Notebooks/13_NetworkX.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Intro to Graph Databases and Network Science"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Network science is an academic field which studies complex networks such as telecommunication networks, computer networks, biological networks, cognitive and semantic networks, and social networks, considering distinct elements or actors represented by nodes (or vertices) and the connections between the elements or actors as links (or edges). The field draws on theories and methods including graph theory from mathematics, statistical mechanics from physics, data mining and information visualization from computer science, inferential modeling from statistics, and social structure from sociology. (from wikipedia)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import operator\n",
    "import codecs\n",
    "import random\n",
    "import math\n",
    "from itertools import chain\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pylab as pl\n",
    "import pandas as pd\n",
    "import networkx as nx\n",
    "\n",
    "from collections import Counter, OrderedDict\n",
    "\n",
    "import urllib\n",
    "from bs4 import BeautifulSoup\n",
    "#import pydot\n",
    "\n",
    "#import datashader as ds\n",
    "#import datashader.transfer_functions as tf\n",
    "#from datashader.layout import random_layout, circular_layout, forceatlas2_layout\n",
    "#from datashader.bundling import connect_edges, hammer_bundle\n",
    "\n",
    "#import holoviews.operation.datashader as hd\n",
    "#import holoviews as hv\n",
    "#hv.extension(\"bokeh\")\n",
    "\n",
    "from SPARQLWrapper import SPARQLWrapper, JSON    #sudo pip3 install --upgrade SPARQLWrapper\n",
    "\n",
    "from IPython.display import display, Image\n",
    "from IPython.core.interactiveshell import InteractiveShell\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  Philosophers Influences Chain  \n",
    "\n",
    "Based on [this](https://www.analyticsvidhya.com/blog/2018/09/introduction-graph-theory-applications-python/), with examples inspired in [this](http://www.coppelia.io/2012/06/graphing-the-history-of-philosophy/) and [this](http://brendangriffen.com/blog/gow-influential-thinkers) experiments. Information crawled from [DBpedia](https://wiki.dbpedia.org/)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The internet is big — very big. One such way to investigate all of this free online content is through graphs.  \n",
    "To start, let’s look at how people influenced each other throughout history as entered by the authors of Wikipedia.  \n",
    "If you search for a notable figure you might find the following on the sidebar:  \n",
    "\n",
    "\n",
    "## [Aristotle Facts](https://en.wikipedia.org/wiki/Aristotle)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we see a list of people that have been influenced by Aristotle. We also see who Aristotle himself was influenced by. At the moment, these are just names, but this provides a way we can connect Aristotle to other people throughout history. If only we had a way to collect this data using a simple database-like query."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our task is to answer the questions:  \n",
    "\n",
    " 1) What are the top 10 personalities in terms of power to generate influences?  \n",
    " 2) What are the 10 personalities that were influenced by the most number of people?  \n",
    " 3) What are the 5 major \"clusters\" of personalities who were influenced by a similar group of the same influencers?   \n",
    "(Consider a cluster as the group of personalities who were influenced by the same Y influencers, Y being an arbitrary number. Start with Y = 2 and grow until there is no 2 people influenced by all of them.  \n",
    "\n",
    " 4) What are the 5 major influences chains (eg, A -> B -> C -> ...)?  \n",
    " 5) What are the countries that generated the greatest influential?  \n",
    " 6) What are the areas of greatest influence?  \n",
    " 7) Create a graphical representation of the graph  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Collect Data\n",
    "\n",
    "First we require a database-like, indexed version of Wikipedia to collect our data. [DBpedia](https://wiki.dbpedia.org/) is one such venture which has been created as part of the Wikipedia project. This structured content is then made available to the public at no cost. DBpedia allows you to query relationships and properties associated with Wikipedia resources, including links to other related datasets. The first graph will connect people via their known influences. The snippet of code entered into the [SPARQL Explorer](http://dbpedia.org/snorql/) looks something like this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "sparql_query = '''\n",
    "SELECT * WHERE\n",
    "{?p a <http://dbpedia.org/ontology/Person>.\n",
    "?p <http://dbpedia.org/ontology/influenced> ?influenced.\n",
    "?influenced a <http://dbpedia.org/ontology/Person>. }\n",
    "'''"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you'd want to do the same process with, say, programming languages, the query would be:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "sparql_query2 = '''\n",
    "SELECT *\n",
    "WHERE { ?p a <http://dbpedia.org/ontology/ProgrammingLanguage> .\n",
    "?p <http://dbpedia.org/ontology/influenced> ?influenced . }\n",
    "'''"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "But we can use Python to make a direct query and use the results:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#sparql = SPARQLWrapper(\"http://dbpedia.org/sparql\")\n",
    "#sparql.setQuery(sparql_query)\n",
    "#sparql.setReturnFormat(JSON)\n",
    "#results = sparql.query().convert()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#len(results['results']['bindings'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#results['results']['bindings'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#for result in results['results']['bindings'][90:100]:\n",
    "#    print(result['influenced']['value'].strip('http://dbpedia.org/resource/').replace('_',' '), \n",
    "#          ' --> ', result['p']['value'].strip('http://dbpedia.org/resource/').replace('_',' '))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#with open(\"../SampleDBs/influences.csv\", mode= 'w', encoding=\"utf-8\") as f:\n",
    "#    f.write('\"influences\";\"influenced\"\\n')\n",
    "#    for result in results['results']['bindings']:\n",
    "#        f.write('\"{}\";\"{}\"\\n'.format(result['influenced']['value'].strip('http://dbpedia.org/resource/').replace('_',' '),\n",
    "#                                     result['p']['value'].strip('http://dbpedia.org/resource/').replace('_',' ')))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "But we will work with a cleaner version of the file, because some of the URLs present incomplete names and we would need to query each individual page to grab them."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Specifying the path to the files:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "datapath = \"../SampleDBs/\"\n",
    "outputs = \"../SampleDBs/\"\n",
    "dataset1 = \"influences.csv\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Loading the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "csvfile = codecs.open(os.path.join(datapath,dataset1), encoding=\"utf-8\").readlines()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8590"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(csvfile)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['\"influences\";\"influenced\"\\n',\n",
       " '\"Abbie Hoffman\";\"Lenny B\"\\n',\n",
       " '\"Alfred Marshall\";\"Léon Wal\"\\n',\n",
       " '\"Amartya Sen\";\"John Maynard Keyn\"\\n',\n",
       " '\"Amartya Sen\";\"Kenneth Arrow\"\\n']"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csvfile[0:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Doing some cleaning  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "influences;influenced\n",
      "Abbie Hoffman;Lenny B\n",
      "Alfred Marshall;Léon Wal\n",
      "Amartya Sen;John Maynard Keyn\n",
      "Amartya Sen;Kenneth Arrow\n",
      "Ambrosius Holbein;Hans Holbein the El\n"
     ]
    }
   ],
   "source": [
    "lines = [line.strip() for line in csvfile]\n",
    "lines2 = []\n",
    "for line in lines:\n",
    "    line = line.replace('\",','\";')\n",
    "    line = line.replace('\"','').strip()\n",
    "    lines2.append(line)\n",
    "for line in lines2[0:6]:\n",
    "    print(line)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dimensions: (8590, 2)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([['influences', 'influenced'],\n",
       "       ['Abbie Hoffman', 'Lenny B'],\n",
       "       ['Alfred Marshall', 'Léon Wal'],\n",
       "       ['Amartya Sen', 'John Maynard Keyn'],\n",
       "       ['Amartya Sen', 'Kenneth Arrow'],\n",
       "       ['Ambrosius Holbein', 'Hans Holbein the El'],\n",
       "       ['Andrzej Waj', 'Jerzy Grotowsk'],\n",
       "       ['Anthony B', 'Ford Madox F'],\n",
       "       ['Anthony B', 'Vladimir Nabokov'],\n",
       "       ['Bill Hick', 'Lenny B']], dtype='<U69')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "influences = np.array([(line.split(';')[0],line.split(';')[1]) for line in lines2])\n",
    "print('Dimensions: {}'.format(influences.shape))\n",
    "influences[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>influences</th>\n",
       "      <th>influenced</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Abbie Hoffman</td>\n",
       "      <td>Lenny B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Alfred Marshall</td>\n",
       "      <td>Léon Wal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Amartya Sen</td>\n",
       "      <td>John Maynard Keyn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Amartya Sen</td>\n",
       "      <td>Kenneth Arrow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ambrosius Holbein</td>\n",
       "      <td>Hans Holbein the El</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Andrzej Waj</td>\n",
       "      <td>Jerzy Grotowsk</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Anthony B</td>\n",
       "      <td>Ford Madox F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Anthony B</td>\n",
       "      <td>Vladimir Nabokov</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Bill Hick</td>\n",
       "      <td>Lenny B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Bob Black</td>\n",
       "      <td>Abbie Hoffman</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          influences           influenced\n",
       "0      Abbie Hoffman              Lenny B\n",
       "1    Alfred Marshall             Léon Wal\n",
       "2        Amartya Sen    John Maynard Keyn\n",
       "3        Amartya Sen        Kenneth Arrow\n",
       "4  Ambrosius Holbein  Hans Holbein the El\n",
       "5        Andrzej Waj       Jerzy Grotowsk\n",
       "6          Anthony B         Ford Madox F\n",
       "7          Anthony B     Vladimir Nabokov\n",
       "8          Bill Hick              Lenny B\n",
       "9          Bob Black        Abbie Hoffman"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd_influences = pd.DataFrame(influences[1:,:], columns = influences[0])\n",
    "pd_influences.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of nodes is: 7233\n",
      "Number of edges is: 8587\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#nodes = influences[1:,0]\n",
    "#edges = influences[1:,1]\n",
    "G = nx.DiGraph()\n",
    "G.add_edges_from(influences[1:], weight = 1)\n",
    "\n",
    "print('Number of nodes is: {}'.format(G.number_of_nodes()))\n",
    "print('Number of edges is: {}'.format(G.number_of_edges()))\n",
    "print()\n",
    "#print(G.edges())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Ivan Turgenev',\n",
       " 'Gustave Fl',\n",
       " 'Robert Louis Stevenson',\n",
       " 'Thomas Mayne R',\n",
       " 'Nikolai Gogol']"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(G.neighbors('Vladimir Nabokov'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Ivan Turgenev',\n",
       " 'Gustave Fl',\n",
       " 'Robert Louis Stevenson',\n",
       " 'Thomas Mayne R',\n",
       " 'Nikolai Gogol']"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(G.successors('Vladimir Nabokov'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Anthony B',\n",
       " 'Thomas Pynchon',\n",
       " 'Edmund Y',\n",
       " 'John Banvill',\n",
       " 'David Cronen',\n",
       " 'John Updik',\n",
       " 'Stanley Kubrick',\n",
       " 'Zadie Sm',\n",
       " 'Daniel Handl',\n",
       " 'Don DeLill',\n",
       " 'Jeffrey Eugen',\n",
       " 'Martin Am',\n",
       " 'Nick Cav',\n",
       " 'Christopher Hitchen',\n",
       " 'Daniel Clow',\n",
       " 'Jhumpa L',\n",
       " 'Michael Chabon',\n",
       " 'Terence McKenn',\n",
       " 'Victor Pelevin',\n",
       " 'Gene Wolf',\n",
       " 'Joanna Newsom',\n",
       " 'Oğuz Atay',\n",
       " 'Javier Marí',\n",
       " 'Richard Rorty']"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(G.predecessors('Vladimir Nabokov'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('Abbie Hoffman',\n",
       "  {'Lenny B': {'weight': 1},\n",
       "   'Marshall McLuhan': {'weight': 1},\n",
       "   'Herbert M': {'weight': 1},\n",
       "   'Abraham Maslow': {'weight': 1}}),\n",
       " ('Lenny B', {'Mort Sahl': {'weight': 1}, 'Irwin Corey': {'weight': 1}})]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(G.adjacency())[0:2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1) What are the top 10 personalities in terms of power to generate influences?  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Influencer</th>\n",
       "      <th>#influenced</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Friedrich Nietz</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Martin H</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Karl Marx</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Michel Foucaul</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Gilles Deleuz</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>William Jam</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Bertrand Russell</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Edmund Husserl</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Murray R</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Immanuel Kan</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Influencer  #influenced\n",
       "0   Friedrich Nietz           27\n",
       "1          Martin H           22\n",
       "2         Karl Marx           21\n",
       "3    Michel Foucaul           20\n",
       "4     Gilles Deleuz           18\n",
       "5       William Jam           17\n",
       "6  Bertrand Russell           16\n",
       "7    Edmund Husserl           16\n",
       "8          Murray R           16\n",
       "9      Immanuel Kan           16"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#most_influencers = Counter(influences[1:,0]).most_common(10)\n",
    "most_influencers = Counter(dict(G.out_degree())).most_common(10)\n",
    "df_influencers = pd.DataFrame(most_influencers, columns = ['Influencer', '#influenced'] )\n",
    "df_influencers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Most influents')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x1200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.arange(len(Counter(influences[1:,0]).most_common(50)))\n",
    "y = list(zip(*Counter(influences[1:,0]).most_common(50)))[1]\n",
    "labels = list(zip(*Counter(influences[1:,0]).most_common(50)))[0]\n",
    "y2max = max(y) + 1\n",
    "\n",
    "plt.figure(figsize=(18,12), dpi=100)\n",
    "plt.bar(x, y, width=0.35)\n",
    "plt.xticks(x, labels)\n",
    "plt.ylim(0, y2max)\n",
    "plt.xticks(rotation=90)\n",
    "plt.ylabel('# of influences given')\n",
    "plt.title('Most influents')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Calculating the Pagerank"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('Edward S', 0.000870386036475088),\n",
       " ('Michel Foucaul', 0.0007850605575474715),\n",
       " ('Ludwig Wittgenstein', 0.0007646463309158927),\n",
       " ('Theodor W. Adorn', 0.0007557018509422481),\n",
       " ('David Foster Wall', 0.0006816730953387156),\n",
       " ('John Stuart Mill', 0.0006661399123114359),\n",
       " ('Imre Lak', 0.0006432551894371495),\n",
       " ('Gilles Deleuz', 0.0006016859404865415),\n",
       " ('John Maynard Keyn', 0.0005979157499774748),\n",
       " ('Abdus Salam', 0.0005975085972426806),\n",
       " ('Roman', 0.0005975085972426806),\n",
       " ('Jürgen Haberm', 0.0005933422791264188),\n",
       " ('William Jam', 0.0005769150887961481),\n",
       " ('Friedrich Nietz', 0.0005737768777933557),\n",
       " ('Giannina B', 0.0005636229293326173),\n",
       " ('Roger J-B W', 0.0005594846348090833),\n",
       " ('Gayatri Chakravorty Spivak', 0.0005478681285082753),\n",
       " ('Richard Dawkin', 0.0005455710142368763),\n",
       " ('Michel Onfray', 0.0005404698716535891),\n",
       " ('Isaac Newton', 0.0005381322933356726)]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr = nx.pagerank(G.reverse())\n",
    "pr_sorted = sorted(pr.items(), key=operator.itemgetter(1), reverse=True)\n",
    "pr_sorted[0:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('Immanuel Kan', 0.0008863168989708462),\n",
       " ('E', 0.0006587032619824896),\n",
       " ('William Jam', 0.000633258043525638),\n",
       " ('David Hum', 0.000534951544522477),\n",
       " ('John Stuart Mill', 0.0005148991548240061),\n",
       " ('Edmund Husserl', 0.000456241507124821),\n",
       " ('Georg Wilhelm Friedrich Hegel', 0.00037416340685577433),\n",
       " ('Max W', 0.0003720017707197295),\n",
       " ('Ludwig Wittgenstein', 0.00035900209757856575),\n",
       " ('Friedrich Nietz', 0.0003547015477411171),\n",
       " ('A', 0.00033516225081502084),\n",
       " ('Jean-Jacques R', 0.00032901980424178347),\n",
       " ('Gottfried Wilhelm Leibniz', 0.0003224002288943368),\n",
       " ('Martin H', 0.0003191940991895533),\n",
       " ('Hilary Putnam', 0.0003188480216596636),\n",
       " ('Johann Gottlieb F', 0.0003164301543834713),\n",
       " ('Baruch Spinoz', 0.0003156522590224273),\n",
       " ('Wilhelm Dilthey', 0.0002815543219862174),\n",
       " ('George Bool', 0.00027369526361076),\n",
       " ('S', 0.00025890279885473083)]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bb = nx.betweenness_centrality(G)\n",
    "bb_sorted = sorted(bb.items(), key=operator.itemgetter(1), reverse=True)\n",
    "bb_sorted[0:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0003547015477411171\n",
      "0.0005150528177899495\n"
     ]
    }
   ],
   "source": [
    "nx.set_node_attributes(G, bb, 'betweenness')\n",
    "nx.set_node_attributes(G, pr, 'pagerank')\n",
    "\n",
    "print(G.nodes['Friedrich Nietz']['betweenness'])\n",
    "\n",
    "print(G.nodes['Karl Marx']['pagerank'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'betweenness': 0.0, 'pagerank': 0.0005150528177899495}"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G.nodes[\"Karl Marx\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " 2) What are the 10 personalities that were influenced by the most number of people? "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Influenced</th>\n",
       "      <th>#influences</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Georg Wilhelm Friedrich Hegel</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Urmuz</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Immanuel Kan</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>William S. B</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lenny B</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Cornelius C</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Martin H</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Edmund Husserl</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Robert E. How</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Friedrich Nietz</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Influenced  #influences\n",
       "0  Georg Wilhelm Friedrich Hegel           48\n",
       "1                          Urmuz           38\n",
       "2                   Immanuel Kan           34\n",
       "3                   William S. B           32\n",
       "4                        Lenny B           31\n",
       "5                    Cornelius C           31\n",
       "6                       Martin H           30\n",
       "7                 Edmund Husserl           30\n",
       "8                  Robert E. How           29\n",
       "9                Friedrich Nietz           28"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#most_influenced = Counter(influences[1:,1]).most_common(10)\n",
    "most_influenced = Counter(dict(G.in_degree())).most_common(10)\n",
    "df_influenced = pd.DataFrame(most_influenced, columns = ['Influenced', '#influences'] )\n",
    "df_influenced"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Most influents')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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SHJnkY1W1e21LkrtW1ZOT3DvJtavqiGW7tW+U5NzVbtrdlya5dPfvS+4NAAAAAMDgFhm135PkdsvWXpvk35L8SZKzk1yW5J5J3pokVXWbJD+a5LR9NyYAAAAAAPuLhUXt7r4wyaeXrlXVd5N8u7s/Pf39NUlOrKp/T3JBkpcnOa27P7Sv5wUAAAAAYPEW+qDIvXBskisy2al9nSTvSvKkhU4EAAAAAMDC7FdRu7t/adnvlyT5nekXAAAAAAAHuUMWPQAAAAAAAOwtURsAAAAAgGGI2gAAAAAADEPUBgAAAABgGKI2AAAAAADDELUBAAAAABiGqA0AAAAAwDBEbQAAAAAAhiFqAwAAAAAwDFEbAAAAAIBhiNoAAAAAAAxD1AYAAAAAYBiiNgAAAAAAwxC1AQAAAAAYhqgNAAAAAMAwRG0AAAAAAIYhagMAAAAAMAxRGwAAAACAYYjaAAAAAAAMQ9QGAAAAAGAYojYAAAAAAMMQtQEAAAAAGIaoDQAAAADAMERtAAAAAACGIWoDAAAAADAMURsAAAAAgGGI2gAAAAAADEPUBgAAAABgGKI2AAAAAADDELUBAAAAABjG1kUPwIFh246da16z64Tt+2ASAAAAAOBAZqc2AAAAAADDELUBAAAAABiGqA0AAAAAwDBEbQAAAAAAhiFqAwAAAAAwDFEbAAAAAIBhiNoAAAAAAAxD1AYAAAAAYBiiNgAAAAAAwxC1AQAAAAAYhqgNAAAAAMAwRG0AAAAAAIYhagMAAAAAMAxRGwAAAACAYYjaAAAAAAAMQ9QGAAAAAGAYojYAAAAAAMMQtQEAAAAAGIaoDQAAAADAMERtAAAAAACGIWoDAAAAADAMURsAAAAAgGGI2gAAAAAADEPUBgAAAABgGKI2AAAAAADDELUBAAAAABiGqA0AAAAAwDBEbQAAAAAAhiFqAwAAAAAwDFEbAAAAAIBhiNoAAAAAAAxD1AYAAAAAYBiiNgAAAAAAwxC1AQAAAAAYhqgNAAAAAMAwRG0AAAAAAIYhagMAAAAAMAxRGwAAAACAYYjaAAAAAAAMQ9QGAAAAAGAYojYAAAAAAMMQtQEAAAAAGIaoDQAAAADAMERtAAAAAACGIWoDAAAAADAMURsAAAAAgGGI2gAAAAAADEPUBgAAAABgGKI2AAAAAADDELUBAAAAABiGqA0AAAAAwDBEbQAAAAAAhiFqAwAAAAAwDFEbAAAAAIBhiNoAAAAAAAxD1AYAAAAAYBiiNgAAAAAAwxC1AQAAAAAYhqgNAAAAAMAwRG0AAAAAAIYhagMAAAAAMAxRGwAAAACAYYjaAAAAAAAMQ9QGAAAAAGAYojYAAAAAAMMQtQEAAAAAGIaoDQAAAADAMERtAAAAAACGIWoDAAAAADAMURsAAAAAgGGI2gAAAAAADEPUBgAAAABgGKI2AAAAAADD2LroAWA9tu3YueY1u07Yvg8mAQAAAAAWwU5tAAAAAACGIWoDAAAAADAMURsAAAAAgGGI2gAAAAAADEPUBgAAAABgGKI2AAAAAADDELUBAAAAABiGqA0AAAAAwDBEbQAAAAAAhiFqAwAAAAAwDFEbAAAAAIBhiNoAAAAAAAxD1AYAAAAAYBiiNgAAAAAAwxC1AQAAAAAYhqgNAAAAAMAwRG0AAAAAAIYhagMAAAAAMAxRGwAAAACAYYjaAAAAAAAMQ9QGAAAAAGAYojYAAAAAAMMQtQEAAAAAGIaoDQAAAADAMERtAAAAAACGIWoDAAAAADAMURsAAAAAgGGI2gAAAAAADEPUBgAAAABgGKI2AAAAAADDELUBAAAAABiGqA0AAAAAwDBEbQAAAAAAhiFqAwAAAAAwDFEbAAAAAIBhiNoAAAAAAAxj66IHgP3Nth0717xm1wnb98EkAAAAAMBydmoDAAAAADAMURsAAAAAgGGI2gAAAAAADEPUBgAAAABgGKI2AAAAAADDELUBAAAAABiGqA0AAAAAwDBEbQAAAAAAhiFqAwAAAAAwDFEbAAAAAIBhiNoAAAAAAAxD1AYAAAAAYBiiNgAAAAAAwxC1AQAAAAAYhqgNAAAAAMAwRG0AAAAAAIYhagMAAAAAMIytix4ADlbbduxc85pdJ2wf5nMAAAAAYF+wUxsAAAAAgGGI2gAAAAAADEPUBgAAAABgGKI2AAAAAADDELUBAAAAABiGqA0AAAAAwDBEbQAAAAAAhiFqAwAAAAAwDFEbAAAAAIBhiNoAAAAAAAxD1AYAAAAAYBiiNgAAAAAAwxC1AQAAAAAYhqgNAAAAAMAwFhq1q+qJVXVGVV0w/Tqtqu675PXrVtUrqurbVXVRVb21qm60yJkBAAAAAFicRe/U/mqSHUl+JsnPJnlvkn+sqp+Yvv6SJPdP8qAkd0tykyRvW8CcAAAAAADsB7Yu8sO7++3Llp5bVU9Mcqeq+mqSxyZ5WHe/N0mq6tFJPldVd+ruD+3jcQEAAAAAWLBF79S+UlVtqaqHJLlBktMy2b19rSSn7r6mu/8tyVeS3HkP97lOVR2++yvJYZs7OQAAAAAA+8pCd2onSVXdLpOIfd0kFyX51e7+bFUdneT73X3+srd8PcmN93DLZyc5blOGBVa0bcfONa/ZdcL2YT4HAAAAgP3X/rBT+8wkRyf5uSR/keT1VfXjG7jfC5PccMnXzTY8IQAAAAAA+4WF79Tu7u8nOWv66+lVdYckT03y90muXVVHLNutfaMk5+7hfpcmuXT371U1/6EBAAAAAFiI/WGn9nKHJLlOktOTXJbknrtfqKrbJPnRTI4rAQAAAADgILPQndpV9cIkp2Ty8MfDkjwsyS8luXd3f6eqXpPkxKr69yQXJHl5ktO6+0MLGhkAAAAAgAVa9PEjRyZ5Q5IfSfKdJGdkErTfPX392CRXJHlrJru335XkSQuYEwAAAACA/cBCo3Z3P3aN1y9J8jvTLwAAAAAADnL745naAAAAAACwIlEbAAAAAIBhiNoAAAAAAAxD1AYAAAAAYBiiNgAAAAAAwxC1AQAAAAAYhqgNAAAAAMAwRG0AAAAAAIYhagMAAAAAMAxRGwAAAACAYYjaAAAAAAAMY+uiBwDY32zbsXPNa3adsH0fTAIAAADAcnZqAwAAAAAwDFEbAAAAAIBhiNoAAAAAAAxD1AYAAAAAYBiiNgAAAAAAwxC1AQAAAAAYhqgNAAAAAMAwRG0AAAAAAIYhagMAAAAAMAxRGwAAAACAYYjaAAAAAAAMY+ssb6qqQ5LcKsmRWRbGu/tf5jAXAAAAAABcw7qjdlXdKcnJSW6RpJa93Em2zGEuAAAAAAC4hll2ar8qyUeTbE/yfzMJ2QAAAAAAsOlmidq3TvLA7j5r3sMAAAAAAMCezPKgyA9ncp42AAAAAADsU7Ps1H55khdX1Y2TfCrJZUtf7O4z5jEYAAAAAAAsN0vUfuv0+18vWetMHhrpQZEAAAAAAGyaWaL2UXOfAuAgtG3HzjWv2XXC9v3+Mw60zzmQ/iwAAABwIFp31O7uL2/GIAAAAAAAsJZZHhSZqnp4VX2wqs6pqltM155WVQ+Y73gAAAAAAHCVdUftqnpikhOTvDPJEbnqDO3zkzxtfqMBAAAAAMDVzbJT+ylJHt/dxye5fMn6R5Pcbi5TAQAAAADACmaJ2kcl+fgK65cmucHGxgEAAAAAgNXNErW/lOToFdbvk+RzGxsHAAAAAABWt3WG95yY5BVVdd0kleSOVfXQJM9O8rh5DgcAAAAAAEutO2p396ur6ntJ/ijJ9ZOcnOScJE/t7jfOeT4AAAAAALjSLDu1090nJTmpqq6f5NDu/sZ8xwIAAAAAgGta95naVfX7VXVUknT3xYI2AAAAAAD7yiwPinxQkrOq6l+r6klV9cPzHgoAAAAAAFay7qjd3T+V5CeT/K8kz0hyTlXtrKqHTY8jAQAAAACATTHLTu1092e6+zndfcskd0+yK8lLk5w7x9kAAAAAAOBqZoray3w3yfeSfD/JteZwPwAAAAAAWNFMUbuqjqqq51bVZ5J8NMntkxyX5MbzHA4AAAAAAJbaut43VNWHktwhyRlJXpvk77r7a/MeDAAAAAAAllt31E7yniSP6e7PznsYAAAAAADYk3VH7e5+7mYMAgAAAAAAa9mrqF1VJyb5g+7+7vTnVXX30+cyGQAAAAAALLO3O7Vvn+RaS35eTW9sHAAAAAAAWN1eRe3uvvtKPwMAAAAAwL50yKIHAAAAAACAvbXuB0VW1T9k5WNGOsklSc5KcnJ3n7nB2QAAAAAA4Gpm2an9nST3SPLTmYTszuSc7XtkEskfnOSTVfXz8xoSAAAAAACSGXZqJzk3yclJntzdVyRJVR2S5M+SXJjkIUleleRPkvzCnOYEAAAAAICZdmo/NslLdwftJJn+/PIkT+juTvLnSf7TfEYEAAAAAICJWaL21iS3XWH9tkm2TH++JCufuw0AAAAAADOb5fiRv0nymqr64yQfma7dIclzkrxh+vvdknxm4+MBAAAAAMBVZonaxyb5epJnJrnRdO3rSV6SyTnaSfLPSf7HhqcDAAAAAIAl1h21u/vyJMcnOb6qDp+uXbDsmq/MZzwAAAAAALjKLDu1r7Q8ZgMAAAAAwGaa5UGRAAAAAACwEKI2AAAAAADDELUBAAAAABjGXKJ2VR0xj/sAAAAAAMCerDtqV9WzqurBS35/U5JvV9XXquqn5jodAAAAAAAssXWG9/x2kt9Ikqo6JskxSe6b5NeTvCjJveY2HQCwIdt27Fzzml0nbN/vPwMAAAB2myVq3zjJ2dOf75fkTd39z1W1K8mH5zUYAAAAAAAsN8uZ2uclufn05/skOXX6cyXZMo+hAAAAAABgJbPs1H5bkpOr6gtJfijJKdP12yc5a16DAQAAAADAcrNE7WOT7Mpkt/Yzu/ui6fqPJHnlnOYCAAAAAIBrWHfU7u7LkvzpCusvmctEAAAAAACwilnO1E5VPbyqPlBV51TVLaZrT6uqB8x3PAAAAAAAuMq6o3ZVPTHJiZmcpX1Erno45PlJnja/0QAAAAAA4Opm2an9lCSP7+7jk1y+ZP2jSW43l6kAAAAAAGAFs0Tto5J8fIX1S5PcYGPjAAAAAADA6maJ2l9KcvQK6/dJ8rmNjQMAAAAAAKvbOsN7Tkzyiqq6bpJKcseqemiSZyd53DyHAwAAAACApdYdtbv71VX1vSR/lOT6SU5Ock6Sp3b3G+c8HwAAAAAAXGmWndrp7pOSnFRV109yaHd/Y75jAQAAAADANa07alfVUUm2dvcXuvviJBdP12+d5LLu3jXfEQEAAAAAYGKWB0W+LsldVlj/uelrAAAAAACwKWaJ2rdP8sEV1j+U5OiNjQMAAAAAAKubJWp3ksNWWL9hki0bGwcAAAAAAFY3y4Mi/yXJs6vqod19eZJU1ZYkz07ygXkOBwCw27YdO9e8ZtcJ233OPv4MAACAfW2WqP2sTML2mVX1/unaLyY5PMk95jUYAAAAAAAst+7jR7r7s0l+MsmbkhyZyVEkb0hy2+7+9HzHAwAAAACAq8yyUzvdfU6S58x5FgAAAAAA2KOZonZVHZHkjpns1L7abu/ufsMc5gIAAAAAgGtYd9SuqvsnOSnJoUkuSNJLXu5MjiIBAAAAAIC5W/eZ2klenOSvkxza3Ud09w8s+frBOc8HAAAAAABXmiVq3zTJy7r74nkPAwAAAAAAezJL1H5Xkp+d9yAAAAAAALCWWR4UuTPJi6rqx5N8KsllS1/s7n+ax2AAAAAAALDcLFH7r6bfn7fCa51ky+zjAAAAAADA6tYdtbt7liNLAAAAAABgwzYUqKvquvMaBAAAAAAA1rLuqF1VW6rqD6rqa0kuqqpbTtf/sKoeO/cJAQAAAABgapad2s9N8qgkz0zy/SXrn07yuDnMBAAAAAAAK5olaj8iyRO6+6Qkly9Z/2SS285lKgAAAAAAWMEsUfumSc5a5V7X2tg4AAAAAACwulmi9meT/OIK6w9M8vGNjQMAAAAAAKvbOsN7XpDk9VV100yi+K9V1W0yOZbkfvMcDgAAAAAAllp31O7uf6yq+yd5XpLvZhK5P5bk/t397jnPBwDAfm7bjp1rXrPrhO3DfA4AALB/m2Wndrr7/TITdMUAACAASURBVEmOmfMsAAAAAACwR7OcqQ0AAAAAAAux7p3aVXVFkl7t9e7esqGJAAAAAABgFbMcP/Kry36/VpLbJ3lkkuM2PBEAAAAAAKxipgdFrrD8lqr6TJIHJ3nNhqcCAAAAAIAVzPNM7Q8luecc7wcAAAAAAFczl6hdVddL8rtJvjaP+wEAAAAAwEpmeVDkebn6gyIryWFJLk7ym3OaCwAAAAAArmGWB0Uem6tH7SuSfDPJh7v7vLlMBQAAAAAAK5jlQZGv24Q5AAAAAABgTXsVtavqJ/f2ht19xuzjAAAAAADA6vZ2p/YnMjlypNa4rpNs2dBEAAAAAACwir2N2kdt6hQAAAAAALAX9jZq/0OSe3b3eVX1vCR/2t0Xb+JcAAAAAABwDYfs5XU/luQG05+PS3Lo5owDAAAAAACrW8+Z2q+tqg9kcq72M6rqopUu7O4XzGs4AAAAAABYam+j9qOS/Nck98vkYZD3TfL/Vriuk4jaAAAAAABsir2K2t19ZpKHJElVXZHJ+drf2MzBAABgX9u2Y+ea1+w6YbvPAQCABdrbndpX6u69PYcbAAAAAADmat1RO0mq6tZJ7p7kyCx72KQztQEAAAAA2CzrjtpV9fgkf5HkW0nOzeQc7d2cqQ0AAAAAwKaZZaf27yd5bnf/ybyHAQAAAACAPZnlfOwfSPLmeQ8CAAAAAABrmSVqvznJveY9CAAAAAAArGWW40fOSvKHVXWnJJ9KctnSF7v7ZfMYDAAAAAAAlpslav9/9u48XLarrhP+9weBhDmIErABmQVEQLAZlGbUFo2g2CrI6wBoA4ovk7RCyxTwldhqgBZsBBmirQgBGsQwNCjzIAIiCoigRMYQICEEMgC56/1j7ZNUTs659+bWrjp3FZ/P89RzT+2qu3971bCH71619oOSfCXJnafbopZEqA0AAAAAwEpc4lC7tXa9VSwIAAAAAAAcyKGMqQ0AAAAAAHvioHpqV9UJSR7fWvvq9PeuWmuPmmXJAAAAAABgm4MdfuR7klxm4e/dtOUWBwAAAAAAdndQoXZr7a47/Q0AAAAAAOtkTG0AAAAAAIYh1AYAAAAAYBhCbQAAAAAAhiHUBgAAAABgGAcValfV+6rqqtPfT6iqy692sQAAAAAA4OKOOMjn3TTJFZKckeSJSZ6d5OxVLRQAADCG6z7m5AM+55Tjjx2mDgAAh7+DDbXfn+QFVfW2JJXk0VX1lZ2e2Fp78lwLBwAAAAAAiw421L5/kuOS/GiSluSHk3xjh+e1JEJtAAAAAABW4qBC7dbaR5LcN0mqal+Su7fWTlvlggEAAAAAwHYH21P7Aq21g7q4JAAAAAAAzO0Sh9pJUlU3SPKI9AtIJsmHkjyjtfavcy0YAAAAAABsd4l7XVfVD6WH2LdN8oHpdrskH6yqH5x38QAAAAAA4EKH0lP7+CRPa609ZnFiVR2f5HeSvH6OBQMAAAAAgO0OZXzsmyZ53g7Tn5/kZsstDgAAAAAA7O5QQu3PJ7nVDtNvleS05RYHAAAAAAB2dyjDjzw3yXOq6vpJ3jFN+/4kv5HkhLkWDAAAAAAAtjuUUPspSc5K8mtJnjpN+0ySJyX5n/MsFgAAAAAAXNwlDrVbay3J05I8raquNE07a+4FAwAAAACA7Q6lp/YFhNkAAAAAAKzToVwoEgAAAAAA9oRQGwAAAACAYQi1AQAAAAAYhlAbAAAAAIBhHNKFIqvqmUme0Fo7feblAQAA2DPXfczJB3zOKccfO0SdTWoLAMCig+6pXVXXWrh7vyRXnKb/Y1Vde+4FAwAAAACA7S5JT+1/rqovJnl7kqOSXDvJJ5JcN8ll5l80AAAAAAC4qEsypvbRSX4qyXun//fqqvqXJEcm+aGqOmYFywcAAAAAABe4JKH2ZVpr726t/X6Sc5J8T5IHJDk/yQOTfLyqPrKCZQQAAAAAgCSXbPiRL1XV+9OHH7lsksu11t5eVd9Icp8kn07yH1ewjAAAAAAAkOSS9dT+D0l+K8l56WH4e6vqrekB962TtNba2+ZfRAAAAAAA6A461G6tfaG19qrW2mOTnJ3eK/sPkrQkv5fkzKp682oWEwAAAAAALllP7e3ObK29JMnXk9wtyfWS/OEsSwUAAAAAADu4JGNqL7pF+hjaSfLvSb7eWjs1yYtnWSoAAAAAANjBIYXarbVPLvx98/kWBwAAAAAAdrfM8CMAAAAAALBWQm0AAAAAAIYh1AYAAAAAYBhCbQAAAAAAhrGnoXZVPbaq/q6qzqqq06rqFVX1nduec1RVPauqvlhVX6mql1XVMXu1zAAAAAAA7J297ql95yTPSnL7JD+Y5DJJ/m9VXWHhOU9Lcs8kPzU9/9uTvHzNywkAAAAAwGHgiL0s3lq7x+L9qrp/ktOS3CbJW6rqKkl+Mcn9Wmt/Mz3nAUk+XFW3b629a82LDAAAAADAHtrrntrbXWX69/Tp39uk995+w9YTWmv/nOQTSe6w0wyq6siquvLWLcmVVri8AAAAAACs0Z721F5UVZdK8vQkb2+t/dM0+RpJvtZa+9K2p39uemwnj03yxNUsJQAAAHvhuo85+YDPOeX4Yw/7GgDA8g6nntrPSnLzJPddcj5PTe/xvXW71pLzAwAAAADgMHFY9NSuqmcm+dEkd2qtfWrhoVOTXLaqjt7WW/uY6bGLaa2dl+S8hXmvYIkBAAAAANgLe9pTu7pnJrl3kru11j6+7SnvTfL1JHdf+D/fmeQ6Sd65tgUFAAAAAOCwsNc9tZ+V5H5JfizJWVW1NU72ma21c1prZ1bV85KcUFWnJ/lykj9I8s7W2rv2ZpEBAAAAANgrex1q//L075u2TX9AkhdOfz8yyb4kL0tyZJLXJfmVNSwbAAAAAACHmT0NtVtrBxzwurV2bpKHTjcAAAAAAL6J7emY2gAAAAAAcEkItQEAAAAAGIZQGwAAAACAYQi1AQAAAAAYhlAbAAAAAIBhCLUBAAAAABiGUBsAAAAAgGEItQEAAAAAGIZQGwAAAACAYQi1AQAAAAAYhlAbAAAAAIBhHLHXCwAAAADfTK77mJMP+JxTjj92iDrragsALNJTGwAAAACAYQi1AQAAAAAYhlAbAAAAAIBhCLUBAAAAABiGUBsAAAAAgGEItQEAAAAAGIZQGwAAAACAYQi1AQAAAAAYhlAbAAAAAIBhCLUBAAAAABiGUBsAAAAAgGEItQEAAAAAGIZQGwAAAACAYQi1AQAAAAAYhlAbAAAAAIBhCLUBAAAAABiGUBsAAAAAgGEItQEAAAAAGMYRe70AAAAAAPtz3cecfMDnnHL8seqsuQbAXtFTGwAAAACAYQi1AQAAAAAYhlAbAAAAAIBhCLUBAAAAABiGUBsAAAAAgGEItQEAAAAAGIZQGwAAAACAYQi1AQAAAAAYhlAbAAAAAIBhCLUBAAAAABiGUBsAAAAAgGEItQEAAAAAGIZQGwAAAACAYQi1AQAAAAAYhlAbAAAAAIBhCLUBAAAAABiGUBsAAAAAgGEcsdcLAAAAAMCYrvuYkw/4nFOOP3aIOpvUlnXV2aS2rKvOutqy6fTUBgAAAABgGEJtAAAAAACGIdQGAAAAAGAYQm0AAAAAAIYh1AYAAAAAYBhCbQAAAAAAhiHUBgAAAABgGEJtAAAAAACGIdQGAAAAAGAYQm0AAAAAAIYh1AYAAAAAYBhCbQAAAAAAhiHUBgAAAABgGEJtAAAAAACGIdQGAAAAAGAYQm0AAAAAAIYh1AYAAAAAYBhCbQAAAAAAhiHUBgAAAABgGEJtAAAAAACGIdQGAAAAAGAYQm0AAAAAAIYh1AYAAAAAYBhCbQAAAAAAhiHUBgAAAABgGEJtAAAAAACGIdQGAAAAAGAYQm0AAAAAAIYh1AYAAAAAYBhCbQAAAAAAhiHUBgAAAABgGEJtAAAAAACGIdQGAAAAAGAYQm0AAAAAAIYh1AYAAAAAYBhCbQAAAAAAhiHUBgAAAABgGEJtAAAAAACGIdQGAAAAAGAYQm0AAAAAAIYh1AYAAAAAYBhCbQAAAAAAhiHUBgAAAABgGEJtAAAAAACGIdQGAAAAAGAYQm0AAAAAAIYh1AYAAAAAYBhCbQAAAAAAhiHUBgAAAABgGEJtAAAAAACGIdQGAAAAAGAYQm0AAAAAAIYh1AYAAAAAYBhCbQAAAAAAhiHUBgAAAABgGEJtAAAAAACGIdQGAAAAAGAYQm0AAAAAAIYh1AYAAAAAYBhCbQAAAAAAhiHUBgAAAABgGEJtAAAAAACGIdQGAAAAAGAYQm0AAAAAAIYh1AYAAAAAYBhCbQAAAAAAhiHUBgAAAABgGEJtAAAAAACGIdQGAAAAAGAYQm0AAAAAAIYh1AYAAAAAYBhCbQAAAAAAhiHUBgAAAABgGEJtAAAAAACGIdQGAAAAAGAYQm0AAAAAAIYh1AYAAAAAYBhCbQAAAAAAhiHUBgAAAABgGEJtAAAAAACGIdQGAAAAAGAYQm0AAAAAAIYh1AYAAAAAYBhCbQAAAAAAhiHUBgAAAABgGEJtAAAAAACGIdQGAAAAAGAYQm0AAAAAAIYh1AYAAAAAYBhCbQAAAAAAhiHUBgAAAABgGEJtAAAAAACGIdQGAAAAAGAYQm0AAAAAAIYh1AYAAAAAYBhCbQAAAAAAhiHUBgAAAABgGEJtAAAAAACGIdQGAAAAAGAYQm0AAAAAAIYh1AYAAAAAYBhCbQAAAAAAhiHUBgAAAABgGEJtAAAAAACGIdQGAAAAAGAYQm0AAAAAAIYh1AYAAAAAYBhCbQAAAAAAhiHUBgAAAABgGEJtAAAAAACGIdQGAAAAAGAYQm0AAAAAAIYh1AYAAAAAYBhCbQAAAAAAhiHUBgAAAABgGEJtAAAAAACGIdQGAAAAAGAYQm0AAAAAAIYh1AYAAAAAYBhCbQAAAAAAhiHUBgAAAABgGEJtAAAAAACGIdQGAAAAAGAYQm0AAAAAAIYh1AYAAAAAYBh7GmpX1Z2q6lVV9ZmqalX149ser6p6clV9tqrOqao3VNWN9mp5AQAAAADYW3vdU/sKSf4hyUN3efzXkzwsyUOS3C7JV5O8rqqOWs/iAQAAAABwODliL4u31l6T5DVJUlUXeaz6hEck+a3W2iunaT+f5HNJfjzJX6x1YQEAAAAA2HN73VN7f66X5BpJ3rA1obV2ZpK/TXKH3f5TVR1ZVVfeuiW50sqXFAAAAACAtTicQ+1rTP9+btv0zy08tpPHJjlz4fap+RcNAAAAAIC9cDiH2ofqqUmusnC71t4uDgAAAAAAc9nTMbUP4NTp32OSfHZh+jFJ3r/bf2qtnZfkvK3728fqBgAAAABgXIdzT+2Ppwfbd9+aMI2Rfbsk79yrhQIAAAAAYO/saU/tqrpikhsuTLpeVd0qyemttU9U1dOTPK6qPpoecj8lyWeSvGL9SwsAAAAAwF7b6+FHvjfJGxfunzD9e2KS+yf5H0mukOQ5SY5O8rYk92itnbvGZQQAAAAA4DCxp6F2a+1NSXYd9Lq11pI8YboBAAAAAPBN7nAeUxsAAAAAAC5CqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhNoAAAAAAAxDqA0AAAAAwDCE2gAAAAAADEOoDQAAAADAMITaAAAAAAAMQ6gNAAAAAMAwhgi1q+qhVXVKVZ1bVX9bVbfd62UCAAAAAGD9DvtQu6ruk+SEJMcluXWSf0jyuqq6+p4uGAAAAAAAa3fYh9pJHpXkua21F7TWPpTkIUnOTvLAvV0sAAAAAADW7Yi9XoD9qarLJrlNkqduTWut7auqNyS5wy7/58gkRy5MulKSfPnLX17hkh6+9p139gGfM8drs0l1Nqkt66qzSW3ZtDqb1JZ11dmktqyrzia1ZdPqbFJb1lVnk9qyrjqb1JZNq7NJbVlXnU1qy7rqbFJbNq3OJrVlXXU2qS3rqrNJbVlXnXW1ZVQH2/Zqra14UQ5dVX17kk8n+b7W2jsXpv+PJHdurd1uh//zpCRPXNtCAgAAAAAwp2u11j6924OHdU/tQ/TU9DG4F31LktP3YFkOR1dK8qkk10py1uB1Nqkt66qzSW1ZV51Nasu66mxSWzatzia1ZV11Nqkt66qzSW3ZtDqb1JZ11dmktqyrzia1ZdPqbFJb1lVnk9qyrjqb1JZNq7NJbVlXnU1qy2iulOQz+3vC4R5qfyHJ+UmO2Tb9mCSn7vQfWmvnJTlv2+Rv3j7721TV1p9ntdZW9rqso84mtWVddTapLeuqs0ltWVedTWrLptXZpLasq84mtWVddTapLZtWZ5Pasq46m9SWddXZpLZsWp1Nasu66mxSW9ZVZ5Pasml1Nqkt66qzSW0Z0AFfh8P6QpGtta8leW+Su29Nq6pLTfffudv/AwAAAABgMx3uPbWTPpTIiVX1niTvTvKIJFdI8oI9XSoAAAAAANbusA+1W2svrqpvS/LkJNdI8v4k92itfW5vl2xY5yU5LhcfomXEOpvUlnXV2aS2rKvOJrVlXXU2qS2bVmeT2rKuOpvUlnXV2aS2bFqdTWrLuupsUlvWVWeT2rJpdTapLeuqs0ltWVedTWrLptXZpLasq84mtWXjVGttr5cBAAAAAAAOymE9pjYAAAAAACwSagMAAAAAMAyhNgAAAAAAwxBqAwAAHEBV1V4vAzC2qrr0Xi8DsDeq6mFVddT093XsVyxPqA0c1qrqygd7m6nek6vqrlsbm1Wpqp+vqpvtMP2oqvr5Gev8zH4e+9256uynxk+uugZ7r6qutZ/Hbr+CelevqptX1S0WbzPMt6rqRlX1XVV1xBzL+s2gqn62qq6w18sxmqo6sarutOIab562N5dbZZ1VOpjXqKr+YMZ6/22X6ZdO8udz1YHtquqIqrriXi/H4Wqd+7T7O66oqhsuOftPV9XxVXXjJeez56rqyL1eBhjMCUm21i8fT/Jte7gsG6Faa3u9DMysqs5IclBvbGvtW1a8OLOZDpgfk+TuSa6ebSdlWmvXn6nO1VprX5z+vnaS/5rkckn+srX21plqXCnJjZN8pLX2laq6dZJHTHVe0Vr7syXnf7ckz0xy+9bal7c9dpUk70jykGXbc7CftWU+Z1W17yBqVC/Tlu75UFWvT3KHJEck+bskb07ypiRvb62ds+z8F+rsS/LVJPdvrb1sYfoxST4zR1um+X0pyc+01l6zbfrTkty3tXbNJed/RJKbJPlaa+1fFqb/WJInJ7lJa22WHd6qOj/JW5L8l9ba6QvTl37NLkkg2lr7wKHWOchluWqSe7bW/mSVdeZUVR9KcsfF92Wa/v1JTm6tHT1TndskOTHJTdO/90lfPyy9Dqiq6yX5yyRbJ5s+lf5Ze8+hL/GOdS6X5O6ttb+a7j81yeJ35Pwkj2+tnTtTvUryk0nump23nT8xQ43PZ9pOJvnfSV7XWjt/2fnuUOfSSe6f3fcD7jZjrRtl99fsyTPVeEWSH0ny70lekOTE1tqn55j3Qo2nJ7lf+mfsJUme11p718w1jknye7nwfblIr6Nlt2fTduwurbX37/L4HyT5hdbaXCe3T0vy2Nba8xamXTrJXyS5eWvtpjPVWeU27WEH+9zW2v9cos51DrLGJw61xrZ6K1+fTXWOSnKLXWr85Qzzv2eSq7XWXrgw7TeTPD59//NvktyntXbGsrWmed89u683HzhHjXXUWfU+7bZ5vjXJD7TWzts2/TuT/HVrbdeT+Qcx78cn+YUk10s/Jntekpe01s5eYpF3qnPjJEe31t69MO3uSR6X5Arpx5y/vWSNc5O8M8kbp9u7WmtfX2aeO9RYy/psh7or+TxX1b0O9rlzrG/2sxy3TPK+GY85V7ovsK3WytdpVXV0ktvuUuOQj9Gq6hNJnprk1emh9vcm+cJOz51r27np9ELaTI/Yi6JV9fwkb26tnbht+pWTPH2GFcwfJ7lzkj9N8tkcZHB/sKrqu5O8Ksm1q+qjSe6b5LXpG/19SR5ZVT/ZWnvFknXulOSvklwxyRlTr4OXJvl0epjxE1V1+dbac5co84gkz90eaCdJa+3MqvqjJI9KsmxIv/hZqyT/K8kTkpy25HwX3XXGeR1Qa+0Hp6D2dknulP6Ze1iSI6vq71prd5yx3BOT/GlVfXdr7UkzznfR/5PkRVX1o621tyUXBAA/kSVf26q6efpn+drT/Vcm+eX04OTmSZ6b5NhlamwvmR7MvKeq7tla++C2x5bx/lwYju7kguA0yap/Nnqd9IBr6VC7ql6dfgB45nT/MUme3Vr70nT/akne2lq72K8GLqF3Jfm/VXXX1tpZ07zvlL5OfdKS8170/CT/kuQXk3wu824Hfjd9v+hnk5yb5NFJ/ijJbWaskfQD2WPTvztJ8qtJPphk66TZTZJ8JsnTZqr39CQPTj/YnPs123LNJPdI8jPp3/+zq+qkJH/WWnvHjHWekR5qn5zkn7KatqSq/mv69uwLSU7dVqeln7BbWmvtx6vq25L8XPrn4riqekN6wPHKOYKB1tojqurRSe411XhLVX0s/bv0p621zy1bI8kL09dbT8kK9s/S9/9eW1V3bK19bPGBqnpGkgdk3m3NsenrszNbay+d9glekv7dnHOfZJXbtEce5PNakmVCoI8v/L14onFx2pzbzZWvz6rqHunb32/d4eG52vKo9H3/rZrfl75eeUKSDyf5/9ID7kctW6iqnjjN9z1ZzfdznXVWtk+7g68k+T9Vda/W2jemWjdNP+HwkmVm3Fp7SpKnVNVd0tdfz0zyjKp6SZI/bq397VJLfqHfSfKPSd6dXHDy/lXpx38fSPLYqjq7tfb0JWo8JMldkjwwfX/vnKp6R/rr9MYkfzfDSe51rc8usOLP88FmCes45phz6IsXZrX7AknWs66ZTjz+WXpe8+VcfD9wmWO030ryB+nf+5beie5ii5D1vP+bobXm5jbLLT34/Wr6xuRSC9OPSXL+DPP/UpLvX+HyvyZ9Q//9SZ6d3kvveeln5i6V5FnpZ5+XrfOWab7/IX2H9Ywkv73w+OOSvH/JGv+e5Kb7efwmST6xgtfwrCTXX9H7c0T6Buxaq/oM7FDzxukHTycl+XqSL8w4Q6rn/AAAIABJREFU733pZ35vn75Bfml6T8dZvi/bat0vyenp4dwfpp9AufEM8z05yRuS/Gj6hn9f+sHYo5NcbgXvx/np4dkz0ncwfmyavvRrluQ7DvY2QzuufIDbHef6DEyv2dUX7n958Ts64/r5Uklenv6rhiPTDy7PSvLwmT8DZyW54dyfrWnep6b3Nt+6f83p9bvCzHXemt4Tf7FNi+/JzyZ554z1Tk/yI6t4zXapd/n04OHkJOcl+dcZ5/2FdbRl2ob+xrpes4W6t04/0DknyefTT2zcaOYaV0/fzzgnydfSD67vtuQ8z0pyqxW/Ns9PckqSb1+Y9vT0/c67rqDe3ab15b2SvDL9xNMxM9dY2TZtXbck35jelyel72PccqfbjPVWvj5L8tH0ff5Z3+9tNU5L8j0L909I8tqF+z+S5KMz1fpskp9bw2dhXXVWsk+7Q53LJXl7khenB0w3Tz+RcsIKal0xyS8leVv6vvQHkzxqhvl+MskdFu5f5BgzvYPAUsec2+pdPz3cPnHajp4/rdtOXvXnYgXvyVo+zytuw8sPcPvrObc169gXWNd7k96B5ulJLr+i+V9pWqfsm/Y3Vrrt3PTbni+A2xre5OQG6WeEXpQp3Ejyw0m+a+Y6+9LP1H4syeuTXHWaPldo8vHsJ6idYf5fSHKL6e8rTu25zcLjN0nypRnqfCl9SIYkuey0wb/lwuM3THLWkjXOzX6Cn6nGOSt4DVcWai/M/7qrmv9U40HpY2Z+evpM/J8kD582LjVjnQvCxvSz2u9P8vfpPcRnP5hN8ivT5+KT+/tsXMJ5nra185LkKtN3ZmU7GdP8t16zB03teVySa6ziNVtxO87fz23fXO1ZfM2m+9sD1NnCk2l99vr0g8CzkvzqCl67V6T/VH9V78sx26Z9Jcn1Zq7z2cX1WHp4uXj/xknOnLHex7e2Oeu6pfdw/NX03tRzHjB9JisIL3aoc5GTP2t6za6Z5DeS/PP0uTsx/aTh15M8cqYat03vgX5GeuBwXHov6LOT/N4S8/1QFgK6Fb0+WyfOPpTkaukh4NnpQ/msquaPT6//B5J86wrmP/w2bVrWrc/tqek/PV/lvvrK12fT9/8GK65xTpLrLNx/d5L/tnD/O5J8daZaX1x1e9ZZZ6o1+z7tLnWOTt8/Pyk90P7dNbTt2Om1nOPY+Zwk1164/9dJnrJw/waZ4dh2l9rXS88fzpypLZdadh6XsN7aPs871D56pvl8PX2IixfscnvlzPtoK98XWNd7k37CfFUd9R6W5Kjp71/ICjqCfbPdDD+y4arqzuk9kN+ePpTCb6YHUbdMPzs790XcPpQeyr0sybunMaNO3/9/OWiPT/LkqvqFNvOYY5NvSd8hT+vjXH81/cBvyxnpZ9WWdeVMr0lr7WtVdXZ6ALTlrPSebsv4dPrZv4/t8vgt0oOV0fxN+nAgp6ywxrPTQ6bfT/KHrbWvrKjOBT/3aq19Yvrp6Z+lh4LLzbjqhF0e+nyS9yX5lZoutNxaW+anrd+aHjKl9WFtvpo+DMXKtdaeMw0TdFL6um0pax7f7qz0nxbv9vPSG6UPe3FY22Uc8ieln0D93+nDHNwimXUc8l9KcuI09M0/pe+wX2DJ96YluWJVLY6dvy/JlWrhglFth2GdLqGjszCGdmtt+wViLpWLjrG9rCcleWJVPbDNeF2A7arq8knund5L++7pYcOLMu9+xu8neXhV/WqbjgZW5KQk/zl9e7AyVXWZ9J7AD5jqfSC9Z9Cfb33Oqure6b2UD2k4mqq6evrwJg9IX7e8Kn2YmNdtvYZV9cL04dYefYhNeUSS46vqwa21Uw5xHvvVWttXVfdN/wXAh9OHhrtXa+2v55h/Vb18l4c+n94Z4TkL281Zxm1etIJt2m77ATvVPuT9gNbaqelDHPxOVd0x/XP2t9N1Fp6XPob7vkOd/w6elNWvz16a3knnX1c0/6Tvp980ySeqXxjylrnoEAtXSz9pM4c/Tu/d/JSZ5rfWOmvcp93p4pD7ktwnfd/8ZelDhlx5qrXsvsBi3csn+en0788d0z97c1z48vT0E6afrKpLpY/du/h6XjYzDT8xja9/1/Tvzl3SjxHelX6i680zlPh6VV2ztXbaVO93kzy1bbuWy4zW8r2pqt9Ickpr7cXT/ZOS/Jeq+mz6r1L+YYnZfzjJy9rC9SG21b5V+q9t57LyfYHJOt6b16V/X/5tBfM+If0aHeem79+9JhcOQcghEGpvvuOTPK61dkJVLQanf5Pei2pOLUlaa1+sqh9IPxh8Z5IdryJ/CH4t/Yzy56rqlFw8zLj1DDW2HySv4qC55eLjMs1d59XpO16vbdsuNlb9ImXH5cLxXEfymvSN5XcneW/6WdQLzBA2Jn1cvjulj6l+XFX9ffqQCm9K8rYZT6gcl94bL0kyzffeVXVclj+g/Z5dpn8s/aTK1uPLfu5aeuB3bi4c++ty2w8KZtzx3/op49Z831hVt08PaZa1zvHt3pckrbUdd/KnCyHNNcbdTuuXudY3O41DvnX/wek9D+ceE+4O6UNE/fAOjy1bp9J/brh92t8v/D1HWz6VftLxI7s8fovpOXN5SXqIedqqtp1V9RfpB0ZnT/We0lp757Lz3cEd0w+af7iqPpiLt2WusPFj6dvQ26ePR7q9zlwXovps+kmMFyW5bdv5QohvTA9VD9Wn0gOS5yd5YWvt8zs85wPZeUzHg/Xi9JPx/zqdqN/+ei11UfJtFwl7U5L/lH7AebOquuB6AEu+L2fuMv11S8zzQFa5TdttP2C72fY/Wx/j+G1V9d/TP9PPTg8C5wydVr4+Sz8+Oqmq/lNW9/0/KcnTq+q304caOTUX7RTwvdl9G3FJHZXkQdOx2Qdy8fYsPW73iuusa5826evaneZT6WNHPzgz7tdMHVoemOSn0nOZl6ZfKPoty8578qYkj6+qX5lqXGqatuVmWbKj0HRNrbukdw57e/oQa89JH0v7G8vMe3upbfcfnP7Lo1WF2uv63jwkvTNAquoHk/xA+jVKfjr9xMZ/XmLe700f1mzHUDt9iLg5L0S40n2BBet4b05O8rvTPsZO24FlMofPpJ+4eHX65/pa1S9OfDHNhSIPSq22owt7raq+kuS7W2sfn0LtW7bW/q2qrpvkn1trO36BDrHWviTX2DqDOk17VHoPjku1Ja94O10UYFetteOWnP++9NB06yrX90wP/7eC0yOT3GOGduxL72G4taG/RfrPNr823T8ifWiYZa56f0x6cHZ++kUItnaMb5Lkoek7YrduS14gaofeEw9N76F5kYPDuTb802u3m7bse7NDvaukHzz/VPpB1L65vjPTRfTesX2Hb7og1ffNuEO7MtP7sbgRqZ3uz/2+7LAcR6UPG/Hvq6wzl+kidJfb7cB4+v4+ZNl12jSvla3Xquo7Dva5c703U4jxV+mh6RwXuFuc950P5nm7nYy4BHWekX7QcptdTjq+J8kbWmsPX6bOwjxfkh4EvzQ7XFhtps/Zn6X/0uR1bfkLQu2vzgv293hr7QEz1fn4/su0689U5+eSnLT9czCX6t0X75jkPSvupX//7CdQatsuIH4I89/f+7FQZp73Za+Ntk3bsi2g+0j6iZTnzNlTe03rs19MD+TPTf+Z+0U6oszxOZvW9X+Uvk0+NcmDWmtvXXj8jeljbP/ODLXeuJ+HW2vtbsvWWGedVTrY/YBkuX2Bqvr19F7ZN07f5j8vyYvadKHtuUzH+69P7xR2fpKHtdb+18Ljr0jy8dbawV6Icaca+9KD0WelD2/y96v4JdX2nGEx15i71jT/dX1vzkkfVu2T0/7hUa21B1fVjZP8bWvtqkvM+8gkl56xQ9aB6v3C/h5fdl9goc7K35tVZg5V9aD066fsr4PxWo6hN4VQe8NV1aeS/HRr7R3bQu17p4+feIMZa905ydt3COl+IP0Cj0vvaK7SgQ6Wtyx70HygcH6hzrIh/Xekn8H+oVz0ivSvS/LQ1trBHCQeqMb+NipbhtiRXVRVV0sf5uQu0+270oefeWtr7d4z1Tg/yQU/o9tW+7Q5NmLVf9p+Tvq41/+07Px2mP9aQsC9VFVHrSpwWod1rdfWZdqO3aq1tsqfha/UdNLi/eknMp+ZC3uHf2d6D8Ej0scknCW0rz4s0A9NvSg5gCkIvk76enjon4NOPzc/N/1E+Uf3enlGMp1gvkt6GPTnrbWzqurbk3y5zTwsWVXdJn0oiiT5UGvtfXPOf6HODdPb85bW2jlVVcuGT1V1zSQ/nx7QXTX95NbzV7HPMdVb+fqsqk5Nv+j98XMG8ixv6mxy6bZtyImq+pYk35jrl4HT9/+/p3+W5/zl1Nb8P5/eCeh5q/quLNQ6Iv045vOttc9se+yWST7VWvviEvP/zlx02JEj0y94+eb0XuHvm+N7tO5Qe12q6jNJfnLKaj6S/gv7k6bX9e9aa9uHxGEDVNWV0q+d8IH0ji47fgfbcsPPfNMQam+4qvq99DGufyr9wPnW6RcG+5Mkf3K4B80sr6qumn5hyEq/kvoZB/gvQ1hV2FhV/5h+cHlGkrek75C9uc03JvBWna2L0n1+2/Qbp/eqm2Unpqr+Lcm9R90oVtXp6T0YvlBVZ2T/vQFn+VlbVV06/WDmIenryxtPJwOfkj7u3W4/4/umVVWPTfK51trzt01/YJJvm6O32TS/E9NPLv3xHPPbK1V1vfSTjj+Yi550fH2SX5nzIK2q/jn95Pas67Ad6tw5fUzmC8K59ItqvXX3/3X4WWcQXFVXSPKY9DHIr57+0/ALzNQj9INJfrG1trLrHVTVm9N7Gp40+omA5IJOAa9NP7lxZC7cBjwjyZGttYfMVOfq6eNq3iUXDjFzdPqQM/fdvn+wRJ2rpQ/bcdf09cyNpvY8P8kZrbVfW2LeX08fH/rEJH+ZbT/R3jLX+mcd67Npv+M/jnzydFNV1WuSvKq19ofbpj8kfYz9H5mx1lnpv3Y+Za55Lsz7Mq21Hb8ro6s+XMOd09c3d0ofKuJtrbWlxm6ejpuekwvHml/pr4PXpaqemT5820fTh9K5buvX9rpvkl9v8wyptDJVdeV24TVA9nvsOtdJp00y9W7/i9baeQd8MrsSam+4qrps+s+B7p8+5MQ3pn//PMn924w/E552jnfVWnvgkvO/dPpFVH46/UDjstvmP9c4TRym1hE2VtVD00PsVfUy2roY1Y+lHzQvbsQunT4czUdaa/eYqd4vpo8T/nPbe7aMYHFjv8aftT0h/WrUT0jy3CQ3nz5n90nyiNbaHeaos0mqDwtyv9baO7ZNv136+3e9mer8ZvqFaE7Oasc6Xoupd9kNp7sfW8V3tKqOTfL/pg9pc8rc859q/GySFyR5efqYmkkf+/ze6fsaf77EvN+X5O6ttTOqX+Ngfye2Zjn4W0cQPNV5UfrB/5+mj6+9fSiFZ8xQ455Jfj3JL69wu/b09Is2HZkenj5v1a/dKk0/yT8r/YLqX8yFv3K8S5LnttZuNFOdFye5fpKfb619eJp2s/SA+GOttZ+Zqc6fpJ80+aX0C4dtteeHkpzQWvuuJea92ANz6/O7fezb2X5Cvab12dPSe7X+9irmvw7Tvub9W2tfrt0vgppkuWsRrKvOQr3T03/9++Ft02+S/mvhqy1bY2Ger0zy8rn2Lb+ZTL9Iu+t0u2+SKy67DqiqN+XA46bP+uvgqvre7J47zHINj+lXtQ9Pcu306178/TT9kUnOOtw7cSz+8rguPizlBU/L8kN2rHVdM9W8Qvo+2k7v/2zHG1V1dPpF1W+Q3hnk9Kq6dXpnoU/PVWeTuVDkhmutfS3/P3vnHSZLVW3x3+ICEoUnioBKkPAQkCTRC4KAgKASRBSQIFyCgazkoICSMygqSbIoOecoIiAIkoNkVIKEh2RY7499+nZNTffM3KlTNXeGWd8333RX95zd01196py9114LNk9JvwWAaQitqzrYR2XNp8lSzOkJDdeq2JtYkB8K7Af8HJgdWBPYJ8P4o5j4sTuRbNyJSDa2cC+R6Kqc1LZ9bOt2akOnantuCS1GgYhNc5HV9g5hFPTb8h9VwI+IpNlzkp6kt7nmRM0AKG4mGtxYbEToW14j6bjC8bsJXfpR9MZMRFKujBeAmTPGGUcYrC6Xfoow0TI+bJCS2LfVHOY06jfu2Z1gFB1eOHaUwldjT6KQPlhcQLv4N1BD16rYhTAIqi0RnPBVYHXbf+r3mYPHKcTnf7ekd+h5zcny+dveTtKPgW8Q1+gbJT1KaCqf6sz69w1gWcLb4p20DGjhCeBTGeOsCqxUTNDZvj8V16/MGGdlQrLjmdL/8wjR/lwFWQqWE4Am5rMxwE4p6V+nQVydeJV2cqmbCepwitPCR+icv5gMmDJzrCbM6UcEUtfJ8rRlSOYh9jS3AYcT3SeVYHv5qmNMCBJT+hRCtnNlYk6ehyBVnZcrTmLsH9Lh+OEdnj4xYgXaZp0rkNF8uIRG5xpJiwCXEtebqYn/8eNEp8DzZNpvSFoQuJr4n2YncgD/IQhpsxJ70lH0g9Gk9ocEDufUWt1T3UFrOLXx/grI0cK3AbC57Usk/ZQw1HhM0j3AUgyzZMYoBoVGko2SNgJ+Asyd7j9MVE5PrTq2k3ZxYrYeYvu/ff9FZTSVBGoEaU6Zi86t+rnMNT8FPNrh+CTExmkUvfE0wcwta/WPJVy+syAX4/tDhu0aiPFZ4KIOxy8EKrEdXZBJc3OSabUnghNepr0ZrAvbU98mczwcfirnAuemBMcWwL7ALyRdChxlOwfBoQlMQiQ2y/g0UYzOGaeTBMG7lK5vFTE17Zb9Ij5Gz26xCYabN7NsYj77PHBXur1A6bFh0eLsgk+Ga/TMaCpOAbcRc8vWpeNbEYnnnGhJnHQqYpjOc8SHDpIeIJK97wG3Eyau1xPM+WHrSUN0Bm9v+9gkRbMtscb9NZ1JHAOGpG8Al9l+N93uiom9eOKevkl/6iarI+njFeM0PdccTqxrtyISzksR1+bTgMpddKU4J9veKZ1nLVxKNULIhwqjSe0RDkmHdXnIhGbko8AFdckS2P4gvYbrgYMqDjcT0W4OwdSbLt2+mNg4jWLko/ZkY2IW7ksYuLXYc8sAx0n6eK7Kue2fSZpUYaRamxFVg0mg2iFpKeICPxsd2pvJt8G4n2DqlTfr69De6I6iJ34LHJHaKFuJqxWJef/QIXtVo2iqw+Fp4vMuz88rpceyoaE2zSYSZxAs9n0kbWy7U9IxB84EJm2ggAqApCUI08DvEGymk4lr98WSfmn7xzXFndL59LyvJM6BLdJ9S5oG+Bmx0cyFa4EjJa3nZOAm6VPEJveajHFuIkgBe6b7TgXincjAoGwSTcxntr9cd4xOUH1eMevZPrPLYwfb/knumDViD+BqhcFh6zuyIrA4wabNBts5C0sjGecT88jNNV7HhgJzElJ3EKzzqW07yRNdS3SQDxbnE3mN5+mbfDTciidnSVqn3OGc5GiuoXeRcGLGwsCWKZf1PuGn8Q9JOxESYX1KoEwAFqO91ijiWeIcGcUAMJrUHvlYhDCHHAM8lI7NA7wPPAj8ADhU0jK276/pNcxJnnPtGaKN/SmC+b0ycCexkBl24vqSPuth7tg8BGgi2bg1oT16SuHYhUlj9afEZrMy1NuI6iqCAbZzup/FiGookIxCViC0wR/o7/kTgOOAO4DV6aA/mxH7AL9LyYVJgLUVLuQbEWYuo+iNg4EZCGZTS3fuLeBA2/vnClKXd0N/+nylGFm0+oYCkqagty5gDuOeQwm5kYWBlq76WMLPY9sM4wPNtWk2KHW0I7FG+nfq3inLHAxaHkrSJwjG+UrAJJJuB75ru1NhuBISM3tDIpk9N8FuWg+4orW5lXQycc0bdFJb0lG2t+lwfGqC4JArGbkjcIWk+wmTszOI/+tF4v/KhR8R3QxPSGoVfz5DSKp9N2OcnYBrkj7s5ESxcX6CqT02Y5xaoBFsRJaKC7uTvGIk1WFM/StJr9i+rBT7cKL4NOiktvrxOSgih9yd7T9JWpo4p9clumjuITwQajP2ravgUI5BPdfn1vjTEz4BLTPn+4ATbVeScrC9a9XXNpHiZWDadPtZIiH7d0JWdaoqAxcLJiOseDIrcDxxngEgaWaiCHBflYGbnmuI9VjLM+J54n97gFh/fibD+C28DXS6rs1DSDiOYgAYTWqPfFxAbPi+V1gQTkdMODcTG8IziETdKlUCdWCFi0hCr05UtKriPKIa/xfgaOA0hQnerGRKNPaFNClPlqRccuBRSTcQOtB/rImdsTHwou1L0v2DiGrg/cB6OdtG02JpCTrLQpzS8Y8mHE0kG2emnZQp4hbyagMfSSRoFyKMqFo4j4ya2n2YdgBQxbSjEONs4Ebbx0iakvi/Zo+H9B3b51SNkTA3sE4dSZkibF+gMFfbi9BQ3IcooH3d9lV1xh6uSImrndNG/HPERvMR53fzrsu7oQkt0B6QNHUT7NmU8DuQSAB0MtGqPAfY/pWkfxHJwHXT4QeAb9u+oOr4BRxGTW2aQ5Q4q1Me6kCCabQXUWDakri21MFCfYYgG5xIfD6dNmL3EK3pVbC6pJdtj2fIpfP78orj9kDSnl6ISPgtSPjRnACcnpENju2nU5fBSrQl1B6wfXWuGCnOvZLmIZLo/0f8P+cCx9qu1EbfEF6WNLPt54FX6MOIjAzzmaTrusQAwBmN6Ajmca1eMYR845mSvmb7ZgBJRxPFwKrzQeMSd7b/RhjT1gqVzOnrKDhImoooMtV2fU5xFiO0od+k7eOxA7C7pJVt35kjzgjDjcBXiET2H4iumhXSsZydNB0h6dPAXrY7sXgnVqxGeGocZnuH1H18HSET+p2KYzc919xFECcfAW4guuo+ThTwc3qtXAjsJam1drakWYk1XK7984iHnNX/bBQTGyQ9C3ylzMKWND9wpe1PpQX1lbYraR2lRWARHxAVpmuJSvB7VcbvEG8p4IvEZHNZ7vE7xHsAmCdHEjCNtzDBalqPqMz/HjjBdjbTMEkPEazjaxOz4WpCX/NrwHu5GIcpAXg6sVF6jZ6bAWfUH0XSssQmfaEU705gH9tZTJUk3UtIgfyidHwPIkHz+UxxXiKMqB5KyZmF0mJ5duB+25VYAIU4a5QOTUZ0cGwM7J1pUf4vwoTqbknrEy3aC6UYW9hepGqMFOda4CDbWRMYo8gHSXMRzNMbbb8pSeU2xBpijvdusF1J5kqSCAbGCzmTV11ivQ6cTVwfb64xzrFE4mJP4FTgh4QcxJbALrZPzxDj07af6fLYUrZvrRojjfUqsKjDT6M4b85GdIZMUWHs94GZbT/fRzFQxDVtom8HTszfcbavSPfnJgoNU+cuNkla1vZNOcfsEmdOQkrjINtHSJqWSNS8B3w1V5GoqYLTKAYGScsRWq3vpdtd4Z76roONVybKTEYUiBYAfmc7Z/fJo0SL+zWlOW1e4M+2y4XcwcZZn5DV+wrBolwD+LLth3OM3yRSsnlNejKOL7T9fuY4exHr2L2IgsMC6bP5NrCd7aUzxKj9+pzi3ETIg23e2i9LmpQguX3W9pdyxBlJkPQxYArbz6kt19TKO+xn++Wa4y8E3Dkc1htFSPoMQZw8h8g33AlskPv7WRckjbH9fioETWv7utSNdgrtz39T23dnijcdoUO/GNEZ8BwhO/JnYLXRtcjAMJrUHuFIm+av2b6+dHx54CLb00r6LPA3230yk4YKkta1fXYfj08KnJ0rQdtHnMWBqXIsmEvjTgp8g2jTXhV4mGA7ndqF7TQhY78BzGv7KUkHEhv2jVJR43rbn6j26sfHeZhgyu3mYa6nJumbRIHhatqa2mOJLoF1bWdxvJb0MjDW9v2ljcwywDm2P5kjTh/x1yeS9OWk92DGepMo+Dwt6RTgOdu7pErz/banqRojxVkL2I+Quvg7vVv178kU53jgtPK8OYrukDQDkaD9MpEMnDudzycCL9veseb4/0vMaZW6KdLG5S1gftfYypxirUnM+6sBTxDz/ilO2roZ4zwFbGT7ekmvEUnhRyVtSHTsrJYhxv3AMi75c0gaC1xie/qqMdJ4zxMFtLtK8+ZXiOLAoFtCm06c1Y2UpP+U7X8Vjv2XOLefqCHepMDy1OgRkeIsSDC/fkaQAt4GVs+58Wuq4JRirUisLzp1uQ1KTqlDjEcJc6vT657XRjIUJvXTOKMufFo/zWv7ydKcNh9wW671U4r1A6Lb5QUioV1r11sdSIXzSwjT1pas5v8S3g2r234sY6zaCw5NXJ9TnDeBRWw/WDo+H3BHLiJNU0gEpy2J6806tp9N79njdc/ZTWG4JrUBFJ1BNxHSmhvWQW5RTf4qiah1MnH9b6zol/b/rc6wO525Y2ukYyRp+IyiMy4ATpS0lqRPp5+1iHa2VhvHEkQidWLFKWnD2gupWn82ULla3h9s317HRtb2e7bPBb5F6CnPBRwCPC3pFIXsyWDxOu12tpWJiwtE0mbKCuOW8SngqLoT2pI+o2jHat1fQtIRkrK1ZjmkMpYktDPXTD8vAkvkSmgntIyoxodWPUZU3XArsZHOgaeBpRVt4KsS/xuEVEROWZ1zCGbOiUQb+9+I9rDW71z4BHC5pKclHazoqqgdkj4qaU1Jn+v/2RMdDieKDLMCxXng98Q5UTeyeDfY/oBgYXRqA84K2+fbXpOYP48j2qmflHSxpLVTkjAHPga0/BteS/chmDS52Fm3Alcm5iwAkr4EXEbMabnQatNsGQNna9O0fYPbHV+PE90GNxR/iHbkx6vEKULSGEk/lnSbpH9J+k/xJ0OIMjPqfehlslsZCqb834k157HEHAqxpjkkZ6xUvPwa8AtirsnG0C7gu8T35FpJD0vaJSXos0LS3sT1ckXg48Q1s/iTC8cSUoAPSbpd0raSshpQSfqkpFMlPSfpPUnvF38yx1oS0/flAAAgAElEQVRW0mmSblHI0SFpw5QUqBOnAVkKDQW0vGLKqOQVI+mw8g+xv3iBYE7+oHB80JD0cnne6vZTJU4BRxHXs8/YXtShnTsrMS8flSlGC7Wb09PM9bk19qwdjn+GkCQaNlCQj1pSKosQPkQA0xFyMbnjzShpAUkLFn9yx6kbaY78U5qjZ0vHtlPvjt4JHbfXHECsCacDvg68VHUOUBhNFu8vSOSudiZ8OlrEibWBqj4+xxLz7wOSbpK0iUImqFbYvtn2L20fNJrQnnCMamqPfGxJJBvOov15v0doXG+f7j8IjKsaSMHU24dg6nVinAxWgmJn4FxJK9n+SyHeJERCeyxhSpcdCtOObwNTA1fVwXBRtLdsSmhN/ZfYAJ5AsBD2JjaJSwxy+KuA4xXmCvPQTpbOTzADc+EKom2mbuPLM4DfAKemDdnVhK7VBpJmsr1PjiC2/0pek6ZOaMqIqhcUutfbEMYnOXAEIT/zOmHken06/iUi0ZELc2QcqytsryHpf4hC0/rADpIeJP7HM3KxHNWcFnkTWJlg0D4j9ciZPQLMlitIhw14bu8GgF2AgyV933ZO3byOSB05hwGHSdqa6ERYDXhR0nHAARULhv8gvjtPEdf7dQlNza8T+rQ5MI5on7xI0ipEi+aFwB62j8wUA2Le/CNh2jMloXPYatPcPWOcx4nz6vnS8Y+lx3Ixp/Ym3rtDiS6UnxNzwJrEeqoKBDwsqciQmga4SyGvAlRamxVRm0eEuptDvQ3MAvypNec4jzkUts8HzleYbW5IdFTsK+kKoqh6ofNI3m0FbGL71AxjdYXtw4HDFey5DQiJg0MUsoGnOY/vyclE0mxfajRyTgmtU4nr8aL0TmhlYbZ2wdLkLdRDfV4x3WTfHiVMyVqPV/2ctuv/KVmxHLBUsSvI9kuSdqHdXZkLTZjTN3F9hiRxKenH9DRzPhg4M1cQNeOvtAewle1TJBV1mv+UHssCSV8g1pWfo3cxOIt+f1OQ9H1irjmCWCu1XvsrxHe4ivdJE3PAlgqz1lbRojZ/Fdv7Etf75QmZ2GMIPfWzgeOLuajBQtI2wG9sv5Vu9/V6chfrRiRG5Uc+JFAwQD+b7v4jZytoIcalBAvgBODflBZKtgedcJD0M8Lg5ku271MwtH9PJM1WyJF4SMmSyWxvne5PTphSzk+wgSYl9Mn/XDVWGn8HYrL8X2ISPh64NDEFW8/5NGFGMqgCVFpc7EdU4n/lpEWc3s93bP+82n8xPs5mhObcSXSWhbgwU5yXicXsQ+ki8G3bYyWtDBxn+7P9DNHX2AOS33FeJ/JJ6WlEdSeZjajSe1b8LorQ7HoD+G7Gz2Yx4jy7qjW/SFodeMV27o1Go0jfw/WI4tPcg/0+dhi3ES3yJpAWlYvafkQ923QXA66wnYX5rAa8G9J3Zipizn+HYAONR6YkYDHeJ4nPfBOiAHAe7cLmzoScz8oVxt8eeN/2UZJWAi4i5oHJgB1yJZ3TNfMS4r1bENjV9jE5xu4QaywFX4XcrJaU9P2kSxJgid10v+2pM8V5DNjG9iXpe7OwQy98G+JaN2gzNIVRdL+osjYrxKrNI0LBZh4QbOfsCii/jlbBaXKi+Fy54JTetyVySiZMQOylCC+CBXO0t6fPfVmHiV9tSEWOw1NCq3iuLUL461RmoEs6t3yIKHItBuyb+zxTzV4xIwmJ7fk127eUjo8lZDVzevisQSQ19yc+n72JPdtG6TVUNg5v+Pp8MFFIa61h3yXmgF2cwWdBDfkrKaQ157P9RGkO+CxxvRm0t0Ypzt2EAfKBdM5rlIsdEzp+eZ4pY3pguUzz8/2EROj5pfdsAUK6r5KvWt1I+YzfEXvKjVWjv0qH2NMQe/VNCMLGA4QH2qC7XCQ9DiyWCnJ9df+5Sm7jw4TRpPaHBGrAvCtNKss4k3B+h/GLTt37pd8rOp+O7r3EhH9huv89gj21CFFBPxGY0fbqmeI9ksY82V3c59MiZL0cm846UWR9dYBzXJBTnNcJo5YnJF1I6J8eqGg/f8j2oCVV1N0YbPxTGCYGYUV0SGy0koB/cWaTk3S+zkEY9tVi3JoYTFvTNgh6ADja9kPd/6pSvMkIFvB30+//2P5UprEb0SJvAqmo+Vfbe6ZrwYIEu+ksYBLb6wzpC5wA9JcMzDUfS1qbKGyuQjDCWlrurxSeMyfwgO3Jc8RMY84GfAF4tMr1U53bb6clWF+XEJtlIKve/UbA78sb8DT3fKcqE0ztToBtCYZxMWE5hpCmet/22CpxCvH+C3zO4XvxT0IT9s60Ob/L9nQ54tQNDbFHRF1ooOB0IPB6YoY1AklLEB1I3yYYuxfZ/k7ffzWgce8nzMBySoF1ilN7QkvSSaVD44unwzHRLGkFYr2c1SC2S6w5ievanMC2DuPdrwJP2b4vw/inEAz9zQhGM8S8/FtiDbJJ1RileI0WHHJdn/sYfyris4FYq2eTjVRD/kqS/kEQP64uzQEbEQn6+TLF+T9Ch7wW7fkO80xH2P5ehljdtPvnBu6psn8uxRlvuF06PgPwfNU9tKSf2D5YNfqr9BN/dcIwcvrhlg8Y6RiVHxnhUAfzLqLV6QRJuc27HiSvTnMP2N5aIQlwNyFzkC2hnTArkVhoYWXgj61KrKQjyah1bHvuATznHSq01Cs0Tfsa/8bBjl0apyl9/vuArSRdQji475mOz0LPlufB4MuF2yI+63Hkk+hA0jcIJtG76XZXOBODuomCSFokH01s/iGkbv6RClHP2j4gU5xvEknSOwi5AYClgHuVWa5D0peJjf83iRbKc4lW4GtzxaCtRf4fQne6lVjIrUXeBHYCrlEwsycHDiK6XD5GtLgOGzRYRDyJSACPtX17l+c8R0hSZEO6plViGCX8jVhXFNtyW/e3BLZIt3O26Z4EXE5vWZBp02NV25tb3RECPk8w9Vt4h1h/5NSIfoZggD5FMMJWJpImixPyGsMFLY+Ilr9FLR4RCsPuSVxq/5XUKjbckSlOueD0S3oXnG4hiqpVMAWwRWJo3kPvLrcdKo4PgNqyI+sRhedrSdJ+zte5uR1wgKQtXYMRaQH/IrpCyzGWIZMEXo4k0kSGC4FJJd1OyMPdQCS5s3UFAigMdi8jZCC+RMgcPE8khDcjZDuqYhtiX/Rn2t+XSYn/MbsMgu2biP1GLSgXalvXZ0mTS9qoaqG2A2ZJP3WQ3BrxVyIKGEdK2pRYX8wiaWni2pyzQHgNce7WktRueJ55HFiY3mu/Val+HSuim2fHR+i5nhoUbB+cbrb8VdZtPaRM/iplpD3uusSaYBlirXZwn380isYxytQe4UgV7RmJ5NwDtCtZqwCH2Z4/Y6zFgQMIzaZ76b04H5Rsg3pqqE4GbE446vbQ6q26+Jf0CrC4k252agfZ1/aJ6f7sBGMuW+JeNWuPdWFQj//SD7cqo0Lf6jyCXfQ725um478gKtBrZ4w1vvKbccwPgJkSc6URdnsp/tQEO2tK4Epn0ohPBZ+xxIbicqKd+R+K1s2fOpOMhqJV/3Tbe5WO/4yQUpmz819OcJxniWTs5UQr5UV1MJwk/YDQon2dWGguavsDRZv72ra/3OcAExkkTUfIRBUZTcd260SZwLG76er2gDNp6hbiTkEk6YsxKksQKaSHtiBYrP+uOt4A4q1ImNF1utYMyvgsMcoGBFds0y3E7CYLshBwnfO1N59EsAyzyU11iXMA8JrtX0j6NmFE9wRRZD/c9i51xs8FhUTTFcSGdm6i8Dg3UWxetszaqhDnNuAg238sHV8b2Nn2kpnivEoUUI/vVnBS+CDs5ApSFOotp1SEbWfxi0nfm9sJrdGz6phz1FO26Q167wFyfTd3JTqnNiV8Y1YjWPSHE2v2o3PESbEmp/Oc+VTFccuycF2R431TdJwtQehRL0e00E9OfE+vs51Fh1jSn4E/2D6sxJ5cgiigfLqfISYk1lwUOvbqYtPWjbqZraXxepDc0mdzIpCF5KaQ0zjL9tlVx+onjgj9/F2JOQeiCHyI7T27/uGEx/k4UUC5jc55jSzkoyYgaRzwU8KX5AQiLzQn8R6Os31WxfFbutCHE4SzYrF0DFHkmj3jfnA6wl9lMYLU8Bxtf5XVnME8WtIXievMt4jr2h8J2ZHKhMCU29rT9n/Vv1nv6wSp74+2s5oujySMJrVHONRTs7XcpnePM7a3pxaWM4i2sB4PUSFJ18+iv4XKi//SYmx+gjUzl+3H0+PLEYnU2avEKcSrXXssTfpFTEYw0fYFdrd9TYWxh8TkQKGn/lEXpDNSweGNXBvnNGb2pHaTSBXrU4nv460ES+YqItEAoRP81UwX5ycJffNbS/PMXITe7YD0ygcQ5w0iYf5o6fjcwN2uoNtaGm9zYi7IadLTLdYXiATWiNMizwn11NUVsRA/Dujhpl4lwVSINTXB9lgX6KUFnnGT+QYhPZEl4dtHnL2J9uk76GDgZnutOuPnQKGosRCxuC/KG40h2KeX2163w5/niD8bYRj9oAu+FzXEWZowo3vE9kV1xckFSdPa/r90e1KiaFosap1OaEbfkCne66Siaen4HMSadtpMcaZqgG3YGCTNnauI3UeMpmSbak9oJWb7CUTyt8dDZCAdlN6rGQhzuytod6AtTXQJ7Osw+cyKtMf5CcHenyTjNe114PO2H1dvbf0HnVHntkPsBYE7XFGqS9E5N4/tF/srPmTapzVVqK2F5KaeXaefoAF/pULsyYmujWkI6aGsfmFpn34qQaQqoxbyUZ2QtAGR2G4RgJ4D9rZ9QoaxW7rQsxEdaMXk6ztEsX4vZzBZLMXN7q8iaSeClT0PsW4+ATiztdbJgZTbWsv2KwPIc32E6Hw93/aAvFI+jBhNao9wqCHzrhTrNmKjeSSdDRWybGrqgqS1CGbOzcTkcbvtrxcePxCYI9emWQ1pj3WJvRyxiPlChTEaNzlIzCi13q+UaFiLYGlckSNGIdZwT2qfTRg3HkMk5+YhWqY2I/QhfwV8LAcTLCXnFkhzS3GeWYhoccyiC6vQbf6D7ZNKx79H6OmukiPOKAYGddZU7ghn1oas8/sp6ViCzbQnsaH5IdFWuyWh13h6pjjXA0fYPj/HeH3E+SfBKD215jhzEt0aLfbc/cCRzmCCVyhq7E14XRQ3r60N0zkOya4qcTYltBIPKxz7DTFvAjxEEAWerhJnpCCdw6u4SydLWmtcnDHZ/BJh0Pbn0vEvApfY/p8ccUpj19KtMYpqqDOhJelPxH7mADoXArN5B0k6h0heHlM6/iNgJdtrZogxD7B8+lmOSJLcREiRXJ/r/5H0DLCu7VtKa8G1iKJDlm66LrEXIpJaOQoOZ9l+u85CTdOF2rpIbuq767SIbElgSd8lmP+17p0lPQFcTBSXau+oawoKOY1pchLBCmNfR3SaZvVsahKSXiC65k6wfe9Qvx6AlLe7Jtd+eiRiVFN75OMmwqW5xV6wpEkI/dOBMKAnBAsQhgq1GLbVDdvnSVqN0M29ktAILuINQlcxF5rSHuuEfxMO3oOG7Tk63a4ZFxDaxscppFv+QjABPi5pB9u/6vOvJxzZq34K/bz+A1eXn/kS8A3bt0m6DHgR2LS1MJO0L6EXlwN3ECaKre9M630bR5t5NCiUWCAXAgcmdvOt6dhSRGvY3uW/rRh3MaIYMCu9Exo5ZW4+DXyjS5wseqo1opOmcifk1FRuAl8HNrJ9vUKG4ibbj6aOhA0I9mkO/BI4NJ0DfwV6tEtmLARMDtySaayOSGyvC4lzotVhMBa4T9LXbV9VZfwWAz9tMs/qlkTNgC2AX7fuSFqVYOxsRLDbjiHmmnGDDaB+/BSKyM1sqwEzAGdLWqvMYFcYrF1CsPZy4Upgf0lr2H41xZke+AXRiZQF/XVrUGE+U7Tob2L7tXS7K3JdaxQdbtvT/ZqWiw06BliTdmHrPuBC19AynQpY9/f7xMFhYeALth+safwiViH0zcu4nEiq58CDhNHlkWnMv7seVttZxBrtW8R1f5LEpDyE6n4HjcD27yRNC7zdV9I6FeyqoFXMXphg6Xcs1FaMUcTU9DQ+buFjVPBvcHOeSkUcTuwDLySSj1fUMccQc//hIyGhnbqZJrX9SMo7tMhhcwPvOpMPgguyiamrhpxzjcL09hhgqXJxWdGdfguwlUMLf7CYxfa7/T+tUdxDrENH0QWjSe2RjybNu+4gmKHDMqkN4JDj6Jjoc4a29hKuILSgamMCd2BSijCl2oVIPuSKsxfBwnijdHxK4Ce298kUalFiYwZhOPNvQk7lm4SW+6CT2h02l1MQi6ZyoqnqJvPIPh4zsfCclOobgBlJhiC2/5PY1MWF2b8IQ8Ic2A24TNJ8xGvfNt3+IsEKqoJOLNYfpJ8ijiXkKCpD0neI9/8KwrjtSoLp/klC0z0LFDrHFxJzwLyEZt/sxPf0zlxxakRTxaym8THa8/Jr6T5EF0/OwllLw7Aoz9QqEuQsBBxPmJ7mNFAq4wA6aEArNKMPJF/C8VqixfmZNP4SxP92v+3fZBi/pQfdwhrABS12vqTdqJ6kHSgzf9DngPrXaGwHqVY8W4UgT5xMYcOVEtqXEpJtW1cYv4wfAzcSRmp3pWMLE9e2DTPGOYjo1vg+Hbo1Ko79Ku3C76sVxxooWoWYQ4H9CPPZ2YkEdJb1mUJu7FLifWrtA3YFnpa0eo6OjRRnauIz6OYRkKMz8H7g4xnGGQheIuaZQ0vH16C6AXoLRxFEh70I4s71qcvi5szEmt2ItdjTxNx1f/p9BnHeDRdcJKnfDhRCy3dQaLBQ20LtJDeVTC8LxycnuilzFTZmJgwO1yN0wt+Q9AfCcydnAf9c4jqQZe4aYpwMnAiUZaiWJK4Ny+cKlM6Dn5DkLlNn+sGZugW3A37bqVvK9quSfg3sQJzvg0ITCe0JXaOlIu4FNb6kYY9R+ZEPAVSjeVcpzrcIraaD6ayllbX9fLhD0mbUrD2W2sI6MSlvJVi7WVgoas7o5A3CEPKpJK9xn+2fSfoM8JAraConRma/cE1u1ZJmJjaemwLX2l614njjTSnT/R5yDZI+CTyX8bOZk9hoFueZA23/vc8/nAgh6R7g17aPbb1vhHP4r4F/2s7CCldINl1me+9CnOcJJvDlNXQejBjULD9yD7C17RskXQ38zfaPFd4BOzmT2ZX6MVp0Ba3t0oJ5EmBjgulxD72vNZU7AiS9RWipPlI6Pg/R2pxFS1XSTYSXw6mSZgIeJopBcwNHVy2gqqRzLuluogX1qHR/VuJak80wug6ot0bjokTBsZVsnIfQvPyrq/uRzElsIP9ge1tJywCXEQmGraqM3SXe1ETHxEKEN8Q9hN5lto2opKdod2u8Rsj4PSppQ2A926vlitUEFCbL29i+JM2dC9t+LM1pS9leP0OMS4m15ga2/5OOzUAwKT+wvXrVGGnMM4li+al0lgbpizjQ17hF3dzFiCTsbnRen2eTn5G0CVF4vIzoPoRINK0KbG775IyxpgeWpW0YOT9wl+2sJKc0Ty5ArAXvKl8XBjlmf94sCwI35FjTSvo7Udju1IHyJaJ4c1KOgl3av9h2XYXaVpwFCNLWncAKBKFiPMktR9Gpqb1gaeypCBnK9YGVgGeczzR+dyKJegmd54GcflEbAlsRZJGlbT8paTvgcduVk5nF61jp+FyEFv30VWOk8XYgCBTH0O7aW4YoDO/hih4BqWNyVdsPdHl8XuBK27NWiVM3mlyjfVgwytT+ECC1aP68gVC/T79PLIYnP+tspOC36fdeHR7L9X6VmZQfAC/YfivD2EW0PuMyFqJk5FYRjwJrSjqPYIi1Lo4zEozKQaOuZHV/SG2OOwPbEq26q9jOJQ20T0rSQHRq7C6pxQzLYqrYQloQb55zzCHEnMQiFqINdGrblnQ4wRTNJXXyOYJpAqGnOKXt11PnwwXkZQU3gsTQ79TeXqlIp95mtJMCm0h6sRQnxybjJGLuuoFgIF+k0DedjGCAZEGVpPUAUHaYb3XmLFB+GZnivUAwZsvJi4WJQk0uLADclm6vS7TRj5W0MtGpUZV1+iTwBYIJ/HFi0180bJ2J5ti1g0apBXgH4P+AjZ10LiX9D3GeV2nRbcV6TCHTcn0iUaxFJJmzJ7RTvP8C2ZI9XdBUtwYAkmakLQn3UDkplAEzEUkZCJmDli7nxeTr4FiOSJCPX/M5PFd2oed3qCq+Cqzu/EbKr9BzPhS9Ozez72dsnyzpAWAboNUJ+ACwjDObqhGvezJCU3uK9LuSFGEn2H4KeCrzsOXPp4xu+5DBoK8OlIvJ24FyBjGftQq1VxOF2g0kzZSr09X2vanI/CPiejANwUTOSXLr9hl8mpqum7bfkHQF0Xk6G23poxwYR8yXrSJQj9D07LIbNCR9n1i7HAHsTnt+eYVIqudg6JrOnQXTkTc/szXw/RIr/0JJ9xHEx6rGt5+kVFwo4T2im2+iRpNrtA8LRpPaIxQaoIFXZvb0SG1FrwVuQIes5qQJajuDG3hYUnExM4ZYNGWRhEjYh1gAHk4YJrT0mlcG7ur6VxMhJE1GXPx3I1pMv2f7jxlD3EjPzcotQLkt98YcgRIrpyvSBmewY29DMDPf6pDYLMfJxZp4mfbi71kikfZ3YHryFgP+Szv5+08imX5fut9U63MWKMyGzgM+T8/ukNacUHXRvH3p/r/oLTeQZZNRZJLYvjoxP75AFNWyMsMVeoZfpnMb/aA3s8UFc0P4LfCbdB602n/HEgW7AbdZDgCT0db/XIlgm0Foxs6cYfzfAcdKmp9gsz1o+6+Fx79IJByyIbWy/5ieBpsHu5omZBE7Aiu7YNxk+2VJexDSSmXZgwGjwJ58gmBPn0fIq/ykyKzMyWxNcWspnhXwD2JN+xRxbq1LFFO+TiQasiC9R8cC36E9R74v6ffADxMpJQeeIb4fTxGt9CsTjM3FqaCnW8LbdE6aTEMUh3PhZfKSJVpoes4cj5S83qCu8SUdRcgLzEe8fzcSc/b1tIsdOeKMATahuzRMFcZhY5+P7edSofQmSUcWOlAuJTpQfpgxXN2F2vHoRHKT9GlJv7G9xWDHVdv00oTkaUfTy8GO3yVmi6G9AXG+PQ2cSUhTZoGb84vamujKOD8VAVu4g9Cjz4EbgV0lreekP56+r7sSxdpcmJnOHi63kGeN1tqTPdrl8QWJ/VStkDSl7TczDVfbGu3DhNGk9shF2cCrlVgoylBkYxukBN21hCt9x5aQQY47oOQ8jMqbtNBwEnA74pw6kWCvFjdg7wBPFBLPlWH7j5JuJi6MRbf2a8iodVwnJIlgfuxDzMG7Ee3tWU1ObC+fc7x+8AR9M2SqzDPbE3Icb9E7sVlENtYEsfj7CrHZ+wNwpMKc5CvkM9eEkAFahmBlXUqYBn6eYGvd2tcfToQ4kpBoWTH9XoIw2TmUSNhVQhObC0nbd2qNTMXBJ1NXxRVk8qOQtDnB+nyRSNIXv0Mm42a2FPejtBO2uYzQ9iWYJjsC+6djzxHMnGwtukTRZytJlxDfx5Y+6Czk0Z89iChcrU18Jt8qPT6W2DhngaTvEmycc2m/T2OJxMAmts/IEOajdGYufYIKmrAJndit69J+37IyWxsonrXQSLcGkVhchNA5bq2Vlibm018Tye4cOI+Ym/9CGDqfppDAm5XqzLkWLiYKW5vRTtItSSTmchqe7kl0oW3sjHrQtm/INdZEiJkJNvD1trMW5Uo4kkhqX0IU/7JpnDb9+TTYgVJ3obY/zABsRpgkDxaNml5KOouYM98gNLX3zbnXHALMQWdi1tuEz1IO7EzsbR5SyLhBSBG11oO58CixBvhF6fi36d3JNxhcCuwr6fJy17nCx+tnxLWoMiQdZbtXHiVJoF1MvkJbnWu0Dw1GNbVHKNRTq1PE4mI1knFcCzmZvJKeBVbKnNTupgndwnh5kzq0uuqGwiiuG6Nh00GO+TiwWGr7fLyPp9oZDHUkTUpUyq+1/XTV8UY6klbfZ4mN5RF0diPPzmyrE5IWKh2ajNio7wDsbrtswjlRQ9LHgCkSW6dlpPNFYkG2X7GaXjHOZ4FpbN+TFkmHFuLsUHenRU4kGZAV0v/yKrCE7YdSMeBQ22U5jIkOkt4EtnQHM6P0+VwJzGB73kzxngR+afvAHOP1Eeds4Ebbx6RF/920DUm/YzvbZjPFmxbA9v/lHDeNvTyRoPso0QK+aTr+C8JvoaqRb6NIsgO/KRdTUjvq5rYrt1JLOoXYvO5Iz2TjwcBNtjeuMPaAjIBzJaQkXUToTI6jQ/EsI7u9HHc2UrdGTgKFwoh6Fds3l44vS/gq5EpolOMuTSTPH7F9UaYxpyc6Hb5Ouz18UiJJt0kV1nmBCdrCXMT89QS9dW4XHWycQrzvAa/b/kPp+LeAqWz/rmqMkYi0DtjI9qVD/VqqQD31u8fS7kDZksJ5mGOdLukvhFHjJcQaYynbd0taCvijM3l49BF/IeDOqnvoxPr9LqFnXCtTVtLpBNnlityEIDVnslyMeT+wq+0LVPCLkbQ10cVbeU5LcWah7bHW8qM4pigZlSHGNwk52qtpy06NJXId69quREBT+EHdSawDjqGtQT0vods9htAO/3eVOCnWY8BpLvgopb3A5QC2l60aI41Z2xrtw4TRpPaHBKrRVKsQYzdC2H6c7ff6e/4Ax+zTSKuIXAkghaHFPnRvCf9Yp78bRJy9CT3tO+hsdrNWjjhNQCVzrRrjXEcfzI+KrY2NIBVqWuj0vwzbIk0ZklYHfpKbNa5wUp8DeCzXXDOKakhSRIvafjwtBMfZvk5hIvd3VzBxbQqS1iHMx75dlDGQNA2xiJ0RWC7Xhk1h3LNwndflFOdfROLsbknrE0yWhQjzyC1yFhzUUxv4Qdsv5Bq7EGMM8NFicUnS7MAbzq9FXCskvQ3M787mTfc6g8FmatM+hDAhniwdfg84gZif/4blaP0AACAASURBVFs1RlMYCcWzIhSGlKu7ZKicuhQvrTuhVQcUkkqtwt8D5XN7kGMO2MfC9s8yxHuYKHBeVzq+HFGEyq5D3QRUs2yPpOeA5W0/nGO8oUKBUDX+UPpd7HrOsk4f6kJtrqR2GustYi/YF6FqooaGwMBP0jiiq21H4ro8jpAj3JVYS5+VI05TkPQForO2VZR/gLg+Z5EJTbmhXxHa98Xv5hWEbFeW809tE+yDbB9R6NZ8D/hqrrXTSFqjDSVG5UdGkROLE5W4lRMbtceXcDAX5iFiKp5KsEBOAP5Nxva5ErYi2Cun1jR+k7iNYObW/Xn9rXR/MqLdbQGCITQcMGS6jUOAh4h5IQvShf9oIhkHsbj8h6SjgWdtH1Bx/FkIdvk+ZQZOaj/dAzgkBwOgNPbkdC6g5TZaqhP3EonSx4kW950kvUO0tNaatM0Fh7zR9MCZkla3fX1iZVxGmNNkS2gn/IHQts3pO9AJ09HWoF0VOMdhrnQJwQSpjLTY/yVhfNo6j+vQBiYxs14uHXsi1/gN42li3VRO/K2UHquEVABYjDCf+gmxUYYoCA7HjdIYQuYGQrZnFuI68yQZDO/Uj2RbC87n37AfcJikDW3/K72GmYjvZSUDR0nfAC6z/W663RU5kpqSlrF9s+1HyNNmPh4DTVRL6tbVOaGYlbiWlfFkemxYQc3J9hwKbCvpRx7erLkm9buvV5gS9yjUEnIx2eR1GsK9RCdq7UnttDZbjs5FmkHPzx4CAz/bx6dOwf0I+bMzCPm2bXMmtNP6dgk67zd6dSgOFg4fku/mGq/D+E8Cq6XPotW184gzddEW4rQkiK5Lha71CEmY1TMmtEfaGm3IMMrU/pCgIab2SX09bvt7GWJsSCSD5wCWtv2kpO2Ax23ncAduvVfL2L673ydXi/MSwTJ6LPO4Q9E6tS6ho3o48Fd6FzRq1TuX9FNCxqGydm8fMWYGJhtmicZGUGrVhFhgzEwwD+a1vXCmOEcSbWzbEczZBVOL3hrAT6uy9CQdQmwsOmoLSjoOeNX2zlXiFMabhyiefbH8EMOMrS9pFWBq2+cmlunFRNHhJYL5fO2QvsAJgKSdiAXmGkTXzqeIhPYzmePsShRRLiH028tt9FkSZ4l1uEeK8zghOXJtYmhdY7uyKWlKXi9CGB6VtYH/ZjuLNnBqPT2EtmxXjyTWcPrOAEj6PiFDdSI9DTY3ITa0v84QY9iz51pQaIEe6jDUOgP4HyIRsAXwBdsLVBy//B59huikK3YE2Rmk21K8u4hN+UcIE0eIJM3blBLDnsAW9LQJn8n286UOsTJyMU7fIUy8ziRatu+vOmaXOD+x3asYl5IDp9leL0OMp4AflZP9aa1x7HBj0KtG2R5JZXm5FYgi6n30vqYNK3mokYAOn08Z0xPrmxxzwKrEXnBPOu8Fs8gqSlqE0FaeitCc/g9hrv4G8HzG+flZwsDvvtLxBQiZlVlyxCmNPRWxn83adSbp64RkyzTAa5Q8XJypCz3FGkNo0BfNry/wMO2sVch1XUUQdr7mfAaRrfFHzBptKDHK1P5wodYKRo6kdV9Im799iA3g7rSZBa8QSa4sSW3CnGPKTGP1heOB9anIxumAgSb2cp4PrUpyMQkzXu+cfCyQbjiNYIvXltQmjFDnof7/ZTiibBYG8dk/TT6jK4A1iQTprZKK8e6jXd2uglWJolk3nEIYe2VJahNsj/cIw5teEkTDAZImtf2e7Stax1K7+bwKbfKXaS9shwVsH5Re+zWEZuvyuRPaCVsQhkrLpZ8eL4N8BotHEJuZ1wmm4fXp+JeIZHoOfI3e2sBXKMwwL88UA+BkIum3L8P0O1OE7V8leZgdCXMliFbdb+cq1NMge64B7EfbOGtv4CKCMfcSGa41LhnSJpLDcjUSQs7v/ymDg+1JOt2uEbMQn8F6wC6S7iHmnTMzz58/kfQf2ye0DqQkyllE114OnAkclT7/G9Ox5YgiXWXm5AASjeORKRG8NCHb82IqcHxg++ZUWD2Kge8bOqHchTMsTNuHEpLuBFa0/bJ668X3wIQWszqgvy6pV4m1bQ60tNQvpLd8S8694OHE3L8V8fqXIgoopxHf0Vxo3MDPYX5bB0P/UKJ4vpszGuyWIWl+4vOfibZky87AC5K+7nqNaiujj+/j28Q17k+thqAM380WRtIabcgwmtQeoejwpZyScG9/p/i8HF9IhZZqpwngVeBhol3/qqpxCAbY5omhs0vh+B0EcysXfgAcIGkfYqIpMw1yGfhNAWwhaSXCrKEcZ1As6mLrVIOYo/+n1Iqlgbf6fVY1bESwAiZ6KPQ4B4RMLPryOfcB8AJhqpWzMv8JoBN7YWryJLfmoM2W64RnCIO9XFiYYBc+mHHMpnE64WreC7b/I+lzREFopsEG6NAJ0BVV5ucOiYZ3CYmDI4td7bnYZuUEWl2w/UuFGdWswFW2W6zNfxAM7hx4ic6b51cpSYVUxDLAsrbLUlRZIWkK2x2vKZJmdgYZmiSVMBexTlq+RhbTHsAhkmplzzWBUvHsEQrFs+EodzBQWY3hANsvEsZdx0iagyBtbAzsL+lG5/M8WR24UtKrDsmoSYGzCR3vXOvfPYlr/TW0WfqTEMm/3TKMX5wrRbAaXyX2MxCmpNMDuUy2a5PtqZvQVEaSndiFdrdOWUYhC0u3ZlxAJMlat2ubuxr+fJrafy5MaN5/IOl94COpa3MnQooy1/fmPOAkSZ0M/CrF6K+YUUSm5OmngKPqTGgnHE8QjRYrSbacTEjqlDtTJzbUVmjuAyNmjTaUGE1qj1yUv5S5GD+dsF2X49MTC7OLJa3j6g7rcwCdTAbeps3cyYFXiOpsuV0+d6V5Qdoa0WV2SdYFTpIDmBO40fabkpRzA+iGtM87JJ1aMheLkZ/x3gO2b69z/Mz4Gz2Z8n2h8vls+4aqYwwQdxAb2qNbodPvcbQlD6rgTWIj2y2xPXt6Ti7cT7RMDmcsLek4270Y7imhfR1tWYXBolMnQDdUOZ/LSdkzK4w1YKgB41OHxuFfS8cuyRiiNm3gEp6mJDlSE+6UtH45eS7pm4QGeif21oCRkn4XAvOlQ89I+qbtO/r4s8GiKfZcbRgIs1XSe8C/iMJN1fVm45A0BVEgnJr4H7LqUktake6JwE1zxnIYBh8A3E18/8udKFXGvj19D89PRJ3NiOLQl53J78L2O8C3Je1BJNDeJAyPs6x1i4lGSQcSSfmtHH4BLeb5LwmZgBxoxPMizWuTls9dhXnou87jfXA8cT6dyjDt1ikWs2z/dAhfSlY0uBd4lyDPQBBdZiU6nF4lJKNyYSuCNHcGHQz8Ko5dzNNMQRDq7qe9l1kKmJ+YB3LgCmKvXLfHzcIUEtoAqSNhd2Ci30cPUaF52K/RJgaMJrVHKJr8Utru06BP0t8IB9+qm4zHicmyvKhclbiY5cLpxAVzfWo0imyCUS1pBmKx/GXi/5ibuKCdIOll2ztmjlerszq9k04fEGyTvWxfWWVgSUsQbtbvd3n8I8Aats+uEqchFBmgixCLsoPpqXW7I7BTjmDqx4SqiIrnwm7AZek8m5QwJJqPqPzn2DT/BdiQdrtxGRvRZmvkwM7AQZJ2o7Om8nCozq8C3Jjawccz2CTNSxQGbwW+VTFGca6cHTiAYH0Uz+eNievMoDEEjLNajU9LsT4NfIPO8/OguoI6MI3mBp5KerTQ1gb+BFBZGzphO6KTastMCZJuuB64VdLetg9M7MBjCYmQ3TOMfzAxh32X6DL6McFiytXOWkQta42GJRQGYjQ6CXEOjpN0iO29KsasDQrvk8lsb53uT07MlfMRrecHSVrZdtWCYCve3sBeRGG41kSgpLHABsA6RLLmAirOzWU4PAE2As4h1v/LJaZ4VqTk7COJDT5F7vETNiV8fMavPW2/n86RW6iePIOesj17EZ4XLdmejp1Wg8TJhMRBuSCzJEE+WD5DjK8SRm1/yjDWkEPSP4DFbb9UOj49cOcwYZ6PR3rdm9GWnbsPONEZzaIJgtvixHl2A7CPwmxzQ6KAkwWJ1fwDSdkN/Ip5GknHEyzqPYvPkfQz8iXpLwEOTnumTvuNXPv0hwlj9ftKx2ektyH2RA1JiwOT2P5L6fiSwPsZSQhD0WE/4jBqFDmK2qEwQ7vVFU0IJI0jjOd2JKqk44iLzK7AOGdyCJb0BrCI7Yf6fXKeeLWxqCWdQlxIxhEL/4VSi9YqwGG2588Up09ndQ8D867UwjazkzmHpNeAhZ20NBUGZc8Nh/+lCEm3ESaKl5aOrwbsa/sLGWJ8QM/PvYXyMVd9/yTNSbSeLkQYntwJHGi7sjawpC8TZiBHAAe3WF/ps98J2JYwjclieqi2eVcnPfLK71VTSAu/a4B9bB+SEtrXEayMtXOyjyVdAxxv+8zS8fWBLWwvnytW3VDNxqeFOCsSDJB/EC369xLFARGb5kHJAqRE2YCQq9Ce5M6mIhLCb9B7Y5bT7Gh1ghX4KNER9DrwXWfQhFToaK/jpEGuMCJ+hjCqHRaO9+ppDt6nhEKTBSNJXwN+aXvWQfxtWeroGULy5oniwaoFR0n3EtqmF6b73yM0TxchOoVOBGa0vXqVOIV4/wR2sn1qjvG6xNif0NSehbiOnk6Yg1Vud++jgLIU8f0cn9CuUkBRmKnNYPvkwrHdCTmSSYlC7beLLMSqSHPaJi5p6KfrwMm2/ydXrNL42WV70rp5UYevRvH4XMAdtqfPEONxYDXbOclMQwYVDF1Lxz8JPG178s5/OfFB0mIEI/hN2gSQxQkJ1JVt35kxzrS2r5M0IyEL9EUiyb1ZucMqQ7xau50lvUqwmzt1ONxhe7oMMWo3C05xVgMOIvI1t6bDSxHFtF2A8b4rE3odbZBA1Yp3G3CQ7T+Wjq8N7Gx7yaoxRpEPo0ztUTSBjwDv9PusfmD7eElvEoyDqYh2oOeAbXMltBPuICqjtSa1G2JRr0yYdz0j9cg3PgLMlmH8Fo4kmPQr0sFZPWOcOlFOyHZqcc/W9q7mdAE/T2fzicdpt75XxcrAgQSTusie3Y/YuOfQ1AfA9mPA5sVjkmaUtJvtX1Qc+zpJPyTO5+3TBs3AdETybOtcCe2EEVGdd7SDr0lITU1DfD5/JZJ2ueU0lqazmecdRAJyOKFu49MW9ie8LfZWGJ99k2jZPZ0KJo5D1KbZTe6sDlxG6GZ+n2g5zmlyNCMFNqPtf6b1zYzUZBaUOgM6MfUH5avg5iUUBoqbaSfWJxRlqSPRU/YuVzvwrESreQsrA390krdIBa9LO/3hIDE51WWg+sOXiA6Es2tgTXdjeV7R5fhgsQMwPoEh6YuEQf1eBDHk50SCe1DdLV1wErHun5Oeur27pMeyQLEJmIFIYL1k+z+5xi7AdDbQm458LfR7EszcjXMUTPpCnev0UoJulZTYbGEM7f3UcMLhRAF989baL3U5HE+QRb6UI0iRIZuKAavmGLeMBrud3yQIDuUOh7Fk8otyM2bBEF0gEO9b61ra2jtfVLg/mOtoWVq3F3GqcDvHfDMfQZwq4y7y7Z+R1Of3wna37uFRFDCa1B5FE9iMtnZ0Jdg+HTg9bc6mKVe2M+FowhjsYDq36OQw1oO4+L9LWwushd8DhxGM9KqYms4uyh+jbVKSA3U6q/dlRtoDOVl63UJkHKspXcAHgF0ljXPoRLZanXcln2zPEUQy4+bCsStS18NvaLch1oWZCd3OSkltANu/lnQxITMwF7FgephIODxTdfxSrKb0B2uHox18feAPwJXAWrbf7efPBoOniaR5WTpnXHpsOKFu49MWPgesl26/B0xp+3VJexHSAL/KGKtWuB+5s1xICaYzCIPTVYi5+sKUbNw9w7ltYJqUyG7hA2DaIlu4KiMYQNIniOTYV7s8JcfmrwkJhQHB9ivAYNm6TRUaP6DnZnwpemrPvwLkZOgeT0jq1eY9YntsjWN/D8YnZj8DvGA7p79FC/PTM2G9DqFv/vMU/y2i6J0zqf1jQgt+R2ItA7EmPJgghlSCwtvgIEJ+atp07DWiu3JXZ9IhT7iRWG+uVypu7UqBoVkROxJF339LeoLee7ScEk51rtOLCbryde1dojskq0RkA1iMQkIbwPZ7kg5i8IXGXpB0LdEF+Erp+EeB8wfbfdYBTezTIfZQv5K0KD0LW5tSs19UDajtGlpMzEtaiT7IVJlCvk1IqZR1yGembSCcA9d3OJY7QT/iMZrUHkVlpE1LJ0xH6EPOQ6bqbAupOl9Xhf736feJxZDkF+xvgkV9E6ED3NLpsqRJiITQdZliQI3O6glFdp6IJMxedE4IDRc0pQu4FVEdf0ZSqyCzIHEufz1TjDmJTXgZrxIyB8MKtp8lFrPZIWlB4F6Ha/uC/byOXAW02tCl4LQsseEcfyBjwWl74BxJXyU00CE6Q+YmGMjDCXUbn7bwX9rs3H8S39eW3mEWo9KUuNieKAZ1YgPnlAWZE/ge8X9sa/v5dD48Zbus4zhY/I3QoFwlbZyvknQp0eb8FSoWamkXy8rH7irczrXeOIKQAVmS2DytRWzU9iDfpnxSQtqm3OE2LyV248SMBguNDxDX38MkzU98Z4prstkIT5dBo7Q2nwTYIiUC7qF3IjBnkrZOiJAbmZ/erMYcmJbQmW5hGaJQ28J9xPo2G2x/QCSdD2oVtHIUs2B8ku8WQqrtJOBB4j2cjyh0LiNpUduv54hH+ITcCDwk6aZ0bFngo0CuRGOZrVknaluntxJ0SU5l8Rq6G4YCrxFz2YOl45+hvUfMgeUprTESpiDOt1xopNvZ9gEKbfVtCZ8NiGvE95zRxyl1HixH5zXaUTliNHgNbYJMdSWwv6Q1nDThFZrxvyAktnKhXMCejFhj7kseD5cPBUaT2qPIgW6bu9eIL/3atiu3UKULf9cqeUa5hjn6f0oWNMGi3gm4JumPTU4snOdPMXKyamp1Vi+z8xRGauc46V1nxHyJ1QKx8J83ySlApuRPAS8DdbR/9oDt2xSa5xsQCQaIws0ZzqfdejuxOd/QPXWoDyavseJIwN8I9ufz6XYnLXIYPo7XTcpBYPtShU/D92mfzxcBx9kebkztuo1PW7iVSM48QEgaHCrp8wSb9da+/nACsDeRjD+UYMr8nChorUm072eBpOUIWZA/EcXy3Ynv0kJEV9g6mUL9wCX9Ydu3SFqE2ExVRZPSQysQJsd3pE6qJ21fldiauxLJ+6poREJhBOEg4CyFbvv8wKWldfJqVL92ltfmrY7JBUrHh425UioGP0LIaNSR1H6WSIY8ldZ+CxHFuhZmoD5CTR3m0NsC7wPz236h+ICk/Yh5dBsydLkB2L4/Fet/RLx3bxKFwGNyyZ00LHvVxDp9bzokfFNH5Xdsn1Jz/Jz4PXEd+DFtuaOxxF7gzK5/NUCUiCDF/RrEenlV4jucC011O5OS19kS2GWktculhHzr1MR5/XHi/3ue6KrOFasJs9AmyFQ/Jop0TyqM0QEWJgrOG2aKQZf35aqURzmM8CcZRT8YNYr8EEBhEtVND2zTIXlRg4CkbUuHWpWsVQlTtwOaf1WDR2J9/dX2nknndEGC2XwW4babZXMuaTraC8yWsd6xtv+ZY/wUYxVgatvnKgw1LiYY+i8RmrE5dYhJ79dCOZPa6m52SOG4nc9M47vAGkDtuoB1I33m5xGfeSux+Bli07mmS6ZBNcRfiDC8m+iTwJJmIxilTre7oqWvOoqRC9VofFqI8VlCruuexNQ5lLap0g45zjNJjwHb2L4kzc8L235M0jbAUrbXrxojxfkz8AfbhxWvA5KWIAwJP50jzkhCSl4vaPsJSU8C69v+k6Q5gPtsT5UhxiTEBnBbekooHAkcWpQlGUUgrc2/RkhPHF1cByhMWG+wff0QvbyJFgozx52A7zufxn1r7P2JQtwviMLCF4HPFqQ0tgA2sr1MxpifBA6hvU/rsQatsq6RdCvwa9sdC0uSNiXkIpYebIyhQkr6dtrXPpUxRu3rdJVM6gvHZwCeHw7r2hbSZ3Iw0SHaIk6+S3TX7mK7UiK4sE+Dznu1NwnvmxM7PDaYeI3s05uApOuJ7rCtiMTvQsRncxpwpO1uZrwTGqcps9AbCb3xMpnqFGAK21mIIWnNvAHtIt09wJk1ySuWY89LGIVO0++TRzGa1B7pSAvjvYg25156YLbXGorXlRMKY7fFXDAtyjTufHRu0ansqJvGXwC4hkhirECYa4xnUTsM8YYtVIOzemHsOpLaA2olq5IASpXe4vvR0mx+ghp1ARUO2l+m8wYgC4tS0Zv3Fdrs2QeAq3N8/n1IHLXwCSJRM2wW/6MYOEaaZMtIhKT/Ap+z/ZSkfxIt23emhPpdtqfLFOd14PO2Hy8ltWcHHrQ9RY44hXid1gG2fVGXP5noIOl2YA/bV0i6kGA37UowNNexXcmUVGEEtj5whe1/55ZQGEV1JHLDmDJbNq3T3htOn5VC8moqImn2DpFoGI8qUkeSpgR+TUjD/AvYwvZNhcevAy63feBgY3SIeRkxxxxD533aBRXG/g+wtO2OxvcpaXJLlfcsjfNxgtjyZOHY/ESha2pC5/iMKjEK484DnEAUHHo8REbiSYp1F8EIrW2dnhK1n+zApF8IuK7qZzMUUPheta4rj+UqCKR9mogO4CWA4nv2DlEEyFZAHUn7dEmvAEvafijdXtr2A5KWBH5ne95+hhhonJsIiahOZqGftZ1FjnaoyVQ50WFfI4IcsAswac4i6kjGqPzIyMdWwCblNtoRhsuA/QmNzcpIm/DzgM/Tk7nbWmhmWTDZvjctzn5EtJ5NA5xLfhb19MTFv1NCs7a2tlythk2hIVZsk1qAAEjanGBJvEhs0oobJpNJGiAlr69MP7kxEP3aYecOLWmjvh4fZm2ndWJESbaoYATYF4ZTogl4hliEPwU8RmhR3kkwdHK26b6S4pQlzRYhY9txU+uAhnAkbfb0z4DLCebRO8AmVQd3GIEdR2o1Hmbn7YcFZxEyTb8sHV+XMBBcrfFXNHjUJnnlMJ/sel22XYds0DLAsrb/1u8zJxwfpXOLfguvpOdUxdHAcySNfkkzEp4+zxHXg5Mljcm0Fz2JMGn7GvWarEONa/YCycWETGTReG4MIYV5eV3x60RKYmfrNiuM29qnNeLT0NQ+vSG8SxgUQ6ylW+aXrxLJ4FxoxCzU9qMpGVwLmaqIukmOdN/X3EqYhY5iABhNao98TE5b12qkYh3yap4dSWyYV0y/lyB09A4lWAfZ4NBR+nnxmKRPS/qN7S2qjp/aNE8nLsSv0TuhWSlpJmlALV6uKHPTgak7ObC7pB46VJ7IzY7crBZgC3sAu+dkFpUh6SjgUZeMRiT9CJjLdqVNaE0bya6Q9DvgBNt1J8qPLN2fjGCgvUPo3I0mtQNz0GbkNOV5UCdeoe+NeBaTQIXxUL9wHj+K84hr5l+IBMdpkjYjNgI5TVfPAg6U9C3iPZpE0liifT/n96WxdUDdsH1a4fZfE9ttXkIGKZc52W1EYWFUMmnixJJAp/XR9ZTWoIOFOpsGk469RbD3Tu4mhTFQuOSxMgLwNJ2LtDkg2omsTuhWIJ5QLEXPAtlGxL5s4ZTQ+jHwQyBHUnth4Au2y2aE2VHzmr2VMF+YkGsomnW+QzDDz6kxfjYMcC9o25tlircx8KLtS9L9gwgPp/uB9XKSlDrt04cp7iJIBo8ANwD7pA6LDQlfrFxoyiy0bjJVk+SG8r7mA+AF229lGv9DgVH5kREOSQcCr9ved6hfS1V0kG4Qwd77BGHq9JtMcV4EVnDoj74KLJHadVYgtCEHwhqtEj+bPrCkhwljiN3q0INLbXNPEhfLrgvjqjI3qeWzP9h2Lnf12iFpcUKT7S+l40sC79vOUtFOeqoL55Rq6RDjWeAbtv9aOr4ocKGHmc6tpPMJ5tqTBCvod7Zzms/0FXtugll/sO0rmog5nCBpiuG+0FOYHY6/S8zR4ygxjV3RRb4wP59BMHM6wna5uFIZkpYGlgYeySnVkTQ7jyUSKGMIxt4Y4n/cJFfr8VCvA4YbJK1LdMwdDvwV6GFCPNxkgZKO5i5096PJZUzeCJI80FIuafUrDGP/4jy66tsTxq2X0dZSXYLwvTmc2LhvSGje/rZCnFn7etwZNZWbgKSVCYbzlrafyDz2BwQTs9tmX8BHq+43JL0JzNtKJiYt4ntt75TuzwP82fYMVeKksW4Htrd9c9WxBhhveoI8NSexLvtPWtv+O8e6MCVofz+c1zWSzuvj4THASsBHcknDSHqI0NS/Nq01riE6OL5GyCmtXWHsIZO7S+ubOQjJlvf6e/4Axxxj+32F1vW0tq9LnRSn0PZW2dT23ZniHQWsRRT/y2ah51QlOZVi1eoZJ+kiwmh3HB3IDUVpqlEMPUaT2iMQJVbrJMDGhLD9PfTWA5uoma1FKPTBi/iAYO9dn7Nin9gmizo0Ox8DxqWLwJzA33Ms/vuJnzOp/V9Cf7SWhKakY4H1aCf/ThtusiNDBUm3AQfZ/mPp+NrAzraXzBTnBOB228flGK9LjLeABcoaZknz7F5n1rltApI+QWzANwbmA64mdBwvcM0GIWnxeVoujbsmkBgNO9nequY4rxHMidOAa2z3xUIbFlANHgFp3G8RrYvLE4mmE4FLR8h7NiuwANGFdJftRzKPP6TrgJyQNIYoAnTb/FUuBqfkWRnZDZabgqQzgeUIZmknnePshaA6kYgB99reunT8WMJEdNkMMc4BriqvNSRtSRiEfVPS1oRO9ecrxCmaxfXCMDzXihrhb9B7n1ZFI3zjgTyvKvtd0r+Jz/judP9FIkl/Tro/NzFPD8rwrCTZtRiwH7AbIXFRfr+yyR+lpObVRGFgduB/HR4O+wGz2u5TQu7DDklrEKarsxAG2AdkGvcNoojyVCLvzWx7I4WO+/W2P1Fh7A+AmWw/X5hr6arb1gAAIABJREFUOsrdZUzST0V0uLW+r/Ok8+xo4Nkq75ukfwEnAyfafrjyi+0/Xq1moYU4tXvG1U1uUHg4rGj74nR/f+Ajhae8D+w5nAteTWJUfmRkovwla+m0LVA6PqwqGjW3gRVxL+Fy+zjRSr2TpHeI1qba2K414QpiAVjL67b9Q0k7AGsTyZP9JV1CJP+u9GjVrC/MR2jOlnFXeiwXHgX2lbQUnTcAR3X8qwmPsSphdFTEVxl+3xkAHKY9hwGHJVbO94gEx+uSTgN+mTuRVsB7xCZgooZ6ywJtIGkaOrCCMxZQNyZM6S4AXpX0e6IAkE2rb6TA9h+AP0j6FJHUPBz4taRTCXmdyuevpAGZ/jizlE9iY9bJyKxtHSDp3IE+twrjrIAjic//EuL/quO6PBJkgYr4KmF2+qehfiGZsAdwdSJNXJOOrUi0o6+cKcYqwM4djl9DMNsgulKqJrbKe5zJ0rEdCKb4cEOdGuFNSbXcCmyj8HBZG5gWuLbweNHMbTAoS3aJ9nlcPJbbV+MwQjJnp1R8buFSojuoMlLRcXtC376Tbu9wNIocS3zPFyX2BQfYfjljiNcJxuxTxPzVWou+BUxZceyhkLvbn1hvLE9PHfWrgZ9Sbc48llg3/0TSLcT+/OyaurfHEFJEPyXMqLObhRbQhGfcGNqSKS8S+7KHCCLf/2YYf2NgdeDidP9HwH20zY/nJXwJckr4jViMJrVHINyw/myTkDQJMBed2Ua5Ns37EW7dEFXAiwnDk5eAb2eK0RQuAQ5WmBx0SmhWNjlIVdczgTMVWp2bEGZEk0qa3/brff39xAZJ1wJr236ldPyjhIN7LomTt4FP0jtBMjOR1MyFLYgF4HLppwgDOZLahwHHJHZzayOzItFSW9uGrQlImpkwIvkKUTW/lNBXu1/STrYHvdiQ9I3yIeLz/xEwHJIp5eTCHUQy6HnClLSFbEk02+cB50ma9v/ZO+9wx8rq+3/WDEgZUIqIIiBdekdAQEaUpiKCNEHpKCoCiiAiHUGKwBeQplKlWJAmHRyK4g8VQbpI792hyUhdvz/2m0nuubllct6T3NzJep555uYkefdJcsr77r32WkRL8FeAWxT60efYzmJ8OpqQWqQPBQ5N0icHEgucD2ZYaN4wWOiG/7PMN5sUUhpj1XR7L8nQMVTlPOCVoV+SFVsAm9m+oqoAbo/RcjsxkbxeLU0haU5CD77Gou/DCMzFBLR9c2rT35NInk0iujd3yFic/Q+wAf0X4BtQ/y7HUVJXdYA2+VslPU18vmEXjUYC2ph4rhL7EUnmrxLX+sMK95YtCB3fVtGpde1KwDeabH+KkL/MgQMIeYOjifvOoQQr/EtkMnJvF9Ja8wiC5HI2oW/9ZAWhrgV+qZAlXYSYlwMsQWiRt4wGCZ1pid/mENtFY+rc+BKwue1bJDXOl++hnhhuCQ752UMkjSfIOT8DjpP0W+CXLkhgloz1rqRrgMXSd5bdLLQB7fCMq5rkuBVwZGHblrWuTUlfJbwIekntYaAnPzLKIekDwNjiAk/SbITuVNe41Cem6XnAx+jfClRpe2v6vibmYB4Pg6U1C7BmJvmRQQ1icn9nkuYhbprbEjecRbswqT259ayw/UNEG9i0meKcTyQwN3QYkdS0+y4Gnre9WY447YKkbxIsqRrD+FHgQNtdZ3aYJrNfJI7ldYjF/y+B82rXTEkbEe18s5aIUzw/TTBEJgB7uPvc1ZG0NrCN7a+2MebihCHu0t3Weg6T5UeWrnLhJGl6ogiwPcGkuZT4nUq1gqY5RjPMCOwG7Ao8bLvYKdZqvOsJ9tdYgjEDsah9lzAm+jhxHq1u+94cMRtiZ5sHpPFEmCe9YHvSUK8vEedpYHybWo8XpznbsHQBvZ1Ii8kNiXMkO6OtIc6VxPf1M5q3UF9SVezcSCzdk4kEU01TeyXCn2Jn26dJ2oNo4c5OEElyZ3fYHjfki4c3XqV6rQPEnJ7+505XrNMUpnOrAc8WE2WSPg/c24bkYFZIeh5Y1/btjTJhaZ5zuu15MsR4CNjV9uUpxrK2H5K0K6GDv2XZGFUjrf0OJooalxE+TvdVGG8WogAwD3Cy7avS9oOAt2znMr99hfg9Kj1uk5zKkunYajzOlgFusj3QPKuVWDMRRaZtCU3t+4jOvYEIA1M6/q2EhGaxkyIr1AbPOEnrAuNsX5gklP5AzDdfArYo+xklPQOs6uSlIOkFYKWGx4sQ8qHZfv/RjF5Se5QjTZj/YPukwvadCWO3z3Vmz6Yckv4J/JuonDab/Leb/dQSJA3L+d32dlXvSw5Imo66/MjqxITmDOAqd5F2q+qGIP8E1qIvS2sswTz4hu35MsX7KHAT0UJ3e9q8LPAcsLbtMq2aHUNia0+qqpiRFn1L03yhmSVxknTUxhAdCL+w/c8mr5mF0IgcbW33XYF0HHyRkCJZjzhvzre9d0d3bBhoUtjcgChkFM31SktPKIxndyDYmQ8TutrnZm4Fbow3hrgXHED4XhxIGK1muRdI2h1YA9iuocD0AaLo9GfgF0Txewbb6+aIWRXSd/U/YIkKpYxIicQFgF1yJeSbxFiA0Lpfir4apIbu0DlWfzPyhYjP8Sj9u9yWzxTzNWCNZveYqlBl4jTJDuxCvTX7fuAE29kYdeqrrwz1DqcDCSLFshliVK7X2hBrHMFu3YyYD/ZBN5w77Uaaf+0ALJY23UMkmbOuAyX9kvhNNiPWBEsTBdSLiWRj6U5EhffRYg596GcI2aPb0jX19m5IaKWkrIni3IBdhl1Y3DwL+GeZjsxhxrkJ+J3tExpJDgpN7YVtr1dR3M8TjPpZcl1nJK1HyKnsR3PT6Fz3muOArWmzZ1xmkuMkomhy/wDPL0ocf13nS9UJ9ORHRj9WJnTmiriBaHHqJiwMbOKCGV0OpCTDtrZfHYpJXTbR0K5kdWKb1i6Yd1cU4ySi4vsEkSz5iu0Xq4jVBvyTmJSZvlqANUwCvtNke0uw/VRKpG9FtDdNIooB5zujEaGk04fYj6yMI4cWdSVIk6WzgQ82C00+LcXvEhPMAc05HPI0vYR2AyTNTSSamzE1s0wwE3NiS6Jd8x3gAsKgKqtmc8UoLrzPqSKIpHuI4s95RPdPFnf7QeJtTJhCzUEsak4oywRvgj2Jot/khZHtVyQdSPg4HCfpYOCaVgYf6nrZELP0ddP2e5IeIJImuY0ui/OYtYD10zFRXPzl0u1+hGC2PgJ8gvhcRwPfzzB+O3BxB2I+Qf/Ow+xQGJEdyQCJUzLdOx0a5FVLZxX1lSG+wyeI+WgOtEOvtYYjCXmNbxK+Hd8GPkrIXoz4Im27oTDSvpqYM9c6Ar4H/EjSOrabedW0ij2IOcbzhFbzjYTsyP8jn377k0RR5nHgIaI78DaiyyH3/bMq1JJue6Z/zZBtjq4hvDwyzgcfAPZPxbpmCdoc8o0QpqdXpk6naYDd0t+fpL9sZCmke8FmRCfq6sQxd1TGEDUpmEvpr4Ofc522NBV5xg2jox5J7xAyi9fa/kOLoZ4k9r1pUpv4jFXI94xK9JjaoxypAryK7bsK25cC/mp7xs7s2ZRDoXV8ZK3NKPPYZxDtX68NxaTuFgY1gEJndqOqkhlJPuFxgmk8mBt9y4vmBgb1kLB9Z4k4NVmbh4kFeWNy9i1CEuTdVsfvFCRdVNg0LXETnQWYkCmhgaRNGNjoJher7QEiWXWw7edyjDlEvIUIPbubbE+SpJxMRw2sD9wPVbEOciG1al9KnD+LElp08xHn1G3OpEWfGEGXEXIjV+QsAI02pOvzf4nk/2DX51JGVAqd7iMIlu5xwBFVdU5Jeh34gu0bCtvHE11pMyeG2z9tFxmdwxn/PcIE6HYGSTbmYmpK2gDYC/hmzuLzcDvCIM+cJnW3rGX7ztSy/Qnb90taCzjadlF/vwdA0jpE4uwbtZbjiuKcSCRO96NJ4tT2uS2O+/6GjolBz7eMDL1ikuc9Yr72oO0sfiSSXiKO4YdyjDdErMeBrW3fIOlVYHnbD0r6GkEU6ZqO2nZA0p8I74Sdar+3pGmIbp0FbA/LvHgKY65GkE9mIuYz12Uc+3DgVduHSdqcKHI/Ssylj+2G7rN2Q82lNSfPcTKyjgeTHbHtBXLESbEWJIpYk48zYi6VRZda0ieJLrpNicT5BYTsSFZCSJPrcx/YLqOt3xYMc/40hiCNrAn81Pb+LcQ5DvgssEKRRCVpBqJT6Drbu03p2FMjekntUQ6F/uTdtr9T2H4i0d6yRmf2bMqh0LD9MVFRbGZ62HJCc7RC0g6ENMjXXN44q9n4ZzKMimiZRXOavNTamQeNVXYik9jtPyeSptk11BTGgFfaflv9TQL7oMo2vdT2fjLhSF00qWhlvF2Jzo8zCQONM4hk8ErAibazMFrSgm+5qheakmYHfkskAUy0/z2cWJwTbe+RKc71hNnitPTXB25kGzlXUrgqSPobcWwfkNonlyHYTecSUkQnZ4ozs+1SRmNTCyRtM5zXuYRRmaQriEn56YSG/rNDvKUUJJ0LrEokAv+eNq9EmO39xfbXJG0BfN/2ii2MfyJhPvoYcR07p4p7Z0O8iYT++DRE8bSPtnbZgkO7kD7H8qll+iFgR9vXp4X6Xd1EoACQtBIwxv21gVcG3rV9a4mxJ9J3LjOO+P3foP+8NsvvX1XiVNK7wEdsP98wV+v3Mir2vckNtUGvtSHW68DiDvmJJwmj8r9Jmp84d2ZqcdxRUzRvRGrZX872vwrbFwduzXWtaUe36wBxVyXucQ+UYICOaqi/l8e0xFz6EOBHLq91PMZdJJ85GCTtRbCyFyGSpKcRHcFZ59GS5rL99BCv2cL2r3PG7TQkfQE4yfa8Lbx3ToJt/hYh3VPzPfk4IeM1DXGtq5zENRrQS2qPcqTq8nXE4q92kf8MsQhcx/afOrVvU4pBKrNdN2FuFxQakQsRN/zH6N86lYVBWyUSg7qG5YjkxVFE+x/UExx72S7dPizpZeImUkVSe7IJ5QDHcw2VH8+SPg7cYPsjGcb6F3CQ7fPV1+TkYGA227uUjZHinA7cbPu0HOMNEudsogK/I2GiUvs86wLH2F4iU5zvAeMJM7KJadusRDLtT7aPzhGnHVBfg6OJhFHfPQqjm0ucSYu+ELNrTbVGC9J17B3i3lIZG7wh3kyEE/zW1CX03gHOAr5n+3VJy6aYLekUq69PxCeBy4mF4DU5OzVSrEELD2UKDg0x5gemcUG3W2F89HYOhnBiTx5t+2JJ5wGzEiSErxMspCxGoe1CKtIdafuCwvaNCROslUuMPaxiE+T5/VPMqhKnaxL35HdSt8Rg14AsDL3E/t+Y6AQyIXdzQVnGYSEJPAbYhjbotUq6E/iO7RslXUd0mXw/kQX2sj13i+NeX9i0PHHNLBbQ/zHSi+aNkPQcQdS5prB9XeBs23NmjFVpt2sPeZGuR8fYXqHkOJOLdenxUcBPqipwF+M1bJ+d6BJueT2oMB88h2BlV1ackXQ3Me9/eYDntyDOz/c1e77FmCsycIdwli7kYezDLISef0vx0j34ZGBt6ONFci3wLdsPZ9nRqQA9Te1RDts3p6rvnsSJP4mYoO1QXOB0ASrTr1V/g6AB0Q2J4AZ0QiMyK2w/Vvtb0u8ImZgrGl5yp6QniAp9js97CaHXm90YxPaYZn93CAuS7x4wL1AzgpoEzJz+/hVwC1FxzoFdgN9JWoPm3Rq59O3WIRzvn5T6KBA8AHys+Vtawh5EcXGyaZ/tiZL2JWRWuiapTSQ1a5PKZ4jj6570uJkGekvQEKZa5NPr62F4aKscl8OAdidJ3yXMDwEedoMxbavJ7Ib3v0mYxJ6fiqrbAicB00hawhlNcHMlLYfAmQSTvjjnW5ko3I3PEOPHBOMYwmDvMuBPwEvA5hnGbzcWp2+3TA23p+daRpt+8yIeJubQjwP/Iq6ffyNMapsmIYaDxkS1C5JAVUDSKUShZCLBahNRePq2pJNc6EqdQhQlcirRa22CM4jOphuBw4E/SNqFIKO0nDy3/ena36mA/hoDFNBb3/X+SJ2AC9HczDuH1MFvgNMkfZ/6vHM1guxyfobxG3EocJikSrpda0gkk+9QN768j/CkGEhrt4fmeI66SW0ZFKXHvkEkHqs6BgaSOpuOYPGWwVxuj0zfC4Qu+Gdsv9H4hKTNiPXgPrmC1ZLkhL7+OsSaaRFgTsK0ui1ISfyWE+iJQLeewoByobT5wSqvN6MVvaT2VIC0wNuq0/tRFo3JzQrQ9cnfZrB9UKf3ITOWIlg5RTxCyYVmAyo3BkltjVcBO1ddXGrSgirClObzBLsxB54FZiO6AR4HVgHuIBbROU2wvkJMXv5HJGIaF5cGciW1xxGt4EXMRl7jnvcTpnpFzEG9MNAtuIUwnbmPMIo5WuHdsHF6Lhd6plojCO1O0KVujd1S6+ydDdvHEUmArMa3hF5vrSOs6u6ZqjoPlqO5ed8tRMtradi+uuHvB4FF0yJtYm52e5vwJrE4LrKkPkJ0BmSBpM8RciZXF7avA4y1fWWmUJUkThsh6SbChP5Ggr09oNFyi+NvRBTRtgfOqh1XKYm6LXCypGvdonRbYxK4nbB9bMPf10laFFiBSGzkklVsSwFd0iqEMXHNo6YRuUzivp/GOpvIY4hI/J1M/jnALkSi6WlJlXS7Svoy8GtCGqLWgboKcHeSa/h92RijDervtVRb1+xNvRiVNWQFY9akGyGO5x1TR00NY4FPEUXIltGmhDZEgfQG4GJJn6/FlbQpMVff13ZOQ8p9gO/aPjF1iu5G5AJOJYg1XYWUxP7bkC/sYUD05EdGIdQB45Z2IummNWs1qUyDuNshaQXqDIB7bN/eyf1pFZJuIwzodrT9Vtr2PsIgZslME8y2GIOklrBPtiGpXWxBrZkqTSBapkov0CX9EnjC9kGSvk0wZm4GVgQutL1D2RgpzrNE4vpwV6h3p9AJ/oft/dJkaWkiYf9rQmd1k0xxzgbWIBactcnMysT39yfbw25T7zQU5nwzOYzixhGL5E8SRaLv5SpKqmeqNVVjkDbdDwLP2i5N1ijIj6xOsI7PILThs153huo8KNN23BDjFWB88b6f5gU32O62AlrlkHQ+kSTZ0Mn0NLUZX0y0g2+WKc6dhFHjFYXt6xEmYcvkiNMk7sfInDhNCdJPEdf9aYgk3Q3Uk9zNCsVTMv6lxPz1hwM8fwSwqO0Ny8RpMu48ALafyDluO5HmMRsU2fSSPg1cmusaIOmfBIP+ACKx1CfJ4IwGwpJmJDrCIPxhSh1fA8Q4YLDncxCHFB4E57pgNCfpIOCrthds/s6pF+rrtdSIW4DtXdBbb3H8DzfIj0yWVSwzbpM4tfXmx4AnCTmgGt4iDEP3d8HbYaRC0hzATcQ6fTPgy0SR60Dbh2WO9V9gCduPKox9x9u+S9JiwARnkNbsobvQS2qPQmj0GrcsQLSULEXfm5khn9vxaIKkDxGJuPHUW0xnAa4HtrD9Qod2rSVI+gTwB+K3ry3EliaOgQ1sd02VU9KxwJseBc7miSk1xnUn+i2oJzRPrRUgMsT5D7CSqzeKXJLwILgNWAu4FFiCYGqvlit+WpT9lEieTZs2v0Po9+5p+78DvXdqhSrShu1hZCMV6EXIDixMFOZqGEuwhA63PVfJOCcBWwBPEJId59p+scyYQ8Q7keg82I8mnQe2z80Q4w+ELNRXbL+bto0l2vjH2V4/Q4xxBEvuMzSXHchSDG4XJH2UWJzPTkiOACxLtLevnSvBqTC9W8wFXXNJ8xEJ3HFN3jaiIWkawrdnTWLuuRbwnu3pS447+Xo/wPMrA793ixrUhbGmIRKzuwK1e8rrwAmEf0hW9qOkzzDwuVO6+6RdBfSUaFomdWtkhaQLh/Gyd4jOwWvdJSaLkt4Ali5+ZwrPgzvcZSa77YD6ei1BIuvk6g5JuZOfU+/Y/DahS92nKONM2vqJfLRxYydFtyIVAf9MrP/WAA6x/eMK4jwJrJ8S2XcSmufnKyR3r7JdNBPtYZSjJz8yOrEWdd2njrTTVYTjiNaSz6T/P0EsOI4m2tFahvq70Q8IZzK8ahNOIGQMlrB9H0xmup9FMF6/0sF9m2Kk5NUChJzOomnzb4DzcicAEwN8foIBkq3duAHTANtL+izNZU66xo0+sRffa3j8a6KYkhtnEfqsWSv+Rdi+W9IiROvpa8Si9kLgRNvZ2toSs+hbkvakL+Povynp1HVI502zhfnjmUJUog3bw4jHy8Q92tQd4hthIglVFjsTx9bDRFJuTal/57HzmRBtQL3zoGYQ+2Bqdd8KKJ3UBn5AJGjvVxg6Qiw230/MF3Pgl8T39SuaMDS7DbafSi3uWxGyHZMItv75mROarxDa8I8Wti9EYU7QCiRtPZzX2T67bKwGLECQT5YhSAevEcdfWXyQYDMOhCdp7rPQCk4gujX2oq8p+YEpxjczxamxgfcnmO1VnTs7EwX082hSQM8Y56/EsZs9qU0hoTgAxhBFzx0l/bTIfp4SSFqI6KY8W2E+vCRRWL3HdjO9/VZxA3E9Ln5nq5NZ77wKdGL9nKvzbxDcRF9t7r9Q9/CYvBu5grlD0kc1SJrB9qSSYzRKwuxJyANdDFza+FyuziDiN1qb8Ff6HXCcwkR4bYKU1MNUhh5TexQjMQ32ISQGBpsIdgUkvQisldrbXwE+Yfv+dBE72nbR5GVKxm67G307kL6nz9r+e2H7J4BrbM/SmT0buUjs2ROA2jGxiO2HJZ0APGX78ExxirIgjbAzudEr3LMPJgpczZKNLU8y1V/XrhneIWQBSpteSDoe2JrQ676T/kaRXVMIGAgpmb4Dkejqmva5tN+nEQz9Pk+RsStIYRD4ru3jU0Go1rkxLSFzclyOOKMJqUCyLQMzAXMlNiuDpDWJ33kC0dLaeD15C3jM9tMZ4pzJMBartrMYZLar80DSXESRrpagvRP4WY7rchr/ZeDztptpd/cwACSdSiRLN6p1AKVk2u+Bv9veseT47xEM43cYWBfWOZJNks4jChvTEQmHG4mE3Z3OsNhMn2XOgToMJc0JPJ3jXpPmzlu4oGmu0EA/PycLUNIzwF62f5VrzML4YwkjxbuIa2WfAnqG8RvngQsSprFH0dzMO1dCa6h9+gJwku15S4wxM2E8uQiR0HwRmJ4oBpbqdpX0xYaHcxFz9N9S9x9ZBdgUOMD2KS19gDahsH6eHdiXMO9rLAatSzB2j6UEJM0AfMb2ZenxT4jrTQ3vAvvlYmy3C+2Yo0k63vauTbaPAy4rm1gvSMIUu+kn/51xLTAbML3tp1O38F7UO4R/PBpY7z1MGXpJ7VGOpAO1VLG1sRuRqsHL234kaZDtaPt6SQsSi79ei1YB6fdfw2EW2rh9OeBG24Nqro9EpJa8gRK0B2cY/zhiAbA7Yea4dEpqb0jogrVcPOkEFPrQCxEJx+for3HYcpFGA+vaFWEiEb217btLxKusEDDMBH0tUNaFWSqkbE7IkKxKMLZ+77ymKpVC0s1E4uRwmmtp3lFR3OzasKMNkn5GLJgup/lv892S409LsOa/UOsIqgrp9368WZJM0rwZOwLagtQ2+x3bN0q6Dvin7e8rDKT2yiGl0A4otEE/V/XvXyVSoulK228Xkk794EweLpI+QMwzVqTOQp6bYGhubLtU94mkewjDy3MIgktl18g0H3iRkO2ZAPzZGXWOm0gCFDEjsFOmpPbzwJrF41mh13qT7WYGz63Geokg6VQmqybpf4TMzWCeMa2OPdQ8cHKiK1dCaxj7NAtxvJfqqJH0C2K9cQch3/RWmiueAfzbdkvdruk7Gw7a9p3lgKTfA9fb/llh+y4EwepLJcffmSiebpAevwbcQxRqITp4jyybPG83qp6jpRgPAefYPqBh2zji/oPtNUqOX5SEaYo2sOy7EgpfoJ2JTtRVbT8maXfgEduXdHbvugO9pPYoh6RLCKO2rmEXD4TUNnu07YsTI2RWghHwdWAF20uWGHtUmmum338WYjL2dNr2UaKleaLtjTq5f1MKSTsRDucvErp5jRcwO49R5GPA5rZvUYM5SGJP3dZthYD0GVavIqk4zEnMGGJRvSfwobITp6owJQn6jEyDVYAdCUbO44SZ66dtj/iW0yIUWporuKRBTw/5kbqctnbBjC5zjKeIRWvVSe2BjCJnJwz8uiYBANV1HqTEy9223xuqYJcj0Snpq8CGwDY5E5nthBrMwYZIOmVNNEkS0TI9mUVvO4dcR238lYmC6eaExMFphFZ81rmspFkJGYXxBGN7MeCfBFv7BtvXlBz/BobXRVG6lV/S/kSCbDvbb6Zt0xHf3QPOYBDYEOsI4HXbh+Qas0mMW4Ef2M7elj/cZBZ0X0Irseg/TySadgW2dEgTrQxc7V63ax+kzqNl3V8ffCGiYFuq8yjlAY500ktXwcAx3Ye+bXvVMnHajTbN0RYkiqVH2v6/1IlwNUFGWT9H10a7kRjaC9Gc5JbtHlo1JH2T6Nb4P+BHwJIp77AtMacaTVLClaGX1B7lSFXNA4gkZjPd3ixsk3ZA0rqEqdGF6QZ5GdEW9hKRhJxQYuzRaq45D3WTu5qx0TyEM/EX3WWyNCnhfJLtIyqM8Qb1G0pjUnsZgqHTctuphmd0A+TTbJX0d4IJeMuQL64Q6Zy9wyPU+KqdCzNJexBJhg8Q7a3n2L5D0tvE8XZvmfE7gXScfdf2nyuMMYZgs2wMzEdcpx8BLgB+1Yy92wNIeppwhm+mRZ0rxj7E/XhHV+NBUIszOfFY2P4x4N6Ren0ZLho7D4CHbb/e4jjFBO1ABbsscxpJtxPSAyL0oYuyA6ULzj2Ug6J1f1NgO8KT5mJg+1rStoJ4CxFSBFsRRtLdNHe+iJACeJNg6UIUHd5HQa81Axv4OEJW7U4qklWTtB7wE8KQttlasGvIOu1EY7erpOUJ74DvEobFN7j3TeqCAAAgAElEQVS7PJYqR1qjHW/76ML2PYBdbQ97nj3A+M8QLNZH0+MXCPP42uNFCNmmrjIJbMccLcVZmpDOOYjw1HqTYL53Y0J7FcIj4GP0n9t0W67mXmCfRNpszDssSVxnPtjhXewK9IwiRz9OSv83mxQZ6JqT3vbVDX8/CCyq0FSamCGZ0WiuuRZdbnJUg+0n0kTss9SNFe+zfV0Hd6sMZiUMIarErQQz44T0uHYs7EhdI65VNBrdCNgobbs1bVuBYNYPO/k9DHwLOFzSwUQxo7hgys3WmpvQtSwy3R6hv97ycMZrSyGgzQyiI9K//W2/28a4WVHoavkBcGRKbjbT0ix1nCU246XA54gkw13EObQYcCaR6C7V2jqKcTSwm6RdKkz8r0QkgdaRdBf9kyZlEz/H1IYCDk7FxxrGAisTrNCugKTvNmuRTtehxxpYVKu1GGJ+4IWGv6vGxW2I0RYo5HSuAna2/UDFsQY1snMGSbWGsSYBZ0t6lEhqbEHorGdJaqduiTUJpvZ4YHHC4PUPhL52N+FlQte8EU80e2EGLE392lXsOM11va4xQC8tjFnTv83ZefBx4DvEvRngPuAE2/fnitFGTAD+T9JWtm+TtD5wEWEefvXgbx0+JK3EwLKK3eQVcwDwS0njCdNQiHvzesBOGcafhQYNbfeXARpDX43tbkE75mg4PMm+AFxL/D5fcEmDyA7iFOrr9W43p54fuL3J9jeBriZqtBO9pPYoh+0xQ7+qe+FMJkcOPcv5Ce2iG3KMOVKQbpDXpn/djt8B6xA3s6qwD3ClpMWJa+Ru6e9PEgu2luEGc7HUcvpbYuH8bto2lihE5Uw0v0wY2xQ7GbIvZhLuBZYFHm7cmD5jKxIow3G8zw5Vq92+H8GW+5qk8wmWccta4x3Ey/RfIBfbm3MdZ9sCnyJMgvpoqyvMgi+WtLXts0vGGRVoUgxaC1hfobFbLDjk6ApplgTKiZqXgYClCMOzGt4iri0/rTB+bhwm6aVmx6vqOpeztzp4Y5FusIJdYu+WRk45hk7Doak9bI+FkihKwE1LLHDfAR4iWpJLQyE7tw1x3xlHaGx/03nNtJ4npOH+BPyCYJjdlXH8tsGZjGCHGasdreVtaV+X9GXg10SyqUYCWQW4W9IWtqu8R1SBXYhCwCMKI99JhNzBf4ha+/tsvzXYAEMhEQF+DNxPf9+brkrU2T5T0n2EVEttXnEfIYH414HfOWw8SRR+BiqQLE3dm6CbsDpxjmado6UOqmbH0JuEQenNwRfpym6qhYFNilI3XYpHiHVzca62HnH+9DAM9ORHeugaSJqeqP4PlGgqdUFOLbqPEa05E4gJeTfeHGtJnp8BqxQZkgpjor8QydSu0u6V9EOi6+BymrNBj88UZ0Fgb6LddCbgNuCInAu01Da3epG9klguf7HdckKjMN7fiAXycTQ3iszKoCpq3HUj1Abt9hRnTUKGZBNCbmAJwpzq5hzjV420/8NC2eNM0jXABNuHD/D8PsR3t26ZOKMFks4Y7mvbmcApi/S5duv2dnlJmwC/IqTTLm3YPhOR0P4QcTw/U1H86YiEzZ62P5xhvLOA09xFOpaDQdKxwJu29+5A7PcT3ScX2f5VybE2IxLZaxLM0jOAy6voEJK0hO17co/bKUiahmCcLwicZ/s1SXMBr7YqCzTaoTCjO9f2/oXtBwFftb1gZ/asdaQusVq361iCuHEtkbi9xiV9JCQ9R+idn1lyV0c9klTPZwn/lv8VnpuBKKZcZ3u3jDFnIeSamuUdspAohpqvtTpHk3TA0K+aHKN0YTqdK/MQ/ib/G+r1JWNNIPTBr6oyTjsgaUfgQGAPwrdhR+K+80NC0u/Xndu77kEvqT0KIWnX4b42VxKwHZB0LsHSvYDmyblSF+TULlX7tzKhnfcwkeC+nnB0fq5MjHZB0qXE/jZ1gE7HyKfdfUaRgzm32/YCbduZkpA0EdjWBVdjSRsCZ9qeNVOcN4Dl2tX6WXVSux0LTbVBu70Qb2ZgSyLBvQLwN+AC28cM+sapCJKeBdaz3VRiQtJywJU5EnQ99NAOpIXMcYSm5Q0NDO0PEwntp0uOPx2xUFqbYLMf6dBs3A44FHgX+FmO65ykiwlpoMeIxOlZtp8qO26nIOkEQuf4AZprEFcqCSBpKeAPtucrOc57hAnxucS8uSm6aS3QDii07a8C5iXkDBZxaJweB0xne+eS419IzP9eHUpiLVMnTS3ujMRnel8hRmmz2DT+G8DSRfZk6ny7w/aMOeKMJih0oj9VtdRRu5BIQdsBCwC7O3wd1gceL1v0kjQnIdXzFkHcqmlQf5wo0k5DrHeyrNUlbUBcO2ciOmiLBJeepnoDFL43/wOWaIN010ZEh8NRNCe5ZbmmtQuStiLma7XC39PAAbZP69hOdRl6Se1RiCaJvzmAGYn2YAhNqjeISlo3JQFfAT7XDhZjYoV/knqS+xNEW+i/bC9RdfyySEm59QZiEEhalGAYzNvePesOJBmQjahrAt4LXOKMBmgKjditgcOIJCZEMWVvQo4iy6JZ0k3AwW6Tjnpi059s++UhXzzlY1e60GyI8yrh4N52tnlKZuwAbGn7Q+2O3ypSoux1278rbN8UmNH2WSXHfwv42EDM1VTYeMR2N+opVorEaNm4eE4mRujFttdqcdzbCDmYiYO0uQLlOqk6lQBqByTtRbjdb0hITXyUSGiX7hJLElffAK4j5jNzEAnnVYj7zu9yMnYlzQF8jZC5WDzFPY24d7492HtHGiRdP8jTbvWcmYL4qxNJ7VLFbYV+9lALvZYJAUOd94UgXdPenoo0rxH34peoG3eNB35he+GS459BGOe9VhVLsxCvdu6vP0CMLDJ0kq4gritnFLZvB2zRLZ1UklYFZrd9WcO2rQkt+nGEh8B3nMFkNd0D5rK9e9mxOo3UvXclcDMhF7dYOm/2Bla0vUmGGPMTnZRrw2SDwJrM5rdyztsl/ZvQo9/H9htDvT5DvDmIBD3A/bZfGOz1Uzj2SoRh718L21cG3rV9a/N3TnGce4AdbN+SY7xB4hR9m6BuiO1c17R2IxUeZ3LBDL2HodHT1B6FsD3ZFEjSloRR3A41pmaSN/gFcGpn9rBlPEVMMitHapuZIOnPBEt7fWJxuOigbxw5mJNC1bKAd4gFbg8FSFqC0ND7MHXdth8AL0jawPm0j79PSFvsAXwkbXuGqDofPdCbWsAJwHGS2lLNtv2TnOMVcBzRXrgMsdCs4SLimpYL7dBubwqHxM3ukvZsd+yS+CFxjSzieeDnQKmkNtH2O1hR6V16c5qBMJ4CMy9hemCNEuNeQt1krkqjwFeoJ846orFfFWwfqTC8/iPwKDA+R0I7YVNga9uXSloSuJM4R5ZxBYyWtAA/BjhGYVC9HSGx8rqkc4jul65gI7o9OsfNOitFzAe+RiSHSqEs03sYaDzvpyfWG/fSV095Ceqm9VkgaQ3ifrMgoav6lKSvEYXNP2cIsQbwSdtvSWrc/ihReCqFxkR1jqT1MPB/BKFpZeAGgrQxJ7AvMQfNhUuBIyStANSSWqsQ16IDJH2x9kI3yC6NQOxPfE+XwWSywWmELNB9wJ4Ek/LADLF+ClyepFvupRrPi3bhcGBf28ekrs0aJhBM6tKw/QiwXrpvLpQ2P+hMHlsFfBQ4vuqEdurSqnUH1SRO3pV0NlE8yRH/ROBI6gaeNXyUWOOunCEGBDHrKEnfzLheboZ2GGC3Hem3rryAMhrRY2qPcqSb5Ca2by9sX4Fob++ai0JqX9qV0IIe0PioZIz3EROwT1OXIXkCuCn9u9H241XEzon0u+9hu2miQdLGwE+7iakPIOn0wZ63vX2GGP8PeAHYxslESdKsxGR2DtufLBujScz3A7gCndh2VLMTs31b4DM0153LwmqT9BKx0Ly/UeZE0nzAvblaW9Um7fbRBEn/Axa1/Whh+3zAfbZLGdKl4/hK6knUIqYjulO6kp1RBVQ3u/snYRTZuOgbS5jQfKMNia8eCmjCOP8cYXbZR7KjTEIjdTfM7yQDImkS8AlXbN4n6SPE4nw7YG7CQPSjhK7zXh5AFm1qRJPOyveI+ccE4Ce220LkyAFJvwSesb1fYftBwDw55mdpvC8TxZJzieT/4mkesAvRzfm5DDEmAqvZvrcw11gd+L3tOcvGaCeSxMWGtv+WOtFWtP3vlGTey/bqmeI0m282w4hmUqbva4Mae1XSoUQHzerp8abAQbYXzxDrZ4SG7vU0l9bsJs+L14GlbD/SZI7+L9vTd3QHpxDpPv1r27+tOM6phFb4LgTLHcI88njgWtvfzBDjdUIa6OHC9vmBO23PXDZGGm8ioQ4wDSETM6nxefckW/phkI4nE3IuDxKypIN1kE316LGaRj8+QvPfeSxRpe8m3EowQR5W6LYVE02lLpSpRXtlwoX2RoLJvuVA7e4jHFcAh0i6ys3NNA4iMRC6DMVW3GkJJ+xZiEVgDixLTPgn1jak9vofAX/PFAPorw+dtuU2ImpH4eo4Iql9OXA31Tm2jyGuXUXMTd4ujq8DrxNJmKIZoomJZg998TzhPP9oYXuRVd8qhsP0zmLaM4rwT+J4Nc2vj5MI8+WsUJgdFgtbpQp2km4k2MzXA7d0m5xFExQZ5+dXEGMssais4R3iupYdkqYFvkgkstchWOH/R/gevJpesxFwOjAik9pDSds0Ihd7spuIJcPApsCKTbafQ8zfsyS1CXbxzrbPlrRFw/ab03M5cA2wOzEXAHC6rh1EzK9LoQOyLeOIezTARKJT899E0T6bLIztMUO/qiswK3016GuyGjX8nTDEy4FtgC/bvjzTeJ3Ey0TeoVisW45CwbZLcDnBOl6c5gSXXN0GXyYIiDc0bLsiFaJ/C5ROahOEkDkJr7BGfITBuyCnFJXJ6KQi3JW2327s+miGEd4JUsRVxG98F3U50pWINdWZJDk3SRu74MPVQx29pPboxx+BUyXtaPs2mMzSPpnQO+wmnE+wffahSTU7A9Yg5B8mEG1nN9rOkYzpBH4MbAz8O7EAajIaiwLfJha7h3Zo31qGmxhbKowpTgYeyhTm38SNv2ho8iGiWpoF6q8PfS2RmP1BepxFH7qqroYCtgA2s116sTcEKl1o1jDKEg3twvnA8Ymdc1PatiZR8Cjt3N1NbKURhPmJjoyHCV+IRn3GtwhfjSyayont8zOiSNfIxhJxry7LynuESJgeCExKHTXXE/frv+X6HO1Cm45nAWdKqnU3TA+cIqloepgjQfsMUcg4n2CDNzN0vZ66t8tIRGOhQYREwytEQhbCxHcWYNjJ78GQCgGTCP+GKtu024VJwGqEuWYjViPYZrnwcer3mEa8Qvw+ObAHcLWke4nz5jxgYeBF4CsZxm+3bMv9xPf2KNER8o2kt74zce5mh6Tpi6SaLsJzxP3zidTBuzxwQMPzMzO4xOOU4D/kW790Gr8m5Gc2Je77YyStRkisdCPpoCZruH+T53LMa2qYkeZGvs+n53LgGuAnkja0/QqApFkIf41rM8XAJf1zhsDFhDTo8wwueZfzt2kHPggcbfuQxo2S9iW8hNZJHU/7EbJ/PTRBT35klCOZDpxFtBnXbsDTAFcTxktdI0Sf2Nmr2r6jovHHEYnt8YT8yLJEgvNG6knubKYNVSMlTU8G1qWvmcbVwLeTLtmoQNKJv8H2R4Z8cfP3v7/h4eqE7tiB9NUE3B/YO1fiVhUaEQ1VwW5Ejmq2pKcJLdh/D/nicnHmJo5fEQvMW6kvND/VTdez0Ya08PsVwdarsT7GEAuZnW2/NdB7e6gOKXH2c8IstrJrvqSbifPyOJq3UN+YKc58hJTKmsS9eh6CfXwzMMH2UTnijAZoCAO6GnIk2JOe8e+6OInVBwqTzdmIa9e7adtYIsn4qu0sngeSHgY2qmpe204ozOAOIBJBjebX2wOH2D48U5yHga/bvq4gcbA1MUcrLQmR4kwDbE50G80E3Aaca3vSoG+c8jiVy7ZI+iowje0zE7HpKuL4fotYC/6mbIwUZyxBPNqZIIfUzLwPAR61fVqOOFVD0snE7/4D4EsEm3qu2jxG0lbA7rZXyhBrO2KNvp3bYEZYJdI88ESic7PmgzKWKApt223F53ZB0h+JdeDWtXto6qo+C5jN9mczxPgoUQycHahJ0i5LzNfWtv1E2RgNsRYkSAgLArvZfj5JyD5uu0gYm+oh6RVgBdsPFrYvBPzD9gckLQr8PZdMzGhEL6k9lUDSItRNDv9VdfKpCki6jXA2rtRRtyHezESCs6avvQzwgO0l2xE/FxR60AsRCYcHGmU1RgskfQ44y3ZL5pdJB7DxYthYBOjzOJcOYJX60E10DWsa2o2P4488mtp7AAsAu7jim0paaG5BtGVVudCcm2inn5eCyZ7t72WKsTzwdk3jVtKGxETwXuDAbkwEp3vNMgRr7642dQr0MAgkvQwsV3FS+3ViUn7/kC/OG3cBImn2HcIxvpvYOT2MUEh6AVi9eDynAvpfbM+eKc4ORFfd11yN0VlbIWkzYDdgsbTpPuC4nJq0Cs+LrxLn/bWEHv3HCFmbQ2yfkCtWO5ASGiu6YKIqaWHgVtsfqCDmjMSa8HHbL2Ycd38iAbw/UdxYMs1rNyeSwKvmilUlJH2Q6MhYnSiabmP7oobn/0jIYP0oQ6zbieSfCCZ9UeIimzxMlZAkosj8AsE8XYqYo99ePLZ76AuFkfPVRJdurcC5DNHhsm6uRHAi721FfY5+J3B+Tjk3STWpnpuBTwGLpWvA3sR1bpNcsUYLJD0H7Gn77ML2rYGjbM+ZJHBubDXPMTWgJz8y9eBR4ob5kO2c2kntxN7A0UnbuJm2VW6Tvf8SbWH/ITTo3qE+Ue8apCR2Vi3oTkHSMcVNhB7Y5xme5u5A+HSJ97aKyvShG3UNJX0WOIJgz9RaW1clJGr2KROnAbXiz/qS7qFC9/Z0/Ton13jNIOkzwKWEbMOihE74fMTxdlvGUKcSbvF3peTcr4GLCLbzjFSoTVcVUsG064qmoxyXEGyzKrWMaxqjlSe1UxfS+IZ/HyK6arKwwXtoDZJWBDajeSEw2z2gTZiGuPYXj+dFKejFl8QuBOngaUmPEfPOyciZ0Eos2i9Rn8feA1yakz2ZkteVmqoR98wxhLzijAT78E3C/DxLQlvSNsCLNZ1jSUcSsmf3Al/JXKxtl2zLZCRGcM65TA1bEyz6P0o6pWH7HdSJVSMeKdH/KUkfAF5vco5sSj5/gsFkFLoJIiQal0hJ7GzM304iJWm/T/26eS+RaPxTrhi2705FrK2onyfnk5mwY/u/ROdelTgc2Nf2MYmwVcME4n7XMiTtOtzX2u4m76MTCGm4Fajna1YiDGQPS4/XJXxyehgAPab2KEeqxp9AVM6h3gp2AvBUrnbAdqCBfVo8aEUGBm3SZl6RuvzIaoS5ylOEFuT1wPU95mHnIKno/PsewQqYAJzeTQUbSb8BXrH99XTjX5r4LJcQ7JksmquS7iZaqP9c2L4G8HPbpQs1Q7W55/osKdbCxPn5Ifqb0R2cKcbfCDOSA2osekLD7VzgKtsnZ4rzCrC87Yck/QBYy/a6SYPw17ZzGRFVglRk2s/2f5sUnPogF7u9hylH0uXbg0gC/YP+ibPSk//UbnoKUXC6m/6FrTtLjr819ST2B4G/EEnsG4mWzG43juxqKAz7zibYZusQ+p2LEBIEF+W8B7QD6Xq2NbGgbJTS2Bv4VcZunQMGe972QZniLESYns1NPVH/cSLx9HnbXafpm6QOFiLYoPc6n7k2ku4Hvml7gqRViWvn7sAXgHdyFmnaIduSChrbAp+h+dxprbIxUpxJwKK2Hyt0IC5OeB/MlCNODyMTidSyQ7s6qqtGku05g2Dt35w2r0b4LWxr+7xO7VurSOdis8JzFmPF1LW3lO1HmnQh/8v29IMOMPjYxW7DOYjCZs2rYxbgDcIvZoFW43QCSdJoF+K+DHGfPqF2jCU5GnuUSLxVgV5Se5RD0nHEBXh3QkNt6XRx2ZBob1+uozs4BUjV0gHhkpqdkl4lktjPUk9i39CNk/0eykFhnrEDfRlNpzuZa2SK0RZ96LTIWMkFIypJSwN/tT1DjjjtgKSdCJ34F4nztPEG5lystjQRWzYlmycSbej3SFoGuMT2fJnivEpINjwg6VrgMtvHSZoXuH+k/zapyLSR7ZebFJwa4VyL5h6mHE0WAo1wjsm/pFUI3cz5GscmX9H5PeBxggV0Wi+JPbIg6U7gVNsnNhQCHyG6UZ6xPWjydqQhkRy+T0hp1Lw6niE044/OyW5uByRdQZyLW9VkTiTNThSh3rP9+QwxijJufdBN0kAKD59FbT+u0Ff/iO2tJS1BrAuytoBXLduiMIzflihsPEN/z4PvZorzD+BY2+cUElr7E7q9a+SI08PIhKQNgL2IglDXm99Kuo8g/xxb2P49YKccpKA03g+B52yfXti+PTCH7SMyxFiA6ARdir6SlIZ812dJTwKb2f5L4RqwEdFNs2CmOFsSBrs7OMmEJXmwXxBzkXNzxKkaCknNfYgcw5Od3p9uRi+pPcqR2hk3t31L4eKyEHCb7fcPMcRUA0nfIJjYvdb5qRiphfpqoiW0xppZCZgBWMd2tpZNtUEfWtJNRAvr12w/l7bNSbDqprc9aLFoJCFdz07KMcEbIs6zwKdt3yfpXsJ86tKU1L45F9tI0gSCKXcdcBqwuO0HUwHvrFzJ8x56qBrpPLmPMNltZhRZqsNJ0s4ES3tNYHrgzyQDZ8JIpzeZ7SAk/ZdoO39U4Rcx3vZdkhYjDDxbMnEeCVAyknZ+ibtKkZhdJ9veNv0+qzj5NzS8Jts9LZFlGjEtsBzRKXqAS5gESrpwuK/NwaKW9DyhZXu7QvP4GNu/Sh0pd2ScA7QloSHpRcKELovR+SBxNiSkAH9C6GofQDAPtwa+YPvaKuN3IxKL/rsMLN00Wyf2qxUkEsiMhHzTW8Q6ajK66bMASHqTuK81M/C7uwzruDDeo8CWtv9S2L4y0bU5f4YYfwDeJSQtHgE+QZhGHg1835nkVCT9lOg02ZSQIlye6Ng6Gzg7Y/fRQ8Amtm8vbF8BuCDHd9YuJHb7krYf7fS+dDN6mtqjH3MQbfNFjGMQRsVIhaTpiQRgs/a5Uq0ztk8t8/4eqkdiFh3MwPITOSZMxxJ6yjs5yZmkhccvgf8jjC+ywG3QhyZaWC8CHpdU07ibh9Bv/FKuIJI2YeBJeS5d0FmB32UaazDcQuiE3wdcQWj5L0UYeuVsq9ydkDT5EnBow8R5E0JeoYceskKSIKjTmYf+GPDF4uIvF2yfQsib1Npn1ySS3HsB00m6mShK/7SK+D0MiYnAzOnvp4AlCe+TWYgkR9ch3ffHEyZutRbguYBXc0ldVJXQSoy1C4jWeQjN6ZmbvHQmIvlUGrYvabL5giRJsDlRuG0V2brkholrgV+mhPYixDwAYAnCoygLbL8jaS8i4VMl3iL0jiuF7UsSW3d/QubqYIKssUEvoT0gDiASjUcTXjeHEh1PXyK+v25C1/nADIEnCMme4rnzWfJqhn+Y6KAo4gXqnUJlsSohcfhi6qp5z/afE0v8eKIAmQP7ACcS389YQoN8LHEP/XGmGBDfS7M85lgiid5N+CMxp320w/vR1egltUc/biVM9GrmKbWF7I7UTeO6ApLWIyZ+H2zytGluutfD6MKvCA3F02jCBsyEFWlIaMPkhceRxPnUMiR9kdBqfjv9PSDKFmkaxnkwSY2sTd2A5D7gulyJLYV5x6HAmcCGxEJ6QYLhfmKOGAm/I/RaTxnqhSXxPWKxD7HgmIlYlD+QnssCh87wUk2e2pNgVIx4SDp96FeB7e2r3pceBoZCk3pPQuIISf8mzI5+lSnEBEJyoh2Jk3uJhdLJKcn4LeA7wHpAL6ndGdxE3GPuIq7Tx0laK237Yyd3rBUozEivIhLN0xFJzteAH6THO2cKVVVC60vAQbYvSI8vA34uaQf66jafQhTxq8QtlDQnc/s12b9N/B7zAF+2/VLavgJh4JYT7UhoHA3sJmmXqrtaEuNz7SpjjDJsRaw5Lpd0IHB+kr67E1iFSDiOWKjBW4VgAP/FXeRvNASOBo6XtCx1oslqhJTPbhnjPJHGLUrFrQY8nSnGWOIeBiHhOBeh2/wYdR3n0rD9FrCTpIOJ9c1MwO0O89Cc+CNwqqQdax3UiaV9MtH92k24Ejg8kaea+d5UfY8eFejJj4xySFqdOFnOIS7CpwKLA58E1rT9j87t3ZRB0gOE+dDBNRmFHqYuJAmd1W3fUWGM5wipjmsK29clWqdargCn6viHbT+vuvFpM7jL9Cf/RSygzy/IHB0MzGa7Zcdr9XW7HkcklS8nkidFM7oRPfkfjUjH8WPA7dQ1+vrB9kZt26ke+iDpPx4C/Iy62dHqROJm36JeZIsxvg7sC5xO83MzlwnRh4hOnfHp3yIp1i0EUztLa2sPUwZJsxFyVk8nPeq9iHnmA8CPbU/s6A5OISRdTCQAdgBeon5PGw/8wvbCmeI8BOyaElqNXg67EnIhW7Y47rRu0J1X+IScBWxA/dychkhob+uMfiGF/ZiBkKJY33a2xMloQpJWOoDo2sqW0Ggi2bIW8B/CI6Z4fc5ifClpnhgupFQkfQLYkjDyLFXYGK1I0kCLOfTbnyGMW29LGsi32/5Ah3dxUEh6G5jb9nOS3iX057N4Ao0EJC3oPeird3/UAJ0prcbYi7hn7kkQBCAY4kcSHg4/yRDjT2msiyWdR3S+/hj4OuHts2TZGCnO/oR29huF7TMAe9rO0n0gaQ7inrYefe9pVxP3tK45BkdTPqCT6CW1pwIkDbi9CRZVTbf3iKK23kiHwlRtOfeMG6daSPo78B1X6Kwt6XjC2fr79K3MHwX83nZXtNcpjKG+UlusStobOMX2y+nx7JLkesIAACAASURBVMCfbC+eIdYbxKT8saRFubbtOyQtDNxie/YSYw9mctcIO5PbtaSHCXPNlwrbZyG8CHLF6XotRUknAl8hEttnAOc4GZH1MDKQzqEDbJ9d2L4NYRidQ6+x0km5pJOIJPbHgXcItukNhKHzX9xzhO8hIxS64J+0fX+hUDsfkaDLIqnS7oRWuidP7tjKKReU9HQbF5UiJE/eIIgCLSeBJN0GfMb2xCQJMpghZS7D6MoNw1OcSq6dks4Y+lWTg2RhwqfE2c8d+uMfJjR17yY6hE7IldAaTZB0P6F3/ldJfyYMww+XtDnxnX2ow7s4KBLh7LcE6ex6Yv3UtIhp+6Y27lrXIMnCHQ7sSn0d8D8iV5MrCbwuMM72hek+8AeCFPASsIXtLB1VAxU20prz+RwJ2vR9zUPIs8xN/Rr9L/d80aZa9ORHpgKkJPBOnd6PDLiAWNT2ktpTL75FtOgcTEyUi2yTHEZO3ycWTGdTv0a+TbQ07Z1hfCRNS7Q271xBS1YN6xJt0jXsQ0w8X06PpyFfy9mzwGxEYvNxomXyDmB+BmHvDgc5Em4tYD6ayxlNB3w0Y5yu11K0/e3EBN6Y0G//iaTLCYmga6pude5hWPgIzTXa/0ImvUbbY4Z+VSksB1xMLJpvLrKAeughM8bQ/B4wN/UW7hx4kjgHHyfmtusQxJOVCB3srEjzjarmHMWC/3tE0uGvGZj6l1D/Pi4uOdaQUHPD8O8BP5KU1TC8qmtnByRbILT0a9/XZsBdtleTVJON64p5TZtxEcHK/SshFXpOkgmal/D4GenYk/htf0isnS4a4HVdJxPaLoJLmif/QNIhRIJ2EvCA7Wz3ANtXN/z9ALBo6rCamHmeLpoXHZchOkVyxXiQMPGs8p7WQxehx9QehZD0/lpyT8m1fSBkSgK2BZJmJLQaX6AnPTBVIlWXzyPclPs8ReYWnXS8LZgePmT7DUkz2J402PumYPwXCCZYJTfjRqmT9Hgy2yw9nhN4OlPV/JfAE7YPkvRtgtV+M6FPfqHtHcrGaAdU1zm/GNiGvuZUY4mFx9q52qiraj3vJBRatNsCWxOFkyWcyVSth9Yg6W7gPNuHFbbvC2xuu5muew89DInEyhoS3dY+K+k3wCu2v56uzUsTc89LgMczMlsPJ4wnD0vMzHMIbeV5gWNtt1xIV2jdDgu2s3lFNNmPuYH9bX+9qhi5kRjHD9LcMHwB29kMwwtxp6+i60TS/MA0xflmmlO/bfvRTHFeB5a0/aikS4kC5BGS5gXutz1DjjijGZJWJUz9HrD9h07vz3AhaSbgVYIs01T6IXeXQ9UorqMats9J3Aema/7OluMtRKw7b7I9SZLKJpybyBA1wzsEOenaVo+5hk6dDxDHQeN+jyWUAk6x/e1Wxm8S7x5ghyo7t9sJSWsSpLoa6/xeQubmT53bq+5CL6k9CtHY+pEuyM1+5OxJwKqRKtenEC05L9H3c2WTHuhh5ELS34ib73E0MYq0fWNFcacj9Gf3sv3hTGMeC7xZZtE6xPjtTGqPAcY0LP62oK6neqrDOKTVsdu2MG9oAzb9GeZvE8mGPWxfViZOQ7yu1lJsBoWm5nZEYvt9wKK9pHZnIenLwG8I85yapvZqRJFmM9sDMauGGndXotX8f+qrfd8PvaLz6ITqmvpnEbr6TVFGeqITSInYq4n7wMKESfTChMHWp4pJjoxxsyW0JF0/zJfa9lplYg2xH8sQrMbs642USOvDdM5B1pE0iZA7/Fdh++LArbnkZ9KYY4lOup2BOYFFHFI3hwCP2j4tQ4wbCemUswrbvwrsaHt82RhpvL8S3TSXE3IUqzik6FYBLrA9d444PYxMpMTcze5yo8gOEFxmJzppP02sPxZO14DTCSb1HiXGHo4M0RjgQ4Rh7U9t799CnG2I++XpRNdO43f2FnEt+39TOu4g8TYgdMi/afvuXON2Auk6fAZwIX3n6BsR+uDndWrfugm9pPYoRONNJf09IKpKAlYBSc8SLtCH2x5Mg66HUQqFdvNytu+vYOzpgAMJ1/a3gCMdhhrbEbIQ7wI/s31EpngnEGzWB2huDlQ2QfsukdR+IT1+DVja9iPpcbakdpXoxMJcoUG8ku0Xc4w3SJyu1lKsIZ07NfmR1YHLiAnaVb1r9ciAwhX+u/Q1Ozra9oCJyGGM+Qiwou2XNLj2fa/oPEqRZBp2ALYAHiEWtOe6y4whmyExc7cgWNo1P5pzc3VrTS3IndROrOOfEXKE0zc+RSayjio0DG8Sa38icbY/8AuC6fxwmgfsbnvVDDFeBZZ3QUM9MUNvtT1L2RhpvPGE/MT7gbNsb5+2H0YUuLMYUnY7UtL0SttvNyRQm8KZTJarwlAd4Y3olu7wDhBcziaSyjsSc7Oah8O6wDG2l8gRZxj78QXgJNvzlhijLYWNxAyfkegIfYuQbJkMd4EnUQ2S7iMIIscWtn+P6BZarPk7e2hEL6k9ipEm5PsQ1fknO70/ZSHpP0SiqaepPZVC0k3Awbavq2DsI4BvEGzGTwJzEIm5VYDDgN/ZHlar9TDjDZasLZ2gTZOyK6nrUG5AuGrXkufTAetlXGiuQXx/CwKb2H5K0teAR2z/OUeM0YYqW8/bBYWB3xbAE9QTWpUWA3rooYeRBUnTA5sQXRqrECZUp9m+tqM7NsIhaXYnvdbU5bITMANwaVVtx4mFTrvWBRUktW8mEk2VdeypjYbhkh4EvmH7j+prSroo8P9sz5ohxivA+GIRMxU7b7A9c9kYDWOOBd7fWNhSGKy+UVWHQ7ehsZNSFZssV41BOsL7vIwu+CxFtJHg8iywbupqaLwGLADcaXumKuM37McsRM6oVPFJ0oLEXGBBYLd0nK9PSLbck2FXa8zwAVHsShnJkPQmIdXYrOh4t+3pm7+zh0b0ktqjHOniuJQz6aV1Ekmu4QUXdEF7mHogaVOCTX0UzXXV7ywx9sMEK+ZSSUsCdwJnEppd2S6UaZLySM4xB4gznJazLGZCSd7gV8C5wNeAxdOEbBfgc7Y/VzZGO5Bav2dvZF9I2ho4CBhHtCJ+xxnNW5rE7yotxbSgeZyQHhjwmO4xtDqHxAK6HrjRSX6ohx6qQmLSnka0Ms9hO5c5VKVoJ3tS0lJE4n8eoltrC8I8ehxhsDiOKA5nMUVUSITtC+xBsM4hDC+PBg6tsqOmgqT268AKVXTsNcR4HzHP3JlgAopgA54M7J1zDpCkTha1/VghobU48LccCS1JfyCYjF+pkTNS8vk3wDjb65eNUYg3B3Uj8vtrHYM9jD4M1RHeiG7qDm8n0nm/vO0HCteAFYGrbc/e4V0cNtLxcCUho/EpQmLxYUl7E519m3R0B0cgUmHzKNunFrbvTHQELNyZPesuTNPpHeihckwgFhaPdng/cmAssFdqx7mT/gnNyoxuehgx+E36//SGbbX2sLLO2nMTMiDYvjtVTo+tIPn8APARkpGKwpBqV9vP5QySI1k9BdgX2Nn22Qo97RpuTs+1DIXJyba2X9UQhicZEqf7AzcQ8hm1xMNpRHHjPsLl/WmisJIdDr25bJpzbcLZDM3S6aGzeAv4IXCapKeAG4nj/EaXMKrVCDGi62FkIDGAt03/ZiSSgl3Rbp5wMfBh4t48WDK57FwD4EiiML8VUQi+jNAh3ik9fwKw9xD7MSU4lJCJ2Zu6ZufqxL1seuBHrQ481H0ZyCJt0YC/E8WAypLaDh+Q3ST9kIJheAXh7gXWILTpG7EJg+jUTyF+ANwE3K8wwSTFfD+QTU9d0jji2N2autb5u6mw+p2Kvr8eOojhJqoTWWjEQ0P4gzTC+bxC/kScM/vVhk6FyL0IQkI34XBgX9vHpAR9DROAXXIGagcjvE04Gjhe0rL07QzaFtitUzvVbegltUc/rgQOT8mZZrq9I1qrq4ClqE/wijfHXlJl6sD8FY49lkj+1PAOUIXBXVGf7XNEwqmb8XFiwVTEK5Rf0L5C/fyu2jl9WeqTSgj23F9t7wQg6QmCtX1groCS5iKSCx+iv+HViDfXs71tp/ehh8Fhe0cASR8lmDNrEozNUyU949bNu5YrPF6emFfWkk2LEF4E/2hx/H5IOorN7vcmTKQfBM60PaxOlR7KITFaNyISpmsQc87dCcZzNrmudsD2mGZ/V4SVgLVs3ynpDuDrhJbpezDZc+OWjPG2IQwBG+f8d6Yi10mUSGoz9H35FaL4mQs7Aqek69nd5O3YGzRBLwlibvgscG2mjqqDgbPS5xkDbCzp40SS6wsZxsf2vZKWJpJKyxCs7bMJn5icnRTHEPeXDehbPDmeSNx8M2OsroakGYDP1DoDJf2EkAWs4V1gP9v/68T+5YCkmYGvEOfsCpQvBrYD3x3m60wc1zmwF/DHxMx+H1H0XAKYjUhudhOWArZssv154IO5gjRhhP8oxViGmI90DSPc9slJgmYPYLO0+T5gc3eZyXYn0Utqj36clP5vxpLKwTZpG2x/utP70ENnYbvIZMkJAWcmhjYEe+kUScVCUE9GoT+eBRaif0fI6kApuYNGxnkb2OezEhqdNdQmTTXUGGJZIGlb4FSimPISfZN1OSfMPfQAMJE4ziYCLxPJmZbbwhvvycnQ5jVgm5qWqqRZCV+CnNrABxOLlyuBv6VtnwDWA04kCp8nS5rG9i8yxu2hOZ4hfvezgG+ROpCAcSkBCHSPQRiApGkJKZCdy3QyDIHZiPsmtl9P84xGc82JQDad4xTvX022/ys91zLa3BUG4XeyIHFtmbwb5OnYG07hfAywMLCjpJ/a3r9EPGxfImkDolPsv8Q17jZgg5ya9LafJnyWqsSXCdmcGxq2XZEkVn5LL6ndiG2Az5M6A4mCwz3UDe8WJToDj+3/1pENSZ8iEotfJj7DhcC3O7pTw4TtKslTA8W8W9IixDHwGiERdSFwou1n2r0/JfEy0Y1cNA9fDngqY5y2McLbAdsXESa7PbSIXlJ7lKMNbJMeeqgUQ2lbNqJk50HRVOKcEmMNBtOfadjtnQa/AI6TtD3xWeZK+tA/BQ4pO7ikG4E/Em14t9h+e4i3tIrniKTYE4mBuDxwQMPzM1NghZXEIcQC9idVapr2MHVD0mHAeGJRcR8hP3I4cFOjmVdJ7AGs0zie7YmS9gWuIVh6ObA6sZA5pXGjpG+k+F+WdCewK3Fd6qFazJr+7Udzqakcica2ImlqL92OUEM8zok7iIV+sbV+l/RcN+F0omvzKzQxiiyDKUnQS/oCQRxqKand6K/iMAVdu5VxBhl/acJk7L2hjucy7PYCZqQvMaCG59NzPdSxFcHIbcSWNd8LSV8lEsFdkdSW9GFCLmEHQtbmtwTz/Eu27+3grnUFbL9CyERNhqS5Jf3c9tc7tFut4NfAEckDy8AYSasR68GcHTttYYS3C8mkcxNgAeCntv8jaXngOds5iwGjFj2jyFEKSY8Dy7nuqr4LcHY3sWVqGIZeH9Bj0I5WqL8zeI2R0/g4/ugCZ+30ea4EaozwDYjKctcywhWUvH0IGZXawuVN4sa834BvHP74ZxKs6Y8RLJb/RyS4JxBGSlna3CWdTLSu/QD4EsGkmSvpayJpK8JMdKVM8V4CPmH7oRzj9dBDM6RrzgvE4vhC2/+uIMZrBLPwhsL2TwOX2s7COk0mccu6uUv8P23PlHQW77Q9LkfMHgbGcE3Cus0gTGFM/qbtvSsaf6h5wHTAehnNFdckNLsfp+7bsCrRefS5lFTtCiRW+zLFa0AH9mMW4PRW52qS3gU+YrsSf5V0jH046cy+R/+5cw3OeJz9kegG2romm5FkNs4CZrP92RxxRgMkPQOsavvR9PgFYKWGx4sAf7f9gY7t5DCRjEg/RVxjzgWusv2upLeJc7VrktrJK2Q/2/8dyjekaq8QZTbZbQcSIehEosAxlugIHAucR/gj5VqvPQlsZvsvBXPNjYi154JDDDFikIqO1xGdQvMBH0+f5cfAvLa37uT+dQt6TO3Ri7npy4w5DLiC7jLtqaFqHd0eRjAauw0kfRY4gkigNi7Mfkz1bZW50C5GeNvgqI4eKukoQoZkJuBe21k0yWu6zZLmI0yN1iQ0SA8BXpd0MzDB9lElQ+1HtPzdSOipb1NLaCdsT7BOc+E0YFOCNdtDD1VhOeKcGQ/sIekt6maRN2RKcl8EnCFpD+qyICsTZoHDKkwPE/8hEoBF9toG6TmAcUQLbw8Vo9uS1VOAaYDt05yjmR9N2WTGcOYB2Vhttm9MOs3fImQNIM7Lk5IsRTdhAlF87mhS2/bLQBnyQdX+KvNTl5dql6TCbsDVwJNJKx7it/ofsG6b9qFbMAsNGtq25yg8P4a+GtsjGesTcnknVyjZ1C4sB0zb8PdA6LFCmyCtmXaSdDDBpp4JuL2C46JdjPB24BjCC2avgpTKFUQxoIdhoMfUHqVorNCnx5OrWJ3dsx56aB2S7iZ0Lv9c2L4G8HP7/7d332GWVWXaxu+nQQVBRQwYRiWpqAgCOioyooKjYxz9HBQTwcQoY8A4fmIaZ8z6YR4HFTGNAUUUEygYQEUFJYgoIkkQDAiIZN7vj73Lri6qu6u7Tp1VZ9f9u666qLP2rjoPV1edOvvda72r7tYm2dI0x1UUo95Uafrzb05XaP43YMMRzja6GfCXmTMKkmzcj181+1eu8fOsQ9dPcX3gJK6/4dWCzgLR0tTP/nkR3fLnZaP4vUlyY7qLib1ZfkF4Dd2Nm5dW1WUr+9o1fJ5nAe+ne7M/VTy/D11BaJ+q+lBfWP/7qnriKJ5TS0+So1ZxuKrqIWMLoxUkeTZdq5sPM/vfzfm0oRubxXKdlmT9qrp89WfO+fvdmO5vy9TNk1OBT4zyOYYgya+AV1TVISs5vhvwX1W15XiTrbkk96NrO/JEun/vj9EVHc9nwmZqLyaTNFM7yTLgpcBj6Da7/CbwuoX6vR/XjPBxSHIxsH1V/XrGrPM7AadV1XqNI04EZ2pLmiRb0G1CMdPUkh2N19g3Ver/yD9o2setgR/QzTwdib633Wzjf5ptfB7+nW720mlTTzH96Ub8XFqi+vZA27H8d2Ynup6XJzKi35uq+ivw3CQvpXudBvj1qIrZ057nf5L8nK4X8NQsydOAnavq2P6cUfXv1hIzrc/xoDYmT7IX3Q3Zz84Y/xfgxlU1c+b4YjbVT3+29xKT1L+96f4qSW5E9zr6UuA2o/q+/d8C9zNYva8Ar09y+FSrlil9y5bX0LXzWPSq6gfAD5K8kK6wvTfd7NNlwEOTnFNVrp4atv8LvJaujcbldKs2bk33szByY5wRPg5X0r0nn+kuzGMz96XGmdoD1c8AeBXdEnroWja8FfjD9POq6l1jjiattSTfoVvG+LSpvoNJNqFbarReVc2pv6fGb2pTpaq641p87dNZXpC7JXAsXTHu23Q9Bxdq48gFleQi4EVVdVDrLBqu/udsQ7oN4abajny3Xz4vqbfQfY5bSfJL4DlVddSM8Z3pVrndtU2ypWsc+6v0hevX0m1CeRXwlqo6tL/J8Z/AtcB7qurNa/sc/fPMZUP3qVV7J49qtdsk669dfkr37/IeYKoN2F3pbjasS7c31kS+9vTtjp4BPI2u1coRVTWXn5Pmknx4LudV1bwKtnNY7boR3Q37RX+jrl958Laq+u/+8a50N2XWr6qZe2PN53m+Azxm6v1r/9pzxCSvBElyIHALYDe6Nnrb0L02H0q3ofsLG8abGBa1ByrJmaz+jn9V1eZjiCONRL8Z2Bfo7l6e0w/fAfgV3Q7bTXssauXms6lSf/F3Nl3v6Q9NahF7piS/A/5hQmcWaEIkeSRdEXtB99RIcm+6N+V3pFt++jfzLMzcdCp7ktlms0x/nkncN0SLxGJpCTFqSa4AtprahG7a+KbAqVW1foNYS1qSj8zlvKraax7P8WbgOXSzJ3cEbgV8BLgf3V5Lnx3FMv1cf0P3Vfkd8MSaoM1JF0qSzejaaT2U5T3WCzgCeO6kv+7A39rsPRrYe4KK2tcBZwEnMPvmqgBU1ePm+TwL/howLkmuBLasqnOmjV3Rj507wueZ+Tf6ErrNwyf2d6Vvefk54N7ATYDz6FbPfJ9uI+eRrngcKovakiZKv5T+oazYr+/I8sVssJLsQzdLe2dgPeB7dLNNvw38ZFL/7ZP8O92swOe3ziLNR5In0a2Y+Trwj3Qbqt4F2AT4wjwLM3+bPdtf0Mz2+x66G/WLfkaTFq8BF7XPBvad2W86yWOB91bV37VJNndJvgLsPtUeLMkrgA9Mm7F3C7qbd3dvGHNRSXIG8MKqOizJ1nQtpw4CnjHu9039e/dN6FYR71hV24/z+Rezfr+Wqd7Zpy9AqzutgSTvBXanK2x/BPi4/yar1r9Pu01V/X7a2KXANlX1mxE+zyD/RgMk2YlulvaGdL3Uj2wcaaJY1JYkTYwkd6crbj+o/7gRcAxwVFW9rV2yNZfkC8BDgD8Cp3D9Da/WenarlrY5buIKjObnLMmJwH9X1XunLjKA3wD/DZxfVa+Zx/feGTimqq5J8iBWsQqtqkbWW19zl2QD4BXALnR9NJdNPz4pqwJnXpgvxEV5C/2M3ScCewHf6Yd3ptts8XNV9ZJW2eZqltYwK8zQ69s5nOeNreWSXAVsVlW/7R9fTreJ7kkNM20K/MLNz7SY9a17Hk/XE3pHulYaHwK+MakTaRbSLO2UYJaWSvN9vznkorbmx40iJS16ztDRlOp2Uf858P4ktwOeC/wb8HBgooradJuezrn4KK2B6ZudBnhcP/bjfmwHun6No/r524Llm1pdBWxQVZXknXQXNWtd1J5eqK6qo+cTUgvmQLoi6ceA85ncjW4DHNQvpYZuZdAHkoysz3Ej+9Ntpv1Nut7G0N14OBh4ZaNMq5XkA1W1z9TDmYfHnWcCrUP3ejzlGpbvtdREVZ3Z34CQFq2quhL4FPCpfoP6PYH3AesmuUdVNf09WoRm22z44wv0XA9LMvUedxmwS78S5W9mrkpajPoNYXepqi/3j99IN1FryrXA/jM3ktXsLGpLmgQPY8UX+lcCn6ErCkL3WuZGRwOX5NbAg1k+S/sudLObfwActdIvXKQmoU+eJtP0n61+luZngH2m+qf2fS7fB4yqB/VFdL0AAX4LbA2cRFc4v/GInmNqk6Cj6VoPHeOb/UXjn4BHVtUxrYPM08wL84W6KB+rfmO+JyZ5FXAv4HLgpKo6q22y1boiyT5V9YHWQSbUorxJMzVBRZoQU23PQnejSDOM+Xpm5t/p/57xuJiMf6c9gEcCX+4f70u3andq08ut6Pprv3P80SaPRW1Jk8AZOktYkvfRFbHvSjfT6Di6TTWOAo6d9MJWklux/KbMadN70kkjsDew0/QNwarq2iTvAI4FXjqC5/gO3V4HJwGfBQ5I8pB+7Jsj+P5TvgE8ENiPbsbUj1mxyP3XET6X5u4iYOJ7jg79RmO/KfHEbExcVS9MMr3f98wVAJO6ImBcBnmTRlpoM9qP7ERXeNwX+FpVrcnGqBqhqlq2+rMmxlOAt8wYe/K0llpPBZ6HRe05sagtSVrstgMOpStiD6Zw1fehfTfwdJb3oL02ycHAvw3l/1PNrUs34+O0GeNbMaP38TzsSzcLEOA/6VZQ7AgcArxhRM9BVb0BIMm6wH1Y3l//ZXSzqezT2sb+wOuT7OHr1uKT5BDguKp684zxlwH3qap/aZNs9arq3GkPVzXr+EZoBUO/SSMthH4izZOAc+j2Hdi9qv7QNpUGaEu6iSBTrqB7HzvlOOC9Y000wSxqLxH9sv3ZNu85sU0iaY0UztBZsqrq/q0zLJB30BXlHk232SV0M0LeBbwd+NdGuTQsHwE+lGQLujfJAPel29jvI6N4gqr607TPrwPeNIrvuwqbA/ek25ByG+BSlm+Ap/F7MV1f9QuSnMn1N73dvkUo/c0DgdfOMv5Vun+7STCXWccHjyOIVi/Jhlz/mnNU7a6khbQPcDZwBt179J2T6y8QnsC9FQZp5qbBE2Qjpt2MrapbzTi+DG/WzplF7YFLsgPdG8G7sbxlw1RfqEnpOSStri+gL/qaRP8HeMKMze++kuRyuh7IFrU1Ci8BfkdXvLptP3Y+8Fa6mydrJclN53ruqIoZST5Jd5F5I7oi9rfpCugnVpU3Ots5tHUArdKGrLhh4JSrgTn/HrfkrOPFL8lmwHvoVs9MXzXjNacmycE4cWqSTGpL0nPp9p+ZuYpyyjb9OZqDeA0wbEl+BvwaeDNwATNepCdgkxiJJHOaTehFjyZJkr8CO1TVqTPG70G3VHyDNsk0VFOF6FEUmZNMbZ60ytO6p6uRFDP65/wD3ZLgbwHfs92FtGpJjgO+XFWvnzH+WuDRVbVDk2AalCTH0L3mH8Ds15zfbpFL0nAluRTYdtJmaic5ANiV7jrwihnH1gd+DBxZVS9okW/SWNQeuP4XfbuqOr11FknSckm+CfwRePrUG5r+jcxHgY2rateW+aRVSbLzXM8dVTEjyc2Bf6CbCbgz3Sq0n9JtFnl0VX1jFM+jtZPkhsze6u7sNokEkOTRwOeBT9LdDALYBdgd+Jeqcqa95i3JX+gKNCubeShJI5Xk/cD+k9b3PMkmdO9fr6Jb4fLL/tBd6fapWZeuhndBm4STxaL2wCU5FPhYVR3SOoskabkkWwNfp2ul8LN+eFu6zUIeVlWntMqm4UjyG1Yxo7qqNp/H9966qk5e26+fryRbAq+i20V+2ahmhGvNJLkL8CG6zUFXOMQIZ+pr7SV5JPBK4F7A5cCJwOucPatRSXIU8J9VdWTrLJKWliQbVdWfW+dYE33LpvcDD2XFNsFHAM+dtNnnLVnUHrgkt6Sb9XcccDLX37znsBa5JEmQ5MZ0Bbmt+qFTgU9U1eXtUmlIksxcungDYDvg4cBbq2qtN3Xs24H8CDgQ+N+qunStg87t+W5BN0P7Qf3H3YE/0/fXFzYLDQAAIABJREFUrqoDFvL5Nbu+7cA1dP3Nz+f6bQd+NtvXSRqOfjPiD9Bt4jnbNeeJLXJJGpYkLwfOrKpP948/Q7dP0e+AR0zae44kGwNb9g9Pn775uubGovbA9UsOP8bsG8E4e0bSopbkIua4YUtVbbzAcaTBSPI84N7z2YsgyT8AewFPoGs5cQhwYFV9dzQpr/d819L11P4u3SaRR1fVSQvxXJq7ftPmHarqF62zSGojyf3oWtxsOm24cMWGpBHqVyA+paqOTfJQ4DPAE4HdgDtW1T82Daixs6g9cEnOBL4M/Ic9eSRNmiR7THt4C7pWA18Hvt+P3R94GN1r3DvHHG/ektwZeDCz96F9/axfJI1Aks2Bn1bVbDe91/R7bUB3MbEnXc/r0+naUXy0qn433+8/7XnuYVuexSfJj4AXVdX3WmdRJ8mfgLtU1R9Wd3PYG8IahSQ/p1tt9hZm3yjyrBa5JA1Lksvp/r6d02+4uF5VPadvhfbDqrp544gaM4vaA9dvFHmvqvp16yySNB9JDgGOqqr3zBjfF9i1qv65TbK1k+RZdL3U/kC3ZG76H+Sqqu2bBNOSkORldD37Nh3x992Sbvb204DbAF+rqseM8jnUXpLpN0PuDbyBrmfzSVy/7cAlY4wm/nZD+H+r6soZN4evp6o+OqZYGrB+xca2VXV66yyShivJecAT+pnapwGvqqrPJrkr8KNRTNbQZLGoPXBJPgp8t6oObJ1FkuYjyV/obtKdPmN8S7oZpxu2SbZ2kpwFvK+q3tw6i4YryQmseMMkdMXmW9EVtT+4AM+5AV2v+DcCG81n2fks+VfKG0Hj0/dTn/lzNfPfybYD0hKR5EvAQVV1SOsskoYryXuARwG/otsjZtOq+kuSJwEv873g0rNu6wBacL8E3phkJ2afPfOuJqkkac39EXgs8PYZ44/tj02amwOfbR1Cg3fojMfXAb+n60c90h7ISR4I7E23Yc91dH0OPzTPbzs9/3rAc4Gfs7wF0f2AewDvm+fzaM08uHUASYvKl4B3Jrkns19zHtYklaSheRFwJnAHuiL2X/rx2+J7wSXJmdoD1zfSX5mqqs3HFkaS5iHJnsCBwFeBH/bD9wUeDjyrqg5qk2ztJPkQ3TK5D7TOIq2tJLej66W9J93u7cfSFbI/U1WXjfi5DgTOr6r9Z4y/DrhDVe09yueTJtkss+lnU1XlJCfNW//ztjKu2JAkLQiL2pKkiZHkvsDzgbv1Q6cC76qqH678qxaPJM+f9nADYD/gcFxJoxHri837Aa+f2dM4yc3oNl1923w2kU7yVWBXur7wBwMfrqrT1j71ap/vYuDeVfWrGeN3Bn5cVTdbqOfWqiXZCHgGy1+bT6H7ebi4XaqlLcljV3H4/nR/S5dV1XpjiiRJ0hpL8hjgq1V1df/5SrkqZOmxqC1J0pisZvXMdK6k0bwkeRtw06p69kqOfwC4uKpePo/nOIxuVvaXq+ratf0+a/B8vwNeMXNVRr+K481VtclCZ9D1Jbk38HXgcuC4fvg+wPrAP1bV8a2yaUX9RlpvAh4NfAJ4dVWd1TaVJEkr168EuU1VXeiqEM1kUXuAkrxjrudW1X4LmUWSRinJFsBewObAC/s3N/8EnF1Vp7RNJy0eSU4G9qmq763k+I7A/1TVPcabbO0leQXwGuB/WF48vS9dH+//qKo3tcq2lCX5LnA6XRuoa/qxdenaRW1eVQ9smU9/W7nxOmAPuhsQ/15VJ7dNpUk3Y/XZKrn6TJK0ECxqD1CSo+Z4alXVQxY0jCSNSJKd6fppHwM8ELhbVZ3RF7ruXVVPaBpwjpKcAdynqiZxc0tNiCSX0f2OnL2S43cETq2qDcabbH6S7Aa8gBVbEB1QVZ9pl2ppS3I5sN3MjUeT3J2uLcyN2yRT32rolcC/AT8FXl5V322bSkPh6jNJUmtuDDJAVeWO9JKG6E3Aq6rqHUkunTb+LWDfRpnWxqaAS+O00C6n+1mbtajdH7t8XGFGpS9eW8BeXC4B7gj8Ysb4HYBLr3+6xiHJy4CXA78Ddq+qLzaOpIGpqs1aZ5C0tCR59aqOV9Xrx5VFi4MztZeIJFsCWwDfqarLk6T8x5c0QZL8BbhnVf2mL2pv28/U3hT4xaRsdjW9L1zrLBquJIcD51XVs1Zy/EDgdlX1iPEm09AkeRfwOOAlwLH98AOAtwKHVNULW2Vbyvq/NZcDRwIr7XlfVY8fWygNXpIbApsBv55qRyRJo5LkhBlDN6B7zbmG7nVn+/GnUkvO1B64JLegm9H0YKCAOwNnAB9KclFVvbhlPklaA38GbgvMXO66HfDb8ceZl4cluXhVJ7h7t+bpbcAR/c/ZW6vqAoAkmwAvA/YE/rFdvDXXF+lWekPezYGaeQndv8vBdNcWAa4C3g+8omGupe5gVvH7Io1SkhsD76br2w5wF+CMJO8GfuueB5JGoaq2mzmW5KbAQcAXxh5IzTlTe+CSHAzcGngmXd/JqZmNDwPeMUkbREla2pK8jW5TuH8BfglsD2xCd+F+cFW9rmG8OVvNrt1T3L1b85bkOcABdLNYLqErcN0MuBp4UVW9v2G8NZbksTOGbkB3U2sP4DVV9aHxp9KUvqi1Rf/w11X115Z5JI1PkgPoVmi8EPgasE1/zflY4LWzFaIkaVSS3BP4UlVt2jqLxsui9sAl+R3wsKr62Yzl+psDJ1bVho0jStKc9Eta30s3w3QdumVm6wCfBPasqpUur15MbD+icUpye2A3YEu6GbS/BD5XVec2DTZCSZ4MPLGqZha9tYCSfH4Op11D19P5iKr60gJHktRIkrPoXod/MOOac0vg+Kq6aeOIkgYsyU50Re2bt86i8bL9yPBtAMw2U2Zj4MoxZ5GktVZVVwHPSvIfwNbAhsAJVfWrtsnWmHeTNTZV9Vvgna1zLLAfAB9sHWIJWmULpd4yutZ3z0zytqpa5QZPkibWrYDZbtZvgO97JI1IkufPHKJrT/k04KvjT6TWLGoP33eBpwP7948ryTK6fppHNUslSWupqs4Gzm6dYx7SOoA0FEnWB57P5PXVn3hVtddcz03yKOB9gEVtaZh+DDySrq82LC9kPxP4fpNEkoboRTMeXwf8Hvgo8Mbxx1FrFrWH72XAN5PcG7gh8BbgHnQztR/QMpgkrU6SdwD7V9Vl/ecrVVX7jSnWfH0UuLx1CGnSJLmIFWf8BbgJ3Yq0pzUJpbn6Hl3RS9IwvRL4apK709UYXtB/viOwc9NkkgajqjZrnUGLiz21l4AkNwP2BbalW65/PPDeqjq/aTBJWo0kRwGPq6o/JzmalS9hrap6yPiSSRq3JHvMGJqanfPDqrqoQSRJUi/JFsArWPGa881VdVLTYJIGKcnfAQxpnxitOYvakiRJmlj9Rc2rq+rZrbNIkiRpYfStdF8FvJju5hnApcDbgf+squtaZVMbFrWXgCQbAX8P3Jpuw56/qaqDm4SSpDWQ5AZ0LTvuVVUnt84jTYokd6BbyXBu//jvgScDP6+qQWyumGRb4PiqWqd1Fklaqvpi05bMfs35nSahJA1KkjcCzwBeAxzTD+8EvBb4n6r6v42iqRGL2gOX5NHAJ+juYl3Cikv3q6o2bhJMktZQkjPoWpH8rHUWaVIk+S7wwar6WJLbAKcBpwB3Bt5dVa9vGnAELGpLUltJ7gd8ErgT198Qu3x9ljQKSc4D9qmqw2aMPxZ4X1Xdvk0ytbJs9adowr0d+DCwYVVtVFU3n/ZhQVvSJPlP4L+S+Nolzd3WwHH957sBJ1fVjsBTgD1bhZIkDcoH6DaD3RrYGLj5tA/ft0kalY2BX8wy/gt8rVmS1m0dQAvu9sC7quqvrYNI0jztS7es9bwkZwGXTT9YVds3SSUtbjcAruw/3xWYmtnyC+C2TRJJkobmzsATqur01kEkDdrP6K4Jnz9jfN/+mJYYi9rD93Xg3sAZrYNI0jwd2jqANIFOAfZJcjjwUGD/fvx2wB+bpVoDST6/mlM2GksQSdLK/JBu4oFFbUkL6WXA4Ul2Bb7fj90fuAPwiGap1Iw9tQcoyWOmPbwV8GrgI8BJwNXTz53Zi0iSFpMkz6frB3xFkjsC57qrtTR3SR4EfAG4KfDRqtq7H/8vYKuqenzDeHOS5CNzOa+q9lroLJKkTpJtpj3cAngD8FZmv+Y8cYzRJA1YktsBzwO26odOpeunfV67VGrFovYAJZlrwcdNOyQtakmuAW5XVRcmuRa4bVVd2DqXNEmSrAPctKoumja2KfBXf58kSWujv+Ysrr8x5JSpY15zSlpQSf4OeHVVPbt1Fo2XRW1J0qKV5GzgjcBXgN/QtVP6w2znVtXZY4w2b0n2AP5QVYf3j98CPBv4ObB7VZ3VMp8kSdLKJLnTXM/1PY2khZRkW+B4b6AtPRa1JUmLVpJnA+9m1XtATOQsoCSnAf9aVd9Kcn/gSOBFwKOAayahLYQWpyTHA7tU1UVJTqCbLTcrN1iVJEnSJLOovXS5UeQA9T1o56Sq3rWQWSRpPqrqg0k+BdwJOBHYlQnZ3G4O7sDyDZX+GTik//89Bji6WSoNwReBK/vP3WBVkjRyM/ZxWiX3cZIkLQRnag9Qkt/M8dSqqs0XNIwkjUjfruN/q+rK1Z48AZJcCDysqk7oZ9O+o6o+lmQL4GdVtWHjiJpwfS/tBwAnVtWfW+eRJA2H+zhJWiycqb10OVN7gKpqs9YZJGkBvAb4MstnoAKQZCO6NzGTdpPuCODAvqB9F7q+4QD3AM5sFUrDUVXXJvkGcDfAorYkaWSqalnrDJKWhiSfX80pG40liBYdi9qSpEmxKTDb3fcbAbcfb5SReB7wBro2JP+nqqbaquwAfKpZKg3NycDmdButSpIkSZPm4jkcP3gcQbS42H5kgJK8A9i/qi7rP1+pqtpvTLEkaa1M69l4KLAHK76pWQfYBXhoVd113NmkxS7Jw4E3AvsDPwEum368qi5pkUuSNNn6fZw+WFVXrG5PJ/dxkiQtBIvaA5TkKOBxVfXn/vOVqap6yLhySdLaWE3PxqvpWnW8uKq+PJ5Eo5XkxsAdgRtOH6+qE9sk0pDM+P2Z/qYv2OdUkrSW+n2c7l1Vf1zNnk7u4yRJWhAWtSVJE6G/YLpPVf2hdZZRSHIr4CDg4bMdt9ioUUiy86qOV9W3x5VFkiRJkkbFntoDleSjwDeBo6rqnNZ5JGkEXgNcOnMwyQ2BJ1XVpPVR+3/AzYD7AkcDjwM2AV4FvLhdLA2JRWtJ0kJJ8jq6a84fVNVVrfNIkpYWZ2oPVJKj6QolN6Rbmn9U//Gtqjq/XTJJWjtJrgVuW1UXzhi/BXDhpM1sTnI+8NiqOi7JJXRLeH/Z9xB/WVXt1DiiBsQ2N5KkUetX0d0JuAL4PsuvOX9YVde0zCZJGj5nag9UVT0oyY2AHYEH9R9PBW6Q5FcsL3B/tllISVozYcWewFP+jtXviL0YbQBMFegvAm4F/BI4Cdi+VSgNS9/m5iPAP63klIm6GSRJWjyqarMkmwIPprvefCbweuCyJMfQF7mr6rhWGSVJw+VM7SUkyXp0Re5/Ap4NbDhpMxslLT1JTqArZm8LnAJMn/mzDrAZ8LWq2q1BvLWW5EfAq6rq60kOA/4M/DvwfOAJVbVF04AahCSfoJtF90JmaXNTVYe3SydJGpokm7G8yP1YYIOqcjKdJGnk/OOyBPT9Zu9P98biwXRtSc4DDmkYS5Lm6tD+v/cCvg78Zdqxq+haLE3i69kBwG37z18HfA14Ct3/056NMml4HkLX5ubHSa4DzqqqI/qWN/8OWNSWJI1EkjsBDwR27v97A+A7TUNJkgbLmdoDleSBrFjEPhv4dv/xnao6t106SVpzSfYAPl1VV7TOshD6nsdbAWdX1R9a59Ew9MXrbarqzCRnAU+uqmP6mXSnVNWNG0eUJE2oJHdk+TXng4BbAsfSX3MCx7mBpCRpoVjUHqh+NtbZwJuBz1fVBY0jSdJIJNkBuFv/8JSqOqFlHmkxs82NJGmhTLvmfD9d/+yfVNW1bVNJkpYKi9oDleRNdHfLtwNOo7tbfjTwbWcASppESW4N/C/da9uf++GN6C6inlRVv28Uba0kWYeuzcguwK2BZdOPV9VDGsTSwCR5KrBuVR3U3xD6GrAxfZubqvp004CSpImV5H/pWo3cCPge3TXnUcAJZaFBkrTALGoPXJINgX+gKwI9iK7I/Uv6NxxV9blm4SRpDST5NLA58PSqOrUfuzvwUeD0qtq9Zb41leQ9dEXtw4Hz6TbD/JuqelGDWBo429xIkkYtyVYsb0GyM7Aey4vcR1fVj9qlkyQNlUXtJSbJxsB+wL8BG1bVOo0jSdKcJLkY2HXmhVGSvwe+UVUbtUm2dpL8ga5A/5XWWSRJkkaln3TwZLprzg2qat3GkSRJA+Qfl4FLsgy4D8tnaj8A2JCu99nnmwWTpDW3DLh6lvGrmdG6Y0JcBZzeOoSGLUmAJ9DNoJutzc3jW+SSJA1Lkk1Yfs35YOAuwJXAd9ulkiQNmTO1ByrJy1hexL4J8Fu6ntpH0bUd+U2zcJK0FpJ8ka6H9u5VdV4/dnvgE8BFVfW4lvnWVJIX07VT2de+k1ooSQ4AnkP39/8Crt/mZq8WuSRJky/JbiwvZN+VbqLBj+ivOYFjq+rKVvkkScNmUXugkpzHikVsZwNKmmhJ7gAcBtwDOKcfvgNwMvCYqjq3Vba1keQLdDOZ/gScwoxZ6M6g1Sgk+RPwVNvcSJJGLclVwI9ZXsQ+pqoub5tKkrRU2H5koKrqdq0zSNIoVdU5SbYHdqXb6A7g1Ko6smGs+fgz8IXWITR4FwNntA4hSRqkm1fVZa1DSJKWJmdqS5IkDVSSPYCHA3s7e06SJEnSUFjUliQtaknWB3apqi/3j98I3GjaKdcC+1fVFS3ySYtZ//vzBbo9Ns7k+m1utm8QS5IkSZLmxfYjkqTFbg/gkcCX+8f70vWgnpp1uhVwHvDO8UdbM0mOpyvQX5TkBGZs2jedxUaNyEeBHYCPM8tGkZIkSZI0iSxqS5IWu6cAb5kx9uSqOgMgyVOB5zEBRW3gi8CV/eeHtgyiJeORwMOq6nutg0iSJEnSqNh+RJK0qCU5H7h/VZ3ZP/49cJ9pj+8C/KiqbtYspLRIJfkFsFtVndg6iyRJkiSNijO1B24Vy9sLuAI4HTioqo4aazBJmruNmNZDu6puNeP4MlbssS1puRcDb0myz9SNIEmSRinJBsArgF2AW9O9N/ubqtq8RS5J0rBZ1B6+rwH/CpwEHNeP3QfYBjgIuDtwZJLHV9UXmySUpFU7F9gaOG0lx7fpz5koSa5j1T211xljHA3Xx4EbA79O8leuv1Hkxk1SSZKG5EBgZ+BjwPm4f4MkaQwsag/fLYG3V9V/TB9M8irgTlX1j0leB+xP1+tVkhabrwCvT3J4VV0x/UCS9YHXAIc3STY/j5vx+AbAdnQbY75m/HE0UC9sHUCSNHj/BDyyqo5pHUSStHTYU3vgklwM7FBVp88Y3xL4SVXdLMlWdP1ob9IkpCStQpJNgJ8CVwHvAX7ZH7orsC/dDdrtquqCNglHK8mTgSdW1WNbZ5EkSVqdJL8BHlFVp7bOIklaOpypPXxXADvS9c6ebsf+GHQ9z65AkhahqrogyY7A+4E3AZk6BBwBPHcoBe3eD4APtg6h4UmyHnDD6WNVdUmjOJKk4difblXdHlX119ZhJElLg0Xt4Xs38IEkOwA/6sfuAzwT+K/+8cPoZkFK0qJUVb8BHp5kY2DLfvj0qvpTw1gj17dTeT7w29ZZNAz95l1vBnYDbjHLKfZulyStsSQnsGLv7C2BC5KcyfX3b9h+jNEkSUuE7UeWgCRPoVuif9d+6DTg3VX1yf74+kDN7FUrSVo4SS5ixYvBADcB/go8taoOaxJMg5LkvcCD6WbRfQx4HnB74DnAK6rqEw3jSZImVJI57/9RVa9byCySpKXJovaAJVkXeCXw4ao6t3UeSdJySfZkxaL2dcDvgR9W1UVNQmlwkpwNPL2qjk5yCbB9VZ2e5GnA7lX1iMYRJUmSJGmNWdQeuCR/AbauqjNbZ5EkSePVvw+4e1WdneRc4PFVdVySzYCTqmrDxhElSRMuyX2AZVX1wxnj9wWuraoft0kmSRoye2oP3zeBnYEzG+eQJE2TZJu5nltVJy5kFg3aGcBmwNnAL+h6ax8HPBr4c8NckqTheC/wFuCHM8ZvD7wcuO/YE0mSBs+i9vB9FXhTknsCPwEum37Qnq2S1MxPWbH9yGzSn+NmflpbHwG2Bb4NvAn4UpJ9gRsA+7UMJkkajLsDx88yfkJ/TJKkkbP9yMAluW4Vh6uqLJRIUgNJ/hl4G/BW4Pv98P2BFwMvo7sQBKCqzhp7QA1SkjsBOwCnuwJAkjQKSf4IPKqqvj9jfEfg8Kq6eZtkkqQhs6gtSVIDSY4DXltVX5kx/gjgP6pqhzbJJEmS5i7Jp4DbAo+tqov7sY2AQ4ELq2q3lvkkScNkUVuSpAaSXA5sX1Wnzhi/G3B8Va3fJpmGIskyYE/g8cCmdK1sfgN8DvhY+SZQkjQCSW4PfAe4BctXmt0LuAB4aFWd0yqbJGm4LGovAUl2Bl4C3K0f+jnw1qr6brtUkrS0JTkeOBl4ZlVd1Y/dEDgQ2Lqqtm+ZT5MtSYAvAY8Afka3SWTo3gvcEzisqv65XUJJ0pAk2QB4Ct0+DpcDJwKfqqqrmwaTJA2WRe2BS/JUuk2iPg8c0w8/AHgcsGdVfbJVNklaypL8PV3RMXQXfgDb9P99VFUd1ySYBiHJXsABdEvBj5px7CF0S8L3raqDW+STJEmSpPmwqD1wSU4FPlhV75wxvh/wrKq62+xfKUlaaNNmNW3VD50KfLKqLmuXSkOQ5BvAt6rqTSs5/kpg56p62HiTSZKGIMljgK9W1dX95ytVVYeNKZYkaQmxqD1wSa4E7lFVp88Y3xI4uarWa5NMkjSbvqf2M6rqJa2zaHIl+R3w8Kr66UqOb0dXjLjNeJNJkoYgyXXAbarqwv7zlamqWmdcuSRJS8ey1gG04M4BdpllfNf+mCSpsSQbJHlGkmOBU4CHt86kibcx3QZdK3MBcPMxZZEkDUxVLauqC6d9vrIPC9qSpAWxbusAWnBvB96V5F7Asf3YA4A9gRe0CiVJgiQPAJ4B7AasD7wT2LuqftE0mIZgHeCaVRy/Ft8HSpLmKckNgK8B+1TVr1rnkSQtHV7MDFxVvb9fgvxiuqIJdD1bn1hVX2yXTJKWpiS3pruxuDdwM+BTwIOA7wMftqCtEQlwUN+GbDY3GmcYSdIw9T21t1n9mZIkjZY9tSVJGqMklwOfAz4OHFFV1/XjVwPbVtXPW+bTMCT5yFzOq6q9FjqLJGnYkrwTuLKqXtE6iyRp6XCm9hKQZCPgCcDmwNuq6k9JtgcuqKrftk0nSUvOWcBOwNn9587M1shZrJYkjdG6wN5JdgV+Alw2/WBV7dcklSRp0CxqD1y/FOxI4GJgU+BA4E/A44E7Ak9vFk6SlqCq2mpaL+0fJfkl3axtAJdPSZKkSbM1cHz/+V1mHPO9jSRpQdh+ZOCSHAkcX1UvS3Ip3dL2M5LsCHyyqjZtm1CSlq4kGwK7A3sB9wO+DXwSOLSqft8ymyRJkiRJi5VF7YFLcjGwfVX9ekZR+07AaVW1XuOIkiQgyd3oZm8/Ddi4qm7QOJIkSZIkSYuS7UeG70rgprOM3wVwFqAkLRJVdSrwkiSvAB7TOo8kSdLKJPn8XM+tqscvZBZJ0tK0rHUALbjDgFcnmZrxV0nuCLwZOKRdLEnSbKrqmqqa84WiJElSAxdP+7gE2AW497TjO/RjF48/miRpKbD9yMAluRnwObo3GDcBzgNuA3wfeERVXbaKL5ckSZIkaaWSvBnYGNinqq7tx9YB3gdcUlUvbZlPkjRMFrWXiCQ7AdsAG9JtHHlk40iSJEmSpAmX5PfATlV12ozxuwLHVtUt2iSTJA2ZPbWXiKr6HvC91jkkSZIkSYOyLrAVcNqM8a2w5akkaYFY1B6oJOsDu1TVl/vHbwRuNO2Ua4H9q+qKFvkkSStKclPgIcBp/aaRkiRJk+AjwIeSbAEc14/dF3hFf0ySpJGz/chAJdkHeGRVPbp/fClwCnB5f8pWwFuq6p2NIkrSkpbkM8B3quo9/Y3InwGbAgGeVFVu5itJkha9JMuAlwAvAG7bD58PHAC8farPtiRJo2RRe6CSfJeuaP2l/vGlwLZVdUb/+KnA86rq/g1jStKSleR3wMOq6mdJngy8DtgW2AN4dlVt1zSgJEnSGupXnlFVl7TOIkkaNvtbDdeWwEnTHl8BXDft8XHA3ceaSJI03c2AP/WfPxw4pKr+ChwO3LlZKkmSpDWUZN0kuwK7A9WP3S7Jhm2TSZKGyp7aw7UR03poV9WtZhxfxoo9tiVJ43UOcP8kf6Iraj+pH7853Y1ISZKkRS/JnYCvAXeku8Y8ArgUeHn/eJ926SRJQ+VM7eE6F9h6Fce36c+RJLXx/4BP0L0Wnwcc3Y8/kBVX2kiSJC1mBwA/prsxf/m08S8AuzRJJEkaPGdqD9dXgNcnObyqVpjx129I9hq6Je6SpAaq6n1Jfkg3q+mIqppqEXUG8Kp2ySRJktbIPwA7VtVVSaaPnwncvkkiSdLguVHkQCXZBPgpcBXwHuCX/aG7AvvS3dDYrqouaJNQkiRJkjTpklwEPKCqfp7kUmDbqjojyU50e4Zs0jiiJGmALGoPWJLNgPcDDwWmbpkXXY+z51bVGa2ySZIgyd8Bj6GbrX3D6ceqar8moSRJktZAkk8DF1fVs/ui9jbA74EvAmdX1V5NA0qSBsmi9hKQZGNgy/7h6VX1p5Z5JEmQZBfgMLp2I1sBJwOb0t2EPL6qHtIunSRJ0tz0N+m/Tvce5s50/bXvDPwBeGBVXdggVYLEAAAFYUlEQVQwniRpoCxqS5LUQJLjgK9W1WumluoCF9JtHvm1qnp/04CSJElzlGRd4El0s7Q3BI4HPlFVl6/yCyVJWksWtSVJaqAvZN+rqn7d96LcqapOSbIt8MWq2rRtQkmSJEmSFqd1WweQJGmJuozlfbTPB7YATukf37JJIkmSpDlI8hi6FWdX95+vVFUdNqZYkqQlxKK2JElt/ADYCTgV+Arw9iT3BB7fH5MkSVqsDgVuQ9c67dBVnFfAOmNJJElaUmw/IklSA0k2BzasqhOTbAC8HdgR+BWwX1Wd1TSgJEmSJEmLlEVtSZIkSZK0xpLcAPgasE9V/ap1HknS0mH7EUmSGkuyIbBs+lhVXdIojiRJ0pz0PbW3aZ1DkrT0LFv9KZIkadSSbJbk8CSXARcDF/Uff+7/K0mSNAk+DjyjdQhJ0tLiTG1Jktr4OBBgb+ACuo2UJEmSJs26wN5JdgV+Alw2/WBV7dcklSRp0OypLUlSA0n+AuxQVae1ziJJkrS2khy1isNVVQ8ZWxhJ0pLhTG1Jktr4EXAHwKK2JEmaOEk2B35TVQ9unUWStPQ4U1uSpAaSbAF8gK4NycnA1dOPV9WJLXJJkiTNRZJrgdtW1YX9408Dz6+qC9omkyQtBRa1JUlqIMn9gE8Cm04bLro+21VV67TIJUmSNBdJrgNuM62ofSmwbVWd0TaZJGkpsP2IJEltfBg4AdgdN4qUJEmSJGnOLGpLktTGnYDHVNXprYNIkiStheL6N+W9SS9JGguL2pIktfEtYFvAorYkSZpEAQ5KcmX/eD3gA0kum35SVT1+7MkkSYNnUVuSpDa+BLwzyT2Bk7j+RpGHNUklSZI0Nx+d8fjjTVJIkpYkN4qUJKmBfnOllXGjSEmSJEmSVsKitiRJkiRJkiRpYixrHUCSJEmSJEmSpLmyqC1JUiNJdk7ypSSn9x+HJfmH1rkkSZIkSVrMLGpLktRAkqcCRwJ/Bd7Vf1wOfDPJk1tmkyRJkiRpMbOntiRJDSQ5FfhgVb1zxvh+wLOq6m5tkkmSJEmStLhZ1JYkqYEkVwL3qKrTZ4xvCZxcVeu1SSZJkiRJ0uJm+xFJkto4B9hllvFd+2OSJEmSJGkW67YOIEnSEvV24F1J7gUc2489ANgTeEGrUJIkSZIkLXa2H5EkqZEkjwNeDEz1zz4VeGtVfbFdKkmSJEmSFjeL2pIkSZIkSZKkiWH7EUmSGkpyQ+DWzNjnoqrObpNIkiRJkqTFzaK2JEkNJLkz8GFgx5mHgALWGXsoSZIkSZImgEVtSZLaOAi4BngUcD5dIVuSJEmSJK2GPbUlSWogyWXADlX1i9ZZJEmSJEmaJMtWf4okSVoAPwdu2TqEJEmSJEmTxpnakiSNSZKbTnt4b+ANwCuBk4Crp59bVZeMMZokSZIkSRPDorYkSWOS5DpW7J0drt9LO0BVlRtFSpIkSZI0CzeKlCRpfB7cOoAkSZIkSZPOmdqSJI1RklcDb6uqv7bOIkmSJEnSJLKoLUnSGCW5FrhtVV3YOoskSZIkSZNoWesAkiQtMWkdQJIkSZKkSWZRW5Kk8XOZlCRJkiRJa8n2I5IkjVGS64CLWU1hu6o2Hk8iSZIkSZImy7qtA0iStAS9hq6wLUmSJEmS1pAztSVJGqN+pvZt3ChSkiRJkqS1Y09tSZLGy7vJkiRJkiTNg0VtSZLGK60DSJIkSZI0yWw/IkmSJEmSJEmaGM7UliRJkiRJkiRNDIvakiRJkiRJkqSJYVFbkiRJkiRJkjQxLGpLkiRJkiRJkiaGRW1JkiRJkiRJ0sSwqC1JkiRJkiRJmhgWtSVJkiRJkiRJE+P/A39h6/yH5WwtAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1800x1200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.arange(len(Counter(influences[1:,1]).most_common(50)))\n",
    "y = list(zip(*Counter(influences[1:,1]).most_common(50)))[1]\n",
    "labels = list(zip(*Counter(influences[1:,1]).most_common(50)))[0]\n",
    "y2max = max(y) + 1\n",
    "\n",
    "plt.figure(figsize=(18,12), dpi=100)\n",
    "plt.bar(x, y, width=0.35)\n",
    "plt.xticks(x, labels)\n",
    "plt.ylim(0, y2max)\n",
    "plt.xticks(rotation=90)\n",
    "plt.ylabel('# of influences given')\n",
    "plt.title('Most influents')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3) What are the 5 major \"clusters\" of personalities who were influenced by a similar group of the same influencers?   \n",
    "\n",
    "(Consider a cluster as the group of personalities who were influenced by the same $\\tau$ influencers, $\\tau$ being an arbitrary number. Start with $\\tau$ = 2 and grow until there is no 2 people influenced by all of them.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4) What are the 5 major influences chains (eg, A -> B -> C -> ...)?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Shortest path between all nodes\n",
    "crescent_shortest_paths = nx.all_pairs_shortest_path(G)\n",
    "\n",
    "paths = []\n",
    "for key, dictvalue in crescent_shortest_paths:\n",
    "    for key, value in dictvalue.items():\n",
    "        paths.append(value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "path_sizes = [len(p) for p in paths]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7ff3359d27c0>]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x1200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(18,12), dpi=100)\n",
    "plt.plot(sorted(path_sizes, reverse=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "crescent_shortest_paths = nx.all_pairs_shortest_path(G)\n",
    "longest_paths = []\n",
    "for key, dictvalue in crescent_shortest_paths:\n",
    "    for key, value in dictvalue.items():\n",
    "        if(len(value) > 14):\n",
    "            longest_paths.append(value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Path 1: ['Herbert Blum', 'W. I. Thom', 'Gabriel T', 'Gottfried Wilhelm Leibniz', 'Blaise Pascal', 'Michel de Montaign', 'Sextus Em', 'Py', 'Dem', 'L', 'E', 'Zeno of Citium', 'Crates of T', 'Antisthen', 'G']\n",
      "\n",
      "Path 2: ['Herbert Blum', 'W. I. Thom', 'Gabriel T', 'Gottfried Wilhelm Leibniz', 'Blaise Pascal', 'Michel de Montaign', 'Sextus Em', 'Py', 'Dem', 'L', 'E', 'A', 'S', 'Virgil', 'Philodem']\n",
      "\n",
      "Path 3: ['Herbert Blum', 'W. I. Thom', 'Gabriel T', 'Gottfried Wilhelm Leibniz', 'Blaise Pascal', 'Michel de Montaign', 'Sextus Em', 'Py', 'Dem', 'L', 'E', 'A', 'S', 'Parmen', 'Heracl']\n",
      "\n",
      "Path 4: ['Herbert Blum', 'W. I. Thom', 'Gabriel T', 'Gottfried Wilhelm Leibniz', 'Blaise Pascal', 'Michel de Montaign', 'Sextus Em', 'Py', 'Dem', 'L', 'E', 'A', 'S', 'Posidon', 'Pan']\n",
      "\n",
      "Path 5: ['Herbert Blum', 'W. I. Thom', 'Gabriel T', 'Gottfried Wilhelm Leibniz', 'Blaise Pascal', 'Michel de Montaign', 'Sextus Em', 'Py', 'Dem', 'L', 'E', 'Zeno of Citium', 'Crates of T', 'Antisthen', 'G', 'Zeno of El']\n",
      "\n",
      "Path 6: ['Herbert Blum', 'W. I. Thom', 'Gabriel T', 'Gottfried Wilhelm Leibniz', 'Blaise Pascal', 'Michel de Montaign', 'Sextus Em', 'Py', 'Dem', 'L', 'E', 'A', 'S', 'Virgil', 'Philodem', 'Zeno of Sidon']\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x1800 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize= (25, 25) )\n",
    "index = 1\n",
    "\n",
    "for i in longest_paths:\n",
    "    print(\"Path \" + str(index) + \": \" + str(i) + \"\\n\")\n",
    "    graph = nx.DiGraph()\n",
    "    nx.function.add_path(graph, i)\n",
    "    ax = fig.add_subplot(3,2, index)\n",
    "    pos = nx.drawing.fruchterman_reingold_layout(graph)\n",
    "    nx.draw(graph, pos, node_color='blue', with_labels=True) \n",
    "    index += 1\n",
    "    if index > 6:\n",
    "        break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5) What are the countries that generated the greatest influential? "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Friedrich_Nietz'"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_influencers.Influencer[0].replace(' ','_')  #is breaking because the names are not complete"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "ename": "HTTPError",
     "evalue": "HTTP Error 404: Not Found",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mHTTPError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-34-87032319c815>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      6\u001b[0m         \u001b[0mname\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf_influencers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mInfluencer\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreplace\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m' '\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'_'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      7\u001b[0m         \u001b[0murl\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0;34m'http://en.wikipedia.org/wiki/'\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 8\u001b[0;31m         \u001b[0msource\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0murllib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0murlopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      9\u001b[0m         \u001b[0msoup\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mBeautifulSoup\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msource\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"lxml\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     10\u001b[0m         \u001b[0minformation_with_tags\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msoup\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfindAll\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'td'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36murlopen\u001b[0;34m(url, data, timeout, cafile, capath, cadefault, context)\u001b[0m\n\u001b[1;32m    220\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    221\u001b[0m         \u001b[0mopener\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_opener\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 222\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mopener\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    223\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    224\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0minstall_opener\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mopener\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36mopen\u001b[0;34m(self, fullurl, data, timeout)\u001b[0m\n\u001b[1;32m    529\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mprocessor\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprocess_response\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprotocol\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    530\u001b[0m             \u001b[0mmeth\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprocessor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmeth_name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 531\u001b[0;31m             \u001b[0mresponse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmeth\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreq\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    532\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    533\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36mhttp_response\u001b[0;34m(self, request, response)\u001b[0m\n\u001b[1;32m    638\u001b[0m         \u001b[0;31m# request was successfully received, understood, and accepted.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    639\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;36m200\u001b[0m \u001b[0;34m<=\u001b[0m \u001b[0mcode\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m300\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 640\u001b[0;31m             response = self.parent.error(\n\u001b[0m\u001b[1;32m    641\u001b[0m                 'http', request, response, code, msg, hdrs)\n\u001b[1;32m    642\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36merror\u001b[0;34m(self, proto, *args)\u001b[0m\n\u001b[1;32m    561\u001b[0m             \u001b[0mhttp_err\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    562\u001b[0m         \u001b[0margs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mdict\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mproto\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmeth_name\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 563\u001b[0;31m         \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_call_chain\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    564\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    565\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36m_call_chain\u001b[0;34m(self, chain, kind, meth_name, *args)\u001b[0m\n\u001b[1;32m    500\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mhandler\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mhandlers\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    501\u001b[0m             \u001b[0mfunc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhandler\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmeth_name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 502\u001b[0;31m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    503\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mresult\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    504\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36mhttp_error_302\u001b[0;34m(self, req, fp, code, msg, headers)\u001b[0m\n\u001b[1;32m    753\u001b[0m         \u001b[0mfp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    754\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 755\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparent\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnew\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mreq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    756\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    757\u001b[0m     \u001b[0mhttp_error_301\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mhttp_error_303\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mhttp_error_307\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mhttp_error_302\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36mopen\u001b[0;34m(self, fullurl, data, timeout)\u001b[0m\n\u001b[1;32m    529\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mprocessor\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprocess_response\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprotocol\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    530\u001b[0m             \u001b[0mmeth\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprocessor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmeth_name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 531\u001b[0;31m             \u001b[0mresponse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmeth\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreq\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    532\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    533\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36mhttp_response\u001b[0;34m(self, request, response)\u001b[0m\n\u001b[1;32m    638\u001b[0m         \u001b[0;31m# request was successfully received, understood, and accepted.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    639\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;36m200\u001b[0m \u001b[0;34m<=\u001b[0m \u001b[0mcode\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m300\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 640\u001b[0;31m             response = self.parent.error(\n\u001b[0m\u001b[1;32m    641\u001b[0m                 'http', request, response, code, msg, hdrs)\n\u001b[1;32m    642\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36merror\u001b[0;34m(self, proto, *args)\u001b[0m\n\u001b[1;32m    567\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mhttp_err\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    568\u001b[0m             \u001b[0margs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mdict\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'default'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'http_error_default'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0morig_args\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 569\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_call_chain\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    570\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    571\u001b[0m \u001b[0;31m# XXX probably also want an abstract factory that knows when it makes\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36m_call_chain\u001b[0;34m(self, chain, kind, meth_name, *args)\u001b[0m\n\u001b[1;32m    500\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mhandler\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mhandlers\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    501\u001b[0m             \u001b[0mfunc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhandler\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmeth_name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 502\u001b[0;31m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    503\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mresult\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    504\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/urllib/request.py\u001b[0m in \u001b[0;36mhttp_error_default\u001b[0;34m(self, req, fp, code, msg, hdrs)\u001b[0m\n\u001b[1;32m    647\u001b[0m \u001b[0;32mclass\u001b[0m \u001b[0mHTTPDefaultErrorHandler\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mBaseHandler\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    648\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mhttp_error_default\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreq\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmsg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhdrs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 649\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0mHTTPError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfull_url\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmsg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhdrs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfp\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    650\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    651\u001b[0m \u001b[0;32mclass\u001b[0m \u001b[0mHTTPRedirectHandler\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mBaseHandler\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mHTTPError\u001b[0m: HTTP Error 404: Not Found"
     ]
    }
   ],
   "source": [
    "#Scraping data from Wikipedia\n",
    "nationality = []\n",
    "main_interests = []\n",
    "\n",
    "for i in range(0,10):\n",
    "        name = df_influencers.Influencer[i].replace(' ','_')\n",
    "        url= 'http://en.wikipedia.org/wiki/' + name\n",
    "        source = urllib.request.urlopen(url).read()\n",
    "        soup = BeautifulSoup(source, \"lxml\")\n",
    "        information_with_tags = soup.findAll('td')\n",
    "        information = [t.getText() for t in information_with_tags]\n",
    "        if 'Nationality' in information:\n",
    "            nationality_index = information.index('Nationality')\n",
    "            nationality = nationality + [information[nationality_index +1]]\n",
    "        else: \n",
    "            nationality = nationality + ['Nationality not found']\n",
    "        if 'Main Interests' in information:\n",
    "            interest_index = information.index('Main Interests')\n",
    "            main_interests = main_interests + ['\\\\'] +[information[interest_index +1]]\n",
    "        else: \n",
    "            main_interests = main_interests + ['\\\\'] + ['Interests not found']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(0,10):\n",
    "    print('{}\\t\\t has nationality {}'.format(df_influencers.Influencer[i], nationality[i]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "6) What are the areas of greatest influence? "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(0,10):\n",
    "    print('{}\\t\\t area is {}'.format(df_influencers.Influencer[i], main_interests[i]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "7) Create a graphical representation of the graph "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=(12,12))\n",
    "nx.draw(G, with_labels=False, font_size=False, node_size=False, node_color='r', arrows=False, alpha=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"Nodes on graph: \" + str(G.number_of_nodes()))\n",
    "print(\"Connected components: \" + str(nx.number_weakly_connected_components(G)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = plt.figure(figsize=(25,25))\n",
    "\n",
    "G2=nx.weakly_connected_component_subgraphs(G)\n",
    "for g in G2:\n",
    "    c=[random.random()]*nx.number_of_nodes(g) # random color...\n",
    "    plt.title('Representacao do Grafo')\n",
    "    nx.draw_spring(g, node_size=40, node_color=c, edge_color='#E6E6E6', vmin=0.0, vmax=1.0, with_labels=False, edge_cmap=plt.cm.gray )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Exporting to Gephi  \n",
    "https://gephi.org/users/supported-graph-formats/  "
   ]
  }
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