merf_testing.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np \n",
    "import pandas as pd \n",
    "from glob import glob\n",
    "import json\n",
    "\n",
    "from merf import MERF\n",
    "from sklearn.model_selection import train_test_split, KFold\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "\n",
    "from merf.viz import plot_merf_training_stats\n",
    "from sklearn.inspection import plot_partial_dependence\n",
    "# import shap\n",
    "import math\n",
    "\n",
    "import seaborn as sns\n",
    "from matplotlib import cm\n",
    "from matplotlib.colors import ListedColormap\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from sklearn.metrics import r2_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def _get_Z_matrix(Z_values=np.array, Z_vars=list):\n",
    "    '''\n",
    "        calculate Z matrix from input variables and selected random effects\n",
    "    '''\n",
    "    for i in range(len(Z_vars)):\n",
    "        Z_vars_array = Z_values[Z_vars[i]].unique()\n",
    "        if i == 0:\n",
    "            # Z_vars_array = Z_values[Z_vars[i]].unique()\n",
    "            Z_df = pd.DataFrame(data=0, columns=Z_vars_array, index=Z_values.index)\n",
    "        # else:\n",
    "            # Z_vars_array = np.append(Z_vars_array, Z_values[Z_vars[i]].unique())\n",
    "        for col in Z_vars_array:\n",
    "            Z_df[col] = np.where(Z_values[Z_vars[i]] == col, 1, 0)\n",
    "\n",
    "    return(Z_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_merf_model(train, Z_vars:list=['SEASON', 'HUC04'], clusters:str='HUC08'):\n",
    "\n",
    "    rf_fe_b = RandomForestRegressor(n_estimators = 1000, random_state = 42)\n",
    "\n",
    "    mrf = MERF(rf_fe_b, max_iterations=10)\n",
    "    X_train = train[['PRECIP', 'MAX_TMP', 'PR_AG', 'PR_INT', 'PR_NAT']]\n",
    "    clusters_train = train[clusters]\n",
    "    y_train = train['LOG_PR_WATER']\n",
    "\n",
    "    if Z_vars is None:\n",
    "        Z_train = np.ones((len(X_train), 1))\n",
    "    else:\n",
    "        Z_values = train[Z_vars]\n",
    "        Z_train = _get_Z_matrix(Z_values, Z_vars)\n",
    "\n",
    "    mrf.fit(X_train, Z_train, clusters_train, y_train)\n",
    "\n",
    "    return(mrf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_dswe_split():\n",
    "    dswe = pd.read_csv('../data/all_data_0118_p2.csv', index_col=0)\n",
    "    # dswe['MAX_TMP'] = dswe['MAX_TMP'] * -1\n",
    "    # dswe['MIN_TMP'] = dswe['MIN_TMP'] * -1\n",
    "    # dswe['PRECIP'] = dswe['PRECIP'] * -1\n",
    "    dswe['HUC_SEASON'] = dswe['HUC08'].astype('str') + '_' + dswe['SEASON']\n",
    "\n",
    "    # dswe = dswe.rename(columns={\"PR_WATER\": \"LOG_PR_WATER\"})\n",
    "    dswe['LOG_PR_WATER'] = np.log(dswe['PR_WATER'] + 10e-6)\n",
    "\n",
    "    # center and standardize independent variables\n",
    "    dswe['MAX_TMP'] = (dswe['MAX_TMP'] - np.mean(dswe['MAX_TMP'])) / np.std(dswe['MAX_TMP'])\n",
    "    dswe['PRECIP'] = (dswe['PRECIP'] - np.mean(dswe['PRECIP'])) / np.std(dswe['PRECIP'])\n",
    "\n",
    "    dswe['PR_AG'] = (dswe['PR_AG'] - np.mean(dswe['PR_AG'])) / np.std(dswe['PR_AG'])\n",
    "    dswe['PR_NAT'] = (dswe['PR_NAT'] - np.mean(dswe['PR_NAT'])) / np.std(dswe['PR_NAT'])\n",
    "    dswe['PR_INT'] = (dswe['PR_INT'] - np.mean(dswe['PR_INT'])) / np.std(dswe['PR_INT'])\n",
    "\n",
    "    dswe['HUC04'] = dswe['HUC08'].apply(lambda x: str(x)[0:3].zfill(4))\n",
    "\n",
    "    train, test = train_test_split(dswe, test_size=0.2, shuffle=True)\n",
    "\n",
    "    return(train, test, dswe)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "dswe = pd.read_csv('../data/all_data_0118_p2.csv', index_col=0)\n",
    "# dswe['MAX_TMP'] = dswe['MAX_TMP'] * -1\n",
    "# dswe['MIN_TMP'] = dswe['MIN_TMP'] * -1\n",
    "# dswe['PRECIP'] = dswe['PRECIP'] * -1\n",
    "dswe['HUC_SEASON'] = dswe['HUC08'].astype('str') + '_' + dswe['SEASON']\n",
    "\n",
    "# dswe = dswe.rename(columns={\"PR_WATER\": \"LOG_PR_WATER\"})\n",
    "dswe['LOG_PR_WATER'] = np.log(dswe['PR_WATER'] + 10e-6)\n",
    "\n",
    "# center and standardize independent variables\n",
    "dswe['MAX_TMP'] = (dswe['MAX_TMP'] - np.mean(dswe['MAX_TMP'])) / np.std(dswe['MAX_TMP'])\n",
    "dswe['PRECIP'] = (dswe['PRECIP'] - np.mean(dswe['PRECIP'])) / np.std(dswe['PRECIP'])\n",
    "\n",
    "dswe['PR_AG'] = (dswe['PR_AG'] - np.mean(dswe['PR_AG'])) / np.std(dswe['PR_AG'])\n",
    "dswe['PR_NAT'] = (dswe['PR_NAT'] - np.mean(dswe['PR_NAT'])) / np.std(dswe['PR_NAT'])\n",
    "dswe['PR_INT'] = (dswe['PR_INT'] - np.mean(dswe['PR_INT'])) / np.std(dswe['PR_INT'])\n",
    "\n",
    "dswe['HUC04'] = dswe['HUC08'].apply(lambda x: str(x)[0:3].zfill(4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "train, test = get_dswe_split()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_test = test[['PRECIP', 'MAX_TMP', 'PR_AG', 'PR_INT', 'PR_NAT']]\n",
    "clusters_test = test['HUC08']\n",
    "y_test = test['LOG_PR_WATER']\n",
    "\n",
    "X_train = train[['PRECIP', 'MAX_TMP', 'PR_AG', 'PR_INT', 'PR_NAT']]\n",
    "clusters_train = train['HUC08']\n",
    "y_train = train['LOG_PR_WATER']\n",
    "\n",
    "X_full = dswe[['PRECIP', 'MAX_TMP', 'PR_AG', 'PR_INT', 'PR_NAT']]\n",
    "clusters_full = dswe['HUC08']\n",
    "y_full = dswe['LOG_PR_WATER']\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### HUC04 and SEASONs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO     [merf.py:307] Training GLL is -48513.9673446295 at iteration 1.\n",
      "INFO     [merf.py:307] Training GLL is -73859.9717182374 at iteration 2.\n",
      "INFO     [merf.py:307] Training GLL is -76667.53289076487 at iteration 3.\n",
      "INFO     [merf.py:307] Training GLL is -77308.13980618764 at iteration 4.\n",
      "INFO     [merf.py:307] Training GLL is -77800.32564844814 at iteration 5.\n",
      "INFO     [merf.py:307] Training GLL is -78325.23185246756 at iteration 6.\n",
      "INFO     [merf.py:307] Training GLL is -78813.73017845998 at iteration 7.\n",
      "INFO     [merf.py:307] Training GLL is -79241.74750342646 at iteration 8.\n",
      "INFO     [merf.py:307] Training GLL is -79745.16230945759 at iteration 9.\n",
      "INFO     [merf.py:307] Training GLL is -80134.49555627009 at iteration 10.\n"
     ]
    }
   ],
   "source": [
    "mrf_huc4_seasons = get_merf_model(train=train, Z_vars=['SEASON', 'HUC04'], clusters='HUC08')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\mdgaines\\.conda\\envs\\dswe\\lib\\site-packages\\merf\\viz.py:65: UserWarning: To output multiple subplots, the figure containing the passed axes is being cleared.\n",
      "  model.trained_b.hist(bins=15, ax=ax)\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1080x1080 with 37 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_merf_training_stats(mrf_huc4_seasons, num_clusters_to_plot=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "Z_vars_huc4_seasons = ['SEASON', 'HUC04']\n",
    "Z_values_huc4_seasons = test[Z_vars_huc4_seasons]\n",
    "Z_test_huc4_seasons = _get_Z_matrix(Z_values_huc4_seasons, Z_vars_huc4_seasons)\n",
    "\n",
    "y_hat_huc4_seasons = mrf_huc4_seasons.predict(X_test, Z_test_huc4_seasons, clusters_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MSE: 0.16653550116127572\n",
      "RMSPE: 40.80876145649066\n",
      "MPE: -1.6071347948591594\n",
      "R2: 0.9435891223004472\n"
     ]
    }
   ],
   "source": [
    "mse_test_huc4_seasons = np.mean((y_test - y_hat_huc4_seasons) ** 2)\n",
    "print('MSE:', mse_test_huc4_seasons)\n",
    "\n",
    "rmspe_test_huc4_seasons = math.sqrt(np.mean( (y_test - y_hat_huc4_seasons) ** 2)) * 100\n",
    "print('RMSPE:', rmspe_test_huc4_seasons)\n",
    "\n",
    "mpe_test_huc4_seasons = np.mean(((y_test-y_hat_huc4_seasons) / y_test) * 100)\n",
    "print('MPE:', mpe_test_huc4_seasons)\n",
    "\n",
    "r2_test_huc4_seasons = r2_score(y_test, y_hat_huc4_seasons)\n",
    "print('R2:', r2_test_huc4_seasons)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MSE: 0.0063573636512287545\n",
      "RMSPE: 7.973307752262391\n",
      "MPE: -0.15069757784814003\n",
      "R2: 0.9978448984361983\n"
     ]
    }
   ],
   "source": [
    "Z_vars_huc4_seasons = ['SEASON', 'HUC04']\n",
    "Z_values_huc4_seasons = train[Z_vars_huc4_seasons]\n",
    "Z_train_huc4_seasons = _get_Z_matrix(Z_values_huc4_seasons, Z_vars_huc4_seasons)\n",
    "\n",
    "y_hat_train_huc4_seasons = mrf_huc4_seasons.predict(X_train, Z_train_huc4_seasons, clusters_train)\n",
    "\n",
    "mse_train_huc4_seasons = np.mean((y_train - y_hat_train_huc4_seasons) ** 2)\n",
    "print('MSE:', mse_train_huc4_seasons)\n",
    "\n",
    "rmspe_train_huc4_seasons = math.sqrt(np.mean( (y_train - y_hat_train_huc4_seasons) ** 2)) * 100\n",
    "print('RMSPE:', rmspe_train_huc4_seasons)\n",
    "\n",
    "mpe_train_huc4_seasons = np.mean(((y_train-y_hat_train_huc4_seasons) / y_train) * 100)\n",
    "print('MPE:', mpe_train_huc4_seasons)\n",
    "\n",
    "r2_train_huc4_seasons = r2_score(y_train, y_hat_train_huc4_seasons)\n",
    "print('R2:', r2_train_huc4_seasons)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "Z_vars_huc4_seasons = ['SEASON', 'HUC04']\n",
    "Z_values_huc4_seasons = dswe[Z_vars_huc4_seasons]\n",
    "Z_full_huc4_seasons = _get_Z_matrix(Z_values_huc4_seasons, Z_vars_huc4_seasons)\n",
    "\n",
    "y_hat_full_huc4_seasons = mrf_huc4_seasons.predict(X_full, Z_full_huc4_seasons, clusters_full)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MSE: 0.09044550108399235\n",
      "RMSPE: 30.074158522557592\n",
      "MPE: -1.2591310000096079\n",
      "R2: 0.9693450898896866\n"
     ]
    }
   ],
   "source": [
    "mse_full_huc4_seasons = np.mean((y_full - y_hat_full_huc4_seasons) ** 2)\n",
    "print('MSE:', mse_full_huc4_seasons)\n",
    "\n",
    "rmspe_full_huc4_seasons = math.sqrt(np.mean( (y_full - y_hat_full_huc4_seasons) ** 2)) * 100\n",
    "print('RMSPE:', rmspe_full_huc4_seasons)\n",
    "\n",
    "mpe_full_huc4_seasons = np.mean(((y_full-y_hat_full_huc4_seasons) / y_full) * 100)\n",
    "print('MPE:', mpe_full_huc4_seasons)\n",
    "\n",
    "r2_full_huc4_seasons = r2_score(y_full, y_hat_full_huc4_seasons)\n",
    "print('R2:', r2_full_huc4_seasons)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SEASONS only"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO     [merf.py:307] Training GLL is -49203.65174852348 at iteration 1.\n",
      "INFO     [merf.py:307] Training GLL is -74277.71941657495 at iteration 2.\n",
      "INFO     [merf.py:307] Training GLL is -76532.19288493694 at iteration 3.\n",
      "INFO     [merf.py:307] Training GLL is -76697.36022609127 at iteration 4.\n",
      "INFO     [merf.py:307] Training GLL is -76853.53421506009 at iteration 5.\n",
      "INFO     [merf.py:307] Training GLL is -76939.0944660035 at iteration 6.\n",
      "INFO     [merf.py:307] Training GLL is -77051.84452042519 at iteration 7.\n",
      "INFO     [merf.py:307] Training GLL is -77137.97646958844 at iteration 8.\n",
      "INFO     [merf.py:307] Training GLL is -77256.22001110065 at iteration 9.\n",
      "INFO     [merf.py:307] Training GLL is -77311.3301955911 at iteration 10.\n"
     ]
    }
   ],
   "source": [
    "mrf_seasons = get_merf_model(train=train, Z_vars=['SEASON'], clusters='HUC08')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\mdgaines\\.conda\\envs\\dswe\\lib\\site-packages\\merf\\viz.py:65: UserWarning: To output multiple subplots, the figure containing the passed axes is being cleared.\n",
      "  model.trained_b.hist(bins=15, ax=ax)\n",
      "c:\\Users\\mdgaines\\.conda\\envs\\dswe\\lib\\site-packages\\IPython\\core\\pylabtools.py:151: UserWarning: tight_layout not applied: number of rows in subplot specifications must be multiples of one another.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1080x1080 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_merf_training_stats(mrf_seasons)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "Z_vars_seasons = ['SEASON']\n",
    "Z_values_seasons = test[Z_vars_seasons]\n",
    "Z_test_seasons = _get_Z_matrix(Z_values_seasons, Z_vars_seasons)\n",
    "\n",
    "y_hat_seasons = mrf_seasons.predict(X_test, Z_test_seasons, clusters_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MSE: 0.11035450803161512\n",
      "RMSPE: 33.21964900952674\n",
      "MPE: -0.5498684188398779\n",
      "R2: 0.9626194138021228\n"
     ]
    }
   ],
   "source": [
    "mse_test_seasons = np.mean((y_test - y_hat_seasons) ** 2)\n",
    "print('MSE:', mse_test_seasons)\n",
    "\n",
    "rmspe_test_seasons = math.sqrt(np.mean( (y_test - y_hat_seasons) ** 2)) * 100\n",
    "print('RMSPE:', rmspe_test_seasons)\n",
    "\n",
    "mpe_test_seasons = np.mean(((y_test-y_hat_seasons) / y_test) * 100)\n",
    "print('MPE:', mpe_test_seasons)\n",
    "\n",
    "r2_test_seasons = r2_score(y_test, y_hat_seasons)\n",
    "print('R2:', r2_test_seasons)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MSE: 0.006397536904264509\n",
      "RMSPE: 7.998460417020584\n",
      "MPE: -0.15898671141698728\n",
      "R2: 0.9978312799859743\n"
     ]
    }
   ],
   "source": [
    "Z_vars_seasons = ['SEASON']\n",
    "Z_values_seasons = train[Z_vars_seasons]\n",
    "Z_train_seasons = _get_Z_matrix(Z_values_seasons, Z_vars_seasons)\n",
    "\n",
    "y_hat_train_seasons = mrf_seasons.predict(X_train, Z_train_seasons, clusters_train)\n",
    "\n",
    "mse_train_seasons = np.mean((y_train - y_hat_train_seasons) ** 2)\n",
    "print('MSE:', mse_train_seasons)\n",
    "\n",
    "rmspe_train_seasons = math.sqrt(np.mean( (y_train - y_hat_train_seasons) ** 2)) * 100\n",
    "print('RMSPE:', rmspe_train_seasons)\n",
    "\n",
    "mpe_train_seasons = np.mean(((y_train-y_hat_train_seasons) / y_train) * 100)\n",
    "print('MPE:', mpe_train_seasons)\n",
    "\n",
    "r2_train_seasons = r2_score(y_train, y_hat_train_seasons)\n",
    "print('R2:', r2_train_seasons)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MSE: 0.04672436511858332\n",
      "RMSPE: 21.615819465979847\n",
      "MPE: -0.34055588390065417\n",
      "R2: 0.9841635991231725\n"
     ]
    }
   ],
   "source": [
    "Z_vars_seasons = ['SEASON']\n",
    "Z_values_seasons = dswe[Z_vars_seasons]\n",
    "Z_full_seasons = _get_Z_matrix(Z_values_seasons, Z_vars_seasons)\n",
    "\n",
    "y_hat_full_seasons = mrf_seasons.predict(X_full, Z_full_seasons, clusters_full)\n",
    "\n",
    "mse_full_seasons = np.mean((y_full - y_hat_full_seasons) ** 2)\n",
    "print('MSE:', mse_full_seasons)\n",
    "\n",
    "rmspe_full_seasons = math.sqrt(np.mean( (y_full - y_hat_full_seasons) ** 2)) * 100\n",
    "print('RMSPE:', rmspe_full_seasons)\n",
    "\n",
    "mpe_full_seasons = np.mean(((y_full-y_hat_full_seasons) / y_full) * 100)\n",
    "print('MPE:', mpe_full_seasons)\n",
    "\n",
    "r2_full_seasons = r2_score(y_full, y_hat_full_seasons)\n",
    "print('R2:', r2_full_seasons)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### HUCs only"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO     [merf.py:307] Training GLL is -59944.2757745281 at iteration 1.\n",
      "INFO     [merf.py:307] Training GLL is -66752.23327521556 at iteration 2.\n",
      "INFO     [merf.py:307] Training GLL is -66856.34154875141 at iteration 3.\n",
      "INFO     [merf.py:307] Training GLL is -66962.16706377898 at iteration 4.\n",
      "INFO     [merf.py:307] Training GLL is -67044.07261865486 at iteration 5.\n",
      "INFO     [merf.py:307] Training GLL is -67134.69230331128 at iteration 6.\n",
      "INFO     [merf.py:307] Training GLL is -67265.29800029552 at iteration 7.\n",
      "INFO     [merf.py:307] Training GLL is -67355.83144608412 at iteration 8.\n",
      "INFO     [merf.py:307] Training GLL is -67478.64191993432 at iteration 9.\n",
      "INFO     [merf.py:307] Training GLL is -67592.05594933413 at iteration 10.\n"
     ]
    }
   ],
   "source": [
    "mrf_hucs = get_merf_model(train=train, Z_vars=None, clusters='HUC08')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1080x1080 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_merf_training_stats(mrf_hucs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Z_vars_hucs = None\n",
    "# Z_values_hucs = test[Z_vars_hucs]\n",
    "# Z_test_hucs = _get_Z_matrix(Z_values_hucs, Z_vars_hucs)\n",
    "Z_test_hucs = np.ones((len(X_test), 1))\n",
    "\n",
    "y_hat_hucs = mrf_hucs.predict(X_test, Z_test_hucs, clusters_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MSE: 0.0696387957169545\n",
      "RMSPE: 26.389163631489822\n",
      "MPE: -0.4751716019719059\n",
      "R2: 0.9764111221875211\n"
     ]
    }
   ],
   "source": [
    "mse_test_hucs = np.mean((y_test - y_hat_hucs) ** 2)\n",
    "print('MSE:', mse_test_hucs)\n",
    "\n",
    "rmspe_test_hucs = math.sqrt(np.mean( (y_test - y_hat_hucs) ** 2)) * 100\n",
    "print('RMSPE:', rmspe_test_hucs)\n",
    "\n",
    "mpe_test_hucs = np.mean(((y_test-y_hat_hucs) / y_test) * 100)\n",
    "print('MPE:', mpe_test_hucs)\n",
    "\n",
    "r2_test_hucs = r2_score(y_test, y_hat_hucs)\n",
    "print('R2:', r2_test_hucs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MSE: 0.009360273397991566\n",
      "RMSPE: 9.674850592123667\n",
      "MPE: -0.212449538882645\n",
      "R2: 0.9968269331527505\n"
     ]
    }
   ],
   "source": [
    "Z_train_hucs = np.ones((len(X_train), 1))\n",
    "\n",
    "y_hat_train_hucs = mrf_hucs.predict(X_train, Z_train_hucs, clusters_train)\n",
    "\n",
    "mse_train_hucs = np.mean((y_train - y_hat_train_hucs) ** 2)\n",
    "print('MSE:', mse_train_hucs)\n",
    "\n",
    "rmspe_train_hucs = math.sqrt(np.mean( (y_train - y_hat_train_hucs) ** 2)) * 100\n",
    "print('RMSPE:', rmspe_train_hucs)\n",
    "\n",
    "mpe_train_hucs = np.mean(((y_train-y_hat_train_hucs) / y_train) * 100)\n",
    "print('MPE:', mpe_train_hucs)\n",
    "\n",
    "r2_train_hucs = r2_score(y_train, y_hat_train_hucs)\n",
    "print('R2:', r2_train_hucs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MSE: 0.021416506064748736\n",
      "RMSPE: 14.63437940766493\n",
      "MPE: -0.26499625365667573\n",
      "R2: 0.9927412523517098\n"
     ]
    }
   ],
   "source": [
    "Z_full_hucs = np.ones((len(X_full), 1))\n",
    "\n",
    "y_hat_full_hucs = mrf_hucs.predict(X_full, Z_full_hucs, clusters_full)\n",
    "\n",
    "mse_full_hucs = np.mean((y_full - y_hat_full_hucs) ** 2)\n",
    "print('MSE:', mse_full_hucs)\n",
    "\n",
    "rmspe_full_hucs = math.sqrt(np.mean( (y_full - y_hat_full_hucs) ** 2)) * 100\n",
    "print('RMSPE:', rmspe_full_hucs)\n",
    "\n",
    "mpe_full_hucs = np.mean(((y_full-y_hat_full_hucs) / y_full) * 100)\n",
    "print('MPE:', mpe_full_hucs)\n",
    "\n",
    "r2_full_hucs = r2_score(y_full, y_hat_full_hucs)\n",
    "print('R2:', r2_full_hucs)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### HUC08_SEASON Hardcoded"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO     [merf.py:307] Training GLL is -49200.247449862334 at iteration 1.\n",
      "INFO     [merf.py:307] Training GLL is -73834.35044505846 at iteration 2.\n",
      "INFO     [merf.py:307] Training GLL is -75695.57496798407 at iteration 3.\n",
      "INFO     [merf.py:307] Training GLL is -75819.96238753876 at iteration 4.\n",
      "INFO     [merf.py:307] Training GLL is -75907.16729846239 at iteration 5.\n",
      "INFO     [merf.py:307] Training GLL is -75960.44912415657 at iteration 6.\n",
      "INFO     [merf.py:307] Training GLL is -75956.72176451168 at iteration 7.\n",
      "INFO     [merf.py:307] Training GLL is -75966.85979999036 at iteration 8.\n",
      "INFO     [merf.py:307] Training GLL is -76049.37299363801 at iteration 9.\n",
      "INFO     [merf.py:307] Training GLL is -76085.28363082188 at iteration 10.\n"
     ]
    }
   ],
   "source": [
    "mrf_huc_szn = get_merf_model(train=train, Z_vars=None, clusters='HUC_SEASON')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABDAAAAQwCAYAAAATlK4WAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAEAAElEQVR4nOzdeXycZb3//9dnlmQmyyRNk6aZ7nublLZI2VSwLEIRjsARDuA5iB6VI4I/zzl+j8f1uB/39biiIuKGHvQgR0FWI3KUfW1DoSttmnRNmz2TzMz1+2PupJM03Se5J8n76WOcmete5jMXbWfyznVflznnEBERERERERHJZwG/CxARERERERERORIFGCIiIiIiIiKS9xRgiIiIiIiIiEjeU4AhIiIiIiIiInlPAYaIiIiIiIiI5D0FGCIiIiIiIiKS9xRgiIiIiIhMMGb292Z2n9919DOz2WbmzCx0jMd93Mx+OlJ1+cHM1prZKr/rEMlHCjBEJK+Y2dVm9piZdZrZLu/xuy3jVjP79CGOc2Y2f7TrFRERyVdm9loz+4uZtZpZi5n9n5mdCuCc+5lz7gK/a/STmb3VzB4Zxdc75PeYbM65Oudc/SiUJDLmKMAQkbxhZu8Dvg58EZgKVAPvAl4DFPhYmoiIyJhiZjHgd8B/ARXANOATQMLPuuTQjnX0ichEpABDRPKCmZUBnwTe7Zy7wznX7jKecc79vXNOX7hERESO3kIA59wvnHMp51y3c+4+59zzcPDoAzO7wMxe8kZrfNvM/mRm78ja9//M7Ktmtt/MNpnZq732bd6IyeuyznWxmT1jZm3e9o8fQ93/aGZNZtbs/WLjaBSY2W1m1u5dfrEyq5YPmNlGb1uDmV3utS8BvgucaWYdZrZ/uBObWb2ZfdobydJhZv9rZpPN7Gfe+3vCzGZn7b/YzO73Rry8ZGZ/57VfD/w98P7+83jtW8zs383seaDTzEJe2/ne9qCZfSjrPTxlZjO8kalf9fq+1cyeN7Olx9DPImOSAgwRyRdnAoXAb/0uREREZBx4GUiZ2Y/N7CIzm3SoHc2sErgD+CAwGXgJePWQ3U4Hnve2/xy4HTgVmA/8A/BNMyvx9u0E3gKUAxcDN5jZZUdZ9znAAuAC4AP9P8gfwRu9esqBu4BvZm3bCJwFlJEZgfJTM6txzr1IZpTnX51zJc658sOc/2rgWjKjWOYBfwV+RGZky4vAxwDMrBi4n0z/TAGuAb5tZnXOuZuBnwFf8F7vb7LOfw2Zfip3ziWHvPa/etvfAMSAfwS6vP45m0xQVQ5cBew9Qj+JjHkKMEQkX1QCe7I/uL3fduw3s24zO9vH2kRERMYU51wb8FrAAd8HdpvZXWZWPczubwDWOud+430OfwPYMWSfzc65HznnUsAvgRnAJ51zCefcfUAvmTAD51y9c+4F51zaG/HxC+B1R1n6J5xznc65F8iEBNccxTGPOOfu9mr7CbA8qx/+2znX5NXyS2A9cNpR1tLvR865jc65VuAeYKNz7gGvr/4bONnb7xJgi9dPSefc08CvgSuOcP5vOOe2Oee6h9n2DuAjzrmXvJGpzznn9gJ9QCmwGDDn3IvOueZjfF8iY44CDBHJF3uByuzrP51zr/Z+I7IX/XslIiJyTLwfat/qnJsOLAXiwNeG2TUObMs6zgGNQ/bZmfW429tvaFsJgJmdbmZ/NLPdZtZKZqRD5VGWvS3r8StebUeSHbZ0AZH+7xNm9hYze9b7hch+Mv1wtLX0G/o+h33fwCzg9P7X8l7v78nM63U42w6zbQaZUSSDOOceIjPS5FvATjO72Zv3RGRc0w8EIpIv/kpmYrFL/S5ERERkvHHOrQNuJfMD/FDNwPT+J2Zm2c+Pw8/JXMoxwzlXRmauCTvKY2dkPZ4JNB1vEWY2i8zok5uAyd4vRdZk1eKO99yHsA34k3OuPOtW4py74Qivd7g6tpG5bOXgg5z7hnPuFKCOzKUk/3a8hYuMFQowRCQvOOf2k7k29dtmdoWZlZhZwMxWAMVZuwbNLJJ1y16dpGDItuAovgUREZG84U0m+T4zm+49n0HmcoxHh9n998BJZnaZN3LhRo48auBwSoEW51yPmZ0GvPkYjv2omRWZWR3wNjKXqxyvYjLhwG4AM3sbgwOcncD0Id8lTsTvgIVmdq2Zhb3bqd6Eof2vN/cYz/kD4FNmtsCbuHOZN4noqd5IlzCZOUd6gFSO3odI3lKAISJ5wzn3BTKTVb0f2EXmg/57wL8Df/F2+wCZ4Zr9t4eyTrF2yLa3jUrhIiIi+aedzMSbj5lZJ5ngYg1w0Moezrk9wJXAF8hctlkLPMnxL7n6buCTZtYO/Afwq2M49k/ABuBB4Eve/BrHxTnXAHyZzCjPncBJwP9l7fIQme8OO8xsz/G+TtbrtZOZXPNqMiNHdgCfJzNJOcAPgVrv8pI7j/K0XyHTf/cBbd45omQm9Pw+sI/MpTZ7gS+d6HsQyXeWucRNREREREQEzCxAZg6Mv3fO/dHvekRE+mkEhoiIiIjIBGdmF5pZuZkVAh8iM0/EcJebiIj4RgGGiIiIiIicSWa1iz3A3wCXHWJZz+NmZn9vZh3D3NYe4bh7DnHch3JZn4jkP11CIiIiIiIiIiJ5TyMwRERERERERCTvhfwuIN9UVla62bNn5/y8nZ2dFBcXH3lHySn1uz/U7/5Qv/tD/T7YU089tcc5V+V3HSNtJL4v6M9Sbqk/c099mnvq09xTn+bWSPXn8X5fUIAxxOzZs3nyySdzft76+npWrVqV8/PK4anf/aF+94f63R/q98HM7BW/axgNI/F9QX+Wckv9mXvq09xTn+ae+jS3Rqo/j/f7gi4hEREREREREZG8pwBDRERERERERPKeAgwRERERERERyXuaA0NERERERETyVl9fH42NjfT09Bxx37KyMl588cVRqGpiONH+jEQiTJ8+nXA4nJN6FGCIiIiIiIhI3mpsbKS0tJTZs2djZofdt729ndLS0lGqbPw7kf50zrF3714aGxuZM2dOTurRJSQiIiIiIiKSt3p6epg8efIRwwvJL2bG5MmTj2rkzNFSgCEiIiIiIiJ5TeHF2JTr/24KMEREREREREQk7ynAEBEREREREZG8pwBDRERExi0zu8XMdpnZmkNsNzP7hpltMLPnzexVo12jiIiMLR//+Mf50pe+dMjtd955Jw0NDYPa/vmf/5mHH34YgN/97necfPLJLF++nNraWr73ve8B8N3vfpfbbrtt5Ao/hLe+9a3ccccdB7W/8MILvOtd7xr1eg5Hq5CIiIjIeHYr8E3gUN8ILwIWeLfTge949yIiIsflzjvv5JJLLqG2thaAlpYWHn30Ub72ta/R19fH9ddfz+OPP8706dNJJBJs2bIFIO/CgpNOOommpia2bt3KzJkz/S4HUIAx4ra1dPGeXzzDOVOSrPK7GBERkQnGOfewmc0+zC6XArc55xzwqJmVm1mNc655dCqEro5WXvn6RbSVnwWrVo3Wy4qIjEmf+N+1NDS1HXJ7KpUiGAwe0zlr4zE+9jd1h93nM5/5DLfddhszZsygqqqKU045hY0bN3LjjTeye/duioqK+P73v09LSwt33XUXf/rTn/j0pz/Nr3/9ax588EFWr14NZJYlTSaTTJ48GYDCwkIWLVoEZEZ2lJSU8P/+3//jiSee4O1vfzvFxcW89rWv5Z577mHNmjXceuut3HnnnaRSKdasWcP73vc+ent7+clPfkJhYSF33303FRUVfP/73+fmm2+mt7eX+fPn85Of/ISioqJDvr8HHniAr3/96+zcuZOvfOUrXHLJJQCsXr2a22+/nfe///3H1KcjRQHGCJtcUsBzjfuZVRD2uxQRERE52DRgW9bzRq/toADDzK4Hrgeorq6mvr4+JwW4dJqTe1+hqTV35xTo6OhQf+aY+jT31KdHp6ysjPb2dgD6evtIpVKH3Nc5d9jtw+nr7Rs4/3CeeeYZfv7zn/Pwww+TTCY566yzWLp0KW9/+9v56le/yvz583niiSf4p3/6J373u99x0UUXsXr1ai677DIA6uvrueyyy2hvbyccDnPRRRcxc+ZMXve617F69WquvPJKAoEAiUSCcDhMe3s71113Hd/4xjc4/fTT+djHPkY6naa9vZ2enh6ef/55HnnkERKJBCtWrOATn/gEDz/8MB/4wAe4+eabufHGG3n961/P1VdfDcAnP/lJvvWtbx1yhEdfXx+NjY387ne/Y9OmTVxyySU8++yzRCIRli9fzte//nVuuOGGY+rTbD09PTn7c64AY4QVFYSYW1nM1vbcrX0rIiIiOTPc+m5uuB2dczcDNwOsXLnSrcrhaImGv85mSnI7J2kERs7U19eTy/9Goj4dCerTo/Piiy9SWloKwKfftOKw+7a3tw/smytPP/00b3rTm6iurgbgsssuwznHY489xtve9raB/RKJBKWlpYTDYaLR6EAde/bsYebMmQPPf/zjH/PCCy/wwAMP8K1vfYtHHnmEW2+9lcLCQgoLC0mlUnR2dnL++ecDmTkq7rvvPkpLS4lEIpx33nnE43EgE+5ceeWVlJaWcsopp/D8889TWlrK008/zbXXXsv+/fvp6OjgwgsvPGS/hMNh3vzmN1NWVsbJJ5/MvHnz2L59OytWrKC6uppdu3adUJ9GIhFOPvnk4z4+mwKMUVAbL+MvL3X5XYaIiIgcrBGYkfV8OtA02kW0x+axeM8DuHQaC2iOdRGRfGM2OO9Op9OUl5fz7LPPHvHYaDRKT8/gX2ifdNJJnHTSSVx77bXMmTOHW2+9dWBb5qrGQyssLBx4HAgEBp4HAgGSySSQCT3uvPNOli9fzq233nrEERBD31//80QiQTQaPeyxo0mfkKOgLh5jb49jf1ev36WIiIjIYHcBb/FWIzkDaB3N+S/6ucpFlFkne3c1jvZLi4jIEZx99tn8z//8D93d3bS3t/O///u/FBUVMWfOHP77v/8byIQOzz33HAClpaWDLklZsmQJGzZsAA6+bOjZZ59l1qxZg15v0qRJlJaW8uijjwJw++23H3PN7e3t1NTU0NfXx89+9rMj7v/f//3fpNNpNm7cyKZNmwbm5diwYQNLly495tcfKQowRkFtTQzgsJPNiIiISO6Z2S+AvwKLzKzRzN5uZu8ys/4Lge8GNgEbgO8D7/ajzpLpmS+HOzY868fLi4jIYbzqVa/iqquuYsWKFbzpTW/irLPOAuBnP/sZP/zhD1m+fDl1dXX89re/BeDqq6/mi1/8IieffDIbN27k4osvHggtnHN84QtfYNGiRaxYsYKPfexjg0Zf9PvhD3/I9ddfz5lnnolzjrKysmOq+VOf+hSnn346r3/961m8ePER91+0aBGve93ruOiii/jud79LJBIB4OGHH+biiy8+ptceSb5cQmJmHwfeCez2mj7knLvb2/ZB4O1ACvj/nHP3eu2nkFkKLUrmy8Z7nXPOzArJLI12CrAXuMo5t8U75jrgI95rfNo59+MRf3PDqI17AUZzG6+eX+lHCSIiIhOSc+6aI2x3wI2jVM4hTZ23Ah6Ejm1rgDf6XY6IiAzx4Q9/mA9/+MMHtf/hD384qO01r3kNDQ0NA8/nzZvHBz/4Qfbv3095eTl33333sK/x8Y9/fOBxXV0dzz//PACf+9znWLlyJZC5NOStb33rwH79S7AO3XbDDTcc9cSbwwUokLl85JlnnuHb3/72UZ1nNPg5AuOrzrkV3q0/vKgFrgbqgNXAt82sfw2c75CZ+bt/rfbVXvvbgX3OufnAV4HPe+eqAD5GZi3304CPmdmkUXlnQ1SWFFJeaKzVCAwREREZxuSpM2h1xdiel/wuRURERsCXv/xltm7detT7//73v2fFihUsXbqUP//5z3zkIx858kE5tnXrVj7xiU8QCuXP1Jn5U0nGpcDtzrkEsNnMNgCnmdkWIOac+yuAmd0GXAbc4x3zce/4O4BvWmbGkQuB+51zLd4x95MJPX4xau8my6xYQJeQiIiIyLAsEGBbYDql7Rv9LkVEREbA6aeffkz7X3XVVVx11VU5reEzn/nMwJwd/a688sphR5YALFiwgKlTp+a0hhPlZ4Bxk5m9BXgSeJ9zbh+Zddcfzdqnfy32Pu/x0HbIWr/dOZc0s1ZgMode1/0gI7Wue7apkST3N7Zz34N/pCA43IptMhK0trY/1O/+UL/7Q/0uubKnYDrLE49rJRIRERkRh7oMZiwZsQDDzB4AhotrPkzmcpBPkVln/VPAl4F/5NBrsR9ujfbjOWZw4wiu697viR0PcO+2BFMXncyy6eU5P78MT2tr+0P97g/1uz/U75IrHcUzmZR4kL27m5hcPd3vckRERPLOiAUYzrnzj2Y/M/s+8Dvv6aHWYm/0Hg9tzz6m0cxCQBnQ4rWvGnJM/bG8h1yaFcv8JmVtU5sCDBERETlIKjYDWqB5wzMKMERERIbhy/hEM6vJeno5sMZ7fBdwtZkVmtkcMpN1Pu6tx95uZmd481u8Bfht1jHXeY+vAB7yZhS/F7jAzCZ5k3de4LX5ojJqlBaGNA+GiIiIDKugYiYAnY1rfa5EREQkP/k1B8YXzGwFmUs6tgD/BOCcW2tmvwIagCRwo3Mu5R1zAweWUb3HuwH8EPiJN+FnC5lVTHDOtZjZp4AnvP0+2T+hpx8CZiypibG2qdWvEkRERCSPRUom00YR7NZKJCIiIsPxZQSGc+5a59xJzrllzrk3eiMs+rd9xjk3zzm3yDl3T1b7k865pd62m7xRFjjnepxzVzrn5jvnTnPObco65havfb5z7kej+y4PVhuPsW5HO6n0sFNxiIiIyARmgQBNoVmUtK33uxQREcmyf/9+vv3tb4/46zzzzDO84x3vAGDnzp1ccsklLF++nNraWt7whjcA0NTUxBVXXDHitQxVX1/PJZdcMuy2888/n3379o1KHZriehTVxmN09abYsrfT71JEREQkD7WVzqWm9xW/yxARkSyHCjBSqdQwex+///zP/+Q973kPAP/xH//B61//ep577jkaGhr43Oc+B0A8HueOO+7I6eueqGuvvXZUAh7wdxnVCacuHgOgoamNeVUlPlcjIiIi+SZduZiKfb+nZdd2KqYMu/q7iMjEds8HYMcLh9wcTSUheIw/5k49CS763CE3f+ADH2Djxo2sWLGCcDhMSUkJNTU1PPvsszQ0NHDZZZexbds2enp6eO9738v1118PwB/+8Ac+9KEPkUqlqKys5MEHH6Szs5P3vOc9vPDCCySTST7+8Y9z6aWX0t7ezvPPP8/y5csBaG5u5oILLhioYdmyZQBs2bKFSy65hDVr1tDV1cVb3/pW1q1bx5IlS9iyZQvf+ta3WLlyJSUlJdx444088MADTJo0if/8z//k/e9/P1u3buVrX/sab3zjG9myZQvXXnstnZ2ZX7B/85vf5NWvfvUh+6GtrY3LL7+cl156ibPPPptvf/vbBAIB3vjGN3LWWWeNyhKtCjBG0YIppYSDxtqmNv5medzvckRERCTPFE2rg/XQvOE5BRgiInnic5/7HGvWrOHZZ5+lvr6eiy++mDVr1jBnzhwAbrnlFioqKuju7ubUU0/lTW96E+l0mne+8508/PDDzJkzh5aWzHSMn/nMZzj33HO55ZZb2L9/P6eddhrnn38+Tz75JEuXLh14zRtvvJGrrrqKb37zm5x//vm87W1vIx4f/DPkt7/9bSZNmsTzzz/PmjVrWLFixcC2zs5OVq1axec//3kuv/xyPvKRj3D//ffT0NDAddddxxvf+EamTJnC/fffTyQSYf369VxzzTU8+eSTh+yHxx9/nIaGBmbNmsXq1av5zW9+wxVXXMGkSZNIJBLs3buXyZMn57DnD6YAYxQVhAIsmFJKQ7NWIhEREZGDTZm3HOqho3EN8Aa/yxERyT+HGSkB0N3eTmlp6YiWcNpppw2EFwDf+MY3+J//+R8Atm3bxvr169m9ezdnn332wH4VFRUA3Hfffdx111186UtfAqCnp4etW7fS3NxMVVXVwDkvvPBCNm3axB/+8AfuueceTj75ZNasWUO2Rx55hPe+970ALF26dGCUBkBBQQGrV68G4KSTTqKwsJBwOMxJJ53Eli1bAOjr6+Omm27i2WefJRgM8vLLLx/xfc+dOxeAa665hkceeWRgPo4pU6bQ1NSkAGO8qY3HqH9pF845MivCioiIiGRUT5tLh4vCrnV+lyIiIodQXFw88Li+vp4HHniAv/71rxQVFbFq1Sp6enoO+fOec45f//rXLFq0aFD7unXr6OnpGdRWUVHBm9/8Zt785jdzySWX8PDDD3PKKacMOtehhMPhgdcPBAIUFhYOPE4mkwB89atfpbq6mueee450Ok0kEjns+x76frKf9/T0EI1GD3t8LmgSz1FWF4+xp6OX3e0Jv0sRERGRPGOBANvDMylp2+B3KSIi4iktLaW9vX3Yba2trUyaNImioiLWrVvHo48+CsCZZ57Jn/70JzZv3gwwcAnJhRdeyH/9138NhA/PPPMMAEuWLGHDhgP/9j/00EN0dXUB0N7ezsaNG5k5c+ag137ta1/Lr371KwAaGhp44YVDzw1yqNpramoIBAL85Cc/OeKkpI8//jibN28mnU7zy1/+kte+9rVAJkjZsWMHs2fPPqbXPx4KMEZZbU1mIs+1TbqMRERERA7WWjKPaq1EIiKSNyZPnsxrXvMali5dyr/9278N2rZ69WqSySTLli3jox/9KGeccQYAVVVV3Hzzzfzt3/4ty5cv56qrrgLgox/9KH19fSxbtoylS5fy0Y9+FIDFixfT2to6EJQ89dRTrFy5kmXLlnHmmWfyjne8g1NPPXXQa7/73e9m9+7dLFu2jM9//vMsW7aMsrKyo35f7373u/nxj3/MGWecwcsvvzxoZMlwzjzzTD7wgQ+wdOlS5syZw+WXXz5Q6xlnnEEoNPIXeOgSklG2pH8lkuY2zlk8xedqREREJN+kKxdRuf9u9u/ZQXnlVL/LERER4Oc///mw7YWFhdxzzz3Dbrvooou46KKLBrVFo1G+973vDbv/P/7jP/LLX/6Sd7zjHfzbv/3bQWEJwOzZswfmwohEIvz0pz8lEomwceNGzjvvPGbNmgVAR0fHwDEf//jHB52jf9uCBQt4/vnnB9o/+9nPDlsXwKpVq1i1atWw237yk5/w7ne/+5DH5pJGYIyyWCTMzIoi1ja1+l2KiIiI5KHotDoAmjY8628hIiIyqm644YaBuSqORldXF6997WtZvnw5l19+Od/5zncoKCgYwQqHt3TpUs4777xReS2NwPBBXTxGgy4hERERkWFMmbsM/gTt29bAGav9LkdEREZJJBLh2muvPer9S0tLD7vs6fF44YUXBtWQTqeJRqM89thjhzzmne98Z05rOBwFGD6orYlxz5oddCSSlBTqP4GIiIgcMHXGAjpdBKeVSEREBmgVx9Fx0kkn8eyzzw48bz/BZWkPt1LK8dAlJD6om5aZB+PFZo3CEBERkcEOrESy3u9SRETyQiQSYe/evTn/YVhGlnOOvXv3HnF51mOhX//7oLYmMzNsQ1Mbp86u8LkaERERyTetxXOZ3Xro4boiIhPJ9OnTaWxsZPfu3Ufct6enJ6c/ME90J9qfkUiE6dOn56weBRg+qI4VMrm4QBN5ioiIyLBSlYuoav0DrS27Kauo8rscERFfhcNh5syZc1T71tfXc/LJJ49wRRNHvvWnLiHxgZlRG4/RoEtIREREZBjRabUANK9/xudKRERE8ocCDJ/UxmO8vKODvlTa71JEREQkz1TNWQFA27Y1/hYiIiKSRxRg+KS2JkZvKs2GXR1+lyIiIiJ5ZurMBXS5QtJaiURERGSAAgyf1MUzE3mubdJlJCIiIjJYIBhke2gGxa1aiURERKSfAgyfzKksJhoO0qAAQ0RERIaxv2Qu1YktfpchIiKSNxRg+CQYMBbXlGolEhERERlWcvJiptBC6749fpciIiKSFxRg+Ki2JrMSiXPO71JEREQkz0Tj3kokG571txAREZE8oQDDR3XxMtp7kjTu6/a7FBEREckzVXNXANC2VSuRiIiIgAIMX9XGY4Am8hQREZGDTZ25gG5XQHrXi36XIiIikhcUYPho8dRSAgYNmgdDREREhgiGQmwPzaCodYPfpYiIiOQFBRg+ioSDzKsqoaFZIzBERETkYPuL5zKlZ4vfZYiIiOQFBRg+q4vHdAmJiIiIDKtv8kKmsof21ha/SxEREfGdAgyf1cZjNLf20NLZ63cpIiIikmciNZmVSJrWP+tvISIiInlAAYbP6uJlADRoFIaIiIgM0b8SSes2rUQiIiKiAMNntTWZlUgamjWRp4iIiAxWM3sxCRcmvaPB71JERER8pwDDZ5OKC4iXRTQPhoiIiBwkGArRGJpOVCuRiIiIKMDIB7XxmC4hERERkWHtK56nlUhERERQgJEXauNlbNzdQXdvyu9SREREJM/0VSyght10tu/3uxQRERFfKcDIA7U1MdIOXtrZ7ncpIiIikmcKa+oA2L7+OZ8rERER8ZcCjDxQF89M5Lm2SRN5ioiIyGBVc5cB0Lr1BZ8rERER8ZcCjDwwfVKUWCSkeTBERETkIDWzl9DrQqS0EomIiExwCjDygJlRG49pJRIRERE5SChcwPagViIRERFRgJEnamvKWLejjVTa+V2KiIiI5JmW4rlUaSUSERGZ4BRg5Im6eIyevjSb93T4XYqIiIjkmd6KhcTdTro6NF+WiIhMXAow8kTtwESeuoxEREQkV8xstZm9ZGYbzOwDw2wvM7P/NbPnzGytmb3NjzqPpLBmCQDbNzzvcyUiIiL+UYCRJ+ZPKaEgGNBEniIiIjliZkHgW8BFQC1wjZnVDtntRqDBObccWAV82cwKRrXQozB5zgoA9r+ilUhERGTiUoCRJ8LBAAunltDQrABDREQkR04DNjjnNjnneoHbgUuH7OOAUjMzoARoAZKjW+aRxecsodcFSe540e9SREREfBPy40XN7OPAO4HdXtOHnHN3m9ls4EXgJa/9Uefcu7xjTgFuBaLA3cB7nXPOzAqB24BTgL3AVc65Ld4x1wEf8c71aefcj0f2nZ2Yupoy7n9xJ845Mt+jRERE5ARMA7ZlPW8ETh+yzzeBu4AmoJTM94j0cCczs+uB6wGqq6upr6/PabEdHR2HPedMqyG4a23OX3e8OlJ/yrFTn+ae+jT31Ke5lW/96UuA4fmqc+5Lw7RvdM6tGKb9O2S+NDxKJsBYDdwDvB3Y55ybb2ZXA58HrjKzCuBjwEoyv115yszucs7ty/1byY3aeIxfPrmNnW0JppZF/C5HRERkrBvutwFDl/u6EHgWOBeYB9xvZn92zh00JNI5dzNwM8DKlSvdqlWrclpsfX09hzvnU0/OJ965juk5ft3x6kj9KcdOfZp76tPcU5/mVr7155i4hMTMaoCYc+6vzjlHZsTFZd7mS4H+kRV3AOd5w0AvBO53zrV4ocX9ZEKPvFU3MJGnZhgXERHJgUZgRtbz6WRGWmR7G/Abl7EB2AwsHqX6jklvxULi6Z10d7b7XYqIiIgv/ByBcZOZvQV4Enhf1siIOWb2DNAGfMQ592cyQ0Abs45t9Noga3iocy5pZq3AZIYfNjqNYYz0kFA4uqE33UmHAb//y3MEd+bd/GFjUr4NeZoo1O/+UL/7Q/2e154AFpjZHGA7cDXw5iH7bAXOA/5sZtXAImDTqFZ5lAqm1hLY6ti+4XnmL3+N3+WIiIiMuhELMMzsAWDqMJs+TOZykE+RGcb5KeDLwD8CzcBM59xeb86LO82sjsMPAT3UtqMZNpppHOEhoXD0Q29mP1tPV0Epq1adkvMaJqJ8G/I0Uajf/aF+94f6PX95v9i4CbgXCAK3OOfWmtm7vO3fJfM95FYze4HMd4d/d87t8a3ow6icswweh/2vPA8KMEREZAIasQDDOXf+0exnZt8HfucdkwAS3uOnzGwjsJDM6InpWYdlDwHtHx7aaGYhoIzMDOKNZJZDyz6m/vjezeiprYnxwnZdQiIiIpILzrm7ycydld323azHTcAFo13X8aiZW0efC9KnlUhERGSC8mUODG9Oi36XA2u89ipvzXbMbC6wANjknGsG2s3sDG9+i7cAv/WOvwu4znt8BfCQN0/GvcAFZjbJzCaR+XJy7wi/tRNWG4+xtaWLtp4+v0sRERGRPFJQGKEpGCeyf73fpYiIiPjCrzkwvmBmK8hc0rEF+Cev/Wzgk2aWBFLAu5xzLd62GziwjOo93g3gh8BPzGwDmZEXVwM451rM7FNkrn8F+GTWufJWrTeR54tNbZw+d7LP1YiIiEg+2Vs0hymdCjBERGRi8iXAcM5de4j2XwO/PsS2J4Glw7T3AFce4phbgFuOv9LRd2AlEgUYIiIiMlhi0kJq2v9MT1cHkaISv8sREREZVWNiGdWJZEpphMqSQhqaD1p+XkRERCa4gppagubYvnGN36WIiIiMOgUYeaguHmNtkwIMERERGaxi9jIA9m15zudKRERERp8CjDxUG4+xYVc7vcm036WIiIhIHonPrSPpAlqJREREJiQFGHmoLh6jL+V4eWe736WIiIhIHimMFLFdK5GIiMgEpQAjD9XWZCby1DwYIiIiMtTe6Bwquzb5XYaIiMioU4CRh2ZPLqaoIEiD5sEQERGRIRKTFhBPN5Po6fK7FBERkVGlACMPBQLGkpqYAgwRERE5SNhbiaRp4wt+lyIiIjKqFGDkqbp4jIbmNtJp53cpIiIikkcqZmVWItm75XmfKxERERldCjDyVG1NjI5Ekm37NDxUREREDojPW0rKGclmrUQiIiITiwKMPFUXLwNgrS4jERERkSyRaDFNgRoK9mklEhERmVgUYOSpBdUlBAOmeTBERETkIHuic5jcrZVIRERkYlGAkaci4SALppSwtqnV71JEREQkz/RMWsC0VBO9iR6/SxERERk1CjDyWG1NZiJPERERkWzhqbWELE3TpjV+lyIiIjJqFGDksdp4jJ1tCfZ0JPwuRURERPLIpFknAbB383M+VyIiIjJ6FGDksdp4DEDzYIiIiMgg0+YvI+WMXq1EIiIiE4gCjDxWV6OVSERERORgkaISmgNTKdz3st+liIiIjBoFGHmsrCjMtPKo5sEQERGRg+yOzqGiSyuRiIjIxKEAI8/VxWNaiUREREQO0lM+n2mpJvp6NVeWiIhMDAow8lxtPMbmPZ109Sb9LkVERETySHhqLWFL0bRRK5GIiMjEoAAjz9XFy3AOXmxu97sUERERySPl/SuRbHne50pERERGhwKMPDewEonmwRAREZEs0+YvJ+2MhFYiERGRCUIBRp6Ll0UoLwrToHkwREREJEu0uJTmwBQKWl7yuxQREZFRoQAjz5kZtTUxGrSUqoiIiAyxOzKHiq7NfpchIiIyKhRgjAF18RjrdrSTTKX9LkVERETySHf5fKalGkn29fpdioiIyIhTgDEG1MZjJJJpNu3p9LsUERERySOh6loKLMX2TQ1+lyIiIjLiFGCMAXXxMgDWah4MERERydK/EknLlud8rkRERGTkKcAYA+ZWFlMYCmgeDBERERkkPn8ZAD1NGoEhIiLjnwKMMSAUDLB4ailrFWCIiIhIluLScppsCgUtL/tdioiIyIhTgDFG1MZjNDS34ZzzuxQRERHJI7sjs5nUucnvMkREREacAowxojZexv6uPppae/wuRURERPJId9kCpqW2ayUSEREZ9xRgjBG1NTEAzYMhIiIigwSql1BofTRvedHvUkREREaUAowxYklNKWZaiUREREQG61+JZM/mF3yuREREZGQpwBgjigpCzKks1ggMERERGSQ+fzkACa1EIiIi45wCjDGkLl6mlUhERERkkJLYJHZQRajlJb9LERERGVEKMMaQ2poY2/d309rV53cpIiIikkd2aSUSERGZABRgjCF18cxEnmubNQ+GiIiIHNBVNp9pyW2kkkm/SxERERkxCjDGkNq4ViIRERGRgwWrlxCxPpq3rPO7FBERkRGjAGMMqSwppDpWqABDREREBimduRSAPZuf97kSERGRkaMAY4yprYnR0KwAQ0RERA6YtuBkALqb1vpciYiIyMhRgDHG1MXLWL+rg56+lN+liIiISJ4oLatgJ5MJ79VKJCIiMn4pwBhjauMxUmnH+p0dfpciIiIieWRnZDblWolERETGMQUYY8zASiRNWolEREREDugqW8C05DbSKY3SFBGR8cm3AMPM3mNmL5nZWjP7Qlb7B81sg7ftwqz2U8zsBW/bN8zMvPZCM/ul1/6Ymc3OOuY6M1vv3a4b1Tc4QmZMKqKkMKR5MERERGSQwJTFRK2X5lde9rsUERGREeFLgGFm5wCXAsucc3XAl7z2WuBqoA5YDXzbzILeYd8BrgcWeLfVXvvbgX3OufnAV4HPe+eqAD4GnA6cBnzMzCaN/LsbWYGAUVsTY61WIhERETkiM1vt/VJkg5l94BD7rDKzZ71fqvxptGvMldiMzEokuzc/53MlIiIiI8OvERg3AJ9zziUAnHO7vPZLgdudcwnn3GZgA3CamdUAMefcX51zDrgNuCzrmB97j+8AzvNGZ1wI3O+ca3HO7QPu50DoMabVxmO82NxGOu38LkVERCRveb8E+RZwEVALXOP9siR7n3Lg28AbvV+qXDnadeZKTf9KJNu1EomIiIxPIZ9edyFwlpl9BugB/p9z7glgGvBo1n6NXluf93hoO979NgDnXNLMWoHJ2e3DHDOImV1PZnQH1dXV1NfXn8h7G1ZHR0fOzhts66OrN8Wv7vkjU4s1jcnh5LLf5eip3/2hfveH+j2vnQZscM5tAjCz28n84qMha583A79xzm2FQb9UGXPKJlWyiwpCWolERETGqRELMMzsAWDqMJs+7L3uJOAM4FTgV2Y2F7Bh9neHaec4jxnc6NzNwM0AK1eudKtWrRputxNSX19Prs5bub2VH655hJIZi1m1LJ6Tc45Xuex3OXrqd3+o3/2hfs9rw/0y4/Qh+ywEwmZWD5QCX3fO3TbcyUb6Fx65CMPKAtMobVuvUA2FiyNBfZp76tPcU5/mVr7154gFGM658w+1zcxuIPPbDgc8bmZpoJLMF4sZWbtOB5q89unDtJN1TKOZhYAyoMVrXzXkmPrjf0f5Y2F1KeGgsbapjUsUYIiIiBzK0fwyIwScApwHRIG/mtmjzrmDZsIc6V945CIMe7RhCYt2/paFZ51FIBg88gHjmMLF3FOf5p76NPfUp7mVb/3p1/UHdwLnApjZQqAA2APcBVztrSwyh8xknY8755qBdjM7w5vf4i3Ab71z3QX0rzByBfCQF4zcC1xgZpO8yTsv8NrGvIJQgPlTSmnQRJ4iIiKHc6hfjAzd5w/OuU7n3B7gYWD5KNWXc1a1mCJLsGPbBr9LERERyTm/AoxbgLlmtga4HbjOZawFfkXm2tQ/ADc65/oXM78B+AGZiT03Avd47T8EJpvZBuBfgQ8AOOdagE8BT3i3T3pt40JdXCuRiIiIHMETwAIzm2NmBWRWOrtryD6/JTMvV8jMishcYvLiKNeZM7GZ3kokm7QSiYiIjD++TOLpnOsF/uEQ2z4DfGaY9ieBpcO093CIGcOdc7eQCUvGndqaGHc81ciu9h6mlEb8LkdERCTveJN730RmBGYQuMU5t9bM3uVt/65z7kUz+wPwPJAGfuCcW+Nf1ScmPn8FAN3b1wB/52stIiIiuebXKiRyguriMQDWNrUxZZECDBERkeE45+4G7h7S9t0hz78IfHE06xopZZOr2UM5wb0HTeEhIiIy5mkNzjFqiRdgaB4MERERybajcDZlHRv9LkNERCTnFGCMUbFImJkVRQowREREZJDO2Hym9W3FpdN+lyIiIpJTCjDGsNqaGA3NCjBEREQkS9Viiq2HnY0ahSEiIuOLAowxrC4eY/OeTjoSSb9LERERkTxROiMz5/mujVqJRERExhcFGGNYrTcPxjqNwhARERFPfMHJAHRtH7OLqYiIiAxLAcYYVhcvAzIrkYiIiIgAlFdOZS9lBPa85HcpIiIiOaUAYwyrjhVSUVygiTxFRERkkB0Fsynr2OR3GSIiIjmlAGMMMzPq4jHWNrf6XYqIiIjkkY7YPOJ9r2glEhERGVcUYIxxtTUxXt7RQV9KX1BERETEU7WYUutmV9NmvysRERHJGQUYY1xtPEZvKs2GXR1+lyIiIiJ5omTGSYBWIhERkfFFAcYYV+etRKJ5MERERKRfzfzlAHQ2aiUSEREZPxRgjHFzKkuIhANaiUREREQGVEyZxj5iWolERETGFQUYY1wwYCyeGqNBE3mKiIhIlqaCWcS0EomIiIwjxx1gmNkvc1mIHL+6eIyGpjacc36XIiIiInmio3Qe8b4tWolERETGjRMZgXFmzqqQE1Ibj9HWk6RxX7ffpYiIiEi+qFpMjC727NjqdyUiIiI5oUtIxoHamsxEnpoHQ0RERPoVz1gKwI4Nz/hciYiISG6EDrfRzF51qE1AOPflyPFYPDVGwKChuY3VS6f6XY6IiIjkganzVsD90Nm4Frjc73JERERO2GEDDODLh9m2LpeFyPGLFgSZW1VCQ5Mm8hQREZGMyVOmsZ8STCuRiIjIOHHYAMM5d86htpnZ6bkvR45XXTzGE5tb/C5DRERE8oQFAjSFZxNr3+B3KSIiIjlxInNg/HfOqpATVlsTo6m1h32dvX6XIiIiInmiPTaPeN8rWolERETGhRMJMCxnVcgJq4uXAZl5MEREREQAXOUiyuhk765Gv0sRERE5YScSYLicVSEnrDbevxKJ5sEQERGRjJLp3kok67USiYiIjH1HWoXkfxk+qDBg8ohUJMeloriAmrIIDVpKVURERDxT562AB6GjcS1wqd/liIiInJAjrULypWHa3GG2iY9qa2KsVYAhIiIinslTZ9BGsVYiERGRceFIAUY5MN059y0AM3scqCITYvz7yJYmx6ouHuOPL+2ipy9FJBz0uxwRERHxmQUCbA/PorRNK5GIiMjYd6Q5MN4P3JX1vABYCawC3jVCNclxqo3HSDtYt6Pd71JEREQkT7SXziPet0UrkYiIyJh3pACjwDm3Lev5I865vc65rUDxCNYlx2FgJRJdRiIiIiKedOUiyumgZXeT36WIiIickCMFGJOynzjnbsp6WpX7cuRETJ8UpTQS0kokIiIiMqDYW4mkeYNWIhERkbHtSAHGY2b2zqGNZvZPwOMjU5IcLzOjtiZGQ7NGYIiIiEhG9bwVAHQ2rvW3EBERkRN0pEk8/wW408zeDDzttZ0CFAKXjWBdcpxq4zFuf3wbqbQjGDC/yxERERGfVdXMot1FYbdWIhERkbHtsAGGc24X8GozOxeo85p/75x7aMQrk+NSFy+ju28Lm/d0Mn9Kid/liIiIiM8yK5HMpqRtvd+liIiInJAjjcAAwAssFFqMAbU1MQDWNrUqwBAREREA2krnMn/fn/0uQ0RE5IQcaQ4MGWPmTymhIBjQPBgiIiIyIF25iAraaNm13e9SREREjpsCjHGmIBRgQXWJllIVERGRAUXT+lciec7nSkRERI6fAoxxqC4eo6GpDeec36WIiIhIHpgybzkAHY1rfK5ERETk+CnAGIdqa2Ls7exlZ1vC71JEREQkD1RPm0uHi8KudX6XIiIictwUYIxDddPKAGhobvW5EhEREckHmZVIZlLStsHvUkRERI6bAoxxaPHUUgDWbtc8GCIiIpLRWjKP6t5X/C5DRETkuCnAGIdKI2FmTy7SSiQiIiIyIF25iEr2s3/PDr9LEREROS4KMMap2niMtVqJRERERDzRaXUANG141t9CREREjpNvAYaZvcfMXjKztWb2Ba9ttpl1m9mz3u27WfufYmYvmNkGM/uGmZnXXmhmv/TaHzOz2VnHXGdm673bdaP+Jn1UFy9ja0sXbT19fpciIiIieWDK3GUAtG/TSiQiIjI2hfx4UTM7B7gUWOacS5jZlKzNG51zK4Y57DvA9cCjwN3AauAe4O3APufcfDO7Gvg8cJWZVQAfA1YCDnjKzO5yzu0bqfeVT2prYgC82NTG6XMn+1yNiIiI+G3qjAV0ugjsetHvUkRERI6LXyMwbgA+55xLADjndh1uZzOrAWLOub865xxwG3CZt/lS4Mfe4zuA87zRGRcC9zvnWrzQ4n4yoceEUBfPBBiaB0NERETgwEokxVqJRERExihfRmAAC4GzzOwzQA/w/5xzT3jb5pjZM0Ab8BHn3J+BaUBj1vGNXhve/TYA51zSzFqBydntwxwziJldT2Z0B9XV1dTX15/wGxyqo6NjRM57KM45YgXw4NMvM6dv4s44Ptr9Lhnqd3+o3/2hfpexpLV4LrNbH/O7DBERkeMyYgGGmT0ATB1m04e9150EnAGcCvzKzOYCzcBM59xeMzsFuNPM6gAb5jyu/6UOse1wxwxudO5m4GaAlStXulWrVh3qbR23+vp6RuK8h7Ni8+PsaU+watVZo/q6+cSPfhf1u1/U7/5Qv8tYkqpcRFXrH2ht2U1ZRZXf5YiIiByTEbuExDl3vnNu6TC335IZDfEbl/E4kAYqnXMJ59xe7/ingI1kRms0AtOzTj8daPIeNwIzAMwsBJQBLdntwxwzIdTWxFi/q53eZNrvUkRERCQPRKfVAtC8/hmfKxERETl2fs2BcSdwLoCZLQQKgD1mVmVmQa99LrAA2OScawbazewMb36LtwC/9c51F9C/wsgVwEPePBn3AheY2SQzmwRc4LVNGHXxGH0px/pd7X6XIiIi4gszW+2terbBzD5wmP1ONbOUmV0xmvWNtqo5KwBo00okIiIyBvk1B8YtwC1mtgboBa5zzjkzOxv4pJklgRTwLudci3fMDcCtQJTM6iP3eO0/BH5iZhvIjLy4GsA512JmnwL659b4ZNa5JoRabyLPtU1t1MXLfK5GRERkdHm/FPkW8HoyIzOf8FYkaxhmv88zAX7RMXXmArpcIWmtRCIiImOQLwGGc64X+Idh2n8N/PoQxzwJLB2mvQe48hDH3EImLJmQZk8upqggSEOTViIREZEJ6TRgg3NuE4CZ3U5m9bKGIfu9h8z3j1NHt7zRFwgG2R6aQXGrViIREZGxx68RGDIKggFj8dRSBRgiIjJRDbci2enZO5jZNOByMpe2HjbAGOlVy0ZrRZtgMM7CnjXjfvUcrRCUe+rT3FOf5p76NLfyrT8VYIxzdfEy/ueZ7aTTjkBguIVZRERExq2jWZHsa8C/O+dSmWm2Dm2kVy0brRVt/rr1Qao3PUxk+VLKJlWO+Ov5RSsE5Z76NPfUp7mnPs2tfOtPvybxlFFSG4/RkUiybV+X36WIiIiMtqNZkWwlcLuZbSEzGfi3zeyyUanOJ9G4txLJhmf9LUREROQYKcAY5+q8iTx1GYmIiExATwALzGyOmRWQmej7ruwdnHNznHOznXOzgTuAdzvn7hz1SkdR1dxlALRt1UokIiIytijAGOcWVpcSDBhrFWCIiMgE45xLAjeRWV3kReBXzrm1ZvYuM3uXv9X5Z+rMRXS7Aq1EIiIiY47mwBjnIuEg86tKaGhWgCEiIhOPc+5u4O4hbd89xL5vHY2a/BYMhdgemkGRViIREZExRiMwJoDaeIy1Ta1+lyEiIiJ5Yn/xHKb0bPG7DBERkWOiAGMCqIvH2NmWYE9Hwu9SREREJA/0TV7EVPbQ3tridykiIiJHTQHGBFBbo4k8RURE5IBITWYlkqb1z/pbiIiIyDFQgDEB1PavRKJ5MERERASonLscgNZtWolERETGDgUYE0B5UQHTyqNaiUREREQAiM9eQsKFSe9o8LsUERGRo6YAY4Kojcdo0ESeIiIiQmYlksbQdKJaiURERMYQBRgTRG1NjE17OunqTfpdioiIiOSBfUVztRKJiIiMKQowJoi6eAznYN2Odr9LERERkTzQN3khNeyms32/36WIiIgcFQUYE0T/RJ6aB0NEREQACmvqANi+/jmfKxERETk6CjAmiGnlUcqiYS2lKiIiIgBUzV0GQOvWF3yuRERE5OgowJggzIzaGk3kKSIiIhk1s5fQ60KktBKJiIiMEQowJpC6eIx1O9pJptJ+lyIiIiI+C4UL2B7USiQiIjJ2KMCYQGrjMRLJNJv2dPpdioiIiOSBluK5VPVs9rsMERGRo6IAYwKpi5cBaB4MERERAaC3YiFxt4uuDl1iKiIi+U8BxgQyt6qYglCAtZoHQ0RERIDCmiUAbN/wvM+ViIiIHJkCjAkkHAyweGopDc0agSEiIiIwec4KAPZvUYAhIiL5TwHGBFNbE2NtUxvOOb9LEREREZ/F5yyh1wVJ7lzndykiIiJHpABjgqmLx9jf1Udza4/fpYiIiIjPwgWFNAWnEW1d73cpIiIiR6QAY4KpjccAWKuJPEVERATYWzSXqu5NfpchIiJyRAowJpjFU2OYaSUSERERyeitWEhNehfdne1+lyIiInJYCjAmmOLCEHMmF2slEhEREQGgYGotAXNaiURERPKeAowJqDYe00okIiIiAkDlnGUA7H9FAYaIiOQ3BRgTUG08RuO+blq7+vwuRURERHxWM7eOPhekb8eLfpciIiJyWAowJqC6eBmARmGIiIgIBYURmoJxIvu1EomIiOQ3BRgTUG1N/0okmgdDREREYG/RHKq6N/tdhoiIyGEpwJiAqkoLmVJaqBEYIiIiAkBi0kJq0jvo6erwuxQREZFDUoAxQdXGY1pKVURERAAomLqEoDm2b1zjdykiIiKHpABjgqqLx9iwq4OevpTfpYiIiIjPKuYsB2Dflud8rkREROTQFGBMULU1ZSTTjvU7NVRURERkoovPrSPpAlqJRERE8poCjAmqLp6ZyLOhWRN5ioiITHSFkSKagjVaiURERPKaAowJamZFESWFIdZqHgwREREB9kTnUtm1ye8yREREDkkBxgQVCBhLako1kaeIiIgAkJi0gHi6mURPl9+liIiIDEsBxgRWWxPjxeY20mnndykiIiLis7C3EknTxhf8LkVERGRYCjAmsLp4GZ29KV5p0W9aREREJrqK2ZmVSPZued7nSkRERIanAGMCq/Um8lzbpIk8RUREJrr4vKWknJFs1kokIiKSnxRgTGALqksIBUzzYIiIiAiRaDFNgRoK9r3sdykiIiLD8iXAMLNfmtmz3m2LmT2bte2DZrbBzF4yswuz2k8xsxe8bd8wM/PaC73zbTCzx8xsdtYx15nZeu923Wi+x7GgMBRk/pQSrUQiIiIiAOyJzmFy92a/yxARERmWLwGGc+4q59wK59wK4NfAbwDMrBa4GqgDVgPfNrOgd9h3gOuBBd5ttdf+dmCfc24+8FXg8965KoCPAacDpwEfM7NJI//uxpa6eBkNzQowREREBHomLWBaqoneRI/fpYiIiBzE10tIvFEUfwf8wmu6FLjdOZdwzm0GNgCnmVkNEHPO/dU554DbgMuyjvmx9/gO4DzvvBcC9zvnWpxz+4D7ORB6iKc2HmN3e4Jd7fqiIiIiMtGFp9YSsjTbtRKJiIjkoZDPr38WsNM5t957Pg14NGt7o9fW5z0e2t5/zDYA51zSzFqBydntwxwziJldT2Z0B9XV1dTX1x//OzqEjo6OETnvieprSQFw+x8eYVmV338cci9f+328U7/7Q/3uD/W7jCeTZp0ET0HLlueZU3uq3+WIiIgMMmI/sZrZA8DUYTZ92Dn3W+/xNRwYfQFgw+zvDtN+vMcMbnTuZuBmgJUrV7pVq1YNt9sJqa+vZyTOe6JO7u7jc4/fR7ByNqtWzfe7nJzL134f79Tv/lC/+0P9LuPJtPnLSDmjVyuRiIhIHhqxAMM5d/7htptZCPhb4JSs5kZgRtbz6UCT1z59mPbsYxq9c5YBLV77qiHH1B/j2xj3yqJhZlRENQ+GiIiIECkqoTEwlcJ9L/ldioiIyEH8nAPjfGCdcy770pC7gKu9lUXmkJms83HnXDPQbmZnePNbvAX4bdYx/SuMXAE85M2TcS9wgZlN8ibvvMBrkyFqa2JaSlVEREQA2B2dQ0WXViIREZH842eAcTWDLx/BObcW+BXQAPwBuNE5l/I23wD8gMzEnhuBe7z2HwKTzWwD8K/AB7xztQCfAp7wbp/02mSIungZW/Z20pFI+l2KiIiI+KynfD7TUk309Sb8LkVERGQQ32ZtdM699RDtnwE+M0z7k8DSYdp7gCsPca5bgFtOqNAJoLYmhnOwrrmNlbMr/C5HREREfBSeWku4KcUrG9cwa8kpRz5ARERklPi6jKrkh7ppMQDNgyEiIiKUzzoJgL1bnve5EhERkcEUYAhTYxEmFYVZu10BhoiIjC9mttrMXjKzDWb2gWG2/72ZPe/d/mJmy/2oM59Mm7+ctDMSWolERETyjAIMwcyoi5dpBIaIiIwrZhYEvgVcBNQC15hZ7ZDdNgOvc84tIzN31s2jW2X+iRaX0hyYQkGLViIREZH8ogBDAKiNx3hpRzt9qbTfpYiIiOTKacAG59wm51wvcDtwafYOzrm/OOf2eU8fZfCy7RPW7ohWIhERkfzj2ySekl/q4jF6U2k27u5g8dSY3+WIiIjkwjRgW9bzRuD0w+z/dg6scnYQM7seuB6gurqa+vr6HJR4QEdHR87Pebx6A9XUpp7goQcfIBAcm18X86k/xwv1ae6pT3NPfZpb+dafY/MTSXKutiYTWqzd3qYAQ0RExgsbps0Nu6PZOWQCjNce6mTOuZvxLjFZuXKlW7VqVQ5KPKC+vp5cn/N4PbF/LQXP/pZ50yuZtWiF3+Ucl3zqz/FCfZp76tPcU5/mVr71py4hEQDmVpUQCQc0D4aIiIwnjcCMrOfTgaahO5nZMuAHwKXOub2jVFte61+JpGXLcz5XIiIicoACDAEgGDAWTY2xtqnV71JERERy5QlggZnNMbMC4GrgruwdzGwm8BvgWufcyz7UmJfi85cB0NPU4HMlIiIiByjAkAF18RgNTW04N+zoWhERkTHFOZcEbgLuBV4EfuWcW2tm7zKzd3m7/QcwGfi2mT1rZk/6VG5eKS4tp8mmUNCiTEdERPKH5sCQAbU1MX7+2FYa93Uzo6LI73JEREROmHPubuDuIW3fzXr8DuAdo13XWLA7MptJnZv8LkNERGSARmDIgLp4ZvJOzYMhIiIi3WULmJbaTrKv1+9SREREAAUYkmXx1BgBg7VNCjBEREQmukD1Egqtj+YtL/pdioiICKAAQ7JEC4LMrSqhQQGGiIjIhNe/EsmezS/4XImIiEiGAgwZpLYmRoNWIhEREZnw4vOXA5DQSiQiIpInFGDIIHXxGE2tPezr1PWuIiIiE1lJbBI7qCLU8pLfpYiIiAAKMGSIWk3kKSIiIp5dWolERETyiAIMGaS2xgswNA+GiIjIhNdVNp9pyW2kkkm/SxEREVGAIYNNLilkaizCWs2DISIiMuEFq5cQsT6at6zzuxQREREFGHKwunhMl5CIiIgIpTOXArBn8/M+VyIiIqIAQ4ZRG4+xcXcnPX0pv0sRERERH8XnrwCgu2mNv4WIiIigAEOGURePkUo7XtrR7ncpIiIi4qNY+WR2Mpnw3pf9LkVEREQBhhystqYMgLWayFNERGTC2xmZTblWIhERkTygAEMOMqMiSmlhiIZmTeQpIiIy0XWVLWBachvplC4tFRERfynAkIOYGUviMY3AEBEREQJTFhO1Xppf0WUkIiLiLwUYMqy6eIx1ze2k0s7vUkRERMRHsRmZlUh2b37O50pERGSiU4Ahw6qtidHdl2Lznk6/SxEREREf1Sw4GYDu7Wt9rkRERCY6BRgyrLp4ZiLPhmZdRiIiIjKRlU2qZBcVhPa+5HcpIiIywSnAkGHNn1JCOGisbdJEniIiIhPdzsJZWolERER8pwBDhlUQCrCwupQGTeQpIiIy4XWWLWBa31atRCIiIr5SgCGHVFsTo6GpDec0kaeIiMhEZlWLKbIEO7Zt8LsUERGZwBRgyCHVxWPs7exlV3vC71JERETER7GZ3kokm7QSiYiI+EcBhhxSrTeR53Pb9vtbiIiIiPgqPn8FAN3b1/hbiIiITGgKMOSQauMxSgtD3Pjzp7nx50/zfxv2kE7rchIREZGJpmxyNXsoJ7j3Zb9LERGRCSzkdwGSv0oKQ/z2ptfw00e38uunG/n9883MmlzE1afO5MqV06ksKfS7RBERERklOwpnU9ax0e8yRERkAtMIDDmsuVUl/Mff1PLYh87ja1etoDoW4fN/WMeZn32QG3/2NI+s16gMERGRiaAzNp9pfVtx6bTfpYiIyASlERhyVCLhIJedPI3LTp7Ghl3t3P74Nu54upHfv9DMzIoirj5tBlecMp0ppRG/SxUREZGRULWY4t13sKNxI1NnLvC7GhERmYA0AkOO2fwppXzkkloe/eB5fP3qFdSURfjCH17i1Z99iBt++hQPv7xbozJERETGmdIZmZVIdm3USiQiIuIPjcCQ4xYJB7l0xTQuXTGNjbs7uP3xrdzxVCP3rNnBjIrowFwZGpUhIiIy9sUXnAz3Qtf2NcAVfpcjIiITkEZgSE7MqyrhwxfX8uiHzuMb15zM9PIivnhvZlTGu37yFH/SqAwREZExrbxyKnspI7DnJb9LERGRCUojMCSnCkNB3rg8zhuXx9m0u4NfPrGN/36qkT+s3cH0SVGuPnUGV66cQXVMozJERETGmh0Fs4i3PsO6Jx5g0SnnYgH9LkxEZCzp603Q1dlOoqudRFcbia4O+no66OvuINnTTqqnk3RvJ663E9fbRe/eHbTULqBiyjS/SwcUYMgImltVwgffsIR/vWAh9zfs5OePbeVL973MVx9Yz3mLp3DN6TM5e0EVwYD5XaqIiIgcha66a5j39H8w/fdvYvvd1WyddjHxs65j1qIVfpcmIjJu9CZ66O5sp6erjURXO73dHfR2d5DsDxkSnaQTB0IG6+vC+joJJLsJJrsJpTK3gnQ3heluCl0PERJEXA8FlqLsGGpJuDDNe987sQMMM/slsMh7Wg7sd86tMLPZwItA/9jER51z7/KOOQW4FYgCdwPvdc45MysEbgNOAfYCVznntnjHXAd8xDvXp51zPx7ZdybDKQwFuWRZnEuWxdm8p5Pbn9jKHU82cl/DTqaVR7nq1Bn83coZTC3TqAwREZF8duql76Z91dU8/9DPiK77Nadt+xHBX9zChuA89sy9lHnnXEdVfLbfZYqIjDiXTtPT3UlXRyuJrg4SXa0kutrp6+70RjJ0kEp04BIdmZChtwNLdhPo6ySY7CKU6ibshQwF6R4vZOgh6hIUWIoCOOqgodsV0GMReigkEYjQG4jSF4jQWVBJazBKKlSEC0VJFxRDuAgrKMYKigkWFhOMlBCKFBOOlBCOllIYLSFSVEphcSlFxTH++sgjrFqyciS78pj4EmA4567qf2xmXwZaszZvdM6tGOaw7wDXA4+SCTBWA/cAbwf2Oefmm9nVwOeBq8ysAvgYsBJwwFNmdpdzbt8IvCU5SnMqi/ngRUt43+sXcX/DTn7x+Fa+cv/LfP3B9Zy7eApvPm0mZy/UqAwREZF8VVpWwWmXvwd4D3uaXmHDH3/M5E2/5Yz1XyH98ldZE1lO1+I3sficvydWPtnvckVkgnPpNN1d7ZkRDZ2ZyyZ6u9vp624n2dNJygsbnHfZhPV2eqMZurzRDF0DQUNhupuI6yHqeoiSIGqO6FHW0R8ydFuEhEXpDUToC0ZpD8dIBaOkQlHSoSJcuAgKMiFDoKCYQGEmaAhFSglHiyksKqUgGqOwqIRocSnRolKiweBR1zHW+XoJiZkZ8HfAuUfYrwaIOef+6j2/DbiMTIBxKfBxb9c7gG96570QuN851+Idcz+Z0OMXOX8jcswKQgEuXlbDxctqeGVvJ794fBt3PLWN+xt2Ei+LcNWpM/m7U6dTUzZR/iqKiIiMPZXxWVT+/X8A/8HWl5+l6eHbmL799yx97qMknv0kT5eeiS27itqz/5bCSJHf5YpInuvrTdDV0UZ3ZyuJzv7LJ9oGLp1I93SQTmTCBno7CPR1ZY1o6KIg1c30vg4a/9Q7KGgoMsfR/gvU7Qrotgg9A0FDlL5ghLZwOalQUWY0QzgzkoGCYqywJBMyREoIFZYQLiqlIFpKQVEp0aIYkZJYJmQIhYgCk0ayAycAv+fAOAvY6Zxbn9U2x8yeAdqAjzjn/gxMAxqz9mn02vDutwE455Jm1gpMzm4f5phBzOx6MqM7qK6upr6+/gTf1sE6OjpG5LzjxRlRWPnqEM/sMuq39fLVB17maw+8zPKqIKtmhFhWFSRgxz4qQ/3uD/W7P9Tv/lC/i2TMXLiCmQtX4NJf4qWn69n/2M9YsPs+Kv7yMG1/eT/PVZxL8co3s+T0CwkEg36XKyInIPvyiYFRDV1t3qiGdpLdXtCQ6IDeTujrJNDXSaAvEzSEUt0UpLooSHcTSfcQoZsi10OBJSnj6C6d6HFhui2aNaIhEzS0hqYQLConFS7GhYpwBcVYuMgLGkoIRjKjGQqipYSjJRQWxYgUlR4UNEh+GrEAw8weAKYOs+nDzrnfeo+vYfCIiGZgpnNurzfnxZ1mVgcM95Nr/5qch9p2uGMGNzp3M3AzwMqVK92qVauG2+2E1NfXMxLnHW/OB/4N2Lq3i9uf2Mqvnmzka08nqCmL8HcrZ3DVqTOIlx/9Pynqd3+o3/2hfveH+l1kMAsEWLTyXFh5Lsm+Xp5/5C56n7mdpXvvo+i+/2XHfZVsrllN9Wvewtylp/tdrsi459JpEoluujva6O5oPTBXQ1ebFza0k050kO5ph/7LJ3o7MqMakp1DLp/oJup6KKLnmC6f6HQRb1RDlEQgEzb0hMroCE0lFSomHSrKzM9QUIwV9AcNJYSiJYQiMQqKSiksKiVSXEakOEZRcSmRcAERDh7RoM/l8W3EAgzn3PmH225mIeBvyUy+2X9MAkh4j58ys43AQjKjJ6ZnHT4daPIeNwIzgEbvnGVAi9e+asgx9cf9hmRUzZxcxPtXL+ZfXr+QB1/cyc8f38Y3HlrPfz20nlWLMnNlrFpURSio5dtERETyVShcwLJzroBzrqCro5Un639JeO0drGz6BeE7fsrm38xix6y/Yfaqt1Aza9GRTygyAST7eunqbKe7Y39mdENna+Yyiq72gckhXaI9M19Doh1LdhH0LqMIp7ooSHVlwoZ0F1Eyl1FELDXsD/tDpZzRRYRui9ITiGZGNgSLMpNBhopJhYpIh4txBcVQkLl0YiBs6B/VUBQjUlxKYVGMopIYkWgJxcEgxaPReTLu+XkJyfnAOufcwKUhZlYFtDjnUmY2F1gAbHLOtZhZu5mdATwGvAX4L++wu4DrgL8CVwAPeauT3Av8p5n1/z29APjgqLwzyZlwMMDqpTWsXlrDtpYufvnENn755DbecduTTI1F+LtTM6Myph3DqAwREREZfUUlZay85Hq45Hpadm1n/R9/StmGOzlz8zdh8zdpCC+lfcFlLDr3WsorhxvEK5KfEj1ddHe0ZVaj6Nw/MLqhr7uNZHc7LtFBOtEOiQ7vMopOgn2dhFKdVCba2fRwLxGXGd1Q5LqJWB8xIHYUr93lCum2TOCQGdlQNDCyIRkqwYUzgQOFJZmRDZFSQv1hQ1HMCxvKiBSXUlRSRiRaTGkgQOlId5rIcfIzwLiagyfUPBv4pJklgRTwrv5JOIEbOLCM6j3eDeCHwE/MbAOZkRdXA3ihx6eAJ7z9Ppl1LhmDZlQU8f8uXMR7z1/AQ+t28fPHtvJf/aMyFlZxzWkzOXfxFI3KEBERyXMVU6Zx+lX/Dvw7TZvX8cqfbiW+9XfUNnya3rWf5dni00jVXUHtqquIFutHKcmd/ssputr3093Rlpm7obOV3v7LKXraSfe04xKZyykCvR0Dk0SGk53e6IbMCIcomcCh0FIUAuVHeO0+F6TLInTjjW4IFNFlhbRGqmgJFWXmbAgX4wpLMytQFJYQiJZ6q08cuIwiWlLuXUYRoygUOurJKUXGA98CDOfcW4dp+zXw60Ps/ySwdJj2HuDKQxxzC3DLCRUqeSccDHBh3VQurJvKtpYufvXkNn75xDau/8lTVMcK+buVM/i7lTOYUaF/zkVERPJdfM5i4nM+h0v/Jxte+Ct7/vIT5u68lylPvI/Oxz/ME+WvI/Kqq1ny6ksIhQv8Lld80Jvooat9/4ERDp2ZCSOT3W2DA4dEJ4G+DgJ9HYT6OgmnMvM3FKa7iKS7KaJ70OUUR3xdF6TLonSTGd2QCBRlLqcorBq4lCJdUIIVlEJhsTe6oXRgdENBcdmB0Q2l5RQWRikLBAZNUKn5GkSOjd+rkIickBkVRbzvgkW897zMqIxfPL6Vb/5xA9/84wbOXlBFSV8vz/S9TEEoQEEwkLkf+jj7+XD7ZLWFAoYdx2ooIiIicngWCDB/+WuYv/w1pJJJ1jx6N11P/oLF++uJ/fFe9vyxnA1TLqDijH9gwYqzsIBGXOarVDJJZ0drZg6HjtaBUQ593e0ku9tI92QmjSTRjnkjHELJDkJJb/6GVBeFrouo66bYdVNgSQo48giH7MChJ1BEIlBEIlRCZ7B6UOAw6HKKaGZ0QzhaSmFxjMLicopKyoiWxCiMFB3V64rI6FGAIeNCKBjggrqpXFA3lcZ9XfzqyUZ+/VQjO1r7SG1ef+QTHCUzMoHGIQKQsHdfOCT4CGeFIYWHOGbocaFggHDACAUDBANGOGiEAoHMfTATpoSy2jL7ZNqDClpERGQMC4ZCLH3tG+G1b6Snu5NnHr4D9/x/86qdv6Hgrl+x7X/jNM64hBlnX8f0+QcN0JVjNHTSyN6uNhJdrSS7O0h2t2UmjeztoHtnI4++eDvWP4dDMjPKodCbNDLquihy3RRZ4qjmcEg7o9ObMLLbCxx6g0V0h8tJhYpJ9QcOBSVYYSnBSCmBSCZsyB7hEC0po6i0TIGDyASgAEPGnemTivjX1y/kX1+/kPr6es4++3X0ptL0pdL0JtP09t8n0ySSw7f3Dtfm7ZsYpq1/v4TX1pFIHjjvIc6ZHnZR39wZCDUCgUzQ4QUiwWBW28C9t72/rT8c6T9mIDjJDkyy9h9yjo1b+9jx+FYCZgQCRjAAAcvUE+xv854HBtoO7DN4X4Y9zuzg9kBgyHGmMEdEZKyLRIs5+cLr4MLraN23h2cf+inFL/2G01/5PoGf3szLoYW0zLuM+ee8hcqpM/wud8S5dJquzja6O9vo6Wijp7OV3u72rNENHaQSHUPmcOjKLImZ6qQg1U1Bquu4J43sbi3IjHKwzCUViUARnQWTvRUqikkXlOIKSrBCL3SIlhKKxghHY94IBy9wKCkjWlSqCSNF5JgowJBxLxAwIoEgkXDQ71IGSaYOEZSk+oMRRzKVJpl2mVvKa0unSaay2rz7YdvSzms/mvOlSfSl6Uinss534Bx9A+fLakuncYcKYhpeGNX+PJKhwcbgsONAMHK03DBvfLiuOFT/uGH2Hm7fYzlnb28vBY88QH9e0/9uDjy3gecHtg1+zwP72uD9B5/PBj1nmPMN99pDc6TsfTNBVX9glhlN1D/yKBjIGnU0ZMRRcGAkUnb4lj1CafAopqGvERpyrnBg8OsOfo3AQa8VOIY/MyJy4somVXLam/4Z+Gd2Nm5kc/1tVG2+izNe+gLJdV/i+eirSCx5E0vOuSbnr+3SaZLJPpJ9vfT19ZLybslkL6lkL8m+PtLJBKlkH6m+XtKpPlLJXlyyj3Sql3QySTrZh0v14lJ9uFTSu+/D9XVDb8fA5RSZFSq6CHthQ2H6QNgQJUGxuaNakvLApJFF9AQiJAJF9AWjdIfLafFGOLhwsRc4FGMFJZnAIWvSyIKiGNGSMiLFMZ586hnOPe98tPabiPhFAYaIT0LBzGUiRWN8PrJUOisE8UKNPz/yf5x+xpmknSOdhpRzpNKOtHef/Thzj7evG7Ivw+zrSDuG2ffg8/U/P7Avh6khs93hBn5wzzbcII7hfnQdfr/hf8gddt9hdz26epqamqipqfaeZVKO/rBj4B6X9fjgbf0bDmxzh9j3wPaBPGXIebJf+6C2IedLu0ywlvLCtu6+1EDIlkpn/lylsgK57MCuP5RLjfSwpmEEDAJA8IF7MiOOLDOSyCwTnva3Wda2ge3D3B84Pnv/Qx/fP3LpqPf3tmU//+SlS/Mu4BU5GtXT51H9D58APsErLz5F0yO3MavpbuLPfJDupz9GNLycJ575FoF0EksnMZckkO4j4JIEXJKgS3n3WTdSA/chkoScd0+KkKUJA2EYkR/gU87o8i6n6AlESViU3mCUjoIqWkNFmTkcCkogXAwFxViklEBhCaFoLBM4FJUQKS7LrFJRXEZRaTkFhRHKYNCkkSciENSPDiLiL/0rJCInJBgwgoEghVn/mkyKBIiX6/czo62+fi+rVp3kdxm+ce5AkNGXSnv3g5/3j0Yadp90mtSQkUeDRx0NDkv6vJFKm7a8woyZM3BesJZ2mUDGuQOP0w7vefb2wdsOPM/ef5jjs4K4vtRR7H/Q62XOAQfOIzLWzVpyCrOWnIJLf5V1TzxA6+M/Y9revxBoe4UUIVIWJGUh0hYiRYh0IEQyUEDaikkHMu0uEMJZEBcIZx579/TfB8MQCEGwAAtm2i2YdQuFCXiPA6ECAqEwgWABwVAYC4YIhjOPA6FCQuEwwVABoVABwXABkaISItFiXU4hInIECjBERGRcMMtc+hEOMqojCurrm1m1asmovZ4cGzNbDXwdCAI/cM59bsh287a/AegC3uqce3rUC5WcsECAxadfAKdfoOUpRUTGIa0/JSIiIuOSmQWBbwEXAbXANWZWO2S3i4AF3u164DujWqSIiIgcNQUYIiIiMl6dBmxwzm1yzvUCtwOXDtnnUuA2l/EoUG5mNaNdqIiIiByZLiERERGR8WoasC3reSNw+lHsMw1oHnoyM7uezCgNqqurqa+vz2WtdHR05PycE5n6M/fUp7mnPs099Wlu5Vt/KsAQERGR8Wq4dX2Gzlp6NPtkGp27GbgZYOXKlS7X8ytozobcUn/mnvo099Snuac+za18609dQiIiIiLjVSMwI+v5dKDpOPYRERGRPKAAQ0RERMarJ4AFZjbHzAqAq4G7huxzF/AWyzgDaHXOHXT5iIiIiPhPl5CIiIjIuOScS5rZTcC9ZJZRvcU5t9bM3uVt/y5wN5klVDeQWUb1bX7VKyIiIoenAENERETGLefc3WRCiuy272Y9dsCNo12XiIiIHDtdQiIiIiIiIiIieU8BhoiIiIiIiIjkPQUYIiIiIiIiIpL3FGCIiIiIiIiISN6zzNxV0s/MdgOvjMCpK4E9I3BeOTz1uz/U7/5Qv/tD/T7YLOdcld9FjLQR+r6gP0u5pf7MPfVp7qlPc099mlsj1Z/H9X1BAcYoMbMnnXMr/a5jolG/+0P97g/1uz/U75Ir+rOUW+rP3FOf5p76NPfUp7mVb/2pS0hEREREREREJO8pwBARERERERGRvKcAY/Tc7HcBE5T63R/qd3+o3/2hfpdc0Z+l3FJ/5p76NPfUp7mnPs2tvOpPzYEhIiIiIiIiInlPIzBEREREREREJO8pwBhhZrbazF4ysw1m9gG/65kIzGyGmf3RzF40s7Vm9l6/a5pIzCxoZs+Y2e/8rmUiMbNyM7vDzNZ5f/bP9LumicDM/sX7d2aNmf3CzCJ+1yRjj74r5Ja+B4wMfb7nnj67c0ufySfOzG4xs11mtiarrcLM7jez9d79JD9rVIAxgswsCHwLuAioBa4xs1p/q5oQksD7nHNLgDOAG9Xvo+q9wIt+FzEBfR34g3NuMbAc/TcYcWY2Dfj/gJXOuaVAELja36pkrNF3hRGh7wEjQ5/vuafP7hzRZ3LO3AqsHtL2AeBB59wC4EHvuW8UYIys04ANzrlNzrle4HbgUp9rGvecc83Ouae9x+1kPgym+VvVxGBm04GLgR/4XctEYmYx4GzghwDOuV7n3H5fi5o4QkDUzEJAEdDkcz0y9ui7Qo7pe0Du6fM99/TZPSL0mXyCnHMPAy1Dmi8Ffuw9/jFw2WjWNJQCjJE1DdiW9bwRfYCOKjObDZwMPOZzKRPF14D3A2mf65ho5gK7gR95w3t/YGbFfhc13jnntgNfArYCzUCrc+4+f6uSMUjfFUaQvgfkzNfQ53uu6bM7h/SZPKKqnXPNkAmIgSl+FqMAY2TZMG1a9mWUmFkJ8Gvgn51zbX7XM96Z2SXALufcU37XMgGFgFcB33HOnQx04vPwvonAuwb0UmAOEAeKzewf/K1KxiB9Vxgh+h6QG/p8HzH67M4hfSZPHAowRlYjMCPr+XQ0lGlUmFmYzJeWnznnfuN3PRPEa4A3mtkWMkOgzzWzn/pb0oTRCDQ65/p/w3gHmS9FMrLOBzY753Y75/qA3wCv9rkmGXv0XWEE6HtATunzfWToszu39Jk8cnaaWQ2Ad7/Lz2IUYIysJ4AFZjbHzArITCRzl881jXtmZmSuJ3zROfcVv+uZKJxzH3TOTXfOzSbzZ/0h55yS71HgnNsBbDOzRV7TeUCDjyVNFFuBM8ysyPt35zw0AZscO31XyDF9D8gtfb6PDH1255w+k0fOXcB13uPrgN/6WAshP198vHPOJc3sJuBeMjPh3uKcW+tzWRPBa4BrgRfM7Fmv7UPOubv9K0lkxL0H+Jn3A9Am4G0+1zPuOeceM7M7gKfJrHrwDHCzv1XJWKPvCiNC3wNkrNBnd47oMzk3zOwXwCqg0swagY8BnwN+ZWZvJxMUXelfhWDO6TJLEREREREREclvuoRERERERERERPKeAgwRERERERERyXsKMEREREREREQk7ynAEBEREREREZG8pwBDRERERERERPKeAgwRERERERERyXsKMEREREREREQk7ynAEBEREREREZG8pwBDRERERERERPKeAgwRERERERERyXsKMEREREREREQk7ynAEBEREREREZG8pwBDRERERERERPKeAgwRERERERERyXsKMEREREREREQk7ynAEBEREREREZG8pwBDRERERERERPKeAgwRERERERERyXsKMEREREREREQk7ynAEBEREREREZG8pwBDRERERERERPKeAgwRERERERERyXsKMEREREREREQk7ynAEBEREREREZG8pwBDRERERERERPKeAgwRERERERERyXsKMEREREREREQk7ynAEBEREREREZG8pwBDRERERERERPKeAgwRERERERERyXsKMEREREREREQk7ynAEBEREREREZG8pwBDRERERERERPKeAgwRERERERERyXsKMEREREREREQk7ynAEBEREREREZG8pwBDRERERERERPKeAgwRERERERERyXsKMEREREREREQk7ynAEBEREREREZG8pwBDRERERERERPJeyO8C8k1lZaWbPXt2zs/b2dlJcXFxzs87Uak/c099mnvq09xTn+bWSPTnU089tcc5V5XTk+ahkfi+oD/fuaX+zD31ae6pT3NPfZpbI9Wfx/t9QQHGELNnz+bJJ5/M+Xnr6+tZtWpVzs87Uak/c099mnvq09xTn+bWSPSnmb2S0xPmqZH4vqA/37ml/sw99WnuqU9zT32aWyPVn8f7fUGXkIiIiIiIiIhI3lOAISIiIiIiIiJ5TwGGiIiIiIiIiOQ9BRgiIiIiIiIikvcUYIiIiIiIiIhI3lOAISIiIiIiIiJ5TwGGiIiIiIiIiOQ9BRgiIiIiIiIikvcUYIiIiIiIiIhI3hvTAYaZ3WJmu8xszSG2m5l9w8w2mNnzZvaq0a5RRERERERERE7cmA4wgFuB1YfZfhGwwLtdD3xnFGoSEREROSbOOb9LEBERyXshvws4Ec65h81s9mF2uRS4zWW+FTxqZuVmVuOcax6dCqG5tZuP/XYtJxenWDVaLyoiIiJjRrI3xb0/WEu6XCGGiIjkViqZpi+RItmbJtmboi+Roq83RbL/vrd/eyrr3tu3N8WOpjQdy3somRTx+60AYzzAOArTgG1Zzxu9tkEBhpldT2aEBtXV1dTX1+esgM4+x30NXURmuZyed6Lr6OhQf+aY+jT31Ke5pz7NLfVnfkj2pdm5ay/da9JsWbqH2csq/S5JRERGSTrtssKDg0OGZG+avkHhQopkIk1fnxdCZIUOmUCiP5xIk0ykSKePLRwPBI1ggREoMAJhR3dfD+1dnQowRokN03bQf0Hn3M3AzQArV650q1atymkRn3riQXb39ZHr805k9fX16s8cU5/mnvo099SnuaX+zA/ttp/vz/oob+y8iXu+9wIXvnMpc1dU+V2WiIgMI9WXpjeRpK8nEx709qTo60lm7hMp+hLeY6+9L5GiNzFkn54DIUWqL31sBRiEC4KECoOECwKECgIECgwLOwKlacKhNMFgklCwj1Swj75ggl5L0Bvooce66aGLbuuk03XQSTsdro32dCtt6VY6aMPZwfVcWPQ/wOTcdOAJGu8BRiMwI+v5dKBptItYUF3C1p0to/2yIiIiMgZUFVXxr695L59Lf5G3bvko9968hgveWce8k6f4XZqIyJiXHTgcCBD6w4RkVgjhtSeG7pOi1wsi+npSpFNHN6IhEDDCkSDhSJCCSIhwYZBwYZDiskJChQFcKIULpUiHkqSCSZLBXnoDCfoCCRJ00xPooocuuuigkw46XTvtrpWOVDudyU46+zK3RCpx5GIcFFJIcaiY4vDgW1V4GsXhhZltBcUUh4opKSihKFxEcaiY9WvWEy+Jn+B/hdwZ7wHGXcBNZnY7cDrQOprzX/RbWF3KYxv3kE47AoHhBoWIiIjISDCz1cDXgSDwA+fc54ZsXwz8CHgV8GHn3JdGv0q4cuGVPPjCg9w6+5PcEP4s935/LRe8HeafohBDRCa2VCpNojNJoquPRFeSns4+Ep199HQlSXR6bV19A/vs25vmlfv+b2CUw1EHDkEvcCg8EDgURDKBQzgSpKAwSDgSytonSLgw5N1nthFO085+9qda2Nu7lz09O9ndvZs93XvY3eXdd++mpaeFdDoNvWRuhxAJRg4KHKoj1QOPS8Je0JD1uCRcQnG4+KDH4UD4+Pp/Q4qicNFxHTsSxnSAYWa/AFYBlWbWCHwMCAM4574L3A28AdgAdAFv86POhdUl9KZh274uZk0u9qMEERGRCcfMgsC3gNeTGZX5hJnd5ZxryNqtBfj/gMtGv8LBrqi4gq6iLn4Y/Bg3hT/PfT9cSzqdZuGpU/0uTUTkhDjn6OtJDQQN2YFDdijRH0b09G/rzIx8OJyCaIhIcYjCojCFRSEKSmHa9EmZsKGwfwREJmwYCB4i2cFDkILCEMHwoRfo7OrrYnf37kEhxO7u3ezp2sPuvQfaWhOtBx0bsAAVkQqqolVURitZMnkJldFKJhVOOiiIyA4cisPFhAJj+sf1ETGme8Q5d80RtjvgxlEq55AWVJcC8PLODgUYIiIio+c0YINzbhOANyLzUmAgwHDO7QJ2mdnF/pR4QMhCfGXVV7jqd1fx87mf562hj/LALQ24NCw6XSGGiPgvlUyT6MqECz2d/SMgMo97vDBiIIjw7vu3u8NMJhkIGZHiMIVFYSLFIUorIlRNL6GwOBNKRIrDFHohRaQo8zhSFKagKHTQCPfM/E61R3wvzjnaetvY3rWb3W1ZwURWSNE/cqIr2XXQ8eFAmMpoJVXRKmaWzuSU6lMGnlcVVQ08rohUEAwEj72zZVhjOsAYK+ZPKQHg5Z3tvL622udqREREJozhViM7/XhPNpKrlkFmVZg1j63hLbG38LUdX+NX077MG9qv54EfNfBiw4uUz9FlqMdCq+zknvo09/zqU+cc6SSkEpDqzdwnBx47Ur3e80TWPr2QTh7+vIEwBAuyboUQKYXiAggW2OBtWTcLglkSGPwC/S2deP/XeeT31tbexl0P3kVrqpW2VBttybaBxwNt3i3JwW+owAooC5YRC8aoCFYwJzqHWDBGLBgbaC8LllEUKMIs69/lHu+2D9Kk2eX9b6zLt7/3CjBGQSwSpiJirN/Z7ncpIiIiE8lRrUZ2tEZ61bLsVWHKN5Tzkf/7CCtXP83ix8+n8fF9LFy4iNrX5M9EavlOq+zknvo093LRp845entS9HT0ZW6dffR09NLTmaTbu8887xvYp7uzj3TyEP8cGgOjHkpLwkSmhL0REOEDl2p4IyAGHheHKYgePBpiJCRSCZo7mmnqaGJ75/bMfcf2gbbd3btxLQe/t1hBjKpoFdVF1SyNLh24pCN7tERVURXFYY2Yz5Zvf+8VYIySeEmA9bs6/C5DRERkIsmL1ciOx6XzL2Vdyzp++uJtfGr1ImYGZvLHn6zDpR11Z03zuzwRGSEu7Uh0J7OCiMx995Dn2e2Jjj7Sh7g8wwwKi8NESzIhRKwyypRZMSLe8/77aIn3uCQTSvi58EBPsofmzuaBYKKpo4mmzqbMvRdQZAtZiOriaqaVTOPM+Jn07O7hlCWnHBRQFAYLfXpHkksKMEbJtBKjvrGDVNoR1EokIiIio+EJYIGZzQG2A1cDb/a3pKP3ryv/lZf3vcynnvgEP7ryx9ivJ1P/s5dIpxwnrZrud3kichT6J6/sausddOtu76WrNcG2LWl+8+RTg4IJd6iBEQEbFDiUTyli6txDBBFeW2E0hOXZzx49yZ5BgUT/rX80xZ7uPYP2D1mIqcVTmVYyjddOey3xkjjTSqYN3FdFqwbNMVFfX8+qxatG+V3JaFGAMUqmlQRIJJNsa+lidqWGJYmIiIw051zSzG4C7iWzjOotzrm1ZvYub/t3zWwq8CQQA9Jm9s9ArXOuza+6+4UDYb74ui9yze+u4V8f+Wd+dt3PsZ8YD9/+Mum0Y/m5M458EhEZEX2JFF1tCbra+uhqS9Dd1ktnWy/dQ4OKtl6SfemDjjeDSGkBaYNAsVERLz4oiMiMnCggUhIiUlJAQSQ4eM6FPDU0oBgYReE93tuzd9D+oUCImuIa4iVxzp5+NvHi+KCQYmhAIRObAoxRMq0ksyzPyzvbFWCIiIiMEufc3WSWVc9u+27W4x1kLi3JSxWRCr5+7te59u5ref8j/8b33n4zD90Cj/xqPS7tWHH+TL9LFBk3kr2HGinRS1f2fVsvyeGW9jSIloSJlhZQFCugZl4ZRbECorECir37olghRbECIiWZyzQy8wu8avTf7AnoTnbT3NE8EEz0j5zoDyhaeloG7R8KhAZCiVUzVhEvORBQ1BTXKKCQY6IAY5TEvQBj/a4OLqjzuRgREREZMxZXLOaTr/kk73/4/XzpmS/ywes/xP0/WMv/3bGBdNrxqgtm+V2iSN5K9aUHQoeugRESB0ZOZLf39gwTSgCFxSEveAhTPTtGUWkBRWUFmaCirODA85IwgWBglN9h7jnn2JfYxyttrwzctrZtHZiLYmhAEQ6EM6FEcZxzZpwz6PKOmuIaqoqqCNjY7xfJDwowRkk0ZMTLIryslUhERETkGF005yJebHmRH635EYsrFnP5O/4W+1EDf/3NRlzaccrq2X6XKDKqnHP0dPbR0ZKgY3+CjpaezP2+Hjr3HQgmEl3Dr/tZWBQaGClRNaN0YKRE0ZBbtLSAYGh8/vDd3tvO1ratB4KK9ld4pTXzuL3vwM8sIQsxrXQa00qmsXjy4kxA4Y2oiJfEqYxWKqCQUaMAYxQtqC5l/U6tRCIiIiLH7r0nv5eXWl7iM499hvnl83n925ZhZjx65ybSKcepF8/xu0SRnHDOkehM0u6FER37emjflxh43LEvE1qkhswtEQgYxeWFlEwqpCJezPRFk7JGShRmjZwIEwpPjEsWepI9bGvfxittr7ClbcugwCJ7LgrDqCmuYVZsFm+Y+wZmx2YzKzaLWbFZxEvihAL6sVHyg/4kjqKF1SU8ummvViIRERGRYxYMBPnC2V/gmt9fw7/U/wu3X3w757+tlkDAePx/N5NOO067ZM6YmORPJi7nHImuZCaIGGb0RIcXVAyd+NICRnF5AaWTIlTNKmXOiipKygspqSikpDxCSUUmoMi3FTdGQ1+6j6aOpkxI0bqFre1bB8KKHZ07cBxY1qQyWsnM0pm8bsbrMgFFaSakmBGboWVGZUxQgDGKFlSXkkim2drSxRxN5CkiIiLHqKywjG+c8w3efPeb+Zf6f+FHq3/EudctwYLGk7/fgks7Tn/jXIUY4osD4UTWSAlvFEX7vgSdXkiR7B0mnCgroGRShKoZpcxZVknJpAglkwoH7qOxAgITMJzol3ZpdnbuHAgmtrRtycxN0b6VxvZGUu7A/B2lBaXMjs3mlOpTmBmbOTCaYmbpTEoKSnx8FyInTgHGKFpYXQpkViJRgCEiIiLHY/6k+fzna/+Tf6n/Fz7z6Gf4xKs/wbn/sJiAwVP3vIJLO864bJ5CDMkp5xypXsfe7R20t/R4YUR2UHGIcMIYuKyjcnoJs06aTOmkSKbNGz1RVDaxw4l+zjn29uwdmDQzO6zY1r6NRCoxsG80FGVm6UwWTVrEBbMuGLjcY1ZsFuWF5fr7L+OWAoxRNH9KJvFcv7OdC+um+lyNiIiIjFXnzzqff1r2T3zv+e+xZPISrll8Dav+fjEWDPD0vVtJpxyvftN8/RAjx8SlHR37E7Tu7qZtdzet3q1tT+a+t9ux7jePD+xvBkVlmXBi8rQSZi2dPGjURMmkzJKh42FljlzqSfawpW0LG/dvpH5/PXc/fPfAvBSdfZ0D+4UCIWaUzmBW6SxeE3/NoNEUU4qm6O+3TEgKMEZRSWGIaeVRXtZEniIiInKC3r3i3axrWccXHv8C88vnc+rUU3ndNQsJBIxnH9hGOu147ZUL9EOODJLqS9O2Nyuc2N1N657MfdueHlLJAyMoAgGjtDJCWVWUqXNi7GptYvnKWkorMiMoissUThxOV18Xm1o3sal1Exv3b2TT/k1sbN1IY3vjwLwUhhFPxZkVm8XyecsPjKQonUVNSY0mzxQZQn8jRtmC6hLW71KAISIiIicmYAE+e9ZnefPv38z76t/HLy/5JTUlNZx11QIsAM8/1IhLOc66eqFCjAkm0Z3MGkHRNRBStO7qpmN/gqw5HQkXBolVRZlUU8zskyqJVUUp824lkwoHBRT19c0sWFntwzvKb229bWzafyCo2NiaCSuaO5sH9gkFQsyOzWZJxRIumXsJc8vnMq9sHlue3cLrz3m9j9WLjC0KMEbZwupS/rJRK5GIiIjIiSstKOUb536DN//+zbz3j+/lxxf9mGgoymuvXHBgJIaD1129cEKuzjBeOefoaus96FKP/uc9nX2D9o+WhimrihJfWE5ZZZSyKUWUVUWJVUaJloYVcB2lfT37MiMphgQVu7t3D+xTGCxkTtkcTp5yMleUX8G8snnMLZ/L9NLphAPhg8653baP5lsQGfMUYIyyBVNK6E2meWVvJ3OrNAuwiIiInJg5ZXP4/Nmf56YHb+ITf/0En33tZzEzXv2m+QSCxtP3bsWl0pk5MhRijBmpVJqOlp5MMLHrwGUe/XNSZE+WaQalkyPEKqPMe1XVoFEUscooBRF95T9azjn2dO9hY+vGQZd9bG7dTEtPy8B+0VCUeWXzODN+JvPK5w0EFfHiOMFA0Md3IDK+6V+zUXZgJZIOBRgiIiKSE2dPP5ubTr6J/3rmv1hSsYTr6q7DzDKrkQSMp+55hXTacc61S7TaQx5JJdPs39VF605vBMWebtp2d9G6u5v2lgQufeBaj1A4QMwLJGYsqciEE1VRyiqjlE6OEAxpLopj4ZxjR+eOA0FF66aBsKK9t31gv9KCUuaVzeOcGecwt2zuwKUfU4unauSKiA8UYIyy7JVIVi/VSiQiIiKSG+886Z2sa1nHV576CgsmLeDV8VdjZpz+xrkEAsYTv9+CS8O51ynEGG2pvkxQ0dLUSUtz5ravuZP9u7oHhRSFxSHKKqNUz46x4NQoZVVFAyMpisoK9APzcUilUzR1NB0UVGxq3URXsmtgv4pIBXPL5vKGOW8YFFRURivV7yJ5RAHGKCvuX4lEE3mKiIhIDpkZn37Np9ncupl/+9O/cfsltzOjdAZmxml/MxcLGI//72bSacf5b12i1SNGQLIvxf6dXZmQoqmTfc2Zx627DwQVFjDKqqJU1BQz9+QqKmqKKa/OBBWFRQfPkSBHJ5VO0djRyIZ9GwaFFZtbN5NIJQb2mxKdwtzyuVy+4PJMUOGFFRWRCh+rF5GjpQDDBwurS1i/s/3IO4qIiIgcg6JwEd845xtc/furee8f38tPL/opReEiAE69eA6BoPHonZtwacf5/1hLUCHGcUn2pti3o2tgJEX/qIq23d04b0CFBYzyKVEmx4uZf8oUKmqKqYgXUz6liGBY/X680i7N9vbtbNifCSo27N/Axv0bDwoq4sVx5pbP5bSppzGvfN5AUBEriPlYvYicKAUYPlhYXcr/bdhLMpUmpC8OIiIikkMzYjP44tlf5IYHb+Aj//cRvvy6Lw8MgT9l9WwsYPz1Nxtxacfr31GnEOMw+npT7N/RRUtTBy3eaIqW5k7a9nQPLEUaCBhl1UVUTi9h4anVTKopHhhVoXkpjl/apWnubGbj/gMhxYb9G9jcupnuZPfAflOLpzKvfB6nTz2deeXzmF8+n7nlcykOF/tYvYiMFAUYPlhQXUpvKs0rLV3M00SeIiIikmOvnvZq/uVV/8KXn/oyP3jhB7xz2TsHtr3qglkEAsb/3bGB9M1ruPCdSyf8D9p9iRT7dhyYm6J/roq2vT0HgoqgUV5dxJSZpSw6fWpmREVNMWVTohO+/06Ec46dXTsHhRT999lBxZToFOaVz+NNC97E/PL5mZU/yudRWlDqY/UiMtoUYPhgYfWBiTwVYIiIiMhIuK7uOl5seZH/eua/WFSxiLOnnz2wbcX5MwkEjT//cj1/uHkNq9+5dEJc1tDbk8xc+tE0+NKP9r09A/sEQsak6iKmzI6x+MyagUs/YlVRjVY5Ac45dnfvHggoNu7fyPr969m0fxMdfQfmhpscmcz88vlcPv9y5pXPY8GkBcwtm0tZYZmP1YtIvlCA4YP+lUhe3tnB6qU+FyMiIiLjkpnx8Vd/nM2tm/n3h/+dn1/8c+aUzRnYvuyczASfD9/+Mvd87wVW/9NSQuGgjxXnTiqZpmuv48W/NHmjKbpoae6go+XAHAmZoKKYqXPLqH1NDRU1JUyqyUymqQlOj59zjr09ewdGUWSPqMhennRS4STmlc/jkrmXDIyomF8+n/JIuX/Fi0jeU4Dhg6KCENMnRXlZE3mKiIjICIqGonztnK9x9e8yk3r+/A0/p6TgwOjPk1ZNJxA06n/2Evd85wUuetdJhArGXojRl0ixY3MrTev307x+Pzs2t5Hqc2xmHcFwgElTi6iZV07FWcUDl37EKiMKKk5QS0/LQZd9bNy/kf2J/QP7lBWWMa9sHhfNvmggpJhXPo/J0cn+FS4iY5YCDJ8srC5l/U4tpSoiIiIjK14S58urvsw773snH/zzB/n6uV8nYAd+cK87axoWMP7403X8/tvP84Z3LyOc5yFGT2cfOzZmAoumDfvZ/Uo76bTDDCpnlLL0rGm0JBo5+8LTiVVGCQTM75LHtI7eDtbvX88j7Y/wl8f+MhBWtPS0DOxTGi5lXvk8zpt53qARFZXRyoFJZEVETpQCDJ8sqC7hz+t3ayUSERERGXGnTj2V95/6fj77+Gf5znPf4cYVNw7aXvuaOIGA8eBtL/L7bz3Hxe9eTrgwf0KMztYEzRu8wGL9fvY2dYDLXAZSPTvGigtmEl9QTs3cMgqima+39fXbKZ9S5HPlY0synWRr+1Ze3vcyL7e8zPp961m/fz3bO7YP7FPcXsy8snm8bvrrBkKK+eXzmVI0RUGFiIw4BRg+WTillL6UY8veroE5MURERERGyjWLr+HFlhf57nPfZfGkxZw367xB2xefWYMFjAdvbeB333yOi29cRkFk9L8qOudo39tD04b9A4FF667MahShwiBT58Q47ZI5xBeUUz07NiYveckHe7v3sn7/el5ueTkTWOx7mY37N9Kb7gUgaEFmx2azrHIZVyy8goWTFv7/7N13fJ1l3fjxzzc7adLdhi7oSkFAQWgRHFjAwVBAZSkq8qC498L1uBV/Pvq4H8WJExkqyBIEIg6QBERktqUtbSm0dDdNV5Lr98c5KWlId5L7nOTzfr3O65z7uq/7vr/nStrc53uuwYqHV/CqE15lokJSZkxgZGRGfW7Jp7nL1pvAkCRJfS4i+OTRn+TRNY/y8b99nF8N/RXTR0zfrs6Bz9uPkpLg5p8+yLXf/jevePdhfZ7ESCmx+snWbcmKJ+atoWV1brLNypoyxk0fziEvnMD4huGM3r/WlUD20Ob2zcxfM/8ZyYqVm1ZuqzO6ejQzRszgtQe9lhkjZzBjxAymDptKRWnFdudqnNdo8kJSpkxgZGT62FoiciuRnPTsrKORJEmDQWVpJf87+385+9qzec9t7+E3p/zmGctTNsyqJ0qCm378AH/81r284t2HU1nde7eMHR2JlUtatiUsls5bw6aWrQDUDK1gfMPwbY+R44YQzl+xW1JKPLnhyW0Jirmr5zJn9RwWrltIe2oHcj//acOn8aKJL6JheAMzRs6gYXiDE2pKKhomMDJSXVGaW4lkuSuRSJKk/lM/pJ5vHPcNzv/T+Xz09o/y3RO+S2nJ9sMwph85liiBm374ANd8815Ofc9hVNaU79X12rd2sPyxdduGhDzx6Fq2bsp9oB46uorJh45iXD5hMWxMtd/w74YNWzdsS1B0Jivmrp7L+q1P31dOqJ1Aw4gGTjjgBGaMmEHDiAb2r9ufshJv/yUVL/8Hy9CMsXXMdSlVSZLUzw4fezifeN4n+Owdn+Vb//oW7z/y/c+oM+25Y3n5hcGffng/V3/jXk597+FUDdl1EmPr5naenP/0hJvLFq6jfWsHACPGDWHGUfsxvmEY46cPp3ZEVa+/t4GkvaOdResXbZesmLN6zvaTapYPYcaIGZw89WRmjMgN/5g+fPp2y+VK0kBhAiNDDfV13D73Kba2d1DueE5JktSPzphxBg+tfIif3P8TDhp5ECdNOekZdaYePoaT3vpsbrjkP1z9jX9x2nufS1Xt9kmMTRu28sSjTycsVizqtqTpsbn5K8ZNH0Z1bcUzrqGc1ZtWbzf0o3NSzU3tmwAoiRIOGHoAh44+lFc3vHpbsmLckHH2WpE0aJjAyNCM+lq2ticeW7mB6WPrsg5HkiQNMhcddRFz18zlv//+30wZNoWDRh70jDqTnzOak9/2HG74/n/4w//+i5decDCrlm7gifz8FSuXbthuSdPnvmx/xnVb0lQ5KSVWbFzBgrULco91C5i/Zj7z1szjqY1Pbas3smokM0bM4MwDz9yWqJg6bCpVZfZYkTS4+VclQ50rkcxZ1mICQ5Ik9bvy0nK+PvvrnH3t2bz31vdy2SsuY0TViGfUO+DQUZz8jmdz/f/9h8s+dxeQW9J03NShTDtirEuadrO1YyuL1y9+OlGxdgEL1y5kwdoF281TUV1WzZRhUzhm/DHb5qmYMWIGo6tHZxi9JBUuExgZmjamcyWS9Zz87HFZhyNJkgah0dWj+eZx3+S8G87jQ3/5ED946Q96nOhx/4NH8eoPHcET89ay39RhLmkKrN+ynoVrFzJ/7fztelUsXreYttS2rd7Y6rFMGTaFU6aewpRhU7Y96mvqHf4hSXvABEaGqitKmTSihrnLWrIORZIkDWKHjj6UTz//03zib5/ga81f46NHfbTHemMPGMrYA4b2c3TZSimxrHXZ9kmK/KPrsI+yKGP/ofszddhUTtj/BKYOm8qUYVOYPHSyE2pKUi8xgZGxGfW1zHElEkmSlLFTp53KQysf4pcP/ZKDRh7EadNPyzqkfrWlfQuPrXtsu54Una83tm3cVq+uvI4pw6fw/PHP39aTYuqwqUyom0B5yd4tNStJ2j0mMDLWUF9H4yOuRCJJkrL3gZkfYM7qOXzujs8xbfg0Dh19aNYh9bq1m9eyYO2CZ/SoWNKyhI7Usa3e+CHjmTJsCkc0HLHdsI9RVaMc9iFJGTGBkbEZ9bW0dSQWrthAQ70TeUqSpOyUl5TzPy/+H8659hzee9t7+e0rfluUE0q2d7SzYusK/rrkr9slKxauW8iqTau21asoqeCAYQfwrFHP4uSpJzNlaC5JccDQA6gpr8nwHUiSemICI2MNY59eicQEhiRJytqIqhF88/hv8obr38AHGj/Aj1/2Y8pLC3NoxNrNa1m4biEL1y5k4bqF24aALFq3iC0dW2Bprt6IyhFMGTaF4yYdt11vivFDxlNa4sopklQsTGBkbPrYp1ciOQVXIpEkSdk7aORBfO4Fn+Mjt3+Ei++6mE8d86nMYulckvSxtY/lkhVdEhZde1OURRkT6yYyeehkXjjhhWx+YjMnPe8kJg+d3OPSsJKk4mMCI2NV5aXsP7KGucudyFOSJBWOk6acxEOrHuKn9/+Ug0YdxJkzzuyza6WUWLlp5bbExLbndQtZsn4J7al9W92RVSOZPHQyx006jslDJzN52GQmD538jEk0Gxsbee7Y5/ZZzJKk/mcCowA0jK1jjkupSpKkAvPe576XOavm8KV/fomG4Q0cPvbwfTrfprZNPLbuse2TFGtzQz/Wb336y5zK0kr2H7o/M0bM4GUHvGxbkmLysMkMrRhcy7hKkp5W1AmMiDgR+CZQCvwopXRxt/3DgF8C+5N7r/+TUvppvwe6CzPqa2l8ZDlb2jqoKHMlEkmSVBhKS0r5yrFf4bXXvZb3N76fy065jPoh9Ts9piN1sGzDMhasW7AtOdGZqHhiwxMk0ra69TX1TB42OTeB5rAp25IU44aMoyS8J5Ikba9oExgRUQp8F3gpsARoiohrUkoPdqn2TuDBlNIrI2IM8EhE/CqltCWDkHdoRn1dbiWSlRuY4USekiSpgAyrHMa3jvsWr7v+dby/8f389MSfUllaScuWltykmflERdfeFJvaN207vqashsnDJnP42MM5fdjpuSTF0Mmu9CFJ2mNFm8AAjgLmpZTmA0TEZcBpQNcERgLqIrdYdy2wCmjr70B3paG+FshN5GkCQ5IkFZrpI6bz5Rd+mfc1vo8zrjmDlq0trNi4Ytv+kihh/JDxTB42mVn7zdquN8WY6jHkbsUkSdo3xZzAmAAs7rK9BHhetzrfAa4ht4hWHXB2Sqmjf8LbfdPG1FISOA+GJEmD1YK/UrduLjw1DipqoWJI7rm0cG7VTjjgBD7+vI9z44IbOWzMYU/PSzF0MvsP3Z+K0oqsQ5Sk4pQSpI6nn+nc7qks7aCso+cy2MW5uh6XnlE2bM39sGVW7u9SASicv4p7rqdUfuq2/XLgXuB4YBpwc0T8NaW0brsTRVwIXAhQX19PY2Njrwfb0tKy0/OOqQ7+cf98jihf2uvXHoh21Z7ac7Zp77NNe59t2rsGQ3vuxnxZkd9/MtAKvCmldE+/BtnRDpe+giMBul+5rDp301hZm09s1HbZruvyeki37fyj+76yStiH3hCvPei1vPag1+7Lu5X2TucHq64fvOj+Qa7b/m0f3nr40PaMel330cO+HXzwI+U+gezW+bu/Toxa8W94ZONuxNjTe9/1+Xcaf2+cv6d23+lrdnK+Hfwcu/48dvXzTx0ctmY1LBi+k59XT+9rF78Te9KuO6y7k/YsYM8FeP5LYOxBWYcCFHcCYwkwqcv2RHI9Lbo6H7g4pZSAeRGxADgIuKtrpZTSJcAlADNnzkyzZ8/u9WAbGxvZ2Xmfs6iZ+U+17LSOnrar9tSes017n23a+2zT3jXQ23M358s6CWjIP54H/B/P7NHZ15HCedfyn7vv5NkHToEtLbC5BbZsgC3rc8+bW3LlW1pg42pYu+Tp7c0t0GWZ0Z0qKeshuVELlXVPv64Ysv129+RJWdUuPhiwk309be/OB6eevk3c+YeI8Y8/DE3znvlBa7c+MO3gQ82uztGrH+h29oFtZzF0f81OzrWzD3LPPNdRrRvgvqodtNGu3mfX87EHdfNlA9SzAe7POoodCYiSfNJzZ6+j2+uSnl/v9Lju5T2dg12cL/c6On/vS0qfWW/b8d23ezjnDuuW5L9K3926O2uf0p7PHSW7OGf385bs5Nqd52IX5+o5hnv/fR+HD5vYJ79he6OYExhNQENETAEeB84BXtetziLgBOCvEVEPHAjM79cod9OM+lpufdiVSCRJ6kW7M1/WacDP81923BkRwyNiXErpiX6LsqQEpryIlY+1w7Nn7/nxKUHbpnyiI5/w6Jrc2NLSw77O7fzrDSuePmbLhtz5itwMgLm9fdZe+EC3yw9rO/kAuLMPWzt63XlMyY6uuTvvIVfesvwpaur365v3vNt1u3yY3Wndntpid+vtzofa3f2QuvPz333PvzjyyCN38/ydH0J39/yd+9iD83d938Xp3gGenO9vaxaRS2QXiKJNYKSU2iLiXcCfyHUL/UlK6YGIeFt+//eBzwM/i4j/kPtv7qMppRU7PGmGZtTX0d6RWLBiAwfu50SekiT1gt2ZL6unOhOAZyQw+nrIae8P6SkDhucfXYrKgF0s/hEdbZS2b6K0fWP+sWnbc0nHViBInR+aduP1vu7vuW4JqfNDbA91N2xoZciQ2h2cD9K2ZVp3dk2ALh8CB7mW6hZqazP+IJO6PRe0BOy8d1RLyTga567baR3tmcEwPLI/FVp7Fm0CAyCldD1wfbey73d5vRR4WX/HtTcaxuaSFnOWrTeBIUlS7+jpU2f3jz27UydX2MdDTgf6kJ7+1tjYyPNtz17l72jvs017n23auwqtPR2rUCCmjhlCScDcZeuzDkWSpIFid+bL2p06kiSpAJjAKBBV5aVMHjXEpVQlSeo92+bLiogKcvNlXdOtzjXAGyPnaGBtv85/IUmSdltRDyEZaKaPrWXOcntgSJLUG3ZzvqzryS2hOo/cMqrnZxWvJEnaORMYBWRGfR23PLyczW3tVJaVZh2OJElFbzfmy0rAO/s7LkmStOccQlJAGuprt61EIkmSJEmSnmYPjAIyo75zJZIWDtpvaMbRSJIkQVt7Bw89sZ6mhatofmwVK1u2UD+0inHDqp5+HpZ7HlNbSVmp349JkvqGCYwCMnXMEEpLwpVIJElSZlq3tHHvojXctXAVzQtXc8+i1bRuaQdgwvBqxg2r4l+LV3Pj/ZvZ0t6x3bElAWPqKtlvWDX7Da1k3LDqbUmO/YZVsd/Q3HNVuUNlJUl7zgRGAaksK+WAUTXMMYEhSZL6yVPrN3P3Y6toWria5oWruH/pOto7EhFwYH0drzliIrOmjGTmASMYP7x623EpJVZt2MKT6zbx5NpNTz/nX89/agP/mLeS9ZvbnnHN4TXl25IZXXty5BIfufKhVWVERH82hSSpwJnAKDANY2uZ61KqkiSpD6SUm2ureeHq/JCQ1dvm3qooK+HwScN524unMnPySI7YfwTDqst3eK6IYFRtJaNqKzlk/LAd1mvZ3LZdYuPJtRu3S3rc//haVrRsecZx1eWlPQ5T6Uxw7DesitFDKikpMckhSYOFCYwCM6O+jpsfXOZKJJIkaZ9tbe/ggaXraF64KpewWLialRtyyYLhNeXMPGAk58yaxMzJIzl0wtA+ufeorSxj+thapo+t3WGdzW3tLF+3+Rm9ODqf/7lgFcvWbaKtI213XFlJUD+0ivoehqssXdXOfk+uo66qnNrKMmoryyg12SFJRc0ERoFpqK+jI8H8pzbwrHFO5ClJknZfy+Y2/rVo9bbhIP9atIaNW3PzV+w/soYXHziGWZNHMmvyCKaOri2Y3guVZaVMGlnDpJE1O6zT0ZFYsWEzy9Zu5omuvTjySY6HnljHrQ8v3/Z+Ab5811+3O0dnIqOuqozaqjLqqsqp69yuzG/n9w2tKqO2srxL3TKGVpVTWVbi0BZJyogJjAIzoz737cScZetNYEiSpJ1avm4TTduGg6ziwaXr6Ei5yTSfNW4oZ8+axKzJI5k5eQT1Q6uyDneflJQEY+uqGFtXxbMn9jxkJaXEuk1tLFu3iZv+ehdTZhxMy+atrN/Utu3RdXvtxq0sWd1KS367a/JjR8pK4umkRmX5tmRHZ0+PnpIjXfd1JktcrUWS9pwJjAIzZXTnSiTOgyFJkp6WUuLRp1qeTlgsXM2iVa0AVJWX8NxJI3jXcdOZOXkkz91/OHVVO56/YqCKCIZVlzOsupylo0uZ/Zxxe3R8W3sHLZvbuiQ8tnbZ3sr6/OuWLvvWbWrj8TWbaNm8fttx7d2GuvSkurx0W0JjSGUZ1eWl1FSUUlNRRnXF069r8q87y6rLny575n6HyUga2ExgFJjKslImuxKJJEmD3pa2Du5fupbmhau4a8Fq7n5sFatbtwIwakgFMyeP4I3HHMDMySM5ZPxQyv1Gf5+VlZYwvKaC4TUVe32OlBKbtnawvktPj5YdJEDWb2pj/eatbNjczsYt7TzVspnWLa1s3NJO65ZcWfelaneloqwkl9QoL6Wmsiyf9HhmcqS6opQh+QRIT8mRzoTIkC6vJSlr/k9UgBrG1vGICQxJkgaV1q2JxkeWb1sh5N7Fa9jclvvwOmX0EF7yrPptw0GmjB7iPAwFKiKozn/oH1u37+fb2t6xLZnRuqUt93prZ4Ijt93add+27XY2bn16/4qWLWzYx+RIWUDFrTdSXlqSf0S359zrstISKkpLKMuXd33dU/2eXpeVxj6do7QkKImgJKC0JPz3Ig0QJjAK0Iz6Wm568Ek2bW2nqtyVSCRJGsjWb9rKWT+4k4efaCXRRGlJcMj4oZz7vAOYNXkER04ewdi64p6/QnuvvLSEYdUlO13Sdm+1tXfQurVr0uPphMfG7V7nnh95dAHjJ0xka3sHWzsSW9s6nvG6rSOxpa2DjVvb2bqpgy1tubKt7R25Oj28TrsecbPPIqA0gpKSoDQin+DIJTeeTnbkX5f0VLdzX/647vtLgtL8+Uq6HNNZ/sy6udePP76Zv7Y8SEnkkl8RbEu8BLGtvGTbvmfWK8knZ7YdFzs+riSCAEpKuh/XeczT9bpuB08/d7Yn5GJ8+jXbXnTWjKDLMT2VPX1Q9/N0v17Xc9Lt+K77Fq/v4MGl60jkfrE6f7+2PZO6vM71mnr6deeZu9fpPEfafpsEPdXbyTU663ekRFtHoqMj/5wS7R1Pl7Xnt7d7pER7e7d9Xcq6nqttB2XbXWdH1+iA9o4O2jsSLRta+e2hG5g8egiFwARGAeq6EsnB453IU5KkgayuqpzpY2s5cMhGzpx9BIdPGs6QSm/R1PfKSksYWlrC0N2cL6Wx7HFmzz64V2NIXT5MbWnvoK09l9TomvjoMQnS1kFbRwdb2p/5emt7x7YPbh0J2rt+UMuXt3ewXVna9kGOHup2PZ4udRNtHR1sbsuVd6/bkZ6+fvfyzrKtbW2UPrk4Xzf3oTclnt6GfknwDDh//+uu6xS5zqRcZxKuNILS0tiurCSCsh2UlXQpKyspoap8+7LO8618ahOV5YUzRNG/jgVoRn2uv+Hc5etNYEiSNAh8+7XPpbGxkRdMH511KFK/ivyHqbJSBmXP48bGRmbPnr3TOimf2OhMaPSU6OhIQLftzl4AHWnHzx35LgEdndsd2x/XkU/YdHTpOrCjngnPKOvWO6Hz2Gf0jOh2fOeLrvXSM86TtjvntismeOCBBzj00EPo3qvjGT06uvbe6Fbv6ddP19muh8hOeplsf83O2HqO5ekEQq5nTlmXHjzblZXEM5IV/bUMdmNjI+OGVffLtXaHCYwCNGX0EMpKwok8JUmSpEFu25AR+ucDa7GrXvkIsw/dsxWIVDwKpy+ItqkoK2Hy6CHMcSlVSZIkSZIAExgFq2FsLXPtgSFJkiRJEmACo2A11NexaFUrm7a2Zx2KJEmSJEmZM4FRoGbU19KR4NGnHEYiSZIkSZIJjAK1bSUS58GQJEmSJMkERqGaPMqVSCRJkiRJ6mQCo0BVlJUwxZVIJEmSJEkCTGAUtIb6WuYutweGJEmSJEkmMApYw1hXIpEkSZIkCUxgFLQZ9XWkBPOWO4xEkiRJkjS4mcAoYDPqawEcRiJJkiRJGvRMYBSwyaOHUF4aTuQpSZIkSRr0TGAUsPLS3Eokc11KVZIkSZI0yJnAKHAN9XX2wJAkSZIkDXomMApcw9haFq9uZeMWVyKRJEmSJA1eJjAKXOdKJI8+ZS8MSZIkSdLgZQKjwHWuRDLHeTAkSZIkSYOYCYwCd8AoVyKRJEmFYfOjj7Lu5ptJKWUdiiRpEDKBUeDKS0uYOrrWlUgkSVLmln35Yh5/93tY8s530bZqVdbhSJIGGRMYRaChvpY5y01gSJKk7KS2Njbecw+VDQ1s+OtfmX/aabT89W9ZhyVJGkRMYBSBhrF1LFm9kdYtbVmHIkmSBqlNDz1ER2sro9/xdiZfcTllw4ez+C1v4ckvfYmOzZuzDk+SNAiYwCgCM+prcyuRLN+QdSiSJGmQam1qBqD6yCOpOuggJl9xBSNe/3pW//wXLDzjTDY9MifjCCVJA50JjCLQUF8HuBKJJEnKTmtTExUHHED52LEAlFRVsd8nP8GkS35A2+rVLDzzTFb9/Oekjo6MI5UkDVQmMIrA5FE1VJSWOA+GJEnKROrooPXuu6k5atYz9tUeeyxTr/4DQ17wApZ96cssfsuFbF2+PIMoJUkDnQmMIlBWWsLUMUOY61KqkiQpA5vnzqVj3TpqZs7scX/ZqFFM/N532e8zn6b17rtZcOpprL/lln6OUpI00BVEAiMinvEXrqeywayhvs4hJJIkKROtdzUB7DCBARARjDjnHKZcdSVl48ex5J3v4on//jQdra39FaYkaYDLNIEREVURMRIYHREjImJk/jEZGJ9lbIWmYWytK5FIkqRMtDY3Uz5+POUTJuyybuW0aUy57DJGvfkC1lxxBQte/Ro23v9AP0QpSRrosu6B8VbgbuCg/HPn42rgu7s6OCJOjIhHImJeRFy0gzqzI+LeiHggIv7Si7H3qxn1tQDMW+4wEkmSdiX/hcjNETE3/zxiB/V+EhHLI+L+/o6xWKSUaG1upmbWjntfdBcVFYz90IfY/6c/pWPjRhaecw4rLvkhqb29DyOVJA10mSYwUkrfTClNAT6UUpqaUpqSfxyWUvrOzo6NiFJySY6TgIOB10bEwd3qDAe+B5yaUjoEOLNP3kg/eHolEhMYkiTthouAW1JKDcAt+e2e/Aw4sb+CKkZbFiygfeVKqncyfGRHhhz9PKZe/QfqXvISnvr611n0pvPZunRpH0QpSRoMsu6BAUBK6dsRcWhEnBURb+x87OKwo4B5KaX5KaUtwGXAad3qvA74XUppUf46RTsl9gEjcyuRzHUeDEmSdsdpwKX515cCp/dUKaV0O7Cqn2IqSq1NzQAMmfXMFUh2R+nw4Uz4368z7stfZtMDDzD/tNNZd/31vRmiJGmQKMs6AICI+DQwm1xPiuvJ9ar4G/DznRw2AVjcZXsJ8LxudWYA5RHRCNQB30wpPeOcEXEhcCFAfX09jY2Ne/M2dqqlpWWfz1tfA3c89BiNNct6J6gi1hvtqe3Zpr3PNu19tmnvGuDtWZ9SegIgpfRERIzNOqBi1drcTOmY0ZQfcMBenyMiGP6q06k58giWfvgjPP6BD9Lyl79Q/6lPUVpb24vRSpIGsoJIYABnAIcB/0opnR8R9cCPdnFM9FCWum2XAUcCJwDVwB0RcWdKac52B6V0CXAJwMyZM9Ps2bP3/B3sQmNjI/t63uc+8S/ufmz1Pp9nIOiN9tT2bNPeZ5v2Ptu0dxV7e0bEn4H9etj1iT66Xp9+4VGQCaWUGP23v7F16lT+8pdemkrswrcw5PobSNf8kZV//zvrzj+frdOm9c65uyjI9ixytmnvs017n23auwqtPQslgbExpdQREW0RMRRYDkzdxTFLgEldticC3QdVLgFWpJQ2ABsi4nZyiZI5FKGGsbVc8++lbNjcxpDKQvnRSZKUjZTSS3a0LyKWRcS4fO+LceTuLfb1en36hUchJpS2LFnCo6tXM/6UkxnZm7GdcAKt557L0o98hLKvfZ3Rb3sbo9/xdqKs9+5vCrE9i51t2vts095nm/auQmvPgpgDA2jOT7j5Q3KrkNwD3LWLY5qAhoiYEhEVwDnANd3qXA28KCLKIqKG3BCTh3o18n7UOZGnK5FIkrRL1wDn5V+fR+6eQHuoc/6Lmr2YwHNXao54LlP+8HuGvfKVrPje93js3NezZdGiXr+OJGngKIgERkrpHSmlNSml7wMvBc5LKZ2/i2PagHcBfyKXlLg8pfRARLwtIt6Wr/MQcCNwH7mEyI9SSkW7TFrnUqpznMhTkqRduRh4aUTMJXdvcTFARIyPiG0zSEbEb4A7gAMjYklEXJBJtAWqtamJ0mHDqJw+vU/OX1pby/ivXMyEr3+NzfPns+D0V7Hmd78npe6jgiVJKpwhJETEBOAA8jFFxLH5mcF3KKV0PblJP7uWfb/b9leBr/ZutNk4YNQQKspKmGsPDEmSdiqltJLcHFjdy5cCJ3fZfm1/xlVsWpubqZ41kyjp2++8hp58MtWHH87Sj17EEx//OC233864z3ya0uHD+/S6kqTiUhAJjIj4CnA28CDQni9OwE4TGINNaUkwbUytPTAkSVKf27psGVsXLWLE6/onx1M+fjz7/+ynrPzxT3jqW99i47/+xfivfIUhR3dfZE6SNFgVxBAScmuzH5hSOjml9Mr849SsgypEM+prmbvMHhiSJKlvPT3/xax+u2aUljL6wrcw+bLLKKmuZtH557Psq18lbdnSbzFIkgpXoSQw5gPlWQdRDBrG1vL4mo20bG7LOhRJkjSAtTY3UTJkCFXPOqjfr1196CFM+d1VDD/rLFb9+CcsOOccNj/6aL/HIUkqLJkmMCLi2xHxLaAVuDcifhAR3+p8ZBlboXIlEkmS1B9am5upPvIIorQ0k+uX1NQw7rOfYeJ3v0PbE0+y4DVnsPo3v3GCT0kaxLLugdFMbtnUa4DPA//Ib3c+1M2MfALDeTAkSVJfaVu1ii3zHu3X4SM7UnfCCUy5+g/UzJzJk5/9HEve/g7aVq7MOixJUgYyncQzpXTp7tSLiKtSSq/p63iKwf4ja6gsK2GuCQxJktRHWpvz81/MmplxJDnlY8cy6ZIfsPqXv2L5//wP8087nfFf+iK1xx6bdWiSpH6UdQ+M3TU16wAKxdMrkTiERJIk9Y3W5maiqorqQw7JOpRtoqSEkW98A5OvuIKykSNZfOFbefILX6Rj06asQ5Mk9ZNiSWA42LGL3Eok9sCQJEl9o7WpmerDDycqKrIO5RmqDpzB5CsuZ+R5b2T1L3/JwjPPZNPDD2cdliSpHxRLAkNdNNTXsXTtJtZv2pp1KJIkaYBpX7eOzQ8/XDDDR3pSUllJ/cc+xqQf/pC2NWtYeOZZrPzZz0gdHVmHJknqQ8WSwIisAygkDWNrAVcikSQNHBFx5u6Uqe+13nMPpFQQE3juSu2LXsjUq69myLHHsvzir7D4zW9m67LlWYclSeojxZLA+GjWARSSzpVI5joPhiRp4PjYbpapj7U2NRHl5VQf9pysQ9ktZSNHMvE732a/z36W1n/dy4JTT2XdzTdnHZYkqQ9kugpJRAwld3MyEbghpfTrLvu+l1J6B0BK6aaMQixIk/IrkbiUqiSp2EXEScDJwISI+FaXXUOBtmyiGtxam5upes5zKKmqyjqU3RYRjDj7LGpmzWLphz/M4+9+D0Nf8HzajzyS0rq6rMOTJPWSrHtg/JTc8JCrgHMi4qqIqMzvOzq7sApbaUkwfWwtcxxCIkkqfkuBZmATcHeXxzXAyzOMa1Dq2LCBTQ88SM3Mwp3/Ymcqp05h8m9+zagLL6TqH3fw6Mkns/aP15KS88FL0kCQaQ8MYFpK6TX513+IiE8At0bEqVkGVQxm1Ndx5/yVWYchSdI+SSn9G/h3RPw6peTs1BlrvfdeaGsr2gQGQFRUMPYD72fOqJFMuPY6ln74w6y58kr2++9PUTltWtbhSZL2QdY9MCojYlsMKaUvApcAtwOjMouqCDTU1/KEK5FIkgaOyRFxZUQ8GBHzOx9ZBzXYtDY3Q2kp1c99btah7LO2Aw5g8mW/Yb/PfJpNDz/M/NNOZ/n//A8dGzZkHZokaS9lncD4I3B814KU0qXAB4EtmURUJBrG5ifydBiJJGlg+Cnwf+TmvTgO+Dnwi0wjGoQ2NjVTdfDBlNYOyTqUXhGlpYw45xym3XA9w049lZU/+jGPvuKVrLvpJoeVSFIRyjSBkVL6SErpzz2U35hSasgipmIxoz63lOpcJ/KUJA0M1SmlW4BIKT2WUvoM3b7kUN/q2LyZjffdV9TDR3akbORIxn/pixzw619ROnQoj7/nvSy+8K1seeyxrEOTJO2BrHtgABAR9RHx44i4Ib99cERckHVchWzSiBqqykuY41KqkqSBYVN+WOnciHhXRLwKGJt1UIPJpvvuI23ZQs2sWVmH0mdqjjiCKVddSf3HLmLjPfcw/5Wn8tS3v0PHpk1ZhyZJ2g0FkcAAfgb8CRif354DvC+rYIpBSedKJPbAkCQNDO8DaoD3AEcCbwDOyzKgwaa1uRkiqDnyiKxD6VNRVsbI885j6vXXU/eSl7Diu99l/itPpeUvf8k6NEnSLhRKAmN0SulyoAMgpdQGtGcbUuGbMbaOufbAkCQNACmlppRSS0ppSUrp/JTSq1NKd2Yd12DS2tRE5YwZlA4blnUo/aK8fiwTvv419v/pT4iyMha/9W0sefe72bp0adahSZJ2oFASGBsiYhSQACLiaGBttiEVvob6Op5ct4l1rkQiSSpyETEjIn4YETdFxK2dj6zjGizS1q20/uveAT18ZEeGHHMMU6/+A2Pe/35a/vo3Hj3lFay45IekLc4nL0mFplASGB8ArgGmRcTfyc08/u5sQyp8DWM7J/K0F4YkqehdAdwDfBL4cJeH+sGmBx8kbdw4ICfw3B1RUcHot17ItOuuZcgLns9TX/86809/FRvu/GfWoUmSuiiIBEZK6R7gxcDzgbcCh6SU7uvcHxEvzSq2QjajPr+UqvNgSJKKX1tK6f9SSnellO7ufGQd1GDR2tQEQM3MIzOOJFvlEyYw6TvfYeL3/4+0ZQuL3vQmHv/gh9i6fHnWoUmSKJAEBuTmvUgpPZBSuj+l1H1MxFcyCarATRxRTXV5qSuRSJKKVkSMjIiRwB8j4h0RMa6zLF+uftDa1EzF1KmUjR6ddSgFoW72bKZe+0dGv+MdrL/pJuafdDKrfv5zUltb1qFJ0qBWMAmMXYisAyhEnSuRzF1uDwxJUtG6G2gmt+LIh4F/5Ms6y9XHUns7rffcM2iHj+xISVUVY97zbqb+8Rqqn/tcln3pyyw440xa7/lX1qFJ0qBVLAmMlHUAhaqh3qVUJUnFK6U0JaU0Nf/c/TG1s57DSfvO5kceoWP9empmmcDoScXkyUz64SVM+OY3aV+zhsde9zqWfuITtK1alXVokjToFEsCQzswo76OZes2s3ajK5FIkgY0h5P2kdbmXEcXe2DsWEQw9OUvY9p11zLqzRew9uprePSkk1l92W9JHR1ZhydJg0axJDAWZh1AoepciWSew0gkSQObw0n7SGtTE+UTJ1I+blzWoRS8kiFDGPuhDzH1D7+nasYMnvzMZ1h4zmvZeP8DWYcmSYNCwSQwIuLQiDgrIt7Y+ejcl1J6dZaxFbLOlUicyFOSNMA5nLQPpJRobWq298Ueqpw+nf1/finjv/r/2Lp0KQvPPJMnP/c52teuzTo0SRrQCiKBERGfBr6dfxwH/D/g1EyDKhIThneuRGIPDEmStGe2PPoo7WvWUDNrVtahFJ2IYNgrX8m0G65nxOtfz+rLfsujJ53Mmt//gZTMt0lSXyiIBAZwBnAC8GRK6XzgMKAy25CKQ0lJ0FBfy1x7YEiSilhEVEXEByLidxFxVUS8PyKqulRZmFVsA1lrUxOAE3jug9K6Ovb7xMeZcuUVVEyaxBMf+xiPvf4NbHpkTtahSdKAUygJjI0ppQ6gLSKGAsuBqbs4RnkNY+vsgSFJKnY/Bw4h1xvzO8CzgF907nQ4ad9obWqmbOxYyidNyjqUold18MEc8JtfM+4Ln2fLo4+y4NWvZtnFX6G9ZUPWoUnSgFEoCYzmiBgO/JDcuu/3AHdlGlERmVFfy/L1m1nb6kokkqSidWBK6YKU0m35x4XAjKyDGshSSrQ2N1MzaxYRzpHaG6KkhOFnnMHUG65n+Ktfzaqf/Yz5J5/MuhtucFiJJPWCgkhgpJTekVJak1L6PvBS4Lz8UBLthob63Eokc12JRJJUvP4VEUd3bkTE84C/ZxjPgLd10SLali93+EgfKBsxgnGf/xyTL/sNpaNH8fj7P8DiCy5g8/wFWYcmSUWtIBIYABHxnIg4FTgCmB4RdhXdTQ1jXYlEklScIuI/EXEf8DzgHxGxMCIWAHcAx2Yb3cDW2twM4Aokfaj68MOZcsUV1H/yk2z8z/3MP+00ln/jG3Rs3Jh1aJJUlMqyDgAgIn4CPAd4AOjIFyfgd5kFVUQmDK+mpsKVSCRJRekVWQcwWLU2NVM6YgQV06ZlHcqAFqWljHz9uQw98eUs/+pXWfn9H7Dumj9S/8lPUHf88VmHJ0lFpSASGMDRKaWDsw6iWJWUBA1jax1CIkkqOimlx7KOYbBqbWqiZuZM57/oJ2WjRzP+K19h2Gtew5Of+xxL3vFOamfPpv6Tn6Bi4sSsw5OkolAoQ0juiAgTGPugob7OISSSJGm3bF26lK2PP+78FxkYctRRTP397xn74Q+z4a67mH/KK3jqO9+lo7U169AkqeAVSgLjUnJJjEci4r4u42G1m2bU1/LU+s2sad2SdSiSJKnAtd59NwA1s2ZlHMngFOXljLrgv5h2/XXUHnccK77zHR496WTW/OEPpI6OXZ9AkgapQklg/AR4A3Ai8Epy42FfmWlERaZzIs+5y+2FIUmSdq71riZK6uqonOFKtVkq328/Jn7jfzngV7+kbMwYnrjoYyw86+xtE6xKkrZXKAmMRSmla1JKC1JKj3U+sg6qmHQupepEnpIkaVdam5upOeIIorQ061AE1Bx5JJMv/y3jv3IxbU89xWOvfwNL3vs+tixenHVoklRQCiWB8XBE/DoiXhsRr+58ZB1UMZkwvJohFaXMdR4MSZK0E20rVrBlwQJqjnL4SCGJkhKGnXYa0264ntHvfhctt9/O/JNPYdlXv0r7er+gkiQonARGNbAZeBm5oSOdw0i0myKC6fV19sCQJEk71Tk8oWamE3gWopKaGsa8851Mu/EGhp5yCqt+/BMeffmJrL7sMlJbW9bhSVKmCiKBkVI6v4fHf2UdV7GZMbbWlUgkSQIiYmRE3BwRc/PPI3qoMykibouIhyLigYh4bxax9rfWpmaipoaqg10ArpCV19cz/uIvM/nKK6mYOoUnP/NZFrzqVbT89W9ZhyZJmSmIBEZEfKuHx+cj4rSsYysmM+rrWNGymdUbXIlEkjToXQTcklJqAG7Jb3fXBnwwpfQs4GjgnYNhWffW5mZqDj+cKC/POhTthupDD+GAX/yCCd/6Jh2bNrP4LW9h0YUXsvnRR7MOTZL6XUEkMIAq4HBgbv7xHGAkcEFEfCO7sIpL50SerkQiSRKnkVumnfzz6d0rpJSeSCndk3+9HngImNBfAWahfc0aNs+ZQ80sh48Uk4hg6MtextTrrmXshz/Mxnv+xfxTT+PJz32ettWrsw5PkvpNWdYB5E0Hjk8ptQFExP8BNwEvBf6zo4Mi4kTgm0Ap8KOU0sU7qDcLuBM4O6V0ZS/HXjAa6nNLqc5Ztp6jpozMOBpJkjJVn1J6AnKJiogYu7PKETEZeC7wz53UuRC4EKC+vp7GxsZeCxagpaWl18/ZXeW//83wlHikrIz7+/haWeuP9szEtKnEp/+b2j9eS/rNb1j5+9+z4eSTaZ39YujjXjUDtk0zZJv2Ptu0dxVaexZKAmMCMARYm98eAoxPKbVHxOaeDoiIUuC75JIcS4CmiLgmpfRgD/W+Avypr4IvFOOHVVFbWcZcJ/KUJA0CEfFnYL8edn1iD89TC1wFvC+ltG5H9VJKlwCXAMycOTPNnj17Ty6zS42NjfT2Obtb9s+7WF1RwTFvfCMllZV9eq2s9Ud7ZuqVr2Tz3Lks+39fpeSqqxjZ1MTYD3+Iupe8hIjok0sO+DbNgG3a+2zT3lVo7VkoCYz/B9wbEY1AAMcCX4qIIcCfd3DMUcC8lNJ8gIi4jFx30Qe71Xs3uZuSAb9WWEQw3Yk8JUmDRErpJTvaFxHLImJcvvfFOGD5DuqVk7tP+FVK6Xd9FGrBaG1qovo5zxnwyYvBorKhgf1/eAktf/0ry77yFR5/93uomTWLsRd9lOpDDsk6PEnqdQWRwEgp/TgirieXlAjg4ymlpfndH97BYROAxV22lwDP61ohIiYArwKOZycJjL7uEgr91/WmrmMz/17SVlDdfPpCoXVlGghs095nm/Y+27R3DfD2vAY4D7g4/3x19wqR+5r6x8BDKaWv9294/a+9ZQObHnyQUW+9MOtQ1MtqX/QihhxzDGuuuIKnvvVtFp5xJsNOP50x73sf5fU7HT0lSUUl0wRGRByUUno4Io7IF3UmJPaLiP06J9ba0eE9lKVu298APpofirLDE/V1l1Dov64380rn89frHuI5s57PyCEVfX69rBRaV6aBwDbtfbZp77NNe9cAb8+Lgcsj4gJgEXAmQESMJzdv1snAC4A3AP+JiHvzx308pXR9BvH2uY3/+hd0dDBk1oDvlDooRVkZI177Woaecgorvv8DVv3iF6y78UZGvfkCRv3Xf1FSXZ11iJK0z7LugfEBcj0fvtalrGsS4vidHLsEmNRleyKwtFudmcBl+eTFaODkiGhLKf1hbwMudJ0Tec5dtp7nTR2VcTSSJGUjpbQSOKGH8qXAyfnXf6PnL0QGpNamJigro/rww7MORX2odOhQ6j/yYUacczbL/+drrPj2d1hzxZWM/cD7GfqKVxAlhbIIoSTtuUz/B0spdfZh/D/gtJTSccBt5Cbz/NAuDm8CGiJiSkRUAOeQ6y7a9fxTUkqTU0qTgSuBdwzk5AVAw9jcUqpzXEpVkiR10drcTNUhB1NSU5N1KOoHFfvvz8RvfZMDfvFzykaNYulHPsrCs8+h9Z6ddXCWpMJWKCnYT6aU1kXEC8mtKvIzckmNHcovufoucquLPARcnlJ6ICLeFhFv6+uAC9W4YVXUuRKJJEnqomPTJjb+5z8OHxmEambNYvIVlzPu4i/TtmwZj73uXJa87/1sWbIk69AkaY9lPYSkU3v++RTg+ymlqyPiM7s6KD9G9fpuZd/fQd037WOMRSEimF5fyxwTGJIkKW/jvf+GrVupnjkz61CUgSgpYfjppzP0ZS9j5Y9/wsof/5iWW25h5JvOY9Rb30ppbW3WIUrSbimUHhiPR8QPgLOA6yOiksKJrejMGFvHXJdSlSRJea3NzRBBzRFH7LqyBqySmhrGvPtdTLvxBoaefDIrf/gjHn3Zy1l92W9JbW1ZhydJu1QoSYKzyA0FOTGltAYYyY6XT9UuNNTXsnLDFla2bM46FEmSVABam5upfNZBlA4dmnUoKgDl++3H+K9czOQrrqBiyhSe/MxnWPCqV9Py979nHZok7VRBJDBSSq0ppd+llObmt59IKd2UdVzFakbnSiRO5ClJ0qCXtmxh4733UuPwEXVT/exDOeCXv2DCN75Bx8aNLL7gzSx661vZ/OijWYcmST0qiASGeldDfW4coxN5SpKkjfc/QNq0yQSGehQRDD3x5Uy97lrGfvhDbLz7HuafehpPfv4LtK1enXV4krQdExgD0H5DcyuRzHEeDEmSBr3W5mYAExjaqZLKSkZdcAHT/nQjw888g9W/+Q2PvvxEVv7sZ6QtW7IOT5IAExgDUkTQ4EokkiQJaG1qomL6NMpGjsw6FBWBslGjGPeZzzD16j9Q/ZznsPzir/DoK1/J+j//GVLKOjxJg5wJjAFqRn2dc2BIkjTIpbY2Nt5zj70vtMcqGxrY/0c/ZNIlPyDKylnyrncz4uv/y4a77so6NEmDmAmMAaqhvo5VrkQiSdKgtunhR+jYsIGaWbOyDkVFqvbYY5n6h99T/6lPUrpsGYveeB6PveGNbLjznyR7ZEjqZyYwBqgZ+Yk8nQdDkqTBq7WpCXD+C+2bKC9n5LnnsuILn6f+4x9jy8KFLHrTm3jsDW9gw513msiQ1G9MYAxQDWM7l1J1HgxJkgar1uZmyvffn/L6+qxD0UBQUcHIN76RaTffRP3HP87WRYtZ9Kbzeez1b2DDP/5hIkNSnzOBMUDVD62krqrMiTwlSRqkUkcHG5ubqZll7wv1rpKqKka+8Q25RMYnP8nWJUtY9F8X8NjrzqXlb383kSGpz5jAGKAighn1dQ4hkSRpkNo8dx7ta9dSM9P5L9Q3SiorGfn6c3OJjP/+FFufeILFb34zj53zWlr++lcTGZJ6nQmMAWxGfS1zl633j4ckSYNQa3N+/gt7YKiPlVRUMPJ1r2PaTX9iv898mq3Ll7P4LRey8JxzaLn9du9FJfUaExgDWMPYOla3bmXlhi1ZhyJJkvpZa3MzZePGUT5hQtahaJAoqahgxDnnMP1PN7LfZz9L+1MrWHzhW1l41tmsb2w0kSFpn5nAGMBm1Ocm8nQeDEmSBpeUEq1NzdTMnElEZB2OBpmoqGDE2Wcx7cYb2O/zn6N91SqWvO3tLDzzLNbfepuJDEl7zQTGANaQX0p1rvNgSJI0qGxZuJD2FStcPlWZiooKRpx5JtNuvIFxX/g87WvWsOQd72Dha85g/S23mMiQtMdMYAxgY+sqGepKJJIkDTqtzc0A1MxyAk9lL8rLGX7GGUy74XrGffGLtLe0sOSd72LBq1/D+j//2USGpN1mAmMA61yJxB4YkiQNLq1NTZSOGkXFlMlZhyJtE+XlDH/Nq5l2/XWM+/KX6WjdwJJ3vZsFr3o16266idTRkXWIkgqcCYwBrqG+jjnLXYlEkqTBpLXZ+S9UuKKsjOGvOp1p113H+K9cTNq0icff814WnP4q1t34JxMZknbIBMYAN6O+ljWtW1nR4kokkiQNBlsff5y2pU84fEQFL8rKGHbaaUy97lrGf/X/kbZu5fH3vY8Fp53OuhtuMJEh6RlMYAxwnSuRzHUeDEmSBoUNTU0A1MxyAk8VhygtZdgrX8nUa//I+K9+ldTezuPv/wDzTz2VdddfT2pvzzpESQXCBMYA1zA2txKJE3lKkjQ4tDY3UzJsGJUNDVmHIu2RXCLjFUz94zWM/9r/APD4Bz7I/FNPY+2115nIkGQCY6AbU1fJsOpy5ix3Ik9JkgaDjU3N1Bx5JFHibZ6KU5SWMuyUU5h6zTVM+N+vEyXB0g99iPmvPJW1f/yjiQxpEPMv2wCXW4mk1iEkkiQNAluXL2fLY49RM9PhIyp+UVLC0JNOYsrVVzPhG98gyspY+uGPMP+UV7D26qtJbW1Zhyipn5nAGAQa6uuYs6zFlUgkSRrgNjY3A85/oYElSkoYeuLLmfKH3zPhW98kKitZ+tGLmH/KK1jzhz+YyJAGERMYg8CMsbWs3biVp1o2Zx2KJEnqQ63NzZTU1FD1rGdlHYrU66KkhKEvexlTfv87Jnz7W0RNDU9c9DEePeUU1vzu9yYypEHABMYg8PRKJM6DIUnSQNba1ET1EUcQZWVZhyL1mSgpYehLX8qU313FxO9+h5IhQ3ji4x/n0ZNOZs1VV5G2bs06REl9xATGINCQT2C4EokkSQNX2+rVbJ47z/kvNGhEBHUnnMCUq65i4ve+R+nQoTzxiU/y6Ekns+rnP6d9vfe+0kBjAmMQGF1bwfCacubYA0OSpAFr4913A1Bz1KyMI5H6V0RQd/xxTL7yCiZ+//8oGz2aZV/6MnNfPJsnPvMZNs2Zk3WIknqJ/QsHgYhgxtg6VyKRJGkAa21qIiorqTr00KxDkTIREdTNnk3d7NlsvP8BVv/616z93e9Zc9lvqTnqKEacey51JxzvECupiNkDY5BoqK9lzrL1rkQiSdIA1drUTPVhh1FSUZF1KFLmqg89hPFf+iLT/9LI2A99kK1LlvD4e9/LvJe8lBXf/wFtK1dmHaKkvWACY5CYUV/Huk1tPLXelUgkSRpo2tevZ9PDD1Mzy+EjUldlI0Yw6s1vZtrNNzHxe9+lcupUnvrGN5g3+ziWfvSjbLzvvqxDlLQH7D81SDTU1wIwZ1kLY4dWZRyNJEnqTRvvuQc6OqiZ5QSeUk+itJS644+n7vjj2Tx/Pqt/9WvW/v73rL36Gqqe/WxGnPs6hp50EiWVlVmHKmkn7IExSMxwJRJJkgas1uZmKC+n+rDDsg5FKniVU6ey36c+yfTb/0L9pz5Jx4YNPHHRx5g3+ziWf/1/2frEE1mHKGkHTGAMEqOGVDCippy5y01gSJI00LQ2NVN96KGUVFdnHYpUNEpraxl57rlMve5a9v/pT6g+8ghW/uhHzDvhJSx593vYcOc/nT9OKjAOIRkkIoKG+jqXUpUkaYDpaG1l4/33M+r887MORSpKEcGQY45hyDHHsPXxx1l92W9Zc8UVrL/5ZiqmT2Pkuecy7NRTKRkyJOtQpUHPHhiDyAxXIpEkacDZ+O9/Q1ub819IvaB8wgTGfvADTP9LI+O+/GVKKqt48rOfY+6LZ/PkF7/E5gULsg5RGtRMYAwiM+rrWL+pjWXrXIlEkqSBorWpGUpKqD7iiKxDkQaMkspKhr/qdCZfeQWTL/sNtccdx+rLLmP+SSez6M1vYf1tt5Ha27MOUxp0TGAMIg1jcxN5Og+GJEkDR2tTE1XPehaltbVZhyINOBFB9eGHM+Gr/4+G225lzHvfw+a5c1ny9nfw6MtPZOWPf0L7mjVZhykNGiYwBpEZXZZSlSRJxa9jyxY2/vvf1Mx0+IjU18pGj2b029/O9D/fzIRvfIPyceNY/tWvMvfFs1n6yU+y6aGHsg5RGvCcxHMQGVVbycghFcx1KVVJ0gAXESOB3wKTgYXAWSml1d3qVAG3A5Xk7omuTCl9un8j3Teb/vMf0pYt1Bw1K+tQpEEjyssZeuLLGXriy9n0yBxW//rXrL3mGtZeeRXVRxzBiHNfx9CXvpSoqMg6VGnAsQfGINMwNjeRpyRJA9xFwC0ppQbglvx2d5uB41NKhwGHAydGxNH9F+K+a21qAnD+CykjVQfOYNxnP0PDXxqp/9hFtK1cwdIPfoh5J7yEp77zXbYuX551iNKAYgJjkJlRX8fcZS2uRCJJGuhOAy7Nv74UOL17hZTTOa6yPP8oqj+QrU3NVDY0UDZiRNahSINa6dChjDzvPKbdcAOTLvkBlQc/ixXf/S7zjj+Bxz/wQVrvucf7b6kXOIRkkJlRX8v6zW08uW4T44ZVZx2OJEl9pT6l9ARASumJiBjbU6WIKAXuBqYD300p/XNHJ4yIC4ELAerr62lsbOzVgFtaWvbsnO3tjGluZtPRR/d6LAPBHrendsk23QOvfS2lJ5xA9e2309F4G+uuv56tkybSOns2m2bNgvzwEtu099mmvavQ2tMExiDTUJ9fiWRZiwkMSVJRi4g/A/v1sOsTu3uOlFI7cHhEDAd+HxGHppTu30HdS4BLAGbOnJlmz569xzHvTGNjI3tyzo333cfCzZtpOP00hvZyLAPBnrands023QtnnUVHaytrr72W1b/8FeW/+CUjrvkjw1/zGka89hz+8eijtmkv8/e0dxVaexZ1AiMiTgS+CZQCP0opXdxt/7nAR/ObLcDbU0r/7t8oC8uMfAJjzrL1HDtjTMbRSJK091JKL9nRvohYFhHj8r0vxgE7HYieUloTEY3AiUCPCYxC09rUDOAKJFKBK6mpYcRZZzH8zDPZePfdrPrVr1h16aWs+ulPGX7IIaxva6P2xS8mysuzDlUqeEU7B0a+y+d3gZOAg4HXRsTB3aotAF6cUnoO8Hny35oMZiOHVDBqSAVzXUpVkjSwXQOcl399HnB19woRMSbf84KIqAZeAjzcXwHuq9bmZiomT6ZsjF9ISMUgIqiZOZOJ//u/TL/1Fka//W2ULV7Mkne9m7nHH8/yr/8vWxYtyjpMqaAVcw+Mo4B5KaX5ABFxGbkJux7srJBS+keX+ncCE/s1wgLVUF/LnOWuRCJJGtAuBi6PiAuARcCZABExnlyvzZOBccCl+S9FSoDLU0rXZhXwnkjt7bTefTdDX/6yrEORtBfK6+sZ85738MAhh3BklLDmiitY+aMfsfKSS6g55miGn3EGdS99KSUuxSptp5gTGBOAxV22lwDP20n9C4Ab+jSiIjGjvo7f3/M4KSUiIutwJEnqdSmllcAJPZQvBU7Ov74PeG4/h9YrNs+dS8e6dQ4fkYpdaSl1s2dTd/xxbF22jLW/+x1rrryKpR/8EKXDhzPstNMYftaZVE6blnWkUkEo5gRGT5+8e1ybKCKOI5fAeOEO9vfprOJQYLO3rt3K+s1t/O7G2xhVXZyjiAqqPQcI27T32aa9zzbtXbZn8do2/8WsWRlHIqm3lNfXM/rtb2fUW9/Khn/cwZorr2TVr3/NqksvpfqIIxh+5pkMPfHllFQ7Eb8Gr2JOYCwBJnXZnggs7V4pIp4D/Ag4Kf9tzDP09aziUFizt1bPX8nPH7yT0dOezYuLdCLPQmrPgcI27X22ae+zTXuX7Vm8WpuaKB8/nvLx47MORVIvi5ISal/4Ampf+ALaVq5k7R+uZs0VV/DExz7Gsi99iWGvfAXDzziDqoO7T/8nDXzF+fV7ThPQEBFTIqICOIfchF3bRMT+wO+AN6SU5mQQY0GasW0pVefBkCSp2KSUaG1upmaWw0ekga5s1ChGXfBfTL3heg74xc+pPW42a676HQte/RoWvOYMVl/2W9pbnJxfg0fRJjBSSm3Au4A/AQ+Rm3jrgYh4W0S8LV/tv4FRwPci4t6IaM4o3IIyYkgFo2srmGMCQ5KkorNlwQLaV61y+Ig0iEQENbNmMeH//T8abv8L9Z/4BGnrVp78zGeYe+yLWfqJT7Dx3ntJqccR9dKAUcxDSEgpXQ9c363s+11evxl4c3/HVQwaxtYxx6VUJUkqOq13NQE4gac0SJUOG8bIN7yeEa8/l0333ceaK69k7XXXs/aq31HZ0MDwM89k2KmvpHT48KxDlXpd0fbA0L6ZUV/LvOUtZmklSSoyrc3NlI4ZTfkBB2QdiqQMRQTVhx3GuM9/nobbb2e/z32WqKpi2Ze+xNxjX8zjH/4IG/55l/f7GlCKugeG9l5DfR0tm9tYunYTE4Y7k7EkScUgpURrUxNDZs1yKXRJ25TWDmHEWWcx4qyz2PTww6y5/ArW/vGPrPvjH6k44ACGn3kGw04/nbLRo7MOVdon9sAYpJzIU5Kk4rN1yRLali2j2uEjknag6qCD2O+/P0XD7X9h3MVfpnT0aJb/z9eYO/s4lrznvbT89W+kjo6sw5T2ij0wBqmGsbUAzF3WwuwDx2YcjSRJ2h2tTbn5yJ3/QtKulFRXM/z00xl++ulsfvRR1lxxJWv/8AfW33QT5ePHM+yM1zD81a+mfL/9sg5V2m32wBikciuRVLoSiSRJRaS1uZnS4cOpnD4961AkFZHKadOov+ijTL/9L0z4369TMfkAVnzr28w7/gQWv/VtrL/lFlJbW9ZhSrtkD4xBbEZ9LXOWuxKJJEnForWpieqZRxIlfgclac+VVFQw9KSTGHrSSWxZvJg1V17F2t/9jiXvfBdlY8Yw7NWvZvgZr6Fi0qSsQ5V65F+/QWxGfR3zlq13ZmJJkorA1iefZOvixQ4fkdQrKiZNYuz738f0225l4ne/Q9XBB7Pyhz/k0Ze+jEX/9V+su+EGOrZsyTpMaTv2wBjEGupr2bClncfXbGTiiJqsw5EkSTvR2nw3ADWzZmUciaSBJMrKqDvhBOpOOIGtTz7JmquuYs1VV/H4+z9A6YgRDDvtNIafeQaV06ZlHapkD4zBbNtKJA4jkSSp4LU2NVEyZAhVBx2UdSiSBqjy/fZjzDvfyfSbb2bSD39IzaxZrPrlL5l/yiuY/+pXs/JHP2Lr449nHaYGMRMYg9iMsS6lKklSsWhtbqb6yCOI0tKsQ5E0wEVpKbUveiETv/VNGhpvY+xFHyXKy1n+P19j3gkvYeFrX8eqX/ySthUrsg5Vg4wJjEFsWE05Y+sqmbPMHhiSJBWytpUr2fLoow4fkdTvykaPZtSb3sSU3/6WaTffxJj3v5+ODRtY9sUvMvfYF/PY+eez5soraV+7NutQNQiYwBjkGupr7YEhSVKB2zb/hRN4SspQxaRJjH7rhUy95mqm/vEaRr/trWxdupQnPvkp5rzwRSx+29tZ+8dr6diwIetQNUA5iecg1zC2jsubF9PRkSgpiazDkSRJPWhtbiaqqqg+5JCsQ5EkACobGhjT0MDod7+bTQ88yLrrrmPdDTfQ0thIVFVRe9xshp58MrXHHktJZWXW4WqAMIExyM2or6M1vxLJpJGuRCJJUiFqbW6m+rmHExUVWYciSduJCKoPPYTqQw9h7Ic/xMZ//SuXzLjxT6y/4UZKamupe8lLGHrKyQw5+miivDzrkFXETGAMcjPqawGYt7zFBIYkSQWofe1aNj/8MKPf9c6sQ5GknYqSEmqOPJKaI4+k/uMfZ8Od/2Td9dez/uabWfuHP1A6YgR1L38ZQ08+mZqZM4kSZzTQnjGBMcg15JdSnbNsPccdNDbjaCRJUnet99wDKVEz0wk8JRWPKCuj9oUvoPaFL6DjM59mw1//yrrrrmft1dew5rLfUlZfz9ATT2ToK06h6tBDiXA4u3bNBMYgN6y6nPqhrkQiSVKham1uJsrLqT7sOVmHIkl7paSigroTTqDuhBPoaG1l/W23se76G1j961+z6tJLKZ80iaEnn8zQU06masaMrMNVATOBIRrG1jF3uSuRSJJUiFqbmql6znMoqarKOhRJ2mclNTUMO+UUhp1yCu3r1rH+5j+z7rrrWPnDH7LyBz+gsmE6Q085haEnnUTFAQdkHa4KjIOOlF9KtYWOjpR1KJIkqYuODRvY9MADLp8qaUAqHTqU4a95Nfv/5Mc0/PV26v/7U5QMHcZT3/gmj778RBaccSYrf/oztj75ZNahqkCYwBAz6uvYuDW3EokkSSocrffeC+3t1Mxy/gtJA1vZqFGMfN3rmPyrXzL9tlsZ+5GPQEos/8pXmDf7OBa+/vWs/s1vaFu1KutQlSETGNq2EonDSCRJKiytTU1QWkr14YdnHYok9ZvyceMY9V/nM+WqK5l24w2Mfs+7aV+9hic/+znmvuhYFl3wZtb87ve0r1uXdajqZyYwxPSxnSuROJGnJEmFpLW5maqDD6a0dkjWoUhSJiomT2bMO97B1Gv/yJSrr2bUBRew5bHHeOLjH2fuC17I4ne9i3XXX09Ha2vWoaofOImnGFZdzn5Dq5izzB4YkiQVio7Nm9n07/sY8YY3ZB2KJGUuIqg6cAZVB85gzPvfx6b77mPd9dez7vobaPnzLURNDXXHHUfl+PG0z5xl4neAMoEh4OmJPCVJUmHY+O9/k7ZudQJPSeomIqg+7DCqDzuMsR/5CK133826665n/Z/+xPA1a5j7s59Rc/TR1J1wPLXHHUd5fX3WIauXOIREQG4p1XnLXYlEkqRC0drcDBHUHHlE1qFIUsGK0lKGHHUU4z77GRr+9ldWffADjDj3XLY89hhPfuazzHvxbBaccSZPfe97bHrkEVLy804xsweGgNxEnhu3trNk9Ub2H1WTdTiSJA16G5ubqTzwQEqHDcs6FEkqClFWxtaGBurfMpuxH/0IWx59lPW33kbLLbew4tvfYcW3vk35hAnUHn88dccfR83MmUR5edZhaw+YwBAADfW5iTznLl9vAkOSpIylrVtp/de9DH/Na7IORZKKUkRQOX06ldOnM/rCt9D21FOsb2yk5dbbWHP55az+xS8oqauj9thjqTvheIa86EWU1tVlHbZ2wQSGgNwcGJBbieSEZzlGTJKkLG164AHSxo3OfyFJvaRszBhGnHkmI848k47WVjbccQfrb7mVlsZG1l13HZSXM2TWrG29M8rHj886ZPXABIYAGFpVzrhhVTQtXMX5WydTVV6adUiSJA1arc3NANTMMoEhSb2tpKaGuhNOoO6EE0jt7Wz8979pufVW1t9yK8u+8AWWfeELVD7rWdQdfzy1xx9H1cEHExFZhy1MYKiL4w4ay6//uYhZX/wzr3ruBM6eNYlDxjvuVpKk/rahqYmKqVMpGzUq61AkaUCL0lJqjjiCmiOOYOyHPsTm+Qtoue1W1t96Gyu+9z1WfPe7lO23H3XHH0ft8Scw5KhZREVF1mEPWiYwtM0XTjuUVz5nPL9tWsRlTYv5+R2P8ewJwzh71iROPXw8Q6uc4EaSpL6W2tvZePc9DD355KxDkaRBp3LqFCqnXsCoCy6gbdUqWhr/wvpbb2HN7//A6l//hpIhQxhy7ItyvTOOPdaJlvuZCQxtU1ISHDNtFMdMG8VnW7fyh3sf5zd3LeKTf7ifL1z3ICc/exznzNqfWZNH2IVKkqQ+svmRR+hoaaFm1qysQ5GkQa1s5EiGv/pVDH/1q+jYtIkNd9xBy623sf6221h/w41QWkrNzJnUnXA8tccfT8XEiVmHPOCZwFCPhtWUc97zJ/PGYw7gP4+v5bKmxVxz71J+d8/jTB09hLNnTeLVR0xkTF1l1qFKkjSgtDY1AVAz88iMI5EkdSqpqqLuuOOoO+449uvoYNN997H+1ttYf+stLPvSl1n2pS9TOWMGtccfR93xx1N16KFESUnWYQ84JjC0UxHBcyYO5zkTh/PJU57Fdfc9wW+bFvPlGx7mq396hJc8q56zj5rEsQ1jKC2xV4YkSfuqtbmZ8okTKR83LutQJEk9iJISqg8/nOrDD2fsB97PlsceY/1tt9Fyy62svOSHrPz+DygbM4ba446j7oTjqTn6aEoq/eK3N5jA0G6rqSjjzJmTOHPmJOYtX89vmxZz1T2Pc+MDTzJuWFVu35ETmTSyJutQJUkqSiklWpuaqT3uuKxDkSTtpooDDmDUm97EqDe9ibbVq9lw++2sv/U21l17LWsuv5yoqaH2BS+g9vjjqZ39YspGjMg65KJlAkN7ZfrYOj5xysF8+OUHcctDy7isaTHfvnUu3751Li+cPppzZu3PSw4eS2WZy7FKkrS7tsybR/uaNdTMdPlUSSpGZSNGMOy00xh22ml0bN5M6113sf6WW3JzZ9x8M5SUUH3Ec6l98YsZcvQxVB38LKLUz0y7ywSG9klFWQknPXscJz17HI+v2cgVzYu5vGkx7/z1PYwcUsGr88uxNtTXZR2qJEkFr7W5GYCaWSYwJKnYlVRWUvuiF1H7oheRPv1pNt3/QG6J1ltu5amvfZ2ngJJhwxhy1Cxqnnc0Q445moqpU10wYSdMYKjXTBhezfteMoN3H9/A3+at4LdNi7j0joX86G8LOPKAEZw9axKnPHscQyr9tZMk9a2IGAn8FpgMLATOSimt3kHdUqAZeDyl9Ir+irEnrU3NlNXXUz5pUpZhSJJ6WURQ/exDqX72oYx5z3vYunw5rf+8iw133kHrHXey/uY/A1A2Zgw1Rx/NkKNzCY3y8eMzjryw+ElSva60JHjxjDG8eMYYVrRs5vf3PM5lTYv4yJX38bk/PsgrDxvH2bP257CJw8wuSpL6ykXALSmliyPiovz2R3dQ973AQ8DQ/gquRynR2tREzVFH+fdRkga48rFjGfbKVzDsla8gpcTWJUvYcMcdtN55Jxv+/nfW/fGPuXoH7M+QfO+Mmuc9j7KRIzOOPFsmMNSnRtdW8pZjp/LmF03h7sdWc1nTYn7/r8f5zV2LOWi/Os6eNYlXPXcCw2sqsg5VkjSwnAbMzr++FGikhwRGREwETgG+CHygn2LrUelTT9H21FMOH5GkQSYiqJg0iYpJkxhx1lmklNg8Zy6td97BhjvuZN1117Hm8ssBqDzwQIYcfTQ1xxxNzcxZlNYOyTj6/mUCQ/0iIpg5eSQzJ4/kv195MH/891J+27SYz/7xQb58w8OceMh+nDNrEkdPHUWJy7FKkvZdfUrpCYCU0hMRMXYH9b4BfATIfLKm8rnzAKiZNSvjSCRJWYoIqg6cQdWBMxh53nmktjY23X8/G+68kw13/pPVv/kNqy69FEpLqX72s6k55miGHH0M1YcfNuCXazWBoX43tKqcc593AOc+7wAeWLqWy/O9Mq7591L2H1nD2bMmccaRE6kfWpV1qJKkAhYRfwb262HXJ3bz+FcAy1NKd0fE7N2ofyFwIUB9fT2NjY27HevuqHnwQTpqa7lj0SJYvLhXzz0YtbS09PrPaLCzTXufbdr7BnSbHnRQ7vG611Ixfz7lDz/ClkcepvX7P2Dl/32fVF7OlmnT2HLQQWw58EDaDtgfSkr26ZKF1p4mMJSpQ8YP47OnDeNjJz+LG+9/ksuaFvHVPz3C1256hOMPGsvZs/bnuAPHUFa6b//wJEkDT0rpJTvaFxHLImJcvvfFOGB5D9VeAJwaEScDVcDQiPhlSun1O7jeJcAlADNnzkyzZ8/e5/fQ1f2f+CTDjjmGQ447rlfPO1g1NjbS2z+jwc427X22ae8bjG3avn49rU1NbLjzTlrvuJPNf/gDACV1ddQcdRRDnve83Aon06fv8RxLhdaeJjBUEKrKSzn9uRM4/bkTWLBiA5c3L+bKu5fw54eaGVtXyRlHTuSsmZOYPHpwjfGSJO21a4DzgIvzz1d3r5BS+hjwMYB8D4wP7Sh50de2Ll1K6cqVDh+RJO2x0ro66o4/nrrjjwegbcUKNvzzn7kJQe+4k5ZbbsnVGzM6NyHo0c+j5uhjqJg4Icuw94oJDBWcKaOH8NETD+IDL51B4yNPcdldi/j+Xx7le42PcszUUZxz1CSq21PWYUqSCtvFwOURcQGwCDgTICLGAz9KKZ2cZXDdtTY3AziBpyRpn5WNHs2wU05h2CmnALBlyZJtyYwNd97JumuvBaB80qR8MiO3bGvZqFFZhr1bTGCoYJWXlvDSg+t56cH1PLl2E1fds4TLmhbx3svupSxgyN9uoqKshIrSku2fu78uK6Eyv13eQ53Kbttd61R2O8+OruUQF0kqLCmllcAJPZQvBZ6RvEgpNZJbqSQTrU3NdFRXUzljRlYhSJIGqIqJE6k44wyGn3EGKSW2zJv3dDLjhhtZc8WVAFQ2NGybELRm1kxK6zKf3/oZijqBEREnAt8ESsl9m3Jxt/2R338y0Aq8KaV0T78Hqn2237Aq3nncdN7+4mncOX8lv7zlHsbsN54t7R1sbutgS1sHW9tzz1vyz62tbbl9neXd6mztxV4cJUGXxEYplWUllJcGFWUllOTHmUUEAUTkHgBB5LY7T9S1zrairmXbDtxWtt15utTZtq/z+l3O270MgpUrN/GrRc3b3lPX0XFdh8pFlz3ble+gzg5ebjf+bsfX2nX9HRVGD7V6GvLX07m619vtc3Ure2LpZv606j89XKHn43cW0+4fu+Od+3bNfV8daHdOsbP4AR5fspm/tjy4g2P37to7e287jWYvfw67E9NuXX+3z7HjSo89toVjXthOZVnprk+kPtXa3MzW6dOJUn8WkqS+ExFUNjRQ2dDAyDe+IbfCyYMPsuGOO2n9552s+e3lrP75L6C0lKpDD2HIuPFsfdazKK+vzzp0oIgTGBFRCnwXeCmwBGiKiGtSSl3vbE8CGvKP5wH/l39WkSopCZ4/fTRbllQwe/ah+3Sujo6US250SXB0Jjm6Jz62dNve3N7B1u518q83b7fdTkqQgJQAUv65syx12fd0Wafcsbljnq6Ttj9ngkTHtjJ2cF6eUbb9eddvTGxavXHb8T3pWpxIOyjvWj/1WM4e1t/RdXva39P2jvT0PruX9HSu3YoB2LKlnQfWLttl3Z1HsPvH7uzIHf1Md33F3WvPnZ1/d66xO5US0NbWRtmTz1ydYW/f387bcyfn3Mufw55U2tn1dxXD7l4mpcSX2xOVRXs3MDC0t7TQtmIFW557eNahSJIGmSgro/o5z6H6Oc+Bt15Ix+bNbPzXvWz4Z25C0CE33QQf/lDWYW5TzLcsRwHzUkrzASLiMuA0oGsC4zTg5yl3Z3tnRAzvnJG8/8NVoSkpCapKSqkq99su6Jxh+EVZhzGgFNqszQOBbdq7GhsbqTV7kbnS2lpm3HkHf8lPsiZJUlZKKisZcvTzGHL08+C97+UvN97IwRMKZ7LPYr5rmQB0/RpuCc/sXdFTnQnAdgmMvl7XHQpv/dxiZ3v2Ptu099mmvc827V22Z+GI0lKoqMg6DEmStpOqqrIOYTvFnMDoaVBv996yu1Onz9d1B7817G22Z++zTXufbdr7bNPeZXtKkqRiUsxLJywBJnXZnggs3Ys6kiRJkiSpwBVzAqMJaIiIKRFRAZwDXNOtzjXAGyPnaGCt819IkiRJklR8inYISUqpLSLeBfyJ3DKqP0kpPRARb8vv/z5wPbklVOeRW0b1/KzilSRJkiRJe69oExgAKaXrySUpupZ9v8vrBLyzv+OSJEmSJEm9q5iHkEiSJEmSpEHCBIYkSZIkSSp4JjAkSZIkSVLBM4EhSZIkSZIKngkMSZIkSZJU8ExgSJIkSZKkghe5lUbVKSKeAh7rg1OPBlb0wXkHK9uz99mmvc827X22ae/qi/Y8IKU0ppfPWXD66H7B3+/eZXv2Ptu099mmvc827V191Z57db9gAqOfRERzSmlm1nEMFLZn77NNe59t2vts095lexYWfx69y/bsfbZp77NNe59t2rsKrT0dQiJJkiRJkgqeCQxJkiRJklTwTGD0n0uyDmCAsT17n23a+2zT3meb9i7bs7D48+hdtmfvs017n23a+2zT3lVQ7ekcGJIkSZIkqeDZA0OSJEmSJBU8ExiSJEmSJKngmcDoYxFxYkQ8EhHzIuKirOMpdhExKSJui4iHIuKBiHhv1jENBBFRGhH/iohrs45lIIiI4RFxZUQ8nP9dPSbrmIpdRLw//2/+/oj4TURUZR1TsYmIn0TE8oi4v0vZyIi4OSLm5p9HZBnjYOW9Qu/yXqFveK/Q+7xf6F3eK+y7YrhXMIHRhyKiFPgucBJwMPDaiDg426iKXhvwwZTSs4CjgXfapr3ivcBDWQcxgHwTuDGldBBwGLbtPomICcB7gJkppUOBUuCcbKMqSj8DTuxWdhFwS0qpAbglv61+5L1Cn/BeoW94r9D7vF/oJd4r9JqfUeD3CiYw+tZRwLyU0vyU0hbgMuC0jGMqaimlJ1JK9+Rfryf3H/2EbKMqbhExETgF+FHWsQwEETEUOBb4MUBKaUtKaU2mQQ0MZUB1RJQBNcDSjOMpOiml24FV3YpPAy7Nv74UOL0/YxLgvUKv816h93mv0Pu8X+gT3ivso2K4VzCB0bcmAIu7bC/BP6C9JiImA88F/plxKMXuG8BHgI6M4xgopgJPAT/Nd7X9UUQMyTqoYpZSehz4H2AR8ASwNqV0U7ZRDRj1KaUnIPehDxibcTyDkfcKfch7hV7zDbxX6G3eL/Qi7xX6VEHdK5jA6FvRQ5nr1vaCiKgFrgLel1Jal3U8xSoiXgEsTyndnXUsA0gZcATwfyml5wIbsFv+PsmPtTwNmAKMB4ZExOuzjUrqNd4r9BHvFXqH9wp9xvuFXuS9wuBhAqNvLQEmddmeiF2Z9llElJO7IflVSul3WcdT5F4AnBoRC8l1Wz4+In6ZbUhFbwmwJKXU+W3fleRuULT3XgIsSCk9lVLaCvwOeH7GMQ0UyyJiHED+eXnG8QxG3iv0Ae8VepX3Cn3D+4Xe5b1C3ymoewUTGH2rCWiIiCkRUUFuIplrMo6pqEVEkBsr+FBK6etZx1PsUkofSylNTClNJvf7eWtKyWz1PkgpPQksjogD80UnAA9mGNJAsAg4OiJq8v8HnIATnfWWa4Dz8q/PA67OMJbBynuFXua9Qu/yXqFveL/Q67xX6DsFda9QluXFB7qUUltEvAv4E7mZcH+SUnog47CK3QuANwD/iYh782UfTyldn11I0jO8G/hV/sPIfOD8jOMpaimlf0bElcA95FYX+BdwSbZRFZ+I+A0wGxgdEUuATwMXA5dHxAXkbv7OzC7Cwcl7hT7hvYKKhfcLvcR7hd5RDPcKkZLDLCVJkiRJUmFzCIkkSZIkSSp4JjAkSZIkSVLBM4EhSZIkSZIKngkMSZIkSZJU8ExgSJIkSZKkgmcCQ1KfioiW/PPkiHhdL5/74922/9Gb55ckSX3PewVJu8sEhqT+MhnYo5uSiCjdRZXtbkpSSs/fw5gkSVLhmIz3CpJ2wgSGpP5yMfCiiLg3It4fEaUR8dWIaIqI+yLirQARMTsibouIXwP/yZf9ISLujogHIuLCfNnFQHX+fL/Kl3V+gxP5c98fEf+JiLO7nLsxIq6MiIcj4lcRERm0hSRJeibvFSTtVFnWAUgaNC4CPpRSegVA/uZibUppVkRUAn+PiJvydY8CDk0pLchv/1dKaVVEVANNEXFVSumiiHhXSunwHq71auBw4DBgdP6Y2/P7ngscAiwF/g68APhbb79ZSZK0x7xXkLRT9sCQlJWXAW+MiHuBfwKjgIb8vru63JAAvCci/g3cCUzqUm9HXgj8JqXUnlJaBvwFmNXl3EtSSh3AveS6q0qSpMLjvYKk7dgDQ1JWAnh3SulP2xVGzAY2dNt+CXBMSqk1IhqBqt04945s7vK6Hf8flCSpUHmvIGk79sCQ1F/WA3Vdtv8EvD0iygEiYkZEDOnhuGHA6vwNyUHA0V32be08vpvbgbPzY2fHAMcCd/XKu5AkSX3FewVJO2U2UVJ/uQ9oy3fv/BnwTXJdMu/JT471FHB6D8fdCLwtIu4DHiHXNbTTJcB9EXFPSuncLuW/B44B/g0k4CMppSfzNzWSJKkwea8gaacipZR1DJIkSZIkSTvlEBJJkiRJklTwTGBIkiRJkqSCZwJDkiRJkiQVPBMYkiRJkiSp4JnAkCRJkiRJBc8EhiRJkiRJKngmMCRJkiRJUsEzgSFJkiRJkgqeCQxJkiRJklTwTGBIkiRJkqSCZwJDkiRJkiQVPBMYkiRJknYqIlJETM+//n5EfGp36u7Fdc6NiJv2Nk5JA5sJDGmQ2tXNxx6ea/+IaImI0vx2Y0S8uTfOnT/fDRFxXm+dbw+u+4WIWBERT/awb3ZELNmLc/Zau0uStLsi4k8R8bkeyk+LiCcjomx3z5VSeltK6fO9ENPkfLJj27VTSr9KKb1sX8/dw7Vm56/1u27lh+XLG7uUnRYR90bEuvx9wC0RMTm/7zMRsTV/39P5WLO770/SvvEfkzQARcRCoB5oA9qBB4GfA5eklDogd/OxB+d6c0rpzzuqk1JaBNTuW9TbrvcZYHpK6fVdzn9Sb5x7D+OYBHwQOCCltLy3zru77S5JUi/7GfCliPh0Sil1KX8D8KuUUls2YfWrp4DnR8SolNLKfNl5wJzOCvmeIz8HXg3cSu7+5mVAR5fz/LbrfYqk/mMPDGngemVKqQ44ALgY+Cjw496+yAD+VuEAYGVvJi8kScrQH4CRwIs6CyJiBPAK4OcRcVRE3BERayLiiYj4TkRU9HSiiPhZRHyhy/aH88csjYj/6lb3lIj4V743w+L8FxWdbs8/r8n3ZDgmIt4UEX/rcvzzI6IpItbmn5/fZV9jRHw+Iv4eEesj4qaIGL2TNtiSb4dz8seXAmcBv+pS53BgQUrplpSzPqV0Vf7Lml4TEeMj4pqIWBUR8yLiLV32HRURzfk2WxYRX8+XV0XELyNiZf7n1BQR9b0Zl1ToTGBIA1xKaW1K6RrgbOC8iDgUtr/5iIjREXFt/o/hqoj4a0SURMQvgP2BP+ZvLD7SpTvkBRGxCLh1B10kp0XEXfkbjqsjYmT+Ws8YehERCyPiJRFxIvBx4Oz89f6d379tSEo+rk9GxGMRsTwifh4Rw/L7OuM4LyIW5bt9fmJHbRMRw/LHP5U/3yfz538JcDMwPh/Hz3Zyjo/nr7MwIs7d1c9jd9p9V+eQJGlPpZQ2ApcDb+xSfBbwcErp3+R6bL4fGA0cA5wAvGNX583/7f4Q8FKgAXhJtyob8tccDpwCvD0iTs/vOzb/PDylVJtSuqPbuUcC1wHfAkYBXweui4hRXaq9DjgfGAtU5GPZmZ/zdBu8HHgAWNpl/z3AQRHxvxFxXET0Sg/THvwGWAKMB84g1zvmhPy+bwLfTCkNBaaR+7lBrrfIMGASufZ4G7Cxj+KTCpI3ytIgkVK6i9wfyhf1sPuD+X1jyA09+XjukPQGYBG53hy1KaX/1+WYFwPPIvfHvydvBP6L3B/mNnI3H7uK8UbgS+S6ZtamlA7rodqb8o/jgKnkunZ+p1udFwIHkrv5+u+IeNYOLvltcjcCU/Pv543A+fnhMicBS/NxvGkHx+9H7kZvArmbiksi4sBdvc8uemz3PThekqQ9cSlwZkRU57ffmC8jpXR3SunOlFJbSmkh8ANyfxt35Szgpyml+1NKG4DPdN2ZUmpMKf0npdSRUrqP3Af33Tkv5BIec1NKv8jH9RvgYeCVXer8NKU0p0uC5vCdnTCl9A9gZP7v9RvJJTS67p8PzCb3t/1yYEX+y4euiYyz8l8+dD5u2833A2wbpvpC4KMppU0ppXuBH5EbzgOwFZgeEaNTSi0ppTu7lI8iN9S2Pf8zW7cn15aKnQkMaXBZSq77aHdbgXHk5nvYmlL6a7fxsT35TEppQ/6GoSe/6HIz8ylyf+xL9z70bc4Fvp5Smp9SagE+BpzTrffHZ1NKG/PfKP0beEYiJB/L2cDH8t1DFwJf4+mbh931qZTS5pTSX8h9S3TWHhy7N+0uSdJeSSn9jdw8EKdFxFRgFvBrgIiYke8V+GRErCP3hcLOhmN0Gg8s7rL9WNedEfG8iLgt39txLbleA7tz3s5zP9at7DFyyYVOXSfabmX35uT6BfAucl+G/L77znwi56yU0hhyX/wcC3Tt0Xl5Sml4l8dxu3HNrsYDq1JK67uUdX1fFwAzgIfzw0Re0SXuPwGXRW64zv+LiPI9vLZU1ExgSIPLBGBVD+VfBeYBN0XE/Ii4aDfOtXgP9j8GlLP7Nyw70/1m5jFyExJ3HQO6Ozczo8l1Ne1+rgk91N2R1fkETdfjx+/B8XvT7pIk7YvOIRRvAG5KKS3Ll/8fud4NDfmhCx8HYjfO9wS5IQ2d9u+2/9fANcCklNIw4PtdzrurpP1ScnNSdbU/8PhuxLUzvyA3POb6lFLrziqmlJqA3wGH7uM1u1pKrhdIXZeybe8rpTQ3pfRacsNivgJcGRFD8l92fDaldDDwfHLzl7wRaRAxgSENEhExi9yH879135fvgfDBlNJUct0yP9BlHOaObi52ddPR/WZmK7CC3FjYmi5xlZIbQrG75+1+M7M/uSEqy3quvkMr8jF1P9ee3BSNiIgh3Y5fuqPK3e2i3SVJ6gs/JzdPxVvIDx/JqwPWAS0RcRDw9t083+XAmyLi4IioAT7dbX8dud4GmyLiKHJzVnR6itzqHlN3cO7rgRkR8bqIKIuIs4GDgWt3M7YepZQWkBvG8ox5siLihRHxlogYm98+CDgVuLN73T1QGbkJOKsioorcvcY/gC/ny55DrtfFr/LXfH1EjMmvHLcmf472/Jwcz87fO60jdx/Tvg9xSUXHBIY0wEXE0HzXw8uAX6aU/tNDnVdExPSICHJ/ENt5+g/iMnZ8Y7Ezr+9yM/M54MqUUju5pcqqIjcreTnwSaCyy3HLgMk7mczyN8D7I2JKfjxq55wZe7T8Wz6Wy4EvRkRdRBwAfAD45Z6cB/hsRFRExIvIfRNyxe4euIt2lySp1+WHTP4DGEKuZ0SnD5FLLqwHfgj8djfPdwPwDXJLjs7LP3f1DuBzEbEe+G+enpCSfO+HLwJ/z88lcXS3c68k97f1g8BK4CPAK1JKK3Yntl3E/beUUk9fOqwhl7D4T0S0ADeSG2bSdR6wzsnGuz7G7uRyLeQm2+x8HA+8FphM7ouP3wOfTindnK9/IvBA/vrfBM5JKW0iN/fWleTuGR4C/sKe37dIRS0cbi0NPBGxkNyQijZy32w8SO4P3PfzH9zJr6yxJKX0yYh4P/Becj0hVgM/SCl9Pl/vNHKTXQ4FvkDuD+cCoLwzaRARk7uWRUQjcAe5STQPIvcH9vzOG46IeBPwZaCU3A3Bu4A3p5T+nJ9Z/GrgEHLLmB2RP98vU0o/yic2Pknum6MqcmNB351SWt09jvy1th3bQzuNyL+3lwObyN2wfSGl1BERs/PHTdxBG8/Ot+n/kZu1vRX4RErpFzv6uexJu0uSJEnangkMSZIkSZJU8BxCIkmSBqyI+ElELI+I+3ewPyLiWxExLyLui4gj+jtGSZK0e0xgSFIvi4gHehgb2xIR52YdmzQI/YzcePIdOQloyD8uJDcsTJIkFaCyrAOQpIEmpXRI1jFIykkp3Z6fH2dHTgN+nnJjau+MiOERMS6l9ET/RChJknZXUfXAiIgDI+LeLo91EfG+iBgZETdHxNz884gux3ws3y30kYh4eZbxS5KkgjMBWNxle0m+TJIkFZii6oGRUnoEOBwgv/7x4+SWHboIuCWldHFEXJTf/mhEHAycQ241g/HAnyNiRucqDD0ZPXp0mjx58h7FtWHDBoYMGbLnb2gAGext4Psf3O8fbAPf/+B+//B0G9x9990rUkpjso5nD0QPZT3OcB4RF5IbZkJVVdWR+++/f1/GpW46OjooKSmq796Knm3e/2zz/mebZ2POnDl7db9QVAmMbk4AHk0pPZZf5nF2vvxSoBH4KLluoZellDYDCyJiHnAUueUdezR58mSam5v3KJDGxkZmz569y3oD2WBvA9//4H7/YBv4/gf3+4en2yAiHss6lj20BJjUZXsisLSniimlS4BLAA488MD0yCOP9H102sZ/Z/3PNu9/tnn/s82zsbf3C8WcwDgH+E3+dX3nWNWU0hMRMTZfPgG4s8sxPXYL7fqNSn19PY2NjXsUSEtLyx4fM9AM9jbw/Q/u9w+2ge9/cL9/KOo2uAZ4V0RcBjwPWOv8F5IkFaaiTGBERAVwKvCxXVXtoewZ3UK7fqMyc+bMtKcZOLN2toHvf3C/f7ANfP+D+/1D4bZBRPyGXC/N0RGxBPg0UA6QUvo+cD1wMjAPaAXOzyZSSZK0K0WZwCC35Nk9KaVl+e1lnTOGR8Q4YHm+fLe7hUqSpIEnpfTaXexPwDv7KRxJkrQPinW2ktfy9PARyHX/PC//+jzg6i7l50REZURMIbfG+139FqUkSZIkSeoVRdcDIyJqgJcCb+1SfDFweURcACwCzgRIKT0QEZcDDwJtwDt3tgKJJEmSJEkqTEWXwEgptQKjupWtJLcqSU/1vwh8sR9CkyRJkiRJfaRYh5BIkiRJkqRBxASGJEmSJEkqeCYwJEmSJElSwTOBIUmSJEmSCp4JDEmSJEmSVPBMYEiSJEmSpIJXdMuoSuobky+6bq+P/eCz23jTHh6/8OJT9vp6kiRJkgYfe2BIkiRJkqSCZwJDkiRJkiQVPBMYkiRJkiSp4JnAkCRJkiRJBc8EhiRJkiRJKngmMCRJkiRJUsEzgSFJkiRJkgqeCQxJkiRJklTwTGBIkiRJkqSCZwJDkiRJkiQVPBMYkiRJkiSp4JnAkCRJkiRJBc8EhiRJkiRJKngmMCRJkiRJUsEzgSFJkiRJkgqeCQxJkiRJklTwTGBIkiRJkqSCZwJDkiRJkiQVPBMYkiRJkiSp4JnAkCRJkiRJBc8EhiRJkiRJKngmMCRJkiRJUsEzgSFJkiRJkgqeCQxJkiRJklTwTGBIkiRJkqSCZwJDkiRJkiQVvKJLYETE8Ii4MiIejoiHIuKYiBgZETdHxNz884gu9T8WEfMi4pGIeHmWsUuSJEmSpL1TdAkM4JvAjSmlg4DDgIeAi4BbUkoNwC35bSLiYOAc4BDgROB7EVGaSdSSJEmSJGmvFVUCIyKGAscCPwZIKW1JKa0BTgMuzVe7FDg9//o04LKU0uaU0gJgHnBUf8YsSZIkSZL2XVElMICpwFPATyPiXxHxo4gYAtSnlJ4AyD+PzdefACzucvySfJkkSZIkSSoiZVkHsIfKgCOAd6eU/hkR3yQ/XGQHooey9IxKERcCFwLU19fT2Ni4R0G1tLTs8TEDzWBvg4Hw/j/47La9Pra+es+PL/b26m4g/A7sC9//4H7/YBtIkqS+V2wJjCXAkpTSP/PbV5JLYCyLiHEppSciYhywvEv9SV2Onwgs7X7SlNIlwCUAM2fOTLNnz96joBobG9nTYwaawd4GA+H9v+mi6/b62A8+u42v/WfP/jtZeO7svb5eIRoIvwP7wvc/uN8/2AaSJKnvFdUQkpTSk8DiiDgwX3QC8CBwDXBevuw84Or862uAcyKiMiKmAA3AXf0YsiRJkiRJ6gXF1gMD4N3AryKiApgPnE8uEXN5RFwALALOBEgpPRARl5NLcrQB70wptWcTtiRJkiRJ2ltFl8BIKd0LzOxh1wk7qP9F4It9GZMkSZIkSepbRTWERJIkSZIkDU4mMCRJkiRJUsEzgSFJkiRJkgqeCQxJkiRJklTwTGBIkiRJkqSCZwJDkiRJkiQVPBMYkiRpwIqIEyPikYiYFxEX9bB/WET8MSL+HREPRMT5WcQpSZJ2zQSGJEkakCKiFPgucBJwMPDaiDi4W7V3Ag+mlA4DZgNfi4iKfg1UkiTtFhMYkiRpoDoKmJdSmp9S2gJcBpzWrU4C6iIigFpgFdDWv2FKkqTdUZZ1AJIkSX1kArC4y/YS4Hnd6nwHuAZYCtQBZ6eUOno6WURcCFwIMGbMGBobG3s7Xu1ES0uLbd7PbPP+Z5v3P9u8uJjAkCRJA1X0UJa6bb8cuBc4HpgG3BwRf00prXvGgSldAlwCcOCBB6bZs2f3arDaucbGRmzz/mWb9z/bvP/Z5sXFISSSJGmgWgJM6rI9kVxPi67OB36XcuYBC4CD+ik+SZK0B0xgSJKkgaoJaIiIKfmJOc8hN1ykq0XACQARUQ8cCMzv1yglSdJucQiJJEkakFJKbRHxLuBPQCnwk5TSAxHxtvz+7wOfB34WEf8hN+TkoymlFZkFLUmSdsgEhiRJGrBSStcD13cr+36X10uBl/V3XJIkac85hESSJEmSJBU8ExiSJEmSJKngmcCQJEmSJEkFzwSGJEmSJEkqeCYwJEmSJElSwTOBIUmSJEmSCp4JDEmSJEmSVPBMYEiSJEmSpIJnAkOSJEmSJBU8ExiSJEmSJKngmcCQJEmSJEkFzwSGJEmSJEkqeCYwJEmSJElSwTOBIUmSJEmSCp4JDEmSJEmSVPBMYEiSJEmSpIJnAkOSJEmSJBU8ExiSJEmSJKngmcCQJEmSJEkFr+gSGBGxMCL+ExH3RkRzvmxkRNwcEXPzzyO61P9YRMyLiEci4uXZRS5JkiRJkvZW0SUw8o5LKR2eUpqZ374IuCWl1ADckt8mIg4GzgEOAU4EvhcRpVkELEmSJEmS9l6xJjC6Ow24NP/6UuD0LuWXpZQ2p5QWAPOAo/o/PEmSJEmStC/Ksg5gLyTgpohIwA9SSpcA9SmlJwBSSk9ExNh83QnAnV2OXZIv205EXAhcCFBfX09jY+MeBdTS0rLHxww0g70NBsL7/+Cz2/b62PrqPT++2Nuru4HwO7AvfP+D+/2DbSBJkvpeMSYwXpBSWppPUtwcEQ/vpG70UJaeUZBLglwCMHPmzDR79uw9CqixsZE9PWagGextMBDe/5suum6vj/3gs9v42n/27L+ThefO3uvrFaKB8DuwL3z/g/v9g20gSZL6XtENIUkpLc0/Lwd+T25IyLKIGAeQf16er74EmNTl8InA0v6LVpIkSZIk9YaiSmBExJCIqOt8DbwMuB+4BjgvX+084Or862uAcyKiMiKmAA3AXf0btSRJkiRJ2lfFNoSkHvh9REAu9l+nlG6MiCbg8oi4AFgEnAmQUnogIi4HHgTagHemlNqzCV2SJEmSJO2tokpgpJTmA4f1UL4SOGEHx3wR+GIfhyZJkiRJkvpQUQ0hkSRJkiRJg5MJDEmSJEmSVPBMYEiSJEmSpIJnAkOSJEmSJBU8ExiSJEmSJKngmcCQJEmSJEkFzwSGJEmSJEkqeCYwJEmSJElSwTOBIUmSJEmSCp4JDEmSJEmSVPBMYEiSJEmSpIJnAkOSJEmSJBU8ExiSJEmSJKngmcCQJEmSJEkFzwSGJEmSJEkqeCYwJEmSJElSwTOBIUmSJEmSCp4JDEmSJEmSVPBMYEiSJEmSpIJnAkOSJEmSJBU8ExiSJEmSJKngmcCQJEmSJEkFzwSGJEmSJEkqeCYwJEnSgBURJ0bEIxExLyIu2kGd2RFxb0Q8EBF/6e8YJUnS7inLOgBJkqS+EBGlwHeBlwJLgKaIuCal9GCXOsOB7wEnppQWRcTYTIKVJEm7ZA8MSZI0UB0FzEspzU8pbQEuA07rVud1wO9SSosAUkrL+zlGSZK0m+yBIUmSBqoJwOIu20uA53WrMwMoj4hGoA74Zkrp5z2dLCIuBC4EGDNmDI2Njb0dr3aipaXFNu9ntnn/s837n21eXExgSJKkgSp6KEvdtsuAI4ETgGrgjoi4M6U05xkHpnQJcAnAgQcemGbPnt270WqnGhsbsc37l23e/2zz/mebFxcTGJIkaaBaAkzqsj0RWNpDnRUppQ3Ahoi4HTgMeEYCQ5IkZcs5MCRJ0kDVBDRExJSIqADOAa7pVudq4EURURYRNeSGmDzUz3FKkqTdYA8MSZI0IKWU2iLiXcCfgFLgJymlByLibfn9308pPRQRNwL3AR3Aj1JK92cXtSRJ2hETGJIkacBKKV0PXN+t7Pvdtr8KfLU/45IkSXvOISSSJEmSJKngFWUCIyJKI+JfEXFtfntkRNwcEXPzzyO61P1YRMyLiEci4uXZRS1JkiRJkvZWUSYwgPey/QRbFwG3pJQagFvy20TEweQm7DoEOBH4XkSU9nOskiRJkiRpHxVdAiMiJgKnAD/qUnwacGn+9aXA6V3KL0spbU4pLQDmAUf1U6iSJEmSJKmXFOMknt8APgLUdSmrTyk9AZBSeiIixubLJwB3dqm3JF+2nYi4ELgQoL6+nsbGxj0KqKWlZY+PGWgGexsMhPf/wWe37fWx9dV7fnyxt1d3A+F3YF/4/gf3+wfbQJIk9b2iSmBExCuA5SmluyNi9u4c0kNZekZBSpcAlwDMnDkzzZ69O6d+WmNjI3t6zEAz2NtgILz/N1103V4f+8Fnt/G1/+zZfycLz52919crRAPhd2Bf+P4H9/sH20CSJPW9okpgAC8ATo2Ik4EqYGhE/BJYFhHj8r0vxgHL8/WXAJO6HD8RWNqvEUuSJEmSpH1WVHNgpJQ+llKamFKaTG5yzltTSq8HrgHOy1c7D7g6//oa4JyIqIyIKUADcFc/hy1JkiRJkvZRsfXA2JGLgcsj4gJgEXAmQErpgYi4HHgQaAPemVJqzy5MSZIkSZK0N4o2gZFSagQa869XAifsoN4XgS/2W2CSJEmSJKnXFdUQEkmSJEmSNDiZwJAkSZIkSQXPBIYkSZIkSSp4JjAkSZIkSVLBM4EhSZIkSZIKngkMSZIkSZJU8ExgSJIkSZKkgmcCQ5IkSZIkFTwTGJIkSZIkqeCZwJAkSZIkSQXPBIYkSZIkSSp4JjAkSZIkSVLBM4EhSZIkSZIKngkMSZIkSZJU8ExgSJIkSZKkgmcCQ5IkSZIkFTwTGJIkSZIkqeCZwJAkSZIkSQXPBIYkSZIkSSp4JjAkSZIkSVLBM4EhSZIkSZIKngkMSZIkSZJU8ExgSJIkSZKkgmcCQ5IkSZIkFTwTGJIkSZIkqeCZwND/b+/+Y++q7/uOP1+yIWVN1JAArmeg9jaXFkqAzCHkR7tvm6T8yCQnU6I6QfzoiLy0IU0rT4uTSammCMnZlKpqF8YsikK1NAg1ELxAQhnNt6xh/EgyY2MIwQMUXDxQfozEyUT2Je/9cY+3my/fr32/X3/vveee+3xIV997zvmcc9+f9zk+9/h9zw9JkiRJklrPAoYkSZIkSWo9CxiSJEmSJKn1LGBIkiRJkqTWs4AhSZIkSZJazwKGJEmSJElqPQsYkiRJkiSp9SxgSJIkSZKk1puoAkaSn0nyQJKHkuxL8m+a8a9KcleSx5u/J/bN85Ek+5M8luTC8UUvSZIkSZKWa6IKGMALwG9U1TnAucBFSS4AtgN3V9VG4O5mmCRnAluAs4CLgGuTrBpH4JIkSZIkafkmqoBRPYeaweOaVwGbgRub8TcC72jebwZuqqoXqupJYD9w/ugiliRJkiRJK2H1uANYquYMiq8B/wj4VFXdn2RNVR0EqKqDSU5pmq8D7uub/UAzbv4ytwJbAdasWcPs7OySYjp06NCS5+maac9BF/q/7ey5Zc+75oSlzz/p+ZqvC9vAsbD/091/MAeSJGn4Jq6AUVUvAucmeSVwa5JfOULzLLSIBZa5E9gJsGnTppqZmVlSTLOzsyx1nq6Z9hx0of9Xbr992fNuO3uOT+5d2u7kqUtnlv15bdSFbeBY2P/p7j+YA0mSNHwTdQlJv6r6X8AsvXtbPJtkLUDz97mm2QHgtL7ZTgWeGV2UkiRJkiRpJUxUASPJyc2ZFyQ5AXgr8A1gF3BF0+wK4Lbm/S5gS5KXJdkAbAQeGGnQkiRJkiTpmE1UAQNYC3w5yR7gQeCuqvoCsAN4W5LHgbc1w1TVPuBm4BHgS8AHmktQJEnSFEhyUfMo9f1Jth+h3euSvJjkXaOMT5IkDW6i7oFRVXuA8xYY/x3gLYvMcw1wzZBDkyRJLdPc+PtT9H7cOAA8mGRXVT2yQLtPAHeOPkpJkjSoSTsDQ5IkaVDnA/ur6omq+jFwE71HrM/3QeBz/P97aEmSpBaygCFJkrpqHfB03/BLHqeeZB3wTuC6EcYlSZKWYaIuIZEkSVqCQR6n/sfAh6vqxWSh5n0LS7YCWwFOPvlkZmdnVyBEDerQoUPmfMTM+eiZ89Ez55PFAoYkSeqqQR6nvgm4qSlenARckmSuqj4/f2FVtRPYCXDGGWfUzMzMEELWYmZnZzHno2XOR8+cj545nywWMCRJUlc9CGxsHqX+d8AW4L39Dapqw+H3ST4NfGGh4oUkSRo/CxiSJKmTqmouydX0ni6yCrihqvYleX8z3fteSJI0QSxgSJKkzqqqO4A75o1bsHBRVVeOIiZJkrQ8PoVEkiRJkiS1ngUMSZIkSZLUehYwJEmSJElS61nAkCRJkiRJrWcBQ5IkSZIktZ4FDEmSJEmS1HoWMCRJkiRJUutZwJAkSZIkSa1nAUOSJEmSJLWeBQxJkiRJktR6FjAkSZIkSVLrWcCQJEmSJEmtZwFDkiRJkiS13upxByBpOq3ffvvIP/OpHW8f+WdKkiRJWhmegSFJkiRJklrPAoYkSZIkSWo9CxiSJEmSJKn1LGBIkiRJkqTWs4AhSZIkSZJazwKGJEmSJElqPQsYkiRJkiSp9SxgSJIkSZKk1rOAIUmSJEmSWs8ChiRJkiRJaj0LGJIkSZIkqfUsYEiSJEmSpNabqAJGktOSfDnJo0n2JflQM/5VSe5K8njz98S+eT6SZH+Sx5JcOL7oJUmSJEnSck1UAQOYA7ZV1S8DFwAfSHImsB24u6o2Anc3wzTTtgBnARcB1yZZNZbIJUmSJEnSsk1UAaOqDlbV15v3PwAeBdYBm4Ebm2Y3Au9o3m8GbqqqF6rqSWA/cP5Ig5YkSZIkScds9bgDWK4k64HzgPuBNVV1EHpFjiSnNM3WAff1zXagGTd/WVuBrQBr1qxhdnZ2SbEcOnRoyfN0zbTnoAv933b23LLnXXPCsc0/KsNcR13YBo6F/Z/u/oM5kCRJwzeRBYwkLwc+B/x+VX0/yaJNFxhXLxlRtRPYCbBp06aamZlZUjyzs7MsdZ6umfYcdKH/V26/fdnzbjt7jk/ubf/u5KlLZ4a27C5sA8fC/k93/8EcSJKk4ZuoS0gAkhxHr3jxmaq6pRn9bJK1zfS1wHPN+APAaX2znwo8M6pYJUmSJEnSypioAkZ6p1r8GfBoVf1R36RdwBXN+yuA2/rGb0nysiQbgI3AA6OKV5IkSZIkrYz2n/P9094EXAbsTbK7GfdRYAdwc5KrgG8B7waoqn1JbgYeofcEkw9U1Ysjj1qSJEmSJB2TiSpgVNXfsvB9LQDessg81wDXDC0oSZIkSZI0dBN1CYkkSZIkSZpOFjAkSZIkSVLrWcCQJEmSJEmtZwFDkiRJkiS1ngUMSZIkSZLUehYwJEmSJElS61nAkCRJkiRJrWcBQ5IkSZIktZ4FDEmSJEmS1HoWMCRJkiRJUutZwJAkSZIkSa1nAUOSJEmSJLWeBQxJkiRJktR6q8cdgKSFrd9++7hDkCRJkqTW8AwMSZIkSZLUehYwJEmSJElS61nAkCRJnZXkoiSPJdmfZPsC0y9Nsqd53ZvknHHEKUmSjs4ChiRJ6qQkq4BPARcDZwLvSXLmvGZPAv+kql4DfBzYOdooJUnSoCxgSJKkrjof2F9VT1TVj4GbgM39Darq3qr6XjN4H3DqiGOUJEkD8ikkkiSpq9YBT/cNHwBef4T2VwFfXGxikq3AVoCTTz6Z2dnZFQhRgzp06JA5HzFzPnrmfPTM+WSxgCFJkroqC4yrBRsmv06vgPHmxRZWVTtpLjE544wzamZmZgVC1KBmZ2cx56NlzkfPnI+eOZ8sFjAkSVJXHQBO6xs+FXhmfqMkrwGuBy6uqu+MKDZJkrRE3gNDkiR11YPAxiQbkhwPbAF29TdIcjpwC3BZVX1zDDFKkqQBeQaGJEnqpKqaS3I1cCewCrihqvYleX8z/TrgY8CrgWuTAMxV1aZxxSxJkhZnAUOSJHVWVd0B3DFv3HV9798HvG/UcUmSpKXzEhJJkiRJktR6FjAkSZIkSVLrWcCQJEmSJEmtZwFDkiRJkiS1ngUMSZIkSZLUehYwJEmSJElS61nAkCRJkiRJrWcBQ5IkSZIktd5EFTCS3JDkuSQP9417VZK7kjze/D2xb9pHkuxP8liSC8cTtSRJkiRJOlYTVcAAPg1cNG/cduDuqtoI3N0Mk+RMYAtwVjPPtUlWjS5USZIkSZK0UiaqgFFV9wDfnTd6M3Bj8/5G4B1942+qqheq6klgP3D+KOKUJEmSJEkra6IKGItYU1UHAZq/pzTj1wFP97U70IyTJEmSJEkTZvW4AxiiLDCuFmyYbAW2AqxZs4bZ2dklfdChQ4eWPE/XTHsOhtH/bWfPrejyhmnNCZMR7zC3Uf8N2P9p7j+YA0mSNHxdKGA8m2RtVR1MshZ4rhl/ADitr92pwDMLLaCqdgI7ATZt2lQz85CskQAADPRJREFUMzNLCmB2dpalztM1056DYfT/yu23r+jyhmnb2XN8cm/7dydPXToztGX7b8D+T3P/wRxIkqTh68IlJLuAK5r3VwC39Y3fkuRlSTYAG4EHxhCfJEmSJEk6Ru3/ybRPks8CM8BJSQ4AfwjsAG5OchXwLeDdAFW1L8nNwCPAHPCBqnpxLIFLkiRJkqRjMlEFjKp6zyKT3rJI+2uAa4YXkSRJkiRJGoUuXEIiSZIkSZI6zgKGJEmSJElqPQsYkiRJkiSp9SxgSJIkSZKk1rOAIUmSJEmSWs8ChiRJkiRJaj0LGJIkSZIkqfUsYEiSJEmSpNazgCFJkiRJklpv9bgDkCbF+u23Lzpt29lzXHmE6WqHI63DY7XQNvDUjrcP7fMkSZKkaeMZGJIkSZIkqfUsYEiSJEmSpNazgCFJkiRJklrPAoYkSZIkSWo9CxiSJEmSJKn1LGBIkiRJkqTWs4AhSZIkSZJazwKGJEmSJElqPQsYkiRJkiSp9SxgSJIkSZKk1rOAIUmSJEmSWs8ChiRJkiRJaj0LGJIkSZIkqfUsYEiSJEmSpNazgCFJkiRJklpv9bgDkJZj/fbbxx2CJEmSJGmEPANDkiRJkiS1ngUMSZIkSZLUehYwJEmSJElS63kPDEkaklHfq+WpHW8f6edJkiRJo+QZGJIkSZIkqfUsYEiSJEmSpNazgCFJkiRJklrPe2BoRez9u+e5csTX+0uSJEmSpsdUnIGR5KIkjyXZn2T7uOORJEmjcbRjgPT8STN9T5LXjiNOSZJ0dJ0/AyPJKuBTwNuAA8CDSXZV1SPjjWy4Rv30g21nj/TjJC3Ap55IP23AY4CLgY3N6/XAf2j+SpKklul8AQM4H9hfVU8AJLkJ2AyMtIAx6v9YSNKw9e/Xtp0918nLyEZdpLEIteIGOQbYDPx5VRVwX5JXJllbVQdHH64kSTqSaShgrAOe7hs+wLxfVpJsBbY2g4eSPLbEzzgJ+PayI+yA35vyHNj/6e4/mIOu9j+fGLjpRPZ/Cf0bxOEc/MKKLvXYHPUYYJE264CXFDDmHS+8kOThlQtVA5jIf2cTzpyPnjkfPXM+HmcsZ6ZpKGBkgXH1UwNVO4Gdy/6A5KtVtWm583fBtOfA/k93/8Ec2P/p7j+0NgdHPQYYsE1vZN/xQkv722nmfPTM+eiZ89Ez5+OR5KvLmW8abuJ5ADitb/hU4JkxxSJJkkZnkGMAjxMkSZoQ01DAeBDYmGRDkuOBLcCuMcckSZKGb5BjgF3A5c3TSC4Anvf+F5IktVPnLyGpqrkkVwN3AquAG6pq3wp/zLIvP+mQac+B/de058D+q3U5WOwYIMn7m+nXAXcAlwD7gR8Bvz3g4lvX3ylgzkfPnI+eOR89cz4ey8p7ejfdliRJkiRJaq9puIREkiRJkiRNOAsYkiRJkiSp9SxgLEOSdyfZl+QnSRZ95E6Sp5LsTbJ7uY+Jaasl5OCiJI8l2Z9k+yhjHKYkr0pyV5LHm78nLtKuU9vA0dZncxO8P2mm70ny2nHEOSwD9H8myfPN+t6d5GPjiHNYktyQ5LkkDy8yvevr/2j97/r6Py3Jl5M82uz/P7RAm05tA9O+zxuHAXJ+aZPrPUnuTXLOOOLsmkGP15K8LsmLSd41yvi6aJCcN98ru5t97t+MOsauGWD/8nNJ/nOSh5qcD3pPJC1iKMeOVeVriS/gl4EzgFlg0xHaPQWcNO54x5UDejdM+x/APwCOBx4Czhx37CvU/38LbG/ebwc+0fVtYJD1Se9GeF8EAlwA3D/uuEfc/xngC+OOdYg5+DXgtcDDi0zv7PofsP9dX/9rgdc2718BfLPL+4Bp3+e1OOdvBE5s3l9szkeT9752f03vxrfvGnfck/wacFt/JfAIcHozfMq4457k14A5/+jhY3rgZOC7wPHjjn2SX8M4dvQMjGWoqker6rFxxzFOA+bgfGB/VT1RVT8GbgI2Dz+6kdgM3Ni8vxF4x/hCGZlB1udm4M+r5z7glUnWjjrQIeny9jyQqrqH3pf5Yrq8/gfpf6dV1cGq+nrz/gfAo8C6ec26tA1M+z5vHI6a86q6t6q+1wzeB5w64hi7aNDvtw8CnwOeG2VwHTVIzt8L3FJV3wKoKvN+bAbJeQGvSBLg5fS+8+dGG2a3DOPY0QLGcBXwV0m+lmTruIMZg3XA033DB3jpwe6kWlNVB6F3UA+cski7Lm0Dg6zPLq/zQfv2hubUwy8mOWs0obVGl9f/oKZi/SdZD5wH3D9vUpe2gWnf543DUvN5Fb1f7nRsjpr3JOuAdwLXjTCuLhtkW/9F4MQks81x5OUji66bBsn5v6d3lvkzwF7gQ1X1k9GEN7WW/D26eqjhTLAk/wX4+QUm/euqum3Axbypqp5JcgpwV5JvNFWoibACOcgC4ybmub1H6v8SFjPR28A8g6zPiV7nRzFI374O/EJVHUpyCfB5YOOwA2uRLq//QUzF+k/ycnq/wv5+VX1//uQFZpnUbWDa93njMHA+k/w6vQLGm4ca0XQYJO9/DHy4ql7s/TitYzRIzlcD/xh4C3AC8N+S3FdV3xx2cB01SM4vBHYDvwH8Q3rH7v91ge86rZwlf49awFhEVb11BZbxTPP3uSS30jt1aWL+87oCOTgAnNY3fCq9iuZEOFL/kzybZG1VHWxOc1rwtL5J3wbmGWR9TvQ6P4qj9q3/C66q7khybZKTqurbI4px3Lq8/o9qGtZ/kuPoFS8+U1W3LNCkS9vAtO/zxmGgfCZ5DXA9cHFVfWdEsXXZIHnfBNzUFC9OAi5JMldVnx9JhN0z6P7l21X1Q+CHSe4BzqF3/yEt3SA5/21gR/VuzrA/yZPALwEPjCbEqbTk71EvIRmSJD+b5BWH3wO/CSx499UOexDYmGRDkuOBLcCuMce0UnYBVzTvrwBeckZKB7eBQdbnLuDy5o7CFwDPH77UpgOO2v8kP99cN0mS8+ntY6fp4LrL6/+our7+m779GfBoVf3RIs26tA1M+z5vHAbZz54O3AJc5i/RK+aoea+qDVW1vqrWA38J/K7Fi2MyyP7lNuBXk6xO8veA19O795CWZ5Ccf4veGS8kWUPvgQVPjDTK6bPk71HPwFiGJO8E/pTe3WlvT7K7qi5M8veB66vqEmANcGtzLLsa+Iuq+tLYgl5hg+SgquaSXA3cSe/OvzdU1b4xhr2SdgA3J7mK3s7u3QBd3gYWW59J3t9Mv47enckvAfYDP6JXye6EAfv/LuB3kswB/xvY0lTxOyHJZ+k9aeOkJAeAPwSOg+6vfxio/51e/8CbgMuAvUl2N+M+CpwO3dsGpn2fNw4D5vxjwKuBa5vv17mqWvRx7jq6AfOuFTRIzqvq0SRfAvYAP6F3fDnJP4SN1YDb+ceBTyfZS+/Shg936SzKcRjGsWO6dWwlSZIkSZK6yEtIJEmSJElS61nAkCRJkiRJrWcBQ5IkSZIktZ4FDEmSJEmS1HoWMCRJkiRJUutZwJAkSZI0NkkONX/XJ3nvCi/7o/OG713J5UsaLQsYklqpOYgZ6HnnSa5PcuawY5IkSUO1HlhSASPJqqM0+akCRlW9cYkxSWoRCxiSJl5Vva+qHhl3HJIk6ZjsAH41ye4kf5BkVZJ/l+TBJHuS/AuAJDNJvpzkL4C9zbjPJ/lakn1JtjbjdgAnNMv7TDPu8NkeaZb9cJK9SX6rb9mzSf4yyTeSfCZJxpALSQtYPe4AJOkIVie5ETgP+CZweVX9aH6jJLPAv6yqr444PkmStHK20/s+/6cATSHi+ap6XZKXAV9J8ldN2/OBX6mqJ5vhf15V301yAvBgks9V1fYkV1fVuQt81j8DzgXOAU5q5rmnmXYecBbwDPAV4E3A3650ZyUtnWdgSGqzM4CdVfUa4PvA7445HkmSNDq/CVyeZDdwP/BqYGMz7YG+4gXA7yV5CLgPOK2v3WLeDHy2ql6sqmeBvwFe17fsA1X1E2A3vUtbJLWABQxJbfZ0VX2lef+f6B1sSJKk6RDgg1V1bvPaUFWHz8D44f9rlMwAbwXeUFXnAP8d+JkBlr2YF/rev4hnrUutYQFDUpvVUYYlSVJ3/AB4Rd/wncDvJDkOIMkvJvnZBeb7OeB7VfWjJL8EXNA37f8cnn+ee4Dfau6zcTLwa8ADK9ILSUNjAUNSm52e5A3N+/fg9aeSJHXZHmAuyUNJ/gC4HngE+HrzZLL/yMJnQ3yJ3n2z9gAfp3cZyWE7gT2Hb+LZ59bm8x4C/hr4V1X1P1e0N5JWXKr8QVNS+yRZD9xB7xeSNwKPA5d5E09JkiRpOlnAkCRJkiRJreclJJIkSZIkqfW8o66kiZHkVmDDvNEfrqo7xxGPJEmSpNHxEhJJkiRJktR6XkIiSZIkSZJazwKGJEmSJElqPQsYkiRJkiSp9SxgSJIkSZKk1vu/7VhfJGk+VlUAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1080x1080 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_merf_training_stats(mrf_huc_szn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "Z_test_huc_szn = np.ones((len(X_test), 1))\n",
    "\n",
    "y_hat_huc_szn = mrf_huc_szn.predict(X_test, Z_test_huc_szn, clusters_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MSE: 0.13469692038432665\n",
      "RMSPE: 36.70107905557092\n",
      "MPE: -1.25738188430838\n",
      "R2: 0.954373863534669\n"
     ]
    }
   ],
   "source": [
    "mse_test_huc_szn = np.mean((y_test - y_hat_huc_szn) ** 2)\n",
    "print('MSE:', mse_test_huc_szn)\n",
    "\n",
    "rmspe_test_huc_szn = math.sqrt(np.mean( (y_test - y_hat_huc_szn) ** 2)) * 100\n",
    "print('RMSPE:', rmspe_test_huc_szn)\n",
    "\n",
    "mpe_test_huc_szn = np.mean(((y_test-y_hat_huc_szn) / y_test) * 100)\n",
    "print('MPE:', mpe_test_huc_szn)\n",
    "\n",
    "r2_test_huc_szn = r2_score(y_test, y_hat_huc_szn)\n",
    "print('R2:', r2_test_huc_szn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MSE: 0.0748486352228765\n",
      "RMSPE: 27.35847861685231\n",
      "MPE: -0.9934519600491638\n",
      "R2: 0.9746268391008172\n"
     ]
    }
   ],
   "source": [
    "Z_train_huc_szn = np.ones((len(X_train), 1))\n",
    "\n",
    "y_hat_train_huc_szn = mrf_huc_szn.predict(X_train, Z_train_huc_szn, clusters_train)\n",
    "\n",
    "mse_train_huc_szn = np.mean((y_train - y_hat_train_huc_szn) ** 2)\n",
    "print('MSE:', mse_train_huc_szn)\n",
    "\n",
    "rmspe_train_huc_szn = math.sqrt(np.mean( (y_train - y_hat_train_huc_szn) ** 2)) * 100\n",
    "print('RMSPE:', rmspe_train_huc_szn)\n",
    "\n",
    "mpe_train_huc_szn = np.mean(((y_train-y_hat_train_huc_szn) / y_train) * 100)\n",
    "print('MPE:', mpe_train_huc_szn)\n",
    "\n",
    "r2_train_huc_szn = r2_score(y_train, y_hat_train_huc_szn)\n",
    "print('R2:', r2_train_huc_szn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MSE: 0.08681881668808943\n",
      "RMSPE: 29.46503295231306\n",
      "MPE: -1.046240257641318\n",
      "R2: 0.9705742907103182\n"
     ]
    }
   ],
   "source": [
    "Z_full_huc_szn = np.ones((len(X_full), 1))\n",
    "\n",
    "y_hat_full_huc_szn = mrf_huc_szn.predict(X_full, Z_full_huc_szn, clusters_full)\n",
    "\n",
    "mse_full_huc_szn = np.mean((y_full - y_hat_full_huc_szn) ** 2)\n",
    "print('MSE:', mse_full_huc_szn)\n",
    "\n",
    "rmspe_full_huc_szn = math.sqrt(np.mean( (y_full - y_hat_full_huc_szn) ** 2)) * 100\n",
    "print('RMSPE:', rmspe_full_huc_szn)\n",
    "\n",
    "mpe_full_huc_szn = np.mean(((y_full-y_hat_full_huc_szn) / y_full) * 100)\n",
    "print('MPE:', mpe_full_huc_szn)\n",
    "\n",
    "r2_full_huc_szn = r2_score(y_full, y_hat_full_huc_szn)\n",
    "print('R2:', r2_full_huc_szn)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>MSE_TEST</th>\n",
       "      <th>RMSPE_TEST</th>\n",
       "      <th>MPE_TEST</th>\n",
       "      <th>R2_TEST</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HUC04 X SEASONS X HUC08</td>\n",
       "      <td>0.166536</td>\n",
       "      <td>40.808761</td>\n",
       "      <td>-1.607135</td>\n",
       "      <td>0.943589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>SEASONS X HUC08</td>\n",
       "      <td>0.110355</td>\n",
       "      <td>33.219649</td>\n",
       "      <td>-0.549868</td>\n",
       "      <td>0.962619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HUC08</td>\n",
       "      <td>0.069639</td>\n",
       "      <td>26.389164</td>\n",
       "      <td>-0.475172</td>\n",
       "      <td>0.976411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>HUC_SZN</td>\n",
       "      <td>0.134697</td>\n",
       "      <td>36.701079</td>\n",
       "      <td>-1.257382</td>\n",
       "      <td>0.954374</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Name  MSE_TEST  RMSPE_TEST  MPE_TEST   R2_TEST\n",
       "0  HUC04 X SEASONS X HUC08  0.166536   40.808761 -1.607135  0.943589\n",
       "1          SEASONS X HUC08  0.110355   33.219649 -0.549868  0.962619\n",
       "2                    HUC08  0.069639   26.389164 -0.475172  0.976411\n",
       "3                  HUC_SZN  0.134697   36.701079 -1.257382  0.954374"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data = {'Name': ['HUC04 X SEASONS X HUC08', 'SEASONS X HUC08', 'HUC08', 'HUC_SZN'],\n",
    "        'MSE_TEST': [mse_test_huc4_seasons, mse_test_seasons, mse_test_hucs, mse_test_huc_szn],\n",
    "\n",
    "        'RMSPE_TEST': [rmspe_test_huc4_seasons, rmspe_test_seasons, rmspe_test_hucs, rmspe_test_huc_szn],\n",
    "       \n",
    "        'MPE_TEST': [mpe_test_huc4_seasons, mpe_test_seasons, mpe_test_hucs, mpe_test_huc_szn],\n",
    "       \n",
    "        'R2_TEST': [r2_test_huc4_seasons, r2_test_seasons, r2_test_hucs, r2_test_huc_szn],\n",
    "        }\n",
    "\n",
    "test_df = pd.DataFrame(test_data)\n",
    "test_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>MSE_TRAIN</th>\n",
       "      <th>RMSPE_TRAIN</th>\n",
       "      <th>MPE_TRAIN</th>\n",
       "      <th>R2_TRAIN</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HUC04 X SEASONS X HUC08</td>\n",
       "      <td>0.006357</td>\n",
       "      <td>7.973308</td>\n",
       "      <td>-0.150698</td>\n",
       "      <td>0.997845</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>SEASONS X HUC08</td>\n",
       "      <td>0.006398</td>\n",
       "      <td>7.998460</td>\n",
       "      <td>-0.158987</td>\n",
       "      <td>0.997831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HUC08</td>\n",
       "      <td>0.009360</td>\n",
       "      <td>9.674851</td>\n",
       "      <td>-0.212450</td>\n",
       "      <td>0.996827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>HUC_SZN</td>\n",
       "      <td>0.074849</td>\n",
       "      <td>27.358479</td>\n",
       "      <td>-0.993452</td>\n",
       "      <td>0.974627</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Name  MSE_TRAIN  RMSPE_TRAIN  MPE_TRAIN  R2_TRAIN\n",
       "0  HUC04 X SEASONS X HUC08   0.006357     7.973308  -0.150698  0.997845\n",
       "1          SEASONS X HUC08   0.006398     7.998460  -0.158987  0.997831\n",
       "2                    HUC08   0.009360     9.674851  -0.212450  0.996827\n",
       "3                  HUC_SZN   0.074849    27.358479  -0.993452  0.974627"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data = {'Name': ['HUC04 X SEASONS X HUC08', 'SEASONS X HUC08', 'HUC08', 'HUC_SZN'],\n",
    "        'MSE_TRAIN': [mse_train_huc4_seasons, mse_train_seasons, mse_train_hucs, mse_train_huc_szn],\n",
    "        'RMSPE_TRAIN': [rmspe_train_huc4_seasons, rmspe_train_seasons, rmspe_train_hucs, rmspe_train_huc_szn],\n",
    "        'MPE_TRAIN': [mpe_train_huc4_seasons, mpe_train_seasons, mpe_train_hucs, mpe_train_huc_szn],\n",
    "        'R2_TRAIN': [r2_train_huc4_seasons, r2_train_seasons, r2_train_hucs, r2_train_huc_szn],\n",
    "        }\n",
    "\n",
    "train_df = pd.DataFrame(train_data)\n",
    "train_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>MSE_FULL</th>\n",
       "      <th>RMSPE_FULL</th>\n",
       "      <th>MPE_FULL</th>\n",
       "      <th>R2_FULL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HUC04 X SEASONS X HUC08</td>\n",
       "      <td>0.090446</td>\n",
       "      <td>30.074159</td>\n",
       "      <td>-1.259131</td>\n",
       "      <td>0.969345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>SEASONS X HUC08</td>\n",
       "      <td>0.046724</td>\n",
       "      <td>21.615819</td>\n",
       "      <td>-0.340556</td>\n",
       "      <td>0.984164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HUC08</td>\n",
       "      <td>0.021417</td>\n",
       "      <td>14.634379</td>\n",
       "      <td>-0.264996</td>\n",
       "      <td>0.992741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>HUC_SZN</td>\n",
       "      <td>0.086819</td>\n",
       "      <td>29.465033</td>\n",
       "      <td>-1.046240</td>\n",
       "      <td>0.970574</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Name  MSE_FULL  RMSPE_FULL  MPE_FULL   R2_FULL\n",
       "0  HUC04 X SEASONS X HUC08  0.090446   30.074159 -1.259131  0.969345\n",
       "1          SEASONS X HUC08  0.046724   21.615819 -0.340556  0.984164\n",
       "2                    HUC08  0.021417   14.634379 -0.264996  0.992741\n",
       "3                  HUC_SZN  0.086819   29.465033 -1.046240  0.970574"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_data = {'Name': ['HUC04 X SEASONS X HUC08', 'SEASONS X HUC08', 'HUC08', 'HUC_SZN'],\n",
    "        'MSE_FULL': [mse_full_huc4_seasons, mse_full_seasons, mse_full_hucs, mse_full_huc_szn], \n",
    "        'RMSPE_FULL': [rmspe_full_huc4_seasons, rmspe_full_seasons, rmspe_full_hucs, rmspe_full_huc_szn],\n",
    "        'MPE_FULL': [mpe_full_huc4_seasons, mpe_full_seasons, mpe_full_hucs, mpe_full_huc_szn],\n",
    "        'R2_FULL': [r2_full_huc4_seasons, r2_full_seasons, r2_full_hucs, r2_full_huc_szn],\n",
    "        }\n",
    "\n",
    "full_df = pd.DataFrame(full_data)\n",
    "full_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "HUC04 X SEASONS X HUC08\n",
      "MSE: 0.16653550116127572\n",
      "RMSPE: 40.80876145649066\n",
      "MPE: -1.6071347948591594\n",
      "R2: 0.9435891223004472\n",
      "\n",
      "SEASONS X HUC08\n",
      "MSE: 0.11035450803161512\n",
      "RMSPE: 33.21964900952674\n",
      "MPE: -0.5498684188398779\n",
      "R2: 0.9626194138021228\n",
      "\n",
      "HUC08\n",
      "MSE: 0.0696387957169545\n",
      "RMSPE: 26.389163631489822\n",
      "MPE: -0.4751716019719059\n",
      "R2: 0.9764111221875211\n",
      "\n",
      "HUC08_SEASON\n",
      "MSE: 0.13469692038432665\n",
      "RMSPE: 36.70107905557092\n",
      "MPE: -1.25738188430838\n",
      "R2: 0.954373863534669\n"
     ]
    }
   ],
   "source": [
    "print('HUC04 X SEASONS X HUC08')\n",
    "print('MSE:', mse_test_huc4_seasons)\n",
    "print('RMSPE:', rmspe_test_huc4_seasons)\n",
    "print('MPE:', mpe_test_huc4_seasons)\n",
    "print('R2:', r2_test_huc4_seasons)\n",
    "\n",
    "print('\\nSEASONS X HUC08')\n",
    "print('MSE:', mse_test_seasons)\n",
    "print('RMSPE:', rmspe_test_seasons)\n",
    "print('MPE:', mpe_test_seasons)\n",
    "print('R2:', r2_test_seasons)\n",
    "\n",
    "print('\\nHUC08')\n",
    "print('MSE:', mse_test_hucs)\n",
    "print('RMSPE:', rmspe_test_hucs)\n",
    "print('MPE:', mpe_test_hucs)\n",
    "print('R2:', r2_test_hucs)\n",
    "\n",
    "print('\\nHUC08_SEASON')\n",
    "print('MSE:', mse_test_huc_szn)\n",
    "print('RMSPE:', rmspe_test_huc_szn)\n",
    "print('MPE:', mpe_test_huc_szn)\n",
    "print('R2:', r2_test_huc_szn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "test['Y_HUC4_SEASON'] = y_hat_huc4_seasons\n",
    "test['Y_SEASON'] = y_hat_seasons\n",
    "test['Y_HUC8'] = y_hat_hucs\n",
    "test['Y_HUC_SZN'] = y_hat_huc_szn\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x13cef523580>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot('YEAR', 'LOG_PR_WATER', data=test[test['HUC08']==8010206].sort_values('YEAR'), color='black')\n",
    "plt.plot('YEAR', 'Y_HUC4_SEASON', data=test[test['HUC08']==8010206].sort_values('YEAR'))\n",
    "plt.plot('YEAR', 'Y_SEASON', data=test[test['HUC08']==8010206].sort_values('YEAR'))\n",
    "plt.plot('YEAR', 'Y_HUC8', data=test[test['HUC08']==8010206].sort_values('YEAR'))\n",
    "plt.plot('YEAR', 'Y_HUC_SZN', data=test[test['HUC08']==8010206].sort_values('YEAR'))\n",
    "\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x13ced648ee0>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot('YEAR', 'LOG_PR_WATER', data=test[test['HUC08']==3150202].sort_values('YEAR'), color='black')\n",
    "plt.plot('YEAR', 'Y_HUC4_SEASON', data=test[test['HUC08']==3150202].sort_values('YEAR'))\n",
    "plt.plot('YEAR', 'Y_SEASON', data=test[test['HUC08']==3150202].sort_values('YEAR'))\n",
    "plt.plot('YEAR', 'Y_HUC8', data=test[test['HUC08']==3150202].sort_values('YEAR'))\n",
    "plt.plot('YEAR', 'Y_HUC_SZN', data=test[test['HUC08']==3150202].sort_values('YEAR'))\n",
    "\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'bodies': [<matplotlib.collections.PolyCollection at 0x13ed0d17fa0>,\n",
       "  <matplotlib.collections.PolyCollection at 0x13ed0d403a0>,\n",
       "  <matplotlib.collections.PolyCollection at 0x13ed0d40760>,\n",
       "  <matplotlib.collections.PolyCollection at 0x13ed0d40b20>],\n",
       " 'cmaxes': <matplotlib.collections.LineCollection at 0x13ed0d17ee0>,\n",
       " 'cmins': <matplotlib.collections.LineCollection at 0x13ed0d41270>,\n",
       " 'cbars': <matplotlib.collections.LineCollection at 0x13ed0d416c0>}"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.violinplot([y_test - y_hat_huc4_seasons, \\\n",
    "                y_test - y_hat_seasons, \\\n",
    "                y_test - y_hat_hucs,\\\n",
    "                y_test - y_hat_huc_szn])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9435891223004472"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r2_score(y_test, y_hat_huc4_seasons)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "dswe",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.2"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}