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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<h1>Grocery Recommendation Model</h1>\n",
+    "<h5>Created by: Cristopher Ian Artacho</h5>\n",
+    "<h5>BSCS 3A</h5>\n",
+    "\n",
+    "<h5>Using a dataset from kaggle, the aim of this project is to train an unsupervised model that would pair a product with another based the frequency of the pair..</h5>"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "from mlxtend.frequent_patterns import apriori, association_rules"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = pd.read_csv(\"Grocery Products Purchase.csv\", header=None)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "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>0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <th>4</th>\n",
+       "      <th>5</th>\n",
+       "      <th>6</th>\n",
+       "      <th>7</th>\n",
+       "      <th>8</th>\n",
+       "      <th>9</th>\n",
+       "      <th>...</th>\n",
+       "      <th>22</th>\n",
+       "      <th>23</th>\n",
+       "      <th>24</th>\n",
+       "      <th>25</th>\n",
+       "      <th>26</th>\n",
+       "      <th>27</th>\n",
+       "      <th>28</th>\n",
+       "      <th>29</th>\n",
+       "      <th>30</th>\n",
+       "      <th>31</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Product 1</td>\n",
+       "      <td>Product 2</td>\n",
+       "      <td>Product 3</td>\n",
+       "      <td>Product 4</td>\n",
+       "      <td>Product 5</td>\n",
+       "      <td>Product 6</td>\n",
+       "      <td>Product 7</td>\n",
+       "      <td>Product 8</td>\n",
+       "      <td>Product 9</td>\n",
+       "      <td>Product 10</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Product 23</td>\n",
+       "      <td>Product 24</td>\n",
+       "      <td>Product 25</td>\n",
+       "      <td>Product 26</td>\n",
+       "      <td>Product 27</td>\n",
+       "      <td>Product 28</td>\n",
+       "      <td>Product 29</td>\n",
+       "      <td>Product 30</td>\n",
+       "      <td>Product 31</td>\n",
+       "      <td>Product 32</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>citrus fruit</td>\n",
+       "      <td>semi-finished bread</td>\n",
+       "      <td>margarine</td>\n",
+       "      <td>ready soups</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>tropical fruit</td>\n",
+       "      <td>yogurt</td>\n",
+       "      <td>coffee</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>whole milk</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>pip fruit</td>\n",
+       "      <td>yogurt</td>\n",
+       "      <td>cream cheese</td>\n",
+       "      <td>meat spreads</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9831</th>\n",
+       "      <td>sausage</td>\n",
+       "      <td>chicken</td>\n",
+       "      <td>beef</td>\n",
+       "      <td>hamburger meat</td>\n",
+       "      <td>citrus fruit</td>\n",
+       "      <td>grapes</td>\n",
+       "      <td>root vegetables</td>\n",
+       "      <td>whole milk</td>\n",
+       "      <td>butter</td>\n",
+       "      <td>whipped/sour cream</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9832</th>\n",
+       "      <td>cooking chocolate</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9833</th>\n",
+       "      <td>chicken</td>\n",
+       "      <td>citrus fruit</td>\n",
+       "      <td>other vegetables</td>\n",
+       "      <td>butter</td>\n",
+       "      <td>yogurt</td>\n",
+       "      <td>frozen dessert</td>\n",
+       "      <td>domestic eggs</td>\n",
+       "      <td>rolls/buns</td>\n",
+       "      <td>rum</td>\n",
+       "      <td>cling film/bags</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9834</th>\n",
+       "      <td>semi-finished bread</td>\n",
+       "      <td>bottled water</td>\n",
+       "      <td>soda</td>\n",
+       "      <td>bottled beer</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9835</th>\n",
+       "      <td>chicken</td>\n",
+       "      <td>tropical fruit</td>\n",
+       "      <td>other vegetables</td>\n",
+       "      <td>vinegar</td>\n",
+       "      <td>shopping bags</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>9836 rows × 32 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                       0                    1                 2   \\\n",
+       "0               Product 1            Product 2         Product 3   \n",
+       "1            citrus fruit  semi-finished bread         margarine   \n",
+       "2          tropical fruit               yogurt            coffee   \n",
+       "3              whole milk                  NaN               NaN   \n",
+       "4               pip fruit               yogurt      cream cheese   \n",
+       "...                   ...                  ...               ...   \n",
+       "9831              sausage              chicken              beef   \n",
+       "9832    cooking chocolate                  NaN               NaN   \n",
+       "9833              chicken         citrus fruit  other vegetables   \n",
+       "9834  semi-finished bread        bottled water              soda   \n",
+       "9835              chicken       tropical fruit  other vegetables   \n",
+       "\n",
+       "                  3              4               5                6   \\\n",
+       "0          Product 4      Product 5       Product 6        Product 7   \n",
+       "1        ready soups            NaN             NaN              NaN   \n",
+       "2                NaN            NaN             NaN              NaN   \n",
+       "3                NaN            NaN             NaN              NaN   \n",
+       "4       meat spreads            NaN             NaN              NaN   \n",
+       "...              ...            ...             ...              ...   \n",
+       "9831  hamburger meat   citrus fruit          grapes  root vegetables   \n",
+       "9832             NaN            NaN             NaN              NaN   \n",
+       "9833          butter         yogurt  frozen dessert    domestic eggs   \n",
+       "9834    bottled beer            NaN             NaN              NaN   \n",
+       "9835         vinegar  shopping bags             NaN              NaN   \n",
+       "\n",
+       "              7          8                   9   ...          22          23  \\\n",
+       "0      Product 8  Product 9          Product 10  ...  Product 23  Product 24   \n",
+       "1            NaN        NaN                 NaN  ...         NaN         NaN   \n",
+       "2            NaN        NaN                 NaN  ...         NaN         NaN   \n",
+       "3            NaN        NaN                 NaN  ...         NaN         NaN   \n",
+       "4            NaN        NaN                 NaN  ...         NaN         NaN   \n",
+       "...          ...        ...                 ...  ...         ...         ...   \n",
+       "9831  whole milk     butter  whipped/sour cream  ...         NaN         NaN   \n",
+       "9832         NaN        NaN                 NaN  ...         NaN         NaN   \n",
+       "9833  rolls/buns        rum     cling film/bags  ...         NaN         NaN   \n",
+       "9834         NaN        NaN                 NaN  ...         NaN         NaN   \n",
+       "9835         NaN        NaN                 NaN  ...         NaN         NaN   \n",
+       "\n",
+       "              24          25          26          27          28          29  \\\n",
+       "0     Product 25  Product 26  Product 27  Product 28  Product 29  Product 30   \n",
+       "1            NaN         NaN         NaN         NaN         NaN         NaN   \n",
+       "2            NaN         NaN         NaN         NaN         NaN         NaN   \n",
+       "3            NaN         NaN         NaN         NaN         NaN         NaN   \n",
+       "4            NaN         NaN         NaN         NaN         NaN         NaN   \n",
+       "...          ...         ...         ...         ...         ...         ...   \n",
+       "9831         NaN         NaN         NaN         NaN         NaN         NaN   \n",
+       "9832         NaN         NaN         NaN         NaN         NaN         NaN   \n",
+       "9833         NaN         NaN         NaN         NaN         NaN         NaN   \n",
+       "9834         NaN         NaN         NaN         NaN         NaN         NaN   \n",
+       "9835         NaN         NaN         NaN         NaN         NaN         NaN   \n",
+       "\n",
+       "              30          31  \n",
+       "0     Product 31  Product 32  \n",
+       "1            NaN         NaN  \n",
+       "2            NaN         NaN  \n",
+       "3            NaN         NaN  \n",
+       "4            NaN         NaN  \n",
+       "...          ...         ...  \n",
+       "9831         NaN         NaN  \n",
+       "9832         NaN         NaN  \n",
+       "9833         NaN         NaN  \n",
+       "9834         NaN         NaN  \n",
+       "9835         NaN         NaN  \n",
+       "\n",
+       "[9836 rows x 32 columns]"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "transactions = df.apply(lambda row: row.dropna().tolist(), axis=1).tolist()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Convert transactions into one-hot encoded DataFrame\n",
+    "unique_items = sorted(set(item for transaction in transactions for item in transaction))\n",
+    "encoded_data = pd.DataFrame([{item: (item in transaction) for item in unique_items} for transaction in transactions])\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Formatting the table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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ULl1a2rZtKydOnJC0adPK1KlTJTw8PEbNo1xdXV9rrKYRI0ZIYGCglC9fXj7++GNJkiSJfPfdd/L8+XMZM2aMUS5//vxSuXJlKVasmKROnVr27dsnS5Yska5duxplrJ2IdO/eXfz8/CRx4sTSrFmzN677v6lUqZJ89NFHMmrUKDl06JD4+vpK0qRJ5cyZM7J48WKZNGmSNG7c2BjTatSoUVK7dm2pWbOmHDx4UNauXStp06a1+UxfX1/JnDmztG/fXvr06SOJEyeWWbNmSbp06eTy5ctGORcXF5k2bZq0bNlSihYtKs2aNTPKrF69WsqVKxctxP+b5MmTS/78+WXRokWSO3duSZ06tfj4+MTasAIvKlSokLRu3VpmzJghDx48kEqVKsmePXtk7ty5Ur9+falSpYqIiGnrb8KECdKhQwcpUaKEMf7X4cOH5cmTJ0Y4K1asmCxatEh69eolJUqUkJQpU0qdOnXE19dXPDw8pFy5cpI+fXo5efKkTJkyRWrVqvXS5xIB4F/ZtS9EAIgHXtYl+cOHD7Vnz57q6empSZMm1Vy5cunXX39t0/20amTX7wEBAfrTTz9prly51NHRUYsUKaJbtmx5rd9t7f77ZT+zZ8+2KXvv3j1t3769pkmTRlOkSKGVKlUyuvH+N1G7fn+Vl3X9rqp64MAB9fPz05QpU2qKFCm0SpUqumPHDpsyI0aM0JIlS6qbm5smT55c8+bNqyNHjtSQkBCjTFhYmHbr1k3TpUunFovlX7uB/7c6t27dWp2cnF45f8aMGVqsWDFNnjy5Ojs7a4ECBbRv3756/fp1o0x4eLgOGzZMM2TIoMmTJ9fKlSvrsWPHNEuWLNG64d+/f7+WKlVKHRwcNHPmzDp+/PhoXZdbbdmyRf38/NTV1VWTJUumOXLk0DZt2tgMEfCq+r+sm/QdO3ZosWLF1MHB4V+7gX/V3/FVv+fOnTvR5oWGhuqwYcM0W7ZsmjRpUvXy8tIBAwbos2fPbMqZtf5+++03LVu2rCZPnlxdXFy0ZMmSunDhQmP+o0ePtEWLFurm5qYiYnQD/91332nFihU1TZo06ujoqDly5NA+ffpoUFDQP64LAHgVi2qU++oAgLfKYrFIQEDAG9+twLsta9asUrlyZZkzZ469qwIAsCOe2QIAAAAAExC2AAAAAMAEhC0AAAAAMAHPbAEAAACACbizBQAAAAAmYJyt1xARESHXr18XZ2fnfxx1HgAAAED8pqry8OFD8fT0lESJ/vneFWHrNVy/fl28vLzsXQ0AAAAA74grV65IpkyZ/rEMYes1WEeNv3Lliri4uNi5NgAAAADsJTg4WLy8vIyM8E8IW6/B2nTQxcWFsAUAAADgtR4vooMMAAAAADABYQsAAAAATEDYAgAAAAATELYAAAAAwASELQAAAAAwAWELAAAAAExA2AIAAAAAExC2AAAAAMAEhC0AAAAAMAFhCwAAAABMQNgCAAAAABMQtgAAAADABIQtAAAAADABYQsAAAAATEDYAgAAAAATELYAAAAAwASELQAAAAAwAWELAAAAAExg17A1atQoKVGihDg7O4u7u7vUr19fTp06ZVOmcuXKYrFYbH46d+5sU+by5ctSq1YtSZEihbi7u0ufPn0kLCzMpszWrVulaNGi4ujoKDlz5pQ5c+aYvXgAAAAAErAk9vzl27Ztk4CAAClRooSEhYXJwIEDxdfXV06cOCFOTk5GuY4dO8oXX3xhvE6RIoXx//DwcKlVq5Z4eHjIjh075MaNG9KqVStJmjSpfPnllyIicuHCBalVq5Z07txZ5s+fL5s2bZIOHTpIhgwZxM/P7+0tcBSjD/5tl9/7OvoXSWvvKgAAAABxnkVV1d6VsLpz5464u7vLtm3bpGLFiiISeWercOHCMnHixJe+Z+3atVK7dm25fv26pE+fXkREpk+fLv369ZM7d+6Ig4OD9OvXT1avXi3Hjh0z3tesWTN58OCBrFu37l/rFRwcLK6urhIUFCQuLi7/fUGFsAUAAADERW+SDd6pZ7aCgoJERCR16tQ20+fPny9p06YVHx8fGTBggDx58sSYt3PnTilQoIARtERE/Pz8JDg4WI4fP26UqV69us1n+vn5yc6dO19aj+fPn0twcLDNDwAAAAC8Cbs2I4wqIiJCPvnkEylXrpz4+PgY01u0aCFZsmQRT09POXLkiPTr109OnToly5YtExGRmzdv2gQtETFe37x58x/LBAcHy9OnTyV58uQ280aNGiXDhg2L9WUEAAAAkHC8M2ErICBAjh07Jn/88YfN9E6dOhn/L1CggGTIkEGqVasm586dkxw5cphSlwEDBkivXr2M18HBweLl5WXK7wIAAAAQP70TzQi7du0qq1atki1btkimTJn+sWypUqVEROTs2bMiIuLh4SG3bt2yKWN97eHh8Y9lXFxcot3VEhFxdHQUFxcXmx8AAAAAeBN2DVuqKl27dpXly5fL5s2bJVu2bP/6nkOHDomISIYMGUREpEyZMnL06FG5ffu2USYwMFBcXFwkf/78RplNmzbZfE5gYKCUKVMmlpYEAAAAAGzZNWwFBATITz/9JAsWLBBnZ2e5efOm3Lx5U54+fSoiIufOnZPhw4fL/v375eLFi/Lbb79Jq1atpGLFilKwYEEREfH19ZX8+fNLy5Yt5fDhw7J+/XoZPHiwBAQEiKOjo4iIdO7cWc6fPy99+/aVv/76S6ZOnSq//PKL9OzZ027LDgAAACB+s2vX7xaL5aXTZ8+eLW3atJErV67Ihx9+KMeOHZPHjx+Ll5eXNGjQQAYPHmzTtO/SpUvSpUsX2bp1qzg5OUnr1q1l9OjRkiTJ/x5J27p1q/Ts2VNOnDghmTJlks8++0zatGnzWvWk63cAAAAAIm+WDd6pcbbeVYQtAAAAACJxeJwtAAAAAIgvCFsAAAAAYALCFgAAAACYgLAFAAAAACYgbAEAAACACQhbAAAAAGACwhYAAAAAmICwBQAAAAAmIGwBAAAAgAkIWwAAAABgAsIWAAAAAJiAsAUAAAAAJiBsAQAAAIAJCFsAAAAAYALCFgAAAACYgLAFAAAAACYgbAEAAACACQhbAAAAAGACwhYAAAAAmICwBQAAAAAmIGwBAAAAgAkIWwAAAABgAsIWAAAAAJiAsAUAAAAAJiBsAQAAAIAJCFsAAAAAYALCFgAAAACYgLAFAAAAACYgbAEAAACACQhbAAAAAGACwhYAAAAAmICwBQAAAAAmIGwBAAAAgAkIWwAAAABgAsIWAAAAAJiAsAUAAAAAJiBsAQAAAIAJCFsAAAAAYALCFgAAAACYgLAFAAAAACYgbAEAAACACQhbAAAAAGACwhYAAAAAmICwBQAAAAAmIGwBAAAAgAkIWwAAAABgAsIWAAAAAJiAsAUAAAAAJiBsAQAAAIAJCFsAAAAAYALCFgAAAACYgLAFAAAAACYgbAEAAACACQhbAAAAAGACwhYAAAAAmICwBQAAAAAmIGwBAAAAgAkIWwAAAABgAsIWAAAAAJiAsAUAAAAAJiBsAQAAAIAJCFsAAAAAYALCFgAAAACYgLAFAAAAACYgbAEAAACACQhbAAAAAGACwhYAAAAAmICwBQAAAAAmIGwBAAAAgAkIWwAAAABgAsIWAAAAAJiAsAUAAAAAJiBsAQAAAIAJCFsAAAAAYALCFgAAAACYgLAFAAAAACYgbAEAAACACewatkaNGiUlSpQQZ2dncXd3l/r168upU6dsyjx79kwCAgIkTZo0kjJlSmnUqJHcunXLpszly5elVq1akiJFCnF3d5c+ffpIWFiYTZmtW7dK0aJFxdHRUXLmzClz5swxe/EAAAAAJGB2DVvbtm2TgIAA2bVrlwQGBkpoaKj4+vrK48ePjTI9e/aUlStXyuLFi2Xbtm1y/fp1adiwoTE/PDxcatWqJSEhIbJjxw6ZO3euzJkzRz7//HOjzIULF6RWrVpSpUoVOXTokHzyySfSoUMHWb9+/VtdXgAAAAAJh0VV1d6VsLpz5464u7vLtm3bpGLFihIUFCTp0qWTBQsWSOPGjUVE5K+//pJ8+fLJzp07pXTp0rJ27VqpXbu2XL9+XdKnTy8iItOnT5d+/frJnTt3xMHBQfr16yerV6+WY8eOGb+rWbNm8uDBA1m3bl20ejx//lyeP39uvA4ODhYvLy8JCgoSFxeXWFnW0Qf/jpXPMUP/ImntXQUAAADgnRQcHCyurq6vlQ3eqWe2goKCREQkderUIiKyf/9+CQ0NlerVqxtl8ubNK5kzZ5adO3eKiMjOnTulQIECRtASEfHz85Pg4GA5fvy4USbqZ1jLWD/jRaNGjRJXV1fjx8vLK/YWEgAAAECC8M6ErYiICPnkk0+kXLly4uPjIyIiN2/eFAcHB3Fzc7Mpmz59erl586ZRJmrQss63zvunMsHBwfL06dNodRkwYIAEBQUZP1euXImVZQQAAACQcCSxdwWsAgIC5NixY/LHH3/Yuyri6Ogojo6O9q4GAAAAgDjsnbiz1bVrV1m1apVs2bJFMmXKZEz38PCQkJAQefDggU35W7duiYeHh1Hmxd4Jra//rYyLi4skT548thcHAAAAAOwbtlRVunbtKsuXL5fNmzdLtmzZbOYXK1ZMkiZNKps2bTKmnTp1Si5fvixlypQREZEyZcrI0aNH5fbt20aZwMBAcXFxkfz58xtlon6GtYz1MwAAAAAgttm1GWFAQIAsWLBAfv31V3F2djaesXJ1dZXkyZOLq6urtG/fXnr16iWpU6cWFxcX6datm5QpU0ZKly4tIiK+vr6SP39+admypYwZM0Zu3rwpgwcPloCAAKMpYOfOnWXKlCnSt29fadeunWzevFl++eUXWb16td2WHQAAAED8Ztc7W9OmTZOgoCCpXLmyZMiQwfhZtGiRUWbChAlSu3ZtadSokVSsWFE8PDxk2bJlxvzEiRPLqlWrJHHixFKmTBn58MMPpVWrVvLFF18YZbJlyyarV6+WwMBAKVSokIwbN06+//578fPze6vLCwAAACDheKfG2XpXvUlf+q+LcbYAAACAuCfOjrMFAAAAAPEFYQsAAAAATEDYAgAAAAATELYAAAAAwASELQAAAAAwAWELAAAAAExA2AIAAAAAExC2AAAAAMAEhC0AAAAAMEESe1cAeF2jD/5t7yq8Uv8iae1dBQAAALxjuLMFAAAAACYgbAEAAACACQhbAAAAAGACwhYAAAAAmICwBQAAAAAmIGwBAAAAgAkIWwAAAABgAsIWAAAAAJiAsAUAAAAAJiBsAQAAAIAJCFsAAAAAYALCFgAAAACYgLAFAAAAACYgbAEAAACACQhbAAAAAGACwhYAAAAAmCCJvSsAwFyjD/5t7yq8Uv8iae1dBQAAANNwZwsAAAAATEDYAgAAAAATELYAAAAAwASELQAAAAAwAWELAAAAAExA2AIAAAAAExC2AAAAAMAEhC0AAAAAMAFhCwAAAABMQNgCAAAAABMQtgAAAADABIQtAAAAADABYQsAAAAATEDYAgAAAAATELYAAAAAwARJ7F0BAHjXjD74t72r8Er9i6S1dxUAAMBr4s4WAAAAAJiAsAUAAAAAJiBsAQAAAIAJCFsAAAAAYALCFgAAAACYgLAFAAAAACYgbAEAAACACQhbAAAAAGACwhYAAAAAmICwBQAAAAAmIGwBAAAAgAkIWwAAAABgAsIWAAAAAJiAsAUAAAAAJiBsAQAAAIAJCFsAAAAAYALCFgAAAACYgLAFAAAAACYgbAEAAACACQhbAAAAAGACwhYAAAAAmICwBQAAAAAmIGwBAAAAgAkIWwAAAABgAsIWAAAAAJiAsAUAAAAAJiBsAQAAAIAJCFsAAAAAYALCFgAAAACYgLAFAAAAACYgbAEAAACACQhbAAAAAGACwhYAAAAAmMCuYWv79u1Sp04d8fT0FIvFIitWrLCZ36ZNG7FYLDY//v7+NmXu3bsnH3zwgbi4uIibm5u0b99eHj16ZFPmyJEjUqFCBUmWLJl4eXnJmDFjzF40AAAAAAmcXcPW48ePpVChQvLtt9++soy/v7/cuHHD+Fm4cKHN/A8++ECOHz8ugYGBsmrVKtm+fbt06tTJmB8cHCy+vr6SJUsW2b9/v3z99dcydOhQmTFjhmnLBQAAAABJ7PnLa9SoITVq1PjHMo6OjuLh4fHSeSdPnpR169bJ3r17pXjx4iIi8s0330jNmjVl7Nix4unpKfPnz5eQkBCZNWuWODg4iLe3txw6dEjGjx9vE8oAAAAAIDbF6M7W+fPnY7ser7R161Zxd3eXPHnySJcuXeTu3bvGvJ07d4qbm5sRtEREqlevLokSJZLdu3cbZSpWrCgODg5GGT8/Pzl16pTcv3//pb/z+fPnEhwcbPMDAAAAAG8iRmErZ86cUqVKFfnpp5/k2bNnsV0ng7+/v/z444+yadMm+eqrr2Tbtm1So0YNCQ8PFxGRmzdviru7u817kiRJIqlTp5abN28aZdKnT29TxvraWuZFo0aNEldXV+PHy8srthcNAAAAQDwXo7B14MABKViwoPTq1Us8PDzko48+kj179sR23aRZs2ZSt25dKVCggNSvX19WrVole/fula1bt8b674pqwIABEhQUZPxcuXLF1N8HAAAAIP6JUdgqXLiwTJo0Sa5fvy6zZs2SGzduSPny5cXHx0fGjx8vd+7cie16iohI9uzZJW3atHL27FkREfHw8JDbt2/blAkLC5N79+4Zz3l5eHjIrVu3bMpYX7/qWTBHR0dxcXGx+QEAAACAN/GfeiNMkiSJNGzYUBYvXixfffWVnD17Vnr37i1eXl7SqlUruXHjRmzVU0RErl69Knfv3pUMGTKIiEiZMmXkwYMHsn//fqPM5s2bJSIiQkqVKmWU2b59u4SGhhplAgMDJU+ePJIqVapYrR8AAAAAWP2nsLVv3z75+OOPJUOGDDJ+/Hjp3bu3nDt3TgIDA+X69etSr169f3z/o0eP5NChQ3Lo0CEREblw4YIcOnRILl++LI8ePZI+ffrIrl275OLFi7Jp0yapV6+e5MyZU/z8/EREJF++fOLv7y8dO3aUPXv2yJ9//ildu3aVZs2aiaenp4iItGjRQhwcHKR9+/Zy/PhxWbRokUyaNEl69er1XxYdAAAAAP5RjLp+Hz9+vMyePVtOnTolNWvWlB9//FFq1qwpiRJFZrds2bLJnDlzJGvWrP/4Ofv27ZMqVaoYr60BqHXr1jJt2jQ5cuSIzJ07Vx48eCCenp7i6+srw4cPF0dHR+M98+fPl65du0q1atUkUaJE0qhRI5k8ebIx39XVVTZs2CABAQFSrFgxSZs2rXz++ed0+w4AAADAVDEKW9OmTZN27dpJmzZtjCZ9L3J3d5cffvjhHz+ncuXKoqqvnL9+/fp/rUvq1KllwYIF/1imYMGC8vvvv//rZwEAAABAbIlR2Dpz5sy/lnFwcJDWrVvH5OMBAAAAIM6L0TNbs2fPlsWLF0ebvnjxYpk7d+5/rhQAAAAAxHUxClujRo2StGnTRpvu7u4uX3755X+uFAAAAADEdTEKW5cvX5Zs2bJFm54lSxa5fPnyf64UAAAAAMR1MQpb7u7ucuTIkWjTDx8+LGnSpPnPlQIAAACAuC5GYat58+bSvXt32bJli4SHh0t4eLhs3rxZevToIc2aNYvtOgIAAABAnBOj3giHDx8uFy9elGrVqkmSJJEfERERIa1ateKZLQAAAACQGIYtBwcHWbRokQwfPlwOHz4syZMnlwIFCkiWLFliu34AAAAAECfFKGxZ5c6dW3Lnzh1bdQEAAACAeCNGYSs8PFzmzJkjmzZtktu3b0tERITN/M2bN8dK5QAAAAAgropR2OrRo4fMmTNHatWqJT4+PmKxWGK7XgAAAAAQp8UobP3888/yyy+/SM2aNWO7PgAAAAAQL8So63cHBwfJmTNnbNcFAAAAAOKNGIWtTz/9VCZNmiSqGtv1AQAAAIB4IUbNCP/44w/ZsmWLrF27Vry9vSVp0qQ285ctWxYrlQMAAACAuCpGYcvNzU0aNGgQ23UBAMRhow/+be8qvFL/ImntXQUAQAIUo7A1e/bs2K4HAAAAAMQrMXpmS0QkLCxMNm7cKN999508fPhQRESuX78ujx49irXKAQAAAEBcFaM7W5cuXRJ/f3+5fPmyPH/+XN577z1xdnaWr776Sp4/fy7Tp0+P7XoCAAAAQJwSoztbPXr0kOLFi8v9+/clefLkxvQGDRrIpk2bYq1yAAAAABBXxejO1u+//y47duwQBwcHm+lZs2aVa9euxUrFAAAAACAui9GdrYiICAkPD482/erVq+Ls7PyfKwUAAAAAcV2Mwpavr69MnDjReG2xWOTRo0cyZMgQqVmzZmzVDQAAAADirBg1Ixw3bpz4+flJ/vz55dmzZ9KiRQs5c+aMpE2bVhYuXBjbdQQAAACAOCdGYStTpkxy+PBh+fnnn+XIkSPy6NEjad++vXzwwQc2HWYAAAAAQEIVo7AlIpIkSRL58MMPY7MuAAAAABBvxChs/fjjj/84v1WrVjGqDAAAAADEFzEKWz169LB5HRoaKk+ePBEHBwdJkSIFYQsAAABAghej3gjv379v8/Po0SM5deqUlC9fng4yAAAAAEBiGLZeJleuXDJ69Ohod70AAAAAICGKtbAlEtlpxvXr12PzIwEAAAAgTorRM1u//fabzWtVlRs3bsiUKVOkXLlysVIxAAAAAIjLYhS26tevb/PaYrFIunTppGrVqjJu3LjYqBcAAAAAxGkxClsRERGxXQ8AAAAAiFdi9ZktAAAAAECkGN3Z6tWr12uXHT9+fEx+BQAAAADEaTEKWwcPHpSDBw9KaGio5MmTR0RETp8+LYkTJ5aiRYsa5SwWS+zUEgAAAADimBiFrTp16oizs7PMnTtXUqVKJSKRAx23bdtWKlSoIJ9++mmsVhIAAAAA4poYPbM1btw4GTVqlBG0RERSpUolI0aMoDdCAAAAAJAYhq3g4GC5c+dOtOl37tyRhw8f/udKAQAAAEBcF6Ow1aBBA2nbtq0sW7ZMrl69KlevXpWlS5dK+/btpWHDhrFdRwAAAACIc2L0zNb06dOld+/e0qJFCwkNDY38oCRJpH379vL111/HagUBAAAAIC6KUdhKkSKFTJ06Vb7++ms5d+6ciIjkyJFDnJycYrVyAAAAABBX/adBjW/cuCE3btyQXLlyiZOTk6hqbNULAAAAAOK0GIWtu3fvSrVq1SR37txSs2ZNuXHjhoiItG/fnm7fAQAAAEBiGLZ69uwpSZMmlcuXL0uKFCmM6U2bNpV169bFWuUAAAAAIK6K0TNbGzZskPXr10umTJlspufKlUsuXboUKxUDAAAAgLgsRne2Hj9+bHNHy+revXvi6Oj4nysFAAAAAHFdjMJWhQoV5McffzReWywWiYiIkDFjxkiVKlVirXIAAAAAEFfFqBnhmDFjpFq1arJv3z4JCQmRvn37yvHjx+XevXvy559/xnYdAQAAACDOidGdLR8fHzl9+rSUL19e6tWrJ48fP5aGDRvKwYMHJUeOHLFdRwAAAACIc974zlZoaKj4+/vL9OnTZdCgQWbUCQAAAADivDe+s5U0aVI5cuSIGXUBAAAAgHgjRs0IP/zwQ/nhhx9iuy4AAAAAEG/EqIOMsLAwmTVrlmzcuFGKFSsmTk5ONvPHjx8fK5UDAAAAgLjqjcLW+fPnJWvWrHLs2DEpWrSoiIicPn3apozFYom92gEAAABAHPVGYStXrlxy48YN2bJli4iING3aVCZPnizp06c3pXIAAAAAEFe90TNbqmrzeu3atfL48eNYrRAAAAAAxAcx6iDD6sXwBQAAAACI9EZhy2KxRHsmi2e0AAAAACC6N3pmS1WlTZs24ujoKCIiz549k86dO0frjXDZsmWxV0MAAAAAiIPeKGy1bt3a5vWHH34Yq5UBAAAAgPjijcLW7NmzzaoHAAAAAMQr/6mDDAAAAADAyxG2AAAAAMAEb9SMEAAAxJ7RB/+2dxVeqX+RtPauAgDEedzZAgAAAAATELYAAAAAwAQ0IwQAAHEKzS8BxBXc2QIAAAAAExC2AAAAAMAEhC0AAAAAMAFhCwAAAABMQNgCAAAAABMQtgAAAADABHT9DgAAEM/RXT5gH9zZAgAAAAAT2DVsbd++XerUqSOenp5isVhkxYoVNvNVVT7//HPJkCGDJE+eXKpXry5nzpyxKXPv3j354IMPxMXFRdzc3KR9+/by6NEjmzJHjhyRChUqSLJkycTLy0vGjBlj9qIBAAAASODsGrYeP34shQoVkm+//fal88eMGSOTJ0+W6dOny+7du8XJyUn8/Pzk2bNnRpkPPvhAjh8/LoGBgbJq1SrZvn27dOrUyZgfHBwsvr6+kiVLFtm/f798/fXXMnToUJkxY4bpywcAAAAg4bLrM1s1atSQGjVqvHSeqsrEiRNl8ODBUq9ePRER+fHHHyV9+vSyYsUKadasmZw8eVLWrVsne/fuleLFi4uIyDfffCM1a9aUsWPHiqenp8yfP19CQkJk1qxZ4uDgIN7e3nLo0CEZP368TSiL6vnz5/L8+XPjdXBwcCwvOQAAAID47p19ZuvChQty8+ZNqV69ujHN1dVVSpUqJTt37hQRkZ07d4qbm5sRtEREqlevLokSJZLdu3cbZSpWrCgODg5GGT8/Pzl16pTcv3//pb971KhR4urqavx4eXmZsYgAAAAA4rF3NmzdvHlTRETSp09vMz19+vTGvJs3b4q7u7vN/CRJkkjq1KltyrzsM6L+jhcNGDBAgoKCjJ8rV6789wUCAAAAkKDQ9ftLODo6iqOjo72rAQAAACAOe2fvbHl4eIiIyK1bt2ym37p1y5jn4eEht2/ftpkfFhYm9+7dsynzss+I+jsAAAAAILa9s2ErW7Zs4uHhIZs2bTKmBQcHy+7du6VMmTIiIlKmTBl58OCB7N+/3yizefNmiYiIkFKlShlltm/fLqGhoUaZwMBAyZMnj6RKleotLQ0AAACAhMauYevRo0dy6NAhOXTokIhEdopx6NAhuXz5slgsFvnkk09kxIgR8ttvv8nRo0elVatW4unpKfXr1xcRkXz58om/v7907NhR9uzZI3/++ad07dpVmjVrJp6eniIi0qJFC3FwcJD27dvL8ePHZdGiRTJp0iTp1auXnZYaAAAAQEJg12e29u3bJ1WqVDFeWwNQ69atZc6cOdK3b195/PixdOrUSR48eCDly5eXdevWSbJkyYz3zJ8/X7p27SrVqlWTRIkSSaNGjWTy5MnGfFdXV9mwYYMEBARIsWLFJG3atPL555+/stt3AAAAQERk9MG/7V2FV+pfJK29q4DXYNewVblyZVHVV863WCzyxRdfyBdffPHKMqlTp5YFCxb84+8pWLCg/P777zGuJwAAAAC8qXf2mS0AAAAAiMsIWwAAAABgAsIWAAAAAJiAsAUAAAAAJiBsAQAAAIAJCFsAAAAAYAK7dv0OAAAAIP5gbDJb3NkCAAAAABMQtgAAAADABIQtAAAAADABYQsAAAAATEDYAgAAAAATELYAAAAAwASELQAAAAAwAWELAAAAAExA2AIAAAAAExC2AAAAAMAEhC0AAAAAMAFhCwAAAABMQNgCAAAAABMQtgAAAADABIQtAAAAADABYQsAAAAATEDYAgAAAAATELYAAAAAwASELQAAAAAwAWELAAAAAExA2AIAAAAAExC2AAAAAMAEhC0AAAAAMAFhCwAAAABMQNgCAAAAABMQtgAAAADABIQtAAAAADABYQsAAAAATEDYAgAAAAATELYAAAAAwASELQAAAAAwAWELAAAAAExA2AIAAAAAExC2AAAAAMAEhC0AAAAAMAFhCwAAAABMQNgCAAAAABMQtgAAAADABIQtAAAAADABYQsAAAAATEDYAgAAAAATELYAAAAAwASELQAAAAAwAWELAAAAAExA2AIAAAAAExC2AAAAAMAEhC0AAAAAMAFhCwAAAABMQNgCAAAAABMQtgAAAADABIQtAAAAADABYQsAAAAATEDYAgAAAAATELYAAAAAwASELQAAAAAwAWELAAAAAExA2AIAAAAAExC2AAAAAMAEhC0AAAAAMAFhCwAAAABMQNgCAAAAABMQtgAAAADABIQtAAAAADABYQsAAAAATEDYAgAAAAATELYAAAAAwASELQAAAAAwAWELAAAAAExA2AIAAAAAE7zTYWvo0KFisVhsfvLmzWvMf/bsmQQEBEiaNGkkZcqU0qhRI7l165bNZ1y+fFlq1aolKVKkEHd3d+nTp4+EhYW97UUBAAAAkMAksXcF/o23t7ds3LjReJ0kyf+q3LNnT1m9erUsXrxYXF1dpWvXrtKwYUP5888/RUQkPDxcatWqJR4eHrJjxw65ceOGtGrVSpImTSpffvnlW18WAAAAAAnHOx+2kiRJIh4eHtGmBwUFyQ8//CALFiyQqlWriojI7NmzJV++fLJr1y4pXbq0bNiwQU6cOCEbN26U9OnTS+HChWX48OHSr18/GTp0qDg4OLztxQEAAACQQLzTzQhFRM6cOSOenp6SPXt2+eCDD+Ty5csiIrJ//34JDQ2V6tWrG2Xz5s0rmTNnlp07d4qIyM6dO6VAgQKSPn16o4yfn58EBwfL8ePHX/k7nz9/LsHBwTY/AAAAAPAm3umwVapUKZkzZ46sW7dOpk2bJhcuXJAKFSrIw4cP5ebNm+Lg4CBubm4270mfPr3cvHlTRERu3rxpE7Ss863zXmXUqFHi6upq/Hh5ecXuggEAAACI997pZoQ1atQw/l+wYEEpVaqUZMmSRX755RdJnjy5ab93wIAB0qtXL+N1cHAwgQsAAADAG3mn72y9yM3NTXLnzi1nz54VDw8PCQkJkQcPHtiUuXXrlvGMl4eHR7TeCa2vX/YcmJWjo6O4uLjY/AAAAADAm4hTYevRo0dy7tw5yZAhgxQrVkySJk0qmzZtMuafOnVKLl++LGXKlBERkTJlysjRo0fl9u3bRpnAwEBxcXGR/Pnzv/X6AwAAAEg43ulmhL1795Y6depIlixZ5Pr16zJkyBBJnDixNG/eXFxdXaV9+/bSq1cvSZ06tbi4uEi3bt2kTJkyUrp0aRER8fX1lfz580vLli1lzJgxcvPmTRk8eLAEBASIo6OjnZcOAAAAQHz2Toetq1evSvPmzeXu3buSLl06KV++vOzatUvSpUsnIiITJkyQRIkSSaNGjeT58+fi5+cnU6dONd6fOHFiWbVqlXTp0kXKlCkjTk5O0rp1a/niiy/stUgAAAAAEoh3Omz9/PPP/zg/WbJk8u2338q33377yjJZsmSRNWvWxHbVAAAAAOAfxalntgAAAAAgriBsAQAAAIAJCFsAAAAAYALCFgAAAACYgLAFAAAAACYgbAEAAACACQhbAAAAAGACwhYAAAAAmICwBQAAAAAmIGwBAAAAgAkIWwAAAABgAsIWAAAAAJiAsAUAAAAAJiBsAQAAAIAJCFsAAAAAYALCFgAAAACYgLAFAAAAACYgbAEAAACACQhbAAAAAGACwhYAAAAAmICwBQAAAAAmIGwBAAAAgAkIWwAAAABgAsIWAAAAAJiAsAUAAAAAJiBsAQAAAIAJCFsAAAAAYALCFgAAAACYgLAFAAAAACYgbAEAAACACQhbAAAAAGACwhYAAAAAmICwBQAAAAAmIGwBAAAAgAkIWwAAAABgAsIWAAAAAJiAsAUAAAAAJiBsAQAAAIAJCFsAAAAAYALCFgAAAACYgLAFAAAAACYgbAEAAACACQhbAAAAAGACwhYAAAAAmICwBQAAAAAmIGwBAAAAgAkIWwAAAABgAsIWAAAAAJiAsAUAAAAAJiBsAQAAAIAJCFsAAAAAYALCFgAAAACYgLAFAAAAACYgbAEAAACACQhbAAAAAGACwhYAAAAAmICwBQAAAAAmIGwBAAAAgAkIWwAAAABgAsIWAAAAAJiAsAUAAAAAJiBsAQAAAIAJCFsAAAAAYALCFgAAAACYgLAFAAAAACYgbAEAAACACQhbAAAAAGACwhYAAAAAmICwBQAAAAAmIGwBAAAAgAkIWwAAAABgAsIWAAAAAJiAsAUAAAAAJiBsAQAAAIAJCFsAAAAAYALCFgAAAACYgLAFAAAAACZIUGHr22+/laxZs0qyZMmkVKlSsmfPHntXCQAAAEA8lWDC1qJFi6RXr14yZMgQOXDggBQqVEj8/Pzk9u3b9q4aAAAAgHgoib0r8LaMHz9eOnbsKG3bthURkenTp8vq1atl1qxZ0r9/f5uyz58/l+fPnxuvg4KCREQkODg41urz7NHDWPus2BYc7GDvKrwU6yxmWG9vjnUWM6y3N8c6ixnW25tjncUM6+3NJYR1Zs0EqvqvZS36OqXiuJCQEEmRIoUsWbJE6tevb0xv3bq1PHjwQH799Veb8kOHDpVhw4a95VoCAAAAiCuuXLkimTJl+scyCeLO1t9//y3h4eGSPn16m+np06eXv/76K1r5AQMGSK9evYzXERERcu/ePUmTJo1YLBbT6/smgoODxcvLS65cuSIuLi72rk6cwXp7c6yzmGG9vTnWWcyw3t4c6yxmWG9vjnUWM+/qelNVefjwoXh6ev5r2QQRtt6Uo6OjODo62kxzc3OzT2Vek4uLyzu1EcYVrLc3xzqLGdbbm2OdxQzr7c2xzmKG9fbmWGcx8y6uN1dX19cqlyA6yEibNq0kTpxYbt26ZTP91q1b4uHhYadaAQAAAIjPEkTYcnBwkGLFismmTZuMaREREbJp0yYpU6aMHWsGAAAAIL5KMM0Ie/XqJa1bt5bixYtLyZIlZeLEifL48WOjd8K4ytHRUYYMGRKt2SP+GevtzbHOYob19uZYZzHDentzrLOYYb29OdZZzMSH9ZYgeiO0mjJlinz99ddy8+ZNKVy4sEyePFlKlSpl72oBAAAAiIcSVNgCAAAAgLclQTyzBQAAAABvG2ELAAAAAExA2AIAAAAAExC2AAAAAMAEhC3gHUA/NQAAAPEPYQsvxcn/2xMRESEWi0VEREJDQ0WE9Q+8Kb4z9rF69Wr57bff7F2NOC0iIsLeVUA8xr7R/ghbeCmLxSLr16+XtWvX2rsq8VpERIQkShT5NRw3bpz06NFDHj9+bISv+Crqzj+hHwgS+vLH1KFDhyQsLExERCZMmCD79++3c40Snt27d0uLFi3k3r17BIYYinoM+OWXX+TIkSN2rpH9HTp0yNieJk6cKAcOHLBzjeKuqBdz//rrL7l//76da5QwEbYgIiLHjh0z/h8RESFBQUEyYMAADqAmsx5k+/btKxMmTJD8+fPL7du3jfnx8UQ8PDzc2Pk/efJELBZLvFzOV7Eu6+PHjyU0NFTCw8PtXKO45+jRo9K2bVv57LPPpHv37vLpp5+Ks7OzvauVoFy4cEFWrVolPXv2lDZt2hj7Mrw+VTXW24ABA6Rfv36ycuVKefToUYLaJ0Z1+PBhadu2rXz++efSo0cP6dWrl6RMmdLe1YqTogb5zz77TD7++GPZvXu3PH/+3M41sy97nNcmeeu/Ee+crVu3StWqVWX27NnSunVrSZQokbi6usrz588lSZIkoqrx/k6LPS1cuFDmzZsnv/32m5QoUUJERMLCwuThw4eSKlUqO9cudoWHh0vixIlFRKRr167y7NkzmTBhQoI5UbZ+l9asWSM//PCDnD17VqpXry516tSRypUr27t6cUauXLmkUaNGMmXKFHn06JHs3r1b8uTJI2FhYZIkCYc1s50/f16aNWsm165dky5duoiIcJyIAev6GjlypMycOVPWrVsnBQoUEEdHRzvX7O07duyY+Pj4SO7cuaVBgwYydepUefz4sezdu1dy587NdzsGrEFr0KBB8sMPP8iMGTOkVKlSCWr7mj17thw6dEjCw8OlcOHC0qFDB7tcGOJSFKRy5crSt29f6dy5s8ybN09ExGie4+bmxgHUZKdPn5ayZctKiRIl5OjRozJp0iQpVKiQeHt7y7fffmvv6sUqa9CqX7++/PHHH1KjRg15+vSpMT++X821WCzy22+/SePGjcXHx0dat24t58+fl27dutFk9zVYr0gmS5ZMMmXKJIkTJ5asWbPK8uXL5enTp5IkSRLuFL4F2bNnl/r164uIyIYNG+TSpUscJ2Lo3r17sn37dpkyZYoUL15cbt26JRs3bpRmzZrJuHHj5Nq1a/auoukGDRokw4cPl7CwMEmePLnkzp1bwsPDJUuWLLJixQp59uwZ3+0Y2rt3ryxcuFCWLFkidevWFQcHBzl//rwsWbIk3je97tu3rwwcOFCSJEkiERER0r9/fwkICLBLXbhMkIAtXLhQChUqJPnz55fRo0dLokSJpF27dhISEiINGjQQVRU3N7do7+MKZsxZ113UdZg1a1YZNmyYBAQEyJYtW6RAgQLSqVMnuX37tvTu3VsaNGggnp6edq557Jk4caKcOnVKNm/eLBkyZBARkZs3b0pYWJhkyJDBCGTxwePHj8XJycl4ffLkSRk8eLBMmjRJOnbsKA8ePJCvvvpKUqdOLb169RIRkRo1atiruu+0qE2uAgIC5ODBg7Jt2zZZtGiRrFy5UkJCQmTEiBGSLFkym/ewr/rvou63RCIvGgwcOFCcnJzku+++k0mTJknPnj3Fy8vLzjWNe1KkSCFXrlyRdevWiaenp0ycOFGuX78uadOmlX79+smjR49kyJAh9q6mqRo1aiQFCxaUJEmSyK1bt6RevXpStGhRWbhwoaxZs0aeP38uw4cPt7kjw3f75aI2HRQRSZIkibi4uEiiRIlk3759Mm/ePFm3bp2EhYWJxWKRH374QSpVqmTHGptj8+bNsnTpUlm+fLmULl1afvnlF5k7d64ULVrUptxb244UCU54eLg+ePBALRaLVqlSRU+dOmXMGzhwoDo4OOi3336rBQoU0AoVKujAgQO1X79+GhAQoD169NCpU6dqRESEHZcgbgoPDzf+f/XqVb19+7bev39fVVXHjRun5cuX12nTpumZM2dUVfXUqVNapkwZvXDhgh1qa54ePXpo06ZNVVV148aNOmDAAE2fPr26urrquHHj7Fy72DN16lT18fHRa9euGdPOnTunHTp00AcPHujly5c1Z86c2rlzZ92xY4fmz59f8+TJo8uXL7dfpeOACxcuaJEiRXTLli2qqvro0SP9/PPPtVSpUtq3b18NCQlRVdVPP/1UDx06ZMeaxg/Wff3GjRu1ffv22rBhQ+3Zs6c+fvxYVVXHjBmjRYoU0V69eunly5ftWdV3XtRjgOr/1u2CBQs0e/bs6uTkpP369dNNmzapauQ23LRp02jvi69++eUXzZw5s/7++++qqvrgwQMdOHCglipVSvv3769hYWGqqtq7d289cuSIPav6zrt+/bqqqp49e1bz5cunZcqUUUdHR+3cubMuXbpUjx49qoUKFdKffvrJzjU1x9y5c7VMmTKqqrp06VJ1dnbW6dOnq6rqw4cPdePGjW+1PoStBOjRo0eqqnr+/Hn18PDQ9957T//66y9j/oABA9RisWiOHDm0VatW2qlTJ23ZsqU2bNhQW7ZsqYcPH7ZX1eOsqOF0+PDhWrp0afX29lYfHx/dunWrqqo+f/7cKPv8+XOtUaOGvvfee3E62L7sJGHOnDmaJEkSrVWrlmbPnl3bt2+vK1eu1C+++EKdnZ311q1bdqhp7Dtz5oxmyZJFK1WqZBO4bt++raqqHTt21ObNmxsnrU2aNFEPDw8tW7asBgcHx+m/u1nGjh2rDRo00LZt22pISIhx8vX48WMdMmSIlixZUt977z319fVVd3d3DQ0NtXON44fly5ers7OzdunSRb/99lt1c3PTSpUq6d9//62qqqNHj9YSJUroRx99pFevXrVzbd9NUfeFs2fP1m7dummHDh10yZIlqhoZLM6dO2eUiYiI0CpVqmifPn3eel3fFus6se7r1q5dq/Xq1dNixYrp9u3bVVU1ODhYBw0apCVKlFA/Pz/18/Pju/0SUbevdevWqcVi0f3796uq6vHjx3X+/Pm6ceNG4zwjPDxcixUrpvPmzbNLfc22cuVKbd68uS5cuFBTpkxpBC3VyPXTrVu3t7qvImwlMF988YV+9913+uzZM1WNvEqcJk2aaIHryy+/1ESJEunChQvtVdV46fPPP9e0adPqb7/9psePH9dy5cppmjRpjCvCT5480fnz52ulSpW0SJEixlX6uHhl03oirKp64sQJvXPnjj59+lTDwsJ09uzZ2qRJE12/fr3euHFDVVV///13rVSpkvE6LrP+vS5duqS5c+fWihUr6pUrV4z5z54901KlSungwYON8p06ddLJkyfrnTt37FLnd1HU7f7Ro0c6YMAAdXV11fLlyxvTrScPT5480ZkzZ2q7du20devWxncn6naIN3fjxg0tXLiwjh8/XlUjQ0GGDBm0a9euNhcEBg8erBUrVow3F0vM0qdPH82UKZN26tRJ+/fvrxaLRUeMGGHMf/TokW7dulVr1KihBQsWTBChYtWqVcb/N2/erI0aNdLChQsbgevhw4c6ffp0bd26tbZq1Yrv9gui7id/+OEHHTVqlFosFvX09NQ9e/ao6v/W1dOnT/XGjRvq7++vxYoVi1frcMGCBcbFzAMHDqibm5taLBadMmWKUebJkyfq7++vbdq0easXNAlbCUzPnj31+PHjqhq50alG3uF6WeDq37+/pkiRwqbZIFfbY+7u3btaqVIl/e2331RVdcWKFZoqVSqdOnWqqkau2/v37+vkyZO1W7duxkE2Lh5so24nLVq00Bw5cmj27Nm1Z8+eevHiRVX933KFhITotWvX1MfHR9u0aWOX+samiIgIY/lPnz6tS5YsUYvFonXr1jWupIWGhmrbtm21YsWKOm/ePO3du7d6eXnZBDL8j/Vu/NWrV3XkyJFqsVj066+/NuZbT75eFBe/O++CqN/fy5cva8GCBfXp06d6+fJl9fT01E6dOhnz169fb/zfeqcL/xP1RHjjxo2aOXNm3bFjh6r+7w7ErFmzjDIbNmzQZs2aaY0aNRJEqDhx4oRaLBZt1aqVMW3Tpk3RAteL64DvdnT9+vVTT09PnTZtmg4aNEjLlCmjLi4uunfvXlWNvDA1cuRIrVixopYtWzZebV8HDx7U/Pnza506dfTu3buqGnlH3mKxaM+ePXXFihUaGBio1atXt7mI8bbOaQlbCcSLG9SWLVv0m2++Ma5Cvipw9ejRQ9OlS6dBQUFvtb5xXaNGjXTIkCE2086dO6eurq5648YN3bBhg6ZMmVKnTZumqpHNoL788ku9d++ezUEkLu4Eo55cTJgwQb29vXXr1q3av39/rVy5stasWdN4Lu3mzZs6ZcoU9fb21vr16xvviw+hfunSpZoqVSrt2bOnVqlSRVOnTq0VKlQwmhSuX79e69atq5kyZVIfHx+jyQds/fDDD+rp6Wk8g3Dz5k0dMmSIOjk56cSJE41yL35X4sM29LZYv7NPnz41plmfFb17967mzZtXZ8yYodmzZ9ePPvrIOEk7e/asVq5cWTdv3vzW6/yu++qrr4z/W9fvvHnz1N/fX1VVlyxZoilTptTvvvtOVSPvGB49elRVVY8cOWK8J76Fihe/l0+fPtUFCxaoq6urtm3b1pi+adMmbdy4sRYrVsx4hu1Vn4HIc7gcOXLo4sWLjWnnzp3TBg0aqJubmx44cEBVVU+ePKlTp0419pfxYfsaM2aMtmjRQnPlyqVJkiTR2rVrG3e4fvrpJ82XL5+mT59eS5curfXq1bNLyCRsJVCdO3fWdOnS6dSpU42NMmrgitpphnU+Xk9oaKiOGDFCkyRJomPHjrWZ17hxY23Xrp06OTnpzJkzjennzp3T6tWr68qVK992dU0zd+5c7dy5s80yLVy4UKtWrao1a9bU8+fP6+PHj3X69Ok6evRoo0xcbDL5omvXrqmXl5eOGTNGVSOvKO7fv1+zZ8+u5cuX15s3b6qq6r179/TKlSs0HfwH586d04IFC2qhQoWMwHXjxg0dNmyYuri46OTJk+1cw/jh4sWL2qVLF718+bIuXbpULRaLnjx5UkNCQrRLly7q4uKitWrVsnnPgAEDtHjx4jbPJEL16NGjarFYtEGDBjbTV6xYoVWqVNEffvhBnZ2djYttqqq//vqrNm3a1KYZZnzYF76OZ8+e6cKFC9XJyckmcG3evFmrVKmirVu3tl/l4ogTJ05osmTJjGfAVSND6bFjxzRTpkyaIUMGPXjwoKr+L2TExYu5L/rqq680ZcqUunbtWj1w4IAOGzZMixYtqjVq1DCOqzdu3NCLFy/qjRs3jKD+tkMmYSsBCwgI0OzZs+uUKVNsApeHh4eWLFnSuPuAN/fs2TOdNGmSJkqUyGjuFBERoX369FEnJyeb5nIPHz7UGjVqaPXq1ePFzk9Vdc2aNZo3b15NnTq1TTMj1cjAVb16da1Vq5aePXvWZl58Obm4ePGiZsmSRf/44w+b6Xv27FFXV1dt0KABPbe9xKt6a7t48aIWLVpUvb29bQLXF198oRaLRX/55Ze3Xtf4ZtmyZZovXz6tUqWKJkuWzObB+R07dmj58uW1cuXKOn36dF22bJkGBASoi4sLPT6+REREhG7ZskU9PDxs7tjv379fS5UqpY6Ojvrll18a0588eaK1atXStm3bxtu7NlGXa8KECdqzZ0+b+dbA5eDgoAEBAcb0ffv2xZvjQmyJui6j/r9ixYrarl07o9m1amQT65o1a2q2bNk0VapUeunSpWjvi4siIiL00aNH6u/vr0OHDjWmW58Jz5Url9arV0/v3bsX7b322J4IWwmA9Ut1+fJlvXbtmj548MCY17lz52iB6+zZs5ojRw7jS4mYefbsmU6cOFETJUpkNCkJDQ3Vxo0bq7e3t9asWVM//vhjLVeunBYsWDBOd4bxsh335MmTNUeOHFqjRo1onV78/PPPWqBAgWh3/uKLZ8+eaYYMGaI1JX348KGWLFlSLRaL1qhRI96E69g2f/78aD2VXbx4UYsUKaIFChQwAtfVq1d11qxZ8aIpzLvgs88+U4vFouXKldPTp0/bzNu8ebN27NhR06VLp0WKFFFfX1+63/4XmzdvVnd3d5vANWnSJM2QIYMGBATo6tWrde3aterr62uX50jelqjHtEOHDulXX32lzs7OOmzYMJtyz54903bt2qnFYtFmzZq98jMSshfXg/UYEh4erqNHj9bSpUvriBEjjHKPHz/Whg0b6sqVK7V8+fLatWtXDQsLizfbmL+/vzZv3jza9FatWqnFYrEJXPZcZsJWArFkyRLNlSuXuru7a6tWrXTFihXGPGvgmjp1qtG8iZOXN/eyg8Hjx491woQJarFYdNSoUaoauW6/+eYbbdmypX744Yc6bNiwON0ZRlQ9e/a0adY1ceJELVOmjLZr1y5aL2W7du1629Uzxat24CNGjNACBQroDz/8YDO9S5cuGhgYaNPNM/7n2rVr6uTkpBUrVozWMc/Ro0c1TZo0WrVq1WidicT17449Wdfd119/rX379tVSpUppy5Ytoz1HGB4ernfv3tVHjx4ZQxbgf17cF4SFhenmzZs1Xbp0WqdOHWP6V199pb6+vpo0aVItX7683Z4jMVtERITNcbFv37764Ycf6tGjR3XixInq5uYW7YLUqFGjtHbt2lqjRg0C1guiro9p06Zp69attUGDBvrjjz+qamRz9V69emmxYsW0XLlyOmjQIC1ZsqSWLFlSw8PDtX79+tq4cWN7VT9WWbetwYMHa8mSJXXHjh02352JEydq3bp11dfXV/v27Wv37xVhKwE4f/685syZU6dNm6bTp0/XGjVqaKVKlYwvqKpq165d1c3NTWfOnKnh4eHx5qrH2xJ1J3j69GmjbbR1PY4bN84mcL2MvXcG/9Xt27e1Xbt2mjFjRpuAMW7cOC1btqy2b9/+pd1Cx+VtzVr3wMBA7dWrl9apU0fnzJmjp0+f1nv37mmHDh00f/782rdvX/3tt9+0W7du6u7ubtyZge3f33rCuXPnTs2WLZtWrVrVZv79+/e1bNmyarFYtEWLFm+9rgnF/PnztXjx4tqyZUvjwXpVpROXfxB1/x0WFmYT/jdv3qxp06bV2rVrG9OCg4P19OnTev/+fbs9R2Ima6/HVvv379fChQvrzp07VTXyedXx48drqlSpjMAVHBysTZs21e+//954H4Erun79+mnGjBm1S5cuxrio1ueeQ0JCdPHixfrhhx/qe++9p23atDGG+mnSpIn27NkzTt/Zunz5st65c8d4Huvvv//W/Pnza8WKFTUwMNC4ENSgQQOdOHGifvLJJ1qgQAG7d/JG2Iqnon6RLl26pK1atTJ2WgcOHNBmzZpp+fLlbdrl9+rVi+e03tCgQYNsrrD37dtXM2bMqC4uLpo3b14dMWKEETDGjRuniRMntumyOi57WTg8e/as9urVSzNmzGhzwBw/fryWK1dOGzRoYPedXmxbtmyZJkuWTFu1aqXvvfeeFihQQCtUqKD79+/X+/fv69ixYzVz5syaN29e9fb2NoI4bE+kRo4cqSNGjDC2j127dqmXl5dWrVrV2NaeP3+ubdu21cOHD3MS9h9ZjxF79uzRGTNm6DfffGOzbc6fP19LlCihLVu21A0bNuiwYcPUwcHB6FYZkU6ePGnzevTo0dq4cWMtVaqUzpw505hvDVx169Z96efEp+25ePHiWrlyZWOZRo0apW3bttU2bdrYHDfu3r2r33zzjSZLlkxz5MihuXPn1gIFCsTb5pSxYf78+ZotWzbdvXu3qkb2amuxWNRisUQbADvq8Cp9+/bVNGnS2PQ2HdcMHz5cS5UqpdmzZ9fatWvrhg0bVFX11q1bWrx4cS1UqJBmy5ZNCxYsqLly5VLVyMGNc+XKZffx/whb8ZB1B7Vhwwbt1KmTfvzxx9F6RTpw4IA2bdpUK1eubNMrHl7frVu3NGXKlFqhQgW9deuWLlq0SDNmzKgrVqzQI0eO6CeffKKlS5fWjz/+2Bh/ZvLkyWqxWHT+/Pl2rn3sefG5jbNnz2rPnj3V09NTZ8+ebUwfNmyYfvHFF2+5dua6ceOGFilSRCdNmmRM27hxozZv3lwrVaqk58+fV9XIg97t27dtnpdM6KKeXF69elXr16+vKVKk0MmTJxsPeO/atUuzZcumPj4+OmDAAK1QoYKWLl3aeG9cvxtsL9ZjhHV4Al9fX82WLZtWr17dphnwzz//rBUrVtScOXNqlixZjAFSEWnMmDFqsVj0zz//VNXIfVyqVKm0d+/e2qxZM82RI4c2atTIaDK9efNmzZAhg1asWNGe1TbVxIkTNWfOnMbr0NBQ/frrr9VisWjevHmj9VwZFhamx44d02HDhunkyZONgMB3O7qQkBCdPn26MTbnqlWr1NXVVb///nv9/vvvjTtc1jFUVSOPxx06dNA8efLY3KWOawYPHqzp0qXTpUuX6po1a9Tf31/TpElj9Hb84MEDXbFihY4ePVqnTZtmbEcdO3bUatWq2XQaYg+ErXhq/fr1mjhxYvX399fs2bNr4sSJjfE8rA4ePKg1a9bUGjVqaFBQEFeRYuD8+fOaO3durVatmk6cODHaXatx48apj4+PLliwQFUjB2f95Zdf4k1zkRkzZmi6dOl0zZo1NtNPnz6tLVq00LRp0+rPP/8c7X3xZVu7dOmSenp66pIlS2ymBwYGat68eXXp0qV2qlnc0atXLy1cuLC2adNGCxcubNz9tR4cr127pvXq1VN/f399//3343RHMu+S7du3q4eHh86YMUNVI+9wOTk5aYECBWyGYjhx4oTu37/fGJAb/xMSEqKNGzdWd3d3/eOPP7RTp066ceNGY/6KFSvU19dXW7Roobdu3dLw8HBdu3at1qpVK95uvz/++KPmz59fz507p5999pl2795dVf93oXHkyJE2rRteth7iy/Hxv3rxmVXVyAtT58+f12vXrmnBggV13Lhxqhr5PKuzs7NaLBYjjFnt3r072jOuccmmTZu0aNGixkWNtWvXqrOzs5YuXVpdXV117dq10d6zd+9e7dGjh6ZOnVoPHz78tqscDWErHrp06ZL+9NNPxhfu+PHj+vHHH2u+fPlsmnapqh4+fJiD6H90/vx5zZs3r1osFv3oo4+iza9Zs6ZWrVo12vT4cEDZvn27tmzZUgsUKKCrV6+2mffjjz9q4sSJ1WKx2Ax6GpeDlrXuBw8e1MuXL+vdu3e1SJEiOmXKFFW1PXEoVaqUzZgxiG758uXq4uKi+/fvN0LUsGHD1GKx6Ndff6337983ylqfO1CNH98de7E+WP7ll19qly5dVDVyH5Y9e3Zt1qyZtmjRQrNkyWJztxavFhISog0aNFBnZ2fNmDGjzThHqqqLFy/W1KlTG3cFo+7/4mPg2rVrl/r5+am3t7c6ODgYd/dVI5sTWiwWnTBhgj58+NCOtXz3PX/+3Pi/tUVE1P3e3r17NX/+/MazcWfPntVu3brp+vXr410zzOPHj2v//v1VVXXdunXq7u6u06dP17/++kvz5MmjqVKlsun0TVV11qxZWrJkyXciaKkStuKdM2fOqLOzs2bIkMHmjsLJkye1a9eumidPHp01a5Ydaxi/WHdmFy5c0KJFi2ru3LltBoRWjTzAVKtWzeZkMa6JiIh45Qnu/v37tUWLFurt7a2rVq0ypq9bt047duwYbwZqtv6tly9frp6enjp48GBV/d8A4Tt27LApW6tWLR0xYoRd6hpXzJ07VwsWLKjBwcE2J54DBw5UR0dH/eabb6I9IxRfTiDsxTrEx40bN/TQoUP6+PFjLVu2rHFh4MyZM5o6dWrNnDmzcdUc/+z58+faqVMntVgsOnPmTI2IiLDZTnPmzPmPnSPFN/7+/uro6KjvvfdetI4yRo4cqYkTJ9ZJkybFu+d3Y8Pq1av16dOnxuuRI0dqpUqVtGLFihoQEGB0rrR7927jLtaBAwe0Vq1aWrNmTeN98eGC1IULF4yLcNbAWb9+fSN4qarWq1dPc+TIoX5+fqpqe3x4l5rtE7bimWvXrumgQYPUxcUl2hgWf/31l37yySeaLl06m44x8Pr+6UqktdfH0qVL6/79+/XBgwf66NEjLVu2rL7//vtvsZax52UBcfjw4dqzZ0/t1q2bcSA9fvy4fvDBB5otWzadPHmybt26VYsUKWLzjFZ8uIq7atUqTZ48uc6cOdOmWcb777+v7u7uOnr0aP3hhx+0V69e6uLiEu3hedj66aef1NHR0Rhywrq9HTlyRJMlS6ZOTk7GM6XxYfuxt6NHj2qtWrX02LFjxrQdO3aot7e38V0+evSo+vr66qeffspYiy/xqu3w6dOn2rRpU02VKpVu3LjRKHf37l3NlStXgng22toLY7NmzXTs2LFatWpVm2fWrEaPHq0Wi+WlTcwTMuvYlN98842qqk6dOlVdXFz066+/1o8++kjLlSunGTJkMO4WDh8+XC0Wi+bMmVOLFStmBJP4cEFq2LBh2rRpU92wYYOxPH///bdmzZrVeK70wYMH+v777+vq1atfOdDzu4KwFQ9dv35dBw0apA4ODtHa7h4/flz79u2rZ8+etVPt4q6oB9nvv/9ee/furR9++KEePHjQmGd9hitVqlRasmRJbdKkSZzdCYaHh2ulSpW0WrVqxrS6deuql5eXNmrUSHPmzKk5c+bUSZMmaUhIiJ46dUr79OmjDg4OmjdvXm3YsKHxvri03K/y9OlTff/993XgwIGqGjmG2unTp3Xs2LG6bt06rVevnlapUkVz5syplSpVotfBKF51ghoWFqblypXT8uXLG135qkY+89e3b1/t37+/pkiRItoAu4iZzZs3a+7cuW1aN/z555+aOXNmYyiQzz//XJs3b27ThBORom7HO3bs0K1bt+q+ffuMaaGhodqwYUN1dnbWrl276vjx47V27drq4+MTL+40vEzUdfLifn7JkiVasWJFbdSokdF7ntW8efPi7TqJqeDgYG3Tpo2WLl1aJ06cqK1bt7Z5Hvivv/5Sf39/zZEjh3HH/9ixY7pv3z7j7xAf1mm/fv00bdq0unz58mi9CLZs2VJz5cqlY8aM0UqVKmnp0qVtBnZ+VxG24qkbN27oZ599ps7OztECl/XEHzHTr18/9fT01A8++EAbNWqkLi4uOm/ePA0ODlbVyMBVpkwZtVgsun///ji9E1y1apVmzJhR33//fb169arWrFnTZoyojz/+WAsVKqQ//fSTMe38+fM2TUfe5R3gm3jy5IkWL15cu3Xrpnfv3tWuXbtqxYoVNUOGDJolSxYdN26c3rt3T2/fvk3zmCii/v1//PFH7d+/v37++edGG/vt27drmTJltFChQrplyxbduHGj+vv7a/369fXevXvq6emp3377rb2qH6dFvSJsNXz4cHVycjKujl++fFkbNGigOXLk0Dx58mjq1KnjdK9lZokaJAYOHGgM55AkSRIdNmyY0cteaGiotmzZUi0WizZq1Ei/+eabeNnD3pdffmn8/8WQFfU7v3TpUq1YsaI2btw4WuBSjZvHRTNYt42HDx/qhx9+qOXKlVMvLy/dsmWLUSY8PFz379+vBQsW1Llz50b7jPhwrF2/fr1myZLFuFgZEhKiN27c0I0bN+rTp0/13Llz2rJlSy1cuLA2aNAgznSYRNiKx6yBK3Xq1LS9jyXff/+9enl5GScjf/zxh1osFnV2dtbp06cbgevMmTPauHFjYwfwru8IXmb16tW6d+9e3bBhg7q5uamPj49WrlxZHzx4YHNwbdKkiRYqVOilnxEf7mhFNXfuXE2ePLm6uLhogwYNjANet27dtGrVqpw4/IPevXtrmjRptEmTJurj46N58uTRzp07q2rkc3+1a9dWJycnzZ49u5YtW1ZDQ0P1yZMnmj9/fnp1/A8CAwPV29vb5vnBxo0ba926dY2r42fPntWFCxfq5MmTGWvxX4wcOVIzZMig27dvV1XV/v37q8Vi0R49ehgXop4/f641atSwGVMrPgWt48ePq8VisVm+F/f1UV8vW7ZMq1SpolWrVo32DBf+x3qe8PDhQ+3YsaMmTZpUO3fubNOc/9mzZ+rt7a2fffaZvappqnXr1qmPj49euXJFT5w4oQMHDtQsWbJopkyZ1MfHx+ilNup5SFw47hK24qCXncC+6qT2xo0b2qtXL/Xy8rIZqR6vJ+oBMiIiQseNG2d0lbxixQp1cXHR+fPna69evdTZ2VlnzZoV7aHMuHiQDQoK0sKFCxs79A0bNmiePHnU09PTuK1v7S3p0KFDmjJlygTTbO748ePGYIrWg2NAQIC2atUqTneCYqbAwEDNmDGj/vHHH6oa2Vzm+++/19y5c2vPnj2NcidOnNCrV68a+6kBAwZorly5eHboP1iwYIFaLBZNkyaNli5dWnfs2KHTp0/XBg0a6OLFi+PkhaC3Keox89y5c1q/fn1dtmyZqkaGiFSpUmmnTp00UaJE2qNHD+NZzvDw8Hi7biMiInTbtm3q6empderUMaa/uLxR1938+fP1448/jrfrJLZY18/jx4+1Q4cOWrhwYZshZZ49e6ZFihSxGZ4hPrDefd++fbsWLFhQK1asqGnTptV27drpzJkz9ffff9dMmTJF63ArrmxPhK04xrrz2rVrl06dOlWHDh2q+/fv/8f33Lx50+iBCq8vao9Av/76qz58+FBPnDihV65c0XPnzqmPj49OnDhRVSO7Ak+aNKlaLJZoXZDGVVu3btVMmTLptm3bVDXyhNnd3V3r169vEyC3bNmimTNnjtMj08fUyZMndeDAgerq6qpHjx61d3XeGS9e1Fm8eLFmzZrVprvnoKAgHTt2rBYrVkzPnTunqv87cO7du1e7dOmiqVKloknbG3px3V+9elU7deqkU6dO1c6dO2uDBg20c+fOmiVLFm3evLmdahn33LhxQ8PCwnT+/Pn66NEj3bFjh3p5eRkP6/fs2VOTJEmibdu2tWm2GVdOBmNi27Zt6uHh8dqB61VlYCvqHa7WrVtr9uzZ1d/fXwcOHKgNGzbUPHnyxIm7Oa/ru+++06xZsxo9Oa9atUrHjBmjy5cv13v37qmq6q1bt7Rw4cI2w8jEJYStOGjJkiXq7u6u1atX1/r166vFYtGJEyfq48eP7V21eGP9+vWaM2dOVY0cdDVnzpxGj2mqkYPsFS5cWE+cOKGqqvv27dPBgwfrlClT4sVOMCIiQp89e6Y9evTQwYMHG12/b9iwQdOmTavvvfeezpw5U3/99Vf19va26Qwjodi3b582b95c8+XLp4cOHbJ3dd5J33//vU6ePFk3bdqk2bNnt+keXzXyLmHixImNO4VRp0+aNCnaMAp4Pdu3b9e6desaF9kWLVqk+fLl0xs3buju3bt1xIgR6urqqhaLJUF1Sf4mlixZYlxo6t27t7Zs2VJV1WjG1KdPH23SpIk+efJEVVWHDBmifn5+Wr58+QQTJiIiInTr1q0xClwJ3b9tI9b5jx490o8++khTpEih5cqVi5fPAN69e1dz586tRYsWjdYZUmhoqN6+fVtr166tZcuWjbPLTNiKY44ePaqenp5GN7JBQUFqsVh0yJAh9q1YPHPy5EktWLCgZsyYUV1dXaM9x7B48WJ1cHDQtWvX6smTJ7V27drGwVg1brQhftHLDog///yzZs2a1dgBhoSE6IYNGzR79uxqsVh0+PDhNtteQjqoPnnyRLdv366XL1+2d1XeSc+ePdOaNWtqw4YN9d69e5o3b15t06aNzSCnly9f1kKFCunvv/8e7f1x9aBqbxEREbpp0ybNlSuXent7G72FDhkyRCtVqmSEg9WrV2uFChWMC0b4n6dPn+qHH36oFotFmzZtqk5OTsYFFeug0PXq1dPGjRtrSEiIhoeHa926daN1ZhCfvGp5QkJCdOvWrZo+fXqbwJWQjgX/RWBgoE2nU1FFbVJYv359/fTTT431Gl/2j9ZlvHfvnubPn1+LFCli7JNCQkJ03Lhx6ufnpyVKlDA6w4iLy07Yeodt2LAh2jMgW7ZsUV9fX1WN7IQhU6ZM2qlTJ2O+9UomO7r/7uOPP1aLxaK5cuUydghRv+QtWrRQi8WiWbJk0SJFisTpXh6jLlfUO3iqqq1bt1Y/Pz+jWWVYWJhu3LhREydObNPTZXw7uUDMWfc/+/bt05QpU+qePXt0165dmipVKm3atKlOnz5dt23bpr6+vlqsWLE4efCMC/r27atVq1bVokWL6uzZs7V58+Y6Z84c47vKM4avFh4ertmyZdMkSZIYXeVH3U7nz5+vFotFq1Wrpt7e3urt7W1cZItvx9+o+/b58+fr8OHDtW/fvjYXmqyB6586zYDtujxx4oRaLBYdNGhQtOPui+WfPHli/D8+rNeff/452vnq/fv31dvbW4sVK2YErpUrV+qYMWOM71ZcvJCtSth6Z50+fVotFot27drV6IhAVXXhwoWaN29ePXnypGbNmlU7depkfAHXrl2rTZo0Mdq44s1Yv/DWf3///XdduXKlFitWTL29vY1xZ6I+y7Vjxw7dvHmzcRCOizuCqCcQAQEB2rZtW71w4YIxbc+ePVq/fn2bpl5hYWE2A6MiYXvVwT8oKEjff/997dq1q6pGjvNUs2ZNzZgxoxYoUECrV68ep69W2tMvv/zyymaWUdflzp07tXv37kavqeXLlzeawsWHkzazBAUFaY0aNbRGjRqaPHly465VaGioccxdtGiRdu7cWfv27Rvvmna9TL9+/dTLy0tr1Kih1atX11SpUtnczbN2mlG2bFn7VfIdFvX7NmLECB0/frymSpVKHR0d9dNPP33ls/VRA1p8uKh5584ddXR01OrVqxvPN1rXzZUrVzRdunTq7+8f7RwjLn+3CFvvsGXLlmmKFCm0R48exhXIGzduaPXq1TVFihRGszXrl69v377q5+dndOeL1xd1B/b333/r1atXjS/2qVOntGDBgurt7W107a6qOnv2bJueB+PijiDqcterV0/z58+vgYGBNgMJPn36VJs2bapNmjT5189AwjZ+/HgdO3as0SObquqMGTM0RYoURjAICgrSW7du6fnz5+NU173vioiICL17965aLBatUaOG0bnIi178Xq5evVqLFy+urq6ur2y2lJC9bD8WFham4eHh+sEHH9gELquoHWGoxu/teNq0aZoxY0ajQ67ffvvN6OVy9erVRrkNGzZo7dq1OS78g5EjR2qqVKl0w4YNum7dOh0/frxaLBbt2bNngunM7OjRo5o5c2b19/e3GdA+ODhYy5cvrxaLRVu1amXHGsYuwtY7bsWKFerg4KA9evTQ0NBQjYiI0NGjR2uuXLm0e/fuevPmTT127Jj2799fU6VKRY9oMRD1atPQoUO1SpUq6ubmpq1bt9bp06erauTI7cWKFdNcuXLpmjVrtFq1alqmTJk4eUAJCQmJ1mThm2++0fz589uErGvXrhk9wd24cUMzZsxodHsPvOjJkyfar18/dXV11apVq2q7du307t27+vTpU/3ggw+0c+fONnfpreLid8ierPurEydOaJo0abR27dqvPTbWhQsXXtlcKSGLug3OmjVL+/Tpo507d9YlS5ZoeHi4Pn/+XFu3bq1OTk66fv16ffTokTZu3Ni4Yxvf3b9/XwcPHmyMK/jrr7+qs7OzTp06VT/88ENNmzatBgYGRnsf3+3oQkJCtFq1ajpo0CCb6dYhGvr27RuvL4ZEPd86duyYZsiQwSZwhYWFaefOnfX06dNx8gL2qxC24gBr4LLu2MPDw3XQoEFavHhxTZIkiRYuXFh9fHwSzDhHZvn88881TZo0+ttvv+mff/6p1atXV09PT+NE5sKFC1q1alXNly+fVqtWzWj+FJea4oSGhqqvr692797d5u7DwIEDtVq1aqqqunHjRu3bt696eHho8uTJtU+fPqoaedeibdu2CebKG2LmypUrOmPGDC1atKjmzZtXW7VqpbVq1dJatWoZXb/Hpe/MuyYiIsIIrcePH9eUKVNqq1at6LkxFvTp00fd3d21d+/e2rRpU82ePbt2795dVSObPnXq1EktFosWKlRIc+fOHaef0/0nLwtJO3fu1EuXLunJkyc1d+7cRpf3a9asUYvFohaLJVpvo7AVHh6ujx8/1oIFCxphKzQ01AgVHTt21MSJE+vAgQONpr7xxdSpUzUgIEBr166t27ZtMx7LsHb6VqhQIe3WrZtWrlxZixYt+tLn5OMywtY75lUnIUuXLlUHBwcNCAgwyt25c8foDS/qHQm8ucuXL2uZMmV03bp1qhrZtXuKFCn0hx9+UFXbL/zp06fjdPOnYcOGaZYsWXTw4MF68eJFVY189iBTpkxapkwZzZYtm3bp0kWXLFmis2bN0iRJkuj169f1zz//VB8fH929e7edlwBxxYwZM7RHjx7GydiIESPsXaU4z7rvWbp0qY4YMUILFSqkFotFGzZsqGfPnrVz7eKu9evXa7Zs2Yz925IlSzRZsmT6448/2pT77bff9Mcff4zTz+n+k6hB69tvv9UJEybYzF++fLmWLl1ar169qqqRz2l98sknOnbs2Hi3Lv6rV93ZGzRokKZNm9ZoiWTdloYOHar+/v5qsVj0u+++e2v1NFv//v01ffr0+vHHH2uzZs00Xbp0OnbsWOMO3t27d7VBgwZap04dbdKkiXERIz7dGSVsvUOsB9Ft27bpqFGjNCAgQDds2GBskNbA1bVr13h7Re1teTHU3rhxQ/PmzavXr1/XFStWaMqUKXXatGmqGvnM0uzZs6M9rBmXdgRPnz7VNWvWGK/HjRunGTNmNHpBevjwoS5dulQ7dOigmzdvNm7pb926VcuVK2ccWDdu3KjXrl2zyzIg7njx+7Vnzx5t3bq11qxZU4OCguxUq/hj48aN6ujoqNOmTdOVK1fqTz/9pM7OzlqnTh0CVwzNmTNHy5cvr6qRQ3s4Ozsbx4CHDx/q1q1bo70nvlx1f5nevXurl5eXfvbZZ8b+XzVy7LwkSZLo8ePH9erVq1qnTh3t2LGjMZ/AFSnq+cH27dt1/fr1euXKFY2IiNArV65o7dq1tXDhwkbgevbsmdatW1c3bdqkn332mWbKlEnv3LkT51sBzJkzR7NkyWI8krBnzx61WCyaIUMGHTFihHE+ER4ebrPO4tt2RNh6xyxdulSTJ0+uDRo00Dx58mj+/Pm1Xr16xgF06dKl6uTkpO3bt3/p8w/4dy/beV28eFF9fHz0008/1VSpUum3335rzDt06JDWqVMnzo5crhrZy2DhwoV14cKFxrSxY8eqp6enDhw40HiOw7punj17ppcuXdKCBQvGq4dUYT+7du1SR0dHY6BYxFzv3r2NIUCsDh48qM7OztqoUSOaFP6Llx0D5s2bp82aNdPVq1fbXGxTjWzK36dPn3j9vFvUdTJ//nx1d3fXvXv3RisXGhqqfn5+arFYNHv27FqgQAEu/v6DTz/9VDNmzKgpUqTQ0qVL69SpUzUiIkL379+vdevWVQcHBy1btqzmzp1b8+bNq2FhYTpz5kwtUKBAvBiaYebMmfrNN9+oauRdUVdXV503b54OGjRIHR0ddfTo0Xrp0iWb98T1gPkyhK13yMWLFzV37tw2YxfNmzdP/f39tWHDhkZTwUWLFmn69Onj9Y7fLFG/xD///LN2797duJry5ZdfqsViMZpqqkaO3l6rVi319fWN01cxT5w4obVq1dLq1avr/PnzjenWwDVo0CBjzJTbt2/r1KlTtUCBAtqgQQOjbHzcAeLtsG47pUuXNh6yx5uzrseOHTtq1apVjenWk7LvvvtOLRaL1qlT55W9FCZ0Ufdjy5cvN9bTqVOnNFmyZGqxWHT27NlGmSdPnqi/v7+2bds2Xu4Do/YkaDV48GBt0aKFqv7v7t2LLTkWLVqkv/76a7xtThkT1gGvrbZs2aLFihXTP//8U48dO6Zt2rTRUqVK6ddff60REREaEhKi8+bN0yFDhui4ceOM0BoQEKB+fn7GM65x0bJly/Tq1at6+fJlvX79ul66dEkLFSqk48ePV1XV69evq6urqzo5OUVrqhsfEbbeIYcPH1YPDw/duXOnMS0iIkLnzJmj+fLls5kel7+E9hJ1J7hr1y6tW7euZsqUSYcPH27MCwgIUIvFop06ddK2bdtqlSpV1MfHJ063IbbW+fTp0+rv76/VqlWLFrgyZsyogwcP1mvXrmlQUJB+//33Nm314+Jy491iDQI0c/vvfv31V3VwcNClS5faTF+4cKGWL19evby8bAacRaSo+7EdO3ZokSJFtHnz5saV9aVLl2qKFCn0k08+0Y0bN2pgYKC+9957WrBgwXg5YPG3335r9Kobdd106NBBy5QpY7y2LvPTp09txlu0issXImPLi83rly9frh06dNB+/foZ0x48eKAff/yxlixZUkePHh3tjuDVq1e1a9eu6ubmFqd7lh4wYIB6enrq5MmTjRZYO3fu1Pz58xt3S48cOaJdu3bVKVOmJIjth7D1Dvnrr780T548xgE06s7Py8tLBw8ebK+qxSu9evXSKlWqaL169TRbtmyaKVMm/eyzz4wDyrRp07RJkybavHlzHTp0aJwfuVz1f9vSqVOnXhm4vLy8dNCgQXrjxo2Xvhf4L86ePavHjx+3dzXilKjdvK9Zs0bXrl1rnNR99NFHmitXLl2yZImqRn5P+/fvr+PGjYsXzY9iW9SQNHbsWG3fvr1my5ZNkyVLph9++KERuH7++Wf18vLSTJkyabFixbRu3brxduDtW7duGct0+PBhY/rkyZM1Z86cumHDBpvHFe7cuaPlypXTX3/99a3X9V3WpUsX7du3r6pGbiNBQUFapUoVTZ48udapU8embFBQkAYEBGi5cuW0f//+xvH177//1m+++UarV6+uhw4deuvLEFu++OILTZs2re7Zs8dmXNItW7Zo+vTpde7cubp3716tXbu2Nm/e3Jgf375bLyJsvUXWnX1YWJjx/xevklWuXFkLFy5s0wQkJCREq1atGq96p7GXxYsXa+rUqXXv3r0aGhqqT5480Y8//liLFi2qQ4YMMXZ8T58+tXlfXNwRvFjnqCdu/v7+WrVqVZvANW7cOE2UKJEuXrz4rdYTQHTW7+uSJUs0a9asWqBAAS1fvrxmyJBBjx49qmfPntWuXbtq0qRJtWTJklqyZEl1dnaO0ydqb8Po0aPVxcVFV61apQcOHND+/ftr0aJFtUWLFsbdwFu3bumZM2eMDg1U4/bFtn+zadMmtVgs+v3336tq5LIWK1bMeM73ypUreurUKa1Vq5aWKVMmTh4PzbRs2TIjkN+9e1dVI+90NWvWTHPnzq0zZ860KR8UFKQtWrTQTp062ZwD/v3330aX6HHR3bt3tXr16vrTTz+pauSdum3btmn79u116dKlWqVKFXV3d9fMmTNriRIlEtSzfoStt+jEiROq+r87BRs2bNC2bdvqJ598YtzNevjwoebOnVsLFiyoc+bM0Q0bNmi/fv3Uzc1NT58+bbe6xxcTJ07U/Pnz65MnT4xpd+7c0ebNm2uaNGl02LBhxt8nLjcXiXownDFjhg4fPlwnTJhgNOGKeodrwYIFRtmoPRYCeHtedgFu586d6urqalxo27Ztm1osFv3iiy9UNfKkbePGjdqvXz8dOXKknjx58u1XPI6IiIjQR48eaZUqVXTIkCE28yZPnqzZsmXTli1bRntYXzX+392/ePGi0TmUNRiEhISon5+f+vj4aNKkSbVIkSJaqlSpeHuXLyZePEeYO3eu+vv7619//aWqkWGjfv36WrFiRZvnAFUjnwe3blfxZfu6d++e8Qz4tm3btGnTplqyZEktVqyYZsqUSWfPnq179uzRnTt3Jrhn/Qhbb0lgYKBaLBbjTsLq1avV0dFR69WrpxUqVFA3NzcdN26cqkZ+Cf39/dXb21szZ86sRYsWNbrNRMxYv9jz5s3TfPnyGcHVupM7duyYpk6dWkuUKKFffvml3eoZ2+rWrat58uTREiVKaOHChTVZsmT622+/qarqyZMntWbNmlq9enXjiqZVfNn5A3HFkSNHjP9bv38zZ87Uli1bqqrqpUuX1MvLy6YDn3v37r3dSsYDNWrU0E6dOkWb3rx5c3VyctJWrVrZDPge37xq337t2jXt3bu3pkyZUmfMmKGqkcfNI0eO6LJly/T3339PcCfIb+qbb77RsmXLaosWLYweQa9cuaL169fXSpUq6Zw5c6K9J74da7///ntNlSqVuri4aN++fTUwMFBVI79fbdu2tSmbkAI7YestuXDhgnbr1k1TpUqlCxcu1Dlz5hhdy16/fl1HjRqlFotFx44da7zn0qVLeu7cOeO2NF7fizsw65f6ypUrmi5dOm3VqpU+ePDAmL9v3z5t1KiRduzYUUuVKvXSq5txQdTlnjRpkmbOnFmvX7+uISEheufOHe3WrZsmS5ZM//jjD1WNfE6wRIkSOnr0aHtVGUjwNm/erBaLRWfNmmUzffjw4dqgQQM9f/68enl52TQ7WrlypQ4ePFgfP35sjyq/8151EtujRw/NnTt3tLuAo0aN0vfee0+rVq2qo0aNitMtG14l6jLNmjVLR4wYoQMGDNCzZ89qWFiY3r9/3whcL16As0pIJ8j/5FXb18yZM7VChQratGlTm8DVqFEjzZcv30t7f4xvLl26ZNMSKzw8XKtVq6aDBg2yY63si7D1Fl28eFF79OihLi4umidPHl2+fLkx78GDB0bgenHEdryZqDvBb7/9Vj/66COtUqWKzp07VyMiInTPnj2aIkUKbdasmS5dulT379+v/v7+2q1bN71+/brNHci4JOpyb9iwQT/77DNt1qyZqv7vIBsSEqLNmzfXokWLGm3DGUIAsK/Lly8bzbiiNjdatmyZli1bVj08PLR9+/aqGvldjoiI0K5du2r79u310aNHdqr1uyvqvnDTpk26cuVKoyORsLAwLVq0qBYtWlT37dunDx480OfPn2uDBg30xx9/1M6dO2vu3LmjPbcb10UNWr1791YXFxetXr26Zs6cWbNly6YTJkzQR48e6d27d7VPnz7q5uZmM94k/ifq9rV161bdvn27zaDXs2bN0vLly9sErosXL2r//v0TVFh9+PCh/v7771q7dm0tUKBAgr4jSth6C6I+A/TgwQPt06ePJk2a1BjozboTDAoK0jFjxqjFYrEZUBEx07dvX/X09NS+ffvqF198oRaLRT/55BNVVd27d68WLlxYs2TJol5eXlqqVCl98uSJPnz4UAsUKKCbNm2yc+3fTNQDadOmTdXX11c7dOigOXLkMHZw1u1wzpw5mj17dmPctpd9BoC369KlS8ZdBWvgCg0N1dq1axvNfx8/fqx3797V/v37q7u7u/EcMF6uX79+miVLFi1TpoymSZNGq1atqocOHdL79+9rsWLFNEeOHJo3b14tUKCA5siRQ1UjBzDOly9fvG2ieefOHfXz89O9e/ca+3zroPfW57UuXbqknTt31urVq3NceEHU9dGzZ09Nmzatenp6aqpUqfT999/X27dvq6rqDz/8oBUrVtTmzZtH64U1IQSuiIgI3bJli9auXVv9/PwS/LN+hK23ZM+ePdq1a1d9+vSpXrlyRbt166aOjo76888/25S7f/++TpgwgS6S/6OtW7dqtmzZjDEdDhw4oBaLxeglRzVyXZ87d06PHDli7EAHDBigWbNmjbNt9tevX69169bVCxcu6Pbt27Vo0aL6+eef2zSZXL9+vRYsWFAvXrxox5oCCZf1wkfUK71PnjzR8PBw7d27tzo7O9t0VFC6dGnNnz+/pkuXTqtUqaKZM2fmOd5/MW3aNE2fPr2xnmbOnKkWi0U3btxolJk3b55+9dVXOmHCBONv0b59e61SpUq8bJ45YcIEzZ07t1aqVEmvX79uM69NmzaaJ08e41h4+/btV/aanFBFXQ/79+/XPHny6O7du/X48eO6bds29fDw0KpVqxpDL8ycOVPz58+vn332WbT3JwTPnj3TAwcOvHR/l9AQtt6SiRMnqre3tzGWxfnz5/WTTz5RFxeXaIEroX0hY8OL7adXr16tVatWVdXIcVNSpkypU6dOVdXIO4j79u2zKX/48GF9//331d3dXQ8ePPhW6hzbRo4cqeXKlVNfX19Vjdyx9e3bV8uWLatt27bV3bt365YtW9Tb21tbtWpl59oCCdu5c+d00qRJqho5GHHq1Kn18ePHevnyZe3bt686OzsbHRWEhobqunXrdPLkybpmzRoGLH4N3bt314EDB6pq5Pp1dXU1jgFRx/+xOn78uHbt2lVTp05t01lJfLJhwwbNkyePurm56fnz51VVjXG0rl+/rilSpIg2aDHnI9H98MMP2rRpU+3QoYPN9IsXL6qbm5t269bNmLZy5coEezcnqvjWEcibImyZxLqDitrFeMWKFbVChQrGa2vgSp069Ut7qcGbs145WbJkiebJk0fnz59vc5BVjRzZvVGjRjZX9q5fv64jRoyI081ydu/erTly5FAPDw8jTIaGhuro0aO1YsWKmihRIi1QoIA2bdrUeA8HUsA+RowYoa6urtqyZUtNliyZTYcEV69eNQLXi2P0ILoX92PPnz/XKlWq6MSJE3Xfvn2aMmVKo2l+WFiYjhgxwmbIi0ePHum8efO0VKlSNoP7xmUvO7l9/vy5bt26VT09PdXf39/mTsPx48c1c+bMunPnzrdZzTjn9u3b2rJlS02TJo3Wrl3bmG69mzVp0iQtUKBAtGehCVwJG2HLROvWrdMPP/xQ169fr6qR7aBz5sypw4YNM8pcunRJO3TooF5eXhocHMzJ738wc+ZMLV68uKpGXrn09/dXi8WiI0eONMo8ffpU69Spoy1atIi2ruPDuj969Kjmy5dPW7VqZQxual2uw4cPG1czVbnSBNhD1P3MBx98oBaLRZs0aRKtQwZr4EqdOjXP8L6mMWPG6J49e1Q1cnzBTJkyaeLEifXHH380ygQFBel7772nQ4cOtXlvWFiYTXPruCzqvv3gwYO6detWvXjxorGNbdmyRdOlS6dVq1bVxYsX66ZNm7RmzZpatGhRQsELXnacPHjwoHbq1EmTJk2qP/zwg828mTNnqo+PT7zZlhA7EglMoaqydOlSmT9/vjRv3lyGDh0q4eHh0rZtWzl+/Ljs27dPREQyZ84sQ4YMkb1794qzs7NYLBY71zzu8vDwEBGRXbt2ibOzs7Ro0UJKliwpmzZtksDAQFmwYIHUr19fLly4IHPnzhWLxSIRERHG++PDuvfx8ZEFCxbIsWPHZMqUKXLs2DFjuQoWLCjZsmUTkcjtM1Eivv7A2/Cy/cyZM2fkyZMn0qhRI9mzZ49MnjxZbt++bZTLmDGjdOvWTZo2bSojR46UoKAgUdW3Xve44unTpxIYGCiTJ0+W0NBQKVeunJQqVUry5MkjWbNmFRGRixcvSrNmzeTBgwcyaNAgERFjnSZOnFhcXV3tVf1YE3Xf3r9/f6lbt660aNFCfHx8pGvXrrJ3716pXLmy/PLLL3L+/Hlp0qSJ/Pbbb5IjRw75888/JXHixBIeHm7npXg3REREGOvy5s2bcuvWLRERKVy4sPTp00dat24tw4YNkxkzZsijR4/kxo0b8ssvv0jGjBnFxcXFnlXHu8auUS+eefHOyO7du7V58+Y6cuRILV68uHbu3Fk7dOig+fLlo3v3/+hld6H+/vtvLViwoH700UfGtPnz52v9+vXVyclJy5Ytq02bNk0QveIcOHBAixcvrh07djTucAGwn/Pnz2ujRo1UNbIpc9myZY2OkAYOHKiZM2fW0aNHG72ZqapxdZzhGV6PtQmXtYn4mjVrtGHDhurk5KTZs2fXggULapkyZRLEMWDKlCmaLl063bhxo968eVN//PFHrVy5sjZo0MBoKrllyxbNkSOH1qtXz3iftTkc/mfw4MGaJ08ezZYtm5YuXdro5v3s2bParl07tVgsmilTJm3Tpo1WqVLFuINI6xFYEbZi2aZNm4w29uHh4dq1a1dt166dBgcH69SpU7VDhw5qsVjUYrHorl277FzbuM960LRas2aNpk2b1qbHKVU1mlBYQ1pC6BXnwIEDmilTpmjNHAC8fevWrdNMmTJpsWLFXjqW3+DBgzVLliw6atQoPX/+vH7++efq7u7Oye9L/NNJbP78+bVNmzbG6+vXr+vWrVt11qxZGhgYaASs+HYMiDrEjKpq8+bNtUuXLjZlVq5cqYUKFdLhw4erauTxc8uWLeru7q4NGzZ8uxV+h0XdvubMmaOpUqXSWbNm6aJFi9Tf318zZsyo8+bNU1XVv/76Sz/66CPNlSuXjhkzxngf31tERdiKRWFhYfrll1+qxWLRli1b6h9//KERERFatGhR/eKLL1Q1sr14165dNWPGjHrmzBk71zhu+/LLL7VBgwY2g4Devn1b/fz8jOfiXhxjSjV+PJv1uujeHXh3fPbZZ2qxWLRgwYLGtKjPag0dOlSzZcum3t7emiFDBi7I/Ys5c+botm3bNCgoyJg2d+5cLVWqlNHl+8uCWXy7oxX1mLZjxw598uSJtmjRQlu2bKmqtss7YMAA9fLyMra7iIgI3bp1qyZJkkQ/+OCDt1vxd9zy5ct1ypQpNucYqqqtW7fWDBkyGAMWHzp0SLt06aJ58+aN1rs0oErYMsXhw4fV19dXy5Ytqz169NC1a9dqvXr19M8//zTK3L9/334VjCc2bdqk9evXV29vby1RooSuWLFCHz16pAsWLNCUKVNGG0ckIaM5A2A/1u/f7NmztU+fPpo/f36tXr26MT9qr7Xbtm3TpUuX2nRmg+geP36sefLk0eL/1969x0VV538cf81wUwSEElDCW5Soq0m26paVeVmKvOeWBhoqZQiSZKShWd4yzHU1lbLykpc2NcVUMlG8IVquVpgkWrrggqLhcgeR2/z+cJ0Vc3ftl+OgvJ9/OXPOHD5zHuP3nPf5fs/3/P73pq5du5qSk5NNRUVFppycHJOPj495YqTb/eLalW37uHHjTM2aNTPl5OSYZsyYYXJycvrFMzuXLl1qeuSRR2r85qqrq0179+41hwe5NDvjHXfcYTIYDOZHNFx5YaRDhw6mkJAQ8+vU1FRTWFiYycPDw7R27dqbXq/UbgaTSXfcWsK5c+fYtm0bf/nLX/jpp5/w8PAgMDCQGTNmWLu024LJZMJgMFBSUsLp06eZNGkSGRkZVFRUEB0dzdSpU3niiSeYNWsWdnZ21i5XROqgy+3U1e9t2bKFl19+mebNm7N9+3bzsu+++47WrVtTv379m13qLamyspKdO3eycuVKvvjiC3r06MHIkSPJyckhOjqa3bt306pVK2uXeVPk5uby2muvMXjwYHr27AlA7969SU1NZe3atTRv3hxnZ2f69+9Pw4YNWbdu3W0xKZSlFBUVsXnzZt58802aN29OYmIiABUVFdjZ2TF06FDs7e1ZunSp+TOHDx9m+fLlhIeH4+PjY63SpRZS2LKwiooKJkyYwMKFC3Fzc+PEiRM4Oztbu6xbypUzAsGlA6ytre0v1tu/fz+bNm3io48+Ii8vj8DAQFatWnUzSxURAf4dtHbv3s22bdvIzMykd+/edO/eHU9PT7788ksiIyPx9vbm008/ZcGCBWzatInExETc3d2tXX6tcq3QevVxIT4+nj179hAbG0uLFi04duwYy5cvZ9iwYTe73Jviyu+/ZMkSIiIi8PX1ZfXq1fj6+gLw888/Exoays6dO7njjjtwcnLCYDBw6NAh7Ozsrrlf66Krf0uXX1+4cIFNmzYRFhZGt27diIuLM59/dO7cmU6dOhEbG1vj8+Xl5djb21vrq0gtpbBlQVc2ZImJidx77700b97cylXduhYsWEB4ePgvpiy/uqE8fPgwX3/9NSEhIdja2uqAIiJWERcXx9ChQ+nVqxfl5eXs27ePAQMGEBkZyQMPPMD27duJiIigqKgIo9FIXFwcnTp1snbZtVZxcTFOTk413ru6ff/73/9unip/9erV17wwd6u78jtXVFTw448/EhkZyd69e9m/fz8dO3ascVzctGkTBQUFAAQGBmJjY/MfL1rWNVfup0WLFnHkyBEyMjIIDg7msccew8PDg7Vr1zJ69Gi8vLxo2bIlzs7OHDp0iB9++EH7UK6LwpaF6UT//+/KRjA2NpaIiAgOHDjwq05GdEAREWvIzMzE39+fsWPHEhoaCkBCQgKTJ0+mTZs2zJ07F1dXV/Lz8zl48CC/+93v8Pb2tnLVtcuWLVvo3LkzjRo1YtKkSVRWVjJz5kxsbGyuuf7lY0ZZWRn16tUDbr9jwK5duzhz5gxBQUG8+OKLODg4MG/ePI4dO8aIESMoKChg//793HHHHeYhb1erqqr6j/uwrho/fjxLly6lX79+5ObmkpSUxNNPP83LL79M69atWbNmDdOnT6ekpIRNmzbRvn174Pb7fYllKGxJrbd7926SkpK4//776du3r7XLERH5nzIzM3n00Uf54IMP8Pf3N7+fkJDAwIEDWbNmjdqz/6KwsJDu3buTk5NDQEAAq1at4uuvvzaf5F6P2+lip8lkori4mEGDBlFeXo6Liwt79uwhOTnZvE/S0tIYOnQoZWVlJCcn4+bmpmB1Hfbv38+QIUNYt24dnTt3BmD16tXExMTQrVs35syZw4ULF/jiiy+Ijo6mS5curF69GlBwletj/N+riFhPUlISw4YNY968eeZ73fR0exGpjS5fuzSZTJSWllJSUkJRUREAZWVlADz++OP4+fmxa9cuq9V5K3BxcWH79u2UlJSwYsUK4uPjad++PZWVlde9jdslaMGl7+Ls7Mzq1as5e/Ys8fHxTJw4sUb4bNOmDatWraJ+/fp069aNf/7znwoC1+Hyb8rV1dX8f3jIkCG88sorfPjhh6SlpeHs7Ey/fv2IiYnh4MGDPPnkkwDav3JdFLakVvP29mbYsGFUVlayceNG4FLjVl1dbeXKREQunahdPkG73C4ZDAZ8fX0ZNGgQI0eO5Pjx4+ZhbSaTCVtbW7y8vKxW862iqKgId3d37r77bkJDQ8nOzsbW1rZOt/9GoxEfHx8eeeQRduzYwSeffGJeZjKZzIErLy+PsWPHWrHS2ulag7kqKyvJz8+nuLgYg8FgvjASFBSEp6cnhw4dAsDR0ZF+/frx5ptvkpmZyenTp29q7XLr0jBCqTWunujicvf8zz//zLvvvsvKlSsJDQ1l4sSJ11xfRORmOXr0KG3btjW/TkxMZP369djY2NC6dWvCw8MpLS3lmWeeISkpiYULF+Lo6Mi3337LokWLOHDgQJ2Zlvx6XatNLykpobCwkP79+5OXl8fevXtp3LixeXl+fj6urq43uVLrO3v2LCEhIVy4cIGQkBCCgoLMyy5evMjPP/+Ml5eXel6ucOVMgRcuXKjxiIV+/fqRkpLCoUOH8PDwAC49wqdbt27MmjWL/v37m9ctKyujoqJCM0vLdVPYklrh6skw0tLSOHLkCC+99BKPPPIIDg4OzJ49m/Xr1/Pcc88RHR0N3F5j8kXk1rB27VpiYmIYN24cQ4cOZefOnfTq1YvBgweTmZnJ+fPncXNzY+/evVRWVjJhwgQ2bNhAgwYNcHZ25oMPPuD++++39teoVa48BuzcuZPc3FwaNmxIx44dufPOOzl16hTPPPMM+fn5bN++nbvuuosRI0Zw7733MnnyZCtXbx3p6elERERQXl5OYGAgw4YNo2fPnnTt2pW33noL0D1FcOk+yccff9z8es6cOWzbto0mTZrg7+9PYGAgp06dYujQoRw7doyZM2diNBpZv3492dnZHDp0qM7vQ/ltFLakVpkwYQLLly9n1KhRFBcXs2zZMp599lkWLlzI6dOn+fDDD4mLi6N///7MnDnT2uWKSB104sQJxowZQ0VFBcHBwXz11Vf4+voSGRlJRUUFBw8e5MUXX8TFxYV9+/YB8I9//AMnJyeMRmOd7Im5Xq+++iorV66kUaNGHD9+nF69ejFy5EiefvppMjIyGDp0KCkpKbRt25bc3FzS0tLq9IPr09PTiYqKIi0tjYsXL+Lo6Mg333yjZz39S2xsLHPnziUqKorQ0FDmz5/PlClTGDVqFElJSVRVVdGnTx8mT55MXl4eEyZMICkpCScnJ5o2bcratWuxs7NTaJXfRGFLao1du3YREhLCunXr6NixIwcPHqRLly6sWrWKwMBA4NLQiZkzZ3L+/Hk++eQT9WqJiFVkZGQQHh6OwWAgKyuLt99+m4CAAOBSb8L+/fsZNWoU48ePZ8SIERr2fB2WL1/O+PHj2bhxI35+fhw7doxp06ZRUFDAuHHj6N27NxcvXuTDDz+kurqa8PBwbG1t6/yJcHZ2Nt988w3nzp0jODgYW1tbTUn+L8ePH2f27NkcPXqUp59+mjNnzvDHP/4Rf39/cnJymDt3Ll9++SX9+/dnypQpAJw5cwYXFxcaNGiAwWDQvpTfTC2/1BplZWU0bdqUjh078umnn9KzZ09iY2MJDAykqKiIAwcO0LhxY15//XVz0NK1AhGxhhYtWrBgwQJsbGz4/vvvSUpKMi+zsbHhgQcewN7enhMnTgAoaF2H77//ns6dO/OHP/wBBwcH/Pz8mDp1KhUVFXz22WcAODg4EBERwdixYxW0/qVJkyb06dOHkJAQ8z5ROLh0m4Gvry/R0dG0adOGuLg4Nm7cyF133QWAu7s7Y8eOJSAggM2bN5uHo3p5eeHk5ITBYKC6ulr7Un4ztf5Sa+Tn55Obm8uWLVsYPXo0MTExjB49Grh08/miRYs4c+YMHh4e5qClni0RsZa7776b2NhY+vbtS0JCAsuXLzcvc3R0pHHjxlRXV2MymXRh6L+4PLugjY0NpaWl5tfV1dW0b9+e8PBwPv30U7Kysn6xH+t60LoW7ZNLv53L5wc+Pj6MHz+eVq1acebMGfPMxgCenp5ERkby5JNP8vHHH7N48eIa29FFErkR9CuSm66iosL87yun8H3qqado0KABffr0YcaMGYSFhQGXZlZaunQpFRUVNGnSxLy+gpaIWJu3tzfvvvsuXl5ezJkzh3HjxrF69WomTJjAnj17CA4OxmAwqL26wtVTt18+oX3wwQfZtWsXn332GQaDwfy+i4sL7dq1w8HBQftR/qcrh+zGxcWRkZGBr68vb7zxBoMHD+bzzz/n/fffN6/v4eFBWFgYkydPZsSIEdYqW25jumdLbpojR47UeADjBx98YJ7+2N/fn44dOxIfH8/kyZNxcXFh+vTpZGVlsXLlSrKysvjuu++wtbVVj5aI1DoZGRlERkYSHx/PfffdR/fu3QkJCakxPbzUPBHesWMHeXl5ODg44O/vj4ODA6+99hpz584lNjaWrl274urqar7nLSEhQW2//FdXnh9MnDiRFStWEBUVxahRo3B0dOTkyZPMnDmTH374geHDhxMaGvqLbWhoqtxoCltyU0yaNInk5GSmTJlC9+7dmTFjBrNnzyYgIIDdu3fj5+dHaGgoAwYMYNu2bbz99tukpqbi4+NDy5YtWbFihWYEEpFaLSsri6CgILy9vVm4cCFubm7WLqnWevXVV1m7di3w756tL774grZt2zJt2jRmz56Ni4sLzs7OODs7s3//fuzs7DTRiFyX6dOnM3/+fLZs2UKbNm1wcnIyB7FTp04xffp00tLSGDhwIFFRUdYuV25zCltyU2zfvp1p06bRqFEjgoKC2Lx5My+88AIPP/wwqampvP766xQUFPDSSy8xcOBAAE6ePEnjxo1xdHTUjEAickvIyMjAxsaGpk2bWruUWmvZsmVERUWxdetWvL29ycvLIyoqisOHD/PVV1/RrFkzvv32WwoKCqioqKBnz57Y2NjoGCDXJTc3l8GDBzN8+HCCgoI4ffo0J0+eZMmSJTz66KMMGjSIwsJCXn75ZRo1asSiRYvUYyoWpbAlFne5N2rPnj1MmjQJV1dX8vLy+Pzzz3F3dwcuzUL1xhtvUFRUREhIiHmq98s0dFBE5NZ0dW/UhAkTyMrK4pNPPjG/V1hYSN++famurmbXrl2/CFUa1SDXKy8vj3bt2jFixAj8/f157733SE9Px2Aw8NNPPzFp0iTGjRtHZmYmd911F0ajUecYYlHqixeLu3yAfPjhh1mwYAHnz5/nyJEj7N+/37zOfffdx/Tp03F1dWXWrFns2LGjxjbUCIqI3HpMJpM5aK1atYqSkhIuXLhASkqKeZ2qqipcXFwICQkhJyeH8+fP/2I7Clpyvdzc3Jg2bRrvvfceffv2pXnz5rz11lt8/fXX9O7d2/zba9q0KUajscbMhSKWoLAlFhMXF8dXX30FQFRUFCEhIdx///3MnTuXdu3asXjx4hqhqn379kyaNIknn3ySxx57zEpVi4jIjXBlb8Hs2bOJiooiPT2dfv36YTAYmDdvHpWVleYg5eHhgdForDFjrcj/R0hICCkpKRw6dIhZs2bRq1cvqqurOXPmDM2aNauxru4BFEvTMEKxiAsXLjBy5EjWrFnDkCFD2LRpE8nJyfj5+QGQlJTExIkTcXd3JyIigh49evxiGxo2IiJy6zt06BALFixgyJAhBAQEUFhYSFRUFD/99BOPPfYYkZGR5ObmEh4eDlyaKEM9DXKjFBcXk5KSwqxZszh16hTffvut7v2Tm0phSyymqqoKHx8fzpw5w+LFi3nuueeoqKjAzs4OgD179vD666/j6elJSEgIAQEBVq5YRERupDVr1vDOO+9QXFzMhg0bzFPh5+TkMHPmTBISEjh58iStWrWiXr16mnVQbiiTycSePXuYM2cOFRUVbN68WTMby02nsCUWk5+fzzPPPIPRaCQ5OZmtW7fy8MMPU1lZidFoxGg0kpSUxPPPP89TTz1FTEyMtUsWEZEb6MSJE0RGRrJjxw6mTp3K+PHjzcsuXLhAaWkpSUlJuLu78+CDD2rWQbnhLl68yNGjR+nQoQNGo1G/L7npFLbkhrnWlcjKykoqKysZMWIEmzdvJiEhga5du5qXl5WVcfr0aVq0aKGrTCIit6GsrCzCwsI4f/48Y8aMMc82e61jhnocxJLUYyrWoLAlN8SVDdjGjRs5e/YsAP7+/rRs2ZLS0lKef/554uPj2bhxI126dCE4OJgmTZowf/58QAdZEZHbVXp6OhEREZSWlvLCCy/w7LPPAnqsh4jc/hS25IaKiopi+fLltG7dmpSUFNq0aUNQUBBjx46lpKSEMWPGsHz5cjp06EBpaSmpqanme7hEROT2lZ6ezksvvURZWRlDhgwhJCTE2iWJiFic+lLlhlm3bh1//etf2bp1K0lJSWRmZuLn58e6detYsmQJDRo0YNmyZWzYsIHIyEiOHj2KnZ0dlZWV1i5dREQsrGXLlsyfP5/i4mIOHz5s7XJERG4K9WzJDfPOO+8QFxfH3r17sbGxwWg0cu7cOcLCwigoKCAxMfEXn9HQQRGRuiU7OxtPT0/dOyMidYJaOvnNLud1W1tbysrKKC8vN8/44+npSXR0NDt37jQ/tf1KCloiInVLkyZNMBqNVFdXW7sUERGLU9iS3+zyzc1PPPEEqamp/PnPfwYwT61aVVVFu3btcHFxsVqNIiJSu6hnS0TqAj1oQG6Ytm3bsmTJEl544QUKCwsZNGgQbm5uTJ06FVdXV1q0aGHtEkVEREREbhrdsyU3XFxcHGPGjMFgMODo6IiHhwe7d+/Gzs5Oz7gQERERkTpDYUss4uzZs5w7d47y8nIeeOABPbVdREREROochS25KdSjJSIiIiJ1jcKWiIiIiIiIBairQURERERExAIUtkRERERERCxAYUtERERERMQCFLZEREREREQsQGFLRERERETEAhS2RERERERELEBhS0RERERExAIUtkRERH6l4cOHM2DAAGuXISIitZzCloiI3DaGDx+OwWDAYDBgb2/PPffcw7Rp06isrLR2af/Vxx9/jKurq7XLEBGRG8zW2gWIiIjcSE888QTLli3j4sWLbNmyhfDwcOzs7IiOjq6xXnl5Ofb29laqUkRE6gL1bImIyG3FwcGBxo0b07x5c0aPHk2vXr3YtGmTeejfW2+9hZeXF76+vgAcOXKEHj16UL9+fe68805GjRpFcXGxeXtVVVWMGzcOV1dX7rzzTsaPH4/JZKrxN1u0aMG8efNqvOfn58eUKVPMr/Pz83nxxRfx9PSkXr16tGvXjvj4eHbv3s2IESMoKCgw98pd+TkREbl1KWyJiMhtrX79+pSXlwOwY8cOjh8/zvbt24mPj6ekpITHH38cNzc3Dh48yGeffUZiYiJjxowxf37OnDl8/PHHLF26lOTkZHJzc9mwYcOvqqG6upqAgAD27dvHqlWrOHr0KDExMdjY2PDQQw8xb948XFxcyM7OJjs7m6ioqBu6D0RExDo0jFBERG5LJpOJHTt2kJCQQEREBDk5OTRo0IDFixebhw9+9NFHlJWVsWLFCho0aADAwoUL6du3L7NmzcLT05N58+YRHR3NU089BcCiRYtISEj4VbUkJibyt7/9jbS0NFq1agXA3XffbV7esGFDDAYDjRs3vhFfXUREagn1bImIyG0lPj4eJycn6tWrR0BAAIMHDzYPy2vfvn2N+7TS0tLo0KGDOWgBdO3alerqao4fP05BQQHZ2dl06dLFvNzW1pbf//73v6qmlJQUvL29zUFLRETqBvVsiYjIbaV79+68//772Nvb4+Xlha3tvw91V4aqG8loNP7iPq6Kigrzv+vXr2+RvysiIrWberZEROS20qBBA+655x6aNWtWI2hdS5s2bTh8+DAlJSXm9/bt24fRaMTX15eGDRvSpEkTDhw4YF5eWVnJN998U2M77u7uZGdnm18XFhaSnp5ufn3fffeRlZXFjz/+eM067O3tqaqq+lXfU0REaj+FLRERqbOCgoKoV68ewcHBpKamsmvXLiIiIhg2bBienp4AjB07lpiYGD7//HOOHTtGWFgY+fn5NbbTo0cPVq5cyd69ezly5AjBwcHY2NiYl3fr1o1HH32UQYMGsX37dtLT0/nyyy/ZunUrcGk2w+LiYnbs2MH58+cpLS29aftAREQsR2FLRETqLEdHRxISEsjNzaVTp0786U9/omfPnixcuNC8ziuvvMKwYcMIDg7mwQcfxNnZmYEDB9bYTnR0NN26daNPnz707t2bAQMG4OPjU2Od9evX06lTJ5599lnatm3L+PHjzb1ZDz30EKGhoQwePBh3d3feeecdy395ERGxOIPp6kHmIiIiIiIi8pupZ0tERERERMQCFLZEREREREQsQGFLRERERETEAhS2RERERERELEBhS0RERERExAIUtkRERERERCxAYUtERERERMQCFLZEREREREQsQGFLRERERETEAhS2RERERERELEBhS0RERERExAL+D0XuRSXxyhOjAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Visualize product frequencies\n",
+    "item_counts = encoded_data.sum().sort_values(ascending=False)\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "item_counts[:10].plot(kind='bar', color='skyblue')\n",
+    "plt.title(\"Top 10 Most Frequent Products\")\n",
+    "plt.xlabel(\"Product\")\n",
+    "plt.ylabel(\"Frequency\")\n",
+    "plt.xticks(rotation=45)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Apply Apriori algorithm\n",
+    "min_support = 0.02  # Adjust based on dataset\n",
+    "frequent_itemsets = apriori(encoded_data, min_support=min_support, use_colnames=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Generate association rules\n",
+    "min_confidence = 0.2\n",
+    "rules = association_rules(frequent_itemsets, metric=\"confidence\", min_threshold=min_confidence)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Visualize support vs confidence\n",
+    "plt.figure(figsize=(8, 5))\n",
+    "plt.scatter(rules['support'], rules['confidence'], alpha=0.5, c=rules['lift'], cmap='coolwarm')\n",
+    "plt.colorbar(label='Lift')\n",
+    "plt.xlabel(\"Support\")\n",
+    "plt.ylabel(\"Confidence\")\n",
+    "plt.title(\"Association Rules: Support vs Confidence\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Model saved as 'apriori_rules.csv'\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Save association rules for later use\n",
+    "rules.to_csv(\"apriori_rules.csv\", index=False)\n",
+    "print(\"Model saved as 'apriori_rules.csv'\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}