Notebooks/12_SPARQL.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction to Databases\n",
    "\n",
    "### Using SPARQL\n",
    "\n",
    "Based on [this](https://rebeccabilbro.github.io/sparql-from-python/), [this](https://www.wikidata.org/wiki/Wikidata:SPARQL_tutorial) and [this](https://towardsdatascience.com/where-do-mayors-come-from-querying-wikidata-with-python-and-sparql-91f3c0af22e2) blog posts   \n",
    "\n",
    "There is a nice introduction to the topic [here](https://medium.com/virtuoso-blog/what-is-the-linked-open-data-cloud-and-why-is-it-important-1901a7cb7b1f)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import sys\n",
    "import time\n",
    "import json\n",
    "import datetime\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import requests\n",
    "import matplotlib.pyplot as plt\n",
    "from datetime import datetime\n",
    "\n",
    "from SPARQLWrapper import SPARQLWrapper, JSON\n",
    "\n",
    "%matplotlib inline\n",
    "plt.style.use('ggplot')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introducing SPARQL\n",
    "\n",
    "[SPARQL](https://en.wikipedia.org/wiki/SPARQL) is a query language used to retrieve data stored as [RDF](https://en.wikipedia.org/wiki/Resource_Description_Framework) (Resource Description Framework) and it is standardized by the W3C. The syntax is similar to SQL, but it has some differences for people trained in SQL. One key difference is that in SQL you tend to avoid `JOIN` clauses as they can slow down queries, but in SPARQL the queries mostly consist of joins.\n",
    "\n",
    "RDF represents data in the format [Subject - Predicate - Object](https://en.wikipedia.org/wiki/Semantic_triple)\n",
    "\n",
    "SPARQL contains capabilities for querying required and optional graph patterns along with their conjunctions and disjunctions.  \n",
    "SPARQL also supports extensible value testing and constraining queries by source RDF graph.  \n",
    "The results of SPARQL queries can be results sets or RDF graphs.\n",
    "\n",
    "SPARQL allows us to express queries as three-part statements:\n",
    "\n",
    "\n",
    "> PREFIX ... // identifies & nicknames namespaces URIs of desired variables  \n",
    "> SELECT ... // lists variables to be returned (start with a ?)  \n",
    "> WHERE  ... // contains restrictions on variables expressed as triples  \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### SPARQL basics:  \n",
    "\n",
    "A simple SPARQL query looks like this: \n",
    "\n",
    "```sparql\n",
    "SELECT ?a ?b ?c  \n",
    "WHERE  \n",
    "{  \n",
    "  x y ?a.  \n",
    "  m n ?b.  \n",
    "  ?b f ?c.  \n",
    "}  \n",
    "```\n",
    "\n",
    "The SELECT clause lists variables that you want returned (variables start with a question mark), and the WHERE clause contains restrictions on them, mostly in the form of triples. A triple can be read like a sentence (which is why it ends with a period), with a subject, a predicate, and an object:   \n",
    "\n",
    "```sparql\n",
    "SELECT ?fruit  \n",
    "WHERE  \n",
    "{  \n",
    "  ?fruit color yellow.  \n",
    "  ?fruit taste sour.  \n",
    "}\n",
    "```\n",
    "\n",
    "Given that color and taste are properties in some triples "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### First Example: Query DBPedia"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Specify the DBPedia endpoint\n",
    "sparql = SPARQLWrapper(\"http://dbpedia.org/sparql\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Query for the description of \"Capsaicin\", filtered by language\n",
    "\n",
    "sparql.setQuery(\n",
    "    \"\"\"\n",
    "    PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>\n",
    "    SELECT ?comment\n",
    "    WHERE { <http://dbpedia.org/resource/Capsaicin> rdfs:comment ?comment\n",
    "    FILTER (LANG(?comment)='en')\n",
    "    } \n",
    "    \"\"\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert results to JSON format\n",
    "sparql.setReturnFormat(JSON)\n",
    "result = sparql.query().convert()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dict_keys(['head', 'results'])\n"
     ]
    }
   ],
   "source": [
    "# The return data contains \"bindings\" (a list of dictionaries)\n",
    "print(result.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'head': {'link': [], 'vars': ['comment']},\n",
       " 'results': {'distinct': False,\n",
       "  'ordered': True,\n",
       "  'bindings': [{'comment': {'type': 'literal',\n",
       "     'xml:lang': 'en',\n",
       "     'value': 'Capsaicin (8-methyl-N-vanillyl-6-nonenamide) is an active component of chili peppers, which are plants belonging to the genus Capsicum. It is a chemical irritant for mammals, including humans, and produces a sensation of burning in any tissue with which it comes into contact. Capsaicin and several related alkaloids are called capsaicinoids and are produced as secondary metabolites by chili peppers, probably as deterrents against certain mammals and fungi. Pure capsaicin is a hydrophobic, colorless, highly pungent, crystalline to waxy solid compound.'}}]}}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Capsaicin (8-methyl-N-vanillyl-6-nonenamide) is an active component of chili peppers, which are plants belonging to the genus Capsicum. It is a chemical irritant for mammals, including humans, and produces a sensation of burning in any tissue with which it comes into contact. Capsaicin and several related alkaloids are called capsaicinoids and are produced as secondary metabolites by chili peppers, probably as deterrents against certain mammals and fungi. Pure capsaicin is a hydrophobic, colorless, highly pungent, crystalline to waxy solid compound.\n"
     ]
    }
   ],
   "source": [
    "for hit in result[\"results\"][\"bindings\"]:\n",
    "    # We want the \"value\" attribute of the \"comment\" field\n",
    "    print(hit[\"comment\"][\"value\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Second Example: Querying Wikidata\n",
    "\n",
    "Based mainly on [this excellent blog post](https://towardsdatascience.com/where-do-mayors-come-from-querying-wikidata-with-python-and-sparql-91f3c0af22e2) with [code available here](https://github.com/njanakiev/wikidata-mayors). Also based on [this tutorial](https://www.wikidata.org/wiki/Wikidata:SPARQL_tutorial)  \n",
    "\n",
    "[Wikidata](https://www.wikidata.org/) is a free and collaborative [Linked Open Data (LOD)](https://en.wikipedia.org/wiki/Linked_data) knowledge base which can be edited by humans and machines. It contains millions of statements, such as “the capital of Canada is Ottawa”, or “the Mona Lisa is painted in oil paint on poplar wood”, or “gold has a melting point of 1,064.18 degrees Celsius”.  \n",
    "The project started 2012 by the [Wikimedia Foundation](https://foundation.wikimedia.org/wiki/Home) as an effort to centralize interwiki links, infoboxes and enable rich queries. Its ambitious goal is to structure the whole human knowledge in a way that is machine readable and it speaks well to the vision of Tim Berners-Lee in his [TED talk](https://www.youtube.com/watch?v=OM6XIICm_qo) of 2009. Surprisingly, the idea of the [Semantic Web](https://en.wikipedia.org/wiki/Semantic_Web) existed already in 2001 which is comprised of Linked Data. There have been many projects preceding Wikidata. There is [DBpedia](https://en.wikipedia.org/wiki/DBpedia) which is based on the infoboxes in Wikipedia, [Friend of a Friend (FOAF)](https://en.wikipedia.org/wiki/FOAF_(ontology)) which is an ontology to describe relationships in social networks, [GeoNames](https://en.wikipedia.org/wiki/GeoNames) which provides a database with geographical names, [Upper Mapping and Binding Exchange Layer (UMBEL)](https://en.wikipedia.org/wiki/UMBEL) which is a knowledge graph of concepts and entities and a whole set of others, but Wikidata seems to be the most ambitious project between them.\n",
    "\n",
    "All of the data there is free (under the [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/) aka public domain), while anyone can edit and contribute to it. So it works in a similar way to Wikipedia. On most (if not all) Wikipedia pages, there is a _Wikidata Item_ link to its corresponding item in Wikidata, where you can find the linked information listed. Note that you can still find holes, but as it is a community effort, this is becoming better and growing over time by every contribution. To access the structured data you can query Wikidata by using its [SPARQL endpoint](https://query.wikidata.org/) which enables you to run advanced queries, or by using its [REST API](https://www.wikidata.org/w/api.php).\n",
    "\n",
    "In this diagram, you can see the structure of a Wikidata item. Each item has a list of [statements](https://www.wikidata.org/wiki/Help:Statements), which are triples in the form `SUBJECT` - `PREDICATE` - `OBJECT` (e.g. Douglas Adams is educated at the St John's College). In Wikidata the subject is referred to as [item](https://www.wikidata.org/wiki/Help:Items) and the predicate is referred to as [property](https://www.wikidata.org/wiki/Help:Properties). Each property has a value, which can be again an item, text, number, date, or GPS coordinates among others. Each value can have additional [qualifiers](https://www.wikidata.org/wiki/Help:Qualifiers) which have additional information with other property-value pairs such as start time. This structure will be important when we start to express queries with SPARQL.\n",
    "\n",
    "![Wikidata Data Model](../Figs/wikidata_data_model.png)\n",
    "\n",
    "image from [SPARQL/WIKIDATA Qualifiers, References and Ranks](https://en.wikibooks.org/wiki/SPARQL/WIKIDATA_Qualifiers,_References_and_Ranks).\n",
    "\n",
    "We can use the Wikidata Query Service (WDQS) endpoint to query Wikidata.\n",
    "\n",
    "Let’s say we want to continue our research into spicy things by searching for information about hot sauces in Wikidata. The first step is to find the unique identifier that Wikidata uses to reference “hot sauce”, which we can do by searching on Wikidata. It turns out to be “Q522171”, which is an “entity”, which corresponds to the “wd” prefix in Wikidata.\n",
    "\n",
    "If we want to get back results for all of the kinds of hot sauces cataloged in Wikidata, we want to query for the results that have the direct property – or “wdt” in Wikidata prefix speak – “\n",
    "\n",
    "NOTE: For simple WDQS triples, items should be prefixed with wd:, and properties with wdt:. We don’t need to explicitly alias any prefixes in this case because WDQS already knows many shortcut abbreviations commonly used externally (e.g. rdf, skos, owl, schema, etc.) as well as ones internal to Wikidata, such as:\n",
    "\n",
    "    PREFIX wd: http://www.wikidata.org/entity/\n",
    "    PREFIX wds: http://www.wikidata.org/entity/statement/\n",
    "    PREFIX wdv: http://www.wikidata.org/value/\n",
    "    PREFIX wdt: http://www.wikidata.org/prop/direct/\n",
    "    PREFIX wikibase: http://wikiba.se/ontology#\n",
    "    PREFIX p: http://www.wikidata.org/prop/\n",
    "    PREFIX ps: http://www.wikidata.org/prop/statement/\n",
    "    PREFIX pq: http://www.wikidata.org/prop/qualifier/\n",
    "    PREFIX rdfs: http://www.w3.org/2000/01/rdf-schema#\n",
    "    PREFIX bd: http://www.bigdata.com/rdf#"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "sparql = SPARQLWrapper(\"https://query.wikidata.org/sparql\")\n",
    "\n",
    "# Below we SELECT both the hot sauce items & their labels\n",
    "# in the WHERE clause we specify that we want labels as well as items\n",
    "\n",
    "sparql.setQuery(\"\"\"\n",
    "SELECT ?item ?itemLabel\n",
    "WHERE {?item wdt:P279 wd:Q522171.\n",
    "SERVICE wikibase:label { bd:serviceParam wikibase:language \"[AUTO_LANGUAGE],en\". }\n",
    "}\n",
    "\"\"\")\n",
    "\n",
    "sparql.setReturnFormat(JSON)\n",
    "results = sparql.query().convert()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'head': {'vars': ['item', 'itemLabel']},\n",
       " 'results': {'bindings': [{'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q249114'},\n",
       "    'itemLabel': {'xml:lang': 'en', 'type': 'literal', 'value': 'salsa'}},\n",
       "   {'item': {'type': 'uri', 'value': 'http://www.wikidata.org/entity/Q335016'},\n",
       "    'itemLabel': {'xml:lang': 'en',\n",
       "     'type': 'literal',\n",
       "     'value': 'Tabasco sauce'}},\n",
       "   {'item': {'type': 'uri', 'value': 'http://www.wikidata.org/entity/Q360459'},\n",
       "    'itemLabel': {'xml:lang': 'en', 'type': 'literal', 'value': 'Adobo'}},\n",
       "   {'item': {'type': 'uri', 'value': 'http://www.wikidata.org/entity/Q460439'},\n",
       "    'itemLabel': {'xml:lang': 'en',\n",
       "     'type': 'literal',\n",
       "     'value': \"Blair's 16 Million Reserve\"}},\n",
       "   {'item': {'type': 'uri', 'value': 'http://www.wikidata.org/entity/Q736782'},\n",
       "    'itemLabel': {'xml:lang': 'en', 'type': 'literal', 'value': 'Llajua'}},\n",
       "   {'item': {'type': 'uri', 'value': 'http://www.wikidata.org/entity/Q966327'},\n",
       "    'itemLabel': {'xml:lang': 'en', 'type': 'literal', 'value': 'harissa'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q1026822'},\n",
       "    'itemLabel': {'xml:lang': 'en', 'type': 'literal', 'value': 'chili oil'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q1392674'},\n",
       "    'itemLabel': {'xml:lang': 'en',\n",
       "     'type': 'literal',\n",
       "     'value': 'sriracha sauce'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q2227032'},\n",
       "    'itemLabel': {'xml:lang': 'en', 'type': 'literal', 'value': 'mojo'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q2258053'},\n",
       "    'itemLabel': {'xml:lang': 'en',\n",
       "     'type': 'literal',\n",
       "     'value': 'samurai sauce'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q2279518'},\n",
       "    'itemLabel': {'xml:lang': 'en', 'type': 'literal', 'value': 'Shito'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q2402909'},\n",
       "    'itemLabel': {'xml:lang': 'en', 'type': 'literal', 'value': 'Valentina'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q3273096'},\n",
       "    'itemLabel': {'xml:lang': 'en',\n",
       "     'type': 'literal',\n",
       "     'value': 'doubanjiang'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q3474250'},\n",
       "    'itemLabel': {'type': 'literal', 'value': 'Q3474250'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q4922876'},\n",
       "    'itemLabel': {'xml:lang': 'en', 'type': 'literal', 'value': 'nam phrik'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q5104402'},\n",
       "    'itemLabel': {'xml:lang': 'en',\n",
       "     'type': 'literal',\n",
       "     'value': 'Cholula Hot Sauce'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q6961170'},\n",
       "    'itemLabel': {'xml:lang': 'en', 'type': 'literal', 'value': 'nam chim'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q7707906'},\n",
       "    'itemLabel': {'xml:lang': 'en', 'type': 'literal', 'value': 'Texas Pete'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q16628511'},\n",
       "    'itemLabel': {'type': 'literal', 'value': 'Q16628511'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q16642516'},\n",
       "    'itemLabel': {'type': 'literal', 'value': 'Q16642516'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q108064182'},\n",
       "    'itemLabel': {'xml:lang': 'en',\n",
       "     'type': 'literal',\n",
       "     'value': 'peri-peri sauce'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q108127132'},\n",
       "    'itemLabel': {'xml:lang': 'en',\n",
       "     'type': 'literal',\n",
       "     'value': 'algérienne sauce'}}]}}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>item.value</th>\n",
       "      <th>itemLabel.value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>http://www.wikidata.org/entity/Q249114</td>\n",
       "      <td>salsa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>http://www.wikidata.org/entity/Q335016</td>\n",
       "      <td>Tabasco sauce</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>http://www.wikidata.org/entity/Q360459</td>\n",
       "      <td>Adobo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>http://www.wikidata.org/entity/Q460439</td>\n",
       "      <td>Blair's 16 Million Reserve</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>http://www.wikidata.org/entity/Q736782</td>\n",
       "      <td>Llajua</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>http://www.wikidata.org/entity/Q966327</td>\n",
       "      <td>harissa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>http://www.wikidata.org/entity/Q1026822</td>\n",
       "      <td>chili oil</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>http://www.wikidata.org/entity/Q1392674</td>\n",
       "      <td>sriracha sauce</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>http://www.wikidata.org/entity/Q2227032</td>\n",
       "      <td>mojo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>http://www.wikidata.org/entity/Q2258053</td>\n",
       "      <td>samurai sauce</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>http://www.wikidata.org/entity/Q2279518</td>\n",
       "      <td>Shito</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>http://www.wikidata.org/entity/Q2402909</td>\n",
       "      <td>Valentina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>http://www.wikidata.org/entity/Q3273096</td>\n",
       "      <td>doubanjiang</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>http://www.wikidata.org/entity/Q3474250</td>\n",
       "      <td>Q3474250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>http://www.wikidata.org/entity/Q4922876</td>\n",
       "      <td>nam phrik</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>http://www.wikidata.org/entity/Q5104402</td>\n",
       "      <td>Cholula Hot Sauce</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>http://www.wikidata.org/entity/Q6961170</td>\n",
       "      <td>nam chim</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>http://www.wikidata.org/entity/Q7707906</td>\n",
       "      <td>Texas Pete</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>http://www.wikidata.org/entity/Q16628511</td>\n",
       "      <td>Q16628511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>http://www.wikidata.org/entity/Q16642516</td>\n",
       "      <td>Q16642516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>http://www.wikidata.org/entity/Q108064182</td>\n",
       "      <td>peri-peri sauce</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>http://www.wikidata.org/entity/Q108127132</td>\n",
       "      <td>algérienne sauce</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   item.value             itemLabel.value\n",
       "0      http://www.wikidata.org/entity/Q249114                       salsa\n",
       "1      http://www.wikidata.org/entity/Q335016               Tabasco sauce\n",
       "2      http://www.wikidata.org/entity/Q360459                       Adobo\n",
       "3      http://www.wikidata.org/entity/Q460439  Blair's 16 Million Reserve\n",
       "4      http://www.wikidata.org/entity/Q736782                      Llajua\n",
       "5      http://www.wikidata.org/entity/Q966327                     harissa\n",
       "6     http://www.wikidata.org/entity/Q1026822                   chili oil\n",
       "7     http://www.wikidata.org/entity/Q1392674              sriracha sauce\n",
       "8     http://www.wikidata.org/entity/Q2227032                        mojo\n",
       "9     http://www.wikidata.org/entity/Q2258053               samurai sauce\n",
       "10    http://www.wikidata.org/entity/Q2279518                       Shito\n",
       "11    http://www.wikidata.org/entity/Q2402909                   Valentina\n",
       "12    http://www.wikidata.org/entity/Q3273096                 doubanjiang\n",
       "13    http://www.wikidata.org/entity/Q3474250                    Q3474250\n",
       "14    http://www.wikidata.org/entity/Q4922876                   nam phrik\n",
       "15    http://www.wikidata.org/entity/Q5104402           Cholula Hot Sauce\n",
       "16    http://www.wikidata.org/entity/Q6961170                    nam chim\n",
       "17    http://www.wikidata.org/entity/Q7707906                  Texas Pete\n",
       "18   http://www.wikidata.org/entity/Q16628511                   Q16628511\n",
       "19   http://www.wikidata.org/entity/Q16642516                   Q16642516\n",
       "20  http://www.wikidata.org/entity/Q108064182             peri-peri sauce\n",
       "21  http://www.wikidata.org/entity/Q108127132            algérienne sauce"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results_df = pd.json_normalize(results['results']['bindings'])\n",
    "results_df[['item.value', 'itemLabel.value']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ok, this was easy. \n",
    "In this next part, we will build queries for Wikidata with Python and SPARQL by taking a look where mayors in Europe are born. This pipeline was used to obtain data used in this [interactive visualization](https://janakiev.com/wikidata-mayors/), which was done with [deck.gl](http://deck.gl/#/)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this example, we want to list all countries in the European Union.\n",
    "\n",
    "```sparql\n",
    "SELECT ?country ?countryLabel WHERE {\n",
    "  ?country wdt:P463 wd:Q458.\n",
    "  SERVICE wikibase:label { bd:serviceParam wikibase:language \"en\". }\n",
    "}\n",
    "```\n",
    "You can try this query yourself [here](https://query.wikidata.org/#SELECT%20%3Fcountry%20%3FcountryLabel%20WHERE%20%7B%0A%20%20%3Fcountry%20wdt%3AP463%20wd%3AQ458.%0A%20%20SERVICE%20wikibase%3Alabel%20%7B%20%0A%20%20%20%20bd%3AserviceParam%20wikibase%3Alanguage%20%22%5BAUTO_LANGUAGE%5D%2Cen%22.%20%0A%20%20%7D%0A%7D). Note that you can test and play with each query at [https://query.wikidata.org/](https://query.wikidata.org/). The editor there offers a handful of useful features. If you hover over the properties and items in the editor you will get information about them and the editor additionally offers autocompletion. You will also find a list of examples which are quite handy when starting fresh.\n",
    "\n",
    "The statement `?country wdt:P463 wd:Q458.` collects all items which have the property [member of (P463)](https://www.wikidata.org/wiki/Property:P463) with object [European Union (Q458)](https://www.wikidata.org/wiki/Q458) into the variable `country`. As you can see, the statements read like a sentence (i.e. country is a member of the European Union). You also notice that there are the prefixes `wd:` and `wdt:`. These denote items (subjects) with `wd:` and properties (predicates) with `wdt:`. We will cover more complicated prefixes later. \n",
    "\n",
    "Finally, you will see a confusing part `SERVICE wikibase:label { bd:serviceParam wikibase:language \"en\". }` within the query. This snippet is responsible for retrieving labels for the collected items into an additional variable with `Label` postfix in the specified language (in this case English). In this query, this would be the `countryLabel` variable storing the label for the `country` variable. Note that the label is only retrieved for items that have a label in the particular language selected (in this case `\"en\"` for English), as there might be items that are not translated into this particular language.\n",
    "\n",
    "Interesting sidenote: When running the query you will notice [Kingdom of the Netherlands](https://en.wikipedia.org/wiki/Kingdom_of_the_Netherlands) with Wikidata item [Q29999](https://www.wikidata.org/wiki/Q29999) in the list of European countries. Surprisingly, [Netherlands](https://en.wikipedia.org/wiki/Netherlands) ([Q55](https://www.wikidata.org/wiki/Q55)) is a constituent country of the Kingdom of the Netherlands, but it is not a country. It is similar to how England is part of the United Kingdom. This [video](https://www.youtube.com/watch?v=WBcn-lzTJbk) does a great job explaining the situation if you were puzzled."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Advanced Queries\n",
    "\n",
    "Let's now explore other properties of the countries we have selected. If you take a look at [Germany (Q183)](https://www.wikidata.org/wiki/Q183), then you can see a whole host of properties like [population (P1082)](https://www.wikidata.org/wiki/Property:P1082), [median income (P3529)](https://www.wikidata.org/wiki/Property:P3529) or even images with the [image (P18)](https://www.wikidata.org/wiki/Property:P18) property. SPARQL enables us to retrieve those too which leads us to the next query.\n",
    "\n",
    "```sparql\n",
    "SELECT \n",
    "  ?country ?countryLabel ?population ?area ?medianIncome\n",
    "WHERE {\n",
    "  ?country wdt:P463 wd:Q458.\n",
    "  ?country wdt:P1082 ?population.\n",
    "  ?country wdt:P2046 ?area.\n",
    "  ?country wdt:P3529 ?medianIncome.\n",
    "  \n",
    "  SERVICE wikibase:label { bd:serviceParam wikibase:language \"en\". }\n",
    "}\n",
    "```\n",
    "You can try this query [here](https://query.wikidata.org/#SELECT%20%0A%20%20%3Fcountry%20%3FcountryLabel%20%0A%20%20%3Fcapital%20%3FcapitalLabel%0A%20%20%3Fpopulation%20%3Farea%20%3FmedianIncome%0AWHERE%20%7B%0A%20%20%3Fcountry%20wdt%3AP463%20wd%3AQ458.%0A%20%20%3Fcountry%20wdt%3AP36%20%3Fcapital.%0A%20%20%3Fcountry%20wdt%3AP1082%20%3Fpopulation.%0A%20%20%3Fcountry%20wdt%3AP2046%20%3Farea.%0A%20%20%3Fcountry%20wdt%3AP3529%20%3FmedianIncome.%0A%20%20%0A%20%20SERVICE%20wikibase%3Alabel%20%7B%20bd%3AserviceParam%20wikibase%3Alanguage%20%22en%22.%20%7D%0A%7D).\n",
    "\n",
    "After trying this query you will notice that the list of countries became shorter.  The reason for this is that each country item that has no population, area or median income as a property is ignored by the query. You can imagine those triples also as a filter constraining the triples that only match this query. We can add the `OPTIONAL` clause which will leave those variables empty if the query cannot find triples within this clause.\n",
    "\n",
    "```sparql\n",
    "SELECT \n",
    "  ?country ?countryLabel ?population ?area ?medianIncome\n",
    "WHERE {\n",
    "  ?country wdt:P463 wd:Q458.\n",
    "  OPTIONAL { ?country wdt:P1082 ?population }\n",
    "  OPTIONAL { ?country wdt:P2046 ?area }\n",
    "  OPTIONAL { ?country wdt:P3529 ?medianIncome }\n",
    "    \n",
    "  SERVICE wikibase:label { bd:serviceParam wikibase:language \"en\". }\n",
    "}\n",
    "```\n",
    "\n",
    "You can try this query [here](https://query.wikidata.org/#SELECT%20%0A%20%20%3Fcountry%20%3FcountryLabel%20%0A%20%20%3Fcapital%20%3FcapitalLabel%0A%20%20%3Fpopulation%20%3Farea%20%3FmedianIncome%0AWHERE%20%7B%0A%20%20%3Fcountry%20wdt%3AP463%20wd%3AQ458.%0A%20%20%3Fcountry%20wdt%3AP36%20%3Fcapital.%0A%20%20%20%20%0A%20%20OPTIONAL%20%7B%20%3Fcountry%20wdt%3AP1082%20%3Fpopulation%20%7D%0A%20%20OPTIONAL%20%7B%20%3Fcountry%20wdt%3AP2046%20%3Farea%20%7D%0A%20%20OPTIONAL%20%7B%20%3Fcountry%20wdt%3AP3529%20%3FmedianIncome%20%7D%0A%20%20%0A%20%20SERVICE%20wikibase%3Alabel%20%7B%20bd%3AserviceParam%20wikibase%3Alanguage%20%22en%22.%20%7D%0A%7D). Now we see in the table that we will find all countries again.\n",
    "\n",
    "![Query Result](../Figs/query_result.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# SPARQL Data Representation\n",
    "\n",
    "We continue our journey with a complicated query which we will unpack step by step. Our goal is now to get for all countries, the capital, the population, the mayor, his birthday and finally his birthplace. The query looks like this.\n",
    "\n",
    "```sparql\n",
    "SELECT DISTINCT \n",
    "  ?country ?countryLabel ?capital ?capitalLabel ?population \n",
    "  ?mayor ?mayorLabel ?birth_place ?birth_placeLabel ?birth_date ?age\n",
    "WHERE {\n",
    "  # Get all european countries, their capitals and the population of the capital\n",
    "  ?country wdt:P463 wd:Q458.\n",
    "  ?country wdt:P36 ?capital.\n",
    "  OPTIONAL { ?capital wdt:P1082 ?population. }\n",
    "  \n",
    "  # Get all mayors without an end date\n",
    "  ?capital p:P6 ?statement.\n",
    "  ?statement ps:P6 ?mayor.\n",
    "  FILTER NOT EXISTS { ?statement pq:P582 ?end_date }\n",
    "  \n",
    "  # Get birth place, birth date and age of mayor\n",
    "  ?mayor wdt:P19 ?birth_place.\n",
    "  ?mayor wdt:P569 ?birth_date.\n",
    "  BIND(year(now()) - year(?birth_date) AS ?age)\n",
    "  \n",
    "  SERVICE wikibase:label { \n",
    "    bd:serviceParam wikibase:language \"[AUTO_LANGUAGE],en\". \n",
    "  }\n",
    "}\n",
    "```\n",
    "You can try this query [here](https://query.wikidata.org/#SELECT%20DISTINCT%20%0A%20%20%3Fcountry%20%3FcountryLabel%20%3Fcapital%20%3FcapitalLabel%20%3Fpopulation%20%0A%20%20%3Fmayor%20%3FmayorLabel%20%3Fbirth_place%20%3Fbirth_placeLabel%20%3Fbirth_date%20%3Fage%0AWHERE%20%7B%0A%20%20%3Fcountry%20wdt%3AP463%20wd%3AQ458.%0A%20%20%3Fcountry%20wdt%3AP36%20%3Fcapital.%0A%20%20OPTIONAL%20%7B%20%3Fcapital%20wdt%3AP1082%20%3Fpopulation.%20%7D%0A%20%20%0A%20%20%3Fcapital%20p%3AP6%20%3Fstatement.%0A%20%20%3Fstatement%20ps%3AP6%20%3Fmayor.%0A%20%20FILTER%20NOT%20EXISTS%20%7B%20%3Fstatement%20pq%3AP582%20%3Fend_date%20%7D%0A%20%20%20%20%0A%20%20%3Fmayor%20wdt%3AP19%20%3Fbirth_place.%0A%20%20%3Fmayor%20wdt%3AP569%20%3Fbirth_date.%0A%20%20BIND%28year%28now%28%29%29%20-%20year%28%3Fbirth_date%29%20AS%20%3Fage%29%0A%20%20%0A%20%20SERVICE%20wikibase%3Alabel%20%7B%20%0A%20%20%20%20bd%3AserviceParam%20wikibase%3Alanguage%20%22%5BAUTO_LANGUAGE%5D%2Cen%22.%20%0A%20%20%7D%0A%7D).\n",
    "\n",
    "Let's unpack what is happening here. First, we start by getting the capital of the country which we simply get via the [capital (P36)](https://www.wikidata.org/wiki/Property:P36) property. Next, we get to a more complicated part. To understand how to get to the mayor we have to look at the SPARQL Data Representation in this diagram.\n",
    "\n",
    "![SPARQL data representation](../Figs/SPARQL_data_representation.png)\n",
    "\n",
    "image from [SPARQL/WIKIDATA Qualifiers, References and Ranks](https://en.wikibooks.org/wiki/SPARQL/WIKIDATA_Qualifiers,_References_and_Ranks).\n",
    "\n",
    "This graph of the data representation that you see here shows the ways you can traverse it to get to various pieces of information with SPARQL starting from an item (in the graph shown as `wd:Q1234`). You can see on the left the classical path we took in our previous triples by using the `wdt:` prefix which leads to the value which can be another item, a numeric value (e.g. the population as in one of the previous queries) or various other data types.\n",
    "\n",
    "If you take a look at an item like [Rome (Q220)](https://www.wikidata.org/wiki/Q220), you will notice that there are various statements for the [head of government (P6)](https://www.wikidata.org/wiki/Property:P6). We want to get the one which has no end date. We can do this by traversing to the statement node with the `p:` prefix and storing it in the `statement` variable. From this variable, we can get the mayor with the `ps:` prefix. We could have done that with `wdt:` as we already have learned but we want to go one step further. We want to get to [end time (P582)](https://www.wikidata.org/wiki/Property:P582) which is stored as a qualifier in the statement. We can traverse to the qualifier with the `pq:` prefix which would give us the end date, but we want mayors without an end date. This can be done by using the `FILTER NOT EXISTS` clause which excludes all triples with statement node that have an end date.\n",
    "\n",
    "In the final part, we collect the birthplace, the birth date and the age of the mayor. In order to calculate his age, we use the `BIND` expression. This expression can be used to bind some expression to a variable (in our case the age variable). For this expression, we subtract the year of the birth date with the current year. This concludes this query. You can dig deeper in [SPARQL/WIKIDATA Qualifiers, References and Ranks](https://en.wikibooks.org/wiki/SPARQL/WIKIDATA_Qualifiers,_References_and_Ranks) which describes the data representation in further detail."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have seen how to work with SPARQL and we can also download the resulting tables in the editor, but how do we will automate the whole processwith Python, which enables us to directly load and analyze the data we have queried. To do this, we will employ the [request](http://docs.python-requests.org/en/master/) module which does a great job at doing HTTP requests with all its necessary tooling. We can create the request by adding the query as a parameter as follows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "url = 'https://query.wikidata.org/sparql'\n",
    "\n",
    "query = \"\"\"\n",
    "SELECT \n",
    "  ?countryLabel ?population ?area ?medianIncome ?age\n",
    "WHERE {\n",
    "  ?country wdt:P463 wd:Q458.\n",
    "  OPTIONAL { ?country wdt:P1082 ?population }\n",
    "  OPTIONAL { ?country wdt:P2046 ?area }\n",
    "  OPTIONAL { ?country wdt:P3529 ?medianIncome }\n",
    "  OPTIONAL { ?country wdt:P571 ?inception. \n",
    "    BIND(year(now()) - year(?inception) AS ?age)\n",
    "  }\n",
    "  SERVICE wikibase:label { bd:serviceParam wikibase:language \"en\". }\n",
    "}\n",
    "\"\"\"\n",
    "r = requests.get(url, params = {'format': 'json', 'query': query})\n",
    "data = r.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have packed the query in the `query` variable and we need to additionally supply request with the SPARQL endpoint URL which is [https://query.wikidata.org/sparql](https://query.wikidata.org/sparql). We want to use JSON as an output file, so we add this also to our request. The API returns XML as default but supports besides JSON also TSV, CSV and Binary RDF. This request returns a JSON with all the rows collected from the query, which we can use collect the rows into a [Pandas](https://pandas.pydata.org/) DataFrame as follows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>population</th>\n",
       "      <th>area</th>\n",
       "      <th>medianIncome</th>\n",
       "      <th>age</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Kingdom of the Netherlands</th>\n",
       "      <td>17100715.0</td>\n",
       "      <td>42201.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>206.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ireland</th>\n",
       "      <td>4761865.0</td>\n",
       "      <td>70273.0</td>\n",
       "      <td>25969.0</td>\n",
       "      <td>84.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Belgium</th>\n",
       "      <td>11431406.0</td>\n",
       "      <td>30528.0</td>\n",
       "      <td>31112.0</td>\n",
       "      <td>191.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hungary</th>\n",
       "      <td>9769526.0</td>\n",
       "      <td>93011.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1021.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spain</th>\n",
       "      <td>46733038.0</td>\n",
       "      <td>505990.0</td>\n",
       "      <td>21959.0</td>\n",
       "      <td>542.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            population      area  medianIncome     age\n",
       "country                                                               \n",
       "Kingdom of the Netherlands  17100715.0   42201.0           NaN   206.0\n",
       "Ireland                      4761865.0   70273.0       25969.0    84.0\n",
       "Belgium                     11431406.0   30528.0       31112.0   191.0\n",
       "Hungary                      9769526.0   93011.4           NaN  1021.0\n",
       "Spain                       46733038.0  505990.0       21959.0   542.0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from collections import OrderedDict\n",
    "\n",
    "countries = []\n",
    "for item in data['results']['bindings']:\n",
    "    countries.append(OrderedDict({\n",
    "        'country': item['countryLabel']['value'],\n",
    "        'population': item['population']['value'],\n",
    "        'area': item['area']['value'] \n",
    "            if 'area' in item else None,\n",
    "        'medianIncome': item['medianIncome']['value'] \n",
    "            if 'medianIncome' in item else None,\n",
    "        'age': item['age']['value'] \n",
    "            if 'age' in item else None}))\n",
    "\n",
    "df = pd.DataFrame(countries)\n",
    "df.set_index('country', inplace=True)\n",
    "df = df.astype({'population': float, 'area': float, 'medianIncome': float, 'age': float})\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's explore the collected data visually and compare the various properties for each country. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABHgAAANYCAYAAAC/+Vr7AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/Il7ecAAAACXBIWXMAAAsTAAALEwEAmpwYAAEAAElEQVR4nOzdfXzO9f///9tx7NiJnTqZ0Whmhi1CzksZNbzDW97vhHelQsnbktMlSiNkrJGy3u9y/vFVmfKu9HknrXKehIiRsyzW6CAns83s5Dh+f/jt+LRsDLPjeM39erm8Lx3H63id3F/PN9vL43iemOx2ux0RERERERERETEss7MDiIiIiIiIiIjIjVGBR0RERERERETE4FTgERERERERERExOBV4REREREREREQMTgUeERERERERERGDU4FHRERERERERMTgVOAREXFBTz31FNHR0Td8nrS0NEwmExs3biyHVCIiInIrWLt2LSaTifT09BLf36zriMiNUYFHROQPnnrqKUwmEyaTCYvFQr169Rg6dCi///67s6NdVXh4OJMmTSq27fbbb+f48eO0a9fOOaFERESkXBU9q/z973+/7LNPPvnE8QxTnu655x6OHz9OcHCwIc4rcqtSgUdE5E/uu+8+jh8/TlpaGm+++SYfffQRTzzxhLNjXRc3Nzdq166Nu7u7s6OIiIhIOQkJCeGzzz7jt99+K7b9nXfeoV69euV+PQ8PD2rXro3ZXL7/fLxZ5xW5VelvkojInxQ9bNStW5eHHnqIkSNHsnr1ai5cuMDrr79OWFgYHh4eNGjQgDfeeKPYsaGhobz00ks8/fTT+Pv7ExgYyIQJE7DZbMX2mTp1arHjnn76aTp16lRqph07dvDggw8SFBSEr68vbdq0YfXq1Y7PO3XqxOHDh5k8ebKjB1JaWlqJQ7T2799Pjx498PX1xdfXl7/+9a8cOnTI8fnixYuxWCxs2rSJli1b4u3tTatWrfj++++vs0VFRESkPDVs2JD27duzePFix7ajR4/y5ZdfMnDgwGL7bt++na5du+Lr60vNmjX5+9//zi+//FJsn7feeou6devi7e1Nt27dOHr0aLHP/zyUym6388wzz9CgQQOqVKlCWFgYEyZM4OLFi45jJk2aRHh4OJ988gkRERH4+PjQqVMnDh48WOp5i95/+eWXdOzYEW9vb+644w4+//zzYnmsVisDBw6kVq1aeHl50bhxYxYuXOj4fMuWLXTs2JEqVapQrVo1Hn30UaxW62XZkpOTadiwId7e3vTu3ZvMzExWrlxJ48aN8fPzo0+fPpw7d67YtT/44ANatGiBl5cXoaGhjB49muzs7Kv+fyZSEVTgERG5iipVqmCz2Xj33XeZOHEiL774IqmpqcTGxvLiiy+yYMGCYvu/9dZbBAcH8/333zN79mzmzJnDW2+9dUMZMjMz6devH9988w07duygW7du9OrViwMHDgCwcuVKQkNDGTNmDMePH+f48ePcfvvtl53nwoULdO3aldzcXNatW8e6devIysriL3/5C3l5eY79bDYb48ePZ86cOezYsYOgoCD69u1LQUHBDd2HiIiIlI8hQ4Ywf/587HY7APPnz+eBBx4o1oNn7969REVFcffdd7Nt2za+/vpr3Nzc6NKlC7m5ucClYV2jRo1i9OjR7Ny5k759+xIbG3vFa9vtdoKCgnjvvffYt28fb7zxBosWLeK1114rtt/x48f517/+xbJly9i8eTPnz59n0KBBV723sWPHMmHCBHbt2kW7du3o168fZ86cAS49y0RFRbFr1y6WLVvG3r17eeutt/D29gbgxIkTdO3albp167J161ZWrVrFnj176NOnz2XZlixZwkcffcTnn3/Opk2b6NOnD/Pnzyc5OZnPP/+cDRs2FLunxYsX889//pMxY8awd+9e/ud//oeUlBSGDh161XsSqRB2ERFxePLJJ+0PPPCA431qaqo9LCzM3q5dO3vdunXtsbGxxfYfOXKkvX79+o739erVs997773F9hk/fry9bt26xfaZMmVKsX0GDx5sj4qKKjVHSZo1a2afOnWq432DBg3scXFxxfY5cuSIHbBv2LDBbrfb7fPnz7dXqVLFfvLkScc+J06csHt5edmXLFlit9vt9kWLFtkB+/bt2x37bNmyxQ7Yf/rppytmEhERkZur6BnhwoUL9urVq9u//vpre0FBgb1OnTr2jz76yL5o0SK7m5ubY99+/foVOz43N9depUoV+3/+8x+73W63d+jQwf7oo48W22fMmDF2wH7s2DG73W63f/PNN8Xel2TWrFn28PBwx/u4uDi7m5ub3Wq1OrZ98MEHdpPJZL9w4UKJ5y16/9FHHzmOOXHihB2wr1692m63X3qW8fT0LDXLyy+/bK9Tp4794sWLjm07d+60A/Z169YVy/bH56Fhw4bZzWZzsbzPP/+8vVWrVo739erVs//rX/8qdr1169bZAfvp06dLbRuRiqIePCIif7J27Vp8fX2pUqUKTZs2JSwsjHfffZf09HQ6duxYbN+oqCjS0tLIyclxbLv77ruL7dOhQwfS09PJzMy87kwnT55k2LBhREREULVqVXx9fUlNTb2si/XVpKamcscddxAYGOjYVqtWLRo3bkxqaqpjm8lkonnz5o73RZMf/nmsv4iIiDiHl5cXAwYMYN68efzv//4vBQUF/PWvfy22z/fff89//vMfx7BsX19fatSoQW5urmOo1N69e7nnnnuKHXfvvfde9frz5s2jXbt21KpVC19fX8aPH3/Zc0lwcDA1a9Ys9t5utxcbLlWSFi1aOF7XqlULNzc3xzPI9u3bueOOO6hbt26Jx6amptK+fXs8PDwc25o3b05AQECxZ506deoUex6qXbs2tWvXLpa3du3ajqwnT57kl19+YfTo0cXa88EHHwQoNtxdxFnKd3p1EZFKoF27dixZsgSLxUJwcDAeHh43VJz5M7PZ7OhOXSQ/P/+Kxzz11FMcPXqUmTNnUr9+fapUqUL//v2LDasqT2azGTc3N8d7k8kEUGwuIREREXGuIUOG0LJlS44dO8bAgQMvW1TBZrMxYMAAXnzxxcuOrVGjxnVfd8WKFcTExBAfH09UVBT+/v6sWLGCl156qdh+fyyyQNmfJ/58XFmOuVZ/biuTyVTitqLrFv13zpw5dO7c+bLzlVZwEqlI6sEjIvInVapUITw8nNDQUMcDhr+/P3Xr1mX9+vXF9l23bh3169d3jPuGSxP7/dHmzZupU6cO/v7+AAQFBZGRkVFsnx9++OGKmdavX8+wYcPo1asXd955J7fddhs///xzsX08PDwoLCy84nmaNGnC3r17OXXqlGPbb7/9xv79+2natOkVjxURERHXcscdd9CmTRs2bdrE008/fdnnrVu35scff6RBgwaEh4cX+1+1atUc59i8eXOx4zZt2nTF665fv5677rqL0aNH06pVKxo2bEhaWlq53deVtGrVir179zomZv6zJk2asGXLlmJfgu3atYtz587d0LNOrVq1uP3229m/f/9lbRkeHo6Xl9d1n1ukvKjAIyJSRuPHj+ett95i3rx5HDx4kHfeeYd//etfTJgwodh+O3fuZNKkSRw4cID33nuPOXPmMGbMGMfn0dHRLF++nDVr1rB//35GjRp11aFWjRs3ZtmyZezevZudO3fyj3/847JiTv369dm0aRNHjx7l1KlTJX7T9eijj1KzZk369evHjh072L59O/3796dOnTr069fvBlpHREREnOGLL77g1KlTNGjQ4LLPJkyYwL59+3j88cfZunUrR44c4ZtvvmHEiBGOL4rGjBnD8uXLmTNnDgcPHmTRokUsXbr0itds3Lgxu3fv5pNPPuHw4cPMmTOHlStX3pT7+7N//OMf1KtXj169epGSksKRI0f46quvWL58OQDPPfccmZmZPPXUU+zZs4eNGzcyYMAA7rvvPu67774buva0adN48803mTZtGnv27GH//v18/PHHPPvss+VxayI3TAUeEZEy+uc//8mrr77Ka6+9xh133MGMGTOIj49n8ODBxfYbPnw4v/zyC61bt2b48OE899xzjBgxwvH5uHHj6NGjB/369eO+++4jICCARx555IrXXrRoETabjbZt29K7d2/+8pe/0KZNm2L7TJ48mbNnz9K4cWNq1qx52RKncKl30po1a/D09KRjx45ERUXh4+PD6tWrS+wOLSIiIq7N29ub6tWrl/hZZGQkmzdvJisri27dunHHHXfwzDPPcOHCBapWrQrA3/72NxITE5k5cybNmjVj2bJlzJgx44rXfPbZZxkwYAADBw7krrvu4rvvvmPSpEnlfGcl8/b2Zt26dTRt2pT+/fsTGRlJTEwMFy5cAC71tFmzZg3p6em0adOGnj170rRpUz788MMbvvaAAQNITk7ms88+o23btrRp04ZJkyZRp06dGz63SHkw2f88EYSIiFy30NBQnn76aV5++WVnRxERERERkVuIevCIiIiIiIiIiBicCjwiIiIiIiIiIganIVoiIiIiIiIiIganHjwiIiIiIiIiIganAo+IiIiIiIiIiMFZnB1Abi0ZGRnOjnBdAgMDOXXqlLNjXBdldx4j51d25zBydnCd/MHBwc6OILcooz7nVDRX+VlhBGqrslNblZ3aqmxcuZ1Ke9ZRDx4REREREREREYNTDx4XdvbsWZYsWcLBgwfx8fHBYrHw0EMP0bZtW2dHu26Fz/RydoTr8puzA9wAZXceI+dXducwcna4/vxu8z4t1xwiIiIityIVeFyU3W4nISGBqKgoRowYAcDJkyfZtm1bmY4vLCzEzc3tZkYUERERERERERehAo+L2rNnDxaLha5duzq21axZkwcffBCbzcayZcvYu3cv+fn5dOvWjS5dupCamsry5cvx8fEhIyODIUOGkJycjI+PD0ePHuXuu+8mJCSE//73v+Tl5REbG0vt2rXZtm0bK1eupKCgAD8/P4YPH07VqlVJTk7m1KlTWK1WTp06Rffu3enevTvLly/H19eXHj16APD+++8TEBBA9+7dndVcIiIiIiIiIrc0FXhc1LFjx6hfv36Jn3399dd4e3szffp08vPzmThxIs2bNwfgyJEjJCYmEhQURGpqKr/88guzZ8/G19eX5557jgceeIDp06fz3//+l9WrV/PUU08RERHBtGnTMJlMfPXVV3z66ac88cQTwKXJAuPi4rhw4QIjR46ka9eudO7cmcTERHr06IHNZmPz5s289tprJWZNSUkhJSUFgPj4+JvQUiIiYnSBgYHOjiAiIiJieCrwGMT8+fPZv38/FouFwMBAjh49ypYtWwDIycnh+PHjWCwWwsPDCQoKchzXoEEDqlWrBkDt2rVp1qwZACEhIezZsweA06dP88Ybb3DmzBkKCgqKHd+yZUvc3d1xd3cnICCAc+fOERQUhK+vL0eOHOHcuXOEhobi5+dXYu7o6Giio6NvSpuIiEjlUN4rVGgVLXEWo841WNGMPt9YRVJblZ3aquzUVmVTnu1UUfMNqsDjom6//Xa+++47x/unn36azMxMxo8fT40aNRg4cCAtWrQodkxqaiqenp7Ftrm7uztem0wmx3uTyYTNZgNg4cKF9OzZk9atW5OamsqKFSscx1gs//dHxGw2U1hYCMADDzzA2rVrOXv2LJ07dy6fmxYRERERERGR66ICj4tq2rQp77//PmvWrHHMw5OXlwdAixYtWLNmDU2bNsVisZCRkUH16tWv+1o5OTmO49etW1emY9q2bcvy5cspLCx0TAJdFkZdKSUwMLDcv2GuKMruPEbOr+zOYeTsYPz8IiIiIkamAo+LMplMxMbGsmTJEj755BP8/f3x8vLiscceo3379litVsaNGweAv78/sbGx132tRx55hFmzZuHj40PTpk2xWq1XPcZisdCkSRN8fHwwm83XfW0RERExpgEDBrB06dJbPoOIiIirMNntdruzQ4jx2Gw2xo0bx+jRo7ntttvKfFxGRsZNTHXzGPlbaWV3HiPnV3bnMHJ2cJ38moOnYrhCceVmZCgsLMTNze26jj3Wo3W5ZhERkcqhvEeylPasox48cs3S09OJj4+nbdu211TcERERkcpt0qRJDBgwgAYNGjjmDkxKSuKzzz7j6NGjDBs2jKNHjzJnzhxee+01zpw5w4IFC8jMzMTT05Nnn32WOnXqkJSUhIeHB2lpaZw7d45//vOfrFu3joMHDxIeHk5MTIzjmosXL+bHH3+katWqjBw5En9/f9LS0pg3bx4XL16kVq1a/POf/8TX17fUfGvXruW7774jNzcXm83GhAkTSEpK4tixYwQHB3PmzBkGDx5MgwYNnNi6IiIiV6YCj1yzunXrMnfuXGfHEBEREYPo3r07kydPZuvWraxcuZJnnnkGT09P3n33XZ555hluu+02Dh48yPz584mLiwMgOzubqVOnsm3bNmbOnMmUKVOoW7cu48ePJy0tjdDQUC5evEiDBg146qmn+PDDD1mxYgWDBw9m7ty5DBo0iDvuuIPly5fz4Ycf8tRTT10x45EjR3j99dfx9fXl008/xdfXl9mzZ3P06FFeeOGFEo9JSUkhJSUFgPj4+HJtMxERqTwCAwMr5Doq8IiIiIjITWU2mxk2bBhjx46lS5cuREREkJuby/79+5k1a5Zjv4KCAsfrVq1aYTKZCAkJISAggJCQEODSSqNWq5XQ0FBMJhP33HMPAPfddx+vv/46OTk5ZGdnc8cddwAQFRXF7Nmzr5qxWbNm+Pr6AvDTTz/RvXt3AEJCQqhXr16Jx0RHRxMdHX0dLSIiIreS8h7CriFat4h+/fo5HoAAYmNjCQoKcmKi4gqf6eXsCNflN2cHuAHK7jxGzq/sN8aoKwaK3Cg3NzeKpnfMz88v9tnx48fx8vLi9OnTwKX5/Hx8fEhISCjxXO7u7sClhSeKXhe9t9lsJR5jMpmuO5+np+cVjxUREXF1Wv6okvHw8CAhIcHxvz8Wd+x2e6kPRCIiIiI3qmbNmvz8888AbNmyxbE9JyeHRYsWMXnyZLKystiyZQve3t4EBQXx7bffApeeU9LS0q7pena73XGdjRs3EhERgbe3N76+vuzbtw+A9evXExkZecV8fxYREeHIlZ6eztGjR68pl4iIiDOoB08lZ7VamTZtGg0bNuTnn39m/PjxfPzxxxw+fJi8vDzat29P3759AYiJiSEqKort27dTUFDA6NGjqVOnDrm5uSxcuJDDhw9jMpno06cP7du3Z9euXSQnJ1NQUECtWrUYNmwYXl5eTr5jERERqQh5eXkMHTrU8b5nz5789a9/Zfbs2aSkpNCyZUvHZ4sXL6Zbt24EBwczdOhQJk+eTGRkJM8//zzz5s1j5cqVFBQU0KFDB0JDQ8ucwdPTk0OHDrFy5Ur8/f0ZNWoUcOmZpmiS5aCgIIYNGwZQar4/69q1K0lJSYwaNYo6depQt25dvL29r7GFREREKpaWSa9k/jhEKygoiCeffJLhw4czZcoUGjVqBEBWVha+vr7YbDZeffVVBg4cSL169YiJiaFnz548+OCDfPHFFxw5coShQ4fy//7f/6OgoMAxOWFWVhY2m43ExETGjx+Pl5cXH3/8MQUFBfTp06dYnj9PPqjlQ0XkVlDrP5uv6ziLxVJsDhKjcZX8Hh4ezo4gBmez2SgoKMDDw4MTJ04wZcoU5syZg8Vy5e9G9ZwjIiIl0TLpcl2KhmgVsVqtBAYGOoo7AJs3b+arr76isLCQM2fOkJ6e7pg8sF27dgCEhYWxdetWAHbv3s3IkSMdx/v6+rJ9+3bS09OZOHEicGlSxD9eo4gmHxSRW9H1TqQXGBhY7pPwVSRXyV/aQ49IWV28eJHJkydTWFiI3W7n6aefvmpxR0RExNn0m+oW8MdhU1arlVWrVjF9+nR8fX1JSkoqNslg0cOL2WymsLCw1HPa7XbuvPPOYoUfERERkcqgSpUq17XsuSZYLxtXKQYbgdqq7NRWZae2KhsjtpMKPLeYnJwcvLy88Pb25uzZs+zcuZMmTZpc8ZhmzZrxxRdfFBui1ahRIxYsWMCJEyeoXbs2ubm5nD59+qrfmhr1wceIf7mLKLvzGDm/souIiIiIGIsKPLeY0NBQQkNDGTVqFDVq1KBx48ZXPebhhx9m/vz5jBkzBrPZTJ8+fWjXrh0xMTHMmTPH0QOof//+6hYvIiIiIiIi4gSaZFkqVEZGhrMjXBcj9whQducxcn5ldw4jZwfXya8vG8RZjPqcU9Fc5WeFEaityk5tVXZqq7Jx5XYq7VnHXME5RERERERERESknKnAIyIiIiIiIiJicCrwiIiIiIiIiIgYnCZZ/hOr1cqMGTNITEx0bEtOTsbLy4tevXqVetzhw4dZt24dgwYNIjU1FYvFUqYJjP8oJiaG6dOn4+/vX+r2n3/+mcTERMaOHcvvv/9Oeno6vXv3vqbrlCQ1NZVVq1bx4osv3vC5rqTwmdLb0JX95uwAN0DZncfI+ZX92hh1hUARERERqTxU4CknDRo0oEGDBsClYomXl9c1F3iu5pdffiExMZFRo0ZRv3596tevT+vWrcv1GiIiIiIiIiJiPCrwXKNJkyYRHh5OamoqOTk5DB06lMjISEcPmEGDBvHll19iNpvZsGEDgwYNok6dOrz77rv8/vvvADz55JNERERw/vx55syZw+nTp2nUqBFXWtDs119/JSkpieHDhxMeHg7A2rVrOXz4MIMHDyYpKYkqVarw888/c/bsWR5//HHat2+PzWZj4cKF7Nmzhxo1amCxWOjcuTPt27dn586dLF68GE9Pz2LFqKysLN5++22sViuenp4MGTKEevXqkZycjNVqxWq1curUKZ588kkOHjzIDz/8QPXq1Rk3bhwWi/5IiYiIiIiIiFQ0zcFzHWw2G9OnT+fJJ5/kww8/LPZZUFAQXbp0oUePHiQkJBAZGcmiRYvo2bMn06dPZ8yYMbzzzjsArFixgoiICGbNmkXbtm2vuATbzJkzGTRoEBEREaXuc/bsWV599VVefPFFli1bBsDWrVs5efIks2bNYvjw4Rw4cACAvLw83nnnHcaNG0d8fDxnz551nCc5OZn69evz+uuv849//IO5c+c6Pvvtt9945ZVXeOGFF3jrrbdo0qQJiYmJeHh4sGPHjmtuSxERERERERG5cepu8Scmk+mq29u2bQtAWFgYVqv1qufcvXs36enpjvc5OTnk5uayb98+xo4dC0DLli3x8fEp9Rx33nknX3/9NS1atMBsLrku16ZNG8xmM3Xr1uXcuXMA/PTTT7Rv3x6z2UzVqlVp0qQJABkZGQQFBXHbbbcB0LFjR1JSUhzHjBkzBoCmTZuSlZVFTk4OAHfddRcWi4WQkBBsNhstWrQAICQkhJMnT16WKSUlxXHe+Pj4q7aViIgRBQYGlst5LBZLuZ3LGYyeX0RERMTIVOD5Ez8/P7Kysopty8rKIigoyPHe3d0dALPZjM1mu+o57XY706ZNw8PD47pzDR48mHnz5jF//nyGDBlS4j5FuYqueTMUDcEym824ubk5Cl8mk4nCwsLL9o+OjiY6OvqmZBERcRVX6oF5LQIDA8vtXM7gKvmDg4OdHUFERESkwqnA8ydeXl5Uq1aNPXv2OHqv7Nq1i+7du5f5HFWqVOHChQuO982aNWP16tWOVbjS0tIIDQ0lMjKSjRs38vDDD/PDDz+QnZ1d6jlNJhPPP/8806ZNY/ny5fTr169MWRo3bsy6deuIiooiMzOT1NRU7r33XoKDg7FarZw4cYLatWuzceNGxzERERFs2LCBPn36kJqaip+fH97e3mW+fxEREZFbkVFXC61oRl6psaKprcpObVV2aquy+XM7GWHVVBV4SvDcc8+xYMEClixZAkCfPn2oXbt2mY9v1aoVs2bN4vvvv2fQoEEMHDiQBQsWMHbsWAoLC4mMjGTIkCE88sgjzJkzh9GjR9OoUaOrdmv38PBg3LhxxMXFERAQgJeX11WztGvXjt27dzN69Ghq1KhBWFgY3t7eeHh48OyzzxIfH4+npycRERHk5uYC0LdvX95++23Gjh2Lp6cnMTExZb73qzHCX4qSuMq30tdD2Z3HyPmVXURERETEWEz2mzWWR1xGbm4uXl5enD9/ngkTJjBlyhSqVq3qlCwZGRlOue6NMvI/GJXdeYycX9mdw8jZwXXya4iWOMuxHq2dHUFERG4SV+qsUNqzjnrw3ALi4+PJzs6moKCAhx9+2GnFHREREZGyWrlyJRs3bsRsNmMymRgyZAgNGzYsl3MPGDCApUuXlsu5REREXIUKPLeASZMmOTuCiIiISJkdOHCA7du3M2PGDNzd3cnMzKSgoMDZsURERFyaCjwiIiIi4lLOnDmDn5+fY4VQf39/Dh06xMKFCxk7dizff/89b7zxBkuWLMFmszF69Gjmzp3LiRMnWLBgAZmZmXh6evLss89Sp04drFYrc+bMITc3lzZt2hS71qeffsq3335Lfn4+bdu2pW/fvlitVqZPn07jxo05cOAA1atX54UXXrihFVFFRERuNhV4bmFF3ZOtVisHDhzg3nvvveL+VquVGTNmkJiYWEEJRURE5FbUvHlzPvzwQ0aMGMGdd97JPffcQ+PGjUlLSwNg3759hISEcOjQIWw2G+Hh4QC8++67PPPMM9x2220cPHiQ+fPnExcXx6JFi+jatStRUVGsXr3acZ1du3Zx/PhxXnvtNex2OzNnzmTv3r0EBgZy/PhxRowYwdChQ5k1axZbtmyhY8eOxXKmpKSQkpICXBoSLyIildfVFkVyBSrwCCdPnmTjxo1XLfCUB6MuH2rkpQSV3XmMnL8yZHelifBE5Np4eXkxY8YM9u3bR2pqKrNnz+axxx6jVq1apKenc/jwYXr06MG+ffuw2WxERkaSm5vL/v37mTVrluM8RcO69u/fz5gxYwDo2LEjy5YtAy4VeH788UdeeOEF4NLCFCdOnCAwMJCgoCBCQ0MBCAsL4+TJk5fljI6OJjo6+mY2hYiIuAhXWEiiiCZZllK99957pKenExsbS1RUFG3btmXu3LlcvHgRgEGDBtG4ceNix8TFxTFw4EDHg8/EiRMZPHiw472IiIjIjTCbzTRp0oQmTZoQEhLC2rVriYyMZOfOnbi5udGsWTOSkpKw2WwMGDAAm82Gj48PCQkJJZ7PZDKVuL1379506dKl2Dar1eoYHlaUJS8vr/xuTkRE5CYwOzuAON+jjz5KZGQkCQkJ9OzZk4CAAF5++WVmzJjByJEjWbRo0WXHdO7cmbVr1wKXlj7Pz89XcUdERETKRUZGBsePH3e8T0tLo2bNmkRGRvK///u/NGrUCH9/f7KyssjIyOD222/H29uboKAgvv32WwDsdrtjSFfjxo3ZtGkTABs3bnSct3nz5nzzzTfk5uYCcPr0ac6dO1dBdykiIlK+1INHLlNYWMiCBQtIS0vDbDYXe8Aqcvfdd/PRRx/x+OOP880339CpU6cSz6Wx6SLiLEYYJ/1nFovFkLmLGD2/uI7c3FwWLlxIdnY2bm5u1K5dmyFDhuDl5cW5c+eIjIwEICQkBH9/f0fvnOeff5558+axcuVKCgoK6NChA6GhoQwcOJA5c+bwySefFJtkuXnz5vz666+89NJLwKWhYcOHD8ds1negIiJiPCa73W53dghxjqJJllNTU1m1ahUvvvgiAMnJyeTm5vL4449jt9t57LHH+OCDDy6bZHnevHnceeed/L//9/+Ij4/H19f3qtc81qP1Tb0nEZEiRpyDJzAw0KXGd18rV8lf2rh0kZtNzzkiIpWXKz1blvaso68nhCpVqnDhwgXH+5ycHKpVq4bZbGb9+vXYbLYSj3vggQdYtGgRDRo0KFNxR0RERERERERuDg3REkJCQjCbzY5Jlrt160ZiYiLr16+nefPmeHp6lnhcWFgYVapUoXPnzmW+litVPa+Fq3wrfT2U3XmMnF/ZRUSunVGfcyqafk6Xndqq7NRWZae2KhsjtpMKPLewpUuXApfmTIiLiyv22euvv+54/fjjjwMQFBTkGJ4FlyYitNvtNGvWrALSioiIiIiIiEhpVOCR67Ju3To++OADnnjiCU1EKCIiIiIiIuJkKvDIdYmKiiIqKsrZMUREREREREQETbIsIiIiIiIiImJ46sFzi1i5ciUbN27EbDZjMpkYMmQIDRs2vKZzbNu2jfT0dHr37n1zQoqIiIiIiIjIdVGB5xZw4MABtm/fzowZM3B3dyczM5OCgoJrPk/r1q1p3br1DWUpfKbXDR3vLL85O8ANUHbncWZ+reQiIiIiInJrUYHnFnDmzBn8/Pxwd3cHwN/fH4CYmBjuvvtufvjhBzw8PBgxYgS1a9dm27ZtrFy5koKCAvz8/Bg+fDhVq1Zl7dq1HD58mMGDB5OUlESVKlX4+eefOXv2LI8//jjt27d35m2KiIiIiIiI3LI0B88toHnz5vz++++MGDGC+fPns3fvXsdn3t7eJCYm8pe//IXFixcDEBERwbRp05g5cyb33HMPn35ack+As2fP8uqrr/Liiy+ybNmyirgVERERERERESmBevDcAry8vJgxYwb79u0jNTWV2bNn89hjjwHQoUMHx3+XLFkCwOnTp3njjTc4c+YMBQUFBAUFlXjeNm3aYDabqVu3LufOnStxn5SUFFJSUgCIj48v71sTkVIEBgbe0PEWi+WGz+Esyu48Rs8vIiIiYmQq8NwizGYzTZo0oUmTJoSEhLB27VoATCaTY5+i1wsXLqRnz560bt2a1NRUVqxYUeI5i4Z8Adjt9hL3iY6OJjo6upzuQkTK6tSpUzd0fGBg4A2fw1mU3XlcJX9wcLCzI4iIiIhUOA3RugVkZGRw/Phxx/u0tDRq1qwJwObNmx3/LVpVKycnh+rVqwOwbt26Ck4rIiIiIiIiItdKPXhuAbm5uSxcuJDs7Gzc3NyoXbs2Q4YMYceOHWRlZTF27Fjc3d0ZMWIEAI888gizZs3Cx8eHpk2bYrVayy2LUVf2cZVvpa+HsjuP0fOLiMi1MepqoRXN6KtkViS1VdmprcrO2W1l1H8TGoEKPLeAsLAwpk6dWuJnvXr14vHHHy+2rU2bNrRp0+ayfTt16kSnTp2ASytw/dHSpUvLJ6yIiIiIiIiIXDMN0RIRERERERERMTj14LmFJSUlOTuCiIiIiIiIiJQDFXhERERExCn69etHSEgIhYWFuLm50bFjR3r06IHZ7BqdzAcMGKBh6CIiYhgq8FQiRQ9JNpuNOnXqEBMTg6enZ4n7rl27lsOHDzN48OAbvm5ycjJeXl706qWJBUVERKTsPDw8SEhIAODcuXO8+eabXLhwgb59+zo1l91ux263OzWDiIjItVKBpxL540PSm2++yZdffknPnj2dnKo4o64u4eyZ5m+Est88WgFARKT8BAQEMGTIEMaPH88jjzyC3W5n2bJl7N27l/z8fLp160aXLl1ITU1lxYoV+Pn5cezYMcLCwhg+fDgmk4mYmBg6dOjADz/8gJubG0OGDOH999/nxIkT/PWvf6Vr167k5uYyc+ZMsrOzKSgooH///rRp0war1cq0adNo2LAhP//8M+PHj3dky8zMZMaMGTz88MO0bNnSia0kIiJSOhV4KqmIiAiOHj1KVlYWb7/9NlarFU9PT4YMGUK9evWK7btt2zZWrlxJQUEBfn5+DB8+nKpVq5KcnMypU6ewWq2cOnWK7t270717dwBWrlzJunXr8Pf3p0aNGoSFhTnjNkVERKQSqVWrFjabjXPnzrFt2za8vb2ZPn06+fn5TJw4kebNmwNw5MgRZs2aRbVq1Zg4cSL79+8nIiICgMDAQBISEli8eDFvv/02U6ZMIT8/nzFjxtC1a1fc3d0ZO3Ys3t7eZGZm8tJLL9G6dWsATpw4QUxMDI0aNXJkOnv2LDNnzqR///40a9asWN6UlBRSUlIAiI+Pr4gmEhExvMDAQGdHKBOLxWKYrEVU4KmECgsL2blzJy1atCA5OZn69evzwgsvsGfPHubOnevo5VMkIiKCadOmYTKZ+Oqrr/j000954oknAMjIyCAuLo4LFy4wcuRIunbtytGjR9m0aRMzZ86ksLCQcePGqcAjIiIi5WrXrl0cPXqULVu2AJCTk8Px48exWCyEh4dTo0YNAEJDQ7FarY4CT1GxJiQkhNzcXKpUqUKVKlWwWCxkZ2fj6enJ+++/z759+zCZTJw+fZpz584Bl/7R8cfiTmFhIVOmTGHw4MHccccdl2WMjo4mOjr6praDiEhlc+rUKWdHKJPAwECXzRocHFzidhV4KpG8vDxiY2MBiIyM5P7772fChAmMGTMGgKZNm5KVlUVOTk6x406fPs0bb7zBmTNnKCgoICgoyPFZy5YtcXd3x93dnYCAAM6dO8e+ffto27atY36fogepkuibLanMrlbRN2LVv4iyO4eRs4Px84vz/fbbb5jNZgICArDb7QwcOJAWLVoU2yc1NRV3d3fHe7PZjM1mc7y3WCyO7X/er7CwkI0bN5KZmUl8fDwWi4WYmBjy8vIA8PLyKnYtNzc36tevz86dO0ss8IiIiLgSFXgqkT/OwXMtFi5cSM+ePWndurVjXHuRoock+L8Ho2uhb7akMrtaRd+Vq/5Xo+zOYeTs4Dr5S/tWS1xbZmYm8+bN4y9/+Qsmk4kWLVqwZs0amjZtisViISMjg+rVq9/wdXJycggICMBisbBnzx5Onjx5xf2HDRvGrFmz+Pjjj+ndu/cNX19ERORmcY01KOWmiYiIYMOGDcClb7z8/Pzw9vYutk9OTo7jgWndunVXPWdkZCTff/89eXl5XLhwge3bt5d/cBEREan0inofjx49milTptCsWTP69OkDwP3330/dunUZN24cY8aMYd68ecV66lyve++9l8OHDzNmzBjWr19PnTp1rri/2WxmxIgRpKam8sUXX9zw9UVERG4Wk11rQFYaAwYMYOnSpcW2lTbJ8h+XSf/+++9ZsmQJPj4+NG3alMOHDzNp0qTLlj8fM2YM48aNIygoqNgky4GBgdSvX79My6RnZGTclHu/2VzlW+nroezOY+T8yu4cRs4OrpNfPXjEWY71KH3YuoiIXGKUlWhd5bmmJKU966jAIxVKBZ6Kp+zOY+T8yu4cRs4OrpNfBR5xFqM+51Q0V/lZYQRqq7JTW5Wd2qpsXLmdSnvW0RAtERERERERERGDU4FHRERERERERMTgVOARERERERERETE4LZNuAP369SMkJASbzUbNmjUZPnw4Pj4+FZ5jzZo1eHp6EhUVVeHXFhEREREREZHSqcBjAB4eHiQkJAAwd+5cvvjiC/7+979XeI6uXbve8DkKn7n6Sluu6DdnB7gORpmdXkRERERERG6cCjwG06hRI44ePQpAWloa8+bN4+LFi9SqVYt//vOf+Pr6MmnSJEJDQ/npp5+4ePEiMTExfPzxxxw9epR77rmH/v37AzBz5kx+//138vPz6d69O9HR0cCl5da7d+/Ojh078PDwIDY2lqpVqxZbNj0lJYWvvvqKgoICatWqxfDhw/H09HRau4iIiIiIiIjcyjQHj4HYbDb27NlD69atgUu9eR577DFef/11QkJC+PDDDx37WiwW4uPj6dKlCwkJCQwePJjExETWrl3L+fPnARg2bBgzZswgPj6ezz//3LH94sWLNGzYkISEBCIjI/nqq68uy9KuXTumT59OQkICdevW5euvv66AFhARERERERGRkqgHjwHk5eURGxvL6dOnqVu3Ls2aNSMnJ4fs7GzuuOMOAKKiopg9e7bjmKIiUEhICHXr1qVatWoA1KpVi99//x0/Pz/++9//8v333wNw6tQpjh8/jp+fHxaLhVatWgEQFhbGjz/+eFmmY8eO8cEHH5CdnU1ubi7NmzcvMXtKSgopKSkAxMfHl1OLSFkEBgYCl4p9Ra+NxsjZwdj5ld05jJwdjJ9fRERExMhU4DGAojl4Ll68yLRp01i9ejWdOnW64jHu7u4AmEwmx+ui94WFhaSmprJ7926mTp2Kp6cnkyZNIj8/HwA3NzdMJhMAZrOZwsLCy86flJREbGwsoaGhrF27ltTU1BJzREdHO4Z+ScU6deoUcKnQU/TaaIycHYydX9mdw8jZwXXyBwcHOzuCiIiISIXTEC0D8fT0ZODAgXz22Wd4enri6+vLvn37AFi/fj2RkZFlPldOTg4+Pj54enry66+/cvDgwWvKkpubS7Vq1SgoKGDDhg3XdKyIiIiIiIiIlC/14DGY+vXrExISwqZNm4iJiXFMshwUFMSwYcPKfJ4WLVrw5ZdfMmrUKG677TYaNmx4TTn69evHhAkT8Pf3p2HDhly4cKFMxxl1ZSdX+VZaREREREREpCQmu91ud3YIuXVkZGQ4O8J1MXKBR9mdx8j5ld05jJwdXCe/hmiJsxj1OaeiucrPCiNQW5Wd2qrs1FZl48rtVNqzjnrwiIiIiIiUg8Jnejk7giH85uwABqK2KjtXayujjlwQY9McPCIiIiIiIiIiBqcCj4iIiIiIiIiIwanAIyIiIiIiIiJicFedg2fAgAEsXboUgB07drBkyRJefvllfvjhBzw9PYmKirrhEGvXruXw4cMMHjz4hs9VFvv27WPevHm4ubkxbdo0PDw8AMjOzmbjxo1069YNgNTUVFatWsWLL754XddJTk7m008/JSkpiYCAAKB4e5Zm5cqV/P3vfwfAarUyY8YMEhMTrysDlG/7Jicn4+XlRa9e1zfG3Khj011lTK/G8oqIyK1q69atvP7668yePZs6depc1/HBwcHUrVu3xM/XrFlTbs+2IiIizlDmHjy7d+9m0aJFjB8/npo1a9K1a1fD/gLcsGEDvXv3JiEhwVHcgUsFnjVr1pTrtfz8/Fi1atU1HfOf//yn3K5fWFhYbucSERERcZZNmzYRERHBpk2bruv477//nvT09BI/KywsNPSzrYiICJRxFa29e/fyzjvvMH78eGrXrg0U78kxadIkwsPDSU1NJScnh6FDhxIZGcnFixdJSkri2LFjBAcHc+bMGQYPHkyDBg345ptv+Pjjj/H29qZevXq4u7sDl3qs/Otf/+L8+fP4+/szbNgwAgMDSUpKwsPDg7S0NM6dO8c///lP1q1bx8GDBwkPDycmJuay3Lt372bp0qUUFhbSoEEDnnnmGdavX8+3337Lrl272LlzJ88//7xj//fee48TJ04QGxtLs2bNaNmyJbm5uSQmJnLs2DHCwsIYPnw4JpOJn3/+mSVLlpCbm+vIWa1atcsydO7cmXXr1tG7d298fX2LfbZ+/Xo+//xzCgoKaNiwIU8//TTvv/8+eXl5xMbGcvvtt9O/f39sNhv//ve/OXDgANWrV+eFF17Aw8ODEydOsGDBAjIzM/H09OTZZ5+lTp06JCUl4e7uTlpaGo0bN6ZevXqOa27bto2VK1dSUFCAn58fw4cPp2rVqiQnJ3Pq1CmsViunTp2ie/fudO/eHbjUo2jdunX4+/tTo0YNwsLCAPjvf//Ll19+iZubG3Xr1mXkyJFl+eMkIiIick1yc3P56aefiIuLY8aMGfTt2/eyntYLFiygQYMGdOrUiWXLlrFt2zbc3Nxo1qwZ7dq1Y9u2bezdu5ePPvqIMWPG8O9//5vQ0FB++uknOnTowIULFxzPtikpKXz11VcUFBRQq1Ythg8fjqenp5NbQURE5MquWuApKCggISGBSZMmXbE7rM1mY/r06ezYsYMPP/yQiRMn8sUXX+Dr68vs2bM5evQoL7zwAgBnzpwhOTmZGTNm4O3tzeTJkwkNDQVg4cKFREVF0alTJ77++msWLlzoOC47O5upU6eybds2Zs6cyZQpU6hbty7jx48nLS3NcQ6AvLw83n77bSZOnEhwcDBz585lzZo19OjRg59++olWrVrRvn37Yvfw6KOPcuzYMRISEoBLQ7SOHDnCrFmzqFatGhMnTmT//v2Eh4c7cvn7+7N582bef/99hg0bdlm7eHl50blzZ/773//St29fx/b09HQ2b97MlClTsFgszJ8/nw0bNvDYY4+xevVqRwar1crx48cZMWIEQ4cOZdasWWzZsoWOHTvy7rvv8swzz3Dbbbdx8OBB5s+fT1xcHACnT59m6tSpmM1m1q5d67huREQE06ZNw2Qy8dVXX/Hpp5/yxBNPAJCRkUFcXBwXLlxg5MiRdO3alaNHj7Jp0yZmzpxJYWEh48aNcxR4PvnkE+bOnYu7uzvZ2dkl/rlISUkhJSUFgPj4+FL//EjZBAYGXvMxFovluo5zBUbODsbOr+zOYeTsYPz84rq+//57WrRoQXBwMH5+fvz888+l7nv+/Hm2bt3KG2+8gclkIjs7Gx8fH1q3bn3Z819BQYHj+SQ5OdmxvV27dkRHRwPwwQcf8PXXX/Pggw9edi0954hIaVz596F+X5eNEdvpqgUeNzc3GjduzNdff83AgQNL3a9t27YAhIWFYbVaAfjpp58cvUBCQkIcPUkOHjxIkyZN8Pf3B+Duu+/m+PHjjs/Gjh0LQMeOHVm2bJnjGq1atcJkMhESEkJAQAAhISEA3H777Vit1mIFnoyMDIKCgggODgYgKiqKL774gh49epShWf5PeHg4NWrUACA0NBSr1Yq3tzfHjh1jypQpwKXiVkm9d4o8+OCDvPDCC/z1r391bNuzZw9Hjhxh/PjxwKWCVFF7/FlQUJDj3sLCwjh58iS5ubns37+fWbNmOfYrKChwvG7fvj1m8+Uj8E6fPs0bb7zBmTNnKCgoICgoyPFZy5YtcXd3x93dnYCAAM6dO8e+ffto27at41ur1q1bO/YPCQnhzTffpE2bNo7///8sOjra8YAkN+7UqVPXfExgYOB1HecKjJwdjJ1f2Z3DyNnBdfIX/e6XymPTpk2OZ8p77rmHjRs30qpVqxL39fb2xsPDg3/961+0atWq1P2KzlWSY8eO8cEHH5CdnU1ubi7NmzcvcT8954hIaVzh92FpXOX3tatz5XYq7VnnqgUek8nEqFGjePXVV4tN/vtnRUOszGYzNpvtBqKWrugaJpPJ8bro/c2+JhS/t7p16zJt2rQyncPHx4cOHTrwxRdfOLbZ7XaioqJ49NFHrzlDXl4eNpsNHx8fR0+fP/Py8ipx+8KFC+nZsyetW7cmNTWVFStWOD6zWP7vj4PZbL7q/D3jx49n7969bN++nf/85z+8/vrruLm5XfV+RERERMoqKyuLPXv2cPTo0WLPfG3atMFutzv2y8/PBy59Ofnaa6+xe/dutmzZwurVqx09nP+stGFXSUlJxMbGEhoaytq1a0lNTS3nuxIRESl/ZZqDx9PTk/Hjx/PKK69QtWpV7r///jKdPCIigm+//ZamTZuSnp7O0aNHAWjYsCGLFy/m/PnzVKlShS1btjh69zRq1IjNmzfTsWNHNm7cSERExHXdWHBwMFarlRMnTlC7dm3Wr1/PHXfcccVjqlSpwoULF8p07szMTA4cOECjRo0oKCjg+PHj3H777aUe07NnT8aPH+94KLnzzjuZOXMmPXr0ICAggKysLC5cuEDNmjWxWCwUFBQUK7j8mbe3N0FBQXz77bfcfffd2O12fvnll2K9mEqSk5ND9erVAVi3bt1V7zUyMpK3336bv/3tbxQWFrJ9+3aio6Ox2WycOnWKpk2bEhERwebNm8nNzcXHx+eK5zPqKlCuXL0VERGpzIqGpg8ZMsSxLS4uDrvdTnp6Ovn5+eTl5bF7924iIiLIzc3l4sWLtGzZkoiICJ577jmg7M95cGnOn2rVqlFQUMCGDRscz04iIiKurEwFHgBfX18mTJhAXFxcqUOJ/qxr164kJSUxatQo6tSpQ926dfH29qZatWo88sgjvPzyy3h7excrSgwaNIi3336bTz/91DF58fXw8PBg2LBhzJo1yzHJcpcuXa54jJ+fH40bN2bMmDG0aNGCli1blrifxWJhzJgxLFq0iJycHAoLC+nevfsVCzz+/v60bduW//3f/wUu9QDq378/U6dOxW634+bmxuDBg6lZsyYPPPAAsbGx1K9fn/79+5d6zueff5558+Y5Jk3u0KHDVQs8jzzyCLNmzcLHx4emTZs6htOVJiwsjHvuuYfY2Fj8/f1p0KABcGlY2ltvvUVOTg5waRja1Yo7IiIiItdq06ZNPPTQQ8W2tWvXjk2bNnH33XczZswYgoKCqF+/PgAXLlxg5syZ5OfnY7fbHXMN3nPPPbzzzjt8/vnnjB49+orX7NevHxMmTMDf35+GDRuWuTAkIiLiTCb7H/u2ljObzUZBQYFjxacpU6YwZ86cK/ZMkcotIyPD2RGui5F78Ci78xg5v7I7h5Gzg+vk1xw84izHerS++k4icktw5ZELrvL72tW5cjtd9xw8N+LixYtMnjyZwsJC7HY7Tz/9tIo7IiIiIlIpufI/6FyJK/+jydWorcpObSVykws8VapU0ZKRIiIiIiIiIiI32eXraIuIiIiIiIiIiKFovJTB9OvXj5CQEODSUuaDBg2icePGVzxmwIABLF269Ir7/Pvf/6Znz57UrVu33LKWpPCZXjf1/DfLb1f4TN2xRURERERExNlU4DEYDw8PEhISANi5cyfvvfcekydPvuHzDh069IbPISIiIiIiIiLOoQKPgV24cKHY0uSffvop3377Lfn5+bRt25a+ffsW299ms7Fw4UL27NlDjRo1sFgsdO7cmfbt2zNp0iQGDBhAgwYNivX42bJlC9u3bycmJoakpCQ8PDxIS0vj3Llz/POf/2TdunUcPHiQ8PBwYmJiKvT+RUREREREROQSFXgMJi8vj9jYWPLz8zlz5gxxcXEA7Nq1i+PHj/Paa69ht9uZOXMme/fu5Y477nAcu3XrVk6ePMmsWbPIzMxk1KhRdO7c+Zqun52dzdSpU9m2bRszZ85kypQp1K1bl/Hjx5OWlkZoaGix/VNSUkhJSQGotBNuBwYGOjvCFVksFpfPWBojZwdj51d25zBydjB+fhEREREjU4HHYP44ROvAgQPMnTuXxMREdu3axY8//sgLL7wAQG5uLidOnChW4Pnpp59o3749ZrOZqlWr0qRJk2u+fqtWrTCZTISEhBAQEOCYD+j222/HarVeVuCJjo4mOjr6Ou/WGFx9OUYjLxlp5Oxg7PzK7hxGzg6ukz84ONjZEUREREQqnAo8BtaoUSPOnz9PZmYmAL1796ZLly43fF6TyeR4nZeXV+wzd3d3xz5Fr4ve22y2G762iIiIiIiIiFw7FXgM7Ndff8Vms+Hn50fz5s1Zvnw59913H15eXpw+fRo3NzcCAgIc+zdu3Jh169YRFRVFZmYmqamp3HvvvZedNyAggPT0dIKDg9m6dStVqlQpt8xGXXHKVb6VFhERERERESmJCjwGUzQHT5GYmBjMZjPNmzfn119/5aWXXgLAy8uL4cOHFyvwtGvXjt27dzN69Ghq1KhBWFgY3t7el13jscceY8aMGfj7+xMWFkZubu7NvzERERERERERuW4mu91ud3YIqTi5ubl4eXlx/vx5JkyYwJQpU6hatWqFXT8jI6PCrlWejNyDR9mdx8j5ld05jJwdXCe/5uARZzHqc05Fc5WfFUagtio7tVXZqa3KxpXbqbRnHfXgucXEx8eTnZ1NQUEBDz/8cIUWd0RERERERETk5lCB5xYzadIkZ0cQERERqZQKn+nl7AiG8JuzAxiI2qrsXKWtjDrnqFQOZmcHEBERERERERGRG6MePJXE2bNnWbJkCQcPHsTHxweLxcJDDz1E27ZtnR2tGKN+s/XnbwRUmRcRERERERFXogJPJWC320lISCAqKooRI0YAcPLkSbZt21Zsv8LCQtzc3JwRUUREROS69OvXj5CQEMf72NhY3nzzTaZOnXrF4yZNmsSAAQNo0KDBDWeIiYlh+vTp+Pv73/C5REREbhYVeCqBPXv2YLFY6Nq1q2NbzZo1efDBB1m7di3fffcdubm52Gw2xo8fz8KFCzl27BiFhYU88sgjtGnTBpvNxrJly9i7dy/5+fl069aNLl26APDxxx+zYcMGzGYzLVq04LHHHuPEiRMsWLCAzMxMPD09efbZZ6lTp46zmkBEREQqKQ8PDxISEoptu1pxR0RE5FakAk8lcOzYMerXr1/q50eOHOH111/H19eX9957j6ZNmzJs2DCys7OZMGECd955Jxs3bsTb25vp06eTn5/PxIkTad68Ob/++ivbtm3jtddew9PTk6ysLADeffddnnnmGW677TYOHjzI/PnziYuLu+zaKSkppKSkAJdW8KosAgMDnR2hzCwWi6Hy/pGRs4Ox8yu7cxg5Oxg/vxjHgAEDWLp0KampqaxYsQI/Pz+OHTtGWFgYw4cPx2QyFdt/3rx5HD58mLy8PNq3b0/fvn2BSz1zoqKi2L59OwUFBYwePZo6depw/vx55syZw+nTp2nUqBF2u90ZtykiInJNVOCphObPn8/+/fuxWCx069aNZs2a4evrC8CPP/7I9u3bWbVqFQB5eXmcOnWKXbt2cfToUbZs2QJATk4Ox48fZ/fu3XTq1AlPT08AfH19yc3NZf/+/cyaNctxzYKCghKzREdHEx0dfTNv1ylOnTrl7AhlFhgYaKi8f2Tk7GDs/MruHEbODq6TPzg42NkRpBzl5eURGxsLQFBQkON1kSNHjjBr1iyqVavGxIkT2b9/PxEREcX2+cc//oGvry82m41XX32VX375hXr16gHg5+fHjBkz+OKLL1i1ahVDhw5lxYoVRERE0KdPH3bs2MHXX39dMTcrIiJyA1TgqQRuv/12vvvuO8f7p59+mszMTMaPHw/gKM7Apfl6xowZc9nDr91uZ+DAgbRo0aLY9l27dl12PZvNho+Pz2XdpUVERETKW0lDtP4oPDycGjVqABAaGorVar2swLN582a++uorCgsLOXPmDOnp6Y4CT7t27QAICwtj69atAOzbt4+xY8cC0LJlS3x8fEq8dmXtqSwi188IPVnV47ZsjNhOKvBUAk2bNuX9999nzZo1jnl48vLySty3efPmfP755wwaNAiTycSRI0eoX78+LVq0YM2aNTRt2hSLxUJGRgbVq1enWbNmfPjhh9x3332OIVq+vr4EBQXx7bffcvfdd2O32/nll18IDQ29alajrj7lKt9Ki4iISHHu7u6O12azGZvNVuxzq9XKqlWrmD59Or6+viQlJZGfn+/43GKxOI4tLCy8pmtX1p7KInL9jPBvBv3bpmxcuZ1K662sAk8lYDKZiI2NZcmSJXzyySf4+/vj5eXFY489dlmhp0+fPixevJixY8dit9sJCgrixRdf5P7778dqtTJu3DgA/P39iY2NpUWLFqSlpfHiiy9isVi46667ePTRR3n++eeZN28eK1eupKCggA4dOpSpwCMiIiJSkXJycvDy8sLb25uzZ8+yc+dOmjRpcsVjIiMj2bhxIw8//DA//PAD2dnZFZRWRETk+qnAU0lUq1aNkSNHlvhZp06dHK89PDwYMmTIZfuYzWYeffRRHn300cs+6927N7179y62LSgoiJdeeulGIouIiIjcdKGhoYSGhjJq1Chq1KhB48aNr3rMI488wpw5cxg9ejSNGjUyXBd9ERG5NZnsWhZAKlBGRoazI1wXV+6edzXK7jxGzq/szmHk7OA6+TXJsjjLsR6tnR1BRJzMCFNSuMrva1fnyu1U2rOOuYJziIiIiIiIiIhIOdMQLRERERGRcmCEb+5dgSt/K+5q1FZlp7YSUYGnTM6ePcvixYs5fPgw3t7eVK1alSeffLJcuoAnJyfj5eVFr169rrhfTEwMXl5emEwmfHx8eO6556hZs+YNX//P15g+fTr+/v6lZly+fDmRkZE0a9bsuq5R+MyV79NV/faH13p4ExEREREREVejAs9V2O12EhISiIqKckxinJaWxrlz5yp8jH9cXBz+/v4kJyfz0UcfMXTo0Aq9PkC/fv0q/JoiIiIiIiIicmUq8FxFamoqFouFrl27OrYVLQe+fPlytm3bBkBmZibNmzdn2LBhrF+/ns8//5yCggIaNmzI008/jdlsZufOnbz//vvYbDb8/Px45ZVXAEhPT2fSpEmcOnWK7t2707179ytmatSoEZ9//rnjuu+++y6///47AE8++SQREREkJyfz22+/ceLECc6fP0+vXr2Ijo4mNTWVVatW8eKLLwKwYMECGjRo4Fhp69NPP+WHH37Aw8ODESNGULt27WLXTkpKolWrVrRv355Dhw6xePFiLl68iMVi4ZVXXqFKlSo31uAiIiIiIiIics1U4LmKo0ePUr9+/RI/69evH/369SM7O5tXXnmFv/zlL6Snp7N582amTJmCxWJh/vz5bNiwgbvuuot33nmHyZMnExQURFZWluM8GRkZxMXFceHCBUaOHEnXrl2xWEr/v2bnzp20adMGgEWLFtGzZ08iIiI4deoU06ZNY/bs2Y7s06ZNIzc3l3HjxtGyZcur3q+3tzeJiYmsW7eOxYsXOwpBf1ZQUMAbb7zByJEjCQ8PJycnBw8Pj8v2S0lJISUlBYD4+PirXt8IjLZUqsViMVzmIkbODsbOr+zOYeTsYPz8IiIiIkamAs8NstvtvPXWW/Ts2ZOwsDBWr17NkSNHGD9+PAB5eXn4+/tz4MABIiMjCQoKAsDX19dxjpYtW+Lu7o67uzsBAQGcO3eOGjVqXHatyZMnk5WVhZeXl2Oo1O7du0lPT3fsk5OTQ25uLgCtW7fGw8MDDw8PmjRpwqFDh/Dx8bni/XTo0MHx3yVLlpS6X0ZGBtWqVSM8PBy4VBgqSXR0NNHR0Ve8ptEYbfI2I084Z+TsYOz8yu4cRs4OrpNfy6SLiIjIrUgFnqu4/fbb+e6770r9fMWKFVSvXp3OnTsDlwo+UVFRPProo8X2KxrKVZI/9tYxm80UFhaWuF9cXBw+Pj68+eabJCcn8+STT2K325k2bVqJvWdMJtNl793c3LDb7Y5t+fn5pR7z5+NFRERERERExDWpwHMVTZs25f333yclJcXRE+WXX34hJyeH7Oxsdu/eTVxcnGP/O++8k5kzZ9KjRw8CAgLIysriwoULNGrUiAULFmC1Wh1DtP7Yi6es3NzceOqppxg7diwPP/wwzZo1Y/Xq1Y5VuNLS0hxzBH3//ff07t2bixcvkpqayqOPPorNZiM9PZ38/Hzy8vLYvXs3ERERjvNv3ryZ3r17s3nzZho2bFhqjuDgYM6cOcOhQ4cIDw/nwoULeHh44ObmduX8Bl2BylW+lRYREREREREpiQo8V2EymRg7diyLFy/mk08+wd3dnZo1a/LUU0+RnJzM6dOnHcOxWrduTb9+/ejfvz9Tp07Fbrfj5ubG4MGDadSoEUOGDOH111/Hbrfj7+/PxIkTrytTtWrV6NChA6tXr2bgwIEsWLCAsWPHUlhYSGRkJEOGDAGgXr16TJ48mfPnz/Pwww9TvXp1AO6++27GjBlDUFDQZfMLZWVlMXbsWNzd3RkxYkSpGSwWCyNHjmTRokXk5eXh4eHBxIkTr1rgEREREREREZHyZ7L/cbyOVBrJycl4eXk5eva4ioyMDGdHuC5G7sGj7M5j5PzK7hxGzg6uk19z8IizGPU5p6K5ys8KI1BblZ3aquzUVmXjyu1U2rOOuYJziIiIiIiIiIhIOdMQrUqqb9++zo4gIiIiIiIiIhVEPXhERERERERERAxOPXgMauXKlWzcuBGz2YzJZGLIkCFXXPXqWgwYMIClS5eWy7n+rPAZ15oTqKx++///a9RVwEREROTmM+pzTkX77eq7yP9PbVV2FdFW+reAuDoVeAzowIEDbN++nRkzZuDu7k5mZiYFBQXOjiUiIiIiIiIiTqICjwGdOXMGPz8/3N3dAfD39+fQoUMsXLiQsWPH8v333/PGG2+wZMkSbDYbo0ePZu7cuZw4cYIFCxaQmZmJp6cnzz77LHXq1MFqtTJnzhxyc3Np06ZNsWt9+umnfPvtt+Tn59O2bVv69u2L1Wpl+vTpNG7cmAMHDlC9enVeeOEFPDw8nNEcIiIiIiIiIrc8FXgMqHnz5nz44YeMGDGCO++8k3vuuYfGjRuTlpYGwL59+wgJCeHQoUPYbDbCw8MBePfdd3nmmWe47bbbOHjwIPPnzycuLo5FixbRtWtXoqKiWL16teM6u3bt4vjx47z22mvY7XZmzpzJ3r17CQwM5Pjx44wYMYKhQ4cya9YstmzZQseOHS/LmpKSQkpKCgDx8fE3v3FussDAQGdHuGYWi8WQucHY2cHY+ZXdOYycHYyfXyre2bNnWbJkCQcPHsTHxweLxcJDDz1E27ZtnR1NRETEcFTgMSAvLy9mzJjBvn37SE1NZfbs2Tz22GPUqlWL9PR0Dh8+TI8ePdi3bx82m43IyEhyc3PZv38/s2bNcpynaFjX/v37GTNmDAAdO3Zk2bJlwKUCz48//sgLL7wAQG5uLidOnCAwMJCgoCBCQ0MBCAsL4+TJkyVmjY6OJjo6+mY1RYU7deqUsyNcs8DAQEPmBmNnB2PnV3bnMHJ2cJ38wcHBzo4gZWC320lISCAqKooRI0YAcPLkSbZt21am4wsLC3Fzc7uZEUVERAxFBR6DMpvNNGnShCZNmhASEsLatWuJjIxk586duLm50axZM5KSkrDZbAwYMACbzYaPjw8JCQklns9kMpW4vXfv3nTp0qXYNqvV6hgeVpQlLy+v/G5OREREKr09e/ZgsVjo2rWrY1vNmjV58MEHsdlsLFu2jL1795Kfn0+3bt3o0qULqampLF++HB8fHzIyMhgyZAjJycn4+Phw9OhR7r77bkJCQvjvf/9LXl4esbGx1K5dm23btrFy5UoKCgrw8/Nj+PDhVK1aleTkZE6dOoXVauXUqVN0796d7t27s3z5cnx9fenRowcA77//PgEBAXTv3t1ZzSUiInJVKvAYUEZGBiaTidtuuw2AtLQ0atasSWRkJHPnziUqKgp/f3+ysrI4e/Yst99+OyaTiaCgIL799lvuvvtu7HY7v/zyC6GhoTRu3JhNmzbRsWNHNm7c6LhO8+bNWb58Offddx9eXl6cPn36hr8pM+rM867yrbSIiEhlcezYMerXr1/iZ19//TXe3t5Mnz6d/Px8Jk6cSPPmzQE4cuQIiYmJBAUFkZqayi+//MLs2bPx9fXlueee44EHHmD69On897//ZfXq1Tz11FNEREQwbdo0TCYTX331FZ9++ilPPPEEcOm5Ki4ujgsXLjBy5Ei6du1K586dSUxMpEePHthsNjZv3sxrr712Wc7KNhRdRK6ssgxD1pDqsjFiO6nAY0C5ubksXLiQ7Oxs3NzcqF27NkOGDMHLy4tz584RGRkJQEhICP7+/o7eOc8//zzz5s1zfIPVoUMHQkNDGThwIHPmzOGTTz4pNsly8+bN+fXXX3nppZeAS0PDhg8fjtlsrvibFhERkUpt/vz57N+/3/FAffToUbZs2QJATk4Ox48fx2KxEB4eTlBQkOO4Bg0aUK1aNQBq165Ns2bNgEvPQXv27AHg9OnTvPHGG5w5c4aCgoJix7ds2RJ3d3fc3d0JCAjg3LlzBAUF4evry5EjRzh37hyhoaH4+fldlrmyDUUXkSurLF/46svrsnHldiptOLoKPAYUFhbG1KlTS/zsvffec7x+9tlni30WFBTkKNb8efu0adMc7/v37+94XdRV+c8SExMdr3v16lX28CIiIiLA7bffznfffed4//TTT5OZmcn48eOpUaMGAwcOpEWLFsWOSU1NxdPTs9i2Pw4bN5lMjvcmkwmbzQbAwoUL6dmzJ61btyY1NZUVK1Y4jrFY/u9x2Gw2U1hYCMADDzzA2rVrOXv2LJ07dy6fmxYREbmJ1BVDRERERCpc06ZNyc/PZ82aNY5tRXP6tWjRgjVr1jgWhMjIyCA3N/e6r5WTk0P16tUBWLduXZmOadu2LTt37uTw4cOXFZpERERckXrwiIiIiEiFM5lMxMbGsmTJEj755BP8/f3x8vLiscceo3379litVsaNGweAv78/sbGx132tRx55hFmzZuHj40PTpk2xWq1XPcZisdCkSRN8fHw0PF1ERAzBZLfb7c4OIbeOjIwMZ0e4Lq48/vJqlN15jJxf2Z3DyNnBdfJrmXQpDzabjXHjxjF69GjHwhZXc6xH65ucSkScyagLxvyZq/y+dnWu3E6ag6cS6NevHyEhIdhsNurUqUNMTMxl49BLk5aWxunTp2nZsmW550pOTsbLy6tMc/EUPmPM+Xp++///W1l+qIuIiEjp0tPTiY+Pp23btmUu7oiIiDibCjwG4uHhQUJCAgBvvvkmX375JT179rzqcYWFhaSlpXH48OGbUuARERERqUzq1q3L3Llzr/k4fRFUNq78rbirUVuVndpKRAUew4qIiODo0aNkZWXx9ttvY7Va8fT0ZMiQIdSrV4/k5GR+++03rFYrNWrUYP/+/eTl5fHTTz/xt7/9jfT09GK9bsaMGcO4ceMICgriww8/ZMOGDfj7+1OjRg3CwsLo1asXKSkpfPXVVxQUFFCrVi2GDx9e5h5EIiIiIiIiInLzqMBjQIWFhezcuZMWLVqQnJxM/fr1eeGFF9izZw9z58519PJJT09nypQpeHh4sHbtWg4fPszgwYOBS8OqSnLo0CG+++47EhISKCwsZNy4cYSFhQHQrl07oqOjAfjggw/4+uuvefDBB6+YNSUlhZSUFADi4+PL5f6dKTAw0NkRrpnFYjFkbjB2djB2fmV3DiNnB+PnFxERETEyFXgMJC8vz7GCRGRkJPfffz8TJkxgzJgxwKXlRrOyssjJyQGgdevWeHh4XNM19u/fT5s2bRzHtWrVyvHZsWPH+OCDD8jOziY3N5fmzZtf9XzR0dGOolBlYMRun0burmrk7GDs/MruHEbODq6TX5Msi4iIyK1IBR4D+eMcPGVxpeFTbm5u/HEBtby8vKueLykpidjYWEJDQ1m7di2pqallziIiIiIiIiIiN48KPAYXERHBhg0b6NOnD6mpqfj5+eHt7X3Zfl5eXly4cMHxvmbNmuzYsQOAn3/+GavVCkDjxo2ZN28evXv3xmazsWPHDh544AEAcnNzqVatGgUFBWzYsIHq1atfc16jTj7oKt9Ki4iIiIiIiJREBR6D69u3L2+//TZjx47F09OTmJiYEvdr2rQpn3zyCbGxsfztb3+jffv2rF+/ntGjRxMeHu7ozh4eHk6rVq2IjY0lICCA22+/3VEw6tevHxMmTMDf35+GDRsWKxiJiIiIiIiIiPOY7H8cpyPCpZ46Xl5eXLx4kbi4OIYMGeKYaPlGZWRklMt5KpqRe/Aou/MYOb+yO4eRs4Pr5NccPOIsRn3OqWiu8rPCCNRWZae2Kju1Vdm4cjuV9qyjHjxymXfeeYf09HTy8/OJiooqt+KOiIiIiIiIiNwcKvDIZUaMGOHsCCIiIiIiIiJyDczODiAiIiIiIiIiIjdGPXgMYsCAASxdutTxfu3atRw+fJjBgwc7MdW1K3yml7MjXDOjrvwlIiIiIiIitw714JFrVlhY6OwIIiIiIiIiIvIH6sFTCSQlJdGqVSvat28P/F9vn9TUVFasWIGfnx/Hjh0jLCyM4cOHYzKZ2LFjB//zP/+Dp6cnjRs3xmq18uKLL3Lo0CEWLVpEfn4+Hh4eDBs2jODgYNauXct3331Hbm4uNpuNmjVr0rZtW9q2bQvAm2++yd13302bNm2c2RQiIiIiTmPEnsrO8JuzAxiI2qrsrrWt1EtfKiMVeAwiLy+P2NhYx/usrCxat2591eOOHDnCrFmzqFatGhMnTmT//v2EhYUxb948Jk+eTFBQEG+88YZj/+DgYF599VXc3Nz48ccfee+99xg7dqzjXK+//jq+vr7s3buXzz77jLZt25KTk8P+/fuJiYm57PopKSmkpKQAEB8ff4Ot4ByBgYFYLBYCAwOdHeW6KLvzGDm/sjuHkbOD8fOLiIiIGJkKPAbh4eFBQkKC433RHDxXEx4eTo0aNQAIDQ3FarXi5eVFUFAQQUFBANx7772OIkxOTg5JSUmcOHECKD4cq1mzZvj6+gJwxx13MH/+fDIzM9myZQvt2rXDzc3tsutHR0cTHR19nXftGk6dOkVgYCCnTp1ydpTrouzOY+T8yu4cRs4OrpM/ODjY2RFEREREKpzm4KkE3NzcsNlsANhsNgoKChyfubu7O16bzWbHfqVZvnw5TZo0ITExkXHjxpGfn+/4zNPTs9i+HTt2ZP369axdu5b777+/PG5FREREbiKr1cqYMWOKbUtOTubTT688VOHw4cMsXLgQgNTUVPbv33/N146JiSEzM/OK23/++WdiYmI4cuQI27Zt4+OPP77m65QkNTXVsD2JRUREyko9eCqBmjVr8vPPP3PPPfewbdu2q06CHBwcjNVqxWq1EhQUxObNmx2f5eTkUL16deBSL6Er6dSpExMmTKBq1arUrVu3TFk11lVERMR4GjRoQIMGDYBLxRIvLy8aN25crtf45ZdfSExMZNSoUdSvX5/69euXaTi6iIiIXKICTyXwwAMPkJCQQGxsLM2bN7+sp82feXh4MHjwYF577TU8PT0dD2wADz30EElJSaxcuZKWLVte8TxVq1alTp06mlhZRESkkpg0aRLh4eGkpqaSk5PD0KFDiYyMJDU1lVWrVjFo0CC+/PJLzGYzGzZsYNCgQdSpU4d3332X33//HYAnn3ySiIgIzp8/z5w5czh9+jSNGjXCbreXet1ff/2VpKQkhg8fTnh4OPB/w9EHDx5MUlISVapU4eeff+bs2bM8/vjjtG/fHpvNxsKFC9mzZw81atTAYrHQuXNn2rdvz86dO1m8eLFjQYkiWVlZvP3221itVjw9PRkyZAj16tUjOTnZ8QXYqVOnePLJJzl48CA//PAD1atXZ9y4cVgsenQWERHXpd9SBrF06dJi7zt16kSnTp2AS4WWadOmOT57/PHHAWjSpAlNmjRxbB88eLDjddOmTXnjjTew2+0sWLCAsLAwABo1asScOXMc+/Xv3/+y6xW5ePEiJ06c4N57773xGxQRERGXYLPZmD59Ojt27ODDDz9k4sSJjs+CgoLo0qULXl5e9Op1acWoOXPm0LNnTyIiIjh16hTTpk1j9uzZrFixgoiICPr06cOOHTv4+uuvS73mzJkzGT58OBEREaXuc/bsWV599VUyMjKYMWMG7du3Z+vWrZw8eZJZs2aRmZnJqFGj6Ny5M3l5ebzzzju88sor1K5dm9mzZzvOk5ycTP369XnhhRfYs2cPc+fOdcxz+NtvvxEXF0d6ejovv/wyY8aM4fHHHychIYEdO3Y4Vg8tUhkWkxC5Vd3KiwJoUYSyMWI7qcBzi0pJSWHdunUUFBRQv359unTpck3H//jjj/z73/+mR48eeHt736SUIiIiUp5MJtNVtxcVMcLCwrBarVc95+7du0lPT3e8z8nJITc3l3379jlW4mzZsiU+Pj6lnuPOO+/k66+/pkWLFpjNJU8R2aZNG8xmM3Xr1uXcuXMA/PTTT7Rv3x6z2UzVqlUdX2xlZGQQFBTEbbfdBlyaN7CoEPPTTz855iFq2rQpWVlZ5OTkAHDXXXdhsVgICQnBZrPRokULAEJCQjh58uRlmSrDYhIitypXWBTAWVxlUQRX58rtVNqCEirw3KJ69uxJz549r/v4Zs2a8fbbb5djIhEREbnZ/Pz8yMrKKrYtKyvLsbIm/N8CDWVZnAHAbrczbdo0PDw8rjvX4MGDmTdvHvPnz2fIkCEl7vPHhSOuNNzrRhQNwTKbzbi5uTkKXyaT6apzHIqIiDibVtESERERuUV4eXlRrVo19uzZA1wq7uzateuKQ6P+rEqVKuTm5jreN2vWjNWrVzvep6WlARAZGcnGjRsB+OGHH8jOzi71nCaTieeff55ff/2V5cuXlzlL48aN+e6777DZbJw9e5bU1FTg/xaUOHHiBIAjB0BERAQbNmwALk0Y7efnp97IIiJSKagHTyWxdetWXn/9dWbPnk2dOnWu6/jg4OBSV8Nas2YNnp6eREVF3VDOwmd63dDxN5tW+RIRkcruueeeY8GCBSxZsgSAPn36ULt27TIf36pVK2bNmsX333/PoEGDGDhwIAsWLGDs2LEUFhYSGRnJkCFDeOSRR5gzZw6jR4+mUaNGV53HwMPDg3HjxhEXF0dAQABeXl5XzdKuXTt2797N6NGjqVGjBmFhYXh7e+Ph4cGzzz5LfHw8np6eREREOIpSffv25e2332bs2LF4enoSExNT5nsXERFxZSb7zerjKhVq9uzZnDlzhqZNm9K3b99rPj4pKYlWrVrRvn37yz4rLCzEzc2tPGJyrIdrL3daWoHHlcdfXo2yO4+R8yu7cxg5O7hO/tLGpUvllJubi5eXF+fPn2fChAlMmTKFqlWrOiWLqz/niMj/uZW/2HWV39euzpXbSXPwVGK5ubn89NNPxMXFMWPGDPr27etYzvTFF18EYMGCBTRo0IBOnTqxbNkytm3bhpubG82aNaNdu3Zs27aNvXv38tFHHzFmzBj+/e9/Exoayk8//USHDh24cOGCY8WMlJQUvvrqKwoKCqhVqxbDhw+/6tLsIiIiIjdDfHw82dnZFBQU8PDDDzutuCMiIuJsKvBUAt9//z0tWrQgODgYPz8/fv7551L3PX/+PFu3buWNN97AZDKRnZ2Nj48PrVu3vqwHT0FBgWPJz+TkZMf2du3aOVaM+OCDD/j666958MEHS7ye0ZYPLa37uBGXyCui7M5j5PzK7hxGzg7Gzy/GNGnSJGdHcLiVewRcC1f+VtzVqK3KTm0logJPpbBp0ya6d+8OwD333MPGjRtp1apVifsWjUv/17/+RatWrUrdr+hcJTl27BgffPAB2dnZ5Obm0rx581LPYbTlQ0v7pWDkXxjK7jxGzq/szmHk7OA6+TVES0RERG5FKvAYXFZWFnv27OHo0aOYTCbHcqZt2rQptoRofn4+AG5ubrz22mvs3r2bLVu2sHr1auLi4ko8d2nDrpKSkoiNjSU0NJS1a9c6VqwQEREREREREedQgcfgtmzZQseOHRkyZIhjW1xcHHa7nfT0dPLz88nLy2P37t2OFSQuXrxIy5YtiYiI4LnnngMuLXl64cKFMl0zNzeXatWqUVBQwIYNG6hevXqZ86rrsoiIiIiIiEj5U4HH4DZt2sRDDz1UbFu7du3YtGkTd999N2PGjCEoKIj69esDcOHCBWbOnEl+fj52u50nnngCuDQc65133uHzzz9n9OjRV7xmv379mDBhAv7+/jRs2LDMhSERERERERERuTm0TLpUqIyMDGdHuC6uMq/E9VB25zFyfmV3DiNnB9fJrzl4xFmM+pxT0VzlZ4URqK3KTm1VdmqrsnHldirtWcdcwTlERERERERERKScqcAjIiIiIiIiImJwKvCIiIiIiIiIiBicJlk2kH79+hESEgKA2Wxm0KBBNG7c+IrHTJo0iQEDBtCgQYMbvv7hw4dZt24dgwYNuu5zFD7T64Zz3Ait4iUiIiIiIiKVkQo8BuLh4UFCQgIAO3fu5L333mPy5MkVcu3CwkIaNGhQLoUiERERERERESlfKvAY1IULF/Dx8QEgNTWVVatW8eKLLwKwYMECGjRoQKdOnYod8/XXX/PJJ5/g7e1NvXr1cHd3Z/DgwWzbto2VK1dSUFCAn58fw4cPp2rVqiQnJ/Pbb79htVqpUaMGXbp0cVzn0KFDLFq0iPz8fDw8PBg2bJhWLRERERERERFxEhV4DCQvL4/Y2Fjy8/M5c+YMcXFxZT729OnTfPTRR8yYMQMvLy9effVV6tWrB0BERATTpk3DZDLx1Vdf8emnn/LEE08AkJ6ezpQpU/Dw8CA1NdVxvuDgYF599VXc3Nz48ccfee+99xg7duxl101JSSElJQWA+Pj4G7n9chEYGHhdx1kslus+1tmU3XmMnF/ZncPI2cH4+UVulLOHohvFb84OYCBqq7K7Wltpqga5FajAYyB/HKJ14MAB5s6dS2JiYpmOPXToEJGRkfj6+gLQvn17jh8/Dlwq/rzxxhucOXOGgoICgoKCHMe1bt0aDw+Py86Xk5NDUlISJ06cAC4N4SpJdHQ00dHRZb/Jm+zUqVPXdVxgYOB1H+tsyu48Rs6v7M5h5OzgOvnVo1RERERuRSrwGFSjRo04f/48mZmZuLm5YbfbHZ/l5+df07kWLlxIz549ad26NampqaxYscLxmaenZ4nHLF++nCZNmhAbG4vVaq2wuYBERERERERE5HIq8BjUr7/+is1mw8/Pj/z8fNLT08nPzycvL4/du3cTERFRbP/w8HCWLFlCVlYWVapU4bvvvnOsyJWTk0P16tUBWLduXZmu/8dj1q5dW+bc6hopIiIiIiIiUv5U4DGQojl4isTExGA2mwkMDOTuu+9mzJgxBAUFUb9+/cuOrV69On/729+YMGECvr6+BAcH4+3tDcAjjzzCrFmz8PHxoWnTplit1qtmeeihh0hKSmLlypW0bNmy/G5SREREbln9+vVzfAFlNpsZNGgQjRs3vuIxAwYMYOnSpVfc59///jc9e/akbt265ZZVRETE1ZjsfxzbI5Vabm4uXl5eFBYWkpCQwP3330/btm0rNENGRkaFXq+8uMq8EtdD2Z3HyPmV3TmMnB1cJ7/m4DGuPxZrdu7cyX/+85+rDgMvS4Gnohzr0drZEUSkFBpJ8H9c5fe1q3PldirtWUc9eG4hycnJ7N69m/z8fJo1a0abNm2cHUlERESkRBcuXMDHx8fx/tNPP+Xbb78lPz+ftm3b0rdv32L722w2Fi5cyJ49e6hRowYWi4XOnTvTvn17Jk2axIABA2jQoEGxgtCWLVvYvn07MTExJCUl4eHhQVpaGufOneOf//wn69at4+DBg4SHhxMTE1Oh9y8iInKtVOC5hRQtfS4iIiLiioqGo+fn53PmzBni4uIA2LVrF8ePH+e1117Dbrczc+ZM9u7dyx133OE4duvWrZw8eZJZs2aRmZnJqFGj6Ny58zVdPzs7m6lTp7Jt2zZmzpzJlClTqFu3LuPHjyctLY3Q0NBi+6ekpJCSkgJAfHz8jd28iNxUgYGBzo7gMiwWi9qjDIzYTirwiIiIiIhL8PDwICEhAYADBw4wd+5cEhMT2bVrFz/++CMvvPACcGnY+YkTJ4oVeH766Sfat2+P2WymatWqNGnS5Jqv36pVK0wmEyEhIQQEBDjmA7r99tuxWq2XFXiio6OJjo6+zrsVkYrkqkNtnMGVhx65ElduJw3RMqCiiQYLCwtxc3OjY8eO9OjRA7PZ7OxowPWNeS98ptdNSlOcxtiKiIgYW6NGjTh//jyZmZkA9O7dmy5dutzweU0mk+N1Xl5esc/c3d0d+xS9Lnpvs9lu+NoiIiI3k2tUCqRERd9izZo1i5dffpmdO3fy4YcfOjsWdrtdDzkiIiJyU/3666/YbDb8/Pxo3rw533zzDbm5uQCcPn2ac+fOFdu/cePGfPfdd9hsNs6ePUtqamqJ5w0ICCA9PR2bzcbWrVtv+n2IiIhUFPXgMYiAgACGDBnC+PHjeeSRR7Db7Sxbtoy9e/eSn59Pt27d6NKlC6mpqaxYsQI/Pz+OHTtGWFgYw4cPx2QyERMTQ4cOHfjhhx9wc3NjyJAhvP/++5w4cYK//vWvdO3aldzcXGbOnEl2djYFBQX079+fNm3aYLVamTZtGg0bNuTnn39m/PjxjmyZmZnMmDGDhx9+WEumi4iIyHUrmoOnSExMDGazmebNm/Prr7/y0ksvAeDl5cXw4cMJCAhw7NuuXTt2797N6NGjqVGjBmFhYXh7e192jccee4wZM2bg7+9PWFiYo2gkIiJidCrwGEitWrWw2WycO3eObdu24e3tzfTp08nPz2fixIk0b94cgCNHjjBr1iyqVavGxIkT2b9/PxEREcClcYQJCQksXryYt99+mylTppCfn8+YMWPo2rUr7u7ujB07Fm9vbzIzM3nppZdo3frSkp8nTpwgJiaGRo0aOTKdPXuWmTNn0r9/f5o1a3ZZZmdNPljek2EZcYKtIsruPEbOr+zOYeTsYPz84nzLly8v9bPu3bvTvXv3y7YXDRc3m8088cQTeHl5cf78eSZMmOCYQ2fSpEmO/du3b0/79u0vO88fV8kKCgoiMTGxxM9ERERclQo8BrVr1y6OHj3Kli1bAMjJyeH48eNYLBbCw8OpUaMGAKGhoVitVkeBp6hYExISQm5uLlWqVKFKlSpYLBays7Px9PTk/fffZ9++fZhMpmJdoAMDA4sVdwoLC5kyZQqDBw8uNsnhHzlr8sHyngzLlSfYuhpldx4j51d25zBydnCd/KVNPCiVX3x8vKMX8sMPP0zVqlUr9PqaA7BsXOVnhRGorcpObSWiAo+h/Pbbb5jNZgICArDb7QwcOJAWLVoU2yc1NbXYpIBms7nYfDkWi8Wx/c/7FRYWsnHjRjIzM4mPj8disRATE+OYgNDLy6vYtdzc3Khfvz47d+4stcAjIiIiUlH+2FNHRETkVqMCj0FkZmYyb948/vKXv2AymWjRogVr1qyhadOmWCwWMjIyqF69+g1fJycnh4CAACwWC3v27OHkyZNX3H/YsGHMmjWLjz/+mN69e1/1/PpmS0RERERERKT8qcDjwoomGixaJv2+++6jZ8+eANx///1YrVbGjRsHgL+/f7FJCa/Xvffey4wZMxgzZgwNGjSgTp06V9zfbDYzYsQIZs6cSZUqVejWrdsNZxARERERERGRa2Oy2+12Z4eQW0dGRoazI1wXI4/pVXbnMXJ+ZXcOI2cH18mvOXjEWYz6nFPRXOVnhRGorcpObVV2aquyceV2Ku1Zx1zBOUREREREREREpJypwCMiIiIiIiIiYnAq8IiIiIiIiIiIGJwmWa4E+vXrR0hIiON9bGwsb775JlOnTr3icZMmTWLAgAE0aNDghjPExMQwffp0/P39r7hf4TO9bvhaV6OVukRERERERORWowJPJeDh4UFCQkKxbVcr7oiIiIiIiIhI5aECTyU1YMAAli5dSmpqKitWrMDPz49jx44RFhbG8OHDMZlMxfafN28ehw8fJi8vj/bt29O3b1/gUs+cqKgotm/fTkFBAaNHj6ZOnTqcP3+eOXPmcPr0aRo1aoQWYxMRERERERFxHhV4KoG8vDxiY2MBCAoKcrwucuTIEWbNmkW1atWYOHEi+/fvJyIiotg+//jHP/D19cVms/Hqq6/yyy+/UK9ePQD8/PyYMWMGX3zxBatWrWLo0KGsWLGCiIgI+vTpw44dO/j6669LzJaSkkJKSgoA8fHx5X3rJQoMDCz3c1oslpty3oqg7M5j5PzK7hxGzg7Gzy8iIiJiZCrwVAIlDdH6o/DwcGrUqAFAaGgoVqv1sgLP5s2b+eqrrygsLOTMmTOkp6c7Cjzt2rUDICwsjK1btwKwb98+xo4dC0DLli3x8fEp8drR0dFER0ff2A1eo1OnTpX7OQMDA2/KeSuCsjuPkfMru3MYOTu4Tv7g4GBnRxARERGpcCrw3ALc3d0dr81mMzabrdjnVquVVatWMX36dHx9fUlKSiI/P9/xucVicRxbWFhYMaFFREREDKYiFpOoDH5zdgADUVuVXVFbacEVuZWpwCPk5OTg5eWFt7c3Z8+eZefOnTRp0uSKx0RGRrJx40YefvhhfvjhB7Kzs8t0Lf3AFRERERERESl/KvAIoaGhhIaGMmrUKGrUqEHjxo2veswjjzzCnDlzGD16NI0aNdKcCyIiIiIiIiJOZLJr+SOpQBkZGc6OcF1cZV6J66HszmPk/MruHEbODq6TX3PwiLMc69Ha2RFEbnkaMXB1rvL72tW5cjuV9qyjHjwiIiIiYgj9+vUjJCTE8T42NpagoCAnJhIREXEdKvCIiIiIiCFcaeVQu92O3W7HbDZXcCoRERHXoAKPiIiIiBiS1Wpl2rRpNGzYkJ9//pnx48fz8ccfc/jwYfLy8mjfvj19+/YFICYmhqioKLZv305BQQGjR4+mTp065ObmsnDhQg4fPozJZKJPnz60b9+eXbt2kZycTEFBAbVq1WLYsGF4eXk5+Y5FRERKpwKPwaxcuZKNGzdiNpsxmUwMGTKEZcuWMWDAABo0aFBu1xkwYABLly4ttu306dMsWrSIMWPGXPd5b/byoRpzKyIiUnnl5eURGxsLQFBQEE8++SQnTpwgJiaGRo0aAfCPf/wDX19fbDYbr776Kr/88gv16tUDwM/PjxkzZvDFF1+watUqhg4dyocffoi3tzeJiYkAZGVlkZmZycqVK5k4cSJeXl58/PHHfPbZZ/Tp06dYnpSUFFJSUgCIj4+vqGYQkSvQ4i9XZ7FY1E5lYMR2UoHHQA4cOMD27duZMWMG7u7uZGZmUlBQUGHXr169+g0Vd0RERERuxJ+HaFmtVgIDAx3FHYDNmzfz1VdfUVhYyJkzZ0hPT3cUeNq1awdAWFgYW7duBWD37t2MHDnScbyvry/bt28nPT2diRMnAlBQUFDsGkWio6OJjo4u9/sUkevnqpPiuhJXnjzYlbhyO2mS5UrgzJkz+Pn54e7uDoC/v/9l+2zcuJH//Oc/ANx11108/vjjrFmzht9++40BAwYAsHbtWg4fPszgwYOZOXMmv//+O/n5+XTv3v2yh5TMzExmzJjBww8/TN26dZkxYwaJiYlYrVbmzp3LxYsXARg0aFCZllcXERERKU9/HDZltVpZtWoV06dPx9fXl6SkJPLz8x2fWyyXHn3NZjOFhYWlntNut3PnnXcWK/yIiIi4OhV4DKR58+Z8+OGHjBgxgjvvvJN77rmHO+64w/H56dOnWbZsGTNmzMDHx4epU6eydetW2rdvz0svveQo8GzevJm///3vAAwbNgxfX1/y8vIYP3487dq1w8/PD4CzZ88yc+ZM+vfvT7NmzbBarY5rBQQE8PLLL+Ph4cHx48eZM2dOiV2TK7rr8s3qQmfE7nlFlN15jJxf2Z3DyNnB+PnF+HJycvDy8sLb25uzZ8+yc+dOmjRpcsVjmjVrxhdffMFTTz0FXBqi1ahRIxYsWMCJEyeoXbs2ubm5nD59utRvTEVERFyBCjwG4uXlxYwZM9i3bx+pqanMnj2bxx57zPH54cOHadKkiaNnz3333ce+ffto27YttWrV4sCBA9x22238+uuvjt42//3vf/n++++BS90Zjx8/jp+fH4WFhUyZMoXBgwcXKyIVKSwsZMGCBaSlpWE2mzl+/HiJmSu66/LN6kLnyt3zrkbZncfI+ZXdOYycHVwnv/4RfusKDQ0lNDSUUaNGUaNGjTL1Ln744YeZP38+Y8aMwWw206dPH9q1a0dMTAxz5sxx9ADq37+//myJiIhLU4HHYMxmM02aNKFJkyaEhISwdu3aMh13zz338O2331KnTh3atm2LyWQiNTWV3bt3M3XqVDw9PZk0aZLjIcbNzY369euzc+fOEgs8n332GQEBASQkJGC324sVmkRERERuhj8vABEUFOSYHLlITExMiccmJSU5Xjdo0IBJkyYBl75Ae+655y7bv2nTpkyfPv0GE4uIiFQcFXgMJCMjA5PJxG233QZAWloaNWvW5NixYwCEh4ezaNEiMjMz8fX1ZdOmTfzlL38BoG3btvznP/8hLS3NUYzJycnBx8cHT09Pfv31Vw4ePFjsesOGDWPWrFl8/PHH9O7du9hnOTk51KhRA7PZzDfffIPNZivTPWiVKxEREams9JxTNq7S288I1FZlp7YSUYHHUHJzc1m4cCHZ2dm4ublRu3ZthgwZwqxZswCoVq0ajz76KJMnTwYuTbLcpk0b4NKKEHXq1CE9PZ3w8HAAWrRowZdffsmoUaO47bbbaNiwYbHrmc1mRowYwcyZM6lSpQp33XWX47Nu3bqRmJjI+vXrad68OZ6enhXRBCIiIiIiIiJSApPdbrc7O4TcOjIyMpwd4boY+RsBZXceI+dXducwcnZwnfyaJ0WcxajPORXNVX5WGIHaquzUVmWntiobV26n0p51zBWcQ0REREREREREypkKPCIiIiIiIiIiBqcCj4iIiIiIiIiIwWmS5UpiwIABly0deiVWq5UZM2ZctrTo9UhNTWXVqlW8+OKLV9238JleN3y9P9OKFSIiIiIiInKrUw+eSqywsNDZEURERERERESkAqgHTyWTmprK8uXL8fHxISMjg9mzZ7Ns2TL27t1Lfn4+3bp1o0uXLsWOsVqtzJ07l4sXLwIwaNAgGjduTGpqKitWrMDPz49jx44RFhbG8OHDMZlM7Ny5k8WLF+Pp6Unjxo2dcasiIiIiIiIi8v9TgacSOnLkCImJiQQFBZGSkoK3tzfTp08nPz+fiRMn0rx582L7BwQE8PLLL+Ph4cHx48eZM2cO8fHxjnPNmjWLatWqMXHiRPbv309YWBjvvPMOr7zyCrVr12b27NmlZklJSSElJQXAcc7yFhgYeFPO+0cWi6VCrnMzKLvzGDm/sjuHkbOD8fOLiIiIGJkKPJVQeHg4QUFBAOzatYujR4+yZcsWAHJycjh+/Di33XabY//CwkIWLFhAWloaZrOZ48ePFztXjRo1AAgNDcVqteLl5UVQUJDjHB07dnQUcf4sOjqa6Ojom3KfRU6dOnVTzw+XikgVcZ2bQdmdx8j5ld05jJwdXCd/cHCwsyOIiIiIVDgVeCohT09Px2u73c7AgQNp0aJFsX2sVqvj9WeffUZAQAAJCQnY7XYee+wxx2fu7u6O12azGZvNdvOCi4iIiIiIiMh1UYGnkmvRogVr1qyhadOmWCwWMjIyqF69erF9cnJyqFGjBmazmW+++eaqRZzg4GCsVisnTpygdu3abNy4scx5tOKViIiIiIiISPlTgaeSu//++7FarYwbNw4Af39/YmNji+3TrVs3EhMTWb9+Pc2bNy/WA6gkHh4ePPvss8THx+Pp6UlERAS5ubk37R5EREREjKDwmV7OjmAIvzk7gIFU5rbSF78i5c9kt9vtzg4ht46MjAxnR7gurjKvxPVQducxcn5ldw4jZwfXya85eMRZjvVo7ewIIoZR3gUeV/kdZARqq7Jx5XYq7VnHXME5RERERERERESknGmIloiIiMgt7uzZsyxevJjDhw/j7e1N1apVefLJJ8ulN1RycjJeXl706nXl4UsxMTF4eXlhMpnw8fHhueeeo2bNmjd8/T9fY/r06fj7+5eacfny5URGRtKsWbNyvbaIiMjNpgKPiIiIyC3MbreTkJBAVFQUI0eOBCAtLY1z585V+HC3uLg4/P39SU5O5qOPPmLo0KEVen2Afv36Vfg1RUREyoMKPJXEzfjmzWq1cuDAAe69914ADh8+zLp16xg0aNB1n7O8Jh/UpGwiIiLlIzU1FYvFQteuXR3bQkNDAVi+fDnbtm0DIDMzk+bNmzNs2DDWr1/P559/TkFBAQ0bNuTpp5/GbDazc+dO3n//fWw2G35+frzyyisApKenM2nSJE6dOkX37t3p3r37FTM1atSIzz//3HHdd999l99//x2AJ598koiICJKTk/ntt984ceIE58+fp1evXkRHR5OamsqqVat48cUXAViwYAENGjSgU6dOAHz66af88MMPeHh4MGLECGrXrl3s2klJSbRq1Yr27dtz6NAhFi9ezMWLF7FYLLzyyitUqVLlxhpcRETkJlGBpxIoyzdvhYWFuLm5XdN5T548ycaNGx0FngYNGtCgQYNyzS4iIiLOdfToUerXr1/iZ/369aNfv35kZ2fzyiuv8Je//IX09HQ2b97MlClTsFgszJ8/nw0bNnDXXXfxzjvvMHnyZIKCgsjKynKcJyMjg7i4OC5cuMDIkSPp2rUrFkvpj6E7d+6kTZs2ACxatIiePXsSERHBqVOnmDZtGrNnz3ZknzZtGrm5uYwbN46WLVte9X69vb1JTExk3bp1LF682FEI+rOCggLeeOMNRo4cSXh4ODk5OXh4eFz1/CIiIs6iAk8lUNo3b6mpqbzyyiv4+PiQkZFBQkIC8+fP5/Dhw7i5ufHEE0/QtGlTrFYrc+fO5eLFiwAMGjSIxo0b895775Genk5sbCxRUVHUr1/f8Y3YoUOHWLRoEfn5+Xh4eDBs2DCtWiIiIlIJ2e123nrrLXr27ElYWBirV6/myJEjjB8/HoC8vDz8/f05cOAAkZGRBAUFAeDr6+s4R8uWLXF3d8fd3Z2AgADOnTtHjRo1LrvW5MmTycrKwsvLyzFUavfu3aSnpzv2ycnJITc3F4DWrVvj4eGBh4cHTZo04dChQ/j4+Fzxfjp06OD475IlS0rdLyMjg2rVqhEeHg5cKgz9WUpKCikpKQDEx8df8boiUlxgYGC5ns9isZT7OSsrtVXZGLGdVOCpBK70zduRI0dITEwkKCiIVatWAZCYmMivv/7K1KlTmTNnDgEBAbz88st4eHhw/Phx5syZQ3x8PI8++mixLs6pqamO8wYHB/Pqq6/i5ubGjz/+yHvvvcfYsWMvu/7NevCp6L9oRvzLXUTZncfI+ZXdOYycHYyf/1Z1++23891335X6+YoVK6hevTqdO3cGLhV8oqKiePTRR4vtVzSUqyR/7K1jNpspLCwscb+4uDh8fHx48803SU5O5sknn8RutzNt2rQSe8+YTKbL3ru5uWG32x3b8vPzSz3mz8dfq+joaKKjo2/oHCK3qvJeftqVl7R2NWqrsnHldiqtc4UKPJVceHi445u0n376iQcffBCAOnXqULNmTY4fP07NmjVZsGABaWlpmM1mjh8/ftXz5uTkkJSUxIkTJwBKfVC7WQ8+Ff0XzZX/cl+NsjuPkfMru3MYOTu4Tn71KL02TZs25f333yclJcXxO/uXX34hJyeH7Oxsdu/eTVxcnGP/O++8k5kzZ9KjRw8CAgLIysriwoULNGrUiAULFmC1Wh1DtP7Yi6es3NzceOqppxg7diwPP/wwzZo1Y/Xq1Y5VuNLS0hxzBH3//ff07t2bixcvkpqayqOPPorNZiM9PZ38/Hzy8vLYvXs3ERERjvNv3ryZ3r17s3nzZho2bFhqjuDgYM6cOcOhQ4cIDw/nwoULeHh4XPOQdxERkYqiAk8lcKVv3jw9Pa96/GeffUZAQAAJCQnY7XYee+yxqx6zfPlymjRpQmxsLFarlcmTJ19zbhEREXE+k8nE2LFjWbx4MZ988gnu7u7UrFmTp556iuTkZE6fPu0YjtW6dWv69etH//79mTp1Kna7HTc3NwYPHkyjRo0YMmQIr7/+Ona7HX9/fyZOnHhdmapVq0aHDh1YvXo1AwcOZMGCBYwdO5bCwkIiIyMZMmQIAPXq1WPy5MmcP3+ehx9+mOrVqwNw9913M2bMGIKCgi7r5ZyVlcXYsWNxd3dnxIgRpWawWCyMHDmSRYsWkZeXh4eHBxMnTlSBR0REXJYKPJVAad+87du3r9h+kZGRbNiwgaZNm5KRkcGpU6cIDg4mJyeHGjVqYDab+eabb7DZbABUqVKFCxculHjNnJwcx0PU2rVry5xVq1+JiIi4nurVqzN69OjLtv+x584f3XPPPdxzzz2Xbb/rrru46667im3r27dvsfeJiYklnjMpKanY+z+u2jlq1KgSjwkJCeG55567bPvjjz/O448/Xuo1/vzZHzPGxMQ4XoeHhzNt2rQSry0iIuJqVOCpBEr75q1o9YkiXbt2Zf78+YwZMwY3NzeGDRuGu7s73bp1IzExkfXr19O8eXNHr5+QkBDMZnOxSZaLPPTQQyQlJbFy5coyrVghIiIiIiIiIjePyf7HWehEbrKMjAxnR7gurjKvxPVQducxcn5ldw4jZwfXya85eMRZjPqcU9Fc5WeFEaityk5tVXZqq7Jx5XYq7VnHXME5RERERERERESknKnAIyIiIiIiIiJicCrwiIiIiIiIiIgYnCZZdlEDBgxg6dKlxbatWbMGT09PoqKiWLt2Lc2aNXOsZPX/sXfn8THe+///HzNZRRJERAQRIYTYag1aVEOPpbqireqm1ZaPapEWrYO2SqooH+nn1N5qFXW0xVHVaGMpai9iXyJIYkSQZpNMZn5/+Jlvc1ChkslknvfbrbcmM9fyfF+umXnnNe/rfQ0ePJiJEyfi6+tbbJn+vP87VfByr9taXnfdEhEREREREbk1FXgcSNeuXW0/x8fHU7NmTVuBp6T3LyIiIiIiIiKlhwo8DmTp0qV4enoSEBDA8ePHmTFjBu7u7kyYMAGANWvWsHPnTsxmM8OGDaN69eq2dXr1ujpyZvjw4bz99tsEBATw0UcfceHCBfLz8+nevTtRUVHA1dFD3bt3Z9euXbi7uxMdHU3FihULbSsuLo5169ZhNpupWrUqQ4YMsd1eXURERERERERKlgo8DigyMpI1a9bQv39/6tSpY3vcx8eHmJgYfvzxR1auXMmrr776l9sZNGgQ3t7e5OXlMWrUKNq0aYOPjw9XrlwhLCyMp556ii+//JJ169bx+OOPF1q3TZs2toLQ4sWL+fnnn+nWrdt1+4iLiyMuLg6ASZMm3XZb/f39b3ud4uDq6lpqstwuZbcfR86v7PbhyNnB8fOLiIiIODIVeMqQNm3aABAaGsq2bdtuufzq1avZvn07AGlpaaSkpODj44OrqystWrSwbWvv3r3XrXv69GkWL15MVlYWubm5NG3a9Ib7iIqKshWC7kRaWtodr3s3+fv7l5ost0vZ7ceR8yu7fThydig9+YOCguwdQURERKTEqcBThri6Xv3nNBqNFBQUAODi4oLVarUtk5eXB0BCQgL79u3jgw8+wMPDg3HjxpGfn29bx2AwXLetP4uNjSU6OpqQkBDi4+NJSEgo1raJiIiIiIiIyM2pwOOgPD09ycnJueVyVapUYdeuXQCcOHECk8kEQHZ2NuXLl8fDw4OzZ89y9OjR29p/bm4ulSpVwmw2s3HjxiJP9qy7YomIiIiIiIjcfSrwlFJ5eXmF5tDp2bNnoec7derE7NmzC02yfCORkZFs2LCBYcOGUbduXduw9WbNmvHTTz/x5ptvUq1aNcLCwm4rX9++fRk9ejS+vr6EhYUVqdgkIiIiIiIiIsXDYP3z9TsixSw5OdneEe5IaZlX4k4ou/04cn5ltw9Hzg6lJ7/m4BF7cdR+TkkrLe8VjkDHquh0rIpOx6poSvNxullfRyN4RERERETugoKXe9k7gkM4Z+8ADsQRj5WmZBCxH6O9A4iIiIiIiIiIyN+jAo+IiIiIiIiIiIPTJVqlVP/+/Vm4cGGhx9auXYuHhwcdO3YkPj6eJk2a2O5eNXjwYCZOnIivr2+xZfrz/u/U7Q5d1hBPERERgRv3jf6KyWQiJiaGKVOm/O19JyQksHLlSkaOHPm3tyUiIlJcVOBxIF27drX9HB8fT82aNYt8e/K7vX8REREReysoKMDFxcXeMUREREoFFXgcyNKlS/H09CQgIIDjx48zY8aMQrdJX7NmDTt37sRsNjNs2DCqV69uW6dXr6sjZ4YPH87bb79NQEAAH330ERcuXCA/P5/u3bsTFRUFXP2GrHv37uzatQt3d3eio6OpWLFioW3FxcWxbt06zGYzVatWZciQIXh4eNjt2IiIiIhzSEhIYMmSJZQvX57k5GSmTZvGV199xYEDB8jPz+fBBx+kS5cuhdYxmUzMnDmTK1euAPDiiy9Sv359EhIS+Oabb/Dx8eH06dOEhoYyZMgQDAYDe/bsYcGCBXh4eFC/fn17NFVEROS2qMDjgCIjI1mzZg39+/enTp06tsd9fHyIiYnhxx9/ZOXKlbz66qt/uZ1Bgwbh7e1NXl4eo0aNok2bNvj4+HDlyhXCwsJ46qmn+PLLL1m3bh2PP/54oXXbtGljKwgtXryYn3/+mW7dul23j7i4OOLi4gCYNGnSbbfV39//ttcpDq6urqUmy+1Sdvtx5PzKbh+OnB0cP784jpMnTzJlyhQCAgKIi4vDy8uLiRMnkp+fz5gxY2jatGmh5StUqMC7776Lu7s7KSkpTJ8+3dYvOXnyJFOnTqVSpUqMGTOGw4cPExoaymeffcY///lPAgMDmTZt2g1z/N1+jkhZZK/PAX0GFZ2OVdE44nFSgacMadOmDQChoaFs27btlsuvXr2a7du3A5CWlkZKSgo+Pj64urrSokUL27b27t173bqnT59m8eLFZGVlkZube11H6pqoqChbIehOpKWl3fG6d5O/v3+pyXK7lN1+HDm/stuHI2eH0pM/KCjI3hGkmNWtW5eAgAAAfv/9d5KSkti6dSsA2dnZpKSkUK1aNdvyBQUFzJ07l8TERIxGIykpKYW2VblyZQBCQkIwmUy2EdPXttGhQwdbIefP/m4/R6QsstfnQGn5DHIEOlZFU5qP0836OirwlCGurlf/OY1GIwUFBQC4uLhgtVpty+Tl5QFXhzfv27ePDz74AA8PD8aNG0d+fr5tHYPBcN22/iw2Npbo6GhCQkKIj48nISGhWNsmIiIics2fLwu3Wq288MILNGvWrNAyJpPJ9vOqVauoUKECkydPxmq10q9fP9tzbm5utp+NRiMWi6X4gouIiBQjFXgclKenJzk5ObdcrkqVKuzatQuAEydO2Do72dnZlC9fHg8PD86ePcvRo0dva/+5ublUqlQJs9nMxo0bizzZs+6KJSIiIndTs2bNWLt2LY0aNcLV1ZXk5OTr+iXZ2dlUrlwZo9HIL7/8cssiTlBQECaTidTUVAIDA9m0aVNxNkFEROSuUIGnlMrLyys0h07Pnj0LPd+pUydmz55daJLlG4mMjGTDhg0MGzaMunXr2oZyNWvWjJ9++ok333yTatWqERYWdlv5+vbty+jRo/H19SUsLKxIxSYRERGRu61z586YTCbefvttAHx9fYmOji60zIMPPsiUKVPYsGEDTZs2veWNIdzd3XnllVeYNGkSHh4ehIeHk5ubW2xtEBERuRsM1j9fvyNSzJKTk+0d4Y6U5usvb0XZ7ceR8yu7fThydig9+TUHj9jL6R4t7R1BxO7sNWK/tHwGOQIdq6IpzcfpZn0dYwnnEBERERERERGRu0yXaImIiIiI3AWaa7BoSvO34qWNjpWI3A6N4BERERERERERcXAawVNK9e/fn4ULFxZ6bO3atXh4eNCxY0fi4+Np0qSJ7S4RgwcPZuLEifj6+hZbpj/v/04VvNzrtpbXN2EiIiIiIiIit6YCjwPp2rWr7ef4+Hhq1qxZ5NuT3+39i4iIiIiIiEjpoQKPA1m6dCmenp4EBARw/PhxZsyYUeg26WvWrGHnzp2YzWaGDRtG9erVbev06nV15Mzw4cN5++23CQgI4KOPPuLChQvk5+fTvXt3oqKigKujh7p3786uXbtwd3cnOjqaihUrFtpWXFwc69atw2w2U7VqVYYMGXLLW46KiIiIiIiISPFQgccBRUZGsmbNGvr370+dOnVsj/v4+BATE8OPP/7IypUrefXVV/9yO4MGDcLb25u8vDxGjRpFmzZt8PHx4cqVK4SFhfHUU0/x5Zdfsm7dOh5//PFC67Zp08ZWEFq8eDE///wz3bp1u24fcXFxxMXFATBp0qTbbqu/v/9tr1McXF1dS02W26Xs9uPI+ZXdPhw5Ozh+fhERERFHpgJPGdKmTRsAQkND2bZt2y2XX716Ndu3bwcgLS2NlJQUfHx8cHV1pUWLFrZt7d2797p1T58+zeLFi8nKyiI3N5emTZvecB9RUVG2QtCdKC13DXDkOxgou/04cn5ltw9Hzg6lJ39QUJC9I4iIiIiUOBV4yhBX16v/nEajkYKCAgBcXFywWq22ZfLy8gBISEhg3759fPDBB3h4eDBu3Djy8/Nt6xgMhuu29WexsbFER0cTEhJCfHw8CQkJxdo2EREREREREbk5FXgclKenJzk5ObdcrkqVKuzatQuAEydOYDKZAMjOzqZ8+fJ4eHhw9uxZjh49elv7z83NpVKlSpjNZjZu3FjkyZ51VywRERERERGRu08FnlIqLy+v0Bw6PXv2LPR8p06dmD17dqFJlm8kMjKSDRs2MGzYMOrWrWsbtt6sWTN++ukn3nzzTapVq0ZYWNht5evbty+jR4/G19eXsLCwIhWbRERERERERKR4GKx/vn5HpJglJyfbO8IdKS3zStwJZbcfR86v7PbhyNmh9OTXHDxiL47azylppeW9whHoWBWdjlXR6VgVTWk+Tjfr6xhLOIeIiIiIiIiIiNxlKvCIiIiIiIiIiDg4zcEjIiIiInIXFLzcy94RHMI5ewdwIKX1WOnGKSKlkwo8DmT58uVs2rQJo9GIwWBg4MCBfPXVV/Tv3586deoU+/7Xrl2Lh4cHHTt2vONtFKXjow8MERERERERkdujAo+DOHLkCDt37iQmJgY3NzcyMjIwm80lmqFr164luj8RERERERERKRoVeBzExYsX8fHxwc3NDQBfX9/rltm0aRPffvstAPfccw/PPPMMa9eu5dy5c/Tv3x+A+Ph4jh8/zoABA9iwYQM//PADZrOZsLAwXnrpJYxGI/3796d79+7s2rULd3d3oqOjqVixIkuXLsXT05NevXoRFxfHunXrMJvNVK1alSFDhuDh4VFyB0RERETKnLIwWllERMReVOBxEE2bNmXZsmUMHTqUxo0b065dOxo2bGh7Pj09na+++oqYmBjKly/PBx98wLZt24iMjOSdd96xFXg2b97MY489xpkzZ9i8eTPvv/8+rq6uzJkzh40bN9KxY0euXLlCWFgYTz31FF9++SXr1q3j8ccfL5SnTZs2REVFAbB48WJ+/vlnunXrdl3uuLg44uLiAJg0aVKR2urv739Hx6g4ubq6lspcRaHs9uPI+ZXdPhw5Ozh+frEvjVYWERH5e1TgcRCenp7ExMRw8OBBEhISmDZtGv369bM9f/z4cSIiImwje+677z4OHjxI69atqVq1KkeOHKFatWqcPXuW+vXr8+OPP3Ly5ElGjRoFQF5enm1dV1dXWrRoAUBoaCh79+69Ls/p06dZvHgxWVlZ5Obm0rRp0xvmjoqKshWCiiotLe22li8J/v7+pTJXUSi7/ThyfmW3D0fODqUnf1BQkL0jyB3QaGUREZG/RwUeB2I0GomIiCAiIoLg4GDi4+OLtF67du3YsmUL1atXp3Xr1hgMBqxWKx07duTpp5++bnkXFxcMBoNtnwUFBdctExsbS3R0NCEhIcTHx5OQkPC32iYiIiLOzRFHK9/JSGWRsqA0jtbUKNKi07EqGkc8TirwOIjk5GQMBgPVqlUDIDExkSpVqnD69GkA6taty/z588nIyMDb25tff/2Vf/zjHwC0bt2ab7/9lsTERNuon8aNG/PRRx/Ro0cPKlSoQGZmJjk5OVSpUqVIeXJzc6lUqRJms5mNGzfi5+dXpPV0hywRERG5EUccrXwnI5VFyoLSMFrzv5WWUaSOQMeqaErzcbrZaGUVeBxEbm4u8+bNIysrCxcXFwIDAxk4cCBTp04FoFKlSjz99NOMHz8euDpsuVWrVgB4e3tTvXp1zpw5Q926dQGoUaMGTz75JB988AFWqxUXFxcGDBhQ5AJP3759GT16NL6+voSFhZGTk1MMrRYRERFnotHKIiIid04FHgcRGhrKBx98cN3j48aNs/187733cu+9995w/ZEjR173WLt27WjXrt11jy9cuND2c2RkJJGRkQD06dPH9njXrl01EaGIiIjcNWVltLKIiIi9qMAjIiIiInan0coiIiJ/j8FqtVrtHUKcR3Jysr0j3JHSfP3lrSi7/ThyfmW3D0fODqUnv+6iJfZyukdLe0cQKRGlcV7N0vIZ5Ah0rIqmNB+nm/V1jCWcQ0RERERERERE7jJdolVG9e/fv9BcOn8lISEBV1dX6tev/5fLLVmyhAYNGtCkSZM7zlXwcq+/fL40fhsgIiIiUhTqxxRNaf5WvLTRsRKR26ECj5CQkICnp+ctCzx9+/YtoUQiIiIiIiIicjtU4HEiO3bsYPny5ZjNZnx8fBgyZAh5eXn89NNPGI1GNm7cyAsvvMDMmTOZOXMmRqOR3Nxc3nzzTf73f/+Xzz77jBYtWhAZGcmyZcvYuXMneXl51KtXj4EDB9puNyoiIiIiIiIiJUsFHicSHh7OhAkTMBgMrFu3jhUrVvDss8/SpUsXPD096dXr6uVTISEhHDhwgEaNGrFr1y6aNm2Kq2vhU+Uf//gHTzzxBAD/+7//y86dO2nZ8vqJBePi4oiLiwNg0qRJt8zo7+//d5tZLFxdXUtttltRdvtx5PzKbh+OnB0cP7+IiIiII1OBx4mkp6fzySefcPHiRcxmMwEBATdcrl27dmzevJlGjRrx66+/8uCDD163zP79+1mxYgVXrlwhMzOTmjVr3rDAExUVRVRUVJEzltZrjB35+mdltx9Hzq/s9uHI2aH05NddtERERMQZqcDjRObNm0fPnj1p2bIlCQkJfPPNNzdcrmXLlnz99ddkZmZy4sQJGjVqVOj5vLw85s6dy8SJE/H392fp0qXk5eWVRBNERERERERE5AZU4HEi2dnZ+Pn5AbB+/Xrb4+XKlSMnJ8f2u6enJ3Xq1GH+/Pm0aNECo9FYaDv5+fkA+Pr6kpuby2+//UabNm2KlEF3lxARERERERG5+1TgKaPy8vJ49dVXbb/37NmT3r17M3XqVMqXL0+jRo0wmUwAtGjRgqlTp7J9+3ZefPFFGjRoQLt27Zg6dSrjxo27btvly5fngQceYPjw4VSsWJE6deqUVLNERERERERE5AYMVqvVau8Q4jySk5PtHeGOlJZ5Je6EstuPI+dXdvtw5OxQevJrDh6xF0ft55S00vJe4Qh0rIpOx6rodKyKpjQfp5v1dYw3fFRERERERERERByGCjwiIiIiIiIiIg5OBR4REREREREREQenSZYdXN++fQkODrb93r59ex555JEbLrtt2zaCgoKoUaPGHe3r+PHjrF+/nhdffPGO1gcoeLnXdY/pzloiIiJSFtyonyPXO2fvAA7k7xwr9bFFnI8KPA7O3d2dyZMnF2nZ7du306JFizsu8NSpU0d3zBIREREREREphVTgKaO++uorduzYgYuLC02aNKFNmzbs2LGDAwcO8O9//5vhw4eTm5vL7NmzuXLlClWrVuW1117D29ubcePGUbduXRISEsjOzubVV1+lQYMGJCQksHLlSkaOHMmxY8eYP38++fn5uLu7M2jQIN21RERERERERMROVOBxcHl5eURHR9t+f/TRR2ncuDHbtm3jk08+wWAwkJWVRfny5WnZsiUtWrQgMjISgBEjRvDiiy/SsGFDlixZwrJly3j++ecBsFgsTJw4kV27drFs2TLGjBlTaL9BQUG89957uLi4sHfvXhYtWsSIESOuyxcXF0dcXBwAkyZNumEb/P3978ahKFaurq4OkfNGlN1+HDm/stuHI2cHx88vIiIi4shU4HFwN7pEq6CgAHd3d/7v//6PFi1a0KJFi+vWy87OJisri4YNGwLQsWNHpk2bZnu+devWAISGhmIymW64fmxsLKmpqbZ93khUVBRRUVF/2Ya0tLS/fL408Pf3d4icN6Ls9uPI+ZXdPhw5O5Se/BpR6nyWL1/Opk2bMBqNGAwGBg4cSFhY2G1tY8eOHZw5c+amcxmKiIiUdirwlEEuLi58+OGH7Nu3j61bt7JmzRrGjh17W9twc3MDwGg0YrFYrnt+yZIlREREEB0djclkYvz48Xclu4iIiMjtOHLkCDt37iQmJgY3NzcyMjIwm823vZ2WLVvSsmXLYkgoIiJSMlTgKYNyc3O5cuUKzZs3Jzw8nP/5n/8BoFy5cuTk5ADg5eWFt7c3Bw8epEGDBmzYsIEGDRoUeR/Z2dn4+fkBEB8fX+T1NJu/iIiI3E0XL17Ex8fH9uWUr68vAIMHD6Zt27bs3r0bd3d3hg4dSmBgIDt27GD58uWYzWZ8fHwYMmQIFStWJD4+nuPHjzNgwABiY2MpV64cJ06c4NKlSzzzzDO2S9xFRERKKxV4HNx/z8HTrFkzunfvzkcffUR+fj5Wq5Vnn30WgHbt2vHZZ5/xww8/MGzYMAYPHmybZDkgIIBBgwYVeb8PP/wwsbGxLF++nObNm9/1domIiIgURdOmTVm2bBlDhw6lcePGtGvXznYJupeXF1OmTGH9+vUsWLCAkSNHEh4ezoQJEzAYDKxbt44VK1bY+kp/dunSJd577z2Sk5OJiYm5YYGnKHMNitiLs82Jpnngik7Hqmgc8TgZrFar1d4hxHkkJyfbO8IdKS3zStwJZbcfR86v7PbhyNmh9OTXHDzOx2KxcPDgQRISEvjpp5/o168f33zzDf/85z+pWrUqZrOZgQMHMm/ePJKSkvjiiy+4ePEiZrOZgIAA3nnnnetG8DRp0oT77rsPgGeffZYvvvjiljlO99AlXlJ6ONvI+dLyGeQIdKyKpjQfp5v1dTSCR0REREQcmtFoJCIigoiICIKDg22XjxsMBtsy136eN28ePXv2pGXLliQkJPDNN9/ccJvXLvkC0PehIiLiCIz2DiAiIiIicqeSk5NJSUmx/Z6YmEiVKlUA2Lx5s+3/1+6q9ed5BNevX1/CaUVERIqPRvCIiIiIiMPKzc1l3rx5ZGVl4eLiQmBgIAMHDmTXrl1kZmYyYsQI3NzcGDp0KAC9e/dm6tSplC9fnkaNGmEymezcAhERkbtDBZ4y5NKlSyxYsIDjx4/j5eVFxYoVee6550rVXAQFL/cq9LuzXRssIiIid1doaCgffPDBDZ/r1asXzzzzTKHHWrVqRatWra5btlOnTnTq1Am4egeuP1u4cOHdCSsiIlKMVOApI6xWK5MnT6Zjx4688cYbwNUhypcvX77jAo/VasVqtWI06ko+ERERkVvRF1dFU5onLi1tdKxE5HaowFNGJCQk4OrqSteuXW2PhYSEMHPmTP744w9at24NwIwZM2jbti1ZWVls27aN7Oxs0tPTue++++jduzcmk4kJEyYQFhbGiRMnGDVqFMOGDbN9c7V161Z27tzJ4MGD2bJlC8uWLcNoNOLl5cX48ePt0nYRERGR/xYbG2vvCCIiIiVKBZ4yIikpidq1a1/3eOfOnVm1ahWtW7cmOzubw4cPM3jwYDZu3MixY8eYMmUKHh4ejBo1iubNm+Pj40NqaiqDBw+mXr16f7nPZcuW8c477+Dn50dWVlZxNU1EREREREREbkEFnjKuYcOGzJkzh4yMDLZu3UqbNm1wcXEBoEmTJvj4+ADQunVrDh06RKtWrfD3979lcQegfv36xMbG0rZtW9q0aXPDZeLi4oiLiwNg0qRJ1z3v7+9/p00rUa6urg6T9b8pu/04cn5ltw9Hzg6On19ERETEkanAU0bUrFmT33777YbPdejQgQ0bNrB582YGDRp0020YDAYAPD09b/g4QF5enu3ngQMHcvToUXbt2sXIkSOZNGmSrWB0TVRUFFFRUTfdp6NcU+zI1z8ru/04cn5ltw9Hzg6lJ39purmAiIiISEnR7LllRKNGjcjPz7eNlgE4deoUBw8epFOnTqxevRqAGjVq2J7ft28fmZmZ5OXlsX37durXr3/DbVeoUIEzZ85gsVjYtm2b7fHU1FTCwsLo27cvvr6+XLhwoZhaJyIiIiIiIiJ/RSN4ygiDwcCIESNYsGAB33//PW5ublSpUoXnn3+eihUrUr169etuCVqnTh2mTJnChQsXuO+++6hTpw4mk+m6bffr14+YmBh8fX0JDQ0lNzcXgC+//JKUlBTgaoGpVq1at8ypu0uIiIiIiIiI3H0q8JQhfn5+DBs27LrHr1y5QmpqKvfee2+hxytXrsyAAQMKPRYQEMCUKVMKPRYZGUlkZOR12x0xYsRdSC0iIiIiIiIif5cKPGXc3r17+de//kWPHj3w8vKydxwRERERERERKQYq8JRxTZo04dNPP73u8U6dOtGpU6eSDyQiIiIiIiIid50mWRYRERERERERcXAq8BSj/v372ztCqcggIiIiIiIiIsVLBR65bQUFBXe+7su9KHi5111MIyIiIiIiIiKag6eEjRs3jv79+1OnTh0yMjIYNWoUsbGxrFq1iqSkJAYNGkRSUhLTp0/nww8/5OLFi8ydO5eMjAw8PDx45ZVXqF69OrGxsbi7u5OYmMjly5d57bXXWL9+PUePHqVu3boMHjzYts8FCxawd+9eKlasyBtvvIGvry+JiYnMnj2bK1euULVqVV577TW8vb1vmi8+Pp7ffvuN3NxcLBYLo0ePJjY2ltOnTxMUFMTFixcZMGAAderUsePRFREREbEffYlVNOfsHcCBnANcZq+wdwwRcRAawVNKdO/enXPnzrFt2zY+/fRTXn75ZTw8PJg1axYvvvgiMTEx9O/fnzlz5tjWycrK4oMPPuC5557jo48+omfPnkyZMoWkpCQSExOBq7dIr1OnDlOnTqVhw4Z88803AMycOZN+/frx8ccfExwczLJly26Z8eTJkwwfPpzx48fz448/4u3tzbRp0+jbty8nTpwoluMiIiIiIiIiIremETylhNFoZNCgQYwYMYIuXboQHh5Obm4uhw8fZurUqbblzGaz7ecWLVpgMBgIDg6mQoUKBAcHA1CzZk1MJhMhISEYDAbatWsHwH333cfHH39MdnY2WVlZNGzYEICOHTsybdq0W2Zs0qQJ3t7eABw6dIju3bsDEBwcTK1atW64TlxcHHFxcQBMmjTJ9ri/v3+Rj01p4Orq6nCZr1F2+3Hk/MpuH46cHRw/v4iIiIgjU4GnhLm4uGC1WgHIz88v9FxKSgqenp6kp6cDYLFYKF++PJMnT77httzc3AAwGAy2n6/9brFYbriOwWC443weHh5/ue6NREVFERUVdd3jaWlpt70te/L393e4zNcou/04cn5ltw9Hzg6lJ39QUJC9I4iIiIiUOF2iVcKqVKliu5xp69attsezs7OZP38+48ePJzMzk61bt+Ll5UVAQABbtmwBwGq12i69Kiqr1Wrbz6ZNmwgPD8fLywtvb28OHjwIwIYNG2jQoMFf5vtv4eHhtlxnzpwhKSnptnKJiIiIFLdrdxM1mUxs2rTplsubTCaGDx9e3LFERESKhUbwFKO8vDxeffVV2+89e/bkoYceYtq0acTFxdG8eXPbcwsWLODBBx8kKCiIV199lfHjx9OgQQNef/11Zs+ezfLlyzGbzbRv356QkJAiZ/Dw8ODYsWMsX74cX19f3nzzTQAGDx5sm2Q5ICCAQYMGAdw033/r2rUrsbGxvPnmm1SvXp0aNWrg5eV1yzyaJE5ERERK2vnz59m0aRP33nuvvaOIiIgUG4P12vU4IrfBYrFgNptxd3cnNTWV999/n+nTp+Pq+tc1w+Tk5BJKeHeVlssO7oSy248j51d2+3Dk7FB68usSLbmmf//+LFy4kHfeeYczZ84QEBBAx44dad26NTNnzuTKlSsAvPjii9SvXx+TyURMTAxTpkxh7NixvPDCC7Yv1saMGcOAAQP+8ou20z1alkCrxNnoC9KiKS2fQY5Ax6poSvNxullfRyN45I5cuXKF8ePHU1BQgNVq5aWXXrplcUdERETEHp5++mlWrlzJyJEjgav9mHfffRd3d3dSUlKYPn16oZtBANx///3Ex8fz/PPPk5ycTH5+/nXFnZvdTELkbtLk9UWjif6LTseqaBzxOOkvcrkj5cqVU0dGREREHFJBQQFz584lMTERo9FISkrKdcu0bduWf//73zzzzDP88ssvdOrU6bplbnYzCZG7qbSOIChtSvNoi9JGx6poSvNxutkIHk2yLCIiIiJOZdWqVVSoUIHJkyczadIkzGbzdct4eHjQpEkTduzYwZYtWzR/j4iIlHoq8DiBPn36MGPGDNvvBQUFDBgw4JYjcBISEmzLJCQkcPjw4WLNKSIiIlIcypUrR05Oju337OxsKlWqhNFoZMOGDVgslhuu98ADDzB//nzq1KmDt7d3ScUVERG5IyrwOAEPDw9Onz5NXl4eAHv37sXPz++2tnG3CjwFL/f629sQERERuR3BwcEYjUaio6NZtWoVDz74IOvXryc6OpqzZ8/i4eFxw/VCQ0MpV64c999/fwknFhERuX2ag8dJ3HPPPezatYvIyEh+/fVX2rdvz6FDhwA4duwY8+fPJz8/H3d3dwYNGlTomj6TycRPP/2E0Whk48aNvPjii2RlZdlu3e7j48OQIUOoWLGinVonIiIicr2FCxcCVyfKHDt2bKHnPv74Y9vPzzzzDAABAQFMmTLF9nh6ejpWq5UmTZqUQFoREZG/RwUeJ9G+fXuWLVtG8+bNOXXqFPfff7+twBMUFMR7772Hi4sLe/fuZdGiRYwYMcK2bkBAAF26dMHT05Neva6OwMnMzGTChAkYDAbWrVvHihUrePbZZ+3SNhEREZG7bf369SxevJhnn30Wo7Fog951O+uiKc0Tl5Y2OlYicjtU4HEStWrV4vz58/z666/cc889hZ7Lzs4mNjaW1NRU4OocPbeSnp7OJ598wsWLFzGbzQQEBNxwuRvdPtTRbjUHjnmLvGuU3X4cOb+y24cjZwfHzy/yZx07dqRjx472jiEiIlJkKvA4kZYtW7Jw4ULGjRvHH3/8YXt8yZIlREREEB0djclkYvz48bfc1rx58+jZsyctW7YkISGBb7755obL3ej2oY74LYQjf3ui7PbjyPmV3T4cOTuUnvw3u3WoiIiISFmmAo8Tuf/++/Hy8iI4OJiEhATb49nZ2bZJl+Pj42+47o3uPnFtnfXr1xdfaBERERERERG5Jd1Fy4lUrlyZ7t27X/f4ww8/zNdff81bb71109uEtmjRgm3bthEdHc3Bgwfp3bs3U6dO5e2338bHx6fIGXRtuoiIiIiIiMjdZ7BarVZ7hxDnkZycbO8Id6S0XHZwJ5Tdfhw5v7LbhyNnh9KTX5doib04aj+npJWW9wpHoGNVdDpWRadjVTSl+TjdrK+jETwiIiIiIiIiIg5OI3hERERERERERBycRvBIiRk5cqS9I9wxZbcPR84Ojp1f2e3DkbOD4+cX+Tt0/hedjlXR6VgVnY5V0elYFY0jHicVeEREREREREREHJwKPCIiIiIiIiIiDk4FHikxUVFR9o5wx5TdPhw5Ozh2fmW3D0fODo6fX+Tv0PlfdDpWRadjVXQ6VkWnY1U0jnicNMmyiIiIiIiIiIiD0wgeEREREREREREHpwKPFLuCggJ7RxAREREpNurriIhIaaACjxSbgoICvvjiC7744gv27t1r7zilhiNeFXnmzBlycnIAx8t/4cIFzGYzABaLxc5pbo8jZ3fkcwYcO78jZ3fkc16ck/o6xcvR3sPsJS8vz94RHMK1QqzOq1vTsSq60vb6c7V3ACmbrFYr8+fPJzs7m3vuuYfvv/+e5ORkHnjgAdzc3Owdr0Rt2LCBkydPEhISQseOHTEYDPaOVGSHDh3ik08+ISQkhPz8fIYMGULFihXtHatI9u/fT2xsLHXq1MFisTBixAiMRseoaTtydkc+Z8Cx8ztydkc+58V5qa9TPC5dukRiYiKNGzfGxcXF3nFKtQsXLrBkyRIAHnjgAWrVqoWnpydWq9Wh+pvFLS0tjWXLluHj48P9999PUFCQvSOVWjc7Vjqnrnez15+9qfckxSInJ4fExERefvll7rvvPh566CFSUlLYsmWLvaOVqF9//ZVVq1ZRv359Vq1axerVqzl//jxQ+iviBQUF/Pbbbzz33HOMHDmS6tWr85///IcjR47YO9ot5eXl8csvv/DSSy8xYsQIXFxcWLZsGWlpafaOdkuOnN2Rzxlw7PyOnN2Rz3lxburr3H2rV69m5MiR/PDDD8ydO1ejov5CQUEBs2fPxs/Pj/DwcNatW8d//vMfAP0h/ic5OTnExsZSuXJlPDw8WLp0KRs2bLB3rFLpr46VzqnCbvT6W7Vqlb1jASrwSDHx8vKiSpUqxMfHAxAeHk7t2rU5cuQIly5dsmu2krR//34efPBBIiMjGThwIGlpaezevbvUVsHz8vLIy8vDarXi4uJCSkoKf/zxBwAPP/wwLi4uJCQk2C7/KE3y8vJsl3S4u7uTlZVlG17ar18/0tLSOHTokO3yj9LE0bM76jkDjp3f0bM76jkvco36OndXQUEBycnJvPvuu4waNYo6deoQFxdHUlISUPq/GCtp58+fx2Kx8OSTT9K5c2e6du3KqVOn2LlzJ6Djdc25c+cwm8307t2bJ554gtatW3Po0CEOHz5s72ilzq2Olc6p/+dGr7+kpCTb68+eVOCRYtO6dWsSExO5ePEinp6eBAcH4+rqysWLF+0drdj85z//sV2SBVC7dm2SkpKwWq2EhYVRu3ZtUlNTOX78uJ2TXm/t2rW8/vrrzJs3j8WLFwPQsmVLLl68SE5ODpUrV6ZevXpkZGRw9uxZO6ct7IcffmD48OEsXLiQn376CYCQkBCysrLIy8sjMDCQevXqceTIETIzM+2ctjBHzu7I5ww4dn5Hzu7I57zIf3PGvs7ddO7cOS5cuABcHSFw8OBBsrOzAWjVqhUhISGsWbPG9rwzO3ToELNnz7Ydj8DAQDIzM9m6dSsANWrUoFmzZmzcuBGLxeK0x+vQoUN88cUXtpF0ISEhuLi4sH//fuBqIbZq1ars3LnT6QsWNztW+/btA64/Vs56TsHNX3/btm0Drn/92ZMKPFJswsPD8fHxsX2zFRoayvHjx0vdRFR3Q3Z2NjNmzGD37t1cunSJadOmkZqaSkBAAC4uLhw8eBCAiIgICgoKbH+0lJYPluTkZLZs2cJ7771Hnz59+O2339i9ezf+/v7k5eXZ3ugbNmxIamoqubm5dk78/xw/fpzNmzczcuRI2rVrx7///W9OnDhBSEgIp06d4vTp0wC0b9++1H2r6sjZHfmcAcfO78jZHfmcF7kRZ+rr3E1ms5nY2Fg+/PBDZs6cSVxcHEajkc6dO9v+gPL19aVly5bk5uY6xOWmxenEiRPMnj2b2rVrs2fPHubNm0dycjK9evVi06ZNAHh6elKvXj3Kly/PqVOn7JzYPn7//Xdmz56Nv78/a9eu5csvv+T8+fNERkaya9cuAPz8/KhVqxb5+flcvnzZzont56+O1e7duwEdq2v+6vV37RK2P7/+EhMT7ZpXBR4pNpUqVaJVq1bs2bOHLVu2YDKZcHd3L7MT5l2+fJkRI0bQq1cv2rZty4oVK/D19cXLy4uDBw+SmZmJn58fVqvV9i2CPSvhWVlZtp9dXFzw8PDA3d0dPz8/+vTpw/r166lQoQJ+fn4cPHiQM2fO4OnpSZUqVTh37pzdcgOF/mDNz8+nZs2aBAYGEhYWxmOPPcbXX39Nw4YNAThw4ABpaWmUK1eOkJAQTCaTvWIDjp3dkc8ZcOz8jpzdkc95kVtxtr7O3ZKYmEhubi7Tp0+nb9++HDp0iLi4OBo3bozZbLb9Me7t7Y2np6fTX6557Ngx6tSpQ1RUFK+88grlypXjt99+IyAgAG9vb9vcHwEBAZhMJsqVK2fnxPaRmJhI06ZN6d69O4MGDeLChQscPnyYqlWrkp+fbyuG1a5dm4SEBKd+nf75WL322ms3PVYhISEkJCTg6uq892b68+vv1Vdfvenrr2rVqphMJry8vOyaVwUeKVb169fnkUceYffu3Xz44Ye0atWKunXr2jvW32Y2m1mzZg1nz54lNzcXq9WKv78/Z86cAaBPnz5cunSJtLQ0GjZsSEZGBkuXLgWu/oFTo0YNu2W/dkvX999/n1WrVnH8+HE8PDzw8fEhIyMDgHbt2mE0Gjl69Cj33Xcf5cqVIzY2lnnz5rF7927CwsLsmv2jjz7il19+IT09HXd3dy5fvsyVK1cA6Nq1Kzk5Oezdu5eHHnqI9PR0PvvsM7744gsOHjxI7dq1lf0OszviOePo+ctCdkc850VuR1nt69xtFy5csI1ctlgspKamYrVaCQ8Pp1mzZqSkpJCWlkbbtm3597//DVwdQXDp0qVSM+K5pGzevJlVq1bZ5j4JDQ0lNzeXS5cuUalSJSIiIvjjjz+4cOECXbt25YcffuDgwYPs37+fK1eu2P0SkZKybds21q1bR2pqKnD1shmAzMxMqlSpwj333MOxY8coV64cjRo1YsWKFZw5c4bExEQqVapEfn6+PeOXqL86VgEBATc9VqdOnaJSpUpONSrxr15/FStWvOnrb9++faXi9acCjxS7e+65h4EDBzJlyhT+8Y9/2DvO33bs2DHefvtt9u7dy3/+8x++/PJLypcvj8ViITk5mby8PFxcXGjfvj0//vgjDRs25PHHH+fChQv885//5I8//iAyMtJu+deuXUtycjJDhgzBxcWFWbNm4e3tjZeXF3v27LFd+961a1dWr16Nr68vffr0oXfv3gQEBDBhwgSCg4Ptkv3bb7/FZDLRt29fzp49y4IFC6hduzYFBQX8+uuvtuX69OnD999/T+XKlXnuuedo37495cuX5/3336dKlSrKfpsc+Zxx9PyOnN2Rz3mR21XW+jp3U1paGuPHj2fGjBnExsZiMpmoWrUqDRo0YM+ePQA0a9YMDw8PUlNTadu2Lf7+/sTGxvLPf/6TnJwcqlatat9GlBCLxcKyZcv4/vvvAZg1axY7duzAw8ODgIAADhw4AFy95L9cuXKkpaURGhrK448/zvbt2/n666957LHHyvxtwM1mM/PmzWP58uWkpKTwr3/9i0OHDlG5cmXMZjPJycnA1ct9//jjDy5evEibNm1o374933//PQsWLKBHjx74+fnZuSXFT8eq6MrK6895x1pJiSpLw/ouXrxI06ZNefbZZ8nMzCQmJoaff/6ZLl26sGLFCkJDQ6lRowbt27dnxYoVHDhwgIYNG/L6669z5coVfH19SzxzXl4e7u7uWCwWrly5Qrt27ahevTrVq1fn8OHDfPnllzz88MPMmjWLkJAQmjRpQnh4OMHBwZw/f54qVarQvHlzmjdvXuLZCwoKcHFxIT8/n4yMDHr16kW9evWoWbMm8+bNY+XKlfTr149PP/2URo0aUa1aNerUqUPdunXJzMzE29ubTp06lXhuR8/uyOeMo+d35OyOfM6L/F1lqa/zd/15Qta1a9cSFhbG008/zZdffsnChQvp378/lSpV4sSJE9SpUwdfX1+qVq3K9u3bbZfXnDt3jlOnTnHffffZuTUlx2g0kpyczLPPPktERAT+/v6sWbOGZ555hkqVKpGYmEjNmjWpWbMmQUFB/PTTT3Tr1o3OnTs71SS4rq6u/PHHHwwZMoTq1asTHx/P/PnzGTNmDEajkSNHjuDn54e/vz9hYWH88ssvtG3blocfftj2GessdKyKrqy8/jSCR+QWLl26xJ49e2y38E1NTcXNzQ24em34Cy+8wKJFiwgNDSUoKIj4+HiOHDlCVlYWVapUoXr16gB4eHiUeHHnwoULfPrpp8yZM4dDhw5hNBopKCjg0KFDtmVeeeUV24zvHTt2JD4+nq+++opp06aRl5dHpUqVSjTzNWlpafzrX/9i8eLFnD17Fjc3N8xmM+vXrweu3p720UcfZcOGDVSqVInIyEi+/fZbVq9ezb/+9S9ycnIoX768st8mRz5nHD2/I2d35HNeRO6+/76co2LFigA888wztve12rVrk5OTY5vro1WrVmRnZ5OdnY2HhwfBwcFOUdxZv349Bw4csM21VqFCBbKysigoKCAyMpLAwED27t1Lo0aNcHNzY8mSJQCkp6cTFhZm65+Wlj8ui8vWrVtJTEzEYrGQmZlp+zLBYrHQqVMnKlasyObNm4mKisJkMtnmRcnMzKRJkya27ThDwULHqujK4utPBR6Rv7B69WpGjhzJDz/8wJw5czh+/DgtWrQgPj7e9oIODQ2lSZMmLF++nD59+hAYGMjixYt55513qF69OhUqVLBL9oKCAmbPno2fnx/h4eHExcWxevVqevTowdatW0lJSQGgXLlydOnShTVr1tC2bVv69u2L0WgkJCSEkSNH2uUbyZycHGJjY6lcuTIeHh4sXryYHTt20KdPH/bv32+7frhatWrcc889bN26lYceeoiuXbuSlJRErVq1eOONN+zyZuvI2R35nHH0/I6c3ZHPeRG5u/bt28eYMWOYO3cuGzduBK6+bxmNxkKXlP7666+EhITQqlUr1q1bx6JFi3j33XepW7cunp6e9mxCibBarVy8eJHx48ezfv16Nm7cyNy5c8nNzcXHx4ekpCTbBPXdunVj48aNVKhQgd69e+Pl5cXEiRPZvHkzDzzwQJmeKNhqtXL+/HlGjRrF2rVrWb58Od988w3lypXD1dWVvXv3YjRe/XP2qaeeYtmyZQQGBvLoo4+SkZHB+PHj2bVrF61atbJzS4qfjlXRWSwW0tPTy+zrT2NJRW6ioKCA5ORk3n33XWrUqMG6dev49ttvefXVV2natClz5szhlVdeAeCBBx5gw4YNWCwWoqKiiIiIwNvbGx8fH7vlP3/+PBaLhSeffBKA4OBgli9fTkREBI899hizZs1i7NixAAQFBdkmbK1atSpPPvmkXf/YOnfuHGazmd69ewNXJzvbsWMH/v7+dO7cmfnz5zNq1CiMRiOurq64u7tjNBqpW7cuoaGhtg8wZb89jnzOgGPnd+TsjnzOi8jdk5mZyeLFi3nooYfw9vbmP//5D1lZWbRu3Zovv/ySiIgIvLy8aNasGStXrmTLli1069aNN954g6NHj9KnTx+7zlFYUiwWC0ajkZycHCpVqsTrr7+OxWJh7ty5zJs3j+eee45PPvmEhg0bUqdOHapXr061atXYtGkTPXv2ZODAgWRnZ9vlkv+SZDabcXV15eLFi9SpU4eXXnqJ5ORkVq9ezb///W+eeOIJJk6cSLt27ahYsSIhISHUr1+f7du307ZtW1577TUuXrxIQECAvZtS7LKzs/Hy8iI9PV3H6hYuX75MhQoVyM3NLbOvP/WqRP7k3LlzXLhwAbg61O7gwYO2b5xatWpFSEgI3333HS+++CJ79+5l9+7dAKSkpFChQgXbUMZq1aqVeHHn0KFDzJ49mzVr1gBXZ8fPzMxk27ZtANSoUYPmzZuzcuVKevbsiaurK19//TVbt27lxx9/LPTNf0n/sXjo0CG++OILtmzZAly9JaOLi4vtdvL169cnMDCQ3377jYceeoi0tDRWrlzJ/v372bdvX6E/EEv6j0VHz+6o54yj53f07I56zovI3WWxWGx3jElPTyc4OJjWrVvTqFEj+vfvz5IlS/Dz86NmzZps3brVdrfRdu3a2W59XrNmTTp37lzmizsWi4VFixaxaNEiDhw4QHJysu090Gg0MmDAAHbt2kV6ejr33nsvmzdvZufOncDVeVTq169v+7k0/3H5d107TnPnzmXfvn0cO3aMzMxM4OqXGo888gi//fYbAG3btuXbb78lKSkJuDqKJSQkBAA3NzenKFisWbOGsWPHcubMGS5cuMDFixcBHav/ZrFYWLJkCWPGjCE9Pd02uTSUvdefelYiXP2WIDY2lg8//JCZM2cSFxeH0Wikc+fOtj/AfH19adWqFefPnyczM5PnnnuO7du3M378eFavXm3X20CfOHGC2bNnU7t2bfbs2cO8efNITk6mV69ebNiwAQBPT0/Cw8NxdXUlLS2NgQMHEhwczLp167j//vvtdteP33//ndmzZ+Pv78/atWv58ssvOX/+PJGRkezatQuAypUrExISQlZWFkajkcGDB9v+4O3YsSP33nuvst8mRz5nHD2/I2d35HNeRO6uX375hddee42lS5cCV9+3jhw5YhthGBQURLt27ViwYAGPPfYYubm5LFq0iFWrVrFs2TJq1aplz/gl6sCBA7z99ttkZWURGBjIkiVLcHV1JSEhgWPHjgFX/8h84okn+PLLL+nYsSNNmjRh/fr1vPXWWxQUFNj1bpQlZe/evYwYMYLs7GwaNWrEV199RWhoKAcPHiQxMREXFxf8/f3p2LEj3333HY8++ijVqlVj2bJlDB8+HE9PTypXrmzvZpQIq9UKQG5uLu7u7sTFxREZGcmJEyc4efKkjtWfHDx4kNdff52cnBzGjRuHn58fTZo04dChQ2Xy9adLtESAxMREcnNzmT59OocOHSIuLg6Axo0bc/jwYXbv3s0999yDj4+P7bZ4rVu3pnnz5uzbt4/GjRvb9e4Zx44do06dOkRFRdGiRQvWrFnDb7/9RtOmTfH29mbVqlX07NmTgIAALly4gNlsJjAwkCpVqtCuXTu7Xt6RmJhI06ZN6d69Oy1btuTrr7/m8OHDVK1albNnz7Jp0ybuvfdeQkJCWLRoEZmZmYSGhhIaGso//vEPZb9DjnzOOHp+R87uyOe8iNw9ubm5bN++nYcffpj169fToUMHgoKCqF27NgsWLOCNN94AoF+/frz//vtkZmby1FNPsXXrVo4cOcLQoUMJDw+3byNKkMFg4KGHHqJDhw7A1fdSk8lE3759mT17NjExMVgsFiIjI0lISLD1M+vVq8eVK1ec5jbx/v7+DBgwgIiICAC2bNmCt7c3jz32GF9//TWjRo3CYrEQFhZGamoq+fn59OzZk5YtW2I2m6lRo4adW1ByDAYDFouFS5cu8eCDD7J//35+//13nnrqKRYtWsQ777yjY/X/K1euHDk5OTz//PMAJCcnExQURM+ePZk3bx4ffvhhmXr9aQSPOK0LFy7Yqt8Wi4XU1FSsVivh4eE0a9aMlJQU0tLSaNu2LcuWLQPAz8+PjIwM27BiV1dX7rnnnhIv7mzevJlVq1Zx+PBh4OpEz7m5uVy6dIlKlSoRERHBH3/8wYULF+jatSs//PADBw8eZP/+/Vy5csU2nBpK/vKObdu2sW7dOtvEq4GBgcDVa/cDAgK45557OHbsGOXKlaNRo0asWLGCM2fOcOrUKSpVqlTozhzKXnSOfM44en5Hzu7I57yIFB9PT09efPFFunfvTpMmTWx3lnnppZfYt28fR44cAa7eQfTaSB1XV1fuvfdeXnzxRacq7sDV9/22bdva3s/r169PWloanTp1wmKx8MMPP2A0Grlw4YJt5AVcvfuYo/1x+XcEBQURERFBdnY2EyZM4Pjx4yxbtoxq1aqRlJTEhg0bMBqNXLlyhfz8fNuE3IGBgU5VsID/N5eTr68vHh4eNGnShI0bN1KvXj1OnTrFpk2bdKz+fyEhIbRu3ZqpU6cya9YsPvvsMyZOnGib0zAuLg6DwVBmXn8q8IjTSUtLY/z48cyYMYPY2FhMJhNVq1alQYMG7NmzB4BmzZrh4eFBamoqbdu2xd/fn9jYWP75z3+Sk5Nj+yOnpFksFpYtW8b3338PwKxZs9ixYwceHh4EBARw4MABACIiImwjjUJDQ3n88cfZvn07X3/9NY899hhBQUElnt1sNjNv3jyWL19OSkoK//rXvzh06BCVK1fGbDbbroVt3749f/zxBxcvXqRNmza0b9+e77//ngULFtCjRw/8/PyU/TY48jnj6PkdObsjn/MiUjKu/RHUo0cPTCYTu3btwtPTk969e/Pvf/+bX375heXLl3P69GmnuDPWX/Hw8MDNzc02587evXtt83gMGjSIs2fPMmnSJKZPn05oaKg9o5YKXl5etGrViv/7v/+jZcuWnDhxgvbt27N9+3amTp3K3Llz7To1Qmlw7VxKSkqiadOmNGvWjFOnTjF9+nS6du3Kpk2bdKz+pH///iQlJVGpUiXGjx9Pq1atOHHiBJ07dyYpKYmYmBhmzJhRJl5/ukRLnILVarV9e7x27VrCwsJ4+umn+fLLL1m4cCH9+/enUqVKnDhxgjp16uDr60vVqlXZvn073bt3Z9CgQZw7d45Tp05x33332a0dRqOR5ORknn32WSIiIvD392fNmjU888wzVKpUicTERGrWrEnNmjUJCgrip59+olu3bnTu3LnQMbAHV1dX/vjjD4YMGUL16tWJj49n/vz5jBkzBqPRyJEjR/Dz88Pf35+wsDB++eUX2rZty8MPP0xeXp5tAmtlvz2OfM44en5Hzu7I57yIlKyKFSvSuXNnvvvuO5o3b84//vEPqlatSkJCAunp6bz55pt4e3vbO2apcG0Ez+XLl2nZsiVw9fKRp556itOnTxMQEOD0hfFrn39du3YF4N5772XSpEl0796d8PBw9u7dy7PPPmsrMDq7WrVqMWfOHE6dOoW3tzcuLi706tULd3d3duzYoWP1//Py8mLcuHFUrFgRgKioKD788EN69uxJkyZN2L9/P0FBQWXi9acRPOIU/nyZAGB7cT/zzDMUFBRw6NAhateuTU5ODps2bQKu3jUrOzub7OxsPDw8CA4OtktxZ/369Rw4cICsrCwAKlSoQFZWFgUFBURGRhIYGMjevXtp1KgRbm5utmHS6enphIWFUVBQANjn8oitW7eSmJiIxWIhMzMTFxcX8vPzsVgsdOrUiYoVK7J582aioqIwmUysWrUKuHr5R5MmTWzbsccfi46c3ZHPGUfP78jZHfmcFxH7sVgsdOnShQoVKthuNezn50e/fv14/fXX9cflnxgMBgoKCvDx8eHUqVNMmjSJZcuWYTAYCA8PLxN/XP5d//35d+7cOfLz83F3d8fd3Z2WLVvqnPoTq9VKRkYGL7zwAuPHjyc0NJTVq1cD6Fj9l2t//wGkpqZSUFBgG13YqFGjMvP6U4FHyrR9+/YxZswY5s6dy8aNG4Gr35QYjUbb7c+7du3Kr7/+SkhICK1atWLdunUsWrSId999l7p169plWLHVauXixYuMHz+e9evXs3HjRubOnUtubi4+Pj4kJSWRm5sLQLdu3di4cSMVKlSgd+/eeHl5MXHiRDZv3swDDzyAi4tLiWc/f/48o0aNYu3atSxfvpxvvvmGcuXK4erqyt69e23DSp966imWLVtGYGAgjz76KBkZGYwfP55du3bRqlWrEs3t6NktFgvp6ekOec5cc+nSJcaNG+eQ+S9fvszYsWMdLrsjn/MiUjpcm+cjIyODzZs3ExgYSK1atew+ArQ0MhgMnDx5kk2bNrFq1Spat27N//zP/+Dl5WXvaKWKxWIhLS2NmTNnMnXqVNq2bet08zYVVc+ePRk9ejQNGzbEarXSs2dPHnnkEXvHKpWsVit//PEHM2fO5JNPPqFt27bUq1fP3rHuPqtIGfXHH39YR48ebd2yZYt137591kmTJll/+OEH65kzZ6yTJk2yJiUl2ZZ97733rKtXr7ZarVZrUlKSdd26ddYtW7bYJXdBQYHVarVaz549a50+fbrtsVmzZlljY2OtmZmZ1g8++MCakJBgzc3NtVqtVuuUKVOsK1eutFqtVmt+fr718uXLdsmen59vtVqt1sOHD1tnz55ttVqvtmP27NnWJUuWWM+fP28dNmyY9fz587ZlP/74Y+vmzZutVqvVmpeXZz137pxdsmdlZVmtVqv10KFDDpf90qVLtryOds5YrVbrhQsXrJcvX7YmJyc7XP4LFy5YDx48aE1JSbHOmDHDobLn5ORYrdarr9c5c+ZYrVbHOedFpHT5/vvvrfPnz7fm5eXZO0qpl5aWZl2+fLmO1S1cunTJ+uOPP+o4FZHZbLZ3BIeQk5NjXbt2bZk+rzSCR8oUi8Viu745PT2d4OBgWrduTaNGjejfvz9LlizBz8+PmjVrsnXrVs6cOQNAu3btbHfGqlmzJp07dyYyMrLEsy9atIhFixZx4MABkpOTbd+cG41GBgwYwK5du0hPT+fee+9l8+bN7Ny5E7g6X0b9+vVtP1+buK+ks8+dO5d9+/Zx7NgxMjMzAahatSqPPPIIv/32GwBt27bl22+/JSkpCbhaTQ8JCQHAzc2NgICAEs0OsGbNGsaOHcuZM2e4cOECFy9edIjsFouFJUuWMGbMGNLT020T30LpP2eu5b92K8/Tp0+TmJjoMPktFguLFy9myJAhbN26lfPnz9veQ0p79oKCAhYtWsTkyZPZsGED27dvJycnByj957yIlE49e/bk+eefx83Nzd5RSr3KlSvz6KOP6ljdQoUKFejatauOUxHZa/S1o/H09KRLly5l+rxSgUfKjF9++YXXXnuNpUuXAldfwEeOHCEjIwO4euvFdu3asWDBAh577DFyc3NZtGgRq1atYtmyZbbbeNrDgQMHePvtt8nKyiIwMJAlS5bg6upKQkICx44dA67+0fjEE0/w5Zdf0rFjR5o0acL69et56623KCgoIDg42C7Z9+7dy4gRI8jOzqZRo0Z89dVXhIaGcvDgQRITE223G+zYsSPfffcdjz76KNWqVWPZsmUMHz4cT09PKleubJfsVqsVgNzcXNzd3YmLiyMyMpITJ05w8uTJUp394MGDvP766+Tk5DBu3Dj8/Pxo0qQJhw4dKvXnzDUbNmwgOTmZyZMnExERQfPmzTl8+HCpz79z506GDx8OXL0l8PHjx2nUqBHHjh0r9dkzMzOZPn062dnZ9OjRg+3btxMWFsa+fftK/etVREqva19IiYiIfekuWlIm5Obmsn37dh5++GHWr19Phw4dCAoKonbt2ixYsIA33ngDgH79+vH++++TmZnJU089xdatWzly5AhDhw6167W9BoOBhx56iA4dOgCQmJiIyWSib9++zJ49m5iYGCwWC5GRkSQkJJCWlkbr1q2pV68eV65coWrVqnbL7u/vz4ABA4iIiABgy5YteHt789hjj/H1118zatQoLBYLYWFhpKamkp+fT8+ePWnZsiVms5kaNWrYLbvBYMBisXDp0iUefPBB9u/fz++//85TTz1lG1lSWrOXK1eOnJwcnn/+eQCSk5MJCgqiZ8+ezJs3jw8//LDUnjNwtbiWmppKt27d8Pb25siRI9SoUYPOnTuzcOFCxo8fX2rzlytXjkGDBhEWFkZubi5btmzh8uXL9OjRg7lz5zJx4sRSmz03N5fz588zbNgwADZv3oyfnx+PPfYYS5Ys4e233y6157yIiIiI/DWV26VM8PT05MUXX6R79+40adLEdmeal156iX379nHkyBEAPDw8bCN1XF1duffee3nxxRftPnFbaGgobdu2tV1eVr9+fdLS0ujUqRMWi4UffvgBo9HIhQsXbN+ww9XZ4O39h3pQUBARERFkZ2czYcIEjh8/zrJly6hWrRpJSUls2LDBNgFjfn6+bdLqwMBAu/+xaLFYMBqN+Pr64uHhQZMmTdi4cSP16tXj1KlTbNq0qdRmDwkJoXXr1kydOpVZs2bx2WefMXHiRIKCgsjIyCAuLg6DwVAqzxm4WlzLyMhg27Zt/PDDD8ydO5dZs2aRk5NDYmIi69evByiV+Rs2bEhYWBhwdWJoV1dXcnNz6d69O2azuVS/Xv39/fHw8CA2Npb333+fw4cP8+233+Li4sLhw4f59ddfS+05LyIiIiJ/zWC9do2CSBlx6dIlYmJi6N27N82bN2fNmjXs3r2byMhI0tLS2LNnD6NGjcLb29veUW8qNjaWWrVq0bNnT06ePMm6detIS0sjOTmZqKgoevXqZe+IN7R27Vq6du3Kpk2bSEtLIzMzk3PnztnuGvHQQw/RtWtXe8e8zieffMKrr76K2Wxm7NixuLu706JFC44dO4a7u3upzZ6dnc3o0aNp3749vXv3Ji4uznZJ4qVLlzCZTKSkpPDAAw+UynMmKSmJ2bNnU7NmTQYOHEhKSgq///47v/32G7Vr1yY5ObnUn/MA48ePp3Hjxjz22GMcPXqU9evXk5aWVmqP/bXC2qFDh/if//kf9u3bx6lTpzh06BAuLi5YrVZOnDhBr169St05LyIiIiI3pwKPlEk//fQTGzdu5L333gNg9+7dJCQkkJ6eztNPP237Rr20uTaCZ9KkSbz44osEBgaSmpqKj48Pp0+fJiAgAD8/PzunvJ7Var3udqiTJk2ie/fuhIeHs3fvXkJCQkrtcf/22285e/Ysp06dwsvLCxcXF0aOHIm7uzs7duwo1dkvXbpExYoVbb9/+OGH9OzZkyZNmrB//36CgoJK5TkDkJeXx5w5czh16hQxMTEAxMXFkZeXR7du3UhISCjV+a+NAPv55585ceIEzz//PK6urlgsFg4dOkRgYGCpzR4fH8+pU6d47rnnAPjiiy8IDQ2lVatW7Nu3r1Sf8yIiIiJyY7pES8oci8VCly5dqFChAnPnzmXevHn4+fnRr18/Xn/99VL9R4vBYKCgoAAfHx9OnTrFpEmTWLZsGQaDgfDw8FL7x+J/F3fOnTtHfn4+7u7uuLu707Jly1J93K1WKxkZGbzwwguMHz+e0NBQVq9eDVDqs/+5uJOamkpBQYHtsppGjRqV2nMGwN3dnaeffhqLxWK7q92vv/6Ki4sLBoOh1Oe/NqnotdftteKO0WikYcOGpTp7YGAgFy5c4MiRI1y+fJnjx49jtVrx8PAo9ee8iIiIiNyYJlmWMufa/BEZGRkcOHCAxx9/3K53yLod1y5l2rRpEyaTifvvv5/OnTvbO1aRWCwW0tPTWbx4MadPn6ZLly52n9uoqHr27Mljjz0GXC329OzZs1DhpDSzWq1kZmby+eefc+bMGaKioqhXr569YxVZxYoVGTBgAPv37+f777/ngQceICoqyt6xbkutWrVYvnw5ZrMZV1fH+FgNDQ2lXr16fP3112RkZNCtWzfuu+8+e8cSERERkb9Bl2hJmbRixQrS09Pp168fbm5u9o5zWy5cuMCGDRvo2bOnw2W/fPkyv/32G/fff7/DZQcoKCjAxcXF3jFuW25uLhs3bqRTp04OedyvuTb6xZFcuzzRUc8dk8mEn5+fwxSmREREROTmVOCRMskR/1AUERERERERuVMq8IiIiIiIiIiIODgNcRARERERERERcXAq8IiIiIiIiIiIODgVeEREREREREREHJwKPCIiIiIiIiIiDk4FHhERERERERERB6cCj4iIiIiIiIiIg1OBR0RERERERETEwanAIyIiIiIiIiLi4FTgERERERERERFxcCrwiIiIiIiIiIg4OBV4REREREREREQcnAo8IiIiIiIiIiIOTgUeEZEScvbsWTw8PAgKCsJsNts7joiIiEixUJ9HxD5U4BERKSFz586lZ8+eVKxYkZUrV/7lsnl5eSWUSkREROTuup0+j4jcPSrwiIiUAIvFwty5c3n++ed57rnnmDVrVqHnQ0JCePfddxk0aBCVK1fmvvvuA2Dnzp107doVb29vqlSpwmOPPcapU6ds6508eZLHHnuMoKAgvLy8aNy4MQsXLizRtomIiIhcc6s+z4ULF+jduzfly5enatWqjBkzhueee46oqKhCy/3v//4v4eHheHp6EhYWxoQJEzQaSOQWVOARESkBP/zwA1euXKFbt27079+fdevWkZiYWGiZGTNmEBAQwJYtW5g/fz4HDhygY8eOtG3blh07dvDzzz/j4uJCly5dyM3NBSAzM5POnTvzww8/sG/fPgYOHMgLL7zAL7/8YodWioiIiLO7VZ/nhRde4Pfff2fVqlX8/PPPnDlzhu+++67QNsaNG8fHH3/MxIkTOXjwINOnT+ezzz5j/PjxJdsYEQdjsFqtVnuHEBEp6x5++GHq1q3LlClTAPjHP/5By5Yt+eCDD4CrI3jq1KnDunXrbOs8//zz5ObmsnjxYttjV65coVKlSixatIhHHnnkpvsKCAhg9uzZxdcgERERkRv4qz7P0aNHqVevHnFxcTzwwAMA5OfnExoaSv369YmLiyM7Oxt/f3+WL1/OP/7xD9t2v/jiC15//XUuXbpkj2aJOASN4BERKWZnz57lP//5D88//7ztseeee4558+YVGmrcunXrQutt376db7/9Fm9vb9t/lStXJjc3l6NHjwKQnZ3NyJEjiYiIwM/PD29vb1avXl3oMi4RERGRknCrPs+BAwcAiIyMtD3v5uZGy5Ytbb8nJCSQk5PD448/XqgP9Morr3D58mXOnz9fYu0RcTSu9g4gIlLWzZ07l4KCAu65555CjxcUFLBy5UoeffRRAMqXL1/oeYvFQv/+/Rk5cuR126xcuTIA0dHRfP/990ydOpX69etTvnx5hg8fzuXLl4upNSIiIiI3dqs+j9F4dXyBwWC46TYsFgsA33zzDfXq1bvueT8/v7uYWKRsUYFHRKQYXZtocPTo0Tz11FOFnvvwww+ZNWuWrcDz31q2bMnevXupU6fOTTtCGzZsoF+/fvTp08e2vyNHjlC1atW72xARERGRv1CUPs+MGTMA2LJli+0SLbPZzM6dO23FnIiICDw9PTlx4gTdu3cv2UaIODgVeEREitEPP/zA6dOneeWVVwgODi703PPPP0+3bt2um2z5mtGjR9O6dWueeeYZhg4dSpUqVUhMTOS7775j6NChtuvVv//+e9sw5qlTp5KcnKwCj4iIiJSoovR53NzceOihhxg8eDCfffYZVapUYcqUKWRkZNi+zPL29mb06NGMHj0ag8FAVFQUZrOZffv2sXv3bmJiYuzRPBGHoDl4RESK0axZs2jTps11HR2Azp074+fnx5w5c264boMGDdi8eTOZmZk8+OCDNGzYkJdffpmcnBwqVqwIwLRp06hVqxb3338/DzzwANWrV+eJJ54oziaJiIiIXKeofZ758+fTqFEjunXrRqdOnahevTpdunTB09PTtvyYMWOYOnUqs2fPpmnTptx7771MmzaNkJCQEmyRiOPRXbRERERERETELgoKCggPD6dXr162O2+JyJ3RJVoiIiIiIiJSIjZs2IDJZOKee+7hjz/+YNq0aSQmJha685aI3BkVeERERERERKREFBQU8MEHH3Ds2DHc3Nxo1KgRv/zyC40bN7Z3NBGHp0u0REREREREREQcnCZZFhERERERERFxcCrwiIiIiIiIiIg4OM3BIyUqOTnZ3hFKlL+/P2lpafaOUaLUZuegNjsHR21zUFCQvSOIk3Kmfo6jvj/cCWdqKzhXe52preBc7S3rbb1ZX0cjeEREREREREREHJwmWS5j+vbtS3BwsO336OhoAgIC7JiosNM9Wto7goiIlDIus1fc1e1pBE/ZsHz5cjZt2oTRaMRgMDBw4EDCwsLuyrb79+/PwoUL78q2/kz9HBERuZGS6uvoEq0yxt3dncmTJ9/wOavVitVqxWjUwC0REREpvY4cOcLOnTuJiYnBzc2NjIwMzGazvWOJiIiUairwlHEmk4kJEyYQFhbGiRMnGDVqFN999x3Hjx8nLy+PyMhI+vTpA8DgwYPp2LEjO3fuxGw2M2zYMKpXr05ubi7z5s3j+PHjGAwGnnjiCSIjI/n9999ZunQpZrOZqlWrMmjQIDw9Pe3cYhEREXF0Fy9exMfHBzc3NwB8fX05duwY8+bNY8SIEWzfvp1PPvmEzz//HIvFwrBhw5g5cyapqanMnTuXjIwMPDw8eOWVV6hevTomk4np06eTm5tLq1atCu1rxYoVbNmyhfz8fFq3bk2fPn0wmUxMnDiR+vXrc+TIEfz8/Hjrrbdwd3e3x+EQEREpEhV4ypi8vDyio6MBCAgI4LnnniM1NZXBgwdTr149AJ566im8vb2xWCy89957nDp1ilq1agHg4+NDTEwMP/74IytXruTVV19l2bJleHl5MWXKFAAyMzPJyMhg+fLljBkzBk9PT7777jtWrVrFE088UShPXFwccXFxAEyaNKmkDoOIiDgQf39/e0eQUqZp06YsW7aMoUOH0rhxY9q1a0f9+vVJTEwE4ODBgwQHB3Ps2DEsFgt169YFYNasWbz88stUq1aNo0ePMmfOHMaOHcv8+fPp2rUrHTt2ZM2aNbb9/P7776SkpPDhhx9itVr56KOPOHDgAP7+/qSkpDB06FBeffVVpk6dytatW+nQoUOhnOrniIhIUZRUX0cFnjLmvy/RMplM+Pv724o7AJs3b2bdunUUFBRw8eJFzpw5YyvwtGnTBoDQ0FC2bdsGwL59+3jjjTds63t7e7Nz507OnDnDmDFjADCbzYX2cU1UVBRRUVF3vZ0iIlJ23O27XGgOHsfn6elJTEwMBw8eJCEhgWnTptGvXz+qVq3KmTNnOH78OD169ODgwYNYLBYaNGhAbm4uhw8fZurUqbbtXLus6/DhwwwfPhyADh068NVXXwFXCzx79+7lrbfeAiA3N5fU1FT8/f0JCAggJCQEuNovOn/+/HU51c8REZGiKKm+jgo8TuDPl02ZTCZWrlzJxIkT8fb2JjY2lvz8fNvzrq5XTwmj0UhBQcFNt2m1WmncuHGhwo+IiIjI3WI0GomIiCAiIoLg4GDi4+Np0KABe/bswcXFhSZNmhAbG4vFYqF///5YLBbKly9/07kIDQbDDR9/5JFH6NKlS6HHTCaT7fKwa1ny8vLuXuNERESKgQo8TiY7OxtPT0+8vLy4dOkSe/bsISIi4i/XadKkCT/++CPPP/88cPUSrXr16jF37lxSU1MJDAwkNzeX9PT0W35rerdnDy/t/P3973q1trRTm52D2uwcnLHNUjokJydjMBioVq0aAImJiVSpUoUGDRowc+ZMOnbsiK+vL5mZmVy6dImaNWtiMBgICAhgy5YttG3bFqvVyqlTpwgJCaF+/fr8+uuvdOjQgU2bNtn207RpU5YsWcJ9992Hp6cn6enpuLi43HFuZ+rnONP7gzO1FZyrvc7UVnCu9jpTW/9MBR4nExISQkhICG+++SaVK1emfv36t1zn8ccfZ86cOQwfPhyj0cgTTzxBmzZtGDx4MNOnT7eNAHryySc1LF5ERET+tms3eMjKysLFxYXAwEAGDhyIp6cnly9fpkGDBgAEBwfj6+trG53z+uuvM3v2bJYvX47ZbKZ9+/aEhITwwgsvMH36dL7//vtCkyw3bdqUs2fP8s477wBXRz0PGTJEdxwVERGHZLBarVZ7hxDnkZycbO8IJcoZK8dqs3NQm52Do7ZZXzaIvThTP8dR3x/uhDO1FZyrvc7UVnCu9pb1tt6sr6OvJ0REREREREREHJwKPCIiIiIiIiIiDk4FHhERERERERERB6c5eBzU8uXL2bRpE0ajEYPBwMCBAwkLC7sr2+7fvz8LFy68K9v6b6d7tCyW7YqIOAJHu8OOo16/rjl4HEffvn0JDg6moKAAFxcXOnToQI8ePUrNJMe32ydSP0dEpHRztL7Yzdysr6O7aDmgI0eOsHPnTmJiYnBzcyMjIwOz2WzvWCIiIiK3xd3dncmTJwNw+fJlZsyYQU5ODn369LFrLqvVir4DFRERR6MCjwO6ePEiPj4+uLm5AeDr68uxY8eYN28eI0aMYPv27XzyySd8/vnnWCwWhg0bxsyZM0lNTWXu3LlkZGTg4eHBK6+8QvXq1TGZTEyfPp3c3NxCtw4FWLFiBVu2bCE/P5/WrVvTp08fTCYTEydOpH79+hw5cgQ/Pz/eeust3N3d7XE4REREpAyoUKECAwcOZNSoUfTu3Rur1cpXX33FgQMHyM/P58EHH6RLly4kJCTwzTff4OPjw+nTpwkNDWXIkCEYDAYGDx5M+/bt2b17Ny4uLgwcOJCvv/6a1NRUHnroIbp27Upubi4fffQRWVlZmM1mnnzySVq1aoXJZGLChAmEhYVx4sQJRo0aZcuWkZFBTEwMjz/+OM2bN7fjURIREbk5FXgcUNOmTVm2bBlDhw6lcePGtGvXjvr165OYmAjAwYMHCQ4O5tixY1gsFurWrQvArFmzePnll6lWrRpHjx5lzpw5jB07lvnz59O1a1c6duzImjVrbPv5/fffSUlJ4cMPP8RqtfLRRx9x4MAB/P39SUlJYejQobz66qtMnTqVrVu30qFDh+uyxsXFERcXB8CkSZOK/+CIiJRi/v7+9o5wW1xdXR0uszi2qlWrYrFYuHz5Mjt27MDLy4uJEyeSn5/PmDFjaNq0KQAnT55k6tSpVKpUiTFjxnD48GHCw8OBq6+zyZMns2DBAj799FPef/998vPzGT58OF27dsXNzY0RI0bg5eVFRkYG77zzDi1bXr20KjU1lcGDB1OvXj1bpkuXLvHRRx/x5JNP0qRJk0J51c8REXEsZb1fowKPA/L09CQmJoaDBw+SkJDAtGnT6NevH1WrVuXMmTMcP36cHj16cPDgQSwWCw0aNCA3N5fDhw8zdepU23auXdZ1+PBhhg8fDkCHDh346quvgKsFnr179/LWW28BkJubS2pqKv7+/gQEBBASEgJAaGgo58+fv2HWqKgooqKiiutQiIg4FEebz0Zz8Ig9/f777yQlJbF161YAsrOzSUlJwdXVlbp161K5cmUAQkJCMJlMtgLPtWJNcHAwubm5lCtXjnLlyuHq6kpWVhYeHh58/fXXHDx4EIPBQHp6OpcvXwaunvN/Lu4UFBTw/vvvM2DAABo2bHhdRvVzREQciyP2a25Ec/CUMUajkYiICCIiIggODiY+Pp4GDRqwZ88eXFxcaNKkCbGxsVgsFvr374/FYqF8+fK269z/m8FguOHjjzzyCF26dCn0mMlksl0edi1LXl7e3WuciIiIOKVz585hNBqpUKECVquVF154gWbNmhVaJiEh4bp+iMVisf3u6upqe/y/lysoKGDTpk1kZGQwadIkXF1dGTx4sK0f4+npWWhfLi4u1K5dmz179tywwCMiIlKaqMDjgJKTkzEYDFSrVg2AxMREqlSpQoMGDZg5cyYdO3bE19eXzMxMLl26RM2aNTEYDAQEBLBlyxbatm2L1Wrl1KlThISEUL9+fX799Vc6dOjApk2bbPtp2rQpS5Ys4b777sPT05P09HRcXFz+VvayMmt5UTnqt99/h9rsHNRmEbnbMjIymD17Nv/4xz8wGAw0a9aMtWvX0qhRI1xdXUlOTsbPz+9v7yc7O5sKFSrg6urK/v37bzoK+ZpBgwYxdepUvvvuOx555JG/XNaZ+jnO9J7oTG0F52qvM7UVnKu9ztTWP1OBxwHl5uYyb948srKycHFxITAwkIEDB+Lp6cnly5dp0KABcHVosq+vr210zuuvv87s2bNZvnw5ZrOZ9u3bExISwgsvvMD06dP5/vvvC02y3LRpU86ePcs777wDXP1Wa8iQIaXm1qUiIiLi2PLy8oiOjrbdJv2+++6jZ8+eAHTu3BmTycTbb78NXL2pRHR09N/e57333ktMTAzDhw+nTp06VK9e/S+XNxqNDB06lI8++ohy5crx4IMP/u0MIiIixcFg1T0gpQQlJyfbO0KJcsbKsdrsHNRm5+CobdYcPGIvztTPcdT3hzvhTG0F52qvM7UVnKu9Zb2tN+vraCiGiIiIiIiIiIiDU4FHRERERERERMTBqcAjIiIiIiIiIuLgNMmyk1i+fDmbNm3CaDRiMBgYOHAgYWFht7WNHTt2cObMmVveQeKvFLzc647XdUTn7B3ADtRm5+DsbXamO+WIlJT+/fuzcOFC2+/x8fEcP36cAQMG2DHV7XGmfo4zfQ44U1vBudrrTG2Fm7dX/ZqyQwUeJ3DkyBF27txJTEwMbm5uZGRkYDabb3s7LVu2pGXLlsWQUERERKT0uHZXLxEREUeiAo8TuHjxIj4+Pri5uQFXbzMKMHjwYNq2bcvu3btxd3dn6NChBAYGsmPHDtut1H18fBgyZAgVK1Ys9E1abGws5cqV48SJE1y6dIlnnnmGyMhIezZTREREyqjY2FhatGhh62tcG+2TkJDAN998g4+PD6dPnyY0NJQhQ4ZgMBjYtWsXX3zxBR4eHtSvXx+TycTIkSM5duwY8+fPJz8/H3d3dwYNGkRQUBDx8fH89ttv5ObmYrFYqFKlCq1bt6Z169YAzJgxg7Zt29KqVSt7HgoREZGbUoHHCTRt2pRly5YxdOhQGjduTLt27WjYsCEAXl5eTJkyhfXr17NgwQJGjhxJeHg4EyZMwGAwsG7dOlasWMGzzz573XYvXbrEe++9R3JyMjExMTcs8MTFxREXFwfApEmTirehIiIlxN/f394RSoSrq6vTtFXsLy8vj+joaNvvmZmZRRo5fPLkSaZOnUqlSpUYM2YMhw8fJjQ0lNmzZzN+/HgCAgL45JNPbMsHBQXx3nvv4eLiwt69e1m0aBEjRoywbevjjz/G29ubAwcOsGrVKlq3bk12djaHDx9m8ODBhfatfo6IlAVl8bPeWfswKvA4AU9PT2JiYjh48CAJCQlMmzaNfv36AdC+fXvb/z///HMA0tPT+eSTT7h48SJms5mAgIAbbrdVq1YYjUZq1KjB5cuXb7hMVFQUUVFRxdAqERH7SUtLs3eEEuHv7++QbQ0KCrJ3BLkD7u7uTJ482fb7tZHDt1K3bl0qV64MQEhICCaTCU9PTwICAmx9mHvvvddWiMnOziY2NpbU1FTg6uVY1zRp0gRvb28AGjZsyJw5c8jIyGDr1q20adPmusu21M8RkbLAET/rb8VR+zBFdbO+jgo8TsJoNBIREUFERATBwcHEx8cDYDAYbMtc+3nevHn07NmTli1b2oY+38i1S74ArFZr8YUXERERp+bi4oLFYgHAYrEUmkvwz/0Ro9FoW+5mlixZQkREBNHR0ZhMJsaPH297zsPDo9CyHTp0YMOGDWzevJlBgwbdjaaIiIgUGxV4nEBycjIGg4Fq1aoBkJiYSJUqVTh9+jSbN2/mkUceYfPmzba7amVnZ+Pn5wfA+vXr72oWZ5uhvaxXjm9EbXYOarOIlKQqVapw4sQJ2rVrx44dOwqNurmRoKAgTCYTJpOJgIAANm/ebHvuz/2ca1943UynTp0YPXo0FStWpEaNGrfM6Uz9HGd6T3SmtoJztdeZ2grO115npAKPE8jNzWXevHlkZWXh4uJCYGAgAwcOZNeuXWRmZjJixAjc3NwYOnQoAL1792bq1KmUL1+eRo0aYTKZ7NwCERERcWYPPPAAkydPJjo6mqZNm1430ua/ubu7M2DAAD788EM8PDyoU6eO7bmHH36Y2NhYli9fTvPmzf9yOxUrVqR69eqaWFlERByCwapra5zW4MGDmThxou2uWiUhOTm5xPZVGjhjlVxtdg5qs3Nw1DZrDh6Bq19weXp6YrVamTt3LoGBgfTs2fO2tnHlyhVGjBhBTEwMXl5et1zemfo5jvr+cCecqa3gXO11praCc7W3rLdVc/CIiIiIiNOIi4tj/fr1mM1mateuTZcuXW5r/b179/Kvf/2LHj16FKm4IyIiYm8q8Dix2NhYe0cQERERKRY9e/a87RE7f9akSRM+/fTTu5hIRESkeBntHUBERERERERERP4ejeApxS5dusTnn3/O0aNHKV++PK6urjz88MO0bt3a3tHuWMHLvewdoUSds3cAO1Cb7cuZ7uAiImVP3759CQ4OxmKxUL16dQYPHnzLCZWvSUxMJD09/ZYTJ9+JpUuX4unpSa9ef92PcaZ+Tmn67CtuztRWcK72Fmdb1ScTe1CBp5SyWq1MnjyZjh072u5udf78eXbs2FGk9QsKCnBxcSnOiCIiIiJ3lbu7O5MnTwZgxowZ/PTTT0W6zKqgoIDExESOHz9eLAUeERERR6ACTym1f/9+XF1d6dq1q+2xKlWq0K1bNywWC1999RUHDhwgPz+fBx98kC5dupCQkMCSJUsoX748ycnJDBw4kKVLl1K+fHmSkpJo27YtwcHBrF69mry8PKKjowkMDGTHjh0sX74cs9mMj48PQ4YMoWLFiixdupS0tDRMJhNpaWl0796d7t27s2TJEry9venRowcAX3/9NRUqVKB79+72OlwiIiJSxoSHh5OUlERmZiaffvopJpMJDw8PBg4cSK1atVi6dCnnzp3DZDJRuXJlDh8+TF5eHocOHeLRRx/lzJkzhUbdDB8+nLfffpuAgACWLVvGxo0b8fX1pXLlyoSGhtKrVy/i4uJYt24dZrOZqlWrMmTIkCKPIBIREbE3FXhKqdOnT1O7du0bPvfzzz/j5eXFxIkTyc/PZ8yYMTRt2hSAkydPMmXKFAICAkhISODUqVNMmzYNb29v/ud//ocHHniAiRMnsnr1atasWcPzzz9PeHg4EyZMwGAwsG7dOlasWMGzzz4LXL3d59ixY8nJyeGNN96ga9eu3H///UyZMoUePXpgsVjYvHkzH3744Q2zxsXFERcXB8CkSZOK4UiJyJ/5+/uXyH5cXV1LbF+lhdosUnIKCgrYs2cPzZo1Y+nSpdSuXZu33nqL/fv3M3PmTNsonzNnzvD+++/j7u5OfHw8x48fZ8CAAcDVy6pu5NixY/z2229MnjyZgoIC3n77bUJDQwFo06YNUVFRACxevJiff/6Zbt263TSn+jkicjOl8fPTmT7Xnamtf6YCj4OYM2cOhw8ftp2oSUlJbN26FYDs7GxSUlJwdXWlbt26BAQE2NarU6cOlSpVAiAwMJAmTZoAEBwczP79+wFIT0/nk08+4eLFi5jN5kLrN2/eHDc3N9zc3KhQoQKXL18mICAAb29vTp48yeXLlwkJCcHHx+eGuaOiomwdJREpfmlpaSWyH39//xLbV2mhNjuOoKAge0eQO3RthDFAgwYN6Ny5M6NHj2b48OEANGrUiMzMTLKzswFo2bIl7u7ut7WPw4cP06pVK9t6LVq0sD13+vRpFi9eTFZWFrm5ubYv0G5G/RwRuZnS+PnpqJ/rd6Kst/VmfR0VeEqpmjVr8ttvv9l+f+mll8jIyGDUqFFUrlyZF154gWbNmhVaJyEh4bphxG5ubrafDQaD7XeDwYDFYgFg3rx59OzZk5YtW5KQkMA333xjW8fV9f+dIkajkYKCAgAeeOAB4uPjuXTpEvfff//dabSIiIg4tT/PwVMUf3X5lIuLC1ar1fZ7Xl7eLbcXGxtLdHQ0ISEhxMfHk5CQUOQsIiIi9qYCTynVqFEjvv76a9auXWubh+dax6RZs2asXbuWRo0a4erqSnJyMn5+fne8r+zsbNv669evL9I6rVu3ZsmSJRQUFNgmgS4KZ5tNvqxXjm9EbRYRkbspPDycjRs38sQTT5CQkICPjw9eXl7XLefp6UlOTo7t9ypVqrBr1y4ATpw4gclkAqB+/frMnj2bRx55BIvFwq5du3jggQcAyM3NpVKlSpjNZjZu3Hjb/Stn6uc402efM7UVnKu9ztRWcQ4q8JRSBoOB6OhoPv/8c77//nt8fX3x9PSkX79+REZGYjKZePvttwHw9fW1DWe+E71792bq1KmUL1+eRo0a2TpAf8XV1ZWIiAjKly+P0Wi8432LiIiI/JU+ffrw6aefMmLECDw8PBg8ePANl2vUqBHff/890dHRPProo0RGRrJhwwaGDRtG3bp1bcPZ69atS4sWLYiOjqZChQrUrFnTVjDq27cvo0ePxtfXl7CwsEIFIxERkdLOYP3z2FWRIrJYLLz99tsMGzaMatWqFXm95OTkYkxV+jjjtwJqs3NQm52Do7ZZc/DIreTm5uLp6cmVK1cYO3YsAwcOtE20/Hc4Uz/HUd8f7oQztRWcq73O1FZwrvaW9bZqDh65a86cOcOkSZNo3br1bRV3REREREqDzz77jDNnzpCfn0/Hjh3vSnFHRETE3lTgkdtWo0YNZs6cae8YIiIiInfkduYPFBERcRSaPEVERERERERExMFpBE8Z0LdvX4KDg22/R0dHM2PGDD744IO/XG/cuHH079+fOnXq/O0MgwcPZuLEifj6+v7lcgUv9/rb+3Ik5+wdwA7U5rvLme7IIiJyp5YvX86mTZswGo0YDAYGDhxIWFjYbW1jx44dnDlzhkceeeSOczhTP8eZPu8dpa3qM4iICjxlgLu7O5MnTy702K2KOyIiIiJlwZEjR9i5cycxMTG4ubmRkZGB2Wy+7e20bNmSli1bFkNCERGRkqECTxnVv39/Fi5cSEJCAt988w0+Pj6cPn2a0NBQhgwZgsFgKLT87NmzOX78OHl5eURGRtKnTx/g6sicjh07snPnTsxmM8OGDaN69er88ccfTJ8+nfT0dOrVq4duxiYiIiL2cPHiRXx8fHBzcwOwjSYePHgwbdu2Zffu3bi7uzN06FACAwPZsWMHy5cvx2w24+Pjw5AhQ6hYsSLx8fEcP36cAQMGEBsbS7ly5Thx4gSXLl3imWeeITIy0p7NFBERuSUVeMqAvLw8oqOjAQgICLD9fM3JkyeZOnUqlSpVYsyYMRw+fJjw8PBCyzz11FN4e3tjsVh47733OHXqFLVq1QLAx8eHmJgYfvzxR1auXMmrr77KN998Q3h4OE888QS7du3i559/vmG2uLg44uLiAJg0adLdbrpImefv72/vCDfk6upaarMVF7VZpHRq2rQpy5YtY+jQoTRu3Jh27drRsGFDALy8vJgyZQrr169nwYIFjBw5kvDwcCZMmIDBYGDdunWsWLGCZ5999rrtXrp0iffee4/k5GRiYmJuWOBRP0dKk7v1fu1M7/3O1FZwrvY6U1v/TAWeMuBGl2j9Wd26dalcuTIAISEhmEym6wo8mzdvZt26dRQUFHDx4kXOnDljK/C0adMGgNDQULZt2wbAwYMHGTFiBADNmzenfPnyN9x3VFQUUVFRf6+BIk4sLS3N3hFuyN/fv9RmKy5qs+MICgqydwQpQZ6ensTExHDw4EESEhKYNm0a/fr1A6B9+/a2/3/++ecApKen88knn3Dx4kXMZjMBAQE33G6rVq0wGo3UqFGDy5cv33AZ9XOkNLlb79eO+t5/J5ypreBc7S3rbb1ZX0cFHidwbcgygNFoxGKxFHreZDKxcuVKJk6ciLe3N7GxseTn59ued3V1ta1bUFBQMqFFREREishoNBIREUFERATBwcHEx8cDFLok/drP8+bNo2fPnrRs2dJ2KfuN/Ln/pEvRRUTEEajAI2RnZ+Pp6YmXlxeXLl1iz549RERE/OU6DRo0YNOmTTz++OPs3r2brKysIu3L2Wb3L+uV4xtRm0VEpCQlJydjMBioVq0aAImJiVSpUoXTp0+zefNmHnnkETZv3my7q1Z2djZ+fn4ArF+//q5mcaZ+jjN99jlTW0XEsanAI4SEhBASEsKbb75J5cqVqV+//i3X6d27N9OnT2fYsGHUq1fPKa9vFBEREfvLzc1l3rx5ZGVl4eLiQmBgIAMHDmTXrl1kZmYyYsQI3NzcGDp0KHC1DzN16lTKly9Po0aNMJlMdm6BiIjI3WGwasyplKDk5GR7RyhRzviNj9rsHNRm5+CobdYcPAJX76I1ceJE2121SoIz9XMc9f3hTjhTW8G52utMbQXnam9Zb+vN+jrGEs4hIiIiIiIiIiJ3mS7REhEREZEyJzY21t4RRERESpRG8IiIiIiIiIiIODiN4ClD+vbtS3BwMBaLherVqzN48GA8PDxuuGx8fDzHjx9nwIABf3u/S5cuxdPTk169et1y2YKXb71MWXLO3gHsQG0uzJnuqCLiqPr378/ChQsB2LVrF59//jnvvvsuu3fvxsPDg44dO/7tfdzNz92iOHjwILNnz8bFxYUJEybg7u4OQFZWFps2beLBBx8EICEhgZUrVzJy5Mg72s/SpUtZsWIFsbGxVKhQASh8PG9m+fLlPPbYYwCYTCZiYmKYMmXKHWUA+/Vr/psz9XOuffbpc05EpPTQCJ4yxN3dncmTJzNlyhRcXV356aef7B1JRETEYezbt4/58+czatQoqlSpQteuXe9KccceNm7cyCOPPMLkyZNtxR24WuBZu3btXd2Xj48PK1euvK11vv3227u2/4KCgru2LREREUemETxlVHh4OElJSWRmZvLpp59iMpnw8PBg4MCB1KpVq9CyO3bsYPny5ZjNZnx8fBgyZAgVK1Zk6dKlpKWlYTKZSEtLo3v37nTv3h24+s3b+vXr8fX1pXLlyoSGhtqjmSIiInfFgQMH+Oyzzxg1ahSBgYFA4ZEc48aNo27duiQkJJCdnc2rr75KgwYNuHLlCrGxsZw+fZqgoCAuXrzIgAEDqFOnDr/88gvfffcdXl5e1KpVCzc3N+DqiJX/+7//448//sDX15dBgwbh7+9PbGws7u7uJCYmcvnyZV577TXWr1/P0aNHqVu3LoMHD74u9759+1i4cCEFBQXUqVOHl19+mQ0bNrBlyxZ+//139uzZw+uvv25bftGiRaSmphIdHU2TJk1o3rw5ubm5TJkyhdOnTxMaGsqQIUMwGAycOHGCzz//nNzcXFvOSpUqXZfh/vvvZ/369TzyyCN4e3sXem7Dhg388MMPmM1mwsLCeOmll/j666/Jy8sjOjqamjVr8uSTT2KxWPjXv/7FkSNH8PPz46233sLd3Z3U1FTmzp1LRkYGHh4evPLKK1SvXp3Y2Fjc3NxITEykfv36hfo2d7Nfs3r1an766SdcXFyoUaMGb7zxxt870URERIqRCjxlUEFBAXv27KFZs2YsXbqU2rVr89Zbb7F//35mzpzJ5MmTCy0fHh7OhAkTMBgMrFu3jhUrVvDss88CV2/3OXbsWHJycnjjjTfo2rUrSUlJ/Prrr3z00UcUFBTw9ttv37TAExcXR1xcHACTJk0q3oaLlEL+/v72jlAsXF1dy2zbbkZtLrvMZjOTJ09m3LhxVK9e/abLWSwWJk6cyK5du1i2bBljxozhxx9/xNvbm2nTppGUlMRbb70FwMWLF1m6dCkxMTF4eXkxfvx4QkJCAJg3bx4dO3akU6dO/Pzzz8ybN8+2XlZWFh988AE7duzgo48+4v3336dGjRqMGjWKxMRE2zYA8vLy+PTTTxkzZgxBQUHMnDmTtWvX0qNHDw4dOkSLFi2IjIws1Iann36a06dP2/oCCQkJnDx5kqlTp1KpUiXGjBnD4cOHqVu3ri2Xr68vmzdv5uuvv2bQoEHXHRdPT0/uv/9+Vq9eTZ8+fWyPnzlzhs2bN/P+++/j6urKnDlz2LhxI/369WPNmjW2DCaTiZSUFIYOHcqrr77K1KlT2bp1Kx06dGDWrFm8/PLLVKtWjaNHjzJnzhzGjh0LQHp6Oh988AFGo5H4+Hjbfu9mv+b7779n5syZuLm5kZWVdV3b1c8pu59zf+Ys74XXOFN7namt4Fztdaa2/pkKPGXItW/DABo0aEDnzp0ZPXo0w4cPB6BRo0ZkZmaSnZ1daL309HQ++eQTLl68iNlsJiAgwPZc8+bNcXNzw83NjQoVKnD58mUOHjxI69atbfP7tGzZ8qaZoqKiiIqKuttNFXEYaWlp9o5QLPz9/cts225GbXYcQUFBt7W8i4sL9evX5+eff+aFF1646XKtW7cGIDQ0FJPJBMChQ4dso0CCg4NtI0mOHj1KREQEvr6+ALRt25aUlBTbcyNGjACgQ4cOfPXVV7Z9tGjRAoPBQHBwMBUqVCA4OBiAmjVrYjKZChV4kpOTCQgIsLW3Y8eO/Pjjj/To0eO22l+3bl0qV64MQEhICCaTCS8vL06fPs37778PXC1u3Wj0zjXdunXjrbfe4qGHHrI9tn//fk6ePMmoUaOAq/2Ua8fjvwUEBNjaFhoayvnz58nNzeXw4cNMnTrVtpzZbLb9HBkZidF4/WwDd7NfExwczIwZM2jVqpXt3//P1M8pu59zf+ao74V3ypna60xtBedqb1lv6836OirwlCHX5uC5XfPmzaNnz560bNmShIQEvvnmG9tzrq7/7xQxGo26zl1ERMocg8HAm2++yXvvvVdo8t//du0SK6PRiMViKZYs1/ZhMBhsP1/7vbj3CYXbVqNGDSZMmFCkbZQvX5727dvz448/2h6zWq107NiRp59++rYz5OXlYbFYKF++/E37Np6enjd8/G72a0aNGsWBAwfYuXMn3377LR9//DEuLi63bI+IiIg9qMBTxoWHh7Nx40aeeOIJEhIS8PHxwcvLq9Ay2dnZ+Pn5AbB+/fpbbrNBgwZ8+umnPProoxQUFLBz584if3vlbHdaKOuV4xtRm0XEEXl4eDBq1Cj++c9/UrFiRTp37lyk9cLDw9myZQuNGjXizJkzJCUlARAWFsaCBQv4448/KFeuHFu3brWN7qlXrx6bN2+mQ4cObNq0ifDw8DvKHBQUhMlkIjU1lcDAQDZs2EDDhg3/cp1y5cqRk5NTpG1nZGRw5MgR6tWrh9lsJiUlhZo1a950nZ49ezJq1Chbgahx48Z89NFH9OjRgwoVKpCZmUlOTg5VqlTB1dUVs9lcqODy37y8vAgICGDLli20bdsWq9XKqVOnCo1iupG71a+xWCykpaXRqFEjwsPD2bx5M7m5uZQvX/6m23Kmfo4++0RESh8VeMq4Pn368OmnnzJixAg8PDxuOEFj7969mTp1KuXLl6dRo0a2Yec3ExoaSrt27YiOjsbX15c6deoUV3wREZES4+3tzejRoxk7duxNLyX6b127diU2NpY333yT6tWrU6NGDby8vKhUqRK9e/fm3XffxcvLq1BR4sUXX+TTTz9lxYoVtsmL74S7uzuDBg1i6tSptkmWu3Tp8pfr+Pj4UL9+fYYPH06zZs1o3rz5DZdzdXVl+PDhzJ8/n+zsbAoKCujevftfFnh8fX1p3bo1//nPf4CrI4CefPJJPvjgA6xWKy4uLgwYMIAqVarwwAMPEB0dTe3atXnyySdvus3XX3+d2bNn2yZNbt++/S0LPHerX2OxWPjf//1f26Xt3bp1+8vijoiIiL0ZrFar1d4hxHkkJyfbO0KJcsZvt9Rm56A2OwdHbfPtzsHzd1gsFsxms+2OT++//z7Tp0//y5EpUnY5Uz/HUd8f7oQztRWcq73O1FZwrvaW9bZqDh4RERGRu+zKlSuMHz+egoICrFYrL730koo7IiIiYhfqgYiIiIjcoXLlyjnt7bFFRESkdLn+3pIiIiIiIiIiIuJQNILHifXv35+FCxdiMpk4cuQI9957718ubzKZiImJYcqUKXe8z4KXe93xuo7onL0D2IGzttmZ7pwiIgL/rx/h7Bn+zJn6Odc+7/X5JyJSemgEj3D+/Hk2bdpk7xgiIiIidldQUGDvCCIiIndEI3iERYsWcebMGaKjo+nYsSOtW7dm5syZXLlyBbh6O9f69esXWmfs2LG88MILtluVjhkzhgEDBtzy1qUiIiJSdo0bN47+/ftTp04dMjIyGDVqFLGxsaxatYqkpCQGDRpEUlIS06dP58MPP+TixYvMnTuXjIwMPDw8eOWVV6hevTqxsbG4u7uTmJjI5cuXee2111i/fj1Hjx6lbt26DB482LbPBQsWsHfvXipWrMgbb7yBr68viYmJzJ49mytXrlC1alVee+01vL29b5ovPj6e3377jdzcXCwWC6NHjyY2NpbTp08TFBTExYsXGTBggO0W6iIiIqWRCjzC008/zcqVKxk5ciRw9Y4g7777Lu7u7qSkpDB9+vTrJpC8//77iY+P5/nnnyc5OZn8/PwbFnfi4uKIi4sD0CSUUqb5+/vbO0KJcnV1VZudgDO2WYpH9+7dGT9+PNu2bWP58uW8/PLLeHh4MGvWLF5++WWqVavG0aNHmTNnDmPHjgUgKyuLDz74gB07dvDRRx/x/vvvU6NGDUaNGkViYiIhISFcuXKFOnXq8Pzzz7Ns2TK++eYbBgwYwMyZM3nxxRdp2LAhS5YsYdmyZTz//PN/mfHkyZN8/PHHeHt7s2LFCry9vZk2bRpJSUm89dZbN1xH/Rzn+PxztvdCZ2qvM7UVnKu9ztTWP1OBR65TUFDA3LlzSUxMxGg0kpKSct0ybdu25d///jfPPPMMv/zyC506dbrhtqKiaYuOPQAAshRJREFUooiKiirmxCL2l5aWZu8IJcrf319tdgKO2uagoCB7R5D/YjQaGTRoECNGjKBLly6Eh4eTm5vL4cOHmTp1qm05s9ls+7lFixYYDAaCg4OpUKECwcHBANSsWROTyURISAgGg4F27doBcN999/Hxxx+TnZ1NVlYWDRs2BKBjx45MmzbtlhmbNGmCt7c3AIcOHaJ79+4ABAcHU6tWrRuuo36Oc3z+Oep74Z1ypvY6U1vBudpb1tt6s76OCjxynVWrVlGhQgUmT56M1WqlX79+1y3j4eFBkyZN2LFjB1u2bHHab61ERETk/3FxccFqtQKQn59f6LmUlBQ8PT1JT08HwGKxUL58eSZPnnzDbbm5uQFgMBhsP1/73WKx3HAdg+H/Y+/P46qu8////3YORw6yuiAqLiGCYpKamNCKFulkvq0ZK1vGFp2ckrFyYVwmU1NTZNBspJnGJfu2KTlOZb8yQ8OtzG1KPWmZSy5gJ9RSgQMcOL8/vHg+EqCIbIfX/Xq5fC4fOOf1ej6fd6bz8vF+nNdiqvL6rFbrJfcVERGp79TgERo3bkx+fr7797y8PJo3b47ZbObzzz+vsIi64447SE5OJioqyv2N1+UY7UkLDb1zXB5lFhExrhYtWnDw4EEiIiLYsmWL+/W8vDxef/11pk2bxpIlS9iyZQtxcXGEhITw5ZdfcuONN+Jyufjxxx+v6H5+LpeLLVu2cPPNN7Np0yaioqLw9fXF39+fvXv30qVLFzZs2ECXLl0uub7fioqK4ssvvyQ6Oppjx45x5MiRSq3HSHWO/u0TEal/1OAR2rdvj9lsdt9kuX///qSmprJhwwa6d+9e4Tda4eHhNG7cmL59+9byikVERKSuFRYW8tRTT7l/HzhwIP/3f//HvHnzyMjIoGfPnu73li5dSv/+/QkNDeWpp55i2rRpdOnShWeeeYaFCxeycuVKnE4nN9988xU1eKxWKz/88AMrV64kMDCQ0aNHA5CYmOi+yXJISAgjR44EqHB9v9WvXz/S0tIYPXo0bdq0oW3btvj6+l7hX0hERKR2mVwXzlMVuUKnTp1i2rRpzJs3D7PZXKl9srKyanhV9YsRv91SZmNQZmPw1My6B49crZKSEpxOJ97e3pw4cYLp06czf/58LJZLfzdqpDrHU48PVWGkrGCsvEbKCsbK29Cz6h48Uq3Wr1/PsmXLePTRRyvd3BERERHxBAUFBUybNo3i4mJcLhd/+tOfLtvcERERqWv6l0qqJD4+nvj4+LpehoiIiEi1a9y4sR4gISIiHkenXoiIiIiIiIiIeDidwfMbdrud5ORkUlNT3a+lp6fj4+PDoEGDKtzvwIEDrF+/nmHDhmGz2bBYLHTu3PmK5k5MTGTWrFkEBgZW+PrBgwdJTU1l3LhxnDx5kmPHjnHvvfde0TzlsdlsrFq1igkTJlz1WJdS/GTFf8OG6Ke6XkAdqK3MRnpSiYiI0f3yyy+88cYb7N+/Hz8/PywWC/fccw+9e/eu66WVYqg6579f1PUKRETkN9TgqSYdO3akY8eOwPlmiY+PzxU3eC7nxx9/JDU1ldGjR9OhQwc6dOhAr169qnUOERERkfrE5XKRkpJCfHw8zz77LAA///wz27dvL7VdcXExXl5edbFEERGRekENnis0depUIiIisNls5OXl8dRTT9GlSxf3GTDDhg3js88+w2w2s3HjRoYNG0abNm3497//zcmTJwF47LHHiIqK4uzZs8yfP59Tp07RqVMnLvVAs+PHj5OWlsaoUaOIiIgAIDMzkwMHDjB8+HDS0tJo3LgxBw8e5JdffuGPf/wjcXFxlJSUsGTJEvbs2UPz5s2xWCz07duXuLg4vv76a5YuXYrVai3VjDp37hyvvvoqdrsdq9XKiBEjuOaaa0hPT8dut2O328nJyeGxxx5j//79/O9//6NZs2aMHz9eNyAUERGRarVnzx4sFgv9+vVzv9aiRQvuuusuMjMz+eqrr3A4HJSUlDBx4kSWLFnC0aNHKS4u5v777+eGG26gpKSEt99+m2+//ZaioiL69+/PnXfeCcD777/Pxo0bMZvN9OjRg0ceeYQTJ06wePFizpw5g9Vq5c9//jNt2rSpqz+BiIhIpej/Gq+CkpISZs2axc6dO1mxYgWTJ092vxcSEsKdd95Z6pKu+fPnM3DgQKKiosjJyWHmzJnMmzeP9957j6ioKO677z527tzJunXrKpxzzpw5jBo1iqioqAq3+eWXX3jxxRfJysoiOTmZuLg4tm7dys8//8zcuXM5c+YMo0ePpm/fvhQWFvLaa6/xwgsv0KpVK+bNm+ceJz09nQ4dOvDXv/6VPXv2sGDBAlJSUgD46aefmDJlCseOHeP5559n7Nix/PGPfyQlJYWdO3eWOVU6IyODjIwMAN2sUKpVcHBwXS/BzWKx1Kv11AZlNgYjZpb65+jRo3To0KHC9w8dOsTf//53/P39eeedd4iOjmbkyJHk5uYyadIkrrvuOjZt2oSvry+zZs2iqKiIyZMn0717d44fP8727dt56aWXsFqtnDt3DoB///vfPPnkk7Ru3Zr9+/ezaNEipkyZUmZuI9c5Rjo+GCkrGCuvkbKCsfIaKevF1OD5DZPJdNnXLzQxwsPDsdvtlx1z9+7dHDt2zP17Xl4eDoeDvXv3Mm7cOAB69uyJn59fhWNcd911rFu3jh49elT4WPIbbrgBs9lM27Zt+fXXXwHYt28fcXFxmM1mmjRpQteuXQHIysoiJCSE1q1bA3Dbbbe5C5R9+/YxduxYAKKjozl37hx5eXkAXH/99VgsFtq3b09JSQk9evQAoH379vz8889l1pSQkEBCQsJl/0YiVyonJ6eul+AWHBxcr9ZTG5TZGDw1c2hoaF0vQWrQokWL+O6777BYLPTv359u3brh7+8PwK5du9ixYwerVq0CoLCwkJycHL755huOHDnCli1bgPO1WHZ2Nrt376ZPnz5YrVYA/P39cTgcfPfdd8ydO9c9p9PpLHctRq5znE6nRx4fqsJTj4VVZaS8RsoKxsrb0LNWVOuowfMbAQEB7m9vLjh37hwhISHu3xs1agSA2WympKTksmO6XC5mzpyJt7d3ldc1fPhwFi5cyKJFixgxYkS521xY14U5a8KFS7DMZjNeXl7uxpfJZKK4uLhG5hQRERHjateuHV999ZX79z/96U+cOXOGiRMnAribM3C+/hk7dmyZwtflcvHEE0+4v5i64JtvvikzX0lJCX5+fu6zl0VERDyFGjy/4ePjQ9OmTdmzZ4/77JVvvvmGAQMGVHqMxo0bk5+f7/69W7durF692n3J1uHDhwkLC6NLly5s2rSJwYMH87///Y/c3NwKxzSZTDzzzDPMnDmT5cuXM2TIkEqtpXPnzqxfv574+HjOnDmDzWbjlltuITQ0FLvdzokTJ2jVqhWbNm1y7xMVFcXGjRu57777sNlsBAQE4OvrW+n8l2K0Jx819M5xeYyYWUREak50dDTvvvsua9ascd+Hp7CwsNxtu3fvzieffMKwYcMwmUwcOnSIDh060KNHD9asWUN0dDQWi4WsrCyaNWtGt27dWLFiBbfeeqv7Ei1/f39CQkL48ssvufHGG3G5XPz444+EhYVddq1Gq3NERKR+UYOnHH/5y19YvHgxb7zxBgD33XcfrVq1qvT+MTExzJ07l23btjFs2DCeeOIJFi9ezLhx4yguLqZLly6MGDGC+++/n/nz5zNmzBg6dep02WsEvb29GT9+PFOmTCEoKAgfH5/LriU2Npbdu3czZswYmjdvTnh4OL6+vnh7e/PnP/+Z2bNnY7VaiYqKwuFwAPDAAw/w6quvMm7cOKxWK4mJiZXOLiIiIlKdTCYTSUlJvPHGG3zwwQcEBgbi4+PDI488UqbRc99997F06VLGjRuHy+UiJCSECRMmcPvtt2O32xk/fjwAgYGBJCUl0aNHDw4fPsyECROwWCxcf/31PPzwwzzzzDMsXLiQlStX4nQ6ufnmmyvV4BEREalLJldNXcsj9YbD4cDHx4ezZ88yadIkpk+fTpMmTepkLVlZWXUyb10x4tksymwMymwMnppZ9+CRumKkOsdTjw9VYaSsYKy8RsoKxsrb0LPqHjwGNnv2bHJzc3E6nQwePLjOmjsiIiIiIiIiUjPU4DGAqVOn1vUSRERERERERKQGlf+8bRERERERERER8Rg6g8cDDBkyhPbt21NSUkKLFi0YNWoUfn5+tb6ONWvWYLVaiY+Pr/IYxU8OqsYV1X8/1fUC6kBNZtbTSUREGrYLNQ+A2Wxm2LBhdO7c+ZL7DB06lDfffPOS2/zrX/9i4MCBtG3bttrWWp6GXufo32ERkfpNDR4P4O3tTUpKCgALFizg008/5Q9/+EOtr+PCo0lFREREasLFNc/XX3/NO++8w7Rp06563KeeeuqqxxAREanv1ODxMJ06deLIkSMAHD58mIULF1JQUEDLli15+umn8ff3Z+rUqYSFhbFv3z4KCgpITEzk/fff58iRI9x00008+OCDAMyZM4eTJ09SVFTEgAEDSEhIAM5/EzZgwAB27tyJt7c3SUlJNGnShPT0dHx8fBg0aBAZGRmsXbsWp9NJy5YtGTVqFFartc7+LiIiItKw5Ofnlzpj+cMPP+TLL7+kqKiI3r1788ADD5TavqSkhCVLlrBnzx6aN2+OxWKhb9++xMXFMXXqVIYOHUrHjh1LnfGzZcsWduzYQWJiImlpaXh7e3P48GF+/fVXnn76adavX8/+/fuJiIggMTGxVvOLiIhcKTV4PEhJSQl79uzh9ttvB86fzTNs2DCuvfZali9fzooVK3j88ccBsFgszJ49m48//piUlBRmz56Nv78/o0aN4u677yYgIICRI0fi7+9PYWEhEydOJDY2loCAAAoKCoiMjOShhx7irbfeYu3atQwePLjUWmJjY90NoWXLlrFu3TruuuuuMmvOyMggIyMDOP80L5GrERwcXNdLKJfFYqm3a6spymwMRswsdauwsJCkpCSKioo4ffo0U6ZMAeCbb74hOzubl156CZfLxZw5c/j222+59tpr3ftu3bqVn3/+mblz53LmzBlGjx5N3759r2j+3NxcZsyYwfbt25kzZw7Tp0+nbdu2TJw4kcOHDxMWFlZqe6PVORcfD4x0fDBSVjBWXiNlBWPlNVLWi6nB4wEuFDunTp2ibdu2dOvWjby8PHJzc92FTXx8PPPmzXPv06tXLwDat29P27Ztadq0KQAtW7bk5MmTBAQE8PHHH7Nt2zYAcnJyyM7OJiAgAIvFQkxMDADh4eHs2rWrzJqOHj3KsmXLyM3NxeFw0L1793LXnpCQ4G4EiVytnJycul5CuYKDg+vt2mqKMhuDp2YODQ2t6yVIFV18idb333/PggULSE1N5ZtvvmHXrl389a9/BcDhcHDixIlSDZ59+/YRFxeH2WymSZMmdO3a9Yrnj4mJwWQy0b59e4KCgtz3A2rXrh12u71Mg8dodc7FxwNPPT5UhZGygrHyGikrGCtvQ89aUa2jBo8HuFDsFBQUMHPmTFavXk2fPn0uuU+jRo0AMJlM7p8v/F5cXIzNZmP37t3MmDEDq9XK1KlTKSoqAsDLywuTyQScv8FhcXFxmfHT0tJISkoiLCyMzMxMbDZbNaUVEREROX9Z+tmzZzlz5gwA9957L3feeedVj3uhxoHzX6Jd7FL1U0lJyVXPLSIiUpPU4PEgVquVJ554gpSUFPr374+/vz979+6lS5cubNiwgS5dulR6rLy8PPz8/LBarRw/fpz9+/df0VocDgdNmzbF6XSyceNGmjVrVqn9jPb0hYbeOS6PETOLiEj1O378OCUlJQQEBNC9e3eWL1/Orbfeio+PD6dOncLLy4ugoCD39p07d2b9+vXEx8dz5swZbDYbt9xyS5lxg4KCOHbsGKGhoWzdupXGjRtX25qNVueIiEj9ogaPh+nQoQPt27dn8+bNJCYmum+yHBISwsiRIys9To8ePfjss88YPXo0rVu3JjIy8orWMWTIECZNmkRgYCCRkZHk5+dfaRQRERGRUi5cln5BYmIiZrOZ7t27c/z4cf72t78B4OPjw6hRo0o1eGJjY9m9ezdjxoyhefPmhIeH4+vrW2aORx55hOTkZAIDAwkPD8fhcNR8MBERkVpgcrlcrrpehBhHVlZWXS+hVhnxbBZlNgZlNgZPzax78BiXw+HAx8eHs2fPMmnSJKZPn06TJk1qbX4j1TmeenyoCiNlBWPlNVJWMFbehp5V9+ARERERkQZt9uzZ5Obm4nQ6GTx4cK02d0REROqaGjwiIiIi0iBMnTq1rpcgIiJSZ8x1vQAREREREREREbk6OoOngfjll19444032L9/P35+flgsFu655x569+5d10srpfjJQXW9hFr1UzWOpSdziIhIQzVkyBDat29PSUkJLVq0YNSoUfj5+dX6OtasWYPVaiU+Pr5K+3t6naNaQ0TEs6nB0wC4XC5SUlKIj4/n2WefBeDnn39m+/btpbYrLi7Gy8urLpYoIiIiUiFvb29SUlIAWLBgAZ9++il/+MMfan0d/fr1q/U5RUREqosaPA3Anj17sFgspYqSFi1acNddd5GZmclXX32Fw+GgpKSEiRMnsmTJEo4ePUpxcTH3338/N9xwAyUlJbz99tt8++23FBUV0b9/f+68804A3n//fTZu3IjZbKZHjx488sgjnDhxgsWLF3PmzBmsVit//vOfadOmTV39CURERKSB6NSpE0eOHAHg8OHDLFy4kIKCAlq2bMnTTz+Nv78/U6dOJSwsjH379lFQUEBiYiLvv/8+R44c4aabbuLBBx8EYM6cOZw8eZKioiIGDBhAQkICAEOHDmXAgAHs3LkTb29vkpKSaNKkCenp6fj4+DBo0CAyMjJYu3YtTqeTli1bMmrUKKxWa539XURERC5HDZ4G4OjRo3To0KHC9w8dOsTf//53/P39eeedd4iOjmbkyJHk5uYyadIkrrvuOjZt2oSvry+zZs2iqKiIyZMn0717d44fP8727dt56aWXsFqtnDt3DoB///vfPPnkk7Ru3Zr9+/ezaNEipkyZUluRRUREpAEqKSlhz5493H777cD5s3mGDRvGtddey/Lly1mxYgWPP/44ABaLhdmzZ/Pxxx+TkpLC7Nmz8ff3Z9SoUdx9990EBAQwcuRI/P39KSwsZOLEicTGxhIQEEBBQQGRkZE89NBDvPXWW6xdu5bBgweXWktsbKy7IbRs2TLWrVvHXXfdVat/DxERkSuhBk8DtGjRIr777jssFgv9+/enW7du+Pv7A7Br1y527NjBqlWrACgsLCQnJ4dvvvmGI0eOsGXLFgDy8vLIzs5m9+7d9OnTx/2Nlb+/Pw6Hg++++465c+e653Q6neWuJSMjg4yMDOD8o0ul6oKDg+t6CZVisVg8Zq3VRZmNQZlFak5hYSFJSUmcOnWKtm3b0q1bN/Ly8sjNzeXaa68FID4+nnnz5rn36dWrFwDt27enbdu2NG3aFICWLVty8uRJAgIC+Pjjj9m2bRsAOTk5ZGdnExAQgMViISYmBoDw8HB27dpVZk1Hjx5l2bJl5Obm4nA46N69e5ltGlqdcyWfdyMdH4yUFYyV10hZwVh5jZT1YmrwNADt2rXjq6++cv/+pz/9iTNnzjBx4kSAUqcTu1wuxo4dS2hoaKkxXC4XTzzxBD169Cj1+jfffFNmvpKSEvz8/NzXyl9KQkKC+9svuTo5OTl1vYRKCQ4O9pi1VhdlNgZl9hy//TdO6r8L9+ApKChg5syZrF69mj59+lxyn0aNGgFgMpncP1/4vbi4GJvNxu7du5kxYwZWq5WpU6dSVFQEgJeXFyaTCQCz2UxxcXGZ8dPS0khKSiIsLIzMzExsNluZbRpanXMln3dPPT5UhZGygrHyGikrGCtvQ89aUa2jx6Q3ANHR0RQVFbFmzRr3a4WFheVu2717dz755BNcLhdw/vItgB49erBmzRr3mThZWVk4HA66detGZmYmBQUFAJw7dw5fX19CQkL48ssvgfPNocOHD9dUPBERETEIq9XKE088wUcffYTVasXf35+9e/cCsGHDBrp06VLpsfLy8vDz88NqtXL8+HH2799/RWtxOBw0bdoUp9PJxo0br2hfERGRuqAzeBoAk8lEUlISb7zxBh988AGBgYH4+PjwyCOPlGn03HfffSxdupRx48bhcrkICQlhwoQJ3H777djtdsaPHw9AYGAgSUlJ9OjRg8OHDzNhwgQsFgvXX389Dz/8MM888wwLFy5k5cqVOJ1Obr75ZsLCwi67VqM9frOhd45FRESqW4cOHWjfvj2bN28mMTHRfZPlkJAQRo4cWelxevTowWeffcbo0aNp3bo1kZGRV7SOIUOGMGnSJAIDA4mMjCQ/P/+y+xitzhERkfrF5LpwKodILcjKyqrrJdQqIzZ4lNkYlNkYPDWzLtGSumKkOsdTjw9VYaSsYKy8RsoKxsrb0LPqEi0RERERERERkQZKDR4REREREREREQ+nBo+IiIiIiIiIiIfTTZY9yJAhQ2jfvj1w/pGew4YNo3PnzpfcZ+rUqQwdOpSOHTte9fwHDhxg/fr1DBs27KrHEhEREfkt1ToiIiJVpwaPB/H29iYlJQWAr7/+mnfeeYdp06bVytzFxcV07Njxqoun4icHVdOKPMNPl3hPT9oQEREpzdNrHU+pc1SDiIg0TGrweKj8/Hz8/PwAsNlsrFq1igkTJgCwePFiOnbsSJ8+fUrts27dOj744AN8fX255ppraNSoEcOHD2f79u3ux50HBAQwatQomjRpQnp6Oj/99BN2u53mzZtz5513uuf54YcfeP311ykqKsLb25uRI0fqqSUiIiJSbVTriIiIXBk1eDxIYWEhSUlJFBUVcfr0aaZMmVLpfU+dOsV//vMfkpOT8fHx4cUXX+Saa64BICoqipkzZ2IymVi7di0ffvghjz76KADHjh1j+vTpeHt7Y7PZ3OOFhoby4osv4uXlxa5du3jnnXcYN25c9QYWERERQ1GtIyIiUnVq8HiQi09b/v7771mwYAGpqamV2veHH36gS5cu+Pv7AxAXF0d2djZwviB6+eWXOX36NE6nk5CQEPd+vXr1wtvbu8x4eXl5pKWlceLECeD8ac3lycjIICMjA4DZs2dXMqkxBAcH1/USaoTFYmmw2SqizMagzCI1z9NqHU+tc6rjc22k44ORsoKx8hopKxgrr5GyXkwNHg/VqVMnzp49y5kzZ/Dy8sLlcrnfKyoquqKxlixZwsCBA+nVqxc2m4333nvP/Z7Vai13n+XLl9O1a1eSkpKw2+0VXh+fkJBAQkLCFa3HKHJycup6CTUiODi4wWariDIbgzJ7Dl1G0zB4Qq3jqXVOdXyuPfX4UBVGygrGymukrGCsvA09a0W1jh6T7qGOHz9OSUkJAQEBBAcHc+zYMYqKisjNzWX37t1lto+IiGDv3r2cO3eO4uJivvrqK/d7eXl5NGvWDID169dXav6L98nMzLz6QCIiIiIXUa0jIiJyZXQGjwe5cF36BYmJiZjNZoKDg7nxxhsZO3YsISEhdOjQocy+zZo14/e//z2TJk3C39+f0NBQfH19Abj//vuZO3cufn5+REdHY7fbL7uWe+65h7S0NFauXEnPnj0rncFoT21o6J1jERGR6uTptY7R6hwREalfTK6Lz3eVBs3hcODj40NxcTEpKSncfvvt9O7du1bXkJWVVavz1TUjNniU2RiU2Rg8NbMu0TKuuq51jFTneOrxoSqMlBWMlddIWcFYeRt61opqHZ3BYyDp6ens3r2boqIiunXrxg033FDXSxIRERGpNqp1RETEyNTgMZALjwMVERERaYhU64iIiJHpJssiIiIiIiIiIh5ODR4PMXTo0FK/Z2Zmsnjx4jpajYiIiEjtGDJkCElJSe7/Z7fbef755y+739SpUzlw4EC1rCExMZEzZ85Uy1giIiI1RZdoyRUrLi7Gy8uravs+OaiaV1O/6OkZIiIi1cvb25uUlJRSr82YMaOOVnNpdVXnqP4QERFQg6dBSEtLIyYmhri4OOD82T5vvvkmNpuN9957j4CAAI4ePUp4eDijRo3CZDKxc+dO/r//7//DarXSuXNn7HY7EyZM4IcffuD111+nqKgIb29vRo4cSWhoKJmZmXz11Vc4HA5KSkpo0aIFvXv3dj+Z4pVXXuHGG2/UzQxFRESkxlWm1rnYwoULOXDgAIWFhcTFxfHAAw8A58/MiY+PZ8eOHTidTsaMGUObNm04e/Ys8+fP59SpU3Tq1Ak9dFZERDyBGjweorCwkKSkJPfv586do1evXpfd79ChQ8ydO5emTZsyefJkvvvuO8LDw1m4cCHTpk0jJCSEl19+2b19aGgoL774Il5eXuzatYt33nmHcePGucf6+9//jr+/P99++y0fffQRvXv3Ji8vj++++47ExMRqzy0iIiLGdnENFBISUqoegvJrnaioqFLbPPTQQ/j7+1NSUsKLL77Ijz/+yDXXXANAQEAAycnJfPrpp6xatYqnnnqK9957j6ioKO677z527tzJunXraiesiIjIVVCDx0P89vTkzMzMSl1XHhERQfPmzQEICwvDbrfj4+NDSEgIISEhANxyyy1kZGQAkJeXR1paGidOnADOX451Qbdu3fD39wfg2muvZdGiRZw5c4YtW7YQGxtb7mVbGRkZ7rFnz55dlegeJTg4uNTvFoulzGsNnTIbgzIbgxEzS/1T3iVaFyuv1vltg+eLL75g7dq1FBcXc/r0aY4dO+Zu8MTGxgIQHh7O1q1bAdi7d6/7C66ePXvi5+dX7tz1pc6pi8+pkY4PRsoKxsprpKxgrLxGynoxNXgaAC8vL0pKSgAoKSnB6XS632vUqJH7Z7PZ7N6uIsuXL6dr167umxhOmzbN/Z7Vai217W233caGDRv44osvGDlyZLnjJSQkkJCQcMWZPFVOTk6p34ODg8u81tApszEoszF4aubQ0NC6XoLUosvVOna7nVWrVjFr1iz8/f1JS0ujqKjI/b7FYnHve/EXW5VRX+qcuviceurxoSqMlBWMlddIWcFYeRt61opqHT1FqwFo0aIFBw8eBGD79u2XLU5CQ0Ox2+3Y7Xbg/LdaF+Tl5dGsWTPg/FlCl9KnTx8+/vhjANq2bVvV5YuIiIjUmLy8PHx8fPD19eWXX37h66+/vuw+Xbp0YdOmTQD873//Izc3t4ZXKSIicvV0Bk8DcMcdd5CSkkJSUhLdu3cvc6bNb3l7ezN8+HBeeuklrFYrHTt2dL93zz33kJaWxsqVK+nZs+clx2nSpAlt2rS5ohsr6ykPIiIiUpvCwsIICwtj9OjRNG/enM6dO192n/vvv5/58+czZswYOnXqVOnT/FXniIhIXTK59FgAQ3I4HPj4+OByuVi8eDGtWrVi4MCBVzRGQUEB48aNIzk5GV9f30rtk5WVVZXleqyGfmpgeZTZGJTZGDw1sy7RkrpipDrHU48PVWGkrGCsvEbKCsbK29CzVlTr6Aweg8rIyGD9+vU4nU46dOjAnXfeeUX779q1i3/961/cfffdlW7uiIiIiIiIiEjNUIPHoAYOHHjFZ+xcrFu3brz66qvVuCIRERERERERqSrdZFlERERERERExMPpDB4PMmTIENq3b09JSQlt2rQhMTHxsjdUvuDw4cOcOnXqsjdOror09HR8fHwYNGhQtY8tIiIicsGV1EKZmZkcOHCA4cOHX/W8qnVERMQTqMHjQby9vUlJSQHglVde4bPPPqvUZVbFxcUcPnyYAwcO1EiD50oUP9lwCyM9OUNERKRmVbUWqi11VeeoBhEREVCDx2NFRUVx5MgRzp07x6uvvordbsdqtTJixAiuueYa0tPT+emnn7Db7TRv3pzvvvuOwsJC9u3bx+9//3uOHTtW6puosWPHMn78eEJCQlixYgUbN24kMDCQ5s2bEx4ezqBBg8jIyGDt2rU4nU5atmzJqFGjKn0GkYiIiEh1ulwtdLHt27ezcuVKnE4nAQEBjBo1iiZNmpCenk5OTg52u52cnBwGDBjAgAEDAFi5ciXr168vVQ+JiIjUZ2rweKDi4mK+/vprevToQXp6Oh06dOCvf/0re/bsYcGCBe5vto4dO8b06dPx9vYuc5pyenp6uWP/8MMPfPXVV6SkpFBcXMz48ePdBU1sbCwJCQkALFu2jHXr1nHXXXfVQmIRERGR/6eytdAFUVFRzJw5E5PJxNq1a/nwww959NFHgfOPNp8yZQr5+fk899xz9OvXjyNHjrB582bmzJlTph4SERGpr9Tg8SCFhYUkJSUB0KVLF26//XYmTZrE2LFjAYiOjubcuXPk5eUB0KtXL7y9va9oju+++44bbrjBvV9MTIz7vaNHj7Js2TJyc3NxOBx07979suNlZGSQkZEBwOzZs69oLZ4mODi4zGsWi6Xc1xsyZTYGZTYGI2aW+u1Ka6ELTp06xcsvv8zp06dxOp2EhIS43+vZsyeNGjWiUaNGBAUF8euvv7J371569+7tPlO5V69e5a6nvtQ5dfE5NdLxwUhZwVh5jZQVjJXXSFkvpgaPB7n4uvPKuNTlU15eXrhcLvfvhYWFlx0vLS2NpKQkwsLCyMzMxGazXXafhIQE91k/DV1OTk6Z14KDg8t9vSFTZmNQZmPw1MyhoaF1vQSpIVdaC12wZMkSBg4cSK9evbDZbLz33nvu9yyW/1cOm81miouLKz1ufalz6uJz6qnHh6owUlYwVl4jZQVj5W3oWSuqdfSYdA8XFRXFxo0bAbDZbAQEBODr61tmOx8fH/Lz892/t2jRgkOHDgFw8OBB7HY7AJ07d2bHjh0UFhbicDjYuXOnex+Hw0HTpk1xOp3uOUVERETqUmVqoby8PJo1awbA+vXrLztmly5d2LZtG4WFheTn57Njx47qX7iIiEg10xk8Hu6BBx7g1VdfZdy4cVitVhITE8vdLjo6mg8++ICkpCR+//vfExcXx4YNGxgzZgwRERHuDmBERAQxMTEkJSURFBREu3bt3EXSkCFDmDRpEoGBgURGRpZqGFWWnvIgIiIi1akytdD999/P3Llz8fPzIzo62v3FVkXCw8O56aabSEpKIjAwkI4dO1ZqLapzRESkLplcF1+nI8L5M3V8fHwoKChgypQpjBgxotpuLJiVlVUt43iKhn5qYHmU2RiU2Rg8NbMu0ZK6YqQ6x1OPD1VhpKxgrLxGygrGytvQs1ZU6+gMHinjtdde49ixYxQVFREfH6+nRoiIiIiIiIjUc2rwSBnPPvtsXS9BRERERERERK6AbrIsIiIiIiIiIuLh1OBpILZu3coDDzzA8ePHq7z/sWPHKnx/zZo1lXrqhIiIiEhlDB06tMxrF9cbmZmZnDp1yv1eYmIiZ86cqdE1qd4RERFPpku0GojNmzcTFRXF5s2beeCBB654/23bthETE0Pbtm3LvFdcXEy/fv2qY5kUPzmoWsapa3pKhoiISPW7uN7IzMykXbt27seb1/b8VVFXdY7qEhERATV4GgSHw8G+ffuYMmUKycnJPPDAA9hsNlatWsWECRMAWLx4MR07dqRPnz68/fbbbN++HS8vL7p160ZsbCzbt2/n22+/5T//+Q9jx47lX//6F2FhYezbt4+bb76Z/Px8fHx8GDRoEBkZGaxduxan00nLli0ZNWoUVqu1jv8KIiIi4unS09Px8fEhJCSEAwcO8Morr+Dt7c3MmTMBWL16NTt27MDpdDJmzBjatGnj3mfQoPPNlbFjxzJ+/HhCQkKYM2cOJ0+epKioiAEDBpCQkACcP3towIAB7Ny5E29vb5KSkmjSpEmpsVTviIiIp1GDpwHYtm0bPXr0IDQ0lICAAA4ePFjhtmfPnmXr1q28/PLLmEwmcnNz8fPzo1evXsTExBAXF+fe1ul0Mnv2bOB8wXVBbGysu0BatmwZ69at46677qqhdCIiImI0cXFxrF69mqFDh9KxY0f36wEBASQnJ/Ppp5+yatUqnnrqqUuOM3LkSPz9/SksLGTixInExsYSEBBAQUEBkZGRPPTQQ7z11lusXbuWwYMHl9pX9Y6IiHgaNXgagM2bNzNgwAAAbrrpJjZt2kRMTEy52/r6+uLt7c0///lPYmJiKtzuwljlOXr0KMuWLSM3NxeHw0H37t0rHCMjI4OMjAwAd7OoIQgODq7UdhaLpdLbNhTKbAzKbAxGzCz1W2xsLADh4eFs3br1stt//PHHbNu2DYCcnByys7MJCAjAYrG4a6Dw8HB27dpVZt/K1Dv1pc6pi8+pkY4PRsoKxsprpKxgrLxGynoxNXg83Llz59izZw9HjhzBZDJRUlICwA033IDL5XJvV1RUBICXlxcvvfQSu3fvZsuWLaxevZopU6aUO3ZFpyGnpaWRlJREWFgYmZmZ2Gy2CteXkJDg/varIcnJyanUdsHBwZXetqFQZmNQZmPw1MyhoaF1vQSpIRbL+dLVbDZTXFwMnK9tLq55CgsLAbDZbOzevZsZM2ZgtVqZOnVqqXrIZDKVGetilal36kudUxefU089PlSFkbKCsfIaKSsYK29Dz1pRraMGj4fbsmULt912GyNGjHC/NmXKFFwuF8eOHaOoqIjCwkJ2795NVFQUDoeDgoICevbsSVRUFH/5y18AaNy4Mfn5+ZWa0+Fw0LRpU5xOJxs3bqzVmx+KiIiIMfj4+FSqNmnRogU7d+4E4ODBg9jtdgDy8vLw8/PDarVy/Phx9u/ff0Xzq94RERFPowaPh9u8eTP33HNPqddiY2PZvHkzN954I2PHjiUkJIQOHToAkJ+fz5w5cygqKsLlcvHoo48C5y/Heu211/jkk08YM2bMJeccMmQIkyZNIjAwkMjIyEo3hkBPeRAREZHzCgsLS91DZ+DAgaXe79OnDwsXLix1k+XyxMXFsWHDBsaMGUNERIT7W80ePXrw2WefMXr0aFq3bk1kZOQVra8q9Y7qHBERqUsm18XntIrUsKysrLpeQq1q6KcGlkeZjUGZjcFTM+sSLakrRqpzPPX4UBVGygrGymukrGCsvA09a0W1jrmW1yEiIiIiIiIiItVMDR4REREREREREQ+nBo+IiIiIiIiIiIdTg0dERERERERExMPpKVqV8Msvv7B06VIOHDiAr68vTZo04bHHHquWmzimp6fj4+PDoEGDLrldYmIiPj4+mEwm/Pz8+Mtf/kKLFi2uev7fzjFr1iwCAwMrXOPy5cvp0qUL3bp1q9IcxU9eOmd9pidjiIiI1J2tW7fy97//nXnz5tGmTZsq7R8aGkrbtm3LfX/NmjVYrVbi4+OrvMa6qnNUo4iICKjBc1kul4uUlBTi4+N57rnnADh8+DC//vprrT+lY8qUKQQGBpKens5//vOfUo8WrS1Dhgyp9TlFRERENm/eTFRUFJs3b+aBBx644v23bdtGTExMuQ2e4uJi+vXrVx3LFBERqTNq8FyGzWbDYrGU+kc/LCwMgOXLl7N9+3YAzpw5Q/fu3Rk5ciQbNmzgk08+wel0EhkZyZ/+9CfMZjNff/017777LiUlJQQEBPDCCy8AcOzYMaZOnUpOTg4DBgxgwIABl1xTp06d+OSTT9zz/vvf/+bkyZMAPPbYY0RFRZGens5PP/3EiRMnOHv2LIMGDSIhIQGbzcaqVauYMGECAIsXL6Zjx4706dMHgA8//JD//e9/eHt78+yzz9KqVatSc6elpRETE0NcXBw//PADS5cupaCgAIvFwgsvvEDjxo2v7g8uIiIi8hsOh4N9+/YxZcoUkpOTeeCBBy5Z07z99tts374dLy8vunXrRmxsLNu3b+fbb7/lP//5D2PHjuVf//oXYWFh7Nu3j5tvvpn8/Hz3GcsZGRmsXbsWp9NJy5YtGTVqFFartY7/CiIiIpemBs9lHDlyhA4dOpT73pAhQxgyZAi5ubm88MIL/O53v+PYsWN88cUXTJ8+HYvFwqJFi9i4cSPXX389r732GtOmTSMkJIRz5865x8nKymLKlCnk5+fz3HPP0a9fPyyWiv+n+frrr7nhhhsAeP311xk4cCBRUVHk5OQwc+ZM5s2b5177zJkzcTgcjB8/np49e142r6+vL6mpqaxfv56lS5e6i6bfcjqdvPzyyzz33HNERESQl5eHt7d3me0yMjLIyMgAYPbs2Zedvz4LDg6+4n0sFkuV9vNkymwMymwMRsws9dO2bdvo0aMHoaGhBAQEcPDgwQq3PXv2LFu3buXll1/GZDKRm5uLn58fvXr1cn9JdYHT6XTXJ+np6e7XY2NjSUhIAGDZsmWsW7eOu+66q8xc9aXOqYvPqZGOD0bKCsbKa6SsYKy8Rsp6MTV4rpLL5eIf//gHAwcOJDw8nNWrV3Po0CEmTpwIQGFhIYGBgXz//fd06dKFkJAQAPz9/d1j9OzZk0aNGtGoUSOCgoL49ddfad68eZm5pk2bxrlz5/Dx8XFfKrV7926OHTvm3iYvLw+HwwFAr1698Pb2xtvbm65du/LDDz/g5+d3yTw333yz+/9/4403KtwuKyuLpk2bEhERAZxvDJUnISHBXSB5upycnCveJzg4uEr7eTJlNgZlNgZPzVzbl1BLzdu8ebP7DOebbrqJTZs2ERMTU+62vr6+eHt7889//pOYmJgKt7swVnmOHj3KsmXLyM3NxeFw0L1793K3qy91Tl18Tj31+FAVRsoKxsprpKxgrLwNPWtFtY4aPJfRrl07vvrqqwrff++992jWrBl9+/YFzjd84uPjefjhh0ttd+FSrvJcfLaO2WymuLi43O2mTJmCn58fr7zyCunp6Tz22GO4XC5mzpxZ7tkzJpOpzO9eXl64XC73a0VFRRXu89v9RURERGrbuXPn2LNnD0eOHMFkMlFSUgLADTfcUG5N4+XlxUsvvcTu3bvZsmULq1evZsqUKeWOXdFlV2lpaSQlJREWFkZmZiY2m62aU4mIiFQ/NXguIzo6mnfffZeMjAz3NzQ//vgjeXl55Obmsnv37lJFw3XXXcecOXO4++67CQoK4ty5c+Tn59OpUycWL16M3W53X6J18Vk8leXl5cXjjz/OuHHjGDx4MN26dWP16tXup3AdPnzYfY+gbdu2ce+991JQUIDNZuPhhx+mpKSEY8eOUVRURGFhIbt37yYqKso9/hdffMG9997LF198QWRkZIXrCA0N5fTp0/zwww9ERESQn5+Pt7c3Xl5el16/nvIgIiIiV2DLli3cdtttjBgxwv3alClTcLlc5dY0DoeDgoICevbsSVRUFH/5y18AaNy4Mfn5+ZWa0+Fw0LRpU5xOJxs3bqRZs2aV2k91joiI1CU1eC7DZDIxbtw4li5dygcffECjRo1o0aIFjz/+OOnp6Zw6dcp9OVavXr0YMmQIDz74IDNmzMDlcuHl5cXw4cPp1KkTI0aM4O9//zsul4vAwEAmT55cpTU1bdqUm2++mdWrV/PEE0+wePFixo0bR3FxMV26dHEXQNdccw3Tpk3j7NmzDB482F2c3HjjjYwdO5aQkJAy9xc6d+4c48aNo1GjRjz77LMVrsFisfDcc8/x+uuvU1hYiLe3N5MnT75sg0dERETkSmzevJl77rmn1GuxsbFs3ry53JomPz+fOXPmUFRUhMvl4tFHHwXOX4712muv8cknnzBmzJhLzjlkyBAmTZpEYGAgkZGRlW4MiYiI1CWT6+JzW6XBSE9Pdz8Joj7Jysqq6yXUqoZ+7Wd5lNkYlNkYPDWz7sEjdcVIdY6nHh+qwkhZwVh5jZQVjJW3oWetqNYx1/I6RERERERERESkmukSrQbqgQceqOsliIiIiIiIiEgt0Rk8IiIiIiIiIiIeTmfwNBBDhw7lzTffrPT2drud5ORkUlNTr3pum83GqlWrmDBhwmW3LX6yft0TqCJ6CoaIiEj9MGTIENq3b+/+/eabb+bee+8td9utW7cSGhpK27ZtqzTXgQMHWL9+PcOGDavS/nVV56huERERUIOnQSsuLtZTrURERMSjeXt7k5KSUqltt23bRkxMTJUbPB07dqRjx45V2ldERKSuqcHTwNhsNpYvX46fnx9ZWVnMmzePt99+m2+//ZaioiL69+/PnXfeWWofu93OggULKCgoAGDYsGF07twZm83Ge++9R0BAAEePHiU8PJxRo0ZhMpn4+uuvWbp0KVarlc6dO9dFVBERETGwt99+m+3bt+Pl5UW3bt2IjY1l+/btfPvtt/znP/9h7NixOBwOFi5cSEFBAS1btuTpp5/G39+fqVOnEhERgc1mIy8vj6eeeoouXbqUOiv5hx9+4PXXX6eoqAhvb29GjhypJ7SJiEi9pgZPA3To0CFSU1MJCQkhIyMDX19fZs2aRVFREZMnT6Z79+6ltg8KCuL555/H29ub7Oxs5s+fz+zZs91jzZ07l6ZNmzJ58mS+++47wsPDee2113jhhRdo1aoV8+bNq3AtGRkZZGRkALjH9ATBwcHVMo7FYqm2sTyFMhuDMhuDETNL/VNYWEhSUpL799///vdcd911bN26lZdffhmTyURubi5+fn706tWLmJgY4uLiABg3bhzDhg3j2muvZfny5axYsYLHH38cgJKSEmbNmsXOnTtZsWIFkydPLjVvaGgoL774Il5eXuzatYt33nmHcePGldqmvtQ5dfE5NdLxwUhZwVh5jZQVjJXXSFkvpgZPAxQREUFISAgA33zzDUeOHGHLli0A5OXlkZ2dTevWrd3bFxcXs3jxYg4fPozZbCY7O7vUWM2bNwcgLCwMu92Oj48PISEh7jFuu+02d3HzWwkJCSQkJNRIzpqUk5NTLeMEBwdX21ieQpmNQZmNwVMz6yyLhqW8S7SKi4vx9vbmn//8JzExMcTExJTZLy8vj9zcXK699loA4uPjS30p1bt3bwDCw8Ox2+3l7p+WlsaJEyfcc/5Wfalz6uJz6qnHh6owUlYwVl4jZQVj5W3oWSuqddTgaYCsVqv7Z5fLxRNPPEGPHj1KbXNxIfPRRx8RFBRESkoKLpeLRx55xP1eo0aN3D+bzWZKSkpqbuEiIiIileDl5cVLL73E7t272bJlC6tXr2bKlClXNMaFGqei+mb58uV07dqVpKQk7HY706ZNq5a1i4iI1BQ1eBq4Hj16sGbNGqKjo7FYLGRlZdGsWbNS2+Tl5dG8eXPMZjOff/75ZZs4oaGh2O12Tpw4QatWrdi0aVOl16OnPIiIiMjVcjgcFBQU0LNnT6KiovjLX/4CQOPGjcnPzwfA19cXf39/9u7dS5cuXdiwYQNdunSp9Bx5eXnumikzM7NS+6jOERGRuqQGTwN3++23Y7fbGT9+PACBgYGlrmMH6N+/P6mpqWzYsIHu3buXOgOoPN7e3vz5z39m9uzZWK1WoqKicDgcNZZBREREjOu39+Dp0aMHAwYMYM6cORQVFeFyuXj00UcBuOmmm3jttdf45JNPGDNmDImJie6bLIeEhDBy5MhKz3vPPfeQlpbGypUr6dmzZ7XnEhERqW4ml8vlqutFiHFkZWXV9RJqVUO/9rM8ymwMymwMnppZ9+CRumKkOsdTjw9VYaSsYKy8RsoKxsrb0LNWVOuYa3kdIiIiIiIiIiJSzdTgERERERERERHxcGrwiIiIiIiIiIh4ON1kuZ4aOnQob775ZqnX1qxZg9VqJT4+nszMTLp16+Z+ukNiYiKzZs0iMDCwxtZ08fxVVfzkoGpcUfXSky9EREQ8R3m1UkVsNhsWi4XOnTtfcrvly5fTpUsXunXrVqU11VWdoxpGRERADR6P0q9fP/fPmZmZtGvXrswjz2trfhERERFPYbPZ8PHxuWyDZ8iQIbW0IhERkeqnBo8HSU9Px8fHh5CQEA4cOMArr7yCt7c3M2fOBGD16tXs2LEDp9PJmDFjaNOmjXufQYPOf6M0duxYxo8fT0hICHPmzOHkyZMUFRUxYMAAEhISgPPfiA0YMICdO3fi7e1NUlISTZo0KTVWRkYGa9euxel00rJlS0aNGnXZx6uLiIiI1KTt27ezcuVKnE4nAQEBjBo1isLCQj777DPMZjMbN27kiSeeYMGCBSxYsACz2YzD4WD06NH84x//4LXXXiMmJoa4uDhWrFjBjh07KCwspFOnTowYMQKTyVTXEUVERCqkBo8HiouLY/Xq1QwdOpSOHTu6Xw8ICCA5OZlPP/2UVatW8dRTT11ynJEjR+Lv709hYSETJ04kNjaWgIAACgoKiIyM5KGHHuKtt95i7dq1DB48uNS+sbGx7obQsmXLWLduHXfddVeZOTIyMsjIyABg9uzZVxu9RgUHB1f7mBaLpUbGrc+U2RiU2RiMmFk8W1RUFDNnzsRkMrF27Vo+/PBDHn30Ue68885SX3iFhYXx7bffEh0dzc6dO+nevTsWS+my+He/+x333XcfAP/4xz/YsWMHvXr1KrVNfalz6uJzaqTjg5GygrHyGikrGCuvkbJeTA2eBiQ2NhaA8PBwtm7detntP/74Y7Zt2wZATk4O2dnZBAQEYLFYiImJcY+1a9euMvsePXqUZcuWkZubi8PhoHv37uXOkZCQ4G4E1Xc5OTnVPmZwcHCNjFufKbMxKLMxeGrm0NDQul6C1JFTp07x8ssvc/r0aZxOJyEhIeVud9NNN/HFF18QHR3N5s2b6d+/f5lt9uzZw4cffkhBQQHnzp2jXbt2ZRo89aXOqYvPqaceH6rCSFnBWHmNlBWMlbehZ62o1lGDpwG58M2T2WymuLgYAC8vL1wul3ubwsJC4Py16Lt372bGjBlYrVamTp1KUVGRe58LpyBfPNbF0tLSSEpKIiwsjMzMTGw2W41mExEREbmcJUuWMHDgQHr16oXNZuO9994rd7tevXrx7rvvcu7cOQ4ePEh0dHSp9wsLC1m8eDGzZs0iODiY9PR0dw0lIiJSX6nB46F8fHzIz8+/7HYtWrRg586dABw8eBC73Q5AXl4efn5+WK1Wjh8/zv79+69ofofDQdOmTXE6nWzcuLHSN3vWUx5ERESkpuTl5blrkvXr17tfb9y4cam6ycfHh44dO/L6668TExOD2WwuNc6FL70CAwNxOBx89dVX7jOlL0V1joiI1CU1eOqpwsLCUvfQGThwYKn3+/Tpw8KFC0vdZLk8cXFxbNiwgTFjxhAREeE+latHjx589tlnjB49mtatWxMZGXlF6xsyZAiTJk0iMDCQyMjISjWbRERERKpLebXS/fffz9y5c/Hz8yM6Otr9xVZMTAxz585l27ZtDBs2jC5dunDTTTcxd+5cpk6dWmZsPz8/7rjjDsaOHUuTJk1K3fNQRESkvjK5Lr5+R6SGZWVl1fUSalVDv/azPMpsDMpsDJ6aWffgkbpipDrHU48PVWGkrGCsvEbKCsbK29CzVlTrmMt9VUREREREREREPIYaPCIiIiIiIiIiHk4NHhERERERERERD6ebLNdTQ4cO5c033yz12po1a7BarcTHx5OZmUm3bt3cT4pITExk1qxZBAYG1tiaLp6/qoqfHFSNK6peevKFiIg0dHa7neTkZFJTU92vpaen4+Pjw6BBFf8bfeDAAdavX8+wYcOw2WxYLBY6d+58RXNXVKtc/PrBgwdJTU1l3LhxnDx5kmPHjnHvvfde0TzlsdlsrFq1igkTJlz1WJdSm3WO6hYREfktNXg8SL9+/dw/Z2Zm0q5du0o/nry65xcRERHj6Nixo/tJUjabDR8fnytu8FzOjz/+SGpqKqNHj6ZDhw506NCBXr16VescIiIiDZkaPB7kwjdsISEhHDhwgFdeeaXUY9JXr17Njh07cDqdjBkzhjZt2pT5Vm7s2LGMHz+ekJAQ5syZw8mTJykqKmLAgAEkJCQA588eGjBgADt37sTb25ukpCSaNGlSaqyMjAzWrl2L0+mkZcuWjBo1CqvVWmd/GxEREbl6U6dOJSIiApvNRl5eHk899RRdunRxnwEzbNgwPvvsM8xmMxs3bmTYsGG0adOGf//735w8eRKAxx57jKioKM6ePcv8+fM5deoUnTp14lIPbj1+/DhpaWmMGjWKiIgI4PyXWQcOHGD48OGkpaXRuHFjDh48yC+//MIf//hH4uLiKCkpYcmSJezZs4fmzZtjsVjo27cvcXFxfP311yxduhSr1VqqGXXu3DleffVV7HY7VquVESNGcM0115Ceno7dbsdut5OTk8Njjz3G/v37+d///kezZs0YP348FotKZxERqb/0r5QHiouLY/Xq1QwdOtT9bRpAQEAAycnJfPrpp6xatYqnnnrqkuOMHDkSf39/CgsLmThxIrGxsQQEBFBQUEBkZCQPPfQQb731FmvXrmXw4MGl9o2NjXU3hJYtW8a6deu46667ysyRkZFBRkYGALNnz77a6DUqODi42se0WCw1Mm59pszGoMzGYMTMAiUlJcyaNYudO3eyYsUKJk+e7H4vJCSEO++8s9SXR/Pnz2fgwIFERUWRk5PDzJkzmTdvHu+99x5RUVHcd9997Ny5k3Xr1lU455w5cxg1ahRRUVEVbvPLL7/w4osvkpWVRXJyMnFxcWzdupWff/6ZuXPncubMGUaPHk3fvn0pLCzktdde44UXXqBVq1bMmzfPPU56ejodOnTgr3/9K3v27GHBggWkpKQA8NNPPzFlyhSOHTvG888/z9ixY/njH/9ISkoKO3fupHfv3qXWVJd1Tl1/No10fDBSVjBWXiNlBWPlNVLWi6nB04DExsYCEB4eztatWy+7/ccff8y2bdsAyMnJITs7m4CAACwWCzExMe6xdu3aVWbfo0ePsmzZMnJzc3E4HHTv3r3cORISEtyNoPouJyen2scMDg6ukXHrM2U2BmU2Bk/NHBoaWtdLqLdMJtNlX7/QxAgPD8dut192zN27d3Ps2DH373l5eTgcDvbu3cu4ceMA6NmzJ35+fhWOcd1117Fu3Tp69OiB2Vz+M0BuuOEGzGYzbdu25ddffwVg3759xMXFYTabadKkCV27dgUgKyuLkJAQWrduDcBtt93mbsTs27ePsWPHAhAdHc25c+fIy8sD4Prrr8disdC+fXtKSkro0aMHAO3bt+fnn38us6a6rHPq+rPpqceHqjBSVjBWXiNlBWPlbehZK6p11OBpQC6cNmw2mykuLgbAy8ur1CnRhYWFwPnr53fv3s2MGTOwWq1MnTqVoqIi9z4XCr2Lx7pYWloaSUlJhIWFkZmZic1mq9FsIiIicvUCAgI4d+5cqdfOnTtHSEiI+/dGjRoB52uAkpKSy47pcrmYOXMm3t7eVV7X8OHDWbhwIYsWLWLEiBHlbnNhXRfmrAkX11IX10Mmk6ncekhERKQ+UYPHQ/n4+JCfn3/Z7Vq0aMHOnTsBOHjwoPubuLy8PPz8/LBarRw/fpz9+/df0fwOh4OmTZvidDrZuHFjpW/2rCc+iIiI1B0fHx+aNm3Knj173GevfPPNNwwYMKDSYzRu3LhUDdKtWzdWr17tvmTr8OHDhIWF0aVLFzZt2sTgwYP53//+R25uboVjmkwmnnnmGWbOnMny5csZMmRIpdbSuXNn1q9fT3x8PGfOnMFms3HLLbcQGhqK3W7nxIkTtGrVik2bNrn3iYqKYuPGjdx3333YbDYCAgLw9fWtdP5LUZ0jIiJ1SQ2eeqqwsLDUPXQGDhxY6v0+ffqwcOHCUjdZLk9cXBwbNmxgzJgxREREuE/l6tGjB5999hmjR4+mdevWREZGXtH6hgwZwqRJkwgMDCQyMrJSzSYRERGpe3/5y19YvHgxb7zxBgD33XcfrVq1qvT+MTExzJ07l23btjFs2DCeeOIJFi9ezLhx4yguLqZLly6MGDGC+++/n/nz5zNmzBg6dep02XsheHt7M378eKZMmUJQUBA+Pj6XXUtsbCy7d+9mzJgxNG/enPDwcHx9ffH29ubPf/4zs2fPxmq1EhUVhcPhAOCBBx7g1VdfZdy4cVitVhITEyudXUREpD4zuWrqHFeRcmRlZdX1EmpVQ7/2szzKbAzKbAyemln34DEWh8OBj48PZ8+eZdKkSUyfPp0mTZrUyVqMVOd46vGhKoyUFYyV10hZwVh5G3pW3YNHRERERBqc2bNnk5ubi9PpZPDgwXXW3BEREalravCIiIiIiMeaOnVqXS9BRESkXij/OZQiIiIiIiIiIuIxdAZPPTV06FDefPPNUq+tWbMGq9VKfHw8mZmZdOvWzf30qsTERGbNmkVgYGCNreni+auq+MlB1bii6qUnX4iIiNRf5dVGl2K320lOTiY1NfWq57bZbKxatYoJEyZccruarnNUq4iIyKWoweNB+vXr5/45MzOTdu3aVfrx5NU9v4iIiEhdKy4uxsvLq66XISIiUi+oweNB0tPT8fHxISQkhAMHDvDKK6+Uekz66tWr2bFjB06nkzFjxtCmTRv3PoMGnf9GaezYsYwfP56QkBDmzJnDyZMnKSoqYsCAASQkJADnvyEbMGAAO3fuxNvbm6SkJJo0aVJqrIyMDNauXYvT6aRly5aMGjUKq9VaZ38bERERMQabzcby5cvx8/MjKyuLefPm8fbbb/Ptt99SVFRE//79ufPOO0vtY7fbWbBgAQUFBQAMGzaMzp07Y7PZeO+99wgICODo0aOEh4czatQoTCYTX3/9NUuXLsVqtdK5c+e6iCoiInJF1ODxQHFxcaxevZqhQ4fSsWNH9+sBAQEkJyfz6aefsmrVKp566qlLjjNy5Ej8/f0pLCxk4sSJxMbGEhAQQEFBAZGRkTz00EO89dZbrF27lsGDB5faNzY21t0QWrZsGevWreOuu+4qM0dGRgYZGRnA+adc1GfBwcHVPqbFYqmRceszZTYGZTYGI2YWz3Do0CFSU1MJCQkhIyMDX19fZs2aRVFREZMnT6Z79+6ltg8KCuL555/H29ub7Oxs5s+f765LDh06xNy5c2natCmTJ0/mu+++Izw8nNdee40XXniBVq1aMW/evHLXUdt1Tn36PBrp+GCkrGCsvEbKCsbKa6SsF1ODpwGJjY0FIDw8nK1bt152+48//pht27YBkJOTQ3Z2NgEBAVgsFmJiYtxj7dq1q8y+R48eZdmyZeTm5uJwOMoUUhckJCS4G0H1XU5OTrWPGRwcXCPj1mfKbAzKbAyemjk0NLSulyA1LCIigpCQEAC++eYbjhw5wpYtWwDIy8sjOzub1q1bu7cvLi5m8eLFHD58GLPZTHZ2dqmxmjdvDkBYWBh2u919xvSFMW677TZ3I+ditV3n1KfPo6ceH6rCSFnBWHmNlBWMlbehZ62o1lGDpwGxWM7/z2k2mykuLgbAy8sLl8vl3qawsBA4f3rz7t27mTFjBlarlalTp1JUVOTex2QylRnrYmlpaSQlJREWFkZmZiY2m61Gs4mIiIhccPFl4S6XiyeeeIIePXqU2sZut7t//uijjwgKCiIlJQWXy8Ujjzzifq9Ro0bun81mMyUlJTW3cBERkRqkBo+H8vHxIT8//7LbtWjRgp07dwJw8OBBd7GTl5eHn58fVquV48ePs3///iua3+Fw0LRpU5xOJxs3bqz0zZ719AcRERGpTj169GDNmjVER0djsVjIysoqU5fk5eXRvHlzzGYzn3/++WWbOKGhodjtdk6cOEGrVq3YtGlTpdaiOkdEROqSGjz1VGFhYal76AwcOLDU+3369GHhwoWlbrJcnri4ODZs2MCYMWOIiIhwn8rVo0cPPvvsM0aPHk3r1q2JjIy8ovUNGTKESZMmERgYSGRkZKWaTSIiIiLV7fbbb8dutzN+/HgAAgMDSUpKKrVN//79SU1NZcOGDXTv3v2yD4bw9vbmz3/+M7Nnz8ZqtRIVFYXD4aixDCIiItXB5Lr4+h2RGpaVlVXXS6hVDf3az/IoszEoszF4ambdg0fqipHqHE89PlSFkbKCsfIaKSsYK29Dz1pRrWOu5XWIiIiIiIiIiEg1U4NHRERERERERMTDqcEjIiIiIiIiIuLhdJPlBmro0KG8+eabldrWZrNhsVjo3LnzJbdbvnw5Xbp0oVu3blVeV/GTg6q8b03SUy9EREQangv1kN1u5/vvv+eWW2655PZ2u53k5GRSU1OrNF9N1TmqU0REpDJ0Bo9gs9n47rvvLrvdkCFDrqq5IyIiIlIXfv7550o/6lxERMRT6QweA9m+fTsrV67E6XQSEBDAqFGjKCws5LPPPsNsNrNx40aeeOIJFixYwIIFCzCbzTgcDkaPHs0//vEPXnvtNWJiYoiLi2PFihXs2LGDwsJCOnXqxIgRIzCZTHUdUURERKSMd955h2PHjpGUlER8fDy9e/dmwYIFFBQUADBs2LAyZzJPmTKFJ554grCwMAAmT57M8OHD3b+LiIjUN2rwGEhUVBQzZ87EZDKxdu1aPvzwQx599FHuvPNOfHx8GDTo/GnFYWFhfPvtt0RHR7Nz5066d++OxVL6P5Xf/e533HfffQD84x//YMeOHfTq1avMnBkZGWRkZAAwe/bsGk5YdcHBwTUyrsViqbGx6ytlNgZlNgYjZpaG6eGHH2bVqlVMmDABgIKCAp5//nm8vb3Jzs5m/vz5ZeqUvn37kpmZyeOPP05WVhZFRUVlmju1VefUx8+hkY4PRsoKxsprpKxgrLxGynoxNXgM5NSpU7z88sucPn0ap9NJSEhIudvddNNNfPHFF0RHR7N582b69+9fZps9e/bw4YcfUlBQwLlz52jXrl25DZ6EhAQSEhKqPUt1y8nJqZFxg4ODa2zs+kqZjUGZjcFTM4eGhtb1EqSeKy4uZvHixRw+fBiz2Ux2dnaZbW688Ub+85//8Mc//pHPP/+cPn36lNmmtuqc+vg59NTjQ1UYKSsYK6+RsoKx8jb0rBXVOmrwGMiSJUsYOHAgvXr1wmaz8d5775W7Xa9evXj33Xc5d+4cBw8eJDo6utT7hYWFLF68mFmzZhEcHEx6ejqFhYW1EUFERETkqn300UcEBQWRkpKCy+XikUceKbON1WqlW7dubN++nS+//LJen4ksIiICavAYSl5eHs2aNQNg/fr17tcbN25Mfn6++3cfHx86duzI66+/TkxMDGZz6XtxFxUVARAYGIjD4eCrr74iNja2UmvQUyBERESktv221snLy6N58+aYzWY+//xzSkpKyt3vjjvuIDk5maioKPz9/S87j+ocERGpS2rwNFCFhYU89dRT7t8HDhzI/fffz9y5c/Hz8yM6Ohq73Q5ATEwMc+fOZdu2bQwbNowuXbpw0003MXfuXKZOnVpmbD8/P+644w7Gjh1LkyZN6NixY23FEhEREbli7du3x2w2u2+y3L9/f1JTU9mwYQPdu3fHarWWu194eDiNGzemb9++tbxiERGRK2dyuVyuul6EGEdWVlZdL6FWNfRrP8ujzMagzMbgqZl1Dx6pLqdOnWLatGnMmzevzBnN5TFSneOpx4eqMFJWMFZeI2UFY+Vt6Fl1Dx4RERERkUpav349y5Yt49FHH61Uc0dERKSuqcEjIiIiIvIb8fHxxMfH1/UyREREKk1fR4iIiIiIiIiIeDidwdNA/PLLLyxdupQDBw7g6+tLkyZNeOyxx67qPgR2u53vv/+eW265BYADBw6wfv16hg0bVuUxi58cVOV9q4uecCEiIlI//PLLL7zxxhvs378fPz8/LBYL99xzD717967rpVVJTdQ5qltERKSy1OBpAFwuFykpKcTHx/Pcc88BcPjwYX799Vd3g6e4uBgvL68rGvfnn39m06ZN7gZPx44d9cQsERERqRYX1y/PPvsscL722L59e6X2r0ptIyIi0pCpwdMA2Gw2LBYL/fr1c78WFhaGzWbjhRdewM/Pj6ysLFJSUli0aBEHDhzAy8uLRx991P249AULFlBQUADAsGHD6Ny5M++88w7Hjh1zP1K0Q4cOrFq1igkTJvDDDz/w+uuvU1RUhLe3NyNHjtRTS0RERKTS9uzZU6Z+adGiBXfddRclJSW8/fbbfPvttxQVFdG/f3/uvPNObDYby5cvd9c2I0aMID09HT8/P44cOcKNN95I+/bt+fjjjyksLCQpKYlWrVqxfft2Vq5cidPpJCAggFGjRtGkSRPS09PJycnBbreTk5PDgAEDGDBgAMuXL8ff35+7774bgHfffZegoCAGDBhQV38uERGRy1KDpwE4cuQIHTp0KPe9Q4cOkZqaSkhICKtWrQIgNTWV48ePM2PGDObPn09QUBDPP/883t7eZGdnM3/+fGbPns3DDz/sbujA+UbSBaGhobz44ot4eXmxa9cu3nnnHcaNG1dm/oyMDDIyMgCYPXt2dUevkuDg4Fqby2Kx1Op89YEyG4MyG4MRM0vtOXr0aIX1y7p16/D19WXWrFkUFRUxefJkunfvDpSubWw2Gz/++CPz5s3D39+fv/zlL9xxxx3MmjWLjz/+mNWrV/P4448TFRXFzJkzMZlMrF27lg8//JBHH30UOP9o8ylTppCfn89zzz1Hv3796Nu3L6mpqdx9992UlJTwxRdf8NJLL5VZZ23UOfX1M2ik44ORsoKx8hopKxgrr5GyXkwNngYuIiKCkJAQAPbt28ddd90FQJs2bWjRogXZ2dm0aNGCxYsXc/jwYcxmM9nZ2ZcdNy8vj7S0NE6cOAGcP026PAkJCSQkJFRTmuqRk5NTa3MFBwfX6nz1gTIbgzIbg6dm1hmlnmnRokV899137qL8yJEjbNmyBThfd2RnZ2OxWErVNnD+EvKmTZsC0KpVK7p16wZA+/bt2bNnDwCnTp3i5Zdf5vTp0zidzlL79+zZk0aNGtGoUSOCgoL49ddfCQkJwd/fn0OHDvHrr78SFhZGQEBAmTXXRp1TXz+Dnnp8qAojZQVj5TVSVjBW3oaetaJaRw2eBqBdu3Z89dVX5b5ntVovu/9HH31EUFAQKSkpuFwuHnnkkcvus3z5crp27UpSUhJ2u51p06Zd8bpFRETEuH5bv/zpT3/izJkzTJw4kebNm/PEE0/Qo0ePUvvYbLYytU2jRo3cP5tMJvfvJpOJkpISAJYsWcLAgQPp1asXNpuN9957z72PxfL/ymGz2ez+0uqOO+4gMzOTX375hb59+1ZPaBERkRqkBk8DEB0dzbvvvktGRob7W6Qff/yRvXv3ltquS5cubNy4kejoaLKyssjJySE0NJS8vDyaN2+O2Wzm888/dxdDjRs3Jj8/v9w58/LyaNasGQCZmZmVXqueBCEiIiLw/+qXNWvWuO/DU1hYCECPHj1Ys2YN0dHRWCwWsrKy3HVHVVxct6xfv75S+/Tu3Zvly5dTXFzsvgn05ajOERGRuqQGTwNgMpkYN24cS5cu5YMPPqBRo0a0aNGCG264odR2/fr1Y9GiRYwdOxYvLy9GjhxJo0aN6N+/P6mpqWzYsIHu3bu7vxlr3749ZrO51E2WL7jnnntIS0tj5cqV9OzZs1bzioiIiOczmUwkJSXxxhtv8MEHHxAYGIiPjw+PPPIIcXFx2O12xo8fD0BgYCBJSUlVnuv+++9n7ty5+Pn5uR8wcTkWi4WuXbvi5+eH2Wyu8twiIiK1xeRyuVx1vQgxjqysrLpeQq1q6Nd+lkeZjUGZjcFTM+sePFIdSkpKGD9+PGPGjKF169aV2sdIdY6nHh+qwkhZwVh5jZQVjJW3oWetqNbR1xEiIiIiIhc5duwYzzzzDNddd12lmzsiIiJ1TZdoiYiIiIhcpG3btixYsKCulyEiInJFdAaPiIiIiIiIiIiH0xk8HmblypVs2rQJs9mMyWRixIgRvP322wwdOpSOHTtW2zxDhw7lzTffLPXaqVOneP311xk7dmyVxy1+ctDVLu2K6YkWIiIiDcOQIUNo3769+/ekpCRCQkLqcEWlVVedo9pFRESqQg0eD/L999+zY8cOkpOTadSoEWfOnMHpdNba/M2aNbuq5o6IiIjI1fD29iYlJaXc91wuFy6XS0+8EhERw1KDx4OcPn2agIAAGjVqBJx/ZOhvbdq0if/+978AXH/99fzxj39kzZo1/PTTTwwdOhSAzMxMDhw4wPDhw5kzZw4nT56kqKiIAQMGkJCQUGq8M2fOkJyczODBg2nbti3JycmkpqZit9tZsGABBQUFAAwbNozOnTvXZHwRERGRUux2OzNnziQyMpKDBw8yceJE3n//fQ4cOEBhYSFxcXE88MADACQmJhIfH8+OHTtwOp2MGTOGNm3a4HA4WLJkCQcOHMBkMnHfffcRFxfHN998Q3p6Ok6nk5YtWzJy5Eh8fHzqOLGIiEjF1ODxIN27d2fFihU8++yzXHfdddx0001ce+217vdPnTrF22+/TXJyMn5+fsyYMYOtW7cSFxfH3/72N3eD54svvuAPf/gDACNHjsTf35/CwkImTpxIbGwsAQEBAPzyyy/MmTOHBx98kG7dumG3291zBQUF8fzzz+Pt7U12djbz589n9uzZZdackZFBRkYGQLnv14bg4OA6mRfAYrHU6fx1QZmNQZmNwYiZpX4rLCwkKSkJgJCQEB577DFOnDhBYmIinTp1AuChhx7C39+fkpISXnzxRX788UeuueYaAAICAkhOTubTTz9l1apVPPXUU6xYsQJfX19SU1MBOHfuHGfOnGHlypVMnjwZHx8f3n//fT766CPuu+++UuupqTrHEz53Rjo+GCkrGCuvkbKCsfIaKevF1ODxID4+PiQnJ7N3715sNhvz5s3jkUcecb9/4MABunbt6j6z59Zbb2Xv3r307t2bli1b8v3339O6dWuOHz/uPtvm448/Ztu2bQDk5OSQnZ1NQEAAxcXFTJ8+neHDh5dqIl1QXFzM4sWLOXz4MGazmezs7HLXnJCQUOasoNqWk5NTZ3MHBwfX6fx1QZmNQZmNwVMzh4aG1vUSpIb89hItu91OcHCwu7kD57/IWrt2LcXFxZw+fZpjx465GzyxsbEAhIeHs3XrVgB2797Nc889597f39+fHTt2cOzYMSZPngyA0+ksNccFNVXneMLnzlOPD1VhpKxgrLxGygrGytvQs1ZU66jB42HMZjNdu3ala9eutG/fnszMzErtd9NNN/Hll1/Spk0bevfujclkwmazsXv3bmbMmIHVamXq1KkUFRUB4OXlRYcOHfj666/LbfB89NFHBAUFkZKSgsvlKtVoEhEREaktF182ZbfbWbVqFbNmzcLf35+0tDR3bQPnv9GF8/VUcXFxhWO6XC6uu+66Uo0fERGR+k4NHg+SlZWFyWSidevWABw+fJgWLVpw9OhRACIiInj99dc5c+YM/v7+bN68md/97ncA9O7dm//+978cPnzY3YzJy8vDz88Pq9XK8ePH2b9/f6n5Ro4cydy5c3n//fe59957S72Xl5dH8+bNMZvNfP7555SUlFQqg54KISIiIjUlLy8PHx8ffH19+eWXX/j666/p2rXrJffp1q0bn376KY8//jhw/hKtTp06sXjxYk6cOEGrVq1wOBycOnXqsmeHqc4REZG6pAaPB7lwE8Dc3Fy8vLxo1aoVI0aMYO7cuQA0bdqUhx9+mGnTpgHnb7J8ww03AOdPN27Tpg3Hjh0jIiICgB49evDZZ58xevRoWrduTWRkZKn5zGYzzz77LHPmzKFx48Zcf/317vf69+9PamoqGzZsoHv37lit1tr4E4iIiIhUKCwsjLCwMEaPHk3z5s0r9QCIwYMHs2jRIsaOHYvZbOa+++4jNjaWxMRE5s+f7z4D6MEHH9TlfyIiUq+ZXC6Xq64XIcaRlZVV10uoVQ392s/yKLMxKLMxeGpm/R/hUleMVOd46vGhKoyUFYyV10hZwVh5G3rWimodcy2vQ0REREREREREqpkaPCIiIiIiIiIiHk4NHhERERERERERD6ebLHu4IUOG0L59e/fvN998c5knXl2wdetWQkNDadu2bZXmOnDgAOvXr2fYsGFV2h+g+MlBVd73SugpFiIiIg3LL7/8wtKlSzlw4AC+vr40adKExx57rF7dc6m66hzVMSIiUhVq8Hg4b29vUlJSKrXttm3biImJqXKDp2PHjnTs2LFK+4qIiIhUlcvlIiUlhfj4eJ577jkADh8+zK+//lrlBo/L5cLlcmE264R2ERFpGNTgaaDefvtttm/fjpeXF926dSM2Npbt27fz7bff8p///IexY8ficDhYuHAhBQUFtGzZkqeffhp/f3+mTp1KREQENpuNvLw8nnrqKbp06YLNZmPVqlVMmDCBH374gddff52ioiK8vb0ZOXJkvfoGTURERBoOm82GxWKhX79+7tfCwsJYsGABZ8+epXfv3gC88sor3HjjjeTm5rJ161by8vI4deoUt956K/fffz92u52ZM2cSGRnJwYMHmThxImPGjOHNN98EYMuWLezYsYPExES+/PJLVqxYgdlsxtfXl2nTptVJdhERkcpSg8fDFRYWkpSU5P7997//Pddddx1bt27l5ZdfxmQykZubi5+fH7169SImJoa4uDgAxo0bx7Bhw7j22mtZvnw5K1as4PHHHwegpKSEWbNmsXPnTlasWMHkyZNLzRsaGsqLL76Il5cXu3bt4p133mHcuHFl1peRkUFGRgYAs2fPrqG/QlnBwcG1NtelWCyWerOW2qLMxqDMxmDEzFI/HTlyhA4dOpR5/fbbb+ejjz6id+/e5OXl8d1335GYmMjGjRv54YcfSE1NxWq1MnHiRHr27ElAQAAnTpwgMTGRTp06XXLOFStW8Le//Y1mzZqRm5tb7jY1Ved4wufOSMcHI2UFY+U1UlYwVl4jZb2YGjwerrxLtIqLi/H29uaf//wnMTExxMTElNkvLy+P3Nxcrr32WgDi4+OZN2+e+/0L34SFh4djt9vL3T8tLY0TJ0645yxPQkICCQkJVQt3FXJycmp9zvIEBwfXm7XUFmU2BmU2Bk/NrDNKjePaa69l0aJFnDlzhi1bthAbG4uXlxcA3bp1IyAgADhf1+zbt48bbriB4ODgyzZ3ADp37kxaWho33ngjsbGx5W5TU3WOJ3zuPPX4UBVGygrGymukrGCsvA09a0W1ji46boC8vLx46aWXiIuLY8eOHcycOfOKx2jUqBEAZrOZkpKSMu8vX76crl27kpqayvjx4ykqKrrqdYuIiIiUp127dhw6dKjc92677TY2bNhAZmYmt99+e4VjmEwmAHx8fMp9Hc6fGX3BiBEjePDBBzl58iQTJkzg7NmzVxNBRESkxukMngbI4XBQUFBAz549iYqK4i9/+QsAjRs3Jj8/HwBfX1/8/f3Zu3cvXbp0YcOGDXTp0qXSc+Tl5dGsWTMAMjMzK72fngohIiIiVyo6Opp3332XjIwM9xkzP/74I3l5efTp04dJkybRpEmTUg+S2L17N+fOncPb25tt27bx9NNPlzt2UFAQx44dIzQ0lK1bt9K4cWMATpw4QWRkJJGRkXz99decPHnSfUZQRVTniIhIXVKDx8P99h48PXr0YMCAAcyZM4eioiJcLhePPvooADfddBOvvfYan3zyCWPGjCExMdF9k+WQkBBGjhxZ6Xnvuece0tLSWLlyJT179qz2XCIiIiIXmEwmxo0bx9KlS/nggw9o1KgRLVq04PHHH6dJkya0adOGG264odQ+HTt2JDU1lZMnT3LrrbfSsWPHci87f+SRR0hOTiYwMJDw8HAcDgcAb731FtnZ2cD5BtM111xT80FFRESugsnlcrnqehFiHFlZWXW9hFrV0K/9LI8yG4MyG4OnZtY9eIyloKCAcePGkZycjK+vL3D+7OIDBw4wfPjwWl2LkeocTz0+VIWRsoKx8hopKxgrb0PPWlGtozN4RERERMQj7dq1i3/961/cfffd7uaOiIiIUanBIyIiIiIeqVu3brz66qtlXu/Tpw99+vSp/QWJiIjUIT1FS0RERERERETEw+kMnnpsyJAhtG/fnuLiYry8vLjtttu4++67MZvrR19u6NChvPnmm1e0T/GTg2poNf+PnmAhIiJiLA888AC33HILzzzzDADFxcWMGDGCyMhIJkyYUOF+NpuNVatWMWHCBGw2GxaLhc6dO1d5HVdb56iGERGRq6EGTz3m7e1NSkoKAL/++iuvvPIK+fn5PPDAA3W6LpfLhe7NLSIiIvWF1Wrl6NGjFBYW4u3tza5du2jWrNkVjWGz2fDx8bmqBo+IiEhdUoPHQwQFBTFixAgmTpzI/fffj8vl4u233+bbb7+lqKiI/v37c+edd2Kz2XjvvfcICAjg6NGjhIeHM2rUKEwmE4mJidx8883873//w8vLixEjRvDuu+9y4sQJ/u///o9+/frhcDiYM2cOubm5OJ1OHnzwQW644QbsdjszZ84kMjKSgwcPMnHiRPfazpw5Q3JyMoMHD9Yj00VERKROXH/99ezcuZO4uDg2b97MzTffzL59+wD44YcfeP311ykqKsLb25uRI0eWegKJ3W7ns88+w2w2s3HjRoYNG0Zubi4rV67E6XQSEBDAqFGjaNKkSR2lExERuTw1eDxIy5YtKSkp4ddff2X79u34+voya9YsioqKmDx5Mt27dwfg0KFDzJ07l6ZNmzJ58mS+++47oqKigPOPi0tJSWHp0qW8+uqrTJ8+naKiIsaOHUu/fv1o1KgR48aNw9fXlzNnzvC3v/2NXr16AXDixAkSExPp1KmTe02//PILc+bM4cEHH6Rbt25l1pyRkUFGRgYAs2fPruk/kTtjfWGxWOrVemqDMhuDMhuDETOL57r55ptZsWIFPXv25Mcff6Rv377uBk9oaCgvvvgiXl5e7Nq1i3feeYdx48a59w0JCeHOO+/Ex8eHQYPOX2Z17tw5Zs6ciclkYu3atXz44Yc8+uijpeas7jrHkz5vRjo+GCkrGCuvkbKCsfIaKevF1ODxUN988w1Hjhxhy5YtAOTl5ZGdnY3FYiEiIoLmzZsDEBYWht1udzd4LjRr2rdvj8PhoHHjxjRu3BiLxUJubi5Wq5V3332XvXv3YjKZOHXqFL/++itwvui4uLlTXFzM9OnTGT58ONdee22560xISCAhIaHG/g7lycnJqdX5LiU4OLherac2KLMxKLMxeGrmi8/MEOO45ppr+Pnnn9m8eTPXX399qffy8vJIS0vjxIkTwPka5nJOnTrFyy+/zOnTp3E6nYSEhJTZprrrHE/6vHnq8aEqjJQVjJXXSFnBWHkbetaKah01eDzITz/9hNlsJigoCJfLxRNPPEGPHj1KbWOz2WjUqJH7d7PZTElJift3i8Xifv232xUXF7Np0ybOnDnD7NmzsVgsJCYmUlhYCICPj0+puby8vOjQoQNff/11hQ0eERERkdrSq1cv3nzzTaZOncrZs2fdry9fvpyuXbuSlJSE3W5n2rRplx1ryZIlDBw4kF69erkvgRcREanP1ODxEGfOnGHhwoX87ne/w2Qy0aNHD9asWUN0dDQWi4WsrKwrvplgefLy8ggKCsJisbBnzx5+/vnnS24/cuRI5s6dy/vvv8+999572fH1dAgRERGpKX379sXX15f27dtjs9ncr+fl5bnrpMzMzHL3bdy4Mfn5+eXus379+krNrzpHRETqkho89VhhYSFJSUnux6TfeuutDBw4EIDbb78du93O+PHjAQgMDCQpKemq57zllltITk5m7NixdOzYkTZt2lxye7PZzLPPPsucOXNo3Lgx/fv3v+o1iIiIiFRF8+bNGTBgQJnX77nnHtLS0li5cmWFD4SIiYlh7ty5bNu2jWHDhnH//fczd+5c/Pz8iI6Oxm631/TyRURErorJpeddSy3Kysqq6yXUqoZ+7Wd5lNkYlNkYPDWz7sEjdcVIdY6nHh+qwkhZwVh5jZQVjJW3oWetqNYx1/I6RERERERERESkmqnBIyIiIiIiIiLi4dTgERERERERERHxcJe9yfLQoUN58803Adi5cydvvPEGzz//PP/73/+wWq3Ex8df9SIyMzM5cOAAw4cPv+qxKmPv3r0sXLgQLy8vZs6cibe3NwC5ubls2rTJfaNgm83GqlWrmDBhQpXmSU9P58MPPyQtLY2goCCg9N+zIitXruQPf/gDAHa7neTkZFJTU6u0Bqjev296ejo+Pj4MGjSoSvsXP1m1/a6EnmAhIiJS/5VXE61Zs8ZdX2ZmZtKtWzf3k6wSExOZNWsWgYGBNbami+evisrUOapTRESkplT6DJ7du3fz+uuvM3HiRFq0aEG/fv2qpblTFzZu3Mi9995LSkqKu7kD5xs8a9asqda5AgICWLVq1RXt89///rfa5i8uLq62sURERERq0sX1ZWZmJqdPn66z+UVERDxNpR6T/u233/Laa68xceJEWrVqBZQ+k2Pq1KlERERgs9nIy8vjqaeeokuXLhQUFJCWlsbRo0cJDQ3l9OnTDB8+nI4dO/L555/z/vvv4+vryzXXXEOjRo2A82es/POf/+Ts2bMEBgYycuRIgoODSUtLw9vbm8OHD/Prr7/y9NNPs379evbv309ERASJiYll1r17927efPNNiouL6dixI08++SQbNmzgyy+/5JtvvuHrr7/mmWeecW//zjvvcOLECZKSkujWrRs9e/bE4XCQmprK0aNHCQ8PZ9SoUZhMJg4ePMgbb7yBw+Fwr7Np06Zl1tC3b1/Wr1/Pvffei7+/f6n3NmzYwCeffILT6SQyMpI//elPvPvuu+7Ho7dr144HH3yQkpIS/vWvf/H999/TrFkz/vrXv+Lt7c2JEydYvHgxZ86cwWq18uc//5k2bdqQlpZGo0aNOHz4MJ07d+aaa65xz7l9+3ZWrlyJ0+kkICCAUaNG0aRJE9LT08nJycFut5OTk8OAAQPcjxlduXIl69evJzAwkObNmxMeHg7Axx9/zGeffYaXlxdt27blueeeq8x/TiIiIiLlulBfhoSEcODAAV555RW8vb2ZOXMmAKtXr2bHjh04nU7GjBlDmzZtypxdPHbsWMaPH09ISAhz5szh5MmTFBUVMWDAABISEoDzZw8NGDCAnTt34u3tTVJSkrseujBWRkYGa9euxel00rJlS0aNGoXVaq2zv42IiMjlXLbB43Q6SUlJYerUqbRp06bC7UpKSpg1axY7d+5kxYoVTJ48mU8//RR/f3/mzZvHkSNH+Otf/wrA6dOnSU9PJzk5GV9fX6ZNm0ZYWBgAS5YsIT4+nj59+rBu3TqWLFni3i83N5cZM2awfft25syZw/Tp02nbti0TJ07k8OHD7jEACgsLefXVV5k8eTKhoaEsWLCANWvWcPfdd7Nv3z5iYmKIi4srleHhhx/m6NGjpKSkAOcv0Tp06BBz586ladOmTJ48me+++46IiAj3ugIDA/niiy949913GTlyZJm/i4+PD3379uXjjz/mgQcecL9+7NgxvvjiC6ZPn47FYmHRokVs3LiRRx55hNWrV7vXYLfbyc7O5tlnn+Wpp55i7ty5bNmyhdtuu41///vfPPnkk7Ru3Zr9+/ezaNEipkyZAsCpU6eYMWMGZrOZzMxM97xRUVHMnDkTk8nE2rVr+fDDD3n00UeB84/2nDJlCvn5+Tz33HP069ePI0eOsHnzZubMmUNxcTHjx493N3g++OADFixYQKNGjcjNzS33v4uMjAwyMjIAmD17doX//VSn4ODgWpmnMiwWS71aT21QZmNQZmMwYmapH+Li4li9ejVDhw6lY8eO7tcDAgJITk7m008/ZdWqVTz11FOXHGfkyJH4+/tTWFjIxIkTiY2NJSAggIKCAiIjI3nooYd46623WLt2LYMHDy61b2xsrLshtGzZMtatW8ddd91Vapuq1DkN5TNlpOODkbKCsfIaKSsYK6+Rsl7ssg0eLy8vOnfuzLp163jiiScq3K53794AhIeHY7fbAdi3b5/7LJD27du7zyTZv38/Xbt2dV9DfeONN5Kdne1+b9y4cQDcdtttvP322+45YmJiMJlMtG/fnqCgINq3bw9Au3btsNvtpRo8WVlZhISEuJ8PHx8fz6effsrdd99diT/L/xMREUHz5s0BCAsLw2634+vry9GjR5k+fTpwvrlV3tk7F9x111389a9/5f/+7//cr+3Zs4dDhw4xceJE4HxDqqJrykNCQtzZwsPD+fnnn3E4HHz33XfMnTvXvZ3T6XT/HBcXh9lc9gq8U6dO8fLLL3P69GmcTichISHu93r27EmjRo1o1KgRQUFB/Prrr+zdu5fevXu7v7Hq1auXe/v27dvzyiuvcMMNN7j/9/+thIQEd3FUW3Jycmp1vksJDg6uV+upDcpsDMpsDJ6a+cK//dLwxMbGAufroa1bt152+48//pht27YB5+uD7OxsAgICsFgsxMTEuMfatWtXmX2PHj3KsmXLyM3NxeFw0L179zLbVKXO8cTPVHk89fhQFUbKCsbKa6SsYKy8DT1rRbXOZRs8JpOJ0aNH8+KLL5a6+e9vXbjEymw2U1JSchVLrdiFOUwmk/vnC7/X9JxQOlvbtm3dpwtfjp+fHzfffDOffvqp+zWXy0V8fDwPP/zwFa+hsLCQkpIS/Pz83Gf6/JaPj0+5ry9ZsoSBAwfSq1cvbDYb7733nvs9i+X//edgNpsve/+eiRMn8u2337Jjxw7++9//8ve//x0vL6/L5hERERGpigu1ysV1ipeXFy6Xy71NYWEhcP5M7N27dzNjxgysVitTp06lqKjIvY/JZCoz1sXS0tJISkoiLCyMzMxMbDZbjWYTERG5WpW6B4/VamXixIm88MILNGnShNtvv71Sg0dFRfHll18SHR3NsWPHOHLkCACRkZEsXbqUs2fP0rhxY7Zs2eI+u6dTp0588cUX3HbbbWzatImoqKgqBQsNDcVut3PixAlatWrFhg0buPbaay+5T+PGjcnPz6/U2GfOnOH777+nU6dOOJ1OsrOzadeuXYX7DBw4kIkTJ7obRNdddx1z5szh7rvvJigoiHPnzpGfn0+LFi2wWCw4nc5SDZff8vX1JSQkhC+//JIbb7wRl8vFjz/+WOospvLk5eW5n0axfv36y2bt0qULr776Kr///e8pLi5mx44dJCQkUFJSQk5ODtHR0URFRfHFF1/gcDjw8/O75Hh6coSIiIhUho+PT6XqshYtWrBz504ADh486D6TPC8vDz8/P6xWK8ePH2f//v1XNL/D4aBp06Y4nU42btzorp8uRXWOiIjUpUo1eAD8/f2ZNGkSU6ZMqfTjKfv160daWhqjR4+mTZs2tG3bFl9fX5o2bcr999/P888/j6+vb6mmxLBhw3j11Vf58MMP3Tcvrgpvb29GjhzJ3Llz3TdZvvPOOy+5T0BAAJ07d2bs2LH06NGDnj17lrudxWJh7NixvP766+Tl5VFcXMyAAQMu2eAJDAykd+/e/P/+f/8/4PwZQA8++CAzZszA5XLh5eXF8OHDadGiBXfccQdJSUl06NCBBx98sMIxn3nmGRYuXOi+afLNN9982QbP/fffz9y5c/Hz8yM6OtpdBFUkPDycm266iaSkJAIDA93XwZeUlPCPf/yDvLw84PxlaJdr7oiIiIhcUFhYWOoeOgMHDiz1fp8+fVi4cGGpmyyXJy4ujg0bNjBmzBgiIiLcp6336NGDzz77jNGjR9O6dWsiIyOvaH1Dhgxh0qRJBAYGEhkZWalmk4iISF0yuS4+p7WalZSU4HQ63U98mj59OvPnz7/kmSnSsGVlZdX1EmpVQ7/2szzKbAzKbAyemln34JG6YqQ6x1OPD1VhpKxgrLxGygrGytvQs1b5HjxXo6CggGnTplFcXIzL5eJPf/qTmjsiIiIiIiIiItWsRrstjRs3rrVHY4uIiIiIiIiIGFXZ52iLiIiIiIiIiIhH0fVSHmbIkCG0b98eOP9Yz2HDhtG5c+dL7jN06FDefPPNS27zr3/9i4EDB9K2bdtqW2t5ip8cdNVj6AkVIiIinq+8+mTNmjVYrVbi4+PJzMykW7du7qdXJSYmMmvWrEo/7KMqLp6/Ki5X56iGERGRmqQGj4fx9vYmJSUFgK+//pp33nmHadOmXfW4Fz/FQkRERKQu9OvXz/1zZmYm7dq1q9TjyWtifhEREU+jBo8Hy8/PL/Vo8g8//JAvv/ySoqIievfuzQMPPFBq+5KSEpYsWcKePXto3rw5FouFvn37EhcXx9SpUxk6dCgdO3Ys9Y3ali1b2LFjB4mJiaSlpeHt7c3hw4f59ddfefrpp1m/fj379+8nIiKCxMTEWs0vIiIiDUt6ejo+Pj6EhIRw4MABXnnllVKPSV+9ejU7duzA6XQyZswY2rRp495n0KDzZ8+MHTuW8ePHExISwpw5czh58iRFRUUMGDCAhIQE4PzZQwMGDGDnzp14e3uTlJREkyZNSo2VkZHB2rVrcTqdtGzZklGjRmG1WuvsbyMiInI5avB4mMLCQpKSkigqKuL06dNMmTIFgG+++Ybs7GxeeuklXC4Xc+bM4dtvv+Xaa69177t161Z+/vln5s6dy5kzZxg9ejR9+/a9ovlzc3OZMWMG27dvZ86cOUyfPp22bdsyceJEDh8+TFhYWKntMzIyyMjIAKi2G24HBwdXyzi1wWKxeNR6q4MyG4MyG4MRM0v9EBcXx+rVq91fPl0QEBBAcnIyn376KatWrbrsGcgjR47E39+fwsJCJk6cSGxsLAEBARQUFBAZGclDDz3EW2+9xdq1axk8eHCpfWNjY90NoWXLlrFu3TruuuuuUttcaZ3TkD5PRjo+GCkrGCuvkbKCsfIaKevF1ODxMBdfovX999+zYMECUlNT+eabb9i1axd//etfAXA4HJw4caJUg2ffvn3ExcVhNptp0qQJXbt2veL5Y2JiMJlMtG/fnqCgIPf9gNq1a4fdbi/T4ElISHAXR9UlJyenWserScHBwR613uqgzMagzMbgqZlDQ0PreglSQ2JjYwEIDw9n69atl93+448/Ztu2bcD5+iE7O5uAgAAsFgsxMTHusXbt2lVm36NHj7Js2TJyc3NxOBx07969zDZXWud44uepIp56fKgKI2UFY+U1UlYwVt6GnrWiWkcNHg/WqVMnzp49y5kzZwC49957ufPOO696XJPJ5P65sLCw1HuNGjVyb3Ph5wu/l5SUXPXcIiIiIhWxWM6XrmazmeLiYgC8vLxwuVzubS7ULjabjd27dzNjxgysVitTp06lqKjIvc+FeufisS6WlpZGUlISYWFhZGZmYrPZajSbiIjI1VKDx4MdP36ckpISAgIC6N69O8uXL+fWW2/Fx8eHU6dO4eXlRVBQkHv7zp07s379euLj4zlz5gw2m41bbrmlzLhBQUEcO3aM0NBQtm7dSuPGjattzXp6hIiIiFSGj48P+fn5l92uRYsW7Ny5E4CDBw9it9sByMvLw8/PD6vVyvHjx9m/f/8Vze9wOGjatClOp5ONGzdW6mbPqnNERKQuqcHjYS7cg+eCxMREzGYz3bt35/jx4/ztb38DzhdFo0aNKtXgiY2NZffu3YwZM4bmzZsTHh6Or69vmTkeeeQRkpOTCQwMJDw8HIfDUfPBRERExFAKCwtL3UNn4MCBpd7v06cPCxcuLHWT5fLExcWxYcMGxowZQ0REhPu09R49evDZZ58xevRoWrduTWRk5BWtb8iQIUyaNInAwEAiIyMr1WwSERGpSybXxee0SoPncDjw8fHh7NmzTJo0ienTp9OkSZNamz8rK6vW5qoPGvq1n+VRZmNQZmPw1My6B4/UFSPVOZ56fKgKI2UFY+U1UlYwVt6GnlX34BHg/BMecnNzcTqdDB48uFabOyIiIiIiIiJSM9TgMZipU6fW9RJEREREREREpJqZ63oBIiIiIiIiIiJydXQGjwdZuXIlmzZtwmw2YzKZGDFiBG+//TZDhw6lY8eONT7/mjVrsFqtxMfHV3mM4icHVXpbPYlCRETEWDy91rlcnaPaRkREapIaPB7i+++/Z8eOHSQnJ9OoUSPOnDmD0+ms1TX069evVucTERER41CtIyIicnXU4PEQp0+fJiAggEaNGgEQGBhYZptNmzbx3//+F4Drr7+eP/7xj6xZs4affvqJoUOHApCZmcmBAwcYPnw4GzZs4JNPPsHpdBIZGcmf/vQnzGYzQ4cOZcCAAezcuRNvb2+SkpJo0qQJ6enp+Pj4MGjQIDIyMli7di1Op5OWLVsyatQorFZr7f1BREREpEFRrSMiInJ11ODxEN27d2fFihU8++yzXHfdddx0001ce+217vdPnTrF22+/TXJyMn5+fsyYMYOtW7cSFxfH3/72N3fR88UXX/CHP/yBY8eO8cUXXzB9+nQsFguLFi1i48aNxMfHU1BQQGRkJA899BBvvfUWa9euZfDgwaXWExsbS0JCAgDLli1j3bp13HXXXWXWnZGRQUZGBnD+CV5XIjg4+Iq2r48sFkuDyHEllNkYlNkYjJhZ6o4n1jpXWuc0pM+TkY4PRsoKxsprpKxgrLxGynoxNXg8hI+PD8nJyezduxebzca8efN45JFH3O8fOHCArl27ur/tuvXWW9m7dy+9e/emZcuWfP/997Ru3Zrjx4/TuXNnPv30Uw4dOsTEiRMBKCwsdO9rsViIiYkBIDw8nF27dpVZz9GjR1m2bBm5ubk4HA66d+9e7roTEhLcxdGVysnJqdJ+9UlwcHCDyHEllNkYlNkYPDVzaGhoXS9BqsATa50rrXM88fNUEU89PlSFkbKCsfIaKSsYK29Dz1pRraMGjwcxm8107dqVrl270r59ezIzMyu130033cSXX35JmzZt6N27NyaTCZfLRXx8PA8//HCZ7b28vDCZTO45i4uLy2yTlpZGUlISYWFhZGZmYrPZriqbiIiIiGodERGRqlODx0NkZWVhMplo3bo1AIcPH6ZFixYcPXoUgIiICF5//XXOnDmDv78/mzdv5ne/+x0AvXv35r///S+HDx92fxN23XXXMWfOHO6++26CgoI4d+4c+fn5tGjRolLrcTgcNG3aFKfTycaNG2nWrFml9tPTI0RERKQ8DaHWUZ0jIiJ1SQ0eD+FwOFiyZAm5ubl4eXnRqlUrRowYwdy5cwFo2rQpDz/8MNOmTQPO33jwhhtuAMDf3582bdpw7NgxIiIiAGjbti0PPvggM2bMwOVy4eXlxfDhwytd9AwZMoRJkyYRGBhIZGQk+fn5NZBaREREjEK1joiIyNUxuVwuV10vQowjKyurrpdQqxr6tZ/lUWZjUGZj8NTMugeP1BUj1TmeenyoCiNlBWPlNVJWMFbehp61olrHXMvrEBERERERERGRaqYGj4iIiIiIiIiIh1ODR0RERERERETEw+kmyw3IL7/8wtKlSzlw4AC+vr40adKExx57rF7di6D4yUGlftfTJkRERORyaqLGsdvtfP/999xyyy0AHDhwgPXr1zNs2LAqj/nbOue3VPeIiEhNUoOngXC5XKSkpBAfH89zzz0HnH+86K+//lrl4sflcuFyuTCbdaKXiIiI1I3K1DjFxcV4eXld0bg///wzmzZtcjd4OnbsSMeOHat17SIiIrVJDZ4GwmazYbFY6Nevn/u1sLAwFixYwNmzZ+nduzcAr7zyCjfeeCO5ubls3bqVvLw8Tp06xa233sr999+P3W5n5syZREZGcvDgQSZOnMiYMWN48803AdiyZQs7duwgMTGRL7/8khUrVmA2m/H19XU/tlRERESkulRU49hsNl544QX8/PzIysoiJSWFRYsWceDAAby8vHj00UeJjo7GbrezYMECCgoKABg2bBidO3fmnXfe4dixYyQlJREfH0+HDh1YtWoVEyZM4IcffuD111+nqKgIb29vRo4cWa/OiBYRESmPGjwNxJEjR+jQoUOZ12+//XY++ugjevfuTV5eHt999x2JiYls3LiRH374gdTUVKxWKxMnTqRnz54EBARw4sQJEhMT6dSp0yXnXLFiBX/7299o1qwZubm55W6TkZFBRkYGALNnzy7zfnBwcBXSeg6LxdLgM/6WMhuDMhuDETNL/VNRjQNw6NAhUlNTCQkJYdWqVQCkpqZy/PhxZsyYwfz58wkKCuL555/H29ub7Oxs5s+fz+zZs3n44YfdDR0430i6IDQ0lBdffBEvLy927drFO++8w7hx48rMf7k657ca0ufJSMcHI2UFY+U1UlYwVl4jZb2YGjwN3LXXXsuiRYs4c+YMW7ZsITY21n0Kc7du3QgICACgd+/e7Nu3jxtuuIHg4ODLNncAOnfuTFpaGjfeeCOxsbHlbpOQkEBCQkKFY+Tk5FQhlecIDg5u8Bl/S5mNQZmNwVMz60wL44iIiCAkJASAffv2cddddwHQpk0bWrRoQXZ2Ni1atGDx4sUcPnwYs9lMdnb2ZcfNy8sjLS2NEydOAOcvASvP5eqc3/LEz1NFPPX4UBVGygrGymukrGCsvA09a0W1jm6u0kC0a9eOQ4cOlfvebbfdxoYNG8jMzOT222+vcAyTyQSAj49Pua8DFBYWun8eMWIEDz74ICdPnmTChAmcPXv2aiKIiIiIlHGpGsdqtV52/48++oigoCBSUlKYPXs2TqfzsvssX76crl27kpqayvjx4ykqKrridYuIiNQ2ncHTQERHR/Puu++SkZHh/ibpxx9/JC8vjz59+jBp0iSaNGlC27Zt3fvs3r2bc+fO4e3tzbZt23j66afLHTsoKIhjx44RGhrK1q1bady4MQAnTpwgMjKSyMhIvv76a06ePOk+I6gienqEiIiIXImKapy9e/eW2q5Lly5s3LiR6OhosrKyyMnJITQ0lLy8PJo3b47ZbObzzz+npKQEgMaNG5Ofn1/unHl5eTRr1gyAzMzMSq9VdY7I/7+9O4+Lsuz3OP6ZYVgFRERE3HBDFMRQNBR3ScVQy8y10tQ8pU9pT57KypRMk8ytovM87qmpqKm5P0onwQ2XXEBcCBURR0R2WWWYOX/4Yo6a5pI4zty/9+vVK2G235f7nrmvue7rum4hhClJB4+FUKlUTJw4kWXLlvHLL79gbW1NjRo1GDFiBC4uLtSuXZs2bdrc8ZhGjRoxe/ZssrKy6NixI40aNSIjI+NPzz1s2DAiIiJwdnamYcOGlJSUALBy5UrjMGc/Pz/q169f+UGFEEIIoSj3a+Pc3a7p0aMHixYt4oMPPsDKyoqxY8dibW1Nz549mT17NrGxsbRs2dI46qdevXqo1eo7Flmu0K9fPyIjI9mwYQOtWrV6qnmFEEKIx6UyGAwGUxchKldpaSkTJ04kIiICBwcH4NbZqPPnzzNq1KinWotWq32qr2dqlj73814kszJIZmUw18yyBo8wFSW1c8z18+FxKCkrKCuvkrKCsvJaetb7tXVkBI+Fi4+P51//+hcvvviisXNHCCGEEEIIIYQQlkU6eCycv78/P/zww59+36VLF7p06fL0CxJCCCGEEEIIIcQTJ1fREkIIIYQQQgghhDBzMoKnEr3++uusWLFC8TUIIYQQQjyMDRs2sG/fPtRqNSqVijFjxvDTTz/x+uuv06hRoyf2OvdqH2VnZ7N06VI++OCDx37e8rf6/uXtcpUtIYQQlUk6eMQjKy8vx8rKytRlCCGEEMKCJCUl8fvvvxMREYG1tTX5+fnodLqn9vqurq5/q3NHCCGEMDXp4HnKpk6dajwLlZ+fz6RJk4iMjGTr1q2kpqYyduxYUlNTmT9/PjNmzCAnJ4fFixeTn5+Pra0t//Vf/0Xt2rWJjIzExsaGlJQU8vLyeOedd4iJieGPP/6gcePGjBs3zviay5YtIz4+HhcXFyZMmICzszMpKSksXLiQ0tJSatasyTvvvIOjo+N969uzZw+HDh2ipKQEvV7PJ598QmRkJJcvX8bT05OcnBxGjRr1RM+uCSGEEEI5cnJycHJywtraGgBnZ+c/3Wffvn1s3LgRgICAAF577TV27drFtWvXeP3114E7rxT69ddfk5WVRVlZGb179yYkJOSO58vPzyciIoJXXnmFOnXqEBERwezZs8nIyOD777+ntLQUgJEjR9K0adPKjC+EEEL8bdLB84zo3bs34eHhHD58mA0bNvDWW29ha2vLggULeOutt6hVqxZ//PEHixYtYsqUKQAUFhby5ZdfcvToUb7++mumTZtGnTp1mDRpEikpKXh5eVFaWkqjRo0YMWIE69evZ926dYwaNYrvv/+ekSNH0rx5c6Kioli/fj0jRoz4yxovXrzIN998g6OjI5s3b8bR0ZG5c+eSmprKhx9+eM/HREdHEx0dDcDMmTNxc3N7on+3Z51Go5HMCiCZlUEyC1G5WrZsyfr16xk/fjwtWrSgffv2NG/e3Hh7dnY2P/30ExEREVSpUoUvv/ySw4cPExQUxKeffmrs4Dlw4AD9+/cHYOzYsTg6OnLz5k0mTZrE888/j5OTEwC5ubl8/fXXDB48GH9/fzIyMoyvVbVqVT777DNsbGy4evUq8+fPZ+bMmX+q+e52zoNY0vtJSZ8PSsoKysqrpKygrLxKyno76eB5RqjVasaOHcvEiRN54YUX8PHxoaSkhHPnzjFnzhzj/W4fqty6dWtUKhX16tWjatWq1KtXD4C6deuSkZGBl5cXKpWK9u3bA9CxY0e++eYbioqKKCwsNDaaOnfuzNy5cx9Yo7+/P46OjgCcPXuW3r17A1CvXj3q169/z8eEhITccbYsMzPzUf4sZs/NzU0yK4BkVgbJbD48PT1NXYJ4DHZ2dkRERHDmzBkSExOZO3cuw4YNM95+/vx5fH19jSN7OnbsyJkzZ2jbti01a9YkKSmJWrVqceXKFeNom+3bt3PkyBHgVhvk6tWrODk5UV5ezrRp0xg1atQdnUgVysvLWbx4MSkpKajVaq5evXrPmu9u5zyIOb6f7sdcPx8eh5KygrLyKikrKCuvpWe9X1tHOnieMisrKwwGAwBlZWV33Hb16lXs7OzIzs4GQK/XU6VKFWbNmnXP56oYwqxSqYz/rvhZr9ff8zEqleqx67O1tf3LxwohhBBC/B1qtRpfX198fX2pV68ee/bseajHtW/fnoMHD1K7dm3atm2LSqUiMTGRhIQEvvzyS2xtbZk6daqxbWNlZUWDBg04ceLEPTt4tm7dStWqVZk1axYGg+GOjiYhhBDiWSWXSX/KatSowYULFwCIi4sz/r6oqIilS5cSHh5OQUEBcXFxODg44O7uzsGDBwEwGAykpKQ80usZDAbj6+zbtw8fHx8cHBxwdHTkzJkzAMTGxtKsWbO/rO9uPj4+xrrS0tJITU19pLqEEEIIIW6n1WrvGCmTkpJCjRo1jD83btyY06dPk5+fj16vZ//+/cbOmbZt23L06FH2799PcHAwcKttVaVKFWxtbbly5Qp//PHHHa83duxYtFotmzZt+lMtRUVFVKtWDbVaTWxs7H1PnN3NauHmv/xPCCGEqEwygqcS3bx5k7ffftv4c1hYGH369GHu3LlER0fTqlUr423Lli2jZ8+eeHp68vbbbxMeHk6zZs147733WLhwIRs2bECn0xEcHIyXl9dD12Bra0tycjIbNmzA2dmZ999/H4Bx48YZF1l2d3dn7NixAPet7249evQgMjKS999/n9q1a1OnTh0cHBwe8S8khBBCCHFLSUkJS5YsobCwECsrKzw8PBgzZoxxqnq1atUYOnQo4eHhwK1Fltu0aQOAo6MjtWvXJi0tjcaNGwPw3HPPsXv3bt5//31q1apFkyZN7ng9tVrN+PHj+frrr7G3tycgIMB4W8+ePZk9ezaxsbG0bNlSRjELIYQwCypDxXwcIR6BXq9Hp9NhY2NDeno606ZNY/78+Wg0f91nqNVqn1KFzwZLn/t5L5JZGSSzMphrZlmDR5iKkto55vr58DiUlBWUlVdJWUFZeS09q6zBI56o0tJSwsPDKS8vx2AwMHr06Ad27gghhBBCCCGEEKJyyDdy8Vjs7e0f6nKgQgghhBBCCCGEqHyyyLIQQgghhBBCCCGEmZMRPAowcOBAOnTowHvvvQdAeXk5Y8aMoUmTJnz88cf3fVxiYiJbtmzh448/JjExEY1GQ9OmTZ9W2UIIIYR4SnJzc1m2bBnnz5/HwcEBFxcXhg8f/kTWM1q7di12dnb07dv3L+83btw47OzsUKlUVKlShX/84x93XEXrSRg3bhxfffUVzs7O960xKiqKZs2a4e/v/8jPX/7WX2eUK2kJIYSoTNLBowC2trZcvnyZmzdvYmNjQ3x8PK6uro/0HImJidjZ2UkHjxBCCGFhDAYDs2bNonPnzkyYMAG4dYnyvLy8p75g9ZQpU3B2dmbt2rX8/PPPd1yN9GkZNGjQU39NIYQQ4kmQDh6FCAgI4NixYwQFBbF//36Cg4M5e/YsAMnJySxdupSysjJsbGwYO3bsHQ26jIwMdu/ejVqtZu/evYwcOZLCwkLjpdudnJx49913cXFxMVE6IYQQQjyuilG6PXr0MP7Oy8sLgKioKI4ePQpAfn4+LVu2ZOzYscTGxrJjxw50Oh1NmjRh9OjRqNVqTpw4werVq9Hr9Tg5OfH5558DkJaWxtSpU8nMzKR379707t37L2vy9vZmx44dxtddsGABWVlZAAwfPhwfHx/Wrl3LtWvXSE9P58aNG/Tt25eQkJA7RiADLF68mEaNGtGlSxcANm/ezPHjx7GxsWH8+PF4eHjc8dqRkZG0bt2aoKAgkpOTWbZsGaWlpWg0Gj7//HPs7e3/3h9cCCGEqCTSwaMQwcHBrF+/nlatWnHp0iW6du1q7ODx9PTkiy++wMrKivj4eFatWsXEiRONj3V3d+eFF164Y3h1QUEB06dPR6VS8euvv7J582beeOONP71udHQ00dHRAMycORM3N7enkPbZodFoJLMCSGZlkMzCUqWmptKgQYN73jZo0CAGDRpEYWEhn3/+Ob169SItLY0DBw4wbdo0NBoNixYtYu/evQQEBPDvf/+b8PBw3N3dKSgoMD6PVqtlypQpFBcXM2HCBHr06PGXV988ceIEbdq0AWDp0qWEhYXh4+NDZmYm06dPZ+7cucbap0+fTklJCR999BGtWrV6YF4HBwdmz55NTEwMy5Ytu+90dZ1Ox7x585gwYQKNGzemqKgIGxubO+5zdzvnQSzp/aSkzwclZQVl5VVSVlBWXiVlvZ108ChE/fr1uX79Ovv37ycgIOCO24qKioiMjCQ9PR24tUbPg2RnZzNv3jxycnLQ6XS4u7vf834hISGEhIQYf87MzPwbKcyPm5ubZFYAyawMktl8PO1pRZbOYDDw3XffERYWRsOGDdm5cycXL15k0qRJANy8eRNnZ2eSkpJo1qyZsU3g6OhofI5WrVphbW2NtbU1VatWJS8vj+rVq//ptcLDwykoKMDOzs44VSohIYG0tDTjfYqKiigpKQEgMDAQGxsbbGxs8PX1JTk5mSpVqvxlnuDgYOP/f/zxx/veT6vVUq1aNRo3bgzc6hi6293tnAcxx/fT/Zjr58PjUFJWUFZeJWUFZeW19Kz3a+tIB4+CBAYGsmLFCqZOncqNGzeMv4+KisLX15f//u//JiMjg/Dw8Ac+15IlSwgLCyMwMJDExETWrVtXmaULIYQQopLUrVuXQ4cO3ff2devW4erqSteuXYFbHT6dO3dm6NChd9yvYirXvdw+WketVt/3ZNKUKVOoUqUK3377LWvXrmX48OEYDAamT5/+p9EzACqV6k8/W1lZYTAYjL8rKyu772PufrwQQghhzuQy6QrStWtXBgwYQL169e74fVFRkXHR5T179tzzsfb29sazZXc/JiYmpnIKFkIIIUSl8/Pzo6yszDjVCODSpUucOXOGo0ePkpCQwMiRI423tWjRgri4OPLy8oBb07avX7+Ot7c3Z86cISMjw/j7x2FlZcWIESOIjY2loKAAf39/du7cabw9JSXF+O8jR45w8+ZNbty4QWJiIo0aNcLNzY20tDTKysooLCwkISHhjuc/cOCA8f9NmjS5bx2enp7k5OSQnJwMQHFx8QNHOVst3PyX/wkhhBCVSUbwKEj16tXvuahhv379iIyMZMOGDfedu966dWvmzJnDkSNHGDlyJK+++ipz5syhSpUq+Pn5GRtzQgghhDAvKpWKiRMnsmzZMn755Resra2pUaMGI0aMYO3atWRnZxunYwUGBjJo0CAGDx7Ml19+icFgwMrKilGjRuHt7c2YMWP45ptvMBgMODs7M3ny5MeqqVq1agQHB7Nz507efPNNFi9ezMSJEykvL6dZs2aMGTMGuDUFPTw8nBs3bvDKK68YTz61a9eODz74AHd39z+tL1RQUMDEiROxtrZm/Pjx961Bo9EwYcIEli5darwS6eTJk7GysnqsTEIIIURlUxluH8MqRCXTarWmLuGpsvS5n/cimZVBMiuDuWaWNXiUYe3atXdcAOJZoKR2jrl+PjwOJWUFZeVVUlZQVl5Lz3q/to508AghhBBCCLPzLHbwCCGEEKYka/CIp+Z+lyG1ZJJZGSSzMkhmIZ4tAwcOfKY6d5T2flFSXiVlBWXlVVJWUFZeJWW9nXTwCCGEEEIIIYQQQpg56eARQgghhBBCCCGEMHPSwSOempCQEFOX8NRJZmWQzMogmYUQf0Vp7xcl5VVSVlBWXiVlBWXlVVLW28kiy0IIIYQQQgghhBBmTkbwCCGEEEIIIYQQQpg56eARQgghhBBCCCGEMHPSwSMqXXl5ualLEEIIIYSoNNLWEUII8SzQmLoAYbnKy8v56aefKC8vp3Xr1vj7+5u6pGeewWBApVKZuoynprCwkCpVqpi6jKeqpKQEOzs7U5fx1CgtbwUl7ttKzCyEtHXgwIEDZGdn4+3tjbe3t6nLqVSHDx/mxo0b+Pn5UbNmTVOXU+lk2wpLZqnfu2SRZVEpDAYDixcvpqioiICAAPbs2UObNm3o3r071tbWpi7vmaLT6YiOjqZFixZUr14dOzs7i/3AqVDRID59+jQdOnQwNhz0ej1qtWUOLKzInJKSQqdOnfD29sbT09Nit7XS8lZQ8r6tpMxCgLR19Ho9GzZs4MiRI3Ts2JHffvuNgQMH8vzzz5u6tCdOp9OxfPlykpKS8PPzIzk5mVdeeYUWLVpY5HFNtq3lbtu7Xbt2DY1GQ/Xq1U1dylOh1WrR6XTUq1fP1KVUGml5iUpRXFxMSkoKb731Fh07dqRPnz5cvXqVgwcPmrq0Z0pycjIfffQR8fHxbNu2jeXLlwNY/MFk165daLVa3n33XTQaDYsWLaKkpAS1Wo2l9jlv3LiRjIwMBg0ahFarZdWqVdy8eROVSmWRmZWWt4IS920lZhYCpK2jVqvRarW88cYbhIWFMXDgQHbu3ElaWpqpS3viNBoNN27c4N133+W1116ja9euLFu2zHhcszSybS1321bQ6XRERkYyY8YMvv/+e/73f/+XmzdvAljksbu8vJz/+Z//ISIigiVLlrBlyxYyMzMBy8srHTyiUjg4OFCjRg327NkDgI+PDw0aNCApKYnc3FyT1vYsyc3NpWXLlnz44YcMGzYMrVbLpk2bgFtnTyxJxUFDr9dTWlpK+/btqV27Nr169aJu3bosWrQIsKwP2Yo1GcrKysjPz6dv3740bdqUl156iSpVqrBmzRrAcjIrLW8FJe7bSswsxN2U2NaJiYnh9OnTFBYWAlC1alUKCwspLy/n+eefp06dOhw4cMAi2jBxcXGkpKSg1+spKCjAysqKsrIy9Ho9nTt3pkaNGmzbtg2wjDabbFvL3bb3kpKSQklJCfPnz2fQoEGcOXOG2NhYdDqdRXZsXb9+3Zh39OjR5Ofns2vXLovsyJMOHlFp2rZtS0pKCjk5OdjZ2VGvXj00Gg05OTmmLs1kcnNzOXHihPGL8NWrV43DuKtUqcLw4cPZsmWL8ey3JcjKyuKHH35g0aJFnD17FrVaTXl5OWfPnjXeZ/To0Zw4cYLU1FSLOOufmZnJv/71L9asWcOVK1ewtrZGp9MRExMD3PpS0K9fPxISErh69arZb2ul5a2gxH1biZmF+CtKaOsYDAZycnIIDw8nJiaGvXv3snjxYkpKSnByciI1NZWSkhIAQkNDOXLkCHl5eSau+vEYDAauX7/OpEmT2LVrFxs2bGDdunXY29uj0WiIj483HsMGDx7M9u3buXnzplkf13Jzc5k6dapsWwvctnfLysoyHpP1ej3p6ekYDAZ8fHx47rnnuHLlyh3Hc3N37do1SktLgVsnH8+fP49Op6NOnToEBgZSUlJCXFyciat88ixnjxXPHB8fH5ycnIxntho2bMj58+eNZ36VZvv27Xz88cfs2LGDRYsWcf78eVq3bs2ePXuMHT4NGjQgICCAqKgowPzPfpeXl7Nw4UJcXV3x8fEhOjqa7du38+KLLxIXF8fVq1cBsLe3p0ePHvz666+AeU9RKy4uJjIykurVq2Nra8uaNWs4evQoAwcO5NSpU6SnpwPg4eFBq1atOHbsmIkr/nuUlreCEvdtJWYW4kEsva2j1+tRqVQUFxdTrVo1Pv/8c9566y0cHBxYsmQJPXv25Ny5c1y6dInS0lI8PT2pXbu2WU5TKyoqQqVSkZ2dTaNGjfj8888ZPHgwBQUF/PzzzwwYMICYmBiuX7+OTqfDy8uL5s2bm+1xLTs7m/z8fIqLi3F1dbXobVtSUoJKpSInJ4fGjRtb/La9W2ZmJuHh4Xz77bdERkaSkZFBzZo1adasGSdOnACgZcuW2Nvbk5qaSllZmWkL/ptycnKYMmUK3333HV9//TWpqal4enry3HPPERsbC0D9+vVp0KABKSkpxlFrlkI6eESlqVatGm3atOHEiRMcPHiQjIwMbGxssLKyMnVpT115eTlarZbPPvuMSZMm0bhxYzZu3IizszMtW7Y0TmcA6Nq1K8XFxRYxZPD69evo9XoGDx5Mt27d6NWrF6dOneLatWv079+fBQsWGO/r4eFBjRo1APPu2Lp27Ro6nY5XX32VAQMG0K5dO44ePUpubi7dunVj6dKlwK357Wq1GicnJ8B8MystbwUl7ttKzCzEg1hqW0ev17Nq1SpWrVrF6dOn0Wq1xpEMarWakSNHcuzYMbKzs+nQoQMHDhzg999/N97epEkTU5b/yHbu3MmUKVNIS0sjKyvLOAKrZs2a9OvXj0OHDgHQrl07Nm3aRGpqKnCrfVe/fn2T1f04Krbtp59+yuXLl0lJSTHeZmnbtry8nFWrVjFr1ixiY2M5cuQIxcXFgGVu29vdfuzdtWsXTZo0ITw8HBcXF1asWEFpaSnVqlXjwoUL5Ofn4+joiIeHB2fPnsXa2trsjt2313vgwAEaNWrEl19+iZ+fH5s3b+aPP/7Ax8eH5ORksrOzsbOzo3r16mRnZ2NjY2PCyp886eARlapi/Y3jx48zY8YM2rRpQ+PGjU1d1lNx7do1srKygFtnsM+cOUNRUREAbdq0wcvLi02bNjFy5Eji4+M5fvw4cGvalrOzs1l+2Jw9e5aFCxeyc+dO4NaXvIKCAg4fPgxAnTp1aNWqFVu2bCEsLAyNRsPq1auJi4vjP//5DxqNBjCvM/5nz55l+fLlxjNaXl5eWFlZcerUKeDWe8DDw4NDhw7Rp08fMjMz2bJlC6dOnSIhIcHYYDaXzErLW0Gp+7bSMgvxOCytrXP69Gk++ugjCgsL8fDwICoqCo1GQ2JiIsnJycCtL/oDBgxg5cqVdO7cGX9/f2JiYvjwww8pLy83myvUVHwpLCkpwcbGhujoaIKCgrhw4QIXL17EysoKNzc3OnfuzKZNm3j55ZepVasW69ev54MPPjB+STQnsbGxaLVaZs2aha+vL61ateLcuXMWt20LCgqYP38+RUVFvPjiixw5coQmTZqQkJBASkqKRW7b2909itDFxQWA1157zTi1ukGDBhQXF7Nv3z4AAgMDKSgoMI5mMyc6nc7477KyMuPPL7/8Mo6OjiQnJ1OtWjVcXFzYsmULAH5+fuTk5Bg7/SyFxtQFCMsXEBBAixYtUKlUZn9G62HodDr+/e9/k5SUhKurK8HBwYSEhNCtWzd27tyJt7c3zs7OtGnThg0bNlBQUMDw4cM5cuQImzdvJi8vjyFDhpg6xiO7cOECCxcuJDQ0lKNHj6LVaunVqxd9+/YlNjaWtm3bYmdnZ+w9z8zMZMyYMSQlJfHrr7/StWtXQkJCTB3jkZw8eZLly5fTvXt3du3axfnz5+nZsydBQUEcO3YMPz8/qlevjpeXF8eOHUOtVjNu3DjOnTvH6tWr6dKlCx06dDB1jIemtLwVlLhvKzGzEH+HJbV1VCoVffr0oVOnTsCtxVgrroq4cOFCIiIi0Ov1BAUFkZiYSGZmJm3btsXb25vS0lJq1qxp4gQPT6VSodfryc3NpWfPnpw6dYqTJ08yZMgQ4ygXvV5PkyZNSE9Pp6ysjLCwMAIDA41reZgTg8FAeno6oaGhODo6kpSURJ06dejWrRsrVqwgPDzcYrZtSUkJ169f55///Cdwa1SHq6sr/fv3Jyoqio8++siitm2FhIQE1q5dS61atWjRogUdO3bE3t4etVpNUVERDg4O9OjRgx07dvDOO+9gb2/PggULyM3N5ejRowQGBmJnZ2fqGA/t5MmTbNu2jerVq+Pj42NcJLusrIzMzEzc3Nxo3749u3fvxtvbm65du/LVV1/x448/cvLkSfz8/Mwq78OQDh7xVFScyVWC21elP3v2LNHR0QC0aNGCc+fOcfz4cQICAnBycsLe3t548GzVqhUJCQm0aNHCLP9eycnJNGrUiJCQEFq3bs3OnTs5dOgQLVu2xNHRka1btxIWFoa7uztZWVnodDrjNI727dub3ZkCuLWtW7ZsSe/evQkMDGT16tWcO3eOmjVrcuXKFfbt20eHDh3w8vJi1apVFBQU0LBhQxo2bEivXr3MLrPS8lZQ4r6txMxC/F3meOy+l4YNG9K4cWP0ej1qtZqmTZty+fJlhg4dyrZt29ixYwehoaFkZWUZR0HA/48QMCcVGZ2dnbG1tcXf35+9e/cycOBAVq5caTyulZaWUlZWZvwi6OHhYeLKH49KpSI/P5/Dhw+TmprKnj17qFWrFm5ubqSkpBATE0PHjh0tYtu6ublha2tLZGQk2dnZZGRkUFxcTEBAAOfOnWP//v0EBwdbzLaFW6OW1qxZQ58+fXB0dGTbtm0UFhbStm1bVq5cia+vLw4ODjz33HNs2bKFgwcPEhoayoQJE/jjjz8YOHAgQUFBpo7xQAaDAb1ez9atWzl48CADBw6kqKiIo0ePGk80JiQkcOnSJapXr463tze7du0iPj6eAQMG8PHHH5OamoqPjw/PP/+8qeM8cZZxJBLCxLKysnB1dTWeCbp9VfrMzEwuXryIq6sr7dq1Y/369QQEBODq6kp+fr5xCKFGoyEgIMDESR7egQMHyM7OpkmTJjRt2pSGDRty6tQpcnNzqVatGr6+vpw4cYKsrCx69OjB7NmzadSoEcXFxZSWlt5x2Ulz+TJ4+PBhbty4ga+vLx4eHnh4eJCXl0dBQQHu7u4EBASQnJxMUFAQfn5+/Pzzz3h5eZGVlUW1atXuGC5rDpmVlreCEvdtJWYWQtybra3tHT/Hx8cb1yIZO3Ysv/76KzNnzkSr1Zr9SL2KacOpqan07t0bnU7Hxo0bmT9/Pj169GDfvn0cPnyYixcv0qdPHxNX+2T06tWLhQsXUlZWRkREBFevXuXkyZM0bNiQS5cucfDgQYvYtgD//Oc/OXz4MGfPnmXy5MnGL/3Nmzfn8OHDHDp0iAsXLtC3b19Tl/rYKo6/arWa7Oxs6tWrR9u2bVGr1bi6uvLpp5/SuXNn6tatS1xcHCqVijp16tC+fXvj0hF169albt26pozx0CryWllZUb16dcaPH0+tWrUoKSnhwoUL3LhxAz8/Pzw8PEhKSsLOzg5fX18CAwONVwhzd3fH3d3dlDEqlXTwCPE3ZGZmEhkZiV6vp0aNGgwcOPCOVekDAgJ47rnn0Gq1pKen07t3b+Li4oiMjOTatWtYWVmZ3ZkCvV7Phg0bOHLkCB07dmTBggUMGTKEmjVr4u7uzunTp2nfvj2+vr6cO3eOzMxM2rRpwyuvvMKRI0dISEhg2LBheHp6mjrKQ9PpdCxfvpykpCT8/PzYu3cvgwcPpnr16uh0OrRaLd7e3gQHB3Py5ElycnJo164d6enp/PLLLyQnJ/Pmm2/i6upq6igPRWl5Kyhx31ZiZiHEw6n4IpWXl0dgYCBw6yp5Q4YM4fLly7i7u5vd5/z91K9fn0WLFnHp0iUcHR2xsrKib9++2NjYcPToUd544w3jaBZz5+HhQa1atTh//jwAtWrVIjExkTZt2hAaGkpiYiKenp4WsW2dnZ3RaDTGCzy0aNGC48ePExQURJs2bUhISDDrbfvbb7+xZs0aunbtyuDBg7GzsyMpKYn8/HxcXFzw9PSkffv2LFu2jDfffJN169axatUqmjdvzrZt23jnnXdMHeGRVOTt3LkzQ4cOpW3btmg0GnQ6HXZ2duTk5Bg7rTp16sThw4dZvnw57dq1Y+fOnYwaNcrECZ4O6eAR4hEZDAbjGeqKVemHDh3KypUrWbFiBa+//rpxVfpGjRrh7OxMzZo1OXLkCL1792bs2LFcu3aNS5cu0bFjRxOneXRqtRqtVssbb7yBr68vbm5u7Ny5k9dee41q1aqRkpJiPBPg6enJ7t27CQ0NpVu3bnf87cyJRqPhxo0bvPvuu9SuXZs9e/awdOlSJk+ejFqtNq635ObmRpMmTfjtt99o164d/fr14+bNm2a3YLbS8lZQ4r6txMxCiIejUqnQ6XQ4OTlx6dIlli1bhqOjIyNHjsTHx8fU5T1RBoOB/Px83nzzTZo3b87KlSvZvn07L730krFzy1LY2NgwdOhQpk+fTlxcHHXq1GH//v0EBQWhUqnw8/MzdYlPlIeHB8eOHSMpKYmaNWty/vx5GjRogK2trVlv25KSEo4cOUK/fv2IiYmhU6dOeHp60qBBA5YtW8aECRMAGDZsGNOmTaOgoIAhQ4YQFxdHUlIS48ePN6v38d15u3XrZjxJrlar0el0lJWVGa/y5urqSq9evXB3d+fChQtMmDDBrPL+HXIVLSEe0eOsSt+mTRuKioooKirC1taWevXqmVXnTkxMDKdPn6awsBCAqlWrUlhYSHl5OUFBQXh4eBAfH4+fnx/W1tZERUUBGKd8lJeXA+Y1dSMuLo6UlBT0ej0FBQVYWVlRVlaGXq+nS5cuuLi4cODAAUJCQsjIyGDr1q3ArfnP/v7+xucxl84OpeWtoMR9W4mZhRCPTqVScfHiRfbt28fWrVtp27Yt//jHP3BwcDB1aU9cWFgYn3zyCc2bN8dgMBAWFsZLL71k6rIqjYuLC6NGjSItLY3IyEiCg4Pp2bOnqcuqFA0bNsTb25vVq1fzxRdf0LFjR7Nqg9+PnZ0dI0eOpHfv3vj7+xuP1aNHjyYhIYGkpCTg1pTLiimWGo2GDh06mGUn7d15165de8fthYWFlJaWUq9ePbKzs41Xe23VqhUDBgwwu7x/h8pgbhe5F8JE7rUq/caNG7G3t6dTp044ODhw4sQJ46r0165dY8GCBbRu3dq4Kv3gwYON872fdQaDgdzcXL799ltUKhU1a9aktLSUMWPGsH37dvR6PaGhoVSpUoUrV64wb948Pv30U1xcXPjhhx/Iy8sjPz+f8ePHm800NIPBQGZmJnPmzMHe3h5HR0dq167NgAEDWLhwIZ6ensZ52ikpKcyYMYMffviBGzdusGLFCnJycigtLWX8+PFmcaUJpeWtUHHFlO+++04x+zZAbm4u8+bNQ61WKyazEOLvycrKIjY2lrCwMKytrU1dTqUrLy83+6ugPaqKhaYtXUZGBq6urhazGPrtcnNziYiI4NVXX6VVq1bs3LnTOBUtMzOTEydOMGnSJBwdHU1d6hNRkXfw4MG0bNkSgKSkJH788UeCg4PZs2cP3bp1o1evXoocbSwdPEI8hIKCAr766qs7VqVv2bIlLVq0YOXKlQwdOtS4ONm0adMIDAwkNDSUy5cv88cff+Dg4GAWq9JXqDjYa7Va1q9fz3vvvYder2fx4sWUlZUxfPhw5s2bx8svv0yjRo2wtbVlzpw5eHt7ExYWhk6no6ioCGdnZ1NHeWg6nQ6NRkNSUhKxsbGMHj0arVbL9u3bcXZ2plu3bnz11VdMmjQJFxcXNBoNs2fPpn379rRr146ysjJycnLMZtG2iktlnjt3jr1791p83gp5eXlUrVpVUft2dnY2Go2GwsJC1q1bp4jMQgghhJLs3r2bvXv38sUXXwBw/PhxEhMTyc7OZujQoWa7ztD97N69m3379hEeHg7Atm3bWLlyJV27dqV///4Wl/dRWH53rRCPSa/XGxcYvH1Vej8/P15//XWioqJwdXU1rkqflpYGQPv27Y1Xxqpbty7dunUzm84dvV7PqlWrWLVqFadPn0ar1RrP6qjVakaNGsWxY8fIzs6mQ4cOHDhwgN9//x24NeyzadOmxn+by5fBisyLFy8mISGB5ORkCgoKAKhZsyYvvfQShw4dAqBdu3Zs3LiR1NRU4NYIGC8vLwCsra3NprNj586dTJkyhbS0NLKyssjJyQEsNy/c2s5RUVFMnjyZ7OxstFqt8TZL37c//fRTLl++TEpKivE2S80shBBCKI1er+eFF16gatWqLF68mCVLluDq6sqwYcN47733LK6zoyKvs7MzixcvJioqCltbWyZPnsyYMWMsLu+jkg4eIe7ht99+45133jHO77x9VXrgjlXp+/fvT0lJCatWrWLr1q2sX7/eONfVnJw+fZqPPvqIwsJCPDw8iIqKQqPRkJiYSHJyMnDrS+GAAQNYuXIlnTt3xt/fn5iYGD788EPKy8upV6+eiVM8mvj4eCZOnEhRURF+fn789NNPNGzYkDNnzpCSkoKVlRVubm507tyZTZs28fLLL1OrVi3Wr1/PBx98gJ2dHdWrVzd1jIdWMWCzpKQEGxsboqOjCQoK4sKFC1y8eNHi8lY4c+YM7733HsXFxUydOhVXV1f8/f05e/asxe7bALGxsWi1WmbNmoWvry+tWrXi3LlzFp1ZCCGEUBq1Wk1paSn5+fkcOHAADw8P6tevb7FTk+7O6+TkREhICM2bNzd1ac8Ey5uEKMTfpLRV6SuoVCr69OlDp06dgFtrrmRkZDBo0CAWLlxIREQEer2eoKAgEhMTyczMpG3btnh7e1NaWmpWa7BUcHNzY9SoUfj6+gJw8OBBHB0d6d+/P6tXr2bSpEno9XqaNGlCeno6ZWVlhIWFERgYiE6no06dOiZO8GhUKpVx/ZmePXty6tQpTp48yZAhQ4wjPSwpbwV7e3uKi4sZMWIEAFqtFk9PT8LCwliyZAkzZsywuH3bYDCQnp5OaGgojo6OJCUlUadOHbp168aKFSsIDw+3uMxCCCGEUv3nP/+hQYMGfPbZZ4pYL0tpeR+FdPAIcZeKVdrd3NzIyckhKiqK999/n9GjRzNu3DiSkpLw9va+56r0HTp0MHH1j69hw4Y0btzYuP5O06ZNuXz5MkOHDmXbtm3s2LGD0NBQsrKyjCM94P+vImaOPD098fT0pKioiLlz55KWlsb69evp1q0bqampxMbG0qlTJ0pLSykrK8POzg7AbBeZrdi2zs7O2Nra4u/vz969exk4cCArV65k3759dOjQwWLyVvDy8qJt27bMmTMHR0dHrly5gp2dHaGhoeTn5xMdHU337t0tat9WqVTk5+dz+PBhUlNT2bNnD7Vq1cLNzY2UlBRiYmLo2LGjRWUWQgghlCosLEwRi2VXUFreRyGLLAvxF5S2Kv3tIiMjqV+/PmFhYVy8eJFff/2VzMxMtFotISEhxqsrWYpdu3bRo0cP9u3bR2ZmJgUFBVy7ds14mdg+ffrQo0cPU5f5RMybN4+3334bnU7HlClTsLGxoXXr1iQnJ2NjY2NxeeHWotKffPIJwcHBvPrqq0RHRxunXObm5pKRkcHVq1fp3r27xezbqampLFy4kLp16zJmzBiuXr3KyZMnOXToEA0aNECr1Vrs+1kIIYQQQomkg0eIB1DaqvQVC0vPnDmTkSNH4uHhQXp6Ok5OTly+fBl3d3dcXV1NXOWTc6/LJ86cOZPevXvj4+NDfHw8Xl5eFrWdN27cyJUrV7h06RIODg5YWVnx8ccfY2Njw9GjRy0ub4Xc3Nw7RqjMmDGDsLAw/P39OXXqFJ6enha1b9+8eZNFixZx6dIlIiIiAIiOjubmzZuEhoaSmJhocZmFEEIIIZRMpmgJ8RcqVmmPj49n8eLFqFQqunfvzrBhwyx24TKVSoVOp8PJyYlLly6xbNkyHB0dGTlypFmuLfQgd2/Ha9euUVZWho2NDTY2NgQGBpqosspjMBjIz8/nzTffpHnz5qxcuZLt27fz0ksvWWTeCrd37qSnp1NeXm6chubn52eiqiqPjY0NQ4cOZfr06cTFxVGnTh32799PUFAQKpXKIjMLIYQQQiiZjOAR4gFKS0uZMWMGaWlpvPLKK/Tu3dvUJVW6pKQkJk+ejLe3N127dqVbt26mLqlS6fV6srOzWbNmDZcvX+aFF14gJCTE1GVVmps3b2JjYwPc6uzJy8tTxNorBoOBgoICfvzxR9LS0ggJCbHo7Vzh7NmznDp1it9//53u3bsrIrMQQgghhBJJB48QD7B582ays7MZNmyYYlZpz8rKIjY2lrCwMMVkzsvL49ChQ3Tt2lUxmcvLy7GysjJ1GU9VSUkJe/fupUuXLorZzhUqFtkWQgghhBCWSTp4hHgA+VIkhBBCCCGEEOJZJx08QgghhBBCCCGEEGZOhiUIIYQQQgghhBBCmDnp4BFCCCGEEEIIIYQwc9LBI4QQQgghhBBCCGHmpINHCCGEEEIIIYQQwsxJB48QQgghhBBCCCGEmZMOHiGEEEIIIYQQQggz939AYz75TYGOoAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1152x864 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('ggplot')\n",
    "\n",
    "plt.figure(figsize=(16, 12))\n",
    "for i, label in enumerate(['population', 'medianIncome', 'area', 'age']):\n",
    "    plt.subplot(2, 2, i + 1)\n",
    "    df_plot = df[label].sort_values().dropna()\n",
    "    df_plot.plot(kind='barh', color='C0', ax=plt.gca());\n",
    "    plt.ylabel('')\n",
    "    plt.xticks(rotation=30)\n",
    "    plt.title(label.capitalize())\n",
    "    plt.ticklabel_format(style='plain', axis='x')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Mayors of all European Capitals\n",
    "\n",
    "In our final query, we will take a look at where mayors are born by adding the coordinates to the query. In order to get the latitude and longitude coordinates as variables, we need to add the following snippet.\n",
    "\n",
    "```sparql\n",
    "?capital p:P625/psv:P625 ?capital_node.\n",
    "?capital_node wikibase:geoLatitude ?capital_lat.\n",
    "?capital_node wikibase:geoLongitude ?capital_lon.\n",
    "```\n",
    "\n",
    "In the first line, we traverse the graph of the previously shown data representation. The slash in `p:P625/psv:P625` means that we continue to the _Value node_ of the [coordinate location (P625)](https://www.wikidata.org/wiki/Property:P625) without using a separate variable for the _Statement node_. Then, `wikibase:geoLatitude` and `wikibase:geoLongitude` are responsible for retrieving the latitude and longitude from the _Value node_ respectively. For more information, take a look at [Precision, Units and Coordinates](https://en.wikibooks.org/wiki/SPARQL/WIKIDATA_Precision,_Units_and_Coordinates)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>countryLabel</th>\n",
       "      <th>capital_lon</th>\n",
       "      <th>capital_lat</th>\n",
       "      <th>population</th>\n",
       "      <th>mayorLabel</th>\n",
       "      <th>birth_date</th>\n",
       "      <th>age</th>\n",
       "      <th>birth_placeLabel</th>\n",
       "      <th>birth_place_lon</th>\n",
       "      <th>birth_place_lat</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>capitalLabel</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Prague</th>\n",
       "      <td>Czech Republic</td>\n",
       "      <td>14.416667</td>\n",
       "      <td>50.083333</td>\n",
       "      <td>1335084.0</td>\n",
       "      <td>Zdeněk Hřib</td>\n",
       "      <td>1981-05-21T00:00:00Z</td>\n",
       "      <td>40.0</td>\n",
       "      <td>Slavičín</td>\n",
       "      <td>17.873493</td>\n",
       "      <td>49.087984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>City of Brussels</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>4.351667</td>\n",
       "      <td>50.846667</td>\n",
       "      <td>185103.0</td>\n",
       "      <td>Philippe Close</td>\n",
       "      <td>1971-03-18T00:00:00Z</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Namur</td>\n",
       "      <td>4.866667</td>\n",
       "      <td>50.466667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Helsinki</th>\n",
       "      <td>Finland</td>\n",
       "      <td>24.934170</td>\n",
       "      <td>60.175560</td>\n",
       "      <td>642045.0</td>\n",
       "      <td>Juhana Vartiainen</td>\n",
       "      <td>1958-05-28T00:00:00Z</td>\n",
       "      <td>63.0</td>\n",
       "      <td>Helsinki</td>\n",
       "      <td>24.934170</td>\n",
       "      <td>60.175560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rome</th>\n",
       "      <td>Italy</td>\n",
       "      <td>12.482778</td>\n",
       "      <td>41.893056</td>\n",
       "      <td>2872800.0</td>\n",
       "      <td>Virginia Raggi</td>\n",
       "      <td>1978-07-18T00:00:00Z</td>\n",
       "      <td>43.0</td>\n",
       "      <td>Rome</td>\n",
       "      <td>12.482778</td>\n",
       "      <td>41.893056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Warsaw</th>\n",
       "      <td>Poland</td>\n",
       "      <td>21.033333</td>\n",
       "      <td>52.216667</td>\n",
       "      <td>1790658.0</td>\n",
       "      <td>Rafał Trzaskowski</td>\n",
       "      <td>1972-01-17T00:00:00Z</td>\n",
       "      <td>49.0</td>\n",
       "      <td>Warsaw</td>\n",
       "      <td>21.033333</td>\n",
       "      <td>52.216667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    countryLabel  capital_lon  capital_lat  population  \\\n",
       "capitalLabel                                                             \n",
       "Prague            Czech Republic    14.416667    50.083333   1335084.0   \n",
       "City of Brussels         Belgium     4.351667    50.846667    185103.0   \n",
       "Helsinki                 Finland    24.934170    60.175560    642045.0   \n",
       "Rome                       Italy    12.482778    41.893056   2872800.0   \n",
       "Warsaw                    Poland    21.033333    52.216667   1790658.0   \n",
       "\n",
       "                         mayorLabel            birth_date   age  \\\n",
       "capitalLabel                                                      \n",
       "Prague                  Zdeněk Hřib  1981-05-21T00:00:00Z  40.0   \n",
       "City of Brussels     Philippe Close  1971-03-18T00:00:00Z  50.0   \n",
       "Helsinki          Juhana Vartiainen  1958-05-28T00:00:00Z  63.0   \n",
       "Rome                 Virginia Raggi  1978-07-18T00:00:00Z  43.0   \n",
       "Warsaw            Rafał Trzaskowski  1972-01-17T00:00:00Z  49.0   \n",
       "\n",
       "                 birth_placeLabel  birth_place_lon  birth_place_lat  \n",
       "capitalLabel                                                         \n",
       "Prague                   Slavičín        17.873493        49.087984  \n",
       "City of Brussels            Namur         4.866667        50.466667  \n",
       "Helsinki                 Helsinki        24.934170        60.175560  \n",
       "Rome                         Rome        12.482778        41.893056  \n",
       "Warsaw                     Warsaw        21.033333        52.216667  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "url = 'https://query.wikidata.org/sparql'\n",
    "query=\"\"\"\n",
    "SELECT DISTINCT \n",
    "  ?countryLabel ?capitalLabel ?population ?capital_lon ?capital_lat\n",
    "  ?mayorLabel ?birth_date ?age ?birth_place ?birth_placeLabel ?birth_place_lon ?birth_place_lat\n",
    "WHERE {\n",
    "  ?country wdt:P463 wd:Q458.\n",
    "  ?country wdt:P36 ?capital.\n",
    "  OPTIONAL { ?capital wdt:P1082 ?population. }\n",
    "  \n",
    "  # Get latitude longitude coordinates of capital\n",
    "  ?capital p:P625/psv:P625 ?capital_node.\n",
    "  ?capital_node wikibase:geoLatitude ?capital_lat.\n",
    "  ?capital_node wikibase:geoLongitude ?capital_lon.\n",
    "\n",
    "  ?capital p:P6 ?statement.\n",
    "  ?statement ps:P6 ?mayor.\n",
    "  FILTER NOT EXISTS { ?statement pq:P582 ?end_date }\n",
    "\n",
    "  ?mayor wdt:P569 ?birth_date.\n",
    "  BIND(year(now()) - year(?birth_date) AS ?age)\n",
    "  ?mayor wdt:P19 ?birth_place.\n",
    "  ?birth_place wdt:P625 ?birth_place_coordinates.\n",
    "  \n",
    "  # Get latitude longitude coordinates of birth place\n",
    "  ?birth_place p:P625/psv:P625 ?birth_place_node.\n",
    "  ?birth_place_node wikibase:geoLatitude ?birth_place_lat.\n",
    "  ?birth_place_node wikibase:geoLongitude ?birth_place_lon.\n",
    "  \n",
    "  SERVICE wikibase:label { \n",
    "    bd:serviceParam wikibase:language \"[AUTO_LANGUAGE],en\". \n",
    "  }\n",
    "}\n",
    "\"\"\"\n",
    "\n",
    "r = requests.get(url, params = {'format': 'json', 'query': query})\n",
    "data = r.json()\n",
    "\n",
    "countries = []\n",
    "for item in data['results']['bindings']:\n",
    "    countries.append(OrderedDict({\n",
    "        label : item[label]['value'] if label in item else None\n",
    "        for label in ['countryLabel', 'capitalLabel',  'capital_lon', 'capital_lat', 'population', \n",
    "                       'mayorLabel', 'birth_date', 'age', \n",
    "                       'birth_placeLabel', 'birth_place_lon', 'birth_place_lat']}))\n",
    "\n",
    "df = pd.DataFrame(countries)\n",
    "df.set_index('capitalLabel', inplace=True)\n",
    "df = df.astype({'population': float, 'age': float,\n",
    "                'capital_lon': float, 'capital_lat': float, \n",
    "                'birth_place_lon': float, 'birth_place_lat': float})\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Taking this data set we can explore the age of the mayors and the population of the capital they are serving."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 5))\n",
    "plt.subplot(1, 2, 1)\n",
    "df['age'].sort_values().plot(kind='barh', color='C0', title='Mayors Age')\n",
    "plt.ylabel('')\n",
    "plt.subplot(1, 2, 2)\n",
    "df['population'].sort_values().plot(kind='barh', color='C0', title='Population')\n",
    "plt.ylabel('')\n",
    "plt.ticklabel_format(style='plain', axis='x')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, let's take a look at how far mayors are born from the capital. For this, we will use the [geopy](https://geopy.readthedocs.io/en/stable/) package to calculate the distance between the coordinates. This [tutorial](https://janakiev.com/blog/gps-points-distance-python/) covers this topic if you are curious why we can't just use euclidean distance on GPS coordinates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from geopy.distance import distance\n",
    "\n",
    "coordinates = df[['capital_lon', 'capital_lat', 'birth_place_lon', 'birth_place_lat']]\n",
    "df['distance'] = [distance((lat0, lon0), (lat1, lon1)).m \n",
    "                for lon0, lat0, lon1, lat1 in coordinates.values]\n",
    "\n",
    "df['distance'].sort_values().plot(kind='barh', color='C0', logx=True, figsize=(12, 7))\n",
    "plt.xlabel('Distance (m)')\n",
    "plt.ylabel('');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we can see that most mayors tend to be born in or close to the city where they later serve (note, that the chart is in log-scale). We can see that Athens leads the exceptions with their current mayor (Giorgos Kaminis) born in New York, USA and Paris with their current mayor (Anne Hidalgo) born in San Fernando, Spain. From there the distances drop significantly.\n",
    "\n",
    "Now we will get a list of all mayors in Europe, with the script from [this source](https://github.com/njanakiev/wikidata-mayors/blob/master/load_european_mayors.py), which deals with exceptions (like mayors born in countries that do not exist anymore) and the queries need to be done for each country separately because there is a limit on the queries.  \n",
    "\n",
    "First we want to select all [members](https://www.wikidata.org/wiki/Property:P463) the [European Union](https://www.wikidata.org/wiki/Q458) and the [European Free Trade Association](https://www.wikidata.org/wiki/Q166546). As before, we will use the [Wikipedia Query Service](https://query.wikidata.org/) and the [Cats](https://www.wikidata.org/wiki/Wikidata:SPARQL_query_service/queries/examples#Cats) example and continue editing from there. Let's start by selecting all countries in Europe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Ireland', 'Hungary', 'Spain', 'Belgium', 'Luxembourg', 'Finland', 'Sweden', 'Denmark', 'Poland', 'Lithuania', 'Italy', 'Austria', 'Greece', 'Portugal', 'France', 'United Kingdom', 'Germany', 'Estonia', 'Latvia', 'Czech Republic', 'Slovakia', 'Slovenia', 'Romania', 'Bulgaria', 'Croatia', 'Cyprus', 'Malta', 'Kingdom of the Netherlands']\n",
      "Length : 28\n"
     ]
    }
   ],
   "source": [
    "url = 'https://query.wikidata.org/sparql'\n",
    "query = \"\"\"\n",
    "SELECT ?country ?countryLabel WHERE {\n",
    "  ?country wdt:P463 wd:Q458.\n",
    "  SERVICE wikibase:label { \n",
    "    bd:serviceParam wikibase:language \"[AUTO_LANGUAGE],en\". \n",
    "  }\n",
    "}\n",
    "\"\"\"\n",
    "r = requests.get(url, params = {'format': 'json', 'query': query})\n",
    "data = r.json()\n",
    "\n",
    "country_list = [entry['countryLabel']['value'] for entry in data['results']['bindings']]\n",
    "print(country_list)\n",
    "print('Length :', len(country_list))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we want to apply a [`UNION`](https://en.wikibooks.org/wiki/SPARQL/UNION) to get countries from both the European Union and European Free Trade Association. Additionally we want to remove doubles that occur through the union, by using the `DISTINCT` modifier before `SELECT`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Belgium', 'Portugal', 'Germany', 'Malta', 'Romania', 'Finland', 'Estonia', 'Austria', 'Switzerland', 'Spain', 'Italy', 'Hungary', 'Bulgaria', 'Ireland', 'France', 'Sweden', 'Denmark', 'Greece', 'Czech Republic', 'Norway', 'Poland', 'Slovakia', 'United Kingdom', 'Slovenia', 'Cyprus', 'Latvia', 'Lithuania', 'Croatia', 'Iceland', 'Liechtenstein', 'Luxembourg', 'Kingdom of the Netherlands']\n",
      "Length : 32\n"
     ]
    }
   ],
   "source": [
    "url = 'https://query.wikidata.org/sparql'\n",
    "query = \"\"\"\n",
    "SELECT DISTINCT ?country ?countryLabel \n",
    "WHERE \n",
    "{\n",
    "  {?country wdt:P463 wd:Q166546} UNION {?country wdt:P463 wd:Q458}\n",
    "  SERVICE wikibase:label { \n",
    "    bd:serviceParam wikibase:language \"[AUTO_LANGUAGE],en\". \n",
    "  }\n",
    "}\n",
    "\"\"\"\n",
    "r = requests.get(url, params = {'format': 'json', 'query': query})\n",
    "data = r.json()\n",
    "\n",
    "country_list = [entry['countryLabel']['value'] for entry in data['results']['bindings']]\n",
    "print(country_list)\n",
    "print('Length :', len(country_list))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's define some utility functions to return a Pandas DataFrame with all the columns from the Wikidata query. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "def convert_datatype(entry):\n",
    "    if 'datatype' in entry:\n",
    "        if entry['datatype'] == 'http://www.w3.org/2001/XMLSchema#decimal':\n",
    "            return float(entry['value'])\n",
    "        elif entry['datatype'] == 'http://www.w3.org/2001/XMLSchema#integer':    \n",
    "            return int(entry['value'])\n",
    "        elif entry['datatype'] == 'http://www.w3.org/2001/XMLSchema#dateTime':\n",
    "            date = entry['value']\n",
    "            date = None if date.startswith('t') else datetime.strptime(date, '%Y-%m-%dT%H:%M:%SZ')\n",
    "            return date\n",
    "    return entry['value']\n",
    "\n",
    "\n",
    "def wikidata_query(query):\n",
    "    url = 'https://query.wikidata.org/sparql'\n",
    "    try:\n",
    "        r = requests.get(url, params = {'format': 'json', 'query': query})\n",
    "        data = r.json()\n",
    "    except json.JSONDecodeError as e:\n",
    "        raise Exception('Invalid query')\n",
    "    \n",
    "    if ('results' in data) and ('bindings' in data['results']):\n",
    "        columns = data['head']['vars']\n",
    "        rows = []\n",
    "        for binding in data['results']['bindings']:\n",
    "            row = [convert_datatype(binding[col]) if col in binding else None\n",
    "                   for col in columns]\n",
    "            rows.append(row)\n",
    "    else:\n",
    "        raise Exception('No results')\n",
    "    \n",
    "    return pd.DataFrame(rows, columns=columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Query for each Country\n",
    "\n",
    "Let's collect all mayors and their birth cities with Wikidata."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "country_query = \"\"\"\n",
    "SELECT DISTINCT ?country ?countryLabel WHERE {\n",
    "  { ?country wdt:P463 wd:Q166546 } UNION \n",
    "  { ?country wdt:P463 wd:Q458 } UNION \n",
    "  { VALUES ?country { wd:Q55 } }  # Add Netherlands\n",
    "  FILTER( ?country != wd:Q29999 ) # Remove Kingdom of the Netherlands \n",
    "  SERVICE wikibase:label { \n",
    "      bd:serviceParam wikibase:language \"[AUTO_LANGUAGE],en\". \n",
    "  }\n",
    "}\n",
    "\"\"\"\n",
    "\n",
    "mayor_query = \"\"\"\n",
    "SELECT DISTINCT \n",
    "  ?city ?cityLabel ?city_coordinates ?population \n",
    "  ?mayor ?mayorLabel ?genderLabel ?birth ?age ?start_date ?duration\n",
    "  ?birth_country ?birth_countryLabel \n",
    "  ?birth_city ?birth_cityLabel ?birth_city_coordinates \n",
    "WHERE {{\n",
    "  ?city wdt:P17 wd:{0}.\n",
    "  ?city wdt:P31/wdt:P279* wd:Q515.\n",
    "  ?city p:P6 ?statement.\n",
    "  ?city wdt:P1082 ?population.\n",
    "  ?city wdt:P625 ?city_coordinates.\n",
    "  \n",
    "  ?statement ps:P6 ?mayor.\n",
    "  ?statement pq:P580 ?start_date.\n",
    "  BIND(year(now()) - year(?start_date) AS ?duration)\n",
    "  \n",
    "  OPTIONAL {{ \n",
    "    ?mayor wdt:P569 ?birth. \n",
    "    BIND(year(now()) - year(?birth) AS ?age)\n",
    "  }}\n",
    "  OPTIONAL {{ ?mayor wdt:P21 ?gender. }}\n",
    "  \n",
    "  # Remove all mayors that have an end time\n",
    "  FILTER NOT EXISTS {{ ?statement pq:P582 ?y. }}\n",
    "  # Remove all mayors that are not alive\n",
    "  FILTER NOT EXISTS {{ ?mayor wdt:P570 ?z. }}\n",
    "  \n",
    "  OPTIONAL {{\n",
    "    ?mayor wdt:P19 ?birth_city.\n",
    "    ?birth_city wdt:P625 ?birth_city_coordinates.\n",
    "    ?birth_city wdt:P17 ?birth_country.\n",
    "    \n",
    "    # Remove all historic countries\n",
    "    FILTER NOT EXISTS {{ ?birth_country wdt:P31 wd:Q3024240. }}\n",
    "  }}\n",
    "  \n",
    "  SERVICE wikibase:label {{\n",
    "    bd:serviceParam wikibase:language \"[AUTO_LANGUAGE],en\". \n",
    "  }}\n",
    "}}\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Belgium Q31\n",
      "Entries : 35\n",
      "\n",
      "Portugal Q45\n",
      "Entries : 2\n",
      "\n",
      "Germany Q183\n",
      "Entries : 266\n",
      "\n",
      "Malta Q233\n",
      "Entries : 0\n",
      "\n",
      "Romania Q218\n",
      "Entries : 269\n",
      "\n",
      "Finland Q33\n",
      "Entries : 11\n",
      "\n",
      "Estonia Q191\n",
      "Entries : 2\n",
      "\n",
      "Austria Q40\n",
      "Entries : 35\n",
      "\n",
      "Switzerland Q39\n",
      "Entries : 19\n",
      "\n",
      "Spain Q29\n",
      "Entries : 51\n",
      "\n",
      "Italy Q38\n",
      "Entries : 27\n",
      "\n",
      "Hungary Q28\n",
      "Entries : 73\n",
      "\n",
      "Bulgaria Q219\n",
      "Entries : 14\n",
      "\n",
      "Ireland Q27\n",
      "Entries : 1\n",
      "\n",
      "Netherlands Q55\n",
      "Entries : 22\n",
      "\n",
      "France Q142\n",
      "Entries : 71\n",
      "\n",
      "Sweden Q34\n",
      "Entries : 0\n",
      "\n",
      "Denmark Q35\n",
      "Entries : 10\n",
      "\n",
      "Greece Q41\n",
      "Entries : 6\n",
      "\n",
      "Czech Republic Q213\n",
      "Entries : 115\n",
      "\n",
      "Norway Q20\n",
      "Entries : 4\n",
      "\n",
      "Poland Q36\n",
      "Entries : 34\n",
      "\n",
      "Slovakia Q214\n",
      "Entries : 6\n",
      "\n",
      "United Kingdom Q145\n",
      "Entries : 13\n",
      "\n",
      "Slovenia Q215\n",
      "Entries : 4\n",
      "\n",
      "Cyprus Q229\n",
      "Entries : 0\n",
      "\n",
      "Latvia Q211\n",
      "Entries : 4\n",
      "\n",
      "Lithuania Q37\n",
      "Entries : 5\n",
      "\n",
      "Croatia Q224\n",
      "Entries : 1\n",
      "\n",
      "Iceland Q189\n",
      "Entries : 2\n",
      "\n",
      "Liechtenstein Q347\n",
      "Entries : 0\n",
      "\n",
      "Luxembourg Q32\n",
      "Entries : 5\n",
      "\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 1107 entries, 0 to 4\n",
      "Data columns (total 20 columns):\n",
      " #   Column              Non-Null Count  Dtype         \n",
      "---  ------              --------------  -----         \n",
      " 0   country             1107 non-null   object        \n",
      " 1   city                1107 non-null   object        \n",
      " 2   cityLabel           1107 non-null   object        \n",
      " 3   population          1107 non-null   float64       \n",
      " 4   mayor               1107 non-null   object        \n",
      " 5   mayorLabel          1107 non-null   object        \n",
      " 6   genderLabel         1103 non-null   object        \n",
      " 7   birth               828 non-null    object        \n",
      " 8   age                 803 non-null    float64       \n",
      " 9   start_date          1107 non-null   datetime64[ns]\n",
      " 10  duration            1107 non-null   object        \n",
      " 11  birth_country       712 non-null    object        \n",
      " 12  birth_countryLabel  712 non-null    object        \n",
      " 13  birth_city          712 non-null    object        \n",
      " 14  birth_cityLabel     712 non-null    object        \n",
      " 15  city_lon            1107 non-null   float64       \n",
      " 16  city_lat            1107 non-null   float64       \n",
      " 17  birth_city_lon      712 non-null    float64       \n",
      " 18  birth_city_lat      712 non-null    float64       \n",
      " 19  distance            712 non-null    float64       \n",
      "dtypes: datetime64[ns](1), float64(7), object(12)\n",
      "memory usage: 181.6+ KB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "# Get Wikidata code from each country\n",
    "df_countries = wikidata_query(country_query)\n",
    "df_countries['code'] = df_countries['country'].str.split('/').str[-1]\n",
    "\n",
    "# Get mayors for each country\n",
    "df_list = []\n",
    "for index, (country, country_label, country_code) in df_countries.iterrows():\n",
    "    print(country_label, country_code)\n",
    "    df = wikidata_query(mayor_query.format(country_code))\n",
    "    time.sleep(2)  # Avoid hitting maximum queries limit\n",
    "    df.insert(0, 'country', country_label)\n",
    "    print('Entries :', len(df))\n",
    "    print()\n",
    "    \n",
    "    df_list.append(df)\n",
    "\n",
    "# Collect all rows into single table\n",
    "df = pd.concat(df_list)\n",
    "\n",
    "# Convert coordinates lon, lat columns\n",
    "df[['city_lon', 'city_lat']] = df['city_coordinates'].str[6:-1].str.split(' ', expand=True)\n",
    "df[['city_lon', 'city_lat']] = df[['city_lon', 'city_lat']].astype(float)\n",
    "df[['birth_city_lon', 'birth_city_lat']] = df['birth_city_coordinates'].str[6:-1].str.split(' ', expand=True)\n",
    "df[['birth_city_lon', 'birth_city_lat']] = df[['birth_city_lon', 'birth_city_lat']].astype(float)\n",
    "\n",
    "# Calculate distance between city and birth city\n",
    "def calc_distance(row):\n",
    "    lon0, lat0 = row['city_lon'], row['city_lat']\n",
    "    lon1, lat1 = row['birth_city_lon'], row['birth_city_lat']\n",
    "    \n",
    "    if np.isnan(lon1) or np.isnan(lat1):\n",
    "        return None\n",
    "    else:\n",
    "        return distance((lat0, lon0), (lat1, lon1)).m\n",
    "        \n",
    "df['distance'] = df.apply(calc_distance, axis=1)\n",
    "\n",
    "# Drop original coordinates columns\n",
    "df.drop(columns=['city_coordinates', 'birth_city_coordinates'], inplace=True)\n",
    "\n",
    "# Show some information about the table\n",
    "print(df.info())\n",
    "\n",
    "# Save table to file\n",
    "df.to_csv('../SampleDBs/european_mayors.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>country</th>\n",
       "      <th>city</th>\n",
       "      <th>cityLabel</th>\n",
       "      <th>population</th>\n",
       "      <th>mayor</th>\n",
       "      <th>mayorLabel</th>\n",
       "      <th>genderLabel</th>\n",
       "      <th>birth</th>\n",
       "      <th>age</th>\n",
       "      <th>start_date</th>\n",
       "      <th>duration</th>\n",
       "      <th>birth_country</th>\n",
       "      <th>birth_countryLabel</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_cityLabel</th>\n",
       "      <th>city_lon</th>\n",
       "      <th>city_lat</th>\n",
       "      <th>birth_city_lon</th>\n",
       "      <th>birth_city_lat</th>\n",
       "      <th>distance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q724638</td>\n",
       "      <td>Hoogstraten</td>\n",
       "      <td>21424.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q98456618</td>\n",
       "      <td>Marc Van Aperen</td>\n",
       "      <td>male</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>4.761111</td>\n",
       "      <td>51.400833</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q688781</td>\n",
       "      <td>Mortsel</td>\n",
       "      <td>26157.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q26132841</td>\n",
       "      <td>Erik Broeckx</td>\n",
       "      <td>male</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>8</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>4.456667</td>\n",
       "      <td>51.170278</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q383723</td>\n",
       "      <td>Herentals</td>\n",
       "      <td>28272.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q97477531</td>\n",
       "      <td>Mien Van Olmen</td>\n",
       "      <td>female</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>4.836389</td>\n",
       "      <td>51.176667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q12886</td>\n",
       "      <td>Anderlecht</td>\n",
       "      <td>117412.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q98000375</td>\n",
       "      <td>Fabrice Cumps</td>\n",
       "      <td>male</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>4.329722</td>\n",
       "      <td>50.839167</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q12886</td>\n",
       "      <td>Anderlecht</td>\n",
       "      <td>120887.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q98000375</td>\n",
       "      <td>Fabrice Cumps</td>\n",
       "      <td>male</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>4.329722</td>\n",
       "      <td>50.839167</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q181314</td>\n",
       "      <td>Wavre</td>\n",
       "      <td>34305.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q67172379</td>\n",
       "      <td>Françoise Pigeolet</td>\n",
       "      <td>female</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2014-01-01</td>\n",
       "      <td>7</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>4.600000</td>\n",
       "      <td>50.716667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q12886</td>\n",
       "      <td>Anderlecht</td>\n",
       "      <td>118241.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q98000375</td>\n",
       "      <td>Fabrice Cumps</td>\n",
       "      <td>male</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>4.329722</td>\n",
       "      <td>50.839167</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q211572</td>\n",
       "      <td>La Louvière</td>\n",
       "      <td>80986.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q29871193</td>\n",
       "      <td>Jacques Gobert</td>\n",
       "      <td>male</td>\n",
       "      <td>1961-05-13 00:00:00</td>\n",
       "      <td>60.0</td>\n",
       "      <td>2006-01-01</td>\n",
       "      <td>15</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>4.188056</td>\n",
       "      <td>50.477778</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q12886</td>\n",
       "      <td>Anderlecht</td>\n",
       "      <td>118382.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q98000375</td>\n",
       "      <td>Fabrice Cumps</td>\n",
       "      <td>male</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>4.329722</td>\n",
       "      <td>50.839167</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q12886</td>\n",
       "      <td>Anderlecht</td>\n",
       "      <td>118920.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q98000375</td>\n",
       "      <td>Fabrice Cumps</td>\n",
       "      <td>male</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>4.329722</td>\n",
       "      <td>50.839167</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   country                                    city    cityLabel  population  \\\n",
       "0  Belgium  http://www.wikidata.org/entity/Q724638  Hoogstraten     21424.0   \n",
       "1  Belgium  http://www.wikidata.org/entity/Q688781      Mortsel     26157.0   \n",
       "2  Belgium  http://www.wikidata.org/entity/Q383723    Herentals     28272.0   \n",
       "3  Belgium   http://www.wikidata.org/entity/Q12886   Anderlecht    117412.0   \n",
       "4  Belgium   http://www.wikidata.org/entity/Q12886   Anderlecht    120887.0   \n",
       "5  Belgium  http://www.wikidata.org/entity/Q181314        Wavre     34305.0   \n",
       "6  Belgium   http://www.wikidata.org/entity/Q12886   Anderlecht    118241.0   \n",
       "7  Belgium  http://www.wikidata.org/entity/Q211572  La Louvière     80986.0   \n",
       "8  Belgium   http://www.wikidata.org/entity/Q12886   Anderlecht    118382.0   \n",
       "9  Belgium   http://www.wikidata.org/entity/Q12886   Anderlecht    118920.0   \n",
       "\n",
       "                                      mayor          mayorLabel genderLabel  \\\n",
       "0  http://www.wikidata.org/entity/Q98456618     Marc Van Aperen        male   \n",
       "1  http://www.wikidata.org/entity/Q26132841        Erik Broeckx        male   \n",
       "2  http://www.wikidata.org/entity/Q97477531      Mien Van Olmen      female   \n",
       "3  http://www.wikidata.org/entity/Q98000375       Fabrice Cumps        male   \n",
       "4  http://www.wikidata.org/entity/Q98000375       Fabrice Cumps        male   \n",
       "5  http://www.wikidata.org/entity/Q67172379  Françoise Pigeolet      female   \n",
       "6  http://www.wikidata.org/entity/Q98000375       Fabrice Cumps        male   \n",
       "7  http://www.wikidata.org/entity/Q29871193      Jacques Gobert        male   \n",
       "8  http://www.wikidata.org/entity/Q98000375       Fabrice Cumps        male   \n",
       "9  http://www.wikidata.org/entity/Q98000375       Fabrice Cumps        male   \n",
       "\n",
       "                 birth   age start_date duration birth_country  \\\n",
       "0                  NaT   NaN 2019-01-01        2          None   \n",
       "1                  NaT   NaN 2013-01-01        8          None   \n",
       "2                  NaT   NaN 2019-01-01        2          None   \n",
       "3                  NaT   NaN 2020-01-01        1          None   \n",
       "4                  NaT   NaN 2020-01-01        1          None   \n",
       "5                  NaT   NaN 2014-01-01        7          None   \n",
       "6                  NaT   NaN 2020-01-01        1          None   \n",
       "7  1961-05-13 00:00:00  60.0 2006-01-01       15          None   \n",
       "8                  NaT   NaN 2020-01-01        1          None   \n",
       "9                  NaT   NaN 2020-01-01        1          None   \n",
       "\n",
       "  birth_countryLabel birth_city birth_cityLabel  city_lon   city_lat  \\\n",
       "0               None       None            None  4.761111  51.400833   \n",
       "1               None       None            None  4.456667  51.170278   \n",
       "2               None       None            None  4.836389  51.176667   \n",
       "3               None       None            None  4.329722  50.839167   \n",
       "4               None       None            None  4.329722  50.839167   \n",
       "5               None       None            None  4.600000  50.716667   \n",
       "6               None       None            None  4.329722  50.839167   \n",
       "7               None       None            None  4.188056  50.477778   \n",
       "8               None       None            None  4.329722  50.839167   \n",
       "9               None       None            None  4.329722  50.839167   \n",
       "\n",
       "   birth_city_lon  birth_city_lat  distance  \n",
       "0             NaN             NaN       NaN  \n",
       "1             NaN             NaN       NaN  \n",
       "2             NaN             NaN       NaN  \n",
       "3             NaN             NaN       NaN  \n",
       "4             NaN             NaN       NaN  \n",
       "5             NaN             NaN       NaN  \n",
       "6             NaN             NaN       NaN  \n",
       "7             NaN             NaN       NaN  \n",
       "8             NaN             NaN       NaN  \n",
       "9             NaN             NaN       NaN  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It appears that [Munich](https://www.wikidata.org/wiki/Q1726) has three mayors currently running, which is after double checking is indeed the case.   \n",
    "Take note that Wikidata is continuously updated and information can be incomplete for certain items.\n",
    "\n",
    "# All Mayors in Europe\n",
    "\n",
    "After collecting the data we can now explore it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>country</th>\n",
       "      <th>city</th>\n",
       "      <th>cityLabel</th>\n",
       "      <th>population</th>\n",
       "      <th>mayor</th>\n",
       "      <th>mayorLabel</th>\n",
       "      <th>genderLabel</th>\n",
       "      <th>birth</th>\n",
       "      <th>age</th>\n",
       "      <th>start_date</th>\n",
       "      <th>duration</th>\n",
       "      <th>birth_country</th>\n",
       "      <th>birth_countryLabel</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_cityLabel</th>\n",
       "      <th>city_lon</th>\n",
       "      <th>city_lat</th>\n",
       "      <th>birth_city_lon</th>\n",
       "      <th>birth_city_lat</th>\n",
       "      <th>distance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q724638</td>\n",
       "      <td>Hoogstraten</td>\n",
       "      <td>21424.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q98456618</td>\n",
       "      <td>Marc Van Aperen</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.761111</td>\n",
       "      <td>51.400833</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q688781</td>\n",
       "      <td>Mortsel</td>\n",
       "      <td>26157.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q26132841</td>\n",
       "      <td>Erik Broeckx</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.456667</td>\n",
       "      <td>51.170278</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q383723</td>\n",
       "      <td>Herentals</td>\n",
       "      <td>28272.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q97477531</td>\n",
       "      <td>Mien Van Olmen</td>\n",
       "      <td>female</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.836389</td>\n",
       "      <td>51.176667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q12886</td>\n",
       "      <td>Anderlecht</td>\n",
       "      <td>117412.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q98000375</td>\n",
       "      <td>Fabrice Cumps</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.329722</td>\n",
       "      <td>50.839167</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q12886</td>\n",
       "      <td>Anderlecht</td>\n",
       "      <td>120887.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q98000375</td>\n",
       "      <td>Fabrice Cumps</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.329722</td>\n",
       "      <td>50.839167</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   country                                    city    cityLabel  population  \\\n",
       "0  Belgium  http://www.wikidata.org/entity/Q724638  Hoogstraten     21424.0   \n",
       "1  Belgium  http://www.wikidata.org/entity/Q688781      Mortsel     26157.0   \n",
       "2  Belgium  http://www.wikidata.org/entity/Q383723    Herentals     28272.0   \n",
       "3  Belgium   http://www.wikidata.org/entity/Q12886   Anderlecht    117412.0   \n",
       "4  Belgium   http://www.wikidata.org/entity/Q12886   Anderlecht    120887.0   \n",
       "\n",
       "                                      mayor       mayorLabel genderLabel  \\\n",
       "0  http://www.wikidata.org/entity/Q98456618  Marc Van Aperen        male   \n",
       "1  http://www.wikidata.org/entity/Q26132841     Erik Broeckx        male   \n",
       "2  http://www.wikidata.org/entity/Q97477531   Mien Van Olmen      female   \n",
       "3  http://www.wikidata.org/entity/Q98000375    Fabrice Cumps        male   \n",
       "4  http://www.wikidata.org/entity/Q98000375    Fabrice Cumps        male   \n",
       "\n",
       "  birth  age  start_date  duration birth_country birth_countryLabel  \\\n",
       "0   NaN  NaN  2019-01-01         2           NaN                NaN   \n",
       "1   NaN  NaN  2013-01-01         8           NaN                NaN   \n",
       "2   NaN  NaN  2019-01-01         2           NaN                NaN   \n",
       "3   NaN  NaN  2020-01-01         1           NaN                NaN   \n",
       "4   NaN  NaN  2020-01-01         1           NaN                NaN   \n",
       "\n",
       "  birth_city birth_cityLabel  city_lon   city_lat  birth_city_lon  \\\n",
       "0        NaN             NaN  4.761111  51.400833             NaN   \n",
       "1        NaN             NaN  4.456667  51.170278             NaN   \n",
       "2        NaN             NaN  4.836389  51.176667             NaN   \n",
       "3        NaN             NaN  4.329722  50.839167             NaN   \n",
       "4        NaN             NaN  4.329722  50.839167             NaN   \n",
       "\n",
       "   birth_city_lat  distance  \n",
       "0             NaN       NaN  \n",
       "1             NaN       NaN  \n",
       "2             NaN       NaN  \n",
       "3             NaN       NaN  \n",
       "4             NaN       NaN  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('../SampleDBs/european_mayors.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How many Mayors (with birth place) are per Country in Wikidata?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.dropna()['country'].value_counts().plot(kind='bar', color='C0', logy=True, figsize=(16, 9));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# How does that look like on the Map?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA7gAAAIZCAYAAACMDpOkAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/Il7ecAAAACXBIWXMAAAsTAAALEwEAmpwYAABLfUlEQVR4nO3de3TU1b3//9fcB0ggl+FiAA8GFHpRqT+slhzEan7Hs9S2Lk9bayur6unPHmjRSpfAqtYuv8IqaCG2lh5speiSnlPbcyr11kMXpaCH9IIoav0KVSEtkGAYEmACTCZz+f0RZ8h8MjOZyW0+2fN8/OXc98zO0L7m/d57OxKJREIAAAAAAIxwzmIPAAAAAACAwUDABQAAAAAYgYALAAAAADACARcAAAAAYAQCLgAAAADACARcAAAAAIARCLgAAAAAACO4iz2AodDc3FzsIQyaQCCgYDBY7GHAgnmxJ+bFvpgbe2Je7Il5sSfmxZ6YF/sayrmpqanJehsVXAAAAACAEQi4AAAAAAAjEHABAAAAAEYg4AIAAAAAjEDABQAAAAAYgYALAAAAADACARcAAAAAYAQCLgAAAADACARcAAAAAIARCLgAAAAAACMQcAEAAAAARiDgAgAAAACMQMAFAAAAABiBgAsAAAAAMAIBFwAAAABgBAIuAAAAAMAIBFwAAAAAgBEIuAAAAAAAI7iLPQAAQGlrCUXU0NisUGdM5T6XltTVaFKZt9jDAgAAIxAVXABAUTU0NmtfMKzmUJf2BcNq2Nlc7CEBAIARioALACiqUGcs7fJJy2UAAIB80aIMACiqcp9LCnWlXwYw5FgeAMBEVHABAEW1pK5GswJ+1ZR7NDPg15K6mmIPCSgJLA8AYCIquACAoppU5tXqa6YVexhAyWF5AAATUcEFAAAoQdblACwPAGACAi4AAEAJYnkAABPRogwAKBib0wAjH8sDAJiICi4AoGBsTgMAAOyIgAsAKBib0wAAADuiRRkAUDDOroXd0DYPAJCo4AIA+oHNaWA3tM0DACQquACAfmBzGtgNbfMAAIkKLgAAMABnugIAJAIuAAAwAG3zAACJFmUAAGAA2uYBABIBFwAAoGSx+zQA09CiDAAAUKLYfRqAaQi4AAAAJYrdpwGYhoALAABQoth9GoBpWIMLAABgmHzX1i6pq1HDzmad7HE/ABjJCLgAAACGSa6tlSSFutSwsznjLtPsPg3ANLQoAwAAGIa1tQBKFRVcAAAAw5T7XFKoK/1yBhwTBMA0VHABAAAMs6SuRrMCftWUezQz4M+6tpZjggCYhgouAACAYfJdW0srMwDT2Cbgnjp1SuvXr9fBgwflcDi0cOFC1dTUqKGhQUePHtX48eN19913q6ysrNhDBQAAeaIFduj097Pt+bi2M9G02zgmCMBIZ5uAu3HjRs2ePVvf/OY3FY1G1dnZqWeeeUYXXnihbrjhBm3evFmbN2/WLbfcUuyhAgCAPOW7my8KV+hn2xKK6KGXD2t/e2fa9X63Q1Wj3BwTBMAItliDe/r0ab399tu66qqrJElut1tjxozRrl27NH/+fEnS/PnztWvXrmIOEwAAFGi4W2BbQhEt3dKkhc++p6VbmnSkIzKkr1dMhX62DY3NvcKtJFWNcuvfPz1dD10zjeo6gBHPFhXc1tZWjR07Vj/60Y/0t7/9TbW1tbr11lt14sQJVVZWSpIqKip04sSJIo8UAAAUIt/dfAdLKVWMC/1srYE438cBwEhii4Abi8V04MAB3X777Tr//PO1ceNGbd68Oe0+DodDDocj4+O3bt2qrVu3SpJWrVqlQCAw1EMeNm6326j3YwrmxZ6YF/tibuxpOOZlxfVj9MD//FXHw12q8Hv0nX++QIFxo4bs9U5Fm9Iud0Q14v728p2XQj/bqjGH1dwjEEvSKI9TK67/yJDOiSn4d8yemBf7Ktbc2CLgVldXq7q6Wueff74k6fLLL9fmzZs1btw4tbe3q7KyUu3t7Ro7dmzGx9fX16u+vj51ORgMDsu4h0MgEDDq/ZiCebEn5sW+mBt7Go558UpaefXks1d0nVIweGrIXm+Mu/flkfa3l++8FPrZfuGj4/Tg0Q51xhKSpCnlbn37qnPlHeI5MQX/jtkT82JfQzk3NTXZ9wuwxRrciooKVVdXq7m5++y1N998U1OmTNGcOXO0Y8cOSdKOHTt06aWXFnOYAADA5vI9/7UUPbUnmAq3klTmc7PmFoBxbFHBlaTbb79dP/jBDxSNRjVhwgQtWrRIiURCDQ0N2rZtW+qYIAAAgGzyPf+1FHHmLYBSYJuAO23aNK1atarX9ffff38RRgMAAGCW4d7wCwCKwRYtygAAABhatG8DKAW2qeACAABg6NC+DaAUUMEFAAAAABiBgAsAAAAAMAIBFwAAAABgBAIuAAAAAMAIBFwAAAAAgBEIuAAAAAAAI3BMEAAAGJFaQhE1NDYr1BlTuc+lJXU1mlTmLfawbIXPCECpoYILAABGpIbGZu0LhtUc6tK+YFgNO5uLPSTb4TMCUGqo4AIAgBEp1BlLu3zScrmUJSu37x4Lp13PZwTAdARcAAAworxxpEMrdxxWOJpIu77tTFRHOiK04Ops5daq3Ocq6HlocQYw0tCiDAAARpRM4VaSwtEELbgfsFa3XQ5pZsCvJXU1BT0PLc4ARhoquAAAYETpivUOt0m04HYr97mkUFfq8oxqvx66ZlrBz0MbOICRhoALAMAIQsuo5HE5FMtQwZUKb8E1TfLvo/1MVH63Q+Vep6pGewqu3CZZg3Kpf74A7I+ACwDACJK2tjLUpYadzVrdj8rcSHbflZO1YvthdcUScjmkieVexeKJVODvi8k/EljX3k6r8Ogbc2u0dmf/3u+Suho17GzWyR6PBQA7I+ACADCC0DIqBUZ79Q8VvrTAlkh0h7sHth3sM8SZ/CNBpr+PgbzfSWVeYz4bAKWBgAsAwAhCy2jmgJqQ8g5xJv9IYP37aDsT1fsdXWn3Men9AoAVuygDADCCLKmr0ayAXzXlnn7timuCTAG1kNBq/VHApB8Jev59+N0OhaMJWffkMun9AoAVFVwAAEYQWkZzVLHzrGybvK6059/HV555R+Ho2aDvkHRBif4oAqB0EHABAMCIki2g5htaS+VHglAknnbZ53akjgoyeaMtAKWNgAsAAEaUZEBNhrR8Npayg+EOlWN9LoWj0bTLSSZvtAWgtLEGFwAAjDgtoYi+8eIB7QuG1Rzq0r5gWF9/br+WbmnSkY5IsYeXUTJUJsd71wsHhnSslaPcWS+bvNEWgNJGBRcAAIw4DY3NCkfTd0/qinfvpJypGtkSimj1S4d06GR3oJw6zqdlV0weUAW10IqsNVSGo4khrZzmWmvMbtwATEXABQAAI441LPb0zrGwlm5p0i0XB7Tp9aBCnTG1nYmmBeL97Z0DDpeFtvlaQ6U0sMppXwE711pjkzfaAlDaCLgAAGDEyRQWk2KJ7kruiu2H1Wk9I6eHbOEy38psoW2+S+pqdNcLB9KCdrbKaT5jGMg62lLZaAtA6SHgAgAA2+kZ8HwuhxwOhzoiMZ3sjGmUSzodldxOKRrP/hy5wq10Nlxaw2RXLKH97Z3ddwp16evP7Vdtlb9XyCy0zXdSmVffv+68vCqn+YRX1tECQG8EXAAAhtlAd9M18YiXnCHTIhzNeHVePB9srzl1nO/s8UKWMOmxbMGZbW1vf9p8862c5hNeWUcLAL0RcAEAGGYDPaLFxCNe+gqZhfK7HQqMduvQybMBsLbSp4Zrz+t131zreXuyhsx8w2p/fpDIJ7xaA/a154/TTU/vU1csIY/LofuunKwLJ5bl9d4AwBQEXAAAhtlAW0tNaE21hr6205nX0/ZX1Si3vnrpRK3ccTgV+G7/f8ZnvK81THZlaXvub4XUGt7veuGAqka5c4bdfKrD1oB909P7Uut7Y9GEVmw/rKdvmtmvMQPASEXABQBgmA20tTTfx9u5ldka+vxuR9rtU8Z6dehkJGvYlKQJY9wq87p06ESnIpb7lftc2vR6MC3wbdoT1Oprelc0F8wOaMX2w72OHerJ45RuuTigpVuaCv48Mx0P1Bzqyll9788mUF2WNcfWywBQCgi4AAAMs4Ee0ZLt8X1tllSsVuY3jnSkKqlup0Pjx7jVYtkBeazPpWkV7rT3tHZnjxBsMTPg191za9TQ2KxxfpdOdsYViyfkcHSH4yV1NXpg28G0x2SrdP9099Gc4VaSaqv82vR6sF+t4bl2fB7M6rvH5VCsx/vwuBw57g0AZiLgAgAwzAZ6REu2x/e1jnW4WplbQhE99PJhNbV3ylqAjcUSaetikypHudPeU0sookg0nnoPE8s88rqcCkfjKve5dMvFAd31woG0nZKnjvPK7ZAOnYzo68/tl9ORHvAy7Zrsczl04Hgk63tJvn5XLKGOSO7W8GwV854/SFjP4x3MjaHuu3KyVmw/nLYGFwBKDQEXAABD9LVZ0nDtstvQ2Jx1B2Qrl0P6hwqfItG4Fj77XioYNjQ2pwXPMq8rLQAv3dLU6xiggyesQTUhv9uRtt41Ob5sleEkv9uh8WM8qefc397Zq43a+nlm2/yr5w8SRzoiBVXvC2kzv3BiGWtuAZQ8Ai4AAIawtsJOGeuVz+3sdyt0oVpCEa3YfjBjhTabGdV+SdK+YHortTWs7w2GdcPP9qrC59CEcl/em1JVjXLr3z89Pe26vh57XoVXj1xXq4XPvpd2fbnXqWkVnqyfZz6bf/VVvW8JRXTv715X26mwyn0uRaLxs0G/j7ZoO6+5BoDhQsAFAMAQmdbmDmfAaWhs7jPcel1SIi7F1b1G9LoLxunRP76fdp+2M9GM4TAhqb0zofbOsLx5HiN07HQ0VRleMDugp/YEdfR09kq33+3Q8vlT1BKKqO1M+oG7VaM9OcNpfzYP62vddCFt5iYeHwUAhSLgAgBgiHzW9vbc8Mnrdure+TX9PivVGs7aLYGwJ4eku+dO1At/PZEKYbFoQmsb3+9139ZT2Z8nKa7uc237aoXujJ3dsfjbWw8p21ZSHmd3xXv5/CmaVObV0i1NaWtl/W5HnxXw/mweVuj5v7lCswnHRwHAQBFwAQAYwQptS1254+xxOGe64gM6K7Wvo356Ski9KrUDEY1L4WhcPpej11rcXGPIpisu+dzO1GdnDYtVo9x9VsP7s3mYtV06btmVa+o4n7wuR16heaDHTwGACQi4AACMYIW2pQ70rNRc62xHux2KRhPKVn/NdaZtfzRnOXqnv/YGw/r/Nr+rylFu+SxH7LSEulK35foRodAfHEKWA3zdLoc+NL4stQa3r8dbd4SurfQp1BlVKBJX+5molm5pYi0ugJJCwAUAYAQrtC0137NSrcHJ4XAoHI33Ouamp7bwICfYHip9Dk0s9+lkZ0xHT3UNelhOaj0VTbVIO3S26pvocVuuHxEK/cFhrM+lcPTsTwLj/C49dtPF2vaXJq3ccViLnt0vj8uhRR+foBf+eqJXcLbuCD0r4FfVaI+Ong4rHO17vABgmjy3aAAAAHZkbUPtqy31visny+92yOWQRnmcWc9KTQan5lCXDhyPaH97p5pDXVnD7VA71ZVIhU2XMz2U+92OPteu9ke2d7o3GNab73dkvK3QHxwqR7kzXk62kscSUjiaUEPj+6n52BcMq2Fnc9bXYy0ugFJGBRcAgBGs0I2Nep6VGggEFAwGM96vrzN1h1skrrRKpc/lUDzRHUHPKfOoIxLLuTvyYLtv6yH53Q6Ve52qGu1JVVSt62D9bqeWbmnK2rKcbf6srePWsJ0MrVnX3bIWF0CJIuACADCC9Wdjo3xYg5PdxBIJRT9oUz5wPKLs21sNnXA0oXC0O1gvfm6/Hv1UbVpg9bkcOnwycnYTrFCX7nrhgBZeOkH/vqtVnR9Uw6tGuRQY40kLv9ZW8p7t0tLZ0JotIBe6mzMAmMKRSCSK02s0hJqbm4s9hEGT69d1FA/zYk/Mi30xN/aUa16OdETSglpyDe5Qrn/NxuWQCtwLqyhmBfxpPzYs3dKUVnXO9/GBQEC/f6tJK7Z3H+fkcTn0xYuq9B9vtKUu33fl5H4f74T+4d8xe2Je7Gso56amJvsPd1RwAQBAL9kqw4WGtmycDsnrcigwyqVDodzn3g403E4Z61E8Mfi7Llu9cyysu188oEQioc5YQkdPFfZ6bR/senwq2qQxbun7152Xquj2PJc3Fk1oxfbDqhrlzmunZQAoJWwyBQAAcmoJRbR0S5MWPvueumIJ1VZ4NWGMW363Q+NHu3Kef5vNBdV+PXLtefK4nBrqFaKRWGJY1qHGEtL+9k4dOB5Rc6jwSvfJzpj2BcM6dDyctpGU1HtNdDia6LXhFACACi4AAOhDpqNofnJdbepysp257Uy0e92n16kyryvV1lzuc6ntdFfaJlB/DYa18Nn9aetKayu8ksOhgyc6B7UN+kQ4pgfrz9Xqlw4P+nPnY6zXqZOR3C+a3LAqHD37GfXc/TjXmmh2SQaAswi4AACUmOQZt8lW2L5aXPs6diafja6WbmlKC7iZ4t7Bk5GCw6fbIfV1clFnLKG1O5sHJdy6JeVuqO6tr3B7XoVXy+dP0dqdzWmfUc+qc8/NpKxnEbNLMgCcRcAFAKBEJIPt/rZwWtBr2NmcM6BmPYrG8rzZjsKRugPaXS8cyHmObqHh0+uUJpR5dOjk2bFZdxtOGsi6YY9Diickp7PwMebjkQ+q4ckQ2xFV6oeHpJ4/IvTcAIxdkgEgHQEXAIASYW01TsrV4toSiui0JdWd7orrSEckFWLTnjfUlTEwTyrzqmqUe1A3eorEJa/LqVkBfyrsLZgd0H1bDw34ucePdqnc51YikdChkxHFElJsCMLt1HFnfwhIhljrzqOZfkAYiqOhAMAEbDIFAECJsLYaJ+Vqcf3mbw7o4IlI2nUHT0RyboCULTBbX8eh7iA5EPvbO/VeW1h+t1NL6mp04cSyAZ+JOzPg14P1/6DmUEQHjhfeNp2vKWM98jgdWvjse1q6pUlHOiIZ75f8AYFNpQCgbwRcAABKhDVgel0OzQz4c7a4nurK3FLcawOkHK+TtKSuRrWVPnmckscpTavwasX/+w/92oW5p654d9BNBr+7507sd8j1OKVINK6HXj6ctZ3aIaV2ke7P89dW+vTYZ2o1xuvS/vbOPoNr2+n0qvex00N73BEAjGS0KAMAYEP5rGstVM+Nisp9Lq24/iPydp3q13Nl2wAp15rQSWVeeVyOVEX0wPHuSvB9V07Wiu2H1RVLKJ7IvIY2H3uDYf367aPa+fdTOqfco6OnCj+qpyvePS5PjhJAQt0BP9LX7lY9+N2OtHNtpb4r38m/gZ4bT0nS0dMxLd3SxPm3AJABARcAABvKZ11roay7HQfGjVIw2L+Am20DpL5kCnUXTizT0zfNlCQtfPa9Aa3T/emrx/r92J76iq65NstKckiq8Dk0odyXMYzm2ryrJRTR4uf2K0sBPVXxZS0uAKQj4AIAYEP5rmu1yrfy2xKK6N7fva62U+Gc97vsHJ/+1NKZdt2/XlLd78phXzsy5zrvdThFLZVfr7N7U6tCJCRNLPdlDaG3XBzQyh3dlWuPy6EFswOpednXGsoabpP2BsN68/0OXTixrLCBAYDBCLgAANhQX0Ewm3wrv/ncryUU0fEuh2rKPUPWJp2sBCeDefuZaK+jfvxuR14V06E0zu9S9WiPTnbGCqow5/phYtPrwdT7ikUT+unuo2oORQp6r/9n2yH98uZZQ9LSDgAjEQEXAAAbynddq1W+ld987jccbdIZX8tilEuSHIp8sEZ3qLidvSu3SVWjPalxf+OF/TpwPPOOx1ZtZ6L6yjPvKBSJa7TbodPRhMb6XKoc5VbwVHpQ3t/emeVZsktWla1zddcLB1Q1yl1Q2CUkAzABARcAABsqZF1rT9kqv9bw4nen76J09FRXr42L+tsm3R/ZjjCSpOOdiX5vPOWUlG9nsXVPZL/bkQqJC2YHtHRLk0KdMfndTtVWeLU/R8j1OCWXs7vyHI52v7dkZTYcjar1VLTwN5OD9fMLRxPdleYCfpgYih80AGC4EXABADDIkroard5xSAdPdoevrlhCRzoivcJLbYVXH51U3r3WM969e7B146L+tkknZaoIJhLKWCW0vlYyXLadifa7PdnrlKaM8ykcjavc51IkGk+rvFpbn6eO88nrcqRVzZNhf+mWprQK86yAXy6HFMsytHKvU6FCF+32w9Rx3ePLtXY53x8mcv2gQXUXwEhBwAUAwCCTyrzyuJ2p43H2t3fqrhcOqMuSxMKxhJ666WJ97qd/SltT2jPU9LdNOilTRTAhZawSWjdcuu/KyQqM9mrx8/sL/gyk7vBaU+492/Yb6lJtpU+zAv7U+1kwO6BNe4IZA62VNfy9cyycs126PRzvV9XZuv64Z0jPdOyR2yEd6YikzZX1R4Fyn0tvHOno9flaN6fK9YMG1V0AIwUBFwAAw2RqV7VKhpdcoaa/bdLZxpGpkvheW1gLn30vLZTFogmt2H5YNeXeXoHO53JocrlHfz8ZybhetueGWA9sO5h2WzgaV8O109OuW31NfjsQWz+n5O8FDknODJXc/oRbt1NKxKWen1IsIXlcDi27YqrW7uy9Tjl5lvDqa6al5urN9ztS5wond2desf1wr883eTRT0pK6Gq1+6bAOnuj+USASjetIR0STyrzD2q4OAANBwAUAwDC52lVdDmlGtV8LZgf01adfV/uZqPxuh8q9TlWN9hRcpS1kHKnw3OO6rrgy7kocjiZSQSvJ45R+cP15mlTm1ZGO7nNie3YBTx3n1Q+vr+379bPo2YbrcznkcDhS7c3Jau87x8JpYfacco/+/dPTe7Uw90emwB5LdFe873rhgMb6XPK7HeqMpq9JtobNp/ak7868aU+wVwXfeln6oPrvcqR+VDhwPKKvP7dftVV++VzpK5SbQ1169u2j+vSHxhf+RgFgCDn7vgsAABhJltTVaFbAr5pyj/zu9GAyo9qvh66Zpqf2BPWXIyG1nuqunFaP9uiha6YN6rrKnuOYGfBrSV1N2nXuAv9fSG2VPzW+SWVeBcZ40m6PWXqGF8wOyO92yOXoblleMDuQ8/mTbbjNoS4dOB7R/vZONYe6tC8Y1qY9Qa2+ZppmVPvTHtN2JppqEfZkeD+Fvkepu+3YKhxNpObKZ7mDNbhnqra6nemPsV7O9tjk2myHo/f9N7x6LOt7AIBioYILAIBherYWH+mIZFxHOxwtp5lanFtCkVT1MdbHHkxTxnrlczuzrgHuq0KbqZKZqyU5107OJztjeuNIh5osR/mEo4lUi3Btlb9XFXfSGLeCZ2I5N8ryOKSuHjdn27gqaazPpWkV7oI+F6cSOhQ6u3Pz+NGZq9nZqv/hbOcnAYDNEHABADBUrp1vB7pDcn/lOu/WKclraZfOVVHuaxOsQkN8rtbutjNRrdh+WJ0Z0mfyeZfU1ejrz+1PWzf8/qlor3XEDklVo1wKjDnbEp5tg6hMKke5c66Ntm7YtWB2QD/60/tp94n3OhRJqffQsLNZ77WF08ad67MBADsh4AIAYKhcO98uqavRo386qrZT4VQ4HI6jYHJVSePqrohOq/BkrPxmGluuoFdoiO8ZmH0uh5pDXalAmyt0Jp93Upk3YxXXKiFp/Jj095j874XPvtdrTXJtZe/ji6x6fj6ZNuyytm/3/CwyfbaSev148OeDJ9Lakv/1kuqc7xMAioGACwCAoXJVMCeVefXYTRcrGAymrkvbKCnHUTD5BOFs98l03m1XLJHWlpup0rr6pUNnz7ANdenB3x/UGK8r5xgKPebIGpgzhU2r5NribK/ZFUucPaqoh2zV5Eyfz22XjNem14MZ75+UqzLeM5x7nN1rmZNjbglF9I0XD5y9T495t879pz80nk2lANgeARcAAEMVWsHMt6U3W2U4WxUxeZ9vzK3pbpv9YOOlKWO9Wj5/Sq/jbzKN89DJiOVyl6Su1PPf9cIBVY1yp3Y8fmpPMBV+v3PV1FT4LaRKbf38poz1KHg6mvMsWWtITq6Bztjym0Gmynra55Plh4dclfGexo/p3kwsqaGxuVd1Olcr93BU+QFgIAi4AAAYqtAKZr6BOFsQzlVFPNkZU0Njc1o10+d2alKZt+BxZhKOJrqrraGutDNfrYEwV9u2VaZxFRrmkoE322Zfme5vrazn88NDpspv1Sh3rzW9fe24nOk+PT308uGzcxjq0uqXDqvh2vOy3h8AhhsBFwAAQ/W1RtUq36CZLQjnqiL6XA7tb0sPv8mg1nOcLaGI1u7sXSGcOs6XsdU3E+sZrz0DYSEbTxX6+eUykOfK54eH5Ny1nYl2z5/XqXKfS4sum6hNe4J577jsdztyrse2nk1svQwAxUbABQCgBGQKLAHLsbD5hrBsQThbFTG5FtW6m3CmoJatwrrsiskZW309TsnldKSvM3U5FMtStcwVFu3afpvPDw/JuVu6pemD83JjOno6ljq/N+mNIx2664UDqTbrRR+fIIekY6e7FIrENdbn0tqdzelrh/uodAOAnRBwAQAoAZmC44ZphbcCS9mDcK6W3oXPvpd2X49TGYNatgprX62+Pa9bMDuQtWqZKywW0r48nLJ93pkCeV8V6pU7DqftsPyjP7fq6ZtmaumWJh09HVY4GlXrqWhqnbT1eaaM9Z7d7OuDywBgJwRcAABKQKFnwvZHrgqwtXJaW+XPWB3tqx0322tYr1t9TVkqAD6w7aDKfS7dcnFAm14PZq3QDsdnNJgyBfJMn1/PIGzdUCrZzm1979Zq+7HTUS189j35XA7VVvoUjsb7vV4aAIYSARcAgBJQ6I7Kgy3f9b3Z7tef9mFrALz/d4eUincZKrTF/owKlSmQf+eqqanPz+92KhKNa/Hz+3sF1iSPyyGpe410Lp2xROrIpFkBvxqunT7wNwAAQ4CACwBACRiMnYoHIt/1vdnu15/2YWsATFhuf+dYWEu3NKXCcrE/o0JlCuQ9P7/uc40zbwLlcih11JEkORy5A25Pycq2XdcsAyhtBFwAAErAYO4InE0y8LT12LCocpS7X8HHGp7az0TTbs+nfdgaAK1iCWlfMJwKy8PxGQ2mvgJ5tl2tZwb8aWfhvnGkI+8dqqWzlW27rlkGUNoIuAAAYFBYz8FNbliUT/CxBtpINH52M6NQl/zu9AqjtX3Y+vgFswPdOwV/sFmSQ1IkS5uu3dfaZtNXILcGfI+ze+2zNQiv3HG412O9TmnKuO61tn63U0okFI4l0oL0SFuzDKA0EHABABgkhbZstoQiWv3SIR062R3kpo7zadkVk3s9ZjhbQfvzWsnHvHssnPH2tjNRLd3SlPU53zjS0Wt9rHUX33KvU9MqPFmrlQ+9fDjtWJsHf39YnT3Ow62t9MnrcuhkZ0xtZ6Jpmy1ZN2Iypd02167WPVnPDZakRz9V2+f7H2lrlgGUBgIuAACDoCUU0TdePHA2OOXRstnQ2Jx25Mr+9s5ej8n2vN+YW9MrkCUSyhnSrCFuxfVjZI0w+bSd5qy2ZnD0VHclN9tzrtxxuNf6WKuq0Z6cn+XBE+kttp2W0BaOxlMbI2U6amjtTvPaba0VXusZuPddOVkXTizrdW6w3+3IK9yPtDXLAEoDARcAgEHQ0Njc6wiWvlo2M62RtD4m2/NmCqIJKWdIsz7mgf/5q1ZePTnnmDK9B+vzWKutDkk+t0NjfS6dzHA0jXVzp0wVxKnjzlZcByM89awuZmrtLYV2W+sZuCu2H9bTN83UfVdO1orth9OCbyZvHOnQyh3p9xvpPwIAMA8BFwCAQZAprPbVsplpEyTrY7I9bz6BzHqd9THHw703YMqn7TTb5kVJF/TYxGjhs++ljpdJsm7uZK0gOqSMrdq5TBnrTasiTyl3q8znzjsgl0K7rfWHhOTlCyeW6embZvb5+GwBGQDshIALAMAgsAYkv9vRZ6haUlej1TsO6WCPNbjWx2R73lU7DqXdz+dyyOt2pt237UxURzoiqaBofa4KvyfjmHK1nbaEImqz7Gicq9qaayfjZADPVEEsdP3r8vlT8lpvmo0p7baZqqwXTiyTpF4/JHj6OPvWKltABgA7cSQSCeP+dWpubi72EAZNIBBQMBgs9jBgwbzYE/NiX6UwN5nWdQ7GJkXZnvfuFw+kHe1SW9m9QdVdLxxIawmeFfCn2kitz7Xi+o/I23WqoPF0n616djMpv9uh7193Xtb32vM1rZs7WY+rGS59bShV7A2nBvJ9uenpfWmfsd/tSFVZ33y/o9cPCcnwm0syNFtbzXs+dykohX/HRiLmxb6Gcm5qarL/CEkFFwCAAcp0RM3anYMTkLIdBROOxntdnlTmVdUod1pLcM82ZetzBcaNUjBYWMC1tidXjXLnfG89XzNTWC+GvjbSGsnnu+aqsmZqRc5V8U3KFm6zrdUFgGIi4AIAMACZdjlesf1wQbsp90e2NaNDtZY0GeKPnsq9ZjiXvs5tHS59rV8eyRtO5WpDzhRm81lXaw3NLodKqnILYGRx9n0XAACQTaZdjq2BYCgC0pK6Gs0K+FVT7tHMgD9VDc12/UAlq5pdPQrHtZW91wyPBH63M+dla2gfSRtO3XflZPndDrkcvausyTAbS0jhD8JsPutqrWt1C127CwDDiQouAAADkGlHYWsVbSgCUrZq6FBVSTO9T68rv/NS7abX9iOWyyN5w6lcOyJnCrP5bDyV7zFCAGAHBFwAAAYg0y7H9105WZv2BPsdkIq9yVGmsVhbk6WR1brbU6cl6IUtl+3SSj3YMoXZfMJrvscIAYAdEHABABiATNW+7oDU9+602dhlk6OWUESLnt2veJbbR1Lrbk+lcOZtJpnCLOEVgGkIuAAADMBQVPvssslRQ2NzxnBbU+4Zca27PQ1VC7KdKu+ZEGYBlAICLgAARZQpFNmlwphp3a0k/funpw/zSAbXULUg26XyDgCljIALAEARZQpFdtnkyBq0i6UYldH+vKZdKu8AUMoIuAAAFFGmUGSXTY6W1NVo+f8cUHvn2Y2JPv+RccM+jmJURvvzmsWsvNu9PRoAhgsBFwCAIsonFLWEInro5cP6+4lORT9YFOt2SOdW+LTsislDFmQmlXn1xGeLv2azGJXR/rxmMSvvtEcDQDdbBdx4PK7ly5erqqpKy5cvV2trqx555BGFQiHV1tZq8eLFcrttNWQAAAYkn1D00MuHtb+9M+26aELa395ZEkGmGJXR/rxmMSvvtEcDQDdbpcUXX3xRkydP1pkzZyRJmzZt0nXXXae6ujr9+Mc/1rZt2/RP//RPRR4lAACDxxqKWkIRLd3SlNZqevBEZ9bH9yfIJNtZT0WbNMYt27ezFqMyapd10Pmyy8ZkAFBstgm4x44d06uvvqobb7xRzz//vBKJhN566y3dddddkqQrr7xSv/zlLwm4AACjZWo1zaU/QSbtNSTbV4GLURm1yzrofI20QA4AQ8U2AfeJJ57QLbfckqrehkIhjR49Wi5X9/9wV1VVqa2tLeNjt27dqq1bt0qSVq1apUAgMDyDHgZut9uo92MK5sWemBf7Ym7ydyralHa5IypNqxqtd4Kn0673OKXzqsdoxXWzFBg3asCv0df8HD5+Rv9ny191PNylCr9H3/nnC1RT4OsiP8nvS1+fufX2B6//CHMyhPh3zJ6YF/sq1tzYIuDu3r1b48aNU21trd56662CH19fX6/6+vrU5WAwOJjDK6pAIGDU+zEF82JPzIt9MTdn9bXb7RjL/zJ3txBP6lWdSz2m65SCwVMFvW7bmWiv1+hrfr69pSlV9T2ksL79/FsjqsI5kiS/L3195szJ8OLfMXtiXuxrKOempiZ7l4otAu6+ffv0yiuv6LXXXlMkEtGZM2f0xBNP6PTp04rFYnK5XGpra1NVVVWxhwoAwID0tdttplbTwWiXtbYl+90OBcp8qTW4fWETo+HX12fOnABAb7YIuF/84hf1xS9+UZL01ltv6bnnntOdd96ptWvX6o9//KPq6uq0fft2zZkzp8gjBQBgYPoKJUO19tP6ulWj3Hr6y3Py/nWdTYyGX1+fOXMCAL05iz2AXL70pS/p+eef1+LFi9XR0aGrrrqq2EMCAKBgyZ2RFz77no6dTm8P9ruH53+KM4ajAiypq9GsgF815R7NDPjZxGgY9PWZMycA0JsjkUgkij2IwdbcnHvHyZGEdQX2xLzYE/NiXybOTV9raXta2mOtpFVthVcN19UO5VAlSUc6Ir1anz86rca4eTGBid8XEzAv9sS82FdJr8EFAGCk6WstbU/W9uCewrHh+Z15pB17AwBAfxBwAQDoh0I2+LGulex12xBrCUW0+qVDOnQyIkmaOs6nZVdMFidrjDyFdA4AQCki4AIA0A+FbPDTc2dkv9spJRIKxxKpgFKI/gSchsZmHTgeSV3e396php3N2jCNNZsjTb6dAwRhAKWKgAsAQD9kOs4nm8FsDy6kNTopU4s0R8qMTPl2DvTn7wQATEDABQCgH4q1prXQs09bQhG1nYn2up4jZUamfDsHOCMXQKki4AIAUAT9bSEt9OzThsZmhaPpG1nVVvo4UqZAdmn5zbdzgDNyAZQqAi4AAEXQ3xbSQlqjpd6VvJpyjxquPa+/wy5Zdmn5zbdzoNC/EwAwBQEXAIBBlG+lr78tpIW2RlPJGxzW+XqvLawjHRHbbtzEsVAASpWz2AMAAMAkyUpfc6hL+4JhNexszng/a9Dsb/BsCUW0dEuTFj77npZuadKRjkja7UvqajQr4FdNuUczA34qef1knZ+uuLLOLQCgeKjgAgAwiPKtzPbVQppvJbiv1lkqeYNjSV2Nvv7cfnXFz17Hxk0AYD8EXAAABlE+LcG5wmvytv1t4bNhKseaT3bLHR6TyryqrfKf/TFBtHsDgB3RogwAwCDKpyU4Vxtz8raelUIpe3AdrFZn9I12bwCwPyq4AAAMonxagq1V12Onu7R0S5NCnTEdPdWV8THZgiu75Q4f2r0BwP4IuAAADDNrG3MoEtfR0+GM9/U4pdqq7NVCQhcAAGcRcAEAGGbWqmv7majC0Wjqdo9TGj/Gk3NzKQAA0BsBFwCAYWatui7d0qTWU2cDbm2VXw9RlQUAoGAEXAAAiqw/62jzPUYIsOJvB4DJCLgAABRZf9bR9nX+LZANfzsATMYxQQAAjECcf4v+4m8HgMkIuAAAjECcf4v+4m8HgMkIuAAAjEBL6mo0K+BXTblHMwPZjxECrPjbAWAy1uACADACcf4t+ou/HQAmo4ILAAAAADACARcAAAAAYAQCLgAAAADACARcAAAAAIARCLgAAAAAACMQcAEAAAAARiDgAgAAAACMQMAFAAAAABiBgAsAAAAAMAIBFwAAAABgBAIuAAAAAMAIBFwAAAAAgBEIuAAAAAAAIxBwAQAAAABGIOACAAAAAIxAwAUAAAAAGIGACwAAAAAwAgEXAAAAAGAEAi4AAAAAwAgEXAAAAACAEQi4AAAAAAAjEHABAAAAAEYg4AIAAAAAjEDABQAAAAAYgYALAAAAADACARcAAAAAYAQCLgAAAADACARcAAAAAIARCLgAAAAAACMQcAEAAAAARiDgAgAAAACMQMAFAAAAABiBgAsAAAAAMAIBFwAAAABgBAIuAAAAAMAIBFwAAAAAgBEIuAAAAAAAIxBwAQAAAABGIOACAAAAAIxAwAUAAAAAGIGACwAAAAAwAgEXAAAAAGAEAi4AAAAAwAgEXAAAAACAEfIOuMePHy/oegAAAAAAhlPeAfeuu+7KeP3dd989aIMBAAAAAKC/8g64iUSi13WnT5+W00mXMwAAAACg+Nx93WHhwoWSpEgkkvrvpI6ODtXV1Q3NyAAAAAAAKECfAXfx4sVKJBL67ne/q8WLF6fdVlFRoZqamiEbHAAAAAAA+eoz4H74wx+WJG3YsEE+n2/IBwQAAAAAQH/0GXCTfD6fmpqa9PbbbysUCqWtyb3pppuGZHAAAAAAAOQr74C7detWPfnkk7rooou0Z88ezZ49W2+88YbmzJkzlOMDAAAAACAveW+B/Otf/1rf+ta3dM8998jr9eqee+7RkiVL5HK5hnJ8AAAAAADkJe+Ae/LkSX3oQx+SJDkcDsXjcX3sYx/T7t27h2xwAAAAAADkK+8W5aqqKrW2tmrChAk655xz9Morr6i8vFxud95PAQAAAADAkMk7nX7mM5/R4cOHNWHCBH32s5/V2rVrFY1Gddtttw3l+AAAAAAAyEveAffKK69M/ffHPvYxbdy4UdFoVH6/fyjGBQAAAABAQXIG3Hg8nvU2p9Mpr9ereDwupzPvpbwAAAAAAAyJnAH35ptvzutJnn766UEZDAAAAAAA/ZUz4P7whz8crnEAAAAAADAgOQPu+PHjC3qyb37zm1qzZs2ABgQAAAAAQH8M6uLZo0ePDubTAQAAAACQt0ENuA6HYzCfDgAAAACAvLH9MQAAAADACARcAAAAAIARBjXgJhKJwXw6AAAAAADylnfAbWpq6vM+d9xxx0DGAgAAAABAv+U8JqinBx98UFVVVZo3b57mzZunysrKXvf5x3/8x0EdHAAAAAAA+co74P74xz/Wq6++qpdfflm//OUvNXPmTF1xxRW67LLL5PP5hnKMAAAAAAD0Ke+A63K5dOmll+rSSy/V6dOn9Yc//EHPPvusHn/8cX384x9XfX29Zs2aNZRjBQAAAAAgq4I3mQqHw/rzn/+sxsZGHTt2THPnztWkSZP06KOP6vHHHx+KMQIAAAAA0Ke8K7ivvvqqXnrpJb322muaNWuWrrrqKi1btkxer1eS9M///M9auHChvvKVrxQ8iGAwqHXr1un48eNyOByqr6/Xtddeq46ODjU0NOjo0aMaP3687r77bpWVlRX8/AAAAAAA8+UdcH/2s59p/vz5+vKXv5xxg6mysjLdeuut/RqEy+XSggULVFtbqzNnzmj58uW66KKLtH37dl144YW64YYbtHnzZm3evFm33HJLv14DAAAAAGC2vFuU/+Vf/kWf/vSne4XbP/7xj6n/vvrqq/s1iMrKStXW1kqSRo0apcmTJ6utrU27du3S/PnzJUnz58/Xrl27+vX8AAAAAADz5V3BfeyxxzR37tyM119++eWDNqDW1lYdOHBAM2bM0IkTJ1KBuqKiQidOnMj4mK1bt2rr1q2SpFWrVikQCAzaeIrN7XYb9X5MwbzYE/NiX8yNPTEv9sS82BPzYk/Mi30Va276DLjvv/++JCkej6u1tVWJRCLttuQa3MEQDoe1Zs0a3XrrrRo9enTabQ6HQw6HI+Pj6uvrVV9fn7ocDAYHbUzFFggEjHo/pmBe7Il5sS/mxp6YF3tiXuyJebEn5sW+hnJuampqst7WZ8C98847U/+9ePHitNsqKir0uc99bgBDOysajWrNmjWaN2+eLrvsMknSuHHj1N7ersrKSrW3t2vs2LGD8loAAAAAAPP0GXCffvppSdJ3vvMdPfDAA0MyiEQiofXr12vy5Mm6/vrrU9fPmTNHO3bs0A033KAdO3bo0ksvHZLXBwAAAACMfHmvwR2qcCtJ+/bt00svvaRzzz1X99xzjyTp5ptv1g033KCGhgZt27YtdUwQAAAAAACZ5Ay4K1eu1L333itJuv/++7OugR1o+J01a5Z+8YtfZLzt/vvvH9BzAwAAAABKQ86AmzyiR5KuuuqqIR8MAAAAAAD9lTPg/uM//mPqv/fv36+6ujrNnDkzdd2+ffv0hz/8YehGBwAAAABAnpz53nHnzp2aPn162nW1tbX63//930EfFAAAAAAAhco74DocDsXj8bTr4vF42rm4AAAAAAAUS94Bd9asWfr5z3+eCrnxeFy//OUvNWvWrCEbHAAAAAAA+cr7mKDbbrtNq1at0le/+lUFAgEFg0FVVlZq2bJlQzk+AAAAAADyknfAra6u1urVq/Xuu+/q2LFjqq6u1owZM+R05l0EBgAAAABgyOQdcCXJ6XTqggsuGKqxAAAAAADQb5RfAQAAAABGIOACAAAAAIxAwAUAAAAAGIGACwAAAAAwAgEXAAAAAGAEAi4AAAAAwAgEXAAAAACAEQi4AAAAAAAjEHABAAAAAEYg4AIAAAAAjEDABQAAAAAYgYALAAAAADCCu9gDAOyqJRRRQ2OzQp0xlftcWlJXo0ll3mIPCwAAAEAWVHCBLBoam7UvGFZzqEv7gmE17Gwu9pAAAAAA5EDABbIIdcbSLp+0XAYAAABgLwRcIItynyvnZQAAAAD2QsAFslhSV6NZAb9qyj2aGfBrSV1NsYcEAAAAIAc2mQKymFTm1eprphV7GAAAAADyRAUXAAAAAGAEAi4AAAAAwAgEXAAAAACAEQi4AAAAAAAjEHABAAAAAEYg4AIAAAAAjEDABQAAAAAYgYALAAAAADACARcAAAAAYAQCLgAAAADACARcAAAAAIARCLgAAAAAACMQcAEAAAAARiDgAgAAAACMQMAFAAAAABiBgAsAAAAAMAIBFwAAAABgBAIuAAAAAMAIBFwAAAAAgBEIuAAAAAAAIxBwAQAAAABGIOACAAAAAIxAwAUAAAAAGIGACwAAAAAwAgEXAAAAAGAEAi4AAAAAwAgEXAAAAACAEQi4AAAAAAAjEHABAAAAAEYg4AIAAAAAjEDABQAAAAAYgYALAAAAADACARcAAAAAYAQCLgAAAADACARcAAAAAIARCLgAAAAAACMQcAEAAAAARiDgAgAAAACMQMAFAAAAABiBgAsAAAAAMAIBFwAAAABgBAIuAAAAAMAIBFwAAAAAgBEIuAAAAAAAIxBwAQAAAABGIOACAAAAAIxAwAUAAAAAGIGACwAAAAAwAgEXAAAAAGAEAi4AAAAAwAgEXAAAAACAEQi4AAAAAAAjEHABAAAAAEYg4AIAAAAAjEDABQAAAAAYgYALAAAAADACARcAAAAAYAQCLgAAAADACARcAAAAAIARCLgAAAAAACMQcAEAAAAARiDgAgAAAACMQMAFAAAAABiBgAsAAAAAMAIBFwAAAABgBAIuAAAAAMAIBFwAAAAAgBHcxR5APvbs2aONGzcqHo/r6quv1g033FDsIQEAAAAAbMb2Fdx4PK4NGzboW9/6lhoaGrRz504dOnSo2MMCAAAAANiM7QPuu+++q0mTJmnixIlyu92aO3eudu3aVexhAQAAAABsxvYtym1tbaqurk5drq6u1jvvvJN2n61bt2rr1q2SpFWrVikQCAzrGIeS2+026v2YgnmxJ+bFvpgbe2Je7Il5sSfmxZ6YF/sq1tzYPuDmo76+XvX19anLwWCwiKMZXIFAwKj3YwrmxZ6YF/tibuyJebEn5sWemBd7Yl7sayjnpqamJutttm9Rrqqq0rFjx1KXjx07pqqqqiKOCAAAAABgR7YPuNOnT1dLS4taW1sVjUbV2NioOXPmFHtYAAAAAACbsX2Lssvl0u23366VK1cqHo/rk5/8pKZOnVrsYQEAAAAAbMb2AVeSLrnkEl1yySXFHgYAAAAAwMZs36IMAAAAAEA+CLgAAAAAACMQcAEAAAAARiDgAgAAAACMQMAFAAAAABiBgAsAAAAAMAIBFwAAAABgBAIuAAAAAMAIBFwAAAAAgBEIuAAAAAAAIxBwAQAAAABGIOACAAAAAIxAwAUAAAAAGIGACwAAAAAwAgEXAAAAAGAEAi4AAAAAwAgEXAAAAACAEQi4AAAAAAAjEHABAAAAAEYg4AIAAAAAjEDABQAAAAAYgYALAAAAADACARcAAAAAYAQCLgAAAADACARcAAAAAIARCLgAAAAAACMQcAEAAAAARiDgAgAAAACMQMAFAAAAABiBgAsAAAAAMAIBFwAAAABgBAIuAAAAAMAIBFwAAAAAgBEIuAAAAAAAIxBwAQAAAABGIOACAAAAAIxAwAUAAAAAGIGACwAAAAAwAgEXAAAAAGAEAi4AAAAAwAgEXAAAAACAEQi4AAAAAAAjEHABAAAAAEYg4AIAAAAAjEDABQAAAAAYgYALAAAAADACARcAAAAAYAQCLgAAAADACARcAAAAAIARCLgAAAAAACMQcAEAAAAARiDgAgAAAACMQMAFAAAAABiBgAsAAAAAMAIBFwAAAABgBAIuAAAAAMAIBFwAAAAAgBEIuAAAAAAAIxBwAQAAAABGIOACAAAAAIxAwAUAAAAAGIGACwAAAAAwAgEXAAAAAGAEAi4AAAAAwAgEXAAAAACAEQi4AAAAAAAjEHABAAAAAEYg4AIAAAAAjEDABQAAAAAYgYALAAAAADACARcAAAAAYAQCLgAAAADACARcAAAAAIARCLgAAAAAACMQcAEAAAAARiDgAgAAAACMQMAFAAAAABiBgAsAAAAAMAIBFwAAAABgBAIuAAAAAMAIBFwAAAAAgBEIuAAAAAAAIxBwAQAAAABGIOACAAAAAIxAwAUAAAAAGIGACwAAAAAwAgEXAAAAAGAEAi4AAAAAwAgEXAAAAACAEQi4AAAAAAAjEHABAAAAAEYg4AIAAAAAjEDABQAAAAAYwV3sATz11FPavXu33G63Jk6cqEWLFmnMmDGSpGeeeUbbtm2T0+nUbbfdptmzZxd3sAAAAAAA2yp6Bfeiiy7SmjVr9L3vfU/nnHOOnnnmGUnSoUOH1NjYqLVr1+ree+/Vhg0bFI/HizxaAAAAAIBdFT3gXnzxxXK5XJKkCy64QG1tbZKkXbt2ae7cufJ4PJowYYImTZqkd999t5hDBQAAAADYWNEDbk/btm1LtSG3tbWpuro6dVtVVVUq/AIAAAAAYDUsa3AffPBBHT9+vNf1X/jCF3TppZdKkn71q1/J5XJp3rx5BT//1q1btXXrVknSqlWrFAgEBjReO3G73Ua9H1MwL/bEvNgXc2NPzIs9MS/2xLzYE/NiX8Wam2EJuN/+9rdz3r59+3bt3r1b999/vxwOh6Tuiu2xY8dS92lra1NVVVXGx9fX16u+vj51ORgMDsKo7SEQCBj1fkzBvNgT82JfzI09MS/2xLzYE/NiT8yLfQ3l3NTU1GS9regtynv27NGvf/1rLVu2TD6fL3X9nDlz1NjYqK6uLrW2tqqlpUUzZswo4kgBAAAA5KslFNHSLU1a+Ox7WrqlSUc6IsUeEkpA0Y8J2rBhg6LRqB588EFJ0vnnn6877rhDU6dO1Sc+8QktWbJETqdT//qv/yqns+h5HAAAAEAfWkIRfePFAwpHE91XhLrUsLNZq6+ZVtRxwXxFD7iPPvpo1ttuvPFG3XjjjcM4GgAAAAAD1dDYfDbcfuC9trCOdEQ0qcxbpFGhFFASBQAAADCoQp2xXtd1xaWGnc1FGA1KCQEXAAAAwKAq97kyXn8yQ/AFBhMBFwAAAMCgWlJXI0+GpJEt+AKDhYALAAAAYFBNKvOqtsqfdp3f7dCSuuzHuwCDgYALAAAAYNAtqavRrIBfNeUezQz49f3rzmODKQy5ou+iDAAAAMA8k8q8HAuEYUcFFwAAAABgBAIuAAAAAMAIBFwAAAAAgBEIuAAAAAAAIxBwAQAAAABGIOACAAAAAIxAwAUAAAAAGIGACwAAAAAwAgEXAAAAAGAEAi4AAAAAwAgEXAAAAACAEQi4AAAAAAAjEHABAAAAAEYg4AIAAAAAjEDABQAAAAAYgYALAAAAADACARcAAAAAYAQCLgAAAADACI5EIpEo9iAAAAAAABgoKrg2t3z58mIPARkwL/bEvNgXc2NPzIs9MS/2xLzYE/NiX8WaGwIuAAAAAMAIBFwAAAAAgBEIuDZXX19f7CEgA+bFnpgX+2Ju7Il5sSfmxZ6YF3tiXuyrWHPDJlMAAAAAACNQwQUAAAAAGMFd7AEgs6amJv3kJz9RJBKRy+XSV77yFc2YMUOJREIbN27Ua6+9Jp/Pp0WLFqm2trbYwy0pv/nNb7RlyxY5nU5dcskluuWWWyRJzzzzjLZt2yan06nbbrtNs2fPLu5AS9Bzzz2np556So8//rjGjh3L96XInnrqKe3evVtut1sTJ07UokWLNGbMGEl8X4ptz5492rhxo+LxuK6++mrdcMMNxR5SSQoGg1q3bp2OHz8uh8Oh+vp6XXvttero6FBDQ4OOHj2q8ePH6+6771ZZWVmxh1ty4vG4li9frqqqKi1fvlytra165JFHFAqFVFtbq8WLF8vt5v9KD7dTp05p/fr1OnjwoBwOhxYuXKiamhq+M0X2/PPPa9u2bXI4HJo6daoWLVqk48ePF+U7QwXXpjZt2qTPfvazevjhh/X5z39emzZtkiS99tprOnLkiH7wgx/ojjvu0OOPP17kkZaWv/zlL3rllVf08MMPa+3atfrUpz4lSTp06JAaGxu1du1a3XvvvdqwYYPi8XiRR1tagsGg3njjDQUCgdR1fF+K66KLLtKaNWv0ve99T+ecc46eeeYZSXxfii0ej2vDhg361re+pYaGBu3cuVOHDh0q9rBKksvl0oIFC9TQ0KCVK1dqy5YtOnTokDZv3qwLL7xQP/jBD3ThhRdq8+bNxR5qSXrxxRc1efLk1OVNmzbpuuuu06OPPqoxY8Zo27ZtRRxd6dq4caNmz56tRx55RA8//LAmT57Md6bI2tra9Jvf/EarVq3SmjVrFI/H1djYWLTvDAHXphwOh86cOSNJOn36tCorKyVJr7zyiq644go5HA5dcMEFOnXqlNrb24s51JLy29/+Vp/5zGfk8XgkSePGjZMk7dq1S3PnzpXH49GECRM0adIkvfvuu8Ucasl58skn9aUvfUkOhyN1Hd+X4rr44ovlcrkkSRdccIHa2tok8X0ptnfffVeTJk3SxIkT5Xa7NXfuXO3atavYwypJlZWVqa6SUaNGafLkyWpra9OuXbs0f/58SdL8+fOZnyI4duyYXn31VV199dWSpEQiobfeekuXX365JOnKK69kXorg9OnTevvtt3XVVVdJktxut8aMGcN3xgbi8bgikYhisZgikYgqKiqK9p2hr8KmvvzlL2vlypV66qmnFI/HtWLFCkndv5D0rFBVV1erra0tFYAxtFpaWrR37179/Oc/l8fj0YIFCzRjxgy1tbXp/PPPT92vqqoq9X/mMfR27dqlqqoqTZs2Le16vi/2sW3bNs2dO1eS+L4UWVtbm6qrq1OXq6ur9c477xRxRJCk1tZWHThwQDNmzNCJEydS/05VVFToxIkTRR5d6XniiSd0yy23pIoNoVBIo0ePTv1ox79bxdHa2qqxY8fqRz/6kf72t7+ptrZWt956K9+ZIquqqtKnPvUpLVy4UF6vVxdffLFqa2uL9p0h4BbRgw8+qOPHj/e6/gtf+ILefPNNffnLX9bll1+uxsZGrV+/Xt/+9reHf5AlKNe8xONxdXR0aOXKlXrvvffU0NCgH/7wh8M/yBKUa16eeeYZ3XfffcM/KOScl0svvVSS9Ktf/Uoul0vz5s0b5tEBI0M4HNaaNWt06623avTo0Wm3ORyOtM4UDL3du3dr3Lhxqq2t1VtvvVXs4aCHWCymAwcO6Pbbb9f555+vjRs39mpH5jsz/Do6OrRr1y6tW7dOo0eP1tq1a7Vnz56ijYeAW0S5AusPf/hD3XbbbZKkT3ziE3rsscckdf/6EQwGU/c7duyYqqqqhnagJSbXvPz2t7/Vxz/+cTkcDs2YMUNOp1OhUEhVVVU6duxY6n5tbW3MyyDLNi9///vf1draqnvuuUdS93di2bJl+u53v8v3ZRj09cPb9u3btXv3bt1///2p/8PB96W4rJ8/34viikajWrNmjebNm6fLLrtMUvfyl/b2dlVWVqq9vV1jx44t8ihLy759+/TKK6/otddeUyQS0ZkzZ/TEE0/o9OnTisVicrlc/LtVJNXV1aqurk51AV1++eXavHkz35kie/PNNzVhwoTU537ZZZdp3759RfvOsAbXpqqqqvR//+//ldS9sdGkSZMkSXPmzNFLL72kRCKhv/71rxo9ejTtlsPo0ksvTf2a29zcrGg0qvLycs2ZM0eNjY3q6upSa2urWlpaNGPGjCKPtjSce+65evzxx7Vu3TqtW7dO1dXVWr16tSoqKvi+FNmePXv061//WsuWLZPP50tdz/eluKZPn66Wlha1trYqGo2qsbFRc+bMKfawSlIikdD69es1efJkXX/99anr58yZox07dkiSduzYkeqGwPD44he/qPXr12vdunX6xje+oY9+9KO688479ZGPfER//OMfJXX/eMf3ZvhVVFSourpazc3NkrqD1ZQpU/jOFFkgENA777yjzs5OJRKJ1LwU6zvjSCQSiWF5JRRk7969qSMcPB6PvvKVr6i2tlaJREIbNmzQ66+/Lq/Xq0WLFmn69OnFHm7JiEajqXUfbrdbCxYs0Ec/+lFJ3W2Yv//97+V0OnXrrbfqYx/7WJFHW5q+9rWv6bvf/W7qmCC+L8WzePFiRaPR1FEN559/vu644w5JfF+K7dVXX9WTTz6peDyuT37yk7rxxhuLPaSStHfvXt1///0699xzUx0ON998s84//3w1NDQoGAxy5EmRvfXWW3ruuee0fPlyvf/++3rkkUfU0dGh8847T4sXL05tOonh09TUpPXr1ysajWrChAlatGiREokE35ki+8UvfqHGxka5XC5NmzZN//Zv/6a2traifGcIuAAAAAAAI9CiDAAAAAAwAgEXAAAAAGAEAi4AAAAAwAgEXAAAAACAEQi4AAAAAAAjEHABACiil19+WStWrBjU52xtbdXnP/95xWKxQX1eAADsjoALAEARzZs3T/fdd1/q8uc//3kdOXKkiCMCAGDkIuACAAAAAIzgLvYAAAAoFcFgUE888YTefvttJRIJ1dXVafr06frd736nBx98UN/5znckSffcc48kaeHChfrv//5v3XzzzZozZ44kKRqN6qtf/aruu+8+nXfeeXm9bltbm37yk59o7969Kisr02c+8xnV19dLkn7xi1/o0KFD8nq9+vOf/6xAIKCvfe1rmj59+hB8AgAADC0quAAADIN4PK7Vq1crEAho3bp1Wr9+verq6tLu88ADD0iSHn74YT311FOaO3eurrjiCr388sup+7z22muqqKjIO9xK0ve//31VV1frscce0ze/+U3953/+p/7yl7+kbt+9e7fmzp2rJ554QnPmzNFPf/rTAb5bAACKg4ALAMAwePfdd9XW1qYFCxbI7/fL6/Vq1qxZfT5u3rx5eu2113T69GlJ0ksvvaQrrrgi79cNBoPau3evvvSlL8nr9WratGm6+uqrtWPHjtR9Zs2apUsuuUROp1NXXHGFmpqaCn5/AADYAQEXAIBhEAwGNX78eLlcroIeV1VVpZkzZ+pPf/qTTp06pT179mjevHl5P769vV1lZWUaNWpU6rpAIKC2trbU5XHjxqX+2+v1qqurix2YAQAjEmtwAQAYBoFAQMFgULFYrOCQO3/+fG3btk2xWEwXXHCBqqqq8n5sZWWlOjo6dObMmVTIDQaDBT0HAAAjBRVcAACGwYwZM1RZWamf/exnCofDikQi2rt3b6/7jRs3Tu+//37adR//+Md14MAB/eY3vymoPVnqDtYzZ87Uf/zHfygSiehvf/ubfv/73xdUBQYAYKQg4AIAMAycTqeWLVumI0eOaNGiRVq4cKEaGxt73e9zn/uc1q1bp1tvvTV1u9fr1WWXXabW1lZddtllBb/2XXfdpaNHj+qrX/2qvve97+lzn/ucLrroogG/JwAA7MaRSCQSxR4EAADI7b/+67/U3NysO++8s9hDAQDAtqjgAgBgcx0dHdq2bVvq7FoAAJAZm0wBAGBjW7du1ZNPPql58+bpwx/+cOr6l19+WT/+8Y973X/8+PFau3btcA4RAADboEUZAAAAAGAEWpQBAAAAAEYg4AIAAAAAjEDABQAAAAAYgYALAAAAADACARcAAAAAYAQCLgAAAADACP8/wy6KhFWAXL4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.dropna().plot(kind='scatter', x='city_lon', y='city_lat', figsize=(16, 9))\n",
    "plt.axis('equal');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA6cAAAIICAYAAACSIZj/AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/Il7ecAAAACXBIWXMAAAsTAAALEwEAmpwYAACSyklEQVR4nOzdd3hWZbb+8e/aSUihQ+hFQUCqAoJgoajYexl7xa5j19GZM2fOzJkzv1FHxbHMoCL2Pir2hgpWmhRBkCJNQKTXJKTs9ftjp9JLws6b3J/r4kretvd6swnJzfM86zF3d0RERERERERiFMRdgIiIiIiIiIjCqYiIiIiIiMRO4VRERERERERip3AqIiIiIiIisVM4FRERERERkdgpnIqIiIiIiEjsFE5FREREREQkdslxF7C5JUuWxF3CXpeZmcmKFSviLkN2ka5b4tK1S1y6dolJ1y1x6dolJl23xFUdrl3z5s23+ZhGTkVERERERCR2CqciIiIiIiISO4VTERERERERiZ3CqYiIiIiIiMRO4VRERERERERip3AqIiIiIiIisVM4FRERERERkdgpnIqIiIiIiEjsFE5FREREREQkdgqnIiIiIiIiEjuFUxEREREREYmdwqmIiIiIiIjETuFUREREREREYqdwKiIiIiIiIrFTOBUREREREZHYKZyKiIiIiIhI7BRORUREREREJHYKpyIiIiIiIhI7hVMREZHt8Ly8uEsQERGpFhRORURENuPu+KxphMPuJ7zrcnzTprhLEhERqfKS4y5ARESksvAN6/BvP8e/+AiWLoruNIPZ06DrQfEWJyIiUsUpnIqISLXm7jB7Ov7Fh/h330B+4TTeug2wwwdhhx+NZTaJt0gREZFqQOFURESqJd+4Hv/2M/yLj+GXn6M7zaBrT4L+x0G3XliyfkxK9RauX4dP/Q6aNMMaN4+7HBGp4vRTV0REqo3iUdIvP8InfF1qlLQ+dtjRWD+NkoqUlvfTDMKH/gL7dyPp9r/FXY6IVHEKpyIiUuVtd5S037FwQG+NkopsRcGypQBYg0YxVyIi1YF+EouISJXlG9fjLz+x9VHSwwdhjZrGW6BIJRcuj8IpmY3jLUREqgWFUxERqbrSMvAfv4eCfOjSg6D/sXDAwRolFdlJBUXhtKHCqYhUPP10FhGRKsuSkgguuxkaNdUoqchuKAqnmtYrInuDwqmIiFRp1rl73CVIJRR+8B9YshBS0yA1PfqYlgY1oo+Wmg77d8MyasZdaqxqXXA1a36cBi33jbsUEakGFE5FRESk2vHpk+HH77f9OBD8+RGo5uG0RufuBI1bxl2GiFQTCqciIiJS7QQnno0fciTk5sCmHMjJgU3ZxZ97bg7Uqh13mSIi1YrCqYiIiFQ71vEALO4iRESkjCDuAkRERERk7/HsLMLhQwjHjo67FBGRMjRyKiIiIlKN+OSx+Lefw+Sx+H4dscwmcZckIgJo5FRERESkWrG+A6F7X8jOInxyCB4WbPO5BSuXE374OuHwIXuvQBGptjRyKiIiIlKNmBnBxb8lnDcL5kzHP3gdO/Hs4sd9Uw4+6Vv8289ZMWMKuEf3n/AbrKk694pIxVE4FREREalmrHYdgsE3EQ75H/ztFwk7HoDl5eLffo5/903UuRggOQUO7E1wyJGQ2TTeokWkylM4FREREamGrHMP7OhT8U/ewv/xe7yg1PTe/TpihxxJ5rGnsConN74iRaRaUTgVERERqabs9IvxxQth+iRo2Bg75Ais7xFYk+YABLXqQM6KmKsUkepC4VRERESkmrKUFIKb/ww//Qht98eCLXtlehhu9X4RkfKmf2lEREREqjEzw9p12nowdceffYTwjWfxwsZIIiIVReFURERERADwRfPwVcuLb2986Qn865H4p2/Dsl9irExEqoNymda7ceNGhg4dys8//4yZce2119K8eXOGDBnC8uXLadSoEbfccgu1atUqj9OJiIiISAUIX3kSfvwemreGuvXZOGMKBAHBVXcWr0MVEako5RJOn3rqKbp3785tt91Gfn4+mzZt4s0336Rbt26cdtppjBgxghEjRnDhhReWx+lEREREpJy5O1a7Lp6aDksWRn8Au/A67MDeMVcnItXBHk/rzcrKYsaMGRx55JEAJCcnU7NmTcaPH8+AAQMAGDBgAOPHj9/TU4mIiIhIBTEzgqvuIHjweYLb/g9OOpdal/yWoN8xcZcmItXEHo+cLlu2jDp16vCvf/2LBQsW0LZtWy699FLWrl1L/fr1AahXrx5r167d6utHjhzJyJEjAbj77rvJzMzc05ISTnJycrV834lO1y1x6dolLl27xKTrloCaNoPDj4wGHfLz465GdpG+5xJXdb92exxOCwoKmDdvHoMHD6Z9+/Y89dRTjBgxosxzzAwz2+rrBw0axKBBg4pvr1hR/fbSyszMrJbvO9HpuiUuXbvEpWuXmHTdEo9vWAezppF5xHGsXLsu7nJkF+l7LnFVh2vXvPm216/v8bTehg0b0rBhQ9q3bw9A3759mTdvHnXr1mX16tUArF69mjp16uzpqURERERkL/DxXxL++26WX3Yy4bOP4DOn4WEYd1kiUsXtcTitV68eDRs2ZMmSJQBMnTqVli1b0qtXL0aPHg3A6NGj6d1bC+lFREREEkKtutC6Lb5xPf7lx4T3/YHw91cQvv4MvnhB3NWJSBVVLt16Bw8ezEMPPUR+fj6NGzfmuuuuw90ZMmQIn332WfFWMiIiIiJS+QW9D4feh1Mvez2rPhyBjx0NK5fhH76Of/g6tGyD9R2A9e6PNai+6+NEpHyZu3vcRZRWNAJbnVSHueVVka5b4tK1S1y6dolJ1y1xFV07D0OYMwMfOxqf8BVkbYieYAYdumJ9B2I9D8UyasZbsAD6nktk1eHabW/NabmMnIqIiIhI1WVBAB26YB264OdeCdO+Ixw7CqaMh5lT8ZlT8ReGwoG9CfoOhK4HYckpcZctIglG4VREREREdpqlpECPviT16ItnbcAnfouPGQWzpsF33xB+9w3UrI0ddBjWdyDs1zEKtyIiO6BwKiIiIiK7xTJqYYcfDYcfja9agY//Igqqi+bjX3yIf/EhNGyM9RkQTf1t1irukkWkElM4FREREZE9Zg0ysWPPgGPPwBfNj9anFjVSev81/P3XoPV+UVA9uD9Wr0HcJYtIJaNwKiIiIiLlylrui7XcFz/9Ipg9HR87Cp/wNSz8CV/4E/6fp6HTAVFQ7XkIlpYRd8kiUgkonIqIiIhIhbAggP27Yvt3xc+7CqZOIBwzCqZOgOmT8emT8Rf+jR3YB+szELr0wJL166lIdaXvfhEREZHN+IwphJ+8RXDeVVijpnGXUyF8+mR8zOeQlAxJSZDZhOC4MyvsfJZSA3oeSlLPQ/GNG/DvvsbHjoJZP+Djv8THfwm16mC9Do8aKbXdHzOrsHpEpPJROBURERHZTPjmczBvFuGMKdjxZ2HHnxmFqyrElyzEv/285I5920MFhtPSrGYtrP+x0P9YfOUyfNwXUS2//IyPeh8f9T40ahpN++0zAGvacq/UJSLxMnf3uIsobcmSJXGXsNdVh812qyJdt8Sla5e4dO0SUyJeN1+7Gv/P09HIIkCjptEoarde8RZWjvyXn/F5s/B5syE9HWvZhuDg/mWeszevnbvDz/OiRkrjRsOaVSUP7tMu6vZ7cD+sTv29Uk8iS8TvOYlUh2vXvHnzbT6mkVMRERGp1sLFC/FR72N16hKcfB4AVrc+dvkteL+jCV8YCksWEj70v9C9L8G5V2ANG8dc9Z6zZq2gSXP8y09g+VLs7gvirccMWrfFWrfFz7wYZk6LGil99w0smIMvmIO/Nhw6HRgF1e59sbT0WGsWkfKlkdNKoDr8D0lVpOuWuHTtEpeuXWKqjNfN3SEMsaQkwlHv4y8MhdR0kh55Zcvn5ufjn72Dv/0ybMqGGjWwE8/BjjkNS06Jofq9pzJcO8/dhE8ZH61PnfYdFBRED9RIjQJq34HQuTuWlBRnmZVKZbhusnuqw7XTyKmIiIjsES8owD8ZgR02CKtdN+5y9tyvSwj/fjvWpSeeUbiNSViw1adacjJ2zOl47/74a8Oj5j1vPod/+xnBeVdjnbvvvbrLiW/cgL/+NHbGxVitOnGXs11WIxXrfTj0Phxfvw7/7qto/9Q5M/BxhVOAa9fFeveLguq+7dVISSRBKZyKiIjIDvmrT+KfvYvPm0VwzV0J/8u/z/4BsjZGHWKL5OUSvvUi1u0g2LcdFpQdibP6DbGr7sAPP5rwpcdg6WLCR/5KcPeTWJ16e/cN7AF3J3zkrzBnBuRkY1fdEd2/fh3+/Tis7xGVdhTSatfBBp4AA0/Aly+NGimNGQVLF0V/Pz97Fxo3j5oo9R2ANd72CI2IVD6a1lsJVIfh+6pI1y1x6dolLl27+PiKXwn/cmMUZi67meDQI3f6tZX1uvmyJfjUidF00Xmzyj5Yqw7BzX/G9mm39dfm5RE+fi98Px476VyCk8+t+IL3UNGvfGaGz55O+J+nCK68HctsAkD42nD84xFY/2MJLroeqLzXrjR3h4U/4WNG4+O/gLWrSx5su38UVHv3qxoj/jspEa6bbF11uHaa1isiIiJ7xDKbYOdeiT/9EP7y4/j+3bCGjeIua49Y4+bYUc0Ju/bA/3htdN8RJ+DfT4g6xTbZ9i9QlpICQQBhCHUTpHvsLz8T3nMntGqLtWoL/Y+DnOxoTe3Y0fhn7wFg/Y+LudBdY2ZRN9992uFnXQozv8fHjMInjoG5M/G5M/FXhkGXnlFQ7d4XS02Nu2wR2QqFUxEREdkpduhR+OSxMHks4VMPEtz6VywI4i5rz5UaUQvOvwY/z2H1CiwtY5sv8YICmPE9QMKsOfXFCyFrI8ycis+cCkAIkJwCaemQnwct94W8XDwnOyE74VpSEnTugXXugV+wCZ8yNpr2+8NEmDoBnzoBT03HehQ2Uup4QKWdwixSHSmcioiIyE4xM4KLrif86cco4Hz6Dnb0qXGXtedKhdAwN5egRg1osINR4fmzIXsjNGlRPC22srNeh2Htn4KFc/Gf5+EL58LPc2H5UtiQFz1p0fxodNUMGjdnTbuO+FmXVfqmSVtjqanYwf3h4P74+rX4hK+ioDp3Jj7m82gP27r1Sxoptd4v4ddSiyQ6hVMRERHZaVanHsHFvyV89G/4G88S7tcJFs+HNasSYt3l1gRBQFGfXl/2C7TcZ4ev8R8mAYkzagqF01/rNYR6DbEDehff71kbYdF8/Oe5hcF1Liz5GX5dzKZVywkuvD7GqsuH1a6LHXEiHHFitNZ4bGEjpWVL8JFv4yPfhqYto2m/fQZgjZrGXbJItaRwKiIiIrvEuvfBDhuEfz0Sf/ZhWLIQgiT8mNOw1LS4y9tNBjg89SD++3vxZx6Glm2wQ4/caiMdn14YTrv02Mt1lj/LqAkdumAduhTf5/l5sORnauflsCG5av26aI2bYyefi590DsyfHa23HfdF1PH3rRfwt16A/TpifQdivQ5PyFFjkURVtf61ERERkb3CzrkC//F7WLwA6jaAtatg1g/Q7aC4S9s9hdmU9WsJ5/wIY0YBo7BW+0LnKICGOTn4m89GU3rnz4GkJNi/626f0vNyYfpkfMWvBEedvFOvCfNzCZJr7PY5d5Ylp0DrtqRlZrKhinYONTNo0wFr0wE/6zKYMQUfOwqfNAZ++hH/6Uf85Seg60FYn4HYgb2xGmqkJFKRFE5FRERkl1l6BsHgWwjv+0MUTAGfPjnaIzQRJSVBfj6sXgEj34Kr74QPXsObtAR3mDYRf/5fsGp59Py0dOzGP223adIO5eQQPvo3SErCDz96u6PO4drV+IP/AxvWwT+e3uJxX7kM1qzC9uu4+/VUY5acDN0OwrodhOdk45PH4GNHww+TYco4fMo4PC0d63lotD51/65b7IMrIntO4VRERER2i3Xogh1zGv7RmwD4DxOBy+MtajeEuTkQltr2vU59+PTtaP3lY/fgaekwY0r0WFIyHNALO+oUbL9OpY6xCVavJCjcfib8+tNoOmjHA7a5bYnVrgOt94MFc3Y86rxyGSyaHx37teEEvxkcdQyeOp5w9EdRN9pmrQj+/LCa+uwhS0vH+h4BfY/A167Gx38ZBdX5s/FvPsW/+RTqNcAO7o/1GQit2uhrLlJOFE5FRERkt9mpF+JTv4vWnf7yM75mFVavQdxl7ZSCh/8a1b3i17IPfD0SwgKokQrzZgMedfRNTYPcHIJLbsBq1i5+umdn4X+9GdasIvzrowQNm8CKpYTffkbQph2evRH/YSLBYYO2qMG69MQXzMF/mLjdUeeg7f4U9O4H47/EP36LcMDx8MNE/MXHoickJ2Mt94VNOdG2MFIurG59bNApMOgUfOmiaH3q2NGwfCn+8Qj84xHQvHVJI6WGjeMuWSShVYHNyURERCQulpJCcMVtRIs2wT8ZEWs9O8vXroZp320ZTCEKpgC5myAwOPIkgr8/Ds1bQXYW/v5/So6zZiXhvb+PtmMJQ5g7CwA75XzsxHPwIIXw/j/iTz9E+MlbW5yqqKFSUfffbdbrDt16Fd3C7/svrHe/qGnTbwYT3Ps0wZW379TepOF/nqLg9kso+PfdO3yulLCmLQlOvYDgb48R3HUvdsQJUKs2LFmIv/kc4V1XUPCP3xN+8SG+cUPc5YokJI2cioiIyB6xVm3ggF7w/Xj88/fx48/aax1OffFCfP4srHnrqLHN8qX4e69gF1yHpaRs8fzw60+j/S07HRiNjOZkb/8EYQifvUv42bsl5/z4TQpGfwjJydFep2EIySnQYh/8i48oeO0pWL8W8vOwU87Djj4Ff+5f+KtPEnpIcMzpJcdvu3800rl0Eb5yOdZwO/urTviq5PPVK/AvPybpf/65s1+qkvrnz4G1q6M9TmWXmVnUzXe/jvjZV8APk6JGSpPHwqwf8Fk/4C89Dt16EfQZGE0DT6n4JlYiVYHCqYiIiOwxO/1C/PvxkJdL+Py/Ca7+3V5Zh+fTJ+GvPglHnQy5mwiH3g0b1kPdhtjpF275ghW/wo/fQ/PWsCcNbTZlw6ZSt/PzorWjm9e3YA5Jv/1vQogC6tsv4b37Y/UbAoWNeDoeAJPH4tMnYf2O2erpzIzg/Kvx7n3wCV9FXX5HPE942CCCOvV2qXQ79gxo3Raattyl18mWLDkZDuyNHdg7mt496dto2u+M72HSGMJJYyC9JnZQYSOl9l2wQBMXRbZF4VRERET2iOdkYy32xXv0hanfwXdf4+O+wPoMqJjzrVxGOPJd+PZTyNoY3TfhK/zTd6IndOuFHXfG1l/cvHXUeGjcF5C1lamXdepDhy4lo5Q9+mKX31o4KjYNWrWFF4dGHXwBMpvAvu2jLr8//VhynAaNsCtvJ2gXNU0K+h9HGCRhjZsVB9Mi1qUHPnls1FBqG+EUwBo2xvodQ3hwf/yWCyEvF3/wz/CnB3f0JSsj6HZQ4m75U4lZegZ26FFw6FH4mpX4uMJGSgt/wr/6BP/qE6ifGTVS6jswWiMsImUonIqIiMhu8fz8aBuZWnUxM5Ku+wPhlx/jzz6CvzgUb98Fa5BZrucMv/sGf+9VWDSvJCBCNE0V4OD+BJffstVtPnzymGgd6eKF0ZYsRYKkaGouDutWw6RvSx6bMg7/eR5JfQbgB/fHP3wjWv8JUYOk1vsRDL452h/1zlKdihs12yJ8BIcfvdX3ZF164hDtsxkW7HCLkiA1jfDi3+JPPgA/zyX84iOC/sdu9zWyd1m9htgxp8Exp+FLFpY0Ulq5DP/oDfyjN6DlvlETpYMHlPv3iUiiUjgVERGR3WLJybBZd1I7/Gh8yjiYMo7w6X8S3PyXcj2nfz2y7FpJsyikmmEnn4cdf1ZxuCt479VoNHP5Uli9MpqKu7nmraNptV99EgVXgIKCksfDEO65k4LCacN8+XHheYOoM+734+HXJdCkeWHILXztzO8J772L4MY/YfXKjpRuzho1hUZNozrnzYad2Ks06DuQgs/ehXmz8BeGUrB+DUknnrPD18neZ81bY6dfhJ96Afz0Y7Q+dfxXsGg+vmg+/saz0KFrFFQPOhTLqBV3ySKx0aR3ERERKTdmRnDx9VCrTjQS+Pn7uDs+fzY+Z/puH9dnTaPgf34LUydEe432PJTggeej9ZMAA44jOPlc2Lge35SDf/cNvPdq9Pyli7YeTCHaSuazd0uCaUqNKChu7tN3omAaJEXrWz2M7m/cDFrsA/PnRMG0WUuoXTd67Od5hH+9BS/cn3R7rEvP6H3uoGtvmdfc+KeSQDz+651+ncTDggBr35ngwusI7n+G4Po/YAcdFv19njkVf/YRwtsuoWDo3fikMXheXtwli+x1CqciIiJSrqxOfYKLrgfAXxvOiqvPJPzbbYSvP7vLx/I1Kym49y7Cf/whCpIAQUDStXdhtetAfn50X2bTaC3qPXcS3v07wrdegLzcHZ8gvSa07Rh1zQVo0gJ69C15PC2j7PPDgmgLmtZto26/SxbC1An4nBnR4/u0x06/OBpZBVi3hvCeO0se34biLWWm73w4DWrVwc4eHN1YPJ9w0tidfq3Ey5JTsO59Ca65k+D+Z7FLbohG8Avy4btvCP/1/whvv4TwuX9F3X/DMO6SRfYKTesVERGRcmc9D4ED+8DKZYSL5kGdetg+++FhuGvdSmvXgzWryk6ZPfWCksfr1IO69eHLj/D0dMjOiqbHbk9aRrRnaZ16MHkszP0R6jaIHlu6KFrPWmRTTtnXBknRNN6UGtGIFxC+8WzJ9ObVK/BnH4YefWDS2Gjaca3a0Yjq9nTsBklJ0TTdrA07PbUzOOrkaFubX37Gn7yf8MHnCZK3v22Jb1i317b6kR2zjJrY4UfD4Ufjq1bg47/Ax4yGRfPwLz7Ev/gQGjYuaaTUvHXcJYtUGHMv3U0gfkuWLIm7hL0uMzOTFStWxF2G7CJdt8Sla5e4dO0Si4chnp9P7QWz2LBfpx02+gHwvDzCV5+EyWOwE88mGHhCcZMlINpb9Pb/h/00A58yDvvtf+P3/j4KlC32gctugr/dVrZZUkWqVRc2rI2CZUFByRrYpKToY9EeqCk1ogBSpy426BQsecs9WAv+8XuY9QPBNXdhBx260yWEq1bgd10RTTXu3oek6/9rm8/1/DzCOy6DJs2x/scSHHrUdo+t77n4+KL5USOlcaNhValr0LptYSOl/ttcz6zrlriqw7Vr3rz5Nh/TyKmIiIhUCAsCrEYN0g8ZyMbt/LIVfvs5LJyLnXAWPu4LGPU+AP7S4xQccDC8/VLJk9t2xGrVxjp0xY48GUtOxu/8Oz76IzwsgKce2n4wNSNqjbsL4TVIioJfrTqQUSvq9LtxffRYWloUTgsKotHUoqnEpZsq5edBfh4+4UtYvRL/5jOCC67F9u9a9jQnnRt90q7zztcGBA0yCU84K+piPHks4a+LCZq02PqTFy+AvLyoMU9qGuwgnEp8rOW+WMt98dMvgtnTo0ZKE76GhXPxhXPx/zwNHQ/A+gzEeh6CpWfs8JgilZ1GTiuB6vA/JFWRrlvi0rVLXLp2iWl7180LCgj/cBWsWg6p6TDwePh1EUydiF14bdQoZsyo6MkWROs8N2XD0aeSdPblZY5VMOIFeO+V6MY+7WDBnC1PWKd+tF3M9vQ7FjvoUHz4EFi3BgbfQpCaStiuE9x+aWF34KCkKVKN1KihUvc+2GGD8LxcmD8bOveAkW9Dz0MwwOfNhLFfQm40Vdj6DsTOugyrW3+nvo47UvC327BehxEcu409Xgt5Tjb+3ddYg0ZYpwO3+1x9z1UunpcLUycQjh0ddYouWnOdUgM78GCs70Do0oNGTZvpuiWo6vA9t72RU4XTSqA6/CWsinTdEpeuXeLStUtMO7puvvAnwjefjxoNAaRnRE2K2nWCt14oeWJSctQwBsAsaiRT1BkXCGdPx//x++2PnPY7mqDfsXjdBvhrw2HCV1t/XrtOsGg+5GRj/Y/FjjqZcPgQWPBT9HiLfaJRyFp1sB598S8/xn4zGBt0Cv7TDPyZR+DXxVs/dv1MWL82GlFNTcPOvAQbcNxOTXsu4vl5W50aXN70PVd5+cYN+HdfR/unzppW8kCt2qQfPohNB/aF/TpiZvEVKbusOnzPKZxWctXhL2FVpOuWuHTtEpeuXWLa2evms36Imgv9shCyNpaMSG5Ny31J+p+Htrg7zN6IP/9vGPfF1l+XlARnXQY9DoEn7oOfNu+ia0TDnKV+PUpOiabpehiNmDZqAu27wNcj4aRz4JO3YFMOwV33En70Jkz6Fho0ikaDN9eqDTbwBNiwDn/zuZL7m7YkGHwz1qbDtr8+Odn4Fx9B34H4n2+AVm2x7n2wHn12uJfq7tL3XGLwlcvxcaOjWQZFXa0BGjWN1qb2GYjtqCmXVArV4XtOa05FRESk0rMOXbDTL8Tv+6+o8VHupigY5udBmw7Y4FuwpCQIAqiRtvVjpGXgC+du5YHCRkUFBfDOy/DKsOi+LfiWy1HzS+036SGsXA7rCvcV7dQd3n0FkpLx1m0hv3DNaV4upKbCplLhulkrSEvHn//Xlqdduojw/90edf298FqCLj2LR7zCggKYNRWatMAGHh+NlG1YD9MnRVvPZG/ETvjNVr8eUj1Yw0bY8Wfhx50Ji+aTNmUsWaM/hOVL8fdejdYj79MO6zsA692/3KaSi5Q3hVMRERGpPL78OPqYnx9N783OAsAuvI6g6Taa/JQSPvq3aDuYzZUeCc3asOV9u6IgP/rTsDGWnRVl2YJ8/LqzSp6zfu2Wr/vl5x0fe+Uy+OdfCIMkaNwU0mvB2lWwajl2yY3Y4YOwfsfg3fviU8fjk8ZipfdllWrNzKBVG2r36E3OCb+BmdOiRkoTv4UFc/AFc/BXn4LOB0ajqT36YmnpcZctUkzhVERERCpU3tyZhB+OgLT04j92yJFYStn9OH3DuqgbaZH0mlE4bdyMoHXbHZ7HVy6H7ydAi31h2eKoK+12GeDRWtbk5C33NN1cSkoUFosaKnXrteW04KQkCL2kWdLuCgtgaak1q2kZeP2SqbtWuw526FHqtivbZEESdDoQ63Qgfv418P14wjGjYNpE+GES/sMkvEYq1r0v1ncAdOqOJSsaSLz0N1BEREQqVP78n/BP3ipzn/UZuMXz/OtPSxoeHXQYfBcFVTvzsp06jzVsRPC/j+C5ufiQP0XhNEiKgh5AvQawZlXpM0Yf/vTPaArx324teSijJhx1MnzzWTSa2bx1tJYvr1Sn38bN8Mljo3NfcyfW4xDIySJ8dTgsXxptMbNmdclI7e5quz920/9ohEt2m9VIhV6Hk9Tr8OL/BPKxo2DOjGit6rjRULsu1rsf1mdANI1ejZQkBgqnIiIiUiF8znR8yniSjz0NO+syyMmO/mzKjpodlX6uO166M29RM6FadQh67vy0VWvaEgPC48+KuvE2aQFrVkL2xs2CaSmvDS/b7bRlG4Kb/4y/+Ry+clk0cnvnPbD8F8I3noPpk6Lnvfpk8bpV69ANCwI8CKJGSTtSs3YUwNu0h8ljYfrkkj1SNzd3Jn7bJfgBvaH7wTB2NNSsHXXrTU6JRnRLfyz8Y4cPwlK3vjZXqi+rVQcbeDwMPB5fvhQf90XUSGnpIvyzd/HP3oXGzaJpv30HYI233bxGpLwpnIqIiEi586yNhA//FbI2ktu4CcGxp2/zuWHWBvydF0vCWWYTmDcr+rx5K8J3Xob0dEjLwNIzIC2jcHpwRvH9pKVhQRK+aVM0Ytm2I9SsFXX+7XQgzJiy7WKLtrApcuzp+NQJ+NcjIaUGwbV3YRk1o4YyHbpETYgyakVBu3BUNhx6N8FxZ0LXnthpF0K9hlijJoSfvVc8Alzs8KMJLri2ZArl4UdHx1gwB583G15/BmrUiPZYLVp3m58HE7+J/hR9jXdwDezgfqBwKtthjZpiJ56Nn/AbWDgXHzMKH/8FLPsFf+cl/J2XolHUPgOx3odjderFXbJUcQqnIiIiUu4soybBxb8lHHoPG579F5ZWi6D34Vt9rr8wtOzWLyt+Lfl81g/4rB9Knru9k6amR8/YfO1o0evT0qNAmVFr+1NtP3gdL9yj1C64FsKQ8KM3ILMpXtiwyS6+Hv/wDZg/GzCYNY1w1jQ4eADB5bdgQRA9b+Y0fNK30OMQ7NjToy1faqRusbbPp02ElctIGng83u8YLCkJz8mC1PRodOuj1+Gbz8t2Dsawcy6PGjvl50XTmPNL/VEwlZ1kZrDPftg+++G/uRR+/D4KqhPHwLxZ+LxZ+KvDoEtPrM+AaAsj/f2SCqBwKiIiIhXCDjoMO+sy/D9P4cOH4PUbYO06b/nECV9t/QDtu2AH9ILsbMjJgpzsKLBlR58Xfyx8jE3ZWz9O0TrW3MKR2VPOg5ef2HbhSxZEH5OS8M/fw1f8ChvXlzyeUgNatysMplAmMo8bTThudBSE02tG05dbtolq/OhNwrR0WPlr9N4yakajvvt1hAVzsOPOjL5uSUnRx7SM6GPjZnDRb/HTLsJffzpamwtQuw7WuBl2QO9tvxeRXWRBEnTugXXugV+wCZ8yNtq+6IeJMHVCNKsgNS3q9NtnYNR0qfDvrMieUjgVERGR3eI52bBgDgRJWPuthE7AjjmNtA1ryf7wDcJH/kbw+39gTUrWsBW89DiEW+lsGwTYTf9DsJOjMx6G0YhpdlYUUrOzouZE47+Crz6JnlTUGGmrwbSwc2+RpOQo1C6Ys+VTa9XBUlPxopHYRk1h1YpoX9OCgqiOovW1pWssfePHqSW362fC6hXYIUdAg0bbfI9Wuy526U34YUcTvvBvWLwgmjp9QG848mR4dVi0rjY1jaR7h5ec99cl+Kj3sd9cFgUPkZ1kqanYwf3h4P74+rX4hK+ioPrTj9HI6phRUKde1Eip78Bo6rsaKckeUDgVERGRHfKwAH5ZhM+dGU3zmzsTlvwcbZnSpQdJN/9lq68zM2pfcTPZixfC1AmE//xzFFBr18VXLYfP39v6CffrtNPBFIim0aZnRH9KCdp3JZz6XbRX6NbUrB2F2W694ftxUbgMgpIgG72Jkj1Ra6RCi30gLxe77g/RL+k52VEDp9UrYMWv2DGnYYNOiUZ8szdCThb+zWfRGtYwhFp1oFtvLD0dX/ATNGwMi+bB2tXbDacQNY4iCLDe/eCwQfiIF+D78dH2IEU1JyVR8NNMgpRkfN5s/MWhEIb41AnQrjPBuVeq86/sMqtdFzviRDjiRHzZL/jY0VFQ/XUx/uk7+KfvQNMW0bTfPgOxRk3jLlkSkMKpiIiIbJev+JXwLzduMRJIUhK0bIe13m+7r7ekZIKr7iD8xx9g4U+Ej/4Nu/kv+BP3l4S+zdWosfX7d5GlpMBJ58BLj0XBsH1nmD09evC0i7CjT8U8hOQUwmvPiO4vGslNToEBx8PPc6PwGYbRnxmTCe+6YtsnXfErllErWttKFDb91yXw5ccw8ASs12HRWtrvx8PSRdjtf8OSkrYYcQpHfQDpGdGodH4e1rg54dC7YfK4KIje9Q9o1ioKtkVTl81gwzq4+w62GI/+dQn8ugTfZ78oZIjsJmvcDDv5XPykc2D+HHzsKHzcF7B0Mf7Wi/hbL8J+HaOQ2utwrHaduEuWBKFwKiIiItvXIDOak9qgEdamQ7TvZtsO0Hq/aP/EzXhOFiSlRMGwkKWlE9zw34R/vz0abbznTlg0f9vn/GESvmAOtk+7PS4/GHAc4efvR2tJZ08HLJqCO38WjHgOb9QsGuVJqRHtd1okPw8+fXvrB63bADIbY5lNou7CmU1KPq+fWeapvm5NtMVMl54w4St81PuliguwX5dgLVpvcQr/5C1okIn/52lITsYuvQkmflvyhLvv2LKuorBvATRuFr3PhXPLPmfZL9v+YonsAjODNu2xNu3x3wyGGZOj6b6TxkTf5z/9iL/yBHQ9KBpRPfDgrf6bIVJE4VRERES2y4IkgnuexGrW2uFzPQwJnxwCa1cTXHMnVmqaqtVrQHDj/xD+/Y7tB9NC4dsvkXTDf+MFBVFDoayNxWtJyc7CszdCdja+bg0sXgC5OVjNOtH9RY2Tiv6U6c5b2NF38tjidZ9bjN8GSZBRE+rWh8ymWItW0Lod1rw1NGy03V+wvaAAnzMDn/Zd1IV34U9lR4gbNsa6HYR1PYiwcTOsWautfB0LoPdhsCkXFs+HNSvxf/4ZWu4Ly3+BTaVCdHoGdDwgamAzf3a0D2p+HqxbHY0ar1mFdegK3XphXXtudzsQdwf34m7DIjvLkpKiENr1IDwnG588Fh87KtrDd8o4fMo4PC0d63ko1mcAdOymNdCyBYVTERER2aGdCaZA9Ivo5LGQkkK4cB6WUYuCVcvxXxZD9kZ8/bpo3ebm271szffjKbj2zM22T9m+He39SY0aULNOdMxTzo/2El21PNq+ZvYPJVN6w4JoeuyGdbB4AT5lbHT8OvWgUVOsUbOoEVLj6HNPTYuaJ02biE+fXDYMJ6fA/l2xrgdhXXtCkxbFU3i3+av5D5PhvdfK3peXG4X69Az4w30waUw0VXjDOmyfdgQDjweOx088m/Clx2HqBHjtKWjVJpq+3Hb/bX/dVq/Ev43WxQZnXgI9D93RV1JkmywtPWqQ1Hcgvm41Pv6rqHnS/Nn4N5/i33wKdRtgBxc2UmrVVo2UBABz39Zij3gsWbIk7hL2uszMTFasWBF3GbKLdN0Sl65d4tK123vKjFbmFDb2yc7Ci0cjy45OetF92dnRKKZvpQPv7jKLtlxJL/2nZtTUJ70mvvwX+HUxtNgXDjqMoGZNwlnTowZHy36JRi1T07YdiM2gRhrFI6oHHEww4Fh8+VJYvhRf9gssXxoF2J0Nyhk1o1+4Ox2IdzwAC0OsXaed/gXcV/xKePfvoq9vQUG0prReJqxZARm1SPrni9Hz8nIJPxoBG9cRdDqweFsZd4fJYwlffjzqJGyG9TsGO+NirGZtfMFP+C8/w4pf8Z9+hB8mFV8z6zuQ4PJbAX3PJarKet186eLCRkqjou+pIs1aFTZSGhBNj6/GKuu1K0/Nmzff5mMKp5VAdfhLWBXpuiUuXbvEpWu3Y+4e7eeZXXoK7FaCZWEnWS81TZbSj5dee1leSne93dr9SUlRECuSnBI1Avrd3QTb2KpmW8KP3sT/81S09rJF62ia7sKfotBYu24UQvPzo495uWXOR/c+JF3/X1sc08MQ1qwsG1iXL8UXzoVlO/H7S8PGUTfTwlFXa9wUGjWLpg2nbn2asC+ah0/8Fv/wjZI6AZq3xnoegvXoi8+fgz/3KHbIkQSDby77+k05+Huv4B+PiL62tepgZ10a7ZU6+4foSe27wNyZ0P1ggsOOhi7di6db7sr3XLhyOUHD7Xcblr2jsv9b6e4wd2bUSGn8l7Ch1D7C7TsXNlI6DKtZO74iY1LZr115UDit5KrDX8KqSNctcenaJa6qfu2KRyuzy/4pu4ZyK8Eyq2gkMzu6XTrg7a7i0cpodJL0DEjLwApHLbe4PyOj8Pk1i0c3PTUVWziPtFnfk/X1ZztuxNPjEJj0LcV7jrbcN5rG2ulAkm796y6V7yuXw8plsM9+WGoavmAO4f/dCi32IenPD5d9buHepOF9f4Cf5+3y+Tw/Pxp1zN0Ey5ZGI7nLl8LyX6IpvqtX7vggdRsUTheOpgpT1KSpUTOoVRtyN+GTvsWfHLLla9Mzor8bhxxBcNnNWx2d9SULCV98DGZOje6onwnNWmKt2kL7Lljb/bfaUXWXwmnh/q5B3fo79XypOIn0b6Xn58P0SVEjpSljo/9cg2iv4W69CPoOgAN6Yynl08G7skuka7e7thdOteZURERkD5UZrdwsRBYHy6ys4pFMLxrVLP0nJ2vn1mHujOSU4qmvxdNgi4JlRk1ISy/zWHHgLJo6m5EBNdJ2qymOr18HNWtiQRIG0K4Ttfv2I3vxomi0sX4mrFm19Wm/RXtvphauSV29MqppxhR85jRs/647XYc1bASlR/EaNo4+rlyGu5cJcJZU2PyoaJRmF0eNLbnw16mUGtCmNtamffFjvmkTvnYlFITRljXLC8PrspKPrFwW7cO6dhU+Z3rJa4s+Sc+I1rcWvYcgwE67CF88H2Z8HzU+Apj23bZrbN6a4Lb/i6ZUvjY82pN17Spovg+2fxcsLWOrr/MwxFcuw4rOvR1Balo0fVpkF1hychQ+D+iN52ThE8dE+6fOmAKTxxBOHhNN4z+osJFSh65q2FWFKZyKiEi15mFB8Uhk6RDppabDlg6QJWsrNwuW5TZamV4SLAtDpG221rIoRFrp+4pGMtMyymzhsjeF77yMf/Afgitvhx59i+/P/vJjfNzoqBHSCb+BF/699QN8+1n0sSgcblwP/Y+DLz4kfPsFgtv/X3GoDDflYDVSd76JSs3akJoejS5nbSgJoqUVBauikZtyYKmp+Edv4l98hDfIxNp1iaYtDjgOa9YKC4Lo7+CqFZsF12jkleVLo79jC+eWbAkThvgbz0SfJyVFgT8pCeo2wD99JxptbdwUGjePgndRLWZY34H4Ab3wES/gn7+Pj3wLn/AldvYV0TTKzb6eebN+IPz91dCyDcHZg7FOB5bb10Zkc5aWgR16JBx6JL5mFT7+yyioLpiDf/UJ/tUnUD8TO7g/1ncA1rJN3CVLOVM4FRGRhFQ8WpmTVWaqa5lgmbXltiPF01+LAma5j1buIFiml7o/bbNgmbp7o5WVRnoG5OUSfjyCpMJw6quWs37ofQDYOZfjoz7c+mvbdoga/kz8puy61G8/i6b3zfoB/34CdmBhw58PX4/2C22xL9ZyX2ixD9bxgGgq7FaYGWQ2jpo1rVi29XBaozCc5pVfOAWi+jNqwqoVUUgfNzoaFa1ZG9p1wtp3xtp1hvadCTYLf+4edQxe9ktxgyaWl/p87epoFBQKmxvNKB5xDe4eVjLaWlpKjahB0lEn4XNnwrxZ+OP34l8eSHD+NVjTFgCEY0ax7sP/RKF90TyNispeZfUaYEefCkefiv/yMz6msJHSymX4R2/gH70Rfd/3HRiF1QZa71wVKJyKiMheVzxauVmw9M2b8hQHy+jjyrxNFKxfVzJ1trxHK9NKQqSVmg5bOlha6amypUYy4xqtrEzs8EH42y/BnOn4vFmwTzvC4Q9GI5UH9MYPOgye+9fWXzx3FmQsjj5PToFOB0ZboZQKiv7I/1Ew8HiSLrgmmhq8YT3MnIoXraO86Dqs0XHbLrBhYThd+Svss1+Zh/zXJZBWGL52oiOvL1lI+PaLJF1z1w6fG5x/NX7ulbBkAT57OsyeHn1cs7Jk/0eItrlpsz/WvgvWvjO03T/qSFy7LtSui+3Xccs6NuWUNGYqHGn1ZUuj7XHqN9x6QZtysA5dsIMOi6btfvUx/vqzMGMK4V9uwI49A446BX/7RQqWL4XDBhH07gf7tt/68UQqmDVrhZ1+IX7aBfDTjGh96oSvo22eXn8Gf+PZaLpvnwHR9N+Mndz6SiodhVMREdlp7h6Fha2EyC2DZTZkbd4NtjCIbsrerfPnb35HcnKZpjwlwbLsmsqSrUe23I4k4UcrKxFLy8D6HxuNanw8Atp0gJlTowY5l9xA+Obz2z9A1sboY35e1AipyHFnwscjor1H168FILj4t3DyefiCOfjksbBxPdZm2/t4AljDxjjgK5ZRevJq+Npw/JO3S6Yi70w4nT4ZY+f3ZbQggJZtommIR5wYfS+t+DUKqXOm47N/gKWLi8O2AwQBtN4Pa9c5CqvtO2O165Y9bmpa1Diq5b47XY3VqgMHHVZcl/U/Du9xCP760/jXn+LvvQpjRmGDTol+6f96JN6hC4G+TyRmZgbtopkGfu6V0b7CY0bhU8aVfO+8+Bgc0JugzwDo1kv/cZhgFE5FRKoJDwsKp7OWDZG++drJzbcd2TxYFmwREXdPmUBZtIZyy2Y9pe+v17wFazblFk+H1S8dlY8deVK0jvG7rws770Kd6//A+jr1sN79oml5OdlR8ArDaKsXD+HWv8Cn78GUcdGBVpfqVjn+SzigF0weC8t+IdywHqZNwL/7BqZPgtxc7ORzsVbbXn/my5fiRQ2SVi0v+2BqWlTDDxOj2zsRTu2QI6F7n539smz5erOS7ryHHhnVuG5NYVAtHFn9eS7Mn43Pn42PfCt6YdOWhUG1cHS1YeOdX3e7vXpq18UuvQk//GjC5/8djUi9MozkNu3Jnzcbf/7feKu2Zb7GPmcG/utigsMG7fH5RXaVJadA9z5Y9z541saom/WYUVFH6onfEE78BjJqYr0Ojxopteus/4hMAAqnIiKVXPFoZVGznpzSwbLU2smi+7M2Fq653OzPbo5WbqFotHJ7HV8zMko17dly2xHS0nfrl4SUzEysirfYT3TWIBO69YbJY6CgAOt/LKm9D2P9ihWwX4eSZkdhYbdeDyGjJkHH7linHhTceXkUHhs3K9l6ZuWy6A/Az3PxWy4oe9KmLaHeNqawFgkCbMP6wpHTX8vWfOI5+IzvoahTbv6Op4tbzVpQs3ynDlqdetDzUKznoQDR9/HcmSVhde5MWLoIX7oIvvw4Gl2tn1kyqtq+CxQ2WdrtGtp1JvjvB/HP3sXfepH8ebOj/0jIyyX8998J/jgEy6gZ/WdXXq6CqVQKllETO2wQHDYIX70SH/dFFFQXzYuakX39KcF9T0OtLbdLkspF4VREpAKVjFaWDZGetVlTnjL7WW55f7mNVhYFyrT0qEFLekapqa5lQ2Tx/Rk1y4xwVpe95mQPLF5Q8vlJ55Z8/vFbJaEUol8UN6yLAlXR6F+t2rBqOXbFbfhPP8Irw7Z9nozakLUeaqRihxyx3ZKsYWPodRj+4eslQbfosaQkgituI/zva6P/CNpGQyR3hzAs0wG3IllaBnTugXXuEZ0/Pw8W/ITP/gGfMwNmT4fVK/BxX8C4L6KwmlEL2nUi6HcMtpsju5aUhB19Kt7rcFLeep5NX38aPbB8KeE9d2LX3EnQrFW0LlikkrH6DbFjT4djT8cXL4hma2RnRdPZpdJTOBUR2QbPy92iC2zJdNfS+1luFiyzSo1k5pTTaGVS8mYdXzO2Hyy3su3I7o5WiuyKcPqkaAuUIuO+gPbRWlAf9X7ZJ3ftGa1tLOwO6/n5xZ16/eG/Fq8vBaKtUlJSo++rYh6NXi78CX9lGHbhddsvbnt7nTZsBEeeBB+9AQX5+M/zyk5hzc/Dn/tXVN9lN5XLVNpdZckpsF/H4sZIHobwy8/RetWi0dXVK+D78XjnHruwInYb56vfkHq3/5XlB/cnfOZRWLUMfl2MP/cofutfo3q2o+BP10Pd+gTX3BWNNIvsZdZiH+yMS+IuQ3aBwqmIVDkehiVrK7eyhnJjAOGKFZttO1J6XWXh6/LLcbSyzCjkdjq+bmvbEY1WSgLwjRvwYQ9EN1JSIW8T/uk7+DmXEYZh9J8sRdIzsJq1o2m2+fmET9yPT5tQ0hRp/VqoWz8aCfzl52gvzzUr4bBB8PXIaKpp1oaSc4/+kIKatQlOu3DbwbFor9PC6e+bT8u1br2i7SmA8PF/EPzxgajhEMCvv+ATvoLcTXjDxgT7toum1LZuWx5fut1iQRBtpdFiHxh4QjSyu3IZPnt6NNW3vM7TuQfB//2b8MWh0fq9pi3KXsut8KyN0TZNC36K/t0TEdkJCqciUql46U6wOVnFo5C+eVOezYNl6WmyOxit3LDdR0spM1pZsnfl1oNlOpZRumts0edpWLB3pgCKxM1fHFoy2tl3QDTtdOkicr75jKBzT8I/P4L/9jfR4207RmvCAMaOLt6bk4ya0ffzcWcSnH4RTP2O8JG/RkEnPx+mTYS6DSApiNaKThoD076LXvv+a4RjRmFHnIAdeiRWp36Z+srsdbry1y3XjNYqdXvpomg09uLfRq9t0Rq7/FZ86N3w7suE515F0oEHl9vXrjxE768Jltmk/I+dkkLSJTfs/PMzapJ0z5N4dlYso8wikpgUTkWkXBSPVm4WIr309NeskpHMrW47kr2x/EYrU9M3C5AZxaEyvUFDst22vu1IUTOf9JqQnKJfqqTK8YKCqOHQujVb3Tdzd4VjR0drH83AnaDHIfi+7fHnHiXrrZcI6zTEn3245AVFnXEB9mmH9e4Xdd388iP8ozejBidBgHfsFu17un5t1PTnkCOxth2hSbNoWmn/YwlX/BpNA16yEFYtj/Y9fPN52G9/7PBjCAq74QIle52uWAaty+51Sq1S27Qkp+BffkzYYl+Co06KuoGOeh8GHg+fvw//eQrft125fg2rIkvPiLsEEUkgCqcigufllV1DWTgK6Zs35ckptbZy8/tzsovXiu2RpKSy6yq31/E1PSMardx878q09O2OVtbOzGSTOr5KNeMbNxD+/Q5Y8WvUYCs1HbofTHDxb7EaqVs+3x1/81n8+wkEv/v7dje195XL8ReGFr0w2pqlYzeYPxtSapA/dyb8pdSoWxBAl54wdQIQTae1I0/CUlLwovNsjOY4WGoadtI5UTfenn0J0stOEfVNm2DE89Hjq5YXzpywaE/U2dNxrHirFii11+nKZVuuyaxZ6tgHHQZjR+Ejnse7H4x//SnMmBJ1zO3WC6ZOIHz0bwS//0e0HUwVEf70I/7lxyRdemPcpYhINaRwKpLAPAyjqW5bneq6WYAsve3I5t1gd2JPv52ytdHKtJJ1ltvcdiS91NYjKTU0WilSETJqwurlUTCt1xAaNYm2HfrgdezU87d4upkRzp4R7Xf5w2Ss9+FbPayHIeFTD0b/pnQ8AGrVwVJqYCk1CD98o6TzbdF+pgB3DyNYu5qwMJz6uy/jE74kuPC6aI0p4D9MxNu0hx6HEJx49jbfls/9ER87evN7ISUF6tSDTt3KPpRZ0hRpc0FyDYo3kTntwug9fT+e8In7sFv/D1uxFP/28yiktmwDi+YRPvxXgrvujf6jLMGF47/CH783+rxPf4JO3bf+vJwsWDAXFs/Hf1kEy5dG64HXr4N2nUi69q69WLWIVCUKpyIx8by8Ms16ynaC3bIbbHGH2NL7WVbEaGXaDjq+lg6WZUYytz9aKSLxMjOCPz0E9RpiqdFIqefnbfffkODU86Npuvt12uZzfORb0ab3tesSXHl7tFcnhduubFgLhxwJ478ombK/f1eS6mcSzpwa3e7QFdatgaWLCO/7r+g2wKL5hE8OIbi7M2y2drTM++p4AN6qbTRVt05d2LC+8D/cjOD6P5bpuAtgDZtsda/TLY5bkIdddhPhX26Cn36ED17DLr0JUtPwUR9EU4jrNYRffiZ87B6CG/6EJSf4r1UHHRpNoc6ohU8ZR8Hkcaxes5KCZUth/Zro505e7vZ/7syfvdfKFZGqJ8H/FRXZ+4pGKwtWLMMXLyoOkV5qnSWlthTx0mGywkYry0533WbH182b9RT90WilSLVgTZqXvb2DrUCs4wHbfdwXzcPfeBaA4JIbi4MpFIbhO+/FgoAgawN5U8ZF959/bfSEXxZFtzt0wU44G//oDfy9V2HWtGjabxhiA47foqnRFjWakfSnB/EVv+JJSVhBAf7eq/hXnxAOvZvgj0PKrnvczshpdMDCEd6NG7AmLQiuuJXw/j/i772GdTwQO/+aKKB+9CasXRX9h970yfhLj8OF1xaPDifKf9YVPPo3mDcr+pmVuykKnutWw6fvArD1HV+Jvk41akQj8rXrRZ2LGzeF9l33VukiUgUpnEq14vl5W0x1JScLzyq9prIkYG4ZLAsb/rizxysWi0Yry+xTWSpYpm0jWBY160nLgHSNVopIxCePwbr33Xvny8slfOJ+KIgmwvrq5Vus4SzaV7dgycKie7DadaLnL43CKU1bYikp2Enn4L37EQ67D+bPif7T7Pgzdroey2xScv7zrsLnz45GX595iODqO0v+A247e50CEBgUULLmdf9u2PG/wd9/lfDJBwj+9CB25qWQloG/9UJxd3D/4kP8iw+j15x1GXbs6Ttde1zCxQthyviS6dZFzKBGKqRnkFw/k/zadaFRM6x5K2i5L7RsQ1BD21uJSPlTOJWE4GEIuTmlur1utoaydIjM2rjZvpWlusHmbfP/gHdNahpBzVqENdLKjE7aVjq+2ubNeoqCZQ2NVopI+QlfGU5Qqw7Wrvz2t9wef/O5aGorQO26WM9Dt17Xz/Pw5UuLXoWP+gA7+dySkdNmLYufa02aF0/htSNO2OGo6bZYjVSCa+4i/L9b4Ltv8M/ew446KXpwB3udEiRFgbvUHqp28rn4zO/hpx8Jn3mE4LrfE5x0DmFqGv7qk1t50+GW91VGP80oCaZnXIy17wKt2hAU7e0KNMzMZIUayInIXqJwKhUuGq3cPERuFixLN+3ZvFlP0WvKY21lEGw5pTW9JrZZs56S+zdr1lO0n2VSEpn6gS0ilUnDRvhXI/dKOPUZU/BP3iq+HVxadkpvmecWdfGtWQs2bsA/f49w0CmwbEl0f5MonLo74X+egu/HR/95t4cjj9akOcElNxA+di/+2nC8bQesTYcd73WalAR5RMG16FjJyQRX3Eb4vzfB5DH46A+wgScQHH1qFFCf/1fJz6iUGljn7ntU+94S9D+WgsULsEGnEFShjsMikrgUTmWb3B02ZZcNlqUb82w2Ouml1lmWGcksx9HKLbYMKdpiZLMQufVtR2pqtFJEqiw75EisXoMKP49v3EA4/MGS8w48Hjug91afG65bE43OAZx6IXz1MSycC5++E41ONmxc3JyJhT/BxyOiz3direnOsF6HY7On45+9S/jYvQT/PQSrWXv7e50mFS6VyN5Y9liZTbCLrscf/wf+ypN4u85Yy30J+h8bBdThQ6IR07xcwof/l+AP92MNMvf4PVS0pPOuirsEEZFiCqeyVQX//jtMGrvlOpTdUXq0Mq10gNxax9eMkqmxZabBRqOVIiKydcFhR+2V8/gL/462DQFo0hw7a3B0fxhGjYG++RS76HosPQN/8TEALC0dG3g8np6BP/lA8dpMSk3pDd97rfCNJBEcd2a51WtnXYbPnQnzZxMOf5Dg+v/a/l6nSYW/GmVnbXGsoHc/wumTo2ZLT9wXBdDUVII+A/DUVMLH7o26Eq9dHQXUO++JZuaIiMhOUTiVrTILcA8LGyJsHhYL967cLFhufdsRjVaKiFQV4djR+PgvoxtBQHDFbZC1gfCTEfhXn5R0wO3QFT/sKJg0BoD0Y09nkxn0Ohx//RlYHYVbaxqF03DtKpgcPZdDjtjmFOHdYSkpBFf/jvCvt8D346Muu9vr2FvYwdgLGx1tcbxzr8TnTIclC/HXnsQuvC66v3tfghv+m/CRv0UzhhbNJ3z8XoLf/lGN60REdpLCqWyVXXYzduXtGq0UEREAfOVy/Pl/l9xxcH/Cd1+B7yeUzLJp2BjrdwzW/WB8xPMQFkCQRM3zr2TTuvVYcjJ21ElRQAVo1hLfuB6/74/Rmk0LCM68tNxrt8wmBINvIXzkr/iI57CTzo3e09b2Oi3aXmfTNsJpahrBlXcQ/v12fPSHeOfuxc2grHMPgpv/QvjQX2BTDkz9jvDlYSSdf3W5vycRkaooiLsAqZwsNVXBVEQkQXheHgX/73bCF4ZG02vL+/hhSDh8SNRLAKKpr2NGwZRx0dYrBx1KcPNfCP7f4wQnng11G+CjC6fu9uxLUCO1+FjW/9hoqxLAc3MJ7/8jFG0r0//Y4q1mypsd2Bs77kwIQ/yzaA9PVi7f8okpReE0Z9vHat0WO+syAMJnHsFXlRzHOnQhuP1v0f6nADOnbnMUVkREylI4FRERSXSL5sG8WfjMqcV7i5YXz88nfPohmDWt5M6CfGjcDDvzEoJ7h5N0zV1Ylx7F5/ZRHxSHOztvs1HD9JpRLwKAt16En+dFn9dIJTjtgnKtfXN22oXQvjNsWBfdsbWR06IgvYNAaUeeBN16RdOah92PhwUlj+3bnuCue6FOvagr8aJ55fQORESqtnKb1huGIXfddRcNGjTgrrvuYtmyZTz44IOsX7+etm3bcsMNN5CcrFnEIiIi5c3nzgLA2nQov2MuX0o4+sOow+7Gkj0/adOB4IyLoUPXbQZhf++V6JN2nQg2Xz+6ZlXUqReikdiUGpCXiw06BatVMaOmRSwpieCqOwj/92ZYvxYOPRJ3L9sXoSic5m7a/rHMCC67ifAvN8Ls6fh7r0X7txY93mIfgt/dDcuW7LW9Z0VEEl25/ffq+++/T4sWLYpvP//885x44ok8/PDD1KxZk88++6y8TiUiIiKlzZ0ZfWy7/x4dxvPz8O++pmDInwj/cBV89EbZYHpAL4Lf/wPreMA2g2n4w0RYuxoAu+CaLc8xe3rZO/Jyo47sR5+6R7XvLKvXMGrkZAafvwfTJ5d9QnE43fE2aFa7LsHlt4IZ/s7LW7w3a9Ic69arnCrffeG3nxN++zmetWHHTxYRiVG5hNOVK1cyceJEjjoqamPv7vzwww/07dsXgIEDBzJ+/PjyOJWIiIhsxudF4XR3R0791yWE/3ma8HeDCYfeEwW25BQo3WW2Vh2CS2/eYfd1f/XJ6JMmzQlatin72Mrl+EtDoxult1gZcFyFj5qWZp27YyefB+7RlNxVK0oeTE2LPu7kHt3W6UDsuDPAQ8Jh9+EbK18A9BHPR/uwVsLaRERKK5d5tk8//TQXXngh2dnR+oz169eTkZFBUmFDnQYNGrBq1aqtvnbkyJGMHDkSgLvvvpvMzMq/YXV5S05OrpbvO9HpuiUuXbvEpWu3pXDdGpYvXwqpaWQe2BNL2rkf7Z6Xy6Yxo8n6+C3ypk0svj+5dVvSjz6FgvVryXr1qeL76936Z1LbtN3uMfMXzWflkp8BqHv5zaQVXqvk5GTqh3mseuCPsGE9AGmHDyJn5DsA1GrUhJp7+br6xdeyZsFscqeMJ+mpB6n/10ew5GTW1qtHDhCE4U7/XfPBN7FqzgzyZ08n5ZXHqXvH3yrNFmruzrJ1awDIbNsOKwrfO0nfc4lJ1y1xVfdrt8fh9LvvvqNu3bq0bduWH374YZdfP2jQIAYNGlR8e8WKFdt5dtWUmZlZLd93otN1S1y6dolL125L/n3hzKR99mPl6jU7fv6alfjHI/BvPysOitSogfXuh/U7lrDt/mzM2kh4+yUlL2rTnvWt2rF+B1/7gkf+Hn1Suy4b2nRkQ+Hz6+XlsPKP18GqFdGIaU42OTNLGixt+PBNsvodu9f3A/VLboT/vZm8H79n+bAhBGddRoFHk8rCTTm79HfNL7sZ/vcmNn07iuVvvkDQ/7gKqnrX+IZ1kJ8H6RmsXL8B1u/a6Km+5xKTrlviqg7Xrnnz5tt8bI/D6cyZM5kwYQKTJk0iNzeX7Oxsnn76abKysigoKCApKYlVq1bRoEGDPT2ViIiIbMbn7WIzpLw8fOTb0b6irdpg/Y/FDh6AZdSMjudO+NSDUaApZOdcucPDhhvWF3f0tePPLKlv6SJWD/lTFEz36xh1yM3Jjrr0pmdARq3ovklj4KDDdvJdlw+rXTdqkHTfH/CP3sTbdcbSM3Ao8/536liNmmIXXocPux9/ZVh0rOatK6TuXVK4/pe69eOtQ0RkJ+zxmtPzzz+foUOH8uijj3LzzTfTtWtXbrzxRrp06cKYMWMAGDVqFL16xd8QQEREpKrxwmZItpPNkKxRU+zswQT/dT/Bfz9IMPCE4mAK4GNHR/uXFqlbf6eO7S8/HgXeGqlw1CnRfUsWEt73X4SrVkCHLtjVd0ZhqXDKqw06BTvmNADCj0fsVP3lzdp3xs64OKrhqQfxgvzogaKPuyDoMwA79CjIzSV8/B/4Tq5brVDF4VSDBCJS+VXYPqcXXHAB7777LjfccAMbNmzgyCOPrKhTiYiIVEsehjBvdnSjzc536g0GnYrt236LdZG+chn+/L/L3Ge9++1w/WSYnwcTvo5uHDaIIAjwRfMJ7/svWLuaGt0OIrjxf7DVhVPV3CG9ZhRODxsUjZ7OnYn/9ONOv4fyZMecDgceDFkbYezo6M6Cgu2/aFvHOu8qaNwcFi/AX3tqxy+oYF7UOVkjpyKSAMo1nHbp0oW77roLgCZNmvD3v/+dhx9+mFtvvZWUlJTyPJWIiIisWArZG6FeQ6x+wz06lIcFhE8OgU3ZZe637n13/OJ3XolGGoMAO+tSfOFcwvv/K9pLtHMP6v3XfVhqGr50Uclxjz4Vy6iFpaZhA6L1mbGNnpoRXHYzNGwMq5ZHd4bh7h0rLZ3gqtshKRn//D188tjyK3R3rC1sSKlwKiIJoMJGTkVERKRiWePmBA++QHDDH/f4WP7JWzC7VGPDI07CLr0J2nXa8Ws/fzf6pFsvbMlCwvsLu/J260Xw2//CUqO9Q72oK3BKCnbUySXv48gTISkZJo3Bly/d4/eyO6xmLYJr7oSi/Vt3Y1pv8bH2aVcyVfjph/DVK8ujxN2jab0ikkAUTkVERBKY1ayNtd5vj47hP8/D33iu1EEDgpPOJjjsKCxp+x10w68+geys6MZhgwgf+G/I2gDtOmNHnoSl1IjO4R7tnwpwYJ8y61ytXkPs4P7gYdSsKSa2b3s49rTohnuZkd5dPtagU6BrT9i4nvDJB/Bw96YJ7zE1RBKRBKJwKiIiUo15Xi7hE/dB6fDU8xCsTr2de/3bL0WfNG0Jw4dEQfWgQwlu+z+sWcuSJ/74PWyMtq6xQSdvcRw7+tToeF+PxDfu2nYn5WrgicWfhkPvwTdt2q3DWBAQXHYT1KkHM6fiH7xeTgXuYh0XXkfwl0ewbgfFcn4RkV2hcCoiIlKN+RvPwi8/RzdqpEaNivofs1OvDWdOg6ImRyuXQU42dnB/givvwJKTsYaNo3O4E771YvHrrFXbLY5lrdpApwNhUw7+xYd79qb2gNWsXXJj8QL8paG7f6w69QkG3wKAv/0iPmfGnpa36zVk1MSaty77vkREKimFUxERkWrKp08uO402NzdqsNS+6869/uXHS27k5WJ9j8Auv2WLqcC530+AnwqDWcPGWI3UrR4vKNxWxj97F9/FfUbLS5CaVnIjKRn/+lPCr0fu9vGsSw/s2NMhDAmH3Y9nxTgqLCJSySmcioiIVEO+cT3h8AdL7hhwPOCQUYtgJzrsh8t/gUXzi2/b4Udjl92IBWWDqbuz8eVhJXc0b73tg3bpGT2+ZhU+7sudeyMV6bQLAPAXhuKL5u32Yey0C2GfdlC4VY+7l1eFIiJVisKpiIhIFeJ5uRQM+dN2p5C6e7SfadE2Iy32wfoVTuWtU3fnzjP0nuLPbcBx2EXXbxFMAZg+mbwfp0ZThqHsOtTNmFnJ2tNP3oovxBXu62odD8QOOwrycgmH3ovnZO3e4ZJTCK68HVLT8fFf4kV7woqISBkKpyIiIlWIf/UJzJwGteps+zljR+ETvopuJCUTXHEbVhS8au84nBbM/B4Wzo1utN0fu+BaLNjyVwp3J3y7cK1pk+bRx6bbDqcA1mdg1ERo0byoiVIcrPC9bFyPnXcNtNgHfl2MP/vobgdma9Icu+Aa7KiTse4Hl2OxIiJVh8KpiIhIFWL9jyO4/W9Y0xZbfdxXLsNfKGnyY2dcjLXcF9avje6oXW/HJ/nm8+hjEMDv7sYKRxq38MNEmDuzsPNv4WjkdkZOASwlBTviRNi/W/Fo6163fzfYtz3UqYelpkb7nxaNeo76YLcPGxxyBMG5VxZvryMiImUlx12AiIiIlB9LSoJ2nbb5uGdnQ9HoX8cDov04AZKSoXlrrHGz7R4/LCiAcV9ENw4dRNI29kGNRk2jbWYyTj2fja8Ojx7YwcgpgJ3wG4KTztnh8ypK0q3/W+a2NW2JXfJb/PF/4K8Ow9u0j/ZEFRGRcqWRUxERkerkpxmwKQfSMwguu7l4Oq716EvSXx4hOPOS7b/+g/9Afh6YYWdfvu3nTZsI82ZB7bqk9ekXnbN2XWw7042LbG2KcNyC3v2wgSdAfn60/2mce7GKiFRRle9ffxEREakQvnQx/uqTAFEDowaZu36MT96KPuncgyA9fevPKbXW1I49g4LlS6MHdjClt7Kzsy8v7robPvWguu6KiJQzhVMREZFqwPPzCZ98AHI3YX0HEvTut8vHCMeOhsJ9Ou2Ca7f9xKkTYP7saKR04PEU/Dw/es1OTOmtzCwlheDq30FGTZgyDv94RNwliYhUKQqnIiIi1YC/90oUGBs0ws67eveO8eZz0Set2xI0arLtJ+7XETvpHOyU87HUNPIXL4zuT/CRUwBr1JTgspsB8DeewWdPj7cgEZEqROFURESkivOffsTfew3MCAbfgmXU3OVjhHNnwsplANi5V233uVazNsGpFxAMPB6A/EXzo/ubttrl81ZG1r0PdszpEIaEj9+LF3U6FhGRPaJwKiIiUoV5TlY0nddD7JjTsf277t6BpoyPPjZoRNC+8y69tGDxguiTKjByWsROvyjqirxmFeGw+/GwIO6SREQSnsKpiIhIFeYvD4PlS6FVG+zUC3b7OMHpF2J3D8OuuWvXzr9xA+GaVdGepfV3vQFTZWXJyQRX3gG16sD0ydHItIiI7BGFUxERkSrKJ36Lfz0SUmoQXHEblpKyR8cLGjYmaLOL+3umptHgnicIrrytUm4RsyesQSbBFbeBGf7OS/iMKXGXJCKS0KrWTwkREREBwNesInzuEQDszEuw5q1jqcOSk0np0AXr3jeW81c069IDO/EccCd84j58zcq4SxIRSVgKpyIiIlWMuxM+8xBsWA+de2BHnBh3SVWanXwOdDoQ1q8lfPwfeIHWn4qI7A6FUxERkSrGR70P0yZCzdoEl91Y5abTVjYWJBFccSvUbQCzp+Mjno+7JBGRhKSfViIiIlWI//Iz/tpTAAQXXY/VaxhzRdWD1alPcNXtEAT4h6/jRd2NRURkpymcioiIVBGen0c47H7Iy8UOPQo76NC4S6pWrENX7LSLAAiHD8FX/BpzRSIiiUXhVEREpIrwt1+ChXMhswl27pVxl1Mt2bGnwwG9IWsD4WP34vl5cZckIpIwFE5FRESqAJ/1A/7h62ABweW3YOkZcZdULVkQEAy+GRo0gvmzi6dYi4jIjimcioiIJDjP2kg4fAi4Y8efhbXrHHdJ1ZrVrE1wzZ2QlIx/9i4+4au4SxIRSQgKpyIiIgnOX34cVi6DfdphJ58bdzkCWJsO2G8GAxA+8zC+dHHMFYmIVH4KpyIiIgksHP8V/u3nUKMGwRW3YsnJcZckhezIE7GDDoOcbMLH7sFzN8VdkohIpaZwKiIikqB89Ur8+X8BYL8ZjDVtGXNFUpqZYZfcAI2bwaL5+MtPxF2SiEilpnAqIiKSgDwMCZ96ELI2QLde2IDj4y5JtsLSMwiuuQuSU/AvPyb85rO4SxIRqbQUTkVERBKQf/YOzJgCteoQXHIDZhZ3SbIN1qoNdv7VAPgL/8IXL4i5IhGRyknhVEREJMH44gX4688CEFzyW6xu/Zgrkh2xw4/GDjkCcnMJh96D52THXZKISKWjcCoiIpJAPC+PcNj9kJ+H9TsG69437pJkJ5gZdsG10Lw1LF2EP/cv3D3uskREKhWFUxERkQTiI56HRfOhcTPs7MvjLkd2gaWmRfufpqbh40bjoz+MuyQRkUpF4VRERCRB+I/f45+MgCAgGHwLlpYed0myi6xZK+yi6wHwV57AF/wUc0UiIpWHwqmIiEgC8I0bCIc/CO7Yiedg+3WMuyTZTUGfAdiA4yA/n3Do3XjWhrhLEhGpFBRORUREEoC/OBRWr4A2HbATz467HNlDds4V0Ho/WPEr4VMPaf2piAgKpyIiIpVeOHY0Pu4LSE0juPxWLCkp7pJkD1lKjWj9aXpNmDwG/+StuEsSEYmdwqmIiEgl5iuX4y8MBaLRNmvSPOaKpLxYo6YEl94IgL/xDD5nRswViYjES+FURESkkvKwgHD4EMjeCAcejB1+dNwlSTmznodgR58KBQWEj/8DX78u7pJERGKjcCoiIlJJ+SdvwaxpUKcewSU3YGZxlyQVwM64BPbrCKtXED55Px6GcZckIhILhVMREZFKyH+eh7/5PADBpTditevGXJFUFEtOJrjqDqhVG36YhH/wn7hLEhGJhcKpiIhIJeO5mwiH3Q8F+djA47FuveIuSSqYNWhEcPmtAPhbL+I/fh9zRSIie5/CqYiISCXjbzwLSxZC0xbYWYPjLkf2Eut6EHbC2eAh4RP34WtWxV2SiMhepXAqIiJSifj0Sfin70BSUrRtTGpq3CXJXmSnngf7d4N1a6KAWlAQd0kiInuNwqmIiEgl4RvXEz71TwDs5POwfdvHXJHsbRYkEVx5O9StD7Om4W+/GHdJIiJ7jcKpiIhIJeDuhM89CmtWQbtO2PFnxl2SxMTq1o8CqgX4+6/hUyfEXZKIyF6hcCoiIlIJ+Lefw3ffQGo6weBbsCAp7pIkRrZ/N+zU8wEInxyCr1wec0UiIhVP4VRERCRmvnwp/tJjANh5V2GNmsZckVQGdvxZ0PUg2Lie8LF78Py8uEsSEalQCqciIiIx8rCAcPiDkJMNPQ/FDj0y7pKkkrAgILj8FmiQCfNm4a8/E3dJIiIVSuFUREQkRv7hGzBnOtRtQHDRdZhZ3CVJJWK16hBc9TtISsJHvo1P/CbukkREKozCqYiISEx8wZzibqzBpTditerEXJFURrZfR+ysSwEIn34IX7Yk3oJERCqIwqmIiEgMfNMmwmEPQEEBdtTJWNeecZcklZgddQr0PASyswiH3oPn5cZdkohIuVM4FRERiYG//hQsXQTNWmFnXBx3OVLJmRnBJTdCo6bw8zz85SfiLklEpNwpnIqIiOxlPvU7/PP3ISmZ4IpbsRqpcZckCcAyahJccyckp+BffEQ45vO4SxIRKVcKpyIiInuRr19L+MxDANhpF2Ct94u5Ikkk1no/7LwrAfDn/oUvWRhzRSIi5UfhVEREZC9xd8JnH4W1q6FDF+yY0+IuSRKQ9TsW6zMAcjdF60835cRdkohIuVA4FRER2Uv8q09g8hhIzyAYfAsWJMVdkiQgM8MuvA6atYJffsaf/xfuHndZIiJ7TOFURERkL/Blv+CvDAPAzr8Ga9g45ookkVlaerT+tEYqPmYU/uXHcZckIrLHFE5FREQqmBcUED75AGzKwXr3i6Zkiuwha94au+g6APylx/GFP8VckYjInlE4FRERqWD+/mswdybUz8QuuBYzi7skqSKCvkdg/Y6B/Lxo/WnWxrhLEhHZbQqnIiIiFcjnzcLffRmA4LKbsJq1Yq5Iqho790po1QaWLyV85mGtPxWRhKVwKiIiUkE8J5tw2P0QhtjRp2KdDoy7JKmCrEZqtP40LR0mfoN/+k7cJYmI7BaFUxERkQrirw2HZb9Ai32w0y+Kuxypwqxxc4JLbwLA//MU/tOPMVckIrLrFE5FREQqgE8Zh3/xESQnE1xxG5ZSI+6SpIqzgw7FjjoZCgoIH78X37Au7pJERHaJwqmIiEg583WrCZ95GAA7/WKs5b7xFiTVhp11KbTpAKtWEA5/EA/DuEsSEdlpCqciIiLlyN0Jn34Y1q+Fjgdgg06JuySpRiw5heDqO6FmbZg6Af/w9bhLEhHZaQqnIiIi5ci/+AimToCMmgSX3YwF+lEre5c1bEQw+GYAfMQL+Mxp8RYkIrKT9BNTRESknPjSRfirwwCwC6/DGmTGXJFUV3ZAb+z4s8BDwif+ga9dHXdJIiI7pHAqIiJSDjw/n3DYA5Cbi/UdSNC7X9wlSTVnp14AHbrC2tWET9yHhwVxlyQisl0KpyIiIuXA33sFFsyBBo2w866OuxwRLCmJ4MrboXZdmDkVf/uluEsSEdkuhVMREZE95HNm4O+9BmYEl9+CZdSMuyQRAKxegyigmuHvvYpP+y7ukkREtknhVEREZA94Thbh8CHgIXbsGViHrnGXJFKGdToQO+U8AMInH8BXLY+5IhGRrVM4FRER2QP+8jBYvhRatcFOPT/uckS2yk44G7r0gA3rCR//B56fH3dJIiJbUDgVERHZTT7xG/zrkZBSg+CK27DklLhLEtkqCwKCy2+Feg3hpx/xN5+NuyQRkS0onIqIiOwGX7OK8LlHAbAzL8Wat465IpHts9p1Ca7+HSQl4R+PwCeNibskEZEyFE5FRER2kbsTPv1P2LAeuvTAjjgh7pJEdoq164SdcTEA4VP/xJcvjbkiEZESCqciIiK7yD9/D36YBDVrE1x6Ixbox6kkDjv6NOjeB7I3Eg69B8/LjbskERFA4VRERGSX+C8/4/95GoDg4uuxeg3jLUhkF5kZwWU3QWYTWPgT/uqTcZckIgIonIqIiOw0z88jHHY/5OVihx6F9Tw07pJEdotl1CK45k5ITsZHfUA4dnTcJYmIkLynB1ixYgWPPvooa9aswcwYNGgQJ5xwAhs2bGDIkCEsX76cRo0accstt1CrVq3yqFlERCQW/vaLsHAuZDbBzr0y7nJE9ojt0w475wr8haH4c4/irffDmrWMuywRqcb2eOQ0KSmJiy66iCFDhvC3v/2Njz76iEWLFjFixAi6devGQw89RLdu3RgxYkQ5lCsiIhIPn/UD/uEbYAHB5bdg6RlxlySyx2zA8djB/WFTDuHQu/FNOXGXJCLV2B6H0/r169O2bVsA0tPTadGiBatWrWL8+PEMGDAAgAEDBjB+/Pg9PZWIiEgsPGsj4fAh4I4dfxbWrnPcJYmUCzPDLroOmraAJQvxF/6Nu8ddlohUU3s8rbe0ZcuWMW/ePNq1a8fatWupX78+APXq1WPt2rVbfc3IkSMZOXIkAHfffTeZmZnlWVJCSE5OrpbvO9HpuiUuXbvEFde1W/vPf5GzchnJ7TrS4LLfYsnl+uOzytP3XOWXf9fdrPzdFfi3n1O75yGkDzoJ0LVLVLpuiau6X7ty++mak5PD/fffz6WXXkpGRtmpTmaGmW31dYMGDWLQoEHFt1esWFFeJSWMzMzMavm+E52uW+LStUtccVy7cPxX+KgPoUYNwktuZOWaNXv1/FWBvucSQM262AXX4E/9k3WP38eGhk2wVm107RKUrlviqg7Xrnnz5tt8rFy69ebn53P//ffTr18/+vTpA0DdunVZvXo1AKtXr6ZOnTrlcSoREZG9xletwJ//FwD2m8FYUzWLkaorOPQo7LBBkJcb7X+anRV3SSJSzexxOHV3hg4dSosWLTjppJOK7+/VqxejR0dtyUePHk3v3r339FQiIiJ7jYch4dP/hKwN0K0XNuD4uEsSqXB2/tXQcl9YtgR/5mGtPxWRvWqPw+nMmTP54osvmDZtGnfccQd33HEHEydO5LTTTuP777/nxhtvZOrUqZx22mnlUK6IiMje4Z+9AzOmQO26BJfesM3lKSJVidVIJbj6TkhLx7/7muwPXo+7JBGpRvZ4zWnHjh159dVXt/rYn/70pz09vIiIyF7ni+bjrz8LQHDxb7E69WOuSGTvsaYtsItvwB+/l/VPPUTQqDnWpkPcZYlINVAua05FRESqCs/LIxx2P+TnYf2Owbr3ibskkb0u6H04dsSJkJ9P+Ni9+Mb1cZckItWAwqmIiEgpPuJ5WLwAGjfDzr487nJEYmO/GUxyu06wchnh8AfxMIy7JBGp4hRORURECvmMKfgnIyAICC6/FUtLj7skkdhYSgr17vg/yKgF34/HP34z7pJEpIpTOBUREQF84wbCp/4J7tiJ52Bt94+7JJHYJTVuRjD4FgD8zefwWdNirkhEqjKFUxEREcBfHAqrV0CbDtiJZ8ddjkilYQf2xo49A8KQ8PH78HVr4i5JRKoohVMREan2wrGj8XFfQGoawRW3YklJcZckUqnYaRdCu86wdhXhsPvxsCDukkSkClI4FRGRas1XLsdfGAqAnXMF1rh5zBWJVD6WnExw1R1Quy7MmIK/+0rcJYlIFaRwKiIi1ZaHBYTDh0D2RujeBzv86LhLEqm0rH5DgituAzP83Vfw6ZPiLklEqhiFUxERqbb8k7dg1jSoU4/g4t9iZnGXJFKpWefu2EnngjvhsAfw1SvjLklEqhCFUxERqZZ84Vz8zecBCC69EatdN+aKRBKDnXQ2dDoQ1q8lfPwfeH5+3CWJSBWhcCoiItWO524ifPIBKMjHBp6AdesVd0kiCcOCpGh6b70GMGc6PuK5uEsSkSpC4VRERKodf+NZWLIQmrbAzros7nJEEo7VqUdw1e8gCPCP3sQnj427JBGpAhRORUSkWvHpk/BP34GkJILLb8VSU+MuSSQhWfvO2BkXAxA+9SC+fGnMFYlIolM4FRGRasM3rCN86p8A2MnnYfu2j7kikcRmR58GBx4MWRsJH7sXz8uLuyQRSWAKpyIiUi24O+Fz/4I1q6BdJ+z4M+MuSSThWRAQXHYzNGwMC+bgrz0Zd0kiksAUTkVEpFrwbz+Did9AWjrB4FuwICnukkSqBKtZi+DqOyEpGf/8fcLxX8ZdkogkKIVTEdlpnpeLz50Zdxkiu8yXL8VfehwAO+8qrFHTmCsSqVqsTXvs7MEA+DOP4EsXx1yRiCQihVMR2SmetZHw/j/iixfEXYrILvGwgHD4EMjJhp6HYoccGXdJIlWSHXEi1utw2JRNOPRufNOmuEsSkQSjcCoiOyc9g2DwLQT9jom7EpFd4h+8DnNmQN0GBBddh5nFXZJIlWRm2MW/hcbNYfEC/KXH4i5JRBKMwqmI7BQzwxo3i7sMkV3iC+bg77wEQHDZTVitOjFXJFK1WXoGwbV3QkoN/OuRhF9/GndJIpJAFE5FRKRK8k2bCIfdDwUF2FEnY116xF2SSLVgLdtg518NgL/4b3zR/HgLEpGEoXAqIiJVkr/+FCxdDM1aYWdcHHc5ItVKcPjR2KFHQW4u4WP34DlZcZckIglA4VRERKocnzoB//x9SEomuOI2rEZq3CWJVDt2/jXQYh9Yuhh/9lHcPe6SRKSSUzgVEZEqxdevJXz6IQDstAuw1m1jrkikerLUVIJr7oTUdHz8l/ioD+IuSUQqOYVTERGpMtyd8NlHYd0a6NAVO+a0uEsSqdasaUvs4usB8FeH4fNnx1yRiFRmCqciIlJl+FefwOQxhVsf3YwFSXGXJFLtBQf3xwaeAPn5hEPvwTduiLskEamkFE5FRKRK8GVL8FeGAdFaN2vYOOaKRKSInX057NMOVi4jfOpBrT8Vka1SOBURkYTnBQWETw6BTTlY735YnwFxlyQipVhKCsHVv4P0mjBlHP7JiLhLEpFKSOFUREQSnr//GsydCfUzsQuuxcziLklENmONmhIMvgkAf/0ZfM70mCsSkcpG4VRERBKaz52Jv/syAMFlN2E1a8VckYhsi3XvGzUqC0PCx/6Br18bd0kiUokonIqISMLynGzCJx+AMMSOOQ3rdGDcJYnIDtjpF8N+HWHNSsJhD+BhQdwliUgloXAqIiIJy18bDst+gRb7YKddFHc5IrITLDmZ4KrfQa06MH1SNC1fRASFUxERSVA+eSz+xUeQnExwxW1YSkrcJYnITrIGmQRX3AZm+Nsv4TOmxF2SiFQCCqciIpJwfN1qwmcfAcDOuARruW+8BYnILrMuPbATzwZ3wifuw9esjLskEYmZwqmIiCQUdyd8+mFYvxY6HYgddXLcJYnIbrKTz4WOB8D6tVFALdD6U5HqTOFUREQSio/+EKZOgIyaBJfehAX6USaSqCxIIrjyNqjbAGb9gL/1fNwliUiM9BNdREQSRv7iBfhrTwJgF16PNciMuSIR2VNWpz7BVbeDBfgHr+NTxsddkojEROFUREQSgufns/bBv0BuLtZ3IEHvw+MuSUTKiXXoip1+IQDh8CH4ymUxVyQicVA4FRGRhODvvkz+nB+hQSPsvKvjLkdEypkdewZ06wVZGwgfuxfPz4u7JBHZyxRORUSk0vM5M/D3/wNmBJffgmXUjLskESlnFgQEg2+GBo1g3iz8P0/HXZKI7GUKpyIiUql5Thbhkw+Ah2ScdgHWoWvcJYlIBbFadQiu/h0kJeOfvoN/93XcJYnIXqRwKiIilZq//ASs+BVataHWeVfGXY6IVDBruz/2m8sACJ9+CP91ScwVicjeonAqIiKVlk/8Bv/6U0ipQXDFbVhKStwlicheYEeeBD0PhZxswqH34Lmb4i5JRPYChVMREamUfM1KwmcfBcDOvBRr3jrmikRkbzEzgktugMbNYNG8aAaFiFR5CqciIlLpuDvh0w/BxvXQpQd2xAlxlyQie5ll1CS4+k5ITsG//Jjwm8/iLklEKpjCqYiIVDr++XvwwySoVZvg0huxQD+uRKoja90WOz/aOspf+De+eGHMFYlIRdJPexERqVR8ycLiLSSCi67H6jWMtyARiZUdfjTW9wjI3UQ49G48JzvukkSkgiiciohIpeH5eYTD7oe8XOywo7Ceh8ZdkojEzMywC6+FZq1g6SL8uX/h7nGXJSIVQOFUREQqDX/7Rfh5HjRqip2rbWNEJGKpaQTX3gU1UvFxo/EvPoq7JBGpAAqnIiJSKfisafiHb4AFBINvwdIy4i5JRCoRa9YKu+h6APzlx/EFP8VckYiUN4VTERGJnWdtJHxyCLhjJ5yFtesUd0kiUgkFfQdi/Y+D/HzCx+7BszbEXZKIlCOFUxERiZ2/9DisWg77tMNOOjfuckSkErNzr4DWbWH5UsKnH9L6U5EqROFURERiFY7/Ch/zOdSoQXDFrVhyctwliUglZik1ov1P0zNg0hh85NtxlyQi5UThVEREYuOrVuDP/wsA+83lWNOWMVckIonAGjcjuPRGAPz1p/Gffoy5IhEpDwqnIiISCw9Dwqf/CVkboFsvbMBxcZckIgnEeh6KDToVCgoIH7sXX78u7pJEZA8pnIqISCz803dgxhSoXZfg0hsws7hLEpEEY2deDG33h9UrCIc/gIdh3CWJyB5QOBURkb3OF83H33gWgODi32J16sdckYgkIktOIbj6d1CrNkybiH/wn7hLEpE9oHAqIiJ7leflEg67H/LzsH7HYN37xF2SiCQwa9CIYPCtAPhbL+I/fh9zRSKyuxRORURkr/IRz8PiBdC4GXb25XGXIyJVgHU7CDvhbPCQ8In78DWr4i5JRHaDwqmIiOw1PmMK/slbEAQEl9+KpaXHXZKIVBF2ynmwfzdYtyYKqAUFcZckIrtI4VRERPYK37iB8Kl/gjt24jlY2/3jLklEqhBLSiK44jaoUw9mTcPffinukkRkFymciojIXuEv/BtWr4A2HbATz467HBGpgqxeA4IrbwcL8Pdfxad+F3dJIrILFE5FRKTChWNH4+O/hNQ0gituxZKS4i5JRKoo63gAdur5AIRPPoCvWh5zRSKysxRORUSkQvnKZfgLQwGwc67AGjePuSIRqers+LOga0/YuJ7wsXvx/Ly4SxKRnaBwKiIiFcbDAsLhD0L2RujeBzv86LhLEpFqwIIg2l6mfibMnYm//mzcJYnITlA4FRGRCuOfvAWzpkGdegQX/xYzi7skEakmrHYdgqt/B0lJ+Mi38InfxF2SiOyAwqmIiFQIXzgXf/N5AIJLb8Rq1425IhGpbmy/jtiZlwIQPv0QvuyXeAsSke1SOBURkXLnuZsIh90PBfnYwBOwbr3iLklEqikbdAr06AvZWYSP3YPn5cZdkohsg8KpiIiUO3/jWfjlZ2jaAjvrsrjLEZFqzMwILr0RGjWFhXPxl4fFXZKIbIPCqYiIlCv/YRL+6TuQlERwxW1YamrcJYlINWcZtQiuvhOSU/AvPiQcMyrukkRkKxRORUSk3PiGdYRP/RMAO/k8bJ92MVckIhKxffbDzr0SAH/uUXzJwpgrEpHNKZyKiEi5cHfC5/4Fa1dBu07Y8WfGXZKISBnW/1js4AGQu4lw6D34ppy4SxKRUhRORUSkXPi3n8HEbyAtnWDwLViQFHdJIiJlmBl20XXQtCX88jP+/L9x97jLEpFCCqciIrLHfPlS/KXHAbDzrsIaNY25IhGRrbO0dIJr7oIaqfiYz/GvPom7JBEppHAqIiJ7xMMCwuFDICcbDjoUO+TIuEsSEdkua9Eau/A6APzFx/CFc2OuSERA4VRERPaQf/A6zJkBdRsQXHgdZhZ3SSIiOxQccgTW7xjIz4v2P83aGHdJItWewqmIiOw2nz8bf+clAILLbsJq1Ym5IhGRnWfnXgkt28CyXwifeVjrT0VipnAqIiK7xTdtInzyASgowI46GevSI+6SRER2idVIJbjmTkhLh4nf4J+9G3dJItWawqmIiOwW/89TsHQxNGuFnXFx3OWIiOwWa9Kc4NIbAfDXnsLnzoy5IpHqq8LD6eTJk7npppu44YYbGDFiREWfTkRE9gKfOgEf9T4kJRNccRtWIzXukkREdpsddBh21MlQkE/42L34hnVxlyRSLVVoOA3DkCeffJI//OEPDBkyhK+//ppFixZV5ClFRKSC+fq1hE8/BICdfiHWum3MFYmI7Dk761Jo0wFWLScc/iAehnGXJFLtVGg4nTNnDk2bNqVJkyYkJydz6KGHMn78+Io8pYiIVCB3J3z2EVi3Bjp0xY4+Ne6SRETKhSWnEFz9O8ioBVMn4B+9EXdJItVOckUefNWqVTRs2LD4dsOGDZk9e3aZ54wcOZKRI0cCcPfdd5OZmVmRJVVKycnJ1fJ9Jzpdt8Sla7f7sj55m/WTx2IZtWh4+/+S1KjJXj2/rl1i0nVLXNXu2mVmsumW/2HN3+7ARzxPnR59qNE18Zq9VbvrVoVU92tXoeF0ZwwaNIhBgwYV316xYkWM1cQjMzOzWr7vRKfrlrh07XaPL1tC+OSD0Y3zr2a1JcNe/jrq2iUmXbfEVS2v3b77Y8efiX/wOqvv+2+CPw3B6tSPu6pdUi2vWxVRHa5d8+bNt/lYhU7rbdCgAStXriy+vXLlSho0aFCRpxQRkQrgBQWEwx6ATTlY734EfQbEXZKISIWxUy+EDl1g7SrCJ+7Hw4K4SxKpFio0nO6333788ssvLFu2jPz8fL755ht69epVkacUEZEK4O+9CvNmQf1M7IJr4y5HRKRCWVISwZW3Q+268OP3+Dsvx12SSLVQoeE0KSmJwYMH87e//Y1bbrmFQw45hFatWlXkKUVEpJz53Jn4e68AEFx2E1azVswViYhUPKvXMAqoZvh7r+LTJsZdkkiVV+FrTnv27EnPnj0r+jQiIlIBPCeb8MkHIAyxY07DOh0Yd0kiInuNdToQO+U8/K0XCZ98gOC/H8QaVN9mNSIVrUJHTkVEJLH5a8Nh2S/QYh/stIviLkdEZK+zE86Gzj1gwzrCx+/F8/PjLkmkylI4FRGRrfLJY/EvPoLkZIIrbsNSUuIuSURkr7MgILjiVqjXEH76EX/z2bhLEqmyFE5FRGQLvm414bOPAGBnXIK13DfegkREYmS16xJcfQcEAf7xCHzymLhLEqmSFE5FRKQMdyd8+mFYvxY6HYgddXLcJYmIxM7adcbOvASAcPg/8eVLY65IpOpROBURkTJ89IcwdQJk1CS49CYs0I8KEREAO/o06N4HsjcSDr0Hz8uNuySRKkW/cYiISDFfugh/7UkA7MLr1ZVSRKQUMyO49CZo2BgW/oS/OjzukkSqFIVTEREBwPPzCYc9ALm5WN8jCHofHndJIiKVjtWsRXDNnZCcjI96n3DcF3GXJFJlKJyKiAgA/u7LsGAONGyMnXdV3OWIiFRatm977OwrAPBnH8F/WRRzRSJVg8KpiIjgc2bg7/8HzAgG34xl1Iy7JBGRSs0GHo/17gebcggfuwfftCnukkQSnsKpiEg15zlZhE8+AB5ix52Bdegad0kiIpWemWEXXw9NW8DiBfiLQ+MuSSThKZyKiFRz/vITsOJXaN0WO+X8uMsREUkYlpZBcPWdUKMG/s2nhF99EndJIglN4VREpBrzid/gX38KKTUILr8VS06JuyQRkYRiLffFzr8WAH/xMXzRvJgrEklcCqciItWUr1lJ+OyjANhZl2LNW8dckYhIYgoOOwo7bBDk5RL++x48OyvukkQSksKpiEg15GFI+NRDsHE9dOmBHXFi3CWJiCQ0O+9qaLEPLFuCP/Mw7h53SSIJR+FURKQa8s/fh+mToFZtgktvxMziLklEJKFZairBNXdBajr+3df45+/FXZJIwlE4FRGpZnzJQvz1pwEILroeq9cw3oJERKoIa9oCu+S3APirw/F5s2OuSCSxKJyKiFQjnp9HOOx+yMvFDjsK63lo3CWJiFQpQe9+2BEnQEF+tP/pxg1xlySSMBRORUSqEX/rRfh5HjRqip17ZdzliIhUSfaby2GfdrByGeFTD+JhGHdJIglB4VREpJrwWdPwj94ACwgG34KlZcRdkohIlWQpKQRX/w4yasKUcfgnI+IuSSQhKJyKiFQDnrWR8Mkh4I6dcBbWrlPcJYmIVGnWqCnBZTcD4G88i8/6Id6CRBKAwqmISDXgLz0Gq5bDPu2wk86NuxwRkWrBuvfBjj0dwpDwiX/g69bEXZJIpaZwKiJSxYXjv8THjIIaqQRX3IYlJ8ddkohItWGnXQTtOsOaVYTD7sfDgrhLEqm0FE5FRKowX7UCf/5fANhvBmNNW8RckYhI9WLJyQRX3QG168KMKfi7r8ZdkkilpXAqIlJFeRgSPvUgZG2Ebr2wAcfFXZKISLVk9RsSXHErmOHvvoxPnxR3SSKVksKpiEgV5Z++Az9+D7XrElx6A2YWd0kiItWWde6BnXQOuBMOewBfvTLukkQqHYVTEZEqyBfNx994BoDgkhuwOvVjrkhEROykc6DTgbB+LeHj/8ALtP5UpDSFUxGRKsbzcgmH3Q/5+Vj/Y7EDD467JBERASxIIrjiNqjbAOZMx998Lu6SRCoVhVMRkSrGRzwPixdA4+bY2ZfHXY6IiJRidepFDZKCAP/oDXzKuLhLEqk0FE5FRKoQnzEF/3gEBAHBFbdiqWlxlyQiIpuxDl2w0y8CIBz+IL7i15grEqkcFE5FRKoI37iBcPiDANhJ52JtOsRbkIiIbJMdczoc0BuyNhA+di+elxd3SSKxUzgVEakC3B1/4d+wZiW03R874TdxlyQiItthQUAw+GZo2Bjmz8ZfGx53SSKxUzgVEakCfOxofPyXkJpGcPktWFJS3CWJiMgOWM3aBFf/DpKS8c/fIxz/VdwlicRK4VREJMH5ymX4i48BYOdcgTVuHnNFIiKys6xNB+zswQD4sw/jSxfHXJFIfBRORUQSmIcF0TrT7I3QvS92+NFxlyQiIrvIjjgRO+gwyMkmHHo3nrsp7pJEYqFwKiKSwPzjETBrGtSpR3Dx9ZhZ3CWJiMguMjPskhugcXNYvKB4NoxIdaNwKiKSoHzhXHzECwAEl96E1a4bc0UiIrK7LD2D4No7IaUG/vVIwq8/jbskkb1O4VREJAF57ibCYfdDQT428ASs20FxlyQiInvIWrbBzr8aAH/x3/jiBTFXJLJ3KZyKiCQgf+NZ+OVnaNoCO+uyuMsREZFyYocNwg45EnJzo/WnOVlxlySy1yiciogkGP9hEv7pO5CURHDFbVhqatwliYhIOTEz7IJroHlrWLoYf/ZR3D3uskT2CoVTEZEE4hvWET71TwDs5POwfdrFXJGIiJQ3S00juOYuSE3Dx3+Jj/4g7pJE9gqFUxGRBOHuhM/9C9augnadsOPPjLskERGpINasJXbR9QD4K8PwBXNirkik4imciogkCP/2M5j4DaSlEwy+BQuS4i5JREQqUNBnADbweMjPJxx6D75xQ9wliVQohVMRkQTgy5fiLz4OgJ13FdaoacwViYjI3mBnXw6t94MVvxI+/U+tP5UqTeFURKSS87CAcPgQ2JQNBx0adXEUEZFqwVJqEFxzJ6TXhMlj8U9GxF2SSIVROBURqeT8g9dhzgyo14Dgwusws7hLEhGRvcgaNSW47CYA/PVn8DnTY65IpGIonIqIVGI+fzb+zksABJfdhNWqE3NFIiISB+vRFzvmNAhDwsf+ga9fG3dJIuVO4VREpJLyTZsIn3wACgqwo07GOveIuyQREYmRnX4x7NcR1qwkHPYAHoZxlyRSrhRORUQqKf/PU7B0MTRvjZ1xcdzliIhIzCw5meCq30Gt2jB9Ev7+a3GXJFKuFE5FRCohnzoBH/U+JCUTXHEbViM17pJERKQSsAaZBJffCmb42y/hM6bgGzcQPv4PfOI3cZcnskcUTkVEKhlfv5bw6YcAsNMvxFq1ibkiERGpTKzrQdgJvwEPCZ+4D//yY3z8l4TPPIKvWhF3eSK7TeFURKQScXfCZx+BdWtg/27Y0afGXZKIiFRCdsp5sH83WL8W/34cdOkJWRsIhw/BCwriLk9ktyiciohUIv7VJzB5LKTXJLjsZixIirskERGphCxIIrjydqhbH2ZPhybNoXZdmDmVrLdejLs8kd2icCoiUkn4siX4K8MAsAuuwRo2irkiERGpzKxufYIr7wAL4LN3sYHHA7Dhxcfx+bPjLU5kNyiciohUAl5QQDjsAdiUgx3cn6DPgLhLEhGRBGD7d8VOuwAA//RdOPRIKCggfOJ+PCc75upEdo3CqYhIJeDvvQrzZkH9TOz8a+IuR0REEogddyZ06wVZG2DxQpJatYFlS/CXn4i7NJFdonAqIhIznzsTf+8VMCMYfDNWs1bcJYmISAKxICD4/+3daZRV1YH28f8+VSXzVMg8BJmMncQp0FGUGFo0RqNx4RCwHUAIySrRFuKrWa9Ls9ZLkkWWAkk7RDsCUeKECTSxk7SJImhEhaC0GqW1jAMqUEAxyEzV3e+Hwko0gChF7Xvr/n+fOKekfGrt2ufch7vP3ZdfDeWd4K1Kyo4YCKVlxKceJS57KnU86YBZTiUpobhjO7kZ0yCXI5x2LuGzR6eOJEkqQKF1W7JvXwslpex44hHCCXWPh+TuuZVYvTZxOunAWE4lKaE4ZwZUrYKefQjnXpw6jiSpgIW+RxLOHw1AXPqnuq1mtm0lN2M6Mef2Msp/llNJSiQuf5b45B+gtIxs7CRCWVnqSJKkAhdOPZtmJ34Fdu6A9zfVbS/z6kvE/56bOpr0sSynkpRA3LSB3N23ABDOu5TQs0/aQJKkJiGEQNsr/i906grvvQ2f6QdA/M19xDdeTZxO2j/LqSQ1shhjXTHdshmOOobwL2enjiRJakKyVq3JvvM9KC2Dl56Dzx23Z3uZm4k7tqWOJ+2T5VSSGllc9Ht48c/QsjXZ6H8jZF6KJUkNK/TuSxg1vu7g1b9Alx6wdjXxfreXUf7yFZEkNaK4+h3iQzMBCBdXEMoPT5xIktRUhaGnE074CuzeBbW1UFZGXPwYuaVPpo4m7ZXlVJIaSaypIXfXNNi1i3DCMLLBJ6eOJElqwkIIhIsroFsvWLcaevQBIM6+nbi+Km04aS8sp5LUSOJ/PQBvVULHzn9baiVJ0iEUmjUn+851cFgzePM16NkHtm8lN2Oa28so71hOJakRxMqXib/7FYRAdvlEQstWqSNJkopE6N6bcElF3cGqd6B1G3htz31JyiOWU0k6xOL2beRmTIeYI5wxgjDwc6kjSZKKTHbCMMKXvwq1NVBSCkB8+H7i6ysSJ5P+xnIqSYdYfPDnsG4N9O5LOOei1HEkSUUqjPwW9DoCNm2Azt0gl6tb3rvd7WWUHyynknQIxWWLiU89BmWHkY37LqG0LHUkSVKRCmWH1e1/2qIlVK2C9uV128vcd2fqaBJgOZWkQyZuXE9u9m0AhPNHE7r1SpxIklTsQuduZKOvqjvYvBFKy4jPPE7u2UVJc0lgOZWkQyLmcuRm/TtsfR8+fzxh2FmpI0mSBEA4fghh+DmQy9V9ii8Q7/0Zcd2axMlU7CynknQIxMd/By8/D63bkF12FSGE1JEkSaoXzrsM+h4J27ZA2/awfVvd86e1bi+jdCynktTA4ntvE3/9CwCyS64gtC9PG0iSpI8IpWVk46+FVm3qlvc2bwGVrxB/91DqaCpillNJakCxZje5u6bC7l2Ek4YTjh+SOpIkSXsVOnYiGzup7mDHDiAQH36AWPlK0lwqXpZTSWpAcf59sPIN6NSVMHJc6jiSJO1X+MIXCWdeAEQ47DCIOXJ3TSVu25o6moqQ5VSSGkj835eIj8yFkJFdPpHQvGXqSJIkfaxwzkUw8POwayc0awHrq4j33ZE6loqQ5VSSGkDctpXczOkQI+GsCwj9j0odSZKkAxJKSsi+dU3dByPt3A4lJcRnF5F75vHU0VRkLKeS1ADi/XdC9VroM4Bw1jdTx5Ek6RMJ7cvrCmrIYM8n9sZ77yCuXZ04mYqJ5VSSDlJu6ZPEZxbCYc3Ixk4ilJamjiRJ0icWPns04RsX1R2UlMKO7W4vo0Z1UK+gZs+ezbJlyygtLaVLly5UVFTQqlUrAObNm8eCBQvIsowxY8Zw7LHHNkReScorsXod8Ze3AxAuHEvo2iNxIkmSPr3wtfOJlS/DS8/VFdTXVxD/68G/lVbpEDqod06PPvpopk6dys0330y3bt2YN28eAO+88w6LFy9m2rRpXH/99cyYMYNcLtcggSUpX8Rcjtysn8C2rXD0YMKXv5o6kiRJByVkGdnlk6DD4VBbA0D87Rziay8nTqZicFDl9JhjjqGkpASAgQMHUl1dDcDSpUsZMmQIZWVldO7cma5du1JZWXnwaSUpj8RHfwMrXoA27cgum0AIIXUkSZIOWmjTlmz8/4E9r/OJubrlvdu2pA2mJq/BnjldsGBB/dLd6upqOnbsWP+18vLy+uIqSU1BfOdN4rx7AMguu5LQtkPiRJIkNZzQ/yjCiMv2HGR128v88mfEGNMGU5P2sc+cTp48mY0bN/7D+ZEjRzJ48GAA5s6dS0lJCUOHDv3EAR599FEeffRRAKZMmcLhhx/+ib9HoSstLS3Kn7vQOW6F62DHLu7aSfUvfkqupoYWp3+Dtqee2YDptD/Ou8LkuBUux64wNdS4xVFj2fR2JTuffQJCIC59kjYnfoUWw77WACm1N8U+5z62nN5www37/frChQtZtmwZN954Y/2StvLyctavX1//31RXV1NeXr7Xvz98+HCGDx9ef7xu3boDCt6UHH744UX5cxc6x61wHezY5ebMIL71OnTuzs5z/tXfg0bkvCtMjlvhcuwKU0OOW7zoO/DXV2HPljKb77yZLV16Ejp3a5Dvrw8rhjnXvXv3fX7toJb1Ll++nPnz53PdddfRrFmz+vODBg1i8eLF7N69m6qqKlatWkX//v0P5n8lSXkhvvI/xD/OhywjGzeJ0Kx56kiSJB0yoWVrsm9f97fnT3duJ3fXVGJNTdpgapIOaiuZGTNmUFNTw+TJkwEYMGAA48ePp1evXpx44olMmjSJLMsYO3YsWeaWqpIKW9y6hdzMnwAQvj6ScMTAtIEkSWoE4TP9CCPHE+/9Wd2Jtu3rPsnXfb3VwA7qN+qWW27Z59dGjBjBiBEjDubbS1LeiDHW3ZQ3roe+RxLOvCB1JEmSGk045Qx47WXikkVQtSp1HDVRvp0pSQcgPruIuPRJaNacbOwkwgfLmyRJKgIhBMIlFdC1J7RqAzu3p46kJsj34iXpY8T1VcT77gAgfHOcHwIhSSpKoXkLson/D9q2J7ikV4eAv1WStB8xV0tu5nTYvg2OPYFw8mmpI0mSlEwoL95tTnTouaxXkvYj/uE/4dW/QLsOZJdOqN8yS5IkSQ3LcipJ+xDffp34n/cCkF12FaFN28SJJEmSmi7LqSTtRdy1k9xd06C2hjDsTMIXvpg6kiRJUpNmOZWkvYhz74FVK6FrT8J5Y1LHkSRJavIsp5L0EfEvzxMfexhKSsjGTSI0a5Y6kiRJUpNnOZWkvxO3bCY366cAhHMuInymf+JEkiRJxcFyKkl7xBjJzb4NNlVD/38inDEidSRJkqSiYTmVpD3i4gXw3NPQvAXZ5VcTspLUkSRJkoqG5VSSgLh2NfH+/wAgjPo2oVPXxIkkSZKKi+VUUtGLtbXkZk6Hndvhi0MIJw5LHUmSJKnoWE4lFb3437+GylegfTnZxRWEEFJHkiRJKjqWU0lFLb75GvHh+wHIxvwboXXbxIkkSZKKk+VUUtGKO3eQu2sa1NYSTj2b8E/HpY4kSZJUtCynkopW/NUsWPMudO9NGHFp6jiSJElFzXIqqSjFF/9MXPh7KC0lG/ddwmHNUkeSJEkqapZTSUUnt7Ga3KyfAhDOvZjQ64jEiSRJkmQ5lVRUYoxsvn0KvL8JjvwC4bRvpI4kSZIkLKeSikz80x/ZufRP0KIV2ZirCVlJ6kiSJEnCciqpiMQ17xEf+DkA4V+/Q+jYKXEiSZIkfcByKqkoxNpacjOmwa6dNB96GtmXTkkdSZIkSX/HciqpKMTfzoE3XoXyw2kz/rup40iSJOkjLKeSmrz4+gribx+EEMjGXE3Wum3qSJIkSfoIy6mkJi3u2F63nDeXI5x2LuGzR6eOJEmSpL2wnEpq0uKcGbB2NfTsQzj34tRxJEmStA+WU0lNVlz+DPHJP0BpGdm47xLKylJHkiRJ0j5YTiU1SXHTBnJ33wpAOO9SQo/PJE4kSZKk/bGcSmpyYozk7r4FtmyGo44h/MvZqSNJkiTpY1hOJTU5cdHv4cU/Q8vWZGOuJmRe6iRJkvKdr9gkNSlx9TvEh2YCkF1SQejQMXEiSZIkHQjLqaQmI9bUkLtrGuzaRThxGGHQyakjSZIk6QBZTiU1GfHhB+CtSujYmTByfOo4kiRJ+gQsp5KahFj5MvH3v4IQyC6fSGjZKnUkSZIkfQKWU0kFL27fRm7GdIg5whnnEQZ+LnUkSZIkfUKWU0kFLz7wc1i3Bnr3I5wzKnUcSZIkfQqWU0kFLS5bTFz8GJQdRjZuEqG0LHUkSZIkfQqWU0kFK25cT272bQCE80cTuvVKnEiSJEmfluVUUkGKuRy5Wf8OW9+Hzx9PGHZW6kiSJEk6CJZTSQUpPv47ePl5aN2G7LKrCCGkjiRJkqSDYDmVVHDiu28Tf/0LALJLJhDal6cNJEmSpINmOZVUUGLNbnIzpsLuXYSThhOOPzF1JEmSJDUAy6mkghLn3wcr34BOXQkjx6WOI0mSpAZiOZVUMOL/vkR8ZC6EjGzsJELzlqkjSZIkqYFYTiUVhLhtK7mZ0yFGwlkXEPp9NnUkSZIkNSDLqaSCEO+/E6rXQp8BhLO+mTqOJEmSGpjlVFLeyy15gvjMQjisWd1y3tLS1JEkSZLUwCynkvJarF5LvPdnAIQLxxK69kicSJIkSYeC5VRS3oq5HLlZP4VtW+HowYQvfzV1JEmSJB0illNJeSs++htY8QK0aUd22QRCCKkjSZIk6RCxnErKS/GdN4jz7gEgu+xKQtsOiRNJkiTpULKcSso7cfcucndNg5oawpfPIBzzz6kjSZIk6RCznErKO3HebHj3LejcnXDh5anjSJIkqRFYTiXllfjK/xD/OB+yjGzcJEKz5qkjSZIkqRFYTiXljbh1C7mZPwEgnD2ScMTAtIEkSZLUaCynkvJCjJH4y9th43roeyThaxekjiRJkqRGZDmVlBfiswuJf/4TNGtONnYSoaQkdSRJkiQ1IsuppOTi+irifXcCEEZ+i9C5W+JEkiRJamyWU0lJxVwtuZnTYfs2OPYEwknDU0eSJElSAqWpA0gqciEjDB5K3LCe7NIJhBBSJ5IkSVICllNJSYUQCF85k3jyaYTSstRxJEmSlIjLeiXlBYupJElScbOcSpIkSZKSs5xKkiRJkpKznEqSJEmSkrOcSpIkSZKSs5xKkiRJkpKznEqSJEmSkrOcSpIkSZKSs5xKkiRJkpKznEqSJEmSkrOcSpIkSZKSs5xKkiRJkpKznEqSJEmSkrOcSpIkSZKSs5xKkiRJkpKznEqSJEmSkrOcSpIkSZKSs5xKkiRJkpKznEqSJEmSkrOcSpIkSZKSs5xKkiRJkpILMcaYOoQkSZIkqbj5zmke+N73vpc6gj4Fx61wOXaFy7ErTI5b4XLsCpPjVriKfewsp5IkSZKk5CynkiRJkqTkLKd5YPjw4akj6FNw3AqXY1e4HLvC5LgVLseuMDluhavYx84PRJIkSZIkJec7p5IkSZKk5EpTBygmTz/9NA899BDvvvsuP/rRj+jXr1/91+bNm8eCBQvIsowxY8Zw7LHHArB8+XJmzZpFLpfj1FNP5dxzz00TXvWmT5/Oe++9B8C2bdto2bIlN910E1VVVUycOJHu3bsDMGDAAMaPH58yqj5izpw5PPbYY7Rt2xaAUaNGcfzxxwP7noNKb/bs2SxbtozS0lK6dOlCRUUFrVq1cs4VCO9jhWHdunXcdtttbNy4kRACw4cP58wzz9zvdVP544orrqB58+ZkWUZJSQlTpkxhy5YtTJ8+nbVr19KpUycmTpxI69atU0fVHu+99x7Tp0+vP66qquLCCy9k69atxT3nohrNypUr47vvvhu///3vx8rKyg+dv+aaa+KuXbvimjVr4oQJE2JtbW2sra2NEyZMiKtXr467d++O11xzTVy5cmXCn0Afdffdd8eHHnooxhjjmjVr4qRJkxIn0v48+OCDcf78+f9wfl9zUPlh+fLlsaamJsYY4+zZs+Ps2bNjjM65QuB9rHBUV1fH119/PcYY47Zt2+JVV10VV65cuc/rpvJLRUVF3LRp04fOzZ49O86bNy/GGOO8efPqr53KP7W1tXHcuHGxqqqq6Oecy3obUc+ePev/hf/vLV26lCFDhlBWVkbnzp3p2rUrlZWVVFZW0rVrV7p06UJpaSlDhgxh6dKlCZJrb2KMPP3005x00kmpo+gg7WsOKj8cc8wxlJSUADBw4ECqq6sTJ9KB8j5WODp06EDfvn0BaNGiBT169HCuFbilS5dyyimnAHDKKac49/LYiy++SNeuXenUqVPqKMm5rDcPVFdXM2DAgPrj8vLy+htCx44d68937NiR1157rdHzae9eeeUV2rVrR7du3erPVVVVce2119KiRQtGjhzJUUcdlTCh9uaRRx7hiSeeoG/fvlx66aW0bt16v3NQ+WXBggUMGTKk/tg5l9+qq6u9jxWgqqoq3njjDfr378+KFSv2et1U/vnhD38IwGmnncbw4cPZtGkTHTp0AKB9+/Zs2rQpZTztx1NPPfWhNzuKec5ZThvY5MmT2bhx4z+cHzlyJIMHD278QPpUDmQcP3oh6dChA7fffjtt2rThr3/9KzfddBNTp06lZcuWjRVb7H/sTj/9dM4//3wAHnzwQe655x4qKioaOaH25kDm3Ny5cykpKWHo0KGAc046FHbs2MHUqVMZPXo0LVu29LpZICZPnkx5eTmbNm3iBz/4wT+s1AshEEJIlE77U1NTw7Jly7jooosAin7OWU4b2A033PCJ/055eTnr16+vP66urqa8vBzgQ+fXr19ff16H1seNY21tLUuWLGHKlCn158rKyigrKwOgb9++dOnShVWrVn3og6906B3oHDz11FP58Y9/DOx/DqpxfNy4LVy4kGXLlnHjjTfWv8ByzuW/j84t72P5raamhqlTpzJ06FC+9KUvAXXvuH3g76+byi8fzKt27doxePBgKisradeuHRs2bKBDhw5s2LCh/gN2lF+ef/55jjjiiPq5VuxzzmdO88CgQYNYvHgxu3fvpqqqilWrVtG/f3/69evHqlWrqKqqoqamhsWLFzNo0KDUcUXdswHdu3f/0HK1zZs3k8vlAFizZg2rVq2iS5cuqSJqLzZs2FD/5yVLltCrVy9g33NQ+WH58uXMnz+f6667jmbNmtWfd87lP+9jhSPGyB133EGPHj34+te/Xn9+X9dN5Y8dO3awffv2+j+/8MIL9O7dm0GDBrFo0SIAFi1a5Aq+PPXRlXjFPudCjDGmDlEslixZwsyZM9m8eTOtWrWiT58+XH/99UDdcrXHH3+cLMsYPXo0xx13HADPPfccd999N7lcjmHDhjFixIiUP4L2uO222xgwYACnn356/blnnnmGOXPmUFJSQpZlXHDBBb4IyzO33HILb775JiEEOnXqxPjx4+ufx9nXHFR6V155JTU1NfXP3HywZYxzrjB4HysMK1as4MYbb6R37971qxNGjRrFU089tc/rpvLDmjVruPnmm4G6lV0nn3wyI0aM4P3332f69OmsW7fOrWTy1I4dO6ioqODWW2+tfyRlf69VioHlVJIkSZKUnMt6JUmSJEnJWU4lSZIkSclZTiVJkiRJyVlOJUmSJEnJWU4lSZIkSclZTiVJkiRJyVlOJUmSJEnJWU4lSZIkScn9f+35heVubwOnAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.collections import LineCollection\n",
    "\n",
    "df_plot = df.dropna()\n",
    "lines = [[(lon0, lat0), (lon1, lat1)] \n",
    "         for lon0, lat0, lon1, lat1 in df_plot[['city_lon', \n",
    "                                                'city_lat', \n",
    "                                                'birth_city_lon', \n",
    "                                                'birth_city_lat']].values]\n",
    "\n",
    "line_collection = LineCollection(lines, linewidths=2)\n",
    "\n",
    "plt.figure(figsize=(16, 9))\n",
    "plt.gca().add_collection(line_collection)\n",
    "plt.gca().autoscale()\n",
    "plt.axis('equal');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# What is the Average Age of a Mayor?\n",
    "\n",
    "We can see that 55 years is the prime age to be a mayor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average age : 55.49 (+/- 10.14)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['age'].plot(kind='hist', bins=50, figsize=(16, 9));\n",
    "print('Average age : {:.2f} (+/- {:.2f})'.format(df['age'].mean(), df['age'].std()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['duration'].plot(kind='hist', bins=20, figsize=(16, 9));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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>country</th>\n",
       "      <th>city</th>\n",
       "      <th>cityLabel</th>\n",
       "      <th>population</th>\n",
       "      <th>mayor</th>\n",
       "      <th>mayorLabel</th>\n",
       "      <th>genderLabel</th>\n",
       "      <th>birth</th>\n",
       "      <th>age</th>\n",
       "      <th>start_date</th>\n",
       "      <th>duration</th>\n",
       "      <th>birth_country</th>\n",
       "      <th>birth_countryLabel</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_cityLabel</th>\n",
       "      <th>city_lon</th>\n",
       "      <th>city_lat</th>\n",
       "      <th>birth_city_lon</th>\n",
       "      <th>birth_city_lat</th>\n",
       "      <th>distance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>678</th>\n",
       "      <td>Spain</td>\n",
       "      <td>http://www.wikidata.org/entity/Q10282</td>\n",
       "      <td>Pamplona</td>\n",
       "      <td>203944.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q2223568</td>\n",
       "      <td>Enrique Maya Miranda</td>\n",
       "      <td>male</td>\n",
       "      <td>1959-11-07 00:00:00</td>\n",
       "      <td>62.0</td>\n",
       "      <td>2019-06-15</td>\n",
       "      <td>2</td>\n",
       "      <td>http://www.wikidata.org/entity/Q77</td>\n",
       "      <td>Uruguay</td>\n",
       "      <td>http://www.wikidata.org/entity/Q1335</td>\n",
       "      <td>Montevideo</td>\n",
       "      <td>-1.650000</td>\n",
       "      <td>42.816667</td>\n",
       "      <td>-56.166667</td>\n",
       "      <td>-34.866667</td>\n",
       "      <td>1.023175e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>858</th>\n",
       "      <td>France</td>\n",
       "      <td>http://www.wikidata.org/entity/Q249884</td>\n",
       "      <td>Saint-Pierre</td>\n",
       "      <td>84961.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q3309639</td>\n",
       "      <td>Michel Fontaine</td>\n",
       "      <td>male</td>\n",
       "      <td>1952-05-06 00:00:00</td>\n",
       "      <td>69.0</td>\n",
       "      <td>2001-01-01</td>\n",
       "      <td>20</td>\n",
       "      <td>http://www.wikidata.org/entity/Q142</td>\n",
       "      <td>France</td>\n",
       "      <td>http://www.wikidata.org/entity/Q239078</td>\n",
       "      <td>Romans-sur-Isère</td>\n",
       "      <td>55.477778</td>\n",
       "      <td>-21.341944</td>\n",
       "      <td>5.050833</td>\n",
       "      <td>45.045556</td>\n",
       "      <td>8.951750e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>629</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>http://www.wikidata.org/entity/Q72</td>\n",
       "      <td>Zürich</td>\n",
       "      <td>434008.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q123363</td>\n",
       "      <td>Corine Mauch</td>\n",
       "      <td>female</td>\n",
       "      <td>1960-05-28 00:00:00</td>\n",
       "      <td>61.0</td>\n",
       "      <td>2009-05-01</td>\n",
       "      <td>12</td>\n",
       "      <td>http://www.wikidata.org/entity/Q30</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>http://www.wikidata.org/entity/Q487977</td>\n",
       "      <td>Iowa City</td>\n",
       "      <td>8.540000</td>\n",
       "      <td>47.378611</td>\n",
       "      <td>-91.525000</td>\n",
       "      <td>41.655833</td>\n",
       "      <td>7.401167e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>584</th>\n",
       "      <td>Estonia</td>\n",
       "      <td>http://www.wikidata.org/entity/Q1770</td>\n",
       "      <td>Tallinn</td>\n",
       "      <td>438341.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q4250802</td>\n",
       "      <td>Mihhail Kõlvart</td>\n",
       "      <td>male</td>\n",
       "      <td>1977-11-24 00:00:00</td>\n",
       "      <td>44.0</td>\n",
       "      <td>2019-04-04</td>\n",
       "      <td>2</td>\n",
       "      <td>http://www.wikidata.org/entity/Q232</td>\n",
       "      <td>Kazakhstan</td>\n",
       "      <td>http://www.wikidata.org/entity/Q491123</td>\n",
       "      <td>Kyzylorda</td>\n",
       "      <td>24.745000</td>\n",
       "      <td>59.437222</td>\n",
       "      <td>65.499890</td>\n",
       "      <td>44.847900</td>\n",
       "      <td>3.156628e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>905</th>\n",
       "      <td>Denmark</td>\n",
       "      <td>http://www.wikidata.org/entity/Q21176</td>\n",
       "      <td>Viborg</td>\n",
       "      <td>40371.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q1364114</td>\n",
       "      <td>Ulrik Wilbek</td>\n",
       "      <td>male</td>\n",
       "      <td>1958-04-13 00:00:00</td>\n",
       "      <td>63.0</td>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>3</td>\n",
       "      <td>http://www.wikidata.org/entity/Q948</td>\n",
       "      <td>Tunisia</td>\n",
       "      <td>http://www.wikidata.org/entity/Q3572</td>\n",
       "      <td>Tunis</td>\n",
       "      <td>9.400000</td>\n",
       "      <td>56.450000</td>\n",
       "      <td>10.180000</td>\n",
       "      <td>36.800833</td>\n",
       "      <td>2.185042e+06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         country                                    city     cityLabel  \\\n",
       "678        Spain   http://www.wikidata.org/entity/Q10282      Pamplona   \n",
       "858       France  http://www.wikidata.org/entity/Q249884  Saint-Pierre   \n",
       "629  Switzerland      http://www.wikidata.org/entity/Q72        Zürich   \n",
       "584      Estonia    http://www.wikidata.org/entity/Q1770       Tallinn   \n",
       "905      Denmark   http://www.wikidata.org/entity/Q21176        Viborg   \n",
       "\n",
       "     population                                    mayor  \\\n",
       "678    203944.0  http://www.wikidata.org/entity/Q2223568   \n",
       "858     84961.0  http://www.wikidata.org/entity/Q3309639   \n",
       "629    434008.0   http://www.wikidata.org/entity/Q123363   \n",
       "584    438341.0  http://www.wikidata.org/entity/Q4250802   \n",
       "905     40371.0  http://www.wikidata.org/entity/Q1364114   \n",
       "\n",
       "               mayorLabel genderLabel                birth   age  start_date  \\\n",
       "678  Enrique Maya Miranda        male  1959-11-07 00:00:00  62.0  2019-06-15   \n",
       "858       Michel Fontaine        male  1952-05-06 00:00:00  69.0  2001-01-01   \n",
       "629          Corine Mauch      female  1960-05-28 00:00:00  61.0  2009-05-01   \n",
       "584       Mihhail Kõlvart        male  1977-11-24 00:00:00  44.0  2019-04-04   \n",
       "905          Ulrik Wilbek        male  1958-04-13 00:00:00  63.0  2018-01-01   \n",
       "\n",
       "     duration                        birth_country        birth_countryLabel  \\\n",
       "678         2   http://www.wikidata.org/entity/Q77                   Uruguay   \n",
       "858        20  http://www.wikidata.org/entity/Q142                    France   \n",
       "629        12   http://www.wikidata.org/entity/Q30  United States of America   \n",
       "584         2  http://www.wikidata.org/entity/Q232                Kazakhstan   \n",
       "905         3  http://www.wikidata.org/entity/Q948                   Tunisia   \n",
       "\n",
       "                                 birth_city   birth_cityLabel   city_lon  \\\n",
       "678    http://www.wikidata.org/entity/Q1335        Montevideo  -1.650000   \n",
       "858  http://www.wikidata.org/entity/Q239078  Romans-sur-Isère  55.477778   \n",
       "629  http://www.wikidata.org/entity/Q487977         Iowa City   8.540000   \n",
       "584  http://www.wikidata.org/entity/Q491123         Kyzylorda  24.745000   \n",
       "905    http://www.wikidata.org/entity/Q3572             Tunis   9.400000   \n",
       "\n",
       "      city_lat  birth_city_lon  birth_city_lat      distance  \n",
       "678  42.816667      -56.166667      -34.866667  1.023175e+07  \n",
       "858 -21.341944        5.050833       45.045556  8.951750e+06  \n",
       "629  47.378611      -91.525000       41.655833  7.401167e+06  \n",
       "584  59.437222       65.499890       44.847900  3.156628e+06  \n",
       "905  56.450000       10.180000       36.800833  2.185042e+06  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(by='distance', ascending=False).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x720 with 16 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pandas.plotting import scatter_matrix\n",
    "\n",
    "df_plot = df[['age', 'duration', 'population', 'distance']].copy()\n",
    "for col in ['population', 'duration']:\n",
    "    df_plot[col] = df_plot[col].apply(lambda x: np.log(x) if x > 0 else 0)\n",
    "df_plot['distance'] = df_plot['distance'].apply(lambda x: np.log(x) if x > 0 else 0)\n",
    "scatter_matrix(df_plot, alpha=0.5, figsize=(10, 10), diagonal='kde');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Conclusion\n",
    "\n",
    "We have learned how to work with Wikidata and SPARQL and also how to integrate it with Python and Pandas.  Wikidata is a great database that enables queries and discoveries that would not be possible with ordinary searches on your favorite search engine. This opens up exciting new possibilities to do data science and exploratory data analysis and a fascinating new way to learn about relationships and curious findings in our accumulated human knowledge.\n",
    "\n",
    "## Resources and a Pile of Links\n",
    "\n",
    "A good read covering the history and an overview of Wikidata can be found in the article [Wikidata: a free collaborative knowledge base.](http://delivery.acm.org/10.1145/2630000/2629489/p78-vrandecic.pdf?ip=188.23.116.132&id=2629489&acc=OA&key=4D4702B0C3E38B35%2E4D4702B0C3E38B35%2E4D4702B0C3E38B35%2EB8CD93A2515AABD1&__acm__=1533116941_da1ef0b41c8a6ea97e62187e7e72de90) by Vrandečić, D., & Krötzsch, M. (2014). There is a great [SPARQL tutorial](https://www.wikidata.org/wiki/Wikidata:SPARQL_tutorial) covering many of the things mentioned here and goes into much more depth into understanding SPARQL. If you are excited about Wikidata and want to contribute, there are [Wikidata Tours](https://www.wikidata.org/wiki/Wikidata:Tours) that can guide you through the process. If you plan on doing large queries, make sure to take a look at the publicly downloadable [Wikidata dumps](https://dumps.wikimedia.org/wikidatawiki/entities/) which are regularly updated dumps of the whole Wikidata data set and here is a documentation on the [Wikibase data model](https://www.mediawiki.org/wiki/Wikibase/DataModel). Wikidata provides also a list of [Tools for programmers](https://www.wikidata.org/wiki/Wikidata:Tools/For_programmers).\n",
    "\n",
    "Here is an unstructured list of resources that contain useful documentation, tutorials or examples that use Wikidata.\n",
    "\n",
    "- [RDF Exports from Wikidata](https://tools.wmflabs.org/wikidata-exports/rdf/)\n",
    "- [Wikidata:List of properties](https://www.wikidata.org/wiki/Wikidata:List_of_properties)\n",
    "- [Wikidata:Database reports](https://www.wikidata.org/wiki/Wikidata:Database_reports)\n",
    "- [Wikidata:Database reports/List of properties/Top100](https://www.wikidata.org/wiki/Wikidata:Database_reports/List_of_properties/Top100)\n",
    "- [Wikidata:Introduction](https://www.wikidata.org/wiki/Wikidata:Introduction)\n",
    "- [Wikidata:SPARQL queries](https://www.wikidata.org/wiki/Wikidata:SPARQL_query_service/queries)\n",
    "- [Wikidata:SPARQL queries examples](https://www.wikidata.org/wiki/Wikidata:SPARQL_query_service/queries/examples)\n",
    "- [Wikidata:Creating a bot](https://www.wikidata.org/wiki/Wikidata:Creating_a_bot)\n",
    "- [Querying Wikidata About Vienna’s Tram Lines: An Introduction to SPARQL](https://noniq.at/0016/wikidata-sparql-introduction/)\n",
    "- [How US Presidents Died According to Wikidata](http://ramiro.org/notebook/us-presidents-causes-of-death/)\n",
    "- [An Ambitious Wikidata Tutorial - SlideShare](https://de.slideshare.net/_Emw/an-ambitious-wikidata-tutorial)\n",
    "- [Wikidata Graph Builder](https://angryloki.github.io/wikidata-graph-builder/), great tool to visualize Wikidata graphs\n",
    "- [Histropedia](http://histropedia.com), visualization of historical timelines"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[List of available SPARQL endpoints](https://www.w3.org/wiki/SparqlEndpoints)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}