{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Self made RP3-beta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import helpers\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import scipy.sparse as sparse\n",
    "from collections import defaultdict\n",
    "from itertools import chain\n",
    "import random\n",
    "import time\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "train_read=pd.read_csv('./Datasets/ml-100k/train.csv', sep='\\t', header=None)\n",
    "test_read=pd.read_csv('./Datasets/ml-100k/test.csv', sep='\\t', header=None)\n",
    "train_ui, test_ui, user_code_id, user_id_code, item_code_id, item_id_code = helpers.data_to_csr(train_read, test_read)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "class RP3Beta():\n",
    "    def fit(self, train_ui, alpha, beta):\n",
    "        \"\"\"We weight our edges by user's explicit ratings so if user rated movie high we'll follow that path\n",
    "        with higher probability.\"\"\"\n",
    "        self.train_ui=train_ui\n",
    "        self.train_iu=train_ui.transpose()\n",
    "        \n",
    "        self.alpha = alpha\n",
    "        self.beta = beta\n",
    "        \n",
    "        # Define Pui \n",
    "        Pui=sparse.csr_matrix(self.train_ui/self.train_ui.sum(axis=1))\n",
    "        \n",
    "        # Define Piu\n",
    "        to_divide=np.vectorize(lambda x: x if x>0 else 1)(self.train_iu.sum(axis=1)) # to avoid dividing by zero\n",
    "        Piu=sparse.csr_matrix(self.train_iu/to_divide)\n",
    "        item_orders=(self.train_ui>0).sum(axis=0)\n",
    "        \n",
    "        Pui = Pui.power(self.alpha)\n",
    "        Piu = Piu.power(self.alpha)\n",
    "\n",
    "        P3=Pui*Piu*Pui\n",
    "        \n",
    "        P3/=np.power(np.vectorize(lambda x: x if x>0 else 1)(item_orders), self.beta)\n",
    "        \n",
    "        self.estimations=np.array(P3)\n",
    "    \n",
    "    def recommend(self, user_code_id, item_code_id, topK=10):\n",
    "        \n",
    "        top_k = defaultdict(list)\n",
    "        for nb_user, user in enumerate(self.estimations):\n",
    "            \n",
    "            user_rated=self.train_ui.indices[self.train_ui.indptr[nb_user]:self.train_ui.indptr[nb_user+1]]\n",
    "            for item, score in enumerate(user):\n",
    "                if item not in user_rated and not np.isnan(score):\n",
    "                    top_k[user_code_id[nb_user]].append((item_code_id[item], score))\n",
    "        result=[]\n",
    "        # Let's choose k best items in the format: (user, item1, score1, item2, score2, ...)\n",
    "        for uid, item_scores in top_k.items():\n",
    "            item_scores.sort(key=lambda x: x[1], reverse=True)\n",
    "            result.append([uid]+list(chain(*item_scores[:topK])))\n",
    "        return result\n",
    "    \n",
    "    def estimate(self, user_code_id, item_code_id, test_ui):\n",
    "        result=[]\n",
    "        for user, item in zip(*test_ui.nonzero()):\n",
    "            result.append([user_code_id[user], item_code_id[item], \n",
    "                           self.estimations[user,item] if not np.isnan(self.estimations[user,item]) else 1])\n",
    "        return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "model=RP3Beta()\n",
    "model.fit(train_ui, alpha=1, beta=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "top_n=pd.DataFrame(model.recommend(user_code_id, item_code_id, topK=10))\n",
    "\n",
    "top_n.to_csv('Recommendations generated/ml-100k/Self_P3_reco.csv', index=False, header=False)\n",
    "\n",
    "estimations=pd.DataFrame(model.estimate(user_code_id, item_code_id, test_ui))\n",
    "estimations.to_csv('Recommendations generated/ml-100k/Self_P3_estimations.csv', index=False, header=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "943it [00:00, 4936.65it/s]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RMSE</th>\n",
       "      <th>MAE</th>\n",
       "      <th>precision</th>\n",
       "      <th>recall</th>\n",
       "      <th>F_1</th>\n",
       "      <th>F_05</th>\n",
       "      <th>precision_super</th>\n",
       "      <th>recall_super</th>\n",
       "      <th>NDCG</th>\n",
       "      <th>mAP</th>\n",
       "      <th>MRR</th>\n",
       "      <th>LAUC</th>\n",
       "      <th>HR</th>\n",
       "      <th>F_2</th>\n",
       "      <th>Whole_average</th>\n",
       "      <th>Reco in test</th>\n",
       "      <th>Test coverage</th>\n",
       "      <th>Shannon</th>\n",
       "      <th>Gini</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3.702446</td>\n",
       "      <td>3.527273</td>\n",
       "      <td>0.282185</td>\n",
       "      <td>0.192092</td>\n",
       "      <td>0.186749</td>\n",
       "      <td>0.21698</td>\n",
       "      <td>0.204185</td>\n",
       "      <td>0.240096</td>\n",
       "      <td>0.339114</td>\n",
       "      <td>0.204905</td>\n",
       "      <td>0.572157</td>\n",
       "      <td>0.593544</td>\n",
       "      <td>0.875928</td>\n",
       "      <td>0.181702</td>\n",
       "      <td>0.340803</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.077201</td>\n",
       "      <td>3.875892</td>\n",
       "      <td>0.974947</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       RMSE       MAE  precision    recall       F_1     F_05  \\\n",
       "0  3.702446  3.527273   0.282185  0.192092  0.186749  0.21698   \n",
       "\n",
       "   precision_super  recall_super      NDCG       mAP       MRR      LAUC  \\\n",
       "0         0.204185      0.240096  0.339114  0.204905  0.572157  0.593544   \n",
       "\n",
       "         HR       F_2  Whole_average  Reco in test  Test coverage   Shannon  \\\n",
       "0  0.875928  0.181702       0.340803           1.0       0.077201  3.875892   \n",
       "\n",
       "       Gini  \n",
       "0  0.974947  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import evaluation_measures as ev\n",
    "estimations_df=pd.read_csv('Recommendations generated/ml-100k/Self_P3_estimations.csv', header=None)\n",
    "reco=np.loadtxt('Recommendations generated/ml-100k/Self_P3_reco.csv', delimiter=',')\n",
    "\n",
    "ev.evaluate(test=pd.read_csv('./Datasets/ml-100k/test.csv', sep='\\t', header=None),\n",
    "            estimations_df=estimations_df, \n",
    "            reco=reco,\n",
    "            super_reactions=[4,5])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Let's check hiperparameters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Alpha"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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      "100%|██████████| 8/8 [02:30<00:00, 18.83s/it]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Alpha</th>\n",
       "      <th>RMSE</th>\n",
       "      <th>MAE</th>\n",
       "      <th>precision</th>\n",
       "      <th>recall</th>\n",
       "      <th>F_1</th>\n",
       "      <th>F_05</th>\n",
       "      <th>precision_super</th>\n",
       "      <th>recall_super</th>\n",
       "      <th>NDCG</th>\n",
       "      <th>mAP</th>\n",
       "      <th>MRR</th>\n",
       "      <th>LAUC</th>\n",
       "      <th>HR</th>\n",
       "      <th>F_2</th>\n",
       "      <th>Whole_average</th>\n",
       "      <th>Reco in test</th>\n",
       "      <th>Test coverage</th>\n",
       "      <th>Shannon</th>\n",
       "      <th>Gini</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.2</td>\n",
       "      <td>268.177832</td>\n",
       "      <td>211.732649</td>\n",
       "      <td>0.262672</td>\n",
       "      <td>0.166858</td>\n",
       "      <td>0.166277</td>\n",
       "      <td>0.197184</td>\n",
       "      <td>0.187661</td>\n",
       "      <td>0.203252</td>\n",
       "      <td>0.320910</td>\n",
       "      <td>0.196132</td>\n",
       "      <td>0.563378</td>\n",
       "      <td>0.580866</td>\n",
       "      <td>0.850477</td>\n",
       "      <td>0.159293</td>\n",
       "      <td>0.321247</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.060606</td>\n",
       "      <td>3.669627</td>\n",
       "      <td>0.979636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.4</td>\n",
       "      <td>10.546689</td>\n",
       "      <td>7.792373</td>\n",
       "      <td>0.268505</td>\n",
       "      <td>0.172669</td>\n",
       "      <td>0.171569</td>\n",
       "      <td>0.202643</td>\n",
       "      <td>0.192489</td>\n",
       "      <td>0.212653</td>\n",
       "      <td>0.326760</td>\n",
       "      <td>0.200172</td>\n",
       "      <td>0.565148</td>\n",
       "      <td>0.583801</td>\n",
       "      <td>0.854719</td>\n",
       "      <td>0.164747</td>\n",
       "      <td>0.326323</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.064214</td>\n",
       "      <td>3.726996</td>\n",
       "      <td>0.978426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.6</td>\n",
       "      <td>3.143988</td>\n",
       "      <td>2.948790</td>\n",
       "      <td>0.274655</td>\n",
       "      <td>0.180502</td>\n",
       "      <td>0.177820</td>\n",
       "      <td>0.208730</td>\n",
       "      <td>0.198176</td>\n",
       "      <td>0.222746</td>\n",
       "      <td>0.332872</td>\n",
       "      <td>0.203290</td>\n",
       "      <td>0.568872</td>\n",
       "      <td>0.587738</td>\n",
       "      <td>0.870626</td>\n",
       "      <td>0.171652</td>\n",
       "      <td>0.333140</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.065657</td>\n",
       "      <td>3.785282</td>\n",
       "      <td>0.977090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.8</td>\n",
       "      <td>3.670728</td>\n",
       "      <td>3.495735</td>\n",
       "      <td>0.281972</td>\n",
       "      <td>0.189868</td>\n",
       "      <td>0.185300</td>\n",
       "      <td>0.216071</td>\n",
       "      <td>0.203541</td>\n",
       "      <td>0.236751</td>\n",
       "      <td>0.339867</td>\n",
       "      <td>0.206688</td>\n",
       "      <td>0.573729</td>\n",
       "      <td>0.592432</td>\n",
       "      <td>0.874867</td>\n",
       "      <td>0.179823</td>\n",
       "      <td>0.340076</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.070707</td>\n",
       "      <td>3.832415</td>\n",
       "      <td>0.975998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3.702446</td>\n",
       "      <td>3.527273</td>\n",
       "      <td>0.282185</td>\n",
       "      <td>0.192092</td>\n",
       "      <td>0.186749</td>\n",
       "      <td>0.216980</td>\n",
       "      <td>0.204185</td>\n",
       "      <td>0.240096</td>\n",
       "      <td>0.339114</td>\n",
       "      <td>0.204905</td>\n",
       "      <td>0.572157</td>\n",
       "      <td>0.593544</td>\n",
       "      <td>0.875928</td>\n",
       "      <td>0.181702</td>\n",
       "      <td>0.340803</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.077201</td>\n",
       "      <td>3.875892</td>\n",
       "      <td>0.974947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.2</td>\n",
       "      <td>3.704441</td>\n",
       "      <td>3.529251</td>\n",
       "      <td>0.280912</td>\n",
       "      <td>0.193633</td>\n",
       "      <td>0.187311</td>\n",
       "      <td>0.216872</td>\n",
       "      <td>0.203004</td>\n",
       "      <td>0.240588</td>\n",
       "      <td>0.338049</td>\n",
       "      <td>0.203453</td>\n",
       "      <td>0.571830</td>\n",
       "      <td>0.594313</td>\n",
       "      <td>0.883351</td>\n",
       "      <td>0.182776</td>\n",
       "      <td>0.341341</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.085859</td>\n",
       "      <td>3.910718</td>\n",
       "      <td>0.974073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.4</td>\n",
       "      <td>3.704580</td>\n",
       "      <td>3.529388</td>\n",
       "      <td>0.273595</td>\n",
       "      <td>0.190651</td>\n",
       "      <td>0.183874</td>\n",
       "      <td>0.212183</td>\n",
       "      <td>0.199464</td>\n",
       "      <td>0.239118</td>\n",
       "      <td>0.329550</td>\n",
       "      <td>0.195433</td>\n",
       "      <td>0.566171</td>\n",
       "      <td>0.592793</td>\n",
       "      <td>0.871686</td>\n",
       "      <td>0.179766</td>\n",
       "      <td>0.336190</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.107504</td>\n",
       "      <td>3.961915</td>\n",
       "      <td>0.972674</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.6</td>\n",
       "      <td>3.704591</td>\n",
       "      <td>3.529399</td>\n",
       "      <td>0.263097</td>\n",
       "      <td>0.186255</td>\n",
       "      <td>0.178709</td>\n",
       "      <td>0.205170</td>\n",
       "      <td>0.191094</td>\n",
       "      <td>0.232920</td>\n",
       "      <td>0.317439</td>\n",
       "      <td>0.184917</td>\n",
       "      <td>0.552349</td>\n",
       "      <td>0.590545</td>\n",
       "      <td>0.868505</td>\n",
       "      <td>0.175419</td>\n",
       "      <td>0.328868</td>\n",
       "      <td>0.999576</td>\n",
       "      <td>0.156566</td>\n",
       "      <td>4.060156</td>\n",
       "      <td>0.969203</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Alpha        RMSE         MAE  precision    recall       F_1      F_05  \\\n",
       "0    0.2  268.177832  211.732649   0.262672  0.166858  0.166277  0.197184   \n",
       "0    0.4   10.546689    7.792373   0.268505  0.172669  0.171569  0.202643   \n",
       "0    0.6    3.143988    2.948790   0.274655  0.180502  0.177820  0.208730   \n",
       "0    0.8    3.670728    3.495735   0.281972  0.189868  0.185300  0.216071   \n",
       "0    1.0    3.702446    3.527273   0.282185  0.192092  0.186749  0.216980   \n",
       "0    1.2    3.704441    3.529251   0.280912  0.193633  0.187311  0.216872   \n",
       "0    1.4    3.704580    3.529388   0.273595  0.190651  0.183874  0.212183   \n",
       "0    1.6    3.704591    3.529399   0.263097  0.186255  0.178709  0.205170   \n",
       "\n",
       "   precision_super  recall_super      NDCG       mAP       MRR      LAUC  \\\n",
       "0         0.187661      0.203252  0.320910  0.196132  0.563378  0.580866   \n",
       "0         0.192489      0.212653  0.326760  0.200172  0.565148  0.583801   \n",
       "0         0.198176      0.222746  0.332872  0.203290  0.568872  0.587738   \n",
       "0         0.203541      0.236751  0.339867  0.206688  0.573729  0.592432   \n",
       "0         0.204185      0.240096  0.339114  0.204905  0.572157  0.593544   \n",
       "0         0.203004      0.240588  0.338049  0.203453  0.571830  0.594313   \n",
       "0         0.199464      0.239118  0.329550  0.195433  0.566171  0.592793   \n",
       "0         0.191094      0.232920  0.317439  0.184917  0.552349  0.590545   \n",
       "\n",
       "         HR       F_2  Whole_average  Reco in test  Test coverage   Shannon  \\\n",
       "0  0.850477  0.159293       0.321247      1.000000       0.060606  3.669627   \n",
       "0  0.854719  0.164747       0.326323      1.000000       0.064214  3.726996   \n",
       "0  0.870626  0.171652       0.333140      1.000000       0.065657  3.785282   \n",
       "0  0.874867  0.179823       0.340076      1.000000       0.070707  3.832415   \n",
       "0  0.875928  0.181702       0.340803      1.000000       0.077201  3.875892   \n",
       "0  0.883351  0.182776       0.341341      1.000000       0.085859  3.910718   \n",
       "0  0.871686  0.179766       0.336190      1.000000       0.107504  3.961915   \n",
       "0  0.868505  0.175419       0.328868      0.999576       0.156566  4.060156   \n",
       "\n",
       "       Gini  \n",
       "0  0.979636  \n",
       "0  0.978426  \n",
       "0  0.977090  \n",
       "0  0.975998  \n",
       "0  0.974947  \n",
       "0  0.974073  \n",
       "0  0.972674  \n",
       "0  0.969203  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from tqdm import tqdm\n",
    "result=[]\n",
    "for alpha in tqdm([round(i,1) for i in np.arange(0.2,1.6001,0.2)]):\n",
    "    model=RP3Beta()\n",
    "    model.fit(train_ui, alpha=alpha, beta=0)\n",
    "    reco=pd.DataFrame(model.recommend(user_code_id, item_code_id, topK=10))\n",
    "    estimations_df=pd.DataFrame(model.estimate(user_code_id, item_code_id, test_ui))\n",
    "    to_append=ev.evaluate(test=pd.read_csv('./Datasets/ml-100k/test.csv', sep='\\t', header=None),\n",
    "            estimations_df=estimations_df, \n",
    "            reco=np.array(reco),\n",
    "            super_reactions=[4,5])\n",
    "    to_append.insert(0, \"Alpha\", alpha)\n",
    "    result.append(to_append)\n",
    "    \n",
    "result=pd.concat(result)\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "ename": "IndexError",
     "evalue": "list index out of range",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-8-e01206177978>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     10\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmetrics\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     11\u001b[0m     \u001b[0mdf\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Alpha'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmetrics\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 12\u001b[0;31m     \u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxes\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mto_iter\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtitle\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmetrics\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m: list index out of range"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x3024 with 18 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "metrics=list(result.columns[[i not in ['Alpha'] for i in result.columns]])\n",
    "\n",
    "charts_per_row=6\n",
    "charts_per_column=3\n",
    "\n",
    "fig, axes = plt.subplots(nrows=charts_per_row, ncols=charts_per_column,figsize=(18, 7*charts_per_row ))\n",
    "import itertools\n",
    "to_iter=[i for i in itertools.product(range(charts_per_row), range(charts_per_column))]\n",
    "\n",
    "for i in range(len(metrics)):\n",
    "    df=result[['Alpha', metrics[i]]]\n",
    "    df.plot(ax=axes[to_iter[i]], title=metrics[i], x=0, y=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Beta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  0%|          | 0/10 [00:00<?, ?it/s]\n",
      "0it [00:00, ?it/s]\u001b[A\n",
      "943it [00:00, 5110.40it/s]\u001b[A\n",
      " 10%|█         | 1/10 [00:19<02:58, 19.79s/it]\n",
      "0it [00:00, ?it/s]\u001b[A\n",
      "943it [00:00, 5154.22it/s]\u001b[A\n",
      " 20%|██        | 2/10 [00:39<02:37, 19.71s/it]\n",
      "0it [00:00, ?it/s]\u001b[A\n",
      "943it [00:00, 5027.65it/s]\u001b[A\n",
      " 30%|███       | 3/10 [00:58<02:16, 19.48s/it]\n",
      "0it [00:00, ?it/s]\u001b[A\n",
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      " 40%|████      | 4/10 [01:17<01:55, 19.33s/it]\n",
      "0it [00:00, ?it/s]\u001b[A\n",
      "943it [00:00, 4962.05it/s]\u001b[A\n",
      " 50%|█████     | 5/10 [01:36<01:36, 19.20s/it]\n",
      "0it [00:00, ?it/s]\u001b[A\n",
      "943it [00:00, 5076.40it/s]\u001b[A\n",
      " 60%|██████    | 6/10 [01:54<01:16, 19.01s/it]\n",
      "0it [00:00, ?it/s]\u001b[A\n",
      "943it [00:00, 5041.93it/s]\u001b[A\n",
      " 70%|███████   | 7/10 [02:13<00:56, 18.95s/it]\n",
      "0it [00:00, ?it/s]\u001b[A\n",
      "943it [00:00, 5050.76it/s]\u001b[A\n",
      " 80%|████████  | 8/10 [02:32<00:37, 18.90s/it]\n",
      "0it [00:00, ?it/s]\u001b[A\n",
      "458it [00:00, 4577.78it/s]\u001b[A\n",
      "943it [00:00, 4472.91it/s]\u001b[A\n",
      " 90%|█████████ | 9/10 [02:51<00:18, 18.91s/it]\n",
      "0it [00:00, ?it/s]\u001b[A\n",
      "943it [00:00, 5422.18it/s]\u001b[A\n",
      "100%|██████████| 10/10 [03:10<00:00, 19.02s/it]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Beta</th>\n",
       "      <th>RMSE</th>\n",
       "      <th>MAE</th>\n",
       "      <th>precision</th>\n",
       "      <th>recall</th>\n",
       "      <th>F_1</th>\n",
       "      <th>F_05</th>\n",
       "      <th>precision_super</th>\n",
       "      <th>recall_super</th>\n",
       "      <th>NDCG</th>\n",
       "      <th>mAP</th>\n",
       "      <th>MRR</th>\n",
       "      <th>LAUC</th>\n",
       "      <th>HR</th>\n",
       "      <th>F_2</th>\n",
       "      <th>Whole_average</th>\n",
       "      <th>Reco in test</th>\n",
       "      <th>Test coverage</th>\n",
       "      <th>Shannon</th>\n",
       "      <th>Gini</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>3.702446</td>\n",
       "      <td>3.527273</td>\n",
       "      <td>0.282185</td>\n",
       "      <td>0.192092</td>\n",
       "      <td>0.186749</td>\n",
       "      <td>0.216980</td>\n",
       "      <td>0.204185</td>\n",
       "      <td>0.240096</td>\n",
       "      <td>0.339114</td>\n",
       "      <td>0.204905</td>\n",
       "      <td>0.572157</td>\n",
       "      <td>0.593544</td>\n",
       "      <td>0.875928</td>\n",
       "      <td>0.181702</td>\n",
       "      <td>0.340803</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.077201</td>\n",
       "      <td>3.875892</td>\n",
       "      <td>0.974947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.1</td>\n",
       "      <td>3.703312</td>\n",
       "      <td>3.528128</td>\n",
       "      <td>0.290138</td>\n",
       "      <td>0.197597</td>\n",
       "      <td>0.192259</td>\n",
       "      <td>0.223336</td>\n",
       "      <td>0.210944</td>\n",
       "      <td>0.246153</td>\n",
       "      <td>0.347768</td>\n",
       "      <td>0.212034</td>\n",
       "      <td>0.581038</td>\n",
       "      <td>0.596328</td>\n",
       "      <td>0.884411</td>\n",
       "      <td>0.187030</td>\n",
       "      <td>0.347420</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.085137</td>\n",
       "      <td>3.957416</td>\n",
       "      <td>0.972784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.2</td>\n",
       "      <td>3.703825</td>\n",
       "      <td>3.528636</td>\n",
       "      <td>0.297137</td>\n",
       "      <td>0.201202</td>\n",
       "      <td>0.196067</td>\n",
       "      <td>0.228169</td>\n",
       "      <td>0.218026</td>\n",
       "      <td>0.252767</td>\n",
       "      <td>0.355655</td>\n",
       "      <td>0.219909</td>\n",
       "      <td>0.588904</td>\n",
       "      <td>0.598160</td>\n",
       "      <td>0.886532</td>\n",
       "      <td>0.190538</td>\n",
       "      <td>0.352756</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.094517</td>\n",
       "      <td>4.053212</td>\n",
       "      <td>0.969980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.3</td>\n",
       "      <td>3.704130</td>\n",
       "      <td>3.528939</td>\n",
       "      <td>0.303499</td>\n",
       "      <td>0.204749</td>\n",
       "      <td>0.199901</td>\n",
       "      <td>0.232829</td>\n",
       "      <td>0.225107</td>\n",
       "      <td>0.260797</td>\n",
       "      <td>0.363757</td>\n",
       "      <td>0.226825</td>\n",
       "      <td>0.599969</td>\n",
       "      <td>0.599964</td>\n",
       "      <td>0.888653</td>\n",
       "      <td>0.194073</td>\n",
       "      <td>0.358344</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.105339</td>\n",
       "      <td>4.147779</td>\n",
       "      <td>0.966948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.4</td>\n",
       "      <td>3.704313</td>\n",
       "      <td>3.529120</td>\n",
       "      <td>0.308908</td>\n",
       "      <td>0.208811</td>\n",
       "      <td>0.203854</td>\n",
       "      <td>0.237241</td>\n",
       "      <td>0.229614</td>\n",
       "      <td>0.266918</td>\n",
       "      <td>0.370758</td>\n",
       "      <td>0.232673</td>\n",
       "      <td>0.609385</td>\n",
       "      <td>0.602014</td>\n",
       "      <td>0.895016</td>\n",
       "      <td>0.197981</td>\n",
       "      <td>0.363598</td>\n",
       "      <td>0.999894</td>\n",
       "      <td>0.132035</td>\n",
       "      <td>4.259682</td>\n",
       "      <td>0.962989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.5</td>\n",
       "      <td>3.704422</td>\n",
       "      <td>3.529229</td>\n",
       "      <td>0.314316</td>\n",
       "      <td>0.211411</td>\n",
       "      <td>0.206768</td>\n",
       "      <td>0.240986</td>\n",
       "      <td>0.237124</td>\n",
       "      <td>0.273416</td>\n",
       "      <td>0.378307</td>\n",
       "      <td>0.239297</td>\n",
       "      <td>0.622792</td>\n",
       "      <td>0.603327</td>\n",
       "      <td>0.903499</td>\n",
       "      <td>0.200572</td>\n",
       "      <td>0.369318</td>\n",
       "      <td>0.999046</td>\n",
       "      <td>0.168831</td>\n",
       "      <td>4.411281</td>\n",
       "      <td>0.956648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.6</td>\n",
       "      <td>3.704488</td>\n",
       "      <td>3.529295</td>\n",
       "      <td>0.314634</td>\n",
       "      <td>0.206209</td>\n",
       "      <td>0.204818</td>\n",
       "      <td>0.240159</td>\n",
       "      <td>0.242489</td>\n",
       "      <td>0.273850</td>\n",
       "      <td>0.376438</td>\n",
       "      <td>0.238428</td>\n",
       "      <td>0.622042</td>\n",
       "      <td>0.600721</td>\n",
       "      <td>0.897137</td>\n",
       "      <td>0.197320</td>\n",
       "      <td>0.367854</td>\n",
       "      <td>0.996394</td>\n",
       "      <td>0.212843</td>\n",
       "      <td>4.621938</td>\n",
       "      <td>0.945932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.7</td>\n",
       "      <td>3.704528</td>\n",
       "      <td>3.529335</td>\n",
       "      <td>0.304136</td>\n",
       "      <td>0.187298</td>\n",
       "      <td>0.191990</td>\n",
       "      <td>0.228749</td>\n",
       "      <td>0.238305</td>\n",
       "      <td>0.256201</td>\n",
       "      <td>0.358807</td>\n",
       "      <td>0.226808</td>\n",
       "      <td>0.593897</td>\n",
       "      <td>0.591207</td>\n",
       "      <td>0.868505</td>\n",
       "      <td>0.182056</td>\n",
       "      <td>0.352330</td>\n",
       "      <td>0.983033</td>\n",
       "      <td>0.256854</td>\n",
       "      <td>4.898568</td>\n",
       "      <td>0.928065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.8</td>\n",
       "      <td>3.704552</td>\n",
       "      <td>3.529360</td>\n",
       "      <td>0.266384</td>\n",
       "      <td>0.147571</td>\n",
       "      <td>0.158660</td>\n",
       "      <td>0.194838</td>\n",
       "      <td>0.214485</td>\n",
       "      <td>0.209336</td>\n",
       "      <td>0.299850</td>\n",
       "      <td>0.184356</td>\n",
       "      <td>0.492852</td>\n",
       "      <td>0.571152</td>\n",
       "      <td>0.803818</td>\n",
       "      <td>0.146414</td>\n",
       "      <td>0.307476</td>\n",
       "      <td>0.936373</td>\n",
       "      <td>0.341270</td>\n",
       "      <td>5.257397</td>\n",
       "      <td>0.895882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.9</td>\n",
       "      <td>3.704567</td>\n",
       "      <td>3.529375</td>\n",
       "      <td>0.162354</td>\n",
       "      <td>0.076967</td>\n",
       "      <td>0.089233</td>\n",
       "      <td>0.114583</td>\n",
       "      <td>0.134657</td>\n",
       "      <td>0.113253</td>\n",
       "      <td>0.160868</td>\n",
       "      <td>0.085486</td>\n",
       "      <td>0.243590</td>\n",
       "      <td>0.535405</td>\n",
       "      <td>0.580064</td>\n",
       "      <td>0.078906</td>\n",
       "      <td>0.197947</td>\n",
       "      <td>0.800106</td>\n",
       "      <td>0.415584</td>\n",
       "      <td>5.563910</td>\n",
       "      <td>0.857396</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Beta      RMSE       MAE  precision    recall       F_1      F_05  \\\n",
       "0   0.0  3.702446  3.527273   0.282185  0.192092  0.186749  0.216980   \n",
       "0   0.1  3.703312  3.528128   0.290138  0.197597  0.192259  0.223336   \n",
       "0   0.2  3.703825  3.528636   0.297137  0.201202  0.196067  0.228169   \n",
       "0   0.3  3.704130  3.528939   0.303499  0.204749  0.199901  0.232829   \n",
       "0   0.4  3.704313  3.529120   0.308908  0.208811  0.203854  0.237241   \n",
       "0   0.5  3.704422  3.529229   0.314316  0.211411  0.206768  0.240986   \n",
       "0   0.6  3.704488  3.529295   0.314634  0.206209  0.204818  0.240159   \n",
       "0   0.7  3.704528  3.529335   0.304136  0.187298  0.191990  0.228749   \n",
       "0   0.8  3.704552  3.529360   0.266384  0.147571  0.158660  0.194838   \n",
       "0   0.9  3.704567  3.529375   0.162354  0.076967  0.089233  0.114583   \n",
       "\n",
       "   precision_super  recall_super      NDCG       mAP       MRR      LAUC  \\\n",
       "0         0.204185      0.240096  0.339114  0.204905  0.572157  0.593544   \n",
       "0         0.210944      0.246153  0.347768  0.212034  0.581038  0.596328   \n",
       "0         0.218026      0.252767  0.355655  0.219909  0.588904  0.598160   \n",
       "0         0.225107      0.260797  0.363757  0.226825  0.599969  0.599964   \n",
       "0         0.229614      0.266918  0.370758  0.232673  0.609385  0.602014   \n",
       "0         0.237124      0.273416  0.378307  0.239297  0.622792  0.603327   \n",
       "0         0.242489      0.273850  0.376438  0.238428  0.622042  0.600721   \n",
       "0         0.238305      0.256201  0.358807  0.226808  0.593897  0.591207   \n",
       "0         0.214485      0.209336  0.299850  0.184356  0.492852  0.571152   \n",
       "0         0.134657      0.113253  0.160868  0.085486  0.243590  0.535405   \n",
       "\n",
       "         HR       F_2  Whole_average  Reco in test  Test coverage   Shannon  \\\n",
       "0  0.875928  0.181702       0.340803      1.000000       0.077201  3.875892   \n",
       "0  0.884411  0.187030       0.347420      1.000000       0.085137  3.957416   \n",
       "0  0.886532  0.190538       0.352756      1.000000       0.094517  4.053212   \n",
       "0  0.888653  0.194073       0.358344      1.000000       0.105339  4.147779   \n",
       "0  0.895016  0.197981       0.363598      0.999894       0.132035  4.259682   \n",
       "0  0.903499  0.200572       0.369318      0.999046       0.168831  4.411281   \n",
       "0  0.897137  0.197320       0.367854      0.996394       0.212843  4.621938   \n",
       "0  0.868505  0.182056       0.352330      0.983033       0.256854  4.898568   \n",
       "0  0.803818  0.146414       0.307476      0.936373       0.341270  5.257397   \n",
       "0  0.580064  0.078906       0.197947      0.800106       0.415584  5.563910   \n",
       "\n",
       "       Gini  \n",
       "0  0.974947  \n",
       "0  0.972784  \n",
       "0  0.969980  \n",
       "0  0.966948  \n",
       "0  0.962989  \n",
       "0  0.956648  \n",
       "0  0.945932  \n",
       "0  0.928065  \n",
       "0  0.895882  \n",
       "0  0.857396  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from tqdm import tqdm\n",
    "result=[]\n",
    "for beta in tqdm([round(i,1) for i in np.arange(0,1,0.1)]):\n",
    "    model=RP3Beta()\n",
    "    model.fit(train_ui, alpha=1, beta=beta)\n",
    "    reco=pd.DataFrame(model.recommend(user_code_id, item_code_id, topK=10))\n",
    "    estimations_df=pd.DataFrame(model.estimate(user_code_id, item_code_id, test_ui))\n",
    "    to_append=ev.evaluate(test=pd.read_csv('./Datasets/ml-100k/test.csv', sep='\\t', header=None),\n",
    "            estimations_df=estimations_df, \n",
    "            reco=np.array(reco),\n",
    "            super_reactions=[4,5])\n",
    "    to_append.insert(0, \"Beta\", beta)\n",
    "    result.append(to_append)\n",
    "    \n",
    "result=pd.concat(result)\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "ename": "IndexError",
     "evalue": "list index out of range",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-10-8f1dc184fb30>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     12\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmetrics\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     13\u001b[0m     \u001b[0mdf\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Beta'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmetrics\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 14\u001b[0;31m     \u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxes\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mto_iter\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtitle\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmetrics\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m: list index out of range"
     ]
    },
    {
     "data": {
      "image/png": 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S6jagD9C1+rgdwABg27WeU9piIURDZMy2uL5JOyyEaIiu1Q7LkA0hhGiaegBHtdbJWusyYCUwtuYBWutftNbF1TcjAfcLuwArwAKwBMypWntcCCGEEEKIWiMFCSGEaJrcgPQatzOqt13NNGAzgNZ6F/ALkF39Z6vW+kAd5RRCCCGEEM2UFCSEEKKZU0pNAcKBt6tv+wKdqeox4QYMUkr1u8p9pyulYpRSMadOnaqvyEIIIYQQogloEnNIXEl5eTkZGRmUlJQYO4q4SVZWVri7u2Nubm7sKEI0RpmAR43b7tXbLqGUGgy8CAzQWpdWbx4HRGqtC6uP2Qz0Bn67/P5a64XAQoDw8PA/THopbbHxSBsqhBBC1K/mft5zM+ceTbYgkZGRgZ2dHd7e3iiljB1H3CCtNbm5uWRkZNC+fXtjxxGiMYoG/JRS7akqRNwD3FfzAKVUCPAJMFxrfbLGrjTgMaXUvwBF1YSW/7mZENIWG4e0oUIIIUT9a87nPTd77tFkh2yUlJTg4ODQ7N4ITYVSCgcHh2ZbXRTiVmmtK4Anga3AAeBrrfU+pdRrSqkx1Ye9DdgCq5VSCUqp9dXb1wDHgL1AIpCotd5wMzmkLTYOaUOFEEKI+tecz3tu9tyjyfaQAJrlG6EpkX8/IW6N1noTsOmybX+r8fPgq9yvEphRWznk/7JxyO9dCCGEqH/N+fP3Zl57k+0hIYQQQgghhBBCiIZLChJCCCGEEEIIIUQToJTimWeeuXh7/vz5vPrqqwC8+uqruLm50a1bN/z8/Bg/fjz79++/eGx5eTnPP/88fn5+hIaG0rt3bzZv3gxAYWEhM2fOpEOHDoSGhhIWFsann356y3mlINHIxMTE8NRTT111f1ZWFnfffXc9JhJCiOZl8eLFPPnkk0DVB/v8+fONnEgIIYQQooqlpSXffPMNp0+fvuL+p59+moSEBI4cOcLkyZMZNGgQF5Zuf/nll8nOziYpKYm4uDjWrVtHQUEBAI8++iitW7fmyJEjxMXFsWXLFvLy8m45rxQkjKyysvKGjg8PD+f999+/6n5XV1fWrFlzq7GM5kZ/H0IIcb201hgMBmPHqDMVFRXGjiCEEEIIIzMzM2P69Om89957f3rs5MmTGTp0KCtWrKC4uJhPP/2UDz74AEtLSwCcnZ2ZNGkSx44dIyoqijfeeAMTk6oSgqOjI3/9619vPe8tP0Ij8PcN+9iflV+rjxngas8rowOveUxKSgrDhw8nLCyMuLg4AgMDWbJkCQEBAUyePJkffviBefPm0aZNG1555RVKS0vp0KEDX3zxBba2tkRHRzNnzhyKioqwtLTkp59+IjY2lvnz57Nx40Z+/fVX5syZA1R1zdm+fTu5ubmMGjWKpKQkSkpKmDlzJjExMZiZmfHuu+9y++23s3jxYtavX09xcTHHjh1j3LhxvPXWW1d8DZWVlUybNo2YmBiUUkydOpWnn36agQMHMn/+fMLDwzl9+jTh4eGkpKSwePFi1q5dy7lz58jMzGTKlCm88sorACxbtoz333+fsrIyevbsyUcffYSpqSm2trbMmDGDH3/8kQULFtC3b99a/bcSQjQMxmiLU1JSGDZsGD179iQ2NpZJkyaxceNGSktLGTduHH//+98BWLJkCfPnz0cpRdeuXVm6dCkbNmzgjTfeoKysDAcHB5YvX46zs/MN5Xv//ff5+OOPMTMzIyAggJUrV/Lqq69ia2vLs88+C0BQUBAbN24EuOJnhrW1NbGxscydO5fCwkLatm3L4sWLcXFxYeDAgXTr1o0dO3Zw7733XtJFUwghhBDGY6zvoACzZs2ia9euzJs370+PDQ0N5eDBgxw9ehRPT0/s7e3/cMy+ffsIDg6+WIyoTc2iIGFMhw4d4vPPP6dPnz5MnTqVjz76CAAHBwfi4uI4ffo048eP58cff8TGxoZ///vfvPvuuzz//PNMnjyZVatW0b17d/Lz82nRosUljz1//nwWLFhAnz59KCwsxMrK6pL9CxYsQCnF3r17OXjwIEOHDuXw4cMAJCQkEB8fj6WlJf7+/syePRsPD48/5E9ISCAzM5OkpCQAzp49+6evOSoqiqSkJKytrenevTsjR47ExsaGVatWsXPnTszNzXniiSdYvnw5Dz74IEVFRfTs2ZN33nnnpn7HzVluYSk/HThJuHdrfBxtjR1HiAbpyJEjfPnll+Tn57NmzRqioqLQWjNmzBi2b9+Og4MDb7zxBr///jtt27a92P2wb9++REZGopTis88+46233rrhdurNN9/k+PHjWFpaXlf7eaXPjDlz5jB79my+/fZbHB0dWbVqFS+++CKLFi0CoKysjJiYmBv/xQigqudMhUFTVmGo+lNZ9Xdpjdvl1dsubq9xu6yikvJKTahXK8K82hj75QghhFHlnCvh54MnUQocbCxwsLXAwcYSB1sLbC3NmvUKFPXJ3t6eBx98kPfff/8P3yEvp7W+4cf/xz/+werVqzl58iRZWVk3GxNoJgWJ66ki1RUPDw/69OkDwJQpUy4Ot5g8eTIAkZGR7N+//+IxZWVl9O7dm0OHDuHi4kL37t0Brlip6tOnD3PnzuX+++9n/PjxuLu7X7J/x44dzJ49G4BOnTrh5eV1sSBxxx130LJlSwACAgJITU29YkHCx8eH5ORkZs+ezciRIxk6dOifvuYhQ4bgtkUygwAAIABJREFU4OAAwPjx49mxYwdmZmbExsZefD3nz5/HyckJAFNTUyZMmPCnjyv+z6mCUj79LZmlu1I5X141zKW7d2smhXswsqsL1hbN4r+2aGSM1RZ7eXnRq1cvnn32Wb7//ntCQkKAqsmZjhw5QmJiIhMnTqRt27YAtGlT9aUyIyODyZMnk52dTVlZGe3bt7/h5+7atSv3338/d911F3fdddefHn+lz4zhw4eTlJTEkCFDgKqeay4uLhfvc+HzpLk7U1RGRFwGcWlnKC2vKhpcLCpUVBcVLikkGCitLjbcxLnYH5ibKhY93J1+fo63/mBCCNGI5BWVsWlvNhsSs4hKybtqm2phZkJbGwscbKsKFG1sLGhra1lduKja1tbGkja2FjjYWGBlblq/L6SWGfM7KMBf/vIXQkNDeeSRR655XHx8POHh4fj6+pKWlkZ+fv4fvnsGBASQmJiIwWDAxMSEF198kRdffBFb21u/ICrfWurY5VXAC7dtbGyAqorUkCFD+Oqrry45bu/evX/62M8//zwjR45k06ZN9OnTh61bt/6hl8TVXBgXBFUFgauNPW7dujWJiYls3bqVjz/+mK+//ppFixZhZmZ2cSx2SUnJFV9jzdtaax566CH+9a9//eE5rKysMDVt3A1OfTmZX8In25NZvjuVsgoDY4JdeaC3F1HHz7A6Jp3n1uzh1fX7GB3syqTuHoR4tJJKtGj2ara3L7zwAjNmzLhk/wcffHDF+82ePZu5c+cyZswYtm3bdnGG6hvx3XffsX37djZs2MA//vEP9u7de0n7CZe2oVdrPwMDA9m1a9c1X19zpLUmOuUMK3ansikph7IKA94O1thYmmFhZoKFqQl2VmZYmplgbmpycZuF2f/9say+bV5ze/XPlhdvm2Juqv7vPtXbLtyuqDTw4KIoZiyNZcVjvejm0crYvxohhKhT+SXlfL/vBBsSs9hx9DSVBk0HRxv+ckdHRnZth42lGbmFZZwuLCW3sIzcogt/l5FbWEpuURlHThRyqrCUsoorz+9ka2lW3cOiqmDRtrqIcaHHRdvqIoaDjSWtrc0xM5XpEWtq06YNkyZN4vPPP2fq1KlXPCYiIoLvv/+ed955B2tra6ZNm8acOXP45JNPsLCw4NSpU2zbto2JEycSHh7OSy+9xOuvv46pqSklJSU31bviclKQqGNpaWns2rWL3r17s2LFCvr27Ut8fPzF/b169WLWrFkcPXoUX19fioqKyMzMxN/fn+zsbKKjo+nevTsFBQV/6G5z7NgxunTpQpcuXYiOjubgwYN069bt4v5+/fqxfPlyBg0axOHDh0lLS8Pf35+4uLjrzn/69GksLCyYMGEC/v7+TJkyBQBvb29iY2Pp0aPHHybR/OGHH8jLy6NFixasW7eORYsWYW1tzdixY3n66adxcnIiLy+PgoICvLy8bubX2uycyC/hf9uO8VVUGhUGzdhurjx5u+/FYRphXm14fIAPMalnWBWdzrcJWayMTsfPyZbJ3T0YF+KGg63lnzyLEE3bsGHDePnll7n//vuxtbUlMzMTc3NzBg0axLhx45g7dy4ODg7k5eXRpk0bzp07h5ubGwBffvnlDT+fwWAgPT2d22+/nb59+7Jy5UoKCwvx9va+OGdEXFwcx48fv3ifK31m+Pv7c+rUqYvby8vLOXz4MIGBxr3yYkznisuJiMvgq6g0jpwsxM7SjHu6e3BfT086tftjj8L6sGRqDyZ8/DuPfBHF6sdvw9dJhtEJIZqW82WV/HSwqgjxy6FTlFUYcG/dgun9fRjd1ZXOLnaXFNZdWl57qABUFZaLyiovFilyC/+vYFGzmJGeV0xC+lnyisqoNPzxS7BS4GRnyf+7szNju7nV6utuzJ555hk+/PDDS7a99957LFu2jKKiIoKCgvj5559xdKzq3ffGG2/w0ksvERAQgJWVFTY2Nrz22msAfPbZZzz33HP4+vri4OBAixYtrjoP4Y2QgkQd8/f3Z8GCBUydOpWAgABmzpx5ydU4R0dHFi9ezL333ktpaSlQ9Ubo2LEjq1atYvbs2Zw/f54WLVrw448/XvLY//nPf/jll18wMTEhMDCQESNGkJ2dfXH/E088wcyZM+nSpQtmZmYsXrz4kp4R1yMzM5NHHnnk4tW8Cz0cnn32WSZNmsTChQsZOXLkJffp0aMHEyZMICMjgylTphAeHn7xdQ0dOhSDwYC5uTkLFiyQgsSfyD53nv9tO8bK6HQqDZrxIW7Mut0X77Z/vCKqlKK7dxu6e7fhldEBfLcnm1Ux6bzx3QHe3HyQwZ2dmdzdg/4dHTE1kV4TovkZOnQoBw4coHfv3gDY2tqybNkyAgMDefHFFxkwYACmpqaEhISwePFiXn31VSZOnEjr1q0ZNGjQJYWD61FZWcmUKVM4d+4cWmueeuopWrVqxYQJE1iyZAmBgYH07NmTjh07XrzPlT4zLCwsWLNmDU899RTnzp2joqKCv/zlL82uIKG1Ji7tDMt3p/HdnmxKKwwEe7TirQldGRVs/KFqTvZWLJ3ak7s/3sWDn+8m4onbrutkXAghGrLSikp+O3yaDXuy+GH/CYrLKnGys+T+np6MCXal2y32xlVKYWtphq2lGV4Of97jz2DQnDtfTm5RKacLyy7pffHr4VPMWZnA/qx85g3v1GzPdwsLCy/+7OzsTHFx8cXbr7766jV7fFpYWPDWW29dsdBgb2/PJ598UqtZAVRtdLO44gMrNRz4L2AKfKa1fvOy/XOBR4EK4BQwVWudWmO/PbAfWKe1fvJazxUeHq4vn9DrwIEDdO7cuTZeyk1LSUm5uOJFc7F48WJiYmL+UIm7WQ3h39EYMs+e56NfjrI6JgOD1twd5s4TA33xdLC+4cc6fKKAr6PT+SY+k7yiMtrZWzEhzI1J4R7X1fCLm6eUitVahxs7R31pqG1xY1EXnxlN4fd/7nw56+IzWbE7jUMnCrC1NGNsN1fu6+lJoGtLY8f7g6TMc9y7MBLnllasntGb1jYWxo7U7DWntvhK7bAQN6qi0kBkch7rEzPZkpRDfkkFrazNGRHkwphgV3q0b9Mgv+yXVRh4feN+lkam0s+vLR/cG0Ir6/ptg5vC5+6tutLv4FrtcJ1cTlBKmQILgCFABhCtlFqvtd5f47B4IFxrXayUmgm8BdScmet1YHtd5BOioUrPK+ajbcdYE5sOwMRwD54Y2AH31jdeiLigo7MdL40KYN7wTvx88ASrotP537ZjLPjlGL182jAp3IMRQS60sJB5PIQQDYPWmoT0s6zYncaGPVmUlBvo6t6SN8d3YXSwKzaWDbeDZ5BbSz59KJwHF0XxyOJoVjzW0+i9N4QQ4s8YDFW90NYnZrFpbzanC8uwtTRjaKAzo4Nd6evbFvMGPkeDhZkJr98VRKCrPS9/m8TYBTtZ+EA4/u3sjB1NXENdfUL2AI5qrZMBlFIrgbFU9XgAQGv9S43jI4EpF24opcIAZ2AL0Ggr2t7e3o2qd0TPnj0vDhu5YOnSpXTp0uW6H+Phhx/m4YcfruVkTV9abjELfjlKRFwGJkpxT3dPZg7sgGur2uvua2FmwvAgF4YHuZB97jzfxGXydUw6c79O5JVv9zGmmyuTu3vQxa2lTIQpxA2aNWsWO3fuvGTbnDlz/nRm65oa22dGXSgoKWddQhYrdqdxIDsfawtTxoW4c39PT4LcGl5viKvp5ePAB/eGMHNZLI8vi+OzB8OxMGvYJ/JCiOZHa82+rHzWJ2axMTGLrHMlWJqZMLizM6ODXRjo79QoV7q4p4cnfs52zFwWy7iPdvLupGCGB7n8+R1rida62Z5L38zoi7oqSLgB6TVuZwA9r3H8NGAzgFLKBHiHqgLF4KvdQSk1HZgO4OnpecVjmvOb4Wbs3r3b2BEuUVfDiRqS46eLWPDLUdbGZ2JqopjSy4sZA3zqfNyxS8sWzLrdl5kDOrD7eB5fx6SzJjaD5bvT6NTOjknhVRNhSldjURuaQ1u8YMECY0f4g8bUhu7JOMvyyDTWJ2ZxvrySQFd7/jEuiLHd3LBtwL0hrmVYYDv+Nb4Lf43Yy7OrE/nP5G6YNMAuzkKI5ufIiQI2JGaxYU82x08XYW6q6O/nyLzhnRgc4Nxo292awrxas2F2X2YsrSoMPzXIl78M7ljn7bCVlRW5ubk4ODg0+XOfy2mtyc3Nve5VHy8w+rtNKTWFql4QA6o3PQFs0lpnXOsfUWu9EFgIVePlLt/fnN8MTcHNvqEbi2OnClnw81HWJWRibmrCQ729mTHAB2f7+n29JiaK3h0c6N3Bgb+PDWR9QhZfx6Tz2sb9vLn5IEMCnZkU7kFf37YNcqygaPikLTaOxtCGFpZW8G1CJl9FpZGUmU8Lc1PGBFfNDdHVvWn01Jrc3ZO8onL+veUgbWwseGV0QJN4XUKIxictt5gNe7LYkJjFwZwCTBT07uDAjP4+DA9qV+9zLdQHZ3srVs3oxcvrknj/56Psy8rnvXu6YW9lXmfP6e7uTkZGBqdOnaqz52jIrKyscHd3v6H71FVBIhPwqHHbvXrbJZRSg4EXgQFa6wtjBXoD/ZRSTwC2gIVSqlBr/fyNBGjub4am4Gbe0A3d0ZMFfPDzUTYkZmFhZsK0vu15rL8PTnbG/9Jgb2XOlF5eTOnlxYHsfL6OSWdtfCbf7cnGtaUVd4d7MDHMHY82Nz+fhWh+pC02nobahiZlnmP57jTWJ2RSVFZJp3Z2vD42kLEhbnV6kmgsjw/wIbewlM92HMfBxoLZd/gZO5IQopnIOVfCd3uz2ZCYRUL6WaCq58DfxwQyoku7BnH+WdcszUz594SuBLm15LUN+7lrwU4+fTCcDo51szSzubk57du3r5PHbqrqZJUNpZQZcBi4g6pCRDRwn9Z6X41jQoA1wHCt9ZGrPM7DVE18ecOrbAjRkBzKKeCDn4/w3d5sWpib8kBvLx7r50Nb2xtbhrW+lVZU8uP+k6yKSee3I6fQGvr4OjAp3INhge0a5bjC+tScZnYHaYvF1RWVVrAhMYsVUWnsyTiHlbkJo7pW9YYIucUl4xoDg0Hz7OpEvonP5B/jgri/pyx5XZ+aU1ss7bBIzS1iS1IOW/blEJ9WVYQIdLVnTLArI7u63NJE6Y1dZHIus5bHUVZh4D/3dOOOzs7GjtRs1PsqG1rrCqXUk8BWqpb9XKS13qeUeg2I0VqvB96mqgfE6uoTkTSt9Zi6yCOEsRzIzueDn4+waW8ONhamPD6gA4/186FNI5mbwdLMlJFdXRjZ1YXMs+dZE5PB6th05qxMwMnOko2z++JUz8NMhBCNx/6sfFZEpbIuPovC0gr8ne34+5hA7gpxo2WLptcb4mpMTBT/vrsrZ8+X89K6JFpbW3Bnl/qbYE0I0XRprTl0oqCqCJGUw8GcAgC6uLXk2aEdGdHFpc56AzQ2vXwcWD+7LzOWxvDokhieGdKRWbf7NvmieENXJz0k6ptUg0VDsy/rHO//dISt+05ga2nGw7d5M61v+yYxSaTBoPn18CmmfhnNzAEdmDe8k7EjNVjN6aocSFssqhSUlLNxTzarotNJSD+LpZkJI7u6cH9PT0I9WzfrE7/zZZU88Plu9mSc44tHutPHt62xIzULzaktlna4eTAYNIkZZ9myL4etSTmk5BajFHT3asOwoHYMDXCWIbbXcL6skhe+2cO6hCxGBLVj/sTgBr2cdFNQ7z0khGiu9mac478/HeHHAyewszLjqTv8mNanPS2tm86VQBMTxe2dnBge2I5lkak8cbtvk5iNWQhx8wwGTWRyLqtjM9iclE1JuQE/J1v+NiqA8aFuTXKytJvRwsKUzx/qzqRPdjF9SQxfTe9FV/dWxo4lhGgEKioNRKXksTUph637TpCTX4KZieI237ZM79+BIQHOONo17KHADUULC1Pem9yNILeW/HPTAZJPFbHwwTC8HGyMHa1Zkm8RQtSC7HPneXndPn48cAJ7KzOeHtyRh/t4N+kuydP7+7A5KYdV0elM6yuT9wjRHKXnFbMmNoOIuAwyzpzHzsqMCaHuTAz3ILiJrJRR21pam7NkWg8m/O93Hv4imjWP98ZHulMLIa6gpLySnUdPsyUphx8PnOBMcTlW5iYM6OjIX4P8GdTJuUmfa9YlpRSP9vOhUzt7nvwqjjEf7uTD+0Lo5+do7GjNjhQkhLgFWmvWJ2bx8rokKgyaZ4d25KHbvLFrgjPFXy7EszXdvVuzaMdxHurthZmpibEjCSHqwfmySjYnZbM6JoNdybkoBX192/LcMH+Z7PY6OdtbsXRaT+7+3+888HkUETNvo11LmY9HCFG1JPK2QyfZkpTDLwdPUlRWiZ2VGYM7OzMssB0DOjrSwkLa2drS168t62f1ZfrSGB5aFMXzIzrxWD8fKajXIylICHGTzhaX8eK6JL7bk02YV2venRTc7Lp6Te/fgceWxPDd3mzGdnMzdhwhRB3RWhObeoY1sRls3JNNYWkFXg7WPDOkI+PD3HFr1cLYERud9m1t+HJqD+5ZGMmDi3bz9YzeMrRFiGbqTFEZPx44wdZ9OWw/cpqyCgNtbS0Y082N4UHt6O3jgIWZXPipK54O1nzzxG08t3oP/9x0kH1Z+bw5vqsUfuqJFCSEuAnbDp1k3po9nCku47lh/jw+oAOmJs2vknpHJyd8HG349LdkxgS7SjVZiCYm51wJEXEZRMRmkHy6CGsLU+7s4sLEMHd6tG8j/+dvUZBbSxY+GMbDi6KZujia5Y/2khNgIZqJE/klfL+vannOyOQ8Kg0at1YtmNLTi+FB7Qjzat0szy2NxdrCjA/vCyFgmz3zvz/E0ZOFfPJAWLNeJrW+SEFCiBtQXFbBPzcdYFlkGh2dbfnike4EurY0diyjMTFRPNbPhxe+2cuuY7ncJjPGC9HolVZU8sP+E6yOyeC3I6cwaOjh3YbHB3ZgZBcXmYm8lt3WoS3v39uNJ5bHMXN5LJ8+GI65DIEToklKzS2qWp5zXw7xaWcB6OBow+MDfBge6EKQm70Ueo1IKcWs230JcLHnqZXxjPlwJwvuC6V3BwdjR2vS5KxCiOsUn3aGuV8nkpJbxGP92vPMUH8ZKw2MC3Hjne8P8cn2ZClICNFIaa1JysxndWw63yZkce58OS4trXhioC93h7nj3bZ5DUerb8ODXPjHuC688M1e5q3ZwzsTgzGRK6NCNAkZZ4pZF5/Jxj3ZHMwpAKCLW8vqeXec8XWyM3JCcbnbOznx7aw+TF8ay5TPd/O3UQE82NtLikV1RAoSQvyJ8koDH/x0hAXbjtHO3ooVj/aSSmkNVuamPNTbm3d+OMyhnAL828kHqxCNRW5hKWvjM1kTm8HBnAIszEwYFtiOiWHu9PFtK92F69G9PTzJKyrj7a2HaG1twcujOsvJrxCNVFFpBZv2ZvNNXCa7knMB6O7dmpdHBTA0wBmPNjIMoKHzcbRl7RO38fSqRF5Zv4+kzHO8fleQXIysA1KQEOIajp4s4OlViezNPMeEUHdeGROAfTNYQeNGTenlxUfbjrFwezLvTAo2dhwhxDWUVxrYdugUq2PS+fngSSoMmmD3lrx+VxBjurrS0lraOGN5YmAHTheWsmjncRxsLZh1u6+xIwkhrpPBoNmVnEtEbAabk3I4X16Jt4M1c4d0ZFyImxQhGiE7K3MWPhDGf386wn9/OsLhk4V8MiVMVkWqZVKQEOIKDAbNl7tSeHPzQawtTPl4SijDg1yMHavBam1jweTuHizfncpzw/yloW4glFLDgf8CpsBnWus3L9s/F3gUqABOAVO11qnV+zyBzwAPQAN3aq1T6i+9qG2HTxSwOiadtfGZnC4so62tBY/08WZiuAcdnaVnU0OglOLlkQGcqe4p0cbGgnt7eBo7lhDiGo6dKiQiNoN18ZlknSvBzsqMu0LcuDvMjVDP1tLTqZEzMVE8PaQjAa72zF2VwOgPd/DxlFDCvNoYO1qTIQUJIS6TdfY8z61JZOfRXAZ1cuLNCV1wspMv2H9mWt/2LNmVwhe/H+eFEZ2NHafZU0qZAguAIUAGEK2UWq+13l/jsHggXGtdrJSaCbwFTK7etwT4h9b6B6WULWCox/iilpwvqyQiLoPVMekkZpzDzEQxqJMTE8M9GOjvKJMnNkAmJoq3JwZz9nw5L67dS2trcymIC9HAnC0uY8OebCJiM0hIP4uJggEdHXnhzs4MCXCWbv1N0LDAdqyd1YfpS2K4Z2Ekr40NkoJxLZGChBDVtNZ8m5DFy98mUWnQ/Gt8F+7p7iGV7evk0caaEV1cWBGZxpO3+2InQ1uMrQdwVGudDKCUWgmMBS4WJLTWv9Q4PhKYUn1sAGCmtf6h+rjC+gotakdxWQXLI9P4ZHsypwtL6dTOjpdHBTC2myttbS2NHU/8CXNTEz66P5Qpn+3mqa8SWDzVnNs6yKTBQhhTeaWBXw+dIiIug58OnKSs0kCndna8eGdnxoa4ysWrZqCjsx3fzurLUyvjeeGbvSRlnuOV0YFYmElx/1ZIQUII4ExRGS+tS+K7vdmEebXm3UnBeDnIrPI3akZ/H77bk82q6HQe7edj7DjNnRuQXuN2BtDzGsdPAzZX/9wROKuU+gZoD/wIPK+1rqyLoKL2FJdVsHRXKgu3J5NbVEZf37Y8dUco3b2l23BjY21hxqKHuzPx411MXxLLyum9CHJrvstMC2EMWmv2ZeUTEZfB+oQscovKcLCxYEovL8aHuhHoKst0Njctrc1Z9HB33t56iI9/PcbhEwV8dH8YjnZS7L9ZUpAQzd62QyeZt2YPZ4rLmDfcnxn9O8jM8jepq3srerZvw6Idx3noNm/pDt5IKKWmAOHAgOpNZkA/IARIA1YBDwOfX+G+04HpAJ6e0nXRWIpKK1gamcqn1YWIfn5t+ctgPxnj2si1srZgybQe3P2/XTy0KIo1M2+jvSzBKkSdO5lfwrcJWUTEVa9AZGrCHZ2dmBDqzgAZ7tbsmZoonh/RiUBXe55bk8jYD3ew5en+MvH9TZKChGi2issq+OemAyyLTKOjsy1fPNKdQFe5+nSrZgzwYeriGDbuyWJciLux4zRnmVRNSHmBe/W2SyilBgMvAgO01qXVmzOAhBrDPdYBvbhCQUJrvRBYCBAeHq5r8wWIP1dYWsGSXSl89ttx8orK6N/RkTl3+BHm1drY0UQtcWnZgiXTejDx41088PluImbehrO9dA0XoraVlFfyw/4TRMRlsP3wKQwaunm04vW7ghjd1YVW1hbGjigamNHBVcMg7/00ko2J2dzXUy7M3AwpSIhmKS7tDM98nUhKbhGP9WvPM0P9ZQKiWjKwoxN+TrYs3H6cu7q5SVdG44kG/JRS7akqRNwD3FfzAKVUCPAJMFxrffKy+7ZSSjlqrU8Bg4CY+oktrkdBSTlLdqXy6W/JnC0uZ6C/I0/d4UeopxQimqIOjrYsfqQ79y6M5MHPo/h6Rm9ZnlWIWqC1Jjb1DBFxGWzck01BSQUuLa14fEAHxoe64+tka+yIooHr5dMGPydbIuIypCBxk6QgIZqV8koDH/x0hA9/OYpLyxaseLQXvTs4GDtWk2Jionisnw/zIvaw4+hp+vk5GjtSs6S1rlBKPQlspWrZz0Va631KqdeAGK31euBtwBZYXV04StNaj9FaVyqlngV+UlU7YoFPjfNKRE0FJeV8+XsKn+04ztnicm73d2TO4I5082hl7GiijnV1b8XCB8N55Itopn0ZzdJpPWlhIYV0IW5Gel4xa+Mz+SYug5TcYlqYmzIiqB0Twtzp5eMgQ3fFdVNKMSHMnTc3H+T46SIZVncTpCAhmo2jJwt4elUiezPPMSHUnVfGBMhYrzoyNsSVt78/xMLtyVKQMCKt9SZg02Xb/lbj58HXuO8PQNe6SyduRH5JOYt3pvD5juOcO1/OHZ2ceOoOP4KlENGs9PFty3uTu/HkV3HMWhHHJw+EyVh2Ia5Tfkk5W5JyiIjNYPfxPAB6+zgw63ZfRnRxwdZSvhaJmzMuxI23thzkm7gMnhnqb+w4jY78zxNNnsGgWfx7Cv/echAbSzM+nhLG8KB2xo7VpFmamfLwbd68vfUQ+7PyCXC1N3YkIRqlc+fL+WLncRbtOE5+SQWDOzsz5w4/urjLfDfN1ciuLpwpDuKldUn8NWIP8+8OxkSu5gpxRReW6lybkMmP+09QWmHA28GaZ4Z0ZFyoG+6trY0dUTQBzvZW9PVz5Ju4TJ4e3FHa5BskBQnRpGWdPc9zaxLZeTSXOzo58a8JXWSd6HoypacXC345yqe/JfPe5G7GjiNEo3LufDmLdhxn0c7jFJRUMCSgqhAhyz4KgCm9vMgrKuPdHw7j62TLEwN9jR1JiAZDa018+lnWxWeyITGLM8XltLGx4J7uHtwV4kY3j1Yyv5WodRNC3ZizMoHI47nc1qGtseM0KlKQEE2S1pp1CZn87dt9VBo0b47vwuTuHvIBVI9aWptzT3dPluxK4blh/ri2amHsSEI0eGeLy1i04zhf7EyhoLSCYYHOPHWHn6wAJP5g9iBfolPyWB6ZxuP9O8gVOdHspZwuYm18JusSMknNLcbSzIQhAc6MC3Gjf0dZqlPUrWGB7bCzNCMiNlMKEjdIChKiyTlTVMZL65L4bm82YV6teXdSMF4OMsGMMUzt682Xu1L4YudxXhwZYOw4QjRYZ4vL+Oy34yz+PYXC0gpGBLVj9iA/Ge4krkopxbgQN+Z+nUh8+hnCvNoYO5IQ9S6vqIyNe7JYG59JfNpZlKqaF+LJ230ZHtQOO5krTNQTK3NTRnZ1YX1iFq+NDcRG5iS5bvKbEk1G8qlClu9OY3VMOufLK5k33J8Z/TvITMlG5N7ampFdXPgqKp3Zd/jJJKJCXOZMURmf7Ujmy99TKSyt4M4uVYWIzi5SiBB/bkiAM5ZmJmxIzJaCRAOmlBoO/Jdc2CXNAAAgAElEQVSqFY8+01q/edn+x4FZQCVQCEzXWu9XSnkDB4BD1YdGaq0fr6/cDVVJeSU/HjjBuvhMth06RYVB06mdHS+M6MSYbq64tJQemcI4JoS5szI6nS1JOUwIczd2nEZDChKiUauoNPDTwZMsi0zltyOnMTNRjOjiwhMDO8gJfQMxvb8P6xOz+Gp3GjMGdDB2HCEahLyiMj79LZklv6dQXF7JnV1ceGqQH/7t7IwdTTQidlbmDOrkxMY92bw8KkAK8A2QUsoUWAAMATKAaKXUeq31/hqHrdBaf1x9/BjgXWB49b5jWutmPxGTwaCJPJ7LuvhMNu/NoaC0Amd7S6b1bc9dIW5yzicahHCv1ng5WBMRlyEFiRsgBQnRKJ0qKGVVdBordqeRda4El5ZWPDOkI5N7eMiklQ1MkFtLbuvgwBc7U3ikT3sszGQMp2i+cgtL+fS34yzZlcL58kpGdXVl9iBfOjpLIULcnNHBrmxOyiEyOZc+vjJuuQHqARzVWicDKKVWAmOBiwUJrXV+jeNtAF2vCRuwQzkFfBOfwfqELLLPlWBracbwoHaMC3Gjl4+DFOFEg6KUYnyIO//56TCZZ8/jJvOnXRcpSIhGQ2tNTOoZluxKZUtSNuWVmr6+bfnb6EAGd3bCTCYrarCm9/fh4S+iWZ+Yxd1SMRbNUHpeMUsjU1m6K5WSikpGVxci/KQQIW7RoE5O2FiYsiExSwoSDZMbkF7jdgbQ8/KDlFKzgLmABTCoxq72Sql4IB94SWv9Wx1mbRBO5JfwbUIma+OzOJCdj6mJYkBHR/7fnZ0Z3NmZFhamxo4oxFWND3XjvR8PszYugycH+Rk7TqMgBQnR4BWVVrA2PpNlkakczCnAzsqMB3p5c38vTzo42ho7nrgOAzo64u9sx6fbk5kQ6iarnYhmodKg+eXgSZbtTuXXw6dQwJhgV54c5Ievk7RdonZYmZsyNLAdm5NyeG1skPRCa6S01guABUqp+4CXgIeAbMBTa52rlAoD1imlAi/rUYFSajowHcDT07Oek9eOwtIKtiTlsC4+k53HTqM1dPNoxd/HBDKqqwsOtpbGjijEdfFoY03P9m2IiMtk1u2+cs57HaQgIRqsIycKWBaZSkRcJoWlFQS42PPm+C6M6eaKtYW8dRsTpRSP9ffh2dWJ/Hr4FAP9nYwdSYg6c7KghK+j0/kqKp3Ms+dxsrNk9iA/7u3hIZOtiToxOtiFtfGZ/HbkFHd0djZ2HHGpTMCjxm336m1XsxL4H4DWuhQorf45Vil1DOgIxNS8g9Z6IbAQIDw8vNEM9yivNLDjyGm+ic/kh/05lJQb8GxjzexBftzVzRUfuegkGqkJYe7MW7OHuLSzhHm1NnacBk++1YkGpbzSwA/7T7B0Vyq7knOxMDVhZFcXpvTyItSzlVQZG7Exwa68vfUgC7cnS0FCNDlaa3Yl57I8Mo2t+3KoMGj6+Drw0sjODA5wxlyGlIk61NfXkZYtzNmQmCUFiYYnGvBTSrWnqhBxD3BfzQOUUn5a6yPVN0cCR6q3OwJ5WutKpZQP4Ack11vyOnL0ZCEro9JYG59JblEZrazNuTvMnXEh7nKuJ5qEO7u48Mq3+4iIy5CCxHWQgoRoEE7kl7BidxpfRaVxsqAUt1YtmDfcn8nhHtJNr4mwMDPhkT7teXPzQZIyzxHk1tLYkYS4ZeeKy1kTl8Hy3akknyqiZQtzHr7Nm/t6esrVPVFvLMxMuLNLO9YnZHG+rFLG2DcgWusKpdSTwFaqlv1cpLXep5R6DYjRWq8HnlRKDQbKgTNUDdcA6A+8ppQqBwzA41rrvPp/FbeupLySTXuzWRmVTlRKHmYmisGdnZkQ5s6Ajo4y1Eg0KRcmX92YmMXfRgVgZS5t8rVIQUIYzYUrissiU9m67wSVBs2Ajo78a7wXA/2dZObkJui+np58+PNRFm5P5v17Q4wdR4iblph+lmWRqWzYk0VJuYEQz1bMnxjMqK4ucuIhjGJ0V1e+ikrnl0MnubOLi7HjiBq01puATZdt+1uNn+dc5X4RQETdpqtbB3PyWRmVzjdxGeSXVODtYM3zIzoxIdQdRzu54CSargmh7qyNz+THAycY1dXV2HEaNClIiHqXX1LO2rhMlkamcvRkIa2szZnWtz339/TEy8HG2PFEHbK3MufeHh4s2pnCvOH+uLe2NnYkIa5bcVkF6xOyWL47jb2Z57C2MGVciDv39/SUHj/C6Hr6ONDW1pL1CVlSkBBGVVRawcY9WXwVlU5C+lksTE0YHtSOe3p40NvHQYZkiGahdwcHXFpaERGbIQWJPyEFCVFvDubks2RXKuviMykuqyTYvSVv392V0cGuckWxGXmkT3u+2JnCoh0p/G10gLHjCPGnjpwoYPnuNCLiMigoqcDf2Y7XxwZyV4gbdlbmxo4nBACmJopRXV1YEZVGQUm5vDdFvdubcY6votNYn5BFYWkFvk62vDwqgPEhbrS2sTB2PCHqlamJYlyIG59sT+ZkQQlOdlbGjtRgSUFC1KmyCgObk7JZFplKdMoZLM1MGB3sygO9vAj2aGXseMIIXFu1YHSwKyuj05hzhx8treWkWTQ8ZRUGtuzLYVlkKlHH87AwNWFEl3ZM6eVFuFdrucInGqTRwa4s/j2FH/afYHyou7HjiGYgv6ScbxOyWBmVxr6sfKzMTRjZxZV7e3gQJm2laOYmhLnz0bZjfBufxWP9fYwdp8GSgoSoE+WVBj7fcZzPfkvmdGEZXg7WvHhnZ+4Oc5cqueCxfj6sjc9keVQqTwz0NXYcIS5KzytmRVQaq2PSOV1YhkebFjw/ohMTw9xlgl3R4IV6tsKtVQvWJ2ZJQULUGa01cWlnWRmVxsY92Zwvr6Sziz2vjQ1kbDc3WraQCw1CAHRwtKWbRysi4jJ4tF97KdBdhRQkRK3bl3WOeWv2sC8rnwEdHXmkjzf9/RwxkUkqRbUAV3v6+bXli50pTOvbHkszGbIjjKfSoNl26CTLIlPZdvgUChjUyZkpvTyl7RKNilKKUcEufP7bcfKKymgjFwBELTpbXMba+ExWRqVz6EQB1ham3BXiyj3dPenq3lK+bAlxBRPC3Hl5XRL7svJlvqmrkIKEqDWlFZV88NNRPv71GK2sLfh4SijDg2RiLXFl0/v78MDnUXwbn8Wk7h7GjiOaoZMFJXwdnc5XUelknj2Po50ls2/35Z4enri2amHseELclDHBrnzyazJbknK4r6enseOIRk5rze7jeayMSmNTUg5lFQaC3Vvyr/FdGB3siq2lfJUQ4lpGd3Xh9Q37iYjLkILEVUgrImpFXNoZ5q3Zw9GThUwIdeflUZ1pZS1XZsTV9fVtS2cXexb+lszdYe5yFVrUC4NBE5mcy/KoNLYm5VBh0PTxdeDFkZ0ZEuCMuamJsSMKcUsCXOzxcbRhQ2KWFCTETcstLCUiLoOV0ekknyrCztKMyeEe3NPDg0BX+VIlxPVqZW3B4AAn1idk8f/u7CznGVcgBQlxS4rLKpi/9TBf/H4cF3srFj/SnYH+TsaOJRoBpRTT+7fn6VWJbDt8kkGdnI0dSTRhabnFrInLICI2g8yz52nZwpyHbvPmvp6edHC0NXY8IWqNUorRXV15/+cjnMgvwdleZnYX18dg0Px+LJevotP4fl8O5ZWaMK/WzJ/oy8guLrSwkOGVQtyMCaHubNqbw7ZDpxgSIOe7l5OChLhpvx89zfPf7CUtr5gHennx1xGdpOueuCGjurry1pZDfPJrshQkRK0rLK1g095s1sRmEHU8D6WqeubMG+7PsMB2stywaLJGB7vy35+O8N2ebKb2bW/sOKKBO5lfwurYDFZFp5OWV0wra3Me6OXNPT086OhsZ+x4QjR6/Ts60tbWgojYDClIXIF8exQ3LL+knH9tOsBXUel4O1izanovevo4GDuWaITMTU2Y2qc9/9h0gMT0s7IUrLhlBoMm8ngua2Iz2Lw3h/PllbRva8Nzw/wZF+Imc0OIZsHXyZYAF3s27MmSgoS4pl8OneTRL2OoNGh6+bThmaEdpWArRC0zNzVhbDc3luxK4UxRmaw4eBkpSIgb8tOBE7y4NomTBSXM6O/D00M6yoeWuCX39PDg/Z+OsPC3ZBbcF2rsOKKRSs0tIiIu8+KQDDtLM+4KceXuMHdCPVvL7O+i2Rkd7Mq/txwkPa8YjzbWxo4jGqgwr9Y81s+Hyd09aN/WxthxhGiyJoS68/mO42zYk8WDvb2NHadBkYKEuC55RWX8fcM+vk3Iwt/Zjk8eCJOr2aJW2FmZc18vTz7dniwnzuKGFJZWsGlP9ZCMFBmSIURNo7q68O8tB9mwJ4snBvoaO45ooOytzHl+RCdjxxCiyQtwtaeziz0RsRlSkLiMFCTENWmt+W5vNq98u4/8knLm3OHHrNt9sTCTGWJF7XnktvYs2nGcz3cc59UxgcaOIxqwC6tkrInNYHNS1ZAMn+ohGeND3XBpKUMyhADwaGNNqGcrNiRmS0FCCCEagAmhbrzx3QGOnizA10nmZ7lAChLiqk7kl/DyuiS+33+Cru4tWX53Tzq1szd2LNEEtWtpxZhgN1ZFpzPnDj8ZWyf+IDW3iIjYDCLiMmsMyXCrHpLRSoZkCHEFo4Nd+fuG/XLyK4QQDcDYbm78a/NB1sRmSs+kGqQgIf5Aa83qmAxe/24/ZRUGXhjRiWl922Mm6+aKOjS9vw8RcRks353Kk4P8jB1HNAAyJEOIWzOyiwuvb9zP+sRs5g6RgoQQQhiTo50lAzs6sjY+g+eG+WNqIhdTAOrkG6ZSarhS6pBS6qhS6vkr7J+rlNqvlNqjlPpJKeVVvb2bUmqXUmpf9b7JdZFPXF16XjEPLopiXsQeOrezZ/OcfswY0EGKEaLO+bezY0BHRxb/nkpJeaWx4zQJN9sW19hvr5TKUEp9WF+ZDQbN70dPM3dVAt3f+JF5EXs4XVjKc8P8+f35QSyd1pOx3dykGCHEdXCyt6KXjwMbE7PQWhs7jhBCNHsTwtw5kV/KzqOnjR2lwaj1HhJKKVNgATAEyACilVLrtdb7axwWD4RrrYuVUjOBt4DJQDHwoNb6iFLKFYhVSm3VWp+t7ZziUgaDZmlkKv/echAFvD42kPt7emEilTtRj2b09+G+z3azNj6Te3t4GjtOo3aLbfEFrwPb6yNvyukivomrMSTDyoxxoVVDMkI8ZEiGEDdrdLArL3yzl31Z+QS5tTR2HCGEaNbu6OxEyxbmRMRl0L+jo7HjNAh1MWSjB3BUa50MoJRaCYwFLp4Ea61/qXF8JDClevvhGsdkKaVOAo6AFCTq0LFThTwfsYfolDP07+jIP8cF4d5aVjoQ9a93BweC3Oz59LdkJod7SEHs1tx0W1x9fBjgDGwBwusiYEFJOZv2Vg3JiE45g1LQz8+Rv47oxNAAZ+kFIUQtGB7YjpfXJbEhMUsKEkIIYWSWZqaMDnZhTWwGBSXl2FmZGzuS0dVFP3w3IL3G7YzqbVczDdh8+UalVA/AAjh2pTsppaYrpWKUUjGnTp26hbjNV0Wlgf9tO8aI//7GoZwC5k8M5stHuksxQhiNUorH+vmQfKqInw6eNHacxu6m22KllAnwDvBsnaUD7lkYyV8j9pJbVMa84VVDMpZM7cGYYFcpRghRS1rbWNDPry0b92RjMMiwDSGEMLYJoe6UlBvYtDfb2FEaBKNOaqmUmkLVlbcBl213AZYCD2mtDVe6r9Z6IbAQIDw8XD5hb9D+rHz+GrGHvZnnGBbozOtjg3CytzJ2LCEY2cWFt7YcYuH2YwwJcDZ2nGbhCm3xE8AmrXXGnw2VUEpNB6YDeHre2DCb54b5Y9/CXIZkCFHHxnRz5elVicSnnyHMq42x4wghRLPWzaMVPo42RMRmMrm7DFGuix4SmYBHjdvu1dsuoZQaDLwIjNFal9bYbg98B7yotY6sg3zNWmlFJe9+f4gxH+4g+9x5FtwXysdTwqQYIRoMM1MTpvZtT3TKGeLSzhg7TmN2K21xb+BJpVQKMB94UCn15pWeRGu9UGsdrrUOd3S8sbGQA/2dCPVsLcUIIerY4M7OWJqZsCFRrsYJIYSxKaWYEOpOVEoeabnFxo5jdHVRkIgG/JRS7ZVSFsA9wPqaByilQoBPqDoBPlljuwWwFliitV5TB9matfi0M4x6fwfv/3yU0cGu/PD0AEZ2dZEvA6LBuae7B/ZWZny6PdnYURqzm26Ltdb3a609tdbeVA3bWKK1/sMqHUKIxsHOypxBnZzYuCebisordjwVQghRj8aHuqEURMRlGDuK0dV6QUJrXQE8CWwFDgBfa633KaVeU0qNqT7sbcAWWK2USlBKXThJngT0Bx6u3p6glOpW2xmbm/NllbyxcT8T/vc7haUVfPFwd96b3I3WNhbGjibEFdlYmjGllxdb9uWQmltk7DiN0i22xUKIJmZMsCunC0vZfTzP2FGEEKLZc2nZgj4d2vJNfEazn9+nTuaQ0FpvAjZdtu1vNX4efJX7LQOW1UWm5mrXsVye/2YPqbnF3NfTkxdGdJLZXEWj8PBt3nz223E+++04r98VZOw4jdLNtsWXHb8YWFzb2YQQ9ev2Tk7YWJiyITGLPr5tjR1HCCGavQlhbjy9KpHolDx6+jgYO47R1MWQDdEAFJSU8//W7uXeT6um4VjxWE/+Oa6LFCNEo+Fkb8VdIa6sjk0nr6jM2HGEEKJRszI3ZWhgOzYn5VBWIcM2hBDC2IYFtsPGwrTZD9uQgkQT9MvBkwx9bzsro9J4tG97tszpz20d5GqIaHwe6+dDSbmBpbtSjR1FCCEavdHBLpw7X85vR2S5dCGEMDZrCzPu7OLCpr05nC+rNHYco5GCRBNypqiMuasSeGRxNLaWZkTMvI2XRgXQwsLU2NGEuCl+znYM6uTEkl0plJQ334ZaCCFqQ19fR1pZm7MhMcvYUYQQQgATwtwpLK1g674cY0cxGilINBGb9mYz5L1fWZ+YxVODfNn4VF9CPFsbO5YQt2x6fx9yi8pYE9u8u7MJIcStsjAzYURQO37Yf6JZX40TQoiGood3G9xbt2jW57lSkGjkThaU8PjSWJ5YHsf/Z+/Oo+Qsr3vf/3b1XIOGKlWXxi6kHrAFFoMFniG2MRa2EXGMHez4GBInPonDTXKxzz2c63NwQlZOHJM4Tk44ueAVx9fJ8iUYO45si2CCB+LEOJJBgAWWWi3QBKhbak0ttXrc94+qxk0jREt0vU9Vvd/PWr2oeut9q/dLaz0q7d7P3ovnt2rDjW/WTVeeq5ZGqiJQH163MqsLls/X3/zwKU3EvAsxALxSV69ZquOjE/ruz/pf/mQAQEUlEqZfuni5/q3vgJ45PBw6nCBISNQod9c9P9mrd3zuQX13W7/+67pX6Rsff5NWL50XOjRgTpmZfuOyVXrqwHHd/8T+0OEAQE173aqc8pkWtm0AQJV438XL5C794yP7QocSBAmJGrTv8LCu/9tN+uRXH1V3e1r3/u5b9Fu/0KnGBn6cqE/rzlusFdk23flgX+hQAKCmNSRM737NEn13W7+OnRwLHQ4AxF4xl9Il5yzU1x7eK/f4VQPzL9gaMjnp+rsfPa0rP/cDbX56UH+w/jzd/Z/foM58OnRoQEU1NiT00Tet1MO7D+snuwZDhwMANe3qC5ZqdHySqjMAqBLvu3i5dg4c15Y9h0OHEjkSEjXiqQPHdd0XHtL/+Keturi4UPf93mW6/o3nKJGw0KEBkfjAJSu0INmkO36wM3QoAFDTLu5YoGUL2rSBbRsAUBXetWaJWhoT+trD8WtuSUKiyo1PTOqOH/Rp3ecf1M+eParPXrtGX/61S7UimwwdGhCpZHOjrr14uR74Wb/GJiZDhwMANcvMdPUFS/XD3gMaPD4aOhwAiL15rU1653mL9c1Hn9XIeLymIJGQqGI/e+6ofumv/11/fO/PdHlPXvffdLk+sHaFzKiKQDyduzijiUmPbRdiAJgrV1+wROOTrn/+6XOhQwEASHrfa5fryPCYHngyXlOQSEhUodHxSf35/dt19f/6ofYdGtZffegi3fGfXqvCvNbQoQFBFXMpSdKugycCRwIAtW31knlalU9pw6Px7OoOANXmzV2LVJjXoq/9JF7bNkhIVJlH9xzW1f/rh/qLB3r17tcs0f03Xa73rFlKVQQgqaO8VWnXIAkJAHglzEzrL1iqHz81qP1HT4YOBwBiryFh+sWLlun72wc0cGwkdDiRISFRJU6OTeh/bnxS7/3f/6Yjw2P6m+vX6vPXXaRsqjl0aEDVaM+0qKUxod0Hj4cOBQBq3nvWLJW79O3Hng0dCgBA0rUXL9fEpOuftsSneo2ERBX48c6DWvf5B3Xngzv1y5d06Ds3Xaa3v7oQOiyg6iQSpo5ski0bADAHutrTWr1knr75GNM2AKAadBcyWrN8vr72MAkJRGBoZFz/4xs/1S/f+ZAm3PWVX3+d/viXXqN5rU2hQwOqVjGX1G62bADAnLj6gqV6ZPdh7WFdBYCq8L6Ll+vJZ4/qiWeOhg4lEiQkAvn+tn5d+bkf6O9/vEu/9qaVuu/3LtMbuxaFDguoeh3ZlHYPnpC7hw4FAGree9YskSSqJACgSqy/YKmaGkxfezgezS1JSETs8IlRfeLuR3XD325SsqVR9/zmG3XL1auVbG4MHRpQEzqybToxOqEDQ6OhQwGAmrcim9TFHQv0zUfpIwEA1WBhqllve1W7/mnLPo1NTIYOp+JISETE3fXtx57VFZ97UN/Ysk83vrVL3/6dN+u1xYWhQwNqytToz92DNLYEgLlw9QVL9eSzR7Wj/1joUAAAKm3bODA0qge3D4QOpeJISERgz+AJ/eqXNum3v/KwFs9v0YYb36RPvvNctTQ2hA4NqDkdufLoTxpbAsCcePeaJUqYtIEqCQCoCr9wbruyqeZYbNsgIVFBYxOT+uvv9+kdf/4DbXpqULe8Z7W+8fE36byl80OHBtSs5QvbZCYaWwLAHGnPtOr1q3L61qPP0J8HAKpAc2NC6y9Yqn95ol+HT9T3NmUSEhXyk12Des9f/lB/8s8/0+U9ef3LJy7Xr715pRob+F8OvBItjQ1aOr9Nu6mQAIA5c/UFS7XzwHFtjUlXdwCodte+drlGJyb1zcfqu3qNfx3PsSMnxvTfvv643vfXP9Kxk2P6wkfW6o7/tFZL5reFDg2oGyuybdpFhQQAzJl15y1WY8L0zUeZtgEA1eC8pfN0biGjr/2kvrdtkJCYI+6uf9qyT2//3Pd19+Y9+vU3r9T9N12ud6wuhA4NqDvFbIoeEgAwhxammnVZT17feuxZTU6ybQMAQjMzve+1y7Rlz2H1DQyFDqdiSEjMgacPHNdHvvgf+t27tmjZwqQ23Pgm/ff3rFaqhVGeQCV05JI6MDSi4yPjoUMBgLpx9QVLtO/wsB7Zcyh0KAAASb944TIlTHVdJUFC4hUYHZ/UX323V1d+/kFt2X1Yt15znr7+W2+kaSVQYcXypI09h6iSAIC58o7Vi9XSmNCGLWzbAIBq0D6vVZf15PWPj+zTRJ1Wr5GQOEs/3nlQ7/rLf9Wffme73vHqgv7lE5frI284Rw0JCx0aUPeK2ZQkRn8CwFxKtzTq7a9u17cff1bjE5OhwwEASHrfxcv17JGT+lHfwdChVAQJiTN06Pio/q97HtUv3/mQTo5N6G9vuES3/8rFKsxrDR0aEBsd2VKFBJM2AGBuXb1mqQ4MjerHTw2GDgUAIOkdqwvKtDbqaw/X57YNEhKz5O762k/26u2f+4G+/vA+/eblnbr//7xcb31Ve+jQgNiZn2zS/LYm7Ro8HjqUqmZm68xsm5ntMLObT/H6TWb2hJk9ZmYPmFmxfPxCM/uRmW0tv/bL0UcPIIS3vqpdqeYGpm0AQJVobWrQe9Ys1T//9DkN1WH/NBISs9A3MKQPfeHH+sRXH9U5uaS+9Ttv1s1XvUptzQ2hQwNiq5hLsmXjNMysQdLtkq6StFrSB81s9YzTHpG01t3XSLpH0mfLx09I+oi7nydpnaTPm9mCaCIHEFJrU4OuPG+x7v3pcxodZ9sGAFSDa1+7TMNjE9r4+LOhQ5lzJCRO4+TYhP78/u266vP/qq3PHNEfvfd83fObb9SrFs8LHRoQex3ZpPYMkpA4jUsl7XD3ne4+KukuSddMP8Hdv+fuU/8TH5K0vHx8u7v3lh8/I6lfUj6yyAEEtf6CpToyPKZ/7R0IHQoAQNLFHQu1clGqLqdtkJB4Cf/ed0Dv+ot/1V880KurXrNYD3ziF/QrrysqQdNKoCoUc0ntPTRM47WXtkzSnmnP95aPvZSPSrp35kEzu1RSs6S+OY0OQNV6U9ciLUg2sW0DAKqEmemXLlqmHz81WHe/kCMhMcPBoRHddPcWfegLP9aEu778a5fqL667SPlMS+jQAEzTkU1qfNL17JGToUOpeWb2YUlrJd024/gSSX8n6Vfd/ZSZHzP7mJltNrPNAwP8NhWoB82NCV11/mJ954n9Gh6dCB0OAEDSey8u/V7p6w/vCxzJ3CIhUTY56fqHTbv19s/9QN989Bnd+NYu3fd7l+myHqqUgWrUwejPl7NP0oppz5eXj72AmV0h6VOS1rv7yLTj8yR9W9Kn3P2hl/om7n6nu69197X5POslUC+uvmCpToxO6Ls/6w8dCgBA0vKFSb1hVU5ff2Sv3D10OHOGhISk3v3HdN2dD+m/fu1x9bRntPF33qJPvvNctTbRtBKoVsVcafQnkzZe0iZJ3Wa20syaJV0nacP0E8zsIkl3qJSM6J92vFnSP0r6srvfE2HMAKrE61bmlM+0sG0DAKrI+167XLsOntDmXYdChzJnYp2QODk2oT+9b5ve9Zf/qu39x/TZ963RXR97vboLmdChAXgZi+e1qrkxod11to9urrj7uKQbJd0n6UlJd7v7VqipSlkAACAASURBVDO71czWl0+7TVJa0lfNbIuZTSUsPiDpMkk3lI9vMbMLo74HAOE0JEzvfs0SfXdbv46dHAsdDgBA0lXnL1ayuaGumlvGNiHx4PYBvfPzD+qvvrdDV1+wVA/cdLk+cMkKmlYCNSKRMK1Y2KbdbNl4Se6+0d173L3T3f+ofOwWd99QfnyFuxfc/cLy1/ry8b9396Zpxy909y0h7wVA9K6+YKlGxyf1na37Q4dS08xsnZltM7MdZnbzKV7/TTN7vJz8/eH0Ec1m9t/K120zs3dGGzmAapNqadS68xfr2489q5Nj9dHjJ5YJiX95Yr8+8sX/UIOZvvLrr9PnPnChcmmaVgK1piObpIcEAFTIxR0LtGxBm775GNs2zpaZNUi6XdJVklZL+uD0hEPZV9z9Ne5+oaTPSvpc+drVKm23O0/SOkn/u/x+AGLs2ouX69jIuO7b+lzoUOZELBMSl5+b1+9fvVobf/ctemPXotDhADhLxVxKuwdP1FVjHwCoFmamqy9Yqh/2HtDg8dHQ4dSqSyXtcPed7j4q6S5J10w/wd2PTnuakjT1l9o1ku5y9xF3f0rSjvL7AYix16/KadmCNn2tTqZtxDIh0dSQ0A1vWknTSqDGdWSTGhoZ54MyAFTI1Rcs0fik696fPhs6lFq1TNKeac/3lo+9gJn9tpn1qVQh8TtneC3jl4EYSSRM716zRP++44BGx085lb2mxDIhAaA+TE3aoLElAFTG6iXz1JlPMW2jwtz9dnfvlPRfJf33M7yW8ctAzLxqcUbjk67ddTBtjoQEgJpFQgIAKmtq28aPnxrU/qMnQ4dTi/ZJWjHt+fLysZdyl6RfPMtrAcREZz4tSdrRT0ICAIJZvrCUkKCxJQBUznvWLJW79O3H2LZxFjZJ6jazlWbWrFKTyg3TTzCz7mlP3y2pt/x4g6TrzKzFzFZK6pb0HxHEDKDKdbaXEhJ9A0OBI3nlSEgAqFmtTQ1aPK+VhAQAVFBXe1qrl8zTBrZtnDF3H5d0o6T7JD0p6W5332pmt5rZ+vJpN5rZVjPbIukmSdeXr90q6W5JT0j6Z0m/7e71MecPwCuSbmnU4nmt6uuv/YREY+gAAOCV6Mgl62L/HABUs/UXLtVn7v2Z9gye0IpsMnQ4NcXdN0raOOPYLdMe/+5prv0jSX9UuegA1KrO9hQVEgAQWjGbpIcEAFTYu1+zRJL0zceokgCAatCVT6tv4Ljc/eVPrmIVS0iY2Toz22ZmO8zs5lO8fpOZPWFmj5nZA2ZWnPba9WbWW/66vlIxAqh9xVxS+4+O6OQYVawAUCkrskld3LFAG7aQkACAatDZntbQyLj2Hx0JHcorUpGEhJk1SLpd0lWSVkv6oJmtnnHaI5LWuvsaSfeoNHdZZpaV9GlJr5N0qaRPm9nCSsQJoPZNlQ5TJQEAlbX+gqX62XPH1Lv/WOhQACD2piZt1Pq2jUpVSFwqaYe773T3UZVGGF0z/QR3/567T/0L4iGVRhlJ0jsl3e/ug+5+SNL9ktZVKE4ANa6YS0li0gYAVNq71ixRwqRvMm0DAILrqpNJG5VKSCyTtGfa873lYy/lo5LuPZNrzexjZrbZzDYPDAy8wnAB1Kpidmr0J40tAaCS2jOtev2qnL716DM1v2cZAGpde6ZF6ZbGmp+0EbyppZl9WNJaSbedyXXufqe7r3X3tfl8vjLBAah6C5JNyrQ2ag9bNgCg4q6+YKl2Hjiurc8cDR0KAMSamakzn9IOKiROaZ+kFdOeLy8fewEzu0LSpyStd/eRM7kWAKTSYlzMJbWLhAQAVNxV5y+WmfTdn/WHDgUAYq8zn1Zff21XCVcqIbFJUreZrTSzZknXSdow/QQzu0jSHSolI6b/rXafpCvNbGG5meWV5WMAcEod2aR200MCACpuQbJZyxe2aRuNLQEguM72tJ47elJDI+OhQzlrFUlIuPu4pBtVSiQ8Kelud99qZrea2fryabdJSkv6qpltMbMN5WsHJf2hSkmNTZJuLR8DgFPqyKa059AJTUyypxkAKq2nPcOkDQCoAs9P2qjhPhKNlXpjd98oaeOMY7dMe3zFaa79oqQvVio2APWlmEtqbML17JFhLV+YDB0OANS1nsUZPdg7oLGJSTU1BG9HBgCx1dVemjbXNzCkC1YsCBzN2eFvEQA1b2rSBts2AKDyegppjU24nj5Q2/uWAaDWFXMpNSaspkd/kpAAUPM6cuWEBI0tAaDiutszkqTt+2v3AzAA1IOmhoQ6ckntqOEtGyQkANS8JfPb1NRgTNoAgAh0taeVMGk7fSQAILjOfFp9A7VbsUZCAkDNa0iYli9k0gYARKG1qUEd2aR6+0lIAEBoXe1p7Tp4XGMTk6FDOSskJADUhY5sUrsGazc7DAC1pLuQYcsGAFSBznypr0+tbl0mIQGgLhRzSe06eELujP4EgErrKaT19IHjGh2vzd/IAUC96MyXJ23UaB8JEhIA6kJHNqljJ8d1ZHgsdCgAUPd6ChmNT7qeYtIGAATV2Z6WpJrtI0FCAkBd6CiP/txFHwkAqLifT9qgjwQAhDSvtUntmZaaHf1JQgJAXSjmSuVqTNoAgMpblU8pYVIvCQkACK4zn67Z0Z8kJADUhakKid0Ha7NcDQBqSWtTg87JpWhsCQBVoLM9pb6BoZrspUZCAkBdaGtuUHumhS0b05jZOjPbZmY7zOzmU7x+k5k9YWaPmdkDZlac9tr1ZtZb/ro+2sgB1ILuQlrbGf0JAMF15dM6dnJcA0MjoUM5YyQkANSNYi5ZsyOP5pqZNUi6XdJVklZL+qCZrZ5x2iOS1rr7Gkn3SPps+dqspE9Lep2kSyV92swWRhU7gNrQU8ho18ETOjk2EToUAIi1qcaWtbhtg4QEgLqxIktCYppLJe1w953uPirpLknXTD/B3b/n7lP/wx6StLz8+J2S7nf3QXc/JOl+SesiihtAjeguZDQx6dpZo53dAaBedOZrd9IGCQkAdaOYTem5oyf5bV3JMkl7pj3fWz72Uj4q6d6zvBZADPUUSh+Ae9m2AQBBLZnfqmRzg/qokACAcIq5pNylvYeokjgTZvZhSWsl3XYW137MzDab2eaBgYG5Dw5A1Vq5KKWGhDH6EwACMzN15tM1OfqThASAutGRK03aoLGlJGmfpBXTni8vH3sBM7tC0qckrXf3kTO5VpLc/U53X+vua/P5/JwEDqA2tDQ26JxckkkbAFAFOvMpKiQAIKTi1OhP+khI0iZJ3Wa20syaJV0nacP0E8zsIkl3qJSM6J/20n2SrjSzheVmlleWjwHAC5y7OKNeKiQAILiu9rSeOXJSx0fGQ4dyRkhIAKgb2VSzUs0NVEhIcvdxSTeqlEh4UtLd7r7VzG41s/Xl026TlJb0VTPbYmYbytcOSvpDlZIamyTdWj4GAC/Q3Z7RrkEmbQBAaFONLWut0XBj6AAAYK6YmTpyKSokytx9o6SNM47dMu3xFae59ouSvli56ADUg55CRu6lUXPnL5sfOhwAiK2p0Z99A0N6zfLaWY+pkABQV4rZpHYdrK3MMADUKiZtAEB1KOaSakhYzTW2JCEBoK4Uc0ntOTSsyUkPHQoA1L1zFqXU1GA0tgSAwFoaG9SRTZKQAICQOnJJjY5Pav+xk6FDAYC619SQ0MpFKRpbAkAV6MyntKPGJm2QkABQVzqyjP4EgCh1FzJUSABAFejMp/X0gRMan5gMHcqskZAAUFeK2ZQkaTcJCQCIRE97RnsOndDwKJM2ACCkzva0RicmtffQcOhQZo2EBIC6snRBqxoTpl2DNLYEgCj0FNLPT9oAAIQzNfqzltZjEhIA6kpjQ0LLFraxZQMAItJdyEiSttNHAgCC6sr/fPRnrSAhAaDudGST2jNIQgIAonBOLqnmhoS2M/oTAIKan2zSonQLCQkACKkjm9QuEhIAEInGhoRW5VPqpbElAARXa5M2SEgAqDvFXFKHT4zpyPBY6FAAIBa6Cxlte44KCQAIrbM9rb6B43L30KHMCgkJAHWng0kbABCpnva09h0e1vGR8dChAECsdeXTOjI8poPHR0OHMiskJADUnWIuKUlM2gCAiEw1tuytoTJhAKhHne21NWmDhASAutORLSUkdtNHAgAi0VMofQBm0gYAhNWZL1UK10pjSxISAOpOqqVRi9LNbNkAgIgUcyk1NybUS0ICAIJaOr9NbU0N6uuvjUphEhIA6lJHNqldJCQAIBINCVNXPq3tTNoAgKASCdOqfIoKCQAIqZhLsWUDACLUU0hTIQEAVaAzn6aHBACE1JFN6pkjwxoZnwgdCgDEQncho2eOnNSxk4xcBoCQOvOlyUfDo9X/OZiEBIC6VMwl5S7tOzQcOhQAiIUeJm0AQFXoKk/a2Hmg+tdjEhIA6tLUpI1dbNsAgEhMTdpg2wYAhNXZXpq0UQvbNkhIAKhLHbny6E8aWwJAJFYsTKq1KUFjSwAI7JxcSgmT+gaqf9IGCQkAdSmfblGyuYFJGwAQkUTC1NWe1nYqJAAgqNamBq3IJmti0gYJCQB1yczUkU1q92D1Z4YBoF70tGfUS4UEAATXmU+rjy0bABBOKSFBhQQARKW7kNFzR0/qyDCTNgAgpM58SjsPHNfEpIcO5bRISACoW1MJCffqXogBoF5MNbbc0c+2DQAIqas9rdHxyaqfOEdCAkDdKuaSOjk2qf5jI6FDAYBYmBr9SWNLAAirM19OEA9Ud4KYhASAutWRK408orElAERj2YI2tTU1aNtz1f0BGADq3VRCoq+/uvupkZAAULeK2dLoz10Hq3shBoB6kUiYugtp9bJlAwCCWphqVjbVXPWTNiqWkDCzdWa2zcx2mNnNp3j9MjN72MzGzezaGa991sy2mtmTZvaXZmaVihNA/Vq2sE0Jk/bQ2BIAItPdnmHLBgBUga58Op4JCTNrkHS7pKskrZb0QTNbPeO03ZJukPSVGde+UdKbJK2RdL6kSyRdXok4AdS3poaEli5o066YJiRIDAMIoaeQ1sCxER0+MRo6FACItc72lHZU+ejPSlVIXCpph7vvdPdRSXdJumb6Ce7+tLs/JmlyxrUuqVVSs6QWSU2S9lcoTgB1rphLxrKHBIlhAKHQ2BIAqkNnPq1DJ8Y0eLx6E8SVSkgsk7Rn2vO95WMvy91/JOl7kp4tf93n7k/OPM/MPmZmm81s88DAwByEDKAedWRT2h3PCgkSwwCC6C6P/ty+nz4Ss6hUu8nMnjCzx8zsATMrTnttwsy2lL82RBs5gHrQ2V5ubFnF2zaqrqmlmXVJerWk5SolMd5mZm+ZeZ673+nua919bT6fjzpMADWimEtq8Piojp0cCx1K1CqeGAaAU1m2oE2p5gb1xjwhMctKtUckrXX3NZLukfTZaa8Nu/uF5a/1kQQNoK50TY3+rOJtG5VKSOyTtGLa8+XlY7PxXkkPufuQuw9JulfSG+Y4PgAxMTVpI6ZVEmdltonh8rlUqwF4ATNTd4HGlppdpdr33H3qL6iHVFp3AWBOLF3QppbGhPpimJDYJKnbzFaaWbOk6yTNttRst6TLzazRzJpU2rfMb+YAnJUVUwmJ+PWRiCQxTLUagFPpYfSndOaVah9Vab2d0lpO+D5kZr/4UheRGAbwUhoSplVVPmmjIgkJdx+XdKOk+1RKJtzt7lvN7FYzWy9JZnaJme2V9H5Jd5jZ1vLl90jqk/S4pEclPeru36xEnADqXzFXSkjEcNIGiWEAwfQUMjowNFrVjdSqiZl9WNJaSbdNO1x097WSPiTp82bWeaprSQwDOJ3OfEo7qjgh0VipN3b3jZI2zjh2y7THm3SKsjR3n5D0nysVF4B4ybQ2KZtqjt2kDXcfN7OpxHCDpC9OJYYlbXb3DWZ2iaR/lLRQ0tVm9gfufp5KieG3qZQYdkn/TGIYwJnofn7SxjG9flUucDTBzKpSzcyukPQpSZe7+8jUcXffV/7vTjP7vqSLVPqlHQDMWmc+rW8//qxOjk2otakhdDgvUrGEBABUi45sUrsHj4cOI3IkhgGE0lOetNEb74TE85VqKiUirlOp2uF5ZnaRpDskrXP3/mnHF0o64e4jZrZIpVHM0xteAsCsdLWn5S49deC4Xr1kXuhwXqTqpmwAwFwr5pI0tQSACC2e16pMS2OsG1vOZguzSls00pK+OmO856slbTazR1WaevQZd38i4lsAUAc6q3zSBhUSAOpeRzapbz32rMYmJtXUQB4WACqtNGkjre0xH/05i0q1K17iun+X9JrKRgcgDlYuSslMVdvYkk/mAOpeRzapiUnXvkPDoUMBgNjoKWTUW6W/kQOAuGhrbtCyBW3qG6jO7cskJADUvWIuJSmWkzYAIJjuQkaDx0d1YGjk5U8GAFRMV3tafVWaICYhAaDuTY3+3H2wOjPDAFCPphpbbn8u3ts2ACC0znxaOw8MaXLSQ4fyIiQkANS99kyLWhoTNLYEgAj1TBv9CQAIpzOf1smxSe07XH3bl0lIAKh7ZqaObFK7DpKQAICotGdaNK+1UdurtEwYAOKiq71UsVaNjS1JSACIBUZ/AkC0zKzU2JIKCQAIqjNf6qdWjaM/SUgAiIWObEq7B0/Ivfr2zgFAveouZLR9/xBrLwAElE01a0GyqSonbZCQABALxVxSJ0YnNEC3dwCITE8hrSPDYxo4xtoLAKGYmbryabZsAEAoHeVJG3vYtgEAkTn3+caW1fchGADipDNfnaM/SUgAiIWObCkhQWNLAIhON5M2AKAqdLandPD4qA4dHw0dyguQkAAQC8sXtsmMhAQARGlRulkLk03q7SchAQAhTU3a2HmguqokSEgAiIWWxgYtnd/GpA0AiJCZPd/YEgAQTme+lJCotkkbJCQAxEZHNqldB6uvuzAA1LOeQlrb9x9j0gYABLR8YVLNDYmqm7RBQgJAbBRzSe0eHA4dBgDESk8ho2Mnx7X/KJM2ACCUhoRp5aJU1TW2JCEBIDZWZJM6MDSi4yPjoUMBgNjobqexJQBUg6726hv9SUICQGwUy6M/6SMBANHpKZT2LZOQAICwOvMp7R48oZNjE6FDeR4JCQCxUcymJDFpAwCilEu3KJdqVi+NLQEgqM72tCa9uj4Lk5AAEBsdz1dIVFczHwCod92FtLYz+hMAgpqatFFN2zZISACIjfltTVqQbGLLBgBErKeQUe/+ISZtAEBAq/KlauFqGv1JQgJArJRGf5KQAIAodRcyGhoZ1zNHToYOBQBiK9ncqGUL2qiQAIBQOrJJKiQAIGI97TS2BIBq0FllkzZISACIlWIuqX2HhjU+MRk6FACIjZ5CafRnLwkJAAiqM59SX/9xTU5WxxY6EhIAYqWYTWl80vXMYcqGASAqC1PNWpRu0XYmbQBAUJ35tIbHJvTs0er4LExCAkCs/HzSBts2ACBKPYU0FRIAEFhXeQtdX5U0tiQhASBWOrKlhMQuRn8CQKR6Chn19g9VTZkwAMTR1OjPapm0QUICQKwsnteq5saEdjNpAwAi1VPI6MTohPYdHg4dCgDE1qJ0s+a1NlZNY0sSEgBiJZEwrVjYFovRn2a2zsy2mdkOM7v5FK9fZmYPm9m4mV0747UOM/uOmT1pZk+Y2TlRxQ2gPvUUSr+V6+1n2wYAhGJmVTVpg4QEgNgp5lLaVec9JMysQdLtkq6StFrSB81s9YzTdku6QdJXTvEWX5Z0m7u/WtKlkvorFy2AOOguT9qgsSUAhNWVT6tvoDq2L5OQABA7Hdmk9gyekHtd72O+VNIOd9/p7qOS7pJ0zfQT3P1pd39M0gtmoJYTF43ufn/5vCF3r+8MDoCKm9/WpMK8Fm2nsSUABNXZntbAsREdGR4LHQoJCQDx05FNamhkXIPHR0OHUknLJO2Z9nxv+dhs9Eg6bGZfN7NHzOy2csXFi5jZx8xss5ltHhgYeIUhA6h3PYWMeqmQAICgphpbVsO2DRISAGKnmJuatMEv/V9Co6S3SPqkpEskrVJpa8eLuPud7r7W3dfm8/noIgRQk7rbM9rBpA0ACKqaRn+SkAAQO1MJiTqftLFP0oppz5eXj83GXklbyts9xiV9Q9LFcxwfgBjqKaQ1PDahvYeYtAEAoaxY2KamBtMOKiQAIHrLFyZlpnqftLFJUreZrTSzZknXSdpwBtcuMLOpkoe3SXqiAjECiJmfN7akjwQAhNLYkNA5uZT6+sM3tiQhASB2WpsatHheq3bX8ZaNcmXDjZLuk/SkpLvdfauZ3Wpm6yXJzC4xs72S3i/pDjPbWr52QqXtGg+Y2eOSTNIXQtwHgPrSXR79uZ3RnwAQVFd7WjuroEKiMXQAABDCimxSuwfDZ4Uryd03Sto449gt0x5vUmkrx6muvV/SmooGCCB25rU2acn8Vm1/joQEAITUmU/rO0/s1+j4pJobw9UpUCEBIJaK2WS9b9kAgKrUXchoO5M2ACCozvaUJiZduw6G/QUdCQkAsVTMJdV/bETDoxOhQwGAWOlpT6tvYEgTTNoAgGC68qWePqFHf5KQABBLHbmUJNV1HwkAqEY9hYxGxidZfwEgoFX50mfhvgEqJAAgcsVsefQnH4gBIFLPN7Zk0gYABJNqadSS+a3a0U+FBABErqOckAi9bw4A4mZq9GcvCQkACKozn2bLBgCEsCDZpExrIxUSABCxdEujli1oo7ElAATW1Z5WX/+Q3MP19CEhASCWzEzFHJM2ACCE7kKaLRsAEFhnPqXjoxN67ujJYDGQkAAQW8VsigoJAAjg3EJGOweOa3xiMnQoABBbnflST5++/nBbmCuSkDCzdWa2zcx2mNnNp3j9MjN72MzGzezaGa91mNl3zOxJM3vCzM6pRIwA0JFLau+hE4yeA4CIdRcyGp2Y1C6SwgAQTFd7OSERsI/EnCckzKxB0u2SrpK0WtIHzWz1jNN2S7pB0ldO8RZflnSbu79a0qWS+uc6RgCQSo0txyZczx4ZDh0KAMRKT3nSBo0tASCcfKZFmZbGoJM2KlEhcamkHe6+091HJd0l6ZrpJ7j70+7+mKQX1OmVExeN7n5/+bwhdyd1DqAinh/9SR8JAIjU1G/laGwJAOGYmVa1h520UYmExDJJe6Y931s+Nhs9kg6b2dfN7BEzu61ccfEiZvYxM9tsZpsHBgZeYcgA4qgjVx79SckwAEQq2dyoFdk2GlsCQGBdgUd/VltTy0ZJb5H0SUmXSFql0taOF3H3O919rbuvzefz0UUIoG4smd+mpgZj0gYABNDTnlEvFRIAEFRne0r7j47o6MmxIN+/EgmJfZJWTHu+vHxsNvZK2lLe7jEu6RuSLp7j+ABAktSQMK1YmNQeKiQAIHLdhYx2HhjSGJM2ACCYqUkbOwfCTNqoREJik6RuM1tpZs2SrpO04QyuXWBmUyUPb5P0RAViBABJ0opsUrsGw406AoC46imkNTbh2nWQNRgAQvn56M8wFWtznpAoVzbcKOk+SU9Kutvdt5rZrWa2XpLM7BIz2yvp/ZLuMLOt5WsnVNqu8YCZPS7JJH1hrmMEgCnFXFK7Dp6QO6M/ASBKPYWMJGnbc2zbAIBQirmkGhMWrI9EYyXe1N03Sto449gt0x5vUmkrx6muvV/SmkrEBQAzdWSTOnZyXIdPjGlhqjl0OAAQG535tMyk7fuP6d1aEjocAIilpoaEirlksNGf1dbUEgAiVcylJDFpAwCi1tbcoI5sUr39TNoAgJA6A07aICEBINaK5dGfu0lIAEDkutsz2s6kDQAIqqs9rV0HTwRpMkxCAkCsrVhYTkjQVA0AItdTSOvpA8c1Os6kDQAIpTOf1vika9fB6H9BR0ICQKy1NTeoPdMSZAEGgLjrKWQ0Pul66gBJYQAIpbO9PGkjwLYNEhIAYq+YS9JDAgAC6C6UPgRv308fCQAIpTNf6qlGQgIAAujIprSbCgkAiFxnPq2ESb0kJAAgmExrkwrzWoJM2iAhASD2irmknjt6UifHJkKHAgCx0trUoGIuRWNLAAisNGkj+u1zJCQAxF5HttTYcu8hqiQAIGo9hbS21/HoTzNbZ2bbzGyHmd18itdvMrMnzOwxM3vAzIrTXrvezHrLX9dHGzmAOOlqT2tn/5DcPdLvS0ICQOx1lEd/0tgSAKLXU8ho18ETGhmvvyo1M2uQdLukqyStlvRBM1s947RHJK119zWS7pH02fK1WUmflvQ6SZdK+rSZLYwqdgDx0plP69jIuPqPjUT6fUlIAIi9YpaEBACE0l3IaGLStTNAqXAELpW0w913uvuopLskXTP9BHf/nrtP/QX0kKTl5cfvlHS/uw+6+yFJ90taF1HcAGKmM1+etBFxHwkSEgBiL5tqVrqlUbuZtAEAkeup70kbyyTtmfZ8b/nYS/mopHvP5Foz+5iZbTazzQMDA68wXABx1dkeZtIGCQkAsWdm6sgm6y4hMYt9y5eZ2cNmNm5m157i9XlmttfM/iqaiAHE0cpFKTUkTL0xb2xpZh+WtFbSbWdynbvf6e5r3X1tPp+vTHAA6t7iea1KNTdE3tiShAQAqNTYctfB+ikXnuW+5d2SbpD0lZd4mz+U9GClYgQASWppbNA5uWS9Vkjsk7Ri2vPl5WMvYGZXSPqUpPXuPnIm1wLAXDAzdbanIx/9SUICAFQa/bnn0LAmJ6PtLFxBs9m3/LS7PyZpcubFZvZaSQVJ34kiWADx1lPIqDfiD8ER2SSp28xWmlmzpOskbZh+gpldJOkOlZIR/dNeuk/SlWa2sNzM8sryMQCoiNLoTxISABC5jlxSo+OTeu7oydChzJUz3bf8PDNLSPozSZ+cxbnsXQbwinUXMnr64HGdHKuvSRvuPi7pRpUSCU9Kutvdt5rZrWa2vnzabZLSkr5qZlvMbEP52kGVKtU2lb9uLR8DgIroak/r2SMnNTQyHtn3bIzsOwFAFStmS418dh08oaULksf9mwAAIABJREFU2gJHE9zHJW10971mdtoT3f1OSXdK0tq1a+umvARAtHoKablLO/qHdP6y+aHDmVPuvlHSxhnHbpn2+IrTXPtFSV+sXHQA8HOd+dLn4Z0DQ1qzfEEk35MKCQBQacuGJO2pn8aWr2Tv8Rsk3WhmT0v6U0kfMbPPzG14APBzPYWMJKm3vy77SABATXh+9GeE2zaokAAASUvmt6oxYdo1WDeNLZ/ft6xSIuI6SR+azYXu/itTj83sBklr3f1FUzoAYK6ck0upMWHaHvNJGwAQUjFXmnrU1x/d52EqJABAUmNDQssWtmnXwfqokJjNvmUzu8TM9kp6v6Q7zGxruIgBxFlzY0IrF6XUW5+TNgCgJjQ3JlTMJiOdtEGFBACUdWST2l0/WzZms295k0pbOU73Hl+S9KUKhAcAL9BTyOjxfUdChwEAsbYq4kkbVEgAQFkxl6ybCgkAqDXdhbT2HDqh4dH6mrQBALWkqz2tpw8e1/jEi6bCVwQJCQAoK2ZTOjI8piMnxkKHAgCx01PIPD9pAwAQRmc+pbEJj6xqmIQEAJStyJYmbdTTtg0AqBU9hVJ39+30kQCAYDrbpyZtRNPYkoQEAJRNjf6so0kbAFAzirmUmhsS2s7oTwAIJurRnyQkAKCso1whQR8JAIheU0NCq/Ip9TL6EwCCmd/WpHymRX0RbZ8jIQEAZamWRi1Kt2g3CQkACKK7kGHLBgAE1plPaQcVEgAQvWKuvkZ/AkAt6WlPa++hYR0fGQ8dCgDEVmc+rb7+Ibl7xb8XCQkAmKYjS0ICAELpLmQkMWkDAELqak/r6MlxHRgarfj3IiEBANN0ZJN65siwRsYnQocCALHDpA0ACG+qsWUUyWESEgAwTTGXlLu099Bw6FAAIHaKuZSaGxPqpUICAIL5+ehPEhIAEKmp0Z80tgSA6DUkTJ35tLY9R4UEAISyZF6rks0NJCQAIGod2ZQk0UcCAALpKaTVy5YNAAgmkTCtyqfYsgEAUVuUblayuUG7qJAAgCB6Chk9c+Skjp0cCx0KAMRWZz6tnQPHK/59SEgAwDRmVp60UfkFGADwYt3lvcv0kQCAcLryae07PKwTo5Udw0xCAgBm6MgmqZAAgEB6yqM/2bYBAOFMNbasdJUECQkAmKGYS2r34AlNTnroUAAgdlZkk2ppTGj7fiokACCUqdGflW5sSUICAGboyKU0Mj6p/mMjoUMBgNhpSJi62tPaToUEAARzzqKkEib1VXj7HAkJAJihI1se/cmkDQAIoqeQUS8VEgAQTEtjgzqySfWxZQMAolUsJyR2HaSxJQCE0F1I67mjJ3VkmEkbABBKZz5d8dGfJCQAYIZlC9vUkDAqJAAgkJ72UmPLHf1s2wCAUDrb03rqwHFNVLCvGgkJAJihqSGhpQtambQBAIGcu7iUkKCxJQCE05VPa3RiUnsPVe4zMQkJADiFYjalXVRIAEAQyxa0qa2pgcaWABBQZ3tKkiq6bYOEBACcwopsUntISABAEImEqbuQprElAAQUxehPEhIAcArFXFKDx0d17CQN1QAghO72DBUSABDQgmSzFqWb1ddfuUbvJCQA4BR+PmmDKgkACKGnkFb/sREdOUFiGABCWZVPawcVEgAQrY5cKSHBpA0ACKOnUG5syaQNAAhmavSne2UmbVQsIWFm68xsm5ntMLObT/H6ZWb2sJmNm9m1p3h9npntNbO/qlSMAPBSOqiQAICgugulvcvbniMhAQChdLWndWR4TIPHRyvy/hVJSJhZg6TbJV0labWkD5rZ6hmn7ZZ0g6SvvMTb/KGkBysRHwC8nExrk7KpZiokACCQZQvalGpuUC99JAAgmM58ZSdtVKpC4lJJO9x9p7uPSrpL0jXTT3D3p939MUmTMy82s9dKKkj6ToXiA4CX1ZFNavdg5Zr4VNrZVqqZ2YVm9iMz22pmj5nZL0cbOQBIZqauQkbbmbQBAMH8fNJGZT4TVyohsUzSnmnP95aPvSwzS0j6M0mffJnzPmZmm81s88DAwFkHCgAvpZhL1uyWjVdYqXZC0kfc/TxJ6yR93swWVDZiAHixnva0eukhAQDBLFvQptamRMVGf1ZjU8uPS9ro7ntPd5K73+nua919bT6fjyg0AHFSzCb1zOFhjY6/qJCrFpx1pZq7b3f33vLjZyT1S2KhBRC5nkJGB4ZGK7Z3GQBweomEadWidM0lJPZJWjHt+fLysdl4g6QbzexpSX8q6SNm9pm5DQ8AXl5HLqVJl/YdHg4dytk460q16czsUknNkvpe4nWq1QBUzFRjy+30kQCAYDrb0zXXQ2KTpG4zW2lmzZKuk7RhNhe6+6+4e4e7n6PSto0vu/uL9j4DQKVNTdqIa2NLM1si6e8k/aq7n7JMhGo1AJU0NfqTxpYAEE5nPqV9h4c1PDox5+9dkYSEu49LulHSfZKelHS3u281s1vNbL0kmdklZrZX0vsl3WFmWysRCwCcrWKunJA4WJONLV9JpZrMbJ6kb0v6lLs/NMexAcCsLJnfqkxLI40tASCgrva03KWnDsz9Z+LGOX/HMnffKGnjjGO3THu8SaUPyKd7jy9J+lIFwgOAl9WeaVFrU6JWG1s+X6mmUiLiOkkfms2F5cq2f1SpQu2eyoUIAKdXmrSRZssGAAQ0NWljx8CQVi+dN6fvXY1NLQGgKpiZOrJJ7arBLRuvsFLtA5Iuk3SDmW0pf10Y4DYAQD3tGfVWaO8yAODlrVyUkpnUV4G1uGIVEgBQDzqyKe2uzQqJs65Uc/e/l/T3FQ8QAGahu5DWP2zeowNDI1qUbgkdDgDETmtTg1YsTFZk0gYVEgBwGh3ZpHYPnpC7hw4FAGLp3MWlxpZs2wCAcDrzqYpM2iAhAQCnUcwlNTw2oYGhkdChAEAs/XzSBts2ACCUznxaTx04ronJuf0lHQkJADiNjucnbdTmtg0AqHXtmRbNa22kQgIAAupqT2tkfFLPHB6e0/clIQEAp1HMlhISNTppAwBqnpmpp5ChQgIAAupsL0/amONtGyQkAOA0li9Mykw1OWkDAOpFdyGj7f3H6OcDAIFMjf6c68aWJCQA4DSaGxNaOr9Ne0hIAEAwPYW0Dp8Y08Ax+vkAQAjZVLMWJptISABA1DqySe06eDx0GAAQW1ONLbezbQMAgulqT6uvf24/EzfO6bsBQB1670XLdPTkWOgwACC2XrU4oxveeI4WZZpDhwIAsfW+i5frxOjEnL4nCQkAeBkfuGRF6BAAINZy6Rb9/vrzQocBALF23aUdc/6ebNkAAAAAAACRIyEBAAAAAAAiR0ICAAAAAABEjoQEAAAAAACIHAkJAAAAAAAQORISAAAAAAAgciQkAAAAAABA5EhIAAAAAACAyJGQAAAAAAAAkSMhAQAAAFSAma0zs21mtsPMbj7F65eZ2cNmNm5m1854bcLMtpS/NkQXNQBEpzF0AAAAAEC9MbMGSbdLeoekvZI2mdkGd39i2mm7Jd0g6ZOneIthd7+w4oECQEAkJAAAAIC5d6mkHe6+U5LM7C5J10h6PiHh7k+XX5sMESAAhMaWDQAAAGDuLZO0Z9rzveVjs9VqZpvN7CEz+8W5DQ0AqkNdVEj85Cc/OWBmu87i0kWSDsx1PFUqTvcqcb/1rJbutRg6gCid5VpcSz/PuRCn+43TvUrcbzWr1bW46O77zGyVpO+a2ePu3jfzJDP7mKSPlZ8Omdm2M/w+tfSznAvcb32L0/3W0r2+5DpcFwkJd8+fzXVmttnd1851PNUoTvcqcb/1LE73WmvOZi2O288zTvcbp3uVuF+c0j5JK6Y9X14+Nivuvq/8351m9n1JF0l6UULC3e+UdOfZBhm3nyX3W9/idL/1cq9s2QAAAADm3iZJ3Wa20syaJV0naVbTMsxsoZm1lB8vkvQmTes9AQD1goQEAAAAMMfcfVzSjZLuk/SkpLvdfauZ3Wpm6yXJzC4xs72S3i/pDjPbWr781ZI2m9mjkr4n6TMzpnMAQF2oiy0br8BZl7fVoDjdq8T91rM43WscxO3nGaf7jdO9StwvTsHdN0raOOPYLdMeb1JpK8fM6/5d0msqHmBJ3H6W3G99i9P91sW9mruHjgEAAAAAAMQMWzYAAAAAAEDk6j4hYWbrzGybme0ws5tP8XqLmf1D+fUfm9k50Uc5d2ZxvzeZ2RNm9piZPWBmtToKS9LL3++0895nZm5mNduJdjb3amYfKP98t5rZV6KOcS7N4s9yh5l9z8weKf95fleIODE7cVqLWYdf8ryaX4eleK3FrMP1JU7rsMRafJrzan4tjtM6LMVgLXb3uv2S1KDSeKRVkpolPSpp9YxzPi7p/yk/vk7SP4SOu8L3+1ZJyfLj36r3+y2fl5H0oKSHJK0NHXcFf7bdkh6RtLD8vD103BW+3zsl/Vb58WpJT4eOm69X9POsi7WYdbh+1+Ez+PnWxVrMOlxfX3Fah8/gflmLqyD2Cv1s62IdPoP7rem1uN4rJC6VtMPdd7r7qKS7JF0z45xrJP2/5cf3SHq7mVmEMc6ll71fd/+eu58oP31Ip2ikVENm8/OVpD+U9CeSTkYZ3Bybzb3+hqTb3f2QJLl7f8QxzqXZ3K9Lmld+PF/SMxHGhzMTp7WYdbh+12EpXmsx63B9idM6LLEW1/NaHKd1WIrBWlzvCYllkvZMe763fOyU53hpPNMRSblIopt7s7nf6T4q6d6KRlRZL3u/ZnaxpBXu/u0oA6uA2fxseyT1mNm/mdlDZrYusujm3mzu9/clfdhK49I2Svo/ogkNZyFOazHrcP2uw1K81mLW4foSp3VYYi2u57U4TuuwFIO1OO5jP2PLzD4saa2ky0PHUilmlpD0OUk3BA4lKo0qlaj9gkpZ/gfN7DXufjhoVJXzQUlfcvc/M7M3SPo7Mzvf3SdDBwbMButw3YrTWsw6jJrHWlyX4rQOSzW+Ftd7hcQ+SSumPV9ePnbKc8ysUaUyl4ORRDf3ZnO/MrMrJH1K0np3H4kotkp4ufvNSDpf0vfN7GlJr5e0oUab+MzmZ7tX0gZ3H3P3pyRtV2kxrkWzud+PSrpbktz9R5JaJS2KJDqcqTitxazD9bsOS/Fai1mH60uc1mGJtbie1+I4rcNSDNbiek9IbJLUbWYrzaxZpQY9G2acs0HS9eXH10r6rpc7gtSgl71fM7tI0h0qLby1vJ9Kepn7dfcj7r7I3c9x93NU2h+43t03hwn3FZnNn+VvqJQJlpktUqlcbWeUQc6h2dzvbklvlyQze7VKi+9ApFFituK0FrMO1+86LMVrLWYdri9xWocl1uJ6XovjtA5LMViL6zohUd7/dqOk+yQ9Kelud99qZrea2fryaX8jKWdmOyTdJOklx+RUu1ne722S0pK+amZbzGzmH+iaMcv7rQuzvNf7JB00syckfU/Sf3H3mvzNxizv9xOSfsPMHpX0/0m6oYY/ONW1OK3FrMP1uw5L8VqLWYfrS5zWYYm1WHW8FsdpHZbisRZbDcUKAAAAAADqRF1XSAAAAAAAgOpEQgIAAAAAAESOhAQAAAAAAIgcCQkAAAAAABA5EhIAAAAAACByJCQQC2Y2UR7p9KiZPWxmb3yZ8xeY2cejig8A4oC1GADCYh1GtWHsJ2LBzIbcPV1+/E5J/7e7X36a88+R9C13Pz+aCAGg/rEWA0BYrMOoNlRIII7mSTo09cTM/ouZbTKzx8zsD8qHPyOps5xBvs3M0mb2QDmT/LiZXRMkcgCoH6zFABAW6zCCawwdABCRNjPbIqlV0hJJb5MkM7tSUrekSyWZpA1mdpmkmyWd7+4Xls9rlPRedz9qZoskPWRmG5wSIwA4E6zFABAW6zCqCgkJxMXwtIX0DZK+bGbnS7qy/PVI+by0Sovx7hnXm6T/WV6YJyUtk1SQ9FwEsQNAvWAtBoCwWIdRVUhIIHbc/UfljG5epUX1j939junnlPfLTfcr5fNf6+5jZva0SpllAMBZYC0GgLBYh1EN6CGB2DGzV0lqkHRQ0n2Sfs3Mppr7LDOzdknHJGWmXTZfUn954X2rpGLEYQNAXWEtBoCwWIdRDaiQQFxM7ZeTShng6919QtJ3zOzVkn5kZpI0JOnD7t5nZv9mZj+VdK+kP5H0TTN7XNJmST+L/hYAoOaxFgNAWKzDqCqM/QQAAAAAAJFjywYAAAAAAIgcCQkAAAAAABA5EhIAAAAAACByJCQAAAAAAEDkSEgAAAAAAIDIkZAAAAAAAACRIyEBAAAAAAAiR0ICAAAAAABEjoQEAAAAAACIHAkJAAAAAAAQORISAAAAAAAgciQkAAAAAABA5EhIAAAAAACAyJGQAAAAAAAAkSMhAQAA8P+zd+fxUVbX48c/NzsJ2fdkQhJIIBCykERAdgQVkX1R3K3Wpf78ilprrbZqba2tXdS61Fq1ti6IICAoYBUBWQRJCAk7hBCyAdkXliyTub8/ZogRAVmSPMnMeb9eeZG5z/NMzijcPHPmnnOFEEII0ekkISGEEEIIIYQQQohOJwkJIYQQQgghhBBCdDpJSAghhBBCCCGEEKLTSUJCCCGEEEIIIYQQnU4SEkIIIYQQQgghhOh0kpAQog2lVE+l1DGl1IozHCtQSp20HT+qlHpHKdXTiDiFEKI7sc2fTUqpoNPGs5VSWikVY5tTm2xzbJVS6gulVEKbc29XSrXYjtcppXKUUpM6/9UIIUT3YZt/x5/lmFJK5Suldp3PdbZ5eH2bx25KqaeVUvuVUsdt17ytlIpp79ch7JckJIT4vplAI3ClUirsDMcna617AmlABvDrzgxOCCG6sYPADaceKKWSAM/TznneNsdGAiXAW6cd/8Z23A94DfhQKeXXcSELIYRdGwWEAL2VUpddxPULgSnAjYAvkAJkAePaLUJh9yQhIeyaLVP7C6VUri1z+5ZSKlQptUIpVa+U+lIp5d/mktuA14Fc4OazPa/WugRYAQzs2FcghBB2413g1jaPbwP+e6YTtdYngY+A1LMct9iezwuIb98whRDCYdwGfAIst31/3myrJ64Epmqtt2itzVrrWq31q1rr05PJQpyVJCSEI5iJdcLsC0zGmkh4HAjG+m/gAQClVDQwBnjf9nXrGZ4L27lRwEQguwPjFkIIe7IJ8FFK9VdKOQNzgPfOdKJSygvraoq8sxx3Bn4CNAOHOiZcIYSwX0opT2AW3933zlFKuV3AU4wHvtVaF3VEfMJxuBgdgBCd4GWt9VEApdQ6oExrnW17vJjvlpXdAuRqrXcppWqB55VSg06da7NEKWUGaoHPgD902qsQQoju79QqibXAbqxlGW09opS6H/DBmmiYetrxoUqpGqwrI8zAzVrrso4NWQgh7NIMrGXK/8P6ntAVuBZYfJ7XBwKHOyY04UhkhYRwBEfbfH/yDI9PNaa8FWuG+FRJxlp+uHxtmtbaT2sdrbW+z7asWAghxPl5F2ut8e2cuVzjL1prPyAG6/zc77Tjm2zH/YGlwMgOi1QIIezbbcBHtlKLBuBjvn/fa8aapGjLFevKNIBKILzDoxR2TxISQgBKqWFY65B/pZQ6opQ6AgwBblRKyUoiIYRoB1rrQ1ibW04EFp3jvEJgLvCSUqrHGY4fA34G3KKUGtRB4QohhF1SSpmAK4Cb29z3zgImttkNqRBrcritWL4rk/sSGGx7LiEumiQkhLC6DfgCGIC1iVoq1oaVPYBrDIxLCCHszZ3AFVrr4+c6SWv9BVAK3H2W41XAm8CT7R6hEELYF1ellMepL6w9ePZhXYV26r63L1DMd7shzQceVEol2LYHzQDuAD4E0Fp/ifXeebFSKl0p5aKU8lZK3auUuqNzX57ozuSTXyGsrgNu1VofaTuolHoXa7JimSFRCSGEndFaH7iA0/8M/E0p9fpZjr8IHFBKJWutcy89OiGEsEvLT3t8AHjpDPe9r2O9730Z+BfW8rhlQCjWZMUTWuuVbS6ZBTyBNXkRDlRgTVI80wGvQdgppbU2OgYhhBBCCCGEEEI4GCnZEEIIIYQQQgghRKeThIQQQgghhBBCCCE6nSQkhBBCCCGEEEII0ekkISGEEEIIIYQQQohOJwkJIYQQQgghhBBCdDq72PYzKChIx8TEGB2GEEJ8T1ZWVoXWOtjoODqLzMVCiK7IkeZimYeFEF3RueZhu0hIxMTEkJmZaXQYQgjxPUqpQ0bH0JlkLhZCdEWONBfLPCyE6IrONQ9LyYYQQgghhBBCCCE6nSQkhBBCCCGEEEII0ekkISGEEEIIIYQQQohOZxc9JIQQXVdzczPFxcU0NDQYHUqH8fDwwGQy4erqanQoQghxRjIXCyFE53KEefd0FzMPS0JCCNGhiouL8fb2JiYmBqWU0eG0O601lZWVFBcXExsba3Q4QghxRjIXCyFE57L3efd0FzsPS8mGEKJDNTQ0EBgYaLcTsVKKwMBAh8p+CyG6H5mLhRCic9n7vHu6i52HJSEhhOhw9j4R2/vrE0LYB3ufq+z99Qkhuh9Hm5cu5vVKQkIIIdqYNm0aQ4cO/d7Y008/TWRkJKmpqQwcOJClS5caFJ0QQnRfSiluvvnm1sdms5ng4GAmTZoEwDvvvENwcDCpqakkJCTwwgsvtJ7bdh4eMGAA8+bN6/T4hRCiu+nZs+dZjz344INERkZisVhax55++mn+8pe/fO+8mJgYKioqADhy5Ahz5syhT58+pKenM3HiRPbt23dJMXZYQkIpNUEptVcplaeUeuwMxx9WSu1SSuUqpVYppaJPO+6jlCpWSr3SUTEKIURbNTU1ZGVlUVtbS35+/veOPfTQQ2zbto0FCxZwxx13fG/yFkII8eO8vLzYsWMHJ0+eBOCLL74gMjLye+dcf/31bNu2jQ0bNvDss89SVFTUeuzUPPzJJ59wzz330Nzc3KnxCyGEvbBYLCxevJioqCjWrl17XtdorZk+fTpjxozhwIEDZGVl8dxzz3H06NFLiqVDEhJKKWfgVeAaYABwg1JqwGmnZQMZWutkYCHw/GnHfwd83RHxCSEcS0FBAQkJCdx+++307duXm266iS+//JLhw4cTHx/Pt99+C8CiRYuYPHkyc+bM4cMPPzzjc/Xv3x8XF5fWTLEQQojzN3HiRD777DMA5s2bxw033HDG8wIDA4mLi+Pw4cM/OBYfH4+npyfV1dUdGqsQQtirNWvWkJiYyM9+9rPzXnG2evVqXF1duffee1vHUlJSGDly5CXF0lG7bAwG8rTW+QBKqQ+BqcCuUydorVe3OX8T0LqGTymVDoQCK4GMDopRCNHJfrtsJ7tK69r1OQdE+PDU5MQfPS8vL48FCxbw9ttvc9lll/HBBx+wfv16li5dyh/+8AeWLFnCvHnzePLJJwkNDWXmzJk8/vjjP3iezZs34+TkRHBwcLu+DiGE6CxGzsVz5szhmWeeYdKkSeTm5nLHHXewbt26H5xXWFhIQ0MDycnJPzi2detW4uPjCQkJaZfYhRCioxk5757JqYTw1KlTefzxx2lubv7RrTp37NhBenr6Rf28c+moko1IoKjN42Lb2NncCawAUEo5AX8FHjnXD1BK3a2UylRKZZaXl19iuEJcuobmFhrNLUaHIc4iNjaWpKQknJycSExMZNy4cSilSEpKoqCggKNHj7J//35GjBhB3759cXV1ZceOHa3Xv/DCC6SmpvLII48wf/58h2tSJER3oLWm9mQzxxvNNJpbsFi00SGJ0yQnJ1NQUMC8efOYOHHiD47Pnz+f5ORk4uLiuO+++/Dw8Gg99sILL5CYmMiQIUN44oknOjNsIcQFaDS3oLXMv11VU1MTy5cvZ9q0afj4+DBkyBA+//xz4OxNKTvyvrejVkicN6XUzVhXQYy2Dd0HLNdaF5/rhWut3wDeAMjIyJC/8cIwO0pq+feGApblltJktuDm4oS3uws9PVzw9nChp7sLPd1d8fFoO+ZKTw8X65i79cvbwxVv23Evdxdcne2v5+zFZnHbg7u7e+v3Tk5OrY+dnJwwm8189NFHVFdXt+6bXFdXx7x583j22WcBa+3yI4+cM08qhDDI3iP1fLKthKU5pRRXn/zeMScFLs5OuDop65/OChcnJ1ycFa7OTrh8b9z6vZuz9biLk2289Xr1vedycVa42p5rUC9/RvftHiunjJyLAaZMmcIjjzzCmjVrqKys/N6x66+/nldeeYXMzEyuuuoqpkyZQlhYGPDdPLx06VLuvPNODhw48L2EhRCi85XXN7KztJadpXXsKq1jZ2ktBZUnSAjz5rqMKKYNiiTAy83oMA1n9Lzb1ueff05NTQ1JSUkAnDhxgh49ejBp0iQCAwN/UCpXX1+Pn58fiYmJLFy4sN3j6aiERAkQ1eaxyTb2PUqp8cATwGitdaNt+HJgpFLqPqAn4KaUOqa1/kFjTCGM0txiYeWOI7yzsYCsQ9V4ujkzK91EpF8P6hqaOdZg5lijmfoGM8cazJTUnGRPQ3PrWMt5fGrn4epkTVK425IYHt8lLnraxrw9XAjwcufapHB6uDl3wiu3X/PmzWPlypVcfvnlABw8eJDx48e3JiSEEF1LUdUJluWWsnRbKXuO1OPspBgeF8QtQ609ss0WTXOLBXOLptli/dPcYqHZYv3TOm4ba9GYbec0t1g42dyCueG08dbj1rFm83fPdWpKv3loL3597QA8XGU+Ppc77rgDPz8/kpKSWLNmzRnPycjI4JZbbuGll17iueee+96xKVOm8NZbb/Gf//yHe+65pxMiFkJorSmuPtmafNhRYv2zrL6x9ZxeAZ4kRvgwMSmc9XkVPPPpLp5bsZvx/UO5LiOKkfFBuNjhB27dzbx583jzzTdbe/gcP36c2NhYTpw4wahRo7jpppt47LHH8Pb2ZtGiRaSkpODs7MwVV1zB448/zhtvvMHdd98NQG5uLrW1tZfUR6KjEhJbgHilVCzWRMQc4Ma2Jyi/Vbq+AAAgAElEQVSlBgH/BCZorctOjWutb2pzzu1YG19KMkJ0CRXHGpm3uZD3Nh/iaF0jvQI8+c2kAcxKN+Hb49x1V6dorWlotlDf2NyasLAmKqyP622P246dSmRU1J/gWKPZmvRoNHNqNdy/vs7n1ZvSiAs5+9Y+4uwKCgrw9fX93nafsbGx+Pr6snnzZgMjE0K0VXmskeXbD/PJtlIyD1kbGqb18uO3UxKZmBROsLf7jzxDx2g0t/DX/+3jja/zySyo5pUbZT4+F5PJxAMPPPCj5/3yl78kLS3tjP18nnzySW688UbuuusunJzkDY4Q7cncYiG/4nhr0mFnaS27SuuoazAD4OykiAvuyYi4IAZE+DAw0pf+4T7fuxd+FNhzpI4FmcUsyS5hxY4jhHi7MzPdxOx0E72DZY7sDCdOnMBkMrU+vu+++1i5ciWvv/5665iXlxcjRoxg2bJlXH/99dx///2MGDECpRQhISG8+eabgLVsY/HixTz44IP86U9/wsPDg5iYGF588cVLilF1VH2PUmoi8CLgDLyttX5WKfUMkKm1XqqU+hJIAk6tCSnUWk857Tlux5qQuP9cPysjI0NnZma2+2sQ4pTtxbX8e+NBPs05TFOLhZHxQfxkeAxj+obg5GRMLwGtNcebWthysIpHFuRwsrmFZ6cPZPog049f3Il2795N//79jQ6jw53pdSqlsrTWDtOYV+Zi0RGONZr5YtcRPtlWyrr9FbRYNH1DezI1NZIpKRFEBXgaHWKr1XvL+PlHOZxsauF30wYyK73rzMcyFzvGXCzzsLhQDc0t7DlS37ryYWdpHXsO19Fotm5v7u7iREK4D4kRPgyM8CUxwod+Yd4XtBKsyWzhqz1lLMgsYs2+closmoxof67LiGJicjg93Q3vItAhHGXePd2FzsMd9n9fa70cWH7a2JNtvh9/Hs/xDvBOe8cmxPlobrGwYscR3tlwkK2FNXi6OTNncBS3Xh7TJT75UkrR092FsQkhLJ87kv+bl81D83PYdKCKp6ckSgmHEKLbajJbWLuvnE+2lfDl7qM0NFuI9OvB3aN6MzU1goQwH6NDPKOx/UJYMXckcz/M5pEFOWzMq+CZaQPt9mZbCNG91J5sbu3zsMuWfMgrP9ZaSuzt4UJihA+3DI0mMdKHxAhfegd5XXKZhZuLExMGhjFhYBhldQ0syi5hQWYRj36cy9PLdjIxKZzrMqK4LMZfmoY7IPkNKcRpyusbmfdtIe9tOkRZfSPRgZ48OWkAszJM+HicX1lGZwv18eCDnw7hxS/38+qaPLYV1UgJhxCiW2mxaL49WMXSnBKWbz9C7clmArzcmJ0exdTUCNJ6+Ru2Iu1ChPp48P5Ph/LKV3m8tGof2UU1vHzDIAZG+hodmhDCgTSZLWwpqCK7sLp15UNh1YnW4yHe7gyM9OWqxFASI6zJB5N/jw5PCIT4eHDv6D7cM6o3WwtrWJBZxKe5h1mYVUxMoCezM6KYkRZJuG+PDo1DdB2SkBDCJqeohv9sLODTXGtZxqi+wfxpZgyj+wZ3i5tgF2cnHrm6H5fFBvDQ/G1MeWU9f5iexLRB59pxVwghjKO1ZmdpHZ9sK2FZzmGO1DXg6ebM1YlhTEmNYERcULfcccjZSTF3fDxDegcw98NsZry2kccnJnDbsBj59E8I0WEqjzWyem85X+05ytf7KjjWaO35EBPoSVKkL9dfFtWafDCq584pSinSo/1Jj/bnyckDWLH9CAuyivjz53v56//2MjI+mNkZJq4cEIq7i6z6tWeSkBAOrclsYcWOw7yzsYDswhq83Jy5YXAUtw6LoU83bbYzum8wyx8YyQMfZvPg/G1syq/k6SmJhnZ911rb9U247LUtxIU5WHHcuk3ntlLyK47j6qwY3TeEJ67tz/j+oXZTcja0dyAr5o7ikQU5PL1sFxsPVPL8rGT8PI3ZAk/mYiHsi9aa/WXH+HL3UVbtLmNrYTVaQ6iPO5NTIhjfP4TLYgO67ArfUzzdXJiZbmJmuolDlcdZmFXMx1nF3P9BNn6erkxLjWRWuqlbrjSz93n3dBczD0tCQjiksvoG5m0u4r3NhyivbyQm0JOnJlt3y/Du4pP2+Qjz/a6E45XV1hIOo7q+e3h4UFlZSWBgoF1OyFprKisr8fDwMDoUIbq0o3UNLMspZWlOKbnFtSgFQ2MDuXtUbyYMDDPsTXpHC/By463bMnhr/UH+tHIP1/59PX+/IZX06IBOjUPmYiHsQ5PZwuaDlazaXcaqPUcpqjoJQFKkL3PHxTMuIZSBkT7d9t95dKAXP7+qHw+O78uGvAoWZBXzwbeFvLOxgAHhPszOMDEtNRJ/r67/O8Pe593TXew83GG7bHQm6Sgszte21rKMUppbNKP7BnP78BhGx3ePsoyLsXZfOQ/N30ZDc4shJRzNzc0UFxfT0NDQqT+3M3l4eGAymXB1/X4yy5E6u4PMxeKHak80s3KndZvOb/Ir0dp60zw1NYJJyRGE+TrWm8ecohr+b142JTUnefjKvvxsdJ9O+90jc7FjzMUyD9unM5ViuLs4MSIuiHH9Q7kiIcSu59PaE80szSnho8xitpfU4ubsxJUDQpmVYWJUfDDOXfQe3hHm3dNdzDwsCQlh95rMFpZvt5ZlbCuqoae7C7PSTdx6ebTD7IF8pLaBB+Zl821BFTcMjuKpycaWcDgKR7oJBpmLhfXTkfyK42zKr2Tt3nLW7C2nqcVCbJAXU1IimJIa0W3L4dpLXUMzjy/azqe5hxkZH8Tfrks1vJbb3jnSXCzzsH3QWrPv6DFW7flhKcYVCaGM7x/CsD5BdlPediF2H65jQWYxi7OLqT7RTJiPBzPSIpmdEUVskJfR4YmzkISEcEhl9Q18sLmQ9zcXUl7fSO8gL269PJqZdlKWcaHMLRZe+HIfr64+QEKYN6/elObwbww6miPdBIPMxY7oVP3y5vxKNh2sYnN+FRXHGgEI8/Hg2uRwpqZGkBTp6xDLVc+X1poPtxTx9NKdeHu48sL1KYyMDzY6LLvlSHOxzMPdV6O5hW8PVrFqdxlf7j5KcbW1FGNgpA/jEkIZ3797l2K0tyazha/2HOWjzGLW7C3DomFwbAAvXp9KhJ/s0NHVSEJCOAytNVsLa3j3mwI+236Y5hbNmH7B3D4shlF2XJZxIdbsLePhj3JoaG7huRlJTE2VXTg6iiPdBIPMxY7AYtHsPVpvTUDkV/FtQRVVx5sAawJiaO8AhvQOZEhsALFBXnLj/CP2Hqnn/g+2kld+jJ+N7sPDV/bFpRvuKtLVGT0XK6UmAC8BzsCbWus/nuGc64CnAQ3kaK1vtI3fBvzadtrvtdb/OdfPknm4ezlVirFq91HW7Xe8Uoz2crSugUVbS3jlq/0MiPDhw7sv77JlHI7qXPOwNLUUduHURLQwq4gD5cfp6e7CTUOiHaos43yN6RfCZw+M4IF52cz90LoLh5RwCCHOpMWi2X24jk35lWw+WMWWgipqTjQDEOnXgzH9ghkaG8iQ3gH0CvCUBMQF6hfmzdL7R/DbZTt5bc0BNh+s4u83DCJSPt2zG0opZ+BV4EqgGNiilFqqtd7V5px44FfAcK11tVIqxDYeADwFZGBNVGTZrq3u7Nch2sepUgzrrhhHyS6q+cGuGI5ainEpQn08+NmYPoT5uvPQ/BxeXZ3HA+PijQ5LnCdJSIhuq9HcwqrdZSzILGLtvnIsGjKi/fnjjN5MSomgp7v89T6bcN8ezLtrKH/7Yh+vrTlAdmGNlHAIITC3WNhZWsfmg5Vstq2AqG+w7mPfK8CTK/uHMrS3NQFh8vc0OFr70MPNmT/OTGZYXBCPL9rOxJfW8fysZK5ODDM6NNE+BgN5Wut8AKXUh8BUYFebc+4CXj2VaNBal9nGrwa+0FpX2a79ApgAzOuk2EU7ONFk5tuDVazZW/6DUowHroiXUox2NH2QibV7y3lp1X6GxwV2+m5G4uLIOzbRrWit2Vlax4LMIj7JKaXG1szm3tF9mJVuktUQF8DF2YlHJyQwODaAh+ZvY8rL6/mDlHDYlc5cJiy6p+YWC7nFta0JiKxD1RxrtCYgegd5MSk5nCG2FRDhvvKpfUeakhJBcqQv/zcvm3vezeK2y6P51cT+snqt+4sEito8LgaGnHZOXwCl1Aas8/XTWuuVZ7n2B7+klVJ3A3cD9OrVq90CFxfHOq/WsH5/JRsOVJBdWE1zi24txbhvTJyUYnSgZ6YNJKuwmrkfbmP53JH4OGDfuO5GEhKiW6g81sji7BIWZhWz50g9bi5OXDUglNkZUYyIC5I6sUswpl8Iy+eObFPCUcVTkwfITXA3J8uExZk0mlusCQhbCUbWoWpONLUAEBfSk6mpEdYVELEBhPjIzXJniwny4uOfDeNPK/fw1vqDbCmo5pUbB0my3f65APHAGMAEfK2USjrfi7XWbwBvgLWHREcEKM7uVBnGhrwKNuRVsPlgFccazSgFiRE+3DEiluF9grgsJkBKMTqBj4crL14/iOv++Q2/WbKDl+YMMjok8SMkISG6rOYWC6v3lLEwq5iv9pRhtmhSTL78btpApiRH4OspGc/2cqqE469f7OMfaw6QXVjNazelyU1w9ybLhAVNZgvZhdVsyq9iU34lWwuraTRbAEgI82Z2uokhvQMZHBtAUE/ZerIrcHNx4jeTBjCsTyA/X5DDpJfX8+z0gUwfZDI6NHFxSoCoNo9NtrG2ioHNWutm4KBSah/WBEUJ1iRF22vXdFik4ryV1JxsTUBsPFBJeb11d6GYQE+mpkYwPC6Iy3sH4u/lZnCkjik92p8Hx8Xz1y/2MaZfsMyfXZwkJESXs+dIHQszi1myrYSKY00E9XTnjhGxzEo30TfU2+jw7JaLsxO/tJVwPDx/G5OlhKO76/BlwqJrKqtrYM3ecr7aU8b6vIrWT+r6h/lw45BeDIm1JiAC5Ea5SxvXP5QVc0cyd942Hpqfw/r9lTwzNREv6Y/U3WwB4pVSsVgTDHOAG087ZwlwA/BvpVQQ1rk5HzgA/EEp5W877yqsq9pEJ6s50cQ3BypZb0tAHKw4DkBQTzeG9QliRFwQw+ICpbdOF3Lf2DjW7a/gN0t2ktbLn+hAL6NDEmchv9VEl1BzoomlOaUsyCxme0ktLk6Kcf1DmJ0exeh+wbjKNmidZqythOP/PrCWcGw+WMWTk6SEw05d0jJhkNrlrqDFotlWVMPqPWWs3lvGztI6AMJ9PZicEtG6E4asKut+wn178MFdQ/j7qv28vDqP7KJqXr0xjf7hPkaHJs6T1tqslLof+Bxr4vdtrfVOpdQzQKbWeqnt2FVKqV1AC/ALrXUlgFLqd1iTGgDPnFq5JjpWQ3MLWwqq2JBXyYa8CnaU1qI1eLk5M6R3IDcPjWZ4XCD9Qr2lGWUX5eykeGFOKte8+DVzP9zGgnsvl/cTXZTSuvuXmsmey91Ti0Xz9f5yFmYW88WuozS1WOgf7sPsdBNTUyMIlOXDhmpusfA3WwlH/3AfXpU65gt2rj2XO+FnX451xcPVtse/AtBaP9fmnNexLhP+t+3xKuAxIA4Yo7W+xzb+T2CN1vqcJRsyF3eequNNfL2vnNV7y1i7r5yaE804OynSe/kzJiGYsf1CSAiTG2V7sjGvgrnzt1F7spnfTBrAzUN6yf/f82TkXNzZZB6+OOYWC9tLatl4oJL1+yvIKqymyWzBxUmR1suf4XFBDI8LJCXKT97UdjPLtx/mvve3cv/YOB65up/R4Tisc83DskJCdLoD5cdYkFnM4uxijtY14u/pyo1DejE7w0RihK/R4Qkb11MlHDEBPPyRtYTjuZnJTEmJMDo0cX5kmbAdsVg0uw7Xta6COLV3faCXG1ckhDC2Xwij4oNlFYQdGxYXxIq5I3n4oxx+s2QHG/Mq+OPMZHx7yP9zIS6U1poD5cdb+0B8k1/ZusVx/3Afbh0azfD4IAbHBEiZVDc3MSmc6zJMvLomjxHxQQztHWh0SOI08i9MdIq6hmY+yz3MgswithbW4OykGNM3mKcnm7iifwjuLlIO0FWNTQjhswdG8n/zsnlgXjab8yv5jZRwdHmyTLj7q2toZsP+ClbvLWP13vLWpmkpJl/mjotnbL8QkiJ9cZJdhhxGUE933rn9Mv61Lp8/f76X3OJ1/OvWDAZESAmHED/maF0DG/IqWG9LQhyts86pJv8eXJsUbm1E2SdQGvzaoacmJ7KloJqH5m9jxdyR+HlKD6WuREo2RIexWDTf5FeyILOIlTuP0NBsIS6kJ7PTTUwfFClbynUzzS0W/vq/fby+1lrC8dpNacQGSYOgc3GkZcIgc/Gl0lqTV3aM1XvL+GpPGZkF1ZgtGm8PF0b1DeaKfiGM6htMsLfcLAvILqzm7neziA304qN7Lzc6nC7NkeZimYe/c7zRzOaDlazfX8n6vHL2HT0GQICXG5f3CWREXBDD+wTRK1AaUTqC7cW1zPjHBsYlhPKPm9Ok5K2TScmG6FQnmswsyCzm7Q0HOVR5Am8PF2ammZidEUWKyVcmgG7K1dmJx65JYEhsAA99tI0pr6xn1c9HE+ItiSUhLtbJpha+ya/gqz1lrN5TTknNScC6Jeddo3oztl8Iab38cJGaZXGaQb38+cnwGJ5fuZeCiuPESIJYODhzi4XcklrW769g/f4KthZak7ruLk4Mjg1gZpqJ4XFBDAj3kZVlDijJ5MsjV/XjuRV7mL+liDmDpRF3VyEJCdFujtQ28J9vCvhgcyG1J5tJjfLj4Sv7cnVimCzvtyNjE0L48O6hTHhxHZ9kl3LXqN5GhyREt3Ko8ritF0Q53+RX0mS24OnmzPC4IP7f2DjG9Asmwq+H0WGKbmDGIBN/+XwvH28t5udXSbM24Vi01hyssPaBWLf/uz4QSkFihA8/HdmbkfFBpEf7y32oAOCukb35en85v122i4yYAOJCpFl7VyAJCXHJdpbW8ta6gyzNKcWiNVcnhvHTkb1Jj/b/8YtFt5QQ5kOKyZePtxZLQkKIc9BaU1B5gtziGrILa/h6fzn55db963sHeXHzkGjGJgQzODZAeumICxbm68HI+GA+zirmwfF9cZZPfYWdqzzWyIYDlWzYb+0FcWpVWaSftQ/EiPgghvUJIsBLegSIH3JyUvztulQmvPg1cz/MZtF9w+R3bxcgCQlxUSwWzZp9Zfzr64N8k1+Jp5szt1wezU+GxUotnoOYkWbiqaU72X24jv7h0lBNCK01h2sbyC2uJbe4pvXPOlvndncXJ4b0DuSWodGM7RciS+xFu5idYeL+D7LZeKCCkfHBRocjRLtqaG5hS0GVtQwjr4KdpXUA+Hi4MKxPEPeO6cPIuCCiAz2lJFicl1AfD56flcJd/83kL5/v5YlrBxgdksOThIS4IA3NLXy8tZi31h8kv/w44b4e/OqaBOYM7iVbjzmYySkR/O7TXSzOLpGEhHBIlccabUkHa+Ihp7iWimPWru0uTop+Yd5cmxxBismXZJMf8aE9Zf960e7G9w/Ft4crC7OKJSEhuj2LRbOztI71eRWszytnS0E1TWYLrs6KtF7+PHJVX0bEB5MU6SsrgsRFu3JAKLcMjeZf6w4yMj6YUX1l7jSSJCTEeSmvb+Tdbwp4b3MhVcebGBjpw0tzUpmYFC432A4qwMuNMf2CWZJdwi8nJMiNgbBrdQ3N7CiuJbfElnwoqm1dKqwU9Anuyai+QaSY/Eg2+dI/3EdqlkWn8HB1ZkpKBB9lFlF7slk+HBDdTlHVCVsCooKNeRVUn2gGrM19bxkazYj4IIbEBuDpJm9bRPt54tr+bMqv5OcLclg5dySBst2rYeRftjinfUfreXNdPkuyS2m2WBiXEMpPR8YyJDZAlsYJZqSZ+HJ3GRvyKiS7LOxGQ3MLO0trySmqZXtJLTnFNa19HwB6BXiS2suP24ZFk2zyY2CkLz3d5depMM7sDBPvbjrEp7ml3DQk2uhwhDgnrTXfHqxiaU4p6/MqOFR5AoBQH3euSAhlRHwgw+OCZBcv0aE8XJ35+w2DmPrqBh5dmMubt2XIexuDyB2U+AGtNevzKvjXuoN8va8cD1cnrrvMxB3DY+kdLN1oxXeuSAjB28OFxdklkpAQ3VJzi4W9R+rJKa5he3EtOcW17DtaT4tFA9Yb5KRIP6anRpIc5UdypC/+0ixNdDFJkb70C/VmQWaxJCREl1V7spnFW4t5f3Mh+8uO4enmzOW9A7l9WAwj4oKIC+kpbwhFp+of7sPj1yTw9LJdvLvpELdeHmN0SA5JEhKiVaO5hU+2lfLWuoPsPVpPsLc7j1zVl5uGRMsNuDgjD1dnJiWHsyS7lN9PM+MlnxKLLkxrTVHVSTIPVZFTZO35sOtwHU1mCwB+nq4kRfoyLqEPySZfUqL8CPWRT+hE16eUYnaGid9/tpu8snriQryNDkmIVrnFNby36RBLc0ppaLaQYvLl+ZnJTEoJlzIMYbjbhsWwdl85v/9sN0NiA+kXJvNnZ5NZQFB1vIn3Nx3iP98couJYIwlh3vxldgqTU8JlKxzxo2akmZj3bRErdxxhZrrJ6HCEaGVusbD7cD1bCqrIPFRFZkE1ZfXWppNebs4MjPTltsutZRcpJj+iAnrIp3Oi25qaGslzK/awIKuYX13T3+hwhIM70WRm6bZS3t9cyPaSWnq4OjMtNZKbhkSTZPI1OjwhWiml+PPsFCa8uI4H5mXzyf3DpQdUJ+uQhIRSagLwEuAMvKm1/uNpxx8GfgqYgXLgDq31IaVUKvAPwAdoAZ7VWs/viBgFHCg/xtvrD/Lx1mIami2M6RfMT0f0ZnhcoNyUi/OWEe1PVEAPFmeXSEJCGOpYo5nswmq2FFSTdaiK7MIaTjS1ANY96of1CSQ9JoCMaH/6hnpLI1ZhV4K93RnbL4RFW0v4xVX9cJGG08IAe4/U88HmQyzaWkJ9o5m+oT15Zmoi0wZF4uMhDVdF1xTU052/XpfCbW9/y3PLd/PbqQONDsmhtHtCQinlDLwKXAkUA1uUUku11rvanJYNZGitTyilfgY8D1wPnABu1VrvV0pFAFlKqc+11jXtHaej0lqzKb+KN9fls2pPGW4uTswYFMkdI2LpGypLlMSFU0oxPTWSl1fncbj2JOG+PYwOSTiII7UNbCmoIutQNVsKqth9uA6LBidlrQudnW4iIyaAjBh/+XspHMLsDBNf7j7Kuv0VjE0IMToc4SAazS2s2H6E9zcfYktBNW7OTkxMCuPmodGkR/vLh1yiWxjdN5g7R8Ty1vqDjOobzLj+oUaH5DA6YoXEYCBPa50PoJT6EJgKtCYktNar25y/CbjZNr6vzTmlSqkyIBiQhMQlam6x8FnuYd5cn8+OkjoCvNyYOy6em4dGE+wt29yISzM9zcTfv8rjk22l3Du6j9HhCDtksWj2ldVbVz8UVLGloLp1280ers4M6uXH/VfEkxHtz6BefnjLJ3HCAY3tF0KAlxsLsookISE6XEHFceZ9W8iCrGKqjjcRHejJ4xMTmJUeRYD0HhPd0KMT+rHxQCW/WJjLyrkjCZE+Up2iIxISkUBRm8fFwJBznH8nsOL0QaXUYMANONCu0TmYhuYW3tt0iDfXHeRIXQN9gr14bkYS0wdFSn2UaDexQV4M6uXHoq3F3DOqt3waIi5ZQ3MLOUU1ZNpWP2w9VE1dgxmwLk2/LMafO0fEkhHjT/9wH1xleboQuLk4MS01kvc2HaL6eJM0pBbtztxi4cvdZby/+RDr9lfg7KS4sn8oNw3txfA+QThJKZzoxtxdnHn5hlQmvbyeny/I4T8/GSx/pzuBoU0tlVI3AxnA6NPGw4F3gdu01pazXHs3cDdAr169OjjS7qehuYUPvy3ktTUHKKtvZGjvAJ6bkcTovsHyD0t0iBlpJn6zZAc7S+sYGCkNq8SFqTzWSOahajILqsg8VM2OklqaW6xbb8aH9OTa5Agyov25LCZAmk8KcQ6zM0y8veEgS3NKuW1YjNHhCDtxuPYk874tYv6WQo7WNRLu68HDV/bl+suiZDciYVfiQrx5clIijy/ezlvrD3LXqN5Gh2T3OiIhUQJEtXlsso19j1JqPPAEMFpr3dhm3Af4DHhCa73pbD9Ea/0G8AZARkaGbp/Qu78ms4WPMot4dXUeh2sbGBwbwN9vGMTQ3oFGhybs3KSkcJ5ZtpPF2SWSkBDnZWlOKev3l5NZUE1+xXEA3JydSIny5c4Rvbksxp/0aH/8POVTXiHOV/9wHxIjfFiQVSQJCXFJLBbN1/vLeX9zIat2H0VjrbP//bRoxvYLlsapwm7dMDiKtfvKeP7zPVzeJ1DuaztYRyQktgDxSqlYrImIOcCNbU9QSg0C/glM0FqXtRl3AxYD/9VaL+yA2OxWc4uFj7OKefmrPEpqTpLWy4+/zE5hWB/ZMUN0Dn8vN8b2C+GTbaX86poEuVERP2pBZhHbS2rJiPbnusuiyIj2Z2Ckr5STCXGJZqebeHrZLnYfrqN/uI/R4YhupuJYIwsyi/ng20MUVZ0kqKcb947uww2DexEV4Gl0eEJ0OKUUf5yRzDUvWbcC/fSBEXi6GVpYYNfa/b+s1tqslLof+Bzrtp9va613KqWeATK11kuBPwM9gQW2N8uFWuspwHXAKCBQKXW77Slv11pva+847YW5xcKSbaX8fdV+CqtOkBLlxx9mJDEqPkgSEaLTzUgz8b9dR1mXV8HYftJQTZzbKzek4e3hImVkQrSzqamRPLt8NwuzivnNpAFGhyO6Aa013x6s4r3NhazccZjmFs3Q3gE8enUCVyeG4eYiHzIIx+Lv5cbfrk/hpjc387tPd/HcjGSjQ7JbHZLq0VovB5afNvZkm+/Hn+W694D3OiIme9Ni0SzLKeWlVfs5WHGcgZE+vH17BmP7hUgiQhhmbEIwvj1cWby1RBIS4kf5espOGEJ0BH8vN3V5KpgAACAASURBVMb3D2VJdgmPXZMgTV/FWdWebGbR1mLe31xIXtkxfDxcuHloNDcN6UVciGwHLxzbsD5B/Gx0H15bc4BR8cFckxRudEh2SdaedDMWi2b5jsO8+OV+8sqOkRDmzT9vSeeqAaGSiBCGc3dxZlJyOB9vLaa+oVm2XhRCCIPMzjCxYscRvtpTxtWJYUaHI7qobUU1/HbZLlKj/PjzrGQmJUfQw03K5oQ45aEr+7Ihr4LHFm0nJcqPCL8eRodkdyRl3k1orVm54zDXvLSO+z/IRgGv3pjG8gdGcnVimCQjRJcxI81EQ7OFFTuOGB2KEEI4rFHxwQR7u7Mwq9joUEQXNjIuiOUPjGTJ/xvO7IwoSUYIcRpXZydemjMIc4uFh+Zvo8Uieym0N0lIdHFaa77cdZRJL6/n3ve20txi4aU5qax8cBTXJodL7bXoctJ6+RET6MnirT/YXEcIIUQncXF2YsagSFbvKaPiWOOPXyAckpOTYkCEND4V4lxigrx4ZupANh+s4vW1B4wOx+5IQqKL0lqzem8ZU1/dwE//m8mxRjN/uy6F/z00iqmpkThLIkJ0UUoppg2KZNPBSkpqThodjhBCOKzZGSbMFs2SbEkQCyHEpZiRFsmUlAj+9sU+sgurjQ7HrkhCoovRWrN+fwUz/7GRn/x7C1XHm3h+ZjJfPjyaGWkm2UpRdAszBpnQGrkJFkIIA8WFeJMa5ceCzGK0lmXGQghxsZRS/H76QMJ8PJj74TbqG5qNDsluyLvbLuSbA5Vc/89N3PzWZo7UNvCH6Ul89fMxXHdZlHTIFt1Kr0BPMqL9WZxdIjfBQghhoFnpJvYerWdHSZ3RoQghRLfm4+HKS3NSKa4+wVOf7DQ6HLsh73K7gMyCKm781yZu+NcmCiqP88zURFb/Ygw3Dukl+z6Lbmt6WiR5ZcfkJlgIIQw0OSUCdxcnFmQVGR2KEEJ0exkxATwwLp5F2SWyEridyLtdA2UXVnPLW5uZ9fo37Dtaz28mDeDrR8dy6+UxuLtIl2PRvU1KisDN2YmPt0qHdyGEMIpvD1euTgzjk22lNDS3GB2OEEJ0e/ePjSMj2p9fL9lBYeUJo8Pp9iQhYYDtxbXc8c4Wpr+2kZ2ldTw+MYGvHx3LnSNi8XCVRISwD76erozrH8KynFKaWyxGhyOEEA5rdoaJ2pPNrNpdZnQoQgjR7bk4O/HinFSUgrnzszHLfe4lkYREJ8opquGu/2Yy+ZX1bC2s5tEJ/Vj36FjuHtUHTzcXo8MTot1NHxRJ5fEm1u0vNzoUIYRwWMP6BBHu6yFlG0II0U5M/p48Oz2J7MIa/r5qv9HhdGvyLriDaa1Zu6+cf67N55v8Srw9XHj4yr78ZHgM3h6uRocnRIca0y8Ef09XPt5awhUJoUaHI4QQDsnZSTEzzcRra/I4UttAmK+H0SEJIUS3NyUlgq/3lfPK6jxmZ0QRFeBpdEjdkqyQ6CDNLRYWZxdzzUvruP3fWzhYcZwnJvZn42NX8MC4eElGCIfg5uLE5JQIvth1lNqTsj1SZ1NKTVBK7VVK5SmlHjvD8duVUuVKqW22r5+2OdbSZnxp50YuhGhvs9JNWDQsliZsQgjRbh4cH49Fw7LcUqND6bYkIdHOjjeaeWv9QUY/v5qH5udg0Zq/zE7h60fHcteo3pKIEA5n+qBImswWVmw/bHQoDkUp5Qy8ClwDDABuUEoNOMOp87XWqbavN9uMn2wzPqUzYhZCdJyYIC8ui/FnQVaRbMfciS4xMfwnpdQO29f1nRu5EOJ8mPw9GdTLj2U5cp97sSQh0U7K6xv58+d7uPy5Vfzu011EBXjy9u0ZrJw7ilnpJtm+Uzis1Cg/egd5sUg+letsg4E8rXW+1roJ+BCYanBMQggDzU6PIr/8OFsLa4wOxSFcSmJYKXUtkAakAkOAR5RSPp0UuhDiAkxOjmD34ToOlB8zOpRuSd4lX6L88mP8atF2hv/pK15bc4BhfYJYfN8w5t9zOVckhOLkpIwOUQhDKaWYPiiSbw9WUVQlWyN1okigbQe7YtvY6WYqpXKVUguVUlFtxj2UUplKqU1KqWkdGqkQolNMTA6nh6szC7NkO+ZOcimJ4QHA11prs9b6OJALTOigOIUQl+Da5HCUgk9llcRFkYTERcourObed7MY97e1fLy1mFnpJlY9PJrXb0lnUC9/o8MTokuZNsj6PniJrJLoapYBMVrrZOAL4D9tjkVrrTOAG4EXlVJ9zvQESqm7bYmLzPJy2U1FiK6sp7sL1ySF8WlOKSebWowOxxFcSmI4B5iglPJUSgUBY4GoM1wrhDBYqI8Hl8UEsCy3VEriLoIkJC6AxaJZtfso1/3zG6a/tpGNByr4f2Pi2PDLK/jD9CR6B/c0OkQhuqSoAE8GxwawOLtEJurOU8L3b15NtrFWWutKrXWj7eGbQHqbYyW2P/OBNcCgM/0QrfUbWusMrXVGcHBw+0UvhOgQs9OjqG808/nOI0aHIqzOmBjWWv8PWA5sBOYB3wBnzCJJYlgI401ODiev7Bh7j9YbHUq3IwmJ89BktrAgs4irX/yaO/+TSXHVCX4zaQAbfzWOR67uR7C3u9EhCtHlzRgUSX7FcXKKa40OxVFsAeKVUrFKKTdgDvC93TKUUuFtHk4BdtvG/ZVS7rbvg4DhwK5OiVoI0aGGxAYQFdBDyjY6x6Umhp+19ZW4ElDAvjP9EEkMC2G8a5LCcZKyjYsiCYlzqG9o5o2vDzDq+dX8YmEuzk6KF65PYe2jY7lzRCw93V2MDlGIbuOapHDcXJxYtFVugjuD1toM3A98jjXR8JHWeqdS6hml1KldMx5QSu1USuUADwC328b7A5m28dXAH7XWkpAQwg44OSlmppnYcKCCkpqTRodj7y4lMeyslAq0fZ8MJAP/65SohRAXLKinO8P6BPGplG1cMHlHfQZldQ28vaGA9zcdor7RzLA+gfxpVjKj4oNQSppUCnExfHu4cuWAUJbllPLrawfIzjOdQGu9HOuS37ZjT7b5/lfAr85w3UYgqcMDFEIYYmaaiRe/3M/HWcU8MC7e6HDsltbarJQ6lRh2Bt4+lRgGMrXWS7EmhqcAZqCK7xLDrsA6231nHXCzLdEshOiiJiWH89ii7ewsrWNgpK/R4XQbkpBoI6/sGP/6Op/F2SWYLRauSQrnnlG9STb5GR2aEHZhxqBIPss9zNp95Vw5INTocIQQwiFFBXgyrE8gC7OKuX9snOwI1oEuITHcgHWnDSFENzFhYBi/XrKDZTmlkpC4APIRJZBZUMVd/81k/N/WsmRbCddfFsXqR8bw6o1pkowQoh2N6htMoJeblG0IIYTBZqWbKKw6wZaCKqNDEUIIu+Dn6cbI+CA+zT0sZRsXwGETEhaL5n87jzDzHxuZ9fo3bCmo4oFx8Wx87Ap+N20g0YFeRocohN1xdXZickoEq3aXUXui2ehwhBDCYV0zMJye7i4skOaWQgjRbiYlR1BSc5LsohqjQ+k2HDIhkV1YzfgX1nL3u1kcqW3g6ckD2PjYFTx8ZV8Ce8qOGUJ0pBlpkTS1WPhsu3QhFkIIo/Rwc2ZScjjLtx/meKO0JhBCiPZwZWIobs5OstvGBXDIhESYrwfeHq68NCeVtb8Yw+3DY/F0k3YaQnSGpEhf4kJ6StmGEEIYbFa6iRNNLSyXBLEQQrQLHw9XRvcL5rPtpVgsUrZxPhwyIRHu24NP/t9wpqZG4uLskP8JhDCMUorpgyLJPFRNYeUJo8MRQgiHlR7tT+8gLynbEEKIdjQ5JYKjdY3So+c8ybtxIUSnmzYoEoDF2SUGRyKEEI5LKcXMdBPfHqziUOVxo8MRQgi7MC4hBA9XJz7NldVn50MSEkKIThfp14PLeweyKLtYuhALIYSBZqaZcFLwsaySEEKIduHl7sK4hFCWbz+MucVidDhdniQkhBCGmJ4WyaHKE2wtlC7EQghhlDBfD0bEB/Px1hKpdxZCiHYyKTmcyuNNbMqXso0fIwkJIYQhrhkYhruLE4uz5VM5IYQw0ux0EyU1J9l4oNLoUIQQwi6MTQjBy82ZT3NLjQ6ly+uwhIRSaoJSaq9SKk8p9dgZjj+slNqllMpVSq1SSkW3OXabUmq/7eu2jopRCGEcbw9Xrk4MY1nOYRrNLUaHI4QQDuvKAaH4eLiwMKvI6FCEEMIueLg6c+WAUFbuPEKTWco2zqVDEhJKKWfgVeAaYABwg1JqwGmnZQMZWutkYCHwvO3aAOApYAgwGHhKKeXfEXEKIYw1PS2S2pPNrN5TbnQoQgjhsDxcnZmSGsGKHUeoa2g2OhwhhLALk5IjqDnRzIa8CqND6dI6aoXEYCBPa52vtW4CPgSmtj1Ba71aa31qz79NgMn2/dXAF1rrKq11NfAFMKGD4hRCGGhkXBBBPd2lbEMIIQw2Oz2KRrOFT3OkK7wQQrSHkX2D8PZwYZmUbZxTRyUkIoG26/6KbWNncyew4kKuVUrdrZTKVEpllpfLp6tCdEcuzk5MTY3gqz1lVB9vMjocIYRwWMkmX/qG9pSyDSGEaCfuLs5MSAzji51HaWiW8uSzMbyppVLqZiAD+POFXKe1fkNrnaG1zggODu6Y4IQQHW76oEiaWzSfbpdP5YQQwihKKWalm9haWENe2TGjwxFCCLswKSWC+kYzX++TD9DPpqMSEiVAVJvHJtvY9yilxgNPAFO01o0Xcq0Qwj4kRvjQN7Qni7dK2YYQQhhp2qBInJ0UC7NkPhZCiPYwrE8g/p6uLMuVD97OpqMSEluAeKVUrFLKDZgDLG17glJqEPBPrMmIsjaHPgeuUkr525pZXmUbE0LYIaUUM9Ksn8odrDhudDhCCOGwQrw9GNsvmEVbizG3SFd4IYS4VK7OTkwYGM6q3Uc52SRlG2fSIQkJrbUZuB9rImE38JHWeqdS6hml1BTbaX8GegILlFLblFJLbddWAb/DmtTYAjxjGxNC2KmpqREoBYuzZTGUEEIYaVa6ibL6RtZJV3ghhGgXk1PCOdHUwld7yn78ZAfk0lFPrLVeDiw/bezJNt+PP8e1bwNvd1RsQoiuJdy3B8P6BLI4u5iHxsejlDI6JCGEcEhXJIQS4OXGwsxixvYLMTocIYTo9obEBhLs7c6nuaVcmxxudDhdjuFNLYUQAmDGIBNFVSfJPFRtdChCCOGw3Fysux99sesoNSdk9yMhhLhUzk6KiQPD+GpPGccazUaH0+VIQkII0SVMGBhGD1dnFm2Vsg0hhDDSrHQTTS0WluaUGh2KEELYhUkpETSaLXy566jRoXQ5kpAQQnQJXu4uXJ0Yyqe5pbJXsxBCGCgxwpcB4T4syJTdNoQQoj2k9/In3NeDT3Ml0Xs6SUgIIbqMGWkm6hvM0vRHCCEMNjvDxPaSWvYcqTM6FCGE6PacnBTXJoWzdl85tSeajQ6nS5GEhBCiyxgeF0SIt7uUbQghhMGmpkbi6qxYKKskhBCiXUxKiaC5RfP5riNGh9KlSEJCCNFlODsppqZGsGZvGZXHGo0ORwghHFaAlxvjEkJZsq2E5haL0eEIIUS3l2LyJSqgB5/mHjY6lC5FEhJCiC5lRpoJs0XLZC2EEAabnWGi4lgTq6WMTgghLplSiknJEWzIq6DquOxidIokJIQQXUr/cB8SwrxZlC1lG0IIYaTRfYMJ6unOwiwp2xBCiPYwKTmcFotm5Q4p2zhFEhJCiC5nRlokOUU1HCg/ZnQoQgjhsFycnZiRFslXe8qokDI6IYS4ZAPCfegd5MUy2Va5lSQkhBBdztTUSJwULJbmlkIIYajZ6dYyuiWyak0IIS6ZtWwjnM0HKymrbzA6nC5BEhJCiC4n1MeD4XFBLM4uwWLRRocjhBAOKz7Um5QoPxZmFaO1zMdCCHGpJqdEYNGwYruUbYAkJIQQXdSMtEhKak7ybUGV0aF0W0qpCUqpvUqpPKXUY2c4frtSqlwptc329dM2x25TSu23fd3WuZELIbqSWekm9hypZ2dpndGhCCFEtxcf6k2/UG8+zZWyDZCEhBCii7o6MQxPN2cp27hISiln4FXgGmAAcINSasAZTp2vtU61fb1puzYAeAoYAgwGnlJK/X/27j1KrvOs8/3v13epqrt16WpLJcmWqiQn7nYUO5E9BCYBQkhkcGQgCdjAmngdGMOAj1krMAv7wPLMOJM5kAwMhzWeRUyAJDMn4xiHi2wUHJ+QywJikIgtOZLiWGpfdLPVut/Vt+f8UbvlSqclta2u2l21v5+1eqX2rndXPdvt9Xrn6fd9noV1Ch3AHLNhbVEdbS368y170g4FAJrCrWuXavOLR7X/2Nm0Q0kdCQkAc9L8jjatv36JNj17QOdGx9MOpxHdLGlXRAxFxIikhyXdNsNr3yfpyYg4EhFHJT0paX2N4gQwx/XOb9f7Bpfor7fu1/kx5mMAuFK3vrUoSdr0LG3uSUgAmLN+6sblOnl+TE/ueDXtUBrRMknVf87cm5yb6gO2t9l+1PaK13ktgIz44NuX69iZUX1558G0QwGAhreqL6frl/XosW0kJEhIAJiz3lFerCU9XfpLqrvXymOSVkbEWlVWQXzm9X6A7btsb7G9ZXh4eNYDBDA3/OvVfVra28W2DQCYJbeuLWrrnmPac+RM2qGkioQEgDmrtcW67caivvadYR06dT7tcBrNPkkrqo6XJ+cuiIjDETH5D/ZTkt4+02urPuOhiFgXEesKhcKsBA5g7mltsX7qbcv0te8M69UTtKoDgCv1429ZKkl6LOPFLUlIAJjTfurG5RqfCG18JtuT9RuwWdIa26tsd0i6XdLG6gG2l1YdbpC0M3n9hKT32l6YFLN8b3IOQIZ94G3LNRFi1drrdIUdjz5ue7vtnbb/0LbrGz2AWlmxaL5uWLFAj2/N9rYNEhIA5rQ3LenWYLGHB+DXKSLGJN2tSiJhp6RHImK77Qdsb0iG3ZM86G6VdI+kO5Nrj0j6qCpJjc2SHkjOAciwUiGvddcs1J9v2aOISDuchnCFHY++X9IPSFor6XpJN0n6wfpEDqAe3v/WonYcOKGh4VNph5IaEhIA5ryfvHGZnt13XM+/ejLtUBpKRGyKiGsjohwRH0vO3R8RG5PX90XEYES8NSJ+OCK+XXXtn0bE6uTnz9K6BwBzy4fWLdfu4dN6es+xtENpFFfS8SgkdUnqkNQpqV0SVZ6BJvLjb1kqW3o8w8UtSUgAmPM23FBUa4v1F6ySAIBU/dhblqrF0lefo4jtDL3hjkcR8Q1JX5F0IPl5IiJ2TnMtgAa1pLdLN12zSI9tze7WZBISAOa8/u4uvXNNn/766X2amGCZMACkpburXcsXzs/08uIamLbjke3Vkq5TpbDwMknvtv3OqRfT7QhobLe+dameP3hKz72SzZXAJCQANISfvHGZ9h8/p6deOJx2KACQaaVCTkPDp9MOo1FcScejn5T0VESciohTkr4o6R1Tv4BuR0Bju+X6ysqzxzPabYOEBICG8N6BJcp3tukvvsm2DQBIU7mQ1wuHTrNibWaupOPRy5J+0Hab7XZVClqyZQNoMoXuTr2jvFiPbzuQyYLBJCQANIR5Ha1af/0SPfGtV3gIBoAUlQo5nR0d14ET59IOZc67ko5Hkh6VtFvSs5K2StoaEY/V9QYA1MWta4t64dBpbd9/Iu1Q6o6EBICGcePVC3Ty/Jj2Hz+bdigAkFmlvrwkUUdiht5ox6OIGI+IX4qI6yJiICI+kuZ9AKid9YNL1NZiPZbBbRskJAA0jHKh8hC8m73LAJCaciEnSdSRAIBZsjDXoX+9pk+Pb83etg0SEgAaxoWExEH+KgcAaSl0dyrf2cYKCQCYRbeuLWrfsbN6es+xtEOpKxISABpGX75DvfPatZuHYABIjW2VCzkNHWKFBADMlvcOXqWO1hY9vvVA2qHUFQkJAA1j8iGYhAQApKtUyLNlAwBmUU9Xu951bUGbnj2QqQLuNUtI2F5v+znbu2zfO83777L9Tdtjtj845b2PJ9WGd9r+Q9uuVZwAGku5kKeGBACkrNSX075jZ3VmZCztUACgabz/rUv1yolz2vLS0bRDqZuaJCRst0p6UNItkgYk3WF7YMqwl1Vpa/S5Kdd+v6QfkLRW0vWSblKl7zIAqNyf1/DJ8zp+djTtUAAgs0pJTZ8X2LYBALPmPdddpa72Fj22NTvdNmq1QuJmSbsiYigiRiQ9LOm26gER8WJEbJM0MeXakNQlqUNSp6R2Sa/WKE4ADWaysCXF1AAgPSU6bQDArMt1tundb+7XF791QGPjU/9vcnOqVUJimaQ9Vcd7k3OXFRHfkPQVSQeSnyciYufUcbbvsr3F9pbh4eFZCBlAI5hsN8e2DQBIz6q+nGwSEgAw225dW9ShUyP6pxeOpB1KXcy5opa2V0u6TtJyVZIY77b9zqnjIuKhiFgXEesKhUK9wwSQkhWL5qu91RS2BIAUdbW3atmCeRo6xFwMALPph9/Ur1xHqx7flo1tG7VKSOyTtKLqeHlybiZ+UtJTEXEqIk5J+qKkd8xyfAAaVHtri65ZnNPugzwEA0CaSoU8yWEAmGXzOlr1noGr9MVvvaLRDGzbqFVCYrOkNbZX2e6QdLukjTO89mVJP2i7zXa7KgUtv2fLBoDsovUnAKSv1JfTC8OnFZGd9nQAUA+3ri3q2JlR/f2uQ2mHUnM1SUhExJikuyU9oUoy4ZGI2G77AdsbJMn2Tbb3SvqQpE/a3p5c/qik3ZKelbRV0taIeKwWcQJoTOVCXi8dPpOJrDEAzFXlQk6nR8b16onzaYcCAE3lXdf2qburTY9vPZB2KDXXVqsPjohNkjZNOXd/1evNqmzlmHrduKRfqlVcABpfuZDX2ETopcNntLo/n3Y4AJBJpaquR0t6u1KOBgCaR2dbq943uERPfOsVnR+7Xp1trWmHVDNzrqglAFxOOUlCsG0DANIz2YZ59yE6bQDAbLt17VKdPD+mrz3X3B0lSUgAaDilC60/SUgAQFqu6ulUrqOVIsMAUAM/sLpPC+e36/Ftzb1tg4QEgIbT09Wuq3o6tfsgf5UDgLTY1qpCTkOskACAWdfe2qL11y/R/7fzVZ0dGU87nJohIQGgIZVpNwcAqSv15TXEXAwANfH+tUWdGRnXV547mHYoNUNCAkBDmkxI0G4OANJTKuS079hZnRtt3r/eAUBa/lVpsfrynXps6/60Q6kZEhIAGlK5kNPJc2MaPkW7OQBIS7mQV4T04mG2bQDAbGttsX7sLUv0d98+qFPnx9IOpyZISABoSBc6bVBHAgBSc6HIMHMxANTErWuLOj82oS/vfDXtUGqChASAhnSh3Rx7lwEgNav6KgkJ6kgAQG2su2ahlvR06bGtzdltg4QEgIa0pKdL8ztaSUgAQIrmd7Sp2NtFpw0AqJGWFuvH1y7V175zUMfPjqYdzqwjIQGgIbW0WKVCTruHeQgGgDSVCnTaAIBaunXtUo2Oh760/ZW0Q5l1JCQANKxyIa/dB3kIBoA0lQs5DQ2fpusRANTIDSsWaPnCeXp8W/Nt2yAhAaBhlQt57Tt2VmdHaDc3HdvrbT9ne5ftey8x7gO2w/a65Hil7bO2n0l+/qh+UQNoNKVCXifPj2n4JF2PAKAWbOvWtUX9w65DOnJ6JO1wZhUJCQANi8KWF2e7VdKDkm6RNCDpDtsD04zrlvRrkv5pylu7I+KG5OeXax4wgIZ1odMGW+gAoGZuXbtUYxOhv/1Wc23bICEBoGGV+ycfgklITONmSbsiYigiRiQ9LOm2acZ9VNLvSjpXz+AANI9SkhweOsRcDAC1Mljs0aq+nB7ftj/tUGYVCQkADWvl4pxazF/lLmKZpD1Vx3uTcxfYfpukFRHxN9Ncv8r207a/ZvudNYwTQINb2tOlrvYWDTEXA0DNVLZtLNVTQ4ebaoscCQkADaurvVUrFs1nhcQbYLtF0u9L+vVp3j4g6eqIuFHSRyR9znbPRT7nLttbbG8ZHh6uXcAA5qyWFqvUR6cNAKi197+1qImQvvit5iluSUICQEOj08ZF7ZO0oup4eXJuUrek6yV91faLkr5P0kbb6yLifEQclqSI+BdJuyVdO92XRMRDEbEuItYVCoUa3AaARkAbZgCovWuv6ta1V+X12Nbm2bZBQgJAQysXcnrh0GmNT9BuborNktbYXmW7Q9LtkjZOvhkRxyOiLyJWRsRKSU9J2hARW2wXkqKYsl2StEbSUP1vAUCjKBXy2nv0jM6P0fUIAGrp1rVFbX7xqA4cP5t2KLOChASAhlYu5HV+bEL7jzXHpDxbImJM0t2SnpC0U9IjEbHd9gO2N1zm8ndJ2mb7GUmPSvrliDhS24gBNLJyIaeJkF46fCbtUACgqd26dqkk6W+2Nce2jba0AwCAK1Hur1R33zV8SisWzU85mrklIjZJ2jTl3P0XGftDVa+/IOkLNQ0OQFMp9SWdNoZP6dqrulOOBgCaV6mQ12CxR49tO6BffGcp7XCuGCskADS0ctJujjoSAJCeUmGyDTN1JACg1t5z3VXauueYTp0fSzuUK0ZCAkBDW5Tr0ML57TwEA0CKcp1tWtLTRetPAKiDtyzrlSTtPHAi5UiuHAkJAA2vXMjT+hMAUlbptMFcXM32etvP2d5l+95p3r/T9rDtZ5KfX0zO/3DVuWdsn7P9E/W/AwBz0eCySjf27fuOpxzJlSMhAaDhlQt5DfEQDACpKhVyGho+pQi6HklS0q3oQUm3SBqQdIftgWmGfj4ibkh+PiVJEfGVyXOS3i3pjKQv1St2AHPbkp4uLcp1aAcrJAAgfeX+nA6dGtGxMyNphwIAmVXqy+vEuTEdPs1cnLhZ0q6IGIqIEUkPS7rtDXzOByV9MSJoYQJAkmRbg8Uebd9PQgIAUnehsCV7lwEgNZNdj6gjccEySXuqjvcm56b6gO1tth+1vWKaJx2YEAAAIABJREFU92+X9L8v9iW277K9xfaW4eHhK4sYQMMYKPboO6+e1MjYRNqhXBESEgAaHp02ACB9pb5Kpw220L0uj0laGRFrJT0p6TPVb9peKuktkp642AdExEMRsS4i1hUKhZoGC2DuGCz2anQ89PzBk2mHckVISABoeCsWzVdHawvF1AAgRcsWzFNnG3NxlX2Sqlc8LE/OXRARhyPifHL4KUlvn/IZPy3pLyNitGZRAmhIg8WksGWDb9sgIQGg4bW2WKv6qO4OAGlqSeZitmxcsFnSGturbHeosvViY/WAZAXEpA2Sdk75jDt0ie0aALJr1eKc5ne0agcJie81gxZH77L9Tdtjtj845b2rbX/J9k7bO2yvrEWMAJpLuT9HDQkASFmpkNPQIeZiSYqIMUl3q7LdYqekRyJiu+0HbG9Iht1je7vtrZLukXTn5PXJM/AKSV+rZ9wAGkNLi3Xd0h5t39/YrT/bZvsDq1oc/agqxXs2294YETuqhr2syoT7G9N8xGclfSwinrSdl9TYVToA1EW5kNcT21/V+bFxdba1ph0OAGRSqa8yF4+MTaijjYW4EbFJ0qYp5+6ven2fpPsucu2Lmr4IJgBIqmzb+MK/7NXERKilxWmH84bU4r8Ul21xFBEvRsQ2TUk2JL2Z2yLiyWTcKVocAZiJciGv8YnQy4eZMgAgLeX+XGUuPsJcDAC1Nljs0emRcb3UwHNuLRISM21xNJ1rJR2z/Re2n7b9iWTFBQBc0mutP6kjAQBpKfUxFwNAvQwWeyWpobdtzLW1dG2S3qnKVo6bJJVUtZeuGj2XAVQrFSrt5qgjAQDpmZyLKWwJALW35qq82lrc0J02apGQuGyLo0vYK+mZZLvHmKS/kvS26QbScxlAtVxnm5b2dmn3Qf4qBwBp6e5qV6G7U0OskACAmutsa9Waq7pJSExx2RZHl7l2ge3JDMO7Je24xHgAuKBcyLNMGABSVuqj0wYA1MtgsUc79h9XRKQdyhsy6wmJmbQ4sn2T7b2SPiTpk7a3J9eOq7Jd48u2n5VkSX882zECaE7lQqX1Z6NOyADQDMr9eVZIAECdDBZ7dOjUiA6ePJ92KG/IrLf9lGbU4mizKls5prv2SUlraxEXgOZW7s/r1PkxHTx5Xlf1dKUdDgBkUqkvp6NnRnXk9IgW5TrSDgcAmtrA0h5JlcKWjfj8O9eKWgLAG3ah0wZ1JAAgNZNzMaskAKD2BopJQmJfY9aRICEBoGms7q88BO/iIRgAUkOnDQCon+6udl2zeH7DFrYkIQGgafR3dyrf2cYKCQBI0fKF89XR2qLdh5iLAaAeBos92n7geNphvCEkJAA0DdsXClsCANLR2mKt7JvPCgkAqJPBYq/2HDmr42dH0w7ldSMhAaCp0PoTANJX6mMuBoB6mawjsaMBt22QkADQVMr9eR04fk6nzo+lHQoAZFapkNPLh89odHwi7VAAoOkNFl/rtNFoSEgAaCrlpJjaCywVBoDUlAp5jU2E9hw5k3YoAND0+ru7VOju1I4DrJAAgFRdaP3JUmEASA2dNgCgvgaLPWzZAIC0Xb14vlpbTEICAFJU7qskh4fotAEAdTFY7NHzB0/p3Oh42qG8LiQkADSVzrZWXb1oPgkJAEhR7/x29eU7WCEBAHUyWOzV+EToO6+eTDuU14WEBICmUy7ktPsgD8EAkCY6bQBA/bxW2LKxtm2QkADQdMqFvF44dFrjE5F2KACQWaVCjhUSAFAnKxbOV3dnW8N12iAhAaDplAt5jYxPaO/RbFd3t73e9nO2d9m+9xLjPmA7bK+rOndfct1ztt9Xn4gBNJNSIafDp0d0/Mxo2qEAQNNrabGuK/awQgIA0lbur1R3z/JSYdutkh6UdIukAUl32B6YZly3pF+T9E9V5wYk3S5pUNJ6Sf8j+TwAmLELXY8obAkAdTFY7NG3D5xsqFXCJCQANJ3Jh+BdBzP9EHyzpF0RMRQRI5IelnTbNOM+Kul3JZ2rOnebpIcj4nxEvCBpV/J5ADBjpWQuZtsGANTHYLFXZ0fH9UIDJYJJSABoOgvmd6gv35H1wpbLJO2pOt6bnLvA9tskrYiIv3m91wLA5axYOE/trbRhBoB6acTCliQkADSlUoHq7pdiu0XS70v69Sv8nLtsb7G9ZXh4eHaCA9AU2lpbdPWi+RpiLgaAuljdn1dHWwsJCQBIW5mExD5JK6qOlyfnJnVLul7SV22/KOn7JG1MClte7toLIuKhiFgXEesKhcIshg+gGZQKebZsAECdtLe26E1XdTdUpw0SEgCaUrmQ09EzozpyeiTtUNKyWdIa26tsd6hSpHLj5JsRcTwi+iJiZUSslPSUpA0RsSUZd7vtTturJK2R9M/1vwUAja5UyOmlw2caqsAaADSywaTTRkRjzLskJAA0pXJ/Ut09o6skImJM0t2SnpC0U9IjEbHd9gO2N1zm2u2SHpG0Q9LfSvrViBivdcwAmg9tmAGgvgaLPTp2ZlT7j5+7/OA5oC3tAACgFlZPtps7eEo3rVyUcjTpiIhNkjZNOXf/Rcb+0JTjj0n6WM2CA5AJ5cJrbZivWZxLORoAaH4DxV5J0vZ9x7VswbyUo7k8VkgAaErFBfPU2daS2RUSADAXlPpo/QkA9XTd0m7ZjdNpg4QEgKbU2mKt6stpNw/BAJCahbkOLZzfzlwMAHUyv6NNq/pyJCQAIG3l/sx32gCA1FU6bTAXA0C9DBZ7taNBOm2QkADQtMqFvPYcOaNzo9RjBIC0lAs5DR1ihQQA1MtgsUf7j5/T0QboNkdCAkDTKhdymgjppcNUdweAtJQKeQ2fPK8T50bTDgUAMmGw2COpMepIkJAA0LRWZ7z1JwDMBaW+SncNClsCQH0MJp02dhyY+9s2SEgAaFqT1d13HSQhAQBpKRUmO21kby62vd72c7Z32b53mvfvtD1s+5nk5xer3rva9pds77S9w/bKesYOoHEtynVoaW9XQ6yQaEs7AAColXkdrVq2YB4rJAAgRVcvmq/WFmduhYTtVkkPSvpRSXslbba9MSJ2TBn6+Yi4e5qP+Kykj0XEk7bzkiZqGzGAZjJY7GmIhAQrJAA0NTptAEC6OtpadM2i+Ro6lLm5+GZJuyJiKCJGJD0s6baZXGh7QFJbRDwpSRFxKiIoiARgxgaKvRoaPqWzI3O7uHvNEhIzWKL2LtvftD1m+4PTvN9je6/t/16rGAE0v3Ihp90HT2tiItIOBQAyq5TMxRmzTNKequO9ybmpPmB7m+1Hba9Izl0r6Zjtv7D9tO1PJCsuAGBGBos9mghp5ytze5VETRISVUvUbpE0IOmOJNNb7WVJd0r63EU+5qOSvl6L+ABkR7mQ19nRcb1y4lzaoQBAZpUKeb1w+LTGSQ5P9ZiklRGxVtKTkj6TnG+T9E5JvyHpJkklVZ6bv4ftu2xvsb1leHi49hEDaAiN0mmjViskLrtELSJejIhtmmY/nO23S7pK0pdqFB+AjCgX6LQBAGkr9eU0Mjah/cfOph1KPe2TtKLqeHly7oKIOBwR55PDT0l6e/J6r6RnkmfpMUl/Jelt031JRDwUEesiYl2hUJjVGwDQuJYtmKfeee3asX9ud9qoVUJipkvUvoftFkm/p0pG+FLjyAYDuKxyf6Xd3G46bQBAakrZTA5vlrTG9irbHZJul7SxeoDtpVWHGyTtrLp2ge3JDMO7JU0thgkAF2W7IQpbzsWilr8iaVNE7L3UILLBAGaikO9Ud1ebdmesujsAzCXlQiU5nKVOG8nKhrslPaFKouGRiNhu+wHbG5Jh99jebnurpHuUbMuIiHFV/jj3ZdvPSrKkP673PQBobIPFHn37lZMaHZ+7TXpq1fbzskvULuEdkt5p+1ck5SV12D4VEd9TGBMALse2ygU6bQBAmhblOtQ7rz1znTYiYpOkTVPO3V/1+j5J913k2iclra1pgACa2mCxVyNjE9o9fEpvXtKTdjjTqtUKicsuUbuYiPi5iLg6Ilaqkhn+LMkIAFeChAQApMt2VjttAEBqLhS23Dd3t23UJCExkyVqtm+yvVfShyR90vb2WsQCAOX+nF49cV4nz42mHQoAZFapL5+5FRIAkKZSIa+u9pY5XUeiVls2ZrJEbbMqWzku9RmflvTpGoQHIENWJ8XUhoZP660rFqQcDQBkU6mQ0xe+uVenzo8p31mzR1AAQKK1xXrzkh5tn8OdNuZiUUsAmFXl/kxWdweAOWWyDfMLGSpsCQBpGyz2aMeBE4qItEOZFgkJAE3v6kXz1dZiEhIAkKILnTbYtgEAdTNY7NXJc2Pac+Rs2qFMi4QEgKbX3tqiaxbP166DPAQDQFquXjxfLZZ2MxcDQN1cKGw5R7dtkJAAkAmVThssEwaAtHS2tWrFovnafYi5GADq5U1LutXa4jlb2JKEBIBMKPfn9dLh0xodn0g7FADIrFJfTkMkhwGgbrraW7W6kGeFBACkqVzIa3Q8tOfImbRDAYDMKhfyeuHQKU1MzM3iagDQjAaKPayQAIA0TRZTY9sGAKSnVMjr3OiEDpw4l3YoAJAZg8UeHTx5XsMnz6cdyvcgIQEgE0oFWn8CQNpKk8lhClsCQN0MzOHCliQkAGRC77x2Fbo7eQgGgBRNJiSGSA4DQN0MLu2VJO04MPe2bZCQAJAZ5UKOFRIAkKJCvlPdnW0aotMGANRN7/x2LV84b07WkSAhASAzJlt/RlBMDQDSYFulAp02AKDeBos92kFCAgDSUy7kdfzsqA6fHkk7FADIrHIhz5YNAKizwWKvXjh0WqfOj6UdynchIQEgM1b3J4UtqSMBAKkpFXLaf/yczozMrYdiAGhmg0lhy51zrI4ECQkAmVGeTEhkZKmw7fW2n7O9y/a907z/y7aftf2M7b+3PZCcX2n7bHL+Gdt/VP/oATSrya5HbNsAgPoZLFYKW27fN7c6bbSlHQAA1MvSni7Na2/NRGFL262SHpT0o5L2Stpse2NE7Kga9rmI+KNk/AZJvy9pffLe7oi4oZ4xA8iGC502Dp3W9ct6U44GALLhqp5OLc51zLnClqyQAJAZLS2VYmq7srFl42ZJuyJiKCJGJD0s6bbqARFR/V+knCSqfQKouZWLc7Jp/QkA9WRbA8UeEhIAkKZKp41MPAQvk7Sn6nhvcu672P5V27slfVzSPVVvrbL9tO2v2X7nxb7E9l22t9jeMjw8PFuxA2hiXe2tWr5wHls2AKDOBou9ev7gSY2MTaQdygUkJABkSrmQ175jZ3V2ZDztUOaEiHgwIsqSflPSbyenD0i6OiJulPQRSZ+z3XOR6x+KiHURsa5QKNQnaAANr9SXmeQwAMwZg8UejY6HvvPqybRDuYCEBIBMKffnFCG9cKjp/zK3T9KKquPlybmLeVjST0hSRJyPiMPJ63+RtFvStTWKE0AGlQo5vXDotCLYKQYA9TLZaWPHHNq2QUICQKaUC5OdNpr+L3ObJa2xvcp2h6TbJW2sHmB7TdXhj0t6PjlfSIpiynZJ0hpJQ3WJGkAmlAp5nRkZ1ysnzqUdCgBkxsrFOeU6WrV9/9zptEGXDQCZsqqvUkyt2RMSETFm+25JT0hqlfSnEbHd9gOStkTERkl3236PpFFJRyV9OLn8XZIesD0qaULSL0fEkfrfBYBmVe5LOm0Mn9bS3nkpRwMA2dDSYl23dG4VtiQhASBTJoup7c5AMbWI2CRp05Rz91e9/rWLXPcFSV+obXQAsqzcX1mtNjR8Sj+wui/laAAgOwaLPXr0X/ZqYiLU0uK0w2HLBoDsKRfy2p2N1p8AMCf1d3cq19GaieQwAMwlg8VenR4Z14uH58b8S0ICQOaUC3kNHTqliQmKqQFAGmyrlJ02zAAwZwwkhS3nyrYNEhIAMmd1f17nRie0//jZtEMBgMwqFXIaYoUEANTVtVd1q73VJCQAIC2vddrgQRgA0lLqy2v/8bM6NzqedigAkBkdbS1a0989ZzptkJAAkDnlQqW6O3UkACA95f6cIqQXDpEcBoB6Giz2aMf+E4pIf/syCQkAmbMo16EF89vZuwwAKSr1TXbaICEBAPU0WOzR4dMjevXE+bRDISEBIHtsq1zIaxcrJAAgNav6ktVqJIcBoK4Gir2SpB0H0t+2UZOEhO31tp+zvcv2vdO8/y7b37Q9ZvuDVedvsP0N29ttb7P9M7WIDwDKhRw1JAAgRfM6WrVswTwNkZAAgLq6bmm3JGn7vvQLW856QsJ2q6QHJd0iaUDSHbYHpgx7WdKdkj435fwZSf8mIgYlrZf0B7YXzHaMAFAu5HXo1HkdPzOadigAkFmlQk5D1JAAgLrq7mrXysXz50SnjVqskLhZ0q6IGIqIEUkPS7qtekBEvBgR2yRNTDn/nYh4Pnm9X9JBSYUaxAgg4y502jjEX+YAIC3lQl5Dw6fnRGE1AMiSwWKvtjfplo1lkvZUHe9Nzr0utm+W1CFp9yzFBQAXlPuThAR1JAAgNaVCTqfOj2n4ZPqF1WphBtuY77Q9bPuZ5OcXq94brzq/sb6RA2h2A8Ue7TlyVsfPprtauC3Vb78I20sl/U9JH46IiYuMuUvSXZJ09dVX1zE6AM1gxcJ5am81dSQAIEWTnTZ2DZ9Sf09XytHMrqptzD+qyh/oNtveGBE7pgz9fETcPc1HnI2IG2odJ4BsGiz2SJJ27D+hd5QXpxZHLVZI7JO0oup4eXJuRmz3SPobSb8VEU9dbFxEPBQR6yJiXaHArg4Ar09ba4tWLs5R3R0AUlQqVDptNGnrz8tuYwaAtAwmnTa2709320YtEhKbJa2xvcp2h6TbJc1omVky/i8lfTYiHq1BbABwQbmQJyEBACla0tOlee2tzZqQmOk25g8k3eUetV39R70u21tsP2X7Jy72JbbvSsZtGR4enqXQATS7Qnen+rs7tSPlwpaznpCIiDFJd0t6QtJOSY9ExHbbD9jeIEm2b7K9V9KHJH3S9vbk8p+W9C5Jd1btmWOpGoCaKPfn9PLhMxodn3ZnGACgxlparFV9OQ1lt8DwY5JWRsRaSU9K+kzVe9dExDpJP6tK57nydB/AqmEAb9RgsSf1Ths1qSEREZskbZpy7v6q15tV2cox9br/Jel/1SImAJhqdX9eYxOhlw6f0eqkyCUAoL7K/Xlt3XMs7TBq4bLbmCPicNXhpyR9vOq9fcn/Dtn+qqQbRbF3ALNosNirrz9/SOdGx9XV3ppKDLXYsgEADeFC60+2bQBAakp9Oe05ekbnRsfTDmW2XXYbc1LIfdIGVVYXy/ZC253J6z5JPyBpajFMALgig8UejU+EnnvlZGoxkJAAkFklEhIAkLpSIacI6aXDZ9IOZVbNZBuzpHtsb7e9VdI9ku5Mzl8naUty/iuSfmea7hwAcEVeK2yZ3raNOdn2EwDqId/ZpiU9Xdp9sCmLqQFAQ5hcrTY0fEpvWtKdcjSzawbbmO+TdN801/2jpLfUPEAAmbZi0Tx1d7Wl2mmDFRIAMq3cT+tPAEjTqr6k9echksMAUE+2NbA03cKWJCQAZFq5kNfug6cUEWmHAgCZlOts09LeLpLDAJCCwWKvvv3KCY1PpPMsTEICQKaVC3mdPD+m4ZPn0w4FADKrVMhp9zArJACg3gaLPTo3OqGhlJLCJCQAZNrk3uVd/GUOAFJT6straJjVagBQb4PLeiSlV9iShASATCv3V/Yu85c5AEhPqZDTyXNjOnRqJO1QACBTyoW8OtpaUitsSUICQKYt6enS/I5W7T7ICgkASEupqtMGAKB+2ltb9OYl3ayQAIA02K4UtuQhGABSUy7QaQMA0jJYrHTaSGPbHAkJAJlXLuQ0xJYNAEhNsXeeutpbWK0GACkYKPbq+NlR7Tt2tu7fTUICQOat7s9r37GzOjMylnYoAJBJLS3WysU5VkgAQAoGi5XCljtS2LZBQgJA5pUv7F3mQRgA0lIu5KkhAQApePOSbtnpdNogIQEg88r9lYQEdSQAID2lQk57jp7VyNhE2qEAQKbM72hTqS9HQgIA0nDN4vlqcfO1/rS93vZztnfZvnea93/Z9rO2n7H997YHqt67L7nuOdvvq2/kALKoXMhrfCL08pHmmosBoBEMFnu1I4XWnyQkAGReZ1urrl40v6lWSNhulfSgpFskDUi6ozrhkPhcRLwlIm6Q9HFJv59cOyDpdkmDktZL+h/J5wFAzZSSThvNlhwGgEYwWOzR/uPndPT0SF2/l4QEAKjyl7kmq+5+s6RdETEUESOSHpZ0W/WAiKhel5eTNNnr6TZJD0fE+Yh4QdKu5PMAoGZW9U0mJJpqLgaAhjBY7JVU/zoSJCQAQJU6EkOHTmt8ov79l2tkmaQ9Vcd7k3Pfxfav2t6tygqJe17Ptcn1d9neYnvL8PDwrAQOIJu6u9rV391JgWEASMFkp43tdd62QUICACSVCzmNjE1o39H6919OU0Q8GBFlSb8p6bffwPUPRcS6iFhXKBRmP0AAmVIq5Oi0AQApWJjrULG3ixUSAJCGydafTbRUeJ+kFVXHy5NzF/OwpJ94g9cCwKwoFyqr1QAA9TdQ7GWFBACkoQkTEpslrbG9ynaHKkUqN1YPsL2m6vDHJT2fvN4o6XbbnbZXSVoj6Z/rEDOAjCsV8jp2ZlRH6lxUDQBQ2bYxdOi0zoyM1e072+r2TQAwhy3MdWhRrqNpEhIRMWb7bklPSGqV9KcRsd32A5K2RMRGSXfbfo+kUUlHJX04uXa77Uck7ZA0JulXI2I8lRsBkCmvddo4pUW5RSlHAwDZMljsUYS088BJvf2ahXX5ThISAJAoF3LafbB5lgpHxCZJm6acu7/q9a9d4tqPSfpY7aIDgO9V7qusVhsaPqWbVpKQAIB6GlxW6bSxY//xuiUk2LIBAIlyId80KyQAoBEtWzhPHW0tdNoAgBQUe7u0YH57XQtbkpAAgMTq/rwOnx7RUfYuA0AqWlusVYtz2k1CAgDqzrYGiz0kJAAgDZOFLYcOsUoCANJSKuSYhwEgJYPFXj33ykmNjk/U5ftISABA4kKnjSaqIwEAjaZUyOnlw2fq9jAMAHjNYLFHI+MT2nWwPolhEhIAkJjcu0wdCQBIT6kvr7GJ0MtHzqQdCgBkzmCxR5Lqtm2DhAQAJFpbrFJfjoQEAKRosvUnhS0BoP5W9eU1r71V2/cfr8v3kZAAgCqVThs8BANAWkqF11p/AgDqq7XFevPS7sZfIWF7ve3nbO+yfe8077/L9jdtj9n+4JT3Pmz7+eTnw7WKEQCmKhdyeunwaZ0fG087FADIpN557erLd7JCAgBSMljs0c79JzQxETX/rpokJGy3SnpQ0i2SBiTdYXtgyrCXJd0p6XNTrl0k6T9I+leSbpb0H2wvrEWcADBVuT+viZBeOszeZQBIS6nA9jkASMtgsVcnz49p79GzNf+uWq2QuFnSrogYiogRSQ9Luq16QES8GBHbJE0tofw+SU9GxJGIOCrpSUnraxQnAHyX1zpt8CAMAGkpF3IaOsQKCQBIw2uFLWtfR6JWCYllkvZUHe9Nzs3atbbvsr3F9pbh4eE3HCgAVFvVVymmxl/mACA9pb68jpwe0bEzI2mHAgCZc+1V3WptcV3qSDRsUcuIeCgi1kXEukKhkHY4AJpErrNNxd4uClsCQIomO20wFwNA/XW1t2p1Id/QKyT2SVpRdbw8OVfrawHgipX786yQAIAUlem0AQCpGiz2NPQKic2S1theZbtD0u2SNs7w2ickvdf2wqSY5XuTcwBQF+VCXrsPnlJE7SsLAwC+1/KF89TealZIAEBKBoo9OnjyvIZPnq/p99QkIRERY5LuViWRsFPSIxGx3fYDtjdIku2bbO+V9CFJn7S9Pbn2iKSPqpLU2CzpgeQcANRFuT+v0yPjevVEbSdgAMD02lpbdM3iHCskACAlg8VeSbUvbFmzGhIRsSkiro2IckR8LDl3f0RsTF5vjojlEZGLiMURMVh17Z9GxOrk589qFSMATKdcoLAlAKSt1NccnTZsr7f9nO1dtu+d5v07bQ/bfib5+cUp7/fY3mv7v9cvagBZN3Ch00Ztt200bFFLAKiV1ZOtP0lIAEBqSoW8Xjp8WmPjUzvENw7brZIelHSLpAFJd9gemGbo5yPihuTnU1Pe+6ikr9c4VAD4Lr3z2rVi0TztICEBAPVV6O5Ud2ebdh8kIQEAaSkXchodD+09ejbtUK7EzZJ2RcRQRIxIeljSbTO92PbbJV0l6Us1ig8ALmpwaW/jbtkAgEZlW6X+PMXUACBFpclOG4caOjm8TNKequO9ybmpPmB7m+1Hba+QJNstkn5P0m9c6gts32V7i+0tw8PDsxU3AGiw2KMXD5/RyXOjNfsOEhIAMI1yIceWDQBI0YV6PgebPjn8mKSVEbFW0pOSPpOc/xVJmyJi76UujoiHImJdRKwrFAo1DhVAlgwuq9SR2HngZM2+g4QEAEyjXMjrwPFzOnV+LO1QACCTFszv0KJcR6OvkNgnaUXV8fLk3AURcTgiJts6fUrS25PX75B0t+0XJf1XSf/G9u/UNlwAeE09Om2QkACAaZQnlwqzSgIAUlPqyzX69rnNktbYXmW7Q9LtkjZWD7C9tOpwg6SdkhQRPxcRV0fESlW2bXw2Ir6nSwcA1Ep/d6f68h017bRBQgIAprG6n9afAJC2ciGvoQZOSETEmKS7JT2hSqLhkYjYbvsB2xuSYffY3m57q6R7JN2ZTrQA8N1sa6DYW9OERFvNPhkAGtjVi3JqbXEW9i4DwJxVKuT0+S3ndfzsqHrntacdzhsSEZskbZpy7v6q1/dJuu8yn/FpSZ+uQXgAcEmDxR798deHdH5sXJ1trbP++ayQAIBpdLS16JpF81khAQApKrF9DgBSNVjs0dhE6PlXazMPk5AAgIsoFfIkJAAgRaWk00Yjb9sAgEZW68KWJCQA4CL+NwN0AAAgAElEQVRW9+f14qEzGhufSDsUAMikqxfNV1uLG73TBgA0rGsWzVe+s61mdSRISADARZQLOY2MT2jv0bNphwIAmdTe2qKrF89nhQQApKSlxbpuaTcJCQCot3J/Ze8y2zYAID2lvsbutAEAjW6w2KudB05ofCJm/bNJSADARZT7SEgAQNrKhZxeOHy6Jg/CAIDLGyj26MzIuF46PPvJYRISAHARvfPb1ZfvbNjWn7bX237O9i7b907z/kds77C9zfaXbV9T9d647WeSn431jRwAXlMq5DQyNqF9bJ8DgFQMFnskqSbbNkhIAMAllAu5hlwhYbtV0oOSbpE0IOkO2wNThj0taV1ErJX0qKSPV713NiJuSH421CVoAJjGZOvP3RS2BIBUrOnvVnurSUgAQL2V+xu29efNknZFxFBEjEh6WNJt1QMi4isRcSY5fErS8jrHCACXVU4SEtSRAIB0dLS16NqrumvS+pOEBABcQrmQ19EzozpyeiTtUF6vZZL2VB3vTc5dzC9I+mLVcZftLbafsv0TF7vI9l3JuC3Dw8NXFjEATGNRrkML5rdrqDGTwwDQFAaLPdqx/4QiZreeDwkJALiEciEnSdp1sHkfhG3/vKR1kj5RdfqaiFgn6Wcl/YHt8nTXRsRDEbEuItYVCoU6RAsgi0p9jbl9DgCaxcDSHh0+PaJXT5yf1c8lIQEAlzC5VLgBH4T3SVpRdbw8OfddbL9H0m9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\n",
      "text/plain": [
       "<Figure size 1296x3024 with 18 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### import matplotlib.pyplot as plt\n",
    "\n",
    "metrics=list(result.columns[[i not in ['Beta'] for i in result.columns]])\n",
    "\n",
    "charts_per_row=6\n",
    "charts_per_column=3\n",
    "\n",
    "fig, axes = plt.subplots(nrows=charts_per_row, ncols=charts_per_column,figsize=(18, 7*charts_per_row ))\n",
    "import itertools\n",
    "to_iter=[i for i in itertools.product(range(charts_per_row), range(charts_per_column))]\n",
    "\n",
    "for i in range(len(metrics)):\n",
    "    df=result[['Beta', metrics[i]]]\n",
    "    df.plot(ax=axes[to_iter[i]], title=metrics[i], x=0, y=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Check sample recommendations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user</th>\n",
       "      <th>rating</th>\n",
       "      <th>title</th>\n",
       "      <th>genres</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>57566</th>\n",
       "      <td>734</td>\n",
       "      <td>5</td>\n",
       "      <td>Emma (1996)</td>\n",
       "      <td>Drama, Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50942</th>\n",
       "      <td>734</td>\n",
       "      <td>5</td>\n",
       "      <td>It's a Wonderful Life (1946)</td>\n",
       "      <td>Drama</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48429</th>\n",
       "      <td>734</td>\n",
       "      <td>5</td>\n",
       "      <td>Rebecca (1940)</td>\n",
       "      <td>Romance, Thriller</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22622</th>\n",
       "      <td>734</td>\n",
       "      <td>5</td>\n",
       "      <td>My Fair Lady (1964)</td>\n",
       "      <td>Musical, Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22461</th>\n",
       "      <td>734</td>\n",
       "      <td>5</td>\n",
       "      <td>Sound of Music, The (1965)</td>\n",
       "      <td>Musical</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35119</th>\n",
       "      <td>734</td>\n",
       "      <td>4</td>\n",
       "      <td>Much Ado About Nothing (1993)</td>\n",
       "      <td>Comedy, Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43403</th>\n",
       "      <td>734</td>\n",
       "      <td>4</td>\n",
       "      <td>Snow White and the Seven Dwarfs (1937)</td>\n",
       "      <td>Animation, Children's, Musical</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2447</th>\n",
       "      <td>734</td>\n",
       "      <td>4</td>\n",
       "      <td>Back to the Future (1985)</td>\n",
       "      <td>Comedy, Sci-Fi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36121</th>\n",
       "      <td>734</td>\n",
       "      <td>4</td>\n",
       "      <td>Silence of the Lambs, The (1991)</td>\n",
       "      <td>Drama, Thriller</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37465</th>\n",
       "      <td>734</td>\n",
       "      <td>4</td>\n",
       "      <td>Aladdin (1992)</td>\n",
       "      <td>Animation, Children's, Comedy, Musical</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38209</th>\n",
       "      <td>734</td>\n",
       "      <td>4</td>\n",
       "      <td>Mary Poppins (1964)</td>\n",
       "      <td>Children's, Comedy, Musical</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39918</th>\n",
       "      <td>734</td>\n",
       "      <td>4</td>\n",
       "      <td>Rear Window (1954)</td>\n",
       "      <td>Mystery, Thriller</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40514</th>\n",
       "      <td>734</td>\n",
       "      <td>4</td>\n",
       "      <td>Titanic (1997)</td>\n",
       "      <td>Action, Drama, Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42508</th>\n",
       "      <td>734</td>\n",
       "      <td>4</td>\n",
       "      <td>Jurassic Park (1993)</td>\n",
       "      <td>Action, Adventure, Sci-Fi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45160</th>\n",
       "      <td>734</td>\n",
       "      <td>4</td>\n",
       "      <td>Tomorrow Never Dies (1997)</td>\n",
       "      <td>Action, Romance, Thriller</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       user  rating                                   title  \\\n",
       "57566   734       5                             Emma (1996)   \n",
       "50942   734       5            It's a Wonderful Life (1946)   \n",
       "48429   734       5                          Rebecca (1940)   \n",
       "22622   734       5                     My Fair Lady (1964)   \n",
       "22461   734       5              Sound of Music, The (1965)   \n",
       "35119   734       4           Much Ado About Nothing (1993)   \n",
       "43403   734       4  Snow White and the Seven Dwarfs (1937)   \n",
       "2447    734       4               Back to the Future (1985)   \n",
       "36121   734       4        Silence of the Lambs, The (1991)   \n",
       "37465   734       4                          Aladdin (1992)   \n",
       "38209   734       4                     Mary Poppins (1964)   \n",
       "39918   734       4                      Rear Window (1954)   \n",
       "40514   734       4                          Titanic (1997)   \n",
       "42508   734       4                    Jurassic Park (1993)   \n",
       "45160   734       4              Tomorrow Never Dies (1997)   \n",
       "\n",
       "                                       genres  \n",
       "57566                          Drama, Romance  \n",
       "50942                                   Drama  \n",
       "48429                       Romance, Thriller  \n",
       "22622                        Musical, Romance  \n",
       "22461                                 Musical  \n",
       "35119                         Comedy, Romance  \n",
       "43403          Animation, Children's, Musical  \n",
       "2447                           Comedy, Sci-Fi  \n",
       "36121                         Drama, Thriller  \n",
       "37465  Animation, Children's, Comedy, Musical  \n",
       "38209             Children's, Comedy, Musical  \n",
       "39918                       Mystery, Thriller  \n",
       "40514                  Action, Drama, Romance  \n",
       "42508               Action, Adventure, Sci-Fi  \n",
       "45160               Action, Romance, Thriller  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user</th>\n",
       "      <th>rec_nb</th>\n",
       "      <th>title</th>\n",
       "      <th>genres</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2936</th>\n",
       "      <td>734.0</td>\n",
       "      <td>1</td>\n",
       "      <td>Return of the Jedi (1983)</td>\n",
       "      <td>Action, Adventure, Romance, Sci-Fi, War</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7231</th>\n",
       "      <td>734.0</td>\n",
       "      <td>2</td>\n",
       "      <td>Fargo (1996)</td>\n",
       "      <td>Crime, Drama, Thriller</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3322</th>\n",
       "      <td>734.0</td>\n",
       "      <td>3</td>\n",
       "      <td>Toy Story (1995)</td>\n",
       "      <td>Animation, Children's, Comedy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2519</th>\n",
       "      <td>734.0</td>\n",
       "      <td>4</td>\n",
       "      <td>Godfather, The (1972)</td>\n",
       "      <td>Action, Crime, Drama</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5958</th>\n",
       "      <td>734.0</td>\n",
       "      <td>5</td>\n",
       "      <td>Contact (1997)</td>\n",
       "      <td>Drama, Sci-Fi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1621</th>\n",
       "      <td>734.0</td>\n",
       "      <td>6</td>\n",
       "      <td>Schindler's List (1993)</td>\n",
       "      <td>Drama, War</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1248</th>\n",
       "      <td>734.0</td>\n",
       "      <td>7</td>\n",
       "      <td>English Patient, The (1996)</td>\n",
       "      <td>Drama, Romance, War</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1455</th>\n",
       "      <td>734.0</td>\n",
       "      <td>8</td>\n",
       "      <td>Fugitive, The (1993)</td>\n",
       "      <td>Action, Thriller</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3542</th>\n",
       "      <td>734.0</td>\n",
       "      <td>9</td>\n",
       "      <td>Jerry Maguire (1996)</td>\n",
       "      <td>Drama, Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8124</th>\n",
       "      <td>734.0</td>\n",
       "      <td>10</td>\n",
       "      <td>Monty Python and the Holy Grail (1974)</td>\n",
       "      <td>Comedy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       user  rec_nb                                   title  \\\n",
       "2936  734.0       1               Return of the Jedi (1983)   \n",
       "7231  734.0       2                            Fargo (1996)   \n",
       "3322  734.0       3                        Toy Story (1995)   \n",
       "2519  734.0       4                   Godfather, The (1972)   \n",
       "5958  734.0       5                          Contact (1997)   \n",
       "1621  734.0       6                 Schindler's List (1993)   \n",
       "1248  734.0       7             English Patient, The (1996)   \n",
       "1455  734.0       8                    Fugitive, The (1993)   \n",
       "3542  734.0       9                    Jerry Maguire (1996)   \n",
       "8124  734.0      10  Monty Python and the Holy Grail (1974)   \n",
       "\n",
       "                                       genres  \n",
       "2936  Action, Adventure, Romance, Sci-Fi, War  \n",
       "7231                   Crime, Drama, Thriller  \n",
       "3322            Animation, Children's, Comedy  \n",
       "2519                     Action, Crime, Drama  \n",
       "5958                            Drama, Sci-Fi  \n",
       "1621                               Drama, War  \n",
       "1248                      Drama, Romance, War  \n",
       "1455                         Action, Thriller  \n",
       "3542                           Drama, Romance  \n",
       "8124                                   Comedy  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train=pd.read_csv('./Datasets/ml-100k/train.csv', sep='\\t', header=None, names=['user', 'item', 'rating', 'timestamp'])\n",
    "items=pd.read_csv('./Datasets/ml-100k/movies.csv')\n",
    "\n",
    "user=random.choice(list(set(train['user'])))\n",
    "\n",
    "train_content=pd.merge(train, items, left_on='item', right_on='id')\n",
    "display(train_content[train_content['user']==user][['user', 'rating', 'title', 'genres']]\\\n",
    "        .sort_values(by='rating', ascending=False)[:15])\n",
    "\n",
    "reco = np.loadtxt('Recommendations generated/ml-100k/Self_P3_reco.csv', delimiter=',')\n",
    "items=pd.read_csv('./Datasets/ml-100k/movies.csv')\n",
    "\n",
    "# Let's ignore scores - they are not used in evaluation: \n",
    "reco_users=reco[:,:1]\n",
    "reco_items=reco[:,1::2]\n",
    "# Let's put them into one array\n",
    "reco=np.concatenate((reco_users, reco_items), axis=1)\n",
    "\n",
    "# Let's rebuild it user-item dataframe\n",
    "recommended=[]\n",
    "for row in reco:\n",
    "    for rec_nb, entry in enumerate(row[1:]):\n",
    "        recommended.append((row[0], rec_nb+1, entry))\n",
    "recommended=pd.DataFrame(recommended, columns=['user','rec_nb', 'item'])\n",
    "\n",
    "recommended_content=pd.merge(recommended, items, left_on='item', right_on='id')\n",
    "recommended_content[recommended_content['user']==user][['user', 'rec_nb', 'title', 'genres']].sort_values(by='rec_nb')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# project task 6: generate recommendations of RP3Beta for hiperparameters found to optimize recall"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "943it [00:00, 4555.12it/s]\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RMSE</th>\n",
       "      <th>MAE</th>\n",
       "      <th>precision</th>\n",
       "      <th>recall</th>\n",
       "      <th>F_1</th>\n",
       "      <th>F_05</th>\n",
       "      <th>precision_super</th>\n",
       "      <th>recall_super</th>\n",
       "      <th>NDCG</th>\n",
       "      <th>mAP</th>\n",
       "      <th>MRR</th>\n",
       "      <th>LAUC</th>\n",
       "      <th>HR</th>\n",
       "      <th>F_2</th>\n",
       "      <th>Whole_average</th>\n",
       "      <th>Reco in test</th>\n",
       "      <th>Test coverage</th>\n",
       "      <th>Shannon</th>\n",
       "      <th>Gini</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3.702928</td>\n",
       "      <td>3.527713</td>\n",
       "      <td>0.322694</td>\n",
       "      <td>0.216069</td>\n",
       "      <td>0.212152</td>\n",
       "      <td>0.247538</td>\n",
       "      <td>0.245279</td>\n",
       "      <td>0.284983</td>\n",
       "      <td>0.388271</td>\n",
       "      <td>0.248239</td>\n",
       "      <td>0.636318</td>\n",
       "      <td>0.605683</td>\n",
       "      <td>0.910923</td>\n",
       "      <td>0.20545</td>\n",
       "      <td>0.376967</td>\n",
       "      <td>0.999788</td>\n",
       "      <td>0.178932</td>\n",
       "      <td>4.549663</td>\n",
       "      <td>0.950182</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       RMSE       MAE  precision    recall       F_1      F_05  \\\n",
       "0  3.702928  3.527713   0.322694  0.216069  0.212152  0.247538   \n",
       "\n",
       "   precision_super  recall_super      NDCG       mAP       MRR      LAUC  \\\n",
       "0         0.245279      0.284983  0.388271  0.248239  0.636318  0.605683   \n",
       "\n",
       "         HR      F_2  Whole_average  Reco in test  Test coverage   Shannon  \\\n",
       "0  0.910923  0.20545       0.376967      0.999788       0.178932  4.549663   \n",
       "\n",
       "       Gini  \n",
       "0  0.950182  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# use better values than (1,0) for alpha and beta\n",
    "# if you want you can also modify the model to consider different weights (we took as weights user ratings, maybe take ones or squares of ratings instead)\n",
    "# save the outptut in 'Recommendations generated/ml-100k/Self_RP3Beta_estimations.csv'\n",
    "# and 'Recommendations generated/ml-100k/Self_RP3Beta_reco.csv'\n",
    "\n",
    "## SOLUTION TASK 6\n",
    "\n",
    "import evaluation_measures as ev\n",
    "\n",
    "model = RP3Beta()\n",
    "model.fit(train_ui, alpha = 0.8, beta = 0.6)\n",
    "\n",
    "top_n = pd.DataFrame(model.recommend(user_code_id, item_code_id, topK = 10))\n",
    "top_n.to_csv('Recommendations generated/ml-100k/Self_RP3Beta_reco.csv', index = False, header = False)\n",
    "\n",
    "estimations = pd.DataFrame(model.estimate(user_code_id, item_code_id, test_ui))\n",
    "estimations.to_csv('Recommendations generated/ml-100k/Self_RP3Beta_estimations.csv', index = False, header = False)\n",
    "estimations_df = pd.read_csv('Recommendations generated/ml-100k/Self_RP3Beta_estimations.csv', header = None)\n",
    "\n",
    "reco = np.loadtxt('Recommendations generated/ml-100k/Self_RP3Beta_reco.csv', delimiter = ',')\n",
    "\n",
    "ev.evaluate(test = pd.read_csv('./Datasets/ml-100k/test.csv', sep = '\\t', header = None),\n",
    "            estimations_df = estimations_df, \n",
    "            reco = reco,\n",
    "            super_reactions = [4, 5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Beta</th>\n",
       "      <th>RMSE</th>\n",
       "      <th>MAE</th>\n",
       "      <th>precision</th>\n",
       "      <th>recall</th>\n",
       "      <th>F_1</th>\n",
       "      <th>F_05</th>\n",
       "      <th>precision_super</th>\n",
       "      <th>recall_super</th>\n",
       "      <th>NDCG</th>\n",
       "      <th>mAP</th>\n",
       "      <th>MRR</th>\n",
       "      <th>LAUC</th>\n",
       "      <th>HR</th>\n",
       "      <th>F_2</th>\n",
       "      <th>Whole_average</th>\n",
       "      <th>Reco in test</th>\n",
       "      <th>Test coverage</th>\n",
       "      <th>Shannon</th>\n",
       "      <th>Gini</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.9</td>\n",
       "      <td>3.704567</td>\n",
       "      <td>3.529375</td>\n",
       "      <td>0.162354</td>\n",
       "      <td>0.076967</td>\n",
       "      <td>0.089233</td>\n",
       "      <td>0.114583</td>\n",
       "      <td>0.134657</td>\n",
       "      <td>0.113253</td>\n",
       "      <td>0.160868</td>\n",
       "      <td>0.085486</td>\n",
       "      <td>0.243590</td>\n",
       "      <td>0.535405</td>\n",
       "      <td>0.580064</td>\n",
       "      <td>0.078906</td>\n",
       "      <td>0.197947</td>\n",
       "      <td>0.800106</td>\n",
       "      <td>0.415584</td>\n",
       "      <td>5.563910</td>\n",
       "      <td>0.857396</td>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.8</td>\n",
       "      <td>3.704552</td>\n",
       "      <td>3.529360</td>\n",
       "      <td>0.266384</td>\n",
       "      <td>0.147571</td>\n",
       "      <td>0.158660</td>\n",
       "      <td>0.194838</td>\n",
       "      <td>0.214485</td>\n",
       "      <td>0.209336</td>\n",
       "      <td>0.299850</td>\n",
       "      <td>0.184356</td>\n",
       "      <td>0.492852</td>\n",
       "      <td>0.571152</td>\n",
       "      <td>0.803818</td>\n",
       "      <td>0.146414</td>\n",
       "      <td>0.307476</td>\n",
       "      <td>0.936373</td>\n",
       "      <td>0.341270</td>\n",
       "      <td>5.257397</td>\n",
       "      <td>0.895882</td>\n",
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       "      <th>0</th>\n",
       "      <td>0.7</td>\n",
       "      <td>3.704528</td>\n",
       "      <td>3.529335</td>\n",
       "      <td>0.304136</td>\n",
       "      <td>0.187298</td>\n",
       "      <td>0.191990</td>\n",
       "      <td>0.228749</td>\n",
       "      <td>0.238305</td>\n",
       "      <td>0.256201</td>\n",
       "      <td>0.358807</td>\n",
       "      <td>0.226808</td>\n",
       "      <td>0.593897</td>\n",
       "      <td>0.591207</td>\n",
       "      <td>0.868505</td>\n",
       "      <td>0.182056</td>\n",
       "      <td>0.352330</td>\n",
       "      <td>0.983033</td>\n",
       "      <td>0.256854</td>\n",
       "      <td>4.898568</td>\n",
       "      <td>0.928065</td>\n",
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       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>3.702446</td>\n",
       "      <td>3.527273</td>\n",
       "      <td>0.282185</td>\n",
       "      <td>0.192092</td>\n",
       "      <td>0.186749</td>\n",
       "      <td>0.216980</td>\n",
       "      <td>0.204185</td>\n",
       "      <td>0.240096</td>\n",
       "      <td>0.339114</td>\n",
       "      <td>0.204905</td>\n",
       "      <td>0.572157</td>\n",
       "      <td>0.593544</td>\n",
       "      <td>0.875928</td>\n",
       "      <td>0.181702</td>\n",
       "      <td>0.340803</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.077201</td>\n",
       "      <td>3.875892</td>\n",
       "      <td>0.974947</td>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.1</td>\n",
       "      <td>3.703312</td>\n",
       "      <td>3.528128</td>\n",
       "      <td>0.290138</td>\n",
       "      <td>0.197597</td>\n",
       "      <td>0.192259</td>\n",
       "      <td>0.223336</td>\n",
       "      <td>0.210944</td>\n",
       "      <td>0.246153</td>\n",
       "      <td>0.347768</td>\n",
       "      <td>0.212034</td>\n",
       "      <td>0.581038</td>\n",
       "      <td>0.596328</td>\n",
       "      <td>0.884411</td>\n",
       "      <td>0.187030</td>\n",
       "      <td>0.347420</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.085137</td>\n",
       "      <td>3.957416</td>\n",
       "      <td>0.972784</td>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.2</td>\n",
       "      <td>3.703825</td>\n",
       "      <td>3.528636</td>\n",
       "      <td>0.297137</td>\n",
       "      <td>0.201202</td>\n",
       "      <td>0.196067</td>\n",
       "      <td>0.228169</td>\n",
       "      <td>0.218026</td>\n",
       "      <td>0.252767</td>\n",
       "      <td>0.355655</td>\n",
       "      <td>0.219909</td>\n",
       "      <td>0.588904</td>\n",
       "      <td>0.598160</td>\n",
       "      <td>0.886532</td>\n",
       "      <td>0.190538</td>\n",
       "      <td>0.352756</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.094517</td>\n",
       "      <td>4.053212</td>\n",
       "      <td>0.969980</td>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.3</td>\n",
       "      <td>3.704130</td>\n",
       "      <td>3.528939</td>\n",
       "      <td>0.303499</td>\n",
       "      <td>0.204749</td>\n",
       "      <td>0.199901</td>\n",
       "      <td>0.232829</td>\n",
       "      <td>0.225107</td>\n",
       "      <td>0.260797</td>\n",
       "      <td>0.363757</td>\n",
       "      <td>0.226825</td>\n",
       "      <td>0.599969</td>\n",
       "      <td>0.599964</td>\n",
       "      <td>0.888653</td>\n",
       "      <td>0.194073</td>\n",
       "      <td>0.358344</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.105339</td>\n",
       "      <td>4.147779</td>\n",
       "      <td>0.966948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.6</td>\n",
       "      <td>3.704488</td>\n",
       "      <td>3.529295</td>\n",
       "      <td>0.314634</td>\n",
       "      <td>0.206209</td>\n",
       "      <td>0.204818</td>\n",
       "      <td>0.240159</td>\n",
       "      <td>0.242489</td>\n",
       "      <td>0.273850</td>\n",
       "      <td>0.376438</td>\n",
       "      <td>0.238428</td>\n",
       "      <td>0.622042</td>\n",
       "      <td>0.600721</td>\n",
       "      <td>0.897137</td>\n",
       "      <td>0.197320</td>\n",
       "      <td>0.367854</td>\n",
       "      <td>0.996394</td>\n",
       "      <td>0.212843</td>\n",
       "      <td>4.621938</td>\n",
       "      <td>0.945932</td>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.4</td>\n",
       "      <td>3.704313</td>\n",
       "      <td>3.529120</td>\n",
       "      <td>0.308908</td>\n",
       "      <td>0.208811</td>\n",
       "      <td>0.203854</td>\n",
       "      <td>0.237241</td>\n",
       "      <td>0.229614</td>\n",
       "      <td>0.266918</td>\n",
       "      <td>0.370758</td>\n",
       "      <td>0.232673</td>\n",
       "      <td>0.609385</td>\n",
       "      <td>0.602014</td>\n",
       "      <td>0.895016</td>\n",
       "      <td>0.197981</td>\n",
       "      <td>0.363598</td>\n",
       "      <td>0.999894</td>\n",
       "      <td>0.132035</td>\n",
       "      <td>4.259682</td>\n",
       "      <td>0.962989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.5</td>\n",
       "      <td>3.704422</td>\n",
       "      <td>3.529229</td>\n",
       "      <td>0.314316</td>\n",
       "      <td>0.211411</td>\n",
       "      <td>0.206768</td>\n",
       "      <td>0.240986</td>\n",
       "      <td>0.237124</td>\n",
       "      <td>0.273416</td>\n",
       "      <td>0.378307</td>\n",
       "      <td>0.239297</td>\n",
       "      <td>0.622792</td>\n",
       "      <td>0.603327</td>\n",
       "      <td>0.903499</td>\n",
       "      <td>0.200572</td>\n",
       "      <td>0.369318</td>\n",
       "      <td>0.999046</td>\n",
       "      <td>0.168831</td>\n",
       "      <td>4.411281</td>\n",
       "      <td>0.956648</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Beta      RMSE       MAE  precision    recall       F_1      F_05  \\\n",
       "0   0.9  3.704567  3.529375   0.162354  0.076967  0.089233  0.114583   \n",
       "0   0.8  3.704552  3.529360   0.266384  0.147571  0.158660  0.194838   \n",
       "0   0.7  3.704528  3.529335   0.304136  0.187298  0.191990  0.228749   \n",
       "0   0.0  3.702446  3.527273   0.282185  0.192092  0.186749  0.216980   \n",
       "0   0.1  3.703312  3.528128   0.290138  0.197597  0.192259  0.223336   \n",
       "0   0.2  3.703825  3.528636   0.297137  0.201202  0.196067  0.228169   \n",
       "0   0.3  3.704130  3.528939   0.303499  0.204749  0.199901  0.232829   \n",
       "0   0.6  3.704488  3.529295   0.314634  0.206209  0.204818  0.240159   \n",
       "0   0.4  3.704313  3.529120   0.308908  0.208811  0.203854  0.237241   \n",
       "0   0.5  3.704422  3.529229   0.314316  0.211411  0.206768  0.240986   \n",
       "\n",
       "   precision_super  recall_super      NDCG       mAP       MRR      LAUC  \\\n",
       "0         0.134657      0.113253  0.160868  0.085486  0.243590  0.535405   \n",
       "0         0.214485      0.209336  0.299850  0.184356  0.492852  0.571152   \n",
       "0         0.238305      0.256201  0.358807  0.226808  0.593897  0.591207   \n",
       "0         0.204185      0.240096  0.339114  0.204905  0.572157  0.593544   \n",
       "0         0.210944      0.246153  0.347768  0.212034  0.581038  0.596328   \n",
       "0         0.218026      0.252767  0.355655  0.219909  0.588904  0.598160   \n",
       "0         0.225107      0.260797  0.363757  0.226825  0.599969  0.599964   \n",
       "0         0.242489      0.273850  0.376438  0.238428  0.622042  0.600721   \n",
       "0         0.229614      0.266918  0.370758  0.232673  0.609385  0.602014   \n",
       "0         0.237124      0.273416  0.378307  0.239297  0.622792  0.603327   \n",
       "\n",
       "         HR       F_2  Whole_average  Reco in test  Test coverage   Shannon  \\\n",
       "0  0.580064  0.078906       0.197947      0.800106       0.415584  5.563910   \n",
       "0  0.803818  0.146414       0.307476      0.936373       0.341270  5.257397   \n",
       "0  0.868505  0.182056       0.352330      0.983033       0.256854  4.898568   \n",
       "0  0.875928  0.181702       0.340803      1.000000       0.077201  3.875892   \n",
       "0  0.884411  0.187030       0.347420      1.000000       0.085137  3.957416   \n",
       "0  0.886532  0.190538       0.352756      1.000000       0.094517  4.053212   \n",
       "0  0.888653  0.194073       0.358344      1.000000       0.105339  4.147779   \n",
       "0  0.897137  0.197320       0.367854      0.996394       0.212843  4.621938   \n",
       "0  0.895016  0.197981       0.363598      0.999894       0.132035  4.259682   \n",
       "0  0.903499  0.200572       0.369318      0.999046       0.168831  4.411281   \n",
       "\n",
       "       Gini  \n",
       "0  0.857396  \n",
       "0  0.895882  \n",
       "0  0.928065  \n",
       "0  0.974947  \n",
       "0  0.972784  \n",
       "0  0.969980  \n",
       "0  0.966948  \n",
       "0  0.945932  \n",
       "0  0.962989  \n",
       "0  0.956648  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.sort_values([\"recall\"])"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "So Beta 0.6 and alpha 0.8 seems to maximze recall"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "model=RP3Beta()\n",
    "model.fit(train_ui, alpha=0.8, beta=0.6)\n",
    "reco=pd.DataFrame(model.recommend(user_code_id, item_code_id, topK=10))\n",
    "estimations_df=pd.DataFrame(model.estimate(user_code_id, item_code_id, test_ui))\n",
    "reco.to_csv('Recommendations generated/ml-100k/Self_RP3Beta_reco.csv', index=False, header=False)\n",
    "estimations_df.to_csv('Recommendations generated/ml-100k/Self_RP3Beta_estimations.csv', index=False, header=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "943it [00:00, 5460.13it/s]\n",
      "943it [00:00, 4803.05it/s]\n",
      "943it [00:00, 5055.06it/s]\n",
      "943it [00:00, 5345.09it/s]\n",
      "943it [00:00, 5630.17it/s]\n",
      "943it [00:00, 5312.63it/s]\n",
      "943it [00:00, 5254.57it/s]\n",
      "943it [00:00, 5601.35it/s]\n",
      "943it [00:00, 4720.28it/s]\n",
      "943it [00:00, 5849.34it/s]\n",
      "943it [00:00, 3628.59it/s]\n",
      "943it [00:00, 4575.68it/s]\n",
      "943it [00:00, 5025.63it/s]\n",
      "943it [00:00, 4779.84it/s]\n",
      "943it [00:00, 4822.16it/s]\n",
      "943it [00:00, 4399.16it/s]\n",
      "943it [00:00, 4856.83it/s]\n",
      "943it [00:00, 4987.44it/s]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Model</th>\n",
       "      <th>RMSE</th>\n",
       "      <th>MAE</th>\n",
       "      <th>precision</th>\n",
       "      <th>recall</th>\n",
       "      <th>F_1</th>\n",
       "      <th>F_05</th>\n",
       "      <th>precision_super</th>\n",
       "      <th>recall_super</th>\n",
       "      <th>NDCG</th>\n",
       "      <th>mAP</th>\n",
       "      <th>MRR</th>\n",
       "      <th>LAUC</th>\n",
       "      <th>HR</th>\n",
       "      <th>F_2</th>\n",
       "      <th>Whole_average</th>\n",
       "      <th>Reco in test</th>\n",
       "      <th>Test coverage</th>\n",
       "      <th>Shannon</th>\n",
       "      <th>Gini</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Self_RP3Beta</td>\n",
       "      <td>3.702928</td>\n",
       "      <td>3.527713</td>\n",
       "      <td>0.322694</td>\n",
       "      <td>0.216069</td>\n",
       "      <td>0.212152</td>\n",
       "      <td>0.247538</td>\n",
       "      <td>0.245279</td>\n",
       "      <td>0.284983</td>\n",
       "      <td>0.388271</td>\n",
       "      <td>0.248239</td>\n",
       "      <td>0.636318</td>\n",
       "      <td>0.605683</td>\n",
       "      <td>0.910923</td>\n",
       "      <td>0.205450</td>\n",
       "      <td>0.376967</td>\n",
       "      <td>0.999788</td>\n",
       "      <td>0.178932</td>\n",
       "      <td>4.549663</td>\n",
       "      <td>0.950182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Self_P3</td>\n",
       "      <td>3.702446</td>\n",
       "      <td>3.527273</td>\n",
       "      <td>0.282185</td>\n",
       "      <td>0.192092</td>\n",
       "      <td>0.186749</td>\n",
       "      <td>0.216980</td>\n",
       "      <td>0.204185</td>\n",
       "      <td>0.240096</td>\n",
       "      <td>0.339114</td>\n",
       "      <td>0.204905</td>\n",
       "      <td>0.572157</td>\n",
       "      <td>0.593544</td>\n",
       "      <td>0.875928</td>\n",
       "      <td>0.181702</td>\n",
       "      <td>0.340803</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.077201</td>\n",
       "      <td>3.875892</td>\n",
       "      <td>0.974947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Self_TopPop</td>\n",
       "      <td>2.508258</td>\n",
       "      <td>2.217909</td>\n",
       "      <td>0.188865</td>\n",
       "      <td>0.116919</td>\n",
       "      <td>0.118732</td>\n",
       "      <td>0.141584</td>\n",
       "      <td>0.130472</td>\n",
       "      <td>0.137473</td>\n",
       "      <td>0.214651</td>\n",
       "      <td>0.111707</td>\n",
       "      <td>0.400939</td>\n",
       "      <td>0.555546</td>\n",
       "      <td>0.765642</td>\n",
       "      <td>0.112750</td>\n",
       "      <td>0.249607</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.038961</td>\n",
       "      <td>3.159079</td>\n",
       "      <td>0.987317</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Self_SVDBaseline</td>\n",
       "      <td>3.642359</td>\n",
       "      <td>3.476956</td>\n",
       "      <td>0.135949</td>\n",
       "      <td>0.079751</td>\n",
       "      <td>0.082423</td>\n",
       "      <td>0.099673</td>\n",
       "      <td>0.106545</td>\n",
       "      <td>0.104164</td>\n",
       "      <td>0.160100</td>\n",
       "      <td>0.079313</td>\n",
       "      <td>0.328798</td>\n",
       "      <td>0.536764</td>\n",
       "      <td>0.629905</td>\n",
       "      <td>0.077617</td>\n",
       "      <td>0.201750</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.282828</td>\n",
       "      <td>5.130008</td>\n",
       "      <td>0.909760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ready_SVD</td>\n",
       "      <td>0.951186</td>\n",
       "      <td>0.750553</td>\n",
       "      <td>0.094910</td>\n",
       "      <td>0.044564</td>\n",
       "      <td>0.051182</td>\n",
       "      <td>0.065639</td>\n",
       "      <td>0.084549</td>\n",
       "      <td>0.074410</td>\n",
       "      <td>0.106164</td>\n",
       "      <td>0.049263</td>\n",
       "      <td>0.228326</td>\n",
       "      <td>0.518988</td>\n",
       "      <td>0.477200</td>\n",
       "      <td>0.045601</td>\n",
       "      <td>0.153400</td>\n",
       "      <td>0.996925</td>\n",
       "      <td>0.219336</td>\n",
       "      <td>4.494800</td>\n",
       "      <td>0.949844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Self_SVD</td>\n",
       "      <td>0.914024</td>\n",
       "      <td>0.717181</td>\n",
       "      <td>0.104454</td>\n",
       "      <td>0.043836</td>\n",
       "      <td>0.053331</td>\n",
       "      <td>0.070716</td>\n",
       "      <td>0.094528</td>\n",
       "      <td>0.076751</td>\n",
       "      <td>0.106711</td>\n",
       "      <td>0.050532</td>\n",
       "      <td>0.194366</td>\n",
       "      <td>0.518647</td>\n",
       "      <td>0.479321</td>\n",
       "      <td>0.045941</td>\n",
       "      <td>0.153261</td>\n",
       "      <td>0.853765</td>\n",
       "      <td>0.148629</td>\n",
       "      <td>3.836334</td>\n",
       "      <td>0.973007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ready_Baseline</td>\n",
       "      <td>0.949459</td>\n",
       "      <td>0.752487</td>\n",
       "      <td>0.091410</td>\n",
       "      <td>0.037652</td>\n",
       "      <td>0.046030</td>\n",
       "      <td>0.061286</td>\n",
       "      <td>0.079614</td>\n",
       "      <td>0.056463</td>\n",
       "      <td>0.095957</td>\n",
       "      <td>0.043178</td>\n",
       "      <td>0.198193</td>\n",
       "      <td>0.515501</td>\n",
       "      <td>0.437964</td>\n",
       "      <td>0.039549</td>\n",
       "      <td>0.141900</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.033911</td>\n",
       "      <td>2.836513</td>\n",
       "      <td>0.991139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ready_SVDBiased</td>\n",
       "      <td>0.939359</td>\n",
       "      <td>0.740564</td>\n",
       "      <td>0.086850</td>\n",
       "      <td>0.036359</td>\n",
       "      <td>0.043933</td>\n",
       "      <td>0.058123</td>\n",
       "      <td>0.076395</td>\n",
       "      <td>0.056913</td>\n",
       "      <td>0.094528</td>\n",
       "      <td>0.043830</td>\n",
       "      <td>0.203204</td>\n",
       "      <td>0.514846</td>\n",
       "      <td>0.443266</td>\n",
       "      <td>0.038036</td>\n",
       "      <td>0.141357</td>\n",
       "      <td>0.994804</td>\n",
       "      <td>0.179654</td>\n",
       "      <td>4.199699</td>\n",
       "      <td>0.962848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Self_KNNSurprisetask</td>\n",
       "      <td>0.946255</td>\n",
       "      <td>0.745209</td>\n",
       "      <td>0.083457</td>\n",
       "      <td>0.032848</td>\n",
       "      <td>0.041227</td>\n",
       "      <td>0.055493</td>\n",
       "      <td>0.074785</td>\n",
       "      <td>0.048890</td>\n",
       "      <td>0.089577</td>\n",
       "      <td>0.040902</td>\n",
       "      <td>0.189057</td>\n",
       "      <td>0.513076</td>\n",
       "      <td>0.417815</td>\n",
       "      <td>0.034996</td>\n",
       "      <td>0.135177</td>\n",
       "      <td>0.888547</td>\n",
       "      <td>0.130592</td>\n",
       "      <td>3.611806</td>\n",
       "      <td>0.978659</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Self_TopRated</td>\n",
       "      <td>2.508258</td>\n",
       "      <td>2.217909</td>\n",
       "      <td>0.079321</td>\n",
       "      <td>0.032667</td>\n",
       "      <td>0.039983</td>\n",
       "      <td>0.053170</td>\n",
       "      <td>0.068884</td>\n",
       "      <td>0.048582</td>\n",
       "      <td>0.070766</td>\n",
       "      <td>0.027602</td>\n",
       "      <td>0.114790</td>\n",
       "      <td>0.512943</td>\n",
       "      <td>0.411453</td>\n",
       "      <td>0.034385</td>\n",
       "      <td>0.124546</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.024531</td>\n",
       "      <td>2.761238</td>\n",
       "      <td>0.991660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Self_GlobalAvg</td>\n",
       "      <td>1.125760</td>\n",
       "      <td>0.943534</td>\n",
       "      <td>0.061188</td>\n",
       "      <td>0.025968</td>\n",
       "      <td>0.031383</td>\n",
       "      <td>0.041343</td>\n",
       "      <td>0.040558</td>\n",
       "      <td>0.032107</td>\n",
       "      <td>0.067695</td>\n",
       "      <td>0.027470</td>\n",
       "      <td>0.171187</td>\n",
       "      <td>0.509546</td>\n",
       "      <td>0.384942</td>\n",
       "      <td>0.027213</td>\n",
       "      <td>0.118383</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.025974</td>\n",
       "      <td>2.711772</td>\n",
       "      <td>0.992003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ready_Random</td>\n",
       "      <td>1.525633</td>\n",
       "      <td>1.225714</td>\n",
       "      <td>0.047720</td>\n",
       "      <td>0.022049</td>\n",
       "      <td>0.025494</td>\n",
       "      <td>0.032845</td>\n",
       "      <td>0.029077</td>\n",
       "      <td>0.025015</td>\n",
       "      <td>0.051757</td>\n",
       "      <td>0.019242</td>\n",
       "      <td>0.128181</td>\n",
       "      <td>0.507543</td>\n",
       "      <td>0.327678</td>\n",
       "      <td>0.022628</td>\n",
       "      <td>0.103269</td>\n",
       "      <td>0.987275</td>\n",
       "      <td>0.184704</td>\n",
       "      <td>5.105122</td>\n",
       "      <td>0.906561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ready_I-KNN</td>\n",
       "      <td>1.030386</td>\n",
       "      <td>0.813067</td>\n",
       "      <td>0.026087</td>\n",
       "      <td>0.006908</td>\n",
       "      <td>0.010593</td>\n",
       "      <td>0.016046</td>\n",
       "      <td>0.021137</td>\n",
       "      <td>0.009522</td>\n",
       "      <td>0.024214</td>\n",
       "      <td>0.008958</td>\n",
       "      <td>0.048068</td>\n",
       "      <td>0.499885</td>\n",
       "      <td>0.154825</td>\n",
       "      <td>0.008007</td>\n",
       "      <td>0.069521</td>\n",
       "      <td>0.402333</td>\n",
       "      <td>0.434343</td>\n",
       "      <td>5.133650</td>\n",
       "      <td>0.877999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ready_I-KNNBaseline</td>\n",
       "      <td>0.935327</td>\n",
       "      <td>0.737424</td>\n",
       "      <td>0.002545</td>\n",
       "      <td>0.000755</td>\n",
       "      <td>0.001105</td>\n",
       "      <td>0.001602</td>\n",
       "      <td>0.002253</td>\n",
       "      <td>0.000930</td>\n",
       "      <td>0.003444</td>\n",
       "      <td>0.001362</td>\n",
       "      <td>0.011760</td>\n",
       "      <td>0.496724</td>\n",
       "      <td>0.021209</td>\n",
       "      <td>0.000862</td>\n",
       "      <td>0.045379</td>\n",
       "      <td>0.482821</td>\n",
       "      <td>0.059885</td>\n",
       "      <td>2.232578</td>\n",
       "      <td>0.994487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ready_U-KNN</td>\n",
       "      <td>1.023495</td>\n",
       "      <td>0.807913</td>\n",
       "      <td>0.000742</td>\n",
       "      <td>0.000205</td>\n",
       "      <td>0.000305</td>\n",
       "      <td>0.000449</td>\n",
       "      <td>0.000536</td>\n",
       "      <td>0.000198</td>\n",
       "      <td>0.000845</td>\n",
       "      <td>0.000274</td>\n",
       "      <td>0.002744</td>\n",
       "      <td>0.496441</td>\n",
       "      <td>0.007423</td>\n",
       "      <td>0.000235</td>\n",
       "      <td>0.042533</td>\n",
       "      <td>0.602121</td>\n",
       "      <td>0.010823</td>\n",
       "      <td>2.089186</td>\n",
       "      <td>0.995706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Self_BaselineIU</td>\n",
       "      <td>0.958136</td>\n",
       "      <td>0.754051</td>\n",
       "      <td>0.000954</td>\n",
       "      <td>0.000188</td>\n",
       "      <td>0.000298</td>\n",
       "      <td>0.000481</td>\n",
       "      <td>0.000644</td>\n",
       "      <td>0.000223</td>\n",
       "      <td>0.001043</td>\n",
       "      <td>0.000335</td>\n",
       "      <td>0.003348</td>\n",
       "      <td>0.496433</td>\n",
       "      <td>0.009544</td>\n",
       "      <td>0.000220</td>\n",
       "      <td>0.042809</td>\n",
       "      <td>0.699046</td>\n",
       "      <td>0.005051</td>\n",
       "      <td>1.945910</td>\n",
       "      <td>0.995669</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Self_BaselineUI</td>\n",
       "      <td>0.967585</td>\n",
       "      <td>0.762740</td>\n",
       "      <td>0.000954</td>\n",
       "      <td>0.000170</td>\n",
       "      <td>0.000278</td>\n",
       "      <td>0.000463</td>\n",
       "      <td>0.000644</td>\n",
       "      <td>0.000189</td>\n",
       "      <td>0.000752</td>\n",
       "      <td>0.000168</td>\n",
       "      <td>0.001677</td>\n",
       "      <td>0.496424</td>\n",
       "      <td>0.009544</td>\n",
       "      <td>0.000201</td>\n",
       "      <td>0.042622</td>\n",
       "      <td>0.600530</td>\n",
       "      <td>0.005051</td>\n",
       "      <td>1.803126</td>\n",
       "      <td>0.996380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Self_IKNN</td>\n",
       "      <td>1.018363</td>\n",
       "      <td>0.808793</td>\n",
       "      <td>0.000318</td>\n",
       "      <td>0.000108</td>\n",
       "      <td>0.000140</td>\n",
       "      <td>0.000189</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000214</td>\n",
       "      <td>0.000037</td>\n",
       "      <td>0.000368</td>\n",
       "      <td>0.496391</td>\n",
       "      <td>0.003181</td>\n",
       "      <td>0.000118</td>\n",
       "      <td>0.041755</td>\n",
       "      <td>0.392153</td>\n",
       "      <td>0.115440</td>\n",
       "      <td>4.174741</td>\n",
       "      <td>0.965327</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Model      RMSE       MAE  precision    recall       F_1  \\\n",
       "0          Self_RP3Beta  3.702928  3.527713   0.322694  0.216069  0.212152   \n",
       "0               Self_P3  3.702446  3.527273   0.282185  0.192092  0.186749   \n",
       "0           Self_TopPop  2.508258  2.217909   0.188865  0.116919  0.118732   \n",
       "0      Self_SVDBaseline  3.642359  3.476956   0.135949  0.079751  0.082423   \n",
       "0             Ready_SVD  0.951186  0.750553   0.094910  0.044564  0.051182   \n",
       "0              Self_SVD  0.914024  0.717181   0.104454  0.043836  0.053331   \n",
       "0        Ready_Baseline  0.949459  0.752487   0.091410  0.037652  0.046030   \n",
       "0       Ready_SVDBiased  0.939359  0.740564   0.086850  0.036359  0.043933   \n",
       "0  Self_KNNSurprisetask  0.946255  0.745209   0.083457  0.032848  0.041227   \n",
       "0         Self_TopRated  2.508258  2.217909   0.079321  0.032667  0.039983   \n",
       "0        Self_GlobalAvg  1.125760  0.943534   0.061188  0.025968  0.031383   \n",
       "0          Ready_Random  1.525633  1.225714   0.047720  0.022049  0.025494   \n",
       "0           Ready_I-KNN  1.030386  0.813067   0.026087  0.006908  0.010593   \n",
       "0   Ready_I-KNNBaseline  0.935327  0.737424   0.002545  0.000755  0.001105   \n",
       "0           Ready_U-KNN  1.023495  0.807913   0.000742  0.000205  0.000305   \n",
       "0       Self_BaselineIU  0.958136  0.754051   0.000954  0.000188  0.000298   \n",
       "0       Self_BaselineUI  0.967585  0.762740   0.000954  0.000170  0.000278   \n",
       "0             Self_IKNN  1.018363  0.808793   0.000318  0.000108  0.000140   \n",
       "\n",
       "       F_05  precision_super  recall_super      NDCG       mAP       MRR  \\\n",
       "0  0.247538         0.245279      0.284983  0.388271  0.248239  0.636318   \n",
       "0  0.216980         0.204185      0.240096  0.339114  0.204905  0.572157   \n",
       "0  0.141584         0.130472      0.137473  0.214651  0.111707  0.400939   \n",
       "0  0.099673         0.106545      0.104164  0.160100  0.079313  0.328798   \n",
       "0  0.065639         0.084549      0.074410  0.106164  0.049263  0.228326   \n",
       "0  0.070716         0.094528      0.076751  0.106711  0.050532  0.194366   \n",
       "0  0.061286         0.079614      0.056463  0.095957  0.043178  0.198193   \n",
       "0  0.058123         0.076395      0.056913  0.094528  0.043830  0.203204   \n",
       "0  0.055493         0.074785      0.048890  0.089577  0.040902  0.189057   \n",
       "0  0.053170         0.068884      0.048582  0.070766  0.027602  0.114790   \n",
       "0  0.041343         0.040558      0.032107  0.067695  0.027470  0.171187   \n",
       "0  0.032845         0.029077      0.025015  0.051757  0.019242  0.128181   \n",
       "0  0.016046         0.021137      0.009522  0.024214  0.008958  0.048068   \n",
       "0  0.001602         0.002253      0.000930  0.003444  0.001362  0.011760   \n",
       "0  0.000449         0.000536      0.000198  0.000845  0.000274  0.002744   \n",
       "0  0.000481         0.000644      0.000223  0.001043  0.000335  0.003348   \n",
       "0  0.000463         0.000644      0.000189  0.000752  0.000168  0.001677   \n",
       "0  0.000189         0.000000      0.000000  0.000214  0.000037  0.000368   \n",
       "\n",
       "       LAUC        HR       F_2  Whole_average  Reco in test  Test coverage  \\\n",
       "0  0.605683  0.910923  0.205450       0.376967      0.999788       0.178932   \n",
       "0  0.593544  0.875928  0.181702       0.340803      1.000000       0.077201   \n",
       "0  0.555546  0.765642  0.112750       0.249607      1.000000       0.038961   \n",
       "0  0.536764  0.629905  0.077617       0.201750      1.000000       0.282828   \n",
       "0  0.518988  0.477200  0.045601       0.153400      0.996925       0.219336   \n",
       "0  0.518647  0.479321  0.045941       0.153261      0.853765       0.148629   \n",
       "0  0.515501  0.437964  0.039549       0.141900      1.000000       0.033911   \n",
       "0  0.514846  0.443266  0.038036       0.141357      0.994804       0.179654   \n",
       "0  0.513076  0.417815  0.034996       0.135177      0.888547       0.130592   \n",
       "0  0.512943  0.411453  0.034385       0.124546      1.000000       0.024531   \n",
       "0  0.509546  0.384942  0.027213       0.118383      1.000000       0.025974   \n",
       "0  0.507543  0.327678  0.022628       0.103269      0.987275       0.184704   \n",
       "0  0.499885  0.154825  0.008007       0.069521      0.402333       0.434343   \n",
       "0  0.496724  0.021209  0.000862       0.045379      0.482821       0.059885   \n",
       "0  0.496441  0.007423  0.000235       0.042533      0.602121       0.010823   \n",
       "0  0.496433  0.009544  0.000220       0.042809      0.699046       0.005051   \n",
       "0  0.496424  0.009544  0.000201       0.042622      0.600530       0.005051   \n",
       "0  0.496391  0.003181  0.000118       0.041755      0.392153       0.115440   \n",
       "\n",
       "    Shannon      Gini  \n",
       "0  4.549663  0.950182  \n",
       "0  3.875892  0.974947  \n",
       "0  3.159079  0.987317  \n",
       "0  5.130008  0.909760  \n",
       "0  4.494800  0.949844  \n",
       "0  3.836334  0.973007  \n",
       "0  2.836513  0.991139  \n",
       "0  4.199699  0.962848  \n",
       "0  3.611806  0.978659  \n",
       "0  2.761238  0.991660  \n",
       "0  2.711772  0.992003  \n",
       "0  5.105122  0.906561  \n",
       "0  5.133650  0.877999  \n",
       "0  2.232578  0.994487  \n",
       "0  2.089186  0.995706  \n",
       "0  1.945910  0.995669  \n",
       "0  1.803126  0.996380  \n",
       "0  4.174741  0.965327  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import imp\n",
    "imp.reload(ev)\n",
    "\n",
    "import evaluation_measures as ev\n",
    "dir_path=\"Recommendations generated/ml-100k/\"\n",
    "super_reactions=[4,5]\n",
    "test=pd.read_csv('./Datasets/ml-100k/test.csv', sep='\\t', header=None)\n",
    "\n",
    "ev.evaluate_all(test, dir_path, super_reactions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# project task 7 (optional): implement graph-based model of your choice "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for example change length of paths in RP3beta\n",
    "# save the outptut in 'Recommendations generated/ml-100k/Self_GraphTask_estimations.csv'\n",
    "# and 'Recommendations generated/ml-100k/Self_GraphTask_reco.csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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