doc2vec_hyperparopt.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Doc2Vec test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import gensim\n",
    "from gensim.models.doc2vec import Doc2Vec, TaggedDocument\n",
    "from nltk.tokenize import RegexpTokenizer\n",
    "from nltk.corpus import stopwords\n",
    "from collections import namedtuple, Counter\n",
    "from random import shuffle\n",
    "import pickle\n",
    "import pandas as pd\n",
    "import multiprocessing\n",
    "import time\n",
    "import numpy as np\n",
    "import re\n",
    "import random\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "numcores = multiprocessing.cpu_count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def standardtext(df, textfield):\n",
    "    newcolname = 'norm'+textfield\n",
    "    df[newcolname] = df[textfield].str.replace(u'\\xa0', u' ')\n",
    "    df[newcolname] = df[newcolname].str.replace(u'\\xa0', u' ')\n",
    "    df[newcolname] = df[newcolname].str.replace(u'/', u' ')\n",
    "    df[newcolname] = df[newcolname].str.replace(u'\\\\', u' ')\n",
    "    df[newcolname] = df[newcolname].str.replace(u'\\u201C', '\"')\n",
    "    df[newcolname] = df[newcolname].str.replace(u'\\u201D', '\"')\n",
    "    df[newcolname] = df[newcolname].str.replace(u'\\u2018', '\\'')\n",
    "    df[newcolname] = df[newcolname].str.replace(u'\\u2019', '\\'')\n",
    "    df[newcolname] = df[newcolname].str.replace('…', '\\'')\n",
    "    df[newcolname] = df[newcolname].str.replace('\\t', ' ')\n",
    "    df[newcolname] = df[newcolname].str.replace(r\"[^A-Za-z0-9(),!?@\\'\\`\\\"\\_\\n]\", \" \")\n",
    "    df[newcolname] = df[newcolname].str.replace(r\"[\\'\\`]s\", \"\")\n",
    "    df[newcolname] = df[newcolname].str.lower()\n",
    "    \n",
    "    # Pad punctuation with spaces on both sides\n",
    "    for char in ['.', '\"', ',', '(', ')', '!', '?', ';', ':']:\n",
    "        df[newcolname] = df[newcolname].str.replace(char, ' ' + char + ' ')\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TEST THE DISTANCE BETWEEN N DOCUMENTS AND THEMSELVES\n",
    "def testself(vectortest, N=100):\n",
    "    testdoc_id = list(np.random.choice(aotable['id'], size=N, replace=False).astype('str'))\n",
    "    indicesmatch = {}\n",
    "    cosinematch = {}\n",
    "    cosinemean = {}\n",
    "\n",
    "    for testmodel in vectortest:\n",
    "        modelname = re.sub(' ', '_', testmodel.comment)\n",
    "        indicesmatch[modelname] = []\n",
    "        cosinematch[modelname] = []\n",
    "        cosinemean[modelname] = []\n",
    "\n",
    "\n",
    "        for docs in testdoc_id:\n",
    "            # grab the document from the list of named tuples\n",
    "            testdoc = [x for x in allao if docs in x.tags][0]\n",
    "            testvec = testmodel.infer_vector(testdoc.words) # document\n",
    "            # run through the model\n",
    "            matchtest = testmodel.docvecs.most_similar([testvec], topn = model.docvecs.count)\n",
    "\n",
    "            # find the index and the cosine similarity of the match of the document to itself\n",
    "            cosinemean[modelname].append(np.mean([b for a,b in matchtest]))\n",
    "            for index,value in enumerate(matchtest):\n",
    "                if value[0] == docs:\n",
    "                    indicesmatch[modelname].append(index)\n",
    "                    cosinematch[modelname].append(value[1])\n",
    "    return indicesmatch, cosinematch, cosinemean\n",
    "        \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# PLOT TEST RESULTS\n",
    "def plotvectortest(t_ind, t_cos, t_mean):\n",
    "    plt.figure(figsize=(20,20))\n",
    "\n",
    "    plt.subplot(2,2,1)\n",
    "    for key in t_cos:\n",
    "        plt.hist(t_cos[key], bins=30, label=key, alpha=0.5)\n",
    "\n",
    "    #plt.xlim(-1, 1)\n",
    "    plt.legend(loc='upper left')\n",
    "    plt.title('Similarity to itself', fontsize=20)\n",
    "    plt.xlabel('Cosine similarity', fontsize=16)\n",
    "    plt.xticks(fontsize=14)\n",
    "    plt.ylabel('Frequency', fontsize=16)\n",
    "    plt.yticks(fontsize=14)\n",
    "    #plt.show()\n",
    "\n",
    "    plt.subplot(2,2,2)\n",
    "    for key in t_mean:\n",
    "        plt.hist(t_mean[key], bins = 30, label=key, alpha=0.5)\n",
    "\n",
    "    #plt.xlim(-1, 1)\n",
    "    plt.legend(loc='upper right')\n",
    "    plt.title('Similarity to other documents', fontsize=20)\n",
    "    plt.xlabel('Cosine similarity', fontsize=16)\n",
    "    plt.xticks(fontsize=14)\n",
    "    plt.ylabel('Frequency', fontsize=16)\n",
    "    plt.yticks(fontsize=14)    \n",
    "    #plt.show()\n",
    "\n",
    "    plt.subplot(2,2,3)\n",
    "    for key in t_ind:\n",
    "        plt.hist(t_ind[key], bins = 30, label=key, alpha=0.5)\n",
    "\n",
    "    plt.legend(loc='upper left')\n",
    "    plt.title('Rank similarity to self', fontsize=20)\n",
    "    plt.xlabel('Rank', fontsize=16)\n",
    "    plt.xticks(fontsize=14)\n",
    "    plt.ylabel('Frequency', fontsize=16)\n",
    "    plt.yticks(fontsize=14)    \n",
    "    #plt.show()\n",
    "\n",
    "    plt.subplot(2,2,4)\n",
    "    for key in t_cos:\n",
    "        plt.hist(np.array(t_cos[key]) / np.array(t_mean[key]), bins = 30, label=key, alpha=0.5)\n",
    "\n",
    "    plt.legend(loc='upper right')\n",
    "    plt.title('self:mean cosine similarity ratio', fontsize=20)\n",
    "    plt.xlabel('Cosine similarity ratio', fontsize=16)\n",
    "    plt.xticks(fontsize=14)\n",
    "    plt.ylabel('Frequency', fontsize=16)\n",
    "    plt.yticks(fontsize=14)    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        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>id</th>\n",
       "      <th>title</th>\n",
       "      <th>subtitle</th>\n",
       "      <th>city</th>\n",
       "      <th>country</th>\n",
       "      <th>location</th>\n",
       "      <th>url</th>\n",
       "      <th>physical_status</th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "      <th>keywords</th>\n",
       "      <th>description</th>\n",
       "      <th>imgurl</th>\n",
       "      <th>subdesc</th>\n",
       "      <th>normsubdesc</th>\n",
       "      <th>tokens</th>\n",
       "      <th>weirdness</th>\n",
       "      <th>weirdpct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5561</td>\n",
       "      <td>Lake Hillier</td>\n",
       "      <td>An Australian lake whose pink hue defies scien...</td>\n",
       "      <td></td>\n",
       "      <td>Australia</td>\n",
       "      <td>Australia</td>\n",
       "      <td>https://www.atlasobscura.com/places/lake-hillier</td>\n",
       "      <td></td>\n",
       "      <td>-34.094179</td>\n",
       "      <td>123.203276</td>\n",
       "      <td>wonders of salt,natural wonders,watery wonders</td>\n",
       "      <td>From a distance, Lake Hillier of Australia’s R...</td>\n",
       "      <td>https://assets.atlasobscura.com/media/W1siZiIs...</td>\n",
       "      <td>An Australian lake whose pink hue defies scien...</td>\n",
       "      <td>an australian lake whose pink hue defies scien...</td>\n",
       "      <td>[an, australian, lake, whose, pink, hue, defie...</td>\n",
       "      <td>0.132377</td>\n",
       "      <td>26.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4290</td>\n",
       "      <td>Gippsland Lakes Bioluminescence</td>\n",
       "      <td>Australian Lake set aglow by Noctiluca Scintil...</td>\n",
       "      <td>Raymond Island</td>\n",
       "      <td>Australia</td>\n",
       "      <td>Raymond Island, Australia</td>\n",
       "      <td>https://www.atlasobscura.com/places/lake-gipps...</td>\n",
       "      <td></td>\n",
       "      <td>-37.922431</td>\n",
       "      <td>147.791342</td>\n",
       "      <td>watery wonders,bioluminescence</td>\n",
       "      <td>The conditions were rare, and they were perfec...</td>\n",
       "      <td>https://assets.atlasobscura.com/media/W1siZiIs...</td>\n",
       "      <td>Australian Lake set aglow by Noctiluca Scintil...</td>\n",
       "      <td>australian lake set aglow by noctiluca scintil...</td>\n",
       "      <td>[australian, lake, set, aglow, by, noctiluca, ...</td>\n",
       "      <td>0.142318</td>\n",
       "      <td>4.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>596</td>\n",
       "      <td>The Haunted Bookshop</td>\n",
       "      <td>Occult books, Tarot, Oddities.</td>\n",
       "      <td>Melbourne</td>\n",
       "      <td>Australia</td>\n",
       "      <td>Melbourne, Australia</td>\n",
       "      <td>https://www.atlasobscura.com/places/haunted-bo...</td>\n",
       "      <td></td>\n",
       "      <td>-37.815472</td>\n",
       "      <td>144.961689</td>\n",
       "      <td>repositories of knowledge,occult,bookstores</td>\n",
       "      <td>The creepy Haunted Bookshop in Melbourne is lo...</td>\n",
       "      <td>https://assets.atlasobscura.com/media/W1siZiIs...</td>\n",
       "      <td>Occult books, Tarot, Oddities.The creepy Haunt...</td>\n",
       "      <td>occult books ,  tarot ,  oddities the creepy h...</td>\n",
       "      <td>[occult, books, tarot, oddities, the, creepy, ...</td>\n",
       "      <td>0.122837</td>\n",
       "      <td>70.29</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     id                            title  \\\n",
       "0  5561                     Lake Hillier   \n",
       "1  4290  Gippsland Lakes Bioluminescence   \n",
       "2   596             The Haunted Bookshop   \n",
       "\n",
       "                                            subtitle            city  \\\n",
       "0  An Australian lake whose pink hue defies scien...                   \n",
       "1  Australian Lake set aglow by Noctiluca Scintil...  Raymond Island   \n",
       "2                     Occult books, Tarot, Oddities.       Melbourne   \n",
       "\n",
       "     country                   location  \\\n",
       "0  Australia                  Australia   \n",
       "1  Australia  Raymond Island, Australia   \n",
       "2  Australia       Melbourne, Australia   \n",
       "\n",
       "                                                 url physical_status  \\\n",
       "0   https://www.atlasobscura.com/places/lake-hillier                   \n",
       "1  https://www.atlasobscura.com/places/lake-gipps...                   \n",
       "2  https://www.atlasobscura.com/places/haunted-bo...                   \n",
       "\n",
       "         lat         lng                                        keywords  \\\n",
       "0 -34.094179  123.203276  wonders of salt,natural wonders,watery wonders   \n",
       "1 -37.922431  147.791342                  watery wonders,bioluminescence   \n",
       "2 -37.815472  144.961689     repositories of knowledge,occult,bookstores   \n",
       "\n",
       "                                         description  \\\n",
       "0  From a distance, Lake Hillier of Australia’s R...   \n",
       "1  The conditions were rare, and they were perfec...   \n",
       "2  The creepy Haunted Bookshop in Melbourne is lo...   \n",
       "\n",
       "                                              imgurl  \\\n",
       "0  https://assets.atlasobscura.com/media/W1siZiIs...   \n",
       "1  https://assets.atlasobscura.com/media/W1siZiIs...   \n",
       "2  https://assets.atlasobscura.com/media/W1siZiIs...   \n",
       "\n",
       "                                             subdesc  \\\n",
       "0  An Australian lake whose pink hue defies scien...   \n",
       "1  Australian Lake set aglow by Noctiluca Scintil...   \n",
       "2  Occult books, Tarot, Oddities.The creepy Haunt...   \n",
       "\n",
       "                                         normsubdesc  \\\n",
       "0  an australian lake whose pink hue defies scien...   \n",
       "1  australian lake set aglow by noctiluca scintil...   \n",
       "2  occult books ,  tarot ,  oddities the creepy h...   \n",
       "\n",
       "                                              tokens  weirdness  weirdpct  \n",
       "0  [an, australian, lake, whose, pink, hue, defie...   0.132377     26.78  \n",
       "1  [australian, lake, set, aglow, by, noctiluca, ...   0.142318      4.00  \n",
       "2  [occult, books, tarot, oddities, the, creepy, ...   0.122837     70.29  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load AO data\n",
    "aotable = pickle.load(open('data/AOmasterdata-nodup-week4-clean', 'rb'))\n",
    "aotable.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TaggedDocument(['an', 'australian', 'lake', 'whose', 'pink', 'hue', 'defies', 'scientific', 'explanation', 'from', 'a', 'distance', 'lake', 'hillier', 'of', 'australia', 'recherche', 'archipelago', 'looks', 'like', 'a', 'swath', 'of', 'solid', 'bubble', 'gum', 'pink', 'draw', 'closer', 'and', 'the', 'color', 'takes', 'on', 'a', 'more', 'watery', 'translucent', 'quality', 'but', 'remains', 'unmistakably', 'pink', 'whereas', 'the', 'causes', 'behind', 'the', 'unusual', 'coloring', 'of', 'other', 'pink', 'lakes', 'such', 'as', 'the', 'nearby', 'pink', 'lake', 'and', 'senegal', 'lake', 'retba', 'have', 'been', 'definitively', 'confirmed', 'the', 'reason', 'for', 'lake', 'hillier', 'color', 'remains', 'a', 'mystery', 'theories', 'abound', 'of', 'course', 'some', 'speculate', 'that', 'lake', 'hillier', 'color', 'like', 'that', 'of', 'the', 'other', 'lakes', 'is', 'the', 'result', 'of', 'high', 'salinity', 'combined', 'with', 'the', 'presence', 'of', 'a', 'salt', 'loving', 'algae', 'species', 'known', 'as', 'dunaliella', 'salina', 'and', 'pink', 'bacteria', 'known', 'as', 'halobacteria', 'unlike', 'other', 'pink', 'lakes', 'however', 'which', 'regularly', 'change', 'colors', 'in', 'accordance', 'with', 'temperature', 'fluctuations', 'lake', 'hillier', 'maintains', 'its', 'pink', 'shade', 'year', 'round', 'the', 'water', 'retains', 'its', 'pink', 'hue', 'when', 'bottled', 'whatever', 'the', 'cause', 'the', 'water', 'does', 'not', 'appear', 'to', 'pose', 'any', 'danger', 'to', 'humans', 'swimming', 'in', 'it', 'is', 'not', 'possible', 'anyway', 'since', 'the', 'island', 'is', 'used', 'only', 'for', 'research', 'purposes', 'and', 'tourists', 'can', 'admire', 'it', 'only', 'from', 'above', 'on', 'helicopter', 'rides'], ['5561'])\n",
      "14090\n"
     ]
    }
   ],
   "source": [
    "allao = pickle.load(open('data/taggeddocs-week4-clean', 'rb'))\n",
    "print(allao[0])\n",
    "print(len(allao))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Testing the effect of vector size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100 vectors vocabulary scanned & state initialized\n",
      "200 vectors vocabulary scanned & state initialized\n",
      "300 vectors vocabulary scanned & state initialized\n",
      "400 vectors vocabulary scanned & state initialized\n",
      "500 vectors vocabulary scanned & state initialized\n",
      "600 vectors vocabulary scanned & state initialized\n",
      "Training 100 vectors\n",
      "Training 200 vectors\n",
      "Training 300 vectors\n",
      "Training 400 vectors\n",
      "Training 500 vectors\n",
      "Training 600 vectors\n",
      "CPU times: user 2h 34min 30s, sys: 24.1 s, total: 2h 34min 54s\n",
      "Wall time: 41min 36s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "initalpha = 0.05\n",
    "genstorun = 20\n",
    "alphastep = initalpha*0.9/genstorun\n",
    "\n",
    "sizetest = [\n",
    "    Doc2Vec(dm=0, dbow_words=1, vector_size=100, window=8, epochs= 50, min_count=2, alpha=initalpha, min_alpha=initalpha, workers=numcores, comment='100 vectors'),\n",
    "    Doc2Vec(dm=0, dbow_words=1, vector_size=200, window=8, epochs= 50, min_count=2, alpha=initalpha, min_alpha=initalpha, workers=numcores, comment='200 vectors'),\n",
    "    Doc2Vec(dm=0, dbow_words=1, vector_size=300, window=8, epochs= 50, min_count=2, alpha=initalpha, min_alpha=initalpha, workers=numcores, comment='300 vectors'),\n",
    "    Doc2Vec(dm=0, dbow_words=1, vector_size=400, window=8, epochs= 50, min_count=2, alpha=initalpha, min_alpha=initalpha, workers=numcores, comment='400 vectors'),\n",
    "    Doc2Vec(dm=0, dbow_words=1, vector_size=500, window=8, epochs= 50, min_count=2, alpha=initalpha, min_alpha=initalpha, workers=numcores, comment='500 vectors'),\n",
    "    Doc2Vec(dm=0, dbow_words=1, vector_size=600, window=8, epochs= 50, min_count=2, alpha=initalpha, min_alpha=initalpha, workers=numcores, comment='600 vectors')\n",
    "]\n",
    "\n",
    "for model in sizetest:\n",
    "    model.build_vocab(allao)\n",
    "    print(\"%s vocabulary scanned & state initialized\" % model.comment)\n",
    "    \n",
    "for model in sizetest: \n",
    "    print(\"Training %s\" % model.comment)\n",
    "    aoshuf = allao[:]  \n",
    "    for epoch in range(genstorun):\n",
    "        shuffle(aoshuf)\n",
    "        model.train(aoshuf, total_examples=model.corpus_count, epochs=1)\n",
    "        model.alpha -= alphastep\n",
    "        model.min_alpha = model.alpha"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "sizeindtest, sizecostest, sizemeantest = testself(sizetest, N=1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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JknRgsI9YMwdbH/EWkhGi5wKvhRAWAc2BEUA74OYY4/OVPttHIYRlwLdDCA+QJNLLgEe/xBQLvwJ6ABOAc0IIS0jmMG5H0r88Dfg3dn/IXCb+g+ThleeT7LunSOZZHkVyEWVYmnUmAC+QJOHzSR5udxzJPtoJXJwaHV3uXpJzbwxQEkJYSHJ8OpD0o38L/BIgxrgsdXxPB15KffZjgHOAp9j3xYwvJca4KYQwnCRB/ucQQhHJtCs7SS4inEoyT3PVh2bWVG395pAOGiaYJTVU/0HydObvALkknfAskqvJz5E8hOTBOnjQSa2JMT4ZQjiHZJ69USSd2ZdIbk37GrX74+EaktEZA4GhJCMdbmD30TtzSDrmnwNzM2jn/yOZX+0cks7zYantPAYQY7wrhPAmcC1JR7g5ydOZ/zdwY4xxTw9QqY32bwS+S/ID7TskHc23U+W3xxjLb+kjxvhhCOEMkttAL0jFmkWSZC4BJpGM/pAkSQcW+4g1c1D1EWOMn4UQBgE/IunDXUWSNH8NmBhjfCjNahcBtwFDSAYQBGAdkFGCOcb4eQjhPOBCYBzJ/LtHkCRlV5OMpH4gk22naWt7COE7JAneUSTHcw3J/v4DaRLMMca3Qgh5JOfXUJKpND4EngT+V4zx5Sr1IzA2hLCYpG88kuQhkxuB/yJ5CGVl55Ict3NJ9n8J8GOSB26O/JIfeZ9ijEWp0f/Xknz/v02S5N1A8vDMR2qhmVr5zSEdTMIB/P9VSdJ+lrpl7FmS2xAvqudwJEmSdACwjyhJ2hvnYJYkVfbj1PuMeo1CkiRJBxL7iJKkPXKKDEk6xIUQckhu3etNMmfdH2OMy+o3KkmSJNUn+4iSpOoywSxJ6k0yJ9iHwHzgivoNR5IkSQcA+4iSpGpxDmZJkiRJkiRJUkYcwVzF0UcfHTt37lzfYUiSJKmerFix4v0YY9v6juNAYN9YkiTp0FXdfrEJ5io6d+7M8uXL6zsMSZIk1ZMQwv/UdwwHCvvGkiRJh67q9ou/UteBSJIkSZIkSZIOTiaYJUmSJEmSJEkZMcEsSZIkSZIkScqIczBXw+eff866devYtm1bfYdySMrKyqJjx440bty4vkORJEmSJElSLTP3Vr++bO7NBHM1rFu3jhYtWtC5c2dCCPUdziElxsimTZtYt24dXbp0qe9wJEmSJEmSVMvMvdWf2si9OUVGNWzbto2jjjrKE7wehBA46qijvIIlSZIkSZJ0kDL3Vn9qI/dmgrmaPMHrj/tekiRJkiTp4Gb+p/582X1vglmSJEmSJEmSlBHnYM7AbU+vqtXtTRrUtVa3J0mSJEmSJDVU5t4aFkcwNxCXXHIJ7dq148QTT6wo27x5M4MGDeL4449n0KBBfPDBB0AyOffVV19NdnY2ubm5vPLKK3Ue35w5c9iwYUOdtyNJkiRJkiTVBfNvmTHB3ECMGzeOJ598cpeyadOmMXDgQEpKShg4cCDTpk0D4IknnqCkpISSkhLuueceLr/88jqPL5MTvKysrI6ikSRJkiRJkmrG/FtmTDA3EKeffjpt2rTZpWzhwoWMHTsWgLFjx1JYWFhRPmbMGEIInHLKKZSWlrJx48a02x01ahSLFi2q+HvcuHE88sgjlJWVcd1119GnTx9yc3O5++67K+rcfPPN5OTk0KNHD6ZMmcKCBQtYvnw5o0ePpmfPnnz66acUFRXRq1cvcnJyuOSSS9i+fTsAnTt3ZurUqfTr14/58+dzxx130L17d3JzcykoKKjVfSZJkiRJkiRVl/m3zDgHcwP2zjvv0L59ewDat2/Pu+++C8D69es57rjjKup17NiR9evXV9StrKCggHnz5jF06FA+++wzioqKmDlzJrNmzaJly5a8/PLLbN++ndNOO438/HxWrlxJYWEhy5Yto3nz5mzevJk2bdowY8YMbrnlFvLy8ti2bRvjxo2jqKiIrl27MmbMGGbOnMnEiRMByMrK4vnnnwegQ4cOrF69mqZNm1JaWlrXu0ySJEmSJEmqNvNv++YI5oNQjHG3shBC2rpnnXUWS5YsYfv27TzxxBOcfvrpNGvWjMWLF3PffffRs2dP+vbty6ZNmygpKeGZZ57h4osvpnnz5gC7XdUBeOONN+jSpQtduyYTqI8dO5alS5dWLB81alTFv3Nzcxk9ejS/+93vaNTI6x2SJEmSJEk68Jl/+4IJ5gbsmGOOqRh6v3HjRtq1awckV0zWrl1bUW/dunV06NAh7TaysrLo378/Tz31FPPmzasYJh9jZPr06RQXF1NcXMzq1avJz88nxrjHL0u5dF+wyg4//PCKfz/++ONceeWVrFixgt69e7Njx459f3BJkiRJkiRpPzD/tm8OGc3ApEFd6zsEAIYNG8bcuXOZMmUKc+fO5dxzz60onzFjBgUFBSxbtoyWLVumHZ5frqCggHvvvZfly5czZ84cAAYPHszMmTM588wzady4MatWreLYY48lPz+fqVOncsEFF+wyRL9FixZs3boVgBNOOIE1a9bw5ptvkp2dzf33388ZZ5yxW7s7d+5k7dq1DBgwgH79+vHggw/y0Ucf0apVq9rfWZIkSZIkSWoQDpTcG5h/qw4TzA3E9773PZ577jnef/99OnbsyA033MCUKVMYOXIks2bNolOnTsyfPx+AoUOHsmjRIrKzs2nevDmzZ8/e67bz8/MZM2YMw4YNo0mTJgCMHz+eNWvWcNJJJxFjpG3bthQWFjJkyBCKi4vJy8ujSZMmDB06lBtvvJFx48YxYcIEmjVrxosvvsjs2bMZMWIEO3bsoE+fPkyYMGG3dsvKyrjwwgvZsmULMUYmTZpkclmSJEmSJEn1wvxbZsK+hlMfavLy8uLy5ct3KXv99dfp1q1bPUUk8BhIkqT9J4SwIsaYV99xHAjS9Y0lSZJqm3mf+pfuGFS3X+wczJIkSZIkSZKkjDhFxiHir3/9KxdddNEuZU2bNmXZsmX1FJEkSZIkSZJ08DhU828mmA8ROTk5FBcX13cYkiRJkiRJ0kHpUM2/OUWGJEmSJEmSJCkjJpglSZIkSZIkSRkxwSxJkiRJkiRJyohzMGfi2Ztqd3sDflK725MkSZIkSZIaKnNvDYojmBuItWvXMmDAALp168Y3v/lNfv3rXwOwefNmBg0axPHHH8+gQYP44IMPAIgxcvXVV5OdnU1ubi6vvPJKncc4Z84cNmzYUOftSJIkSZIkSbXJ3FvmTDA3EI0aNeI//uM/eP311/nzn//MnXfeyX//938zbdo0Bg4cSElJCQMHDmTatGkAPPHEE5SUlFBSUsI999zD5ZdfXucxZnKSl5WV1VE0kiRJkiRJUvWYe8ucCeYGon379px00kkAtGjRgm7durF+/XoWLlzI2LFjARg7diyFhYUALFy4kDFjxhBC4JRTTqG0tJSNGzem3faoUaNYtGhRxd/jxo3jkUceoaysjOuuu44+ffqQm5vL3XffXVHn5ptvJicnhx49ejBlyhQWLFjA8uXLGT16ND179uTTTz+lqKiIXr16kZOTwyWXXML27dsB6Ny5M1OnTqVfv37Mnz+fO+64g+7du5Obm0tBQUGd7D9JkiRJkiRpT8y9Zc45mBugNWvW8Oqrr9K3b1/eeecd2rdvDyRfhHfffReA9evXc9xxx1Ws07FjR9avX19Rt7KCggLmzZvH0KFD+eyzzygqKmLmzJnMmjWLli1b8vLLL7N9+3ZOO+008vPzWblyJYWFhSxbtozmzZuzefNm2rRpw4wZM7jlllvIy8tj27ZtjBs3jqKiIrp27cqYMWOYOXMmEydOBCArK4vnn38egA4dOrB69WqaNm1KaWlpXe8+SZIkSZIkaY/MvdWMCeYG5qOPPuL888/n9ttv58gjj9xjvRjjbmUhhLR1zzrrLK6++mq2b9/Ok08+yemnn06zZs1YvHgxf/nLX1iwYAEAW7ZsoaSkhGeeeYaLL76Y5s2bA9CmTZvdtvnGG2/QpUsXunbtCiRXeO68886Kk3zUqFEVdXNzcxk9ejTnnXce5513XjX3hNQwvPTYWzWqf/I5X6ujSCRJkr6c6vZr7M9Ikhoyc2815xQZDcjnn3/O+eefz+jRo/mXf/kXAI455piK4fcbN26kXbt2QHLVZO3atRXrrlu3jg4dOqTdblZWFv379+epp55i3rx5FUPlY4xMnz6d4uJiiouLWb16Nfn5+cQY9/iFKZfuS1bZ4YcfXvHvxx9/nCuvvJIVK1bQu3dvduzYsY89IUmSJEmSJNUuc2+ZcQRzJgb8ZL83GWPk0ksvpVu3bvzoRz+qKB82bBhz585lypQpzJ07l3PPPbeifMaMGRQUFLBs2TJatmyZdoh+uYKCAu69916WL1/OnDlzABg8eDAzZ87kzDPPpHHjxqxatYpjjz2W/Px8pk6dygUXXLDLMP0WLVqwdetWAE444QTWrFnDm2++SXZ2Nvfffz9nnHHGbu3u3Lmz4imd/fr148EHH+Sjjz6iVatWtbj3JEmSJEmS1GCYe2tQuTcTzA3ECy+8wP33309OTg49e/YE4MYbb2TKlCmMHDmSWbNm0alTJ+bPnw/A0KFDWbRoEdnZ2TRv3pzZs2fvdfv5+fmMGTOGYcOG0aRJEwDGjx/PmjVrOOmkk4gx0rZtWwoLCxkyZAjFxcXk5eXRpEkThg4dyo033si4ceOYMGECzZo148UXX2T27NmMGDGCHTt20KdPHyZMmLBbu2VlZVx44YVs2bKFGCOTJk0yuSxJkiRJkqT9ytxb5sK+hlMfavLy8uLy5ct3KXv99dfp1q1bPUUk8Bio4XIOZklqeEIIK2KMefUdx4EgXd9Yhy7nYJYk1RXzPvUv3TGobr/YEcySVE01TRZLkiRJkiQd7EwwH0L++te/ctFFF+1S1rRpU5YtW1ZPEUmSJEmSJEkHh0M192aC+RCSk5NDcXFxfYchSZIkSZIkHXQO1dzbV+o7AEmSJEmSJElSw2SCWZIkSZIkSZKUERPMkiRJkiRJkqSMOAdzBu4qvqtWt3dFzytqdXuSJGn/ue3pVfusM2lQ1/0QiSRJknRwMPfWsDiCuYHYtm0bJ598Mj169OCb3/wmv/jFLwBYvXo1ffv25fjjj2fUqFF89tlnAGzfvp1Ro0aRnZ1N3759WbNmTZ3HePvtt/PJJ5/UeTuSJEmSJElSbTL3ljkTzA1E06ZNWbJkCa+99hrFxcU8+eST/PnPf2by5MlMmjSJkpISWrduzaxZswCYNWsWrVu35s0332TSpElMnjy5zmPM5CQvKyuro2gkSZIkSZKk6jH3ljkTzA1ECIEjjjgCgM8//5zPP/+cEAJLlixh+PDhAIwdO5bCwkIAFi5cyNixYwEYPnw4RUVFxBjTbrtv3778/e9/r/i7f//+rFixgo8//phLLrmEPn360KtXLxYuXAgkJ+a1115LTk4Oubm5TJ8+nTvuuIMNGzYwYMAABgwYAMBDDz1ETk4OJ5544i5fsiOOOIKf//zn9O3blxdffJEpU6bQvXt3cnNzufbaa2t5z0mSJEmSJEl7Z+4tc87B3ICUlZXRu3dv3nzzTa688kq+/vWv06pVKxo1Sg5jx44dWb9+PQDr16/nuOOOA6BRo0a0bNmSTZs2cfTRR++23YKCAh5++GFuuOEGNm7cyIYNG+jduzc//elPOfPMM/ntb39LaWkpJ598Mt/5zne47777WL16Na+++iqNGjVi8+bNtGnThltvvZVnn32Wo48+mg0bNjB58mRWrFhB69atyc/Pp7CwkPPOO4+PP/6YE088kalTp7J582YuvfRSVq5cSQiB0tLS/bdDJUmSJEmSpBRzb5kxwdyAHHbYYRQXF1NaWsp3v/tdXn/99d3qhBAA0l4xKV9W1ciRIxk0aBA33HADDz/8MCNGjABg8eLFPProo9xyyy1AMhfN22+/zTPPPMOECRMqvlxt2rTZbZsvv/wy/fv3p23btgCMHj2apUuXct5553HYYYdx/vnnA3DkkUeSlZXF+PHj+ed//mfOPvvsmu4WSarxAyB8wIMkSV946bG36jsESZIOCObeMuMUGQ1Qq1at6N+/P3/+858pLS1lx44dAKxbt44OHToAyRWVtWvXArBjxw62bNmS9mQ5vemhAAAgAElEQVQEOPbYYznqqKP4y1/+wrx58ygoKACSL8ojjzxCcXExxcXFvP3223Tr1o0Y4x6/MOX2dEsAQFZWFocddhiQXOF56aWXOP/88yksLGTIkCE12xmSJEmSJElSLTL3VjOOYM5AfYx8e++992jcuDGtWrXi008/5ZlnnmHy5MkMGDCABQsWUFBQwNy5czn33HMBGDZsGHPnzuXUU09lwYIFnHnmmXs9MQsKCrj55pvZsmULOTk5AAwePJjp06czffp0Qgi8+uqr9OrVi/z8fH7zm9/Qv3//XYbpt2jRgq1bt3L00UfTt29frrnmGt5//31at27NQw89xFVXXbVbux999BGffPIJQ4cO5ZRTTiE7O7tudqAkSZIkSZIaBHNvDSv3ZoK5gdi4cSNjx46lrKyMnTt3MnLkSM4++2y6d+9OQUEBP/vZz+jVqxeXXnopAJdeeikXXXQR2dnZtGnTht///vd73f7w4cO55ppruP766yvKrr/+eiZOnEhubi4xRjp37swf//hHxo8fz6pVq8jNzaVx48Z8//vf54c//CGXXXYZZ511Fu3bt+fZZ5/lpptuYsCAAcQYGTp0aMUXsLKtW7dy7rnnsm3bNmKM3HbbbbW74yRJkiRJkqR9MPeWubC34dSHory8vLh8+fJdyl5//XW6detWTxEJPAY6MOyP+QlPPudrdd7Gwcg5mFWfbnt61T7rTBrUdT9EotoSQlgRY8yr7zgOBOn6xjr41HYfx/6MJKmmzPvUv3THoLr9YkcwSzro/Wn+AzWq/60Ro+soEkmSJEmSpIOLCeZDyFNPPcXkyZN3KevSpQt/+MMf6ikiSZIkSQer96bPqFa9tlf9sI4jkSRp/zhUc28mmA8hgwcPZvDgwfUdhiRJkiRJknTQOVRzb1+p7wAkSZIkSZIkSQ2TCWZJkiRJkiRJUkZMMEuSJEmSJEmSMuIczBmo7sMqqsuHWkiSJElS/bir+K5q1bui5xV1HIkkqZy5t4bFEcwNTFlZGb169eLss88GYPXq1fTt25fjjz+eUaNG8dlnnwGwfft2Ro0aRXZ2Nn379mXNmjV1Htvtt9/OJ598UuftSJIkSZIkSXXB3FvNmWBuYH7961/TrVu3ir8nT57MpEmTKCkpoXXr1syaNQuAWbNm0bp1a958800mTZrE5MmT6zy2TE7ysrKyOopGkiRJkiRJqhlzbzVngrkBWbduHY8//jjjx48HIMbIkiVLGD58OABjx46lsLAQgIULFzJ27FgAhg8fTlFRETHGtNvt27cvf//73yv+7t+/PytWrODjjz/mkksuoU+fPvTq1YuFCxcCyYl57bXXkpOTQ25uLtOnT+eOO+5gw4YNDBgwgAEDBgDw0EMPkZOTw4knnrjLl+yII47g5z//OX379uXFF19kypQpdO/endzcXK699tpa3muSJEmSJEnSvpl7y4xzMDcgEydO5Oabb2br1q0AbNq0iVatWtGoUXIYO3bsyPr16wFYv349xx13HACNGjWiZcuWbNq0iaOPPnq37RYUFPDwww9zww03sHHjRjZs2EDv3r356U9/yplnnslvf/tbSktLOfnkk/nOd77Dfffdx+rVq3n11Vdp1KgRmzdvpk2bNtx66608++yzHH300WzYsIHJkyezYsUKWrduTX5+PoWFhZx33nl8/PHHnHjiiUydOpXNmzdz6aWXsnLlSkIIlJaW7qe9KUmSJEmSJH3B3FtmHMHcQPzxj3+kXbt29O7du6Is3VWREMI+l1U1cuRI5s+fD8DDDz/MiBEjAFi8eDHTpk2jZ8+e9O/fn23btvH222/zzDPPMGHChIovV5s2bXbb5ssvv0z//v1p27YtjRo1YvTo0SxduhSAww47jPPPPx+AI488kqysLMaPH89//ud/0rx582rvE0mSJEmSJKk2mHvLnCOYG4gXXniBRx99lEWLFrFt2zY+/PBDJk6cSGlpKTt27KBRo0asW7eODh06AMkVlbVr19KxY0d27NjBli1b0p6MAMceeyxHHXUUf/nLX5g3bx533303kHxRHnnkEb7xjW/sUj/GuMcvTOU6e5KVlcVhhx0GJFd4XnrpJYqKivj973/PjBkzWLJkSbX3iyRJkiRpH569qfp1B/yk7uKQpAOYubfMmWDOQNurfrjf27zpppu46aakU/Dcc89xyy238MADDzBixAgWLFhAQUEBc+fO5dxzzwVg2LBhzJ07l1NPPZUFCxZw5pln7vXELCgo4Oabb2bLli3k5OQAMHjwYKZPn8706dMJIfDqq6/Sq1cv8vPz+c1vfkP//v13GabfokULtm7dytFHH03fvn255ppreP/992ndujUPPfQQV1111W7tfvTRR3zyyScMHTqUU045hezs7DrYe5IkSZIkSWoozL01rNybU2Q0cP/+7//OrbfeSnZ2Nps2beLSSy8F4NJLL2XTpk1kZ2dz6623Mm3atL1uZ/jw4fz+979n5MiRFWXXX389n3/+Obm5uZx44olcf/31AIwfP55OnTqRm5tLjx49ePDBBwG47LLLOOussxgwYADt27fnpptuYsCAAfTo0YOTTjqp4gtY2datWzn77LPJzc3ljDPO4LbbbqutXSNJkiRJkiR9Kebe9i3sbTj1oSgvLy8uX758l7LXX3+dbt261VNEAo+Bvpw/zX+gRvW/NWJ02vKXHnurNsLZq5PP+Vqdt3Ewuqv4rhrVv6LnFXUUiQ5Ftz29ap91Jg3quh8iUW0JIayIMebVdxwHgnR9Yx18aruPU96feW/6jGrVr49RapVVtx/RoPsPTpEh6QBn3qf+pTsG1e0XO4JZkiRJkiRJkpQR52A+hDz11FNMnjx5l7IuXbrwhz/8oZ4ikiRJkiQdUBztLEkZO1RzbyaYDyGDBw9m8ODB9R2GJEmSJEmSdNA5VHNvTpEhSZIkSZIkScqICWZJkiRJkiRJUkZMMEuSJEmSJEmSMuIczBl46bG3anV7J5/ztVrdniRJkiRJktRQmXtrWBzB3IB07tyZnJwcevbsSV5eHgCbN29m0KBBHH/88QwaNIgPPvgAgBgjV199NdnZ2eTm5vLKK6/UeXxz5sxhw4YNdd6OJEmSJEmSVNvMvWXGBHMD8+yzz1JcXMzy5csBmDZtGgMHDqSkpISBAwcybdo0AJ544glKSkooKSnhnnvu4fLLL6/z2DI5ycvKyuooGkmSJEmSJKlmzL3VnAnmBm7hwoWMHTsWgLFjx1JYWFhRPmbMGEIInHLKKZSWlrJx48a02xg1ahSLFi2q+HvcuHE88sgjlJWVcd1119GnTx9yc3O5++67K+rcfPPN5OTk0KNHD6ZMmcKCBQtYvnw5o0ePpmfPnnz66acUFRXRq1cvcnJyuOSSS9i+fTuQXA2aOnUq/fr1Y/78+dxxxx10796d3NxcCgoK6mpXSZIkSZIkSTVi7m3fnIO5AQkhkJ+fTwiBH/zgB1x22WW88847tG/fHoD27dvz7rvvArB+/XqOO+64inU7duzI+vXrK+pWVlBQwLx58xg6dCifffYZRUVFzJw5k1mzZtGyZUtefvlltm/fzmmnnUZ+fj4rV66ksLCQZcuW0bx5czZv3kybNm2YMWMGt9xyC3l5eWzbto1x48ZRVFRE165dGTNmDDNnzmTixIkAZGVl8fzzzwPQoUMHVq9eTdOmTSktLa3r3ShJkiRJkiTtxtxbZhzB3IC88MILvPLKKzzxxBPceeedLF26dI91Y4y7lYUQ0tY966yzWLJkCdu3b+eJJ57g9NNPp1mzZixevJj77ruPnj170rdvXzZt2kRJSQnPPPMMF198Mc2bNwegTZs2u23zjTfeoEuXLnTt2hVIrvBUjnfUqFEV/87NzWX06NH87ne/o1Ejr3lIkiRJkiRp/zP3lhmzeQ1Ihw4dAGjXrh3f/e53eemllzjmmGPYuHEj7du3Z+PGjbRr1w5IrpqsXbu2Yt1169ZVrF9VVlYW/fv356mnnmLevHl873vfA5IvyvTp0xk8ePAu9Z988sk9fmHKpfuSVXb44YdX/Pvxxx9n6dKlPProo/zqV7/i73//u4lmSZIk6QDwP68t2medf+oxdD9EIklS3TP3lhmzeBk4+Zyv7fc2P/74Y3bu3EmLFi34+OOPWbx4MT//+c8ZNmwYc+fOZcqUKcydO5dzzz0XgGHDhjFjxgwKCgpYtmwZLVu2TDtEv1xBQQH33nsvy5cvZ86cOQAMHjyYmTNncuaZZ9K4cWNWrVrFscceS35+PlOnTuWCCy7YZZh+ixYt2Lp1KwAnnHACa9as4c033yQ7O5v777+fM844Y7d2d+7cydq1axkwYAD9+vXjwQcf5KOPPqJVq1a1vxMlSZIkSZJ0wDP31rBybyaYG4h33nmH7373uwDs2LGDCy64gCFDhtCnTx9GjhzJrFmz6NSpE/Pnzwdg6NChLFq0iOzsbJo3b87s2bP3uv38/HzGjBnDsGHDaNKkCQDjx49nzZo1nHTSScQYadu2LYWFhQwZMoTi4mLy8vJo0qQJQ4cO5cYbb2TcuHFMmDCBZs2a8eKLLzJ79mxGjBjBjh076NOnDxMmTNit3bKyMi688EK2bNlCjJFJkyaZXJYkSZIkSdJ+Ze4tc2Ffw6kPNXl5eXH58uW7lL3++ut069atniISeAz05fxp/gM1qv+tEaPTlr/02Fu1Ec5e1cdV2oPBXcV31aj+FT2vqKNIdCi67elV+6wzaVDX/RCJaksIYUWMMa++4zgQpOsb6+Cztz5OJlNklPdn3ps+o1rtt73qh9WqV1eq249o0P2HZ2+qm+0O+EndbFfSIce8T/1Ldwyq2y/2IX+SJEmSJEmSpIw4RcYh5K9//SsXXXTRLmVNmzZl2bJl9RSRpPpW3ZFF5ep7hJEkSZIkSQeqQzX3ZoL5EJKTk0NxcXF9hyFJkiRJNdJQptsod0hMuyFJ2s2hmntzigxJkiRJkiRJUkZMMEuSJEmSJEmSMmKCWZIkSZIkSZKUEedgzsCf5j9Qq9v71ojRtbo9SZIkSZIkqaEy99awOIK5ASktLWX48OGccMIJdOvWjRdffJHNmzczaNAgjj/+eAYNGsQHH3wAQIyRq6++muzsbHJzc3nllVfqPL45c+awYcOGOm9HkiRJ0oHrpcfe4qXH3uJv77bd50uSpAOJubfMmGBuQK655hqGDBnCypUree211+jWrRvTpk1j4MCBlJSUMHDgQKZNmwbAE088QUlJCSUlJdxzzz1cfvnldR5fJid5WVlZHUUjSZIkSZIkVZ+5t8yYYG4gPvzwQ5YuXcqll14KQJMmTWjVqhULFy5k7NixAIwdO5bCwkIAFi5cyJgxYwghcMopp1BaWsrGjRvTbnvUqFEsWrSo4u9x48bxyCOPUFZWxnXXXUefPn3Izc3l7rvvrqhz8803k5OTQ48ePZgyZQoLFixg+fLljB49mp49e/Lpp59SVFREr169yMnJ4ZJLLmH79u0AdO7cmalTp9KvXz/mz5/PHXfcQffu3cnNzaWgoKBO9p8kSVJDFEI4PYTwaAhhfQghhhDGVVkeQgi/DCFsCCF8GkJ4LoTwzSp1WocQ7g8hbEm97g8htNqvH0SSJOkAZ+4tc87B3EC89dZbtG3blosvvpjXXnuN3r178+tf/5p33nmH9u3bA9C+fXveffddANavX89xxx1XsX7Hjh1Zv359Rd3KCgoKmDdvHkOHDuWzzz6jqKiImTNnMmvWLFq2bMnLL7/M9u3bOe2008jPz2flypUUFhaybNkymjdvzubNm2nTpg0zZszglltuIS8vj23btjFu3DiKioro2rUrY8aMYebMmUycOBGArKwsnn/+eQA6dOjA6tWradq0KaWlpXW9KyVJkhqSI4C/AfelXlX9GPhXYBzwBvBz4OkQwjdijFtTdR4EOgFnARG4F7gfOKdOI5ckSWpAzL1lzhHMDcSOHTt45ZVXuPzyy3n11Vc5/PDDK4bkpxNj3K0shJC27llnncWSJUvYvn07TzzxBKeffjrNmjVj8eLF3HffffTs2ZO+ffuyadMmSkpKeOaZZ7j44otp3rw5AG3atNltm2+88QZdunSha9euQHKFZ+nSpRXLR40aVfHv3NxcRo8eze9+9zsaNfKahyTp4HPb06v2+ZLSiTEuijH+NMa4ANhZeVlIOncTgWkxxkdijH8DxgItgAtSdboBQ4DLYox/ijG+CPwAODuE8I39+VkkSZIOZObeMmeCuYHo2LEjHTt2pG/fvgAMHz6cV155hWOOOaZi+P3GjRtp165dRf21a9dWrL9u3To6dOiQdttZWVn079+fp556innz5lUMlY8xMn36dIqLiykuLmb16tXk5+cTY9zjF6Zcui9ZZYcffnjFvx9//HGuvPJKVqxYQe/evdmxY8c+9oYkSZKALsBXgcXlBTHGT4GlwLdSRacCHwF/qrTeC8DHlepIkiQd8sy9Zc7hohn41ojR+73Nr371qxx33HG88cYbfOMb36CoqIju3bvTvXt35s6dy5QpU5g7dy7nnnsuAMOGDWPGjBkUFBSwbNkyWrZsmXaIfrmCggLuvfdeli9fzpw5cwAYPHgwM2fO5Mwzz6Rx48asWrWKY489lvz8fKZOncoFF1ywyzD9Fi1asHVrcifmCSecwJo1a3jzzTfJzs7m/vvv54wzztit3Z07d7J27VoGDBhAv379ePDBB/noo49o1cppASVJkvbhq6n3d6qUvwMcW6nOe7HSL5AYYwwhvFtp/V2EEC4DLgPo1KlTrQYsfVkv/+PlvS5fU3wXAFf0vKLW274rtW3pQJTJ3VCTBnWtg0ik2mHurWHl3kwwNyDTp09n9OjRfPbZZ3zta19j9uzZ7Ny5k5EjRzJr1iw6derE/PnzARg6dCiLFi0iOzub5s2bM3v27L1uOz8/nzFjxjBs2DCaNGkCwPjx41mzZg0nnXQSMUbatm1LYWEhQ4YMobi4mLy8PJo0acLQoUO58cYbGTduHBMmTKBZs2a8+OKLzJ49mxEjRrBjxw769OnDhAkTdmu3rKyMCy+8kC1bthBjZNKkSSaXJUmSaqbq8JVQpSzd8Jaqdb6oHOM9wD0AeXl5ex8aI0mSdBAx95YZE8wNSM+ePVm+fPlu5UVFRbuVhRC48847q73txo0bs2nTpl3KvvKVr3DjjTdy44037lZ/ypQpTJkyZZey888/n/PPP7/i74EDB/Lqq6/utu6aNWt2abd8wnFJkiTVyD9S718F1lYqb8cXo5r/AbQLIYTyUcypuZvbsvvIZ0mSpEOaubfMOAezJEmS1DCtJkkgDyovCCFkAd/mizmXXwSOIJmLudypwOHsOi+zJEmSlBFHMB9C/vrXv3LRRRftUta0aVOWLVtWTxFJUv2oyzkU62LOR0mHrhDCEUB26s+vAJ1CCD2BzTHGt0MItwP/FkJYCawCfkbyUL8HAWKMr4cQngTuDiF8n2RqjLuBP8YY39jPH0eSJOmgdqjm3g7IBHMI4XTgWqA30AG4OMY4p9LyAPyC5OEjrYFlwJUxxr9XqtMauAMYlip6FLgqxliaSUzVeXrjgS4nJ4fi4uL6DqPG9vVUTEmSpINYHvBspb9vSL3mAuOAm4FmwJ180S/OjzFurbTOaJJ+8eLU348CP6zTqCVJkmrI3Fv9+bK5twN1iowjgL8B1wCfpln+Y+BfgauAPsC7wNMhhBaV6jwInAScBQxJ/fv+TILJyspi06ZNJjrrQYyRTZs2kZWVVd+hSJIk7XcxxudijCHNa1xqeYwx/jLG2D7GmBVjPCPG+Lcq29gcY7wwxnhk6nVhpoMuJEmS6oK5t/pTG7m3A3IEc4xxEbAIIIQwp/Ky1OjlicC0GOMjqbKxJEnmC0hu/+tGklTuF2P8U6rOD4D/CiF8o6a3A3bs2JF169bx3nvvfbkPpoxkZWXRsWPH+g5DkiRJkiRJdcDcW/36srm3AzLBvA9dSJ6UXX6LHzHGT0MIS4FvkcwpdyrJ3HOVH1zyAvBxqk6NEsyNGzemS5cuXzJsSZIkSZIkSVWZe2vYGmKC+aup93eqlL8DHFupznux0rj6GGMMIbxbaf0KIYTLSOZzplOnTrUesCRJderZm2pvWwN+UnvbkiRJkiQd9A7UOZiro+qkLKFKWbpJW6rWSSrGeE+MMS/GmNe2bdtaDFGSJEmSJEmSDl4NcQTzP1LvXwXWVipvxxejmv8BtAshhPJRzKm5m9uy+8hnSZIkSVI9eW/6jPoOQdqn255eVeN1Jg3qWgeR1J6D8TNJqh8NcQTzapIE8qDyghBCFvBtvphz+UXgCJK5mMudChzOrvMyS5IkSZIkSZIydECOYA4hHAFkp/78CtAphNAT2BxjfDuEcDvwbyGElcAq4GckD/V7ECDG+HoI4Ung7hDC90mmxrgb+GOMsUYP+JMkSZIkSZIkpXegjmDOA15NvZoBN6T+PTW1/GbgVuBOYDnQHsiPMW6ttI3RwGvAYuCp1L8v2h/BS5IkSZIkSdKh4IAcwRxjfI5k1PGelkfgl6nXnupsBi6s5dAkSZIkSZIkSSkHZIJZkiRJkpTen+Y/sM863xoxutrbWf/GB18qnv95bVHa8s/e31Dx7w5H9/hSbUiSpAPXgTpFhiRJkiRJkiTpAGeCWZIkSZIkSZKUERPMkiRJkiRJkqSMOAezpHpTnfkDJUmSJEmSdOAywSxJkiRJBxkv5EuSpP3FKTIkSZIkSZIkSRkxwSxJkiRJkiRJyogJZkmSJEmSJElSRkwwS5IkSZIkSZIyYoJZkiRJkiRJkpSRRvUdgCRJkiRJkuC2p1fVdwiSVGOOYJYkSZIkSZIkZcQEsyRJkiRJkiQpIyaYJUmSJEmSJEkZcQ5mSTqAvPTYWzWqf/I5X9ut7L3pM2orHEmSJEmSpL0ywSxJkiRJqhd/e7dtjep/8EmPatW7q/iuTMKRJEkZcIoMSZIkSZIkSVJGTDBLkiRJkiRJkjJiglmSJEmSJEmSlBETzJIkSZIkSZKkjJhgliRJkiRJkiRlxASzJEmSJEmSJCkjJpglSZIkSZIkSRkxwSxJkiRJkiRJyogJZkmSJEmSJElSRkwwS5IkSZIkSZIy0qi+A5AkSZIk1b71b3xQ3yFIkqRDgCOYJUmSJEmSJEkZMcEsSZIkSZIkScqICWZJkiRJkiRJUkZMMEuSJEmSJEmSMmKCWZIkSZIkSZKUERPMkiRJkiRJkqSMmGCWJEmSJEmSJGXEBLMkSZIkSZIkKSMmmCVJkiRJkiRJGTHBLEmSJEmSJEnKSKP6DkCSJEmSpNrQef6yatVbM6JvHUciSdKhwxHMkiRJkiRJkqSMmGCWJEmSJEmSJGXEBLMkSZIkSZIkKSPOwSxJkr7w7E37rjPgJ3UfhyRJkiSpQXAEsyRJkiRJkiQpIyaYJUmSJEmSJEkZMcEsSZIkSZIkScqICWZJkiRJkiRJUkZ8yJ+kWvGn+Q/UdwiSJEmSJEnazxzBLEmSJEmSJEnKiCOYJUmSJEmqB3cV31Wtelf0vKKOI5Gq57anV9V4nUmDutZBJJIOJI5gliRJkiRJkiRlxASzJEmSJEmSJCkjTpEhSTogVfeWUUmSJEmSVH8cwSxJkqT/x969R+t51feB//5khdhu5FrUpr5MhWEckwZiJ6lTuw6uYwaRaZmyaDJOMhDiTtMqjRMyOExIXC51QxIu7URQwF2I1QlkjVmkCi3LbjKzkBkbcGQbe5IYXMDC4+tIviMhGV8UW3v+OK/M4Vjyec+j93lv5/NZ66zzvs+zn2f/yFpZbH35nb0BAAA6ETADAAAAANCJgBkAAAAAgE4EzAAAAAAAdCJgBgAAAACgk7WTLgAAVuq0rTcNPfbui87psRIAAABY3XQwAwAAAADQiQ5mAAAA6NNdXxx+7EvO768OAOiBDmYAAAAAADoRMAMAAAAA0ImAGQAAAACATgTMAAAAAAB0ImAGAAAAAKATATMAAAAAAJ0ImAEAAAAA6ETADAAAAABAJwJmAAAAAAA6ETADAAAAANCJgBkAAAAAgE4EzAAAAAAAdCJgBgAAAACgEwEzAAAAAACdCJgBAAAAAOhEwAwAAAAAQCcCZgAAAAAAOhEwAwAAAADQiYAZAAAAAIBOBMwAAAAAAHQiYAYAAAAAoBMBMwAAAAAAnQiYAQAAAADoRMAMAAAAAEAnAmYAAAAAADoRMAMAAAAA0ImAGQAAAACATgTMAAAAAAB0ImAGAIAZVVVHVdW7q+quqnpy8Pt3qmrtojFVVZdX1a6qeqKqrquql0+ybgAA5sfa5YcAMGnf/tLNh7z+8N1/OuZKhvfwhz489NgT3/yrPVYCMNd+M8mvJLk4yVeSnJnkE0meSvLuwZi3JXlrkn+S5PYk70qyrape1lrbN+6CAQCYLwJmAACYXeclubq1dvXg+91VdVWSc5KF7uUkb0ny3tbapwfXLk7yUJI3JPno+EsGAGCe2CIDAABm1/VJLqyqH0iSqvrBJK9KcvBPXF6S5KQknz34QGvtiSRfyEI4DQAAR0QHMwAAzK73JVmX5KtV9UwW1ve/21q7YnD/pMHvB5c892CSUw/1wqralGRTkmzYsGHkBcM0OG3rTcuOufuic8ZQyYy79j3Djbvwsn7rAGCidDADAMDs+tkkv5CF7S5+dPD5kqr6xSXj2pLvdYhrCwNb29JaO7u1dvaJJ5446noBAJgzOpgBAGB2/Zsk/7a19qnB969U1YuTXJbkPyR5YHD9pCT3LXruRXluVzMAAKyYDmYAAJhdxyZ5Zsm1Z/Kddf5dWQiZNx68WVVHJzk/yfZxFAgAwHybyYC5qo6qqndX1V1V9eTg9+9U1dpFY6qqLq+qXVX1RFVdV1Uvn2TdAAAwYlcn+a2qem1VnVZV/zjJryf5z0nSWmtJPjAY81NV9YokH0/yWJJPTqhmAADmyKxukSmkZKMAACAASURBVPGbSX4lycVJvpLkzCSfSPJUkncPxrwtyVuT/JMktyd5V5JtVfWy1tq+cRcMAAA9eHMW1r9XZGHbi/uTfCzJby8a8/4kxyT5SJL1SW5K8hprYpgDwx6yBwA9mtWA+bwkV7fWrh58v7uqrkpyTrLQvZzkLUne21r79ODaxUkeysIBKB8df8kAADBag5D4LYOfw41pSS4f/AAAwEjN5BYZSa5PcmFV/UCSVNUPJnlVkj8d3H9JFg4y+ezBB1prTyT5QhbCaQAAAAAAjtCsdjC/L8m6JF+tqmey8J/jd1trVwzunzT4vfRk7AeTnLr0ZVW1KcmmJNmwYUMvBQOwOlzxl1csP2jgkh++ZPlB/vR14jZv2zHpEgAAAKbWrHYw/2ySX8jCdhc/Ovh8SVX94pJxbcn3OsS1tNa2tNbObq2dfeKJJ/ZRLwAAAADA3JnVDuZ/k+TfttY+Nfj+lap6cZLLkvyHJA8Mrp+U5L5Fz70oz+1qBgAAAACgg1kNmI9N8sySa8/kOx3Zd2UhZN6Y5OYkqaqjk5yf5DfGVCMAAAAz6rStNw017u6LzhntxHd98TmXrjjEtcO55PgzR1kNACxrVgPmq5P8VlXdleS/JvmRJL+e5A+ThZOyq+oDSd5eVV9PsiPJO5I8luSTkykZAAAAAGC+zGrA/OYk705yRRa2vbg/yceS/PaiMe9PckySjyRZn+SmJK9pre0bb6kAMGeGPXjwwsv6rWMEHOAHAABwZGYyYB6ExG8Z/BxuTEty+eAHAAAAAIARW7P8EAAAAAAAeC4BMwAAAAAAnQiYAQAAAADoZCb3YAb6t33rlZMuAQAAAIApp4MZAAAAAIBOBMwAAAAAAHQiYAYAAAAAoBN7MAMAANCrXY/cOtS4U044q+dKAIBR08EMAAAAAEAnOpiBubHz9t0rGn/qy9b3VAkAAADA6qCDGQAAAACATgTMAAAAAAB0ImAGAAAAAKATATMAAAAAAJ045A9gie1brzzk9ec7RPDFZ/3DvspZFR7+0Iefc+20B26eQCUAAADASuhgBgAAAACgEwEzAAAAAACdCJgBAAAAAOhEwAwAAAAAQCcCZgAAAAAAOhEwAwAAAADQiYAZAAAAAIBOBMwAAAAAAHQiYAYAAAAAoBMBMwAAAAAAnayddAEAk7Lz9t2TLmHsbnvoxBU/84oXPfzs54c/9OFRlgMAAADMOB3MAAAAAAB0ImAGAAAAAKATATMAAAAAAJ3YgxkAAGCGrMZzJACA6SVgBgD6ce17lh9z4WX91wEAAEBvbJEBAAAAAEAnAmYAAAAAADoRMAMAAAAA0Ik9mAEAAKbE9q1XTroEAIAV0cEMAAAAAEAnAmYAAAAAADoRMAMAAAAA0ImAGQAAAACATgTMAAAAAAB0ImAGAAAAAKCTtZMuAACA4WzetuN571+68YwxVQIAALBABzMAAAAAAJ0ImAEAAAAA6ETADAAAAABAJ/ZgBgAAABix5c5OAJgXOpgBAAAAAOhEwAwAAAAAQCcCZgAAAAAAOhEwAwAAAADQiYAZAAAAAIBO1k66AAAAAGbH/p27Jl0CADBFBMwAI3DPrX+64mdefNY/7KESYFZt3rZj0iUAAACsmC0yAAAAAADoRMAMAAAAAEAnAmYAAAAAADoRMAMAAAAA0IlD/gBgQq74yyuWH7Tny0mSS44/s+dqZo9D8QAAACZPBzMAAAAAAJ0ImAEAAAAA6ETADAAAAABAJ/ZgBgAAAPpz7XuGH3vhZf3VAUAvRh4wV9X3tdYeG/V7gdVn5+27J10CAHRmXQwAwGrQxxYZD1TVR6vqR3p4NwAAzArrYgAA5l4fAfMHkvwPSW6pqpur6p9W1bE9zAMAANPMuhgAgLk38oC5tfaOJBuSXJTkm0k+lmRXVX2oql4x6vkAAGAaWRcDALAa9NHBnNbaM621/9Ra+8kk35/k32dhYX1rVV1fVT9fVd/Tx9wAADAtrIsBAJh3Iz/k7xAeTbIrC10bL0pyUpJPJPndqvq51toNY6gBAAAmzboY5s2ee5K79k+6ClZo87Ydky4BYK700sGcJFV1TlX970l2Jvm9JH+W5Edba6cn+aEk9ybZ0tf8AAAwDayLAQCYZyPvYK6qX07yS1lYLO9I8vYkH2+tfevgmNbaV6vqnUmuGfX8AAAwDayLAQBYDfrYIuODSa5O8tbW2ueeZ9w3krynh/kBAGAaWBcDADD3+giYT2ut7VpuUGttZ5J39jA/AABMA+tiAADmXh8B87FV9crW2vVLb1TVjyd5oLX2//YwLwAATBPrYlihXY/c+rz39+3fm3XHvfSw93c/ftZQ86w/9vnnAQCG19cWGbcnec5COsk/TnJGktf1MC8AU+zmB26edAkA42ZdDADA3FvTwzt/LMl1h7l3XZJzepgTAACmjXUxAABzr4+A+bgkTx7m3v4kf72HOQEAYNpYFwMAMPf6CJjvTHLhYe5dmOSeHuYEAIBpY10MAMDc6yNg/j+S/HpV/VJVfU+SVNX3VNUvJbk0yR/2MCcAAEwb62IAAOZeH4f8vS/J303y75N8uKoeTnLCYK7PJHlvD3MCAMC0sS6GIezbv3fSJQAAR2DkAXNr7Zkkr6+q1yTZmORvJHkkyWdba9eMej4AAJhG1sUAAKwGfXQwJ0laa59N8tm+3g8AALPAuhgAgHnWW8CcJFX1wiRHL73eWtvV57wAADBNrIsBAJhXIw+Yq2pdkt9P8nNJjj3MsKNGPS8AAEwT62IAAFaDPjqYP5zkZ5J8PMlXkjzVwxwAADDtrIuZOft3aqoHAFamj4D5HyR5W2vtQz28G2BufPtLN0+6hKHc9tCJKxr/ihc93FMlADPHuhgAgLm3pqd3fq2H9wIAwCyxLgYAYO71ETD/xySv7eG9AAAwS6yLAQCYe31skfFfkvy7qvprSf40yTeXDmitfaGHeQEAYJpYFwMAMPf6CpiT5KVJ/lmStuheDb47LRsAgHlnXQwAwNzrI2De2MM7ATiElR7AB8BYWRfzXbZvvXLSJQCM3eZtO1b8zKUbz+ihEqAvIw+YW2ufG/U7AQBg1lgXAwCwGvRxyF+SpKrWV9V/X1VvrKr1g2vf09d8AAAwjfpeF1fVyVX1iap6uKqerKqvVtUFi+5XVV1eVbuq6omquq6qXj6q+QEAWN16CZir6j1JdmXhMJM/TPKSwa0/qap39DEnAABMm77XxVV1fJI/y8Kezq9N8reTvDnJQ4uGvS3JWwfXf2xwb1tVrTvS+QEAYOQBc1X9ZpJLk7wnyY9nYbF70NVZWPgCAMBcG9O6+G1J7m+t/UJr7Uuttbtaa59rrX1tUEMleUuS97bWPt1auy3JxUnWJXnDCOYHAGCV66ODeVOSd7fWfjvJl5bc+0aS03uYEwAAps041sWvT3JTVf1RVT1UVX9ZVb86CJaThY7pk5J89uADrbUnknwhyXmHemFVbaqqW6rqlocffngEJQIAMM9Gfshfkv8myfbD3Nuf5Pt6mBMA5toVe768ovGXHH9mT5UAKzCOdfFLk1ySZHOS9yb54SQfGtz7cBbC5SR5cMlzDyY59VAvbK1tSbIlSc4+++w2ghoBAJhjfXQw70pyuENDfijJ3aOYxGEmAABMuXGsi9ck+fPW2mWttb9orf1Bkn+X5FeWjFsaFNchrgEAwIr1ETD/cZJ3VdU5i661qvpvk/yvSf7oSCdwmAkAADOg93VxkvuTfHXJta8l2TD4/MDg90lLxrwoz+1qBgCAFesjYL48yR1Z+HPArw2ufSrJbUnuysIhJ0fKYSYAAEy7y9P/uvjPkrxsybUzktwz+HxXFkLmjQdvVtXRSc7P4bfvAACAoY08YG6tfTvJ30/yz5L8eZLrknw5ya8m+e9aa0+NYJqRH2YCAACjNKZ18eYk51bV26vq9Kq6KMmvJfnIoIaW5ANJfquqfqqqXpHk40keS/LJEcwPAMAq18chf2mtPZ3kDwY/fRjpYSZVtSkLp3xnw4YNS28DAEAnfa+LW2s3V9Xrk/xekncmuXfw+4pFw96f5JgshM7rk9yU5DWttX191ARwRK4d8o87Lrys3zoAGFovAfMYrElyS2vt4H+j/EVVfX8WDjP58KJxQx1m4qRsAABmVWvtT5L8yfPcb1nYruPyMZUEAMAqMvKAuaq+kec/kbq11pbuE7dShzvM5H8ZfF58mMl9i8Y4zAQAgLEY07oYAAAmqo8O5pvy3IX030hybpK9WdgH+Uit5DCTm5PvOszkN0YwPwAALGcc62IAAJiokQfMrbWfP9T1qnphkv8rz/PneyuwOcn2qnp7kj9K8iNZOMzkXw5qaFX1gSRvr6qvJ9mR5B1xmAkAAGMypnUxAABM1JpxTdRa+2YWDhj5VyN4181JXp/kZ5LcluR3c+jDTH4/C4eZ3JLk5DjMBACACRvluhgAACZt3If8PZ5kwyhe5DATAABm2MjWxQAAMEljCZirak2SH0zyriwcxgcAAKuOdTEAAPNm5AFzVf1VnnuYyZoklYU9kF876jkBAGDaWBcDALAa9NHB/L48dyH9ZJJ7kvxJa213D3MCAMC0sS4GAGDujTxgbq29Y9TvBACAWWNdDADAarBm0gUAAAAAADCb+tiDecsKhrfW2i+NugYAAJg062IAAFaDPvZg/gdJ1iU5LsmBJLuTrM9Ct/TeJPsWjV26Jx0AAMwL62IAAOZeH1tk/EwWFsw/n+SY1tqJSY5J8qbB9Ytaa39r8LOhh/kBAGAaWBcDADD3+uhg3pzk/a21Tx680Fr7qyRXVtULk3wwyTk9zAsAANPEuhgAgLnXR8B8VpJ3Hube7Ul+qIc5AQBg2lgXw5Ta/fhZQ41bf+ytPVcCALOvjy0yHkzyPx7m3kVJHuphTgAAmDbWxQAAzL0+Opg/mOR/q6qTkmzNwsL6b2ZhD7rXJnlrD3MCAMC0sS4GAGDujTxgbq1trqrHs/DngP9o0a1dSX65tbZl1HMCAMC0sS4GAGA16KODOa21j1bVx5K8OMnJSe5Pck9r7UAf8wEAwDSyLgYAYN71EjAnyWDRfNfgBwAAViXrYgAA5lkfh/ylqs6sqv9YVQ9U1f6q+tHB9d+pqtf0MScAAEwb62IAAObdyAPmqjovyU1Jzkryn5IctWS+fzHqOQEAYNpYFwMAsBr00cH8viSfS/K3k/xaklp075Ykf6eHOQEAYNpYFwMAMPf62IP57yT56dbagaqqJfceSfI3e5gTAACmjXUxAABzr48O5qeSHHOYeycl+VYPcwIAwLSxLgYAYO710cF8fZJfq6rPLLrWBr//aZJre5gTgBHY9djOFY0/5ftO7akSgLlgXQwAwNzrI2B+VxYW03+RZGsWFtE/X1XvT3Jukr/bw5wAADBtrIsBAJh7I98io7X2F0l+IsmeJJdn4TCTtyQ5OsmFrbWvjXpOAACYNtbFAACsBn10MKe1dnOSC6rq2CQnJNndWtvXx1wAADCtrIsBAJh3I+1grqoXVNVDVfWPkqS19nhr7V6LaAAAVhPrYgAAVouRdjC31vZXVSV5cpTvBYCZctcXlx/zkvP7r2MWXPue5cdceFn/dcCIWRcDALBajHwP5iRXJfnpHt4LAACzxLoYAIC518cezFcl+XBVfSrJZ5Lcn4UTs5/VWvtCD/MCAMA0sS4GAGDu9REw/+fB758Z/CxeRNfg+1E9zAsAANPEuhgAgLnXR8C8sYd3AgDArLEuBgBg7o0kYK6qVyX5Umvtsdba50bxTgAAmDXWxQAArDaj6mDeluTvJflSklTVmiTXJfnF1to3RjQHAFNm12M7n3PtiQO3TqASIEk2b9ux7JhLN54xhkpWNetiADhCw6xplrLGgclZM6L31CG+vzLJuhG9HwAAZoF1MQAAq8qoAmYAAAAAAFYZATMAAAAAAJ2Mag/mJDm1ql46+HzUomt7lg5srd05wnkBAGCaWBcDALBqjDJg/uNDXPvMYcYedZjrADNr/85dK3vghBP7KQSASbMuZuqseJ0CADCkUQXM//OI3gMAALPMuhgAgFVlJAFza+0To3gPAADMMutiAABWG4f8AQAAAADQiYAZAAAAAIBORnnIHwArsOuRW1c0/pQTzuqpEmA12bxtx7JjLt14xhgqAQAA5oEOZgAAAAAAOhEwAwAAAADQiYAZAAAAAIBOBMwAAAAAAHQiYAYAAAAAoJO1ky4A6N/2rVdOugSAFbnhzkef/Xzj0zsmWAkAMM02b7NOAJg0HcwAAAAAAHQiYAYAAAAAoBMBMwAAAAAAnQiYAQAAAADoxCF/AIzU7sfPWtH49cfe2lMlAAAAQN90MAMAAAAA0ImAGQAAAACATgTMAAAAAAB0ImAGAAAAAKATh/wBwErc9cVJVwAAAABTQ8AMAAAAzJZr35MkOffeR5cdeuOGTX1XA7Cq2SIDAAAAAIBOBMwAAAAAAHQiYAYAAAAAoBMBMwAAAAAAnTjkDwCYaufeu2WocQ7wAQAAGD8BMwAAwITtvH13p+f279w14krIk9/6zuf990yuDgCYEbbIAAAAAACgEwEzAAAAAACdCJgBAAAAAOjEHswAzLXTtt409Ni7Lzqnx0qWuOuL45sLAAAAeiJgBgAAgDlxxZ4vDzXukuPP7LkSAFYLW2QAAAAAANCJgBkAAAAAgE4EzAAAAAAAdCJgBgAAAACgEwEzAAAAAACdrJ10AQAAADCrTrvm/qHG3f3qk3uuBAAmQwczAAAAAACdCJgBAAAAAOhEwAwAAAAAQCf2YAYA5sK5925ZdsyNGzaNoRIAAIDVQ8AMAABwBLZvvXLSJQAATIwtMgAAAAAA6ETADAAAAABAJwJmAAAAAAA6sQczMBY7b9896RIAAAAAGDEdzAAAAAAAdKKDGQAAAICZtnnbjk7PXbrxjBFXAquPDmYAAAAAADoRMAMAAAAA0ImAGQAAAACATgTMAAAAAAB04pA/AAAA6Nlp19y/7Ji7X33yGCoBgNHSwQwAAAAAQCcCZgAAmBNV9S+rqlXVhxddq6q6vKp2VdUTVXVdVb18knUCADA/BMwAADAHqurcJP88yZeX3HpbkrcmeXOSH0vyUJJtVbVuvBUCADCP7MEMM2b71isnXQIAMGWq6q8nuTLJLyZ516LrleQtSd7bWvv04NrFWQiZ35Dko+OvFgCAeaKDGQAAZt+WJH/cWvu/l1x/SZKTknz24IXW2hNJvpDkvPGVBwDAvJr5gNk+cwAArGZV9c+TnJ7knYe4fdLg94NLrj+46N7S922qqluq6paHH354dIWy6uzbv3eoHwBgts10wGyfOQAAVrOqelmS30vyxtba/ucZ2pY+eohrCwNb29JaO7u1dvaJJ544okoBAJhXMxswL9lnbvei69+1z1xr7bYkFydZl4V95gAAYF78vSQnJLmtqp6uqqeTXJDkksHnRwfjlnYrvyjP7WoGAIAVm9mAOSPcZ86fAQIAMKM+k+SHkvzwop9bknxq8HlHkgeSbDz4QFUdneT8JNvHXSwAAPNn7aQL6GLRPnNvOsTt59tn7tRDva+1tiULgXXOPvvsQ/6pIAAATJvW2p4kexZfq6pvJ/nm4C/5UlUfSPL2qvp6FgLndyR5LMknx1wuAABzaOYC5kX7zJ0/qn3mAABgjr0/yTFJPpJkfZKbkrymtbZvolUBADAXZi5gznfvM3fw2lFJ/n5V/YskLx9cOynJfYues88cAABzr7X2E0u+tySXD34AAGCkZnEPZvvMAQAAAABMgZnrYLbPHAAAAADAdJi5gHlI9pkDAAAAAOjZXATM9pkDAAAAABi/WdyDGQAAAACAKSBgBgAAAACgEwEzAAAAAACdzMUezAB92b9z16RLgE6u2PPlocdecvyZPVYCAADAPNPBDAAAAABAJwJmAAAAAAA6ETADAAAAANCJgBkAAAAAgE4EzAAAAAAAdLJ20gUA0J9dj9y6ovH79u/NuuNe2lM10++0rTctP2jP/UmSu199cs/VAAAAwPTTwQwAAAAAQCcCZgAAAAAAOhEwAwAAAADQiYAZAAAAAIBOHPIHE7Z965WTLoEZsdID+w7at3/viCuBI3PDnY9OugQAAABGRAczAAAAAACd6GAGAABgruzbe+eyY9Yd99IxVAJMu83bdqz4mUs3ntFDJTC7dDADAAAAANCJgBkAAAAAgE4EzAAAAAAAdCJgBgAAAACgE4f8AQAAMJR9+/dOuoSx2n3ggqHGrV/z+Z4rGb0r9nx56LGXHH9mj5X079x7tww99sYNm3qsBGA+6WAGAAAAAKATATMAAAAAAJ0ImAEAAAAA6ETADAAAAABAJwJmAAAAAAA6ETADAAAAANCJgBkAAAAAgE4EzAAAAAAAdLJ20gUAs2nn7bsnXQIwIlfs+fKKxl9y/Jk9VQIAAMCs0cEMAAAAAEAnAmYAAAAAADoRMAMAAAAA0ImAGQAAAACAThzyB8D823PP8mOOf3H/dTBx5967ZahxN27Y1HMlAAAA80EHMwAAAAAAnQiYAQAAAADoxBYZAAAAwETdcOejky4BgI50MAMAAAAA0ImAGQAAAACATgTMAAAAAAB0ImAGAAAAAKATATMAAAAAAJ0ImAEAAAAA6ETADAAAAABAJwJmAAAAAAA6ETADAAAAANCJgBkAAAAAgE7WTroAAAAAYH7ccOejky4BgDHSwQwAAAAAQCc6mAEgSfbcM+kKAAAAYOboYAYAAAAAoBMBMwAAAAAAndgiAwAAgPn39FPf/f3Jb02mDgCYMzqYAQAAAADoRMAMAAAAAEAnAmYAAAAAADoRMAMAAAAA0ImAGQAAAACATtZOugAAAACea//OXZMuYSrt23vnpEsAABbRwQwAAAAAQCc6mAGYqN2Pn7XiZ9Yfe2sPlTAKN9z56KRLAAAAYIx0MAMAAAAA0ImAGQAAAACATgTMAAAAAAB0ImAGAAAAAKATATMAAAAAAJ2snXQBADCLTrvm/hWNv/vVJ/dUCQAAAEyODmYAAAAAADoRMAMAAAAA0ImAGQAAAACATgTMAAAAAAB0ImAGAAAAAKATATMAAAAAAJ0ImAEAAAAA6ETADAAAAABAJwJmAAAAAAA6WTvpAgCA6XDfnieWHfO3jj9mDJUAAAAwK3QwAwAAAADQiYAZAAAAAIBObJEBAADQk5237550CQAAvdLBDAAAAABAJwJmAAAAAAA6sUUGAIzBadfcP/TYu199co+VAAAAwOjoYAYAAAAAoBMBMwAAAAAAnQiYAQAAAADoRMAMAAAAAEAnDvkD4Lvs23vnisavO+6lPVXCNLpvzxO54ZuPTroMerZ5247nvX/pxjPGVAkAADDtdDADAAAAANCJgBkAAAAAgE5skQEAAHAY27deOekSYKJsjwXAcnQwAwAAAADQiQ5mGCEdLgDAOFXVZUl+KsnLkjyV5MYkl7XWbls0ppL8qySbkqxPclOSX2mt/dfxVwwAwLzRwQwAALPrJ5JckeS8JK9K8nSSa6rqhYvGvC3JW5O8OcmPJXkoybaqWjfeUgEAmEczGTBX1WVVdXNV7a2qh6vq6qp6xZIxVVWXV9Wuqnqiqq6rqpdPqmYAABi11tpPttb+oLV2W2vtK0nelOTEJD+ePNu9/JYk722tfXrQ2XxxknVJ3jCpugEAmB8zGTBHpwYAABzKuiys8XcPvr8kyUlJPntwQGvtiSRfyMJaGgAAjshM7sHcWvvJxd+r6k1JvpWFTo2rl3ZqDMZcnIWQ+Q1JPjreigEAYCw+mOQvk9ww+H7S4PeDS8Y9mOTUQ72gqjZlYb/mbNiwoYcSAQCYJ7PawbyUTg0AAFa1qvr9JK9M8tOttWeW3G5Lhx/i2sLA1ra01s5urZ194okn9lApAADzZCY7mA/hiDo1dGnMv+1br1zxM+dd9MYeKgFGbs89k64AYOKqanOSn0tyYWvtzkW3Hhj8PinJfYuuvyjPXSsDAMCKzXwH8yg6NXRpAAAwq6rqg1nYBu5VrbWvL7l9VxZC5o2Lxh+d5Pwk28dWJAAAc2umO5h1agAAsJpV1UeSvCnJ65PsrqqDf8n3WGvtsdZaq6oPJHl7VX09yY4k70jyWJJPTqRoAADmyswGzINOjZ9L8hPLdGrcPBh/sFPjN8ZZJwAA9OiSwe/PLbn+r5NcPvj8/iTHJPlIkvVJbkrymtbavnEUCKvB7gMXDD12/ZrP91jJZF215o6hx77uwOk9VgLAOM1kwKxTAwAAktZaDTGmZSFsvrzvegAAWH1mMmCOTg1gFdu3f++kSwAAAABIMqMBs04NAAAAAIDJWzPpAgAAAAAAmE0CZgAAAAAAOpnJLTIAAAAYnZk94+Hppzo/uu/xXcuOWXfsKZ3f36fTrrl/qHF3v/rknitZvc69d0sv771xw6Ze3gvQJx3MAAAAAAB0ooMZSJLsvH33pEsYm/07l+9WAVa3YbqSdBgBAADoYAYAAAAAoCMBMwAAAAAAndgiAwAAWJW2b72y87OraXsxRmv3gQsOe6/d8X3Pfq7T/3wc5QDAEdPBDAAAAABAJzqYAabAvv17J10CAAAAwIrpYAYAAAAAoBMBMwAAAAAAnQiYAQAAAADoxB7MAAAAAEnOvXfLpEsAmDkCZmDm7d+5a9IlAAAAAKxKtsgAAAAAAKATATMAAAAAAJ0ImAEAAAAA6MQezAAAAEyPp5+adAXP2vf48md9rDv2lJHNd/ydjz37ef3d94/svUfqqjV3TLoEAKaYDmYAAAAAADrRwQwzYOftu1c0/tSXre+pEgAAAAD4Dh3MAAAAAAB0ImAGAAAAAKATATMAAAAAAJ3YgxkAAADm0GnX3L/smLtfffIYKgFgngmY4TC2b71y0iV0ttJDAafR/p27Jl0CAAAAAMuwRQYAAAAAAJ0ImAEAAAAA6ETADAAAAABAJ/ZgBgAAmEP79u+ddAkAc2nzth0rfubSzuDAkQAAIABJREFUjWdM7TxwpATMwNg4uI9R2f34Wd/5cuC0ZcevX/P5/oqZEffteWJk77pqzR0je9dSrztwem/vZnSG+ceOf9wAAMDqYIsMAAAAAAA6ETADAAAAANCJgBkAAAAAgE4EzAAAAAAAdOKQPwAAAOho3+OjOch63bGnjOQ9wHQa5pBkmFU6mAEAAAAA6ETADAAAAABAJwJmAAAAAAA6ETADAAAAANCJQ/4AAIC5s33rlZMuARiBq9bcMfTY1x04vcdKADgcATPAkPbt37ui8etecFxPlUyXfXvvXPEz64576fKDnvxWh2oObfeBC1Y0fv2az49sbgAAAJhntsgAAAAAAKATATMAAAAAAJ0ImAEAAAAA6ETADAAAAABAJw75A77L/p27Jl3CWK304D4Yh9OuuX/osXe/+uQeKwGgD6ttvQUAzDcdzAAAAAAAdCJgBgAAAACgEwEzAAAAAACdCJgBAAAAAOjEIX8AAAADO2/ffcjrwxzM94JTTxl1OdC75Q4XfuGTTydJbn3lCeMoZ9U7994tQ427ccOmnisBGJ6AGSbgcP9wAabD7gMXrGj8+jWf76mS4d2354lJlwAAAMAqZIsMAAAAAAA6ETADAAAAANCJgBkAAAAAgE7swQwAADBD9u3fO+kSGINhz4RYyVkQewcH9gHAKAmYmUnbt1456RIAAAAAYNWzRQYAAAAAAJ0ImAEAAAAA6ETADAAAAABAJwJmAAAAAAA6ccgfAAAw93bevnvSJcBIPfX0gSTJ3gNPT7iSbq5ac8dMzP26A6f3WAnAfBAwA/Rk3/69ky5heE8/tfyYtd87sun2ffNrI3vX81l37Cljmadve588/D8cX/hf7lv4PeS7bn3lCSOoCAAAABbYIgMAAAAAgE4EzAAAAAAAdCJgBgAAAACgE3swAwAAM2X71isnXcIh7d+5a9IlTLdhznxgJPY+dfRzrv1VnfZd3485+uRDPnvsgWt7qOi7nXX9I0ONc3bEaJx775ahxt24YVPPlQDzSsDMSHVZ7J930Rt7qAQYuWH/UTjCwwBhmg3zjzX/UAMAAOadLTIAAAAAAOhEwAwAAAAAQCcCZgAAAAAAOhEwAwAAAADQiUP+YImdt++edAkssW//3qHHrnvBcT1WAqO398mnJ13CVLlqzR1Dj33dgdN7rGQ0VvOp7Zu37RjJey7deMZI3gMwD/Y9vuvZz88caEmSJ/IDzx1Y46rouc66/pHJTQ7AROhgBgAAAACgEwEzAAAAAACdCJgBAAAAAOhEwAwAAAAAQCcO+QMAAACe19LD+x5fc+Ehxz1+BG1sxx64tvvDWdlhwaM2bwcVs7p0PZzZYcwcJGCGVWD/zl3LDwIAAACAFbJFBgAAAAAAnQiYAQAAAADoRMAMAAAAAEAnAmYAAAAAADpxyN+U2L71yhWNP++iN/ZUCctZyYF5Lzj1lB4r4VD27d876RKmy9NPTbqCidr3+KH///WZA23ZZ49aU0PNse7YU7L7wAUrqmuxp9YcGGrckZ6qDsBkDLs2WfeC43quZAVW+fqB79j71NGHvfdXdX+S5JijT+5t/rOuf2Socbe+8oTeaphW5967ZWbmv3HDph4rYZI2b9ux4mcu3XhGD5UwaTqYAQAAAADoRMAMAAAAAEAnAmYAAAAAADoRMAMAAAAA0IlD/pi4lR5wuFI7b9/d6/ufz7QdCLiSA/Cm6qCZaTCqw27Wfu9o3jPNpuBgoGEO8RvVPE89ffhD+r537fT977jDHpaTTP+BOVetuWNF41934PSeKgFGqe+1IUyjZw607Hls56TLSJI8vubCZz8fPMhvEnOvxPdvP/T1LockL13/rHS9wXMNeyCgwwA5HIcJTr/p+5cvAAAAAAAzQcAMAAAAAEAnAmYAAAAAADoRMAMAAAAA0ImAGQAAAACATtZOugC66XK69nkXvTFfuvrOFT3z9JM3rHieafDtm7707Of93/5rE6xkePt37kqS7Nu/d8KVMBWefmrSFUzEMwfasmOOWlNjqGR4Tzx5+NPVnzjM9WOOPrmfYgAAxuz51kIHDbP2GeY9wzjSddZZ1z+y7JhbX3nCEc2x2K6d35+19z16yHuPLlpNfuO8r4xszsP5//b+0dBjH1pzx7OfX3fg9D7KGYlz790y9NgbN2zqsZLx2bxtx6RLmApd/u9w6cYzeqjk0Ka9vpXSwQwAAAAAQCdzHTBX1SVVdVdVPVlV/09VnT/pmgAAYBKsjQEA6MPcBsxV9bNJPpjk95L8SJLtSf7Pqtow0cIAAGDMrI0BAOjL3AbMSX49ycdbax9rrX2ttfbmJPcn+eUJ1wUAAONmbQwAQC+qteUPVJo1VfWCJI8n+Z9aa1sXXf9Ikle01i5YMn5TkoO7ub8sye3LTHHC/8/enYdJUV19HP+eyK7I4hJRNGDQiMoICqKJUVBBJSomqIwSFhEVd8mrAfPGRE1eY4waFBU1oiBxQTCBxA0ERaMiCjrRGFRMQNncQBAUEPC8f9zbY9P0zPT0dE/P8vs8Tz09XXW76tbpmu5Tt2/dAioe+V8qS3HND8U19xTT/FBc80NxzQ/FNT9qSly/4+67FLoSuVINuXFdV1OOy/pC8a5+inn1U8yrl+Jd/RTz6pXPeGeUFzfI08YLbWdgO+CjlPkfAcemFnb3u4GMby1qZvPcvWuVaijbUFzzQ3HNPcU0PxTX/FBc80NxzQ/FNW/ymhvXdTouq5fiXf0U8+qnmFcvxbv6KebVqybEuy4PkQGQ2j3b0swTEREREakPlBuLiIiISM7V1QbmT4EtwG4p83dl254bIiIiIiJ1mXJjEREREcmbOtnA7O5fAfOBXimLehHumF1VumQwPxTX/FBcc08xzQ/FNT8U1/xQXPNDcc2DasiN6zodl9VL8a5+inn1U8yrl+Jd/RTz6lXweNfJm/wBmFl/YCJwAfAiMBw4GzjA3d8vZN1ERERERKqTcmMRERERyZe6epM/3H2Sme0E/BJoA/wL6KMEWkRERETqG+XGIiIiIpIvdbYHs4iIiIiIiIiIiIjkV50cg1lERERERERERERE8q/eNTCb2QVmtsjMNpjZfDP7YQXlzzSzEjP70sw+NLM/m9luKWX6mdm/zWxjfPxxynIzs6vNbLmZrTez2WZ2QD72r1ByHVczO8fM/mFmq8xstZk9a2ZHpKzjajPzlOnDfO1jIeQhrkPSxMzNrElVtlub5CGms8uI6VtJZTKKe22WRVwvNLMF8TPxHTMblKaMPltzHFd9tgZ5iKs+W3MfU322Sl5kcaweFcttMLP/mtnwlOXbmdlvkta5yMx+a2Z1dijCyqpMzM2sjZk9aGZvm9kWMxtfRrlyc4T6LNfxziR3qO/ycYwnlT8jfrc9lvOK12J5+lzZ0cxutXBusdHM3jOz0/O2E7VInuJ9aSyz3syWmtntZrZD3nailqlkzH9iZjPM7BMzW2tmc83s5DTl8vvd6e71ZgL6A5uAc4COwBhgHbBXGeV/AGwBRgDtgcOA14BZSWUOBzYD/xvX+b/xefekMiOBtUA/4EDgEWA50LzQManBcX0AuAjoAnwPuBP4AtgnqczVwNvAbknTLoWORw2P65AYx+SY7VaV7damKU8xbZ0Sz+8AnwO/rkzca/OURVzPj8vPAPYGiuNn5ElJZfTZmp+46rM1P3HVZ2vuY1rvP1s15X7K4lhtH4+xMbH8OfH1/ZLK/AJYBZwEtANOBj4Drir0/taEKYuYtwNujf/fLwHj05SpMEeor1Oe4l1h7lCfp3zEPKns3sBS4HngsULva02Z8nScNwReBp4EjoivOQLoVuj9LfSUp3ifCWwEBsbyRwOLgHGF3t+aMGUR81uAUcChQAfg14R2jB8mlcn7d2fBA1fNb9Jc4E8p8xYCvyuj/OXA+ynzzgLWJT2fBDydUmYm8FD824AVwP8mLW9KOJE6r9AxqalxTfMaAz4ELk6adzXwr0Lvf22Ka/yQLzPO2Wy3Nk3VdKwOiB/me1Ym7rV5yiKuLwF/TJl3E/BC0nN9tuYhrmleo8/WHMRVn63VcqzWu89WTbmfsjhWfw8sTJl3DzAn6fljwISUMhNQY1BWMU8p9xjpGybKzRHq85SPeKcpt03uUJ+nfMWc0OA5FxgMjNdnSn5jDpwL/BdoVOj9q2lTnuJ9G/BcyrxrqMPnINUV86TyrwA3JT3P+3dnvRkiw8waAYcAM1IWzQC+X8bLXgTamNlJFuxM6GXzRFKZw9Osc3rSOtsTetSUlnH39YRfIcvabq2Rx7imagQ0IfQISba3mS2Llw48bGZ7V34vap48x7Wpmb0fL0N5zMy6VHG7tUI1HqvnAE+6+5KU+WXGvTbLMq6NgQ0p89YDh5pZw/hcn635iWsqfbYGuYirPlu3lutjtV59tkruZXmslvVd1DXpWH0B6Glm+8Xt7E/oiVVerlAv5PGzr6IcoV6qxu+asnKHeifPMf8/YLG7T6jieuqUPMb8FMK53xgLwyL+28KwcWXlJfVCHuP9AtDZzA6L29mLcAWQvjtzF/PmbP05nffvznrTwAzsDGwHfJQy/yNCI8U23H0O4fLNB4CvgE8Iv9gOTiq2WwXr3C1pXkbbrWXyFddUvyVcEvC3pHlzCb2XTiCceO4GvGRmO1V2J2qgfMX1HWAo0DeW3QC8aGb7ZLvdWiTvx6qZ7QscBfwpZVFFca/NsjlmpgNDzaxbbLjvCgwj9NTYOZbRZ2t+4ppKn61BVeOqz9Y8Hqv19LNVci+bY7Ws76IGfHOs/h6YCPzbzDYBbxF6NN+Ri0rXcvn67KsoR6ivquu7Jl3uUF/lJeZm1ptwifzwisrWQ/k6zvcGTiPkIj8CriLE/3dVWGddkJd4u/vDhCGmno/fne8DbxKGQKzvqhxzM7sQaEvITxLy/t1ZnxqYEzzluaWZFxaEHgi3Ar8h/IJwPCH4d2Wxzoy3W0vlI66J8pcC5wE/cffPSzfo/qS7P+Lub7j7TOBEwjFdXkN1bZPTuLr7HHef4O4l7v4PQuLyH+DibLdbC+XtWCU0xq0AHt9qg5nHvTarzDHzG0KMXiKMLTWNcDkxhEvgK7POunysQn7iGlakz9ZkVYqrPluBPB6r1O/PVsm9yv4fpiufPL8/MIgwnuTB8e8LzOzsKtazLsnHZ19d/jytqrzFpqzcQXIX83jF5HhgsLvX+17i5cj1cf4t4GPgHHef7+6PAr8CzjczK/+l9UJO421mRxEa8S8gfHf+BOhBGCZDgqxibmb9gD8AA9z9/VysM1P1qYH5U8JJS2rr/K5s24qfcCXwirv/IZ5oTyf8Aww0sz1jmQ8rWOeH8bEy261N8hVXoDSJ+S3Qx91fKa8i7r6O0GukLvRcymtcE9x9CzCPb2KWzXZri3wfq40IDXD3ufvm8iqSJu61WaXj6u7r3X0o0IxwU4e9gMWE8ZM/jcX02ZqfuAL6bCVPcU16jT5bc3es1tfPVsm9bP4Py/ou2gysjM//ANzo7g+7+5vuPhG4mZBD1Hf5+uyrKEeor/L6XVOZ3KEeyUfMDwTaADPNbLOZbSb8cNUnPv9e1rWtG/J1nK8A3o25RMICQq5S1pWA9UG+4v1bwti/98Tvzr8SejT/3MwaVGG9dUHWMY+NyxOBQe6eepVJ3r87600Ds7t/BcwHeqUs6kXoQZNOM7btSZN4nvgVa04F61xEeCNLy5hZE+CH5Wy31shjXDGznxHGnvqRu79QUV1iXPcjfDnUavmMa7L4a2wRMWZZbrdWqIaYnkJIPsZVVJfUuNdmVTlm3H2Tuy+NiVwx4eYlX8fF+mzNT1z12ZqnuCbTZyuQu5jWy89Wyb0sj9U5wLFpys9z903xeVm5Qr05zypLHj/7KsoR6qV8ftdUNneoL/IU81eBTkDnpOlvwD/i34uyXG+dkMfj/EWgg5klf3bvC3xJGR0K6oM8xrus785631s825ib2enAn4Eh7j4lTZH8f3eWdfe/ujgRLmH7ijDOX0fgFsL4Ud+Jy+8H7k8qP4Rw6eb5hDF5fkD4wJ+fVOb7hF4MVxJOwK+Mr+meVGYk8Dmh2/+BwMPAcqB5oWNSg+N6RVzn6YRfWRJTi6QyNxLGZGwPdCfcofTzxHZr+5SnuP4aOC4u7wzcG19zaKbbrc1TPmKaVHYmKXdlrUzca/OURVz3BQYSehkeGj8TVwLtksroszU/cdVna37iqs/WHMc0qWy9/WzVlPspi2O1PfAFMDqWHxZf3y+pzHhgKWHMznbAjwn3bLipuvarJk+VjXmcl2hUe57QsNYZ2D9peYU5Qn2d8hTvCnOH+jzlI+ZptjGe8CNswfe3Jkx5Os73JOS7Y4DvEfKLpcAfCr2/hZ7yFO+rY7yLCd+1vYD3gEcLvb81YapszGMcNwGXpnxOt04qk/fvzoIHrgBv1AWEyzA3En4VODJp2Wxgdkr5iwmXBn9J6BHzINA2pcypwNvxAFhAGJMqebnFf6AVhBvQPAccWOhY1OS4xnV5mml8UplEY9JXwDLgUcr5Yq6NUx7i+kfCAPobCWNMTQcOr8x2a/uUp8+AvYGvgdPL2GZGca/NU2XiSviSfD3GdA0wFfhemnXqszXHcdVna97iqs/W/HwG1PvPVk25nypzrMZ5RwGvxfKLgOEpy5sTGqDfB9YD/wWuA5oUel9rypRFzNN9Ty1OKVNujlCfp1zHmwxyh/o+5eMYTyk/HjUw5z3mwGGE3pzr4+f9tUCjQu9rTZjy8LnSgNBRYGGM9xLgDqBVofe1pkyViXl8ni7mqe9LXr87LW5ERERERERERERERKRS6v3YYCIiIiIiIiIiIiKSHTUwi4iIiIiIiIiIiEhW1MAsIiIiIiIiIiIiIllRA7OIiIiIiIiIiIiIZEUNzCIiIiIiIiIiIiKSFTUwi4iIiIiIiIiIiEhW1MAsIpKGmR1uZo+Y2XIz+8rMVprZ02Y22My2y/G2hpiZm1m7XK63qnJdLzPrEdfXI2nebDObnYv1J61zvJktTnrezsyuNrO9c7kdERERkfpAebHyYhGRiqiBWUQkhZldBrwItAZGAscCQ4F3gbHAiTne5OPA4cCKHK+3qnJdr9fi+l7L0frK8hvgx0nP2wG/BpRIi4iIiFSC8uJSyotFRMrRoNAVEBGpSczsSOBm4DZ3vyRl8TQzuxnYPpfbdPdPgE9yuc5cyHW93P1z4OVcrS+VmTV2943u/p98bUNERESkvlBe/A3lxSIi5VMPZhGRrY0CVgE/T7fQ3f/j7m8knpvZoWY208zWmdkXZjbLzA5Nfo2ZdYuXEa40sy/N7L9mdkfS8m0uuTOzxWb2ZzMrNrMFcd3zzOyI1DqZ2VFxu2tjuelmdmBFO1rFeg00s3fMbL2Z/cPM9jGz7c3srri+j8zsJjNrkPTabS4FTFOnJmb2RzP7V4zph2b2dzPbL6Vcom5HmtlkM1sNzI3LSi8FjNt6Nr7s6fgaj3V5zMy26TViZu3N7GszO6+iGIqIiIjUYcqLM6uX8mIRqffUwCwiElkYQ64HMMPdN2RQvgh4DmgFDAEGATsCz5nZQbHMDsB0YEss0we4lsyuIPkh8D/AVUB/YDvgMTNrmVSHHwGzgHXAT4EzgebAP8xsz3LqXpV6HQlcQLhMcjDwXeBR4AFgLVAM3A38DDg3g/Ulaxzr/1vgR8D5QBPgZTPbLU35B4BFwKmEk6BUrwEXxr8vIVyKmLgc8Q6gS+qJT6zzF8CDlay7iIiISJ2gvFh5caS8WEQyoiEyRES+sTPQFHg/w/K/AjYCx7j7agAzexpYTBjb7CfAfoRE++fJPTyA8Rmsf0egs7t/Ftf9IfAqIelNJHm3AM+5e9/Ei8zsWeC/hCT8sjLWXZV67QAc7+5r4vZ2i/V4xd0vj2Wejkn+aYSENSNxncOS9mU7QsL/EXAG8MeUl0xx97S9auL6Pjezf8enC9y99FJEM3uKEKfzgFfivIbAWcAD7r4203qLiIiI1DHKi5UXKy8WkYypB7OISPaOBB5LJNFQOp7a34Cj4qyFwGrgLjP7aXm9J9KYk0iiozfj414AZrYPoZfEA2bWIDEBXwJzYv3KUtV6rUl6/nZ8nJ5S7m2gMusFwMxON7O58fK+zYReEzsA30tT/K+VXX+Cu38N3AUUm1mLOPsU4NtxvoiIiIhkRnlxoLxYROolNTCLiHxjJbAe+E6G5VuT/k7SHxJ6QSR6HvQElhN6LHwQx1Hrl8H6VyU/cfeN8c8m8XHX+DgO2JQynQjsVNaKq1ivz1Kef1XO/CZUgpmdBEwCFhAua+wOdCPcVCXduqp6J+9xhO/CgfH5cEKPk9eruF4RERGR2kx5sfJi5cUikjENkSEiErn7ZjObDfSyeOflCl6yCkg3/tluJCXB7l4C9Iu9KLoCVwKPmNlB7v6vKlR5ZXy8EpiZZvlXaeaVymO9qqIYeM/dhyRmxMvzWpdR3quyMXdfaWaTgfPMbDrh5GJYBS8TERERqdOUFysvRnmxiFSCejCLiGztekIPhz+kWxjvpFwUnz4H/MjMmictbw6cFJdtxd03x7HOriJ8/nasYl3fIYxrd4C7z0szvVHB6/NVr6poRrj8L9lAwo1cspU4IWpaxvI7gAOBe4DPgYersC0RERGRukJ5sfJi5cUikhH1YBYRSeLuz5vZz4Cbzawj4eYeHxAu7TuG8Cv+mcAbwG8Il9zNMrPfE3oNjCQkg9cCmNmJhLsvTyXc1Xl7wl2b1xLGg6tKXd3MLgSmmVkj4BHgU8JYad8HPnD3m9O9Np/1qqKngFPM7I/AY8AhsV6ry31V+d4lJOdDzWwVIbF+J3GzEnd/2cxeI4zNN8bdv6zKDoiIiIjUBcqLlRcrLxaRTKkHs4hICncfDRxBSN5uBJ4hJNQdCXdW/nss9wbQg/Dr/gRgIrAOOMrd/xlXt5Awft1VwJPAfYSkrpe7L81BXZ8gJIDbE3oaTAduIFyOWF5CnNd6VcGfgP8D+hPi/CNCz5c15b2oPO6+ErgIOIjQg+ZVQoKebEp81E1MRERERCLlxcqLRUQyYe5VGqZHRESk1jOzF4Gv3f2Hha6LiIiIiEihKC8WkWxoiAwREamXzKwxcDBwLOHSyb6FrZGIiIiISPVTXiwiVaUGZhERqa/aAC8RLvm8zt3/VuD6iIiIiIgUgvJiEakSDZEhIiIiIiIiIiIiIlnRTf5EREREREREREREJCtqYBYRERERERERERGRrKiBWURERERERERERESyogZmEREREREREREREcmKGphFREREREREREREJCtqYBYRERERERERERGRrKiBWURERERERERERESyogZmEREREREREREREcmKGphFREREREREREREJCtqYBYRERERERERERGRrKiBWUTqNTNrZ2ZuZuOrcZuzzczzvI3xcb/aJc2rtn01s8Vmtjjf26nL4ns1O8383cxsgpktNbMtsVzLAlRRRESk1jOzIfG7dEiaZb3N7CUz+yyWmVqAKkol1eY81MyujsdajzxuI+0xX11xS3eeUpeV9xkjUpeogVlEqkX8Uk2etpjZqtjYOsTMrNB1lPyqruTKzHrE7Vydz+0U0HhgIPAc8FvgGmBDISskIiJS18TGr2lAe+A+wvftwwWskkidVYhOP7lSD849RDLSoNAVEJF655r42BDoAPwYOAroClxUqEpVs0FAszxv40rgemBZnrdTlmMKtN06zcwaAb2Ame4+oND1ERERqcOOBZoA/+PuDxa6MlIptTkPvY3wQ8YHedzGX4GXgRV53EZ5Cn2eUt0KHW+RaqEGZhGpVu5+dfJzM/sB8DxwgZnd5O6LClKxauTu+UwYE9tYQQGTGHf/T6G2XcftRrj6aHmhKyIiIlLH7R4f9Z1by9TmPNTdPwU+zfM21gBr8rmNCrZf0POU6lboeItUFw2RISIF5e4vAm8DBhySvMzMGpnZRWb2hJm9b2Yb47AaM83shHTrS4wdZmbNzOwPZvZBfN17ZjYy06E4zOxbZnZrvNzpL2bWJIPXnGxms8xsRdzmcjN7zswuSCm3zRjMyZdWmVlXM3vKzNbEMf8eNbM9Y7m9zexhM/vEzNab2bNmdlCaumQ8tpmZ7Wtm15vZvLjejTHed5tZ2zTlk+t6qJk9Ht+X0u2ljuFmYSzh++LT+1KGS2kXt+9mNqiMOh4Sl/+9gn0ZDzwbn/46ZTs9kso1NrNRZvaGmX1pZp+b2T/M7PSK4pWyvb1jnN6L78cqM3vTzO40s53SlD8jvmefmdkGM1tgZr80s8YZbGsx8H58Ojhpv8ZXps4iIiK1UaZ5Vizb2sx+F79n18ecapaZ9c5gOz1inpa46u7ZdLlEOa/3mOt928zuNbOPzOwLC2M5/zCW2d5Cnvp+3Je3zOy0ctaZcf5gZqeY2Z/N7N243XVmNt/MLjGzbc7/k3NGMzsv5jEbYr3vNrMWFe1zyvq2M7PhZvZijPv6mCfdY2b7pJRtEd+nd+I2PzOz6WZ2bJr1mpkNjnH8JJZfEsv3Tym7zVjCljRUm5n1jO/R2pgDPm5mHcvYn2ZmdqWZlSTFc46ZnVHJuBSZ2UOxbhvjPrxmZqPNrGFSubRjMOfyuLJKDFsX36MrzOwZC/f/+CrW/W9mdlgZr0nUdbf4vi+zMDzikLh8q/MUC0NLJDoZJee4iffr+Pj3vWVsr7GZfRqnTHLqiuqX8bmRZXDuUV68LZzjPGpmHydt5w4za1PRfojUNOrBLCI1QaLRd1PK/NbALcBLwNPAJ0Ab4CTgCTM7x93vSbO+hsAMQs+TJ4HNwCmES7Ga8M0JQ/rKhMbkPwP9gNuBS9z96wpecy5wF/Ah8HdCz4NdgSLgLOCO8l6fpBswkjC+7p+ATsBPgE5mdjLwAqFB/n7gO3HZ02a2t7uvy3AbqX4CDCckRy8BXwEHAMOAk8ysq7unu4TtcMIlbi8A9wI7x9eNdW8XAAAgAElEQVSmMx5YDfQljGdYkrRsNXAncAVwXty3VOfFx7sq2JfEzXcGE2I4O2nZYigdZmI6YWiWtwnvcTPgVGCSmXV2919UsB1i4vcqsCPwBPAo4fhqTxgj+TZgZVL5ccBQYCnwF8J+Hwb8BjjGzHq5++ZyNjkaaAdcCvwzaV9LynqBiIhIXVCZPMvMvkP4/m8H/AN4CtgeOBF4yszOc/c/lbO5xYRcsQchV5gQ5yWWERuOngWec/ceadbREngRWAs8RMhpi4HpZnZ43JfWwGOEvPUMQg6yxN1fTtn3yuYP1wNfA3MJQxC0AI4m5NTdCDlKOjcAxxHiOwPoCZxDGNLu6DJes5WYYz1OGF5kCfAg8DnhvfgxIWdcGMsmYrQ/IZ8aTcglTwdmmNn57p6c9/0fIe9cBDxC6BHaJu7TacCkTOpIOA76Es4R7ozb7wN0M7P9Yw/ixP60BJ4BugCvEfLdbxHi9KCZHeDuv8wgLkWE98OBv8V92JEQ2wuAX7LteVA6OTuuKqEjIfbPE97bz4C9gJOBE8zsJHd/Ks3rWhOGhVhHOG6/Bj4qYxuz476l5rgQ8tx/Av8B+pvZiNgjOFk/YCfgJnffmOF+lVe/ypwbVXjuURYzO5Fw/mDAFEJHkkOA84G+ZvYDdy93HSI1irtr0qRJU94nQkLlaeYfCWwBNgJtUpY1BtqmeU0L4F/AKqBpyrLFcVtPJC8jnISsjlPDpPntYvnx8XlrwsnI18DISuzf/LgPu6ZZtnPK89mpsSCcxHicBqQsGxfnrwL+N2XZVXHZpSnzx8f57cra16T5ewCN09S7d3xvxpZT1/PKiMdiYHHKvCHxNUPKeM1jcXmnlPk7EBLpD4DtMngvEvW7uozlVyYdIw1SjpHE8fP9DLZzcbrYx2Xbpxx/iX3/S5pj9uoy3kMHZqfMS/seatKkSZMmTXV5yiLP+hooTpnfktBYtR74dtL8tPlJ0vdzjzTbTOQas9MsS+RIdwLfSpo/MCmf+zvQJGnZD+Oyv6asK5v84btp6vQtQkO5A91Tlo2P8z8A9kqa34DQqOjAoRm+T9fxTSNq45RljYFdkp7fFcveBVjS/H0Ijccb2TqPXUloZG+WwTGwmLLz0M3AMSnLfheX/byM2KTOb0L44eJroHMGcbkprqdvmmWtUo6TtMddno6r1GM+XdxapMY3zm9LGD5mQTn/A/eTlGuniWvy+9uOcnJc4PK4/KI0y2bHZftmeJxWVL9sz42uLmN728SbcH7zaVzfD1PKj4zlZ2SyP5o01ZRJQ2SISLWKl31dbWb/Z2aTgJmEX20v9zAeVyl33+juS1PX4eFX63sJCVm3MjZ1ibuvT3rNx4Sesy2A75VRt+8QegV0Bwa6++8ruXubSdP7wJN6QmTgBXd/IGXehPi4htArJVmit2/nSmxjK+6+zNP82u/uM4C3CL000inxrXuWVNXY+HhuyvwBhCTsHnffkoPtDCUkbT/zpB4/8Rj5TXw6rBLrW586w92/SD7+CD0yNgNDU+YTt7mSsJ8iIiKSXoV5loVhw44CHnX3h1PKrQZ+TWgc7FfFurxC6NmZdmgv4EvgCt/6CrgHCfvQitAovCGpbv8gNO6l5nOVzh88zfjDsR63xKdl5XXXetJ9QmKOdF98emgZryllZtsReuOuB4an5pYxr/8klm0I/JTQe/RKd/ekcguBW4FGbBvfTYQGudT9q0yu/bC7z0qZd3d8LN1PC0Od/RSY5+43pGxvA6ER0IAzK7HtdDnjZ17BlZJJcnVcZczd16SLbzxHmwLsZ2Z7pXnpV4Tzu/KuzquM+4ANfHNVIwBm9j3C//yz7v5uJdZXZv2qcG5UGX0Jva4nxfcp2U2E961XGbEVqZE0RIaIVLdfpzx34Gx3vy9dYTM7gDB0wpGEy+BSx0LeI83L1rj7e2nmL4mPrdIs+x4wh9Dz9IQ0iWdFHiAkA2/FhvPngBcTiXQlzEszL3FzmZI0DayJy7O2GSs5U2ZmhJOTIcBBhPhsl1SkrGEvXsl2m2V4knDJ4EAzG+nuX8b55xJOJtINh1IpZtaccDniMnd/O02RZ+JjlwxW9zdCT53bzew4wrAbLwL/Tj5RMrNmhLh+Clxm6YcB30g4URUREZFtZZpnHR4fW8RxXVPtEh+r9J0bc5R0eUTCu+6+NuU1W8zsI2B7d/9vmtcsI3RyALLPH2LD6BWEYR/2JuS2ydLlzpA+By0vd061H6Ejx1x3r+jGiPsRhid70d1XpVn+DGHYiOR87AHC1WNvmdlkwjEwx7cdLqEime5nN0I+7GUcS4lxkzM5liYRfiyYamZTCB1sXkz3Y0AFqnxcZcPCTdkvJfx/7Upo/E+2B6EHfLLFsfNGTrj7SjN7BBhkZt9395fiokTHlDsrucoy61eFc6PKODg+PpO6wN03m9nzhF7dXdg2tiI1khqYRaRaubtBuAkFIUkZB9xpZu+7+1ZfsPHGEc8QPqtmERr0Pidejkb45TfdjRxWl7H5xC/U26VZti9heIwSwhhrleLuN5vZp4SeG5cAlxES0ucIPQ3SJbPppEuSN5e1LCYg8E2Sm42bCfVdQWgkXcY3PSyGEMZ6TufDKmxzG+7+tZndReil3Z9wM8BDCAnY1AxOVjKRuFFNWXeuTsxvWdGK3P19MzuUcCnj8YTx2gCWmNmN7n5rfN6K0MNlF7b9gUVEREQqUIk8K3GD3V5xKssOeatsUFaj5+YKliWfn1c6f4hjBr9KuB/EK4Qr3VbFdSfGuC3rJmjp8ufycudUidwp3X07UmWTj40gjMM7FBgVp81m9gTwP2V0Lklnm/1MyqeT9zNxLHWj7CsmIYNjyd1fsXAjvv8l3PNjIICZvQNc4+4PZVb1nBxXlWJmPyb0VN5AuCfOf4AvCOdjPQi9h9MdUzk9T4juIPRqPw94Kd7QbzDwMVuP25yJ8uqX7blRZeTsnESkplADs4gUhLt/Acw0s5MIDboTzOx7Sb1WIfRcaAr0dPfZya83sysJDcy58nfgHUKP1Flm1ruSl9vh7vcD98fk/vuEm5kMJdx4o2Muf8XPFTPblXCi9i/CuMNrU5aXd4dsL2dZtu4l3FjnPMKlcJne3C9TieR7tzKWt0kpVy53X0C44UgDQg+HYwm9a24xsy/cfVzSul5394PLWJWIiIiUI8M8K/Gde2nSD721VTb5wzBC4/I17n518oJ4E7hLc1e9bSQabsvqIZ2s0vlYvIrvFkKOtStwBOEGd6cBB8Qb7mV6g7dMJLb9R3f/WVVX5u5zgBNjo+ghhM4JFxNuFviJu8+s6jby5DeEHrtdY95bKnYMOaqM1+X8PMHd55rZa8DpZnYZcALhh4Dfu3tlexWnrV8Vz40qI6fnJCI1gcZgFpGCcvc3gD8RhngYkbK4A7AqtXE5KiuZqUpdfhfr0AV41sy+neV6Vrv7E+5+DuEmFq0JN9moifYmfBfMSJNAtY3LcyUxvEeZvWDipa5TgO7xcrwzCGOQzcjFduI+/gfYw8z2SfPanvGxUr3Y3X2zu8+P43YnEs9T4rJ1hPHaDjCz1pVZr4iIiGytgjzr5fhYU/OujGWZP3SIj4+mWZbz3DnF24RG5iIz272Csu8QxhPubGbpht8oNx9z94/d/S/ufjrhasfvAgdmV+0yvULopZvTYymORf2Su/+K0JAJue00k2sdCMO/pTYuf4vQyJ8rFZ4nRGMJQyYOIgyP4YRzyVzJ5two07onez0+9khdEDuuJGJb6StrRQpFDcwiUhP8lnDZ1eUpSeZioLWZFSUXNrOzyc3NFbbh7qOB84EDgOcySJATdTo+JgOpdo2PX6ZZVhMsjo9HxJuzAGBmOxCStVxe6bIyPlZ0s4rEzf4mES47vLsSNz/JZDv3Ei45/UPKPu8MXJVUplxmdmgZP0Ik5iW/5zcTxqu7N/a8Sl1XKzNT72YREZE0Ms2z4lAZ/wB+YmZDy1hXp9hLsSr1aWZmZd3cLJcqmz8sjo89Usp1Aa7MUx2B0h7GdxCuPrwz9tRNrkMjM9sllv2KMKbyDsC1KeW+S2h43QRMjPMam9kxljIQdbxZYKLxPae5duwR/wDQ1cyuSnf8mdl3zax9Resysx+aWYs0i9LljDXNYmCf5HOi+D78Gtg/h9v5jNBYXNH/1IOEXr0/J/xo8nQWY1mXZ3F8rMy5UabnOMmmEoavOSMOC5nsMkJD9szkG2+K1HQaIkNECs7dl8VLrC4lJAuJBHg0oSH5hXhThzVAV8IvulMIY5jloz53mtkGwvjQz5vZ0Rl8uT8MbDCzFwiJiRF6PHQD5hNu5lHjuPuHZvYw4RLDEjObQRgTrBeh0b+EKtx5OsUcQgJ9WeyJ81GcPyb5Bi3u/qKZ/ZMw5MQmMmjsTfEOYay0YjP7inBjDAcmuvv7wI2ES+r6Av+MY/c1I1xiuStwg7u/kMF2zgQujOM/vkdIjL8LnES46c7opH26N44nfQHwHzObHuvVmnAp65GEIUGGV3JfRURE6oPK5FlnEnq1jjOzS4C5hJ61bYEiQk/XwwnjtmbrUOBZwo3melRhPeXKIn+4n3CDv9Fm1hNYCOwDnAj8hXCPi3y6hnBDuZOAd83sMWAtsCfQO9ZtfCw7ivAeXmRm3Qjx3Bk4HWgOXOTui2LZpoT3eLGZzQXeJ/Ri7UW4yd7fUnvY5shFhPhdS7gJ9QuE/HX3uN1uhCvXFpW5huB/gN5mNhv4L7CO0JnlBEL+eHce6p4rfyTcQO91M3uUkJv/gNC4/HfCe11l7r4uvrc/NLMHgHcJPYP/Fq94TZT70swm8E3v71wNo5dYfzbnRhWde6Tbzrr4I9hkQqemyfF1hxD+Vz7km6ECRWoFNTCLSE3xO+Ac4BIzG+3uH7n7U3GM5l8SEuIthMvVehJ+1c1LAzOAu483s42ERD3RyJzuzswJowiN4QcT7tq9gZD8jgTGuvumfNU1B84mJLv9gQuBTwg3VPwV6S+xzIq7f2Zm/Qg9Hs7im7ua/5ltxxe7j9BAO83dP6IS4t20f0y4WWDiJMWAF4D33f0rM+sF/IxwEnox4QYo/wQuq8SNVh4i3NTk+4T3vSkhuXwYuMnd/5VSrwvN7EnCSeCxhJt2rCIkk38gxEFERES2lXGe5e5LY6PsxUA/YADh0vUPgX8DY4A3q7X2VVCZ/MHdl1u4mdz1hA4ZxxGGrriA0ECb1wbmmGMdH+s6iHADNgOWA38l5GKJsqviuNBXEm6U/DPCjdReAf7g7snDo31BeK97EvKuUwgN1/8hXHlY2c4Ime7P52Z2FGEohjMJx1MTQiPzQsLQek9nsKo7CA3J3QmNsw2ApXH+TWU1QtYE7n5XPCe6jPB+ridcJXAWIR45aWCOBhIatI8nNNwbIU5vpJS7l9DAvIJwzpJrlTo3qujco6yNuPu0OCTgLwj/qy0In1N3Ar/J0Q3ORaqNuefjHk0iIiLZM7PxhCT2WHefVeDqiIiIiIhIDWBmQwidUX7r7ldVUFxEqokamEVEpEYxsz0JvUL+Cxzg+qISEREREan34ljYrxGGKGnv7ksLXCURiTREhoiI1AhmdiawL2HMs8bAVWpcFhERERGp38zsCMJN/XoAnYDb1LgsUrOogVlERGqKcwk3q1kCjHD3nI3/LCIiIiIitdaxhPu4rAL+RLgxvIjUIBoiQ0RERERERERERESyoh7MKXbeeWdv165doashIiIiIgUyf/78T919l0LXoyZQbiwiIiJSf2WaF6uBOUW7du2YN29eoashIiIiIgViZu8Xug41hXJjERERkfor07z4W/muiIiIiIiIiIiIiIjUTWpgFhEREREREREREZGsqIFZRERERERERERERLKiMZgzsGnTJpYuXcqGDRsKXZV6qUmTJrRt25aGDRsWuioiIiIiIiIiIpJjansrrKq2vamBOQNLly6lefPmtGvXDjMrdHXqFXdn5cqVLF26lPbt2xe6OiIiIiIiIiIikmNqeyucXLS9aYiMDGzYsIGddtpJB3gBmBk77bSTfsESEREREREREamj1PZWOLloe1MDc4Z0gBeOYi8iIiIiIiIiUrep/adwqhp7NTCLiIiIiIiIiIiISFY0BnMW/vj0uzld34he++Z0fSIiIiIiIiIiIrWV2t5qF/VgriWGDh3KrrvuyoEHHlg6b9WqVfTq1Yt99tmHXr168dlnnwFhcO5LLrmEDh06UFRUxGuvvZb3+o0fP57ly5fnfTsiIiIiIiIiIiL5oPa37KiBuZYYMmQITz311Fbzrr/+eo455hgWLlzIMcccw/XXXw/Ak08+ycKFC1m4cCF33303559/ft7rl80BvmXLljzVRkREREREREREpHLU/pYdNTDXEkceeSStW7feat60adMYPHgwAIMHD2bq1Kml8wcNGoSZcdhhh7F69WpWrFiRdr39+/fniSeeKH0+ZMgQHn30UbZs2cIVV1xBt27dKCoq4q677iotc8MNN9CpUycOOuggRo0axZQpU5g3bx4DBgygc+fOrF+/nlmzZtGlSxc6derE0KFD2bhxIwDt2rXj2muv5YgjjmDy5Mnceuut7L///hQVFVFcXJzTmImIiIiIiIiIiGRK7W/Z0RjMtdhHH31EmzZtAGjTpg0ff/wxAMuWLWPPPfcsLde2bVuWLVtWWjZZcXExkyZNok+fPnz11VfMmjWLsWPHMm7cOFq0aMGrr77Kxo0b+cEPfkDv3r15++23mTp1KnPnzqVZs2asWrWK1q1bc9ttt3HjjTfStWtXNmzYwJAhQ5g1axb77rsvgwYNYuzYsVx22WUANGnShBdeeAGA3XffnUWLFtG4cWNWr16d75CJiIiIiIiIiIhkTO1vFVMP5jrI3beZZ2Zpy55wwgk888wzbNy4kSeffJIjjzySpk2bMmPGDO6//346d+5M9+7dWblyJQsXLmTmzJmcddZZNGvWDGCbX3UA3nnnHdq3b8+++4YB1AcPHszzzz9furx///6lfxcVFTFgwAD+/Oc/06CBfu8QEREREREREZGaT+1v31ADcy327W9/u7Tr/YoVK9h1112B8IvJkiVLSsstXbqU3XffPe06mjRpQo8ePZg+fTqTJk0q7Sbv7owZM4aSkhJKSkpYtGgRvXv3xt3L/GdJSPcPlmz77bcv/fvxxx/nwgsvZP78+RxyyCFs3ry54h0XERERERERERGpBmp/q5i6jGZhRK99C10FAE4++WQmTJjAqFGjmDBhAn379i2df9ttt1FcXMzcuXNp0aJF2u75CcXFxdxzzz3MmzeP8ePHA3DccccxduxYjj76aBo2bMi7777LHnvsQe/evbn22ms588wzt+qi37x5c9auXQvAfvvtx+LFi3nvvffo0KEDEydO5Kijjtpmu19//TVLliyhZ8+eHHHEETz44IOsW7eOli1b5j5YIiIiIrWQmR0JXA4cAuwOnOXu4+OyhsBvgROA7wKfA88Co9z9g6R1NAZuBM4AmgKzgAvcfWn17YmIiIhI5mpK2xuo/S0TamCuJc444wxmz57Np59+Stu2bbnmmmsYNWoUp59+OuPGjWOvvfZi8uTJAPTp04cnnniCDh060KxZM+67775y1927d28GDRrEySefTKNGjQAYNmwYixcv5uCDD8bd2WWXXZg6dSrHH388JSUldO3alUaNGtGnTx+uu+46hgwZwvDhw2natClz5szhvvvu47TTTmPz5s1069aN4cOHb7PdLVu28NOf/pQ1a9bg7owYMUKNyyIiIiJb2wH4F3B/nJI1Aw4G/g8oAVoANwFPmVmRuye6powG+hIamFcCNwOPmdkh7p7/24qLiIiI1BJqf8uOVdSdur7p2rWrz5s3b6t5CxYsoGPHjgWqkYDeAxEREak+Zjbf3bsWuh6pzGwdcFGiB3MZZfYH3gKK3P1NM2sBfELo+fxALLMn8D5wgrtPL2+b6XJjERERkVxTu0/hpXsPMs2LNQaziIiIiEjdsWN8/Cw+HgI0BGYkCrj7EmAB8P10KzCzc81snpnN++STT/JZVxERERGpAzRERj3x5ptvMnDgwK3mNW7cmLlz5xaoRiIiIiKSS2bWiDBExt+TxlfeDdgCfJpS/KO4bBvufjdwN4QezPmprYiIiEjdU1/b39TAXE906tSJkpKSQldDRERERPLAzBoAfwZaAidn8hJAjcciIiIiOVRf2980RIaIiIiISC0WG5cfAoqAY9x9ZdLiD4HtgJ1TXrYroReziIiIiEiVqIFZRERERKSWMrOGwCRC43JPd/8wpch8YBPQK+k1bYGOwEvVVU8RERERqbs0RIaIiIiISA1lZjsAHeLTbwF7mVlnYBWwHJgMdANOAtzMEuMqr3H39e6+xszGAX8ws4+BlcDNwBvAzGrcFRERERGpo9TAnI1nf5fb9fW8MrfrExEREZG6oivwbNLza+I0Abga6Bvnz0953VnA+Pj3CGAzoadzU2AWMMjdt+SlxiIiIiJVpba3WqXah8gwsyPN7G9mtszM3MyGpCw3M7vazJab2Xozm21mB6SUaWVmE81sTZwmmlnLlDKdzOy5uI5lZvYrM7Nq2MW8WLJkCT179qRjx44ccMAB3HLLLQCsWrWKXr16sc8++9CrVy8+++wzANydSy65hA4dOlBUVMRrr72W9zqOHz+e5cuX5307IiIiIvWFu892d0szDXH3xWUsM3cfn7SODe5+sbvv5O7N3P0kd19SwN0SERERqXHU9pa9QozBvAPwL+BSYH2a5T8H/ge4mHC538fA02bWPKnMg8DBwAnA8fHviYmFZrYj8DThxiXdgEuAK4Cf5Xhfqk2DBg246aabWLBgAS+//DK33347//73v7n++us55phjWLhwIccccwzXX389AE8++SQLFy5k4cKF3H333Zx//vl5r2M2B/mWLeo4IyIiIiIiIiIihaW2t+xVewOzuz/h7r9w9ynA18nLYg/jy4Dr3f1Rd/8XMBhoDpwZy3QkNCqf6+4vufsc4DzgRDP7XlzVAKAZMNjd/+XujwK/B35WW3sxt2nThoMPPhiA5s2b07FjR5YtW8a0adMYPHgwAIMHD2bq1KkATJs2jUGDBmFmHHbYYaxevZoVK1akXXf//v154oknSp8PGTKERx99lC1btnDFFVfQrVs3ioqKuOuuu0rL3HDDDXTq1ImDDjqIUaNGMWXKFObNm8eAAQPo3Lkz69evZ9asWXTp0oVOnToxdOhQNm7cCEC7du249tprOeKII5g8eTK33nor+++/P0VFRRQXF+clfiIiIiIiIiIiImVR21v2atoYzO2B3YAZiRnuvt7Mnge+D9wFHA6sY+u7Xr8IfBHLvBPL/MPdk3tITwd+A7QDFuVvF/Jv8eLFvP7663Tv3p2PPvqINm3aAOEf4eOPPwZg2bJl7LnnnqWvadu2LcuWLSstm6y4uJhJkybRp08fvvrqK2bNmsXYsWMZN24cLVq04NVXX2Xjxo384Ac/oHfv3rz99ttMnTqVuXPn0qxZM1atWkXr1q257bbbuPHGG+natSsbNmxgyJAhzJo1i3333ZdBgwYxduxYLrvsMgCaNGnCCy+8AMDuu+/OokWLaNy4MatXr853+ERERERERERERMqktrfKqWkNzIm7Xn+UMv8jYI+kMp+4uycWurvHu2LvllRmaZp1JJZt1cBsZucC5wLstddeVal/3q1bt45+/foxevRodtxxxzLLJYWnVFmdt0844QQuueQSNm7cyFNPPcWRRx5J06ZNmTFjBm+88QZTpkwBYM2aNSxcuJCZM2dy1lln0axZMwBat269zTrfeecd2rdvz7777guEX3huv/320oO8f//+pWWLiooYMGAAp5xyCqecckqGkRCRfLl94LCcru/CiffkdH0iIiIiIpKZlyY/kPVrv3/agBzWRKT2UNtb5RViDOZMpL5DljJv23ew4jJWxnzc/W537+ruXXfZZZfK1rXabNq0iX79+jFgwAB+8pOfAPDtb3+7tPv9ihUr2HXXXYHwq8mSJd/cu2Xp0qXsvvvuadfbpEkTevTowfTp05k0aVJpV3l3Z8yYMZSUlFBSUsKiRYvo3bs37l7mP0xCun+yZNtvv33p348//jgXXngh8+fP55BDDmHz5s0VREJERERERERERCS31PaWnZrWg/nD+LgbkHxn6135pgfyh8CuZmaJXsxxXOVdUsrsxtZ2jY+pvaMrr+eVVV5FZbk7Z599Nh07duRnP/vmXoUnn3wyEyZMYNSoUUyYMIG+ffuWzr/tttsoLi5m7ty5tGjRIm0X/YTi4mLuuece5s2bx/jx4wE47rjjGDt2LEcffTQNGzbk3XffZY899qB3795ce+21nHnmmVt102/evDlr164FYL/99mPx4sW89957dOjQgYkTJ3LUUUdts92vv/669C6dRxxxBA8++CDr1q2jZcuWOYyeiIiIiIiIiIjUGmp7q1VtbzWtgXkRoXG4F/AqgJk1AX4IXBHLzAF2IIyznBiH+XBg+6Tnc4Dfm1kTd98Q5/UClgOL87sL+fHiiy8yceJEOnXqROfOnQG47rrrGDVqFKeffjrjxo1jr732YvLkyQD06dOHJ554gg4dOtCsWTPuu+++ctffu3dvBg0axMknn0yjRo0AGDZsGIsXL+bggw/G3dlll12YOnUqxx9/PCUlJXTt2pVGjRrRp08frrvuOoYMGcLw4cNp2rQpc+bM4b777uO0005j8+bNdOvWjeHDh2+z3S1btvDTn/6UNWvW4O6MGDFCjcsiIiIiIiIiIlKt1PaWPauoO3WumdkOQIf49CXgeuBvwCp3/8DMRgL/CwwB3gV+CRwJfM/d18Z1PAm0Bc4hDH1xN7DY3U+Ky1sQbvY3G/gtsC8wHrjG3W8qr35du3b1efPmbTVvwYIFdOzYsSq7LVWk90Ck+mgMZhGp78xsvrt3LXQ9aoJ0uXcOy4MAACAASURBVLGIiNQeGoNZagu1+xReuvcg07y4EGMwdwVej1NT4Jr497Vx+Q3AzcDtwDygDdA70bgcDQD+CcwApse/ByYWuvsaQo/l3eM6bgduiusVERERERERERERkRyo9iEy3H0239xwL91yB66OU1llVgE/rWA7bxJ6Pkv05ptvMnDgwK3mNW7cmLlz5xaoRiIiIiIiIiIiInVDfW17q2ljMEsederUiZKSkkJXQ0REREREREREpM6pr21vhRgiQ0RERERERERERETqADUwi4iIiIiIiIiIiEhW1MAsIiIiIiIiIiIiIlnRGMxZuKPkjpyu74LOF+R0fSIiIiIiIiIiIrWV2t5qF/VgriU2bNjAoYceykEHHcQBBxzAr3/9awAWLVpE9+7d2Weffejfvz9fffUVABs3bqR///506NCB7t27s3jx4rzXcfTo0Xz55Zd5346IiIiIiIiIiEguqe0te2pgriUaN27MM888wz//+U9KSkp46qmnePnllxk5ciQjRoxg4cKFtGrVinHjxgEwbtw4WrVqxXvvvceIESMYOXJk3uuYzUG+ZcuWPNVGREREREREREQkM2p7y54amGsJM2OHHXYAYNOmTWzatAkz45lnnuHUU08FYPDgwUydOhWAadOmMXjwYABOPfVUZs2ahbunXXf37t156623Sp/36NGD+fPn88UXXzB06FC6detGly5dmDZtGhAOzMsvv5xOnTpRVFTEmDFjuPXWW1m+fDk9e/akZ8+eADz00EN06tSJAw88cKt/sh122IFf/epXdO/enTlz5jBq1Cj2339/ioqKuPzyy3McORERERERERERkfKp7S17GoO5FtmyZQuHHHII7733HhdeeCHf/e53admyJQ0ahLexbdu2LFu2DIBly5ax5557AtCgQQNatGjBypUr2XnnnbdZb3FxMY888gjXXHMNK1asYPny5RxyyCH84he/4Oijj+bee+9l9erVHHrooRx77LHcf//9LFq0iNdff50GDRqwatUqWrduzc0338yzzz7LzjvvzPLlyxk5ciTz58+nVatW9O7dm6lTp3LKKafwxRdfcOCBB3LttdeyatUqzj77bN5++23MjNWrV1dfQEVERERERERERCK1vWVHPZhrke22246SkhKWLl3KK6+8woIFC7YpY2YAaX8xSSxLdfrppzN58mQAHnnkEU477TQAZsyYwfXXX0/nzp3p0aMHGzZs4IMPPmDmzJkMHz689J+rdevW26zz1VdfpUePHuyyyy40aNCAAQMG8Pzzz5fuR79+/QDYcccdadKkCcOGDeMvf/kLzZo1q2xYREREREREREREqkxtb9lRA3Mt1LJlS3r06MHLL7/M6tWr2bx5MwBLly5l9913B8IvKkuWLAFg8+bNrFmzJu3BCLDHHnuw00478cYbbzBp0iSKi4uB8I/y6KOPUlJSQklJCR988AEdO3bE3cv8h0ko65IAgCZNmrDddtsB4ReeV155hX79+jF16lSOP/74ygVDREREREREREQkh9T2VjkaIiMLF3S+oNq3+cknn9CwYUNatmzJ+vXrmTlzJiNHjqRnz55MmTKF4uJiJkyYQN++fQE4+eSTmTBhAocffjhTpkzh6KOPLvfALC4u5oYbbmDNmjV06tQJgOOOO44xY8YwZswYzIzXX3+dLl260Lt3b+6880569OixVTf95s2bs3btWnbeeWe6d+/OpZdeyqeffkqrVq146KGHuPjii7fZ7rp16/jyyy/p06cPhx12GB06dMhPAEVEREREREREpFZQ21vtantTA3MtsWLFCgYPHsyWLVv4+uuvOf300znxxBPZf//9KS4u5pe//CVdunTh7LPPBuDss89m4MCBdOjQgdatW/Pwww+Xu/5TTz2VSy+9lKuuuqp03lVXXcVll11GUVER7k67du147LHHGDZsGO+++y5FRUU0bNiQc845h4suuohzzz2XE044gTZt2vDss8/yu9/9jp49e+Lu9OnTp/QfMNnatWvp27cvGzZswN354x//mNvAiYiIiIiIiIiIVEBtb9mz8rpT10ddu3b1efPmbTVvwYIFdOzYsUA1EtB7IFKdbh84LKfru3DiPTldn4hIvpnZfHfvWuh61ATpcmMREak9Xpr8QNav/f5pA3JYE5Hyqd2n8NK9B5nmxRqDWURERERERERERESyoiEy6pHp06czcuTIrea1b9+ev/71rwWqkYiIiIiIiIiISN1QX9ve1MBcjxx33HEcd9xxha6GiIiIiIiIiIhInVNf2940RIaIiIiIiIiIiIiIZEUNzCIiIiIiIiIiIiKSFTUwi4iIiIiIiIiIiEhWNAZzFj4Zc1tO17fLxRdlXHbLli107dqVPfbYg8cee4xFixZRXFzMqlWrOPjgg5k4cSKNGjVi48aNDBo0iPnz57PTTjsxadIk2rVrl9N6pxo9ejTnnnsuzZo1y+t2RERERERERESk7lLbW3o1te1NPZhrmVtuuYWOHTuWPh85ciQjRoxg4cKFtGrVinHjxgEwbtw4WrVqxXvvvceIESO2uYNlPowePZovv/yyUq/ZsmVLnmojIiIiIiIiIiJSOWp7qzw1MNciS5cu5fHHH2fYsGEAuDvPPPMMp556KgCDBw9m6tSpAEybNo3BgwcDcOqppzJr1izcPe16u3fvzltvvVX6vEePHsyfP58vvviCoUOH0q1bN7p06cK0adOAcGBefvnldOrUiaKiIsaMGcOtt97K8uXL6dmzJz179gTgoYceolOnThx44IFb/ZPtsMMO/OpXv6J79+7MmTOHUaNGsf/++1NUVMTll1+e46iJiIiIiIiIiIhUTG1v2dEQGbXIZZddxg03/D979x5lZ1Xfj/+9JUIIUggaDBAo8KUgaMItiOAFgZJAbEF/Fcgy3BREFBWoPy9V7A9pK5iv36JcG1ruYoHAtxEkaCBiUcBIkHipQOIiUUi4SQiGuwn798echCEkkHkyk5k583qtddY5z977ec7nnGEWe71nZz8Ts3jx4iTJE088kY033jiDBnX8GEeMGJH58+cnSebPn58tt9wySTJo0KBstNFGeeKJJ/KWt7zlVdcdP358rrnmmnzta1/Lww8/nAULFmT33XfPl7/85ey33365+OKLs2jRorzzne/MX//1X+fyyy/P3Llzc88992TQoEFZuHBhNtlkk/zrv/5rbr311rzlLW/JggUL8sUvfjF33313hg4dmjFjxmTKlCn54Ac/mGeeeSbveMc7cvrpp2fhwoU59thjc99996WUkkWLFq2lbxMAAAAAXiZ7a0bA3E98//vfz6abbprdd989P/7xj5NkpX8VKaW8bt+KDjvssBxwwAH52te+lmuuuSaHHnpokmTatGm5/vrr881vfjNJ8vzzz+cPf/hDbrnllpxwwgnLf7k22WSTV13zrrvuyvvf//4MGzYsSTJhwoTcdttt+eAHP5h11lknf/d3f5ck+Yu/+IsMHjw4xx13XD7wgQ/kb/7mb7rytQAAAG3krJtnr9a4Uw7YvocrAWCgkb01J2DuJ26//fZcf/31mTp1ap5//vn86U9/ysknn5xFixZlyZIlGTRoUB566KFsvvnmSTr+ovLggw9mxIgRWbJkSZ566qmV/seYJFtssUXe/OY351e/+lWuvvrqTJo0KUnHL8p1112XHXbY4RXja62r/IXpPGZVBg8enHXWWSdJx194fv7zn2f69Om56qqrcu655+ZHP/rRan8vAAAAALCmZG/N2YO5nzjjjDPy0EMPZd68ebnqqquy33775corr8y+++6ba6+9Nkly2WWX5ZBDDkmSHHzwwbnsssuSJNdee23222+/1/wPc/z48Zk4cWKeeuqpjBw5MkkyduzYnHPOOcv/g73nnnuSJGPGjMm//du/ZcmSJUmShQsXJkk23HDD5f+EYM8998x///d/549//GOWLl2a//zP/8w+++zzqvd9+umn89RTT2XcuHH51re+lVmzZq3xdwUAAAAAXSF7a84K5gaGfebTvV3Cct/4xjcyfvz4nHrqqdl1111z7LHHJkmOPfbYHHnkkdluu+2yySab5KqrrnrN63z4wx/OSSedlK9+9avL27761a/m5JNPzqhRo1JrzdZbb53vf//7Oe644zJ79uyMGjUqb3zjG/Pxj388n/70p3P88cfnoIMOymabbZZbb701Z5xxRvbdd9/UWjNu3Ljlv4CdLV68OIccckief/751Fpz1llnde8XBAAAAEC/InvrX9lbea3l1APR6NGj68yZM1/Rdu+992bHHXfspYpI/AxgbTrvyOO69XonXvEf3Xo9gJ5WSrm71jq6t+voC1Y2N4aeZA9m6F53TL6y8bl7HzqhGyuB1yb36X0r+xms7rzYFhkAAAAAADRii4wB5Ic//GG++MUvvqJtm222yX/913/1UkUAAAAA0B4GavYmYB5Axo4dm7Fjx/Z2GQAAAADQdgZq9maLDAAAAAAAGhEwAwAAAADQiIAZAAAAAIBGBMwAAAAAADTiJn8N/PyGB7r1eu/8221Xa9zWW2+dDTfcMOuss04GDRqUmTNnZuHChTn88MMzb968bL311rnmmmsydOjQ1Fpz0kknZerUqRkyZEguvfTS7Lbbbt1a94ouvfTSjBkzJptvvnmPvg8AAAAA7Uv2tnJ9NXuzgrmfufXWWzNr1qzMnDkzSXLmmWdm//33z5w5c7L//vvnzDPPTJLcdNNNmTNnTubMmZMLL7wwn/zkJ3u8tksvvTQLFizo0jlLly7toWoAAAAAoGtkb10nYO7nvve97+Xoo49Okhx99NGZMmXK8vajjjoqpZS8613vyqJFi/Lwww+v9BqHH354pk6duvz4mGOOyXXXXZelS5fm85//fPbYY4+MGjUqkyZNWj5m4sSJGTlyZHbeeed86UtfyrXXXpuZM2dmwoQJ2WWXXfLcc89l+vTp2XXXXTNy5Mh87GMfywsvvJCk469Bp59+et7znvdk8uTJOfvss7PTTjtl1KhRGT9+fE99VQAAAADQJbK312eLjH6klJIxY8aklJJPfOITOf744/Poo49ms802S5Jsttlmeeyxx5Ik8+fPz5Zbbrn83BEjRmT+/PnLx3Y2fvz4XH311Rk3blxefPHFTJ8+PRdccEEuuuiibLTRRrnrrrvywgsv5N3vfnfGjBmT++67L1OmTMmMGTMyZMiQLFy4MJtssknOPffcfPOb38zo0aPz/PPP55hjjsn06dOz/fbb56ijjsoFF1yQk08+OUkyePDg/PSnP02SbL755pk7d27WW2+9LFq0qKe/RgAAAAB4FdlbM1Yw9yO33357fvGLX+Smm27Keeedl9tuu22VY2utr2orpax07EEHHZQf/ehHeeGFF3LTTTflfe97X9Zff/1MmzYtl19+eXbZZZfsueeeeeKJJzJnzpzccsst+ehHP5ohQ4YkSTbZZJNXXfP+++/PNttsk+233z5Jx194Otd7+OGHL389atSoTJgwId/5zncyaJC/eQAAAACw9snemhEw9yPLNvDedNNN86EPfSg///nP89a3vnX58vuHH344m266aZKOv5o8+OCDy8996KGHVrkB+ODBg/P+978/P/zhD3P11VcvXypfa80555yTWbNmZdasWZk7d27GjBmTWusqf2GWWdkvWWcbbLDB8tc33nhjTjzxxNx9993Zfffds2TJktf5JgAAAACge8nemhEw9xPPPPNMFi9evPz1tGnT8o53vCMHH3xwLrvssiTJZZddlkMOOSRJcvDBB+fyyy9PrTU/+9nPstFGG610if4y48ePzyWXXJKf/OQnGTt2bJJk7NixueCCC/LnP/85STJ79uw888wzGTNmTC6++OI8++yzSZKFCxcmSTbccMPlNb7tbW/LvHnz8rvf/S5JcsUVV2SfffZ51fu+9NJLefDBB7Pvvvtm4sSJWbRoUZ5++uk1/r4AAAAAYHXJ3pqzH0ED7/zbbdf6ez766KP50Ic+lCRZsmRJPvKRj+TAAw/MHnvskcMOOywXXXRRttpqq0yePDlJMm7cuEydOjXbbbddhgwZkksuueQ1rz9mzJgcddRROfjgg7PuuusmSY477rjMmzcvu+22W2qtGTZsWKZMmZIDDzwws2bNyujRo7Puuutm3Lhx+frXv55jjjkmJ5xwQtZff/3ceeedueSSS3LooYdmyZIl2WOPPXLCCSe86n2XLl2aI444Ik899VRqrTnllFOy8cYbd/O3BwAAAEB/IXvrX9lbeb3l1APN6NGj68yZM1/Rdu+992bHHXfspYpI/AxgbTrvyOO69XonXvEf3Xo9gJ5WSrm71jq6t+voC1Y2N4aedNbNs1dr3CkHbN/DlUB7uGPylY3P3fvQCd1YCbw2uU/vW9nPYHXnxbbIAAAAAACgEVtkDCC//vWvc+SRR76ibb311suMGTN6qSIAAAAAaA8DNXsTMA8gI0eOzKxZs3q7DAAAAABoOwM1e7NFBgAAAAAAjQiYAQAAAABoRMAMAAAAAEAjAmYAAAAAABpxk78G7ph8Zbdeb+9DJ6zWuEWLFuW4447Lb37zm5RScvHFF2eHHXbI4Ycfnnnz5mXrrbfONddck6FDh6bWmpNOOilTp07NkCFDcumll2a33Xbr1rpXdOmll2bMmDHZfPPNe/R9AAAAAGhfsreV66vZmxXM/chJJ52UAw88MPfdd19++ctfZscdd8yZZ56Z/fffP3PmzMn++++fM888M0ly0003Zc6cOZkzZ04uvPDCfPKTn+zx+i699NIsWLCgS+csXbq0h6oBAAAAgNUne2tGwNxP/OlPf8ptt92WY489Nkmy7rrrZuONN873vve9HH300UmSo48+OlOmTEmSfO9738tRRx2VUkre9a53ZdGiRXn44YdXeu3DDz88U6dOXX58zDHH5LrrrsvSpUvz+c9/PnvssUdGjRqVSZMmLR8zceLEjBw5MjvvvHO+9KUv5dprr83MmTMzYcKE7LLLLnnuuecyffr07Lrrrhk5cmQ+9rGP5YUXXkiSbL311jn99NPznve8J5MnT87ZZ5+dnXbaKaNGjcr48eN75PsDAAAAgFWRvTVni4x+4oEHHsiwYcPy0Y9+NL/85S+z++6759vf/nYeffTRbLbZZkmSzTbbLI899liSZP78+dlyyy2Xnz9ixIjMnz9/+djOxo8fn6uvvjrjxo3Liy++mOnTp+eCCy7IRRddlI022ih33XVXXnjhhbz73e/OmDFjct9992XKlCmZMWNGhgwZkoULF2aTTTbJueeem29+85sZPXp0nn/++RxzzDGZPn16tt9++xx11FG54IILcvLJJydJBg8enJ/+9KdJks033zxz587Neuutl0WLFvX0VwkAAAAAryB7a84K5n5iyZIl+cUvfpFPfvKTueeee7LBBhssX5K/MrXWV7WVUlY69qCDDsqPfvSjvPDCC7npppvyvve9L+uvv36mTZuWyy+/PLvsskv23HPPPPHEE5kzZ05uueWWfPSjH82QIUOSJJtsssmrrnn//fdnm222yfbbb5+k4y88t9122/L+ww8/fPnrUaNGZcKECfnOd76TQYP8zQMAAACAtUv21pyAuZ8YMWJERowYkT333DNJ8uEPfzi/+MUv8ta3vnX58vuHH344m2666fLxDz744PLzH3rooVVuAD548OC8//3vzw9/+MNcffXVy5fK11pzzjnnZNasWZk1a1bmzp2bMWPGpNa6yl+YZVb2S9bZBhtssPz1jTfemBNPPDF33313dt999yxZsuR1vg0AAAAA6D6yt+YEzP3E8OHDs+WWW+b+++9PkkyfPj077bRTDj744Fx22WVJkssuuyyHHHJIkuTggw/O5Zdfnlprfvazn2WjjTZa6RL9ZcaPH59LLrkkP/nJTzJ27NgkydixY3PBBRfkz3/+c5Jk9uzZeeaZZzJmzJhcfPHFefbZZ5MkCxcuTJJsuOGGWbx4cZLkbW97W+bNm5ff/e53SZIrrrgi++yzz6ve96WXXsqDDz6YfffdNxMnTsyiRYvy9NNPr/H3BQAAAACrS/bWnP0IGtj70Am98r7nnHNOJkyYkBdffDHbbrttLrnkkrz00ks57LDDctFFF2WrrbbK5MmTkyTjxo3L1KlTs91222XIkCG55JJLXvPaY8aMyVFHHZWDDz446667bpLkuOOOy7x587Lbbrul1pphw4ZlypQpOfDAAzNr1qyMHj066667bsaNG5evf/3rOeaYY3LCCSdk/fXXz5133plLLrkkhx56aJYsWZI99tgjJ5xwwqved+nSpTniiCPy1FNPpdaaU045JRtvvHH3f3kAAAAA9Auyt/6VvZXXW0490IwePbrOnDnzFW333ntvdtxxx16qiMTPANam8448rluvd+IV/9Gt1wPoaaWUu2uto3u7jr5gZXNj6Eln3Tx7tcadcsD2PVwJtIc7Jl/Z+NzeCvgYmOQ+vW9lP4PVnRfbIgMAAAAAgEZskTGA/PrXv86RRx75irb11lsvM2bM6KWKAAAAAKA9DNTsTcC8mlbn7o193ciRIzNr1qzeLqPLbOMCAAAA0N5kb71nTbM3W2SshsGDB+eJJ54QdPaCWmueeOKJDB48uLdLAQAAAKAHyN56T3dkb1Ywr4YRI0bkoYceyuOPP97bpQxIgwcPzogRI3q7DAAAAAB6gOytd61p9iZgXg1vfOMbs8022/R2GQAAAADQdmRv/ZstMgAAAAAAaETADAAAAABAIwJmAAAAAAAaETADAAAAANCIgBkAAAAAgEYEzAAAAAAANCJgBgAAAACgEQEzAAAAAACNCJgBAAAAAGhEwAwAAAAAQCMCZgAAAAAAGhEwAwAAAADQiIAZAAAAAIBGBMwAAAAAADQyqLcLAAAAAOhrzp91fqPzPrXLp7q5EoC+zQpmAADoo0op7yulXF9KmV9KqaWUY1boL6WU00opC0opz5VSflxKefsKY4aWUq4opTzVelxRStl4rX4QAADaloAZAAD6rjcl+U2Sk5I8t5L+LyT5XJLPJNkjyWNJbi6lbNhpzHeT7JbkoCQHtl5f0YM1AwAwgNgiAwAA+qha69QkU5OklHJp575SSklycpIza63XtdqOTkfI/JEkk0opO6YjVH5PrfWO1phPJPlJKWWHWuv9a+uzAADQnqxgBgCA/mmbJMOTTFvWUGt9LsltSfZuNe2V5Okkd3Q67/Ykz3QaAwAAjQmYAQCgfxreen50hfZHO/UNT/J4rbUu62y9fqzTmFcopRxfSplZSpn5+OOPd3PJAAC0GwEzAAD0b3WF47JC24r9Kxvz8uBaL6y1jq61jh42bFg3lQgAQLsSMAMAQP/0SOt5xZXIm+blVc2PJNm0tV9zkuV7Nw/Lq1c+AwBAlwmYAQCgf5qbjgD5gGUNpZTBSd6bl/dcvjPJm9KxF/MyeyXZIK/clxkAABoZ1NsFAAAAK1dKeVOS7VqHb0iyVSlllyQLa61/KKV8K8lXSin3JZmd5NR03NTvu0lSa723lPKDJJNKKR9Px9YYk5J8v9Z6/1r+OAAAtCEBMwAA9F2jk9za6fhrrcdlSY5JMjHJ+knOSzI0yYwkY2qtizudMyHJ2UmmtY6vT/LpHq0aoAecP+v8Rud9apdPdXMlq+fnNzzQ+Nx3/u223VjJ6pt//5PLX3e1/t6qGeh9AmYAAOijaq0/Tseq41X11ySntR6rGrMwyRHdXBoAACSxBzMAAAAAAA0JmAEAAAAAaETADAAAAABAI/ZgBgAAoF856+bZrzvmlAO2XwuVAABWMAMAAAAA0IiAGQAAAACARgTMAAAAAAA0ImAGAAAAAKARATMAAAAAAI0M6u0CAAAAgIHj/Fnn93YJAHQjK5gBAAAAAGhEwAwAAAAAQCMCZgAAAAAAGhEwAwAAAADQiJv8AQAAAHSTZTcxrI+8pUvn7TF8dE+UA9DjrGAGAAAAAKARATMAAAAAAI0ImAEAAAAAaKTPBcyllHVKKf9USplbSnm+9fzPpZRBncaUUspppZQFpZTnSik/LqW8fYXrDC2lXFFKear1uKKUsvHa/0QAAAAAAO2pzwXMSb6Y5MQkn03ytiQntY7/odOYLyT5XJLPJNkjyWNJbi6lbNhpzHeT7JbkoCQHtl5f0dPFAwAAAAAMFINef8hat3eSG2qtN7SO55VSrk+yZ9KxejnJyUnOrLVe12o7Oh0h80eSTCql7JiOUPk9tdY7WmM+keQnpZQdaq33r9VPBAAAAADQhvriCuafJtm3lPK2JCml7JRkvyRTW/3bJBmeZNqyE2qtzyW5LR3hdJLsleTpJHd0uu7tSZ7pNAYAAAAAgDXQF1cwfyPJhkl+W0pZmo4a/6XWen6rf3jr+dEVzns0yRadxjxea63LOmuttZTyWKfzlyulHJ/k+CTZaqutuutzAAAAAAC0tb64gvnwJEelY7uL3VqvP1VKOXaFcXWF47JC24r9KxvTMbDWC2uto2uto4cNG9a4cAAAAACAgaQvrmD+30m+WWu9qnX861LKX6bjJn8XJXmk1T48yYOdzts0L69qfiTJpqWUsmwVc2vv5mF59cpnAAAAYE3cesbqjx26Uc/VAcBa1xdXMA9JsnSFtqV5uda56QiQD1jWWUoZnOS9eXnP5TuTvCkdezEvs1eSDfLKfZkBAAAAAGioL65gviHJl0opc5P8T5Jdk/x9ksuT5XspfyvJV0op9yWZneTUdNzU77utMfeWUn6QZFIp5ePp2BpjUpLv11rvX9sfCAAAAACgHfXFgPkzSf4pyfnp2Pbi4ST/nuT0TmMmJlk/yXlJhiaZkWRMrXVxpzETkpydZFrr+Pokn+7RygEAAAAABpA+FzC3QuKTW49VjalJTms9VjVmYZIjurk8AAAAAABa+lzADAAAAECHOyZf2dslALymvniTPwAAAAAAdrqLcAAAIABJREFU+gEBMwAAAAAAjQiYAQAAAABoRMAMAAAAAEAjbvIHAAAAtK3zZ53f2yUkSTb+7UOv2f/MH+ry14/Pm/pyx/ChPVUSQLewghkAAAAAgEYEzAAAAAAANCJgBgAAAACgEQEzAAAAAACNCJgBAAAAAGhkUG8XAAAAAL3lrJtnr9a4Uw7YvocrWQtuPaNr4/f9h56pA4C2YgUzAAAAAACNCJgBAAAAAGhEwAwAAAAAQCMCZgAAAAAAGhEwAwAAAADQiIAZAAAAAIBGBMwAAAAAADQiYAYAAAAAoBEBMwAAAAAAjQzq7QIAAACA/uX8Wee/smHRr1b/5KHv7d5iesHWk2e87pgnn915LVQC0PusYAYAAAAAoBEBMwAAAAAAjQiYAQAAAABoRMAMAAAAAEAjAmYAAAAAABoRMAMAAAAA0IiAGQAAAACARgTMAAAAAAA0ImAGAAAAAKCRQb1dAAAAAAAv+81jw5a//uNTj3fp3C12GNrd5QC8JiuYAQAAAABoRMAMAAAAAEAjAmYAAAAAABoRMAMAAAAA0IiAGQAAAACARgb1dgEAAAAAdJ9nZvy82Ykb/1X3FgIMCFYwAwAAAADQiIAZAAAAAIBGBMwAAAAAADQiYAYAAAAAoBEBMwAAAAAAjQiYAQAAAABoRMAMAAAAAEAjAmYAAAAAABoRMAMAAAAA0Mig3i4AAAAAgJV7cf6CLo1/ZtGcHqoEYOWsYAYAAAAAoBEBMwAAAAAAjQiYAQAAAABoRMAMAAAAAEAjbvIHAAAA9HtbT57R6Lx5h+7ZzZUADCxWMAMAAAAA0IiAGQAAAACARgTMAAAAAAA0ImAGAAAAAKARN/kDAAAAaBOPPbNB43PX3bj5+/78hgcan/vOv932Fcd3TL6y8bX2PnRC43OBZqxgBgAAAACgEQEzAAAAAACNCJgBAAAAAGhEwAwAAAAAQCMCZgAAAAAAGhnU2wUAAAAAfdCtZ6y6b9Gv1l4d9Irf/3LqGp3/lzuP66ZKgL7OCmYAAOinSinrlFL+qZQyt5TyfOv5n0spgzqNKaWU00opC0opz5VSflxKeXtv1g0AQPsQMAMAQP/1xSQnJvlskrclOal1/A+dxnwhyeeSfCbJHkkeS3JzKWXDtVsqAADtyBYZAADQf+2d5IZa6w2t43mllOuT7Jl0rF5OcnKSM2ut17Xajk5HyPyRJJPWfskAALQTK5gBAKD/+mmSfUspb0uSUspOSfZLsmzjzG2SDE8ybdkJtdbnktyWjnAaAADWiBXMAADQf30jyYZJfltKWZqO+f2/1FrPb/UPbz0/usJ5jybZYmUXLKUcn+T4JNlqq626vWCgm73Wjfj6qrk/Wf2x27y35+pYDfWut6y0/clnd17LlfQ/XblJ4JLnh/ZgJUBPs4IZAAD6r8OTHJWO7S52a73+VCnl2BXG1RWOy0raOgbWemGtdXStdfSwYcO6u14AANqMFcwAANB//e8k36y1XtU6/nUp5S/TcZO/i5I80mofnuTBTudtmlevagYAgC6zghkAAPqvIUmWrtC2NC/P8+emI2Q+YFlnKWVwkvcmuWNtFAgAQHuzghkAAPqvG5J8qZQyN8n/JNk1yd8nuTxJaq21lPKtJF8ppdyXZHaSU5M8neS7vVMyAADtRMAMAAD912eS/FOS89Ox7cXDSf49yemdxkxMsn6S85IMTTIjyZha6+K1WyqsXWfdPLu3SwCAAUHADAAA/VQrJD659VjVmJrktNYDAAC6lT2YAQAAAABoRMAMAAAAAEAjAmYAAAAAABoRMAMAAAAA0IiAGQAAAACARgTMAAAAAAA0ImAGAAAAAKARATMAAAAAAI0ImAEAAAAAaETADAAAAABAIwJmAAAAAAAaETADAAAAANCIgBkAAAAAgEYEzAAAAAAANCJgBgAAAACgEQEzAAAAAACNCJgBAAAAAGhEwAwAAAAAQCMCZgAAAAAAGhnU2wUAAAAArLFFv1/9sRv/Zc/VATDAWMEMAAAAAEAjAmYAAAAAABoRMAMAAAAA0IiAGQAAAACARgTMAAAAAAA0ImAGAAAAAKARATMAAAAAAI0ImAEAAAAAaETADAAAAABAI4N6uwAAAACA3rL15Bmr7Hvy2Z275T0W/+mB1x2z4Pk/dst7AaxtVjADAAAAANCIgBkAAAAAgEYEzAAAAAAANCJgBgAAAACgETf5AwAAANraky/t88qGZzfqnUIA2pAVzAAAAAAANCJgBgAAAACgkT4ZMJdSNiulXFZKebyU8nwp5bellH069ZdSymmllAWllOdKKT8upbx9hWsMLaVcUUp5qvW4opSy8dr/NAAAAAAA7anPBcytEPj2JCXJB5LsmOQzSR7rNOwLST7Xat+j1XdzKWXDTmO+m2S3JAclObD1+oqerh8AAAAAYKDoizf5+0KSh2utR3Vqm7vsRSmlJDk5yZm11utabUenI2T+SJJJpZQd0xEqv6fWekdrzCeS/KSUskOt9f6181EAAAA46+bZvV0CANBD+twK5iQfTDKjlHJ1KeWxUsqsUsqnW8FykmyTZHiSactOqLU+l+S2JHu3mvZK8nSSOzpd9/Ykz3Qas1wp5fhSysxSyszHH3+8+z8RAAAAAEAb6osB87ZJPpXkgSRjk3w7yZlJTmz1D289P7rCeY926hue5PFaa13W2Xr9WKcx6dR3Ya11dK119LBhw7rrcwAAAAAAtLW+uEXGG5LMrLX+Q+v4nlLKX6UjYD6307i6wnllhbYV+1c2BgAAAACAhvriCuaHk/x2hbZ7k2zVev1I63nFlcib5uVVzY8k2bTTthrL9m4ellevfAYAAAAAoIG+GDDfnmSHFdq2T/L71uu56QiQD1jWWUoZnOS9eXnP5TuTvCkdezEvs1eSDfLKfZkBAAAAAGioL26RcVaSO0opX0lydZJdk3w2yZeTjr2USynfSvKVUsp9SWYnOTUdN/X7bmvMvaWUHySZVEr5eDq2xpiU5Pu11vvX9gcCAABoR2fdPLu3S+hzVvc7OeWA7Xu4EgBYO/pcwFxrvauU8sEkX0/y1SR/aD2f32nYxCTrJzkvydAkM5KMqbUu7jRmQpKzk0xrHV+f5NM9Wz0AAAAAwMDR5wLmJKm13pjkxtfor0lOaz1WNWZhkiO6uzYAAAAAADp0aQ/mUsqbeqoQAABoJ+bOAAAMBF29yd8jpZRJpZRde6QaAABoH+bOAAC0va5ukfGtJB9Nclwp5RdJLkhyVa312W6vDAAA+jdzZ6CZW8/o7QroBYtf/FOj8zZc9y+6uRKArunSCuZa66lJtkpyaJKFSf49yYJSyjmllHf0QH0AANAvmTsDADAQdHWLjNRal9Za/2+tdWySv0rHSoxDk/yylPLTUsoRpZQ3dnehAADQ35g7AwDQ7rocMK/giSQL0rEioyQZnuSyJL8rpey1htcGAIB2Yu4MAEDbaRQwl1L2LKVcnGR+kq8nuT3JbrXW7ZKMTPKHJBd2W5UAANBPmTsDANDOunSTv1LKJ5N8Ih0T4dlJvpLk0lrrU8vG1Fp/W0r5apJburNQAADoT8ydAdrH4j890NslrJKbAwK9rUsBc5JvJ7khyedqrdNfY9ycJG57CwDAQGbuDABA2+tqwLx1rXXB6w2qtc5P8tVmJQEAQFswdwYAoO11dQ/mIaWU96yso5Ty7lLK/+qGmgAAoB2YOwMA0Pa6GjB/O8n/s4q+DyU5a83KAQCAtmHuDABA2+vqFhl7JJm0ir4fJzlyjaoBAID2Ye4MAKth/v1PNj53ix2GdmMlQBNdXcH8F0meX0Xfi0k2WrNyAACgbZg7AwDQ9roaMD+QZN9V9O2b5PdrVg4AALQNc2cAANpeVwPm7yT5+1LKJ0opb0ySUsobSymfSHJKksu7u0AAAOinzJ0BAGh7Xd2D+RtJ3pnkgiTnllIeT/KW1nWmJDmze8sDAIB+y9wZAIC216WAuda6NMkHSyljkhyQ5M1J/phkWq31lh6oDwAA+iVzZwAABoKurmBOktRapyWZ1s21AABA2zF3BgCgnTUKmJOklLJJksErttdaF6xRRQAA0GbMnQEAaFddCphLKRsm+dck45MMWcWwdda0KAAA6O/MnQEAGAi6uoL53CSHJbk0ya+TvNDdBQEAQJswdwYAoO11NWA+KMkXaq3n9EQxAADQRsydAQBoe29oMP7enigEAADajLkzAABtr6sB8zVJPtAThQAAQJsxdwYAoO11dYuM7yc5u5SyQZKpSRauOKDWelt3FAYAAP2cuTMAAG2vScCcJNsmOS5J7dRXWsfuhA0AAObOAAAMAF0NmA/okSoAAKD9mDsDAND2uhQw11qn91QhAADQTsydAQAYCLq6gjlJUkoZmmTPJG9OMrXW+mQp5Y211j93a3UAANDPmTsDANDO3tDVE0opZyRZkI4blVyeZJtW142llFO7sTYAAOjXzJ0BAGh3XQqYSylfTHJKkjOSvDsdNydZ5oYkH+i+0gAAoP8ydwYAYCDo6hYZxyf5p1rrv5RSVrzj9Zwk23VPWQAA0O+ZOwMA0Pa6GjCPSHLHKvpeTPKmNSsHAADahrkzsEpn3Tx7lX3v+sMTy1/vte2b10Y5ANBYV/dgXpDk7avoG5lk3hpVAwAA7cPcGQCAttfVgPnaJP9YStmzU1stpfyvJP9vkqu7rTIAAOjfzJ0BAGh7XQ2YT0vyu3T8U797W21XJflNkrnpuIEJAABg7gwAwADQpT2Ya63PlFLel+TIJGOTPJTkiSQTk1xea/1z95cIAAD9j7kzAAADQVdv8pda65Ikl7QeAADAKpg7A8u86w8X9nYJ8LpenL+gy+esu8XmPVAJ0J90dYsMAAAAAABI0sUVzKWUOUnqawyptdYd1qwkAADo/8ydAQAYCLq6RcaMvHqS/OYk70rypyS3dUdRAADQBsydAQBoe129yd8RK2svpWyS5AdJbuyOogAAoL8zdwYAYCDo8k3+VqbWurCUMjHJ6Umu7o5rAgBAOzJ3BuiCuT/p7QoAeB3deZO/Z5Ns1Y3XAwCAdmXuDABAW1jjgLmU8oZSyjuS/GOSe9e8JAAAaE89MXcupWxWSrmslPJ4KeX5UspvSyn7dOovpZTTSikLSinPlVJ+XEp5e3e8NwAAdGmLjFLKn/PqG5W8IUlJ8nSSD3RTXQAA0K+tjblzKWXjJLcn+Wnreo8n2TbJY52GfSHJ55Ick+T+dITbN5dSdqi1Ll7TGgAAGNi6ugfzN/LqSfLzSX6f5MZa65PdUhUAAPR/a2Pu/IUkD9daj+rUNnfZi1JKSXJykjNrrde12o5ORwD9kSSTuqEGAAAGsC4FzLXWU3uqEAAAaCdrae78wSQ/KKVcnWTfJAuS/EeS82qtNck2SYYnmdaprudKKbcl2TsCZgAA1lB33uQPAABYu7ZN8qkkDyQZm+TbSc5McmKrf3jr+dEVznu0U98rlFKOL6XMLKXMfPzxx7u/YgAA2kpX92C+sAvDa631E12sBwAA2sJamju/IcnMWus/tI7vKaX8VToC5nM7X3/F8lbStqyQC5NcmCSjR49e6RgAAFimq3swH5RkwyR/keSlJE8mGZqOie2fknS+SYjJKAAAA9namDs/nOS3K7Tdm+Sk1utHWs/DkzzYacymefWqZgAA6LKubpFxWDomw0ckWb/WOizJ+kmObLUfWmvdsvXYqntLBQCAfmVtzJ1vT7LDCm3bp+NGgknHDf8eSXLAss5SyuAk701yR8P3BACA5bq6gvmsJBNrrd9d1lBr/XOSK0spm6Rjz7c9u7E+AADor9bG3PmsJHeUUr6S5Ookuyb5bJIvt96vllK+leQrpZT7ksxOcmqSp5N8d+WXBACA1dfVFcw7J7l/FX33Jxm5ZuUAAEDb6PG5c631riQfTMdq6d8k+ZckX01yfqdhE5P8a5LzksxMslmSMbXWxQEAgDXU1RXMjyb5cJKbV9J3aJLH1rgiAABoD2tl7lxrvTHJja/RX5Oc1noAAEC36mrA/O0k/6eUMjzJ5HRMmt+ajhUTH0jyue4tDwAA+i1zZwAA2l6XAuZa61mllGfT8c/u/rZT14Ikn6y1XtidxQEAQH9l7gwAwEDQ1RXMqbVOKqX8e5K/TMf+bQ8n+X2t9aXuLg4AAPozc2cAANpdlwPmJGlNiOe2HgAAwCqYO0N7OOvm2b1dAgD0SW/o6gmllFGllGtKKY+UUl4spezWav/nUsqY7i8RAAD6J3NnAADaXZcC5lLK3klmJNk5yf9Nss4K1zqh+0oDAID+y9wZAICBoKsrmL+RZHqSHZN8Nknp1Dczye7dVBcAAPR35s4AALS9ru7BvHuSv6u1vlRKKSv0/THJW7unLAAA6PfMnQEAaHtdDZhfSLL+KvqGJ3lqzcoBAIC2Ye4M0C6WvLD6Ywet13N1APRBXd0i46dJPltK6XxebT1/LMmt3VIVAAD0f+bOAAC0va6uYP7HdEyU70kyOR0T5CNKKROTvCvJO7u3PAAA6LfMnQEAaHtdWsFca70nyfuTLEpyWjpuVHJyksFJ9q213tvN9QEAQL9k7gwAwEDQ1RXMqbXelWSfUsqQJG9J8mStdXG3VwYAAP2cuTMAAO1utQPmUsq6SR5Kcmyt9YZa67NJ/tBjlQEAQD9l7gzQ9yx+dsHLBy8+0XuFALSZ1d4io9b6Yjr+Wd/zPVcOAAD0f+bOAAAMFF3agznJ9Un+ricKAQCANmPuDABA2+vqHszXJzm3lHJVkilJHk7H3bCXq7Xe1k21AQBAf2buDABA2+tqwPxfrefDWo/OE+TSOl6nG+oCAID+ztwZAIC219WA+YAeqQIAANqPuTMAAG3vdQPmUsp+SX5ea3261jp9LdQEAAD9krkzAAADzerc5O/mJDstOyilvKGUclsp5a96riwAAOiXzJ0BABhQVidgLis5fk+SDbu/HAAA6NfMnQEAGFBWJ2AGAAAAAIBXETADAAAAANDI697kr2WLUsq2rdfrdGpbtOLAWusD3VIZAAD0T+bOAAAMGKsbMF+7krYpqxi7ziraAQBgIDB3BgBgwFidgPmjPV4FAAC0B3NnAAAGlNcNmGutl62NQgAAoL8zdwYAYKBxkz8AAAAAABoRMAMAAAAA0IiAGQAAAACARgTMAAAAAAA0ImAGAAAAAKARATMAAAAAAI0M6u0CAAAAgPa09S0P93YJDDB3TL6y8bl7HzqhGyuBgcMKZgAAAAAAGhEwAwAAAADQiIAZAAAAAIBGBMwAAAAAADTiJn8AAAC8wlk3z+7tEgCAfsIKZgAAAAAAGhEwAwAAAADQiIAZAAAAAIBGBMwAAAAAADQiYAYAAAAAoBEBMwAAAAAAjQiYAQAAAABoRMAMAAAAAEAjAmYAAAAAABoRMAMAAAAA0Mig3i4AAAAAAJqYf/+Tjc/dYoeh3VgJDFxWMAMAAAAA0IiAGQAAAACARgTMAAAAAAA0ImAGAAAAAKCRPn+Tv1LKl5P8S5Lzaq2fbrWVJP9fkuOTDE0yI8mJtdb/6XTe0CRnJzm41XR9ks/UWhetxfIBAACgzzp/0a96uwQA+rk+vYK5lPKuJB9PsuL/8b6Q5HNJPpNkjySPJbm5lLJhpzHfTbJbkoOSHNh6fUVP1wwAAAAAMFD02YC5lLJRkiuTHJvkyU7tJcnJSc6stV5Xa/1NkqOTbJjkI60xO6YjVD6+1npHrfXOJJ9I8jellB3W7icBAAAAAGhPfTZgTnJhkmtrrT9aoX2bJMOTTFvWUGt9LsltSfZuNe2V5Okkd3Q67/Ykz3QaAwAAAADAGuiTezCXUj6eZLskR66ke3jr+dEV2h9NskWnMY/XWuuyzlprLaU81un8zu93fDr2c85WW221ZsUDAAAAAAwQfS5gbm1h8fUk7621vvgaQ+sKx2WFthX7VzamY2CtF6ZjxXRGjx69svMAAACAXvTkS/v0dgkArERf3CJjryRvSfKbUsqSUsqSJPsk+VTr9ROtcSuuRN40L69qfiTJpq39mpMs37t5WF698hkAAAAAgAb6YsA8JcnIJLt0esxMclXr9ex0BMgHLDuhlDI4yXvz8p7LdyZ5UzrC6mX2SrJBXrkvMwAAAAAADfW5LTJqrYuSLOrcVkp5JsnCWutvWsffSvKVUsp96QicT03HTf2+27rGvaWUHySZ1NrPuSSZlOT7tdb719qHAQAAAABoY30uYF5NE5Osn+S8JEOTzEgypta6uNOYCUnOTjKtdXx9kk+vzSIBAAAAANpZvwiYa63vX+G4Jjmt9VjVOQuTHNGTdQEAAEBPuvOBJ15/UJK9tn1zD1cC3evF+Qu6fM66W2zeA5UAa6ov7sEMAAAAAEA/IGAGAAAAAKARATMAAAAAAI0ImAEAAAAAaETADAD8/+3de5hlVXkn/u8LLRexiRggCErU0dFEM8YJGkQRvBCTqInRcbyLl4iGqDFqzHjLYDRGYwIyUSegPl4xKvqbRIxRLoooqIBGCVFABEVp7rduELptWL8/9ilyqK6qrtpVp07V6c/neeqpOnuvvfdbe9dln+9ZZy0AAADoRcAMAAAAAEAvAmYAAAAAAHoRMAMAAAAA0IuAGQAAAACAXgTMAAAAAAD0smbcBQAAAADAanfG8ceN5bgHPO3ZYzkuTNGDGQAAAACAXgTMAAAAAAD0ImAGAAAAAKAXATMAAAAAAL2Y5A8AAACAbc6l5193h8dnnnDRvLd92JPus9TlwKqlBzMAAAAAAL0ImAEAAAAA6EXADAAAAABALwJmAAAAAAB6MckfAAAAAL1sunTduEtYMj/+7ufn3XbzLbuNsBJYXfRgBgAAAACgFwEzAAAAAAC9CJgBAAAAAOhFwAwAAAAAQC8CZgAAAAAAehEwAwAAAADQi4AZAAAmRFW9vqpaVb17aFlV1RFVta6qbq6qU6vqgeOsEwCAySFgBgCACVBV+yd5cZJzpq16bZJXJ3l5kocmuTLJSVW1dnkrBABgEgmYAQBglauqX0hyXJIXJbluaHkleWWSt7fWPtNaOzfJoUnWJnnWOGoFAGCyrBl3AQAAwKIdm+TTrbUvVdVfDC2/d5K9kpw4taC1dnNVnZbkgCTHTN9RVR2W5LAk2XfffUdaNAAsxKZL1/Xabod99l7iSoBhejADAMAqVlUvTnLfJG+aYfVeg89XTFt+xdC6O2itHdta26+1tt8ee+yxdIUCADCR9GAGAIBVqqrun+RtSQ5srW2ao2mbvukMywAAYMH0YAYAgNXr4Ul2T3JuVW2uqs1JDkpy+ODrawbtpvdW3jNb9moGAIAFEzADAMDq9U9Jfi3Jrw99nJ3kE4OvL0hyeZJDpjaoqp2SHJjkjOUuFgCAyWOIDAAAWKVaa9cnuX54WVXdlOTa1tq5g8fvSvKGqjovXeD8xiQ3Jvn4MpcLwAqyYdP6Xtut3WHXJa4EWO0EzAAAMNn+JsnOSd6TZLck30zyW621DWOtCgCAiSBgBgCACdJaO3ja45bkiMEHAAAsKWMwAwAAAADQi4AZAAAAAIBeBMwAAAAAAPRiDGYAAABY5d57/TnjLgGAbZQezAAAAAAA9CJgBgAAAACgFwEzAAAAAAC9CJgBAAAAAOjFJH8AAADbiKNOumDcJcDKsHnjuCsAmBh6MAMAAAAA0IuAGQAAAACAXgTMAAAAAAD0ImAGAAAAAKAXATMAAAAAAL0ImAEAAAAA6EXADAAAAABALwJmAAAAAAB6ETADAAAAANCLgBkAAAAAgF4EzAAAAAAA9CJgBgAAAACgFwEzAAAAAAC9CJgBAAAAAOhlzbgLAAAAAIBR2XTpugVvs8M+e4+gEphMejADAAAAANCLgBkAAAAAgF4EzAAAAAAA9CJgBgAAAACgFwEzAAAAAAC9CJgBAAAAAOhFwAwAAAAAQC8CZgAAAAAAehEwAwAAAADQi4AZAAAAAIBe1oy7AAAAAFiN9r/k2HGXAABjpwczAAAAAAC9CJgBAAAAAOhFwAwAAAAAQC8CZgAAAAAAehEwAwAAAADQi4AZAAAAAIBeBMwAAAAAAPQiYAYAAAAAoBcBMwAAAAAAvawZdwEAAADAtuG62w4adwks0oZN63ttt3aHXZe4EmCl0IMZAAAAAIBeBMwAAAAAAPQiYAYAAAAAoBcBMwAAAAAAvZjkDwAAAGCpbN44/7ZrdhxdHQDLRA9mAAAAAAB6ETADAAAAANCLgBkAAAAAgF4EzAAAAAAA9CJgBgAAAACglzXjLgAAAABgm7R54/zbrtlxdHUALIIezAAAAAAA9CJgBgAAAACgFwEzAAAAAAC9CJgBAAAAAOjFJH8AAADAVt3r5MvGXQKr2IZN63ttt3aHXZe4kvnZdOm6OddfPMv6HfbZexTlJEn2uf9uI9s3LIYezAAAAAAA9CJgBgAAAACgFwEzAAAAAAC9CJgBAAAAAOjFJH8AAACwyv3k+pu32uaed915GSoBYFujBzMAAAAAAL0ImAEAAAAA6EXADAAAAABALwJmAAAAAAB6MckfAAAAbAPmMxFgYjJAABZGD2YAAAAAAHoRMAMAAAAA0IuAGQAAAACAXlZcwFxVr6uqs6pqfVVdVVUnVNWDprWpqjqiqtZV1c1VdWpVPXBam92q6qNVdcPg46NVddfl/W4AAAAAACbXSpzk7+Ak701yVpJK8pdJTq6qX22tXTto89okr07y/CTnJ/mLJCdV1f1baxsGbT6eZN8kv5OkJXl/ko8medLyfBsAAAAwea677aBxlwDACrLiAubW2uOHH1fVc5PckOQRSU6oqkryyiRvb619ZtDm0CRXJnlWkmOq6leS/HaSR7bWzhi0eUmSrw5C6POX7RsCAAAAAJhQK26IjBmsTVfndYPH906yV5ITpxq01m5OclqSAwaLHp7kxiRnDO3n9CQ3DbW5XVUdVlVnV9XZV1111ZJ/AwAAAAAAk2g1BMxHJ/nfW/kvAAAgAElEQVROkq8PHu81+HzFtHZXDK3bK8lVrbU2tXLw9ZVDbTK07tjW2n6ttf322GOPpawdAAAAAGBirbghMoZV1ZFJHpluqItbp61u05tPWzZ9/UxtAAAAAADoacUGzFV1VJJnJHl0a+2ioVWXDz7vleQnQ8v3zH/2ar48yZ5VVVO9mAdjN++RLXs+AwAAQPa/5Nhxl7AqbPjZukVtv/bOey9RJUCSnHH8cb23PeBpz17CSthWrcghMqrq6HQT9j2mtXbetNUXpwuQDxlqv1OSA/OfYy5/Pcld0o3FPOXhSXbJHcdlBgAAAACgpxXXg7mq3pPkuUmenOS6qpoaM/nG1tqNrbVWVe9K8oaqOi/JBUnemG5Sv48nSWvt+1X1hSTHVNWL0w2NcUySz7XWzl/mbwkAAAAAYCKtuIA5yeGDz6dMW/7mJEcMvv6bJDsneU+S3ZJ8M8lvtdY2DLV/dpL/k+TEwePPJnnZCOoFAAAAANgmrbiAubVW82jT0oXNR8zR5tokz1mywgAAAAAAuIMVOQYzAAAAAAArn4AZAAAAAIBeBMwAAAAAAPQiYAYAAAAAoBcBMwAAAAAAvQiYAQAAAADoZc24CwAAAACWz4O/dvWc63fdSVQAwPzpwQwAAKtUVb2uqs6qqvVVdVVVnVBVD5rWpqrqiKpaV1U3V9WpVfXAcdUMAMBkETADAMDqdXCS9yY5IMljkmxOcnJV3W2ozWuTvDrJy5M8NMmVSU6qqrXLWyoAAJPI+14AAGCVaq09fvhxVT03yQ1JHpHkhKqqJK9M8vbW2mcGbQ5NFzI/K8kxy1sxAACTRg9mAACYHGvT3eNfN3h87yR7JTlxqkFr7eYkp6Xr9QwAAIuiBzMAAEyOo5N8J8nXB4/3Gny+Ylq7K5LsM9MOquqwJIclyb777juCEoFt3Yafreu97do7772ElQCwFPRgBgCACVBVRyZ5ZJKnttZunba6TW8+w7KuYWvHttb2a63tt8cee4ygUgAAJomAGQAAVrmqOirJM5M8prV20dCqywef95q2yZ7ZslczAAAsmIAZAABWsao6Ot2EfY9prZ03bfXF6ULmQ4ba75TkwCRnLFuRAABMLGMwAwDAKlVV70ny3CRPTnJdVU31VL6xtXZja61V1buSvKGqzktyQZI3JrkxycfHUjQAABNFwAwAAKvX4YPPp0xb/uYkRwy+/pskOyd5T5LdknwzyW+11jYsR4HAwnx2uwvHXcKKtpgJAgEYDQEzAACsUq21mkebli5sPmLU9QAAsO0xBjMAAAAAAL0ImAEAAAAA6EXADAAAAABALwJmAAAAAAB6ETADAAAAANCLgBkAAAAAgF4EzAAAAAAA9CJgBgAAAACgFwEzAAAAAAC9rBl3AQAAAMzuqJMuGHcJq9r+lxw77hIAYKLpwQwAAAAAQC8CZgAAAAAAehEwAwAAAADQi4AZAAAAAIBeTPIHAAAA3G79LZvnXH/rbS1Jsv12tRzlALDC6cEMAAAAAEAvAmYAAAAAAHoRMAMAAAAA0IuAGQAAAACAXkzyBwAAANuYazY9YNH7mJrsb2tMBrhENm+cf9s1O46uDoBp9GAGAAAAAKAXATMAAAAAAL0ImAEAAAAA6EXADAAAAABALyb5AwAAgCX22e0uXFD7B3/t6u7zAo/z3UfuvsAtYHXZsGl9723X7rDrElYyP5suXbfgbXbYZ+8RVALLRw9mAAAAAAB6ETADAAAAANCLgBkAAAAAgF4EzAAAAAAA9GKSPwAAAIBJsnnjwtqv2XE0dQDbBD2YAQAAAADoRcAMAAAAAEAvAmYAAAAAAHoRMAMAAAAA0IuAGQAAAACAXtaMuwAAAADY/5Jj5932G/seNsJKVpcHf+3qcZcArGJnHH9c720PeNqzl7ASVjM9mAEAAAAA6EXADAAAAABALwJmAAAAAAB6ETADAAAAANCLSf4AAABYVRYyIeAk+9l2j17E1pctWR0AbNv0YAYAAAAAoBcBMwAAAAAAvQiYAQAAAADoRcAMAAAAAEAvJvkDAACAWXx2uwvHXQJAkuTS86/rve0+999tCSuBO9KDGQAAAACAXgTMAAAAAAD0ImAGAAAAAKAXATMAAAAAAL2Y5A8AAICR2P+SY5d8n30n3fu92+67xJUwX7fe1ubVbvvtasSVsK3ZsGl9r+3W7rDrElcyt02Xruu13Q777L3ElcxstskFzzzhoq1u+7An3WfWdWccf1zvmg542rN7b8vS04MZAAAAAIBeBMwAAAAAAPQiYAYAAAAAoBcBMwAAAAAAvZjkDwAAAAAm2GwT9cFS0IMZAAAAAIBeBMwAAAAAAPQiYAYAAAAAoBcBMwAAAAAAvZjkDwAAgImw609/c9Z169rd5tx2731+sMWynU6/IA+uaxdcx3cfufuCtwFWjg2b1i/r8dbusGuv7TZdum7B2+ywz969jjWTH3/381tts/mW3ZbseKxcejADAAAAANCLgBkAAAAAgF4EzAAAAAAA9CJgBgAAAACgFwEzAAAAAAC9rBl3AQAAALCa/Wy7R9/h8a4/vfO8t9188xlJkvUbd1rwcX9ely14G4DlsunSdbnp+h8saJtdfvNht3996fnXzdruzBMumnM/D3vSfRZ0XBZHD2YAAAAAAHoRMAMAAAAA0IuAGQAAAACAXgTMAAAAAAD0YpI/AACAMTjqpAvGXcI25YK6ds71Z2934RbLHryVbRiPW29rW22z/Xa1DJVMkM0bR7PfNTuOZr9s83783c/PuX7zLbvNuu6Apz17qcvZ5unBDAAAAABALwJmAAAAAAB6ETADAAAAANCLgBkAAAAAgF5M8gcAADAPJuWbXNtfcUnufPOtWyxfv3GneW3/87rsDo93XdCPyi8N9rGQbSbTfCbvA5bfpkvXjbuEBbv0/OtmXXf8W98957b73H/2CQIXa1InGNSDGQAAAACAXgTMAAAAAAD0ImAGAAAAAKAXATMAAAAAAL2Y5A8AANimbeuT9+1/ybHzbvuNfQ/bYtm3139y1vZXbndhr5q25sFfu3rG5T/b7me99nfzLT/PLjf80hbLTbwHi7R542j2u2bH0ex3G7AaJ+ybJGccf1zvbVfyBIF6MAMAAAAA0IuAGQAAAACAXgTMAAAAAAD0ImAGAAAAAKAXk/wBAABMmIVM3LdUDjzlnC2W7bpx5sn4ZrN+407za5ct2+264y0LOhYkya23tXm12347Mz6uaguZbHAMEwhu2LS+13Zrd9h1iSuZW586N7crsvdd9h5BNawkejADAAAAANCLgBkAAAAAgF4EzAAAAAAA9CJgBgAAAACgFwEzAAAAAAC9rBl3AQAAAFOOOumCebX700P+64grWb2+vf6TuXK7C5dkX7v+9Dfv8Hj9NWds0eYeuWeS5NbbdrjD8u23O3tJapiv9Rt3ys/rsmU9JivXrbe1cZfAKG3eOO4KVrUNm9Yv27Fu/vkv5cqbdpl3+x3Ov26E1TAqE92DuaoOr6qLq+qWqvpWVR047poAAGAc3BsDADAKExswV9XTkxyd5G1JHpLkjCT/WlX7jrUwAABYZu6NAQAYlYkNmJO8KsmHWmvva619v7X28iSXJfmjMdcFAADLzb0xAAAjMZEBc1XtkOQ3kpw4bdWJSQ5Y/ooAAGA83BsDADBKkzrJ3+5Jtk9yxbTlVyR53PTGVXVYksMGD2+sqvNHW942bfckV4+7CJaUazp5lvSavuxjH1iqXdGf39PJ45qO1i+Pu4AlNpH3xq8a3a79ft3BP2+tgfO1cM7ZwjhfC+N8LZxztjDO18Is4fl6ztLsZmHmdV88qQHzlOnTxtYMy9JaOzbJsctS0Tauqs5ure037jpYOq7p5HFNJ49rOnlcU3pybzwPfr8WxvlaOOdsYZyvhXG+Fs45Wxjna2G2lfM1kUNkpHtl4NYke01bvme27LkBAACTzL0xAAAjM5EBc2ttU5JvJTlk2qpD0s2YDQAA2wT3xgAAjNIkD5FxZJKPVtWZSU5P8tIkeyf5h7FWxTb7dssJ5ppOHtd08rimk8c1ZaHcG8+f36+Fcb4WzjlbGOdrYZyvhXPOFsb5Wpht4nxVa1sMuzYxqurwJK9Ncvck5yb509baaeOtCgAAlp97YwAARmGiA2YAAAAAAEZnIsdgBgAAAABg9ATMAAAAAAD0ImBmpKpqx6r6+6q6uqpuqqrPVtU9FrD966uqVdW7R1kn89fnmlbV66rqrKpaX1VXVdUJVfWg5aqZO6qqw6vq4qq6paq+VVUHbqX9QYN2t1TVRVX10uWqlflZyDWtqqdU1YmD38UNVfXNqvq95ayXrVvo7+nQdo+sqs1Vde6oa4RJUVVHDO43hz8uH3ddK11V3b2qPjz4f3JLVX2vqg4ad10rUVX9aIafsVZV/zLu2laiqtq+qt4y9H/w4qp6a1WtGXdtK1lVra2qd1XVj6vq5qo6o6oeOu66VoKqetTgeeulg9+9509bX4P/BesG5+7UqnrgmMpdEeZxzp5SVV8c/A9oVXXweCpdGeY6X1V1p6p6R1WdM8hQLquqj1fVvmMseckJmBm1dyV5apJnJjkwya5JPldV229tw6raP8mLk5wz0gpZqD7X9OAk701yQJLHJNmc5OSquttoS2W6qnp6kqOTvC3JQ5KckeRfZ/vnVlX3TvL5QbuHJPnrJH9fVU9dnorZmoVe0yQHJflSkicM2n8+yf+bb4DJ6PW4plPb7ZbkI0lOGXmRMHnOTzf54dTHr423nJWtqu6a5PQkle7/ya8keXmSK8dZ1wr20Nzx5+u/J2lJPjXOolawP0/yx0lekeQBSf5k8Ph14yxqFXh/kscnOTTd37AT0z3n2mesVa0Md0k3ue2fJLl5hvWvTfLqdH/HHprub9lJVbV22SpcebZ2znZJd4/6quUsagWb63zdOd3f/b8afP79JPdM8oVJeuHMJH+MTFX9QpKrkrygtXbcYNk9k/w4ye+01r64lW2/nS5g/osk57bWXjb6qpnLYq7ptP3cJckNSZ7cWjthVPWypar6ZpJzWmsvHlr2gySfbq1tcdNeVe9I8pTW2v2Glr0/yQNbaw9fjpqZ20Kv6Sz7ODPJV1trrx5RmSxA32taVf9fku+mC3z+R2vNO0VgHqrqiPidWZCqeluSg1prjxh3LatRVb0hyZ8l2bu19rNx17PSVNXnklzTWjt0aNmHk/xia+2J46ts5aqqnZNsSPLU1to/Dy3/VpJ/ba29cWzFrTBVdWOSl7XWPjR4XEnWJXl3a+2vBst2Thcyv6a1dsy4al0ppp+zaet2T5cRPLq1duoyl7YizXW+htr8apL/SPLfWmv/vly1jZIezIzSbyS5U7pXTpMkrbWfJPl+up6sczk23RPpL42uPHpYzDUdtjbd35/rlrQ65lRVO6S7hidOW3ViZr9+D5+h/ReT7FdVd1raClmontd0Jmvj93FF6HtNq+rwJHsleevoqoOJdp/B21ovrqpPVNV9xl3QCvfkJN+sqk9W1ZVV9Z2qetkgqGEOg3P0oiQfEy7P6mtJHl1VD0huD2Iek+5dV8xsTZLtk9wybfnNSR65/OWsKvdOdw81/Bz35iSnZWH307AQuw4+T8xzMAEzo7RXkluTXD1t+RWDdTOqqhcnuW+SN42uNHrqdU1ncHSS7yT5+hLVxfzsnu7G84ppy+e6fnvN0n7NYH+MV59regdV9cdJ7pHko0tbGj0t+JpW1a8l+d9Jnt1au3W05cFE+maS5yf5nXTvntsryRlV9YvjLGqFu0+Sw5NclO4t+UcneXu6YQyY2yHpAq33j7uQFewd6e5LvldVP0/Xy+/DrbX3jreslau1tiHdc6s3VtU+g3Gsn5Ous8jdx1vdijd1f9X7fhoWYtCh5O+SnNBa++m461kqAmYWbDDBwkyTVAx/HDzXLtKNOTbTvu+fbszJZ7fWNo2gfGYwyms6w7GOTPcq+lMFIWMz/Vpt7frN1H6m5YzPQq9p16gbS/ud6f7m/ngUhdHbvK5pVe2Y5BPp3sJ58XIUBpOmtfavrbVPtdbOaa2dnOSJ6Z4nHbqVTbdl2yX5dmvtda21f2utfTDJ/4mAeT5enOSs1tp3xl3ICvb0JM9L8qx045U+L8nhVfWisVa18j03yW1JfppkY7oxrP8xXQchtq7X/TQsxGDM5Y8luWuSF4y5nCU1MYNJs6zele4XYi6XJNk/XS+sqTF5puyZ7u0mM3n4oP25Q++w2z7Jo6rqpUl2aa1t7Fk3sxvlNb1dVR2V5Bnpxme6qF+pLMLV6W4wp78Sv2e2fMV+yuWztN+c5JolrY4++lzTJLeHyx9N8rzW2mdHUx49LPSa3j3Jryb5YFV9cLBsu3Tvwt6c5Hdba9OH2wDm0Fq7sar+I8n9ttp423VZku9NW/b9dJMbMYuq2jPd5E6C+Lm9M8nfttY+MXj871X1y+km+fvA+Mpa2VprP0xyUFXtkmTX1tplVfXJJF6Antvlg897JfnJ0PKt3k/DQgzC5X9MNwnnwa21iXo+LWBmwVprV2fLIRK2MJhQ4Ofp3gb28cGye6SbZfqMWTb7pyRnT1v2wSQ/SNezWa/mERjxNZ3a9uh04fLBrbXzFlszC9da2zS4hockOX5o1SFJPjPLZl9PN87isEOSnN1a+/nSV8lC9Lymqar/meTDSQ5trX16tFWyED2u6aXpblKHHT5o/wdJfjSCMmGiVdVOSR6Q5MvjrmUFOz3J/act+6/pJn5mds9P17P0E1tpt627c7bsdXtrvAN7XlprNyW5qap2SzeEzWvHXNJKd3G6kPmQJGclt/8fODDdZJywaIP5iz6R5EHpMpHLt7LJqiNgZmRaazdU1QeSvLOqrkzX2/HIJOckOXmqXVWdl27G1ne31q5Pcv3wfqrqpiTXttbOXb7qmUmfazp4/J50b9l6cpLrqmqqZ96NrbUbl/N7IEcm+WhVnZnuyeFLk+yd5B+SpKo+kiSttecN2v9DkpdV1buSHJPkEemeHD1zectmDgu6plX1jHQ9l1+T5LSh38dNrbVrl7l2Zjbvazp4oecO/x8Hf583+r8J81NVf5vkhHTv1toz3Twgu6R7IY6ZHZVunOo3JPlkkoekezv+68da1Qo2mNzvD5N8YjBeLrM7Icn/qqqL042//JAkr0rykbFWtcJV1ePThfDnpZvT6J1Jzk/XYWubVlV3SXdOku4c7VtVv54uZ7hk8FznDYPnsRckeWOSGzPoVLUtmsc5u1uSfdMN9ZAk962q65NcPonh6dbMdb6SrEvXceShSZ6UpA09B7thMKnkqidgZtT+NN1b6T+ZZOckp6R7O/bwK9L3j8nCVpM+1/TwwedTpu3rzUmOGE2ZzKS19snBpEVvTPfW+nPTvYV+qsfRvtPaX1xVv5vuieQfpfvn+IrW2qy9Y1leC72m6cLKNemGxnnX0PKvJDl4tNUyHz2uKbA490j3ltWpIcC+kWR/Y9PPrrV2VlU9Od07DN+ULpx/UxKTsM3u4HTDrjxnzHWsBi9P8pZ0P097phuS5X1J/nKcRa0Cv5Dkr9P9Tbs23Tuf3uBdh0mS/XLHd6W8efDx4XSdZ/4m3XPb9yTZLd3kr7+1jb8YtLVz9nu544sX7xtqd8Toy1tx5jpfR6QbHilJvjVtuxck+dCIa1sW1ZoxywEAAAAAWDhjGAEAAAAA0IuAGQAAAACAXgTMAAAAAAD0ImAGAAAAAKAXATMAAAAAAL0ImAEAAAAA6EXADDABqur5VdWGPjZV1Q+r6m1VtdMIj3vw4HiPG9UxAACYn6p6eFV9qqrWDe4Hr6mqk6rq0KrafomPNXX/ea+l3O9iLXVdQ/e7Bw8tO7WqTl2K/Q/t80NV9aOhx/eqqiOq6j5LeZzFGpzfF86yfMX9PADLQ8AMMFmeluThSZ6Q5ItJXpfknWOtCACAkauqVyY5Pcndkvx5kscleWGSC5L83yRPXOJD/ku6+87Llni/i7XUdX17sL9vL9H+ZvOWJH8w9PheSf53khUVMCd5frqfq+lW6s8DsAzWjLsAAJbUd1prFw6+Pqmq7pfkRVX1J62128ZZGAAAo1FVj0pyZJJ3t9ZeMW31P1fVkUl2WcpjttauSnLVUu5zKSx1Xa219Um+sVT7m66qdmytbWyt/XBUx5jP8Re7n5X68wAsDz2YASbbt5PsnGT3JKmqParqmKq6oKp+VlU/qaqPV9U+wxsN3o7Xqup+VfUvVXVjVf24qv6iqub831FV96mqH1TV6VW12+i+NQAABv5XkmuTvHamla21H7bWzpl6XFUPq6qTB/d4N1XVKVX1sOFtquqhg+E1rhncN15UVe8dWr/FkAhV9aOq+lhVPaOqvj/Y99lV9cjpNVXVQYPjbhi0+2JVPWhr3+gi63puVZ1fVTdX1VcH97q7DO6Pr6mqK6rq76pqzdC2WwyRMUNNO1XVUVV17uCcXl5VJ1TVA6a1m6rtUVV1fFVdn+Sbg3W3D5ExONaXB5udVP85DN7BVfW5qtqiN3VV3buqbquql8xR59T38pSqel9VXZXkisG6+1bVR6vq4sH5uaiq/u/w/fxgWJCDkjxiqKZT5zjvd6qqtw7O/6bB57dW1Z1mqxFYnQTMAJPtXkluSHLN4PHdktySbuiM307yZ0nul+T0mnms5v+X5EtJnpzkn5K8Ocmhsx2sqh6S5Iwk30/yuNbadUvyXQAAMKPqxlY+OMmJrbVb5tH+vyX5SpLd0g138Lwkuyb5SlU9eNDmLumGW7t10OZ3k/xl5vcu6AOTvDrJm5I8Pcn2ST5XVXcdquEJSU5JcmOS5yR5VpK1Sb5aVfeco/bF1PWoJIenGz7k0CT/JclnkhyXZEOSZyQ5Nsmrkhw2j/0N23FQ/1vTDVX3R0l2SvKNqtprhvbHJbk4yf9I9+LAdN9O8seDr1+RbuiJqWE63pvkIdNfEBjUfFOSj8+j3r9PUkmem+48JsneSX6a5JVJHp/uvD42yeeHtjs8yb8lOWeopsPnOM6H031/H0k3RMsH053/D8+jRmAVMUQGwGTZftDjYm26MdyemuSVrbVbk6S1dn6SP5lqPHhCcnqSS5L8TrpAedjftdY+OPj65Kp6TJJnprs5vIOqeuxg++OTHDZ1TAAARmr3dO9Y+/E82/9Fko1JHttauz5JquqkJD9KN+bvU5I8IF0A/drhns9JPjSP/e+a5NenOhpU1eVJzkoXBk+Fn0cn+Upr7fenNqqqLye5KF04/cpZ9r2Yuu6S5LdbazcMjrfXoI4zW2uvGbQ5aRB+Py1dkDsvg33+4dD3sn26IPyKdPfOR03b5NOttRl7mw/2t76qvjd4+P3W2u1DdFTVF9Kdp5ckOXOw7E5JXpDkuNbahnmUfGZr7Q+HF7TWTkty2tBxzkhyYbrQ/yGttX9rrX2vqtYnWTNc00wGvdGfmeTNrbUjBotPrKpbk7ylqt4+7RoCq5gezACT5bwkP0/3FskPJDmmtfbu4QZV9UdV9d2qujHJ5nThcpLcf4b9/cu0x+cm2XeGdk9L17vhPa21FwmXAQBWrEcl+dxUuJzcPs7wZ9MNf5AkP0hyfZJjquo5c/UqnsHXp72L7d8Hn/dNkurmCPkvSY6rqjVTH0l+luTrg/pms9i6bhh6fN7g8xentTsvyUL2mySpqv9ZVd8cDHuxOV1v4rtk5nvs6Z065m0wr8oxSZ5RVb8wWPzkJL80WD4fWxy/qnaoqtdX1XlVdXO65xRfHaye6XvYmqnr+LFpy6ceHxRgYgiYASbLHyR5aLoeIicnObyqnje1sqpenq43xsnpeqc8LMn+g9UzDZFx7bTHG2dp99QkN2eGns0AAIzUNenuw355nu3vluSyGZZfnq538FSP3EcnWZfu3vGSwfjCT53H/u9w/zg0gdzUPeSeg88fSBdiDn88MckvzrbjRdY1fei2TXMsn+l+d1ZV9aQkn0w3TNyzkvxmunvyq2bZ10znfyE+kC7Pee7g8UvT9Ur+t3luP9Px/zrJEekC4Ceke57wlMG6BZ2PgbvNcqzLp60HJoAhMgAmy7mttQuTpKq+lG58tHdW1WdaazelG1vulNbaq6c2qKp7L8FxD0vymiSnVtVjWmvnbW0DAAAWr7W2eTDR2iFVteNQoDuba5PMNC7wXhkKh1tr30ny1EHv4v3SzeHxqap6cGvt3EWUPDU3yOvSdXqYbtMMy243wroW4xlJLmytPX9qwWDYitlC1LaYg7XWrqmq45O8pKq+mC50/8OtbLa14z8jyUdaa2+dWjAY87qvqZ+lvZL8cGj51M/eNQEmhh7MABNq8OTiz9L1EpmafOPO6XqHDHvBEhxufbrJQC5K8uWq+pUl2CcAAPPz9nQ9f98508qquvdgcr+km+DvCVW1dmj92iRPGqy7g9ba5sF4u29KlyEs9j7v/HTjPT+wtXb2DB/zGpd3BHUtxp3TDYsx7LnpJjjsa+qFgp1nWf/eJA9K8v509+KfWMSxkvk/T9g4R03Dpn6WnjFt+bMHn08LMDH0YAaYYK21z1bVWUleU1XvTvKFJH9eVa9PNynIY9LNXr0Ux9pQVb+dbtzmL1fVY1tr/7EU+wYAYHattdOq6lVJjhy80P+hdPNs7Jbksel6tz4r3bvb3pJuKIpTquod6Xqz/nm6gPEvk6SqnpjuHWr/lOTiJLskeUWSDenGSV5Mra2q/jjJP1fVDkk+leTqdGMIH5DkktbakTNtO8q6FukLSZ5cVUcl+VyS3xjUdf2cW83tgnSh9Qur6tp0we75U5P4tda+UVXfTjfW8d+31n62mG8g3fdwaFX9e7rJ/Z6S7npM9710w/A9PV3P5A2DicTvoLX2H1X1j0mOGPQ2PyPJw9O9IPCPJviDySJgBph8b0w3eclL0z1puGuSP003ltpX8p89jxettXZjVf1ukhOSfGkQMo/rrYoAANuM1tq7qurMdHJoDuoAAAE3SURBVPd5f5tk93TB69lJXpLu/iyttXOq6uAkf5Xkw0kqyTeSHNRa++5gdz9IN67zm5LcfbCfs5Ic0lr76RLU+vmqelSSN6TrgbtzurF5v5FuLOPZjLSuRXhfuokBX5juXJ+Vrkf4Yibzu6aqXpYu/P9Kut7Qj05y6lCzTyf575n/5H5zeXm6n4W/Gjz+fJJnpuuUMuwd6Sb9e3+6SQy/kuTgWfZ5aLrnGS9M95xk3WD7Ny9BvcAKUq0taugfAAAAAJZZVZ2e5LbW2oHjrgXYtunBDAAAALAKVNWO6XotPy7dEBa/P96KAATMAAAAAKvF3dONZ3x9kre11j475noADJEBAAAAAEA/2427AAAAAAAAVicBMwAAAAAAvQiYAQAAAADoRcAMAAAAAEAvAmYAAAAAAHr5/wGNEhm2nMBiTQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1440x1440 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotvectortest(sizeindtest, sizecostest, sizemeantest)\n",
    "plt.tight_layout()\n",
    "plt.savefig('fig/OPT_vectors.jpg', format='jpg', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "sizeratiotest = {}\n",
    "\n",
    "for key in sizemeantest:\n",
    "    sizeratiotest[key] = np.array(sizecostest[key]) / np.array(sizemeantest[key])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[15,10])\n",
    "ax = plt.subplot(111)\n",
    "pt = plt.violinplot(pd.DataFrame.from_dict(sizeratiotest, orient='index'), showmeans=True, showextrema=False)\n",
    "for p in pt['bodies']:\n",
    "    p.set_facecolor('#D43F3A')\n",
    "    p.set_alpha(0.6)\n",
    "\n",
    "pt['cmeans'].set_color('#1b325fff')\n",
    "pt['cmeans'].set_linewidth(4)\n",
    "\n",
    "ax.set_xticklabels([0,100,200,300,400,500,600], fontsize=16)\n",
    "ax.set_ylim(-1,13)\n",
    "ax.set_yticklabels(['',0,'',4,'',8,'',12],fontsize=16)\n",
    "ax.set_ylabel('Self:mean cosine similarity', fontsize=20)\n",
    "ax.set_xlabel('Vector dimensionality', fontsize=20)\n",
    "plt.tight_layout()\n",
    "plt.savefig('fig/OPT_vectors2.jpg', format='jpg', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Testing the effect of different alphas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "alpha 0.025 vocabulary scanned & state initialized\n",
      "alpha 0.050 vocabulary scanned & state initialized\n",
      "alpha 0.075 vocabulary scanned & state initialized\n",
      "Training alpha 0.025\n",
      "Training alpha 0.050\n",
      "Training alpha 0.075\n",
      "CPU times: user 2h 16min 44s, sys: 20.1 s, total: 2h 17min 4s\n",
      "Wall time: 36min 38s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "alphatest = [\n",
    "    Doc2Vec(dm=0, dbow_words=1, vector_size=150, window=8, epochs=50, min_count=2, alpha=0.025, min_alpha=0.025, workers=numcores, comment='alpha 0.025'),\n",
    "    Doc2Vec(dm=0, dbow_words=1, vector_size=150, window=8, epochs=50, min_count=2, alpha=0.050, min_alpha=0.050, workers=numcores, comment='alpha 0.050'),\n",
    "    Doc2Vec(dm=0, dbow_words=1, vector_size=150, window=8, epochs=50, min_count=2, alpha=0.075, min_alpha=0.075, workers=numcores, comment='alpha 0.075')\n",
    "]\n",
    "\n",
    "for model in alphatest:\n",
    "    model.build_vocab(allao)\n",
    "    print(\"%s vocabulary scanned & state initialized\" % model.comment)\n",
    "    \n",
    "for model in alphatest: \n",
    "    print(\"Training %s\" % model.comment)\n",
    "    aoshuf = allao[:]  \n",
    "    genstorun = 50\n",
    "    alphastep = model.alpha*0.9/genstorun\n",
    "    for epoch in range(genstorun):\n",
    "        shuffle(aoshuf)\n",
    "        model.train(aoshuf, total_examples=model.corpus_count, epochs=1)\n",
    "        model.alpha -= alphastep\n",
    "        model.min_alpha = model.alpha"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "alphaindtest, alphacostest, alphameantest = testself(alphatest, N=1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotvectortest(alphaindtest, alphacostest, alphameantest)\n",
    "plt.tight_layout()\n",
    "plt.savefig('fig/OPT_alpha.jpg', format='jpg', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Testing the effect of the number of iterations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20 epochs vocabulary scanned & state initialized\n",
      "50 epochs vocabulary scanned & state initialized\n",
      "100 epochs vocabulary scanned & state initialized\n",
      "Training 20 epochs\n",
      "Training 50 epochs\n",
      "Training 100 epochs\n",
      "CPU times: user 2h 34min 58s, sys: 25.3 s, total: 2h 35min 23s\n",
      "Wall time: 42min 21s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "itertest = [\n",
    "    Doc2Vec(dm=0, dbow_words=1, vector_size=150, window=8, epochs=  20, min_count=2, alpha=0.050, min_alpha=0.05, workers=numcores, comment='20 epochs'),\n",
    "    Doc2Vec(dm=0, dbow_words=1, vector_size=150, window=8, epochs=  50, min_count=2, alpha=0.050, min_alpha=0.05, workers=numcores, comment='50 epochs'),\n",
    "    Doc2Vec(dm=0, dbow_words=1, vector_size=150, window=8, epochs= 100, min_count=2, alpha=0.050, min_alpha=0.05, workers=numcores, comment='100 epochs')\n",
    "]\n",
    "\n",
    "for model in itertest:\n",
    "    model.build_vocab(allao)\n",
    "    print(\"%s vocabulary scanned & state initialized\" % model.comment)\n",
    "    \n",
    "for model in itertest: \n",
    "    print(\"Training %s\" % model.comment)\n",
    "    aoshuf = allao[:]  \n",
    "    genstorun = model.epochs\n",
    "    alphastep = model.alpha*0.9/genstorun\n",
    "    for epoch in range(genstorun):\n",
    "        shuffle(aoshuf)\n",
    "        model.train(aoshuf, total_examples=model.corpus_count, epochs=1)\n",
    "        model.alpha -= alphastep\n",
    "        model.min_alpha = model.alpha"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "iterindtest, itercostest, itermeantest = testself(itertest, N=1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotvectortest(iterindtest, itercostest, itermeantest )\n",
    "plt.tight_layout()\n",
    "plt.savefig('fig/OPT_alpha.jpg', format='jpg', dpi=300)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}