TCN.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from matplotlib import pyplot as plt\n",
    "import seaborn as sns\n",
    "import quandl\n",
    "from fredapi import Fred\n",
    "import tensorflow as tf\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "import yfinance as yf\n",
    "from pandas_datareader.data import DataReader\n",
    "pd.set_option(\"display.max_rows\",200)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "pd.set_option(\"display.max_rows\",200)\n",
    "sns.set(rc={'figure.figsize':(16,10)})\n",
    "fred_key = \"df4910b2cad947d95cf6ab16ba11d74d\"\n",
    "fred = Fred(api_key = fred_key)\n",
    "quandl.ApiConfig.api_key = 'Qq5R29Xiqp2yUbb9dzNq'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot(prediction,target,grey=None,start=None,end=None):\n",
    "    # if start is None:\n",
    "    #     start=df.index.min()\n",
    "    # if end is None:\n",
    "    #     end=df.index.max()\n",
    "    # recessions=DataReader('USREC', 'fred', start=start,end=end)['USREC']\n",
    "\n",
    "    # pd.concat([,target],axis=1,ignore_index=False).plot()\n",
    "    fig, ax = plt.subplots(figsize=(10, 3), dpi=300)\n",
    "    \n",
    "    # if isinstance(df,pd.DataFrame):\n",
    "    # else:\n",
    "    #     ylim = (df.min(),df.max())\n",
    "        \n",
    "\n",
    "    Results=pd.DataFrame(prediction,index=target.index)\n",
    "    Results.plot(ax=ax,legend=True)\n",
    "    Results['target']=target\n",
    "    ylim = (Results.min().min(),Results.max().max())\n",
    "    ax.fill_between(Results['target'].index, 0, ylim[1]+1e-2, Results['target'],facecolor='k', alpha=0.1)\n",
    "    ax.legend([\"Prediction\", \"NBER recession indicator\"])\n",
    "    return fig,ax"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# DATA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fetching data from APIs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "MacroCode=pd.read_csv(r'Data\\Macro Variables.csv')\n",
    "MacroCode.replace({'Average HOUST':'HOUST','S&P 500':'SP500'},inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    }
   ],
   "source": [
    "errors=[]\n",
    "indicators={}\n",
    "freq={}\n",
    "for code in MacroCode['Variable']:\n",
    "    if not ('S&P' in code):\n",
    "        try:\n",
    "            col=fred.get_series(code).to_frame(code).squeeze()\n",
    "            if code == 'CPFFM':\n",
    "                indicators[code]=(col)   #.resample('MS').last()\n",
    "            elif code == \"ICNSA\":\n",
    "                indicators[code]=(col).resample('MS').sum()\n",
    "            elif code == \"SP500\":\n",
    "                indicators[code]=(col).resample('MS').first()\n",
    "            else:\n",
    "                indicators[code]=(col) # .resample('M').interpolate()\n",
    "        except ValueError:\n",
    "            errors.append(code)\n",
    "\n",
    "indicators['S&P: indust']=(yf.download('^SP500-20')['Close'].to_frame('S&P: indust').squeeze()).resample(\"MS\").last()\n",
    "indicators['S&P div yield']=(quandl.get(\"MULTPL/SP500_DIV_YIELD_MONTH\").squeeze().to_frame('S&P div yield').squeeze()).resample(\"MS\").last()\n",
    "indicators['S&P PE ratio']=(quandl.get(\"MULTPL/SP500_PE_RATIO_MONTH\").squeeze().to_frame('S&P PE ratio').squeeze())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1860, 124)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "S&P PE ratio       0.000000\n",
       "S&P div yield      0.016667\n",
       "AAA                0.326882\n",
       "IPMANSICS          0.326882\n",
       "INDPRO             0.326882\n",
       "BAA                0.326882\n",
       "AMBSL              0.342473\n",
       "TB3MS              0.423656\n",
       "NDMANEMP           0.455914\n",
       "SRVPRD             0.455914\n",
       "USGOOD             0.455914\n",
       "USWTRADE           0.455914\n",
       "USTRADE            0.455914\n",
       "USFIRE             0.455914\n",
       "USCONS             0.455914\n",
       "PAYEMS             0.455914\n",
       "USTPU              0.455914\n",
       "DMANEMP            0.455914\n",
       "USGOVT             0.455914\n",
       "CES3000000008      0.455914\n",
       "IPFPNSS            0.455914\n",
       "IPFINAL            0.455914\n",
       "MANEMP             0.455914\n",
       "AWHMAN             0.455914\n",
       "IPCONGD            0.455914\n",
       "IPMAT              0.455914\n",
       "TOTALSL            0.482258\n",
       "NONREVSL           0.482258\n",
       "DTCOLNVHFNM        0.482796\n",
       "DTCTHFNM           0.482796\n",
       "WTISPLC            0.501075\n",
       "CPIMEDSL           0.507527\n",
       "CPITRNSL           0.507527\n",
       "CES0600000007      0.507527\n",
       "CPIULFSL           0.507527\n",
       "REALLN             0.507527\n",
       "CPIAPPSL           0.507527\n",
       "CPIAUCSL           0.507527\n",
       "BUSLOANS           0.507527\n",
       "CUSR0000SA0L2      0.507527\n",
       "PPICMM             0.507527\n",
       "IPDMAT             0.507527\n",
       "IPBUSEQ            0.507527\n",
       "IPNCONGD           0.507527\n",
       "IPDCONGD           0.507527\n",
       "INVEST             0.507527\n",
       "CES2000000008      0.507527\n",
       "CES0600000008      0.507527\n",
       "WPSID62            0.509140\n",
       "WPSID61            0.509140\n",
       "WPSFD49207         0.509140\n",
       "WPSFD49502         0.509140\n",
       "UNRATE             0.513978\n",
       "CUMFNS             0.513978\n",
       "CLF16OV            0.513978\n",
       "CE16OV             0.513978\n",
       "UEMPMEAN           0.513978\n",
       "UEMPLT5            0.513978\n",
       "UEMP5TO14          0.513978\n",
       "UEMP15OV           0.513978\n",
       "UEMP27OV           0.513978\n",
       "UEMP15T26          0.513978\n",
       "GS10               0.547849\n",
       "GS5                0.547849\n",
       "GS1                0.547849\n",
       "IPFUELS            0.552688\n",
       "IPNMAT             0.552688\n",
       "IPB51222S          0.552688\n",
       "FEDFUNDS           0.555914\n",
       "TB3SMFFM           0.555914\n",
       "T10YFFM            0.555914\n",
       "AAAFFM             0.555914\n",
       "T1YFFM             0.555914\n",
       "T5YFFM             0.555914\n",
       "BAAFFM             0.555914\n",
       "CUSR0000SAC        0.565591\n",
       "CUSR0000SAS        0.565591\n",
       "CUSR0000SAD        0.565591\n",
       "AWOTMAN            0.565591\n",
       "CUSR0000SA0L5      0.572043\n",
       "CES1021000001      0.578495\n",
       "TB6MS              0.584409\n",
       "TB6SMFFM           0.584409\n",
       "HOUST              0.584946\n",
       "HOUSTNE            0.584946\n",
       "HOUSTMW            0.584946\n",
       "HOUSTS             0.584946\n",
       "HOUSTW             0.584946\n",
       "PCEPI              0.585484\n",
       "DDURRG3M086SBEA    0.585484\n",
       "DNDGRG3M086SBEA    0.585484\n",
       "DSERRG3M086SBEA    0.585484\n",
       "RPI                0.585484\n",
       "M1SL               0.585484\n",
       "W875RX1            0.585484\n",
       "DPCERA3M086SBEA    0.585484\n",
       "NONBORRES          0.585484\n",
       "TOTRESNS           0.585484\n",
       "M2REAL             0.585484\n",
       "M2SL               0.585484\n",
       "PERMIT             0.591398\n",
       "PERMITNE           0.591398\n",
       "PERMITMW           0.591398\n",
       "PERMITS            0.591398\n",
       "PERMITW            0.591398\n",
       "MZMSL              0.599462\n",
       "ICNSA              0.636022\n",
       "CMRMTSPL           0.637634\n",
       "UMCSENT            0.658602\n",
       "EXUSUK             0.662366\n",
       "EXSZUS             0.662366\n",
       "EXJPUS             0.662366\n",
       "EXCAUS             0.662366\n",
       "TWEXMMTH           0.696774\n",
       "RSXFS              0.797849\n",
       "AMDMUO             0.798387\n",
       "BUSINV             0.798387\n",
       "ISRATIO            0.798387\n",
       "DGORDER            0.798925\n",
       "NEWORDER           0.798925\n",
       "ACOGNO             0.798925\n",
       "S&P: indust        0.805914\n",
       "CPFFM              0.830645\n",
       "SP500              0.934946\n",
       "dtype: float64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "if len(errors)>0:\n",
    "    raise Exception(\"Erorrs found\")\n",
    "data=pd.concat(indicators,axis=1).copy()\n",
    "# data.to_csv('Data/HistoricalVariables.csv')\n",
    "print(data.shape)\n",
    "data.isna().sum().sort_values()/data.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def deltaX(data):\n",
    "    return data.diff()\n",
    "\n",
    "def delta2X(data):\n",
    "    return data-2*data.shift(1)+data.shift(2)\n",
    "\n",
    "def logdata(data):\n",
    "    return np.log(data)\n",
    "\n",
    "def difflog(data):\n",
    "    return np.log(data).diff()\n",
    "\n",
    "def difflog2(data):\n",
    "    return np.log(data)-2*np.log(data.shift(1))+np.log(data.shift(2))\n",
    "\n",
    "def diffpercent(data):\n",
    "    return (data/data.shift() - 1) - (data.shift()/data.shift(2) - 1)\n",
    "\n",
    "\n",
    "\n",
    "transformation={1:(lambda x: x),\n",
    "                2:deltaX,\n",
    "                3:delta2X,\n",
    "                4:logdata,\n",
    "                5:difflog,\n",
    "                6:difflog2,\n",
    "                7:diffpercent,\n",
    "                }\n",
    "df_transformed=pd.DataFrame()\n",
    "for column in data.columns:\n",
    "    type=MacroCode[MacroCode['Variable'] == column]['Transformation'].iloc[0]\n",
    "    df_transformed[column]=transformation[type](data[column])\n",
    "    df_transformed=df_transformed.copy()\n",
    "df_transformed=df_transformed.fillna(method=\"ffill\").dropna(thresh=110)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Adding Recession"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(659, 126)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=df_transformed.copy()\n",
    "recessions =  DataReader('USREC', 'fred', start='1800')\n",
    "df[f'in a recession']=recessions\n",
    "df['target'] = recessions.shift(-9)\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<Figure size 3000x900 with 1 Axes>, <Axes: >)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 3000x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(df.iloc[:,-1],df.iloc[:,-2])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def createXY(dataset,n_lookback = 60,n_forecast = 3,target_col=-1):\n",
    "    X = []\n",
    "    Y = []\n",
    "\n",
    "    for i in range(n_lookback, len(dataset) - n_forecast + 1):\n",
    "        X.append(dataset[i - n_lookback: i, 0:dataset.shape[1]-1])\n",
    "        Y.append(dataset[i: i + n_forecast,target_col])\n",
    "\n",
    "    return np.array(X),np.array(Y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(659, 126)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_lookback=12\n",
    "n_forecast=1\n",
    "\n",
    "df_for_training=df[:\"2003-01-01\"]\n",
    "df_for_validating=df[\"1996-01-01\":\"2003-01-01\"]\n",
    "df_for_testing=df[\"2003\":\"2022\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_for_training.iloc[:,-1].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Extract the last column from each dataframe\n",
    "train_data = df_for_training.iloc[:, -2].copy()\n",
    "valid_data = df_for_validating.iloc[:, -2].copy()\n",
    "test_data = df_for_testing.iloc[:, -2].copy()\n",
    "\n",
    "train_data.loc[:] =1\n",
    "valid_data.loc[:] =1\n",
    "test_data.loc[:]  =1\n",
    "\n",
    "# Create a figure and axis\n",
    "# Create a figure and axis\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "# Shade the training period\n",
    "ax.fill_between(train_data.index, 0,1+1e-2, color='blue', alpha=0.1)\n",
    "# Shade the validating period\n",
    "ax.fill_between(valid_data.index,  0,1+1e-2, color='orange', alpha=0.1)\n",
    "# Shade the testing period\n",
    "ax.fill_between(test_data.index,  0,1+1e-2, color='green', alpha=0.1)\n",
    "\n",
    "ax.plot(df.index, df.iloc[:,-2],color='r')\n",
    "\n",
    "\n",
    "# Set labels and title\n",
    "ax.set_xlabel('Date')\n",
    "ax.set_ylabel('Value')\n",
    "ax.set_title('Training, Validating, and Testing Data')\n",
    "\n",
    "# Add legend\n",
    "ax.legend(['Training','Validating','Testing'])\n",
    "\n",
    "# Display the graph\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "df_for_training shape:  (384, 126)\n",
      "df_for_validating shape:  (85, 126)\n",
      "df_for_testing shape:  (268, 126)\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "((372, 12, 125), (73, 12, 125), (256, 12, 125))"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "print('df_for_training shape: ',df_for_training.shape)\n",
    "print('df_for_validating shape: ',df_for_validating.shape)\n",
    "print('df_for_testing shape: ',df_for_testing.shape)\n",
    "\n",
    "# Scalling\n",
    "\n",
    "scaler = MinMaxScaler(feature_range=(0,1))\n",
    "df_for_training_scaled = scaler.fit_transform(df_for_training.fillna(0))\n",
    "df_for_validating_scaled = scaler.transform(df_for_validating.fillna(0))\n",
    "df_for_testing_scaled=scaler.transform(df_for_testing.fillna(0))\n",
    "\n",
    "print()\n",
    "trainX,trainY=createXY(df_for_training_scaled,n_lookback=n_lookback,n_forecast=n_forecast)\n",
    "validX,validY=createXY(df_for_validating_scaled,n_lookback=n_lookback,n_forecast=n_forecast)\n",
    "testX,testY=createXY(df_for_testing_scaled,n_lookback=n_lookback,n_forecast=n_forecast)\n",
    "trainX.shape,validX.shape,testX.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Prediction "
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## TCN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "def CustomLoss(labels, pred,w=0.3): \n",
    "    logits=tf.math.log(pred/(1-pred))\n",
    "    return tf.nn.weighted_cross_entropy_with_logits(labels, logits, w)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tcn import TCN\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.layers import InputLayer, Dense,LSTM\n",
    "from tensorflow.keras.callbacks import EarlyStopping\n",
    "from tensorflow.keras.callbacks import ModelCheckpoint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential_33\"\n",
      "_________________________________________________________________\n",
      " Layer (type)                Output Shape              Param #   \n",
      "=================================================================\n",
      " tcn_26 (TCN)                (None, 900)               7744500   \n",
      "                                                                 \n",
      " dense_50 (Dense)            (None, 1)                 901       \n",
      "                                                                 \n",
      "=================================================================\n",
      "Total params: 7,745,401\n",
      "Trainable params: 7,745,401\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n",
      "Epoch 1/150\n",
      "1/1 [==============================] - 110s 110s/step - loss: 0.9464 - recall: 1.0000 - precision: 0.1549 - auc: 0.5172 - val_loss: 0.2658 - val_recall: 0.0000e+00 - val_precision: 0.0000e+00 - val_auc: 0.5000\n",
      "Epoch 2/150\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[185], line 24\u001b[0m\n\u001b[0;32m     18\u001b[0m model\u001b[39m.\u001b[39mcompile(optimizer\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39madam\u001b[39m\u001b[39m'\u001b[39m,\n\u001b[0;32m     19\u001b[0m               metrics\u001b[39m=\u001b[39m[\u001b[39m'\u001b[39m\u001b[39mRecall\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39mPrecision\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m\"\u001b[39m\u001b[39mAUC\u001b[39m\u001b[39m\"\u001b[39m],\n\u001b[0;32m     20\u001b[0m               loss\u001b[39m=\u001b[39mCustomLoss\n\u001b[0;32m     21\u001b[0m               \u001b[39m# loss='BinaryCrossentropy'\u001b[39;00m\n\u001b[0;32m     22\u001b[0m               )\n\u001b[0;32m     23\u001b[0m \u001b[39m# fit the model\u001b[39;00m\n\u001b[1;32m---> 24\u001b[0m history \u001b[39m=\u001b[39m model\u001b[39m.\u001b[39;49mfit(trainX, trainY, epochs\u001b[39m=\u001b[39;49m\u001b[39m150\u001b[39;49m, batch_size\u001b[39m=\u001b[39;49m\u001b[39m500\u001b[39;49m,\n\u001b[0;32m     25\u001b[0m                     \u001b[39m# validation_data=(validX,validY),\u001b[39;49;00m\n\u001b[0;32m     26\u001b[0m                     validation_split\u001b[39m=\u001b[39;49m\u001b[39m0.2\u001b[39;49m,\n\u001b[0;32m     27\u001b[0m                     verbose\u001b[39m=\u001b[39;49m\u001b[39m1\u001b[39;49m,\n\u001b[0;32m     28\u001b[0m                     callbacks\u001b[39m=\u001b[39;49m[\n\u001b[0;32m     29\u001b[0m                         \u001b[39m#  f1,\u001b[39;49;00m\n\u001b[0;32m     30\u001b[0m                         \u001b[39m# f2\u001b[39;49;00m\n\u001b[0;32m     31\u001b[0m                     ]\n\u001b[0;32m     32\u001b[0m                     )\n",
      "File \u001b[1;32mc:\\Users\\amine\\OneDrive\\Documents\\PFA\\.venv\\lib\\site-packages\\keras\\utils\\traceback_utils.py:65\u001b[0m, in \u001b[0;36mfilter_traceback.<locals>.error_handler\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m     63\u001b[0m filtered_tb \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m\n\u001b[0;32m     64\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m---> 65\u001b[0m     \u001b[39mreturn\u001b[39;00m fn(\u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)\n\u001b[0;32m     66\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mException\u001b[39;00m \u001b[39mas\u001b[39;00m e:\n\u001b[0;32m     67\u001b[0m     filtered_tb \u001b[39m=\u001b[39m _process_traceback_frames(e\u001b[39m.\u001b[39m__traceback__)\n",
      "File \u001b[1;32mc:\\Users\\amine\\OneDrive\\Documents\\PFA\\.venv\\lib\\site-packages\\keras\\engine\\training.py:1564\u001b[0m, in \u001b[0;36mModel.fit\u001b[1;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing)\u001b[0m\n\u001b[0;32m   1556\u001b[0m \u001b[39mwith\u001b[39;00m tf\u001b[39m.\u001b[39mprofiler\u001b[39m.\u001b[39mexperimental\u001b[39m.\u001b[39mTrace(\n\u001b[0;32m   1557\u001b[0m     \u001b[39m\"\u001b[39m\u001b[39mtrain\u001b[39m\u001b[39m\"\u001b[39m,\n\u001b[0;32m   1558\u001b[0m     epoch_num\u001b[39m=\u001b[39mepoch,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   1561\u001b[0m     _r\u001b[39m=\u001b[39m\u001b[39m1\u001b[39m,\n\u001b[0;32m   1562\u001b[0m ):\n\u001b[0;32m   1563\u001b[0m     callbacks\u001b[39m.\u001b[39mon_train_batch_begin(step)\n\u001b[1;32m-> 1564\u001b[0m     tmp_logs \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mtrain_function(iterator)\n\u001b[0;32m   1565\u001b[0m     \u001b[39mif\u001b[39;00m data_handler\u001b[39m.\u001b[39mshould_sync:\n\u001b[0;32m   1566\u001b[0m         context\u001b[39m.\u001b[39masync_wait()\n",
      "File \u001b[1;32mc:\\Users\\amine\\OneDrive\\Documents\\PFA\\.venv\\lib\\site-packages\\tensorflow\\python\\util\\traceback_utils.py:150\u001b[0m, in \u001b[0;36mfilter_traceback.<locals>.error_handler\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    148\u001b[0m filtered_tb \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m\n\u001b[0;32m    149\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m--> 150\u001b[0m   \u001b[39mreturn\u001b[39;00m fn(\u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)\n\u001b[0;32m    151\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mException\u001b[39;00m \u001b[39mas\u001b[39;00m e:\n\u001b[0;32m    152\u001b[0m   filtered_tb \u001b[39m=\u001b[39m _process_traceback_frames(e\u001b[39m.\u001b[39m__traceback__)\n",
      "File \u001b[1;32mc:\\Users\\amine\\OneDrive\\Documents\\PFA\\.venv\\lib\\site-packages\\tensorflow\\python\\eager\\def_function.py:915\u001b[0m, in \u001b[0;36mFunction.__call__\u001b[1;34m(self, *args, **kwds)\u001b[0m\n\u001b[0;32m    912\u001b[0m compiler \u001b[39m=\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mxla\u001b[39m\u001b[39m\"\u001b[39m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_jit_compile \u001b[39melse\u001b[39;00m \u001b[39m\"\u001b[39m\u001b[39mnonXla\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m    914\u001b[0m \u001b[39mwith\u001b[39;00m OptionalXlaContext(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_jit_compile):\n\u001b[1;32m--> 915\u001b[0m   result \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_call(\u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwds)\n\u001b[0;32m    917\u001b[0m new_tracing_count \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mexperimental_get_tracing_count()\n\u001b[0;32m    918\u001b[0m without_tracing \u001b[39m=\u001b[39m (tracing_count \u001b[39m==\u001b[39m new_tracing_count)\n",
      "File \u001b[1;32mc:\\Users\\amine\\OneDrive\\Documents\\PFA\\.venv\\lib\\site-packages\\tensorflow\\python\\eager\\def_function.py:947\u001b[0m, in \u001b[0;36mFunction._call\u001b[1;34m(self, *args, **kwds)\u001b[0m\n\u001b[0;32m    944\u001b[0m   \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_lock\u001b[39m.\u001b[39mrelease()\n\u001b[0;32m    945\u001b[0m   \u001b[39m# In this case we have created variables on the first call, so we run the\u001b[39;00m\n\u001b[0;32m    946\u001b[0m   \u001b[39m# defunned version which is guaranteed to never create variables.\u001b[39;00m\n\u001b[1;32m--> 947\u001b[0m   \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_stateless_fn(\u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwds)  \u001b[39m# pylint: disable=not-callable\u001b[39;00m\n\u001b[0;32m    948\u001b[0m \u001b[39melif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_stateful_fn \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[0;32m    949\u001b[0m   \u001b[39m# Release the lock early so that multiple threads can perform the call\u001b[39;00m\n\u001b[0;32m    950\u001b[0m   \u001b[39m# in parallel.\u001b[39;00m\n\u001b[0;32m    951\u001b[0m   \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_lock\u001b[39m.\u001b[39mrelease()\n",
      "File \u001b[1;32mc:\\Users\\amine\\OneDrive\\Documents\\PFA\\.venv\\lib\\site-packages\\tensorflow\\python\\eager\\function.py:2496\u001b[0m, in \u001b[0;36mFunction.__call__\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m   2493\u001b[0m \u001b[39mwith\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_lock:\n\u001b[0;32m   2494\u001b[0m   (graph_function,\n\u001b[0;32m   2495\u001b[0m    filtered_flat_args) \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_maybe_define_function(args, kwargs)\n\u001b[1;32m-> 2496\u001b[0m \u001b[39mreturn\u001b[39;00m graph_function\u001b[39m.\u001b[39;49m_call_flat(\n\u001b[0;32m   2497\u001b[0m     filtered_flat_args, captured_inputs\u001b[39m=\u001b[39;49mgraph_function\u001b[39m.\u001b[39;49mcaptured_inputs)\n",
      "File \u001b[1;32mc:\\Users\\amine\\OneDrive\\Documents\\PFA\\.venv\\lib\\site-packages\\tensorflow\\python\\eager\\function.py:1862\u001b[0m, in \u001b[0;36mConcreteFunction._call_flat\u001b[1;34m(self, args, captured_inputs, cancellation_manager)\u001b[0m\n\u001b[0;32m   1858\u001b[0m possible_gradient_type \u001b[39m=\u001b[39m gradients_util\u001b[39m.\u001b[39mPossibleTapeGradientTypes(args)\n\u001b[0;32m   1859\u001b[0m \u001b[39mif\u001b[39;00m (possible_gradient_type \u001b[39m==\u001b[39m gradients_util\u001b[39m.\u001b[39mPOSSIBLE_GRADIENT_TYPES_NONE\n\u001b[0;32m   1860\u001b[0m     \u001b[39mand\u001b[39;00m executing_eagerly):\n\u001b[0;32m   1861\u001b[0m   \u001b[39m# No tape is watching; skip to running the function.\u001b[39;00m\n\u001b[1;32m-> 1862\u001b[0m   \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_build_call_outputs(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_inference_function\u001b[39m.\u001b[39;49mcall(\n\u001b[0;32m   1863\u001b[0m       ctx, args, cancellation_manager\u001b[39m=\u001b[39;49mcancellation_manager))\n\u001b[0;32m   1864\u001b[0m forward_backward \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_select_forward_and_backward_functions(\n\u001b[0;32m   1865\u001b[0m     args,\n\u001b[0;32m   1866\u001b[0m     possible_gradient_type,\n\u001b[0;32m   1867\u001b[0m     executing_eagerly)\n\u001b[0;32m   1868\u001b[0m forward_function, args_with_tangents \u001b[39m=\u001b[39m forward_backward\u001b[39m.\u001b[39mforward()\n",
      "File \u001b[1;32mc:\\Users\\amine\\OneDrive\\Documents\\PFA\\.venv\\lib\\site-packages\\tensorflow\\python\\eager\\function.py:499\u001b[0m, in \u001b[0;36m_EagerDefinedFunction.call\u001b[1;34m(self, ctx, args, cancellation_manager)\u001b[0m\n\u001b[0;32m    497\u001b[0m \u001b[39mwith\u001b[39;00m _InterpolateFunctionError(\u001b[39mself\u001b[39m):\n\u001b[0;32m    498\u001b[0m   \u001b[39mif\u001b[39;00m cancellation_manager \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m--> 499\u001b[0m     outputs \u001b[39m=\u001b[39m execute\u001b[39m.\u001b[39;49mexecute(\n\u001b[0;32m    500\u001b[0m         \u001b[39mstr\u001b[39;49m(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49msignature\u001b[39m.\u001b[39;49mname),\n\u001b[0;32m    501\u001b[0m         num_outputs\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_num_outputs,\n\u001b[0;32m    502\u001b[0m         inputs\u001b[39m=\u001b[39;49margs,\n\u001b[0;32m    503\u001b[0m         attrs\u001b[39m=\u001b[39;49mattrs,\n\u001b[0;32m    504\u001b[0m         ctx\u001b[39m=\u001b[39;49mctx)\n\u001b[0;32m    505\u001b[0m   \u001b[39melse\u001b[39;00m:\n\u001b[0;32m    506\u001b[0m     outputs \u001b[39m=\u001b[39m execute\u001b[39m.\u001b[39mexecute_with_cancellation(\n\u001b[0;32m    507\u001b[0m         \u001b[39mstr\u001b[39m(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39msignature\u001b[39m.\u001b[39mname),\n\u001b[0;32m    508\u001b[0m         num_outputs\u001b[39m=\u001b[39m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_num_outputs,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    511\u001b[0m         ctx\u001b[39m=\u001b[39mctx,\n\u001b[0;32m    512\u001b[0m         cancellation_manager\u001b[39m=\u001b[39mcancellation_manager)\n",
      "File \u001b[1;32mc:\\Users\\amine\\OneDrive\\Documents\\PFA\\.venv\\lib\\site-packages\\tensorflow\\python\\eager\\execute.py:54\u001b[0m, in \u001b[0;36mquick_execute\u001b[1;34m(op_name, num_outputs, inputs, attrs, ctx, name)\u001b[0m\n\u001b[0;32m     52\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m     53\u001b[0m   ctx\u001b[39m.\u001b[39mensure_initialized()\n\u001b[1;32m---> 54\u001b[0m   tensors \u001b[39m=\u001b[39m pywrap_tfe\u001b[39m.\u001b[39;49mTFE_Py_Execute(ctx\u001b[39m.\u001b[39;49m_handle, device_name, op_name,\n\u001b[0;32m     55\u001b[0m                                       inputs, attrs, num_outputs)\n\u001b[0;32m     56\u001b[0m \u001b[39mexcept\u001b[39;00m core\u001b[39m.\u001b[39m_NotOkStatusException \u001b[39mas\u001b[39;00m e:\n\u001b[0;32m     57\u001b[0m   \u001b[39mif\u001b[39;00m name \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "PT_path = 'Model/TCN-test'\n",
    "f1 = EarlyStopping(monitor='recall', mode='max', verbose=1, patience=30)\n",
    "f2 = ModelCheckpoint(filepath=PT_path, monitor='recall',\n",
    "                     mode='max', verbose=0, save_best_only=True)\n",
    "\n",
    "\n",
    "model = Sequential()\n",
    "model.add(InputLayer(input_shape=(trainX.shape[1], trainX.shape[2])))\n",
    "model.add(TCN(nb_filters=100, kernel_size=3, dilations=[27,36], \n",
    "              padding='causal', return_sequences=False))\n",
    "# model.add(LSTM(100, return_sequences=False))\n",
    "model.add(Dense((n_forecast), activation='sigmoid'\n",
    "                ))\n",
    "model.summary()\n",
    "\n",
    "\n",
    "# fit the model\n",
    "model.compile(optimizer='adam',\n",
    "              metrics=['Recall', 'Precision', \"AUC\"],\n",
    "              loss=CustomLoss\n",
    "              # loss='BinaryCrossentropy'\n",
    "              )\n",
    "# fit the model\n",
    "history = model.fit(trainX, trainY, epochs=150, batch_size=500,\n",
    "                    # validation_data=(validX,validY),\n",
    "                    validation_split=0.2,\n",
    "                    verbose=1,\n",
    "                    callbacks=[\n",
    "                        #  f1,\n",
    "                        # f2\n",
    "                    ]\n",
    "                    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x13b124e5c90>"
      ]
     },
     "execution_count": 178,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1600x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plt.plot(history.history['loss'], label='Training loss')\n",
    "plt.plot(history.history['val_loss'], label='Validation loss')\n",
    "plt.legend()\n",
    "plt.show();\n",
    "plt.plot(history.history['auc'], label='AUC')\n",
    "plt.plot(history.history['recall'], label='recall')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# best_model=tf.keras.models.clone_model(model)\n",
    "# best_model.load_weights(PT_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12/12 [==============================] - 0s 7ms/step\n",
      "3/3 [==============================] - 0s 7ms/step\n",
      "8/8 [==============================] - 0s 6ms/step\n"
     ]
    }
   ],
   "source": [
    "prediction_train=model.predict(trainX)\n",
    "prediction_valid=model.predict(validX)\n",
    "prediction=model.predict(testX)\n",
    "trainResults= pd.DataFrame()\n",
    "validResults = pd.DataFrame()\n",
    "testResults = pd.DataFrame()\n",
    "min_length_train = min(len(df_for_training), len(prediction_train))\n",
    "trainResults['Actual']=df_for_training.iloc[-min_length_train:,-2]\n",
    "trainResults['Pred']=prediction_train[-min_length_train:]\n",
    "min_length_valid = min(len(df_for_validating), len(prediction_valid))\n",
    "validResults['Actual']=df_for_validating.iloc[-min_length_valid:, -2]\n",
    "validResults[\"Pred\"]=prediction_valid[-min_length_valid:]\n",
    "min_length_test = min(len(df_for_testing), len(prediction))\n",
    "testResults['Actual']=df_for_testing.iloc[-min_length_test:,-2]\n",
    "testResults['Pred']=prediction[-min_length_test:]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<Figure size 3000x900 with 1 Axes>, <Axes: >)"
      ]
     },
     "execution_count": 181,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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bkdME3DBYHjsyZ47WvWzfpuX/bQXcTs/mtVjw/mOAux4+oamM93nJ3QPa4tbIHxwQcAMAAAAgSU+eyJjTO7yuLwFBQsANaIE9opQfqfUqFAppYsS9UWeSgBsQaI3+Nf9UlxvcHMfRgWMZz8ccPHm20cD6BWQsHdfQ06G287aP6kO/foX+P6+5UG+7cp/+269docsv2OzfotEVoVBIG40Wt24cc7J5GtxaYY0olaQF48Kvl8lMQX/7jad0ZDKvUtnRwVOL+r+/8aRmXMZzWQG37RuTLZ+/npzN122OAwA0rlp1dNT4S+olBNzQb6zxpIlYRBfvGV++vdsIuEnewc9q1dE/32W3ty354cMnB+68pfr/snfW8W2d59u/jtCWbMu2zMxJHCdxmKmQUtqU167t1m3d1m2/jveOeeugW9etW1dYmdKkaRiaNMyJmZlJtiRLshjOef9Q7NjWeQSm2Mnz/Xw6z8LjSDp6nvu+7utiOaj8ELjRiFIKhUKhUCgUCoUCAE1eDBVU/bTeQJkZUDUOhTIG7HZ+lw0JdXC7oSFFxlEHNwpleuOvg9tUR5Sq9VYYTN7PH609wwRuhL8jLlI24vfIsCBsXJiITUuTEa+Uj/9AKdcEkqh6siNKOY6DycIvxqICN++EeBG4jSWm9EJ1P1zsyEatw8mhsF7ncVu9if/xY8KlWJoTwXvdIKTjttrZSXGGo1AolBsVVb/Zp6Nnn47GQ1NmDhzHobhOzXtdXkYkxKKrNTSlImhoKGc0bSqywO1yTa9fjZgerXnEcND1gGbADqfLt2hPrbfB6RqbWzCFQqFQKBQKhUK5fmjyYqjQP2CD1R54jZpCmWqowI1CGQMkB7cgCRW43cgQBW6TLDagUCjjw1/rZc0UR5Q2epmmGWSkgxu/40ecUsZ7OWVmE3WNRNUWmxMswf2CCty8EywRQESIlh0giAa90drLf+7qVHueq3QEIVq4XISVcyJBCikWixg8eWsK8Ri6aUwphUKhTBidfd7d2wDq4EaZWbT3Goku2MPjSQG3Q3FyNP/wTXsvv8CN5TjsO9/i9/FcqLy+Ykp7tP7tT1mODl5SKBQKhUKhUCg3Ov4kBvVSFzfKDIAK3CiUMWAlRpRSgduNDMlNhxYSKZTpi8XmhN6HS9ogasPUCjkaO71vNgD/IkpHO7hRrg9IEaWagcl11DJayI8vpwI3rzAMQ3RDC1Tg5mI5dBOamn16z3OVgSBwU8jFUIZJMCcllPf6zcvikBQVjHA5/2vb40csFoVCoVD8gyTiGY7GYKVOTJQZQ0k9v3ubgGEwPzPK4/LkWP71COmzUVKv9ksYOsjFahVY9vqJKfUnnnSQXhpTSqFQKBQKhUKh3ND06a1ea/uA/2YQFMq1hArcKJQxYCcI3GhE6Y0NycHNZHXBaud/z1AolGtLIAt2rcEKjuBcNRk0dPl2cNMb7dAZbbA5XNAQBHhU4HZ9QhJVGy1OotPsRGD0IsQKCSJHcFLchJIEbgFGlLqjpvjPR9oB+4joUpbjoCc8vuKKcO2+VfEIk408tpVzIrFslju+NC5Synv/nn7aLKVQKJSJoqPPt8CN40B0xKJQphvFBIFbTrKC1/k3OSaE9/adfUYPYRrHcdh7riWg49Eb7ahp6w/oPtMZfx3cAEBFBW4UCoVCoVAoFMoNTZMfiUEqKnCjzACowI1CGQM2gliJOrjd2JDi4gAaU0qhTFcCEbg5nCwGzJPrjjWIzeFChx8uHgDQ2jPgdeNBBW7XJyRRNQBoDJP3PiVNeQkYBsFSKnDzBUng5k04yEenhtzQZDmgf9i6w2RxjhC8DWdQ4BYqE+M792bi7uVx2Dg/Cl+4JQVbVsaDYdzhpXERQbz3pw5uFAqFMnH4I3ADaEwpZWagNVhHuE0PJz87mvdyksDN7mSh6h+536lo1qK1h//x8zIiIRLyl7wvVF0/MaXd1MGNQqFQKBQKhUKh+EmTj3hSAOjR0noDZfpDBW4UyhggOaMESajA7UYmTCaGUMDwXkdjSimU6UmPJrCJlKlyzGjpNhAFKaNpVQ0QhXpCAYOocH5hCmVmo5B7+c6ZRFG1iSBwkweLhsRQFDKhMn6BmyFggZv3YoN62LqD5N4GXBW4AYA8SITVc5W4bUksckdFlsZF8Du49elsNCqPQqFQJgCLzYk+nX/rTH9vR6FcS0jubQCwMNsznhQAEqPkEBDWk8NjSn25tz24PhP5WUre6wpre+FwznyHfaeLRV8AojXq4EahUCiUsWK2OtDB46ZKoVAolJlFox8Ct9GDRRTKdIQK3CiUMUASuNGI0hsbgYBBZKhnzAZABW4UynQl0AW7Rj81DUV/NhuDtPaQBW4xEcEQCuhy73pEKGAQEcL/naOdxO8ckoMbX8wUxROSg1tLjzmgaNkuLw5uANCnv9rE1Bn5XzOhgIE8yL+1K8nBjeUAtZ6ucSgUCmW8dKpNft+WOrhRZgIl9X28lydFhyA6PJj3OolYiDglv/v0cIFbXbsODR388Tr5WVFIiQ3FirlxvNdbbC6UNmi8HfqMoEdjRiA6A7Xe7vcAFYVCoVAoAOBiWXxwpA7PvHAav3r9Er774hlUtWiv9WFRKBQKZQw4nCzae/kdsIfTozGD4+i+gTK9oR1PCmUMkBqQNKKUQoqMowI3CmV6Ml0d3Bo7+Rs2fLR5cXCj8aTXN9fiO8dkJTm4UYGbP8SE8zuhWewuXKzp9+sxWI7zKXAbLjrTE6KVFXIR0SVlNFEKCdExkMaUUigUyvjxN54UoAI3yvRAa7Dif/uq8OOXz+GP7xSgoKZ36Dqz1YGaNh3v/UjubYOQYkrbVO7PCMdx2H2mmXj/u1alAgDmZSghk/IPFly8DmJKAxHFAoCL5WhdikKhUCgBcbq0G58VdmBQ5mC0OPCvj8uIdSEKhUKhTF/aVANwunwL18w2J3HAnUKZLlCBG4UyBmx2gsCNRpTe8BDFBpMYF0ehUMYGy3HoCdTBbQoEbhzHBSRw0xhsRAcDKnC7vokM5f/OUU/idw7RwS2ICtz8IScxBEES/i3YmUqNX3Gf2gE7bA7vt+sbHlFqIgnc/H/NREIBohX877eefhp5RaFQKOOlozcAgVs/FbhRri12hwsvbC/FuYoe9OmsaOwy4KVdFfjfvipY7U6UNWmIbmELc7wL3FIIArdBt4HC2j6ieG5uWgQyExQAALFIgCWzo3lvV9qohnmGN+dJolhlqASk+YVeGlNKoVAolAA4XdbtcZndyeLyMFE7hUKhUGYGTQEkBqm0tOZAmd5QgRuFMgZITUXq4EaJIogN6KQshTL90A3YYCeczxOj5byXT1REaZfahNOlXShpUHsIWvr0VhgIjksk1ITjogK36xuSqJpGlE5fgiRCrJwdyXudwexEUYPO52N0qX2fh9TDIkr1JifvbQIRuAHkmNJuLXVwo1AolPESkMBNb6GRIZRryumybnT0eTqInavowe/fLsCJok7e+0WESpEaG+r1sUkObjqjHRq9FR8dqyfed/OqtBG/r8jljyl1ujgU1vJHqM4UOnn+/QEgMSoISkJdSkUFbhQKhULxExfLjogHHw7pcgqFQqFMXxq7/DdUIKUFUSjTBSpwo1ACxMWyRHcNqZh+pG50lGH80WMGsxN2p29XFgqFMnV4W6jPTeMXoEyEg9vRwg786vVLePNgDf71cRl+/3bBCNFQkxf3NlLMDok4JRW4Xc+Qmld6k8MvJ7CxYCII3OTBgb03b2RWz1VCJOS31jhZrgFLcDwZpMsPQZnB7ITN4XYcJjq4yQIVuPGvcaiDG4VCoYwPjuN4xUIkLDYXTFZ+8TKFMtmwHIfPCtqJ13drzKgjuEvnZ0eB8RGPThK4AcBreyuhMfCvO2anhCMnOXzEZTkp4YgI5V+/XJjhMaWdBAe32IggxITz/83UwY1CoVAo/tKjMRPrSiSRNYVCoVCmLwE5uAWYekShTDVUjUOhBIjNTm4Y04hSSmQYuVmspTGlFMq0giRwC5OJkRTN31jREhoq/qI1uF0H2GGuG+29Rrx5oHro98ZO/s1GQpQcWUmKgJ6POrhd35Ac3DgA2oGroqYWlQmvH2rGT14+j5d2lkM7DqGm0cLfUKcObv4TEizC0pwI3us0BjsqWrwXHDo1/tnEq684+ekIArdweYCC2Uh+Bze9yQGLzRXQY1EoFArlKv0DNphtgQnW+nQ0MoRybaho0kA1xpjchdne40kBQBEiRZicf41LEs4xDPDoLTke4jkBw2D5nFje+9S09kOtn5mfI5vDhV7CaxAbLkUsQeCm6qeuuxQKhULxjzYvLm1dahN1E6ZQKJQZhMFkJyYA8UEd3CjTHSpwo1ACZNANgw8aUUqJCJFAQBhIpjGlFMr0okfDv1CPjZRBqeAXchgtDtjsYxdyFNT0wunyLAIV16tR0awBADQQ7KIzE8KQ4iPSZzjyIBFCZfzNIcr1QWSoGCQPjMHvnJ5+K1470IzqtgH0aM24VN2L37x5ecwbVVJEqZwK3AJibZ6SuF44XqYmFos5jkOXxr+ChFpvB8txMJAc3EImxsENoA1TCoVCGQ/eYp6EhC8LKnCjXCuOFHSM6X7BUiFmp/AL/EfjzcWNj5sWJhHvs2Iuv8CNA/CX94vR3O2/k8F0oVtjAklWEBchRQxhzaY22OHy4RRMoVAoFArgfX1qtDhgMNE+B4VCocwUAnFvAwAVFbhRpjlU4EahBIidCtwoXhAKGESE8AtKqMCNQple9BCsluO8CNwAQD0O96vadh3xug+O1MNsdaKDUETKTFQgNQCBG40nvf4RCQVQyPlFSporrqH7LvbA5hjpPmu0OPDC9lIMmAP/XjJa+cVSIUFU4BYIkaESLMjgd2Ts1lpR18l/HtCbnDBZ/RPZqg02GC1OkPqYgUaUKuRiBEn4t480ppRCoVDGTgchalAZJkUswY2XCtwoY8XhZNHRa0S3JvB4sS61CZXN2jE977wMJURC/8rQgQjcQoLFuHddutfHiifsizQGK/70XhFOlXb5/XzTAVI0nEjIIDJUQowodbo49NNkAQqFQqH4QbtqwOv1HWoaU0qhUCgzhaZufkMFEqp+y4gEIgplukEFbhRKgFi9OPfQiFIKQI6MowI3CmV6QXJwi1PKEBkqJTpjjTXekeM41BNidQC39fPr+6uIU/WZiQqkxvnf7KHxpDcG3r5zWlVmNHTxFx17+y14cUc5HE7/HQmdLpboYEgjSgNnw3xyTNeJMjXv5V1a/wUNar0dehM58o4kjiTBMAziIvjFvz3UwY1CoVDGTAdBrJIYHYJowtAFKZ6QQvFGc7cBv3r9In71xiX8/LWL+PN7hTAThhf4+KxwbO5tALAwO9rv26YEIHB7cEMm5F4GLRiGwcq5ccTrnS4Wbx2swVsHqwNaF19LSKLY2HApBAIGMQryXlalo0MJFAqFQvGNNwc3AOgirF8pFAqFMv1o7OR3cIsO5683OJws+g1030CZvlCBG4USIDSilOILKnCjUKY/DqcLGj2/ICMuUuZ2xiK5MRLu54sujZkY7zhIcT2/qEUmFSFeKYMyLMhvIREVuN0YKEP536faATuOlvR5vW9Dpx7/21ft90SWycv7lwrcAic2Igi5KfyujM09ZrSqPEW4nWr/zz99ejv0hHhSkZCBPCjwdSspppQ6uFEoFMrYIbn3JseEIDo8mPc66uBGCZTmbgOe+7AYqmHiyLoOPV7ZU0WMRh+OyerAuYpu3utS40Lx+VuyIRLyy6pEQgbzMpR+H6u/Dm7p8aFYMz/e5+02LkpERCg5ah0ATpV249n3ilDVoiXu2ViOQ5fahLPl3XjvcC3+t68KRws7vCY9TAYkB7dB5zaxSIBIwh6hlwrcKBQKheIDvdEGg9l7/bJT7V0AR6FQKJTpActyaO7mF7h5GwQipR9RKNMB0bU+AAplpkEqXAkFjN9xC5TrG5LATU2jICiUaUNvvwWkNs6gMEypCILO6Pm51YzRwa3OSzypLzISwiBg3A2j1NgQVLb0+7xPXKR8zM9HmTmQvnOae8ywO1ne64ZzuaYX0eHBeHBDps/behNoyqnAbUxsmB+Fqjb+6I/jZX148tbUEZd1afw//6gNNugIAjeFTAyGIXl7kPHm4MZx3Jgek0KhUG5kHE4WPVr+wnFSdAgMhDjxPh11zqT4T2u3AX/fWsybSFDepEFpgwb52WRnWQA4VdoFu4N/bblpSTJW5sUhK0mB/+6q8Hh/3r48BbIg/0vQcUr3wJHT5X0t+/lbc4b2SN6QB4nx488vxL8/KSc6JgJAa88A/ra1BAAQESpFckwIkmNCwDBAU5cBzd0DsNhGuuOeq+hBSYMa33lw/pTVBEkObsPXaTHhUmh4alDUwY1CoVAovmjz4d4GAJ00opRCoVBmBN0aEzGZbm56JE6WdEFv4tk3aM2YmxY52YdHoYwJqsahUAKE5OBG3dsog5DcdPQmh88CLYVCmRpIjUQBwww5ZSjD+IUcYxW41Y9D4JaZqBj6/ylx/I5Po4lTUge3G4FIgsDNH3HbIAcutOJkSafP23kTuIUE07mZsZASI0NGPL8YtabdiB7tyPNNp8Z/xx6rnUUX4fYK+dheL5KDm9XOEt3iKBQKhUKmW2MixtMnRcuJDm7aASvdW1L8oqvPiF+8cg4mKzm2/KNj9V7fTy6WxVFCPKlCLsHSOTEAgLS4MPz6yWW4Y0UKIsOkiIkIxgPrM3DP6vSAjlkoECAx2vuwzpp58chMUHi9zXBiImT4+RNLsGJurF+37x+woaxRg/3nW7HvXCuqWvo9xG2DVDZrcaLY91p6IrDYnNAS4oJih63TBt3cRkMd3CgUCoXiC1/xpIDbTdQfB1gK5XrB4WSh0pqn3LmXQhkvTV387m1CAYPU2FDEElKASP0zCmU6QDtRFEqAkJTOUgkVuFHckNx0OA7oNzoQrfAejUGhUCYf0gI9OjxoaPKeKHAbQ0Qpx3GoHZfALWzo/6fG+ha4MQwQQ2iIUq4vSKLqQHn30zooFUHISyfHRxkt/E09iVgAsYiug8bKxvlRaOrmn34+UabGIxuSALj//Q1mcnOaj4Yu/sdVyMfmuBdLcHAD3DGl4YRoZwqFQqHwQ3JiEgkZd6GZ4E7Fce6hi9gIOtBAIdOrNePnL5+DbsC7qEnVb8FnBR24fXkK7/XFdWqiqGrjwsQRzmWyIBEe2pCFhzZkjf3A4Y4pbe3hd7kNlorwgB/uw6ORSoT46uZcZCYosPVoPVFcOhZ2n2nGyrw4yIM811gcx+FYUSfKmzQAgA0LE5Gf5d0xj4Q3x5zhgwixhKGEXp0NLMtBIKCuuxQKhULhp03F//07HKvdBa3BBqWCXCOgUK4XLlWr8N7hOhgtDkhEAqyaF48tq9OgCKF9Psr0p5EgcEuKCYFELERsRDBv8pBK6/+QNYUy1VAHNwolQEgKfQl1cKNcISJEDFKpUGOgMaUUynSgR8MvcBs+sUIq0ozFwU2jt6LfR2OJBAMgI/6qO0GqHw5u0YpgiEV0mXcjoAwLTKgkJDSzWI7DSzsroOonT2eZrPwOXSE0nnRcZCXIkajkP9+UNuuH1g7e4klFQv7XlSSIG6vALVgqJN53tNschUKhUHxDiktMUMohEgoQ5aVp2KejBWcKGa3Bil+8cg5qP98ne881w8ATTQMARwraeS8XCRmsX5g45mP0RnJMCPG6e9ekQyEfm6ieYRjcvDgJP/78ogkV5pusTuw92+JxOcdxeGN/Nd4/UoeyRg3KGjX418dluFzTO6bn6SSIYqViwYg1GsnBzeni0G+krrsUCoVCIeOPgxtAY0opNwYdfUb8b1/VUKqF3cniRHEnfvLKBew+0wyrPbBBVAplqiE5uGUkuA0V4ggObirq4EaZxtDOJ4USIN2Ek7pUTD9OFDdikYDY/FVTgRuFMi3oIYh4hi/oIwkObv0DNrjYwCKhxuPelhAlhyzoquludHgwgqXeRdU0nvTGQSoW+h0Pmh4fhmcenE8yg4HV7sK2Yw3E+5MiSkN4nCoo/sMwDDbM53fx4DjgVIUaADmeNEwmQrwXZzU+xipwA8gxpT39NPJqIunsM+Kf20vx45fP4a8fFKGlh78gRaFQZjYdhAZiYrRb3CMVC6EgiHD6+qnAjcLPgNmOX75yDt0BNJ4tNhd2nm7yuLy1ZwD1HXre+yyfEztmoZkv5mXwuwonRstx0+Lxi+qykhT49ZeWYVZy+Lgfa5CjhR0ejaCjhR04W9Hjcdt3DtWMKeKqkyCKjQ2Xghm2yI/xkhygojGlFAqFQiFgd7j8jqXrVPsnhKNQZjIHL7TB6fJ0/bU5XNh9phk/eeUCThR3BtwroFx/NHcb8Py2Evz01Qt4cUcZujXXXgRstTuJ5+rMKwI3UkRpn94Cp4u+rynTE6rIoVACwOF04UKlive6KAWNgqNchRRTWts+AI6buBgMCoUyNkgObsOFYVEEgRvHIWA3Nj6bZ8DdoFmY7T2eZng8KQAIGAYpMd5d3Ghc1Y2FMtQ/sdKWNenIz4rC52/JId6muF5NnMIlCdzk1MFt3MxNDUMUYe1QWK/DgNlBdHBLUAYhShFYc3k8Arf4SP5zY08/dXCbKExWB577sBiljRr06ayoadPh2XeLxhSRTaFQpjftBDem4e5VpNj5Ph09J1A8GTDb8betJWgjxHt641Rpl0csGcm9DQBuWZIc8HP4S1ykDBtGucPJg0T46uZcCAUTU85WyCX44aP5+Po9czE3LWLcrsQulsP2E41Dvzd1GfARYXjEZHXiYhV/fdEbpHX66EhSiViAiBD+v6eXnjsoFAqFQqBTbYK/rYsuguiaQrleMJjsuFzjfb1mMNnxzqe1+NXrl1DZop2iI6N4w+liYbFNrbOeWmfBcx8Wo6JJC5XWjOJ6Nf7yfhHMhDSUqaKle4B4Ts9IcCcGkQRuHDfSNd7hZPHppTb86b1C/O9gMypbDbTXTblm+Gf3QKFQAACFdX3E5u6CLP7pUsqNSZRCgsZuz01efZcJ5c0GzM9Q8NyLQqFMBQNmO0xW/k1OXITviFLAHTkaiLC5juB6kJMcjtuXpaC8SUuciMlM8DxfpMaFenWFow5uNxbKMAlae727uCRGBQ+tVW5enIQ+nQWHL/M3LA9eaMVTm3M9Lic6uFGB27gRCBisnx+FHWe6PK5zujicqdR6EbgFQxhgnzdcPvZtIMnBrU9vh4vliDG4FP85fKkdBvPIz5vTxeLgxVY8vmnWNToqCoUy0QyY7dAb+R2+k6LlQ/8/OjyY10GLRpRSRqMz2vD3rSVeI8MyE8IwJy0S+861eFzHccDWo/X40aML3euPsi5cquZv6uUkKZAa533oZrw8sSkHOckK1LTqECaXYPW8uAkf5BEKBFieG4vlubHgOA46ox3tvUa09w6gvdeILrUZHDjEK+XIiA9DRkIY4pUy/ObNy7xDT0V1fahp7UdSTAj+u6sCLpbc9Dla2IE18+NHOK/5gixw89y7xkZIeeNIe6mDG4VCoVAI+BtPCgAdNKKUcp1zuqyL172Nj26NGc9vLcEX75iNdQsSJvnIKHzY7C5sO9GAE0Wd4ADkZUTii7fN9trjmSh2nWmG1T7SndlgduDw5XbcuzZj0p+fRGMXf09KHiRCbIS7txUTHgwGAN87vUdrRrzSXZt473AtTpd1D11X0z6Axdnh2LIyHhIR9dOiTC1U4EahBMCpEs+mIwAES4VYNjt2io+GMp2ZkxyKizX9vNftvdiDnKQQBEm8RwxSKJTJQaUlNwOHC8OCpSIES0W8Ez9ag/9NAb3R5hFVM0hOUjiiw4Nxx/IU7OVpMgFAZiKPwC3WezMpjjB5Q7k+IbmGDufWRTEjmmcP35SF6tZ+3uLlxSoV7l2b7iHiNFGB26SyMFOBz4p7oTd5nnPOV2thd/KLYBOVQXD5WXAbZHwRpfyFIRfLoU9vI15P8Z+iuj7ey6ta+NeWFAplZtLhxfUiaZiDWzTRwW3kmrZNNYALVSqIhAwWZEXxDklQrl+0Biue+7AYKi/RtSkxIfjuwwsgEQlxsaqH1wWwpk2H9w7XobRR7XXPM5nubYMwDIMVuXFYkRs36c81+HwRoVJEhEoxP9P7EOv96zLw+v5q3uu2HqtHRIgUGoN3p7S2XiPqO/TI8TMm1WC2w2DiF8XyDSDEhEtR0+651lfRWHkKhUKhEBjt5OqNbrUJLMdBEIBQm0LxBcdxaO81gmEYxEXKIB6HcKa6RYvqtn7IpGIsz41FRCg5wn00LpbF8eLOgJ6PA/D2oRqEysRYmB0d4NFSxsu+8y04XnT1Nato0uLlPRX46WOLIZjEYVyLzYmC2l7e64rr1ddU4NbUZeC9PD0hbKhPIBYJoFQEQc2TGjHYR2vqMowQtw1SWK9Dp9qCx29ORlSY/58vCmW8UIEbZUbTozXDYLIjKVoOWdDkNldV/WbUtOl4r1uRGwcpFStRhpGTFILk6GC093kWlwcsThwqUOHeVXSSg0KZCvRGG9r7jFBpLejRmtHYyT+5EiQRQiEfKRRShgWhgyc6Su2jWTEcPseNQQabGXeuTMW5im5oRjWRUuNCEc/jxubLLYEK3G4slKHeBW4JyiDMTfWMur1zRSpe2VPpcXsXy+HTi+14bNPIKFOSwI1GlE4MIqEAa/OisO9ij8d1JHEb4H59LTYX8XrP52Egk4593RqlkEDAAHyGJD1aKxW4jZPefjPRnaVHa4beZPf4rppKbA4Ximr7YHO4MD9TiUhCnDeFQvFNB8EhIyRYPOJzHh3O/znr01vAcRwYhkFZoxr//LhsKH7k4IU2fOG2WVhL3QNuCHr7zXjuwxKvgqp4pQzffyQf8iu1s4c3ZuM/O8t5b+urmacMC8LCnKixH/B1wMq8OHxW2IFWnijYNpURbSr/HHCOFnb4LXAj7WMBfge3mHD+JlNPvw3vH2tHmFyEMJkYCpkIKTEyRPrYU1AoFArl+icQBze7k4VaZ0HMBLurUm5c6tp1eOfTWnRdqYlIRAJkJ4djTmoE5qRGIDU21G+h0q7TTdhztmXo90OX2vCjR/KRGB1CvtMwShs0AQ24D8JxwMu7K/GjRxYiK4kOHE0VDieLIwWeSSWNnQZUNGswP3Py9i4FNb2wO/jrtu29Rqj1loCSgCaKjl4jcVB29DBcXKSMV+DWc8W04WghfwoM4N5bvLi7CQ+tTUReWhjxdhTKREIFbpQZCctyeH1/Fc5XuqMSgqVCPLFpFlbMnbypzlOl/O5tAKjlLMUDAcPg/tUJeHF3I28D+GJNPxZlhSMlhm4AKZTJwmx14s2D1Sis5XfCGU1spMwjHiZKwS9w0/As+EmQokSjw4OGJsekYiG+89AC/PWD4qEYyPAQCb5w2yzeyJq4SBkkYgHv5kkqESI8hDYnbiR8ObjdsjCW9320ZHY0dp4KRi9PxNmpsi7cvToNYVca7C6W9RBgDkId3CaOZTkROFbSB7OfgjWZVIhwuTggwVq4XBxQFNZoREIBosOlvO4fF2r6YbGziI2QIjZcCnkQ3W4GSnG92uv19e06LJkdM0VHMxK3gKJ46FwgEgrw1OY5WDaHOllTKGOBb40JuONJh5+nSQ5uFpsLJqsTQgGD1/ZWDYnbALdY/Z1Pa5EQJed1Ax58/g8/q0eX2oTo8GDcty4Dc1Ijxv4HUa4J3RoTnvuwGDpC3C0AxCvl+NGj+QiTXV0zLsqJwuyUcOIgpzduXpwEoeDGjqERMAweuSkLf/mgeFyPU1TXh/4Bm09HEaPFgfeP1PFeJ5MKERLkuRaMJQjcXCyH8hZPN4e1eUrcsTSWOvFQKBTKDQp7xTkrEDr7TFTgRhk3LpbFnjMt2He+ZcSexu5kUdmsRWWzFgAgk4owKyUc6/MTMC9DSaxt9WjN2HeudcRlBpMd/91diV8/uQRike8a2tHCDt7LRUIBNi5MxPHiTjhd/KImh5PFPz8uxU8fX4yEKLnP56KMn8ZOPVFkdrKka1IFbmfLPZ3NhlPaoMHNi5Mm7fn50Bqs+Mf2Utgc/PXljISRQrTYSBkqrnzOhqPSmqE32nCpmt+hbhCbg8V7x9qxLk+J25bEQjiJjnkUCgDc2NUIyozl08ttQ+I2wF3YfeNADbo15IiP8eB0sTjLY78JuF10fDnpUG5M4iODsCaPP9aCA/DJ2S64+NRvFMoNTnuvEW8drMbftxZj2/GGoUmRQLDYnHh+W4nf4jYAiOdxPYskWCtrA3BwqyMI3EZP6idFh+C5b6zCt+6bh+88OB+/f2o50uP5p14EAgYpMfzfPXE8Qj3K9Y03t4XYcCny0vnfR0KBALevSOG9bvTk2/bjjURXECpimjgkYgFW5Ub6ffsEZRAYhoFULESYzL/XIWwc8aSDkFzaWlRm7D7fjVcPtOD3H9Tizx/V4URZHxxeHOgoIykmxJMOQhJNTwVbjzaMELo6XSzePlSLATNZVEGhUPhxuljUEoRFw+NJAbLADQB6+y04WtgBk9Uz3trFcnh5dwVMVk8H1rp2HX7/dgGqW/uhN9nR0KnHPz8unbSaykyB5TiUNqhx6GIbShrU4Ljpu1/XG224WKXCn98v8ipuS4oJwZ++tRoRoSO/uxmGwaO35CDQbUNilBw3LUocyyFfd8xKicDinPHFT7lYDid8OOZxHIe3DtYQXURSY/j3fyQHNxKnKzQ4eFnl83bT+XNBoVAolLGj1lthtfOLIUjrBZL7OGX643C6cKlahT1nmlHWqLlm3+99Ogv+/H4R9p4bKW7jw2xzorhejRe2l+GjYw3E212o7AHL82BdahN2nWn2eUxdahOqW/mdr5bNicGjt2TjT19bgZVeDFdMVndvon9gYqLhbXYX799EcVNFeL0At8Bsol6H0aj6zajzkt4DACX1/venJgKLzYkXtpcR/+ZgqRBZiZ4Obnz09JtxssT/PvapCg1eO9iCAYtnfYJCmUhoN4oy43C6WHx6ydMO0+liceBCK75yV+6EP2dJvRoGM38s13rq3kbxwi35MShrNkBn9Hz/9PTbcLZSg3XzbuxoDwplOKp+M/78fuFQ3F5lSz8+vdiGxbOicefKVKTF+bY5ttic+Me2UjR1eU6le2N0MxEAlAp+EYe3+J/hmK0OYvwUXxSNVCLE4ln+NUnS4kLRwBNTk0Qnw244ZFIhwkPEvN81N+VHe3VhWJ0Xj91nmqHnaYweK+rEnStSUdaoweHLZCvyOJ4YXcrYWZUbiVPlGq+xpIMkKq+eo6IUUhjMvgsI4fLxbwHjIqQo9eN2OpMDhwp6YTA7cc+K+HE/7/XOgNmOei/xYwBZND3ZGMx2lDZ4ustZbE5cqu6d8mlUyvWFi2VxuqwbXWoTIkODcPPiRL+m6r09ntPFQSISTFvR//GiTl4HVcA99DAchVwCiUjA+73Q0Wf0+h2tMdjwxv5q/N/984b+LVp7BvDPj0s9xMd2B4udp5vxzXvzAv1zrgtcLIsXd5SjrFEzdFl+VhT+74F508LRSq23oLZNh9p2HerbdVD1879/hpOeEIbffW0VwkOlUKs99yTJMSFYvyABJ0rIiQWDiIQM1i1IwP3rMiERj/3zeb3x4MZMlDSofTZ9pGIhZEEi3kbTyZJObF6VBrGIfw79eHEnirwI4EnDEVKxEJEhYmh59ggkTldoEBIswnqeOpXV7sKx0j4UNeghFDBIiwnG6rlKmkxAoVAoE4DN4cLRwg5UNmsRGynD+gUJU26q0K7yjN0GAAbArGR+11cqcJuZ2B0uPPtuIdqG1aw3LEzE45typnTde76iB+8eriUKK71x+HI7Vs6N4/2cFHpZNx262IZF2dFEl2vAvVcjMVj7UCqC8NW7cxEZJsX+8628t9UabHh+Wwl++tgiyILGNmxqtDjw5oFqlDVqIBIKsDIvDp+/JRsiIfUvGk51i6f72CAsx+FMWRfuXp0+4c97rrzH521q2nQwW52QBTAgXtmixeFL7TBbHchJDsfmVWkIlvq+v9PF4j87y4lu8QBw+7IUj8eKjeQfqtMb7ThaxO9mSKJFZcZrB1vwtTvSEBJMZUiUyYGeASkzjqK6PhhM/NOpFypVk6LEJsWTSsVCLM+lkTwUMhKxAPeuJDd0jxT3ot/LtDWFcqPxwZH6IXHbIByAgto+/O6tAvxtazGqWrTEqTKb3YV/bi/lFX55QyQUYDlPxJoyjCBw01v9mmyr79CDdCs+gVsgrJnPf25ZmTd5cd2U6QnDMFg527OxlR4nw7w076JQsUiA25byu7hZbE58+Fk93jxYTbx/ZkIY0WmQMjZkUhGWzfIvIi5BebUAEa3wL5pYIRu/g1uCkv/cSOJclRZqgusI5SqlDRqfE8sdvUZeN6bJprxRQ/w+u1Dpu6BHoZDQm+z4/VsFeOdQLT4r6MC24w34zZuXA3LLHYRlORy62IbvvXgW3/j7Sfz6jUuo9FLovlYMmO3YTXAOYADMTRv5nc4wDNHFbfeZ5qF4exLF9Wp8VuAuSqu0ZvxjW4nHenvotnV9MNygroyHL7WPELcBQEmDGmcIbv5ThcXmxIs7yvD//nser++vxpmybr/EbdnJ4fjjN1Yj3Ef05b3rMhDsJepcJGSwcVEi/vz1lXh806yAGjM3ArERMtyyxLfI+4u3z8Jty/jX3AazAwU1/LE/baoBbD1KdihZPjsS2Ymeg1qD5GeSm7ckDl5WobBeN+Ky9j4z/rWrEafKNTBanNCbHChtNuClfc34774mVLQYwNKEAgqFQhkTLpbFK7sr8fGJRlS39uNEcSf++mERWnv4BWeTBSmeNDoimCgG6uyjAreZyM7TTSPEbQBworgTJ/0YepgIrHYnXt1bidf2VY1J3DbI6TLP4+3WmLy+LzkO+N/+atgJ0Y0WmxNnK/jX/+nxoR410PvXZWD1PHItvrPPhH/tKIfDGfjfyXIcXtpZjuJ69zCFzeHCieJOvLqnkjrqDsNic6K52/v58lRp94SvVVmOwznCe2U4LpZDRbPG5+0GqWjW4IVtpShv0qCxy4CDF9vwh3cKoDd6r6sOuj5XtZDd7BZmR+GulWkel8d5iZoeIJj/eKNXZ8P/DrXAbJt8JzeO41DdNoCzlRo09ZjoZ+MGgQrcKDMOb9b9LpYbEac1Eah1lqGM99EsmxPjl2qacmMzOzmUKDBwODnsPt9Nv3QpFLgtySuavC/2q1r68betJfjd2wX4rKB9hKjZ5nDhnx+X+rSFHk2UIgjffnAer1sbSeBmd7I+m4kA2WlHESJBjJe4KX9IiQ3FF2+fBZHQPVknFDB4eGMW5qT6J4yhXF+snafEbYtjEB4ihkQkQH6mAk/cnAyBwPfk5fr8BGLM6Jnybtgd/E5iIcFifP2eudPC1eR6Y22eEkI/XrvhQrOoMD8FbiHjF7hlxssRGuAUXllTYK6aNyLFfsQWcHCLp6ea0aKP4TR2GdDbH3icOIWiN9rw1w+KPJor3RozXtheCjNP7CYJk9WBf35chm3HG4bWaB19Jjz/UQkOX26fVvutXaebiYXeFXPjeNekJIGbvwN+2443oKiuD3/bWkJ0pwfcNZXzFTeeaNVsdeLABX7nhaOFHdfs/cNyHP67uwLF9Z4Omt7ISQ7HH55ehVCZ77VBmEyCx2+d5XG5UMBg40K3sO2JTbMQSdgXUYC7V6UhJJi8vtqwMBEr5sZhzbx4SAnud58Vejoj2OwuvLy7Ek4X/1o8JlyKLau8p0psXBDtc+CFjx1nOlHTPgCW43CyXI3/7msmOsG19lrw3rF2/H1HA85VaYh7BwqFQqHwc6FShZJRbtkWmwtvHqgeUyShzmjDO5/W4tl3C/H2oRq/14skgVtKTAgSCGkRPVoT8XuKMj2x2V1EQ4+PTzT6FNGMFxfL4r+7KnGh0ncsui8uVfd6vP8Kan3XVVRaMz451cR73fnKHqLo7qZFnkMNDMPgi7fPxvxMJfH56tp1ePtQrc/jGk1Zg5rXObGgtg+nr/EQznSitk3n81ypMVgnfPitprUfGj+HeUef40nYHS68fbDGwx26W2PGXz4o9no+33W6Gee87OUzE8LwtXvm8vYKIsOCAnIFFAsZbFwQDW+V655+G14/1DouEasvbA4X3jrShrc/a8Peiz149UALtp3qnFb1H8rkQJU5lCnF4WRRUNOLjj4jQmUSpMeHIi0uDFKJf/EGXWoT7xf6cE6WdOJuP+06/eFUWTfRrWBdPo0npfjH3SviUNdphI2n0FfTbkRl6wDyxlB0pFCuJ06VdhHPt6Np7RlAa88APvysHllJCiyZHUPc9A0SLBUhNTYEMREyxEXKEBsRjNhIGeKUMqJAhxRRCrg3Rr6aRnUd/MeTkxQ+IZFZ6/PdzZIejRmxkcEIktCl3Y2KgHFvLDcuiAbLcQGJzoKlIty0KAl7z7X4fR+GAb5+z1xEjVOoSeFHIRdjUZYCl+t0xNtIRAIoh4naohXeHVoGCZePX+AmEgrwxVtT8O7RduhN/k3ylTXrcVO+fxHM/mC0OFDRpMGAxYH5GUrERs7seCybw0UcqhlNXbsO+VlTF3HvdLE+p00vVKlwzyTEPVBmJizLob5DB6FAgOTYEF5Bh85ow3MfFqNbwy+O7Ogz4aVd5fjuQwt8Flo7eo349yflvJGfHAdsPVqPbo0Jj92ac82jXDp6jThRwj+0JxUL8eCGTN7rosLHJy5ysRz+/Um5X7c9VdqFTUuTp22862Rw+HIbTARBZXuvEa2qAaTFTf1+/WhBByqaAmvEzE2LwDMPLAgoBmllXhzEIgFOlnYNxeDcsjjZ616IchVZkBhb1qTj/SN1Htelxobi0ZuzrtxOhFV5cTjOM7jb3G1AU5cBGQlX32fvf1aHHi3/OVIsEuCJW1IgEQng9OIIIhYJ8NhNyeg32tGlscJgcsBgdsJgccJgcqCx2wQ+MwuWA94/1o6k6GA09/gnYtcM2LHnQg+OlvThc+uSkJNEdpajUCgUihuW5bCPEG/Y1mtEQU0vlvEkTpBQ9Zvxp/eKhhKQGjr1KK7rw08eX4w4H3vmNhW/wC05JgSJBIGb08Wht99CFMBRph8XqnqIbs4WmxNbjzXg6/fMnbTnP1feg3IfA+7yIBEe2JAJo9mB6tZ+1HfoeYWURosD5U0aLMy+WmsqrOV3xR3NkcvtWJQTPSJhheM4HOUZOgDcQ77L5sTwXicSCvCNLXn464fFaO7mH+48V9GDtfPjMSvFv8F0jiOfGwDgw8/qMSs5POBaWGefEQ2dekSESjEnNQJikX+9+elMVat/+6WTJV2Yl0EWIgbK2XL/RYZlDRo4XazPesSRgnaiaK5Ha8ZfPyjCjx5dOGL4yGp3Ys/ZFhy62EZ83JiIYDzz4HzisI1AwCA2Itjv2OnF2RG4a3k80mNl2HqyA2bCOaVTY8Ubh1vxldtSic89Vlwshw+Od6C2Y+R3V3GjHnOSQzE/I3Ana8rMgXZBKVOG3eHCC9tLPcQHAoZBYrQcGVcirrx9KZMKwcOx2Fw4WdKF25fzW/8HgotlcYbH5hYAkqLlyKCRXBQ/CZOJcdviGOy5wK+g/7RQhdyUUL+cdiiU6xGnix3T5NGgk40vN5uIUCl+/NiigF3TwuQSiIQMnC7Pqr9Gb/Xa6LI5XGgh2GOPN550OFKxEKlxoRP2eJSZz1gc1W5ZkoRPL7f57bjwwPpMzE33jEWlTBzr50WhoF5HjKxMUAaNeK39dXALm4CIUgBIigrGjx/KRlufBT1aK3r6rVDpbOjR2mDhmc7r6behV2dDTLh/Qjxv9PaPnFzcytTjG1vysGQ2f7FxJlDVooXd6d/nj+QOOlnUd+iJBfBBLlSqcPeqtBtKEEPhR6234K8fFEOtd0eMBkuF2LAwEbcuSUZ4iPvz3z9gw18/LIaKINwYpKqlH28frMGX75pDfG9dqlbhjQPVPr+/TpZ0QaU145v3zfPqtDSZcByHDz6rI57X71qZighCnCTJwW0y6NaY0dhpQFbSjVEQNlocOHzZexLAqdLuKRe4tfcasf0EOZqSj6WzY/DU5jmQjKF5sGR2zIz+Hr3WbFiYgOrWfhTVXXUNiVIE4Rv35Y1oHN60OIlX4Aa43QIzEnKhM9pwrqLHazzuo7dkIz7S/zVVRIgEESGea8WiBh22neI/HoeL81vcNhyT1YX3jrXje/dn8j4nhUKhUK5yuabX65p456kmLMqJ9mtIw2hx4IXtZUPitkEMZgf+ub0UP//CEuI62Gx1QGOw8l6XHBuK+CvDwXwuSV1q0wiBW7fGhIomLRwuFmEyCcLkEijk7p+hMvE1Hzi5keE4DseLvPdYL1apsHpeHPLSJ04INIjD6cKuM81ebzM7JRxPbc4dEvBsXpUGi82JH/znLK8T1PmKniGBW2+/mSjUHA0H4I391fjtl5cNGbDUtOmIA1jrFiR4FYNJJUJ896H5ePa9IuJneuvRBvzyySV+1W0rmzRo7CT3O2wOF17dW4WfPr7I78/U3nMt2HW6aWg/mhYXiu8+tABh8pm9Xqv2Esk5nNIGNXRG21BdYjxYbE4U+uEWOIjZ5kRDhx6zvSTv6E127PciagQAVb8Ff/mgCP/v0UWIDJPiQqUK2080QGe0E+8TEizG9x5egDAfRg2xkTK/BW6r89xDtzlJIfj2lgy8cbgNvTp+YV5brwVvHWnDlzalQiKamPM/x3HYe6HbQ9w2yPkaLRW4XedQgRtlyth6rIHXWYflOLT3GtHeaxzKeF+cE42nNueOcHazOVw4V+5fVMaRgnbcsiRp3Ivl8kYt8Yth3YIE2sChBMSK2ZEoatChQ+25WezT21HZNjCm6AgK5XqguF7tUYCZKBQhEvy/RxeOKRJUwDCIDA3idQTxZUHd1GXwsJMeZNYECtwolIkgVCbBugUJ+KyAf1JxOItnReOOCRgkoHgnSiHFvLQwlDXzT38OjycFgIhQCQQMeF04hhMeMnFbQIGAQVqsDGmxV4dT9CYH/vSRp4MJ4HZxu2Xh+JrnLMvh359UjLDl5zjg1b2VSI0LnVIRyEQSSPxca88ArHbnlLl2lvoRpdCjNV8zh6NB7A4XOA5+u4NTJh4Xy+KfH5cNidsA9wDawQttOHK5HSvnxmHl3Di8fagGqn7PtRUfZyt6oFQE4d61GR7PteNEEw5dIk8pj6amTYc/vlOAbz84H/HKqXeZKKojuw1HKYJw27Jk4n0DWcemxIb43dghcaq0a8IEbr06C5q69IhSBCMzIWza1VEOXPAdm3Kxqgef25g1ZecXu8OFV/ZU8g7ZjCYmPBjZyQqsmhuHOWl0+OBaIRQI8PV75uJyjQq1bTrERARjfX6ih5AgMUqOOakRqG71bMRdrlGhTTXgs7G0ZFY0Ni5MhEYTWHQtH4uywmG0OHHg8vhjwoZjd7I4XNiLz633jPKiUCgUihuW47DvfIvX26j6LThb3o31+Yleb+d0sXhpZzlRWKPqt+ClneX4/ufyeXtmpHhSwB1RKhYJERMRzOss2tFnHBLJny7twluHaogDHQCgDAvC0jkxuG9tBsQTJHag+EdTlwFtXl7rQd77tA6/+8oyj6GJ5m4DCmp7ESQRYU5KBDITA1vbHy3sJEYsCgUM7l2bjjuWp3qYQARLRVg8KxpnefrDJQ0amKwOyIPEAQmOAPc+5d3DtUPObEcIQy8M4x5m8EWoTILvP7wAz75bCD1Pn6NVNYDzFT1YPS/e52N9fKze522auw3Ye7YF963L8HnbQxfbsHNULGtLzwBe2VOJH3wuf8Yab+iNNr9FWS6Ww9nybty1Mm3cz3u5ptfvIdVBShrUXgVuu083+RXn2aez4i8fFEERIkFjJ3/NeBCJSIDvPDQfsRG+nf5iI/2rOcxJjUB85NWadHiIBE/dnopXD7RAbeDv7zX3mPHuZ21DDtTj5XSFBhdqyMLG5h4zNAa7338TZeZBVw+UKaGwthcnCBOKvLev68Pr+6tG5CRfqlLBbOOPjBhN/4ANF6s8izM2hwsl9WrUtet4LW1HQ8qiF4sEWJkX59exUCiDCAQM7ludANKa/0RpH80Gp9ywkL4jJGIBshLH3lwLk7vFbeOJriNF82j0/JONg5AcduRBIiREU+t+yvTj9mUpEPooaMQrZfjynWQnHcrEsn4+OYZytMBNKGBGRJbyIRYyCJ7k5rxCLkZqDP85t6zZMO61zumyLnT0eRZknS4Ou0438dxj+sOynF8iskFcLIfGLu9FrImktNF7fMggFyontjnuL90aE37zxiU8/feT+O6/z2DHyUY4Aiw0UsgMxo0eLexAbVu/18/w6bJudPbxF5edLg6ny7rdzm1+itsG2XO2BadLu2C0OFBY24f3DtfiF69dDEjcNoiq34I/vlOIssbxC0MCweF0YdtxcpPi4Y1ZXh0B/BXvikUCfO/hfKyc63+UFR+XalSw+Fl/IdE/YMPLuyvwk5fP49U9VXj23UI8v60UBvPkDLWMBZ3RhmOEGKLhWGwuFPgZdzQcjuNgsvoX5T2cbccb0EVo1EhEAty0KBFPb5mLv39rNf789Ep85a5cKm6bBohFAqzKi8eX7pyDu1amEV1yblnML/pyujifDTplWBC+NMFr8XXzorAuLzCXlmiFb6eP4kY9OtWBne8pFArlRqKkXk1cOw9nz9kW2B1k0QPHcXjnUC1xkGKQmjYd3vm0lnc9TxI9yYNEQw7DiYRa5uCaRdVvvvL4Xg8DGoMVhy624eXdFdO6F1LepMEbB6rxxv5qVLYEFhk/XSG5yI6mV2cZ4SQ1YLbjlT2V+P3bBTh4wS2Ueva9Qvzy9Us4crkdRovv9a7Z6sR+gqBTKGDwk8cW4a6VaUSh1aq5/P1Yp4vF5Rr3Or2AIHAL9ZJkcK6iBy9sL8ML28tQSXACy8+KQpTCv/1YdHiw14jXHScbYfMhYmrq1KOwxr+9x77zLajv0Hm9zdnybmw7zu8MXd3aT3xdZgJ8QyPeOFnSxetEGSikeFKFXIKF2fy13JJ6NfGc19FnxEmCHoEPtd7qU9zGMMDX75mLzAT/emtxfojgAHcKzGjCZGJ89Y40RIaQP2v1XSY8u7UWO891oa3XPObzf3mLwa/hnKIG3ZgenzIzoAI3yqSj0Vvx5oGagO9XUNuHz4YVGv2JJx3OoYttQydIjuNwsqQTP/j3WfxrRxn+/H4Rnn23EGoeR55BtAYrSglF7yWzYiAPujaxJpSZTaIyGPPT+RcUnRorGrr8mzagUGYSA2Y7LlT1oKJZwysu7taYiJuRFblx+NkTi/GTxxZhfmZgRfdQmRg/enThuB06IsP4batbVQMoa9SgpF6NwtpeFNf3ob3XCNuVohNJ4JadFD6mCEkKZbKJDAvCCi8N8SCJEP93/zwES6kJ9FSRqAzG7OQQj8vFIgZzkj2jiaMI56tBFHLxlIgT52fwu3j16mxQESzr/cFic3pMnA7nQqXK6+T5dKWhU48Bc2ACiDofzYuJokdr9hkjOcjFKhVYXxaCE0yfzi1WGmzI2Owu7D/fihe2l45bnENxu6S9tq8Kf3qvCO8fqcNfPijG6/ureddzVrsTu057j5sZD28dqsF3/nka/9lZjmNFnQGL5IZjtjnxwvYy/OeTcq81gYnk8OV29On4hyNmp4Rj8axor/ePIgxcjGZDfiIUcgke3zTL54BHvFKGJ++YzXud3cHiYvXYRKtOF4uDF1rxs1cv4FL1yMZMZbMWf3i7AB3T5Fy971yL35P3pAFIPlp7BvDa3ir83wun8MwLp/Hbty6juN4/R4mSBjWOeYmOevSWbDy+aRaWzYklRtpSpjcLsqKgDPPvMz0cAcPg61vmQj4JMcu3L43FoizfzS+JSICH1ibiBw9k45ktGViYqYC3+Zj9l1XTWrxAoVAo1wqO47D3XItft+0fsHldGxy40IozBLHFaM6UdePQRc8hkXaC+29yTMhQDSExir++OijO3nasgZhkwUdxvfqaDUn5Ys+ZZvxjWynOlHXjTHk3nt9aguNFvociAoHlOOw714KfvXoBP3v1AnacbPTLlGOsGC0Oj7W5Nw5caEW3xoSCml788n8XeQ1FutQmfHi0Ht//91m8urfS60DUoUutMFn59+gbFiYi08eA+6zUCOLa93xFD9R6C5q7+QU/ty1LwRo/XNNI3EQYTiAxOzUCi3L493c6o93noNYOP9zbBuE44LW9VcT6R2mD2md/fteZZmIfY7pTFaDATa23+h1pSkKlNaO+gz8+dmVeHPG179VZ0EWIwN12rMGnODhQPn9LDhYSjoUPfwwilIog5BMEfAq5GE/dkQaFnLxXsdpZXKzpx0v7mvGPnY04WaaGIYB6aFuvGR+d9O9cXNigmxAxI2V6QgVulEnFxbJ4bW+l385ro9l2rAGNXXq09BjQ3D3AexupmH/KuVNtQnmTBla7E//bV4W3D9WOOI6WngH8Y3spzDzTtBzH4SMvXyjr833b0VIoJDZ4cWM5Xja1TgIUymTCshz2nm3GD/5zDq/uqcLzH5Xijzzi4sF4aj4G7b9zksPx3YcW4I9fXY57VqchgVBUGSQk2C1uIxVfAoHUfKhr1+GF7aX4144y/GdnBV7cUY5fv3EJ3/j7SfzgP2fJArfkiYl7olAmgztXpILUo/rq5txrEul2o/PgmsQRE3ACBti8LA7yIE+hYZQPN41wL0WGiWReWhjxfVTWxF8E8od951q8Fj44uKdhJxu7w4XzlT3YfqIB5yq6xy3qKiHEk0pEAuRl8DvyTFXxsSwAZzm9yR7w9Ox4cDhZvLSrgnevWd3aj798UAS9ceyCSgpw4HyrRyPjXEUPr5Dt0MW2ccXNJ0XL8e0H5hNjijjO/Rn3h8WzovG9hxcQ3ZMGKazrw8//dxG7TjcNDSiMF47joOo3o6pFi7Pl3dh7rgXvfFqLfedaeW/PMMAjN2f7FB9LxEKEh3g/x4uEAtx+JUI8WCrCN7bM5Y2gAtzr2x98Lh+r8uIQRnA0OF3qX6N0OJXNWvzq9UvYfqKR+G+q1lvxx/cK/RZ8TRZqncXrPmQ09R16dGvIA2ksy6G4rg9/eb8Iv33rMs5X9sBic/8btPYM4MUd5fjvrgreuKJB9EYb3jxQTbx+UU401i2g9aiZjkDA4KZF3qPm+LhvXfq43M29IWAYPLAmEbOSPAcrBklQBuGZLRlYnB0OwD2I8bn1SfjxwzmICedvODd1m1Ddzl/PpVAolBuZ8iYtWnv8Pz/uP98CM484qKCmFztOBuZk/vGJRo8oR9KgWHLM1cG6xGj+7wiV1oKKZg2KCftab2w9Vj8mt9vJ5ERJJ3adGbnf4QB88Fk9GrvGXs8YzbZjDfjkVBN6tGb0aM3Yf74V//6kfNKGxs6UdQckoHOxHJ59txAv7arwKUBxulhcqFThLx8U43dvFaBNNfK9rTfacJgQ/ykVC7F5VZrP4xEwDHEot75Dj08v8T8+4N4fPnJz9piGQ+IiZcj1EitJ4qENmcSUjIMXW4lRrV1qI86UBmb2otZb8f6ROo/LGzv1+O+uCp8iH44DXtlT6ZcT33ixO1wTJjriOA7VBHfFxbOiif/+JwM00xnN2QryPnl1XhzmZyqJKV4lPHvg8iYNKpr5/44oRRBSYz0HnL0RJhPj6S1zcXOAwsw4PwRuNy9KglBAlhZFhkrw1dtTERrsezi+V2fDwQIV/vxRHT462QG13nv9TmOw4+3P2uB0+ff+0RkdaOqmhjLXK1TgRplU9p1rRR1ByewPLpbDy7sqRtjhjubrW+YSG2g7TzXj928X4DxhEqRbY8Z/d1fCxY5c2O052zJkazuaeKUM2UlUnEAZO/GRQbxuLIC7+NfW659LBoUyndEZbfj7RyXYebp5xOa5tWcAz28rHdowOZwuoqVzenwo0uJGugDFK+W4d20G/vDUcvz+qeXYsibdQ8SmDAvCDx/JRxKh8BIopIhSb/QP2IhTiznJ4eM8Igpl8ohXynEXT2HpvrXpAU19USaOkGARvnd/Fh7dkIT7VyfgO/dmYvlsftFTlI+I0rApEriFycRIi5vYmNI+nQWf+hFHWNaomVTxl93hwvMfleC1vVU4eKEN/9tXjT9/UMQ7NOMPHMehiCDyyE2LxLx0fvfSxi7DlMRw+htPOsiFyp5JOhJPPjpW77Up1KYy4o/vFvrtQHc9YbQ48PahGvzs1Qv4+9biMX0mVP1m7CWIsg5caEVF89X3hs5oG1Nc6CDJMSH40aMLkZ8dha/dTd7f+4JhgAfWZ+Cb9+ZhXoYSv/ziEp/DDg4niz1nW/CL1y7gbHk3Cmv7cKq0CwcutGLb8Qa8caAa7x+pQ3mT789CdYsWP375PH76ygX8bWsJXt9fjZ2nmnCiuJMo9lq/IAEpfhasfcWUrl+QMKJpkxIbisc35XjcLkwmxg8fyUdkWBBEQgFWE9wMmrsNfrliGi0OFNf14T+flOPvH5Wgx4/PnM3uwr93lOPAhdZr5u6052xLQC4jAL/oz2Z34bOCdvzs1Qt48ZNy1Hr5vF2u6R16r43+u50uFq8fqCY6eoaHSPDkHbNpTPx1wtoFCURBLx8r5sbijhWpk3hE7niwxzYmIy3Wcw23OjcS39ycjmiFZ2NYIRfjjiVkF+j9F7sD/qxRKBTK9YzbvS0w52OT1emxH27qMuC1fVWBPz+A1/ZVDu2lnC6WGJGdEnu1tkoaNmY5Dv/bRxboe2PA7MCOE4ENqXEch1OlXfjXx2V4aVcFyggpTKOx2JxoUw3A4SQPtpQ1qvHep55CIcDdq3xldyWv0DBQatv6eQVfZY2aSRnaYzkOJwjxpBGhUmKEJ8lxzRutqgE8+24hLg1zg957rgV2B3/94rZlyVDIfUefA+SYUgA4Wsjv6pQSE4LYCBlkQSJ86U5+92pv3LQocUzr79hIGVFgZHew+ITwOu880QjSssmbC925ih789YMi7D/fguZuAzr6jHhhe6nfbtX9Aza8vq9q0vZmA2Y73j5Ug/974RS+/twJvLSzfNyfpV6dBRoDvyhqRW4ssY5dXK/2OnTkDZblcLacv+6VHh+KxOgQhMokyCYMpZSMGiJ1sSy2HeOPjwWAhzdm4YeP5iM93nfNQChgcNuyZDz7tZVYNoe8NicRKhN7TW2RiARY54f5T5RCiq/ekQZ5EL850WhYDihu1OP5Txqw/XQnNIaRr41ab8ORol68cqAZJmtgg4mXa6duCJcytdB8IcqkUdeuw56z5IX65lVpWDk3Fk1dBjR1G3CmrJu3SaMx2KAx8Dd95qRGID8rCotyolFY53mbVpXvKZjKZi22Hm3AY7e6C7+XqlXYfYZ83GvnJ9CCImXcbJgfjZp2/mbBiTI1vnBLyhQfEYUycVQ0a/C/vVXE6a4erRn//LgUP3pkIQpr+4ib5fX53qfaE6PkSFyTji1r0tGlNqG52wCJWIi89MgJjVAcS3wMCYlYEPDUDYUy1dy7Nh2RYVJcqlIhSCLCqrw4LJkdc60P64ZGLBJgQYbvAQu+puNwwuVTt/1bkK5Ac4+nyEFtsKNba0WC0rtQYzTbjjX4PaX38YlG/PTxRZOyZt97rsVjgKehQ48XtpfhB5/Lh1TiXwFnkC6NGb2EqMWF2VFE4YvTxaK52zCpommLzUkURgkFDG+zurCuD084XJAQXLYnikvVKq8xPYOo9VY8+14hvvvQAqTH80fnXm9YbE78+f0idF1pUvVozahq7cfX75nrd5GT4zi8d7jO64T///ZW4bdfXgZFiBS7TjcTGxYSkcBrUT0lJgQ/fHThkNva4lnReOSWbHz4mf+xLAAgDxLh61vmIm+YKDQ6PBg/e2IxXtlTiTIfYk2NwYbX95Mbc0cLO7BmXjy+cPssXle0gppevLKnMiARR7BUhHvXZfh9++jwYGIUikjI4I4VnnvIdQsSIBYKcOBCK7QDNuQkKfDYphxEKa6eg9cuSMBBnqgqADhd2oXP3zpSJKc32VHXrkNtWz/q2nXo6BvbVDQH9/m6s8+EJ++YBbFocs8bw+nRmomT95FhUoTKJLwC2rMV3bh/fcbQe6C524CXdlZAY+CPn+XDZHXi9f3VuFDZg2W5sWjrMaK5x4A2lZH4mWMAPLU516crIWXmEBIsxm3LkonujoB7wDY3NRKLcqIwOzViSmqRErEAX70jDafL1WhWmSEVC7BiTiQy4ryLhWcnhyAjToYmnrWfqt+Gy7VabI6h+wkKhXL9MWC2o7JZC5FQgPmZSr/2QTVtOjR28kcp5iSHo1U1AJvds4l/+HI7bl6cBI3BipMlnbhQpSIOPYmEAjy8MRPbjvPHXtodLP7+UQnuXJGK7CQFcQ2SHHNV4BYbEUzcB5KcnEVCAVws6zV670RJF1bNi/fLpZTjOLx5oGZEJGtBTS8euzWHKCbiOA4HLrRi56lmsBwHqViIjQsTcffqtBH145YeA/67q9Kru5Rab8U7n9bg6/fMHfP3ssPpwtuHaonXH7zYhqToEKzMI4u5AqWqWYteHX/dYUN+AiLDgrzuhQLF7mTx8u5KtPcasWZePNE12b0e8r8PlhgdgtTYUL/6voMsHlbPzEtX4tYlyThSQHZ7G05MRDDWjsM9+e7VaThb3s3b+zhb0YOblySNGO7XGqz4jDA4Fq+U4ckrAj1SJHFNmw41bbqAXR0HKW3U4Mjldmzy4zUxWhzYc7YZXWoTkmNCsGFhImIj+AddVf1mvLCtFKphta+C2j706az42ROLfQ59OF0s7x6cFDXKAJiVEoEgqQgFPEY2LpbD2fJu3DmG4ZHqtn6i+97wwbEF2VG85j9NnQYYTHaEXRF1ni7tJgqMs5IUWDwrGgzD4AefW4h/bCtBYxf/d8e8DCUeuTlrXMkrDMMgLjKYmKa3Ym6s3/vRmHApnro9Da8faoHRT1EaywGF9ToUN+iwKDsc8RFBKGnSo72P/9w1HHmQkFf8Vtasw32rqQP69ci0Frg1NjZix44duHz5Mtrb2zEwMACpVIqkpCQsWrQI99xzDxYtWjSlx6TVavHJJ5/g3LlzqKurg06ng1AoRExMDPLy8nDbbbfh1ltvhVA4dYW56YjR4sCreyuJC9esJAW2rEmDUCBAvFKO1fPikRobircOes8CH83GhW7xw+0rUngFbv5ytLADCUoZ0uLDvC7klGHSoeekUMZDWqwMabEytKg8i39VbQNQ9VsRGzFxohrK2GhTDWDnqSaYrE6kxoXivrUZkPFEwlHcOF0sdp1uxoEL5CL9II2dBryypxIGM38BJFgqxPIAJk0SouQ+Y0vHSmJ0CAQMMyH22ZkJCmJUFIUyXRAwDDbkJ2KDD5EpZfrhK6JUMUUObgAwNy0Muy908+4HypoNAQncmntMRHdlPho69Sht0CA/mxwLPxa0BisxVqOhU49/f1KGbz+4ICBHFr54AsBdkFuQFYWQYDGCpcKhmLvh1LXrJlXgVtmsJYp17l6dxhtTabW7UNKgHtO0qL/0aM14M4B944DZgb9+UIxv3Z83Qvx0vbL1aP2QuG0QjgNe318NpSIImQm+G0eXqntRSYjIGMRgduC1fVV45OZsnC4jNyz++NXlqGzW4uDFNg83sNS4UPzgc/keRdJblyRDoyd/3kaTnxWFR27JRgyPw1mwVIRvPzAf2080eI2t8Ycz5d3QGKz41n15kAVdPeaz5d1440C118YdH1tWpyFM5p9bAQDev2+QNfPiEUkYyliZF4eVeXHgOI63ERcXKUNOcjivoPV8ZQ8e2pgJsUiI5m4Ddp9pRnmjxu+4WH84X9mD3n4zvnnfvDHFBo2FXaebiK/XPavTAYC3PjVgdqCkXo0ls2NQ3dqPf+0o421A+0NlSz8qCU2Z0dy2PAW5afzurZSZy5Y16TBZnThV0gUXy0EhlyA3LQK5aZGYkxpB/ExPNkIBgw0LorEhgPswDIM7l8Xh33v4G6qfFqhwy/IsBEloPYVCoVw/XK7pxTuHaobEK9HhQXh6S57PwZp951qI1z20MRNlDRrs5bmNzeHCL/530a8Ywac2z8GyOW4xwqt7+V3ejBYHth1vIMb4CQXMCLGESChAvFIW0HDDDx/JR1aiAkaLAwcvthLX4+8cqsWvv7TEa/QdAOw83cwr7vnws3okRskxmydKcu+5lhF7V5vDhUOX2nCusgcPrs/Eqnlx0OqteGF7GdF1eTiXqnuRmxY55tj4/edbfToev3mwBnFK2YQNaR0nuLcJBQzWLUhAmFyCs+XdqGnTTcjzDbL/fCuOF3US6wqbV6UFPKS+Mi8uIIHbklkjXbweuTkL4SES9x5kUPTHjfgBqViInORwPHJzFqTjGN6TB4mxZU06PiAMb310tAH/7/MLh/Zoe07xC1IB4I7lqRAwDB69JRt17TqiYNEfYsKDiffffqIR2cnhXt97fToL/vx+0ZDQq6qlH8eKOnHv2nRsWpo84nPc0KHHv3aU8Z63WlUD2Hb8qvnMaOo7dHjvcB06eo2ICg/CQxuyRgxgVxHiSVPiQhESLMac1AhEhwehT+c5jHSqtAu3L0+BIAChKsdx+JQwGCYSMliee7UOlp8Vhe3HPV36OACljWqsnZ8Ao8WBnafJYsRHbsoeem/IgkT4/ufy8dLO8hF7yNiIYDxyczYWZE1M/TM2UkYUuN28ODmgx4qPDML37s/CZ8V9KG7UwWr3z02Q5YCCOp3fz7MoKxx5aWF45zPP18bh5FDWrEdSwsQJhinTg2m5qzQajXj22WfxySefeFr2O52ora1FbW0tPvzwQ9x666344x//CIViciMjOY7D22+/jX/84x+wWkeeDB0OB9ra2tDW1oYDBw4gOzsbzz//PHJy+E/K1yNOFwuV1oz2PiM6ek2oaNJAS7AGlUlF+NrduR6L1bXz41HfrsPZCv9ibRRyyVDTKjNBgZwkxbjiUN8/Ug95sIg49SIRC/B/988P2JWBQiGxcX4U3jzCvyA6UabG59YHlpFOmVgKanrx8u6rU1vuZrkaP3188ZQ1Xkj09ptxsUoFqViIJbNjrlnhezjN3QZ8+Fk9Gjr9Pw8X15Mt5FfNjZ8251uFXIJFs6J5J34CZV7G9d9Yp1Ao147QYJFXt6SpFLiFBouQGSdHQ7dn8busSY/bFsf4NfHMchx2n+MXz3hjx8lGzM9UQkAo1o+FXaebvcaCVrb045U9lfjGvXNH7HWcLhaXa3pRUq+G08UiNlKGeKUMCUo5Cmv5BW5ZSYqhic7spHBe96nJjGIFgNIG/u/piFAp7lyRiiOX23knkS9UqiZN4GZzuPDSzvKABSU2hwv/3F6Gr96dO6niu2tNaYMap8v4p7kdThYv7ijHL7+wxGv8utnqwNaj/rmnVbX047kPi4lCobtXpSFUJsGKuXFYnhuLymYtLlX3ot9oQ05yOG5flkx07Xr4piwMmB04zxN7GxkmxZzUiCv/RfpcmwsEDD53UzYW5UTj/SN1aFP5jt0kUd3ajz+9V4TvPrQASkUQjhd14N3D/DFG3ohXynATwWWCRJySfyJeKGD8mj73ds5dtyCe95xisjqx/3wr2lRGjzgVfwmWCpEcE+r1nNXYZcBv3ryEr90zF3MJQi6O49DZZ0KP1ozUuFCfka0k2lQDuFTNv66PiQjGqrw4OF0sPjxaz3uuOVXWBZFQgJd2VXh1OZwoUmNDcX8ATn+UmYNQIMATm2bh4Q1ZcLEcgqXCGZ0YkRQVjPwMBUqaPGsCAxYnDl1sw71rM+B0sahq6UdRXS96NGYIhQLcvjyF7pUpFMqMwl03rhixDu7TWfH8RyX4f59fNML5bDgNHXpUt/IL3OemRSAzQYH4SDmOFXXw7rX8Ebfdty5jaM+zYm4cerRm7DnbQrw9SXwUr5R7DG8lRMn9FrgtnhU9NJAVJpfgvrUZKKrr4xWbdPQZ8VlBh1c3r1OlXURxIMtx+O/uCvz6yaUj6uSXqlW8g1mA23XujQPVOF7cCYvNSXSh4+ODI3XISlQEPGzd2WfE/vO+B8OdLhYv7ijDr55civCQ8fUhNHorcR2/KCcaiiuP/8Rts/DrNy55dc4XMG7X6DXz43GhUoVTpV1EN6tBzDb+5Ba3mUjgIsHlubHYdqzBr0H0xCi5h6MVwzC4Y0XqpEe/D7JhYSKOFXXyihpr23X45FQTspPCEREqxQHC+zsyTIoVc92f6WCpCF+9Oxd/eq9oTMP4q/Li8MRts/CHdwrQyfNZdrEcXt5dgV8/uYzX6MFkdeCF7aUer7vDyWL78UYU1PTiS3fOQVJ0CC7X9OK1vVVe90xHCzswOyUCi0cJEUsb1Pj3J+VD56c+nRUv7arA1+7JxYrcOLAcRxRk5l4RugoYt4CTz9Gut9+CQxfbAnJxO3y5HRWEQcCF2dGQDxuCi1fKERspg4rndT9d2o26dh0KavqIotoVc2ORkTBSZBgsdYvcShrU6OwzISk6BHkZkRNqppAWG4oLlSqPy2clhxO/17whDxJhy8p43Lk0FtVtAyio16G+yxjwcCCJzHg57l8dD4ZhEBIsgtHieb4pqOvHnasn5vko04dpJ3DTarV48sknUVtLtmgdzpEjR1BRUYG33noLaWlpk3JMLMviJz/5CXbv3u3X7evr6/HQQw/hb3/7G2699dZJOabpAMtyuFDVg2NFnWhTDfgdGfTkHbNHxGEMwjAMHt80Cy09A0RLzuGsXZAw4sR9+/JU1HWU+f8HjILlOAwQ4vQA4Kubc5EaR2PlKBNHTlII4iOD0K313NSVNulx66IYRIb6P9FPmTiqW7R4da+nJblab8Xz20rw08cWjXBtmCpYlsOuM83Yf65laKJo99kWfP2eXMzPnFiXGn+wOVy4VKXC8eJOtPBE+IyH9WPY4E4mT901B/IgEYrq+oa+KwQMA4GAgfDKfzaHy2ssVUQodQGlUCiTC8MwiFZI0Knhj0oLn0KBGwDMzwjjFbhpjQ50qK1IjvYtTiiq16FDzT9ZmhwTgjC5hNdpqlNtwvnKnhERAeOhvdeIs4QYiOEU1fXhzQM1+PJdc2CxOXGiuBNHCzugM/pfLAfcxbFBcpL5BW71nXq4WNbnlPtYYFkOZU38kY4LMpUQCQVYOicWJ3gmwcubNDBaHOOK0rPZXdCbbBCLhJCKBZCIhRAKGLx/pI7YUGEYtxNVt4Z/Gt7Fcnh1j9u94HoUuRktDp+O6AaTHf/8uBQ/fXwxcVJ+x6km6ANo7pD20DHhwdi46Oq6h2EY5GUokeengEHAMHhq8xzkZ0ehslkDjgPSE8IwJzUCMeHBYxKBZCeF41dfXIpTZV345GSTXw1CPjrVJvzhnQIsz43122VuOOEhEnz7gfkBF6LnZyoRJBHCOkp0tS4/AVFjFHsNsnhWDN4/Ug8LTwPKW0PUF6vz4vDghkyEyiXYfbqZ141kkAGzA89vLcGWtenYvCptaJqeZTkU1vVh/7kWtA1zAZyfqcQD6zMDKrQbTHa8tKuCeP29a9IhEgogEgqwfE4MTpV6nvcrm7Sobun3K442J0kBk83J2zzyB4lYgK/dk0sdoK9zpstg10SwaXEMylsMvJ+PgxfaoNJaUNKg9jjXVLf2444VKXhwfeY1E/lxHIeiOjXOlHWhU21CenwYblqUiFkpnm5AFArlxqasUY1X9vCnF5msTvz9I3ftODbSczjB21po86o0AG6nnrtWpmHb8YaAj21VXhw2rxwp2NiyJh2qfgsuVnmKFrzBt8ZKjA4BCIMCwxEJGTy0MWvEZRKxEI9vmoV/bCvlvc+u081YShjkLm/S4B0vsZ6Aey35n50V+MljiyAWCdDYpfcrdrO5mz/yzxuDEZy//OJi4sDOaFiOw9uHav1aQwKAzmjHfz4px//7/EK/n4OPk6VdRDHJ8Dp1vFKOO1ekEtf+idFyfPnOOUPOXlvWpOPuVWkob9Lgs4J2v52JB9myJmNMf5dCLsHc9EiUE+oVwxktmroWiIQCPHxTFv71MX/v2i149C56vG1pyoj9QGaiAlvWpmPnqcCiSOdnKvHkHbMhEgrw9JY8/P6ty7wDsn06dw/smQfmQyG/2p90OFn8e0c5seYCAM3dA/jtm5exMDsKBYSBztG8eaAaqbEhQ3vaiiYN/rOznPez8taBGiQo5eA4suB3TtrVtduaefHYdbqZ97E+PtEIZVjQCOc1Eo1denx8wtORbZDV8zwdwhZmReEQT+RsQ6feq0mEWCTAA+syea9jGAYLs6NH1AwnklXz4vHJ6SbYHVffF0IBgwc28B+Pv4hFAszPUGB+hgJ6kwPFjTpcrtVBMxBYrXQ4MeFSPH5T8tBnY2GmAqcrPM8LTd0m9PabEUOI0KXMTKaVwM3pdOKb3/ymh7gtOzsbGzZsQFRUFNRqNY4fP46GhquLu+7ubnzzm9/Etm3bEBISuILUF88995yHuC0qKgqbNm1CSkoKjEYjCgsLcf78+aHrrVYrfvSjH2Hr1q2YPXv2hB/TtcZic+KVPZW8jRZvrM9PGGEhOhqpRIhv3peH371V4NUOmGGA9aMsgOdnKRGvJDc0AGBhdhRW5cXj5d0Vfi8kAeD+dRlYPIt83BTKWGAYBhvmR+HDEx0e17EccLpCgy0rfTdlHU4Wqn4zwkOk42okUty09gzgxU/KiaLdzj4T/vlxGX7wuXxIxmFRDbg3thcrVThT3o1OtQkZ8WG4eXES5qZ7uhaYrQ68urfK47xrsTnx0q4K/PjziybMthwAXCyLzj4TBswOCBj3+1UgYMAwV5tM58p7iFNYo2EAv6OMspMUSIqe+O/z8SARC/HF22fjC7fNgovlIBAwHhbWThcLjcGK3n4LVFozVP0W9PZb4HC6kBAlx5Y16ddV84JCoUxPosLIArewKRa4zU0Nw65z3eBbdpc364cEbizHobnHjPZes7u4xjAYPMNeriMXSR+5ORsyqYgYpbjrdDOWzYkNKDKUxPYTDX5/j52r6EGfzoJW1cCIolAgLBwWr0qKIbXZXWhTGX1+/7tYFnXtemj0ViREyZEWH+ozhqG520AULg2K6lfk8gvcXCyHgppebBiDqNtsdWLb8QacKev2GDTwFRd+/7oM3LQoCf/ZWY4qQnGd5Ti8ssc9xLAi9/qKKHjvcK1fwrSOPhNe2VOJbz8w38PhsKnLgBNF/PE1gfLAhsxxi3IYhsHS2TFY6qWGECgCgTuGe8msGOw63YTjxZ1jmh7Wm+w+xW0hwWJEhkoRESpFRFgQIkKlSIySY15G5JiaOUESEZ7eMhev7KkaEofkpUfikZuyA/8DRiEVC7FibiyOT9DrnxITgsc25SA7KXzosvvWZSAhSo43DlQT3TA5uM/dDZ16fPnOOShv0uDAhTbeyfeyRg3KGzVYnhuLe9em+yxYW2xOvLC9FL39/KLpxGg5lg1rbqxdkMArcONAdjoB3A2ApXNisGlpMtLiwuB0sThwoRX7zrX4PRg6yBObZnm4TlAo05nIUAlWz43EqXLPerHN4eJ15Rzk4IU2WG0uPLYpJ6C4qImgurUfH59oHCFyUOutuFzTi/ysKDy4ITNglx4KhXJ9Ut3aj//s9N5bMpjs+NvWYvzkscVDzskWmxMfn2gkinJyksNHCGpvWpSIIwXtPt2xhpObFoEv3j7bQyjMMAy+fOdsaA1W1AeQgJQSyyNw8/NceMuSZMTwDGDMy1BiyewY3pQMm8OFDz+rx7funzfi8jbVAF7aVeGXW5U7YaQOd65MxYsfl3l1YPeH3LQI1LbpeF/vjj4j3jlUi3mZSpgsDhgtDgxYHGBZDvFKOZbMuuqOBgAnS7oCSj4B3C7H73xaiy/fOccvAbiLZWGxuWC1OWG1u2CxO3GqlN8RP14pw6yU8BGX3bUyFXXtuhHOWEIBg7tWpmLzqjSP/Z1AwGBBVhTmZypx4EIrPjnZ5FfdJCFKjlV5Y9+Pr8yL9UvgtmSa9HQXZCoxJzWC6N7ojZBgMW8c7uaVqZCKBDhwsc0v98HMhDB8Y0ve0GuYGCXHY7fm4E3CkFxTlwF/fKcA33loARKj5OA4Dm8eqEatH0kCLpbzW9wGuF3+XtlTiR8/tgi17TqvvTn7FWf6Zbn8r61IyIzYgypCpMjPjiKmJ7y+vwoRoVJi3Q1wu9a9vKuSeN5PiQ3hHeTLz+YXuPli09Jkr677k0lIsBg/fWwx3jxYjc4+E2IignHv2gxkJU5ciqJCLsaG+dFYmxeF0iY9jpb0QWPwX+gmYIBF2eHYvCwOQcN6bYuzwnkFbgBwtrwH91FX9OuKaSVwe/nll1FcXDz0u1gsxq9+9Ss8/PDDI273wx/+ENu3b8fvf/972GzuBV5jYyOeffZZPPvssxN6TJcuXcKbb7454rJHH30UP/3pTyGVjrSGLSoqwve+9z309Lg36xaLBd/5znewf/9+iETT6p96XPT2m/GvHeXo8sNlbTgJUXI8crPvwmu8Uo4v3j4Lr+6tIt5mQWaUxwlewDC4Y3kq3jjgOZUhFDB4cEMmNi1NvuIUl4O3fUx8DLJibizuGjX1QqFMFPPSwnA4TML7BX65rh835UcjNJj//OFiWRy62IZDF9tgsjohEjK4bVkK7lubMaFxXCR0RhsuVqlQ166DyeKAUCiAUMhAJLjyUyhASLAYs5LDkZ8dNSOmznv7zfjHthIPV4TR1Hfo8fLuSnzr/rwRrikcx6Gp24C6Nh0kYiHmpkcijmdaDwAaO/X44LP6EQXUkgY1ShrUmJsWgQc3ZA25Rnb0GfHvT8qJzRi7g8W/Pi7DL3xETvmC4zi09AzgXEUPLlWrvLpaBsKmpclYnhuLv20thsXmO1JsLA3xqYJhGIiE/J8vkVCA2AgZYiNkNF6FQqFcM6IU/PEVEpEAwZKp/S6WB4mQlRCCuk7POMCyZgNuWxKLihYDjpX0QaXzv3APuAVgc67EDizPjeWdRtcYrDh4oRV3rUolupzZHS7UtPWjVWWEgHE/1mi36coWLSqa+EV0JAJpHIwmIUo+Yto/LS6UGD1b164jCtw4jkNhbR92nGyEatgaIiJUisU50Vg6JwYRkXIIedaNpY38ESZikWBoGjYrSQFlWBA0Bk9B5YmSTqTFhyIlJtTvdWlDpx6v7qmEWs8v0PTW0JiXocQdK1IhYBh896EFeH1/NdGhgOOA1/ZWAZw7sud64FK1ihi5yEdZowYfHWvAo7dc3Z+7WBbvHKohNiRWzI1FSb3a5zoZcBfPl0yDaXlvhASL8fimWVifn4gdJxtR3qgBB7djVkiwGCFBYsiDxWjvNY7J6W3zqjTctzZ9wp2I5mdG4blvrER7rxEhwWK3i8YEsW5+wrgEbhGhUsxKCcfC7Ggszonm/ewvz41FTEQw/rWjDHovzpYVTVr84N9nfTbIOAAXqlS4XNOLdQsScPfqNN4YJ6eLxUs7y726Tt+3NmOEqCYjPgyJ0fKA3NeWzIrGo7fkjIjNFQkFuGd1OpbMisFbB2t8NjbFIgEyE8KwaWkK8rOn3qWbQhkvG+dHo6BOB7Mfe//RHC/uhNXuxJfvmjMpDrWjae0ZwMcnG4nDEoC7TlPaqMa6BQnYsiZ93FFxFMponC4WDidLdNelTB8aOvX4l5+iKY3Bhr99VIKfPLYIrT0DeOfTGmgN5D3v3Vfc2waRiIW4e3WaT9cywB3/eeuSJNy+PIV47hSLhPjhIwux81QTjhV18O4tR8Pv4OZb4BYSLMbmlWnE6x+9ORsVTRrefUVhXR8+OdWI2SkRSI4Jgd3B4h/bS3lj40mcKOlCcb0ahnHWtWclh+M7Dy7A8eJObD1az3ubsxU9OFvBL97eerQeC3OisTE/AXFKOT4+QXbkS4oOQUefZ90EcAszypu0SIsLRXp8GNLiQpEcEwKD2Y4utQndGjO61CZ0qU3o1Vn8Ht7ZuDDRY68iFgnxvYcX4PDldjR2GhCnlGF1XpzPPQfDMLhrZRoSo0Pw6p5Kn3vGB9aNr3+1MDua19l6OLGRMr/er1MBwzD43E1Z+O2bl/0enBzklsVJvAPzDMNg07IU3LI0Ge0qIypbtKhs1qK+Q+8RCZoaF4rvPLTA43HWzI9HdWs/LhBqJ2q9Fc++W4hv3ZeHmjby7SaCxi4DXt5diYomjc9zrLvWxy8cy0pUQDrKlOLetRkobVDziuacLg4v7ijDz55YzDtYxHEc3thfzVv3Aq44bt89l3c4IzMxDCHB4oDqCWEycUCxqZNBalwofvOlZWBZDswV44vJQChgsCgrHAsyFChu1OFYSR+0A+R/q+ToYCzKVGBeugIhPD3zuMggJCqDeIe+z5R3Y8va9Ak9fsq1heG4iUq6HR9qtRq33norzOarU5l/+ctfcO+99xLvc/jwYXz729/G4J8gFApx8OBBpKZO3If/gQceQEVFxYjfvYno2tra8NBDD0Gn0w1d9uyzz+KBBx6YsGOaSjQaI9hhquSa1n78Z2c5TFb/HHsGEQkF+NUXlyApgOiIdz6t5XUEAIDvPrQA8zM9xQMsx+HfO8pHZMpHhErx9Ja5I1TbAPDhZ/U4UuB94jozIWzcFsDXG4MLT7XarXh3Ot2LSIZhEBk5cgGg1ZowTU4x05pLtVp8cpY/8mpOSijuXRk/JFqKinI3itpVA3jjQDWauz0L9ItzovG1e3In5X1rs7tQVNeHc5U9qGrR+r1higyT4pbFyVi3IAGyoOlZsNEbbXj2vUL06fgXq3ysnR+PJ++YDavdhQuVPThe3OWxGU2NDcWy3Bgsmx0LpSII/QM2fHyiAed5suxHsyI3Fjkp4fjoaINXV8tBEqPl+JmXyCkSfToLzlf24HylitcdYazIg0T4yuZc5Ge5GzPVLVo8v63U65RjSLAYf//WKnrenUYwDIOoqJHf32q1kZ7fA4T0/TkViK58nga/Q9gAXGwpV7mWr2EglLcY8P4xzzVuojIIz2wZn6X8WCio68fHZ/gnhsNDxNAZAy86CwUM/vDU8iERmKrfjF+8dpH4/SIPErkFF7OikZsWCb3JhrJGDcoaNahp7R9R3BcKGNyzJh13rUiFQOB2DPvdW5fRpuIvNouETMCOPL64a2UqHlg/8rV67sNi3mnfhdlReOaB+R6X8zmR8BEeKsXKefFYPS8BeZlK9PebwXEcfvPGpRFRgIPMz1Tiuw8tGPp9x8nGK5Ea/MiDRJiVEoE5qRGYnRqBBKXMozjGshz2nW/BnjMtfk3ljyYyTIrffGnZCCdjluPw0dEGr/s9hgGe2pyLlTNc5KY32vDL1y+NSYS1cVEiohXBEAoZdKlNOFnC/1lVhgXhD08tR3FD31DMqzd++vgij/33dMfFsmBZzmMN6h6AKR0hEvXFgxsyr3lReqz89s3LaFWRRWDDiVIEYXZKBGalhCMnORxRiiC/i9/9Aza8tKscjZ2BR0J5QyISYNW8eGzIT0BKrHtYiOU4vLa3ymssV156JL738AKP4z9yuR0fEhqao1mfn4AnNs3y2qxjOQ7Hizqx/3wLdEY7BAyDxGg50uNDkRYfhvQ4t6huItwP6fr9+mUmrEnPVGqw7yLZrc0XC7Oj8PSWvAlx4eWjo8+IfedaAhKHA+4m5m1LU3DT4qQRkV0Uylio79DhwPlWVLb0w8WyyEpU4J7V6bypDoPQ8/u1o7VnAH/9sJg3zt0boTKxzwHi9Pgw/OILiz3WIU4Xi9+8eZloNJGbFoEN+YkBD5YbrjgRHyvqIAqEJGIBnv/WGo86Psty+ObzJ70K5J7YlIONi5K8HsORgnZ8+JnvNZZIKPAQ64wXhoHPnka8UoafPbEY8iAxOI7DPz8uCzjNajgSsYDo7j43LQLPPDAff/mgiLfXMxmQXt+JoEttwr92lBEH9TMTw/Czxz3f74Hyxv5qnCnn76kB/HWVa81bB6t5HaJJSMVCPPfNVQGlNtkdLtR16FDbpoPN7kJspAwbFiYQxa8WmxO/fesy8fUCfLvpB0JilBydAZrnBMJ9a9Nx92pPIdOFqh6vtYwoRRB+/oUlHus7X+eqr9w1B6vnkVO4/revCucIItjRiEUCfPvB+ZibRl4HXGsmcx/iYjkUNehwvPSq0E0ZKkF+pgILMxXEge7hnKvSYM8F/n/vH39+4Qin1BsZluMADmMWGgsEDJTKa5vANW0Ebi+++CL+/e9/D/2+bt06vPbaaz7v94c//AHvvvvu0O++BGiBcPHiRXzhC18Y+l2pVOLIkSOQy72rvg8fPoxnnnlm6PeUlBQcPnx40lSuk8lwgdvJkk68d7guoGhPAJBJRfj6lrkBu9k4nC48+26RR3E1PT4UP39iCfGDx7IcLtf0oq13AMqwIKzOi+dVuLtYFv/6uJxoZRsZJsUvv7iUFixGQQVuE4/TxeKv2+thMPNvkMVCBuvmR2PjgmjEx8Xg4IU27Drd5LWZOjslHM88MH9Cpv84jkNtmw6ny7pRVNfnl9CKRJBEiHULEnDLkiQPd5RridnqxF8/KOJt5Ppidko4mrsH/Pp3SY8PQ6faOOa4Mn/IS4/Edx6aP7Rp4TgONW06XKjsQXuvETaHCw4nC7uThcPp/v8T3ZgHgJwkBb52z1xEho10lPO1mbhtWTI+NwExS5SJgxZQJwYqcJv5zIRmIuCOLv/TR3Uerhl3LYvF2rypd4Ix21z444e1Ae8hvLFpabKHM/S7h2v9ch4SiwR+TdxnJSnw1c25aOjQ47V9/N9bWYkKPLghE89/VOLXBLw/CBgGv/3KMo/ol91nmrH7TLPH7eVBIvzzO2uHpkXbVG4nkkAd5wAgVCbBwuwozEoJdzuc8TC6WdGpNuGX/7vo93OEySWYkxox9J+AYfDq3soxO94JBQx+8tgiZPLEJXAch52nm7DvHFmAxzDAl++cg1V5cTNyv85xHP71cRlKCc2WeKUMLheHXp3/4iw+vv3g/KGBhTcPVON0GbkovygnGv83KlZopmO0OPCvHWVo8ON9+titObh5sfeG3nTmeFEH3j1c5/U2qXGhuG9tBuZlRI7rc+N0sdh+vNHn4OFYSY8Pw4b8BLT1GnG0sIN4u6ToEPzksYWQBXk2jowWB77/7zM+90u3L0/BQxsy/f73cLEsjGYHgqUiSMQTP9hD1+/XNzNhTep0sXj+kwavLgy+yE2LwJO3z4bZ5oTBbMeAyQGD2Q6b3QV5sBgKuQRhcgkUIRIo5BIESbzXv2x2Fy5Vq3CqtAuNXeMT1zKM29ln8awYLJ4VPcLVzcWy6NGY0aYyor3PCLvDhTmpkViYHTUlaQuUwLDYnKjv0KFLbUZIsBj52VEBCQkCheM4VLZosf9cKzHmbU5qBB7ckMnr0kzP71OP3mRHaYMaH59oHNNAiT98/+EFvPF2AKDWWfC3j0qGxCchwWKsmR+P9fkJiPURz+4Ls9WBo4UdOFLQ4fG3eRMHeRuISIyS4zdfXurThdPFsvjD24V+D1bwsW5BAkob1ND7Ec84yOq8OGxenYaPjjaMMMkYjkIuwc+/sHhE78JgtuPXb1zy6kA8FiQiAX731HLEhAejf8CG3719ecKfg491CxLw5B2zJ+3xTVYHXt5d6eGQKmAY/PixhRMyDFXd2o/nPiwmXv/rJ5cOpeNMFyw2J/76QbHf7/s7VqTioQ2TL9Lr1pjwt60lAUUiDxImlyAlNsSvGtR96zJw54oU/O3DEr+iTsfCz55YTIzT3H++BTtONhHvmx4fiqe35EEeJEKQRIRW1QCefbeQWM9cnReHr2zO9Xo8xXV9ePGTcq+3CZWJsXJuHG5ZnIQonmjn6cRU7EM4jkOf3g6xiEG4XBxQzcFkdeLZrfw6ltXz4vCVu7y/XtcrLMuhsUuP4jo1ihvU6Ou3gGHcws7o8OBh/wUhLlKG+Cg5ryvhIFTgNoybbroJnZ1XGxJvvvkmVq1a5fN+KpUKGzduhMvl/hCFhobi/PnzEIvHvxH58Y9/jF27dg39/vTTT+N73/ueX/e944470NR09US5fft2zJ/vOVk/3TlT2I5ujQn1HXqcr/StMhYKGMQpZUiODkFSTAiSokMwOyV8zAU7g9mOV3ZXDrkVpMaG4lv3502YMMZsdeLZ9wo9pmCkYiF++viioYlfylWowG1yOFWuxoHL3h295EFCRIYFo91PEVZKbAi+93D+uESazd0GbD/egJo23Zgfgw8Bw2BhThQWZUcjLyMSobKJF5JabE5wHAehQACBgIFQwAw5sWj01iHr7i61CfWdeq9TKv5Mdk0nNuQn4N51GThX3oOTJZ0BOU6Ml9y0CGxcmISFOVHERdDBi63YfryR97pnv7aCGOtKuTbQAurEQAVuM5+Z0EwcpFNtwXvH2tFvdEAoYLB8dgQ2L4u7Zk21t460oqY9cBE5HyHBYvz56ys8hAh6ow0/fuX8hIrIpRIhpCIBMdrkZ48vRlaSAhVNGvzz4zKfIj6xSIC5aZHQGW3o1ph5xfH3rknHPWs8p029FW/XLYiHzmhHj8Y8biGTL577xiqPOHSS25s/jHcS+JGbs7FpaTLxerfIrRn7zrV4fZwwmRjJsaFIiQ1BamwoUmJDESoTQyhgIBQIIBQyQ+saluNgs7tgsTlhsbtgtTlhsTshDxIjMUoe8N7XaneiS21GZ58RnWoT+nQWSMRCpMSEIDNRgdS4UI+IDZbj0KMx41K1CnvO8v9tAobBz7+wGEESIf7wTmHAbhODLM6JxreGCdZsdhd+9/ZldGs8XX8FDIM/fHX5dbmWczhd+N++alyu4Xf7YRjgS3fMwZr55OntmYDZ6sTPXrsAA0+jMCk6BPetTUd+dtSECkILanrxxoFqv+JvJ5ooRRB++vjiEZGio3l5d4VXl6f712XgrpWp00okS9fv1zczZU1a3qzH+8fJ4tJgqXBCB+6kYiEiQqWICg9CtCJ46KcsSISCml5cqFJNynmGAZCdpECcUob2XhM6+oy8wxQpMSH43E1ZmDNFrhwcx8Fqd8HuZOF0snC4rv50uTiEysSIiQj2eu5yOFl35FmTFiabA/IgMbKTFMhOCvd63pwK9EYbOvpMsDlcEIsEEAsF7p+D/436XSQUgGGYK4I2PWrb+lHTpkNrz8CItahULMSGhQnYtDRlQv9Gp4tFaYMG+8+3eI3LHs6SWdG4f33miHXV8PM7y3LQGW2oa9KgT2+GRm+FzmhHSLAYOcnhmJUS7rU5SSGj0ppRXK9GUX0fGjv0PiMF18yLR5fGhKYxiGcf3piF25eneL0Ny3Fo7jZAKhIiTikbt9PraKx2J06XdqO8WQOnk8XS2THYwBNfOYg3RyJvYr3RNHcb8Ie3CwKObASAJbNj8PSWuWjo0OO5D4v9GqjLSVLgB48sHHIHLW/S4MPP6tEzLM0kTCbG9x7O5xVGVbf2428fFo/peEk8tDETdyy/6vzc2KnHXz4ompRh9OFMhfjLxbLYe7YFhy61we5gIQ8S4ZGbs726XQUCy3H4f/89xxv9G6UIwl+eXjmt1ueD2B0uFNb1obatH739Fqj6LbzCsrkZSnzngXkT/nkn0T9gwz8/LiWmF/AhEQvw488vQlpcKC5UqvDBZ3W86W8iIYMv3zkHK6645/cP2PDrN/x3oZdKhH7FFAdJhHjxu2uJAluO4/DOp7VE5/rReOsJxitl+NUXl/Ka64x+zuc+LPborwoFDBZkRWH1vDjMy1BO2es8XmbCPuS9Y+2oaPH8PpaIBfjr06sQdp2ZGtkdLt7PHcdx6OgzoqiuDyUBxnYr5BLMy1BifqYSuWmRHm6fVOB2hfr6emzevHno9/DwcJw7dw5CoX+F4c9//vMoLCwc+v21117DunXrxnVMHMdh1apV0Gqvqo537dqFOXPm+HX/F154Af/973+Hfv/qV7+KH/7wh+M6pmvBF3/7KbSEbOnhxEQE46m7cpEaFzrh9vEcx0FntMNqdyIu0jPSZrxo9Fb8+5PyIdV8qEyMb2zJw+xUalXJBxW4TQ42hwt//qgelgkutsVEBOMHn8tHdIDKf5XWjB2nmlBAaOBMJAyAjIQwzMt0f2GKRUJ0q03o1prRrTGhW22GWu9u9GXEh2HxrGjMz4zytEjnODR06HG5phfF9X28mxvmyv8E8racnRKOhzZm4W9bS8bcGJwMfDWEJ9I62hfyIBFWz4vHhoWJfjU0OY7DVp7YMOreNj2hDbKJgQrcZj4zYRM/HI7joDM5IJeKIBFf20JJUYMO2075dlfzhVDA4Fv3zxtykhrNJ6eafAqZJorRop+Cml78d3cF7xojTC7BzYsSsWFh4pCon+M4aA0291pHYwYYIDNBgYwET6cGwL1W/L9/nJpQJ7xASYoOwe++sszj8rPl3Xh9f/WUH8+WNem4Z3Waz/0hx3HYfaaZKATzFwHDQChkvDoABkmEWDYnBqvnxSMrUcEbx9rSM4DKZg2augzoVJug1nvfbwsYBskxIchIDINMKkJztwHN3QM+16V3r0rDfesyAACVLVr846PSgNeGUokQf3xquYcjb0evEb9/p8Dj3+LWJcl49Jbrdy3Hchx2nGjEwYttIy4XChh87Z65WDo75hod2cRS3dqPV/ZUDonc4pUy3Ls2A4tnRU9ao7xHa8ZLO8vR0UeOqxEwDJbnxmBOaiQOXWojxnX5S0iwGD97YrHP/Ut1ixbPbS3hvW66OvbR9fv1zUxak35aoMLxsqsOOfJgd2z8klnRmJMaiboOHV7cUTapLvdjITJMyltTmgjys6Lw0MZMxCu9J8SwHAej2YH+ARv6B2zQGW3gOA5hcinCQyWICJEiTC6BSCgAx3HoH7ChpWcALT0DaO0ZQEuPwWcsYqhM7I6STwnH7NQIxEXK4GI5VLVocbm6F0X1auJ6I0oRhKwrYrfsRAUSor07PYwHg8l+5W8zoKV7AK2qgTG5zIiEArhY1q+aoEjIYM28eNy+IhUxV2qqeqMNzd1XjqNnAANmO8QiIaRioXswRixAkFgEkYjBgNkBvdEGndEOndHG23j0h8F1IAcOHOeuZzICBk4nC7Xe4nVdGhEqxbI5MViRG4eU2JBpKfQYDstxaOoyoLi+D/XterhYDrlpEVg9L37ShyfMVidq2/tR3dKPyhYt7yAHiRW5sXhqcy7MNnc6iLe1zHCUYVJ88fbZfovBphOny7rw5oEaj8vzMiLx/YfzA3qs9w7X4pgfTuzDyUpS4EeP5EN8pdb1WUE7PvARdxoTHoyff2Gxx5C908WisNYtNgoPlWJ9fqJXs4Cdp5qwd4JqDikxIfjlk0s8xDiTvb9ekRuLr90zd9IefzRmq9uJNSJE6lMMFCg7TjZi/3lPx/Y7V6TiwSlwPpsobA4X+nRWWF0sDCY7oiNkWJgTDY1mavurVrsTr+yuJDrED4dhgGfun4/87Kv1Ob3RhveO1KGwtm/oslCZGN+8N88jGrKsUYMXtpf6fJ418+KxeXUa/vB2gU9BXH5WFL79oHejIV/Jbv4gEQnwiy8uQVK0fwIfo8WBw5fbUN6kRZhMgryMSCzPjUXYJJh+TDYzYR9S3TaAtz9r471OKGAwL0OJZbkxWJgV7fWcxLIcBizu9ZzBbIfBZIfJ4hwyUxEKGYiE7iEKkYBBmFyCpJgQjwHV0Y/ZqTahsUsPk8WBMLkEsREyxEXKECrzz63ObHW7D9dcGdZoUw1MqjmLgGGQlaS4ksIB2BwsRCIBvnrftTX1mhYCt/feew+///3vh36/+eab8dJLL/l9/9FisieeeAK/+MUvxnVMdXV1uPvuu4d+DwsLw6VLl/zeCJw/fx5PPvnk0O+zZs3Cnj17xnVM1wJ/BG5zUiPwjXvzJtW+e7Jxuli0qYyw2J3IiA+bkFjH6xUqcJs8Cur78fFp/6YHAkERIsHmlWkIlgoRJBEhSOL+KRELIGDcrmYCxv3aOl0cjhS041RJ1zVtoPpCJGSQmxaJRTnRiA4PRnFdHwpqe6GbYAvvlNgQ/PjzixAsFaGuXYe/bS2B0zU5hdcoRZDPBucgC7Oj8MjN2fj7MIv6yYQBPKbTREIGafFhWDc/AcvmxATsVsJxHC5WqXCypAs2hwsr58Zh46LEGTOtciNBG2QTAxW4zXxmwiZ+umK1u/D7D3zHlDIAUmKCIRQKAI4DB/c5iOOAtPhwrJgb6zXKwuFk8cL20iH358lCKGDw+6c8XaoKa3vx5oEamK80ApOi5di0NAXLc2MnZAjo2XcL0dA5tijPiYAUUxPoFKy/rJkXj9uWp8DpZGF3umBzuGB3sGAYt7P3aNGVL3adbhq3yC0QYiKCsXpePBZkKtHaM4CKZi2qWrRjbnAGQkpsCH7xhSUj1lUnSjrxzqHagB7Hm0NebVs//rOzYqjIvGxODJ7anHtDrOUu1/Ri56kmaA1WJEbL8cjN2RMSszOdsNicaO81QiYVITFaPiVNcZvDhfc+rcXZUY4gIiGDNfMTcPvylCGRActyOF/Zg12nm6HxYyhzNFKxEP/v8wt549/4eHVPJS5UXXVcFzAMvnzXbKzKm56OfXT9fn0z09akOrMTHX0WpCZEIz0hzEME1dChxz+2l06LgcKsJAUeXJ+JrCQFCmp68fGJRr/rNIEgFDDYsDARS2ZFQ2+yQ2twC9gGxWyDgjZ/1s6hcgk4jvMpZvMHRYgEDgc7tJYNBJlUhMxExRWHNwXS48MgFgkwYHagV2dBX7/F/VNngdPFQhkWhJiIYMRGyBAbKYMiRAIBw2DAbEdrzwCahwn1Jkts6A8MA2QnhaNPx++wM1OIi5Rh8axoiIQCWGxOWO1OWGwuWOxOOBwspBIhgiRCBEvddeNgiQhBUhHCQySIi3S/RnyOwl1qE+radahr16GxU48Bi9vpLzRYjFC5BKEyMcJk7p+hw36GXfkpEDCoatGipF6N0gayu0hWogKr58Vh2ZzYob6Nw+lCe68Jzd2GIUGnPEiErEQFspPDkeAlXstgtqOz14jqNh2qW7Ro7h4Y05DwopxofOPeuUMCJb3Rhj+9X+SzVnvzoiTcvz5jxvagHE4Xfvn6pRF/Z5hcgp89sXhoreYvNocLL2wr9TuuMDYiGD//wpIRvUiO4/C/fVU4X8mfjiOTivDzLyz2KSz2B47jcOhSGw5eaBvaBwVLRQgNFkMeLEaoTIxujQl9Ou/fHQwD/OILS4hr0YKaXuw52+y3YNIbQgGD4Cuf50U50bhrZdqEm5RcKyw2J371+kVohn1PKOQS/PGryz1c/6c702X9zrIcPjxaj6OFZBdewPugT3O3ARVNGsiD3dGbpHPd9uMNHsNjw1k5Nw5fuWvO0HfF8z6G9h69ORu3enH4H8Ric+IvHxQF5FY3nC/dMRtrFySM6b4znZmwD3GxHP70UR2MFu/rWYlYgNlXhJd2hwsOJwv7lf8sNicGzPaAhWMMAyQo5UiNC0VqXCjS4kLBshzqO/So79CjoVNP3PMES0WIi3SvjYOlIggYBsyVvr2AYeBwsWjq0qOlZ3IFbf4QGRaEt3992zU9hmkhcPvFL36B7du3D/3+zDPP4P/+7//8vv/hw4fxzDPPDP2+cOFCbN26dVzHtGfPHvzoRz8a+n358uV45513/L6/TqfD8uXLh34XCoUoKipCUFBgRfhrjS+B202LEvHIzdk3RBGb4oYK3CaXmvYB7LvYA7UhMKGWSMhMunU1iXilDAuyoiAUMHCxHJwuFi7WPWlaXK+eNEHYZBMTHoyfPrF4xNRWUV0f/rOzfEIXEPFKGR69ORtz0yNR2qDBxycbiW4EDIB7r0TgCBgGKq0Zf3inYMIbpQwDzE2LxMq8OCzKdk8ycJx7WpTlOHAcd2VSgZ77bwSmywZ7pkMFbjOfmbCJn868e7QNla38cTwMgPkZCty0IAqxESP3S4G+f1mOQ3GdGherVShv1PDGgI6XmxYl4vFNs3ivs9icaFMNQBEiRayP2KdA+fhEIw5c8JxO9of8rCjctSoVvf0WFNb2obxJ49XxgY/BSFYSHb1GFNf3obq1Hw2dhjGvAYOlInzx9llYNid2TPf3xu4zzdh9pnnCH3c6IRIy+NWTS3mniUkT7nzkpkXgew8v8Lrec7pYdKlNCJVJrnlUGeX6gOM4lDdpcKK4C06WRXpcGDYuSkR4CP/7y+FkcbKkE/vOt/LGqvIhFDD4zkPzkZfuv2OK08XiTFk3yps0kAeJcfvyFCREjb9JOlnQ9fv1zUxbk/qzlmtTDeDvH5VMiEhrLCRGy/HA+kwsyFSOWLs5nCxOFHdi77kWv2O0KG6EAgZikcDvWFiJSABZkGjCB1cpE0dkmHRI7KYbsKGuXTclgxvDkYgEyE2LhHbAis4+k1cRqDxI5HYYTFJAKBSgS20acs+eiM9zXkYknrl/vodQSK234M/vF/EKM2MjZfjSHbORkxw+7ue/1pisDuw+04w2lRGJUXLcsiRpzAIyluNQ2axFdWs/2lUDaOs18n4fxIQH4/ufW4CYCE9HP5vDhWffLUR770jBilDA4HsPL0DuBMdDcxwHi80JiVjo0RtlObcT5oniLpTUq3kFObcvS8HDN2X5fB6jxTHkXtnSM4DmbsMIsa1YJEB8pAwJUXLER8mRoJQjShHkNjqQihAsEQ5FNF+vaA1W7D/fih6tGTERwbh7VVrAw3DTgem2fj9S0I6tR+t5+2CblibjkZvH79zudLH4y/tFaOSJd16eG4uvbs4dWvcCwOHL7mMi8buvLPPbVa1/wIY/vlsQsIh+5Vy3a+f1/JnyxkzZh+y/1IPTFWN36aN4hwrcrvDoo4+iqKho6Pd//OMfuPPOO/2+f01NDbZs2TL0e3h4OC5evDiuY/rHP/6Bl19+eej3Rx55BL/97W8DeoylS5fCYLh6Yt67dy9ycnLGdVxTDUngJmAYPHZrNjYumn5RDJTJhQrcJh8Xy+FSjRaflfTBZPW+QAiWivDozdnITlbg71tLJmWylI9QmRjL58RiZV4c0uJCiQs6vcmO40UdOFbUOaOKgQq5BD8lTJ2dLOnE2wT3i1CZGGvnJ2BdfgIYuN0dLlWp0NbrOQ0iDxJhy5p0bFg40rXMxbI4V96DXWeaR2xYg6UifO3uXCwYFcvmdpYrnhCBY2pcKFbOjcPyOTFQEJpIlBuP6bbBnqlQgdvMZ6Zs4qcrqn4rXtzTNOL7imGA/AwFNi6IRkw4//fOeN6/docLlc1aFNT2oaTBM2IpJSYE8zKVWJAZBUWIBG/sr/Y5OR4kEeLPX1+JMC+xJZNFRZMGz2/zHeEwnKxEBR7ckOnRRLHanShv0qK8WYvL1SrYfDQfw+QSPP+t1SOKi96wO1xo7NSjuq0f1a39aO7yzxUhO0mBr96diyhFYJP/gbDnTDN2Xccit4c2ZOKOFanE6wtre3G5phe6ARucLAeXi4OTZd0/XSzkwWLMTYvEljVpQ7E/FMp0x+FkUVTXh5Mlnahp03m97dfuycWK3LipObBrBF2/X9/MtDWpv2u5bo0Jf9taMqUuWdlJCmxclIhls2O9rnHMVic+K2zH+UoVVFr/owspFH+YnRIOjoPfDlaUa8/qvDg8ftssYgxZj9aM/3xSjs4rA8wChsHty1Nwz+q0gBMwbkQ4joPeZEebyoj23gEYLQ5EhAZh/YIEr3FyWoMVL2wvQ0efuw4vFQvx5bvmYOnsmKk6dA/6B2w4XdqFU2Vd0BpsEIsEWL8gAY/cnO333no0g/HHQVIhohXBY34cyvRiOq7fS+rVeGVv5Yh60ep5cfjSnXMmLJZca7Dib1tL0DNsfbU6Lw5P3jnbY9jO7dZYjfOVPaMfBhGhUvztm6sCEp519Bnxp/cKYbH5t5aOi5ThV08uQZBkZrpvTgQzZR/Sp7fhhZ2N0zqlbCZDBW5XWL9+PXp6rp6QPvjgAyxevNjv+2u1WqxcuXLEZUVFRZDLxz5N+aMf/WhEpOh3v/tdfOMb3wjoMTZv3oz6+qtq4ldeeQUbNmwY8zFdC/gEbvIgEb55bx7mTPDUA2VmQAVuU4fV7sLJMjVOV2p4xUvzM5X44u2zh9wSdEYbnv+odGgTNxnMTgnHpmUpyEuPDMi50e5w4VxlDw5fah+xWJ2OxCtl+OZ985DoZSL/VGkX3j9SN+R8MjslHBsWJmJRTjTvv0u3xoRL1b2obu2H1e7E/EwlNi1N8RrtbHO4cLFKhYYOPSLDpNi4MJEoOjtf2YPX9lZ5/bsEDIP87CjMSY2ARCSAWCyAWCiERCyAWChATETwjJxuokw+03GDPROhAreZz0zZxE9nerRWHCvtg87oQHJ0MFbMiUS0wrugeqLev04Xi5q2frSrjAiTS5CbFunhOMWyHD693IZPTjYRiyD3rcvA3avSxnQM44VlOfz6jUtDjRJvJEWH4L616cjPjiIW+AbP71a7E8W1vThX1o0LFd28ThtfuWsOVs8bexSfxeZEXbsO1a39qGnt9xD/CxgG96xJw+aVaVNSoD9b3j005X09sXR2DL5+z1za5KDc0HRrTDhZ0oWz5d0jnGUYAJ/3EqVzPUHX79c3M21NGshaTq2z4NV9VWjoGBnJzgAIuRJ1KJUIYTQ7oDPZYHcE7hYbEizGqrw4rFuQELATI8dx6OgzoaCmFwW1vejWkNcRAoZBVHiQz6hCyvRAwDBjiqgcD/Mzldi8Kg1ZiQpwHIeKZi0+PtHo4UBFmR7ERsqwKDsKS2bH+BVx7nCyqGrRwmR1IC9deU0GpG5EHE4X6jv0MFmdyE5SEF2ApxqO4zBgcUAiEtzQ4hgKmem6fjeY7DhR3Amrw4XsRAUW5kRP+HOYrQ4U1PZBa7AiK0nh1Wnb7nDhrx8Wo2mU69tTm+dgVV7gNavOPiPe/bQWDZ0Gr+uAxCg5nnlwfsAxzNcbM2kfcr5ai30Xe6jIbRgioQB56ZHIz46CTCpCn96CPp0Vap0FfToL1HqrX/9eVOB2hXnz5sFuv2o/ffjwYaSmkieOR8NxHHJzc8GyVze1R48eRVLS2ItWX/nKV3DmzJmh3//whz/goYceCugxnnjiCVy6dGno9z/96U+4//77x3xM14Inf/spWI5DZFgQosKCkBQTgrUL4qGQT4+FIWXqIQvcgIiIkYWh/n7TNc+Cvh7QmRw4WtyH0iYdbA4W8UoZ7lyRhtXz4jwalmarA//8uAx1Ezz1lxwTgoc2ZiEvPXJc9rssx6G6pR8l9X0obdSgT3dtC31KRRASlHIkRsuRECVHcnQIUuJC/ZpAsdqd6OwzISo8aFqcE/ecacbO000elysV7gm3tQsSps2mnjKzYBhAqRy5wdZojPT8HiBU4DbzmUmb+OuJa/H+bVMN4JXdFega1bSMi5ThN19eRpzUnwq6NSb8b28VmrrdxbxgqQjxShnilfKhn4lRcsRGesa2jIbv/N6jMrhd72p63ZHpjDt+Ytmc2AmNYBgw21HbpkN77wAEAgYr58bxRs1MNkazA229A2hVDaCtZwBtqgF0a83X5DtOIhYgQelekxpMdjR1G2D2EfskYBgkxciRkaBAflYU5mUqJ2ySmkKZ6TicLhTU9KGmrR8MA6zKi0NOcsS1Pqwpga7fr29m2po00LUcx3Ho0pgwYHJAHixGmFyMkGAxb2S21e6E3miH3mRH/4ANar27MaO+0qBR6y1wujgIBQxmpYRj3QL3YOLoSMGx0tlnxOWaXrSqBmB3uBAXKUNKbChSY0ORGC2HWCREXbsOW4/Wo7nbM35rphAsFWFWcjh6tOZpNxwgFQvhdLEBNy/DZGLMSo3AnJQIzE6NQGRYEE6XduHgxdaA48oCQSQUYGFOFDavTENKbKjH9SzH4WKVCjtPNaJP539Kh1QsRFR4EEKCxWjsNMDpClz8SfEkIyEMi3KisSgneszxmxQKheIPdP3uP3aHCztONqKyWQvmikPmqjzPXmkgOJwsLDan+z/7lZ82F6x2J6LDg5EaG0odODHz9iFaowMXa7QoazZM6vpuOiMLEiE/KwoLc6KRlx7pVWRttTtR1dKPskY1yho1RGdtKnADYDKZsGjRohGXnTt3DkolWaHLx6JFi2AyXZ1k37lzJ3Jzc8d8XPfffz8qKyuHfg80NhUAnn76aRw/fnzo95/+9Kd48sknx3xM1wKniw3IpYly49Db23utD+GGw8VyEEnDEBUe5HW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bGgBpVUj5PS17AUiDnsiJ48aNi/vvvz/OOuusnJ4xadKkeOSRRzrU3KZ+B3Z3hZTf1e8A23VXTpwwYUIi/vWvf53zM2praxPHjO7oOduo34HdXSHld/U7kI80uMFuaK+99mpRuHzve99rcVZ6a95444341a9+1WK8sbGxw+v43e9+F/X19dl4+PDhcfzxx3d4noit58lPmzYtGw8bNiwuuuiiTs0FkK8KKb+nZS8AadATOfGJJ56I0047Le66666c1vjkk0/GaaedFrNnz87pevU7QGHld/U7wHbdlRNPP/30RPzCCy/k3ARxzTXXRF1dXYvxLVu2tHq9+h2gsPK7+h3IRxrcYDf1ta99LRG/9dZbce655yZeL97c4sWL44tf/GJs2LChxWelpaUden4mk4l77rknMXbWWWdFSUlJh+bZ5vvf/36sWLEiG19++eXRr1+/Ts0FkM8KKb/39F4A0qQ7c+KPfvSj+PKXvxyvvfZadqysrCyOOeaYmDp1alxyySUxZcqUOProoxPzLF68OL761a/GD3/4w3b3o34H2KqQ8rv6HWC77siJhx9+eIwfPz4xdvXVV7f6Vp1tMplM/PSnP23xu5ttysrKWh1XvwNsVUj5Xf0O5BsNbrCbOuKII+Izn/lMYuxvf/tbnHjiiXHDDTfEwoULY8OGDVFXVxcLFiyIH/3oR3HKKafE22+/HRERRx55ZOLetn7wbcuzzz4bS5YsycalpaUtvpGQqyeeeCJ+//vfZ+OPf/zjMXny5E7NBZDvCim/9/ReANKku3LiLbfcEr/4xS8SYx/96Edj5syZccstt8SUKVPic5/7XEydOjV++ctfxqOPPhrHHnts4vpbb701fvazn7W5F/U7wHaFlN/V7wDbdVdOvPrqq6OysjIbNzY2xrRp0+Lcc8+NRx99NFatWhUNDQ2xYsWKePjhh+PMM8+MG2+8MSIiBgwYEOPGjWv3Oep3gO0KKb+r34F806unFwD0nO985zuxZMmS+POf/5wdW79+fVx//fVx/fXXt3nfpEmTYsqUKTFnzpzsWJ8+fTr07IcffjgRH3300TFo0KAOzRGxdb3vfTV6VVVVXHrppR2eB6CQFEJ+36Yn9wKQNrs6Jy5atCiuu+66xNgpp5wS11xzTRQXt/79uBEjRsSNN94Y06dPj//93//Njv/sZz+L4447LsaMGZO4Xv0O0FIh5Pfu2gtAPumOnLjPPvvEj3/845g6dWps3rw5Oz537tyYO3dum88oLS2N6667Lm677bZYsGBBdry8vDxxnfodoKVCyO/duReAncUb3GA3VlZWFj//+c9zfrNOUVFRnHfeeXHjjTe2ePVsVVVVzs9tbGyMRx99NDF26qmn5nz/e1199dWxbNmybHzppZfGwIEDOzUXQKEohPy+TU/tBSCNdnVOvP3226OhoSEbjxo1Kq644oo2mx/e+5zLLrss8e3gxsbGuOmmm1pcq34HaKkQ8nt37QUgn3RXTjzmmGPitttuiyFDhuT0nFGjRsVvfvObmDhxYqxbty7x2eDBgxOx+h2gpULI79uo34F8osENdnOlpaVx1VVXxZ133hlHHnlk9OrV8sWOJSUlcfTRR8cdd9wRF110UZSWlkZNTU3imrYKo9Y8//zzUV1dnY379u3bqVeaP/XUU/G73/0uGx9//PFx0kkndXgegEKUz/m9uZ7YC0Ba7cqc+NhjjyXiL37xi9G7d++c1tWrV6+YOnVqYmzWrFmxcePGbKx+B2hbPuf37twLQL7prpw4fvz4mDlzZnzta1+LYcOGtXrN0KFDY+rUqXHffffFwQcfHBERa9eubfM56neAtuVzfu+pvQB0lSNKgYiIOOyww+K2226LmpqaeOWVV2LFihXR2NgYQ4cOjYMOOigGDBiQuP4f//hHIn7f+96X87OefvrpRHzUUUd16lz2yy67LBGPHj06fvOb37R734oVKxLxn/70p1i0aFE2Hjp0aBx33HEdXg9AGuVjfm9Ld+4FIO12dk5cunRprF69OjF27LHHdmhNH/nIR6KioiL7Dd6GhoZ4+eWXY/z48RGhfgfIRT7m9+7aC0A+646c2Ldv3/jmN78Z3/jGN+LVV1+Nt99+O9asWRN9+/aNfffdN0aPHh1FRUXZ6+vr6+PNN9/Mxn369IlBgwZlY/U7QPvyMb/35F4AukKDG5AwYMCAOOKII9q9buHChYl49OjROT+jeQNER3+xus27776biG+44YZOzXP77bcn4gkTJvgBGyg4+ZTf29MdewHIFzsrJ65atSoRV1ZWdvhoibKyshg5cmS89tpr2bHly5dn/139DpC7fMrv7VG/A2zXHTmxqKgoxowZE2PGjNnhdYsWLUocYb3//vsnjq9WvwPkLp/ye3vU70BaOaIU6LBMJhMvvPBCYqy9Ymqb2traWLBgQTYuKiqKSZMm7czlAdBJhZTfu7IXgEKTS05sampKxCUlJZ16Vt++fRNxfX19p+YBoH2FlN/V7wDbdVdOfO655xLx2LFjd/ozANiukPK7+h3oCd7gBrupTCYTa9asiZUrV0ZDQ0McdNBBOd87f/78xDeA999//zbPfW/upZdeSvxydb/99svptbgA5KaQ8ntP7QUgjXZ1Tmz+Np+1a9fGhg0boqKiokPrbH4MXkffEgSwuymk/K5+B9iuu3Li5s2bY+XKlbFy5coYNWpUDBw4MOfnzJ49OxEfeeSROd8LsLsqpPyufgfyjQY32A3V1tbGv/zLv2RfT1tVVRVz5szJ+f77778/EX/0ox/N+d7nn38+EY8fPz7ne5t79dVXO3XfOeecE/PmzcvGM2bMiIkTJ3Z6HQBpUSj5PaJn9wKQNt2RE4cNGxbl5eWxadOm7Nj//d//dei46dWrV8eSJUsSY3vvvXf239XvAEmFkt8j1O8A79VdOfHaa6+NW265JRt/97vfjbPOOiunZ6xYsSLmzp2bjUtLS+Ooo45KXKN+B0gqlPweoX4H8pMjSmE3VFlZmeiir66ujvnz5+d078qVK+P3v/99Ni4qKoozzjgj52e/8sorifjAAw/M+V4AdqyQ8ntP7gUgbbojJ5aVlcWECRMSY/fee2+H1nnvvfdGJpPJxnvvvXfss88+HZoDYHdSSPld/Q6wXXflxP322y8RP/HEEzmv8Ve/+lW2qSEi4sQTT4x+/frlfD/A7qiQ8rv6HchHGtxgNzVp0qREPGPGjHbvaWpqim9/+9uxYcOG7Nixxx4bo0aNyvm5r732WiJuXqQB0DWFlN97ai8AadQdOfHUU09NxLNmzYrHHnssp/UtWbIkfvGLXyTGTj755JzuBdidFVJ+V78DbNcdOfEjH/lIlJSUZOOnn346Fi1a1O5znnnmmcR6ioqK4txzz233PgAKK7+r34F8o8ENdlOnnXZaIv7jH/8YDz/8cJvXb968Ob797W/H008/nR0rLS2Niy66KOdn1tfXx1tvvZUYGzlyZM73A9C+QsrvPbEXgLTqjpx40kknxejRoxNjF110UTz++OM7XNsbb7wRX/ziF2PdunXZsUGDBsUXvvCFHd4HQGHld/U7wHbdkROHDBmSaE7YsmVLXHTRRYmmg+aeffbZ+MY3vhGNjY3ZsU9+8pMxbty4He4HgK0KKb+r34F8o8ENdlMHHXRQfPzjH8/GmUwmLrjggrjqqqti8eLF2fGampq4//774/TTT48HHnggMcfFF1/coSOHli1bFk1NTYmxIUOGdG4DALSqkPJ7T+wFIK26IycWFRXFD3/4w6ioqMiO1dXVxZQpU+LrX/96zJ07N/HL1L///e/xk5/8JD75yU/Gm2++mR0vKSmJa665JiorK7uyZYDdQiHld/U7wHbdlRMvuOCC6NWrVzZ+6aWX4vTTT49HH300Nm7cGBFbGyMWLlwY06dPj3PPPTfWrFmTvX7UqFEaEwA6oJDyu/odyDdFmUwm09OLADqv+TdwX3311ZzvXbNmTXzmM5+JN954o8Vnffr0iaKioja/DXDeeed1+AffefPmxTnnnJONKyoq4vnnn+/QHDvDOeecE/PmzcvGM2bMiIkTJ3b7OgB2RH7fqrv3ArCr5UN+nz17dnzzm9+MTZs2tfr5HnvsERs3boyGhoYWnxUXF8dll10WZ511Vk7PyoX6HcgH8vtW6neg0ORDfr/jjjviiiuuaDFeUlIS/fr1i/Xr1yfe6LPNnnvuGbfddlvsu+++OT0nV+p3IB/I71up34F84g1usBsbOHBg3HbbbXHwwQe3+Gzjxo2tFix9+vSJadOmdapgee+RFhER5eXlHZ4DgPYVUn7v7r0ApFl35cTJkyfHXXfdFe973/ta/XzdunWtNj8MGDAgbr755p3a3AawOyik/K5+B9iuu3LiZz/72bjkkkuitLQ0Md7Y2Bg1NTWtNj+MHz8+7r777p3e3AawOyik/K5+B/KJBjfYzQ0fPjzuuuuuuPjii2P48OFtXldRURGf/vSn46GHHoqzzz67U89qXgSVlZV1ah4A2ldI+b079wKQdt2VE8eNGxePPPJITJs2rd1fig4fPjymTp0as2bNimOOOabDzwKgsPK7+h1gu+7KiZ/73Ofi3nvvjRNOOCFKSkravG7cuHHxgx/8IO68887Yc889O/wcALYqpPyufgfyhSNKgaxMJhOvvfZaLFiwIFavXh1NTU3Rv3//2H///ePggw/WkAaQpwopvxfSXgC6qjtz4rvvvhsvvvhiVFdXx7p166Jv374xaNCg+MAHPuCtDwA7WSHld/U7wHbdlRPXr18ff/3rX+Odd96JdevWRZ8+fWLYsGHxoQ99aIeNCwB0TiHld/U7kGYa3AAAAAAAAAAAAEglR5QCAAAAAAAAAACQShrcAAAAAAAAAAAASCUNbgAAAAAAAAAAAKSSBjcAAAAAAAAAAABSSYMbAAAAAAAAAAAAqaTBDQAAAAAAAAAAgFTS4AYAAAAAAAAAAEAqaXADAAAAAAAAAAAglTS4AQAAAAAAAAAAkEoa3AAAAAAAAAAAAEglDW4AAAAAAAAAAACkkgY3AAAAAAAAAAAAUkmDGwAAAAAAAAAAAKmkwQ0AAAAAAAAAAIBU0uAGAAAAAAAAAABAKmlwAwAAAAAAAAAAIJU0uAEAAAAAAAAAAJBKGtwAAAAAAAAAAABIJQ1uAAAAAAAAAAAApJIGNwAAAAAAAAAAAFJJgxsAAAAAAAAAAACppMENAAAAAAAAAACAVNLgBgAAAAAAAAAAQCppcAMAAAAAAAAAACCVNLgBAAAAAAAAAACQShrcAAAAAAAAAAAASCUNbgAAAAAAAAAAAKSSBjcAAAAAAAAAAABSSYMbAAAAAAAAAAAAqaTBDQAAAAAAAAAAgFTS4AYAAAAAAAAAAEAqaXADAAAAAAAAAAAglTS4AQAAAAAAAAAAkEoa3AAAAAAAAAAAAEglDW4AAAAAAAAAAACkkgY3AAAAAAAAAAAAUun/AXO1MmDnMl95AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 3000x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plot((trainResults['Pred']),df_for_training.iloc[-min_length_train:,-2])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plot((validResults['Pred']),validResults[\"Actual\"])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<Figure size 3000x900 with 1 Axes>, <Axes: >)"
      ]
     },
     "execution_count": 183,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 3000x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot((testResults['Pred']),df_for_testing.iloc[-min_length_test:,-2])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
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