFtbS2WELCysmLfYYZhGo2LiwsEAgGOHz/OdygMwzAMw7RuLEnQlt27dw/9+/fHqlWrsGbNGr7DaXSihMGRI0fw9OlTGBoaYsyYMSxh8JFiY2MxatQolJaWwt/fH3Z2dnyH1OYJhULIysrin3/+wYQJE/gOh2mjhEIh/vvvP2zbtg2XLl2Cnp4epk6dioULF6JDhw58h8cwyMrKQlRUlFhC4MmTJyAi6Orqik0XZGVlBWtra75DZhimjTEyMsLs2bOxevVqvkNhGIZhGKZ1Y0mCts7T0xNLlixBcHAwBg4cyHc4TUaUMDh06BCeP38OIyMjTJgwAdOnT4elpSXf4bU4mZmZmDx5Mq5evYodO3ZgxowZfIfU5mlra2Pt2rVscWmmySUnJ+PQoUP466+/kJSUhKFDh8LDwwMuLi6QlpbmOzymjUpOThZLBoSFhSElJQUAxBICdnZ26NWrV6ubipFhmJYnOzsb6urqOHv2LEaNGsV3OAzDMAzDtG4sScC8vY313r17uH//PjQ0NPgOp8mFhYXh4MGD8PPzQ3JyMqysrODm5oZJkybBwsKC7/BaDKFQiNWrV+PXX3/FnDlz4OnpCYFAwHdYbVaXLl3g6uqKdevW8R0K0wZUVFQgODgYu3fvxsmTJ6GpqYnp06dj3rx5MDQ05Ds8po15NyFw9+5dpKWlAaiaEOjTpw+0tLR4jphhGKaqq1evYvDgwUhMTISBgQHf4TAMwzAM07qxJAHz9nb7Hj16oGvXrjh79mybnVu3oqICN2/ehK+vL44fP47U1FQuYTBlyhSYmZnxHWKLcOzYMcycORM9e/aEr68vW6eAJ0OHDoWFhQX+/vtvvkNhWrHU1FR4e3tj165diI+Ph4ODA7766is4OzuzJCHTJN5NCISGhuL169eQkpKCubm52HRBDg4OUFdX5ztkhmGYetm2bRvWr1+P169f8x0KwzAMwzCtH0sSMG9dv34dQ4YMwfbt2zF//ny+w+Fd5YTBsWPHkJaWxiUMpk6dChMTE75DbNYePHgAFxcXlJeXw9/fHz179uQ7pDZn0qRJKC8vh5+fH9+hMK1QWFgYtm7diqNHj0JBQQETJkzA4sWL2ZztTKMpLy9HTEyMWELg/v37KCgogLS0NMzMzMTuELC1tUW7du34DpthGOaDzZo1Cy9fvkRQUBDfoTAMwzAM0/qxJAHzf9asWYPffvsNoaGh6N69O9/hNBtCoRC3bt2Cr68vfHx8kJGRwSUM3N3dYWxszHeIzVJGRgYmTpyI27dvY8+ePZg8eTLfIbUpixcvxv3793Ht2jW+Q2FaiZycHBw7dgzbtm1DVFQU7Ozs4OHhgalTp7LOWKZBlZWVITY2ViwhEBERgcLCQggEApiamoolBHr27Ak5OTm+w2YYhmlQdnZ2GDJkCH7//Xe+Q2EYhmEYpvVjSQLm/1RUVGDYsGFIT0/H3bt3WadPNUQJg0OHDuHYsWPIycmBnZ0dpk2bBjc3N+jp6fEdYrNSXl6O5cuXY+vWrViwYAH+/PNPyMrK8h1Wm7BhwwYcOXIE0dHRfIfCtHBhYWHYvXs3Dh8+DCkpKUyePBkLFixgyWSmQZSWliIuLq7KosLFxcVQVFRE9+7duemCRIsKs3aEYZjWTigUQklJCTt27MD06dP5DodhGIZhmNaPJQkYca9evUL37t0xYcIE7Nixg+9wmrWSkhJcvHgRvr6+OH36NPLz89G3b1+4ublh4sSJ0NHR4TvEZuPUqVOYMWMGjI2Ncfz4cXTu3JnvkFq9nTt3YtWqVcjMzOQ7FKYFysvLg4+PD3bs2IH79+/D1tYWc+fOxZQpU6CoqMh3eEwLlZeXhwcPHnCJgMePH+Phw4coLS2FsrIyunbtKnaHgKWlJSQlJfkOm2EYpsk9e/YMJiYmuH37Nnr37s13OAzDMAzDtH4sScBUdeLECbi5ueHEiRNwcXHhO5wWobi4GIGBgfD19cWpU6dQUFDAJQwmTZqE9u3b8x0i7+Li4jBhwgQ8f/4cXl5emDBhAt8htWr+/v5wdXVFcXExZGRk+A6HaSEeP36MXbt2Yd++fSgvL8dnn30GDw8PODo68h0a08Lk5OTg4cOHYncHREdHo6KiAqqqqrC2thZLCFhZWUFCQoLvsBmGYZqFgIAAfPbZZ8jOzoaKigrf4TAMwzAM0/qxJAFTvTlz5uDUqVN4+PAhGxH/noqKihAUFARfX1+cPHkSRUVF6NOnD9zc3DB58mRoa2vzHSJviouLsXLlSmzbtg0eHh7Yvn0768BuJDdu3MCAAQPw6tUr6Ovr8x0O04yVlJTgzJkz2L17N4KCgmBmZoaZM2di9uzZ0NDQ4Ds8pgXIyspCVFSUWELgyZMnICLo6urCzs5ObMoglhBgGIap3e+//44tW7bg1atXfIfCMAzDMEzbwJIETPUKCgpgY2MDIyMjnD9/nl3Mf6DKCQN/f38UFxejT58+cHd3x8SJE9vsyKAjR45g3rx5sLCwwPHjx2FkZMR3SK1ObGwszM3NER4eDhsbG77DYZqh2NhY7Nu3D3v27EFeXh7Gjh0LDw8PDBs2jNX5TI2Sk5PFpguKiorC48ePAYBLCIgevXr1YgMNGIZhPsCsWbOQkJCAwMBAvkNhGIZhGKZtYEkCpma3bt3CgAEDsH37dsyfP5/vcFq8wsJC/Pvvvzh48CAuXrwICQkJDB8+HG5ubnB2doaysjLfITapJ0+ewM3NDSkpKdi7dy+cnZ35DqlVyc7OhpqaGs6fP4+RI0fyHQ7TTJSWluL06dPYvXs3Ll26BH19fcyaNQsLFixo03c5MdWrnBAICwvD3bt3kZaWBqBqQsDe3p59hxiGYRpIv379YGdnh+3bt/MdCsMwDMMwbQNLEjC1+9///ofNmzcjPDwc5ubmfIfTamRnZ+PMmTPw9fXFxYsXISkpCUdHR7i5ucHFxQVKSkp8h9gkCgsL8eWXX2Lfvn2YO3cu/vzzT7Rr147vsFoNOTk57NmzB1OnTuU7FIZnSUlJ8PLywo4dO/D69WsMHToUHh4eGDduHKSkpPgOj2kG3k0IhIaG4vXr15CSkoK5ubnYdEH9+vVjU1ExDMM0InV1dWzcuBELFizgOxSGYRiGYdoGliRgaldeXg4HBwcIhULcunULAoGA75BanaysLJw9exa+vr64cOECpKSkuITBuHHjoKioyHeIjc7f3x9z5syBtrY2jhw5AltbW75DahU6dOiApUuXYtmyZXyHwvCgoqICwcHB2L17N/z9/aGtrQ13d3fMnz8fnTp14js8hifl5eWIiYkRmzIoPDwcmZmZkJaWhpmZmdgdAjY2NlBQUOA7bIZhmDYjLS0NOjo6uHTpEoYOHcp3OAzDMAzDtA0sScDULTo6Gra2tlixYgXWrVvHdzitWmZmJgICAuDr64vz589DIBBg2LBhcHNzw/jx41t1R01iYiLc3d0REhKCVatWYc2aNZCUlOQ7rBbNzs4OI0aMwM8//8x3KEwTSk1Nhbe3N3bs2IHExETurgFnZ2eW6G1j3k0IhIWFISIiAoWFhRAIBDA1NRVLCNjZ2UFeXp7vsBmGYdq0K1euYMiQIUhOToauri7f4TAMwzAM0zawJAFTP9u2bcPXX3+NGzduwN7enu9w2oQ3b97g33//ha+vL86dOwdZWVmMGjUK06ZNw8iRIyEjI8N3iA2OiLBt2zasWLECAwYMgLe3N/T19fkOq8VycnKCnp4e9u7dy3coTCMjIly69P/Yu/O4qOrFf/yvgRn2HUFBXBBkV6+gpOHSTTQ3XC+piWi55b5kpWlqH83Sbotdl8TKBJeMxN1SM7dEU3BBkU1BRJBNZIdhGOb7Rz/m54SalvAemNfz8ZgHcs6ZM6/DTbyP8zrv9/s4wsLCsHfvXpiamiI0NBSzZ8+Gi4uL6HjUABQKBZKTkzUKgdjYWFRWVsLMzAzu7u7q6YJqFxU2NDQUHZuIiP5k48aNWLhwIYqKikRHISIiIt3BkoCejkqlQv/+/XH79m1cvnyZ88Y3sMzMTPz444+IjIxEdHQ0LC0tERQUhODg4CZZGFy4cAFjx45FUVERvv76awwZMkR0pEZp/PjxKCgowIEDB0RHoXpSWFiIH374AWvXrsWNGzfg5+eHKVOmYNy4cXwivAkrKSnB1atX1dMFxcfH4+LFi6iqqoKFhQU6dOigMTrAw8ODa08QETUSc+bMwYULF3Du3DnRUYiIiEh3sCSgp5eZmQkfHx+8/vrr+Oyzz0TH0VkZGRmIiopSFwZWVlYYPHgwgoOD0b9//yYznUhFRQUWLlyIL7/8EsHBwdi0aROsra1Fx2pU3n77bZw+fRq///676Cj0nMXGxiIsLAwRERGQyWQYPXo0ZsyYgY4dO4qORs9ZcXEx4uLiNEYHJCYmoqamBpaWlvDx8dEoBDw9PTlVGxFRI/bKK6/A0dERW7ZsER2FiIiIdAdLAno2W7ZswaRJk3Dy5En07NlTdBydd+fOHezZs0ddGFhbW2PQoEEIDg7GgAEDIJVKRUf8xw4fPoxJkyZBJpPh22+/RZ8+fURHajTWrFmDjRs3Ii0tTXQUeg6Ki4vx/fffY/369YiLi1OPGhg7dmyTXq9ElxQWFuL69esahUBCQgJUKhWsra01pgvy8/ODl5cXJBKJ6NhERPQctWvXDpMnT8aiRYtERyEiIiLdwZKAnt2wYcOQkJCAK1eucDoLLZKeno69e/ciMjISZ8+eha2tLQYOHIjg4GAMHDiwUU81kZeXh2nTpiEqKgqTJ0/Gp59+CjMzM9GxtN6WLVswc+ZMlJWViY5C/0DtqIEdO3aguroaQUFBmDNnDgICAkRHo38gKytLY7qg2j8DgIODg0YZ0KVLFy5eSUSkA6qrq2FsbIyIiAiMHj1adBwiIiLSHSwJ6NllZWXBx8cHb7zxBv773/+KjkOPkJaWhv379yM8PByXLl1Cy5YtMXLkSAQHByMgIKDRPnkaGRmJadOmwcLCAt999x169eolOpJWO3ToEAYPHoySkhKWKo1MZWUlDhw4gLVr1+Ls2bPw8PDAhAkTMHnyZNjY2IiOR8+othCofcXExCA7OxtA3ULghRdegL29veDEREQkQmpqKlxcXPD777/D399fdBwiIiLSHSwJ6O/59ttvMXnyZJw6dQo9evQQHYeeID4+HpGRkdi1axcSExPRqlUrDB8+vNEWBtnZ2Zg6dSoOHjyImTNnYs2aNTA0NBQdSytdvHgR/v7+uHXrFtq1ayc6Dj2FpKQkbNmyBZs3b0ZZWRmGDBmCKVOmoE+fPo3u76qu+nMh8PvvvyMvLw9A3UKge/fuaNasmeDERESkLY4fP47AwEDk5ubCzs5OdBwiIiLSHSwJ6O8bOHAgUlNTcfnyZU471EjUFgY7d+5EcnIyWrdujWHDhjW6wkClUuHrr7/GW2+9hTZt2uCbb77h01aPkJ6ejrZt2+LcuXPo1q2b6Dj0GFVVVdi3bx/CwsJw/PhxuLi4YNKkSXjjjTd4g0CLKZVKJCYmakwZFB0djYKCAkilUri5uWkUAp07d+baEURE9ESbN2/G/PnzUVJSIjoKERER6RaWBPT31U47NGnSJKxZs0Z0HHpGtYXBjh07kJKSgjZt2mDo0KEIDg5uNKNDbt++jcmTJ+PEiROYM2cOVqxYARMTE9GxtEZFRQVMTEywb98+DBkyRHQc+pNbt25h8+bN+Pbbb1FQUIB///vfmD17NgYPHtxoCjtdUV1djaSkJI0RApcvX0Z5eTlkMhnat2+vUQj4+fmxPCciomf23nvv4dChQ7h69aroKERERKRbWBLQP/P1119j6tSpnHaokastDLZt24Zbt27B2dkZQUFBGD9+PHx9fUXH+0sPr1UQFhaGwMBA0ZG0hoWFBT7//HNMnDhRdBQCUFNTg19//RVhYWGIiopC8+bNMW7cOEyfPh2tW7cWHY8AKBQKJCcnaxQCsbGxqKyshIGBAVxdXessKmxkZCQ6NhERNQFjxoxBRUUF9u7dKzoKERER6RaWBPTPqFQq9O/fHxkZGbh8+TLnhm8C4uPjERERgYiICGRlZcHLywvBwcEYPXo0PDw8RMd7rOzsbMycORNRUVEICQnBF198wQVeAbi6umLixIlYtGgRACAvLw95eXmwsbFBixYtBKfTHVlZWYiIiMCGDRtw9+5dvPzyy5gyZQqGDx8OqVQqOp7OKi0txZUrV9TTBdUuKiyXy2Fubo6OHTtqFAIeHh7Q19cXHZuIiJqoF154AQEBAfjss89ERyEiIiLdwpKA/rn09HR4e3vj7bffxrJly0THoeekpqYG0dHRiIyMRGRkJO7du6cuDF577TW4ubmJjvhIBw4cwJtvvomamhqsX78eI0aMEB2pwVy4cAHXr1/HvXv3kJeXh/z8fBw8eFB9U7OoqAhKpRIAcOzYMY64qGcPjxrYs2cPbG1tMWHCBEydOhXOzs6i4+mc4uJixMXFaYwOSExMRE1NDSwtLeHj46NRCHh6ekJPT090bCIi0iH29vZ4//33MWvWLNFRiIiISLewJKDn49NPP8XixYtx+fJleHp6io5Dz9nDhcGuXbuQk5OjLgzGjh2L9u3bi46o4f79+5g7dy62bduGUaNG4YsvvtCJp+YjIiIQGhoKmUwGiUSC6upq1NTU1DlOJpOhqKiIc6bXk5ycHHz33XcICwtDamoq/Pz8MGXKFISGhnJamgZSWFiI69evaxQCCQkJUKlUsLa2hpeXl0Yh4OXlxXUgiIhIqNLSUpibm+PAgQMYPHiw6DhERESkW1gS0POhVCrh7+8PMzMznDx5kjdbmjClUolz584hMjIS33//PXJzc9WFwbhx4+Di4iI6otrhw4cxY8YMFBYWYtWqVZg6dWqTfjJYoVCgdevWyM7OfuwxEokEL774In777bcGTKYbYmNjERYWhoiICBgYGGDUqFGYNWsWfHx8REdr0rKysjSmC3q4EHBwcNAoA7y9vdGuXTvRkYmIiOqIi4tDp06dcP36dXh7e4uOQ0RERLqFJQE9PzExMejWrRvCwsLwxhtviI5DDeDhwmDHjh3Iz8+Hl5cXQkNDMW7cODg6OoqOiIqKCqxevRofffQRfHx8sGnTJnTp0kV0rHqzevVqLF68WD2t0J8ZGBhg8eLFWLp0aQMna5qKioqwa9curFu3DteuXVOPGhg7dixMTU1Fx2tysrKyNEYHxMTEqEuxPxcC/v7+aN68ueDERERET2f//v0YNmwYSkpK+P8hiIiIqKGxJKDna+7cuYiIiEBCQgLs7e1Fx6EGJJfLcfToUURGRmLfvn0oLS1F9+7dERwcjFdffRUODg5C8127dg1Tp07FxYsXMX36dHz44YcwMzMTmqk+FBYWwtHRERUVFY895vTp0+jZs2cDpmp6akcNbN++HXp6ehgzZgzefPNNdO7cWXS0JuPPhcCFCxeQm5sLoG4h0L17dzRr1kxwYiIior9v/fr1WLZsGfLz80VHISIiIt3DkoCer7KyMvj4+CAgIADbtm0THYcEqaysxLFjxxAZGYm9e/eirKxMXRiMHj1a2NO9KpUKERERmD9/PoyMjPDll1/+5cLGcrkcSqUSJiYmDZTyn5szZw42btwIhUJRZ5+hoSGKiopgaGgoIFnjVllZiR9++AFffPGFev2V8ePHY8qUKbC2thYdr9FSKpVITEzUmDLo3LlzuH//PqRSKdzc3DSmC/L19YWNjY3o2ERERM/VkiVLsG/fPly7dk10FCIiItI9LAno+Tt8+DAGDRqEI0eOoF+/fqLjkGAPFwZ79uxBRUUFunXrhuDgYIwZM0bIiJN79+5h3rx52LVrF0aMGIHPP/8crVu3fuSxH3/8MS5cuIAff/yx0axncPv2bbi4uNRZtFgikeDf//43jh8/LihZ45SYmKheiLi8vBxDhgzBlClTEBgYKDpao1NdXY2kpCSNEQJXrlxBWVlZnULAz88Pvr6+jaqgIyIi+rsmTpyIjIwMHD16VHQUIiIi0j0sCah+jBw5EpcuXcL169c5pyapVVRU4JdffkFkZCSioqJQWVmpLgzGjh3b4NOFHDlyBLNmzUJWVhYWL16Mt956CwYGBur92dnZcHFxQXl5OebNm4fPPvusQfP9EyNHjsSBAwc0RhMYGBjggw8+wMKFCwUmaxzkcjn279+PsLAw/PLLL2jfvj0mTpyIiRMnclqbp6RQKJCcnKxRCFy6dAkVFRWQyWRo3769RiHQpUsXGBkZiY5NREQkxKBBg9CsWTNs3bpVdBQiIiLSPSwJqH5kZWXBy8sL06ZNw0cffSQ6Dmmh8vJyHD9+HBEREdi/fz8AoG/fvggODsawYcNgYWHRIDkUCgU2bNiAJUuWoEWLFvjyyy8xYMAAAMDrr7+O7du3q2+0f/nll5g1a1aD5PqnLl68CH9//zrbf//990dub4pUKhV27dqF0aNHP/V7UlJS8M033+Cbb77BgwcPMGDAAMyZMwd9+vSBRCKpx7SNW2lpKZKSktTTBdUuKiyXy2Fubo6OHTuqpwvy8vKCv7+/RiFHRESk63x9fdGvXz98/PHHoqMQERGR7mFJQPVn3bp1eOuttxAXFwd3d3fRcUiLFRYWYv/+/YiMjMTRo0ehp6eHwMBABAcHY/jw4TA3N6/3DJmZmVi0aBEiIiIwePBgTJs2DYMHD8bDvyL19PQQFRWFoUOH1nue5+GFF15AbGwslEolAMDU1BRFRUXQ19cXnKz+KRQKTJo0CeHh4YiPj4eXl9djj1UqlTh8+DC+/PJLHD9+HI6OjggJCcGMGTPQqlWrBkzdOBQXFyMuLk5jhEBSUhKUSiUsLCzQoUMHjRECnp6ejWaqLiIiIlEcHBywcOFCzJkzR3QUIiIi0j0sCaj+KJVK+Pn5wc7ODseOHRMdhxqJBw8e4MCBA4iMjMSRI0egr6+vLgxGjBgBMzOzZzpfRUUFTp8+jVdeeeWpjv/pp58we/ZspKamQiKRqG+wA3/M6W9gYIDTp083iqfxo6KiMHLkSAB/FBz9+/fHoUOHBKeqfyUlJRgxYgROnjwJlUqF6dOn48svv6xzXFZWFiIiIrB+/XpkZmbi5ZdfxpQpUzB8+HBIpVIBybVPYWEhrl+/rlEIJCYmoqamBlZWVvD29tYoBLy8vDjigoiI6BkplUoYGhpix44dePXVV0XHISIiIt3DkoDq19mzZ9GzZ09ERUVh2LBhouNQI1NQUICDBw8iMjISP//8M2QyGfr06YPg4GCMHDnyqda72L17N1599VUsXboU77///lM90bx9+3aEhIQ8cp9UKoWVlRViYmLQpk2bZ76mhlRTU4N27drhzp07kEqlWL16NebNmyc6Vr3Kzs5Gv379kJiYqJ4mytTUFDk5OTA1NUVNTQ1+/fVXhIWFYc+ePWjWrBnGjx+PN998E23bthUbXrAHDx5oTBcUGxuLhIQEqFQqODg4qIuA2imDvL29RUcmIiJqEu7duwdHR0ecPn0aPXv2FB2HiIiIdA9LAqp/ISEhOHPmDBISEmBiYiI6DjVS9+/fx6FDh9SFgYGBAV5++WWEhoZiyJAhMDQ0fOT7goODERUVBeCPNQ927twJa2vrx35OZWUlXF1dce/ePdTU1DzyGJlMhrZt2+LChQuwsrL65xdXj9atW4fZs2dDpVLhypUr6NSpk+hI9SYhIQF9+/ZFbm6uxoLN+vr6+OSTT1BVVYVNmzYhLS0NAQEBmDNnDoYNGwaZTCYwtRhZWVkaZUBsbCzu3bsHABqFgKgnWuoAACAASURBVJ+fH7p27YoWLVoITkxERNR0Xbp0CX5+fkhJSYGrq6voOERERKR7WBJQ/cvOzoaHhwfmzp2L5cuXi45DTUB+fj6ioqIQHh6O6OhoWFpaIigoCMHBwXjllVfUC6KWl5fD1tYWlZWVAP64ud+sWTPs27cPXbt2feS5V65cieXLl2tMM/QoMpkML7zwAo4fP67VC7CWlZXB0dEREokEBQUFTXZu+HPnzmHgwIEoLS1FdXW1xr7a6W9sbGwwYcIETJ06Fe3btxcRU4g/FwIXLlxAbm4ugLqFQLdu3WBnZyc4MRERkW45dOgQBg8ejJKSkmeeWpOIiIjoOWBJQA3jk08+wbJlyxAfHw9nZ2fRcagJuXv3Lnbv3o3IyEhER0fDysoKgwcPRnBwMIqLizFu3DiNxYelUikkEgk2bNiASZMmaZwrKysLrq6uqKioeKrP1tfXx7hx47Bly5bnek3P2+LFi5GYmIjdu3eLjlIvoqKiMGbMGCiVyieWO9HR0ejevXsDJmtYSqUS6enpGlMGnTt3Dvfv34e+vj7c3d01pgsKCAiAjY2N6NhEREQ67+uvv8b8+fNRXFwsOgoRERHpJpYE1DAUCgU6deoEd3d37NmzR3QcaqJu376NH374AT/88ANiY2NhYGCA6urqR04bJJFIMHbsWISFhcHY2BjAH2tobN68GTExMUhKSkJ1dTX09fUhk8nUoxEedZ4VK1Zg8eLF9Xptf6ZQKFBaWorS0lLI5XIUFRUBAEpLSzWm2gH+KD/Onz+Pf//73xq5HzVVkqWlJfT09GBsbAwjIyNYWVnB0NDwqdZ/EGHt2rXqdRae9M+ZTCbD+PHjsXnz5oaKVq+qq6uRlJSkMULgypUrKCsrg1QqhZubm8YIAV9fX073RkREpKU+/PBDbN26FcnJyaKjEBERkW5iSUAN5/jx4wgMDMThw4cxYMAA0XGoiYuLi4Ovr+8TnyyXSqXw9PTE/v376yxaq1AoEB8fj6tXr+Lq1avqm7C1T3gZGRlBoVBAqVRCIpFg+/btGDNmzDNllMvlyM7ORmZmJvLz8/HgwQMUFBSgoKBA48+135eXl6OiogJFRUWPXS+hPpmbm8PQ0BAWFhYwMzODjY2N+mVtba3xfbNmzdC8eXM4OjrC0tLyuWdRqVRYuHAh1qxZ89TvMTQ0RHZ29nNdR6KyshI1NTX1egNeoVAgOTlZoxC4dOkSKioqIJPJ0L59e41CwM/PT118ERERkfZ76623EB0djXPnzomOQkRERLqJJQE1rJEjRyIuLg7Xr19/7EKzRM/D9u3bERoa+pc302UyGUxNTbFr1y7069fvL8+bkZGBK1eu4OrVq7h8+TJiYmKQkZEBAwMDHDt2DD179gTwRwGQlpamfmVmZiIzM1NdCmRnZyM/P1/j3CYmJo+84V77vampKYyMjGBpaQlDQ0OYmZnB1NQUBgYG6sWYjYyM6twgNjAwqDMSoLq6GiUlJRrbampq1CMSysvLIZfL8eDBA1RVVaGsrAwlJSWoqqpCUVERSktLNUqM2iLj/v37KCwsrHNdjo6OaNGiBVq2bIkWLVrAyckJbdq0gbOzM5ydnWFra/uXP/talZWVGDt2LPbu3fvMZcm6deswY8aMZ3rP4+zZswfz5s3DV199hf79+z+Xc1ZVVSElJUWjEIiJiYFcLoeZmRk6deqkni6odlFh/i4lIiJq3CZOnIisrCz89NNPoqMQERGRbmJJQA0rPT0dXl5eWLZsGd555x3RcagJGzRoEI4cOfKXCxADUC/m+/7772Pp0qVPvbhvZWUlEhIScPnyZZw9exYpKSlQqVRITU3FvXv31NPfWFtbw8nJCU5OTmjevLn6a6tWrWBvb49WrVqhWbNmMDIy+vsXrEVqamqQn5+PnJwcdSFy9+5d5OTkqL9mZGQgKytLfZPfwsIC7dq1U5cGrq6u8PDwgI+Pj8ZCugUFBRgyZAjOnj0LiUTyxCmG9PX1YWxsDHNzc5iamsLc3Bw9e/bE2rVr/9H13bhxAzNnzsSJEycgkUiwcuVKvPfee898npKSEvUoldpXUlISlEolLCws0KFDB43RAZ6enk124WkiIiJdNnLkSBgYGGDnzp2ioxAREZFuYklADW/58uX44osvkJKSonHzj+h5KSoqgp2dXZ25+Z9GUFAQtm3bBgsLC/W26upqxMfH49q1a7hx4wZu3LiB+Ph4pKWlQalUQiaTwcXFReMm98Ov5zm9TVNSVVWF9PR0jREXta+UlBT1iIRmzZrBx8cHnp6eKCkpgbGxMVxdXdGsWTOYm5vDysoKpqam6iLA0tISZmZmz/0J+8LCQnz88cf49NNPIZFIoFAooKenh6FDhyIqKuqJ7y0qKsK1a9c0CoHExETU1NTAysoK3t7eGoWAl5cXJBLJc81PRERE2qlPnz5wc3PDxo0bRUchIiIi3cSSgBpeWVkZ2rdvj5EjR+J///uf6DjUBIWHh2P8+PEA/lig91GL7kokEpibm9e5ESuVSuHh4YGhQ4ciMTERsbGxuHz5MsrLyyGTydCqVSt4eXmpp3zx9vaGt7d3kxkFoE0ePHiA+Ph4dSlz48YNXLt2DTk5OQAABwcHjRvrAQEBsLGxee45VCoVIiIiMG/ePBQXF6O6ulpjf8uWLXH37t06uR8uBBISEqBSqeDg4KAxXRALASIiIvLz80O/fv3w0UcfiY5CREREuoklAYmxefNmTJ8+HXFxcfD09BQdh3RYZWUlzp8/j5MnT+LUqVO4ePEiysrKYGRkhE6dOqFLly7o0qWLeroXqVQqOrLOy8rKUs/VX/s1JycHenp68PDwQO/evdGrVy/07t0bDg4O/+izLl68iOnTp+PSpUtQqVSPnd5owYIFSEhIwKVLl3Dv3j0AQNu2beHr66vxat68+T/KQ0RERE2Pi4sLJk+ejIULF4qOQkRERLqJJQGJoVQq0blzZ7i6uv7lNB1Ez1N1dTV+++03nDhxAidPnsTvv/8OuVyONm3a4KWXXkJAQAC6du0Kb29vyGQy0XHpKWVkZCA2Nhbnz5/HqVOnEBMTg+rqari7u6N3797o3bs3+vXrh2bNmj3V+e7du4elS5fim2++gb6+fp3RA39ma2uL7t27q0cHvPDCC7C3t38el0ZERERNnK2tLVauXIlp06aJjkJERES6iSUBifPTTz9h4MCBOH78OF5++WXRcagJKygowPHjx3HgwAEcPHgQDx48gIODA3r06IHAwEAEBATA29tbdEx6jsrKynDu3Dn89ttvOHv2LM6cOQOFQoHOnTtj8ODBCAoKgq+vb51pfhQKBTZs2ID33nsPCoXiqda1kMlkWLVqFRYsWFBfl0NERERNlEqlgoGBAcLDwzFmzBjRcYiIiEg3sSQgsfr164eioiKcP3+ec3LTc5WTk4Pvv/8eu3fvRnR0NPT19dGrVy8MGjQIgwcPhqurq+iI1IBKSkpw9OhRHDp0CIcOHUJubi6cnZ0xZMgQvPbaa/D398fBgwcxe/ZspKWlPdO59fX1ERwcjJ07d9ZTeiIiImqqSkpKYGFhgcOHD2PAgAGi4xAREZFuYklAYl29ehW+vr7Ytm0bn5yhf6yiogL79u1DREQEjh49ChMTEwwbNgxBQUHo168fLCwsREckLVBTU4OLFy/iwIED2L17NxITE+Hq6or27dvD1tYWWVlZSExMxL1799RrEBgZGaGmpgZVVVWPPKezszNSU1Mb8jKIiIioCcjIyEDr1q0RHR2N7t27i45DREREuoklAYn3+uuv4+TJk0hISICRkZHoONQIJSUl4YsvvsCOHTtQXl6OV155BSEhIRg6dCiMjY1FxyMtd/HiRWzbtg07d+5Efn4+XnrpJcyaNQuvvPIKUlNTkZKSgps3byIlJQU3btxAcnIy8vLyAAASiQR6enqoqalBcXExzMzMBF8NERERNSbXrl1Dx44dcePGDXh6eoqOQ0RERLqJJQGJl5mZCXd3dyxfvpxzetMzOXHiBD777DMcPnwYLi4umD59OsaMGYPmzZuLjkaNkEKhwJEjR7B582YcPHgQ7dq1w9y5czFhwgSYmppqHFtWVqZRHqSkpGDhwoVwc3MTlJ6IiIgao+joaAQEBCAjIwNOTk6i4xAREZFuYklA2mHJkiXYsGEDUlJSYGtrKzoOablffvkF7777Li5duoRevXph/vz5CAoKgp6enuho1EQkJyfj888/R3h4OIyMjPDWW29h3rx5HJlCREREz9WJEyfw8ssvIzc3F3Z2dqLjEBERkW4q5h010grvvvsupFIp1qxZIzoKabGkpCQEBQWhb9++aNmyJS5evIhTp05h6NChLAjouXJzc8PGjRuRnp6OWbNm4aOPPoKHhwd27twJdutERET0vCgUCgCATCYTnISIiIh0Ge+qkVYwNzfHu+++i/Xr1yMnJ0d0HNIycrkcb7/9Njp06ICMjAz88ssv2L9/P7p06SI6GjVxzZo1w/Lly5GcnIzAwECEhITgxRdfRGJiouhoRERE1ARUVVUBAAwMDAQnISIiIl3GkoC0xowZM2BlZYWPP/5YdBTSIjdv3kRAQADCwsKwbt06xMbGok+fPqJjkY5xcHDAN998g5iYGNTU1KBr164IDw8XHYuIiIgaOY4kICIiIm3AkoC0hpGRERYuXIivvvoKd+/eFR2HtEBkZCT8/PwAALGxsZgyZQr09fUFpyJd1rlzZ/z222+YOnUqJkyYgAkTJkAul4uORURERI1UVVUVJBIJpFKp6ChERESkw1gSkFaZMmUKWrRogVWrVomOQoJt2rQJo0ePRmhoKM6ePQtXV1fRkYgA/PGk33//+18cOHAA+/btQ1BQEMrLy0XHIiIiokZIoVBAJpNBIpGIjkJEREQ6TKLiCoykZcLCwjBz5kwkJSXB2dlZdBwSICoqCsHBwfjggw+wZMkSIRnOnj2LtLQ0jW1SqRSWlpawsbFBhw4dYGJiot6Xl5eHI0eOqL/v27cvmjdvrvF+uVyOqKgoKJVKAICenh769+8PGxsbyOVybN26FVevXkXLli3Ro0cP+Pv749ixYwgKCnqqzAkJCTh9+jSuX78OGxsbdOnSBYGBgTA2Nv67Pwb6C5cvX0bfvn3Rq1cv/Pjjj1xAm4iIiJ7Jt99+i9mzZ6O0tFR0FCIiItJdxbybQVrn9ddfR+vWrfHhhx+KjkICpKWlYfz48XjzzTeFFQQA8OKLL8LOzg6hoaGYNWsWUlJSUFlZicuXL+Pjjz+Gra0tBg4cqF7A1s7ODv369cOZM2cwbtw4DBs2rM40NIaGhhgwYACOHTuGjRs3olevXrCxsUFhYSF8fX1x4cIFjB8/Hl27dsWmTZtgZmaGX3/99S+zlpWVYd68eQgJCYGLiwuWLVuG4cOH48SJE/Dz88Ply5f/1s+A0+j8tc6dO2Pv3r04fPgwPv30U9FxiIiIqJFRKBRctJiIiIiE40gC0kpbt27FxIkTER8fD3d3d9FxqAENGTIEaWlpiImJgaGhoeg4sLW1hZ2dnboMqHX8+HGEhISgsLAQJ0+exAsvvKDe5+HhgaSkJEyYMAFbtmypc87t27cjMTERK1asAADMmTMHx44dQ3x8vMZQ8xkzZsDAwACff/75EzMOGjQIycnJiIuLqzNqYMWKFVi5ciXOnDkDf3//Z7r2BQsWYM2aNXw6/imsWrUKK1euRHJyMpycnETHISIiokbif//7H1auXImcnBzRUYiIiEh3cSQBaaeQkBC0b9+eowl0zI0bN3Dw4EF8/PHHWlEQAHjsk119+vTBN998g8rKSowcOVLjqXtTU1N0794d3333Hb744otHntPMzEz9/cWLF2FoaFhnLtp33333L+en3bBhAw4fPowlS5Y8clqhuXPnwtTUFJMmTYJCoXjiuR527do1fPXVV099vK5bsGABbG1t8eWXX4qOQkRERI0IRxIQERGRNmBJQFpJX18fS5cuxY4dO5CQkCA6DjWQPXv2wMHBAQMHDhQd5akMHDgQffr0QWZmJiIjIzX2RUVFwcnJCQsWLMAvv/zyxPN4enriypUrmDVrFqqqqtTbW7dujf79+z/xvcuXL4eenh7GjBnzyP3m5uYYPnw4rl27hsjISOzatQs7d+7Ejz/+qD7mxx9/xM6dO7F3714Af6zHMHjwYJSVleH777/XuLbKykpERERg4cKF2LdvHyoqKjQ+Ty6X4+jRo1i8eDHWr1+PW7duaey/ffs2li1bhoqKCty+fRvLly/Hxo0bUVhYCAC4desWPv74Y3z22Wd48OBBnespLi7G5s2bMX/+fKxbt05r5u81MDBAaGgo9uzZIzoKERERNSK1CxcTERERicSSgLTWqFGj4OXlheXLl4uOQg0kLi4O3bp1+8un57VJ9+7dAQAnTpzQ2N6iRQvs3bsXBgYGGDVqVJ2b5Q9btGgRmjVrhnXr1qFDhw74+eef1fv69ev32PdlZWUhLy8PDg4OT3wCrU2bNgCAK1euYODAgVi/fj0mTpyo3h8QEICPPvoI06ZNAwCoVCr07NkTAGBpaQlLS0sAQHp6Ovr16we5XI6ZM2fif//7H3x8fFBZWQngjwKhf//+ePDgAd5++22oVCp07twZUVFRAIDvv/8ePXv2xP/93//h0KFDWLp0KW7evIlZs2Zh4sSJOH36NJYsWYLr16/j3XffRUhIiMZ1pKSkICQkBG3atMH48eOxadMm/Otf/1IXDKJ1794dN2/eRFlZmegoRERE1EgolUro6+uLjkFEREQ6jiUBaS09PT0sXboUP/74I5KTk0XHoQZQWloKc3Nz0TGeiZubGwAgIyOjzj4/Pz988803KCgowNChQ1FSUvLIc7i6uuLXX39Fx44dkZycjAEDBmDgwIFISUl54mfHxcUBAFq1avXE42r337hxA+bm5ujcubPGfgcHB401FXr06KG+roEDB6qLismTJ8PT0xOTJk2Ck5MT5s2bh7S0NPz0008AgIkTJ8LZ2RmjRo2ClZUVZs6ciVdeeQUhISG4e/cuRo8ejcmTJwP448n78PBwbNu2DVOnTkVUVBTS09Oxc+dObNu2DQsXLsThw4dRXFyszjVjxgy88cYb6NevHzp16oRPPvkEt27dwmefffbE628oFhYWAPDY/52JiIiIiIiIiLQRSwLSaiNGjICrqys++eQT0VGoATRv3hyZmZmiYzyT2qfG7ezsHrl/zJgxWLhwIeLj4xESEoLHrRXfoUMHxMbGYu3atbC2tsZPP/2ETp064ejRo4/97Non/B++kf4otZ9pa2sLAI9ciPivFie+efMmjh07hmHDhqm3DRo0CNnZ2Rg+fDjKy8sRGRlZp4CYNm0aKioq1As4167F0KtXL/UxnTp1AvBHOVHLw8MDANT/Pdy7dw/Hjh1DdHQ0Fi1ahEWLFuHQoUPo0qULysvLn5i9oWRkZEAqlaJZs2aioxARERERERERPTWp6ABET6Knp4cFCxZg1qxZ+OCDD+Do6Cg6EtWjHj16YObMmSgpKWk0IwqSkpIAAF5eXo895sMPP8T169exf/9+LF26FB07dnzkcVKpFLNnz8bYsWMxf/58hIeHY9SoUbh9+7a6EHhY7Wemp6c/MePdu3cBAD4+Pk91TY9SuzbIwwsuA4C9vT0AIDo6GgqFAlKp5j8r7du3BwD1aKDaMuLhKaUetUh17fRJtYst146qeOedd7T2JvzPP/+Mbt261fkZEBERERERERFpM44kIK0XGhoKW1tbfPHFF6KjUD0bMWIEpFIpNmzYIDrKU6mqqsLBgwchlUoxfPjwxx6np6eH7du3w9PTEytXrqyzyPHq1as1vre1tcXWrVsxZswYFBYW4uzZs488r6WlJTp37oyysrInrnmQmJgIPT099O3b9xmuTpOxsTEA4MiRI3X25eXlQalUAvijLHhY7Q392umL/q7a0uDSpUt19mnD9D4ZGRmIjIzE+PHjRUchIiIiIiIiInomLAlI6xkaGmLu3Ln46quv8ODBA9FxqB5ZWVlh/vz5WLlyJVJTU0XH+UuffPIJbt68iblz5z5xJAHwx3z1+/fvh7W1dZ2S4MyZM8jOzq7znhEjRgCo+/T+wzZs2ACJRII1a9Y8cv/du3exe/duzJw5E//617/UWeRyucZxKpVKfaP/YbXbvLy8oKenhwMHDmgcd+vWLcTExKBz584wNDSsU2jk5eUBgHoh5L/L3d0d+vr6WLZsGaqqqjTOv3379n907n9KpVJh2rRpaNOmDcaNGyc0CxERERERERHRs2JJQI3Cm2++CX19fWzcuFF0FKpn7733HlxdXTFs2LC/nGu/vikUCvVN7ofJ5XLMmzcPH3zwARYtWoSVK1dq7M/MzHzkPPmurq744YcfoK+vr7G9pqYGoaGhKC0t1di+fft2dOzYEd26dXtsxm7dumHFihUIDw/HyZMnNfYVFxdj8uTJ6NatGz788EP19jZt2kAul+PYsWNQqVTYtWsXoqOjUVRUhKKiIiiVSvUaC7GxsThz5gxsbGwQGhqKuLg4BAcH49dff8X69evx/vvvo3///rC3t8esWbOQlpaGEydOqD9r7969CA4ORu/evQFAfY21aznU/pwBoKKiQr2turpa4zhra2u8+eabOH/+PHr37o0dO3bgu+++w9ixYzFmzJjH/nwawvLly3H06FF8++23j5w6iYiIiIiIiIhIm3HiZGoUzM3NMX36dKxduxbz5s1TT31CTY+BgQH279+Pbt26oV+/fvjpp59gbW3d4DnOnDmDtWvXQqlU4tatW/D19UXbtm2hp6cHuVwOJycnnD9/Hr6+vur3XL58GRs2bEBOTg4mTJiAKVOmIDAwUOO8gYGB+PTTT1FZWaneZmNjg8rKSvTq1Qv/+te/4ODggH379sHOzg779u1TT7XzOIsXL0ZAQADmzp0LPz8/dO7cGenp6Thz5gyGDh2Kd999V2Nh4tdeew1r165Fv3790Lx5c6xZswYBAQHIysrCypUrsXDhQvTv3x/NmzfHgAED8Mknn6Bnz55Yu3YtioqKsGfPHuzZswdt27ZFZGSken2B1atXo6amBqNGjcIbb7yB7OxsVFRUIDw8HBKJBMeOHcOuXbsAACtWrMC8efNw69YthIWFAQA++ugjvPPOO8jPz1dPOfXZZ5/h//7v/+Dp6Yk1a9agpKQE4eHhOH/+PCwsLLB169ZHrtfQUFatWoUVK1Zg8+bNCAgIEJaDiIiIiIiIiOjvkqhUKpXoEERPIzc3F23btsV///tfTJ8+XXQcqmcpKSkIDAyETCbDrl274OfnJzrSc5Wfn6+erz8zMxMtW7aESqXC9evXcf/+fbi4uKBVq1bPfN6ioiLEx8fDyckJrVu3fuxxtZ/l4uICExMTpKSkwMnJSaOAUygUqK6urlPKZWVlIS8vD15eXpDJZHXOXVFRgcTERHh6esLIyOiZr+Gv5Ofn486dO/D09BRWGJaWlmLatGnYsWMH1q9fjzfffFNIDiIiImrcVq1ahS1btiAlJUV0FCIiItJdxSwJqFGZPn06fv75ZyQnJ0Mq5UCYpi4vLw+hoaE4fvw4VqxYgXfeeUf91DqRKDdu3MCoUaOQnZ2NrVu3YuDAgaIjERERUSPFkoCIiIi0QDHXJKBG5e2330ZGRkadhV+pabKzs8OhQ4ewdOlSLFmyBH379sXVq1dFxyIdVVJSgvfeew9+fn6wtbXF1atXWRAQERERERERUaPHkoAaFWdnZwQHB2P16tWio1AD0dPTw5IlS3DmzBmUlJTAz88PkydPRnZ2tuhopCOUSiU2b96M9u3b46uvvsKqVatw/PhxODo6io5GRERERERERPSPsSSgRmfBggW4evUqTpw4IToKNaBu3brh/Pnz2Lp1K44cOQI3Nze89dZbSE9PFx2Nmii5XI5vv/0WHTt2xIwZMzBq1CikpKRg3rx50NfXFx2PiIiIiIiIiOi5YElAjY6vry9efPFFrF+/XnQUamASiQRjx45FUlISli5dih9++AGurq4YM2YMLl68KDoeNRH5+flYuXIl2rRpg2nTpqFr1664du0a1q5dC1tbW9HxiIiIiIiIiIieK5YE1CjNmDED+/btw927d0VHIQGMjY2xYMECpKam4rvvvkNycjL8/f3RvXt3rF+/Hvfv3xcdkRoZpVKJn3/+GSEhIWjdujU+//xzvPHGG7h9+za+++47uLu7i45IRERERERERFQvWBJQo/Sf//wHzZo1w6ZNm0RHIYFkMhnGjh2L2NhYnDhxAu3bt8fChQvh6OiIYcOGYffu3ZDL5aJjkha7cuUK5s+fj1atWmHgwIFIS0vD559/jjt37mDVqlVwcHAQHZGIiIiIiIiIqF6xJKBGycDAAJMmTcKmTZt4E5gAAC+99BLCw8ORm5uLbdu2QalUYvTo0bCxsUFQUBDCwsKQlZUlOiYJplQq8dtvv2HhwoXw9PRE586dsXv3boSGhiIpKQlnz57F1KlTYWpqKjoqEREREREREVGDkKhUKpXoEER/R1ZWFtq2bYvvvvsOr732mug4pIWysrKwb98+HDhwACdOnEBVVRX8/f0RFBSEwMBA+Pr6QiqVio5J9SwjIwO//vorDh06hCNHjqC4uBg+Pj4YPHgwhg4dihdeeAESiUR0TCIiItJBq1atwpYtW5CSkiI6ChEREemuYpYE1Kj95z//wb1793D27FnRUUjLlZWV4dixYzh48CAOHTqE7OxsmJubo0ePHujVqxd69+6Nrl27sjRoAtLS0nD69GmcPHkSp06dQlpaGgwMDNC7d28EBQVh8ODBcHZ2Fh2TiIiIiCUBERERaQOWBNS4nThxAi+//DJiYmLg5+cnOg41EiqVCjdu3MCpU6dw+vRpnDp1CtnZ2TA1NYW/vz+6du2KLl26oEuXLryZrOWKiooQGxuLmJgYxMTEYKjj1AAAIABJREFU4Pz588jIyICRkRH8/f3x0ksvoXfv3ujWrRtMTExExyUiIiLSwJKAiIiItABLAmr8OnbsCH9/f3z99deio1AjlpiYiNOnT+PcuXOIiYlBQkIClEolbG1t1YVBx44d4eXlBTc3NxgYGIiOrHMyMjKQkJCA69evq4uBlJQUqFQqODg4oEuXLujatSt69+4Nf39/GBkZiY5MRERE9EQsCYiIiEgLsCSgxm/Dhg1YsGABMjIyYGtrKzoONRFlZWW4cuWK+gn12NhYJCcnQ6lUQiqVwtXVFd7e3vD09IS3tzfc3d3h7OwMKysr0dEbtaqqKqSnp+PmzZuIj49HYmIirl+/joSEBBQXFwMAmjdvDl9fX3V54+fnh5YtWwpOTkRERPTsWBIQERGRFmBJQI1faWkpnJycsGTJEixYsEB0HGrC5HI5EhMTNW5cx8fH49atW1AoFAAAGxsbODs7o127dhpfW7VqBUdHR1haWgq+CrHkcjlycnJw9+5d3L59G6mpqUhNTUVaWhpSU1ORmZkJpVIJAHBwcICXlxe8vLw0ChmWgURERNRUsCQgIiIiLcCSgJqGWbNm4ciRI0hKSoJEIhEdh3RMVVWV+iZ37deH/1z7BDwAGBsbo2XLlmjRooX6q6OjI+zt7WFjYwNra2vY2NioX4aGhgKv7K+pVCoUFBTgwYMHKCgoUL/u37+P7OxsZGZmanzNz89Xv1cmk6F169Zo165dnVLF1dWVozKIiIioyWNJQERERFqgWCo6AdHz8Prrr2PdunU4d+4cXnzxRdFxSMcYGBjA3d0d7u7uj9x///59ZGVl4e7du+qn6HNycpCZmYmLFy8iMzMT+fn5KCsrq/NeU1NTdWFgZGQEc3NzmJqawsDAANbW1jA0NISJiQnMzc0hlf7xK93CwgL6+voa57G2ttb4vry8HHK5XGNbcXGx+in+oqIiVFVVoaSkRH3sgwcPUFVVhbKyMhQVFakLgT+TyWSwsbFB8+bN4eTkBEdHR/j7+8Pe3h5OTk4a2/+ck4iIiIiIiIiIGhZLAmoSfH190aFDB4SHh7MkIK1ja2sLW1tbdOjQ4YnHyeVy9Y33Pz+ZX1BQgMrKSpSUlKCsrAxyuRypqamorKxERUWF+ga/SqVCYWGhxnmrq6tRUlKisc3Q0FA9SqH2Rr2JiYl6m7m5OQwNDWFhYaHe3q5dO3UpYWlpqTHi4eGXubn58/rRERERERERERFRPWNJQE3GuHHj8OGHH+Lzzz+HsbGx6DhEz8zQ0BAODg5wcHBokM/r06cPnJ2d8fXXXzfI5xERERERERERkfbREx2A6HkZO3YsSktLcfDgQdFRiBoFDw8PJCYmio5BREREREREREQCsSSgJsPR0RGBgYEIDw8XHYWoUfDw8EBCQoLoGEREREREREREJBBLAmpSQkND8fPPPyM7O1t0FCKt5+HhgYKCAuTl5YmOQkREREREREREgrAkoCZl+PDhMDU1xffffy86CpHW8/DwAABOOUREREREREREpMNYElCTYmxsjJEjR3LKIaKn4OTkBDMzM045RERERERERESkw1gSUJMzbtw4XL58GXFxcaKjEGk1iUQCd3d3JCUliY5CRERERERERESCsCSgJqd3795o164dtm3bJjoKkdbz9PTkdENERERERERERDqMJQE1ORKJBGPHjsX27duhVCpFxyHSau7u7pxuiIiIiIiIiIhIh7EkoCYpJCQEWVlZOHnypOgoRFrNw8MD6enpKC8vFx2FiIiIiIiIiIgEYElATZKbmxs6deqE3bt3i45CpNU8PT1RU1ODlJQU0VGIiIiIiIiIiEgAlgTUZI0cORJRUVGccojoCdq3bw+pVMp1CYiIiIiIiIiIdBRLAmqyXn31VeTk5OC3334THYVIaxkYGMDZ2ZklARERERERERGRjmJJQE2Wu7s7vL29OeUQ0V/w8PBgSUBEREREREREpKNYElCT9p///AeRkZGoqakRHYVIa7EkICIiIiIiIiLSXSwJqEkbMWIEsrOzcfHiRdFRiLSWh4cHkpKSWKYREREREREREekglgTUpHXs2BFt27bFwYMHRUch0loeHh6oqKjAnTt3REchIiIiIiIiIqIGxpKAmrxBgwaxJCB6Ai8vLwBAQkKC4CRERERERERERNTQWBJQkxcUFIQrV64gPT1ddBQirWRlZQV7e3uuS0BEREREREREpINYElCT99JLL8Hc3ByHDx8WHYVIa3l6eiIpKUl0DCIiIiIiIiIiamAsCajJMzQ0RGBgIKccInoCDw8PTjdERERERERERKSDWBKQThg0aBBOnDiByspK0VGItJK7uzunGyIiIiIiIiIi0kEsCUgn9O3bFxUVFYiOjhYdhUgreXp6Ijc3F/fv3xcdhYiIiIiIiIiIGhBLAtIJrVu3hpubG44dOyY6CpFW8vDwAACuS0BEREREREREpGNYEpDO6Nu3L3755RfRMYi0UuvWrWFiYsIph4iIiIiIiIiIdAxLAtIZgYGBuHTpEvLz80VHIdI6enp6cHNzY0lARERERERERKRjWBKQznj55Zehr6+PEydOiI5CpJU8PDxYEhARERERERER6RiWBKQzLCws4Ofnx5KA6DFYEhARERERERER6R6WBKRTevbsiTNnzoiOQaSVPDw8kJqaCrlcLjoKERERERERERE1EJYEpFN69OiB+Ph43L9/X3QUIq3j4eEBpVKJlJQU0VGIiIiIiIiIiKiBsCQgndKjRw9IJBJER0eLjkKkddzd3aGvr6+ecqioqAgXLlzA1q1bkZaWJjgdERERERERERHVB6noAEQNycbGBp6enjhz5gyCgoJExyHSCnfu3EFSUhISExNhamqKt99+G9OmTUN+fr76mOTkZIEJiYiIiIiIiIiovrAkIJ3DdQmI/rBmzRp88MEHKC8vBwDIZDKoVCoUFxdrHGdsbAwXFxcREYmIiIiIiIiIqJ5xuiHSOQEBAbh06RIXZyWd99prr6G6ulr9vUKh0Pi+lpeXF/T0+M8FEREREREREVFTxLs+pHO6du2KqqoqXL16VXQUIqGcnJwwd+5cyGSyxx4jk8nQtWvXBkxFREREREREREQNiSUB6Rw3NzdYWVnh4sWLoqMQCbdo0SIYGxs/dr9KpUKnTp0aMBERERERERERETUklgSkcyQSCXx9fRETEyM6CpFwVlZWWLx4MfT19R+5v7q6miUBEREREREREVETxpKAdFLXrl1ZEhD9f2bPng07OztIJJI6+yQSCby9vQWkIiIiIiIiIiKihsCSgHRSly5dcOPGDZSUlIiOQiSckZERVqxY8ciSwMnJCRYWFgJSERERERERERFRQ2BJQDrJz88PNTU1uHbtmugoRFrh9ddfh4uLC/T0/v9/FvT09ODn5ycwFRERERERERER1TeWBKST2rZtC3Nzc1y/fl10FCKtoK+vj9WrV6Ompka9TSqVonPnzgJTERERERERERFRfWNJQDpJIpHAy8sL8fHxoqMQaY3hw4eja9eukEqlAACFQsFFi4mIiIiIiIiImjiWBKSzfHx8OJKA6E8+/fRTVFdXAwBUKhVLAiIiIiIiIiKiJo4lAeksb29vxMXFiY5BpFV69uyJ/v37AwBMTEzQpk0bwYmIiIiIiIiIiKg+sSQgneXj44P8/Hzk5uaKjkKkVVavXg2JRIIOHTpAIpGIjkNERERERERERPVIKjoAkSg+Pj4AgBs3bsDe3l5wGiLt0bFjR4wdOxYWFhaioxARERERERERUT1jSUA6y8HBAWZmZrh16xZeeukl0XGI6p1KpUJhYSEUCgVKS0tRUVGByspKAEBhYSFUKpX62P79++PKlSuIjIyscx6JRAIrK6s62w0MDGBqagoAMDc3h1QqhbW1NaRSKczNzevpqojoSWr/3iuVShQXF6OqqgplZWUAgPLycsjl8jrvKSsrQ1VVVZ3tMpkMZmZmdbY//HffxMQEhoaG6t8BVlZWHJFERERERESk5VgSkE5zdnZGamqq6BhET6WoqAj37t1DXl4eCgoKUFhY+MRXcXGx+iZgcXExlEql0PxGRkYwNjaGmZkZDA0NYWVlBSsrK1hbW6v//OeXjY0NHBwcYG9vD2NjY6H5iRpaZWUl8vLykJOTg/v376OoqAiFhYV48OABioqKNF6FhYUoKipCWVkZSktLoVAoUFRUhJqaGtGXoS4WawtDExMTWFpawsrKCpaWlupX7e+D2u9tbGzQokUL2NnZ8e8/ERERERFRPWJJQDrNxcUFt27dEh2DdFxBQQHu3LmDjIwM3L59G7m5ucjKykJubi5yc3PVxUDtU/+1TExMHnlj3dHREVZWVrCwsICpqSkMDAxgaWkJfX19jRt1tTftAaiP+zNra+s622pHIvzZw08fFxcXo7q6GoWFhaiurkZJSQnkcjnKy8tRVlaGyspKdZnx4MED3L59u07JoVAoNM5vbm4OR0dH2NnZwd7eXl0etGzZEq1atULr1q3Rpk0b3kwkrZefn4+7d+8iIyMDd+7cQU5ODnJzc5GTk4O8vDzk5eXh3r17KCkp0Xhf7c32h2+kW1lZwdbWFu3atYOlpSVMTU3VT/FbWlpCT08P1tbW0NfXh4WFhcZogIdHADzM0NAQJiYmdbY/PProYQ+PSKgtKGqLycLCQtTU1GiMZigvL9coN+7du1enAPlzuWFmZoYWLVrA3t5e/TugtkBo06YNnJyc4OTkxOkDiYiIiIiI/gaWBKTTXFxccOrUKdExqIkrLS1FcnIykpOTcfPmTfWNwTt37iA9PV099QcA2NnZoUWLFmjRogWaN28ONzc39c1we3t79U1yW1vbR97UbwgymeyR5cGjtv0TZWVluH//PrKystRPU9cWJjk5Obh27Rpyc3ORkZHx/9i777Ao7sR/4G86iHSVLkiRUKUoSMCoBDSaoBhFgwpqYlAvyanxot55F/GJMZrcJXp3MWrsxooFWzzFLnZROsgiIE0BpUlflvn94Y/9SsSuDOX9ep59ArOzO++BzCZ83jOfeexn2LNnT5ibm8PCwgI9e/aEra0t7Ozs0KtXL6ioqLzWnER/lJ+fj4yMDEgkEvmxnpubKy8Gampq5OsaGBjIB7+NjIzg4eEh/xxoGhA3NDREt27dRL9PiIaGRosl3Os+9gHgwYMHuH//Pu7evdusOGn6+tatW7h48aK8WGmirq4Oc3NzmJmZycvDnj17wsbGBra2tjAzM3vtWYmIiIiIiNo7lgTUqVlbW2PDhg1ix6AOIisrCykpKbh586a8FEhPT0d+fj6Ah4PrTYPW5ubm8PLykg9iNQ1o8yz4/6OpqQlNTU307Nnzmev+8WqM3Nxc5Obm4urVq9i1axfu3LkD4OHvwNLSEnZ2drCzs4OtrS169+6NPn36QF9f/03vEnUgpaWlSEpKkpd/EokEGRkZyMjIkJdWXbt2haWlpXyQeuDAgfKz3k1NTXnMP4WWlha0tLRgaWn5zHVramrkJUxeXh5ycnLkX1+/fh23b9+WX5WhoaEBW1tb2NjYyIsDGxsbODs7w8DA4A3vFRERERERUdukIDx6p0qiTubo0aN47733UFpa2uKNWIlaUl9fD4lEgtjYWMTGxiIlJQVxcXG4d+8egIdn1VpZWcHBwQGOjo6wsrKSf88BQXHU1dUhIyMDKSkpyMzMRGZmJpKTk5GUlITy8nIAD39vDg4O8PDwgIeHBxwdHeHs7CzaFRvUNkilUqSnpyMlJQXJycnyYz4rKwuCIEBVVRVmZmYtHvOWlpZQVFQUexcID0udpmO/6fhPSUmBRCJBRUUFgOafAY6OjnBwcIC7u3uLUy8REb0uS5YswYYNGyCRSMSOQkRERJ1XBUsC6tSSk5Ph5OSE5ORkODg4iB2H2qDGxkYkJyfj4sWLuHjxIi5dugSJRAKZTAYtLS04OzvDxcUFrq6ucHFxgZOTE7S0tMSOTS/gzp07SExMRFxcHOLj45GQkIC0tDQ0NDRAQ0MDffr0gbe3t/zB6Uo6roaGBiQlJeHSpUu4cuUKrly5gps3b6KhoQGqqqqwt7eHs7MznJyc4OLiAkdHx+e60oXatry8PCQnJyMhIQFJSUlISkpCSkoKamtroaSkhN69e8PT0xOenp7o378/nJ2dOW0ZEb02LAmIiIioDWBJQJ1bSUkJDAwMEB0dDX9/f7HjUBtQXV2NmJgYnD9/HhcvXsTly5dRUVGBrl27wtPTE97e3nBzc4OrqyusrKygoKAgdmR6A+rq6uSDhteuXcOFCxeQmJiIhoYGmJmZ4e2334a3tzd8fX3h7u7Os8XbqeLiYpw9exaXLl3C5cuXERsbi+rqamhpacHDwwNeXl5wc3ODk5MTevfuzYHhTkQmk0EikSAxMRHx8fG4fPkyrl69ivLycmhoaMDd3V1eGrzzzjswMjISOzIRtVMsCYiIiKgNYElA1KVLF6xatQphYWFiRyERNDY24saNGzh+/DiOHz+OmJgY1NbWwtjYGL6+vvDx8YGHhwc8PT057UwnV1VVhRs3biA2Nhbnz5/H6dOnUVxcDAMDA/j5+cHf3x8BAQHo1auX2FHpCSorK3Hp0iX58X7jxg0oKCjAzs5OPs1UUznAQoBakpmZiZiYGPl0c9euXUNdXR2srKzg7+8Pf39/vPvuu7zHCRE9N5YERERE1AawJCCysrLCtGnTMG/ePLGjUCupqKjAwYMHsX//fpw8eRL379+HkZGRfIAnICAAJiYmYsekNk4QBCQmJiI6OhrHjx/H2bNnUV1dDVtbWwwZMgQffvghBg4cCCUlJbGjdlqCICA2NhZRUVGIjo5GbGwsBEGAs7Mz/Pz84Ofnh4EDB3KKMHpplZWVOHfuHE6dOoWTJ0/KiydXV1cEBAQgKCgInp6evOqMiJ6IJQERERG1ASwJiHx8fNCvXz8sX75c7Cj0BpWVleHAgQPYvXs3jh07hsbGRgwePBhDhw5FQEAAnJycOIhDr6Surg7nz59HdHQ0fv/9dyQkJKB79+4YNWoUxowZg8GDB0NZWVnsmB2eTCbD2bNnsW/fPuzfvx85OTmwsLDA8OHD4efnh0GDBqFbt25ix6QOqqSkBGfOnMHJkyfx+++/IzMzE6amphg5ciSCgoIwaNAgXqVCRM2wJCAiIqI2gCUB0ZgxY6CoqIhdu3aJHYVeM5lMhsOHD2Pt2rU4evQoFBQU4O/vjzFjxmDEiBGcDoLeKIlEgt27d2P37t24fv06DAwMMHbsWEybNg19+vQRO16Hc/nyZaxfvx579uzB/fv34ezsjKCgIAQFBcHd3V3seNRJJSQkYN++fYiKikJcXBz09PQQFBSETz75BD4+PmLHI6I2gCUBERERtQEsCYimTZuGzMxMREdHix2FXpO8vDysW7cOa9euRUFBAfz9/REaGorAwEDo6OiIHY86oaysLERGRmLDhg1IS0uDl5cXpk2bhnHjxqFLly5ix2u37t27hy1btmDdunVITk6Gk5MTwsLCMGrUKNjY2Igdj6iZrKwsREVFYcuWLbhx4wbeeustfPzxxwgLC4OhoaHY8YhIJCwJiIiIqA2oUBQ7AZHYdHV1UVZWJnYMeg0SEhIwevRoWFpaYuXKlZgwYQLS09Nx9OhRTJw4kQUBiaZXr16YO3cuUlJScOrUKfTq1QszZsyAqakp5s+fj/v374sdsV1JTk7GhAkTYGpqioiICPj4+ODy5ctITEzEV199xYKA2qRevXph9uzZuH79OmJjY+Hn54clS5bA3NwcY8eORVxcnNgRiYiIiIiok2JJQJ2ejo4OS4J2LjU1FePGjYObmxuysrKwdetW5ObmYunSpbC2thY7HpGcgoICBg0ahO3btyM3Nxfz5s3D+vXr0atXL/zjH/9AaWmp2BHbtPj4eAQHB8PFxQUJCQlYvXo1CgoKsHr1anh6eoodj+i5ubu74+eff0ZBQQHWr1+PjIwMuLu7Y+TIkbh27ZrY8YiIiIiIqJNhSUCdno6ODsrLy8WOQS/h3r17mDx5MpycnJCamorIyEjExsZi3LhxUFVVFTse0VN1794d8+fPR2ZmJv7617/il19+gZWVFf75z39CJpOJHa9Nyc7Oxocffgg3NzdkZGQgMjIS8fHxmDx5MjQ1NcWOR/TSNDQ0MHHiRMTGxmL//v24e/cu+vXrh/fff59TjxARERERUathSUCdHqcbap/27t0LJycnnDx5Etu2bUNcXBw+/PBDKCgoiB2N6IV07doVf/3rX5GZmYmZM2fiH//4B3x8fJCamip2NNHJZDKsWLECzs7OuHnzJvbv34/r16/jww8/hKIi/xeGOg4FBQUEBgbi8uXL+N///oeCggL06dMHy5YtQ0NDg9jxiIiIiIiog+Nf2NTp6ejoQCqVoqqqSuwo9BzKy8sREhKCMWPGIDAwEElJSRg3bhwHDKnd09bWRkREBGJjYyEIAtzd3fHjjz9CEASxo4ni5s2b8PHxwdy5czFnzhzcuHEDgYGBLAKpwxs6dCiuXr2Kr7/+GosWLYKnpycSExPFjkVERERERB0YR9Wo09PQ0AAA1NbWipyEniUnJwe+vr44c+YMjhw5gl9//RXa2tpixyJ6rRwcHHD+/Hl8/fXXmDdvHqZMmQKpVCp2rFZ19OhReHl5QRAEXL9+HREREZxCjDoVZWVlzJ8/H/Hx8dDU1MTbb7+N/fv3ix2LiIiIiIg6KGWxAxCJrWngqbMNwrU3d+/ehZ+fHzQ0NHD58mWYm5uLmue333575jr6+voYPnx4s2X5+fmIjIyERCKBgYEBBg0aBG9vb+Tk5EAmk6GkpATZ2dny9RUUFNCjRw/06tULFhYWUFFRaXFbhw4demzarGHDhsHAwED+/fXr15GSkiL/XkNDAzU1NS+8rXPnzuH27dtP3XcXFxe4uLg8dR0AKC0thY+PD+bNm4dJkyahoaEB+/fvxy+//ILAwEDMnDnzme/RESkrK+Ovf/0r3NzcEBwcjPr6evz222+d4oqZQ4cOYfTo0fjoo4+wZs0aqKmpiR2pzR3vf/Ss7Tg4ODz3vj7vMcjPgdZha2uLkydP4osvvsCYMWOwbds2BAcHix2LiIiIiIg6mI4/2kD0DE2DMPX19SInoSeRSqUYNWoUlJWVceLECdELAgCYNWsW0tPTUVZWhvT0dISGhmLNmjWoqKjAnTt3sGXLFsyZM6fZa7777jv0798fdXV1CA8Px8yZMyGVSjFs2DAMGDAA6enp8PHxgYGBAUJDQzF79mzcuXMHFy5cwIgRI9CzZ08cO3asxTwDBgzApUuXEBoaihkzZsDV1bVZQQA8PEM9OTkZkyZNgpqaGoKCgl5qW76+vjAxMUFoaCj+/ve/o2vXrujatSvU1dVx//59fPPNN9i2bdtz/RyVlZVhYGCArl27AgDy8vJQUFCAEydOsLgD8N577+HAgQPYt28fFi1aJHacNy4uLg7BwcGYNGkSNm7c2CYKAqDtHe8vup0mdXV1z3y/5z0G+TnQelRUVLBq1Sp89tlnmDBhAi5evCh2JCIiIiIi6mgEok4uNjZWACBkZGSIHYWeYPHixYKmpqaQkpIidhS5M2fOyL9OTU0VAAgzZsyQL2tsbBQmT54s//6nn34SVFRUhJiYmMfeq6amRvDy8hLWr18vX6atrS04OjrKv79//75gY2MjKCgoCDdu3GgxU3V1tWBoaCgoKysLJSUlLa6zfPly4Ysvvmi27GW2JQiCoKGhIbi4uDy2vKCgQJg9e/YTX/cs9+7dEwAIP/zww0u/R0ezcuVKQUlJSbh27ZrYUd6Y+vp64a233hL8/PyEhoYGseM00xaP95fZzpw5cwSZTPbM/X2RY5CfA62nsbFReP/99wVLS0uhpqZG7DhE9Jp8++23go2NjdgxiIiIqHMr55UE1OnxSoK2raKiAj/88APmz58Pe3t7sePI+fr6PvV5BQUFTJ8+HQCwfft2zJ49G9988w18fHweW1ddXR3/+c9/UFJSIl+mqqra7Aat+vr6GDduHARBwI4dO1rcpoaGBmbMmIGGhgbs3bu3xXUOHDiAr776qtmyl9lWU+6WGBsb47PPPnvi655FWZkz4f3RjBkz0K9fP0RERIgd5Y3ZtGkTsrKysG7dOigpKYkdp5m2eLy/6HYSExOxatWqZ+8sXuwY5OdA61FQUMDatWtRXFz83L9LIiIiIiKi58G/wKjTa7onAUuCtunIkSOorq5+pcGmN+F55ob38vICACxevBgAHpuv/FH9+vWDIAhPfb+mmzTn5eU9cZ3p06fju+++w3/+8x988sknzZ5LS0uDtrb2c03X9DzbasmVK1fQt29fWFtby5dJJBL8/vvvKCsrg6enJ4YNGyZ/rra2FpGRkTA0NMSQIUMAoNlgKQDs3LkTjY2NUFFRwZgxYwAAu3fvhlQqhYaGBoKCggAAt27dwsaNGxEREYEjR44gJSUFs2fPhoqKCioqKrBz506kpqbCysoKkydPlk9tAgAxMTE4cuQIzM3NoaioiPDw8Bfa79Ywe/ZsTJgwASUlJdDX1xc7zmu3ZcsWBAcHw9LSUuwoj2mLx/uLbOf8+fMYP348qqqqsGPHDqioqCA4OPiJx8wfj8EXxc+BN8fIyAihoaHYsmULZs2aJXYcIiIiIiLqIHglAXV6TWesymQykZNQS65fvw4XFxfo6emJHeWlZGRkICUlBcrKyrCzs3vqup6enk99fvv27QCAd99994nrGBoa4qOPPkJ8fDxOnz7d7LnVq1fLz3Z+lufZ1h81NDTgm2++aXYs/fnPf8Ynn3yCiRMn4u2338b777+PZcuWAXhYWoSEhCAsLAxxcXFPfN/hw4fj559/blZ6+Pj44LvvvsOMGTMAAJs3b4avry8WL16M3377DV9//TXmzZuHq1evQiKRYOLEibCwsMCkSZOwevVx9giYAAAgAElEQVRquLq6ym/0PG/ePOTk5GDBggXQ1dV9bG75tmLQoEFoaGhAQkKC2FHeiGvXrsHPz0/sGK+ktY73F92OIAgYMGAAAEBHRwc6OjpPPWZeBT8H3jw/Pz/ExcXxfg1ERERERPTasCQgojatoqICOjo6Ysd4adnZ2QAAGxsb+VUrz+vBgwe4du0azp8/j5CQEMTFxWHy5MmYPHnyU183c+ZMAMCKFSvky2pqahATEyM/S/d1bevWrVsYOHAgBg4cCGNjYxw6dKjZ85s3b8bQoUNhYGCAgIAA2NvbIyoqCgDw1ltv4eeff37GTwHQ0tKCm5tbs2XGxsbyM7cBICwsrNng4fXr15GWlgZvb2989tln+PjjjzFkyBD06dMHP/zwA27duoUff/wRUqkU69atQ9++fdGlSxd89NFHj12B0Vbo6uoCAMrLy0VO8vpJpVLU1NTI97G9aq3j/UW34+vri969ewN4ONg+ZMiQpx4zL4qfA61LT08PjY2NePDggdhRiIiIiIiog+B0Q0TUphkbGyM6OlrsGC/tVebVVlJSwu3bt5Gbm4shQ4Zg/vz56NOnzzNf5+bmhgEDBuDAgQPIyspCr169sHPnTgQHBz9xGpGX3Za1tTXOnDkD4OGUXaGhoc2eP3z4sPxeEleuXIEgCKipqZE//+hUH0/T0nQvf1ymoaEBAAgJCQEA2NnZ4c6dO4iOjoarqysuX74MAKisrETfvn1RXV0NFRUVaGlpwd/fH6tXr8awYcOwYMGC58rU2rKysgAAJiYmIid5/VRUVNC9e3f5PrZXrXW8v675+ls6Zl4GPwdaV2ZmJjQ1NdvtFXZERERERNT2sCQgojbNz88PCxcuRGJiIpydncWO88JsbW0BPJyPu6amRj6A9Ty6dOmC0aNHv9R2Z86ciXPnzuG///0v/vWvf2HDhg3Ys2fPG9lWE1VVVfzpT39qNmjn4+ODffv2Ye/evRg6dCgsLS2Rn58vf/555np/Xi0VIBKJBAAwd+5cdOvWrcXX/fe//0VoaCiGDx8Ob29vbNy4Ed27d39tuV6XqKgo6OvrP3Y2dUcREBCAPXv24MsvvxQ7yktrreP9VbbzqFe990BL+Dnw5u3evRv+/v5v5PdHRERERESdE6cbIqI27e2334aLiwsWLlwodpSXYmpqCkdHR8hkMiQlJT113WfdyPRFBAUFwcLCAuvWrcO5c+dgbm7+xMGx12ngwIHy+3wADwfl1q9fj19//RUTJ06EmpraG8/wqKapWK5fv/7Yc01Tdbz//vvIyMjArFmzEBsbi759+yI1NbVVcz5LWVkZfvzxR0ydOvW1nUXe1nz22We4cOECDh48KHaUl9Zax7tYnyvPi58Db87JkycRHR2Nzz//XOwoRERERETUgbAkIKI2TVFREf/85z8RFRWFDRs2iB2nRU2DcE8ajFu0aBGAhwNl9fX1La5TXFzcbP8EQXilwT0lJSV8/vnnKC8vx9ixY+U39mzJq2zraa+LjY3FDz/8gM8++wzq6urP9Zon0dbWRl1d3WPbftYNx+3s7KCkpISFCxc2+9kXFxdj69atqKqqwq+//gp9fX389NNPOH36NCorK+U3jW0LBEFAeHg4lJWVMW/ePLHjvDHe3t6YOHEipk6ditzcXLHjPFFbOd5fZjsAnnnMvAx+DrSOwsJCTJo0CaNGjYK/v7/YcYiIiIiIqANhSUBEbV5AQADmzZuH6dOn43//+5/YcR5z9+5dAA/nuG7J6NGjsXjxYpw5cwaffvopqqqqmj2fk5ODpUuXyufxrq+vR2lpKSoqKl4p19SpU6GpqYnu3bvDx8enxXVedluNjY2oqqpCWVnZE9fp0qULgIfT5DQ0NOD48eOIj49HaWkpJBIJsrKy5D+zR38mLS2zsLBAXV0doqOjIQgCdu7ciQsXLqC8vBzl5eWQyWSQSqUAgPv378tfp6enh+nTp+PSpUsYOHAgtm3bho0bN2LChAkICQlBY2MjFi5ciNraWgAPB6ptbW3b1DQjc+bMQVRUFLZs2QJ9fX2x47xRv/zyC3r06AF/f38UFBSIHadFbeV4f9HtNP07HRsbi3PnzqG2trbFY+bRffvje/4RPwdaT3FxMQICAqChoYF169aJHYeIiIiIiDoagaiTk0gkAgAhNjZW7Cj0FI2NjcKUKVMEVVVVYdOmTWLHkdu6davQr18/AYCgq6srLF68WMjNzW1x3d27dwtOTk6ChoaGMHDgQOGzzz4TPv30UyEiIkKoq6sTBEEQzpw5I3z44YcCAAGAMGPGDOHKlSsvnW/GjBnCypUrW3zuZbd1+vRpYezYsQIAQUFBQZgzZ84TXxcaGiooKioKhoaGwqpVq4TFixcLioqKwl/+8hchJydHmDFjhgBAcHBwEI4cOSIUFBQ0WxYVFSUIgiBUVVUJTk5OAgDB0NBQ2LRpkxAeHi7o6ekJf/nLX4TVq1cLdnZ2AgAhODhYiI+Pl2eoqqoSwsLC5Pupra0t7Nu3TxAEQaioqBA0NDQEZ2dn4d///rcQEREhTJkyRaivr3/RH/VrV19fL0yZMkVQUlIStm/fLnacVnP37l3B3t5eMDc3b3Ofy23xeH+e7QiCIGRmZgqGhoaCnp6esHbtWmH37t0tHjNPOgb/iJ8DrScpKUmwsrISrK2thZycHLHjENFr9u233wo2NjZixyAiIqLOrVxBEESYrJaoDcnIyICtrS1iY2Ph7u4udhx6CkEQsGjRIixatAjBwcH45ZdfYGBgIHasF1ZVVYXExETY2Ni88fsEFBUVoWvXrvKzecVQXFwMXV1dqKioAABKS0uhp6f3wu8jCAKSkpJgbW2NLl26QCKRwMzM7Llv2nrv3j3k5OTA3t5e/hpBEFBTUwOZTAaJRILevXuja9euL5ztdUtOTsbkyZORlpaGbdu2ITAwUOxIraqiogLjx4/HsWPH8OWXX2LRokWtPo/969Jax/vzbEcqlaKhoeGlb3T8Kvg58OIaGhrw888/Y8GCBejTpw/27t0LQ0NDsWMR0Wu2ZMkSbNiwQX6TdSIiIiIRVLAkoE6PJUH7c+TIEXz66aeQyWRYtWoVRo4cKXYkoteioaEB//rXv7Bw4UK4u7tjw4YNsLOzEzuWKBobG7F27VrMmTMHlpaWWLt2Lby8vMSORdQqEhISMHXqVCQmJmLevHn429/+Jr8BMxF1LCwJiIiIqA2o4D0JiKjdGTZsGBISEuDn54egoCCMGjUKCQkJYsciemmCIGDv3r1wc3NDREQEvv32W8TExHTaggB4eNPy8PBwxMfHw8jICD4+Ppg4cSJSUlLEjkb0xkgkEnz88cfw8PCAuro64uLiEBERwYKAiIiIiIjeKJYERNQu6evrY+vWrTh8+DBu374NNzc3jB07FsnJyWJHI3pugiBg//79cHd3R3BwMBwcHBAfH485c+ZAUZH/iQYAKysrHDt2DFu3bkVcXBycnZ0xduxYxMfHix2N6LVJSUnBxIkTYW9vj/Pnz2PdunU4c+ZMpy4KiYiIiIio9XAEgojateHDhyM2NhaRkZFIS0uDi4sLgoKC8L///Q+NjY1ixyNq0YMHD7B69Wq4ublh1KhRsLKyQlxcHHbu3InevXuLHa/NUVBQwLhx45CQkIBdu3YhPT0dbm5uGDp0KCIjI1FXVyd2RKIXJpVKsW/fPnzwwQdwdnZGXFwcNm/ejJSUFISFhUFBQUHsiERERERE1EmwJCCidk9BQQEffvihfJC1vLwcw4cPh42NDb777jsUFhaKHZEIABAXF4fp06fD1NQUs2fPhqurK65fv449e/bA2dlZ7HhtnqKiIkaPHo0bN27gwIEDUFZWRkhICMzMzPDll1/ySiJqF9LS0jB37lyYm5tjzJgxkEql2L17NxISEjB+/HgoKSmJHZGIiIiIiDoZ3riYOj3euLhjSktLw5o1a7Bp0yZUVlYiICAAo0ePxsiRI6Gvry92POpE0tPTsWfPHkRGRuLGjRuwt7dHeHg4Jk2aBD09PbHjtXv5+fnYuHEj1q9fj8zMTLi7u2PUqFEICgqCk5OT2PGIADz8b1JUVBT27duHK1euwMLCApMnT8aUKVNgYWEhdjwiEhFvXExERERtQAVLAur0WBJ0bLW1tdizZw927dqFY8eOQSaTYfDgwRgzZgyCgoLQvXt3sSNSB5SSkoLdu3djz549SEhIQI8ePTBq1CiMHz8e77zzjtjxOiRBEHD69Gns3LkTBw4cwJ07d2BjYyMvDPr378/7PFCrEQQBV69exb59+xAVFYW0tDT06NEDI0aMQHBwMPz9/fnvIxEBYElAREREbQJLAiKWBJ1HdXU1Tpw4gcjISOzbtw/V1dVwc3ODv78//P39MWDAAKipqYkdk9qhyspKnDp1CocOHUJ0dDSysrLQrVs3DBs2DMHBwXjvvfegoqIidsxOo7GxETdu3MDBgwexa9cupKamQktLC15eXvLj3d3dnXO+02uVmZmJ48ePIyYmBidPnkR+fj4sLCwwcuRIBAYGYtCgQVBWVhY7JhG1MSwJiIiIqA1gSUDEkqBzqqqqwtGjR3H8+HFER0cjIyMDmpqaeOeddxAQEIABAwbA1dWVAzrUooqKCly+fBmnT59GdHQ0YmNjoaCggH79+iEgIABDhw6Ft7c3zxRuI5KTkxEdHY0TJ07g7NmzqKiogImJCfz8/ODn54f+/fvDzs6Ovy96boIgQCKR4NKlSzh58iROnjyJ3NxcdO3aFe+88w78/PwQEBAAFxcXsaMSURvHkoCIiIjaAJYERCwJCACysrIQHR2N6OhonDx5EiUlJejSpQv69u0Lb29veHt7o3///jA0NBQ7KrUyQRBw8+ZNXLp0CRcvXsTFixeRkpICmUwGa2trBAQEICAgAH5+ftDV1RU7Lj1DQ0MDrl27Jh/YvXDhAmpqaqCjo4N+/frBy8sLnp6e8PT0hJGRkdhxqY0oLi7G5cuXceXKFfmjtLQUampq6N+/P/z8/PDuu+/C09OTVw0R0QthSUBERERtAEsCIpYE9EeNjY1IS0vDpUuXcOHCBVy6dAmpqalobGyElZUV3N3d0adPH/Tp0wcuLi686WQHIpVKcfPmTcTHxyMhIQFxcXG4du0aSkpKoK6uDg8Pj2alkYmJidiR6RVJpVLEx8c3GwC+efMmBEFAz5494ebmBicnJ7i4uMDZ2Rm2tra8wqgDk8lkyMjIQGJiIhITE5GUlIQbN24gKysLAGBrawtPT095meTm5gZVVVWRUxNRe8aSgIiIiNoAlgRELAnoeZSXl+PSpUu4fPky4uLiEB8fj6ysLAiCAD09Pbi4uKBPnz7yQUQ7OzuehdyGNTQ04Pbt20hPT0daWhoSEhKQkJCA5ORk1NXVQVVVFQ4ODujTpw/c3Nzg7e0NNzc3niHcSZSVlckLg4SEBCQmJkIikUAmk0FNTQ0ODg5wdnaGk5MTevfuDVtbW1hbW/OeJu1IfX09MjMzIZFIkJ6ejqSkJCQmJiIlJQU1NTVQUlKClZUVXFxc4OLiIr/KRF9fX+zoRNTBsCQgIiKiNoAlARFLAnpZFRUV8sHl+Ph4xMfHIyUlBQ8ePAAAaGtrywcQe/fuDTs7O9jY2MDc3JwFQiuQSqXIz89Hdna2fCBQIpHg5s2byMzMRH19PQDA0NBQXvI0/dPe3p6FADVTW1uLlJQU+dnlTaVSfn4+AEBRURHm5uawsbGBra0tbGxsYGNjA2tra5iZmXEqKhGUl5cjLy9PXgZkZGTIHzk5OZDJZAAAY2NjODo6wtnZWf5wdHSEhoaGyHtARJ0BSwIiIiJqAyp4vTwR0UvS1taGr68vfH19my0vKChAenq6fFA6PT0dO3bsQGZmJqRSKQBAXV0dPXv2RM+ePWFubg4LCwtYWFigZ8+eMDY2Ro8ePWBgYCDGbrULDQ0NKC4uRlFREXJzc5GTk4OcnBzk5ubi9u3buH37Nu7cuSMfBNTS0pIXNmPHjoWdnR3S09OxbNkyVFRUoFu3bvDz88OQIUOgpKQk8t5RW6Surg53d/fHyuSqqir5wHPTQHRqaioOHjwoLxAAoGvXrvLj3czMTH7cm5mZwdjYGN27d0f37t2hoKDQ2rvW7giCgHv37qG4uBh3796VH/d5eXnIy8uTfxZUVFTIX2NsbCwvbwYPHiwvcWxtbdG1a1cR94aIiIiIiEh8vJKAOj1eSUCtpaGhQT6YnZOTg+zs7GYD3Ldv30ZNTY18fVVVVXTv3h2GhoYwMjJCjx495F/r6elBT08Purq6zR7a2toi7uHLaWxsRFlZGcrKylBaWtrs63v37qGwsBDFxcW4c+cOioqKUFRUhOLiYjz6ny99fX156WJpaSkfjG36/klXbpSXl2P//v3YsmULTpw4AT09PYwZMwahoaGPlT9EL6q6ulp+nOfl5T02mP3HY15JSQndunVD9+7d0aNHDxgZGaF79+7yZU3HvI6ODnR0dORft+cz3mtra1FeXo6ysrJm/ywtLUVxcbH8UVhYKD/2i4uL5QUg8H+l6x/LFzMzM/lngKampoh7SUT0ZLySgIiIiNoATjdExJKA2pKioiIUFhbi7t27LQ6ONy0vLS1tNrjYRFFREbq6uvLBRFVVVWhqaqJLly5QU1ODlpYWlJWVoaenByUlpWalgq6u7mNnMTe97lGVlZXyKyKa1NfXo6qqCsDDQf/y8nJIpVJUVlaipqYGtbW18teVlZVBKpXKC4FHz/Z9lLa2NgwMDOQDpUZGRjA0NGxWlnTv3h1mZmav5Uzg3NxcbNu2DevWrYNEIoGDgwOCg4MxZcoU3pya3phHi7C7d+82GxQvLCyUnzFfXFyMsrIytPS/bWpqavLiQFtbG+rq6tDQ0JAfv127doWKigp0dHSgqKgIPT09+WtbOsYVFBRanB6ppe0/euwDQGlpqfwzoKGhAQ8ePJCvU1tbi5qaGjx48EBeCNTV1bX4c9HT04OBgQF69OghL00MDQ3lV1w0Hf9Ny4iI2iuWBERERNQGsCQgYklA7VVdXZ38rPuWHqWlpfLBuerqatTV1aGiogINDQ3ygfrKykoAgEwma3GwvqKiotkZuwDkA5CPUlRUhI6Ojvx7PT09KCsrQ0tLS75+00BlU3nxx6sgHi03dHV1oaio+AZ+as8nNjYWmzdvxrZt21BSUgJvb2+EhYVh/PjxnJqERFVeXi5/NJ11/+jXFRUVqKurQ3V1tfy4f/DgARoaGlBeXg6ZTIaysjL5+7V0jDcN7v9R0zH8qD8e+zo6OlBSUoKurq78M6CprNTQ0IC6ujq0tLRavCLi0a+JiDoLlgRERETUBvCeBERE7ZWamhoMDQ1haGgodpQOx8PDAx4eHvj+++9x7NgxbNmyBZ9//jlmzZqFDz74AKGhoRg+fDjvX0CtrmkwvTWwRCciIiIiIuocxDtNk4iIqI1TU1NDYGAgdu3ahcLCQixfvhwFBQUYMWIELCwsMHPmTMTHx4sdk4iIiIiIiIjopbEkICIieg56enoIDw9HTEwMUlJSMHXqVBw8eBCurq5wdHTEsmXLUFRUJHZMIiIiIiIiIqIXwpKAiIjoBdnb2yMiIgIZGRk4d+4cfH198e2338LExAQBAQHYvHkzqqurxY5JRERERERERPRMLAmIiIhekqKiInx9fbF69WoUFRVh+/btUFdXxyeffAJTU1OEhYXh+PHjEARB7KhERERERERERC1iSUBERPQaqKurIzg4GAcPHsTt27cRERGBpKQkBAQEwNLSEvPnz8etW7fEjklERERERERE1AxLAiIiotfMxMQEM2fOxPXr15GUlISQkBBs2rQJNjY26Nu3L1asWIH79++LHZOIiIiIiIiIiCUBERHRm+To6IilS5ciLy8P0dHRcHBwwIIFC2BqaorAwEBERkZCKpWKHZOIiIiIiIiIOimWBERERK1ASUkJ/v7+2Lx5M/Lz87FmzRrU1tZi3LhxMDIywrRp0xATEyN2TCIiIiIiIiLqZFgSEBERtTIdHR2EhYUhOjoat2/fxty5c3Hq1CkMGDAAjo6OiIiIQHZ2ttgxiYiIiIiIiKgTYElAREQkInNzc8ybNw/p6em4du0a/P39sXLlSlhbW8PX1xdr1qxBZWWl2DGJiIiIiIiIqINiSUBERNRGeHh4YMWKFcjNzUVUVBRMTEzwxRdfoEePHhg7diwOHjwImUwmdkwiIiIiIiIi6kBYEhAREbUxampqCAwMxK5du3D37l0sX74cBQUFGDlyJCwsLDBz5kzExcWJHZOIiIiIiIiIOgCWBERERG2Ynp4ewsPDERMTg5SUFEydOhWHDh2Cm5sbHB0dsWzZMhQVFYkdk4iIiIiIiIjaKZYERERE7cRbb72FiIgISCQSnDt3Dr6+vvj2229hYmKCgIAAbN68GdXV1WLHJCIiIiIiIqJ2hCUBERFRO6OoqAhfX1+sXr0aRUVF2L59O9TV1fHJJ5/A1NQUYWFhOH78OARBEDsqEREREREREbVxLAmIiIjaMXV1dQQHB+PgwYO4ffs2IiIikJycjICAAFhaWmL+/PnIyMgQOyYRERERERERtVEsCYiIiDoIExMTzJw5E7GxsUhKSkJISAg2bdoEW1tb9O3bFytWrMC9e/fEjklEREREREREbQhLAiIiog7I0dERS5cuRV5eHqKjo+Hg4IAFCxbAzMwMgYGBiIyMhFQqFTsmEREREREREYmMJQEREVEHpqSkBH9/f2zevBkFBQVYs2YNamtrMW7cOBgZGWHatGmIiYkROyYRERERERERiYQlARERUSehra2NsLAwREdH4/bt25g7dy5Onz6NAQMGwMHBAREREcjOzhY7JhERERERERG1IpYEREREnZC5uTnmzZuHmzdv4tq1awgICMDKlSthbW0NX19frFmzBpWVlWLHJCIiIiIiIqI3jCUBERFRJ+fh4YEVK1YgNzcXUVFRMDExwRdffIEePXpg7NixOHjwIBoaGsSOSURERERERERvAEsCIiIiAgCoqakhMDAQu3btwt27d7F8+XIUFBRg5MiRsLS0xMyZMxEXFyd2TCIiIiIiIiJ6jVgSEBER0WP09PQQHh6OmJgYpKamYurUqTh06BDc3Nzg6OiIZcuWobCwUOyYRERERERERPSKWBIQERHRU9nZ2SEiIgISiQTnzp2Dr68vlixZAlNTUwQEBGDz5s2orq4WOyYRERERERERvQSWBERERPRcFBUV4evri9WrV6OwsBDbt2+Huro6PvnkE5iYmCAsLAzHjx+HIAhiRyUiIiIiIiKi58SSgIiIiF6Yuro6goODcfDgQeTk5GDRokVITk5GQEAALCwsMH/+fEgkErFjEhEREREREdEzsCQgIiKiV2JsbIyZM2ciNjYWSUlJGD9+PDZt2oTevXujb9++WLFiBe7duyd2TCIiIiIiIiJqAUsCIiIiem0cHR2xdOlS5OfnIzo6Gg4ODliwYAHMzMwQGBiIyMhISKVSsWMSERERERER0f/HkoCIiIheO0VFRfj7+2Pz5s0oKCjAmjVrUFtbi3HjxsHQ0BDTpk1DTEyM2DGJiIiIiIiIOj1lsQMQERFRx6atrY2wsDCEhYUhLy8PW7duxfr167FmzRrY29tj7NixmDRpEnr16iV21E6rsbERAQEBKCoqki+rr6+HkpISxo0bB3V1dflyHR0dnDp1CioqKmJEJSIiIiIioteMVxIQERFRqzEzM8O8efNw8+ZNXLt2DQEBAVi5ciVsbGzg6+uLNWvW4MGDB2LH7HQUFRVhYWGB5ORkJCUlISkpCenp6ZDJZMjIyJAvS05OhpGREQsCIiIiIiKiDoQlAREREYnCw8MDK1asQF5eHqKiomBiYoIvvvgCPXr0wNixY3Hw4EE0NDSIHbPTGD9+PARBeOZ6EydObIU0RERERERE1FpYEhAREZGoVFVVERgYiF27dqGwsBArVqxAQUEBRo4cCQsLC8ycORM3btwQO2aH5+fnh+7duz91HU1NTQwbNqyVEhEREREREVFrYElAREREbYauri7Cw8MRExOD1NRUfPrppzh8+DDc3d3h6OiIZcuWobCwUOyYHZKioiLGjx8PVVXVFp9XUVHB2LFjoaam1srJiIiIiIiI6E1iSUBERERtkp2dHSIiIpCeno5z587B398f33//PUxNTREQEIDNmzejqqpK7JgdSkhICOrr61t8TiqVYvz48a2ciIiIiIiIiN40lgRERETUpikqKsLX1xcrVqxAfn4+9u3bBz09PUydOhWmpqYICwvD8ePHn2s+fXo6Ly8vWFhYtPicgYEBBg0a1LqBiIiIiIiI6I1jSUBERETthrq6uvz+BXfu3MH333+PzMxMBAQEwMLCAvPnz4dEIhE7ZrsWGhoKFRWVZstUVVURGhoKJSUlkVIRERERERHRm8KSgIiIiNolAwMD+f0LkpKS8PHHH2PHjh3o3bs3+vbtixUrVuDevXtix2x3JkyYAKlU2mxZfX09QkJCREpEREREREREbxJLAiIiImr3HB0dERERgczMTJw7dw4eHh74+9//DjMzMwQGBiIyMvKJc+0/TVVV1Uu9rj1766234ODgAAUFBfkyc3Nz9OvXT8RURERERERE9KawJCAiIqIOo+n+BatXr0ZRURG2bNkC4OENeY2MjDBt2jTExMQ89/v99ttvGDx4MIqKit5U5DYpLCxMPrWQqqoqJk2a1Kw0ICIiIiIioo6DJQERERF1SBoaGggODsbBgweRnZ2NhQsX4vLlyxgwYADs7e0RERGBrKysp77HunXrcOHCBbi6uiIuLq6Vkotv/PjxkMlkAB5ONfTRRx+JnIiIiIiIiIjeFJYERERE1OGZmZlh5syZiIuLQ1JSEkaOHIlffvkFNjY28PX1xZo1a/DgwYNmr8nIyMC1a9cAAEVFRfDy8sLWrVvFiN/qzAkZdd8AACAASURBVM3N4eXlBeDh9EOOjo4iJyIiIiIiIqI3hSUBERERdSqOjo5YunQpCgoKcPToUVhZWWHWrFno0aMHxo4di4MHD6KhoQFbtmyBsrIyAEAmk6G+vh4TJ07E/Pnz0djYKPJevHmhoaEAgEmTJomchIiIiIiIiN4klgRERETUKSkpKcHf3x+bN29GXl4efvzxR+Tl5WHEiBGwtLTETz/9BKlU+tjrfvjhB3zwwQeoqKgQIXXrCQ4OhoqKCkJCQsSOQkRERERERG+QstgBiIiIiMSmr6+PGTNmYMaMGUhPT8eSJUuwadOmFtdtbGxEdHQ0+vfvj99//x2WlpatG/Yl1dTUoLa2FqWlpaitrUVNTQ1kMtljZcejy0aPHo0rV67gypUr0NLSkl9Z0URbWxtKSkrQ0NCAuro6dHV1oa6uji5durTafhEREREREdGrYUlARERE9IjevXtDRUUFKioqLV5JAAANDQ3IyMiAq6sroqKiMGjQoFbJJpPJUFhYiPz8fBQVFeH+/fsoKSlp9nh0WVVVFerq6lBWVvbS29yxY8dLvU5HRwfq6urQ1NSErq4uunXrBn19ffnDwMBA/nX37t1hZmYGQ0PDx4oIIiIiIiIierP4VxgRERHRI2pra7Fjx44nFgRNpFIpHjx4AH9/fyxfvhyff/75K2+7sLAQmZmZyMzMRHZ2Nu7cuYPc3FzcvXsXeXl5KCwshEwmk6+vrq7+2IC7ubk5XF1doa+vD01NTaipqUFXV7fZ2f5qamrQ1NQEAOjq6kJBQaFZjpaWlZaWNvteEAR5+VBdXY26urpmVymUl5ejrq4OlZWVKC0tlZcXKSkpzYqMmpoa+XsqKirC0NAQpqamMDExgZmZGYyMjGBpaQkrKytYW1vDyMjolX/ORERERERE9H9YEhARERE94sCBA6iqqnqudZtuYPzFF1/g5s2b+Omnn555JnxJSQkSExORkpICiUQiLwUyMzPl21VVVYWFhQWMjY1hbm4OW1tbmJmZwdjYWD6AbmRk1KrT+ujp6T22TF9f/5Xft7q6GoWFhSgoKEB+fj7u3LmDvLw83L17F8nJyTh+/Dhu376Nuro6AECXLl1gZWUlf9ja2sLe3h7Ozs7o1q3bK+chIiIiIiLqbFgSEBERET1i8+bNEAThqesoKSlBUVFR/n1DQwP++9//Ii0tDTt37oS+vj7q6uoQHx+PhIQEJCcnIykpCcnJybhz5w6Ah2fr29rawsrKCoGBgfJBb2tra5iZmTV7/46sS5cu6NWrF3r16vXEdRobG5Gfn4/MzEzcunVLXqpcuHABmzZtkl/lYGhoCCcnJzg6OsLJyQnOzs5wdXWFurp6a+0OERERERFRu6MgPOuvYKIOLiMjA7a2toiNjYW7u7vYcYiISGQxMTGora2Vf9/Q0IAHDx40W6eysrLZdEQymQzZ2dnIzs5GZWUlysvLERsbi9raWqiqqsLGxgaOjo5wcHCAh4cHHB0d0atXr8em9KGXU1paiuTkZKSkpCA5ORmxsbGIj49HZWUllJWV0bt3b3h4eMgfnp6eUFVVFTs2ERGWLFmCDRs2QCKRiB2FiIiIOq8KXklARERE9AhfX99nriOTyRAbG4uTJ0/i1KlTuHjxIh48eAANDQ24urqiX79+mD59Ojw9PWFjY9NprgoQi56eHnx9fZv97gRBwK1bt3DlyhVcvXoVV69exZ49e1BdXY2uXbuif//+GDx4MAYPHox+/frxhslERERERNRp8a8hIiIioueQnJyMY8eO4eTJkzh79iwqKipgbGyMwYMH4/vvv4eXlxecnJygoqIidlQCoKCgABsbG9jY2GD8+PEAHl4VkpSUhCtXruDcuXP4+eefsWDBAmhpaWHAgAEYPHgwAgIC0KdPH5HTExERERERtR6WBEREREQtkMlkuHjxIg4dOoT9+/cjLS0NWlpa8PLywt/+9jf4+/vD3d2dUwa1I8rKynB1dYWrqyvCw8MBAJmZmTh+/DhiYmKwYsUKfPXVV7CwsMDQoUPxwQcfYOjQoZyaiIiIiIiIOjSWBERERET/X2NjI06cOIHffvsNhw8fxv3792Fvb4+goCCMGDECXl5enDqog7GyskJ4eDjCw8MhCAKuXbuGqKgoHDhwAGvWrIGenh6GDx+OCRMmYMiQIVBSUhI7MhERERER0WvFkoCIiIg6PYlEgk2bNmHz5s3Izc1F//79MW/ePAQFBcHW1lbseNRKFBQU0K9fP/Tr1w/ffvstbt26hQMHDmDPnj14//33YWxsjNDQUEyePBlvvfWW2HGJiIiIiIheC54KR0RERJ1SY2Mj9u7di3feeQd2dnbYsGEDxo8fj9TUVFy8eBFfffUVC4JOztraGrNnz0ZMTAxu3ryJKVOmYNu2bbC3t8fbb7+NXbt2QSaTiR2TiIiIiIjolbAkICIiok6lrq4Ov/76K+zt7REcHAx9fX0cPnwYOTk5WLp0Kc8QpxbZ2tpi8eLFyM7OxrFjx2BqaoqQkBDY2dnhl19+QU1NjdgRiYiIiIiIXgpLAiIiIuoUZDIZVq1aBUtLS3zxxRcYMGAAkpOTERUVhWHDhnGueXouioqKCAgIQGRkJG7evAl/f398+eWXsLS0xL///W80NDSIHZGIiIiIiOiFsCQgIiKiDu/s2bPo27cv/vznPyMkJARZWVlYu3YtrxqgV2JjY4NVq1YhOzsbkydPxty5c+Hq6ooTJ06IHY2IiIiIiOi5sSQgIiKiDqu8vBwTJkzAoEGDYGRkhMTERPz4448wNjYWOxp1IIaGhli2bBmSk5NhbW0Nf39/BAcHo6SkROxoREREREREz8SSgIiIiDqkuLg49O3bF6dPn8aBAwdw5MgR2NnZiR2LOjBra2vs378fR48exZUrV+Du7o4rV66IHYuIiIiIiOipWBIQERFRh7Nx40Z4e3ujZ8+euH79Oj744AOxI1EnMmTIEFy/fh0ODg4YMGAAVq1aJXYkIiIiIiKiJ2JJQERERB3Kv//9b3z88ceYPXs2jh07BkNDQ7EjUSdkYGCAQ4cOYcGCBfjTn/6E77//XuxIRERERERELVIWOwARERHR67Jnzx7MmjULy5Ytw1dffSVKht9+++2Z6+jr62P48OHNluXn5yMyMhISiQQGBgYYNGgQvL29kZOTA5lMhpKSEmRnZ8vXV1BQQI8ePdCrVy9YWFhARUXlufKlpqbi7NmzSEpKgr6+Pvr27Qt/f39oaGi80H7SsykqKuLrr7+Gvr4+/vznP8PExAQTJ04UOxYREREREVEzvJKAiIiIOoScnBxMmTIFM2bMEK0gAIBZs2YhPT0dZWVlSE9PR2hoKNasWYOKigrcuXMHW7ZswZw5c5q95rvvvkP//v1RV1eH8PBwzJw5E1KpFMOGDcOAAQOQnp4OHx8fGBgYIDQ0FLNnz8adO3dw4cIFjBgxAj179sSxY8eemquqqgqzZ8/GxIkTYW1tjYULF2LUqFE4deoUPDw8cOPGjZfa37q6upd6XWfy+eefY86cOQgPD0dGRobYcYiIiIiIiJpREARBEDsEkZgyMjJga2uL2NhYuLu7ix2HiIhe0tixY5GYmIgbN25AXV1dtBxnz57FO++8AwBIS0uDvb09ZsyYgZUrVwIABEHAxx9/jA0bNgAAli9fjrlz5+LUqVPw8fFp9l61tbUYNGgQpk2bhilTpgAAdHR0YG5ujqSkJABASUkJvLy8cOvWLVy/fh2urq4t5nr//feRnp6OhISEx64a+Oabb7B48WKcO3cOnp6eL7S/f/nLX/D9999DUZHnnjyNVCpFv379YGZmhkOHDokdh4jaiCVLlmDDhg2QSCRiRyEiIqLOq4J/zREREVG7l5WVhb179+Kbb74RtSAAAF9f36c+r6CggOnTpwMAtm/fjtmzZ+Obb755rCAAAHV1dfznP/9BSUmJfJmqqioUFBTk3+vr62PcuHEQBAE7duxocZsrV67E77//jr///e8tTis0a9YsaGpqYurUqZBKpc+1nwCQmJjIm/I+JxUVFSxZsgS///47UlJSxI5DREREREQkx3sSEBERUbt3+PBhaGlpISgoSOwoz3VGvZeXFwBg8eLFAPDY/Qke1a9fPzzrwk9tbW0AQF5eXovPR0REQFFRESEhIS0+r6WlhVGjRmH9+vWIjIyEkpISGhsboaKigjFjxgAAdu/eDalUCg0NDQQFBeH8+fMYP348qqqqsGPHDqioqCA4OBjAwysgIiMjkZycDG9vbwwZMqRZOVFXV4czZ87gzJkzMDExwXvvvQdra2v589nZ2diwYQPmz5+PwsJCbNy4EYaGhggJCYGuri5u3bqFyMhIqKqqYsqUKdDT02u2PxUVFdi5cydSU1NhZWWFyZMno2vXrk/9GbaGYcOGwdDw/7F331FVXPvbwB+6IFVUuke6NBVF1AD2bohGY9Qo2Nu1oIk98V6s0RhNbLmWa8OaiIqaxCRgRSwoxIKoIEgHBaRIb/P+4cv8JGBHhvJ81jpLmHaeczizwf2d2VsPJ0+ehK2trdRxiIiIiIiIAHBOAiIiIqoHwsLC0K5dOygq1p3rHx4+fIjw8HAoKirC2tr6ldu+bgigQ4cOAQB69uxZaV1SUhJSU1NhYGAAZWXllx5DJpMBAG7evIkBAwZgy5YtmDBhgrjexcUF3377LaZNmwbg+bBJbm5uAJ4PgaSlpQUAiI2NRZ8+fVBYWIgZM2Zg06ZNsLe3R0FBAYDnBYR+/fohIyMD8+bNgyAIcHR0xLFjxwAAhw8fhpubG5YtW4bffvsN//73v/Hw4UPMnDkTEyZMwMWLF/HNN98gLCwMCxYsqDQRcGRkJEaPHg2ZTIYxY8Zg27ZtaNu2LTIzM1/5HtYEOTk5ODs7i0NFERERERER1QYsEhAREVGd9+zZM2hoaEgd463ExMQAACwsLF7ZeV+VZ8+e4caNGwgKCsLIkSNx8+ZNjB07FmPHjq207e3btwEAJiYmrzxm+frw8HBoaGjA0dGxwnoDAwPxDgjg+bBKVlZWAJ7fCdGnTx8AwKRJk2BjY4OJEyfC2NgYc+bMwaNHj3D69GkAwIQJE2Bqaorhw4dDW1sbM2bMQN++fTF69GgkJCRgxIgRmDRpEoDnQyv5+Phg//79mDJlCo4dO4bY2FgcOnQI+/fvx8KFC/H7778jOztbzDV9+nSMHz8effr0QZs2bbB27VpERUVh/fr1b/MWfzCampoV8hIREREREUmt7lxuR0RERPQSenp6CAwMlDrGW3mfux4UFBQQGxuL+Ph49OnTBwsXLkSbNm2q3Lb8Cv/XdUyXD2mkq6sLoOphk143lNLDhw/h7++P33//XVw2cOBApKSkoHnz5sjLy8ORI0ewbt26CvtNmzYNvr6+2L17N5YsWSIODVQ+ATQA8fW9OOdDq1atAACJiYnQ1NREcnIy/P390bZtW1y7dg0AkJOTAycnJ+Tl5b0ye01JSEiApaWl1DGIiIiIiIhELBIQERFRnde5c2ds2rQJaWlpaNq0qdRx3kh5R3FkZCTy8/OrnFD4ZdTU1DB06NA32rZ87PvY2NhXblc+n4G9vf0b5/ine/fuAUCl8f+bN28OALh8+TKKi4srFUjK34uIiAgA/1eMeHGCZhUVlUrPV34HRvlky5GRkQCA+fPn18rPQXZ2Nq5evVrlHR9ERERERERS4XBDREREVOcNGDAAmpqa2LJli9RR3piRkRHs7OxQWlr62jHqXzdx8atoaWnB0dERubm5iIqKeul29+/fh7y8PHr37v3Oz1Ve6Pjzzz8rrUtNTUVpaSmA58WCF5V36JcPX/SuyosGoaGhldY9e/bsvY5dHbZt2wYlJSUMGjRI6ihEREREREQiFgmIiIiozmvcuDHmzp2L7777Dg8fPpQ6jqi8c/9lnfxLly4F8PzK96Kioiq3SU1Nxe7duysc822LBj/99BPk5OTw3XffVbk+ISEBR48exYwZM9C2bVsAz8fOLywsrPR6yjv6X1S+zNbWFvLy8jh16lSF7aKionDjxg04OjpCRUUFQUFBlV4jAHEi5HdlbW0NBQUF/Oc//6nwfqampuLAgQPvdez3FR8fjxUrVsDLywva2tqSZiEiIiIiInoRiwRERERUL8ydOxfW1tYYOnQocnJypI4DAEhJSQGAl+YZOnQoVqxYgQsXLmDSpEnIzc2tsD4uLg6rV6+Gh4cHAKCoqAgZGRlvPfFtp06dsHz5cvj4+OD8+fMV1mVnZ2PSpEno1KkTVq5cKS6XyWQoLCyEv78/BEHAzz//jMuXLyMrKwtZWVkoLS1Fs2bNAAAhISEIDAxEkyZN4Onpidu3b2PYsGE4e/YstmzZgiVLlqBfv35o3rw5Zs6ciUePHuHcuXPic/n5+WHYsGHo2rVrhffrxfejfEih/Px8cVlJSUmF7XR0dDB16lRcvXoVXbt2xcGDB7Fnzx6MGjUKI0eOfKv3rDrl5+djyJAhMDY2xtdffy1ZDiIiIiIioqooeHt7e0sdgkhKT58+xaZNmzBlyhQYGBhIHYeIiN6RgoIC+vXrhx9//BF//PEHPvvssyrHsa8pBw8exIoVK5CUlIS4uDiUlpbCzMwMmpqaFbbr0qUL7O3tcejQISxatAj+/v64ceMG/Pz8EBUVBW9vbygrK+PixYuYN28ewsPDkZ2djSdPnqB58+YwMjJ6ozxdunSBq6srZs+ejevXryM+Ph5HjhzBypUr0bdvX+zYsaPC+9WqVSucPHkS69atw9atW9GjRw8Az8f9L58M2MTEBIcPH4aPjw/at28PZ2dn9OjRAw8ePMDx48fh4+OD8PBw/PDDD2LOXr16IScnB0uWLEF6ejr279+P6Oho+Pj4QElJCf7+/li/fj2ePHmCvLw8WFlZITg4GOvWrUNSUhKys7NhaWmJ8PBwfPfdd4iLi0NWVhYcHBzQrFkzdOvWDQkJCfjtt99w7NgxnDt3DqtWrRLvkKhpeXl5GDRoEO7du4czZ86I8zMQEQFAYGAgbt68iVmzZkkdhYiIiBquQjnhfQa5JaoHHj58CEtLS4SEhKBdu3ZSxyEiovcUHh6Onj17omnTpvD19YW1tbXUkd5Ybm4u7ty5AwsLiw868W5WVhbu3r0LY2NjtGjR4qXbCYKAsLAwmJubQ01NDZGRkTA2Nq4wyXJxcTFKSkoqTbyclJSE1NRU2NraQklJqdKx8/Pzcf/+fdjY2KBRo0bV9+L+v7S0NMTFxcHGxuatJoWuTtHR0Rg2bBji4uLg7+8vWaGCiGqvVatWYffu3eLE60REREQSyOZwQ0RERFSv2Nra4vr169DQ0ECHDh3w888/Sx3pjTVu3BidOnX6oAUC4Plkxh999NErCwQAICcnBwcHB6ipqQEALC0tK3W4KykpVdkJb2hoiDZt2lRZIACeT3Ls6Oj4QQoEwPPJkNu1aydZgeC3336Dk5MTysrKcPXqVRYIiIiIiIio1mKRgIiIiOodY2NjnD9/HmPGjMHIkSPh4eGBxMREqWNRA/D48WNMmDAB7u7uGDp0KK5cuQJzc3OpYxEREREREb0UiwRERERULykrK2PTpk3w8/PD5cuX0apVK6xatQoFBQVSR6N6qKioCN9//z2srKwQEBCAX375BTt27Phgd0oQERERERFVFxYJiIiIqF775JNPcPfuXSxatAirVq2CjY0NtmzZgry8PKmjUT1QUFCAbdu2wdbWFv/+978xZ84c3Lt3D5999pnU0YiIiIiIiN4IiwRERERU7zVq1AiLFy/GgwcP0L9/f8ybNw8ymQxLly5FWlqa1PGoDsrIyMCqVavQsmVLeHl5oUePHrh37x68vb3FORyIiIiIiIjqAhYJiIiIqMEwMjLCTz/9hJiYGEydOhUbN26ETCbDmDFjcP78eQiCIHVEqsUEQUBgYCAmTJiAFi1aYO3atRg3bhxiYmKwfft2yGQyqSMSERERERG9NRYJiIiIqMFp3rw5li9fjtjYWHz33Xe4e/cuunfvDjMzM3h7eyM6OlrqiFSLxMbGYvny5bCyskKXLl0QGhqKlStXIjY2Ft9++y309fWljkhERERERPTOWCQgIiKiBktdXR3Tp0/HjRs3EB4ejuHDh2Pbtm0wNzeHnZ0dFi5ciEuXLvEOgwYoOjoaGzZsgKurK0xNTfHDDz+gR48euHHjBv7++2/MmjULmpqaUsckIiIiIiJ6bywSEBEREQGwsbHB6tWrER8fj9OnT8PNzQ379u2Dm5sbzM3NMXv2bPj7+3PC43oqPz8fZ8+exdy5c2FhYQFzc3N8++23sLW1xalTp/D48WNs27YN7du3lzoqERERERFRtVKUOgARERFRbaKoqIh+/fqhX79++O9//4vr16/jxIkTOHnyJDZs2ABlZWV07NgRPXr0QPfu3dGpUyeoqKhIHZveUlFREa5du4azZ8/i/PnzuHr1KgoKCtCqVSt89tlnGDRoEDp27Ah5eV5TQ0RERERE9RuLBEREREQvIScnB2dnZzg7O2PlypVISkrC2bNnce7cOfj4+GDp0qVQVVUVt3F2dkaHDh04gW0tFB8fj+vXryM4OBjBwcG4du0a8vLyIJPJ0L17d4wbNw7du3eHiYmJ1FGJiIiIiIhqFIsERERERG/I0NAQo0ePxujRowE8n9D23LlzuHTpEv7880+sX78epaWlaN68uVgwaN26NRwcHGBqasqr0mtAWVkZYmJiEBYWhtu3b4uFgZSUFCgoKMDGxgbOzs4YPXo0unXrBjMzM6kjExERERERSYpFAiIiIqJ3JJPJMHbsWIwdOxYAkJubi9DQUAQHB+P69evYu3cvHj16BEEQoKamBhsbG9jZ2cHOzg729vawsrKCTCaDkpKStC+kDiopKUFsbCwiIyNx584dhIeHIywsDHfv3kV+fj4AoGXLlnBycsJXX32FDh06oH379lBXV5c4ORERERERUe3CIgERERFRNWncuDHc3Nzg5uYmLsvJyUF4eHiFjuwzZ84gMTERwPM5EExMTGBubg5zc3OYmZnB3NwcpqamMDQ0hJ6eHuTk5KR6SZIRBAGPHz9GcnIyYmJiEBUVVeERFxeHkpISAICBgQHs7e3RunVrhISEwMLCArNnz8bEiRM5XwQREREREdFrsEhARERE9AGpq6uL8xW8KDMzEw8fPkRUVBSio6MRFRWFiIgInD59GgkJCSgrKwPwvIigp6cHY2Nj6Ovrw8TEBPr6+tDX14euri6aNGki/tukSZNa3SleVFSEp0+fIj09vcK/KSkpSElJQXx8PB4/fiz+W1xcDOD53BDGxsZiAaVr165iQcXCwgJNmjQRn2PmzJn473//i7lz52LZsmUYN24cZs6cCSMjI6leNhERERERUa0mJwiCIHUIIik9fPgQlpaWCAkJQbt27aSOQ0REhKKiIsTFxSE5ORkJCQliB3pKSgoSEhKQnJyMx48f49mzZ5X2VVdXFwsHqqqqUFNTg6amJho1agR1dXWoq6tDRUUFWlpaAAAlJaVKQ/CoqalVKDYUFRUhNze3wjY5OTliJ352djYKCwvx7Nkz5OTkoLCwEFlZWcjPz0deXp5YEMjJyakyr56eHgwMDMRCyD8LIjKZ7K2LH48fP8aePXuwceNGpKWlYdCgQZg7d26lYg0RkZRWrVqF3bt3IzIyUuooRERE1HBl804CIiIiolpGWVkZFhYWsLCweOV2xcXF4tX4L16ZX/51eSd9dnY28vLy8OTJEzx79gwFBQVigaGgoEAcw79cdnY2SktLxe/l5eXFokK5Ro0aQVVVFQCgoaEBFRUVaGpqonHjxmjUqBHMzMygpqYGVVVV8S6HF+94KP9aWVm5Ot6ySvT09LBgwQLMnj0bP//8M77//nt07NgRLi4u8PLywpAhQ6CgoPBBnpuIiIiIiKguYZGAiIiIqI5SUlIShx6qbvXlTjsVFRV4enrC09MTly5dwpo1azB8+HCYmZlh0qRJmDp1aqUCCBERERERUUMiL3UAIiIiIqKa4OrqilOnTiEiIgIDBw7E8uXL0aJFC3h5eSE2NlbqeERERERERJJgkYCIiIiIGhQLCwts2LABiYmJWLZsGY4fPw4zMzO4u7sjKChI6nhEREREREQ1ikUCIiIiImqQtLS04OXlhaioKBw+fBjp6elwdXWFk5MTfHx8xImZiYiIiIiI6jMWCYiIiIioQVNSUsKwYcNw+fJl3LhxA7a2tpgwYQJkMhm8vb3x9OlTqSMSERERERF9MCwSEBERERH9f+3bt4ePjw8iIiLg6emJjRs3QiaTYcqUKbh3757U8YiIiIiIiKodiwRERERERP9gamqK1atXIzY2FuvWrcOFCxdgb2+P3r1749SpUxAEQeqIRERERERE1YJFAiIiIiKil9DQ0MDkyZMRHh4OPz8/AMAnn3wCR0dHbN++Hfn5+RInJCIiIiIiej8sEhARERERvYa8vDzc3d3h7++P0NBQdOzYEV5eXmjZsiUWLlyIxMREqSMSERERERG9ExYJiIiIiIjegqOjI7Zt24aYmBhMmzYNO3fuhJmZGTw9PXH79m2p4xEREREREb0VFgmIiIiIiN6Bnp4evL29kZCQgB07duDvv/9GmzZt4OrqiiNHjqC0tFTqiERERERERK/FIgERERER0XtQUVGBp6cn7ty5g8DAQOjo6GD48OGwtrbGhg0bkJubK3VEIiIiIiKil2KRgIiIiIiomri6uuLUqVN48OABBg4ciMWLF8PQ0BBeXl6Ii4uTOh4REREREVElLBIQEREREVUzS0tLbNiwAUlJSVi2bBmOHz8OU1NTuLu74/Lly1LHIyIiIiIiErFIQERERET0gWhpacHLywsPHz7E4cOHkZaWBhcXFzg5OcHHxwclJSVSRyQiIiIiogaORQIiIiIiog9MWVkZw4YNw5UrV3Djxg3Y2tpit37P/AAAIABJREFUwoQJaNGiBby9vfH06VOpIxIRERERUQPFIgERERERUQ1q3749fHx8EBERAU9PT2zcuBEymQxTpkzBvXv3pI5HREREREQNDIsEREREREQSMDU1xerVqxEbG4t169bhwoULsLe3R+/evXHq1CkIgiB1RCIiIiIiagBYJCAiIiIikpCGhgYmT56M8PBw+Pn5AQA++eQTtGvXDtu3b0d+fr7ECYmIiIiIqD5jkYCIiIiIqBaQl5eHu7s7/P39ERoaCmdnZ3h5eaFly5ZYuHAhkpKSpI5IRERERET1EIsERERERES1jKOjI7Zt24ZHjx5h2rRp2LlzJ8zMzODp6Yk7d+5IHY+IiIiIiOoRFgmIiIiIiGopfX19eHt7IyEhAdu3b0doaChat24NV1dXHDlyBKWlpVJHJCIiIiKiOo5FAiIiIiKiWk5FRUW8i8Df3x86OjoYPnw4WrVqhQ0bNiA3N1fqiEREREREVEexSEBEREREVEfIycmhV69eOHXqFO7fv48BAwZg8eLFMDIygpeXF+Li4qSOSEREREREdQyLBEREREREdZCVlRU2bNiAmJgYLFq0CMeOHYOZmRnc3d1x+fJlqeMREREREVEdwSIBEREREVEd1qxZMyxYsABRUVE4dOgQUlNT4eLiAicnJ/j4+KCkpETqiEREREREVIuxSEBEREREVA8oKytj2LBhuHr1KgIDA2FmZobx48fD0tISa9asQUZGhtQRiYiIiIioFmKRgIiIiIionnF1dcUvv/yCiIgIDB8+HKtXr4ZMJsOUKVNw//59qeMREREREVEtwiIBEREREVE9ZWZmhtWrVyMuLg7Lly/HX3/9BTs7O7i7uyMgIEDqeEREREREVAuwSEBEREREVM9paGjAy8sLUVFR8PPzQ0FBAXr37g1HR0ds374dBQUFUkckIiIiIiKJsEhARERERNRAyMvLw93dHf7+/ggJCYGDgwNmzJiBli1bwtvbG2lpaVJHJCIiIiKiGsYiAREREVEDV1ZWhp49e8LBwUF8DBw4EAoKChg+fHiF5a6uriguLpY6MlWDdu3awcfHB3FxcZg6dSo2b94MY2NjeHp6IiwsTOp4RERERERUQ1gkICIiImrg5OXlIZPJcPfuXYSFhSEsLAwREREoLS3Fw4cPxWV3796Fvr4+lJSUpI5M1UhfXx/e3t5ISEjA9u3bxTsMXF1dcerUKQiCIHVEIiIiIiL6gFgkICIiIiJ88cUXb9QZPHr06BpIQ1Jo1KiReBeBv78/dHR0MGjQIFhbW2PDhg3Iy8uTOiIREREREX0ALBIQEREREXr06IFmzZq9cpvGjRujf//+NZSIpCInJ4devXrh1KlTuH//Pvr374/FixfD0NAQXl5eiI+PlzoiERERERFVIxYJiIiIiAjy8vL44osvoKysXOV6JSUlfP7551BRUanhZCQlKysrbNiwATExMVi0aBGOHj0Kc3NzfP7557hy5YrU8YiIiIiIqBqwSEBEREREAICRI0eiqKioynXFxcX44osvajgR1RbNmjXDggULEB0djQMHDiAuLg4fffQRnJyc4OPjg5KSEqkjEhERERHRO2KRgIiIiIgAAB07doRMJqtyna6uLrp161azgajWUVZWxrBhw3D16lUEBgbCzMwM48ePh5WVFdasWYOMjAypIxIRERER0VtikYCIiIiIRB4eHlBSUqqwTFlZGR4eHlBQUJAoFdVGrq6u+OWXX/DgwQN8/vnnWL16NWQyGaZMmYIHDx680TH8/f2xa9euD5yUiIiIiIhehUUCIiIiIhKNGjUKxcXFFZYVFRVh5MiREiWi2s7c3ByrV69GbGwsli9fjj///BO2trZwd3dHQEDAK/dds2YNJk6ciPXr19dQWiIiIiIi+icWCYiIiIhI1KpVK9ja2kJOTk5cZmJigg4dOkiYiuoCTU1NeHl5ITo6Gn5+figoKEDv3r3Rrl07bN++HQUFBRW2Dw8Px9mzZyEIAr766issWbJEouRERERERA0biwREREREVIGnp6c4tJCysjLGjBlToWhA9Cry8vJwd3eHv78/bty4AXt7e8yYMQOmpqbw9vZGWloaAGD9+vVQVFQU91u1ahWmTZuGsrIyqaITERERETVILBIQERERUQVffPEFSktLATwfamjEiBESJ6K6qn379vDx8UFsbCymTJmCTZs2wdjYGMOHD4ePj0+Foa3KysqwY8eOKoe8IiIiIiKiD4dFAiIiIiKqwMTEBB07dgTwfPghOzs7iRNRXWdgYABvb2/ExsZi3bp1OHPmDEpKSiptV1paCl9fXwwaNAj5+fkSJCUiIiIianhYJCAiIiKiSjw8PAAAY8aMkTgJ1Sfq6uqYPHky5OXlIQhClduUlJQgICAAvXv3RnZ2dg0nJCIiIiJqeFgkICIiIqJKhg0bBiUlJYwcOVLqKFTPHDp0COnp6a/cpri4GMHBwejSpYs4hwEREREREX0Yiq/fhIiIiIjqurKyMmRlZSE3NxcFBQXIysoCAGRlZVWYKFYQBGRmZgIAhg4diuDgYAQHB0NLSwvy8v93fYmcnBy0tbUBAJqamlBVVUXjxo2hqakpTnpMVJX169e/0XbFxcUIDw9H586dce7cORgbG3/gZG+WKScnB/n5+SgoKEB2djZKS0tRWlpa5V0P5dv9k4qKCtTU1Cot19DQgKKiIhQUFKCpqSlu17hxYygrK3+Q10RENScnJwfFxcXi796MjAwA/9e2/FNRURFyc3OrPJa2tjbk5OQqLdfR0QEAKCkpQV1dXWxH1NTUoKKiUo2vhoiI6hMWCYiIiIjqkOLiYqSkpCA+Ph6pqalIT0/H06dPkZaWhrS0NDx9+hTp6elIT09Hbm6uWBgoKip6p+c7fPjwW++jrKwsFgzU1dXRpEkT6Orqio+mTZtCV1cXTZo0QbNmzWBsbAwDAwN2gjYAFy9exK1bt6CkpARFRUWUlJRUKFL9U3FxMWJjY9G5c2ecP38e5ubm7/X86enpePz4sXjuZGZmvvKRm5uL7OxslJSUiMUzKWlpaUFRURFaWlpQU1ODtrZ2lQ8dHR1oa2uL55ienh6aNm0qdXyiOqusrAypqani4+nTp8jKyqrwyMzMrPB9RkaG2Mn/soKhFMqLkVpaWlBRUYGWlha0tLTE9qP86/LlWlpaYluir68PLS0tqV8CERF9ACwSEBEREdUiT58+RVRUFKKiohAdHY2kpCTEx8cjKSkJiYmJSElJqTCWu7q6eqXO99atW0NXVxeNGzcWOxNVVVXFrxs1aiTeBaCurg4lJaUKGf5518CLdxeUe/Gqx6ysLOTn5yMvLw9ZWVkoKCgQO1dzcnLEQkZCQgJu3rwpFjOePXsmHk9OTg56enowNDSEkZERTExMYGhoCFNTU5ibm8PCwgK6urrV/n5TzdLU1MTmzZuRnp6OtLQ0pKenIyUlBcnJyXj69KnYqfai4uJiJCQkwMXFBQEBAbC3t6903LS0NMTFxSE+Ph6xsbHiMVNTU5GSkoKUlBSkpqZWOraGhkaVneympqbQ1taGmpoatLS0oKCgAG1tbfHKXFVVVTRq1KjC+VPVVb3l2//Tywp35VcVl5SU4NmzZygoKEB+fr64fVZWFkpKSpCVlYW8vLwKBY24uDhkZmYiIyMDmZmZFc6v8izNmzeHnp4e9PX10bx5c+jr60NfXx8tWrQQH82aNXuDnyRR/ZCXl4e4uDgkJCSIj/JCQEpKCp48eYK0tDSkpqZWKmhqaGhU6GAv/1pPT09sS/55FX95m1F+192L7Ub5HQAvkpeXr7JT/mV3L734u7m8QFHejuTl5aGwsFC8myE7OxuFhYVicSMzMxMxMTGVCh7/LG6oqKigadOm0NPTg56eHpo1a4ZmzZrB0NAQBgYGMDExQYsWLWBgYFDp7wsiIqq95ISXzRhG1EA8fPgQlpaWCAkJQbt27aSOQ0REDUBRURHCw8MRFhaG+/fvIyoqCg8fPkRUVJTYSaikpIQWLVrA0NBQ/M+2sbGxeNV9eWdeXR46oKioCKmpqYiLi0NycjISEhKQmJgoFkYSExMRFxcndqZqa2vD3NxcLBpYW1vDwcEBtra2dfp9oIry8vLEO2NSU1ORlpaGpKQkREREID09Hfb29khJSRGLAjExMcjLyxP3L++4MjQ0FDvFDQwMxKtgyzvIdXV16/XQWKWlpUhPT0dqaioeP36M5ORkPHnyBCkpKXj8+DGePHmCpKQkPH78GCkpKeJ+qqqqkMlkFQoHFhYWsLKygpWVFTQ0NCR8VfXPqlWrsHv3bkRGRkodpV7Kzs5GZGSk+Ds2ISEB8fHxiI+PR0JCQoX5UVRVVWFsbIzmzZuLd+CUd4KXtyXlHeK6uroViun1WWFhodiWlBdcXyyipKam4smTJ0hOTkZKSgpKSkoAPC9w6OvrQyaTwcjICMbGxpDJZDA3N4elpSXMzMx4ByERUe2RzSIBNXgsEhAR0YeUnJyMkJAQ3LlzB7dv38adO3cQERGB4uJiKCsrw9LSEhYWFmLHd3knuEwmg6Iib/osLS1FXFyc2MFT/m9UVBQePHiAoqIiKCoqwtLSEg4ODmjdujXs7e3Rvn37WjGGPb2d2NhYhIeH4/79+4iIiEBERAQePHiAxMREAM+LZzKZDDKZDCYmJpU6s1u0aIFGjRpJ/CrqnsLCQsTFxVW4GyM2Nlb8OiYmBsXFxQAAQ0NDWFtbi0UDa2tr2NrawtTUVOJXUTexSPD+ygvvERERYkEgMjISkZGRePLkCQBAUVERLVq0EK9yLy+6m5iYwMTEBMbGxhySqxqUlpYiJSUFsbGxSExMREJCgtiuJCYmIiYmRixKKigooEWLFuLfQRYWFrC0tBTbk6rmWyAiog+GRQIiFgmIiKi6FBcX4/bt27h06RJCQkIQEhKC8PBwAICBgQHs7Oxga2uL9u3bw87ODnZ2duzQfA8lJSWIi4vD3bt3xff67t27uH//PsrKymBgYID27duLDzc3N3GYJZJWcXExIiIiKvzcgoODxQ49HR0dmJmZwdbWFnZ2djAzMxO/V1VVlTh9w1N+rkVHRyM6Ohp3795FeHg4oqOj8ejRIwiCAE1NTTg4OFRo59q1a1flBM30f1gkeDtJSUlim1HefoSFhaGwsBDA//2uLW8z2HbUPoWFhUhMTKzQjpQ/ytsTZWVlWFhYiH8v2draokOHDtDX15c6PhFRfcUiARGLBERE9K4KCgoQFBSEgIAAnD17Fn///TeKi4vRvHlzdOzYER07dkSnTp3g5OTEif5qUHZ2NkJCQnDlyhUEBwfj2rVrSElJgaKiItq0aYOePXuiZ8+ecHV1ZQdmDXnw4AGuXr2Ky5cv48qVK7h37x5KSkqgpqYGe3t7tG3bFm3atEHr1q3h4ODA86UOyc7ORlhYGG7fvo2bN2/i1q1buHPnDnJzc6GoqIhWrVqhU6dO+Oijj9CpUye0atWKVwi/gEWCl4uLi8O1a9fEx61bt8S5Nlq2bAkHBwfY29uLd5BZWVlx+Jo6Ljs7G+Hh4bhz5w7u3Lkjti3lw0IZGBjAyckJzs7O6NixI5ydnfn7goioerBIQMQiARERvY2bN2/ijz/+wJkzZxAUFIT8/HxYWVmhZ8+ecHNzQ6dOnTjsRi0UGxuLq1ev4tKlSwgICMD9+/ehoqKCjz76CD179kTfvn3Rvn17dl5Wg+LiYvG9vnLlCq5cuYK0tDQ0atQITk5O6Ny5M5ycnNCmTRtYWFjU63kBGqqysjI8fPgQt27dEgt2169fR35+Ppo0aYLOnTujU6dOcHNzQ+fOnRt0xy6LBM8VFhaKhcRr164hODgYycnJUFBQgJ2dHTp27AgnJyfxbhVNTU2pI1MNSk5ORlhYGG7duoUbN27g6tWriI2Nhby8PKytrcWigaurK+zt7fm7nIjo7bFIQMQiARERvUpZWRn+/vtvnDp1CocOHUJERASaNWuGbt26oVevXujTpw9atmwpdUx6S48fP8bFixcREBCAP/74A3FxcTAxMUH//v3x8ccfo1+/flBSUpI6Zp0RHR2NgIAABAQEwN/fH5mZmeJwT66urnBxcYGTkxOH12rASkpK8ODBAwQFBYlDsoWHh0NNTQ0fffQRevXqhV69eqFdu3YNqoOvoRYJSktLcfPmTQQEBODSpUu4cOECnj17VmmYOFdXV+jo6Egdl2qhzMxM3LhxQ2xPrly5gvT0dPFvNBcXF7i6uqJ9+/ZSRyUiqgtYJCBikYCIiKpy7do17NmzB8ePH8fjx49hbW2NTz/9FEOGDIGTk1OD6sRqCEJDQ3H8+HEcP34cd+/eRbNmzTBo0CCMGTMGrq6uUserdYqKihAQEIBjx47hr7/+Qnx8PLS0tNC9e3f07t0bvXv3hqWlpdQxqZaLjo6Gv78/AgICcObMGWRkZMDIyAh9+/bF4MGD0adPH6ioqEgd84NqSEWCpKQknDhxAr///jsuXryI7OxsGBoaokePHujRowe6d+/Ooju9s7KyMty8eRNnz57F2bNnERgYiJycHJiYmKBnz55wd3dHv379OMwgEVHVWCQgYpGAiIjKpaWlYf/+/fjf//6Hu3fvwsHBASNGjMDgwYNha2srdTyqIRERETh+/DgOHz6MmzdvolWrVhg/fjw8PT2hp6cndTzJFBYWwt/fH76+vjhx4gSysrLQoUMHDBgwAL1794azszMUFRWljkl1VGlpKW7cuAF/f3+cPn0aV69ehYaGBtzd3TFs2DD06dOnXt6JUt+LBOXtqZ+fH65du4bGjRujT58+6NmzJ3r06IFWrVpJHZHqqeLiYgQHB+Ps2bP466+/cOXKFSgrK6NPnz749NNP8fHHH0NXV1fqmEREtQWLBEQsEhAR0e3bt7FmzRocPXoUKioqGDFiBCZMmABnZ2epo5HEQkNDsXPnThw8eBC5ubkYPHgwFixY0KCGL7h+/Tq2bdsGX19fZGdno1OnTvjss8/w2WefoUWLFlLHo3oqMTERR48eha+vL4KCgqCuro5PP/0UU6ZMQefOnaWOV23qY5EgKSkJe/fuxf79+xEeHo5mzZrB3d0dn376KXr16lUviz1U+z158gQnT56En58fAgICUFpaim7dumHMmDEYOnQoVFVVpY5IRCQlFgmIWCQgImq4Ll++jG+//Ra//fYbHBwcMGfOHAwbNgyNGzeWOhrVMvn5+Th69Ch+/PFHhISEoG/fvli8eDG6dOkidbQPIicnB4cOHcLWrVsRGhoKBwcHjB8/HkOHDoWJiYnU8aiBSUpKwrFjx7B7926EhoaiTZs2mDJlCkaNGlXnJ7CtL0WC4uJi/Pbbb9i5cydOnz4NbW1tfPHFFxg6dChcXV05QTnVKs+ePcPp06dx+PBh/Prrr2jcuDFGjhyJCRMmNKiLAIiIXpAtL3UCIiIiopp2584d9OzZEy4uLnj69ClOnjyJmzdvYuzYsSwQUJVUVVUxevRo3LhxA3/88Qfy8/PRtWtXdOnSBX///bfU8apNamoq5s2bByMjI8yaNQt2dnYICgrC7du3MXv2bBYISBKGhoaYMWMGQkJCcO3aNbRr1w5z586FkZERZs+ejZSUFKkjNlhZWVlYvnw5TExMMHToUBQWFuLAgQNITEzExo0b0bVrVxYIqNbR0NDA559/jmPHjiE+Ph5ff/01zp8/DycnJzg6OuLQoUMoKyuTOiYRUY1ikYCIiIgajOzsbHz55Zdo164dcnJycO7cOQQFBeHjjz/mRMT0xvr27YsLFy7g0qVLEAQBHTp0wIwZM5CZmSl1tHeWkZGBb775BmZmZti/fz+WLFmCxMRE+Pj44KOPPpI6HpHI2dkZu3btQmJiIpYvXw5fX1+Ym5tj/vz5SEtLkzpeg/H06VP8+9//RsuWLbF+/XpMnDgRUVFR+OuvvzB8+PB6P+E01R96enqYO3cuwsPDcenSJdjY2MDDwwO2trbw8fFBSUmJ1BGJiGoEiwRERETUIPz++++wsbGBj48PtmzZgitXrqBbt25Sx6I6zMXFBRcvXsTOnTvh6+sLa2trHD9+XOpYb6W0tBTr1q2DmZkZtm3bhiVLliAqKgpz585FkyZNpI5H9FLa2tqYPXs2IiMjsWLFCuzduxdmZmZYtWoVO/U+oMLCQixbtgwtW7bETz/9hK+++goxMTFYsWIFWrZsKXU8ovfi4uKCgwcPIjw8HJ06dcKECRPQqlUrHDt2TOpoREQfHIsEREREVK8JgoBly5bB3d0dPXr0wIMHDzB58mTIy/PPIHp/cnJyGDNmDO7fv49PPvkEQ4cOxeLFi1FaWip1tNd68OAB3Nzc8PXXX8PLywvR0dGYP38+1NTUpI5G9MZUVVUxZ84cREdHY9GiRVixYgU6d+6Mu3fvSh2t3gkKCoKjoyPWrl2LxYsX49GjR/jmm2+gpaUldTSiamVlZYU9e/bgwYMHcHFxwWeffYYhQ4YgKSlJ6mhERB8M/3dMRERE9VZOTg4GDRqElStXYvPmzdi3bx90dXWljkX1kLa2Nnbs2IGdO3fihx9+wMCBA5GVlSV1rJfauHEjHB0dUVxcjJCQEHh7e0NDQ0PqWETvrHHjxli0aBFu3rwJJSUltG/fHmvXroUgCFJHq/Py8/MxY8YMdOnSBS1btkRYWBgWLlzINoPqPTMzM+zduxcBAQG4ffs27OzssHv3bqljERF9ECwSEBERUb2Ul5eHgQMHIjg4GOfPn8e0adOkjkQNwLhx43Dp0iWEhYWhX79+ePbsmdSRKigpKcGkSZPw5ZdfYtGiRbhy5Qrs7OykjkVUbaysrBAYGIhly5Zh8eLFGDt2LIqLi6WOVWclJyejW7duOHjwIHx8fPD7779DJpNJHYuoRvXo0QN37tzBxIkTMWHCBEyfPr1O3DFIRPQ2FKUOQERERPQhjB8/HuHh4Th//rwknaD79++v8L21tTU6dOiAzMxM/P777ygrKxPXKSgowNnZGVeuXHntcZs0aYI2bdrg3Llzb7StpqYmYmJixGVycnJo3rw5TE1NIZPJoKSkVOW+gYGBiI2NfeXxW7dujdatW782R0ZGBlxcXLBgwQKMGTMGJSUlOHHiBP773//C3d0dXl5erz1GXdK+fXucPXsWXbt2xejRo+Hn51crJsYWBAGTJk3CL7/8guPHj8Pd3V3SPImJiW/8OW7atCkiIiIqLFdUVMSIESNeul9hYSH27t2LW7duwcjICK6urnB2doa/v3+Vr/3XX3+tNPl0//79K9x9FBoaivDwcPF7VVVV5Ofni9/z/KodFBQUMH/+fLRp0wbDhg1DUVERDhw4wGHm3lJKSgq6d+8OALh27RosLS0lTlT5d2tVaqrNqEpiYiKOHDmCyMhI6Orqolu3bujcuTPi4uJQWloKW1vbNzoOgDc+l9me1AxVVVWsXbsWnTt3hoeHB7KysrB3714oKChIHY2IqFrwryQiIiKqd3bv3g1fX18cPnxYsqukZTIZPDw8MHHiRNja2qJDhw4Ang9L8/HHH+OXX36Bh4cHzp49i0GDBiE0NBSzZ89GREQEMjMzERERAQ8PD2zfvh3Z2dlITk7Gvn378NVXX+Hy5ctvvK2Liwt0dXXh4eGBOXPmIDk5GZcvX8Ynn3yCFi1a4K+//qoyv6urKwwNDeHh4YFvvvkG6urqUFdXR6NGjZCeno7ly5fj4MGDb/ReKCoqQldXF+rq6gCAhIQEJCUl4cyZM/X2Cl8rKyv4+vri9OnT2LJli9RxAABr167FgQMHcPToUckLBADe6nPs7OwMmUyG8ePHw8PDA5qamvjkk09eeuzMzEy0a9cOwcHBGDNmDDp06IBt27ZBXV0dZ8+erXIfNzc3XL16FR4eHpg2bRratm1baXgyW1tb3L17F2PGjIGKigoGDx7M86sW69u3L06cOAE/Pz8sXbpU6jh1SmFhodhOnD9/vlYUCADUqjbjn7799lt06tQJhYWFmDx5Mry8vFBcXIz+/fvDzc2tQtGisLDwtcd703OZ7UnNGjJkCE6cOIGjR4/i66+/ljoOEVH1EYgauMjISAGAEBISInUUIiKqBjk5OULTpk0FLy8vqaMIGhoagqmpaZXr1q5dKwAQ9u3bJwiCIOzatUu4cOGCuP7evXsCAGHatGnisrKyMmHs2LFvtW05TU1Nwc7OTvw+PT1dsLCwEOTk5IS///77pa9BVVVVaN26daXlSUlJwpw5c1718l8pLS1NACCsXbv2nY9RFyxatEjQ0tISMjIyJM0RHh4uKCkpCd9//72kOV70Lp/jli1bCrq6uq899qxZswQbGxuhrKyswvJ//etfwuzZs1+6X15enqCnpycoKioKT58+rXKbH3/8UZg5c2aFZTy/areffvpJUFBQEEJDQ6WOUsnKlSsFCwsLqWNUsmDBAkFLS0uIiIiQOkoFta3NKPfDDz8ISkpKwqVLlyqty8/PFzp27Cjs2rVLXPbVV18JpaWlrz3u25zLbE9q1q5duwQ5ObkKn0kiojosi3cSEBERUb1y4MAB5ObmYsmSJVJHgaqqKho1avTSdQDE9XZ2dnB1dX3l8eTk5DB16tS32racsrJyhSFvmjRpguHDh0MQBBw+fPilx3lZfgMDA0yfPv2VGV5FUbFhjHq5cOFCCIIg+USHy5cvh42NDebMmSNpjhe96+dYWVn5tce+fv06VFRUKg3ztGDBglcO/aSqqopp06ahpKQEx44dq3KbkydPYt68eRWW8fyq3aZNmwYnJyd4e3tLHaVOSElJwcaNG7F8+fJacwdBudrWZgDAoUOHMGfOHCxfvhwuLi6V1jdq1AibNm3C06dPAQB37tzB1q1bX5sJeLtzme1JzRo3bhz69u2LxYsXSx2FiKhasEhARERE9cqvv/6KAQMGVBompLZzdnZ+o/GyO3bs+FbbvoqmpiaA58MJvI14VzqHAAAgAElEQVTg4GCUlZXB3NxcXBYZGYkNGzZg6dKlOH36dIXtCwoKsG/fvgpDr/yz0+Xnn3/GoUOH4OvrKy7z9fXFoUOH4OfnJy6LiorCkiVLUFpail9//RXfffedOARCdnY2duzYgS+//BKbN29GTk7OW72uD0FTUxODBw/GqVOnJMuQn5+PEydOYObMmbVqTPbq+hxXxcbGBjdv3sTMmTNRVFQkLm/RogX69ev3yn2nTp0KFRUVbNq0qdK6+/fvQ1NTEyYmJq/N0NDOr0uXLuHrr7/G1q1bsX379rd6zTXBy8sLp0+frjTvBFXm6+sLJSUlTJ48WeooldTGNmPFihUAgAEDBrx0mw4dOsDNzQ1BQUH4+OOPkZubi8OHD+PIkSMAXn7uve98NmxPPqx58+YhKCgIUVFRUkchInp/Et/KQCQ5DjdERFS/mJqaCqtXr5Y6hiAIgtC8eXPBxsamynWbN28WAAhHjhypcn1Vwyi8zJts27RpU8He3r7CsrZt2woAKgyB8E86OjoVhi8oLi4WPv74Y6GoqEhcNnPmTMHNzU1IS0sT/vrrL0FOTk78Gdy7d08YPHiwAEBYs2aNuE9WVlaF4Quys7MFFxcXQVNTU9wmKSlJcHBwEPT19QVBEIS9e/cK+vr6AgBhz549gqOjowBACAoKEiIiIgR3d3fhzz//FG7evCnY29sL5ubmkg/zIwiCsGnTJqF58+aSPX9oaKgAQHjw4IFkGd7Em3yOraysBAMDg9ceKzIyUmjatKkAQLCyshJOnz79VlnGjBkjABDOnTtXYfns2bOFP/74o9L2Df38mj9/vnDgwAEhNzdXOHTokKCurv7K91cKiYmJAgAhMDBQ6igV1MbhhsaMGSP0799f6hivVRvajPL/SyoqKgqFhYWv3T4wMFAYNWqUAED49ddfhT///POV594/z+VXYXtS84qLiwVFRUXh8OHDUkchInpfHG6IiIiI6pecnBxxwr3aICkpCWPHjq302LdvX41nefbsGW7cuIGgoCCMHDkSN2/eFPO8SlRUFLp27YquXbvCwMAAv/76a4X1Pj4+6Nu3L3R1ddG7d2/Y2NiIVxO2atXqjSbu1dDQgKOjY4VlBgYGFa4I9fT0xIQJE8TvQ0NDcf/+fXTu3BnTp0/H+PHj0adPH7Rp0wZr165FVFQU1q9f/9rn/tA0NTXx7NkzyZ4/OzsbAKClpSVZhppmYWGBs2fPonXr1oiIiED//v0xYMAAREZGvtH+Xl5eAIANGzaIy/Lz83Hp0iX06dOnyn0a6vlVXFyMnTt3wsnJCWpqahgxYkSF49QW2traAICsrCyJk9R+WVlZ4vvVULxrmxETEyPu/ybDGrm6usLKygrA8zsP+vTp88pz722xPalZioqK0NDQ4B1KRFQvcHA5IiIiqleaN2+O5ORkqWOI9PX1sXnz5krLt2/fjmvXrtVoFgUFBcTGxiI+Ph59+vTBwoUL0aZNm9fuZ25ujgsXLgAAioqK4OHhUWH9b7/9BhsbGwDPhzYQBAH5+fni+jct2lQ1jMQ/l5XP5TBy5EgAgLW1NZKTk+Hv74+2bduK72lOTg6cnJyQl5f3Rs/9ISUmJkJPT0+y5zc0NAQAxMXFSZqjpjk4OCAkJAQ//fQTvL29cfr0aZw/fx5+fn4v7egv5+joCDc3N5w8eRKPHj2Cqakpfv75ZwwbNuylw3801PNLSUkJGhoa6NWrF7Zt24b+/fvj66+/fqNMNam8M7f8fKCXMzIyQmhoqNQxaty7tBnVNV5/Vefeu2B7UrOePn2KzMxMGBsbSx2FiOi9sUhARERE9Urnzp1x5swZcYxgqcnLy1f5n24VFZUaz6KmpoahQ4e+1zGUlZXxr3/9q0JngIuLC44fP45jx46hb9++aNmyJRITE8X11TkOflUdtOVXes6fPx9NmzattueqLmfOnHmnK0Kri4WFBUxMTODn54cOHTpIlkMKioqKmDVrFkaNGoUvv/wSPj4+GD58OGJiYl57Z4WXlxcCAwOxefNmrFu3Drt378bRo0dfun1DPr82b94MDw8PDBgwAJ07d8aePXvQrFmzastVHfz8/NC0aVO0bt1a6ii1Xu/evbF161bExcWhRYsWUsepUW/bZpRP7BwZGYn8/HyxY/xtve/cA1Vhe/LhHT16FCoqKujSpYvUUYiI3huHGyIiIqJ6ZeTIkbh69SpCQkKkjlJvde3aFQoKCuL38+fPx65du7Bjxw6MHj26xgsg5UM8VHXlq5TD/ADA3bt3cfbsWfFKSinIyclh8uTJ2LJlC1JTUyXLURPKO6DWrFlTYbmuri727t2LkSNHIjMzE0FBQa891uDBgyGTybBz504EBgbCxMSkRopQdfH8GjhwIB4+fIjZs2cjJCQETk5OuHfvXo3mfJXMzEz8+OOPmDhxYoX3lqrWv39/yGQyLFmyROooH9z7thlGRkaws7NDaWkpwsLCXvlcgiBUT+i3wPbkw8nJycHKlSvh6ekJDQ0NqeMQEb03FgmIiIioXunRowc6d+6MWbNmobS0VOo476y8M+FNOhXeZFtBEN65g+JV+4WEhGDt2rWYPn06GjVq9Eb7vIympiYKCwsrPffrfo7W1tZQUFDAf/7zHxQVFYnLU1NTceDAgbfOUV0EQYCXlxfatGmDgQMHSpYDeH5VvI6ODsaPH4+ysjJJs7zMm37mX7a+rKwMO3bsAAAEBgYiJSWl0jZDhgwB8GZDaigoKGDGjBnIysrC559/jmnTpr0yU0M9v3Jzc7Fjxw40adIEP/zwA86fP4+cnBwcOnTorTN+CIIgYPLkyVBSUsL8+fOljlMnKCsrY/369di3bx/2798vdZyXqi1txtKlSwE874B/8Rx5UWpqKnbv3l1h2Yf4G4XtSc0QBAFTpkxBXl6e+PMnIqrrWCQgIiKiemfr1q0IDQ2V9CpIQRCQk5ODjIyMKteXTyb7svXlnRU5OTmvfa7XbVtUVISMjAzxOd9UWVkZcnNzXzkhn5qaGoDnQ3mUlJQgICAAt27dQkZGBiIjI/Ho0SMxV25urrhfVctkMhkKCwvh7+8PQRDw888/4/Lly8jKykJWVhZKS0tRXFwMAEhPTxf309HRwdSpU3H16lV07doVBw8exJ49ezBq1ChJr+BfuXIlLl68iG3btlXrEA7vQkNDAwcPHoS/vz9mzpwpyRWtr/Mmn/nk5GSkpaVV6pwqLCzErFmz0LJlSwDPP7uenp6VjnXgwAG0bt0anTp1eqNMEydOROPGjdGsWTO4uLhUuU1DP7/Kysrwn//8BwUFBQCeD/lmaWlZa4YHmTdvHvz8/LBv3z7o6OhIHafOGDRoEL766itMmDABJ0+elDpOlWpLmzF06FCsWLECFy5cwKRJkyqcd8Dz+WBWr14tzg9Qfm6EhIQgMDAQBQUFVZ57L762fx7zn9ie1JzyCwCOHDmC/fv3Q19fX+pIRETVQyBq4CIjIwUAQkhIiNRRiIioGu3atUuQk5MTfvzxR0mef8SIEQIAAYAwZ84c4dq1a4IgCEJGRobw/fffC0ZGRgIAwcHBQdixY4eQn58v7nvgwAGhQ4cOAgBBW1tbWLFihRAfH1/l87xu2wsXLghDhgwRs0ybNk0IDg5+bf7z588Ln3/+uQBAkJOTE7766quX7ufh4SHIy8sLenp6wtatW4UVK1YI8vLywty5c4W4uDhh2rRpAgDB1tZWOH36tJCUlFRhmZ+fnyAIgpCbmyvY29sLAAQ9PT1h7969wuTJkwUdHR1h7ty5wrZt2wRra2sBgDBs2DDh1q1bYobc3FzB09NTfJ2amprC8ePHX/+D+kC2bt0qyMnJCVu2bJEsQ1WOHTsmKCkpCR4eHkJBQYHUcUSv+xxfvXpVGDVqlPjzNTY2Fjp06CA4OzsLrVu3FjQ0NAQ5OTkhISFBEARBGDVqlDB06FDB0dFRGDdunLB48WLBzs5O6Natm/Do0aO3yjZt2jThp59+qnIdzy9ByM7OFlRVVQUHBwdh48aNgre3tzBu3DihqKjord7n6lZUVCRMnDhRUFBQEA4dOiRplldZuXKlYGFhIXWMKpWVlQlTpkwRFBUVhQ0bNkgdp4La2Gb4+voK9vb2gqqqqtC1a1dh+vTpwqRJkwRvb2+hsLBQ3C46OlrQ09MTdHR0hP/973+Cr69vlefey87lf2J7UnNyc3OFYcOGCUpKSsKRI0ekjkNEVJ2y5AShFl5GRFSDHj58CEtLS4SEhKBdu3ZSxyEiomq0bt06zJs3D19++SVWr14NRUVFqSPVW6mpqdDW1oaSkhKA53dIvMtVu4IgICwsDObm5lBTU0NkZCSMjY3feDLItLQ0xMXFwcbG5p0nkHwfZWVlWLJkCb799lssXbq0Vo7pfebMGQwdOhQmJibYu3dvvfz7JzExEUZGRuLnKT09Hebm5jAxMXnrYz158gTq6uriVbhSqM3nlyAIyM/Px/9j787jqqrz/4G/2EH2Ha7sgiDgAgJuUC5IasJVy8pSMsd0asolTc1sxmqytGYam6ZGW1SssaQUxKWENBVxBUEWUa7ssiv7vpzfH/3u+Yq4oCKH5fV8PO6Dc88999zXvXDO1c/7fD6f1tZWZGRkYPDgwZ0azulRSktLw/z585GWloZdu3YhODhY0jx3s2HDBmzbtk0cG78n2rx5M9544w1MmTIFX375ZZ+czLgrzxm1tbVITk6Gs7PzHecxaW5uRktLiyTfUzyfPJjY2Fi8/PLLKCkpQXh4OCZOnCh1JCKirlTFIgH1eywSEBH1bbt27cLLL7+MkSNHYvfu3bC0tJQ6EvVRVVVVCA0NxS+//ILPP/8cCxculDrSHWVnZ2PBggU4ceIEVqxYgffff19sMCLqrdra2vD1119j+fLlGDp0KLZv3w43NzepY91VbygSAEBcXBwWLlyInJwc/PWvf8Wbb74p+TBqRN2hsrISf/3rX/H5559j6tSp+PLLLx+oeERE1MNV8VudiIiI+rQ5c+YgNjYWeXl58Pb2xg8//CB1JOqD9u7di6FDh4pjTPfkAgEAODg4ICYmBps2bcJnn30Gb29v7N27t0fOVUDUGVFRURg5ciSWLFmCd955BydPnuzxBYLeZOzYsUhISMCyZcvwzjvvwNfXl+cM6tNqamrwySefwNXVFT/++CN27dqF/fv3s0BARH0WiwRERETU540YMQLnz5/H1KlT8cILL2DSpEm4dOmS1LGoD8jIyMDUqVPx1FNP4fHHH0dCQgJ8fX2ljtUpqqqqWL58OZKSkuDu7o6nn34aPj4+OHDggNTRiDrt8OHDGD16NORyORwcHJCQkIA1a9ZATU1N6mh9jra2Nj744AMkJCTAwcEBTz/9NIYPH44ff/wRbW1tUscj6hKVlZX44IMP4OjoiPfeew8vvvgi0tLS8Mwzz0gdjYjokWKRgIiIiPoFExMTfP311zh58iQqKiowfPhwLF68GJmZmVJHo14oJycHr732GoYOHYqCggIcO3YMYWFhMDc3lzrafXNxccGPP/6ICxcuwNbWFsHBwfDx8cE333yD2tpaqeMRdVBfX48dO3Zg9OjReOKJJ2Bqaopz585h7969cHd3lzpen+fp6Ymff/4ZSUlJ8PDwwPPPPw83Nzds2rQJRUVFUscjeiCJiYl4/fXXYW9vj48//hh//vOfkZWVhY0bN8LExETqeEREjxyLBERERNSvjB49GmfPnsUXX3yBmJgYuLq6Yu7cuUhJSZE6GvUCly9fxksvvQQXFxfs378fn376KeLj4xEQECB1tIc2bNgwRERE4Ny5c3Bzc8Nf/vIX2NjYYMmSJUhNTZU6HhEuX76MN954AzY2Nli0aBEcHBxw6tQpHDhwACNHjpQ6Xr/j6emJXbt2IS0tDUFBQfjoo49gZ2eHmTNnYv/+/WhtbZU6ItFdVVRU4Msvv4SPjw+8vLxw+PBhrF27FtnZ2Xj//fdhamoqdUQiom7DIgERERH1O2pqali4cCEuX76M7du3IykpCcOGDcOUKVMQHh6OxsZGqSNSD9Lc3Iy9e/di+vTpcHd3x+nTp7F161ZkZGTglVdegbq6utQRu9TIkSPx3XffIT8/H2vXrsWhQ4fg6emJ0aNH4x//+AdycnKkjkj9SF5eHv71r3/B398fQ4YMQUREBN58803k5ubihx9+wOjRo6WO2O+5urri888/R0FBAbZt24aqqiqEhITA1tYWr7zyCg4fPoympiapYxIBAG7cuIGwsDDMmjULMpkMK1euhIeHB44fP4709HSsWrUKRkZGUsckIup2KgJnGqJ+TqFQwMXFBfHx8fD29pY6DhERSUAQBOzfvx9btmzBL7/8AmNjY8ydOxcLFy6Eh4eH1PFIIunp6fjmm2+wc+dOlJaWIjAwEIsXL8aMGTOgqtp/rrURBAExMTHYtWsXIiMjUV5eDl9fXzz99NN4+umn4ejoKHVE6mNycnLw888/46effsLp06dhaGiIkJAQzJkzB0FBQX3q+NuwYQO2bduGjIwMqaN0qatXr+J///sfIiIikJCQACMjI0ybNg0zZ87ElClToKenJ3VE6kfy8vIQGRmJiIgIHDt2DGpqapg4cSJmzZqF2bNnw9DQUOqIRERSq2KRgPo9FgmIiOhmBQUF2LlzJ7766itcvXoVTk5OmD59OmbPno1x48ZBRUVF6oj0CKWmpmL//v2IiopCXFwcZDIZ5s6di8WLF7MxHEBraytOnTqF8PBw/PjjjyguLoaTkxMCAwMRGBiIoKAgNrbQfauvr8fJkycRExODmJgYJCQkwNDQEMHBwZg9ezaCgoKgpaUldcxHoq8WCW6Wm5uLX375BVFRUfj1118hCAKGDx8unjcCAgL67O+XpFFTU4PTp0+3O6fo6Ohg4sSJmD17NuRyOb+riIjaY5GAiEUCIiK6HUEQcPz4cfz888+IiIhAXl4eHB0dMWvWLEyfPh1jxoxho0Yf0NzcjNOnT2P//v3Yu3cvMjIyIJPJMGPGDDz11FMYP358n7pquSu1tLTg2LFjOHz4MKKjo5GYmAh1dXWMHTsWkydPxuOPP46RI0dCR0dH6qjUwzQ2NiI+Ph7Hjx/H4cOHERcXh6amJgwdOhRBQUEICgrC+PHjoaGhIXXUR64/FAluVlZWhl9//RVHjhzBkSNHkJ2djQEDBsDf3x8TJ06Ev78/vL29ed6g+1JWVoYzZ87g+PHj+O2335CYmAgAGDFiBCZNmoRJkybh8ccf57/biIjujEUCIhYJiIjoXgRBwPnz57Fnzx7s3bsXly9fFhs1Jk2ahMDAQIwYMYKNyb2AIAhISkrCb7/9ht9++w3Hjx9HbW0tBg0ahFmzZmHmzJkYNWoUf5cPoKSkBDExMWLRoKCgABoaGvD29saYMWMwZswYjB07FjY2NlJHpW5WUFCAU6dOIS4uDqdOnUJCQgIaGxthZWUl9kCZPHkyrKyspI7a7fpbkeBWmZmZYsHg6NGjKCoqgrq6OoYNG4ZRo0bBz88Pfn5+cHNz43mZAAANDQ1ISEjA2bNnxdvVq1cBAO7u7pg4cSImTpyI8ePHw9jYWOK0RES9BosERCwSEBHR/crKyhIbmY8cOYKSkhKYmppi3LhxGDVqFEaPHg1fX1/o6+tLHbXfq6mpwfnz53H69GmcOXMGJ0+eRGlpKczMzDBhwgTxCkNnZ2epo/Y5mZmZOHXqlNg4nJycjJaWFtjY2MDHxwfDhw8Xb46OjhzKq4/IyspCUlISLl68iKSkJJw/fx65ublQU1ODp6cnxo4dizFjxmD06NFwcXGROq7k+nuR4FZZWVk4ffq02PibkJCAhoYGGBgYwNvbG0OHDhVvHh4e/J7t44qKipCcnIyLFy8iJSUFFy9eRHJyMpqbm2Fqago/P792xSRTU1OpIxMR9VYsEhCxSEBERA9DEAQkJyfjt99+Q1xcHM6cOYO8vDyoqalhyJAhYsFg2LBhbNB4xGpqapCamoqLFy/i3LlzOHPmDFJTU9Ha2gqZTIbRo0dj7NixmDhxIoYPH86rUrtZbW0tzp07h1OnTuHChQtISkqCQqFAW1sbDAwMxILB0KFDMXjwYLi6usLa2lrq2HQHRUVFuHz5Mq5cuYLk5GSxMFBRUQFVVVU4OTlhxIgRGDFiBMaMGcPC6R2wSHB3zc3NSEpKwpkzZ5CYmIiLFy8iLS0NNTU1UFFRgaOjI4YOHQpPT0+4u7vD2dkZzs7OMDExkTo6dZIgCMjPz4dCoYBCoUBqaqpYGCgrKwMAWFpaisWhkSNHYtSoUSzuExF1LRYJiFgkICKirlZQUIAzZ86IV68nJCSguroaKioqcHBwEBs0hg0bBjc3Nzg7O0NXV1fq2L1GXV0dFAoF0tPTxasLk5OTkZWVBUEQoKurCy8vL7FXx6hRo2Brayt1bLqN2tpasYE5MTERSUlJSE1NRVVVFQBAX18fgwcPFm+urq5wdnaGnZ0dLC0tJU7f95WUlCA3NxcKhQJXrlwRiwJXrlwRf0fq6upwcnLC448/Di8vL7HQw4JA57BIcP/a2tqQlZWF5OTkdrerV6+iubkZAGBqaioWDFxcXODi4gInJyfY2dnBysqKReJu1tjYiGvXriEnJ0csBmRkZIjL9fX1AAA9PT0MGTIEw4YNg6enp1gYsLCwkPgdEBH1eSwSELFIQEREj5ogCMjOzkZycnK77vJXrlxBS0sLAMDa2houLi4YNGiQ2LDh5OSEgQMHwtLSsl81aAiCgOLiYly7dg2ZmZlQKBS4evWq2Jhw7do1AH80Tjo7O4uNCMrCi6OjY7/6vPqim69SV94uX76MzMxMsRFQW1sb9vb2sLOzE28ODg5iI6CVlRWMjIwkfic9V1VVFQoLC1FUVIScnBzk5OQgNzdXvOXk5IgNdxoaGnB0dBQLNYMHD4aLiwuam5uxYcMGnDhxAkZGRnjmmWfwwgsvYNy4cRw+qpNYJOg6LS0tHRqhlQ3R2dnZaGpqAvDH3/PAgQNhY2MDe3t72NjYiMsymQyWlpYwNzfnJLedVFNTg+LiYhQXFyM/Px/5+fnieSQ/Px95eXkoKioSt9fX1xeLN8p/7yjv98d5SYiIeggWCYhYJCAiIqk0NTUhIyOjXQO4cjk3N1csIGhoaMDS0hJ2dnawtrbGwIEDxeKBqalpu5uJiUmPbZy7fv26eLtx4wauX7+OkpIS5Ofn49q1aygoKEB+fj4KCwvFhmA1NTXY2dmJxZObiyguLi5sxOlnWlpa2jViZ2dnt2vYzs3NRUNDg7i9lpYWLCwsYG1tDQsLC1hYWEAmk8Hc3BwmJiYwMjKCkZERjI2NxeXe2Kunrq4O5eXlqKioEG/l5eUoLy9HSUkJCgsLUVJSgpKSEhQUFKC0tLTD53RzscXe3l4swCh/amho3PH1r127hp9++glhYWFISEiAra0tZs6ciZdeegkjRozojo+g12KRoHu0tLSIDdg5OTntlvPy8pCfny8ObaNkaGgIKysrmJmZwdzcHFZWVrCwsIC5uTmMjY1haGgIQ0NDGBkZiT8NDAwkeocPr62trd05pKKiApWVlaisrER5eblYCCgtLUVpaSmKiopQWloqFhOBP76zraysxOKLra0tbG1tYWdnBxsbG/YCIyLquVgkIGKRgIiIeqLm5mbk5uaioKAAeXl5KCwsbNeYnpeX1+E/5wCgoqIiFgz09PRgaGgIbW1t6Orqtls2MDCAmpoaVFRUOlxtraOjA21tbfF+Y2Mj6urq2m1TWVmJtrY2tLW1obKyEnV1daivrxeXGxoaUFFRgdraWrEw0NbW1uF1zMzMYGtrC5lMJl7ZaW1tLa6zs7ODpqZmF3+61JcVFRW1awy/dVnZYF5eXo7GxsYOz9fQ0BCLBvr6+hgwYAC0tLTEY8bY2Bjq6urQ19eHtrY2dHR0APzROHa7BkJDQ8N2PVsEQUBFRUWH7aqrq8XCYH19PRoaGlBTU4Pm5mZUVFSgpaUFVVVVaGpqQm1tLWpqasTCgPIK6ZtpamrCxMREbNy0tLRsVzAxNzeHTCaDhYUFrKysuqy4mJqaivDwcISFhSErKwvu7u4IDQ1FaGgo55i4DRYJeo76+nrk5+eLjeDFxcUoKSkR7xcWFqKsrAylpaUoLy+/7XGn/E5V3tTV1WFoaAgNDQ3o6elBS0sLAwYMEL9ndXV1xe845XnlVnp6eh2KdHV1dR3OX7eeW2pra9HU1CSeW5Tf2+Xl5eJ3d2Njo1gMqK6uvu3noqurC2NjY1hYWIi9LJTnFeWy8jxiZWUFdXX1+/7siYhIciwSELFIQEREvVldXZ14Vf7169dRVlYmLtfU1KCyshL19fWoq6vrsNzW1obm5mbU1NS02+fNjZXA7RsulI0WygaRAQMGQFtbu8Oyrq6uWLQwMzNr1+thwIAB3fIZEd1JfX29eNX9rVfQlpeXo7q6Wmywr66uFhvslceN8jHg9sU0ZUPcrZQFB6XGxkbo6uqKx5myIVF5nCkbGw0MDMTH9PX12zVG3tojQurjq62tDXFxcdi5cyd++OEH1NTUYMyYMQgNDcWcOXM4Z8H/xyJB76UsjN98xf2tV+E3NzejsrISLS0tqK6uFs8TykZ+ZSEQABoaGtoV/gVBQEtLC2pra3Frs42mpuZtez3p6+uLjfTKQoTyPGJoaAg1NTUYGRmJRU1tbe3b9ohQ3gwNDdnoT0TUP7BIQMQiARERERFJadiwYRg/fjw+++wzqaM8Eg0NDYiOjsbOnTsRGRkJVVVVBAcHY968eZgyZcpdhzLq61gkoDs5ffo0xowZg6ysLDg4OEgdh4iI+rYqzuhGREREREQkIblcjsjIyA5XC/cV2traCA4Oxu7du1FUVIQtW7agvLwccrkcVlZWWLx4MWJjY/vs+yd6EBkZGdDS0oKtra3UUYiIqB9gkYCIiIiIiEhCcrkcubm5SNey8PcAACAASURBVEpKkjrKI2dsbIzQ0FBER0cjOzsbq1atwrFjxxAQEABHR0esWbOGV9UT4Y8e705OTu2GJiMiInpUWCQgIiIiIiKS0MiRI2FjY4PIyEipo3QrOzs7rF69Gunp6UhJScFzzz2HHTt2YPDgwfDx8cHmzZtRUlIidUwiSWRkZMDZ2VnqGERE1E+wSEBERERERCQhFRUVBAcH97siwc08PDzw0UcfIT8/H9HR0XB3d8e6desgk8kwefJkhIWFoba2VuqYRN1GOXceERFRd2CRgIiIiIiISGJyuRwXLlxAdna21FEkpaamhsDAQISFhaGkpAS7du2CtrY2Fi5cCJlMhtDQUERFRaGlpUXqqESPlEKhYE8CIiLqNiwSEBERERERSWzixIkwMjLC/v37pY7SY+jo6GD27NmIiopCYWEhPv74Y2RmZiIkJAT29vZYunQpYmNjpY5J1OXKyspQXl7OngRERNRtWCQgIiIiIiKSmIaGBoKCgvr1kEN3Y2pqikWLFiE2NhaXLl3Cyy+/jIMHDyIgIAAeHh5Yv349MjMzpY5J1CUUCgUAsCcBERF1GxYJiIiIiIiIegC5XI5jx46hvLxc6ig9mpubG9avX4+MjAycP38egYGB+OKLL+Di4gJ/f39s3rwZZWVlUsckemAZGRnQ0tKCra2t1FGIiKifYJGAiIiIiIioB3jyySehoqKCX375ReoovcbIkSOxefNm5OfnIyIiAk5OTli7di1sbGwQHByM8PBwNDU1SR2T6L4oFAo4OTlBTU1N6ihERNRPsEhARERERETUAxgaGiIgIIBDDj0ATU1NBAcHIywsDAUFBdi6dSsAYM6cObC0tERoaChiYmIgCILESYnuLSMjg0MNERFRt2KRgIiIiIiIqIeQy+U4dOgQr35/CIaGhggNDUVUVBRycnKwfv16pKamYvLkyeKEx4mJiVLHJLojhULBSYuJiKhbsUhARERERETUQ8jlclRXV+P333+XOkqfMHDgQCxduhTx8fFISUnBggULEBUVBS8vL3h4eGDjxo0oLCyUOiZROwqFgj0JiIioW7FIQERERERE1EPY2dlh+PDhHHLoEfDw8MD69euhUChw4sQJ+Pv7Y8OGDbCxsYG/vz+2bt2K6upqqWNSP1dWVoby8nL2JCAiom7FIgEREREREVEPIpfLERkZyfHzHxFVVVX4+/tjy5YtKC4uRkREBGQyGV5//XVYWFjgmWeeQVRUFJqbm6WOSv2QQqEAAPYkICKibsUiARERERERUQ8il8tx7do1XLhwQeoofZ62tjaCg4Oxe/duFBUVYcuWLSgvL4dcLoeVlRUWL16M2NhYFmyo22RkZEBLSwu2trZSRyEion6ERQIiIiIiIqIexMvLCw4ODhxyqJsZGxsjNDQU0dHRyM7OxqpVq3Ds2DEEBATA0dERa9asQUZGhtQxqY9TKBRwcnKCmpqa1FGIiKgfYZGAiIiIiIioh5k+fTqLBBKys7PD6tWrkZ6ejpSUFDz33HPYsWMHBg8eDB8fH2zevBklJSVSx6Q+KCMjg0MNERFRt2ORgIiIiIiIqIcJCQlBUlISsrKypI7S73l4eOCjjz5Cfn4+oqOj4e7ujnXr1kEmk2Hy5MkICwtDbW2t1DGpj1AoFJy0mIiIuh2LBERERERERD3M+PHjYWRkhKioKKmj0P+npqaGwMBAhIWFoaSkBLt27YK2tjYWLlwImUyG0NBQREVFoaWlReqo1IspFAr2JCAiom7HIgEREREREVEPo6GhgSlTpnDIoR5KR0cHs2fPRlRUFAoLC/Hxxx8jMzMTISEhsLe3x9KlSxEbGyt1TOplysrKUF5ezp4ERETU7VgkICIiIiIi6oHkcjmOHz+O69evSx2F7sLU1BSLFi1CbGwsLl26hJdffhkHDx5EQEAAPDw8sH79emRmZkodk3oBhUIBAOxJQERE3Y5FAiIiIiIioh5o6tSpUFVVxS+//CJ1FOokNzc3rF+/HhkZGTh//jwCAwPxxRdfwMXFBf7+/ti8eTPKysqkjkk9VEZGBrS0tGBrayt1FCIi6mdYJCAiIiIiIuqBDA0N8fjjj3PIoV5q5MiR2Lx5M/Lz8xEREQEnJyesXbsWNjY2CA4ORnh4OFpbW6WOST2IQqGAk5MT1NTUpI5CRET9DIsEREREREREPZRcLsehQ4fQ0NAgdRR6QJqamggODkZYWBgKCgqwdetWAMCcOXOwYcMGFBcXIyYmBoIgSJyUpJaRkcGhhoiISBIsEhAREREREfVQM2bMQG1tLX7//Xepo1AXMDQ0RGhoKKKiopCTk4NJkyahqakJkydPFic8TkxMlDomSUShUHDSYiIikgSLBERERERERD3UwIED4eXlxSGH+qCBAwdi7NixsLW1RUpKChYsWICoqCh4eXnBw8MDGzduRGFhodQxqRspFAr2JCAiIkmwSEBERERERNSDyeVy7Nu3j8PR9GEeHh5Yv349FAoFTpw4AX9/f2zYsAE2Njbw9/fH1q1bUV1dLXVMeoTKyspQXl7OngRERCQJFgmIiIiIiIh6MLlcjoKCApw/f17qKPSIqaqqwt/fH1u2bEFxcTEiIiIgk8nw+uuvw8LCAs888wyioqLQ3NwsdVTqYgqFAgDYk4CIiCTBIgEREREREVEPNnz4cDg6OnLIoX5GW1sbwcHB2L17N4qKirBlyxaUl5dDLpfDysoKixcvRmxsLHuY9BEZGRnQ0tKCra2t1FGIiKgfYpGAiIiIiIiohwsODmaRoB8zNjZGaGgooqOjkZ2djVWrVuHYsWMICAiAo6Mj1qxZg4yMDKljUidduHABERERSElJQUNDA4A/ehI4OTlBTU1N4nRERNQfsUhARERERETUw8nlcqSkpLAhmGBnZ4fVq1cjPT0dKSkpeO6557Bjxw4MHjwYPj4+2Lx5M0pKSqSOSXeRm5uLmTNnYujQoRgwYACsra3x5Zdfoq6uDh9//HGHAgIREdGjxiIBERERERFRD/fYY4/B2NgY+/fvlzoK9SAeHh746KOPkJ+fj+joaLi7u2PdunWQyWSYPHkywsLCUFtbK3VMuoW3t7e4LAgCioqKUFpaimvXrmHdunXtCgi7du2SMCkREfUXLBIQERERERH1cOrq6pg2bRqHHKLbUlNTQ2BgIMLCwlBSUoJdu3ZBW1sbCxcuhEwmQ2hoKKKiotDS0iJ1VAJga2sLY2PjDutbWlrQ1NQEAFBRUYGNjQ2efvrp7o5HRET9EIsEREREREREvYBcLkdsbCzKysqkjkI9mI6ODmbPno2oqCgUFhbi448/RmZmJkJCQmBvb4+lS5ciNjZW6pj9no+PD1RUVO74uIqKCj744ANoaGh0YyoiIuqvWCQgIiIiIiLqBaZOnQoNDQ0cPHhQ6ijUS5iammLRokWIjY3FpUuX8PLLL+PgwYMICAiAh4cH1q9fj8zMTKlj9ku+vr7Q1NS87WOqqqpwcHDAnDlzujkVERH1VywSEBERERER9QJ6enoYP348hxyiB+Lm5ob169cjIyMD58+fR2BgIL744gu4uLjA398fmzdvZi+VbuTt7S0OLXQrQRCwceNGqKurd3MqIiLqr1gkICIiIiIi6iXkcjl+/fVXNDQ0SB2FerGRI0di8+bNyM/PR0REBJycnLB27VrY2NggODgY4eHhd2zApq4xcuRICILQYb2qqirc3Nwwa9YsCVIREVF/xSIBERERERFRLxESEoK6ujocOXJE6ijUB2hqaiI4OBhhYWEoKCjA1q1bAQBz5syBpaUlQkNDERMTc9vGbHo4Dg4OMDQ07LC+ra0Nn3zyCVRV2VxDRETdh986REREREREvYRMJoOPjw+HHKIuZ2hoiNDQUERFRSEnJwfr169HamoqJk+eLE54nJiYKHXMPsXLy6vd5MVqamrw9fXFtGnTJExFRET9EYsEREREREREvUhISAgiIyPR1tYmdRTqowYOHIilS5ciPj4eKSkpWLBgAaKiouDl5QUPDw9s3LgRhYWFD7Tv1tZW9kz4/0aNGtVu8uLW1lZs3LhRwkRERNRfsUhARERERETUi8jlchQXF+PcuXNSR6F+wMPDA+vXr4dCocCJEyfg7++PDRs2wMbGBv7+/ti6dSuqq6s7vb9ff/0VwcHBqKysfISpe4ebJy9WV1fH448/jgkTJkicioiI+iMWCYiIiIiIiHqRoUOHwtnZmUMOUbdSVVWFv78/tmzZguLiYkREREAmk+H111+HhYUFnnnmGURFRaG5ufmu+/nuu+9w4MABjBo1ClevXu2m9D2Tt7e32KuipaUFH330kcSJiIiov2KRgIiIiIiIqJeZPn06iwQkGW1tbQQHB2P37t0oKirCli1bUF5eDrlcDisrKyxevBixsbEdhhWqqanB3r17AQBXr16Fl5cXoqOjpXgLPcKgQYOgp6cHAJg6dSpGjx4tcSIiIuqvWCQgIiIiIiLqZeRyOdLS0nDlyhWpo1A/Z2xsjNDQUERHRyM7OxurVq3CsWPHEBAQAEdHR6xZswYZGRkAgD179ojD67S0tKCmpgZTpkzpt+Pwq6ioiJMXf/jhh1LHISKifoxFAiIiIiIiol4mICAAZmZmiIqKkjoKkcjOzg6rV69Geno6zpw5g5CQEGzbtg2urq4YN24cNmzYABUVFXF7QRDQ1taGtWvX4rnnnkNdXZ2E6aXh5+eH2bNnY/jw4VJHISKifkxd6gBERERERER0f9TU1DB16lRERkZixYoVUsch6sDPzw9+fn749NNPcfToUWzduhWnTp3qMAQRALS1teHnn39GWloaoqKiYG9vL0HiB1NfX4+GhgaUl5ejoaEB9fX1aG1tRVVVVbvtbrcOADQ1NfHEE08gJiZGXGdgYAA1NTXo6OhAW1sbRkZG0NbWxoABAx75+yGizqurq0NjYyPa2trEydiV65SqqqrQ2tp6x33c63FVVVUYGhp2+nFNTU3o6uoCAAwNDaGqqtpuHdGdsEhARERERETUC8nlcjz77LMoLS2Fubm51HGIbktNTQ2BgYFITk7G3r170dLSctvtWlpakJ6eDi8vL+zZswfjx4/vtoytra0oLi7GtWvXUFJSguvXr+PGjRvtbjevq62tRWNjIyoqKroto5KhoSG0tbWhq6sLIyMjmJmZwcTERLyZmpqKy+bm5rCxsYGlpSXU1dn8Q/1PW1sbysvLUVFRgYqKCpSXl6Ompgb19fWorq5GdXU1GhoaxOX6+nrU1NSgqqoKDQ0N4nJraytqa2vR1NTUriDQGymLkBoaGtDT0xOLDLq6utDR0YGBgUG7ZT09Pejo6EBfX7/dspGREYyMjGBsbAwjIyOoqalJ/dboIfFbgoiIiIiIqBd64oknoKGhgQMHDmD+/PlSxyG6q+3bt9/1alkAaG5uRlVVFSZPnowvv/wSCxcu7JLXLi4uRmZmJjIzM5GdnY3CwkLk5eWhqKgI+fn5KC4ubpdNW1u7Q4O7ra0tRowYARMTE+jq6kJLSwtGRkbtrvbX0tISr9Y1MjJqN7TSndaVl5e3uy8Iglh8UF6RfHMvhcrKSjQ2NqKmpgbl5eVi8SItLa1dIaO+vl7cp6qqKiwtLTFw4EDIZDLY2NjAysoKDg4OcHJywqBBg2BlZdUlnzXRo9Dc3IyysjKUlZWhpKQExcXFKCsrEwsAtxYClMu3670DAOrq6tDX14e+vj60tbU7LMtksnYN4xoaGuKxDvwxFwvwx7lCR0cHwP8d3zevA9Duebdz6/a3Uh77d9LY2NhuqDZl7ybg/84vN++joqICgiCI61paWlBdXd2ueFJcXCwu37y+pqYGzc3Nt82hLBwoiwa3WzY3N4eFhQUsLCxgZmYGc3NzaGho3PG9UfdikYCIiIiIiKgX0tPTw8SJExEZGckiAfVo6enpuHjxYqe2VTbWL1q0CGfPnsV//vOfTjUi3bhxA8nJyUhLS0NGRoZYFMjMzERtbS2AP4bhsLe3h7W1NWxtbeHi4gIbGxtYW1uLDehWVlbdOqyPsrHxZiYmJg+937q6OhQXF6OgoADXrl1DYWEh8vPzUVRUhNTUVMTExCAnJ0ccFmXAgAFwcnISby4uLhgyZAiGDh0KMzOzh85DdKuWlhYUFxcjNzdX/PssLS1FSUkJSkpKUFZWhtLSUpSWluLGjRvtnquuri72orm5MdrGxqZdw/TtGqr19fV7Vc8abW3tuxYZupty6DRlIeZuRZqysjIoFApUVFTgxo0bKCsr61BkMDIygqWlJczMzGBmZgYLCwvxvvL8bGdnB0tLSxYUHrHec1QQERERERFRO3K5HMuXL0ddXR3HK6ce67vvvgPwR8PevYakEAQBKioqaGpqwldffYXLly/jp59+EofUamxsRFJSEi5evIjU1FSkpKQgNTUVhYWFAP5ocHJxcYGTkxOCg4PFRu9BgwbBxsYGqqqqj/bN9hADBgyAo6MjHB0d77hNW1sbrl27hszMTFy9elUsqsTFxWHHjh3iVciWlpbw9PSEh4cHPD09MXToUIwYMaJHNVxSz9Lc3Izc3Fzk5OQgPz8f165dQ0FBAfLy8sTCVVFREdra2sTnWFlZwdzcHObm5rC0tISXl1e7+8orz83NzWFqairhu+vf1NTUYGxsfNsCZ2fcuHFDLAKVlZWhuLi43f3MzEycPn0apaWlKC4uFuexUVFRgZWVFWQyGQYOHCgWEGxtbSGTyWBvbw8HBwdoamp25dvtV1SE280aRNSPKBQKuLi4ID4+Ht7e3lLHISIiIiLqtOLiYshkMkRERCA4OFjqOHSfNmzYgG3btiEjI0PqKI/Uvn37UFRUdM9hM243uW9FRQUaGhpgaGiI+Ph4xMfHo6GhAZqamnB2doaHhwfc3d0xcuRIeHh4wNHRscOQPvRgysvLkZqairS0NKSmpiI+Ph5JSUmoqamBuro6Bg8ejJEjR4o3Pz8/NtD1I+Xl5e167Nx8y83NFecf0dLSgomJCWQyGZycnGBtbQ2ZTNbup4ODAyfWpQ6am5tRWlqKwsJCFBQUtPuZmZkpFp6qq6vF5xgbG7frFXXzzd7ennMn3FkViwTU77FIQERERES92ejRo+Hp6Ymvv/5a6ih0n/pLkaCzWltbER8fjyNHjuDo0aM4deoUqquroaOjgxEjRsDX1xe+vr7w8/ODs7Nzv+kV0JMIgoCrV6/i7NmzOHfuHM6dO4cLFy6grq4Oenp6GD16NCZMmIAJEybA19e3Vw3rQh1VV1fj8uXLuHTpEi5duiQuZ2VliePea2pqwsHBQey5cvPNwcGBw1XRI1dWVoacnBxkZWV1uGVnZ4vDqmlpacHBwQFDhgyBm5sb3NzcxGUDAwOJ34XkWCQgYpGAiIiIiHqzDz/8EP/6179QUFDAK+R6GRYJgNTUVBw+fBhHjhzB8ePHUVVVBWtra0yYMAEBAQEYNWoUPD09ORZ1D9bS0oKUlBScPXsWJ06cwJEjR1BQUAB9fX0EBARgwoQJmDx5MoYPHy51VLqDyspKJCUlIS0tDWlpaUhPT0d6ejry8vIA/FEIGDx4MIYMGQJXV1c4OzvD0dERTk5OkMlkLNhRjyUIAgoKCpCVlSUOrZaeno7Lly8jPT1dLCAMHDhQLBy4u7tjyJAh8PLygpGRkcTvoNuwSEDEIgERERER9WZpaWnw8PDAyZMnMXbsWKnj0H3oj0WC1tZWnDp1Cvv370dkZCTS09Ohr6+PUaNGITAwEIGBgfD29uaQQb1cZmYmYmJiEBsbi6NHjyI/Px/29vZ44oknMH36dDzxxBMcmkgiymGklMN3xcfHIz09HW1tbTA0NISzszOcnJzg7u4uDufl5ubGIjT1SQUFBUhLS0NmZqY4vFpKSgqKiooAANbW1uKQasrjwd3dvS9+R1Wx3xcREREREVEv5u7ujsGDByMyMpJFAuqR2tra8Ntvv+G7777DgQMHcP36dQwZMgQzZsxASEgIRo0axSuR+xgnJycsWrQIixYtgiAIOH/+PCIiIrBv3z5s3boVxsbGmDZtGl544QUEBQWxAfoRqaqqwsmTJxEXF4dz584hMTERxcXFAAAHBwd4eXnh2WefhZeXF0aMGAFbW1uJExN1L5lMBplM1mF9QUEBLly4gMTERFy4cAE7d+5EZmYmAMDc3FwcAm/cuHEYO3Zsn+hxwJ4E1O+xJwERERER9XYrV67Evn37cOXKFamj0H3o6z0JMjIysGPHDoSFhSEvLw+jR4/GrFmzMGPGDLi4uEgdjyRy9epV7Nu3Dz///DPi4uJgbW2NefPmYf78+XBzc5M6Xq+Wl5eHEydOIC4uDidOnEBKSgra2towePBgjBo1CiNGjBALAsbGxlLHJepVKisrxaLBhQsXcPbsWaSnp0NVVRXu7u4ICAjA2LFj4e/vDwcHB6nj3i8ON0TEIgERERER9XYnTpzAY489hvT0dLi6ukodhzqpLxYJ2traEBERgX/961+IjY1lAzDd1a2FpDFjxmDZsmV46qmn2LugE27cuIHDhw/j0KFDOHr0KPLy8qChoQFvb2+MGzcO/v7+GDduHCwsLKSOStQnlZaWIi4uDrGxsYiLi8P58+fR1NSEgQMHYvz48Zg6dSqeeOKJ3jCBN4sERCwSEBEREVFv19raCmtra6xcuRKrVq2SOg51Ul8qEjQ2NiIsLAyffPIJFAoFgoODsXjxYg4lQ52iHJJq69at2LNnDxwdHbFixQrMnz8fOjo6UsfrMdra2pCQkIBffvkFBw8exNmzZ6GiooJx48YhMDAQAQEB8PX1xYABA6SOStQvNTQ04Ny5c4iNjRXnZWlpaYGPjw+mTp2KqVOnwtfXtycOscciARGLBERERETUF7z00ku4cuUKTp48KXUU6qS+UCRobW3FV199hXfffRfl5eWYO3cuVq5cyV4D9MAUCgU++eQT7NixAwYGBnj77bfx6quvQl29f06rKQgCYmNj8d133yEiIgIlJSWQyWRig2NgYCAMDQ2ljklEt1FdXY3ffvsNhw4dwqFDh5CXlwczMzOEhIRg3rx5eOyxx3pKwaCqR6QgIiIiIiKihyOXy3H69GkUFRVJHYX6iePHj8PHxwdLlizBnDlzkJWVha+//poFAnoozs7O+O9//4vs7GzMnz8fq1atwogRI/Dbb79JHa1bpaen45133oGTkxMee+wxnD59GsuWLUNiYiKuXbuGr7/+Gk899RQLBEQ9mL6+PmbMmIEtW7YgNzcXycnJePPNN5GYmIgJEybAwcEBb731FlJTU6WOChYJiIiIiIiI+oCgoCBoa2vj4MGDUkehPq6yshIvvPACxo8fDysrKyQnJ+Of//wnrK2tpY5GfYilpSU2btyI1NRUDBo0CIGBgZg9ezZu3LghdbRHpqGhAd988w38/PwwZMgQbNu2DbNnz0ZSUhKSkpLw1ltvYfjw4VLHJKIH5OnpiVWrViE+Ph6pqamYO3cu/ve//8HT0xPe3t7473//i7q6OkmysUhARERERETUBwwYMACTJk1CZGSk1FGoD0tMTISPjw9+//137Nu3D4cOHeJk2fRIDRo0CJGRkfj1119x9uxZeHt74+zZs1LH6lIVFRV49913YWdnh7/85S9wdXVFTEwMcnNzsWnTJgwbNkzqiETUxdzd3bFhwwZkZWXh999/h5eXF5YvXw5bW1usW7eu2wuiLBIQERERERH1ESEhIYiOjkZtba3UUagP2r59O8aMGQM7OzskJCRg+vTpUkeifiQoKAgJCQlwd3dHQEAA/vvf/0od6aE1NDRgw4YNcHJywmeffYZXXnkF2dnZ2LlzJyZNmtRTxionokdIVVUVjz/+OL755hvk5uZi+fLl2Lp1KxwdHfHuu+92W88Cnm2IiIiIiIj6iJCQEDQ2NiImJkbqKNTHfPbZZ1iwYAGWL1+Ow4cPw9LSUupI1A+Zmppi//794mTGmzZtkjrSA4uOjsbQoUPx4YcfYsmSJcjMzMS7774LKysrqaMRkUTMzc2xbt06ZGZmYtWqVfj000/h4eGBAwcOPPLX7p9TwxMREREREfVBFhYWGDVqFCIjIyGXy6WOQ33Ezz//jGXLlmHjxo148803Jcnw3Xff3XMbExMTmJmZ4cqVK+3Wq6ur47nnnrvj8xobG7Fjxw4kJSVh4MCB8Pf3h5+fH6KjoxEcHNypfJcuXcLx48eRkpICExMT+Pj4IDAwEDo6Op16PnWeqqoq/vrXv8LExARLliyBTCbD3LlzpY7VaS0tLVi3bh02bdqEWbNm4ejRo7CxsZE61j2dPHkSWVlZ7da5urrC19cXFRUVOHjwINra2sTH1NTU4Ofnh1OnTt1z3yYmJhg+fDiOHj3aqW0NDAyQnZ0trlNRUYGFhQUcHR1hb28PDQ2N2z43Nja23fOAP/6eTExMYGVlBXd3d2hqat4zw73k5ORg69at+P777zu83sO4du0awsPDkZGRAVNTU4wfPx5jxoxBbm4uWltb4e7u3mWvdTfl5eUYN24cVq9ejRdffLFbXrO/0dPTw9tvv40FCxZg5cqVCA4OxpIlS7Bp06Yu+Ru9HfYkICIiIiIi6kPkcjn27duH1tZWqaNQH5Cbm4uXXnoJr7zyimQFAgBYtmwZrly5goqKCly5cgXz5s3D1q1bUVVVhcLCQuzcuRMrVqyAn58f7O3tsWDBAsybNw8GBgYICQm5434rKirEMe5ffPFF+Pr6YsuWLdDT08ORI0fumau2thbLly/H3LlzMWjQIPztb3/DzJkzcfToUYwcORIXLlx4oPfb2Nj4QM/rT1577TWsWLECixYtgkKhkDpOpzQ1NeHZZ5/F5s2b8emnn+Knn37qFQUCABg3bhzs7e0xb948LFy4EO7u7vD19QUAGBkZYfr06di9ezfmzZuHI0eOQC6XIyEhodPHblxcXKe3HTduHExNTTFv3jwsBS6bjwAAIABJREFUX74chYWFiIuLQ0hICOzs7HD48OE7vgczMzOEhobijTfeQGtrK0xMTFBYWIi33noLQ4YMQXh4+EN/VpmZmfj999+Rn5//0PtS+vDDDzF69Gg0NjZi0aJFWLp0KZqbmzF16lQEBAR0KI4+Surq6jA1NYWenl6nn8Nz2oOxtrbG999/j59++gnbt29HSEgI6uvrH82LCUT9XEZGhgBAiI+PlzoKEREREdFDu3TpkgBAOHHihNRR6B4++OADwdnZWeoYdzV79mzBzc1NqK+vlzTHsWPHxGXl3/grr7wirmtraxPmz58v3ndwcBBMTU3vud8lS5YIQ4YMEdra2tqtf/XVV4Vly5bd8/nTpk0TnJ2dhbq6ug6Pvffee4KmpqZw5syZe+7nVitWrBBaW1vv+3n9TVNTkzB8+HDhySeflDpKpzz33HOCoaGhcPLkSamjPDB9fX3B0dHxto99/PHHAgBh586dgiAIwrffftvpY/d+tlUyMDAQPDw8xPvXr18XnJ2dBRUVFeHChQt3fA8mJiaCq6trh/XLli0TAAh79+6920fQKW+++aagpqb20PsRBEH49NNPBQ0NDSE2NrbDY/X19cKoUaOEb7/9tkte61HhOe3hnT9/XjA1NRVCQkI6fGd1gUr2JCAiIiIiIupD3Nzc4OrqisjISKmjUC+XlZWFPXv24P3334e2trakWfz9/e/6uIqKCv785z+L9zU1NTs1JMO5c+egpaUFFRWVdutXr17dYd2tvvjiCxw8eBDr1q277bBCy5Ytg66uLhYuXIjm5uZ7ZlFKTk7uE5PydgcNDQ1s2LABBw8eRFpamtRx7ur777/H7t27sWfPHowdO1bqOA9MR0fnjucD5XGgfNzDw6PTx+79bKukqanZ7jg1MTHBs88+C0EQ8MMPP9xxP3c6N7z++usA/pik/WHdacij+7Vr1y4sX74c77//PsaNG9fhcW1tbfz73//GjRs3uuT1HgWe07rGyJEjsW/fPhw8eBBbt27t8v1zTgIiIiIiIqI+JiQkBHv37sXHH38sdRTqxQ4cOAB9fX3MmDFD6ihQVb33NY6jRo267/0OGTIE3377LV5//XX84x//EBsP7ezsMGXKlLs+d/369VBVVcWcOXNu+7i+vj5mzpyJb7/9FuHh4VBTU0NbWxs0NDTw9NNPAwB++uknNDc3Q0dHBzNmzMDJkyfx/PPPo7a2Fj/88AM0NDQwe/ZsAEBDQwPCw8ORmpqKMWPGICgoqF1xorGxEceOHcOxY8cgk8kwZcoUDBo0SHw8Ozsb27Ztw5o1a1BcXIzt27fD0tISc+bMgZGREa5evYrw8HBoamripZdegrGxcbv3U1VVhR9//BGXLl2Ck5MT5s+ff1/DjTwqU6dOhaWlJfbt29dtY7I/iA8//BAvvfQSJk6cKHWUbuPn59ep7e7n2L3XtgYGBgDwQEP9FBcXA+hYRLjXsQUAzc3N2Lt3Ly5cuIDx48e3m58hMjISdXV1AP4odCjnSElNTcXFixcBAEFBQTA1Ne2Q6e9//zsAYNq0aXfM7evrC0EQOp1XoVBg+/bteO+993D16lXs3r0bFhYWmD9/frviRmxsLA4dOgRbW1uoqqpi0aJFAP7vXGRpaYmgoKC7bn+3c9rdzimdzXin8+LDfOY92dixY/Hqq69i48aNWLhwIdTU1Lps3+xJQERERERE1MfI5XIoFApcunRJ6ijUi6WkpMDb2xvq6n33+sK33noLZmZm+PzzzzF06FD88ssv4mM3N37dqqCgAKWlpbC2tr5rjwV7e3sAQGJiIqZNm4b//Oc/+NOf/iQ+Pm7cOHz44Yd45ZVXAACCICAgIAAAYGhoCENDQwB/TIQaFBSExsZGvPbaa/j3v/8NT09PNDQ0APijoWzKlCkoLy/Hm2++CUEQ4OXlhT179gAAfvjhBwQEBOC9997DgQMH8Ne//hUKhQKvv/46/vSnP+H48eNYt24dUlJSsHr16g4TAWdkZGDu3Lmwt7fHiy++iC1btmDEiBGoqKjo9Gf9qKioqMDPzw8pKSlSR7mjwsJCpKamYt68eVJH6fN27doFAJg0adJ9Pa+iogJr166FtrY2Fi9eLK6/17EFAJWVlZg6dSouXbqEN998E8XFxfjnP/8pPu7q6ooVK1bg+eefh4+Pj7h+yJAh+Oabb3Djxg2YmJh0yKRQKJCWlgZ1dXW4urreNb+yIHOvvDt27IC/vz8++OADHDhwAGvWrMGpU6ewaNEivP/+++L+Vq9ejdzcXLz99tswMjLCihUrAADp6emYM2cOQkNDkZiYeM/t73ROu9s5pbMZ73ZefNDPvDcIDQ1FVlYWrl692rU77uoBjIh6G85JQERERER9TWtrq2BlZSV8+OGHUkehu+jpcxI8//zzglwulzpGB7cbq/xWgwcPFqytrTu1v4sXLwrDhg0TAAgAhKlTpwpXrly563MOHTokABBGjx591+2+/fZbAYA4Zv5rr70mGBgYtNtm4cKFgpWVlXj/3XffFQC0G3N68uTJwqJFi8T7+/fvF1RUVIQ9e/YIgvDH7+qll15qt9+nn35a0NHREfLy8trtNzIyUtzm1VdfFQAIYWFh4rp169YJAITKysp2r3/zOO3K9//OO+/c9f13l7lz5wrBwcFSx7ijixcvCgCEtLQ0qaM8NAsLC8HQ0FB48cUXO9xGjRolABDCw8Nv+9zOHLv3s62ZmZlgb28vnDt3ToiNjRWee+45AYAwf/78u47ZbmVlJWhrawtPPvmkMHv2bMHLy0vQ09MTzMzMhOTk5HbbdubYevXVV4UZM2a022b69Ont5iT4/vvvBQDCr7/+Kq5ramoSfHx8hJaWltvmjI6OFgAIbm5ud3wvt+pM3lWrVnU4F0yYMEEYPHiwmMvU1FS4fPmy+PjSpUvF5WvXrgkAhI0bN3Zq+zud0+52TrlXRuU+7nZefJDPvDfIz88XAHT13Cack4DoXuNMEhERERH1Nqqqqpg2bRrnJaCHYmlpiWvXrkkd45EbOnQo4uPjsXnzZhgbG+PQoUMYPnw4Dh8+fMfnKK+Graqquuu+hf8/BIhySIvbDZt0r6GUFAoFoqOj2w379OSTT6KoqAgzZ85EXV0dwsPD4eXl1e55r7zyCurr67Ft2zYAEIfxeOyxx8Rthg8fDqD9nA9ubm4AIP7uCwsLER0djbi4OLz11lt46623cODAAfj4+IjDeUgtPz8fVlZWUse4I0dHR6ipqSEpKUnqKF3CysoKn3/+eYfbM8880+1Z1NTUkJOTg3PnziEoKAiJiYnYtm3bPdt67OzssH//fvz4448IDw/Hli1boKKigqlTpyIsLAwAOnVslZSU4KuvvurQ82jYsGHt7j/77LNwdnbGJ598Iq7bu3cvZsyYccchY+63F1dnzwW6uroA2g9h5OnpKQ7RpKGhAX19fQQGBuLQoUMAgLffflvc9tZhxu61/a06c065V8Z7nReBB/vMe4MLFy5ARUWlw5BXD6vv9hkk6iTlWGb3M5EUEREREVFPJ5fLsX37dhQWFsLa2lrqOHQbzc3NXTa55aMwZswY/Pvf/0ZZWRnMzMykjvNIqaurY8mSJXjhhRfwxhtvICwsDM8++yyys7PFgsDNlGPf5+Tk3HW/ygYtT0/PB86mHDbs1oY5CwsLAEBcXByam5s7NCi6uLgAAK5cuQLg/4oRNzeeamlpdXg95fBJyv8jZ2RkAABWrVrVI/8OqqqqcPr0acyfP1/qKHekp6eHkJAQfPrpp5g9e3avbqAE/vhbut18FLf7e3rUBgwYgKeeeuq+n6c8DpSNrYMGDcKYMWMwePBgLFiwAH5+fsjPz7/nsZWUlITm5uYORapbixRqampYvXo1Xn75ZZw9exZ+fn745ptvsGPHjjtmVL5ORkYG6uvrbztB+s3u91xwM11dXbS0tIj3P//8c8ybNw/Tpk3DmDFjsH37dpibm9/x+Xfb/ladOafcK+O9zovAg33mPV1bWxs++eQTBAYGwtLSskv3zZ4E1O8pv8SampokTkJERERE1HUmT54MHR0d7N+/X+oodAc9vUgwbdo0GBgY4D//+Y/UUbqcspFq48aN7dabmppix44dmDNnDioqKnDy5MnbPt/Q0BBeXl6ora2967jQ6enpUFVVxeTJkx84q7Jh8Ndff+3wWGlpKVpbWwH80UB4M2Xj2+DBgx/4tYH/KxokJCR0eKy6uvqh9t0VtmzZAg0NDcjlcqmj3NX777+P5ORkrF27VuoodAeOjo7w9fVFa2srzp4926ljS3kMFBYW3nP/oaGhGDhwID744ANcvnwZRkZGd+0BM3DgQHh4eKC1tfWec24IgtCl54Inn3wSCoUCy5YtQ3x8PHx8fO46z9H9bN8V55R7nReV7vcz7+nef/99nDp1Chs2bOjyfbNIQP2eskjQ2NgocRIiIiIioq6jo6ODwMBADjnUg/X0IoGuri5WrlyJTZs2QaFQSB1HpBzCR/nzXtvdqq2tDV999RUA4MSJEygqKuqwzaxZswB0vEr1Zl988QVUVFSwadOm2z6en5+Pn3/+Ga+99hpGjBgBADAwMOjwf8+bG/duplzn7u4OVVVVREVFtdvu6tWrOH/+PLy8vKClpdWhoKFsKFNOGvqgXF1doaamhr/97W/tLq4rLS3F999//1D7flh5eXn4+9//jqVLl8LIyEjSLPfi4eGBLVu24JNPPsGaNWvQ1tYmdaRu19ljt7PbCoLQqX3dj+vXrwP4Y1LxzhxbyuG5lMPs3OzW37GmpiZWrlyJqKgoLFu2DH/+85/vmefdd98F8MdV93e6uLW0tBTbtm3rsnNBbW0tvvrqK5iYmODTTz/F77//jpqaGnFS6AfdXnn+6opzyr3Oi0oP8pn3RIIg4L333sO7776Lzz77rN1kzF2FRQLq9/T19aGqqoqKigqpoxARERERdSm5XI6YmJgecbUvddTTiwQAsHLlSri6/j/27jssiut9G/iN9F4FRBQQBKRo7CZgwRb7GrHEgmiMNSZ2TTSmqWkmmqZGTb6xpVlDbEksSERNQEQREaSL9I70dt4/8mNfURBUYBa4P9e1F8vu7Mw9k51jOM/MOQ7w9PREfn6+1HEAQN6p/7g8ycnJyMjIeKRDvqSkBG+88Qasra0B/NeJN3PmzEfW9eOPP6Jr167o169frdvo168fNmzYgH379uHChQvV3svLy8PcuXPRr18/bNq0Sf66lZUVSkpKcObMGQgh8Ouvv+Ly5cvIzc1Fbm4uKioq5EN0BAUF4eLFizAyMsLMmTMREhKCSZMm4fz589i2bRvWr1+PESNGwNTUFK+//jpiY2Ph6+sr39Zvv/2GSZMmYeDAgdWOV0FBgXyZqiGFioqK5K9VDedRtZyhoSEWLFiAf/75BwMHDsRPP/2EPXv2YPr06Zg6dWqtx6exFRUVYcKECbC0tHzs+OeKxMvLC3v37sXWrVsxatQopKamSh3piQghkJ+fj+zs7Brfr5qjo7b363Pu1nfZ0tJSZGdn1zkvSE2fe/BK8yr37t3DypUrcefOHcyaNQu2trb1OrecnJwwYsQInDhxAnv27JFv4/r16xBCICEhodowPnPnzoWxsTFiY2Ph4eFRZ15PT09s3LgRfn5+mDt3brXzFwDu3r2Ljz/+GF5eXvVuC7KysgA8et6XlZWhpKQElZWVePfdd1FcXAzgv6HnOnfuLG+bHm5L6lr+4TZNU1OzzjalrowWFhaPbRcf9KTHXNFkZGRg/Pjx2LBhA7799lvMnz+/cTbUkNMgEzVXxsbGYtu2bVLHICIiIiJqUBkZGUJZWVkcOXJE6ihUg8WLF4sBAwZIHaNOcXFxwszMTPTv31/k5eVJmuXHH38UvXv3FgCEgYGB2Lhxo0hISJC//88//4jp06cLAAKAsLS0FL179xZ9+vQRXbt2Fbq6ukJJSUncu3dPCCHE9OnThaenp+jevbuYPXu2WLt2rXB2dhaDBg0SsbGx9crk6+srunXrJl555RXx9ddfi5UrV4q+ffuKDz/8UFRUVFRbtqCgQLi4uAgAwszMTOzdu1fMmzdPGBoaipUrV4qMjAwRExMjzMzMhKGhofjuu++EEELk5uaKl156Sb5f1tbWIjAwUL7eiooKsXz5ctG2bVuxZs0a4e3tLSZPniyKioqEEEL89ddf8u0uWLBAREREiFOnTsmP5YwZM0RISIg4f/68cHd3FwDExIkTRVhYmDz3zJkz5dvX09MTx44de+r/js+qoKBADB06VBgbG4vIyEjJcjytgIAAYWNjIwwNDcX27dtFeXm51JHq9Pfff4uXX35Z/h1YtmyZ+Pfff4UQQmRnZ4vPPvtMtG/fXgAQrq6uYvfu3fLvnxB1n7sPqmtZPz8/MWHCBHmWhQsXioCAgDr3wc/PT3h6egoAQkVFRXTt2lWMGTNG9OrVSxgbG4u+ffuKnTt3VvtMXeeWEEKkpKSI/v37CwDC3t5ejBs3TsyYMUPo6OiIxYsXy9ubKqtXrxZbtmyp+6A/4PDhw8LFxUVoamqKgQMHitdee03MnTtXvPfee6KkpKTeeX/77TdhbW0tAIglS5aImJgY8csvvwgbGxsBQKxatUpERUUJTU1N4erqKr766ivx3nvvidmzZ4vS0lJx9+5dsXDhQgFAODk5idOnT4u8vLxalxdC1NimPa5NqU/G1NTUOtvFZz3mUquoqBDfffedMDY2Fh06dBD+/v6NublcJSEa+L4comaoS5cuePnll/Huu+9KHYWIiIiIqEH1798fnTp1atYT9bVU8+fPR3R0NM6ePSt1lDqFhYVhyJAhMDExweHDh+Hg4CB1pAaRmJiI9u3bQwiB0NBQZGZmwtbWFh06dHjideXm5uLWrVuwtLREx44da12ualu2trbQ0tJCZGQkLC0tq01KWlZWhvLy8kcmKk1KSkJ6ejqcnJxqvAulqKgI4eHh6NKlCzQ0NJ54H+qSkZGBu3fvokuXLnVOotpYYmJiMGnSJNy9exdnzpyRD+XU3BQWFuLTTz/Fxx9/DBsbG7z11luYPn16s5/UuKWqz7kVHR2NiooKdO7cGXFxcTA2Noaent4jy40ePRoHDhyAoaHhE+coKCjAzZs3YWdn99iJxJ+lLRBCoKioCBUVFYiMjIS9vf1jh16rz/K1tWkN0abU1S4Cz3bMpXD27FmsXr0aN2/exKJFi7Bhw4Yav0sNKI9FAiIAQ4YMga2tLXbt2iV1FCIiIiKiBvXZZ5/ho48+QmpqKlRUVKSOQw945ZVXkJycXONY1oro3r17mDx5MkJDQ7F7925MmTJF6kjUypw8eRJeXl6wsrLC4cOHYWtrK3WkZxYZGYn3338fP//8M+zs7LB06VJ4e3tDS0tL6mjUCC5fvox9+/bh22+/lTpKq9FcjnlxcTEOHDiArVu3Ijw8HBMnTsR7772HLl26NMXm8zgnAREAW1tbREdHSx2DiIiIiKjBjR8/HllZWY9MZEjSaw5zEjzI0tISFy5cgLe3N6ZOnQovLy8kJiZKHYtagdTUVMyZMwdjx46Fp6cnrly50iIKBADQuXNnHDhwALdu3cLAgQOxYsUKtG/fHvPmzcPff//dKic4bmkCAgLg7u6O+fPnY82aNfjkk0+kjtTiNZdjLoTApUuXsGjRIrRv3x6LFy9Gnz59cP36dfz6669NVSAAwImLiQCwSEBERERELZednR26dOkCHx8fqaPQQ0pLS6GmpiZ1jCeipqaGr7/+Gr/99hsuX74MR0dHfPjhh/IJK4kaUmlpKT777DPY29vj7NmzOHjwIHbv3t0oQylJzdHREbt27UJ8fDzefvttBAQEYODAgejUqRPWrl2LsLAwqSPSM4iMjERMTAy++OIL6OvrSx2nVVDkYx4REYF33nkHdnZ2cHd3x8WLF7Fq1SrExcXhhx9+gKura5Nn4nBDRACOHTuGiRMnIjc397HjrBERERERNUdvvfUWDh48yAtjFMyECROgrq6On3/+WeooT6W4uBhbtmzBhx9+iLZt22LlypWYPXs2h0mhZ1ZcXIy9e/di8+bNSEpKwurVq7F69epW990KDQ3FgQMH8NNPPyEhIQGurq4YNWoURo4cCTc3Nw4hR9RMVFRU4MqVKzh9+jROnz6N4OBgWFhYYOrUqZgxY4YizK3COQmIACAuLg42Nja4ePEi3N3dpY5DRERERNSg/vnnHzz//PO4efMmXFxcpI5D/2f48OHo2LEjvvvuO6mjPJPExERs2rQJe/bsgba2NhYvXozXXnvtsZNqEtUkOzsbO3bswFdffYWcnBzMnDkT69atg5WVldTRJFVZWYm///4bR48exenTpxEVFQV9fX0MGzYMI0eOxIgRI2BhYSF1TCJ6QGpqKv744w+cPn0af/31F7Kzs9GpUyeMGDECL730Ejw8PBRponIWCYiqtG3bFuvXr8cbb7whdRQiIiIiogZVWVkJS0tLLF68GGvXrpU6Dv2ffv36wc3NDZ9//rnUURpEWloavv76a2zfvh3FxcWYOHEiZs+ejYEDB0JJSUnqeKSghBDw9/fHnj17cPDgQaioqGDBggVYsmQJzM3NpY6nkKKionD69GmcOnUKfn5+KC4uhrOzM9zc3ODm5gZ3d3fY2NhIHZOoVbl79y4uXryIy5cvw9/fHzdv3oS6ujoGDBiAkSNHYuTIkXBwcJA6Zm1YJCCqMnz4cJiZmWH//v1SRyEiIiIianDz5s3DjRs38O+//0odhf5Ply5dMHXqVLzzzjtSR2lQ+fn52Lt3L3744QcEBQXB2toa3t7emDlzJjp16iR1PFIQ8fHx2LdvH/bt24eoqCg899xzmD17NmbNmgU9PT2p4zUbRUVFuHDhAnx9fXHp0iUEBQWhpKQEFhYW8oKBm5sbunXrxuGJiBpIeXk5bt68iUuXLuHSpUvw9/fHvXv3oKqqip49e8LNzQ0eHh7w8PBoLsOksUhAVGXDhg349ttvkZiYKHUUIiIiIqIGd+LECYwbNw53796FpaWl1HEIgIWFBdasWYMlS5ZIHaXR3L59G3v37sXevXuRkpICJycnjB07FmPGjIGbmxvvMGhlYmJicPz4cRw6dAiXL1+GgYEBJk2ahHnz5qFnz55Sx2sRysvLcePGDfj7++PSpUvw9fVFRkYGVFVV0blzZ/Ts2VP+6N69O7S1taWOTKTQysrKcOfOHQQFBckfwcHBKCwshK6uLvr27VutIKepqSl15KfBIgFRlUuXLsHd3R2RkZGws7OTOg4RERERUYMqKSlB27ZtsXnzZsyfP1/qOARAW1sb27Ztw6xZs6SO0ujKy8tx9uxZ/Pbbbzh+/DiSkpJgY2ODcePGYfTo0XBzc2suV1vSEygqKsKVK1dw6tQp/Pbbb4iOjoaZmRnGjRsHmUyG4cOHQ1VVVeqYLZoQAmFhYbh69SqCg4MRHByMGzduIDc3F8rKynBwcED37t3RvXt3uLq6wsHBAR07dmQBj1qlhIQEhIeHIzQ0VH6+hIeHo7y8HLq6uujWrZv8fOnVqxecnZ3Rpk0bqWM3BBYJiKqUlpbCyMgIn332GRYsWCB1HCIiIiKiBjdhwgQUFxfj1KlTUkdp9crLy6GqqoqjR4/ipZdekjpOkxJCIDAwED4+Pvj9998RGhoKNTU19O3bF4MHD4aHhwf69esHdXV1qaPSEyotLcW///6L8+fP48KFC/jnn39QXFwMR0dHyGQyyGQy9O3bt6V0qjVbQgjExMTIO0GDg4Nx/fp1JCcnA/ivgOng4AAHBwc4OTnB0dERjo6O6Ny5M89LavZKS0sRGRmJ8PBwRERE4Pbt2wgPD0d4eDjy8/MBAKampvJiQNXD1ta2JbddLBIQPYh/NBERERFRS7Z3717Mnz8f6enp0NXVlTpOq5aZmQkTExOcO3cOgwcPljqOpJKSknD+/Hn4+vrC19cXsbGx0NTURJ8+feSP3r17w8rKSuqo9JCEhAQEBgYiICAAAQEB+Pfff1FYWAgrKyv5eNweHh7o0KGD1FGpHrKyshAeHl6t0/T27duIi4tDRUUFlJWVYWNjAzs7O9jY2FR7dOrUCYaGhlLvAhEAIDs7G7GxsY88oqKiEBsbi/LycrRp0wbW1tbyYpiDgwO6dOkCR0dHmJiYSL0LTY1FAqIHVf3RlJaWxomSiIiIiKjFyczMhLm5OX7++WdMnDhR6jitWkxMDGxtbXH16lWOxf6Q+Ph4+Pr6wt/fH4GBgbh16xYqKipgamoqLxh07doVrq6usLGxaclXdiqMyspKxMXFITQ0FCEhIfLCQEpKCpSVldGlSxf06dMHbm5uGDRoECeobmFKSkoQERGBiIgIhIeHIzo6Wt7pmpiYiMrKSgCAgYFBtcKBtbU1OnTogHbt2sHS0hJmZmZQVlaWeG+ouauoqEBqairu3buH5ORkJCQkID4+vloxIDs7GwCgpKSE9u3by7+Ttra2cHBwgKOjIxwcHKChoSHx3igMFgmIHlT1R9O+ffswdepUqeMQERERETW4gQMHomPHjti/f7/UUVq14OBg9OjRg3Oi1UNBQQGuXbuGgIAABAYGIjAwELGxsRBCQEtLC126dIGzszOcnZ3h4uICe3t7WFlZcaz7p1BeXo74+HhERkbi5s2bCAsLQ2hoKG7fvo2CggIAgLW1NXr16oW+ffuid+/e6NmzJ3R0dCROTlIpLS19pIO26hEfH4+0tDT5ssrKyjA3N4elpSXatWsnLyC0b98e7du3h5mZGdq2bQsTExMWE1qhyspKpKenIyMjA6mpqUhMTERiYiKSkpKQkJCA5ORk3Lt3D6mpqSgvL5d/ztjYGFZWVvI7Wh4uVHGIrHphkYDoYaNGjYKSkhJOnjwpdRQiIiIioga3ZcsWbNiwAWlpaexElZCfnx8GDRqEtLQ0tG3bVuo4zU5+fj7CwsKqdWQAPG80AAAgAElEQVTfunULiYmJAAAVFRV06NABtra2sLW1RadOnWBrawsbGxtYWFjAzMysVU7MKoRAamoqkpOTERcXh+jo6GqPu3fvyjvf2rVrBxcXl2oFGCcnJ951T0+kpKQESUlJ8g7f5ORk3L17V97hW/VeSUmJ/DNKSkowMTFB27Zt0bZtW5iamsLU1FReQDAzM4OpqSkMDQ1hYGAAAwMDDqGngPLz85GTk4OcnBxkZ2cjPT0dKSkp8kJAWloaUlNTkZGRIX+t6q4UAFBXV5cXkR4uLFlaWsLCwgLt27fn3QANg0UCoof98ssv8PLywt27d9GuXTup4xARERERNajo6GjY2dnh/Pnz8PDwkDpOq3Xs2DF4enqiuLgYampqUsdpMXJychAVFYXo6GjExMRU+3nv3j15B5SKigrMzMxgaWkJc3NzdOjQAebm5jA3N4exsTGMjIzkP42MjBT6StTS0lJkZWUhMzOz2s+UlBSkpKQgISEBqamp8p9lZWUA/uuItbS0lBdQHvxpZ2cHIyMjifeMWpP09HT5Iy0tDWlpadWuKk9LS5N3Jqenpz/yeWVl5WpFAwMDg2q/Vz3X1taGpqYmDAwMoKmpWePz1lhAfFB2djaKi4tRVFSE7OxsFBUVobi4WP68oKBA3vlfVQCo6fcHr/avUlX8qfppbm4u/93U1BRmZmby90xNTSXY+1aLRQKihxUVFcHCwgJr167FqlWrpI5DRERERNTgXFxcMHToUHzxxRdSR2m1tm/fjnfeeQcZGRlSR2k1SktLq13BXNWBnpKSIh/bOjU1Fffv33/kszo6OvLCgaamJrS0tKCnpwcNDQ3o6OhAR0cH6urq0NfXBwCoqqo+MgSPlpZWtWJDaWmpfAifKvn5+fJO/Ly8PJSUlOD+/fvIz89HSUkJcnNzUVRUhMLCQnlBID8/v8a8ZmZm8ituq4Z4ebAgYmVlpdDFD6LaVFRUID09vdZO6sd1XhcWFqKwsPCx69fQ0ICmpiYMDQ3lz9u0aSM/v6vOZSUlJRgYGNT62sPrq83jChNVY+vXpKoj/0G5ubmorKxESUmJfD+rXnuwzcnLy0NFRUW1YkBN63uYpqYmtLW1ay3G1PR71WsmJiZQUVF57PpJMiwSENVkyZIl8PHxQXR0NMfBIyIiIqIWZ926dfjxxx8RFxcndZRW691338WRI0cQGhoqdRR6SFlZmfxq/AevzK96XtVJn5eXh+LiYuTn5+P+/fsoLi6WFxhq6myr6pSr8mCnY5UHOxN1dXWhrq4OPT09aGtrQ0NDA/r6+tDS0oKmpqb8LocH73ioes67U4geLycnB0VFRbVeLV9UVIScnBwUFhaipKQE5eXl8vO7qphX02sVFRXIy8urtq379+/XeFU9gGrrqImOjk6tQwMqKys/MvyXrq4uVFRUoKKiIh+CqabXqtarpqYGbW1t6OvrywugD95ZYWhoWO0uC2qxWCQgqklUVBQcHBxw5MgRjB8/Xuo4REREREQNKiAgAH379sWNGzfQtWtXqeO0SvPnz0d0dDTOnj0rdRRqQlFRUejcuTOCgoLQo0cPqeMQkQJh+0ASymsjdQIiRWRnZ4eRI0fy9msiIiIiapF69+4NS0tL+Pj4SB2l1UpJSYG5ubnUMYiIiIjAIgFRLVatWgU/Pz9cvHhR6ihERERERA1KSUkJo0ePZpFAQikpKTAzM5M6BhERERGLBES1GThwIAYMGICNGzdKHYWIiIiIqMHJZDJcu3YNCQkJUkdplVJTU1kkICIiIoXAIgHRY6xfvx5//fUXLl++LHUUIiIiIqIGNXjwYOjo6OD48eNSR2mVUlNTOdwQERERKQQWCYgeY+jQoRg6dCiWL18OzvFNRERERC2Juro6XnzxRQ45JIHs7GwUFxezSEBEREQKgUUCojps3rwZgYGBOHr0qNRRiIiIiIgalEwmg6+vL3JycqSO0qqkpKQAAIsEREREpBBYJCCqw3PPPYepU6dizZo1KCoqkjoOEREREVGDGTVqFIQQ+PPPP6WO0qqkpqYCAOckICIiIoXAIgFRPWzevBlZWVl47733pI5CRERERNRgjIyM0L9/fw451MTi4+OhoaEBU1NTqaMQERERsUhAVB/t2rXDRx99hC1btiAoKEjqOEREREREDUYmk+HUqVMoLS2VOkqrERcXBysrKygpKUkdhYiIiIhFAqL6mjdvHgYMGIA5c+agrKxM6jhERERERA1i/PjxyM3Nxd9//y11lFYjPj4eVlZWUscgIiIiAsAiAVG9KSkpYceOHbhz5w62bNkidRwiIiIiogZhZWWFrl274vfff5c6SqsRHx8Pa2trqWMQERERAWCRgOiJ2Nvb4+2338a7776L8PBwqeMQERERETUImUwGHx8fCCGkjtIqVA03RERERKQIWCQgekKrVq1Cly5d4O3tjZKSEqnjEBERERE9s3HjxuHu3bu4ceOG1FFavIqKCiQkJPBOAiIiIlIYLBIQPSFVVVUcPHgQERERWLFihdRxiIiIiIieWc+ePWFpaQkfHx+po7R4SUlJKCsr450EREREpDBYJCB6Cp07d8bevXuxfft27N+/X+o4RERERETPRElJCWPHjmWRoAnEx8cDAO8kICIiIoXBIgHRU5LJZHjjjTewcOFC3Lp1S+o4RERERETPRCaTITg4GHFxcVJHadHi4uKgpqaGdu3aSR2FiIiICACLBETPZPPmzejevTsmTJiAvLw8qeMQERERET21wYMHw8DAACdOnJA6SosWHx+PDh06oE0b/jlOREREioH/V0L0DFRVVfHzzz8jOzsb8+fPhxBC6khERERERE9FVVUVw4cP55BDjSwqKgq2trZSxyAiIiKSY5GA6BlZWlri559/xpEjR/DWW29JHYeIiIiI6KnJZDL4+fkhOztb6igtVkREBBwcHKSOQURERCTHIgFRAxgyZAj27t2LzZs344svvpA6DhERERHRUxk9ejSUlJTwxx9/SB2lxbpz5w6LBERERKRQWCQgaiBTp07FRx99hBUrVuDQoUNSxyEiIiIiemL6+vro378/hxxqJOnp6cjMzISjo6PUUYiIiIjkVKQOQNSSrF69GikpKZgxYwYMDAwwbNgwqSMRERERET0RmUyGt99+G6WlpVBTU5M6TosSEREBALyTgIiIiBQK7yQgamCff/45pkyZgokTJ+L69etSxyEiIiIieiIymQz379/HhQsXpI7S4kREREBbWxvt27eXOgoRERGRHIsERA1MSUkJu3fvRs+ePTFy5EjcunVL6khERERERPXWsWNHdOvWjUMONYKIiAjY29tDSUlJ6ihEREREciwSEDUCdXV1HD9+HE5OTujfvz+uXr0qdSQiIiIionqTyWTw8fGBEELqKC1KREQEhxoiIiIihcMiAVEj0dbWxvHjx9GrVy8MGzYMAQEBUkciIiIiIqoXmUyGxMREXLt2TeooLQqLBERERKSIWCQgakRaWlo4fvw4+vfvj+HDh+PKlStSRyIiIiIiqlP37t1hbW3NIYcaUHl5OWJiYlgkICIiIoXDIgFRI1NXV8fhw4fh4eGBYcOGwdfXV+pIRERERER1GjNmDIsEDSgqKgplZWVwdHSUOgoRERFRNSwSEDUBNTU1/Prrr3jxxRcxbtw4/PHHH1JHIiIiIiJ6LJlMhpCQEMTGxkodpUUICQmBiooKunTpInUUIiIiompYJCBqIlWFAk9PT4wdOxY7d+6UOhIRERERUa0GDhwIQ0ND/P7771JHaRFu3rwJe3t7aGhoSB2FiIiIqBolIYSQOgRRa/Pll19i+fLlWLx4MbZu3Yo2bVivIyIiIiLFM23aNKSkpOD8+fNSR2n2ZDIZNDU18csvv0gdhZpIZWUlhg0bhrS0NPlrpaWliI6Oho2NTbWCkb6+Pnx9faGqqipFVCJqYmwfSMHkqUidgKg1WrJkCSwsLDBz5kwkJCTgwIED0NLSkjoWEREREVE1MpkM06dPR2ZmJoyNjaWO06yFhITg1VdflToGNaE2bdrAysoKvr6+ePj6zKioKPlzJSUlTJgwgR2ARK0I2wdSNLx8mUgikyZNwvnz5+Hv7w8PDw+kpqZKHYmIiIiIqJqRI0dCWVkZp0+fljpKs3b//n3Ex8eja9euUkehJjZt2rRHOgBrMmPGjCZIQ0SKhO0DKRION0QksTt37mD06NGoqKiAj48PXF1dpY5ERERERCT34osvQl9fHwcPHpQ6SrN16dIluLu7IzY2FtbW1lLHoSZUWVkJc3NzpKen17qMjo4OMjIyoK6u3oTJiEhqbB9IgeTxTgIiidnb2+PKlSvo0KED+vXrh3379kkdiYiIiIhITiaT4fTp0yguLpY6SrMVEhICPT09WFlZSR2FmlibNm0wbdo0qKmp1fi+qqoqJk+ezA5AolaI7QMpEhYJiBSAiYkJzp07h1WrVmH27NmYOXMmioqKpI5FRERERASZTIaCggJcuHBB6ijN1s2bN+Hq6golJSWpo5AEpk6ditLS0hrfKysrw7Rp05o4EREpCrYPpCg43BCRgjl+/DhmzpwJGxsbHD58GJ06dZI6EhERERG1cj179kSfPn2wY8cOqaM0S/3794erqyu2b98udRSSiLW1NeLj4x953djYGKmpqVBWVpYgFREpArYPpAA43BCRohk7diwCAwNRUVGBHj164NixY1JHIiIiIqJWTiaT4ffff6/XBItUnRACN2/ehIuLi9RRSEJeXl5QVVWt9pqamhq8vLzYAUjUyrF9IEXAIgGRArKzs8OVK1cwfvx4eHp6Yt26dSgrK5M6FhERERG1UjKZDElJSbh69arUUZqdyMhI5ObmomfPnlJHIQlNnz79kb/pSktLMXXqVIkSEZGiYPtAioBFAiIFpaWlhT179mDnzp3YunUr3NzcEBERIXUsIiIiImqFunXrBhsbG/j4+Egdpdm5evUqVFVV0bVrV6mjkIQcHR3h5ORUbV6KDh06oHfv3hKmIiJFwPaBFAGLBEQKbu7cubh27RqEEOjevTs++eQTVFZWSh2LiIiIiFqZsWPHskjwFIKCguDi4gJNTU2po5DEZs6cKR86RE1NDd7e3pzMmogAsH0g6bFIQNQMODo64sqVK3j33Xexfv16jBgxAomJiVLHIiIiIqJWRCaTITQ0FJGRkVJHaVauXr2KXr16SR2DFMC0adNQUVEB4L+hRF5++WWJExGRomD7QFJjkYComVBRUcGaNWvg7++P+Ph4uLi44Mcff5Q6FhERERG1EgMGDICxsTFOnDghdZRmo7KyEsHBwZyPgAD8N3xI3759Afx3IZizs7PEiYhIUbB9IKmxSEDUzPTp0wfXrl3DlClT4OXlBS8vL2RmZkodi4iIiIhaOBUVFYwYMYJDDj2B8PBw3L9/n3cSkJyXlxcAwNvbW+IkRKRo2D6QlFgkIGqGtLW18e233+LEiRPw9fWFk5MT7yogIiIiokYnk8ng7++PjIwMqaM0C1evXoWamhpcXFykjkIKYtKkSVBVVcXUqVOljkJECobtA0lJSQghpA5BRE8vLy8P69evx7Zt29C/f3/s3LkT9vb2UsciIiIiohYoPz8fbdu2xc6dOzFz5kyp4yi8JUuW4MqVKwgICJA6CjWSvLw8FBcXIz8/H/n5+SgrK0NpaSkKCgqqLVdeXo779+8DAI4ePYoJEyYAAHR0dKCqqlptWW1tbaipqUFVVRU6OjrQ0dGBuro69PX1m2aniOixcnNzUVlZicrKSuTm5gIAysrKkJ+fL1+moqICeXl5j13Pw58BqrcPVarahMfR1dWFiopKjZ/R09ODsrIylJSUYGBgUPcOUmuUxyIBUQtx+fJlzJ8/H9HR0Vi9ejXWrl1b5z8iRERERERPauTIkdDS0sKRI0ekjqLw3Nzc0K1bN2zfvl3qKPQYWVlZSE5ORmpqKjIyMpCVlfXIIzs7G1lZWSgsLER2djZKSkpQWFjY5Fk1NTWhoaEBAwMDaGlpwcjICEZGRjA0NJQ/r3oYGxvD3Nwc7dq1g7GxcZNnJWpq2dnZyMvLQ25uLvLy8lBYWIjc3FwUFxejqKgI9+/fR2lpabXX8vLyUFpairy8PBQVFaG4uFheBKhaBoC8CNhSqKioQFdXFwCgoaEBTU1NeRFBXV0dWlpa0NXVhZqaGvT19eXL6OnpQU1NDXp6evL2SF9fH5qamtDX14eenh709fVhYGAAJSUlifeSngCLBEQtSVlZGbZv345169bB1tYWu3btkk98Q0RERETUEL799lusXLkSGRkZ0NDQkDqOwqqoqIC+vj6++OILvPrqq1LHabUyMzMRGxuLmJgYxMfHIzExEUlJSUhOTkZSUhKSkpJQXFwsX15JSalaR/vDne/a2trVOtH09PSgrq4OXV1daGlpQV1dHW3atKnxqn9DQ8NHXsvJycHD3TJVHZRVdyQ82LH5YCdmQUFBjQWNqqJGZWWlfJ0aGhowNzdH+/bt0a5dO1hYWMDCwgLW1tawsbFBp06dYGJi0oBHnujJFRQUIDMzE5mZmUhPT0dmZiaysrKQk5ODvLw85OTkyJ8/WAyoel6bBzu4VVVVH+n0ruk1ZWVlqKmpQVtbG8D/L9AB1a/arzqvlZWVoaenV227Vet5nPp0pmdnZz/2/QfvaKhy//59lJeXV/v8g3c3PFjoLCwsRElJifz9mgooj3utNnp6evKiwYPPDQwM5K8ZGBjA2NgYxsbGMDExkT/X0dF57D5Tg2ORgKglioyMxPz58/H3339j4cKFeP/992FkZCR1LCIiIiJqAZKSkmBpaYnjx49j9OjRUsdRWNevX0f37t0REhICV1dXqeO0aJmZmQgNDcXt27cRFRWFmJgYeWGgqkNMWVkZFhYWsLS0hLm5ufxnVad5+/btYWZm1qI6yjMzM5GSklKtIJKcnIzExEQkJyfj3r17SEpKknck6urqygsGNjY2sLOzQ5cuXeDi4oK2bdtKvDfUHOXk5Mjv0klMTERaWtojRYCqQkBmZma1gh3w33lrbGwMAwMDeYdy1fOHO5719PRgaGhY7XUtLS0O09UEqu7aqCrW5Obmyos5VYWcBws62dnZ8t9zcnKQmZkpb4eqqKurywsGxsbGMDIyQtu2beXFBFNTU1hYWMDMzAzt2rWrsQhLT4RFAqKWSgiBvXv34s0330R5eTk++OADzJ8/v84qNhERERFRXfr06YPnnnsOu3btkjqKwtq2bRvWrl2LrKws/j94A8nPz0dwcDBu3bqFW7duISwsDKGhoUhLSwMA6Ovro3PnztU6uqued+zYkcOx1qCsrAx3795FbGysvLBS9TMqKkp+BbKJiQlcXV3lRQMnJyd07979kSunqXVIT09HQkICEhMTkZqaiqSkJKSlpckLAUlJSUhJSanW6a+qqgpTU1OYmJhU6/Ct7WFiYsLx81uR3NzcaoWjB4tHDxeWMjIykJaWVm34Jw0NDZiamqJ9+/bVfrZr105+91SHDh1gamoq4V4qNBYJiFq6goICbN68GR9//DFsbGywdetWjBgxQupYRERERNSMbdq0CV9//TWSkpLQpk0bqeMopBkzZiA9PR1//vmn1FGapbKyMty5cwdBQUEICgrCpUuXcP36dVRUVEBPTw+dO3eGk5MTnJ2d5T9tbGw4BnYDy87Olhdkqn6GhITICzPt2rVDz5494e7uDjc3N/To0QNaWloSp6ZnUVpaKr/LJDk5GTExMYiJiZH/HhkZWW1CXg0NDRgaGsLCwkLeGVvTTzMzMxZMqUEVFRXJ75R6+Gd2drb8eUpKinxYN3V19WrDrnXq1AmdOnWS/25vby+fq6GVYZGAqLWIiorC2rVrcejQIYwZMwZffvklOnXqJHUsIiIiImqGQkND4erqiitXrqBfv35Sx1FItra28PLywnvvvSd1lGYhJycHFy9exIULF+Dn54eQkBCUlZXB0NAQvXr1kj969uwJKysrqeO2egkJCQgKCsLVq1flj8zMTKioqMDV1RUDBgzAoEGDMGDAAA59q4BycnIQFRWFqKgoREZGIjIyElFRUYiNjUVKSop8OU1NTXTs2BEdOnRAx44dqz06dOgAS0tLFoVI4RUVFeHevXtISEhAQkIC4uLi5M+rfn9wbgUzMzNYW1ujc+fO6Ny5M+zs7GBnZ4fOnTu35GGNWCQgam3OnTuHpUuX4s6dO1iwYAE2bNjAW0SJiIiI6InZ29vD09MTH330kdRRFE5aWhrMzMzw559/Yvjw4VLHUUiFhYU4f/48zp8/Dz8/P9y4cQNCCLi4uGDQoEF4/vnn0atXL9jZ2UkdleopNjYWgYGBuHLlCi5cuICQkBAAgKurKwYNGoRBgwZh6NChnJC0iZSUlOD27dsIDw+vVgiIjIxERkYGgP+GALK2tpZ3gNra2soLAByahVqTjIwMJCQk4O7du4iPj0dsbCzu3LkjL55VDW1kbGwsLxrY29vDzs4Ojo6OcHJykk9s3UyxSEDUGpWXl+N///sf1q1bBwBYuXIlli5dCnV1dYmTEREREVFzsXz5cvzxxx8ICwuTOorC+e233+Dp6YmMjIyWfNXhE0tLS8Mff/yBEydO4PTp08jPz0enTp0wdOhQDB06FB4eHi1q4uDW7v79+/j3339x9uxZnD17FsHBwWjTpg369u2LsWPH4qWXXoK9vb3UMZu9iooKxMfHPzIsVGhoKEpKSqCiooKOHTvKh1V58OHs7NzcOzaJmkRSUhLCwsLkw29VPcLCwuR3IVQNv/bgMHguLi7Npa+NRQKi1iwjIwObNm3Cjh07YGlpiQ8++AAvv/wyx5UlIiIiojr5+flh0KBBiIiIYEffQ9asWYNTp07h5s2bUkeRXFxcHPbv34/ffvsNwcHB0NLSwrBhwzBmzBiMGTMGZmZmUkekJpKeno5Tp07hxIkT+PPPP3H//n1069YN48ePx4wZM3jXSD0UFRUhODgYgYGBCAoKQmhoKMLCwlBSUoI2bdqgU6dOcHV1hZOTE1xdXeHi4gJ7e3uoqqpKHZ2oRSovL0dkZCRCQ0MRGhqKW7duISQkBDExMaioqICampp8wveePXuid+/eijp3C4sERPTfeJIbN27E999/D0dHR7z77ruYNGmS1LGIiIiISIFVVFTA3Nwca9aswcqVK6WOo1D69+8PJycn7Ny5U+ooksjLy8Phw4exd+9eXLx4EW3btoWnpyfGjh0LDw8PXrlMKCkpgZ+fH44fP44jR44gJSUFL7zwAmbOnInJkyfDwMBA6oiSq6iowO3btxEQECB/hIaGoqysDMbGxujZsye6desmLwh06dJFETseiVql4uJi+R09VYWDoKAgpKenQ0VFBc7OzujTp4/84eTkBBUVFSkjs0hARP/f7du38e677+Lw4cPo168fPv74YwwYMEDqWERERESkoLy9vREbG4u///5b6igKo6ysDAYGBti2bRtmzZoldZwmFRwcjK1bt+Lw4cMQQmDcuHHw8vLCiBEjpO78IAVWUVGBv/76CwcOHMCxY8cghMBLL72EZcuWoXfv3lLHazKlpaX4559/5PN0XL16Ffn5+dDS0kL37t3Rp08f9O7dG7179+ZdF0TNVGxsLAICAhAYGIiAgABcu3YNBQUF0NbWRo8ePeDh4QEPDw88//zzTT1MEYsERPSoy5cv46233sLff/8NmUyG999/H926dZM6FhEREREpmKNHj2Ly5MlITk5G27ZtpY6jEAIDA9GnTx/cvn0bjo6OUsdpdEII/PHHH/j8889x7tw5dOvWDYsWLeLV4PRUqu5C2b59O4KCgjBgwACsWLECY8aMaXHD4lZUVCAoKAjnz5+Hr68v/P39UVhYCGtrawwaNAgvvPAC+vTpA2dnZxbZiFqoiooKhIWFISAgAFeuXIGvry9iYmKgqamJF154AYMHD8bgwYPRq1evxm4HWCQgotqdOnUK69atw40bNzBu3Di888476NGjh9SxiIiIiEhBFBQUwMTEBDt27Gh1V83XZsuWLfj444+RmpoKJSUlqeM0quPHj+Ott95CWFgYhg8fjhUrVmDYsGFSx6IWwtfXF1u2bMHJkydhb2+PTZs2wdPTU+pYzyQvLw8nTpzAkSNHcO7cOeTm5sLc3ByDBw+Gh4cHBg8ejE6dOkkdk4gkFB8fj/Pnz8sfSUlJ0NXVxZAhQzBhwgSMHTu2MYrwLBIQUd3Onj2LdevWISAgAEOHDsXGjRvRt29fqWMRERERkQIYPXo01NTUcOzYMamjKIRx48ZBTU0Nhw8fljpKowkNDcXy5ctx9uxZTJo0CevXr4eLi4vUsaiFCg8Px6ZNm/Djjz9iwIAB2Lp1K7p37y51rHrLysrC77//jiNHjuDMmTOorKzE4MGDMWbMGAwePBhOTk5SRyQiBRYeHo7z58/j5MmTOHv2LABgyJAh8PT0hEwmg4mJSUNsJq9l3atFRI1i6NCh+Pfff3HmzBnk5+ejX79+cHd3h6+vr9TRiIiIiEhiMpkMf/31FwoLC6WOIrnKykpcunQJAwcOlDpKoyguLsYbb7yB5557Djk5Obh48SJ+/fVXFgioUTk6OmL//v34559/UFZWhl69emH+/PkoKCiQOlqtSkpK8Msvv2DEiBEwNzfHwoULoaSkhJ07dyI1NRV//PEHFi9ezAIBEdXJ0dERixYtwsmTJ5GWlobvv/8e6urqeP3112Fubo5hw4Zh//79KC4ufqbtsEhARPU2dOhQXLlyBRcvXoS6ujoGDx4Md3d3nDt3TupoRERERCQRmUyG4uJi/j8hgJCQEGRlZbXIIkFERAT69euH/fv34/vvv8c///wDNzc3qWNRK9KnTx/4+/vjwIEDOHr0KHr37o3Q0FCpY1WTkJCAlStXon379vDy8oK6ujr27t2L1NRU/P777/D29oahoaHUMYmomdLX18eMGbig2wkAACAASURBVDNw7NgxpKWl4aeffoKenh7mzJkDCwsLLF26FLGxsU+1bhYJiOiJVRUGLl68CENDQwwdOhS9evXCvn37UFFRIXU8IiIiImpCZmZm6N27N3x8fKSOIjk/Pz8YGRm1uCvrf/nlF/Tq1Qvq6uoIDg6Gt7d3i5tElpoHJSUlTJ06FcHBwTA2Nkbfvn2xb98+qWMhMjIS3t7esLW1xcGDB7Fs2TLEx8fDx8cHU6dOhZ6entQRiaiF0dHRweTJk3HkyBEkJCRgzZo18PHxgb29PaZNm4bbt28/0fr4rzoRPTV3d3ccP34cFy9eRPv27TF79mw4OTlh165dz3ybExERERE1HzKZDMePH2/1F4z4+fmhf//+LaoDfceOHZg2bRrmzJmDixcvwtraWupIRLC0tISvry8WL16MWbNm4YsvvpAkR1ZWFl5//XU4OzsjMDAQu3fvRnR0NNatWwcLCwtJMhFR62NmZoY1a9YgMjISe/fuRWhoKLp27YqFCxciPT29XuvgxMVE1GCio6Px1VdfYffu3dDR0cGiRYuwePHihppEhYiIiIgUVFhYGJydnXHp0iW88MILUseRhBAC5ubmePPNN7Fs2TKp4zSIo0ePYtKkSdiwYQPWrl0rSYZLly49MnSCg4MDevfujZycHJw6dQqVlZXy95SVldGnTx9cuXKlznUbGRmhW7du9ZprzcjICHp6eoiLi5O/pqSkBFNTU9jY2MDKygqqqqo1fvbixYuIj49/7Pq7du2Krl271pkjOzsbbm5uWLNmDby9vVFeXg4fHx/s2LEDY8eOxZIlS+pcR0uzZcsWrFy5Evv378f06dObbLunT5/Gq6++isrKSnzwwQd45ZVXoKys3GTbbwgt4fx6eB+UlJSgrq4OPT09uLi4sFjzgIfbj8bwtG1SU2RrTSorK7F//368/fbbKCsrw7fffovx48c/7iOcuJiIGo6trS2+/PJLxMXFYdGiRfjmm29gaWmJmTNnIiIiQup4RERERNRInJycYG9v36qHHLp16xbS0tJazHwEcXFx8Pb2xoIFCyQrEACAm5sbrKys4OXlhVdffRVOTk7o3bs3AMDAwABjxozBwYMH4eXlhfPnz0Mmk+HatWtYunQp7ty5g5ycHNy5cwdeXl7YtWsX8vLykJycjP3792PFihW4fPlyvZd1c3ODsbExvLy8sGzZMiQnJ+Py5csYN24cOnbsiL/++qvGfXB3d4eFhQW8vLzw9ttvQ0dHBzo6OtDQ0EBmZiY2bNiAn376qV7HQ0VFBcbGxtDR0QEA3Lt3D0lJSTh37hzKysoa5qA3M8uXL8eKFSvw6quvNtnfnV9++SXGjBkDNzc3hIaGYu7cuc2uQAC0jPPrhRdeQNu2bTFz5kwsW7YMWVlZuHfvHtauXYsOHTpg+fLlKCoqasrDqrAebj8aw9O2Sc+SraSk5Ik/I+V6m0KbNm3g7e2NW7duQSaTYcKECViyZEm1ot8jBBFRI8nPzxdffvmlsLGxEcrKysLT01NcuHBB6lhERERE1AhWrFghOnfuLHUMyXzzzTdCX19flJeXSx2lQYwbN044OzuL4uJiqaMIIYTQ1dUVNjY2Nb63efNmAUDs379fCCHE//73P+Hn5yd///bt2wKAWLhwofy1yspKMWvWrCdatoqenp5wdnaW/56ZmSns7OyEkpKSCA4OrnUfNDU1RdeuXR95PSkpSSxbtuxxu/9YGRkZAoDYvHnzU6+juSsrKxM9e/YUw4YNa/Rtvf3220JZWVls37690bfVVFrC+WVkZCS6dOlS7bVp06YJAOL999+v6xBQA2rqNmnFihWioqKi2axXCj/88INQVVUVy5cvr22RXN5JQESNRltbG2+88QYiIyPx448/IikpCYMGDUK3bt2we/duFBYWSh2RiIiIiBqITCZDZGRkq72D1M/PD+7u7s3yauKHhYeH4/jx4/joo4+grq4udRwAgKamJjQ0NGp9D4D8fWdnZ7i7uz92fUpKSliwYMETLVtFTU0NSkpK8t+NjIwwZcoUCCHwyy+/1Lqe2vK3a9cOr7322mMzPI6KispTf7alUFFRwaeffoozZ84gODi40bZz8uRJbNq0Cd999x0WLlzYaNtpai3h/FJTU3vktTlz5gDAYz9HDa8p26SbN2/i22+/bTbrlcqsWbOwf/9+bN26FYcOHapxGf5LQkSNTllZGVOmTMGUKVNw7do17Ny5E0uWLMGqVavg7e2NpUuXwsbGRuqYRERERPQMqoZ88PHxwerVq6WO06QqKytx4cIFvPnmm1JHaRA+Pj4wNTXFmDFjpI7yVPr06VOv5fr27Vvvdda1rJ6eHoD/htp4EgEBAejVqxdsbW3lr0VGRuLUqVPIyclBnz59MHLkSPl7xcXFOHToEMzMzDB8+HAAqNahCgC//vorKisroaqqiokTJwIADh8+jLKyMmhqasrHpY6OjsaePXvw3nvv4fTp0wgLC8OyZcugqqqKvLw8/Prrr7h9+zY6deqEWbNmVRsGxN/fH6dPn0aHDh3Qpk0bzJs374n2uzEMHjwYNjY2OHbsGLp3794o23j77bcxadIkzJo1q1HW3xw0p/Or6nM19Tc87Xc8Ojoax48fx9KlS+XL2Nvbw8vLq9qk9SUlJfDz84Ofnx8sLCwwYsSIaud5VFQU9uzZgw8++ADR0dE4ePAgTE1NMWvWrGrzLzzuXKtrHx5WU/tR1zYeVp/9f7hNqvKkbVtdx+jSpUuYNm0aCgoK8Msvv0BVVRWTJk167LE5d+4c0tLS5NsdNWoU7ty5g6ioKADA8OHDER4eXut6m7MpU6bgzz//xPr16+Hp6Vnt+woAvJOAiJpUjx49sHPnTiQlJeH999+Hj48P7OzsMGzYMBw/fhyCc6kTERERNUvKysoYPXp0q5yX4MaNG0hPT8eQIUOkjtIgQkJC0Ldv31o7euhRP//8MwA80XegvLwcGzZsQEVFhfy1N954A3PmzMGMGTPwwgsvYPTo0fjkk08A/HeHx9SpUzFz5kxcv3691vWOGjUK27Ztk19FDfw39vxHH30kv/p93759cHd3x8aNG3HgwAG88847WLNmDQIDAxEZGYkZM2bAysoK3t7e2LlzJ5577jnk5OQAANasWYO7d+9i3bp1MDAwwIoVK+p/oBrZ888/j5CQkEZZd3JyMq5fv45FixY1yvqpdk9zflVWVuLDDz8EAMydO7fae0/7Hf/mm2/w3HPP4dNPP8VPP/2ERYsWYevWrZg1axYmT54sX39xcTFGjBiB7OxsrFq1CkIIdO/eHUePHgUA7N27F+7u7ti0aRNOnjyJN998E1euXMG8efOwYcMG+Xoed67VtQ8Pq639eJLzub77X5Mnbdvqc4yEEOjfvz8AQF9fH/r6+nUemx49euDMmTOYNm0aTp06BX19fbRr1w5z5syBnp4ejIyMal1vS7Bo0SJEREQgOjr60TebZuQjIqKalZWViUOHDomBAwcKAMLR0VF89dVXIisrS+poRERERPSEjh07Jtq0aSOSk5OljtKkPv30U2FiYtJixi4eN26cmD59utQxqjE1NRX6+vrC29v7kUffvn0FAHHo0KEaP1vTOOi1qc+yJiYmwsrKSgQGBgp/f3/x8ssvCwBi1qxZorKystbPGRoaCm1tbTFgwAAxYMAAYWJiIgCI0tJS+TL6+vpi48aN8t+dnJxEv3795L8nJiYKAOKTTz6Rv5abm/vI+N+LFy8Wenp61bb/6quvCnNzc/nv69atEwDEnj17hBBChIeHi8rKSjFs2DBx7Ngx+XKnT58WAMT69etFaWmpMDY2FhEREfL3lyxZUus+N7UFCxYIDw+PRll3cHCwAFBt31uKlnB+mZubi/bt24s9e/aIDRs2CCcnJ9G3b98acz/Ld3zKlClCW1tbHDhwQAjx35wizz//vAAg/vzzTyHEf3MhzJ49u9o2J06cKDQ1NUVCQoIQQojVq1cLAMLHx0e+jIeHh7C3txdCiDpzPG4favNw+/E053N99r+mNulp2ra6jpEQQrz//vsCQLXvRl3HprS0VLi7uwtdXV1x9+5dsWTJEnH06NFq+1nTeluCquN88eLFh9/K5XBDRCQpFRUVTJw4ERMnTkRISAi++eYbrF27FmvWrMGkSZMwd+7cOscwJCIiIiLFMHz4cGhoaODkyZPVrmJu6c6dO4ehQ4c+cut+c2VmZobIyEipYzzC3Nwc33zzzSOv79q1C//++2+TZlFWVkZ8fDwSEhIwfPhwvPnmm+jWrVudn7O1tYWfnx8AoLS0FF5eXtXeP3nyJLp06QLgv6GIhBAoKiqSv/+4oUQeVNN38eHXqsaanzp1KgDAwcEBycnJOHPmDJ577jn5Mc3Pz0evXr1QWFgIVVVV6OrqYujQodi5cydGjhyJdevW1StTU0hISIC5uXmjrNvW1hbKysoIDAyEvb19o2xDSi3h/FJVVYWdnR1+//13hIWF4eTJkxg1alS1ZZ71O66trQ09PT1Mnz4dwH9zinz00UcYNGgQzpw5A3d3dxw6dAiff/55te0uXLgQhw8fxg8//ID169dDW1sbAKrlc3FxkWd6XI669qE2D7cfT3M+17X/Dw5j9KCnadvqOkY1qc+xUVVVxb59+9CtWzeMHTsWI0aMwEsvvfTY/W4pAgICoKSkBAcHh0feY5GAiBRG165dsWvXLnz++ef4+eefsW/fPvTv3x8ODg6YPXs2XnnlFbRt21bqmERERERUCy0tLQwZMgQ+Pj6tpkhQWloKf39/fPHFF1JHaTDu7u7Yv38/cnNzFWqYhTZt2tTYkSTF5MpaWlrw9PR8pnWoqalh0aJF1Trv3dzccOzYMRw9ehQvvvgirK2tkZiYKH+/IQtRNQ0nVVUcWr16NUxMTGr83DfffAMvLy+MGjUKzz//PPbs2aMQf6cVFhbi4sWL+Pjjjxtl/bq6upgyZQo+/PBDvPTSS9DS0mqU7UilJZxfmpqacHNzg7OzM4KCgjBr1iyEhIRUKxw1xHf84XOnd+/eAP4rUl2+fBllZWWPTN7buXNnAMCdO3cA1Hwua2tro7y8vM4c9dmHmtS0zac5nx+3/7V5mratPsfoYfU9NjY2Nvjwww/x+uuvY/ny5bUu15KUlJTggw8+wLhx42r8b9wyLnMgohZFV1cX8+bNg7+/P0JDQzF+/Hh8+umn6NChAyZPnoyzZ89y7gIiIiIiBSWTyXD27FkUFBRIHaVJXLp0CQUFBS1mPgLgv/+Gampq2LFjh9RRWryBAwdCWVlZ/vvq1avxv//9D7t378aMGTOavINWTU0NAHDt2rVH3rt//z4AYPTo0YiKisLSpUsRFBSEXr164fbt202asya7d+9GeXm5fLLmxvDhhx8iLS0NM2fORGlpaaNth56NgYEBfvzxR2RlZcHb27ta/0FjfMfV1NSgrq6Ojh07yucYuXz5crVlqjqsn+QulNpy1GcfnnUbT+LB/a9NU7Vt9T02lZWV8Pf3x5AhQ/DGG288tsDREpSXl2POnDmIjY3Fp59+WuMyLBIQkUJzdnbGxx9/jPj4eGzbtg13797FsGHD4OjoiM2bNyM5OVnqiERERET0gLFjx6K0tBRnzpyROkqTOHfuHGxtbWFjYyN1lAajr6+P5cuXY+PGjYiJiZE6zjOr6iCsz4VG9VlWCPHUFy097nNBQUHYvHkzXnvtNWhoaNTrM7XR09NDSUnJI9t+cJLkmjj8P/buO66q+v8D+IupbFmXJVtRQVy4Fw7CEabmSCu3kmVlmml+SzPzm6XmqLTce5XmNgeaoLhxJRvZ67K5bC5wfn/043xBMRdwGK/n43EeF+4453WIe8PP+3zen1atoKamhq+++qrSIHhqair27t2LvLw8bN68GUZGRlizZg0uXbqE3NxccWFZqcTHx+Orr77CRx99VKOzGmxtbfHHH3/g3LlzGDp0KFJTU2vsWPVFXXp/VdSrVy8sXrwY586dw6pVq8T7q+N3vLCwsNKxrl69iqKiInTt2hUdO3ZEkyZN4O/vX+k55b8r5QviPsu/5XjWOTyvl30//9v5V6U6P9uepvyz7Xl/NsuWLcOkSZOwd+9eaGhoPFFMeny/9VlmZiaGDx+Oo0eP4vfff39qoYpFAiKqF3R1dTFt2jRcv34d9+/fh6enJ5YvXw5ra2u8/vrrOHjw4BP/oyIiIiKi2ieTydCtWzccO3ZM6ii1onw9goZm4cKFaNmyJUaMGPHCV6ZWN0EQkJubi8zMzCofVygUAPDUx5OTkwH805f6WZ713OLiYmRmZorHfF5lZWXIy8tDVlbWU59T3r7m6NGjKCkpgY+PD+7fv4/MzEyEh4cjKipKzFVxpk5V99na2qKoqAjnz5+HIAg4ePAgrl69iuzsbGRnZ6O0tBRKpRIAkJ6eLr7O0NAQM2fOxPXr1+Hu7o59+/Zhx44deOeddzB+/HiUlZXhq6++Ev/t1aNHD7Rs2VLSdkN5eXkYOXIkLC0tsXjx4ho/Xp8+feDn54fw8HC4urrijz/+qPFj1qSG8P4qKSlBWlraE6/74osv0KdPHyxcuBCnTp0CUD2/49nZ2YiNjRW/P3PmDDp37oxRo0ZBJpPho48+QlRUFP766y/xOUePHsWYMWPg7u4OAMjIyACASn35S0pKoFQqUVRU9K85nnUOT/P4Z8XLvp//7fyrOs7LfrY962cEQMwaEBCAy5cvQ0tL65k/mzNnziA9PR1DhgyBmZkZVqxYgb/++qvSFfaP77e+jjedPHkSbdu2xb1793Dx4sV//3ulJldMJiKqSYWFhcLx48eFMWPGCBoaGoKBgYEwYcIE4fz58w1uBXoiIiKi+uT7778XjI2NBaVSKXWUGpWVlSWoq6sLv/32m9RRakRMTIxgYWEh9OjRQ8jMzJQkg5+fnzBu3DgBgABAmDNnjnDjxg1BEAQhMzNTWLVqlWBlZSUAEFxdXYXNmzcLBQUF4uv37t0rdOnSRQAgNGvWTFi2bJkQFxdX5bGe9VxfX1/hzTffFLO8//77ws2bN595DpcuXRLGjh0rABBUVFSETz/99KmvmzBhgqCqqiqYmZkJv/76q7Bs2TJBVVVVmDdvnhAbGyu8//77AgDB2dlZ+PPPP4XExMRK9x09elQQBEHIy8sT2rZtKwAQzMzMhJ07dwre3t6CoaGhMG/ePGHjxo1Cq1atBADCmDFjhPv374sZ8vLyhIkTJ4rnqa+vLxw5ckQQBEFQKBSClpaW4OrqKvz444/CkiVLhClTpgjFxcXP/DnUBIVCIfTt21cwNTUVIiIiavXYWVlZwpQpUwQVFRWhX79+wq1bt2r1+NWhIby//Pz8hFGjRomvmzlzZqXXxcbGCoaGhoK6urowYsQI4fz586/0Oz516lRBR0dHeOONN4T169cL3t7eQu/evYWoqCjxmKWlpcLcuXMFU1NTYcGCBcKkSZOEsWPHij+7o0ePCnZ2dgIAYfbs2UJkZKRw4MABwd7eXgAgfPbZZ0JERMS/5vi3c6hKVZ8fL/N+ftb5P+0z6UU/257nZySXy4XIyEjBzMxMMDQ0FLZs2fLMn82hQ4cEPT09YerUqUJJSYkgCIKwYcMGAYCgpqYmfP7550J+fn6V+61P7t27J3h6egoAhLfffltIT09/1kuyVQSBjb2JqP7LyMjAoUOH8Ouvv+Lu3buwsbHB+PHj4e3tDQcHB6njERERETUq4eHhcHJygp+f33O3VqiPjh49ilGjRkEul7/Q4pH1SWhoKDw8PKCtrY2DBw+iQ4cOUkdq8FJTU9GsWTNoaGgA+OcKbkNDwxfejyAIePjwIRwdHaGtrY3w8HA0b94cWlpaz/X6tLQ0xMbGok2bNuJrBEFAQUEBSktLxfd5VYvd1oagoCCMGTMGGRkZ8PHxgYuLiyQ5rl27hnnz5uHq1avw9PTE/PnzG9QaJQ3Zy/yOT5s2DWfOnEFUVBSCgoJgYGDw1HZzBQUFCAkJQZs2bSq12Xkez/teq+ocqvsYFb3I+T+uuj7bHqdUKlFSUvLE+b/Kz+bf9luX+fr6YuXKlTh9+jQ6d+6MVatWoW/fvs/zUgWLBETU4AQEBGDnzp3Yv38/MjIy0L9/f0yYMAEjRoyAgYGB1PGIiIiIGoXWrVtj2LBhWLlypdRRaszMmTNx9+5d3LhxQ+ooNSolJQUTJkyAn58fvvvuO8yePVvqSNTI7d69G++//z5cXFxw8OBB2NnZSR0JZ86cEduWuLi4wNvbGxMmTKiWQVCqO8oHyRMSEqSOIonGfv51UXZ2Nvbu3YuNGzfiwYMH6NOnD+bPn4/XX38dKioqz7sbBdckIKIGx83NDT/++CMSEhJw6NAh6OrqwtvbG+bm5hg1ahQOHz5cb/vJEREREdUX5YvkNWRnzpzB4MGDpY5R42QyGU6fPo358+dj7ty5GDp0KIKDg6WORY1QREQERo4ciUmTJmHWrFnw9/evEwUCABg8eDAuXryI27dvo2fPnvjiiy9gaWmJESNGYPfu3f+6HgXVH/n5+ZX65jc2jf386wqFQoF9+/Zh1KhRsLS0xGeffQY3Nzdcv34dfn5+8PLyepECAQAuXExEDZimpiZGjhyJo0ePQi6XY+PGjSguLsa4ceNgbGyMsWPH4sSJE+KCXURERERUfYYPH46IiIgGO5gcFBSEmJiYRlEkAAA1NTV8/fXXuHTpEpKTk9G+fXt8/PHHlRa9JaopWVlZmDdvHlxcXBAREYHz58/j+++/h7q6utTRnuDm5oZNmzYhMTERGzZsgFKpxIwZM2BmZoYhQ4Zgy5YtSEtLkzomvSClUokNGzbA19cXOTk5WLRoEeLj46WOVWsa+/nXBenp6di+fTu8vLwgk8kwefJk5OXlYe3atUhMTMS2bdvQrVu3l94/2w0RUaOTnp6Ow4cPY9euXbh69SoMDQ3x+uuvY+LEiRg4cOALV1uJiIiI6EllZWWwsrLC7Nmz8fnnn0sdp9qtXr0ay5YtQ2pqKtTU1KSOU6vKysqwfft2fPnllygqKsIHH3yADz/8EObm5lJHowYmNTUV69evx/r166GiooKlS5dixowZ9e49l52djZMnT+Lw4cM4c+YMiouL0b17dwwYMAADBgxA9+7dX7hnPRE1bMXFxbh+/TouXryIixcv4tq1a1BXV4enpydGjRqFYcOGVWc7M65JQESN26NHj7B//37s378fQUFBsLW1xdixYzF69Gh06dKFBQMiIiKiVzBt2jQEBQXh2rVrUkepdp6enjAyMsKBAwekjiKZnJwcrFu3Dj///DOysrLwzjvvYO7cuZItIEsNR2hoKNasWYNdu3ZBR0cHH3zwAebOndsg1pjLy8vD6dOnce7cOVy8eBGRkZHQ0tJCz549xaJB586d6+QsCSKqOaWlpbhz545YFLhy5Qry8/NhZ2eHAQMGwNPTE0OHDoWenl5NHJ5FAiKicvfv38eBAwfw22+/ITIyEjY2Nhg1ahRGjx6N7t27Q1WVHdqIiIiIXsTx48cxcuRIxMfHw8LCQuo41SY/Px/Gxsb45ZdfMHnyZKnjSK6wsBB79uzB6tWrERISgn79+mHixIkYNWpUTQ1mUAOUl5eHI0eOYNeuXbhw4QIcHR0xZ84cTJo0Cdra2lLHqzExMTHioODFixeRmJgIPT09dOnSBV27dkWXLl3QpUsXWFtbSx2ViKpRQkICbt26hVu3buHmzZu4desWsrOzYW5uLhYMBwwYAHt7+9qIwyIBEVFVAgMD8fvvv+O3335DcHAwTE1NMXjwYIwZMwZDhgzhVR1EREREz6GgoACmpqZYs2YNZsyYIXWcanPq1CkMGzYM8fHxsLS0lDpOnSEIAv78809s27YNJ0+ehJqaGkaOHIkJEybAw8Oj3rWIoZpXVlaGv/76C7t27cIff/yB4uJiDBkyBFOnToWXl1ejvFArJCQEvr6+uHHjBm7evImQkBCUlpbCwsJCLBh07doVnTt3hpGRkdRxieg5ZGVl4fbt22Ix4NatW0hISICqqipat24tvq/79esHZ2dnKSKySEBE9CzlBYPff/8dQUFBMDExwZAhQzBmzBgMHjwYGhoaUkckIiIiqrNGjBiBkpISnDx5Uuoo1eajjz6Cv78/7ty5I3WUOisrKwvHjx/H7t27ceHCBRgaGmLgwIHw8vLC8OHDG0TbGHo5BQUF8PHxwcmTJ3Hy5EkkJibC2dkZEydOxJQpUyCTyaSOWKfk5ubi3r17CAgIELfg4GAIggBDQ0M4OzvDzc0NLi4ucHZ2RseOHaGjoyN1bKJGSalUIiwsDEFBQQgMDBRvy9+zFhYWcHNzE7devXrVlWIfiwRERC8iMDAQhw8fxqFDh/D333/D1NQUw4YNw/Dhw/Haa69BS0tL6ohEREREdcr27dvx/vvvIzU1tcG0nmnZsiVGjx6N5cuXSx2lXoiIiMCRI0dw4sQJXL16FWpqanB3d8ewYcMwcOBAqa6apFoUGhqKixcv4vjx47h06ZK4cO+wYcMwcuRItGrVSuqI9YpcLsedO3fw999/4+HDh3j48CGCg4NRWFgIVVVVODg4wNXVFS4uLmjbti1atGiBFi1asDhHVE1ycnIQERGB8PBwBAUF4eHDh/j777/x6NEjlJaWQlNTE87OzuJ70NXVFZ06darLrRdZJCAielmhoaE4cuQIjh49ilu3bqFp06bw9PTE8OHD4eXlBRMTE6kjEhEREUkuPT0dZmZm+O233/Dmm29KHeeVBQcHw9nZGVeuXEGvXr2kjlPvpKen4/Tp0zhx4gTOnj0LhUIBMzMzuLu7w93dXcpWC1SNylvm+Pr64tKlS0hKSoKuri48PT3h5eUFLy8vmJqaSh2zQSktLUVERAT+/vtvBAYGVhq0LCkpAQDIZDK0aNECLVu2FAsH5V+zgEBUmUKhQERERKUtPDwc4eHhBheMwAAAIABJREFUkMvlAAA1NbVKRTlXV1e0bdsWLVu2rG9tqlkkICKqDmlpaTh9+jROnjyJ06dPo6CgAD169MCwYcMwYsQIXhlDREREjVqfPn3g4OCAnTt3Sh3lla1cuRLfffcdUlJS2GP/FZWUlCAgIEAcTL5y5QoUCgVkMhl69OiBzp07ixsvwKm7MjIycPv2bXG7du0akpOToauri969e6Nv375wd3dHly5d2KpVAkqlElFRUeIAZ8XBzpiYGLGAYGpqCkdHR9jY2MDa2ho2NjawtbUVv+d7kBqa9PR0xMXFITY2FjExMeLXsbGxePToEVJSUgAA6urqsLGxEQtr5cW1li1bwt7eHpqamhKfSbVgkYCIqLrl5OTg7NmzOHbsGE6dOoXMzEy4urpi+PDheOONN+Dm5tYoF+AiIiKixmvVqlVYvnw55HJ5fbuy7gnu7u6wtbXFrl27pI7S4JSWluLOnTvw8/PDjRs3cOvWLURHRwMA7O3txYKBq6sr2rRpA1tbW6ioqEgbupGJjY1FcHAwHjx4gICAANy+fRuPHj0CANjY2KBLly7o1q0b+vbtCzc3t3r/fm/olEoloqOjxcLBo0ePxIHSuLg48WppANDS0oKdnR2sra3FIoK1tTVkMhksLS1hZmYGMzMzFk9JcqWlpUhJSYFcLkdiYiJSUlIQFxdX6Xc7Ojoa+fn54mtkMpn4u21rawt7e3txlo2dnV1DKQT8GxYJiIhqUklJCXx9fXH8+HEcO3YMMTExkMlkGDp0KIYOHQpPT09O6yQiIqIGLyIiAi1btsSlS5fg7u4udZyXlpGRATMzM+zduxdjx46VOk6jkJaWhlu3bolXqQcEBCAhIQEAoKurizZt2ogLtrq4uDSmAZ0ao1QqERMTg4iICLHX/cOHDxESEgKFQgEA4uKb5YWbLl26cMHhBqiwsFC8sjouLg4xMTGVvo+Pj6800KqqqgqZTAaZTAYrKyvIZDJYWFjA3Nwc5ubmsLS0hLGxsbixiETPq6SkBOnp6eKWlJSE5OTkSoWAhIQEyOVypKSkoKysTHyttrY2rKysqpwhU14U4PqSLBIQEdWqyMhInDhxAidPnoSvry/KysrEBbs8PDzg5uYmdUQiIiKiGuHs7IzBgwdj9erVUkd5aXv37sWUKVOQkpKCZs2aSR2n0crKykJgYCCCgoIQFBQkfl1ePFBVVYWVlRUcHBzg6OgIe3t7ODg4iFdBm5mZNeoiglKphFwuFwd9IyMjK23x8fEoLS0F8E8xoLwIU16IcXZ2hpGRkcRnQXVFbm4uEhMTIZfLqxy4LX8sJSVF/L0qZ2BgAFNT00qFg4qbqakpTExMYGBgAAMDAzRr1gz6+vosLtRjpaWlUCgUyMzMhEKhQFZWFtLT05GamlqpCFBxS01NRVZWVqX9VFWQKp/RUl6QKr9PT09PorOtV1gkICKSSkZGBi5cuAAfHx+cOHECSUlJsLOzg6enJzw8PDBkyBDo6upKHZOIiIioWixcuBAHDhxAVFSU1FFe2vjx45GamgofHx+po1AVsrOzERYWhp07d2Lv3r1o27YttLS0EBkZidjYWCiVSvG5MpkMZmZmaN68eaVbExMTGBkZiZuxsXG9mPmbnZ2NjIwMZGRkID09XbyVy+WIj4+vdFuxhYy6ujqsra3h4ODwxObo6AhDQ0MJz4oakrKyMqSkpFQa/E1LS/vXweH09PQq96WjowN9fX1xKy8gGBgYVLpfV1cXenp60NTUhIGBAZo2bQotLS3o6+tDU1MT+vr60NLSQtOmTWv5p1F/FBYWoqCgADk5OSguLkZ2drZ4n0KhQHFxMRQKBfLy8qBQKJCdnQ2FQlGpEFDx/ry8vCqPY2RkBBMTkyqLRSYmJk88JpPJ2NqqerFIQERUF5SWluLGjRs4deoUTp8+jXv37kFbWxv9+/fHoEGDMGjQIDg5OUkdk4iIiOilXb9+HT169MDff/+Ntm3bSh3nhZWUlEAmk2Hx4sX45JNPpI5DVfDx8cFnn32GBw8e4J133sF3330HS0tLAP/890tMTER8fDySk5PFthQVB9DLBzAfv9pZTU1NLBqUDzo2adIE+vr60NbWRpMmTdCsWTM0adIEOjo6AIAmTZpAW1u70n50dHQqzWBQKpXIzc2t9JyCggIUFhYCAPLz81FUVITMzEwUFRUhPz8fOTk5KCoqgkKhQG5urlgYeDyzqqoqjI2NYWZmBktLS1hYWMDS0hLm5uawsrISb5s3b86rsqnOKisrQ3p6OrKzs5GdnY2srCxx0DklJQX+/v7w9/dHz5490bRp0ycGpHNzc5GTkyMuzvxvnlY4MDAwgKqqKlRVVcWCoaampvher/hcPT29J95Pj7/vH6ehofGvFwfm5eWhuLj4qY9X9TlSUlKCnJwcABA/Ox7fl0KhQGlpKQRBEK/Sr/g5U14QeBZ1dXXo6elBV1e3UoFGX18fhoaGYhHn3x4zNjbmgL/0WCQgIqqL4uPjcfr0aZw9exYXLlxAdna2OMtg0KBBGDhwYL24oomIiIioXFlZGZo3b45Zs2bhiy++kDrOC7t06RL69++PsLAwtGzZUuo4VMHt27exYMECXLx4ER4eHli9ejVcXV1fen/lV+WXX5FfcSsfdCwfqK9qIB+oemAvOzu7Up9sFRWVJ9pWVRwwLO+R3bRpU5iZmUFHR6dSgUJXVxeGhoaVZj6Uz35gOyxqqMLCwrB+/Xrs2LEDJSUlePfddzF//nw4Ojo+9TVlZWVPvQK+vDCXlZWF4uJi5Obmiu/figPoFQfey/cDVH6vP/4eB4DMzMx/PZ9nFQGeVUQAgGbNmlVaxL3iZ0vF15fPpAD+WdNFQ0MDwP8KIeXP1dXVhaamplj81NbWrnJGRvnrqEFgkYCIqK4rLS3FvXv34OPjAx8fH3Etgw4dOsDDwwMeHh5wd3cX/wdPREREVFd5e3vj3r17uHnzptRRXti8efNw6tQpBAcHSx2F/l9MTAy+/fZbbNmyBV26dMGKFSvQt29fqWNVq3fffRd37tzBw4cPORhHjVZZWRkuXryITZs24Y8//oCNjQ3ee+89TJ8+HcbGxlLHI2oIWCQgIqpvMjIy4OPjg7Nnz+LcuXOIj4+HkZERPDw84OnpiYEDB8LOzk7qmERERERPOHXqFIYNG4bY2Fg0b95c6jgvxNHREWPHjsXy5culjtLopaenY+XKlVi7di3s7OzwzTffYPTo0ZWupG0ogoOD0bZtWxw8eBCjR4+WOg5RrcrJycH+/fuxbt06BAUFoVevXpg9ezZGjhzJNllE1YtFAiKi+i4wMFAsGFy+fBn5+flwdHTEwIEDMXDgQPTv3x+mpqZSxyQiIiJCUVERTE1NsWLFCsycOVPqOM/t7t276NSpE27evIkuXbpIHafRys/Px08//YTly5dDU1MTX3zxBWbNmtXgBwtHjx6NiIgI3L17t0EWQogeFx4ejq1bt2Ljxo0oKSnB22+/jY8++qhermdDVE+wSEBE1JCUlJTg/v37YmsiPz8/FBcXw8HBQWxN5OnpyfUMiIiISDKjRo1Cfn4+/vzzT6mjPLdFixZhx44diI2N5SCtBMrKyrBnzx58/vnnyMnJEde10NPTkzparbh//z46duyIY8eOYdiwYVLHIaoR5S2F1q1bh1OnTsHBwQEzZszAjBkzYGRkJHU8ooaORQIiooZMoVDA19cXFy5cwIULFxAYGAh1dXV0795dnGnQtWtXaGpqSh2ViIiIGoldu3bB29sbKSkp0NfXlzrOc3F2dsagQYOwZs0aqaM0Oj4+Ppg7dy5CQkIwZcoULF26FGZmZlLHqnXDhg1DSkoKbty4IXUUomqlUChw4MABrFmzBiEhIWJLoTfffBNqampSxyNqLFgkICJqTFJSUuDr6wsfHx+cP38eUVFR0NbWRseOHdG7d294eHigd+/eaNq0qdRRiYiIqIHKyMiAmZkZ9u3bhzFjxkgd55nCwsLQqlUr+Pn5oU+fPlLHaTSuX7+OBQsW4PLlyxg9ejS+/fZbtGjRQupYkrlx4wa6d++Oc+fO4bXXXpM6DtErCwsLw/r167F161aoqqpi/Pjx+Pjjj+Hi4iJ1NKLGiEUCIqLG7NGjR7h06RJ8fX1x6dIlxMXFQUtLCz169IC7uzv69euHbt26oUmTJlJHJSIiogakX79+sLa2xu7du6WO8kz//e9/8dNPPyEhIYFXtdaC0NBQLFq0CIcOHUKPHj2wcuVK9OzZU+pYdYKnpyfy8vLg7+8vdRSil/J4SyFHR0dMnz4d3t7eMDQ0lDoeUWPGIgEREf1PYmIi/P39K800UFdXR/v27cU1DXr16gUtLS2poxIREVE9tmbNGixduhQpKSnQ0NCQOs6/cnNzQ5cuXfDrr79KHaVBS0xMxNdff41t27bByckJS5YsqRczTWqTr68v+vXrB19fX/Tt21fqOETPLTs7Gzt27MDatWsRGxuLAQMGwNvbmy2FiOoOFgmIiOjpKhYNfHx8EBkZKRYNevXqhd69e2PAgAEwNjaWOioRERHVI5GRkXB0dMTFixfRv39/qeM8VXR0NBwcHHDmzBl4enpKHadBys3Nxfr16/Hf//4XBgYGWLRoEaZNm8aBw6dwd3dHkyZNcO7cOamjED1TaGgoNmzYgK1bt0JNTQ3jxo3DJ598gjZt2kgdjYgqY5GAiIieX3R0NPz8/HD58mX4+/sjODgYqqqqaNu2Lfr27YvevXujT58+sLS0lDoqERER1XGurq4YOHAg1q5dK3WUp/rhhx+wbNkyyOVyaGpqSh2nQVEqldi+fTsWL16M4uJiLFiwALNnz+baWM9w7tw5DBo0CP7+/mzDRHVSWVkZTp06hR9//BEXLlxAixYtMG3aNLz33nto1qyZ1PGIqGosEhAR0ctTKBS4efMmfHx8cOXKFdy+fRtFRUWwsLBA7969xdkGnTp1goqKitRxiYiIqA754osvsHfvXkRHR0sd5al69eqFli1bYseOHVJHaTAEQcChQ4ewcOFCxMXFYebMmViyZAn7kb+AXr16wdjYGMePH5c6CpEoKysLO3fuxJo1axAXF4cBAwbg448/hpeXF/8tSFT3sUhARETVJy8vD9evX8fly5dx5coVXL9+HXl5eTA1NUW3bt3QvXt3dO/eHV27doWenp7UcYmIiEhCN2/eRLdu3XD//n20a9dO6jhPSE5OhpWVFY4cOYI33nhD6jgNwoULF7BgwQLcvXsXo0aNwvfffw97e3upY9U7J06cwBtvvIHbt2/Dzc1N6jjUyN29exe//vor9uzZA3V1dYwbNw5z5sxB69atpY5GRM+PRQIiIqo5JSUluHPnDq5evYrr16/j2rVriI2NhZqaGpydncWiQffu3dG6dWuoqqpKHZmIiIhqiSAIsLGxgbe3NxYtWiR1nCds2LABCxYsQEpKCrS0tKSOU68FBQVhyZIl+P333+Hh4YGVK1eiQ4cOUseq1zp37gx7e3v8/vvvUkehRqi0tBSnT5/Gjz/+CB8fHzg5OeGDDz7A9OnToaOjI3U8InpxLBIQEVHtSk5Oxq1btxAQEAB/f39cvXoV+fn50NPTQ7t27cQ2Rd27d4epqanUcYmIiKgGzZw5E7dv38bt27eljvIEDw8PGBsb4+DBg1JHqbfi4uKwbNkybN26FZ06dcL3339fpxeqrk8OHTqEsWPH4sGDB2jbtq3UcaiRSElJwfbt27FhwwbEx8ezpRBRw8EiARERSau0tBQhISFi0eDKlSsIDg6GIAiV1jZwc3ND165duWggERFRA/Lnn3/i9ddfR0xMDKytraWOI0pPT4e5uTn27NmDt956S+o49U5GRgZWrFiBdevWwczMDEuXLsWECRM4iFiNBEFAu3bt0L59e+zZs0fqONTA3blzBxs3bsTu3buhqamJSZMmYc6cObCzs5M6GhFVDxYJiIio7ilfEPnKlSsICAjA1atXkZGRAR0dHXTo0AFubm5wc3ODu7s7bG1tpY5LREREL6moqAimpqb47rvv8MEHH0gdR7Rt2zZ88MEHSElJgb6+vtRx6o3i4mL88ssvWLJkCdTU1PDZZ5/hk08+QZMmTaSO1iDt2bMHkydPRlBQEJycnKSOQw1McXExjh07hk2bNsHHxwetW7fGzJkz2VKIqGFikYCIiOq+srIyBAUFiesa3LhxA8HBwSgrK4OdnR169OghLozcoUMH/kOUiIioHhkzZgwUCgXOnj0rdRSRl5cX1NTUcOzYMamj1AtlZWU4fPgwFixYALlcjo8++ggLFy6EgYGB1NEatNLSUjg7O6NPnz7YsmWL1HGogZDL5dixYwfWr1+PhIQEDB06FLNnz8bAgQM5G4io4WKRgIiI6qfc3Fzcu3dPbFN06dIlpKamQl1dHU5OTuJsg/KNCw4SERHVTXv27MHUqVORkpKCZs2aSR0HCoUCMpkMv/76KyZPnix1nDrPx8cH8+bNQ2BgIKZOnYolS5bAwsJC6liNxtatW/H+++8jLCyMrV/olQQEBGDTpk3YtWsXmjZtiokTJ2Lu3LmcuU3UOLBIQEREDUdYWBhu376NgIAABAQE4O7du1AoFNDQ0EDbtm0rFQ3atWvHGQdERER1QFZWFmQyGXbv3l0n+v/v2LED7733HpKSkmBkZCR1nDrr1q1bWLBgAf766y94eHhgzZo1XEBXAkqlEk5OThg6dCjWr18vdRyqZ8pbCq1btw7+/v7o2LEjZs6ciXfffRfa2tpSxyOi2sMiARERNWyJiYli0SAgIADXrl1Denp6lTMOOnXqxD+GiYiIJDBgwACYm5tj3759UkfBoEGDoK2tjSNHjkgdpU6KiYnBokWLsGfPHnTr1g0rVqxAnz59pI7VqG3YsAFz587Fo0ePYGVlJXUcqgeSk5Oxc+dO/PTTT0hOTsaQIUMwe/ZseHh4SB2NiKTBIgERETU+LBwQERHVLevWrcNXX32FlJQUaGpqSpYjNTUVlpaW2Lt3L8aOHStZjrooLS0Nq1atwtq1a2Fvb4+lS5di9OjR7FFeBxQVFcHR0RFjx47F6tWrpY5DdVhAQADWrVuHAwcOwNDQEFOmTMEHH3wAGxsbqaMRkbRYJCAiIgJYOCAiIpJSTEwM7OzscP78eUmvZP3555/x+eefQy6XQ0dHR7IcdUleXh5+/vlnfPvtt9DT08PixYsxdepUqKurSx2NKli9ejUWLVqEqKgoyGQyqeNQHVJUVITjx49jzZo1uHbtGjp16oT33nsPEyZM4LptRFSORQIiIqKqCIKA8PBwBAQE4M6dO+JtdnY21NXV4eLigk6dOqFdu3Zo164d2rdvD2NjY6ljExER1Vvt27dH37598dNPP0mWoVevXnBwcMDu3bsly1BXlJSUYNu2bViyZAlycnIwa9YsfPHFF9DT05M6GlUhPz8f9vb2mDp1KpYvXy51HKoDkpKSsHHjRmzYsAHZ2dkYPnw4vL292VKIiKrCIgEREdHzEgQBERERlRZGvn//PtLS0gAAVlZWlYoG7dq1Q6tWrXilHRER0XNYvHgxdu7ciejoaEla2MTGxsLOzg4nT57E0KFDa/34dYmPjw/mzJmD0NBQTJkyBUuXLoWZmZnUsegZli9fjm+//RZRUVEwMTGROg5JpGJLISMjI0yePBkffvghmjdvLnU0Iqq7WCQgIiJ6VZmZmQgMDBSLB0FBQQgMDERhYSE0NDTQsmVLuLi4wNnZGW5ubujSpQvMzc2ljk1ERFSnBAQEoHPnzrhz5w46duxY68f/7rvvsHLlSiQlJUm6LoKUrl+/jvnz5+PKlSsYPXo0li9fDkdHR6lj0XNSKBSws7PDxx9/jCVLlkgdh2pRUVERDh48iNWrV+P+/ftwc3ODt7c3Jk6ciKZNm0odj4jqPhYJiIiIaoJSqURYWJhYMCgvICQlJQEADA0NxaKBm5sbXFxc4OLiwj/iiYio0RIEAba2tpg6daokA5zt27dHz5498csvv9T6saUWEhKCxYsX4/fff4eHhwe+//57dOrUSepY9BKWLFmCtWvXIjo6Gs2aNZM6DtWwxMREbNq0CevXr4dCocDw4cMxe/Zs9OrVS+poRFS/sEhARERUmyrOOqhYQOCsAyIiImDWrFm4evUq7t69W6vHDQ4OhrOzM3x9fdG3b99aPbaUEhISsHTpUmzbtg2tWrXCV199hTFjxkgdi15BdnY2bG1tsWDBAixcuFDqOFRDrly5gh9//BFHjhyBiYkJJk2ahI8++ghWVlZSRyOi+olFAiIiIqkVFxcjODgYDx48wIMHD3D//n08ePAAcrkcAGBhYSGuddCmTRu4uLigTZs2XDiQiIganHPnzmHQoEGIjIyEvb19rR33yy+/xPbt2xEXFwdVVdVaO65UcnNzsX79eixbtgyGhob48ssvMW3aNKipqUkdjarBwoULsXnzZkRHR0NXV1fqOFRNCgsL8dtvv+GHH37AgwcP4Obmho8//hjjx4+HhoaG1PGIqH5jkYCIiKiuksvllYoGgYGBCA4ORkFBAQDA1tYWbdq0Qdu2bSsVD/T19SVOTkRE9HKUSiVkMhmWLl2Kjz76qNaO6+TkhOHDh2PlypW1dkwpKJVKbN++HYsWLUJJSQnmz5+P2bNns91hA5Oeng47OzssXboUc+bMkToOvaKoqChs3LgRW7ZsQW5uLt544w3MmTMHPXr0kDoaETUcLBIQERHVN4mJiWKrovLb+/fvIzc3F8D/1jsob1vk4uKC9u3bw9TUVOLkREREzzZu3Dikp6fj/PnztXK8GzduoHv37ggICGiwffgFQcChQ4ewcOFCxMXFYebMmfj666/Zs74Bmzt3Lvbv34/IyEhoaWlJHYdeQsWWQqampvD29sasWbP4Nz0R1QQWCYiIiBqKlyketGvXDjKZTOLkRERE/7N//35MmjQJcrkchoaGiIiIwLFjx3D8+HGcOHHilWbMffvttzAyMsK4cePEAfJPPvkEZ86cQUhISHWdQp3i4+ODBQsW4N69exg1ahRWrFgBOzs7qWNRDUtOToaDgwNWrVqFDz74QLw/IyMDBw8exPvvvy9hOnqa3Nxc7Nu3Dz/99BMePnzIlkJEVFtYJCAiImroXqZ44OrqCjMzM4mTExFRY5SZmQkzMzMMHToUwcHBCAsLg4qKCgRBQFFRETQ1NV963yNGjMCxY8egoaGBkSNHYvLkyZgxYwZmzJiBr776qhrPQnqBgYH4/PPPcfLkSXh4eGDVqlVo37691LGoFs2aNQsnTpxAREQEsrKy8MMPP+Cnn36CIAjIz8+HioqK1BHp/z169AibN2/G5s2bkZeXh7Fjx+LTTz/le5aIaguLBERERI2RIAiIjo5+ongQEhIiFg8sLCzQunVrODk5wcnJCa1bt0arVq1gZ2fHhQ2JiKhaFRUV4fLlyzhx4gQOHDiAlJQUqKuro6SkRHyOmppape9fxpAhQ3DmzBkAEPevoqKCGTNmYM6cOWjduvUr7b8uiIuLw7Jly7B161Z06tQJK1asQL9+/aSORRKIi4uDo6Mj3N3dcfnyZZSVlUGpVAIAUlNTYWJiInFCKm8p9Mcff8DMzAwzZszAhx9+yP82RFTbWCQgIiKi/xEEATExMQgKCkJQUBDCwsIQFhaGkJAQyOVyAICmpiZatGiBVq1awcnJCa1atRI3Y2Njic+AiIjqmyNHjuDdd99Ffn4+NDU1UVxcXOXztLS0kJ+f/0rH6t+/Py5duvTE/RoaGlAqlWjXrh2mTp2Kd955p94N0mVkZGDFihVYt24dbGxssGzZMowePZpXizdSMTEx+OGHH7BhwwYAQGlpaaXHG/IaHHVdTk4O9u/fjx9//BGBgYHo1asXZs+ejZEjR0JdXV3qeETUOLFIQERERM8nOzsbERERiIyMRGRkpDgDITQ0tFLrIgcHBzg4OIitixwcHNCmTRtoa2tLfAZERFQXKZVK9OjRAw8ePBCvcq6KoaEhMjIyXulYvXr1wtWrV5/6eHlbo6+//hqLFy9+pWPVlvz8fPz000/47rvvoK6ujnnz5uGTTz5BkyZNpI5GEggPD8e3336L3bt3Q1VV9anvqSNHjmDEiBG1nK5xi4iIwJYtW7Bp0yYUFBRgzJgxmDdvHtq1ayd1NCIiBUuURERE9FwMDAzg5uYGNze3Jx7LzMwUiwblBYTdu3cjOjoaZWVlAP5pX1ReNKhYQLC3t+dVjkREjZiGhgb++OMPuLq6oqSkBE+7jk1LS+uVj1VUVPSvj6upqeH111/Hl19++crHqmllZWU4fPgw5s+fj9TUVHz44Yf4z3/+80oLO1P9lpOTg6FDhyIiIgLAk7MHymloaCAuLq42ozVaZWVluHjxIjZt2oQ//vgDtra2WLBgAaZPn84ZuERUp7BIQERERK/M0NAQvXv3Ru/evSvdn5+fL7YsCgsLQ3BwMO7cuYMDBw5AoVAAAPT19cV1D5ycnODo6IgWLVqgRYsW9a7VAxERvRwbGxts27YNo0ePfupzarpIoK6ujtatW2Pv3r1QVVV95WPVJB8fH3z66acIDg7GlClT8PXXX8Pc3FzqWCQxPT09XLx4Eb1790ZiYuJT1/BQVVVlkaCGlbcUWrt2LYKDg9GrVy/s37+fLYWIqM7iJxMRERHVGG1tbXTo0AEdOnR44rGkpCSEhoYiLCwMoaGhCA0Nxf79+xEVFSX2ozYwMECLFi3EwkHFWysrq9o+HSIiqkGjRo3CzJkzsWXLlioHN6ujbd3TWq+oqamhWbNmOH36NHR0dF75ODXl5s2bWLBgAS5dugQvLy8cOnQILVu2lDoW1SHW1ta4cuUK+vTpg8TExCp/55VKJWJiYiRI1/CFh4dj69at2LhxI0pKSvD222/jt99+Q9u2baWORkT0r7gmAREREdU5j7cvKt/CwsKQk5MD4J8FlJttCZEeAAAgAElEQVQ3by6ugVCxjZGtrS3U1NQkPgsiInpRRUVF6NKlC0JCQp4Y3OzWrRuuX7/+Svt3cHBAVFRUpftUVFSgoaEBPz8/dOvW7ZX2X1PCwsLw5Zdf4tChQ+jevTu+//579OnTR+pYVIfFx8ejT58+SEhIqLJQ4Obmhtu3b0uQrO4rKiqCXC6HjY3Ncz2/vKXQunXrcOrUKTg4OGDGjBmYMWMGjIyMajgtEVG14MLFREREVL9kZmZWKhyUr4EQGBiIrKwsAP/02rW2tq5UQCjfuIgyEVHdFh4ejvbt26OgoKDS/QMHDoSPj88r7dva2hrx8fGV7lNRUcHevXsxfvz4V9r3i/rss8/w1ltvoXPnzk99TlpaGlatWoU1a9bA0dERX3/9NcaMGVOLKak+S05ORp8+fRATE/NEocDU1BQpKSkSJau7cnJy4OXlBRsbG+zevftfn6tQKHDgwAGsWbMGoaGhGDhwILy9vfHmm2/yYhUiqm9YJCAiIqKGIy0tDREREXj06BEiIiIqfZ2amgrgn5YSNjY2Ytsie3t72NnZwd7eHvb29lwHgYioDti5cycmT55c6b4RI0bgyJEjr7Rfc3NzyOVy8XtVVVUsWrQIS5YseaX9vqhVq1bhs88+g7u7Oy5duvTE43l5efj555/x7bffQk9PD4sXL8a0adM48EgvLDk5GX379kV0dHSlQoGqqioKCwuhoaEhYbq6JSUlBa+99hr+/vtvqKurIz4+HjKZ7InnhYWFYf369di6dStUVVUxfvx4fPzxx3BxcZEgNRFRtWCRgIiIiBoHhULxROHg0aNHiIqKQkJCAkpLSwEAurq6TxQOKn6vr68v8ZkQETUOEyZMwMGDB6FUKqGqqopx48Zh7969r7RPIyMjZGZmAvhn1pmXlxcOHz4MFRWV6oj8XHbv3o1Jkyah/J/if/75JwYPHgzgn17x27dvx1dffYXc3Fx8+umnWLBgQbUs2kyNl1wuR58+fZ4oFERFRcHOzk66YHVIdHQ0BgwYgPj4eCiVSmhoaGDx4sX48ssvATzZUsjR0RHTp0+Ht7c3DA0NJU5PRPTKWCQgIiIiUiqVSE1NRVJS0hOtjCIjIxEdHY2ysjIAgKGhISwsLGBpaflEKyMnJyfo6elJfDZERA1DXl4e2rdvLy6wOnnyZGzevPmV9qmvr4+cnBxoaGigdevWuHbtWq0uVOzj44MhQ4aICzOrqanByckJDx8+xKlTp/Dpp58iJiYGkydPxjfffFPlVcxEL0Mul6Nv376IiooSCwV+fn5c2wJAYGAgBg4ciIyMjEpFFFNTUwQFBWHv3r1Yu3YtYmNjMWDAAHz88cfw8vKq1eIiEVENU6hLnYCIiIhIahoaGrC0tISlpSXc3NyeeLy4uBjx8fFVroXg4+ODqKgo8YpQQ0PDKtdCsLCwgIODA68GJSJ6Tjo6Ojh06BC6du0KpVJZLZ+fJSUlUFFRgaGhIc6cOVOrBYKbN29i2LBh4sw1ACgtLUVISAhatmyJ6OhovP322zh37hyv7qZqZ2ZmBl9f30prFMTGxkodS3I3btyAp6cn8vPzxeJdubS0NFhZWUFLSwtTpkzBrFmz0KJFC4mSEhHVLBYJiIiIiJ5BU1NTHOyvikKhQHR0NKKioiptp0+fRlRUFHJzcwH8c8WopaUlbG1tYWtrC2tra1hbW8PGxgZ2dnawtraGgYFBbZ4aEVGd1qFDB6xZswYffvhhtRUJNDU1cerUKVhaWlZDwucTHh6OwYMHQ6lUoqrJ/PHx8bh69Sq6detWa5mo8TE3N8fly5fRt29fhIeHN/oiwcmTJzFq1CiUlpZWKt6VU1FRgYWFBR4+fAhdXV0JEhIR1R4WCYiIiIhekb6+Ptq1a4d27dpV+XhaWhqioqIQHR2NmJgYxMbGIiYmBmfOnEFsbCwyMjLE5xoYGMDa2losGtjY2MDa2hq2trawsbGBpaUl1NX5JxwRNR6zZs3CxYsXoa2t/cr7Ki0txd69e9G5c+dqSPZ8EhMT0a9fP+Tk5FQ5ECkIAkpLS3HlyhUWCajGlRcK+vXrh7i4OKnjSGb37t2YMmUKBEEQW0o+rqysDDExMQgJCanVzwwiIilwTQIiIiIiiRUWFiIxMRGRkZFITEystDZCYmIioqOjkZ+fLz6/Ykujx9dHKP+eiKihUCqViI6OxunTp9G7d2/k5eWhuLhYfKx8thbwT4siTU1NAP+0ktPV1YWenh6aNWsGHR0d/PDDD1i8eHGtZc/OzkbPnj0RHh5eqdd5VfT09BAdHQ0jI6NaSkeNUWFhIQoKChAdHY1NmzZh+vTpAICCggIUFhZWeq4gCMjKynpiH2pqatDX13/ifj09Pairq0NdXR16enrQ0tJC06ZNoa+vDzU1tZo5oZewbt06zJkzp8pZPY/T0NDA22+/jR07dtR8MCIi6XDhYiIiIqK6rqysDMnJyYiOjkZsbCzi4uLE2QixsbGIjY1FZmam+PzHZyNYWVmJt5aWlrCxsanVPtxERFUpKytDdHQ0IiIikJCQgLi4OCQkJCAxMRFxcXFIT09HZmYm8vLyqu2YOjo6aNasGYyMjMTZWRU/I1u0aAE7O7tqGdAsKCjAgAEDEBAQ8MwCAQCoqqpi3rx5+P7771/52NRwFRYWIjk5GUlJSeJ7JDMzE1lZWVV+nZeXB4VCAaVSiezsbMlyq6qqwsDAAE2bNoWWlhaaNWsGQ0ND8bZ8q/i9TCaDubk5ZDJZtbwnBUHA/Pnz8cMPPzxXgaCchoYGEhMTYWJi8soZiIjqKBYJiIiIiBqC3NzcSkWD8kJCdHQ0EhMTkZCQUOkKwWbNmokDY5aWluIAmZWVlThwxqtZiag6CIKAR48eISAgAH///TdCQ0MRGhqKsLAwFBUVAQC0tbVhY2MDCwsLNG/eHM2bN4epqSmaNWtWaas4yAj8b+CxnEKhEFv6lF8xrVAokJWVJW6ZmZlIS0tDfHy8WJSIjY0VixFNmjRBixYt0Lp1azg5OcHV1RVubm5o2bIlVFRUnuucS0pKMGLECJw9e/aJxVArUldXh6qqqjgzwtDQEBEREfz8bYQEQUBSUhKioqIQExODuLg4JCUlISUlBQkJCUhNTUViYuITA/1Nmzb914F2HR0dGBgYQENDA/r6+mjSpAm0tbWhq6sLDQ0NGBoaAvjfzJvHGRgYQFVVtdJ9RUVFlWY4liu/YKF8hk9+fj6KioqQnZ2NkpISZGdni68tfy9WLGhULHJUbM2lqqoKmUwGU1NTWFlZQSaTwcLCAhYWFuI6T7a2tv/6vikpKcHUqVOxe/du8b7y95+KigrKyspQUlJSZfFAR0cHq1evhre391P3T0RUz7FIQERERNRYZGZmiu2MKrY1qvh1xRkJTZo0gZWVldjCqGJro/KvbW1t61QLASKSXnp6Onx9fXHt2jUEBATgzp07yM7Ohrq6Olq1aiUOvrdu3RqtW7dGy5YtxYFKKWVlZSE8PByhoaEICQkRixkhISFQKpXQ19dHp06d4Obmhh49esDd3b3KK4sFQcC0adOwfft28b7ytWTKCwY6OjpwcnJCp06d0Lp1azg7O6NNmzawtbV9YkCWGo78/PxKRbKYmBhxi42NFYtFGhoasLCwEAfELS0tYWZmBgsLC5ibm8PMzAyWlpYwMTGplgW96yKFQoHk5GTI5XJx5kR5wSQlJQVJSUlISkpCcnKy+Bo9PT3Y2trCzs4OdnZ2sLW1hZOTE+zs7PDf//4X/v7+0NXVhbGxMUxMTGBsbCwWU4yMjCoVWipuXAuKiBoBFgmIiIiI6H8UCgXi4+MRHx8vXl2bkJAgtgJJTExEWlqa+HwNDQ1YWlqKV/6Wf21mZlbptqqrE4moYcjLy8PFixfx119/4a+//sKDBw8AAG3btkXnzp3FgfX27dvXywHNoqIiPHjwAAEBAeL24MEDlJWVwdXVFf3790f//v0xYMAA6Onp4T//+Q+WL18O4J+ZAS4uLnB1dRULAW3atOHaMQ1cZmYm7t27h9DQUAQHB4tFp9jYWAiCAA0NDdjb21e6Ct7W1hb29vawsbGBlZUVC/DPqbCwsFKxpXyLjo5GVFQUEhISAACamppo0aIF2rRpIxYr27Rpg7Zt26Jp06YSnwURkeRYJCAiIiKiF1NYWPivRYSEhATI5fJKLTZ0dHSqLB6wmEBUP6Wnp+PUqVM4efIk/vzzT+Tm5sLBwQEeHh7w8PDAwIEDG3TLnLy8PFy7dg0+Pj7w8fHB3bt3oaGhga5du8LS0hJvvfUW3N3dG/TPgP6RmJiIgIAABAUFITAwEAEBAQgODoYgCDAwMECLFi3g4OAAZ2dnuLi4wMHBAS4uLhyYriVFRUWIiIhAUFAQIiMjERgYiKCgIAQHByM/Px/q6upwcnKCi4sLnJ2d4ebmhu7du8PU1FTq6EREtYlFAiIiIiKqGVW1N3r8Ni4urtKCnk2bNoWhoWGl9kZPuyWi2pWfn49Dhw5hx44d8PPzg6amJl577TUMHz4cXl5ekMlkUkeUTHp6Ok6ePIljx47h7NmzKCwsRM+ePTFlyhSMGTMGenp6UkekalBYWIhbt27hypUr8Pf3x/Xr15Geng4VFRU4ODigU6dO6NChAzp27IgOHTrAwsJC6sj0FKWlpXj06BHu3r1baUtNTQUAODo6omfPnujVqxd69+4NZ2fn516ThIioHmKRgIiIiIikIwgC5HI55HI54uPjn3qbkpJSqZhQcWaCubk5zM3NxQUNTU1NxftkMhk0NTUlPEOi+u/mzZvYvHkzfvvtNxQWFmLYsGF45513MGjQIGhra0sdr84pKCjA+fPnsW/fPhw7dgxqamoYPXo0pk+fjt69e0sdj15Abm4uLl26hMuXL8Pf3x+3b99GUVERLC0t0bt3b/Ts2VMsCOjr60sdl6pBQkIC7t69i4CAALEQlJOTAyMjI7Fo4O7ujq5du7IlFBE1JCwSEBEREVHdV1UxobytUWJiIlJSUiCXy5GUlIS8vLxKrzU2NoaZmZm4+KNMJhMXgDQ1NYWFhYX4OBcnJPqHIAg4efIkfvzxR/j4+MDZ2RkTJ07ElClTGvWMgReVnZ2NgwcPYteuXfD390fHjh3xySef4O233+bnTR0VGRmJEydO4OTJk7h8+TKKiorg4OAgXlHeq1cvuLi4SB2TaklpaSlCQkLg7++PK1eu4PLly4iOjoauri769euHYcOGYciQIbC2tpY6KhHRq2CRgIiIiIgalvz8fCQlJUEulyMlJeWJIkJKSgqSk5ORnJyMgoKCSq+VyWSQyWSVZieUFxbK7zc1NYWpqSlnKFCDJAgC9u3bh2XLliE0NBReXl6YN28e+vbtK3W0eu/69etYuXIljh49CgcHB/znP//BpEmToKqqKnW0Rk2pVOL8+fM4dOgQzpw5g6SkJMhkMnh6emLw4MHw9PRkf3qqJDQ0FH/++SfOnj0LX19fFBQUoF27dhg6dCjeeustdOjQQeqIREQvikUCIiIiImq8CgoKkJmZKa6TUPHrivfFx8dDoVBUeu3j6ycYGho+8X3516amptDQ0JDoLImej5+fHz799FPcvXsXEyZMwPz589GmTRupYzU44eHhWLVqFbZt2wYXFxesWrUKHh4eUsdqVEpLS3Hp0iUcPHgQhw8fRmZmJrp37w4vLy8MGjQIHTt2ZPGGnktBQQH8/Pxw5swZHD16FNHR0WjVqhXeeustjBs3jp+hRFRfsEhARERERPQ8srOzIZfLkZqaitTUVKSkpCAlJUX8vnzmQlpaGlJTU1FaWiq+VkVFBSYmJuIshPKWR+X3lc9QKP/exMREwjOlxkYul+PDDz/EoUOHMGjQIKxcuRKurq5Sx2rwQkJCMH/+fJw4cQLDhg3Dr7/+ykXZa1hkZCR++eUX7NmzB8nJyejYsSPGjRuHt956C7a2tlLHo3pOEATcuHEDBw4cwO+//47ExES0b98eM2bMwMSJE7mAORHVZSwSEBERERHVhIKCgkqzER6fsVDx+5SUlEpFBeCfmQqPz1KoarZC+WZubs4rX+mFHTlyBO+99x50dXWxYcMGDB48WOpIjc7Fixcxc+ZMpKenY/369Rg3bpzUkRoUQRBw7tw5/Pzzzzh9+jQsLS0xffp0jB8/Hk5OTlLHowaqrKwMfn5+2LNnD/bv3w91dXVMnDgRs2bNQuvWraWOR0T0OBYJiIiIiIikVlJSgtTUVKSlpYmzE9LS0pCeno709HSkpaWJMxTK7398PQUNDQ2YmJjA2NgYxsbGMDExgUwmE79+/H4jIyNe1diIFRcXY9asWdiyZQumT5+O1atX8/dBQvn5+Zg/fz42bNiAd955B5s3b0bTpk2ljlWvlZWVYd++ffjmm28QFhaG/v37Y9asWRg+fDgXjaZalZmZie3bt2PDhg2IjIyEp6cnvvnmG3Tp0kXqaERE5VgkICIiIiKqj8rXU6i4PT5ToeL9CQkJKCoqemI//zZj4WmbhYUFVFRUJDhrqg7/196dR1VV9f8DfzOJKMMFDBxQREy6ToCaE6iYBYRmDimipDgwpUglpo/VN1OfnLIshSe1VFBLHk1ZqYipgDKUIRSmAioiCsQgMs9czu8Pf/c8EohA6kF5v9Y6C87Z+5zzuWfdjcv9OXvvwsJCTJ8+HXFxcdi/fz8mT54sdUj0/506dQouLi7o378/QkJCOPVYKx0/fhyrVq3C1atXMW/ePLz//vsYMGCA1GFRO1dXV4ewsDB89tlniI2NxbRp07Bu3TqOLCCitoBJAiIiIiKi9qKkpEQckZCfn4979+6JW1P7f6epqQlDQ0MYGBiIm3JfOWJBJpNBX1+/3k+ZTMYpkVohMTERcrkcHTp0+MfXysnJwYQJE1BUVIQTJ05g8ODBjyFCepySkpIwceJEqKmpISIiAiYmJlKH9MxISkqCp6cnoqOjMXXqVKxbt44Lx1KbdOzYMXz44YdISkrCwoULsXnzZo7mIiIpMUlARERERERNa8moBeXW2DoLwP2RC42NTtDS0npomXIzMjJql9OETJo0CbGxsXB3d4e7uzv69u3bquuUlZXBzs4OxcXFCA8PR48ePR5zpPS4KJM5qqqqiIqKgp6entQhtWmCIGD79u1YsWIFBg0ahK+//hojRoyQOiyiJtXV1eHAgQPw8/ND586dERQUBFtbW6nDIqL2iUkCIiIiIiJ6MhpLLjxsq6ysrFc/Ozsbjf1X5VGJhKaSDs/q4s5jxoxBdHQ0NDQ0UFtbi3Hjxolzq2toaDTrGnV1dZg8eTLi4uIQGxsLc3PzJxw1/VN37tzByJEjIZfLERYW1i4TZM2Rm5uLt99+G+Hh4fjoo4/w4Ycf8lnRMyU3NxeLFi1CaGgoVqxYgbVr1z6T/1YR0TONSQIiIiIiImp7ampqUFhYWG8rKCio97OprbKyssE11dXVxWmPlJsygSCTyaCnpwcdHR1x09PTg66uboNjT5ulpSUuXbok7qupqaGurg4ymQweHh7w8PBAnz59mrzGf/7zH/j6+iI6OhrDhw9/0iHTY/LHH39g1KhRWLduHZYtWyZ1OG3OzZs34eDgAEEQ8P333/O7Tc+0Xbt2YenSpZg4cSIOHDgATU1NqUMiovaDSQIiIiIiInr+VFRUPDKRoEw4KJMORUVFKCkpQUlJCcrKyh567cYSB40d09PTg7a29kOPde7cuVmfxdzcHDdv3my0TDm6wM7ODt7e3pgyZUqD0QU5OTmQy+Xw9PTE+vXrm/8QW+j48eMoLCysd+z111+HoaGhuJ+QkICrV6+K+1paWqioqBD3VVRUYGRkBDMzM5iamj5ypERVVRUCAwORmJiIHj16wNbWFsOHD8fp06fxxhtvPKZPJq1PP/0UmzZtwpUrV9C7d2+pw2kzsrOzMXr0aBgYGCA0NBRGRkaSxbJ///56+xYWFnj55ZdRWFiI0NBQ1NXViWVqamoYPnw4fvnll0de18DAAJaWloiIiGhWXV1dXdy6dUs81tL2pJSUlITz58/j8uXLMDAwwLBhw/Dqq69CS0urWedT650/fx6TJ0+Gvb09Dh48yBEFRPS0MElARERERET0d4IgoLCwEMXFxWLioLS0tFXHqqqqGr2Hqqpqs5IJW7duRUlJSZPxqqurQ6FQwNDQEAsXLoSXl5fYofzee+/hyJEjSEpKQqdOnR73oxIVFRXhww8/hL+/P7S1tfHLL79g4MCB9epUVlaKnd4HDx7EtGnT8PPPP8PJyQldunTBihUrUFZWhuDgYBQUFCAwMBD29vaN3q+wsBA2NjYYNWoUPDw8UFRUhL179yI4OBg+Pj748ssvxbpVVVUtfiu3Nec8CVVVVRg0aBDGjx+PHTt2SB1Om6BQKDBu3DjcvXsX0dHR6NKli6TxREVFYezYsdDU1ERsbCyGDBkilhUXF8PV1RXHjh3D/PnzsX37dpw4cQLe3t545513YGRkhNzcXKxduxZjxozBrFmzUFZWhjNnzuD27dtYs2ZNs+tevXoVYWFhrWpPwP11Sz766COcP38eGzduhJWVFTIyMhAUFISwsDAcOHAA1tbWLX4+baUtPSvOnTsHR0dHrFq1Ch9//LHU4RBR+8AkARERERER0ZNUXV3d6gRDSUkJkpKSUFtb26J7qqqqwsnJCe7u7vDw8MDSpUuxatWqJ/QJ/6eiogJmZmbIz89Hbm4u9PX1G9T56quvkJqaiq+//lo8pqenh549e+Ly5csAgHv37mHEiBFITU1FQkICrKysGlzH19cXp0+fxpUrV6CioiIeX7x4MTp06FAvSeDn54dNmza16K3c1pzzpGzduhWffPIJsrOz+TY37n+HVq5cibi4uAaJKKno6uqiS5cujY76+fzzz7F8+XLs27cPrq6u2LNnD8zNzTF27FgAQHJyMuRyOby9vREQEADgfqJywYIFGDt2bLPr7tmzB0Dr2hMATJw4EdeuXcOlS5cafM/Wrl2LdevWISoqqsXTOrWltvSs+Oqrr7B8+XIkJiZCLpdLHQ4RPf+K+ReaiIiIiIjoCerQoQMMDAzQp08fWFlZYcyYMXBycsLMmTPh4eEBPz8/fPrpp/jiiy+wc+dO/Pe//0VYWBhiYmLqrUXwKOrq6lBRUYGGhgZeffVVTJw4EQUFBcjLy4Orq+sT/IT/o6WlBW9vb9TW1uLIkSON1vnpp5+wfPnyesc6dOhQr6PfwMAAzs7OEAQBBw8ebPQ6cXFx0NTUrHceAKxYsaLesT///BPffPNNiz5Ha855kmbPno2KigocP35c6lAkV11djQ0bNsDHx6fNJAgAiIulP6wMgFg+YMAA2NraNnk9FRUVeHl5taiuUmvaU0BAAEJDQ/HRRx81moh699130blzZyxatAg1NTVNxvOgttaWnhU+Pj6wsLDAZ599JnUoRNROqEsdABERERERETWuurq6yVEEGhoaqKmpgUwmw6RJkzB58mQ4OjpCR0cHALB+/Xr06dMHvXr1elohw8vLC+vXr8e2bduwcOHCemXJycnQ1dVFz549H3kdXV1dAEBGRkaj5XK5HLt374aPjw+2bNmCDh06AAB69eoFR0dHAEBMTAxmz56NsrIyHDx4EBoaGpgxYwYA4Pr16wgNDUVhYSGGDx+O119//ZHnFBcXIzg4GElJSejTpw/c3Nygra3diqfUMkZGRrC2tkZMTIwYS3sVFRWF7OxsvPPOO1KH0mrNfRN/xIgRzb7mo+o+qj2tXr0aqqqqcHFxabRcR0cHU6dOxe7du3Ho0CFxAXUNDQ289dZbAIDDhw+jpqYGWlpamDJlSpNtqbKyEocOHcKVK1cwatQo2Nvb10tOVFVV4dy5czh37hy6d+8OR0dHmJubi+W3bt3Cnj17sHLlSuTk5GDv3r0wNjaGi4sLZDIZUlNTcejQIXTo0AHz589vMKpJqrbcXKqqqvD29sbKlStRXV0t/n0jInpSOJKAiIiIiIiojSotLa23r6amBjU1NaioqGDQoEFYtWoV4uLicO/ePezbtw8zZswQEwQAcPv27aeaIAAAY2NjzJo1C4mJiYiMjKxXtmPHjnpvPDflhx9+AABMmDCh0fJ//etf6NKlC7Zv345BgwYhLCxMLFPOuy4IAsaMGQMA4loPALB06VIsXLgQrq6uGD16NCZOnIiNGzc2ec7169fh6uoKU1NTzJs3Dzt27ICVlVWDxZqflL59+9ZblLa9SkxMhImJCRdxbqGm2lNWVhby8vLQrVu3JjujTU1NAQB//PEHnJyc4O/vXy8RaGNjg/Xr18Pb2xvAw9tSeno67O3tUVVVhSVLlmDbtm0YOHAgKisrAdxPIDg6OqKgoADLly+HIAiwtrYWRycdPHgQY8aMwZo1a3DixAn83//9H27cuAEfHx8sXLgQ58+fx0cffYTLly9jxYoVDUZSSd2Wm2vMmDEoKSlBamqq1KEQUTvAJAEREREREVEbVVZWJv6uqakJBwcHBAQEICMjA5cuXcLq1asxbNiwBlPuKBUUFEAmkz2tcEW+vr4A7s+rrVRRUYHo6OiHLpxaUlKCixcvIiYmBi4uLvjjjz/g5uYGNze3Ruv37dsX4eHhGDx4MK5du4bXX38dTk5OuH79uljH1tYW/fr1AwA4OTmJ9w4KCoKDgwMMDQ3x2muvQS6XIyQkpMlzFi9ejAULFsDe3h6WlpbYvHkzUlNT8cUXX/yDJ9V8WlpaYidqe1ZcXCy+Fd/WZGVlid/ZB7d9+/Y99Vha0p6U05o9aoSPsvzq1avQ0dFpsIhxt27d6o1oeFhbcnd3h1wux6JFi2BiYoL33nsPaWlpOHnyJABg4cKFMDMzg7OzM2QyGZYsWQIHBwe4uroiIyMDs2bNgru7O4D7UysFBQVh//798PT0xJEjR5Ceno4ffvgB+/fvx8qVKxEaGori4mIxLqnbcnMpkypFRUUSR5C8LIkAABMDSURBVEJE7QGnGyIiIiIiImqj6urq4OnpiTfeeAOvvPJKixetNTExQXR09BOK7uGsra0xZswY/PTTT0hLS4OZmRmCg4MxY8aMhyY01NTUkJ6ejjt37sDe3h4rV66EpaVlk/cZNGgQ4uPjERAQgNWrV+PkyZOIjIxESEjIQ5MRAHDixAlxMdDffvsNgiCgoqLiofX/+usvnD59GlZWVrhw4QKA+6M8hg0bhvLy8kc9jsfi3r17kiR82pquXbsiMzMTCoUCampqUodTT9euXbF9+/YGx3fu3Cl+b56WlrQnZWf0gx3pjREEAQBgaGgIAI0uRPyoxYlv3LiB06dPIzQ0VDw2ceJEZGdnw8jICOXl5Th06BC2bNlS7zxvb28cPnwYe/bswccffyxODaRc0BmA+PkeXMPhpZdeAgBkZmZCV1e3TbTl5kpPTwcAdO/eXeJIiKg9YJKAiIiIiIiojTI1Nf1Hi3726tULN2/ehCAID+2cf1J8fX0RFRWF7du3Y8uWLdizZw9+/PHHh9bv1KkTpk+f3uL7qKurY+nSpZgzZw7ef/99BAUFwdnZGbdu3RI7P//OxsYGR48exZEjR+Dg4IDevXsjMzPzofdQjk744IMP0KVLlxbH+DgkJibi7bffluTebcm4ceNQVFSE6OhojBs3Tupw6lFVVW10XntNTc2nHktL2lP//v0B/K9T+mGU6xn8kwWjk5KSAKDBczIyMgIAxMbGoqamBurq9burXnzxRQDAtWvXAPwvGfHg37XGnrNy+iTlYsttoS031/Hjx2FmZvbUp4wjovaJ0w0RERERERE9pyZMmIC8vDxJRhNMmTIFpqam+O677xAVFYWePXs+1k455RoCSoaGhggMDISLiwsKCwsRExPz0HM/+OAD7N69G7t27YKrq+sjO3GVHY0JCQkNykpKSloRfcvEx8fj5s2b4uLK7ZlcLoeNjQ3+/e9/Sx3Kc0NPTw/W1tYoKytrcv775ORkqKqq4rXXXmv1vZSjoU6dOtWgLC8vDwqFAsD9ZMGDlH87lNMXtZbUbbm57t69ix07dmDRokVSh0JE7QSTBERERERERM+pAQMGYMiQIQgKCnrq91ZTU8OSJUtQVFSEmTNniouZNkYQBHEqk+aKiopCdnZ2g+PTpk0D0PBNZWXnY3x8PDZv3ozFixejY8eO9WL4O+U5FhYWUFNTwyeffILq6mqxPC8vDwcOHGhR3K2xb98+WFhY1JvvvT3bsGEDzp49i2+//VbqUB4L5XevOW2gOXVb054CAgKgoqKCTZs2NVqekZGBH3/8EUuWLIGVlRUAQFdXF1VVVQ3urWw3D1Ie69+/P1RVVXHs2LF69VJTU3Hx4kVYW1tDU1OzQZIvLy8PAMSFkFtL6rbcHIIgwNPTE3p6evDx8ZE6HCJqJ5gkICIiIiIieo55enpi3759SE5Ofur3XrRoETp37owXXngBNjY2jdaprq5GQUHBI+dD/7u6ujrMnTsXpaWl9Y4fOHAAgwcPxsiRIwEAL7zwAoD7yYGoqChxmpKQkBDU1tbizJkzSExMREFBAa5fv460tLQG52hpacHLywu//vorxo0bh++//x579+7FnDlz4OLi0qK4WyotLQ27du2Cp6fnE73Ps8TW1hYrV67E4sWLcebMGanDgSAIKC0tRUFBQaPlyu/2w8qVya6/f5dbU7e17WnkyJFYu3YtgoKCEBkZWa+suLgY7u7uGDlyZL0RHKampqiqqsLp06chCAKCg4MRGxuLoqIiFBUVQaFQNGhLBgYGmDt3Li5duoQZM2YgPDwc/v7++Pjjj+Ho6AgjIyP4+PggLS0NERER4r1CQkIwY8YMcYop5ed/cHF35ZRCD64vUltbW6+evr6+ZG25uf71r3/h2LFjCAwMhI6OjtThEFF7IRAREREREdFzS6FQCMOHDxfGjh0r1NXVPfX7e3t7CwEBAY2WnTt3Tpg2bZoAQAAgeHt7C7/99luzrjtnzhxh+vTpgrW1tTB//nxh1apVwoABAwQ7OzshLS1NrHfz5k3B2NhY0NfXF7799ltBEATh7bffFlRVVQVjY2Phm2++EdatWyeoqqoKfn5+Dz2nrKxMmDt3rhirrq6ucPTo0X/wZJpn0qRJwoABA4Tq6uonfq9niUKhEGbPni1oaWkJISEhksYya9Ys8Xvx3nvvCRcuXBAEQRAKCgqEzz//XOjRo4cAQBg0aJCwa9cuoaKiQjz3wIEDwssvvywAEGQymbBu3Trhzp07jd7nUXX/SXtSioiIECwtLYUFCxYI27ZtE/z8/IQRI0YIn332maBQKOrVLSsrEwYOHCgAEIyNjYXAwEDBw8ND0NfXF/z8/IS7d+822paKioqEqVOninH27t1biIuLE6+rUCiE999/X3jhhReEFStWCPPmzRNmzpwpPreff/5ZvK+Xl5eQkpIihIaGis/G1dVVuHTpkhAeHi7Y2toKAIS33npLuHr1qhi3FG35URQKheDr6yuoqqoKQUFBUodDRO1LkYogtHAMGhERERERET1T4uLiMGrUKKxZswarVq16qvfOzc2FtrY2OnXq9Fivm5mZiR49ekAQBFy+fBn5+fkwNzdHz549G9StqalBbW2tOB86cH96EZlMBg0NDQD33/LW19dv8hzg/lzht2/fhlwub1D2uG3duhXLli1DZGTkP55m5XmkUCjg4+ODb775Bj4+Pti0aZMkiwQ/j4qKinDlyhWYmJg0uXCusv2Zm5ujU6dOuH79OkxMTOq1jYe1paysLOTl5aF///5iO3xQRUUFkpOTIZfL600N9rg8zbb8KNnZ2ViwYAHOnj2LwMBAzJo1S9J4iKjdKWaSgIiIiIiIqB3YuXMnvLy8sHfvXsydO1fqcOgRjh07hqlTp2Ljxo1YtmyZ1OG0aYcOHYKHhwd69OiB/fv3i3PmEz0LDh8+DE9PTxgZGWH//v0YOnSo1CERUftTzDUJiIiIiIiI2gEPDw/4+fnB3d0dBw8elDocakJISAicnZ3h7e3NBEEzzJgxAwkJCZDJZBg5ciSWLVuGu3fvSh0WUZMuXbqESZMmYebMmXBxcUFCQgITBEQkGSYJiIiIiIiI2okNGzZg8eLFmD17NtavXy91ONSIrVu3Yvr06Zg3bx62bt0qdTjPDDMzM5w7dw5btmzBgQMHYG5ujrVr1zZrMWCipyk1NRWurq6wtrZGTk4Ozpw5g+3bt0s+5RERtW+cboiIiIiIiKid8ff3h6+vL2bOnImAgADIZDKpQ2r3SkpK4Ovri8DAQGzcuBF+fn5Sh/TMKi0txdatW/H5559DU1MTHh4e8PLyQo8ePaQOjdqxCxcuwN/fHwcPHkSfPn2wbt06TJ8+HSoqKlKHRkTENQmIiIiIiIjao59//hlubm5QU1PD7t278dprr0kdUrt1/vx5zJs3D+Xl5fjuu+8wadIkqUN6LuTn5+Orr77Czp07kZ+fjylTpmDx4sWws7OTOjRqJyorKxEcHAx/f3/ExcXB2toavr6+mDNnDtTV1aUOj4hIiWsSEBERERERtUf29va4fPkybGxs4ODgADc3N2RmZkodVruSnZ0NT09PjB8/HlZWVvjzzz+ZIHiMDA0NsWbNGty+fRuBgYHIyMjA+PHjIZfLsWbNGqSkpEgdIj2H6urqEBkZCW9vb5iYmMDDwwPm5uaIjo5GQkIC5s2bxwQBEbU5HElARERERETUzv34449Yvnw5cnJysGzZMnzwwQfQ1taWOqznVnl5Ob744gts3LgR+vr62LBhA2bPni11WO1CfHw89u7di8OHDyM7OxvW1tZwdnaGs7MzevfuLXV49IwSBAG//vorgoODcejQIWRlZcHS0hLOzs5wc3NDt27dpA6RiKgpnG6IiIiIiIiIgJqaGgQEBGD16tVQV1fHwoUL4evry86tx6i4uBh79uzB5s2bUVhYCD8/P6xYsYILlkqgrq4OsbGxOHToEIKDg5GTk4M+ffrg1VdfxaRJk2Bvbw9NTU2pw6Q27N69ezh79izOnDmD0NBQZGRkwMzMDDNnzsS8efMgl8ulDpGIqLmYJCAiIiIiIqL/yc/Px7Zt2+Dv74+ysjK4ubnBx8eHHV7/wPXr1+Hv74/vvvsOGhoa8PLywrvvvgsjIyOpQyPcT5BFREQgLCwMYWFhSEpKQufOnfHKK6/A0dER48aNg1wuh6oqZ2xuzyorK3Hx4kWEh4fj5MmTiIuLg4qKCkaPHg1HR0c4OTnB0tJS6jCJiFqDSQIiIiIiIiJqqLy8HLt378aXX36JmzdvYuTIkZg/fz6cnZ2hp6cndXhtXklJCQ4fPozdu3cjJiYGJiYmePfdd+Hu7g4dHR2pw6MmpKenIywsDKdOncLZs2dRXFwMfX19jB49GjY2NrC1tcXLL7+Mjh07Sh0qPUF3795FbGwsoqOjERMTg/j4eFRVVaFXr15wcHCAo6MjJkyYwL+HRPQ8YJKAiIiIiIiIHq6urg7h4eHYs2cPjh49CgCYNGkSpkyZAicnJ8hkMokjbDuKi4sRFhaGo0eP4vjx46ipqcGbb74JNzc32NvbQ01NTeoQqYUUCgUSExMRExODmJgYREdHIzMzEx06dIC1tTWGDBkCKysrDBkyBAMHDmTi4Bl17949/P777+IWHx+PlJQUqKqqon///rC1tYWNjQ1sbGxgZmYmdbhERI8bkwRERERERETUPEVFRQgODsbhw4cRGRkJALCzs8PkyZPxyiuvoH///tIGKIGUlBSEh4fjp59+QkREBBQKBcaOHYvp06fDxcUF+vr6UodIj9mtW7cQHR2NCxcu4Pfff0diYiJKS0uhrq4OuVwOa2trWFlZoX///rCwsECvXr04VVEbUVVVhevXryM5ORlXr14VkwLp6ekAgG7dusHa2hrW1tYYNWoUbGxsmAglovaASQIiIiIiIiJqucLCQpw8eRIhISE4deoUioqKYGxsjPHjx8POzg5jxoyBhYXFc/X2fF1dHVJSUhAdHY3IyEhERETgr7/+gra2NhwcHPDmm29i4sSJMDAwkDpUeorq6upw48aNem+iJyYmIicnBwCgpaUFCwsL9OvXDy+99BJeeuklvPjii+jduze6dOkicfTPH4VCgaysLKSlpSElJQUpKSlISkpCSkoKbt26BYVCATU1NZiZmYkJHWVioGvXrlKHT0QkBSYJiIiIiIiI6J9RKBRISEhAREQEIiMjERUVhdLSUmhra8Pa2hpDhw7F0KFDYWlpiX79+kFTU1PqkB+puroaN27cQGJiIi5evIj4+HgkJCSgpKQEnTt3hq2tLezs7GBnZ4dhw4ZBXV1d6pCpjSkoKKjXQZ2SkoLk5GSkpqaipqYGANC5c2f07t1b3ExNTWFqaoqePXvCxMQERkZGz0R7eZpKS0uRmZmJ7OxspKenIy0tDenp6bh16xbS09Nx584d8fnq6OjAwsICFhYWkMvl6Nevn7jP50pEJGKSgIiIiIiIiB6v2tpa/Pnnn4iPjxc72C9duoTq6mqoqanB1NRUfKv6xRdfFDtEu3fvDmNj46cWZ25uLrKyspCRkYE7d+7gxo0bSE5OxrVr15CWlgaFQgENDQ0MGjQIQ4cOxbBhwzB06FAMHjwYGhoaTy1Oer7U1NQgPT29Xsf2rVu3xM7urKwsKBQKsb6+vj66du0KY2NjdO/eHUZGRujWrRu6dOkCfX39BtuztDC2IAgoKChosN27dw+5ubnIzc1FZmYmcnNzkZ2djezsbJSXl4vnd+zYUUysKJMsyp9mZmbo3r27hJ+OiOiZwSQBERERERERPXnV1dViB/y1a9eQnJyMlJQUpKamIj8/X6ynqamJbt26wcjICDKZTNz09fUhk8mgqqpab45wmUwGFRUVCIKAwsJC8XhhYaHYAVlYWFhvy8vLQ2ZmJqqqqsT6+vr66Nu3r/iW8YPTw/CNY3qaampqkJWVhaysLDGRlZOTg5ycHPz111/isfz8fJSWljY4X11dXWwzurq66NSpEzQ1NaGnpwcNDQ3o6uqiY8eO0NLSgra2tpjwUtZ7kLLeg0pKSlBbW1vvWGlpqfj2fnl5OaqqqlBcXIyamhoUFRWhqqoK5eXlKC0tRVVVVb122RgDAwMYGRmJCRFjY+MGSZKuXbuiW7durX7OREQkYpKAiIiIiIiIpFVRUYE7d+4gKysLd+7cQWZmJu7evVuvY1/ZqVhbW4uSkhIAaJAY0NPTExeI1dHRETtL/55sMDQ0hImJiTh6oWfPnujUqZMkn53on6itrW30TXxlmykuLhY77YuKilBTU4Pi4mJUVlaioqICxcXF4qiFB39XerDzX+lRyQTl77q6utDQ0ICenh40NTXRqVMnaGtrQ1NTU0z6NTYSggsFExE9dUwSEBERERERERERERG1U8WqUkdARERERERERERERETSYJKAiIiIiIiIiIiIiKidYpKAiIiIiIiIiIiIiKidUgdwSOogiIiIiIiIiIiIiIjoqav4f2watrSKTchGAAAAAElFTkSuQmCC", - "text/plain": [ - "" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "viz = web_analysis_bn.to_graphviz()\n", - "viz.draw('web_analysis.png', prog='dot')\n", - "Image('web_analysis.png')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "832d93dd-4cfa-459a-8e1e-01a66cbee2d9", - "metadata": {}, - "outputs": [], - "source": [ - "cpd_dns_ctrl_failure = TabularCPD('A', 2, [[0.2], [0.8]])" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "id": "13312638-208f-4798-8eae-268fb29a817c", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'DNS VP Failures'" - ] - }, - "execution_count": 49, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "list(web_analysis_bn.nodes)[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 52, - "id": "57082d9d-01d0-43ec-91af-2a54e85ae0a2", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'DNS VP Failures'" - ] - }, - "execution_count": 52, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "child = list(web_analysis_bn.nodes)[0]\n", - "child" - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "id": "fb31f020-28d9-4f3c-9d72-1ed687623fea", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['DNS Ctrl Failures']" - ] - }, - "execution_count": 53, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "web_analysis_bn.get_parents(child)" - ] - }, - { - "cell_type": "code", - "execution_count": 67, - "id": "b3cad79a-bce8-4efb-b811-80f6458fb16c", - "metadata": {}, - "outputs": [], - "source": [ - "def print_boilerplate():\n", - " cpd_list = []\n", - " for x in list(web_analysis_bn.nodes):\n", - " var_name = x.lower().replace(' ', '_')\n", - " var_name = f\"cpd_{var_name}\"\n", - " s = f\"{var_name} = TabularCPD('{x}', variable_card=2, values=[\\n\"\n", - " parents = web_analysis_bn.get_parents(x)\n", - " padding = \" \"*(int(len(s)/2))\n", - " for _ in range(2):\n", - " s += padding + \"[\"\n", - " s += \",\".join(\"0.\" for x in range(len(parents)))\n", - " s += \"],\\n\"\n", - " s += padding + f\"],\\n\" \n", - " s += padding + f\" # parents={parents}\\n\"\n", - " s += padding + f\"evidence={parents},\\n\"\n", - " s += padding + f\"evidence_card=[],\\n\"\n", - " s += padding + \"state_names = {\\n\"\n", - " for p in parents:\n", - " s += padding + f\"'{p}': [],\\n\"\n", - " s += \"}\\n\"\n", - " s += padding + \")\"\n", - " print(s)\n", - " cpd_list.append(var_name)" - ] - }, - { - "cell_type": "code", - "execution_count": 68, - "id": "509c45ee-b22d-461a-998b-a701c5090580", - "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'TabularCPD' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[68], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m cpd_dns_ctrl_failures \u001b[38;5;241m=\u001b[39m \u001b[43mTabularCPD\u001b[49m(\n\u001b[1;32m 2\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDNS Ctrl Failures\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 3\u001b[0m variable_card\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m3\u001b[39m,\n\u001b[1;32m 4\u001b[0m values\u001b[38;5;241m=\u001b[39m[\n\u001b[1;32m 5\u001b[0m [\u001b[38;5;241m0.8\u001b[39m],\n\u001b[1;32m 6\u001b[0m [\u001b[38;5;241m0.15\u001b[39m],\n\u001b[1;32m 7\u001b[0m [\u001b[38;5;241m0.05\u001b[39m],\n\u001b[1;32m 8\u001b[0m ],\n\u001b[1;32m 9\u001b[0m state_names\u001b[38;5;241m=\u001b[39m{\n\u001b[1;32m 10\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDNS Ctrl Failures\u001b[39m\u001b[38;5;124m\"\u001b[39m: [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnone\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnxdomain\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mserver_failure\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m 11\u001b[0m },\n\u001b[1;32m 12\u001b[0m )\n\u001b[1;32m 13\u001b[0m cpd_dns_vp_failures \u001b[38;5;241m=\u001b[39m TabularCPD(\n\u001b[1;32m 14\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDNS VP Failures\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 15\u001b[0m variable_card\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m3\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 26\u001b[0m },\n\u001b[1;32m 27\u001b[0m )\n\u001b[1;32m 28\u001b[0m cpd_resolver_config \u001b[38;5;241m=\u001b[39m TabularCPD(\n\u001b[1;32m 29\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mResolver config\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 30\u001b[0m variable_card\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 37\u001b[0m },\n\u001b[1;32m 38\u001b[0m )\n", - "\u001b[0;31mNameError\u001b[0m: name 'TabularCPD' is not defined" - ] - } - ], - "source": [ - "cpd_dns_ctrl_failures = TabularCPD(\n", - " \"DNS Ctrl Failures\",\n", - " variable_card=3,\n", - " values=[\n", - " [0.8],\n", - " [0.15],\n", - " [0.05],\n", - " ],\n", - " state_names={\n", - " \"DNS Ctrl Failures\": [\"none\", \"nxdomain\", \"server_failure\"]\n", - " },\n", - ")\n", - "cpd_dns_vp_failures = TabularCPD(\n", - " \"DNS VP Failures\",\n", - " variable_card=3,\n", - " values=[\n", - " [0.8],\n", - " [0.15],\n", - " [0.05],\n", - " ],\n", - " evidence=[\"DNS Ctrl Failures\"],\n", - " evidence_card=[3],\n", - " state_names={\n", - " \"DNS VP Failures\": [\"none\", \"nxdomain\", \"server_failure\"],\n", - " \"DNS Ctrl Failures\": [\"none\", \"nxdomain\", \"server_failure\"],\n", - " },\n", - ")\n", - "cpd_resolver_config = TabularCPD(\n", - " \"Resolver config\",\n", - " variable_card=3,\n", - " values=[\n", - " # These values were estimated based on a query against the OONI dataset from 2024-01-01 to 2024-08-10\n", - " # with this query:\n", - " # -- ## quad_resolvers\n", - " # -- 15169, # Google LLC\n", - " # -- 13335, # Cloudflare Inc\n", - " # -- 42, # WoodyNet, Inc. | quad9\n", - " # -- 36692, # Cisco OpenDNS, LLC\t\n", - " # SELECT \n", - " # CountIf(resolver_asn IN (15169, 13335, 42, 36692)) as quad_external_count,\n", - " # CountIf( \n", - " # (resolver_asn = probe_asn OR resolver_as_cc = probe_cc) \n", - " # AND NOT (resolver_asn IN (15169, 13335, 42, 36692)) \n", - " # ) as provider_vp_consistent,\n", - " # CountIf( \n", - " # (resolver_asn != probe_asn AND resolver_as_cc != probe_cc) \n", - " # AND NOT (resolver_asn IN (15169, 13335, 42, 36692)) \n", - " # ) as provider_non_vp_consistent,\n", - " # COUNT() as total_count\n", - " # FROM obs_web\n", - " # WHERE \n", - " # measurement_start_time > '2024-01-01' \n", - " # AND measurement_start_time < '2024-08-10'\n", - " [0.56],\n", - " [0.08],\n", - " [0.36],\n", - " ],\n", - " state_names={\n", - " # provider_vp_consistent: means the resolver is consistent with the country and/or AS of the probe and is \n", - " # not a quad (eg. 8.8.8.8, 9.9.9.9, etc.) or third party resolver\n", - " # provider_non_vp_consistent: means the resolver is not a quad resolver, \n", - " # but is not consistent with the metadata of the probe\n", - " # quad_external: means the resolver is something like quad9, google, cloudflare, etc.\n", - " \"Resolver config\": [\"provider_vp_consistent\", \"provider_non_vp_consistent\", \"quad_external\"]\n", - " },\n", - ")\n", - "cpd_dns_answer_meta = TabularCPD(\n", - " \"DNS Answer Meta\",\n", - " variable_card=6,\n", - " # These values were calculated using the following query.\n", - " # WITH\n", - " # (dns_answer IS NOT NULL \n", - " # AND ip_asn IN (13335, 209242, 20940, 9002, 16625, 63949, 16509, 14618, 15169, 396982, 54113, 8075, 8068)\n", - " # ) as is_cloud_provider\n", - " # SELECT \n", - " # CountIf(is_cloud_provider) as cloud_provider,\n", - " # CountIf(\n", - " # dns_answer IS NOT NULL AND ip_is_bogon AND NOT is_cloud_provider\n", - " # ) as answer_is_bogon,\n", - " # CountIf(\n", - " # dns_answer IS NOT NULL AND ip_asn = probe_asn AND NOT is_cloud_provider\n", - " # ) as answer_matches_probe_asn,\n", - " # CountIf(\n", - " # dns_answer IS NOT NULL AND (ip_cc = probe_cc AND NOT ip_asn = probe_asn AND NOT is_cloud_provider)\n", - " # ) as answer_matches_probe_cc,\n", - " # CountIf(\n", - " # dns_answer IS NOT NULL AND (ip_cc != probe_cc AND ip_asn != probe_asn AND NOT ip_is_bogon AND NOT is_cloud_provider)\n", - " # ) as answer_ok,\n", - " # COUNTIf(dns_failure IS NOT NULL) as dns_failure,\n", - " # COUNT() as total_count\n", - " # FROM obs_web\n", - " # WHERE \n", - " # test_name = 'web_connectivity'\n", - " # AND measurement_start_time > '2024-01-01' \n", - " # AND measurement_start_time < '2024-08-10'\n", - " ## The list of cloud providers was manually curated\n", - " # CLOUD_PROVIDERS_ASNS = [\n", - " # 13335, # Cloudflare: https://www.peeringdb.com/net/4224\n", - " # 209242, #\tCloudflare London, LLC\t\n", - " # 20940, # Akamai: https://www.peeringdb.com/net/2\n", - " # 9002, # Akamai RETN\n", - " # 16625, # Akamai Technologies, Inc.\t\n", - " # 63949, # Akamai Technologies, Inc.\t\n", - " # 16509, #\tAmazon.com, Inc.\n", - " # 14618, #\tAmazon.com, Inc.\t\n", - " # 15169, #\tGoogle LLC\n", - " # 396982, # Google Cloud: https://www.peeringdb.com/net/30878\n", - " # 54113, #\tFastly, Inc\n", - " # 8075, # Microsoft Corporation\n", - " # 8068, #\tMicrosoft Corporation\n", - " # ]\n", - " values=[\n", - " [0.034306],\n", - " [0.003745],\n", - " [0.004537],\n", - " [0.060217],\n", - " [0.19626],\n", - " [0.700935]\n", - " ],\n", - " # parents={parents}\n", - " evidence=[],\n", - " evidence_card=[],\n", - " state_names={\n", - " \"DNS Answer Meta\": [\n", - " \"answer_failure\", \n", - " \"answer_is_bogon\", \n", - " \"answer_matches_probe_asn\", \n", - " \"answer_matches_probe_cc\",\n", - " \"answer_is_cloud_provider\",\n", - " \"answer_ok\"\n", - " ],\n", - " },\n", - ")\n", - "cpd_dns_tls_consistency = TabularCPD(\n", - " \"DNS TLS Consistency\",\n", - " variable_card=2,\n", - " values=[\n", - " [],\n", - " [],\n", - " ],\n", - " # parents={parents}\n", - " evidence=[],\n", - " evidence_card=[],\n", - " state_names={\n", - " \"DNS TLS Consistency\": [\"\"]\n", - " },\n", - ")\n", - "cpd_dns_consistency = TabularCPD(\n", - " \"DNS Consistency\",\n", - " variable_card=2,\n", - " values=[\n", - " [0.0, 0.0, 0.0],\n", - " [0.0, 0.0, 0.0],\n", - " ],\n", - " # parents={parents}\n", - " evidence=[\"DNS Answer Meta\", \"DNS TLS Consistency\", \"Resolver Config\"],\n", - " evidence_card=[],\n", - " state_names={\n", - " \"DNS Consistency\": [],\n", - " \"DNS Answer Meta\": [\n", - " \"answer_failure\", \n", - " \"answer_is_bogon\", \n", - " \"answer_matches_probe_asn\", \n", - " \"answer_matches_probe_cc\",\n", - " \"answer_is_cloud_provider\",\n", - " \"answer_ok\"\n", - " ],\n", - " \"DNS TLS Consistency\": [],\n", - " \"Resolver config\": [\"provider_vp_consistent\", \"provider_non_vp_consistent\", \"quad_external\"]\n", - " },\n", - ")\n", - "cpd_dns_outcome = TabularCPD(\n", - " \"DNS Outcome\",\n", - " variable_card=2,\n", - " values=[\n", - " [0.0, 0.0, 0.0, 0.0, 0.0],\n", - " [0.0, 0.0, 0.0, 0.0, 0.0],\n", - " ],\n", - " # parents={parents}\n", - " evidence=[\n", - " \"DNS VP Failures\",\n", - " \"DNS Ctrl Failures\",\n", - " \"Resolver config\",\n", - " \"DNS Consistency\",\n", - " \"DNS VP Got Answer\",\n", - " ],\n", - " evidence_card=[],\n", - " state_names={\n", - " \"DNS VP Failures\": [\"none\", \"nxdomain\", \"server_failure\"],\n", - " \"DNS Ctrl Failures\": [\"none\", \"nxdomain\", \"server_failure\"],\n", - " \"Resolver config\": [\"provider_vp_consistent\", \"provider_non_vp_consistent\", \"quad_external\"]\n", - " \"DNS Consistency\": [],\n", - " \"DNS VP Got Answer\": [],\n", - " },\n", - ")\n", - "cpd_vp_state = TabularCPD(\n", - " \"VP State\",\n", - " variable_card=2,\n", - " values=[\n", - " [0.0, 0.0, 0.0, 0.0],\n", - " [0.0, 0.0, 0.0, 0.0],\n", - " ],\n", - " # parents={parents}\n", - " evidence=[\"DNS VP Failures\", \"Resolver Config\", \"TLS VP Failures\", \"HTTP Failures\"],\n", - " evidence_card=[],\n", - " state_names={\n", - " \"DNS VP Failures\": [],\n", - " \"Resolver Config\": [],\n", - " \"TLS VP Failures\": [],\n", - " \"HTTP Failures\": [],\n", - " },\n", - ")\n", - "cpd_dns_vp_got_answer = TabularCPD(\n", - " \"DNS VP Got Answer\",\n", - " variable_card=2,\n", - " values=[\n", - " [],\n", - " [],\n", - " ],\n", - " # parents={parents}\n", - " evidence=[],\n", - " evidence_card=[],\n", - " state_names={},\n", - ")\n", - "cpd_tcp_vp_failures = TabularCPD(\n", - " \"TCP VP Failures\",\n", - " variable_card=2,\n", - " values=[\n", - " [0.0],\n", - " [0.0],\n", - " ],\n", - " # parents={parents}\n", - " evidence=[\"DNS Outcome\"],\n", - " evidence_card=[],\n", - " state_names={\n", - " \"DNS Outcome\": [],\n", - " },\n", - ")\n", - "cpd_tcp_outcome = TabularCPD(\n", - " \"TCP Outcome\",\n", - " variable_card=2,\n", - " values=[\n", - " [0.0, 0.0],\n", - " [0.0, 0.0],\n", - " ],\n", - " # parents={parents}\n", - " evidence=[\"TCP VP Failures\", \"TCP Ctrl Failures\"],\n", - " evidence_card=[],\n", - " state_names={\n", - " \"TCP VP Failures\": [],\n", - " \"TCP Ctrl Failures\": [],\n", - " },\n", - ")\n", - "cpd_tcp_ctrl_failures = TabularCPD(\n", - " \"TCP Ctrl Failures\",\n", - " variable_card=2,\n", - " values=[\n", - " [],\n", - " [],\n", - " ],\n", - " # parents={parents}\n", - " evidence=[],\n", - " evidence_card=[],\n", - " state_names={},\n", - ")\n", - "cpd_tls_vp_failures = TabularCPD(\n", - " \"TLS VP Failures\",\n", - " variable_card=2,\n", - " values=[\n", - " [0.0],\n", - " [0.0],\n", - " ],\n", - " # parents={parents}\n", - " evidence=[\"TCP Outcome\"],\n", - " evidence_card=[],\n", - " state_names={\n", - " \"TCP Outcome\": [],\n", - " },\n", - ")\n", - "cpd_http_failure = TabularCPD(\n", - " \"HTTP Failure\",\n", - " variable_card=2,\n", - " values=[\n", - " [0.0],\n", - " [0.0],\n", - " ],\n", - " # parents={parents}\n", - " evidence=[\"TCP Outcome\"],\n", - " evidence_card=[],\n", - " state_names={\n", - " \"TCP Outcome\": [],\n", - " },\n", - ")\n", - "cpd_tls_outcome = TabularCPD(\n", - " \"TLS Outcome\",\n", - " variable_card=2,\n", - " values=[\n", - " [0.0, 0.0],\n", - " [0.0, 0.0],\n", - " ],\n", - " # parents={parents}\n", - " evidence=[\"TLS VP Failures\", \"TLS Ctrl Failures\"],\n", - " evidence_card=[],\n", - " state_names={\n", - " \"TLS VP Failures\": [],\n", - " \"TLS Ctrl Failures\": [],\n", - " },\n", - ")\n", - "cpd_tls_ctrl_failures = TabularCPD(\n", - " \"TLS Ctrl Failures\",\n", - " variable_card=2,\n", - " values=[\n", - " [],\n", - " [],\n", - " ],\n", - " # parents={parents}\n", - " evidence=[],\n", - " evidence_card=[],\n", - " state_names={},\n", - ")\n", - "cpd_http_failures = TabularCPD(\n", - " \"HTTP Failures\",\n", - " variable_card=2,\n", - " values=[\n", - " [0.0],\n", - " [0.0],\n", - " ],\n", - " # parents={parents}\n", - " evidence=[\"TLS Outcome\"],\n", - " evidence_card=[],\n", - " state_names={\n", - " \"TLS Outcome\": [],\n", - " },\n", - ")\n", - "cpd_http_outcome = TabularCPD(\n", - " \"HTTP Outcome\",\n", - " variable_card=2,\n", - " values=[\n", - " [0.0, 0.0],\n", - " [0.0, 0.0],\n", - " ],\n", - " # parents={parents}\n", - " evidence=[\"HTTP Failures\", \"HTTP Response is plaintext\"],\n", - " evidence_card=[],\n", - " state_names={\n", - " \"HTTP Failures\": [],\n", - " \"HTTP Response is plaintext\": [],\n", - " },\n", - ")\n", - "cpd_http_body_consistency = TabularCPD(\n", - " \"HTTP Body Consistency\",\n", - " variable_card=2,\n", - " values=[\n", - " [],\n", - " [],\n", - " ],\n", - " # parents={parents}\n", - " evidence=[],\n", - " evidence_card=[],\n", - " state_names={},\n", - ")\n", - "cpd_http_response_is_plaintext = TabularCPD(\n", - " \"HTTP Response is plaintext\",\n", - " variable_card=2,\n", - " values=[\n", - " [0.0],\n", - " [0.0],\n", - " ],\n", - " # parents={parents}\n", - " evidence=[\"HTTP Body Consistency\"],\n", - " evidence_card=[],\n", - " state_names={\n", - " \"HTTP Body Consistency\": [],\n", - " },\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "85d58bf9-eb93-48fb-96ba-927657cfd1ef", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6eebd10f-58da-41a8-b2ef-520a1733607c", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "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": "3.12.5" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/notebooks/web-analysis-bn.ipynb b/notebooks/web-analysis-bn.ipynb new file mode 120000 index 00000000..8c60223f --- /dev/null +++ b/notebooks/web-analysis-bn.ipynb @@ -0,0 +1 @@ +../oonipipeline/notebooks/web-analysis-bn.ipynb \ No newline at end of file diff --git a/notebooks/web-analysis-full.bif b/notebooks/web-analysis-full.bif index 4eb90444..8255ee41 100644 --- a/notebooks/web-analysis-full.bif +++ b/notebooks/web-analysis-full.bif @@ -129,8 +129,8 @@ probability ( TLS Outcome | DNS Answer Consistency, TLS VP Result ) { ( consistent, bad_certificate ) 0.95, 0.01, 0.03, 0.01; ( consistent, connection_reset_after_ch ) 0.9, 0.01, 0.07, 0.02; ( consistent, timeout_after_ch ) 0.85, 0.01, 0.09, 0.05; - ( consistent, timeout ) 0.01, 0.08, 0.01, 0.9; - ( consistent, connection_reset ) 0.07, 0.01, 0.07, 0.85; + ( consistent, timeout ) 0.55, 0.02, 0.4, 0.03; + ( consistent, connection_reset ) 0.65, 0.01, 0.25, 0.09; ( consistent, other ) 0.07, 0.01, 0.07, 0.85; ( consistent, down ) 0.07, 0.01, 0.07, 0.85; ( inconsistent, none ) 0.02, 0.01, 0.05, 0.92; diff --git a/notebooks/web-analysis.bif b/notebooks/web-analysis.bif index cccf8eb2..f537addd 100644 --- a/notebooks/web-analysis.bif +++ b/notebooks/web-analysis.bif @@ -1,98 +1,69 @@ -dns_ground_truth_nxdomain_count -dns_ground_truth_failure_count -dns_ground_truth_ok_count -dns_ground_truth_ok_cc_asn_count -dns_ground_truth_failure_cc_asn_count -dns_ground_truth_nxdomain_cc_asn_count +network unknown { +} +variable DNS Answer Meta { + type discrete [ 7 ] { answer_failure_nxdomain, answer_failure_other, answer_is_bogon, answer_matches_probe_asn, answer_matches_probe_cc, answer_is_cloud_provider, answer_ok }; +} +variable DNS Consistency { + type discrete [ 2 ] { consistent, inconsistent }; +} +variable DNS Ctrl Failure { + type discrete [ 3 ] { none, nxdomain, server_failure }; +} +variable DNS Outcome { + type discrete [ 3 ] { blocked, ok, down }; +} +variable DNS TLS Consistency { + type discrete [ 3 ] { tls_consistent, tls_inconsistent, tls_connection_failed }; +} +probability ( DNS Answer Meta | DNS Ctrl Failure ) { + ( none ) 0.0238, 0.01, 0.003745, 0.004537, 0.060217, 0.19626, 0.700935; + ( nxdomain ) 0.9, 0.03, 0.014, 0.014, 0.014, 0.014, 0.014; + ( server_failure ) 0.015, 0.91, 0.015, 0.015, 0.015, 0.015, 0.015; -dns_consistency_system_answers -dns_consistency_system_success -dns_consistency_system_failure -dns_consistency_system_answer_count -dns_consistency_system_is_answer_tls_consistent -dns_consistency_system_is_answer_tls_inconsistent -dns_consistency_system_is_answer_ip_in_trusted_answers -dns_consistency_system_is_answer_asn_in_trusted_answers -dns_consistency_system_is_answer_asorg_in_trusted_answers -dns_consistency_system_is_answer_cloud_provider -dns_consistency_system_is_answer_probe_asn_match -dns_consistency_system_is_answer_probe_cc_match -dns_consistency_system_is_answer_bogon -dns_consistency_system_answer_fp_name -dns_consistency_system_answer_fp_scope -dns_consistency_system_is_answer_fp_match -dns_consistency_system_is_answer_fp_country_consistent -dns_consistency_system_is_answer_fp_false_positive -dns_consistency_system_is_resolver_probe_asn_match -dns_consistency_system_is_resolver_probe_cc_match -dns_consistency_system_answer_ip_ground_truth_asn_count -dns_consistency_system_answer_asn_ground_truth_asn_count -dns_consistency_other_answers -dns_consistency_other_success -dns_consistency_other_failure -dns_consistency_other_answer_count -dns_consistency_other_is_answer_tls_consistent -dns_consistency_other_is_answer_tls_inconsistent -dns_consistency_other_is_answer_ip_in_trusted_answers -dns_consistency_other_is_answer_asn_in_trusted_answers -dns_consistency_other_is_answer_asorg_in_trusted_answers -dns_consistency_other_is_answer_cloud_provider -dns_consistency_other_is_answer_probe_asn_match -dns_consistency_other_is_answer_probe_cc_match -dns_consistency_other_is_answer_bogon -dns_consistency_other_answer_fp_name -dns_consistency_other_answer_fp_scope -dns_consistency_other_is_answer_fp_match -dns_consistency_other_is_answer_fp_country_consistent -dns_consistency_other_is_answer_fp_false_positive -dns_consistency_other_is_resolver_probe_asn_match -dns_consistency_other_is_resolver_probe_cc_match -dns_consistency_other_answer_ip_ground_truth_asn_count -dns_consistency_other_answer_asn_ground_truth_asn_count +} +probability ( DNS Consistency | DNS Answer Meta, DNS TLS Consistency ) { + ( answer_failure_nxdomain, tls_consistent ) 0.01, 0.99; + ( answer_failure_nxdomain, tls_inconsistent ) 0.001, 0.999; + ( answer_failure_nxdomain, tls_connection_failed ) 0.001, 0.999; + ( answer_failure_other, tls_consistent ) 0.01, 0.99; + ( answer_failure_other, tls_inconsistent ) 0.001, 0.999; + ( answer_failure_other, tls_connection_failed ) 0.001, 0.999; + ( answer_is_bogon, tls_consistent ) 0.03, 0.97; + ( answer_is_bogon, tls_inconsistent ) 0.01, 0.99; + ( answer_is_bogon, tls_connection_failed ) 0.01, 0.99; + ( answer_matches_probe_asn, tls_consistent ) 0.999, 0.001; + ( answer_matches_probe_asn, tls_inconsistent ) 0.001, 0.999; + ( answer_matches_probe_asn, tls_connection_failed ) 0.3, 0.7; + ( answer_matches_probe_cc, tls_consistent ) 0.999, 0.001; + ( answer_matches_probe_cc, tls_inconsistent ) 0.001, 0.999; + ( answer_matches_probe_cc, tls_connection_failed ) 0.2, 0.8; + ( answer_is_cloud_provider, tls_consistent ) 0.98, 0.02; + ( answer_is_cloud_provider, tls_inconsistent ) 0.001, 0.999; + ( answer_is_cloud_provider, tls_connection_failed ) 0.1, 0.9; + ( answer_ok, tls_consistent ) 0.9999, 0.0001; + ( answer_ok, tls_inconsistent ) 0.01, 0.99; + ( answer_ok, tls_connection_failed ) 0.2, 0.8; -tls_success -tls_failure -tls_is_tls_certificate_valid -tls_is_tls_certificate_invalid -tls_handshake_read_count -tls_handshake_write_count -tls_handshake_read_bytes -tls_handshake_write_bytes -tls_handshake_time -tls_ground_truth_failure_count -tls_ground_truth_failure_asn_cc_count -tls_ground_truth_ok_count -tls_ground_truth_ok_asn_cc_count -tls_ground_truth_trusted_failure_count -tls_ground_truth_trusted_ok_count +} +probability ( DNS Ctrl Failure ) { + table 0.994, 0.004, 0.002 ; +} +probability ( DNS Outcome | DNS Ctrl Failure, DNS Consistency ) { + ( none, consistent ) 0.1, 0.9, 0.0; + ( none, inconsistent ) 0.9, 0.1, 0.0; + ( nxdomain, consistent ) 0.2, 0.0, 0.8; + ( nxdomain, inconsistent ) 0.8, 0.0, 0.2; + ( server_failure, consistent ) 0.1, 0.8, 0.1; + ( server_failure, inconsistent ) 0.7, 0.1, 0.2; -tcp_address -tcp_success tcp_failure -tcp_ground_truth_failure_count -tcp_ground_truth_failure_asn_cc_count -tcp_ground_truth_ok_count -tcp_ground_truth_ok_asn_cc_count -tcp_ground_truth_trusted_failure_count -tcp_ground_truth_trusted_ok_count +} +probability ( DNS TLS Consistency | DNS Answer Meta ) { + ( answer_failure_nxdomain ) 0.96, 0.02, 0.02; + ( answer_failure_other ) 0.96, 0.02, 0.02; + ( answer_is_bogon ) 0.0, 0.02, 0.98; + ( answer_matches_probe_asn ) 0.05, 0.8, 0.15; + ( answer_matches_probe_cc ) 0.05, 0.8, 0.15; + ( answer_is_cloud_provider ) 0.9, 0.08, 0.02; + ( answer_ok ) 0.94, 0.04, 0.02; -http_success -http_failure -http_is_http_request_encrypted - -http_response_body_proportion -http_response_body_length -http_response_status_code - -http_ground_truth_failure_count -http_ground_truth_failure_asn_cc_count -http_ground_truth_ok_count -http_ground_truth_ok_asn_cc_count -http_ground_truth_trusted_ok_count -http_ground_truth_trusted_failure_count -http_ground_truth_body_length - -http_fp_name -http_fp_scope -http_is_http_fp_match -http_is_http_fp_country_consistent -http_is_http_fp_false_positive \ No newline at end of file +} diff --git a/notebooks/web_analysis_complex.png b/notebooks/web_analysis_complex.png new file mode 100644 index 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"metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "from tqdm.notebook import tqdm\n", + "from IPython.display import Image\n", + "from pgmpy.models import BayesianNetwork\n", + "from pgmpy.factors.discrete import TabularCPD\n", + "tqdm.pandas()" + ] + }, + { + "cell_type": "code", + "execution_count": 92, + "id": "3f8fc6f9-9786-4013-8802-359432fb01a2", + "metadata": {}, + "outputs": [], + "source": [ + "dns_analysis_bn = BayesianNetwork([\n", + " ('answer_matches_probe_cc', 'answer_is_blockpage'),\n", + " ('answer_matches_probe_asn', 'answer_is_blockpage'),\n", + " ('answer_contains_unreachable_ip', 'answer_is_blockpage'),\n", + " ('answer_contains_bogon', 'answer_is_blockpage'),\n", + " ('answer_is_blockpage', 'contains_tls_consistent_answer'),\n", + " ('answer_count', 'answer_is_blockpage'),\n", + " ('answer_is_cloud_provider', 'answer_is_blockpage'),\n", + " #('contains_tls_consistent_answer', 'dns_outcome'),\n", + " #('bogon_present_in_ctrl_and_exp', 'dns_outcome'),\n", + "\n", + " #('dns_consistent_failure', 'dns_failure_outcome'),\n", + " #('dns_exp_is_nxdomain', 'dns_failure_outcome'),\n", + " #('dns_failure_outcome', 'dns_outcome')\n", + "])" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "id": "fcf3aa05-a59d-4e5a-af62-9805f413bfcf", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "execution_count": 95, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "viz = dns_analysis_bn.to_graphviz()\n", + "viz.draw('dns_analysis_bn.png', prog='dot')\n", + "Image('dns_analysis_bn.png')" + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "id": "1ee80ef0-9056-4c9d-b650-3231387a596b", + "metadata": {}, + "outputs": [], + "source": [ + "samples = pd.read_csv('dns_analysis_samples_1M.csv.gz', usecols=[\n", + " 'answer_matches_probe_cc',\n", + " 'answer_matches_probe_asn',\n", + " 'answer_contains_unreachable_ip',\n", + " 'answer_contains_bogon',\n", + " 'answer_is_blockpage', \n", + " 'contains_tls_consistent_answer',\n", + " 'answer_is_cloud_provider',\n", + " 'answer_count',\n", + "])" + ] + }, + { + "cell_type": "code", + "execution_count": 166, + "id": "bba49cb2-7a0b-4618-9c1d-714803780d74", + "metadata": {}, + "outputs": [], + "source": [ + "#samples_full = pd.read_csv('dns_analysis_samples_1M.csv.gz')\n", + "samples_extra = pd.read_csv('dns_analysis_samples_extra_1M.csv.gz')" + ] + }, + { + "cell_type": "code", + "execution_count": 171, + "id": "dffd0e2f-39ef-42e5-a545-084c2b354c28", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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    answer_counttls_consistenttls_inconsistentcontains_tls_consistent_answeranswer_ip_in_trusted_answersanswer_asn_in_trusted_answersanswer_asorg_in_trusted_answersanswer_matches_probe_asnanswer_matches_probe_ccanswer_contains_bogonanswer_is_cloud_provideranswer_is_blockpageanswer_contains_unreachable_ip
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    ..........................................
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    1000000 rows × 13 columns

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    " + ], + "text/plain": [ + " answer_count tls_consistent tls_inconsistent \\\n", + "0 med 1 0 \n", + "1 med 1 0 \n", + "2 med 1 0 \n", + "3 low 1 0 \n", + "4 med 1 0 \n", + "... ... ... ... \n", + "999995 med 0 0 \n", + "999996 high 0 0 \n", + "999997 med 0 0 \n", + "999998 med 0 0 \n", + "999999 low 1 0 \n", + "\n", + " contains_tls_consistent_answer answer_ip_in_trusted_answers \\\n", + "0 1.0 0 \n", + "1 1.0 1 \n", + "2 1.0 0 \n", + "3 1.0 0 \n", + "4 1.0 0 \n", + "... ... ... \n", + "999995 NaN 0 \n", + "999996 NaN 0 \n", + "999997 NaN 0 \n", + "999998 NaN 1 \n", + "999999 1.0 0 \n", + "\n", + " answer_asn_in_trusted_answers answer_asorg_in_trusted_answers \\\n", + "0 1 0 \n", + "1 1 0 \n", + "2 0 0 \n", + "3 0 0 \n", + "4 1 1 \n", + "... ... ... \n", + "999995 0 0 \n", + "999996 0 0 \n", + "999997 0 0 \n", + "999998 1 1 \n", + "999999 0 0 \n", + "\n", + " answer_matches_probe_asn answer_matches_probe_cc \\\n", + "0 0 0 \n", + "1 0 1 \n", + "2 0 1 \n", + "3 0 0 \n", + "4 0 0 \n", + "... ... ... \n", + "999995 0 1 \n", + "999996 0 0 \n", + "999997 0 0 \n", + "999998 0 0 \n", + "999999 0 0 \n", + "\n", + " answer_contains_bogon answer_is_cloud_provider answer_is_blockpage \\\n", + "0 0 1 0 \n", + "1 0 1 0 \n", + "2 0 1 0 \n", + "3 0 0 0 \n", + "4 0 0 0 \n", + "... ... ... ... \n", + "999995 0 0 1 \n", + "999996 0 0 0 \n", + "999997 0 0 0 \n", + "999998 0 1 0 \n", + "999999 0 0 0 \n", + "\n", + " answer_contains_unreachable_ip \n", + "0 0 \n", + "1 0 \n", + "2 0 \n", + "3 0 \n", + "4 0 \n", + "... ... \n", + "999995 0 \n", + "999996 0 \n", + "999997 0 \n", + "999998 0 \n", + "999999 0 \n", + "\n", + "[1000000 rows x 13 columns]" + ] + }, + "execution_count": 183, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "samples_extra_clean" + ] + }, + { + "cell_type": "code", + "execution_count": 164, + "id": "9cb379b3-958b-4a87-85b9-e17d2a736880", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'20240212194929.466091_FI_webconnectivity_a8a12429797483d9'" + ] + }, + "execution_count": 164, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "samples_full.iloc[2007]['measurement_uid']" + ] + }, + { + "cell_type": "code", + "execution_count": 108, + "id": "d5c3bf40-9e7d-4001-8b18-9583f804c6bc", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
    \n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
    answer_countcontains_tls_consistent_answeranswer_matches_probe_asnanswer_matches_probe_ccanswer_contains_bogonanswer_is_cloud_provideranswer_is_blockpageanswer_contains_unreachable_ip
    \n", + "
    " + ], + "text/plain": [ + "Empty DataFrame\n", + "Columns: [answer_count, contains_tls_consistent_answer, answer_matches_probe_asn, answer_matches_probe_cc, answer_contains_bogon, answer_is_cloud_provider, answer_is_blockpage, answer_contains_unreachable_ip]\n", + "Index: []" + ] + }, + "execution_count": 108, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "samples[\n", + " samples['answer_contains_unreachable_ip'] != 0\n", + "]" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "id": "0887dbd4-0625-42d4-964c-486f321e61e8", + "metadata": {}, + "outputs": [], + "source": [ + "from pgmpy.estimators import MaximumLikelihoodEstimator\n", + "mle = MaximumLikelihoodEstimator(model=dns_analysis_bn, data=samples)\n", + "dns_analysis_bn.fit(data=samples, estimator=MaximumLikelihoodEstimator)" + ] + }, + { + "cell_type": "code", + "execution_count": 103, + "id": "49231f4d-62a9-473c-b4a3-f85f1f71fc78", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 106, + "id": "2cecd5e1-6d51-4aaa-afa2-c7144fa69a60", + "metadata": {}, + "outputs": [], + "source": [ + "cdp = dns_analysis_bn.get_cpds('answer_contains_unreachable_ip')" + ] + }, + { + "cell_type": "code", + "execution_count": 107, + "id": "8da3b7bf-740b-4bbd-b3a6-2d272428996f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+-----------------------------------+---+\n", + "| answer_contains_unreachable_ip(0) | 1 |\n", + "+-----------------------------------+---+\n" + ] + } + ], + "source": [ + "print(cdp)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "f67d57d4-9472-47c7-94a7-03eb97c8c4f9", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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samples_extra_clean.copy()[:100]" + ] + }, + { + "cell_type": "code", + "execution_count": 226, + "id": "471912f3-694c-409b-b719-d0d46545cea6", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/art/repos/ooni/data/oonipipeline/.venv/lib/python3.11/site-packages/pgmpy/factors/discrete/DiscreteFactor.py:489: RuntimeWarning: invalid value encountered in divide\n", + " phi.values = phi.values / phi.values.sum()\n", + "/Users/art/repos/ooni/data/oonipipeline/.venv/lib/python3.11/site-packages/pgmpy/factors/discrete/DiscreteFactor.py:489: RuntimeWarning: invalid value encountered in divide\n", + " phi.values = phi.values / phi.values.sum()\n", + "/Users/art/repos/ooni/data/oonipipeline/.venv/lib/python3.11/site-packages/pgmpy/factors/discrete/DiscreteFactor.py:489: RuntimeWarning: invalid value encountered in divide\n", + " phi.values = phi.values / phi.values.sum()\n", + "/Users/art/repos/ooni/data/oonipipeline/.venv/lib/python3.11/site-packages/pgmpy/factors/discrete/DiscreteFactor.py:489: RuntimeWarning: invalid value encountered in divide\n", + " phi.values = phi.values / phi.values.sum()\n", + "/Users/art/repos/ooni/data/oonipipeline/.venv/lib/python3.11/site-packages/pgmpy/factors/discrete/DiscreteFactor.py:489: RuntimeWarning: invalid value encountered in divide\n", + " phi.values = phi.values / phi.values.sum()\n" + ] + } + ], + "source": [ + "from pgmpy.inference import VariableElimination\n", + "from pgmpy.estimators import MaximumLikelihoodEstimator\n", + "bn_estimated_pc = BayesianNetwork(estimated_model)\n", + "bn_estimated_pc.fit(data=samples_extra, estimator=MaximumLikelihoodEstimator)\n", + "infer = VariableElimination(bn_estimated_pc)\n", + "def infer_blockpage_2(row):\n", + " evidence = {}\n", + " for key in row.keys():\n", + " if key != 'answer_is_blockpage' and not pd.isnull(row[key]):\n", + " evidence[key] = row[key]\n", + " res = infer.query(['answer_is_blockpage'], evidence=evidence)\n", + " row['answer_is_blockpage_0'] = res.values[0]\n", + " row['answer_is_blockpage_1'] = res.values[1]\n", + " return row\n", + "samples_extra_clean_part = samples_extra_clean_part.apply(infer_blockpage_2, axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 241, + "id": "387e6e49-d072-4bb2-85da-221b9959ae36", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0" + ] + }, + "execution_count": 241, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(bn_estimated_pc.get_cpds('tls_consistent').get_evidence())" + ] + }, + { + "cell_type": "code", + "execution_count": 242, + "id": "b68e6c98-9273-4674-a88c-94f00cc72f70", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "3072" + ] + }, + "execution_count": 242, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(a[0])" + ] + }, + { + "cell_type": "code", + "execution_count": 246, + "id": "16cc24a0-44df-4b33-9875-f031d4510b61", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "3072" + ] + }, + "execution_count": 246, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "2**10*3" + ] + }, + { + "cell_type": "code", + "execution_count": 218, + "id": "11483302-ea84-4021-9ab6-0df180d83c0d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'20240220062610.565789_VE_webconnectivity_0b7437bb2801006a'" + ] + }, + "execution_count": 218, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "samples_extra.iloc[16]['measurement_uid']" + ] + }, + { + "cell_type": "code", + "execution_count": 150, + "id": "72042d2c-6583-4127-9fa7-77e3e354c047", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "" + ] + }, + "execution_count": 150, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "viz = estimated_model.to_graphviz()\n", + "viz.draw('estimated_pc_stable_1M.png', prog='dot')\n", + "Image('estimated_pc_stable_1M.png')" + ] + }, + { + "cell_type": "code", + "execution_count": 151, + "id": "25c7616b-b626-4895-a16d-7d1ca586b437", + "metadata": {}, + "outputs": [], + "source": [ + "from pgmpy.estimators import MaximumLikelihoodEstimator\n", + "bn_estimated_pc = BayesianNetwork(estimated_model)\n", + "bn_estimated_pc.fit(data=samples, estimator=MaximumLikelihoodEstimator)" + ] + }, + { + "cell_type": "code", + "execution_count": 152, + "id": "95e6ad05-83ab-472d-9251-3563c0176368", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "execution_count": 152, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "viz = bn_estimated_pc.to_graphviz()\n", + "viz.draw('estimated_pc_stable_1M.png', prog='dot')\n", + "Image('estimated_pc_stable_1M.png')" + ] + }, + { + "cell_type": "code", + "execution_count": 115, + "id": "4b491d78-6b7b-4a07-9b4e-564352424975", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 153, + "id": "39d61a52-95b3-48a7-a930-33d97d0db243", + "metadata": {}, + "outputs": [], + "source": [ + "from pgmpy.inference import VariableElimination\n", + "infer = VariableElimination(bn_estimated_pc)" + ] + }, + { + "cell_type": "code", + "execution_count": 189, + "id": "9643f31a-b393-431d-8698-85a873231a00", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+------------------------+----------------------------+\n", + "| answer_is_blockpage | phi(answer_is_blockpage) |\n", + "+========================+============================+\n", + "| answer_is_blockpage(0) | 0.9992 |\n", + "+------------------------+----------------------------+\n", + "| answer_is_blockpage(1) | 0.0008 |\n", + "+------------------------+----------------------------+\n" + ] + } + ], + "source": [ + "print(infer.query(['answer_is_blockpage']))" + ] + }, + { + "cell_type": "code", + "execution_count": 154, + "id": "c713290f-afda-4cca-be84-bf281d12b4fa", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 154, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bn_estimated_pc" + ] + }, + { + "cell_type": "code", + "execution_count": 155, + "id": "688fc8a7-17d3-4597-af04-3d002644eccf", + "metadata": {}, + "outputs": [], + "source": [ + "samples_inference = samples.copy()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "88be89fb-86cd-472b-9347-1881c3a02def", + "metadata": {}, + "outputs": [], + "source": [ + "estimated_model" + ] + }, + { + "cell_type": "code", + "execution_count": 156, + "id": "a80d59c2-822a-4140-9910-b86c2bdd4111", + "metadata": {}, + "outputs": [], + "source": [ + "def infer_blockpage(row):\n", + " evidence = {}\n", + " for key in ['answer_count', 'contains_tls_consistent_answer',\n", + " 'answer_matches_probe_asn', 'answer_matches_probe_cc',\n", + " 'answer_contains_bogon', 'answer_is_cloud_provider',\n", + " 'answer_contains_unreachable_ip']:\n", + " if not pd.isnull(row[key]):\n", + " evidence[key] = row[key]\n", + " res = infer.query(['answer_is_blockpage'], evidence=evidence)\n", + " return res.values[0]\n", + "samples_inference['answer_is_blockpage_prob'] = samples_inference.apply(infer_blockpage, axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 202, + "id": "c7115696-2216-4c97-b708-68e42f30a433", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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"id": "f9b2502a-be79-49c6-b294-9e629dada251", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "\n", + " 0%| | 0/1000000 [00:00" + ] + }, + "execution_count": 111, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "viz = estimated_model.to_graphviz()\n", + "viz.draw('estimated_hillclimb_1M.png', prog='dot')\n", + "Image('estimated_hillclimb_1M.png')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6e0703ab-7419-4d43-ad95-03d226b74004", + "metadata": {}, + "outputs": [], + "source": [ + "cpd_answer_matches_probe_cc = TabularCPD(\n", + " \"answer_matches_probe_cc\",\n", + " variable_card=2,\n", + " values=[\n", + " [0.77],\n", + " [0.23],\n", + " ],\n", + " state_names={\n", + " \"answer_matches_probe_cc\": ['t', 'f']\n", + " },\n", + ")\n", + "\n", + "cpd_contains_unreachable_answer = TabularCPD(\n", + " \"answer_contains_unreachable_ip\",\n", + " variable_card=2,\n", + " values=[\n", + " [0.15],\n", + " [0.85],\n", + " ],\n", + " state_names={\n", + " \"answer_contains_unreachable_ip\": ['t', 'f']\n", + " },\n", + ")\n", + "\n", + "cpd_contains_unreachable_answer = TabularCPD(\n", + " \"answer_contains_bogon\",\n", + " variable_card=2,\n", + " values=[\n", + " [0.015],\n", + " [0.985],\n", + " ],\n", + " state_names={\n", + " \"answer_contains_bogon\": ['t', 'f']\n", + " },\n", + ")\n", + "\n", + "\n", + "cpd_contains_unreachable_answer = TabularCPD(\n", + " \"answer_is_blockpage\",\n", + " variable_card=2,\n", + " values=[\n", + " [0.015],\n", + " [0.985],\n", + " ],\n", + " evidence=[\"answer_contains_bogon\", \"answer_contains_unreachable_ip\", \"answer_matches_probe_cc\"],\n", + " evidence_card=[3, 3],\n", + " state_names={\n", + " \"answer_is_blockpage\": ['t', 'f']\n", + " },\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4b02005e-aa58-4ab9-ab2d-79f6b4de1bff", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "95eebdc8-959b-4378-936e-da93fd532d6e", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "817d57dd-4b58-46f7-8c07-d3cdaa15bcb0", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 80, + "id": "7c3f0650-e34c-4fc2-9706-8439f8223400", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f139f2ea-b491-46aa-b75f-1acc3f7b6169", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6a0480af-d3c1-4c58-a8ac-4631487ee48f", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 54, + "id": "b739753b-d515-4903-8a1d-a7725604131a", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 55, + "id": "5482a37f-2532-494d-9e15-e3e40dea854b", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c6b1e906-58fa-4ba2-9e35-b76e9c64e4fc", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3bdc153b-19df-4434-983a-30e7a8e22cd4", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ea33f35b-a596-4818-ad61-ee0730fe8e24", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fd1ffe75-dcba-4b67-b7fe-c839fb5030ff", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "07310d97-6023-47e9-bca3-2f011a823111", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.11.7" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/oonipipeline/notebooks/DNS Similarity.ipynb b/oonipipeline/notebooks/DNS Similarity.ipynb new file mode 100644 index 00000000..0be88cf2 --- /dev/null +++ b/oonipipeline/notebooks/DNS Similarity.ipynb @@ -0,0 +1,416 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "f309af11-65e3-4d73-88de-655921a52693", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/art/repos/ooni/data/oonipipeline/.venv/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", + " from .autonotebook import tqdm as notebook_tqdm\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "from IPython.display import Image\n", + "from pgmpy.models import BayesianNetwork\n", + "from pgmpy.factors.discrete import TabularCPD" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "3f8fc6f9-9786-4013-8802-359432fb01a2", + "metadata": {}, + "outputs": [], + "source": [ + "sample_uids = [\n", + " '20240101113125.808243_BG_webconnectivity_ba4cf234d47b73ec',\n", + " '20240220050354.524776_US_webconnectivity_a690552818804fc3',\n", + " '20240224232654.007984_RU_webconnectivity_9164a3df2d35316c',\n", + " '20240226225131.261075_VE_webconnectivity_a3e31c999fc8b161',\n", + " '20240226225231.612531_VE_webconnectivity_47d3561e542337d8',\n", + " '20240226225245.422977_VE_webconnectivity_37dcdd51581cbd13',\n", + " '20240227160142.829208_US_webconnectivity_2c9b945991901f8d',\n", + " '20240311005741.675686_SE_webconnectivity_2a4a84928bd17ab0',\n", + " '20240316062349.575036_US_webconnectivity_b63efd0ed694e005',\n", + " '20240328194436.111684_TR_webconnectivity_5414b98b9c9f873b',\n", + " '20240409035157.511121_BR_webconnectivity_85b1de4e410314f7',\n", + " '20240410115514.842786_BR_webconnectivity_6d224ea8b6b3ca7c',\n", + " '20240410124541.400148_BR_webconnectivity_ac16eb05475f622a',\n", + " '20240410134516.191956_BR_webconnectivity_a947a71df23203f3',\n", + " '20240410135012.070725_BR_webconnectivity_d3e9bce608599d5e',\n", + " '20240413230148.929136_KH_webconnectivity_33ae9436d7b6779c',\n", + " '20240415141511.755790_BR_webconnectivity_07547042a9307621',\n", + " '20240416214307.425888_BR_webconnectivity_c9d912510d61bc0b',\n", + " '20240418071953.744226_BR_webconnectivity_2c6b65eeff39f34f',\n", + " '20240506163355.336279_VN_webconnectivity_8de9ce661982414d',\n", + " '20240508114544.444840_BR_webconnectivity_379718729eeed45b',\n", + " '20240514091759.626287_NL_webconnectivity_38962f675df0f676',\n", + " '20240519182127.049517_US_webconnectivity_6e12ec842e98674a',\n", + " '20240522113817.495473_NL_webconnectivity_e81ed947814f9d2a',\n", + " '20240524142956.125292_JO_webconnectivity_5cd31e0f03494bd2',\n", + " '20240627074955.407639_RU_webconnectivity_99e23c2b9680c1cb',\n", + " '20240704234509.514733_NL_webconnectivity_6f924d2e43209ae1',\n", + " '20240705015016.667807_AE_webconnectivity_392604bce72a44d5',\n", + " '20240722041303.591874_MM_webconnectivity_98e6671dd7dce61a',\n", + " '20240722041334.778473_MM_webconnectivity_93a628687303be86',\n", + " '20240722042950.433988_MM_webconnectivity_d388cdc8bad1f15c',\n", + " '20240728114019.011456_VE_webconnectivity_1f0ba3819685e272',\n", + " '20240810175938.750056_VE_webconnectivity_016721e1ebfdc2ed',\n", + " '20240810182504.634031_VE_webconnectivity_853b19341a35d2f0',\n", + " '20240810182604.928599_VE_webconnectivity_f42bd5020088c498',\n", + " '20240815043926.030750_VE_webconnectivity_f034e025b6db08ea',\n", + " '20240815092817.050941_DE_webconnectivity_661003d3498d802f',\n", + " '20240815172949.387668_VE_webconnectivity_427addcd5d1ea806',\n", + " '20240818234433.791006_VE_webconnectivity_8fac03865551a8eb',\n", + " '20240820163242.249906_JO_webconnectivity_a826f460299fa996']" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "f67d57d4-9472-47c7-94a7-03eb97c8c4f9", + "metadata": {}, + "outputs": [], + "source": [ + "from pathlib import Path\n", + "from oonidata.dataclient import load_measurement\n", + "from oonidata.apiclient import get_measurement_dict_by_uid\n", + "\n", + "from oonipipeline.netinfo import NetinfoDB\n", + "from oonipipeline.transforms.observations import measurement_to_observations" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "id": "6e0703ab-7419-4d43-ad95-03d226b74004", + "metadata": {}, + "outputs": [], + "source": [ + "netinfodb = NetinfoDB(datadir=Path(\"datadir\"), download=False)\n", + "# 20231129041111.939896_NP_webconnectivity_32105af63774eabf\n", + "#raw_msmt = get_measurement_dict_by_uid(\"20240804233508.181041_TR_webconnectivity_9a7272e520f3d836\")\n", + "def make_obs_ctrl(measurement_uid):\n", + " raw_msmt = get_measurement_dict_by_uid(measurement_uid)\n", + " msmt = load_measurement(msmt=raw_msmt)\n", + " web_observations, web_control_observations = measurement_to_observations(\n", + " msmt, netinfodb=netinfodb\n", + " )\n", + " return web_observations, web_control_observations" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "id": "4b02005e-aa58-4ab9-ab2d-79f6b4de1bff", + "metadata": {}, + "outputs": [], + "source": [ + "from collections import Counter\n", + "def most_frequent(asns):\n", + " if not asns:\n", + " return 0\n", + " count = Counter(asns)\n", + " most_common = count.most_common(1)\n", + " return most_common[0][0]\n", + "\n", + "CLOUD_PROVIDERS_ASNS = [\n", + " 13335, # Cloudflare: https://www.peeringdb.com/net/4224\n", + " 209242, #\tCloudflare London, LLC\t\n", + " 20940, # Akamai: https://www.peeringdb.com/net/2\n", + " 9002, # Akamai RETN\n", + " 16625, # Akamai Technologies, Inc.\t\n", + " 63949, # Akamai Technologies, Inc.\t\n", + " 16509, #\tAmazon.com, Inc.\n", + " 14618, #\tAmazon.com, Inc.\t\n", + " 15169, #\tGoogle LLC\n", + " 396982, # Google Cloud: https://www.peeringdb.com/net/30878\n", + " 54113, #\tFastly, Inc\n", + " 8075, # Microsoft Corporation\n", + " 8068, #\tMicrosoft Corporation\n", + "]\n", + "def is_cloud_provider(as_number):\n", + " return as_number in CLOUD_PROVIDERS_ASNS\n", + "\n", + "def dns_feature_vector(dns_answers, w_ctrl):\n", + " ctrl_map = {}\n", + " for ctrl in w_ctrl:\n", + " ctrl_map[ctrl.ip] = ctrl\n", + "\n", + " unreachable_count = 0\n", + " for answer in dns_answers:\n", + " if ctrl_map.get(answer.ip):\n", + " if ctrl_map[answer.ip].tcp_success == False:\n", + " unreachable_count += 1\n", + " dns_answer_vector = {\n", + " \"answer_count\": len(dns_answers),\n", + " \"answer_cloud_provider\": 1 if any([is_cloud_provider(x.ip_asn) for x in dns_answers]) else 0,\n", + " \"unreachable_answer_count\": unreachable_count,\n", + " \"top_answer_asn\": most_frequent(map(lambda x: x.ip_asn, dns_answers))\n", + " }\n", + " return dns_answer_vector" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "95eebdc8-959b-4378-936e-da93fd532d6e", + "metadata": {}, + "outputs": [], + "source": [ + "obs, ctrl = make_obs_ctrl(\"20240316062349.575036_US_webconnectivity_b63efd0ed694e005\")" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "id": "817d57dd-4b58-46f7-8c07-d3cdaa15bcb0", + "metadata": {}, + "outputs": [], + "source": [ + "from pprint import pprint\n", + "#pprint(obs[0])" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "id": "7c3f0650-e34c-4fc2-9706-8439f8223400", + "metadata": {}, + "outputs": [], + "source": [ + "from scipy.spatial import distance\n", + "netinfodb = NetinfoDB(datadir=Path(\"datadir\"), download=False)\n", + "def compute_dns_distance(measurement_uid):\n", + " web_observations, web_control_observations = make_obs_ctrl(measurement_uid)\n", + " exp_dns_answers = list(filter(lambda x: x.dns_answer is not None, web_observations))\n", + " if len(exp_dns_answers) == 0:\n", + " return None\n", + " exp_vector = list(dns_feature_vector(web_observations, web_control_observations).values())\n", + " ctrl_dns_answers = list(filter(lambda x: x.dns_failure is not None or x.dns_success is True, web_control_observations))\n", + " ctrl_vector = list(dns_feature_vector(\n", + " ctrl_dns_answers,\n", + " web_control_observations\n", + " ).values())\n", + " try:\n", + " d = distance.cosine(exp_vector, ctrl_vector)\n", + " return d\n", + " except:\n", + " print(exp_vector, ctrl_vector)\n", + " return None" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "id": "f139f2ea-b491-46aa-b75f-1acc3f7b6169", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "20240101113125.808243_BG_webconnectivity_ba4cf234d47b73ec\n", + "2.511132244364944e-07\n", + "20240220050354.524776_US_webconnectivity_a690552818804fc3\n", + "2.0243516862805677e-09\n", + "20240224232654.007984_RU_webconnectivity_9164a3df2d35316c\n", + "2.811796573354286e-09\n", + "20240226225131.261075_VE_webconnectivity_a3e31c999fc8b161\n", + "5.679824388593602e-10\n", + "20240226225231.612531_VE_webconnectivity_47d3561e542337d8\n", + "2.811796573354286e-09\n", + "20240226225245.422977_VE_webconnectivity_37dcdd51581cbd13\n", + "1.1247181741502743e-08\n", + "20240227160142.829208_US_webconnectivity_2c9b945991901f8d\n", + "None\n", + "20240311005741.675686_SE_webconnectivity_2a4a84928bd17ab0\n", + "1.834545071410787e-09\n", + "20240316062349.575036_US_webconnectivity_b63efd0ed694e005\n", + "[3, 0, 0, None] [2, 0, 0, 60781]\n", + "None\n", + "20240328194436.111684_TR_webconnectivity_5414b98b9c9f873b\n", + "1.3396325160286437e-09\n", + "20240409035157.511121_BR_webconnectivity_85b1de4e410314f7\n", + "0.0\n", + "20240410115514.842786_BR_webconnectivity_6d224ea8b6b3ca7c\n", + "2.8117966843765885e-09\n", + "20240410124541.400148_BR_webconnectivity_ac16eb05475f622a\n", + "1.2861659182128449e-08\n", + "20240410134516.191956_BR_webconnectivity_a947a71df23203f3\n", + "0.0\n", + "20240410135012.070725_BR_webconnectivity_d3e9bce608599d5e\n", + "7.02948984576679e-08\n", + "20240413230148.929136_KH_webconnectivity_33ae9436d7b6779c\n", + "None\n", + "20240415141511.755790_BR_webconnectivity_07547042a9307621\n", + "2.811796573354286e-09\n", + "20240416214307.425888_BR_webconnectivity_c9d912510d61bc0b\n", + "[3, 0, 0, None] [4, 0, 0, 40428]\n", + "None\n", + "20240418071953.744226_BR_webconnectivity_2c6b65eeff39f34f\n", + "0.0\n", + "20240506163355.336279_VN_webconnectivity_8de9ce661982414d\n", + "4.189776303675785e-10\n", + "20240508114544.444840_BR_webconnectivity_379718729eeed45b\n", + "3.71212472660698e-06\n", + "20240514091759.626287_NL_webconnectivity_38962f675df0f676\n", + "1.8090338116394378e-09\n", + "20240519182127.049517_US_webconnectivity_6e12ec842e98674a\n", + "2.7760629350837007e-09\n", + "20240522113817.495473_NL_webconnectivity_e81ed947814f9d2a\n", + "None\n", + "20240524142956.125292_JO_webconnectivity_5cd31e0f03494bd2\n", + "6.872500064591947e-07\n", + "20240627074955.407639_RU_webconnectivity_99e23c2b9680c1cb\n", + "1.8345449603884845e-09\n", + "20240704234509.514733_NL_webconnectivity_6f924d2e43209ae1\n", + "4.6097892170138266e-10\n", + "20240705015016.667807_AE_webconnectivity_392604bce72a44d5\n", + "[5, 1, 0, None] [2, 1, 0, 16509]\n", + "None\n", + "20240722041303.591874_MM_webconnectivity_98e6671dd7dce61a\n", + "4.6097892170138266e-10\n", + "20240722041334.778473_MM_webconnectivity_93a628687303be86\n", + "4.6097892170138266e-10\n", + "20240722042950.433988_MM_webconnectivity_d388cdc8bad1f15c\n", + "2.7787750989105575e-09\n", + "20240728114019.011456_VE_webconnectivity_1f0ba3819685e272\n", + "2.2500359353472277e-09\n", + "20240810175938.750056_VE_webconnectivity_016721e1ebfdc2ed\n", + "1.1115099285419205e-08\n", + "20240810182504.634031_VE_webconnectivity_853b19341a35d2f0\n", + "7.668048529474447e-09\n", + "20240810182604.928599_VE_webconnectivity_f42bd5020088c498\n", + "[3, 1, 0, None] [16, 1, 0, 54113]\n", + "None\n", + "20240815043926.030750_VE_webconnectivity_f034e025b6db08ea\n", + "2.7787750989105575e-09\n", + "20240815092817.050941_DE_webconnectivity_661003d3498d802f\n", + "None\n", + "20240815172949.387668_VE_webconnectivity_427addcd5d1ea806\n", + "2.7787750989105575e-09\n", + "20240818234433.791006_VE_webconnectivity_8fac03865551a8eb\n", + "1.8345454044776943e-09\n", + "20240820163242.249906_JO_webconnectivity_a826f460299fa996\n", + "1.004488997979891e-06\n" + ] + } + ], + "source": [ + "distance_map = {\n", + "}\n", + "for uid in sample_uids:\n", + " print(uid)\n", + " d = compute_dns_distance(uid)\n", + " print(d)\n", + " distance_map[uid] = d" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "id": "6a0480af-d3c1-4c58-a8ac-4631487ee48f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "3.9001535001581544e-08" + ] + }, + "execution_count": 88, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "compute_dns_distance(\"20240729235930.015020_IR_webconnectivity_eda3016ef01b4d3b\")" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "id": "b739753b-d515-4903-8a1d-a7725604131a", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 55, + "id": "5482a37f-2532-494d-9e15-e3e40dea854b", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c6b1e906-58fa-4ba2-9e35-b76e9c64e4fc", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3bdc153b-19df-4434-983a-30e7a8e22cd4", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ea33f35b-a596-4818-ad61-ee0730fe8e24", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fd1ffe75-dcba-4b67-b7fe-c839fb5030ff", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "07310d97-6023-47e9-bca3-2f011a823111", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.11.7" + } + }, + "nbformat": 4, + 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