{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "|--- TIT <= 1058.15\n",
      "|   |--- TAT <= 543.87\n",
      "|   |   |--- TAT <= 528.12\n",
      "|   |   |   |--- value: [22.39]\n",
      "|   |   |--- TAT >  528.12\n",
      "|   |   |   |--- value: [10.12]\n",
      "|   |--- TAT >  543.87\n",
      "|   |   |--- TAT <= 549.23\n",
      "|   |   |   |--- value: [6.44]\n",
      "|   |   |--- TAT >  549.23\n",
      "|   |   |   |--- value: [4.53]\n",
      "|--- TIT >  1058.15\n",
      "|   |--- TIT <= 1076.55\n",
      "|   |   |--- TAT <= 545.34\n",
      "|   |   |   |--- value: [6.61]\n",
      "|   |   |--- TAT >  545.34\n",
      "|   |   |   |--- value: [2.96]\n",
      "|   |--- TIT >  1076.55\n",
      "|   |   |--- TIT <= 1091.35\n",
      "|   |   |   |--- value: [1.71]\n",
      "|   |   |--- TIT >  1091.35\n",
      "|   |   |   |--- value: [1.28]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import pickle\n",
    "import pandas as pd\n",
    "from sklearn import tree\n",
    "\n",
    "data = pd.read_csv(\"data-turbine/clear-data.csv\")\n",
    "model = pickle.load(open(\"data-turbine/tree-gs.model.sav\", \"rb\"))\n",
    "features = (\n",
    "    data\n",
    "    .drop([\"CO\"], axis=1)\n",
    "    .columns.values.tolist()\n",
    ")\n",
    "\n",
    "rules = tree.export_text(model, feature_names=features)\n",
    "print(rules)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[if (TIT > 1058.15) and (TIT > 1076.55) and (TIT > 1091.35) -> 1.283,\n",
       " if (TIT > 1058.15) and (TIT > 1076.55) and (TIT <= 1091.35) -> 1.708,\n",
       " if (TIT <= 1058.15) and (TAT > 543.87) and (TAT <= 549.235) -> 6.441,\n",
       " if (TIT <= 1058.15) and (TAT > 543.87) and (TAT > 549.235) -> 4.533,\n",
       " if (TIT > 1058.15) and (TIT <= 1076.55) and (TAT <= 545.34) -> 6.609,\n",
       " if (TIT > 1058.15) and (TIT <= 1076.55) and (TAT > 545.34) -> 2.956,\n",
       " if (TIT <= 1058.15) and (TAT <= 543.87) and (TAT > 528.115) -> 10.121,\n",
       " if (TIT <= 1058.15) and (TAT <= 543.87) and (TAT <= 528.115) -> 22.394]"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from src.rules import get_rules\n",
    "\n",
    "\n",
    "rules = get_rules(model, features)\n",
    "display(len(rules))\n",
    "rules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[if (TIT > 1058.15) -> 1.283,\n",
       " if (TIT > 1058.15) and (TIT <= 1091.35) -> 1.708,\n",
       " if (TIT <= 1058.15) and (TAT > 543.87) and (TAT <= 549.235) -> 6.441,\n",
       " if (TIT <= 1058.15) and (TAT > 543.87) -> 4.533,\n",
       " if (TIT > 1058.15) and (TIT <= 1076.55) and (TAT <= 545.34) -> 6.609,\n",
       " if (TIT > 1058.15) and (TIT <= 1076.55) and (TAT > 545.34) -> 2.956,\n",
       " if (TIT <= 1058.15) and (TAT <= 543.87) and (TAT > 528.115) -> 10.121,\n",
       " if (TIT <= 1058.15) and (TAT <= 543.87) -> 22.394]"
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from src.rules import normalise_rules\n",
    "\n",
    "\n",
    "rules = normalise_rules(rules)\n",
    "display(len(rules))\n",
    "rules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[if (TIT > 1058.15) -> 1.283,\n",
       " if (TIT > 1058.15) and (TIT <= 1091.35) -> 1.708,\n",
       " if (TIT <= 1058.15) and (TAT > 543.87) and (TAT <= 549.235) -> 6.441,\n",
       " if (TIT <= 1058.15) and (TAT > 543.87) -> 4.533,\n",
       " if (TIT > 1058.15) and (TIT <= 1076.55) and (TAT <= 545.34) -> 6.609,\n",
       " if (TIT > 1058.15) and (TIT <= 1076.55) and (TAT > 545.34) -> 2.956,\n",
       " if (TIT <= 1058.15) and (TAT <= 543.87) and (TAT > 528.115) -> 10.121,\n",
       " if (TIT <= 1058.15) and (TAT <= 543.87) -> 22.394]"
      ]
     },
     "execution_count": 170,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from src.rules import delete_same_rules\n",
    "\n",
    "\n",
    "rules = delete_same_rules(rules)\n",
    "display(len(rules))\n",
    "rules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "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>AH</th>\n",
       "      <th>TIT</th>\n",
       "      <th>TAT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4480</th>\n",
       "      <td>83.256</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>540.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24883</th>\n",
       "      <td>73.583</td>\n",
       "      <td>1099.8</td>\n",
       "      <td>538.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21557</th>\n",
       "      <td>81.089</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>534.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1705</th>\n",
       "      <td>64.757</td>\n",
       "      <td>1086.6</td>\n",
       "      <td>549.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21388</th>\n",
       "      <td>75.645</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>534.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25725</th>\n",
       "      <td>85.663</td>\n",
       "      <td>1072.2</td>\n",
       "      <td>549.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5014</th>\n",
       "      <td>75.280</td>\n",
       "      <td>1058.0</td>\n",
       "      <td>549.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22584</th>\n",
       "      <td>92.874</td>\n",
       "      <td>1067.2</td>\n",
       "      <td>550.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>93.029</td>\n",
       "      <td>1099.9</td>\n",
       "      <td>524.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20828</th>\n",
       "      <td>88.840</td>\n",
       "      <td>1079.9</td>\n",
       "      <td>550.02</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>29386 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           AH     TIT     TAT\n",
       "4480   83.256  1100.0  540.65\n",
       "24883  73.583  1099.8  538.53\n",
       "21557  81.089  1100.0  534.04\n",
       "1705   64.757  1086.6  549.76\n",
       "21388  75.645  1100.0  534.21\n",
       "...       ...     ...     ...\n",
       "25725  85.663  1072.2  549.82\n",
       "5014   75.280  1058.0  549.86\n",
       "22584  92.874  1067.2  550.15\n",
       "501    93.029  1099.9  524.78\n",
       "20828  88.840  1079.9  550.02\n",
       "\n",
       "[29386 rows x 3 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "4480     0.3527\n",
       "24883    1.2522\n",
       "21557    1.4718\n",
       "1705     1.3117\n",
       "21388    1.7835\n",
       "          ...  \n",
       "25725    2.4980\n",
       "5014     3.2652\n",
       "22584    1.2630\n",
       "501      0.7851\n",
       "20828    2.7272\n",
       "Name: CO, Length: 29386, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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>AH</th>\n",
       "      <th>TIT</th>\n",
       "      <th>TAT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18246</th>\n",
       "      <td>84.837</td>\n",
       "      <td>1088.7</td>\n",
       "      <td>550.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20343</th>\n",
       "      <td>59.574</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>542.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2924</th>\n",
       "      <td>81.262</td>\n",
       "      <td>1092.9</td>\n",
       "      <td>544.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>88.135</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>526.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5713</th>\n",
       "      <td>86.846</td>\n",
       "      <td>1080.2</td>\n",
       "      <td>550.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21917</th>\n",
       "      <td>75.935</td>\n",
       "      <td>1081.1</td>\n",
       "      <td>549.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13099</th>\n",
       "      <td>78.314</td>\n",
       "      <td>1089.8</td>\n",
       "      <td>550.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26704</th>\n",
       "      <td>79.478</td>\n",
       "      <td>1073.0</td>\n",
       "      <td>550.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4182</th>\n",
       "      <td>41.623</td>\n",
       "      <td>1100.2</td>\n",
       "      <td>539.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2982</th>\n",
       "      <td>69.233</td>\n",
       "      <td>1091.6</td>\n",
       "      <td>549.98</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7347 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           AH     TIT     TAT\n",
       "18246  84.837  1088.7  550.39\n",
       "20343  59.574  1100.0  542.01\n",
       "2924   81.262  1092.9  544.91\n",
       "117    88.135  1100.0  526.21\n",
       "5713   86.846  1080.2  550.25\n",
       "...       ...     ...     ...\n",
       "21917  75.935  1081.1  549.66\n",
       "13099  78.314  1089.8  550.37\n",
       "26704  79.478  1073.0  550.19\n",
       "4182   41.623  1100.2  539.10\n",
       "2982   69.233  1091.6  549.98\n",
       "\n",
       "[7347 rows x 3 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "18246    1.34970\n",
       "20343    1.63430\n",
       "2924     0.78632\n",
       "117      0.72742\n",
       "5713     1.35980\n",
       "          ...   \n",
       "21917    1.45140\n",
       "13099    1.00960\n",
       "26704    2.01190\n",
       "4182     0.37685\n",
       "2982     1.15990\n",
       "Name: CO, Length: 7347, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "random_state = 9\n",
    "\n",
    "y = data[\"CO\"]\n",
    "X = data.drop([\"CO\"], axis=1).copy()\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    X, y, test_size=0.2, random_state=random_state\n",
    ")\n",
    "display(X_train, y_train, X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[if (TIT = 1100.9) -> 1.283,\n",
       " if (TIT = 1074.75) -> 1.708,\n",
       " if (TIT = 1001.3) and (TAT = 546.552) -> 6.441,\n",
       " if (TIT = 1001.3) and (TAT = 550.6) -> 4.533,\n",
       " if (TIT = 1067.35) and (TAT = 511.04) -> 6.609,\n",
       " if (TIT = 1067.35) and (TAT = 550.6) -> 2.956,\n",
       " if (TIT = 1001.3) and (TAT = 535.993) -> 10.121,\n",
       " if (TIT = 1001.3) and (TAT = 511.04) -> 22.394]"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from src.rules import simplify_rules\n",
    "\n",
    "rules = simplify_rules(X_train, rules)\n",
    "rules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AH</th>\n",
       "      <td>36733.0</td>\n",
       "      <td>77.867015</td>\n",
       "      <td>14.461355</td>\n",
       "      <td>24.085000</td>\n",
       "      <td>68.1880</td>\n",
       "      <td>80.4700</td>\n",
       "      <td>89.3760</td>\n",
       "      <td>100.200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TIT</th>\n",
       "      <td>36733.0</td>\n",
       "      <td>1081.428084</td>\n",
       "      <td>17.536373</td>\n",
       "      <td>1000.800000</td>\n",
       "      <td>1071.8000</td>\n",
       "      <td>1085.9000</td>\n",
       "      <td>1097.0000</td>\n",
       "      <td>1100.900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TAT</th>\n",
       "      <td>36733.0</td>\n",
       "      <td>546.158517</td>\n",
       "      <td>6.842360</td>\n",
       "      <td>511.040000</td>\n",
       "      <td>544.7200</td>\n",
       "      <td>549.8800</td>\n",
       "      <td>550.0400</td>\n",
       "      <td>550.610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO</th>\n",
       "      <td>36733.0</td>\n",
       "      <td>2.372468</td>\n",
       "      <td>2.262672</td>\n",
       "      <td>0.000388</td>\n",
       "      <td>1.1824</td>\n",
       "      <td>1.7135</td>\n",
       "      <td>2.8429</td>\n",
       "      <td>44.103</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       count         mean        std          min        25%        50%  \\\n",
       "AH   36733.0    77.867015  14.461355    24.085000    68.1880    80.4700   \n",
       "TIT  36733.0  1081.428084  17.536373  1000.800000  1071.8000  1085.9000   \n",
       "TAT  36733.0   546.158517   6.842360   511.040000   544.7200   549.8800   \n",
       "CO   36733.0     2.372468   2.262672     0.000388     1.1824     1.7135   \n",
       "\n",
       "           75%       max  \n",
       "AH     89.3760   100.200  \n",
       "TIT  1097.0000  1100.900  \n",
       "TAT   550.0400   550.610  \n",
       "CO      2.8429    44.103  "
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe().transpose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/user/Projects/python/fuzzy-rules-generator/.venv/lib/python3.12/site-packages/skfuzzy/control/fuzzyvariable.py:125: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
      "  fig.show()\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "from skfuzzy import control as ctrl\n",
    "import skfuzzy as fuzz\n",
    "\n",
    "# AT = ctrl.Antecedent(np.arange(-6.2348, 37.103, 0.0001), \"AT\")\n",
    "# AP = ctrl.Antecedent(np.arange(985.85, 1036.6, 0.01), \"AP\")\n",
    "# AH = ctrl.Antecedent(np.arange(24.085, 100.2, 0.1), \"AH\")\n",
    "# AFDP = ctrl.Antecedent(np.arange(2.0874, 7.6106, 0.0001), \"AFDP\")\n",
    "TIT = ctrl.Antecedent(np.arange(1000.8, 1100.9, 0.1), \"TIT\")\n",
    "TAT = ctrl.Antecedent(np.arange(511.04, 550.61, 0.1), \"TAT\")\n",
    "CO = ctrl.Consequent(np.arange(0.000388, 44.103, 0.1), \"CO\")\n",
    "\n",
    "# AT.automf(3, variable_type=\"quant\")\n",
    "# AP.automf(5, variable_type=\"quant\")\n",
    "# AH.automf(5, variable_type=\"quant\")\n",
    "# AH.view()\n",
    "# AFDP.automf(3, variable_type=\"quant\")\n",
    "TIT.automf(3, variable_type=\"quant\")\n",
    "# TIT[\"low\"] = fuzz.zmf(TIT.universe, 1025, 1035)\n",
    "# TIT[\"average\"] = fuzz.trapmf(TIT.universe, [1025, 1035, 1056, 1075])\n",
    "# TIT[\"high\"] = fuzz.smf(TIT.universe, 1065, 1075)\n",
    "TIT.view()\n",
    "TAT.automf(3, variable_type=\"quant\")\n",
    "# TAT[\"low\"] = fuzz.zmf(TAT.universe, 520, 525)\n",
    "# TAT[\"average\"] = fuzz.trapmf(TAT.universe, [520, 525, 535, 540])\n",
    "# TAT[\"high\"] = fuzz.smf(TAT.universe, 535, 540)\n",
    "TAT.view()\n",
    "CO.automf(names=[str(i) for i in range(1, 18)], variable_type=\"quant\")\n",
    "# CO[\"low\"] = fuzz.zmf(CO.universe, 10, 13)\n",
    "# CO[\"average\"] = fuzz.trapmf(CO.universe, [10, 13, 30, 33])\n",
    "# CO[\"high\"] = fuzz.smf(CO.universe, 30, 33)\n",
    "CO.view()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA1MAAANECAYAAABVa3W/AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAADENUlEQVR4nOzdf1yUdb7//wcgDKIOiAbIRzRO7vojfxUWTj/8+ANBYzuabLfc3LQkPXnAE7JHzVIXtZai/Fkk21bSfoMs96Rb2ioTLpqJv9hYFctTrR12Nwf3pDipCSPM9w8/XOsIKIz8GnjebzducL3fr7nm/boYLuY113W9Ly+n0+lEREREREREGsW7tQcgIiIiIiLiiVRMiYiIiIiIuEHFlIiIiIiIiBtUTImIiIiIiLhBxZSIiIiIiIgbVEyJiIiIiIi4QcWUiIiIiIiIG1RMiYiIiIiIuEHFlIiIiIiIiBtUTImIiIiIiLhBxZS0Oa+++ipeXl5ER0cbbTfffDNeXl7X/crOzm69gYtIm1bXvuVKV+5LvL29CQ8PJzY2loKCgpYdqIh4lIbsW5KTk+vsy87OxsvLi0OHDjXnEKUZdWrtAYhcLScnh5tvvpkDBw7w1Vdf0a9fP9asWcO5c+eMmI8++oh33nmH1atX07NnT6P9rrvuao0hi4gHqGvfcrXx48czffp0nE4nJ06c4NVXX2Xs2LFs27aNiRMntsKoRaSta8i+RdovFVPSppw4cYK9e/fy/vvv82//9m/k5OTwy1/+ksmTJ7vE2Ww23nnnHSZPnszNN9/cKmMVEc9R377laj/+8Y/5+c9/biw/8MADDB06lDVr1qiYEpFaGrpvkfZLp/lJm5KTk0P37t2Jj4/npz/9KTk5Oa09JBFpB9zdtwwZMoSePXty4sSJZh6hiHgivW8RFVPSpuTk5DBlyhT8/Pz42c9+xpdffsnBgwdbe1gi4uHc3becOXOGM2fO0KNHjxYYpYh4mobuWy5evMj//u//1vq68hIG8UwqpqTNKCoq4osvvmDq1KkA3HPPPfTu3Vuf8ojIDWnMvqXmDc8//vEPDhw4wIMPPkhVVRUPPvhgSw9bRNq4xuxb3njjDW666aZaX3Pnzm3pYUsTUzElbUZOTg6hoaGMGTMGuDz7zUMPPcTGjRupqqpq5dGJiKdqzL6l5g1PSEgI0dHRfPrpp6SmppKSktIKIxeRtqwx+5ZJkyZhtVprfc2fP781hi5NSBNQSJtQVVXFxo0bGTNmjMu1CdHR0axcuZL8/HxiY2NbcYQi4okau2+ZNGkSycnJeHl50a1bN2699Va6dOnSGkMXkTassfuW3r17ExMTU2s9f/vb31pkvNJ8VExJm7Bz505OnjzJxo0b2bhxY63+nJwcFVMi0miN3bfU94ZHRORKet8iNVRMSZuQk5NDSEgImZmZtfref/99Nm/eTFZWFp07d26F0YmIp9K+RUSag/YtUkPFlLS6H374gffff58HH3yQn/70p7X6w8PDeeedd/jggw946KGHWmGEIuKJtG8RkeagfYtcSRNQSKv74IMP+P777/nXf/3XOvtHjhzJTTfdpFn9RKRRtG8RkeagfYtcScWUtLqcnBz8/f0ZP358nf3e3t7Ex8ezfft2vvvuuxYenYh4Ku1bRKQ5aN8iV/JyOp3O1h6EiIiIiIiIp9GRKRERERERETeomBIREREREXGDiikRERERERE3qJgSERERERFxg4opERERERERN6iYEhERERERcUOn1h5Aa6qurubbb7+lW7dueHl5tfZwRNoNp9PJ999/T3h4ON7eHe8zG+1bRJqP9i/av4g0F3f2Lx26mPr222+JiIho7WGItFt//etf6d27d2sPo8Vp3yLS/LR/EZHm0pj9S4cuprp16wZc3mBms7mVR/NPDoeDvLw8YmNj8fX1be3hNIjG3DI8Zcx2u52IiAjjb6yjaav7lpbkKa/VtkTbrGG0f2k/+5f29JpvT7lA+8qnMbm4s3/p0MVUzeFxs9ncpnZIDoeDgIAAzGazx7yANeaW4Wlj7qinoLTVfUtL8rTXalugbdY42r94/v6lPb3m21Mu0L7ycSeXxuxfOt7JxiIiIiIiIk1AxZSIiIiIiIgbVEyJiIiIiIi4QcWUiIiIiIiIG1RMiYiIiIiIuEHFlIiIiIiIiBtUTImIiIiIiLihQ99nSjq2wWk7yLjz8veKqn/eT+Cb5+NbcVQi0hpufmpbvX3aJ4iI3Jj2vI/VkSkRERERERE3qJgSERERERFxg4opERERERERN+iaKRERERERaRX1XU/lKddSqZiSVtGeL0QUERER6Yiu9f6uvdJpfiIiIiIiIm5QMSUiIiIiIuIGFVMiIiIiIiJu0DVT0q5d69xdk08LDkRERERE2h0VUyKN4OkzzoiIiIhI01ExJW2OChYRERER8QQqpkSu0hGn9RQRERGRxtMEFCIiIiIiIm5QMSUiIiIdXnp6OnfccQfdunUjJCSEyZMnc/z4cZeY0aNH4+Xl5fL1xBNPuMSUlpYSHx9PQEAAISEhzJ8/n0uXLrnEFBQUcPvtt2MymejXrx/Z2dnNnZ5Ik7n5qW31fnVEOs1PmlVH/cMSERHPsmvXLpKSkrjjjju4dOkSTz/9NLGxsRw7dowuXboYcbNmzWL58uXGckBAgPFzVVUV8fHxhIWFsXfvXk6ePMn06dPx9fXlV7/6FQAnTpwgPj6eJ554gpycHPLz83n88cfp1asXcXFxLZewiDQJFVMiIiLS4W3fvt1lOTs7m5CQEIqKihg1apTRHhAQQFhYWJ3ryMvL49ixY3z88ceEhoYyfPhwVqxYwcKFC0lLS8PPz4+srCwiIyNZuXIlAAMHDmTPnj2sXr1axZSIB1IxJe2CjoCJiEhTOnv2LADBwcEu7Tk5Obz99tuEhYVx//33s2TJEuPoVGFhIUOGDCE0NNSIj4uLY86cOZSUlHDbbbdRWFhITEyMyzrj4uJISUlp3oREpFmomJIbdvNT2zD5OMm4Ewan7aCiyqu1hyQiIuK26upqUlJSuPvuuxk8eLDR/vDDD9O3b1/Cw8M5fPgwCxcu5Pjx47z//vsA2Gw2l0IKMJZtNts1Y+x2Oz/88AOdO3d26auoqKCiosJYttvtADgcDhwORxNl3Dpqxu/peUD7ygWunY/Jx9miY2iq9TRkfe48p4opkSZwrSNjuj+WiIhnSUpK4ujRo+zZs8elffbs2cbPQ4YMoVevXowbN46vv/6aW265pVnGkp6ezrJly2q15+XluVyv5cmsVmtrD6HJtKdcoO58Mu5smef+6KOPmnR9DfndXLhwodHrVTElHkOn8smVnn/+eRYtWsSTTz7JmjVrALh48SK/+MUv2LhxIxUVFcTFxfHqq6+6fApcWlrKnDlz+OMf/0jXrl2ZMWMG6enpdOr0z91hQUEBqamplJSUEBERweLFi3n00UdbOEMRaQ3Jycls3bqV3bt307t372vGRkdHA/DVV19xyy23EBYWxoEDB1xiysrKAIzrrMLCwoy2K2PMZnOto1IAixYtIjU11Vi22+1EREQQGxuL2WxufIJtiMPhwGq1Mn78eHx9fVt7ODekPeUC185ncNqOFhnD0bSmuYawMb+bmiO/jaFiSkQ8zsGDB/n1r3/N0KFDXdrnzZvHtm3b2LRpE4GBgSQnJzNlyhQ+/fRTQDNtiUj9nE4nc+fOZfPmzRQUFBAZGXndxxQXFwPQq1cvACwWC8899xynTp0iJCQEuPxpuNlsZtCgQUbM1Z+4W61WLBZLnc9hMpkwmUy12n19fdvFm3ZQLm1ZXfm01OUcTb0dG/K7cec5dZ8pEfEo586dY9q0afzmN7+he/fuRvvZs2d54403WLVqFWPHjiUqKooNGzawd+9e9u3bB/xzpq23336b4cOHM3HiRFasWEFmZiaVlZUALjNtDRw4kOTkZH7605+yevXqVslXRFpGUlISb7/9Nrm5uXTr1g2bzYbNZuOHH34A4Ouvv2bFihUUFRXxzTff8MEHHzB9+nRGjRplfLATGxvLoEGDeOSRR/jzn//Mjh07WLx4MUlJSUZB9MQTT/CXv/yFBQsW8MUXX/Dqq6/y3nvvMW/evFbLXUTcp2JKRDxKUlIS8fHxtWbDKioqwuFwuLQPGDCAPn36UFhYCNQ/05bdbqekpMSIqWumrZp1iEj7tH79es6ePcvo0aPp1auX8fXuu+8C4Ofnx8cff0xsbCwDBgzgF7/4BQkJCXz44YfGOnx8fNi6dSs+Pj5YLBZ+/vOfM336dJf7UkVGRrJt2zasVivDhg1j5cqVvP766zryLeKhdJqfiHiMjRs38qc//YmDBw/W6rPZbPj5+REUFOTSHhoaet1ZtGr6rhVT30xb0L5n23KXp81sda3ZqVoqB0/bZq2lubaP03ntGcoiIiLYtWvXddfTt2/f6144P3r0aD777LNGjU9E2iYVUyLiEf7617/y5JNPYrVa8ff3b+3huOgIs225y1NmtrrW7FRNPaPU9XjKNmst7sy2JSLu0S1vrk/FlIh4hKKiIk6dOsXtt99utFVVVbF7925eeeUVduzYQWVlJeXl5S5Hp8rKylxm0Wrqmbagfc+25S5Pm9nqWrNTNdWMUtfjadustbgz25aISHNp8mIqPT2d999/ny+++ILOnTtz11138cILL9C/f38jRtMXi0hjjRs3jiNHjri0PfbYYwwYMICFCxcSERGBr68v+fn5JCQkAHD8+HFKS0uNWbKaY6Yt6BizbbmrrW2D+m+xUP8nry09/ra2zdoabRsRaUuafAKKXbt2kZSUxL59+7BarTgcDmJjYzl//rwRM2/ePD788EM2bdrErl27+Pbbb5kyZYrRXzN9cWVlJXv37uWtt94iOzubpUuXGjE10xePGTOG4uJiUlJSePzxx9mxo2XmvheRltWtWzcGDx7s8tWlSxd69OjB4MGDCQwMJDExkdTUVP74xz9SVFTEY489hsViYeTIkYBm2hIREZGm1eRHprZv3+6ynJ2dTUhICEVFRYwaNcqYvjg3N5exY8cCsGHDBgYOHMi+ffsYOXKkMX3xxx9/TGhoKMOHD2fFihUsXLiQtLQ0/Pz8XKYvBhg4cCB79uxh9erVmhFHpINavXo13t7eJCQkuBz1rlEz09acOXOwWCx06dKFGTNm1DnT1rx581i7di29e/fWTFsiIiItrP4zCeCb5+NbcCTX1uzXTJ09exaA4OBg4PrTF48cObLe6YvnzJlDSUkJt912W73TF6ekpNQ7Fk+ZccvTZnQy+TgxeV+eBanmuydoqTE35e/RU14bLTW+goICl2V/f38yMzPJzMys9zGaaUtERESaSrMWU9XV1aSkpHD33XczePBgoHWnL/a0Gbc8ZUanK2fBWjGiuvUG4qbmHnNzzATW1l8bmm1LREREOoJmLaaSkpI4evQoe/bsac6naTBPmXHL02Z0Gpy2A5O3kxUjqllyyJuKas+YQrOlxtyUM4F5ymtDs22JiIhIR9BsxVRycjJbt25l9+7d9O7d22gPCwtrtemLPW3GrbY6rqtdef+Bimovj7sfQXOPuTl+h239tdGWxyYiIiLSVJq8mHI6ncydO5fNmzdTUFBAZGSkS39UVFSrTV8sIiLSWPVdBN2WLoAWEZHW0eTFVFJSErm5ufz+97+nW7duxjVOgYGBdO7c2WX64uDgYMxmM3Pnzq13+uKMjAxsNlud0xe/8sorLFiwgJkzZ7Jz507ee+89tm2rf+YPERERERGRptLk95lav349Z8+eZfTo0fTq1cv4evfdd42Y1atX85Of/ISEhARGjRpFWFgY77//vtFfM32xj48PFouFn//850yfPr3O6YutVivDhg1j5cqVmr5YRERERERaTLOc5nc9mr5YREREREQ8XZMfmRIREREREekIVEyJiIiIiIi4oVnvMyUimglMREREpL3SkSkRERERERE3qJgSERERERFxg4opERERERERN6iYEhERERERcYOKKRERERERETdoNj9psPpmpRMRERER6Yh0ZEpERERERMQNKqZERERERETcoNP8REREREQ6oPou4TD5OMm4s4UH46F0ZEpERERERMQNKqZERESkw0tPT+eOO+6gW7duhISEMHnyZI4fP+4Sc/HiRZKSkujRowddu3YlISGBsrIyl5jS0lLi4+MJCAggJCSE+fPnc+nSJZeYgoICbr/9dkwmE/369SM7O7u50xORZqJiSkRERDq8Xbt2kZSUxL59+7BarTgcDmJjYzl//rwRM2/ePD788EM2bdrErl27+Pbbb5kyZYrRX1VVRXx8PJWVlezdu5e33nqL7Oxsli5dasScOHGC+Ph4xowZQ3FxMSkpKTz++OPs2LGjRfMVkaaha6ZERESkw9u+fbvLcnZ2NiEhIRQVFTFq1CjOnj3LG2+8QW5uLmPHjgVgw4YNDBw4kH379jFy5Ejy8vI4duwYH3/8MaGhoQwfPpwVK1awcOFC0tLS8PPzIysri8jISFauXAnAwIED2bNnD6tXryYuLq7F8xaRG6MjUyIiIiJXOXv2LADBwcEAFBUV4XA4iImJMWIGDBhAnz59KCwsBKCwsJAhQ4YQGhpqxMTFxWG32ykpKTFirlxHTUzNOkTEs+jIlIiIiMgVqqurSUlJ4e6772bw4MEA2Gw2/Pz8CAoKcokNDQ3FZrMZMVcWUjX9NX3XirHb7fzwww907tzZpa+iooKKigpj2W63A+BwOHA4HDeYaeuqGb+n5wGem4vJx1l3u7fT5Xtb05jt3JjfjTu/PxVTIiLSrtQ31a9IQyUlJXH06FH27NnT2kMhPT2dZcuW1WrPy8sjICCgFUbU9KxWa2sPocl4Wi7Xm/58xYjqlhlII3300UeNfkxDfjcXLlxo9HpVTImIiIj8P8nJyWzdupXdu3fTu3dvoz0sLIzKykrKy8tdjk6VlZURFhZmxBw4cMBlfTWz/V0Zc/UMgGVlZZjN5lpHpQAWLVpEamqqsWy324mIiCA2Nhaz2XxjybYyh8OB1Wpl/Pjx+Pr6tvZwboin5jI4re6JT0zeTlaMqGbJIW8qqr1aeFTXdzSt4dcXNuZ3U3PktzFUTImIiEiH53Q6mTt3Lps3b6agoIDIyEiX/qioKHx9fcnPzychIQGA48ePU1paisViAcBisfDcc89x6tQpQkJCgMufhpvNZgYNGmTEXP2putVqNdZxNZPJhMlkqtXu6+vrUW/ar0W5tJ6KqmsXShXVXteNaQ3ubOOG/G7cWa+KKREREenwkpKSyM3N5fe//z3dunUzrnEKDAykc+fOBAYGkpiYSGpqKsHBwZjNZubOnYvFYmHkyJEAxMbGMmjQIB555BEyMjKw2WwsXryYpKQkoyB64okneOWVV1iwYAEzZ85k586dvPfee2zbptNTpfno9Ofmo2JKRETEDdd6c/LN8/EtOBJpCuvXrwdg9OjRLu0bNmzg0UcfBWD16tV4e3uTkJBARUUFcXFxvPrqq0asj48PW7duZc6cOVgsFrp06cKMGTNYvny5ERMZGcm2bduYN28ea9eupXfv3rz++uuaFl3EQ6mYEhERkQ7P6bz+rGX+/v5kZmaSmZlZb0zfvn2ve3H86NGj+eyzzxo9RhFpe3SfKRERERERETeomBIREREREXGDTvMTaSW63kJERETEs+nIlIh4jPXr1zN06FDMZjNmsxmLxcIf/vAHo//ixYskJSXRo0cPunbtSkJCQq37uZSWlhIfH09AQAAhISHMnz+fS5cuucQUFBRw++23YzKZ6NevH9nZ2S2RnoiIiHgYFVMi4jF69+7N888/T1FREYcOHWLs2LFMmjSJkpISAObNm8eHH37Ipk2b2LVrF99++y1TpkwxHl9VVUV8fDyVlZXs3buXt956i+zsbJYuXWrEnDhxgvj4eMaMGUNxcTEpKSk8/vjj7NhR940NRUREpOPSaX4i4jHuv/9+l+XnnnuO9evXs2/fPnr37s0bb7xBbm4uY8eOBS5PaTxw4ED27dvHyJEjycvL49ixY3z88ceEhoYyfPhwVqxYwcKFC0lLS8PPz4+srCwiIyNZuXIlAAMHDmTPnj2sXr1aUxeLiEibpXtJtQ4dmRIRj1RVVcXGjRs5f/48FouFoqIiHA4HMTExRsyAAQPo06cPhYWFABQWFjJkyBBCQ0ONmLi4OOx2u3F0q7Cw0GUdNTE16xARERGpoSNTIuJRjhw5gsVi4eLFi3Tt2pXNmzczaNAgiouL8fPzIygoyCU+NDQUm80GgM1mcymkavpr+q4VY7fb+eGHH+jcuXOtMVVUVFBRUWEs2+12ABwOBw6H48YS9lA1ebdG/iaf698vqLm5k3drbjNPou0jIm1JkxdTu3fv5sUXX6SoqIiTJ0+yefNmJk+ebPQ/+uijvPXWWy6PiYuLY/v27cby6dOnmTt3Lh9++KFxp/G1a9fStWtXI+bw4cMkJSVx8OBBbrrpJubOncuCBQuaOp0OR4eIpa3r378/xcXFnD17lt/97nfMmDGDXbt2teqY0tPTWbZsWa32vLw8AgICWmFEbYfVam3x58y4s8Wfspbr3bT1Wlpjm3mSCxcutPYQREQMTV5MnT9/nmHDhjFz5kyXC7+vNGHCBDZs2GAsm0wml/5p06Zx8uRJrFYrDoeDxx57jNmzZ5Obmwtc/tQ3NjaWmJgYsrKyOHLkCDNnziQoKIjZs2c3dUoi0ob4+fnRr18/AKKiojh48CBr167loYceorKykvLycpejU2VlZYSFhQEQFhbGgQMHXNZXM9vflTFXzwBYVlaG2Wyu86gUwKJFi0hNTTWW7XY7ERERxMbGYjabbyxhD+VwOLBarYwfPx5fX98Wfe7Baa0/WcjRtMZfX9ea28yT1Bz5FRFpC5q8mJo4cSITJ068ZozJZDLeuFzt888/Z/v27Rw8eJARI0YA8PLLL3Pffffx0ksvER4eTk5ODpWVlbz55pv4+flx6623UlxczKpVq1RMiXQw1dXVVFRUEBUVha+vL/n5+SQkJABw/PhxSktLsVgsAFgsFp577jlOnTpFSEgIcPkogNlsZtCgQUbM1UcVrFarsY66mEymWh8KAfj6+nb4N8WtsQ0qqrxa9PnqciM563Vzbdo2ItKWtMo1UwUFBYSEhNC9e3fGjh3Ls88+S48ePYDLF38HBQUZhRRATEwM3t7e7N+/nwceeIDCwkJGjRqFn5+fERMXF8cLL7zAmTNn6N69e53P6ynXNXjitQYmb6fLd0/Qlsdc3+/eU66paK7xLVq0iIkTJ9KnTx++//57cnNzKSgoYMeOHQQGBpKYmEhqairBwcGYzWbmzp2LxWJh5MiRAMTGxjJo0CAeeeQRMjIysNlsLF68mKSkJKMYeuKJJ3jllVdYsGABM2fOZOfOnbz33nts26ZTYEVERMRVixdTEyZMYMqUKURGRvL111/z9NNPM3HiRAoLC/Hx8cFmsxmfGBuD7NSJ4OBglwvEIyMjXWKuvIi8vmLK065r8MRrDVaMqG6agbSgtjjm611v0davqWiuaxpOnTrF9OnTOXnyJIGBgQwdOpQdO3Ywfvx4AFavXm1cZ1lRUUFcXByvvvqq8XgfHx+2bt3KnDlzsFgsdOnShRkzZrB8+XIjJjIykm3btjFv3jzWrl1L7969ef311zUtuoiItAm6vr1tafFiaurUqcbPQ4YMYejQodxyyy0UFBQwbty4Zn1uT7muwROvNTB5O1kxopolh7ypqG79U2waoi2Pub7rLTzlmormuqbhjTfeuGa/v78/mZmZZGZm1hvTt2/f6xaro0eP5rPPPnNrjCIiItK86isov3k+voVH0gamRv+Xf/kXevbsyVdffcW4ceMICwvj1KlTLjGXLl3i9OnT171AvKavPp52XYMnXmtQUe3VJq5XaIy2OObr/d7b6mu2Rlsem7Qf+nRWRERaW6vftPdvf/sb3333Hb169QIuX/xdXl5OUVGREbNz506qq6uJjo42Ynbv3u1yXYbVaqV///71nuInIiIiIiLSlJq8mDp37hzFxcUUFxcDcOLECYqLiyktLeXcuXPMnz+fffv28c0335Cfn8+kSZPo16+fcT3CwIEDmTBhArNmzeLAgQN8+umnJCcnM3XqVMLDwwF4+OGH8fPzIzExkZKSEt59913Wrl3rcgqfiIiIiIhIc2ry0/wOHTrEmDFjjOWaAmfGjBmsX7+ew4cP89Zbb1FeXk54eDixsbGsWLHC5fS7nJwckpOTGTdunHEx+bp164z+wMBA8vLySEpKIioqip49e7J06VJNiy4iIm1CWzqfX0REmk+TF1OjR4/G6ax/qukdO64/wUFwcLBxg976DB06lE8++aTR4xMRERERkfanrg+yTD7OG56t+lpa/ZopERERERERT6RiSkRERERExA0qpkRERERERNygYkpERERERMQNKqZERERERETcoGJKRERERETEDU0+NbqIiIiIiLivvnvVSdujI1MiIiLS4e3evZv777+f8PBwvLy82LJli0v/o48+ipeXl8vXhAkTXGJOnz7NtGnTMJvNBAUFkZiYyLlz51xiDh8+zL333ou/vz8RERFkZGQ0d2oi0oxUTImIiEiHd/78eYYNG0ZmZma9MRMmTODkyZPG1zvvvOPSP23aNEpKSrBarWzdupXdu3cze/Zso99utxMbG0vfvn0pKirixRdfJC0tjddee63Z8hKR5qXT/ERERKTDmzhxIhMnTrxmjMlkIiwsrM6+zz//nO3bt3Pw4EFGjBgBwMsvv8x9993HSy+9RHh4ODk5OVRWVvLmm2/i5+fHrbfeSnFxMatWrXIpukTEc6iYEmmD6jtX+ssVsS08EhERqVFQUEBISAjdu3dn7NixPPvss/To0QOAwsJCgoKCjEIKICYmBm9vb/bv388DDzxAYWEho0aNws/Pz4iJi4vjhRde4MyZM3Tv3r3FcxKRG6NiSkREROQ6JkyYwJQpU4iMjOTrr7/m6aefZuLEiRQWFuLj44PNZiMkJMTlMZ06dSI4OBibzQaAzWYjMjLSJSY0NNToq6uYqqiooKKiwli22+0AOBwOHA5Hk+bY0mrG7+l5QNPnYvJxNsl63H5+b6fLd09Wk0NDfjfu/P5UTImIiIhcx9SpU42fhwwZwtChQ7nlllsoKChg3Lhxzfa86enpLFu2rFZ7Xl4eAQEBzfa8Lclqtbb2EJpMU+WScWeTrOaGrRhR3dpDaDIN+d1cuHCh0etVMSUiIiLSSP/yL/9Cz549+eqrrxg3bhxhYWGcOnXKJebSpUucPn3auM4qLCyMsrIyl5ia5fquxVq0aBGpqanGst1uJyIigtjYWMxmc1Om1OIcDgdWq5Xx48fj6+vb2sO5IU2dy+C0HU0wKveZvJ2sGFHNkkPeVFR7tepYblRNLg353dQc+W0MFVMiIiIijfS3v/2N7777jl69egFgsVgoLy+nqKiIqKgoAHbu3El1dTXR0dFGzDPPPIPD4TDe1FmtVvr371/v9VImkwmTyVSr3dfX1+MLkBrKpbaKqrZRwFRUe7WZsdyohvxu3PndaWp0ERER6fDOnTtHcXExxcXFAJw4cYLi4mJKS0s5d+4c8+fPZ9++fXzzzTfk5+czadIk+vXrR1xcHAADBw5kwoQJzJo1iwMHDvDpp5+SnJzM1KlTCQ8PB+Dhhx/Gz8+PxMRESkpKePfdd1m7dq3LkScR8SwqpkRERKTDO3ToELfddhu33XYbAKmpqdx2220sXboUHx8fDh8+zL/+67/y4x//mMTERKKiovjkk09cjhrl5OQwYMAAxo0bx3333cc999zjcg+pwMBA8vLyOHHiBFFRUfziF79g6dKlmhZdxIPpND8RERHp8EaPHo3TWf/MZTt2XP8aluDgYHJzc68ZM3ToUD755JNGj09E2iYVUyIiIiIiLay+e0qKZ9FpfiIiIiIiIm5QMSUiIiIiIuIGFVMiIiIiIiJuUDElIiIiIiLiBhVTIiIiIiIiblAxJSIiIiIi4gYVUyIiIiIiIm5QMSUiIiIiIuIGFVMiIiIiIiJuUDElIiIiIiLiBhVTIuIx0tPTueOOO+jWrRshISFMnjyZ48ePu8RcvHiRpKQkevToQdeuXUlISKCsrMwlprS0lPj4eAICAggJCWH+/PlcunTJJaagoIDbb78dk8lEv379yM7Obu70RERExMN0au0BiIg01K5du0hKSuKOO+7g0qVLPP3008TGxnLs2DG6dOkCwLx589i2bRubNm0iMDCQ5ORkpkyZwqeffgpAVVUV8fHxhIWFsXfvXk6ePMn06dPx9fXlV7/6FQAnTpwgPj6eJ554gpycHPLz83n88cfp1asXcXFxrZa/iIh4npuf2tbaQ5BmpGKqg9Iftnii7du3uyxnZ2cTEhJCUVERo0aN4uzZs7zxxhvk5uYyduxYADZs2MDAgQPZt28fI0eOJC8vj2PHjvHxxx8TGhrK8OHDWbFiBQsXLiQtLQ0/Pz+ysrKIjIxk5cqVAAwcOJA9e/awevVqFVMiIiJiaPLT/Hbv3s39999PeHg4Xl5ebNmyxaXf6XSydOlSevXqRefOnYmJieHLL790iTl9+jTTpk3DbDYTFBREYmIi586dc4k5fPgw9957L/7+/kRERJCRkdHUqYhIG3f27FkAgoODASgqKsLhcBATE2PEDBgwgD59+lBYWAhAYWEhQ4YMITQ01IiJi4vDbrdTUlJixFy5jpqYmnWIiIiIQDMcmTp//jzDhg1j5syZTJkypVZ/RkYG69at46233iIyMpIlS5YQFxfHsWPH8Pf3B2DatGmcPHkSq9WKw+HgscceY/bs2eTm5gJgt9uJjY0lJiaGrKwsjhw5wsyZMwkKCmL27NlNnZKItEHV1dWkpKRw9913M3jwYABsNht+fn4EBQW5xIaGhmKz2YyYKwupmv6avmvF2O12fvjhBzp37uzSV1FRQUVFhbFst9sBcDgcOByOG8zUM9Xk3Zz5m3yczbbu5nKt7dES26w90PYRkbakyYupiRMnMnHixDr7nE4na9asYfHixUyaNAmA3/72t4SGhrJlyxamTp3K559/zvbt2zl48CAjRowA4OWXX+a+++7jpZdeIjw8nJycHCorK3nzzTfx8/Pj1ltvpbi4mFWrVqmYEukgkpKSOHr0KHv27GntoZCens6yZctqtefl5REQENAKI2o7rFZrs607485mW3Wz+eijj64b05zbrD24cOFCaw9BRMTQotdMnThxApvN5nL6TGBgINHR0RQWFjJ16lQKCwsJCgoyCimAmJgYvL292b9/Pw888ACFhYWMGjUKPz8/IyYuLo4XXniBM2fO0L1795ZMS0RaWHJyMlu3bmX37t307t3baA8LC6OyspLy8nKXo1NlZWWEhYUZMQcOHHBZX81sf1fGXD0DYFlZGWazudZRKYBFixaRmppqLNvtdiIiIoiNjcVsNt9Ysh7K4XBgtVoZP348vr6+zfIcg9N2NMt6W8tnz4xt9m3WHtQc+RURaQtatJiqOYWmrtNnrjy9JiQkxKW/U6dOBAcHu8RERkbWWkdNX33FlKeciuOJp8eYvJ0u3z2BJ47ZU04Daq7xOZ1O5s6dy+bNmykoKKi1H4iKisLX15f8/HwSEhIAOH78OKWlpVgsFgAsFgvPPfccp06dMvY1VqsVs9nMoEGDjJirjyBYrVZjHVczmUyYTKZa7b6+vh3+TXFzboOKKq9mWW9rqdlOet1cm7aNiLQlHWo2P087FccTT49ZMaK6eVbcjDxpzDWvibZ+GlBznYaTlJREbm4uv//97+nWrZvxAUtgYCCdO3cmMDCQxMREUlNTCQ4Oxmw2M3fuXCwWCyNHjgQgNjaWQYMG8cgjj5CRkYHNZmPx4sUkJSUZBdETTzzBK6+8woIFC5g5cyY7d+7kvffeY9s2zYIpIiIi/9SixVTNKTRlZWX06tXLaC8rK2P48OFGzKlTp1wed+nSJU6fPn3dU3CufI66eMqpOJ54eozJ28mKEdUsOeRNRbVnfFrsiWP2lNOAmus0nPXr1wMwevRol/YNGzbw6KOPArB69Wq8vb1JSEigoqKCuLg4Xn31VSPWx8eHrVu3MmfOHCwWC126dGHGjBksX77ciImMjGTbtm3MmzePtWvX0rt3b15//XVNiy4iInUanLaDjDsvf29vR83l2lq0mIqMjCQsLIz8/HyjeLLb7ezfv585c+YAl0+vKS8vp6ioiKioKAB27txJdXU10dHRRswzzzyDw+Ew3lBarVb69+9/zeulPO1UHE88Paai2svjdiKeNGZPOQ2oucbmdF7/lEx/f38yMzPJzMysN6Zv377XnQhg9OjRfPbZZ40eozQt3RNPRETasia/z9S5c+coLi6muLgYuDzpRHFxMaWlpXh5eZGSksKzzz7LBx98wJEjR5g+fTrh4eFMnjwZuHxzzAkTJjBr1iwOHDjAp59+SnJyMlOnTiU8PByAhx9+GD8/PxITEykpKeHdd99l7dq1LkedREREREREmlOTH5k6dOgQY8aMMZZrCpwZM2aQnZ3NggULOH/+PLNnz6a8vJx77rmH7du3G/eYAsjJySE5OZlx48YZp+usW7fO6A8MDCQvL4+kpCSioqLo2bMnS5cu1bToIiLiseo7Teib5+NbcVQiInItTV5MjR49+pqn4nh5ebF8+XKX6xOuFhwcbNygtz5Dhw7lk08+cXucIiIiIiIiN6LJT/MTERERERHpCFRMiYiIiIiIuEHFlIiIiHR4u3fv5v777yc8PBwvLy+2bNni0u90Olm6dCm9evWic+fOxMTE8OWXX7rEnD59mmnTpmE2mwkKCiIxMZFz5865xBw+fJh7770Xf39/IiIiyMjIaO7URKQZqZgSERGRDu/8+fMMGzas3tsqZGRksG7dOrKysti/fz9dunQhLi6OixcvGjHTpk2jpKQEq9XK1q1b2b17t8vkWHa7ndjYWPr27UtRUREvvvgiaWlpvPbaa82en4g0jxa9z5SIiIhIWzRx4kQmTpxYZ5/T6WTNmjUsXryYSZMmAfDb3/6W0NBQtmzZwtSpU/n888/Zvn07Bw8eZMSIEQC8/PLL3Hfffbz00kuEh4eTk5NDZWUlb775Jn5+ftx6660UFxezatUqzUgs4qFUTImIiIhcw4kTJ7DZbMTExBhtgYGBREdHU1hYyNSpUyksLCQoKMgopABiYmLw9vZm//79PPDAAxQWFjJq1Cj8/PyMmLi4OF544QXOnDlD9+7daz13RUUFFRUVxrLdbgfA4XDgcDiaI90WUzN+T88DwOTtdPnu6dpTPjU5NOR15s5rUcWUiIiIyDXYbDYAQkNDXdpDQ0ONPpvNRkhIiEt/p06dCA4OdomJjIystY6avrqKqfT0dJYtW1arPS8vj4CAADczalusVmtrD+GGrRhR8726dQfSxNpTPg15nV24cKHR61UxJSIiItJGLVq0iNTUVGPZbrcTERFBbGwsZrO5FUd24xwOB1arlfHjx+Pr69vaw2mQwWk76mw3eTtZMaKaJYe8qaj2qjPGk7SnfGpyacjrrObIb2OomBLxIIPTdpBx5+XvFVWuO7dvno9vpVGJiLRvYWFhAJSVldGrVy+jvaysjOHDhxsxp06dcnncpUuXOH36tPH4sLAwysrKXGJqlmtirmYymTCZTLXafX19PaYAuR5PyuXq/721+qu9rhvjSdpTPg15nbnzOtRsfiIiIiLXEBkZSVhYGPn5+Uab3W5n//79WCwWACwWC+Xl5RQVFRkxO3fupLq6mujoaCNm9+7dLtdlWK1W+vfvX+cpfiLS9unIVDt281PbWnsIIiIiHuHcuXN89dVXxvKJEycoLi4mODiYPn36kJKSwrPPPsuPfvQjIiMjWbJkCeHh4UyePBmAgQMHMmHCBGbNmkVWVhYOh4Pk5GSmTp1KeHg4AA8//DDLli0jMTGRhQsXcvToUdauXcvq1atbI2URaQIqpkRERKTDO3ToEGPGjDGWa65TmjFjBtnZ2SxYsIDz588ze/ZsysvLueeee9i+fTv+/v7GY3JyckhOTmbcuHF4e3uTkJDAunXrjP7AwEDy8vJISkoiKiqKnj17snTpUk2LLuLBVEyJiIhIhzd69Giczvqngfby8mL58uUsX7683pjg4GByc3Ov+TxDhw7lk08+cXucItK2qJgSEREREfl/dJmENIYmoBAREREREXGDiikRERERERE3qJgSERERERFxg4opERERERERN6iYEhERERERcYOKKRERERERETeomBIREREREXGDiikRERERERE3qJgSERERERFxg4opERERERERN3Rq7QGIiIhI/W5+alu9fd88H9+CIxERkavpyJSIiIiIiIgbdGRKRERERDqcax31FWkoHZkSERERERFxg4opERERERERN+g0PxERaVU61UZERDyVjkyJiIiIiIi4QcWUiHiM3bt3c//99xMeHo6Xlxdbtmxx6Xc6nSxdupRevXrRuXNnYmJi+PLLL11iTp8+zbRp0zCbzQQFBZGYmMi5c+dcYg4fPsy9996Lv78/ERERZGRkNHdqIiIi4oFapZhKS0vDy8vL5WvAgAFG/8WLF0lKSqJHjx507dqVhIQEysrKXNZRWlpKfHw8AQEBhISEMH/+fC5dutTSqYhICzp//jzDhg0jMzOzzv6MjAzWrVtHVlYW+/fvp0uXLsTFxXHx4kUjZtq0aZSUlGC1Wtm6dSu7d+9m9uzZRr/dbic2Npa+fftSVFTEiy++SFpaGq+99lqz5yciIiKepdWumbr11lv5+OOP/zmQTv8cyrx589i2bRubNm0iMDCQ5ORkpkyZwqeffgpAVVUV8fHxhIWFsXfvXk6ePMn06dPx9fXlV7/6VYvnIiItY+LEiUycOLHOPqfTyZo1a1i8eDGTJk0C4Le//S2hoaFs2bKFqVOn8vnnn7N9+3YOHjzIiBEjAHj55Ze57777eOmllwgPDycnJ4fKykrefPNN/Pz8uPXWWykuLmbVqlUuRZeIiIhIqxVTnTp1IiwsrFb72bNneeONN8jNzWXs2LEAbNiwgYEDB7Jv3z5GjhxJXl4ex44d4+OPPyY0NJThw4ezYsUKFi5cSFpaGn5+fi2djoi0shMnTmCz2YiJiTHaAgMDiY6OprCwkKlTp1JYWEhQUJBRSAHExMTg7e3N/v37eeCBBygsLGTUqFEu+5G4uDheeOEFzpw5Q/fu3Ws9d0VFBRUVFcay3W4HwOFw4HA4miPdNq8m74bkb/JxNvdwPILJ2+nyvSE64uurI+YsIm1XqxVTX375JeHh4fj7+2OxWEhPT6dPnz4UFRXhcDhc3hANGDCAPn36UFhYyMiRIyksLGTIkCGEhoYaMXFxccyZM4eSkhJuu+221khJRFqRzWYDcNkv1CzX9NlsNkJCQlz6O3XqRHBwsEtMZGRkrXXU9NVVTKWnp7Ns2bJa7Xl5eQQEBLiZUftgtVqvG5NxZwsMxIOsGFHd4NiPPvqoGUfSNl24cKG1hyAeRLOFSnNrlWIqOjqa7Oxs+vfvz8mTJ1m2bBn33nsvR48exWaz4efnR1BQkMtjrn5DVNcbppq++njKp8eN+UT3Wlry0153PlFtbe1tzG3xNdxRLFq0iNTUVGPZbrcTERFBbGwsZrO5FUfWehwOB1arlfHjx+Pr63vN2MFpO1poVG2bydvJihHVLDnkTUW11w2t62haXBONqu2p+d8tItIWtEoxdeU1D0OHDiU6Opq+ffvy3nvv0blz52Z7Xk/79Lghn+heS2t82tuYT1TbivYy5rb0CXVrfHJcc9pwWVkZvXr1MtrLysoYPny4EXPq1CmXx126dInTp08bjw8LC6s14U3Ncl2nJgOYTCZMJlOtdl9f3+sWEu1dQ7ZBRdWNFQ7tTUW11w1vk/b8umvPuYmI52kTN+0NCgrixz/+MV999RXjx4+nsrKS8vJyl6NTZWVlLm92Dhw44LKO673ZAc/59Lgxn+heS0t+2tuUn6i2lI405pb+lLo1PjmOjIwkLCyM/Px8o3iy2+3s37+fOXPmAGCxWCgvL6eoqIioqCgAdu7cSXV1NdHR0UbMM888g8PhMP7+rFYr/fv3r/MUPxEREem42kQxde7cOb7++mseeeQRoqKi8PX1JT8/n4SEBACOHz9OaWkpFosFuPxm57nnnuPUqVPG9Q9WqxWz2cygQYPqfR5P+/T4RsfVGp/2NsUnqi2tI4y5pV/fzfV8586d46uvvjKWT5w4QXFxMcHBwfTp04eUlBSeffZZfvSjHxEZGcmSJUsIDw9n8uTJAAwcOJAJEyYwa9YssrKycDgcJCcnM3XqVMLDwwF4+OGHWbZsGYmJiSxcuJCjR4+ydu1aVq9e3Sw5iYhnSEtLq3V2S//+/fniiy+Ay7d1+cUvfsHGjRupqKggLi6OV1991eWyhNLSUubMmcMf//hHunbtyowZM0hPT3eZ0VhEPEur/PX+53/+J/fffz99+/bl22+/5Ze//CU+Pj787Gc/IzAwkMTERFJTUwkODsZsNjN37lwsFgsjR44EIDY2lkGDBvHII4+QkZGBzWZj8eLFJCUl1VksiUj7cOjQIcaMGWMs1xxpnjFjBtnZ2SxYsIDz588ze/ZsysvLueeee9i+fTv+/v7GY3JyckhOTmbcuHF4e3uTkJDAunXrjP7AwEDy8vJISkoiKiqKnj17snTpUk2LLiK6rYuI1NIqxdTf/vY3fvazn/Hdd99x0003cc8997Bv3z5uuukmAFavXm28ybny050aPj4+bN26lTlz5mCxWOjSpQszZsxg+fLlrZGOiLSQ0aNH43TWP2GIl5cXy5cvv+a+IDg4mNzc3Gs+z9ChQ/nkk0/cHqeItE+6rYuIXK1ViqmNGzdes9/f35/MzEwyMzPrjenbt2+buuBeRERE2rfWuK2Lp8xE7I6mmr34WlpqZmNPnCH4WtpTPjU5NOR15s5rUSfpioiIiFxHa93WxdNmInbHjc5efC0tPbOxJ84QfC3tKZ+GvM7cmY1YxZSIiIjIdbTWbV08ZSZidzTV7MXX0lIzG3viDMHX0p7yqcmlIa8zd2YjVjHVDuju3iIiIi2rpW7r4mkzEbujOXNp6dl6PXGG4GtpT/k05HXmzutQxZSIiIhII7XUbV2kYfTBsrQWFVMiIiIi16HbuohIXVRMiYiIiFyHbusiInVRMSUiIiJyHbqti4jUxbu1ByAiIiIiIuKJVEyJiIiIiIi4Qaf5iYhIi9BsWyIi0t6omBIREWlnrlW4fvN8fAuORESkfdNpfiIiIiIiIm5QMSUiIiIiIuIGneYnIiIiIm2erruUtkhHpkRERERERNygYkpERERERMQNKqZERERERETcoGumRERERKTN0LVR4kl0ZEpERERERMQNOjIlIiLSgdT3qb9u5isi0ngqpjyEDnmLiIiIiLQtKqZEOgB9Ei0iIiLS9FRMiYhIk6kp3E0+TjLuhMFpO6io8mrlUYmIiDQPFVMiIiJyzdPJdRRbmtrNT23Thy7SLmg2PxERERERETeomBIREREREXGDiikRERERERE36JopERFpNN2uQURERMWUiIiIiDQTffAi7Z1O8xMREREREXGDiikRERERERE36DQ/ERGpk07PkRr1vRZ0/ykB7SukY1Mx1YbU7Ix0EzsREfEEutGviHR0Hn+aX2ZmJjfffDP+/v5ER0dz4MCB1h6SiLQTHWX/cvNT2+r8EpHm01H2LyLtnUcfmXr33XdJTU0lKyuL6Oho1qxZQ1xcHMePHyckJKS1hyciHkz7FxFpLp66f9GHLCK1eXQxtWrVKmbNmsVjjz0GQFZWFtu2bePNN9/kqaeearLn0WkM0l7ptV2/ltq/tBS9CZKWpuus6teW9y/aV4g0jscWU5WVlRQVFbFo0SKjzdvbm5iYGAoLC+t8TEVFBRUVFcby2bNnATh9+jQOh6Pe5+p06Xy9ff3+873GDr3+56n5Xu3kwoVqOjm8qar2jGumNOaW0ZJj/u6779x+7Pfffw+A0+lsquG0qMbuX9zdt7grOj2/0Y9p6Z29J/59tbaOss2u9X9z/6Jx13289i/Nu3+51nueJn+udvSab0+5QPvKpyaX7777Dl9f32vGurN/8dhi6n//93+pqqoiNDTUpT00NJQvvviizsekp6ezbNmyWu2RkZHNMsYb8XBrD8ANGnPLaKkx91x54+v4/vvvCQwMvPEVtbDG7l88ad/Skjzx76u1dfRt1pj9jvYv7WP/0p5e8+0pF2hf+TQ2l8bsXzy2mHLHokWLSE1NNZarq6s5ffo0PXr0wMur7VTddrudiIgI/vrXv2I2m1t7OA2iMbcMTxmz0+nk+++/Jzw8vLWH0iI8Zd/SkjzltdqWaJs1jPYv7Wf/0p5e8+0pF2hf+TQmF3f2Lx5bTPXs2RMfHx/Kyspc2svKyggLC6vzMSaTCZPJ5NIWFBTUXEO8YWaz2eNewBpzy/CEMXviJ8Y1Grt/8bR9S0vyhNdqW6Ntdn3avwQ15xBbXHt6zbenXKB95dPQXBq7f/HYqdH9/PyIiooiP/+f1w5UV1eTn5+PxWJpxZGJiKfT/kVEmov2LyLti8cemQJITU1lxowZjBgxgjvvvJM1a9Zw/vx5Y3YcERF3af8iIs1F+xeR9sOji6mHHnqIf/zjHyxduhSbzcbw4cPZvn17rYs6PY3JZOKXv/xlrcP6bZnG3DI8ccyeqr3uX1qKXquNp23WcWj/cll7es23p1ygfeXT3Ll4OT11blEREREREZFW5LHXTImIiIiIiLQmFVMiIiIiIiJuUDElIiIiIiLiBhVTIiIiIiIiblAx1cZkZmZy88034+/vT3R0NAcOHGjtIRl2797N/fffT3h4OF5eXmzZssWl3+l0snTpUnr16kXnzp2JiYnhyy+/bJ3B/j/p6enccccddOvWjZCQECZPnszx48ddYi5evEhSUhI9evSga9euJCQk1LqZYktav349Q4cONW4uZ7FY+MMf/tBmxyvtV1P8zZ8+fZpp06ZhNpsJCgoiMTGRc+fOucQcPnyYe++9F39/fyIiIsjIyGju1JrNjW6zb775hsTERCIjI+ncuTO33HILv/zlL6msrHRZT3vaZtKxPP/883h5eZGSkmK0edr/tb///e/8/Oc/p0ePHnTu3JkhQ4Zw6NAho78tvh+qS1VVFUuWLHHZ36xYsYIr56Zry7m01P+o61Ex1Ya8++67pKam8stf/pI//elPDBs2jLi4OE6dOtXaQwPg/PnzDBs2jMzMzDr7MzIyWLduHVlZWezfv58uXboQFxfHxYsXW3ik/7Rr1y6SkpLYt28fVqsVh8NBbGws58+fN2LmzZvHhx9+yKZNm9i1axfffvstU6ZMabUx9+7dm+eff56ioiIOHTrE2LFjmTRpEiUlJW1yvNJ+NcXf/LRp0ygpKcFqtbJ161Z2797N7NmzjX673U5sbCx9+/alqKiIF198kbS0NF577bVmz6853Og2++KLL6iurubXv/41JSUlrF69mqysLJ5++mljHe1tm0nHcfDgQX79618zdOhQl3ZP+r925swZ7r77bnx9ffnDH/7AsWPHWLlyJd27dzdi2uL7obq88MILrF+/nldeeYXPP/+cF154gYyMDF5++WUjpi3n0hL/oxrEKW3GnXfe6UxKSjKWq6qqnOHh4c709PRWHFXdAOfmzZuN5erqamdYWJjzxRdfNNrKy8udJpPJ+c4777TCCOt26tQpJ+DctWuX0+m8PEZfX1/npk2bjJjPP//cCTgLCwtba5i1dO/e3fn66697zHil/XHnb/7YsWNOwHnw4EEj5g9/+IPTy8vL+fe//93pdDqdr776qrN79+7OiooKI2bhwoXO/v37N3NGza+p9pMZGRnOyMhIY7k9bzNpv77//nvnj370I6fVanX+3//7f51PPvmk0+n0nP/DNRYuXOi855576u33lPdDTqfTGR8f75w5c6ZL25QpU5zTpk1zOp2elUtz/Y9qCB2ZaiMqKyspKioiJibGaPP29iYmJobCwsJWHFnDnDhxApvN5jL+wMBAoqOj29T4z549C0BwcDAARUVFOBwOl3EPGDCAPn36tIlxV1VVsXHjRs6fP4/FYmnz45WOoyF/84WFhQQFBTFixAgjJiYmBm9vb/bv32/EjBo1Cj8/PyMmLi6O48ePc+bMmRbKpmW4u588e/assc+CjrXNpP1ISkoiPj7e5fUPbf//8NU++OADRowYwYMPPkhISAi33XYbv/nNb4x+T3k/BHDXXXeRn5/Pf//3fwPw5z//mT179jBx4kTAs3K5WlP9j2qITk03bLkR//u//0tVVVWtu5+HhobyxRdftNKoGs5mswHUOf6avtZWXV1NSkoKd999N4MHDwYuj9vPz4+goCCX2NYe95EjR7BYLFy8eJGuXbuyefNmBg0aRHFxcZscr3Q8Dfmbt9lshISEuPR36tSJ4OBgl5jIyMha66jpu/LUGU/nzn7yq6++4uWXX+all15yWU9H2WbSPmzcuJE//elPHDx4sFZfW/0/XJ+//OUvrF+/ntTUVJ5++mkOHjzIf/zHf+Dn58eMGTM84v1Qjaeeegq73c6AAQPw8fGhqqqK5557jmnTpgGe8d6uPk31P6ohVExJh5GUlMTRo0fZs2dPaw/luvr3709xcTFnz57ld7/7HTNmzGDXrl2tPSwRaUF///vfmTBhAg8++CCzZs1q7eGIuOWvf/0rTz75JFarFX9//9Yezg2rrq5mxIgR/OpXvwLgtttu4+jRo2RlZTFjxoxWHl3jvPfee+Tk5JCbm8utt95KcXExKSkphIeHe1wurUmn+bURPXv2xMfHp9bsNWVlZYSFhbXSqBquZoxtdfzJycls3bqVP/7xj/Tu3dtoDwsLo7KykvLycpf41h63n58f/fr1IyoqivT0dIYNG8batWvb7Hil42nI33xYWFitCXQuXbrE6dOnXWLqWseVz9FeNGY/+e233zJmzBjuuuuuWhNLdKRtJp6vqKiIU6dOcfvtt9OpUyc6derErl27WLduHZ06dSI0NNSj/q/16tWLQYMGubQNHDiQ0tJSoO2/H7rS/Pnzeeqpp5g6dSpDhgzhkUceYd68eaSnpwOelcvVmup/VEOomGoj/Pz8iIqKIj8/32irrq4mPz8fi8XSiiNrmMjISMLCwlzGb7fb2b9/f6uO3+l0kpyczObNm9m5c2etU2OioqLw9fV1Gffx48cpLS1tU9u9urqaiooKjxmvtH8N+Zu3WCyUl5dTVFRkxOzcuZPq6mqio6ONmN27d+NwOIwYq9VK//79293pag3dT/79739n9OjRREVFsWHDBry9Xf9Vd6RtJp5v3LhxHDlyhOLiYuNrxIgRTJs2zfjZk/6v3X333bVusfLf//3f9O3bF2i774fqcuHChVr7Fx8fH6qrqwHPyuVqTfU/qkFuePoMaTIbN250mkwmZ3Z2tvPYsWPO2bNnO4OCgpw2m621h+Z0Oi/PxPPZZ585P/vsMyfgXLVqlfOzzz5z/s///I/T6XQ6n3/+eWdQUJDz97//vfPw4cPOSZMmOSMjI50//PBDq415zpw5zsDAQGdBQYHz5MmTxteFCxeMmCeeeMLZp08f586dO52HDh1yWiwWp8ViabUxP/XUU85du3Y5T5w44Tx8+LDzqaeecnp5eTnz8vLa5Hil/WqKv/kJEyY4b7vtNuf+/fude/bscf7oRz9y/uxnPzP6y8vLnaGhoc5HHnnEefToUefGjRudAQEBzl//+tctnm9TuNFt9re//c3Zr18/57hx45x/+9vfXPZbNdrbNpOO58rZ/JxOz/q/duDAAWenTp2czz33nPPLL7905uTkOAMCApxvv/22EdMW3w/VZcaMGc7/83/+j3Pr1q3OEydOON9//31nz549nQsWLDBi2nIuLfE/qiFUTLUxL7/8srNPnz5OPz8/55133unct29faw/J8Mc//tEJ1PqaMWOG0+m8PA3lkiVLnKGhoU6TyeQcN26c8/jx46065rrGCzg3bNhgxPzwww/Of//3f3d2797dGRAQ4HzggQdc3ri0tJkzZzr79u3r9PPzc950003OcePGGYVUWxyvtF9N8Tf/3XffOX/2s585u3bt6jSbzc7HHnvM+f3337vE/PnPf3bec889TpPJ5Pw//+f/OJ9//vmWSrHJ3eg227BhQ737rSu1p20mHc/VxZSn/V/78MMPnYMHD3aaTCbngAEDnK+99ppLf1t8P1QXu93ufPLJJ519+vRx+vv7O//lX/7F+cwzz7jcdqEt59JS/6Oux8vpvOI2xyIiIiIiItIgumZKRERERETEDSqmRERERERE3KBiSkRERERExA0qpkRERERERNygYkpERERERMQNKqZERERERETcoGJKRERERETEDSqmRERERERE3KBiSkRERERExA0qpkRERERERNygYkpERERERMQNKqZERERERETcoGJKRERERETEDSqmRERERERE3KBiSkRERERExA0qpkRERERERNygYkpERERERMQNKqZERERERETcoGJKRERERETEDSqmRERERERE3KBiSkRERERExA0qpqTZvfrqq3h5eREdHV1nv5eXV51fYWFhRkxaWppLX0BAAH369OH+++9nw4YNVFRU1Frvo48+6vIYs9nMsGHDWLlyZZ3xItI+1LdPufqroKCAb775Bi8vL1566SUAbr755gY9Njs7u3WTFJEW1Zj9So363v9oP9O+dGrtAUj7l5OTw80338yBAwf46quv6NevX62Y8ePHM336dJe2zp0714pbv349Xbt2paKigr///e/s2LGDmTNnsmbNGrZu3UpERIRLvMlk4vXXXwegvLyc//qv/+I///M/OXjwIBs3bmzCLEWkrfj//r//z2X5t7/9LVartVb7wIED+eGHH1za1qxZw7lz54zljz76iHfeeYfVq1fTs2dPo/2uu+5qhpGLSFvVmP1Kjfre/2g/0844RZrRX/7yFyfgfP/995033XSTMy0trVYM4ExKSrrmen75y186Aec//vGPWn1vv/2209vb2xkdHe3SPmPGDGeXLl1c2qqqqpwjRoxwAs6///3vbmQkIp4mKSnJWd+/uxMnTjgB54svvlhn/4svvugEnCdOnGjGEYqIp7nWfsXpbNj7nxraz3g2neYnzSonJ4fu3bsTHx/PT3/6U3Jycpr8OaZNm8bjjz/O/v37sVqt14z19vZm9OjRAHzzzTdNPhYRERGRlnj/I22DiilpVjk5OUyZMgU/Pz9+9rOf8eWXX3Lw4MFacRcvXuR///d/Xb4ac13TI488AkBeXt51Y7/++msAevTo0eD1i4iIiDRUQ9//iOdTMSXNpqioiC+++IKpU6cCcM8999C7d+86P5154403uOmmm1y+3nnnnQY/1+DBg4F/FkpXqinOvv76a9LT09myZQtDhw6lf//+bmYmIiIiUrfGvP8Rz6cJKKTZ5OTkEBoaypgxY4DLM+E89NBDvP3226xcuRIfHx8jdtKkSSQnJ7s8/tZbb23wc3Xt2hWA77//3qX9/Pnz3HTTTS5td911V60LRkVERESaQmPe/4jnUzElzaKqqoqNGzcyZswYTpw4YbRHR0ezcuVK8vPziY2NNdp79+5NTEyM289XMytOt27dXNr9/f358MMPgcsz+0VGRtK7d2+3n0dERESkPo19/yOeT8WUNIudO3dy8uRJNm7cWOcU5Dk5OU26Mzl69ChArWnXfXx8bqhIExEREWmoln7/I61PxZQ0i5ycHEJCQsjMzKzV9/7777N582aysrLqvJeUO2pO24uLi2uS9YmIiIg0Vku//5HWp2JKmtwPP/zA+++/z4MPPshPf/rTWv3h4eG88847fPDBBzz00EM3/Hy5ubm8/vrrWCwWxo0bd8PrExEREWmsln7/I22Diilpch988AHff/89//qv/1pn/8iRI7npppvIyclp9M7kd7/7HV27dqWyspK///3v7Nixg08//ZRhw4axadOmphi+iIiISKM15/sfabtUTEmTy8nJwd/fn/Hjx9fZ7+3tTXx8PDk5OXz33XeNWvecOXOAyxNL9OzZk+HDh/Pmm2/y8MMPYzKZbnjsIiIiIu5o7Psf3e+yffByOp3O1h6EiIiIiIiIp9FNe0VERERERNygYkpERERERMQNKqZERERERETcoGJKRERERETEDSqmRERERERE3KBiSkRERERExA0d+j5T1dXVfPvtt3Tr1g0vL6/WHo5Iu+F0Ovn+++8JDw/H27vjfWajfYtI89H+RfsXkebizv6lQxdT3377LREREa09DJF2669//Su9e/du7WG0OO1bRJqf9i8i0lwas3/p0MVUt27dgMsbzGw2G+0Oh4O8vDxiY2Px9fVtreG1Sdo29dO2+Se73U5ERITxN9bR1LdvuVJ7eL14eg6ePn7omDlo/1J7/9IRXwdtVXvIoz3kAO7l4c7+pUMXUzWHx81mc61iKiAgALPZ7NEvouagbVM/bZvaOuopKPXtW67UHl4vnp6Dp48fOnYOjdm/pKen8/777/PFF1/QuXNn7rrrLl544QX69+9vxIwePZpdu3a5PO7f/u3fyMrKMpZLS0uZM2cOf/zjH+natSszZswgPT2dTp3++XaqoKCA1NRUSkpKiIiIYPHixTz66KMu683MzOTFF1/EZrMxbNgwXn75Ze68885G5X3l/qUjvw7amvaQR3vIAW4sj8bsXzreycYiIiLSoezatYukpCT27duH1WrF4XAQGxvL+fPnXeJmzZrFyZMnja+MjAyjr6qqivj4eCorK9m7dy9vvfUW2dnZLF261Ig5ceIE8fHxjBkzhuLiYlJSUnj88cfZsWOHEfPuu++SmprKL3/5S/70pz8xbNgw4uLiOHXqVPNvCBFpch36yJSIiIi0f9u3b3dZzs7OJiQkhKKiIkaNGmW0BwQEEBYWVuc68vLyOHbsGB9//DGhoaEMHz6cFStWsHDhQtLS0vDz8yMrK4vIyEhWrlwJwMCBA9mzZw+rV68mLi4OgFWrVjFr1iwee+wxALKysti2bRtvvvkmTz31VHOkLyLNSMWUiIiIdChnz54FIDg42KU9JyeHt99+m7CwMO6//36WLFlCQEAAAIWFhQwZMoTQ0FAjPi4ujjlz5lBSUsJtt91GYWEhMTExLuuMi4sjJSUFgMrKSoqKili0aJHR7+3tTUxMDIWFhXWOtaKigoqKCmPZbrcDl09hcjgcxs9XfvdE7SEHaB95tIccwL083MlZxZSIiIh0GNXV1aSkpHD33XczePBgo/3hhx+mb9++hIeHc/jwYRYuXMjx48d5//33AbDZbC6FFGAs22y2a8bY7XZ++OEHzpw5Q1VVVZ0xX3zxRZ3jTU9PZ9myZbXa8/LyjEKvhtVqbcgmaNPaQw7QPvJoDzlA4/K4cOFCo9evYkpEREQ6jKSkJI4ePcqePXtc2mfPnm38PGTIEHr16sW4ceP4+uuvueWWW1p6mIZFixaRmppqLNfMNhYbG+syAYXVamX8+PEeO2FAe8gB2kce7SEHcC+PmiO/jaFiSkRERDqE5ORktm7dyu7du697D5no6GgAvvrqK2655RbCwsI4cOCAS0xZWRmAcZ1VWFiY0XZljNlspnPnzvj4+ODj41NnTH3XaplMJkwmU612X1/fWm8Q62rzNO0hB2gfebSHHKBxebiTb7PP5vf888/j5eVlnC8McPHiRZKSkujRowddu3YlISGh1o6ltLSU+Ph4AgICCAkJYf78+Vy6dMklpqCggNtvvx2TyUS/fv3Izs5u7nRERETEwzidTpKTk9m8eTM7d+4kMjLyuo8pLi4GoFevXgBYLBaOHDniMuue1WrFbDYzaNAgIyY/P99lPVarFYvFAoCfnx9RUVEuMdXV1eTn5xsxIuJZmrWYOnjwIL/+9a8ZOnSoS/u8efP48MMP2bRpE7t27eLbb79lypQpRn9TTT8qIiIikpSUxNtvv01ubi7dunXDZrNhs9n44YcfAPj6669ZsWIFRUVFfPPNN3zwwQdMnz6dUaNGGe9hYmNjGTRoEI888gh//vOf2bFjB4sXLyYpKck4cvTEE0/wl7/8hQULFvDFF1/w6quv8t577zFv3jxjLKmpqfzmN7/hrbfe4vPPP2fOnDmcP3/emN1PRDxLs53md+7cOaZNm8ZvfvMbnn32WaP97NmzvPHGG+Tm5jJ27FgANmzYwMCBA9m3bx8jR45ssulHpWXc/NS2evu+eT6+BUciIiJt3dX/M0w+TjLuhMFpOzj+3E+a5TnXr18PXL4x75U2bNjAo48+ip+fHx9//DFr1qzh/PnzREREkJCQwOLFi41YHx8ftm7dypw5c7BYLHTp0oUZM2awfPlyIyYyMpJt27Yxb9481q5dS+/evXn99ddd3pc89NBD/OMf/2Dp0qXYbDaGDx/O9u3ba01KISKNd+X+5cp9S0WVV7O9J222YiopKYn4+HhiYmJciqmioiIcDofL1KEDBgygT58+FBYWMnLkyCaZfrQuDZletGb5yu/yT3VtG5OP87rxHYFeN/+kbSAibYnTWf//KYCIiAh27dp13fX07duXjz766Joxo0eP5rPPPrtmTHJyMsnJydd9PhFp+5qlmNq4cSN/+tOfOHjwYK0+m82Gn58fQUFBLu2hoaHXnVq0pu9aMTXTj3bu3LnWczdmelFoP1NCNocrt03GnfXHXe+fTnuk1417U4uKiIiIeJomL6b++te/8uSTT2K1WvH392/q1d+QhkwvCu1nSsjmUNe2GZxW/3VqR9M6zimXet38kztTi4qIiIh4miYvpoqKijh16hS333670VZVVcXu3bt55ZVX2LFjB5WVlZSXl7scnbpyWtCmmH60Lo2ZXvRa7eK6bSqqvK4Z19HoddMxf+8iIiLS8TT5bH7jxo3jyJEjFBcXG18jRoxg2rRpxs++vr4u04IeP36c0tJSY1rQpph+VEREREREpDk1+ZGpbt26MXjwYJe2Ll260KNHD6M9MTGR1NRUgoODMZvNzJ07F4vFwsiRIwHX6UczMjKw2Wx1Tj/6yiuvsGDBAmbOnMnOnTt577332Lat/pnlREREREREmkqzzeZ3LatXr8bb25uEhAQqKiqIi4vj1VdfNfqbavpRERERERGR5tIixVRBQYHLsr+/P5mZmWRmZtb7mKaaflRERERERKQ5NPk1UyIiIiIiIh2BiikRERERERE3qJgSERERERFxg4opERERERERN6iYEhERERERcYOKKRERERERETeomBIREREREXFDq9y0VzzTzU9tw+TjJONOGJy2g4oqr9YekoiIiIhIq9GRKRERERERETeomBIREREREXGDiikR8RhVVVUsWbKEyMhIOnfuzC233MKKFStwOp1GjNPpZOnSpfTq1YvOnTsTExPDl19+6bKe06dPM23aNMxmM0FBQSQmJnLu3DmXmMOHD3Pvvffi7+9PREQEGRkZLZKjiIiIeA5dMyXN6uanttXZ/s3z8S08EmkPXnjhBdavX89bb73FrbfeyqFDh3jssccIDAzkP/7jPwDIyMhg3bp1vPXWW0RGRrJkyRLi4uI4duwY/v7+AEybNo2TJ09itVpxOBw89thjzJ49m9zcXADsdjuxsbHExMSQlZXFkSNHmDlzJkFBQcyePbvV8hcREZG2RcWUiHiMvXv3MmnSJOLjLxfjN998M++88w4HDhwALh+VWrNmDYsXL2bSpEkA/Pa3vyU0NJQtW7YwdepUPv/8c7Zv387BgwcZMWIEAC+//DL33XcfL730EuHh4eTk5FBZWcmbb76Jn58ft956K8XFxaxatUrFlIiIiBh0mp+IeIy77rqL/Px8/vu//xuAP//5z+zZs4eJEycCcOLECWw2GzExMcZjAgMDiY6OprCwEIDCwkKCgoKMQgogJiYGb29v9u/fb8SMGjUKPz8/IyYuLo7jx49z5syZZs9TREREPIOOTImIx3jqqaew2+0MGDAAHx8fqqqqeO6555g2bRoANpsNgNDQUJfHhYaGGn02m42QkBCX/k6dOhEcHOwSExkZWWsdNX3du3d36auoqKCiosJYttvtADgcDhwOR5251LTX1+8JPD0HTx8/eGYOJh+n67K30/jekDw8KVcRaf9UTImIx3jvvffIyckhNzfXOPUuJSWF8PBwZsyY0WrjSk9PZ9myZbXa8/LyCAgIuOZjrVZrcw2rxXh6Dp4+fvCsHDLurLt9xYhqPvroo+s+/sKFC008IhER96mYEhGPMX/+fJ566immTp0KwJAhQ/if//kf0tPTmTFjBmFhYQCUlZXRq1cv43FlZWUMHz4cgLCwME6dOuWy3kuXLnH69Gnj8WFhYZSVlbnE1CzXxFxp0aJFpKamGst2u52IiAhiY2Mxm8115uJwOLBarYwfPx5fX9/GbIY2w9Nz8PTxg2fmMDhth8uyydvJihHVLDnkTdHSCdd9fM2RXxGRtkDFlIh4jAsXLuDt7Xqpp4+PD9XV1QBERkYSFhZGfn6+UTzZ7Xb279/PnDlzALBYLJSXl1NUVERUVBQAO3fupLq6mujoaCPmmWeeweFwGG9QrVYr/fv3r3WKH4DJZMJkMtVq9/X1ve4b3IbEtHWenoOnjx88K4eKKq+626u9GpSDp+QpIh2DJqAQEY9x//3389xzz7Ft2za++eYbNm/ezKpVq3jggQcA8PLyIiUlhWeffZYPPviAI0eOMH36dMLDw5k8eTIAAwcOZMKECcyaNYsDBw7w6aefkpyczNSpUwkPDwfg4Ycfxs/Pj8TEREpKSnj33XdZu3aty9EnERERER2ZEhGP8fLLL7NkyRL+/d//nVOnThEeHs6//du/sXTpUiNmwYIFnD9/ntmzZ1NeXs4999zD9u3bjXtMAeTk5JCcnMy4cePw9vYmISGBdevWGf2BgYHk5eWRlJREVFQUPXv2ZOnSpZoWXURERFyomBIRj9GtWzfWrFnDmjVr6o3x8vJi+fLlLF++vN6Y4OBg4wa99Rk6dCiffPKJu0MVERGRDkCn+YmIiIiIiLhBxZSIiIiIiIgbVEyJiIhIu5aens4dd9xBt27dCAkJYfLkyRw/ftwl5uLFiyQlJdGjRw+6du1KQkJCrVsklJaWEh8fT0BAACEhIcyfP59Lly65xBQUFHD77bdjMpno168f2dnZtcaTmZnJzTffjL+/P9HR0Rw4cKDJcxaRlqFrpsTFzU9ta+0hiIiINKldu3aRlJTEHXfcwaVLl3j66aeJjY3l2LFjdOnSBYB58+axbds2Nm3aRGBgIMnJyUyZMoVPP/0UgKqqKuLj4wkLC2Pv3r2cPHmS6dOn4+vry69+9SsATpw4QXx8PE888QQ5OTnk5+fz+OOP06tXL+Li4gB49913SU1NJSsri+joaNasWUNcXBzHjx8nJCSkdTaQiLhNxZSIiIi0a9u3b3dZzs7OJiQkhKKiIkaNGsXZs2d54403yM3NZezYsQBs2LCBgQMHsm/fPkaOHEleXh7Hjh3j448/JjQ0lOHDh7NixQoWLlxIWloafn5+ZGVlERkZycqVK4HLt2LYs2cPq1evNoqpVatWMWvWLB577DEAsrKy2LZtG2+++SZPPfVUC24VEWkKOs1PREREOpSzZ88Cl2f2BCgqKsLhcBATE2PEDBgwgD59+lBYWAhAYWEhQ4YMITQ01IiJi4vDbrdTUlJixFy5jpqYmnVUVlZSVFTkEuPt7U1MTIwRIyKeRUemREREpMOorq4mJSWFu+++m8GDBwNgs9nw8/MjKCjIJTY0NBSbzWbEXFlI1fTX9F0rxm6388MPP3DmzBmqqqrqjPniiy/qHG9FRQUVFRXGst1uB8DhcOBwOIyfr/zuidpDDtA+8vDkHEw+zn/+7O10+d6QfNzJWcWUiIiIdBhJSUkcPXqUPXv2tPZQGiQ9PZ1ly5bVas/LyyMgIMClzWq1ttSwmk17yAHaRx6emEPGnbXbVoyoBuCjjz667uMvXLjQ6OdUMSUiIiIdQnJyMlu3bmX37t307t3baA8LC6OyspLy8nKXo1NlZWWEhYUZMVfPulcz29+VMVfPAFhWVobZbKZz5874+Pjg4+NTZ0zNOq62aNEiUlNTjWW73U5ERASxsbGYzWbg8qfpVquV8ePH4+vr25hN0ma0hxygfeThyTkMTtth/GzydrJiRDVLDnlTUe3F0bS46z6+5shvY6iYEhERkXbN6XQyd+5cNm/eTEFBAZGRkS79UVFR+Pr6kp+fT0JCAgDHjx+ntLQUi8UCgMVi4bnnnuPUqVPGrHtWqxWz2cygQYOMmKs//bZarcY6/Pz8iIqKIj8/n8mTJwOXTzvMz88nOTm5zrGbTCZMJlOtdl9f31pvdOtq8zTtIQdoH3l4Yg4VVV6126q9qKjyalAu7uSrYkpERETataSkJHJzc/n9739Pt27djGucAgMD6dy5M4GBgSQmJpKamkpwcDBms5m5c+disVgYOXIkALGxsQwaNIhHHnmEjIwMbDYbixcvJikpySh2nnjiCV555RUWLFjAzJkz2blzJ++99x7btv3ztiOpqanMmDGDESNGcOedd7JmzRrOnz9vzO4nIp5FxZSIiIi0a+vXrwdg9OjRLu0bNmzg0UcfBWD16tV4e3uTkJBARUUFcXFxvPrqq0asj48PW7duZc6cOVgsFrp06cKMGTNYvny5ERMZGcm2bduYN28ea9eupXfv3rz++uvGtOgADz30EP/4xz9YunQpNpuN4cOHs3379lqTUoiIZ1AxJSIiIu2a0+m8boy/vz+ZmZlkZmbWG9O3b9/rXsQ+evRoPvvss2vGJCcn13tan4h4Ft1nSkRERERExA0qpkRERERERNygYkpERERERMQNKqZERERERETcoGJKRERERETEDU1eTK1fv56hQ4diNpsxm81YLBb+8Ic/GP0XL14kKSmJHj160LVrVxISEmrdCby0tJT4+HgCAgIICQlh/vz5XLp0ySWmoKCA22+/HZPJRL9+/cjOzm7qVEREREREROrV5MVU7969ef755ykqKuLQoUOMHTuWSZMmUVJSAsC8efP48MMP2bRpE7t27eLbb79lypQpxuOrqqqIj4+nsrKSvXv38tZbb5Gdnc3SpUuNmBMnThAfH8+YMWMoLi4mJSWFxx9/nB07djR1OiIiIiIiInVq8vtM3X///S7Lzz33HOvXr2ffvn307t2bN954g9zcXMaOHQtcvmHewIED2bdvHyNHjiQvL49jx47x8ccfExoayvDhw1mxYgULFy4kLS0NPz8/srKyiIyMZOXKlQAMHDiQPXv2sHr1apcb44mIiIiIiDSXZr1mqqqqio0bN3L+/HksFgtFRUU4HA5iYmKMmAEDBtCnTx8KCwsBKCwsZMiQIS53Ao+Li8NutxtHtwoLC13WURNTsw4REREREZHm1uRHpgCOHDmCxWLh4sWLdO3alc2bNzNo0CCKi4vx8/MjKCjIJT40NBSbzQaAzWZzKaRq+mv6rhVjt9v54Ycf6Ny5c53jqqiooKKiwli22+0AOBwOHA6H0V7z85VtHYXJ59p3iTd5O12+u6s9btuO/Lq5mraBiIiIdATNUkz179+f4uJizp49y+9+9ztmzJjBrl27muOpGiU9PZ1ly5bVas/LyyMgIKBWu9VqbYlhtSkZdzYsbsWI6ht6no8++uiGHt+WdcTXzdUuXLjQ2kMQERERaXbNUkz5+fnRr18/AKKiojh48CBr167loYceorKykvLycpejU2VlZYSFhQEQFhbGgQMHXNZXM9vflTFXzwBYVlaG2Wyu96gUwKJFi0hNTTWW7XY7ERERxMbGYjabjXaHw4HVamX8+PH4+vq6sQU81+C0a0/iYfJ2smJENUsOeVNR7eX28xxNa3/XtnXk183Vao76ioiIiLRnzVJMXa26upqKigqioqLw9fUlPz+fhIQEAI4fP05paSkWiwUAi8XCc889x6lTpwgJCQEuf9JvNpsZNGiQEXP1kQ2r1Wqsoz4mkwmTyVSr3dfXt843v/W1t2cVVQ0rkCqqvRocW5f2vF074uvmah09fxEREekYmryYWrRoERMnTqRPnz58//335ObmUlBQwI4dOwgMDCQxMZHU1FSCg4Mxm83MnTsXi8XCyJEjAYiNjWXQoEE88sgjZGRkYLPZWLx4MUlJSUYh9MQTT/DKK6+wYMECZs6cyc6dO3nvvffYtm1bU6fTbt38lLaViIiIiMiNaPJi6tSpU0yfPp2TJ08SGBjI0KFD2bFjB+PHjwdg9erVeHt7k5CQQEVFBXFxcbz66qvG4318fNi6dStz5szBYrHQpUsXZsyYwfLly42YyMhItm3bxrx581i7di29e/fm9ddf17ToIiIiIiLSYpq8mHrjjTeu2e/v709mZiaZmZn1xvTt2/e6ExSMHj2azz77zK0xioiIiIiI3Khmvc+UiIiIiIhIe6ViSkRERERExA0qpkRERERERNygYkpERERERMQNKqZERERERETcoGJKRDzK3//+d37+85/To0cPOnfuzJAhQzh06JDR73Q6Wbp0Kb169aJz587ExMTw5Zdfuqzj9OnTTJs2DbPZTFBQEImJiZw7d84l5vDhw9x77734+/sTERFBRkZGi+QnIiIinkPFlIh4jDNnznD33Xfj6+vLH/7wB44dO8bKlSvp3r27EZORkcG6devIyspi//79dOnShbi4OC5evGjETJs2jZKSEqxWK1u3bmX37t3Mnj3b6Lfb7cTGxtK3b1+Kiop48cUXSUtL47XXXmvRfEVERKRta/L7TImINJcXXniBiIgINmzYYLRFRkYaPzudTtasWcPixYuZNGkSAL/97W8JDQ1ly5YtTJ06lc8//5zt27dz8OBBRowYAcDLL7/Mfffdx0svvUR4eDg5OTlUVlby5ptv4ufnx6233kpxcTGrVq1yKbpERESkY9ORKRHxGB988AEjRozgwQcfJCQkhNtuu43f/OY3Rv+JEyew2WzExMQYbYGBgURHR1NYWAhAYWEhQUFBRiEFEBMTg7e3N/v37zdiRo0ahZ+fnxETFxfH8ePHOXPmTHOnKSIiIh5CR6ZExGP85S9/Yf369aSmpvL0009z8OBB/uM//gM/Pz9mzJiBzWYDIDQ01OVxoaGhRp/NZiMkJMSlv1OnTgQHB7vEXHnE68p12mw2l9MKASoqKqioqDCW7XY7AA6HA4fDUWcuNe319XsCT8/B08cPnpmDycfpuuztNL43JA9PylVE2j8VUyLiMaqrqxkxYgS/+tWvALjttts4evQoWVlZzJgxo9XGlZ6ezrJly2q15+XlERAQcM3HWq3W5hpWi/H0HDx9/OBZOWTcWXf7ihHVfPTRR9d9/IULF5p4RCIi7lMxJSIeo1evXgwaNMilbeDAgfzXf/0XAGFhYQCUlZXRq1cvI6asrIzhw4cbMadOnXJZx6VLlzh9+rTx+LCwMMrKylxiapZrYq60aNEiUlNTjWW73U5ERASxsbGYzeY6c3E4HFitVsaPH4+vr+91c2+LPD0HTx8/eGYOg9N2uCybvJ2sGFHNkkPeFC2dcN3H1xz5FRFpC1RMiYjHuPvuuzl+/LhL23//93/Tt29f4PJkFGFhYeTn5xvFk91uZ//+/cyZMwcAi8VCeXk5RUVFREVFAbBz506qq6uJjo42Yp555hkcDofxBtVqtdK/f/9ap/gBmEwmTCZTrXZfX9/rvsFtSExb5+k5ePr4wbNyqKjyqru92qtBOXhKniLSMWgCChHxGPPmzWPfvn386le/4quvviI3N5fXXnuNpKQkALy8vEhJSeHZZ5/lgw8+4MiRI0yfPp3w8HAmT54MXD6SNWHCBGbNmsWBAwf49NNPSU5OZurUqYSHhwPw8MMP4+fnR2JiIiUlJbz77rusXbvW5eiTiIiIiI5MtQM3P7WtzvZvno9v4ZGINK877riDzZs3s2jRIpYvX05kZCRr1qxh2rRpRsyCBQs4f/48s2fPpry8nHvuuYft27fj7+9vxOTk5JCcnMy4cePw9vYmISGBdevWGf2BgYHk5eWRlJREVFQUPXv2ZOnSpZoWXURERFzoyJSIeJSf/OQnHDlyhIsXL/L5558za9Ysl34vLy+WL1+OzWbj4sWLfPzxx/z4xz92iQkODiY3N5fvv/+es2fP8uabb9K1a1eXmKFDh/LJJ59w8eJF/va3v7Fw4cJmz01Emsfu3bu5//77CQ8Px8vLiy1btrj0P/roo3h5ebl8TZjgev3W6dOnmTZtGmazmaCgIBITEzl37pxLzOHDh7n33nvx9/cnIiKCjIyMWmPZtGkTAwYMwN/fnyFDhjRo0g0RabtUTImIiEi7dv78eYYNG0ZmZma9MRMmTODkyZPG1zvvvOPSP23aNEpKSrBarWzdupXdu3e7HK222+3ExsbSt29fioqKePHFF0lLS+O1114zYvbu3cvPfvYzEhMT+eyzz5g8eTKTJ0/m6NGjTZ+0iLQIneYnIiIi7drEiROZOHHiNWNMJlOds3UCfP7552zfvp2DBw8aN/x++eWXue+++3jppZcIDw8nJyeHyspK3nzzTfz8/Lj11lspLi5m1apVRtG1du1aJkyYwPz58wFYsWIFVquVV155haysrCbMWERaioopERER6fAKCgoICQmhe/fujB07lmeffZYePXoAUFhYSFBQkFFIAcTExODt7c3+/ft54IEHKCwsZNSoUfj5+RkxcXFxvPDCC5w5c4bu3btTWFhYayKbuLi4WqcdXqkhNwX3xJs3X6095ADtIw9PzuHKm4JfeUNwaFg+7uSsYkpEREQ6tAkTJjBlyhQiIyP5+uuvefrpp5k4cSKFhYX4+Phgs9kICQlxeUynTp0IDg7GZrMBYLPZiIyMdIkJDQ01+rp3747NZjParoypWUddGnNTcE+6eXN92kMO0D7y8MQc6rop+IoR1QDNdlNwFVMiIiLSoU2dOtX4eciQIQwdOpRbbrmFgoICxo0b14oja9hNwT3x5s1Xaw85QPvIw5NzuPKm4FfeELyi2oujaXHXfbw7NwVXMSUiIiJyhX/5l3+hZ8+efPXVV4wbN46wsDBOnTrlEnPp0iVOnz5tXGcVFhZGWVmZS0zN8vVi6rtWCxp3U3BPunlzfdpDDtA+8vDEHOq6KXhFtRcVVc13U3AVU+1YffefEhERkfr97W9/47vvvqNXr14AWCwWysvLKSoqIioqCoCdO3dSXV1NdHS0EfPMM8/gcDiMN2RWq5X+/fvTvXt3IyY/P5+UlBTjuaxWKxaLpQWzE5GmpKnRRUREpF07d+4cxcXFFBcXA3DixAmKi4spLS3l3LlzzJ8/n3379vHNN9+Qn5/PpEmT6NevH3Fxl08LGjhwIBMmTGDWrFkcOHCATz/9lOTkZKZOnUp4eDgADz/8MH5+fiQmJlJSUsK7777L2rVrXU7Re/LJJ9m+fTsrV67kiy++IC0tjUOHDpGcnNzi20REmoaKKREREWnXDh06xG233cZtt90GQGpqKrfddhtLly7Fx8eHw4cP86//+q/8+Mc/JjExkaioKD755BOX0+tycnIYMGAA48aN47777uOee+5xuYdUYGAgeXl5nDhxgqioKH7xi1+wdOlSl3tR3XXXXeTm5vLaa68xbNgwfve737FlyxYGDx7cchtDRJqUTvMTERGRdm306NE4nc56+3fs2FFvX43g4GByc3OvGTN06FA++eSTa8Y8+OCDPPjgg9d9PhHxDCqmPISufxIRERERaVt0mp+IiIiIiIgbVEyJiIiIiIi4QcWUiIiIiIiIG1RMiYiIiIiIuEHFlIiIiIiIiBtUTImIiIiIiLhBxZSIiIiIiIgbVEyJiIiIiIi4QcWUiIiIiIiIG1RMiYiIiIiIuEHFlIiIiIiIiBtUTImIiIiIiLihyYup9PR07rjjDrp160ZISAiTJ0/m+PHjLjEXL14kKSmJHj160LVrVxISEigrK3OJKS0tJT4+noCAAEJCQpg/fz6XLl1yiSkoKOD222/HZDLRr18/srOzmzodERERERGROjV5MbVr1y6SkpLYt28fVqsVh8NBbGws58+fN2LmzZvHhx9+yKZNm9i1axfffvstU6ZMMfqrqqqIj4+nsrKSvXv38tZbb5Gdnc3SpUuNmBMnThAfH8+YMWMoLi4mJSWFxx9/nB07djR1SiIiIiIiIrV0auoVbt++3WU5OzubkJAQioqKGDVqFGfPnuWNN94gNzeXsWPHArBhwwYGDhzIvn37GDlyJHl5eRw7doyPP/6Y0NBQhg8fzooVK1i4cCFpaWn4+fmRlZVFZGQkK1euBGDgwIHs2bOH1atXExcX19RpiYiIiIiIuGj2a6bOnj0LQHBwMABFRUU4HA5iYmKMmAEDBtCnTx8KCwsBKCwsZMiQIYSGhhoxcXFx2O12SkpKjJgr11ETU7MOERERERGR5tTkR6auVF1dTUpKCnfffTeDBw8GwGaz4efnR1BQkEtsaGgoNpvNiLmykKrpr+m7VozdbueHH36gc+fOtcZTUVFBRUWFsWy32wFwOBw4HA6jvebnK9tam8nH2dpDAMDk7XT57q62tG2bSlt83bQWbQMRERHpCJq1mEpKSuLo0aPs2bOnOZ+mwdLT01m2bFmt9ry8PAICAmq1W63WlhhWg2Tc2dojcLViRPUNPf6jjz5qopG0PW3pddNaLly40NpDEBEREWl2zVZMJScns3XrVnbv3k3v3r2N9rCwMCorKykvL3c5OlVWVkZYWJgRc+DAAZf11cz2d2XM1TMAlpWVYTab6zwqBbBo0SJSU1ONZbvdTkREBLGxsZjNZqPd4XBgtVoZP348vr6+bmTf9AantY2JNUzeTlaMqGbJIW8qqr3cXs/RtPZ3XVtbfN20lpqjviIiIiLtWZMXU06nk7lz57J582YKCgqIjIx06Y+KisLX15f8/HwSEhIAOH78OKWlpVgsFgAsFgvPPfccp06dIiQkBLj8ab/ZbGbQoEFGzNVHN6xWq7GOuphMJkwmU612X1/fOt/81tfeGiqq3C9cmkNFtdcNjamtbNfm0JZeN62lo+cvIiIiHUOTF1NJSUnk5uby+9//nm7duhnXOAUGBtK5c2cCAwNJTEwkNTWV4OBgzGYzc+fOxWKxMHLkSABiY2MZNGgQjzzyCBkZGdhsNhYvXkxSUpJRDD3xxBO88sorLFiwgJkzZ7Jz507ee+89tm3b1tQpiYiIiIiI1NLks/mtX7+es2fPMnr0aHr16mV8vfvuu0bM6tWr+clPfkJCQgKjRo0iLCyM999/3+j38fFh69at+Pj4YLFY+PnPf8706dNZvny5ERMZGcm2bduwWq0MGzaMlStX8vrrr2tadBERERERaRHNcprf9fj7+5OZmUlmZma9MX379r3uJAWjR4/ms88+a/QYpfXd/FT9RxC/eT6+BUciIiIiIuKeZr/PlIhIc3j++efx8vIiJSXFaLt48SJJSUn06NGDrl27kpCQUGuimtLSUuLj4wkICCAkJIT58+dz6dIll5iCggJuv/12TCYT/fr1Izs7uwUyEhEREU+jYkpEPM7Bgwf59a9/zdChQ13a582bx4cffsimTZvYtWsX3377LVOmTDH6q6qqiI+Pp7Kykr179/LWW2+RnZ3N0qVLjZgTJ04QHx/PmDFjKC4uJiUlhccff5wdO9rGjJoiIiLSdqiYEhGPcu7cOaZNm8ZvfvMbunfvbrSfPXuWN954g1WrVjF27FiioqLYsGEDe/fuZd++fcDle8odO3aMt99+m+HDhzNx4kRWrFhBZmYmlZWVAGRlZREZGcnKlSsZOHAgycnJ/PSnP2X16tWtkq+IiIi0XSqmRMSjJCUlER8fT0xMjEt7UVERDofDpX3AgAH06dOHwsJCAAoLCxkyZAihoaFGTFxcHHa7nZKSEiPm6nXHxcUZ6xARERGp0Ww37RURaWobN27kT3/6EwcPHqzVZ7PZ8PPzc7kZOEBoaKhxiwabzeZSSNX01/RdK8Zut/PDDz/UeVPwiooKKioqjOWamxY7HA4cDkedudS019fvCTw9B08fP3hmDiYf14mqTN5O43tD8vCkXEWk/VMxJSIe4a9//StPPvkkVqsVf3//1h6Oi/T0dJYtW1arPS8vj4CAgGs+1mq1NtewWoyn5+Dp4wfPyiHjzrrbV4yovu4svgAXLlxo4hGJiLhPxZSIeISioiJOnTrF7bffbrRVVVWxe/duXnnlFXbs2EFlZSXl5eUuR6fKysoICwsDICwsjAMHDrist2a2vytjrp4BsKysDLPZXOdRKYBFixaRmppqLNvtdiIiIoiNjcVsNtf5GIfDgdVqZfz48fj6+jZwK7Qtnp6Dp48fmjaHwWn1T7JyNK3p7uF49fOYvJ2sGFHNkkPeFC2dcN3H1xz5bYzdu3fz4osvUlRUxMmTJ9m8eTOTJ082+p1OJ7/85S/5zW9+Q3l5OXfffTfr16/nRz/6kRFz+vRp5s6dy4cffoi3tzcJCQmsXbuWrl27GjGHDx8mKSmJgwcPctNNNzF37lwWLFjgMpZNmzaxZMkSvvnmG370ox/xwgsvcN999zU6JxFpG1RMiYhHGDduHEeOHHFpe+yxxxgwYAALFy4kIiICX19f8vPzSUhIAOD48eOUlpZisVgAsFgsPPfcc5w6dYqQkBDg8if6ZrOZQYMGGTFXfzputVqNddTFZDJhMplqtfv6+l73DW5DYto6T8/B08cPTZNDRZXXNdffVOp7nopqrwY9jztjOX/+PMOGDWPmzJkuM3zWyMjIYN26dbz11ltERkayZMkS4uLiOHbsmHEkfNq0aZw8eRKr1YrD4eCxxx5j9uzZ5ObmApeLvNjYWGJiYsjKyuLIkSPMnDmToKAgZs+eDcDevXv52c9+Rnp6Oj/5yU/Izc1l8uTJ/OlPf2Lw4MGNzktEWp+KKRHxCN26dav1ZqNLly706NHDaE9MTCQ1NZXg4GDMZjNz587FYrEwcuRIAGJjYxk0aBCPPPIIGRkZ2Gw2Fi9eTFJSklEMPfHEE7zyyissWLCAmTNnsnPnTt577z22bav/RtMi0rZNnDiRiRMn1tnndDpZs2YNixcvZtKkSQD89re/JTQ0lC1btjB16lQ+//xztm/fzsGDBxkxYgQAL7/8Mvfddx8vvfQS4eHh5OTkUFlZyZtvvomfnx+33norxcXFrFq1yiim1q5dy4QJE5g/fz4AK1aswGq18sorr5CVldUCW0JEmppm8xORdmP16tX85Cc/ISEhgVGjRhEWFsb7779v9Pv4+LB161Z8fHywWCz8/Oc/Z/r06SxfvtyIiYyMZNu2bVitVoYNG8bKlSt5/fXXiYtrutOcRKTtOHHiBDabzWUWz8DAQKKjo11mAg0KCjIKKYCYmBi8vb3Zv3+/ETNq1Cj8/PyMmLi4OI4fP86ZM2eMGM0WKtK+6MiUiHisgoICl2V/f38yMzPJzMys9zF9+/a97kXuo0eP5rPPPmuKIYpIG1czk2dds3heOctnzanBNTp16kRwcLBLTGRkZK111PR179693tlCa9ZRl4bMFuqJszperT3kAO0jD0/O4crZQq+cKRQalo87OauYEhEREWmjGjNbqCfN6lif9pADtI88PDGHumYLXTGiGqDZZgtVMSUiIiIdVs1MnmVlZfTq1ctoLysrY/jw4UbMqVOnXB536dIlTp8+fd2ZQK98jvpiavrr0pDZQjUzZdvRHvLw5ByunC30yplCK6q9GjQrqTuzhaqYEhERkQ4rMjKSsLAw8vPzjeLJbrezf/9+5syZA1ye5bO8vJyioiKioqIA2LlzJ9XV1URHRxsxzzzzDA6Hw3gDarVa6d+/P927dzdi8vPzSUlJMZ6/KWcL1cyUbUd7yMMTc6hrttCKai8qqppvtlBNQCEiIiLt2rlz5yguLqa4uBi4POlEcXExpaWleHl5kZKSwrPPPssHH3zAkSNHmD59OuHh4ca9qAYOHMiECROYNWsWBw4c4NNPPyU5OZmpU6cSHh4OwMMPP4yfnx+JiYmUlJTw7rvvsnbtWpejSk8++STbt29n5cqVfPHFF6SlpXHo0CGSk5NbepOISBPRkSkRERFp1w4dOsSYMWOM5ZoCZ8aMGWRnZ7NgwQLOnz/P7NmzKS8v55577mH79u3GPaYAcnJySE5OZty4ccZNe9etW2f0BwYGkpeXR1JSElFRUfTs2ZOlS5ca06ID3HXXXeTm5rJ48WKefvppfvSjH7FlyxbdY0rEg6mYEhERkXZt9OjROJ3Oevu9vLxYvny5y20SrhYcHGzcoLc+Q4cO5ZNPPrlmzIMPPsiDDz547QGLiMdQMdWG3PyUbgoqIiIiIuIpdM2UiIiIiIiIG1RMiYiIiIiIuEHFlIiIiIiIiBtUTImIiIiIiLhBE1CIiIjINdU3QdI3z8e38EhERNoWHZkSERERERFxg45MtQJNgS4iIiIi4vl0ZEpERERERMQNOjIlIiIibrnWmRa6nkpEOgIdmRIREREREXGDiikRERERERE36DQ/aXM0Ba+IiIiIeAIdmRIREREREXGDiikRERERERE3qJgSERERERFxg4opERERERERN2gCimZyrXtviIiIiIiI59ORKRERERERETeomBIREREREXGDiikRERERERE3qJgSERERERFxg4opERERERERNzR5MbV7927uv/9+wsPD8fLyYsuWLS79TqeTpUuX0qtXLzp37kxMTAxffvmlS8zp06eZNm0aZrOZoKAgEhMTOXfunEvM4cOHuffee/H39yciIoKMjIymTkVERERERKReTV5MnT9/nmHDhpGZmVlnf0ZGBuvWrSMrK4v9+/fTpUsX4uLiuHjxohEzbdo0SkpKsFqtbN26ld27dzN79myj3263ExsbS9++fSkqKuLFF18kLS2N1157ranTERERERERqVOT32dq4sSJTJw4sc4+p9PJmjVrWLx4MZMmTQLgt7/9LaGhoWzZsoWpU6fy+eefs337dg4ePMiIESMAePnll7nvvvt46aWXCA8PJycnh8rKSt588038/Py49dZbKS4uZtWqVS5Fl4iISEd0rXsdfvN8fAuORESkfWvRm/aeOHECm81GTEyM0RYYGEh0dDSFhYVMnTqVwsJCgoKCjEIKICYmBm9vb/bv388DDzxAYWEho0aNws/Pz4iJi4vjhRde4MyZM3Tv3r3O56+oqKCiosJYttvtADgcDhwOh9Fe8/OVbY1l8nG6/di2zOTtdPnekm7k99ESmuJ1015oG4iIiEhH0KLFlM1mAyA0NNSlPTQ01Oiz2WyEhIS49Hfq1Ing4GCXmMjIyFrrqOmrr5hKT09n2bJltdrz8vIICAio1W61WhuSVp0y7nT7oR5hxYjqFn/Ojz76qMWf0x038rppLy5cuNDaQxCRelzrqJWIiDROixZTrW3RokWkpqYay3a7nYiICGJjYzGbzUa7w+HAarUyfvx4fH193XquwWk7bni8bZHJ28mKEdUsOeRNRbVXiz730bS4Fn2+xmqK1017UXPUt6mlp6fz/vvv88UXX9C5c2fuuusuXnjhBfr372/EXLx4kV/84hds3LiRiooK4uLiePXVV10+xCktLWXOnDn88Y9/pGvXrsyYMYP09HQ6dfrnLrGgoIDU1FRKSkqIiIhg8eLFPProo82Sl4iIiHimFi2mwsLCACgrK6NXr15Ge1lZGcOHDzdiTp065fK4S5cucfr0aePxYWFhlJWVucTULNfE1MVkMmEymWq1+/r61vnmt772hqioatlCo6VVVHu1eI6eUqDcyOumvWiu/Hft2kVSUhJ33HEHly5d4umnnyY2NpZjx47RpUsXAObNm8e2bdvYtGkTgYGBJCcnM2XKFD799FMAqqqqiI+PJywsjL1793Ly5EmmT5+Or68vv/rVr4DLpyTHx8fzxBNPkJOTQ35+Po8//ji9evUiLq5tF/UiIiLSclr0PlORkZGEhYWRn59vtNntdvbv34/FYgHAYrFQXl5OUVGREbNz506qq6uJjo42Ynbv3u1yXYbVaqV///71nuInIp5v+/btPProo9x6660MGzaM7OxsSktLjf3F2bNneeONN1i1ahVjx44lKiqKDRs2sHfvXvbt2wdcPq332LFjvP322wwfPpyJEyeyYsUKMjMzqaysBCArK4vIyEhWrlzJwIEDSU5O5qc//SmrV69utdxFRESk7WnyYurcuXMUFxdTXFwMXP6Et7i4mNLSUry8vEhJSeHZZ5/lgw8+4MiRI0yfPp3w8HAmT54MwMCBA5kwYQKzZs3iwIEDfPrppyQnJzN16lTCw8MBePjhh/Hz8yMxMZGSkhLeffdd1q5d63IKn4i0f2fPngUgODgYgKKiIhwOh8skNwMGDKBPnz4UFhYCUFhYyJAhQ1xO+4uLi8Nut1NSUmLEXLmOmpiadVytoqICu93u8gX/nNymvq+GxLT1L0/PwdPHX18OJh9nq3/VN95asVdMbNSYnJtaWloaXl5eLl8DBgww+i9evEhSUhI9evSga9euJCQk1DpLprS0lPj4eAICAggJCWH+/PlcunTJJaagoIDbb78dk8lEv379yM7ObpZ8RKRlNPlpfocOHWLMmDHGck2BM2PGDLKzs1mwYAHnz59n9uzZlJeXc88997B9+3b8/f2Nx+Tk5JCcnMy4cePw9vYmISGBdevWGf2BgYHk5eWRlJREVFQUPXv2ZOnSpZoWXaQDqa6uJiUlhbvvvpvBgwcDlyeg8fPzIygoyCX2/2/v7uOiqvP//z9BYBR1wCuuVjQy14sULU2izCgV9MNWtn7cUktzzbIPVkqbLvsrQ93C1TXTUqlt03bTNd1Pmmmp4xVmoiZBhqkfNc1KwV1NUVQY4Xz/6McsI9cnYGbwcb/duMmc8z5nXq85cJwn52KuvclNeTfBKZlX2Zi8vDxdvnxZTZo0cZpX05vblNYQblji6T14ev1S2R7c4SZIFd00qKLaZvQurtaNhuryBjc333yzNm3a5Hhc+jpKTiEGUJ5aD1MxMTEyjIpvm+3l5aXp06dr+vTpFY5p2bKlli1bVunzREZG6tNPPzVdJwDPlpCQoOzsbO3YscPVpVT75jal2e2ef8MST+/B0+uXKu7BHW6CVNFNg66trfSNjTKmDqpyvXV1gxvpp/BU3rXXJacQL1u2TPfee68kafHixerSpYt27dql22+/3XEK8aZNmxQcHKyePXtqxowZmjJlipKTk+Xn5+d0CrH009k4O3bs0Ny5cwlTgIe6ru7mB6BhmDBhgtauXavt27erbdu2jukhISEqLCzUuXPnnI5O5ebmOt3AZs+ePU7ru/YGNhXd5MZqtZY5KiXV/OY2NR3j7jy9B0+vXyrbgzvcBKmi17Si2gqKvaq1HepyWx0+fFhhYWFq3LixoqOjlZKSonbt2lV5CvHtt99e4SnETz31lPbv369bbrmlwlOIJ06cWGc9AahbhCkAHsMwDD399NNatWqVtm3bVubz5nr16iVfX19t3rxZQ4cOlSQdOnRIJ06ccLrJzcsvv6zTp087PtPOZrPJarWqa9eujjHXnm5ks9kc6wDQ8ERFRWnJkiXq1KmTTp06pWnTpumuu+5Sdna2y04hln66JrOgoMDx+NprMku+L/2vJ2oIPUgNow9P7sHS6D9nx5W+HlOqXj9meiZMwWNU9kGTx2fG12MlcJWEhAQtW7ZMH374oZo3b+54gxIQEKAmTZooICBAY8eOVWJiolq2bCmr1aqnn35a0dHRuv322yVJsbGx6tq1qx599FHNmjVLOTk5euGFF5SQkOA4ujR+/Hi98cYbmjx5sn77299qy5YtWrFihdat48NOgYZq8ODBju8jIyMVFRWl9u3ba8WKFeWGnPpSk2syG+L1f56qIfThiT2Ud03mjN7Fkiq+jrM0M9dkEqbQIFQWtCpCAPM8ixYtkvTTtZmlLV682PGBunPnznXcuKb0h/aWaNSokdauXaunnnpK0dHRatq0qUaPHu10HWdERITWrVunSZMmad68eWrbtq3efvttrmmA2+mWvEGz+vz0rzuc2teQBAYG6pe//KWOHDmigQMHuuQUYql612Q25Ov/PE1D6MOTeyh9TWbp6zELir0qvI6zNDPXZBKmAHiMym5uU6Jx48ZasGCBFixYUOGY9u3bV/kXqpiYGGVmZta4RgANw8WLF3X06FE9+uijLj2FuCbXZDbE6/88VUPowxN7KO+PSgXFXiooqrtrMuv1Q3sBAADc0e9+9zulpaXp+PHj2rlzpx588EE1atRIw4cPdzqFeOvWrcrIyNCYMWMqPIX4yy+/1IYNG8o9hfibb77R5MmTdfDgQS1cuFArVqzQpEmTXNk6gJ+BI1MAAOC69/3332v48OE6c+aM2rRpo759+2rXrl1q06aNJE4hBlA+whQAALjuLV++vNL5nEIMoDyEKQAATOAOowAAwhQAAJUwc7dQAMD1gRtQAAAAAIAJhCkAAAAAMIEwBQAAAAAmEKYAAAAAwATCFAAAAACYQJgCAAAAABMIUwAAAABgAmEKAAAAAEzgQ3sBAECt48OOAVwPODIFAAAAACZwZAoAcN1z56MoldVmaVSPhQAAyiBMAQBQyyoKQMdnxtdzJQCAukSYwnWLNzsAAAD4ObhmCgAAAABMIEwBAAAAgAmEKQAAAAAwgWumAADXjdLXSloaGZrVR+qWvEGSV70//7W4XhMAPA9hCqgBbloBAACAEoQp4Bru/HkzAAAAcB+EKQBAg8IfRAAA9YUw9TPxnzYAoDbw/wkAeB7CFFALbvj9OqeL2QuK/nMxO9dTAQAANEzcGh0AAAAATCBMAQAAAIAJhCkAAAAAMIFrpgAAHokbNgDA9cmd9v+EKQAAAAA/W22GHE+5gRdhCgAAAICTa+9OXN/c6ehTZQhT1eApGxPuqaKfH0/5iwvgSux/AXiCkn1VRR+TUh8qe1/Be5G64/FhasGCBZo9e7ZycnLUo0cPvf766+rTp4+rywLQALB/qR8EJlyP2L94JnfeX5mprbxlSgIhqsejw9T777+vxMREpaamKioqSq+99pri4uJ06NAhBQUFubo8AB6M/QuAusL+xb25c2CC+/HoMPXqq69q3LhxGjNmjCQpNTVV69at0zvvvKPf//73Lq4OqFxlO2sOu7se+xdzeBMCVI39i3tgf4Xa4LFhqrCwUBkZGUpKSnJM8/b21oABA5Senl7uMgUFBSooKHA8Pn/+vCTp7Nmzstvtjul2u12XLl3SmTNn5OvrK5+r+XXUhefxKTZ06VKxfOzeKip23UWJ7qg2X5ubfreixsvsTur/s56zNl24cEGSZBiGiysxp6b7l+ruW0q7dj/jaaJSNsvibeiFW4rV8//7QAX//8+8J/2n0hD2Zw2thzNnzlQ5nv1L2f2Lp+9PpJ/fQ1TK5hovUxf7q4b2O+mpPUhl+6ir/Ysn/b/n5N///reKiooUHBzsND04OFgHDx4sd5mUlBRNmzatzPSIiIg6qbGhGuHqAtyYK1+b1nNc+OQVuHDhggICAlxdRo3VdP9yPe9bPH1/4On1Sw2rh9azq78M+5eGv3/xVA3pd9LTle6jJu+TarJ/8dgwZUZSUpISExMdj4uLi3X27Fm1atVKXl7/Sd55eXkKDw/Xd999J6vV6opS3RavTcV4bf7DMAxduHBBYWFhri6lXlR331JaQ/h58fQePL1+6frsgf1L2f3L9fhz4K4aQh8NoQfJXB9m9i8eG6Zat26tRo0aKTc312l6bm6uQkJCyl3GYrHIYrE4TQsMDKzwOaxWq0f/ENUlXpuK8dr8xBP/YlyipvuXmu5bSmsIPy+e3oOn1y9dfz2wfwksd93X28+BO2sIfTSEHqSa91HT/Yt3TQtyF35+furVq5c2b/7PObLFxcXavHmzoqOjXVgZAE/H/gVAXWH/AjQsHntkSpISExM1evRo9e7dW3369NFrr72m/Px8x91xAMAs9i8A6gr7F6Dh8Ogw9dBDD+lf//qXpk6dqpycHPXs2VPr168vc1FnTVksFr300ktlDquD16YyvDYNS13tX0o0hJ8XT+/B0+uX6MFT1fb+pSG8hg2hB6lh9NEQepDqrw8vw1PvLQoAAAAALuSx10wBAAAAgCsRpgAAAADABMIUAAAAAJhAmAIAAAAAEwhTpaSkpOi2225T8+bNFRQUpCFDhujQoUOuLsvtzJw5U15eXpo4caKrS3EbP/zwgx555BG1atVKTZo0Uffu3bV3715Xl4U6tn37dt13330KCwuTl5eXVq9e7TTfMAxNnTpVoaGhatKkiQYMGKDDhw87jTl79qxGjhwpq9WqwMBAjR07VhcvXnQas2/fPt11111q3LixwsPDNWvWLLfp4fjx4xo7dqwiIiLUpEkTdejQQS+99JIKCwudxnh5eZX52rVrl8vrl6QbbrihTG0zZ850GuPO22Dbtm3lvr5eXl76/PPPJdXtNqhODx988IFiY2PVqlUreXl5KSsrq8w6rly5ooSEBLVq1UrNmjXT0KFDy3yw7YkTJxQfHy9/f38FBQXp+eef19WrV2ulB3eTnJxcZnt17tzZMf+tt95STEyMrFarvLy8dO7cuTLrqM7+xVU9nD17Vk8//bQ6deqkJk2aqF27dnrmmWd0/vx5p3W4wzavals8+eST6tChg5o0aaI2bdrogQce0MGDB92qj6p6KGEYhgYPHlzu77Gre5Cq7iMmJqbM/PHjx9dpH4SpUtLS0pSQkKBdu3bJZrPJbrcrNjZW+fn5ri7NbXz++ed68803FRkZ6epS3MaPP/6oO++8U76+vvrkk0/09ddfa86cOWrRooWrS0Mdy8/PV48ePbRgwYJy58+aNUvz589Xamqqdu/eraZNmyouLk5XrlxxjBk5cqT2798vm82mtWvXavv27XriiScc8/Py8hQbG6v27dsrIyNDs2fPVnJyst566y236OHgwYMqLi7Wm2++qf3792vu3LlKTU3VH/7whzLr2rRpk06dOuX46tWrl8vrLzF9+nSn2p5++mnHPHffBnfccYdT7adOndLjjz+uiIgI9e7d22lddbENqtNDfn6++vbtqz/96U8VrmPSpEn66KOPtHLlSqWlpenkyZP69a9/7ZhfVFSk+Ph4FRYWaufOnXr33Xe1ZMkSTZ06tVZ6cEc333yz0/basWOHY96lS5c0aNCgcn/XSlS1f6kPFfVw8uRJnTx5Un/+85+VnZ2tJUuWaP369Ro7dqxjWXfa5pVti169emnx4sU6cOCANmzYIMMwFBsbq6KiIrfqo7IeSrz22mvy8vIqM91depCq7mPcuHFO80v/8atO+jBQodOnTxuSjLS0NFeX4hYuXLhgdOzY0bDZbMbdd99tPPvss64uyS1MmTLF6Nu3r6vLgItJMlatWuV4XFxcbISEhBizZ892TDt37pxhsViMf/zjH4ZhGMbXX39tSDI+//xzx5hPPvnE8PLyMn744QfDMAxj4cKFRosWLYyCggLHmClTphidOnVyix7KM2vWLCMiIsLx+NixY4YkIzMzs9ZrLs1s/e3btzfmzp1b4Xo9bRsUFhYabdq0MaZPn+6YVl/bwDDK9lBaRXWcO3fO8PX1NVauXOmYduDAAUOSkZ6ebhiGYXz88ceGt7e3kZOT4xizaNEiw2q1Om2bhuKll14yevToUeW4rVu3GpKMH3/80Wl6dfYvda26PZRYsWKF4efnZ9jtdsMw3Geb17SPL7/80pBkHDlyxDAM9+ijOj1kZmYav/jFL4xTp06V+T12hx4Mo+o+qnp/Whd9cGSqEiWHmlu2bOniStxDQkKC4uPjNWDAAFeX4lbWrFmj3r17a9iwYQoKCtItt9yiv/zlL64uCy527Ngx5eTkOP2+BAQEKCoqSunp6ZKk9PR0BQYGOh09GDBggLy9vbV7927HmH79+snPz88xJi4uTocOHdKPP/7o8h7Kc/78+XL3m/fff7+CgoLUt29frVmzpk5qLq0m9c+cOVOtWrXSLbfcotmzZzud8uFp22DNmjU6c+aMxowZU2ZefW+D6srIyJDdbnfqs3PnzmrXrp3T70v37t2dPtg2Li5OeXl52r9/f73XXB8OHz6ssLAw3XjjjRo5cqROnDhR7WWrs3+pDzXp4fz587JarfLx8ZHkXtu8un3k5+dr8eLFioiIUHh4uCT36aOyHi5duqQRI0ZowYIFCgkJKbOsu/QgVb0tli5dqtatW6tbt25KSkrSpUuXHPPqog/CVAWKi4s1ceJE3XnnnerWrZury3G55cuX64svvlBKSoqrS3E733zzjRYtWqSOHTtqw4YNeuqpp/TMM8/o3XffdXVpcKGcnBxJctphlzwumZeTk6OgoCCn+T4+PmrZsqXTmPLWUfo56kp1erjWkSNH9Prrr+vJJ590TGvWrJnmzJmjlStXat26derbt6+GDBlS52/mq1v/M888o+XLl2vr1q168skn9corr2jy5MlO6/GkbfDXv/5VcXFxatu2rWOaq7ZBdeXk5MjPz0+BgYFO06/9fXHVdnCFqKgox6lvixYt0rFjx3TXXXfpwoUL1Vq+OvuXulaTHv79739rxowZTqchuss2r04fCxcuVLNmzdSsWTN98sknstlsjj/AuEMfVfUwadIk3XHHHXrggQfKXd4depCq7mPEiBF67733tHXrViUlJenvf/+7HnnkkTrtw8dkLw1eQkKCsrOzyz2f9Hrz3Xff6dlnn5XNZlPjxo1dXY7bKS4uVu/evfXKK69Ikm655RZlZ2crNTVVo0ePdnF1QP354YcfNGjQIA0bNkzjxo1zTG/durUSExMdj2+77TadPHlSs2fP1v333++KUp2Uri0yMlJ+fn568sknlZKSIovF4sLKau7777/Xhg0btGLFCqfp7r4NUNbgwYMd30dGRioqKkrt27fXihUrnK4rcmfV7SEvL0/x8fHq2rWrkpOTXVBp5arTx8iRIzVw4ECdOnVKf/7zn/Wb3/xGn332mdu8b6qshzZt2mjLli3KzMx0YYXVU9W2KB3Gu3fvrtDQUPXv319Hjx5Vhw4d6qQmjkyVY8KECVq7dq22bt3q9Je961VGRoZOnz6tW2+9VT4+PvLx8VFaWprmz58vHx8fxwWW16vQ0FB17drVaVqXLl1qdDoGGp6S0ySuvRtZbm6uY15ISIhOnz7tNP/q1as6e/as05jy1lH6OepKdXoocfLkSd1zzz264447qnVjhqioKB05cqT2ii1HTeq/trarV6/q+PHjjvV4wjaQpMWLF6tVq1bVCkj1sQ2qKyQkRIWFhWXuSHft74urtoM7CAwM1C9/+ctqb7Pq7F/qW3k9XLhwQYMGDVLz5s21atUq+fr6Oua56zYvr4+AgAB17NhR/fr10z//+U8dPHhQq1atkuSefZTuYcuWLTp69KgCAwMd7/MkaejQoYqJiXHU6W49SFX/XkRFRUmSY35d9EGYKsUwDE2YMEGrVq3Sli1bFBER4eqS3EL//v311VdfKSsry/HVu3dvjRw5UllZWWrUqJGrS3SpO++8s8wt9P/v//5P7du3d1FFcAcREREKCQnR5s2bHdPy8vK0e/duRUdHS5Kio6N17tw5ZWRkOMZs2bJFxcXFjv8AoqOjtX37dtntdscYm82mTp061fkdI6vTg/TTEamYmBjHHa28vav+ryUrK0uhoaF1UneJ6tZfXm3e3t6OU6Q8YRtIP/0ftnjxYo0aNcrpDWlF6mMbVFevXr3k6+vr1OehQ4d04sQJp9+Xr776yikg2Gw2Wa3WMn/QaoguXryoo0ePVnubVWf/Ut+u7aHkTpl+fn5as2ZNmaM47rrNq9oWhmHIMAwVFBRIcs8+Svfw+9//Xvv27XN6nydJc+fO1eLFiyW5Zw9S1duipJeS+XXSh6nbVjRQTz31lBEQEGBs27bNOHXqlOPr0qVLri7N7XA3v//Ys2eP4ePjY7z88svG4cOHjaVLlxr+/v7Ge++95+rSUMcuXLhgZGZmGpmZmYYk49VXXzUyMzONb7/91jAMw5g5c6YRGBhofPjhh8a+ffuMBx54wIiIiDAuX77sWMegQYOMW265xdi9e7exY8cOo2PHjsbw4cMd88+dO2cEBwcbjz76qJGdnW0sX77c8Pf3N95880236OH77783brrpJqN///7G999/77TvLLFkyRJj2bJlxoEDB4wDBw4YL7/8suHt7W288847Lq9/586dxty5c42srCzj6NGjxnvvvWe0adPGGDVqlOM53H0blNi0aZMhyThw4ECZ56jLbVCdHs6cOWNkZmYa69atMyQZy5cvNzIzM51+TsaPH2+0a9fO2LJli7F3714jOjraiI6Odsy/evWq0a1bNyM2NtbIysoy1q9fb7Rp08ZISkqqlR7czXPPPWds27bNOHbsmPHZZ58ZAwYMMFq3bm2cPn3aMAzDOHXqlJGZmWn85S9/MSQZ27dvNzIzM40zZ8441lHV/sWVPZw/f96Iiooyunfvbhw5csRp33H16lXDMNxnm1fWx9GjR41XXnnF2Lt3r/Htt98an332mXHfffcZLVu2NHJzc92mj6p+nq6la+7m5w49GEblfRw5csSYPn26sXfvXuPYsWPGhx9+aNx4441Gv3796rQPwlQpksr9Wrx4satLczuEKWcfffSR0a1bN8NisRidO3c23nrrLVeXhHpQckvia79Gjx5tGMZPt7V+8cUXjeDgYMNisRj9+/c3Dh065LSOM2fOGMOHDzeaNWtmWK1WY8yYMcaFCxecxnz55ZdG3759DYvFYvziF78wZs6c6TY9LF68uMJ9Z4klS5YYXbp0Mfz9/Q2r1Wr06dPH6RbYrqw/IyPDiIqKMgICAozGjRsbXbp0MV555RXjypUrTs/jztugxPDhw4077rij3Oeoy21QnR4q+jl56aWXHOu4fPmy8T//8z9GixYtDH9/f+PBBx90CluGYRjHjx83Bg8ebDRp0sRo3bq18dxzzzluo93QPPTQQ0ZoaKjh5+dn/OIXvzAeeughx622DeOnW0RX9Z6lOvsXV/VQ0c+MJOPYsWOOdbjDNq+sjx9++MEYPHiwERQUZPj6+hpt27Y1RowYYRw8eNBpHa7uo6qfp2tdG6YMw/U9GEblfZw4ccLo16+f0bJlS8NisRg33XST8fzzzxvnz5+v0z68DMMwzB3TAgAAAIDrF9dMAQAAAIAJhCkAAAAAMIEwBQAAAAAmEKYAAAAAwATCFAAAAACYQJgCAAAAABMIUwAAAABgAmEKAAAAAEwgTAEAAACACYQpAAAAADCBMAUAAAAAJhCmAAAAAMAEwhQAAAAAmECYAgAAAAATCFMAAAAAYAJhCgAAAABMIEwBAAAAgAmEKQAAAAAwgTAFAAAAACYQpgAAAADABMIUAAAAAJhAmILbOHr0qJ588kndeOONaty4saxWq+68807NmzdPly9fdoyz2+2aP3++brvtNjVv3lzNmjXTbbfdpvnz58tut7uwAwAAAFxPvAzDMFxdBLBu3ToNGzZMFotFo0aNUrdu3VRYWKgdO3bof//3f/XYY4/prbfeUn5+vuLj45WWlqZf/epXGjRokLy9vbV+/XqtWbNGd999t9atW6emTZu6uiUAAAA0cIQpuNyxY8cUGRmptm3basuWLQoNDXWaf+TIEa1bt07PPvusnnzySb311lt6/fXXNWHCBKdxCxYs0IQJEzR+/HgtWrSoPlsAAADAdYgwBZd76qmnlJqaqs8++0x33HFHheO+//573XDDDbr77ru1efPmcsfce++9+vTTT3Xs2DG1bdu2rkoGAAAAuGYKrvfRRx/pxhtvrDRISdInn3yioqIijRo1qsIxo0aN0tWrV7V+/fraLhMAAABwQpiCS+Xl5emHH35Q9+7dqxz79ddfS5J69OhR4ZiSeQcOHKidAgEAAIAKEKbgUnl5eZKk5s2bVzn2woULVY4tmVeyXgAAAKCuEKbgUlarVdJ/glJlSoJSZWOrE7gAAACA2kCYgktZrVaFhYUpOzu7yrFdunSRJO3bt6/CMSXzunbtWjsFAgAAABUgTMHlfvWrX+no0aNKT0+vdNzgwYPVqFEj/f3vf69wzN/+9jf5+Pho0KBBtV0mAAAA4IQwBZebPHmymjZtqscff1y5ubll5h89elTz5s1TeHi4xowZo02bNpX7OVKpqanasmWLxo4dy23RAQAAUOf4nCm4hTVr1uihhx5SkyZNNGrUKHXr1k2FhYXauXOnVq5cqccee0xvvvmmLl68qMGDB2vHjh26//77HUegNmzYoA8//FB333231q1bp6ZNm7q4IwAAADR0hCm4jcOHD2v27Nmy2Ww6efKkLBaLIiMj9fDDD2vcuHGyWCySpMLCQi1cuFDvvfeeDh48KMMw1LlzZ40aNUr/8z//I19fXxd3AgAAgOsBYQoAAAAATOCaKQAAAAAwgTAFAAAAACYQpgAAAADABMIUAAAAAJhAmAIAAAAAEwhTAAAAAGCCj6sLcKXi4mKdPHlSzZs3l5eXl6vLARoMwzB04cIFhYWFydubv9kAAICG6boOUydPnlR4eLirywAarO+++05t27Z1dRkAAAB14roOU82bN5f00xs+q9Va7hi73a6NGzcqNjZWvr6+9VmeaZ5Ws6fVK3lezfVdb15ensLDwx2/YwAAAA3RdR2mSk7ts1qtlYYpf39/Wa1Wj3jTLHlezZ5Wr+R5NbuqXk6fBQAADRkXMwAAAACACYQpAAAAADCBMAUAAAAAJhCmAAAAAMAEwhQAAAAAmECYAgAAAAATCFMAAAAAYAJhCgAAAABMuK4/tLcmuiVvUEFR2Q8gPT4z3gXVAAAAAHA1jkwBAAAAgAmEKQAAAAAwgTAFAAAAACYQpgAAAADABMIUAAAAAJhAmAIAAAAAE7g1+s90w+/XlTudW6YDAAAADRtHpgAAAADABMIUAAAAAJhAmAIAAAAAEwhTAAAAAGACYQoAAAAATCBMAQAAAIAJhCkAAAAAMIEwBQAAAAAmEKYAAAAAwATCFAAAAACYQJgCAAAAABMIUwAAAABgQo3D1Pbt23XfffcpLCxMXl5eWr16tWOe3W7XlClT1L17dzVt2lRhYWEaNWqUTp486bSOG264QV5eXk5fM2fOdBqzb98+3XXXXWrcuLHCw8M1a9asMrWsXLlSnTt3VuPGjdW9e3d9/PHHNW0HAAAAAEypcZjKz89Xjx49tGDBgjLzLl26pC+++EIvvviivvjiC33wwQc6dOiQ7r///jJjp0+frlOnTjm+nn76ace8vLw8xcbGqn379srIyNDs2bOVnJyst956yzFm586dGj58uMaOHavMzEwNGTJEQ4YMUXZ2dk1bAgAAAIAa86npAoMHD9bgwYPLnRcQECCbzeY07Y033lCfPn104sQJtWvXzjG9efPmCgkJKXc9S5cuVWFhod555x35+fnp5ptvVlZWll599VU98cQTkqR58+Zp0KBBev755yVJM2bMkM1m0xtvvKHU1NSatgUAAAAANVLjMFVT58+fl5eXlwIDA52mz5w5UzNmzFC7du00YsQITZo0ST4+P5WTnp6ufv36yc/PzzE+Li5Of/rTn/Tjjz+qRYsWSk9PV2JiotM64+LinE47vFZBQYEKCgocj/Py8iT9dHqi3W4vd5mS6RZvo9o9l17OFUqe25U11ISn1St5Xs31Xa+nvC4AAAA/R52GqStXrmjKlCkaPny4rFarY/ozzzyjW2+9VS1bttTOnTuVlJSkU6dO6dVXX5Uk5eTkKCIiwmldwcHBjnktWrRQTk6OY1rpMTk5ORXWk5KSomnTppWZvnHjRvn7+1fay4zexZU3ew13uH7r2qOE7s7T6pU8r+b6qvfSpUv18jwAAACuVGdhym636ze/+Y0Mw9CiRYuc5pU+ohQZGSk/Pz89+eSTSklJkcViqauSlJSU5PTceXl5Cg8PV2xsrFPYK81ut8tms+nFvd4qKPaq9nNlJ8f97HrNKql54MCB8vX1dVkd1eVp9UqeV3N911ty1BcAAKAhq5MwVRKkvv32W23ZsqXCoFIiKipKV69e1fHjx9WpUyeFhIQoNzfXaUzJ45LrrCoaU9F1WJJksVjKDWu+vr5VvsEsKPZSQVH1w5Q7vMGuTl/uxNPqlTyv5vqq15NeEwAAALNq/XOmSoLU4cOHtWnTJrVq1arKZbKysuTt7a2goCBJUnR0tLZv3+503YXNZlOnTp3UokULx5jNmzc7rcdmsyk6OroWuwEAAACA8tX4yNTFixd15MgRx+Njx44pKytLLVu2VGhoqP77v/9bX3zxhdauXauioiLHNUwtW7aUn5+f0tPTtXv3bt1zzz1q3ry50tPTNWnSJD3yyCOOoDRixAhNmzZNY8eO1ZQpU5Sdna158+Zp7ty5jud99tlndffdd2vOnDmKj4/X8uXLtXfvXqfbpwMAAABAXalxmNq7d6/uuecex+OSa5BGjx6t5ORkrVmzRpLUs2dPp+W2bt2qmJgYWSwWLV++XMnJySooKFBERIQmTZrkdC1TQECANm7cqISEBPXq1UutW7fW1KlTHbdFl6Q77rhDy5Yt0wsvvKA//OEP6tixo1avXq1u3brVtCUAAAAAqLEah6mYmBgZRsW3Ca9sniTdeuut2rVrV5XPExkZqU8//bTSMcOGDdOwYcOqXBcAAAAA1LZav2YKAAAAAK4HhCkAAAAAMIEwBQAAAAAmEKYAAAAAwATCFAAAAACYQJgCAAAAABMIUwAAAABgAmEKAAAAAEwgTAEAAACACYQpAAAAADCBMAUAAAAAJhCmAAAAAMAEwhQAAAAAmECYAgAAAAATCFMAAAAAYAJhCgAAAABMIEwBAAAAgAmEKQAAAAAwgTAFAAAAACYQpgAAAADABMIUAAAAAJhAmAIAAAAAEwhTAAAAAGACYQoAAAAATCBMAQAAAIAJNQ5T27dv13333aewsDB5eXlp9erVTvMNw9DUqVMVGhqqJk2aaMCAATp8+LDTmLNnz2rkyJGyWq0KDAzU2LFjdfHiRacx+/bt01133aXGjRsrPDxcs2bNKlPLypUr1blzZzVu3Fjdu3fXxx9/XNN2AAAAAMCUGoep/Px89ejRQwsWLCh3/qxZszR//nylpqZq9+7datq0qeLi4nTlyhXHmJEjR2r//v2y2Wxau3attm/frieeeMIxPy8vT7GxsWrfvr0yMjI0e/ZsJScn66233nKM2blzp4YPH66xY8cqMzNTQ4YM0ZAhQ5SdnV3TlgAAAACgxnxqusDgwYM1ePDgcucZhqHXXntNL7zwgh544AFJ0t/+9jcFBwdr9erVevjhh3XgwAGtX79en3/+uXr37i1Jev311/Vf//Vf+vOf/6ywsDAtXbpUhYWFeuedd+Tn56ebb75ZWVlZevXVVx2ha968eRo0aJCef/55SdKMGTNks9n0xhtvKDU11dSLAQAAAADVVeMwVZljx44pJydHAwYMcEwLCAhQVFSU0tPT9fDDDys9PV2BgYGOICVJAwYMkLe3t3bv3q0HH3xQ6enp6tevn/z8/Bxj4uLi9Kc//Uk//vijWrRoofT0dCUmJjo9f1xcXJnTDksrKChQQUGB43FeXp4kyW63y263l7tMyXSLt1H9F6LUcq5Q8tyurKEmPK1eyfNqru96PeV1AQAA+DlqNUzl5ORIkoKDg52mBwcHO+bl5OQoKCjIuQgfH7Vs2dJpTERERJl1lMxr0aKFcnJyKn2e8qSkpGjatGllpm/cuFH+/v6V9jajd3Gl86/lDtdv2Ww2V5dQI55Wr+R5NddXvZcuXaqX5wEAAHClWg1T7i4pKcnpaFZeXp7Cw8MVGxsrq9Va7jJ2u102m00v7vVWQbFXtZ8rOznuZ9drVknNAwcOlK+vr8vqqC5Pq1fyvJrru96So74AAAANWa2GqZCQEElSbm6uQkNDHdNzc3PVs2dPx5jTp087LXf16lWdPXvWsXxISIhyc3OdxpQ8rmpMyfzyWCwWWSyWMtN9fX2rfINZUOylgqLqhyl3eINdnb7ciafVK3lezfVVrye9JgAAAGbV6udMRUREKCQkRJs3b3ZMy8vL0+7duxUdHS1Jio6O1rlz55SRkeEYs2XLFhUXFysqKsoxZvv27U7XXdhsNnXq1EktWrRwjCn9PCVjSp4HAAAAAOpSjcPUxYsXlZWVpaysLEk/3XQiKytLJ06ckJeXlyZOnKg//vGPWrNmjb766iuNGjVKYWFhGjJkiCSpS5cuGjRokMaNG6c9e/bos88+04QJE/Twww8rLCxMkjRixAj5+flp7Nix2r9/v95//33NmzfP6RS9Z599VuvXr9ecOXN08OBBJScna+/evZowYcLPf1UAAAAAoAo1Ps1v7969uueeexyPSwLO6NGjtWTJEk2ePFn5+fl64okndO7cOfXt21fr169X48aNHcssXbpUEyZMUP/+/eXt7a2hQ4dq/vz5jvkBAQHauHGjEhIS1KtXL7Vu3VpTp051+iyqO+64Q8uWLdMLL7ygP/zhD+rYsaNWr16tbt26mXohAAAAAKAmahymYmJiZBgV3ybcy8tL06dP1/Tp0ysc07JlSy1btqzS54mMjNSnn35a6Zhhw4Zp2LBhlRcMAAAAAHWgVq+ZAgAAAIDrBWEKAAAAAEwgTAEAAACACYQpAAAAADCBMAUAAAAAJhCmAAAAAMAEwhQAAAAAmECYAgAAAAATCFMAAAAAYAJhCgAAAABMIEwBAAAAgAmEKQAAAAAwgTAFAAAAACYQpgAAAADABMIUAAAAAJhAmAIAAAAAEwhTAAAAAGACYQoAAAAATCBMAQAAAIAJhCkAAAAAMIEwBQAAAAAmEKYAAAAAwATCFAAAAACYQJgCAAAAABNqPUzdcMMN8vLyKvOVkJAgSYqJiSkzb/z48U7rOHHihOLj4+Xv76+goCA9//zzunr1qtOYbdu26dZbb5XFYtFNN92kJUuW1HYrAAAAAFAhn9pe4eeff66ioiLH4+zsbA0cOFDDhg1zTBs3bpymT5/ueOzv7+/4vqioSPHx8QoJCdHOnTt16tQpjRo1Sr6+vnrllVckSceOHVN8fLzGjx+vpUuXavPmzXr88ccVGhqquLi42m4JAAAAAMqo9TDVpk0bp8czZ85Uhw4ddPfddzum+fv7KyQkpNzlN27cqK+//lqbNm1ScHCwevbsqRkzZmjKlClKTk6Wn5+fUlNTFRERoTlz5kiSunTpoh07dmju3LmEKQAAAAD1ok6vmSosLNR7772n3/72t/Ly8nJMX7p0qVq3bq1u3bopKSlJly5dcsxLT09X9+7dFRwc7JgWFxenvLw87d+/3zFmwIABTs8VFxen9PT0umwHAAAAABxq/chUaatXr9a5c+f02GOPOaaNGDFC7du3V1hYmPbt26cpU6bo0KFD+uCDDyRJOTk5TkFKkuNxTk5OpWPy8vJ0+fJlNWnSpNx6CgoKVFBQ4Hicl5cnSbLb7bLb7eUuUzLd4m1Ut22n5Vyh5LldWUNNeFq9kufVXN/1esrrAgAA8HPUaZj661//qsGDByssLMwx7YknnnB83717d4WGhqp///46evSoOnToUJflKCUlRdOmTSszfePGjU7XbZVnRu/iGj3Xxx9/XKPxdcFms7m6hBrxtHolz6u5vuotfbQZAACgoaqzMPXtt99q06ZNjiNOFYmKipIkHTlyRB06dFBISIj27NnjNCY3N1eSHNdZhYSEOKaVHmO1Wis8KiVJSUlJSkxMdDzOy8tTeHi4YmNjZbVay13GbrfLZrPpxb3eKij2KndMebKTXXftVknNAwcOlK+vr8vqqC5Pq1fyvJrru96So74AAAANWZ2FqcWLFysoKEjx8fGVjsvKypIkhYaGSpKio6P18ssv6/Tp0woKCpL001/TrVarunbt6hhz7ZEfm82m6OjoSp/LYrHIYrGUme7r61vlG8yCYi8VFFU/TLnDG+zq9OVOPK1eyfNqrq96Pek1AQAAMKtObkBRXFysxYsXa/To0fLx+U9eO3r0qGbMmKGMjAwdP35ca9as0ahRo9SvXz9FRkZKkmJjY9W1a1c9+uij+vLLL7Vhwwa98MILSkhIcASh8ePH65tvvtHkyZN18OBBLVy4UCtWrNCkSZPqoh0AAAAAKKNOwtSmTZt04sQJ/fa3v3Wa7ufnp02bNik2NladO3fWc889p6FDh+qjjz5yjGnUqJHWrl2rRo0aKTo6Wo888ohGjRrl9LlUERERWrdunWw2m3r06KE5c+bo7bff5rboAAAAAOpNnZzmFxsbK8Moe/e78PBwpaWlVbl8+/btq7yBQ0xMjDIzM03XCAAAAAA/R51+zhQAAAAANFSEKQAAAAAwgTAFAAAAACYQpgAAAADABMIUAAAAAJhAmAIAAAAAEwhTAAAAAGACYQoAAAAATCBMAQAAAIAJhCkAAAAAMIEwBQAAAAAmEKYAAAAAwATCFAAAAACYQJgCAAAAABMIUwAAAABgAmEKAAAAAEwgTAEAAACACYQpAAAAADCBMAUAAAAAJhCmAAAAAMAEwhQAAAAAmECYAgAAAAATCFMAAAAAYAJhCgAAAABMIEwBAAAAgAm1HqaSk5Pl5eXl9NW5c2fH/CtXrighIUGtWrVSs2bNNHToUOXm5jqt48SJE4qPj5e/v7+CgoL0/PPP6+rVq05jtm3bpltvvVUWi0U33XSTlixZUtutAAAAAECF6uTI1M0336xTp045vnbs2OGYN2nSJH300UdauXKl0tLSdPLkSf361792zC8qKlJ8fLwKCwu1c+dOvfvuu1qyZImmTp3qGHPs2DHFx8frnnvuUVZWliZOnKjHH39cGzZsqIt2AAAAAKAMnzpZqY+PQkJCykw/f/68/vrXv2rZsmW69957JUmLFy9Wly5dtGvXLt1+++3auHGjvv76a23atEnBwcHq2bOnZsyYoSlTpig5OVl+fn5KTU1VRESE5syZI0nq0qWLduzYoblz5youLq4uWgIAAAAAJ3VyZOrw4cMKCwvTjTfeqJEjR+rEiROSpIyMDNntdg0YMMAxtnPnzmrXrp3S09MlSenp6erevbuCg4MdY+Li4pSXl6f9+/c7xpReR8mYknUAAAAAQF2r9SNTUVFRWrJkiTp16qRTp05p2rRpuuuuu5Sdna2cnBz5+fkpMDDQaZng4GDl5ORIknJycpyCVMn8knmVjcnLy9Ply5fVpEmTcmsrKChQQUGB43FeXp4kyW63y263l7tMyXSLt1Gd9sss5wolz+3KGmrC0+qVPK/m+q7XU14XAACAn6PWw9TgwYMd30dGRioqKkrt27fXihUrKgw59SUlJUXTpk0rM33jxo3y9/evdNkZvYtr9Fwff/xxjcbXBZvN5uoSasTT6pU8r+b6qvfSpUv18jwAAACuVCfXTJUWGBioX/7ylzpy5IgGDhyowsJCnTt3zunoVG5uruMaq5CQEO3Zs8dpHSV3+ys95to7AObm5spqtVYa2JKSkpSYmOh4nJeXp/DwcMXGxspqtZa7jN1ul81m04t7vVVQ7FXtvrOTXXftVknNAwcOlK+vr8vqqC5Pq1fyvJrru96So74AAAANWZ2HqYsXL+ro0aN69NFH1atXL/n6+mrz5s0aOnSoJOnQoUM6ceKEoqOjJUnR0dF6+eWXdfr0aQUFBUn66a/pVqtVXbt2dYy59siPzWZzrKMiFotFFoulzHRfX98q32AWFHupoKj6Ycod3mBXpy934mn1Sp5Xc33V60mvCQAAgFm1fgOK3/3ud0pLS9Px48e1c+dOPfjgg2rUqJGGDx+ugIAAjR07VomJidq6dasyMjI0ZswYRUdH6/bbb5ckxcbGqmvXrnr00Uf15ZdfasOGDXrhhReUkJDgCELjx4/XN998o8mTJ+vgwYNauHChVqxYoUmTJtV2OwAAAABQrlo/MvX9999r+PDhOnPmjNq0aaO+fftq165datOmjSRp7ty58vb21tChQ1VQUKC4uDgtXLjQsXyjRo20du1aPfXUU4qOjlbTpk01evRoTZ8+3TEmIiJC69at06RJkzRv3jy1bdtWb7/9NrdFBwAAAFBvaj1MLV++vNL5jRs31oIFC7RgwYIKx7Rv377KGzjExMQoMzPTVI0AAAAA8HPVyedMAQAAAEBDR5gCAAAAABMIUwAAAABgQp3fGv16dcPv11U47/jM+HqsBAAAAEBd4MgUAAAAAJhAmAIAAAAAEwhTAAAAAGACYQoAAAAATCBMAQAAAIAJhCkAAAAAMIEwBQAAAAAmEKYAAAAAwATCFAAAAACYQJgCAAAAABMIUwAAAABgAmEKAAAAAEwgTAEAAACACYQpAAAAADCBMAUAAAAAJhCmAAAAAMAEwhQAAAAAmECYAgAAAAATCFMAAAAAYAJhCgAAAABMIEwBAAAAgAm1HqZSUlJ02223qXnz5goKCtKQIUN06NAhpzExMTHy8vJy+ho/frzTmBMnTig+Pl7+/v4KCgrS888/r6tXrzqN2bZtm2699VZZLBbddNNNWrJkSW23AwAAAADlqvUwlZaWpoSEBO3atUs2m012u12xsbHKz893Gjdu3DidOnXK8TVr1izHvKKiIsXHx6uwsFA7d+7Uu+++qyVLlmjq1KmOMceOHVN8fLzuueceZWVlaeLEiXr88ce1YcOG2m4JAAAAAMrwqe0Vrl+/3unxkiVLFBQUpIyMDPXr188x3d/fXyEhIeWuY+PGjfr666+1adMmBQcHq2fPnpoxY4amTJmi5ORk+fn5KTU1VREREZozZ44kqUuXLtqxY4fmzp2ruLi42m4LAAAAAJzUepi61vnz5yVJLVu2dJq+dOlSvffeewoJCdF9992nF198Uf7+/pKk9PR0de/eXcHBwY7xcXFxeuqpp7R//37dcsstSk9P14ABA5zWGRcXp4kTJ1ZYS0FBgQoKChyP8/LyJEl2u112u73cZUqmW7yNanZctYqeq7bXX9fPU1s8rV7J82qu73o95XUBAAD4Oeo0TBUXF2vixIm688471a1bN8f0ESNGqH379goLC9O+ffs0ZcoUHTp0SB988IEkKScnxylISXI8zsnJqXRMXl6eLl++rCZNmpSpJyUlRdOmTSszfePGjY4gV5EZvYur0XH1fPzxx7W2rsrYbLZ6eZ7a4mn1Sp5Xc33Ve+nSpXp5HgAAAFeq0zCVkJCg7Oxs7dixw2n6E0884fi+e/fuCg0NVf/+/XX06FF16NChzupJSkpSYmKi43FeXp7Cw8MVGxsrq9Va7jJ2u102m00v7vVWQbFXrdSRnVy3pyGW1Dxw4ED5+vrW6XPVBk+rV/K8muu73pKjvgAAAA1ZnYWpCRMmaO3atdq+fbvatm1b6dioqChJ0pEjR9ShQweFhIRoz549TmNyc3MlyXGdVUhIiGNa6TFWq7Xco1KSZLFYZLFYykz39fWt8g1mQbGXCopqJ0x1fHFjudOPz4yvlfWXqE5f7sTT6pU8r+b6qteTXhMAAACzav1ufoZhaMKECVq1apW2bNmiiIiIKpfJysqSJIWGhkqSoqOj9dVXX+n06dOOMTabTVarVV27dnWM2bx5s9N6bDaboqOja6kTAAAAAKhYrYephIQEvffee1q2bJmaN2+unJwc5eTk6PLly5Kko0ePasaMGcrIyNDx48e1Zs0ajRo1Sv369VNkZKQkKTY2Vl27dtWjjz6qL7/8Uhs2bNALL7yghIQEx5Gl8ePH65tvvtHkyZN18OBBLVy4UCtWrNCkSZNquyUAAAAAKKPWw9SiRYt0/vx5xcTEKDQ01PH1/vvvS5L8/Py0adMmxcbGqnPnznruuec0dOhQffTRR451NGrUSGvXrlWjRo0UHR2tRx55RKNGjdL06dMdYyIiIrRu3TrZbDb16NFDc+bM0dtvv81t0QEAAADUi1q/ZsowKr+FeHh4uNLS0qpcT/v27au8611MTIwyMzNrVB8AAAAA1IZaPzIFAAAAANcDwhQAAAAAmECYAgAAAAATCFMAAAAAYAJhCgAAAABMIEwBAAAAgAmEKQAAAAAwgTAFAAAAACYQpgAAAADABMIUAAAAAJhAmAIAAAAAEwhTAAAAAGACYQoAAAAATCBMAQAAAIAJhCkAAAAAMIEwBQAAAAAmEKYAAAAAwAQfVxeA/7jh9+sqnHd8Znw9VgIAAACgKhyZAgAAAAATCFMAAAAAYAJhCgAAAABMIEwBAAAAgAmEKQAAAAAwgbv5eQju9AcAAAC4F45MAQAAAIAJHh+mFixYoBtuuEGNGzdWVFSU9uzZ4+qSAAAAAFwHPPo0v/fff1+JiYlKTU1VVFSUXnvtNcXFxenQoUMKCgpydXn15tpTAC2NDM3qI3VL3qCCIq9yl+HUQAAAAODn8egjU6+++qrGjRunMWPGqGvXrkpNTZW/v7/eeecdV5cGAAAAoIHz2CNThYWFysjIUFJSkmOat7e3BgwYoPT09HKXKSgoUEFBgePx+fPnJUlnz56V3W4vdxm73a5Lly7Jx+6touLyj/K4G59iQ5cuFVda802/W1Hj9e5O6v9zSytXyWt85swZ+fr61slz1DZPq7m+671w4YIkyTCMOn8uAAAAV/HYMPXvf/9bRUVFCg4OdpoeHBysgwcPlrtMSkqKpk2bVmZ6REREndToSiPqYJ2t59TBStGgXbhwQQEBAa4uAwAAoE54bJgyIykpSYmJiY7HxcXFOnv2rFq1aiUvr/KP4OTl5Sk8PFzfffedrFZrfZX6s3hazZ5Wr+R5Ndd3vYZh6MKFCwoLC6vz5wIAAHAVjw1TrVu3VqNGjZSbm+s0PTc3VyEhIeUuY7FYZLFYnKYFBgZW6/msVqtHvGkuzdNq9rR6Jc+ruT7r5YgUAABo6Dz2BhR+fn7q1auXNm/e7JhWXFyszZs3Kzo62oWVAQAAALgeeOyRKUlKTEzU6NGj1bt3b/Xp00evvfaa8vPzNWbMGFeXBgAAAKCB8+gw9dBDD+lf//qXpk6dqpycHPXs2VPr168vc1OKn8Niseill14qc3qgO/O0mj2tXsnzava0egEAADyBl8G9iwEAAACgxjz2mikAAAAAcCXCFAAAAACYQJgCAAAAABMIUwAAAABgAmGqCgsWLNANN9ygxo0bKyoqSnv27HF1SQ7bt2/Xfffdp7CwMHl5eWn16tVO8w3D0NSpUxUaGqomTZpowIABOnz4sEtqTUlJ0W233abmzZsrKChIQ4YM0aFDh5zGXLlyRQkJCWrVqpWaNWumoUOHlvlQ5vq0aNEiRUZGOj7oNjo6Wp988onb1nutmTNnysvLSxMnTnRMc/eaAQAAPAlhqhLvv/++EhMT9dJLL+mLL75Qjx49FBcXp9OnT7u6NElSfn6+evTooQULFpQ7f9asWZo/f75SU1O1e/duNW3aVHFxcbpy5Uo9VyqlpaUpISFBu3btks1mk91uV2xsrPLz8x1jJk2apI8++kgrV65UWlqaTp48qV//+tf1XmuJtm3baubMmcrIyNDevXt177336oEHHtD+/fvdst7SPv/8c7355puKjIx0mu7ONQMAAHgcAxXq06ePkZCQ4HhcVFRkhIWFGSkpKS6sqnySjFWrVjkeFxcXGyEhIcbs2bMd086dO2dYLBbjH//4hwsqdHb69GlDkpGWlmYYxk+1+fr6GitXrnSMOXDggCHJSE9Pd1WZZbRo0cJ4++233breCxcuGB07djRsNptx9913G88++6xhGJ7zGgMAAHgKjkxVoLCwUBkZGRowYIBjmre3twYMGKD09HQXVlY9x44dU05OjlP9AQEBioqKcov6z58/L0lq2bKlJCkjI0N2u92p3s6dO6tdu3ZuUW9RUZGWL1+u/Px8RUdHu3W9CQkJio+Pd6pNcv/XGAAAwNP4uLoAd/Xvf/9bRUVFCg4OdpoeHBysgwcPuqiq6svJyZGkcusvmecqxcXFmjhxou68805169ZN0k/1+vn5KTAw0Gmsq+v96quvFB0drStXrqhZs2ZatWqVunbtqqysLLesd/ny5friiy/0+eefl5nnrq8xAACApyJMod4lJCQoOztbO3bscHUpVerUqZOysrJ0/vx5/fOf/9To0aOVlpbm6rLK9d133+nZZ5+VzWZT48aNXV0OAABAg8dpfhVo3bq1GjVqVOZOZ7m5uQoJCXFRVdVXUqO71T9hwgStXbtWW7duVdu2bR3TQ0JCVFhYqHPnzjmNd3W9fn5+uummm9SrVy+lpKSoR48emjdvnlvWm5GRodOnT+vWW2+Vj4+PfHx8lJaWpvnz58vHx0fBwcFuVzMAAIAnI0xVwM/PT7169dLmzZsd04qLi7V582ZFR0e7sLLqiYiIUEhIiFP9eXl52r17t0vqNwxDEyZM0KpVq7RlyxZFREQ4ze/Vq5d8fX2d6j106JBOnDjhVq93cXGxCgoK3LLe/v3766uvvlJWVpbjq3fv3ho5cqTje3erGQAAwJNxml8lEhMTNXr0aPXu3Vt9+vTRa6+9pvz8fI0ZM8bVpUmSLl68qCNHjjgeHzt2TFlZWWrZsqXatWuniRMn6o9//KM6duyoiIgIvfjiiwoLC9OQIUPqvdaEhAQtW7ZMH374oZo3b+64RicgIEBNmjRRQECAxo4dq8TERLVs2VJWq1VPP/20oqOjdfvtt9d7vZKUlJSkwYMHq127drpw4YKWLVumbdu2acOGDW5Zb/PmzR3XoJVo2rSpWrVq5ZjubjUDAAB4MsJUJR566CH961//0tSpU5WTk6OePXtq/fr1ZW7q4Cp79+7VPffc43icmJgoSRo9erSWLFmiyZMnKz8/X0888YTOnTunvn37av369S65nmbRokWSpJiYGKfpixcv1mOPPSZJmjt3rry9vTV06FAVFBQoLi5OCxcurOdK/+P06dMaNWqUTp06pYCAAEVGRmrDhg0aOHCgW9ZbHZ5YMwAAgLvyMgzDcHURAAAAAOBpuGYKAAAAAEwgTAEAAACACYQpAAAAADCBMAUAAAAAJhCmAAAAAMAEwhQAAAAAmECYAgAAAAATCFMAAAAAYAJhCgAAAABMIEwBAAAAgAmEKQAAAAAwgTAFAAAAACb8Py5/aFodiTJQAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1000x1000 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "data.hist(bins=30, figsize=(10, 10))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[IF TIT[high] THEN CO[1]\n",
       " \tAND aggregation function : fmin\n",
       " \tOR aggregation function  : fmax,\n",
       " IF TIT[average] THEN CO[2]\n",
       " \tAND aggregation function : fmin\n",
       " \tOR aggregation function  : fmax,\n",
       " IF TIT[low] AND TAT[high] THEN CO[3]\n",
       " \tAND aggregation function : fmin\n",
       " \tOR aggregation function  : fmax,\n",
       " IF TIT[average] AND TAT[low] THEN CO[3]\n",
       " \tAND aggregation function : fmin\n",
       " \tOR aggregation function  : fmax,\n",
       " IF TIT[average] AND TAT[high] THEN CO[2]\n",
       " \tAND aggregation function : fmin\n",
       " \tOR aggregation function  : fmax,\n",
       " IF TIT[low] AND TAT[average] THEN CO[5]\n",
       " \tAND aggregation function : fmin\n",
       " \tOR aggregation function  : fmax,\n",
       " IF TIT[low] AND TAT[low] THEN CO[9]\n",
       " \tAND aggregation function : fmin\n",
       " \tOR aggregation function  : fmax]"
      ]
     },
     "execution_count": 199,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from src.rules import get_fuzzy_rules\n",
    "\n",
    "fuzzy_variables = {\n",
    "    # \"AT\": AT,\n",
    "    # \"AP\": AP,\n",
    "    # \"AH\": AH,\n",
    "    # \"AFDP\": AFDP,\n",
    "    \"TIT\": TIT,\n",
    "    \"TAT\": TAT,\n",
    "    \"consequent\": CO,\n",
    "}\n",
    "fuzzy_rules = get_fuzzy_rules(rules, fuzzy_variables)\n",
    "\n",
    "fuzzy_cntrl = ctrl.ControlSystem(fuzzy_rules)\n",
    "\n",
    "sim = ctrl.ControlSystemSimulation(fuzzy_cntrl, lenient=False)\n",
    "\n",
    "display(len(fuzzy_rules))\n",
    "fuzzy_rules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=============\n",
      " Antecedents \n",
      "=============\n",
      "Antecedent: TIT                     = 1032.5\n",
      "  - low                             : 0.36663336663350904\n",
      "  - average                         : 0.6333666333664919\n",
      "  - high                            : 0.0\n",
      "Antecedent: TAT                     = 524.71\n",
      "  - low                             : 0.3078481012659794\n",
      "  - average                         : 0.6921518987340216\n",
      "  - high                            : 0.0\n",
      "\n",
      "=======\n",
      " Rules \n",
      "=======\n",
      "RULE #0:\n",
      "  IF TIT[high] THEN CO[1]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - TIT[high]                                              : 0.0\n",
      "                                                 TIT[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                                     CO[1] : 0.0\n",
      "\n",
      "RULE #1:\n",
      "  IF TIT[average] THEN CO[2]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - TIT[average]                                           : 0.6333666333664919\n",
      "                                              TIT[average] = 0.6333666333664919\n",
      "  Activation (THEN-clause):\n",
      "                                                     CO[2] : 0.6333666333664919\n",
      "\n",
      "RULE #2:\n",
      "  IF TIT[low] AND TAT[high] THEN CO[3]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - TIT[low]                                               : 0.36663336663350904\n",
      "  - TAT[high]                                              : 0.0\n",
      "                                    TIT[low] AND TAT[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                                     CO[3] : 0.0\n",
      "\n",
      "RULE #3:\n",
      "  IF TIT[average] AND TAT[low] THEN CO[3]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - TIT[average]                                           : 0.6333666333664919\n",
      "  - TAT[low]                                               : 0.3078481012659794\n",
      "                                 TIT[average] AND TAT[low] = 0.3078481012659794\n",
      "  Activation (THEN-clause):\n",
      "                                                     CO[3] : 0.3078481012659794\n",
      "\n",
      "RULE #4:\n",
      "  IF TIT[average] AND TAT[high] THEN CO[2]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - TIT[average]                                           : 0.6333666333664919\n",
      "  - TAT[high]                                              : 0.0\n",
      "                                TIT[average] AND TAT[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                                     CO[2] : 0.0\n",
      "\n",
      "RULE #5:\n",
      "  IF TIT[low] AND TAT[average] THEN CO[5]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - TIT[low]                                               : 0.36663336663350904\n",
      "  - TAT[average]                                           : 0.6921518987340216\n",
      "                                 TIT[low] AND TAT[average] = 0.36663336663350904\n",
      "  Activation (THEN-clause):\n",
      "                                                     CO[5] : 0.36663336663350904\n",
      "\n",
      "RULE #6:\n",
      "  IF TIT[low] AND TAT[low] THEN CO[9]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - TIT[low]                                               : 0.36663336663350904\n",
      "  - TAT[low]                                               : 0.3078481012659794\n",
      "                                     TIT[low] AND TAT[low] = 0.3078481012659794\n",
      "  Activation (THEN-clause):\n",
      "                                                     CO[9] : 0.3078481012659794\n",
      "\n",
      "\n",
      "==============================\n",
      " Intermediaries and Conquests \n",
      "==============================\n",
      "Consequent: CO                       = 9.796844832357262\n",
      "  1:\n",
      "    Accumulate using accumulation_max : 0.0\n",
      "  2:\n",
      "    Accumulate using accumulation_max : 0.6333666333664919\n",
      "  3:\n",
      "    Accumulate using accumulation_max : 0.3078481012659794\n",
      "  4:\n",
      "    Accumulate using accumulation_max : None\n",
      "  5:\n",
      "    Accumulate using accumulation_max : 0.36663336663350904\n",
      "  6:\n",
      "    Accumulate using accumulation_max : None\n",
      "  7:\n",
      "    Accumulate using accumulation_max : None\n",
      "  8:\n",
      "    Accumulate using accumulation_max : None\n",
      "  9:\n",
      "    Accumulate using accumulation_max : 0.3078481012659794\n",
      "  10:\n",
      "    Accumulate using accumulation_max : None\n",
      "  11:\n",
      "    Accumulate using accumulation_max : None\n",
      "  12:\n",
      "    Accumulate using accumulation_max : None\n",
      "  13:\n",
      "    Accumulate using accumulation_max : None\n",
      "  14:\n",
      "    Accumulate using accumulation_max : None\n",
      "  15:\n",
      "    Accumulate using accumulation_max : None\n",
      "  16:\n",
      "    Accumulate using accumulation_max : None\n",
      "  17:\n",
      "    Accumulate using accumulation_max : None\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "np.float64(9.796844832357262)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/user/Projects/python/fuzzy-rules-generator/.venv/lib/python3.12/site-packages/skfuzzy/control/fuzzyvariable.py:125: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
      "  fig.show()\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# sim.input[\"AT\"] = 4.5878\n",
    "# sim.input[\"AP\"] = 1018.7\n",
    "# sim.input[\"AH\"] = 83.675\n",
    "# sim.input[\"AFDP\"] = 3.5758\n",
    "# sim.input[\"TIT\"] = 1086.2\n",
    "# sim.input[\"TAT\"] = 549.83\n",
    "# sim.input[\"AT\"] = 7.8167\n",
    "# sim.input[\"AP\"] = 1022.2\n",
    "# sim.input[\"AH\"] = 88.135\n",
    "# sim.input[\"AFDP\"] = 4.6605\n",
    "# sim.input[\"TIT\"] = 1100.0\n",
    "# sim.input[\"TAT\"] = 526.21\n",
    "sim.input[\"TIT\"] = 1032.5\n",
    "sim.input[\"TAT\"] = 524.71\n",
    "sim.compute()\n",
    "sim.print_state()\n",
    "display(sim.output[\"CO\"])\n",
    "CO.view(sim=sim)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "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>AH</th>\n",
       "      <th>TIT</th>\n",
       "      <th>TAT</th>\n",
       "      <th>Real</th>\n",
       "      <th>Inferred</th>\n",
       "      <th>RMSE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4480</th>\n",
       "      <td>83.256</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>540.65</td>\n",
       "      <td>0.3527</td>\n",
       "      <td>1.030988</td>\n",
       "      <td>0.678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24883</th>\n",
       "      <td>73.583</td>\n",
       "      <td>1099.8</td>\n",
       "      <td>538.53</td>\n",
       "      <td>1.2522</td>\n",
       "      <td>1.054438</td>\n",
       "      <td>0.198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21557</th>\n",
       "      <td>81.089</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>534.04</td>\n",
       "      <td>1.4718</td>\n",
       "      <td>1.030988</td>\n",
       "      <td>0.441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1705</th>\n",
       "      <td>64.757</td>\n",
       "      <td>1086.6</td>\n",
       "      <td>549.76</td>\n",
       "      <td>1.3117</td>\n",
       "      <td>2.037783</td>\n",
       "      <td>0.726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21388</th>\n",
       "      <td>75.645</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>534.21</td>\n",
       "      <td>1.7835</td>\n",
       "      <td>1.030988</td>\n",
       "      <td>0.753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36422</th>\n",
       "      <td>69.953</td>\n",
       "      <td>1076.7</td>\n",
       "      <td>549.96</td>\n",
       "      <td>2.9304</td>\n",
       "      <td>2.405596</td>\n",
       "      <td>0.525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21816</th>\n",
       "      <td>70.858</td>\n",
       "      <td>1087.8</td>\n",
       "      <td>549.43</td>\n",
       "      <td>1.7219</td>\n",
       "      <td>1.978597</td>\n",
       "      <td>0.257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34158</th>\n",
       "      <td>47.855</td>\n",
       "      <td>1085.2</td>\n",
       "      <td>549.91</td>\n",
       "      <td>1.5878</td>\n",
       "      <td>2.102088</td>\n",
       "      <td>0.514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12784</th>\n",
       "      <td>69.850</td>\n",
       "      <td>1090.5</td>\n",
       "      <td>550.26</td>\n",
       "      <td>2.0753</td>\n",
       "      <td>1.829492</td>\n",
       "      <td>0.246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30182</th>\n",
       "      <td>70.275</td>\n",
       "      <td>1060.9</td>\n",
       "      <td>550.13</td>\n",
       "      <td>4.1917</td>\n",
       "      <td>2.703573</td>\n",
       "      <td>1.488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3996</th>\n",
       "      <td>61.376</td>\n",
       "      <td>1092.2</td>\n",
       "      <td>549.89</td>\n",
       "      <td>0.3633</td>\n",
       "      <td>1.722400</td>\n",
       "      <td>1.359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31492</th>\n",
       "      <td>63.967</td>\n",
       "      <td>1085.9</td>\n",
       "      <td>549.98</td>\n",
       "      <td>2.0315</td>\n",
       "      <td>2.070541</td>\n",
       "      <td>0.039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36021</th>\n",
       "      <td>61.707</td>\n",
       "      <td>1081.1</td>\n",
       "      <td>549.34</td>\n",
       "      <td>2.3146</td>\n",
       "      <td>2.264986</td>\n",
       "      <td>0.050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21791</th>\n",
       "      <td>96.150</td>\n",
       "      <td>1087.7</td>\n",
       "      <td>549.79</td>\n",
       "      <td>1.2175</td>\n",
       "      <td>1.983683</td>\n",
       "      <td>0.766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1054</th>\n",
       "      <td>80.911</td>\n",
       "      <td>1086.1</td>\n",
       "      <td>550.32</td>\n",
       "      <td>1.1838</td>\n",
       "      <td>2.061306</td>\n",
       "      <td>0.878</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           AH     TIT     TAT    Real  Inferred   RMSE\n",
       "4480   83.256  1100.0  540.65  0.3527  1.030988  0.678\n",
       "24883  73.583  1099.8  538.53  1.2522  1.054438  0.198\n",
       "21557  81.089  1100.0  534.04  1.4718  1.030988  0.441\n",
       "1705   64.757  1086.6  549.76  1.3117  2.037783  0.726\n",
       "21388  75.645  1100.0  534.21  1.7835  1.030988  0.753\n",
       "36422  69.953  1076.7  549.96  2.9304  2.405596  0.525\n",
       "21816  70.858  1087.8  549.43  1.7219  1.978597  0.257\n",
       "34158  47.855  1085.2  549.91  1.5878  2.102088  0.514\n",
       "12784  69.850  1090.5  550.26  2.0753  1.829492  0.246\n",
       "30182  70.275  1060.9  550.13  4.1917  2.703573  1.488\n",
       "3996   61.376  1092.2  549.89  0.3633  1.722400  1.359\n",
       "31492  63.967  1085.9  549.98  2.0315  2.070541  0.039\n",
       "36021  61.707  1081.1  549.34  2.3146  2.264986  0.050\n",
       "21791  96.150  1087.7  549.79  1.2175  1.983683  0.766\n",
       "1054   80.911  1086.1  550.32  1.1838  2.061306  0.878"
      ]
     },
     "execution_count": 201,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn import metrics\n",
    "import math\n",
    "\n",
    "\n",
    "def fuzzy_pred(row):\n",
    "    # sim.input[\"AT\"] = row[\"AT\"]\n",
    "    # sim.input[\"AP\"] = row[\"AP\"]\n",
    "    # sim.input[\"AH\"] = row[\"AH\"]\n",
    "    # sim.input[\"AFDP\"] = row[\"AFDP\"]\n",
    "    sim.input[\"TIT\"] = row[\"TIT\"]\n",
    "    sim.input[\"TAT\"] = row[\"TAT\"]\n",
    "    sim.compute()\n",
    "    return sim.output[\"CO\"]\n",
    "\n",
    "\n",
    "def rmse(row):\n",
    "    return math.sqrt(metrics.mean_squared_error([row[\"Real\"]], [row[\"Inferred\"]]))\n",
    "\n",
    "result_train = X_train.copy()\n",
    "result_train[\"Real\"] = y_train\n",
    "result_train = result_train[:10000]\n",
    "\n",
    "result_train[\"Inferred\"] = result_train.apply(fuzzy_pred, axis=1)\n",
    "result_train[\"RMSE\"] = result_train.apply(rmse, axis=1)\n",
    "result_train = result_train.round({\"RMSE\": 3})\n",
    "result_train.head(15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "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>AH</th>\n",
       "      <th>TIT</th>\n",
       "      <th>TAT</th>\n",
       "      <th>Real</th>\n",
       "      <th>Inferred</th>\n",
       "      <th>RMSE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18246</th>\n",
       "      <td>84.837</td>\n",
       "      <td>1088.7</td>\n",
       "      <td>550.39</td>\n",
       "      <td>1.34970</td>\n",
       "      <td>1.931475</td>\n",
       "      <td>0.582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20343</th>\n",
       "      <td>59.574</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>542.01</td>\n",
       "      <td>1.63430</td>\n",
       "      <td>1.030988</td>\n",
       "      <td>0.603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2924</th>\n",
       "      <td>81.262</td>\n",
       "      <td>1092.9</td>\n",
       "      <td>544.91</td>\n",
       "      <td>0.78632</td>\n",
       "      <td>1.674815</td>\n",
       "      <td>0.888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>88.135</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>526.21</td>\n",
       "      <td>0.72742</td>\n",
       "      <td>1.227915</td>\n",
       "      <td>0.500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5713</th>\n",
       "      <td>86.846</td>\n",
       "      <td>1080.2</td>\n",
       "      <td>550.25</td>\n",
       "      <td>1.35980</td>\n",
       "      <td>2.296405</td>\n",
       "      <td>0.937</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21917</th>\n",
       "      <td>75.935</td>\n",
       "      <td>1081.1</td>\n",
       "      <td>549.66</td>\n",
       "      <td>1.45140</td>\n",
       "      <td>2.264986</td>\n",
       "      <td>0.814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13099</th>\n",
       "      <td>78.314</td>\n",
       "      <td>1089.8</td>\n",
       "      <td>550.37</td>\n",
       "      <td>1.00960</td>\n",
       "      <td>1.870484</td>\n",
       "      <td>0.861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26704</th>\n",
       "      <td>79.478</td>\n",
       "      <td>1073.0</td>\n",
       "      <td>550.19</td>\n",
       "      <td>2.01190</td>\n",
       "      <td>2.501657</td>\n",
       "      <td>0.490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4182</th>\n",
       "      <td>41.623</td>\n",
       "      <td>1100.2</td>\n",
       "      <td>539.10</td>\n",
       "      <td>0.37685</td>\n",
       "      <td>1.007260</td>\n",
       "      <td>0.630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2982</th>\n",
       "      <td>69.233</td>\n",
       "      <td>1091.6</td>\n",
       "      <td>549.98</td>\n",
       "      <td>1.15990</td>\n",
       "      <td>1.761544</td>\n",
       "      <td>0.602</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7347 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           AH     TIT     TAT     Real  Inferred   RMSE\n",
       "18246  84.837  1088.7  550.39  1.34970  1.931475  0.582\n",
       "20343  59.574  1100.0  542.01  1.63430  1.030988  0.603\n",
       "2924   81.262  1092.9  544.91  0.78632  1.674815  0.888\n",
       "117    88.135  1100.0  526.21  0.72742  1.227915  0.500\n",
       "5713   86.846  1080.2  550.25  1.35980  2.296405  0.937\n",
       "...       ...     ...     ...      ...       ...    ...\n",
       "21917  75.935  1081.1  549.66  1.45140  2.264986  0.814\n",
       "13099  78.314  1089.8  550.37  1.00960  1.870484  0.861\n",
       "26704  79.478  1073.0  550.19  2.01190  2.501657  0.490\n",
       "4182   41.623  1100.2  539.10  0.37685  1.007260  0.630\n",
       "2982   69.233  1091.6  549.98  1.15990  1.761544  0.602\n",
       "\n",
       "[7347 rows x 6 columns]"
      ]
     },
     "execution_count": 202,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_test = X_test.copy()\n",
    "result_test[\"Real\"] = y_test\n",
    "\n",
    "result_test[\"Inferred\"] = result_test.apply(fuzzy_pred, axis=1)\n",
    "result_test[\"RMSE\"] = result_test.apply(rmse, axis=1)\n",
    "result_test = result_test.round({\"RMSE\": 3})\n",
    "result_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "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>AH</th>\n",
       "      <th>TIT</th>\n",
       "      <th>TAT</th>\n",
       "      <th>Real</th>\n",
       "      <th>Inferred</th>\n",
       "      <th>RMSE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7673</th>\n",
       "      <td>87.114</td>\n",
       "      <td>1032.5</td>\n",
       "      <td>524.71</td>\n",
       "      <td>43.397</td>\n",
       "      <td>9.796845</td>\n",
       "      <td>33.600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23461</th>\n",
       "      <td>86.171</td>\n",
       "      <td>1011.7</td>\n",
       "      <td>523.67</td>\n",
       "      <td>34.267</td>\n",
       "      <td>12.157933</td>\n",
       "      <td>22.109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7566</th>\n",
       "      <td>96.843</td>\n",
       "      <td>1048.1</td>\n",
       "      <td>532.44</td>\n",
       "      <td>31.538</td>\n",
       "      <td>3.713874</td>\n",
       "      <td>27.824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6451</th>\n",
       "      <td>75.234</td>\n",
       "      <td>1086.5</td>\n",
       "      <td>549.41</td>\n",
       "      <td>30.866</td>\n",
       "      <td>2.042539</td>\n",
       "      <td>28.823</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30712</th>\n",
       "      <td>41.576</td>\n",
       "      <td>1085.4</td>\n",
       "      <td>549.99</td>\n",
       "      <td>26.286</td>\n",
       "      <td>2.093210</td>\n",
       "      <td>24.193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23299</th>\n",
       "      <td>86.811</td>\n",
       "      <td>1020.8</td>\n",
       "      <td>527.23</td>\n",
       "      <td>25.431</td>\n",
       "      <td>9.787437</td>\n",
       "      <td>15.644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24429</th>\n",
       "      <td>90.582</td>\n",
       "      <td>1032.7</td>\n",
       "      <td>527.79</td>\n",
       "      <td>25.248</td>\n",
       "      <td>8.521376</td>\n",
       "      <td>16.727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30711</th>\n",
       "      <td>42.412</td>\n",
       "      <td>1085.4</td>\n",
       "      <td>549.83</td>\n",
       "      <td>24.239</td>\n",
       "      <td>2.093210</td>\n",
       "      <td>22.146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28102</th>\n",
       "      <td>82.969</td>\n",
       "      <td>1021.3</td>\n",
       "      <td>528.98</td>\n",
       "      <td>22.648</td>\n",
       "      <td>8.826828</td>\n",
       "      <td>13.821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13945</th>\n",
       "      <td>97.060</td>\n",
       "      <td>1036.7</td>\n",
       "      <td>531.58</td>\n",
       "      <td>22.364</td>\n",
       "      <td>5.647694</td>\n",
       "      <td>16.716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28103</th>\n",
       "      <td>82.795</td>\n",
       "      <td>1023.8</td>\n",
       "      <td>530.13</td>\n",
       "      <td>21.538</td>\n",
       "      <td>7.724971</td>\n",
       "      <td>13.813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13606</th>\n",
       "      <td>93.559</td>\n",
       "      <td>1059.2</td>\n",
       "      <td>538.95</td>\n",
       "      <td>19.798</td>\n",
       "      <td>2.719744</td>\n",
       "      <td>17.078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7475</th>\n",
       "      <td>90.801</td>\n",
       "      <td>1062.8</td>\n",
       "      <td>538.95</td>\n",
       "      <td>17.437</td>\n",
       "      <td>2.682083</td>\n",
       "      <td>14.755</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21909</th>\n",
       "      <td>94.108</td>\n",
       "      <td>1024.9</td>\n",
       "      <td>530.78</td>\n",
       "      <td>16.883</td>\n",
       "      <td>7.024421</td>\n",
       "      <td>9.859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23319</th>\n",
       "      <td>99.787</td>\n",
       "      <td>1036.5</td>\n",
       "      <td>540.31</td>\n",
       "      <td>16.707</td>\n",
       "      <td>5.784987</td>\n",
       "      <td>10.922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14132</th>\n",
       "      <td>86.278</td>\n",
       "      <td>1056.5</td>\n",
       "      <td>539.51</td>\n",
       "      <td>16.487</td>\n",
       "      <td>2.739673</td>\n",
       "      <td>13.747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31058</th>\n",
       "      <td>76.429</td>\n",
       "      <td>1020.6</td>\n",
       "      <td>534.28</td>\n",
       "      <td>15.436</td>\n",
       "      <td>7.386979</td>\n",
       "      <td>8.049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35692</th>\n",
       "      <td>77.444</td>\n",
       "      <td>1024.2</td>\n",
       "      <td>537.25</td>\n",
       "      <td>14.354</td>\n",
       "      <td>6.957822</td>\n",
       "      <td>7.396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35767</th>\n",
       "      <td>82.608</td>\n",
       "      <td>1023.9</td>\n",
       "      <td>537.28</td>\n",
       "      <td>14.335</td>\n",
       "      <td>6.984216</td>\n",
       "      <td>7.351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16283</th>\n",
       "      <td>97.666</td>\n",
       "      <td>1037.7</td>\n",
       "      <td>536.87</td>\n",
       "      <td>14.330</td>\n",
       "      <td>5.645364</td>\n",
       "      <td>8.685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35538</th>\n",
       "      <td>57.388</td>\n",
       "      <td>1025.0</td>\n",
       "      <td>537.06</td>\n",
       "      <td>14.319</td>\n",
       "      <td>6.889985</td>\n",
       "      <td>7.429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29463</th>\n",
       "      <td>62.448</td>\n",
       "      <td>1023.4</td>\n",
       "      <td>532.80</td>\n",
       "      <td>14.022</td>\n",
       "      <td>7.133375</td>\n",
       "      <td>6.889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16142</th>\n",
       "      <td>86.553</td>\n",
       "      <td>1031.2</td>\n",
       "      <td>531.64</td>\n",
       "      <td>13.972</td>\n",
       "      <td>6.305942</td>\n",
       "      <td>7.666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36332</th>\n",
       "      <td>85.795</td>\n",
       "      <td>1028.2</td>\n",
       "      <td>533.72</td>\n",
       "      <td>13.921</td>\n",
       "      <td>6.634563</td>\n",
       "      <td>7.286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31061</th>\n",
       "      <td>74.602</td>\n",
       "      <td>1024.8</td>\n",
       "      <td>537.19</td>\n",
       "      <td>13.808</td>\n",
       "      <td>6.904978</td>\n",
       "      <td>6.903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29491</th>\n",
       "      <td>57.403</td>\n",
       "      <td>1024.9</td>\n",
       "      <td>527.72</td>\n",
       "      <td>13.798</td>\n",
       "      <td>9.191775</td>\n",
       "      <td>4.606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16308</th>\n",
       "      <td>94.312</td>\n",
       "      <td>1038.0</td>\n",
       "      <td>537.41</td>\n",
       "      <td>13.694</td>\n",
       "      <td>5.608827</td>\n",
       "      <td>8.085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17015</th>\n",
       "      <td>91.229</td>\n",
       "      <td>1037.3</td>\n",
       "      <td>536.74</td>\n",
       "      <td>13.535</td>\n",
       "      <td>5.693009</td>\n",
       "      <td>7.842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16440</th>\n",
       "      <td>90.749</td>\n",
       "      <td>1038.9</td>\n",
       "      <td>538.70</td>\n",
       "      <td>13.427</td>\n",
       "      <td>5.494759</td>\n",
       "      <td>7.932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6200</th>\n",
       "      <td>74.598</td>\n",
       "      <td>1026.4</td>\n",
       "      <td>531.47</td>\n",
       "      <td>13.401</td>\n",
       "      <td>6.828658</td>\n",
       "      <td>6.572</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           AH     TIT     TAT    Real   Inferred    RMSE\n",
       "7673   87.114  1032.5  524.71  43.397   9.796845  33.600\n",
       "23461  86.171  1011.7  523.67  34.267  12.157933  22.109\n",
       "7566   96.843  1048.1  532.44  31.538   3.713874  27.824\n",
       "6451   75.234  1086.5  549.41  30.866   2.042539  28.823\n",
       "30712  41.576  1085.4  549.99  26.286   2.093210  24.193\n",
       "23299  86.811  1020.8  527.23  25.431   9.787437  15.644\n",
       "24429  90.582  1032.7  527.79  25.248   8.521376  16.727\n",
       "30711  42.412  1085.4  549.83  24.239   2.093210  22.146\n",
       "28102  82.969  1021.3  528.98  22.648   8.826828  13.821\n",
       "13945  97.060  1036.7  531.58  22.364   5.647694  16.716\n",
       "28103  82.795  1023.8  530.13  21.538   7.724971  13.813\n",
       "13606  93.559  1059.2  538.95  19.798   2.719744  17.078\n",
       "7475   90.801  1062.8  538.95  17.437   2.682083  14.755\n",
       "21909  94.108  1024.9  530.78  16.883   7.024421   9.859\n",
       "23319  99.787  1036.5  540.31  16.707   5.784987  10.922\n",
       "14132  86.278  1056.5  539.51  16.487   2.739673  13.747\n",
       "31058  76.429  1020.6  534.28  15.436   7.386979   8.049\n",
       "35692  77.444  1024.2  537.25  14.354   6.957822   7.396\n",
       "35767  82.608  1023.9  537.28  14.335   6.984216   7.351\n",
       "16283  97.666  1037.7  536.87  14.330   5.645364   8.685\n",
       "35538  57.388  1025.0  537.06  14.319   6.889985   7.429\n",
       "29463  62.448  1023.4  532.80  14.022   7.133375   6.889\n",
       "16142  86.553  1031.2  531.64  13.972   6.305942   7.666\n",
       "36332  85.795  1028.2  533.72  13.921   6.634563   7.286\n",
       "31061  74.602  1024.8  537.19  13.808   6.904978   6.903\n",
       "29491  57.403  1024.9  527.72  13.798   9.191775   4.606\n",
       "16308  94.312  1038.0  537.41  13.694   5.608827   8.085\n",
       "17015  91.229  1037.3  536.74  13.535   5.693009   7.842\n",
       "16440  90.749  1038.9  538.70  13.427   5.494759   7.932\n",
       "6200   74.598  1026.4  531.47  13.401   6.828658   6.572"
      ]
     },
     "execution_count": 209,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_test.sort_values(by=\"Real\", ascending=False).head(30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'RMSE_train': 1.7299137907376438,\n",
       " 'RMSE_test': 1.698938435821616,\n",
       " 'RMAE_train': 0.9848798137462832,\n",
       " 'RMAE_test': 0.9911061203140067,\n",
       " 'MAE_train': 0.9699882475249134,\n",
       " 'MAE_test': 0.9822913417238822,\n",
       " 'R2_train': 0.4294619850284326,\n",
       " 'R2_test': 0.4301952907925036}"
      ]
     },
     "execution_count": 203,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rmetrics = {}\n",
    "rmetrics[\"RMSE_train\"] = math.sqrt(\n",
    "    metrics.mean_squared_error(result_train[\"Real\"], result_train[\"Inferred\"])\n",
    ")\n",
    "rmetrics[\"RMSE_test\"] = math.sqrt(\n",
    "    metrics.mean_squared_error(result_test[\"Real\"], result_test[\"Inferred\"])\n",
    ")\n",
    "rmetrics[\"RMAE_train\"] = math.sqrt(\n",
    "    metrics.mean_absolute_error(result_train[\"Real\"], result_train[\"Inferred\"])\n",
    ")\n",
    "rmetrics[\"RMAE_test\"] = math.sqrt(\n",
    "    metrics.mean_absolute_error(result_test[\"Real\"], result_test[\"Inferred\"])\n",
    ")\n",
    "rmetrics[\"MAE_train\"] = float(\n",
    "    metrics.mean_absolute_error(result_train[\"Real\"], result_train[\"Inferred\"])\n",
    ")\n",
    "rmetrics[\"MAE_test\"] = float(\n",
    "    metrics.mean_absolute_error(result_test[\"Real\"], result_test[\"Inferred\"])\n",
    ")\n",
    "rmetrics[\"R2_train\"] = metrics.r2_score(result_train[\"Real\"], result_train[\"Inferred\"])\n",
    "rmetrics[\"R2_test\"] = metrics.r2_score(result_test[\"Real\"], result_test[\"Inferred\"])\n",
    "\n",
    "rmetrics"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "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": "3.12.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}