03-churn-prediction.ipynb

{
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   "cell_type": "markdown",
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   "source": [
    "# Mobile phone customer churn\n",
    "\n",
    "*This notebook first appeared as a part of [forests-intro](https://github.com/wildtreetech/forests-intro).*\n",
    "\n",
    "<a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-sa/4.0/\"><img alt=\"Creative Commons License\" style=\"border-width:0; display: inline\" src=\"https://i.creativecommons.org/l/by-nc-sa/4.0/80x15.png\" /></a><br /><span xmlns:dct=\"http://purl.org/dc/terms/\" property=\"dct:title\">Forests intro</span> by <a xmlns:cc=\"http://creativecommons.org/ns#\" href=\"https://github.com/wildtreetech/forests-intro\" property=\"cc:attributionName\" rel=\"cc:attributionURL\">Tim Head</a> is licensed under a <a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-sa/4.0/\">Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License</a>.\n",
    "\n",
    "*Feel free to use, distribute, and modify with the above attribution.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%config InlineBackend.figure_format='retina'\n",
    "%matplotlib inline\n",
    "\n",
    "import numpy as np\n",
    "np.random.seed(123)\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams[\"figure.figsize\"] = (8, 8)\n",
    "plt.rcParams[\"font.size\"] = 14\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "churn_df = pd.read_csv('churn.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# A real mix of feature types\n",
    "\n",
    "This data set consists of a mixed bag of features. Some are categories, some strings,\n",
    "some numerical, ... with different scales/ranges.\n",
    "\n",
    "Tree based methods are fairly robust against this. For Neural Networks you commonly\n",
    "have to center and scale all your numerical features, figure out what to do with\n",
    "categories, etc. No such preprocessing is needed here. Tree based models also deal\n",
    "fairly well with \"useless\" features or repeated features. This means you can save\n",
    "yourself the time of having to do feature removal if you have a lot of them. Or even\n",
    "use the random forest you built to learn about the \"important\" features of your\n",
    "data.\n",
    "\n",
    "*Note: These statements come with all sorts of caveats, ask me over beer.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>State</th>\n",
       "      <td>KS</td>\n",
       "      <td>OH</td>\n",
       "      <td>NJ</td>\n",
       "      <td>OH</td>\n",
       "      <td>OK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Account Length</th>\n",
       "      <td>128</td>\n",
       "      <td>107</td>\n",
       "      <td>137</td>\n",
       "      <td>84</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Area Code</th>\n",
       "      <td>415</td>\n",
       "      <td>415</td>\n",
       "      <td>415</td>\n",
       "      <td>408</td>\n",
       "      <td>415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Phone</th>\n",
       "      <td>382-4657</td>\n",
       "      <td>371-7191</td>\n",
       "      <td>358-1921</td>\n",
       "      <td>375-9999</td>\n",
       "      <td>330-6626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Int'l Plan</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VMail Plan</th>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VMail Message</th>\n",
       "      <td>25</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Day Mins</th>\n",
       "      <td>265.1</td>\n",
       "      <td>161.6</td>\n",
       "      <td>243.4</td>\n",
       "      <td>299.4</td>\n",
       "      <td>166.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Day Calls</th>\n",
       "      <td>110</td>\n",
       "      <td>123</td>\n",
       "      <td>114</td>\n",
       "      <td>71</td>\n",
       "      <td>113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Day Charge</th>\n",
       "      <td>45.07</td>\n",
       "      <td>27.47</td>\n",
       "      <td>41.38</td>\n",
       "      <td>50.9</td>\n",
       "      <td>28.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Eve Mins</th>\n",
       "      <td>197.4</td>\n",
       "      <td>195.5</td>\n",
       "      <td>121.2</td>\n",
       "      <td>61.9</td>\n",
       "      <td>148.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Eve Calls</th>\n",
       "      <td>99</td>\n",
       "      <td>103</td>\n",
       "      <td>110</td>\n",
       "      <td>88</td>\n",
       "      <td>122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Eve Charge</th>\n",
       "      <td>16.78</td>\n",
       "      <td>16.62</td>\n",
       "      <td>10.3</td>\n",
       "      <td>5.26</td>\n",
       "      <td>12.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Night Mins</th>\n",
       "      <td>244.7</td>\n",
       "      <td>254.4</td>\n",
       "      <td>162.6</td>\n",
       "      <td>196.9</td>\n",
       "      <td>186.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Night Calls</th>\n",
       "      <td>91</td>\n",
       "      <td>103</td>\n",
       "      <td>104</td>\n",
       "      <td>89</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Night Charge</th>\n",
       "      <td>11.01</td>\n",
       "      <td>11.45</td>\n",
       "      <td>7.32</td>\n",
       "      <td>8.86</td>\n",
       "      <td>8.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Intl Mins</th>\n",
       "      <td>10</td>\n",
       "      <td>13.7</td>\n",
       "      <td>12.2</td>\n",
       "      <td>6.6</td>\n",
       "      <td>10.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Intl Calls</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Intl Charge</th>\n",
       "      <td>2.7</td>\n",
       "      <td>3.7</td>\n",
       "      <td>3.29</td>\n",
       "      <td>1.78</td>\n",
       "      <td>2.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CustServ Calls</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Churn?</th>\n",
       "      <td>False.</td>\n",
       "      <td>False.</td>\n",
       "      <td>False.</td>\n",
       "      <td>False.</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       0         1         2         3         4\n",
       "State                 KS        OH        NJ        OH        OK\n",
       "Account Length       128       107       137        84        75\n",
       "Area Code            415       415       415       408       415\n",
       "Phone           382-4657  371-7191  358-1921  375-9999  330-6626\n",
       "Int'l Plan            no        no        no       yes       yes\n",
       "VMail Plan           yes       yes        no        no        no\n",
       "VMail Message         25        26         0         0         0\n",
       "Day Mins           265.1     161.6     243.4     299.4     166.7\n",
       "Day Calls            110       123       114        71       113\n",
       "Day Charge         45.07     27.47     41.38      50.9     28.34\n",
       "Eve Mins           197.4     195.5     121.2      61.9     148.3\n",
       "Eve Calls             99       103       110        88       122\n",
       "Eve Charge         16.78     16.62      10.3      5.26     12.61\n",
       "Night Mins         244.7     254.4     162.6     196.9     186.9\n",
       "Night Calls           91       103       104        89       121\n",
       "Night Charge       11.01     11.45      7.32      8.86      8.41\n",
       "Intl Mins             10      13.7      12.2       6.6      10.1\n",
       "Intl Calls             3         3         5         7         3\n",
       "Intl Charge          2.7       3.7      3.29      1.78      2.73\n",
       "CustServ Calls         1         1         0         2         3\n",
       "Churn?            False.    False.    False.    False.    False."
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "churn_df.head().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3333, 21)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "churn_df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Chopping and reformatting in double speed\n",
    "\n",
    "In the interest of time, just believe me that these are sensible things to do\n",
    "to the data before feeding it to a random forest."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fraction of users leaving: 0.144914491449\n"
     ]
    }
   ],
   "source": [
    "to_drop = ['State', 'Area Code', 'Phone', 'Churn?']\n",
    "churn_features = churn_df.drop(to_drop, axis=1)\n",
    "\n",
    "yes_no_columns = [\"Int'l Plan\", \"VMail Plan\"]\n",
    "churn_features[yes_no_columns] = churn_features[yes_no_columns] == 'yes'\n",
    "\n",
    "X = churn_features.as_matrix().astype(np.float)\n",
    "y = np.where(churn_df['Churn?'] == 'True.', 1, 0)\n",
    "print('Fraction of users leaving:', y.mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Let's get predicting\n",
    "\n",
    "Using what we learnt before we evaluate the performance of the model\n",
    "using cross validation and compare it to a baseline."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.cross_validation import cross_val_score\n",
    "\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.dummy import DummyClassifier\n",
    "\n",
    "\n",
    "# always remember, baselines!\n",
    "classifiers = [('Dummy', DummyClassifier(strategy='most_frequent')),\n",
    "               ('RF', RandomForestClassifier())]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dummy scores: [ 0.85508551  0.85508551  0.85508551]\n",
      "RF scores: [ 0.93249325  0.94329433  0.94059406]\n"
     ]
    }
   ],
   "source": [
    "for name,classifier in classifiers:\n",
    "    scores = cross_val_score(classifier, X, y, scoring='accuracy')\n",
    "    print(name, 'scores:', scores)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What happened here? The dummy classifier achieves a performance of 85%?\n",
    "\n",
    "Most people do not switch mobile phone providers, so always predicting \"no switch\",\n",
    "gets you a long way. This is why you need something to compare to.\n",
    "\n",
    "For unbalanced datasets (like this one), `accuracy` is not a useful metric. Instead\n",
    "look at something more sophisticated like:\n",
    "\n",
    "\n",
    "# The Receiver Operating Characteristic\n",
    "\n",
    "(Everyone just calls it ROC curve.)\n",
    "\n",
    "This shows you for each possible \"false positive rate\" (FPR) what \"true positive rate\" (TPR)\n",
    "you can achieve. Depending on your use-case you might want to have a small FPR or a very\n",
    "large TPR."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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DI7Mn+RdKqecB2/UR6fhjuU7bReRt0CNKPgg9KigX+jXuMIAnADyslOoTkWud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XXALcAooDfQF3s5wC+BdZZlTfDTZ/0C+BK4DSgA+gNxQCZwMvBz4Ap/fFY4c9Q73IF+nxkMKNCL\niIiEA19hPi8vj8LCQjLU8EZEpNvw95T7qxsetwEXGmOcTUejjTE1wApghWVZS4B/Am9aljXJGFPl\n53qwLKsAeAE7xFcAvwXexf7dz8f+AiID+K9lWRONMfu78FkPA9cABlgNPNHweBy7j8BJwAWAs7Of\n0R04jZM6Z5070O+oUqAXEREJBwrzIiI9i78D/XTsMPsnY0ybodUY85RlWWcB3wKuB+71cz0ADwJ9\nsKf+n22MWeFx7H3LslYDT2MvEfgVcGVnPsSyrO/SGOZ/b4y5vYXT3gXub2gY2GO5tqzLrIgG6vnq\nuB3oTzghhEWJiIhEOIV5EZGex99r6Ac3PG7weK/e9cSyrLgWrnkWe+r9Aj/XQsM0+tnYIfufTcI8\nAMaYZ7CDtgV8x7KslE58Th/g/obPecNHmPf8zLqOfkZ34qh3ADCk0v7Xa3f9YDIyIClgiypERESk\nNQrzIiI9k78DfXTD4yGP98o9ng9q4Zo9DY/D/FwLwHyP5//4/+zdeZxT5d3///eVyWzsCCI6bkjn\nFhGXWteqFEVbreutlbF6WyhflapYrftSLW211tbWqvXWqq3irVRtxdEKLaAOrhWt4spP1Lpg2UTZ\nYWYymXx+f5wkkwyz5yQnybyej0ceJ3NynXM+gWGYd67rXFcH7RKvlUg6vgfXOU3SVvHnP+/B8UWl\nsdnroU8MuV+h4Qy3BwAgQH/84x8J8wBQhPwO9Kvi24Ep+1bKG+4uSaPbOGb7+Lavz7VI3iR0kjeD\n/qsdtKtr45juqIlvvzSzBYmdzrkhzrmRzrmB7RxXlBJD7rch0AMAkBemTJmiyZMnJ78mzANAcfA7\n0L8T3+6W2GFmTZLein95ehvHJP53+Y/PtUjeBwgm6YOO7uk3s+WSNqQc02XOOSdpv/h13orvO885\n94G8Dzg+kLQmvlzeBc650u6/jcKSGHL/869HNegK6fXLvqUHhg/X3xb/LeDKAADonUKhkO6++25N\nnjyZMA8ARcTvydmek3SUpPGS/pCy/yFJ+0j6H+fcF5IekdcjP0neTPMmabafhcTv1x8aP3dXPiz4\nTF6Y36Gbl9pBUv/4dVY75/4qb6i/xR8Ju0m6WdJJzrljzWzDFmcqEo3NjQrFpKgzrauQpDXaYFJT\nrCno0gAA6LUSoX716tUaOrTbUwYBAPKQ3z30j8W333bObZWy//eS3pc38dyFkl6SNE8tPfarJN3g\ncy2pU7BtbLfVlm36dfM6qe/zWHlh/t+STpZ360FfeR9wvCIv4B8i6Z5uXqOgNEYbNWSz1Nzquysc\nKurJ/QEAyHuhUIgwDwBFxNdAb2aL5Q0/H6+U2e3NrEHS4ZLmyAv1qY8Fkr6Ryfrv7ahMeR7pQvvG\nNo7ritR7/yskfS7pYDOrNbONZtZgZvMlHSbvlgQn6TvOua918zoFI9Ic0fCNUpRADwAAAABZ43vC\nMrPX2tm/TNLRzrkqSbvHr/2BmX3gdw1x9SnP21our7XyNo7rioaU5ybpRjP7vHUjM6t3zl0t6Yn4\nrlMltflnVegamxsJ9AAAAACQZX4Pue+UmS01s7lmNjuLYV5qmeRO6tow+kSbrgzPb+s6Lr79Rwdt\nn1LLjP/7decizrl2H9OmTetexVnWGCXQAwAAAEDCtGnT2s1zmch5oG+Pc26Qn+czs4ikL+Jfbt9R\n25Q2Jm9yvO74j9Inv2v3+PitB4matu7ORcys3Ue+BXqG3AMAkDtm1nkjAECgpk2b1m6ey0TggT6+\nVvsNkj7OwukXyes5r3bOtftenXPbShqQckyXmdlmSZ+k7Crp5JDE680dtipgDLkHACA3IpGITj75\nZN1+++1BlwIACEBggd45t41z7iZ5YfgytQRqP70Q3/ZRx0Pcx7VxTHc8l/J8ZHuNnHMD5C2lJ0lL\ne3CdgsCQewAAsi8SiaimpkaPPfaYpk6dSqgHgF7Il0DvnNvJOTfZOfcT59xVzrnT2htCHw/yt0r6\nSNKP5M0S7yQt96OWVmamPP9/HbSbHN82q2XSuu74S8rzkztod5Ja7rV/roN2BY0eegAAsisR5mtr\na5P7pk6dqvvvvz/AqgAAuZZRoHfOlTvn/ihv3fW7JV0r6eeS/k/SEufchSltXXyW9w8lnSdveTgn\n757zqeqgZ7unzOx1SfPj15nknDu4jfdwurxl9kzSdDP7otXrOznnYvHHM+1c6u+S3oxf5wLn3F5t\nXKdK0nXxLxsl3duzd5X/uIceAIDsaSvMS1J1dbXGjx8fUFUAgCBkmrAekXSsWnqdU/WT9Bvn3CZ5\nAf9JeWuxJ9p+JOkGeSE62sbxfrlA0kvyRgLMcc79UtLT8t77iZJ+GG+3XNI1HZyn3dkKzMycc+dI\nqpM3vP+5+O0EiVntD5R0uaTt4ue5ysxWZPKm8lljtFHbEugBAPBdR2G+rq5OVVVVAVUGAAiC6+ms\nes65b8nrmTZ5S7fdJ+l1ecPWR0v6vqThkpZJmitpUvzQTyRNk/SgmeVkYjjn3Dcl/VnSIG354YPJ\nm6n+BDN7o41jd1LLhH3zzezwDq5zrKT7JQ1s5zomaZqZXdf62A7OaVJhzWB7c90N+tHhV2lNmdOF\n31ulm34XUzQW1dA+Q1VaUhp0eQAAFCTCPAAUp8TSdWbW7TXsMuky/Z/4dpOk/VqvKe+c+62kVyXt\nJGmivDD7J0nnx5dvyxkzm+uc20Neb/yxknaU98HDx/Lus7/NzNZ1dIpW2/au86RzbndJ56dcJyzv\nQ41nJP3ezN7J5L0UgtIvVkuSNrp+2mPXIdq6b8AFAQBQ4AjzAIC2ZBLo95MXcG9uHeYlycy+dM5d\nJWlGvN1zZnZWBtfLiJktk3RF/NGd4z5V50vRpbZfLumq+KNXKlvlBfoVZf01alTAxQAAUOAI8wCA\n9mQyKd628e3LHbR5KeX5HzK4FgpIxRdrJUkrwgO0664BFwMAQIF78MEHCfMAgDZlEuj7xbefddAm\n9bUPM7gWCkjZSu/uhZVlAzViRMDFAABQ4CZNmqQLLrgg+TVhHgCQkMmQeydvKH2svQbx2d8TX27O\n4FooICXL1kuS1g8YpDAT2wMAkBHnnG6++WZJ0uzZswnzAICkjNahB9pS+cUGSdLmwVsFXAkAAMUh\nEeoXLFhAmAcAJPnRfzoypRc+o3ZmtsiHehCwAWs3SZI2DRwScCUAABQP55wGDx4cdBkAgDziR6Cv\n7eT1xFJvXWnHAO0iMGidd3dF/eChAVcCAAAAAMUr0wDd7YXvUfyGbPACfWTosIArAQAAAIDilUmg\nv923KlA8zDR0Q6MkqXnrbQIuBgAAAACKV48DvZmd72chKBLr1qm8Oab1ZVLlVgOCrgYAgLwWi8UU\nCjFHMQCgZ/gfBP5asUKS9NEg6Y61x2vwjYO19a+31shbRwZcGAAA+SUSiejkk0/WDTfcEHQpAIAC\nxSR08Fc80C/rL0WsXpGGeklSpDkSZFUAAOSVSCSimpoa1dbWqrbWmzf4yiuvDLgqAEChoYce/ooH\n+uX903eHQ3x2BACAlB7mE6666irdeeedAVYFAChEBHr4KxHo+6XvJtADANB2mJek6upqHXfccQFV\nBQAoVAR6+Cse6FcS6AEASNNRmK+rq1NVVVVAlQEAChWBHv4i0AMAsAXCPAAgGwj08FXzsnig75u+\nn0APAOitCPMAgGwh0MNXsXigX9UnfT+BHgDQGxHmAQDZRKCHr9yK5ZKkVfTQAwCgmTNnEuYBAFlD\noIevQmtXS5LWVqTvJ9ADAHqjU089VT/5yU+SXxPmAQB+ImXBP83NCjVHFZMUdSWSmpMvEegBAL3V\ntGnTJEkzZswgzAMAfOXMLLsXcG6UpOGS+kh61sw2ZfWCRcY5Z5KU7b8nX2zeLPXtq/qw1O/KCsVK\nGpIv7V+1vxacuSDA4gAACNb69es1YMCAoMsAAOQZ55wkycxcd4/NSrepc24rSVdLmiRpUMpLe0ha\nlNLuDEnflbTOzL6bjVqQQ42N3qZECrtKfXHF54rGoorGoslvUgAAeivCPADAb74HeufcbpL+LmkH\nSakprq0u5vmS/iQp5Jz7g5nN97se5FAkIklqDEulqlD/8v4BFwQAAAAAxcvXSfGcc5WSnpS0o6T1\nkn4i6bD22pvZZ5Lq4l8e62ctCEBKD31pqCzgYgAAAACguPndQ3+OpBGSNkg6xMzeldTZcOu/SzpC\n0oE+14Jciwf6SIlUXlLRSWMAAAAAQCb8Xrbuv+UNrb81Eea74K349is+14JcS/TQhwn0AIDiF41G\nC2PSWgBA0fI70O8W387rxjFfxreDOmyF/Jcy5L6ylEAPAChekUhEp5xyiq688kpCPQAgMH4Pue8X\n327sxjHl8W2Tz7Ug11J66CtLyztpDABAYYpEIqqpqVFtbW1y3w033MCKLgCAnPO7hz7R275zN44Z\nHd+u9LcU5FxilvsSqU8ZPfQAgOLTVpi/8cYb9dvf/jbAqgAAvZXfgf6N+PaQbhzzP/Luu3/Z51qQ\nayk99H0rCPQAgOLSVpiXpOrqap166qkBVQUA6M38DvQz5a09f7ZzbrvOGjvnzlHLsnaP+FwLci1l\nlvt+FQy5BwAUj47CfF1dnaqqqgKqDADQm/kd6O+T9J6kSkl1zrmxrV43SXLOjXbO3S3p9/F9r5jZ\nEz7Xghxr2tQyKV4/eugBAEWCMA8AyFe+TopnZs3OuRMkvSipWl6o/yKlyWzn3AC1zGjvJC2TdIqf\ndSAY9WsaVarEsnX00AMACh9hHgCQz/zuoZeZfSBpb0lz5AX2reMvOUk7SRocf+4kPSVpPzP7j991\nIPfq17X00H+4+kMNuGGAtrpxKw379TBd+dSVAVcHAED3EOYBAPnO72XrJElmtkzS0c65vSSdIGlf\nScMklUj6QtJCSY+b2YJsXB/BaFjbMimec04bIhuSr21u2hxUWQAA9Mjs2bMJ8wCAvJaVQJ9gZm9K\nejOb10D+aNjQsmxdyKUP/giHsvqtBgCA70488UTddNNNuuSSSyQR5gEA+YeUBd9E1rf00BPoAQDF\n4OKLL5Yk/eEPfyDMAwDyjq/30Dvn7nTOHeznOVE4Ihtblq0j0AMAisXFF1+shQsXEuYBAHnH70nx\nzpb0nHPuI+fcz51zu/l8fuSxpo0tk+I5ubTXCPQAgELWt2/foEsAAGALfgf6qLzZ63eWdJWkd5xz\nrznnLnTODff5Wsgz0U3tD7kvLSkNoiQAAAAAKFp+B/rhks6V9JJalqb7qqTfSPrMOTfXOXeGc46P\nuYtQ86aUHnpHDz0AAAAAZJOvgd7MVpvZnWZ2iKRdJF0j6T15wb5E0nhJ90la6Zyb4Zw7xjlX4mcN\nCE6sPmXZOobcAwAAAEBW+d1Dn2Rmn5jZ9WY2Wt469DdLWiEv3PeRVCPpCUnLnHO3OucOyFYtyI1Y\nQ8uydfTQAwDyWVNTk8ws6DIAAMhI1gJ9KjN73cwulrSDpG9K+j9JG+WF+60lTZX0Yi5qQfZYY0sP\nfWsEegBAvohEIpowYYLOO+88Qj0AoKDlNGWZWUzSU5Kecs5VSDpN0k2SBkmtxmij8DS2LFvXGoEe\nAJAPIpGIampqVFtbm9x3++23bzGyDACAQpDzlOW8/zG/Kel0SSdKYoK8IuEiLZPiXf71S/XASQ8o\nGosqGouqX1m/gKsDAPR2bYX5O+64Q9tuu62uueaaACsDAKBnchbonXP7yQvxNZKGJXbHt8slPZSr\nWpAdJU0tQ+4HlA/QgPIBAVcEAICnrTAvSdXV1Zo8eXJAVQEAkJmsBnrn3EhJ/yNvaP1XErvj242S\nHpP0gKSn48PxUaCam6WS5pYe+vJwecAVAQDg6SjM19XVqaqqKqDKAADIjO+B3jm3taRT5fXG75fY\nHd9GJc2TF+Jrzaze7+sjGOvXS+Vq6aGvCFcEXBEAAIR5AEBx8zXQO+f+Lm+t+cS0aIkg/6q8EP+Q\nma3y85rID2vXSmVqWbaOQA8ACBphHgBQ7Pzuof9WyvOPJD0o6QEz+8Dn6yDPrOyjOOwAACAASURB\nVF0rVaT00JeXMOQeABAcwjwAoDfwO9CvlvSwvBD/T5/PjTy2bp00UC3L1tFDDwAIUl1dHWEeAFD0\nQj6fb7iZnUeY733Wrk25h55J8QAAAfvWt76lu+++O/k1YR4AUIx87aE3s6if50PhSA30sbKwQs7v\nz4oAAOieM888U5J000036emnnybMAwCKDqkLvkgN9K6c4fYAgPxw5pln6o033iDMAwCKUo966J1z\n5yaem9n/trW/J1LPhcKybl1KoK8g0AMA8kcF/y8BAIpUT4fc/16SxR//28b+nmh9LhSQtWtMZWqS\nJLly7p8HAAAAgGzL5B561839KGIbV3tr0EdCUkVppQ6991C9tfIthUNhhUNhzf2fudpr+F4BVwkA\nAAAAxaOngX7rbu5Hkdu8pmUN+opwhTY0btD6xvXJ163HAzcAAAAAAG3pUaA3sy+7sx+9QGPKknUl\n5WqINqS9HA75uqACAKAXi0QiKikpUUlJSdClAAAQKGa5hy9cJL2HPhpLX8GQQA8A8EMkEtGECRM0\nceJENTc3B10OAACB8jVlOecekTe53UVmtrSLx2wj6TZJZmY1ftaD3EkG+hKpPFxOoAcA+C4R5h9/\n/PHkvunTp9NTDwDotfzuof9O/DGwG8f0SzkOBSrURA89ACB72grzDz74oK6++uoAqwIAIFgMuYcv\nXJM3y31jCYEeAOCvtsK8JFVXV+v8888PqCoAAIKXD4G+Mr5tDLQKZKQk6v31ReKT4hHoAQB+6CjM\n19XVqaqqKqDKAAAIXj4E+nHx7fIgi0BmGHIPAPAbYR4AgI5llLKcc79q56WLnXOdLWFXLmmkpCPl\nTaT3fCa1IFiJHnqG3AMA/ECYBwCgc5mmrEvkhfFUTtKkbpzDSdokqb0PB1AAUnvoGXIPAMgEYR4A\ngK7JNGVtVnqg7xv/ukFSrIPjEm2WS3pJ0u/MbHGGtSBA9NADAPzyz3/+U3/729/S9hHmAQDYUkYp\ny8z6pX7tnEuE+P3MbFEm50ZhKWlOv4f+i8u+UHOsWdFYVNFYVOUl5QFXCAAoFN/4xjc0Y8YMnXba\naYrFYoR5AADa4Xe36SK19L6jFymJtixbVx4uV7+yfp0cAQBA+2pqaiRJP/3pTzVv3jzCPAAAbfA1\n0JvZGD/Ph8IRbm5Ztq4iXBFwNQCAYlBTU6OTTjpJpaWlQZcCAEBeyodl61AEwq2G3AMA4AfCPAAA\n7SPQwxfJQF8i7pcHAAAAgBzo0ZB759wr8admZge0sb8n0s6FwkIPPQAAAADkVk/vod83vm29Bv2+\n8X2uB+dsfS4UkNJY+rJ1AAAAAIDs6mmgn622A3h7+1HkkoE+7M1yDwBAWyIRb1WUsrKygCsBAKDw\n9SjQm9mx3dmP4heOtSxbRw89AKAtkUgkuRzdww8/TKgHACBDTIqHjMViUplYtg4A0L5EmK+trVVt\nba1qamqSvfUAAKBnCPTIWDQqlStlyD2z3AMAUqSG+YTa2lpddtllAVYFAEDh6+k99Blxzu0paaik\nj83s4yBqgH/SAj099ACAFG2FeUmqrq7WpZdeGlBVAAAUB18DvXNuuKTT4l/+yczWtnp9N0l/lTQq\nZd8cSWeY2Zd+1oLcad1Dv2TdEu1/z/4Kh8IKh8IaM2yMnp30bMBVAgByraMwX1dXp6qqqoAqAwCg\nOPg95P4kSTdJOquNMF8haZa8MO9SHt+S9ITPdSCHmprSe+idc9rctFnrG9drdf1qrW9cH3CFAIBc\nI8wDAJB9fgf6I+UtW1fbxmuTJO0cfz5T0nnxdk7Sgc65U32uBTnSuoe+xJWkvR4OBXJnBwAgIIR5\nAAByw+9A/1/x7SttvJYI7E+b2XfM7A4zO0nSXHmhvsbnWpAj0ahUppZl60Iu/duKQA8AvQdhHgCA\n3PE70G8d336WujM+3P5Aeb3397Q65r74dh+fa0GOpPbQRwj0ANCrLVy4ULNnz07bR5gHACA7/A70\ng+LbWKv9B0gqkxfo57V6LTHL/TCfa0GOeIG+QZLUVOpkZmmvE+gBoPc44IAD9Oijj6qsrEwSYR4A\ngGzyO9Bvim+3abV/bHz7/5nZmlavNcW3zT7XghxJDfQqL1ezpf9VEugBoHc59thj9eijj2rMmDGE\neQAAssjvQP9+fHtEq/3/La93/rk2jkmE/5U+14IciUalcucNubeyMkVj0bTXCfQA0Psce+yxWrhw\nIWEeAIAs8jvQ/13eBHdTnHMTnHPDnXNXSto7/npbs98nXlvmcy3IEW/ZOq+H3pVXEOgBAJKkcJif\n/wAAZJPf/9PeJm85uq0k/bnVa6+bWev75yXpGHm996/5XAtyJHVSPFWUE+gBAAAAIAd87aE3sy8l\nHS1vojuX8nhb0imt2zvnRkk6KP7lU37Wgtzxlq3zpkII0UMPAAAAADnhe9Iys38556ol7StpuLyh\n9K9b66nPPQMlXRZ/3lbvPQpANCqVm7cOfaiikkAPAAAAADmQlaQVD++vdqHdAkkLslEDcifaZCqX\nF+hdeYVO2f0UHbfrcYrGoorGogR6ACgSkUhEzc3NqqysDLoUAACgLAV69C7NjVGFZIo6qaysUuFQ\nWP3K+gVdFgDAR5FIRDU1Ndq4caMef/xx9enTJ+iSAADo9bIa6J1zAyQdImkPeRPlSdJqeffUv2Bm\n67N5feRGrN6bEK8xLFWEKwKuBgDgt0SYr631Fqs54YQTCPUAAOSBrAR659wgSb+UdIak9hJeg3Pu\nfklXmtnabNSB3GjeHA/0JVJ5uDzgagAAfmod5iXpqaee0oUXXqi77rorwMoAAIDf69DLOTdS0luS\nzpJUqfTZ7lMflZLOlvSmc24Xv+tA7lgDPfQAUIzaCvOSVF1drZ/85CcBVQUAABJ8DfTOuTJJf5e0\nvbzQ/oakqfJmvN8+/thX3lr1r8fb7CBptnOu1M9akDuxBm9CvEgJgR4AikVHYb6urk5VVVUBVQYA\nABL87qGfIukrkkzStZK+Zmb/a2avm9my+ON1M7vDzPaVdE38uGp5vfUoQMke+hKpvIQh9wBQ6Ajz\nAAAUBr8D/UnywvxMM7uunbXnk8zsekmPyuup/47PtSBHGHIPAMWDMA8AQOHwO9DvHt/e241jEm13\n77AV8ldjSw89gR4AChdhHgCAwuJ3oB8Y3y7rxjHL49sBPteCHEntoWfIPQAUrkWLFmnu3Llp+wjz\nAADkL78D/er4dkQ3jtmp1bEoNPTQA0BR2HvvvTVr1qzk+vKEeQAA8pvfgf4NeffD/6AbxyTavulz\nLcgR7qEHgOIxbtw4zZo1S3vvvTdhHgCAPOd3oH8kvj3COXeHc67d8dfOuVLn3C2SvilvIr2HfK4F\nuRJpWbauPFyuy+ddrn6/6KdBvxykob8aqjtevSPgAgEA3TFu3Di99tprhHkAAPJc2OfzTZe3xvw+\n8pahO8Y596CklyV9Li+4byPpAEmnyVuDXpJek3S/z7UgR1wkfch9Q7RBm5o2JV+PNEeCKg0A0EOh\nkN+f+QMAAL/5GujNLOacO0bSPEljJG0v6bJ2mrv49m1Jx3a2xB3yWCR9yH00Fk17ORzy+3MjAAAA\nAIDvH7+b2UpJ+0n6ibwZ7F07j+WSrpW0v5l97ncdyB2XMileeUk5gR4AAAAAciArScvMGiX93Dl3\nnbye+jGStoq/vFrSO5LeoVe+OLimlh76cChMoAcAAACAHMhq0ooH9rfjDxSpUMo99CEXUtTSA31p\nSWkQZQEAUkQiETU2Nqp///5BlwIAAHzi65B751zIOUd662Vcyj30IReihx4A8kwkElFNTY2OOuoo\nrV+/PuhyAACATzIO9M65XZxzdznnPpPUJKnBObfKOfewc27/zEtEvnNNLcvWOecI9ACQRxJhvra2\nVi+99JKOPvpoQj0AAEUio0DvnBsv6Q1J/0/SdmqZ8G4rSd+R9KJzbkqmRSK/hZpaDbkn0ANAXkgN\n8wkvvfSSpk6dGmBVAADALz0O9M65rST9WVI/eSHeJP1b0mJ5PfVOUomk25xze2deKvJWc7MkKRqS\nnOihB4B80FaYl6Tq6mrdcMMNAVUFAAD8lEkP/ZmShsoL8vdL2tbMqs1sN0lDJP08/lqJpIsyLRT5\nKxZreU4PPQAEr6MwX1dXp6qqqoAqAwAAfsokaX0rvp1vZpNSXzCzTZJ+4pwbIunclLYoQrGUxQe5\nhx4AgkWYBwCg98gkae0urwf+Dx20+V95gX6oc26omX2RwfWQp6xVD/0Tpz6hpliTorGoorGo+pex\nRBIA5AJhHgCA3iWTQD8ovn2/gzaprw2SRKAvQqlD7p2cysPlKld5cAUBQC9EmAcAoPfJ5B76svg2\n0l4DM0sde13WXjsUtuZWPfQAgNz78MMP9cwzz6TtI8wDAFDcSF/IWOqQe+dccIUAQC82evRozZs3\nTwMGDJBEmAcAoDcg0CNjrWe5BwAEY//999e8efO03377EeYBAOgF/Jh+/Bbn3AYf2pmZnexDPcix\n1vfQAwCCs//++2vBggWMmAIAoBfwI9Af3snriUXNOmuHAkUPPQDkF8I8AAC9Q6aB3s/fGKzzJshH\nMe6hBwAAAICcyyTQD/atChS0WMpHMfTQAwAAAEBu9DjQm9k6PwtB4Yo1tzznHnoAAAAAyA26U5Ex\n7qEHgOyKRCJas2ZN0GUAAIA8Q/pCxlKH3HMPPQD4KxKJqKamRocddpi+/PLLoMsBAAB5xI9Z7tHL\nWase+u1+s502RDYoHAorHArr/anva3AlUy4AQHclwnxtba0kafz48Xr66ac1ZMiQgCsDAAD5gB56\nZKz1OvQbIxu1MbJRaxvW6ovNX6gkVBJccQBQoFqHeUl688039YMf/CDAqgAAQD4h0CNjre+hj8ai\naa+HQwwEAYDuaCvMS1J1dbV+97vfBVQVAADINwR6ZKz1OvQEegDouY7CfF1dnaqqqgKqDAAA5BsC\nPTJGDz0A+IMwDwAAuoNAj4ylBnozk6ll2nsnx1J2ANAFhHkAANBdJC1kLDXQx1KnvBe98wDQFYR5\nAADQEwR6ZIxADwCZ+eyzz/TCCy+k7SPMAwCAzhDokbFYywj7tOH2EoEeALpi5MiRqqur09ChQyUR\n5gEAQNdkLdA754Y75y52zv3VOfeCc+4159yIVm1GOue+7pzbO1t1IPtSO+WbY81prxHoAaBrxowZ\no7q6Oh188MGEeQAA0CVZSVvOuSslXSupLLFLkkmqbNV0b0l/kRRxzu1oZp9nox5kV+tJ8VIR6AGg\n68aMGaPnn39ezrmgSwEAAAXA9x5659yNkq6TVC5pvaRnOmg+U9JSSaWSTva7llZ1VTnnbnTOveuc\n2+CcW+Oce905d41zblCWrumcc/90zsXij+bOjyossZjSBtk3Gz30AJAJwjwAAOgqX9OWc25/SZfK\ny3h3SrrYzOqdc7G22puZOef+KukCSeMl3eFnPSl1HSVphqRBSs+fe8kbJXC2c+4EM3vd50tPlXRA\n/JpF+RtaU1P618P7DdfmqzYrGosqGotuMUkeAAAAAMAffvfQT41vnzOzc82svgvH/DO+HeNzLZIk\n59ye8ob1D5S0Sd6tAIdIGifpZklRSVWS/uacG+7jdbeXN1IhJmmVX+fNN9Fo+tchF1JlaaX6l/fX\n4MrBGtJnSDCFAQAAAECR83s89CHyeqO709O+JL7dzudaEn4nqa+84H6Umb2Y8trzzrmFkv5P0nB5\nAfxMn657h6R+ku6R9F+Shvl03rzSVqAHAAAAAGSf3+lr2/j2g24c0xDflvtci5xz+8jriTdJ97YK\n85IkM3tQ3n3+TtL3nHNDfbhujaRjJH0u6fJMz5fPWgd67v0EgHSRSESrVhXtQC0AABAgvwN9Y3zb\nnUnmtolv1/pciySdlPL8Tx20S7xWIun4TC4Yn2DvFnkfIlxsZtl4X3mDHnoAaF8kElFNTY0OPfRQ\nLV++POhyAABAkfE7fSWGz1d345jD49v3fa5F8m4BkKTNkl7toF1dG8f01G/kDa9/xsxmZHiuvLdF\nD31xzv0HAN2WCPO1tbVavHixDjvsMEI9AADwld+BPjF0fUpXGjvntpN0trze7Hk+1yJJo+Pn/sCs\n/enWzWy5pA0px/SIc+4wSd+XdxvBOT09TyGhhx4AtpQa5hMWL16sKVO69N8jAABAl/idvm6XN/nc\n3s65Kztq6JwbKenv8mafb5C3zJ1vnHNlkhL3w/+nC4d8Ju/DiB16eL1ySXfJ+wDhF2b2YU/OU2ha\nL1vHPfQAeru2wrwkVVdX6447srI6KwAA6KV8DfRm9oGkn8kLxtc5555zzv0wpcnxzrmLnHMzJS2S\nt1SdSbrUzD73sxZJ/VOeb+xC+0Sbfj283jRJIyUtlnRjD89RcOihB4AWHYX5uro6VVVVBVQZAAAo\nRn4vWyczuy7eO36VvPvRD5YX2iXp+pSmLr7/WjP7X7/rkFSZ8jzShfaJCf0qO2zVhvha9xfLez/n\nmFlTJ4cUDe6hBwAPYR4AAORaVrpTzexaSQdJmimpXl54T300SZol6WAzu76982SoPuV5WRfaJ5bN\nq++wVSvOG2N+j7wZ8u83s2e7c3yho4ceAAjzAAAgGFlLX2b2qpl9R94SdntL+qakoyXtJ2mwmR1n\nZi9n6/pqmeRO6tow+kSbrgzPT3WhpH0lrZZ0STeP7TLnXLuPadOmZeuynWIdegC9HWEeAAB0Ztq0\nae3muUz4PuS+NTOLSnor29dp47oR59wXkoZI2r4Lh2wvb8j8Z9281OXx4+okHdHOX8iwxBPnXE38\nacTMHuvqRcys80YBaB3o5/57ribVTlI4FFY4FNa3q7+tB056IJjiACAHVqxYoVdfTV8ZlTAPAABS\nTZs2rd2O2ExCfdYDfcAWSRorqdo5F2pv6Trn3LaSBsgL5ou6eY1yebcRfCf+6Myf49u1kroc6PNV\n60AfiUZUH225a2Fz0+YcVwQAubXjjjuqrq5Ohx12mJYuXUqYBwAAOVPsNzy/EN/2kTfUvz3j2jim\nO6wLj7baFrzWy9Y1W3Pa1+FQsX9mBAAtPfKHHXYYYR4AAOSMr2krvhxdT5mZnexbMZ6Z8mbbl6T/\nJ2lBO+0mx7fNkp7ozgXMbHBnbZxzdZK+EW9f0p3z57vWPfQEegC9VXV1tZ555pmgywAAAL2I32nr\nRPWs5zmxhJ2vzOx159x8eT3wk5xz083sxbQLO3e6pPHx6083sy9avb6TpI/jX843s8P9rrOQtQ70\nsVZ3NRDoAQAAACA7/E5bb6nzYN5X0k6SSuNtl8i7nzxbLpD0Uvy6c5xzv5T0tLz3fqKkH8bbLZd0\nTQfnKYoh8n5rHeijsfQdpaHSHFYDAAAAAL2Hr4HezPbuSjvnXIWkCZJ+Je8+/olmlpWZ8M3sbefc\nyfImoxsk6WfxR7KJvJntTzCzFR2VnY36Ct0WPfQxeugBAAAAIBcCmRTPzBrM7H5Jh0jqL2mWc25o\nFq83V9Iekn4tbxb7jZLWSXpD0k8k7Wlmb3R0CmU+kV3RTISXaoseekvfQaAHAAAAgOwIdJZ7M/tQ\n0q2SqiRdnOVrLTOzK8xsjJkNMLPBZraPmV1nZus6OO5TMyuJP8b38NqHxY8vunTLPfQAilkkEtHS\npUuDLgMAAKBN+bBs3dPx7YmBVoEe6eweegI9gEIViURUU1Ojgw8+WJ988knQ5QAAAGwhHwL9xvh2\nh0CrQI9469C33EnQHGPZOgCFLxHma2tr9emnn2rcuHGEegAAkHfyIdDvFd82BVoFeqS5WUoEeid6\n6AEUvtQwn/Dpp5/q7LPPDrAqAACALQWatpxz20m6Vl4izMos98gd55wuP+Ry/eigHykaiyoai6qs\npCzosgCgy9oK85JUXV2te++9N6CqAAAA2uZroHfOHd+FZiFJgyXtJ+m7kgbKC/R3+VkLcshZvJPe\nKRwK0ysPoCB1FObr6upUVVUVUGUAAABt8zt51ap7S7Ml1nb/o5k96HMtyLGQc503AoA8RJgHAACF\nKBtdqV1NdRFJ/5R0m5nNzEIdyJnufIYDAPmFMA8AAAqV34H+q11oE5O0QdJSM2MivGIQH3Lv6KEH\nUGAI8wAAoJD5GujN7E0/z4dCkZjlnkAPoLCsXr1ab7/9dto+wjwAACgUvi5b55z7XvxxgJ/nRWGg\nhx5AoRk+fLjq6uo0cuRISYR5AABQWPxeh/4+SfdK2snn8yKfOe6hB1C4dthhB9XV1enoo48mzAMA\ngILi9z306yQNkPSBz+dFXksMuff78yEAyI0ddthBs2fPDroMAACAbvE7gX0S3w7y+bzIZ/GR9oy4\nBwAAAIDc8TvQPyEv3h3t83mR15gUDwAAAAByze9Af4ukZZKmOucO8vncyFsEegAAAADINV8DvZmt\nlnSUpP9IqnPO3eSc+6pzrsTP6yDPJIfcO53yl1PU5/o+GnDDAG1141aa9f6sYGsDAAAAgCLl66R4\nzrnV8aelksok/Sj+MOfcJknNHRxuZjbEz3qQKy2z3DdEG1QfrU9+HbNYEAUBgCKRiJYuXaoRI0YE\nXQoAAEBW+D3kflD80Tf+tYs/QpL6p7ze3gMFKT7k3jlFY9G0V8IhvxdSAIDORSIRTZgwQQcddJDe\ne++9oMsBAADICr/T1i0+nw8FoeUeegI9gKAlwvzjjz8uSRo3bpzmz5+vUaNGBVwZAACAv3qctpxz\nO8afLjWzZkkysx/5UhUKS+IeegI9gIC1DvOStHLlSk2ZMkXz58+XY31NAABQRDIZcv+JpI8k7epP\nKShc8XvoGXIPIEBthXlJqq6u1owZMwjzAACg6GR6Dz2/HSGJHnoAQekozNfV1amqqiqgygAAALLH\n70nx0Bu5xD30ItADyDnCPAAA6K0I9PABs9wDCAZhHgAA9GYEemTOEegB5B5hHgAA9HYEeviGe+gB\n5NL69ev1wQcfpO0jzAMAgN7Ej0BvPpwDBa3lW4BADyBXhg4dqrq6Oo0ePVoSYR4AAPQ+fqStuc65\nJh/OY2Y20ofzINdShty/c847isaiycegikEBFwegmA0bNkx1dXWaMmWKfv/73xPmAQBAr+JHoPfr\ntyd6+gtWYpZ7p/JwucpVHnA9AHqTYcOG6bHHHgu6DAAAgJzzI9Avk+RHDz0KnHMu6BIAAAAAoNfw\nI9B/08wW+XAeFCqXGFxBoAcAAACAXGGWe/gmRKAHAAAAgJwh0CNziR568jwAAAAA5AyBHj5omRQP\nAPwQiUT0/vvvB10GAABAXiPQwwcEegD+iUQiqqmp0YEHHqiFCxcGXQ4AAEDeItDDN8xyDyBTiTBf\nW1urNWvWaPz48YR6AACAdhDokbnkLPcA0HOpYT5hzZo1Ovfcc2XGzxkAAIDWMlm2bkR8u9SPQlC4\nXGLIvePzIQA901aYl6Tq6mr99a9/ZQQQAABAG3oc6M3sUz8LQeFyikmSjF+4AfRAR2G+rq5OVVVV\nAVUGAACQ3zLpoQckSaF4oK8vMZVfV65wKKxwKKytKrfSxxd8HHB1APIZYR4AAKDnCPTImHNeoG8u\nkSLNEUWaI5Kk0lBpkGUByHOEeQAAgMxw0zMyFrJ4oG/13RQO8XkRgLYR5gEAADJHoEfGQoke+lD6\nPfQEegDtqa+v13/+85+0fYR5AACA7iHQI2OJe+hjjkAPoGsGDhyoefPmad9995VEmAcAAOgJAj0y\nlli2jiH3ALpj0KBBmjdvnk499VTCPAAAQA+QuJCxRA99cwk99AC6Z9CgQfrzn/8cdBkAAAAFiR56\nZCykZkkMuQcAAACAXCLQI2Oh+JD7WHqeJ9ADAAAAQBYR6JExJ5atAwAAAIBcI9AjY8lZ7lm2DgAA\nAAByhkCPjIXooQeQIhKJ6O233w66DAAAgKJH4kLGEoF+52g/NVzdoGgsqmgsGnBVAIIQiUQ0YcIE\nPf300/rHP/6hgw8+OOiSAAAAihY99MhYYh16FwqpPFyuvmV9NbBioAZWDAy4MgC5lAjzjz/+uDZu\n3KijjjpKL774YtBlAQAAFC0CPTKW6KFXiG8noLdKDfMJGzdu1A9/+EPFYrEAKwMAACheJDBkLBno\n5TpsB6A4tRXmJam6ulpPPPGEQnzYBwAAkBX8loWMJYbc00MP9D4dhfm6ujpVVVUFVBkAAEDxI4Eh\nY4keegvRQw/0JoR5AACAYBHokTHuoQd6H8I8AABA8EhgyFgoMeTe0UMP9AaEeQAAgPxAoEfGuIce\n6F2ampq0Zs2atH2EeQAAgNwjgSFjDLkHepe+fftq1qxZGjt2rCTCPAAAQFBIYMgYgR7offr166dZ\ns2Zp0qRJhHkAAICAhIMuAIUvGei5hx7oVfr166d777036DIAAAB6LbpUkbHEPfQvlCxVxXUV6veL\nfhr0y0G66umrAq4MAAAAAIoXPfTIWKKHPupMjc2NamxulCRFmiNBlgUAAAAARY0eemQsZF4PfSyU\nPuQ+HOLzIgAAAADIFgI9MpbooY8llq+LI9ADAAAAQPYQ6JGxxD30sVZz4pWGSgOoBkAmIpGIXnvt\ntaDLAAAAQBcQ6JGxUDzQN9NDDxS0SCSimpoaHXLIIZo7d27Q5QAAAKATBHpkLDHk3hz30AOFKhHm\na2tr1dDQoBNOOIFQDwAAkOcI9MhYsofe0UMPFKLUMJ/Q0NCgSy+9VM3NzQFWBgAAgI4Q6JGxlnvo\nCfRAoWkrzEtSdXW1Zs+erZKSkoAqAwAAQGcI9MhYyBKz3Kcj0AP5raMwX1dXp6qqqoAqAwAAQFcQ\n6JGxUDuz3BPogfxFmAcAACh8BHpkLDnknlnugYJAmAcAACgOJC5kLDHL/cl999Oz5y1SNBZVNBZV\nRbgi4MoAtEaYBwAAKB4EemQsMeS+pCRMiAfynJkpEomk7SPMAwAAFCaG3CNjIfMCvXN8OwH5rry8\nXI8++qi+/e1vSyLMAwAAFDISGDKWuIfeQq6TlgDyQUVFhR599FGde+65s59qgQAAIABJREFUhHkA\nAIACxpB7ZCwx5N6xXjVQMCoqKnT77bcHXUbOOMcHjgAAIHvMrPNGWUAPPTKWmBRPDLkHAAAAgJyh\nhx4ZS95DHyLQA8hvQX16DgAAilPQowBJYMhY4h56EegBAAAAIGdIYMhYiEAPAAAAADlHAkPGEkPu\nCfRAsCKRiF588cWgywAAAECOkMCQscSkeKxDDwQnEomopqZG48aN08yZM4MuBwAAADlAAkPGktNA\nlPDtBAQhEeZra2sVjUZVU1NDqAcAAOgFSGDIWGLI/W8+fUiV11eq/w39NfjGwXrn83cCrgwofqlh\nPiEajeqaa65RNBoNsDIAAABkG8vWIWOJIfdRNash2pDc7xTsEg5AsWsrzEtSdXW15s6dq3CYH/EA\nAADFjB56ZCzRQx+zWNr+cIgwAWRLR2G+rq5OVVVVAVUGAACAXCHQI2OJfvjmxPJ1cQR6IDsI8wAA\nAJAI9PBBYh16euiB7CPMAwAAIIFAj4wlh9yLQA9kE2EeAAAAqQj0yFhLDz1D7oFscs6ptLQ0bR9h\nHgAAoPci0CNjLh7omxlyD2RVaWmpHnzwQZ1yyimSCPMAeq6hoUG33HKLxo0bp6233lqlpaUKhUIK\nhUK66KKLsnbdZ599Nnmdww8/3Lfz7rzzzsnzLlmyxLfz5ovLL79coVBIFRUV+vjjj4MuBygoDQ0N\n2n777RUKhXTMMccEXY7vCPTIGEPugdxJhPqLLrqIMI9eYdy4ccmg1tajf//+2mGHHXTkkUdq2rRp\n+uijjzK6XlNTk5588kmdd9552meffVRVVaWKigptvfXW2n333VVTU6Pp06dr9erVGb+31atX64EH\nHtDEiRO11157abvttlNFRYUGDhyonXfeWUcffbSmTZumhQsXZnytVOvWrdP++++vH/3oR3ruuee0\nevVqxWIxOefkXG6WnPX7Oonas1F/Y2Oj/vSnP+noo4/WzjvvrMrKSm277bb6+te/rhtvvFErV670\n/ZqpFi9erN/97ndyzumcc87RiBEjsno9FK6XXnpJU6ZM0ejRozVw4EANHDhQo0eP1pQpU/TSSy9l\n9dqrVq3STTfdpKOOOkrbb7+9+vTpo8rKSg0fPlzf+MY39OMf/1gffPBBt85pZnrkkUf03e9+VyNH\njlT//v01YMAAjRo1ShMnTtScOXO6dJ6Kigr99Kc/lST94x//0BNPPNHt95fXzIxHHj8kmffXlJ/u\nustsbbjMTLKyn5Wapin52Ni4MejyAMDMzPL9ZynaN27cOAuFQp0+nHPmnLNQKGQXXHCBNTY2dvta\nDz30kI0cOTJ5rsT5Wl/DOWcDBgywX/ziF1ZfX9/t66xZs8auuOIK69evX7vXan29MWPG2COPPNLt\na7Xl7LPPTl6vtLTUjjrqKJsyZYqdf/75dv7559vMmTN9uU5b5s+fn7z2YYcd5tt5d9555+R5P/30\nU9/O+/rrr9uoUaM6/H7Yaqut7OGHH/btmq0df/zx5pyzyspKW7FiRdaug8K1adMmmzx5cps/T1L3\nnXXWWbZ582bfr//73/8+7edZez/LwuGwXXjhhdbU1NTpOd955x3bfffdOz3nMcccYytXruz0fE1N\nTbbTTjtZKBSyUaNGWXNzsx9v3cz8+R0j5Rzdzot0oSJjjnXoAQBZZGZyzmnUqFEaP3582msbN27U\ne++9p1deeSXxQbhuvfVWrVixQg899FCXzt/c3Kyzzz5b9957b1ov74477qivfvWrGjZsmNauXasP\nP/ww2Vu+YcMGXX311aqtrdWTTz6prbfeukvXevfdd3Xsscfq008/ldTSUz1y5Ejtvvvu2nrrrRWJ\nRLRy5UotXLhQq1atSh5XU1OjTz/9VJdcckmXrtXee50xY0by62eeeUaHHHJIj89XzN577z0dccQR\nWrt2bfL7YuzYsRo5cqRWrVqlp556SvX19VqzZo1OO+00hcNhnXTSSb7WsGDBAv3tb3+Tc04TJ07U\nNtts4+v5UfhisZgmTJig2bNnJ3+e7LLLLjrwwAMlSS+//HJy5NI999yjL774QjNnzvTt+r/61a90\nxRVXJP+NlJSUaL/99tOIESNUUlKijz/+WK+++qoikYhisZhuueUWLVu2TA8//HC753zjjTc0duxY\nbdq0Kfme9thjD331q19VOBzWokWL9MorrygWi2n27Nk68sgj9cILL6h///7tnjMcDuviiy/WBRdc\noPfff1/Tp0/X97//fd/+HALVk08BeNBDn3DXXWYbSkrNJHPTXFoPfbQ5GnR5AGBm9NAXsnHjxiV7\nZ77//e+3227x4sW2zz77pPXmPPbYY126xoknnpjWA3TQQQfZP//5zzbbLlmyxCZOnJjWS1RdXW1f\nfvllp9f517/+ZQMHDkweV1paaj/4wQ/s3//+d7vHvPLKK3bGGWdYOBy2UChkP/3pT7v0ntqzaNGi\n5Hv9r//6r4zO1ROF0kPf3Nxsu+22W/LvasSIEfb222+ntfnyyy/tyCOPTH7P9enTx5YsWZLxtVOd\ncMIJyffV+vqAmdn111+f/B4Jh8N26623btHmlltusZKSkuTPrV//+te+XPvDDz+0srKy5HmPOOII\ne//997dot2TJEjvppJPSfj7X1ta2ec76+vpkT7pzzoYNG2ZPPfXUFu3eeust23XXXZPnmzBhQqf1\nrl+/3vr162ehUMh23XXX7r/hdvjxO4Yy6KEPPLDyKPxAvykUNpPs93W/ss2Rzba+Yb2t3rzaYrFY\n0OUBgJkR6AtZVwO9mdny5cutf//+yV8uv/Wtb3V6/htvvDEtzJ911lldquu+++5LG/55/PHHd9h+\n7dq1NmLEiOQvqYMHD7bnnnuuS9cy84af7rHHHhkH+hdffDH5fr/xjW9kdK6eKJRAf9dddyXDR0VF\nhb377rttttu0aVPyNo1QKGSTJk3K+NoJ//73v5Mh7MADD/TtvCgeX375ZfJDwlAoZFdffXW7ba+4\n4oq020TWrFmT8fWnTZuWPOf222/f4XD+5uZm22uvvZL/Vk455ZQ22918881pQ/QXLFjQ7jmXLFli\ngwYNSp7z5Zdf7rTmxK0JoVDInnzyyc7fZBcEHeiZFA8ZSyxbFy4pVWVppfqX99fgysE5m1gHAABJ\nGj58uE455ZTkLzkvvPBCh+0/+ugj/fjHP07+f3X00Ufrrrvu6tK1Jk6cqOuvvz55rSeffFIPPvhg\nu+0vu+wyffLJJzIzlZSU6IknntChhx7a5fe2++67a8GCBTryyCO7fExbIpFI8nkoxK+B7bn99tsl\nebdETJo0SaNHj26zXZ8+ffSzn/1MktdJNmPGDK1du9aXGv74xz8qFvNuZ6ypqfHlnCgu06dP1/r1\n62VmGjRokH784x+32/baa6/VwIEDJUlr167VAw88kPH133rrLUnev5Pjjz9elZWV7bYNhUL67ne/\nm/x68eLFbbZ75JFHkuc87rjjtP/++7d7zh122EHnnntu8utbbrml05pT/y398Y9/7LR9IeAnOTKW\nWLZO/GIA9FgkEtEzzzwTdBlAwdt7772Tz+vr6zsMV7/5zW8UjUZlZqqsrNSdd97ZrWtdeuml2nPP\nPZNf//rXv26z3YoVK3T//fcn7zE9//zze3TfemVlpQ466KBuH/fpp59usVScmWn+/PlbrBrQ0VJy\n//rXv3ThhRdqzz331JAhQ1RRUaHtt99e48eP129+8xutW7eu27V1JhKJ6LbbbtPYsWM1bNgw9enT\nR1/5yld0+umna/78+b5fT5I+/vjjZFCRpEmTJnXY/jvf+U7y3t1oNOrbDNqpHxD993//d5eOWbVq\nlaZPn67Jkydr33331ZAhQ1RWVqZBgwZp11131RlnnKHa2tounWv69OnJ74vJkydL8r5v/vKXv+ik\nk07SV77yFfXt21ehUEj3339/u+d57rnnNHXqVO25554aOnSoysvLtd122+nwww/XTTfdpPXr1+f8\nvRWLxPt1zmnChAmqqKhot21lZaUmTJiQ/NqP++g3btyYfD548OBO26e2SXxYlSoWi+nVV19N+5C1\nM9/+9rcled+bs2bNSvvQsi3jx4/XwIEDZWaaPXu2bx/ABaon3fo8GHKfcNddZhHnzCS765+3B10O\nUJAaGxuT9/Def//9QZdTlPL9Zyna150h92Zmd999d9p9msuXL2+zXUNDg/Xt2zc5VLUr527Ln/70\np7TrvfDCC1u0ue6669KGkPo5C3tXfPLJJ23Oet3WagFtDYPfvHmznX766Z3O/j9kyBB78MEHO6yl\nO0PuFy1alLxHtr1rnnvuudbU1OTrkPt77rknef7+/ft3aTbsb37zm8nrT5w4MaPrm3n3ByfOt8su\nu3TpmNtuu83C4XCHf7+J1/bdd99O7/e/77770v7tLVu2zMaOHdvm+adPn77F8UuXLrUjjjiiS983\n7d1Pna33VgwaGxuTc2uEQiF76KGHOj1mxowZyT+nsrKyLs0235Gzzjor+fdxwgkndNp+6tSpyfan\nn376Fq9//vnnaX/Hc+bM6fScn332Wdoxzz77bKfHHHfcccn2Xflz64wfv2MogyH3TEOOjIUs8YQe\neqC7IpGIampqkp+yT5w4UZJ0xhlnBFkWULCWLVuWfF5SUqIhQ4a02e7ll1/W5s2bJXm9W6effnqP\nrldTU6Mf/OAHikajkqS6ujodfPDBaW0So2+cc/r617+uHXfcsUfX6qkBAwZo6tSpkqSlS5fqscce\nk3NO22233RY9v9XV1WlfNzQ0aPz48Xr55ZeTvWbbbLONxo4dq4EDB+qTTz7Rs88+q6amJq1evVpn\nnHGG1q5dmzYMtieWLFmi8ePHJ9d4d85p9OjR+trXvibnnF5//XW98847uvPOOzsc5tsT7777bvKa\ne+yxR5duTdhnn300b968tOMzkTiXpC7fmrF06VLFYjE557Tzzjtrt91207Bhw1RZWakNGzZo0aJF\neuONN2Rmeu211zR27Fi98cYbyWHYHWloaNDxxx+v1157TeFwWAcddJCqq6vV1NSkN998c4v2ixcv\n1hFHHKGlS5cmv2/22msvjRkzRn379tXKlSv1/PPPa/Xq1Vq9erVOPvlkzZgxI60HOVfvrVC99957\nam5uluR9r+6zzz6dHpPaJhqNavHixdp99917XMMJJ5yge+65J9k7/sILL7Q7+ujdd9/Vvffem6z3\nnHPO6fF125L4Pnv33Xc1duzYDtseeuihevLJJyVJc+bMKfhbWgj0yFhJfMi9I9AD3dI6zEveqKlf\n/OIXqqmpUVlZWYDVAYXpH//4R/L5Pvvso9LS0jbbpd5f75zTAQcc0KPr9enTR2PGjNHChQvlnNvi\nvv1oNJoWhnsyZD5TgwcP1q233ipJevbZZ/XYY49J8sJ7Yn97LrnkkmT9oVBIv/zlL3XRRRelzZOz\ndOlSnXHGGZo/f77MTBdddJEOOOAAfe1rX+txzZMnT9aKFSskeR9IPPDAAzr22GPT2syZM0enn366\nfvvb37b799wTqff27rTTTl06JvEhjZnpvffey7iGBQsWJJ+n3tbRkV133VW33nqrTjzxRFVVVbXZ\n5uOPP9a5556rOXPmaMmSJbriiit0xx13dHruv/71r2pubtbYsWM1ffr0Lf5cUoc519fX6+STT9ay\nZcvknNORRx6p2267bYsPixobG3XDDTfouuuuk5nprLPO0oEHHtjmB17ZfG+dWbNmja699tqMz5Nq\nyJAhmjZtWkbnaH0Pelc+KEy0Sfz7fe+99zIK9Mccc4yOOuoozZkzR83NzTryyCM1ZcoUfe9739Mu\nu+ySXLbukUce0a233qr6+nqVlJToV7/61RYffErSVlttpVAolBilnFzesyOt23Tl31/qrVmp/9YK\nVk+69Xkw5D7hrj/EzCQzye75191BlwMUjMQw+8S/8cSjurra/vOf/wRdXtHJ95+laF93htwnhggn\n2t97773ttj3zzDOTbXfeeeeMapw4cWLyXK2XQlq6dGnaEOGgb6vpzpD3jz76KG2pq5tvvrndtps2\nbbI999wzee4jjjiix9efO3du2t/jvHnz2r3u888/nzbk2o8h9wcccEDyXBdeeGGXjpk5c2ZazZFI\nJKMaRo0alTzXrFmzMjpXa01NTcm/q759+9ratWvbbJc65N45Z3vssYfV19d3ev7ELSaJ1R86W/Xo\nmmuuSbY/77zzevSeErr63rojccuKn48RI0ZkXNcdd9yRPN+gQYO6fNyAAQOSf9533fX/s3ffcVEc\n/R/AP7MHeBQBRRE7Cig2bDHYxZZYImiKxqBBUYwxscTEEuPjo3nsJSYQE2sEW9SYWKKi8RfFLooS\nFRETGyCKolTpHPP7A29zB1e5wzvw+3697uUeNzsze7e77ndndma9wfUoKCjgH374YZlHH0q/BEHg\n3bt353/88YfG/OTTjwqCwIcNG6a1/C+//FLpHKuqK39pit30JRIJz8/P13l7VTHGNQYM6HJPTarE\nMC/uoBUDEASJaetCSCWhqmUeKGktO3HihNrWB2KeGKv8r8osJycHUVFRmDRpkjhwF2MMI0eO1DiY\nWWpqqpi2Zs2aBtVBcaCnZ8+eKX0mf89f/H/p6OhoUFkv0/r168WBq1q0aIFp06apTWtjYyO29nPO\ncfz4cfzzzz/lKlc+8jRjDH5+fujXr5/atN27d8cHH3wgfr/GoDjQl67d+UunU8yjPBRbHRs0aGBQ\nXqVZWFhg1KhRAEpa08+ePasxPeccjDEsX75c46BrQEmPlO+//14sZ926dVpnPZozZ444SNnPP/+s\nx5aUpe+26Yq9GNDSmC9DlWc/LZ3W0P0UACwtLREWFoaLFy+KXfpVbWvjxo0xbNgwdO7cWWN+fn5+\nAEr2u99//11jC3pCQgJ+/PFHMMbEc0BWVpbWOtetW1d8lIZzrlNPAHNGXe6JQRgv+Y++mMEoJydC\nqjoK5gkpv9DQUISGhqr9nDEGe3t7TJ48WZxKTB3Fiz47OzuD6qW4fukRu0tfXBpa1sukOPOGfHwP\nTXr16gV3d3fcvn0bQMl4AqW7WevixIkT4rIu44kEBARonDJQX3l5eeKyro8+VatWTel9bm6uTqN+\nq5KRkaFUB3XjQGjy7NkzREZGIjY2FqmpqcjOzlYaVVyxW3J0dLQ4Urg6jo6OePPNN7WWGxUVhceP\nH4Mxhl69esHFxUXrOlKpFF27dkV4eDjS09MRExOD1q1bv7Rt06Zx48bis+rmpDz7KaC8r+bm5hql\nLhs2bMDChQuRmJgICwsLeHt7o1mzZpBIJLh79y7OnTuH+Ph4fPHFF1i+fDl27NihdkaNyZMn49tv\nv0V6ejqKi4sxZMgQ7Nixo8yNvatXr2L48OHIyMhQikF02SaJRAIHBwekpaUBKJmJpDznKnNBAT0x\niDyg5wwQGHX4IEQTCuarJiM2DBIt1N04Vmyd/eqrrzBjxgytecmnGQMMb6VSXN/e3l5tOcYo62X6\n66+/xOWuXbvqtE63bt3EgP7KlSt6l/nw4UOkpKSI77W15gGAt7e3UgudoRRbobVNgSWXn5+v9N6Q\ngfqys7OV3tvY2Oi87u3btzFz5kwcOnQIhYWFOq3z9OlTjZ8zxtCuXTudGm7Onz8vLicnJ2Py5Mk6\n1eHOnTvicmJiosqAviK2rTIrz34KKO+rhg4oyTlHQEAAtm3bJt7ECQ0NLTPGwpMnTzBp0iTs3bsX\nT548wZAhQ3Dy5Em89tprZfKsUaMGtm3bhqFDh6KoqAhPnz7FG2+8AS8vL7Rv3x4SiQQ3b95EZGQk\nOOdwcXGBu7u7OH5J6XOuOjY2NmJAX/qYq2wooCeGkXe5ZwADtdATok5hYSEF84QYyNPTE3379hXf\n5+XlITExEefPn0dWVhY455g1axbi4uLEbtvqyLvZc87F7vflJb8oBMq2psrfy4OhyjLncUZGhlLQ\npOvgcE2aNBGXyxNMKQbzEokEdevW1bpO9erV4eDgYLTvVrEXha4tmKXTGbMnhq43Kv7880/4+voi\nNzdXp27d+nRRdnZ21qkOirNMxMTEICYmRqf1FCkeT3IVuW2VVXn209JpDd1PV61aJQbzrVq1Qnh4\nuMrHMpydnbF79270798fJ06cQF5eHoKCghAdHa0y30GDBuHQoUMYPXq0eE64du0arl27JqZhjKFZ\ns2bYtWsX/vOf/4h/1/WxJmM+pmNq1KRKDKLY5Z5a6AlRTyKRlHlOl4J5QvTj7e2N4OBg8bV+/XqE\nh4cjMTERn332GYCSi7zQ0FB88803GvNydXUVlxMTEw268L9+/bpYtmK+AMSpteSMMaXZy1C6J4Gt\nra1O6ymmK893Wt7ngnWtny4Ub8rIp83TRj4iP1DS8mfIqPult0WXYC01NRXDhw9HXl6euB8uWbIE\nZ86cQVJSErKzsyGTycTXTz/9JK6r2F1dHV1/i4yMDHG5vM+Vy6eAfFnbVlkp7qeZmZk6tdLn5uYi\nKytL/K4NGT9EPkuBPK///Oc/GsdYEAQBCxcuBFASTF+7dg1RUVFq0/fv3x/37t3Dd999hzfeeAP1\n6tVDtWrVUKtWLXTr1g0hISGIjo6Gl5eX0s3Dhg0b6lR/xePKmOcPU6AWemIQeUAf7QIE7AvA+N/H\nw0KwQIe6HXByzEkT144Q8yEIAjZs2AAA+OmnnyiYJ8SIqlevjpUrVyIzMxMbN24EUNL13s/PD25u\nbirXUZwrmXOOyMhIjYOvqZOTk4OYmBjxorb0HMzy50kjIiLAGMOFCxf0LsMUSrfcZWdn6/RMuGLX\nVV27vqorV59WR2N2mW3evDnCw8MB6DZtFlAyOBdQEsR6enoaVL6DgwOkUqn4jPTTp0+1/l+xbt06\npKWlid3jT506pTFIKT3Wg7Eo/n4TJkwwyrRxpt42c522rnnz5krv4+PjtT4HLt9P5QMdGrKvXrx4\nUexNwRiDj4+P1nU6d+4Ma2trcd+OiopS2e1eztraGp9++ik+/fRTjfnGxsaKy506ddJaj6KiIqUe\nPbr0BDJnFNATg8gD+gIJIOMyyIpKBg3JLTTOIBuEVCXyoL5+/fr46KOPKJgnxMhWr16N8PBwJCUl\noaCgAHPmzMGuXbtUpvX29oaNjY0YNG7fvr1cAf3OnTvFrumMMfTu3btMmj59+ohztJ89exaJiYk6\ntyKZioODA6ysrMRWv/j4eJ1GW79//764XKtWLb3LrV27trgsk8nw6NEjrRfbWVlZSi3DhpLPy805\nx/Xr11FcXCyOiK2O4ngBhszrLdekSRPcvHkTAPDgwQO0bdtWY3rFAQznzp2rtcWxokb1rlOnjris\n2GvBEKbetszMTKxZs8aoebq6uhoc0Ht6ekIikYi9EKKjo7UG9Ir7qUQiKXNTQB8PHjxQeq/L4I2M\nMdSoUQMPHz4EY8woj8nExsaKx78gCDqNu/Ho0SOxy70gCGjUqJHB9TAl6iNNDPPiYCgstSdZCHSv\niBBVBEHA119/TcE8IRXA1tZWvEjmnGPPnj24evWqyrRSqRQBAQHiPL6//PILEhMT9SpPJpOJU7UB\nQOvWrdGtW7cy6caNGwcrKyswxlBcXIzVq1frVY6ptGvXTlw+d+6cTusoThPWsWNHvcusV6+eUlCv\nOMiaOvLBsYxFcfTt7Oxsjd2CgZIByRR7XqgbvVsfXl5e4rI8sNdE8dl1TSPEy508WTG9KL29vQGU\nHH+6/Ha6MIdtM8dp66ysrNC1a1dx34+IiNC6jvy7YYyhe/fusLAo//V66cEadRmLhHMu9rYAjDON\n586dOwGUbNPAgQN1urEgP6YYY2jevLleswSYIwroiUEUW+gVUUBPCCHEFMaMGaP0HLum6eumT58O\nCwsLMMaQm5uLiRMn6lXWsmXLxEGaGGOYOXOmynR169ZVunkQEhJSrvmxc3JyjBYk6UIxMA0LC9Oa\n/tSpU0pzz6vqraALxfW2bt2qNf3mzZvLVY46TZo0QZs2bcT3mqZKBIBff/1VHC/AwsICvr6+BtdB\nHhgDUHtTSpFigKjt8YPIyEhcvny5QqYb7tq1q/hoRkpKCvbs2WNwnqbeNvm0dcZ8KY7qb4ihQ4cC\nKAmUd+3aVWa2BUV5eXnYvXu3+P6dd94xqGz5QJny71qxJ4U658+fR25urngTwt3d3aA6PH36FN9/\n/734XtdzuOIxpXisVVYU0BODyAP6IgroCSGEmAGJRII5c+YAKLnI3b9/v9qRtt3c3PD111+LgfaR\nI0cwYcIEnVp7w8LCMG/ePLG1bdCgQfD391ebftmyZeKNBplMBl9fX3GaJV1cv34d3t7eOHbsmM7r\nGGrChAliV/ObN29q7FmQl5eHKVOmiBf3/fr1K/fF+vjx4wGU/H4HDhzQuM2nT5/Gzp07jR6cyp/Z\n5ZwjNDRUbSt5bm4u/vvf/wIoCWw++OADo7Q6vvHGG+KyLvuJ4lgRpWdTUZSdnY2goCAAFTPKt5WV\nFaZNmya+nzJlivjcti5UDUJoLttmjj788ENxqsz09HQsWrRIbdqvv/5a7OLu6Oio8Xyli7Zt24q9\naTjnWLRokcYbCsXFxZg7d6743tbWFj169Ch3+QUFBfD390d6ejoYYxgwYAAGDRqk07qnT58WlxWP\ntUpL/p8YvczzBYCX/EzmKeybp5wD/JcW4Jj/76v/lv6mrhohhIjM/VxK1PPx8eGMMS4IAh87dqxO\n6xQWFvLGjRuL6w0fPlxj+iFDhnBBEDhjjDPGeOfOnfm5c+dUpo2Pj+cffvihmDdjjLu7u/OnT59q\nrVdUVBS3t7cX17O0tOQff/wxv3Pnjtp1Ll68yEeNGsUlEgkXBIEvWLBAazmaREREiHXv3bu31vSf\nfvqp+L1YWFjwlStXcplMppQmMTGR9+7dW0xXrVo1fvnyZYPK79Onj5jOwcGB79+/v0ya8PBwXrNm\nTS4IAq9WrZqYPj4+Xut2aVNUVMRbtGgh5tm0aVN+7do1pTRPnz7iSXxgAAAgAElEQVTl/fv3F7fb\nxsaGJyQkGFy2nJubm1i+pn2Ec843bNgg1kMqlfKwsLAyaWJjY3mnTp04Y4xXr15d63EVGhqq97HH\nOefZ2dncy8tLrI+zszPfvn07LyoqUpk+IyODb9myhffq1UvlsVoR21aVLFq0SOkYDQ4O5sXFxeLn\nxcXF/LvvvuMSiUT8XlauXKkxz169eol5ajpOly5dKqYTBIH36tWL3717t0y6R48e8aFDhyqlnTt3\nrtp8161bx0NCQnhKSorKz6Oiori3t7fSPpaYmKhxm+SKioq4o6OjeK5KS0vTaT1NjHGNoZCH/vFi\neVaiFwX0cltWPeEc4DtaKwf0A7cNNHXVCCFEZO7nUqJeeQJ6zjlfu3ateLEnkUj4zZs31aYtKiri\nY8eO5YIgKAX2rq6ufNiwYXzChAn8/fff5x07dhQ/k9epU6dO/PHjxzrX6/r169zV1VWpHMYYb9as\nGR86dCgfP348DwgI4G+++SavU6dOmfJWr16tc1mq6BvQ5+bm8q5duyrVt27dunzEiBE8KCiIv/HG\nG9zKykqpjj/88IPB5d+7d4+7uLgoldu6dWseEBDAx4wZw9u2bSvm88UXX3BXV1ejBvScc37z5k1e\no0YNsQ7yOo8fP577+flxW1tbpX1sz549RilXbt68eToHYPn5+dzT01Npf/H09OQjRozggYGBSr9h\n48aN+apVqyosoOec8/v373MPDw+l38/JyYkPHjyYjxs3jgcFBfF3332Xt27dmltYWIhp3nvvvZey\nbVWJTCbjgwcPVvqu3d3d+ahRo/ioUaO4u7u70vE5bNgwrXn6+PiI50NNx2lBQQHv37+/UtkWFha8\nW7duPDAwkI8fP5736dOHS6VSpTp0796d5+Xlqc139uzZYl7t27fnH3zwAZ84cSIfPny40r4gCAJ3\ndnbmMTExOn9fR48eFdcdOnSozutpQgE9vSp1QL91ZTLnAA/zUg7oh+wYYuqqEfLS5Ofn84MHD5q6\nGkQDcz+XEvXkAT1jTK+L84KCAt6wYUNx3ZEjR2pd5+eff+Zubm7ihWzpoFt+ESgIAre3t+cLFy7k\nubm5em9TWloanzVrFrezs1NbjmJZgiDwjh078t9//13vskqTB9TaWt4U5ebm8lGjRqn9XuR/c3Jy\n4jt27DBa+bGxsbx58+Yay5w4cSIvKiqqkICec86jo6N5y5YtNdahZs2a/JdffjFamXJ3794Ve2Z0\n6tRJa/rbt2/zZs2aaaxru3bt+K1bt3QK1g0J6DnnPD09nfv7+3MLCwutx5MgCNzOzo4vX778pWxb\nVZOTk8MDAwO1fs9BQUE6nbMUz7vajtPc3Fw+adIkcV/V9juPGTOGZ2Vlacxz9uzZOp0bBw8ezO/d\nu6fPV8UDAwPFPIx17WbqgJ4edCaGeTFVBo1yT15VBQUFGDFiBPbt24fvv/8en3zyiamrREiVw148\nH830eE7a0tISs2fPxuTJkwEAe/bswYIFCzRO6/T+++/j3XffRXh4OMLDw3HhwgU8fvwYz549g52d\nHZydndGmTRsMHDgQvr6+qFmzZrm2x9HREUuXLsXMmTNx6NAhHDt2DFevXkVKSgpSU1MhlUpRs2ZN\ntGjRAt7e3hg2bJjSIG2G0vf7lEql2Lp1K6ZNm4YtW7bgxIkTSEpKQnZ2NpycnODp6YnBgwdj3Lhx\ncHBwMFr5LVq0wLVr17B+/Xrs2rULcXFxyMnJQd26ddGpUyeMHz8effv2VcpXn31EF+3atUN0dDS2\nb9+O3bt3IzY2Fk+ePIGjoyNcXV0xbNgwjBkzBs7OzkYtFygZnM/Pzw979+7F5cuXce3aNaXR70tz\nc3NDdHQ0fvjhB/z666+Ii4tDfn4+6tSpA09PT7z//vsYOXIkrKyscP78eZ1+h/Ice3IODg7Ytm0b\n5s2bh+3btyMiIgJ3797Fs2fPxM/d3NzQtm1b9OnTBwMGDFA7JV1FbFtVYm1tjU2bNmH8+PEIDQ3F\n6dOnkZSUBACoX78+evTogTFjxqBLly4656nrdyiVSrFmzRpMnz4dYWFhOHPmDG7duiXOUe/o6Ah3\nd3d07doVY8aMgaenp9ayP//8c7Ru3RrHjx9HdHS0eB52cHBAvXr10LNnTwwfPlzlrCKaPH/+HLt3\n7wZjDB4eHhg8eLBe65srVnJDgJgrxlhJM72Z/k7bVzyE/8z6WNsR+HjIv39/r+V72P3ebvUrElIF\nKAbzchTUmyf5BYm5nksJIUSVqKgovP7662CMYdy4cVi/fr2pq0RIpRUSEoKpU6eCMYaNGzdi7Nix\nRsnXGNcYCnnofReKRrknBpGPck8t9ORVoyqYB4Dg4GDk5uaaqFaEEEKqktdeew1+fn7gnGPr1q1I\nTk42dZUIqZRkMhm++eYbAECzZs0QEBBg4hoZDwX0xDAvutwXUUBPXiHqgnkPDw8cP34c1tbWJqoZ\nIYSQqmbp0qWwtLREQUEBFi9ebOrqEFIpbd68GfHx8WCMYfny5eKUnFUBdbk3c+be5f7nJfcxck4T\n3HMAbkT+jj5N+6CouAgSJoGtlernoAipzDQF8ydOnED9+vVNVDOiCXW5J4RUZl9++SWWL18OKysr\nxMbGokmTJqauEiGVRl5eHtzd3fHo0SMMGDAAhw4dMmr+pu5yT82oxCAMXL6AahbVYGNpY9oKEVKB\nKJgnhBBiCkuWLMGSJUtMXQ1CKiWpVIoHDx6YuhoVpur0NSCm8aLLfTF7dUYSJa8mCuYJIYQQQoi5\noYCeGEQ+KF4xAwRGuxOpmgoLCymYJ4QQQgghZociMGIQeUDPATBQCz2pmiwsLNC4cWOlv1EwTwgh\nhBBCTI0CemKYF4M/UAs9qcoYY1i9ejWmTp0KgIJ5QgghhBBiHmhQPGIQxS739Aw9qcrkQX2dOnXw\n4YcfUjBPCCGEEEJMjgJ6YhB6hp68Shhj+PLLL01dDUIIIYQQQgBQl3tiIPEZegroCSGEEEIIIeSl\nogiMGEbhGXoaFI8QQgghhBBCXh4K6IlBqMs9IYQQQgghhJgGRWDEIErT1tGgeIQQQgghhBDy0lBA\nTwzzosv98m5At5+6wWaRDeyX2GNd1DoTV4wQ3RQUFODXX381dTUIIYQQQgjRGwX0xCDyFvoiASgq\nLkJuUS6yCrIg4zIT14wQ7QoKCjBixAi8++67WLJkiamrQwghhBBCiF4ooCcGUQzoFVkINCMiMW/y\nYH7fvn0AgDlz5lBQTwghhBBCKhUK6IlhKKAnlVDpYF5u8+bNeP78uYlqRQghhBBCiH4ooCcGYS+e\noaeAnlQW6oJ5Dw8PnDhxAnZ2diaqGSGEEEIIIfp5ZQJ6xlh9xtgyxtgNxlgWYyyNMXaFMfYfxpij\ngXlbMMbeYIytYIydZow9YYwVMMbSGWNXGWPBjLFWxtoWcyLvci+jgJ5UAtqC+fr165uoZoQQQggh\nhOjvlYi6GGMDAOwA4IiSGdbk2gJoB2ACY8yPc36lHHnXAhAHoOaLPynmXx1AawBtAExijC3lnM8t\nxyaYr2Lqck8qBwrmCSGEEEJIVVPloy7GmBeAXwDYAMgGsBTAcZRsux+AKQDqA/idMdaRc56sZxHV\nUBLMcwAxAPYDOA8gGYAtgD4ApgFwAPAlY0zGOf+vodtlLqiFnlQGFMwTQgghhJCq6FWIur5FSWBd\nBGAA5/yswmenGWPRALYCcAGwEMB4PfPnAI4BmMc5j1Tx+RnG2A4A5wDUAjCbMfYT5zxez3LMEnvR\nIaGIKf+dAnpiLmQyGQXzhBBCCCGkSqrSz9AzxjoA8EFJ0L25VDAPAOCcb0dJiz0D8OGLLvQ645w/\n5Jy/qSaYl6e5DeDrF28tAAzVpwyzRl3uiZmTSCRo27at0t8omCeEvOry8vLw3XffwcfHB7Vr14al\npSUEQYAgCJg+fXqFlXvy5EmxnD59+hgtX1dXVzHfhIQEo+VrLmbNmgVBECCVSnHv3j1TV4eQSiUv\nLw8NGjSAIAgYPHiwqatjdFU96npbYfknDel+QknXeAkAXy1py+uEwrJ7BeRvEtTlnlQG8+fPBwAs\nWLCAgnlCKhkfHx+cOnVK7ee2trZwdHSEp6cnunXrhg8//BBNmzYtd3mFhYU4evQowsPDcf78eTx+\n/BjPnj1D9erV4ezsjNatW2PQoEEYMmQIatasqT1DDVJTU3H48GEcO3YMf/31F1JSUpCamopq1aqh\nRo0aaNGiBby9veHn54f27dsbVJaijIwM9OjRAzExMQAAxpjSvy+DsctijBk9z+LiYty4cQOXLl1C\nVFQULl26hGvXrqGwsBBAyb55/Phxo5apyq1bt/Dtt9+CMYaPP/4YTZo0qfAySeV07tw5hIWF4fTp\n00hKSgIA1K9fHz169EBAQAC6du1aYWU/ffoU69evxx9//IFbt24hLS0Njo6OaNSoEQYNGqTXufmf\nf/7B2bNnER0djRs3buD+/ft48uQJcnNzYWNjA2dnZ7Rr1w6DBw/G8OHDYWNjozE/qVSKBQsWICgo\nCEeOHMGBAwfg6+trjM02D5zzKvsCEAGgGEAWAEFDurov0skA/FRBdWmvUMa3eqzHS34m83R4Sjjn\nAG87ERzz/339efdPU1eNkDKCg4P5gwcPTF0NYgLmfi4l6vn4+HBBELS+GGOcMcYFQeBTp07l+fn5\nepe1c+dO7ubmJuYlz690GYwxbm9vzxcvXsxzc3P1LictLY3Pnj2b29nZqS2rdHmtW7fmu3fv1rss\nVSZMmCCWZ2lpyQcMGMA/+ugjPnnyZD558mT+22+/GaUcVSIiIsSye/fubbR8XV1dxXzj4+MNzm/f\nvn3c1tZW6Tco/RsZs/6a+Pr6csYYt7a25snJyS+lTFK5ZGdn88DAQJX7quLfgoKCeE5OjtHLX7Nm\njdLxouo8Zm1tzVeuXKk1r6KiIo3HXeltqlu3rk7nrMLCQt64cWMuCAL39PTkMpnMGJvOOTfONYZC\nHnrHmVW9GbUlSr6cfzh/0ZSsAuf8EWMsC4Ddi3Uqgo/C8s0KKuPlezEP/cI/AbezsWjk0AhFxUWw\nsdR8p4wQU5g8ebKpq0AIKQfOORhj8PT0RN++fZU+e/78OeLi4nDx4kX5jXAEBwcjOTkZO3fu1Cl/\nmUyGCRMmYPPmzUotvY0aNUL79u3h7OyM9PR03L59G9HR0QCArKwsfPXVV9i3bx8OHjyI2rVr61TW\njRs38NZbbyE+vmQoHXlZbm5uaNWqFWrXro2CggI8fvwY0dHRSElJEdcbMWIE4uPj8cUXX+hUlrpt\n3bFjh/j++PHj6N69e7nzq6rS09ORk5OjstVfvj++DJGRkfj999/BGENAQADq1KnzUsollUdxcTGG\nDx+Ow4cPi/tl06ZN0blzZwDAhQsXcPfuXQDAxo0b8fTpU/z2229GK3/u3LlYvHixeO6USqXo0aMH\nXF1dkZWVhbNnzyIxMRF5eXmYMWMGMjMzsWDBAq35yvNzd3eHh4cHnJ2dIZVKkZ6ejqtXr+LmzZJw\nKjk5Ge+++y42bdqEMWPGqM3PwsICn3/+OaZOnYq///4bYWFhGDt2rLG+BtMqz12AyvACYIV/W8QP\n6JA+5kX6pAqoiw2A+y/yzwHgose6Zt2qFP7pQc4BftAD/F7aPVNXhxBCVDL3cylRz8fHR2yhGTt2\nrNp0t27d4h06dFBq0dm7d69OZQwdOlSpFahLly78/PnzKtMmJCTwgIAApZYiDw8P/uzZM63lREVF\ncQcHB3E9S0tLPnHiRH7nzh2161y8eJGPHj2aW1hYcEEQ+IIFC3TaJnViY2PFbW3WrJlBeZVHZWmh\nDw0N5YIg8Lp163JfX1/+v//9jx85coRPmzatQuqvjp+fn1je9evXK7w8UvksWrRI3EcsLCx4cHBw\nmTTfffcdl0gk4nlrxYoVRin70KFDSufOQYMGqexFsmbNGm5lZSWmO3z4sNo8i4uL+cSJE/nBgwd5\nenq62nRXrlzhbdu2Fc/5dnZ2PDExUWN9MzMzuZ2dHRcEgTdv3lz3DdXCGNcYMKCF3uSBd0W9ADgp\nBPQ7dEh/4UX6jAqoy48KdVmm57pmfRF65JMDnAP8QDPw+2n3TV0dQghRydzPpUQ9XQN6zjl/9OgR\nr169unjR+Oabb2rNf9myZUoXpEFBQTrVSx7wyV++vr4a06enp/MmTZqIwXyNGjX4qVOndCqLc85j\nYmJ4mzZtDA7oz549K25vr169DMqrPCpLQP/48WOVwcH8+fNfWkB/584dMQjr3LlzhZZFKqdnz56J\nNwkFQeBfffWV2rSzZ88Wg9+aNWvytLQ0g8tv166dWHb79u15YWGh2rTBwcHisdO6dWteXFxscPkp\nKSncyclJzHfx4sVa15E/miAIAj948KDBdeDc9AF9VR7l3lphuUCH9Pkq1jMYYywQwEcv3sYAmGfM\n/E1NPigeByCwqrw7EUIIMXcuLi547733xIucM2fOaEx/9+5dzJ07V+ymOnDgQKxfv16nsgICArBo\n0SKxrIMHD2L79u1q08+cORP3798H5xwSiQQHDhxAjx49dN62Vq1aITIyEv3799d5HVUKCv69JBIE\n+n9bHWdnZzRo0MCkddi0aROKX8wmNGLECJPWhZinsLAwZGZmgnMOR0dHzJ07V23aefPmwcHBAUDJ\nIyXbtm0zqOy///4bV69elTdAYsGCBbCwUP809yeffIKGDRuCc47Y2FgcO3bMoPIBoFatWhg69N/J\nw+SPRGmieCxt2rTJ4DqYg6p8Js9VWLbSIX01FesZhDE2ECWt8wCQAuBtznm+hlUqnxcHcTF7uaPj\nEkIIIaq0a9dOXM7NzUV6erratKtWrUJRURE457C2tsbatWv1KmvGjBnw8vIS369YsUJluuTkZGzZ\nskV8JnTy5Mnlem7d2toaXbp00Xu9+Pj4MlPFcc4REREh/l2XqeSioqIwbdo0eHl5wcnJCVKpFA0a\nNEDfvn2xatUqZGRk6F03bQoKChASEoKePXvC2dkZNjY2cHd3h7+/PyIiIoxenjlRvEE0bNgwndZJ\nSUlBWFgYAgMD8dprr8HJyQlWVlZwdHRE8+bNMXr0aOzbt0+nvMLCwsT9IjAwEEDJfvPLL7/g7bff\nhru7O2xtbSEIArZs2aI2n1OnTuHTTz+Fl5cXatWqhWrVqqFevXro06cPVq5ciczMzJe+bVWFfHsZ\nYxg+fDikUqnatNbW1hg+fLj43tDn6C9cuCAuSyQSrTcbBUHAG2+8Ib7fs2ePQeXLOTs7i8tZWVla\n0/ft2xcODg7gnOPw4cMa/4+oNMrTrF8ZXjDxM/QAegLIfpFnKoC25czHrLuJ/jHxV84B/qsneFJm\nkqmrQ14x+fn5fMuWLUbptkWqNnM/lxL19OlyzznnGzZsUHqO/tGjRyrT5eXlcVtbW7G7qC55q/LT\nTz8plXfmzJkyaRYuXCimsbCwMEqXcH3cv39f5ajXqmYLUNWNPCcnh/v7+2sd/d/JyYlv375dY130\n6XIfGxvLmzdvrrHMSZMm8cLCQqN3uVfnZXW5v3btmlhO06ZNdVonJCSEW1hYaPx95Z+99tprPCEh\nQWN+oaGhSsfew4cPec+ePVXmHxYWVmb9pKQk3q9fP532m3379r3UbasK8vPzxbE1BEHgO3fu1LrO\njh07xO/JyspKYxd5bZYvX6400rwu/ve//4nrNGnSpNxlK1IcZ2LixIk6rTNkyBBxHV2+N22McY0B\nA7rcV9lR7jnnBYyxpyh5ll6XPlMNUPJFJhpaNmPsdQC/o6T7/nMAgzjnVw3MU+1n//3vf8V5tl82\nscs9oy735OUqKCjA8OHDsX//fty4cQNLliyhXiKEEDx8+FBclkgkcHJyUpnuwoULyMnJAVDyf6y/\nv3+5yhsxYgQmTpyIoqIiAMCJEyfQrVs3pTTyucoZY+jatSsaNWpUrrLKy97eHp9++ikAICkpCXv3\n7gVjDPXq1SvT8uvh4aH0Pi8vD3379sWFCxfEc2ydOnXQs2dPODg44P79+zh58iQKCwuRmpqK0aNH\nIz09HZMmTTKozgkJCejbty8eP34MoOS7a9myJTp27AjGGK5cuYKYmBisXbsW1tZGfVrSLCh2R9b1\n0YykpCQUFxeDMQZXV1e0aNECzs7OsLa2RlZWFmJjY/HXX3+Bc47Lly+jZ8+e+Ouvv8Ru2Jrk5eXB\n19cXly9fhoWFBbp06QIPDw8UFhbi6tWyl7i3bt1Cv379kJSUJO43bdu2RevWrWFra4vHjx/j9OnT\nSE1NRWpqKt555x3s2LFDqQX5ZW1bZRUXFweZTAag5Pjo0KGD1nUU0xQVFeHWrVto1apVhdVRk4SE\nBOTk5GidQ16T48eP4+DBg+L7d999V6f1evToIa539OjRl/ZIy/z583Ua4V9fVTagfyEWJS3lHowx\ngauZuo4xVheAPUoC+lhDCmSMtQUQDqA6gDwAfpzzC5rX0o6/6NpubuQBfTEDGCiYIi+HYjAPAMuW\nLQMACuoJIThy5Ii43KFDB1haWqpMp/h8PWMM3t7e5SrPxsYGrVu3RnR0NBhjZZ7bLyoqUgqGy9Nl\n3lA1atRAcHAwAODkyZPYu3cvgJLgXf53db744gux/oIgYOnSpZg+fbrSuTYpKQmjR49GREQEOOeY\nPn06vL290bFjx3LXOTAwEMnJyQBKbkhs27YNb731llKao0ePwt/fH998843a37myioyMFJcVH+vQ\npHnz5ggODsbQoUNRv359lWnu3buHSZMm4ejRo0hISMDs2bPx448/qkyraM+ePZDJZOjZsyfCwsLQ\nuHFjpc8Vx2bIzc3FO++8g4cPH4Ixhv79+yMkJKTMzaL8/HwsWbIECxcuBOccQUFB6Ny5s8obXhW5\nbdqkpaVh3jzjDoHl5ORkcGPcrVu3lN7rcqNQnkZ+/MbFxZU7oFecqvPp06fIy8vT2OUfgDhdJ1AS\n29y6dQvt27fXq9zMzEzExsZi586dWLt2rXijZ9SoUWWmNVVH8dEsxWOtos2fP1/t727Q9Wt5mvUr\nywvAQvzb7d5bQ7qRCukCDSivBYDHL/LKQ0nLvKHbYNbdRP8vaCfnAN/ZCvzJ8yemrg55BeTn53M/\nPz+xa5L85eHhoXF6E/JqM/dzKVFPny738i7C8vSbN29Wm3b8+PFiWldXV4PqGBAQIOZVeiqkpKQk\npS7CW7ZsMagsQ+nT5f3u3btKU12tXr1abdrs7Gzu5eUl5t2vX79yl//HH38o/Y7Hjh1TW+7p06eV\nulxXlS73np6eYjmHDh0yat6FhYXib2Vra6v2/07FLveMMd6mTRuem5urNX/5Iyby2R+0PRb3n//8\nR0z/ySeflGub5HTdNn3IH1kx5ssY3c1//PFHMT9HR0ed17O3txe/7/Xr15e7fMXHQgRB4Pv379eY\nXiaT8UaNGikdq5qObbm5c+eq/R4FQeDVqlXjc+fO1avuiYmJYh4SiYTn5+frtX5pxrjGAHW5V+s3\nAHNeLI8DoO4WTOCLf2UADpSnIMaYG4BjAGoDKALgzzk/XJ68KhOlFnpqGSUVrHTLvJyHhwdOnDhR\npbvWEfPFFlT+cx//r3n2AtNFTk4OYmNj8dNPP2HdunUASv4/GjlyJMaMGaN2vdTUVDFtzZo1DapD\njRo1xOVnz54pfSZ/zzkHYwyOjo4GlfUyrV+/Xmz9atGiBaZNm6Y2rY2NDYKDg9G7d29wznH8+HH8\n888/ZVpldSEfeZoxBj8/P/Tr109t2u7du+ODDz7QOMNAZaTYkmns0fYtLCwwatQozJo1C7m5uTh7\n9iwGDRqkNr18312+fLnWFtiioiJ8//33Yjnr1q3Ten04Z84chISEICMjAz///LO4fnnou226MvY1\nrjHye/78ubisz2Mn8scUSuehrzZt2qBp06a4e/cuGGOYP38+Bg0apHak+++//x6JiYlK267LIHaA\n6u+Lcw4vLy9s3boVrVu31qvudevWhSAIKC4uBucc8fHx5TpXmYsqHdBzzq8wxiIA+AAYwxgL45yf\nVUzDGPMH0Bcld0XCOOdPS33eGMC9F28jOOdlhn9ljDUE8CeAeihpnQ/knP9q5M0xTzRtHXlJtAXz\n6rrgEUKqjtDQUISGhqr9nDEGe3t7TJ48GV9//bXGvBQvJO3s7Ayql+L6pUfsLn3BamhZL5P82X+g\nZJo+bXr16gV3d3fcvn0bQMl4AuW5SD5x4oS4PHr0aK3pAwICqlRAn5GRgby8PPG9unEgNHn27Bki\nIyMRGxuL1NRUZGdni1PgASVdreWio6O1Br2Ojo548803tZYbFRWFx48fgzGGXr16wcXFRes6UqkU\nXbt2RXh4ONLT0xETE6MxQDP2tmnTuHFj8Vl1c6K4j1hZ6TKhV4lq1aqJy7m5hk3u9dVXX2HcuHHg\nnOPq1asYMmQINm/erPS7c87x448/4osvvigTmOtSfufOnfHJJ58AAGQyGVJTU3H16lXcunULV69e\nRceOHREYGIgVK1bofH6VSCRwcHBAWloagJKZSCigN29TAZwDYAvgKGNsKUqCbwsAQwFMeZHuEYD/\naMhHZfMFY6wmgP8D0OhFmjUAohljmh5Iyeac39djG8wW4wrT1tEz9KSCUDBPzFllbt2ubNS1anGF\ncWa++uorzJgxQ2te1atXF5cNaaUqvb69vb3acoxR1sv0119/ictdu3bVaZ1u3bqJAf2VK1f0LvPh\nw4dISUkR33fu3FnrOt7e3mCMme14Q/rKzs5Weq/PoGG3b9/GzJkzcejQIRQWFuq0ztOnTzV+zhhD\nu3btdGpVPn/+vLicnJyMyZMn61SHO3fuiMuJiYkqA/qK2LbKTLG3hOIYBtrk5/87g7ahA0qOHTsW\nx44dw65du8A5x9GjR9G0aVP07NkTjRs3xvPnz3HmzBmxZf7tt9/Gr7/+2+ZZ+vyoyuDBgzF48OAy\nf79y5QomTZqES5cuYd26dbh06RIiIiJ0DuptbGzEgL70MRncNAwAACAASURBVFfZVPmAnnN+nTH2\nDoCfATgC+PrFS0yCkpHt/TjnyRqyUncWawPAQyHN5BcvTSIAqJ/otRKRd7n/aAhQtMoFFoIFLAQL\nPPjsAapX036QEqINBfOEEDlPT0+lQY/y8vKQmJiI8+fPIysrC5xzzJo1C3FxcWK3bXXk3ew552L3\n+/KSXxQCZVtT5e/lwVBlmfM4IyNDKWgqPQiaOk2aNBGXyxNMKQbzEokEdevW1bpO9erV4eDgUGm+\nW33peqPizz//hK+vL3Jzc8EY0xqAy/PVpduz4lzfmijOMhETE4OYmBid1lOkeDzJVeS2VVaKgas+\nLe2KaY3RY2jbtm1wcXFBSEgIiouLkZ+fjz/++EP8XP57jR49GkuXLlUK6A15BKlDhw6IiIhAr169\ncOnSJURHR2PGjBk6D4RYVW4AAsAr0Ueac/4HSgLvFSgZxf45gAwAfwH4LwAvzvlf6nNQGnxL2+e6\nvqqGFwF9oQQokBUgpzAHmfmZsBCq/L0i8hIUFxdTME8IEXl7eyM4OFh8rV+/HuHh4UhMTMRnn30G\noOTiMTQ0FN98843GvFxdXcXlxMREgy78r1+/LpatmC8AcWotuRs3bpS7nJepdE8CW1tbndZTTFee\n77S8zwXrWr/KoPS26BKspaamYvjw4cjLyxP3wyVLluDMmTNISkpCdnY2ZDKZ+Prpp5/EdRW7q6uj\n62+RkZEhLssDOX1eAMQpIF/WtlVWijcPMzMzdWqlz83NRVZWlvhdGzp+CAAIgoBvvvkGMTExmDZt\nGtq2bYsaNWqgWrVqaNy4MUaMGIFjx44hNDS0zDmhYcOGBpUtlUqxatUqACUB+ubNm5X2QU0Uj6vK\nfv54ZaIuzvlDALNfvPRZLx6ARMPnJzV9XtWx4n8HxVNEAT0xBkEQ0LNnT6WAnoJ5Qkhp1atXx8qV\nK5GZmYmNGzcCKOl67+fnBzc3N5XrdO/eXVzmnCMyMlLj4Gvq5OTkICYmRrxAVswXKBmky9vbGxER\nEWCM4cIFg2eyfSlKt9xlZ2crDf6njmLXVV2602oqV59Wx8reZVaRg4MDpFKp+Iz006dPtf6ft27d\nOqSlpYnd40+dOqUxSCk91oOxKP5+EyZMMMq0cabeNnOdtq558+ZK73UZ2C0hIQHAvwMdenp6GlSH\n0vWRB9fqKN7QdHJyKnMDtDy6desGGxsb5OTkoLCwEBcvXkT//v01rlNUVKTUo0eXnkDmjKIuYhAG\nDg5AVqqvh0R4Ze9xECObPn06AODzzz+nYJ4QotHq1asRHh6OpKQkFBQUYM6cOdi1a5fKtN7e3rCx\nsRGDxu3bt5croN+5c6fYNZ0xht69e5dJ06dPH3GO9rNnzyIxMdHglqmK5uDgACsrK7HVLz4+XqfR\n1u/fvy8u16pVS+9yFee2lslkePTokdaL7aysLJ1b5SqLJk2a4ObNmwCABw8eoG3bthrTKw5gOHfu\nXK0tjoqj6BtTnTp1xOXkZE1PsurO1NuWmZmJNWvWGDVPV1dXgwN6T09PSCQSsRdCdHS01oBecVwL\niURS5qZARTt37hyAknNlly5djJInYwwODg7IyckBUHamEVUePXokdrkXBAGNGjUySl1M5ZXock8q\nEC8u0zovMIFGvCdGNX36dGzcuJGCeUKIRra2tuJFMucce/bswdWrV1WmlUqlCAgIEOfx/eWXX5CY\nmKhXeTKZDMHBweL71q1bo1u3bmXSjRs3DlZWVmCMobi4GKtXr9arHFNp166duCy/ENfm7Nl/JxPq\n2LGj3mXWq1dPKahXHGRNncjIyCr1PCwAeHl5icvywF4TxWfXdZnC6+TJk+WrmBbe3t4ASo4/XX47\nXZjDtpXn8QFdHi8whJWVFbp27Sru+xEREVrXkX83jDF0795d7RRzFUF+npXTZeYMXRQVFSkF8bo8\nRiA/phhjaN68uV6zBJgjirqIQeyrA0Wl9iLqbk8qwrhx4yiYJ4RoNWbMGKVunJqmr5s+fTosLCzA\nGENubi4mTpyoV1nLli3DtWvXAJRcGM6cOVNlurp16yrdPAgJCVEKfHWVk5NjtCBJF336/Dt+b1hY\nmNb0p06dwj///CO+V9VbQReK623dulVr+s2bN5erHHMmD4wBqL0ppUgxQNT2+EFkZCQuX75s9LnV\ngZLZEOSPZqSkpGDPnj0G52nqbZNPW2fMl+Ko/oYYOnQogJJgedeuXUoj2JeWl5eH3bt3i+/feecd\no9RBVxs3bhR7T7i4uMDPz88o+R49elRp/IAWLVpoXUfxmFI81iorCuiJQdq1o4CeEEKI+ZBIJJgz\nZw6Akovc/fv3qx1p283NDV9//bUYaB85cgQTJkzQqbU3LCwM8+bNE1vbBg0aBH9/f7Xply1bJt5o\nkMlk8PX1xZkzZ3TeruvXr8Pb2xvHjh3TeR1DTZgwAYJQ8p/8zZs3NfYsyMvLw5QpU8RAql+/fnB3\ndy9XuePHjwdQ8vsdOHBA4zafPn0aO3furJDg1JTeeOMNcVmX/URxrIh9+/apTZednY2goCAAFTPK\nt5WVFaZNmya+nzJlivjcti4eP35c5m/msm3m6MMPPxSnykxPT8eiRYvUpv3666/F58YdHR01nq+M\nLTo6GrNmzQJQcoPm22+/hUSi+vFcfWYdSU1NxYwZM8Tjv1OnTjo9znT69GlxWfFYq6wooCcGo4Ce\nEEKIORkzZoz4TCTnHP/73//Upp09ezbeeustcR7zjRs3omvXrmpbwhMSEhAQEICxY8eKNwKaNm2K\n0NBQjXVydHTEL7/8gurVq4MxhrS0NPTp0weTJk3C3bt31a536dIljB49Gu3bt0dsbKz2jTciV1dX\nfPzxx+J2zpw5E6tWrSozcviDBw8waNAgXLt2DZxzWFlZYcmSJeUut1+/fkqt9O+99x4OHDhQJt2R\nI0fEFkpLS8tyl2eOWrZsiaZNm4JzjoSEBI37CAAMGTIEQMn+vmzZMmzZsqVMmps3b6J3796IiYkx\nynRl6nz++edo06YNOOdITk5Gp06dsGPHDshkMpXpMzMzsXXrVvj4+GDKlCllPjenbTM3Tk5OYs8g\nzjmWLFmCkJAQpRsanHMEBwdj+fLlAEoC6jlz5micMs7HxweCIEAQBKWeOqoEBQXh6NGjKn/foqIi\nrF+/Hn379kV6ejoYY3jvvffw3nvvqc1v+PDh8Pf3x59//ql2lgLOOQ4dOoSuXbsiLi5OHORPvo2a\nyGQyMaC3tLTEm2++qXUdc0eRFzEYBfSEEELMiYWFBb788ksxGP31118RFxendkTnvXv3IigoSOxW\nHhkZiW7duqFx48Zo3749ateujczMTPzzzz9Kg0oBwGuvvYaDBw+WmX9elY4dO+Ls2bMYMmQIEhIS\nUFRUhLVr12Lt2rXw8PBAy5YtUatWLRQWFiI5ORl//fUXnjx5Iq7PGBNb416WFStW4MqVK7hw4QJk\nMhlmzJiBVatWoWfPnrC3t0d8fDwiIiKUBgZcvXo1OnToYFC5mzZtQpcuXfDkyRNkZmZi6NChaNWq\nFTp27AjGGKKjo3Ht2jUwxjB9+nTs2bPH6IOhDRo0CI8ePVL6m+JAb5cuXUL79u1V1t3Q7QcAf39/\n8WbU3r178fnnn6tN++GHH2LVqlW4desW8vPzMWbMGCxZsgRt27aFra0t4uLicOHCBXDO0ahRI0yZ\nMgVffPGFwXVUxcbGBgcOHED//v1x584dpKSkYNSoUZgyZQo6d+4MFxcXCIKAtLQ0xMXFIS4uTgwG\n3333XbPeNnM0e/ZsnDt3DuHh4ZDJZJg6dSqCg4PRuXNnAMCFCxfELv6MMfj5+Wncl+TpdO31cvDg\nQWzatAkODg7o2LEjGjVqBIlEguTkZJw5c0YcsJIxhrfeegvbtm3TmJ9MJsPPP/+Mn3/+GXZ2dvDy\n8kLjxo1hb2+PgoICPHr0CJcvX0ZKSopSfb/77jv07NlTa33//PNPZGRkgDGGgQMHaryxUWnI77rS\nyzxfeDFvvdlav54n24Jj/r8v5xXOpq4VIYQoMftzKVHLx8eHM8Y4Y4yPHTtW5/UKCgp4w4YNxXVH\njhypdZ2ff/6Zu7m5cUEQxJd8fflL/nd7e3u+cOFCnpubq/c2paWl8VmzZnE7Ozu15SiWJQgC79ix\nI//999/1Lqu0iIgIMf/evXvrtE5ubi4fNWqU2u9F/jcnJye+Y8cOo5UfGxvLmzdvrrHMiRMn8qKi\nIu7q6ir+PT4+XufvQxN5nvq8BEHgJ0+eNEr5d+/e5RKJhAuCwDt16qQ1/e3bt3mzZs00fl/t2rXj\nt27d4qGhoeLf1R1XuqTRJD09nfv7+3MLCwutx5MgCNzOzo4vX778pWxbVZOTk8MDAwO1fs9BQUE6\nnbMUz7vajlMXFxet5drY2PBFixbxoqIirWW/+eabGs/BpfebZs2a8T/++EPn7yowMFDM4+DBgzqv\np4kxrjEU8tA7XqSmVGIQzjm10JNyKSgoQFhYGMaPH1/lnn0khBiX/Byhz7nC0tISs2fPxuTJkwEA\ne/bswYIFCzRO6/T+++/j3XffRXh4OMLDw3HhwgU8fvwYz549g52dHZydndGmTRsMHDgQvr6+Oo2m\nrIqjoyOWLl2KmTNn4tChQzh27BiuXr2KlJQUpKamQiqVombNmmjRogW8vb0xbNgwtGnTplxlqaLv\n9ymVSrF161ZMmzYNW7ZswYkTJ5CUlITs7Gw4OTnB09MTgwcPxrhx4+Dg4GC08lu0aIFr165h/fr1\n2LVrF+Li4pCTk4O6deuiU6dOGD9+PPr27auUr7H/P9E3P2OW36RJE/j5+WHv3r24fPkyrl27pjT6\nfWlubm6Ijo7GDz/8IPZKyc/PR506deDp6Yn3338fI0eOhJWVFc6fP6/T71CeY0/OwcEB27Ztw7x5\n87B9+3ZERETg7t274ojkDg4OcHNzQ9u2bdGnTx8MGDBA7ZR0FbFtVYm1tTU2bdqE8ePHIzQ0FKdP\nn0ZSUhIAoH79+ujRowfGjBmj11Rxun6HR44cwbFjxxAREYE7d+7gyZMnyM3NhbOzM5o2bYohQ4Zg\nxIgRqFevnk7lhoeH4/z584iIiEBUVBT+/vtvPHz4EM+fP4eVlRUcHBzg6uqKjh07wtfXV6/pRp8/\nf47du3eDMQYPDw8MHjxY53XNGeP81Rg0orJijJU005vp71S8fh0SZ06E62f//q2RQyPET6uY+U1J\n1VBQUIARI0Zg3759+Pjjj7FmzZpX5j9dYhry/ctcz6WEEKJKVFQUXn/9dTDGMG7cOKxfv97UVSKk\n0goJCcHUqVPBGMPGjRsxduxYo+RrjGsMhTz0viCmgN7MmXtAL1u3FsLEj7GhAxAQmYei4iLIuAz2\n1V7uM36k8lAM5uUoqCcVjQJ6QkhlNWzYMOzfvx/VqlXDvXv34OLiYuoqEVLpyGQyuLu7Iz4+Hs2b\nN8eNGzfEWTwMZeqAnka5JwbhABgACWOoZlENtla2FMwTtVQF8wDwf//3f0hLSzNRrQghhBDztXTp\nUlhaWqKgoACLFy82dXUIqZQ2b96M+Ph4cTR8YwXz5qDqbAkxCc7l00lQyyrRTF0w7+HhgRMnTpT7\nWVRCCCGkKmvevDmmT58OANiwYQPu3btn4hoRUrnk5eVh/vz5YIxhwIAB4lSIVQV1uTdz5t7lvmDt\nGlh9/Cl+6iggMEr1/KKEaAvm69evb6KakVcFdbknhBBCSEWgLvekUpPvtoxa6IkaFMwTQgghhBBS\nMSigJwYRu9xTPE9UoGCeEEIIIYSQikMBPTHMiyZ6aqEnpXHOMXLkSArmCSGEEEIIqSAU0BODFCt0\nuidEEWMMAwcOVPobBfOEEEIIIYQYDwX0xEAlAT1NH05UGT9+PDZs2ACAgnlCCCGEEEKMzcLUFSCV\n27+jOVJET1QbP3487Ozs0KNHDwrmCSGEEEIIMSIK6IlBuLyFngJ6osH7779v6ioQQgghhBBS5VCX\ne2IQeQs9hfOEEEIIIYQQ8nJRQE8MwsGxpyUwZmA+pAulsFtsh9F7R5u6WoQQQgghhBBS5VGXe2IQ\nzjmKBKBYAPJl+ciX5aNAVmDqahFCCCGEEEJIlUct9MQgHCUBvSILge4TEUIIIYQQQkhFo4CeGETe\nQq+IAvqqr6CgACEhIZDJZKauCiGEEEIIIa8sCuiJQVS10FsKlqapDHkpCgoKMGLECEyZMgUBAQEU\n1BNCCCGEEGIiFNATg3CAWuhfIfJgft++fQCA7du3U1BPCCGEEEKIiVBATwzCeTEF9K+I0sG83MWL\nF5GammqiWhFCCCGEEPLqooCeGIZTC/2rQF0w7+HhgRMnTqB27domqhkhhBBCCCGvLgroiUGKQS30\nVZ22YL5+/fomqhkhhBBCCCGvNgroicEooK+6KJgnhBBCCCHEfFFATwxC09ZVXRTME0JI1ZWXl4fv\nvvsOPj4+qF27NiwtLSEIAgRBwPTp0yus3JMnT4rl9OnTx2j5urq6ivkmJCQYLV9zMWvWLAiCAKlU\ninv37pm6OoRUKnl5eWjQoAEEQcDgwYNNXR2jo4CeGIS63FdNnHP4+/tTME8IMTkfHx8xUFP1ql69\nOho2bIj+/ftj/vz5uHv3rkHlFRYW4uDBg/jkk0/QoUMH1K9fH1KpFLVr10arVq0wYsQIhIWFGWUw\n0NTUVGzbtg0BAQFo27Yt6tWrB6lUCgcHB7i6umLgwIGYP38+oqOjDS5LUUZGBl5//XV89tlnOHXq\nFFJTU1FcXAzGGBhjRi1LHWOXI6+7MfP9559/8MMPP+CDDz6Al5cXatSoASsrKzg5OaFNmzYICgrC\nsWPHjFaeOrdu3cK3334Lxhg+/vhjNGnSpMLLJJXTuXPn8NFHH6Fly5ZwcHCAg4MDWrZsiY8++gjn\nzp2r0LKfPn2KxYsXw8fHB3Xr1oVUKoWLiwtef/11g87NGRkZCAkJQe/evdGwYUNIpVI0bNgQvXv3\nxvfff4/MzEyteUilUixYsAAAcOTIERw4cKBcdTFbnHN6mfELJTPDcXP1cNUCXgzwn7vZ89zCXJ6V\nn8VzC3NNXS1iBDt37uQSiYTL90EPDw/+4MEDU1eLkHIx93MpUc/Hx4cLgqD1xRjjjDEuCAKfOnUq\nz8/P17usnTt3cjc3NzEveX6ly2CMcXt7e7548WKem6v//3lpaWl89uzZ3M7OTm1Zpctr3bo13717\nt95lqTJhwgSxPEtLSz5gwAD+0Ucf8cmTJ/PJkyfz3377zSjlqBIRESGW3bt3b6Pl6+rqKuYbHx9v\nUF7Hjx/nbdq0Ufr+Ne0Lr7/+Oo+LizPSlpTl6+vLGWPc2tqaJycnV1g5pPLKzs7mgYGBKvdXxb8F\nBQXxnJwco5e/Zs0abmtrq/FYsba25itXrtQr32PHjvEGDRpozLdhw4b8+PHjWvMqLCzkjRs35oIg\ncE9PTy6Tycq7uWUY4xpDIQ+940VqSiUG4ZyDAZBwAVILqamrQ4xoxIgRAAB/f380bdqUWuYJISbD\nOQdjDJ6enujbt6/SZ8+fP0dcXBwuXrwovxGO4OBgJCcnY+fOnTrlL5PJMGHCBGzevFmplbdRo0Zo\n3749nJ2dkZ6ejtu3b4ut5VlZWfjqq6+wb98+HDx4UOfZPm7cuIG33noL8fHxAP5tqXZzc0OrVq1Q\nu3ZtFBQU4PHjx4iOjkZKSoq43ogRIxAfH48vvvhCp7LUbeuOHTvE98ePH0f37t3LnV9VdOXKFcTE\nxIi/DWMMLVu2hKenJ5ycnJCamopz587h4cOHAIBLly6hS5cuOHHiBNq2bWvUukRGRuL3338HYwwB\nAQGoU6eOUfMnlV9xcTGGDx+Ow4cPi/ts06ZN0blzZwDAhQsXxNbxjRs34unTp/jtt9+MVv7cuXOx\nePFi8dwplUrRo0cPuLq6IisrC2fPnkViYiLy8vIwY8YMZGZmiq3lmpw6dQpvvfUWCgsLwRiDpaUl\n+vTpgwYNGiAxMRHHjx9HUVERHjx4gMGDB+PPP/9Ely5d1OZnYWGBzz//HFOnTsXff/+NsLAwjB07\n1mjfg0mV5y4AvaiFXu7Byv9yDvBfujqauiqkguzfv59a5kmlZ+7nUqKej4+P2DIzduxYtelu3brF\nO3TooNSSs3fvXp3KGDp0qFLrT5cuXfj58+dVpk1ISOABAQFKrUQeHh782bNnWsuJioriDg4O4nqW\nlpZ84sSJ/M6dO2rXuXjxIh89ejS3sLDggiDwBQsW6LRN6sTGxorb2qxZM4PyKo/K0EK/cuVKLggC\n9/Ly4t9//z1PSUkpk6a4uJhv2LCB29raivuCu7t7uXqGaOLn5ydu1/Xr142aN6kaFi1aJO4jFhYW\nPDg4uEya7777jkskEnFfXbFihVHKPnTokNK5c9CgQSp7kaxZs4ZbWVmJ6Q4fPqwx34yMDF67dm0x\nfYcOHXhCQoJSmvj4eN6+fXuxfBcXF/78+XON+WZmZnI7OzsuCAJv3ry5/hushjGuMWBAC73JA1Z6\nVe6APnHlvJKAvlsNU1eFEELUMvdzKVFP14Cec84fPXrEq1evLl4Evvnmm1rzX7ZsmdIFaVBQkE71\nCg0NVer+6evrqzF9eno6b9KkiRjM16hRg586dUqnsjjnPCYmhrdp08bggP7s2bPi9vbq1cugvMqj\nMgT0+/fv1/mxg19//VVp/9mwYYNBZSu6c+eOGIR17tzZaPmSquPZs2fiTUJBEPhXX32lNu3s2bPF\nG541a9bkaWlpBpffrl07sez27dvzwsJCtWmDg4PFY6V169a8uLhYbdo5c+aIdXVycuJPnjxRme7R\no0e8Zs2aYh3mz5+vtc7yRxMEQeAHDx7UvpE6MHVAT4PiEYOU7H8Aw8sZRIcQQghRx8XFBe+99554\nkXPmzBmN6e/evYu5c+eK3VQHDhyI9evX61RWQEAAFi1aJJZ18OBBbN++XW36mTNn4v79++CcQyKR\n4MCBA+jRo4fO29aqVStERkaif//+Oq+jSkFBgbgsCHQZqIqvry+GDRumU9q3334bnTp1Eq+HDh06\nZLR6bNq0CcXFxQD+fQyOEEVhYWHIzMwE5xyOjo6YO3eu2rTz5s2Dg4MDACA9PR3btm0zqOy///4b\nV69eFff9BQsWwMJC/dPcn3zyCRo2bAjOOWJjY9UOKCmTybBu3TqxC/+MGTPUPtLk4uKCzz//XDwP\n//jjj2J91FE8ljZt2qRtMysFOpMTg3DIA3pCCCHE9Nq1aycu5+bmIj09XW3aVatWoaioCJxzWFtb\nY+3atXqVNWPGDHh5eYnvV6xYoTJdcnIytmzZIl6gTp48uVzPrVtbW2t8RlSd+Pj4MlPFcc4RERFR\nZtYATVPJRUVFYdq0afDy8oKTkxOkUikaNGiAvn37YtWqVcjIyNC7btoUFBQgJCQEPXv2hLOzM2xs\nbODu7g5/f39EREQYvbzyUPwtjTmlnOINIl1vMKSkpCAsLAyBgYF47bXX4OTkBCsrKzg6OqJ58+YY\nPXp0mRls1AkLCxP3i8DAQAAl+80vv/yCt99+G+7u7rC1tYUgCNiyZYvafE6dOoVPP/0UXl5eqFWr\nFqpVq4Z69eqhT58+WLlypU6jlBt726oK+fYyxjB8+HBIperHs7K2tsbw4cPF94Y+R3/hwgVxWSKR\naL3ZKAgC3njjDfH9nj17VKaTz7whD8wDAgI05jtmzBhxOSUlBadPn9aYvm/fvnBwcADnHIcPH9b4\nf0SlUZ5mfXpRl3u5+yu+4hzgv3ZzMnVVCCFELXM/lxL19Olyzzn/f/buO6yp6/8D+PuEvXGhiANF\nqhX3wq0MrbYq9Ks/0eLCgaN11NZqrbWu1lGrVTusVkWrdVQfrVVxgy2uVkXFgbYORFwICMgKSc7v\njzS3CWQnEIif1/Pk6Y2cdZN70/u559xz+Pr161Weo3/8+LHadIWFhSrPP+tTtjobN25UqS8hIaFU\nmkWLFglpbG1tTR4Sbqj79++rnfVa3WoB6obB5+fn88jISJ0zvlerVo1v27ZNa1sMGXJ/48YN3rhx\nY611Tpo0iRcXF5t1yL2hPvjgA6Hu5s2bm6XMq1evCmU2bNhQrzxr1qzhtra2Wr9fxd/atWtX6pnk\nkmJiYlTOvUePHvHu3burLX/z5s2l8qelpfHQ0FC9jpt9+/aV675Zg6KiImFuDZFIxHfs2KEzz88/\n/yx8Tvb29lqHyOuybNkyoSxvb2+98ixcuFDI06BBA7Vp5syZI3zHTZo00avc1157Tcjz2Wef6Uzf\nv39/Ib0+n5su5rjGgAlD7mmWe2IS/u/ds3JatpYQQgjRSjHzOCDvNapWrZradOfOnUN+fj4Aee9W\nZGSkUfVFRERgwoQJkEgkAIC4uDh06dJFJc3JkyeFejp37ox69eoZVZex3N3d8d577wEA0tLSsHfv\nXjDGULt27VI9v/7+/irvCwsLERISgnPnzgmPJtSsWRPdu3eHh4cH7t+/j1OnTqG4uBiZmZkYPnw4\nXrx4gUmTJpnU5gcPHiAkJARPnz4F8N9M823btgVjTJiJfu3atXBycjKpLlNdvXpV2K5bt65ZylQe\njqzvoxlpaWmQyWRgjMHX1xevv/46vLy84OTkhNzcXNy4cQOXL18G5xwXL15E9+7dcfnyZWEYtjaF\nhYUYMGAALl68CFtbW3Tq1An+/v4oLi7GlStXSqW/desWQkNDkZaWJhw3LVu2RLNmzeDi4oKnT5/i\njz/+QGZmJjIzMzFw4ED8/PPPKj3I5bVvlVVycjKkUikA+fnRpk0bnXmU00gkEty6dQsBAQFl1kZt\nHjx4gPz8fDg7O6v8+/Xr14VtffZJke7vv/8ulV+Tbt264cCBAwCAI0eOVPpHWiigJyb5N56nZ+gr\nEbFYjNWrV2PKlCmwt7e3dHMIIcSsDh8+LGy3adMGdnZ2atMpP1/PGENgYKBR9Tk7O6NZs2ZITEwE\nY6zUc/sSiUQlGDZmyLypqlSpgtWrVwMATp06hb17g0viywAAIABJREFU9wKQB++Kf9fkww8/FNov\nEomwZMkSTJ8+XdgfQB5sDR8+HPHx8eCcY/r06QgMDETbtm2NbvPo0aPx5MkTAPIbElu3bkW/fv1U\n0hw5cgSRkZFYsWKFxu+5rN2/fx8nT54UPg/lIcWmOH/+vLCt/FiHNo0bN8bq1asRHh6ucZnZe/fu\nYdKkSThy5AgePHiAWbNm4fvvv9dZ9u7duyGVStG9e3ds3rwZ9evXV/m78twMBQUFGDhwIB49egTG\nGHr16oU1a9aUullUVFSExYsXY9GiReCcY9y4cejYsaPaG15luW+6ZGVlYe7cuSaXo6xatWqYN2+e\nSWXcunVL5b0+NwoVaRTHa3JystEBvfJz7c+fP0dhYaHWIf8AhOU6AXmn4K1bt9C6dWuVNMr7VfI4\n00R535OTk3WmV340S/lcq7SM6danFw25V7izdBbnAN/brYalm0L0UFRUxMPDwzkAHh4ebvbldQip\nqCr6bynRzJAh94ohwor0mzZt0ph27NixQlpfX1+T2jhy5EihrJJLIaWlpakMEd6yZYtJdZnKkCHv\nd+/eVVnqauXKlRrT5uXl8RYtWghlh4aGGl3/0aNHVb7HY8eOaaz3jz/+UBlyXd5D7gcMGCC01dPT\nk2dmZpql3CZNmgj7c/DgQbOUqVBcXCx8Vy4uLvzFixdq0ykPuWeM8ebNm/OCggKd5SseMVGs/qBt\nNnPOOf/000+F9O+++65R+6Sg774ZQvHIijlfmoabG+L7779XOfb05e7uLnze69atM7p+5cdCRCIR\n//XXX7Wml0qlvF69eirnqrpzu2bNmsLfv/76a73asmLFCuGzqF27ts70qampQnobGxuTr4fNcY0B\nmuWeWArnNCleZSEWixERESFMoLJv3z5ERESo3FUnhJDKJj8/HxcuXMCkSZOEibsYYxg6dKjKZEkl\nZWZmCmmrVq1qUhuqVKkibGdkZKj8TfFe8f9LT09Pk+oqT+vWrRNmWX/99dcxbdo0jWmdnZ2F3n7O\nOU6ePCkMgTWUYuZpxhjCwsIQGhqqMW3Xrl3xzjvvCJ9veVq/fj1+++03APK2zp07V+VYMIVyT2ad\nOnXMUqaCra0thg0bBkDem3769Gmt6TnnYIxh2bJlOntgJRIJvvnmG6EexWzl2syePVuYpGz79u0G\n7Elphu6bvhQTWprzZaqXL18K24Y8dqKcVrkMQzVv3hwNGzYUzr158+YJjx6p88033yA1NVXl33Jz\nc0ule/nypfD56Ltfhu6Tt7e3sMoH51zlfKuMaMg9MYnif5805L5iKxnMK1y/fh1ZWVmoWbOmhVpG\niBWwhklELBAMGSMmJgYxMTEa/84Yg7u7OyZPnowFCxZoLUv5QtLV1dWkdinnLzljd8kLVlPrKk+K\nZ/8B3TNNA0CPHj3QqFEj/PPPPwDk8wmUHGatj7i4OGF7+PDhOtOPHDlS65KBZeHMmTOYPHmyEHiE\nhobi/fffN0vZ2dnZKCwsFN5rmgdCm4yMDJw/fx43btxAZmYm8vLyhJszgOqw5MTERLz55ptay/P0\n9MQbb7yhs94LFy7g6dOnYIyhR48eqFWrls48jo6O6Ny5M2JjY/HixQtcu3YNzZo1K7d906V+/frC\ns+oVifIxYsgjlA4ODsJ2QUGBSW345JNPMGbMGHDOceXKFfTv3x+bNm1S+d45ly8n9+GHH5a6kaGu\nfmP2y9B9srGxgYeHB7KysgDIVyIx5reqoqCAnpiEQ4Z+7wCxjZ7BbpEjbEW22D14N/o06mPpppF/\naQrm/f39ERcXR8E8IaTS0NSrpdw7+8knn2DGjBk6y3JzcxO2TemlKpnf3d1dYz3mqKs8Xb58Wdju\n3LmzXnm6dOkiBPSXLl0yuM5Hjx4hPT1deN+xY0edeQIDA8EYK7de+uTkZISHh6O4uBicczRq1Mjk\nNb2V5eXlqbwvOWmYNv/88w8++ugjHDx4EMXFxXrlef78uda/M8bQqlUrvXqVz549K2w/efIEkydP\n1qsNd+7cEbZTU1PVBvRlsW+VmfJoCUNGWxYVFQnbpk4oGRUVhWPHjmHnzp3gnOPIkSNo2LAhunfv\njvr16+Ply5dISEhAamoqGGP43//+hz179gj5S/4+AvL9UgTl+u6XMfvk7OwsBPQlz7nKhgJ6YhoO\nSESATAQUSYtQJC3SnYeUG13BvKaJZQghBqgkvdvWoEmTJggJCRHeFxYWIjU1FWfPnkVubi4455g5\ncyaSk5OFYduaKIbZc86F4ffGUlwUAqV7UxXvFcFQZVnzODs7WyVo0ndyqgYNGgjbxgRTysG8jY0N\nvL29deZxc3ODh4dHuXy2KSkp6NWrFzIyMsA5R506dXD8+HGVCcLMTd8bFSdOnMCAAQNQUFCg17Bu\nRbnqhj2X5OXlpVcblFeZuHbtGq5du6ZXPmXK55NCWe5bZaU82seQnnbltOYYMbR161bUqlULa9as\ngUwmQ1FREY4ePSr8XfF9DR8+HEuWLFEJ6NU9guTq6or8/HwwxvTeL2P2yRKP6ZQVeoaemETGOSQl\njiJbEd0nqggomCeEWJvAwECsXr1aeK1btw6xsbFITU0VhjszxhATE4MVK1ZoLcvX11fYTk1NNenC\nPykpSahbuVwAwtJaCvosqVQRlBxJ4OLiolc+5XTGfKbGPhesb/tM8ejRI4SEhODRo0fgnMPLywsn\nTpww+zKEJfdFn6AmMzMTgwcPRmFhoXAcLl68GAkJCUhLS0NeXh6kUqnw2rhxo5BXebi6Jvp+F9nZ\n2cK2sc+Vl3wOu6z3rbJSvnmYk5OjV292QUEBcnNzhc/a1PlDAEAkEmHFihW4du0apk2bhpYtW6JK\nlSpwcHBA/fr1ERERgWPHjiEmJqbUb4K6ZR6V90uxbKUuihUxDJkTRfm8Ko/fj7JEkRcxEQX0FREF\n84SQV4mbmxuWL1+OnJwc/PjjjwDkQ+/DwsLg5+enNk/Xrl2Fbc45zp8/r3XyNU3y8/Nx7do14QJZ\nuVxAPklXYGAg4uPjwRjDuXPnDK7DEkr2cuXl5ek14Zvy0FV1w2kNqdeQXseyHjKbnp6O0NBQ3Lt3\nD5xzVKtWDSdOnCiT5249PDzg6OgoPEv8/Plznf/f/uGHH5CVlSUMj//999+1Bikl53owF+XvLzo6\n2izLxll63yrqsnWNGzdWeZ+SkqLzeHzw4AGA/yY6bNKkiUltKNmer776Smsa5Rua1apVK3UDVFHO\nzZs3AUDvyeoU+wVAr32SSCQqI3r0GQlUkVHkRUzCKaCvkEaMGEHBPCHklbNy5UrExsYiLS0NYrEY\ns2fPxs6dO9WmDQwMhLOzsxA0btu2zaiAfseOHcLQdMYYgoKCSqUJDg4W1mg/ffo0UlNT1fZMVSQe\nHh6wt7cXev1SUlL0mm39/v37wnb16tUNrld56LpUKsXjx491Xmzn5uaq9AybW1ZWFkJDQ3Hr1i1w\nzuHh4YGjR48avX63Pho0aCAENQ8fPkTLli21pleewHDOnDk6exzLalZv5Xl5FL2mprL0vuXk5ODb\nb781a5m+vr4mB/RNmjSBjY2NMAohMTFRZ0CvPK+FjY1NqZsCZe3MmTMA5L+VnTp1UpsmICBAuIZN\nTEzUq1zl/dLnvHz8+LEw5F4kEpl9lE15oyH3xCSchtxXSMOGDVOZGZSCeULIq8DFxUW4SOacY/fu\n3bhy5YratI6Ojhg5cqSwju8vv/xSakklXaRSqbBUGwA0a9YMXbp0KZVuzJgxsLe3B2MMMpkMK1eu\nNKgeS2nVqpWwrbgQ10V5mbC2bdsaXGft2rVVgnrlSdY0OX/+fJk9D5uTk4NevXohKSkJnHO4ubnh\n8OHDaN26dZnUp9CiRQthWxHYa6P87Lq2GeIVTp06ZVzDdAgMDAQgP//0+e70URH2rSIuW2dvb4/O\nnTsLx358fLzOPIrPhjGGrl27wta2/K7ZFb+zCppWzggODhbS37p1S+ew+8ePH6sskanIr43inGKM\noXHjxgatElARUUBPTEIBfcXUr18/7NmzB/b29hTME0JeKaNGjVIZxqlt+brp06fD1tZWmHxpwoQJ\nBtW1dOlSXL16FYD8wvCjjz5Sm87b21vl5sGaNWuMWh87Pz/fbEGSPpQvjDdv3qwz/e+//65yYa1u\ntII+lPP99NNPOtNv2rTJqHp0ycvLwxtvvCH0/jk7O+PgwYNC0FqWlOvQdFNKmXKAqOvxg/Pnz+Pi\nxYtmCSpL6ty5s/BoRnp6Onbv3m1ymZbeN8WydeZ8Kc/qb4rw8HAA8uvxnTt3qsz2XlJhYSF27dol\nvB84cKBZ2qCvH3/8URg9UatWLYSFhalN1717d1StWlX4DnX99igvZVq9enV069ZNZ1uUz6nyOJ/L\nGgX0xCQ05L7i6tevHw4cOEDBPCHklWJjY4PZs2cDkF/k/vrrrxpn2vbz88OCBQuEQPvw4cOIjo7W\nq7d38+bNmDt3rtDb9uabbyIyMlJj+qVLlwo3GqRSKQYMGICEhAS99yspKQmBgYE4duyY3nlMFR0d\nDZFI/j/5mzdvah1ZUFhYiClTpqisy96oUSOj6h07diwA+fe3f/9+rfv8xx9/YMeOHWYPTgsLC/HW\nW2/h/PnzAOQjOvbv319qjoSy0rt3b2Fbn+NEea6Iko/cKcvLy8O4ceMAlM0s3/b29pg2bZrwfsqU\nKSrPN+uirje2ouxbRTRixAhhqcwXL17g888/15h2wYIFwnPjnp6eWn+vzC0xMREzZ84EIL9B8/XX\nX8PGxkZtWhsbG4wfP174XV6+fLnK6hfKnjx5gq+++kr4HZ40aZJevwV//PGHsK18rlVaig+LXhXz\nBYDLv6aKKWnRFB4wCRzz/nslPU2ydLMIIURFRf8tJZr17NmTM8a4SCTiUVFReuUpLi7m9evXF/IN\nHjxYa/r+/ftzkUjEGWOcMcY7duzIz5w5ozZtSkoKHzFihFA2Y4w3atSIP3/+XGe7Lly4wN3d3YV8\ndnZ2fOLEifzOnTsa8/z555982LBh3MbGhotEIj5//nyd9WgTHx8vtD0oKEhn+vfee0/4XGxtbfny\n5cu5VCpVSZOamsqDgoKEdA4ODvzixYsm1R8cHCyk8/Dw4L/++mupNLGxsbxq1apcJBJxBwcHIX1K\nSorO/dJGLBbzN954Q9gfR0dHfujQIZPKNIafn5+wT9qOEc45X79+vUp7N2/eXCrNjRs3ePv27Tlj\njLu5uek8r2JiYgw+9zjnPC8vj7do0UJoj5eXF9+2bRuXSCRq02dnZ/MtW7bwHj16qD1Xy2LfrMnn\nn3+uco6uXr2ay2Qy4e8ymYyvWrWK29jYCJ/L8uXLtZbZo0cPoUxdvxNjx47lhw8fVvv9FhcX8x9+\n+IFXqVJFqDsiIkLnPmVnZ/MaNWoIedq2bVvqvL5//z5v3bq18Hvq7e3NX758qbNsiUTCPT09hd+q\nrKwsnXl0Mcc1hlIZBseL1JVKTMI59dATQgipWGxtbfHxxx9j4sSJ4Jxjz549SE5O1jj78d69ezFu\n3DhhaOf58+fRpUsX1K9fH61bt0aNGjWQk5ODv//+W2XyJQBo164dDhw4UGr9eXXatm2L06dPo3//\n/njw4AEkEgnWrl2LtWvXwt/fH02bNkX16tVRXFyMJ0+e4PLly3j27JmQnzEm9MaVly+//BKXLl3C\nuXPnIJVKMWPGDHz11Vfo3r073N3dkZKSgvj4eJWJAVeuXIk2bdqYVO+GDRvQqVMnPHv2DDk5OQgP\nD0dAQADatm0LxhgSExNx9epVMMYwffp07N6922yToc2ZMwdHjx4VevoaN26MQ4cO4dChQ3rlX7Nm\njVnaERkZiYULFwKQH6MffPCBxrQjRozAV199hVu3bqGoqAijRo3C4sWL0bJlS7i4uCA5ORnnzp0D\n5xz16tXDlClT8OGHH5qlnSU5Oztj//796NWrF+7cuYP09HQMGzYMU6ZMQceOHVGrVi2IRCJkZWUh\nOTkZycnJkEqlAIBBgwZV6H2riGbNmoUzZ84gNjYWUqkUU6dOxerVq9GxY0cAwLlz54Qh/owxhIWF\naT2WFOn0HfVy4MABbNiwAR4eHmjbti3q1asHGxsbPHnyBAkJCcKElYwx9OvXD1u3btVZpru7O3bv\n3o3evXujuLgYly5dgr+/P0JCQuDj44OHDx/i5MmTwu+Oo6Mj9uzZo9fycydOnEB2djYYY+jbty88\nPT312s8KzZi7APSiHnqFKwvf435TVHvo/87429LNIoQQFRX9t5RopuihZ4wZ1NsmFot53bp1hbxD\nhw7VmWf79u3cz8+Pi0Qi4aXIr3gp/t3d3Z0vWrSIFxQUGLxPWVlZfObMmdzV1VVjPcp1KXqofvvt\nN4PrKknRQ65Pz5tCQUEBHzZsmMbPRfFv1apV4z///LPZ6r9x4wZv3Lix1jonTJjAJRIJ9/X1NVsP\n/ahRo9R+H/q8RCKRSXUru3v3rjAyo3379jrT//PPP/y1117T+nm1atWK37p1S6/ed2N76BVevHjB\nIyMjua2trc7zSSQScVdXV75s2bJy2Tdrk5+fz0ePHq3zcx43bpxev1nKv7u6ztNatWrprNfZ2Zl/\n/vnnGkdpaHLixAlep04drd97vXr1eHx8vN5ljh49Wsh/4MABg9qjiTmuMUA99MRSOPXQE0IIKWOK\nniJDnpO2s7PDrFmzMHnyZADA7t27MX/+fK3LOg0ZMgSDBg1CbGwsYmNjce7cOTx9+hQZGRlwdXWF\nl5cXmjdvjr59+2LAgAGoWrWqUfvj6emJJUuW4KOPPsLBgwdx7NgxXLlyBenp6cjMzISjoyOqVq2K\n119/HYGBgXj77bfRvHlzo+pSx9DP09HRET/99BOmTZuGLVu2IC4uDmlpacjLy0O1atXQpEkTvPXW\nWxgzZgw8PDzMVv/rr7+Oq1evYt26ddi5cyeSk5ORn58Pb29vtG/fHmPHjkVISIhKueZ6lt7Ycsz5\nLH+DBg0QFhaGvXv34uLFi7h69arK7Pcl+fn5ITExEd99950wKqWoqAg1a9ZEkyZNMGTIEAwdOhT2\n9vY4e/asXt+DMeeegoeHB7Zu3Yq5c+di27ZtiI+Px927d5GRkSH83c/PDy1btkRwcDD69OmjsYe1\nLPbNmjg5OWHDhg0YO3YsYmJi8McffyAtLQ0A4OPjg27dumHUqFEal4pTR9/P8PDhwzh27Bji4+Nx\n584dPHv2DAUFBfDy8kLDhg3Rv39/REREoHbt2gbvV3BwMK5fv44tW7Zg9+7d+Oeff5CRkYFq1arB\n398fgwYNwogRI+Dm5qZXeS9fvsSuXbvAGIO/vz/eeustg9tUETH5DQFSUTHG5N30FfR7urzwPbT4\n7FvEBtVF8OFbkMgkcLF3gYjRfIuEkIpDcUFSUX9LCSFEnQsXLqBDhw5gjGHMmDFYt26dpZtESKW1\nZs0aTJ06FYwx/Pjjj4iKijJLuea4xlAqw+C7UBR1EZNwLoOIA3acwcnOCW4ObhTMlyGxWIxFixYh\nPz/f0k0hhBBCSBlr164dwsLCwDnHTz/9hCdPnli6SYRUSlKpFCtWrAAAvPbaaxg5cqSFW2Q+FHkR\ns3hVhjRZklgsRkREBD799FOEhYVRUE8IIYS8ApYsWQI7OzuIxWJ88cUXlm4OIZXSpk2bkJKSAsYY\nli1bJizJaQ2sZ0+IRci4zNJNeCUognnF+qvHjx+noJ4QQgh5BTRu3BjTp08HAKxfvx737t2zcIsI\nqVwKCwsxb948MMbQp08f9O/f39JNMisK6IlZMFAPfVkpGcwrpKSkCEuBEEIIIcR6LV68GFKpFAUF\nBWjQoIGlm0NIpeLo6IiHDx9CKpXi4MGDlm6O2VFAT0zCoZj8gQL6sqApmPf390dcXBy8vb0t1DJC\nCCGEEEKIpVFAT0yimM2RHqE3P13BvI+Pj4VaRgghhBBCCKkIKKAnJhECeuqhNysK5gkhhBBCCCG6\nUEBPTCKjIfdmR8E8IYQQQgghRB8U0BMT0ZB7cxs9ejQF84QQQgghhBCdKKAnJlEMuaceevMZO3Ys\nnJ2dhfcUzBNCCCGEEELUoYCemET276B7CufNp2fPnjh48CCcnZ0pmCeEEEIIIYRoxP7rYSUVEWOM\nA8o94RXLgU+HoL/tTtjIADt7R9R0qYn70+5bullWISEhAQ0aNKBgnhAzYP8+F1RRf0sJIYQQUjmZ\n4xpDqQyD+0ltja6VEAASSAEAUhEglRSiSFpk4RZZj65du1q6CYQQQgghhJAKjIbcE5NIuEzlva2I\n7hERQgghhBBCSHmggJ6YRAoK6AkhhBBCCCHEEiigJyapX8VX5T0F9IQQQgghhBBSPiigJybxcKqi\n8p4CekIIIYQQQggpHxTQE5MoJsVToIBeM7FYjE8//RQ5OTmWbgohhBBCCCHEClBAT0wioWfo9SIW\nixEREYFFixahb9++FNQTQgghhBBCTEYBPTEJzXKvmyKY37dvHwDgzJkzFNQTQgghhBBCTEYBPTEJ\nDbnXrmQwr5Ceno6XL19aqFWEEEIIIYQQa0ABPTEJ9dBrpimY9/f3R1xcHGrXrm2hlhFCCCGEEEKs\nAQX0xCTUQ6+ermDex8fHQi0jhBBCCCGEWAsK6IlJghyaQDofKHoYhbzZeTj4zkFLN8niKJgnhBBi\nqKioKIhEIohEImzZssXSzSGEEFJJUEBPTCbigD1s4GznDGc7Z0s3x6IomCeEEPPr2bOnEOyOHj3a\n0s0pU4wxSzeBEEJIJULjowkxo3HjxlEwTwghZsYYo0CXEEIIUYN66Akxo3fffRfu7u7CewrmCSHE\nPDjnlm4CIYQQUuFQQE+IGXXo0AHHjh2Du7s7BfOEEEIIIYSQMkVD7gkxsw4dOuDEiRPw9vamYJ4Q\nQgghhBBSZiigJ6QMtGvXztJNIIQQQgghhFg5GnJPCCGEEKs3f/58Yab8BQsW6EyfkpIipG/YsKFe\ndWRkZGDlypV488034evrC1dXVzg6OqJOnTro1asXFi5ciJs3b5q6Kzhz5gyqVq0qtG/w4MEoLi42\nuVxCCCGVD/XQE0IIIeSVYehs+fqmX7x4MRYvXoyXL1+Wyvf48WM8evQIJ06cwGeffYbDhw+jd+/e\nBrVD4cCBA4iIiEBhYSEYY5gwYQK+/fZbo8oihBBS+VFATwghhBBiJJlMhoiICOzZs0dYXs/W1haB\ngYHw8/ODg4MDnj17hsTERDx48AAAUFhYaFRdMTExiI6OhkQiAWMMn332GebOnWvO3SGEEFLJUEBP\nCCGEEGKkOXPmCME8AIwdOxaLFi1CjRo1SqW9fv061q9fD2dnZ4PrWbp0KT7++GMAgI2NDdasWYMJ\nEyaY1nhCCCGVHj1DT0zyqqwLLBaLMXPmTGRkZFi6KYQQQiqIf/75B8uWLROC+Tlz5uCHH35QG8wD\nQEBAAL7++muEhoYaVM/7778vBPMODg7Yvn07BfOEEEIAUEBPTPSlexJEnwH2dWPg/Lkz5pycY+km\nmZ1YLEZERASWLVuGkJAQCuoJIaUohlrr+6po5RPjrFixAjKZDADQsmVLzJs3z6zlSyQSREZGYtWq\nVQAANzc3HDp0CIMGDTJrPYQQQiovCuiJSSQ+3uAMKOYSFEgKIJVJLd0ks1IE8/v27QMAXLlyhYJ6\nQgghAIDDhw8L2++9955Zb6bk5+ejX79+2L59OwDAy8sL8fHxCAoKMlsdhBBCKj96hp6YRCKTqLy3\nFVnPIVUymFfIz89HUVGRhVpFCCGkInj27Bnu378vvDdnoJ2eno6goCD89ddfYIzB19cXR48ehZ+f\nn9nqIIQQYh2sJ/oiFmGtAb2mYN7f3x9xcXGoXbu2hVpGCCGkInj69KmwzRhDgwYNzFb2xx9/LMxk\n//rrr+PEiROoWbOm2conhBBiPWjIPTGJNQb0uoJ5Hx8fC7WMEFJRcc4NelW08onhcnNzhW1jZq3X\nxsHBAYwxcM7x7NkzlZsHhBBCiDIK6IlJrC2gp2CeEEIIAGGyO03c3d2F7fz8fLPW/cUXXyAwMBAA\n8Pz5c4SGhuLKlStmrYMQQoh1oICemMSaAnoK5gkhxHrZ2dkJ2xKJREtKuezsbK1/Vx4CzzlXeZ7e\nVB4eHjh69Cg6duwI4L+g/vLly2argxBCiHWggJ6YxJoC+kmTJlEwTwghVsrNzU3Y1melkqSkJK1/\nr1Gjhspz8ydPnjS+cWq4urriyJEj6Ny5MwB5m3v16kVBPSGEEBUU0BOTWFNAP23aNFSvXl14T8E8\nIYRYD+XgOzExUWf6HTt2AIDWOQnefPNNYfvbb781oXXqubm54fDhw+jatSsAeVAfGhqqV/sJIYS8\nGiigJyaxpoC+WbNmiIuLQ/Xq1SmYJ4QQK9OhQwdhork///wTN2/e1Jh2//79iI2N1bmu/Pvvvw8b\nGxtwznH58mV89tln5m42XF1dERsbi27dugEAMjMz0atXL1y6dMnsdRFCCKl8KKAnJrGmgB6QB/Xx\n8fEUzBNCiJXx8vJCSEgIAHmv+5AhQ5CamqqShnOOjRs3YsiQIXB0dNS5YkDDhg0xa9YsIe/ChQsx\nbtw4pKenq01/7do1TJ06FcePHzeo7S4uLjh06BC6d+8O4L+g/uLFiwaVQwghxPpU7uiLWJy1BfQA\nEBAQYOkmEEII0eDXX39F69at9U4/ceJEREdHA5DPHh8XFwepVIqkpCQ0btwYQUFBqFu3Ll68eIHT\np08jLS0NdnZ2WLt2LcaMGaOzl37+/Pm4ffs2du/eDc45NmzYgC1btiAwMBB+fn6wt7dHeno6Ll26\nhAcPHoAxJtxYMIQiqH/rrbdw6tQpZGVloXfv3jh27BjatGljcHmEEEKsQ+WPvohFbXl7C2LCYyCR\nSSCRSWAnstOdiRBCCDEC5xxZWVnIysrSKz1jDE+ePBHet2vXDps2bcKYMWMgkUhQVFSE2NhYlfSe\nnp6IiYlBy5YthTq1EYlE2LlzJxYtWoQlS5Y5a9x0AAAgAElEQVSgoKAAEokECQkJSEhIUClb8TJ2\n3XpnZ2ccPHgQ/fr1Q3x8PLKyshAaGoqjR4+iXbt2RpVJCCGkcqMh98RkIiaCvY09nO2cYWdDAT0h\nhBDzUw6I9X2pM2zYMFy7dg3R0dHw8/ODs7MzPDw80KJFC3zyySdISkrCgAEDStWpy5w5c3Dnzh18\n8cUXCAoKgo+PDxwcHODk5IS6deuiV69e+Pzzz3H79m2EhoZq3UdtFEF9cHAwGGPIzs5G7969ceHC\nBZ1tJIQQYn2YrjvPxLIYYxzQ3UNACCFEM0WQRL+lhBBCCDEnc1xjKJWh+w5yCdRDTwghhBBCCCGE\nVEIU0BOrJxaLMW3aNDx+/NjSTSGEEEIIIYQQs6GAnlg1sViMwYMHY9WqVejZsycF9YQQQgghhBCr\nQQE9sVqKYP7XX38FANy+fZuCekIIIYQQQojVoICeWKWSwbwC5xwymcxCrSKEEEIIIYQQ86GAnlgd\nTcG8v78/4uLi4OPjY6GWEUIIIYQQQoj5UEBPrAoF84QQQgghhJBXBQX0xGpQME8IIYQQQgh5lVBA\nT0zCObd0EwBQME8IIYQQQgh59dhaugGkcmv6XVPczrgNW5EtbEW2uBh9EU2qNyn3dkyZMoWCeUII\nIYQQQsgrhXroiUkkMglkXAaxVIz84nyImGUOqQ8++EAlcKdgnhBCCCGEEGLtKKAnJpHIJCrvbUWW\nGfShHMBTME8IIYQQQgh5FdCQe2KSihLQA/KgPj4+Hk5OThTME0IIIYQQQqweBfTEJBUpoAeARo0a\nWbR+QgghhBBCCCkvNOSemKSiBfSEEEIIIYQQ8qqggJ6YhAJ6QgghhBBCCLEMCuiJSSigJ4QQQggh\nhBDLoICemIQCekIIIYQQQgixDAroiUnKOqAXi8V49913cf/+fbOWSwghhBBCCCGVHQX0xGic8zIN\n6MViMSIiIvDdd9+hZ8+eFNQTQgghhBBCiBIK6InRZFym8p6BQcTMc0gpgvl9+/YBAFJSUiioJ4QQ\nQgghhBAl9MAzMZqNyAayuTLIuAwSmaRUb72xSgbzCvb29rCzszNLHYQQQgghhBBS2THOuaXbQLRg\njHFAPrz9VaApmPf390dcXBx8fHws1DJCSGXGGAPw6vyWEkIIIaR8mOMaQ6kMZmheGnJPKgwK5gkh\nhBBCgO+//x4ikQg2NjZISEiwdHMIqXTatm0LkUiEli1bQiaT6c5QiVFATyoECuYJIYSo07NnT4hE\nIpXXL7/8YlAZX331VakyRo8eXUYtfjWo+16UX25ubqhbty569eqFefPm4e7duybVV1xcjAMHDuDd\nd99FmzZt4OPjA0dHR9SoUQMBAQGIiIjA5s2bkZmZafK+ZWZmYuvWrRg5ciRatmyJ2rVrw9HRER4e\nHvD19UXfvn0xb948JCYmmlyXOhkZGfj000/BGMOAAQPQtWvXMqmHVH5JSUmYPn06WrRogWrVqsHV\n1RWNGzfG8OHDcfjw4TKt++XLl1i1ahX69u2LOnXqwNHREdWrV0erVq0wY8YMJCUlGVSeTCZDUlIS\nNm7ciEmTJqF9+/ZwcHAQflOCg4MNKm/p0qUAgGvXruGbb74xKG+lwzmnVwV+AeDyr8l6FRUV8fDw\ncK7YV8XL39+fP3z40NLNI4RYgVfht9Ra9ezZk4tEIpVXv379DCqjRYsWpcqIiooqoxa/GtR9L+pe\njDHOGOMikYhPnTqVFxUVGVzXjh07uJ+fn1CWorySdTDGuLu7O//iiy94QUGBwfVkZWXxWbNmcVdX\nV411layvWbNmfNeuXQbXpc2UKVOEei9fvmzWsol1kEqlfNasWdzGxqbUcap8fIaFhfGMjAyz179n\nzx5erVo1reejjY0NnzFjBi8uLtZZ3r59+7iLi4tK20uWGxQUZHA7O3fuzBljvFq1ajwnJ8eYXdWL\nOa4xlMowOF6kSfGIxX344YfUM08IIUQjzrnKM4pHjhxBeno6atSooTPv5cuXkZSUpJJfsU1Mo/gs\nmzRpgpCQEJW/vXz5EsnJyfjzzz+F50pXr16NJ0+eYMeOHXqVL5VKER0djU2bNoExJnxv9erVQ+vW\nreHl5YUXL17gn3/+EXrLc3Nz8cknn2Dfvn04cOCAXscIAFy/fh39+vVDSkoKgP+eZ/Xz80NAQABq\n1KgBsViMp0+fIjExEenp6UK+iIgIpKSk4MMPP9SrLm0ePnyIdevWgTGG3r17o2XLliaXSazPu+++\nix9++EE4L7y9vdGtWzc4Ojri4sWLuH79OgBg//79eOuttxAfHw8HBwez1L1+/XqMHz9eqNvW1had\nO3eGv78/ioqK8Oeff+L27duQyWRYvnw50tPTsWnTJq1lvnjxAvn5+Wp/m035zZ41axbCwsKQlZWF\n5cuXY/78+UaVU+EZcxeAXtRDb04PHjzgfn5+1DNPCCkzr8JvqbXq2bOn0FPTrFkzYXvlypV65Z86\ndara/NRDbxrl70XbZ3nr1i3epk0blR63vXv36lVHeHi4Si9dp06d+NmzZ9WmffDgAR85cqRKL6G/\nv79evZMXLlzgHh4eQj47Ozs+YcIEfufOHY15/vzzTz58+HBua2vLRSIRnz9/vl77pIvy8XrgwAGz\nlEmsy7Zt21TOi1mzZpXqBd+xYwd3cnIS0rz77rtmqfvy5cvc3t5eKLdDhw5qz5Pdu3dzNzc3oZ3f\nffed1nJjYmK4SCTi3t7efMCAAXzhwoX88OHDfNq0aUIZxvTQy2Qy7uvryxljvGrVqjwvL8/gMvRh\njmsMmNBDb/GAlV4U0HP+X1BPwTwhpCy8Kr+l1kg5cFywYIFwkdqqVSudeSUSCa9ZsyYXiUS8bt26\nKsESBfSm0Teg55zzx48fczc3NyEIeOONN3SWv3TpUpWgZdy4cXq1SxEYKF4DBgzQmv7Fixe8QYMG\nQjBfpUoV/vvvv+tVF+ecX7t2jTdv3twsAX1OTg53d3fnjDFep04dLpPJTC6TWBexWMwbNmwoHN+R\nkZEa065du1a4kWZvb8///vtvk+sPCwsTyqxbty7PysrSmHb//v3COVyzZk2em5urMe3Tp095ampq\nqX+fN2+eSQE955wvWLBAKOObb74xqgxdLB3Q06R4pEKoW7cu4uLiaJg9IYQQjTw8PDBgwABwznH1\n6lWdky7Fxsbi2bNnAIBhw4bRUHsLqVWrFv7v//5PuPjUNWv73bt3MWfOHOH76tu3L9atW6dXXSNH\njsTnn38u1HXgwAFs27ZNY/qPPvoI9+/fB+ccNjY22L9/P7p166b3vgUEBOD8+fPo1auX3nk02bFj\nB3Jzc8EYw8CBA+l4JaUcPHgQ9+7dE45XxcRv6owfPx7+/v4AAIlEgrVr15pUd15eHmJjY4Wh9jNm\nzICnp6fG9P3790enTp3AOUd6ejp+/vlnjWm9vLxQp04dk9qnSUREhLC9YcOGMqnD0iigJxVG3bp1\nKZgnhBCi1ciRI4XtzZs3a02r/HflfIZ4/PgxFi9ejKCgIGEm56pVq6JFixaYOnUqrly5olc5UqkU\nx48fx8cff4yQkBDUqVMHzs7OcHJyQp06ddC7d28sW7YMWVlZepWnmPnZxsZG+Lc7d+7gww8/RLNm\nzeDh4QF3d3cEBARg+vTpSEtLM2r/zaVVq1bCdkFBAV68eKEx7VdffQWJRALOOZycnAwORGbMmIEW\nLVoI77/88ku16Z48eYItW7YIAcrkyZONmlHeyckJnTp1MjhfSco3Ht5++2298uTk5GDXrl2YOHEi\nOnXqBC8vLzg4OMDd3R0NGzbE4MGDsWXLFkgkEp1lnTp1Su2M4keOHMGwYcPQuHFjuLu7QyQSYcGC\nBRrLSUxMxIwZM9C2bVvUrFkTDg4OqFmzJrp06YIFCxbg6dOn5b5v1mLv3r0A5HM8hISE6LxuHjVq\nFAD5iGxFXmNdvHgRxcXFihHE6NOnj848b775prC9e/duk+o31muvvYamTZuCc44rV64I8wtYFWO6\n9elFQ+4JIaQyod/Sykt5aPeqVau4VCrltWrV4owx7u3tzaVSqdp8WVlZ3MHBgYtEIh4YGMg55yrP\nY+oz5H7BggXc2dlZ60zOIpGIjx8/XutMzqmpqSozQmubOd3d3Z3v3LlTZ9uUy+Cc8/Xr1wttVVeu\nq6srP3LkiM5y9WXIkHtF+5T3/fHjx2rTFRYWchcXF5NXI9i4caNKfQkJCaXSLFq0SEhja2vLU1JS\njKrLHLKysritrS1njHFnZ2cuFot15tm7dy93cHDQeEwpf/+NGjXiV69e1VpefHy8yvDmnJwcPnDg\nQLXlq3vEIDs7mw8ZMqTU+aHuWFy7dm257pu1qFOnjvB5LFmyRGf6M2fOqHyG9+7dM7ruXbt2qZSl\nz4oVP/30k5DHwcGBSyQSg+o0x5B7zjmfPHmyQZ+bocxxjQEThtzTLPfEaPzfO3Q0JIwQQkh5EYlE\niIyMxIoVK/D06VMcOXIEffv2LZVu+/btEIvFYIwZ3DvPOcfQoUOxa9cuofe2Vq1aCAwMhJeXFwoK\nCnDp0iXcuHEDALBu3To8evQI+/fvV1teXl4eMjMzwRiDh4cHAgIC4OvrCzc3NxQXF+PBgwc4d+4c\nXr58idzcXAwdOhR2dnY6e2k5l8/+/NNPPyE6OhqMMfj7+6N9+/ZwdXXFP//8g99//x1SqRR5eXkY\nNGgQrl+/jrp16xr0eZjDo0ePhG0bGxtUq1ZNbbpz584hPz8fgPz6IjIy0qj6IiIiMGHCBKH3Ni4u\nDl26dFFJc/LkSaGezp07o169ekbVZQ4nT56EVCoFYwzt27eHnZ2dzjxPnz5FcXExGGOoXbs2AgIC\n4O3tDWdnZ+Tn5+P27dv466+/IJVKcefOHfTo0QOXLl2Cr6+vzrI55xg2bBh+++03iEQitGnTBgEB\nAWCMITk5udS137NnzxAcHIwbN24I50zjxo3RqlUreHh4IDMzE6dPn8bjx4+Rl5eHiRMnIjc3V+PK\nAGW5b5VVTk4O0tLShM++TZs2OvO0bt0awH/X6tevX7fYZ1RcXIzbt2/j9ddfL/e6u3XrJqxFf+TI\nEcycObPc21CWXpmAnjHmA2AKgH4A6gGQALgHYC+ANZxzzWO/DKunPYBJAHoA8AaQA+A6gG0ANnHO\nZeaopyL4M+1PdNzQESImgq3IFoE+gfg96ndLN4sQQoiVGzFiBFasWAEA2LJli9qAfsuWLQAAOzs7\nDBkyxKDyFyxYIATzXl5eWLNmDQYNGlQq3cmTJzFixAg8evQIBw8exIoVKzB9+vRS6ZycnDB58mQM\nHz4cbdu2VXsjXCwW4+uvv8acOXOE5dr69OkDJycnje1UlBMdHY3q1atj8+bNpT6LpKQk9OnTRwik\nFi5cqPfz6OZ0+PBhYbtNmzYaA1bl5+sZYwgMDDSqPmdnZzRr1gyJiYlgjJV6bl8ikeDcuXPCZ2iO\nIfOmOH/+vLCt/LiANrVr18YXX3yBQYMGwc/PT22aZ8+e4YMPPsC2bduQnZ2NiRMnIjY2VmfZp0+f\nhkQiQbNmzbBt2zY0b95c5e/FxcXCNucc77zzjhDMt23bFt9//z3atm2rkkcmk2Ht2rX44IMPUFRU\nhNmzZ6NHjx5o3759ue6bPiZPnmyWcpStWbPGpPy3bt0C8N+NvPr16+vM4+joiBo1aiA9PV24GfPW\nW28ZVX/JJSBTUlKEZ/Q1USwDqZCcnGyRgF7xyA/nHBcuXBA+Q6thTLd+ZXsB6AMgE4AMgLTESwYg\nFUAbM9QzG/IbBSXrkf37SgDgYWCZFXaYaEJKAsc8CK9OP3aydJMIIUStivxbSrQrOeReoWXLlsLw\n5OzsbJU8t27dEvK8/fbbwr/rM+Q+JSWF29nZcZFIxKtUqaJzZujr169zR0dHLhKJuJeXFy8oKDBh\nb1Vnd1+3bp3GdIo0jDHu5OTEr1y5ojGtYrZpxhj38PDQ+JiCIQwZch8TE6MyVHfTpk0a044dO1ZI\n6+vra1IbR44cKZTVuHFjlb+lpaWpDOXesmWLSXWZqk+fPkJ7vv32W7OX37dvX6H8W7duqU2jPOSe\nMcZr1arFnz9/rrPsrVu3Cvk6dOjA8/PztabfsGGDkP6tt94yan+U6bNvhlJ+PMYcL8WjMaaIjY1V\nKe/Fixd65WvRooWQZ/bs2UbXn5WVxW1sbIRzRvn3WJPOnTurtHn9+vUG1WmuIfcymYzb2dkJZZlj\nxn9l5rjGAM1yrxljrAWAXwB4AMgDMBdAVwA9AayEPAD3AfAbY6yWCfWMBrAIAANwH0A0gA6QjwjY\nD/mX1AnyEQFWQSJTnYTEVqQ64EMsFiM6Oho3b94sz2YRQki5Y/OZQa+KVn5lpBhGX1hYiF27dqn8\nLSYmplQ6fa1atUoYpv3JJ5+gUaNGWtM3bdoUI0eOBOccz58/V+mJNkZUVJSwfezYMZ3pGWMYN26c\n1l7dfv36oWbNmgCA3NxcJCcnm9RGfeTn5+PChQuYNGkSRo8eLbR16NChwkRd6mRmZgppq1atalIb\nqlSpImxnZGSo/E3xnv/7+KC22brLw71794TtspjtW/m4On78uM70jDF89tlnGh+NULZy5Uph+7vv\nvtM6qgQARo8ejcaNG4NzjsOHD+s9EaQmhu6bPhSPDZjzZaqXL1+qvNf1OatLV7IMQ3h6eqJ79+5C\nELl8+XKtk1vu378fZ8+eVdn33Nxco+s3BWMM3t7ewnvl880avApD7r8G4AJ54N6Hc35a6W9/MMYS\nAfwEoBbkAflYQytgjHkA+BLyoD0NQAfO+XOlJLGMsXX/lt2DMTaMc77VqL2pQEoG9HY2/w2fE4vF\niIiIwL59+7B//37ExcVZZIgNIYQQ6xQZGYmPPvoIMpkMmzdvxtix8v99c86F2cKrVatm8PDSgwcP\nCttDhw7VK09ISIgwjD0hIQHh4eEa00qlUvz111+4cuUKHj16hNzcXJXhywqccyQmJupV/+DBg7X+\nnTGGVq1a4ciRIwCA+/fvo2nTpnqVrY+YmBiVmyjq6nd3d8fkyZO1zo4OqF7wu7q6mtQu5fw5OTka\n6zFHXaZSnvldnyC6pJcvX+Ls2bO4fv06nj9/jpcvX0IqlQp/V17lQNdxxf8djqy83JcmT548waVL\nl8AYg5+fX6lh9poEBwfj1q1b4Jzj9OnT6Nevn8a05tw3fSmXX1EUFhaqvLe3t9crn4ODg7BdUFBg\nUhs+/fRTxMfHgzGGtLQ09OrVC9u3by9143P37t0YPXp0qRsZptZviurVqyM1NRWA/Li1JlYd0DPG\n2kDeE88hf379dMk0nPNtjLEoAMEARjDGZpUIxvUxFkCVf+uZqSH/+wD+D4A7gBkArC6gV/TQKwfz\ngPx/UkFBQYiPj0eTJk3KvZ2EEEKsj5eXF9544w0cOnQIZ86cwd27d9GwYUPExcUhNTVV6A22tdX/\nUiczMxO3b98GYwwikQiLFy/WK9/Dhw+FbcUFY0lFRUVYunQpvv/+e53LdjHGhB5/bRSBV8nnm9VR\nDhKzs7N1pjeEpt5HRe83IB/tMGPGDJ1lubm5Cdum9CaWzO/u7q6xHnPUZaq8vDxh29nZWe98T548\nwccff4xdu3bpHSzpOq4YY/D19VUZ4aDJ2bNnhW2xWKz3s+d//fWXsK3pnCmLfavMHB0dVd6LxWK9\ngvqioiJhW99efU2CgoIwa9YsLF26FJxzXLx4EU2bNkWXLl3g7++PoqIinD9/Xvgd7datG27cuCF8\nLyXPu/KkfF4pn2/WwKoDegD/U9reqCXdRsgDehsAA3SkVUcxDW0uALWLLHLO8xhjv0Ae/DdjjDXk\nnN81sJ4KRV1AXzKYV3B3d7foSUwIIcT6jBgxAocOHQIgnwRv3rx5Kj3Fw4cPN6i8x48fC9tSqRTf\nfvutQfk552qHD+fk5CA0NBQXLlwAoP/qMPoOTy0ZrKqjPAmduhEBpmjSpAlCQkKE94WFhUhNTcXZ\ns2eRm5sLzjlmzpyJ5ORkbNiwQWtZimH2nHNh+L2xlL+Lkr3eiveK70Lb0OHypnwjRJurV68iJCQE\nGRkZeg3rVpSrz3Hl5eWlVxuUVy948OCBwecMALXnTFnuW2VVchRJQUGBXgG98s0Qc4xE+eKLL1Cl\nShXMnTsXYrEYUqkUp06dwqlTpwD897hCnz59sG3bNpXJ+yz5aIu+51VlZO0Bfdd//5sP4C8t6eJK\n5NE7oGeM2UL+rDwHcI5zru3/knH4b0h/VwBWFdCLIFIbzPv7+yMuLg4+Pj7l2TxCCCk3/LOyvVAo\n6/Irq7CwMHh4eCA7Oxs//fQTPvzwQ+zduxeMMTRp0gTt2rUzqDzlnmtjn3lVN1T3vffew4ULF8AY\ng729PUaNGoU333wTTZs2Ra1ateDk5ASR6L9pjRTbleUCNDAwEKtXry7177m5uZg/fz5WrFgBxhhi\nYmIQEBCgdiUABeUltVJTU5Gbm2t0h0BSUhKA/3qclXl5ecHJyUkYxnz9+nWj6jAXFxcX4fjTpze6\nuLgYAwcOFJZDrFGjBiZMmICgoCD4+fmhevXqKj26p06dQlBQEAD5bPO66NuTa45zRjFnhUJZ71tl\nVfKm1NOnT+Hh4aEzn/LwclPnpVCYMWMG3nnnHaxduxbHjx/HnTt3kJOTAy8vL7Ru3RpRUVEIDw9H\nUVGRyugXSyyZqaB8Xrm4uFisHWXB2gP6ppAH2n9zLcvFcc4fM8ZyAbj+m8cQr0H+OXIAN3SkVZ6F\nxnwPr1lIyYD+4l8X8XjfY5V/o2CeEEJIWXFwcMDgwYOxfv163L9/H1OnTkVeXp5Ra88D//Vecc7h\n6OgorIduisePH2Pbtm1gjMHGxgZHjx5Ft27dNKa3ph5GNzc3LF++HDk5Ofjxxx8ByIfeh4WFaVyK\nrGvXrsI25xznz59HaGiowXXn5+fj2rVrQpCpXC4A2NraIjAwUHge+Ny5cwbXYU61atUSgmN9ho3v\n2bMHd+7cAWMMderUwYULF0otK6as5BwC5qLc49u7d2+zLBtXEfatIi5b17hxYwD/3ThJSUnBa6+9\npjVPUVGRsGQdALM++urj44OFCxdi4cKFGtPcvHlTuDHJGDP4Jqs5paenC9vKE+RZA6sN6Blj9gCq\nQx5oP9SRHJAvXdcUgKG3jpSnItVVj/JDQpa7RWUmJQP6xw8pmCeEEFK+RowYgfXr1wMANm3aBEDe\nwx0ZGWlwWYqZ4AH5hXB2drZePWDanDx5UnjWvW/fvlqDeaD0us3WYOXKlYiNjUVaWhrEYjFmz56N\nnTt3qk0bGBgIZ2dnoTdt27ZtRgX0O3bsEB4tYIwJPbjKgoODER8fL0zMlpqaarEexIYNGwrrjCvP\nyaDJiRMnhO1p06ZpDXiBsjuulM8Zc000VhH2zZhHB7RhjJkc0Lu7u8PHxwdpaWlgjCExMRG9evXS\nmufSpUsA/ptvIyAgwKQ2GOrMmTMAINRtqcknOecqx2fJETuVnTUvW6c8PkufmU4UaQw90gypR/nv\nlp1O1QxKBvRQGgNBwTwhhJDy0KVLF/j5+akMTw8KCjLq/z81a9ZEvXr1hPenT5eaS9dgys8YN2vW\nTGd6xXOo1sTFxQXz5s0DIL+w3r17N65cuaI2raOjo7AMIOccv/zyi8ZJ0zSRSqUqjwA0a9YMXbp0\nKZVuzJgxsLe3B2MMMplMZfm18qa87KA+y/1WlOMqMDAQgPx7vX79ullGmFSEfauIy9YB8ptQCvHx\n8TrTKz/X7uvrW+6BrPKNO2NGTZnL33//LTza4erqqnM50srGmgN65Yd/xHqkV0wBaej0j4bUU6S0\nbdo0kxWApoCegnlCCCHlafjw4SoXzqZcOCovn/Xdd9+Z3DblC3ldMyvLZDKsXbvWbBf/FcmoUaNU\ngglty9dNnz4dtra2YIyhoKAAEyZMMKiupUuX4urVqwDkn/9HH32kNp23t7fKzYM1a9YYdRMnPz9f\nZbZ3YygCYwAab3YoM+S4Sk1Nxf79+8vkuPL19RWWQJRKpfjhhx9MLrMi7JtUKjXrq+Q8AcZSLInJ\nOcfx48dVbn6oozxJ6P/+9z/NCcvA8ePH8ccffwD470adpSjOKUsP+y8r1hzQK88oos9CjYpFGg1d\nINGQehyUti23EKOZqAvoKZgnhBBS3qZPn46//vpLeOlal12bDz74ALa2tuCcIzY21qAAJSMjo9RE\ndsrPih88eFDrpF0LFy60+ORsZcXGxgazZ88GIA9Gfv31V1y7dk1tWj8/PyxYsEAItA8fPozo6Gi9\nJgncvHkz5s6dK9zcefPNN7U+frF06VLhRoNUKsWAAQOQkJCg934lJSUhMDAQx44d0zuPOsHBwcJx\nd/HiRYjF2vuIlI+rkpMRK5NKpRgzZozZVzZQNnPmTADy73X+/PnCMG99qFvCsSLtW0XTr18/leN1\n1qxZGtOuW7cOt2/fBiCfM2L8+PHl0UQA8scgxo6VzwPOGMO8efNKTepXnhQ3FgD5XA/WxpoDeuUx\nP/oMb1ekMXQhUkPqUf67QfVoG8KjGMZW3sa0GQPZXBnSxqehye4m8LvlR8E8IYSQcufq6oo2bdoI\nL+Ul2gzVoEEDzJ07F4A8QJk4cSKmTp2KZ8+eqU3POUdCQgImTpyIevXqlZqhPDg4WFj/+O7duxg2\nbFipZboKCwsxc+ZMzJ8/H66urpVmdntDjRo1SnikgXOudTKtWbNmoV+/fmCMgXOOH3/8EZ07d9bY\nE/7gwQOMHDkSUVFRwo2Ahg0bqvRQquPp6YlffvkFbm5uYIwhKysLwcHBmDRpEu7e1bwY0V9//YXh\nw4ejdevWuHFD15zIurm7u6N79+4A5PM36Lqp0L9/f2F769at+PLLL0utsPDw4UP069cPx48fL9Pj\nKjIyUniWOy8vDz169MC3336rsv65ssLCQuzduxdhYWEICwsr9feKtG8VjZ2dHRYtWgRAfg5t27YN\nH3/8cakRALt27cL7778PQB5DREdHawz8RKYAACAASURBVB1mHhUVBZFIBJFIhIYNG2ptw4wZM7Bn\nzx5hhQhlnHPs2bMHXbt2xYMHD8AYQ6dOnfDBBx8YuqtmdfLkSWFbeRRWeZs3b17ZPJKh+NGzxheA\nZwCkAC7pkfbFv2nPGVhHU8gHm0sBrNCRtrVS2iV6ls/lX1PF9vTpU/7w4UNLN4MQQtSqLL+lpLSe\nPXtyxhgXiUR81apVJpU1bdo0oayoqCitaceNG8dFIhEXiUScMcbt7Ox4YGAgHz58OJ84cSKPjIzk\n3bt35x4eHpwxJpSbl5dXqqz58+cLaRhjvEqVKrxv37583LhxPCwsTChDJBLxnTt3qpSniT5plI0a\nNUpIv3nzZr3yaKP8vej6LJWtXbtWaLuNjQ2/efOmxrQSiYRHRUWpfA+MMe7r68vffvttHh0dzYcM\nGcLbtm2r8vmKRCLevn17/vTpU73blZSUxH19fVXqYYzx1157jYeHh/OxY8fykSNH8jfeeIPXrFmz\nVH0rV67Uuy5NNm7cKJT33nvv6UwfFBSk0g5fX1/+v//9j48dO5YHBwdzOzs7zhjjnp6efP369ULZ\nQUFBasuLj4/XmUaTrKws3r59e5XPz83Njffq1YtHRUXx8ePH84iICN6mTRvu4OAgpGnfvn257Ju1\nmTBhgspn7ePjw4cMGcJHjRrFmzdvrnJsduzYkRcUFGgtb9SoUcJ51qBBA61pO3bsyBlj3MXFhXfr\n1o2PHDmSR0dH8/DwcJVzQ1F3dna2XvvUt29f3qpVK5VXrVq1hLJcXV1L/b1Vq1b84sWLWsu9ffu2\nUEarVq30aouhzHGNoVSG4TGvMZkqywtA/L8BdC4AkZZ03kqB9kYD67CF/Nl5KYDDOtIOVapnhJ7l\n00UoIYSYiH5LKy9LBfScy4PPGjVqlAooSwZzilfnzp25WCwuVY5MJuNjx47VWI5IJOIuLi5848aN\nnHP9gvWKEtAzxgwK6MViMa9bt66Qd+jQoTrzbN++nfv5+al81pq+B3d3d75o0SKdAYw6WVlZfObM\nmdzV1VXv77xt27b8t99+M7gudXJzc4WbO97e3lwqlWpNn56ezgMDA7V+Jg0aNODnz58XgnXGmM6A\nXlsabYqKiviUKVO4g4ODXp+fg4MDnzJlSrnsm7WRyWT8448/5ra2tmo/I8W/hYeH84yMDJ3lKX4f\nGGN6BfS6zkM7Ozs+ffp0tTc4NfH19VV7vGh7iUQifurUKa3lKm6oikQi/s033+jdHkNYOqC35iH3\nAKAYr+QMoL2WdD3V5NEL51wC4E8ADEBHxpi2pQCNrocQQgh5VZk8HFFNWfqUOX78eNy/fx9r167F\nwIED4efnBw8PD9ja2sLT0xMBAQEYNGgQvv76a9y+fRu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4yH3/ui4/LkH7YXSbl6wzKBEx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\nnAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x110765f98>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 515,
       "width": 506
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.cross_validation import StratifiedKFold\n",
    "from utils import draw_roc_curve\n",
    "\n",
    "clf = RandomForestClassifier()\n",
    "cv = StratifiedKFold(y, n_folds=3)\n",
    "    \n",
    "draw_roc_curve(clf, cv, X, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Things to remember\n",
    "\n",
    "* what is the baseline you are comparing to? How well would you do with a dummy classifier?\n",
    "* cross-validation: keep data in reserve in order to evaluate the performance of your model\n",
    "* accuracy is not the be all, end all\n",
    "* can tune the false positive and false negative rate depending on what is important to you\n",
    "\n",
    "\n",
    "# The End\n",
    "\n",
    "All the material is available on Github: https://github.com/wildtreetech/forests-intro\n",
    "\n",
    "<img src=\"img/thatsall.gif\" />"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "## Aside: Confusion matrix\n",
    "\n",
    "Look at which classes your classifier gets wrong and in which direction. This can\n",
    "tell you something about which cases are hard and which easy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.cross_validation import cross_val_predict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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I8AAAADAAAjwAAAAMgAAPAAAAAyDAAwAAwAAI8AAAADAAAjwAAAAMgAAPAAAA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SDAAwAAQA8I8AAAANADAjwAAAD0gAAPAAAAPSDAAwAAQA8I8AAAANADAjwAAAD0gAAP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\nAC9JkiRJUg/8H/ruph0loT1sAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1107a3b70>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 992,
       "width": 504
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_confusion_matrix(cm, ax, title='Confusion matrix', cmap=plt.cm.summer_r):\n",
    "    ax.imshow(cm, interpolation='none', cmap=cmap)\n",
    "\n",
    "    ax.set_xticks([0,1])\n",
    "    ax.set_yticks([0,1])\n",
    "\n",
    "    ax.set_xticklabels(['stay', 'churn'])\n",
    "    ax.set_yticklabels(['stay', 'churn'])\n",
    "\n",
    "    for i in range(cm.shape[0]):\n",
    "        for j in range(cm.shape[1]):\n",
    "            ax.annotate(str(cm[i][j]), xy=(j, i), color='black')\n",
    "\n",
    "    ax.set_ylabel('True label')\n",
    "    ax.set_xlabel('Predicted label')\n",
    "    ax.set_title(title)\n",
    "\n",
    "\n",
    "fig, axarr = plt.subplots(nrows=len(classifiers), figsize=(7, 7*len(classifiers)))\n",
    "\n",
    "for (name,classifier), ax in zip(classifiers, axarr):\n",
    "    y_pred = cross_val_predict(classifier, X, y)\n",
    "    plot_confusion_matrix(confusion_matrix(y, y_pred), ax,\n",
    "                          'Confusion matrix (%s)'%name)\n",
    "    \n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}