fork-of-houseprices.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "75b9e129",
   "metadata": {
    "papermill": {
     "duration": 0.018162,
     "end_time": "2022-08-10T15:30:24.560081",
     "exception": false,
     "start_time": "2022-08-10T15:30:24.541919",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Fork of Ryan Holbrook notebook, it is implemented:\n",
    "\n",
    "* More EDA\n",
    "* New Models\n",
    "* Hybrid Model\n",
    "* Tuning of the Hiperparameters, used library `Optuna`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b3ea6251",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:24.597167Z",
     "iopub.status.busy": "2022-08-10T15:30:24.596446Z",
     "iopub.status.idle": "2022-08-10T15:30:26.608671Z",
     "shell.execute_reply": "2022-08-10T15:30:26.607535Z"
    },
    "papermill": {
     "duration": 2.033279,
     "end_time": "2022-08-10T15:30:26.611935",
     "exception": false,
     "start_time": "2022-08-10T15:30:24.578656",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import warnings\n",
    "from pathlib import Path\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "from IPython.display import display\n",
    "from pandas.api.types import CategoricalDtype\n",
    "\n",
    "from scipy import stats\n",
    "from scipy.stats import norm\n",
    "\n",
    "from category_encoders import MEstimateEncoder\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.feature_selection import mutual_info_regression\n",
    "from sklearn.model_selection import KFold, cross_val_score\n",
    "from xgboost import XGBClassifier, XGBRegressor\n",
    "\n",
    "\n",
    "from sklearn.pipeline import make_pipeline\n",
    "from sklearn.preprocessing import RobustScaler\n",
    "from sklearn.linear_model import Ridge\n",
    "from sklearn.svm import SVR\n",
    "\n",
    "# Set Matplotlib defaults\n",
    "plt.style.use(\"seaborn-whitegrid\")\n",
    "plt.rc(\"figure\", autolayout=True)\n",
    "plt.rc(\n",
    "    \"axes\",\n",
    "    labelweight=\"bold\",\n",
    "    labelsize=\"large\",\n",
    "    titleweight=\"bold\",\n",
    "    titlesize=14,\n",
    "    titlepad=10,\n",
    ")\n",
    "\n",
    "# Mute warnings\n",
    "warnings.filterwarnings('ignore')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "013396cd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:26.648957Z",
     "iopub.status.busy": "2022-08-10T15:30:26.648281Z",
     "iopub.status.idle": "2022-08-10T15:30:26.654468Z",
     "shell.execute_reply": "2022-08-10T15:30:26.653709Z"
    },
    "papermill": {
     "duration": 0.027139,
     "end_time": "2022-08-10T15:30:26.656532",
     "exception": false,
     "start_time": "2022-08-10T15:30:26.629393",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def load_data():\n",
    "    # Read data\n",
    "    data_dir = Path(\"../input/house-prices-advanced-regression-techniques/\")\n",
    "\n",
    "    df_train = pd.read_csv(data_dir / \"train.csv\", index_col=\"Id\")\n",
    "    df_test = pd.read_csv(data_dir / \"test.csv\", index_col=\"Id\")\n",
    "    # Merge the splits so we can process them together\n",
    "    df = pd.concat([df_train, df_test])\n",
    "    # Preprocessing\n",
    "    df = clean(df)\n",
    "    df = encode(df)\n",
    "    df = impute(df)\n",
    "    # Reform splits\n",
    "    df_train = df.loc[df_train.index, :]\n",
    "    df_test = df.loc[df_test.index, :]\n",
    "    return df_train, df_test\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "879c99b9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:26.692175Z",
     "iopub.status.busy": "2022-08-10T15:30:26.691456Z",
     "iopub.status.idle": "2022-08-10T15:30:26.781794Z",
     "shell.execute_reply": "2022-08-10T15:30:26.779811Z"
    },
    "papermill": {
     "duration": 0.112856,
     "end_time": "2022-08-10T15:30:26.785386",
     "exception": false,
     "start_time": "2022-08-10T15:30:26.672530",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1460, 80) (1459, 79)\n"
     ]
    }
   ],
   "source": [
    "data_dir = Path(\"../input/house-prices-advanced-regression-techniques/\")\n",
    "dfTrain = pd.read_csv(data_dir / \"train.csv\", index_col=\"Id\")\n",
    "dfTest = pd.read_csv(data_dir / \"test.csv\", index_col=\"Id\")\n",
    "\n",
    "\n",
    "dfTrain.Exterior2nd.unique()\n",
    "print( dfTrain.shape, dfTest.shape )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0007e6ba",
   "metadata": {
    "papermill": {
     "duration": 0.016165,
     "end_time": "2022-08-10T15:30:26.820192",
     "exception": false,
     "start_time": "2022-08-10T15:30:26.804027",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# EDA"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5c9677a",
   "metadata": {
    "papermill": {
     "duration": 0.015804,
     "end_time": "2022-08-10T15:30:26.852169",
     "exception": false,
     "start_time": "2022-08-10T15:30:26.836365",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "First, we will analysis target(depend variable) `SalePrice`. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e44012e2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:26.887795Z",
     "iopub.status.busy": "2022-08-10T15:30:26.887359Z",
     "iopub.status.idle": "2022-08-10T15:30:27.584535Z",
     "shell.execute_reply": "2022-08-10T15:30:27.583381Z"
    },
    "papermill": {
     "duration": 0.718257,
     "end_time": "2022-08-10T15:30:27.587041",
     "exception": false,
     "start_time": "2022-08-10T15:30:26.868784",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count      1460.000000\n",
       "mean     180921.195890\n",
       "std       79442.502883\n",
       "min       34900.000000\n",
       "25%      129975.000000\n",
       "50%      163000.000000\n",
       "75%      214000.000000\n",
       "max      755000.000000\n",
       "Name: SalePrice, dtype: float64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Y = dfTrain[\"SalePrice\"]\n",
    "sns.distplot(Y, fit =  norm)\n",
    "fig = plt.figure()\n",
    "res = stats.probplot(dfTrain['SalePrice'], plot=plt)\n",
    "\n",
    "Y.describe()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "40ca0844",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T12:05:46.678770Z",
     "iopub.status.busy": "2022-08-10T12:05:46.678369Z",
     "iopub.status.idle": "2022-08-10T12:05:46.686902Z",
     "shell.execute_reply": "2022-08-10T12:05:46.685451Z",
     "shell.execute_reply.started": "2022-08-10T12:05:46.678740Z"
    },
    "papermill": {
     "duration": 0.017987,
     "end_time": "2022-08-10T15:30:27.623079",
     "exception": false,
     "start_time": "2022-08-10T15:30:27.605092",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Skewness and Kurtosis\n",
    "\n",
    "We see that the Target, show asymetric distribution with skew positive. While, the Kurtosis have highe value to indicate the presence of some outliears. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d9441ee8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:27.659202Z",
     "iopub.status.busy": "2022-08-10T15:30:27.658763Z",
     "iopub.status.idle": "2022-08-10T15:30:27.666247Z",
     "shell.execute_reply": "2022-08-10T15:30:27.664631Z"
    },
    "papermill": {
     "duration": 0.028412,
     "end_time": "2022-08-10T15:30:27.668740",
     "exception": false,
     "start_time": "2022-08-10T15:30:27.640328",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Skewness: 1.882876\n",
      "Kurtosis: 6.536282\n"
     ]
    }
   ],
   "source": [
    "print(\"Skewness: %f\" % dfTrain['SalePrice'].skew())\n",
    "print(\"Kurtosis: %f\" % dfTrain['SalePrice'].kurt())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0f31833",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T12:05:46.689368Z",
     "iopub.status.busy": "2022-08-10T12:05:46.688646Z",
     "iopub.status.idle": "2022-08-10T12:05:47.093215Z",
     "shell.execute_reply": "2022-08-10T12:05:47.091976Z",
     "shell.execute_reply.started": "2022-08-10T12:05:46.689323Z"
    },
    "papermill": {
     "duration": 0.017709,
     "end_time": "2022-08-10T15:30:27.703730",
     "exception": false,
     "start_time": "2022-08-10T15:30:27.686021",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Plot Categorical Variable \"Overallqual\" \n",
    "\n",
    "Box plot overallqual/saleprice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "12f5a1cc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:27.740494Z",
     "iopub.status.busy": "2022-08-10T15:30:27.739340Z",
     "iopub.status.idle": "2022-08-10T15:30:28.137356Z",
     "shell.execute_reply": "2022-08-10T15:30:28.136058Z"
    },
    "papermill": {
     "duration": 0.418642,
     "end_time": "2022-08-10T15:30:28.139809",
     "exception": false,
     "start_time": "2022-08-10T15:30:27.721167",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "var = 'OverallQual'\n",
    "data = pd.concat([dfTrain['SalePrice'], dfTrain[var]], axis=1)\n",
    "f, ax = plt.subplots(figsize=(8, 6))\n",
    "fig = sns.boxplot(x=var, y=\"SalePrice\", data=data)\n",
    "fig.axis(ymin=0, ymax=800000);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b05bfe8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T12:05:47.095527Z",
     "iopub.status.busy": "2022-08-10T12:05:47.094930Z",
     "iopub.status.idle": "2022-08-10T12:05:56.024564Z",
     "shell.execute_reply": "2022-08-10T12:05:56.023331Z",
     "shell.execute_reply.started": "2022-08-10T12:05:47.095481Z"
    },
    "papermill": {
     "duration": 0.017645,
     "end_time": "2022-08-10T15:30:28.175293",
     "exception": false,
     "start_time": "2022-08-10T15:30:28.157648",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Scatterplots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "41166c7f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:28.213690Z",
     "iopub.status.busy": "2022-08-10T15:30:28.213002Z",
     "iopub.status.idle": "2022-08-10T15:30:37.502938Z",
     "shell.execute_reply": "2022-08-10T15:30:37.501212Z"
    },
    "papermill": {
     "duration": 9.316123,
     "end_time": "2022-08-10T15:30:37.509637",
     "exception": false,
     "start_time": "2022-08-10T15:30:28.193514",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1260x1260 with 56 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set()\n",
    "cols = ['SalePrice', 'OverallQual', 'GrLivArea', 'GarageCars', 'TotalBsmtSF', 'FullBath', 'YearBuilt']\n",
    "sns.pairplot(dfTrain[cols], size = 2.5)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35bcddf2",
   "metadata": {
    "papermill": {
     "duration": 0.022963,
     "end_time": "2022-08-10T15:30:37.556228",
     "exception": false,
     "start_time": "2022-08-10T15:30:37.533265",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Missing Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "57986445",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:37.604683Z",
     "iopub.status.busy": "2022-08-10T15:30:37.603733Z",
     "iopub.status.idle": "2022-08-10T15:30:37.634800Z",
     "shell.execute_reply": "2022-08-10T15:30:37.633990Z"
    },
    "papermill": {
     "duration": 0.057549,
     "end_time": "2022-08-10T15:30:37.636815",
     "exception": false,
     "start_time": "2022-08-10T15:30:37.579266",
     "status": "completed"
    },
    "tags": []
   },
   "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>Total</th>\n",
       "      <th>Percent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>PoolQC</th>\n",
       "      <td>1453</td>\n",
       "      <td>0.995205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MiscFeature</th>\n",
       "      <td>1406</td>\n",
       "      <td>0.963014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alley</th>\n",
       "      <td>1369</td>\n",
       "      <td>0.937671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fence</th>\n",
       "      <td>1179</td>\n",
       "      <td>0.807534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FireplaceQu</th>\n",
       "      <td>690</td>\n",
       "      <td>0.472603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LotFrontage</th>\n",
       "      <td>259</td>\n",
       "      <td>0.177397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageYrBlt</th>\n",
       "      <td>81</td>\n",
       "      <td>0.055479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageCond</th>\n",
       "      <td>81</td>\n",
       "      <td>0.055479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageType</th>\n",
       "      <td>81</td>\n",
       "      <td>0.055479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageFinish</th>\n",
       "      <td>81</td>\n",
       "      <td>0.055479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageQual</th>\n",
       "      <td>81</td>\n",
       "      <td>0.055479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtExposure</th>\n",
       "      <td>38</td>\n",
       "      <td>0.026027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtFinType2</th>\n",
       "      <td>38</td>\n",
       "      <td>0.026027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtCond</th>\n",
       "      <td>37</td>\n",
       "      <td>0.025342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtQual</th>\n",
       "      <td>37</td>\n",
       "      <td>0.025342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtFinType1</th>\n",
       "      <td>37</td>\n",
       "      <td>0.025342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MasVnrArea</th>\n",
       "      <td>8</td>\n",
       "      <td>0.005479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MasVnrType</th>\n",
       "      <td>8</td>\n",
       "      <td>0.005479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Electrical</th>\n",
       "      <td>1</td>\n",
       "      <td>0.000685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MSSubClass</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Total   Percent\n",
       "PoolQC         1453  0.995205\n",
       "MiscFeature    1406  0.963014\n",
       "Alley          1369  0.937671\n",
       "Fence          1179  0.807534\n",
       "FireplaceQu     690  0.472603\n",
       "LotFrontage     259  0.177397\n",
       "GarageYrBlt      81  0.055479\n",
       "GarageCond       81  0.055479\n",
       "GarageType       81  0.055479\n",
       "GarageFinish     81  0.055479\n",
       "GarageQual       81  0.055479\n",
       "BsmtExposure     38  0.026027\n",
       "BsmtFinType2     38  0.026027\n",
       "BsmtCond         37  0.025342\n",
       "BsmtQual         37  0.025342\n",
       "BsmtFinType1     37  0.025342\n",
       "MasVnrArea        8  0.005479\n",
       "MasVnrType        8  0.005479\n",
       "Electrical        1  0.000685\n",
       "MSSubClass        0  0.000000"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total = dfTrain.isnull().sum().sort_values(ascending=False)\n",
    "percent = (dfTrain.isnull().sum()/dfTrain.isnull().count()).sort_values(ascending=False)\n",
    "missing_data = pd.concat([total, percent], axis=1, keys=['Total', 'Percent'])\n",
    "missing_data.head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25631ae9",
   "metadata": {
    "papermill": {
     "duration": 0.022404,
     "end_time": "2022-08-10T15:30:37.682579",
     "exception": false,
     "start_time": "2022-08-10T15:30:37.660175",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Clean Data ###\n",
    "\n",
    "Some of the categorical features in this dataset have what are apparently typos in their categories:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74585070",
   "metadata": {
    "papermill": {
     "duration": 0.023075,
     "end_time": "2022-08-10T15:30:37.728946",
     "exception": false,
     "start_time": "2022-08-10T15:30:37.705871",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Comparing these to `data_description.txt` shows us what needs cleaning. We'll take care of a couple of issues here, but you might want to evaluate this data further."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "3f3bb64b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:37.776891Z",
     "iopub.status.busy": "2022-08-10T15:30:37.776184Z",
     "iopub.status.idle": "2022-08-10T15:30:37.782509Z",
     "shell.execute_reply": "2022-08-10T15:30:37.781344Z"
    },
    "papermill": {
     "duration": 0.032919,
     "end_time": "2022-08-10T15:30:37.784813",
     "exception": false,
     "start_time": "2022-08-10T15:30:37.751894",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# read data_description for more cleaning\n",
    "\n",
    "def clean(df):\n",
    "    df[\"Exterior2nd\"] = df[\"Exterior2nd\"].replace({\"Brk Cmn\": \"BrkComm\"})\n",
    "    # Some values of GarageYrBlt are corrupt, so we'll replace them\n",
    "    # with the year the house was built\n",
    "    df[\"GarageYrBlt\"] = df[\"GarageYrBlt\"].where(df.GarageYrBlt <= 2010, df.YearBuilt)\n",
    "    # Names beginning with numbers are awkward to work with\n",
    "    df.rename(columns={\n",
    "        \"1stFlrSF\": \"FirstFlrSF\",\n",
    "        \"2ndFlrSF\": \"SecondFlrSF\",\n",
    "        \"3SsnPorch\": \"Threeseasonporch\",\n",
    "    }, inplace=True,\n",
    "    )\n",
    "    return df\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b3a7ed4",
   "metadata": {
    "papermill": {
     "duration": 0.023064,
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     "exception": false,
     "start_time": "2022-08-10T15:30:37.808700",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Encode the Statistical Data Type ###\n",
    "\n",
    "Pandas has Python types corresponding to the standard statistical types (numeric, categorical, etc.). Encoding each feature with its correct type helps ensure each feature is treated appropriately by whatever functions we use, and makes it easier for us to apply transformations consistently. This hidden cell defines the `encode` function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6a14dbee",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "\n",
    "# The numeric features are already encoded correctly (`float` for\n",
    "# continuous, `int` for discrete), but the categoricals we'll need to\n",
    "\n",
    "# do ourselves. Note in particular, that the `MSSubClass` feature is\n",
    "# read as an `int` type, but is actually a (nominative) categorical.\n",
    "\n",
    "# The nominative (unordered) categorical features\n",
    "features_nom = [\"MSSubClass\", \"MSZoning\", \"Street\", \"Alley\", \"LandContour\", \"LotConfig\", \"Neighborhood\", \"Condition1\", \"Condition2\", \"BldgType\", \"HouseStyle\", \"RoofStyle\", \"RoofMatl\", \"Exterior1st\", \"Exterior2nd\", \"MasVnrType\", \"Foundation\", \"Heating\", \"CentralAir\", \"GarageType\", \"MiscFeature\", \"SaleType\", \"SaleCondition\"]\n",
    "\n",
    "\n",
    "# The ordinal (ordered) categorical features \n",
    "\n",
    "# Pandas calls the categories \"levels\"\n",
    "five_levels = [\"Po\", \"Fa\", \"TA\", \"Gd\", \"Ex\"]\n",
    "ten_levels = list(range(10))\n",
    "\n",
    "ordered_levels = {\n",
    "    \"OverallQual\": ten_levels,\n",
    "    \"OverallCond\": ten_levels,\n",
    "    \"ExterQual\": five_levels,\n",
    "    \"ExterCond\": five_levels,\n",
    "    \"BsmtQual\": five_levels,\n",
    "    \"BsmtCond\": five_levels,\n",
    "    \"HeatingQC\": five_levels,\n",
    "    \"KitchenQual\": five_levels,\n",
    "    \"FireplaceQu\": five_levels,\n",
    "    \"GarageQual\": five_levels,\n",
    "    \"GarageCond\": five_levels,\n",
    "    \"PoolQC\": five_levels,\n",
    "    \"LotShape\": [\"Reg\", \"IR1\", \"IR2\", \"IR3\"],\n",
    "    \"LandSlope\": [\"Sev\", \"Mod\", \"Gtl\"],\n",
    "    \"BsmtExposure\": [\"No\", \"Mn\", \"Av\", \"Gd\"],\n",
    "    \"BsmtFinType1\": [\"Unf\", \"LwQ\", \"Rec\", \"BLQ\", \"ALQ\", \"GLQ\"],\n",
    "    \"BsmtFinType2\": [\"Unf\", \"LwQ\", \"Rec\", \"BLQ\", \"ALQ\", \"GLQ\"],\n",
    "    \"Functional\": [\"Sal\", \"Sev\", \"Maj1\", \"Maj2\", \"Mod\", \"Min2\", \"Min1\", \"Typ\"],\n",
    "    \"GarageFinish\": [\"Unf\", \"RFn\", \"Fin\"],\n",
    "    \"PavedDrive\": [\"N\", \"P\", \"Y\"],\n",
    "    \"Utilities\": [\"NoSeWa\", \"NoSewr\", \"AllPub\"],\n",
    "    \"CentralAir\": [\"N\", \"Y\"],\n",
    "    \"Electrical\": [\"Mix\", \"FuseP\", \"FuseF\", \"FuseA\", \"SBrkr\"],\n",
    "    \"Fence\": [\"MnWw\", \"GdWo\", \"MnPrv\", \"GdPrv\"],\n",
    "}\n",
    "\n",
    "# Add a None level for missing values\n",
    "ordered_levels = {key: [\"None\"] + value for key, value in\n",
    "                  ordered_levels.items()}\n",
    "\n",
    "\n",
    "def encode(df):\n",
    "    # Nominal categories\n",
    "    for name in features_nom:\n",
    "        df[name] = df[name].astype(\"category\")\n",
    "        # Add a None category for missing values\n",
    "        if \"None\" not in df[name].cat.categories:\n",
    "            df[name].cat.add_categories(\"None\", inplace=True)\n",
    "    # Ordinal categories\n",
    "    for name, levels in ordered_levels.items():\n",
    "        df[name] = df[name].astype(CategoricalDtype(levels,\n",
    "                                                    ordered=True))\n",
    "    return df\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "44d3809f",
   "metadata": {
    "papermill": {
     "duration": 0.022717,
     "end_time": "2022-08-10T15:30:37.941225",
     "exception": false,
     "start_time": "2022-08-10T15:30:37.918508",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Handle Missing Values ###\n",
    "\n",
    "Handling missing values now will make the feature engineering go more smoothly. We'll impute `0` for missing numeric values and `\"None\"` for missing categorical values. You might like to experiment with other imputation strategies. In particular, you could try creating \"missing value\" indicators: `1` whenever a value was imputed and `0` otherwise."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7fac2c69",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2022-08-10T15:30:37.996163Z"
    },
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     "status": "completed"
    },
    "tags": []
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   "outputs": [],
   "source": [
    "def impute(df):\n",
    "    for name in df.select_dtypes(\"number\"):\n",
    "        df[name] = df[name].fillna(0)\n",
    "    for name in df.select_dtypes(\"category\"):\n",
    "        df[name] = df[name].fillna(\"None\")\n",
    "    return df\n",
    "\n",
    "def deleteVariables(DF, tol = 0.15):\n",
    "    df= DF.copy()\n",
    "    total = df.isnull().sum().sort_values(ascending=False)\n",
    "    percent = (df.isnull().sum()/df.isnull().count()).sort_values(ascending=False)\n",
    "    missing_data = pd.concat([total, percent], axis=1, keys=['Total', 'Percent'])\n",
    "    df = df.drop((missing_data[missing_data['percent'] > tol]).index,1)\n",
    "    df = df.drop(df.loc[df ['Electrical'].isnull()].index)\n",
    "    return df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51d117ae",
   "metadata": {
    "papermill": {
     "duration": 0.023215,
     "end_time": "2022-08-10T15:30:38.046829",
     "exception": false,
     "start_time": "2022-08-10T15:30:38.023614",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Load Data ##\n",
    "\n",
    "And now we can call the data loader and get the processed data splits:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b53b4c60",
   "metadata": {
    "execution": {
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 1460 entries, 1 to 1460\n",
      "Data columns (total 80 columns):\n",
      " #   Column            Non-Null Count  Dtype   \n",
      "---  ------            --------------  -----   \n",
      " 0   MSSubClass        1460 non-null   category\n",
      " 1   MSZoning          1460 non-null   category\n",
      " 2   LotFrontage       1460 non-null   float64 \n",
      " 3   LotArea           1460 non-null   int64   \n",
      " 4   Street            1460 non-null   category\n",
      " 5   Alley             1460 non-null   category\n",
      " 6   LotShape          1460 non-null   category\n",
      " 7   LandContour       1460 non-null   category\n",
      " 8   Utilities         1460 non-null   category\n",
      " 9   LotConfig         1460 non-null   category\n",
      " 10  LandSlope         1460 non-null   category\n",
      " 11  Neighborhood      1460 non-null   category\n",
      " 12  Condition1        1460 non-null   category\n",
      " 13  Condition2        1460 non-null   category\n",
      " 14  BldgType          1460 non-null   category\n",
      " 15  HouseStyle        1460 non-null   category\n",
      " 16  OverallQual       1460 non-null   category\n",
      " 17  OverallCond       1460 non-null   category\n",
      " 18  YearBuilt         1460 non-null   int64   \n",
      " 19  YearRemodAdd      1460 non-null   int64   \n",
      " 20  RoofStyle         1460 non-null   category\n",
      " 21  RoofMatl          1460 non-null   category\n",
      " 22  Exterior1st       1460 non-null   category\n",
      " 23  Exterior2nd       1460 non-null   category\n",
      " 24  MasVnrType        1460 non-null   category\n",
      " 25  MasVnrArea        1460 non-null   float64 \n",
      " 26  ExterQual         1460 non-null   category\n",
      " 27  ExterCond         1460 non-null   category\n",
      " 28  Foundation        1460 non-null   category\n",
      " 29  BsmtQual          1460 non-null   category\n",
      " 30  BsmtCond          1460 non-null   category\n",
      " 31  BsmtExposure      1460 non-null   category\n",
      " 32  BsmtFinType1      1460 non-null   category\n",
      " 33  BsmtFinSF1        1460 non-null   float64 \n",
      " 34  BsmtFinType2      1460 non-null   category\n",
      " 35  BsmtFinSF2        1460 non-null   float64 \n",
      " 36  BsmtUnfSF         1460 non-null   float64 \n",
      " 37  TotalBsmtSF       1460 non-null   float64 \n",
      " 38  Heating           1460 non-null   category\n",
      " 39  HeatingQC         1460 non-null   category\n",
      " 40  CentralAir        1460 non-null   category\n",
      " 41  Electrical        1460 non-null   category\n",
      " 42  FirstFlrSF        1460 non-null   int64   \n",
      " 43  SecondFlrSF       1460 non-null   int64   \n",
      " 44  LowQualFinSF      1460 non-null   int64   \n",
      " 45  GrLivArea         1460 non-null   int64   \n",
      " 46  BsmtFullBath      1460 non-null   float64 \n",
      " 47  BsmtHalfBath      1460 non-null   float64 \n",
      " 48  FullBath          1460 non-null   int64   \n",
      " 49  HalfBath          1460 non-null   int64   \n",
      " 50  BedroomAbvGr      1460 non-null   int64   \n",
      " 51  KitchenAbvGr      1460 non-null   int64   \n",
      " 52  KitchenQual       1460 non-null   category\n",
      " 53  TotRmsAbvGrd      1460 non-null   int64   \n",
      " 54  Functional        1460 non-null   category\n",
      " 55  Fireplaces        1460 non-null   int64   \n",
      " 56  FireplaceQu       1460 non-null   category\n",
      " 57  GarageType        1460 non-null   category\n",
      " 58  GarageYrBlt       1460 non-null   float64 \n",
      " 59  GarageFinish      1460 non-null   category\n",
      " 60  GarageCars        1460 non-null   float64 \n",
      " 61  GarageArea        1460 non-null   float64 \n",
      " 62  GarageQual        1460 non-null   category\n",
      " 63  GarageCond        1460 non-null   category\n",
      " 64  PavedDrive        1460 non-null   category\n",
      " 65  WoodDeckSF        1460 non-null   int64   \n",
      " 66  OpenPorchSF       1460 non-null   int64   \n",
      " 67  EnclosedPorch     1460 non-null   int64   \n",
      " 68  Threeseasonporch  1460 non-null   int64   \n",
      " 69  ScreenPorch       1460 non-null   int64   \n",
      " 70  PoolArea          1460 non-null   int64   \n",
      " 71  PoolQC            1460 non-null   category\n",
      " 72  Fence             1460 non-null   category\n",
      " 73  MiscFeature       1460 non-null   category\n",
      " 74  MiscVal           1460 non-null   int64   \n",
      " 75  MoSold            1460 non-null   int64   \n",
      " 76  YrSold            1460 non-null   int64   \n",
      " 77  SaleType          1460 non-null   category\n",
      " 78  SaleCondition     1460 non-null   category\n",
      " 79  SalePrice         1460 non-null   float64 \n",
      "dtypes: category(46), float64(12), int64(22)\n",
      "memory usage: 478.9 KB\n"
     ]
    }
   ],
   "source": [
    "df_train, df_test = load_data()\n",
    "df_train.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce3e6f82",
   "metadata": {
    "papermill": {
     "duration": 0.024044,
     "end_time": "2022-08-10T15:30:38.350208",
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     "start_time": "2022-08-10T15:30:38.326164",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Uncomment and run this cell if you'd like to see what they contain. Notice that `df_test` is\n",
    "missing values for `SalePrice`. (`NA`s were willed with 0's in the imputation step.)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c05e7d0a",
   "metadata": {
    "papermill": {
     "duration": 0.02288,
     "end_time": "2022-08-10T15:30:38.396337",
     "exception": false,
     "start_time": "2022-08-10T15:30:38.373457",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Establish Baseline ##\n",
    "\n",
    "Finally, let's establish a baseline score to judge our feature engineering against.\n",
    "\n",
    "Here is the function we created in Lesson 1 that will compute the cross-validated RMSLE score for a feature set. We've used XGBoost for our model, but you might want to experiment with other models.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "327046ec",
   "metadata": {
    "_kg_hide-input": true,
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   "outputs": [],
   "source": [
    "\n",
    "def score_dataset(X, y, model=XGBRegressor()):\n",
    "    # Label encoding for categoricals\n",
    "    #\n",
    "    # Label encoding is good for XGBoost and RandomForest, but one-hot\n",
    "    # would be better for models like Lasso or Ridge. The `cat.codes`\n",
    "    # attribute holds the category levels.\n",
    "    for colname in X.select_dtypes([\"category\"]):\n",
    "        X[colname] = X[colname].cat.codes\n",
    "    # Metric for Housing competition is RMSLE (Root Mean Squared Log Error)\n",
    "    log_y = np.log(y)\n",
    "    score = cross_val_score(\n",
    "        model, X, log_y, cv=5, scoring=\"neg_mean_squared_error\",\n",
    "    )\n",
    "    score = -1 * score.mean()\n",
    "    score = np.sqrt(score)\n",
    "    return score\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d144f9c4",
   "metadata": {
    "papermill": {
     "duration": 0.023525,
     "end_time": "2022-08-10T15:30:38.501101",
     "exception": false,
     "start_time": "2022-08-10T15:30:38.477576",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "We can reuse this scoring function anytime we want to try out a new feature set. We'll run it now on the processed data with no additional features and get a baseline score:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b68f788e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:38.550243Z",
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    },
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Baseline score: 0.14351 RMSLE\n"
     ]
    }
   ],
   "source": [
    "X = df_train.copy()\n",
    "y = X.pop(\"SalePrice\")\n",
    "\n",
    "baseline_score = score_dataset(X, y)\n",
    "print(f\"Baseline score: {baseline_score:.5f} RMSLE\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1cd0893a",
   "metadata": {
    "papermill": {
     "duration": 0.025408,
     "end_time": "2022-08-10T15:30:41.625476",
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     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "This baseline score helps us to know whether some set of features we've assembled has actually led to any improvement or not.\n",
    "\n",
    "# Step 2 - Feature Utility Scores #\n",
    "\n",
    "In Lesson 2 we saw how to use mutual information to compute a *utility score* for a feature, giving you an indication of how much potential the feature has. This hidden cell defines the two utility functions we used, `make_mi_scores` and `plot_mi_scores`: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "628d8882",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:41.674029Z",
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# mutual information\n",
    "\n",
    "def make_mi_scores(X, y):\n",
    "    X = X.copy()\n",
    "    for colname in X.select_dtypes([\"object\", \"category\"]):\n",
    "        X[colname], _ = X[colname].factorize()\n",
    "    # All discrete features should now have integer dtypes\n",
    "    discrete_features = [pd.api.types.is_integer_dtype(t) for t in X.dtypes]\n",
    "    mi_scores = mutual_info_regression(X, y, discrete_features=discrete_features, random_state=0) # mutual information regression\n",
    "    mi_scores = pd.Series(mi_scores, name=\"MI Scores\", index=X.columns)\n",
    "    mi_scores = mi_scores.sort_values(ascending=False)\n",
    "    return mi_scores\n",
    "\n",
    "\n",
    "def plot_mi_scores(scores):\n",
    "    scores = scores.sort_values(ascending=True)\n",
    "    width = np.arange(len(scores))\n",
    "    ticks = list(scores.index)\n",
    "    plt.barh(width, scores)\n",
    "    plt.yticks(width, ticks)\n",
    "    plt.title(\"Mutual Information Scores\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a35da61",
   "metadata": {
    "papermill": {
     "duration": 0.02471,
     "end_time": "2022-08-10T15:30:41.733425",
     "exception": false,
     "start_time": "2022-08-10T15:30:41.708715",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Let's look at our feature scores again:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "3a61033a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:41.782377Z",
     "iopub.status.busy": "2022-08-10T15:30:41.781660Z",
     "iopub.status.idle": "2022-08-10T15:30:43.408735Z",
     "shell.execute_reply": "2022-08-10T15:30:43.406680Z"
    },
    "papermill": {
     "duration": 1.655941,
     "end_time": "2022-08-10T15:30:43.412601",
     "exception": false,
     "start_time": "2022-08-10T15:30:41.756660",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OverallQual     0.571457\n",
       "Neighborhood    0.526220\n",
       "GrLivArea       0.430395\n",
       "YearBuilt       0.407974\n",
       "LotArea         0.394468\n",
       "                  ...   \n",
       "PoolQC          0.000000\n",
       "MiscFeature     0.000000\n",
       "MiscVal         0.000000\n",
       "MoSold          0.000000\n",
       "YrSold          0.000000\n",
       "Name: MI Scores, Length: 79, dtype: float64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = df_train.copy()\n",
    "y = X.pop(\"SalePrice\")\n",
    "\n",
    "mi_scores = make_mi_scores(X, y)\n",
    "mi_scores"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65823a7c",
   "metadata": {
    "papermill": {
     "duration": 0.024449,
     "end_time": "2022-08-10T15:30:43.461469",
     "exception": false,
     "start_time": "2022-08-10T15:30:43.437020",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "You can see that we have a number of features that are highly informative and also some that don't seem to be informative at all (at least by themselves). As we talked about in Tutorial 2, the top scoring features will usually pay-off the most during feature development, so it could be a good idea to focus your efforts on those. On the other hand, training on uninformative features can lead to overfitting. So, the features with 0.0 scores we'll drop entirely:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "f57cda06",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:43.513496Z",
     "iopub.status.busy": "2022-08-10T15:30:43.513078Z",
     "iopub.status.idle": "2022-08-10T15:30:45.131517Z",
     "shell.execute_reply": "2022-08-10T15:30:45.130304Z"
    },
    "papermill": {
     "duration": 1.64797,
     "end_time": "2022-08-10T15:30:45.134117",
     "exception": false,
     "start_time": "2022-08-10T15:30:43.486147",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_mi_scores(mi_scores  )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "122fa497",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:45.185642Z",
     "iopub.status.busy": "2022-08-10T15:30:45.185243Z",
     "iopub.status.idle": "2022-08-10T15:30:45.289249Z",
     "shell.execute_reply": "2022-08-10T15:30:45.287775Z"
    },
    "papermill": {
     "duration": 0.132573,
     "end_time": "2022-08-10T15:30:45.291787",
     "exception": false,
     "start_time": "2022-08-10T15:30:45.159214",
     "status": "completed"
    },
    "tags": []
   },
   "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>LotFrontage</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>57.623288</td>\n",
       "      <td>34.664304</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42.00</td>\n",
       "      <td>63.0</td>\n",
       "      <td>79.00</td>\n",
       "      <td>313.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LotArea</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>10516.828082</td>\n",
       "      <td>9981.264932</td>\n",
       "      <td>1300.0</td>\n",
       "      <td>7553.50</td>\n",
       "      <td>9478.5</td>\n",
       "      <td>11601.50</td>\n",
       "      <td>215245.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YearBuilt</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1971.267808</td>\n",
       "      <td>30.202904</td>\n",
       "      <td>1872.0</td>\n",
       "      <td>1954.00</td>\n",
       "      <td>1973.0</td>\n",
       "      <td>2000.00</td>\n",
       "      <td>2010.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YearRemodAdd</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1984.865753</td>\n",
       "      <td>20.645407</td>\n",
       "      <td>1950.0</td>\n",
       "      <td>1967.00</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>2004.00</td>\n",
       "      <td>2010.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MasVnrArea</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>103.117123</td>\n",
       "      <td>180.731373</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>164.25</td>\n",
       "      <td>1600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtFinSF1</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>443.639726</td>\n",
       "      <td>456.098091</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>383.5</td>\n",
       "      <td>712.25</td>\n",
       "      <td>5644.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtFinSF2</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>46.549315</td>\n",
       "      <td>161.319273</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1474.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtUnfSF</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>567.240411</td>\n",
       "      <td>441.866955</td>\n",
       "      <td>0.0</td>\n",
       "      <td>223.00</td>\n",
       "      <td>477.5</td>\n",
       "      <td>808.00</td>\n",
       "      <td>2336.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TotalBsmtSF</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1057.429452</td>\n",
       "      <td>438.705324</td>\n",
       "      <td>0.0</td>\n",
       "      <td>795.75</td>\n",
       "      <td>991.5</td>\n",
       "      <td>1298.25</td>\n",
       "      <td>6110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FirstFlrSF</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1162.626712</td>\n",
       "      <td>386.587738</td>\n",
       "      <td>334.0</td>\n",
       "      <td>882.00</td>\n",
       "      <td>1087.0</td>\n",
       "      <td>1391.25</td>\n",
       "      <td>4692.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SecondFlrSF</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>346.992466</td>\n",
       "      <td>436.528436</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>728.00</td>\n",
       "      <td>2065.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LowQualFinSF</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>5.844521</td>\n",
       "      <td>48.623081</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>572.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GrLivArea</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1515.463699</td>\n",
       "      <td>525.480383</td>\n",
       "      <td>334.0</td>\n",
       "      <td>1129.50</td>\n",
       "      <td>1464.0</td>\n",
       "      <td>1776.75</td>\n",
       "      <td>5642.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtFullBath</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>0.425342</td>\n",
       "      <td>0.518911</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtHalfBath</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>0.057534</td>\n",
       "      <td>0.238753</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FullBath</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1.565068</td>\n",
       "      <td>0.550916</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HalfBath</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>0.382877</td>\n",
       "      <td>0.502885</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BedroomAbvGr</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>2.866438</td>\n",
       "      <td>0.815778</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.00</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KitchenAbvGr</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1.046575</td>\n",
       "      <td>0.220338</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TotRmsAbvGrd</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>6.517808</td>\n",
       "      <td>1.625393</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.00</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.00</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fireplaces</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>0.613014</td>\n",
       "      <td>0.644666</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageYrBlt</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1976.507534</td>\n",
       "      <td>26.306739</td>\n",
       "      <td>1872.0</td>\n",
       "      <td>1959.00</td>\n",
       "      <td>1978.0</td>\n",
       "      <td>2001.00</td>\n",
       "      <td>2010.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageCars</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>1.767123</td>\n",
       "      <td>0.747315</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageArea</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>472.980137</td>\n",
       "      <td>213.804841</td>\n",
       "      <td>0.0</td>\n",
       "      <td>334.50</td>\n",
       "      <td>480.0</td>\n",
       "      <td>576.00</td>\n",
       "      <td>1418.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WoodDeckSF</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>94.244521</td>\n",
       "      <td>125.338794</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>168.00</td>\n",
       "      <td>857.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OpenPorchSF</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>46.660274</td>\n",
       "      <td>66.256028</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>25.0</td>\n",
       "      <td>68.00</td>\n",
       "      <td>547.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EnclosedPorch</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>21.954110</td>\n",
       "      <td>61.119149</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>552.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Threeseasonporch</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>3.409589</td>\n",
       "      <td>29.317331</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>508.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ScreenPorch</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>15.060959</td>\n",
       "      <td>55.757415</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>480.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PoolArea</th>\n",
       "      <td>1460.0</td>\n",
       "      <td>2.758904</td>\n",
       "      <td>40.177307</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>738.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   count          mean          std     min      25%     50%  \\\n",
       "LotFrontage       1460.0     57.623288    34.664304     0.0    42.00    63.0   \n",
       "LotArea           1460.0  10516.828082  9981.264932  1300.0  7553.50  9478.5   \n",
       "YearBuilt         1460.0   1971.267808    30.202904  1872.0  1954.00  1973.0   \n",
       "YearRemodAdd      1460.0   1984.865753    20.645407  1950.0  1967.00  1994.0   \n",
       "MasVnrArea        1460.0    103.117123   180.731373     0.0     0.00     0.0   \n",
       "BsmtFinSF1        1460.0    443.639726   456.098091     0.0     0.00   383.5   \n",
       "BsmtFinSF2        1460.0     46.549315   161.319273     0.0     0.00     0.0   \n",
       "BsmtUnfSF         1460.0    567.240411   441.866955     0.0   223.00   477.5   \n",
       "TotalBsmtSF       1460.0   1057.429452   438.705324     0.0   795.75   991.5   \n",
       "FirstFlrSF        1460.0   1162.626712   386.587738   334.0   882.00  1087.0   \n",
       "SecondFlrSF       1460.0    346.992466   436.528436     0.0     0.00     0.0   \n",
       "LowQualFinSF      1460.0      5.844521    48.623081     0.0     0.00     0.0   \n",
       "GrLivArea         1460.0   1515.463699   525.480383   334.0  1129.50  1464.0   \n",
       "BsmtFullBath      1460.0      0.425342     0.518911     0.0     0.00     0.0   \n",
       "BsmtHalfBath      1460.0      0.057534     0.238753     0.0     0.00     0.0   \n",
       "FullBath          1460.0      1.565068     0.550916     0.0     1.00     2.0   \n",
       "HalfBath          1460.0      0.382877     0.502885     0.0     0.00     0.0   \n",
       "BedroomAbvGr      1460.0      2.866438     0.815778     0.0     2.00     3.0   \n",
       "KitchenAbvGr      1460.0      1.046575     0.220338     0.0     1.00     1.0   \n",
       "TotRmsAbvGrd      1460.0      6.517808     1.625393     2.0     5.00     6.0   \n",
       "Fireplaces        1460.0      0.613014     0.644666     0.0     0.00     1.0   \n",
       "GarageYrBlt       1460.0   1976.507534    26.306739  1872.0  1959.00  1978.0   \n",
       "GarageCars        1460.0      1.767123     0.747315     0.0     1.00     2.0   \n",
       "GarageArea        1460.0    472.980137   213.804841     0.0   334.50   480.0   \n",
       "WoodDeckSF        1460.0     94.244521   125.338794     0.0     0.00     0.0   \n",
       "OpenPorchSF       1460.0     46.660274    66.256028     0.0     0.00    25.0   \n",
       "EnclosedPorch     1460.0     21.954110    61.119149     0.0     0.00     0.0   \n",
       "Threeseasonporch  1460.0      3.409589    29.317331     0.0     0.00     0.0   \n",
       "ScreenPorch       1460.0     15.060959    55.757415     0.0     0.00     0.0   \n",
       "PoolArea          1460.0      2.758904    40.177307     0.0     0.00     0.0   \n",
       "\n",
       "                       75%       max  \n",
       "LotFrontage          79.00     313.0  \n",
       "LotArea           11601.50  215245.0  \n",
       "YearBuilt          2000.00    2010.0  \n",
       "YearRemodAdd       2004.00    2010.0  \n",
       "MasVnrArea          164.25    1600.0  \n",
       "BsmtFinSF1          712.25    5644.0  \n",
       "BsmtFinSF2            0.00    1474.0  \n",
       "BsmtUnfSF           808.00    2336.0  \n",
       "TotalBsmtSF        1298.25    6110.0  \n",
       "FirstFlrSF         1391.25    4692.0  \n",
       "SecondFlrSF         728.00    2065.0  \n",
       "LowQualFinSF          0.00     572.0  \n",
       "GrLivArea          1776.75    5642.0  \n",
       "BsmtFullBath          1.00       3.0  \n",
       "BsmtHalfBath          0.00       2.0  \n",
       "FullBath              2.00       3.0  \n",
       "HalfBath              1.00       2.0  \n",
       "BedroomAbvGr          3.00       8.0  \n",
       "KitchenAbvGr          1.00       3.0  \n",
       "TotRmsAbvGrd          7.00      14.0  \n",
       "Fireplaces            1.00       3.0  \n",
       "GarageYrBlt        2001.00    2010.0  \n",
       "GarageCars            2.00       4.0  \n",
       "GarageArea          576.00    1418.0  \n",
       "WoodDeckSF          168.00     857.0  \n",
       "OpenPorchSF          68.00     547.0  \n",
       "EnclosedPorch         0.00     552.0  \n",
       "Threeseasonporch      0.00     508.0  \n",
       "ScreenPorch           0.00     480.0  \n",
       "PoolArea              0.00     738.0  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.loc[:, mi_scores > 0.0].describe().T "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "877ec35b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:45.345071Z",
     "iopub.status.busy": "2022-08-10T15:30:45.344656Z",
     "iopub.status.idle": "2022-08-10T15:30:45.349887Z",
     "shell.execute_reply": "2022-08-10T15:30:45.348867Z"
    },
    "papermill": {
     "duration": 0.03528,
     "end_time": "2022-08-10T15:30:45.352057",
     "exception": false,
     "start_time": "2022-08-10T15:30:45.316777",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def drop_uninformative(df, mi_scores):\n",
    "    return df.loc[:, mi_scores > 0.0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59ea3261",
   "metadata": {
    "papermill": {
     "duration": 0.02498,
     "end_time": "2022-08-10T15:30:45.401953",
     "exception": false,
     "start_time": "2022-08-10T15:30:45.376973",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Removing them does lead to a modest performance gain:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "ab19015a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:45.456486Z",
     "iopub.status.busy": "2022-08-10T15:30:45.455804Z",
     "iopub.status.idle": "2022-08-10T15:30:48.515188Z",
     "shell.execute_reply": "2022-08-10T15:30:48.514046Z"
    },
    "papermill": {
     "duration": 3.088703,
     "end_time": "2022-08-10T15:30:48.518006",
     "exception": false,
     "start_time": "2022-08-10T15:30:45.429303",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.14338026718687277"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = df_train.copy()\n",
    "y = X.pop(\"SalePrice\")\n",
    "Xd = drop_uninformative(X, mi_scores)\n",
    "\n",
    "score_dataset(Xd, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "188f7516",
   "metadata": {
    "papermill": {
     "duration": 0.02639,
     "end_time": "2022-08-10T15:30:48.571495",
     "exception": false,
     "start_time": "2022-08-10T15:30:48.545105",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Later, we'll add the `drop_uninformative` function to our feature-creation pipeline.\n",
    "\n",
    "# Step 3 - Create Features #\n",
    "\n",
    "Now we'll start developing our feature set.\n",
    "\n",
    "To make our feature engineering workflow more modular, we'll define a function that will take a prepared dataframe and pass it through a pipeline of transformations to get the final feature set. It will look something like this:\n",
    "\n",
    "```\n",
    "def create_features(df):\n",
    "    X = df.copy()\n",
    "    y = X.pop(\"SalePrice\")\n",
    "    X = X.join(create_features_1(X))\n",
    "    X = X.join(create_features_2(X))\n",
    "    X = X.join(create_features_3(X))\n",
    "    # ...\n",
    "    return X\n",
    "```\n",
    "\n",
    "Let's go ahead and define one transformation now, a [label encoding](https://www.kaggle.com/alexisbcook/categorical-variables) for the categorical features:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "08c60ce8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:48.625941Z",
     "iopub.status.busy": "2022-08-10T15:30:48.625511Z",
     "iopub.status.idle": "2022-08-10T15:30:48.656218Z",
     "shell.execute_reply": "2022-08-10T15:30:48.655145Z"
    },
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     "duration": 0.060713,
     "end_time": "2022-08-10T15:30:48.658635",
     "exception": false,
     "start_time": "2022-08-10T15:30:48.597922",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# all to numerical\n",
    "def label_encode(df):\n",
    "    X = df.copy()\n",
    "    for colname in X.select_dtypes([\"category\"]):\n",
    "        X[colname] = X[colname].cat.codes\n",
    "    return X\n",
    "\n",
    "X =  label_encode(X)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b75e3011",
   "metadata": {
    "papermill": {
     "duration": 0.025062,
     "end_time": "2022-08-10T15:30:48.708602",
     "exception": false,
     "start_time": "2022-08-10T15:30:48.683540",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "A label encoding is okay for any kind of categorical feature when you're using a tree-ensemble like XGBoost, even for unordered categories. If you wanted to try a linear regression model (also popular in this competition), you would instead want to use a one-hot encoding, especially for the features with unordered categories.\n",
    "\n",
    "## Create Features with Pandas ##\n",
    "\n",
    "This cell reproduces the work you did in Exercise 3, where you applied strategies for creating features in Pandas. Modify or add to these functions to try out other feature combinations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "3871671c",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:48.761146Z",
     "iopub.status.busy": "2022-08-10T15:30:48.760051Z",
     "iopub.status.idle": "2022-08-10T15:30:48.769532Z",
     "shell.execute_reply": "2022-08-10T15:30:48.768355Z"
    },
    "papermill": {
     "duration": 0.038352,
     "end_time": "2022-08-10T15:30:48.772023",
     "exception": false,
     "start_time": "2022-08-10T15:30:48.733671",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "\n",
    "def mathematical_transforms(df):\n",
    "    X = pd.DataFrame()  # dataframe to hold new features\n",
    "    X[\"LivLotRatio\"] = df.GrLivArea / df.LotArea\n",
    "    X[\"Spaciousness\"] = (df.FirstFlrSF + df.SecondFlrSF) / df.TotRmsAbvGrd\n",
    "    # This feature ended up not helping performance\n",
    "    # X[\"TotalOutsideSF\"] = \\\n",
    "    #     df.WoodDeckSF + df.OpenPorchSF + df.EnclosedPorch + \\\n",
    "    #     df.Threeseasonporch + df.ScreenPorch\n",
    "    return X\n",
    "\n",
    "\n",
    "def interactions(df):\n",
    "    X = pd.get_dummies(df.BldgType, prefix=\"Bldg\")\n",
    "    X = X.mul(df.GrLivArea, axis=0)\n",
    "    return X\n",
    "\n",
    "\n",
    "def counts(df):\n",
    "    X = pd.DataFrame()\n",
    "    X[\"PorchTypes\"] = df[[\n",
    "        \"WoodDeckSF\",\n",
    "        \"OpenPorchSF\",\n",
    "        \"EnclosedPorch\",\n",
    "        \"Threeseasonporch\",\n",
    "        \"ScreenPorch\",\n",
    "    ]].gt(0.0).sum(axis=1)\n",
    "    return X\n",
    "\n",
    "\n",
    "def break_down(df):\n",
    "    X = pd.DataFrame()\n",
    "    X[\"MSClass\"] = df.MSSubClass.str.split(\"_\", n=1, expand=True)[0]\n",
    "    return X\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41a169a0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-01T15:52:44.495097Z",
     "iopub.status.busy": "2022-08-01T15:52:44.494712Z",
     "iopub.status.idle": "2022-08-01T15:52:44.508932Z",
     "shell.execute_reply": "2022-08-01T15:52:44.507641Z",
     "shell.execute_reply.started": "2022-08-01T15:52:44.495067Z"
    },
    "papermill": {
     "duration": 0.025788,
     "end_time": "2022-08-10T15:30:48.823287",
     "exception": false,
     "start_time": "2022-08-10T15:30:48.797499",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Here are some ideas for other transforms you could explore:\n",
    "- Interactions between the quality `Qual` and condition `Cond` features. `OverallQual`, for instance, was a high-scoring feature. You could try combining it with `OverallCond` by converting both to integer type and taking a product.\n",
    "- Square roots of area features. This would convert units of square feet to just feet.\n",
    "- Logarithms of numeric features. If a feature has a skewed distribution, applying a logarithm can help normalize it.\n",
    "- Interactions between numeric and categorical features that describe the same thing. You could look at interactions between `BsmtQual` and `TotalBsmtSF`, for instance.\n",
    "- Other group statistics in `Neighboorhood`. We did the median of `GrLivArea`. Looking at `mean`, `std`, or `count` could be interesting. You could also try combining the group statistics with other features. Maybe the *difference* of `GrLivArea` and the median is important?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "7ade5a93",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:48.875905Z",
     "iopub.status.busy": "2022-08-10T15:30:48.875479Z",
     "iopub.status.idle": "2022-08-10T15:30:48.884772Z",
     "shell.execute_reply": "2022-08-10T15:30:48.884008Z"
    },
    "papermill": {
     "duration": 0.03817,
     "end_time": "2022-08-10T15:30:48.886821",
     "exception": false,
     "start_time": "2022-08-10T15:30:48.848651",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# New ideas\n",
    "\n",
    "def diffGrLivArea(df):\n",
    "    X = pd.DataFrame()\n",
    "    X[\"DiffGrLivArea\"] = df.GrLivArea - df.GrLivArea.mean(axis=0)\n",
    "    return X\n",
    "\n",
    "\n",
    "def group_transforms(df):\n",
    "    X = pd.DataFrame()\n",
    "    X[\"MedNhbdArea\"] = df.groupby(\"Neighborhood\")[\"GrLivArea\"].transform(\"median\")\n",
    "    X[\"StdNhbdArea\"] = df.groupby(\"Neighborhood\")[\"GrLivArea\"].transform(\"std\")\n",
    "    X[\"CountNhbdArea\"] = df.groupby(\"Neighborhood\")[\"GrLivArea\"].transform(\"count\")\n",
    "    return X\n",
    "\n",
    "\n",
    "def logTransformer(df):\n",
    "    X = pd.DataFrame()\n",
    "    X['logGrLivArea'] = np.log(df['GrLivArea'])\n",
    "    X['logTotalBsmtSF'] = df['TotalBsmtSF']\n",
    "    X['HasBsmt'] = pd.Series(len(X['logTotalBsmtSF']), index=df.index)\n",
    "    X['HasBsmt'] = 0 \n",
    "    X.loc[X['logTotalBsmtSF']>0,'HasBsmt'] = 1\n",
    "    \n",
    "    X.loc[X['HasBsmt']==1,'logTotalBsmtSF'] = np.log(X['logTotalBsmtSF'])\n",
    "    \n",
    "    return X"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d52c8f0c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-01T15:52:44.495097Z",
     "iopub.status.busy": "2022-08-01T15:52:44.494712Z",
     "iopub.status.idle": "2022-08-01T15:52:44.508932Z",
     "shell.execute_reply": "2022-08-01T15:52:44.507641Z",
     "shell.execute_reply.started": "2022-08-01T15:52:44.495067Z"
    },
    "papermill": {
     "duration": 0.025288,
     "end_time": "2022-08-10T15:30:48.937326",
     "exception": false,
     "start_time": "2022-08-10T15:30:48.912038",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## k-Means Clustering ##\n",
    "\n",
    "The first unsupervised algorithm we used to create features was k-means clustering. We saw that you could either use the cluster labels as a feature (a column with `0, 1, 2, ...`) or you could use the *distance* of the observations to each cluster. We saw how these features can sometimes be effective at untangling complicated spatial relationships."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "57b83b33",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:48.991587Z",
     "iopub.status.busy": "2022-08-10T15:30:48.990888Z",
     "iopub.status.idle": "2022-08-10T15:30:49.000358Z",
     "shell.execute_reply": "2022-08-10T15:30:48.998948Z"
    },
    "lines_to_next_cell": 2,
    "papermill": {
     "duration": 0.039887,
     "end_time": "2022-08-10T15:30:49.003310",
     "exception": false,
     "start_time": "2022-08-10T15:30:48.963423",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "\n",
    "cluster_features = [\n",
    "    \"LotArea\",\n",
    "    \"TotalBsmtSF\",\n",
    "    \"FirstFlrSF\",\n",
    "    \"SecondFlrSF\",\n",
    "    \"GrLivArea\",\n",
    " \"Neighborhood\",\n",
    "]\n",
    "\n",
    "\n",
    "def cluster_labels(df, features, n_clusters=10):\n",
    "    X = df.copy()\n",
    "    X_scaled = X.loc[:, features]\n",
    "    X_scaled = (X_scaled - X_scaled.mean(axis=0)) / X_scaled.std(axis=0)\n",
    "    kmeans = KMeans(n_clusters=n_clusters, n_init=10, random_state=0)\n",
    "    X_new = pd.DataFrame()\n",
    "    X_new[\"Cluster\"] = kmeans.fit_predict(X_scaled)\n",
    "    return X_new\n",
    "\n",
    "\n",
    "def cluster_distance(df, features, n_clusters=20):\n",
    "    X = df.copy()\n",
    "    X_scaled = X.loc[:, features]\n",
    "    X_scaled = (X_scaled - X_scaled.mean(axis=0)) / X_scaled.std(axis=0)\n",
    "    kmeans = KMeans(n_clusters=20, n_init=50, random_state=0)\n",
    "    X_cd = kmeans.fit_transform(X_scaled)\n",
    "    # Label features and join to dataset\n",
    "    X_cd = pd.DataFrame(\n",
    "        X_cd, columns=[f\"Centroid_{i}\" for i in range(X_cd.shape[1])]\n",
    "    )\n",
    "    return X_cd\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "0410536b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:49.055583Z",
     "iopub.status.busy": "2022-08-10T15:30:49.055179Z",
     "iopub.status.idle": "2022-08-10T15:30:50.884600Z",
     "shell.execute_reply": "2022-08-10T15:30:50.883202Z"
    },
    "papermill": {
     "duration": 1.858919,
     "end_time": "2022-08-10T15:30:50.887362",
     "exception": false,
     "start_time": "2022-08-10T15:30:49.028443",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 488.975x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "XclusterLabel= cluster_labels(X, cluster_features, n_clusters =8)\n",
    "XclusterDistance= cluster_distance(X, cluster_features)\n",
    "\n",
    "X[\"Cluster\"] = XclusterLabel\n",
    "#Xle[\"ClusterDistance\"] = XclusterDistance\n",
    "\n",
    "sns.relplot(\n",
    "   x=\"LotArea\" , y=\"TotalBsmtSF\" , hue=\"Cluster\", data=X, height=6,\n",
    ");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "d0d5696d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:50.943004Z",
     "iopub.status.busy": "2022-08-10T15:30:50.942605Z",
     "iopub.status.idle": "2022-08-10T15:30:53.827793Z",
     "shell.execute_reply": "2022-08-10T15:30:53.826499Z"
    },
    "papermill": {
     "duration": 2.918196,
     "end_time": "2022-08-10T15:30:53.832033",
     "exception": false,
     "start_time": "2022-08-10T15:30:50.913837",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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YsWMHv/zlL9m8efMZXSMqKgpo/SH4zW9+Q2Fh4Qlb6AFef/11amtr2b9/P36/n6FDhzJw4MB2rf4zZ84kOTmZvXv3csstt5CRkUFpaSmbNm3in//8Z7sB+HD23VW2bNnCjTfeGPp7/PjxfPvb3yYpKYmCggIWLFhAREQEn376KWazmeuvvx4gNKnA4sWLaWxs5NJLL2XdunVAawB4fJeXPXv2UF5ezvvvv98meDzesGHDGD16NNu3b+f6669n9OjRVFVVsXnzZh577DGmTJmCqqr4/X5++9vf0tzcTH5+/hmXW5xf5J4+c8OGDQuNabztttsYOHAgH3zwAYqihLrAHb2fv/jiC375y18yYcKE0Oeal5cXmoSns46OeayoqGDVqlXAsa6r1157LUlJSSQkJFBWVgbQZkbE05WQkEBhYSF//etfWbFiBXfffTfr16/nt7/9LWPGjKFfv35UVVWxf/9+TCZTaAIu0bdJndF9/vnPf7JixQoyMjIwGAyhMh0d85mQkEBxcTFPPfUUaWlpfO973ztn166oqOCaa65h6NChoQmFli1bBhBq7BJC1nkUnXK0ewq0Pqwcdfvtt3PppZfi8XjYsmUL999//xmdf/To0dx///3Y7XbWrl3LlVdeedJuXPfeey/FxcUUFBQwYcIE/vKXv7QZU3GU1Wrl5ZdfZt68eZSUlLBo0SKOHDnC1Vdf3a5ry7lSX18fGu+0c+dOjhw5EsrH7NmzOXz4MOvWrWPChAn85z//CXVVufHGGxk9ejTl5eW88sor7Nmzh6VLlwLwwAMP8MILL4T+Hf2h+PDDD/H7/SfMh6qqvPDCC9x88800Nzfz3nvvsW/fPmbOnMnIkSOJj4/npz/9KdHR0WzYsIGhQ4e2GUcl+j65p8+Mqqr87W9/47rrrqO6uppPP/2UrKws/va3v4UCqTlz5jBt2jRcLhevvvoqGzduZO7cudxwww2oqsq6deu47777On3Nffv2sXDhQj7//HMGDhzIE088waxZs4DWB7ojR46waNEitm7dyoQJE9qsv3i6HnzwQfr168eOHTtYuHAhVVVVjBkzhssvv5yioiIWL17M5s2bGT16NC+88EKbMVCib5M6o3sMGTIEnU7H8uXLWbRoEdHR0fz0pz9l8ODBADzyyCPEx8ezevVqFi5ciNvtPmfXjo2N5ZZbbsHj8fDpp5/y0UcfkZCQwE9+8hMZzyhCFE36qAkhhBBCCCGE6IC8eRRCCCGEEEII0SEJHoUQQgghhBBCdEiCRyGEEEIIIYQQHZLgUQghhBBCCCFEhyR4FEIIIYQQQgjRIQkehRBCCCGEEEJ0SIJHIYQQQgghhBAdkuBRCCGEEEIIIUSHJHgUQgghhBBCCNEhfU9n4HxUXd1EMKidcp+ICCu1tS3dlKOu19fKA32vTH2tPNC9ZYqJcZzRcZ2pD6B3fj+Sp87pbXnqbfmBvpenrq4PepPe+N2djb5Unr5UFji/y3OmdUJfJG8eu4her+vpLJxTfa080PfK1NfKA32rTL2xLJKnzulteept+QHJ0/msr31Ofak8faks0PfKc6GS4FEIIYQQQgghRIckeBRCCCGEEEII0SEJHoUQQgghhBBCdEiCRyGEEEIIIYQQHZLg8TyhKKBpfoJBD6p8a0II0YbUkUKIrhMkGPSgKMGezogQPU6W6jgvaFRWlrB69Rc0NzczbNhwhg8fiU5n7umMCSFEL6BRUVHCmjVf0NLSwtChw6SOFEKcNUWBlpY6Vq/+grKyMlJTU5kyZRpGo72nsyZEj5H22fNAc3MdH374AY2NjQSDQXbt2kl29h4UpadzJoQQPa+pqZaPPmqtIwOBALt27WTfvr2oqlSSQogz5/e7WbJkMWVlZQAUFBTw8ccfomm+Hs6ZED1Hgsdexq9plNe7qWjw4NdaFxquqalut1929l6CQW93Z08IIXoXBRrdMHj0LIaOmoTFYgFa68hAwNOzeRNCnNeaXD76D5nI8HEziI6OAaCuro6WluYezpkQPUe6rfYiTR4///lwP9sOVAAwbnAsd87Nwmxu3/XK6XSiKLLYqhDiwqUBu4/U8rd3duPxBbBZDNwzdxY5O1bidDpRVT1ftsEJIcRpqW7y8uxre6isdaGqCldPHUaC6TDlpYUYDIaezp4QPUbePPYSiqKw42B1KHAE2LK/gl2Hq4mKiiEmJiaUrqoqU6dOAyR4FEJcuGqbvTz31g48vgAAzS4f/1mWT/rgkUydOg1Nk584IcTpC2jw8kf7qKx1ARAMaixaXUhU4iAmT56CyWTr4RwK0XPkzWMvodOpbN5f1i596/5ypg+P5/LLr6Curhqv10dERARms6MHcimEEL1HTYOHQLDtq8WGZi8JSQNwOh3y1lEIcUbcvgB7ctsPGdL0dtLT+0ndIi5o0izbSwQCQUYPimmXPnJQDIGAhk5nIioqkYSEfpjNTkAmghBCXNgiHCa+OieOzWIgzGGVhzshxBkzG3Rk9gtvlx4dbkN6fYkLnQSPvYSmaYwdHEtGakQoLatfBKMGRaPJU5AQQrQTaTdy7/zh6L6MIE0GHd+5cRR2k3SqEUKcOZ0CX79yKE6bMZR2zfQBJEZaejBXQvQO8gvbizhMen5w0ygq6l2AQmyYGYNO3jAKIcSJKMCEjBgGfnsq9c1eohxmwqx6aXATQpy1uDATT983map6FxaTgWiHEVXWSBNCgsfexqBTSIq09nQ2hBDivBFpMxL55RsCiRuFEOeCpoHNqMMWY+/prAjRq0i3VSGEEEIIIYQQHZLgUQghhBBCCCFEhyR4FEIIIYQQQgjRIQkehRBCCCGEEEJ0SIJHIYQQQgghhBAd6pbZVouKivj2t78d+ruxsZGmpiY2bdrEkSNHePTRR6mrqyM8PJxnnnmGtLQ0gG7fJoQQQgghhBDixLrlzWNycjLvv/9+6N8ll1zCvHnzAHjyySe59dZbWbZsGbfeeitPPPFE6Lju3iaEEEIIIYQQ4sS6vduq1+tlyZIlXH/99VRXV5OdnR0KJOfNm0d2djY1NTXdvk0IIYQQQgghxMl1S7fV461YsYK4uDiGDh3Knj17iIuLQ6fTAaDT6YiNjaW0tBRN07p1W2RkZKfLEBXVuQVjY2IcnT7n+aCvlQf6Xpn6Wnmg95eps/UB9M6ySJ46p7flqbflByRPcHr1QW/SG7+7s9GXytOXygJ9rzwXom4PHt955x2uv/767r7sOVVd3UQwqJ1yn5gYB5WVjd2Uo67X18oDfa9Mfa080L1lOtMftM7UB0fP39u+H8lT5/S2PPW2/EDfy1NX1we9SW/87s5GXypPXyoLnN/lkaD3mG4NHsvLy9m8eTPPPvssAAkJCZSXlxMIBNDpdAQCASoqKkhISEDTtG7dJoQQQgghhBDi5Lp1zON7773HzJkziYiIACAqKoqsrCyWLl0KwNKlS8nKyiIyMrLbtwkhhBBCCCGEODlF07Ru618xe/ZsHn/8cWbMmBFKy83N5dFHH6WhoQGn08kzzzzDgAEDemRbZ0m31b6hr5Wpr5UHpNtqV5M8dU5vy1Nvyw/0vTxJt9XzV18qT18qC5zf5ZFuq8d0a7fVZcuWtUtLT0/n7bffPuH+3b1NCCGEEEIIIcSJdftSHUIIIYQQQgghzj8SPAohhBBCCCGE6JAEj0IIIYQQQgghOiTBoxBCCCGEEEKIDknwKIQQQgghhBCiQxI8CiGEEEIIIYTokASPQgghhBBCCCE6JMGjEEIIIYQQQogOSfAohBBCCCGEEKJDEjwKIYQQQgghhOiQBI9CCCGEEEIIITokweMFQlUVVFW+biFE76KqCqpOQVF6OidCiN5MVVVUVSoKIXqavqczILqYAqW1Lj5Yl0dtg5s5k9IYnBKGQSeBpBCi5ygKVDZ4+WRTPvlljVw8NpmR6VE9nS0hRC/jDWjsL6jl4w35RIdbuGJyGgkRZjStp3MmxIVJgsc+rqLew5P/2oA/0FrL7sur5cEbRjJ2UJRUvEKIHlPX4uMXL26g2e0H4GBhHTdcNJA74sN6OGdCiN5CURR2HKrk7+/tbk3Ir2Xj3jKevm8y0Q5Tz2ZOiAuUvH7qwxQFDhTUhgLHo95ddQhfoIcyJYQQQFFlcyhwPGrx6sNU1rX0UI6EEL2Nxx/knVWH2qT5/EEOFdf3UI6EEBI89gKKAk0eP/UuP3Du+vNrGuhP0D3VoFdR5JsXQvSgE41d0ulU1M4OflSg0e2n0e0/l9WmEKIXURROOMzmRM825+6aCi5fkLoWHwHpoSVEO9JttYf5gxrrs8t5/ZMDeH0BpgxP5KZLBmI3nZuvJjMlHItJj8tzrIX/pksz0J2TswshxJlJibER5TRT3eAOpd18WQYxEVYqKxtPeazLF+CTTYUsXXsEgHlT+zN7Qgpmg9RsQvQlRp3CzZdl8Mc3tofSbGY96Uld071dA/YV1PGPRbtpaPYyuF8E37xmGBFWQ5dcT4jzkQSPPaygspn/W5od+nvtrhJiIyxcPTUNLXj2TV5RDiO/+MZEth6ooLbRw6Sh8aTE2M76vEIIcTbsJj2P3zWeHQcrKapoZvyQWAbEOzp17L78Wt5ffTj09/urD5McZ2fswOiuyq4QogdoGmSlhPOzr09gw94yIp1mxg2OJdJm6JJ5G6oaPPz+9a2hc+/Pr+WlpXv53o2jpKueEF/qtuDR4/Hw61//mvXr12MymRg1ahS//OUvOXLkCI8++ih1dXWEh4fzzDPPkJaWBtDt27qbosDhE/TbX72zmNkTUjHqzr4vlqZBtMPE3AmpKIpCIBA863MKIcS5EG41cNGoJFS183WTXq+ydndpu/R1u0qZODgWv1/qOCH6Ep2q0D/OzsDEDDRNIxjUumzCv/Lalnbn3nu4hkaXnzCLvG8RArpxzOPvfvc7TCYTy5YtY8mSJTz88MMAPPnkk9x6660sW7aMW2+9lSeeeCJ0THdv626aBrER1nbpaQlOjOe4P38wqEngKITodTTt9OqmYFBjUHJ4u/SBKeEEz0FvDSFE7xQIBLv8HndYje3SIp1mzAZ57yjEUd1yNzQ3N7No0SIefvhhlC8nQ4iOjqa6uprs7GzmzZsHwLx588jOzqampqbbt/WU9CQnGanhob8tJj03XDSI1p73QgghjhcMakwaGk90mDmUFh1mZvKweAkehRBnJTHSykVjk0N/q6rC/fOHS/AoxHG65R18YWEh4eHhPP/882zcuBGbzcbDDz+M2WwmLi4Ona51kgOdTkdsbCylpaVomtat2yIjI7vjo2jHZtTx3RtHUVLVgtcfICHKRrhVL2swCiHESYRbDTx5z0RKqpoBSIy2YTPKZDlCiLNj0CncdPEgZo5OpqnFS1yklWiHUZ7JhDhOtwSPgUCAwsJChgwZwo9//GN27tzJ/fffz1/+8pfuuPw5FxVl79R+MTGdm/wBICWh9y+MfTrlOV/0tTL1tfJA7y9TZ+sD6J1lOV/zFAOkJYV3eV5C1+tln1Nvyw9InuD06oPepDd+d2fjbMuTFO88Rzk5e/LdiN6mW4LHhIQE9Hp9qLvoyJEjiYiIwGw2U15eTiAQQKfTEQgEqKioICEhAU3TunXb6aiubuqwe1RMjKPD6eaPp3y5ZlkgoOGwGnrdrF6nW57zQV8rU18rD3Rvmc70B60z9cHR8/e276c78qQoCg1uH1oQnFZ9hz3yL9TP6XT0tvxA38tTV9cHvUlv++6CQGOLD71OxW7WnfZbv95WnrPRl8oC53d5JOg9pltilMjISCZOnMjatWuB1hlPq6urSUtLIysri6VLlwKwdOlSsrKyiIyMJCoqqlu39SR/UGPt3nJ+9P/W8r2/rubfS7NpPG5dRiGEOB95/UE+3lLII8+t4ft//YI3PjtEszfQ09kSQvRSjR4//1qyl+/9dTU/emEt67Ir8EufUSF6FUXTuueuLCws5Cc/+Ql1dXXo9Xq++93vMnPmTHJzc3n00UdpaGjA6XTyzDPPMGDAAIBu39ZZ5/rNY35lM794cWObtHnT+nP99AF009fTofO5tehk+lqZ+lp5QN48drWuztO+wjp+99q2Nml3XpnFrBGJJ63bLsTP6XT1tvxA38uTvHnsfooCb63K5aP1+W3Sf/6NiaRGd3596t5SnnOhL5UFzu/yyJvHY7pt0ZqUlBReeeWVdunp6em8/fbbJzymu7f1BEWBvNKGdulrdpRw5aR+mPS9rQOrEEJ0TKdT2HGwsl366h0lzBiRyNmvYiuE6EtcviBrd7VfwzW/rPG0gkchRNeSyKSHaRpEh1napaclODBK4CiEOE8Fgxqpce0nnRiYHIYqkaMQ4iuMepXU+PZvd6Kc5hPsLYToKRKd9AL9Exxk9Y8I/W0x6bnp0gxpmRdCnLc0DUakR5ESe2z2SafNyGXjU9HOs259QoiupwK3Xp6J+bhld4b2jyLtBAGlEKLndFu3VXFyVqOO71w/kpLqFjy+AAlRVsKtBllXSAhxXnOY9Tx6xzhKqpoJBIMkRtuxm2Q9RiHEiSWEW/jNA1MorW7BZNSRGGmV4TtC9DISPPYSJr1K/7jWFnpFUdDpVAKBgASQQojzmsWgkp7Q8ZsDRQGdTgJLIS5kmqYRZjEQlnz6a1/rdCqKdNkSostJ8NiLKAq43VUUHthJ2ZEc+mWOJGnAcFSjdNkQQvRdQV8jJYf3kL9/B8npWSQPGoXOFN7T2WrDp3io9FThD/qJtcRg1qw9nSUhBK3PTq76EnJ2rMPV1MDQCTOxR6WCYjir8wYUH9W+Glp8LURbonAoTmnQFwIJHnuVZl8Va955idqyIgCKc/eRNuQAk+bcgSZflRCiD1Lws3XFuxzeuxWAotx9RO3azKU3Pwhq+8nEekJVcw0v7XmdXeX7AIi2RvK9ifcSrvTsGsFCCHA3lLHk/35PMNC6Pnbe/h1cdtP9RCYNOeNz+hQvH+UtZ1nuKgAsBjM/nPwAcfqEc5FlIc5r0pG8l9B0AYpKc0OB41F52dtxN1X3UK6EEKJruZtqQoHjUdVlhTTVVvRQjtrLrjwYChwBqlpqWH7kCxT5BRWiRykKlOYfCAWOR23/4kMU/Cc5qmPl7rJQ4Ajg8rn5z863CKjeMz6nEH2F/PT1Ep6ghxaf6yRbpRO/EEL0BFVVyK8rape+r+ogfnw9kCMhRFvtn5HOduxjnae+XVpBfTGeoOfsTixEHyDBYy9hViwErGYiE1LapKcNHY3ZLl2jhBB9k9keSfqw8W3SohNTsYfH9lCO2goGNTKi+rdLH5swAj1nN6ZKCNHW6QZ9mgYJ/TLR6dsO7Rk1/cqzGu4TZYlql5YVPRBzL+lKL0RPkoF0vUVQYVBcJrkzgsSUVdNUXEzCoCz6DRzZa8Y7amiU1rrJLarHYTWQnhSGw9w78iaE6B0URaGywc2h4noURWFgUhjRDuNJJ5rQ0DNm1nwS0zLJz9lB8oAsEtKHg673PKRlxgxkdvpMPsn9Ag2NrOiBzEiZhBbs6ZwJ0Td4A0EKKpoprGgkIcpGvzg7FkPnZl82O+OYd9cPObRrA67meoaMn4ktIqXjA08h1hjLghHX8/qe9/EH/cTbY7lt+PWoQXnmEULugl7EqUQwPGUcDQkNWCdYsGIlGOg9XVYPlTbx24WbQw+BMREWfnrneAkghRAhZXVunvzXerz+1sjKbNTxi29MIsZpOukxqtFOUuYEUodMIiLCRmVlY3dlt1PCzU6u6j+XGSmT8Wt+Ig2R8hApxDmiAR9vLGDRF4dDadNHJnLHnEz0nXgVqWlgdiYwcub1KArnpA7RaXomxU4ka2Ymbr+HCFM4huDJ6zAhLiTSbbWX0QeNRKrRmAO2XhU4NrZ4eeWjfW3eHlTWusgr610PeUKInqPTqXy2tSAUOAK4vQHW7S5FVU9dn2ka+P2991WeElQJVyOJ1sVK4CjEOVTb5GXx6sNt0lbvLKGyzn1a5wkEgue0DtGC4FTCiTXESeAoxHEkeBSd4vMFaGhuP8tYi+fMZzMTQvQtigLVJ3jgq25wdxg8CiEuTF5/kOAJurV7fL23MUmIC5kEj6JTIpxmrpiS1iZNVRXS4h09kyEhRK/j9we5dHz7sUYzRiX16reKQoieE+U0MSDR2SYt0mkmLqL3jHsWQhwjfW9EpyiKwvQRCehUlY835BHlNHPL5ZnEhZtbBywIIQQwMCmMh742kv+tOISqKnztkkH0j7f3dLaEEL2UQVV46GsjWbo2j637KxjSP5LrZqVjMcj7DSF6IwkeRadZDDouG5vE9BHx6HVq62trCRyFEMcxqApjBkYxvH8koGDQcdKZVoUQAiDMYuC2ywZxw0UDMekVebYQoheT4FGclmBQw6iT1kAhxMlpGui/HOMogaMQolM0MOkkcBSit5MoQAghhBBCCCFEhyR4FEIIIYQQQgjRoW4LHi+++GLmzJnDNddcwzXXXMPq1asB2LFjB1dffTWzZ8/m7rvvprq6OnRMd2/rLRQFqpu87Dhcw96COprcshyGEOLCpShQ2eBhe241+wrrafYGejpLQojzWCCoUVTdwpaDVeSWNeKR2aCF6LRuffP417/+lffff5/333+f6dOnEwwG+eEPf8gTTzzBsmXLGDduHL///e8Bun1bb1JS4+Ynf1/HX9/awR9e38Yv/7OJepcEkEKIC1NeRTOP/X0dz729k9+9tpVnX9tKk0cCSCHE6VNU2HSggif+tYEX3tnF0//ZzKuf5OALyGBLITqjR7ut7tmzB5PJxLhx4wC4+eab+fjjj3tkW6+hKLzz+UF8x7WCVda52Z9fgyJrbAshLjABDRZ+tJ/gcauIF5Y3kVfW0IO5EkKcrxpa/Cz8cH+btLW7Siivc/VQjoQ4v3TrbKuPPPIImqYxduxYvv/971NaWkpiYmJoe2RkJMFgkLq6um7fFh4e3rWF76RAUKOipn0FVlnvRlEUNJm6UAhxAfEFg1TXt68TG1p8PZAbIcT5zusL4vG177nQ4pEeXkJ0xmkFj5s3b+bNN9+koKCA559/nrfffpsZM2YwYsSIDo997bXXSEhIwOv18vTTT/PUU09x2WWXnXHGe1JUVOcWvI6JcZzWeYM+D4qqY/akfry4eG+bbaMzYjp93a5yuuU5H/S1MvW18kDvL9Pp3Je9sSw9nSct4EcLBlENxlDa8XkKBjUun5jK/1YcanPcoJTwbs17T39OX9Xb8gOSJzi9+qA36Y3f3ek4+vyk6Fofa09VHovNS0ZqBDkFtaE0s1FHWkIYMTG97/s737+br+pr5bkQdTp4XL58Od/5zncIBoMoikJUVBRvvvkmOTk5/PWvf+3w+ISEBACMRiO33norDzzwAAsWLKCkpCS0T01NDaqqEh4eTkJCQrduOx3V1U1tulCdSEyMg8rKxk6dzxBsQSvcSfPOT9GHx3HR6CvwzR3M2ysOYTHpWTB3MPHh5k6fryucTnnOF32tTH2tPNC9ZTrTH7TO1AdHz9/bvp+ezJOChqkhn6YtSwi2NGIbMwctfggRcTHt8jRzVBJeX5BlG/MJt5u468ohRNsN3fr/Rm/67npbfqDv5amr64PepDd+d51lCLSgFe9qfX4Ki8U25goc/Yd0WJ4H5g/jv58dYsu+MtISnHx93hBMKr3uczifv5sTOZ/LI0HvMZ0OHl944QUiIiIYMGAAW7ZsQa/XM2bMGHbu3NnhsS0tLQQCARwOB5qm8eGHH5KVlcWwYcNwu91s2bKFcePG8eabbzJnzhyAbt/WU1RVIZizjrpVrwLgLTuM69BW5tz6SyYNnYaqKJj0iiy0LYToU0zNxVT+9ynQWsd3e0pyiLzi2xB3cbt9bUYd86f1Z/aEVPQ6BaNO6kQhLnSqqhA8uJ66la8A4C3NxXVoK8Y7fw266FMeG2Yx8M15Wdw+OwOTXodOQYYFCdFJnQ4ejxw5wlVXXYXZbGbLli0AREREUFdX1+Gx1dXVPPTQQwQCAYLBIOnp6Tz55JOoqsqzzz7Lk08+icfjISkpid/97ncA3b6tpxj8TdRsfL9Nmub3EqgqwJwc1/r3cfVZEGj2+DHqdZglqBRCnAOKqtD85ZJANrMerYvfnCgKeIv2hQLHoxo3vY8ja+IJj9E0DYtB/fK/uzR7QohzTAOa3H5MRh2mc9T4o/c3UXuC5ydv+RFIPHXwCKAAVoPu7DMixAWm08FjTEwMe/fuZfTo0QDU1dWxbt064uPjOzw2JSWFRYsWnXDbmDFjWLJkSa/Y1iMUFUVvaJ+utq/QGlx+XvvkAJv3lRMdbubea4czMMHRWisLIcQZ8PiDfLGrhHdX5gJw3UXpzBiRiEnftZNxK7r29Z6iN7XOo4+suSZEX1Hv8vPqsv1s3V9BTISF+64dzoC4czC2UFFR9Mb2ySeoW4QQ506nnw4uv/xy9u7dyxtvvAHAjBkzKCoq6vFun+c7r2oh4rJ7UAymUJpqdaKL7tdmv6AGCz/ez+Z95QBU1bn57cItVDV4ujW/Qoi+ZX9hHW98koPHF8DjC/DGJznsL6zr0mtqGhiSs1CM5jbpzinXozNZuuSaiqKgqrLekRDdKQj83wfZbN1fAUBlrYtfv7yZ6ibvWZ/bp1oIm35zmzTV6sQY3/+sz32mpJ4RF4JOv3l88MEHKSkp4cMPPwTA6/Uyd+5c7r///i7LXF9nDDShlR/AXZhNxEW3o9ri8NY2YkpKxW2MarNvk8fPtgMVbdKCQY3S6haiHSaEEOJMrN5R0i7tix3FjB0Ujd/fdW8APZY4om/6Od68HQRbGjANHIc/LBUAfXM9/ppqdHY7Wng0QeXM34IqCphayvDm7SDQUo85fRz+8DQCSHc1Ibpao8vPrkNVbdKCQY2ymhai7O3fGp4OTQMtcQTRN/wEd+5WdM5ojGkjMUYno1Q1oKurxt/QgD48nIAzssu7u5vdFXjzdxJorMacPoZARH/8yFtQ0fd0Ong0m8388Y9/5Kc//SnFxcUkJSURGRnZlXnr0/T4cW9+l+ZdK0JpxoRMWhpiaFj4FumP/AB/eOyxbXqVCIeJ2sa2bxrtVqmYhBBnLi3B0a5hakBCWJfPGKlp4LbEowyZi6qA58vr1Wdnk/P0M/ibmkBVSb3jNqxTZxBUz6yuM7nKqXrrKTRPCwBNWz8iev4PCcQMPWdlEUKcmFGv4rQZaWhu+6bRZj43y4z7FSP+yAx00ZmtdYqmYQ8E8O3cRs4Lf0Pz+1FNJtK/+zBqxtAumxTH7K2i+u2nCLqaAGja9jFRVz2MkjhaxmiLPqfTzbmff/45r776KmFhYQwfPpywsDBeffVVVq1a1YXZ67v0ruo2gSOAt/QAzoFJeMrKKVv0Prrjxv1YDCr3Xjsc5bjeEBOHxJEYZe2uLAsh+qApwxMJO+4NQJjdyJThCd223ICmaaFr6b0tHPzL862BI0AwSMHLr0Bl+Rmf31+aEwocj2pY9zYGxXfG5xRCdI7VqOPea4a1eXaZPDyBhHP87BIMaqHAsKW4mCNfBo4AQY+Hw889j66x9lSnOCuBiiOhwPGo+tVvYtDcXXZNIXpKp5t+fvnLX5Kamsrtt98OgE6n4/PPPycvL49Zs2Z1Vf76LC0YOMmW1oCxcfdu4j1uMLVWsJoGGUlOfvPAVMqqm7FbjSRFWTHpunZSCyFE3xZpM/DUNyZRVNkMQHKMDcc5eitwlKIonWrx15qb8JS1DxR91dXo4pLP4Lqg+dsHiUGvB0WTSXmE6GqappGVGh56dnFYjSR24tlFVZUzbsDy1dSGAsejAi0tBBrqwR5+RufsiBZoX89ofm9rPSNDIEUf0+knhIqKCiZPntwmLT4+no0bN57zTF0IgrZoTP2G4cnfE0rThcfjKm8AwDliBJqp7WQSChDrNBHrlDGOQohzx2HWk5USdu5PHPBQX1VAeeFhwqPjiEocgM7oPOnuis2BOSEed2lZm3RDVNQZzb+qaWBIzGidvfq4BjvnxGvwKSaZqVqIbnA6zy5Bfwu15flUl+YTFZ9CZFwaisF2WtczREai6PVtAkid1YrOGYb/FMedDX1sf9DpIXDsCo6J1+JVbbK2kOhzOh08xsXFsXr1aqqrq4mKiqK6uprVq1cTFxfXlfnrs3wYcVx8D6actbgPbsYQN4igEsPhl/6LKT6euKuvxN/5XsVCCNGtFCWA39OMTm9A0VnaPR8pCuTuWcvmzxaF0uJS0pl13b2gO/GMqn6jhUHfeZB9v34Gf2Mjik5Hyh23Q0zHS0KdjMeeRMxNP6NpywcEm2qxjZ2LFj9UnueE6AaK5sPva0FvsKApp54gR9H87Fq9hAPb14bSBo2cyJiLbwSl82OerUmJDHjwWxx54e8EvV50FjPp33mIgCOiywI5jzWBmJuepGnrUgINVdhHXQ5JwwlIRSP6oE4HjzNnzuTVV1/lkksuISEhgdLSUjweT6gbqzh9HkME6pDL2F9ej9YE8U6FsLtupNbTSH5lHvFWCzpTeE9nUwgh2gi4a9m84l3y9+/EHhbJtHm3Ex6fjqYd65/lc9exddXSNseVF+bSWFOGI+bkU+k7h2SR8fTT+KurWmdbjYgmeBYNaZqm4HakYb7kWyho+ILSKCdEV1MUcDeWsXbpa1SW5BOdkMrUebdhcSacNH5zN1W3CRwBDu7cyJDxl2B2dr4BSdHp0A8bTeZvfkOgof642Va7LpDTNHDbUzBdfD+qpuHXVGmgEn1Wp39FH3roIcaOHYvb7ebIkSO43W7Gjh3LQw891JX56/MCfh8H92zlwO6NfL52Kas2fMjO7avxuFrYtup9VOVkYyOFEKL7qQTY/Nk75O/fCUBTfQ3L3nged2Nlm/20YIBgoH0nscAJxgYZNTA2eDE2evG3ePFbnZAygEBE7FkFjsfzBxUJHIXoBqqqEPTW88kb/4/KknwAqkoL+OSN/0fA23TS405UN5wq/SgdYHIFMNR5MAVaIzYNhUBYFKQMwO/o+mU6jgoEWusZCRxFX9bpN49HZ1fdu3cvRUVFJCcnM3ToUBRFRgKfDdVoZ9jES9i5dlkoTac3oKoqh7O3Mfai+VgUO8FaN1pQQxdpwWuSikkI0QO0AM11xeQf2NU2ORiksaYck/3Y8kImSxj9s0ZzZN/2UJrZaiM8Ih5DtQvNE0AXbkYx6Kj5NBfvlxP2mBMdOC/qj1cvvy1CnG80v4u8nK0E/F5aGuvbbHM1NdDSUIM9yn7CY63OaCLjkqgpLw6lRcQkYAuLRlXA0OwnUOdGMetRws14VdBr4MuupHpL63q1qkmHYf4QMElDkRBd5ZTBY0lJCXa7HafTSUlJ640ZGRkZWt+xtLQUgMTExC7OZt+laZCcnoXRZCJn50bsYZH0HzKKras+wO6MwKQYqFq0n0BLa8ubatQRMz8Lj1kWuBZCdK+WuhKO7NuK1RHW7sHQaGk7qUUQPWMvvo7wmERy92wiJjGNUVNm415XQ11B67E6uxHn0NhQ4AjgLmnEWtiAMiBMGsmEOI8oCpQV7GP9x28x4ZJr2s2yrCgKRvOJxzsDoJq56Ppvsn/zKgoP7SV54BCyxl2EorOiq2im/MODoV3NqWE4Z/aDZj/1XwaOAEFPgPJPDhExLwOvtD8J0SVOGTxecskl3HnnnTz66KNcfPHFJ3zLqCgK2dnZXZbBvk6vV/CXV9Avpj/KKIXiIwdY88GbKMClV34DtUkNBY4AQW+Alr0VGMYndts6bEIIoShQXpTLwZ2bGDPzCtYv+19o8ol+g0fiiExod4zOFMbgCbPJGDMLVWdEV+2hsqA0tN0YYcFV1NDuOHdJA9ZBEfj9vXM5DUUBXV0V7sIC0DTMKf0IRERLsCsuaKoSZN/mVQAczt7OsIkXsXvDsfWsx150FSZb5CknOdabIxkxcz7Dpl6JqjcSDCoYgxpVq/La7OcuqMdR70XztO8a76txoQSCoL8w3j4qioJaVYqnqAjFoMeU2g+/PaKnsyX6sFMGj5qmtWk1OtFg464cgNyXKYpCo8sH7maaPlxFxYH9hF86i8xBWWQOmYhFC0NfrsNvPLbArKJX0fxBfDUuTApnNHW9EEKcCU0Di9WBx9XMvq2rmXbFLaj2ONCbiYuJRFHbTsOv97TgLy3C7/FiTEwk4DS1e9DzVrfgGByDu7htAGlJDSMQ6L01nK66nJynfom/qXX8ls5qJePJJwhEnfmssEKc7zRUHBExVBTnUVVaQFRiP2bc8iNUnY4wi4LZFoVGx72mVLeLYFkJ/hYXhvgEFGd0m0b00PW8AVRH+xlcjXF2ghdI4Aiglhaw/xdPoflaPyNjdBQDf/IT/M6oHs6Z6KtOGTzu37//hP8tzo7HH2Tl9mLe+zyXYFDjshFXMmVABnUfLYblkHzjreB1EH5pfwLNXpRBNir7eSj31RCrjyDNEYU/IEG7EKJ7RSelYw+LRG9yktsUydsfFdLs9jNhaBy3XZaJw9z6k6Jvrqfgb3+j6cvfDZ3VSsZPH0cXHt+66NuX1VegxYchyoIlLRxXXh0AtgmxFMU1UFC1nzCTk1R7MlZOPEaqJ6iqQu36daHAEVoXIK/94nMibriZgNTN4gIVDMLQiZeQt387KcNnkOMfxAuvHgQUrp7en0vH6TB3ENPp3U2U/N9L1G3dBoBqNJL508exDoqk5WDNsR1VBV2YCb9ZR+SMNGrW5ENQQ+8wEXdZOo2AT/FQ3FJCWXMFMdYokqxJmDlFt9nzkE4JUrpoUShwBPBWVdO8LxvzpOnSG0J0iU5NmOP3+5k7dy7Tpk3jySef7Oo89XmHShp467Njffc/3lFJwrTBJNlX4G9qwt9YQ+wNs3FrGqrFxLqmQyw9cKzrx6x+k7gu4mp0wU7PdySEEGdNbw5nzu3fo7Dax1MLj02as2lvOWE2E7dcMhA0cB/JDQWO0BpclfzvHZK/9SCxVw+mdlUevkYP9qwY1Fgb9kQHjgk+VJ3KFs9e/rbmldCxAyP788DoOzFr1m4t68moqoK7uKRduquomEhFBWSGbHHhsoYncs09j7G9wMfH7x+tAzTeXZVLcqyDUQMiT3m8r7AgFDgCBL1eCl5+mfQf/BhVp9KUU40h3ETkzP54LTo0DdQB4cQlOdC8AbAZMMc6aKiqZ0XhFyzO+TR0rhmpE7kh42p0wc6vGdnbKQE/nvLyduneyiosXxlzKsS50qn3+nq9nmAwiNvt7nhncUo6ncrm7PY3+roCD5b0gQA4Bmfic7dOIFEdqOWD3JVt9l2Vv4Fqb3XXZ1YIIb5CZwqjvKH9A8manSW4fUFUVcFbXtFuuysvD83rwRtuIuLawcTdNgLT+EQ8egUfGl6LnjqTi4U732lz3KGaI5Q1FKKccqRU9/H7g0ROn94uPfqiWfj9EjiKC5umgSUsnvV7q9ptW7urFP2X3UlV9cSz2fjr69uluQqL8Pu9mCYnE3fbCCKuysTjNIbeqgU1DY9RxWs3hCbJqQ/UsuTg8jbn+aJgI9Xu9nXT+SygMxFz6aXt0h3Dh8m8GKLLdLpT+IIFC/j444957733yMvLo6SkJPRPdF4wqNE/0dkuvX+kAUXRGPS976C326h44zX07ia8AR/aCR6avAFPd2RXCCHaCT/BOKOUWDvGahfB7Cpsaf3bbY+cOoWgqbXLmBcNjwqBr7SKBwgyNWooVyZOIszkCKXXFxei5R6gt6wMZRyYQb977kbvcKC320m9awHGjKyezpYQvUIwGGRQani79IHJYeh8QfRlzQR2VWCobMHwlaHNxoT2E29FTJqIZrURCLbWG95O5MHg17gmYQoJxy0fBNBYmIfedfK1Js83mqZhGzOOpBtvQGcxY4gIZ8BDD6Imp/V01kQf1ul+j7/5zW9QFIWf/OQnbdJlttXTo2kaowZFsyzSSllNCwBhdiNXDI/EFDaGgtf/ixbwEzNzBsGqciJTk0lyxFPcWBY6R4QljGhzNL2kIV4IcYFJjbUzfGAUuw+19oAw6lVum5RGwye5ENQwJ5pJXXAHRW/+l6DXS8TECURecgn+U9RZasCPef8hRr+xlaDXy5i5s1gd3cjamr1ENQXJe/ufDHzql/hNtpOfpJsEDGYsU2eSMWYsigYBq52AtPILAbQ2kk8ZlsDKLUVUN7T2WIsOMzNpSByNawpoOVwb2tcxPBbT2IRQ3aAmJJF2/30UvryQgMuFc8Rw4q6dj7+T7zoUNOp376Hu5VdILytn2LTxHB42hNeLVxFudmI5XI4vkI+SMfScl7unBCx2HHPmETZjFqg6AiYLUh2JrnRag+ZkttVzI8xi4Kd3jae4qhlN00hx6rEU5ZDz4v+F9il+5z0GxMRgSE7n2+O+zpKDy9hVsZ/BUQOZP3hul47/UZTW7rWBQFAGWwsh2rEYdHxr/ghKKhtxe/0kWM3oVuaFAih/QxDb4BEMeXYsAb8fJSwcv3Lqnxut8Ai5f/pL6G/va+9y0TduY1K/QfheeB1fbR143NALgkdofUAOHs2LPKkJ0Ua41cDP75lIcXUziqaRGGUiEig/LnAEaNxdgXVILH6zrnU5OIMJ84QpZGYNQfN6UZzh+HWdH6Ooqy5j789/ieZvndm58aMVDHBPY+7EKYz2RdPy6kJ8X4+nfd+J81swCEHzlxOLSXUkuling8dzNdvq888/z3PPPceSJUvIyMhgx44dPPHEE3g8HpKSkvjd735HVFTr9MLdva07WY06MpKcmFtKaN65nOp9ze32qfxiNSkTphAWjOD2wTfhyXRjUk0Q6LopqF00s7/mILsr9pEVPYghUZnYcHR8oBDiwhH0UnNkF7s/e4+A34958mzikvuh5QVxT7OxyXuQKt8uJqnjSI1IRa+d+qfGqAao3LSxXbp31QbM4WHU1tbhHD4M7GFdVSIhxDlmMynE6spZ/+F/2dlYw+Ax00kfMwrPtrZL82hBjQatjp0Ve8mrK2JMwjAGOdMxaqd3v5u9VTQdyg4Fjkc1fbGeywbdRf4//w2AKTFR4ishzkKnopDc3FxeeeUVPvjgA7zezvQ2P7G9e/eyY8cOkpKSgNZ+8T/84Q954oknWLZsGePGjeP3v/99j2zrCaZAE02bl+AtOYg1JQmdxdxmuz4yguDRsY1BBZNm6dLAMaj6eevAYv69/XU2Fm/nPzvf4v92vYlfPfPvXAjR99RX5vPF4oW4mhvxelxsWrWIWks5vql2fp/3Mu/nL2dtyVb+sOEfZNftO+FYReXLRJ1OwaQ1Y3C0n0LfEB6Gr6ERR1YWKXfehV+VGaaFOF+4G8pZ9vrzNNRWEPD72btpJbnV29BHHXvWMcXbabJ5+NOmf/LmnvfZULSVFza/zKritSjKiUO84+sTnU7BqNOw6P24tiyFYPvnFb3DgaewCJ3NSv9v3Y+akHTOyyrEhaTDSGTdunXMnz+fX//61zzyyCPcfvvtBIOnv3iz1+vlqaee4uc//3kobc+ePZhMJsaNGwfAzTffzMcff9wj27qeH5+vBUUJENDA1FxMy7o38dgTyB95Hx/osyi9+WGsN90BioJqNKIflUVjXWU35Q9qfbVsKt7eJm1f1UGqPO1nTRNCXJh0OpWqilIGTphDTPLAUHpOzkaqHS7mpM7g1oyryYgcAMD/sj/Aqxyb4EvnbUE7mE3LimU0N9axbtsh/u/TQgoHT8d20WWh/RS9noRrrib1vvtI+d738YVHd18hhRBnTlHw+IO0tLTw1bEvB3avxzImAkOEGeeYBCIuGUCDt5FLE6dweb8ZmPQmAD7I+YxGrfH4U6KrrcSzcTUtqz5FV1VKVV0jH645yKJV+8nNK6cg8SKakwZjTUttc83UuxYQdfkcMn/zW0zjJhNQ+85SHUL0hA6bcZ9//nm8Xi9Op5OWlhZ2797NZ599xmWXXdbRoW385S9/4eqrryY5OTmUVlpaSmJiYujvyMhIgsEgdXV13b4tPDz8tMrTWYqi0NhYzWeffUp9fT0xMTFMnjQF99JnUCwO1sRP5s1PckL794tz8K0f/Ywml4+CplyyjOZTnP3cCmonbhQIysBHIcSXKhs9LD8Syb58lSGpM5k2eyZ7P/0P/bLGEKwPUr4+H7/fz5hBAxk2YBArStaHZoxWtSC1H31I2ZKlpDz9NH/4337yylsnDvtwSzk3XTSFS0YMIlBVhiUpHi25H4FAL5liVQjRoXqXjyVrj7BlXwUZKWFcdMX9ZH/6En5f6xtBe1gk+oRwwq+JI6BAvauBLSs3UFFRgcPp4N6JN7Lw8Ps0epvadC3V1VRw4Oe/INDcOsTH/vgv+fn/tuIPtD63vLu+jJ/fmMaiXQ1cfcfdxBXvx9/swp45BC15ID5V13oiGZ8sxFnrMHg8ePAgY8aM4ZVXXmHXrl3ccsstHDhw4LSCx+3bt7Nnzx4eeeSRs8psbxEVZe/UfjExDmpra1m6dHGou29lZSUrV61g7pAZtOijeOfTtm8W88ubKFT687+Nh7j78hHEJSej13dPK5nVq2N47GB2Vxwb39o/PIVkZwyNddVEhDvQG/rWMPOYmL41nrOvlQd6f5k6Wx9A7yzL6eSput7Fs/9cT0WNC4AN+6oprLJx3fjLiEoexPtLlob2PZJzmCzrEG4dfi1JUTEANOcXUPbBhwCUutVQ4HjUO1/kM+mbIzAVrECXOhGzWYfZeuoJcvwtLbQUFhFoasKcEI/luAbCc6m3fXe9LT8geYLTqw96k3PxOTW2ePnNa1s5WNi6VuOW/ZUcKjJx58Qr2b/mPRRFYfq8W4iObZ1noqWlhUWLPqKurq71+IZGtq3czLzps6jWGkiNjEOva31MLV63KhQ4muPj2JDfEgocoXUCq092N3DpEBt/XlHJj9JLscU60fdLRm9WsdpPv3yu0jLcJSXorFasqSnobT0zWVdvvK/ORl8rz4Wow+CxsbGRYcOGodPpGD16NABNTae3Rs7mzZvJzc3lkksuAaCsrIx77rmHO+64o806kTU1NaiqSnh4OAkJCd267XRUVzd1uPhqTIyDyspGamtr2o0TbWxsxGPNQPOrBAL+dscGXbXckFVDTEQWtbVuwH1a+Tsbdwz7GtsqdrG1dBcjYrMYEzWYFa+8QFVpAf0yRzJ65lXozZHdlp+udPQ76iv6Wnmge8t0pj9onakPjp6/O8qi1wKA1uHsph3lSa+BWuum5XAteqcJc1o4+Q2uUOB4VHFlMwnXzaCs4nC7cxQfLmLeiHGha6iNTa3TAgL+E3R0CASDoDNwyDmQA//6HY6IKCbPuQlnTH80rf0bSJ3PTc3iRZR/1Dr8QGcxM+ixRwkmpnVY9tPR2+6t3pYf6Ht56ur6oDc53c/JGNAIlDXhKW7AlOREF2/Hq1Mob3CHAsej6po8WBOGM2t+OGHRCViccaFruVz1ocDxKL/fT4opntFxY6j9sq5RVQVP3bFZWlWjkRZP+wqk2QuqzoCqgGXMXHJzdrHr+acwmi1MvPx6opOzoBP1IoCuvIicX/+aQHNrA1f0xRcRc8PXCBi7bqb7E+mN99XZOJ/LI0HvMZ2afWXfvn0sXLiQhQsXAq0T3xz9+2jaqdx7772sWbOGFStWsGLFCuLj43nxxRf5xje+gdvtZsuWLQC8+eabzJkzB4Bhw4Z167auYjab2qXpdDqMOhVLwQZmDGs706vTZiQ9yk6CzUptwe7QpBLdxYaDGXHT+MHYb3FRzFhW/utPlBceJuD3c3jvVla//x8UTSbQEaK3UYN+tEP7KPj9M+T9+lcE9mxD5/d0fOAJKIqCVtJExZIDNO2toG59IRWL9mHR606wLxgNRpxOZ7ttUVHRGFUzqgIE3fisBqwDW8dCxlsVnLa2PRlmjEwEXwNV5SX4fV5qK0r56NW/UlJ1gEMtB/EobRvSAiVFocARIOByk/+vf6P3d1+DmxAXEgPQuLaA6uWHadpXRfXywzSuK8SAgkmvQ1XbP7PY7Hbi+o/G7Ihv0whkMBjR69sHc1H2aGyYIehBUcDbUkMg7tizUkthEVP6t38LeGmGg2hfCw/PT6e+pZndG1bg9bhoqq/hs7f/RVNNcafKqAt4KVy4MBQ4AlStWIm/qLBTxwvR13WqCWbLli2hgOtEfy9YsOCMLq6qKs8++yxPPvlkm6UzemJbV7FYHIwbN4EtWzaF0oaNmkgxFmLih3JdrJGkhEGs3lXGgHg7UzKMbFnxCumDhmOxRULQA0r3dhXVNI2AH+qryvB62r5lqCjOw91ch8ke2615EuJ0GDUXSnMVGMz4zNEET/DWqq/RivI5+NtnQn/n/vmvDHzk+6iDR5z2uQxBjeoNbR+Ugi4/0ZrCpeNTWb65IJR+5ZQ0IuxGAuZ4YmJiqKxs7YpvMBgYN2483uYasjevoPDgHhLTMhhy3wKav9hE/T9e4GcP/YCPNpVwqLSJiVlRxJgbeH/pF2QOGkZGTCI5W79ACwaprijib6WfcEn/acxPvxIl2BrE+uvr2uXdVVgEbjfYu2+8uBAXCrXFj+tIXZs01+FanGMTCbMauG5WOv9bcSi0beqIRGLCTnwvGgwWZs6cxWefLQ+ljR07DgM+tnz6BqX5B0nLGkXmiPFUeKqJf+AeGj5ZSdDlItpTyWMLRrJ4dSF+f4C5mTasy9+lIHsvUQ8+wMqDOUyccwvbPnkTd0trd9fS/ANkRKd1uD654nXTnNu+J4W/thaZakeITgSP48ePP+cXXbFiRei/x4wZw5IlS064X3dv6xoqWVnDSU1Npbm5CYvVQWlVkIpGL860WYTZAoyp3sf46Q42b/mYrYuOAFBTUczoaXNQdQYCpz+57TlhNLWfOl+nN6DT961xj6JvMXsqqFv6F3zVxaDqCJv6NfSDL8KvtO8F0FfodArVGza0S6/46GOSh4w4YRfRU1EA7QQVj97t47qZAxifFUtJVTNJMXZSY2wogF5vZvbsK6mrqyEQ8BMeHoFF8fPRm/+kpqJ1uEDOzg2UFx3mskvmEjF7Bu8WfYYpXeHrw0exdcN6sr8cEnHg4CEmjx+NTq8n4Pejffl24rMja5iZOpkoXesYSkN0TLs8OoZkgaVnxiYJ0ddpJ+mSqwU1FODSsSkM7hdJYXkj8ZFWUuPsGE7wNhJaJ2JNSurPDTfcRGNjAzarBbs+yNLXnqO5oQ6APRtWUFV0hKmZ/QnYoGHqUMLjEnnRvZno2gPcpYKnoYbmF3fi8flaz3skH4D1W3YyYvzF7Py89ZnP5ozoMHAE0MxWwkePpHbz1jbpxthYWR9SCDoRPL7yyivdkY8+TVF02O2R2O2RaBrUuhvweeuo13SU5DWS6PPRVF1IVfGRNsft3fI5g8bOQtF1bx/7o6xhsQwcMZFDu44t3j3h0vkYreGcwWotQnQ5veKncc2brYEjQDBA/eo3iU4YhD88vWcz14U0rXUts6/SORxoigKn+cjj0ymEj0uiZnV+KE0xqOgirZj1KoMSnQxKbN9NVVWNREbGA2Dy11NTuC8UOB5VX11Boz6MnBVLSQD6T5zGzs07242lr6ptwBERjd5kolA5tqi4N+iDL3vPKnGJ9PvG3RQufJWg14slKYmUu+7Cr5P3A0J0CbsBU5wdT/mx+9UUbwdb6z1n1CkMiLMzIK6zEwcpWK1h2O1hqPkbqQyoocDxqLKiIzRPn4du2R9JmnQjR1QX+6sPMyZ6MK6Cclr2HWh7RrOJQH0LHo8H3ZeN4LawSGJTOvcbEFD0JNx0M57KKlry8lH0epJvuRk1IZlAJ0slRF92Wisu19XVsWzZMgoKCrj//vvZv38//fv3Jzpa1t/qrCpfLcsrPmZ7+Q7sVTYeGvp1yur8xFrad+swma0oSvsxRt1GNTJm1nwGDp+Ix9WA1RmNPSJBAkfRa+n9Ltx5u9qlBxoqoQ8Hj8GgRtj4cZQtWUrw6ARdqkrcFXMJBE6/rTwY1DD0DyfaoqdpdwX6cDP24XF4zLp267adTKO7mqoT1GsAlc1BGpuaqSrKpaGqnPgRF1NRUdFmn9jYOJzOK7DGOfn97r8DkGSPJdoUBV/WQUGdAcvkGQweMoyg24UaHonf2L7HhBDi3PAC4ZcMwHO4FteRWixp4ZjSI/Gc7cgAXy2blSbUE3QMVRSFg1VBBg2ZQ7guSGJKBhR+zM7qHObOuRL254TqJZ3VijcxHk9FGXq9nvCYFCZe/XXs8REYzJGdrb7wh8eQ9uhjBGuqUc1mgs5IAvT94Q9CdEang8eDBw9y1113UVNTA8D999/PN7/5Ta655hp+8YtfdFkG+xJF1fi88Au2lW8HoNHTxCsH/8dNCXMw6nXYwyJpqq8J7T/p8utRdKZOV3ZdQdFbCYsbeF7PkCUuHAGdGVPCQDxF+9uk6+yRtJ/XuG8JxiSR+dQvaNqzh6Dfj2PYMLT45BPuq9erp6xXdPhQGwoJuIoIGxmBEhODW+184KiqCpsa8tlTeYhRI8eRv/PYGPnkweP4bHcLUwaMpqool/qqckZHh5HndNLQ0PqGMTomjtwaM2+uKOC+mxyEm50Mi+jHvP4zMATbdj8OahB0RoIzFFMKIbqIPuhBa8xHbygjfFw0WqQZz0m6pZ6OIm8N/85ZxtT4USQNyqLs4L7Qtv6jZ7F8VyOxw+KJtumJtiYws98kPs/fwHvebG748QOYckvQmyw0Rkbyxb5sFEVh+Ngp/GFRCWOyork+MxHtNF8b+vVmiE2SekWIr+h08Pjb3/6W+vp6UlJSKCwsxOFwMH78eNavX9+V+etTXJqLDSVt+9AXNpbiSqkjpjHArHm30lBfTUtLE3EJyTjjM2Q9WyFOgw8Dzll3UP3Obwm6Whs7bCMvJRie0sM563qaphGITsB6UQKgEDxBoOf1BzlQVM+KLYUkxNiYPTGNcIuuTUyoqgrqkS1ULftHKM2UkoV99oN41c6NJfTj44vi7RQ3lhGdNJahqfPxVtcSEZdMdrGDov31uJ3H1rgtzNnOnHnXkJNbgccf5Ei5n49XFOCwGhjsr2aIMQ2bx4LZEInM9SxEz1AVjeC+5dSufTuUZs2ahmn6Avyc+VwIigJHGssAWFu2g7mZUxiakYmvrp7wqHRW52jkFtdgHWNHjemPGtRzTfocpsTOYMe+el7d1sTUIeMYEB0ggIEBihM/Rt5aXU5FrYtxmQnoAjJXgxDnSqeDx127djFv3jycTmdoHGRiYiKbN2/ussz1NUbFSJwthry6trMY6nwutJUL0QCH3kj/q7+HFp6IR+vBLqtCnKc8tiQib/kVWkM5islKwBqLr5tnLO5JrYFg+8BRVRU251Ty4uK9AOw8VMXn24r51b2TibAZ0DQfjY11OHVBGle1HevuKdyHvbYYojI6lQdV0ZEclkBxYxkrS7byuaJiM1q5iHg+3lLJN2cncnD5/4DWLmnp0WnodmeTnDGKV5cdYOfBSjJSw7nnysHEUIYSH0fQHo+3D096JERvEgx6aWysAxQcjnBU1YDBXUXV+nfb7Neybw3WUZfjd6Se8bU0DcIt4aG/Pypah05RGR47FG+2xtbsau6aM5DEQeF49K1jrVW/gf97J5cjZa0zqe49XM2ErBhmDXBTUmPj460FmAw6Hpg/hNQYmUBLiHOp08GjxWKhpqamzVpeBw4cIDw8vCvy1SepQT23DZ/PM2tfwB9s7UQ3KDyV+Oqq0D6a34vP6yGgD+upbApxXtM08OjDIFLuoeO5fEHe/uxg2zSPn4KKRhwpFpYv/4SKinIunTASx1eW6AHQfMfWTtTpFHwBjaoGD4FAkOgwc9sZFQMKV6Rfws6ybNx+D0EtiN1gIyt6EOO+EYap5iDBjBGgQWpcGg3/W4o7PJyUcRN5/K4JlFc3YdIF8TRU0Ki3YbJHcZpD9IUQZ8jna+ajjz6grq4OgOjoaC6/fC4mvxeC7ft+at6266oeXevR5Q1Q1eDBbNQRaTeecsRgf0cqaeEpocZ1VdUxJ/1iaq0W5k/PIC7MjPe4OqasqjkUOB61aV8l104ZyRDPFsZcl0ZETDxhTieeplqaXU1YHBHojI4eHQokRF/Q6V/jsWPHsmzZMnJycgC44YYb2Lt3L1deeWWXZa4vcgbjeXjEfbQEKrFoQeJ0TmwNtRydt0wxmCEsoUfzKIToizRUpf3jm6IolJQUU1FRDsDBkiompo/Bl3usi72iN6KLSIBgC0rFQdx5O3E7kshzxfPPz8oZlBrBt+YPx2E+9pMSo4/lyek/oKS5DIOqJ8EajxU7qqrQuC6PqPUHQFGoKl5F2PChRE4cj4aC2aTHGGhg5dv/orqsCIDBY6YxYto8FH3PzDwtxIVCVRUOHswJBY4AVVVVFBbmkzWgP8a4AXjLj62BqFqdKGGtMyyrShBjQyHuQ5vRdAaqrRn86ZMaahs9XDN9AHMm9sOoO3EIacXBg2PvobS5FE/QS4Itjgg1ipT+J470FFVtlxYXaSHCrGfYnOuorXUR8Pso3L+ZtR++QTAQwGy1c9lND2CLTJEAUoiz0Ong8Uc/+hF79uyhsLC1VWjPnj0kJyfz/e9/v8sy1+cokH2olCElS9GOtHb31QBf+lhsQ6fir6/GMWIWwYYSfKqegN6K0WiRSk4IcdbMeh03XZbBP97bHUqzWQz0i3dwaG92KC2/qJiBEyYQY3HiO7QJQ1QSzlm3o9lj8W9bRMP690L7Do1M4cYpN/Hm2grW7Sll7oRUgl8O1NY0cCrhOO3hbfLROjPseCqWfYLeaSfjO3fgLdhMsPwL1CIHPssY9m9eGQocAfZvW0PKoOFEJmV10acjhABQVSgpKW6XXlhUTL0Ww4TZ9+Pa/D7uw9sxJg7CMfUWApZw1ICGsTaPyv/+kqPd5h06PQ9d/F1+saiCRV8cZnh6NP1PsYSHRbMywHpsVuxTrckYF+1gUHIYB4vqURT49uXxDPFno336IdVpwzENu5hmj5/VS14NHeNuaWLVey8x984foehkVmYhzlSng8eEhASWLFnCypUrKSkpISkpiZkzZ2KxyA3YWT6/RoxaHwocj/IW7MVx009pqa+jetkLeMfcRFmzi0ZPI2kJYcRFhoNMES2EOAuapjFmYBQ/un0sq3eWkBBlZeywSKqD+SQP6Ud+QT5Nja19ID7btJOZM2dgTJ6MxxDFroIWYuvLiCgpaHPOYE0hWZmtXVy37KvgymGJqHVudE4TfqueAEdndtXaLBnij4hl0M9/js5VRtWiZzn6sFmz5C8oNz9BwcHdfFVVaQFRyUM6tci3EKLzfH4f1YFKqt21RJjDGTJ8KCUlbddndUQmoPlaeO+zzZgMsQyafA/2uIHsL3Xhz88lOdpMxN6PaTPeOuAnsnYvMRGpVNa6qKxzMSDejtETJFDnRtGpKOEmvF95G3l0NuhA4OTznBpUhYduGM72AxUYNB9Dit7EV9K63qOvqhD94R24J9/W7rjGump87iaMNnl2FeJMndYgErPZzNy5c7sqL32eQa/gtBz7yBW9Edv0O/AZw8nZvw+PFiDiiif51Zs5NLa0dg+OdJr5yZ2jiTxBRaco0OwJENQ07Gb96a4DLoS4wBh0KoOTwxicZuPjvJX8atOnAAwK78c3Z15JRWE5Ow4fZsTYsdjjI9i2x8Ubn+wMHX/T1IuZGlePVpkHX47bVr+cyH70gCjqPjqIv8EDQOQV/an1lXBg+1rs4ZEMGjEZszMhFPxp4ZE0ePLxz7oRU/4+Akda1+ds2bWC5PQh7Nu6uk3eo+KTJXAU4hxTVPg8fyP/3PJaKO224fO5bNZMfDV1NPq8NKKn0WfF0JRHRsZwUuNjqfbDz/+zi2aXD4CYcDM/vnw6hpxNrSdRdRAMoAQ8GHStXUyjwy2YWvyUv7cPzddabxiirETOGYhHr6AQpKmmkP1bV6OoKpmjp2GLTAbad1H1qx40k5spo+OwNVVSuelA2+01JdhO8HLD5ozAYJYJdIQ4G6cMHrOyOu4ipCgK2dnZHe4nAA0iElNwxw1Aa6jAPu528l59H09xKdaBA0m79w4W7ainscUXOqSmwc2G/WVcPj4R/XHrm/kCQdZll/PfT3Pw+YPMmZzG3ImpWI0yQ6sQ4tSKmktZktMaON6QMI3B2ysp/vtT6ExGZt90IwcNdeQVN/Lf5Q1tjntrXTkj7/g6vtId2MxmbA3F5LsdDEjUMSHChv9QPQCqSUdx+X6++ORYl7ED29Zy1d0/xmiLQVOC7K0/wMsHltDgaWRsQibzB9yK/rPXoaWeoTPmU5p/kLqq1un7B42YSGR8Wvd8OEJcQOoDdfzftv+G/lYUhejGACxejHvPXmzRUcTfdAf5FiMBU39iIi18UrGGytzUUOAIUFnnZldtApNTh+JNG0t9ixuz0YgpZgCla/O4YkoaqTE26tcUhgJHAF91C/7yJkhy0FRTyNL//CG07eCujcy76wfYIlKPyx+U+Up5cfsbFDeWkRqWxDdGXI/JaG43cY/NZGLK3JtZv+wttGAQo8nCRdfdjaq3ynAgIc7CKYPHzrTySktwx4wB0BrcKKqC3mJBP/EeFE8lOX/8J4HmFgAcF09hx6bPyasb3u74grJGSt1lpBj7hdKOlDfx8gfHFtH9YO0RYiMszBieIN+JEOKUGryta2BGWMIYnO+hcUXrW76Ay03RfxYS+dACKq1RofGLR2kaFJZVcPjzZQAMGTeDwcP6MTHLSOM7xxoRDf1t7Nj8Xptj/T4v1aV5JAyModJXwXOb/i+0bWvFAUzxBuYnZxI2ZT7N5ihm3/Y9musr0ekNWBzRaIqhSz4LIS5kzb5mfF/2IgCYGjMcyzuraDxwCABvVTU1f3+OQY8/yYpcH2HhdZS6q6mubD+xX35FC2NGz+Oj1/8WSotJ7MdfHvwGVmsYZkWhtqb9TM7+Bg/GtHD2bf2i7QZNI2f7WsZdlhbqwtpCE3/a8E8ava0zrRbUF/PHzf/hp3Puxr/4hdCh5gGjwRZNalYC8f0ycLc0YXNGojOFyTOSEGfplMHjZ5991l356LPM3iBVH+SEunIZo63YBkTibVYINLdgTEjAfvvd1PjKKN68l/ETJrA/r7bNOTLSzazO38Qdg/sTCARRVYWdB6vaXWvl1iKmDYuX0ZFCiFOKtUYDMNzZH//HO9pt1+cWwVgz4Q4TdY2eULrTZsTgO1Y/ZW/5gpShk9Ec8SgGNfRGQYtxkDT+OmJ9XoL1+RzevhI0DQUFY5OPMndZu2tuKM/ma5d/F0tsGs01btBZsEW2vnGQRz0hukaEKRynyUGDp7VBKcsQh+vA8jb7aIEA1FQSZo2hylfKoZrDXDViFgcL69rsNyYjgs+X/r1NWmVJPt76cmqaFCxKgOgJYXiyVdzFrQ3nqlVPS4KNwpJ6ItMnU1VaTH3VsfGWypczRKuKgqHZR7GvMhQ4HlXnbqA+Ip6Uqx7GW3wAS9JAgjEZeGntrWWwRmP4ss6TwFGIs3fK4DEpKam78tEnqaqCK6c6FDgCeKtasPWPQDVaMCYl0XjDvRR4TViq9+L1uLA27WfexAyWba1AVRXmzUimILCN/hHxx81iqJF0gkVv0xKcqCpoJx9jLoQQROmj+fb4u1h7ZAO65Hgobju7ohYdwYqiz3j4hvtY+FEeR8qa6Bdn52uTwzjw2Utt9j2YX8nSHcX84Nqh6L4oxNsvjH9vK2HHodYGrrT4RObPuoWDa98hOiqZysX7scxs/xYx3haDaoxA0RkAd7vtQohzz4KNR6bey/Mb/kNFSzVuPTgdDvyNjW3201mtLNtUwjcHxjHQkURGfT5XjY3jox2V6HUK142LJTPWxL6mhnbXKK2s5Q8ftc6ePG90DBeZq7ENTMJbGaB8dCy/f2kTHm8Anapw60XXEX7gfeoqCkFRyBw5mUAgiLHOQ+Unh9BPtKCgoB3XpKQqKmaDHV9CKrqkMTii7FRWNrbLhxDi3Oj0hDlNTU38/ve/Z8OGDdTW1oZabxRFYePGjV2WwfOZqig0F7evSL31bswJ0dju+CY1moWF7+7h4SsHACvI276C8Jj9fHvWFCKSUnmjZAkNDQ0MsY8jp7ie9AQnKjBsQBQJUTZKq1tb4GxmPVdM7ieBoxCiQ4qmMixsKFkTB6KPryBnVzYBV2t3MnNSIoaMTDw5m1Dzt3O3WgYT07CFK2za/A5ez7FuZzZnBJUuI4UVNXyyJY8rwss5pNpCgSNAXlkThRlpzL/ym5j9BgzDyzEb4hkeO5jdFfsB0Ckqt4+8rs24biFE19M0GBwzkMcmf4cmfwsRRifBBZHkvvA8RwcGRk6agj4ihmini+oKC/MTp1P7+DOMTUlh4pRZEPDjXfYfiL+D/kMncnj3+tD5VZ2OFpxA67PK0u2VDJkVzSBTLYGh0Ty3OBuPNwBAIKjx6ooifrXgThxlB7E6IlF0dgy+erSaIzgH5BOmDOC6wbN5Z//HoWt8beg8IvThaEHadbUXQpx7nQ4ef/GLX7BkyZJ26coJFp0WrQJBDdugKDxlTW3S/UlGlGgTwUYLpvJGghp8vMvDlZfdQcG2ZQwYPgFbdDya5uee9OvwYeSJf+3FHzjCk9+YSL9oG06znp/cOY7iymYCwSCJ0XbCrXoZBC6ECFGDfqgoxVNWit7pRJ+USsBkBVofsmLtUdQ7VPrf8wP8zdUoOh3mxASKiiv5TuY3iGtpJu+fbwDQotcz8Rt3sD/sACWFuUQmpROZOYv/90FrF7NdRc1cPXsA2Tvbt/jvPFLHqO1r8JUU0+8799NkUYhzRJMVO49gMMhAez981R7KdQVALIpike5lQnQjo2YhUmfBGICGmnAGfvvH+Btr0FnsBJot6Mv8XDHYhSnCidnoxJKYiKugAAoWhs7h8mpY0qaQabaQt3sDzsgYEkfN4aVVbYfi1Gt6/M1NuCKTaWj2ttmmaVB1pJTGl/4FQMTkiSRcMYsWi5EaZwI2o0ogEOCmYVfjC/owqAY8Hje1dZW0NLmw2+04HDI+Woiu1Ongcc2aNaSlpTFw4EA+++wz/vjHP/L000/zwAMPdGX+zmuapmFIDcM+OJqm/VWggHlYFFsqPUyI0XC46zCHq9xzeSJbclv4f8ubeGj+19m/ex21u1oHq+t0OmZefAXBLx+kNu4pY8AlAwkENGxGHRlJzuOu1yPFFEL0MgHFT4W3nPLaYkx1zTgO5dPy8SoiJk4g/s6vEzBaUPBRXV4MOhVXQQBfrbn12CYXuv2f49mxnYYJ44iaPInq9RvQ/H4q/rWQkY//hJTJ1/HOF4Vsf78odM1h/WwoniYGh6t8ZdoLRsWb8O7Kw1tdQ/mqDdRePp7luWsAuGXQVWxZvoHGhtagU6/Xc+2112G1hnfHRyXEBU1RFBprq/C1NGG0OvGrRgwRNhp2lgM2WkcctxDVL5ZYnMQkhhEMaji/eQ85T/8Gzdc642r4pIlU2h18vLmapqZEZk64mwlDU/jHkgNU1bXthh6u+DBFRxHYvZ1wezh1TceG9qgKOAMujqbUrt+IbtQEXjqoMjErhoRwH4uyPw3tnx7ej+n6kSxe+X4obcKECQwePIITLfEhhDh7nQ4eGxsbmTt3LiZTa7eiyy67jDVr1vC///2P225rvxCraOXVK5gnJWMaFc3uyv34CPLSq4cYO3wc5TW72bbmY/x+H+MyRjN86iS8rgZqa4+10gUCAbJ3b2VcZiqb9lURZjdKkCiEOClFgR3VO3lpx7Hp98cOzOTyi6ZQu3IdMbNn448JZ+0Hr1JWkIvZamf63Fsx77fgLXPhKXeRNP8G3GUl1GzaQuS0qaT99IdUVpdS61D5d81yLk++NvRbAJCeFMakgVYq3nqdpIHDmJSRyoac1npsSIqT4VoFLdU1APgPHUCZOQkAk86I3W3icMOxt5V+v5+tWzczc+ZlBKUbvhBdRiFIZcFe1ix9HY+rmfh+g5h65W2YhoahK60nUNUa9OmynDSH+UmwZOA92i00ZQCDf/NrPOWlNOuDLHftZ+XhvzF2yGgy3COpbNTx29d3ccWU/pTXuqisdaGqCtdPTSHZ1kTFis9xH8jhga9/h+c+r6DJ5cOoV7lnZiLa0oVt8ukuryC3xEp2Xi0/vicDg6oPzRA7LXYs+1fubrP/pk2bSEtLx2x2dP2HKMQFqNPBo91ux+12k5iYCMCvfvUr1q1b1ybQESfm1zRUq5GtTdnE+ccya2wyzVVlbFq5OLRP0YFtjIiMxmYZ1O74pqYGoiJMmI06xmbGSp/+HqaoCr5AEL2qyDSQotdp0hp5bc+iNmlbaw4wY+RsWLkO9ArrP3qTsoJcANwtTXz67r+49pZHiEiLxhVuIqemBcu9j5Ji8+O2a/xs899o8jZD6zKOFDb9nXsnfZvrpiXiaWnB21JLnENPRYsL1wfvccW48Vw2fTzGuHiUdStoenPVscwMHUVOkZ80Zz/qvLV4Wjx8VV1dHQR9gHQ/E6KruBrL+eztf4X+Lss/yMZP38YxZRwFGWUMHt4PnclITcCH1tDEYHMYdgXQWns6BcJjyDc28McN/widY0v5Ni5LjSLRPBy94mdAhIeHLo+gMZiEyWLDrAYx+4M0NDcTaG5G//Jz/HjO1TSZw4hKjkXZsYHq4qI2+fRGxJAQBanxDtZsrueqEZfybs6XYx4DJ55BNeBuBAkehegSnX6nn56ezsGDB5k6dSqapvHf//6X0tJSRo0a1anjv/Wtb3H11Vdz7bXXcuutt7JvX+sahUeOHOGmm25i9uzZ3HTTTeTl5YWO6e5tXSkYULgmcw4DE6IYne6govBQu32O7NtKuNPcLj1jcBYDkiP55b2TiXHKhBI9qdHt5/01R3jy35t45ZMcapt9HR8kRDfyBr14/O0DMrcaRNHrCdgtlOQdaLtR06ivr6Q6TOXJ93bxy/d385PXt/Pq1hqqNE9r4HicGQnj8dcWs371pxw8sAOD6mftsreIvWI2AC1bNuP7vxewbvwMq1FtfR0KWEeM5EjUIN5bXsggLuK6jCtDDZLHGzIwDVNz+Tn6RIQQJ9JYU9kurejgXkwBhY8KP+e/ZZ9SWG3i768W88IbuTzy/9aQU9xwbPkMVeFAdftnmdzGHIamGIjTFbJx03qqa6vQqrPZ+d6zWPUushsMhF98KQD+xiaa334d5ZW/ERloxD56GLaBAwBQdDocV16NLy6FpBg7BwvqMBkMDLGP4Lvj72ZexiX0i0vBbre3ub7NZsNQsR9TQGZcFaIrdPrN45///Geam5tJS0vjD3/4Ax9++CFRUVE8+OCDnTr+mWeeweFobQVavnw5P/nJT3jvvfd48sknufXWW7nmmmt4//33eeKJJ1i4sLXLQndv62phagSlLTXUFu8jKdzebntETAJ5e7YwddI4tu/KxuPxMHT4MAYPzsSgs6JpMq6xJwU0+PeSvezOrQagtLqZXQer+MU3J2I16Ho4d0K0CtOHMTh6IPurjj3UmXRGov1GEh5/DM0Wjs0ZQXND214jJqOet9fnUVnnwmYxYNSrrNxWzEVTh6IqKsEvp3JOdiQQ3WBn4+7WWbZra2spKS1j0qjJeCPiSHz4uzQ3eUCn4rPZWV+lMvdXl1Ja0cjHh1ysW9saFBYW+Lh0SDo2k8LUSePZtnMPPp+PwRkDcZgNeCvzUezJUucJ0UVMtvZv5hzh0dgNrZNq3Zx6A79ZeCjU28nrD/LcWzv4zQNTsJv0BIMaiY64due4KvViln24BK+3dTKcuro6MgYNJKF/JnVV5fx1aRPj08O46f5v4auuIRAVR1hSJE3hBvxuK4Y7v0VcSz0mm5ktFfDB8iOU17SuC1la3UxhRSPfvXkomeFZBAMasy+9iLXrN1FWXk5cXCxDB/Un4K9FayyHcHn7KMS51uGbx8LCQrZt24bT6SQtLY09e/bwwQcf0NTURHJyMtHR0Z260NHAEVqX/VAUherqarKzs5k3bx4A8+bNIzs7m5qamm7f1h10Oh1Bv5uamiqssQOJjO8X2mY0WUjNHM6+LZ+zZ8XbDE4K57orZtOvuYHyI7vJazmCpgS6JZ/ixGqaPKHA8ajqBjflNa6THCFE91ODeu4acSMTk8egV/Wkhafw48n3kTJsElpKOorewoyrF6Cqxxo8Bg0fj1bVxJEqD9+/OI7HBjXxg/hSfnZJNE1VOm4bPj+07+S40RzKPtjmmn6/n4BioNkUxQfVdn62poWfr2lhR7MVnd7AqqIgu5stDB2cwLSRCdw3fyj3zBuCwxZGQ1Upe1f+jyEpkYzLSqVy31o+X/wyfkesBI5CdCFHRAIDR0wM/a3qdEy/+nYsQR13ZM7DVxtoM0xGUaDZ7aex5ViPm0HhA+gXdmxNcJvRijNoDQWORx08lMuwQeOJqXdx04QY9hY3s9/Rn78URfDY8lp+/2klLS12XlhykEdf3sX33s7nyfcLiI9xhgLH0LkK66lvhGBAQ8HPpo/eIEyrY/LIQURo9axb/H+U1zWgmNqvhy2EOHsdvnn8xS9+wc6dO1m3bh0ul4v777+f6upqNE1j06ZNeL3eTr99fPzxx1m7di2apvHvf/+b0tJS4uLi0OlaH2J0Oh2xsbGUlpaiaVq3bouMjOz0hxYV1f6t4YnExLRv8Yq0Geg/eAx/eDePqyfNJ3NoAwR96KxRFOdtAMDd0sze9Z8Qqxipe/F1FL0e4/fupGKQiWFxmZ3O57l2ovKc706nTK6AhqrAV4ecWi2GXvPZ9JZ8nEu9vUydrQ+g+8oSg4PvRNxFvacRi8GMzWhtsz0ycgQ3PvgkddXlWKx2jE0eil59i6e+/gBqaTUkDSbgq6fonYWk3/0NSEgnefw3afC30M+ZSqWxEJerbaOJwWCgrDbAgfw6AkENfyDAmyty+eGNQzAZVX716h6+dslAfrxgQpvjGit1uJob2bNuWShNVXXo7OFE9aLvvrf9f9jb8gOSJzi9+qDnOZh59W0MmzATt6uZ8Kg4ouKS8Ho8hFdFUF5Zil6ncNnIJKalRmIOaLgMKnGO1t88LRiE0hq+OehqanCBXke/yFRclU3trqTX6/HkF1L95ltkDB3Od268h5eX5VBc2dol/nBJA396ey+/uGUQj796gNpGD5W1LvyB9o3migJ2m5GYGAcet4tAwE9e9lbysrced0EjtrgUnCZLl3163aU33ldno6+V50LUYfB48OBBxo0bh8Fg4PPPP6eqqoro6Gi++c1v8re//Y0lS5Z0Onh8+umnAVi0aBHPPvssDz/88NnlvodUVzd1OGlNTIyDyspGFAXc7iYaGuowmy3E6YKokVZuHd6AqyQHXVIW20vNrNqVx/fmpKPqthAVnwyahq6yDgDN78ewMZsj0UYS9Ek9MmHO0fL0JadbJote4appA3h/9eFQ2shB0UTYjL3is5Hv6OyvdSY6Ux8cPX/3fz8GWgjQQvvrqgYHsUYX1as34Wpqov/td1H7RTH+xi/fKqgqaXfcT8n7b1M0OIYjObsAqEnPYtLkS1i5YtWXu6lER0cTHxtNzc41XBbXgHPsCJbt8bEnr4FN+yq4b5KBoQMiOVRUT21tM37/sWlUrc5YbI4ImhuPdaMdOmEmmjm61/z/fLLvTlFau7PrFKVb16Xsjfd6X8tTV9cHvYWqaERFJ9C0/yA1KxbTHBuLY/QYiI7A7NrJE9cPwVnsJbixGAArrevHVmnNNDc38MHLfyIYaJ351OaMpN/tD2OzOYmOjqaqqgpVVdE0jfGDB9P49rs4xo1GHTeM8r1LuHpQBIwbyEvLy3F7A1TWuagszOPn18bx8CsFTMwIY4Bawuxx8SzbUhbK82UTUrEa1NB3O2r6FXz29j+PlUmnJ3HgCGoa/EAjqgo+Vx0Bvx+TLQytF03EpRCgsaqQI/u2YrE5Sc0Yiem4Xhe98b46G+dzeSToPabD4LG2tpb4+HgAtmzZgqIofO1rX+POO+/k4MGDLFmy5LQveu211/LEE08QHx9PeXk5gUAAnU5HIBCgoqKChIQENE3r1m1dpaGhisWL3yfwZevZ7Vdfycb3/kVzw5ddZQ9sY/TUK5l8wziGpVgYG+/AX1OK3h5FwG+iZukytEAApcVFmMnRpxbO1uvV1hnbAufJfPwazJmYyuB+EeQU1pIa52RQchhGndLTOROi8zQ/taWH0NXUUfHCS+jsNhLu/Caq0Ym1HzQeqETzBSGo4S4Ca0oqBr0/dHhx7j6GTb2cK+bNJtzbhL6pAl94Eotf/jN+35dd1bI3M+eyBTS5Hdw8No3m3GoeHhiOkhZBMBBEr1cJBjWCQQ3V6GD27d/h8J6NVBQeIWP0JGKSB6Npvfe+UhQorXXz3he5lFe3cNmEVMZmxmDWy7py4vygKAqu+hKyN69kkCmG0v+8Ftpm/uJzkn7yM+zDJhDvh+odRRz/K123uZxYp4Wm+pJQ4AjQ3FBDReFBEgdNYM6cK1DritGqC1BVPQG3RqEGvtEZrP/i2JqMZutabpt1Jy9+UoJep2IJtmAvzWV81lDun5KC/3A1N0QYueGeZLaV1xLr1JGYENtmzFV0Uiazb3mQfVtXYbE5GTbxIgy2uNYALOgjb+8GNn22iIDfR2JaJlOuuBWdOaLrPtzTUFuWy7LXnw/9vWvdJ8z7+o8w2mJ6MFdCnFqHwaPdbic/Px+ADRtau1WOGzcOALfbjdncfnbQr2pubqahoSEUpK1YsYKwsDCioqLIyspi6dKlXHPNNSxdupSsrKxQF9Lu3nbu+fn881UYDAYmjxiMXa/R0FB1LHD8Us6mT5k3Jwvv/k00bDy2Nps5bTQDH3qAg39+HqaMJsEW3yfGAOnwo6/Lo2X3SlSDCcuwWXjsKWj03ofFo0x6lczkMLJSw8+r1mUAVYWg342iM6Jp8pB7oaqvOMKapa8yJXYYpkGDSLz9AVrWFVO+5SCGMDNR09KoWV9A0O0n4AoQOXECKz/8d5tzuBvrSQozUbf0Tyg6PTXD5x0LHL9UvHMF37/yPlwfHflySZsG2FNB3BX9KXrvVUzR0URMm0YwNhGDJYqsiVcydLJCRITtrFumFQJ4W+oIBPxY7BFoivGszvdVVY1envz3BnxfvkF9cclemt0ZzB4nE/yI84OnuZIPXv4DWUMnUL30WJdx09BhRNz8DVzrK/Hn1+Ey6ggbnYCrqAF3cUPrTkENf30dEf5GTGYrHvexMYktTfUoioK1uYzKd38NwdaGc50tjOT7vsEHn/y3TT7cLc2Eqa1rAN15eX/CGz8j4Grg3qnzqP3w0LHlsPZWM2lmDOWfvIvp0kshdRDBo+O2VQPhCRlMv3YwmgaRkcfqkMbaYtYvezt0vZK8A+ze8CmjL/raGTdQKQoEfM14musxWezozWFn9Dyg4Gfb521fwPi8HsoLDpI6JEbqEtFrdRg8jhkzhs8++4yJEyfS0NCAw+Fg/PjxAOzbt4+kpKQOzgAul4uHH34Yl8uFqqqEhYXx97//HUVR+PnPf86jjz7KCy+8gNPp5Jlnngkd193bzjktwLDMdBwGDZO7DjV3Iy39xrfbLRgMYnCqNH7xbpt0d952nGOvx/rzZ2lUDdg8DgwGD/7ystZurbHx+A0dB++9jb4ml6r//Sb0d9PuVcTc8gvc9pSey9RpOt8Cx4Cnnv071nBo90ai4pIZM+sqzM4E+XHqQ1p8AcprXOhUhbhICyZdawOBLuBDq64g6PZgjIslZ8d6VJ0eFZWoG++iZVUBgS8nwPDVu6lZl0/YiHhqNxdjy3CCsRqv+9j4RkVRiIlNwrPxLQj6QW9oHfv0FZoWwNropuH4/8c0aMqpxVNWRu3GTVQs/4zMXz5FIDIu9CbybGkBN/u2LGf3uk/RNI341HSmzVtwTt80FFY0hQLHo97/4jAzRiRiNkjDjOhddAEvWmU5QZ8PfWwcfpON+soS/D4vJrMFzXdsAhzDlddjLHbhyq8DIOgNULuxiKjp/ULBozHKjL92L9QXEpWQTMmRnNDx8akZqMEWGta/EwocAQLN9aiGIFqw/RjGKIeO394YiTNYiM6lwzbxaur31LRdR1kDd7EXV1Ep+3/1WzIeexTSB7c5j9/fvh6qryxtl5aXvY2R0+ah6K3ttnVEUaC5ppDlb/8DV1MDBpOZWdfeRVRy1hkEoxoBX/vlvgJ+WQJM9G4dBo8//vGPKSgoICcnB6vVylNPPYXRaGTr1q3k5uby9a9/vcOLREdH89Zbb51wW3p6Om+//Xav2Hau1ZblsfmDhQS/rCzHTJxBP4sJs82Bu/lYy/qICRdjVnU0H9f9A0AbNIPXtjWzfGtrxWwx6fnR3FS8f/4Vmt+PPWMQqQ98C7+jd3S/6Ay9TqNpywdtE7Ug7twtqKNTz7ug7HygEGT754vJ3bMZgOaGOkrzD3H1Nx5D30u67oizU9vi4zcvb6aq3g3A4H4RPHT9cJx4qXx/ERXLPgHAGBnJ8PvuYn9EP1zmGAwBfShwPCroCWCIMRM5IwzNXYTBEsO8m+5BV1+OTtGwxKeTn7ef6MbWmYc1r4sYpx1Vp2/ThW3wmKkE9e0fFINBDefEcbTkFxD0eHDlHsIY2X66f4CgplFR76G0uhmHzUhKtA1TB11D6yoL2LX2k9DfZQW57N/6OcOmXXvOGksMJ8iDxaRHVXt/7wnRt+lUUAni11qHhehcjZS/8To169YDYE5IYMAj30enb3380+KzsFxmwPe/NzEnxJMSn0TtjoPtzquh4RxtB9yYo/XUrdqCbfhM0gwxVJcWYTRbmHj5DTiiUqgvO4C+qbbdOQyuKoZPncvmT/93LM1oRtM0Vr7/EnqDkdlz52Pyugn42t9jmqJi6ZeKq6iY0sWLSfl+Jv4OAjZbWNvfuMiE/qSMu4od+S6ctgDJnahTjhf0NYcCRwCfx81n//sX8+/9GXrLafZiUwyMnD6Xle+8GEpSVR3x/TKkYVf0ah0GjykpKSxevJj6+npsNhv6LyuckSNHsm3bNkwmWbT+RBpqq/ji/f+EAkeAbRu/IOnaW7jimgcob2nA5W7G7mlGl5PPkc9fJOWar1O/+qXQ/pVxE1i+uDj0t8vj5z/ry/nm1Bk0fb6CppyDNG7djPWi2efXWEjtBGMcz6f8n2d87npy925pm+Z101BTTmSiBI/nO0VR+HRTQShwBNifX8ue7MOMN1SHAkcAb00N9ctWYLl8Pn9fWcJj16XhP24KYV2CHQaGU19+mKIXnkfzejFGRjLgnhupX/smPi2IW1FJnPcwumEX4S3/v9bjjmzl4uvu5PDe7XhczSQPHErR4X0YMkxYDTY033FvIOKDuGqOa/E/ya2vKAp782r505vbQ2ljs6K5fnYiERYbJq39LIqKolBdmt8uPf/AToZOngvqufm9So2zE+U0U91w7DO/Y+5gTHpFqjLRIxQFTM2ltOz8BF9lPtZhs9CljsGVeygUOAK4S0upWraMyOuupd/g0azY04JdiWPWbV8n1mnHnV2BMdyC23Wsgds4MIImi4e6dWtpXvMFqsFA/3tuxpw1nDRTFP0GjUJTda33V9DDps8/YuaI6fhWv9Emj03OdDbnNTHkolupPbwZkzMGS9Ioaj2tjU5+n5e16z/n0kmTsA+bgPtIfZvj/TF+1GB/WLuezgqLSaFf5kjyD+zE5gjHlnUVz75TABQAMHFYHAvmDsKi61zXdndLQyhwPCoYCNDUUEP4aQaPmgaxKVlceuN97N24gv/P3nnHyVHcefvp7sl5Znc25yCtslY5R5QlkMjJRIPB2DjeObw++3y2z+dwTocD2Bgbg8lRQgEFlFBAOazCanPOk/NM9/vHiF2WFRhsIQs8zz/6qLq6qrpnpra+Vb+gN1kYPXUhOkvWh2onRYpLzQfebrFarf3CEZJhlw0GQ3/aixSDiYQChIOBIeUxnYNjXRI/3+DiV6+HOOnNJJpQE6ipwVvTg3nCCkSdEW3+KHzqoTk0GzsDkDNg3uk5egzVxyhIQzwhYJq0anChIKIrm5Q6dfyIEEUVavXQP4wq1eUTcS7F34+MwumGoblq67sixIPRIeX+02cxazS09IY46w5hn5IHQGJqLs9HInz1xRP89GAY8TNfQWW3Ee3ro+XlzehKkr7uKDKRfS+gzS7HOvVKJJMdKS2HI7s24XV1oygKB7a9SvO5Kro7mjDMdaAtMKMtNKOdZWXfWy8RVZKLRVGrRV9WesHnCkbjPLq2alDZodM9nG7u5LdH/kyIoekAFEXB7swZUp5VWI4oXbzvu1mr4lt3Tuaeq0azek4J375rKqML7SnhmOKfhjbSS+9z3yNw4g2iHXX49r+C6G4kVF87pK73+AlUqJm06Ho6XFG2VLn4wVGBHmsxgepeTBVOhPPrivjUXJ7xBPjiE2d4NF6BdP9XEbVa6h97hoQrSuxgG/6NrcinvGiiCoIgIYkS3So7ptm3IJlsqOzZ2ObdhV/Ws+lgF7/ZFuGgPIcNLaX84tU2vOGBH467uwPZ7KTVdRbtTCvaAjO6QjPaWRb27n+xf+7IWrXqb546AogqI1OX3sKK27/C3Bu/RJcLhuVZ+6/vP9nJydY2okL4fVoZQKMzonl3+g9BQG+yfKD7hw5QQ1reKOZf9zmmLb8dvS0PPgbxH1L8a/PxUR0fM4xmOxZ7xqAyQZLojtv4zfrTuHwRAuE4T+1tp6loPJLRgPvYMUK5lWgXf57E8EXYDUOFeWV5OhmVo1HfdyPmNUuxTZl8QTv/y5l4Whnp130T/bCpGEfPxXnjd4h8jPwdP25IWjOTr1gzqCwzvwRz2tBFdoqPH5IgMH3M0IjRo4ttSNqhc4iuYiSCMZk8+0/rTyGY1NiWlPJkVTu7qjqIxWXqO/z8ZHM76lXXA+A/V4s4Yg7+hTciVC5AlVZA+9qtoLZhqJiOqXQKJRXj6Wlvpq2hut98NSe3mGMnN/NW32u81fsaa1/9Od0djZjNNjKWLmb4d76NnHbhaNfRuII3MFT8xmMi5/rqaPA1XfA+e2YRhRXj+v9vtNgZM30x8kUOEmXVq5kxMoPVs4opyjAipUxWU/wTSfQ2I0eSgWs0WcWYxy2gZ/1v0KYZh9TVjh6HJyGh1pi4YnLyb28oEqfNH0YQBVz7m7FPzsW6uJQnT7Sy63g78URyXvjx5g5Uq64jEQgSau0j0OsnMFKiy+DFc66dkBxm0orrObL7dRQxl4R+MpFYOY3PbEXn7iXLYSASS3CytpemTh+iKGBUDfzO84rL8QVD9HW3seWNP3Kgbz37e9ax9tVf4Optx2xLZ9j/+yZSSfkHfjeCpCPNWoCxIcYib4IHCp38vzVj0ZwXyO5AkPZQx99oJYlaZ2XemjsRpeRhiiAIzFx2I1pD2gcez4VIyAIXSGmZIsVlyd80W03x96FV6Zm78Ba2b3kcn7sXrc7A/NW3semsZ0jdN2pD3DlyNPqMNGS3h+Y/PE7M48EwvpJPL7+Gx1+vIRqXKcw0c+O4PMJH+tib7eFMWj2fnzAb3SXc7tYoEcSYH1ltJCr8fcF6Ekgk7MPQXZGMjBb+uKTq+JiiKJA/bDLL07PpaWvAZEsnLasIQfr4J09OkfQhnDE6i9oWDwdOdyIKsHxSJiVSB/GOo2Qtu4KOjVtBUdBkZeObvoiXNtbwwLWj+eumc8T0atx9QY6e6x7UbjQu06syYwAM5aW86DrB9s4j5JgyeGDyDXR94TsE64vJu24Np3/4a2yL5lFUNoqGmioEUWTM5PnIbx1n/OIF7Nz8PN3tTUgqNUvW3IUFHcpEB4LpvdMPmfUqKoc7OXJ2YFwqSUBlSJ4QdAV6GWkZavEuqo1MW/opxk5fQiIew2RzIqg/msTtisLHy2UgxScWQRpYzhkrpuPa/tdkebSd9Hlz6Nm+EwBdYRFtxeN59amj/L/bJzGxIgOPP8Kru+rZcKKNb88fTu+2Ovr2NhOdlM2x2t5B/bw9L5gNBrCZ2Gw4zLb6vSgojEuvYGVwIS/UbuTem+6i46E/4z9zFlN5GfZJE+j83W/4zB2f5Tf7FbpdIYw6FZ9eUUbH/mSakLSsPCbNXcXLf/45BqOZectvZsfGpwl43eTklzFjxnJi3hBxgwnNh9isUSPg2d1I+HwQINxhMjoD3Dy7lCd21iLpQ3gjCfgASxpZVrDnDGf1vd8i6HWhN1nQGtNQUmcxKf6FSInHjwg5liD2ZoD5424joY+jtxtQaUSchtCQupkmCXVCjXPGDM79+CfEPEl7+uDRI+T1dPPje7+Mvy+OyR9F3ttCXFaoHFbBmx2H+N3Rp/j61M+jVj5631NdoAX3648Q625CnZ6PbfG9RMz5f7ep1sftxPRjjajGnF6MxVmcMq37BGLSqvjMVaO4fmE5qlAP5o5DRA69SdjVgXbmbcQL/w0lHOFsWMPare3EEwoTR5v55mfK2dtzgOEZozDoVATDg4N26YQEaqsV+ZqF7Gp+FYA2fxdPnNvA1dMmkj11OrW/+T0xj4ee516mcMJ4yicvx1w2ErFbpO3cw7iDG5iUV0YsdxQWZxY9z79Ge9UpADQOO2Vf/zrxtwPmKAm625rwuvowWBzcvmwEWrWK/VXtZDkMrFzkZEN7Mvhasa3gvb/LogaDPe8jedcpUlyOCI58JKuThKcbJRbpLw9V7yS68BtEyiYjygmOeyU2bu9AVqC1s4f6MwcZX1HBvM9PI5rw0ZHowbwqGyUCaoMRvVZFKPKueUFUyL/3Pup0PrbW7ekvP9ZzhpK0QrqDfRzvq6ZAnTQVd0ydQtMTSTEr//6XfGHhEuITSzGowFB3mGGTFhDs6kIKhGmpPokkqZg8aSGuPzzJFVdfiVCYT6yqhtrv/jfIMogi+ffcg3HKdN7t7SII4O7pxNvdgUZnQGdKR4wIA8LxPIlAlHKbnruuz2dd69M8mHf3h3nbqPUOrOd9HFN/UlP8q5ESjx8RkkGDsdSO/2QPlrEmmv/vl0S6uhj3Xz9irUmL25+c3LVqiRUTs1C/qaFz4ya0Tifm2bOIF+STQEHv9WNobUI+JQwk6RUgTtK+ocPfhS/uxyElxaN4fvPrApHz/yHinm76Xv4JiUDy5DTW00zvSz/GcdP3iaisf+PuFJcLKeH4yUUE0kwaVMZ0VLox4G4j7uog3lHN2g4LZ5uTm1KiKDCvMpulo/LxdrmYlRhOvLqWT83M5uGtzf3tTRyeTm6xg/g3P8/3q/5MQpEptxUxO2MyYlTBvCYXuauPmGfAmsJ7+CgcPor57gdRBBvaomKkipFEq0/j2rMH/eor8Z0XjgDRPhddG9bjvOUOEiRoOr0vmZNNUZBUKhbdcD/3XjmSGxYXc6qvimfP/hEBgVvHXE2OPie1akuR4jwRlRX7mq8TbzyGpBtsVRIL+fn59sFWTxaDGrtJQ87EqaiCClJfCJNaoOWJ52lrbEa/cCYtozK47YpSHn6tpv++ycPTySnJpj4mcCK4a1CbC/NnkkM695bchFv0kLl8IZ6TVciRATErRyL41yc3otKvu4aW514g58pVeLbvwDR+HPnTV+PUO+l7+nmi3d10v7SW7Hvvo+nxxwcWNrJMy6OPMry8HGyDY0MEXS1sfPL/iEaSG/XjZi5h3PglSTfCd80XeluMtTVPcdOY1TjVztR8kiLFByQlHj8iRJWIeVIu8XwN3eE+NNetwdzThzsu8583j6Sh3UfUFyAz4SX0i//G5/Wizcwk65Yb2FZfT/fJEwDodDquWjQeTg3kKpLGWNnSnUx3YdVZMKj0CMi43T0cPnyIRCLB+PETSEvLRBAuTkCjmKe7Xzi+jRzyofh7wZYSjylSXC7EBQ1xcxHmyqWEGquQ6w9w09z5fL/NR066kRvmZJCj0+BZV0/CE8UNSCYjlRUJvjnPQZ89k4jop02u5uunnuDWsWuIxKPcNHwVxUIOAX8AQRDYuGUbU8aNw1BWQrCmbmAAoohkMCHmpPNccyU1BwJMLp/Gos9MIHr66JDx+k+fJSMeJRJys3fjQEqnRCLBsd0bmbsmF6vGwLScSkZnlSIJKoyYUhshKVK8i4gmDWHYAlRKGOPoeQRObgfA3nWIKybNYcvBNgCmjUxn0TgjHQ115HvsBGrcAAiSQPbia6j59Y/xvbSBPGE58XHpfHN+Gj2yBofTSkGmgbgoc7J9N1bjQJCYFUXzEeuiHGzbD4BGo6FkwSxGfOcbBDR69BlO1IqCeK4W9+Yt6HNziPT0AOA5cYL0zz7Ic2cinPjLacYW21h63aeIPfIrTGNGEvH6UOLvSmUWjxP3ehHfIR4FJcKudX/pF44Ax97cRNmYqVgn5OA51NZfrsu3oM6w8h/ZX8KAKRWwL0WKD0FKPH6E9IbdvPzGWuLnJ71MZwbD9SJGQWBkuIeGvzxMVJJIBJNO7o4pk/HabHT3DvgYhMNhjlafZtaVU4i0+YmlCaxz7aKmvRG1qOIz42/GIKtwebp45dVX++9ra2tjxYqVpF0gKIogyMTjUURRhSAM/QoIgjDEj0fSGUEQB6fZEERE3VBn/BQpUnz0CEqUkN+FSq1BrbchCCLxsIdoJIjOYCViyiZt8aeJ9TRjl9r575tLQK9n+7bXKRo2j4hnIEhFwh9D9Jsx7Hiexmsm8GLTdjSSGqPawOmeGh4YfxsNb1Wztes0kIy2PXv2bHbu3Mk1t95C8/f+GyWRAEGg4JZbUOdn8P9ePkNLVzIi6pYj7bQV2vjimDF0bX1j0HPYp01F1mgJ9gyEv7dnF5MxdjlHG6N0725n1rhcbJKbpuP7iEejlI6dismeBxdpcyxFik8KigIRdGim34R+9DyUcADBmsmqsMKITIWIrCbLJrNzx1aumrGMyKGBSM1KQsF3JkLGvIV0bHyN8Bt7sI0dQej3P8cBlD3471Av0Tcswram3awYtoBSRyF1ribyxAyOth3qbysajXL4bD1jR4zi1Y3rkc+fGhZkZTFq5XJsWVk0Pv4EALr8fP56MsRbZ5L+zbtPdlHXbuCr99yP1q5GZU1H0utJhAZEoWQ0oLIakeVIfwqeeDSEqyu50Z6RV0zJiErE9OFsOu4jw6Rn4uJS6PajsWkR0tUc3fM6iXisfz5J+S2mSPHBSInHj4hYLMa+fXv6hSNAZ3cXFZEg7WEtBRYbuddcTdznRWO346tvIG32bA63DY0g2NXVRWyqBrXDjtgTYIZhDGNLy7AnTGg2hghP6+Js09CkvseOHWXRolwSiQEhGI8H2bdvD3V1dVitVubPX4DV6kRRQJMIQE8dsZ5GNOmFkF5CVEqKQ7UjB8ucG/DuGMjbZJl1PTHd0HQiKVKk+GiJh/vY9cqf6GptQJRUTJ5/JWnZ+Wx59hGikRAmq4OF192LMWMEos6MT1BIjwVocPuZOXMmYs3QsH5xPxTecRsHw8f5UvFq0tsDxP1+/KShjmro7hoIXBOPx6muriYvLw9vTw95111DIqeAXn0aHaKEJgYdvYNTFZ1qdBNbMo7sVctpf20jyDLWsaNJmzODqJyMiiqIIoIgkD52Jb9aO2BCu2l/M19Yns7JfdsAOHN4N8tv+xLm9OKP6A2nSPHxJi5oiVuKwAIICkGhBV1+jHy9lX2bk36KqoRA7F33JbxR9MVZZC1fhmXMKGI6G/K3voFdoyHR3EGkqwa7rpBxtlJeq97G7MIpTMkdh8o9VHiZLRZ27H2zXzgCNHV0MHLxMs7W92G94XaUnZuwzJvPW39tGHRvW28QX+YY7GmgVaKUfuGz1P3m98S9XtRWCzn33M1LT/8qGVjnmntQ69NQaY1k5pdgsacjqdR4EwYeebaGDJuW8QUGHjrdxpxyK9aHfoyuuIB4sYMzpw5y+vBuVtz2JUxpRRf1M0iR4pNKSjx+RESjUfr6huZei4YDlJpVnPvJT/tPHAVJYthXHsCz5WfkzP40h991T3l5OUoiQu3x/WS056HvDpL0aPAm/SBdoFYP/Sg1msG5/QRBZteuHTQ3JxdlHo+HV199heuvvxGDRkv4recInNjeX984dgGaaTcRR403HuI1TYRRS2/DGIkQ1GppNtkYJUqQinuTIsUlQxQUju1eT1drAwByIs7+LS8ybfE1/eZafk8f257/A7NvvQ/FakE6vpOIz4tLV0b1gYNcO2U51LkHtasrMvPmobVcOWEO9T/5P7re9mUUBLK/8kUkSSLxjljybreb8vJybKXleMvDVPd46O72sGV3FyaDmpsWV/CXDaf760uiQDAcxySeo/wz16By5BLrOEm86QDCmJVoDWksuPpuzp08xNYTvkFjiydkantE9CZLf4LuE3s3M+uqey+6f3eKFJ802qOtNAc62HhuO4XmHDJVRvR6PQaHnnfHf9dlG1AXG2nX+jl2YjuOnCIK8obT/PtHiTS39Ne78vbraNL3sKvxLQAeHHHbkH6zs7M5fvz4kHJXIMjPdvSikgS+ctuD+LQXjpwqxuOEm2rw7ngUUWei+OYrUGePoqm7jQ3bniISDhIO+Ni/6Rlmr74XBTUzlt9Me8Np9r3+Inlzx3PvfJliz1uIzUdRnKW4zYuQZs7Bu/Zl8ipv4QyAolC1fyszVn160GZ7ihQpLkzqjP4jIoGK0rJhQ8qdznTcxw73C0cAJZGgc/MONNnD0J/ZyrRJE5CkpDlWcXExGZkZuDua6GytB9XQSVaOx0m3mvrvgaTp6bhxlYMmwkgk1C8c+++VZTweN1Kga5BwBAgc34YUTJ42NHnaeK1+Nz+u2ch3mt/gRzUbefj483jloalHUqRI8dGRiAVpPDt0QRaNhBDEgSldUqtwezuRfb0oBzYQcg6n6tRprpo3A41Sj3mUGUQBBDCNTqe64yBqSSRSfW5QEBwUhZ6XXqE0f3Au1uLiYopKizgeqeX7Bx/iydo/si/yHLdcm4k3EMPtCfB/N2fw4NJMrCYNayZlEPH5idny8B96Dve2h1Bb7fhPvIFaDqEg4Cwcw6yVN19QECYUBVEYeD45EUdIRbhIkWIIkghqUUYQQJYSNPvaePr4K3T6uznaeYrKaZVcPWcS0YOP4ZhhRTyfD1abacQyJZO3jm1n/5sbaGuo5uSe15FbWwYJR4DA8+tZ4ZyMRWumMnsUTruTSZMmoVIlN7ILCgqQJImy8rIh4xNMCa5ZkkM8ofDrl0+j1Yj89vY8vr9Mx7+vyKAgQ8+iMemIAS8dUQOCRo8qp5xI+0mCx1+gva2GSHhgDdVad4ZENPl/nTmTgNcNQF66ntKGF1FOv0HC70KuP4h9329JH1GQHEdk4Nw1kUqymCLFByZ18vgRcfBUJ33xNIYNG865c9VoNBpmTppOTBsj5nENqR/z+ogzGn2aQFHbbmwLrsTt89PS0kJVVRWlmVaaak8wbuVCGIidg6AWCWn9HNn2ArPmrcbtDyNpdBQXl2Iy2QcFlVCpVOh0OsLh8KC+NRotSsJ/4QeJJyfXaOLdxi0Ql+Mk5ERqC+JjjKSA5IuS8ESQjGoUm45Y6vO8rBFVWjJyi2itOzOoXK3RocgyoiSxcNGVmNxNKG++iHbYJKTpq+lW6Vkzbjzuv76EG8hcMJ30mUbkcIiwRebIsxu4YslVJJqGWkzEfT5GD6+gsb2daDTKsGHDKCoppiHezp+OPodyXsR5Iz7Wt7zI3ClXcbLWzdLYAcqajvLza79EV52b187EuTbrvJ90Ig6KjMqRjSJqQEn6aznS07hqTik/fmLAf0oUBcozBKoOu/vLxkxbREL+4LneUqT4pCMIAlp/M4HD64m7OzGMW4iUP5pwPEIkEaXQlMWtxskoT7xAVziCc84kok3rsI4Yhqi1ErEbOdN0kMbqwZtTiUh4SF+JUIiZ2mIqnRn0RfxoXH60oprKykokSaK9vZ233nqL6fNmEI1GaWxoRK/XM3LKGF5u3sII+2hsZi1uXwS/uxfD5v/GDJgFkf+84l562nzsbIaZI8x4x1/F2erTmExZjCwfQVYgSM2ZY/1jcWTkIqm1KCTzMDpzCkFRyFL7iXYMdulJBNyIvi4QRWKGgRRno6cuTJ06pkjxAUmJx48CUWD93gbaewL877UTGGsvg5iCCTUbWw9QMbIYNm0fdItj0kSan3kBSa+j9J6riQY8dLS20draRuXMiVhsDoZNW0F7zEXWHBtCt4LaoEGTo+Ol539ByO9l37rHmbb4OorHVCIr0pBohJKkY+7c+WzatKG/rLS0FIvFhqAYUTmyifcNKFN1Wh6KyQlArjkLk8aIPzrgx1SZNQqLypoyW/2YIooCSq2brp0N/WXGcgeG6fnEUmvyyxYFFZMXXk1P2y/6d99LR0/GZEvmHJs0bR66468R8SYjGUY769GVTyKtoJizv/x5fzveqlOU3X8bgcNPoJ1xbbJuLIojy5HM+fOO47/MRQvo+f2jrLzpeqR0J15PkCZ3K706X79wfJveoAtbFkwt0aE0n0OJRYjsf5aGgpspcEaRGvajKa1E1JkRVGosM64jrAwOfFOeY+Ebt09i075GDDo1S6YW4lC5CY+eRCwaYdSU+VicRRf93aZI8XFGG2yn55n/Qokng2FF22vRzb6OOeXzKCvJIkNOUPfDH/XnbPKdOUvJvbfgPfhMcjNn5s0IytAgVBGdClGrHZRyI33GNFqefBp/TS32RfM5rjpGxaR5bDtQRfC8ZdWS5UtZ2/wG2aVOSotH4o8H+EvLq/gifrRqDQWZ05BEAX33yYHOFBn/jj8Tnv1VqmpdTMjuZv+29QAkMnNpaG6kZOzU/upqjZaZK29BEQaEYF7pCLILh+Hra0f77kB/AIJE6Ze/wJmeWgqHj2XklAVYnYUpO4YUKT4gKfH4ESAC6TY95RlmQvtaiXuTE660PJN8OYsX+vZw04N3El+3AyUSJm3mDPx19cjhMM45UxHkMOknNpFutDNz0RK6zWkcbRR4Zq+GhOxh1WwrY3OiOIMN+Da9xqKZVxASNJjyKtCYncgXmPwBFEUhKyuPa6+9Ho/Hg06nw2ZzIAhqIoIa+6ovEzyynnD9cXTF4zBMWEZYNACQZXbytRmfZe25zdS6GpmaW8nc/BmIcira4ccVdUSma8/gAE2Bc30Yx2SCWfMed6W4HNBZslh19zfwu7tRa3Vo9QYObHmZqYvWUGAzEjjWM6i+7Ouj+43tQ9rpO1SFObsYjS0TgKqTR8kYP46y+2+jY/Nu4l4fGQtmI2o1BBsaCf7of3F+/h4szhLcogEvQ08kbDoLJpWOClMdCV/yFDPa3cTYuSaUliosk1cQOL2HuKcHXX4FCWPGkDYkUaA820LFdeNAUc6fCOiZuux2BAHi8dQyL0WKd5Pobe4Xjm8TPbgRtTIaa7WMP3R4SLLfnjcPkzZiBOGWU9jS86k/e4rikROoPzUQfaGmrYbJX/kC7vWbiLS2YZ84AUGtomd3MvCOa/MblN1zK4ff3MCs2avZtW8vpcNHY9Fa6Qr04jSm8ddzrw7qt8BYwumwzBeuKkV8/fFBwk2JhpCI8aWV+Wx77iUEUWTh4isx9dYhtx9DU5PgU/d8mZ5AGKMtC5XePihCvMWezpw1nybi70MzZSX+/QN960snYRgzlYjGwlhxfPK9Jd69BZYiRYr3IyUePwJkWeGq2SVs29s44KMoCqDoKBLtpJkc/E/X63zljmsxbjlE+2sbSAQCaJ1OzAUG3Dv/mrynt5VYyxnSr/42P3i9Aa1GRZ83zHNb67GsHobj7G4Svh7EQ+vIufprhE0DaTkEIdnvu1NuKIqAwWDDYLANGXdY60Q9/TZ0U8MkJB3hd5mEOUQnt4+4iRhRNGiHbOal+JiRkFHiQz9EJZr6YC93FAUkrRVrphVRFKg5spXGs0dpPHsU54o1AAgaA4bh01ESAkqoB0mnG9KOqFGjyx8DlmymLr+ZjrpTdKks5DqtFNywGGQV3rP1NP31+eQNsowSDmPQGzAltHR7znFVxWJePbsZRVHQqrTcPe5Gsg9tJ35mZ38/2pLxCPW1mLIy6Fn7M97Oxt278REcy+5HKJh6wbyNiXd9P1NmZSlSvA/9Ps8C2sIxqEwZxH3tyGE5adKuHbopKGjUKHIc86Sr6Vy3ndjUpfSIIUbNLcXfWU1WfjnGrFLaohLi0kVkqDW4nn6GwLnawe1EosRjEdLjCRaVjaDFXMCZjjjz82fQHemhzFFETV8DAAXWXCbYyygsrkbncqMkBudwlKxOLFkOervCSCo14ybORF+1hagrmacx7u4k1lZD+uqvExX0Q9Y5yXehQ2vJQT1mOWm5I4l3N6Cy54CzmLBkBuXt+SRBKORHFEV0OhOKkjK7SZHib5ESjx8Rw/OtOGIm1CEdvZubkPQq5LCPwKZNLDLrWLrsdogGUVlNJAJJU9D0GRMJnds9uCE5jtrVyDeGB8HvIzppGE+dDvPm0W6m3PggVlcXgjmDiNoKCggoaP0tRBuPg6hCWziGsGForsf3IqEIJAT9e5uiygJqtKlduk8Ask5Cm20m0j4Q2VLUSIjW1KnjxwlRFOhtT54gm+zpWIpGoSh3EXYl8DY0o8/JQnIUk1aSQffOXQPmqKJI2swZdGx6nVjMQEQSKRo7HUGfxv9ubWXVuCzE3/+MuNvd35dkNKLLyedYV4TNB+r57LxSRH8rkybeiSseIdTZQ8/2beQV5JBQ61BiYdQ5w1BPWMHRNjXjuw/Bu2YP34F1mAsqiZH63qVI8feiKAnilkxU9iz0I5bTuWUfweYDOKZPwZILcV8U64QxdKo3ocTOxzAQBLKumE+0p53ml3YT7XPhKpvL83s7MOhU5KRXMrcolz/+sQq9VsVPry1AqTmDqaSU9Bkz6H5jO8GmZgSVirhOzfhpi+jZtpODhdN5cVPSJ/HLq/O5Qh9gdto43KULiCoiPSeOse/xX4Ki0G61s3je7UT3Pocc9CLZszEsvJed3jpOHjdx1ZxlGMJuEqfbBj1vrLsRwd8F5sL3fS8xUQfpFQjOCqLvWrjE4yF27NhGa2srAKNHj2b8+EmIYmouSpHi/UiJx4+IzrpqNr/8GDOW3oD2yiz0cYXan/yY6NvpO7btJmflYuyTKzGPHEUAAdliQuPJIXHgBRKBgWiHij+A/4Wnz//vNW6/53Ns8WuJCgJqe/n5Ssl/tL4mup/+br+Nv7D3BdJv+A5hY+4levIUHxdigH1+Eb6DbQTrXGicRuyzCoioxXev71NcxsTjMkUjJ9Bad4ZZy28k2N1Fz0vbCdTW9dfJWroYOVeh4hvfoG//PlAUDPl5NDz2FwxlpcQ1akKhBH3dAn/aeopYXGbNOBvOz3yWnj8/SqSjE01GBnmfuZseSxqvbK3hgckJYut+CoChYhaq7JEk7AXU6TrZcuAQ02bdis6WS1xno9YVJy1NJNFzgUWZ1kAkGkFUpxZsKVL8PQiCQFtbE9u3v8Eti++j5rs/IhFKpu3p3LiZSFcfluHL8J2JUHb/Vwk0n0GOBNFlZNL01+cJnRdP5jnz2N+Q3MwOhuPUtLjJzzThtOm5pdJC649/PBApXhAouv1TtL+2HueN1xAvyCEQ9qJatZqXHjsBwNLKdIrqXiHYkvRpNAP68YvxxNT95rN+jwuX2kHv5C+RbxPpjWvZ1xGkSazl+gXXYRXdaMOuISlFAARJ/T7vRCEcDhCNRjAaTUiSdtB1UYSzZ0/3C0eAkydPkpdXQEZG3of+DFKk+FciJR4/AlTE2LnlRYrGT+as0s36sy9xu3EKsXfmfZRl2l7diHHyVFr1Itu370CWZTQaDYtn3IF296PIIT+SyU7ENdiHIf76WhY/cB96wThokS9JAoEjGwc5hyvxKOFz+xEnXIMspxRBisGE1SK6GfmYpuYhiwJhlJRw/BiSnlPO/KvvZPtLj7Fk1moCtXWIOh36m1bhcmhpRSDPYEUtGYksm4HX1Ym+x4+2opyOmcMwOHPoqtby9KZaxpXamTZMT5oqgC8oUrP0TkZmqpHtMj+uX0u4PcKdK9eg2/IYcUA19Tr2dMVp2ZtcIObm5jJjzT3sP+PlmRfrmT4mi5UzCqg/e5icsjJErQE58naYfQFl5AK6evvIyjL/095fihQfZxQlyt69e4jH43gb2/qF49u4Dx8ifcZSwm0JIlEjHWl6SnLziNd3EHW70eRkob3zGnosWlZLOiQcBEJxjhwLYzMnzd1zfW30vCPFGIpCz959ZH7hPurVAZ6vfpZwIsKiojnMmexkx1vdTMpJoOw9OWgsoaObGXPdt0kvHEEsEiKutvHwG33Ut3eSZtXxxRsqSVNkiizTyLBqEYRMGru6SC+fSuzc/v52NMNnIBudF/x7FYlEOHeuir1796IoCnq9npUrV6HX294xfJn6+roh97a3t5GVlZ9aL6VI8T6kxONHQDwepqO1HufCufz5aNJ/MWpRGGJJL4q4jRreeGVLv81+NBpl68GTXL3w06h7GxAthZz+n98Muk0JhUg3aocEqxEAOTwQDVUy2lASceSwH0kQSKmCFBcioSgkREh9Pz6+CCo9Ko2OcDBA0OsFQP/ZW/hV3zb87ck5IceUwadGr+ZH+x4BQBIl7r7qBh4/9gLX6Rdh87v4wZ1TaDyymYatB2kURWYsuZ6JI4vpkFz836E/9fdX6zpLZiyMqDfRLtlpaR9YILa2tmJLz2XDwWT6n7eqOsl1mkm3lXO2s43cefeic7dAPEzUXsDWkw3MmVs66HlEUUgt3lKk+IAoykCeQkEz9ARf1GqJOxSCY4McqtpET0czziuWoW7ZTOldK6kpKeR/Dz6OfH7jeUL2aNSSGkOJxHjnQiYV5sHBfUPaTQSDBAwSDx18sr/suTPruHbYGswn1YjKhXInKvQ1V9MSy+ThzT5gwG2i1xPmRF0vz26p5q7lZQyfKBCPyygqHbXmCornjED0tCNbs/GbMtELmiEBgAB6enrYs2dP//9DoRDbtm1lxYqrGFj2iuTn59PXNzg1UUZGxgeae5JhJYQL+1umSPEJ55JkdHO5XNxzzz0sWbKEVatW8bnPfa7/B3v06FGuvPJKlixZwl133UVvb2//fZf62sVCkHQMGzuV/Z0DC6r9sWYMMyYNqmdZuoBQJDJk8gmFQgRFLd6DG4l5PSjvSl7rXLEMtc4+pN94QsE4fjEqRx72K76GbsSDGMd/GePoNcgXyrqdIkWKjxxBACURxN3TiXCR8toIQlJgeUIxqhpdnG7xIGoMCKJISAOmMaPYpTQPSq3T5u+ixdfB5wpWcmPJIkRB5KUzm5hRMAlDVMDTdoZI23EaTx0EQeCK5Z/CGhYRqqsxu4PYddb+tnZ0VSGOX4jank1Tt3vI+Dy97dy4aDj/dv1ovnb9KAoyTax9swlZ1OMVDKw752ZtXYiXdx8lN68As9mGIIA2IuM62EqiqhutL4aYil2R4l8QUQA56kWJ+RHf8SMIRBOcbfVwosFFXyDaHxhPkjRMnjQZgB4RzCMqBrWXduUy9uxbT1QMUTyykmmLrsZcPBrd1FW0lRTxpxMvYVDrMWmSOVgPt5+kyJbHmy0HSUhdnN35POQ43xGQJ4l5wXy6Ar18NX0J39TP54vZyyi35LOvYx/3XlVMrU+PZEkfdI86dzgtHe3opMHrGpUkcu2CctKtOr5wzWhyLFoCkTiKAtnZebT2+XjxYA2vtci8fqYDc8Z7nw56z2+gvZPe3l7i74hEqygwcuRobDZbf1lhYSEZGdkXbPNtkvNUAmrcKKd70AbiqVTXKf7lEJRLsG3idrs5e/YsU6cmc/P86Ec/wuPx8P3vf58lS5bwwx/+kEmTJvGb3/yG5uZmfvjDHyLL8iW99mHo7fX/7Z2pmIt1rXvYULejv2hl9jTmGyuINXVAugWN1UpCo+eF9RsGCUi9Xs/KK2agOb4NVdY4EnEVXdu2E3e7yVi6BMO4SuIawwW7VRFD1ReiY219f5mglsi4egQR3d+fVsPpNNPd7fvbFT9GfNKe6ZP2PHBpn8np/PvMJt9vPhCQ6Ws7y+51TxL0eykeUcnEBWuQtLa/qy9BALG3k0BVFbFQiN70Qv542E9LT5AJ5Q5WDvdisqVjM9v4We1zNLpbB90/N2cilv3niEXCZC9dzGM16/jy1Ltpev118osqaK4+QVdrA7PnrUbeuJNgXQOS0YixpBjxyvl8v+E5EudPJx4YuZrREagNSOw6eGxQP1OmzSAjrBBc/wpKJIxq7iJCRSNIz7QiJgJIkkgoFEKr1WEwWBAECW1EpvulU8iRgUVlxpXDidqHRom91Fxuv63LbTzwyRvTRzEffBDkmJ/TB7Zw6q0dSGo1kxeuJn/YJHwxkZ8+eZjmruSJvlYt8Z1PTyXL+vbvI46nt4dA2I8mEsUSCJLo7UOTl0/E7iDgb2f7y48jn49smpaVz+j5VxGwKigtnRjrukCRCZRk8efeXcwrmcGLpzZwZ8VV+Ha/RTQUYN6UZbg2bSPu92OYO5tYTg6G+nran32hPxCX9c4b2JruZkXaZCJRFZlmNdFjm0h01KAqGkvYWUa3x4vO5OBoj53ntiWjtt68ZDhvHmvj9nEGVLu3kOhowzF3DraZs0kYLShKDJ/PgyzLmM3WIT6M7yQS8fDMM88MKktPT2f58it5t8GdLEfx+72IoojJZBly/d1oIwm6XzyNHB2YpzJXjyDyEQWauxx/V/8IH+fn+XvnhE8il2TDxGaz9QtHgPHjx9PW1sbJkyfRarVMmpQ8kbvxxhvZuHEjwCW/drFRZJkywY5elZzYl+fNZZ5hJtQY0FpHYCmsQGzuxP/Sq8ybPh1JSgo7jUbDpDlTUCHRsbuVsz/5DTW/fAjz6FFYv/wN2gvH0RVVvbeBoajBfXSwGYYSSxBp8SJJ4qBdzBQpUny0hLydvP7M7wj6kzvh9aePcGTHWgTh7zuBFHs6qP7Of9L058fp3bYNc0sVX1mcidmg5vC5PlQZowlrczjZEePqkjVo3hVQYpyzAovRRtDvRWzvZWrueLJ74vi6u7Da03Fk5THqijtIV1kI1jWQu+Y6im77MrZR15DWl843xtyLKIhoJQ1CBJoUB+acYeTlDQSYyMnJoTgjA9/TjxOsqSHU3ILvicewtNVgMWgxmRwYjXbS03MwGu0IQnLui3X6BwlHAM/+FtRCas5K8a+BKAo0nz3MyX3bkOUEsUiYPeufxtvbTE2Lp184AkRiCZ7fdg4EgYQCXd44Te4E7T1+jtfWEtQYOWIfyX5JTbXSRqc+zoIb72HGrOWIkkRvRzMxn5tStxrl53/B9/w6fC+sR/n549yTNg+1mJw7skwZOHMKGT73RlwagcCyRXQvXoimaBSOHgsaaQTln/8m1jHjAPA//QprMqYT9rhJDxuI9poIjbkRaem/IY9czMmTx3hry8v43N2kqzr43FWF3HdlCYosc2WFkfij/0fw2BEinZ20P/scvevXIQkKgqDGYkknLS0LjUaPSiX0n7y+G6fTyYwZM/uv6/V65s9fwIWEoShqsFjSMZkcF7z+TgQBoi2+QcIRwHOwFXVqbZXiX4hL7vMoyzJPPfUUCxYsoL29nZycgTQSDocDWZZxu92X/No7TRf+Fmlppr9ZZ8/GTZzev407r1gKdivDO3Pw7+1IXmwGVTxKMBaiLc9Ez4ENzJkyH4PRjk4j0Rnqoau+gUB9AwCSXkervYhfPPwW4WgCUYC7rhzN0mmFaDWDP8JELIEvMjhnkjbHhC7NQPhoJ4JaxFyWhjbL9J4T73vxSdx1+aQ90yfteeDyf6b3mw/ONB8f4pNTW3WQGcuuw+pwfui+WnZtJREKYZs/G2+hk91V+1H3nOGbK1cT1uWz62Qfm99Kpu1wWHTcc939/PbkQ0iixILiGVhlDXmFY4gkokRcLq6ZchWqI2dZNfsa3OEo2RUz+MPmDr6Q34d1XCUq43B8J5ML1nArmNt0/Mec++nuaqB6w1rK5t3BIy9Wc/+CPCoqhpNIyORYM6DGR+6q+5GMUZqf/RPhjg4iO7eimTMDqa+Lvv0HiPn9pE2birliOJJGg6t+aDxFOZLAbNQi6d87quKl4nL7Hl5u44HUmOCDrQ/ei0g4RPXRPUPKu1vr6VVGDCn3h2IEYwnW76ln/Z5GAGxmLd+4fhZNzd2I6UGerX+cSCJprmnRmvm8dS7Tpy6mN+SjMHsEro3rBlJ3AEo8juHAWYJz8rh77I143DaOhEYxLGRC62vGZDZT5Cwivr2b+PkT1lATZCy4Ct/Z09iWXUH9qSOcPbYPo8XBlKkrUXVkUpWQKVB34unpYNWaL6Lx6IjLMhE9HK47QWu0gOF6N+FwePCzb9lK3pqrECSJYHM7gqgn5urCc/IYuuwsHFMmYSwsGPJuJk+eRFlZKeFwGKvVisVi+bs/l3fSc6ZvSJkcSWA26ZC0H82S+nL8Xf0jfNKe51+RSy4ev/e972EwGLj11lvZvHnzpe7+ovC3zFI0GpFwwE8sEiZQfY4Jk5cSONqFyqbBUKAiEfGjzlXTdLKHs6cOArBn7eNIKhWrrr2PQy88wcKpK3jbW0m/cCk/29NL+Pxul6zAH145SVmO9Xw0MtDEPCi+LgStEdvUTDrXJqOIaSdaMKRb6Xj1TP/43AdbybhmBL0JHxqNFq3W8DcT436cTQ3ei0/aM33Sngc+/marqguYl5tt6URjwgd6LkGAcFwmGpex6NVEvV5UJhOh0mwO7UlaTYSB7S8/ysIbHuwXjgB93jCbd/Vw9/yb6Qp14Q/GqI3oONuZRl7RakaUmun96W8Jn61JjtVsJuuLXyTfrkNfXIgxM4eYx495lBn/2SBKXCbeF0bbKnNy4wtMvOI6nHmFLJlmpckfojjHRmY0iu+VxuQkBSBA/k13c+7nP0AymTlR24tx61qCe3YB0PHaBoZ94+tQWoE205iM+vWOV2mZkI0rEEbxD15QXmre+T1UlCiBgB+NRoNWa/ynJBW/HH/rn7Qx/TPMVkVRwZ6RS1/X4JyGeoOFYXbboLLJIzMZXmjn0JmufuEI4PZF+MsbTayZV8KR3tf6hSOAN+Kj2SiTY5nA2RovfWc9jL6Af2Dc42GubTEv7vOz9XAy7UZru4ebK7PJIIhBUuHRqUgEB0RnqDmOc9FimnUJqvbvBCAabuX1dY+w8MYvE3LpCRgzWLris7jWNxFVzn8uosDEOWMx+GPILv+QsYg6LdFInK7XXsZaMZuoq5rGv/yx/3r72nWU/+d3iJsd/WVOpxmXKwTo0Ol0RCJctO+mNnfo98JSmYXLF0IZ+ir/YS70HX47DUksFsVoNCMI//zNtQ/K5ThPfFBSoneASyoef/SjH9HY2Mjvfvc7RFEkOzubtraBSbKvrw9RFLHZbJf82kUlGqe4YCxF2Zloavag6aknYstEZe6i9nd/RkkkEFQqiu66lUazjYDPDUAiHscX9rP4hvuJvLatv7mIJY0+79DFU5c7iFGvIj3RRc/zP0AOJSde86SVZF65CF+LjxrXQYq7xgy6T0kouM908nr9ToLBINOnz6C0dDjw9/tEpkiRYiiWtBzyy0bTXJMMniWIIrNW3Azie/vrvI0CVLd6eeTlk7h8YaaOyuLOUSMxdrRzou7kkPrt9adw2p10uwbC9J9r8lLcF+Nw92Eqxat4dNuAL/TmQzq+OG4anBePcb8fpa6GNeNH4X5jMz3bk/7aaruN4js/h/tAcjvL6Mjiulu/Sqy9C9/GVyjILuL1TjWbj/TxtZHZA8Lx/EPEeiWMZaUYFi3j/z19jK/Mn4rqvHgEaHvxRfL+/StEzCoy14zAe7CNRDCGZXwWQo6ZxGUUzDAS8bF+/Tp8Ph+CIDBt2nTKykb0m96mSPGPIMsCY6YvouncCWKR5N98a1omGYXDEDQGPnvNWP6y4TSxuEzlMCe7DjUwt3JoDuezTS4UoDcyNCCgQVPGd5+oQlaSgXm+M28S7N07qI5u0jgObXsVk2Mh987JRqtTk912Gu+vfkuToiDpdRTf83n8VdKACacgoB9TQfXGP6PW6nDmFhPyuXF1t+N3d/DouiBleVa+VPSu9Bqygq4b7LYQ2vx8yM0j2trSf9m46mq8ioQuLQc5lqDt1RcGjTXm8RBpakIa5eDDoEgJEkocDboPJfZjJjWZq0fgOdiKHElgmZANmcYLBX39SFCUOGfPnuKtt/ajKAoWi4Vly1ag1aaETYpLxyUTjz/72c84efIkjzzyCJrzoaRHjx5NOBzm4MGDTJo0iaeffpqlS5f+U65dVFQSTkc20c4QwvDFJIKtWMaWcPr7f+p3Klficbr+8jRzvvxFNrz8237TNsXjw9AbxLpyObHy0dDTiaqoEOeZZrrdA4tCQYBOV4jfv3KSzy/PI1sc+Ch9B9ehLalELtDhqe8G/QXGGJeRJAlZlnnzzd1kZmadt/lPkSLFxUJQGZi+/FZG97WTiEcwWNLRmZ0faKHR6Q7wo78c7K+772QH6YYcVi2Yh/H4LnppGVTfaLUTDMUGlVUUW2j0HWRKxnTWvdwx6FqvN4wnbxj5K5fTs/tNcq5chevIUWxA2/aBQF8xl5uuba9hqVhBIpwgZhDZdyzAWy0SFWmjmCh7WW728UzCSTx6AV9OWUR/4+38z6YWFAUafQLDzSbivuRmVyISYd25TVR5G7lmxHIqrxpJ0BcljnLJFmQfDJldu3bi8719Aqmwd+8esrKyMZvT/sljS/FJQWfJ4sq7v4Gnpx1RkrCm5yCqk8Jg8jAno4ocCFKcx9ZWc9ucTHriQzeixpSk0druY0bONGr7Bk4li2x5HDju7d/fkRV4ribBXZ/9PIFN60FRMM2bzsnmKmJynLlyI6F9R8hetoTqlwdEWyIUpumvj5G35rP4zyR/D+Zx6bjETkomXoFbVci+2jA5GSoqJyroYx5unJLBofYocjSByqJFZdIQ6Q6gxGTEBJRl5HG87hQl99yNqr2deE8PLnsuLzbBSk+EDEkCAeT44DkOGBKR/n0RFNqirbx4fD09wT4WlsxmckYlOi4chPDdyEDEqsG8qAQULvk85fO52b9/IG2K1+tlz57dLFiwBEVJxX1NcWm4JOLx3LlzPPzwwxQVFXHjjTcCkJeXx69//Wt+/OMf853vfIdIJEJubi4/+clPABBF8ZJeu5govjA9u9oQhqXT5Guno09kmtSL2mwm//rbEHV2UGSirhba+2IUj51D/bEdZBWUQW0zcZuDjg1/4MyCW9nQLhJ9uY5bllTwzJZqvIEoapXI1fPK2H20FV8wxs9ebeL7V1yFet+f+8cg+/tQzLm01J9m/LJFMNgKhrhTwnN6wMfI7/elxGOKFB8BgsqAJaO031zngyw0EokwNU3dQ+q+dqCNYTYt42ctoqXhbH/kRL3JQsKUz/SxcbYdaEJWICfdyNXzi/ndqQ2MsI8mIYdZM6WASdlWtDJ4RZAJ0L1zN8V33k7Hptfx19ZhLisdMh7fuWrSbrgaxWjgyW0t7DnZCcDZRthv1/H5wjijMtSEc8wI1YNPO7x5Fr7+7LH+3f0Mo0AiOLARplo0ky1tu4jEI/zv3of59rwvkinmcLmRSERpa2sdUu73+1LiMcVFQ1FApbOTljc0HRdKHCnWR8gfpjzPTItPYF91B0umFbJ5fyOyAllpBq4fm4u5xYs8vJQbRq5i3bmtqCUVq/Nm06qYWXSVE6MMQRG21nSzrlPk1qvuoUfVxpZNfyUeizJ/+U1oGrqJm0wEm5qHDCXa04OUBupSC8EigVpNG7VbNhEtXsNzW5MWDqcbYN8ZNd9emUt50AUlJmLFMtGYRENrC1kFmdjdWvQlVkJBhc5IFt0dCmmO4exuNnP0WDeSKHDzciPBphqso4vJWryC1pee6x+HqNWizc/ng8rH3ngP/7P7of6o0U+ffIXoiCiLcufzYTKaxf5JeWj9/qEmny0tLSQSMcQPYNGSIsXF4JKIx/Lycs6ePXvBaxMmTGDt2rWXxbWLgVYl4jvShZhvYMup3bg8bgBKHQ6K7/4cniNhlHjyxy8ZM0gblkMsPY0peaXYu7ro+vNfMd10A6GmZqZnJ/ArmVQ1ePD6/HzhmnKCMYnm7jA7j7TS3ps0IwtHE7hlM+8MvyGa0zFY0skpKufIqU1UTl8CjQkElYBmlIMN+7cOGrfR+Pc7+adIkeL9kUSFRDSczPn4AdYcXq+HC8VeSLfqseoF1NW7WP2pL9Lb0YEgi0jpuXzribMUZlu4ftFwUBRcvgi6tijfKrsXWR+j6BoNGbVu5LeSO0k2wLGgiFpJJNTeju9Mco6WjMYh/ZpGjeDN7S9iLZ/BnpODFy8drjDusVmo4gKNQTcVs20o9XEEBHRjM/jNzjqy04xMH5ONw6JjdJ4ez4RKNDYrpspxuPy93GtbwFrPURr87RxpP8ny/Nx/KN3BR4EkqcnMzKSzs3NQeWruTHEpSES9NJ07hizpcXn9jCsdwW/WNtHY4aM0z8r1i4ajyAq5dj36o51E/FFsOSYqM8opG1WAUa0hEdRQopPxnZ8DTMCa4WlEC60o+gTn9h4hLTufsonTUR2uIRKO0vfWAUzlZUPGo8nJZpd4jv2GszSea6XcVsDKiYv46atNg+oFQjFaesKU5JsJvvY4G970IkoS4+asoKr+FIUFRRitZr61/yE+XXElZSo7Xm8XSpEKr9/CNVeUIEsC6dddj9zUinnEOArNZnr37ECXk4NzyWKIxUicPo7G6UROy3zf99jia+sXjm+zqWYHs3Knob2gmdblxYXmm6ysbETx4+P3mOLjzyUPmPNJR4pECTd6iE0y9QtHgLZAiMy4GiUe7C9LBGLQF0WbYUA63EDXay8j6XUIooio1RIK9LKyOIu5RdkkrGbe2PgSw0ZP5qXtncTiA5OfShKw6M+bK4gSjiX3IiAj1u9l3pRp+CUdxw69wfDxM7BlFhAIRwiEBpKHT548BZPJ9lG/mhQp/uUQBNAGWgkcWk97bwuGsQuRCicQld5fcGjUasqzEnz96myCPi8JtZkNR3wsnVGCMz1CV9TLvr8+RF7xCCoqptEd1xGNy5xrdnOu2Q2AXqti0UIT8f1uTkv7GD3yCkKtg4Wfe08LmVcsQw77UJ03JfWdrSbjioV0bXsDZBldfi7i5DG0v/EC1rLpFxTAKocDXVyFVeqiqvowo8dMQd1di9c0jttWjmLPyXZefKOGaFxm2ugsbr39Xti9hbof/wwAURC47a4b+K0hgllr4hKkH/47kJgzZx7r1r1KKJQ8OZ0wYSJms+2fO6wUn3hEUaC95RzuMJyoOgyALxjFbMgAoLbFQ21L0pLotsVllI7TwzGFcKOXE6dfp7n2FABX3fDv+A4NtgyQz/aSOzqDzx78LiU5+WgkM93helZYrHTueR0AT9Up8u+6jZa/PIUSi6G228i55zZ+1/Qca/KuoNRxJTpZjWI3IYquIeNXmU3s2fxnQudTFsmJBEfeeJXJKz7FvkNHGJZj5+cT7yXe3UfrK8+jRGOMXzQX1ZRCfvnX4/3zxs2LhmPXiZiHFWCeNxtFTuDetJHW555PdiQIlHzusygL57/nu9RKQ/MxGjUGxI9JzAeLxc748ZUcPXoESKYhmT17Dpco816KFEBKPF50ZLWENsvEu63yRUTi3qG2+upognRNBE/taUyz5pAxawZNDz1E3qduItzhov5Xj4IoYn3gS1QunEUw4uHOK8v5w8vVyLKCKMC9q8eQXWZEzPkvBJ2JRMc5up/5Xn8fmtxhzFn+BSJi0qnbaNRzzTXX4/f70Gq16HQmUhNPihQXH224m55nvocSSwa/iG75I5bpbsRxV76viZROJVN76E1OHzofWEYQuP+Wz1ET9tEjidQ21BCLhqk/e4T6s0eYvPxOCjJNNHUORCu8YWYx6po+hFwdPWebiRUMjWQoh+NYx46j7ve/ofBTt1L7m9/hOnAQU1kpxd/6Gr54gK7mevbveBmAvtoDzB07h+3HuvvbKMk2Y3Pa+ePzVRRlmbl1/DTkU5uIjr4CAjIxlZtXdtYRPb/hte9kB9kOPWO37xwYiKLge+Ilrvzi9VRkjUIZnG3ossFgsHL11dfj93vRaLTo9am5M8UlQEkQl6Hq9IAFV2tLE0tmjqWqvq9/M8egU5Gu6mHda39h8YrPIAQkXAcHfJ0Drj6kC+zLKKEoJrWeM73JKO1WrZkbxtyK59hxYh4PmnEjONh5mvFffxAiMaIS7HpzA59bfBOWnXFkj4c4oLL4uH5+KX/eODBOh1lDQY6ZU33dQ/pNRJPzohxOUP/7P6JEY6RNn4bnZBW1//cIafd8nnjiHfNGmpGrZhYix2VAQOzqHBCOAIpCw+8fxTZyBKgvvEGXZ84l3eCgJziQcuOm0avRKJr3zp99GSEIKsaOnUh5+TCi0SgmkwWVSnuZ+Yen+KSTEo8XGYUYtqlZKA192K12XJ7kLlxDayOTJowkujs4qL4uR0OtP0j42rsoyjAhVJ+h7GtfoautgZ5sHeoHb0V3op7Y668RvfVqHjnzFNnGTG67cRFZ6gKyHWbsRnXyJNJcgDbhw/3GXwb1EW2tRu5rRkmrSI5RAUnSYbXq/uHnVXl7iXV3I5lMkJ6BfH5XTxAEPKEY3e4QRp2adIsWVSqJbop/MRK9zf3C8W18B9aRPnIeYem9844F/N4B4QiUzZzH+p632NdxDICp5WMZlT2fmt1vAHD49b/w1bv/i+qWEG09fkZkGckngiDr8Fg8uHs6CCl+NJKE8o7wpdpcA23rXiZ39SoCuQ5U//NljKIWU8zImw0Rskuc9PkOIstJj6KuprOMmFBAxVUTOFrjYliBjbK0GL999QydfUE6+4LMGF4CmlxOPfV7AHQGEw8su52fvdrWb4r65okOJowaQ6RjYGErRyKMNReTbc+7bEO5J+dOLVbrh8/RmeKfRzSh0OkKEZdlsuwG9OqPmeAXJHQGE/I7dpy0Wi3+7hq+d/t4TjR5IREixxji3K5nkBMJ9u15kRkLr8fvGRBJfb42sixFJLyR/jLJoIZoG192jKXTZELQW8hSzLSHPYTvvhJDfTtY0sgYmc0vazfR7u/CaXBw06z5OOIaop6BNU3cG2GiYsV53Sj2nOoiJ03LhFIrOiGG2ZaGzz341FNS65gwdixtv30UlcFA2vRpyLEYWcuWEO7qQjq8h9K8mf3WFG8eb2Pp1ALU59cScd/QeUIOh4n7/WC/sHg0YeGr0z5Lnbsed8RLub2YbG32x0x8iej1VvTnrWw/XmP/5yMDvb4IHn+UNKsOuyFl8vthSYnHi008To+SQONUWJgxi+buDjq6uih0OBCdaswTM/Ef70ZUS2jHWegWu3m2fR3uiJe7rNdSHnbQZzXws/o38XiSJh5jRpSyJnckNo0GURAxaQ2Myc0mrdNDzwsv0xmNkb5gPkJeMYIcQw4HhgxLiV78PGlCcx1nfvg/yNFkHqmsVSuxrViFrNLS3Bvkv//0Vn9uyuUzirhqZhFq6WP2RztFin8AQRo6xQoqDYrw/r+DUGjg96rR6vE7jeyrHwinv7/jOKUVVzJuzdcJRRLk2lSkKSEmSF7SX3+UcFs7DYpC+ry5tKQlzbH2732JVSu/gP9ADzF3BH2+AVHXh+foESLXzuNnxx8jS+/gZtMkAm+dZowoYU+bRvmsxfR1tBLwJjfC1EoQk9jN9VMyEMUQ4aCfFZV6dleLHKv1oFX8HDm0u3+s4aCf9uMbmTZiPnuqegAozbVAXdegZ9akp6Gzv7+/UooUH5ZAJMFvXz7BqfqkiHLa9Hz9U5OwGz8+C0ZBULDbnSyfOx19uA+DWoUkmenatJOs/HJUDjdvbnqKU5GBQFTu3k7cnvZB7Zw4tJVRd3wX7/5Owq1etNlmNJOyOd7WQGZEw/CAj7Y9hzi1cjxPNmxBQWFF5hTmerRYNh7grqI8eodP4Petm3mx/U2+Mvp2orgH9aHUuLCU91Hk24sqpMZWcTU+d4DZK29my/N/IBoOIQgC4+euxGYyomnrxms0Yi4vo+mvTyefV6Wi+K7b6attIh6TmTrcTlG6hrCoRy0J/ak+NOlORI2mfw0CoHU60TrTCb+P9YIZC+Ns4wZM8FPi618GGdh1vJ3HN5xOBqeSBL580wRG5NsuU3eJy5OUeLzIRCUjT75xgvEFevI07XRUHaJ81CRUQRXffOY0OekG7lhWQBwvxwJ1vFSzA08kuXtW1VNDVluU9VYZT3gg2+wJdy2zR01kTFYhP07/D7SCFlVrG2f+87v9qT96d7/J8P/4f8SLSjCMmEHw9Jv99wuSGsmeM8SU9h9BFQ1S+7uHB03aHWvXYZ04kVhOEY+8fKJfOAKs39PAlBGZFDiHBuNIkeKTiuAoQDKnkfAN7Lhb59xITGUenA/xXaiMdkRJhZyI48jM4XSgaUidY71n8VcZOdPgQhIFfvKpcgLPPUm4dSC0cs/2HZQ98GnOnj5IJBTEF21HSZxFm2un79ABfKdPY162gD+cW0s0EeMW8xQC//sH3j5L6N31JsO+9HlWrv4c7s4uJFGN2qVBaUhgGK/juaf+l8T50PkLpy1kzYRipPhQ89i+9gbGLTSxp6oHk17NmrnlOMdoqG9pJtrXhy4nm+IHHiCuTc0PKS4uZ5pd/cIRoNsdYvOBJm6YX3bZLxYlQUGWFY7VesjRhTEeeIp4Xxt+kptQzhm34pLVeBQD0XcIR4CC8lEYbXYcGTn0dbWhN5qZsfQ6tr7+KBMrF2CcXM5fdzWy65G9yejMaTa+tqoA9epCnqx9CgWFEkselacDtG58NNno0eOYnOlcd8cCnm7dTkQcqtD0FXaO1mxDZ7ZSMW46ax//ObKcQGcwMm/VzQgiiCYLdlHAv/FhYsJIHJMm9gtHSKYya3rqWQq+8lXuDgWwnXsNpaERXflUdFEbYXUyMnzClkbZv32Vht/+lmifC11uDsUPPIDGbocPYL1wmX/8KT4Cen2RfuEIEE8o/Pr5Y/zw/pmYtB8Pv9fLgZR4vMhE4gmqm7zsO9nFt68rYl5lApVaIGAUeeCKdMRogFj7SUg3sqPjcL9wBCi2ZmOYZuNc0ytD2m2P9jFeFtArRkRBwLV3L+92mupcv4Gcz30Bw7TrEA0Wgqd2oXbkYplzExF9xsXdXQuHiLwr6iBAzO0m4pRp6Rq6gHT5IinxmOJfiojahv2abxJvPoHs6URTOI6Eo+RvRhKNafSMXXIXNW8+j7evmxLjME5QPahOrr6Qnb1JmZeQFZo7I2jrGwbVMZYUYcuwcv21N6O1OJDDQYQJBbiP1eI7cwYAoSiXDs9JSh2FiLuPDh6IotC7/yDarDYcpVNxH+0iJiWwTMnh8LHX+oUjQNW+rcy98lNEYkOtHHILh1HReZbf3zaKRFY+WkkASzll//VfKMEggslMXHP5RzpM8fGjvs07pOxUfR+Jecpl660qCCC0N9G57jWiPT0ULVyMySnj6xvYGFLiUSLN+2lQl/HqfjdrrriVc3teIhwMkFs2itziCjprTjJv1lwkUSSqNqLoTWQVV+ARFP66sZqqugFR3dYbpNYj4MgQ+kX1XMsI/JufHjS2WHcP0+IOcipWIdc24ryiGPfBPhLBGPqRTnrT1GRa15BhF9n+xK/6Td7DwQCvP/coV97+IOcO7eWU18WEUXMxKEYCrR7eTdznQyOHsex5CNFoQ9GZCB7fiuzpwrDkQWKoURQQSoZR9l/fS84jZjNxdWoeSfHeuH2RIZsGgXCcQDiWEo8fgpR4vMiY9CKTRqZhtYM+XcTXZ8XrDmIK12M9twP7zDX0bv4TKDJfWHI3j+qsnOg6Tbk1n7LuDqSeY0zMHc6mpr2D2s2zZYMi877BGRQFFIWI2oY06QYclStB0qCERTQRmYRWJH6xBKTRhLG0hEBt3aBijdOJoBEZUeTgdEPfoGsZjg+WhDdFik8SEU0aUvkczAYV/qDygVJQ6I0KzQYj6tE3o5fiZJgt5JnP0OJrx6qzsDR/GQ6hkMgoD28cbiESTXCgKcCK8WPxHD4KgKEwn5zF43G99jNAwS+I2Gddi/fEDiSNnhHf/BLBqITk1FPekI8MF96KVxRcb+0n1NKAY83VhPQ22mOtVJ/cN6RqPB5FFEQmzlnOkd2bkOUEtrQMRuWPIh4KUV97GM/JHRSNmIAjpxRFZwJdKtVFio+OEUUO1u9pGFQ2dXQWKlG47NLBvI3Y3c7Z7/839gljMZUV4t74GqbVk4bUS3i76fEEqG3z8wevlsUTbsOhAUlnJs3STXrtOcJnNgIgmWw4ln8FMTgcChykWVspzbVSe164qVUiGrWAFHZwVfEadnds572iFAjePjLfegXTlFuJB1txlQbJLh1Pa/1R9j/3PDZnFllLriESGupCE/D6cPV109FUS3tbE6MrpzGsYhSI4qANca3TiSgkUKbfQHVzE5IoUThuGbHD6xDDLtAlI80qCsTfMY+IYtJUXhAUFCUVZyHFYNJteiRRIPGO377DosNqHBqFN8V7kxKPFxkp7GHmdCPVbSfweSfy32ub8QVjpFkzeHDhvWjOrMU4cibe9CwahSirSudxa8UaVM0niW3+A2Fg/tiv0+Tv5HRfHaIgMrdoGqd76ymzDUeFBlmRMU6aDBs3DZpsM5Yv4+0MHrICimIguL8N/+mkn5FpVAaGyiyi0j8+ocYlLYX33kPdL35JuL0DUaOh4K47wZmFJAjcvWokP3/6CK3dATQqkTtWjiTDkkpgm+JfC0EQkAI+Ip1+ojEF0apBSjciS+8frMoq2rCl9dARa0EQTJz2NHHLqBsQUOjqUPOnF84QCB8nw67ntmUjeHz9adLtOjImXUmku5dwczNZV8zEf+RZ+k0OFBn33pexTl2F+80XCCphjsiFxLqDLB++mJ5QH+o8Bxw4PCAiBQHbrJnQ2UHk0BEaxD5UUggBsGfk4OoaOAlBEFDrjai0Gfi7Q0y7egR6IYqqoRG5z82exkP4z/tN1pw8wOSFqymrXPChEnOnSPFhKc2xsGJmERv2NCArMGF4BrPHZl+2whEg3NFK+X03EqrZgRyqJWfxVDTpJUPq6YonEQolf0Buf4RndyZ9HO+72oZe9hPoqO2vm/C78Z16nfioazjb5KezL4jTbmDexDxe3F7DjYuG0xb00K740Qgmbim/nYNdu1m4aC7ejdv629GkpyFJIZRYhFjrIZQpt3LsnJffPnGCvAwz85Z+huo3/kTT6WNY7E68roEoq4IoovEEKB9eSUdTLdFwiMN736DWUcXCB+6j6Q+PkQiF0KQ5yL1mDV6VwPrXXuyfj04dk1i+4mqQLuyvmoi4OX10Nw2nj5BdUMaoaYtQG9L/8Q8kxScGh1HNl2+awG9eOEYgHMdh0fHlmyrRq8WUGfOHICUeLzKSWkNVWxUTDKP4j7+c6s/H2OsJ84vNfXxn+hgi5UX86OhThGJhqIHKjHEsyl1ExqxbiO9+EnNjHdfmzeVUVgWgcLj9JK3eDlbkzEPQaqht8/DHTZ3cc+8XUR/bh5BIkLFoAWJBCW+vwwQB4i3efuEI4K/qQptlQsg3X5QfSTwtm5L/+Day24Wo15Mw25HP71U6jBr+484pyUTlGhU2owoltUhM8S+GFA7g7fTRFerDG/SRq8rGIYhIWbr3FU0BxY834iHTbsKsMZJnKuXPL7WzZm4Jv31+f//Ct8sV4tVdddyzchjl6g6Oex20z7uFXHUUVZEAJwY6EbQGRO3A6X/Y3YM6I4P1zU/T25oUdcW2PO773+8QeX4TsiCgmjCeDaer8AYCLL3xWn595kk8ER+fn3IH+fPnk9iyBW9vJxqtnpGLViDrjfx2Qyt17T40KpGJo9KYO7ICW18N/hOD878d2bmeopGTENXvHXVWFY8iu3oQ1GoUmwP5Y5KLLcXlg04lcvXsEuZPyEOWFexm7WX/LTKk6+hb+xve/qMZOLYeUaPCsuJB/NseQ46EMI9dgOSsYLohjZ1n++jqS/o8jiiyEzN1kOhoHdyoKIHPRVcgykPrT/UXH6nu4lt3TqHZ087u3hfo7kquGbKNWXx63C1kFMg4ikpx7dmHIT8Lc1EavkPJ9BhxTwfBhMILWxsAaO8NcKJW4v4Fqzm76znm33AP+157Bp+rB63OwPhla4hsPYhKp2XSnOUc27cNUZLIHTWL9T4bs7/+LawhNwmtlpZggM4jewdZQ8hygoaOTqwj5vBuMyqBGHvWPUFbY9K839vXTUvdWVbc8VVEtQkp5CfhcSOZzCRMqeAo/6ooCowqtPHD+2cSCMWwmDQYUsLxQ5MSjxeZhMaEpICn19cvHN/G5YsQzx/NU3WvJYXjeY50HaPMOJqIaRzZqufRFlXQHfXxwqn1/XUWF80m1NpBxNhDa4dCe1+I724JUZQ9AZVWZJ5fzyyVuj8Ih0ol4a8ZbDYKEKpzYSiyEo9fHCUX1xggw8CFWtOIApnn04GkhGOKf0UikRibjmzH50/6Nh/lOPOmzaHcaSIiXHj3PC7GePzYs5zsHsiVVmYr5NPLb6SlMzrkxKSzL0iO0onSfRzN8EqiumbUjmIknQ1BrQVZxjrzLhLxTBJhkBxGtPnncNtLqA4cpzc0IOrq3S2cjXYweuV8th2qovvY0f5rO/buY9rYSjY27mBT7U5MaiOO6SMoUk0jSJwmVYgcl0Bdu4/r5+cxtiCOJ9hDQOXF7LQPeU5ZTiDK7x3GS+Xto/kPv8d36jSIIlmrVmJfsoxEyjcyxYdEILmh+XEh4e8e8kczeGonnWlTSFv1dYzdbbQ8vY5g4+sIKhXf/OrX6dZaUGtUZDk1dHg6ILO4/17DiCvQZE4l5tfh8IncNreMx3fUABCJJojGZFpjZ+kODmw2twc6ONVzhmPbdjOscgblt67Eu+kRfAcGgn8JpVPo6OnFqFMROB/eNBxN4FesxGNRWgNdxGeNoUiyEBBihIUEsYNHUOJxrN7xDFv8AN3eKPbhetIC9eyJ+BiZXUb13ipUiog+PnR+kBPxC5rThn19/cLxbQLePoKeXsyhLs794lfE3G4ko4GSBz6LOGwUynsa5qb4JCPLCiat1O/jmBKOH57L1V/8Y0s4nKDIXohVLyG8a17Sa1VobBYaPK1D7osIfjYeaMd87bf4cf1Gsm1OMo1ONJKaxSWzKQ8b2PjSQ6x/4hcEq57nU/OzAWho91LT4iYUlRHfkUcxkZDR5g7d0dfkmEkkUr+UFCkuBa6Ap184vs2+o28Re9exoyCAKxDlaF0fx2tcDDePR68eMG2tcTcSjIcwqoaemZgNavRSjE1WNevqtjPBVoZ8rh5fjxfr3E9jX/AA7pNW3Id8+Kp8dL3egW7U7RztVdMSaBjSXm1vA8FQiO7uwUm9fT4faRorAN6In7nF0zjuquGZ5jfwCBGyPQKyysTyyU7M3dvZ9dTvOP7K8zS8/CoqrRa9afB8NHr8NLTxC6cQEgXo27olKRwBZJmOV14l3lh/4RedIsUnCEE/NLCcoDfjDcvg9VD7o18TbGwEkpFJO3/yQ2y+WgzRVva/8meadmxGq83EMGohmpzhoJtB794g3hN9KPtbmeCNsWJyQX/bGpVIa2hoROcGbxNqjQ5kmTM11WgqlyHqjCCq0IxeQLPkpLe7jXTb4A0dlQQ5paMx2NPZ03mcl9rfRBcXMG47jBJPikxRb2DDwV7Kh+n4zfHHeOrUWjbUbud/9/+B7PH59Pb1kV8x4V0vQaAoNw8xMjSSqiipEN696AIMooran/+CmNsNQCIQpOZnv0D09A6pmyJFig9GSjxeZBQFxEgaORk2bltU1l8uigK3L69A3yEzIX3kkPtsagcIAm5BodrVQKOvnZus07jTNot5+nJObByIwOruasWmdGDUJ08uBAHKC+yDThNlWUFb6kBtH1iAqtMMaAtT5hopUlwqEhcIcRyLxUiIgxc5Xd4I33pkH7969igPPXuSl14OsLrw+sFtxeMYZIUbZg34PkmiwH2LspFsEl2xAEuLZnF28wbO7N1OQHSwrtGIh0ISgcE7+J63ulDLGkY5xgwZ3yiDE1VsaKALR5qDtlAyN+OcjHH4jhznjvxFfLXiRhbZxjJqxEwKMyyMzorTUn2y/75oJMTJHZuYcv3tjJ44k6yCUmbOXUKRJoogXtj4RYyGcR04MKQ8UFtzwQViihSfJNQZZYjmd/rqCRhmXEuoYRfx9vYh9RVFQWWzcvzN1+nrbKWvs4Xu3fvo2FGHqfJWfKcHiy25w8/C8mTAGbNBTUO7h3HOsUPaHWktwt3TAcDpo/upUxx0VN6Ca+anecNtYu+x02Tn5dHRG+y/Jy/DSEaalQ7TdLbuVvj2pAf570mfY1TAhn74KMyTJiDqdGQsW8KwfCPt/qZBUecBXq7dQmF5EafrW5i28lPkl4+iaNholq24Fm3LMeQL+DxqDHbGTL9iUFlB+WjEcIyYZ3DEXSUeJ9471DIrRYoUH4yU2epHgCqhob2vhWlGmeKVebg0VhRJIt2sJlzjZVneDHrsLs65GlCLKq4rW0ZLg8Syyem4fElTNa2o4eimJykeNppG99BQ4zFvG8Pyx+ILRlg+JZOWc0cozJg7KLpYRC3gWDkcxRdJFpi1RFLbBSlSXDLURisqlYp4fCAf2thx44nKKt6OCi5JIm8caiEUGagTCMdpaRBJNzjoCfYxzFaEDgV0IjMEidFXjSGghqw0CUvbHuJn2vnMsAk0RRR6musYs+h2vv/sWXzBGFMynUN8vJRYgrElaYS0ejqCbRzqOIYoiFxRNIMMez6Kq5v50yay6+Ax4vE4ZrOZkdPG8FTdOu4Ycw3DVVkc3Ps87WeqGFU5D8vIEhIqPQaVC4cRplyxmprjb9F3PqCOu7ONjnAvo1V+yi0JYidfwzh5BTH9hYNZyGoNpuHDiXQNPv3U5+WnNr9SfOIJqx04rvkmclcNiaCHqCWXKpeAIa2QQCKAymwi7htIh1Xy6VvA28KsdDXKsAl4tHaEul4CdfUEmzpAGWqyK8cTfHZ5GfnZZv60uZ4xI9KYnjuJfa2HQID5hdPJM2WiXr4cnS0b3hLREqHJ5ae+oQGAEcMrMDuM3Loml7b2OLkOE/kWhV++UkefN8K40jTEujCnIy0cqTqBLMuUjKxg5h2fIhDyMqcM/Fo7kiCSeIeZbjgeQWVU09nZTV+fm2vnzUA+9CrRnQewXPd1wgwNvqcgUjH5CrIKyulpb8CWnkNaTglSOIak15EIvcPKQRRRWS0khrSSIkWKD0JKPF5kPKEYFlWQE2++wZjhk4k/+gj6QAB9bg6BZTegcuag297Cp4ctJVCsoEpI2PUZ1BYGyTCE2NDVRIYxHY0rQH7xcMaUltDmHpoDKS2niCnBAJFIkKoDxzCZTChKgnd/pBERsKainKZI8c8gpktQuXAyndWtBLwBsktzEdJ1qFVifxBUQYD2d+zcv43XqzBx9ChMipphlgJ6uty0tdYwbfxs7M1eiiwBXC//D77Y+c2h029StOxePBNmEdTk4AsmTT67FYVslYjyDssEw3gnPboOmrZvYYRaxeTCJQhA58HjNE+x8UTD63xl1BrWVBYh27LoSqTxxsFubppyK4hu3uo9x+jFa7D6dMTfchPTBHBbG9n6/O+TPkmiyIQ5ywDo62oja/hI8m25qKwRVFkK0ph5yNmjib1H6BIZkcxVq/BVVRHtS/pk2iZUoi0tY2ha8hQpPnnEdGlEcuxsOdjMcy8m/RMNOhXf/tQUcv9rAv6q0/S9+DK2KRMQE80Edm5P3lh3GGv+KOSZ12Lx+ZCMGnQFVsJNA+sI0ajmaLeP0jIDeOq4c2kJh053YAlP4MGxU1DLQZr2vEHzeAtPNGxEI6m5a8UqsizFKLo+8vLz0Wo0pBsd0B5AbUmgl0/Q+MZBTDNvwHV+w3rF2Fw8kodDB4/0922zGNm9/q+0NSQ3yq1pmdy+YAV/PLe2v87y0rn4TnsoLS6msqICY6gFuXwytoV3EDbkvGfOakHSY8+pYNi4yXR3J08zExoovv9+an/5K5REAkSRwrvuQHE4L9ZHlSLFvxwp8XgREUU4VddLlqYbhzOHPfs2MvnWNUhNnSAI+HMz+cv2Ru6cXoS6zoXJpRAuMeHXQUf1Uar7PMxfOJtVooS2p4sCfZD4Wy9SvPSL9Ll8dLbXY0/PxJlbTK8/wtmzNf19jx9fiSCoU7vyKVJcRvREOvhN1V+Ykz+Z7JIM1rbsxNXh5ntzvoES1WPRqYjHZRZOyuPYucGnbKMqDJgN2bjDHpqjbqY4ChllzqXPHSaYocXkPYnytnA8T+zEDtJGr6H9HZvsj2w/x1eXjMDa4kXwx4iWa9gsHua1t7Zzd+WVNL6ylqaqo/31HWPHEElE+e25jfxH5e28cSDA829WUTnCzt6enexpTpqTvgTMy5nK0vRxxFQhtr/0GHIiKe0UWebwzg1MXnAlTTVVlE5cwNMbXCwozKJM8WIoriDG+wcwiTsyKfvud4l1JFMBiRlZxNXvn+IkRYqPO9poH4m208Q9XXRlzeGVnXXcMS+LIkMAU2YWNbVVbDp7GrVazazP3kOmVUvPc9/rv18ZN48DmRm8Xv009y66jsCbMbQzMxBMGlQdfhIOPZ0OHX9dV8UNTitqnY+Jgo/YySewOJxUHW4nGklGbi0dVQFANBHjqYYt3FWwhj273hwYq1bLnOkT2PnU7xElFeNmLcWlTmPOBB3zyrJJb3RTaxyY11QqFVqi/cIRwNPbSV5zD/Pyp1DrbWFe3iRGWMrRWWLE8qxEPJ0o5gyk7ApCavt7Csf3QlFANXIsI/7nf4j29qK221AcTmThco+5myLF5UtKPF5EFAQq8tS4enX0tDfhzC7gjR0vY7TYKFuxCp/QSY8/zDdfPs7EYelIgoixvYfFeSZGVJSzbfMOzGGRbl+EUmcB0qRriXYk8LwRYPSUuZjsDtoazqJSqRkzbCR2gxkVAjpnOhkZuSnhmCLFZYYOkQeGXY3aB4pb5Jb0OZyWOzh0ppsn1jYwd0IeV88pZXiOmXtWDOe5nQ2IgsD184qRzB08fPJZAB6a/BXCu934usIYCvVY0uuQnbloRs8ndm4/SiR5cillVxBQx4go3Wg1EpFoArcvwreeP8qXbhhLg7KPN9sO4YsmfRpfaNzONROnUv3mG0AyL6WsS/oTuUIe/N21eMPpOG16Vixw8r8Hnhr0fNvb9jO7ZDySGCcWHRz8RpFlTPZMmgwZPP7IORQFDlfDd28YQb5k+ECLwLjeglBsQYGUiVmKTzzauAf3Kz8m7kr6GXZPLuffVmSSfeQRBElFo3wlZ84kLQqi0Sjbdu4ib9Ui3v4xSSYbRzIzOefvYnneDNI9BsKebkINbv7S3ItNr6ahppO6di8jSqy0hGs42HiIismfIR6L0tlc1z8WlVpD5B2uhZ6wF190sIVEJBIhotYy+fYvE4j14tMovH7uWSYUDyfXaCUeT2A32/rrm81mvD1DfTY7Gs5x9ci7iJvjyMeCRNo7SIw00dN7ioaqvTgycqmYOBet5u+LjCkjINudiHZnah5JkeIikBKPFxEBiAVcKGojpswSMtLtuHs7CPq8NAQ7EfU6rl6ZQ805habWCMumOTAE63jzia1IKjWTpi5EpdaQlZeOImhRQkbCnR0YJznYsuOxfsf1eDhEpqxD++Jaom4XxkWL0CxwEDdcOPR/ihQp/jnkYaU6oOG5/T10ucLMHOVgzqhxuFwisgJvHGrBadOzPDdB1p9/wVdnzgU5QfgPT1Py5QdxTL8PrSKg6lSIdCXFmaZCRU19iJO7/4paq2fK1Osw1Owm0VGLpmAEvqiH9S2b+PQNt1J1PEqHO8TCEVmYTAE2ntg5aHzusBddbjKNhqRSM3LRCl7pPARAlsmJKb2cmcU9XLNgMt2JDsrTipmYM4ZIPIpWpeFA6zESGhlNQkRnMBEODvhhiZKKJo+GN44295cpCpzri5NfTIoUKd6F0tfcLxwBCuwqtHU7SfhdqEcv4EzD0Ejt9X1hsodNJ1a9F6ViCpnaDKKHztHWvg6pZBRjZs4jvLebGyflstftQ+oLsmJeNqZMF6/WJ60IgmE/M5ffwJsbniUWCaPW6Bi17EqeaNvR30+GwUEiODR1RiCg4tdPNTJxZDpL52TxbwUW+p56kYa69dgmVFI4ehU52dm0tbfj9XoZVTIcju8b1EbRiEoMgoWubdUosQQap4FWaji88TUAOpvrqK06yKq7vo5KNzTtT4oUKS4tKfF4EZFlBb1WzeGDRygePglf2MfsVbcT62jjjCHMpuZ9zMlTU2t4i/wJuWijWRzZ/HL//Qdefw7z9Z+l3tPJ2Mw8dHYbxoXFuDpq+oUjQOXI6TQ/9HD/Flz7y68giCKWFVchpw4fU6S4bOgNqvjVK00kzv8wtxzuIp5wsrgyo7/OjiOtTItEibndxF4biKrct30Xw267g/Cxw8RiSf8cyaCmuauRg3uTJ4XhYICtG19ixZpbMFYKdCkaLEYzvoifv9Q8yvfGfQ7VWR3RUz2EHUYEQRhkoTDOWYFZ0rHs1s8T1or8ofplWv2d2PVWbq24kZ+90MZnlpWjllSkq9OoSC/j6ROv9t+/umIJtmCArpc3MvfmW9nx6hOEg37UWh0zl9/AgbahkVFNJl0qr1aKFBdAeVdeQ7uvhnBPbTKPsq8bh7UCr3cggJ7JZMKc5UDJWIU5t5yYOZ2ql58iHExaFtSdOYzH1cWs8usIv9XK/DnpuOznOOKqwVWf9IF06G1oQwlOHdrFqru+Sp+3D4vWSkOkh0BL0nzVprNw/9gb8DX2DBpfZmYW3pBEJJZghANyezuo/elvSASS/fft2Uuko5NF99xJuyMNBTBLOoaNnET1qYMA5JaMoHjkFKI6DZY1FVSf68GSDsdf2Dyor2g4hLurifSClHhM8cnh//7v/2hsbOSnP/3pP3soH4qUeLzIOEx6bBYDh/duIr+ojBatQoEjjfz2JkKxEE69g8r0kXSFe+ioOj7k/tZzx4hmTqNd30ppmp14Qibxjpxwoighuf1DbDe6Nm/GtvAKZO3Q/FApUqT459DpSeCw6Jg1PheNSqSly8/uqg5mjM3tr1OUbUa8QL5FUaMGdy+1v/4to77zYzjhQp2n59TRPUPqtvT18YJchSvk5XOVt5BryqLV38HuwBFmG0agxGT0RyJ8efZd/Kn6RfqCbiozKpihKeHQlleYc8Pt/PbMS3xm7E3EO0OYLWn8/IVamjr9/HrtWb51ayUBMci66i2D+l17djMjTPNJW7OcLa/9lYoJM5BUGhRZ5sDWV5m55jO8vJv+TS2bWcuwfNvFfMUpUnxiEBy5CGotKAqi1kDk7B70JePxHd5ErPEkE5bMp6W9k3g8Tn5hPmljsvjZ0Ufwx4IsLZrFTEHbLxzfprezhdj4KABGr8Sy0ql0+ttxhTyUWfK5ddgy9j39Z8rHTuXhcy9xuqcWh87KVwtu51u5dxOUYqQbTajeeg3tuDXMuyKbgKsLsyCga24htO1FfnLNlWjPPE88PrpfOL5NoK6OaH0j2qZGujduxgdkjh5J6eKb0RbkozNnoAhqFAUEvZqjvX5y4sm1zruJx6KIooCc2iVP8TFj7dq1PPbYY9TX12M0GqmoqOC+++67KG23tLSwcOFCqqqqUKkujay7JL386Ec/YtOmTbS2trJ27VqGDRsGQH19PV//+tdxu93YbDZ+9KMfUVRU9E+5drGIiVr0BiPTpk1DC6hzTHxt72+5OncWXy67lSZXA2MdhWSbZ3Ci9TW63uFjAGAQ1djlKKGYQCLhJyGpMdmdpOcU0tPWiKzIoB0aaEJtt4OU2gtIkeJywmHRsXByPq/srCMUiVOWZ+POFSM505yMBKjXqlgztwybz0jHCy/A2xtFoohjzhyivS4krYYORcY+MYuYL4LBYsfd0zmon6gael1uIokoPz34R7498wE6+5pwhz1ES704M1UoYR9pUQMPjryN7vZzdJ2uorZnK4uuupNETx3usIcXazaxwraGn7xQQ1tvchFY3+HHE4wS0AaG+FUnFBmlIBtUNoI+L0d3vz7oupQI8/3PTOdciwe9VkV5nhWrPmVenyLFhagPmrCs+Aa+zjr8XhfOvBJEUxqanhaiTVUIu/7M1Ys+S3tEjZim8OP9D/ff+1rdDsaMyBvSpihJGNIlNNNjeLJEHn+lm7sWXoNaGyPq8bLv2cdJz85HVZLH6ZNJs/a+sIez6i6KQwUUmBSip1+hLXcODz1TzcpRNoq2PE+os4vg+RRESl831kUVCOqhucAElQpDUTHqcWPRj6ogWFOHvjAfXekwBL0DBVB5egmeOU3M7eb6ESPxp2XTJSzk4Bvr+tsxmK3J50mJxxQfMx577DEeeeQRvvvd7zJr1izUajW7du1i69atGAyGf/bwiMfjH1p0XpKsfwsXLuTJJ58kNzd3UPl3vvMdbr75ZjZt2sTNN9/Mt7/97X/atYtFOCFw7Ngx9uzZgyREqe9tICbHeKb5DR4++QKVWEh75TdEHv0SFUUFqNQDQlBnMOHUWDB6uzGY9Hz3rYf44b5fUh1pYeqKmxg/70qKRkxAU5CPLidnoFNRJP9TtxJXpVJypEhxOSGpVDy9ubo/h2NNi5uDZzqZNtLJv90ykR/eP4NMqxZyCqj4z++QuXwZWStXUPHd/0TJykedno4hPx9fxMPOU08RLYhSPmYyojSwK2+w2AhYtEQSydMFRVFYe24blVEjE3ZvQv3iz3G//hN8B5+gBi/ekIbiWDETyxexcOKdmINRlGgYQRBxhT1sPd3WLxwBbCYtctSLQ2vFqB78h86sNeHMKkVnTcdosQ26ptZoMVgdZNn0zBmTxaTy9JRwTJHifVDLAXatf4Jdm1/myP4dvP7CY1Q3NtE+5g7iy/8foem3sfPIKTzeAPWe5iH37/NVUzZu6qCyCVPnEH3zz7jo5pi3napmHw9t6EDVZsAQtDB/xm1MnLya3555YdB9PUEvD+9t4KWzXoIFC/np+i563GEyCRBubUN5R+7acGsbgsZBwl2LY8qEQe3k3Xg9iYwc0FrQjZiIc/X16MdOQ9A7AFD5+qj5wQ9o+P0faH3uec79139hbD5Hek4RUxetoWTkBMZMX8joqfORVBri70g5lCLF5Y7P5+NXv/oV3/72t1m8eDEGgwG1Ws2CBQv42te+Nqju/v37mTNnzqCyBQsWsGdP0tro+PHjXH311UyYMIEZM2bwwx/+EIBbb70VgMmTJ1NZWcmRI8nUOM8//zzLli1j8uTJ3H333bS2DvhMDx8+nCeffJLFixezePHiD/1cl+SoatKkSUPKent7OXXqFI899hgAK1eu5Hvf+x59fX0oinJJrzkcjov2rIIcZsGUqWRKIsGOLioKczBpjBjVOpY6KvGKJuxXfwN35yliaoVZN91JT1d7UgBasun671+S97kHeKZ2C92BXgB+feDP/Nv0+ygZM4NEIoZKpaHka/9OpLERORhEm58PGTmkptQUKS4v3s41VlFgJ92i43h9L0fOdnPP0nLS860IgkI02Ec8GkaflYH92hv77xWAhMVB/u23caL2CJ0tdfiDvbTWVzNl4WrisShWiwOzWk9nZxMP5i5jrecY9f42cnTpJEyZWBfdh+ztRFapqdMJrO+s4nb7MMKH3ABoSwQinn30lpUT6YwwK2cm7pgJSIbXl0SBe1aUsev5X7Lkpgf40rR7+P3hJ+kM9JBlyuDeCbegx4iigituuJ+dL/8JV3c7Zlsac1bfgVpnR1GUlI9jihQfACHcg6+va1BZzf7XmHJNOT2KCXdPJ8OzsjH4einXWgllTWNdx0DwmfZAD1fNuJrSsjH4Qz7MFjMaOUBvzgJe7j3FKFUuJblW7plRQmxvM0pCQWXSEF6oMNJRBggc7zlDQk4w3JGHo6KDglzoi2rxh5L+mAmVdsjCUZAkRL2BwNGD2IbNxjb2RhJRBW1RKVJOEQkGfJ8TicGTQbihnmhf36Cylif+SvF/fJO2+rN4+7rpbKmnfOxU0keW/+MvOUWKS8iRI0eIRCIsWrToH27rBz/4AbfddhurV68mEAhw7tw5AJ544gkWLlzIgQMH+k8Qt2zZwsMPP8zvfvc7CgsLeeSRR/jKV77C008/3d/eli1bePbZZ9HpPnwKrH+anWN7ezuZmZlI53fQJUkiIyOD9vZ2FEW5pNc+rHhMSzO957XWEzVIGzZSX5UMpy3pdXzrqw8QbeskLVpEuFnEHw6jG1XJC/7t7K59DQGB5dlTsTy1F31RIcH0dHpq3YPa3dt6iAen3zW4s6L8DzXufxSn03xJ+7sUfNKe6ZP2PHD5P9P7zQdpnQa+e814bO0+JF+UNXPLORmJoVfJWMwqTuzbxv7NLyHLCaxpmSy96X7i8Sg1Jw6gKArlY6egMxkI+9xodHpCQT/ZRWXs3fg8zsw8bPpcGl9dDyTF5qfuvIG/WEXGxeyc/fdvoklzoLn9an7VtY1gLMS/T/k0Bncc7bw8BPzIsVa6zWN5oXUft45ezehgHIk9TL5pNp4wOB163nrtYcJBP0FfH2PLZvB9x7/hjfixaE1YdZaBh3Waufoz3yDo96IzGDG+I0T/h+Vy/MwvtzFdbuOB1Jjg/eeDv0VX4+C8rSZbGkUzZhM2eLDoDJQqedT/8Me4AkFcwKiyEoyr5/BM205UooqryhcSO3ic7iefQZFlxEnjqZo7jCdbtzHGOZxinZZh02Xy9S7kOTkocRWCJKCERG7umIUsK1w36grcxjDHdh/G1dtH9ZlTzFu8GkkUSMgKO1pirJo9j+Cu7f3jzFm1GLVJjXX6GsJNVYjOXKqVUg6dUrjKKTIs+70/g453nGC+TTwYxGQwMHPZ9XhdPQiCgMWePsji4m9xOX4X/14+Sc8Cn7zneT/cbjd2u/2i+CKqVCqampr6D73Gjx//nnWffvpp7r33XkpLSwG47777ePjhh2ltbe23Ar333nux2Wx/31j+rrv+xent9b+nzb3Q7cJ3XjgCJEJh/C9uIPeqa+nb7evPbRbtCnLjgisY4yzFqjWT1hVDu6SMrd0Sm56p4/4b7qSutw21RuGoax8One19+/2ocTrN/aconxQ+ac/0SXseuLTP9Pf+QXu/32WhUYN7ay2JmEwCEHqCTJ+YjUol09ZYx95Nz/fX9fR2snv906jUGhrPJoNpaROgd4mkT1pOwDmDrHyRptOHWXj1HZjiEvU/+Mmg/nxPvsSDX32Qpp89BEC0t4/Eb5/k619/gLAco3brZtTFk9Cf1KF1GpDjmWhsIl+afDex5lN0+yFiHEF63xnSes9wotbQfxKiNdro7vYhiv+fvfuOj6LMHzj+mdmWXjZ1UyB0Qm8KqIDSUQQsiKLiqYhd7zzv1NMTRT1PvZ9nP6/o3amcBQtNEEQUAaXX0EuAhPTeNttmfn9EFpYESEI63/frxetFnpmdeZ6ZnWfnO/MUlSA1FGepRm5pDedGDaGiEioq63feWuL3uKXlqaXlB9penhqjPjiXQGsERrOFuMQORETZcHdqx67CfXQq8JClGmDJLjzlJ+darDx4mIH2kYT2uQFbQCSW3GKO/3eud3nZhi30iI/nd31vQKl0se6Tt5lwy/2UVeQREBRA/tfHiRieRP7yU8ZeyCwnakQMISERxHXoi9sDpSVFzLy6O39fsIeNh4oJTu7L5EcGYclPw+BvwJObQsn2PYRf9xQbLUOZ++0BikrTAdi4J5sX7h5K2BmmEjMlJKIYjT7NYGOvvopS3YRWaAcCQYf8gooaP1+TlvhdrK+2VBZo3eWpT50QFhZGYWFhvfoVnu6FF17gjTfeYMKECSQkJPDAAw9wxRVX1LhuRkYGf/rTn3jppZe8abquk52d7Q0ebTZbvfPSbMGjzWYjOzsbj8eDwWDA4/GQk5ODzWbzFrCpljUkZ35BtTT7sTQUxVxtUuyKbXn0uSiO0jQF56ZsAq7swNLvtzN1dDde/WAXlc6q6WyvuXwMQ2yR0klciNam2IHu8m1QXr49m6Du3Sgrzq+2+vHUfQwccaU3eEzoOABXeQCWrAo6WIspX72AJI+boOgQXJX+1UZd1pxO3AdS0SorvWkeu53ArBJKPKV06j6IoIxQXI4K7OlVP+AWJZDUDBc/7w/h+81VfSJCAgN47IZpHP7fn0BRGDhiIoFhMRSUO1m7I5OjWaWM6B9Pt4RQzMYm6TovRJtXYQzk+ptm4di0AE/az/iFqPQyWin+Zi6BgyaTduRYtc/omfkkO/uj+BmoOHqg2vKS9ZuI7ZXMmg1fc/n1d+IJCObTZT8y4hIrsR3DqTxeUu0zHqeRfUVRrFtb1a8yPNjCE7cm8uyvelJQ4iQ0QMVgKIGibJyH9+CJ68Xx9lfhroC/L9iN23OyzrM73KTnlhHWvuYpNvQoG93++BQZX3yBMy+P6HHjCBp4EW653xFtQP/+/TGbzaxYsYLx48efdV1/f38qT/3t9ngoOKVJd1JSEq+++iqaprF8+XIeeugh1q9fj6JUnxLLZrNxzz33MGnSpDPur6bP1Vaz/epHRESQnJzM4sVVo2ktXryY5ORkrFZrky9rSAHt21VLCx/YFwzV2xSrRhXHITeuTdkEdgumdN0PPHpNNxb+eMgbOAJ89cMRCnM9nMd5FkI0A0MNTxoVowomIwE1NOuMimtHUW7VnK4h4VEYi/1wrU3DL7iAwm9ex5l9BFdeOoXff4TBakU9ra+C2WrFbbf7blRVMdqiiTCFEGhthyHI/2T+AkwYewVgd7m9gSNASbmTT1dnM3HmU0y560m6DBhJSaXKs++t56tVh9iyL4e/frKVn3Zlo6pSMQnREEIqyyld8AqOoym4i3Mo++krPAWZmKPbU3lwHeED+1T7jF9UOyr2FmLfW4R/bPWH4YGdOqIFhxPUYQDfrdnMhrUb6d27N7sP7CSgn7XGEVLTgHW7Tva9LCx18PkPh4mJDKdrjAF/1cmSPRqLtaFkXHY/W6yXMm9zKS6PjqWG7RkNZ77V1FHQ4pNIePDXdHz6GfwvuwK3n0w5JtqG4OBgHnroIebMmcOKFSuw2+24XC5WrVrFyy+/7LNuhw4dcDgc/PDDD7hcLv72t7/hdDq9yxcsWEBBQQGqqhISUtVlRFVVrFYrqqqSlnZyEK0bb7yRf/zjH95+kaWlpSxdurTBytUkwePzzz/P8OHDycrK4vbbb+eqq64C4JlnnuGjjz5i3LhxfPTRRzz77LPezzT1soYSEBVK4rTJ3pu6sH59COthwxjgQTX7ttcPuSgOU5yBwG4uctfMI3PBl5CRTk6hvdp207MLcDjKq6ULIVou3eLCEOTbXCukdygOrYJgaxy9hozypvsFBDJkzHWk7tkGQM8+Iyjdkok5IgBH+sZq267c9x3x99yOOaLqAZjFZiNyxjTUKN8HYnE3Xk/+ytXkqyrfrFwGnQy4LwJ9oIH8pGwWf/UahUXVmxHtP1aI4heBJSgaHQNpuWWUVvhOYj5v5QHKHZ5qnxVC1J2xJAvd7fRJK9u9loDOA/AUZRPULgjrkKrRVFWzmYSp0/CUVAVaxl4BZGkl+HdMOrm94CCiRo/jyyVfs//AIdxuN9nZVfNEDh3Yh8/n/glTB3845QGQ6mcku8K37yXAvmOFZBW58Q+Nw9+aSFx7fzKC1/Dq3rdYUvAhkyb6k5pRxIRLOvh8LirMn/iocweDbsWA22ipNh2QEK3dHXfcweOPP84777zD0KFDufzyy5k7dy6jR4/2WS84OJjZs2fz1FNPMXz4cPz9/YmNjfUuX716NVdddRX9+/fnhRde4K9//St+fn74+/tzzz33cNNNNzFo0CC2bdvGmDFjmDlzJo888ggDBgxg4sSJ/Pjjjw1WJkWXK7XOztSnQVUV/IrSyVv2Jn5Jg1FUM+68A1Qe3UbA+PsxmtuhFejgBP/2wdgrsjgw+zmfbQSNHM0/nd04muV7M/fQlPZ0ig8jODiiUct2Jq25nfqZtLUytbXyQOvv8+jcs5XgSBvOXAfuUg9+cX44CtKwdO6CK9AKuovK0nycDjtBoREYzIGU5B0jZd0KuicPRV2vY/A3ERi3k7LtX/ts29LlItYVaNiiE+ic0B2X24ULD0phGWaDEdVkQrWYcQb4systnZ0Hq55ADu3XjS0rfIfl7zLmHt76OssnbUgvG3ddnYzyS9FSjhby6sdbfdbxtxj5ywOX4V/D24b6aonf45aWp5aWH2h7eWqOPo9q1k6KF/6fb5p/EEE9h1OyqWpgrOgbX6V0/16MoaE4soOxHyoEwDnQw/fL/0OffpcR5RcGmobdBFGd+vLZkkXV9nX50D78vOh/BIaEM3z4TZhKq6b68u8Uw87SCv46d4fP+kN72xjW10b3hDB0VeO/uz9hY8Y273KL0cI1EfeybV8+vTpFciy7lPBgC+HBFi7pGYOhCZtOtcTvYn21pbJA6y7PhTTQz7lIZ5UGpOs6TmcoQd0voXzrAso2z6Py6DYMsZ04kHqIT/73ApuPLscSb6Dwu+chzEJghyT8E07Of1m5eQP3Te5BZFjVm0uzUeXWsR3ISduHv7805RCiNQmJDiZvwZOUbXwJ59G/U7D0SbSi7aiBv4zIqJjwC4klJKoDqjkEHQPBkR24bPJdRHXrRehF8bhLHJii+qKYTpnHVTXiSuxD5tED7Nz+ExWlRWSHwEeVW/ivZS/p7YPIj/Rjg5LFEYPDGzgCGIxmTufKTmHqqM7eJqjtY4O5YWRnb+AI0C46mODTBr2YOrIzgZbaj4AohDgzU2R7jNY4n7SQgRMo31M1z1vwgImU7CrFVVTE4bffIbBzqHe9E6HZjm1r+G7dYr7bsIQNG1agagomk+91a7FY8A8JJTqhA5UVZSxd/A4rtrzPhiOLKHWVYrFXcvWlSd4Xkkm2ELokhhERUtXk3a5XsClju882HW4HCXEWdh3O56Nv9rD3SAHfrj9KWJAFozRtF6JNkdFWG5jDomAw9iVyYjsceUewqxayyhxs/2klAN37DKZ8+2coRn+0zDwstlhUg4GYsWPIWLiYhJtuxBwRxJO39ubQ0WzQnOQe38GQIZdgMvlLkw4hWhHNXgiaB81RgeaoGi3Qvn8dgZfdCIbqQdwJnl9agpo6WYkMsVB5uJCIq57EXXwQe1kRdv9wVv3wLYqicOXVv8J18AjG1eu4uk9nUiLcvLLjQ37f4yY6R3ehpMxFnz59SElJQdM03Jhp37U3R/fvBEBRVZL7DCA0th1DethwuD1EBFkwGXxv+EL8jcy+czBrd2RyLLuU4f2qBsyRgbyEaBgOYwhhk3+HJ2Mv7uIcXEGR2E1m1D5j8RgteMI7U7GyBOulPQmeEUCWkkrssGAq0lXUMBMBwaFUlBZ7tzdw+JV4NAPjR49jxQ/fYbfbCQ4OZtIll1C+eQs98lXMfUdzrCKX/fu2MnzsVLKfeRocDgZ27sylU2/lqNufojInneNDiQq1gA4mxUxMUBRZZb5zUhoDypkzayg/bE2nsMTBFQMT6BgbLPO8CtHGSPDYgHQdKkwmnBY7luJATCEDcflVUlawja69B9K5c3dMKV9jju2JHj+U/X9+zfvZ/J/W0f2pP6DHJ6FpOmFBwfTrbqayspK+yZ0wSl8AIVofS0C1JENgKCi+Va+igMVZSEVZIYVFBagmCyFR7cASCjGB+MUH4zqWSkmJkZLgOApyMoiKT6Jv/xHk/uM/2I/90lF+63Z6jRjKwV6d2Fx+lItdQezYso3BfS6i+4Qu5FcU4tE8XNS1M906JOFya4S37445vB26BuGBJuDkWwrNVU5JXjpORyWhkbFYg6KZfGkSqqrgdvuOIiuEqB9FAVdFAUV5GSiKQrAxkrLDR9lu/5mczJMjrMYkdqLX8Bk4UCjrHIuz6DiW797EHJuEZ7PG6MuGc7ywhMKSUjp27UlYSAip2akEWsK58vJx5JUXkhAczLEXX8ZVVFS10c1b6TT1WnredBfs+5ng26/FXe7EGGjB7FeANa4fBkWperP5yy2IweHk7oTx5BZn4wg0Mf/4GtqHJRLtF4XFYuGmkZ1RFKkjhGirJHhsYCH+ZspibBzfv5XMXTvo2m8IXfpdir+jkMqNS/HvdD2VOVCw6TOfz+keD8U7Uwhp3xk0HV0HVbUQEFDVVE3iRiFaIWs7zLZOODMPeZPCRt2O0xDgM3WPxZ5F4fFDLP1mAS5H1VDdgcFhjL/11xj9rFU3YW43We/PJeZ391NkMGA0mKCg6GTg+IuyH9cx7OJbMFojiSKEK7sMp/ynXCq1Uqzdw8gNqUDPOYRxzxqMQKDtUZx69WZlmquMVV/+k5zjqQCoqoEJtzxEUGQHedsoRAPQNR2H3Y2iFbDkg1dxOqoGy/MPCmFYrxH0c4WSGdOO45mpxMV3JHnwKNJLzRSUHqekuIT1+fu4re9wnNu+r9pgdipdh01Fa9eOiqJ8TKqJDpWxlG4pwq1WEt3birsk42Tg+IusBYtJGPBbjrVLJNLpwbJnGQ57GUq/MVjaDcDjOXm9a84SVn7+LvlZVfM4qgYDv7nlfgIjEzDrVd1tqtaXOkKItkqCxwam6xAYGMolo6/iSGJ7So4cpjxrB5UWC9FD7yFn4SH8E2tuxqHr8pROiLbEqQajXHI3ak4qqqsCLSiWyrBOqKdc/waDgvPoDvYdy/YGjgDlpUUcP5RCUq8R6LqOMSaOkF/dwL/zV1NpdmNLiCBGK6txvz1C2vPd0i9oP2Aq9o0nBydw7C4k4dI4dMMvVb9qRA2JrnEbRblp3sARQNM8rFs2jzHTf42unLnJrRDi3MqLHSz5YieKAh0SD3sDRwB7WQl5njKMi1YR6GehT1J7YpL6gr+Vdv5QjigQdQABAABJREFU4mel6GgOA0O7Umn3J/iSbpjCAnD7q5S4VFZ9/Rlul4MJw+6lIqVqQB1d03FszSNkQM23fdsKj/Bh+nf4GS08Ono6QV+/hyWpL06P781KQfYxb+AIoHk8bPtuESNveEDCRSEuEBI8NpLC3Eyc6elUzp1PWWkpisFA6AOdAbAfLyNq+BhKd+8++QFVJWzgQDzyRF+INqO0uJKP/rkHAEVR0fUcuvaE0Vf3QP/lVktRFDz+oRQW7qr2+eK8qnkUPR4dt8WfvK7R7Nu8DICjxceJiw+hc1wcjowM72esF19E6fotdOnUByW/ep4ch0qwhBoxhEQSdeU9VPhH1fiSwFFRfWqgksI8NI8LpYZBd4QQteNxa3z1v22UFlfSoYuVsqKsauuUVpbTd8atVBw7Skjffijx7TjxeDk4OIwe4TYK//shBalHKACMQUG0/93DLPvy77hdTjp064cnzVltu8agSEyhIbiKS7xpQRNG8klRVR/oSreDTzM38+tJD6JHdq72+cry6iNllhTkVtULBlO1ZUKItkeCx0ZSUVKMa0sK7tKqilb3eNC1X94qaDrO3AA63fcbCjasRg30J+Ly4Wixic2YYyFEQyvKr/D+/0Rrg/27cxgxrivGX+Z9dbs1ykxBJHRKJic91efz7br1weOpumVUFIWM8lyf5fMzfuLpu6cTvmEvFUePEtylM57KSrIWLyH67tshqHpzVEukP4H9rsb/4msJiImh/AzDpodFVZ9wvFv/SzCYA9CkkYQQ9VZR6qS0uOp+4PixYoYNH0jWsYM+6yT1GIgxIZnQfoPQNN3n+Y6iGLHk5GJPPeJNc5eVUbhsJRHRcWQfP0JJUR50MEC2777dLhPBt16POS0He+pRAi+9mO8sGWTmnBz85mhpFo7YrqD5Vcu7NSahWlq3/pdiMEm9IMSFQqbqaCR+Zj+cacd90iqO7cUSWzXdhjOnkrI9CjG33QE3TkBJ7ICODGctRFviH1j9DV1EZCAGo2/VW1xcTHlJIb2GXIHRZMbiF8CAEVcSGnFy2H5d1+kYnuTzOU3XcJoNFG7cCJpG1vIVZC2tejOpl5ZSrOZhCD75NkD1MxLQMwa7IRSHWn0wn1MFhNoYe+O9BIaEo6oGkgcNp/tFI9E0qaeEOB8WPyPGX+oAp8NDTl4oPYdciclsweznzyVX3kh4bEd0nRr7FxuNKvbjGdXS7UePEhYaCUB+djrOqEpUv5PvCAyhZir97QS070DY5OuIf+T3lPbpwPKczT7bGRTXFwv+NeY9IDyO0TfMIjA4DNVgoOfFV9C1/zAJHIVoIVJTU5k2bRrjxo1j2rRpHDlypNo6Ho+HZ599ltGjRzNmzBjmzZtXp33Im8dGEhxjI+TiQdjTTvYNyFjwBT1eeBGzGoHmdFPkZ2enM5XkgO7ousyVJkRbEx4ZQLee0ezbVfVU32BQGXt1Mspp854FW2NYs+QTQiNi6D1kJJrmoaK0uOot36lzLQYmcGOvSXy+ewldw9oxLuYiQpQA7J07U/TTzz7b1IICWP3d/7j4sskkxvbAbAnCEO5PpbF2wZ+OijU+mYl3PIHmcWEwB6HXMLCOEKL2DPZSDKmHGTkykeXLjwKwc2s+YyYN4Jq7LwNVwWAKQtd137ERdBf20lzsFeVUEoga077atoMG9cceGeT9+7tl7zPl5sexeAJAUTCE++EyqXg8GppW1Y852hzL7f1vYO6Or3B6XHSP7MykLmPhjA+JDEQm9mLinZ3QPB6M5iCkt40QLcfs2bOZPn06kydPZsGCBTz99NN88MEHPussWrSIY8eOsXz5coqKipgyZQpDhw4lIaF6y4KaSPDYSCx+/lgvvQRXdi4Fa39CMRqJvHIsGzYuxWM2EHHxxaRV5hPsjMMTpKBK7ChEm2OxF9HbvoPuw7vh1A0EauUEHNuOGnupzxuF4Ih4eg8dzc5137F19TcEh0cxZtq9aCceKik6ua4c9hUcwmww89zw35C5ZRObP/4vAJdffg0hpaWU7EzB4O9Pu1tvwZDchZFxMQQEhaGGhuNWTLjrmH9dB1Q/VNVPRnwW4jwZdA95C74id8VK/Dp24rrLr8RuDCKiUwKB1kBUFYq0QvbnbcTuqqRbRCdiTLHgcbFn43J2rF0OgNFkZtjkewmZdC2lSxehu92EXjSQIqsfmqZx9e2/xV5eRmBoBGpQGC6lqh5xAXi00/JkZHyXy+ke3hWX5iLEGIpBO/utYVW94I+qIoGjEHX0w+Y0Pli6h7xCO5Hh/syYkMzlAxum21p+fj67d+/m3//+NwATJ07kueeeo6CgAKvV6l1vyZIlTJ06FVVVsVqtjB49mm+++YaZM2fWaj8SPDYiJSCU0EuHoA7qRVlpERsPbKUwr6pjfEDHJD479jVG1cij4feTaIhv5twKIRqaIy2NwuVLgaUAOIGSgAC69eqD5nfyDYFi8KPn0Kvo1HsIbpeDwJBIMJxsNpbpzODFNW/i+WVE5ns6TmL3j0u9y39YNZ/kPkPoc/X1eAo92I86MRSWYhvdA6dB3hYK0SIUFZD7XdW0GpWHD1F5+E0Agv74FER0plAr4E9r36DcWdVXWlEUHrvkfqzleANHALfLyaYVc4kd8iv6/X4gBs1NpRECyh0Eh0ZiCLcSEF77bCmKQhAhVR2ZpPmpEI3mh81pvDVvOw6XB4DcQjtvzdsO0CABZGZmJjExMRgMVQ+MDAYD0dHRZGZm+gSPmZmZxMWd7BZjs9nIyqo+cNeZSJ/HRqVTkX6MVT/O5+efl3oDRwBPeQUG1YBbc7M67WcMBjkVQrQ5NUy/o2saSg2v8XQMWIKiCQxP9AkcVQMsPfS9N3AE0CorT/uwzp7tP1Nu91CaUoa71Ikjqwy98LT1hBDNR9drnLRZ13UUBfYXHPQGjifSF+z7Bnt5cbXPlBbl0c5qpOTHPArXFGH/oQjPRjtFK9IwVnoatRhCiPr5YOkeb+B4gsPl4YOle5opR/UjEUsj8pj8CE5MIrFd12rL1OBAPFrVF6jYUQyKtP0Qoq2xJLTDEBjokxZ3zRTcAcG13oaOTkml74ioHv/qA/FYo+NRS33fMupOuYkUoqVQwq1YL7vUJ80vzoYp1gYolDvt1T5T4qxqfnq6CFt7NFfNU+bIdS9Ey5RXWP0aP1t6XdlsNrKzs/F4quoAj8dDTk4ONput2noZp0zxlZmZSWxsbK33I8FjI9J1MLXvTL/Bo4iytQNANRjoNmwU68sOedcb1WEYHrcEj0K0NZ6wCLr+8SmiJ4wjpGcPOjxwH8GXDa9T/0HdozC20wiftG9zNjPsmhmYzBYAgsOjGDZ6Os6DZT7rGcKqD7UvhGgebsVI7A3TaHf7rwju3o24666l429/i9uvaoCc5MguKKeNuj6+0xUEhMQwfPIMjKaqYDHEGk3f0TdiCgjEEOQbQBoCTRAk8y0K0RJFhtc8ivGZ0usqIiKC5ORkFi9eDMDixYtJTk72abIKMH78eObNm4emaRQUFLBixQrGjRtX6/0oui7DINRVfn5ZjcNnnyoqKpjcU+ZPMyguKksL0Ss1MtVSPktdilv3MLnbWLqGdMWot+zK/vTytAVtrUxtrTzQtGWKiqr928BT1aY+MBhUwkP9yCuoOOt6Z+JSnOwp2svi/SswG0xcm3wlHQKT0OxluBwV+AWFYdH8qNieRenuXIxBZqwjknBb/c7ahaklfmckT+fW0vIDbS9PjVkfKAoYVAXttKk4dEXjmP0YX+5dQrmzggldRtLb2gOz7oeigLuyCJejEr+gMFCrHgz5OTwUrT5K5fFSLHHBhA9rT6Vf3Ubga4nn7ny0pfK0pbJA6y5PfeuEU53e5xHAYjLwwNS+DTZozqFDh3j88ccpKSkhJCSEl156iY4dO3LXXXfx0EMP0bt3bzweD3PmzGHt2rUA3HXXXUybNq3W+5DgsR7qEzyeoCoKJo+O0+DGo4JBM7aKUQxb8wV/Jm2tTG2tPNB2gscT2z+fsigKuBUXqqKieGq+OTQoYPSAroJLqbF7VYPmqTFIns6tpeUH2l6eGrs+OBtddaOhY9RNtbo/MKJg8GhoBhUXdd93Szx356MtlactlQVad3kaIniExh1ttanIaKtNTNN1HCqgG1E91KOaF0JciHQdDOdooeDRwXOiM4JULkK0SopmxEDtL2E3Om6DUodPCCGay+UDE1tdsHg66fMohBBCCCGEEOKcLsjgMTU1lWnTpjFu3DimTZvGkSNHmjtLQgghhBBCCNGiXZDB4+zZs5k+fTrLli1j+vTpPP30082dJSGEEEIIIYRo0S644DE/P5/du3czceJEACZOnMju3bspKCho5pwJIYQQQgghRMt1wQ2Yk5mZSUxMDAZD1WiFBoOB6OhoMjMzq82Dciaqqpx7pTqs11q0tfJA2ytTWysPtPwy1SV/LbEskqfaaWl5amn5AclTc+yvobTWfJ9JWypPWyoLtL3yXIguuOCxIYSHB9ZqvYiIoEbOSdNqa+WBtlemtlYeaPllqm19AC2zLJKn2mlpeWpp+QHJE9StPmhJWuK5Ox9tqTxtqSzQ9spzIbrgmq3abDays7PxeKom6PR4POTk5GCz2Zo5Z0IIIYQQQghRdy+99BIjR46kW7du7N+/v8Z1PB4Pzz77LKNHj2bMmDHMmzevzvu54ILHiIgIkpOTWbx4MQCLFy8mOTm51k1WhRBCCCGEEKKuSlN+5Nibd3P4hes59ubdlKb82GDbHjVqFHPnziU+Pv6M6yxatIhjx46xfPlyPv30U958803S09PrtJ8LLngEeOaZZ/joo48YN24cH330Ec8++2xzZ0kIIYQQQgjRRpWm/Eje1+/iLskDdNwleeR9/W6DBZCDBg06Z0vKJUuWMHXqVFRVxWq1Mnr0aL755ps67eeC7PPYqVOner2mFUIIIYQQQoi6Kvx+Lrrb4ZOmux0Ufj+X4F7DmyQPmZmZxMXFef+22WxkZWXVaRsX5JtHIYQQQgghhGgq7pL8OqW3VBI8CiGEEEIIIUQjMoZE1Cm9MdhsNjIyMrx/Z2ZmEhsbW6dtSPAohBBCCCGEEI0o/IqbUYwWnzTFaCH8ipubLA/jx49n3rx5aJpGQUEBK1asYNy4cXXahgSPQgghhBBCCNGIgnsNJ/KqezCGRAIKxpBIIq+6p8H6Oz7//PMMHz6crKwsbr/9dq666ioA7rrrLnbu3AnA5MmTSUhIYOzYsdxwww3cf//9JCYm1mk/iq7reoPkWAghhBBCCCFEmyVvHhtYamoq06ZNY9y4cUybNo0jR440d5YAGDlyJOPHj2fy5MlMnjyZ1atXA7Bt2zYmTZrEuHHjuOOOO8jPP9lptzGWnY8zTX56tmPe1MsaojxnOlfQ8s9XYWEhd911F+PGjePqq6/mgQceoKCgoFny3ljfw/poinqhKa+P2mrq70Nt3XfffUyaNIkpU6Ywffp09uzZc17Ho6HO71tvveVz/przGDXlb0ZtORwOZs+ezdixY7n66qv54x//CDT/eWtJWmI9UF8ttf44Hy217jkfLaneEk1EFw3q1ltv1efPn6/ruq7Pnz9fv/XWW5s5R1WuuOIKfd++fT5pHo9HHz16tL5x40Zd13X97bff1h9//PFGW3a+Nm7cqGdkZFQry9mOeVMva4jy1HSudL11nK/CwkJ93bp13r///Oc/60888UST570xv4f10RT1QlNeH7XVlN+HuigpKfH+/9tvv9WnTJmi63rzHquUlBT9zjvv9J6/5j5GTfWbURfPPfec/sILL+iapum6ruu5ubm6rjd/Xd6StMR6oL5aav1xPlpi3XM+Wlq9JZqGBI8NKC8vTx84cKDudrt1Xdd1t9utDxw4UM/Pz2/mnNV8I7B9+3b9qquu8v6dn5+v9+vXr9GWNUZZznbMm3pZQ5Snpr9PaI3n65tvvtFvu+22Js97U3wPa6up64XGvj7OR2N+H+rrq6++0q+55ppmPVYOh0O/4YYb9LS0NO/5a+5j1FS/GbVVVlamDxw4UC8rK/NJb2nf8ZaiJdcD9dUS64/z0RLqnvPREust0TSMzf3msy3JzMwkJiYGg8EAgMFgIDo6mszMTKxWazPnDh599FF0XWfgwIE88sgj1SYKtVqtaJpGUVFRoywLCwtr8DKd7Zjrut6kyxryHJ9+rkJCQlrd+dI0jY8//piRI0c2ed6b+nt4Ns1ZLzTG9VHfPDf296Gu5/XJJ59k7dq16LrOv/71r2Y9Vq+//jqTJk0iISHBm9YSjlFT/GbUNk9paWmEhYXx1ltvsX79egIDA3n44Yfx8/NrMd/xlqol1QP11dLqj/PRkuqe89FS6y3R+KTP4wVi7ty5LFy4kC+++AJd15kzZ05zZ0mcQVs5V8899xwBAQHccsstzZ0V0QK0tO/DCy+8wA8//MBvfvMbXn755WbLx9atW0lJSWH69OnNloeatLR6yOPxkJaWRo8ePfjyyy959NFHefDBB6moqGjWfImm0dLqj/PRUuqe89FS6y3RNCR4bEA2m43s7Gw8Hg9Q9WOXk5ODzWZr5pzhzYPZbGb69Ols2bKl2kShBQUFqKpKWFhYoyxrrHKd6Zg39bKGLBP4nqsT6a3lfL300kscPXqU1157DVVVmzzvTf09PJvmrBdayve8Kb4P9TVlyhTWr19PbGxssxyrjRs3cujQIUaNGsXIkSPJysrizjvv5OjRo816jJrqN6Mu+TEajUycOBGAvn37Eh4ejp+fX4v4jrdkLaUeqK+WXH+cj+aue85HS623RNOQ4LEBRUREkJyczOLFiwFYvHgxycnJzd4EpqKigtLSUgB0XWfJkiUkJyfTq1cvKisr2bRpEwCffPIJ48ePB2iUZY3hbMe8qZc1hDOdK2icc9IY5+vVV18lJSWFt99+G7PZ3Cx5b+rv4dk0Z73QEr7nTfV9qK3y8nIyMzO9f69cuZLQ0NBmO1azZs1izZo1rFy5kpUrVxIbG8t7773HzJkzm+0YNeVvRm1ZrVYGDx7M2rVrgapRJvPz80lKSmr273hL1xLqgfpqafXH+Whpdc/5aIn1ljj7CMWnstvt/PrXv2bMmDGMHz+e77//vm47arLelReIgwcP6tdff70+duxY/frrr9cPHTrU3FnSjx07pk+ePFmfOHGifuWVV+oPPvignp2dreu6rm/evFmfOHGiPmbMGP1Xv/qVd/S6xlp2Pp577jl92LBhenJysn7JJZfoV155pa7rZz/mTb3sfMtztnOl6y3/fO3fv1/v2rWrPnbsWH3SpEn6pEmT9Pvuu69Z8t5Y38P6aIp6oSmvj9pq6u9DbeTm5upTp07VJ06cqE+aNEm/9dZb9ZSUlGY/ViecOtBJcx2jpv7NqEu+brnlFn3ixIn6lClT9B9++EHX9ZZx3lqKllgP1FdLrD/OR0uve85HS6i3xJlHKD7dm2++qT/55JO6rut6amqqfskll1QbjOxsFF3X9QYKeIUQQgghhBBC1GD10Q18vGMB+RUFRARYuanPZIa1v7hR9rVs2TI+/vhj/vOf//ikX3XVVfz5z3+md+/eANx9991MmTKFCRMm1Gq7MtqqEEIIIYQQQjSi1Uc38PeNc3F6nADkVRTw941zARo8gDx1hOLTZWRkEB8f7/3bZrORlZVV621Ln0chhBBCCCGEaEQf71jgDRxPcHqcfLxjQYPvqzFHKJbgUQghhBBCCCEaUX5F9cFrzpZeX6ePUHy6uLg4jh8/7v07MzOT2NjYWm9fgkchhBBCCCGEaEQRATWPhHum9PqoaYTi040fP55PP/0UgCNHjrBz506GDRtW631I8CiEEEIIIYQQjeimPpMxG3wDOrPBzE19JjfI9g8cOMDf//53cnJyuPHGG5k8eTL3338/AJMnTyY7OxuAO++8k5KSEsaMGcPdd9/NnDlzCAoKqvV+ZLRVIYQQQgghhGhkTTnaamOR4FEIIYQQQgghxDlJs1UhhBBCCCGEEOckwaMQQgghhBBCiHOS4FEIIYQQQgghxDlJ8CiEEEIIIYQQ4pwkeBRCCCGEEEIIcU4SPAohhBBCCCGEOCdjc2dACCGEEEIIIcT5ue+++0hPT0dVVQICAvjjH/9IcnKyzzoej4fnn3+e1atXoygKs2bNYurUqbXeh7x5FPXWrVs3unXrRnp6eq3Wv/XWW+nWrRtffvlljcvT09O92xTn9uWXX9KtWzcmT55c68+MHDmSbt26sX79+kbMmRA1kzqjdtpquUTbJNd1dSd+n2+99dZaf+bxxx+nW7duvPnmm2dcp67Huraa65ifKPMLL7zQpPttTjmrfmTTzLtZO+V6Ns28m5xVPzbo9l966SUWLlzI/PnzueOOO/jDH/5QbZ1FixZx7Ngxli9fzqeffsqbb75Zp++UvHkU9TZjxgwAgoKCmjkn50/TNN555x3mz59PVlYWgYGBJCQkcOONN9bpaUxzO1PFv3HjRkJCQmq9Hbvdzquvvsq3335LXl4eQUFBJCUlMWvWLEaOHAlUBaLHjx+v9tn58+dXe8olBLStOgOgpKSEd999l++++46MjAwsFgs2m41hw4bxyCOPYDSe+Sf28ccf56uvvmLGjBk8+eSTPsuCgoK8x6ouysvLufTSS7Hb7ZjNZtauXVun616I+mhL1/Wbb77JW2+9BcDbb7/N6NGjAZg8eTJ79+7lxRdf5Nprrz3ndjp37syMGTNo3759o+ZXtC45q37k0NvvojkcADhy8zj09rsARI8Y3iD7CA4O9v6/rKwMRVGqrbNkyRKmTp2KqqpYrVZGjx7NN998w8yZM2u1DwkeRZ25XC5MJlO1G57W7IMPPuDNN98kLi6Oa6+9lvLyclJSUti2bVurCh5PmDhxIlar1fu32Wyu1ec0TQPg//7v//jwww/p1KkT119/PYWFhWzfvp29e/d6g8cTrrjiChITE71/n7pfIaBt1hkFBQVMmzaNY8eOERgYyBVXXEFQUBCHDx/m/fff5/77768xeDxxjZ1NWFhYvY7Vt99+i91uB8DpdLJ06VKmTZt2xvVPnBch6qMtXtenevPNNxk1alSNN9/n0qdPH/r06dMIuWp4LperubNwwTj24Vxv4HiC5nBw7MO5DRY8Ajz55JOsXbsWXdf517/+VW15ZmYmcXFx3r9tNhtZWVm13r4Ej23cY489xvz583nssce44447AHjiiSf48ssv+f3vf8+MGTOYNWsW+/fvp7i4GD8/PwYNGsTs2bOx2WzAybdZTzzxBB988AGKovDdd99507/77jsSEhL485//zPLly8nNzUVVVbp168Zvf/tbBg8e7JOn9PR0br75Znbt2kXv3r158cUXSUhIqDH/GRkZvPLKK2zatAm73U6fPn14/PHH6dq1a43r//jjj6xevfqMx+NMP3Lr1q0D4A9/+ANjxozxphcVFXn/X1hYyF//+lfWrFlDYWEh3bp149FHH2XQoEFA1du6f/7znyxZsoSMjAzCwsJ44IEHuOGGG3C5XLz//vt89dVXZGVlYbPZmDZtGjNmzEBVVb788kueeOIJBgwYQO/evfnyyy/x9/fnd7/7HZMmTQIgOzubJ554gi1bttCjRw+GDBlyxnLOnDmzVm//br31VjZs2MDMmTPZsGEDu3btYvny5d5mrX/5y1/o0aMHALquU1JSUm0b119/vffprGj9pM7wdaY64/XXX+fYsWOEhYXx1Vdf+fwQHzp0CIvFApz5Gjub9PR0Ro0aBcC+ffvOeU7uvPNOABYuXAhAjx492L17NwsXLvQJHk+0Fvj1r3/N4sWLOXz4MHv27Dln3fbee+/x6aefkpOTg9vtpmPHjtx3332MHz/+rOUQLYdc177OFfAqisLevXtZvnw548aNq3Gdzz//nA8++IC0tDSioqK49tprmTlzJkaj0fubfvHFF/Phhx8CMHfuXP7xj39QWVnJzJkz+fjjjzl+/LjPG06ouu944IEHWL16Ne3atePll1+u9nu+du1a3nvvPQoKChg7dixPP/00fn5+QNVDpHfffZfDhw8TFhbG5Zdfzm9+8xtCQkJ86pZnnnmGt99+mw4dOvDiiy96t71o0SJeffVVysrKuOaaa7zNHnVd57PPPuOjjz7ylvnKK6/kvvvu89Z3Gzdu5LXXXmPfvn34+fkxePBgfv/73xMTEwPApk2bePbZZ0lLS2Ps2LEXXODqyMuvU3p9nWgGPH/+fF5++WX++c9/Nuj2pc9jGzdlyhQAli5dClQ9YVqxYgUGg4Grr74aXdfJzc3lsssuY+rUqSQmJvL999/z1FNPVdvWX//6Vy666CIuvfTSGveVnp5Onz59uP766xk8eDDbt2/n4YcfpqyszGe9f/zjH8TFxZGYmMiGDRt4+OGHa9ye3W7ntttuY+nSpXTr1o2RI0eyYcMGbrvtNgoKCmr8zPbt2/nggw/O+O9MoqOjAXjqqaf43e9+x9y5c0lPTycsLAyoeltw33338emnn2Kz2ZgwYQL79+/njjvu4PDhw97Pvv322xQUFHDVVVfRo0cPUlNTvcfuRGV85ZVXUlhYyIsvvljtgt6yZQtbtmyhT58+5OTkMHv2bO/xe/TRR1m7di02m42EhISzVgb/+te/eOGFF3jhhRe8TXDO5r333iMiIoKrrroKs9nsPR733HMPTz75JF988QV5eXmEhoZW++znn3/u3deF1G+hrZI6o3Z1xsqVKwGYOnWqT+AI0KlTp2pvHU+/xuriXOcEICcnx/sQbM6cOaiqyubNm2vsx/Lmm2/StWtXxowZU6u6LT09na5du3LNNdcwatQoDh48yO9+97sG73clGo9c17W7rk8YPHgwYWFhvPXWW+i6Xm35J598wpNPPklJSQnjx4/HYrHw17/+lXfffbfG7a1fv545c+aQnZ3NZZddxsKFC8nMzKxx3blz56LrOgkJCezfv5/nnnuu2jpvvPEGAwcOxGQy8cUXX/Daa68BsGrVKh544AH27dvH2LFjCQwM5H//+x+/+c1vqm3jtddeY/jw4QwYMMAn/dVXX2XgwIGUlZXx3//+l59//hmA//3vfzz99NNkZmYyYcIEPB4P7777rvd3f+/evdx+++1s3ryZYcOGER8fz+LFi5k5cyYul4uSkhLuvfde9u/fT9++fSksLOSbb74580logyyREXVKP19Tpkxh/fr1FBYW+qTbbDYyMjK8f2dmZhIbG1vr7cqbxzZu8ODB2Gw2duzYQVpaGocOHaKkpITLLrvMGyC89dZbfP/99+Tm5tK1a1d2797Nxo0b0XXdp7nGH//4R66//voz7uv5559n2bJlHD9+nPbt2+Pv709hYSH79+/3qZymT5/OH/7wBwoKChg2bBgpKSkcOHAAf39/n+398MMPHDt2jJiYGDp06ABUfeGPHTvGsmXLuOmmm6rl4cEHH+TBBx+s83G677772LVrFykpKSxcuJCFCxeiqir33XcfDz74ICkpKWzZsoXAwEDvm7j27duze/duvvzyS+644w4WL14MwH/+8x/vOi6XC13X+fjjj4GqSvniiy9mxYoV3H///Xz44Yfcfffd3nyEhYUxd+5cVFWlb9++VFRUkJqaSlRUFBs2bADg/fffx2azYbVa+fe//11jeU7kBSA+Pp4HHnjgrOWfNGkSL7/8svfvxx57jPT0dI4cOcLnn3/O559/jslkYvbs2dWa8X7//fc+f7fVJkwXCqkzaufETWt8fDxQ9bbxyiuv9C4/vW/U6ddYXdTmnHz99dd4PB569uxJ7969GTBgAJs2bWLRokXce++9Ptu7++67vTfqO3bsOGvd9uijj/K73/2O5cuXc+TIEUwmE1arldzcXLZu3XrGN0WiZZHrum4CAwO58847+b//+z9vwH2qE28T+/TpQ1BQEN26dWP//v18/PHHNf7enmgVcM011/Diiy96y1xTM/bhw4fz9ttvs27dOm677Tb27NlTbZ1nn32W0aNHe+8l5s+fz+OPP85HH30EVD34feCBB7z7WbNmDampqT7N1F977TWGDh0K4PMg6PXXX6dPnz5kZWWxceNGdu/ezdChQ5k7dy5Q9Rt/zTXXsHfvXiZPnsy8efN48skn+eSTT3C5XFx77bW8+OKLuFwuRowYwf79+1m/fj35+fmUlJTQvn17/vOf/6AoCtdeey27du2q9Xlp7drderNPn0cA1WKh3a03N8j2y8vLKSkp8bYWWLlyJaGhod4XISeMHz+eefPmMXbsWIqKilixYoX3/NaGBI9tnKqqTJo0ib///e8sXbqUQ4cOAVUVGFQ1IZgxYwYej8fncw6Hg7KyMp+Ot6c/nTpVYWEhkyZNIicnp9qy058MdurUCajqGxceHk5ubi5ZWVneH4UTTgzGkp2dXe1J4bFjx2rMR32bqsTGxvLFF1+wb98+Nm7cyNdff82WLVt4++23ufnmm715KS8vrzEvJypes9nsvQEDMJlM5OfnU1FR4VP2jh07ApCbm4vT6fSu37FjR2/zD39/f8rKyqioqCA7OxsAPz8/b6WQlJR0xnLWddCa089t165d+eabb9i5cycbN25kwYIF7Nu3jz//+c9cf/31PjcSpze5Ea2b1Bm+zlRnWK1WcnJyvP1EwsLCmDFjBosWLar2lBfOfizO5VznBE7enJ64FseMGcOmTZtYuHBhteDx1Lycq25zOp1MmzaN/fv3V8vXmd76iJZHrmtftXnIecstt/Dvf/+bt99+G1X1bah3Ik/Lli3zSc/Ly6O8vLzatk78hp/47T+1zKc78dt9YrCrE/cPpzr9XqKwsBCn0+nNV037ycjI8BnAZ+DAgTWW+8Q9zIlzfmL/J7Z9+r41TSMzM7Pavk0mE4mJieTn55ORkeHtBtS+fXvvPURSUtIFFTye6Nd47MO5OPLysURG0O7Wmxusv6Pdbufhhx/GbrejqiqhoaG8++67KIrCXXfdxUMPPUTv3r2ZPHky27dvZ+zYsQDcf//9PmNXnIsEjxeAyZMn8/e//51FixaRmZlJUFCQ9wZj2bJleDweLr/8cl577TUOHDjgfbN0elONszW12rx5Mzk5OURFRTF//nxCQkK49NJLa+wjd+JHq6CgwHuTVdPr8hNP9Hv27MkXX3zhrWxKSkpqbEYCJ5uqnMmZfjC2bdvmHaa6W7duTJo0iYsuughd17Hb7d68REVFsXLlSu+xqKyspLS0FIPBAFQNUrFnzx5v5e92u7Farfj7+2O32zl8+DARERHe5qxRUVE+x/XUpm6nBmgn+gtUVlaSmZmJzWbjyJEjZyxnXZ1+bjdt2kTfvn29nf4vueQSpkyZgsPhwOPxnHUUSdH6SZ1x0pnqjCuuuIJPP/2Uzz//nFtuuYWoqCiefPJJNmzYUGPwWNemqqc72zk5dOgQu3fvBqreGrz++uvezx0+fJidO3fSu3fvGvNyrrrt0KFD7N+/H6PRyDfffENCQgITJ07k4MGDZzymomWS6/qk2gSPAQEBzJw5k5dffrnaoDnx8fEcPHiQd955x9uHECAtLY3AwMBq2zrxG3706FHAt8ynO/H7eraBeg4dOkSHDh28TcvDw8Mxm83Ex8dz6NAhb3phYaF3P6c3rz/TeTzT/k/ddp8+fbz7UFUVm83mPU8n0l0uF2lpad59n3gwfvToUe/b7Ia8j2ktokcMb9DBcU4VGRnJZ599VuOyU7s6GQwGnn322XrvR+4ALwCdOnWid+/e7Ny5E4DrrrvO27E6MjISqAqennvuOTZu3FivfUREVLXXLigo4MUXXyQtLa3Gp2VQ1W6+sLCQvXv34na76dmzJ507d6427cOIESNISEhg165d3HTTTXTt2pXMzEw2bNjAP/7xj2qd76H+TVXef/991q1bx4ABA4iJifE+CUtKSiIuLg6bzUb//v3ZunUr1113Hf379ycvL4+NGzfyxBNPcO211zJx4kQWL17Mr371K0aNGkVJSQnt2rXj97//PTfddBPvv/8+v/3tbxk2bJi3v9Qtt9xSq/zFxsZy0UUXsXHjRu644w569+7NkiVL6lzO2vrTn/5ETk4O/fr1IzIy0ttk9uKLL5bA8QIgdca5PfTQQ6xdu5b09HQmTpzIZZddhr+/v/dmqbaWLl3K9u3bvX9feeWVNb7JP9s5WbBgAVAVAJ46wmNKSgrZ2dksWLDAJ3g8Va9evc5at11yySWoqorb7ebPf/4z5eXl3htg0brIdV1306dP5/333ycvL88n/eabb+bZZ5/l97//vbfvcEpKChEREd4mraeaNGkSn3/+OV9++SV2u539+/fXauTlM5k9ezYrV670dhs5Md/zzTffzI8//sjf//530tPT2bVrF263m0svvZQOHTqcVz/lm2++mTlz5vDCCy+wYcMGbx/r66+/HovFwrRp05g3bx7z58/H4XCQkZFBfn4+Xbp04eKLL8ZutxMcHMzRo0f51a9+hdls9j70Eq2LDJhzgTi1edOJjvNQFbyMHj0ah8PBpk2buOeee+q1/f79+3PPPfcQFBTE2rVrueqqq7xP2k43a9Ysjh8/zrFjx7j44ot5/fXXa3zCFhAQwH//+18mTpxIRkYG8+fPJzU1lUmTJlVr1nK+JkyYQO/evUlJSeGLL74gMzOTMWPGeF/3q6rKO++8w4033kh5eTlfffUVe/bsYcSIEfTt2xeo6udx3333ERYWxqJFi9ixY4e3aelvfvMbHn74Yfz9/Vm8eDGhoaH8/ve/56677qp1Hv/yl79wySWXkJGRwZEjR7j99tsb9BicaurUqSQlJbFlyxY+//xzSktLmTJlCi+99FKj7VO0LFJnnF1kZCSff/45t912G0FBQSxbtoxvv/2Wdu3acc8995xxMJHT5ebmsn37du+/muZOPaGmc6LrureP87333ss777zj/XdikIwlS5bgdrtr3Oa56rbY2FieeuopIiMjWbduHT179qR///61KptoeeS6rht/f/8af6dvuukmnn/+eRITE1m2bBmrVq3CarWesS/o4MGDefrpp4mKimLNmjVcffXV3kC7PtPlPPTQQ2zatAmn08k111zDr3/9awDvm+MuXbqwbNkySktLmTZtGn/961/rvI/TTZ8+ndmzZxMTE8PXX3+Nqqrcfffd3re4ycnJvPfee/Tr149Vq1aRnp7OVVddxb/+9S/MZjOhoaH87W9/o0uXLmzbto2goCBvs0nRuii6tDsRQgghhBCi0ZSWlnr7EWZlZXHFFVegaZr3oZMQrYW0PxNCCCGEEKIRTZkyhREjRhAWFsbXX3+NpmmMGDFCAkfR6kjwKIQQQgghRCPq2bMnX3/9NRUVFcTFxXHHHXdw3333NXe2hKgzabYqhBBCCCGEEOKcZMAcIYQQQgghhGgj3nrrLbp161bjHL12u51f//rXjBkzhvHjx3tH7a0tabYqhBBCCCGEEG3Arl272LZtm3fuzdO99957BAUF8e2333LkyBFuvvlmli9fXuMcpTWRN49CCCGEEEII0ch2bk7n9ee/Y85vF/P689+xc3P9596sidPpZM6cOTzzzDNnXGfp0qVMmzYNqJrPvFevXvz444+13oe8eRRCCCGEEEKIRrRzczqL5+3E5fIAUFxoZ/G8nQD0HpjQIPt4/fXXmTRpEgkJZ95eRkaGz1tJm81GVlZWrfchbx6FEEIIIYQQohGtXLrPGzie4HJ5WLl0X4Nsf+vWraSkpDB9+vQG2d6ZSPAohBBCCCGEEI2ouNBep/S62rhxI4cOHWLUqFGMHDmSrKws7rzzTtasWeOzXlxcHMePH/f+nZmZSWxsbK33I81W6yE/vwxNO/cMJ+HhARQWVjRBjppWWy0XtN2ytdVyQcOVLSoquF6fq2190NRa0zlvLXltLfmE1pPXlprPpqgPWmrZz6W15hsk782lLeS9vnXCqULD/WsMFEPD/c972wCzZs1i1qxZ3r9HjhzJu+++S9euXX3WGz9+PJ9++im9e/fmyJEj7Ny5k//7v/+r9X7kzWMjMhoNzZ2FRtFWywVtt2xttVzQtst2PlrTcWkteW0t+YTWk9fWks/G0FrL3lrzDZL35iJ5rzJyQjdMJt/tmUwGRk7o1mD7OJPJkyeTnZ0NwJ133klJSQljxozh7rvvZs6cOQQFBdV6W/LmUQghhBBCCCEa0YlBcVYu3UdxoZ3QcH9GTujWYIPlnG7lypXe/y9YsMD7/4CAAN544416b1eCRyGEEEIIIYRoZL0HJjRasNhUpNmqEEIIIYQQQohzkuBRCCGEEEIIIcQ5SfAohGhWqgqa5gA851xXCNHwFAU0zYmuu1AUpbmzI4Q4RdUl6aK0tBS5PEVLIH0ehRDNxuOpZOvWbezZs5ugoCCGDx9BeHgMesub+UKINknTnBw+fIDNmzdhNBoZOvQS4uLaAa13dEQh2g6NzMw0fvppLU6nk/79B9C5c3cMBnNzZ0xcwOTNoxCiWagq7NixlZ07d+B2uykqKmLRooVUVBQ3d9aEuCAoCmRkVN2YOhwOysvLWbHiWwoL85o7a0IIoLg4n+XLl1FWVobT6WT9+nWkp6dKCwHRrOTNoxCiWbjdDnbv3u2Tpus6RUWF+PuHnte2nR6NglInfmYDYYEmkDeZQlSjKJCSsrNa+pEjqURGxuLx6Dg8GgUlDgIsRkLlWhKiyaiqQnr6MWJs8UTHd0HTwV6Szc6dO0lK6oK8/xHNRYJHIUSzUBQDgYGBlJSU+KSbTOfXHKewwsWrH2/heG45BlXhhtFduKJfPEZVntQK4UshLCyMnJwcn9SQkBA0DfJKnbzyv83kFtoxGhRmTEhmaM8YDPLWQ4hGp+s61uh4Nqf789midHQduiaGcv2wwUjgKM5k5MiRmM1mLBYLAI8++ijDhg3zWcdut/PEE0+wa9cuDAYDjz32GFdccUWt9yHBoxCiWaiqkREjLmfRooXetOjoGMLDI+q9TQ343/J9HM8tB8Cj6Xy8fD/dEsNpFxV4vlkWok3RNJ2+fftz+PBh3G43UDV5dGJiO1yazj8XppBbaAfA7dF5f/FuOsaHEhfu35zZFuKCoOtQUGHmh61Z3rT9acXsSrfSJUlBBgdonfZt/Zl1y7+gtCif4LAIhoy9jm79hzboPt544w26du16xuXvvfceQUFBfPvttxw5coSbb76Z5cuXExhYu/skCR6FEM1C1yE8PIbrr7+BoqJCLBYLYWERGAyWem+z0uVh+4Hq/bVyiuwSPApRg4CAMK677gYKC/NRVRWrNRKj0Z/SSjcH0oqqrZ9bZJfgUYgmoKoKB9JLqqVv2pPLVUM7YJQGAK3Ovq0/8/1X/8HtcgJQWpTP91/9B6DBA8izWbp0KX/+858BSEpKolevXvz4449MmDChVp+X4FEI0YwUAgLCCAgIa5Ct+ZkMdG0Xxu7UAp90a4hfg2xfiLZG13UsliBiY4N80v3NBhKjg0nLKfVJtwbLtSREU9A0nQ62kGrpvTpFYDKArjVDpsR5Wbf8C2/geILb5WTd8i8aNHh89NFH0XWdgQMH8sgjjxAS4vs9ysjIID4+3vu3zWYjKyvr9M2ckTSaFkK0GSpw24RkQgJP9pscN6Q9CZEBzZcpIVoho6pw9zW9CPQ7+Yz5mhGdiLXKW0chmkqXhFAGdo/2/h0bEcC4i9tJ4NhKlRbl1ym9PubOncvChQv54osv0HWdOXPmNNi2T5A3j0KINiU61MILdw8lp8iOv9lIVKhFBvgQoh7irf786d5LyCuqJNDfSESwXEtCNKUAs4FZk3qSO7wTqArWIDN+Rnnv01oFh0XUGCgGh9V/rIfT2Ww2AMxmM9OnT+fee++ttk5cXBzHjx/HarUCkJmZyeDBg2u9D/kGCiHaFF2HQLOBDtFBxIb5yc2uEPWk6xBsMdIhJojoELmWhGgOJlUhzupP3y5REji2ckPGXofxtBHljSYzQ8Ze1yDbr6iooLS0qquBrussWbKE5OTkauuNHz+eTz/9FIAjR46wc+fOaiOyno28eRRCCCGEEEKIRnSiX2Njjbaan5/Pgw8+iMfjQdM0OnXqxOzZswGYPHky//jHP4iJieHOO+/k8ccfZ8yYMaiqypw5cwgKCjrH1k+S4FEIIYQQQgghGlm3/kMbbWTVxMRE5s+fX+OyBQsWeP8fEBDAG2+8Ue/9yPtvIYQQQgghhBDnJMGjEEIIIYQQQohzkuBRCCGEEEIIIcQ5NUmfx/T0dO6//37v36WlpZSVlbFhwwZSU1N5/PHHKSoqIiwsjJdeeomkpCSAJl8mhBBCCCGEEKJmTfLmMSEhgQULFnj/jRo1iokTJwIwe/Zspk+fzrJly5g+fTpPP/2093NNvUwIIYQQQgghRM2avNmq0+lk0aJFXHfddeTn57N7925vIDlx4kR2795NQUFBky8TQgghhBBCCHFmTT5Vx8qVK4mJiaFnz56kpKQQExODwWAAwGAwEB0dTWZmJrquN+kyq9Va6zJERNR+LpSoqOBar9uatNVyQdstW1stFzRv2epSHzS11nTOW0teW0s+ofXktbXkszbqWh+01rK31nyD5L25SN6bhsPh4E9/+hM///wzFouFfv368dxzz/ms4/F4eP7551m9ejWKojBr1iymTp1a6300efD4xRdfcN111zX1bhtUfn4Zmqafc72oqGByc0ubIEdNq62WC9pu2dpquaDhylbfH4fa1gdNrTWd89aS19aST2g9eW2p+WyK+qCllv1cWmu+QfLeXNpC3ltLAPnKK69gsVhYtmwZiqKQl5dXbZ1FixZx7Ngxli9fTlFREVOmTGHo0KEkJCTUah9NGjxmZ2ezceNGXn75ZQBsNhvZ2dl4PB4MBgMej4ecnBxsNhu6rjfpMiGEEEIIIYRoLCW7c8hfcxR3iQNjiIWIy9oT0iO6QbZdXl7O/PnzWbVqFYqiABAZGVltvSVLljB16lRUVcVqtTJ69Gi++eYbZs6cWav9NGmfx6+++ooRI0YQHh4OQEREBMnJySxevBiAxYsXk5ycjNVqbfJlQgghhBBCCNEYSnbnkLP8IO4SBwDuEgc5yw9SsjunQbaflpZGWFgYb731Ftdeey233normzZtqrZeZmYmcXFx3r9tNhtZWVm13k+Tvnn86quvePLJJ33SnnnmGR5//HHeeecdQkJCeOmll5ptmRBCCCGEEEI0tPw1R9Hdmk+a7tbIX3O0Qd4+ejwe0tLS6NGjB4899hjbt2/nnnvu4dtvvyUoqOHGZ2jS4HHZsmXV0jp16sS8efNqXL+plwkhhBBCCCFEQzvxxrG26XVls9kwGo3eWSX69u1LeHg4qamp9O7d22e9jIwM+vTpA1R/E3kuTT5VhxBCCCGEEEJcSIwhljql15XVamXw4MGsXbsWgNTUVPLz82nfvr3PeuPHj2fevHlomkZBQQErVqxg3Lhxtd6PBI9CCCGEEEII0YgiLmuPYvQNvRSjSsRl7c/wibp79tln+fvf/87VV1/NI488wssvv0xISAh33XUXO3fuBGDy5MkkJCQwduxYbrjhBu6//34SExNrvY8mn6pDCCGEEEIIIS4kJ/o1NtZoqwCJiYl8+OGH1dL/+c9/ev9vMBh49tln670PCR6FEEIIIYQQopGF9Ihu0GCxOUizVSGEEEIIIYQQ5yTBoxBCCCGEEEKIc5LgUQghhBBCCCHEOUnwKIQQQgghhBDinCR4FEIIIYQQQghxThI8CiGEEEIIIYQ4J5mqQwghhBBCCCFasfT0dO6//37v36WlpZSVlbFhwwaf9TweD88//zyrV69GURRmzZrF1KlTa70fCR6FEI1KVRVQAB00TW/u7AjR4hkMCqDg8WjNnRUhRAtgMCh45PezTdizZw+rV6+mtLSU4OBghg0bRnJycoNsOyEhgQULFnj/fuGFF/B4PNXWW7RoEceOHWP58uUUFRUxZcoUhg4dSkJCQq32I8GjEKLRlFS6Wbcri637chmUHMPFydEE+0m1I0RNHG6N3UcK+W5TGgkxwYwelEhUiBld7hmFuGAdL7SzbN0RSitcjB/Sns5xIRgUpbmzJephz549LF++HLfbDVS9GVy+fDlAgwWQJzidThYtWsR7771XbdmSJUuYOnUqqqpitVoZPXo033zzDTNnzqzVtuUuTgjRKJwenbc+387B9GIA9h0rZPuBXB66vg9GVX74hDiVosCalCzmfrMXgN1HCliz/TjPzxpKWICpmXMnhGgOWcWVPPPPdd63jtsP5PHozQPokRjWvBkT9bJ69Wpv4HiC2+1m9erVDR48rly5kpiYGHr27FltWWZmJnFxcd6/bTYbWVlZtd62DJgjhGgUucV2b+B4QsrhfPJKHM2UIyFargqXxpffH/RNq3STllPWTDkSQjQnRVHYcTCvWnPV+asOIY0RWqfS0tI6pZ+PL774guuuu67BtwsSPDYOBUor3WTll6PIGxZxgVLO0KxGlWtCNABFUbC7NErs7jZxI6VQ87Uh14sQFy5DDde/0aBWVRincXp0iuwu3NI3ssUKDg6uU3p9ZWdns3HjRq6++uoal9tsNjIyMrx/Z2ZmEhsbW+vtS/DYwCpcHr74MZVH3ljNA698z7eb0nHKoAfiAhQV6kefzpE+aRf3jCUi2NxMORJtha7D9tQCnnj3J379+o/8bUEKJZXuc3+wBQswG7hxTFeftNAgM4nRQc2UIyFEc9J1nT6dIzEbfW/Vr728M8op8aGiQEahnTn/2cAjr6/m+f9uIrvYgXSLbHmGDRuG0ejbY9BoNDJs2LAG3c9XX33FiBEjCA8Pr3H5+PHjmTdvHpqmUVBQwIoVKxg3blytty99HhuQosC2A3l8vTYVAI/m4X/L9xEfFURyYmgz506IpmVSFe66uic7D+eTkppPn06R9OxglY7+4rxlFVfy2idbvX9v2pODv8XI7eO7N2Ouzo+m6VzcLYqIWwbyc0oW8VGBXNQ9mhAZYEqIC1Z0iIU5s4bw884syirdXNbHRmJkoM86ZQ4PL36wiXK7C4Bj2aW8/NEmnp81FH+TvCNqSU70a2ys0VZP+Oqrr3jyySd90u666y4eeughevfuzeTJk9m+fTtjx44F4P777ycxMbHW22+yXyWHw8Gf/vQnfv75ZywWC/369eO5554jNTWVxx9/nKKiIsLCwnjppZdISkoCaPJl50tXFFZtPV4tffPeHHolhcuw6+KCE2gxMLRHNJf2ikXTNBk1UjSIrLzyamlrd2QybVRXAlrxzZLJoNI9IZSe7cPRdV2mthHiAqfrEB3ixzXDOhAREURubvW+cXlFdm/geEJhqYOCkkriIwKaKquilpKTkxs8WDzdsmXLqqX985//9P7fYDDw7LPP1nv7TfYr+8orr2CxWFi2bBmLFi3i4YcfBmD27NlMnz6dZcuWMX36dJ5++mnvZ5p62flSgE7x1d8wto8NRtMkcBQXJl0Hj0cCR9FwggKrN32OiwzEZGgbb7U9Hk0CRyGE19nqg6AAc7UmqkaDQqC/jNIsGkeTBI/l5eXMnz+fhx9+2DuIRmRkJPn5+ezevZuJEycCMHHiRHbv3k1BQUGTL2sIuqYz6qJEQk65sYmNCKRv50i5cRZCiAaSGBXIgG5R3r+NBoWZk3piksFlhBAXmPAgMzeN6eaTNmNCskzxIxpNkzRbTUtLIywsjLfeeov169cTGBjIww8/jJ+fHzExMRgMBqDqNWp0dDSZmZnout6ky6xWa4OUNSLQzHN3DeF4XjkWs5HoMD8CzYYG2bYQQgjwM6rcdXVPMi6poKLShS0yEGuQmTYx7KoQQtSBClzeP44eSVYKSiuJCPUjOtSvubMl2rAmCR49Hg9paWn06NGDxx57jO3bt3PPPffw+uuvN8XuG1xExNlHv4sCOibWPMJRWxEV1bDDCrckbbVsbbVc0LxlO1d90Jxa0zmvT14TbE0/EFlbP6bNobXkszbqWh+01rK31nxD2827LTqkCXNSd231uF+ImiR4tNlsGI1Gb3PRvn37Eh4ejp+fH9nZ2Xg8HgwGAx6Ph5ycHGw2G7quN+myusjPL6tVf5SoqOAaOze3dm21XHD2sikKVLo07C4PwX7GVjVq6IV6zuq6nfqobX3Q1FrTOW8JefXoUFrpws9kwN+k1tjVoCXks7ZaS15baj6boj5oqWU/l9aab2jbeXd6dCocbgItxhbX/7stHHcJIE9qkj6PVquVwYMHs3btWqBqxNP8/HySkpJITk5m8eLFACxevJjk5GSsVisRERFNukyIs1IgNbucp/+1nkdeX81Lc7eQX+Zs7lwJIRpAYYWLVz/dxiOvr+apf6zjQGbrvMkRQlx4vPM8vr+BR95YzQsfbCK7uFLmeRSNRtH1phnKJS0tjT/84Q8UFRVhNBr59a9/zYgRIzh06BCPP/44JSUlhISE8NJLL9GxY0eAJl9WW/LmsW2WC85ctqIKF4+9sxaX++SouQnRQfzxVxe1ikE6LsRzVp/t1Ie8eTx/zZlXtw6v/G8LB9KKvGkGVeGl+y/FetqornJMG15Lzae8eTyz1ppvaJt5L3d6ePxvP/lM1xEebGlR8zy2heMubx5ParJ5HhMTE/nwww+rpXfq1Il58+bV+JmmXibEmeQU2X0CR4D0nDKKyp1EBVuaKVdCiPNVWuH0CRwBPJpOdkFFteBRCCFamrximedRNK2W8UhCiBYuuIb5kvwtRvxlJF0hWjWL2eAzvdIJQQESOAohWr4gf5nnUTQtCR6FqIWoUD8mXtrBJ+2uyb0IkcpZiFYt0Gxk1uRePjdfoy5KJDbMv/kyJYQQtSTzPIqm1mTNVoVozYyqwqRLk7ioRwzFZQ6iwwOICjG3yL5uQoja03WdHu3C+PN9l5JdUEFIoJnY8IAWN1qhEELURAWuOGWex8hQf6JCpTuNaDwSPIo2R1UVVFXBfVofxfNlVBUSIwJIlD4EQrQ5UcEWooItKAoYDCoej04TjScnhBDnxaAoxFn9ibO27RYTRqOKpuny4L6ZSfDYCByKnbzKPPJzzYSoYZg0eQLUVNz2Ao7s3Ux+5jE69hxEZHxXFGPbrkyFuJBVKhXkVuZhUk1EWiIxavVvqqW5ysk+uoej+7YT264ziV37YrCENVxmhRCiMSg6RVohxY4SwiyhhKlh6HrbaT2hu+3kHT/A4V0bibC1I6n7QIz+Ms1ec5HgsYGVUMTbG/9NekkmAD2iunJ772kEIEP8NjaPs4RvPnqd8tJCAI7s3c7Ay6+my8AxNU74LYRo3Yr0Av667h/kVRQAcHF8P6Z1m4IfdW8doCgedv60hL2bVwNwdN92Dmxfx+gbH0QxSmsDIUQLpejsKNrJv7b8D4+uYVAN3DdoBsnByW3i3kdR4MD21WxZVTVH+5G929m7eQ1XzngU1Sz31s1BBsxpQIoCP6dv9AaOALtz97O38IBM1toESvIyvIHjCdvWLMXjKGmmHAkhGo2qs/TQSm/gCLDh+DaOlB2r1+ac5UXs3bLGJ60g5zhlRdnnlU0hhGhMxVoR/9r6MR69qquOR/Pwj81zKdGLmzlnDcPjKGH72m980spLCinOz2imHAkJHhuSqpOSu69a8oGCVFRVDnVjq+kBm67XnC6EaN1cuNiTd6Ba+vHSLJR6Pa3TqfExvVQgQogWrMRRikfz+KQ5PE5KnWXNlKOGpVNz1Syaj0Q0DUjRVQba+lRL7xHVFY+nYQdvEdWFRtjwDwrxSet76ViMlpAzfEII0VqZMTEgtle19Pah8fUa6MYcYKVL3yE+aWERsQSFR9c7j0II0djCLKGYDb59vf1NfoSa28a9j9ESTJ9LxvikBQSFEBpha6YcCenz2IA0Teei2P7syT3gfQN5WbuL6RzSsZlzdmEwWEKZcMuvObxrA7nHj9C57xBiErvLE6tzUBTILXFwOKMEg0GlY1wI1kCTHDfRoumawqikYRwqPMrhwmMoKIztNJzEwMR6vS3UUek3fBIxCZ04vHsTcUndaJ88EMUYWKftKArklzk5nFGCrkPHuBAig81yPQkhGkWwGsL9F/2Kdzd9iN1dSaApgPsv+hVBSkibGDFa1xU69x9BYFg0R1LWE25rT6feg1HbSHDcGknw2MACCWZW39socBYQ4GfGXwtC1eQwNxVTQCTJg6+il0HF5fKc+wOCzMJKZv9rHa5fpjYJ9Dfx7J2DsQaZmzlnQpxdMGE8PHAWBc5CTKqRcGM4aPVvUKOagkjoPpikXpfg8Wj1Gg4+p8TB7H+uo9JZVf/4mQ08O3MIUSEy6rYQohHoCl2DuvLs8EcpdZUTbApqM4EjVE2/tim1gn8vLqdD3CXk76gkPDWNB6da8TdKA8rmIEe9ERg0I1HGaJLCEyVwbAaapkvgWEuqqrDk5yPewBGg3O5i8/7cevYbE6JpGTUz0cYYwtWI8wocT9B1cLk89QocVVXhx20Z3sARoNLpYdW24xgMcj0JIRqHpukEEkKsyUYgwW0mcAQoq/Tw3693Y3e42Z1aQHZBBXuPFpKRV97cWbtgSfAoxAUur8heY5qqys2uEHWhqgq5NVxP2QV2eRgjhBD14NY0KhzuaukOp7wkaC4SPApxAdM0nXFD2ldLH9wzVgZ5EqKO3G6NKwbEV0sfNSgBt1uuJyGEqKtgfyOX9o7zSTMbVWyRdeuPLhqOtKkU4gKXnBjGrCm9+PKHg5gMBm4c05X2UVIpC1EfHW0hPHB9X+atPICu69wwqgud4mRgByGEqA9FhxtGdSY02MLqbceJjwrilnHdsAaa21Tz3NZEgkchLnBmo8rQ5BgGdIlEVRRMBkVGhhSinkyqwsAuEfTuaAUdzEa5noQQ4nwEWYxcP7wjVw1tj9moooIEjs1IgkchBLquYzaov/y/mTMjRCun61VB5In/CyGEOD+6ruMno6u2CHIWhBBCCCGEEEKckwSPQgghhBBCCCHOqcmCx5EjRzJ+/HgmT57M5MmTWb16NQDbtm1j0qRJjBs3jjvuuIP8/HzvZ5p6WUNQFCiscLHzSCFrth2ntLL68MJCCCFqRwdyShxsO5zP/owS7C4ZtVQIIS4kmq6TVVzJtkP5HMwspVLm8m5WTfrm8Y033mDBggUsWLCAYcOGoWkav/vd73j66adZtmwZgwYN4i9/+QtAky9rKDnFDp76+8/89ZOtvPThJma/t56iCleD7kMIIS4EigIHM0v5w9/W8sZn2/nzB5t464vtEkAKIcQFQlEUdh8r4g9/+4k35m3nT//dyL++3oNDpj9qNs3abDUlJQWLxcKgQYMAuPHGG/nmm2+aZVlDUA0Ky9Yfw37KZKZFpQ627s+VCaKFEKKOHB6d9xamoJ0y6MyeI4Wk5ZY1X6aEEEI0mQqnh38t3OWTtmVvDhn5Fc2UI9Gko60++uij6LrOwIEDeeSRR8jMzCQu7uTEn1arFU3TKCoqavJlYWFh510+XYe0nNJq6Zn55aiqgscjw+4JIURtuT0aecWV1dIrKqU1hxBCXAhcHo2Scme1dPkdaD51Ch43btzIJ598wrFjx3jrrbeYN28ew4cPp0+fPuf87Ny5c7HZbDidTl544QXmzJnDmDFj6p3x5hQREXTGZWOHtOdAWpFP2pDecVitbWvS9aio4ObOQqNpiLJpHheKakBRWs6YVHLOGsfZ6oPm1prOeU15dbs9XD4ggZWb0rxpqgLtbaHNVrbT96trHtB1FEPLm/mqtZz/1pLP2qhrfdBay95a8w1tO++a24lqNDdRbuqmvsc92OlmUHI0m/bkeNOMBqVJfwda83emMdT6127FihU89NBDaJqGoihERETwySefsH//ft54441zft5mswFgNpuZPn069957LzNmzCAjI8O7TkFBAaqqEhYWhs1ma9JldZGfX4am1fwWsWe7cG4a25WvfjiEyahy09huJEYGkJtb/Y1kaxUVFdymynOq8y2bSatAP76Tiu0rMFrjCeg3FkdgXLPP9SbnrHbbqY+z1QfNqTWd87PldcqwjqDDqq3pRIX5c/vVPQnzNzZL2U7Np4KOpfQoZZuXotlLCRowHi26G27F0uT5qklrOf8tNZ9NUR+01LKfS2vNN7TdvPs5C3DsW0Plke34dxqIqctQHKbwJs7hmZ3vcb9lXHcsJiM/78zAFhnIzEm9CLKoTXIuT+RdAsiTah08vvPOO4SHh9OxY0c2bdqE0WhkwIABbN++/ZyfraiowOPxEBwcjK7rLFmyhOTkZHr16kVlZSWbNm1i0KBBfPLJJ4wfPx6gyZc1FD+TyrhBCVzWO47AQDO4PS3yxlI0PEUBz4E1FK/6HwCOjANU7FtH5E1zqPSLbubcCdE6BVkM3DK2K9de3hGjQcViUJr9YQyApew4uZ/MAb1q0AZH2m6sVz8Mtv7NnDMhxIXErNspWvoGruwjADgzD2E5mkLghIdx0TIeZp2vED8jd1zVnZtGd8FkVDGpStVQ3KJZ1Dp4TE1N5eqrr8bPz49NmzYBEB4eTlFR0Tk/m5+fz4MPPojH40HTNDp16sTs2bNRVZWXX36Z2bNn43A4iI+P55VXXgFo8mUNSdPA36QSEerfap9wibozu8vIXzffJ013VeIpSIO45g8eHR4Nj0cnwGKkRdx9C1Fbuk6AyXDiv81OURScaTu9geMJZRsWEjSlFy7dVL/tqgrlDjcqCgEWgzx4FEKcW0m2N3A8wZG2m+CyXAhK8F1XgXKHB6Oq4GcyoLeECrWWFB0CzIbmzoagDsFjVFQUu3bton//qqeqRUVF/PTTT8TGxp7zs4mJicyfP7/GZQMGDGDRokUtYpkQ50VRUAzGag/Dmrvfo6brrNl2nH8uSKGozMHIgQlMuqwDQZaW10dLiNZBB0P1AFExmID6jaxtd3lYtS2DBT8exmhQmD6uG4O6RVc9YRdCiDNQ1DPcY5x271Hh9LB0/VGWrTtKoL+J267sQe8O4RhkNgBRR7W+qx07diy7du3i448/BmD48OGkp6c3eLPPtkKVH/wLjtMQROiwaT5pakAIakS7ZspRlayiSl76cBMFJZVoms6KjWks25CG/F6IC01D1cu6DubEXigm3yZhwUOuwaXX/aGMosDOwwV89t0BHC4P5ZVu/rlgF6mZ0nJFCMFZp3vTgqLx69DXJ82/+1C0wKhTPg8/7sjk67VHcHt0isucvPHZNjLy7Y2WZ9F21fpX7oEHHiAjI4MlS5YA4HQ6mTBhAvfcc0+jZa41UhUdS/FRKlO3kW804Z/Uj8qghFbVNEDUj67r0G4QEdeGU3lgI8bwWMxJ/ak0RzRrvtJzqs+J9/3mNK4a2h4/Y8sZDVZc2IweJ1p+LrqmYYiMxm1suL46Js2OkncIR9ouTJHtMMR1P+/BJBwBNiKnzcZxaBOavRS/rkNwh7Wv38YUhe9OGVH2hI17s0luF4bHI5NhC3EhUhSwVGThPLaTfFcFfu364gxJRONk802X4kfQyDsJyMnAmZ+HOTIaJcqGk5OtIxxunZWbjlXb/oH0ItpFBbSI7gCi9ah18Ojn58err77KU089xfHjx4mPj8dqtTZm3lolS8FBcj5/0dsXRlm/gKipT2EPbt63T6JpuBULRPbAFNMLTdOpbAE1cnBA9WG7Y8IDMBnk1aNoGSpzcsl8/30K128AIDi5O4mzZuEOPv/fGFUBz56VFK+d500zRScRcvWjOA31n2ZF13UqA+JQ+07GqIDjPObxVRRIjA6uNs1TfGSg9HsU4gJmqcgi79Nn0J2/zHf703yipv6ByvAu3nUUdOz7Ujn89jtoDgcGfz86PvQQhm49vfWHyaBgiwgkr8h33lxriJ8EjqLOav3aYdWqVXz00UeEhobSu3dvQkND+eijj/jhhx8aMXuti8moULp5qc8gCrrbSeWBjdKM9QLj8Wgt5m1z+5gguiSGef82qAozrkqWfg6ixSjavt0bOAKU7tlL8fp1DVJvmpwFFK/7yifNlXMEijNq/kAdaZqO5zwCRwDNozNucDsC/E4+z40I8aNfl6gWU48IIZqWooDzWMrJwBEAnZJ18zGpHm+KoTifQ2++heZwAOCxV3L4jTdRiwtObguYNrorplNaGyXGBNEpLqSxiyHaoFq/eXzuuedo164dt9xyCwAGg4FVq1Zx5MgRLr/88sbKX6ui4kFzVlRL99hLsRhUNM1Tw6faFkVpGaMhipMCzAb+8KuL2Xe0gEqHG1tkIFEhFhnmWrQIBoNKwY6UaunFm7cQOnYCWg0D0NSpntE08NRQ93rcdcxp44oOtfDC3UNJyynDoCokRgUR5CeDWglxoVIUBd1VvU+i7ij3qQBdRUXoLpfPOh67HXdJMQSfbJ4fb/XnxXsuIT23HItJJTE6SEYvFfVS6zePOTk5xMfH+6TFxsaSnZ3d4JlqrVyagYDuw6ul+3UciMvV1gNHD+WFaRze/gNZhzfjqSxq7gyJU0SG+dM1LoQ+HaxEBUvgKFoOTdMI7d2zWnpIv35op/1Eaa4y8o7t5ODW7yjOOQSa45zb9/iFE9DjUp801T8YJTzu/DLewHQdQv1N9GofTnJimASOQlzgNE3H0r4Pp4/gHHTRRJ+BuYxhYShG3/pC9fPDGOL7VlHXwRpkpk+HcLolhErgKOqt1r9OMTExrF69mvz8fCIiIsjPz2f16tXExMQ0Zv5aFU3TMcZ2I3TYDOwH1qKoRvy7j4Cwtt3fUVEgP30/3376N29acFgE427+NQZLaDPmrOVRceN22TEYzehK25i8V4jzoesQ1rcvof37Ubx1GwCBnToRNvQS3Kf099M9dlYv/DdZRw940y4ecx0d+4w461tIt24gYMhUTBEJVOxZizm2E4EDJlChmMFdhmoKktYSQogWyRmcSNQNT1G6YT5aZTlBgyaix/bwWUcPDSX+jls5/u+P0F0uVLOZhJm3oYWEyoNi0ShqHTyOGDGCjz76iFGjRmGz2cjMzMThcHibsYoqzoAIjJ2HEhybjNFsxmkJwtmAowa2SB4H65d/7pNUWpRPYU46kYkSPJ7gtuezccUXHDuQQnh0HJddNZ1Aa3vp0yQueH4x0cTffS+23Jyq0VajonGb/X3WKSvM8gkcATZ/v4B2Xfud8yGVwxiK2nMCwT1Goek6+3ZvYNP3C9E1jf7Dr6RDz6EoRv+zbkMIIZqahkplWCf8x/+G0GAL+cWuautUlOSxatcq+tx2PUa3hsuo8N2mbxjduROWoOhmyLVo62odPD744IPs2bOHzZs3k5qaCsCgQYN48MEHGy1zrZVq9AejAdVkQjG2/UFJNN2Dw15eLd3jOneTsguFojtZvfC/5Bw/AkBhTgZLP3qDyXc9idHv/KYMqHUecKN7XChGf3nTIpqdRQO9zIliUvE4PVVTc9gSAaipN6LHVf2myeN2o2luatP4StN0NEwUHN/Nz9985k3f+N18AkPCienQv9pnVFVBc1egKEZ0xVRtuRBCNAW3pqKa/YDq9aDbaaekMI81P33tk+5xV1ZbtzVTFNDddhSDCb324YtoBLU++idGV921axfp6ekkJCTQs2fPs05ceiGyuDQKvz2MM7cqmPJrH0bIZe1wtuEg0mAKoNeQUWz+YZE3TVUNhEXHn+VTjUNVwFThwVNsRzEZUcItOFvASLeV5cXewPEEt8tJaWEO4bbGDR4VRSHjyAF+XvY5hTkZdO4zmO6DrsBgllHWRPPwc2jkfb0Pd6kTgJDeMVj6xeA6y7UabI3B4heAo/LkoGRJ3fth8Q+jtrMgGgwqh3dtqpa+b+ta4joP8Bk1VXdXkLp3Ezt/XoElIJCLRl9LeFjvWu5JCCGahtniT3B4JKWFed40a3QcJlPbafXmcZawb/MPHNixnvBIGxeNvoaAMJlDvbmcNXjMyMggKCiIkJAQMjKqhjW3Wq3e+R0zMzMBiItrWQMPNBdVVag8UOANHAEqjxYR2NmKkhjcZt/2aBp07HMJRpOZ3ZtWERwawcArrsYvOLrJy2wsdJC9cK+3nb8lLpjQkR1wNvOchkazBZPZgsvp+zbW7BfQ6Pt2VuSx8P2/4HZV3ainrPsOe3kJF4+9GU2v9ZhZQjQIo6pQsjHdGzgClOzMJiopDKx+Z/6cXygTZvyG7auXkJtxlE69LqJLv8t8Jss+F13XCY+OB3wDSGuEDaOu4Pml4lAUhWP7t7Dul+b45aVFLJv7JtfOehxTkPzeCSFaDkVX6T34CjKPHST3+FFiEjsSFd8etQ51Y0umKBpbVy3g0M6NAGSWl7Lkg78yaeYTmPwjmjl3F6azBo+jRo3itttu4/HHH2fkyJE1vmVUFIXdu3c3WgZbEwNQkVVKSN9A3OW5KIqKwS8SR3YZlvaheDy1fT7e+qjGQDr2vZyknkNQDEZ03dDkgaMZhcIfjvh0EHdklKIXVUJE8/ZnMlpCGDp+Gj8u/MCb1qXvUAJDG3/AqZL8bG/geMKhlE30H341BktYo+9fiFOpbp3K46XV0j3FlWcNHnUdLEExDLnyNjSPE9Xoh1bHKlXTdJK69mPXhu+xl5UAYPELoGN8f/RCO4T+8qRec7Brw/fVPp9xZD9JveNqrNsUBdS8LBzHj6OazZgT2+EOlD7fQojzYywrwpl2jJzdHoyx8WgRMT5v3AIJoSy/iPKSIhI6JZOXmUZ4SCyBBNMWGq66K0s4lOL7wM/tclKSn01EggSPzeGswaOu6z5f0JpeD8sr45M8QGAnlf1/eQmPwwm6jikslK6PPIarDQeOJ2iaDqoFg8OOOysDzeHAHGvDExLeJIGkoum4Sqv3s9SdzT9Niq6DrVN/rr7TRllBLn5BIQRb40A1n/OziqJQ4fTg8mgE+xlrmPXu7Izm6k1XzBY/FFX6DIim5zEo+LcPpXxfvk+6Mcwf5xk+cypNVzHaHTgzD6MaTRhtcbgtgbXef4ApnDGX3kmZXoiGToghHNfGCrQJOqUONwZFIcjPSEBwKCUFuT6f9Qs4cwsS5fgR9s55Ht1d1WPTLyGejo8+ijuoafo0C9EUnJpOek4pRnQM0m2p0RlL8jn44p9x5lbVRarZTLfZf8QTk+hdx2Aw0V5Pxta7E3ZXKUmxfTBlm9rMb7yiGjFb/HBW+s55aarh3kY0jbN+s/bu3Vvj/0XNFHQKt6zDfMdUsoJ0DEBMoYfSg3vwj4u7IAJtY0Upx9/7J8XbdwBgCAig61NP4mmC/o9uo0JQchRlu3J80g2hfjUOwNHkFAMBofEEhNb+WGg6pKTm8/7i3ZRWOBncM5abRncluA5zwIVYbcS260zWsYPetCHjpmK0BFcF/EI0IY+uEzwgDmduBa6CqpuBsIFxEO5HgZZHWkk6BtVAu+AEQpSwap83FmRx4IU/4SquenMY2KUz7e9/AHdQ9XVr3L9ZRclRMB2ratLloBStdwwfbzvO8g3HMBlVbhrTjQGjb2Tpv/+E/svrzYDgUOI6dKWmR1EGzc3xTz/zBo4AlenHsR86iKnvRbU/OEK0UIqikJZXzt++3EFmfgWdE0KZNbk3kcHnfgAq6kdRoHzPbm/gCKA5nWQtXEjsrHvx/NLtRAtQCUkKJ39NBv4uPxSzh9DhMegBRlpDfyk75aSXH6fEWYYtMIZYSyyqfrLJrdESzJBxU/lxwcmWWzGJnQi22poju4JaDpjjdruZMGECl112GbNnz27sPLVaiq5TOrAz/5f6Ja7CqhGxgsyB/LbDFAJVxWcwhrbKcTTVGzgCeCoqyPjsM+LvfxC30rhPwTyaTmC/WNB0yvbmYgwyYx3RAVdA6336llVk57VPt3n/XpeSRZC/iZtHd631wwjFGMDYG+8m48ghykuLsMbEExQeL4GjaDaVZpXwiV2h3IViUgmKDWZvXiovrHkDl+dk3fnEJQ8Qpp5slmRAJ2fJUm/gCFB+4CD2/fswDRhcq327dQgb1p6SdWlUHCrEzxbMelVj6bqjAHicHv799W7+cNtFTLrjcfKzjmIyWbDakrBGx5GbW73JreJ2UZmdXS3dVVCIWWkV929CnFWJ3cWf/ruRyl9a8hxML+bVj7fwzJ2DMTfzmAJtlaIoOHNyq6VXZmSieNzelkvuwlwO/e0VbOOuRrUE47EXcODNf9P58ScgLLKps10nDsXOv7Z9xN78Q960ewbeSp+wPt57HE3TsXXsx1W/iqYgO53A4DDCY9qhGBt/zAhRs1rdVRuNRjRNo7KyLbSebjy6QeGHigPemx+AMmc5u5V8Yi6QG/VTn5CdUH44FZwOsDR+EOcwKliGxBM40IauKrjUxrlxUxSlSd4kZ+RVnwJl9bYMrhneCX9T7Qe7CQmPxOG2IL0DREvhVICgqukvglSF5YdXVas7t2encHnc5d5rTfG4KD9wsNq27GnHsAwaUqsHIooCDpNCwLD2hAxth8Og8P2/N1Rbb+ehPLoO74hfSOw5t+mx+BM1ciTHP5vnkx7YubMEjqJNyCmyewPHE7IKKigscxATeua+yqL+NE0nuHcvMhcs9EmPGjUSj8Hivblxl5bizM3j6Ef/9lnPXV7W4oPHTHuWT+AI8OHOL5gzrCN+nNIdQTESZG1HkLVdE+dQ1KTWd/MzZszgtdde4+KLL6Z///6YzSebKshoq1V0XSfPUVgtPa+yGPUCefPo3676hW0dOgTNL8BnIJvG5NF0PCeehDbwPi1uHXd2GZ5SJ2ZbMFqoucYmsYoCBmclqAoeo6XeN5AhAdWbBMVFBmJuw1O/iAuPR9fILc+vlp5dlIkprBinf9W0MprJgvXSS6oFaUHJyecMHBUFzA4NV2YpmtODIS4YZ6AJVEiyBXMs2/eNYlxUUK0fEOk6hF42DE+lHUdWNn4x0QQmJ6PGt6uxmasQrU2Qf/V5Ts1GFT9z623Z0xoYEjvQ8YH7KN2zF0VVMUdFETjwYjyn1E1mqxWDvz8e+8k+gcaQEEzh4TXMCtmyVLqqv5SqcNpx61JztmS1fnXx4osvUllZyR/+8AcmTJjAqFGjGDVqFKNHj27M/LUuusqIqL7VkgeEdkar67CArZQhoT2JM25F/eXhQmi/vkSOH4+mt/5gx+LRKfh6P/krDlO0Pp2c+Xsgo6zaKMQGZyXOTes49MxsUuc8iztlK6qnNkOBVJcYHUivTiffFxoNKr+a2EMGKhBtislgZFTHS6ul9zXYKN600XuNaZpO6KWXYh06BADFaCRu6vWYkjqdcx9mh0buV3so+OEIRT+lkf35bkzFTnRN56pLOxBwSj/i+KggktvXbaAvT2AIYYMG4S4tIW/NWioOHUY5ZU5KIVqzyBA/pgzv6JN2+9U9CQuU4LEx6YqCISCQsgMHKN62HYO/H6in3bp7NNpNn4b5l2n0LFFRJN5wHYqn5QdgsYExmE4b2OfihH4EqkHNlCNRG3W66mW01bNTNQ/xKdnc1HEUS7I3YDQYuSZ6CBG7MlBH9m3TU3Wc4DGaCRwxiu79B6C7XChhVtznOeKXwaCg6zR7Hz2tsBJXke9TssI1R4mc2hPHKbGc88BeUv/2rvfvQ399na5PPgEdup11+6qq4HGWoygqitEPXQd/k4H7rulNRl45FQ43cZGBRASZpSmcaDNUBdxlhfQM68z0jmP5+vjPVXVn1BD8l26kIiiUoMtPttxwB4YRe8dMYq67DkU1oIWG4/nl4ZTBoKLrerW6QlHAlVGKVunbTqB443GCx3QkJsTIC7Mu5nh+JUaDSkJkIAHmus2RpuZl+4y2mvHFl3jsFVivnYanzmMkC9GyGBSYMKQ9/btFU2Z3ER5kITrUD73t39Y0K/34MQ68/Ir376Pv/ZskkwnLRZd47wPcBYUc+/gzEqddh1+0FXtGDkc/+piuj7WDYGsz5bx2wg1WHrv0fj5OmU9GaTaXJA5iXIfLUTSZg7olq/VdfUONtvrWW2/x5ptvsmjRIrp27cq2bdt4+umncTgcxMfH88orrxARUfWmpamXnS+PYiCqfRLRlbn0C++LqukE2nVIan9BBI4naDpowec/PL2maGQ6jrMxYxsBJn8GxPYhyhjTbA8sdHf1c6g5PVVNY3+5NzSqkLV8ebX1Cn76majOyWf8HuhuO4f3bGD72m8wmixcNPoaohN7gGrCz6jSMTb45LoSOIo2wuIqonLHMtL3rMUUEc+oi66hs70UraQM+ydfUFlWRtyvH6523bgVI4RFVf2hg0dxk2ZPY1PGdiICwukX3QurIeKUa0VBc1RvYK65PFSUZrN+xRdkpx0ivmN3Bl5xDaY6Bo4Ajox0n9FWAXKWryBy/JV4AkLqvD0hWhqTqpAYEUBUVHCNA0eJhqWqCsU7d1RLz1mylKQBF3sfzJvCI+g4cxruzK2UHj6IObYbnWbehCk0nOqTl7Usug42UzwPD7wbl+7EXwmQBxKtQK1C+0OHDvHhhx/y9ddf43TWr/kdwK5du9i2bRvx8VVTFWiaxu9+9zuefvppli1bxqBBg/jLX/7SLMsagq7rmAJdlKz7jKBKB34VJZSs/RCLvH2vlzT7Uf605k2+PbyaBfuW8/ya18lz55z7g43EEO6HYvS9ZIL7xuI6ZaQ5HTDV8DDCHGE9Y9CrKJCZupP1335BZUU5ZcUFfP/Fe5TkpzVo/oVoTqe2tDYYVPxMGq5D67Dv34BWUYIjbQ95C/+CLakdpd98j6eyEtuUyVg6n/2NvaLA3pJ9vPLT3/j+yE98vvtrXlz7JkXayf7nuq5jSagewPkPsbL0f29w/PAe3C4nR/ftYOXn74Kn7oPDqTXMOWYMDEQ31D0QFUIIXddRQ6rfQBqt4T5NV42hZuy7FuJxlBA8cDye8jwcB5djCG498yAaNCN++rkDR+mx0zKcM3j86aefuOaaa/jTn/7Eo48+yi233FKv/ntOp5M5c+bwzDPPeNNSUlKwWCwMGjQIgBtvvJFvvvmmWZY1BJOq46yopHzyKyx3D2KVcTjO61/FVZSLwSCv4OvEoLNo/wqfJJfHRUre3mp9DJuK089IzDXJ+CeFYQr1I+ySdvj1iEI7JSj0aBA9bhyK6eTgAgZ/f0IvuviMzW4VPOzeuKpaevrBFFRVakrRfHTA6dHP+j2sGgzMgcdTWa0rDoCquVDSDlPxw7doB/eQW1DCN2v3sXTNATLD+pE39CEqL7sXxWBCdzsxBhnp8corJL/yMqETp+DxO/tw7C7Fyee7v/ZJK3dVcLTE9+GLK9BEzJTuWOKCMVn9iRjZkXJ3CfayEp/1ivKyqSgtOPuBqYE5oR3+7RJ90tr96jY8fvL0UFxYFEXH7bajac5m+71uC1RVwdHJhjH4ZMsjxWDAOG4YHsPJ/ozu0hyU8Y+yv+uv+DK7Iwd7zISR9+Epqz76fWulup2oWWmU7d+P+9hhjOXFzZ2lC9o5m62+9dZbOJ1OQkJCqKioYOfOnXz33XeMGTOmTjt6/fXXmTRpEgkJCd60zMxMn5FarVYrmqZRVFTU5MvCwsLqVJ6aaKgcD+/LM//e4g0ULCYDc+7sT4y0NawTHR1nDYPMuDwulGaaN03XdSoDjARenoSqg1sFZw0BoRabQPfn5lBx8CCKQcW/U2e0iJgzj/yqqIRYI8nP8r3ZDQo989tKIRpbWn4Fn3y7j9wiO+MGt2dor1gCTL5v0XTdzeHDh1i37mfcbjd9+vSlZ88+GAxVT7wVRcGZsoPDb7wJQMAfX+SZf20+pX7M4ulpHflwp5HbB07DuOEjMPnhDq19VwINDZdWfUxBt+Y5bT1whFoIGVs1uI4bHWNx9alwFEXBZK77xOfuwBCSHvktjtRDuAqLCOjYASWunc/DJSHaOrfbzpYtG9m3bx9+fn4MGzac2NhE6jA+o/iFrsN2LYuIe6cQlVMJThdlceEscO7mTvp713MGRPHR14f4ee+Jh15ZjOwbxYwxHWvecCujqgpFmTms3FvMmgMlJFotXNMXOnUy4jIHnnsDosGdM3g8cOAAAwYM4MMPP2THjh3cdNNN7Nu3r07B49atW0lJSeHRRx89r8y2FBERNT9JdjocLP4qzecNk8PlYcPefH51dXxTZa9JREUFn3ul8zQpeSx//emf3r8VRWFgfO8zHv+G0iBliwzGmty11qsPGH4lx/an4HFX3QT7B4WQ1L0PEZENd5yb4pw1l+YsW2N/H89HfY/LwbRC5ry3Hs8vddncZftwe3RuHt/d503CoUOH+PHHk2/Nt23bSmhoiLd1h7OgkG3//S8AgV278vWO/Gr146YDxYzsEUqmbqbbRRNRImyEh/tjNJ67S77mcmHPKGByp1H8J+VLb7rJYKJrVBJR4WcvvzPYSK/BV5Cy/ntv2sDLJxIdl4DRVH1qAjjHMY0Khg6JZ17exFrLNd9a8lkbda0PWmvZa8q3pml8//0G7xgZdrud5cuXccMNN5CYKNdFffR0duO51W+hKioGg4ojw8kDg24lynpyXImduwtOCRyrrNyey/jBiSR3azllre9xL8vN48ut+fy4u2o6p4KSSvZmlPHnGWF0Tj73PLw1cToqcVZW4BcYjNFYc11/qtb0nWkK5/x1Li0tpVevXhgMBvr3r3rSUVZWVqedbNy4kUOHDjFq1CgAsrKyuPPOO7n11lvJyMjwrldQUICqqoSFhWGz2Zp0WV3k55fV2ATRYlEoq6z+BLyk3ElFhYPy8vr3F21JmqqzfAf/JH49eCbLDq8i0OTPuE6XE05ko+67uQYCMAXGMunOxynMScdgNBIenYimhpwxLypgKnVhTy1EtRjwax+Gw9/g80bWiAdQcKO26QEOGqps9f1xOFN90NzO57gcSi/yBo4nLFpzmBH94vD7pd+vqiqkph6p9tldu3aRlNQVXVcwVZTjLq+arkKxmCmrrD5oTZlTw2gyEhcRytofs8hb+zxJ3fvR97IJGPzOPPCWqnuwb/iJo+/9m9jLLmbmJeP5sXwfkQERjOk4nGBPeI3lt7h0XMdLcBXY8WsfRu/BE0js0ofykkKCwiIItsZRWFQJVO/32FDfNQMaCjoexdBorShayzXfUvPZFPVBSy37mZjdOp7sMlw55ZjjglGiAnCd0qRd113s2bMHi8VC+7g4KiorSc/MJCcnFz+/sObL+Cla2zGPNsXzxKX3sezQKspddsZ0uIzOIV18yuA6wxziLo/eYsp6Pse9rNTNmj2+8wA7nB7SC52E1nGbigKVpVlsWP4FuRlHade1N/2GT8R4lt+aE3mXAPKkWo22umfPHj744APv37t27fL5e8aMGWf9/KxZs5g1a5b375EjR/Luu+/SuXNnPvvsMzZt2sSgQYP45JNPGD9+PAC9evWisrKyyZY1BE1XGNk/lt2phT7pg7pH4nC09Klaz5+DCtIqMsgpzyU+2Eacfxwmve7Nv04w6Ca6BHala/+uKDpoHs7c9LOV03Udc2AUMR2iarW+schB9oKTIyArmzOIvrYHDj8DqseJ++A+js1fgGI0EjtlMp7Qfo2Uc9EWWWqY+Ds4wOwzv6iu6zU+eIuKikJVdDTdQ4VmJ2zYJRR+/yPle/YyfvyNpBzyfUI+tHc8fkYnOem7KcrPwuWs5MCOdZQW53P5tfegKzU/FVYKcjn63r9B07D/uI7gDdu4sX8fEm69EpchyCcoUxQo0go5UnwUZ1kl7QzR+B+upHRnNuGXtSe0cydCout3rOpC1TX0tFQyFizAXVpGzFVXYknuhcfs1/g7F+I8mHQo/uEIjuO/9BHekU1w7xgsA2Nx/3KtqaqBAd27E5FfSMUPazBYw+k/Yhh6UP1bZygKoDlRDCY07QLsP6krxJnbMbPXDEJC/SgssFe7D4qx+pMQGUB63sl5ZTvHBxMd1jbqFYPFgp/FSMVpDx/9/asPCKQoOg5HOboOfn4B6Lpvc2mPo4SlH76Ow17VZeFQykZKC3MZecMD6Er971cvNLUKHjdt2sSmTZvO+Pe5gsczUVWVl19+mdmzZ/tMndEcyxqCqrnpnuDHg9cls/jn45iNKlMuSyQhXMFgMOB2V3/q3la4VSef7V3IuvQt3rRruo9ndMIVcJ4Vvu5uszFjvZhUhZJNx33SdJeG83gpSucwPIcPcvCV//MuK92zF/Oc2RDXoamzKlqp9jFBxFj9yS6we9NuuzIZs1HxBmW6DnFxCYSGhlJcXDV4QZwtli6J0Xz32Zu4HQ56DbmC4JFDMYYEU7z6Z8L2buDRacP4as1RTEaVa4YnkXpgE2lHj2CxWBg88np2r15IaWEeWUcP4KgowhxY8wMVd1ExnDJ4m1ZZSfHPG4i96mqI9b1ZLfDk8+LaNyl3Vd1cGVUjj112JwHLXBStTyM6KRSHoQluTLPS2ff8C958H37zLTo+cD+m/hfJFDyiRVPKXCcDx1+U7swmoGcUbktVX2hFMRBfVEL6/z6pWuHoUcp2ptDtuWepz+wLbkcR+zf/yNH924nvmEyPi67A6N8wU6u1Nh6PjtFQ8y27oyCdeybEsWZvBTtSixnYOYyLO5lxFGYQEN2piXPa8AL9TNw6rit/X7Dbm9YpPpS42FCf9TTNyc4dW9mxcwe6rtO1a1cuumgIBsPJILq0KMcbOJ6Qc/wIlWWFWIJjGrcgbcg5g8eLLrqowXe6cuVK7/8HDBjAokWLalyvqZedL101UpyVSuqyjxnVqTe6x82Orz4i+oa7cQVFNso+W4o8R55P4AiwYN9yLrL1J1Q5/zkfxSl00JzVf4p1tweTQSW9hhGEc1etJuKWThfUfKOi/oIsRp6YcREH04spKXfSOSGU+IiAagGOyRTAxIlTKCrKR9M8+Csuvv7gNe/yVQs+ZOSV1xPeLQLjgNtZYz/Cd2lvMnBwf/pH9WD3j996A0+Hw8GadZu45OJRbFz2KQajCcNZ+qKYIqwoRqPP3Iqm0BAMoWGc+phOURS25+zyBo4Abs3NioL1XBd7Ma6ciiZ5OqUoCqW7dvkEvABZCxeS1KcfbvXc/W6EaC76GUbZP3VqBbWynOyFi32Xu904jh7DFFW3cR8U3cGP898n9/gRAEoKcslI3cu4Wx5BMZx9BOYLjr+Z1e/9haiEjtzYqzvZqatZuzWNq+76XXPnrFYUBRxuDadH5//ZO+8oOcor7f8qdI4z0z05B0mjnDMCIUSQBCKDwSQHnI3XYe2113Ht9dprr73rD9vrSPBiG0zOIIEQyjmHGUmTc+ocK3x/9KhHrREggQQC+jlH56jfrvB2TdVb97nhuTajxMluPA0N2dvPVz46mbauCDkuM2ZXkKQcxMwIgezr6WD3nt3pzw0NDRTke6mumZgWHzScIstDlGQkQzbqeCZ4S/L44IMPvhvz+EBAEFQadq4jmYjTdnAkMttyeDeFleOJn+/dWt8B4qdQRtV0LaWYelrx7SxOF0ldxzm9iP4Xj4wMCmAqdaHoOrJttPqYbLdmlVuzOCM4zTLTa/PeUt1Ykkx4PUXInTvZeeToqO/3793J/LG12K0Rnm/fgKqprGvfSJU5P00cj0PTNJThNKPZl1yDweI+mWulobo91NzzRZp+/RvUaBTZ6aT6n76EanVkkEFRBF9stKz7YNyHYJFwTi5EMYpwzutWdSTzKQwXmw1dyCpRZnF+Q3SYkF0mFP+IIWOpcKNbZNIPnCAims1w0nMtvIH41JshEhhIE8fj8A/0Evb1Yc+rOOPjfZBhtVmZMH0uIU0Fh4zV46WkvAqz9f2Rtnq0O8Tvn9hLry/K7PEFfOSSsTgtI4ZjRA8TGrBw7+N7sFkMxOIK42td5F1mx2FLkUdJEmluaR517MYjR6kbM5HjPkarM5/aSbM4sndrepuZi6/CYHFnsz/OAGdk1vt8Pl588UVaW1v59Kc/zaFDh6iqqsLj+WBH1U4XkihisozO7TfbHB/4fn1eiweXyYE/PlK8XOUuJ9eYw9vKV8nizVFgw3NFHcFdXYhmGee0YpJ2GU3V8V5+GQObNqcjHILBgGfhQmLnoahLFuc/TueFKiaGOCAlSJpGe28lo5U+13jyDz1BrbeCwwPHAIjocUwmE/GTvGpubxEX33wP3sLyNySOADoC8oQpjP3xv6MGg0juHFSrY9R8VVVnWtEkXj72esb4xYVzsefmIpc6T9ly52xD18E2fjySxYIaHU4HFgSKr70WVZDefOcssniPERfBs2wMkUP9xNoDWGtyMNXkEj/BU6MazZTe8hGO/uKX6TGDy4m5soozLdp5o6yDN8tG+LDCHAngnTKR54+toblnL7Wecj5aMQ1LJEjiPM96GwjG+ff7t6ZFpjbv7yGp6HzumonpCKSakHn8pS4AorEkmg57G3xcMa8Chn3lggD5Xg+HGxozjl9UmI+EPnL/iUamL76OmklzCAd9OHPyceQVo+sfbBv9bOO0yWNjYyN33nkng4MpsYNPf/rTfPKTn2TlypV8//vfP2cTfD9B0QTq51xEa8OedIqHbDBSUjcB4QPuWbbqdr4679M8cfgFGgaOMa1oIstqliBp2VSAU0EQBCRJQFW1tLErChrGYCfKYBui0YrgqSQuu065vyIA+Vacl9eiA3FNTzt/9eIKxv3g+wR27UKQJZyTp2KvqyXWf2YqyVlkcbroVP38Yt9j3F17FQajiWQiRQgFUcQzdgHrDoW4uaiS8R5XmjweDBzlukWXsGr1arTh9XL8pJk8sGaQi6aV4T2NNE5N09HsOWDPSRkHJ3FAk+JH72+hJhHif2Z8nD+3baA11M1VY5Yy0TMBXTeTOEvuZlEUEMXMZ3rUfPMKGPO97xLauwclHME5dQoUl2drurN4XyBmFJGnFlC6qBJfIJp675wAXQfDuAmM/fa/Eti9C0NuLvaJk86ob+txmGy51M9cxMFta9NjVeOnY3Gc32TovUDYbOYXWx8iGE+9448MtfKr2LN8d8YdnO9uqa7ByCh14h2HewnGFJzmFEXRVZnSXCM3LrHjVAZJSFZ2DthInpDwpus6DrNMXl4uAwMpnuJwOPC6HWiCwIkvB0G24i4cg/vtdfnIgjMgj//xH/+B3++nrKyMtrY2HA4Hs2bNYuPGjedyfu8r6ILGk30bWXrL3QQ72hAlGXNRIauH9nCDt/K9nt45R67o5a4Jt5IgjgnzOxbK+aAiGFPY0dDH7sZ+ZozLZ0qdB7tRwtDfQN+jP+H4ImfwlOK68mvEDacmkADJU0RMdAT0wjKcy8rRdVB1PaM3XxZZnG20R1Iy6g+1rubmq65C7Pejqyqe4on8+tkerpjixlQ3h4VWNyVWDw3djYyzlZAYamfuomUMBYLogoFX9wxxsMXPRy8f/47nZFL8+J/+Ocm+1uERgc9e9zUi3hoMuhld09HPEm0LxBS2HuzhQNMgcyYUMrEqF6txtNmm66DmFWJdXIQgcF62eMkiizeDpulIBukN7924IHNE9LLTPgWnwcQcyUn+W6S+nwo6EpPmL6O0ZgJ9nc3kFZaRW1gFYtYhfTL6tWSaOB7HQHSIfl3hfJeAsZlHOwnddhNGeSTg4rQY+NysJMqaXwNgARYU12PO/0x6G12H3pYGytwy46qmoAOJ0CDN+zZRUjXhXP+MDx1Omzzu2bOHFStW4HQ603WQxcXFbN269S32/PBATYLZYOGH++7DYbSh6Trh/gg3T1iJonw4jARBEzFhea+ncd4ioen8+vG9HG5JtXPZ1djHzHH5fHFlHf5XH+RE71iyvx2l7yh60SSEN2hX8GbIGqZZvFuwG1P9r0KJMH848jRWg4VyVxmWfRFUDaaNLyVudWIPBzD/8E9MNRpIDPmw330b7ZGj7O91s25fJ267ia98ZDIFrtES7G8FQYBEIkIwGMBisWAMtJxAHAF0/K88iOuG75I4i7G+mKLx84d20NabMt52NvRx8cxSbr1kzCjhh/RMdD1bX5PFBw6CILD7SD+/fmxPeuz5Dc38291zybWdOekTZCu5JfV4ysZn32dvAotoRkDIcIaJgohZOv9rHos9VmbVF7D1YA+QWsc/uXIiFoOYXiNNSoDwpr9m7Kd3HsQa7SJhcQIpe6dqwkye/vN/Zog7LbvtS6jqu/NbPkw4bfJosVgYHBzE6XSmxw4fPnzKPl8fVoiazoW2MWwx7CKYSEkB51pcjFfdw+lM2cXvTKFoOv2BOLIkkOswcS6SfwUh9dJ7N15Ofb5omjgex7ZDvcQvK0MJD43aPjzUz2t7n2fJkqXIcpaUZ3F+osxeSm1OBUeGWoCUgNaymktQ8nL4yGIbNqOMroPS10PS50vvF3z8eUqvXYalsIeLx5eR5y3AZpKJDHVgtNhSIgYI+MJJIjGFXKcJszx6FZAkgcHBXp599ul0S6TbFtSP2k4NDSGoCmczl6t7MJImjsfx6vZ2ls+rJOdtGMxZZPF+RVzR+PvqhoyxaFyhpTtIbs3bb7HxYSeOAgqJiI/ejgEE2TEq+uqOwPKaxTxzdKSTwXVjLiMnrKO9ceLSeQGTJHLX8noum1NBMJKgKM+G12XK7NOrJtFi4VH76olYxmeru5gr7/oah3euR00mGDt9IfbcsnP9Ez6UOG3yOGPGDF588UUaGlILw/XXX8/+/ftZvnz5OZvc+w26IOD0Jfh0+XIGiCDoAvmCFXtE+9Avfm8FURSQUFCR0iIZgZjCb06I0i2ZWcZ1F1ZjNpw9y88c6yXZthc1NISpahqae9zbOo4oCmi6jsCZp+cABHUL7ilLCG45oY2MIBI1uenp2UV7eytVVWOz0YoszktYsPHpaXfSFe0mqsQoshWQK+WBLTP2JloyJfbjnV3Ef/1npv36f4iZnAQHWnnqL78hGg4iyQYuuu5THPY5uf+5gyiqTq7TzD9/dAaFbjOaDqakH7XrEMmeo5icJUysrWDXoZTi65BuxCCIGb0E7FOWkJTtCAjIQuZ683bxRo9k9lHNIosUPojmjyzpoOso2rnVs9DVKMmew2idDSSScYSiOowl9XBCOYtqNFElT+amqjLihDFho1DIRTGcG4f72YZZFqkuHC02eRyKyYVlzGyiDZvTY4JkQMopInnCdrouYHGVMGPJzQgCKEpWrfFc4bTJ4z//8z+zb98+2traANi3bx+lpaV8+ctfPmeTe79BR6ArMsD250YIQBNw0VW3U5C1+t8QpqSP5JFNhBo2YSytxzLxYhIWL6/tbM+I0q3e1saUOg8TK85O30hTvI+BR36AFk1FDYJbn0G89qvgmfim+0mSiK7raJqOIEBvIM7zG1to6wly8cwyptZ6sBhOvWTnuyyMrcjJ+F0zxuXjsBgwTVya6gW3axWSPQdh2pW8tr8ZgO7uLurqxpNMZvMvsjg/YcFGteWEhtSnWPKEvHwKll1Bz3PPp8dKb7oRs8dDeGCIVx/9A9FwSrFZVZJ0DMT443Pt6W0HAzF+89gerrmolv6ePuYNPonStj/9/dgJF9JfVEB7Vw/rDzRzzcovE1r3V5TAILYpF2OatBSSAZSmrYQOvI6xsBbLlKXEzG+/Mqgox0pZvj0j+njhtNJs1DGLDx1MssiNS+r4zWN702MWk0xVkeM9nNXZhYSCPHCU0LanQdexz7oSJa8O9RxJ00j+DsIv/XYkyrb3FYzLP49YNiPt+PIrBn751z0k0mQphNU8wL99YgYfhC7bii5hX3AzotlG5OAGDLnFuBbfTtycf8r3TLaf9bnHaZPHoqIinn76aV599VU6OzspKSnhwgsvxGLJptIdh4BGS+NeEATyCkrQVJWhvi46W49QPHZ29oY+BQxCkvDrDxI9sh2ARE8zsSPbsN3wb2w71Ddq+8OtQ0yuyn3TSK6sgxhKokUSSA4TilXmVJRL7T2WJo7HMbTmr5iv/zrHov0YRZl8cz5GPVU3IKARGmqnaf82TBYrZXVTSBo9bDnQQ7HXRqHHhj+U4PXdnVw2uwz9FHM0SAKfvWYSOxr62NXYz8xx+Uyp9SAJAnHZiTTtOuTyGRxqPMqBTQfSKXg5OTl0dbXi9ZZko49ZnNeQJBHQT5mmr0oGclasxDV9OsmhIYweD2JRCaLBQCzmI+QfzNg+lBxtkLV0B+nsDzPGEkoTR9FkJTb9Zlq1XCrKC5k2ReLAge2EnGUEZt9OcKifg82dVMsNjAsdILx3DZBabyKNW8i96QfEDe639XvNBpGvfGQ6Ww71sP/YIPMmpgRzshJVWXzYoOs6U2s9fO2jM3hlWzuFeVYWTS0mz278wLy35KEm+h/9cfpzrHU/nuu/iZo75qyfS5IEkp2HUSauoMdYjqILFIo+EvvXYiudiEaqNjwQ1UkoGg6rgcI8G519IcIxhVBMJ+eNA3rnEZL0RnsJJsIU2L24DDmcbC7HDDkY5t1G3uxr0EQTMYzZ9I73EGfU59FsNnPFFVecq7m876EjUjtpDhPmLCYqaQgCmJIgSoa0FH0WmRAjg2nieByKvw851MOkmjzaeoIZ39WUuN+UOEpAfE8PwV3d6THPpTUIxfZRLy9dSXAytGSMV5rX8uixlDz4lVUXcrl3NrLRhj/cT/ehw9TkTYMYqN0RkoUJXt/VQe9Qqm+b02bk+ovrCMdVrG8QfXSYZS6aUsyS6SWoqkZC1QnFVSwmCTQdg7MA0drLhAVTiJHAa8sl2hPihRee58Ybb8ZofF+8DbL4sEFXCPS30rhrA2arnZpJc7C4ijKeO11UCRqTGKvLMep1KfVRoC88wL5AE1a7k0gokNpYECjPNfOpCwvpCKi8vH+QeEKlyGNjwB+luM6UTlkKzvsMP3xuiEisF+ilLN/OPdcsRNE0Nm7fRcX4KvInl2F3u4hs82VMW4sE0H2d4HW/7Z/utMhcOqOUy2eVvWmrjiyy+KDDIArUlzuoLK9AFmSMmhn9A/JAyLJIZO8ro8bDe1ZjvmTcWU+T1HUI547lF8/30dbXD4DVLPPtq1dgF6Q0ebJbDdy+pJhx7gSGZIyEIYd9gwZs5vO9UQfoeoInjz7Py63rATCIMl+dfTfl9spRJQWqLqCKbx7FFgQIJ1R0Hewm+QNz751veFPyWF8/WnDgZAiCwIEDB87ahN7P0DQdV0U5azq38UrzViRRYnn5QuZ6J2eNiTeCKMJJdUkAgqawdFY5uxv76ehLRQdn1hcwpvTNq7+lcDKDOAIMvNpM/o0TiMuZsQBDQQ2IMmgj7Yul6ZewqmMbAgKfqViG6/ntNOx4BKMnj9LbP0qxUkt8S8q4Fc0ye+t8aeIIEAgnaO32M9ETIBgJk5NfgsmeP2oB03UdVYW2/gj/+8ReOvrCTKjO5a7l43HbDQTyE/xt31Po6BhEmTvHXYfJZCIYDJKXlyWPWZx/8PUc5cWH7k1/Prh9LVd+7OuY7KmU0CA+/r7/KXZ27SPPmsPHpt5MlaUSXRc41HeUh4+8xCcuW87epx5FVRUuvuhakk8+Rs6+/RQWFjDnmlv47c4oyxZUEffHMEdNaK58BFsOzx5SicRGnuO23hCbGvtYt7uDr33kArq7GjGEkwyR5FB1LfNMZjiwaWTy4js3sjRNz9a2Z/GhR5ggzzS+xOutW3AY7dw2+VrGOcch6uc/kXkr6DqIxtHZdqLRck5sPF2HQwErbX0jNkYkpvDsgSSfqB65nnYpxix7iMG/PkmgtQ1LVRULbrgKUY7Dea5+3xXtThNHgKSm8Ps9f+M7876ExJmpxSZUnY0Hunl4VSOKqrHygmounl5yVnUyskjhTWtpU3Lib/4vG1EbgSzB3qGjvNi2kaSmEFPiPHpsNU3hLkQxm8R0KijmPOzTLs0YMxbXoTuLcFkMfOuOmXzvE3P44afmcfeV40/ZO+1E6CcYkOmxpIqeHLlPZV1B9g+gYiP/lh9gqZ2BsaCSnMvv5jU5jj8eZJpnDK7ntxHZkZIcT/QPcOyXv8LkGCnPlm1GWrqDo87X0h1i/5bXWPP4n3jqj/9B1N95yrn6I0l+dP9WOvpSKmL7jw3y3w/voj/Zz1/3PZmW3U5qCn878gzVE2uxWm1v+vuzyOK9gCio7Fz7XMaYqih0Nh1MKRmLKg/te5ydXfsAGIgM8fON/8uAOoAgCHQEuwknI9zXvorCKy9n4U13EXt+DcF9qbTUeHcP0vpV/PvKckrkGBO8dnxbfDhnfArD2MW09I/OIhgMxLjz0lI2P/Zn9jz9KPteeIrDj/2DSjGPgcoRx6ghrxTBXXwOr04WWZz/EAWQQz7k4CAib8+uE0RY3bKWtS2b0XWdQDzIvVvvpyfe/dY7vw+gqhqWiRdlOpsEEeukxeekLEmSBNoHoqPGm7tDGSJE5liYnt/dT7Q1pUkSbWqi948PYo7HRu17vsEfDzDNO4GvjLmTf6n6OJ+qu4mkqhBXz3zuRzsD3P/sQaJxhaSi8Y9Xj7Dn2CDZNtdnH28aeVy9evW7NY8PBHQRNvfvHzW+d/AIU4tmfmC90nJwiERnO4IoYSgpRbE633qnYai6iGnalRhLxhJv2YuxsAapZAJxMaXKaJZFyj2nT5hEpwlBFtFPSB8x5JrBIgM6cmiIroceYmjLViSLhbLbbsV20adAElFFGa3lRQCmmsuJ7Ho98+CahhIaAFJzU5wGphbnsmZPJjmcVWOhb2dK8VFVkuzd+BIzFl9NYLAXi92F2Z6H5PfRO6QRT2RWY7b1hBiMBkb9rmAiTHlFBS7VDDoksothFucJFF1nwJ/AM/Fy7PmHadr5ajrSrus6Bh1CcT97eg9m7KfpGj3hPnIdHmpzKwHwx4M8dOwlPlW8FPPRY+ltS667hkhzCwe/+S1Ek4n8G2+EwlL614ewlOazaILMQ71HMo5f7LFhSvbg7+9Jj+m6Tsu6tUxYeR32KUsweCswFI0l2tmHZI+iuz1owvtBnzCLLM4epESUwJpX6Hz8CXRVJf+SJeStuArVemZCNzGirGsd3fu7I9RNUW7J2Zrue4q4vQzvzd8jdnQbAOaamcTtpefsfHVFoyOH8+pzkCUVRUmZ8NqQH8FiwXLVDYQlC3YlTPLFp9B9fgRXYca+cjyM2teLYDQiePJRxTPvIX02UeUooyRhQ1sdAJI4ZCP/svTjWA12ThSrEAQwKjp6OIlgklHMIieW1UuSyNaDo50Ur25vZ259AfpJ2W2aqJDQE5gFM5xjxdwPIt6UPJaUfDAe9ncNukCpo4ijgy0ZwyXO4g9sj0d5oJuGH/4QJZhKLTUVFVLztX9Gceae9jESkg2KpmEonY6q6Sjv4FIljCL5V45lYPUxlEAcU4GdnMVVxNCRBJ3+555naEvq5aZGozT/7g+MLSpGL6sGFS6pXURroIshLUqu253Rkw5ANKeIozbeyz86h9CDUVYsrOLlza2omsbSmcW4EkcYiI70JAoM9rF19aM0H9yFM8fLxVOW0Pr7PyN+9FOj5m8ySOSa3QiCkJHqmmfJwXQkQe/Ogxg9VnIurSVuODMGKQgCkhpHl2RUPbtYZvHOEUmqPPRSAxv2dgFQUVjEdRffyv7Vf0GUJEorxxHd1Y1qiuEyOfDHMyP1NmPqeRrrqeba+it48vBLqJqKxeZEtFhQo1EsJcUkfT6Gtu8AQIvFaH3gAWo++2VinRBtDzJ9cgH9M0pZtbMDoyxy+bxKDrUMUlw5ujdYJOjDIXmQ59+O3tHK/m/+W2r9EkXKb/sotgUXvG2DShBAUuLokhE1K5mTxfsEiaONdDz8SPpz70svYy4pwbJw8RnVjMkYyLd7aBpqzRh3mk5daiEKGugauiC/YdqnIAooqo4sCudF/ZqOQMxehjitHIDYOQwKaJqOXenipouKeXJDDwlFY9FkDxWWfnS1Kr2dKdeD79pP8L9rOkkoQUxGic/d9CkM7hxOzMWSfX0c+/l/EetKrdfeSy7Gc/V1qOZzm9Ek6wpqLH7K75xRC737AhiKbOhOCb0jhrDBj3FlUYaT3BRW6HvmMLqqoykqOfPLkWpy0vxS03RK80c7OyqKnJyorCMI0Kv08NfdT3DM18rUwvFcO3Y5Ttxn7wd/CHDagjmhUIif/exnbNq0iaGhofRDLAgCmzdvfou9PxwwiiLTcmextXM3kWQq1SDH7KbcUpvqA/gBizyKIvS9/HKaOALEu7oJ7d2DZeFFo14GAgq6piLK5lNei7NBsHUdEi4juVePQ1A0NIPI8eQHIRZhcMOGUfvE2towlVUDUOTI59OTb8eXDGD9ZCXHfvaLdONG69RpiNWVWBMBDphFNhxMRTSKPTZWLKyisshJtSvCU398MeP4FWMnsW/TqwBMmTCH1t/9CV1RMO7axNKJF/DyvoH0tnetGE+BycPnZt7BH3b+lZgSJ8fs4lPVN6KvThneif4I0UN9yFMKTvueig8MEn19HX2rVmEqLKTo6qvRisrPi5dxFu9fNLb508QRoKU7zJFAOVdefgcWuxuT4ES1HsSQ8HHHpKv51ba/pNOxZxRPptBcADo4THYuKb6I2YXT0ZQY0rYDGG6+kZY/349j3Fh8u3aPOnesvw1z5XiUgRhGIckNC0tZNrucSELlV0/so2sgzIKawpS1cMJ9Xjp+Hi9vH+KGuRaa7r13ZP3SNFrvf4BxY+qg4MwbS8uhIYbWrmVo0ybsY8eRf8UVKLn5Z3ycLLJ4NyFJIkM7d44aH1i7loqFi1DOoFOgpMl8ZMLV/GTDvahayqyvzamgzHZyIEInPNTGrrXPEQn6mDh3CYWVExHkzChbIKawels72w71MKXWw6Wzy3Fb39tI2XG8G/acpulY7S7UdQ/xqYWLECQj/UdeQS6aji4Y0uvakOTkt2sOkhzOuIonVH7zWg//OaaC4511RTR6n34mTRwB+la9gmv6dMQxb96e7O1CUhIkjx5moPkYg4KAs24sYkUNmjhCPfSYQvxSJ08ObqAt0s3C6dOZEqlEUHQYdpAbgdDednKma6ihdkSzGzU8gBy2o9pS94Ou68wY6+X5Dc1E4gqCkOInl8wsy/hbhfQg/7nhN4STEQC2duymLzzIP838FLKWba90ujht8vj973+fp59+etS4kE0mTiMJvPiajy8s/AxqPJiKHkl2Nm4PMOaK0g9cw1JRU4kcOzZqPNrWik0U0mRQQCfQ38zWVx4nGgwwYfZiKupnIRpsxBUVgywinMV1WD+e1nmy2qnBhKWslODBQ5nDuakoaTiusnNTMwdbhphQmUt99XjG/PCHdB1uIiqZ2BQw8tzvtnPr0jH4hiLp/Tv7wzz66hHKChx86frxLLjqTna/9hRKMs6UeUsJBX3EY6nt5YSKPtx+I7pzGwtMJqZfNJtYbiH5+U4KXGaMCRhzJJdvFX2cuE0jR3aQWN2DdkLdZrTZh3tywWlVpogCdL/wIu0P/yO1b3sHgT17GfvDf0PNffv97bL4cENGpaFlYNT4riNDzG7YRfvmjVTedTtSTSn+qIFwIsZNk64kqSYxykYKxFwGe3qQBBlZLkDXZRyCi2QkxPa+RtwFZVR/858xJBXiA4MkBjLbeCQsEgP2dux149jaHETeN8AShwVhXy9fXFhDd0IhxypzwbWfYverjxMN+ymfOJ8esYa1Ozu4cqKLWNfoNKfkwCDSGZJHWU3Scf/9+HfuAiDW2UVg925qv/e9M0rjzyKLdxuapmGpqBg1bqupRTsVcRTAF4yBwClbJZSaivn+3C/QFezGLJsodRRjJDPyGAt08+z9/4U+rJmx9qkHWbD8FsrGzUs7NJOazr2P7qaxzQ9AV3+YPUf6+dc7Z2GWPxyZM6Io0DhopnLm5TRtfY5kIk7llIs4FsmnWtU5rgE4FEowpTaHuWPtiFocTTTz+j4/vnASqz0lOiPGYwT27hl1jlhbO7axE8+J4E+yu5UOfyf7uvYgiRKTPQ6KbBbIL09v48uJ858b/kxUSbn5Hwk+z2DZPG4yVXLcwBFVHaO9iaFX7k/vZ8ivxlL5BTihk6XbauCn11cSOXwITVGxjxuH7DJktP3ojfanieNxNPva8CV8eOSss+90cdrkcd26dVRWVlJbW8vq1av5r//6L370ox/xmc985lzO730Fg6xxzbx81q1+gXg8FaK32ewsvvDSD6RgjirI5C1aRPhYU8a4a9q0jChiJNDF8w/+Mv1S2Pzyo5g8NWw62su63R1UFbu4cUktBS7zaS1ggiAwqPbTGepGFmVK7cXYeOvaDEWUKbnlFhp++CO0eBwEgfyrlkNZIUoixEMvt7JxX8qYXLWllSUzy1gyq4xvbTgMjAhy/P2VI3zm2kmjjj+uIof7X2xkwlgHY5Z9gnyDRODee6m4ehkHJQlNVUkaRARZThPI2Kb1yLt3MOPHP0axW5BEgfDWdkIH+xEBqyRgne0mdlJtpKXSjfoGL++TIUVCdD71TMaYlkgQb29HzpLHLN4GBEEgtmcXlabRaniTi80k1x0DTaP5zw9g+PzXiXm9PNrwJ3yxVD3vJ+pvYte6bRhkmbG1VQSHeqioGYugabz69AOUzryW53aH6NzuY/74XK5esYLQ4cOo0ZSBYR9TBwUeGvvtPPLASEPyWddNRQ4nsXUMUVplQEoK9AtF+EtW4rJJPHUoQHtvD3MnFqIcbcRcWECsuydj/oa8vDOWC9GHBtLE8TgSg4Mku7sQqrPkMYvzF7oO9kmTMRcXEetMRaVkp5O8S5ZwcjLQQDjBo68e4XDLELPqC1g2rxKn5SQzsrudYM8RYhYNXRPwN3ZRNHF2hhOlr6MpTRyPY8/6Fymtmwpiak0ZCMTTxPE4OvvD9PmilJ2BDsL7GZqmY7Va+c3TcS6cdAMWo8jf9vqYMc6A4YQ0Xo9LZkZpnH1bR7IAF06ZRZ5zhGRrJjPOyZPpX/NaxjksZWXnhDjKIrQPdrJh3bPpsdfWPM5lK24nr6gibSN2xHqRRImrKhbhlKw0hNtZ07GFS+uWYCd1zwgECWx7JOP4yd5j6LFucI6QR6G3naM/+CFaLPWeEGSZum9/C0pGUnwtsukUc5UxStmo45ngtMljMBjkiiuuwGRKXfilS5eybt06/vGPf3Drrbeeswm+nyDpGl0th9PEESAcDhHo70CuKnoPZ3ZuoOs6tukzyO/ppu+lVQiSRPH112Koqj2xzpmBrtaM9Miimkk8vmmAbYdTUYuhw70cbB7kx5+Zj9P8xrfkcQLenejix+t/RUJNKZ96rLl8de5ncPDmbTwA9OIKxv7oRyS7u9Dz3WxZ/zyt//tvmK02Fsy/mt5BO0c7U2lsq7e1ceH00YXwqqZRXuhg4ZRi1u1OieVUFjkZU+nCWdnO823/INGfZG7RLC69aSWBJ19k3Mw5HNi9gUPH9rDoM3fT8r9/QEskEM1mqr/4BVRHDug6UjxB6FD/yHxVHSWYwFaXR7gxdb2MXhuWcV7ip5s2I4pIZnN6QT0OwXBGbV6zyCINKRbi2H33UzjvQuaNqWZjwxAAVYU2ZlsCRI6nRmkaiSEfW/oULA4zPgIU2L3Eu0Lke/MosMsceO1RlGSCoclzmDjrQoomLuFXz3YTT6ZWkWc2daJQxi0/+hGJrk5EowmpqAS/Bk89sy1jXquO9rHsigKeHljL+pbtmGQjd0++iwQGHlnbAUBhnpX6ylz6AyGKViyn7e8Pj9Q83v5R8L4Nh4ospfL4TzKIBcP5kWKXRRZvBsWZS/U3vkmyqx1d1TAWF6PYczK2CSdUfnTfVnzBlH3z0pZWmrsDfOXmaRiG382ymqAx2csvBl5CHRYoqbAX8tlYLfYTyKNsGG2oG80WBFFK+0Nl6dTRxTca/yBCFMFhl5hcl8tzW1JOrvJCO9Pqc9FPcB4LiQCHD+zK2PfAnm1MrCwGS4poa4jkr1hBqKEh7STwXnIJcnkVma7pswNB1DncsGvUeEtbA94Js9Pk0Sqb+FjREg6vfoHWUICy8hqmz1+JLIjp36drCnp8tOqspo049SVJZHDL9gw7R1cU+l58ieK7P01yWEzDa/KysGwW69pGhJ1uGL8cl+Q+uWNcFm+C07Ye7XY7sViM4uKUpPkPf/hDNmzYwNDQ0Dmb3PsNmi4yeJLACoDf70NVP3iRRwDV6iTvupvxXHo5iCKa3TXKW2k8KTrhLp/Ethcz092icYXO/jDOU/RxFFAJDrTRfHAnFrsDsciLQTKkyWN/ZJDDg43Mypv5lh40XddR3R6knFy2vvh/tDamWgfEImH2rvo/ll3yKX7VOVLDKUsCU8d42dXQlx67Yl4luTYjd1w+jhXzK0mqOglFpTV6lOeOjrQr2Ni5hdIaNzXxONPmXUbtrIswmW3IJgdjf1yDGvAju92ozlx0XUcQNLraD2FymFACJzggmgbJu6oOx8witIQGNgPx4dtJ1WEgGCeeUPG6zadM51HMNirvuI3G//7VyN/E68FUVsHoxiZZZPHWEDQNJRwh+cLTXDFzFksWzETOz8d0aDf+vzw1sp0sgzsHoVtnSeml/OXQX8gxu4gMhKkuymPzc/+X3vbI7k24cjwo5mriyUzBjYPNAwxNNtE22IRsNFHucSKaPKNKAXa3DuIc38q6rhSpjClx/mfHb/nynHuYMW4GqqrRNRDmwecP8uW5Dtofe4z8JRcjGo04pk+H/AI0XTqtiP6J0N15FF65nO4nR0o7HBMnIBcUZZ+xLN4XUKwOhNrxqf+f4kXaOxRNE8fjaGj1MRSKk+9MveMVEjzSvS5NHAFaQt20q4OMozI95i2pxmy1E4uMvGtnXnw1OiPOllyHkUtmlbNq68haMGd8AV73mfX+ez9DEESCYid6+U7+Ze6FSKLE7v49NIR3UM2SdFJxQh1N/3RdJ6FpnBhnU9xeqr/1bdT+YbXVXC+qdG4cXKomYne6R43bXLkZmWnuhMSGpx5JBxj6Wo8iSTKWq6emCDKgGN3Yxi8gfGBdej/BYELMGamllWWR+Cn4SNLvRzzBLJI0A9eNuZK5pTMYivnJt3ooNBdmieMZ4rTJY01NDY2Njdx222387Gc/4+9//zu6rjN37tzT2v+zn/0s7e3tiKKI1Wrl29/+NvX19TQ1NfGNb3wDn8+H2+3mJz/5CZWVlQDv+nfvFIouUD9mDN3dmXU0VZWVJJMfXBNCRQDHsJfyFEZXXmElNmcu4UCqZklXE5iM0qg2FaY3aOQ61H2UFx/6f+nPBqOZm69awR+PjKRi9kUGETynr8amJsIc279t1LisjKTJTK714HWa+fiK8Rxp99PcFWBMuZuqIicCIAmQ7xpOsQkl6DpJYQ5gQ+8eZt94DZotB8vw1DQdcOWBKy9lWA6PJ6MB1j73IFdc/jmU9XHQwTg1l055iLUvP4XH42HKlGlYRAPoEFc0nlzfxAsbU+q+XreFr982g1xbpldX13Vy581hjNNJuKERe01Vqk+VqiCio2VVIbM4Q6hWOwVXXE73088Q2bYVtm0Ft5vyT3+S8BobSjCIZDFT+PG7eW5I5GjnEKWFhXxl9mc4FjhGXX4FQ0f2jjpu457NTL48U7xBFODmeQ6eu//naYGIPetfZMVd/8wV8yt5Zt1I2vy08W42d2amZQHs7d3PmuethCIJli+s5tqFFdSUCITuupuYw4koK2zdt4dINMrUqdMoLCxFEE4/Mq8hknPpFdjHjCV0+BCW8grMdWNRTtFQPIsszjdouk5zb5jHXztKIqly1QXVjC11IZ9QbmOWR79bRVHgxGShhEGiP+obtV2IZMZn2ZLLsju+QnfzYaKRICVV9dhyMkV1ROCaRVVMqfNwpM1HVbGL2hIn8gdMZ0OOhVAH+hEtFvQcD5owYgfpuk5MDXB10QXs27WHRCLJzInjaRa6QEhy3IS3upxYLBai0ZHonN1ux+YcnTKvmKxQUnmm/rEzhqbpTJizhGMHd6GpKfvXYDJTXj8jQ8AmPNA/ym7rbjpMMhZCtgw7JXQRy5zrEe25RA6sxZBXhmPBjcTN3vQ7IZlUMU2bBWvWZBzLtOAiTpYbMepmqizVVB1fnrO6gWeM0347/vKXvyQcDlNZWcnPf/5znnvuOfLy8vj85z9/Wvv/5Cc/weFI1aWtWrWKb37zmzz++ON897vf5ZZbbmHlypU8+eSTfOc73+GBBx4AeNe/e6cQdYWcHBdTJk1k/8FDiKLI1EkTsFgtiKIIb7Px7vsdktnNFbd9if7OJuKREMXV9dxmU/nDkyM9MesrcyjOs47aV0Bhx5pMoaZkIoY8GMIsm4gpKU/oBO/YM1I/k2Qjbk8hQ31dGeNOt4uqYiOzxxcyf1IhkgA2o8SU6lym1ea94Tny7Aaqcot5vSNzvMBaRKxkHNbTquUERVF4bd1fmDX7KmzWPPb3N7Fvd+o6DQwM0NzczLXX3ojBYKG9P5wmjgB9viiPvNLIp66cyMmroWyxIFTW4ZAkGv/z56jhMIIsU/mJj2OcMRtdODVxP5sQBAFFiCMIEqJ67s+XxbmDpgvkLr0UY14u/jiIOTl4yjz4JBt5X/8WxliYgGDi52u6aO5KOVX+8nyQeZMKuXnZLJSIH90zOj00L78YryeP6mIHxzqDOKwGxpS56D+8PkMxVVUU2hr2sHzeJRTkWFmzo50Sj5FLJhcTaCuiP5IprmOT3ERiETQdnn79GN+7upKmH3wfAM9XvsSz27amDZiXX36JJUsuobS0+oxqgVSTFXHsRNz1k9A0/bRSwTRRQUdH1g3npO4oiyxOBx0DUX745y3pzz9/aAdfu3U69WXu9FihMcz8CR6MJjP5uVZauwMUu0TyxCBJUka+CQsXVczl2SOvZBy/1DW6/MNgyaN8/HwE4Y2V6C0GiQnlbiZV5nzg1OoBpP4ujvznf6bEwESR4uuvxXnxUrThujxN06k3l/HUkyOO8t5Xern44ouQdSltUcaiPi6//DLWvb6Ovv5+CgoKWDB/PuHoEA57Zn2oIAgkhTgSEoJ2bt/DQdFD3ZK7ESLdCKJI0lxAWHBzontbtozWq7A53EhyphM8bnAjTr+WnCmXo4kmYrrEyYtmLM+D4+OfRVn9HChJpIsuI1lc+obk8IPYBeHdwlsmj7e1tbFjxw6cTieVlZXs27ePZ599llAoRGlpKR6P57ROdJw4QqrthyAIDAwMcODAAVasWAHAihUrOHDgAIODg+/6d2cFgkxHSwt9SgGF4xbjqV1En5JHd0f7h94wkExuiionU+kuI75uCzP8DfzmrvHcsayeL39kGp+9djKmUymo6TpKMjFq2CQYMMsmHCY7d8+4lRJz8RnNRxdMzF/2EURpZPEsHzOZ+vpx/Osds7hidhkOU6Zv5c0XGYGJ+WModYzUtloNFsbbZ/LwmmaE0xBMks0upi64DN9ADy8//3tafQ3sP3AgY5t4PI7fn7pfuwdG97Dbd2yQmHJqs1WKhDj2P79CDaf20xWFpv/9HeJA71vO7Z0iQYwtA1v50ab/5hfbfktzrAld+HA6Uz4oiFscHCicwr/vN/Avq3z8bXeU1kGFf7rvAF98uJVOxUJzV2Zfx417u4lHDcQG+lATMfIKRoxKg8nMlPlLMMomvvKRadz7kSq+PzbIXd4BJtZMxmjOjOIpyTgWg8TCiYV85bpKSode5OU/foeFrnGYTxBFKHOUEh10oJwgudc//OxINht94fAoz/eOHdvR9bdXCXQ6xogmqByJNPKzrb/mx5v+m11Du0kKo9e5LLI41xBFgc0HRqsOP7s+870lG2QumlnJkXYfD69qYCgYZ0p9CaJ0QtsFDS4qX8jS6guQRIlci5t75nyCfNOpNR90/TSflw+ggS9rSdrvv39ERVrT6Hz4H+hdIx5oURTpaGsfte/evfsQTghGiDYbu9Y+waQxFVx5xVLGVxayZ+OzSNZM4hgnyqa+zfxo4y/55Y7/pTXewlmVuj8Boijw9Lom/ueZTn67TuDXazTufaaDLQd6MgQk44KL4jHT058FUaR2wbVE1dHCNpoGccFKUh9NegUBfB27sJQV4Pno7XhuvwvbmCq6j20eRTKlSABl7w4Czz6B3rAfKTG6njKLN8dbRh6///3vs3v3bjZs2EA0GuXTn/40AwMD6LrOli1bSCQSpx19/Na3vsX69evRdZ0//OEPdHV1UVBQgDRswEuSRH5+Pl1dXei6/q5+l5t7+k3t8/JO3fA2kUjQrXh5aHULRR4bqqrROxTlnmvrcLk+WOlLXu9bq5uejIHNWzj07z9Jfza4XCz70Q+wlo32Sp6IGRctZ9Ujf0h/FkWJ2jFT+FHeRciiSI7FfcZzAfDkTeDGz32Xof4uzGYbeUWlWO0u3krHbSjq59hQK4FYkCJHPlU5ZZhkE14crCi5ib5YLxoqUsKJMaizpCZCsPcYOd4C3KeIthyHf6CX/NJKbrzzO4gREdUhse1AE8lkZsqP0WjA63VQVhAZdYwptR7yPTZMpxDDMSSjJAZPqgnQdfSgH2/9mLf41e8MLx/ZyX27Hk5//tmG3/K9i79Mvbf2rBz/7dyPZwtvtB6cDziX1+VQ8yCPvNJIMJK6P1/e1o7LKvH1q6v5yRPHCIRHkyFZEnBarEQMFtauvp+Jsy+iZtLMlPKiIOBwuHF5Hfj27GX/j/4tLUAjWa0suP16tu5ei65rhIN+qidMT197NcfMhVfdSuPezVj8cf5r7r+gDsQRNAgaJL7/j8wUWbeYRAF0VUUWRzutjEYjTqclLRB3Is7GNd3Tc5BfbPp9+vPvdvwfX5z7MRZWzHrHxz4R7+VzcSZ4v8zzdHCm68H58Nsd1tECNnabAbfbmhaoOdgU5xd/20w0nkpBPNwyxG8fP8C37ppJRcZvcHCH+XJuyp+EaDBjza9AlM8vJcvz4ZrHenpGtQ0DUIcGKZg+Jf3ZII+uSTQYDFgtRszWVLaWI2mkcM5cBjs7aT26B0dJCQUzZ1CcV5Sx/3OHt/LAnlTLrt5wPz/d8Gt+cPFXGeutPts/D0VVGfCnSNmJJUpDgVjGM9IXiOGqvoDJ0+eCrqLLFtYcUpg604nDdmb3TX3VBJp/9Vtiw4Tb4Mlj6j99nty8kb93MhCg4f/9MaN3cPE1K6m49SOIbyJwdj7cM+cT3pI8NjY2MnPmTAwGA6+99hr9/f14PB4++clP8pvf/Iann376tMnjj370IwCeeOIJfvrTn3LPPfe8s9m/RxgYCJ3SEyYZRI52x/jyVflEuw8iSkYMnjEc7Ung90dIJM6FptW7D6/XQV9f8K03PAGyEqflwf/LGEv6/fgOHSZsPrVITiLqQxRlvGXjWHLD3ezf/AoWu5OJcy9BsnghIqAAfaEzm0vmxNy4C90AhKNgtZP+baKgAxo6UtpxlRTi/OXgI2zrHOmX9E9zPsZEYz66plFsd/GLB1IvhK+stGHxHcadkIhs24laVY4ydTq6wztqGmrMx0t//R/mL7yB4LZutISK5DIye/JM1m/fmN4uJycHu91FX1+QwhwzKxZW8ez6JnQdCnOtXHdRDQHfaC+a1+sgaTBjcLtJnijqJAjgcJ3x3/NMoEkKzzZkpjHp6OztOoRXKDztOtU3wtu5H9/oOG8Hb7QevNc4W9dlNDQiQx207d3KtXVgyq/nL68P0e+L8eruHi65Kod54z1ML0jQOCGfLYf6UIYFEq5eVINJ0hFzCjGZLOzb/Gr6qDMvWoFqdDHY56fzH49lKJeqkQh2f5yFRZPRkkmsl05m0Kjh6OtHiPrAaMHoKGbSwmsQQ2EGn2lGDaZIrSCL/PMV4/nmwzsRBYHbl9YirXoIBdBiMTyKgslkylDJnjVjOs0HdhAOBSkoq8Vk96LrZ+eaSpLAlrZdo8afb3iVcY6x6GdJXO3c/f3PLs7Xeb4b68H58tunj/HyxGtH0wrHogDL51cxNDiS3dI7GE0Tx+PoGgjT74tjlUd+gzney9BTv0AZ6gIEHLNXYJi8nKR4fgjdnC/XXNYN2MeOIXS4IWNcdOdkzK+ivJLtO3dlOJFnT59FMKwSDI9sV5k/FjGnEENtjITJArIL31AMSKmPKmKCZxtPeg/rOod6j5CH95xkx102p4KDzZkO61njCzN+X5FNxWnppbOtlyHfIGUlpVw9oYJ4NEEscqJAk048HiYY9GMymXE4XJxIYQQBogcbibW1Y/R4ECSJeE8PgU3bEYuq08+k0N6cQRwBOp98GteChaju0bYZjNwzWQI5grckj0NDQxQWFgKwbds2BEHghhtu4I477qCxsZGnn376LY4wGldffTXf+c53KCwspKenB1VVkSQJVVXp7e2lqKgIXdff1e/OBgyizvLJRtY88v/SYXJReo2LbvriOzaQ3/fQNNTw6EiZFouPGlPjfraueoSWw3uQZAOzl1xNWf0cFt84AQEho+ErDOet6xCJK5gMEtI7tL0EQSc81MHeDS8SDviYMOdi8svrESQzPbFednTto8JdSjgRYbq7kqKD2+jb9SpoGjmTLuJ/PrWMhzf2YY91I289RP/+g6kDr11PsqmNgtvuRD1JjKO3vRFRkjENmoklUr3wVH+Ccq2AmqtvIRALEVZjeL0FiGIqGmKURK5eWMmiKcXEkyoelxnTm8iYq1YH1V/4PEd+9nPUaBRBkij/2J2Qd24b44oIuEwOOoOZ/fRsRivZSvXzH6bkIFpfMygJJG85gzGFp+/7+Qlr3OvctvRufvFUF8W5JpRDr/K5i28j0dTHHfku7pxSQquqIGghKiq86BqY7Xks/9i/0NPXR6C7GafTSiToY9OzDzBz0fJU64yTkOjtw7d7N4n+AYTnX6b6W18huOOPJHqaEc12cpZ+Ar10EkIUnBMKiXUEiLb50RUNV6ufn31mHrok4ZEVenflED+cOm5k9RpWfv6zdPb1EI1GyXFY2P7S3wgO9jF5/iVsefkRZi+9AaPt1IbFmULTwGkabYS4zA4EhOwTkcW7jnyXmR/cPZc9R/pJKBpT67wU5Zgzludc+ykiYLKIyzryLpMFldCGfwwTRwCd4Jan8ZRPgtxzm93yfoMiGSi/804af/LTlENXECi6+iqkotJ0vbQkgblP58o5l9EV6iOhJCjNLcLSrGEq0IknU8aOIAjYBloIHNlDJKcCw2ATrrEzSbhH6rZFQcRhtNMXzlS6t8qWc1ZWNa48h09fO4lHXz2CQRK5eekYKvMzc7uUyACvvPoSAV9qXo37dzLrgksZn1dMTLAP/z4YGurlmWeeRht2Kk6YMIHp0+ekhc1EUSTe1c2Yr/0rBocXEFAjQ/StfQERLS0MqJ2iDApNS/fezuL08Jbk0W6309KSEuXYtGkTADNnzgQgFothNr+1NykcDhMIBNIk7ZVXXsHlcpGXl0d9fT3PPPMMK1eu5JlnnqG+vj6dQvpuf/dOIaFzbNeajPxqTVUYbNlHWWUdyeSHt8ZLM1spvHI5rfc/ODIoilirUz2GBEEFTUWQTOzfvoaWw6nInqok2fjiI+Tkl+A4KbVCECAR6qMroPK3Vzs43OZnfFUedy6rx203InAaRb2nQDTQw7P3/RxNSy3hax7/MwtX3Erp2LkYdIXvVl+GrfkgqqMcu62M4NqR9LPw3ldxe8v4+PKLGNzRT99x4jiMwbXrKFi+AvIKT/gdAuGAD4vdAaGReydndimJ/gi+HUcRzTJlCyvQZUuGEIeIgMcxOrXuVNB1ECrrGPvjf0cZHERyOFLqbm/rKp0BVImrx17OoYF7004Uh9HG2NzaD30t8PkOc2KAwUf/HTU43GO0pJ59guekNU4l1nOQsvxSbl5YhG2gjqFXOkkODffbOjRI5eQ8Yr17MFo1utUoYc3BE1t87Dk6QE1JDtfOcXJwy5MkYlE6mw+z7IqraLr3txlzsZSW0Ls65TnXFYXQ+s0YpdQ5tFiIwOancYo1DLzWihpVsFa4yV1QzuD6VtRAAo8VVNmIhpGC2+4kf9ky1GQS2VuAarJS68plz2uP8/qLa9Ln3L7mGeZddj09bUcorz875FHXdabkT+DZhtVEldT8JUHkipqL0T4YySlZvO+gUSb04pW2ga5gFqaT0CvRGKktK1B8XDHFw/O7R/oQ3zqvEI/iI0nKASmpUWIto1WUFV93ljyeAoq3mJoffZ+IfwCjyYzBmZ/hWJYkmbg/jrKzjwKzjCAbUfcOkMyzoKsqx014Q6KfjpiDPzdWcbjNz4TKOu4oM1No9ZE0uAEQVZnr65fznxt+gz7sFXCZHFS7K8/Z7zNKAnPH5TOlxoPFYkBPKqPe+X6/L00cj2PnpjXUTp4LphR51LQkr722hmn1dXhtBuKawPbDzdTVjcXpTOmu6LpOwdIribZE6N/Wiq7pOMd7Kbn2oyiiOCxzD4aCIgw5bpJDvvT5nJMmIuTknbPr8EHEW5LH6dOns3r1aubMmUMgEMDhcDBrVqou4+DBg5SUlLzFESAajXLPPfcQjUYRRRGXy8Vvf/tbBEHge9/7Ht/4xjf49a9/jdPp5Cc/GamJe7e/e6cQRAEleYpIWiKG9E7DYe9jJFSN3oEYat0sir9di++BPyI7HBRffx16fgmhgWa2v/oU0XCQ+ZffyLF9W0cdY6C7DWd+pvphPNzPoQMHuG+LnO4/tf/YAD/9y3aWzC5j875ubri4jroSJ9KbyHsbdRDiKhhSJKq/oylNHMsnLcSQP4HmsAFpKERhLETwxftRAIOnDF0D+8wbUOMakkEjcmg10YPrsY29CKt1tEw2gH6SoI2u6xRWjGH3+hfR6wVoB2OeFSUUJ3wsVUyvxRT6Vx0l/9rxqI6335dJ1/VU82d7zjlpDPxGKDWX8e0L/okjg8cwy2Zqc6pwCTlvvWMW7ymUzkNp4giAwKkFrESFr12Zh6l9I8aiC0nuzJQdDu4fxFTq5uAP/oPy732f/366lY7+VCbCkXY/vx6I8O3rPocgapglN5LZSM2Xv0Tftp0kJs8mYXMzONSDnONGGX7pK7EYJtfIs2CfeDW9LxxLf460+BBkEXORA2OlnaGkgHP4jafKRigoRYD0c6AmwhzcMdJH7DiSiTjSKdoUvBPkSR6+tfAejviaSKpJ6nKr8cr52UB8Fu8JTMF2+v72PY57L4LbnsVzw78Qzxmb3kYMDLBYaOW6zyxAT+gIBuh9+gn0movAmSKPqmTBXDUFxV1MRDQiiyLGniNIrvxR75ukptPri5JIahTkWLAaTy2CIgUGUXw+ZKcL1ZWL/gFqLZWMDrDmsT8w2NOBJMvMufR6ysbOhmECqSgqQl7KLtFiI5ExuSrTiRyIifz40WP4Qik7aF/TED/1xfjhrWM5sYyvwlLOv15wD0eGmrAaLNS6q3EK7nP3+1Sdwf4B+no6EAURb1EpeW4X4gn2mHYKj5mmqRlLoaIkWTJ9HOKmv6IOdWM1mFix4CbCysi7SJIElICGf+eIgn5gXy+y04Sc7+D44qpYndR981/oeeZZQocOkzNnFrmLL0aRzq+63PMdb0kev/71r9Pa2kpDQwNWq5Uf/OAHGI1Gtm/fztGjR7nrrrve8iQej4eHH374lN/V1NTwyCOPnBffvVMICEyceQGdTSfksAsClWMmfWgjLOGEyu+e3MfeoykDND/Hwje+/C08NhkFiai/k+ce+EU6IrV30ypyC0uJHMlUGXXkeEZdw4HOJsw5VfiCRzLG+3xRCtwW5o3xovZ0k0j24yjMR7U6Rh3DHFMZePEISV8M0SwjXFqLxZpKKSubMI/doTq2bD+ebtnOPSvKqbO5UcM+BKMFJZFP8wN/Q1cUJKuVqrtuRBSHUHUJW3klltISou0jhrRjfD1inmdU0xZ7bjEXrryD5ua91M6cjqwZCR7sG3U9lYEIOEbXiJ730AUK5EIKCwo/tM/C+w2CIKCFfRljic4Gxl/4MdqOHjxxQ3ILSnj2wf+mvHoc84pH19zqmo6ppAQ9maRvKJYmjscRiiYxayZMzTGUQC8Ug2C3E1lwOf/x2CEUtQeTQeLLt30O6Q+/QI1EyJ1WT2jzpvQxNMUGZNYyhZuG8FxaxZDaz3f+0MCXbpo2Km3qOETJSG5BMf2dmf1aJVmmsKLurN63ug45Yh6zcvMQhOFAbva5yOI9gCgKRBs2cXLYO7j1WayXj033yJOLS/BaSwi82IkaVZCdJkqWXYvoHCF9ii6hT1vOiw/9mlgkVS9ZUz+VWc7M0qBoUuPBFw6xaX9K5dVtN/GtO2eRZx8x4EVRQD28j8Zf/g9aPI5gMFD92c9gmDTtnPUmFgRQkyFiQR9Giw2DJeecva8EVLa89A8Ge1L2gaoobHjub1xZUIY1pwxIrQsBbQDXYi+CL4ymJBFz3PQne7AyojDf61PSxPE4+oai9Ad1ik7Ub9JFCg3FFBUUvyvv4XCwn8GeDgIJEyIgdjZhFMtxuUaifG6nG7PVlr5fACZMnYPJYBiu1ky1S1N3PEFyKHW/6Mk40TUP4P3I9zhOHwVBINIeGDWHSJMP1/jMrBElp4CiOz6GGI+hmCwo56FmwfmOtySPZWVlPPXUU/j9fmw2G7Kc2mXKlCns2LHjlGp0H1boukbI72feZdfT0rAXSZapGDOJcCSI94PjLDsjHG71pYkjQO9QlBe3tnPz4loEdHrbjmTUg7YfO8RFK2+jt62JRDxlhBZXjSWnoGLUsUVRwn4Ki0sUoNIiMTbRTNt9D9KmKBhcTmq++lX0ovL0dkZIE0dIefa6nz5E0Q1jMVlsmAomsuWFTAL3x9Vd/OCCy5C2/R1jyUwaf/1/oOsIkoR58lR6BxTKF1yEpiUQw51U3n4NQ7sbCew/RM7MmbgWLsQvJ1D0CA7JiXi8z5JgwFsxCW/ZGEz+VtTAAAa3nXg0s/ZLshne191Cs8Tx/QNd1zGW1mcOaiq5sswVN36SPdteR5QkyusmcnDb6wC0HjvE2ClzMdjMqOERgQdznZOAmloHTKKGLAlpER1IGY/WcCrKp8T2cOTXz4GmYSwq4svX3MFPX+oknlT53fo+vnHzrXgK3ej5HjT1RgzHNqAOtiPZzJxMHmWXicMtG+loO0xV8YXsOtRLdWH1KQVNdMHIgqVX8+xDv01HV8vrJlBcMQaTq+ic3bvZZyKL9xKSJJBUkqPGdVVBFDXQUpEvXbfge+UI+vBzqwTi+NZ04bqyKr2PgMrmV57BZHFQPnkxyaiflgObqZ22EHfhiNOzuTuYJo4AvlCcR9cc4ZNXjk93jhD9gzT+z6/QhoWs9GSSY/f+mnH/8WN4A2GTd4qIr4OX//ZrouEgoiSzYPlHKK6ZDif1QY4JYbojvejoFFoLsOhvpdE+GpoSpf3o/lHjoaHeNHkEcFjsDDz3HENrU1kR1ppqSj5+OycuYRbTaFNeFMBkOHUfR1kU0QD1ZAGJswhREhgKJfj1ywHCw1HTXKeJe65OkJcnogx7JSxWO5cuuZwjrW30D/RRVzOGIpcNRbKnHWpizE+yp2nUOVR/LzgqAUgmNUweK+GGzBRYo8dK8oTfKQhgiqr4N7cT7w5hrc7BPrWImOFDaqS/TbwleTwOlysz2iHLcppIZpGCjs6R/dvo72qjqKKWZDzOuuf+Tt2k2VRNWvBeT+9dhygKNHX5R40faBpEuVBHEsBgOqmFia7TsHszV33iGwQGe5ENRhw5hSClthMEkCQxpXxYWs3Qqte4cno1T+8YIXnXza/COdRP4wN/To8l/QGa7r2Xmu98F8WYkrcWYmqaOI6cH/SwzvI7vsKBjjiQSR5D0SSau4y8Bdehirmg68gOB8Idn+XBvSFa90SYp/Zw9XwJrb0dOdCBQTtKwdxCTIvm8Lr/MA9vf5qEmmRW8RRuGHcVNhzHfzoWTWXwxd+hBAbIvfSb9PeJ6MOLrKnQjpD7wWr5ksX5DcVVgefKf8L3+kNo8TC28YuRrR5cITMXXrSS9RteYMPzD2c4gPxDvXhn1GDqsYBPRSiW6Qg3IA7EkSxm3OFBbpxdyEMbR9KLblhQRqIliNETpfWhkYbYia4u7BtfZkrVfHY3+RnwxxAnzeBIVy8PPNzMQMDO0hl3ctlluXTrIYylVtT24aimKCBNNLHzmRcZM/MS7igux9g4SPTVZpzTikg6jRmOGCMxEpseZtnFlxDWRIxWB5ZwH7bYEAnnW5dnZJHF6UAC5KiCGkgQiWnIZpH3UqpDVXWk8omwe1WqUeMwDPUXoOoj9fBqMJEmjumxUAIxkkQzprQvNDWOvWgs3c4Cnt0ygNvh4pol04jFRzINBOHUPYoPtQyRUHRMwyU+SsCPGs18P+uKguLzIZwL8qhGefWxPxEdVjDVVIXXn3qQq+8ux2QfabEV0H38YvPv6A2naj/zrXn805xPnXH6p0EUyCsoJRzyU141nmBgkK7WRqyWER0RXdcRu/rTxBEgcvQYofVbcV9XmSZXFqPAihmFPLN9hJBfN68E80mESNaBnjCB3d1INiOOaYUk7IZz4sCSRFi335cmjgCDgTgH2sLUVI7MKyhYMTlyqZcOonuNyISIOOqQT9BiUAQJyelFDWTaY/qwLQepa2UuNCI7TCjDZUyiWcZWYyd6AtM2Kjq9Tx1Ci6bmFTrQR3IwivOyWpLZ9I/TRpb9nU0IMuVjJ9Pb0UxH0+H0cEnV2HestqqKSfxJP7Io45Jc6Nr55yUJJ1Sau4MM+GNUFjkoybMxriKXZ9c3Z2w3Z0IBspgiS/mlNZhtDmLHJacFgSkLL0cy5ZBTlFkTZ9BA6wwSOtiHwWPFNj4fpaSQGZvWUX/RAvy6TGGRF9exMMmhwVHzi3f3oIWCkDu84BhERLOcUUsAIFgNGKweykuSyFJDRoRkQpmTHKudWMMhjJV5IAgYV97Iv7/SS2y4FcurOzvpC8SxmUvoH8rhrkuuoMy3ndZoL3/Z+1j6WLt6DjC9eBLFtiIskhm35ELtDqAEBkDX8K37f+TO+Ag6Ocg5HvDmkjjH2jZZZHEiVCT0mJUk45HyrETFQmKhMGanhBpIYLM4Rq1tuQUlHNi7Hl9/N253Pl0bjxILB1l6xa0Yv/BPtEZ1JoaP8YPb5tLZOYBDi5LXsg05fwrJwMCoOcQP7WfC9Rezu8lPab6dcFLix4+3pT3vT65vRVE0fPmbKCr3sGTiTHR/lJDiY/2r92F15lJbN53Ecy3pFKdos4+C68YTP0FBUlCTJHqa0TsaOJ5PEwOsV3zm7F/YLD6UEAQQOkP0vHQ0PeacXoRh0uiawHcLmqajOIsxrriHsBBHR8eOGc2ej3rCpAyn6LknGEQkszFNfmWjhZZEKc9tSfXZC8cU7n06zPc/Ni29j65DeeFoteFZ9QWYZCFNiGSXG8liwejJw1ZVSbStnUhbO7L73NTrJ2JhgkOjS0XC/sE0eRRFge2du9PEEaA3MsDW7l0sLVl8Ri2bJF3lkktvJtato7UkwCNiWmDFaA6nf58siww2NI7a17drJ96VK1HF1N/EIMPEChcTyx34gnFynWYUHYyGkfkIAugdQQZWnVAX3jREwfUTiFtOHaF8J1A1gY6B0fXxPX4F9QSbSk+EoOcYogCSK59Y5xFc1dOJKTHk4aCBanRinH89YnsjGNwIKChSEtXmSScwGwwi4eaDiE4/7vo6QCDe30rwiB/bnPkc7zKjBRJp4ngc8e4QQjQJliwlOl1kr9RZhI5GTeVE7JeYEEMREAR0p51CT/k7Sg8I4eeB3Q+zv68RSRBZOe4yFhXPx6CfPynDUUXj//1jD4dbR3r6fOqaSUytzWPZ/Eqe39iMrsOUOg8XTB7Jt5ctuSy//Sv0tB8hEQ1TUF6H1T26dYooCiQP9uHbkqoPiHUGCTcMoC0twbhvL7E//oIcXafia9/F1xZAnjz65WTMy0W02dFIRS9VGTxLqul9riH9wsqZU4o6LD2eazfwLzdO4HcvHKVnKMr0ajfXlGv0/uNRii+eQKx5ExW3Xscho4tYoj/jXPuODnDTJWPYfqiPjXv7KZhQR5miUWjz0B3uRxZlbp18NU8cfIGecD8W2cwPZ/4T+u4A1jELiBx+HS3sw7f2NyCIeG/5N2JZ4pjFuwxJEul+6UV8O3dR/q9fpf+ZFwhv2wWiiOeyS6ibPpmB3g56OpoQRYlpCy/FN9BPQWkVIf8gTQ27qK6bzMQxM0E34DPYufflZi4dX8kKTaHMIXDsj3/CN+Qj99NVGEyjla9NNXU09ifw5li45fIx9PZGONlGW7Wzi+/dsYQf7P5vnuM1LiubR72jmLnLb6cvakbYM7pNUOToAIZpRWiajpyIoiUVXBfcgm/NAydEYASk3BJGJ/VlkcWZw5jU6X01M/0usKOL/OpcVNt7Z46pNhsv9LbxctPr6LrOrOIp3Fh0FSfqRMUsEs45RQQ2D2cMCOC+sJyIBaTh7SJxnVd2ZrZk0nXoGEhSekKwsMxr5/rFtTz22lE0TWdMuZtl8yoz6n5VRw5jv/HP9L3yCoFDDdhrqim//aNoOXnnpD7YYLJic+YQDmT2JbQ43On/i6JA48Do9MnGwWNcVrbklOIvbwTV5EDvChLbOWw7DECyM0LR1dWMrFY61qrRJTuO+nokg5RW+5LFJC6HyN/W96FqAkY5xM0LChGEEZJk0AWGtnVi9FowF8voCkSaYiS7gwjV7rMefdQ1jSXTSphSaKDaGANBZH/IwMRxhRn2sDkWwL/5cWRXPlLYR7K3hcCqP+K+/psksAxfBQMmSzFNLz5JrKMT0Wym/M6PIlnyTsgeEQjsO0Dv6lcz5uGaNBH73PkjWxlOYUiJAsKbtDnLYjSy5PEsQhYEhN5+4g8/Q6w7tYDaa2vhxjzkktK3dUxB0Fnd/Dr7+1LeJ1XXeOzg81S7K6iyVL/F3u8euvrDGcQR4MHnDzLpswu4blE1F88oRVV1ch3GUcqnsiWXkrrZI8IRp4BB0end0ZUxpsUU9KDOY+MVli68G4+nhA5No+jyQkjqFN5yE91/ewQ0Dclipuqzn0K3WAgHhzh8+CCqqjFh/EQKbpqIFkwgWAzYixwMBlK1lgIC3kNb+II7DHUFaAfWEX55J5bSUpKhALI7DyXSRk7ZHCCTPJqNEjrwr5d44am/cfSRNmw1VXz99hv5+pG/MKd0Gi8feZ2eYQ9mVIlxYKCRmj4z1hkXYUUg0rgeyZFH7uI7SdiLsoIaWZxTyJEgifYWtFgMU3EJmqcwFSkxGHBdsQT/3n0p4gigafQ//xLllRWMTziYNOsKBE3Hplh5aedqxo2bwYzcOuwXrGRw1Rra/vOXqXM47Pzbl77KL1/vZ8k8aLJGUL54E6VxC6LswuzOJf+SS+hdtQoAQ46bkmtv4Eq/GetiOyZiNA2OfhByHSZcw+uKjs4LbRtwTbiKusIa8kWBSNuxUfskRAWjqCM0H+HY7/9ArKsb58QJlF5zD0Or70WyOsm55C4StuJR+2aRxduBnlTRT9GyS48p8B6Sx6OBo7x0bG3689bO3dTklHNh0aJ0NK0zECenVMRZWIEWVRDtMgNaHC0o4bGnHNmyJJDjNBOMZLpbrKbMyJZRElg2t5z5k4pIKBq5DiPySXaBlIzS/MCDRI6mnt14Tw+hY8eo+dfvoJjPvMbwrSAarFx0zV289Ndfk0zEEASBOUuvw+IYYb2qqjG7ZCq7ezIF/eYUT0dVzyweakjAwN7MDCk9qZH0KzCcHKXrIJlMuKZMxr871b7MXFiIvbYGVdNguJVKIqmQZ0zw+Qs8RBQBmwEUIYyi2tPNVnR0rDVmfDvX0P7Ea8g2KyXX3IRoKUU5J2mrIrMcCi0P/R/xrpTtNrtuDGWTP4EgCun7Sgn5cVx0N1F3PklFwSAJyI2bUaNRGFasl5U4LX+8j1hHJwBaLEbzb//AuH+vgvxUSYGqakinaB0omIwkT/jT6DYDtrpcwo0j1949p5SkScoWoJ8BsuTxLEJXNXw7d6WJI0DoyBHCTcewTp78to6ZIMHWzt2jxlv87VRbq8+bez2WHL1wRuMKipYS1s49RcrLyXjz36JzKoE1l8VBSE/QaorR0babcUfCtLy2CUOeB+uNyxD++S70UAQxN4+kLQ+tsROD00xHewdDviEOHjzANddci8OT6hUkmWQEAZSYH/9QD9KEGgyvb2LoofvS5/QumEH08Cqc05Yi2GsRX3uB6VXj2dE0Ut951QXVeIUYyv2/QQmlRG/CR5tI/uqPXPfJpcRtRl5v2ZLefkxOFS2JbibPmMvQli5MBRfgnL8YXZfQvGVo+vEfrxONBgmHQ9hsdiwWB6e8MFlkcQaQw35afvlLwi0tWFfewEDUSrIPyopyKLzsUvyRQQJ/f2rUfuHDDcQajxJ7bR2m4iIM19/M5SvuoueBv9DTeBTr3W6G1r6e3l4JhvD/4+9899ZbSRweolayouXn8t89j1KVW8miUDWFl63AMWYmWjKGKDkIrPNjTw7hKi4hvGEDJVVzqci309Kbeq4EAe5cOgZDvBVBECiweVhacwE5Zhc9yS7yDB7kSTkY/DEsZQJKxI9sdTJUpGHt76Zv316MV1+FATD0DdD692eo+dJ/ohqMJMRz10A7iw8hLDKGHPNID1RAkEVE53vXJkCSRPb1HBw1vrlzF4tKFsJwiUyOOc7/7HuA9tCIfTPLO4GP1Fyd/izrCZYvqOJ/H9uTzg4o9thw207RXkoHt/WN206p/X1p4ngc8e4elL4eKDv7jnNdB4enipWf/BaRwCAmqx2jNTdDLEfXYVzOGC6tXsSqpnXo6FxStZD6nDFnvE4IJJGdJhhrI6zHMEgGjN0qgn5CSw5ZxH+sCclspuwjN4GmkfQH6Fm1Gse0KSClrp/damXgudfpffq59L5FN1yL65KL05E5RYBI6y76XktF5pRgiJYH/si4b/8rcOq2Yu8EoigQ3LohTRwBIo0NxI4cxFo6UkMqecpQwwmsEQlNERBNCskJi8F8wpwiIcJHjnIyEr29yMPkUdN03PPn0/3iy+jK8DUUBAqXLePExL+kANa5pVjHelEDMeRcC5rThJJd6M8IWfJ4VqETbhqd0hBt7+BN2gy+KQyCgdqcSrZGMwlkoT3/vDJqivNsmAwS8RNI5PxJxTgs8lmJmCUkAfecUobWjcjoSzYj5jwnt+ZczX07H+ZTXaUMPv0CAMkhH9Gf3Iv41Tt5QW/hNv9YQq8Ot8wQ4LILFvH0jlWEw2H27t3DokWXpNW/4sFennvwF8SjqaL+4oo6Jt18PUPPv0TB5ZdidIQJHwvh3/YCUtlyImtWc/WlZi5cXE9Alcg3afQJKrbwUJo4pn9Hfz8zTOUEvG5eMa9HQODz1bfgaNQR+nQssx1Yr3AQafUhWK0YSxzEhRHi2Np6hDVrRtIyFi++mPLy2vPqXsji/Yd4axPhpiasV9/IH3tyaNnbDXQjCPDdj82m3ONEv/Um9CE/Jl1H3bWb4MbNmCvK8G3cjO2m29isFbBxfYCKAoGrlt2I9MdfoSZGJ3xGjh5FGdAI7EoZ0JItwZcuvoV7dv+MugIb/U3NVCYnEmuLA6nnxz7RQ/zwAfrWrKaibDJfmF5OhwSRpEaJ3UR1nogWM/GlshVE8+z8btff0YZTT68ZdznTCidgK+znyL1/THupPB+9gcTkaWxKJhjcvw8Ah93ORRctIhGMoua5stH+LM4qEkDOFbUMdvcSjISwmizkeb0kjOJ7dq8JAlRZvbx20vg4RwkGSNcJDyYG6Iv5WFE0lwLRQZMywGt9u7mqOoCJlKBiQhPxGEPcsyKfgagBk6STZ06gJ8OcKUERDacmlqJ87hTHdV1HMrlweN+4HZZZt7KyejmXVl8E6FiwpRVpzwSKBCxw8+QLz6AMk50x1XUszJ2Z3iaZ1HBOqKfz6WcY3DzibK7+zKfQpJGyJbW/P4M4AnQ9+gSOaZMhP9WrQ4pH6Vu7lpMROnYUW+XZtyE0RSF4eLRTItx0BOtFizl+wwu6jNqiEDiQqjcVJIHcpZVwgoyUYLFgyvcS782sSRVPEvL057uwffWTCLsOoScVmD4ef0keJxcxKZJA1KMRc2vYDCk9jSzODFnyeBahiyKuWTMJneQhcUyZfEaF1BnQRK4acxmHBo4SjKcMqSkF46mwl73Fjm8fggCKpiOL4mkL/eTYjHz343N46OXDtPcGuWBKCUtnlaVlt98pdB0M1Tl4nSYiRwYxeKyYKtzEJZFQNMpSzzT8D6b6d0pWK2oshq6qFPrh8sIFaKtPUH3VIbapjxlTprJ223p0XU8vnEoywY61z6SJI0BnSyNjL59BzZe+QPsjj+EaW4Vt2o0ggKqlXoiRl57FxLN4RRFbbQ01X7gHaVBiRDYpBUGWaYr3Umuo5JPTb4XBOJZVQZLDBeR9TzaQt6Qa89wSVFUjfsL1i8fDrF2b+Yp/7bU13HhjEUbj2U/jyeLDAZ8+gNKf8g4PeCto2TcSWdB1eOilBj6+xMsL69an14NxdTXUFORjr64h55KlPBbxsuFgb+oY/hgHW2S+//kvYxRHk0fX5MnEOkeEFNRwEr0pRpWrjILSyTSToFk2UVuTgzAQxZRvRhdDaMc0kn4/A5ufxzNvKfZBEdkpYyvMwbetB0EwUzyliu/u+32aOAI8fugFpuTW0fan+zPSG3xPv4S/pIJB/8jaEAyFaNM1Cuy2tGjF8UwEJRknZsvWxWTx9iEI0NLfxsuvvpQemz59OhMnTgfem3tLVTUmOMuodpdzzJdyznqsuSwqmIhygjCf0Wjmq97LSfzlKdRQkJleDzNvvhLpBNV9k0GgdevTdLc2IggCuq7TClx842eATC0DORYi2dmBlohjLCpGc3sz7Y1cD96ll9D38qr0UM7cOQjeAs413qyERhB0OvrDbNrXjQ7MnVBAqdd+xiKGiqqxZsPaNHEEaDjWyLi6atzmFN3RNJ24Nx/vFz5LYtMWtEgE8/y5xMpKMQtS2uGghEar16JpaOFI+q7SDUbMxcUk+k9qZZGXd06cz5ogkjNnzih72DllckbNox4zEz7QPvJZ1fGv7yR3eTnqMD/2Y8J4/UdJ/uFetETq3WG7eCn9plzyh/cTBNjZvZ+/tT6OtywPWZDo6nicS00XcW3N8hGRHkGnKdrM73b8H/5YgCJ7Pp+ecRse6dzfVx8kZMnjWURSF0lUV+GYMpng7j0gCLgWLiDs9eB+B6mFuaKH7yz8Mj2RXoySkXyT95yJ5YTiCq/v6WL97k7qytysWFCV0bj3jaDrOnk2nVsX5aKqTvLyPJjNcipnH5BDSdRAHMFiAJeJ5AnvSV3Q8Ks+fHE/OWY3LtEN+ujrlRQArxVzoT21qA6veDlmF7IthnvGDJz140j6fBjcbgwuJ5rViks3Ar6MY2kJlQJXPivmTMCbl4ecDKCKdgaGAvR3Np/iuoRoMJdivel2omtfpO+1TbimTCZvXjWWkmKiw7n4osmE95abCUfDSJpE/srl9D75bPo4juuXc//Adu4uH0teUMcZz2dIbcs4l39bB7mljlHy7fF4DE3LdJFpmkY8HsuSxyzeFjRR4b4df2elZwIAsVN40KfWuljz+poMw+5QczNVy6+itX0Q6+SZbHw400CIxhX6sOHMU8m75ioGn34OXVGwlJdReNlVDKzNrI9O9if42gW30H24jfKONkxeDw0WD3sGklywYx3FFy3A6KnClJ/P0NbNRPt7cF51JRR4iXYPovmiqIEE0XIbkWR01G/wRQPoyUwia8xx094/Wl2xJxBAtzshqYOepL1hB5tefAQlmcBbUsmilXcim0cL+2SRxVshmYxlZI4A7Nixg+rqWqxW93syJ12HPL2YT4rLGaiNoaGRF7LhjXuIn/C6KVIsDO1tIveSi1FCIWSnk9jWRvLKJ6ffVWoyQWCojymLViBbnAiCTm/TAeLhzJZdUjhA672/IjSsJCqazYz99rdQC0ac4glBJrFoKSX1E4g1NWEqLydaWEZMMPDGya7vDKqm09YToqnTT36OlZoSF+aT6jXb+4P8+MFdzB3rBuDHD+zgG7dNo9RzZpFVVUkyMDhaFT4SieIe/r8sSxxuaWXzzh0UlBUjGwx0HT6EZ6Cfq64o5njNoynfg8HlJOkPpI9j9HgwenJH/jaCRPGNNxA6dDhNwCwV5Zhras9JqxhN03HMmo370CF823eAIOBdfCGmMfUZarnJ6OizK8E4ijZCT1RV5xebw9x02z3kqmESspknW5MsjpMmjwaDxDFfCwtLFpIvVaLrAoGcTpr8R1N+meGTBjQfv9z0e5Ja6rxdoV5+tfXPfGvelzDqo2smszg1suTxLEJAY0vDYRyTxlOxcB66IHCgrw9bRwfl9ePe0bGtup0qSyr94Fylt2jAQy83smlfKgrR2R9mZ0MfP7x7LvZTNKE9EclkhKeeepxwOOUBkySJa665Frs9F9qC9KwaMS6ttbnY5pelyKCgs8e3lz/s+CuariEJIp+eeTvjnfWjCKQgCIT0AGoihkuQkWU3iibgMXpQXUls1VU0/f6P6e3tY+qwrLwUszkHVRIyelTJThO2yDGU136PD5DdBeSs/CpHQjbyq6fQtCszwpdjkpB8+/jlHi83L7wArchO5YLLoH8I9/RpeBZdAJqGMGkiz2zcQDCYaj1y+fJLkKvyMAbjxFxmHo8eQhaNNK5bRd+xRi5e+Tki86zIgog9biKxYwBBEklViqbmayCJGOnHYTRhNBpJJEaiNiaTCas1SxyzeHsIqSEaB5t53KFwy6c/ipEkokCGmmldkY31h0cTsq6+AL98vpsbLq5l6hgvOw9nEjFJiZEIR9msa8z+0udxGmR0iwE0B5BJHk21dvwbN+L76yPpsZyxdVx9y80M1S9jaNPrGOdeSOHnPocUCdMp6jy9YUMqzUySWDpvMZYdYAtIFNg8aSEqAEkQIWlDdjpRAiPGVWJwiKqKShoaM6Xwx9SN4XgwIOLrZt0z/5f+rq+jmW2rH2PeiruQdRUx0g+CiGrxoGRfp1m8BZLJOMnk6Gh8LBZ9z8ijKAqEj/rQdgcYaY7lx1+q47jMQXJYTUUIRYgP+eh5aSQSWHTlcgiFIDdlm4gGM/OvuoNX1m4gGm0GoKa6krziTMXQeFNKZTX3rtvRRRG9qYXOR/5B8ee+iDpcYxhOJHmtMcBLm3y4bAUEG4LMnTjANRe5yLGcfSNfkgTW7urkvhcOpccmVuTwxRumIMspp5rRKHGkuZ8fXCpjOfQPQGf5ZZezp6WfmpIc4vHTF80xmi1UlJbS0t6eMe50jZBQTdPSkd2e3t70uCzJ6JKUzuyUHTYqv/Q5Ov/+GFoohOhyUnLjtch2ewYx1IsqGPujH5Lo7EAwmjCWlKFYRyvTny1o8XCqXvOmGwAItbWhJyJw3JYFBPvoQIhUYEM1GtMhF4fFwBULKgnoAkd9FpxmI5WVOkXekT6PyaTGBYWL+ftzbbzcmlr/S/Jd3L7yGk7Mc+6PDqWJY3osMog/6ccrZ8nj6SKbg3MWIQoiY8bUcqS1ldV79/LKnj20dXVRUVH6vqhJC0SSaeKYHgsn6BqIIIo6mpY4Ze2mIEBnZ3uaOAKoqsr27dswqBpDa5szto8cGUQIpgiQX/Pxx51/S6eZiYLIxtYtJITMNAxBgKboMQa69iK//nfCf/0+sXV/whrtQG54jdLBAO0P/yNjn1BDI3ZVZNuWZzHNdSMN9/CRnCZyLywksO6B9LaKr4fo3tXouk7cNYHS2vGpbWWZmfMvxtyxH3HXE1w+0cq2Y1FaWhsIhsN0G3PQvIV0PvEkA9t3svvIkTRxBNi8cQfh4jz+W9nEL7qfZ0iPsmLMEgK9vUxZfC2Pv/QMqza9ygsbV7P66EaMs/Jwzy1LN6s1KQGia/9E/1/+hcgj32XZhfOw21MLr91uZ9myFcjZBS+Lt4G4otHSESXH4uJosJ1fJ7ci1Jr43iemUZpvx2KSuXJ+JUWiicKCzJQeQRDIKTAyrtrJI68c4foFpfzn1Q6+vTyHxRNzqCuy4RYVFMHEnKnjydO74fBzJJ77KZp/B66p+WmdJ1O1g7jQT89jmYI8wcONGNob8Fhj6BfM5bFXnubvq1+kwyjx2jBxhNRa88qWtUgTHOj7Q3x24kcptKUUEh1GGx+t/ygPPd+L8ba7MQ4LYxly3NTc83m8haVMnToVYXhhq68fT2lZZfrYQV+mijJAS8NeiPmIvPT/6P/LN+l/8BskNv0fRjU0atsssjgRFosNt9udMSbLMg7HG9fYnWvIsgTC6KIvQdKR5JEXvqYq+LZuy9im69nnEfQRwiSgsfdgA8lkksqyMvK9Xo4eayYSP6F+TQBVEhm86AKeP3aU5xsb2OF2YJ4/FyEZT28XiSd4cWMbmqYzFIyjqDrrdncTjI7uHXg2EAwl+evqTEfSvpYhOvtGbBGjUWJmrh/Dut+h9Lei9Lchr/s9M3N9GAxn5jyKxZNMmTKTAm9qrTIYDFw4fwExbeR9rmk65WXlyHLmsWdOm0HyBP6TkNwkC+z03bmEjR+dxsDtS0jm24mL9oz9dF1HzclHmjANsW78OSWOkiTQ9/IqBtZvoO3vj9D290cY2rAJ/87t6fUWIGLQsS6qQDSmnAYGjxXL3FIS6sjfWZMS6ILKg88f5IWNzTy8qoGtB7tRiJ1wRp3uLmhsHXEQdvRGONyYyLC/nabMawJglk1YZcvZ+/EfAmRdpWcRAjq6S6C2vo6jh44giiJjp9STNCfQzjAfHsCk6GiDUXRNR8oxkzBL55SEiqKALIkoJ+SjW0wyXofKq6++RE9PD5WVVcydOwcYSWUVBIFQKDjqeIFAAF3T0BKjvXH68FggHkQd7o00yzuWlbYKLIe3I/Y/iHn6MuKOcnQEgnqAtu4DzG44gsEzniQVIBoIH9wOiSEkjwMtHh91Hq1vkMmmIgZ9DSi1BmrGzUU1m4jvegQ9mbl9ovsYnlkajUNJFlVczLTqCkRNRW/YiDKYEtsxSzpDYY3KXC9H+iV+9Y+teF1mrrzpC9SWu+na8XrGMYcGBxnXCf9a9HGihfB67zb+sOPvfHrmZTQ2t2fUOwz5h/Db47i8puHrCmrbHqKHNqZ+SzSI+NJ/c+2VXyZmLcBkMiGKxveFYyKL8w+tvSF+949GPnL9StAGGS8V0LX3MDZnL9++fiwNXQMU5Dkxy1bmXDCPjes20Nvdi9VqZcLcyfy54WEunLGCQ8cC9Hd2ULnlXjzAjXVz0MYspD2hk6OE8cRVel85iKYIeOd/hNixzci1Ku4Vs1BiITZveoZKY/Wpn19FwzzUQchShCiKaJqGpmmjarETiQQJQUUASuUCvjHviwSTQUyimV88eIiWrhA/HoyxbOmdFJs18gpc6KUeRNHAlCmzGTculbZrMlnRT8h4sNhGp6LlFZQiDLQQa96THgvveRVT2UQomXF2/jhZfCCh6jITpl/Awd0bGRzox+FwMH7qfBRM5ywV862g6zrmQgielJ1jrzWCrnLcy5NMjn4+0TSSygn1y2oCt8XInOmViEc3gz2XxKKZBKMjmQu6DpFcN7u2bk6P9fb305ibS67Zmo4SJRPqKd9tyVPYE2cDiqJlCP4dR+yE8yUSGsbmDRmUBcDYtJ7kuNlndL4kIt984BCfvXIOs+dJaJrIfS+3s3hmkmEfFwBmh5vrr76OY8eOEYvHqa2pweX2ZKZ+CnHua3w53ULktdYtzCudwS3jrkPU3xszXxI14i1to8ajrW3kGSQSiZTtk6cMMHBoG/bJtUi2HMJHDiH1RzFX16IM25mBSJJHV2WKUbZ0Benuj+EpTa3RoijS0Oobdb69Rwe4an5l+nOunMu19ct47GBKYEhA4GNTb8Yhut6+NsmHEFnyeBahiRqPt7yCwSCzfPkFqLrKY8deoaqniPFlZ9aqw5TUGXjmMEogtWALkkD+NfXETyV5fZbgsshct7iWv69qSI/ddUU1L7/wDNHhxb+3t5eDR9qoqqzEJKXIrKbplJWVs3379ozjTZw4CQwy5lInsfYRb5Agi4iuFEHKMbswSgZEQeRqaxnSqr+QBJJAtHEb3pu/T8xeii/up0qyI9rGcuTXI2lkjnF1FN39UcIWKzmzpjO0ZWQOksWMlkjQ/9RzWGtrCM4eQ3SgmeC6LeTPq8NUOhE5fyJqNIlsN+Grq+Enr/8XwUSYPPOl1G5/mmR8pF2vVDGVTS1JZtdYqSq4nH9/JHWd+vwx/rQuRllBmJVTq9i3N1MZ1+1yExdV/tH4EgeHjlLhLEJGIhAcHanw9XdSlWsgaStHkkRiRzOvqR6PkNz6BPblX0dRTv1yzSKLt4IgCDR1BQjHFLZuVvnIFAcvPnVv+nurw8Wym+/hJ0+18NkrKvHrQ/SXx6mtH49fCfHn5scIJyIk8lP3cJ5xxLBMNG7GXX8BVYoLKaHS8NP/wlk/FoPbSctDT1Bxy9UkDryKkFsH/b2M81YiunKRZ07Hv21H+jiSxYJs1lADIfx/+gOLb76eV3fvRlEUJEnK6KtmsVhw5jqwXFtK3Cxj0CRyJROiKLBwciHHOgNE4wqPbu1FEOCfr7MjSCZ0Usbs8Zrhk58nR14xdVPm0bg75cAxGE0sXH4z0bX3j7qm8bb9GMpnZYhBZJHFiRgKxfnJXw9xweRxVE02MxBU+J8nWvjyzbnUFJ27KBCCQDShYpBF5JP82Jqmo5mC5M2XSAxZ0FUweZIkDQMoiTKOl0/IuW4MbjdJny+9r622Bt1pS6cX2mWBSU6V2JanMFaMR4v6EV75HWXXfSNDgGrwFO++5vZ2ZqhJBCFl47htIosmepnj1bHGgsTMdjb0COTZpVH7ng24HSZmjvWy7YT0e6tZpsR7YlmIjmRzj9pXsrnP+F0smuEzN1WxN7iN+/ZsI9eSy5KFl1LmzMwk0jQdo9XFxKkzyMmx0dcX5GSKOxgfGNV7cmP7dpbVXEyu5OU9gSBgXjCLUOORjGHz1ImcWHulBMMoJV5e3f08/sE+qmsnUt0nU1hSimJJpaWKukw8Mbo2Uj+hRl9VNaZW57F2Z0fGNnPHF2Z8FnWZi4oXMtE7Fn8siMeaS66UmyWOZ4gseTyLkFWdS0tnUhYMYV73KLpk4O7JCxhwus/4WMnuYJo4QkqBKrCtE9viSpRzdJPrOiyeWkxVsZODzYOU5TuoyFE4MEwc6yfP4uighV8+3o7T1stdK8YztsSFIIDTmcdll13Bhg3rSCaTTJs2nbKyShKajntRBYHNHUiGBCZvHNllQpdjgBWH4OLzs+9id9sOTHvXZxZuayqJ9v0I9aW4TU5s7kqGXnkRQZLQhw1He91YDvm7eK31AJ+9fBFGl4PBbbuwFBeTN28ubX9/GIDIkaPUXHcl3fc9RKSlBXNBLkqilObf/i19uqJP34VVNhNMhPlL8+v806UfxbN/C0pvM1TMoiVnFrONbupLzSjIRBOZPajaekIUlk2lv7+X7q4uBEFgypQpHDN088CBRxEEgdtrVjLbOIHkQIiSubWs2bWezp6RVOECh5HogfXIcytQVR1j+QSix3ZmnMdUMWmUcE4WWZwJdF2n1JtK31k2vYAtq3+T8X0k6Geop42P1aiIAjgSCdqC7WzszHRmGLHy6UtdOBsezizF9g0SP2xA0w8w5gt3kOjcjhbpJPfWJSTCcewTL6L7mRcY2piKPkg2G1VfuQezJ4/BzVuxlpZQcPFsog0vI+bOItHTg7ejlxvmX4mPMIsWLWL9+vUkEgksFgtXXLIYc56LuJbZ6FnTdOZOKEDTFF7c0oXDKrNyjofqUjf6abz+BMnC9MXXMW76QhLxKJ7CYnTJgVpWT6Ir0ygyFtUNN+7OIotTQ5ZFdB1e3dmdMW40nBtCBBCMKzz+2jHW7e6gMM/Gx6+cQEW+LW2/a5pGh+qlyHwMZeAFBE0j7p1FjzCOUuEEJXJ/gJJrr8a3cxfhpmac4+uxVVUiBMMwnPGnKnGkUD+OaUuJHNmObHOTu/gW1GAfuKqA1OPpdI1O0y0uLkYU5fT5HJLGR/KGaPn9n4iTin/edPNNWORzozSvoXPn5fUUuK1sONBNVaGDmy4eg8NuTBOLZFLDWjWFyL7X0IcjroJkwFo97ZRRyzeDJalyOLSFdR2pNbAj2MlfGh7gOzPvBjKvj4E44lA3Eb+O0eIlIWbqHGhvcG5VUY5r6rwHkDBOHIdz2SUEX1qDIEk4r7oMobIsw36JSgKrXn0UTU1Zf4cPbCNRGyNPnZTexmk2smh6CWu2jxBDi0mmzDuSGSKKAmNzDCya6GXtvpQDYHpNDrNKbYiikEEOJV2mQC6iwD6sAJzljWeMLHk8i9BEmWmKzNBw9AzA0HGY8Td8/Yz6PIqigBoandev+GNnrfXFG8Eoi4wpdjKuNBXCD4VSamAul5tWv42XtqSKu/t8UX76l+388O55FOdaAJHCwjKuueaGYRGLkQU3ZhBxzXXiX/W/DO1OeccMnjLcK75EzJhHrbWOqrGFJA43jJqPIMnIWgx3yz5C25/Dlmcl74u30frwSyQGhzDne9nqb2BP7yFiVUvJnVVH3rxZdDz5Ik1//HOGISlaLEh1FdDSgoBE1zMvZJyr576/8q/f+xpfPXAfkWSUfz/4JP+68DNUmPKJaiK5Xa3sfe0B9hzLp37GBayYU8iL23oJRZPpa9fcpzAk1bHk8jl43VZMJhtRonzZ6SFfcCG+Moi/v2X4jANcvHg+jwWfR9M05k0Zh7lxLUJhJbqeMvCNVdMxHt5IoislOGTIr8JYPYtY1kuWxTtEVZGDeRMLEQUNJTE6JU1VFZRIlP6IRKGU4I6y+fxX4/NEk6mkrUsrF1FttlAYX0+sN1NtVZBz0TUd95RK/K/+Gl1NPSPJvjYcM67EUDKNoY0jGQRqOEz/S6tw37iS2iULYaANxTeA5JlDy1+fBCB89AgOYRzWUJyCy0q5dvklJIMBHIUVINtIvAFvMxsMXDKzkvnjvaAlMJssIJ1BnbBoxJpThhXI8Tro6wtiHn8h0SPbUQZTKsum8glIJeNRso9lFm8Ct9XA9RfX8cjqBtwOM4Fwgil1Hgpzzk29lQ78bVUjG/emHJTtvSF+dN8WfvyZBRkq6i7Nwu+2mJk+9jpMMry6zc8dC+1wgnCbURc49Kf7cI6vJ3fWDEJHjjKwcRMTfvT9tL2DZEI0mvFvfByAZF8r0bYDeK/5Ska0zGQyUVlZSXNzMwA2m42ampqMFhnGYJDG+x/gRLT//WEmTB5P0pzDuYDVInPzklquXlSNURJR0TNIhygKxP0KORffhurrBXQkdwGJQBKxUBhpB3EaiOpx1nZsBcBldhJNRkmoSbpjg3gd1entjEqA8Gv3ETuaysqQcwrIueqrxEwjEcV82UWFo4SW4Ai5GuuuJl90vWe8SEXFr5iRF88n/4I56OjEZJmgYiZPHJE/DcZCaJpKeXU9TkcOra0NNB3dz8xLrhkRZdHhukW1eN0WXtvRQXmhg+sX15FjHSnbkWUR8cAuLjm2k8XDgpWGA1tgUyvStddmBCaSqkbnYBR/KI43x0KBy4z4dpuxf0iRJY9nEbqmEdm1etR4vGE7prKpp30cTdMxFTuBzPC7fULBOZFUfqM5ANhsLmpr65BNdv66sXfUdk3dgWHyeHzRlxEEMhZcQYBk+z7irSNpFcn+NmKHXsdYs5ho0zGQJFyzV9L/5M9H9jOYMJROQGnZztBLv0+PJ7qOUn7LJ2l7+AXCLS14pzn5j7F3omw5wGD/AO7pOQiimEEcXTNnEHY40cOpKKp2CsU7LRbDEAhyQ8VCchyF2OMg+iPEXBEiew8gd3YyvWoKHdFBWnsjmC1Ols2rwO2ycOhYL0umFxLu3IvVptLbJ+LJ86DrAmas1FhrMPRH6evP/JuGN/dw44XziHbsRd32f6jRMOYLbkqTw7ghF8eKryIEugEdnIXEBOuouWeRxZnCYpC4a1k9gUCMKfOWsuXVJ9PfSbJMTn4J//zSMQJbdvCrT9ZSPtTI9+uvpc8go0YTtG3awIZjL3HVdbdj6G8l2XUEQTbimnc9iaAdJeBHJJImjscR3v8KgqNq1HwkUUQeDDF08BAmux0tbqD9H4+hD9cFuyZMI9YZQU9qJDoD6L0v4S6dim50oChvHvHTNDCbbcDZUSaOGT24rv0WBLoRRAndUUhcyApXZfEW0OHySblcXFZN2DeAxZGP2V2ALp0bwzUUU0aJ4CmqTld/OE0eRVHE1Ozj5oIchlQjqqpzZ7UJ455upBLHiFCl2/P/2TvLwLiuO+3/LgyjRiNmtCVbZmZ2OE4catM0KW6Z2+Uu9N12u+12u1vGpNykTQMOOmAnMTPLIFnM0ow0DBfeDyPPaCKnjVsnbXb1fJLOpXPv3HvOef7w/LHX1RI400zgTKr4e96aVSi2DJFLahqhU9lK5agKybFhGK9uIwgwNDSEJEksW7YMTdNIJBLs3buXm28uToetauFY+ttPQ9dRg+FMfYarDF2NMzTQyWBXK67cQrwlNUjGTDixIID/8Cnyls1Gzru07jHi23sM77Qry3cWDRYW581gpV6G4WIveo6D3lIztlcJuugD59PEEUDxDxA9/hzS4rehjednGwJR3l+6lb3hk5wKXGCuu4GFlgbEYBjV8+dZL4iaQL7ux6gZ0YdaQJQQCupR8KOqGQE2o93F5nW3E9m5l0RfCwsXzCXSuAjEbHpiM0lcO8/LqjoJk9mKwZKt96BpOpGeTrxNDahjveiqhqG+mrEzzXh0hUu5u4qm89judp7a054+9q+2NLGkMQ99KnDkdWOKPF5FCKKAaLJiaFxDwluNIIDcfQLJfOULFtVlxLu5Fv/uTrS4gmtuEYZKF4k3OclNECSWLFlOMBzGe+YiY6/yiDqtf7gGpCiKxHvOTWqPd5xk+GAfvvHQtbxN6yjY+tfELhxEsrkw1S5EMZgJHXoy+0BdQ0uOYMrPx1pZySZXCV3//V3iQ6lQhYFnt1P/mU/iappJ8Px5XDObOCbmU61ZkWKphaxoNiMajel6RwCm/Hy0cD9za2fxyqO/wNeXSvZ2uHNZ1rCckW0pT6Xnb/+Vf33kIkklVUxdlkQ+f99s9vziX9DHwzEMJjMNFZ8Be2aW0y+zwFVjCmZnGWpHFKFxJea6xcQdpVlhFAnBkg75mcIUriZsFgPC0X4c9ukYr7XRfOQVShtmUTp9JkfaNQLhBDcs8KLv/RX+3tSCMRewzLuW9kgEQRCIDwTR/Hk4GuegJVXafvEixTfmgGhCVybHTAkGM4opO3dbsttxrVvH8EA/oieH8NFjxNs7KL75RnoeeYz8tRsQjUXoyVQOsoyMqXEVop5P/A8QxzcKCdEG7po/y7Wn8NaELOj4+1vZ8cyviYaDyAYjy9fcTOn0BSiGq+99NMgiTptx0rxtNWXnilkq3RiGe/EI3YAGxjzIL8zypCetORS+/W4SrecJt7XjmFaPXFWLZramcx5FXUMwmIHsuo6qkFkn6Dp4vV52795Fa2smYmHu3LlZEUuS0zIpx1KyWpHddt4IvVVBgLbTezjw/CPptoLSalZv/SsEKfXbKIpG4cbFDD/yHxmjmCRTuOWviV3hOGQSLGxVagl19aEWlCDrOqU7TlFw95z0PqIokBxsn3RsvPMUjkVJtHFBmZiqYDh+mmvLZ7DROhc5niDcfJz44gV/vkW+rmEnwfAjX4FxUUTBYCL3xo9lOUFyJDPnvv+ztGCa75nnyV21AtOS9SQnvn/BXp598HuEA35ESWbZ5q2UTFsC46VddB08ixfS8l9fR42momMEWabukx8bT1FI9WE4EM8ijgAPPHmGhsrlOM1TlOj1YupJXWVIC25mx94j9F1M1QqqrahhefXMKwpbhdRrLhTZyL21EQGdpCSQ+DOFKoqiEZfDyD3XTucLPz6AOt6Psnw7VUWXL4wrCKCLKgISqqphqphJ5PTLWfuYSmbQ98ouAKzT6vCXenj+Z9/HmZuHLA+yumYZ7Ud2U2pMDdxCcR3BmUsYFVQ87hK8ty+n2xeitL83TRwvof3HD1D78Y9jKpvDqajKA8+e48tlJsx1dUgWC9q0Suo+9le03f8LEiM+LGWllN+2mbBLpCs6hGfxAvJ80zi/60WCoyN0h4dwFBchCgKvnB8jOWGiUFSNHUd6KfQW4htMhbEl4zH625qpmlWQVoaU3BaEVynaOWbmE7c6kZe8HV0n5XGcCn2bwhsMIzES/h7G/P2YcyXMtnL8Z3upv/5GnuraRcfRA8zKm8ndN8+gVgmh723OOj56bDtrb/07BoNRlBf34Nu9l+EJn/fIgVdwNmxBVa1I9hzUUKauo2HetZxoPkrFlhvwPbUdTVEo/evP8sKxIwyMf8e10+upLSzEXFhI4z/8K4HTEcIXMuJVgsdMi89PbfWVFeaewhT+nFBDI7y0/TdEwyl1ciWZ4OUXHmZLUTlGb8UfOPrK4dBifODGaXRHfeiGEBImIj4TxebsaADZEWZs+zdQwynSJxjM5N/xj0T0jNctkoyjmvKRpzuw1M0iLhoJSSasahKzlFrAC4KIbeltjD2dEd+SbC5kT1EWYXC5clm9ejV79uwhmUxSW1tHQ0NTVsRSQtSpuvdWOn/zNLHePkz5eZTfeQMJ+Y0xFimxMU7s2c7C5TfhtHpJajGOHXmOoK8PZ14qjFSSRKKth9AWXcNIXipfLne4n2jrAeT8aVcmlhUOEjeZeUWJEzx/DkEQmDdvNl7fKLI9FZKqaTqGotpJh5pr56OKxrQyreZyotlEWr/zJUx5XmJDwxS/4y5Up+PPtsgXJYnwqZfTxBFAT8aJdZ/FWDSLS3pnsd7eSUrbI7v2UHDLzeBIPQeROC89/jPCgdQ8oqkKu556kC2FZZjc5enjgs1n08QRQFcURnbvo3DG7HTbpTSjiYgnVWJxZYo8XgGmntTVhK5xvqOXvoFMeGdLRxeV5aU0lP4Rp9MhcSnJ8S8gx63ca+OLH1hGvy+CLImUFdixGyd7FhJCjObR82xv3UmO2cUNdRspL2rA1riS8JlUKYuU6EsOCV8qp9KycjG796TqvI0OpcQE+trPcnTv85RdtwVRTXK8aR6/aH02fZ17mm5hpr0SbeQy+aHhCJos8cPDA5zrGeOf72jEOXoSv3+Yoltv5bg0SKGoU7ZlIYLBjh4eZMQS45s9R9MFxgtsuWy95iZOPfUog8O9eIsKUUfHCMQn/xaBiEqZKTtsLRYNZ+VwJCwi+VsaGN3bhTIaw96Yj3l6LvG/gN92Cv93IAoq3eePsnv7oyTiUWavuIbSujJym2bzXyd/Rnjcu7erey8N3hHmWedNPommMhbR+Mb2EB92TlaJNLjsuOpCJMwm4te9B7GnBTEcIFpYzqDFRc/LLzNgMNJwz83k5JdwYXg4TRwBWjo7KZ01i6iWINJ+HnvVTNSwimiRMM7J5am9L7B0+TKSv6dSsSAIk0p6XE1M/LanMIXXg1g0TDg4mtWmaxrh0BhG7+WP+VOgaQl0Ww+PXfw16nhM3tLiuSjiMiB1QUEQiLcfRQ2PIchGEAT0ZIzgsWcwrnwPl/hQ70iYR3Z18441pQioJFSVHz5xig/fUk+xNzX3qZIFyebGfeMnSPSeR7S6Mbjz0cVXRyhJVFZOo7S0Ak3TMBotWSVyAHxYMQ41U7JxGoJlGXp8lGjfEeJVM3gjMh51XWPDpvehHYmhhpMYZBvrltyLOqFbggDB2ib+5/zT9J1JRUwV2Lx8vO5acq/QQaALGgc6O9N1oXVd53BzM6WlZVlyOUJeHfY5GwgdewHQMZVMw9y4ltgEnhoVIzzq7uGGf/goYlzBZJb59cB+bhebMPHnCVvVdRUtOllVVwmPYZEELmUO6abJ0WuS2czE10GNjjEy0DNpv9DocBZ5TI4FJu2TGPWjT1hj5edYMBulrBIspfl23A7T67qvKaTwppBHv9/P5z73OTo7OzEajVRUVPCv//qveDwejh07xuc//3ni8TglJSV85StfITc3F+BN3/anQhUE2nr6J7X3DI0w7X9JLHWe00RjjZehocl1HSE1ER0fOcUDx1Iqp+10c2KgmX9c9SmKVt6Ldf716JqKbs8jdOgIiCIGh4PYJPFpCI35MJmt7Dqwl/m3votf7fte1vZfnnqMvy+9BRMgGAzoE/IY89evZVQJc+uSEryxIhI9AeKWOqQVpfT5ushz2QhJLly1c6DzJJLLzTGTkCaOAAPhEbq8EawOF+UlNUQP7SQZCLDqBjv7zmYXD183r5CTj7RntZXVzsyypOo6xO0GnJtrMMSDKGPd6P5hjDmlaDGFRHc3uqZhKi1FcXhez8+R8mirMWJhH0H/CEazFUducTrMZgpTeDWio73s2PYrAGYu20xvUOPAtieZvmZWmjheQvPwecyLrkG3udJeCQBD+QyGFCN9IxHCc2chvrwzbT2W7Ha8mzaDMcmQxcQ/7/0GFoMZq2xhpOUUVoOFexYvo/n5p9i391mW3fpBOruyPZsAg6EQerkLwajiLjcg5tgxEyPuP8maBQ1Ycy6/2pZ1EEdjxPtCGHLMSPk2kqKOMNxPfKAf2e5AKi5BNf6xiyqdcHiUwcEBjEYT+fkFGAy//1yCAMmon7HhPkRJwpVbjGh8A0szTOEvEianG7PVRiySKTyPIGB7jXf5T0XEqPPLlqfTxBFgb+9RlhXN4VJmnSgKqJExhC2fZzAYQ9N18l129DNPIwo66nhQaq7TxD2rc4gH2lATcQxmKx+6sTQrdUXVRCSzBy2RRLTmgNGCZnSjX/ZdF1JhrpeZ+wFMdgunclZTK/ZhHjlPPKeai7aF1FvfGDJkNbuInRhADafWEbqiET3gp+D2aVzyi+k6HIuNsDFnFkXjear9TjgaG2HDFV5PMRjoGxiY1B5WklnkMSHZMCx+G96mDRhliBlyiJFNdMJahGXOaex57JdEQwFsTjcrNl1HRI3gkDNrCUEQSESGGRvuRzYYcOaWIBomp1XpSpigrw9VUbC5vZhs3is2lCmqiHHGauLdZ7PaTTULiMczv3kk34GxsoxEe6YmpO2264g4DJjGr2mSJVy5eYyNZEeYWS2Zd0FVNTxLFjD04otZ+xRsWs/EiGKXxcDf3beQ7z1ykp6hMA2VHt5zYyNGcUow50rwppBHQRB473vfy+LFiwH48pe/zFe/+lX+3//7f3z2s5/lS1/6EgsWLODb3/42X/3qV/nSl76Epmlv6rarAYMkU1xazOBgtrBMbmE+4u+xkP9vQkKI8+T557PaVF2jbbSDvNx8FMt4zR0dbNOmUf1X7yXc2obF6GBm01Ja206zaM5qjFEFg8lO4fVvZyw4xnAigfaqbGZV14jbDKi9Y9T/zWfo3/Yk8YEhclctJ1ni5dBL27hm1R30P/s0gtNKT56R5uf2pI9fsPE2Hm/pQRAEGhqmcc5/aNL9dEQHWTt3KQWSmxFRxLZiFdbCHP7lvQW09Ixx/MIwmxaXU1dkxXPzvZzY/SwGk5l5q2/E7im9bASqNHqRgd/8G4xLUztXvpe2nzxCYngEANlhp+4f/xHVU3CZozMQBJ3AUBsB3wC7n3ownW9ZPm0WSzbfjSBPEcgpTEbAnzJ85BSU4Cyu4fDOVLxpjsVJqbOI7kBGYMMgyowpUUq3/DWRg4+hDrYjVTQhVM7DlFSpKXHyrb1+Pv+pv0XvukhuSQHx/n7GDhzEMW0acVeKjEaTsbRKayQZJbeyhoY1b8NmtWCw5lBcWMjwcLZBJr+0hPv7tnHv9JuQjSLSnh8QGeoEUrkzljv+kZgtO6RDFAXU8z6Gd3em28zlLszFIc5/9T/TrsKcpUsovOdeVOOVfyOjo4M8/nhGXMhms3HTTbf8XgIZDw3w5ANfIxFPCXY5PflsvOsjyGb3FV9/Cm9dCCY3a26+j+d+831UJYkgCCzbfDtG5+8f6/9YxAWVkYh/UntYy4T2qapGuH4dTzyxjcS4BoAoitx041YMWmZB7TDrdB8/TOe5YzhzvPiH+mhadg2FeYsz9yeAFjSSaDUjOyogKRFuV3GtMLwqT1FhoO00e599iEQ0wvQFK5mxaGOWQcUlGSmvyWf7MZ2RQB4uRNbNy8MjyUwOPPzTIcR1dEXDuNBBRA1iki2InTpqSOWS885kkqhJ2kl8/xFi47mYeS4Xho/fg9EooyhXkI2paRQWFND/KgJpskwW3lJ0CcVSiDPPQfAyhvsczcj+bY+QTKR+13BglOanHmPTfR/P2i861sOTP/kaSjLVz9yiMtZu/SskYyb8X0uG6O28QCiaIJFUcIUjFBQmMTuKXv+9AaIAMU8lhtX3wpkdIMkwYwMxRzEWkXTYql+M03P7Uqr8yxF9AZJleTyrd/C2RBIMl84lsnz5Wp5/dlt6DJ27aCUOmXQ4tCQJxO0GCt5zD4HndqIrCs51K0nm2rHJAsp4Aq+u65R6rPzzexaj6jqyIPB/ZHl+VfGmkEe3250mjgBz5szhV7/6FadOncJkMrFgwQIA7rrrLtavX8+XvvSlN33b1UAymaSypoqerh6GxkOwysvL8eS9MVbFPydEMRUS9mprlIiASZ7s/je8SjlL0hQGn3ySoefGieZ2yF+2lNqt7+XiSDuRHIEKsxNbIAqFlbT3d2EzWgknMp4Ru9GG8WI/nb/4LZ5lSzBsWEFwdIjdF07iP9nLzVs/SLjtArbKMiSvB1toICuU7fhLT9CwZisHjxzn6NGjzFs3g1OD2cI+C4tn09Hm4fFmHzUb3kVukZdIewhZFhEE2LK6hjKvFUkQKKyeS2HVTBBEdF26LHE0kGBs589BVZDsOYhWJ6HWnjRxBFCCIUZ2vEjuHXf/3hyKeHCI9uYjdF04nSaOAJ3nTtC4cC2u/CkxjylMhtnhpn7hBqY3zedE81mK8gtZNn0h8vkEnzDcymiDyvfaf8NQdITrylfQuX83+XU3YFr4HjBEGerr4NTeF8mdN5fNmw04zQUMhC1UVlbS9q3/IekfBaCPJ6j5zCdYW74aN6WIAnTHL9AZaoNwgp8f0BGFKG9fHSbXYcLr9aYJZGlFGae1DnzRUXJteWj950gOZQihnowT3Pc7LBs+gqJnpn5DQmNwf6qcEAKYKu0Yqwz0/e7prBhT/9595G3YABWT84l+H2KxGHv37slqC4fDDA31U1xcfdljRBFO738xvegBCPgG6W9vpqxh6VTo6/8h6LqOsbiYTe/9JMaERFLWEGzWtOjH1YZRttDgraV5OFOTVEAg15aJthJFgbaOLhKJBFarFVEUCYVCHD95grVrNqaVjOOhUWorZjE7bzmJgTimORaGlR4SkQAWR4pdGXWNkX09oIHmskJEI9EfJDkUhtKMhzLk62XH736U/v/MgZ2YzFamL7qGS1OZMNyHNzLK6rmF+IIJcuxG8iLDkAhB/tXPD9VEBXUuPPvkN1P1EYF5i6/FYcmQJlUF24l2whNEfJJjY7iPt6HWLb2i65mMEivmzeOpl14iEkmta+ZOb8BrNF127SD8HuEMJRhME8dLiEXCqMEQjHNRUVA5vOPxNHEEGOnrwtfXTl7FrHRbNBriwLEzhMIZ7/ialcuodHrR9GyhM2BSDcV0f0WBwyfPUlNQgXfZRwHoHfUxdrGD2XPzuSTuUGDx8rvQ8zwU68XsNBEeinDfzFuxGx0kLtUYNTixDV7g2hXLiQoGjJKI1HEM2b46TR5lWeLkuWM0H9tP9aImRFHi8JmXKAx2sqaiISvn1pTUibX4SPYEkGs8yGVOEvKU5/FK8KbnPGqaxq9+9SvWrVtHX18fxcXF6W0ejwdN0xgdHX3Tt7nd7td9D7m59su2R8NhnEEja/LmE6vREQUBw7CGLWbBaDSSl/eHldp3XnoAAJucSURBVEn/0pFUNM5cHOHw2QGKPWZmFprIzc9BnhBKcufMG/nPPd9P/28zWmkoqCXPlbEqhi5ezBDHcfj37CW+ajb3D+zk3VXXcurAy4wO9FI+bRZV85bx0bJ7+PGJ3zAY8ZFvy+Ve7yriP34US3ER8VE/VlEgHAtRXj+DaXOXYo6rXPj5r9DHTVzmslLmr1vHoYOpcirJRAx5fN2ZSCQokQpYUbKA3eOF0DdUr6AuZzrf/H4qtyEYd7C5TKSjP8j+06nw5GKvjY/eMYeZNa/PQKAERhhNxAiu+iTHByVcDiv1R5+btF+0rR23y4wovfai4nzvGax2F8Ex36RtaiJKXl52qNCr/78c1JhCYjiMGkliyLFgzLUivAXCOV7Pvb1ReK3x4C8Br34uQ74wraMOziUbSPYkKCwspqnQTeKlwbQ133JO4K+vfzfngmcJnGrGZvMSOTmCuq8f143VnNz/ApbVi/nu6UfT511Rspjq0fw0cbyE3gcfpuTm9/CDZy4CMKOmmnvXLWHw2Cu8f00DLSNGvrmti396WxUbywYILN5AT3yM42NnOdPXwsdn38u+nqNsDGcvjACU4W6cVgHJmrnH+EgYXdGQLDLCAhMHDz+F/0wv1bPn0XD7negd/fQ88utUrnU0csXvjc/nIxqNTmqPxWKvea5kIs5If/ek9oBvAK/3jX1v/5zfxZXgrdLP14PfNx7EkjH6Lo5gP6eR6Iwiek1EZylYS6wUuK6+kVnX7dzcsInkqSQt/g5sRiu3NVxLkauAPHvmmScTSW5ceQ3mMRFUnWSuwJm+FixWA+bxnDQh5CK0f5Cx4VRkVbRzDGeNB7nSnP79wiNjyDMcdPhPc273S1jtLuavuQXE7N+460wnr8b5o3uYu2ITVkcqaDMQM3IqmMv9D5zBbTczGozxtmurWF5q+JPfl8sdP9w3yisv/DJNHAGO7H+akukNVOSVpNs6O7smHZto78LpNJNmaq8DgbYRhr7+DdauXEmyrBwZiL2yG8VopHBjtuF3qLeDtrMnOBeLUtkwm4LSamRDhsjFgg4EUcwyIkuyjNFqT99rJBTAP5RdtiXV7s96Hr3dF6gqraTSU4qoiYSJcvLcGWpq68n1ZPbzB2KcujjCqdZhakvdzKrzUuDJhMCqqsrcmlkY+wKoQ50IgkixMQdvaS45OZn9mo+cYh2VKDWzCWoxvFgZO3Cc2KZ6CkoytSzjq+5grK8LKaYgyAL2mibsJdU4JpBqHRElmWB4pB9RlEjEY+g62OxmnFKK7iSDcXq2nSLpS43jsZ4A9mle8jfXIV1Gw+MS/jeNUVcDbzp5/MIXvoDVauUd73gHzz03edH8VsDISOiylhanRSJ+xo9sUnFGYgiCiKIYULsiJCoTjI1NLsT9VkPHUJgv3L+fD68uInfHM1w8eoi+8jLK3nkPenEluq5Taani71Z8lGMDp3GbnMzwTseSdDAwGCSaVDHJIobg5AUYQCQa5OaylTQ/9ru0pf7Csb2Ex3zMKp7Fu8vfzoimYMGAzezk5GYXPQGFudO8tLW8SE/zAQBmzFlO994daeIIEOvqJo+VaaWLnPxiRsf7YTAYiIwEye00876a2ykpKcFrKUBVRRoqPTS3+2iqySUWV9PEEaB3OMyz+zoocEq8ns9JFA0El36Qf/7lBRRVR5YEPr+kCfbszdovd/VqfP7I7/VKSAYzfR0XKK+dQeeFU5kNgoDVlZ2Xmjde3FwQIJGIkkjEsFhsSNKEIrs6xI/1EzwxHkYjCuTfUE/SY/6L9o5curercZ4/Bq81Hvy58ernokdD/Oi5i+w5M4wsibgX5NFUJmNOhBBLrMR6xr36mo5wMUzP8ZSRZel1N6Ab7LQFk7QPRliw5T7+ce9Xs661v+8wNxvWT+qDGg7hMEq8+8YZPL2nndOto5wvt1BfXMq+Z36Cp7iaNbPXMBZI4Nz7ECaDidolN1JSsZg7K5eTUDX+u+1F1s64c9K5bTNWMRoV0cKZe5QFAVt9Lkl3gqef/Hbayn7myCtEQgFm2ddQed9HaPnOV5C8eVf83siyQH19PUeOZOquCYKAx5P7e/PAp81dzp6nf53VXlzdeFXe29fC1fou/hAEQScWC6OqClarnStdVrxZ/bxSvBHjQUIJ4DiQQBkYrzfcrWAallFuijKUeGOeQZGxmHfOvoNQIoZJknEZ7QhRE0PRzPXm18zAv601U/ZGgKXXLyASThAMpNYthqhIcjjbiBNpHSN/VuY7kmWJdv9Jjr/yFADRcJDnHvom1937WfQJv7HZ5mDGkvUU1s5CVTW0eJiLx/cQiWmEY6n9fLqZ1o5hrl1SRddgkMUzCukfVOgtcqL+Ce/La71vyUSSSGiy4Eo0GkrvL0ki3mXLGTtyLGuf3OXL8fnCV6S2atI0Ej4/I799OKtdW70yq3+J8BBP3P8fJBOp3+Horme47h0fx5GXiXRIqAIL123hwAuPpCIsBIGFG7aSUIX0uURRoH7uMo6+lF36zFNYkXW9HFsOrrBI8uwoOmAziKxctZSkSno/HXj45YtZJS8aqzx87LbZGMdzQU0mCWs0zMVf/g8JXyp02lxaQtV7P8LYWITEuGCNqql4HBXk63aIRUg6XJyz9qOpevp6ggDa4AhDT71M4OARzIUF5N2+hbjJiz6hDEztrCW48grp72xFU1WmzVmKJ78Eny+z3jSMxdPE8RJC54axzSkkbr48ebz0zkwRyAzeVPL45S9/mY6ODr773e8iiiJFRUX09vamt/t8PkRRxO12v+nbrgZ0QcRSLtH5yweItLcD4J49m6Kb77oq5/9zQxAFfrezhcV1HvL2PkX41EkAwhdaOP//vsj0L/4bisuLqEuUGMsoqyhPh7b6w0l+/uw5jpwbpDTfzl9vnYalopxoR8YCaSoqIpDjwBGJ0B3P/rh7284xa9UtNLdrdA0kyMuR2H3iDEP+1H47Tg1z28r5OHLaCPqHMMlGEkPZOVQAQlJBFEXyS6uYteI6du45SFlZGbW1tezdu5dYLEZgLMDMiibQRCQB3nfTDB54qplITEFnsgfkdNsIwWAuDscfFl4SBImXL8RQxst1KKrOTp+Fa2+7Hf+2x9E1jaIbrsfaNCurxtbl4PAUIRmMFFfUomka3a1nsDpcrLj+bsyOy1VR1unt7WDHjhdRFAWr1cq1116P3Z6DroMYSmSII4CmM/LCRXJvbSQxlRTwloKAkhUmKWkK7S09dAxGuW9FEbOLTPh/9B26BlPh9d7lK7HXrSLSmiKQRpOZNZvfidtiJtLezlhbF+byaTzVqpCfU0hSzc46SmoKclVZKkZzgvXbtHoj39zZxWgwxrtunMGPHj9Ny6BKiTCGpqkMd19gWv1qbNr4oiQZxzTQgdx6nHjvBSRXHn+77g767VYqN72XsZd+iZaIYZ+1DsP0lZOUihVdx76whN6OU1nhWQDt54/TdM1aQucSVP7NP6LnFV1xWRyHw4Hdbmf+/PmcP38ei8VCY2MjDofrNY/RdZ2S2lk0LR3m9IEdSJKBBetuwvUGhN692dC0JM3NJzly5DC6ruP1etm4cTOGy4hwTAHMcZHIQPbcpsUU5BDwBqWoR2MiR87E0OUYSlKgqdxFWR7pd99kkol1hbLrEOsQPz1CTrGT8PhcdanElGQ3YnCbSQxH0GIKTCBMiViIc4dfyrq+rusM93dj92Tykz1FlVzs97P9+R1IkoTJZOKazXeO1+Mb73cCBv0RDu7JzEmNVR7mNV4dgcNXQzQ5cHkLGRueIHooCJgcGe+XJAkY3E5Ktt5K37YnACi84XqMOW4kSWCCrfoPQvY4Kdi0gf4nn85czmDAXFaelhASBOhtO5MmjgDoOsdeeYrVWz+ENh6yb7easQgh8jdfTzSpYTWIGIQw0oT8SU2DmqalRINjnDu2B6PRzOJNt+HwZLyqAHbVwkhXRtlUT2oIZ0IYygpJjluR/eEEz+xtzzruTJuPAX+UMm8qCk0ERg/vJuHzY/TkoKsqse4eIq2ncdZk3oXc/GpiL++k67e/A11HdthZ8MlPYLbncElXR1Qi9D38CIFDRwGItHfQ+fVvU/vPf49QUJm5x1iU/c8/QmlNI5IoceCFx9i45b6sfgq8BsEX/vIMwH/JeNPI49e+9jVOnTrF97//fYzGlKVg5syZxGIxDh06xIIFC/j1r3/NNddc82fZdjUgCBBoPpQmjgCjx4+Ts2gh9qbKq3adPxcUNUkklmRVjZnIkyeztmnxOIn+fsQJoTeXrK+qrvOdR05yoWsUgO7BEJ/78XH+830fJPrSCwSOHcc6o5HI3JU89UqAd6x0T7q2bDAypPqI6wYWV3oQrQYefak1a59t+wf5wIqVnN31Oy62N7N41XIGn3o2a5+cijJuzNuAMNKFLdLLtSUglRRxdnAAg8FARUUFc+bMQ5IyeZtuq4GP3TaLcEyhrT/I068qMNtU5Wak6yyumSv+oAdKECAcy55hXmz2Y1hUzz1f/SqapqLZ3X+QOAIIkoUlm99OYKQXT34pC9dvwWBxIsrWy3oKY7Egzz//XDrnMxKJsH37M2zZchuCYECLKpOOUcNJBEUD4xR7fEtASxLwdTM2NkZS1cnNy8flzkcIjuE06HzI3QkHLpKwWkkMZpTrhne/grNxNmAAAdRCgbjk5beHO2nxWVlS0kRF5xk+MGcamOxM81SjojEYHiEQD2KRzfSaXFR8+tP4nthG0j+KYcUa9uhF+AKpfN6TrSPUlLiYUe7AnjSTX1zBYG8HbquIpzMVMSAYLZjLZ+B7/gEA1LEhPKcP0u2uo7O4mOJ7voBZk0gaXMT1y4dTx2UBo3MyeTGYzAiKgBKI0xEzUw1caUC2LMuUlVXS3t5KXV0dZrOZ/PwCZPn3e+dFg52Zy25k2vw1CIKAZHT8RXvzXy8CAR+HD2eExoaHhzl27AiLFq38X3F/VxsG2QiigCCJGHMtKIE4aiSJyWh4Q0RgdOCir482w0ucGDyJ1+ohJ34Djkgdbst4OKoAWmyy0IsWV7MW1KLTiLa8jP39AU73jrGw0sNsrw3dngmf1BEx21zZarKAZMwO5/SNjlLucLFw2XJEIKiqnD97lvkLFpJUx5elusTB5mwxmTNtPlTlyvKUXy/GYiLli7bSvufXBEdHMBjNTF+1laGoBfu4bUgQBBBBdjsovvlGAGSHFV3Sf29O4uUQSoB9xkwKdfAfPoLJm4t3xXIisnGClqqAkpj82yTisawcbqsSYWjvb0GUsVodqJEAqq6TVzWbmCFj2JKMThYs3sys8iZEoxGpsBRFeFUeY3QyA06ORBFULaWCQ2ptd7mljjLBcChoKjGfD+Nn3k2zPoJBkKhXnETP9uCa8KzkwT56f5PxvirBEF0/+hGVf/O3YEkJ+eiBAIHDx7KupSeTJAcGMY6TR7NZpq23nYXrbqblxAE0VWXuqmvo7bnI7KoGYsnUNeNSDDnXhDKSIeSmWgcxwgi8thFwCtl4U8jjhQsX+N73vkdlZSV33ZXywpWWlvKtb32L//iP/+Cf/umfskpnQErt683cdjWgJuOMnTg5qX3s3Hm8myaHdL3VkIiFWTPbS2QsjNtizirGCiCaLxPvr0XxBZL0DYexWQyExwu0vnttHfKAgLtxE971t+IfiRLVNDyWGDtPJ6monUFPy+n0aeatuY5tva/wgbI7ie3opbNxcn6IqmoI48I8wdFhXOtugliEoZf3YnC7KL31WqInHiY51AGANa+E5LFnSR57lulVc5hzywdw5uTg908OqRUBh1lmWpmTtfNK2HEkZZkry7cxtyiK9DpryimKxtp5JbxyLLtm0YLGQhKW8ZCIK1h0CbIVV0H2ZPpa3QiHQ5P6GAwGicWiWCwGpMvUOTIV2NGmiONbBiF/Ly3tnZw6kxF+WrN6NbVl5RhOnST4zJMUbFyP7+DhScfG/YMYZ8wgWKoTMzr4z18cZWQ8ZO10G1wzZxqbuzuwlHi5u3AdY+E4EXuSuvxKTCERKSrRZyvjyOKtFLpM/PylTsZCGSGopKLSWOmmuv884d/9mpkrlhJbcT3uYg8O12LipXXY3R5Gn/1BVr+UnnMkJS+HfvEEc26/m7KyRiyvQRwvwe4poriqnt628+m2RctvQm2JIxU7sLrMf7ShWZLM1NbOQNdVRFFC015fvUdNF9Kqhv8biJUgpKJ3Xo329nYWLFiC8OpF6RRImnRsG4voi/ho726lqLKQcmcxivmNeSGiapK9wy9ycig1lw5FRvjl+Z/xmYUfx01KCEZRNCzFIsFT2cfaaw0kkyqMa1EGBYVv7Gqloz8VJXDq4ghLZxbyvrJiLuX6GU1mlqzfwjMPfif9kjtz8sgvyni3JAk8gkQyFKT9Bz9CCUfIXbOSmevWkFSSIIwvSzWdhbVermsswqZDVITnLwwivEEfj9kg8cDOEZY13E5tDoQSIg/s8fHxO7Lf4+TwMP6TpzA01qf+P9WM12TCWHdl15PiMVq+/R1EkxHXzJkkRke5+P0fUv6xj0FuSn1X13VKqhs48tITWXP3rOWb0MiEWGqJGJaGdehCLnFfEHOlCyHZh56IZaVhSr5+zn/x30mOC/7kLFpI4T3vRLVkwjFF52RaYKl2o8liut64yyEzuz6X4+cz43tejpk8zwRDgiCQ3LqOrx5/IN13g2Tg7ze8C1XN3IvinzyGxHr6kKIhtHHyKJnNyDYbSii7bqRsyxgJdR3sObm8+Lv7020jA92suP4ukAQuWWci4WECpT5yyopgVEfPFegeO0tVYi6yaYo8vl68KeSxrq6Oc+fOXXbbvHnz2LZt21/Etj8VgiRjmDEbWi9mtcu19W/I9f5YiKJAMKaQVDScVsPrlik2Gs1ooU5s+dU4b70T/y9+kt7mnjcXuag4rWhlEJOE/P3s2f47Zq7awr1r7KlQfFMOzZ0xZgYTJCMKYoGdkScvAOAE7piRz/fP9VHTtJH19bMJ+oZxGG3klNWzOugk+kIPelKjUJKwWwyEohl77bVLysj3jFFw8zuxaiKCrxezrYem//gXImdeIdL8O/R4KixPkLPFiwyeYnTBjCz//k/CJEncvtzL7MIIigpaoJO2fYe55h2feN0LwvI8O39370Iee+Uiuq5z08pqKgveeNEVq3WyN8ZqtWIypWaXpEUi77o6Rl5sQ4spGPOs5Kyrukyg7hT+EiHLAoFgIE0cC/K8NFYWY1DCJJIJfDt2AhBua8cxvR7fvgNZx4dKHPwk8SjBtjA3570vTRwvYfuJYZbd2cizP/4yuqbh8hZy7Y0fYXRbB9HxkDery8S6ZV66EgJjoWyL+aaFpTh2bsNklTG/bSta/yA5/jgDQx3sSPQxu2A6eX09aPHsWpNi8TT6+7rRdZ3RlhYcBSXYTHYkNBRdSi9MBAEkNHRBRMXC8hvuY2ywi/CoD6chF6lDRLeKWBaXYrb/acQmdUlpYoTu/znoOrhckxdbxcUlSJLh//SzeS1Eo2GOdzVztjlV+669vZ3zubmsXb0Cq+nqzwEJIZImjpeg6RqjyREqxsmjruvoDOFdZSfUqqMrYK8R0YVedKEsfVz3qJ4mjpew91Q/N62opGB8OhV0HU5dYOOKmwkoUYyyEfNoFMOIH2yp8E9VBT00Ruf3f5w+z8iLLyE67BTefAvx8fcm32bm3mmFJA6mUo0cwO2NeRidk+N7RVFAVkOARFL843L0bSaZz905A5OoIiWC6AYz9RV55Odk2JfZbGBYU+koNtN+IJU7WF43E5umkms2EI9Pjt55LegaaMkkSijE0Esvp9vVZPY5rO4Srn/npzi++xnisQhNSzbiLc1eU4q2XKIUEDaKBHPMOGUDNr0M2wRVXQmNgUcewVBWgXzDVsREjPBLz5Nsb0NsyKitJtRRXPM8BE6Ooic1zMU2zDUmFCUCYurZh7UAt6+tp6pokCPnBqkrc7NmXglhdQy7nEqZEQTY3n8wi/Qm1SRH/OcpL2oYN0yAOXdyio2lvAzZZk974+MmC57bt6KePYelrBQ1EiXc10cyJyftpVVVjb7285POdfHMESpmLOeSVd4qmDjQvJfA2AgOdy6jJ/uprZ+DUXnNgNYpXAZvumDO/2aogsBo1UzM9aeJnU+9xNYFCxnJLeMvJbtF1XUOnRvmgSfPEIkpzJuWzzuvnY7T/HteBVEjpkcxGE3MmtHACy88h6mmjrJPfRxDIIg5Nxe5rALFaEUQwBTqIdx9lp379zFrzRa2P/88Toedxmk16Ikubp1fjnIigaPai29PtuqafmaQ6+cWs79tkLKTz6B09+BLJrF/8qM4bVb0ZGo4MRwf4O+ua+TFi8N0DIdZ3ujGEjjDS49uRxQl1qy5BaetEOP6e+g0C5TWNBE5m8rFEAwmPOvuYXTvowAYC6sxN60n9jonHIs9l+nVKv7BHqTcauYuWY1kcr/u30AUoLbIwafvmpMaz94kN4TF4mDFipXs3r0LXdeRZZkNGzalRXM0QM+3kXfbDEiq6GaZ2JUmhU3hzwZdB3XcI7dk1nQqwm0kdv8AQZJhzbswFBZDewehllYqli0l2tVDtKcHBAH7+pW0WmO8LedaXIqVC8pkz54A+Ib70op+DkcOkWPDWblSylgcaTBI15nH+cztt/LcMR+qprFknovcgdMITdXsO/Q8oXYfbm8hS0sbqLK4KVNiiJqKuaqJeGgjkWPPAzqSp4RIUSP9R38HpOp9laga6oFfE+09h2XaMow1i1AUA9FTxxl+/nlMRcXkX3sNQkEpOSUN5JYJGJIaVOhoZpHk1Ct91ZCT42XatGlp47DNZmPBgoVTxPE1oApCmjhewsjICJFkEutrHPOnwCqbcJmdjMWyhWCc5gxR1XUYddgxnN+OpMUQDEYirWHU5bfgmPCtKOrlPxxlwvcvRAIMP/kMajiMIMskNI2QpmG+751Yy1OERxBSBqxXY+yVPXg3bYJx7489qTFwNFsdVDkzRG69l/gEb5pRi6Ce34P/wOOIBjOuVW9DLZqJypUZiIySSp4UJPbyT0n0nkdy5FK89l1oqhFkx/iz0hi1QPv5TIRZ54VTlFTWU3KF87hiMmHfdC2BbY+m2ySLGaEgu56ijoAtt4KVW96Pw2lidHRyGGssGOV8sJeWg0fTbY1NS3AGo+BO/dZCIo7atJBnBszs3T+IyWDkbbd+kLykH7uQWYaog4MIahxnkxVdE0EI4t91BM/116GMexoMqo1tuy7QPRhmbn0e5zp9fOdhH5+9e3am3yJElMmm53AyijhBwV0y51J6+130/O436KqKIcdN2dZ7EMXsSDaxIJ/I7j2M7N2H7HRSfM/dJEQ5TR4FQcRgsTJr2QbMFhs6oCQTBPzDSFKmzqNsMDPLU024aga+wDDTq5sw9Ywgmq1T5PEKMEUeryJEVBImicMzbqBpRcoC/kq/xmrzX07YX58vyrcfPpH+/8i5QZw2I+/cPC09egiCQIQQMSWGwSDz1PkX2NNzmBJHAffOvoM777wTn28Us9mC0ZjKr7sUJW9K+Bn57b+R2PApvAtraO/txGQy0VRXzoGnfoau6xwGmuavpcm0bnIHdTAisLpMJvx4e7rZYDJjsplBVEDT0ZMq5j3d3Jxvw3FbA4/c/6/0jedZaJrK3gPb2bzyFob/56e45s4m1NTI2KwbsMgiMRUunLvIwms/hCTK6PZ8YsLrl9jWdTDa8ymwX06U5grwpit0ilRXT6e4uJRoNIrdbk//fpeg6zpxiVRs0RRxfEtBVXXyCgpxOp2UM0ri9A4AdE0l+Nx3yb/mbwkeO4oWi9H5i19ReP21lN19D2GHyGP+Q1yvTUN/wY88S6KwxEJejiUtSAVw3dIyBs49mv7f7shFC07O1DKqJqIBH6e2/Sdve/sH+U3/Ln7b3ca/VL+NQ/ufp3zZChBFAq2tvLz3KRbe9nZICNif+h5S40qsi27F1rSeZGSU06dPcPKZx4DUuNQ0ZyGhR76OGkyFSyX627AHR4iFPHT9/JcAhFpa8R84wLQvfAHVk4+m6cQlIRW6NPVKX1WIopHFi1cwc+YsFEXB4XAhim/9klRvFFT98p4pRX9jlq1mzLxr5s3896Gfo4+//LPz6imzZDxSggDPDp0ilGtmbd48JEFgn/8ina3P8cn5mVjMQqeBikJHlvdxUWMBXktmfSMZZEwFBUQuXkSfUPJCdmWK0Os6GDw5k/pqLCpEM03I9lPUy3+vSQWYkK/ZeZTRnT8HQCPAyLb/xnvHP6C6ryw3MhENEdvxYxIDqcgxNThC4Imvk3PXP6OMlzVRVZ2u1uZJx3ZebKZx6aYrup7ZJKI0zcdmdSAc3gP5RSgLVqBOeFYToWoCBoMJmEweI8kILWePZrWdObWfujnL01GrusXCvpgbRQxz101FaKrICwcHKNtYh23CczYYTFz4n2+jTci1LL7lZsQJYbLhsILdamL5LBcd/QFmVHsRBIFhfwzXuEiPqglsKl/GmQk1RgEWF89Oex0BdEFFT1RS84G/QVNiCIKNSLuCpT7Opd/ZiEDosW2Ezqei1JRAgM5vf5fpX/xCmvBJElTUzeTlbb9gbCRVTsbqcLHu1nch6CqXMtx1txfjojm0hjoZKvIgiDamT29EtTqm5ocrwBR5vIoQdLAlemis8tLqk5BEncXTVRzaMPDGJHm/HiQ1nQF/FEXVGRyNTNq+92Qft6+txWIQQdBpjbTygyO/JBAPUuwoYFPtKvZ0H6J9tJsv7voG/77xb9LKoq82tmlj/ejVS/jZnhBRRWdxcYzGabUc2/FoVvjCycM7mLFgPZLNiBrODFKSzUhxqYWxnz3FpSnKs3oVodNnKFi5DHFVLmMvtac+clHAUGums/XIpAT9aChAaHCA8MU2whfbsB4/hW9eFQO+IfIbVpHILaYnYcPtcjA24sdms2KfUC/ufy8EzGYHZvMlS+qfuTtTuGpIJiMcPX6S6zauR3/um1nbBIOJiDmK8V8/iUHV8UYkjAkbY0f8CMvyuLliE8pjfSBAyDDK4Ud/zIdv+gQnOyJ0DARZ1JBPhTvBiwczkQKdbSdpXLqM5OFs67LZa6JxxkIO7t1OrL+X6/LnESqejSpbCMwu55Hu51F1jTll01lctoyOkW5+3bOTv115C9r2n2GuX4KSUwW2AkpmGAlEIgiSSPW8JdiUOP7gSNb1dFWi95FHs9q0eJx4dycRq4dYXMHtMGF8C9QrfWtCwmabTAb+knBpDlQ1nYIcC2b5z2PQNRklKmuraW/JpLY43S4ctjdGatWgRCjdt52/n7aZIUHDKojk93VjHR0g4U7NAZoGJfZCChMe5B2nIZ5g0cJGrG43AkKadOaLGu/aXMfRtlE6B4LUlbqZXe7EbRC5ZGJSDFZK334HF/79q2nyaK2twVJWxEQZFkdJKa7rbiBYUElSF3GHhymqK0OSTCiXFDZtIDtNKBPC50WLjOTIkBgZhdCx7ZPuO95+HHFe3RWVUDIlxgiFfSjr3k7c4UJOxLEcfwkxMAD2lDqoKEJxeQ1dLdmhwCVltVcsmKPGErSceJqc+jXECu5BlnQMiQEsA1Ec9rlXdK7LBIqArme1x+MKniKBDucBHu27gCRKrF+1jtFEBEHwpNcCCZ8vizgCDL24k5wNm9P/S5JALK7w5O6LlBc6Od/px+0wMa8+o0WhKNDTZedjc+/hqfaXMYgy11etoaXNTOWE4UI3RrEUGQicSOUzCoYweatcKMKENyYUJPQqjz26TmJgCDmvdPx6GkM9HZQW1zCvfhHoOv5EkI5zJ3AV1HCJGcalBN9ve5KLo5m5bF3lMra6i1Pu0im8LkyRx6sIEYGSqmq8Fy5S3HIawShjds3ElF/2hw9+gxBOqPxg22lOXEiVrbj3+oZJ+5QV2DGOT6Zjqp+v7/sB6rgltDc4wDMXdrKiYiE72vaSVJP0BPqptThASyAIEvp4gntC1QiYy+gpz+PY7hNIosCtS+vRwwPEY5NJ60W1D+MKI87jMmp/BLnQirjYTWisDeNd76L8hhGSFied/gSxsSA1gp1c1zA5K6PIVjchRWLH8z9h2rzlCK8SrPHkF6N1ZyS3Iy0tlN50HV3WefzPM33oOpgMo7z/xmrOH32ReDzOosVLWLxo4Z/8zEVRQBCEK6r5NIUpXCkEQSUe9oOuYzPbCHe0UWqx0tPdQ3leOYnBjkt7Et30Tv7rwjYC8RD3lKzD2JtEO9+Bo34GDpMXvb+f4SSIRolgeIhoKMjeX32BnPxi5uXkMrS7n5l3fJCGBStpPvQKkPJSSxVWnIpE8NQQolHCPt1K9+9+RuGcWTRc8zHCRguOXXux7HyewS9+lO1dmXqmx4bOUlSeS7HZS1yJ0yokmGk0kwyO8MqJFiwWK9OnN7DshncjCALJpIo8dhFjYTVJX29KDAJAUxANRlSyx5iYAp/75i4Sikax18Yn75pLrn3KK/Z/Da+eAwtzrXzu7vm4rW++oI8gG5kxpwGH14GvexhHnpvyilIkLl9f7k+GGkVpP4m9/SQTMyqV0gZwp/7WdZ2Faj6tX/t/xC/VmnhlHxv+/nNoE0JVhzSBWoNKzgwv8QYvFlHHrSQZ1AQumV0jqsagaKH+Hz5DbMiPZDYh5zi4GDFSMX49QYDR0RjbpHr2vJL6TTxOO58qk6mOBlHGRaX8MT+OVXlEj44R6wliKrBhX+jFFxvCbEoRBh0RyemF9FiXgmTPRbtCy6gky6ib3k/0Qge8sJ9ERRHC3JvQHJmAYlmWyBPt5BWWM9SfIh95BWXky3bkyxgkdFEjSQKTbkJ/lciXLBmIB4Y5++y3cLg8xKJhkvEYlbd/+Ir6DWD3FOJw5xIczRjWcvKLsXsK0v+bZI0+TnPOl/LeqZrK9o7n+Mjc7KQqwTR5jBSNRvQJxjdNhzJzkhtmJtDPvIBUU0+7p4Z4YoJHUdNBN/GDX/Vw77qbiCsaX7u/g/fcODPL8xgzGBGcF8ldYkfXZBBCxE1GZCZ4YE1mjB4PiVcJdBmczixnoVO2IB1uYbQlpbJvKSnGfseNCBP26o8MZBFHgB3te1lfuRK3+MaUgfnfiCnyeDUh6CR6++j7ZkYtUHhpNyV//ykorvyzdOlspz89aQL0DIWZVZvLiZbUIGOURe69rpHxuq4MxXxp4ngJ/aEh7qi/hmP9Z/BHx8iVHPReOMiJPdsxmq3MX3Y9VqGAoEHm3x8+yYbF5QComk5Es5GfW0xOXhH+oUz+gsliozs0wEPnnmJZ+TzqGys5HzrHqTMXuK/qXr704+O898ZGnny+nT5falFo2jPMP97oxbHze4COYfoycjy5nDu6m8Ubb+XoK88Qj4bJyS9m0YwVDH7vgaz7iORU8vDjx9L/x5MqP3+uk7uWNdF88hAH9u+jorwCi+WPU9wSBPCpwxzsOcZgeIQlpfOptJUj65dCbARQYyBKWfWspjCFK4WWDHNyz1OcPbILdJ2quiZqpBxijz9D6V2345iziljrEQSTBcuC63lw9AJj8SDXFi6i8OG9jFxsB8B/8CCeJYvJX78WU6GBeH8IjyuTc+Mf7MU/2EvT/GV09Y6h5S9kw50zMBpkHDIIQT+xYAfmcplkMED7T7aTHAswduI4wns+zVd2dtJQUs47b7qFA8MXJ93HcX8LyviiS9E0EGUGwgqtrakyPM3NZ7j11tuxWJyECLAvMcDZ2gqabIup9fkRDz6DZhDx3nQtfT/9Vfq8BpcLvy2HpY0m9jX76B0O86Ntp/n0XXPTY90U/m/gXOdo1hzYPxLh+UNd3L6mJrXAfRMhBpKEv/49iq5dRUFtIWIgSvwbP0Z6z/ug0DNpf3mcUyrqpE2vC3GjEUNpA8nuiaGWAtgzi2RRFAgcPIr+qiKFI08+S8nHGrmU0jiW0OkJ63z3saMEI0m8bjMfvqURc0LDMR4bqegaJ7oihCz9tJ3Yhc2RQ8nsDQQE0roPug5duo09zd3pa/kCMbadC/PhxowHVtU0Yh0vIUtDeBZMJzl8mEirBbVmWXofRRexL7wJLRbGUjEDXVOJtp/CUDbzshoGAgqR4BiCIE6KugkbTUR3HiL0zIuphoOQ2H0I5+c+mpU9mTh9jibRC0uaUg1d/cRPnoXVmTQcQYAhdZDfnXmK9tFuFpfMZX3FSuxMDN9VWbb2dp753XfSpK+idhYO52Ql+T8EUbax/s4PcXzX0/R3nKekupGmZZtgQt5gXExyYnhyNYD+WD8zhPrM8ygsQHY4UIKZ8GTPzTegWUxcUkS0ywpz2/fg3zNuDDxxksLyMjwf+cSEM+ssqTAxL6Th/9k3EWSZL225FSk/21DSGxDRbdV4tBH0WBDdnseZITPzHDLG8WWSarZR+f73cf4/vpKuI+xduxqxqCTt0VZVDdNIiKGWTAm3WE8vrtYetFkClzyPSWVyqoWOjqImed3qkVOYWsFeTaiaRvDZnVltuqoSOXwCmua96f0RRYHW7rGstucPdLJldQ1bVtcQi6kU5lrJsRnTXjunMVvxTRAEqt0VeM4P8BF9HqdrJOLdPbz8+M/S+zz9m29x3e0fx7gnyY3zSunwRagsctLeF6DPF+eH29r57K1v49zLD+Eb6MZid7JizZ0MoKPpGrv6DrGLVK2wpvwGnto7hMkoMRpOpokjpMjeY6cS3Fs2A7XrFMmze6hffjfPPnuGE3ueY/q85birqggJCvGHd2blXLgWLuDCSLZ6JIA/GEc0ZCbtsWDwjyaPo5qfL+3+JuFkqs97uw/zvnlvZ27OXLRkhM4LRzi193lMFhsL12/BlV+NPjVaTeGPwFDXOcyCxjUbrwNgOBghmVNM0dvvIjy9iF4xwbRr/5rwhRa04jouHE6p+U1T3cTHieMl+PbtJ3/tcqzVIFlc6GGBpetu5OArz6IkE1TWNVKdYycWvMD/vGLjXWtzqMwXiQhWHFYNQZZo/9GPszuo65jiqVDy5p4Qw9PLKDX7J91HuauE8742JFGizujCtOoeXjyWIZmqqtLb2015XQ0/OPwzWvwpD8NBTrOieA5v2/rXnD5+mMBYK9Pfew/Jc62YCvIxNzaw86WHKBJEPrZ5E48cTXK2w08kruD4feJgU/hfBVEUuNg7Nqn9VOsIt66qftNHXy0YItbRSey7P89qT/r8GAozhdMlPYk80kLoyFMIkgH7/OtI5FSni8K/XiSSArEZ1yLWrMIXk7EawGWXGExKTKQo6mXYqaao4+uClLXFYhD49a42PrTWjUWLEMDOgy+08qFbGtPHGCWJalMPx3c+DkDAN8RAVyvr7/lMeh9RhL7g5Oud6w0T0nQuSUQ4DDB65EnQVKIXLkUsCLgblmaFwOqWHGRPEaHmvaBr2JvWoExax0DY382hFx8l4Btk2twV1DQtRTRmUlXUQITAcy9lP7++AZT+IQyOzG/jWLyAtv/4r/T6QpAkKj/3yazjgnqAL+/+FpFkKqB3e+tLDISHeO/MexA16dKtoCQS3Lj1EwRHhzGaLFidLqLxIFau1AOmcvj4KSKim8pF19I3MMSJM+dYsMBDhhGZaPDUM9fqIS+eRJUkzuoR3KZcRDHNyeiKR7C86x4MXd1o/lHk6dM5HhhlcTKKQUgptjsiY3Tt2Yt9RgPm6XUkOrsJHD6GPTCE7kn1XZYEpI42+n/8o3Qve7/1Der+7m8w5HjS3kd/WOPrD51jUUMe5QVF7NoxQL8vwn9/YgWXfKC6DkLtdBr+/UskBgaQ7XbEwmJUQ4Yci6JItLVt0pMJN58ld4vGpfc43+wh3+plMJIxKM3Nn4FLvnyu6RQuj6lZ9CpCECRETcPaNAtt9mIENPS9L2G84lLUVweaptNY5eGZfdkhHbIkUpVvT1uaJoZ75hq83FS/kcfPP8fc3FpudteS09uJKAyjSx42umfx7LYHsi+k61zsPEf5jMXUJVUe2HmBD9/RSH6uglFMkuMt4f4XBmgou4EbN7oReuIkj0Yomm5hdm4Dx0dSVlGb0cocxwp+cKELt91EIDyZ7PX4EmgT4uolLTWAR0IBVJNMtxpiel4Vpi3X4Zwzi+DZC1jqawmV15JnkBGE7Dy/Ao+FZCxjYcuxW5AEPa1aeSXoCvakieMlPNz8FE0rGuhtOcbepx8EIDg6wtO/+AY3vuuzWN2llzvVFKbwmpAkEaug4Bg5g3o29W0Xe4pwVn6ApLEOe44Db8jHhf/4d2recyuBjjburHo7XbEOpLjM5SQ7FH8Xgh5D8lRhbWhCam7mhtVr0EQRsfcsiX2/RZ6+BpetgdGYgRHfKF96vJOZ1R4+va4ag9udrh0GqQVV2GQHUgQyanPSaDNS56nkgq8dALfZyezCBuiHd828mVJjLk+/+DKjgYwyZHltBUKezIVAC/NKmvDHAoxEUyR0V+8xNlav4dTxg6DrdLWfw1tcQW15A8/89lvpc/i3389Nm9/Pgwkds/ENCg+cwl8kNE1nekUOT+1pz2pfNKMgpZ/0Jud8G91uDDlukv7RTKMoYvZme5tkXyvDv/ty+v9o61Hy7vo8MWfVFV3PpAu0arn84Lkgo6EgogC3rCpnRUPGwycIQMMsePppJsrkyqvWowli+iEl4gn+qnEEYe+DgE6OKPG+Fe8jGk9it6TOJ6pRzh3ekdUHTVMJD/fgyS1JX6+4yEZpvp2lTUVIokBrzxgOq4xdVFAuieGocdBeTTJ1mKDgKYoC8d5TdJdXc9hjxiYamW2yUD7aiZKTKWcRDw/z5E++hqamRr8jLz1BIhahacXNaONzvQGJy9Vqll5lYlDNCnUffSfRSKrdYtFIWLL7ORAZpD63mnlFM5BFIxElyosXdxFQxnCLnvR5TTYr+195lKqaOQwOd5Boi7Bg2Y1cqaM5EgnS0pIKR+3tS6XrDAwMMnNmE2bzOClKirwtby6Rx76CnkytrRbml8PahVnfgcVmY/uOl7FYLJhdDvxnTlFRXYkgmtKCMrqapPAD72bIbGYoKWApK6No5eJU/ZFxyBIMbX9uUl99+w5Q3DAz/X+OTeDdm4ops4cxan3UrbJzdsiNWcoII0FKdVb1FCB5CtBh0jNSVQ3n7FmMvLIrq929aBEaIpc6b5dd3DdtK0dHTnMx1MUMdz2zPdMxitYpDYgrwBR5vIoQRLDfdhdnIgoBUqER7pJ3UOj88xVLril2smlxOc8d6ETXYVatl5WziiZ9JLIsppLLNZkNZWtYUDATT/cFonseJ9BwLTHRgjMxiFXScObkYTCZGR3qT+cyymYHLYkk02wmblhVxnT7AMKeZ2B0mMZpC6i6eR4XhiQuSkMUFeVglV1YHFbe676eDmcDmsWI2VzEF++/gK6nPIKFuZPrEq5rtCO2H0cllT/iLmpg7YYCbFYXxriVITnKr88/zXDUz/qaZRTX30BPLMHDHb/AIll42w038PCzPcQTKh6nmXduLOfo3meRZZk1y5aiv3w/alE1hpmbSUqTr38JAmCMqiSHwogGEclrvezEo+oaqAqn9j2fvUHXGehqoTqndGrAmsIVQsOR8BMcyhiFFF8fif4jnDQt59mHT1NdYGXVBz9Jl6RxPqKgRkN4pBLEolysjdOInMnU3XXPm4XqayXWeRzzln/iCw+dQlG93DTbTkXX09CVUmeOeBvo3xvGbnJiK7DxmfcU8u1fXOSLzyj8zcc+xNC2J4n29KEEg1jveif3H095fAQBDMoIcb/IR6e/nQuhboKREMa4RO6IgdvC5ZiO7Ccsa6xdtJIHBwdJJBJU1FfR5RrmN4deAEAWZd4+62YeOvUEMSW1+BElA2u33McrT/wCJZkgt7CE88cyeZWXEBtu5SO3bcYwJZrzfw41xU42L6lg+/4OdB2aanJZOav4zzPu2hyUf+SjdHz9v1CCIUSjkZL3vAc5ryCtGilLAqEjz7zqQJ3o2d3IS2uuKJdeVQUeeqmX0VDqe9F0ePilTubUzONSfI2uQ7PqpPSvPoF8dA/EE2gLlnMo5uR6MgKUJcYQgYMPZlo0FcO+n5B7+7+gjYdjGgQDJrOVWDi7HqTJmFkDqSo43CqLZxTy6EutJBWNmTW5XLeqiKRBQhiPKpTtBUiO3LSyMoBotiM7C9PEQdITXDTL/KpjL+vzZxLXkny3dx8fmXY9eaKQFswZG+pNE8dLOHPoJRoWrUc0pLyPRsmId90ahp9/Mb2PIS8XqysnbXDTdZACPnxVM/CpAXQgV3Li6DyVdW6XwczSvNWcPBmhqzdOY72L2+tuwypJ6ccnqiLysJl519zKqG+AvBIvLms+ul+FbMfpH4SqXp5uTmx3yAr+A4+liSOANtiJY6wHPMXpNqPFxewFczh55ATRaBRProc58+eDKqWdmHqOm/4w3P98PwO+KE6bkXvXFzOnwJ52lWi6cFlVXUOOC3ECH8+3JMnzjMHZV9BG+/FUzaWsdjZGPY5+hQVszNMa8K5dzfCOlAfZNW8ezoWLULLC0yXKXBXkGnJIqklMBiNWq3NqHXaFmCKPVxGCptFvgSc7H2QoMh7D7irH672VvD9Df2RZxCGL3Lm2lo0Ly1E1jVyHOSvnRxGStIfb2dV1EK8lh6WlC/BKeRTLToIYGF31Cb72aAe+YIxibyGfqHMSLdrAyTY/DfNMlOs9uMw6uqgw2vIoY/VN3DKjEuXIDqJd51KWqINP41SS6GXlfOf4EwDkmF3oQZ1Py++kqLUATVEwLLPTVOniwLnUszvTNsKHb5tFfHQYjyGG0+PBlehHPeVHchdgWnobnb39uNV8EruDhNYJfLflQaJKjFvLllAeDpCbq2BU4fbCTSSMKruHnmfLljlMt9ViPnEMw9nDbKqfhstpI3byJKbS6QT3/xZPQTVC0ZzXHFCMoSQDjzSny21IVgMVtxZjkk3ElczgvGX6ZgyCGavdRcA3lHUOk9k2NWBN4YohSTLxgcnhOcneZnbGqmlu99Hc7sNmr8NbrPD08M/THvH5+XO57UMfIGfHTgJnzuGaUYs5B8Lj36WajHC2I+XZ+1p3gM/eeB1lw61oM6/nxW4rn7mpAJc3hxeO9xGK+PnwbTNxGhV6ol10VTpwzq2iYvocnjujMDjaSXmBg1uWeuk/+BDDBplNq+5mrtmO6rASiIcY/MVDdLW3U7r1evSRPUg2Dzdffw2jA8M4LTJyKMmZ8Tp1iqbw1PkdLCtfwIsXd7OgeDZuQw5StZeb319FMhrB6vKw+4mfMtLfjdFkQZRlYuEgXq+HohzLFakvTuF/BywGiTvW1LBhQdll58A3E7oOcmUNNV/4NxI+H+YcF7rTk1W1SQcEw2TREkE2XdZA+fsQ0SU6+oMsqM1hfomJoYjGMyd9DAcSlIxXmtI0nbpSB/9y/wWKvAuRrQJtuwL8473ZaqVSYpRX1zLQE1FkJUiC1MkMmsayNTdj03XUYT+i2UTMYsBid2fOI4Hfr/HwjkwJh1OtIxTkmrhzU3l6UarrNtwrP0Tg8C9IDlxEzivDtfAemJA3qMoSo0qYjwoF8PxvEQwmZi++lj41hndCV2VDpgTIJZgsNkQxE4mg6QrakrWUVFQQ3LsPc30dwqwFhDVxQi1BCFTP5PsnfkFXoBeAUkcR75/9DiYW7tIVKz99+CzDoykv6dl2P8vn5lG10ZkmYEmzTEvBEN86mAlhLrUX8ok57+ZKtXftdic5OTn4/ZnUgIKCAmy2zLPSdBXN3zPpWC04gjDBHhGOSMytqKSpvBRN1zFJEs19ceprMqWOAkmBH27vw2aW2biskO6+KN95spN/e08TedZL19PJ37Ce0QMH0yG+ksWCa/ZsEhOEdSxamMCO+9GTqWelHn8OUywIy+64wqcAqsVB/tvvoWDzRnRNQ/AWkRQnO29EUcZun5xjPIXXjynyeBWR0GWOjhxPE0eAjrFOLkY6aeLKwk3+FOhAz0iE7Qc6UVSNTYsqKM+z8WqjuyDo+IODjA75mG6r5Kmul3ixfQ9fXPRRDux8movNR7A7c/j7LbdhlXQS1iK+te0857tGATh6ARY0FLCyoIcze7YB0N16mrLK6TQa8slZei/B/T9HV5MkT+zEXHhn+tr+WMor0YePkp5Ux1xhhXcv87J+fhnd/hiaptNgHkQ/+120SADBZMW26V0ENn2Ijo6LnHn0wVROVv0cmuZuZNAdZo46g0Krh4VSEaaQjcgFBYtdQhhTOHvuJJvXL+e7539NU9ENjD34czyL5+EtFIkefwKDJGP0XIepuI5Q21H6TZUkYyJFHht2s5QmerIgMHawJ6tOoxpJkttn5O+Wf5SXO/fSFxpiXeUyap01aLrE/DU38tTPvp6e/C12J/mlNW/Arz+F/80woCLGwlA2Hc7uy9oWLZzDxT0Zi39Bvokdg09mhVIfHjzK8pLZzKi2YTLZiPe+TLgzFSYqOTyMxVWmlbs51zkKwDNnYnz45r/Dn7RyM+cYjMA/PdCOMu79OHBqiE/dPp2zT/4CdXyBcOHYPjbf9UFuqJ+NMJxAicWpXHwTRmuc0P5vowx1gijjWnQD1R++h96zraiqgFmuRff3YbBXEf/hA/QMD1Nos/Gx+7byfeEgA9ERhiM+yl3F3D39ZuaWzEbUZHRANrmRTW50YO6q63E3TKdfjBDTEtSZ8inNnzZFHP8PQ4C/GKVdXQfsLgx2F548B0ND2V46VdWxz7uW6PmDZNxUMuZpS4hd4TtsEJL8400VmHc8QfCZoxTkelh21z3EnBnSJAgC4a7D/NVaG8NxG6oO1zXJ+M48R9marelI1rjNCZIMEzx4ks1NxGLNLCQTUdwKnPvKf6cJg626ipx3vYOJMiXDg5OD5w83j3Dn6iouCc8KkSQDO8LYa+7GMg2UMYGhnSHyr09CTorOabpA/VgEm6EAYfknEAQNxd+MyaVnpai4vCV48kvwDWbI09LNdyDItvScHDLY6Y93c7qznbw5TQQCAdztLcxsmsdE6nl85GyaOAJ0B/s4NnyG2oLydNvgSDJNHC9h77EhblpeQd64V3FUjfFYx/PcXXMN1rgOBplj4XZaI/3MNLov82u+NgTBwDXXXMepUyfp7u6ioqKShoYZMLE2oygj1C6Do09kHavklCNPeFZV1ii9A73s3/5bopEQdbMW0zRvJUlVT0duBGMC167JY1A6xcnhM1TNrOA9S5YwGoG8cU5mkAUifgs1H/oc8cFOBFHClFuKEjRjN8pEo+NvRHAkTRwvIX7+APbFN5O4wqA9gxZDa9nF6O7fomsKjoU3YJyxgYR0ha7cKfxBTJHHqwhd1OgITvYI9IS73tR+9Pqi/NMP96UHg32n+vn8uxdRWmhkJO5DEkVyDG7aW1rYvSsVHy5JEm9bfT0dajcndj5J25lUwdnQmI/nHvoB119zA/7hBOe7ssUHDjUPsawi26/a1X6WaYtraP/VU5Ret4rI6RcQTVZi2uQJQ0aC8YAdLRIh5jCxbU8ns8tzKPfq6DtTxBFAj0cIPvU9ogtv58ThPelz9HScxbVyEd84+FMAFuXPYtZYMaGWgfQ+NbUFjJaM0XL4HB9adAceYw5Rmw3vgjqCBx9M7+d79nt41t3DaAz+44ETROMKTpuRv79vIXmO1BQiAGpocqFeJZggr6yA22tvAUFHVfT03O/wVnLTe/6awZ42jCYL3uIqZPNfdm20KfxlQQj003LuBG3tZ1i36jqoW0L0wn5Ax1yzgNOmaUBG0dhqha72yWNPQAkROrMb84q7SPr70SIB5LwKlHlb2H/8NFWFs9Lk0WaROdqtMdc+TPdPf86Fmz6QJo6XsG1vL6trZtF17ggA8VgEu+DC/1wX+iWpRlHAtcHLyNC4RLqmMLbvUTwODyE5wZGzR9m46XqMZift3/4JieGUmIEaDhP87i+45dN3893uZ2jw1DJroBTRl0A5twd50WI0hzt1yvGFdcxh5v4TL6TFKgRB4K/zP0wZU9/bFN4aSDgryHvbPxE9tw9BkjHXLSZuL73iIuZGNKw7n2DsaGo+T4z4GP7ON6j9l3+CcVEWUYSAf5jmgw8jyTKCIDKSTFBQdqk2XoowJAQLruXvILj/IbR4BMnuxrn0HYyJpvRCUjQa6Hrwt1lideGLbcSHhhCLUsZSVYV852TfWk2hE4vBQHJ8yBAkEUGA0IVQZicBREMm5tGgKbjstfj2qaiRFBkx5c/GWQ7aBGO5YLIy75a7GOhqJRkO4ywsxl5ckeXJVdFpPnGAyspK3G43Xq+Xs2fPojVmBIEALviyi94DnH9VmyxdxlAhCIiiccK/GlsLl3Pq0YdJjpcdqm+ai7P8j1uWGww25s1bwrx5CxEEeZKxzCjEiTcuRIwNo509gGg0oy+5gYjXi2nCrqOREDt+lxFAO39sLwajiYWrriOqpQRqrE4DJ7peoG20kzxbLmdGztE61s6nFnwkfZykg9IfI9wfRZALQNeJdUWwTbcgTohblUyTQ1MFoxnZaGHyKuv3Qxi6wOjOjCc3uO9Rclx5CJXLp6K8rjKmpB6vImRE5hfNntQ+M3/6VbuGKAiYkhqmhIZ8maK0kiSw+0TvpA9lODbCt47+iH995Wv800tf5RfNv2UknKmZo6oqJ/ccY6N3Pm3Nx7KO1XWdUEK7Ylnz+MAAyG6QZHKueT92e37W9kKrl/yQ49KNIZnjWIxW3lfqYWFHkOlyLE0cMx1VMJO9eC2fNZ8Hzz6V/n+5ay5KS7Y1N9EyxvTSWgKBAOWKnfiOvTT8498S782+11S/27goVBKNpybAQDjBb168wKVJVAEcswonHWcudaDrOqqqpYjjBOgImJ3FlDcsp7B63hRxnMIVwaglOHbgRfa98gTxaISB7S8zfGwMc+NtGJd/iPaSGzkzoLFqbgnvuGY6JqPE0TOjzMpvnHSuAmsOwRU30hxXOF++gcDKD3C2eDWPvXIYj7eQc12pb0cUBRbNKOSnz7QSaesCQbjs2lUDJmqCuXLzSbRHMsQRQNOJtCUw5mfXFNMiY9S481i2+XaONzfz/POPo65fgntTRvZeV1WswQQ1rnLelreZ6IFBZHuS4V27wR9HOTaAenoYU1RFFKF55HyaOEJq/Np2/tnUamYKU3gLQEMk5qhEWvQ2xPm3E7OXTaoT+HogJ5OMHTn6qpNrKEOD6X9VVaewOlV2QlUUlGRqyV41eyUTl4imQT+tP3wUsWgD5sat6M6lnPvaj7D5M5ENWjxObCA7PQNACWQIoChCpdvC7JqMoqjdYuCOFVVZ+ji6LJKzKFtQzj2/BN0wQfRKkon2msFjwbCpBnltJYoqoCWy59dhZYj/PvFLhk0KiVwHewPneejcUyBNXEsoLF68GJ/Px/79+zl//jyLFi1CErLHjbmeGZPub75nZtb/bquFkrxszYRrlpRjkjLE0KhDx8svpYkjQNfJo1hjl5M0e33QddB16bJRFqIA3z73OPfbdXpveDdn123l331HaQl3MnEpOTrUO+nYC8f3E4ln0nHi2ij5phKuz7+XQv8m1jvvZnnBKoLxzHsVSWrY61JuSF3R0Mdrhlor3EQiGVoo5VZgyK/Mup571Z3E5CtbI0mSSLTlwKT2yMmdyOLU2H+1MeV5vIoQNJUGZwNzCto5NnASAYGVZUsplov+8MGvA7IOyvkRBg90o6s61hoPjiWlaHISUY2jyjZ0JMRXkco8t4U+9TznRzJe0f09x5gxqx7XRRdjYylvYiwWQwnr2BxuwoFsWX2jLGIdvUBdSQ0XejITwbx6L1IsO46+tKIe5dxFBIMBS/V0zCX5RJr30eQt52uLP8izA6cosHppMFUhvOhDLrCRs8BDtO0F1OBC1HHvphY1IxjNmWLgAIKIYHVkXS+3uJxo39n0/+JrTLKCLlBdVcmJE69QrRkYO3oCoz1nsnXLkcdPXx6gMNdCQ7mL7qEoLV1jxBUVkyyi6zpymRPPygrGjvYhGiVylpWhOF47LEoUBURRQFFev9jBFKZwCdHgMOdO7gdSZEgXBQKnmwm3d+K/+2N8+8VMbSunzchHt85EjvXjLl3BcHSE9tFuZFFm6/RrECUDbZLOSLIHt2ThhYMpQZz8/HyaZjcRNwVYVOdmVrmFImecT91ShtDfhhIIMN2WRJYElAnFw29cUsz5pzI1Fq12F3ps8nuuxlMW5YkQZCOC2cILj9xPIp4ifIM97TTNXYm9rJRYV6oWXFXxND4wNAPtcATHmkICF09Rfsd9BI6NATqJkSiBI70U3DYjizheQiARRkdDeKOKsU9hClcZcVVjcCSGKAjku82XFXuKJFTa+4P4AjEqCp0UeyxIE4u5G0SMnhwSvuz5XLdlvkNJEjnZb6Rp4zvpOrodVUlSNnsdJwZtVE6we+uqQnJ0lK6HHs/uhJoJSNVtOXiXL2Zg+4tZu5hLitImX0EAtyRxX2kuI41FJFSNPFEiNxBHKjajqinCmjAKYDHgWV6OrmiIsoguCihmMe2BFVQRpdyFIgW52HYYo8FA5bJqojET5gl8YSwyxl2uhZx9ajvJeIyC0kq8y5YQ0SJYx9VpLEYjp06dYng86iESibBr1y623npr1r00qGWsKFrArr5UebFlhfNo0Mqy9nFaRd5/TSmn2gN0DieZWW6irtSB02pAGx87BUXB19/NqxELBiB/UvOfjIRgoNTiYZOzEmc4gS7K5JavYkhRs8ijxTzZE+jM8SKKYtp4aMVAoqeKXx3KrP1qyx0svtmd/l9VwVpixTW7kLGTAwiigHt+MYZcA8kJ3o2Y5MR1wyfRB86jjA1iLKpDcVdecZqBpukYvOWT2g35Vah6Rm11ClcHU+TxKkKXRB7e3ocmNHFL/QJA4OjRMPuHAtSWlPzJ5xfH4qhjo9gbDQguB4mgjDDaRmjvL0kOdmCuX4h98VaWzSrimf0d6Y+vvNjGudFDk87XPNTChsVL2L59OwAOhwN9UGXZ6tt4/okfpkM6iqsbMFlzUHf/kg+s+RDHAnUca/OxoCqXck+IhF9g7sprGOxuozivDFdQYeTpx8l7718x1nES5UhmshFcBcxd8mEUXy9D6nmKNjbgjxqQ+vbgqtnA2LbO9L6B5gQ5y9+N/6Xvg6aAIGJdezeJ4mpmrbyW4e6L5JXVUlI8jWvtKg+dTl3nQrKLZTkVqP6MpUzONRMz6cytaWJs0IUeHKHr/l8z+yv/QOTCodT5AcFogeKZXLdIwKoPM9B7ioqKPCo3zMBsFNNK1EkRxNoccqvcIAgkXmNgEgSIxYK0trYwOjpKff00cnPzEYSpT28Krx+6KCGIIrqqEvQPY731JnSHDVfTEr7/XF/WvoFwgnAiTokxxs4f/pDVcxayqWQGoqrj23OcM7ODbOt8hTtmXE+70s+0dU2gQYW3hBx/O0ua70cQRNRTo4SMZvKW381AIoClugrl4Z/yt3e+h92DAoGYwuIaM7LvJPPXXE9f+3msDhfFldOwGl2Ez49k9cvWmMvYc/3p/63TFqMLRkZCkTRxvIQzJ/eyfvkaYr/upvTut2EsLMNkCzKYm+C50/uJJ5PMtigkpifwDfuoa6pCPB4ietHPzLrpPHr2WfQJ3+R1tesQNWlq+TCFtwQCUYX/+c0xLvamIm9mVHv4q5tnYjdl5o24qvGth4/T3DGabvvglhksbixMz/0Bk4j9fW9DsZoYFmPYBCOO3jHGci0T+ImOw6DzrecjLG28EYMk8KM9o6xtUjGIOonxOU93OzBXlhNrz8zRrsUL0OzmtH8yrkvkb1iHGo0xvHsfBoed8rffgaGolEuzsSBAciSM3uKjpMyGaBCI9cYIiQIFdc60MVfTQSpzIAWTaKE4os2I5jAyMahHFSAiBnjimYw67cmzZ9ly3Q1Z5MOdEHnhmcw6ZLi7HcMRC3LJ3HTURDQaTRPHS9A0jbHAGBZrRlzFbXVy44V5rK9aAIC1XcNdmF0bOhEcZs+DX8Zsc1DrzKF/Vz9+i41N7/wcRmPKI2kwOCipbaSn5UzWsa7cN4A5AkJS546CRQz4gjQnjQi6TrlsptLmziKPTtFEXkEZQwOplAdRkpjbtByDColx21siZublw4NZ52/pDBIOGvBOcLhejOmc1WKs31qLjs4jh/tYUeog91W5jHHZBSULEUoFYn9kfKmu65gq5yIdeSat0Cua7Via1l1xrvAU/jCmVrBXEZqqE0uqnGr1caQ5015V6P6Tzy2KAoqvm67ffJOEz49kteJ6x30MBPLwKgq6miTavAct6KP8+k/z+XfN46WjvWi6yKK6PC6K9bT5s/Ofym3FDA0NYbOlvvb181cT3+XDYDNwzTs+S09/Dw6njYjZTHNCoHHF3VgLvVRINpabTAhykqee+xmxcBCL3UnDrKXkGB2YjCC8/1MMO80U7v5R1jX1sQEciSFGTE4OHTqIcuICNXWN2BtXYh5QEAwi+njSgxpOMnrKgeOWfyEcHMbsdNI/NMDF7Y9SVNVA1fz17Nl3gJyyEEsK5mOWjDzX9grtsT42b16JdnqMaGcAc5kTc5UL8Ugf0Z5ezA4LtkX1hBwONGs+uZvejeLvA0FENFlR1RhSqJtzHalSCKOjowwO9FByy21IUsZiq2k6CQF+n0UrkQjz6KO/Iz4e8tHScoF169ZTVlZ7xcp5U/i/B0lJoHa1E+/vZdaitVw8f4KyDRt4YHgPb196PYk+A4nkZJl2XyxEMi+CM8dL2+FsYZ3KOY1ousaDp5/gM/PfzVcOpb7RL+V/jMiBR7JCxfVEDFN4hJMn9zBj6WK8JidWfZQbKg2EBZVEYgTNKGKzuyisqGeopw2n6iF4eojclRWEzg2j6+CYV0hiNIpn/adBHQJRQDDa6XtmJ7G6ykn9FyUZx+w5eGfPR7ZCon0fAUcp2154Ib3Pizt3sGTJElraW2m+cJabVl2HHlApMhXx2eUf5LGzzxJORriudh0N7mlTOS9TeEtAFAX2nu5PE0eA0xd9nLroY2ljfvo97h0IZBFHgJ88c46Z1blYjKmlnU000ldg438O/zQ938wvmMEt9ob0MZoGM/J1qvLNvHg0FXJanGthdY2Mqglcmt8Skoj5xg3YewZJtHVjnFaNUphLEjFLUCZisxNbNIOqtctIaiqjkoRkzHizdB0MFh3Xajt+Xy+KksA9vxBDxI6gqTBBHVMFVIcBHK+hnKIpHDlxPKtJURS6ujqZ4S1MR/okRgOTDu1raUZMJsGYyr+UjAbMZjOxWLZ4i8mcHS0RMsdwVechnRlKjW2NeYRMcSbGQ12K3IqFg+myJUoyQSIaSpNHTZdYvOk2Xg4/wHBfJ7LByOLNW3G4/nRHw+VgFqFD0TlrHGWX7zAOg5X1ucupV0RsE9V+R8PMspWiLJ+DqmtYNJH4i7tJ1GdSsjRdv+x4qk+oEyqKAvGxYWyDO/nlzsMIgkDD/FWEx+zkOYsu61n8U9dEMZOXnNs/j+7rRNc0JE8ZcZNnyun4BmCKPF5FCJLOqgVeTrVmcgkFAWZOc/yeo14fxEiIlu9+Kx1+okYi+H/0PcLv+hRM34pn6D8BiHefxRHxkWOWWTvdwf4dg+w82s+Gu6dz2nmOjkAqTGKmdxqWoIwoCGyetxYxqKHs9qEnVdBkTnULBHOSbGv9GTo6oiDy3jl38/ijw7T1trG0sYAPrrbhLShhzDdEeX0TwZCfE807WHLN3Xz5d8N89qbSrKLDl+CwiDz+YqaQ6/mzJ3G7HeRW1ZIjleN7qT29TbOb+O2RCHMaSujb+Wt6288D0HvxLIUVdZSXNuB0ujBhYUneYhbkz0USJFBFzAvsWOty8b3cQfBUxkqmBZNIEYnyd90Hsoj/pV+hq0nQdWzTlhAze2nvyNTQg1QISyAwRk5O9kTyh+DzjaSJ4yXs37+PkpJyBOHPV/9zCn/5kCQBf+cA/V1+rKqANxDFfssdfOnwj9hQsgzDgTDENbYsrOAnOy6kjzPKImZnlAfPPs17F6xjbILF3epwMaqnFke6rhPzj1DtLGWapxazIqELIsbGVWA0o7YeQg36MBqM2Bxujh19GUEUmbvyGo489VRWXw1GEzfd+xmKo1XE9gZA0xELTYxVj+EqLCLUEyV+sJcAgCAjmmRkB2gJAVMgit3lITSWGTcXrLsZU2EF8sBphn/5VSSrk+7G7PAxgAsXLlBeXk5LSwvnelpZPX8FUVWgwlTJR+e9D13XkHR5ijhO4a0DAY6dn5w3eKZ9hOUzC9N1HqOJyblx0biCklRgnDxqusJPTz2atSg/PHCaDWVLyXEWAKlxINdt5wO1hxmZVY2qgzfRQ76nLMtjo4hWgnocit0kc82YLBbURBi7lBG/EQSdU/ue4+zhV7L6df29n8aeWzF+PUiaohw89DyyzYbRZOHUgSMsW3UTpivMTZMk4bI1DjVNy/rmrQ7XpH3ceUUYDKY0rzAZYOWK5Zw4cYKqIi/DY2EMFisuW3Y6itYZw3fYh7XCDQL4dnciz8uBCemZTvfkMhB2lweLLXstaDB7WX/nR4lHxpANRgwW9+WWTFcFmi5wNtHLwy0pL+0A0DrayWcXvI+aCZ5HQ2kR4d8+TLw3FdESFgSqPvVRBIs9rXvhNSeZX5fD4QuZcOhCj4Uie6bzgiigjZzj4pnDQOo9O3PoJVYXVSAIxbxRjC4uuyA/lcOb5A27zP95TJHHqwhdF2lTj3LvrdPZfySIQRZYPN9BZ+wkiyn7wyf4PVADoyR8vqw2XVWxxYKcjNlZZ89BDfkRDCYE2YjdYCIZjlBWbsE/EmHHQ528876t9IZ6EASRYI+fsy2n2XrdNZi7EgROji/4zDKe5YWowWG2tW1Lh35pusYDJ37Npjn30NYbpDoXAk/8N4uu+TAXzp+m5cQBzDYHy6+9A7s9F1EcBYOMsWE5iTOZiUSyueAy9XVazp8l7ozQaK/GdUM9kaEwQV3npC9MZb6TQluMw+PE8RL6Oy5wzarr0wVedV1H0jOELKFpWE0yiZHIqy+HwelEzC8iKcpYG5YTPb8f0WjB4CkiGvYjiiLaq0ZxSbryfKnLWdJefd4pTOHVEARo7wvwlUfaCUWTGGWR96+dRyLUj67rVFiLUUdSJHCWAn+1pYEXDvWR45aZO8vM490PoWgKruISRElGUxWMZgv1m67nh51PAyAKIo7ROB+su4WX9h/mxMgFauZu4cBLT5KIRZk5Zw2FyigoVhYVNNBVUE7zmYO4cgsm9bewopb+rlYqS5swFzgJJXycbH2RlrMHMZmt3Ljuk+mwNXTQYgrYDeQuXYgWHeLauW+na3CQseF+yuqacBdUIith/M//GHQNXUlglCdPVyaTiWRyPOdK1FGsMowvrgVVRECcWjtM4a0FHRY1FnCuMztPcVZtXtbckeuUMBkk4hMiDxZO92I3JoCUkTOWjKbLYk1EMJ4tKBcz55M7Zy05w+2gqYjeRcStRUxkYJLZgOiuoffkiyRjIcyOXIqb1mI0ZPbRklEunpqcIjM20p9FHsdCforqGmk+9AqxSIjaWYsY9PXhzC+5slWpEmdu4wyeGcwYhwVBoLykGFkWuMQrc2xuqutncfF8Kr9bkg0sW30TgmRKp6KYY2HK8VPgChA9/jwVeeU4Z9yIPtpHIi8j7iP1J0koGuEJTgKpf2IhErC78lly7ds5sP1BNFXFZLGxcsu7kQ3WyYYs0YRpXEzwjVwaJESdnT37s9p0Xacz1Ee1uzbdNjg6gLZpGXm6EeIJVJeNfaf3sHJaI4ip90ozity7rpLaAjsHLo7RUGRl/bxiLFY1ndtqEBXaL6SetyCKoOvouk5v62mqZy8lEplaB72VMUUeryIkQaDCns8vzt5Pw8x6FFXhl+0X+Njce//0c9vsSDYrajibCMXNNhwI6EoCc3kjzkU3EVUVnvnVNwj4h7G7c9l0/R288Iyfwy8M0TjfS0fXOQyiwM2rFiI1n6HnhV0UrL8OQTaTDPTS8cCjOO+7lUpHMQuddQwkRtk9fIqEmkQypgQzljc60ctupbOzlZN7U6Fk0XCQl7b9go13fYx33TCDZKyPTsFJ2aItiN2n0XOKiXgqicUmCzA73E5eHjhKWaGTf/vtWRY3FLB+Zi5zIyNo2x+FGzZc9rmYTJbfq0IXN0k4ZhUSPJ7JtZLsRsQ8J0lRQABsjcsRJQk15Ed2eTFdPMG8xnoOncqI8BQXFyMa7BOEy18fPJ5cDAZDZoELLFq0GEkyTtWdm8JrIpJQ+a+HThAar4WVUDS+v7OH99+TEnc4G2yjtnAuan8EocXHtKIczs6/wEhshJ+1tAOQZ8ulSC5ky92fIaiHkK1m/vv0g0SSUUySkftqr8OesCGbzFSVluKyGtn+8A/TfTiw63mWb7wVHttBpL2D2vfcR9k7VmK12Whaup5T+15E13Xc3gLKa2dy4cQ+8kpLGC0cIjTUiyTqSLJMPBZBc6oIkpBW3AOI1XqI6KN4ot14ilYg5dWnjTahuIoaD6IGUrkrWjxCoVnDZDJlefLr6up4+eWXAWhsnE5SnVqQTOGtDU3TWdiQz4mWYY63pHLwls8qorEiJ4t42IUgH95SzVP7B+kdibJwei6zykRkFC7RSbNkZHZuPcdHMoZXQRDIs0xWsoybvFDizTS8iuXoqpmTvRIVjTci6UmSGDl0McTNRRlvmigb8RSU0N+ZXbrCas94/gQBVFlgzzO/SV/j5N4XmL18I4pwhXOiyYwjHOS6tWs5ef48RqORWfX1iEE/qpoRT1E6uigfTFC59AYUNMxJGPn+z8j5+79Hs6T6r0sGIid2EOs8DUCiq5mRgTa8Wz+X9UjMVS6iHdmE3FL1Ks+mIFE1YzEF5XVEIyEcLg8Gk+PPGgFhQsdhsDLEq3LRTTZEkTTRJpnkwIHnABBFCU1TsTndiGoSbZw86oqE/ztfZ9rYKE3VdSi7uvA/FcT5L59HcqZOoyNRWlZL/vz5+OUkIgLOGLjjEooy2Vs8hbcWpsjj1YSqMNNTzeaKlTzb8QqSKHFn/fWUW71/+Ng/dGq7m+oPfYiW//p6qoaSIODYcju/6UzyzjWF5E3/OMGj2xl67L+Q8ytZuXIdu/a8QsmsDfRGNJbfPI2LxwdwOQvYtLGS+Lk9hHd8D61kM9GuLtof+F76WtaKCmbKDvLO24jseZyqwgJWbL2en4UPoCfM/N37avlJ13ZKLF70Q6+yMuo6o0NdnGhzs3qGm+Mv7uW0wURBSQWB1l7ip1u55s6P43Q6CQRSeQgGg4GZs5p46NDzqIWryMuxMtcZZ+QfPpMxxTmsFFfU0duRCc8rrWnAbM/l90HVdayz8jF5LIQujGD0WrHV5ZKQUhTQFB1k8DdfQo+nSHm4eQ85a95O1WAreUvnMDAWwZPjpi/h4eP/s4e3b5rGmjnFSJcpk3I5mEx2brllK2fPnmF0dJSGhkby8y8f7z+FKVxCIJJgNJQd7pxIauQJXlxmJ3v6j7Bizjzce02oY3GkIyE2X7OUHzX/BoAadwXvKL4eS8JIa3KI/2j+Ie+o2MiHbMsZNYSwV1XxXO9BfjBwgurRMm4uWspoe8ekfpw+upt5lWVE2jvwvbCDkrzbUFrOUFRcgXndTaDrhAOj7N3+W+YvvR6LRyZy+Cy8sotcbx7VN97CrmMv0h0Zw7ikFNdAGDGhEi5x8NsTPaxZUE3BigUY3C70oSCqqtHrj/Klnx6iutDKB+sWk7yQytnU9/ySG5a9nQEcJDUoKsjj4sU2qivLmVGah+nY4xhX3E1CnKwWOIUpvJVgN8l8eOssRgIxRFEg12GaVFfNYTEz1neCRaUC1ukuBnrPkO+ai0kSuGRi1gQjt9akDK/HR87jsbi5p+YarAYbV4pBf4xHX27FZJBwO0yMjEVRVJ0VM4vIz0mFrurILN64lSd/+l/pkh+lNY248jKRV4IAAd/wJHLaeuow9YvWXlH9OFERId9N/FePMK+sHC08RKirg5wbN6OqE88vMLbnAOxJlXIIApLVykRTsJaMpYnjJeiJGEpolEsJjbquEbQZsNZ5iFxIeR6ttTkE7Uacr3IbapqA2ZaL2ZY7fuwV3NgbABmZWxuu4z/3fj8dUeY0OahzV2R5PHOcueSXVNAwrRFZFOgdHMTtKkQSDGmvojY8RvTiRQASIxlvZqJ3CIszVfc7ntBxzZvNF/d9j+S4Iq/NYOVvFr2PRGLKyPdWx5tCHr/85S/z7LPP0tPTw7Zt26ivrwegra2Nv/mbv2F0dBS3282Xv/xlKisr/yzbrgY0QcZ05BnWzVjB8uJ5CIAx7Md87iDk/Wlhq7quI06bQeO//B3BQR9Rs5PehMjbGMbVsRNfVzPJ4ZQgTrLnHKK/j+XXfIZP/6QVRQ0CA2xeXEFQ0Dl7bJCFJRXIi7Zgt5cjmkxoE6z5JVtvYeSRJwjtTS3aYu0dCP99P5/8wt+TtFn5+qmf0RsaxF5kocDmJBLMtsLpWpIVtSL3P9/Lu9bfw9mXH6Kz5Qw2h5u169+JPximrq7u/7d333FWlPfixz8zc3rbs2d7B5Zt9C6I0hWiSLFhsCTGEq83yU39xdyYmMTkJibe+0tuNL/Em2huYqqxYywIgoKCIF16X2B73z195vn9ceDsHpa2y8IWn/frxevFPlPOMzPnPPN8Z56CxdLel+D4kePMzr0Cn93HlePb8B7aTUOHEq3x3fcZ9dnbyRlSRmX5AfKKRpJdOALUs0+PERfSaVhXjiXFgf9QA81bKklfWIrutRKt3BsPHE9p3fEu9rxhRFf9huLh09gXzOLJV2NPUv/05h7KBvnITu48yfGZrxvYbB7Gj78SRUFO1SFdELsZ3A4zLf72N9aqAoQ9fG30nRyq280h/x4mzhyGt1ZHhBuoOGGloHUei0qTGFwjCC9vIDrTy68P/xWAZ48s5+Gx95Cv5POTPX+msi32VmN/wxH+N9TCZ12TO+XD4XCjV8em5rGmpqAfW0Nw73ocprkcD2js3LQWIQSDSkaTm5FL3Zrl1LyzCoBAeTnB3/yeCfctRbic/PBvH5PmtWO3mti74RC6IZh71alh1GPCuuBX/9hGWyDC9kNN7C6dTlmRILzvQ1SLHafNht2cictnpur3X2dY9hAQgtCugwQRuEbNAm/hJboqknT5mBTISDp7H/uWkI7ZYiHD50PXdVLKStmzbz+ZGVfF1wkFFYTNxbzsK7ghdyoAQU2jNWTHZT3bns/MfbIfZSiiU1Ufu2dazRoOU2J3Drs3l4X3fZvm+irMFivu5CzoMNCcEGCxd37AY3d5UDUNunCLVPQQ2vHt2G67luamNlSThsNpwVF5GM03iMjJJr3WvHzMSUloDgeWZC+t+w+Qc8vNGE53bFhXQDE7UMxWRCTxoZ3SYRJ7VVUJHtyFf8t6ksdeAUDjlldRTBNRi6ZfeMZ7g9CoaK1m6aiF1AeasGpmTJqZxnAzKbaU+JtHd5KXWcNLaV7/POhRijMLSRp/NWGzvT0CNptRNA1xWn9Txdr+pVI1eLt8XTxwBGiL+NnasJ/Z2bnyAXo/d1mCx9mzZ3PXXXdx++23J6Q/8sgjLF26lIULF/Lyyy/z3e9+lz/84Q+9sqwnqCrYi6YQ+Pt/YDKZEcJAV02YF3yjR/YvUFDdNiIvP4nF5mCQZoYhozAPHkPr5rcS1jX8zTTV1MTnYxua6WSSsxX3uh0MMtnYHyogZ8gYQtVV5H96Cf7ycqKtbbhLiok2N1O/7rS28dEo4kQ1++ytnGiN9S/YULWDB6feQP0Lf4337XN7UxC6QVv9PlQ1h81Vbkpm3I9diVA2KBub2cEH2zawfftW7HY7E4ePw6nZ8TgdDBtcyuObf0dVay3DHFM6HX/L6vcJXj2Cqxd9DkOYL+hJnqoqhI40oQeiBI61j7jWvKkC15zBnQq/2LFGsE9YgDLyU/z8lUNsfTdxHsv65uAFB4+n6LI5ndQFDovBZ+YO4n9eO0gorKOpCp+bX8YL645xX6nO6BN7CFfsJRp8jkZAjLuJP20zUV7dxri0VMJbK0FAk9FKc7h9XtY9/gpC7oJ44HhKrb8eZ2EmDndS/GGQqmqMKBpHzVtPo5hMpF09jpaToyeHt7zJ0NxhlN3zNUI1jTS9uRIlrY7adxMHyhC6jgcrBw9v4TPXTeFXz2+PLysblEx2auIbEH8oyom6tvjf//16BSMHTeKBxYtxNug0f9RKtKkS543pgEHoRGLzOCH7E0ufEM3+ELt37+6UPnHSldhPxmoOi5n/9/dycrMtpKUbRCMa766r418WZ3f58zI8Nm6cMogXPjgcT7t7TjE+tyVhrmRVCJwRJ1pTGprThDnJSqhDfKko4HR5EgbJUhSFsnFTMUciRLQLv7eqJhVj/wYsH76CK2soRMOEqw5hjJmL2qGCoHuSyf3O/2Hvtg9oqKuieP692AvKEgKYiNWH5+olNK1srxNaC0aheNsf/Ou6QN+0jqZNH9G4qb3VVZKIYFw77YLz3RsalTbeOLCKOn8DTouDiB4hrEe4sWwehZ7B7SuGG2l+/7n4n5HKA/h3vI1l2j3oJ98LKx4PKQsXU/vCP+LruSZdgZLSoZWdAjVtieN0QCxNUdpH8ZX6p8sSPE6YMKFTWl1dHTt37uSZZ54BYP78+Tz66KPU19fHRmW6jMt8vs4DuHSHoQtaTOkkL36ESFU1iqZiSksjIJz0VEOqiCOTlAVfpvHjdzhcNpYXjm1gid5KpqqBkRgIBY3Y5bWaNT5bptH61P/lVJXRluSh4d4v43E5OfD7/8Kano5mt1P/4QayF96Aye0m2pw4vHUw5MdkBU1R0YVBxIjyXNUabrjxZjxtAiMSQY9G2LzmDcbMWMzSwUPZsLuWJ14+ytjiNEpKXYRVBU9yGg6Hg+snzCGyrhYj1IJi1jAcQdqCbYSiIWpyHVgcDnR/+1tBzzXTiDo0BJYuDemsmFQsg5Mx6v1Em04+VdQNFMCUVQSqKT7PI4Bn8mKCqouwRVDX2nlEu9SkrgWOktQVigK2QIjSUCWPX5dCszOZEAqpPhuDnCmEP1iJY8wUbIPGoYdbabZn87dtESrqWrhl6mCyG4IgwJRip9zWwPiMEeyo20coGiLHkYXbZkNVVAyRGGjVtFQzfOJ0TC4nzcEWMtNyiZ6oJunOm8kcWoqoO4w5cyiRyljT8cixnbjbAhz86S/IuPZTWLyDMCcldRrYK2xEKBo1BdWeyvfvm0x5VQvJbisFGW5spsRGak6ribwMF+VV7QHv9sNN1NbmE/qwKp4mzMnYiycS2LshnmbypqMkZfbYdZCkvsxhs5DiS6a4cBDoUUI6HK+oosNUkPiDIXYfaWD3aS3SG5vayE9zdenzhFXlhnG5jMr00BiIkOqykp/rSQgcFQXU6gBV/2zvY6k5zaQuLCVkjv3WDQNCTU2UjJkSG2tAj2K1OTh+YDcFhcO7lKewsOAonkpr+Rbaho5B1XUskRCWnGEomkL05O07Emhg14fvkOXJICPFSbixiaP6dvKHXRl/CG0YoA6ejHthOtG6Y6guH5bMQsJq+wOuaNTAlJ6Joml4hsfy2vzxx2jpmX2+VZFNs5FiT6bO30BbuL1elWTz0GFIBvTGSjRPKvYhV4JqIVq3n8CBj3Bc+Wl0Lfadsdut1I+/ksxBg9GrKtF8KQRSs7G5LPGQUBgKkzImsbfuYEI+hvmGy7eOA0Cv9XmsqKggIyMjPoKlpmmkp6dTUVGBEOKyLutq8JiScuZC19/cjKOpmn1P/CpegbLn51PwmTuwWPJIS7uAJpYXIu0qDvmSeHLNrwB4pXIznx9/LWLD6/FVHCNnsrsx1oRgakkypvJteG6/EX3fYdo2biHS1ExW/SHCaYX4Jk+ift2H7dsWZJF/2y0cfKp9jkZ3aQl1up/jH+3g+ilX88rh1QCcaK1hb2ot2UcbObZrC0IInG4vDruVg2t+R2rBfAqyPHxuwQgy0mIdBxpaM5k1ZRaRd2sxwrGAV0R0AisquGnatTy17+88XfUO935hCbnH/ITq6jAXD0H3uRlWNAyn+8JvehW1raxqamPdkRqG5yRxVWkq5g0nSJ6YiyvFhfAVYb7j+zRueA29pZ6k8fOwDxmL5oh9xr8tGcuPfv8hjS0hTJrCZ+cPpyg/GZu1/3UXTku7+Clj+qrePLazlQfd1fDxx+x59MfogQAASaNHkTF8GI5BJXgtCod276b67RVYfD6yb1yE/4MPWDDnU1w9VKEsP51oYwT/EBNudxKDttUyqO1KIiWzaPVG2fzBRyQlebm+8Fpe3d8+sfaM7AnUbt9O3pARvK8f4/3aTejVOqqicv+Q+fgf/zmR5hYyr5mBfXASwUMnn7obAlQVV+EYmjY1kHvzpzn41JPx/ToLC0kfOwF3duxNR2a6h3GlnUdrhfZr+G9LxvLDZ9p/c3fOLsZzpDleKbEVJnMwAG05nyLHOwjt6EfY8kfgGTMLS1rX36h0VX/6HfWXvPaXfF6IrpYH3T12f2OUsrwUPnrzzxiGjt3pZsaNd6MpOqkn92lE/GSl2KmoCyRs67Ur3fvcVEhKc2EEo2hOCyZH4nRT0UCEY+/vSUjT2yLQGCRtWPvvPmBxsWn7WzQ31KKoGiCYM2cJSjhCWt6F58sfDFNbOJ5XzI2sKV+FSTOxaPJMrkrOJ8vT/sj++McHST/SSMP6twFQLRbS778LqymM2xvrkxiNRlm58gO2b9+Opmno+lFcrv3cdtttJCW1D4jjmHwVKaUTCJ7QQShkzFlMwGvF4Yj9u9S6+31pqK9mcelcHv/gKfSTLxoynKkUufNJTW3fZ1tzDmrGdA7+8Z/ogQBJo0aQPe8unMlePNbYg/PWsJ/lu1aQYy9Bz8pBs0Q40LiCzw29iXRXbF+RqE7NOjcLhizgvYrVmFQT07NmUXnUxszinr1nXg4DqYzqCf2vBtwH1NW1nvHJiduh0bDxIyyTphDKHIwKKAc/JlB+guCIEbS0dB5ltDs0TWHDiR3xvw82HeeFNDfzr7+P9Aio7hSEN58pQRPbjviZNCWJF8r97Gz8mOIJ+Syafg/B//4DkZZm3vrLE8yZfyfFM2cRaW7C4lAQkSAVK1aRf8dSjFAI1WwmGghgz8gmuHUtw9vMfGnYrbRZFWyaBYuhkjxOJSu7AEVRyRhUwuodTVjsbiYUWbjuqljH65qa2PDgbrsdNazSGE6cy0pEDTx6rMD3RwL8vuZdvj/n6ySpdgxdR6DhD4I/mDjM+NlEheBXL+6Iz5l18HgTH6XU8cht44i4zfH8YMvBMv3zKBi4Ujyx9JMT+6a6zPzo/inUNwdx2s14HWZamgNcWA76jrQ0d/vxDjA9dWzdvTmcrTzoDi3czNE//jkeOAI0bd1G2rSZWJKS2PufjxGqjr2BC9fXc/QPz5Jz02IaqvewY93rpN32ZXbSwAhrCg0vH4z356GyDd/0bPKGjAbVSqHbTWppLiGliRSrE3sbeK+00drawpVmD0WDM9DNCllhK+IvrxNsirVCqHzrHQrv/zSwEc/E69EcJlKmXkm0VcEI6YSq3Qz91/9DuKkGk9PJfnsK/7ummuuvdOCynn2qm47XMMWZ+JtLs5qIHGokqCnY8pOoSnfy3afexxCQ7PZSlL2QazIGU4gHLvF3vD/9jvpLXvtqPi9HeXAxxy4MnQ0rXiI7v5CkZB/lhw/wwet/Z97tX4zv02Jz8MANpfzsbzvITHFS3xxkclkauT7zRZ3zeL7bggnpVkH8gXBHUX8o/nmqChbNzMSsEYSHudAROHUVa0sQ4XJ2KV+apvBh4x7eO74ZgIge4bm9y8m9ogBTTfuIskpDC83r25uZGuEwjS++jm/YKGoisc8Lh/0cOHCAEeOmEjYsWM2CE4d3UllZTTgce2vqcFhxW93UbmifGiR4AlKuL6StLYzfn9hf8kKZTCqGIc77vbmY74vd0Ehdr/Ctif/CiVANFtVMjkjBvV+lztISHzRHa9I5+qfn49s1bduBNTUVSqagN8de5dZEa3j/+AZgQ8JnzKybjBKIvSRRFMhM8vLXZdVcMXoxUV3wwgt1/OvNSX3y934up867DCDb9VrwmJWVRVVVFbqun3zKo1NdXU1WVhZCiMu6rMdEdQKDSnlqc5Cj+2OVrZEFw7nLZSFdPfvonKoCmr8FoaroNtd5m2QaBiTbkyjzDmaGq4R0cxIBi8Iu0UJq4XROjYKc4oSv3FHGT9f/kuqTfZx2NR6iIljHvy6ei+H1Et0ZZvmrf+DGBx7BbCnFGqikZdNHtB04SNuBg7GS/mSpUjrlUW6YMZPwx6tQjiXhnDifV158jpbGxKGfZ9z+Nf6++gRfuu4qNKFjOu3YTZpKfVhHMamIDk09FE2hTYsVvgoKd4+5FatwEI0KoOtzLDa0hDtNtnyiro0TwTAF7sQnprpx5kk4hAC7WSUnRY7gKF1aqqoQrK8jeLS807JwQwOq1RMPHE8xwmFMaakcPbqV6z79rzhUmK6FEDUGDR0qImqag4/qwjzz9lEMEWvK/oUbS1HbDJojUfyBCrT0JN5f9ud4v8EJk+YQ+us/MYKJFUQ9rJI8/dMEKw5gcSSRvmgR+vEg/gOtROpCROoAxYtaksqf1h3jeG0bumFw+5ziC2pufvpvLgIoRT5cJSkIYPO6I/GYuKElxId7QtS1Rvn3O8d3aRodSerPWtv8XH/DLZiPbMKo30nJqNFUCjuBcBDbyeknCLZi1Q1+cdNowocaMafYaU6xE/IHsF+C3heGHsBR6KBle4dB9FQF1WbEpw8RAupNGt7BhVS9+ApGSwvmOTNpK8jGFYqCduEttHQlwroTH3HD4NmkqV5QFPYHjrKrZh8lntL4WAPC33mu5+Dx4xCNwMmPU1WFotEz+M2rBwiGdRQFbpo+As3cMT+CwO7aTvsK7KrFmt/17k9hXbD/eBNrtlWQm+5k8vAsfE7z+TfshoiqYqBi/0cDhZiI9TmsJTprcEIgEKio7LRt3QfrSb3xZrCdfGNoqJhUjXFpZQx15VARrGdNxWYU0b4nIWBUoY+ahhxeWXMYk6Zy66xCCrM9l+T4pMurK6Mi96iUlBTKyspYtmwZAMuWLaOsrAyfz3fZl/UUxWxhQ5uTozXtAz5sP9LMAe3sn2EKttL8xjJ2ff3r7H3oIUIfrkWLnvsNpRCCKZ4Sbt5jxfKzP9L4o19i+8dKJpaDWpcYLDWGG+KBYzwt2Ex4TBEbtscGtzAMHXGy/1PIkYm9Y7+DkxVJZ+FgIhU7aXv3T0TqjhMu30nDS//J1ClXJ+zb6fZissYKP79uxmN1YdETK4zhqOB37+zDmJCNcnLKDFQFx1UFZGZl8eDEz/C96V+jyFXUpb6Np1PPErBr5wjkJam3mKOClkAr3onjOy9zpyLQUG2dR180+3wUBx2c+P7P4Ngumt/4HxCJfXXbBnt5+u098aArFNH5n2X7UFuPc+idp9i37lWazREm33Y3peOvYsjw8aQUDMZZWtTp80y+JJqicMyeQ1VDA1FXMpahmdgLvPF11CQb5U4Tx2tjZeE7Hx2jLdy5//CFEkIQ1Q0MQ2A1d36QZLVoXODsOZI0IGQkueH9vxA+uJloQwXhzW+QFaxCM7U/6AxEVVIadZpWHCJwsIHmDSdQ3zuK2Xxpmg0KVILVu/CMdGNOtmPLcuAd7yDU1B6QCAFOp4tKk8C4fjrqzfNoys8AqxWztWvNPq2YWDL4egJb6/l49VY+XrWF5GNWxvuGo3ao3VrTOtfBksaMwrC1B2q6YuXZt48SPNWVRsA/Vh0lYHQcKVagmDu/c1GtWpen4lBVhfW7qnj8z5tYt6OCf6zczw+eXk9zsPvl5Ln4ETTlu1Fd7cesFnipNhkJ58rk9Xba1p6fB+b2a2MVbr458rPk7arn2PMv4/5wH18tuQ2Pmjh1mmirxHnsVb59czbfWJiGvvtviEDN6buX+qHLEjz+8Ic/ZNq0aVRWVnL33Xdz/fXXA/C9732PZ599lrlz5/Lss8/y/e9/P77N5V7WE8K6wbYjzZ3S91S0nWHt2Gv9ti2bOfHcPzBCIaItLRz+zVPoRw+ecf2OtP3HaF7xbnzo5KbtOwhWVHDiz3/GFG1vOmEzWU+ObJWopbGO5oZYUFk2/mpMttjTICHASM8j/+7PcKpE0RwO8u+9i9DWNxJ3YugkqdH4kzmz1ca0GdeiBGJvKvJSvOj7Kml4Yz/WaHvJqmlgNqn8bPU+Do9Mp35cBkdHp7NXMUg1ZTLcPZxULR1FXNzX0+eyMGdi4hQpw4f4SPeeffhzSepNbncyqVddg2f4CCDWNyf31qVEGm00WYKk3bIoYf3MRQto2riR2jfewjO8lNDRjQg9gqrVoXZoJtoY1jtVbprbwgizBxSF4qkzWdO4iw3Bw2RMnEJm0QQ+WvMW7mtmYkltrxCkz53D9iO7Wfbma6xfu4KQP1a2hTQF14wC0m8ahuu6ItYmW/i//9wZ3y7ZY8WsXfztRgjByMIUrJbEAPLGGUPl4H3SJ4rS2tBpmqnQnnXY9PaWAk7NTOuW01ortEWwtvZMF5rTRU1WHIUFHH7254Qa36dpz2scfvYpLFntfZE1DZSIn/Wv/ZH333qOtStfZM1Lz2C01hISkXPs/QyfJwQNR2ppaW5vBll5vAJajYTyzmwKU3DnzWgnX7c6hw4hY/pobHr7eWgNRKlrSmxlAdDQ3L5OOBzFVZx6ct6kkxRwFaUR7uLDMX9I529v701Ia24LU17depYtLo5JUThmtLAhy0n9uExqxmfySiBAyBqh46Dz5rxBJI0eFf9btVjIveN2olp70Ok2G2x/7QVqTtZVG2sq2fj8s7iV9nOlqgoVR/eTNWwym7ZsYvuO7QwaO4OaiiNnfbAv9R+Xpdnqww8/zMMPP9wpvbCwkOeee+4MW1z+ZT3BpBqMLUxi/7HGhPSS3DM3edSETu2KFZ3Sm7ZsIXlo2Vnbv2uaSsOOHZ3SW3btxuLzIZoaICU26qBXS2ZhybW8tPvN+HrzCqfjaIXUrHyKRk8ht2g04mSgpiiAWcV59QzKSksJN9Qh3C6UlOTYfEetDZ2O4bpZ1xDWDWwigrHpFSrG3Med03IxnnsWbc5CIrV+9Fo/ZMZGLVME3DyriO/9dj2/eD1WwUxLtvPtz0w84/F2lwIsnlbI8MEp7DhUR3Gel2EFPiw9UImVpJ6kKQJDA48jnaoV+0geu5iM2YswJzlo3NyMkqyx9aPXiYSCjPr8nWj+EIbNQiDJhf93fwPACIZQLLHKUdO6Z/BdeR+RtiT0qImMPDeq0t4FEsDnseHLT6Vw8WJW1e+goqWW4TnD+OfhNdRvKyXJNYfdH0PxvM+RawqSke4mqXEzkdr2yo07JT3+/wiAy0zEqrKlvCFefikK3LtgBBZN6ZGJstM8Nn5w32Q+2l1NWzDCpGGZ5PjkCMjSJ4tq6ty8UzFZMJlM8SaiSjR65tnpzzBFVU/RhpYw9Btfw79/P5p7GPbCoUTdyQnr1J44QjSSGMBu/uBtbhhSRsR04Q93VQWOHz+OpmlkZWcRjUaprKiktqqGvLz2+V4VoaCfeIfBd16LoprRW47j3/kmruFXxNdx281k+hxU1rcH5IqSOLq6rgsUh4W0mYMJ1cbWs6Q6iDotXZ6OSyhnvjQX09rqXOzREOlpJiK08t7BFpxOjaKRCm57rNXGqY/V7S6y73+AjMrjGIEg5swsjOS0hMyGWhtprK1I2H8kHCTQVIvF5gVAwUB1JLN+7br4OmvWbeTa2TPkVB0DgBwwpwcJRaU4JcCwQR52Ho69gZwyLIVMeyuRSOcfilBUbDk5tB06nJBuTU8/ZwFiGAbOoYXUrFiZkO4YVEDb4SMoHZq2KUJlZs7VlPqGUhdswGdLJsueiVWxUjRyGkJo8c8KK0F2Nuxh1ZH3yXKlM7PgSuyWLGw2O7rmwHP1bdS/9J/xfWvOJFSHF/2N36ARqzzapt5KnseE+43nyZgxh7aDsZuU3hZJKKByfHZ+9MAUjle3YjZr5Ge4cF+CEUztZpXRQ3yMK0rFMIweqbxKUk9RECjHj1Dx6qtEG5vI+/I3MCVZCRxpJXAE0q/NINpSi5YcqyjWVR/nner2eUfHTbseT34+TQ0NNO/cTdY1n0FvrkYxWWh457/RktIQk27GFGnh8zeW8PQr+wlFdDxOCw/OzMR87BCaS3Bt3hRqjFZe2Pk6hjBYOHYif3jxKAAfASZN4XvzNcJVexFaFjaHiys/dRuOM0yNYTdr/NstoymvbqUtGCU71UmG19Zjvz0hBGluK9ddkQ8gh32XPpFMqXmY0gqI1rTPw+G56hbC5qR4vdywGHhGJtO0pX36HM1uwuIzETh9hz3EUDTIKsCeXYAQcPr7OF0HRe38AFdRAFPX6gCKoTJixHBqLc18ULsVu2Zl8sgryCYlsbxxZKK502jb8vKpLfFd8yUCor0ppkVT+OKtY/jZsx/R2BrCbFK5d8EIUtyJQXrUomLOcmFynRwYxm0honX9TZrDrHLzzKH88Y32uTqddjN56ZemSbFi0khpErQ4zEycoBGO6Hi0JNw1dRj2xGa9utUBBUWoEHsQcVrhbbLY0Exm9Gjim2KLrcOLEkVl/6GjnfJxvKKanPzSHjoqqbfI4LEH6dEo2S6F+69w0zjSg6YquK0RrE71jBUcXSikX3cdDRs/ig9KYUlJwTVyFNFz1IeEAEfZcFylJbTujg2LbU1Px56Tg2vYMAx3csIrBpOwkGcrIM9WcHIHpxarnLrLKAqsr9rIX3e8AsC+ukN8eHwLn81fzLa1m7n22nlkpZeRdtsjBI9sB6sD3ZvFlo+3UnDV7Zj0MGGTnQ92bOXKmSNJn7KYtn0BjFDs6aI5zUG4wzEJAWluK2nuSz+0NdDlp4KSdDkoVcfZ/f0fxPsWH3v1ZWyT5qLU+MEQ6IFa0q6y4q9UGDVuNpXlB+LbqppGzpAyrKmDaN23D9VsJuzXiJjGEG1pIfnqG/BbBbv27MI5eQzL6v7I4htnQNRKVGvBkRyl+Rt/wJeZQfIX7uVXO/8W3/eu4Bq+eecClq8vx2NVmD1UI2nT07hnf5axnlwmmMyoZvdZH3I5LBoluUlnXNZTZNAofZKFVBfe+V9Gr9hLtOEE1twy9ORBCXUHVQki2t4nedIEgsdVTEkCq7eJSNN+cI67pPk718Oi9LwhmMyWhLeP46bOQ1cd0IVbdURAKMXgmQ3to4Nurd7Fd6Z+IaF8aIpEsRffhqOoDvQAWFLxm90oRghTh+aY2ck2fvT5KdS3BHHZLXgdpjMeR0RTwBuru3S3ZiEEXDkiE5/HxspN5eRnuJk+Nhevw3xJHnK3KAo2t0rh0XoCmzZj8iZhHTkCI92b8GD/QlgcXqbMvYU1r/05njbiilnY3Wnxv4UAl6tzIOxynf2+IfUfMnjsQQoq9uYA5Y8/EU/zm0yUPPRlDOPMzUSMjFxKHn2U0LFyFE3Dmp9P1JV8xnU7irq85H/py+iVxzECgVhbfosV0rO6VakKKgFe3vNWYlo0RKspiK7rLF/+Jrfe+mlMnsH4ppVRefQwkXCAA/t2smNzez/PwaWjcfgyCRyrw4i0oTnMJF9dgO7poTkuJamfUzAINFfR3FCNJWrgnXYljavWABBY+y61ZZMwjc0gVVUJuyIElv0Ysy8Ll1LI3OtvZt+BvdicHgpLR6GHo/htHkr/48fodVXsfexxjHCsQlb77lqGfPWLZBYP468H36XWX8/Lh16I50MzzWHeQ9/ClObjYNMx/iV7LkG7iRePvcvEvJGUpfkYm24Q2r+RcOVhHHPvJ+obgolYZUtWACSpd4XMyZB/BeoghdAZ7vtqRBA48B5CfwdLxhDCh+rwN1bhu+ErvZDbds1RlWuWPIgS0hG6QHVoHK9rJF2cedTzs9KivLb/nYQkQxhsq9rBtQV58bqQsJnYU7OT7JShqCQTjLTR0LaP4oKZ6B0G9IuP9OxzxP++lKymWMuo8cWpCCHQdXHJPtOqmGk5cJjjv/pNPE1dvoKCb38TcVqMZ0TaaK47QSQcJCklE6srFSHar4thQH5aAdfOvJm2kB+byUpqzmAU1RRvjGoYglGjRnPgwAH0k82kLRYLgwYPkQ/+BgAZPPYgxRBUr1yTkCaiUZq27yatdAxnekYlhEBPTsOUHHti05Uu11GLHfKHopxxz10kwKR2/jqcGmwnGo0SCPhxu+1oJjMWdyZ2TeW6O7/Mjg+WU3XsEIUjJjJ4xBWEVTOWcVlkjMwAVSGsKhdU0VQUiEYMohEDq11+NaWBR1EUast38fZzT8VrJgVDhjFk+lQaV68l2tpKxq51NE39FMu2VTJUdzNt6q00r34Wqo+gKSpXTF+K4c3CrLho+ziE/0g1jT47iuNQPHA8pfqV18n5yucxN2/snBdUTEWDeP3ZX1BXdQwAzWTim3d9CVdyHoYOfnMq2ojrsCoQisq395LUF52tMq6rdrxX3Ur98qcJlcfGF7BkDkFz+uja0DQ9R1EgGgrhbLUT3lyPEYpiLvLiTHFhGFEU5cKnqtAwMCsmhnrzmeQrIyp0VlVtxoSSMPqyw51GzvAxbFv7Bi31VRSOnkp+2YSEwLE3RS9D2aqEQ9S9+lpCmhEMEt5/EEv24HjQakRaeffF31J1LDYYjqppXHfnl3H6CuLbmUJt7P/p44RrY9O0+YEGs5nSn/wYPSk1vp7TmcxNN91CVVUlFouZlJQ0rFaX7D40AMgaeg9SNTAincM/EdHp652DbTi4Zdh8nt7813iax+rGHowV5BaLBbvdmbCNrhuY7KmMm/1phBEG1dLe6doQ6Kf6AVxg4Fh9vIU3XvyY1pYQ+UN8zJlfhtUhv6LSwGFEWmNNfTr8Jo4c3Enh1AWwei0AaWNGkZ6dRGleMko0gqjWcU39V0wuG4bXw8b1qwkGDjI2aTahI7HBa3R/BFXpXB009CjPH3qHTxXOZG/9oXi6WTNT5htK1bGD8cARYk3vt658jWk3PRAvsWSTb0nqnxQT+I/uwDf/C+gtdag2N4a/CRG+NCN6XgghINOaSsPy9lHlQ3sbyRiTjllT6EocZRgWbi++jn3r3uXIu6+iaSYWT51JQcao094oCpzebK5ecDcOu4mWNuMT13JCFeoZB0o6vclqY015PHAEMHSddW89x5wlX0IosRZkemNDPHA8RUQiRGpqUDsEj0KAzeahoMBDWpqbmpoWGTgOELJm3oMEKunTr6F5e4eRUFWVpJHj0LR41+M+SQjBaN8Ivjr5fj6q2Eaaw0da1Mu29zZhsViYO3ceZrP9jAWuIQDFclHxcVtzmOf/uClesBw9WM/yV3cyf8moc28oSf2IHg0TbGvpvCDJTeb860kaPx4lJx8DENEIbWtXc/T3f4ivlnP3HVSfOMKosdcQ2tJeATSCUVxlRSiahuhQQTDNvYr3q1aRk5THF0bfxda63dg1K8O9ReQ6szhyeH2nrDTVVSGikdiY+pIk9VuKHiKcO4rXl71EMOBHIJg4eQZFaeff9lJRVYjWdh6uJ7ivEeeIFOhCsaOqULNvN4e3fAhA1Aiza9WbpGfmkZSd1Wn9qK5gtTtobj1DGTzARc1Wshcu4OD/a2+2qpjNeIqKElq8hfydHyw019Vg6BGUkyP8ak4nmt2GHkic2sSUlHTxreCkfkEGjz1IR6BoKRT+y5epfX8VmtWC74rpKIrnsjRLuFgmYaHQMZTi4mKEEITDfgpuyMdud5w1cOwpTQ2BTk+kyg81EPJH5dtHacAw29zkFpZx7MCueJqqanjzC7EOm4xhiPgzGKWhlqN/eDZh+xPP/o0Rn7mJlpY6PO4hRFvam6m27TMo/ta3qF75NnqbH+OqMbwq9hPSwzy760UmZY7ihuy5NFYHyXNloCgWUrMKOF3xmCtRzbZTY/hIktRPRUx23l+3Fn9r+7gEH65dQVbRSHprtmPDID5SaUcmrwVhsUIXmpLqepAj2zd1Sq88uJf8QWMJh/vuA/vLTRUGoepq8pfeRuO27ZhcLjzDygg3taBmtK+XlNo56C4eMwXN4ojfE3R3MoM+fz8H/vuJ+GBvObctgQ5TN0kDm5zwridFo6iWEG37TXhKF+DIv5a2/QpC9K9X9bpuYBgCk8mO2+3DZLL1eOCoqhDR2zvH2xyd+zk4XRZMFvkVlfo/RVHQNBWBiclzb6OgJPZG3e1NZe7tX8DsSOnUbyna0sLpEZyIRDDpgp1b38U0ypEwtoTJZ8Vvt5Dxuc/i/tI9PNb0Nlsa98eXV7TVsW1jDatfL0dRYo/3Xb5sZt74OWwOF6qqMWzidApHT5WBoyQNAKFQiLqq453SW1p7r9kqgDnTjTm1ff5ExaTinZx7sk5w4TTVRnJGdqd0b1oW0agMHDtSwiFq3llN+d//AUIQrKzk8NO/J1hentg/1JvFnFvux+7yoCgKJWOvpHTCTAyjfSUhwDx8DGU//g+GfuPrlP7oh7hnzsE4w7gZ0sAkr3QPiggz/trDWLNtmF0WUCBUW0E4lIToS0/A9ACtjdWgKLiS0kC7vBNst4V03tl8nPe2HCc/080ts4aSlmxnxLhsdmw6AcTa4c9dPAKTWe1XgbcknU5rrKFl0yaCx4/jnTQRy5Aipsy/m0nXtKGaLKimM7/lM/tSOjUNMnk8BFWDcCjA6rXPMnXabXjt6ag2C2qyjaAepLUh1sToO1c8wOMfPUNLuI1MZxo3pF/PmtUnuOHmUVhspliwqpjJGDyW+fcUUdvYxsvrqnnlb3u5dU4xQzPdCZUKSZL6F7PVji8jh/rTAkinx3eWLS6PkKaR/KliRIMfETUwJdsJWU1dHt40qguGT57NsX0fEw7GmsJ6UzPJKiiVD8BOY1jt+KZMpvK1f9L88c54un3IkNNOu0Zq/ggW3PPvGHoUk9WFITo/xDcUFVIyUVMyZVPVTyAZPPYgXTdwDSujetnr1L37WxRVJf26ebjyhveZ3o56qJFVL/6W2hOxyVtTs/KYceN9aFbvZfl8ocBzq/bz7ubYzaymMcDOQ/X8xwNTmDp7KCPGZhPwR/D6HDjcFhk4Sv2aqaWefT/8EZHGRgBqV79Lwefuxn7VDMIWM+VtRznRWkWeJ5tcRw4W0d6YTPf4GPqNr3PoiV8Rrq/HmpZG8m2L8butzLnlPkwWO86ULKKm2LDyRriF9W/8haP7tgPg8qbwvU8/QKtJwRq101qjc8f9ebg81tPecgq2HgnyxD/a+2r/+H838P37JpOX0mHSZ0mS+hVFszJ1+gKWL/sjQX8riqIwZsIM3FZ3r9dJwipwsnyJQrfmxVAUqAp4uOaz/0ZDzQlUk4mklBzqAg6ye6tdbh9lCPDOuJq2Y+W0bN2OYjaTvvB61KzMTsNVCAFojtggkLIOJp2BDB57kEmBw/4qlo3SmTxpKYYCb7YdYEmwjozk7s2/2JMURaF837Z44AhQW1HO0T1bGDJ65mUZfazFH+W9LYlPQQOhKCdq/ZTlJZGc5uT8s1xKUv8QKi+PB46nHPvb3xgyaRzPHXyNdcfa++tcVzSL6wquRTFiT3mFEKiDhlL09YcJNzZgOEz4W0OkK14seemdpvWpqzgYDxwBWhvr2PPhu4ydcQuGGdz5sfTTf+WGgNfeP8TptuytoWDqoF4vtyRJ6h61pZmqn/+Gq2dPI+q2Y0LFv2Y9kfQi1JKk3s7eRTMEmJwNfGv9rzBE7P2X0+Lga+MfRFUdsuzqQMFg/YbliAI3uRM/TVQYrNu7iYl1JfhyPL2dPamfkcFjD1LNCisad7C9bj/bae9rtNU7iHnqKAyjd5/1aZpCxeHdndJPHNpF0bjZl6WPgKYqWM0awdOa8VrMsm+jNACdoe2UiOrU6I0JgSPA6/vfYWrORLxqSjzNHBZUv30cEWnfTzMB0tOSwdXeT1hVFeorj3G6isN7GGOEY6Mhn4WiKHhd1k7pbqflEzecvSQNKMIg2tpK7fOvnJY8MBoamswKrx9aEQ8cAdrCfvY37CPbJQdv6UgYYaqO7qetuZFD+9tbmTTWVpKSWyZbeUldImvsPUgY0Bht65TebAT6RN8hXTfILx7dKb2gZAz6Geb/uRRcNo2lc0sT0gpzkshJcZ5lC0nqv6x5eWiOxKafWYsWEDrDvDZCCMLGae8To0ZC4BhfN5T4ezUMQVru4E7rFZSOQdHOHjie/GAWTS9EVdsLKafNxKjCFFmhkKR+zHAnkXn9dQlpJrcLa25eL+Wohxk6jeHmTsnN4VYURVZvO1I1GwUlnet/vsxcWc5LXSbfPPagqC64Jn8qe+sOJqRPyhpDJNLbPQxi7dizBg+ncMREDuzYAMCQ4ePJHjLishUeQsDksnRyUp3sO9ZIRrKDoTlJ2OSbR2kA0r2pFH/3O9S+/TaBo0dJnT0b+/CRaDZItifREGiKrzvIm4vPkkzH0QcMmwlLhotwVfvoiIpJRfV0DgiT0wcxYvJsdqxfCUKQNaiY4jFXXdDAEXmpdn74+SnsOdKA1axRnO8lxSX7HEtSf2YIBe+ca7FmpFO7ajWOwYNJnTWLqHtgdA4RQmNu/jSeavxLQvqYjLJ+MT3a5WQIGDZxFrUVR6k+dghFURh15bUkpQ6QBwnSZaUI2S6py+rqWs/alt4QIbbVfswrh1ZgUU3cOHQeJd4iRB+K0xURJdhWD4DN5ety3tLS3NTUXPwku4qi9LlmcT11bH3NQD0u6LljS0tzd2u7c5UHp6iqgoqBLpR4QNYo6li2bzm7aw8wJnM41w6ZgQdvp21tEYOmteUEjjRi9tnxzRhM2HPmJqUKBmF/Pbquk56VRXNr1ypQitKtcSsuWn/5fvaXfEL/yWtfzeelLA86fsblOHZFAU0RGKg90g+wL10zXQTYUr2DZYffwa7ZuLl4HkM9hRhoZ1y/L+W9q3oi74oIE2itR9PMWJzJiDOMpHopDITz3t0yYSDqOxHNAKEqVsZnjmdM+gisFjORSM8U1j1JKCasJ/sD9GbO+lrgKEmXimEIDBLbrnuVFO4oXUJYhLAqNsRZ4rygWcU1cxCeqEBoEIKzRngCFbMjFTNgtTuhtWs3a/mTlKSBRwiICoXeveNfGppiZ1LWJMZnjkZFBcXc5+pcfYlQLNjcmbH/y9MkdZNsK3gJ6LoAYcHj8chCTJKkszMULOLsgeMpESEIaRC+PLmSJEnqN3QjVucyhEnWuSTpMpDBoyRJkiRJkiRJknRen8jg8dChQyxZsoS5c+eyZMkSDh8+3NtZkiRJkiRJkiRJ6tM+kcHjI488wtKlS3nzzTdZunQp3/3ud3s7S5IkSZIkSZIkSX3aJy54rKurY+fOncyfPx+A+fPns3PnTurr63s5Z5IkSZIkSZIkSX3XJ2601YqKCjIyMtC02DDOmqaRnp5ORUUFPp/vgvbRcTLtnly3PxmoxwUD99gG6nFB7x5bXz6vfTlvp+svee0v+YT+k9f+ks8L0dVj6a/H3l/zDTLvvUXmfeD4xAWPPSE52XnB66akuC5hTnrPQD0uGLjHNlCPC3r32LpSHlxu/ema95e89pd8Qv/Ja3/J54XoannQX4+9v+YbZN57i8z7wPGJa7aalZVFVVUVuq4DoOs61dXVZGVl9XLOJEmSJEmSJEmS+q5PXPCYkpJCWVkZy5YtA2DZsmWUlZVdcJNVSZIkSZIkSZKkTyJFCPGJm1H1wIEDPPTQQzQ3N+PxeHjssccYMmRIb2dLkiRJkiRJkiSpz/pEBo+SJEmSJEmSJElS13zimq1KkiRJkiRJkiRJXSeDR0mSJEmSJEmSJOm8ZPAoSZIkSZIkSZIknZcMHiVJkiRJkiRJkqTzksGjJEmSJEmSJEmSdF4yeLwEDh06xJIlS5g7dy5Llizh8OHDvZ2lLpk1axbz5s1j4cKFLFy4kPfeew+ALVu2sGDBAubOncvnPvc56urq4tuca1lveeyxx5g1axYlJSXs3bs3nn6u69PdZZfb2Y7tbNcO+sf1a2ho4L777mPu3LnccMMNfOELX6C+vv6i8t9Xju1i9Zfvc3+6hg8++CALFixg0aJFLF26lF27dgF975ye8sQTTyRc/752PqHn7x8D5ffbUV+6l3TVue4xfUl3ysu+ojv3976iu+V/X3CuvJeUlHDDDTfEz/2ePXt6Obe9TEg97s477xQvvfSSEEKIl156Sdx55529nKOumTlzptizZ09Cmq7rYs6cOWLDhg1CCCGefPJJ8dBDD513WW/asGGDOHHiRKfjOdf16e6yy+1sx3amaydE/7l+DQ0NYt26dfG/f/KTn4hvfetb3c5/Xzq2i9Vfvs/96Ro2NzfH/798+XKxaNEiIUTfO6dCCLFjxw5xzz33xK9/XzyfQvTs/WMg/X476kv3kq462z2mr+lOedlXdPX+3pd0p/zvK86WdyGEKC4uFq2trb2VtT5HBo89rLa2VowfP15Eo1EhhBDRaFSMHz9e1NXV9XLOLtyZCqitW7eK66+/Pv53XV2dGDNmzHmX9QUdj+dc16e7y3rThd5c+uv1e+ONN8RnPvOZbue/Lx9bd/W373N/uYYvvviiWLx4cZ88p6FQSNx6662ivLw8fv376vnsyfvHQPz99tV7yYXqDwFMRxdaXvZF/TF4PN2FlP991am8CyGDx9OZevvN50BTUVFBRkYGmqYBoGka6enpVFRU4PP5ejl3F+7rX/86QgjGjx/PV7/6VSoqKsjOzo4v9/l8GIZBY2PjOZd5vd5eyP3Znev6CCG6tayvXdfTr53H4+mX188wDP7yl78wa9asbue/rx5bT+nr3+f+cA2//e1vs3btWoQQ/Pa3v+2T5/QXv/gFCxYsIDc3N57WV88n9Nz9YyD+fgdCHeFM95j+QJ77y+tCy/+++FvumPdT7rzzTnRdZ9q0aXzxi1/EYrH0Yg57l+zzKHXypz/9iVdeeYXnn38eIQQ/+MEPejtL0gUaSNfu0UcfxeFwcMcdd/R2VqRu6g/X8Ec/+hGrVq3iK1/5Cj/96U97OzudbN68mR07drB06dLezsoFGUhlkNSZvL69p7+d+/5Q/p/N6XlftWoVL7zwAn/605/Yv38/Tz75ZC/nsHfJ4LGHZWVlUVVVha7rAOi6TnV1NVlZWb2cswt3Kq8Wi4WlS5eyadMmsrKyOHHiRHyd+vp6VFXF6/Wec1lfc67r091lfcmZrt2p9P50/R577DGOHDnCz3/+c1RV7Xb+++Kx9aS+/H3ub9dw0aJFrF+/nszMzD51Tjds2MCBAweYPXs2s2bNorKyknvuuYcjR470yfPZk/ePgfj77S/3krM52z2mP5Dn/vLpSvnf15yed2g/9y6Xi1tuuaVPn/vLQQaPPSwlJYWysjKWLVsGwLJlyygrK+s3TSL8fj8tLS0ACCH45z//SVlZGSNGjCAYDLJx40YA/vrXvzJv3jyAcy7ra851fbq7rK8427WDc1+jvnb9/uu//osdO3bw5JNPxpuFdDf/fe3Yelpf/T73h2vY1tZGRUVF/O+VK1eSlJTU587p/fffz5o1a1i5ciUrV64kMzOT3/3ud9x777196nxCz98/BuLvtz/cS87mXPeY/kCe+8ujq+V/X3KmvDc1NREMBgGIRqO8+eabffbcXy6KEEL0diYGmgMHDvDQQw/R3NyMx+PhscceY8iQIb2drQtSXl7OF7/4RXRdxzAMCgsLefjhh0lPT2fTpk088sgjhEIhcnJy+NnPfkZqairAOZf1lh/+8Ie89dZb1NbWkpycjNfr5bXXXjvn9enusr5wbL/+9a/Peu3g3Neor1y/ffv2MX/+fAYNGoTNZgMgNzeXJ598stv57yvHdrH6y/e5v1zD2tpaHnzwQQKBAKqqkpSUxDe/+U2GDx/e585pR7NmzeLXv/41xcXFfep8wqW5fwyU329Hfele0hXnur59TXfKy76iO/f3vqK75X9fcLa833vvvXz3u99FURSi0Shjx47l3//933E6nb2c494jg0dJkiRJkiRJkiTpvGSzVUmSJEmSJEmSJOm8ZPAoSZIkSZIkSZIknZcMHiVJkiRJkiRJkqTzksGjJEmSJEmSJEmSdF4yeJQkSZIkSZIkSZLOSwaPknSakpISSkpKOHbsWG9nRZKkXibLA0mSOpJlgvRJJ4NHSZIkSZIkSZIk6bxk8ChJkiRJkiRJkiSdlwwepQHnm9/8JiUlJTz99NPxtG9961uUlJTw29/+lrvvvpupU6cyYsQIJkyYwAMPPEBFRcVZ93d6E5Vf/vKXlJSU8NBDD8XXWbFiBTfffDPjxo1j5syZ/OQnPyEQCFy6g5Qk6YLI8kCSpI5kmSBJF0cGj9KAs2jRIgBef/11ACKRCG+//TaapvGpT32KmpoarrrqKm655Rby8vJ45513ePjhh7v9ee+99x4PPvggx44d45prriEjI4NnnnmGH/zgBz1xOJIkXQRZHkiS1JEsEyTp4sjgURpwrrjiCrKysti2bRvl5eWsXbuW5uZmpkyZQk5ODk888QSlpaXY7XaKi4sB2LBhA0KIbn3eH//4RwCGDRuGx+OhtLQUgBdffFE+WZSkXibLA0mSOpJlgiRdHFNvZ0CSepqqqixYsIDf/OY3vP766xw4cACAxYsXs3HjRu666y50XU/YJhQK0draitvtPu/+T9/2+PHjAKxdu5a1a9fG04UQlJeXx28+kiRdfrI8kCSpI1kmSNLFkW8epQFp4cKFALz66qusWLECl8vFnDlzePPNN9F1nRkzZrBlyxaee+65+DZne6pot9sBaG1tBWDfvn0Jy3NycgD49re/zZ49e+L/3n77bXlTkKQ+QJYHkiR1JMsESeo++eZRGpAKCwsZOXIk27dvB+Cmm27CZrORmpoKwJYtW3j00UfZsGHDefdVVlbGpk2bePTRRxk8eDArVqxIWH777bezevVqHn/8cbZs2YLVamXPnj00NjaycuXKnj84SZK6RJYHkiR1JMsESeo++eZRGrAWL14c//+pDvJ33HEHc+bMIRQKsXHjRh544IHz7uc73/kOxcXF7Nq1i8rKSm688caE5dOnT+fJJ5+ktLSU1atXs3z5clRV5a677urR45EkqftkeSBJUkeyTJCk7lFEd3sAS5IkSZIkSZIkSZ8Y8s2jJEmSJEmSJEmSdF4yeJQkSZIkSZIkSZLOSwaPkiRJkiRJkiRJ0nnJ4FGSJEmSJEmSJEk6Lxk8SpIkSZIkSZIkSeclg0dJkiRJkiRJkiTpvGTwKEmSJEmSJEmSJJ2XDB4lSZIkSZIkSZKk85LBoyRJkiRJkiRJknRe/x+s9c36irtOtAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 920.975x576 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Xy = X.copy()\n",
    "Xy[\"Cluster\"] = Xy.Cluster.astype(\"category\")\n",
    "Xy[\"SalePrice\"] = y\n",
    "sns.relplot(\n",
    "    x=\"value\", y=\"SalePrice\", hue=\"Cluster\", col=\"variable\",\n",
    "    height=4, aspect=1, facet_kws={'sharex': False}, col_wrap=3,\n",
    "    data=Xy.melt(\n",
    "        value_vars=cluster_features, id_vars=[\"SalePrice\", \"Cluster\"],\n",
    "    ),\n",
    ");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "975421b2",
   "metadata": {
    "papermill": {
     "duration": 0.031937,
     "end_time": "2022-08-10T15:30:53.893560",
     "exception": false,
     "start_time": "2022-08-10T15:30:53.861623",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Principal Component Analysis ##\n",
    "\n",
    "PCA was the second unsupervised model we used for feature creation. We saw how it could be used to decompose the variational structure in the data. The PCA algorithm gave us *loadings* which described each component of variation, and also the *components* which were the transformed datapoints. The loadings can suggest features to create and the components we can use as features directly.\n",
    "\n",
    "Here are the utility functions from the PCA lesson:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "220bd564",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:53.954994Z",
     "iopub.status.busy": "2022-08-10T15:30:53.954606Z",
     "iopub.status.idle": "2022-08-10T15:30:53.965452Z",
     "shell.execute_reply": "2022-08-10T15:30:53.964477Z"
    },
    "papermill": {
     "duration": 0.044095,
     "end_time": "2022-08-10T15:30:53.967813",
     "exception": false,
     "start_time": "2022-08-10T15:30:53.923718",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "\n",
    "def apply_pca(X, standardize=True):\n",
    "    # Standardize\n",
    "    if standardize:\n",
    "        X = (X - X.mean(axis=0)) / X.std(axis=0)\n",
    "    # Create principal components\n",
    "    pca = PCA()\n",
    "    X_pca = pca.fit_transform(X)\n",
    "    # Convert to dataframe\n",
    "    component_names = [f\"PC{i+1}\" for i in range(X_pca.shape[1])]\n",
    "    X_pca = pd.DataFrame(X_pca, columns=component_names)\n",
    "    # Create loadings\n",
    "    loadings = pd.DataFrame(\n",
    "        pca.components_.T,  # transpose the matrix of loadings\n",
    "        columns=component_names,  # so the columns are the principal components\n",
    "        index=X.columns,  # and the rows are the original features\n",
    "    )\n",
    "    return pca, X_pca, loadings\n",
    "\n",
    "\n",
    "def plot_variance(pca, width=8, dpi=100):\n",
    "    # Create figure\n",
    "    fig, axs = plt.subplots(1, 2)\n",
    "    n = pca.n_components_\n",
    "    grid = np.arange(1, n + 1)\n",
    "    # Explained variance\n",
    "    evr = pca.explained_variance_ratio_\n",
    "    axs[0].bar(grid, evr)\n",
    "    axs[0].set(\n",
    "        xlabel=\"Component\", title=\"% Explained Variance\", ylim=(0.0, 1.0)\n",
    "    )\n",
    "    # Cumulative Variance\n",
    "    cv = np.cumsum(evr)\n",
    "    axs[1].plot(np.r_[0, grid], np.r_[0, cv], \"o-\")\n",
    "    axs[1].set(\n",
    "        xlabel=\"Component\", title=\"% Cumulative Variance\", ylim=(0.0, 1.0)\n",
    "    )\n",
    "    # Set up figure\n",
    "    fig.set(figwidth=8, dpi=100)\n",
    "    return axs\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "00564309",
   "metadata": {
    "papermill": {
     "duration": 0.029067,
     "end_time": "2022-08-10T15:30:54.026392",
     "exception": false,
     "start_time": "2022-08-10T15:30:53.997325",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "And here are transforms that produce the features from the Exercise 5. You might want to change these if you came up with a different answer.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "ff85b5e2",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:54.090026Z",
     "iopub.status.busy": "2022-08-10T15:30:54.089614Z",
     "iopub.status.idle": "2022-08-10T15:30:54.097139Z",
     "shell.execute_reply": "2022-08-10T15:30:54.095648Z"
    },
    "papermill": {
     "duration": 0.042773,
     "end_time": "2022-08-10T15:30:54.099831",
     "exception": false,
     "start_time": "2022-08-10T15:30:54.057058",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "\n",
    "def pca_inspired(df):\n",
    "    X = pd.DataFrame()\n",
    "    X[\"Feature1\"] = df.GrLivArea + df.TotalBsmtSF\n",
    "    X[\"Feature2\"] = df.YearRemodAdd * df.TotalBsmtSF\n",
    "    return X\n",
    "\n",
    "\n",
    "def pca_components(df, features):\n",
    "    X = df.loc[:, features]\n",
    "    _, X_pca, _ = apply_pca(X)\n",
    "    return X_pca\n",
    "\n",
    "\n",
    "pca_features = [\n",
    "    \"GarageArea\",\n",
    "    \"YearRemodAdd\",\n",
    "    \"TotalBsmtSF\",\n",
    "    \"GrLivArea\",\n",
    "    \"Neighborhood\",\n",
    "    \n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e959069",
   "metadata": {
    "papermill": {
     "duration": 0.029581,
     "end_time": "2022-08-10T15:30:54.160267",
     "exception": false,
     "start_time": "2022-08-10T15:30:54.130686",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "These are only a couple ways you could use the principal components. You could also try clustering using one or more components. One thing to note is that PCA doesn't change the distance between points -- it's just like a rotation. So clustering with the full set of components is the same as clustering with the original features. Instead, pick some subset of components, maybe those with the most variance or the highest MI scores.\n",
    "\n",
    "For further analysis, you might want to look at a correlation matrix for the dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "fb20f61e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:54.224899Z",
     "iopub.status.busy": "2022-08-10T15:30:54.224467Z",
     "iopub.status.idle": "2022-08-10T15:30:56.070744Z",
     "shell.execute_reply": "2022-08-10T15:30:56.069640Z"
    },
    "papermill": {
     "duration": 1.88164,
     "end_time": "2022-08-10T15:30:56.073244",
     "exception": false,
     "start_time": "2022-08-10T15:30:54.191604",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def corrplot(df, method=\"pearson\", annot=True, **kwargs):\n",
    "    sns.clustermap(\n",
    "        df.corr(method),\n",
    "        vmin=-1.0,\n",
    "        vmax=1.0,\n",
    "        cmap=\"icefire\",\n",
    "        method=\"complete\",\n",
    "        annot=annot,\n",
    "        **kwargs,\n",
    "    )\n",
    "\n",
    "\n",
    "corrplot(df_train, annot=None) # plot Xfinal"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a43287e",
   "metadata": {
    "papermill": {
     "duration": 0.032616,
     "end_time": "2022-08-10T15:30:56.137260",
     "exception": false,
     "start_time": "2022-08-10T15:30:56.104644",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Groups of highly correlated features often yield interesting loadings.\n",
    "\n",
    "### PCA Application - Indicate Outliers ###\n",
    "\n",
    "In Exercise 5, you applied PCA to determine houses that were **outliers**, that is, houses having values not well represented in the rest of the data. You saw that there was a group of houses in the `Edwards` neighborhood having a `SaleCondition` of `Partial` whose values were especially extreme.\n",
    "\n",
    "Some models can benefit from having these outliers indicated, which is what this next transform will do."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "055d8625",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:56.202992Z",
     "iopub.status.busy": "2022-08-10T15:30:56.202584Z",
     "iopub.status.idle": "2022-08-10T15:30:56.208004Z",
     "shell.execute_reply": "2022-08-10T15:30:56.207156Z"
    },
    "papermill": {
     "duration": 0.042518,
     "end_time": "2022-08-10T15:30:56.210923",
     "exception": false,
     "start_time": "2022-08-10T15:30:56.168405",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def indicate_outliers(df):\n",
    "    X_new = pd.DataFrame()\n",
    "    X_new[\"Outlier\"] = (df.Neighborhood == \"Edwards\") & (df.SaleCondition == \"Partial\")\n",
    "    return X_new\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb4cd8fb",
   "metadata": {
    "papermill": {
     "duration": 0.030843,
     "end_time": "2022-08-10T15:30:56.272996",
     "exception": false,
     "start_time": "2022-08-10T15:30:56.242153",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "You could also consider applying some sort of robust scaler from scikit-learn's `sklearn.preprocessing` module to the outlying values, especially those in `GrLivArea`. [Here](https://scikit-learn.org/stable/auto_examples/preprocessing/plot_all_scaling.html) is a tutorial illustrating some of them. Another option could be to create a feature of \"outlier scores\" using one of scikit-learn's [outlier detectors](https://scikit-learn.org/stable/modules/outlier_detection.html)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9fa3460",
   "metadata": {
    "papermill": {
     "duration": 0.031227,
     "end_time": "2022-08-10T15:30:56.335872",
     "exception": false,
     "start_time": "2022-08-10T15:30:56.304645",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Target Encoding ##\n",
    "\n",
    "Needing a separate holdout set to create a target encoding is rather wasteful of data. In *Tutorial 6* we used 25% of our dataset just to encode a single feature, `Zipcode`. The data from the other features in that 25% we didn't get to use at all.\n",
    "\n",
    "There is, however, a way you can use target encoding without having to use held-out encoding data. It's basically the same trick used in cross-validation:\n",
    "1. Split the data into folds, each fold having two splits of the dataset.\n",
    "2. Train the encoder on one split but transform the values of the other.\n",
    "3. Repeat for all the splits.\n",
    "\n",
    "This way, training and transformation always take place on independent sets of data, just like when you use a holdout set but without any data going to waste.\n",
    "\n",
    "In the next hidden cell is a wrapper you can use with any target encoder:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "943f06d1",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2022-08-10T15:30:56.401098Z",
     "iopub.status.busy": "2022-08-10T15:30:56.400337Z",
     "iopub.status.idle": "2022-08-10T15:30:56.410897Z",
     "shell.execute_reply": "2022-08-10T15:30:56.410066Z"
    },
    "papermill": {
     "duration": 0.046367,
     "end_time": "2022-08-10T15:30:56.413373",
     "exception": false,
     "start_time": "2022-08-10T15:30:56.367006",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "\n",
    "class CrossFoldEncoder:\n",
    "    def __init__(self, encoder, **kwargs):\n",
    "        self.encoder_ = encoder\n",
    "        self.kwargs_ = kwargs  # keyword arguments for the encoder\n",
    "        self.cv_ = KFold(n_splits=5)\n",
    "\n",
    "    # Fit an encoder on one split and transform the feature on the\n",
    "    # other. Iterating over the splits in all folds gives a complete\n",
    "    # transformation. We also now have one trained encoder on each\n",
    "    # fold.\n",
    "    def fit_transform(self, X, y, cols):\n",
    "        self.fitted_encoders_ = []\n",
    "        self.cols_ = cols\n",
    "        X_encoded = []\n",
    "        for idx_encode, idx_train in self.cv_.split(X):\n",
    "            fitted_encoder = self.encoder_(cols=cols, **self.kwargs_)\n",
    "            fitted_encoder.fit(\n",
    "                X.iloc[idx_encode, :], y.iloc[idx_encode],\n",
    "            )\n",
    "            X_encoded.append(fitted_encoder.transform(X.iloc[idx_train, :])[cols])\n",
    "            self.fitted_encoders_.append(fitted_encoder)\n",
    "        X_encoded = pd.concat(X_encoded)\n",
    "        X_encoded.columns = [name + \"_encoded\" for name in X_encoded.columns]\n",
    "        return X_encoded\n",
    "\n",
    "    # To transform the test data, average the encodings learned from\n",
    "    # each fold.\n",
    "    def transform(self, X):\n",
    "        from functools import reduce\n",
    "\n",
    "        X_encoded_list = []\n",
    "        for fitted_encoder in self.fitted_encoders_:\n",
    "            X_encoded = fitted_encoder.transform(X)\n",
    "            X_encoded_list.append(X_encoded[self.cols_])\n",
    "        X_encoded = reduce(\n",
    "            lambda x, y: x.add(y, fill_value=0), X_encoded_list\n",
    "        ) / len(X_encoded_list)\n",
    "        X_encoded.columns = [name + \"_encoded\" for name in X_encoded.columns]\n",
    "        return X_encoded\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a4e8284",
   "metadata": {
    "papermill": {
     "duration": 0.03096,
     "end_time": "2022-08-10T15:30:56.475230",
     "exception": false,
     "start_time": "2022-08-10T15:30:56.444270",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Use it like:\n",
    "\n",
    "```\n",
    "encoder = CrossFoldEncoder(MEstimateEncoder, m=1)\n",
    "X_encoded = encoder.fit_transform(X, y, cols=[\"MSSubClass\"]))\n",
    "```\n",
    "\n",
    "You can turn any of the encoders from the [`category_encoders`](http://contrib.scikit-learn.org/category_encoders/) library into a cross-fold encoder. The [`CatBoostEncoder`](http://contrib.scikit-learn.org/category_encoders/catboost.html) would be worth trying. It's similar to `MEstimateEncoder` but uses some tricks to better prevent overfitting. Its smoothing parameter is called `a` instead of `m`.\n",
    "\n",
    "## Create Final Feature Set ##\n",
    "\n",
    "Now let's combine everything together. Putting the transformations into separate functions makes it easier to experiment with various combinations. The ones I left uncommented I found gave the best results. You should experiment with you own ideas though! Modify any of these transformations or come up with some of your own to add to the pipeline."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "7292fa85",
   "metadata": {
    "execution": {
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     "status": "completed"
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    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.14254681703465139"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def create_features(df, df_test=None):\n",
    "    X = df.copy()\n",
    "    y = X.pop(\"SalePrice\")\n",
    "    mi_scores = make_mi_scores(X, y)\n",
    "\n",
    "    # Combine splits if test data is given\n",
    "    #\n",
    "    # If we're creating features for test set predictions, we should\n",
    "    # use all the data we have available. After creating our features,\n",
    "    # we'll recreate the splits.\n",
    "    if df_test is not None:\n",
    "        X_test = df_test.copy()\n",
    "        X_test.pop(\"SalePrice\")\n",
    "        X = pd.concat([X, X_test])\n",
    "\n",
    "    # Lesson 2 - Mutual Information\n",
    "    X = drop_uninformative(X, mi_scores)\n",
    "\n",
    "    # Lesson 3 - Transformations\n",
    "    X = X.join(mathematical_transforms(X))\n",
    "    X = X.join(interactions(X))\n",
    "    X = X.join(counts(X))\n",
    "    # X = X.join(break_down(X))\n",
    "    X = X.join(group_transforms(X))\n",
    "\n",
    "    # new Transformations\n",
    "    X = X.join(diffGrLivArea(X))\n",
    "    X = X.join(logTransformer(X))\n",
    "    \n",
    "    \n",
    "    X = label_encode(X) \n",
    "        \n",
    "    # Lesson 4 - Clustering\n",
    "    X = X.join(cluster_labels(X, cluster_features, n_clusters=20))\n",
    "    #X = X.join(cluster_distance(X, cluster_features, n_clusters=20)) #\n",
    "\n",
    "    # Lesson 5 - PCA #\n",
    "    #X = X.join(pca_inspired(X))\n",
    "    #X = X.join(pca_components(X, pca_features))\n",
    "    #X = X.join(indicate_outliers(X))\n",
    "\n",
    "      \n",
    "\n",
    "    # Reform splits\n",
    "    if df_test is not None:\n",
    "        X_test = X.loc[df_test.index, :]\n",
    "        X.drop(df_test.index, inplace=True)\n",
    "\n",
    "    # Lesson 6 - Target Encoder\n",
    "    encoder = CrossFoldEncoder(MEstimateEncoder, m=1)\n",
    "    X = X.join(encoder.fit_transform(X, y, cols=[\"MSSubClass\"]))\n",
    "    if df_test is not None:\n",
    "        X_test = X_test.join(encoder.transform(X_test))\n",
    "        #X_test = X_test.fillna('bfill')  \n",
    "        \n",
    "    if df_test is not None:\n",
    "        #X=X.fillna('bfill')  \n",
    "        return X, X_test\n",
    "    else:\n",
    "        return X\n",
    "\n",
    "\n",
    "df_train, df_test = load_data()\n",
    "X_train, X_test = create_features(df_train, df_test)\n",
    "y_train = df_train.loc[:, \"SalePrice\"]\n",
    "\n",
    "score_dataset(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "4c4256be",
   "metadata": {
    "execution": {
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     "exception": false,
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     "status": "completed"
    },
    "tags": []
   },
   "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>Missing Ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [Missing Ratio]\n",
       "Index: []"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.fillna(method='ffill', inplace= True)\n",
    "X_test.fillna(method='ffill', inplace= True)\n",
    "\n",
    "\n",
    "def check_missed_values(all_data):\n",
    "    all_data_na = (all_data.isnull().sum() / len(all_data)) * 100\n",
    "    all_data_na = all_data_na.drop(all_data_na[all_data_na == 0].index).sort_values(ascending=False)\n",
    "    missing_data = pd.DataFrame({'Missing Ratio' :all_data_na})\n",
    "    return missing_data\n",
    "\n",
    "check_missed_values(X_train)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cdf2004e",
   "metadata": {
    "papermill": {
     "duration": 0.033175,
     "end_time": "2022-08-10T15:31:03.685691",
     "exception": false,
     "start_time": "2022-08-10T15:31:03.652516",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Step 4 - Hyperparameter Tuning #\n",
    "\n",
    "At this stage, you might like to do some hyperparameter tuning with XGBoost before creating your final submission."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "d32bd38b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:31:03.752682Z",
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     "exception": false,
     "start_time": "2022-08-10T15:31:03.718959",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.1246171947138812"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#X_train = create_features(df_train)\n",
    "#y_train = df_train.loc[:, \"SalePrice\"]\n",
    "\n",
    "xgb_params = dict(\n",
    "    max_depth=6,           # maximum depth of each tree - try 2 to 10\n",
    "    learning_rate=0.01,    # effect of each tree - try 0.0001 to 0.1\n",
    "    n_estimators=1000,     # number of trees (that is, boosting rounds) - try 1000 to 8000\n",
    "    min_child_weight=1,    # minimum number of houses in a leaf - try 1 to 10\n",
    "    colsample_bytree=0.7,  # fraction of features (columns) per tree - try 0.2 to 1.0\n",
    "    subsample=0.7,         # fraction of instances (rows) per tree - try 0.2 to 1.0\n",
    "    reg_alpha=0.5,         # L1 regularization (like LASSO) - try 0.0 to 10.0\n",
    "    reg_lambda=1.0,        # L2 regularization (like Ridge) - try 0.0 to 10.0\n",
    "    num_parallel_tree=1,   # set > 1 for boosted random forests\n",
    ")\n",
    "\n",
    "xgb = XGBRegressor(**xgb_params)\n",
    "score_dataset(X_train, y_train, xgb)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bfc87c32",
   "metadata": {
    "papermill": {
     "duration": 0.031481,
     "end_time": "2022-08-10T15:31:30.260811",
     "exception": false,
     "start_time": "2022-08-10T15:31:30.229330",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Tuning to Hyperparameters\n",
    "\n",
    "We used the library ´optuna´ for this process."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "a52a8504",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:31:30.326844Z",
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     "exception": false,
     "start_time": "2022-08-10T15:31:30.292211",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2022-08-10 15:31:30,936]\u001b[0m A new study created in memory with name: no-name-76cd162b-935c-4bcf-a500-3e73e686a5a5\u001b[0m\n",
      "\u001b[32m[I 2022-08-10 15:33:43,539]\u001b[0m Trial 0 finished with value: 0.12523070375863432 and parameters: {'max_depth': 4, 'learning_rate': 0.07990864418776197, 'n_estimators': 5938, 'min_child_weight': 6, 'colsample_bytree': 0.9600202674481157, 'subsample': 0.3677486466875953, 'reg_alpha': 0.05383029419053908, 'reg_lambda': 0.4397770744662958}. Best is trial 0 with value: 0.12523070375863432.\u001b[0m\n",
      "\u001b[32m[I 2022-08-10 15:36:00,264]\u001b[0m Trial 1 finished with value: 0.12092953433817388 and parameters: {'max_depth': 9, 'learning_rate': 0.005167459280580282, 'n_estimators': 4153, 'min_child_weight': 4, 'colsample_bytree': 0.5958816172010266, 'subsample': 0.792197275466372, 'reg_alpha': 0.3707195271922529, 'reg_lambda': 0.0001771101414623181}. Best is trial 1 with value: 0.12092953433817388.\u001b[0m\n",
      "\u001b[32m[I 2022-08-10 15:37:24,611]\u001b[0m Trial 2 finished with value: 0.11891471380978738 and parameters: {'max_depth': 4, 'learning_rate': 0.010609654269962817, 'n_estimators': 3520, 'min_child_weight': 3, 'colsample_bytree': 0.7430579538261304, 'subsample': 0.5790346307121876, 'reg_alpha': 0.05769007641090065, 'reg_lambda': 0.00015188498661852207}. Best is trial 2 with value: 0.11891471380978738.\u001b[0m\n",
      "\u001b[32m[I 2022-08-10 15:38:45,821]\u001b[0m Trial 3 finished with value: 4.106789089967635 and parameters: {'max_depth': 8, 'learning_rate': 0.00021000238693702044, 'n_estimators': 5039, 'min_child_weight': 7, 'colsample_bytree': 0.8385042285681601, 'subsample': 0.6358189246725903, 'reg_alpha': 0.07407193997710583, 'reg_lambda': 15.563161062708843}. Best is trial 2 with value: 0.11891471380978738.\u001b[0m\n",
      "\u001b[32m[I 2022-08-10 15:40:10,511]\u001b[0m Trial 4 finished with value: 0.28419066026904377 and parameters: {'max_depth': 5, 'learning_rate': 0.004835061986719351, 'n_estimators': 4793, 'min_child_weight': 1, 'colsample_bytree': 0.8439942265653084, 'subsample': 0.20827426389428166, 'reg_alpha': 33.39316370672473, 'reg_lambda': 71.94660236213709}. Best is trial 2 with value: 0.11891471380978738.\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "import optuna\n",
    "\n",
    "def objective(trial):\n",
    "    xgb_params = dict(\n",
    "        max_depth=trial.suggest_int(\"max_depth\", 2, 10),\n",
    "        learning_rate=trial.suggest_float(\"learning_rate\", 1e-4, 1e-1, log=True),\n",
    "        n_estimators=trial.suggest_int(\"n_estimators\", 1000, 8000),\n",
    "        min_child_weight=trial.suggest_int(\"min_child_weight\", 1, 10),\n",
    "        colsample_bytree=trial.suggest_float(\"colsample_bytree\", 0.2, 1.0),\n",
    "        subsample=trial.suggest_float(\"subsample\", 0.2, 1.0),\n",
    "        reg_alpha=trial.suggest_float(\"reg_alpha\", 1e-4, 1e2, log=True),\n",
    "        reg_lambda=trial.suggest_float(\"reg_lambda\", 1e-4, 1e2, log=True),\n",
    "    )\n",
    "    xgb = XGBRegressor(**xgb_params)\n",
    "    return score_dataset(X_train, y_train, xgb)\n",
    "\n",
    "study = optuna.create_study(direction=\"minimize\")\n",
    "study.optimize(objective, n_trials=5)\n",
    "xgb_params = study.best_params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "97f84845",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:40:10.618620Z",
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     "shell.execute_reply": "2022-08-10T15:41:34.761910Z"
    },
    "papermill": {
     "duration": 84.219416,
     "end_time": "2022-08-10T15:41:34.802992",
     "exception": false,
     "start_time": "2022-08-10T15:40:10.583576",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.11891471380978738"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xgb = XGBRegressor(**xgb_params)\n",
    "score_dataset(X_train, y_train, xgb)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0510d0c",
   "metadata": {
    "papermill": {
     "duration": 0.032397,
     "end_time": "2022-08-10T15:41:34.870306",
     "exception": false,
     "start_time": "2022-08-10T15:41:34.837909",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Just tuning these by hand can give you great results. However, you might like to try using one of scikit-learn's automatic [hyperparameter tuners](https://scikit-learn.org/stable/modules/grid_search.html). Or you could explore more advanced tuning libraries like [Optuna](https://optuna.readthedocs.io/en/stable/index.html) or [scikit-optimize](https://scikit-optimize.github.io/stable/).\n",
    "\n",
    "Here is how you can use Optuna with XGBoost:\n",
    "\n",
    "```\n",
    "import optuna\n",
    "\n",
    "def objective(trial):\n",
    "    xgb_params = dict(\n",
    "        max_depth=trial.suggest_int(\"max_depth\", 2, 10),\n",
    "        learning_rate=trial.suggest_float(\"learning_rate\", 1e-4, 1e-1, log=True),\n",
    "        n_estimators=trial.suggest_int(\"n_estimators\", 1000, 8000),\n",
    "        min_child_weight=trial.suggest_int(\"min_child_weight\", 1, 10),\n",
    "        colsample_bytree=trial.suggest_float(\"colsample_bytree\", 0.2, 1.0),\n",
    "        subsample=trial.suggest_float(\"subsample\", 0.2, 1.0),\n",
    "        reg_alpha=trial.suggest_float(\"reg_alpha\", 1e-4, 1e2, log=True),\n",
    "        reg_lambda=trial.suggest_float(\"reg_lambda\", 1e-4, 1e2, log=True),\n",
    "    )\n",
    "    xgb = XGBRegressor(**xgb_params)\n",
    "    return score_dataset(X_train, y_train, xgb)\n",
    "\n",
    "study = optuna.create_study(direction=\"minimize\")\n",
    "study.optimize(objective, n_trials=20)\n",
    "xgb_params = study.best_params\n",
    "```\n",
    "\n",
    "Copy this into a code cell if you'd like to use it, but be aware that it will take quite a while to run. After it's done, you might enjoy using some of [Optuna's visualizations](https://optuna.readthedocs.io/en/stable/tutorial/10_key_features/005_visualization.html).\n",
    "\n",
    "# Step 5 - Train Model and Create Submissions #\n",
    "\n",
    "Once you're satisfied with everything, it's time to create your final predictions! This cell will:\n",
    "- create your feature set from the original data\n",
    "- train XGBoost on the training data\n",
    "- use the trained model to make predictions from the test set\n",
    "- save the predictions to a CSV file"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba240b07",
   "metadata": {
    "papermill": {
     "duration": 0.032729,
     "end_time": "2022-08-10T15:41:34.936781",
     "exception": false,
     "start_time": "2022-08-10T15:41:34.904052",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "\n",
    "### Other Models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "b36dc288",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:41:35.003849Z",
     "iopub.status.busy": "2022-08-10T15:41:35.003381Z",
     "iopub.status.idle": "2022-08-10T15:41:54.699873Z",
     "shell.execute_reply": "2022-08-10T15:41:54.698441Z"
    },
    "papermill": {
     "duration": 19.733384,
     "end_time": "2022-08-10T15:41:54.702415",
     "exception": false,
     "start_time": "2022-08-10T15:41:34.969031",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "XGBRegressor(base_score=0.5, booster='gbtree', callbacks=None,\n",
       "             colsample_bylevel=1, colsample_bynode=1,\n",
       "             colsample_bytree=0.7430579538261304, early_stopping_rounds=None,\n",
       "             enable_categorical=False, eval_metric=None, gamma=0, gpu_id=-1,\n",
       "             grow_policy='depthwise', importance_type=None,\n",
       "             interaction_constraints='', learning_rate=0.010609654269962817,\n",
       "             max_bin=256, max_cat_to_onehot=4, max_delta_step=0, max_depth=4,\n",
       "             max_leaves=0, min_child_weight=3, missing=nan,\n",
       "             monotone_constraints='()', n_estimators=3520, n_jobs=0,\n",
       "             num_parallel_tree=1, predictor='auto', random_state=0,\n",
       "             reg_alpha=0.05769007641090065, reg_lambda=0.00015188498661852207, ...)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor, GradientBoostingRegressor\n",
    "from sklearn.linear_model import ElasticNet, ElasticNetCV, RidgeCV\n",
    "\n",
    "y_train = df_train.loc[:, \"SalePrice\"]\n",
    "\n",
    "gbr = GradientBoostingRegressor(loss='huber',random_state=42)  \n",
    "gbr.fit(X_train, np.log(y_train))\n",
    "\n",
    "\n",
    "ridge = RidgeCV()\n",
    "ridge.fit(X_train, np.log(y_train))\n",
    "\n",
    "SVM = SVR(C= 20, epsilon= 0.008, gamma=0.0003)\n",
    "SVM.fit(X_train, np.log(y_train))\n",
    "\n",
    "xgb.fit(X_train, np.log(y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "78a1ac08",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:41:54.769794Z",
     "iopub.status.busy": "2022-08-10T15:41:54.769395Z",
     "iopub.status.idle": "2022-08-10T15:41:54.775019Z",
     "shell.execute_reply": "2022-08-10T15:41:54.773813Z"
    },
    "papermill": {
     "duration": 0.042686,
     "end_time": "2022-08-10T15:41:54.777465",
     "exception": false,
     "start_time": "2022-08-10T15:41:54.734779",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from sklearn.metrics import mean_squared_error\n",
    "\n",
    "def rmsle(y, y_pred):\n",
    "    return np.sqrt(mean_squared_error(np.log(y) , np.log( y_pred )))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7c36d59",
   "metadata": {
    "papermill": {
     "duration": 0.033719,
     "end_time": "2022-08-10T15:41:54.843716",
     "exception": false,
     "start_time": "2022-08-10T15:41:54.809997",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "3f37c2de",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:41:54.913645Z",
     "iopub.status.busy": "2022-08-10T15:41:54.912150Z",
     "iopub.status.idle": "2022-08-10T15:41:55.904570Z",
     "shell.execute_reply": "2022-08-10T15:41:55.903409Z"
    },
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     "duration": 1.031492,
     "end_time": "2022-08-10T15:41:55.907525",
     "exception": false,
     "start_time": "2022-08-10T15:41:54.876033",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "MHPred =  np.exp( 0.1*ridge.predict(X_train)+0.8*xgb.predict(X_train) + 0.1*SVM.predict(X_train) )##+ 0.1*randomFR.predict(X_train))\n",
    "xgbPLUSridge = np.exp( 0.4*ridge.predict(X_train)+0.6*xgb.predict(X_train) )\n",
    "XGBPred = np.exp(xgb.predict(X_train) )\n",
    "RPred = np.exp(ridge.predict(X_train) )\n",
    "SVMPred = np.exp(SVM.predict(X_train) )\n",
    "                 \n",
    "             "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4de9e25",
   "metadata": {
    "papermill": {
     "duration": 0.031589,
     "end_time": "2022-08-10T15:41:55.971409",
     "exception": false,
     "start_time": "2022-08-10T15:41:55.939820",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### RMSL for the models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "938e2cc8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:41:56.038400Z",
     "iopub.status.busy": "2022-08-10T15:41:56.038026Z",
     "iopub.status.idle": "2022-08-10T15:41:56.048186Z",
     "shell.execute_reply": "2022-08-10T15:41:56.047257Z"
    },
    "papermill": {
     "duration": 0.045583,
     "end_time": "2022-08-10T15:41:56.050082",
     "exception": false,
     "start_time": "2022-08-10T15:41:56.004499",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model Hybrid: 0.029568233029551336 \n",
      " xgb + ridge: 0.059764015748899835 \n",
      " XGB:  0.025352322500730502 \n",
      " Ridge:  0.12315260261247299 \n",
      " SVM:  0.007976489327412857 \n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(\"Model Hybrid:\", rmsle(y_train , MHPred),\"\\n\",\n",
    "      \"xgb + ridge:\", rmsle(y_train, xgbPLUSridge), \"\\n\", \n",
    "      \"XGB: \",  rmsle(y_train , XGBPred), \"\\n\",\n",
    "      \"Ridge: \",  rmsle(y_train , RPred),\"\\n\",\n",
    "      \"SVM: \",  rmsle(y_train , SVMPred),\"\\n\",\n",
    "     )\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ffced91e",
   "metadata": {
    "papermill": {
     "duration": 0.032013,
     "end_time": "2022-08-10T15:41:56.113718",
     "exception": false,
     "start_time": "2022-08-10T15:41:56.081705",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Predicctions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "699aa6b8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:41:56.180820Z",
     "iopub.status.busy": "2022-08-10T15:41:56.180130Z",
     "iopub.status.idle": "2022-08-10T15:41:56.758747Z",
     "shell.execute_reply": "2022-08-10T15:41:56.757867Z"
    },
    "papermill": {
     "duration": 0.614944,
     "end_time": "2022-08-10T15:41:56.761262",
     "exception": false,
     "start_time": "2022-08-10T15:41:56.146318",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "predictions = np.exp(0.15*ridge.predict(X_test)+0.8*xgb.predict(X_test) + 0.05*SVM.predict(X_test) )\n",
    "predxr = np.exp( 0.5*ridge.predict(X_test)+0.5*xgb.predict(X_test) )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "86984fbd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-08-10T15:41:56.830094Z",
     "iopub.status.busy": "2022-08-10T15:41:56.828908Z",
     "iopub.status.idle": "2022-08-10T15:41:56.842176Z",
     "shell.execute_reply": "2022-08-10T15:41:56.841324Z"
    },
    "papermill": {
     "duration": 0.048702,
     "end_time": "2022-08-10T15:41:56.844224",
     "exception": false,
     "start_time": "2022-08-10T15:41:56.795522",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Your submission was successfully saved-! \n",
      "\n",
      "Size:  (1459, 2)\n"
     ]
    }
   ],
   "source": [
    "output = pd.DataFrame({'Id': X_test.index, 'SalePrice': predictions })\n",
    "output.to_csv('my_submission.csv', index=False)\n",
    "print(\"Your submission was successfully saved-! \\n\")\n",
    "\n",
    "print(\"Size: \", output.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b939968",
   "metadata": {
    "papermill": {
     "duration": 0.031773,
     "end_time": "2022-08-10T15:41:56.908075",
     "exception": false,
     "start_time": "2022-08-10T15:41:56.876302",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "To submit these predictions to the competition, follow these steps:\n",
    "\n",
    "1. Begin by clicking on the blue **Save Version** button in the top right corner of the window.  This will generate a pop-up window.\n",
    "2. Ensure that the **Save and Run All** option is selected, and then click on the blue **Save** button.\n",
    "3. This generates a window in the bottom left corner of the notebook.  After it has finished running, click on the number to the right of the **Save Version** button.  This pulls up a list of versions on the right of the screen.  Click on the ellipsis **(...)** to the right of the most recent version, and select **Open in Viewer**.  This brings you into view mode of the same page. You will need to scroll down to get back to these instructions.\n",
    "4. Click on the **Output** tab on the right of the screen.  Then, click on the file you would like to submit, and click on the blue **Submit** button to submit your results to the leaderboard.\n",
    "\n",
    "You have now successfully submitted to the competition!\n",
    "\n",
    "# Next Steps #\n",
    "\n",
    "If you want to keep working to improve your performance, select the blue **Edit** button in the top right of the screen. Then you can change your code and repeat the process. There's a lot of room to improve, and you will climb up the leaderboard as you work.\n",
    "\n",
    "Be sure to check out [other users' notebooks](https://www.kaggle.com/c/house-prices-advanced-regression-techniques/notebooks) in this competition. You'll find lots of great ideas for new features and as well as other ways to discover more things about the dataset or make better predictions. There's also the [discussion forum](https://www.kaggle.com/c/house-prices-advanced-regression-techniques/discussion), where you can share ideas with other Kagglers.\n",
    "\n",
    "Have fun Kaggling!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ed121184",
   "metadata": {
    "papermill": {
     "duration": 0.03155,
     "end_time": "2022-08-10T15:41:56.971735",
     "exception": false,
     "start_time": "2022-08-10T15:41:56.940185",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "---\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "*Have questions or comments? Visit the [Learn Discussion forum](https://www.kaggle.com/learn-forum/221677) to chat with other Learners.*"
   ]
  }
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