P26. Supervised ML - Multiple Linear Regression - Cars dataset.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Supervised ML - Multiple Linear Regression - Cars dataset"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import statsmodels.formula.api as smf\n",
    "import statsmodels.api as sm\n",
    "from statsmodels.graphics.regressionplots import influence_plot #for Leverage value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "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>HP</th>\n",
       "      <th>MPG</th>\n",
       "      <th>VOL</th>\n",
       "      <th>SP</th>\n",
       "      <th>WT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>49</td>\n",
       "      <td>53.700681</td>\n",
       "      <td>89</td>\n",
       "      <td>104.185353</td>\n",
       "      <td>28.762059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>55</td>\n",
       "      <td>50.013401</td>\n",
       "      <td>92</td>\n",
       "      <td>105.461264</td>\n",
       "      <td>30.466833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>55</td>\n",
       "      <td>50.013401</td>\n",
       "      <td>92</td>\n",
       "      <td>105.461264</td>\n",
       "      <td>30.193597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>70</td>\n",
       "      <td>45.696322</td>\n",
       "      <td>92</td>\n",
       "      <td>113.461264</td>\n",
       "      <td>30.632114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>53</td>\n",
       "      <td>50.504232</td>\n",
       "      <td>92</td>\n",
       "      <td>104.461264</td>\n",
       "      <td>29.889149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>322</td>\n",
       "      <td>36.900000</td>\n",
       "      <td>50</td>\n",
       "      <td>169.598513</td>\n",
       "      <td>16.132947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>238</td>\n",
       "      <td>19.197888</td>\n",
       "      <td>115</td>\n",
       "      <td>150.576579</td>\n",
       "      <td>37.923113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>263</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>50</td>\n",
       "      <td>151.598513</td>\n",
       "      <td>15.769625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>295</td>\n",
       "      <td>19.833733</td>\n",
       "      <td>119</td>\n",
       "      <td>167.944460</td>\n",
       "      <td>39.423099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>236</td>\n",
       "      <td>12.101263</td>\n",
       "      <td>107</td>\n",
       "      <td>139.840817</td>\n",
       "      <td>34.948615</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>81 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     HP        MPG  VOL          SP         WT\n",
       "0    49  53.700681   89  104.185353  28.762059\n",
       "1    55  50.013401   92  105.461264  30.466833\n",
       "2    55  50.013401   92  105.461264  30.193597\n",
       "3    70  45.696322   92  113.461264  30.632114\n",
       "4    53  50.504232   92  104.461264  29.889149\n",
       "..  ...        ...  ...         ...        ...\n",
       "76  322  36.900000   50  169.598513  16.132947\n",
       "77  238  19.197888  115  150.576579  37.923113\n",
       "78  263  34.000000   50  151.598513  15.769625\n",
       "79  295  19.833733  119  167.944460  39.423099\n",
       "80  236  12.101263  107  139.840817  34.948615\n",
       "\n",
       "[81 rows x 5 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# import the dataset\n",
    "cars=pd.read_csv('Database/Cars.csv')\n",
    "cars"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## EDA "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 81 entries, 0 to 80\n",
      "Data columns (total 5 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   HP      81 non-null     int64  \n",
      " 1   MPG     81 non-null     float64\n",
      " 2   VOL     81 non-null     int64  \n",
      " 3   SP      81 non-null     float64\n",
      " 4   WT      81 non-null     float64\n",
      "dtypes: float64(3), int64(2)\n",
      "memory usage: 3.3 KB\n"
     ]
    }
   ],
   "source": [
    "cars.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "HP     0\n",
       "MPG    0\n",
       "VOL    0\n",
       "SP     0\n",
       "WT     0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cars.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Correlation Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>HP</th>\n",
       "      <th>MPG</th>\n",
       "      <th>VOL</th>\n",
       "      <th>SP</th>\n",
       "      <th>WT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>HP</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.725038</td>\n",
       "      <td>0.077459</td>\n",
       "      <td>0.973848</td>\n",
       "      <td>0.076513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MPG</th>\n",
       "      <td>-0.725038</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.529057</td>\n",
       "      <td>-0.687125</td>\n",
       "      <td>-0.526759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VOL</th>\n",
       "      <td>0.077459</td>\n",
       "      <td>-0.529057</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.102170</td>\n",
       "      <td>0.999203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SP</th>\n",
       "      <td>0.973848</td>\n",
       "      <td>-0.687125</td>\n",
       "      <td>0.102170</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.102439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WT</th>\n",
       "      <td>0.076513</td>\n",
       "      <td>-0.526759</td>\n",
       "      <td>0.999203</td>\n",
       "      <td>0.102439</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           HP       MPG       VOL        SP        WT\n",
       "HP   1.000000 -0.725038  0.077459  0.973848  0.076513\n",
       "MPG -0.725038  1.000000 -0.529057 -0.687125 -0.526759\n",
       "VOL  0.077459 -0.529057  1.000000  0.102170  0.999203\n",
       "SP   0.973848 -0.687125  0.102170  1.000000  0.102439\n",
       "WT   0.076513 -0.526759  0.999203  0.102439  1.000000"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cars.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x25e78fc47c0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x900 with 30 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Scatterplot between variables along with histograms\n",
    "sns.set_style(style='darkgrid')\n",
    "sns.pairplot(cars)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Building"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "model=smf.ols('MPG~HP+VOL+SP+WT',data=cars).fit()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Intercept    30.677336\n",
       "HP           -0.205444\n",
       "VOL          -0.336051\n",
       "SP            0.395627\n",
       "WT            0.400574\n",
       "dtype: float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Finding Coefficient parameters\n",
    "model.params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Intercept is Beta0=30.677336, Beta1=-0.205444, Beta2=-0.336051, Beta3=0.395627, Beta4=0.400574"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Intercept    2.058841\n",
       " HP          -5.238735\n",
       " VOL         -0.590970\n",
       " SP           2.499880\n",
       " WT           0.236541\n",
       " dtype: float64,\n",
       " Intercept    0.042936\n",
       " HP           0.000001\n",
       " VOL          0.556294\n",
       " SP           0.014579\n",
       " WT           0.813649\n",
       " dtype: float64)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Finding tvalues and pvalues\n",
    "model.tvalues , model.pvalues"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.7705372737359844, 0.7584602881431415)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Finding rsquared values\n",
    "model.rsquared , model.rsquared_adj   # Model accuracy is 75.85%"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "# For pvalues<0.05, the features HP and SP are significant and useful in building regression equation\n",
    "# pvalues of features VOL and WT are not-significant(insignificant) as pvalue>0.05 ; thus either of the one insignificant varaibles can be used in regression equation\n",
    "# To check which variable to be used, perform Simple linear regression (SLR) & Multiple linear regressin (MLR) on each insignificant varaible and find their tvalues and pvalues"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Build SLR and MLR models for insignificant variables 'VOL' and 'WT'\n",
    "# Also find their tvalues and pvalues"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Intercept    14.106056\n",
       " VOL          -5.541400\n",
       " dtype: float64,\n",
       " Intercept    2.753815e-23\n",
       " VOL          3.822819e-07\n",
       " dtype: float64)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "slr_v=smf.ols('MPG~VOL',data=cars).fit()\n",
    "slr_v.tvalues , slr_v.pvalues  # VOl has significant pvalue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Intercept    14.248923\n",
       " WT           -5.508067\n",
       " dtype: float64,\n",
       " Intercept    1.550788e-23\n",
       " WT           4.383467e-07\n",
       " dtype: float64)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "slr_w=smf.ols('MPG~WT',data=cars).fit()\n",
    "slr_w.tvalues , slr_w.pvalues  # Wt has significant pvalue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Intercept    12.545736\n",
       " VOL          -0.709604\n",
       " WT            0.489876\n",
       " dtype: float64,\n",
       " Intercept    2.141975e-20\n",
       " VOL          4.800657e-01\n",
       " WT           6.255966e-01\n",
       " dtype: float64)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mlr_vw=smf.ols('MPG~VOL+WT',data=cars).fit()\n",
    "mlr_vw.tvalues , mlr_vw.pvalues  # VOl & Wt together have insignificant pvalue, either of the one has to be used"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Validation Techniques \n",
    "### Two Techniques: 1. Collinearity Check & 2. Residual Analysis"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "1) Collinearity Problem Check\n",
    "# From correlation analysis, the independent variables are suspected to be collinear to others and may be causing collinearity problem. This collinearity can be detected by finding VIF (Variance Inflation Factor) for all independent variables.\n",
    "# For Vif > 20, independent varaibles have collinearity."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Variables</th>\n",
       "      <th>Vif</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HP</td>\n",
       "      <td>19.926589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>VOL</td>\n",
       "      <td>638.806084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SP</td>\n",
       "      <td>20.007639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>WT</td>\n",
       "      <td>639.533818</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Variables         Vif\n",
       "0        HP   19.926589\n",
       "1       VOL  638.806084\n",
       "2        SP   20.007639\n",
       "3        WT  639.533818"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate VIF = 1/(1-Rsquare) for all independent variables\n",
    "rsq_hp=smf.ols('HP~VOL+SP+WT',data=cars).fit().rsquared\n",
    "vif_hp=1/(1-rsq_hp)\n",
    "\n",
    "rsq_vol=smf.ols('VOL~HP+SP+WT',data=cars).fit().rsquared\n",
    "vif_vol=1/(1-rsq_vol)\n",
    "\n",
    "rsq_sp=smf.ols('SP~HP+VOL+WT',data=cars).fit().rsquared\n",
    "vif_sp=1/(1-rsq_sp)\n",
    "\n",
    "rsq_wt=smf.ols('WT~HP+VOL+SP',data=cars).fit().rsquared\n",
    "vif_wt=1/(1-rsq_wt)\n",
    "\n",
    "# Putting the values in Dataframe format\n",
    "d1={'Variables':['HP','VOL','SP','WT'],'Vif':[vif_hp,vif_vol,vif_sp,vif_wt]}\n",
    "Vif_df=pd.DataFrame(d1)\n",
    "Vif_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Here, VOL & WT both have VIF>20, thus have collinearity problem.Thus remove either of the collinear variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "2) Residual Analysis\n",
    "# Residual or error annalsis is performed to detect any outliers or influencers and to find patterns.\n",
    "# Good model should have no outliars and no patterns or clusters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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CODgJAiGEcHASBEII4eAkCIQQ4j+6dW0Be00nfbsqVrVCCFHO5K4tkDutdGKiwvjxOiAz35PD5ZlcEQghxH9Q2NoCGRm2XVtAc/4cbrPewuvRh3H+fnfJP18GNQkhRKVQnC4fu60toKo4/fwTVYYFU+2RZrhFLsB0XxOyG99f4k1JEAghHJa1A31hy0mOH68rEAY2X1sgKwvX9Wvw7PIUXs92xmVHAhnDRnJ1735SPl6NWr16iTcpQSCEqDQsHdgLe72oA31xu3zCwrLQ6/Mf9PV6lbCwrFL92ZRLl3CbP5vqvk2pOmoYSmoq1+cs4N/f/yTtzQjM9e65/W0XNdfQpUuXSElJQavVEhcXR1BQEPffX/JLj9Iicw3Zl7SNddI+lpVm28TH55/LP/ege/NNW8g5IAcGGlmzxrnA63q9ytWrBc+FfXzM/PprGrVqeaCqBbt3FEXl4sXUIusp6Y1iS+3jtP839LHRuH6+EcVgIKvTM2QMGY7xqY6gKf65vLW5hooMgkGDBvHKK6+watUqunTpwpo1a1ixYkWxd17aJAjsS9rGOmkfy0qrbW4dpQPWD+xarYrJVFh/vQpYPtD7+rqTmGg5KEpbvvbJzsb1y03o42Jw3vsjZncPsgIHkDHkFUwNG93W9v/TpHPZ2dm0atWKlJQUnn32WVlgXghhV5a6bK5eLfzmrMlUsu3n9u3bqsvnZsrVf9FHLaRaywepOjQYzcULpM6YzdX9f5I6++3bDoGiFPkcgdFoZPbs2bRs2ZIff/wRU0lbVQghSlFJR+NotYWHgZeXSmYmBa4scg/0OV07mf+5y6dYNR4+hPbjZVRftRIlMxND+6dInbsQQ6dncn6AMlZk19CpU6fYs2cPAQEBbN++nQcffJA6deqUeWGWSNeQfUnbWCftY1lptY2lLhsvLzOZmUqx7xEsXJgJYJMDfaFMJly2fo0+LhqX3TtR9Xoy+waSMXQ4pialfx/2P61ZXKdOHVxcXIiJiaFNmza4u7uXanFCCFESYWFZhd4jmDUr50y+sAN769Ymiwd8Wz/9qyQnoVv1CfrlsWjPnMLk7UPqa2/hOmo4qRqdTWvJq6moK4KwsDDuvPNOvv/+e1555RVWr15NXFycreorQK4I7EvaxjppH8vKetRQeZ/OQXv8L/Rx0ejWrkZJT8Pw6GNkDB2OoVsPcHKy6wplRV4RnDlzhoiICPbt20fHjh2JjY0t1eKEEKKk/P2zy/2BHwCzGZdvt6OPi8Flx3ZUFxey+gSQMXQ42Q8+ZO/q8hQZBCaTiatXrwKQmpqKpgTjVoUQwhEpqddxXbsa/fL3cDr+F6Zad5E2JZyMoEGoNWvau7wCigyCsWPH0r9/fy5fvky/fv2YNm2aLeoSQogKR3Pqb/TLY9GtWoHmegrGR1qSEr2MLL9e4OJi7/IsKjIIWrduzTfffMPVq1fx8vJCUcp4IiUhhKhIVBXn3TtzRv988xVotWQ91zun++eRVvaurlgsBkG/fv0sHvTXrFlTZgUJIUSFkJ6OLn4d+mUxOP15GHONGqSPm0Bm8BDMd9W2d3UlYjEIFi5caMs6hBCiQtCcS0T/fhy6Tz5Ec+0axmbNSYmKJquXP+jsM/zzv7IYBN9//z0BAQEsWLCgwJXB+PHjy7wwIYQoN1QVp59+RL8sBtcvN4GqYujuR8awERjbtIUK3mVuMQjuuusuABo0aJDvdblHIIRwGFlZuH4WnzP52x+/Y/b0JGPEGDIGDcFcp669qys1FoOgffv2ABw4cIDXX3897/VJkybRq1evsq9MCCHsRHPxAroPl6P/6H00Vy6T3bgJ1+e/Q2bfflAJZ1ewGAQrV64kOjqa5ORktm7dmvd6w4YNbVKYEELkstWTxE6/7cuZ+3/Tp5CdjaFzFzKGjsD4xFMVvvvHmiKnmIiJiWH48OG2qqdIMsWEfUnbWCftY9ntto2l9QcWLswsnTAwGnH94nP0sdE47/sZs0cVMgcMJGPwMMwNbHfia88pJooMgtTUVHbu3InBYMh7zZ5dQxIE9iVtY520j2XFbZtbz/7T07G6ktjtUq5cQb/iA3QfLEN74R+y6zcgc8grZAa+gFql6m1v93aV67mGRo4cyZ133knt2jnjYuVmsRCirNx69p+YqJCzklhBJV2XIJf24AH0y2LQxa9DycrC8FRHUhdEYnj6mRIt/ViZFBkEqqry9ttv26IWIYSDK2z1scKWk4QbK4kVi8mEy9dbcp7+/X43qpsbmYEDc5Z+bNzk9guuJIoMgsaNG7N///58C9a7lPKcGb169aJKlZzLFh8fH2bPnl2q2xdCVAyWz/Lzry9c3CUjlaRr6FauQP9+LNqzZzDVqUvqGzPJfCEI1dOrdIquBIoMgr1797Jjx468rxVFISEhodQKyMrK+cdcsWJFqW1TCFExeXur/98dlJ+Xl4q7u1rsUUPaY0fRx8WgW78aJT0dw2PtSH1zFoau3cGpyMOewynyZnFZ279/P5MmTcLb25vs7GzGjx9PixYtLH6/2WzGZCrbkrVaDSaTuUz3UVFJ21gn7WNZcdpm9WqFESMU0tNvhIGbm0p0tEr//kX8f282o3z9FZoli9Fs347q6orafwCmUaPhofIz978lZf274+xsee3jIoMgISGBVatWYTQaUVWVpKQkNm/eXGrFHT16lP379xMQEMCpU6cYOnQoX3/9NU4WUltGDdmXtI110j6WWWqbW0cJde6czbZtTsU++1eup6BbsxLdsvdw+vskprtqkzl4KBkDg1Fr1CjLH6lUletRQ++++y6vvfYaa9asoU2bNuzZs6dUi6tfvz716tVDURTq16+Pp6cnly9fzhulJISovAobJbRmjXOxnhHQnDyB/v1YdKs+QZN6HWPL1qRMCSerR09wdrZF+ZVGkWOlvLy8ePjhhwHo06cPFy9eLNUCNmzYwJw5cwC4ePEiqamp1CyHK/gIIUpfYaOEMjIUIiJcC/+AquL83bdUHfg81dr6ov9gGYYu3bj2zbckbdlOVu++EgK3ocgrAmdnZ37++Weys7PZtWsXly9fLtUC+vbty9SpU+nfvz+KojBr1iyL3UJCiMrF0iihAq+npaHbsDZn7v+jRzDXqEn6+ElkBr+MudZdNqi0civyHsHFixc5efIkNWvWJDIykq5du/Lss8/aqr4C5B6BfUnbWCftY1lu29x8T0CjAZOpYBjkPjWsOXsmZ+7/lR+hSUrC2LwFGUOH58z972rhqqGCKtf3CEwmE/Xq1QNg6tSppVeVEMLh3HpPwGSCAs8I6MwseT6BqoOW4PLVF6AoZD37HBlDhpPd5tFKPfmbvRQZBOPGjUNRFMxmM4mJidSrV4/Vq1fbojYhRCVj6clhrVbF2ZTJSK9VTHWPosbCPzB7eZExKjRn7n+fOnap11EUGQRr167N+3tKSkq+tQmEEKIoN3cFFdYRXZvzjDQtZVqN99BcuUJ2rfu5viCKTP/nwc3N9gU7oBLdla1SpQpnzpwpq1qEEJVMYVNI52rDj4QQRQDr0WLC2LIbGUOGY2z/pHT/2FiRQdCvXz8URUFVVa5evUrbtm1tUZcQohK4tSvIGQMBrCeEKNqwl2SqEq0dTfU3hvLMcOn+sZcig2DhwoV5f3d1daVGBXpSTwhhX7nDQGtyiVd4jxFEczf/cJT7GM1itt39IuNec+aZMlhtTBSf1SD4448/WLVqFefOnaNWrVr079+fb7/9lsaNG9O8eXNb1SiEKIdu7vv39FRRFLh2Lf80EQ+pvxFKFP1ZjSsGvqIrg3mfw96d2PdbBm8AICFgbxaDYOfOnSxZsoQxY8bg7e3NqVOnmDlzJh4eHnz88ce2rFEIUU7kHvwTExUUBVQ154z/2rUb3T//JJpI/mATK4niCXaRijtxDGUJozlKk5xlJsMz7fUjiEJYDIJly5YRGxuLp6cnAA0aNGD79u2cOHFCVikTwoFYOvjfOgLIi6sMYRmjeJd6nOEk9RnPAt5nMMl4Aio+PuYyW3he3D6LQaCqal4I5GrXrh2nTp0q65qEEOXEraN+Chv+2ZSDjGExQazAjQx20IEQoviCHpi5MfWxovCf1hgWZcfipHNZWVkYjcZ8r3Xq1AlTzqOAQohKLD7eCV9fd0aMKHzopwYTPdjMNjpxkAd5kY9ZyQs0Zz9Ps4NN9MwXAgB1ZFBQuWUxCPz8/Jg2bRrJyckAJCUlER4eTo8ePWxWnBDC9nKvAhITNdy6XnBVkgnlHY5xH5t5jsYcZSqzqMNZhhHHAXIHkeS/dNDrVWbMsOsaWMIKi11DQUFBrFixgn79+nH9+nWqVKnCwIEDGThwoC3rE0LYWGHTQDTiGGNYTDAfUoVUdvM4U5jD5/TEiDNeXirVFHOBUUM3Ly7Tv78LSUl2+qGEVXZfqrKkZPZR+5K2sa4it8/NN4VzrgRUnmEroUTSna/IwoU1BLKYMezjEXx8il497GYVuW1soVzPPiqEqNzi452YNs31/4eAKriTyot8zBgWcz9HuEAt3mA67zEMZ59ahIVl8ZV/qr3LFqVIgkAIB3bzqKB7+JtRvMsQluFJMj/TkoGsYB3P46TPXT5SRv1URsUKgh9++IGzZ8/SvHlz6tevj2slWxBCCEcVMdOFNhn/I4QonmMTKgob6EskofzIowD/3wVU9BrCouIq1lxDFy5c4MSJEzg7OxMbG5tv/iEhRAWUkYFu43q+OBfLQ/zBFaozhylEM4Jz+OR9W+5KYaJyK3Lx+n379jFv3jzc3Nzo3bs3iYmJtqhLCFEGNOfP4R7xJh4PPECVcaNRUHmZZdThLOFE5AsBvT7nZrCo/Iq1VGVWVhaKomAymdBoiswOIUQ5Er9By9dv/Erg5SX0ZQMKKpt4jkhC+Y4nufVZAVCpVk0lIkKmgnAURQbBSy+9RJ8+fbh69SoBAQEEBwfboCwhxH8RH+/EvJkKj59bRyhRDGcfSdzBO4xlCaM5zT2FfEot8ZBQUTkUGQTdunXjscce4/Tp0/j4+FCtWjVb1CWEuA3x8U68M+Ua/ZJj+Z4Y7uIif9KEESxlBUGk4WHxszIXkOOyGATjx4+3OMvoggULyqwgIcTt2blwP1Xmx/KHaQ0uGPmS7kQRwjY6oxZ9OxBv7wr1bKkoRRaDIDAwMN/XuctVCiHKh/h4J+bO1NDq3GeMJQp/vuc6HsQwnMWM4TiNir0tuTHs2CwGQevWrQH4999/iY6O5tSpUzRq1Ijhw4fbrDghRI5bVwOrknWFAenL2Ek0dUjkOA0J5R0+JJgU7ijWNhVFRVWR+wKi6OvFsWPH0rBhQyZMmICPjw+TJk2yRV1CCHICoHHjnOmgExM1NFMPMO/aMI6k12M2YRylMX5sojFHiSLUYggoigqoaLU5f/r4mFm6NJNLl1L59dc0CQEHV6wni/v37w9AkyZN+Prrr8u0ICFEjtzpH7IyzPRkE6FE0oH/kY6ej3mRKEI4TNMitiJDQUXRigyCBg0asGnTJtq0acOhQ4fw9PTk77//BqB+/fplXqAQjmrxjAxGZCxlNEuozynOUIdJzGUZQ7hGUaP3ZCioKL4ip6EOCgoq/IOKYpdF7GUaavuStrGuOO1z83TPWi2YTOT7817TESa4LiYw62M8SGMn7YkihM/ohakYF/F6vfr/E8SVrwCQ3x3ryvU01CtWrCjVYoRwZLeuAZy78qvZZKYr3xBqiqQr35CV5cIqBhBFCL/zcBFbVdFowGyWG7/i9hQZBIsWLSI+Pj7fa7t37y6zgoSojAou+pLDg+u8xEeMYTGNOcZ5avMab/Eer3CZOwvZkoq7u4qrK3mrgcmBX/xXRQbB//73P3bs2IGLi4st6hGi0rn1KgCgAScYzRIG8z53kMKPtGEAK9lAX4xY+n9NJTq6/HX5iIqvyCB44IEHyMrKKrMgMJvNTJ8+naNHj+Li4sLMmTOpV69emexLCFuLj3di9GgdJlPO0o8d2UEokfTgC0xoWcfzRBHCXtoUuS0fH1VCQJSJIoOgUaNGtGvXjho1aqCqKoqikJCQUGoFbN++HYPBwNq1a/n999+ZM2cO0dHRpbZ9IWxp9WqFsDB3EhMVFAVUFfRkMJBPCCGKZhziEjWJIIxoRvAPd3yskhoAABn2SURBVBdru/LkryhLRQbBli1bSEhIoGrVqmVSwL59+2jfvj0ALVq04ODBg1a/X6tV8PR0K5NabuxDU+b7qKikbQq3erXCuHEKV69C7j0AH/UMo3iXocRRjWv8RguC+YA1BJKFjtwHvG4dNWQyQbVqOZPAXb0KderAjBkq/fu7gMVuo/JPfness2f7FBkEd999N3q9vsy6hlJTU/HwuDEjolarJTs7GyenwkszmVQZPmpH0jYF5b8HoPI4uwklkt58ioLKp/QmihB20Z7ckLidIZ5JSWVTv63I74515Xr46IULF+jcuTN16tQBcp4fWLNmTakV5+HhQVrajalvzWazxRAQwh6sjfv38lJJTlZwMht4kTWEEokvv3EVLxbwKksZyRny3/PSasvnOH/huIo1fLQs+fr68u2339K9e3d+//137rvvvjLdnxDFFR/vxLRprly7dmPIZ+64/9w/Xa9d4A2ieYX3qMUlDvEAw3iPTxhIBgUv88vrw17CsRUZBNnZ2Xz99dcYjUYALl26xFtvvVVqBXTu3Jk9e/YQGBiIqqrMmjWr1LYtxO0oLABu1ZKfCSWS51mHE9l8QQ+iCCGBpy18Rub8EeVXkUEwefJkOnTowK+//sqdd95Jenrp9mFpNJpSDRYh/ovCxvzncsJIXzYQQhRt+ZEUqrCUkSxhNCe495bvlqd9RcVRZBDodDpeeeUVTp06xezZsxkwYIAt6hLCLiIiXAuEQA0uM4xYRrIUb87zF/cyhig+JJhUCt6A02pVliyR7h9RcRQZBKqqcvnyZdLS0khPTyc5OdkWdQlhF+fO3QiBh/idEKIYwCp0ZPENzzCUOL6mq8WlH93cVBYskBAQFUuRQTB69Gi2bdtGz549efrpp+nVq5ct6hKiTFkaCaRRs3mOzYQSyZPsJA03PmAQUYRwhCZoNKCayRv/7+Wloig35v2JiIBu3SQERMVS5DTUuVJSUtBoNPnG/NuDTENtXxW9bSzdCPbkGkNYxije5R5Oc4p6LGE0y3mZJDyLfaO3ordPWZK2sc6ezxFYXKry0KFD9OrVC6PRyNatW+natSv+/v7s2LGjTIoUorTExzvh6+vOnXd6ULu2R74/R47Uce2ahtwQuJ/DRDOcRHyYzyT+pj69+JSGnGABr+LhcwfR0ZkcOSLLOYrKy2LX0KJFi5gzZw7Ozs688847xMXFUa9ePYYMGULHjh1tWaMQRbq5qydnjp/Cx/2rKiiY6cZXhBLJM2wjE1dW8gJRhPAHD+VtU1FUfv017dZdCVHpWAwCVVVp0qQJFy9eJCMjg6ZNc9ZG1WiKXO9eCJu6dcinpc7OKqQwiA8YzRIacZxEvJlGBLEM419qFPh+b+9i9ZoKUeFZDAKz2QzArl27aNu2LQAGgyHfdBBClAeFDfm82b38xWiWMIgPqMp1fuBRXmMG8fiTjXOhn5HZPoUjsRgEbdu2JTAwkAsXLhAdHc2ZM2eYPn063bt3t2V9QhTp5iGfN6h0ZhshRNGdLWTjxDqeJ5JQfqFVvu/LffArd/SQPAAmHI3VUUMnTpygWrVqeHl5cebMGY4ePUrnzp1tWV8BMmrIvspj2/j6upOYmNNl6UYaQawghCge4E8ucicxDCeG4VygNpDT96+qZXPAL4/tU15I21hXbmcfbdiwYd7f69atS926dUuvKiFuU+6N4XPnFDw9VQwGqMffjGIpQ1iGF0nsw5cX+ZANmn5kmF3RagGTKmf7QhRC5nsWFUbBZwBUHry2i1Ai6cnnqChspA8fVBlDz7mPsKCviQUYAaOdKxeifJMgEBXCzSODXMlkAKsIIYoW7OdfqjGPSSxlJInUwecOMx/3lUENQhSXBIGoECIiXPHKOE8YSxlGLDW5wgGaMZRYVvJCvrn/C795LISwRIJAlHtOv+xlXuIy+rIBLSY240ckoXxLBwqb+1/G/wtRMhIEoty4+SZwzTuy6GVcz+C0JbRhL924gyhCeJdR/E0Di9uQ8f9ClJwEgbCrW6eGqKleIpz3GJEUTW0ucJT7GMUSPuIl0rh1wkMVd3cVV9cbs3/KiCAhSk6CQNjNzTeAH+ZXQtVIAlmDKwa+oiuDCeEbuhQy978MAxWiNEkQCJvLvQr4J9FE7/9f+rE9u0nFnTiGspgxHKOxxc8rCjIZnBClSIJAlKpbH/bKXbQl9+9XrypU4ypDiGIU71KXs5ykPuNYyPsMJoU7ityH3AwWonRJEIj/zNIU0DkPfpH396YcZDZRDOQT3MgggY6MZglf8ixmtMXal9wMFqL0SRCIYrn5TN/b253OnbPZts2pwMH/1pmrNJh4li8JJZKn2UEGOj5hIFGEcJAHC+wndx6g3CUgr15VZDI4IcqYBIEo0q3z/ScmKnzwgTO5Y/gLm7awKskM5n1Gs4SGnOQMdZjMHJYxhKtUL2QvcgNYCHuRIBBFKny+/8Kf3r2Po4xhMcF8iAdp7KIdU5jDp/TGZOHXTa9XWbgwUwJACDuRIBCFurkryPJE5TkUzHRmG6FE0p2vyMKFNQQSRQi/8kjhnynDqaCFECUjQSDyWLrpa4k7qbzIx4QQRROO8g938TpvEsswLlILLy+Vaoo536ghefBLiPJHgkAAxV/3F6A+JxnFEl7mfTxJZi+tGMgK1hFALR9npodl4e+faqPKhRD/lQSBg8o/CkglPR2r6/6CylN8SyhRPMcmzIqWL3X+zMkIJdGnDWFhWSzyNwAGW/0IQohSIkHggAobBQSFXwLoyOAFVhJCFM05gFqjBulBr5IZPITHat/NJgDkKV8hKjIJgkro1rP93Aewcl/TaMBksj4KyIezjCCaYcRSg3/5Q2nOtwOjabdkIOlZ8mSvEJWJBEElU9jZfkiIDkUBgyHnNZPJ0qfNPMYPhBCFP/EoqHxOT1bXHMPTb7bBv68J9HrIkgXIhahMJAgquOL09RuN1kf/uJBFP9YyThvFw6Z9XMOTZR5jqTJlCM8M86Y9ABbTQwhRwdk1CFRV5YknnuCee+4BoEWLFrz66qv2LKlCKUlff2FqcYHhxDCcGO7iItdqNub6uIVkBwTi73Hr3P9CiMrKrkFw5swZmjZtSkxMjD3LqBAK6/cvyRO/N2vJz4QQRT/W4oKRBF03fhk6gjbhT5KtyHq/QjgaRVWLem607GzZsoW4uDg8PDzQ6XRMnTqVBg0sL0MIYDabMZnKtmStVoPJZC7TfZTE6tUKI0YopKffOEi7ueV0AxV+4Ffzve7srOKMkR7GTwklksf4get4kNg5mHsXjYT77it2LeWtbcobaR/LpG2sK+v2cXa2PMOvzYJg/fr1fPTRR/lee/311/n333/p1q0bv/zyC7NnzyY+Pt7qdoxGE0lJZXuz0tPTrcz3URK+vu4kJt66ShdotWoho3/Ay8uMuzucO6fQ7K7LxLWKpunOWDySznOchqy4YzR13+jPcwPdSlxLeWub8kbaxzJpG+vKun1q1qxi8T27XhFkZGSg1WpxcXEBoF27duzatQvFSveEIwZBrVoeFqZ7UNHr898czp3A7fkmv6NfFoMufh1KZiaGJzuQMXQ4hk5dQFMwVIqrvLVNeSPtY5m0jXX2DILbPyKUgiVLluRdJRw5coS7777bagg4Kksrcvn45Bz0fXzMKIpKXW8jG19cx+BPulCtw2PoNq4n8/kBXN21l+T1n2N4ptt/CgEhROVk1yuC5ORkJk6cSHp6Olqtltdff52GDRta/UxlviIo7Iawv392gdFBkH/qZiU5Cd3KFejfj0V75jQmnzpkDB5G5gtBqF7VSrVGOauzTtrHMmkb6+x5RWDXUUN33HEHsbGx9iyh3ChsKOj48Togd57+zAIh8Xzzw+gnRaNbtxolPR1D28dJnR6BoWt3cJJHRIQQxWPXK4LbUVmvCCzdEPbxMfPrrzfN5WM247JjG/rYaFz+twPV1ZXMPgFkDnmF7AcfKvM65azOOmkfy6RtrHPYKwJxw7lzhd8byX1dSb2O65qV6Je9h9PJE5hq3UXalHAyXhyMWqOGLUsVQlQyEgTlhLe3+v9PBuf3WK3juIcvQrfqEzSp1zE+0pKUmOVk9egJ/z/aSggh/gsZQlJOhIVlodfn9tKpPM12vtT4setiY/Tvx2F4pivXvkog6asdZPUJkBAQQpQauSIoJ/z9s3EyXOX4G+sISlpCUw6T4VaT9GETyQx+GfNdte1dohCikpIgKAc0iWfRvx/H4E8+RJOUhLFZc1KGRZPVyx90OnuXJ4So5CQI7EVVcf7ph5zRP1s2A2Do7kfGsBEY27QFebBOCGEjEgS2lpWF66cb0MfF4HxgP2ZPTzJGhpAxeChmnzr2rk4I4YAkCGxEc/ECug+Wof/4fTRXrpDd5H6uvx1JZt9+4Fbyyd+EEKK0SBCUMadff0EfG43rpk/BZMLwTFcyho7A2P5J6f4RQpQLEgRlwWjEdfNn6OOicd73C+YqVcl4eRgZg4dhrm99vQUhhLA1CYJSpFy5gv7j99F9uBzthX/IbtCQ67Pnk9VvAKqH5ce7hRDCniQISoH2wB85c/9vXI+SlYWhw9OkLlqMoUMnmfZZCFHuSRDcruxsXL76Ev2yGFx+2IPq5k5m/4FkDBmO6b7G9q5OCCGKTYKghJRrV2/M/Z94FlPdeqS+OYvMAQNR7/C0d3lCCFFiEgTFpD16BH1cDLr1q1EyMjA83p7UmXMxdOkGWsuLQgshRHknHdjWmM24bP2KO/r2pFr71ujWrSKzTwBXv/2e5E+/xNC9R4lCID7eCV9fd2rV8sDX1534eMlhIYT9yZGoMCkp6GNj0S97D+2pvzHVvpvUsDfIHBiMWr36bW2y6BXIhBDCPuSK4Cbak8dxnzYRp3vq4hE+BXPNO0mJ+5CrvxwgI/RVqyFQ1Nl+RIRrvjWHATIyFCIiXMvkZxFCiOKSKwJVxfl/O3JG/2zfCk5OnGzVj5DjY/jql1Z4/6MSlp1l9ay9OGf7Ra1AJoQQ9lIprghuq+89LQ3dB8vwat8az369cf79N9InTOHjGUdp/vvHbLnUGlVVSEzUMH68zuo2i3O27+1d+NLQll4XQghbqfBBkHs2npioKdaBW3PmNO7Tw6ne4n6qTB6PqncjZcl7/PvrIdInTiV8ST3S00vWhVOcs/38K5Dl0OtVwsKyivujCiFEmajwXUPWzsbzunNUFefvd6OPi8Hl6y9BUcjq0ZOMoSPIbtU63+Rvt9OFY2m94ZvP9nNqySQiwpVz5xS8vXNCQG4UCyHsrcIHgdUDd0YGuo3r0cfF4HT4IOZq1cgYM46M4Jcxe/sU+rniHNRvFRaWle8eARR+tu/vny0HfiFEuVPhu4YKO0B7k0ikRxjVH76fKuNGg6pyfdES/v3tT9LC3rAYApBzUHdzK1kXjr9/NgsXZuLjY0ZRVHx8zCxcKMNChRAVg6KqaoW6W2k0mkhKSs/7+saIHXiUHwklkr5sQKuYMXR9loyhwzE+3r5Ec/9/9ZU7YWFIF04hPD3d8rW/yE/axzJpG+vKun1q1rQ8A3KF7xrK7Xu/Z1x/umZ+TrJyB4c6jsJnzhDM9e65rW3276/SrZv8wgohHEOFDwLICQP95TZcd26Pod8A7vbwwGzvooQQooKoFEEAkDF8tL1LEEKICqnC3ywWQgjx30gQCCGEg5MgEEIIB2fzINi2bRuvvvpq3te///47AQEBBAYGsmTJEluXI4QQDs+mQTBz5kwWLFiA2XxjTM8bb7zBggULWL16Nfv37+fQoUO2LEkIIRyeTUcN+fr60qlTJ9auXQtAamoqBoOBunXrAtCuXTt++OEHmjZtanEbWq2Cp6dbmdap1WrKfB8VlbSNddI+lknbWGfP9imTIFi/fj0fffRRvtdmzZpF9+7d+emnn/JeS01NxcPDI+9rd3d3zp49a3XbJpNa5k8nyhOQlknbWCftY5m0jXWV7snigIAAAgICivw+Dw8P0tLS8r5OS0ujatWqZVGSEEIIC+z6QJmHhwfOzs6cOXOGOnXqsHv3bkaPtv5gmLOz1mqylRZb7KOikraxTtrHMmkb6+zVPnZ/svjNN99kwoQJmEwm2rVrx0MPPWTvkoQQwqFUuNlHhRBClC55oEwIIRycBIEQQjg4CQIhhHBwEgRCCOHgJAiEEMLBSRDc4vr16wwfPpyBAwfSr18/fvvtN3uXVC7dOnmgIzObzbz++uv069ePoKAgTp8+be+SyqX9+/cTFBRk7zLKFaPRyMSJExkwYAB9+/YlISHBLnXY/TmC8uaDDz7g0UcfJTg4mJMnT/Lqq6/y6aef2ruscmXmzJns3r2b+++/396llAvbt2/HYDCwdu1afv/9d+bMmUN0dLS9yypX4uLi2LRpE3q93t6llCubNm3C09OT+fPnc+3aNXr37s3TTz9t8zrkiuAWwcHBBAYGAmAymXB1dbVzReWPr68v06dPt3cZ5ca+ffto3749AC1atODgwYN2rqj8qVu3LosXL7Z3GeVO165dCQ0Nzftaq9XapQ6HviKwNDle8+bNuXz5MhMnTmTatGl2qs7+ijt5oKO7dfJErVZLdnY2Tk4O/b9XPl26dCExMdHeZZQ77u7uQM7vUEhICGPHjrVLHQ79m2ppcryjR48yfvx4Jk2aROvWre1QWflQ3MkDHd2tkyeazWYJAVFs//zzD6NGjWLAgAH4+fnZpQbpGrrF8ePHCQ0NZcGCBTz55JP2LkdUAL6+vuzcuRPIWXHvvvvus3NFoqK4cuUKgwcPZuLEifTt29dudchpyy0WLFiAwWAgIiICyDnbkxt/wprOnTuzZ88eAgMDUVWVWbNm2bskUUHExMSQkpLC0qVLWbp0KZBzY12n09m0Dpl0TgghHJx0DQkhhIOTIBBCCAcnQSCEEA5OgkAIIRycBIEQQjg4GT4qypU5c+Zw6NAhLl++TGZmJnXq1MHLy4sXXniBNWvWsGjRojLd/9GjR0lJSaFVq1aMGzeOuXPn4uLiUuzPP/744+zZsyffa2lpaSxcuJD9+/ej0+nw8PBg8uTJ1K9fv1RqTkpKYteuXfj5+REbG8ujjz7K8ePHOXnyJBMmTCiVfYjKTYJAlCtTpkwBYOPGjfkOZLaa0mLr1q3UqFGDVq1alVroTJkyhTZt2vDaa68BcOTIEUaNGsXatWupUqXKf97+0aNH2bFjB35+fgwbNgzIeTBSiOKSIBAVxunTpxkyZAhXr16lQ4cOjBkzhqNHjzJz5kwAPD09mTVrFlWqVGHOnDns27cPgB49evDSSy8xZcoUkpKSSEpK4r333mPZsmX8/PPPqKpKcHAwvr6+fPrppzg7O9O0aVPGjh3LV199xT///EN4eDhGoxGdTseiRYu4cuUKc+bMwWw2k5KSQnh4OL6+vgVqvnjxIqdOnco34VqTJk3o2LEjW7duRVGUvMDLysqiW7du7Nixg71797JkyRIAMjMzmTt3Ls7Ozrz66qvcddddnD17lgcffJA333yTmJgYjhw5wtq1a/ntt9/o3r17vhpWrFjBF198gaIodO/enRdffJGtW7cSFxeHk5MT3t7ezJs3D41GeoodlQSBqDCysrJYunQpJpOJp556ijFjxvDaa68xa9Ys7r33XtavX8+yZcto0aIFiYmJrFu3juzsbAYMGMCjjz4KkDfF+HfffUdiYiJr1qwhKyuL559/nhUrVtC7d29q1KhB8+bN8/Y7d+5chg0bxhNPPMGWLVs4fPgwKSkpTJ48mcaNG7N582Y2btxYaBCcP38eHx+fAq97e3tz7ty5Qt8D+Ouvv5g/fz61atUiJiaGr7/+Gj8/P06dOsXy5cvR6/V06tSJy5cvM3z4cNasWVPo+hnHjx9ny5YtrFq1CkVRCA4Opl27dnzxxRcEBwfz7LPP8tlnn5GamkrVqlX/yz+PqMAkCESF0ahRo7z++txJ3U6cOMGbb74J5CzyUb9+fU6cOEHLli1RFAVnZ2ceeughTpw4AZDXL3/s2DEOHTqUt1BKdnY258+fL3S/f//9Nw8//DBA3tn2L7/8wtKlS9HpdKSlpeWbffRmd999d6Gzbp46dYoGDRrke+3mh/xr1apFREQEbm5uXLx4MS9k6tatm7evmjVrkpWVZbXNjh07xvnz5wkODgYgOTmZM2fOMHXqVN577z1Wr15NgwYN6NSpk9XtiMpNgkBUGIqiFHitfv36zJ07l7vvvpt9+/Zx+fJlXF1d2bhxI8HBwRiNRn777Td69+6dbxsNGjSgTZs2zJgxA7PZzNKlS/Hx8UFRFMxmc759NGzYkAMHDvDYY4+xadMmkpOT2bhxI2+//TYNGzYkKiqKc+fOFVpzrVq1qFevHitXruSFF17g7bffxmQykZCQwMiRI9m9ezeXL18G4NChQ3mfCw8PZ/v27Xk3lnNDorA20Gg0BWrO1aBBA+69916WLVuGoih8+OGH3Hfffaxdu5YxY8ZQvXp1Xn/9dbZt25bXRsLxSBCICm369OlMnjwZk8kEQEREBPXr12fv3r3069cPo9FI165dadq0ab7PdezYkb179zJgwADS09Pp1KkTHh4eNGvWjHnz5tGwYcO87500aRKvv/460dHR6HQ65s+fT3Z2NiNHjqR69ercddddXLt2zWKNc+fOZeHChQQEBKDRaNDpdNSuXZtjx47Rvn17Vq9eTf/+/WnatGne/PQ9e/bk+eefp2rVqtSoUYNLly5Z3H7dunU5duwYH374YYH3mjRpQtu2benfvz8Gg4HmzZtTq1YtmjdvzqBBg/D09MTd3Z2nnnqqBK0uKhuZdE4IO7h+/ToXLlygUaNG9i5FCAkCIYRwdDJeTAghHJwEgRBCODgJAiGEcHASBEII4eAkCIQQwsFJEAghhIP7P/wdzlBSr6YsAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Test for Normality of Residuals (Q-Q Plot) using residual model (model.resid)\n",
    "sm.qqplot(model.resid,line='q') # 'q' - A line is fit through the quartiles # line = '45'- to draw the 45-degree diagonal line\n",
    "plt.title(\"Normal Q-Q plot of residuals\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[array([ 0, 76], dtype=int64)]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(np.where(model.resid>10))  # outliar detection from above QQ plot of residuals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Test for Homoscedasticity or Heteroscedasticity (plotting model's standardized fitted values vs standardized residual values)\n",
    "\n",
    "def standard_values(vals) : return (vals-vals.mean())/vals.std()  # User defined z = (x - mu)/sigma"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(standard_values(model.fittedvalues),standard_values(model.resid))\n",
    "plt.title('Residual Plot')\n",
    "plt.xlabel('standardized fitted values')\n",
    "plt.ylabel('standardized residual values')\n",
    "plt.show() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Test for errors or Residuals Vs Regressors or independent 'x' variables or predictors \n",
    "# using Residual Regression Plots code graphics.plot_regress_exog(model,'x',fig)    # exog = x-variable & endog = y-variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure(figsize=(15,8))\n",
    "sm.graphics.plot_regress_exog(model,'HP',fig=fig)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "# Plot1-4: Difference between y(mpg-blue dot) and fitted y(fitted mpg-red dot) is the error or residue. Idealy No or lesser distance is a good model else otherwise.\n",
    "# Plot2-4: Straight block line irrespective of slope & no patterns or clusters is a good model else otherwise.\n",
    "# Plot3-4: Straight block line irrespective of slope & no patterns or clusters is a good model else otherwise.\n",
    "# Plot4-4: More the slope, better the variable; consider in regression equation; sign of good model, else otherwise."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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of9kiNygFGCLXmXr16jFkyBDGjRuHy+Xi5ZdfJiIi4oLnHT16lO3bt/PBBx8QGBjIunXrmDt3Lm3atAFgx44drF27ltDQUAYMGMDSpUsZMGAAL774IrNmzeLee+/ls88+Y/ny5Ret5d133+WTTz7x3H/00Ufp3r27536fPn344osvPG90XC4X69evZ/r06SQkJPDaa6/x/vvvU65cOfbv38/jjz/Ohg0bmDt3LoGBgXzxxRckJyfz17/+9YIAw2q10rVrV1avXk3Dhg1JTU3lm2++YerUqUyfPp1WrVrRv39/Tp06RWxsLL169cJiufSsuXr16jFixAheeOEFxo8fT6NGjS7r70RERMRX9evXD4Dk5GQCAgJo2bIl06dPB2Dt2rX88ssvrFixApvNxrJlyxg/fjyLFi1i5syZzJo1i9tuu42tW7cSHx/P3Xff7Tnu3r17efPNN/nnP/9JpUqVLnuK6Pvvv88LL7xAkyZNyMjIoHXr1uzevZvw8HDPcxYvXlzo7/Hu3bvTvXt3Ro0ahb+/P2vWrKFHjx6kpqYyZswYFi9eTGRkJElJSfTo0YN69eoB7tGgmzZtIjQ0lLfeeovIyEjeeecdMjMzGTduHGlpaZesPy4ujscff5yYmBj27dvHsmXLLggwbDYbPXr0YOXKlZ4AY9myZfTu3RvDMPjpp5+oVatWviApT9OmTXn99dcvqy9FSiMFGCLXob59+7J+/Xpq165NixYtCnxOtWrVmDlzJp9++imJiYn89NNPZGRkeB5v3LgxoaGhANxyyy2kpqbyyy+/YLPZuPfeewHo0KHDJd+QXGwKyeXYtm0bJ0+e5LHHHvO0GYbBoUOH+Oabbxg7diyGYVC+fHlP6HK+rl270q1bN0aPHs1nn31Gq1atCAsLo02bNowaNYqdO3dy7733Mn78+ELDizzffvstlSpV4quvvqJPnz6X/ToRERFflDeFZM+ePfTv358mTZpQoUIFAL788kt27dpF165dAXC5XGRlZQEQExPDwIEDadGiBffddx9PP/10vuN+88033HfffVSqVAmARx55hK1btxZaz4wZM9i8eTMLFizgt99+Iycnh8zMzHwBxuX8Ho+KiqJevXps2rSJe++9l2+//ZaXX36ZHTt2cOrUKZ5//nnPcw3D4OeffwbcX1bkvf9p1qwZ/fv35/jx4zRt2pRhw4YRFhZ2yfrbt2/PlClT2LRpE02bNmXo0KEFPq9Hjx7ExMSQnp6Ow+Fg69atvPTSS57HHQ5Hga/Lzc3FMIxL1iBSmumduch1KjIykurVq1/08T179vDII4+Qnp7Offfdx1NPPZXv8cDAQM+fDcPANE0Az20em807OafL5eLee+/ln//8p+e/5cuXU7du3QvqKGh6DLhDmltuuYWvvvqK1atX061bNwBatmzJ+vXrad++PXv37qVjx46cOHGi0JoWLVrEb7/9xieffMLx48d56623iuFKRURESl6DBg0YM2YMo0eP9izO7XK5eOqppzy/h1etWsXHH38MwJAhQ/joo49o2LAhq1evLnAq5sV+V5/7vgLItxj2o48+ytdff02tWrV4/vnnqVy58gXvPS7393iPHj1Yu3Ytn332GQ888AAhISE4nU5q166d7/3FsmXLuP/++wEIDg72vL5Ro0Zs3LiRRx55hKNHj9K9e3d27959yfp79uzJJ598wn333cfWrVvp1KkTOTk5F9QWERFB06ZN+de//sXatWtp166dJxy57bbbSExM5NSpUxe8Lj4+/oZZzFTEGxRgiNygvv/+exo2bMjjjz9O48aN2bhxY77dSwpSr149TNPk66+/BmDjxo2kpqYWqQ6r1er5luHcP997771s27aNAwcOAO65q506dSI7O5tmzZqxcuVKXC4XqampbNy48aLH79GjB4sWLSIrK8szzWTYsGH861//IiYmhkmTJhEaGsqhQ4cuWef27dv5+9//TlxcHOXLl2fu3Ln84x//YMuWLUW6fhEREV/RoUMHGjVq5JlCcv/997Ny5UrS09MBeOONNxg5ciQOh4NWrVqRlZVFr169mDRpEj///DO5ubmeY913331s27bNEyysWbPG81i5cuXYs2cPpmmSnp7Ol19+CcCZM2fYtWsXw4cPp23btpw4cYJDhw5dsN7W5f4eb9OmDXv27GH58uX06NED+F848P333wPuqS7t2rUrcBHxWbNmMW/ePB544AHGjRtHnTp12L9/P+XLl2f//v3k5ORgt9tZv3695zU9e/Zk7969PPzww0ydOpUzZ84UGESAeyrtp59+ytq1a/MFQBEREfTt25ehQ4fmq2vVqlVs2LDhgtEuIvI/mkIicoPq0KEDGzZsoH379rhcLlq2bElqaqrnTUpB/Pz8eOutt3jppZeYM2cO9evX9wwzvVqtWrVizpw52O127rjjDt566y0GDhzIm2++yZQpUxg6dCimaWKz2Zg/fz4hISEMGjSISZMm0b59e8qXL59vYbCCjj958uR8v+yfe+45xo0bx7Jly7BarTzwwAPcfffdJCUl0b9/f95+++1864YcOXKEoUOH8vLLL3tGtdSpU4eJEycyYsQI1qxZQ5UqVYrUDyIiIr5gwoQJdOrUiS1bttC9e3fPGhGGYVClShVmzJiBzWZj7NixDB8+HJvNhmEYxMbG4u/v7zlO3rpR/fr1IyQkJN+6UXnHb9u2LRERETRu3BjTNClTpgz9+/fnr3/9K8HBwURERHDHHXeQmJhIVFSU5/UX+z1+Pn9/fx566CG2b9/uOX/elxAzZ84kJycH0zSZOXMmkZGRfPfdd/le369fP0aPHk2HDh3w9/enXr16xMTEYLFYuPvuu2nfvj2VKlWiSZMmnikow4cPJzY2ltdffx3DMBg4cCCRkZEF9nWTJk2YNm0aZcuW9azBkWfYsGGsWLGCZ599ltzcXHJzc/nzn//M0qVLqVatmud5I0eOZMyYMZ77vXv3ZsSIEYX+PYvcqAzz/DFbIiIiIiIiIiI+RlNIRERERERERMTnKcAQEREREREREZ+nAENEREREREREfJ4CDBERERERERHxeV7bhWThwoVs2rQJu91Or169aNy4MaNHj8YwDOrWrcukSZOwWJSfiIiIiIiIiEjhvLILSXx8PP/4xz+YN28eWVlZvPPOO+zZs4fHH3+cJk2aMHHiRJo1a0abNm0ueRyXy4XTWfo2SbFajVJ53cVJfVh06sOiUx8Wnfqw6LzVh35+1mI/5rVUWt9jgH6uioP6sOjUh0WnPiwa9V/RebMPL/Y+wysjMLZu3crNN9/M888/T3p6OiNHjmT58uU0btwYgObNm7Nt27ZCAwyn0yQlJdMbJfq08PDgUnndxUl9WHTqw6JTHxad+rDovNWHlSqFFfsxr6XS+h4D9HNVHNSHRac+LDr1YdGo/4rOm314sfcZXgkwkpOTOXbsGAsWLODIkSM8++yzmKaJYRgAhISEkJaWVuhxrFaD8PBgb5To06xWS6m87uKkPiw69WHRqQ+LTn1YdOpDERERuVF4JcAIDw+nVq1a+Pv7U6tWLQICAjhx4oTn8YyMDMqUKVPocUrrtyNKA4tOfVh06sOiUx8Wnfqw6DQCQ0RERG4UXllF884772TLli2YpklSUhJZWVnce++9xMfHA7B582buuusub5xaRERERERERG5AXhmB0bJlS77//nu6deuGaZpMnDiRyMhIJkyYwJw5c6hVqxbt2rXzxqlFRESuCafTQXLyKRyO3JIu5ZKSkgyKsl63zeZPuXKVsFq9tnGZiIiIyGXx2ruRkSNHXtC2ZMkSb51ORETkmkpOPkVgYDAhITd51njyRVarBafTdVWvNU2TjIwzJCefomLFKsVcmYiIiMiV0dcpIiIiV8HhyPX58KKoDMMgJKQM6ekpJV2Kz/t8bxLztiSQlJZDRFgAzzWLpn39iJIuS0RE5IaiAENEROQq3cjhRZ7ScI1F9fneJGI37Cfb4R7pciIth9gN+wEUYoiIiBQjBRgiIiLXqR9+2MELLwxg8uRYWrdu62nv168nN9/8J/7f//sPN910E4ZhwTRNypQpy/jxLxEcHMLRo0eYP38uJ0+eJDAwkICAAJ599gVq1apdgld0fZq3JcETXuTJdriYtyVBAYaIiEgx8souJL5u1arlJV2CiIiUMuvW2WjZMpg6dUJp2TKYdeuK5zuEGjWi+fe/13vuHzjwK1lZWZ77r78+j7i4hbz55ttERkaxbt2nZGdnM3r0UHr2fJS3336XuXMX8PjjTzNnzivFUlNpk5SWc0XtIiIicnVKZYAxb97cki5BRERKkXXrbAwbFsCxYwaBgSbHjhkMGxZQLCFGnTp1SUo6QVpaGgDr1/+Ltm3bX/A8l8tFenoaQUFBbNu2mTvvvJuGDRt5Hr/llobExS0scj3Xyk8//UTfvn0B2LNnD82aNaNv37707duXf/3rX9e0loiwgCtqFxERkatTKqeQ/PLLLyVdgoiIlCKzZvljmuDv777v7w+5ue72mBhHkY/fvHlLNm/+koce6sjevXvo06cfSUknABg8+DkMw4JhGNSv34AHH4zh44+XUK1alOf1o0cPJT09nd9/P80bb8yncmXfnvawaNEiPvnkE4KCggD473//y+OPP84TTzxRIvU81yw63xoYAIE2C881iy6RekRERG5UpTLAyM3VkE4REbl2Dh+2EBho5mvz83O3F4c2bR5k9uwZVK1ajVtvvT3fY6+/Pg+bzS9fW0REBPv2/ddzf8aMOQD07/8YTqezWGrypurVqxMXF+fZsn337t0cPHiQjRs3UqNGDcaOHUtoaOg1qydvnQvtQiIiIuJdpXIKiYiIyLUUFeXCbs/fZre724tDtWqRZGVlsXLl0gKnj5zv/vtbsGPHd+zevcvTduTIYU6dOnld7DrSrl07bLb/fQfTqFEjRo4cyYcffkhUVBRvvfXWNa+pff0IPu3fhO+GNefT/k0UXoiIiHhBqRyBISIici0NH57LsGEB5Oa6R17Y7WAY7vbi0rp1G9av/xfVq9fg2LGjl3xucHAwr7zyGgsWxLFgwe84nQ6sVhsjR47lppuqFFtN10qbNm0oU6aM589Tp04t9DVWq0F4eLC3S/NJVqul1F57cVEfFp36sOjUh0Wj/iu6kujDUhlgmKZZ+JNERESKSd46F7Nm+XP4sIWoKBfDh+cWef2LO+64izvuuAuAbt160q1bTwDuuacp99zTFHC/uXA6LxzpUaVKVSZPnl6k8/uKJ598kgkTJtCoUSO++eYbGjRoUOhrnE6TlJTMa1Cd7wkPDy61115c1IdFpz4sOvVh0aj/is6bfVipUliB7aUywBAREbnWYmIcxbJgp1zopZdeYurUqfj5+VGxYsXLGoEhIiIi1x8FGCIiInLdiYyMZPny5QA0aNCApUuXlnBFIiIi4m1axFNEREREREREfJ4CDBERERERERHxeQowRLxs3TobLVsGU6dOKC1bBrNunWZuiYiIiIiIXCl9khLxonXrbAwbFoBpQmCgybFjBsOGBQBoMT8REREREZEroBEYIl40a5Y/pgn+/mAY7lvTdLeLSOljSUwgaNYMLIkJxXI8p9PJ0KED+etfH+Lzzz8DYNWqZQDk5OTw6adrL/tYkyaN4YcfdhRLXSIiIiLeoABDxIsOH7bg55e/zc/P3S4ipYslMYHguNewHj5EcNxrxRJi/P77aVJSUliz5l+0b98BgPfeeweAP/74/YoCDBERERFfpykkIl4UFeXi2DED/3MGXNjt7nYRKT3ywgszIACzcgRGagrBca+ROWgIrhrRV33cmTNf5siRw8yc+TI331yP1NRUzpxJZdasGTidDhISDrJ48dt069aTGTOmkJqaCsDgwSOoXbsOq1Yt57PP1lKhQkWSk5OL6WpFREREvENfA4t40fDhuRgG5Oa6p47k5rqnkgwfnlvSpYnINZIvvCgbDoBZNhwzIKDIIzGGDRtNdHRNKlSoCEC/fk9SpkxZhg8fzd/+9gTR0TV58sn+vP/+O9x5Z2Pi4hYycuQ4Zs2aTnp6OitWLGXhwneZMWMODoe9OC5XRERExGs0AkPEi/IW6pw1y5/Dhy1ERbkYPjxXCzA6wkoAACAASURBVHiKlCIBK5aC3Y5ZOSJfu1k2HOPoEQJWLCVr+Giv1vDbb7/yww872LhxAwBpaWkkJiZQs2Yt/M8OEatfv4FXaxAREREpKgUYIl4WE+MgJsbBqlXL6dq1R0mXIyLXWE73ngTHvYaRmuIZgQFgpKaAnx853XsW6/lM03Qf37Bgmu7pajVqRNO27S20bfsgycl/8Omna6latRoJCb+Rk5ONzebHL7/8TNu27Yu1FhEREZHipCkkItfImjUrS7oEESkBrhrRZA4agpGT4w4tcIcXRk5OkdfAKEh0dE2mTJlAuXLlsNsdvPXWG/ztb0/w5Zf/x8CB/Rk2bBC1atWmXLlyPPXUAAYMeILhw18gKCioWOsQERERKW6GmfdVjQ+y252kpGQW+3ErVy7DyZNniv24xSU8PNgr112a+GIftm59Pxs3bi3pMi6bL/bh9UZ9WHS+3IcnTiRy0001Lvv5eWthYLeDn59XwouCWK0WnM6iLRxc0LVWqhRWpGOWNG+9x7ge+PLP1fVCfVh06sOiUx8Wjfqv6LzZhxd7n6ERGCLXyPHjx6/o+atWLfdSJSJSEvJGYjijql+z8EJERETkRqIAQ8RHxcZOLukSRKSYuWpEkzV8tMILERERkaugAEPEx6xbZ6Nly2AOH95Jy5bBrFuntXZFRERERES89smoS5cuhIW5561ERkYyYMAARo8ejWEY1K1bl0mTJmGxKD+R0iM7O7vQ56xbZ+PppwNxOADKsmcPPP10IIsWZWvrVREfZJomhmGUdBle5cNLZYmIiEgp45UAIycnB4APPvjA0zZgwAAGDx5MkyZNmDhxIhs3bqRNmzbeOL2IT8rISC/0OYMGBZwNL/7H4XC3K8AQ8S02mz8ZGWcICSlzw4YYpmmSkXEGm82/pEsRERER8U6AsW/fPrKysnjiiSdwOBwMHTqUPXv20LhxYwCaN2/Otm3bFGBIqVLYt5ijRg0jPX1hgY+lp9+YH45ErmflylUiOfkU6ekpJV3KJRmGUaRRFDabP+XKVSrGikRERESujlcCjMDAQJ588km6d+9OQkICTz/9dL5htiEhIaSlpRV6HKvVIDw82Bsleu24xcFqtfh0fdcDX+3DS9W0bt0/gYIDjMJe6w2+2ofXE/Vh0fl6H1aoUKakSyhUcWyjKiIiIuILvBJg1KxZkxo1amAYBjVr1iQ8PJw9e/Z4Hs/IyKBMmcLf9Dmdptf2lfXlPX+1J3HR+WofXqoml+vS35Ce/9pVq5bTtWuPYqmrIL7ah9cT9WHRqQ+Lzlt9eLH92UVERES8xSuraK5cuZIZM2YAkJSURHp6Ovfddx/x8fEAbN68mbvuussbpy6UJTGB8WdvRXzNgw8WvM5FQe1r1qz0djkiIiIiIiI+wysBRrdu3UhLS6NXr14MGTKE2NhYxo0bR1xcHI888gh2u5127dp549SXZElMIDh2Cl2A4NgpCjHE57z/fjYPPuggbz1Aw3CHF++/X/gOJkW1atVyr59DRERERETkanllCom/vz+zZ8++oH3JkiXeON1lyQsvbDu+oy5g2/EdwbFTyBw7EVeN6BKrS+R8eWFF5cplSEo6c83Ou2bNSq9OSRERERERESkKr4zA8DXnhhfWk0nYwH17NsTQSAy5EWlEhYiIiIiI3EhKRYARtGgBfvHbsZ5MAouVXACLFevJJPzitxO0aEFJlyg3oJIOELRGhoiIiIiI3EhKRYBhHDuG5eRJwADb2VkzNhtgYDl5EuPYsZIsT25QChBERERERESKT6kIMKzHj4J/AFgMcDgIAHA43Pf9A9yPi1yhkh5hUdyOH1eQJyIiIiIivqtUBBgZEybjqlyZbIcVZ1YOVty32Q4rrsqVyZgwuaRLlOvQjTbCIiHhYLEe70YLeEREREREpGSVigDD0fR+3qs7mVy7gQMrJhYcWMm1G7xXdzKOpveXdIlyHSpsxML1NqIhOzvnko9faSBxowU8IiIiIiJSskpFgGFJTMC1cSsbaEsmwTixkkkwG2iLa+NW7UIiV+X48eNFevx6U1ggoREXIiIiIiLiTaUiwAhYsRSLK5e9NOATOnOCCD6hM3tpgMWVS8CKpSVdotzA1q2z0bJlMJBMy5bBrFtnK+mSgOIPHDTiQkREREREvKlUBBg53XvisvhTlhQOUYP3+RuHqEFZUnBZ/Mnp3rOkS5Qb1Lp1NgYNCmTfPgtQhn37LAwaFHjJEMNbgcf5gcWVBg7XYkqMRnGIiIhcvs/3JtHx7Xgaz95Mx7fj+XxvUkmXJCLiVaUiwHDViOZInyEEkU1ZUgAoSwpBZHOkzxBcNaJLtkC5YU2cGEB6OrhcACYuF6Snu9sLsm6djWHDAjh2zAAyOXbMYNiwgGIJMYo6QqK4F/ksiEZxiIiIXJ7P9yYRu2E/J9JyMIETaTnEbtivEENEbmilIsAAGDi7Gsf6DiHEkk0UhwmxZHOs7xAGzq5W0qXJdSo7O7vQ5xw9agBguG88t3nt55s1yx/TBH9/931/fzBNd3tJK2yRTxGRa+mnn36ib9++ACQmJtKrVy969+7NpEmTcLlTY5Eb2rwtCWQ78v9bz3a4mLcloWQKEhG5BkpNgAHuEOPh+IEk8C4Pxw9UeCFFkpNz+R/o3e+lLRT2nvrwYQt+fvnb/Pzc7SIi4rZo0SLGjx/v+f/w9OnTGTx4MB999BGmabJx48YSrlDE+5LSCn4fcrF2EZEbQan7VOSqEc20s7ci3mazFZxYXKw9KsqF3Z6/zW53t3uby+X0+jlERIpD9erViYuL89zfs2cPjRs3BqB58+Zs3769pEoTuWYiwgqejnqxdhGRG4FvbIcgcoPKzS04I7xY+/DhuQwbFkBubt7z3NNOhg/P9VaJHlc65HrVquV07dqjWGu4FguFisj1r127dhw5csRz3zRNjLNz9EJCQkhLSyv0GFarQXh4sNdq9GVWq6XUXntx8YU+HNGuHuP+uZts+/9+fwf6WRjRrl6J13Y5fKEPr3fqw6JR/xVdSfShAgwRHxIT4wDca14kJwdTtarJ8OG5nnZfsmbNynwBRnGED8ePHy/yMbzJG6GNiBSdxfK/UDgjI4MyZcoU+hqn0yQlJdObZfms8PDgUnvtxcUX+rB5jXDGtqnLvC0JJKXlEBEWwHPNomleI7zEa7scvtCH1zv1YdGo/4rOm31YqVJYge2lbgqJyLWUt2hnNAcZzxSiOZivvSAxMQ6+/DITKMeXX2ZeNLzwtdEKeeFD3jawmzatuOQ2sNfjlqnaJUXEN91yyy3Ex8cDsHnzZu66664Srkjk2mhfP4JP+zfhu2HN+bR/E9rXjyjpkkREvEoBhogXtWvnIJqDTGMcXVjLNMYRzUHatSv6iApfHK1w7jawFkvOJbeB9YUw4HoMUUTkQqNGjSIuLo5HHnkEu91Ou3btSrokERER8QIFGCJetGTqPhbfNJY/sxsDkz+zm8U3jWXJ1H0lXZpXnLsNrGH41jawcGFg4QshiohcncjISJYvd/9M16xZkyVLlrBs2TKmT5+O1Wot4epERETEGxRgiHhJdaeTkNgpNAvfyZ9uD+AMP/Gn2wNoFr6TkNgpWBITAJg82Z+oqFBOn04iKiqUyZP9sW3fyr8B2/atJXoNV+pqt4HNm3by++/7LzntpKgUWIiIiIiIXL8UYIh4yVOZmdh2/ogZFAyBge7GwEDMoGBsO38kcNECJk/2Z948f3JyAFzk5MDOt77F7P0kzYCwZ564rkKMq9kG9txpJ5B1yWknhSlsSoivrRsiIiIiIiKXTwGGiLecXajTMIDsbGrgvs1bwNMA/v5395SLvAX0m7OZJfSiTGYSFsBy8uQFIca1Gq1wNYYPz8Uw3Nu/mublbQNbnNNOChth4YvrhoiIiIiIyOVRgCHiJX8PCsbe6DZIScG6/xciAev+XyAlBXuj28h6egA5Of/bkeT+s+FFVZJwYuAADIuRL8QoztEK3hAT42D27ByqVjVxuQKoWtVk9uycS24De7XTTkREREREpHTRJwQRLzlktZLd7wmMM2ewpKdhBSzpaRhnzpDd7wlcNaIJCHCPNog2D7KC7lThOE4MTM4uQGe1ng0xkggZObREF8l0OOyFP4n/bQPbqlX3S24Dm+dqpp2IiIiIiEjpowBDxEuqO50Ez3oFS0oyGAYuAMPAkpLsbk9M4KmncqnJQaaY4yhPiucH0nruT6ZhYJgm1pTkEh2tYJqmV457NdNORERE5Mp9vjeJjm/H03j2Zjq+Hc/ne5NKuiQRkSuiAEPES8anp+P37Taw2TCDQ7ADZnAI2Gz4fbuNkMkTmfzYLyyrO4ZG7OIokZiAH05shtN9EJcLnE7M4BDSp073jFao7jzIeNccqjsPXvejFc6ddgJBlzXtRERERK7M53uTiN2wnxNpOZjAibQcYjfsV4ghItcVBRgiXnK3w45hAlYbWCzkgHu1TqsNwwRr/HaCY6dwm3UXf7ojkGO2o5jRNd1rfzqd7kkkTidmUDBpr8WR+9duDB+eSw3XQZ498wo1OOy+dR287kcr5E07qVCh7mVNOxEREZErM29LAtmO/F94ZDtczNuSUDIFiYhcBQUYIl7yUkgoZlAg2HPdIynAfWvPxQwKxNnoVvx2/gjBwZgB7m1WXVWq4oyuCbh/OM8NLwA6NvyVpbdPxxYayGFqYAsNZOnt0+nY8FfPefN2Kdm0aYXP7VLi6wrbhlVEROR6lZSWc0XtIiK+yKsBxu+//06LFi04cOAAiYmJ9OrVi969ezNp0iRcrut3yLvI5fhnYCBps+e6V9rMzSEIIDcH/P1Jmz0XZ+26gHvdh3O5ypXHGRHBGcgXXlgSEwiOe42oun48/EQIQUFxPPxECFF1/QiOew1LYkK+XUoslpzL3qXEkpjAeNPEkphQ7P1wPSlsG1YRkYvR2gLi6yLCAq6oXUTEF3ktwLDb7UycOJHAQPc3y9OnT2fw4MF89NFHmKbJxo0bvXXqi8r7ZhqS9c20XBO5f+1G+pgJYJ7dV8Q0SR8zgdy/diP76QE4Gt2GkZUJ2dnuF2RnY2Rl4mjajDvOvj5PwIqlYLdjlg3Pdw6zbDjY7QSsWOrZpaSO9SBjna9Sx3qw0F1K8oKRaPAEISIicvm0toBcD55rFo2fxcjX5mcxeK5ZdMkUJCJyFbwWYLzyyiv07NmTypUrA7Bnzx4aN24MQPPmzdm+fbu3Tl2gc7+ZhszL/mZa5GpYEhMYlpGBbftW/H7eh735XzgD2Jv/Bb+f92FJTMBVI5qMsRNx1m+AkZVJmGliZGXirN+AjLETSTjvmDnde4KfH0ZqSr52IzUF/PzI6d6Tw4ct1LYcZGDGK9QwDzEw4xVqWw5edJeSvPDCDAjgMGAGBFwQYij4ExG5NK0tINcLu8u85H0REV/nlQBj9erVlC9fnmbNmnnaTNPEMNypb0hICGlpad449UXNmuVPRoZBcrIBVCE52SAjw7jkN9MiVyMvFPiT00HYiMGQk4PjjruYCzjuuCtfSHBuiGGaeMILV43oC47rqhFN5qAhGDk5nhDDSE3ByMkhc9AQXDWiuSfiAM+lvUI2QRwxIskmiOfSXuGeiAMXHC8iM5PguNc4eDyId9dWwmQU766txMHjQQTHvQYHD7JunY1BgwLZt88ClGHfPguDBgVe9yGG1gkRkeKktQXkejB9wy9X1C6+QdPTRPLzyrv2VatWYRgG33zzDXv37mXUqFH88ccfnsczMjIoU6ZMocexWg3Cw4OLpab9+y3knrdRQ04O/PqrpdjOUVysVt+r6XpzLfrQMLjwHAcPYlkYB2VCqWiaWGxWAn7Zh1mxPACBgX4QWAkOH8b/01W4xk+A8FtgxnS+2PA5t8yYTpmaNT2Hu+D44bfAuLFYXp1JpMtJgOnENW6s+zUHDzKvxkz+71AQZwjHNLNIIZwyBsyrMZOXc3PyHa9N0nGO22rxWXxFyrqSac4O9p+5i8+2VqRbk0NEf/whL/1jIhkZea8wcbkMMjLgpZcCadDAmu94Fkv+n1ebzXrJv4OCHj//GFeqsHNaLAZffRXMiBEWTBMslhxOnAhhxIhAQkJcV1XzpehnuejUh0WnPvS+iLAAThQQVmhtAfElWY6CR1tcrF1KXt70tLwRXnnT0wDa148oydJESoxXAowPP/zQ8+e+ffvy0ksv8eqrrxIfH0+TJk3YvHkz99xzT6HHcTpNUlIyi6Umuz20wPbcXIrtHMUlPDzY52q63ni7Dy2JCYxxODjz0389oyXOnY5hBoawx2qliV+A+x/Zli2EA9nZdveoCdMgs2NXXHk1lotgVlAwT5SLgHPqLvAaykVgeWYQhz78kJRnBuE6+5qgxf+gaqUs7nmwEtu3m2Rn2wgNNbmnaShVg/+gxXeH8x3v/yKqEPCTH1Udidzp2kFZTlLFcYb/WO5ix0/+RC3sw+EpnP2g7741DPdGKocPQ716TlJSMlm3zsasWf6cOvULt98Ow4fnEhPjwOFwXvLvoKDHXa6i/cwXdk6Xy2TyZPf/W/z93ddjs5nk5sLkyVCt2pXXfCn6WS469WHReasPK1UKK/ZjXq+eaxad70MGQKDNorUFRKRILjU9TQGGlFbXbBvVUaNGERcXxyOPPILdbqddu3bX6tTAhTs9FNYucjGWxASCY6fQyeUiOHaKZ72I8xfZTDUs2JvcA1YbRnY2jbhwysfVctWIZnZISL5j5K2RcXPlP+jXz07Nmsvp18/OzZX/AD8/Nlapmu8YScHB/COnD/fYt1DReRwDCxWdx7nHvoV/5PSBsyNBjPzrfeW7n39tmSzP2jJfv3uE3gd+9ckFQQ8ftuDnl7/Nz4+LrhMCmnIiIpfWvn4EY9vW5aawAAzgprAAxratqw8Y4lOMK2yXkqfpaSIX8nqA8cEHH1C7dm1q1qzJkiVLWLZsGdOnT8dqtXr71PnYLvJ542LtIgXJCy9se/dgALa9ezwhxrmLbBopKdxrzwUTEsIakphgcIrOfLbSybqGI4oUXlxMYWtkJAXnH0IekZnJk/YF2LHicu+Rggsrdqw8aV8ABw9StaoL04TqroOMZxrVXe5dTapWdX8bcO6uJxPMOdSxHiTKcRDX9NeIyMq85ruaHD9+rNDnREW5sNvzt9nt7vaCXO3WtCJSurSvH8Gn/Zvw3bDmfNq/icIL8TkP33rTFbVLydPWtyIXumYjMEpa2bIFD7W4WLvI+c4NLwgO5gxAcLAnxADIHDSEEzv/4Mj7Wwhx1Cfx3a388K2dQf7z2U1dYp2jeGZGPa99+D03xKiUnVXgaI9162w8el8Sz27N4nZ7PKmU4yA1ySaQg9QklXI0tP+A5c04Ond2EM1BRvEK0SScvT1I584OgPy7nnCY0WnjmJAzntPpQZwKDCpwVxNvOn78eKHPGT48F8Nwz+wxTfetYbjbC5IX0uRNOfH3p9CtaUVERHzN6AdupuutN5G3k6rFgK633sToB24u2cLkop5rFk2gLf/HNU1Pk9Ku1AQYdrtBUFD+tqAgd7vI5QhatAC/nT9CcDBmQCCA+zY4GL+dPxK0aAFffmnjhx8s2O1g4MLhMHE6DY4aUUxjCCeCal7Wh19LYgLjz95eqbwQIykouMDw4o3Bx+iZOJMwzlCePwggh2wCSaQG2Zy9rrPP37/hMOOsM8ghkMNUJ4dAxllnsH/DYYB8u56kEcqfHHv4U+4uwsLcRzDLhl92iJG39ay3w46YGAezZ+dQtaqJyxVA1aoms2fnEBPjKPD5VzPlpLisWrXc6+cQEZHSY/QDNxM/tDnfD2tO/NDmCi98nKaniVyo1AQYUVEuAgNNIiJMLJYkIiJMAgPNiw4bFzlf3of689dN8dw/cwbX9Nc4ZVRme2ArUijLJlpzkso8nz6TaA4BhX/4zVsMNBquevSCq0Y0H9Wuk2+B0d4HfmXT5G95IesV7NYgvrK04ASVqc4hypIKQCDZBJPJT8YduDp34ZGEV3H6BRERkMLfeIeIgBScfkE8kvAqDf74nbnVZpBNEMlmOH/mv9hNK5lGCO3DthJ6dp6GWTYc7Hb3GiGFXHOU03lNRmzExDj48stMWrXqzpdfZl40vIArn3JSnNasWen1c4iIiIjv0vQ0kfxKTYBxpcPGRc6X/fQAHI1uw8jKhNRUqgOkpmJkZeJodBuUKUN2mp10WziplnJs5l5SjXBSCMdm5vIoq4BLf/g9dyeTw1AsUzA8gUjaGcYmPkeAkcsZSzgpRlk2WdtzkopU5xAVOUkwmeymIXsfnYRl89eEh+QS6kzhgdx1lCGdB3LXEepMITwkl74HDlC9Sg73tg8lLMxkF3/G6m8lOtpF2TAHNdPTAPc6HPj5udcIKeSaj1qt13zayaWsWrVc/+8QEREREfERpSbAiIlx0KuXncxMA9OMIDPToFcv+yW/eRU5l6tGNBljJ+KqHo316BHCAOvRI7iqu9uznh5AYJgfoY4Uz2v8/SGcFByGP0voeskPv9XPjj4wAwI8O5lcyRSMgpwbDpTNtWP1M6hv30VZVzIAWYHhbLS0J4VwypHMf42G/Nx3EgNnV8PV51HuqnGS9vZPcZhW0gnBYVppb/+Uu2qc5IPatfPtepIT9AG1Hm1MuH8GOBwcDA0rdNeVfFvPFtM1F6c1a1Ze8ZST4nQ5i5KKiIiIiJQWpSbAWLfOxscf+/GngN8Yz0j+FPAbH3/sp50E5Iq5QkIwK1TADpgVKuAKCXG314jGMmYIQWQRYneHGGXNFMJs2bwbMYIE/nTJD7/ds7PzbcOa53KmYBQkIjMzXzhwMCyMclUCsJhO7srZRlkzFacTrDbwu7U+CSTRbs3fGDi7mvsAhw9TNXUvwSG4n4QFrDaCQ6Bq6l6AC3Y9wQBn/QY46jcgyOkodMvY87eeLeo1FyY7O/uqXnclU06K0+UsSioiIiIiUlqUmgBj1ix/ohwHGWp/hZocYaj9FaIcB7WTgFw2z2iBihXJbd2Gn4Hc1m0wK1b0jBZo8VgkodOGUCEkiyhOUCEki7Kxg/nnzgig3CU//K4IDPzfNqypKTQHz58vNQXjYlofPwZ2O7+cLM977/mx60gfPk+7n/AKFsJsWfzZtZeqwcm0u/0ElWoF8zMQuHqFZ9SDdeoUMAys9WpRqYKTAA5TqYITa71aYBj0PXAg364n1ZxOjJwcMsZOJHPsxAIXET1fQVvPGilXf80Xs26djZYtg0lPP0TLlsEKLkVERERErkOlJsCwJCYyJNe9W8JhqpFNEENyX8GSmFjSpcl14tzRAmbZcLZYLJ4/nztaoMVjkbTeMIiTQWtovWEQLR6LvKzjH7Ja3WHA6dP4bfw//gT4bfw/jNOnCw0CCrKxSlUOHQ/gm8/TSUszMAwHxzLLsyW1ERUquDAq/0L3FsepUtWFWbHiBWtuOCdMBJsNcnJwRUaSDbgiIyEnB0yTE0GBWBITcNWIJvvh7kS5nGQ/3B1XjegLFhG9mLwAxHL6NH5bv6asaeK39WssV3nNBVm3zsawYQEcO2YAmRw7ZjBsWIBCDBERERGR60ypCDAsiQmM95tBpiuIMxb3UPUzlnAyXUGM95tR4vPs5fpw7miBcxU0WsBVI5rZISFX9QHckpGB5fff8Qcsv/+OJSPjwudcxpajScHBvHB0NIFkUc5IwTCgnJGC3fDnxYD5nA4MxATMihULXH+CqCjSXn0dIzcXcnJIBMjJIfNkBptPN+DEsdZsbBvH93O+JXD1Cg5brPlGcFzyGs/uipL3XM/GLib57xeDWbP8MU33eiTgvr2crWzPd37NIiIiIiJybZWKACNgxVJub5DNGUs4Tqe7zel0hxi3N8gu9nn2cmM6d7pEXohR2CKVV6K600lI7BQshxJwVYskDXBVi8RyKMHdfvaD85VsOfptUm3mhY0ikCwizSMEksW8sFH884+/kO7nB4GBF11/wvLhEhxN7/eEGFWAzJMZbEtuwM+5tThiuYnc9Fxqz3yBIwfsl72DSF79EVmZBMdOISR2CgfTK7P05AP87rqXpScf4GB65WJbxPPwYQt+fvnbCtvK9pI1+8DioiIiIiIipVGpCDByuvckspaNjs1OExZmYmIjLMykY7PTRNayFds8e7nxnRtiRJpmgeFF3noLv/++/4rWW3gqMxPbzh8xg4Ixy5YlETDLlsUMCsa280cCFy244i1Ho6JcHHDV5M2QUSQa1XkzZBQHXDWJinKxsUrVS44ocfV5FMATYpwG/pPVgERLLTL8wilHCn82d5HlCuDMtv8SkNWXd9dW4uDxIPeH/czMC+qxJCZwesQbrPwslO+O92Pf54dJ2fQTm7+2ciyzHJtpwrHMcny6pSJHfnMUS7gYFeUiPR3CTicwnkWEnU4gPR3uiThwWSMqzu3zU4FBPrNDioiIiIhIaVMqAoy8D501q2TxWJdTWC2v8liXU9SsklVs8+yl9Mj795RoGAWGF/9bbyHrytZbMM7eGOc1n71vOXPmirccHT48F8OAX501ibWO4FdnTc82rknBwZccUULNmp7jOJrezxfAkeyKpNvc525o/hdcTlIoi4GTRuwiLc3whA+tz9sCNC+82LQ9hGOZ5TAMB/GuxpxK9ed++5eUN9xbu1qtUMaVwv/bE1gs4eJf/uIgIjOBYc5XiMZ9e2fmFib4zyh0RMX5O7mAd7d5XbVqebEeT0REpLT7fG8SHd+Op/HszXR8O57P9yaVdEkiUgSlIsCAy/vmXORyuWpEE2u1XfDv59z1FgzjytZb+HtQMPZGt0FmJkaOe7tPIycbMjOxN7oNs0yZK95yNCbGwezZOVStauJyBVywjavr/7N35/FR1Pf/wF8zu5tNNqdHiARCEk45PKqWQwQFFMRIRSHcUautVlSOJhhELgW5A1UsVfz1EJDDYK3ViEUh34JIaUuLFhQRJCEQWERJyLnn/P5Ydskme2aPlK2yNwAAIABJREFUmc2+no+Hj5jJ7sx7Pxk2M+/9fN7vzCyU9JmFD7db0BGT8eF2C0r6zHL572ITgNhEDRLMtmTHYaEXTFYVklENCSp8iV5OyYdd7dOdnq8t3oojhyy4JKZApbKNT63mKuzCMKglI242/ROA7fk6sQGLTbN9/vdZUqLGlIF6PHXhF5gyUO+UMPp2ZwVeUC+HFgZk4ySuwQ94Q/gVvj9twkmz2WMywt7JJVxtXt97b3tQ90dERBTNdnytx5Kd3+JcjQESgHM1BizZ+S2TGEQRLGoSGIDnT86JgiGQegunVCrUz5kPc8/eQH09kgCgvh7mnr1RP2c+Gn75K5+LiDaVk2NGaWk9hg7NbdHGtaREjSeX9cASSyHK0B5LLIV4clkPlzNGygCIz89EHBoQb6rCRaTgS9wALQz4WnMjqpDslHzQ63ROzzfkTkBVXQxS0Cx+AAdxCypUWcjAGcSiAWtiCmHNzPQ6ZvbX8MqMSkwoX4EsnMSE8hV4ZUYlSkrUEMvLML5sJeJEA25R/w/tUIkhwv8BALJqDkOsvuQ0o6L5shdvy2z8nSHCGRZERESB8WdGxbq9ZWg0W522NZqtWLe3LMRRElGoRFUCo6REjTsf7YUXrT/gzkd7sY0itcqLL8YgIyMBJlMjMjIS8OKLV2ZXZGRYYTI5P95ksm33hTUzCyUDXsLOypsg4UbsrLwJJQNecrQmDXYRUfuMkXNx2ViMmTgXl+1xxsidj3ZEwuKZuCa+AR2t52ARtZgZ+zqsao3X5IM1MwvbsmYhxtqAJKst/iRrFRLUjVggvoyXtC+jDBlYrSlEhTobBQVGn17DliVnMK1hOUwqW4tkkyoO0xqWY8uSM9AWb0V67A/oaf4fzFAjHg2QJAEpqEKiuh69LLZkjn1GRfNlL96W2fg75pxhQURE1Hr+zqjQ1xj82k5Eyhc1CQzn2gT1/tUmILrsxRdjsG5dDAwGALDCYADWrYtxJDHsNSeMRtvSEaMRjpoTvrDPiHgBi/EXDMcLWOw0I6JpEqODxRLwUihfZ4yoP/8Mn17+euejHTFs57MQu+zHVctm4N+6QVitKfQp+TBxTge8GlcIjaUBHaynobE04LX453DvUx1gzsjCYuEFmDOynJa5eGKfYWEUnVskG8U4jC9bCUuXruiXcBiiZEGDFAs9UmGGGmrJjA4x51Eh2l6nfUZF82UvgPOYpzY2cPkZkYKNHj0aeXl5yMvLw/PPPy93OEQUZP7OqEhL1Pq1nYiUL2oSGE1rEwD+1SYgsvt//892Hl2+74Uo2s6j//f/bOdR05oTQFyLmhPe+DIjwn5DXaFSBXwj7cuMEfXnnyHx6SfQH0Di009A/flnsGZmYXOXrrjz0Y4oKjL4nHzIyTFj+m/SsTXzOZSjM7ZmPofpv0nHggVGlJbW45prurVY5uKJtngrUuKNqIJzjYoqpCAl3ojYDX9E3G3Xo0MnEYmaRjRChyptGhISJGhSk5FhtTrNqGi+7MXOPub6OF2bT15wmQtFKoMts4yNGzdi48aNWLp0qcwREVGw+TujYuqgLMSqnW93YtUipg7KCnZoRBQmUZPACKQ2AZGdweC6S4ihyd9Ne80Jf2/GAd/PU2tmFori4wO+kW46YwRoOWPEnrwQz5+HAEA8f96RxLDz9/Xm5JixaV8a9t9zEJv2pfk1Ps0Zcieg980qJFmrYLHYtlkstqUpvW9WoX7W85CuuhrxA3qiV3cjkrEPXXsIEO4aCKg1+EEQfZ5RYU/atOXkBcBlLhS5jh49ioaGBjz22GN4+OGHcejQIblDIqIg83dGxcieaZgzvBuuS9RCAHBdohZzhnfDyJ5pIYySiEIpatZPZGRYUVkpOGZgAP7VJiACAK22ZRJDkmzbgyHc56k9ebBqVQwuXtQhPV1CQYHRtn3PPxzJC6jVMJqMiFWrHUmM3u3bhyQmf1gzs3DtyukYOusV/PNLCd816pCuu4i+N9bj2pXTYc7MQn2HjtCtXQNzr16o+vIQzL16ATFa1Kz8DY5OHItBbXxGBVG0iI2NxeOPP47c3FyUlZXhl7/8JT7++GOo1a4vdVQqASkprmddtXUqlRi1rz1YOIaBa80YzhrRAy+8fxiNpivXRbEaEbNG9HC7r4kDsjFxQLbLn4XCX7+oRNEnx3C2uhHtk2ORf093/OymlktUg4HnYWA4foGTYwyjJoFRUGBEfr7W7SfNRL74xS+MWLcuBtbLfzetVtt59ItfBOc8kuM8zckxIyfHjLS0q1FaWu3YrsqfCejPAZoYwH4DcPmrqD+HX12qdrW7sLMnMcauXYM/b12Ph+6f5DSjwr78Q7d2DU4C6B+jdfy8KD4ej19+nFhehkknjkMsL5MtoXG2WRFRIvJddnY2MjMzIQgCsrOzkZKSgu+//x7t3SRbLRYJVVX1Ln/W1qWk6KL2tQcLxzBwrRnDwZkpmHNPN6zbWwZ9jQFpiVpMHZSFwZkpivh92IuM2ut0VFY34oW/HEZdvSEksz54HgaG4xe4UI5hamqiy+1Rs37CuTaBzu/aBEQAsGCBEVOnGi/PuBCg1QJTpxqxYEFwEgzKOk8FCG5/AtvUE4XwVhfE/vMywOXPxfIyWxvVhnro1q6BWF4WpsidnT17NuTHYI0Laqu2b9+OZcuWAQD0ej1qa2uRmpoqc1REFGwje6bhgyf64Z/5g/HBE/0UtRyEbVuJQs/nBIZer0dlZWVYLrBDxb5WX6NJ87s2AZHdggVGVFTUQqOJQ0VFbdCSF3ZKOU8tRathSWsPWMyA+XIMZjNgMcOS1h6vX99Tlrjc8VYXxJqZhcWC4DZ5IWm1+D42DpJWK2sSIxC+JCdY44KUorKy0u1/rTF27FjU1NRg4sSJmDlzJpYsWeJ2+QgRUSiwbStR6Hn8y378+HG89NJL2LBhAx555BEkJydDr9dj0aJFGDRoULhiJGoT4uMT5A7BP4MHo+a3byDx6Schfq9HDABYzLCmpqHmt2/gyLpX5Y4wYJ0sFkfyQkq2dTKRklOA6irbjIz6yJpW+N572zFmzDi5wyDyycyZMwEAVVVVqKurQ7du3XD8+HFce+21eO+99/zeX0xMDIqKioIdJhGRz9IStTjnIlnBtq1EweNxBsaqVaswa9YsAEBqaiq2bduGt956C+vXrw9LcERtycCBd3j8ubt12nIy334Han77BqypaZAAR/LCfLvn1xIpchsbAZPJkbywk5JTAJMJw1iTgktOKGS2bduGbdu2oWvXrvj444/xxz/+EX/729+Qlqac6eBESrfjaz1GrT+AvkV7MGr9Aez4Wi93SFGNbVuJQs9jAqOhoQE33HADACAx0VZEIzMzE2Yzl14QBdvUqdMAACUlagwZooPJpMeQITqUlMg7BdqexPgH0KaSFwBQHBsLaDQQqquctgvVVYBGg13tQ1M1PJJwyQmF2rlz55CQYJuhptPpcP78eZkjIooM9oKR52oMkACcqzFgyc5vmcSQEdu2EoWexwSGwXBlCtS6desc/881pRTNQpVgGDNmHEpK1Hj22VgcPSoCSMLRoyKefTbW5THCOWPDfPsduPvy17bk1OWin4LB4EhiCNVVEAwG1D87E3odW2v5izM2yF933HEHpkyZgmXLlmHSpEl44IEH5A6JKCKwYKQyKbnIKFFb4PHOq127dvjyyy9x4403OrZ9+eWXrOpNUaukRI38fO3lBhz1qKxMQn6+bV1jMIptzp+vRW2trXUqIMFqFVBba9vefP/tOTsgKJq2WU1tbHAkL+RqpRrpWIeD/DVz5kx8++23+PbbbzF69Ghcf/31cofUKju+1rdo7cgbFwolFowkomjkMYExa9YsTJ06Ff3790dmZiYqKiqwf/9+vP766+GKLySsVovcIVCEWrUqBpIExMTYvo+JAYxG2/ZgJDDOnLE1LhUEW5dS+1f7dgoNexJDv28vkxdEYVJcXIzc3FwUFRVBsGVtcfToUXz00Uf49a9/LXN0/rFP5bd/Gm6fyg+ASQwKGRaMJKJo5HEJSUZGBoqLi/GTn/wE9fX16NOnD7Zu3Yr0dM+f/FosFjz//POYMGECJk+ejFOnTqG8vBwTJ07EpEmTsGDBAlitVo/7CCU5j02RraJChEbjvE2jsW335sEHx/p0DEHw/L19Ccvu3cWKqJGhFGJ5GfLr6lrd/tSamYXNXboyeUEUJtdddx0AoHPnzsjOznb6L9JwKj/JgQUjiSgaebzrqq+vx/bt29HY2Ihf/OIXGDVqFHQ+rAkvLS0FAGzduhXTpk3D0qVLsXTpUsyYMQObN2+GJEnYtWtXcF4BURhlZFhhMjlvM5ls273xZVp9erptP7YlKle+2rfbl7BUVgoQRQMqKwXk52tdJjF8TZjYiaLrt4Phw+PQrl0CACvatUvA8OFxfu03HMTyMujWrkHG5baorU1iKIU9SfXDD98ySUVtlr0d+4gRIzBgwADccccdqKysRN++fWWOzH+cyk9yYMFIIopGHhMYs2fPxrlz53Do0CH85je/8Xmnd999NxYtWgQAqKysxLXXXosjR444LkoGDx6Mzz//PICwieRRUGCEINiWjQC2r4Jg295ca4psLlpkhE4nwZZLECCKgE4nYdEi2/6bLmERBNtXSbJtb87fOgSiqGqxbfjwOBw65Lz90CGVopIY9uSFpNXijEoFSauN6CSGPUmlrijDXOllqCvK3CapWuMsW8OSwhQUFODw4cNYuXIlNBoN5s+fL3dIfnM3ZZ9T+SnUvjhTjfO1ti4k52sN+OJMtcfHs+0qEUU6j1fEFy9exKuvvgqr1YrHHnvMvx2r1SgsLMQnn3yCV199FaWlpY41rvHx8aipqfG6D5VKQEpKaLoAhGq/waBSiYqOLxKEagwnTwbi4yUsXizi4kUdMjIEzJ1rxejRMQCckwgZGRl+x3Bl/wK+/PISevdOxty5kmP/p0+LiIu7sqxEFAVotcDp097/rajVKqfHNP9eEJz/XahUIg4dcr2vQ4dUuO8+5+eLouBx/97icbUPr06ehPjGWiApAUhJgSAA2rRUoKoKMW+shXXWc0Cz6eg+x3zyJKacPIGUi3rHPry9puaan4feni+KAtasiUWm9SRmmFbAjEv4tWkFfiMWYs2abEye7Hmmjy/x6fXn/Pq9+Pua/X28N3w/DJzSx/DSpUsYNmwYNmzYgBUrVmDv3r1yh+S3qYOynGpgAJzKT6G37NNjePeLc47vrRIc38++u3uLx7NWCxG1BR4TGPaEgyiKraobsXz5chQUFGDcuHFOLVnr6uqQlJTk9fkWi4Sqqnq/j+uLUO03GFJSdIqOLxKEcgzvusv2X4cOafj00wsAgKqqlo8zmy2tisHT/jt21KGyUnAUEbVaJRiNQMeO3v+tNI+n+fdardbpe9sNj/tJWs2fb7VKHvfv7fmu9uFN3O//CFVdA6wp1wCNJkgS0NhoAmLjIf5wEYfzC5D1h41Oz3EVc0mJGqtWxeCbb7biJz8BFj5yDDmHVyK1rg7ml5c4Cnv6+zttfh56e77VKkH67iSmm5dBIxnREaegt3bD9MZlKPpuNqqqPHeA8iU+b2Ps7TzxprXnvTt8PwxcqMYwNTUxKPsxmUz4wx/+gN69e+P48eOoq6sLyn7DyX7zxy4kFE5NkxfNt7tKYHiq1cJzVT7sYETkH49LSCRJgslkgtFodPp/o7HldPmm/vKXv+CNN94AAMTFxUEQBPTp0wcHDhwAAOzZswe33XZbkF4CkTxiY8M/NbjpEhZJ8ryExV9ZWZFXOM+QOwHQaCBUO2eQhOoqQKPB2qqLjm1ieRnmSlKLpSXN64qoK8pQO3cNTp6Nw/excWFdktLJYsFczTKoLEb0svwPKahGL8v/oLIYMVezLGKXxRB5UlhYiB9++AFPPfUUDhw4gIULF8odUquM7JmGD57oh3/mD8YHT/TjDQgpDmu1KI99Vsy5GtsyIPusGC7tIXLPYwLjzJkzuPfeezFy5Ein/x85cqTHnQ4fPhxfffUVJk+ejMcffxxz5szB/PnzsXbtWowfPx4mkwkjRowI6gshCjc5bvhzcswoKjIgPV2C1apFerqEoiJDUFq4tm/fsrvQzTe7bjnsbnu42dufCgaDI4khVFdBMBhsbVEvFx2218nIAlokI5rWFclGOX5tWo4GxOH/Dl0DAJCSUxxJjLT60M4EyG1sxE+7fI/elv/BaFXjEpJgtKrR2/I//LTL99AWbw3p8YnkcMstt+COO+7Axx9/jFtvvRU9evSQOySiNom1WpSHHYyI/OdxCUm/fv1atVOdTodXXnmlxfZNmza1an/B1PRTWLZLpEC4uuFvyt8uIL7KyTEjJ8eMKVPGYdOmd0JyDLudOxtaFPK8+WYLdu5swJQpnp8bqtffnD2JoVu7Bh0sFkfywv7vu2mRzwrAkYyof3YmAFsL3NhYW7uXiZZ3oBZNqFW3h7kaSLw8Q15KToFw5jSGhbgA5j6NBgXVXyGpgxbf/ZAA1FuAWA06XXMRydVfoeb2J0J6fCI5rF69GufOncOJEyeg0Wiwfv16rF69Wu6wiBQvRiXAaJFcbneFtVqUh7NiiPzncQbGkSNHcPDgQaSnpyMnJwc5OTm47777cN9994UrvqDy9CksUbD52wUk3HxNMOzc2YDz52sBiDh/vhY7dza4fFzzrivhfP32JEaFSuWUvEirr3ckLwBg8OXH25MYnSwWp9a4W1TjYBY0SDBXITn5ykWhfUnKLi9Jq0ANNJlgvr4nJFGNGGsjACDG2ghJVMN8fU9oPv8spMcnksPBgwexYsUK6HQ6PPjggzh9+rTcIRFFhFi168t4d9vZdlV5OCuGyH8eExh//etf8dprr8FgMGD9+vX473//i06dOjl6t0cSd5/CMolBShXqGhvBTjB4m5Hi2z78bz0L2OpY3PloL8xprMSdj/ZytBwddrYS9uyE5sA/kHL5KwDAZEJuY6NTXZGTyMRqTSHi0IC7bv4BgOslKaFSHBuL8ppr8bezN8JqNCMZVbAazfjb2RtRXnOtreYHURtjsVhgMBggCAIsFgtE0eOlCRFdVmNwvZzT3XZAmbVaorm169RBWS0STpwVQ+SZ16uE7t27o6CgABs2bED//v1RVFSEceOU/clyc02TF1JyCgDnde1MYpASabWxQd1fuJZ0BKI1SZCmRTiBBlRWCsjP16KkRG2bMdHYCM3evwNqFaoBQK2yfd/YiOLY2BZ1RcwZWUhYPBPZ7RuQ2tjQYklKKJ1SqTDtzGwYEYOjmhtQhWQc1dwAI2Iw7cxsLnujVtmyZYvcIXj08MMP46GHHsK3336L3NxcTJo0Se6QiCJCW/j0fsfXeiz6+JhTEctFHx+LmiQGZ8UQ+c9jDQy72tpafPLJJ/jwww/R0NCAn/3sZ6GOK6i0xVsBkwlSO+c3A/u6dm3xVjQUzJYpOopUkZAQaCrQGRf2tspK07QIpyDYvhqNtu23XAUIAGpqBFSUqQAMxFdfmZBxjYCmcyla1hXpiPrymdDv2xu25IXdP/Rd8GNiIZ6tX46T6AS1GIN1ukIc03cGUBu2OKjt2LZtK0aOfEDuMNx6++23sWXLFpSVlaFjx464+uqr5Q6JKCK0hZoWRbtPwGR1ruNhskoo2n0iam7iR/ZMi5rXShQMHhMYO3bsQElJCSorKzF8+HC8+OKL6NixY7hiCxpD7gTo1q6BUF3lmIEBXFnXzmnZ1BpKr3ERLZoW4bTTaGzbZzVWogKZ2PX9MPQz70MS6mA1avHO98Mw7Psq5DY2ut2vNTMLm7t0xX1hSl6I5WXIr6tDaccT+NeFzngtvhAjG97AjvgnccKSjYwMq/edEEUgQRDw/PPPIzs727F85Ne//rXMUREpn/2md93eMuhrDEhL1GLqoKyIuhmubnTdRc3ddiIijwmMmTNnonPnzrj++utx7NgxrFmzxvGzoqKikAcXLE27FAgVpzAIgFhxCtBqw/7pKpFSRdqMEruMDCsqKwXExFzZZjLZtu+6Kh1xR2IhQcC/tQPRpeHfOKG9DZJFwLEvjUiWrE4dic6GsMuIWF6GSSeOu+yAZF/mlmGx4NUOyzDh/PM4jmwsEn6NFEs7CAJQUGAMWWxEchozZozcIRBFLH56T0TRxmMCY8OGDeGKI+SsmVlofCgXibNmoCMAzX/+jZqVv2HyghSrtQUtW0sJM0pak0QpKDAiP18LoxGQJNvyEfsN/5YtOiw2zUa+uAwGxGEPBiAdZrSDHnX1ApJEydFS1ZqZhbNnz4bgVV1JUKQ11Dsdr+nPJK0WZ1QqPNhNg61YimlnZuOTqlSkp0soKDAiJ4efRlHb9OCDD8odAlGbteNrvaJnaCRpVbjkouhoklbl4tFERF4SGH379g1XHCEnlpch9s/FMN16Gyq/PYaMW29D7J+LUd+hI5MYpEhTp06TOwSPmicbgjGDozVJFPuN/apVMaiqinO64d+yBbBmZmJNRSF+bVqODFzCVVbAKgkwJKXibIPKUcy3/tmZAcfvStMExfexcS2O56rAcEa3Kvyl0xLcceF9fFxaFpK4iIiobdvxtR4v7fgG5surLM/VGPDSjm8AwG0SI9wJj4JhXZ1iBAC1YNtORORKVPQqa3oDYe3YCXtFEdaOndiFhBTN28283Es+msfnb/IhmPHn5JhRWlqPa67phtLSeqfZCgUFRlSos7FaU4gqJMJqFfC90A43DEoE4NyRqJPFfeu5Vjl50mMHpNg3X7cVGG5Sm8f+GHub13BqusyFiIgi26pdx50SAwBglmzbXdnxtR5Ldn7r1BFkyc5vQ9oRZGTPNMwf2cOpC8f8kT0UNUvEm2huA0skh6hIYDi6kLi5SdAWb5UpMqLWU8KSj0CEK357m1RzRhaqkAoxPhYDRiagW7crRTF9TRj4m3QR397k8b1HAACNxlZQuAl7geHi2OC20vUYa7NlLkxiEBFFNldLMzxtX7e3zKmjCQA0mq1Yt7cs2KE5GdkzDR880Q//zB+MD57oF3HJC29JHyY4iIIrKhIYhtwJHm8S2IWEqG2zz9DYIi7HyJ8J6N7uRwBAYmICAN8TBv4mXayTp3h872n45a9Q/+xMCAaD4zFCdRUEgwH1z87EKVV41gC7W+bCJAYRUfTQ1xj82k7ekz5yzGohauuiIoFh70Li7iaBNTCIosMpldrpvSAhIdFlwqCkRI0hQ3TYvbsYQ4boUFLisVyQe9nZXt977O9P4oULGGEwQLxwIazvS02TF66WuaTV14clDiIiCq7kWNd/u9xtT0vU+rU9XJQ2g6FpPOe8JH3kmtVC1JZFRQIDcE5idJQkJi+IFOjdd98J6PnuOrfYExIm03nc+WgvlPSZBcFgQGpjQ4v3gpISNfLztaisFCCKBlRWCsjP17Y6idH0vcfV8ewkABAufw0jb0vshoWwtSwREYVO/tAu0IiC0zaNKCB/aBeXj586KAuxaudbg1i1iKmDshzfhzuZoLQZDM3jccee9OGsFqLgi5oEBnDlRqJcEJi8IFKg997bHtDz27dPb7GtaUJCEBpQWSngyWU9UNJnFvRxuhbvBatWxUCSgJgYWzvWmBhbe9ZVq2JaHZf9vcfV8RwzIK69Fn+L0UK69tqQLd8Qy8uQX1fntG9vS+x2uRhTIiJSvpE90zDv3u5OBTLn3dvdbY2JkT3TMGd4N6fHzxnezfF4OZIJSpvB4CoeVwZ2vgqAcme1RBqlzcIhebVyXnTksmZmYYlKjaeZvCCKCq4SEkYjsPCt7ujQpSvua/ZeUFEhIjbW+XMVjca2PRDWzCxsbnY8d8s3UF3ld1eUph1EXCVn7cfKsFgcbVybLmHRrV0DuFjmon/huYBeNxERyWdkzzS/imJ6erynZEKoCm8qbQaDr8fd991FALZZLUt2fus0bs1ntZBn9sSZfQztiTPAfTtgatuiagYGEUWfigoRGo3zNk8JiYwMK0wm520mk217a7mrqWFfvnHs/NV46y0NGhqexVtvaXDs/NV+tVH11kGkaaLkjErVokinNTMLJX1m4cPtFpi/ux0fbregpM8szlIjIiIHOZIJSpvB4Otx7WPibVYLeae0WTgkPyYwiMgnV111tdwhtIqrhERtLWAwwGWRzoICIwTBNktDkmxfBcG2vTU81dQw5E7AqbNa7CupxYULAiRoceGCgH0ltTh1VutTG1WxvAwXZr2C7R8m4J9nH8H2DxNwYdYrjuSEtyKdYnkZSkrUeHJZDyyxFOKUmI4llkI8+mIPjL7pPAZ8ciumDNR7rQEStMKnRESkSL4mE/yd7u/p8b7U5QgnV/G40nRMlNgmNpKWZChtFg7Z2M+h7vM+Dvs5xAQGEfnk5ZeXyx1CqzRPSNTUAA0NAjQauCzSmZNjRlGRAenpEqxWLdLTJRQVGZCTY27V8T3V1LBmZuHnR2dDbW5EklQFQEKSVAW1uRE/PzrbaxtVe/Ji9+fxqKy/CoJgRmX9Vdj9ebwjieGtSKe2eKsjxnNx2ViqmYUyIRvt6srwyLkVyMR3mFC+Aq/MqHSblAh24VMiIlIeX4t8+lMnw9vjlTCDoenN/rq9Zcjp3c4RT3KsGmrnOqmKXyKitMKo3ihtFg7Jfw4xgUFEPhkzZpzcIbRK04QEEAeLRUB8PBAfL7kt0pmTY0ZpaT2GDs1FaWl9q5MXgPclLAfOd8FyFCIOjchABeLQiOUoxIHzrqvEN6Ut3oojhyy4JKZApbIlSFQq4JKYgiOHLNAWb/VapNOQO6FFjKm1ZSjEctRLsTgjdoRJFYdpDcuxZckZl3HYEyBdVScxx7ISXVUnAy58SkREyuJLMsHf6f6+PF7OGQyubtRKjpzH1EFZ+Gf+YHz69O2YP7JHRC0RUcKSDH9mgChtFg7Jfw7x4zEiavNycszIyTGjV69uMBr1bot0Zma6bsMaiIwMKyorBcQ0uZeollSzAAAgAElEQVRvXlPjJLKxQijEJGkDNgsP46SU7VN22ZA7AVVrXkOKqgo1uDLDIgVVqKqLgSF3gtcindbMLKcYs6RyzLS8gQbE4pKQAhENuCSmIFECxpethFj+TIvaGBUVIrprvsMzdcthlWrxTN1yrNUV4lhF50CGjsgvVqsVCxcuxDfffIOYmBgsXrwYmZmZcodF1KZ4Kwrq73R/pS8P8KVwqb+FUuUm95j7W5TTvm3d3jLoawxIS9Ri6qCsiBrztkbuc4gzMIgoqngq0umqDWugvNXU6NDBlkw5iWwsxjycRLbTdk+smVnYljULMdYGJFltyYkkaxVirA3YlnWlCKc9iSEYDOhgsTglL5rHONH8DmJgRBVSnJIuVUhBSrzRtiSlmf5pJzC1ZjkaEYfTQkc0Ig5Ta5ajf9qJ1g4bkd8+/fRTGI1GbNu2Dfn5+Vi2bJncIRFFHX+n+yt9eYDcN2qhIPeYt+bTeyXWEYlmcp9DnIFBRFGloMCI/Hyty4TCli3BP559+cmqVTH45htbTY2CAqNj+0svGfDss7FoaAAsFgGiCMTF2bbPmuV9/xPndMArMwoxrWE5Oli/BywJeDWuENPnpAO4svTFnsSoKN7mlLxoHuOmS1MwX/cqUo1VqBVSIEmAxWJLjPS+WWVbktKEWF6GVzu8gt3l8bgkpUCSGnBRSkESgFc7LINYPp3dTCgsDh48iEGDBgEAbr75Zhw+fNjj40+c+BaPP/7LcISmOGq1CLO59Z2ViGPoTnW9Eed/bIBVupKEFwQBFwQg4w0JMSoRHVJicbUuBmq1iOpLjS0fD+CCKLR4vK9+rDfiTFUjjBZrq57f1A+Vl2C0tPw9x6hEjN6b1Kp9BlNrzkNXvyNREBB3dRxGfxT6pZ+HKqpcbj8HYPRHKS5/Fir8d9w64TqH9u3b63J71CUwxPIyzLGYIZaX8aKaKAp5SiiEIoFhP2ZOjhlTpozDpk3vuIinEatWxeCrr2px/fUJjnh8SWDYnp+OLUuew4Djf8L+zEcxfU66y7od1swsFMXH43EX731XYpyF+15egQuzXsE/v5Rw0pCAdN1F9L2xHteubJmM0BZvRaf2BgwYmYbPP5dw4YIaiYkSBtyegE66H2Ep3oqGgtm+DxZRK9XW1iIhIcHxvUqlgtlshlrt/lJH7UM3gbZIEISofe3BwjF0rV1SLERRxOmL9TCYrVCrRJgtVpgv3+cYLVaU/VgPURSRmqht+XhRgEUCzFbJ8fjyHxsgiiKuTfB+Y3Sh1ojyJjdW/j6/uYyrdTh5oa7FjVrG1TpF/P5bcx42H3OtWkTHq3StGp/W0KpFGFwkDbRqMexjyn/HrSP3ORRVCQx7O8FMSYJu7ZoWn0ISUdtQUqK+nKAoxpAhcU4zHgDPCQU5NK3RUVrq/7IL2/PTMGXKQWzaVIimMy+aEsvLkF9X5zWBa83MwrUrp2Ps2jX4+6fv4s67R7h9vzTkToBu7Rp0b/cjuj2Sgj//uRgPPZRrKxJq0LSYsUEUKgkJCairq3N8b7VaPSYvunTphu3bPwxHaIqTkqJDVVW93GFENI6hb4a9tg+XDJYW21VaFT6Ze0+LMRy1/gDOuViekZioxfYn+nk93qj1B9AugOe7suNrvWLrL0Tiedi8BgZgK8opR/HTSBw/pZFjDKMm5WRPXkhaLU4LAiStFrq1ayCWl8kdGhEFkZwtPd99V/5kiDv298AMi8Wn9z77khN9nM5jsrdpfQ3BTZFQonC45ZZbsGfPHgDAoUOH0L17d5kjIiJXyQtP293VljhXY/CpY0Wgz3eF9Rf86xrijRJa41Jki4oZGE2TF1KybW2VlJwCVFdxJgZRG2Nv6RkTA9TX274ajeFp6fnee9sV2W626XvgGZXKkcD19t5nzczC5i5dcZ+X98emnU5SGxuYvCBZ3HPPPdi3bx8mTJgASZKwZMkSuUMiIj+lJWpdzsAA4Ghj6qljRaDPjxb+zCrxt2uILyKtcwspS1TMwNAWbwVMJkfywk5KTgFMJpdV9YkoMlVUiNBogE6Wk3jevBKdLCcdbVKjkbsEbrBnofk6Y4MoVERRxEsvvYStW7di27Zt6NKli9whEbV53j6ZF9w8z932qYOyEOulJoGnjhWBPj8a2BMS52oMTkkdd7MqWtM1hCiUQnJFbzKZMGvWLEyaNAljx47Frl27UF5ejokTJ2LSpElYsGABrNbwVXw15E4ANBrH9GY7oboK0HCNNlFbkpFhRfvGk3imbjkypVN4pm452jeeREZGdFaZDmcC1z5jg8kLIqK2z5cbYXcNwd1tb768wB13S0UCfX408Dch0RZbyVJkC0kC469//StSUlKwefNmvPnmm1i0aBGWLl2KGTNmYPPmzZAkCbt27QrFoV3iGm2i6PDgg2Ox8JFjmNG4HHWWOFSgI+oscZjRuBwLHzkWsuOWlKgxZIgOu3cXY8gQXVjqbfiKCVwiIgoFX26Er0vUunyuu+2Ac80Jd49LC+Hz2zp/ExLuxiqax5DkFZIExr333ovp06c7vlepVDhy5Aj69u0LABg8eDA+//zzUBzaLWtmFkr6zMKH2y1It07Eh9stKOkzi8kLojYk97a+yDm8En3v1EBKToYkqSElJ6PvnRrkHF6JThbXRcMCIWfRUF8wgUtERKHgy42wqyUdsWoRUwdl+XQMuZ/fFvmbkOAYktKE5Ao7Pj4egK0n+7Rp0zBjxgwsX74cgiA4fl5TU+N1PyqVgJQUXVBi+stfgKkrrkeGNBs5+B1KpKdQsSIb67KsGD06KIcIGpVKDNrrjlYcw8DJMYZqtSqgY4qvvQsIEnr0uwY9+gFbt27HhAkTAFwDVFRgnNHgtH/78f7yF2DxYhFffVWMu++Ox9y5tvcFX+JZs0aEIABara1oaGysAKMRWLMmFg8/DJfHcxu/6Pye17FjB7/Gw+3+U3oBL8yBuHIFOlot0EoWWF+Yg6TsbK/78Pd3EujvsDn+Ww6cIATvbym5p+RWi9R2KOk8c1cws+mNsD221sYs9/PbiqbnTVKsGmoBMDdZx+MpIcExJKUJ2UeEZ8+exdNPP41JkyZh1KhRWLlypeNndXV1SEpK8roPi0UKWl/ZF1/UwWKRUKnNwmLMRJr2OliMEl58EbjrLmX1/2VP4sBxDAMnxxiazZaAjimOGmMrWKn/HlJyCqxWKxobTbYZB5KAd2K0eKzJ/s1mC95+24j8fC0kSYIoGlBRocOvfiWgrs7gUzxlZQmIjZVgL+tjtUpQqYCyMgEWi9Xp+d72Z7U6v+e1a3edX+Phaf8ln3fAlr8/h36Ga3Hf3x/DxIEdkHNVy8c234e/v5NAf4fN8d9y65WUqLFlyRkMOH4T7u99EhPndEBOjjlo+09NTQzaviJdKKr0EzWntPNs6qAsp3gA1zfCgXackPv53igpqeRK8/OmutEMjSggKUZEjcHiU8zsGkJKEpIExoULF/DYY49h/vz5GDBgAACgV69eOHDgAPr164c9e/agf//+oTi0WxUVImJjnUsGRXNnAqK2qGk7T7hYLnHqow9bPMdT29Vnnhnr9ZgZGVZUVgqIadKl1WRCUIqGPvig9+P7oqREjWee0aKxsQt2YjFU3wnY94zt/TCYN7SkHCUlarwyoxLTGlYAqEVm+Qq8MqMQQDp/5yHgqRYAL/opWNydZwt3fIMFH30T9ptnfjKvvKSSK67OG5NVwjUxaux6ZmBYYlB6kociS0ju3l9//XVcunQJ69atQ15eHvLy8jBjxgysXbsW48ePh8lkwogRI0JxaLcyMqwwmZy3Besmg4iUo2nNh9TGBqdaD+3bt2/xeHvb1absyc0xY8Z5PV5BgRGCYEt6SJLtqyDYtgfKl+P7Yt68GNTXC5dnidhmi9TXC5g3L8bbUylCbVlyBtMalsOkisMZsSNMqjhMa1iOLUvOyB1am+RqGr2n7USt4a7mhFWCT+0wQ6FpwcwPnujn8qbUW6vVSBYJLUbl7iLib9tWIm9CMgNj7ty5mDt3bovtmzZtCsXhfFJQYJsmbrx8TxHMmwwiUhZ7EkO/b69Tocr27dNbPNY+g6Kr6iSeMr+JEssvcdyS7XNy0/5p9qpVMfjmGy3S0yUUFBgvb1dGgqCy0parFgRbksX+1b6d2haxvAzjy16DURWHGjEFQAMuiSlIlIDxZSshlj/D4q1BJgq2m0hX24mCxV3NiaaUNvPH0wyFiQNa1mGKNHInB3zhS62SUOIMNQq2qLl6zckxo6jIgPR0CYAO6ekSiooMnEpL1EZZM7OwuUtXrzdqBQVGZFpP4qlLy9HJegpPXVqOTOtJv5KbOTlmlJbWY+jQXJSW1ivyfUWSPH9PbYe2eCtS4o2oQorT9iqkICXeCG3xVpkia7tcJS88bSdqDVfdIFxR0s1zJMxQCEQktBiVu4tIJCR5KLJETQIDuHKTodGkKfYmg4jCa1Sf49j6k6VQJ8SiAllQJ8Ri60+WYlSf43KHFjQdOtjuouxJC/tX+3ZqWwy5E9D7ZhWSrFWwWGy/b4sFSLJWoffNKhhyJ8gdYptznZubFXfbiVpjZM80zBneDdclaiHA/QwfJd08t/WbV7mTA75oft5cl6jFnOHdwjb7IRKSPBRZoiqBQUTRrXlRzLT6eujWrkFGNw0eeiwe2dnv4KHH4pHRTQPd2jUQy8vkCTTIXnrJgIQEQBQBQIAoAgkJtu3U9lgzs3DtyukYensd0nUXIUlqpOsuYujtdbh25XQuHwmBSLiJobahac2JhSN7KP68a+s3r3InB3zlS62SUOH7IwVbyNqoKllsbNt40yQi/zQvijnsbCWQ0QlSO+c/5FJyCoQzp6Et3oqGgtnhDDEkbLPNGrFqVQy++qoW11+f0KROB7VF9iTG2LVrsHfXexg07B6nejAUXOzGQHKIhPPO11arkUwJLUbl7vLh6fiRcJ5SZInKBIZWGyt3CESkALvap2OcRgOhugpS8pV6AUJ1FaDRtKmp9jk5ZuTkmNGrVzeUlp6QOxwKA0cx2/2fMXkRBkq4iaHoo/TzjjevoSd3K1dfjq/085QiS1QmMIiIAECv06H+2ZnQrV0DVFcBsCUvmrZeDSdXbV6JAmHNzMLWbt1xL5MXRCSTSL95lXt2gzdyd/mQ+/gUfVgDg4ii1oMPjnV8Si0YDEhtbJAteQG4bvNKRERE8rDPLjhXY4CEK7MLdnytlzs0B7kLpcp9fIo+TGAQkSKI5WWYdOJ4WAtn2mtiOKbax+lCmrxoXkSUiIiIlCsS2sDKXShV7uNT9InKBAanaRMpi1heBt3aNUhrqJet+4c1Mwubu3QN6cyL5kVEiYiI/LHjaz1GrT+AvkV7MGr9AUXNBGiLWjO7INy/I1+6fIQyJnYZoXCLyhoYnKZNpBz25IWk1eL72DhIWi10a9ew6CAREVETchdrjEZpiVqcc5GsaDq7oGmNjEStCg0mK0xWCUB4fkfeCqWG+rxhoVYKt6hMYBCRMjRNXti7gEjJKUB1FZMYMuEyFyIiZWKxxPDz1ga2eXLgksHSYh/h+B15KpQajvMm0gu1UmSJyiUkRKQM2uKtgMnk1MIUuJzEMJlsP6ew4jIXIiJlYrHE8BvZMw1zhnfDdYlaCACuS9RizvBuTrMOmicHXJHzd8TzhtoazsAgItkYcidAt3YNhOoqpySGUF0FaDQw5E6QMbrw4+wHIiJyx5flDN4osSVoqGMKdP+eZhf4mgQQBKBv0R5ZxjwY5w2RknAGBhHJpmkLU6G6CoAteSFnK1M5cfYDERG5E2ixRCW2BN3xtR6LPj7mFNOij48FLaZQv2ZfkwBWCbKNOYtsUlvDBAYRyappEiO1sSFqkxdERESeeFvO4I0SW4IW7T7hKHhpZ7JKKNp9Iij7D/VrdpUcUAtAcqwaAgBRaPmccI95oOcNkdJwCQkRyc6exNDv28vkRQB8WYLCNtJERJErkGKJSqyFUN1o9mu7v0L9mr114OhbtCekx/cVi2xSW8IEBhEpgjUzC5u7dMV9TF60mi9LUNhGmogoOkVjLYRwvGZPyYFoHHOiUOMSEiIicouFRYmI2oZorIUg92uW+/hEbRFnYBARkVssLEpEFD6h7MjhbbmDHATYilu62h4Mcr9mV8cf2PkqrNtbhgUffaOI3wFRpGECg4goCMTyMkw6cRxieRlreBARkd/sHTPsRSftHSsABDWJoaSb5Yduug7vfnHO5fZgkfs1Nz1+OH7HRG0dl5AQkexKStQYMkSH3buLMWSIDiUlkZVbFcvLoFu7BmkN9dCtXQOxvEzukGTDJSdERK2jxC4hoTb77u4Yc9N1jm4dogCMuek6zL67u7yBhUg0/o6Jgi2y7hKIqM0pKVEjP18LSQJE0YDKSh3y823FrXJyglOFPJTsyQtJq8X3sXGQtFro1q5B/bMzgZRecocXdlxyQkTUOq6KPXra3lbMvrt7m01YNKfETjBEkYYzMIhIVqtWxUCSgJgYQBBsXyXJtl3pmiYvpOQUAICUnOJIYuDkSZkjJCKiSCG6Kfzgbntr7Phaj1HrD6Bv0R6MWn8AO77WB2/n5JW77iPsSkLkOyYwiEhWFRUiNBrnbRqNbbvSaYu3AiaTI3lhJyWnACYTxLc3yRQZERFFGqurapYetvvLXn/hXI0BEq7UX2ASI3zaalcSJsYonJR/h0BEbVpGhhUmk/M2k8m2XekMuRMAjQZCdZXTdqG6CtBoYJ08RabI3GONCmqLJEnCoEGDkJeXh7y8PBQVFckdEpHfrnPzKby77f5i/QX5jeyZhjnDu+G6RC0E2H63c4Z3i+gCnkyMUbixBgYRyaqgwIj8fC2MRtvSEaPRtpSkoMAod2heWTOzUP/sTNtykctJDKG6CoLBgPpnZyIpOxuoqpc5SmesUUFt0alTp9C7d2+8/vrrcodC1GpTB2U5dagAgvvpfLTW2FAaubuiBJunxFhbep2kHFE5A4OfQBIpR06OGUVFBqSnS7BatUhPl1BUZIiIAp7AlSSGYDAgtbHBkbxgK1Wi8Dly5Aj0ej3y8vLwy1/+Et99953cIRH5LdSfzvtSY4NLAchfLExK4RbSGRhffPEFVq1ahY0bN6K8vByzZ8+GIAjo1q0bFixYAFGUJ3/CTyCJlCUnx4ycHDOmTBmHTZvekTscv9mTGPp9e5m8IAqx4uJivPXWW07b5s+fjyeeeAIjR47Ev//9b8yaNQvvvvuux/2oVAJSUnShDFWxVCoxal97sIRqDCcOyMbEAdlB3y/gucZGSooOf/2iEks++RaNJtun6edqDFjyybeI12nxs5vSgx4Pz8PAKWEM2yfHorK60eV2uWPzRgnjF+nkGMOQJTDefPNN/PWvf0VcXBwAYOnSpZgxYwb69euH+fPnY9euXbjnnntCdXgiorDOtrJmZmFzl664j8kLopDKzc1Fbm6u07aGhgaoVCoAwG233Qa9Xg9JkiAI7ts3WCwSqhS2xCtcUlJ0UfvagyUSx/C6RK3L5SLXJWpRVVWPlX/7xpG8sGs0WbHyb99gcGZKi+cFKhLHUGmUMIa/GpjpcunTrwZmyh6bN0oYv0gXyjFMTU10uT1kUyA6deqEtWvXOr4/cuQI+vbtCwAYPHgwPv/881AdmogIAGdbEUWL1157zTEr4+jRo0hPT/eYvCCKRt46YHApALVGWyxMSsoWshkYI0aMwOnTpx3fN/0kJD4+HjU1NaE6NBEREUWRJ554ArNmzcLf//53qFQqLF26VO6QiBTHfkO5bm8Z9DUGpCVqMXVQlmN7mpsZGmlB6oJCbVdbK0xKyha2LiRN613U1dUhKSnJ63OidX0q12MFjmMYOFnWtKlVsv7eAj1+8+fzPAwcxzBwgtD2/5YmJydj/fr1codBpHiebjRD3QWFiCgYwpbA6NWrFw4cOIB+/fphz5496N+/v9fnROv6VK7HChzHMHByjKHZbJH19xbo8Zs/n+dh4DiGgZOk0Pwtdbc2lYhab8fXerczJELN2wwNIiIlCFsCo7CwEPPmzcPq1avRuXNnjBgxIlyHJiIiilrjx0+QOwQi8sGOr/VOMyDO1RiwZOe3ABDWJAYTFkSkZCFNYHTs2BHvvGNriZidnY1NmzaF8nBERETUzMSJEzmLhSgCrNtb5rR8AwAazVas21vGpAIR0WUh60JCRERERES+YRcQIiLvmMAgIrrswQfHyh0CERFFKXfdPtgFhIjoCiYwiIguGzNmnNwhEBFRlJo6KAuxaudLc3YBISJyFrYinkRERERE5Bq7gBAReccEBhERERGRArALCBGRZ1xCQkRERERERESKxwQGERERERERESkeExhEREREREREpHhMYBARERERERGR4jGBQURERERERESKxwQGERERERERESkeExhEpBgPPjhW7hCIiIiIiEihmMAgIsUYM2ac3CEQEREREZFCMYFBRERERERERIrHBAYRERERERERKZ5a7gCIiIiIIt2Or/VYt7cM+hoD0hK1mDooCyN7pskdFhERUZvCBAYRERFRAHZ8rceij4/BZJUAAOdqDFj08TEAYBKDiIgoiLiEhIiIiCgARbtPOJIXdiarhKLdJ2SKiIiIqG1iAoOIiIgoANWNZr+2ExERUeswgUFEREREREREiscEBhEREREREREpHhMYRERERERERKR4TGAQEQXJgw+OlTsEIiIiIqI2iwkMIqIgGTNmnNwhEJEMrkvU+rWdiIiIWocJDCIiIqIATB2UhVi18yVVrFrE1EFZ8gRERETURqnlDoCIiIgoko3smQYAWLe3DPoaA9IStZg6KMuxnYiIiIKDCQwiIiKiAI3smcaEBRERUYhxCQkRERERERERKV7YZmBYrVYsXLgQ33zzDWJiYrB48WJkZmaG6/BEREREREREFMHCNgPj008/hdFoxLZt25Cfn49ly5aF69BEREREREREFOHClsA4ePAgBg0aBAC4+eabcfjw4XAdmoiIiIiIiIgiXNiWkNTW1iIhIcHxvUqlgtlshlrtPgSNRoXU1MRwhKc40fq6g4ljGDiOYeA4hoHjGAaOY9hSNF9jADwngoFjGDiOYeA4hoHh+AUu3GMYthkYCQkJqKurc3xvtVo9Ji+IiIiIiIiIiOzClsC45ZZbsGfPHgDAoUOH0L1793AdmoiIiIiIiIginCBJkhSOA9m7kBw7dgySJGHJkiXo0qVLOA5NRERERERERBEubAkMIiIiIiIiIqLWCtsSEiIiIiIiIiKi1mICg4iIiIiIiIgUjwkMBXjjjTcwfvx4PPTQQyguLkZ5eTkmTpyISZMmYcGCBbBarXKHqGgmkwn5+fmYMGECJk2ahBMnTnAM/fDFF18gLy8PANyO2zvvvIOHHnoI48aNQ2lpqZzhKlLTMfz6668xadIk5OXl4fHHH8eFCxcAcAy9aTqGdh988AHGjx/v+J5j6FnTMfzhhx/w1FNPYfLkyZgwYQJOnToFgGMYrXid0Xq8xggMrzECx2uMwPEaI3CKusaQSFb/+Mc/pCeffFKyWCxSbW2t9Oqrr0pPPvmk9I9//EOSJEmaN2+etHPnTpmjVLZPPvlEmjZtmiRJkvTZZ59JzzzzDMfQR+vXr5fuv/9+KTc3V5IkyeW4nT9/Xrr//vslg8EgXbp0yfH/ZNN8DCdPnix99dVXkiRJ0pYtW6QlS5ZwDL1oPoaSJElfffWV9PDDDzu2cQw9az6GhYWFUklJiSRJkrR//36ptLSUYxileJ0RGF5jtB6vMQLHa4zA8RojcEq7xuAMDJl99tln6N69O55++mn86le/wl133YUjR46gb9++AIDBgwfj888/lzlKZcvOzobFYoHVakVtbS3UajXH0EedOnXC2rVrHd+7Grcvv/wSP/nJTxATE4PExER06tQJR48elStkxWk+hqtXr0bPnj0BABaLBVqtlmPoRfMxvHjxIlatWoU5c+Y4tnEMPWs+hv/5z3+g1+vx6KOP4oMPPkDfvn05hlGK1xmB4TVG6/EaI3C8xggcrzECp7RrDCYwZHbx4kUcPnwYr7zyCl588UUUFBRAkiQIggAAiI+PR01NjcxRKptOp8OZM2cwcuRIzJs3D3l5eRxDH40YMQJqtdrxvatxq62tRWJiouMx8fHxqK2tDXusStV8DNu1awfA9ua+adMmPProoxxDL5qOocViwQsvvIA5c+YgPj7e8RiOoWfNz8MzZ84gKSkJf/rTn9C+fXu8+eabHMMoxeuMwPAao/V4jRE4XmMEjtcYgVPaNYba+0MolFJSUtC5c2fExMSgc+fO0Gq1OHfunOPndXV1SEpKkjFC5fvTn/6EO+64A/n5+Th79iweeeQRmEwmx885hr4TxSs5Tfu4JSQkoK6uzml70zcoaumjjz7C7373O6xfvx5XX301x9APR44cQXl5ORYuXAiDwYDjx4/j5ZdfRv/+/TmGfkhJScHQoUMBAEOHDsWaNWvQp08fjmEU4nVGYHiNETy8xggOXmO0Hq8xgkPuawzOwJDZrbfeir1790KSJOj1ejQ0NGDAgAE4cOAAAGDPnj247bbbZI5S2ZKSkhz/QJKTk2E2m9GrVy+OYSu4Grcbb7wRBw8ehMFgQE1NDU6cOIHu3bvLHKlyvf/++9i0aRM2btyIjIwMAOAY+uHGG29ESUkJNm7ciNWrV6Nr16544YUXOIZ+uvXWW/H3v/8dAPCvf/0LXbt25RhGKV5nBIbXGMHDa4zA8RojMLzGCA65rzE4A0NmQ4YMwb/+9S+MHTsWkiRh/vz56NixI+bNm4fVq1ejc+fOGDFihNxhKtqjjz6KOXPmYNKkSTCZTJg5cyb69OnDMWyFwsLCFuOmUqmQl5eHSZMmQZIkzJw5E1qtVu5QFcliseDll19G+/bt8eyzzwIAfvrTn2LatGkcwwClpqZyDP1QWFiIuXPnYuvWrUhISEBRURGSk+UKg/oAACAASURBVJM5hlGI1xmB4TVG8PAaIzC8xggdXmP4R+5rDEGSJCkkeyYiIiIiIiIiChIuISEiIiIiIiIixWMCg4iIiIiIiIgUjwkMIiIiIiIiIlI8JjCIiIiIiIiISPGYwCAiIiIiIiIixWMbVSIK2OTJk/HMM89gwIABjm2LFy9Gjx49kJCQgE2bNkEURZjNZowfPx6jR48GAAwdOhQ7duxgqyoiIiJyidcYRNQUExhEFLBx48bh/fffd1xcGI1GlJaWon///ti4cSNef/11JCYmorGxEdOmTYNWq8XIkSNljpqIiIiUjtcYRNQUl5AQUcDuvfdeHDhwAA0NDQCAXbt2YeDAgSguLkZBQQESExMBALGxsSgsLMTbb78tZ7hEREQUIXiNQURNMYFBRAHTarUYNmwYPvnkEwDAn//8Z4wfPx4VFRXo1KmT02MzMjJQWVkpR5hEREQUYXiNQURNMYFBREGRm5uL999/H3q9HpcuXULv3r2RlpaGM2fOOD2urKwM7du3lylKIiIiijS8xiAiOyYwiCgoevTogbq6OmzYsAFjxowBAOTl5WHFihWora0FANTV1WHFihWYPHmynKESERFRBOE1BhHZsYgnEQXNmDFjsHLlSpSWlgKwVQCvra3FL37xCwiCAKvVirFjx+K+++5zPGfixImO/x81ahR+/vOfhz1uIiIiUjZeYxARAAiSJElyB0FERERERERE5AmXkBARERERERGR4jGBQURERERERESKxwQGERERERERESkeExhEREREREREpHhMYBARERERERGR4jGBQURERERERESKxwQGERERERERESkeExhEREREREREpHhMYBARERERERGR4qnlDoCIgNOnT+Oee+5B9+7dHdskScLDDz+MsWPH+rWv//u//8MXX3yB6dOnY9euXdi/fz/mzp3r8dijRo3Cf//731bHL5cHHngAGzduRFJSUsiO4ev4FBcXw2g0YvLkySGLhYiIKFJYLBZs2LABH3zwASwWC0wmE4YMGYLp06cjJiYGAKDX67FmzRocOXIEgiBAq9XiySefxN133w0AGDp0KDQaDWJjYyEIAkwmEwYOHIjZs2dDFMUWPzcajRBFEc899xwGDx7cIiZP+6usrOTfe6IIwAQGkULExsbi/fffd3yv1+tx//33o0+fPrj++ut93s///vc/VFdXAwCGDRuGYcOGBT1WpWg6XnI7ePAgunXrJncYREREirBw4UJUV1fjrbfeQmJiIurr61FQUIAXXngBK1euxI8//ogJEyZg+vTpWLp0KQRBwNGjR/Hzn/8ccXFxGDhwIABg1apVuOGGGwAARqMReXl52Lx5M6ZMmdLi5wDw8ccfY86cOfjss89cxuVuf3fddZdPr4t/74nkxQQGkUKlpaUhMzMTZWVl6NSpExYuXIjy8nJUVVUhPj4eq1atQufOnZGXl4fk5GR89913uO+++7B161ZYLBYkJiYiMzMTf/vb3/DGG2/g0KFDWLlyJYxGI77//nvcfvvtWLJkidvjnz59GpMnT0aXLl1w5swZbNy4EadPn8aqVavQ0NAAURTxzDPPYMiQIbBYLFixYgV2796NxMRE3HjjjThx4gQ2btzoFN/EiRMxevRovPzyyzh27BhMJhMGDBiA5557Dmq1Gq+++io++eQTaDQaXHXVVVi6dCnatWvndnuPHj2wf/9+XH311fjtb3+LkpISqFQqZGdnY968eUhNTUVeXh5uvvlm/Oc//8HZs2cxYMAALFq0CKLovIIuLy8PvXr1wsGDB3Hx4kU88MADmDZtmtNjTCYTli1bhv3790OlUuHGG2/E888/j/3792P37t3Yt28fYmNj+akMERFFtdOnT+ODDz7AZ599hoSEBACATqfDiy++iP/85z8AgM2bN+OWW27B6NGjHc+7/vrr8eqrr7qdWRkTE4Nbb70V3333ncufS5KE06dPIzk52ac4m+6vaQKDf++JlIsJDCKF+u9//4tTp07hpptuwp49e5CUlIRt27YBAObPn4+3334b8+bNAwAkJSXho48+AmD7433x4kXMnDkTf/7znx3727BhA6ZNm4Z+/fqhrq4Ow4YNw+HDh5GSkuI2hnPnzqGoqAi33XYbqqur8fzzz+P3v/89OnbsCL1ej3HjxqFHjx7Ys2cPjhw5gg8//BCCIOCpp55y2k/T+J5//nn07t0by5Ytg8ViwezZs/HHP/4R999/P9566y3s378fMTEx+MMf/oAvv/wSvXv3drndPr0UAN59913s3bsX27dvh06nw9q1azF79mz8/ve/BwCcOnUKGzduRH19PUaOHIl//vOf6N+/f4vXe/LkSWzZsgUNDQ0YN24cbrjhBqdPWX73u9/h/PnzeP/996FSqfDCCy9gxYoVeOmll7Br1y5069aNFzNERBT1jhw5gq5duzqSF3apqakYMWIEAODw4cMYNGhQi+f+9Kc/dbtfvV6P0tJSzJgxw7GtoKAAWq0WVVVVAIA77rgDr7/+uk9xutofwL/3RErGBAaRQjQ2NuKBBx74/+zdeVzUdeI/8Ndnbu6BAUHlEvBWIDXL5CjXs7LNEtNKv9lhu/5qN4+OtS0180hzt61Wzba2sqy0012j0kpAM3MrPEkFLwpBHQW5hzl+f6DEwMwwwxyfmeH1fDx6xHwYPp/35+3M53h93geA5n6j4eHhWLVqFbp3747u3bsjLi4OGzZswKlTp/D999/jqquuavnbYcOGdbj+FStWID8/H+vWrcPx48fR2NiIuro6mwGGTCZDeno6AKCwsBDnzp3D//t//6/l94Ig4MiRI8jLy8Pvf/97KJVKAMAdd9yBDRs2WCzfjh07cODAAXzwwQct+w00tzjp168fJk2ahKysLGRlZWHEiBEwGo0Wl7eWn5+P2267DYGBgQCAGTNmYN26ddDpdACAG264ARKJBMHBwUhISGjpYtPWHXfcAblcDrlcjvHjx2Pnzp1mAUZ+fj7mzJkDuVwOoLnVRuv6ICIiIkAikcBoNNp8jyAIMJlMHa5r/vz5UKlUMBqNkMvlyMnJaQlBgN+6hJSWlmLmzJno378/4uLiHF7fL7/80vIenu+JvBcDDCIv0XYMjNY2btyITZs24a677sLEiROhVqvNTrRXbtxtufvuu9G3b19kZmZiwoQJ2LdvX4cXDgqFAjJZ82HCYDAgOTkZmzdvbvl9RUUFIiIizFp6AGjXPaN1+YxGI/7xj38gOTkZAHDp0iUIggCJRIK3334bBw4cwO7du7Fs2TJkZmbiscces7q89ToFQTB7rdfrW16rVKqWn21dMF3ZV6C5JUvb/bC0naamJovrIiIi6qpSU1Nx/Phx1NTUmLXCqKiowFNPPYUXX3wR6enpKCwsbBnL4or33nsP9fX1mDlzJoD2Y1xYExcXh5UrV2LGjBlIS0tDamqqxffZsz6e74m8F6dRJfIBO3fuxKRJk5CTk4NevXrh66+/hsFgsPheqVRqdvMONIcEBw4cwPz58zF27FiUl5fj9OnTHT4daS09PR2nTp3C3r17AQBFRUUYN24cKioqkJ2djS1btkCn00Gv1+Pjjz+2up6MjAy88cYbMJlM0Ol0+OMf/4i3334bP//8M26++WYkJyfjwQcfxD333IMDBw5YXd5aZmYmPvzwQ9TV1QEANmzYgKuvvrpllHN7bdmyBUajEVVVVcjNzcWoUaPabefdd99FU1MTjEYj3nnnnZZBxizVOxERUVcUHR2NiRMnYsGCBaipqQEA1NTUYNGiRVCr1VCpVLjjjjvw/fffY8uWLS0PFg4ePIgXX3zRbFY2R1wZU2PRokUOXeO0xfM9kfdiCwwiH3Dvvffi6aefbul2kZ6ejqNHj1p877XXXov58+djyZIlGDhwIIDmMShmzZqFSZMmITAwENHR0RgyZAhOnTpls5llaxEREXjxxRexcuVKNDY2wmQyYeXKlYiNjcVtt92GEydO4NZbb0VgYCBiY2MREBBgcT1PPvkkli5diokTJ6KpqQnXXXcd7r//fsjlckyYMAG33347AgMDoVKp8Ne//hX9+vWzuLy1yZMn48yZM8jJyYHRaERCQgKef/55e6u3RUNDAyZPnoza2lrceeedGDFihFlLlz/+8Y947rnncOutt0Kv1yM1NbVlHJKsrCysWLECAPDggw86vG0iIiJ/snDhQqxZswZTp06FVCqFTqfD6NGj8fDDDwMA1Go1NmzYgFWrVuGVV16BRCJBQEAAli5d2hIWdMbcuXMxYcIEbNq0CVOnTu3UOni+J/JegsmezmdERDbs3LkTWq22ZQyPZ599FkqlEo8++qjIJbPf9OnTcdddd2H8+PFiF4WIiIiIiCxgFxIiclrv3r3xySefYOLEibjppptw8eJF/OEPfxC7WERERERE5EfYAoOIiIiIiIiIvB5bYBARERERERGR12OAQURERERERERejwEGEREREREREXk9r55G1Wg0wmDwzBAdUqngsW35AtaHOdaHOdaHOdaHOdaHOX+tD7lcKnYRnOLJawxv46+fSU9iHTqPdeg81qFzWH/Oc2cdWrvO8OoAw2AwobKyziPbUqsDPbYtX8D6MMf6MMf6MMf6MMf6MOev9REVFSJ2EZziyWsMb+Ovn0lPYh06j3XoPNahc1h/znNnHVq7zvDqAIOIiIjIHkajEYsWLcKRI0egUCjw7LPPIiEhQexiERERkQtxDAwiIiLyedu3b4dOp8P777+PefPmYcWKFWIXiYiIiFyMAQYRERH5vB9++AGZmZkAgPT0dBw8eFDkEhEREZGrsQsJERER+byamhoEBwe3vJZKpdDr9ZDJLF/qSKUC1OpATxXPq0ilki67767COnQe69B5rEPnsP6cJ0YdMsAg6qTcogqsKTiJiupGRIcoMTszERP6R4tdLCKiLik4OBi1tbUtr41Go9XwAnD9IJ6+dE7gwHXOYx06j3XoPNahc1h/zhNjEE92ISHqhNyiCiz78hjKqxthAlBe3YhlXx5DblGF2EUjIuqShgwZgvz8fABAYWEh+vTp47Ft85xARETkGQwwiDphTcFJNOiNZssa9EasKTgpToGIiLq4MWPGQKFQYOrUqVi+fDn+8pe/eGzbPCcQERF5BruQEHVCRXWjQ8uJiMi9JBIJnnnmGVG2zXMCERGRZ7AFBlEnRIcoHVpORET+i+cEIiIiz2CAQdQJszMToZKZf31UMglmZyaKUyAiIhINzwlERESe4dYAY9++fZg+fToA4NChQ8jMzMT06dMxffp0fPbZZ+7cNJFbTegfjQVjeyMmRAkBQEyIEgvG9vbaEeeJiMh9eE4gIiLyDLeNgfHqq69iy5YtCAgIAAAcPnwYM2fOxL333uuuTRJ51IT+0bw4JSIiADwnEBEReYLbWmDEx8fjpZdeanl98OBB7NixA3fddRcWLFiAmpoad22aiIiIiIiIiPyM2wKMcePGQSb7rYFHamoqHnvsMbzzzjuIi4vDP//5T3dtmoiIiIiIiIj8jMemUR0zZgxCQ0Nbfl6yZEmHfyOVClCrA91dtMvbknhsW76A9WGO9WGO9WGO9WGO9WGO9UFERETkGh4LMO677z489dRTSE1Nxe7duzFw4MAO/8ZgMKGyss4DpQPU6kCPbcsXsD7MsT7MsT7MsT7MsT7M+Wt9REWFiF0EIiIi6mI8FmAsWrQIS5YsgVwuR2RkpF0tMIiIiIiIiIiIADcHGLGxsdi0aRMAYODAgXjvvffcuTkiIiIiIiIi8lNuG8STiIiIiIiIiMhVGGAQERERERERkddjgEFEREREREREXo8BBhERERERERF5PQYYREREREREROT1GGAQERERERERkddjgEFEREREREREXo8BBhERERERERF5PQYYREREREREROT1GGAQERERERERkddjgEFEREREREREXo8BBhERERERERF5PQYYREREREREROT1GGAQERERERERkddjgEFEREREREREXk8mdgGIiIiIfF1uUQXWFJxERXUjokOUmJ2ZiAn9o8UuFhERkV9hgEFERETkhNyiCiz78hga9EYAQHl1I5Z9eQwAGGIQERG5ELuQEBERETlhTcHJlvDiiga9EWsKTopTICIiIj/FAIOIiIjICRXVjQ4tJyIios5hgEFEREQ+Z9u2bZg3b17L68LCQuTk5GDq1Kl4+eWXPVqW6BClQ8uJiIiocxhgEBERkU959tlnsXr1ahiNv3XbWLhwIVavXo13330X+/btw6FDhzxWntmZiVDJzC+pVDIJZmcmeqwMREREXQEDDCIiIvIpQ4YMwaJFi1pe19TUQKfTIT4+HoIgICMjA7t37/ZYeSb0j8aCsb0RE6KEACAmRIkFY3tzAE8iIiIX4ywkRERE5JU2b96MN99802zZsmXLcOONN2LPnj0ty2pqahAcHNzyOigoCKWlpTbXLZUKUKsDXVbWaSN6YdqIXi5bnztJpRKX7ntXxDp0HuvQeaxD57D+nCdGHTLAICIiIq+Uk5ODnJycDt8XHByM2tralte1tbUIDQ21+TcGgwmVlXVOl9EXqdWBXXbfXYV16DzWofNYh85h/TnPnXUYFRVicTm7kBAREZFPCw4Ohlwux+nTp2EymbBz504MGzZM7GIRERGRi7EFBhEREfm8xYsXY/78+TAYDMjIyEBaWprYRSIiIiIXY4BBREREPueaa67BNddc0/I6PT0dmzZtErFERERE5G7sQkJEREREREREXo8BBhERERERERF5PQYYREREREREROT1GGAQERERERERkdfjIJ5ERERETsotqsCagpOoqG5EdIgSszMTMaF/tNjFIiIi8itubYGxb98+TJ8+HQBw6tQpTJs2DXfeeScWLlwIo9Hozk0TEREReURuUQWWfXkM5dWNMAEor27Esi+PIbeoQuyiERER+RW3BRivvvoq/vrXv6KxsREAsHz5cjzyyCPYuHEjTCYTvvrqK3dtmoiIfERuUQUmrt+D4avzMXH9Ht7wkU9aU3ASDXrzBzMNeiPWFJwUp0BERER+ym0BRnx8PF566aWW14cOHcLw4cMBAFlZWfj222/dtWkiIvIBfGpN/qKiutGh5URERNQ5bhsDY9y4cfjll19aXptMJgiCAAAICgpCdXV1h+uQSgWo1YHuKmKbbUk8ti1fwPowx/owx/owx/owZ299rNt1yuJT63W7TmHaiF7uKp7H8fPR7JtvvoFSqcR1113Xsmz79u0YPXq0iKVyjegQJcothBXRIUoRSkNEROS/PDaIp0TyW2OP2tpahIaGdvg3BoMJlZV17ixWC7U60GPb8gWsD3OsD3OsD3OsD3P21seZqgary/2pPv318xEVFWL3exctWoTq6mro9Xq88cYbePnll6FQKPDWW2/5RYAxOzMRy748ZhbIqWQSzM5MFK9QREREfshj06gOGDAAe/bsAQDk5+dj2LBhnto0ERF5IWtPp/nU2v8cOXIEq1evxj/+8Q9kZmbikUceAdDcOtMfTOgfjQVjeyMmRAkBQEyIEgvG9uYsJERERC7msRYYjz/+OJ566in87W9/Q1JSEsaNG+epTRMRkRfiU+uuw2AwQKfTQaFQYPr06SgrK8Ozzz4rdrFcakL/aAYWREREbubWACM2NhabNm0CAPTq1Qtvv/22OzdHREQ+5MrN3pqCk6iobkR0iBKzMxN5E+iHZsyYgZtvvhnvvfceIiIi8Nhjj+Gpp57CDz/8IHbRiIiIyId4rAUGERFRW3xq3TXcfPPNGDNmDBQKBQBAEAQ8++yzuPPOOwGIM5hn8flavPL1MVyfEolh8WooZR7rVUtERESdxACDiIiI3E6pbD+2yYABAwBAlME8A+QSfPnzOXxyoBwBcglGJEYgO0WDjKQIhKrkHi0LERER2YcBBhEREYlKjME8e4YFYNvsEfhfaSXyirXIL9Hi62PnIRWAq2LDkJ0SiewUDbqHqjxeNiIiIrKMAQYRERGJShAEUbarkElwXa8IXNcrAo+PTkFReTXySrTYUazF6m9KsPqbEvSOCkJ2sgbXp0SiT7cg0cpKREREDDCIiIiIIBEEDOweioHdQzE7oxdKL9Yjr0SL/OLzeH3Pafzru9OICVEiK1mDrBQNhsaGQSbluBlERESexACDiIiIRCVGF5KOxIUH4O5hsbh7WCwu1ulQcPwC8ou1+PRgOTYVliFEKcN1vcKRnRKJEYnhCFbykoqIiMjdeLYlIiIiUZw9exbdunXDzJkzxS6KTeGBCtwyKAa3DIpBQ5MBe05dRF6xFgXHL+CLn89BLhUwLE6N7BQNspI1iApuP2ApEREROY8BBhGRD8ktqsCagpOoqG5EdIgSszMTOQ0p+Yx//OMfePfdd9HU1ISGhgYkJiZi69atGDVqlNhFs5tKLr08wGckDEYT9pddujwI6Hms2F6MFduLMTAmpCXMSNIEctwMIiIiF2GAQRZt2VeGVV8c4U0SkRfJLarAsi+PoUFvBACUVzdi2ZfHAIDfT/IJBQUFyM/Px7JlyzBz5kwsXrxY7CI5RSoRcFVsGK6KDcOfs3vhxIU65BVrkVesxZqdJ7Fm50nEqlXITm6e0SS1RyikEoYZREREncUAg9rJLarAsm3H0NDUdW+S2j7lfnRcX2QlqMUuFnVxawpOtoQXVzTojVhTcLLLfDfJt6nVaigUCtTW1iIhIQH19fViF8llBEFAkiYISZogzLwmHudqGpFf0hxmbCr8Fe/88AvUAXJkJkUgO0WDaxLCoZJLxS42ERGRT2GAQe2sKTjZEl5c4Y83Sdaa4lt6yv3kpwexYExvr99/di/wbxXVjQ4tJ/I2MTEx+OCDDxAQEIDVq1ejpqZG7CK5zIrtR/Hx/nIYTYBEACalxuCJ0X1we1oP1DTq8d3Ji9hRfB7fFJ/Hfw5VQCmT4JqEcGSnaJCZFIHwQIXYu0BEROT1GGBQO13hJslWU3yLT7mbvD/AYfcC8Xiqy1V0iBLlFr6H0SEcMJB8wzPPPIMzZ85g/Pjx+Pjjj/HCCy+IXSSXWLH9KD7cV97y2mhCy+snRvdBsFKG0X2jMLpvFPQGI378pQr5JVrsKNYiv0QLiQCk9ghFVrIG2SmRiA8PEGtXiIiIvBonMKd2rN0M+dNNkq2m+L4a4NjaJ3Kf3KIKPPnpQZRXN8KE34Kj3KIKl29rdmYiVDLzw7ZKJsHszESXb4vIlQwGA3Q6Hf70pz+hW7duUCgUyMnJ8fkxMK74eH+53ctlUgmGJ4Rj/qgU/OeB4Xj77iG479p41OoMeDH/BG5/fS+mvPE//LPgBA6duQSjF04xS0REJBa2wKB2Zmcmmo2BAfjfTZKtkMJXn3L7avDi6zzZ5erK+thNiHzNhx9+iHXr1uH8+fMYP348TCYTpFIphg4dKnbRXMJoJWOwtvwKQRDQNzoYfaODMeu6RJRVNTSPm1GixYa9pXjj+1JEBimQlaxBVooGV8epoZDx2RMREXVdDDConQn9oxEUqPTrWUhshRSzMxPNumIAgEru/QGOrwYvvs7TwdGE/tF+9V2krmHKlCmYMmUKPvjgA0yePFns4ricRLAcVjg64UiPMBWmDumJqUN6oqq+CbtOXEB+iRafF53FR/vPIFAuxXW9wpGVosHIXhEIVcldswNEREQ+ggEGWXRLWg+/nnXDYkhxuZWJpafcvjALia19IvdhcERkv4yMDMyfPx8XL17EuHHj0LdvX6SlpYldLKdNSo0xGwOj9fLOCguQ48YB0bhxQDQa9Ub873Ql8krOI7/kArYfPQ+pRMCQ2DBkJ2uQnaJBTKjKmV0gH8XBu4moq2GAQV1SR03x2z7lVqsDUVlZJ0pZ7cXuBeLoCl2uiFzl6aefxsyZM7FmzRoMGzYMTzzxBDZt2uTQOqqrq/Hoo4+ipqYGTU1NeOKJJ3DVVVehsLAQS5cuhVQqRUZGBh566CE37UV7T4zuAwAWZyFxBaVMgpFJERiZFIEnRptw6Ew18kq0yC/W4vlvSvD8NyXo2y0Y2Ze7mvSJCoIgONj8g3wOB+8moq6IAQZ1Wf7YFN8f98nbdYUuV0Su0tjYiBEjRmDt2rVISkqCUul4S6V///vfuPbaa3HPPffg+PHjmDdvHj7++GMsXLgQL730EuLi4jBr1iwcOnQIAwcOdMNeWPbE6D4uCyxskQgCBvcIxeAeoXgosxdOXahrHjejWItXd5/C+t2n0D1UeXlGEw2u6hkGmZTjZvgjW4N38xxERP6KAQYRkZP8vcsVkasoFAoUFBTAaDSisLAQCoXC4XXcc889LX9nMBigVCpRU1MDnU6H+Ph4AM1dVXbv3u3RAEMsCRGBmB4RiOlXx+FCnQ47Sy5gR/F5fHKgHO//VIYQpQwjkyJwfYoG1yaGI0jBSz9/wcG7iagr4lmMiIiIPGLJkiV47rnncPHiRbz++utYtGiRzfdv3rwZb775ptmyZcuWITU1FefOncOjjz6KBQsWoKamBsHBwS3vCQoKQmlpqTt2watFBCpwy+AY3DI4BvVNBuw5eRE7SrTYeXkgULlUwNXxakwY3APDugcjMphj9fgyjsFERF0RAwwiIiLyiJiYGDz44IM4efIkevfujbi4OJvvz8nJQU5OTrvlR44cwdy5c/HYY49h+PDhqKmpQW1tbcvva2trERoaanPdUqkAtTqwczviA9QAbo0Kwa1Xx0NvMOLH0kp8VXQW24oq8NSWQwCAtNgwjO7XDaP7RyOZ42Y4RCqViP75eXRcXzz56UHzMZjkEjw6rq/oZbOHN9Shr2MdOof15zwx6pABBhEREXnEmjVrUFBQgMGDB+ONN97A+PHjcc899zi0juLiYvz5z3/GCy+8gH79+gEAgoODIZfLcfr0acTFxWHnzp0dDuJpMJi8fnBmV+qjVqHPiHj84do4nNMZ8d+ffsWO4vNYvf0YVm8/hvjwgOZxVjKLrQAAIABJREFUM5I1GNwjFFJH54DtYrxhcO+sBDUWjOndbvDurAS16GWzhzfUoa9jHTqH9ec8d9ZhVFSIxeUMMIiIiMgj8vPzsXHjRkgkEuj1etx5550OBxirV6+GTqfD0qVLATSHF2vXrsXixYsxf/58GAwGZGRk+MX0rO4gCAL6RIfg3mvjce+18Thb3dg8CGiJFu/9+Cve/t8vCA+QIzM5AlnJkbgmQQ2VXCp2sckKDt5NRF2NXQHG0aNHUVlZCY1Gg+TkZHeXiYiIiPxQREQE6uvrERQUhKamJkRERDi8jrVr11pcnp6e7vCUrAR0C1FicnoPTE7vgZpGPb49cQH5JVp8few8thysgEomwbWJ4chK1iAzSQN1oFzsIhMRURdmNcDQ6XRYv349Pv/8c2g0GkRGRuLSpUuoqKjAjTfeiHvuuQcqlcqTZSUiIiIfdMcdd0AQBGi1WowbNw59+/ZFSUkJ1GrO3uNNgpUyjO3XDWP7dUOTwYgfS6uQV6JFXvF57CjWQiIAaT3DkH15itZYdYDYRSYioi7GaoDx9NNPY+LEiZg9ezYkkt/mDzeZTMjPz8fTTz+NlStXeqSQRERE5Lv+9re/iV0EcpBcKsE1ieG4JjEcj45KxpGzNdhRrEV+iRYv5B3HC3nHkaQJxPUpGmSlRKJ/dDAkHASUiIjczGqAsWLFCovLm5qakJ2djezsbLcVioiIiPyHIAjYtWsXEhISMHz4cLGLQw4SBAH9okPQLzoEfxiZiF+r6pF3Ocx48/tSvL6nFFHBiuZBQFM0GBanhlwq6XjF5HG5RRXtBv3kGBpE5EusBhjz58/H0qVLoVT+Npd0cXEx5s6diy1btnikcOQYnpSIiMgbrVu3Dl9//TUWLFggdlHIBXqGBeDOobG4c2gsKuub8O2JC9hRrMVnhyvw4b4zCFJIMSIxAtenaHBdrwiEqDhmvDfILarAsi+PoUHfPO1qeXUjln15DAB4vUhEPsPqGeWaa67BtGnT8PzzzyMpKQmbNm3CunXr8NRTT3myfGQnnpSIiMhb/fGPf0RTUxOOHz8udlHIxdQBctw4IBo3DohGo96IvacvtrTO2H70HKQSAUNjw5CdokFWsgYxoRw/TSxrCk62XCde0aA3Yk3BSV4rEpHPsBpg5OTkYMCAAZg/fz7Cw8MhCALef/99REVFebJ8ZCeelIiIyFuFh4djzpw56Natm9ny+vp6BARwIEh/oZRJkJGkQUaSBn8xmXDwTDXyipsHAV31dQlWfV2Cft2CkZWiwfUpGqREBkHguBkeU17d6NByIiJvZLNNX1NTE3Q6HRoaGhAbG4vg4GBPlYscVGHl5GNtORF1LexiRmJSqVQWZy6bPn06PvjgAxFKRO4mEQSk9ghFao9QPJzVCycv1CG/WIu8Ei1e/fYU1n97Cj1ClchKiUR2sgbpsWGQSRhmEBGRbVYDjLVr1+I///kPVq5ciUGDBuGtt97ClClTsHLlSvTv37/TG7z11lsREhICAIiNjcXy5cs7vS76TXSI0mKCHh2itPBuIupK2MWMvJXJZBK7COQhiRGBSBweiBnD46Ct1aGgpDnM+GhfGd778VeEqWQYmRSB7GQNrk2MQKBCKnaRiYjIC1kNME6cOIHNmzcjKCgIADBjxgykp6djzpw5+Pzzzzu1scbG5hvsDRs2dOrvybrZmYlmNygAoJJJMDszUbxCEZFXYBcz8lbsPtA1aYIUuDW1O25N7Y46nQHfnbqI/OLz2Hn8Aj47fBYKqYDhCeHIStYgM1mDyCCF2EUmIiIvYTXAWLlyZbtlqampeP/99zu9sZ9//hn19fW49957odfrMXfuXKSnp3d6ffSbKzchbCJORG2xixmJbfXq1e3CCpPJhIqKCpFKRN4iUCHFqN6RGNU7EnqjCft+rWoeN6NEi53HL0DYdgyDuociO0WD7GQNEjWBYhfZZwkALLV5YoxIRL7E4XmtwsLCOr0xlUqF++67Dzk5OTh58iQeeOABfP7555DJOL2WK0zoH83AgojaYRczEltSUpLF5XPnzvVwScibySQChsapMTROjTnXJ6HkfB12FJ9HfokWLxecwMsFJxAfHoDrL89oMqh7KKQcN8Nut6XF4MN95RaXExH5CsHkwQ6oOp0ORqOxZSCvyZMn46WXXkL37t0tvt9oNMJg8EzxpFIJDAZjx2/sIlgf5lgf5lgf5ry9PrbsK8OTnx5EQ1OrLmZyCZb+fhBuSevh8u15e314mr/Wh1zu2BgFJpMJe/fuRVlZGbp3747hw4eL2oWkqcmAyso6l63PlwbKVasDXbrvnlBR3Yj8kuYZTf5XWgWD0YSIQDkykzTITtHg6ng1VA5+Jp3hi3UIACu2H8XH+8thNAESAZiUGoMnRvcRpSy+WofehHXoHNaf89xZh1FRIRaXezTA2LhxI44ePYpFixahoqIC//d//4f//ve/VltguPriwhZ+gM2xPsyxPsyxPsz5Qn148ubKF+rDk/y1PqxdWFhy/vx5PPjgg0hISEBsbCxOnjyJ0tJSvPLKK+2mVvUUV15j5BZVYHHuEbR+5iIVgIUT+npliOHrn8maRj2+PXEBO4q1+PbEBdTqDFDJJLg2MRzXp0RiZFIE1AFyt5bB1+vQG7AOncc6dA7rz3liBBhW+25Mnz7d6pMRk8kEQRDw1ltvOVSIyZMn4y9/+QumTZsGQRCwbNkydh8hIvIAdjEjMa1YsQLz58/HiBEjWpbl5+dj+fLl+Pvf/y5iyVxj+bZjaNtg1GBqXs7vnesFK2UY268bxvbrhiaDET+UViKvWIv8Ei12FGshFYC0nmHIvtzVJFYdIHaRiYjIRaymB+6YKUShUGD16tUuXy+RLzXdJSLqasrLy83CCwDIysrCmjVrRCqRa9U3We4iZG05uY5cKsG1iRG4NjECj/0uBUUVNci73NXk7zuO4+87jiMlMghZlwcB7R8dzNlviIh8GJs/kM/LLaowm0K2vLoRy748BgAMMYjIYxikWieRSMQuAnUBgiBgQEwIBsSE4I8jE/FLZf3lcTO0eGPPabz+3Wl0C1YgK7l53IyhcWrIpb792eRxh4i6GgYY5PPWFJxsCS+uaNAbsabgJE/iROQRtoLUaSN6iVk0r9CjRw988803uOGGG1qW7dixAz179hSxVOTvYtUBuHNoLO4cGovKuibsPNEcZvz3UAU+2HcGQQopRvaKQHaKBtf1ikCw0rcui/kAh4i6It86UhNZUGFhekhby4mIXM1WkMoAA3jsscfw8MMP4/3330d8fDx++eUXaLVarF27VuyiuUSATEC9vv2Y6AEydlXwFupAOW4eGIObB8agocmA709XIr9Yi4LjWnx55BxkEgHD4tTIujxuhi9MM80HOETUFVkNMCoqKvD8889j1apVGDNmDOrr61FXV4c33ngDqampniwjkU3RIUqUWwgrfOHig4j8A4NU2yIiIvDOO+/g4MGDKC0txfjx4zFkyBCxi+UyfxnbB4s+O4LWt5KSy8vJ+6jkUmQlNwcVBqMJB89cQl6xFnklWqz8qhgrvypG/+hgZKdokJ0cieTIQK8cN4PHHSLqiqwGGEuXLsXvf/97AEBMTAw2bNiAgwcP4sUXX8T69es9VkBfx76J7jc7M9GsCSUAqGQSzM5MFK9QRNSlMEi1bezYsZg0aRJuv/12DBo0SOziuNyV8zrP975HKhGQ1jMMaT3D8KfsJJzU1mFH8Xnkl2ixbtcprNt1Cj3CVLj+csuMtJ5hkEm8I8yQSQBL48TKfHtYDyIim6wGGFVVVfjd735ntmzQoEGoqqpye6F8jbWQgn0TPYMXjuSvGID6Dgaptr333nv49NNPMWvWLPTs2RNTpkxBdna22MVyKU5V7B8SNYG4RxOPe66Jx/laHQouDwL6QWEZNv7wK8JUMmQkReDGtJ4YHBWIALlUtLJam+SGk98QkT+zGmDodLqWn//1r3+1/KxU8mlSa7ZCCvZNdD3e0FFXwQDUtzBItS0iIgIzZ87EzJkzsX//fnz44Yd44YUXMGbMGMyePVvs4hFZFBmkwKTU7piU2h11OgO+O3kBO4q1KDh+AVsPn4VSJsHV8WpkJ2uQmayBJkghdpE7xOsoIvJ1VgOMkJAQnDp1CgkJCS2hxalTpxAYGOixwvkCWyEF+ya6lrUbun2/VmHrobO80SO/wgDU9/AJvH1SU1NhNBohCAI+/fRTBhjkEwIVUozqE4VRfaKgNxhRXNWIrfvKkFd8HjuPX4Cw7RgG9whF9uUpWhMivO96mcE4EfkDqwHGI488gtmzZyMnJwcJCQkoLS3F5s2b8fzzz3uyfF7PVkjhaJ9opuK2Wbuh+3h/OYxtBn/njR75Ogag5G9+/fVXfPLJJ/jss8+QnJyMKVOmYOHChWIXi8hhMqkE1yZp0C8iAHOvT8Kxc7XIK9Eiv1iLlwpO4KWCE0iMCEBWciSyUzQY1D0EEi8YBJTBOBH5A6sBxoABA/DGG2/gk08+wY4dO9C9e3e8+uqriImJ8WT5vJ6tkMKRPtFMxTtm7catbXjR0fuJfAEHhSR/cvfdd+P8+fOYPHky3nrrLWg0GrGLROQSgiCgT7dg9OkWjAdGJKD8UgPyL4+b8c4Pv+CtvaXQBCmQmRSB7BQNro4Ph9JFo2zGWDlPxFg5TzAYJyJ/YDXAMBqNOHjwIFJTU/HAAw94skw+xVZI4UifaKbiHbN2QycRLIcYvNEjX8ZBIcmfPPTQQ7j22mvFLgaR28WEqjDlqp6YclVPVDfosevEBeQVa7HtyDl8cqAcAXIJRiQ2hxkje0UgLEDe6W05ep5gME5E/sBqgLFo0SJUV1ejrq4Ohw8fxsyZMz1ZLp/RUUhhb59opuIds3aivmlgN7MxMK4s540e+TIOCkn+hOEFdUUhKhnG9++G8f27Qac34n+llcgv0SK/RIuvj52HVADSY8OQnRKJ7GQNeoSpHFq/PeeJFduPtnS1FdD8X+tnPrxeIiJfYzXAKC4uxsaNG9HU1IQHHniAAYYNrhi4jal4x2ydqNN6hvFGj/wOB4UkIvIPCpkE1/WKwHW9IvDY71JQVFGDvOLzyCvW4m/flOBv35Sgd1RQyyCgfbsFQ7Bj3Axb54kV24/iw33lLa+vBBcqqYBGg4nXS0Tkk6wGGDJZ86/kcjmMRk4o7W5sLm4faydq3ugREfmGY8eOoXfv3mIXg0g0EkHAwJgQDIwJweyMXii9WH95ENDzeH3Pafzru9OIDlEi63KYMTQ2DDKp4+NmfLy/3OJyndGE7+dlObsbRESisBpgkGexuTh1hLPUEHU9/vi9X7JkCd56661O/31dXR3mzZuHqqoqBAQEYNWqVYiIiEBhYSGWLl0KqVSKjIwMPPTQQy4sNZH7xIUH4O5hsbh7WCwu1umw83jzuBlbDpZjc2EZgpVSjOwVgeyUSIxIDEew0r7Ld2uDnFtb7iv88bhIRPazegT88ccfkZGRAQCorKxs+RkAdu7c6f6SdUFsRUDWcJYaoq7HH7/3BQUFqKqqarmOaH1tYa9NmzZh4MCBeOihh/DRRx9hzZo1+Otf/4qFCxfipZdeQlxcHGbNmoVDhw5h4MCBrt4FIrcKD1Rg4qAYTBwUg4YmA/acqkR+yXnkl1zAFz+fg0wiYFi8GtnJGmQla9DNRldja4OcS2z0TPH2cMAfj4tE5BirAcbBgwc9WQ4isoGz1BB1Pf74vf/ss8+g1WqxdetWAJ0LMO655x4YDAYAQFlZGSIjI1FTUwOdTof4+PiW9e7evZsBBvk0lVyK7JTmbiQGowkHyi4hr0SLvOLzeO6rYjz3VTEGxIQ0hxkpGiRrAs3GzZiUGmM2Bkbr5Zb4Qjjgj8dFInKM1QDj5ZdftvpHbJZJ5FmcpYao6/HH7/3y5csxffp0LF++3K73b968GW+++abZsmXLliE1NRUzZszA0aNH8e9//xs1NTUIDg5ueU9QUBBKS0tdWnYiMUklAtJjw5AeG4Y/ZfXCiQt1yCtuntFk7a6TWLvrJGLVqpZxM9J6hOGJ0X0AoGUWEonQHF5cWd6WL4QDnTkuenurEiJyjNUA4+2330ZoaChuuukmxMTEwGTy8Q5z5JAt+8qw6osjPNh7Cc5SQ+Qe3nxh66/f+zFjxtj93pycHOTk5Fj83VtvvYWSkhI8+OCD+OSTT1BbW9vyu9raWoSGhtpct1QqQK0OtLss/kQqlXTZfXcVsepwy74yrN52FGeqGtA9TIV5Y/rgml4R+PrIWXxVdBabC8uw8YdfER4oxw19u2H0gO5YeMtgBCikHa7bVjjgjn3tTB12D1OhrKrB4nJL69qyrwzLth1DQ1OrViXbjiEoUIlb0np0ruBehN9l57D+nCdGHVoNMHbu3ImCggL897//RVFREcaOHYtx48YhKCjIk+UjEeQWVbQ/2HtZE8KuhrPUELmetzeX9tfv/YwZM5z6+1deeQXR0dG49dZbERgYCKlUiuDgYMjlcpw+fRpxcXHYuXNnh61FDQYTKivrnCqLr1KrA7vsvruKGHXY9phVVtWAJz85iAVjezePo9Y7ErU6PXafuIi8Ei22Ha7ARz/9CqVMgmsSwpGdrEFGcgQiAhUW128rNHXHvnamDv8wMsHicfEPIxMsrmvVF0darmevaGgyYtUXR5CVoO5cwb0Iv8vOYf05z511GBUVYnG5zWlUb7jhBtxwww2ora3Ftm3bMG/ePAQEBODvf/+7WwpJ3mFNwcn2B3sva0Lo7yw9FV4wtrfFJ8Xe/ASZyJt5e3Npzk5l2e23347HH38cH374IQwGA5YtWwYAWLx4MebPnw+DwYCMjAykpaWJXFIi17LnmBWkkGF03yiM7hsFvcGIH3+pQn6JtqW7iQAgtUfo5bE1IhEfHtCyLntCU7GvORw9LvpjVzyirs6ueZgOHTqEH3/8EWVlZRg5cqS7y0Qi48FeXNaeCi8Y2xv/mXWNXe8FvOMJMpE384VjHWenai8yMhKvvfZau+Xp6enYtGmTCCUi8gxrx6by6kYMX53f7mZeJpVgeEI4hieEY94NyTh6rhZ5xeeRV6zFi/kn8GL+CfSKCGwZKHRcv24ArIcD7rrmWLH9qN3jdFzZlr3b89eueERdmdUAY//+/di6dSu+/fZbpKen4+abb8bixYvNRjcm/+RLB3uxnwS4g71PhXOLKrAo90i7KdK86Qky+R5//E5Z40vHOl/3/vvvW/3dHXfc4cGSEPkua8csADDBdqAgCAL6dgtG327BmHVdIs5cakB+sRY7SrTYsLcUb3xfisggBTKTI/DEmN64Ok4NhUxitg53tFpbsf2o2UwpRhNaXtsKMezlr13xiLoyqwHGlClTkJycjMzMTMjlcuzatQu7du0CAMydO9djBSTPyi2qQJ1O3265Nx7s/bX1gT1Pha/su6X53W2tg8gWf/1OWcMLW885d+6c2EUg8nmWjllt2RsodA9V4Y4hPXHHkJ641NCEXScuIK9Yiy+KzuHj/eUIlEsxolc4spI1yEiKQKhK7pZWax/vbz/N65Xlrggw2BWPyP9YDTDsneKM/Efbm5crwlQyzBuV7HUHe2efBHjrk2Z7ngpb2ndr7yWyl7ePCeFqvLD1nNYDap49exZ6vR4mkwlnz54VsVREvmVC/2js+7WqpbuFNY4GCqEqeUu3jEa9Ef8rrUR+sRZ5JVp8dfQ8pAJwVZwawUopqhsN7f6+7TWHI9dX1vbD1v45yte74nnr9SqRWKwGGH379sWAAQOs/uGhQ4cwcOBAtxSKxGHtpjhALvXKA6UzTwK8+UmzPU+Fbe0jnyBTZ/nCmBCu5usXtr5mwYIFKCwsRH19PRoaGhAXF8dxK4jslFtUga2HznZ4c+/MQwylTIKRvSIwslcEHh+dgsPl1ci7HGZYCi+UUqHdIJ+OXF9JBMthhYQ91gF49/UqkVgk1n5RUFCAefPmYdu2bTh9+jRqa2tRXl6OL774An/+85+Rn5/vyXKSB/jazYu1E7Q9J25bT5rFNqF/NBaM7Y2YECUEADEhypYp0q6wto8SAe3eS2QvZ75TRPY4fvw4tm7dioyMDGzduhVKJT9bRK3lFlVg4vo9GL46HxPX70FuUUXL7zpqfQm49iGGRBAwqHso/l9mL2y6Zxg+vPdqjO0XBbn0t3RBJZfi0JlqfH/qIvQGo8PXV5NSYxxa3tV48/UqkVistsB48MEHUV5ejnfffRevvfYaLl68iMjISAwfPhyPP/44evTo4clykgf42oB2zvRf9/awpqOnwtb2neEFOcPTY0KwWWzXExQUBEEQUFdXh4iICDQ1NYldJCKvkVtUgWdyj0B/uUVCeXUjnsk9AqD5usDWNYoAuP04Gh8egKU39QcAXKjTYWfJBeSVaPHJgXK8/1MZQpQyVDe2H0cNsH59dWWcC0dmIelKvP16lUgMNqdRjYmJwZw5cwAAlZWVCAsL4ywkfszXBrRzpv+6r4U1bbHvPrmDJz9XbBbbNQ0cOBCvvfYaunXrhjlz5kCvt3yzQ9QVPf9VcUt4cYXe1Lx8Qv9oq9cuMSHKdtOsu1tEoAK3DI6BXCbg54pqnK3RQW8wQkDzjChtmQBcvTrfYkCR1jMMu45fREV1I7oFK5HWM8zsb7ty2O3r16tE7mAzwACAvXv3YvHixTAYDBg/fjx69OiBnJwcT5SNPMwXb4o723/d18IaSzq77135QoA65qkxIbragKHUbO7cuaipqYFKpUJ+fj7S0tLELhKR17hkYYyJ1su97dqlbRBdrzdCCgACYLAxOOeVaVJXTE7vMMz2xbDblddZ3vZvTuQNOgwwXnjhBbz99tt4+OGH8Yc//AHTpk3zWIBx4kQJ5syZD7lcDplMBrlcbvazTGb5tVwua/e7337f+nfNr+VyOcLDQ9DQYGizLvP1SqVSv2+BcuXmRa0ORGVlndjFcRtfDGtcQcwLAQYn1BqbxXZNL7/8stnrw4cPm81QQkTWedu1i6Ug2gAgVCFFoEJmseXAFR/uK8fkqy/in/knbIbZvhZ2u/o6y9v+zYm8QYcBhkQigVqthiAIUCqVCAoK8kS5AABNTU04caIETU1NaGpqgl6vv/z/JjQ16S//v8mjTVBbhyEKhfUQxZ7AxV1hTOv3KxQKq2FMV9cVZx8Q60LAF5+g+AJfDoXYLNb9vPHzERkZCQAwmUw4fPgwjEbbAxISdSVhKhmqGtpf04apfrtcd/baxZXHBWuBc3WjAV89NBJAc7cRa6b9a4/V35VXN2L46nyL3VFsbVts7rjO6orXq0S2dBhgxMfHY/Xq1aisrMT69es7PXin0WjEokWLcOTIESgUCjz77LNISEiw+Td9+vRDXt53Ha7bZDJZDTfaBx9tw4/m1wqFBFVVNTaDEsvrMl9P69/p9Xo0Njaitramg/V4PowRBMFmUKJUKiGRSD0SxsjlCothjOW/YxjjDLGeevvaExRf4OuhEJvFupe3fj6mTp1q9vr+++8XqSRE3mfeqGQs+fwomlrNKyqXCJg3Ktkl63f1ccHZIPofU9Lw+EcHrM6sYmu2WG8Nu9m6kMj9OgwwFi9ejM2bN2Po0KEICAjAkiVLOrWh7du3Q6fT4f3330dhYSFWrFiBtWvXdmpdbV25GZfL5Z1eh7d0mXBFGNP2/TqdzkJQ0jZwMf8dYEJdXYPDYUx9ow6NuiYYDXrAaLkvp6t1FMZ0FLho6w04cVGHRqOAAKUCA3uGIykqpFVLGwWCgwNgMMBqSxfr2/euMEasp948oTvH0hMzXw+F/KVZrDe2cgC8NzQ8ceJEy8/nzp3DmTNnRCsLkbeZ0D8a+36tMpuR45bBrnv67urjgj1BtEoqoMHCgBgqqYAbB3dHVU0Dln5xFI3WBs2wwJvDbrYuJHK/DgMMmUyGadOmOb2hH374AZmZmQCA9PR0HDx40Ol1+iNXhDGu0JlAp22ybzKZoJKYMP+GRIxKDrcafDQ16dq8ttwyxfrvbIcxtlrGaKvrcaayFkaDATDq0WAwYOdRPX6QAYLR4HUtY6yFMfZ2LepWpUPxqSoYIAWkUggSGeQyOfoP7o6NG4/aHcZERISgoUFvdxjDE3rnWXtiZu2JlS+FQr7eLNadrRycDUa8NTR8+umnW35WKpV47LHHRCwNkXfJLarA1kNncaUBhtEEbD10Fmk9w1xyrHT1ccGeIPqmQdEtg3a2dtOgaIvr6CjGEADcOCDKa88dbF1I5H4dBhiuUlNTg+Dg4JbXUqkUer0eMpnHikBOsOdium2yLwgCGk0CXttbgVuvSnRtORoul2Osc087J67fA9gxJVlYWADOnauyu2WMGGGMTmdfyxyDoX3LmDe+7HQVWtU6jBGkMjQYBUCQAlIZBIkUEqkMJnUgxn4QYCMI6XicF/t+13HLmOauTJZ+J4dEInF9BdnJ2hMziQAYLVzpMRTyHHe1cnBFMOKtoeGGDRtE3T6RN3N3yyl3HBc6CqJ3Hb/Y4fLW65i4fo/NwT9NAD7aX4HSygbcPSwOw+LUUMjEO0e35S+tC4m8mcfSg+DgYNTW1ra8NhqNHYYXUqkAtTrQ3UW7vC2Jx7blC1rXx5Z9ZVi27RgamlpdTG87hqBAJW5J+21MFFvJvivq1t5yOMLeMkulEnTrpu7UNlxty74yrN52FGeqGtA9TIXHxvRxaP9NJpPZ+C3W/ms7zstv/+lhMOjR2Kiz8Z7248McK6/ETyfPo66hESop0DtShchAWZt1NKK+vqYlqLFdDsthjDtIJJJ2rV2sDeh7JUgxbxVj7b/fgpLjFxrw3ckq1DSZEBqowuiBPTAkMRLFu34GJM2hjyCVt7ScgUQKpUKOJpOk+fdSKZQKBe4e3h+VlWetbtMTYUxXOZ46cvxwpD7W7Tpl8SZm3a5TmDail13reHRcXzz56cGW4yUAqOQSPDquryj/NqNGjTKbxUvd5nM3AAAgAElEQVQmk0Gv10OhUCA3N9fj5SHyRu5uOTU7MxHP5B6BvlX4LRPg1tYBju6TpRYMlvzvdBX2nq5CkEKKEYkRyE7RYGSvCISoxH8w6uutC4m8nce+5UOGDME333yDG2+8EYWFhejTp0+Hf2MwmDw2LoW3jIHhLVrXx6ovjphdBANAQ5MRq744gqyE327qbSX7rqhbe8vhCHvL7C2fj7ZPZsuqGvDkJwdRW9fYiZOlAEBxueWBY3/pLfVhNBodGjOmo5YxOp3Oyu86HjOmvr7BrPVLQ0OthTJZbhmja2pq7sZ02UUAr30GvNaJOnn4Fdu/vxLGWGpp0rZFS2daxigUcgQHB5qNGWN9G7a7SdluNdMcxog5BoW7jh9nqhqsLrd3PVkJaiwY07td3WQlqF323Y2KCrH7vZ9//jlMJhMWL16MqVOnIjU1FYcPH8bGjRtdUhYif+CJllNtG+7ZP/JE5zi6T/Z2KTEB+Pukgcgr1iK/RIvtR89BKhEwJDYM3YIV+P5UJc7X6tgCgsgPeSzAGDNmDHbt2oWpU6fCZDJh2bJlnto0Ocne9Nzd/f7c8WTC1/oqeuvAfGKRSCRQKBRQKBSilsPZQGfi+j04c6keMBpgujwei8loQFSABHcP7Y6XdxSjUdcEk1EPk0EPhWDEXUNjMLRHiNWuRc50U2obuDQ01KOmxr4wxpMtYwSJxKxb0mmJDPdJpVAHBSA0UGk1cFEobI8ZY2+AklZfh9NHz0Fv+m1MGYVcjlHXJmDv3j0tf2dtzBhr3ZRcdRPjTU8Br3xHS0tLkZqaCgAYMGCA2aCeRF2du69JVn9dgrZjZRpMzcvddazozD7Z06UkJkSJjCQNMpI0+IvJhINnqpFXrMVnhyuw93Rly/vKqxvx7BdHYTKZcOOAGNftGBGJxmMBhkQiwTPPPOOpzZEL2Xsx7e5+f+7quwn4Tl9Fbx2Yj5xTUd0IQZAAUklzN5HLLgKYfsMQRMb09NrPqKUWEHdck2B1zBhbgYujYcw7359CTUMjTJdnPWoOeAyA1IS0XmFWw5jq6iq7x6UxGm03Y7ZkeScaFbRuGQOpDA0GAZBIIUiaAxqJVAZTWCDGfejYmDH2hjGOtoyRyxWIihro8H6GhITghRdeQGpqKn766Sf07NnT8coi8lPuviaparA8ILm15a7g7D7ZE4BIBAGpPUKR2iMUX/58tt06dAYTFuYexcLcowgPkONP2b1w88DOhxltz3sjk8Kx6/jFTv+beetsVkTeSvyOYuT1HEnP3fnEz11PJrzpKWVHvHVgPnJOR/+u3voZtTbYZFCgElkJaiiV7v1cbl6dj3ALywUAr8zLcsk2jEajA61ZLIcxCoUEVVU1DrWMKTlbhUO/VqKuUQelxISkcAU0AVKzMKaurn03JVeHMbaYTI43Pn/++efx8ccfIz8/H8nJyXjkkUdcWiYiXyf28d4dN9PO7JOjAUhHD3Qu1jdh8edH8cn+ckwb2hMjEiMQqLB/CntL573Ws6w4OuiyO2ezIvJXDDCoQ97SSsFbyiEmX+vyQvbxxX/X3KIKLMo90m4mlAa9Eau3HUXW/cPdXgZPBHoSiQRKpdKpMMabxoxxNozp7NTSBw4cwODBg/Hjjz8iISEBCQkJAIDdu3cjIyPDHbtLRG2EKqW41Ni+i1+osvkG3ltvph0JQKydF9raX3YJ+8ouQSEVcHV8OLJSNMhK1iAyqH2X1NahjmBlBrDWHOnay67BRI5jgOFjxGpmJvYTAW8rh1gY4vgnX/t3vXKRa+0iztoglK7mi8GPmFwRxnTW7t27MXjwYGzdurXd7xhgEHnG/N+lWJyFZP7vUgCIdzPtymtbe2cxMQFYNyUV+SVa7CjWYte2C1i+7RgGdw9BVrIG16dEIlET2C7UsbfhWesQxdb+sWswkeMYYPgQb03GybN8McRh/86O+dK/q6WL3Na6h6k8Ug5PBD/87LrGrFmzAADLly+HwWCAyWRCYWFhy4CeROR+HR0zxbiZbtuar7y6EYtyj5iV1xFt99Fai4mYECWGxqkxNE6NR7KTUHK+Dnkl55FXrMU/d57EP3eeRHx4ALQ1ug7DEEskwm/7Z+vanV2DiRzHAMOHsJmZuLrCjYw79tHVwVtny9gV/v08xdbFrEomwbwxHU+T7SruDH4YGrveqlWrEBcXh7KyMhw6dAhRUVFYsWKF2MUi6jJsHTPFuJl+9ouj7QIGo6l5uTPjZlz527bHcaB9Sz1BEJASFYSUqCDcd20CKqobkV+iRX6xFqcv1neqDFf2qaNrd7YkJHKcpOO3kLdgMzPxbNlXhmVfHkP55TnJr9zI5BZVWP2b3KIKTFy/B8NX52Pi+j023+sNrpzkHdlHe9g6eXuqjO7at67K2sWsRAAWjO2NW9J6eLhE7uHKzy41++GHHzB16lT89NNPeO2113DmzBmxi0REl83OTIRKZn5r4O6baV3beV07WO6oCf2jsWBsb8SEKCGgueXFgrG9bYYj0SFK5KT3wEuTB6NbsO1p2gUry2Munyc7unbvTPmIujq2wPAhbGYmntXbjjrU+sUXn9y6q4WPK4O3zpaRrZdcy9oTI3+76GJo7HpGoxH79+9HbGwsdDodLly4IHaRiOgyXxuPyV7OtNR7KKtXu/OdVACClDJcujz9rIDmMTWuaB362HPt7ktdSIm8AQMMH8JmZuKxNiihtRsZX7xhdtfNmiuDt86WkTeiruWvF7ltMTR2vd///vdYsmQJli1bhlWrVmHGjBliF4mIWuHNtDlr57vx/bqhqKIGeSVabD1UjopqHQBAJhEwPEGNhPBAmEwmXrsTuQEDDB/SVW4avFH3MBXKLIQY1m5kfPGG2V03a648eXe2jLwRdb2ucJHLC0/Xu+uuu3DLLbegrKwMc+bMQWBgoNhFIiIRXR0Xir2llywu9xbWzncDYkIwICYEfxyZiF8q65FfokVesRY7j19AfskFdAtWIDNZg5yreuDLorM4W6PjtTuRCzDA8DG+cNPg6sESvWHwxXlj+uDJTw7afSPjizfM7rpZc2Xw1tky8kbUd4n5/Wdo7HpffPEF1q5dC4PBgPHjx0MQBMyePVvsYhGRSNZMScfsTYVmIcbVcaFYMyVdxFI5LlYdgDuHxuLOobGorG/CruMXsKP4PLYeqkCD3ogghRSj+0YhO1mDkUkRYheXyKcxwCCLNwjTRvTq9LpcPeOEN4wlcUtaD9TWNdp9I+OLN8zuvFlzVfDW2TLyRtQ3ecP33xdCY1/y73//G5s2bcJ9992H2bNn4/bbb2eAQdTFuTuscHcQbmn9Nw2Mxk0Do9HQZMDe05XIK9GioESLbUfOQSYRMDQuDFnJkchKjkBMqGemHifyFwwwujhrNwhBgUpkJagdXp+rx37wprEkHLmR8dUbZl+4WetsGX1h38icN33/yTUkEgkUCgUEQYAgCAgICBC7SETkx1wRhNsKQDpav0ouRWayBpnJGhiMJhw8cwn5JVrsKNZi1dfFWPU10D86GFnJGmSnaJASGQRBsDa3CREBDDC6PGs3CKu3HUXW/cMdXp+rx37wxbEkruANM5FzfPn7T5YNGzYM8+bNQ0VFBZ5++mkMHjy40+sqKSnBlClT8O2330KpVKKwsBBLly6FVCpFRkYGHnroIReWnIh8kbNBeEcBhSPrl0oEpPUMQ1rPMDyclYST2jrkXR43Y/23p/DKt6fQI0yF7MthRlrPMMgkDDOI2mKA4SLeME5DZ1i7EbA260ZHXD32gy+OJUFErsHvv/+ZO3cu8vPz0b9/fyQlJWHUqFGdWk9NTQ2ee+45KBSKlmULFy7ESy+9hLi4OMyaNQuHDh3CwIEDXVV0IvJBzgbhHQUUzqw/UROIRE0g/m94HM7X6lBQokV+iRYf7ivDuz/+ijCVDBlJEchKicSIxHAEyKV2lZnI30nELoA/uJLOllc3woTf0tncogqxi2ZVblEFJq7fYzZvdWvdwzrXH292ZiJUMvOPlTNjP7h6fUTkO/j99x96vR5ffvklvvvuO2RlZeH+++/H4MGD8cgjjzi8LpPJhKeeegpz585t6YJSU1MDnU6H+Ph4CIKAjIwM7N6929W7QUQ+xlrgbW8Q3lFA4ez6r4gMUmBSanf8fdIgbJt9HZ6b2B8jkyJQcPwCHt9yGKP/+S3mfHwQn+w/A22tzqF1E/kbtsBwAV/rp922OVxbKpkE88b06dS6XT32gzvHkvDVVjNEXYWvjiVD7c2fPx9SqRTnzp1DcXExYmNj8eSTT2LGjBk2/27z5s148803zZb16NEDN954I/r169eyrKamBsHBwS2vg4KCUFpaanPdUqkAtbprTuMqlUq67L67CuvQeZ6ow0fH9cWTnx5EQ1OrQdXlEjw6rq9d2+4epkKZhVbJ3cNUUKsDnV6/JWoAt3ULwW3DE6A3GPG/Uxex/eez+KroLHYePwZh+zGkx6oxun83jBsYg4QIfg47i99j54lRh4LJZLL2EF50TU0GVFbWeWRbanVgp7c1fHW+xZYMAoDv52U5VS53mLh+j8Vm2QAQ02oWEk/VvRgshTgqmQQLxva2eHPkzOfDH7E+zLE+zLE+zPlrfURFhdj93ttuuw0fffQRdDodbr/9dsjlcqxatQrJyckOb3fMmDGIiYkBABQWFiI1NRWvvPIKpkyZgs8++wwA8Oabb0Kv1+O+++6zuh5PXmN4G3/9THoS69B5nqpDZx5Y2XO9uGL7UXy8vxxGEyARgEmpMXhidOceBNpiMplQfL4WO4q1yC/W4uezNQCAhPAAZKdEIjtFg0HdQyDhIKB24/fYee6sQ2vXGWyB4QJi9NN25mBsrTmcAOA/s65xYSm9l6+1miEi8mVXWkcoFAoYjUa8/vrrUKsdn+kKALZt29by86hRo/D6669DqVRCLpfj9OnTiIuLw86dOzmIJxEBcG5Q9Y5aAuYWVWDrobMwXn6SaTQBn+4vx/Yj53GpQe/SloOCIKB3VDB6RwXjgREJKL/UgL1l1fj8wBm888MveGtvKSIC5chM1uD6FA2ujg+HUmZ5tAC2QiZfxgDDBWZnJlpMZ93VT9vZKaE4MB5nNyAiEotGo+l0eGHL4sWLMX/+fBgMBmRkZCAtLc3l2yCirsdWAGLpgZjeBFQ16AF0btpWe8WEqjA9PgIT+0WhukGPb09cwI5iLbYfOYdPD5T///buPL6pOt0f+Cdbm7ZpkzYthUJLl7BZZCsDIqVFUBHB6/0VoRtBHRVF0atTuYygiBuMKOpFdBBfd0SBF0pdLyozMlpTGCuyKwXUBGihQKGhBbq3yfn9UciQkq5ZTtJ83n+155wkT56e5nzPc558D4IUUtwQH4H0JC3GJ0ZAE6QA4JpbyxKJiQUMF/D097Sd7R7oSsGlowqtr1ZwWcQh8g+++hnV0xiNRuTl5bW0QF/++YqVK1d2+3m/++47288jRozA5s2bnYqTiKgrOnPhyxMdvqFKOaYM6YUpQ3qhsdmKPSerYDC23NWk4PcKyCTAiH5qpCVpsX7XSXYhk09jAcNFnGlP6ypnuwc6W3DpqELryxVcT3fNuAJPxIi6xpc/o3qaN954w/ZzVlaWiJEQEblOWxfEWjtzqQFjVhZ6ZPwWIJdiXHwExsVH4L8n63C4vBqFxgp8bzTj9e+Ptvk4diGTr2ABwwe5onugMwWXjjo9fHkeCV+7uwFPxBzz5qKON8fmL3z5M6qnGTNmjNghEBG5nKMLYm0R4Pnxm1QiQXLvUCT3DsW81AScrKrDnA17canBcs22miAFmixWKGSO580g8hYsYPggT3UPdNTp4evzSHiya8ZZPBG7ljcXdbw5Nn/i659RRETk3VpfEAsNlKGuyYoma9s3eRRj/Hb1RRWlwnGBorKuCbf+tQjjEyKQlqTFjQkRUAXyVJG8D/dKH+Sp7oGOOj04j4Tn8ETsWt5c1PHm2HxZV7ta+BlFRETu1vqC2NXHqrbKGK4ev7V3fGx9UaWuyXG3iCZIjrQkLbabzuMfR85BLpVgdJwG6UlapCVp0YvHTvISflXA6Ekt3Z7oHuio08MX55HwVTwRu5Y3F3W8OTZf1Z2uFn5GERGRp109Rr9j7U6H4zeJBC6bE6Oj46OjiyqOXKhrxjNTBsFiFfDLqYswmFomAX35WyNe/tYIuVSCZqsAbbACj6Un4Pbrenc7ZiJn+M2XnK78c5+5XA298s+99XC52KF5ralDorHo1gHoHRoICYDeoYFYdOsA24dsR+vJdR6eEA9lq3t5+/uJWFvFG28o6nhzbL6qva6WtvAzioiIxORo/AYAVgEuOx/p6PjY2YsnV8YoMqkEI/qp8V/pifj43tF4NC3eVrwAAHNtE5Zu/Q2PffIL9p6ssi0n8hS/6cBgS3f3dNTp4UvzSPgyX5t01BO8+eq6N8fmq7rb1cLPKCIiEkvr8ZtE0lK8uJqz5yMdHR87c6eUtsYoEokE+ftOX1OkEAAUHa9E0fFKqJVypCZpMTFJi7Hx4QhSyLr1Pog6y28KGGzpJl/HEzF73lzU8ebYfBW/RkVERL7o6vHbmJWFDrdx5nyko+Ojo4sqCqkEQQopLjVYOhyjtBfbX+4Ygu+NZhQazfiquByBcinGxGmQrtNiQpIWEcEB3X5fRG3xmwIGB79EPY83F3VcGZs75+/xlbmB2NVCRES+zh3nIx0dH6cOicaBsgv47OczsAqAVAL8x/XR+PPNA52KuXdoICYPjMLkgVFotlixr+wCDEYzDEYzth89Dwl+x7CYMKTrWiYB7R8RbHusr4w9yDvJli5dulTsINpitQqor29yyXOFBytQdKzSrgVKKZfiT5OSMCBKBaVS4bLX6gmYD3vuyMfWw+X402fFeOP7o/i/g2cQHqzAgCiV2x7nStw/7LkzH1fm76mqbwYAVDdaUHSsEn3UgU7/3d313O7Ix4AoFfqoA3H4TDVqGi3oHRqIP01K8okBT0/9fwkJ8e0LAK4cY/ianrpPehJz6Dx/zGFH5yNdpVQqEBsa2O7xcevhcvztxxO2W7sKAI6Zazt9rO9MzFKpBH3VQbgxIQLZo/oiXReJyJAAmMy1+PrQWWzefwr//PUcyqsbsL/sAlYXHsOFLow93DX29cd90NXcmcO2xhl+04HBlm7yJt25o4IzjyPf5c75e3xtbiBv7rghIiLqiLvOR9o7Pjp7rO9qzBKJBIN6qTColwoP3Ngfpy/Wo9BohsFkxoZdJ2BxMOdne/Fw7Eut+U0BA+Dgl7xHdw8mvnbCSc5z5/w9nBuIiIjIszx9PuKKY70zMfcJUyJzVF9kjuqLi/VNmPxWkcPtzlxqwMX6JoQpFXbLOfal1jxWwBAEAWlpaYiPjwcAjBgxAnl5eZ56eSKv0t2Dib+dcPI7ku6dv4dzAxEREfVs3nSsD1Mq0Ludu6Lc+nYRRvZTI10XiXSdFn3ClH439qWOeayAUVpaiuTkZKxZs8ZTL0nktbp7MPGmg5C7sWWwhTsnr+TEmERERD2bJ471HV1wunp9aKAMCqnENicHAATKJLh7bCwamwUYTGasLDBhZYEJA6JCEBwgQ02j5ZrX7IljX+ocjxUwiouLUV5eDr1eD6VSiaeeegqJiYmeenkir9Ldg4k/nXCyZbCFO+fv4dxAREREPZu7j/UdXXBqvf5igwVyCaBWynGxvvmaeB6ZkIDSyjoYjBUoNJlR66B4ESiT9MixL3WORBAEB1OpOCc/Px/vv/++3bIlS5bAbDZj6tSp2L17N5YvX45PPvmk3eexWq2wOJrpxQ1kMiksFmvHG/oJ5sOeO/LxfwdOYeW233D6Qj36qJXIu2Ug/mN4jNse50qe2D8GPvN3OPrvlwD47YXb3Pa63ckv/1/sMR/2emo+FAqZ2CE4panJgqqqWrHDEIVGE+y3791VmEPnMYfO84Yc3rF2Z5u3Wd0yd2yH6ztSWduIt3ccx9bDZ9FwuQiilEuRrtMiXReJcfHhUAV275q8N+TP17kzh1FRoQ6Xu6WA4UhdXR1kMhkCAgIAAKmpqdi+fTskEkmbj/Hk4II7sD3mwx7zYc8T+XD2gNcdra8SAC0HyUW3Dmj3SgX3D3vMh72emo+2Bha+ggUM/3zvrsIcOo85dJ435HDMysI2Lzj9lJfW4fquqG+yYGdJJQxGM7YfPY+quiYoZBKMjtUgXadFWpIWUarOf7XEG/Ln68QoYHjsKySrV6+GRqPBAw88gCNHjiAmJqbd4gUR+Tcxvi7Dr60QERERdV5H87O5cv42pUJ2eYLPSFisAn4+dREGoxkGUwX+8k8j/vJPI5J7h9qKGYnaYJ5v9kAeK2DMnTsXCxYsgMFggEwmw/Llyz310kTkg8SYn4EzXRMRERF1XkcXnNx1QUomlWBkPzVG9lPjv9ITcNRci0KTGQajGW/vOI63dxxHrEaJtKSWO5oMiwmDTMpiRk/gsQKGWq3G2rVrPfVyRNQDePpe6f50lxciIiIiZ3V0wckTF6QkEgmSIkOQFBmCe8fG4Vx1g62YsXl/GTbuOQlNkAITEiOQrtNibP9wKH18Hid/5rECBhGRO3R0666u8Ke7vBARERG5QkcXnDx9QSpKFYgZw2MwY3gMqhuaUXS8EgZjBQqMFdhSXI5AuRRj+4dj6rA+SOmtQnhwgMdiI+exgEFEPqujW3d1FW8rSkRERNRzqALluGVQFG4ZFIVmixV7Tl5AodEMg8mMws8OQioBhsWEtcytkaRFbHiQ2CFTB1jAICKf5Y5JNz19lYCIiIjIl7myG9ad5LKWzoux/cPx5KQknKqz4Mt9J2EwmfE/hqP4H8NRJGiDkZ6kxUSdFkN6h0LKSUC9DgsYROSzOOkmERERkXhc3Q3rKRKJBMkxYegbHI8Hx8fj1IX6y/NmVGD9rhNY99MJRIYEIC1Ji3SdFqNjNQiQS8UOm8ACBhH5ME66SURERCSennIL+hi1Elmj+iJrVF9cqGvCv46dh8FoxtbD5fj059MICZBhXHw40nRajE+IQJhSIXbIfosFDCLyWZx0k4iIiEg8PbEbVh2kwO3XReP266LR0GzF7tIqGEwVMBjN+OdvFZBJJRjVT430y90ZvcOUYofsV1jAICKfxUk3iYiIiMTT07thA+VSjE+MwPjECPz5ZgHFpy+1TABqNOPVAhNeLTBhUC8V0pO0SNNpMTAqBBLOm+FWLGAQkU/jpJtERERE4vCnblipRILrY8JwfUwY5k9IQMn52svzZpjxblEJ1haVoE9YoG3ejJF91ZDLOG+Gq7GAQURERERERF3mz92w/SOCoY8Ihv4PsTDXNGLH0ZZixue/nMFH+04hTCnH+IQIpOu0uCE+HCEBPPV2BWaRiIiIfIYgCEhLS0N8fDwAYMSIEcjLy8P+/fvx0ksvQSaTITU1FfPnzxc3UCIiP8FuWEAbEoA7r++DO6/vg7omC348XgmDyYwdJjO2Hj4LhUyCP8RpkK6LRFpiBCJVPeMrNmJgAYOIiIh8RmlpKZKTk7FmzRq75c8++yzefPNNxMbGYu7cuSguLkZycrJIURIRkb8KUshw04BI3DQgEs1WAT+fugCDsaU7Y/m237EcwNA+oZcnAY1EfEQQ583oAhYwiIiIyGcUFxejvLwcer0eSqUSTz31FHr16oXGxkbExcUBAFJTU1FUVMQCBhERiUoulWBUPw1G9dPg8fREmMy1MBhb7mjy1o7jeGvHccSFByEtSYuJOi2G9gmDTMpiRntYwCAiIiKvlJ+fj/fff99u2ZIlSzB37lxMnToVu3fvxoIFC/DWW29BpVLZtgkJCcGJEyfafW6ZTAKNJtgtcXs7mUzqt+/dVZhD5zGHzmMOnSNG/kaHh2C0Lgp5AE5fqMd3v57FPw+X46N9Zdiw+yQiQgIwaVAUbh4cjfE6LZQKmUfj6yoxcsgCBhEREXmlmTNnYubMmXbL6urqIJO1DOhGjx6N8vJyhISEoKamxrZNTU0NwsLC2n1ui0VAVVWt64P2ARpNsN++d1dhDp3HHDqPOXSO2PkLAjBtYCSmDYxEdUMzfjh2HgajGVsPnsHHe8uglEtxQ3w40pK0mJCohSZYIVqsbXFnDqOiQh0uZwGDiIiIfMbq1auh0WjwwAMP4MiRI4iJiUFoaCgUCgVKS0sRGxuLHTt2cBJPIiLyGapAOW4d3Au3Du6FJosVe09cgMFkhsFYge+NZkglwPC+6svzZmjRTxMkdsiiYQGDiIiIfMbcuXOxYMECGAwGyGQyLF++HADw3HPP4cknn4TFYkFqaiqGDx8ucqRERERdp5BJMTY+HGPjw7FgUhKOnK2GwWhGocmMNwxH8YbhKJIig5GepEWaLhJDolWQ+tEkoBJBEASxg2hLU5PFY209YrcQeRvmwx7zYY/5sMd82GM+7PXUfLTV2ukrPDnG8DY9dZ/0JObQecyh85hD5/hi/sou1NmKGftPXoBFAKJUAUi73JkxOlYDhUzqsXj4FRIiIiIiIiIiukZfdRByUvohJ6Ufquqa8K+j52EwmfFVcTk+OXAaIQEy3JgQgfQkLW5MiECosued7ve8d0REXbb1cDne3n4c5ZcaEB0aiIcnxGPqkGixwyIiIiIiIgc0QQpMS47GtORo1DdZsKu0CgaTGdtNZmz79RxkUglS+qmRrotEWlIEeocpxQ7ZJVjAIPJzWw+XY9k3v6O+2QoAOHOpAcu++R0AWMQQEYtKRERERNQZSoUME5K0mJCkhVUQcPD0JRiMFTAYzXjlOyNe+Q4Y3EuFNJ0WE3Va6CJDIPHReTNYwCByEV894Xx7+3Fb8eKK+mYr3t5+3Cfi74lYVCIiIiKi7pBKJBgWE4ZhMWF4NC0Rx821l+9oYsa7P5Rg7Q8liAkLRJouEhN1Wgzvq4Zc6jvFDBYwiFzAl084yy81dGk5uR+LSkRERETkCvHaYMRrg3H3mFhU1DRih8kMg8mMT7ie1Y8AABCLSURBVA+cwod7y6BWyjE+sWXejBviIxAcIBM75HaxgEHkAr58whkdGogzDooV0aGBIkRDgPhFJV/tJiIiIiKitkWGBOA/h/XBfw7rg9pGC34sqUShsQI7jp7H14fOIkAmwZj+4Ui7/HWUyJAAh88j5liRBQwiFxD7hNMZD0+It+seAQClXIqHJ8SLF5SfE7Oo5MvdRERERETUOcEBMkwaEIlJAyLRbBVwoOwCDEYzDJcLGpJtv2NonzCk67RIT9IiXhsMQPyxIgsYRC7gy10MVz5oeMXde4hZVPLlbiIiIiIi6jq5VIKUWA1SYjV4YmIijBU1MBjNKDSZsXr7Mazefgxx4UGYqNPiy+JyUceKLGAQuYCvdzFMHRLNk1MvImZRyZe7iYiIiIjIORKJBAOiVBgQpcL94/rjzMV6FJrOo9BUgY17ymCxCg4f56mxIgsYRC7ALgZyNbGKSr7cTURERERErtU7TIlZI2Mwa2QMLtU34//970+4UN98zXZhSjmq6pqgCVK4NR4WMIhchF0M1BP4ejcREREREblHqFKOvElJ14wVAeBCfTNu+2sRhvdVt8ybodOirzrI5TGwgEFERDbsJiIiIiKitjgaKz6U2h/xESEoNFbAYDLj9e+P4vXvj0IXGYI0nRYTdVoM7qWCRCJx+vVZwCAiIjvsJiIiIiKitlwZK2o0waiqqrUtT+4dinmpCThZVYdCkxnfG81Yt7MUf/uxFL1UAUhLaunMSInVQCGTduu1WcAgIiIiIiIiIpfopwlCTko/5KT0Q1VtE3YcM8NgNGNLcTk+PnAaIQEyjE+IQLpOixsTIqAK7HxZggUMIiIiIiIiInI5TbAC05N7Y3pyb9Q3WfBTaRUMxgpsN53HN7+eg1wqwehYDdJ0WqQlaTucOJ4FDCIiIiIiIiJyK6VChrSklkKFxSrg4OmLMBjNMJjMWPGtESu+NWJItAo3DYjEf09PdvgcLGAQERERERERkcfIpBIM76vG8L5qPJqWgOPn62AwVqDQZMbaH0pYwCAiIiIiIiIi7yKRSJCgDUaCNg73jI2DxSq0va0gCG2vJSIiIiIiIiLyAt27dwkRERERERERkQexgEFEREREREREXo8FDCIiIiIiIiLyeixgEBEREREREZHXYwGDiIiIiIiIiLweCxhERERERERE5PX8voCxbds25OXlOVz34osvIiMjA3q9Hnq9HpcuXfJwdJ7XXj42b96MjIwMzJo1CwUFBR6OzHPq6+vx6KOPIicnBw888ADOnz9/zTb+sG9YrVYsWbIEmZmZ0Ov1KCkpsVv/3XffYcaMGcjMzMTmzZtFitJzOsrHe++9h2nTptn2iaNHj4oUqWcdOHAAer3+muX+tn9c0VY+/HX/IO/wzjvvIDMzExkZGcjPz0dJSQmys7ORk5ODZ599FlarVewQvVZTUxPy8vKQlZWFnJwcmEwm5q8Lrv5MbCtv/jK+7K6rc3j48GHk5ORAr9fjvvvuQ0VFBQDmsCOOjs1btmxBZmam7XfmsH1X59BsNmPevHnIzc1FVlYWSktLAXgwh4Ife+GFF4QpU6YIjz/+uMP1WVlZgtls9nBU4mkvH2fPnhWmT58uNDQ0CBcvXrT93BP97W9/E1atWiUIgiB8+eWXwgsvvHDNNv6wb/zjH/8QFi5cKAiCIOzbt0946KGHbOsaGxuFm2++WaiqqhIaGhqEjIwM4ezZs2KF6hHt5UMQBCEvL0/45ZdfxAhNNGvXrhWmT58uzJw50265P+4fgtB2PgTBP/cP8g4//vij8OCDDwoWi0Worq4WVq1aJTz44IPCjz/+KAiCIDzzzDPCN998I3KU3mvbtm3CY489JgiCIOzYsUOYP38+89dJrT8THeXNn8aX3dE6h7m5ucKhQ4cEQRCETZs2CcuWLWMOO+Do2Hzo0CFhzpw5tmXMYfta53DhwoXCV199JQiCIBQVFQkFBQUezaFfd2CMGjUKS5cudbjOarWipKQES5YsQVZWFj7++GPPBieC9vLx888/Y+TIkQgICEBoaCji4uJw5MgRzwboIXv27MGECRMAAGlpaSgqKrJb7y/7xtV5GDFiBA4ePGhbZzKZEBcXB7VajYCAAKSkpGD37t1iheoR7eUDAIqLi7F27VpkZ2fjnXfeESNEj4uLi8Obb755zXJ/3D+AtvMB+Of+Qd5hx44dGDhwIB555BE89NBDmDhxIoqLizFmzBgALce5H374QeQovVdCQgIsFgusViuqq6shl8uZv05q/ZnoKG/+NL7sjtY5fO211zBkyBAAgMViQWBgIHPYgdY5rKysxKuvvopFixbZljGH7Wudw71796K8vBz33HMPtmzZgjFjxng0h3K3PKuXyc/Px/vvv2+3bNmyZbj99tuxc+dOh4+pra3F7Nmzce+998JisWDOnDkYOnQoBg8e7ImQ3ao7+aiurkZoaKjt95CQEFRXV7s1Tk9wlAutVmt7ryEhIdd8PaQn7xtXq66uhkqlsv0uk8nQ3NwMuVzeY/eH9rSXDwCYNm0acnJyoFKpMH/+fBQUFOCmm24SK1yPmDJlCk6ePHnNcn/cP4C28wH45/5B3qGyshKnTp3CmjVrcPLkScybNw+CIEAikQBwfJyjfwsODkZZWRmmTp2KyspKrFmzBrt27WL+OqH1Z6Kj/c5fjxed1TqHvXr1AtByArlhwwZs3LgR27dvZw7bcXUOLRYLFi9ejEWLFiEwMNC2DffD9rXeD8vKyhAWFoZ169Zh9erVePfddxEfH++xHPpFAWPmzJmYOXNmlx4TFBSEOXPmICgoCABwww034MiRIz3iJLU7+VCpVKipqbH9XlNTY7eT+ipHuZg/f77tvdbU1CAsLMxufU/eN67W+m9utVptJ+s9dX9oT3v5EAQBd999ty0H6enpOHTokN+eoPrj/tEe7h8kJo1Gg8TERAQEBCAxMRGBgYE4c+aMbb2j4xz927p165Camoq8vDycPn0ad999N5qammzrmb/Ok0r/3fh9JW88XnTd119/jb/+9a9Yu3YtIiIimMMuKC4uRklJCZYuXYqGhgYYjUa89NJLuOGGG5jDLtBoNJg0aRIAYNKkSXj99dcxdOhQj+XQr79C0p7jx48jJycHFosFTU1N2Lt3L5KTk8UOSzTDhg3Dnj170NDQgEuXLsFkMmHgwIFih+UWo0aNgsFgAAAUFhYiJSXFbr2/7BujRo1CYWEhAGD//v12f++kpCSUlJSgqqoKjY2N2L17N0aOHClWqB7RXj6qq6sxffp01NTUQBAE7Ny5E0OHDhUrVNH54/7RHu4fJKaUlBRs374dgiCgvLwcdXV1GDdunK3jsrCwEKNHjxY5Su8VFhZmG4Sr1Wo0NzfjuuuuY/66wVHe/Gl86QpffPEFNmzYgPXr1yM2NhaAf43RnTVs2DB89dVXWL9+PV577TXodDosXryYOeyilJQU27nSrl27oNPpPJpDv+jA6Ir33nsPcXFxmDx5Mu644w7MmjULCoUCd955JwYMGCB2eB53dT70ej1ycnIgCAKeeOIJu9arniQ7OxsLFy5EdnY2FAoFVq5cCcD/9o1bbrkF//rXv5CVlQVBELBs2TJs2bIFtbW1yMzMxJ///Gfcd999EAQBM2bMQHR0tNghu1VH+XjiiScwZ84cBAQEYNy4cUhPTxc7ZI/z5/3DEe4f5A1uuukm7Nq1C3fddRcEQcCSJUvQr18/PPPMM3jttdeQmJiIKVOmiB2m17rnnnuwaNEi5OTkoKmpCU888QSGDh3K/HXDwoULr8mbTCbzm/GlsywWC1566SX06dMHjz76KADgD3/4Ax577DHm0ElRUVHMYRcsXLgQTz/9ND788EOoVCqsXLkSarXaYzmUCIIguOWZiYiIiIiIiIhchF8hISIiIiIiIiKvxwIGEREREREREXk9FjCIiIiIiIiIyOuxgEFEREREREREXo8FDCIiIiIiIiLyeixgEFGnrFmzBgcPHsTkyZNRWlpqt27evHn44YcfIAgCNm7ciOzsbOj1euj1ett9ogFg/Pjx7b6GXq+3+722thbTpk3DTz/9ZFu2YMECbN68GefOncPzzz/vgndGRERE3io3NxdFRUV2y1588UXk5+dj69atyM3NhV6vR3Z2Nj7//HPbNpMmTUJDQ4OnwyUiN2MBg4g6dPr0afz2228YOnQoZsyYgS+++MK2rqKiAseOHcO4cePw0UcfYe/evVi3bh3Wr1+PVatWYfXq1di/f3+3Xjc4OBivvPIKFi1ahKqqKmzcuBEAMGvWLERFRSEkJMSuuEFEREQ9y6xZs+zGHY2NjSgoKEB4eDg+/PBDrFmzBuvXr8d7772Hr7/+Glu3bhUxWiJyNxYwiMimqakJixYtQm5uLrKzs7Fz504AwKZNmzBlyhQAwIwZM/Dll1/aHvP5558jIyMDEokEGzZswOLFixEYGAgACA8Px/z587Fp06Zux3Tddddh9uzZePzxx/HJJ5/YdV1Mnz4dH3zwQbefm4iIiLzbbbfdhp07d6Kurg4A8O2332L8+PHIz8/Hk08+idDQUACAUqnEwoULbRc7iKhnYgGDiGzy8/MRHh6OjRs34u2337YVC3766ScMGjQIABAdHY2EhATs2bMHALBlyxZkZGQAACorKxEREWH3nLGxsTh16pRTcWVkZODAgQO49dZbERQUZFuu0+mwd+9ep56biIiIvFdgYCAmT56Mbdu2AQA+/fRTZGZm4sSJE4iLi7Pb1hVjDiLybnKxAyAi7/Hbb79hz549+PnnnwEAzc3NqKysRGVlJSIjI23bXWnnlMlk6N+/v22dSqVCVVUVNBqNbduSkhL06dPHqbgWL16MRx55BJs2bcLEiRMxePBgAIBMJoNMJoPVaoVUynosERFRTzRz5kysWLECY8eOxcWLF5GcnIzo6GiUlZVBrVbbtjt+/LjTYw4i8m4c8RORTWJiIqZNm4b169fj3XffxW233Qa1Wo2IiAhcvHjRtl16ejr27duHzz77DJmZmbbls2fPxosvvojGxkYAgNlsxurVq5GVldXtmNatWweZTIb7778fzz33HPLy8mxtpIIgQC6Xs3hBRETUgw0aNAg1NTX44IMPMGPGDAAtE3+vWLEC1dXVAICamhqsWLECubm5YoZKRG7GDgwissnKysLTTz+N2bNno7q6Gjk5OZBKpRgzZgwOHDiAmJgYAC2dD5MnT8bf//53LF261PZ4vV4Pi8WC3NxcyOVySCQSPPzwwxg1ahQAoKqqyvZ1EwD44x//iOnTp7cZz/79+7Fp0yZ8/PHHAIDU1FSkpaXh+eefx/Lly/Hrr79ixIgRbsgEEREReZMZM2bglVdeQUFBAYCWu4xUV1fj/vvvh0QigdVqxV133YXbb7/d9pjs7Gzbz3fccQfuvfdej8dNRK4lEQRBEDsIIvJuZWVlePnll7Fq1Sq3vo5er8f69es7vf2KFSswadIkjB492o1RERERERGRN2DfNRF1qG/fvhg0aBB++eUXsUOxOXfuHKqrq1m8ICIiIiLyE+zAICIiIiIiIiKvxw4MIiIiIiIiIvJ6LGAQERERERERkddjAYOIiIiIiIiIvB4LGERERERERETk9VjAICIiIiIiIiKvxwIGEREREREREXm9/w/3XNhHzZtPOQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1080x576 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure(figsize=(15,8))\n",
    "sm.graphics.plot_regress_exog(model,'VOL',fig=fig)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure(figsize=(15,8))\n",
    "sm.graphics.plot_regress_exog(model,'SP',fig=fig)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure(figsize=(15,8))\n",
    "sm.graphics.plot_regress_exog(model,'WT',fig=fig)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Deletion Diagnostics (checking Outliers or Influencers)\n",
    "### Two Techniques : 1. Cook's Distance & 2. Leverage value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([6.04797739e-02, 2.80207825e-02, 1.84833331e-02, 7.27752720e-03,\n",
       "       2.96019879e-02, 4.81278004e-03, 2.07405847e-02, 2.55586700e-03,\n",
       "       4.05692942e-03, 7.54004910e-04, 2.97311924e-03, 8.72887201e-02,\n",
       "       3.32487183e-04, 3.06716174e-03, 5.27414633e-03, 5.29293219e-03,\n",
       "       1.16531605e-03, 7.63273362e-02, 6.47114749e-04, 5.79692771e-04,\n",
       "       1.13359020e-05, 1.03054091e-02, 1.53244850e-04, 3.10730928e-04,\n",
       "       1.49488694e-03, 5.85742198e-02, 1.00598054e-02, 6.55605611e-05,\n",
       "       3.30438001e-02, 1.81295962e-04, 1.33814932e-02, 9.97753151e-04,\n",
       "       4.02570308e-04, 1.13711936e-03, 2.85608656e-03, 4.41332141e-05,\n",
       "       3.27632348e-04, 4.70959014e-03, 1.21704644e-02, 8.96948188e-03,\n",
       "       2.35324656e-04, 9.75839299e-06, 4.49488700e-03, 4.48437031e-03,\n",
       "       1.02593360e-05, 4.75617324e-04, 2.22586830e-05, 4.66305687e-05,\n",
       "       1.27051048e-02, 5.33728062e-03, 2.98638028e-03, 5.00671925e-03,\n",
       "       1.29659561e-04, 1.14393086e-02, 8.61438068e-04, 2.46695414e-04,\n",
       "       1.39988281e-02, 5.43648632e-03, 1.26939574e-02, 3.75528829e-03,\n",
       "       2.73160527e-03, 1.13382659e-02, 1.34658848e-03, 3.70550296e-03,\n",
       "       2.72053841e-03, 2.36724088e-02, 5.79292874e-03, 1.71235466e-04,\n",
       "       6.23810482e-04, 1.82506221e-03, 2.41644005e-01, 6.81796865e-04,\n",
       "       9.32782333e-06, 2.11972740e-04, 2.04958742e-02, 4.06714404e-03,\n",
       "       1.08651940e+00, 1.42362225e-03, 1.81267746e-01, 1.23888350e-01,\n",
       "       3.73455378e-02])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 1. Cook's Distance: If Cook's distance > 1, then it's an outlier\n",
    "# Get influencers using cook's distance\n",
    "(c,_)=model.get_influence().cooks_distance\n",
    "c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-28-ca5cd1df4fff>:3: UserWarning: In Matplotlib 3.3 individual lines on a stem plot will be added as a LineCollection instead of individual lines. This significantly improves the performance of a stem plot. To remove this warning and switch to the new behaviour, set the \"use_line_collection\" keyword argument to True.\n",
      "  plt.stem(np.arange(len(cars)),np.round(c,3))\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the influencers using the stem plot\n",
    "fig=plt.figure(figsize=(20,7))\n",
    "plt.stem(np.arange(len(cars)),np.round(c,3))\n",
    "plt.xlabel('Row Index')\n",
    "plt.ylabel('Cooks Distance')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(76, 1.0865193998179896)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Index and value of influencer where C>1\n",
    "np.argmax(c) , np.max(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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zevRoDhw4wLffflu3q3ABZCJoXpr7NWju7x+a3zXw6oLMYifHChwczC2n1KtTUu7Gq+tYjCo2o4F28XbaxdppG2Mj2mYKaBZSncYINm3axLvvvku3bt1YtmwZTqeTBx54AFVVuffee7nlllsu7F1KkiRJtTKqCm1jbLSNsXFNh7igJ8KApo+qqorR6MsZn332GbGxsQwYMACAgoICwsPDgxagJEmSFFwBtQgGDhzInDlzyM/P59133+WOO+4AYNu2bTz//PNcffXVQQ1SkiRJCp6AWgTz5s3j+PHj3HnnnbRq1YqpU6cCcNNNN+HxeHj55ZeDGaMkSZIURAG1CDp16sTevXvJy8sjLi7OPyixatUqunXrhsEQvKp4kiRJUnBd0IKy+Pj4at/36NGjXoORJEmSGl6tiSAiIiLgokiKolBcXFxvQUmSJEkNp9ZE8OSTTzZodTxJkiQpNGpNBFUDwpIkSdKlLeAxgvz8fDZv3ozL5aJqMbIQAofDwbfffsuiRYuCFqQkSZIUPAElgo8++oi77roLp9Pp7y4SQvi/7tSpU/AilCRJkoIqoHUE06ZNo0+fPvz000/cd9993HXXXezevZs5c+ZgNpuZO3dusOOUJEmSgiSgFsG+fft47733uOyyyxg6dCizZs2ia9eudO3alcLCQqZPn87w4cODHaskSZIUBAG1CEwmk38fgk6dOrF//348Ht8mzNdddx179+4NXoSSJElSUAWUCPr06cOyZcsA6Nq1K0IINm7cCMDx48eDF50kSZIUdAF1DU2YMIGbb76ZnJwc3nnnHX73u9/xhz/8geHDh7N8+XKGDRsW7DglSZKkIAmoRXDjjTeyadMm/zjA4sWLuemmm/j+++8ZOXIkr7/+elCDlCRJkoInoB3KGhu5Q1nz0tyvQXN//yCvQX29/zrtUPavf/3rvM/5f//v/11YRGfQNI3JkyeTkZGBwWBg1qxZtG3b9qLP11R5vV4WLpzHmjUr8Xo1hg+/iUmTJoQ6LEmSLnEBJYJ777231sesVivh4eF1SgRffvklAO+88w6bN29m1qxZ/O1vf7vo8zVVixe/znffbeLFF1/F4/EwY8ZU5s2z8eCDfw11aJIkXcICSgSFhYVnHSsrK2PDhg1MnDiRJUuW1CmI66+/nsGDBwOQmZl5VrnrXzIYFKKj7XV6zcbG5XLx0UcfMGfOy1x9tW8bUEWZzNNPP8Ujj4zFarWGOMLQMRjUS+7f+0I09/cP8hoE+/0HlAiioqJqPHbnnXficDh49NFH2bJlS90CMRoZP348q1evZsGCBed8rqaJS66/cNeunVRUVNCxY7r/vaWlpeNwONiyZRvdu/cMcYShI/uHm/f7B3kNgj1GENCsoXNJSUlh9+7ddT0NAC+99BKrVq3i2WefxeFoXv/oeXk52Gw2wsPD/cfCwsKx2Wzk5OSEMDJJki51AbUICgoKzjqm6zqZmZnMmDGDDh061CmIjz/+mOzsbB566CFsNhuKojS77S+dTicmk/ms4yaTCY/HHYKIJElqLgJKBPHx8bVuUmOxWHj//ffrFMQNN9zAhAkTuOuuu/B6vUycOBGLxVKnczY1Foulxhu+x+Np1uMDkiQFX0CJ4I033jgrESiKQmRkJEOGDKlxDOFC2O125s+fX6dzNHUJCUlUVFTgcJRjt4cBUF5eRkVFBfHxiSGOTpKkS1mdp49K9SMtLQ2bzcb27VsZOPBqALZu/QmbzUbHjmkhjk6Szu2zzz5h5szna3xs4cLFpKV1YsGCV/nmmw0ADBx4NY888gSRkZENGaZUi1oTwauvvnpBJ3riiSfqHExzZrFYGTnyNl59dQ6TJ4chhGDevDnceecfml03mdT0XHfdMPr3H1jt2MyZ0ygrK6V7957MmjWNY8eO8vLLrwEwe/Z0XnrpBWbMmBOKcKVfqDURjBs3rtr3iqIghMBgMJCQkEBhYSEulwuz2UxsbKxMBPXgz39+BJfLxfjxj2MwGBg2bARjxz5KWZkcLJYaN4vFisXy81jWhg3r2bp1C//+93sYjUa++WYDTz75DF26dAXgjjvuZs6cmaEKV/qFWqeP6rru/2/lypUkJiby4Ycf4nK5yMzMpKKigi+++IKkpCRmz57dkDFfssxmM089NZGVK9ezYsVaHntsHEZjwNtKS1Kj4PV6+fvfX+O3v72TVq1aAxAREcXq1asoKyujvLyMtWtX0bVrtxBHKlUJqOhcp06dmDBhAqNHjz7rsSVLljBp0iSOHTsWlABr0lyKzgkhOFbm4eMfT3C6xIUAkiMtXN85gW4tIlBrmcl1qZGLiZrW+1+zZhUvvvgCy5atIDLSN5Hk+++/44UXplBUVIiiKLRokczf/vZ/xMWdu4pAlaZ2Depboyg6l5WVRUJCQo2P2e12ioqKLj4yqUa7s0pY9PVRilxeNE3HYlBBgeOFDr47Vkis3cxfrk6le7IcbJMal48++oARI0b6kwDAiRPHSUlJ5fnnfd1BCxfOY9q0Kcyb93qtU9OlhhNQi2D48OHk5ubyySef0LJlS//xw4cPM3LkSLp27cqHH34Y1EDPdKm3CH44Vsgr6w9jNqhE2Exomn7WcxxuDbem8/jg9vRPiQ1BlA2nOX4aPN8snPbtOzBv3sts3rwJk8nMqFG/4p577kdV61wsoE7y8nK57bYRLF78T7p16w7AyZMnuPPOX7F06Qe0bZsCwOnTWfz2t7cyf/7f6NOn73nP2xx/B87UKFoEr732GoMGDaJdu3b06NGD+Ph4cnJy2LVrF+3ateO1116rc4CSz8miCuZ9dQSbyYDFqNb6acluNmDwKiz4KoOXbrXROtrWwJFKwXTmLJyoKBvFxRXVZuE89thfKCoqYtasVzAajbz00nRcLhd//nNoK9V+++03JCYm0bVruv/Y/v37MJnM/iQA0KJFMlFR0WRmngooEUjBFdDHh7S0NPbv38+cOXPo2LEjQgi6dOnC66+/zo4dO6q1EqS6+XxPNl5dYDGe/5/GYlTRdMGnu7MbIDKpIVksVuLi4omLiyc+PoHdu3exdesWpkx5gSNHDrFt209MmTKNnj0vo1u37jz11ETee+8/OJ3OkMa9a9cOevXqXe0DTHx8Am63i+PHfx5HLCjIp6Sk2D+YLIVWwFNSIiIiGDt2LGPHjg1mPM2aw62x/lA+EdbAZwqFW41sPJzP3Ve0JswsZxhdin45C2fdujVYLBY6derif05aWifcbjf79u3hssv6hCzWw4cPMWjQkGrH0tO707lzV2bNmsajj45DVRUWLpxH585d6dWrd4gilc5U653j1ltv5ZVXXiEtLY1bb731nCdRFIX//ve/9R5cc3M4rxwBGNXAB8+qnnsot5xerepW6kNqnL744gtycrK56y7f5k+xsbG4XC6Ki4uIiooGIDvb1yosLDy7QGRDKijIJyKi+gQGo9HInDnzWLhwHk899ShCCPr1G8DYsU+GfExD8qk1EZSWlqJpGgAlJSVyZL8BVHi0i/o5UYeflRq/d999u9osnG7dutOyZSvmzJnF+PGTEUJn4cK5GAwGPB5vSGNdtmxFjcdjY+OYMuWFBo5GClStiaBq+0iA9evXN0QszV4g4wK1/2zzKtvdXOTl5fLjjz/y0EOP+I+ZzWZmzJjD889P4qabhmK12hg9+kH27t1DWFhYCKOVmqqAO5WLioooLy+nVatWeL1e5s6dy/Hjx/nVr37FkCFDzn8C6bxSY+0IAZouMATYPaTrAiEE7eKa7zZ+l7Jvv/2GpKQW1WbhgG9MYMmS9yksLMBuD0PXdRYtmk/Llq1CFGng3F6dE0UV5JS50HSBzWSgTbSNhHCz7HkIkYASwYYNG7jlllsYM2YML730Eo888giLFy8mJSWFRYsW8fbbb/O73/0u2LFe8qJsJgakxvBtRgHRdlNAP1Pi8jIgJYZoW2DPl5qWXbt20Lfv5dVukCUlJTzzzBNMmfICLVokA7B27Wri4uJJTW0XqlDPSQjB7tOlfLYnm59OFKOqCgiBwDfGqAtBmNnIiK6JDO0UT6z97E2apOAJqC9i8uTJXHnllTzxxBMUFhbyxhtvMG7cOI4cOcITTzzBzJmyeFR9uSU9CQBPDYvIfsmj6SDg5sqfkS49hw8fOqsMeWRkJG63mwULXuXEieN8//13zJ37EqNHP9goP1EXOty8tPYQ01cdYOvJYiJtRiKtRiJtJqJsJiKtRqJtJoQQvL8tk7Ef7mLN/lwCWOsq1ZOAEsGPP/7IU089RVJSEp999hler5e77roLgFtuuYX9+/cHNcjmpEN8GPcNaEupS8PtrT0ZuL06pU6Ne/u3IS0hvNbnSU1bQUF+jRs/TZs2C6ezgvvuu4s5c2YxevSD3Hbbr0MQ4bkdzXfw5Me72XaqmCibkSibqdYaWWajSozdhNmgsHjTMeZ9dQRvAB+IpLoLqGvIbrfjcrkAWLFiBcnJyfTs2ROAEydOEBt7aZc4aGg3dEnEZjLwj2+PUehwowqBuXIg2a3peDSB2aDy8DWpDOoYWNEuqWlatmxFjeUFWrZsxauvLgxRVIHJKnEydeV+vLp+QV2XZqNKjEHh24xCDIrCI9c2zu6uS0lAiWDIkCFMmTKFnTt38sEHH/DXv/qWsX/88cdMmjSJG264IahBNkfXdIjjirbR7M5z8P6WE+RW7knQKsrGiK6J9E+JwWqSM4WkxknTBQu+ysDl1YmyXfhCR0VRiLEb+SajgMvbRHFzjJwNFUwBFZ3Lzs7m3nvvZePGjVx55ZW89957REdHk5KSQlpaGu+88w7x8Q33yfRSLzp3puZebAvkNajp/Wu6YEdmCWv253K6xIlL07GbDLSLC+OGLgm0j7OHdLxg7YFc/mfTMWJsxjrF4fJqCKGw9IH+eCqa7wZNjaLoXFJSEp9//vlZx3/66Sfi4uLqFtklLrvUxZcHczmYWw5Ax/gwhnZKIClCbj8pXTivpvP53hw+2XWaEqcXVQWzwVecsNTl5VhRBV8dzqNVlI3f9EpmQGpMgycEIQQf7cjCZqq9aGKgLEYDRQ4PGw/lMaCVLLkeLBfUZvv6669Zu3YtWVlZTJw4kV27dtG7d2+Sk5ODFV+T5dF0/vfb43x1KA8BmA2+P4hdWaX8d+dpru4Qy58Gpvr7/iXpfMrdXl5ed4hdWWWEW9QapxjbTAaEEOSUOZm7/ggjuiVyT782DbqJ0eE8B/nlHiKt9dN1aTaqLN+eKRNBEAWUCCoqKvj973/Pp59+SmRkJKWlpfzpT39i7ty57Nixg/Xr19O1a9eLCsDj8TBx4kROnTqF2+1mzJgxXHfddRd1rsZCF4L564/w/fFCou3VZ0mEVT6+4VAB5S6NcUM7Brx4TGq+3F6dl9YcYn9OGbH2c3e3KIpCmNmIzSj4fG8OCnBPvzYN1jLIKHCgC1Fvr2c1qRzNd+D26vKDU5AEdFXHjx/P5s2b2bhxI3l5ef75vUuWLKFVq1ZMmDDhogNYvnw50dHR/Oc//+Ef//gHL7zQ9OuRbD1ZzA8nioix1zxVTq0cCPvpZDE/npC7u0nn9/ZPp9iXXUb0BfS5q6pCtNXIZ3uy+eF4w/2eHcotoz4/26iKgkFVOF3qqr+TStUE1CJ45513mD17NldddZW/EB34xg6effZZHnzwwYsOYPjw4dx4443+7w2G8zcnDQaF6OjGW1Jh1dpDWEwGTKZzX16LV7DqQB439Kq9LIDBoDbq99oQmvs1cGk6aw/lERNuxmS48E/ENh0+2Ztzzt+z+uRVFExGA8Z6rH+legVmm7nZ/h4E+28goERQXl5OYmJijY/ZbLY6bYZRVSSrrKyMsWPH8thjj533ZzRNhGQWSanTy7dHC8gscWIzGrisdRQtIy1szyyhzKVhNxtIbxHBtuOFxNhNeL21VwTVdEGFy8P6A7mMf387HRPCGNwxjoTw6oPIzX3GDMhr8N2pElxuDbtRPefvVG2sBjh4upRth/NIbYCaVIqm4/FqeL31140jhMBZ7qKoqHlOmW4Us4YGDBjA/PnzueGGG/zN0qr/v/HGG/Tr169OwWVlZfHwww/zhz/8gZEjR9bpXMGgC8HbP57k09056JXdYpqu83/fHcet6cSHmaGqi0IAACAASURBVFEVBVXxlYQudHiItpmosQUvILfcTW6ZCyF8595+qphtp4r5cFumHESWzrLsp1N1qkxb9be6en8uD16Zcp5n112H+DA2HMmvt/MJIfDqghaRcqZdsASUCGbPns2gQYPo0qWLPxksWrSIffv2sWXLFtatW3fRAeTl5XHfffcxZcoUBg4ceNHnCaY3vzvOqv25RFmNGFQFIQTHCisq9wAQ5JW7aR9nx2xU8WqCk0UVZBQ4aBdnP2uMIKfMRW6Z2zdArAgUoRBV2e+rC8GGwwWUOjWeuq7jBW1QI12ahPD9PkWY6/bBwGxUOVrQMK2qlFg7xnrccMbl1UmOssoFlEEU0L/W5Zdfzvfff88VV1zBRx99hMFg4OOPPyY+Pp5vvvmmTjfwv//975SUlLBo0SLuvvtu7r777pDvu3qm44UVrN6fS3RlEgAoqvBQ7tIwqGA0+PYNzqlc+Ws0KMTaTZS7NArKqy+AcXl1csvcGFUFRfF1D0VZfx78UxWFGJuRrSeL+f5YYcO+UalR8uqiXmbgqErDbV7UKTEcu9mA6xy1si6E06Nzc/cW9XIuqWYBryPo1q0bb7/9do2PeTweTKaLK4M8efJkJk+efFE/2xBW78tB4JuBAb5PaHnlHhTl5ya3UVUocXrQdAsGVSEuzEJhhYe8cg9xYT/XWC90eHwnVajsYlKIC6tebldRFMxGheW7TnNlO1nDqbkzqgoKvlZoXZKBLnzTMBuCUVW4NT2JJT/WrUsLfOtxDKrC0C6J4A7t7muXsvP+K+3bt499+/bV+viHH3540WsImoK9OWXV/oA0XeD26tWnx1V+XfUJyGpSaRVlw63pFDs9/um2JU4PamVLQNchOdJSY3M3zGwgI9+Bwy23n2zuFEUhIcJc50/Xbk0nOdJaT1Gd3/CuSSRFWCh1XfzNWwhBqUvjj1e0JlruTxBUtSaCrKwsBgwYQHp6Ounp6QwYMIDc3Fz/49u3b2fIkCH89re/JT+//gaGGptfXqCqwkzn+3QWYzeRFG4hxm6muMJLUYUHtybQha8kQJsYK7FhNf9yK4qv68gtS/BKwK09W1LhufjfBSEECLiuU0I9RnVuZqPKY4PagwDnRXRJCSEoqvCS3iKCG7vUPGNRqj+1JoKnn36aHTt2MGHCBGbOnMmRI0cYN24cAFOnTuWKK67gm2++YcyYMRw8eLDBAm5oPVpG4jzjj9CoKqiVA7tVqr48sxms6QK72cAro9KZcUtXHr66HWkJYSRHWegQbyfSWntXmqYLVEUhzCwHxyS4rmuivyV5MZxenfhwC12TGnbfig7xYTxzfRoeTVByRsv4fDRdUOjw0CkxnKev69ig5TGaq1rHCNatW8eUKVN45plnAEhPT+ePf/wjTzzxBPPmzWPYsGHMnz+fLl26NFiwoXB95wRW7Mn27yNcVR43v9yDWnmf1nRBjN1UrVREidPL4I7x2M1GOsQb6RAfhtur84/vjp23NVH1sxezeEi69MTYzQxMjeWbjAJiAtzCtIoQAodb4499W4ekGmmPlpHMGtmN1zYc4XhhBRajWmsxOk0XlLi8KMBtPZP5Ta+Wchp1A6n1Kufl5TFgwAD/99deey0lJSX8z//8D2+++SarVq265JMAQHKklV/1TKaowuPfPjIuzIxBVdB0gVcTmAwKiWcsBHO4NcxGlVE9qs90GNguFrvJQPk5+v49mm/8YUQ32RyWfja6f1sSwy0UV3gC/hkhBIUVXq5oG83QtIbrFvqltjE2Zo3sxpirUokPM1Ps9FLi9JJf5ia/3E2hw0Op00u5W+Oa9rG8OLIbf7i8tUwCDajWFoHH48Fu/3kVYtUK4Jdeeol77rkn+JE1Ir+9rCVhZiPvbj1FuduDVxNE20zkl7t9SSDCgiYELpeGR/N1CT1zfRoto6oPztnNBiYMS2PaqgMUOTxEWo3VZiOVuTS8uuDPV6WSGts8l9JLNYuwGpkyvBPTVh0gp9RF5BnTmWvi0XRKnV4uax3F2Gvbh7ywoVFVGJwWz6COcWSXujheWEFOmQtv5d9LmxgbKTF27LI7NCQueOugxrroK5gUReHm9CSu75zA1pNF5Jd7MBkU0hLCOVHkYPX+PIoqPERajFzXKZ6B7WKx1bL4JS0hnFm3dOW9rZn8cLzQ3/+p6YJOieH8vndL0pNluV3pbAnhFmbe3JV//3CCr48UoAmBzaRW7kfgmyLq9Gh4dIHFqPLby1pye6+WjWphoqIotIi00qIBZzBJ53fBiUCtxxWDTY3FqDIgtfrc/nZxdq7tcGG7s7WOtvHEkA4UOTycKKpAF4LECEuDTu+TmqYIq5G/XNOOu69ow4bD+azcm0O+w41H07EYVdpE27ilewuuaBMtu1akgJ0zEbzyyiskJSUB+Ef8Z8+eTUJC9f5GRVGYP39+kEK8dEXbTTVuLiJJ5xNhNXJzehI3p//89xnKrSmlpq3WPYtTU1MD/sVSFIUjR47Ua2DnIvcsbl6a+zVo7u8f5DUIWfXRo0eP1vlFJakuGuOnXE3T+N///TsrVizH7XbRv/9AnnzyGSIjo9i5cztjxtxf7fk2m43VqzeGKFpJCswFjxFI1Z0sqiC3zI3FqJKWECbn/tdRocPN+oP5rNyXQ6HDg9Gg0LttDDekxdGjZWTIFxctXryIlSs/5dlnpxEVFcXMmdOYM2cWL7zwIkePZtChQ0defXWh//nNeUxNajpkIrhIh/PK+d9vj5ORX45B9a00thoN3N4zmZHdkxrdJ9mm4McTRcxdfwSPpmM3G4ixGxECtp8s5sejBaQnRzBuaMdaZ2QFW3l5Ge+//zZTp87kiiv6AzB27BPMnj0Tr9dLRsZhUlPbExd3YZMHJCnU5MeVi3Awt4wpn+/jeKGDKJuRCKuRqMqNaJZsOcH/fXc84OX0ks/e7FJeXncIo+qr02Qx+lafqqpCtN1ElM3IzswSXl53qFp5j4a0ffs2FEXhyiuv9h/r06cv77yzDKPRSEbGEVJSUkMSmyTVhWwRXCAhBIu+PooChFurXz6zUSVaNbF6fy6D0+LpGB8WmiCboH9uPoFBVWrdfMRX2sPE7qxSdmaW0KtVVANHCCdPniApqQXffLORN9/8B0VFhfTvP5BHHnmC8PBwMjKOYLPZueeeOykpKeayy/rw178+JlsIUqMnWwQX6HC+g6xiZ60F4VRVAQW+2JfTwJE1XUfzHRwrcJy3yJ6vhQCf7s5uoMiqczjKycvL45///AePPPI4zz03nQMH9jF16kTKysrIy8vF6/XyzDOTefbZaWRlZfLkk2PxemUdfalxq7VF8NNPP13Qifr06VPnYJqCrGJntU1pamIzqhzJa75T3S7UobxyBOcv7Q0QZjay+3Rp8IOqgdFoxOEoZ+LEqaSldQLgmWemcP/9f6SoqJBVq9ZjtdowGHwJbebMOdx22wi2bv3RP6YgSY1RrYmgb9++tf5h1jStT9OaxyYqJoOCfyeaWmiCOu/MdD6aLtiRWcL6Q77yFgnhFoamxdM1KbzJDVR7dJ1Au/1Vxbd9YyimlsbH+xZStmvX3n8sNTUVgNOns2jduk2158fGxhEZGUVurmwdSo1brYngyy+/9H+dkZHBmDFj+NOf/sSvf/1rWrRoQX5+PitWrOD1119n0aJFDRJsY9CthW9BRlVZ6pp4vDpXdwjeNpMFDjczvjjAqSJf68RoUNifXcbXh/PpkhTOU9d1JMzcdIZ/Ymwmf/G983FrglibKTQllXv0AuDAgX1069YdgIwM30JKq9XKsGHX8u9/v0eLFr6qs6dPn6a4uIiUlHYNHqskXYha7xaDBg3yfz1p0iTGjx/P1KlTqz1n4MCBREREMGfOHO68886gBdmYRFpNDE6LY+3+PGLsxrNuSOVuDZvJwDXt44Ly+h5N54VVB8gqdlYvT2H2tdT2nC5jztpDPDe8c5NpGVzWKgqTQcGj6eddh+Fwa9zaJzQbmbdq1ZrBg4cya9Y0xo+fjNFoYvbsGQwceBWdOnUhPj6eWbOm8cgjj+N2u5g372V6976c9PTuIYlXkgIVUP/FTz/9xJVXXlnjY7169WL//v31GlRjd2+/tvRsGUFhhZdSpxePpuP0aBQ6PBgUmHhDGuGW4Hwi//FE0dlJoFLVpjn7cso4kFMelNcPBqvJwI1dEih1auecduv0aJgNKkM6hm4WzqRJz9OrV2+eeuoxHn30z7Rr14HnnpuB2Wzm5ZcXYLfb+Otf/8QTT/yVNm3aMn36SyGLVZICVWutoTP16dOHrl27snTp0mrHdV1n1KhR5Ofns2nTpqAF+UuNodaQVxdsPVnEit05nCquwGYyMLhjHEPS4ompx422f1lj5PmV+zmQW0bEORJNkcPD4LR4/nxVar3FEWxur87M1QfYc7qMCKuhWsvAYFApcrjRdHh6aAf6tIkOYaTVub06JU6Pf3prMFY+N/c6OyCvQchqDZ1p+vTpjBo1iu3btzN8+HDi4+PJycnhk08+ITMzk9WrV9c5wO3bt/Pyyy/z73//u87nagjlLi85ZW6SIsx0iLczMDWWDvH2oHfHFJS7MZ+n+8RkUMgrcwc1jvpmNqpMHNaJ97ad4ot9uZS7vei6QFF8iaBttI3R/drSuYH33a1NXpmLFXuyWXsgD48mAEGE1cTIyn0rQrX6WZIuRkCJ4KabbmLjxo3Mnj2bJUuWUFhYSFxcHEOGDGHSpEl069atTkH84x//YPny5dhstjqdp6GsP5jH4m+PVW4y75sltGJ3Nt1bRjJuSIdaF0XVhyibiXyH+5yzkjyVeyg3NWajyh/7tuE3vVqy/VQJhRUejKpCn/ZxxJoaz5KXjHwHz6/cT4VHI9xi8O+q5fRo/PuHE3x5MI+pIzoTaW16/wZS8xRQ11CwrVq1is6dO/P000/z3nvvnff5uq6jaaEJe+vxQib9dzfhFmO1jT+EEBSUuxnYPo4pt9QtMZ7JYFDRKvdKBli3L5tXVh8kJqzm7ichBEUVHmaM6s5ljagLpS5+eQ1Cqczl5YF/baHCoxFRy42+oNxN95aRvPSrHvXSQmxM7z9Umvs1qK/3b6rlQ2rAI5rFxcW89tprrF27ltOnT/PBBx/w6aef0qtXL4YPH16n4G688UZOnjwZ8PM1TYSsv/D/Nh5BEQIVgddbfe1EpMXApkN57D6WT6uo+mnd/LJvsFucnWirkfxSJ1G26jciIQTFFV5S4+ykhJsumT7VxtQ/vHp/DoXlbmLsprP+/atEmFV2nChi+5F8UuPqvvd0Y3r/odLcr0GwxwgCam8fPXqUHj168OqrrxIZGcmBAwdwuVzs2LGDkSNH8vnnn9c5wKag3O3lYG454Zba6+FowrfQK1isJgPP3tiJWLuZIoeHMpcXp0ejxOml2OmlTYyNZ65PazJTR5uaVXtzz7tYUFEUBLD+UF7DBCVJdRRQi+DRRx8lOTmZtWvXYrVaMZt93RJLly7F4/Ewbdo0RowYEdRAGwOPJs5bXgJ8C8qCqUWklbm3d+eHE0Ws2Z9LcYWH+HAzN3ZJpFerqGqblXs0nR9PFHEgtxyDotCzZSTpyREhr+vfVBU43JgN5792RoNCTpmrASKSpLoLKBGsW7eOJUuWEB4eflYpiYceeojbbrstKME1JuVuL98ezSen1MWJwgrMBpVIq5G4MHO1sQKDqtAmpu7dAWc6mu/gQG4ZAB0TwmgXa8dsVLmqXSxXtat9BfP+HN/isjK3FyFAIPhk92mSI6w8MyyNpAhLvcZZF1klTradKsbl0UmKtHB568a5+brFqOL06uf9w9F1gb0Jre6WmreAflPNZjMVFRU1PlZQUIDFUvcbSuvWrQMaKA6F44UVTP18Hxn5Dio8GpoAt6ZR7tbId3hIjrQQF2am3OUlymqiZ8vIenndIoeH6Wu2s+tkMboQCEBVFDrGh/Hk0A7EnmO9QlaJk+lfHEABon8xlnC6zMXUz/fxym3d/TNeQsXh1nh9YwZbThT59xkwKAoWk8qDA1O4OkgrtC/WVe3i+GT36QBqSSkMTI1pkJgkqa4C+sh18803M3nyZA4ePOg/pigKBQUFzJo1ixtvvDFoAYaaR9OZ8cUBThRW4NUFFqOCUf257Jzbq5NV7CSrxImiKDw1tGOtNYguhMurM3XlPvZklRJlMxIbZiYuzEy0zcjhvHKmfr4fp+fswUq317fKefnOLNxevcYbfZTVSIHDwzcZ+XWOsy40XfDimoP8cKKIaJuvdRUXZia6cmHWgq8y2HysIKQx/tL1neNRFV85jNo43L5ppaHYM0GSLkZALYJXXnmFwYMHk56eTlpaGgD3338/GRkZxMbGMmfOnKAGGUo/nigi3+HG6dUxqKAoKhZF4NUFXk2gC986gkiLidm3dqNFpLVeXnfzsQKySlwkRFqrzU5RFN+OXTmlLr49WsCQNF9FzJ2ZJXy4PZM9p8sAQXapi4Rwc61VOi1GlbUH8hjWObFe4r0Y2zOL2Z9TRozt7JpNFqOKLgRvbj7BsB6tGjSuc21Qb8dF1I532LPtexSjibjug0jodwuKoiKEoMzl+7caN6RjtbEaSWrMAmoRJCQk8OOPP/Laa6/Rs2dPrr/+ejp06MDUqVPZtm0bLVu2DHacIbMrqxS3R682SKwoCiaDis1swGJUiLQY8Gh6vSUBgHUH8ipLXtfMZFBYe8A3K2XN/lymf3GAg7nlxNiNRNtMeHVBdqmbzGJnjfV7DKriv2mFyqq9OZXJteb3aTMZKK7wsPd08GZh1WTx4kV89tlynn12GgsW/J1jx44xZ84sACZOfIqy7GP8+enppN78MIUHt3BswwcUOTwUVXhpG2Pj+Zu6NJoV0JIUiIBHs6xWKw899BAPPfRQteNlZWVs2LCBa6+9tt6DawyMlTuO1bbsTlEU/3/1pajCw6kiJ26vjqbX/MJGg0qpy0t+uZv/++4Y4Zaf6/Moim+VrqYLiiq8RFo1In6xrabLq5GWENqtNHPLzl8uQwEKHB5aNdBK6XNtUL937262bfuJN95YQqdOXbjjBsGnPVvw6tQnGD1mDJ1bxpIaW78TBSSpIQTUIjAYDNx///24XGdPh9u9ezdDhgyp98AaglfT2Z1Vwg/HCzlVXPNgeO/WUVgMamUyOPumLASYDCp9Wte9P9jp0Vi0MYMx723naGEFp4qd7MkqIbvEddZrOz0abWPsfHUoD70yhjPF2c2+5KVAfnn1ukNCCDQdbu6WVOeY6yLKZsJTS6KrIlCCVsm1JufaoD4rKwuLxUKnTl0A38D9jQN74/V6SPLmyCQgNVkB/YUJIVi6dCnbtm3jgw8+oF27pr/RxsbD+byx+Tiuyjn/ui7onBjOI9e2Iz7851lQPVpG0jbWRrHTQ4VHx6D+3OdeVWvIbjYwqkfdauRXDZzuyS4jymrEZFDJyNdQgbxyN15dp1W0b7WyLnxjE8O7JPD53pwa+6Jj7SZfzG4N5xnrGjyaTqlTo19KND3qaXbTxbq+cwJ7s2vfdtLt1bGaVLq3jKS81NkgMZ1rg/rY2FhcLhfFxUVERfnKd2Rn+/ZPLixsXIPaknQhAp6ovXTpUlRV5fLLL+fTTz8NZkxBtymjgIUbMwCItBqJtBqJshnZn1vGs5/to8z182bjqqIw6YZOdE+OxGxUcGsCl0fH5fVtr5gYYeGRa9vRKbFufcI7MkvYl+0bODWoCnaTwVfGQPgWsRVVeHF5f973YHDHeLq1iCDcYkCroaWiqgqpsXYirEaEEJQ4vZQ4vXg0wa96JfPY4A4hX1R2RZtoksItFFd4znrMq/sGXu/o3eq8m9XUp3NtUN+tW3datmzFnDmzKC0tpaSkmIUL52IwGPB45Ab1UtMVcJu7TZs2fP311/4FZOPHj2f69OmoauNb9HMuuhD864cT2ExqtbngiqIQbTOR7/Dw1eH8at0msXYzL9+Wzs7MEtYdzONInoNIq4H+KTEM6hh/Vs2fi/Hlwbzqq5YVaBlpJcxqJLvYhdOrcbrESUqsnTv6tOaGLgkoisJV7eJYfyi/xtlBBlUh0mri//VrQ+9WUSiKLzkEez/lQJmNKlOGd2bW6oOcLK5ACF/MWmX56d/1bskNXRIaNKZzbVCfk5PNjBlzeP75Sdx001CsVhujRz/I3r17CAsL7XiLJNXFBXW+WiwW/vnPf9KnTx/GjRvH999/z6RJk4IVW1AcL6iguMJT683balRZfzDvrP5zVVHo1SrqouaGu7w6W44XsTe7FJvJwBVto0lLCKt24y52ejD+cpaQAnFhFqLMRvLKXQzuGM9frmlX7ZN8enIEHePDOJhbTvQZ0zCFEJS6vERYjYzomnTWorLGIi7MzOxR3dhzupRNGQU4PDop0Tau6RhHfC0VVoPpfBvU9+3bjyVL3qewsAC7PQxd11m0aD4tWzbsFFdJqk8XNQo3duxYevbsye9//3t+/etf13dMQeXS9HN2iRhUpVqfepX8cje7skrRhKBDnB1dwNdH8imq8NAuLoyr28fWeLM9nFfOzNUHKXf7ug50XfDJrtN0T45g3NCO/r0LUmPt7Msuw27yLUhyazoGVSHa7huoNqgqnZPCz4pdVRSeuT6NeeuPsCurBE0IhPDVukkKt/DUdR0bbRKooioK3ZMj6Z4c2jELOPcG9ZGRkfzlLw8wZcoLtGiRDMDatauJi4snNbXpj5tJzVdAiWDQoEFERlb/Ix08eDA//PADt99+O9u2bQtKcMHQKsqKEL7B2ZpWADs8GpefUcffq+n83+bjfFk5Z1/gKzym6YJYuxmzUeHrIwW8/eNJxl7bjv6pP9f+KXV6mf7FAbyaXu1mLIRgR2Yp/7PpGI8O8n3yvK5TAp/sOs2BnDL/zRwFThU7ibebsJoNDEytua5QuMXI5Bs7cbywgt2nS/BqgvbxYXRLCr/gaa05pS52ZZXg1QXt48IaZNe1xuR8G9S73W4WLHiVMWMeISsrk7lzX+KBB8Y0q2skXXrqvDGNx+MhMzOTlJSU+oopgNes257Ff//6KOsO5hJjN1X7A/ZoOuVujZm3dKV9nK/P9382HWXN/jxibEZUVSG31E12qRMU34Kn9nG+G6XLq+Py6Lx4azfaxvhm96zYnc2/fjhR425heuUA7sLf9CQ+zEx2qYsH3t5KgcODQVWoylGa7kta9w9oy/0Dg3eN3V6df3x7jI1H8n0F6oRAVRRS4+yMG9oxJN00VRq6Fn1FRQWvvz6PtWtXo+kaV155LeOeHE94eDiZmad4+eVZ7Ny5nejoWO644w/8+te/D2o8zb0WP8hrELI9i8eOHcu4ceNo27YtY8eOPefJFUVh/vz5dYuwAd3Tvw2nip0cyC3DoCoYVd+NXFXggQFt/Ukgv9zNlwd/TgK6gDyHG6NBBXyzh8rdGuEWIxajSoVb47M92f5N4388UVTr6mBVUVCAQ7llxIfF8vmebOxmI5E2E3llbspdGroQ2MwGoqxGtp0qqbVcRH3432+P8dWhPH+dH/Alg6P5Dl5YuZ85o9IbZTXQYLDZbAy9Ywx5nUdxJN/BHgHT1h7jd71b0bdtK159dWGoQ5SkelVrIvjkk0+4//77adu2LcuXLz/nDaipJQKbycBzIzqz9WQR6w7kUeby0iE+jOs7J9C6cq5+dqmLxZuOkl3iotjkIdpmwmTw1ZNRVQVQEPg+1YdbjP4FX6v25mAyKPQIqL9bQaksX/dNRgFhZgMGteqIb42CRxPklLoocXo5VuAgNa7+Z6fklrnYcDi/WhKAn+saZZe6+OlkEQNq6Zq61Kzcm80b353AbFSIsfn+RLJKnMxed4i7+7ZmZPe6rRmRpMam1kSQkZHh//ro0aMNEUuDMqoKV7SN4Yq2Z5cK3nysgPlfZVBS4cGt6WiVxcRMBqXyhv/zzVIIXwG64wUOHG4NVVVYvS+X1ftzUfB1udS0MlbXBSD8NWm8msCgwLHCCircGiZjVbkIBaGqVHg03tx8gudv6lLv12JXVqm/xHVNVNW39iJYiUAIwYGcclbuy+ZUkZO4MDPXd07gslZR9VLJ9UIUOTy89f1JIqyGausXwixGLJrO0h9PMrBdbEi7yiSpvgXU1h86dCj79u2r8bEdO3Zw2WWX1WtQoZRX5mL+VxlYjCoJERZURcGgKhhU36dzTYczqyKEW4ycLKqgwuObaRRfWUY52mZCF1BY4aG4onqJB134agANTUvwDyKnJ0eQX+FbCfzLaaS6EBhVhb3ZpZwsqrkURl3UVs+oiqL4FtIFgxCCf285yXOf7+Pbo4Vkl7nYnlnC7LWHeHndIbwNvGH5NxkF6LqocRGb0aAiBHxzOLTluyWpvtXaIli+fDler2/K4/r161m+fDl79uw563lr1qzh8OHDwYuwga09kIdXE5gMvhtfmNlAeeXN2aBWlp3WdHRFwWhQMBtVyl0aIDAaVGLO2Cwmxu6rAmpSDRRVePw3XFVRuKZDLPf2b+N/7sjuLVhzIK/GFoeuQ0K4GVDYc7rU331VGyEEh/LKOV3iIsJiJD054pyrczvEh6FU/lxNXYBeTdAq0srOzBISIyz1urPZlhNFfLorm+jKcRgAm8kXy48nivlkdzajr22YSp5eTedUUQW+uWE1UxU4XSq3oJQuLbUmgnXr1rFgwQLA94nwmWeeqfUk53qsMTqa72DNgVxOFjlJjDBzXVoCnRLDEMAX+3PILHZStWBaQUFVFLxnfCK2mw24vL7powXlbnQhsJoMtIm2nTU4bFQVhnaOp3erKI4WODAbVS5rFUXyL0pWd04MZ0BKDF/sz8FbuTeyEL5KopFWIwnhZgocnlqroFY5XljB3PWHfRvlVL4Dq0nlTwNTGFjLtpapsTbSEioXpf1ihlN+uZu8MjfLd59m5b4cNF3QtUUEf7k6lYTwuieE5TtPYzYq/iRQRVEUwiwGPt2dzd1XBXeO/uG8ct7f77rfCwAAIABJREFUlsnWk8WUOL2Uu70oiq8o3i8Toy4gMUJ2C0mXlloTwezZs3n88ccRQtC+fXuWLVtG7969qz3HYDAQFRVFRETNU5IaGyEEH2zL5MPtWQjAbFDYly346lA+Q9LisRgUMvIdlQu4qmbO+LpOoqxGjAZfX/1DV6UwrFMCe7LL2HK8iDUHckkKt5z5Qb7aa1oMakCrkn/VK5ldWcXoAt++uKpCXLgFkyJwenU8Xp3IytpBNX1yL3C4ee7zfbi9OlHWn1cZu7w68746gt1c865ZiqLw5JCOTFu1n8xiJ4ria7U4PBq5ZW6SI8zEVk61FUKwN7uUySv2MWdUNyKtdVusllHgwGaqebtMi1GlqMJDidMbeFGsC7Q7q4QZqw8ihCDKZiTMbOBAroeTxU5cXkFS5M/Jrqr0xVXtGtf2mZJUV7UmArPZ7F8bkJGRQcuWLTGZGvcK1fPZfqqED7ZnEWk1VhuE1IXgi305uL06LSIsnChy+m+2iuL7VF/i8tI22kaLSAu39UhGVRT6p8TQKSGMjUfy0Svn3Z+paoZRn9bRvwylRt2TI0iJtZNZ7CSxsvvFo8ORfAcOj4bNqDJ/wxE+2mnj4avbkfKLsser9+XicGtnrVuwGFU8ms7bP52qNRlF203MHpXO1pNFbMooxK3pHMwpw2xQq52vqiZTocPDugN53NYzOaD3Vhur0VDr4j69cmGdxajiObsuXZ3pQrBwYwZGVfFvNG82KiRFWMkucZJb5iLC4KHg2/cpOeJbNNm5Zz+st3cC6q97TJJCLaCVxSkpKezbt4/PP/+c8vJydL36AJ6iKDz77LNBCbA+/XfXaYyqctZNR1UUdF1Q7PTSMsqC3WzA4db8JacFAk0Iipxexg5qX+2GH2M3c32nBL7Yl0OUzXRGS0JQ6PDSOtqKw+3lZFEF2aUuHG6NFpEWOsaHnfWpXlUUJg7rxMzVBzhV7MTt0cgp96ALQZjZQGqsHVWBk0VOnvt8Py+O7FptV7RvMgqwmWr+7BxmNpCR///be+84K8qz//89M6efs73BAsvSlg7SFaSJIGLAQlAsmGgejYkaKxrRCBpAYiWWxJgYY6K/5zG2n6ARBGU1qCgoRXqvC9vb6Wdm7u8fs3tk2V22syw779eLFzBz5t57ZufMNfdVPpefsmCk1rf4kzOpfGGVm/+/TcQ7a75FnFaZNXuabggm9krmgx9OkFhDjUJ5UOW8TrG47RZKTgm4Nwd78nyUBFTiTjnHFLcNmyJxrCTI4c/eQCrPo9eV93Fx72Q+efNF/vCH37No0bnbntWk/VEvQ/Dqq69y6623AuDxeKopjjbFEOi6zoIFC9i1axc2m42FCxe2WJXyvgIfzlOauUc0QYE3RJ43hKrDnnwfSW4bNhlKQ1q0NZmMxGX9UhnZtXq66c9HZSBLEqt25VVskfCHDcnnYyVBFqzYRaE/jF1RSHQbxiI91sG9E3tUC/wmuW08dbmhdPrXrw8R1ATJbhsuqxJ1PcU6LBT7IyzbeoJbR2dGj1X10xecSZLxmfoQVqu25zwVuRZNpoZyab9UsvcWUBKIRN1ZQgi8Fam41w7t3OSfURslwUhN3jyojA8AOce38Zt7HuCKaZchSRJJeilPPbW4xeZkYtIa1Mv1unjxYq688kqKioooLS2luLi4yp+iosY35Vi9ejXhcJi33nqL++67jyVLljR6rLpwWpUqqZIRTWd/oS8q6yBh+IFzy8PoSGSluMlMdNEt0Ul6nJ0JvZJrHNciS9x8fgZ/vnowd47rztS+KVhkiZQYG4pMdPywplPkj+CxKewr9PHzNzdy/T+/4853fuDDbbkEIkYP4Uql05KASkaiC5dNqRZ/iLErrN1f9boPSo8lEK65D3FI1Ul02UiopwBdrMNKjN0SbdxzKv6wRt9m6Mub6LLx+2l96JcWQ2lQpbyib0J6rIMFU3uTmdRyXb+S3DYEosbOcwCaAJc7hq8//xSfz4fP5+XTT1fSt2+/FpuTiUlrUK8VQU5ODq+++ipxcU1vx3gq3333HWPHjgXgvPPOY+vWrc3+M3LLQ6zamU9pIMLx8iApbhvxTiu5ZSFUTWBRpOjfSBKKBGVBlXinlRiHhdJAhE5xTvrU0Xwm3mnlgswE3tmUg8uu4LDIHCv5MfgqK8ab9sGiACFVRxcCf0TDEgzzt68P8e6mHG4d3ZVhXeKxKobhkGUJXRMEIzpF/jCBiBFEjnNaqmUQTeuXxud7CwmpepWeA5ou8Ic15ozoUm+JCkWWuGJgB17/9ghWxYqEdJKhAgRc1r95Wl12iHXw6NTe5JWHKPCFiXVY6BTnaHEhtx5JLjrEOsgrD1Xr6RypUKm9594Hef7phVx66UQkSaJDh478+c+vtui8TEzONPUyBMOGDWPz5s1MmDCh2Sfg9XrxeH58wCqKgqqqWCy1T01RJOLj6/emuOlICfOX7yCi6jhsCiBxvCxEgS9SkeMvVQQrZbolujhSHEDTBQJBnjeMkCQSPQ4WXjmQhDry9wFOlAXJ9YaJd9lQdRGVk472CcCoUnbZFVRNp8AbJt8Lmq6TWx7k8ZW7SI938avx3enbMZZDhT6Cqk5OidGqUZYgrBmGKiXGhsNtj0pZx8e7ePQnfVmychdlIeOhXRmwvmZEBleNyGjQw3X2Bd3I8Ub4YHMOpQEjdVVguJ+m9E3lvO7Jzdo9LD7eRVYN2xVFrvfvu6E88pN+PPDuD5QGVWIcVmQZvEEVIeDXE3vg3ZZNjx49+PWvfw1IPP30kzzxxAL++tdXz5jiaEuef1uhvV+Dlj7/ehmCJUuWcN1116GqKqNGjcLlqj6hoUOHNmoCHo8Hn88X/b+u66c1AgCaJuqlxBeMaCxYZqwwYh3Gw7Jnsouc0hClAcMQoEi47BbSY+04rDI9k12UBlRKAhGsisT/jOrCBd0ScVK/n1lQEkDoAk3Tq1TFVrof1AppCVXTCUZ0qpaPGRIHKR6NJz7eSa9kF4eLAvjDKjaL/GOQWxg6RJomeHnNHn4+MiN6fN8kFy/NHMjXB4s4Uhwk3mlhdLdEOsQ6KC1teFVygl1GkSRiHRajXsKiEOOwsPVYGYuWb+PuCT0aPGZDaUnlySSrzOLL+vCf7bms3VdEUNfpnxbD5QM7EKuWcO3iRbz55jtkZBhxq8cf/wOzZs1gzZr/MnTo8BaZ06m0d+VNMK9Bq6mPnsy4ceMAmDt3brW3oMo0S02r2TddF0OHDmXNmjVMmzaNTZs2kZVV0zth4/jmUDHBiF6lSMqqyHRNdBKM2Nid76NTvKNKNbAiSyS6rVgUGNwpjouyGtYqMdVjx2qRiGh6NENJ10W0YEoIQ1MopOrR+tWTnu+owlhV+CM6eeVBZElCExCM6CgyWCoC9akeGwkuK6t35TN7SKfoqgAM2YvJvVMbccWq4g2pvLflBCkea4Xi6o84rTLrDhZzsMhPZmLbflNLi7Fz06gMbhqVUWX7p5+uw2q1RY0AQIcOHYmLiycn59gZMwQmJi1NvQzBmjVrWmwCkydP5ssvv2T27NkIIVi8uPkyMg4XB2oVC3BYFTwV8hEJpzzHdGFoCk3t0/CHqc0ic1m/NN7ZlEOCy0qK28bxshBShXSEIeUQTUbiZLsqVfjeSwIqDquEQMKiyDiEIW2h6gKHVaZzvDMaA9AjOoX+MJ3i6nZbNZQtOWWGzlEN7h9JktCF4NtDxW3eENRGcnIK4XCIw4cPRY1BUVEhZWWldOrUctlMJiZnmnp3KKtEVVUKCgpITk6u04VTH2RZ5vHHH2/yODUR67DWKMmgaqJC+8cIpB4vDZLosmFRjIBoWBVclJXMoPT6t04sCUT4fG8BW3LKsMgSGYkuDhf7AYHHrlAaVJEQxDoslAQMDadTa6hExTZjzobRkCUjvmBTJKzCSHe1VTyYDR0iUWtlblMJqfrpZHeQJAl/LVlKrYmqG5a2JgPWEPr3H0Dv3n154onHueuu+5FliRdfXErv3n0ZPHhI3QOYmLQR6v0kX7duHY888ghr165FVVW+/fZbnn32WTIzM1m4cGFLzrHRnJ+ZwP9+d7RK5WpZ0Cju0nVDyCfeacMf0cj1hkhwWumS4GTGgA5ckJlQ72Dg9hPlLFm9h5CqG1LVOvgiGgJB5zgnvVKt9ElxYbVYCEY0/m/jMcqChjEwAtMGFQsCA2Hk6id7bBwtDvzogtMFEU3HZpHxhjR6JLtJdLWM9k1lp7XaJC0kDMG6s4U9+V7e3XycjUdLEUKQkeDiqkEduKBbYqMCuxaLhaeeWsqLLy5l7ty7EEIwcuT5/OY391WrpTExacvUyxB89tlnXHrppYwdO5ZFixbxwAMPADBgwAAeeeQREhMTuffee1t0oo0hLcbOZf3TWL41F7ddBiFxuMhfIR0hkR5nJ8Fli1YBX9Y/jeuGNWzJ7w2p/OHTPUCF2qgmOFQcIBjR0HRBaUClQ6ydiKbz0MW9SHDZ6BLv4Ok1+/GHNVRNAwksFSmmlXLPmq6TGuPE47AY21UdRf4xtFweMgzJyQqmzU33JBddE10cKvZX6bkM4AuruO1KjQV2rcGGw8U8s8ZQwY1zWpCAXG+QpZ/vZ2+hnznDOzfKGCQmJjHvkcfZklPK9hPlyEgcDcjExlWXFDExaavUq2fxiBEj6Nu3L//85z9RVRWbzcaGDRsYOnQo8+fP56233qq1X0FL0JCexUIIPtyey6tfH+ZEeQhNNzJuYu0KXRJdUTdLRNOJaIK/zj6vSg5+XXyyM4+/f3PYeFAKQxcoEDFkq0VFrKF7kpOQKuia6GLJ9L6EVJ0Hlm0nrzyEQHCoKBDtcVD5y3BYZBKcVkqCKrquo+oCTRiuo85xDnqmeLj5/Ax611Hb0FTyvSEWfLyLQl8YRZGQMdxTDqvCI1Oy6JnS8iuCujImghGNW9/ajCKD3VLVTVYpHbLwsj70Smn4tTpWGuCJVXsoqFCZBcNgd4pz8NDFvUhuBgXWumhPGTM+n5fnn3+WL7/8AoALLriQO++8l4yMDhQUlPHii0tZvXoFqqoxdeo0br/97javgVYfWjprqF5PvK1bt3LDDTcA1SUHJk6cyKFDh5o4vZYjpOp8tb8IiwwOi4TTKuOwGPIIBwr8hCsqZ62KjKoLTpQFGzT+zlxv1Nfvj2gE1B8by1Req7BmKFseKg6wI9eLw6qw4NLe9E7zUOANI0sSFtmoUE5wWnFUZB2dKA+hSGC1yNgtMnZFIsVtxWW38PCUXi1uBABSPHaeuaI/t43JpF9aDL1SPNwwogt/vGrAGTEC9eG7o6WEVb2aEQDDvSYBn+zMb/C4vrDKYx/vothvtCpNdNlIdBnFiMdKg/x+5e4z3jjnXOfZZ59k3769PP30Czz99Avs27eHP/zh9wC88spLrFv3FUuWPMsTTzzN2rVf8Je/vNTKMz43qJchSE1NrbEpDcCOHTtITW16qmJL8fneQvYV+A39IEUx+gvIMhZFRtV18rxGkxEhDKmBhhZIOawylc8Cf1irFlyVIOqK0nWdbcfLAENa4RfndyXeaSMj0Um3ZDcD0mPpnuyie5I7GuQOa6JC/liiS4KTzgkuIqpO9p6CplyWBp6jwoReyTw8JYtHp/bmJ/3TiKunVMWZILcshHaaha3dInOkEZ3dvjpQVFFoVt2DGu80ejl/d7S0weOa1M6XX37BNddcR58+fenTpy+zZ8/h22+/IRQK8f7773DHHXczYMAghgwZxt13z+WDD94lFGrYy5tJder11PvZz37G7373O1577TXy8403K1VVWb16NQsWLOC6665r0Uk2hRU783Ba5ah8sn7SA0ORJcoCKrouCER0Ujx2OsY2bKk/pltitLvXqQghQDKUP8GwESevqH7IKUWWjYdKjN0SXVloQmC3yFgtMjEOCxkJTnqnuqMPX5tFZu2B4oZdiHOYWIcFuWb5OAAiul5vjaWT+e++ImxK7eNKkmEsTJqPmJg4Vq1aidfrraLttHPnTgKBAOed92Ph6pAhQwkEAuzZs7sVZ3xuUK9g8fz58zly5Ai/+MUvog+y0aNHI4TgqquuarH0z+agxB+Jdg2Lc1oo8Bna/BalQvZBEgQiKmGNRgUU+3WIoW8HD9tOeKtIQOsVLSZTPTYU2YgXKLLEwJNSUssCkYo2l2FsiozHrlSobwISyALsVhmPveqvSZZolEuiyB/ms90FrD9cggCGdo7l4qyUM+LnbkmGZ8Tz6rrDqLrR2/lkKuM0F/duWGEg/Kg3VBuyLEVdiybNw9y5D/H73z9aTdtp//6dOJ3OKnI0brcHh8NBXl7eaUY0qQ/1MgSKovDaa6/x4IMPkp2dTVFREXFxcVx44YUMHjy4pefYJDrG2TlSHMCiGBIN3ZJcHC0JVOS/G4VaFkXhVxd2ZUQjMmAkSeLBSb3427rDfLm/EKsiEaroLpYWYyPJbSOsauSWh0nx2CgJhAmpGm99n8P7W44bHbhCESQkLLLh/nFYlaiHKcZe/VcUiOic17lhAoAnp7jaLcb78/tb/Hy4LZf7JvZgSD2b55yNxDutzBzckbc2HsNjt0SD/aouKAuo9O/oqbM7XE306xDD/kJ/NenySjRN0K9D2+jO11Y4cuQwXbtm8thjRmHpiy8u5fHHH2XmzKuwWqunSVutNiKR5u9V0d5oUEVYnz596NOnT0vNpUW4rH8H/vj5flwVufBWxTAGIdUQfBvTPZH7L+pZ7U2yITisCneM7cYNwzuz/Xg5b208xvHyILouOFDoxxfWsCoyjqDKc9n78YeMlNE0j53ykEqoQo5C0wUHi/z0SHbjtCgEIhoxDgviJOnskKphkSUmN+ANtzyo8ofVe5CgSrcxp00hGNF4Zs1+np85oMXqEc4EMwd3JMZu4d+bcigLqlFH0dS+qVw3rFOjfr8X907hP9vziGh6tdhRqCIpYFwPs21lc3H06BGWLn2qirbT4sVPMWvWDK6//toaH/iRSBiHw1Ftu0nDqNUQzJgxo0EDLVu2rMmTaQnO75rAt5kJfH2gCLtFxmFViGg6vrBGVqqbO8Z2a5IROJl4p5XR3RO5oFsC+wv9/PPbI3x7uITuSXbcNgtIRgHZsZIgIEhy2eia6ORgUYBIhatH1QXHSgJ0SXAR77RwojyMpusokhR1fdwzoTsdY+t/8/93fyFBVa/WwhIMI1bZdvKn56U3y3VoDSRJ4pK+qUzqncKhIj+aLugU7zCueyPpGOvg1tFdeeWrQ+hoeGwKQoAvrKHIEvdO6H5WBc3bOrt27axV2+ngwYMEAgH8fh8ul5Gt5vN5CQaDJCefvckqbYVavyVlZWVV/OVfffUVsixzwQUX0KFDBwoLC1m3bh2qqjJ9+vQzMtnGoMgSvxnXneFd4vloWy45ZUFiHRZmndeJi7KSW0SeQarIM99f6KdDjA1fWKMkEECWpZOMjkSBL0yneAc9k92Uh1QKfWECYY2gqtMz2cWUPqnExThY+cNxfGGN3qluxvdIriKiJ4RRh+ANqyS4rDVqDm0+VhaNk9SE3SKz6VhpmzYElVhkqVmrnSf2SiYz0cV/tuey+VgpkiwxuXciU/umVusuZ9I0TqftNGTIUJxOJ5s3b+SCCy4EYOPG73E6nfTs2as1p31OUKshyM7Ojv77ySefpKSkhI8//pgOHTpEtxcXFzN9+nQ6dz67BbgUWWJsjyTGnsFl/K48L96wSlFFz+FKtAp9IIdVoSyo0qlie1lQxR82ZCkkIfHD8TI2HytjcEYC94zNrKIuWsnGoyW89s0R8r0hQ6VUF2Qmubjlgq5VHoaSRI2aS5VUBrLPNkoCEb7YW8C3R8vwBiJ0S3QytW8aWanV+z23JN2SXNw+ttsZ+3ntldNpOw0bNozp06/g2Wef4pFH3AghWLr0Ka68chZ2e9tOdjgbqFdlcWpqKq+++mqNb/4ffvghc+bMobj4zKUzNqSyuLVYsSOX36/cjUWWohLUYEhHBCNGdbNVkenfMYZ8b5i88pDRKU0XuK0KmUkuhBCUhTQm9Ezilyf1JgZYf8iQVLBZ5Gh6rBBG0xtJgscu7RM1Btl7Cnj5y4NVVhInU+KPcOPILkzr1zwdx5qDbSfK+UNFcNvtsKBrOkFVRwgY1yOJ28ZknpXGqyVoT5XFRUWFvPjiUtav/6aKtlNmZjp5eSX88Y9P8+mnn6AoCpMnX8odd9zdLOKXZztnRT8CTdNq7Ut85MgRbLa2G2RsKEIIduR6OV4WxGFVGJweWyW983BxgL35Xj7ZmY+oEI47GUWWUSQNVYBS4dYpC0awyLJRdyAg2WNcT0mSiHfZ+HxPIdcN7RwtbFJ1wStfH8JhlausFCRJIsZhoSyo8uq6wyz+SV/AEN9787ujlNdQHOULqThtCmO7nz1Bz7zyEEtW7UGWjOC2xaKgqhoOq4IuBJ/vLSTJbWP20E51D2bSpkhMTOLRR39f4z6bzcbcufOYO3feGZ7VuU+9DMFVV13F3LlzcbvdTJ06FY/HQ1lZGe+99x4PPfQQ//M//9PS82xxNF2wJaeMI8V+4wHfKY60mKpLzn0FPp7L3k+BL4QwxEuRJYkZAzpwce9knv/8ALvyvAAcKw2i6YJAWMdhlaN9B4QwmqJDRXpjMEJYE0Q0DasikRZjr2JYFFkCCfYX+qIpkNuOl+ENacQ5a/71xdgV9hf6OF4WpGOsA4dV4dFLerPwk92UBCIVhWtGwxy33cK8yb1qrJ5tLT7ZlU9Yqzm4LUsSsQ6Fj7blcsXADjW6zEzOHXxhlW8OFnPcrxIIhOkc72B0t0RiHWaQvjmp17d/6dKlHD9+nKuvvtpIwbRaiUQiCCG44YYbWLJkSUvPs0U5UOjnyU/3UBJQUTUdSZKQJcMFccvorlgVmRNlQR5bsQtdCOIclqiPWtUF727O4X+/O4ovbCiO6kIQVnUkjMKyQESL5u4HKwqQFAkSnBYiOqi6iiwZhqWmLJRTHSAlgUiNlczRz0sSiiRR7I9Es4u6JDh5fuZAvjlUxPdHShEChnSO4/zMhLPuYfr53oJoNXZNWBQZX1hle245Q9tw/YNJ7ai64K3vj/Kf7XmGUKQio+uGa/D1b48wvmcyN43KaJBApEnt1MsQuN1uPvzwQ7Zs2cKXX35JSUkJSUlJTJgwoVlbS7YGhb4wj63YharrVd6wdSHI3luILEvcNiaTZVtPEKohBdMiS5QHVQr9EewVPn7d8PBE+xHrwlhxWGTDl29XJIQEyTF2XFZLdBWh6YIiX5iOcT+mhqoV/QpODv567BZOFysVwjBGpxaj2S0y43okM65HcmMv1xnBH9ZwncYQVBKImFW95yKaLliavY9vDxcT67BikaWoe7By/2d7CsgpDfLIlCxspjFoMg3yBwwaNIhBgwa11FxahVW78ghEtGoPeFmSiHdZyN5bwMzBHfliX2GN7hNfSKMkEEHix4d2hXIFOj8aA02ATQYbEgiwKzIuq4IkQbLbRm55CFk2soc6VhTBCiEo84eZ1Cu5irtoYMdYbBaZsKrX+CXwhzU6xjnoHN82C23SYuwU+MK1GgMhBAJBchsugDOpnVW78vn2UDEJLmuN2WGKLJHgtLAzz8vbm3K4fvjZnbXYFqiXIejWrVud6Xr79+9vlgmdadbuL6r1gRPRBKWBCH/+7wGK/RHSY2VOddQU+MJROYiKpmdUuOCRTloZIASBikIkm0UmI8EZvaZJbhshVafYH0aTjAd5RNPRBYzolsiNI6o2n7FZZG4c0YW/fHUID4bRqow1aMJoZXnTyIwzmmLZnFzWL42/fH0omg11KoGITpLLRlbq2SGDbdJ86ELwwQ/HcdmU096/kiQRY1dYuTOPn56XbrqImki9DMHll19e7Zfi9Xr56quvyMvLY968thvFD6t6td7BuoBjJQHKgiqaLlh3uBhvSGNnnkpGorOKy8UXVpEBlQrJ6ZPGkSWiDWesipEV5LFb6JLgrJL6KEnQKc6BRZHw2BW6JjhJctuYlJXCmD5plJVVl1CelJWCEPDHL/ZTdJIxkiWJRJeVj7bl0j3Z1aTK2tZiTPdE/rMjl6MlQeJPCYgHIxphVecX49uuoTOpnT15PkoCaq2JECdjVWR84QibjpUy6izplNdWqXewuCaEEMyePZvDhw8366TOJL3TYthwuJg4549vFDmlQcqCKoa8jESy247HpnGsNMjhIj/dk93RimSjv4GEpNUevJVl6JnixhcyCsZUvXoBV+Wb/EMXZ1URMjs1/TQY0dh0rJSyoMr3R0qxyRIZCU4EYJWl6Orm+2Ol/GH1XuZP7d3m8u0dVoX5U3vzwhcH+CGnDEIamqqjKBIuq8K9E3swtIsZJD4XKQ6EqdbU4zToAor9kZabUDuhSa+LkiTxy1/+kquvvprnnnuuueZ0RvlJvzTWHyqO6viEVZ3SQASLIqFpRl8Ap9X44w1plAQjnCgNkpnkQtMFVkVC0yHRZaXIH4nGBODH2znZZUMCPHaFW87P4IX/HsQf1qKy076QihDw08Eda1WzFEKwbGsu72zKIaLrRFTBifIgsgTJbjupMfYqAeQEp4Xd+V62Hi9rlPJmaxPrsPLwlCyOlgTYXxqitNxIhT2vUyyWBjYPMmk7KLLUoJWeBM2mFdaeabLfYPv27aiq2uSJrFq1ihUrVvDMM880eayG0DvNw7XDOvO/3x0FjNaWuhCoGlgUqYovv0uCA7dPJtcbpsgfwWFRmNInhW8PFRNrtxKuELM7+X3GaZVJj7NTElC5dlhnLuieRHq8k/9sz+Pbw8Voms6g9DimD0hjQMfYGmZo8PamHN7ZdJwYh4JbsUa7cqm6UbNQ6A/TJcGJx2ZkFEmS0aJx1a78JhsCVRdsO15GbnkIiyyRleo5Yzo7neOdDMhMajeVte2drgku9IoU7NP1ggDj5UgCMhNdZ2Zy5zD1MgS/+c1vqm3TdZ2cnBw++uijJnfjkqvYAAAfxUlEQVQoW7hwIWvXrqVv375NGqexXD6wA/07xvDx9lzW7i/CIkukxtiJd1pP8eVLJLptSLLMP68fEs2//+++Qv609gAuq4WwqqMKgYwRFE7xWCkNalzQLZHpAwydpq6JLn51YSa/IrNe8yvwhXlvy3HinBYUWSK/PMSJsuCPwWkJghGdQ0UB4hwWOsc7kSQjqJxXHmrStcneW8Ab64/iC6to+o/B8KxUD7+6MLNBKqgmJnWRGmNnQHos246X1ans6o/opMc56JFsGoKmUi9DsGzZsmrLNUmSiI2N5d577+Xhhx9u0iSGDh3KxRdfzFtvvdWkcZpCz2Q3d47rzpjuiTz16d5ab8KgqpPstlXJUlBkyRB9E0bnM1mXEEC8w8KQTvFM65fGoE6xdb7h1MZ/9xYihPFzSgMR8rxhlIr+BdERpYp006BKXnmItFg7qiaIbYJM8n+25/KPb47gtitVrocQgj35XuZ9uIPFP+lrGgOTZuWaIek8erws2kSpJiKaTkjVuX5YJzNpoBmolyE4ePBgs/ywt99+m9dff73KtsWLFzNt2jS++eabeo+jKBLx8S3zFjAuxsGr3xzBF9aqtYgUQhAKqvzPqAwSEozUxa/3FfDi2oO47BZ6nNTyUdMFJf4w8TF2xvfvUOVmPV4a5FChD0mSyErzkHCafHhFkTnhD2OzKiiKTIE/YgSnJYlIhRtKqpAX1YWxCigKROgY7wRJ4vKhnRt1rfLKg7z5/TESPLZqTVkAkqwWSvxh/v7tEZ76act2qVMUucV+322B9nb+I+JdPHKZzJIVuwiHNGKdViMWYFHQK2RZhIC7JvVi0sCOrT3dM0JL3wP1MgQXXXQRf/rTn2rsTrZlyxZuvPFGNm3aVOc4s2bNYtasWQ2f5SlommhRn/Hd47rx+Mrd5JcFibErKLJEIKITjGgM7RLPBZ3jKCnxowvB85/uwSqDRSJa+VhJrF3h8135TM1KpnuSmxNlQf729SG2Hi+PZgMJITi/awI3n9+1xoK1+HgXshBEVI1AyMgaUiQjW0mRJVRNGAJGlfULCIQQHCsO0DXRSe94R6Ou1fvfH0NVdSSbqHZelbitMluOlrLtUGGNfRCai/akvlkT7fH8+ye7WHRZHz7ceoK1B4qwKDKaZsTvhmckMGNAGr1SPO3murSa+uiyZcuiQeDs7GyWLVvG9u3bq31u9erV7Nu3r8kTPJvoleLhyRn9WL71BF/sKyKkanSKczBjQBrjeiZHsxTqynmuXAVk7ynEbbPw8Ec78YWNz1fu03XBVweL2V/kZ9FlfautQgBGZSSwZk8BekVwrPJYm2JIT2sVVWuSbAR2dV0Q67Tw6CWNL7/fcKQEh/X0x1YGpHfl+VrUEJi0TzISnPx6bDd+NqoLQUmmtCxAsttmCs61ALUags8++4znn38eML7wv/3tb2sd5HT72ipGm8JMbh2daWQn1OCHLAlGqgnCnYpVkcgtD/GPbw4bXcRO8dnLskSCy0pOaYjlW09w7bDq5fID02NJ9djJLQsiBNH5SJKE3SJXPPzBbVOwKjIWWeL+iT1I9jS+YUdEE3WeGxgpsppe/7xvE5OG4rZZ6BTvoqSOFxOTxlOrIXjyySe55557EELQvXt33nvvPYYMGVLlM4qiEBcXR0xMzcuNhjBq1ChGjRrV5HFagtqCUTF2S52lL6omcFhlvjlUTNxppJ5jHQorKsrlT/XJK7LEvMm9WLBiF/m+MGFNYJUrH8JgkWUyk104rHJFc3v5tKmo9aFrgpPc8mCdyqSyBKkeU/PHxKQtU+uTyWaz0bWr0Tf0wIEDpKenY7WaS7KTyUr14LYrlAUjlAdVvGENBDhtCkkuK86KN5heyW42HC45bdaQVZEJRFSK/JFqfRAAOsQ6ePry/ry9MYd/fHuYiK5jVWRSPXajeYsiEdF0fGGdX1+Y0eRq4kv6pvLNoeJaV0NgxCti7NYmGx0TE5PW5bTBYiEEK1eupHPnzlEjcOjQIRYsWMCOHTsYOHAg8+bNo1u39tnP1SJLZKW4+f9/OIGMkc0E4A2qlAdVHBaZcT0S61XwUikdfZoe83jsFm46P4NhGfE8s2YvwYiOIkMgoqGGjAKcm0d2YULPpstM903z0K9jDFtzyklwWaoZg4imE4jo/OL8rm1OwsKkffCf/yxn8eLHatz34ouvMGDAIF58cSmrV69AVTWmTp3G7bff3S5feGs1BF6vl0suuYR169axaNEiBgwYQElJCWPGjKGgoIBp06axfv16Ro4cyYYNG6Krh/bEd0dK+O5IKR1jHOT7QugnyeMbQVxB/46xdE92g0RUxqImgqpOostGkrtuN8ug9Fj+cvVg1h0sZuOxUjRd0DvVw9geScQ3oW7gZCRJ4v6JPXlmzV62nShHwuhnIIRRfS1JEjePymBsj7OnxaWJyclMmjSZUaMuqLJt8eLH8XrLGTBgEK+88hLr1n3FkiXPEolEWLRoARaLlTvuuLuVZtx61GoIlixZwu7du1m+fDlTpkwB4Nlnn+X48eP8/e9/52c/+xmapjFlyhQee+wx/v73v5+xSZ8tvLMpB6tiBHsT3VbKgqqhZipLxFbEAz7anseMgR25qGcyK3fm1aixLoTAH9a4bmjnehfHOKwKE3olM6FXyzWZcdkUHpmSxa48Lyt35HGoOIBFkRmREc/EXskk18NomZi0Fna7A7v9x2LHL77IZuPGDfzrX/9G0zTef/8d5s9fxIABRo+Vu++ey2OPPcwtt9xW5bj2QK2G4N1332XevHlMmzYtuu2dd94hISGBOXPmAEaw+Je//CX33HNPy8/0LKPEH+FAoT+aOqpUZP+cSmlAZV++j+uHd2ZfgZ89BT48dqXi7VpU1CfonN81gYt7p5zp06gTSZLokxZDn7SmJwSYmLQWqqry8ssvMGvWtXTq1JmtW38gEAhw3nlDo58ZMmQogUCAPXt2R41De6HWfKyDBw9WyRLKzc1l586dTJgwAVn+8bD09HQKCgpadpZnIQFVi1b4ng5ZgqCqGQ3kp2YxZ3gnLLJESSBCSUAl3mnltjFduXtCj3braxdCcN99v+Hdd6tKjEQiEX72s9lkZ2e3zsRMzhmysz8lLy+X66+/EYCCgjycTicejyf6Gbfbg8PhIC8vr7Wm2WrUuiJwOp34/T9WslV+GSdPnlzlc0ePHiU+vv1pw8c7rYiKXsS1PcAr4wSVfn+HVWHGwI5c1r8D5SEVCYh1VA/EtiWEENx//12MHj2GmTOvqTNAd/IbGBjihUuXPsU333zF6NFjottDoRCPPfYI+/btbdH5m7QP3n//HS69dDqxsYYSbzAYxGqt7tq0Wm1EIuEzPb1Wp1ZDMHLkSD744IOoa+jNN99EURSmT59e5XP/+Mc/GDZsWMvO8izEaVUY0z2B/+4rqtElBOALa3RNcFWTbFZkqdmCuq1JTQ/xugJ0J3Ps2FEWLVpAXl4uHs+Prqddu3ayaNF8ZLnuBvYmJnVRUJDP5s0buf32u6Lb7HZ7jQ/8SCSMw9G+4gNwGkMwd+5cLrnkEo4ePYqu66xcuZKbb76Z9PR0ANavX8/zzz/PqlWrWL58+Rmb8NnEzMHprD9UgjekVpOGCEY0NF3w81Fdajm6bVPbQ/x0ATqLpeo12rZtK92792TJkme4+eYbotu/+249Y8aM4+c//wWTJl3Y8idjck7z9ddfkpqaRt++/aPbUlLSCAQC+P0+XC5DQNLn8xIMBklOTm2tqbYatcYIJk2axLJlywgEAhw5coT77ruPP/3pT9H906dP57333uOZZ56pElBuT3SMdfDYpX2Ic1gpCUQo8oUp8ocpCUSQJYkHJ/Wi7zkaZK18iP/9729U8bOezKkBulOZMmUq99//2+hyvZLrrpvDL395e7vL3DBpGbZu3cLgwUOquGB79eqF0+lk8+aN0W0bN36P0+mkZ89erTHNVuW0BWXTpk2r9SH/wQcfkJWVRUJC+24anZnk4oWfDuSHnDJ25HoNSY4kN0O7xNUo33yuMGXKVKZMmXraz5waoDMxaQ327dvL+PETq2yz2x1Mn34Fzz77FI884kYIwdKlT3HllbOw2xuv0dVWaXSryrNVF6g1kCWJwZ3i2mRv4Jbk1ACdiUlrUFRUSExMdRmU2267k1AoxIMP3oOiKEyefCm33vrrVphh69PknsUmJjVRU4DOxKQ1eO+9j2rcbrPZmDt3HnPnzjvDMzr7OHd9FyatSk0BOhMTk7MT0xCYtAg1BehMTEzOTkzXkEmLUFOAzsTkbEYIQYEvzOHiAGVBFQF4bAoZCU7SYuzn9EuNaQhMoggh2JHr5XhZEE0XxDgsDEqPxW1r+G1SW4CuNt55p+ZalLVrN7TLnr0mZ44Cb4jP9hSwYkcegYiGLEnRrnuyZDSAsioyF/dOYXLvFDrGnntpzZIQos31GYxEtHbzYDgTD0FVF6zelc+yrSco8ocr2mGCIhsZUeN7JnH5wI41NsxpCcKqzvdHS9hf4McX1kiOc9LRbWFYl/hzOiW3NkxD2DLXQNV03t9ynPe2nEAXArdNqbXHd0TT8YY0JAku6ZPKtUM71dm9rzlpteb1Ju2DkKrz9Gd72XysDJdNJu4U7SNVF3y6q4CvDhTzu0uy6JHsPu14uhDsyfNRHAgjgFi7hd6pHiz1eICXB1U+2n6CFTvyCakamjCa7UiShNAFDqvC1L4pXNavAzGnaftpYlIXRf4wiz/Zw5GSADEOS619QiqxKjIJLhlNF6zYkceGwyU8PCWL9LhzY3VgrgjOclrybVAIwTNr9vHtoZIau5CdjC+kosgyf5jRr8aVgTek8vneQpZtPUFZUAUEEoAkYbfITOuXxqSsZBJdNfcwyC0P8fiKXeR7w3gcCraTDIfFoqCqGmHVeCtLjbHxu0t6n7EVSmtjrgia9xoU+cP87qOdFPnDjRZ9LA+qOKwKCy/rc0ZcRS29Imh/62yTKHsLfGw4XLcRAHDbLfgjGu9vOV5t39GSAPd/sI1/rj9CSNWIc1qIc1qJdVqNLxpGE59739/GrlxvteNLAhEWfLyLokCERLe1ihE4GZtFJtFtpdBvfL4kEGnUeZu0X1Rd8NSneynyh4lzVm8SVV9iHBYCEZVFn+wmGNGaeZZnHtMQtGM+3mHortf3yxDnsPDffYV4Q2p0W155iPkf76I8qJLgstboN7VZZBJcVnQh+P0nu9hf6Kuy/1/rjxhfzHq6e+IcFor8Yd7YcKRenzcxqWTFjlz2F/qjHQSbQqzDSr43zFsbjzXDzFqXVjcE5eXl3Hbbbdxwww1cc801bNy4se6DTJqMqgu+PlDUIF+7IktoQrA5pyy67aW1B/CF1XqN47IZRuKZz/ahV3gkSwMRvjpQ3OAvZqzDwpf7iykLmqsCk/rhDan873fH8NiVZksFjXVY+HhHHrnloWYZr7VodUPw2muvcf755/PGG2/wxBNP8Pjjj7f2lNoFgbCGLmhwVzRdN/yjYLiEduZ66/0mD+CxWyj0h9l+ohyA/+4vQojam/vUhiJL6ELwxb6iBh1n0n5Zu78IVRfNmnmmyBJCwGe785ttzNag1Q3Bz3/+c2bPng2ApmntUvmvNWhsW0xJIpphsXpXPhL1dy1FxwA+3JYLwIbDxViVxs3FpkhsOFzSqGNN2h8rd+bhqCU9tCm47Qqf7MqnDebdRDmjOXhvv/02r7/+epVtixcvZtCgQeTn5zN37lzmzatbAEpRJOLjXS01zbMKRZFb5FzjhCDBY0fV9AblQ1sUjZ7pccTHu9ie78PtsGKxNCyfOs4tsSvfR3y8i7AAm9Vy2jEkqHG/TYewEOf8vdBS90BboqnXIBTRyPWGSXA1PkBcGxaLQrEvTMSikBrTMhlELX0PnFFDMGvWLGbNmlVt+65du7j33nt54IEHGDlyZJ3jaJpoN+l0LZk6ODUrmf/9/hiWen4vghHNKLn3WCkp8VPmDyN0HVWt+9iTEULgC6qUlPiRdEFE1bCe5kWtMn30VCKqhiTO/XvBTB9t+jXYV+ADIdA0vRln9SNCCLYdKsbWuWUk18/59NG9e/dy11138cwzzzB+/PjWnk67YkLPZBRZIqzW/eUQQuAPa8wY2AG54o3KYVGiQd+GoAuwVyzRMxKdhBr55QypOhkJzro/aNLu8Yc1WlIpSAhRJZuurdHqhuCZZ54hHA6zaNEi5syZw69+9avWnlK7Id5l5VdjMvGGtdMaAyEExX6VAemxXNI7Jbq9XwcPwUjDH+K+sEbPFKNC+eKsFKSKn9EQhDAK1i7OSqnzsyYmLa8XJ0VfkNoirV6n/+c//7m1p9CuGdsjCQG8/OVBfGENl02Jvq3ruqioEoZhXeK4a3z3KlIRU3qn8tnuAuOh3IAvgS4E0wekAdA9yUWnOCd55UHc9vrfjv6wRpcEJ92T2rfv3KR+xDqstGQoV5Jo07InbXfmJs3GuB5JDOwYQ/aeQj7cnkuxPxJ9gzo/M4FL+6aRlequ9rDPTHKRmeTicLGfWIe1Xj/LH9aIsVsYlG74UiVJ4sYRnVm8ag82Ta9Xal9E0wlrgjkjupzT0sAmzUd6nAMhBHqFflVzIoRA00WbdlOahsAEgASXjSsHd+SKQR3wRzRUzVBjrEss7o6x3Zj34Q58YbVOuepgRCOiCX57cY8qIl+DO8Vx6+iuvPLVIZxWcdospmBEIxDRuXV0Vwal11/m2qR9Y5EluiW5OVzsx9OAlWd9CKk6iS4r8c76vQydjbR6jMDk7EKSJNw2QyuoPoqhneOdPHpJbyySTLE/QqSGwK+qC2OfLnhgUk/6daieuTApK4W5F/XAosiUBCKUB1U0XUTftsqDKiWBCBZFZu5FPZhkxgZMGshl/dNQ9eZ3EAUjOtP6pTX7uGcSc0Vg0mR6prh5+or+rNyZx8qdefjDKroQCASKZATRJvdOYVq/tNPK9g7PSODlzvFsPlbK8q0n2F/oJ6jquO3QK8XN9AEdGNwprk7JYBOTmhjRJR6nVSEY0Zqtl0BE01FkiXE9kpplvNbClKE+y2lrOeRhVWdLThklgQi6EMQ6jHhApc5QY2hr16C5ae/nD813Db4+UMRz2fvrpbhbF0IIigMqPx/RhWn9W3ZFYDamMWlT2CwywzPiW3saJiY1cn5mAqO6xvPtoRLim2gMSgMqWSluLumb2owzbB3MGIGJiUm7QZIkbh/bjaw0DyV+tVH6QEIISgIROsY5eHBSr0brdp1NmIbAxMSkXeGwKjw8uRejuiVQElAb1FgmrOoU+1X6dYjh8Uv7tOnagZNpkzECExMTE5Pmw1wRmJiYmLRzTENgYmJi0s4xDYGJiYlJO8c0BCYmJibtHNMQmJiYmLRzTENgYmJi0s4xDYGJiYlJO+fcqIZoo+i6zoIFC9i1axc2m42FCxfStWvX6P7PPvuMl156CYvFwsyZM7n66qsBuOKKK4iJMTRDOnfuzBNPPNEq828qdZ0/QCAQ4KabbmLRokX06NGjXse0JRpzDeDcuQeg7mvw4Ycf8vrrr6MoCllZWSxYsADgnLkPGnP+siw37z0gTFqNlStXigcffFAIIcTGjRvFbbfdFt0XDofFxRdfLEpKSkQoFBJXXXWVyMvLE8FgUFx++eWtNeVm5XTnL4QQW7ZsEVdeeaUYPXq02Lt3b72OaWs05hqcS/eAEKe/BoFAQEyaNEn4/X4hhBD33HOPWL169Tl1HzTm/Jv7HjBdQ63Id999x9ixYwE477zz2Lp1a3Tfvn37yMjIIC4uDpvNxrBhw9iwYQM7d+4kEAhw8803c+ONN7Jp06bWmn6TOd35A4TDYV566SW6d+9e72PaGo25BufSPQCnvwY2m43/+7//w+k0un+pqordbj+n7oPGnH9z3wOma6gV8Xq9eDye6P8VRUFVVSwWC16vN7rsA3C73Xi9XhwOB7/4xS+YNWsWBw8e5JZbbmHFihVYLG3vV3m68wcYNmxYg49pazTmGpxL9wCc/hrIskxycjIA//rXv/D7/YwZM4aPP/74nLkPGnP+u3fvbtZ7oO1dtXMIj8eDz+eL/l/X9egv8tR9Pp+PmJgYunXrRteuXZEkiW7duhEfH09+fj4dO3Y84/NvKqc7/+Y85mymMedzLt0DUPc10HWdp556igMHDvDCCy8gSdI5dR805vyb+x4wXUOtyNChQ/niiy8A2LRpE1lZWdF9PXr04NChQ5SUlBAOh9mwYQNDhgzhnXfeYcmSJQDk5ubi9XpJSWmbbRtPd/7NeczZTGPO51y6B6Dua/Doo48SCoX405/+FHWRnEv3QWPOv7nvAVN9tBWpzBbYvXs3QggWL17M9u3b8fv9XHPNNdGsISEEM2fO5PrrryccDvPQQw+Rk5ODJEncf//9DB06tLVPpVHUdf6VzJkzhwULFlTJGjr5mMpMmrZIY67BuXQPwOmvwYABA5g5cybDhw+PNpG58cYbmTRp0jlzHzTm/MePH9+s94BpCExMTEzaOaZryMTExKSdYxoCExMTk3aOaQhMTExM2jmmITAxMTFp55iGwMTExKSdYxoCkzbFhAkT+MlPflLjvuzsbCRJYsOGDbUen5mZyR133NFS0zMxaZOYhsDExMSknWMaAhMTE5N2jmkITExOwefzceedd5KWlobT6WTChAls3Lgxus/j8VTTft+2bRuSJPHZZ58BkJeXx4033khiYiIej4cZM2Zw4MCB6OcXLFjA8OHDueeee4iPj2fMmDEAHD9+nJtvvpn09HSsVivp6encfffdhEKh6LFFRUXMmTOHhIQEkpKSePDBB7npppuYMGFC9DOqqvLoo4+SkZGBw+Fg+PDhfPrppy11yUzaOG1TpcmkXSOEQFXVats1TWuWsWfMmMGWLVtYvHgxHTt25MUXX2TChAl8//339OjRgxkzZvD222/z0EMPRY9766236NChAxMmTCAQCDBx4kQCgQAvvPACLpeLJ554gnHjxrFlyxYSEhIA2Lx5Mw6Hg3fffZdgMIiu60ydOhVJknjppZeIi4tj5cqVPPnkk/To0YM777wTIQTTp09n//79/PGPfyQmJoZHH32UPXv2cP7550fnc8stt/Dvf/+bxx9/nP79+/PGG29w6aWXkp2dzejRo5t8nUzOMZqts4GJyRlg/PjxAjjtn/Xr19d6fNeuXcXtt99e6/4VK1YIQKxatSq6LRKJiKysLHHTTTcJIYRYvny5AKKNYoQQok+fPuKuu+4SQgjx8ssvC0VRxI4dO6L7S0tLRXx8vHjssceEEELMnz+/2lwPHz4sxo8fLzZv3lxlToMGDRIzZ84UQgjxySefCECsWbMmuv/YsWPCbreL8ePHCyGE2LFjhwDEX//61yrjXHTRRWLixIm1nrtJ+8V0DZm0OS688ELWr19f7c/LL7/c5LHXrFmDy+Vi/PjxqKoaXXlMmTIl6lq55JJLSEpK4u233wZgy5Yt7Ny5k+uuuy46Rq9evejZs2d0DJfLxdixY6u5Z/r27Rv9d5cuXcjOzmbAgAHs2bOHjz76iMWLF5Obmxt1DWVnZxMXF1fFDZSenl7lLT87OxuAadOmRX++qqpMmzaNtWvXEg6Hm3ydTM4tTNeQSZsjLi6O4cOHV9vu9XqbPHZhYSF+vx+bzVZtn9Vqjf7905/+lLfffpvf/va3/Pvf/6Z79+6MHDkyOsbOnTujnz+ZXr16Rf/tdrtxu91V9r/66qs8/PDD5Obm0rFjR0aNGoXT6URUaEMWFBTUKDeclpbG8ePHoz8foFOnTjWeY0FBAenp6XVeC5P2g2kITExOIi4ujtTUVD766KPTfu7aa6/lL3/5CwcPHuTtt9/m2muvrTLG4MGD+dvf/lbtOLvdXuuYn3/+Obfccgu/+93vuOOOO6IP/EoDA8bbf35+frVjT94WFxeHJEl8+eWXNRqjyo5XJiaVmK4hE5OTuPDCC8nPz8fj8TB8+PDonzfffJM33ngj+rlx48bRuXNnnnzySXbv3h11C1WOceDAATIzM6PHDxs2jOeee44PP/yw1p+9bt06JEnikUceiRqBnJwcfvjhh+iKYNy4cZSWlkYbmYBhBL7++usqP18IQXl5eZVzWL16Nc8991yb7eRl0nKYd4RJu2Pz5s0sXbq02vbZs2czffp0RowYwbRp05g/fz4ZGRm8++67vPTSS1ViEJIkMXv2bJ577jkGDRpEv379ovtuvvlmnn/+eSZPnsxDDz1EYmIir7zyCu+++y7Lly+vdV4jRoxA13XuvvtuZs2axeHDh1m0aBGhUAi/3w/AxIkTGTt2LNdddx1LliwhJiaGhQsXEgwGkWXjve68885j5syZ3HDDDSxYsIC+ffuSnZ3NwoULeeCBB6KfMzGJ0srBahOTBjF+/Hhx2WWX1bhvzZo19coaopZso6+//loIIURxcbG49dZbRWpqqnA4HGLgwIHitddeqzbW999/LwDxxBNPVNt35MgRMXv2bJGQkCBcLpcYOXKkWL58eXT//Pnzhdvtrnbcs88+KzIyMoTD4RA9e/YU8+bNE/PnzxdxcXEiGAwKIYTIzc0VV199tfB4PCIxMVHMmzdPjB07VkyfPj06TjAYFA888IDo3LmzsNlsolevXuLJJ58Uuq7Xem1M2i9mhzITkzbEgQMHWL9+PVdddVXUxaNpGpmZmcyaNYtnn322lWdo0hYxXUMmJm0IIQRz5sxh1apVXHvttYTDYf72t7+Rn5/PLbfc0trTM2mjmM5CE5M2RPfu3fnggw/Yvn07V1xxBVdffTXFxcVkZ2dXqUkwMWkIpmvIxMTEpJ1jrghMTExM2jmmITAxMTFp55iGwMTExKSdYxoCExMTk3aOaQhMTExM2jn/D0GwRob63q9LAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 2. Leverage Value using High Influence Points : Points beyond Leverage_cutoff value are influencers\n",
    "influence_plot(model)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.2222222222222222"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Leverage Cuttoff Value = 3*(k+1)/n ; k = no.of features/columns & n = no. of datapoints\n",
    "k=cars.shape[1]\n",
    "n=cars.shape[0]\n",
    "leverage_cutoff = (3*(k+1))/n\n",
    "leverage_cutoff"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "From the above plot, it is evident that points 70 & 76 that are beyond leverage cutoff value=0.22 are the outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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>HP</th>\n",
       "      <th>MPG</th>\n",
       "      <th>VOL</th>\n",
       "      <th>SP</th>\n",
       "      <th>WT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>280</td>\n",
       "      <td>19.678507</td>\n",
       "      <td>50</td>\n",
       "      <td>164.598513</td>\n",
       "      <td>15.823060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>322</td>\n",
       "      <td>36.900000</td>\n",
       "      <td>50</td>\n",
       "      <td>169.598513</td>\n",
       "      <td>16.132947</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     HP        MPG  VOL          SP         WT\n",
       "70  280  19.678507   50  164.598513  15.823060\n",
       "76  322  36.900000   50  169.598513  16.132947"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Those Outlier values of index is in index numbers\n",
    "cars[cars.index.isin([70,76])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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>HP</th>\n",
       "      <th>MPG</th>\n",
       "      <th>VOL</th>\n",
       "      <th>SP</th>\n",
       "      <th>WT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>49</td>\n",
       "      <td>53.700681</td>\n",
       "      <td>89</td>\n",
       "      <td>104.185353</td>\n",
       "      <td>28.762059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>55</td>\n",
       "      <td>50.013401</td>\n",
       "      <td>92</td>\n",
       "      <td>105.461264</td>\n",
       "      <td>30.466833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>55</td>\n",
       "      <td>50.013401</td>\n",
       "      <td>92</td>\n",
       "      <td>105.461264</td>\n",
       "      <td>30.193597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>70</td>\n",
       "      <td>45.696322</td>\n",
       "      <td>92</td>\n",
       "      <td>113.461264</td>\n",
       "      <td>30.632114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>53</td>\n",
       "      <td>50.504232</td>\n",
       "      <td>92</td>\n",
       "      <td>104.461264</td>\n",
       "      <td>29.889149</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   HP        MPG  VOL          SP         WT\n",
       "0  49  53.700681   89  104.185353  28.762059\n",
       "1  55  50.013401   92  105.461264  30.466833\n",
       "2  55  50.013401   92  105.461264  30.193597\n",
       "3  70  45.696322   92  113.461264  30.632114\n",
       "4  53  50.504232   92  104.461264  29.889149"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# See the differences in HP and other variable values\n",
    "cars.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Improving the Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>HP</th>\n",
       "      <th>MPG</th>\n",
       "      <th>VOL</th>\n",
       "      <th>SP</th>\n",
       "      <th>WT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>49</td>\n",
       "      <td>53.700681</td>\n",
       "      <td>89</td>\n",
       "      <td>104.185353</td>\n",
       "      <td>28.762059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>55</td>\n",
       "      <td>50.013401</td>\n",
       "      <td>92</td>\n",
       "      <td>105.461264</td>\n",
       "      <td>30.466833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>55</td>\n",
       "      <td>50.013401</td>\n",
       "      <td>92</td>\n",
       "      <td>105.461264</td>\n",
       "      <td>30.193597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>70</td>\n",
       "      <td>45.696322</td>\n",
       "      <td>92</td>\n",
       "      <td>113.461264</td>\n",
       "      <td>30.632114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>53</td>\n",
       "      <td>50.504232</td>\n",
       "      <td>92</td>\n",
       "      <td>104.461264</td>\n",
       "      <td>29.889149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>322</td>\n",
       "      <td>36.900000</td>\n",
       "      <td>50</td>\n",
       "      <td>169.598513</td>\n",
       "      <td>16.132947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>238</td>\n",
       "      <td>19.197888</td>\n",
       "      <td>115</td>\n",
       "      <td>150.576579</td>\n",
       "      <td>37.923113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>263</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>50</td>\n",
       "      <td>151.598513</td>\n",
       "      <td>15.769625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>295</td>\n",
       "      <td>19.833733</td>\n",
       "      <td>119</td>\n",
       "      <td>167.944460</td>\n",
       "      <td>39.423099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>236</td>\n",
       "      <td>12.101263</td>\n",
       "      <td>107</td>\n",
       "      <td>139.840817</td>\n",
       "      <td>34.948615</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>81 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     HP        MPG  VOL          SP         WT\n",
       "0    49  53.700681   89  104.185353  28.762059\n",
       "1    55  50.013401   92  105.461264  30.466833\n",
       "2    55  50.013401   92  105.461264  30.193597\n",
       "3    70  45.696322   92  113.461264  30.632114\n",
       "4    53  50.504232   92  104.461264  29.889149\n",
       "..  ...        ...  ...         ...        ...\n",
       "76  322  36.900000   50  169.598513  16.132947\n",
       "77  238  19.197888  115  150.576579  37.923113\n",
       "78  263  34.000000   50  151.598513  15.769625\n",
       "79  295  19.833733  119  167.944460  39.423099\n",
       "80  236  12.101263  107  139.840817  34.948615\n",
       "\n",
       "[81 rows x 5 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Creating a copy of data so that original dataset is not affected\n",
    "cars_new=cars.copy()\n",
    "cars_new"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\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>HP</th>\n",
       "      <th>MPG</th>\n",
       "      <th>VOL</th>\n",
       "      <th>SP</th>\n",
       "      <th>WT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>49</td>\n",
       "      <td>53.700681</td>\n",
       "      <td>89</td>\n",
       "      <td>104.185353</td>\n",
       "      <td>28.762059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>55</td>\n",
       "      <td>50.013401</td>\n",
       "      <td>92</td>\n",
       "      <td>105.461264</td>\n",
       "      <td>30.466833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>55</td>\n",
       "      <td>50.013401</td>\n",
       "      <td>92</td>\n",
       "      <td>105.461264</td>\n",
       "      <td>30.193597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>70</td>\n",
       "      <td>45.696322</td>\n",
       "      <td>92</td>\n",
       "      <td>113.461264</td>\n",
       "      <td>30.632114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>53</td>\n",
       "      <td>50.504232</td>\n",
       "      <td>92</td>\n",
       "      <td>104.461264</td>\n",
       "      <td>29.889149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>175</td>\n",
       "      <td>18.762837</td>\n",
       "      <td>129</td>\n",
       "      <td>132.864163</td>\n",
       "      <td>42.778219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>238</td>\n",
       "      <td>19.197888</td>\n",
       "      <td>115</td>\n",
       "      <td>150.576579</td>\n",
       "      <td>37.923113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>263</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>50</td>\n",
       "      <td>151.598513</td>\n",
       "      <td>15.769625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>295</td>\n",
       "      <td>19.833733</td>\n",
       "      <td>119</td>\n",
       "      <td>167.944460</td>\n",
       "      <td>39.423099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>236</td>\n",
       "      <td>12.101263</td>\n",
       "      <td>107</td>\n",
       "      <td>139.840817</td>\n",
       "      <td>34.948615</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>79 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     HP        MPG  VOL          SP         WT\n",
       "0    49  53.700681   89  104.185353  28.762059\n",
       "1    55  50.013401   92  105.461264  30.466833\n",
       "2    55  50.013401   92  105.461264  30.193597\n",
       "3    70  45.696322   92  113.461264  30.632114\n",
       "4    53  50.504232   92  104.461264  29.889149\n",
       "..  ...        ...  ...         ...        ...\n",
       "74  175  18.762837  129  132.864163  42.778219\n",
       "75  238  19.197888  115  150.576579  37.923113\n",
       "76  263  34.000000   50  151.598513  15.769625\n",
       "77  295  19.833733  119  167.944460  39.423099\n",
       "78  236  12.101263  107  139.840817  34.948615\n",
       "\n",
       "[79 rows x 5 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Discard the data points which are influencers and reassign the row number (reset_index(drop=True))\n",
    "cars1=cars_new.drop(cars_new.index[[70,76]],axis=0).reset_index(drop=True)\n",
    "cars1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Collinearity Remedy : Best Subset Selection using Rsquared and AIC values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Rebuild the Models using either of the collinear variables on new data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Exclude variable \"WT\" and generate R-Squared and AIC values\n",
    "model_v=smf.ols('MPG~VOL+HP+SP',data=cars1).fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.8161692010376005, 446.11722639447737)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_v.rsquared , model_v.aic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Exclude variable \"VOL\" and generate R-Squared and AIC values\n",
    "model_w=smf.ols('MPG~WT+HP+SP',data=cars1).fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.8160034320495303, 446.1884323575032)"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_w.rsquared , model_w.aic"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Select model with high Rsquared value and low AIC value.\n",
    "Thus, select 'VOL' variable in regression equation so that collinearity problem gets solved and mdodel has 81.62% accuracy"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "## To improve the Model Accuracy further, perform Model - Re-build, Re-check and Re-improvement steps until no influencers are found using Cooks distance ##"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model - Re-build, Re-check and Re-improve - 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Rebuild the model on the new data (Select final model from above)\n",
    "model_v=smf.ols('MPG~VOL+HP+SP',data=cars1).fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Recheck influencers using Cook's distance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([5.53495774e-02, 2.85062799e-02, 2.85062799e-02, 5.34950005e-03,\n",
       "       3.55869338e-02, 3.79038996e-03, 2.85062799e-02, 1.32771748e-03,\n",
       "       1.32771748e-03, 7.56691001e-04, 3.33261259e-03, 1.23339926e-01,\n",
       "       1.14076048e-03, 3.33261259e-03, 6.21782521e-03, 3.33261259e-03,\n",
       "       7.09472284e-04, 1.23339926e-01, 7.09472284e-04, 1.25650858e-04,\n",
       "       1.65511111e-04, 1.01187126e-02, 9.35876569e-06, 1.90597263e-04,\n",
       "       1.71252801e-03, 9.20677227e-02, 4.07373927e-03, 1.65511111e-04,\n",
       "       4.16239310e-02, 3.31390188e-04, 6.85632716e-03, 1.32756399e-03,\n",
       "       3.93747165e-04, 7.49398680e-04, 1.27154771e-03, 6.48751557e-06,\n",
       "       4.76583309e-04, 4.91748288e-03, 4.91748288e-03, 1.49663702e-02,\n",
       "       1.43677902e-04, 3.71158078e-05, 2.37724155e-03, 2.97638136e-03,\n",
       "       6.13773416e-05, 6.29555458e-04, 8.19182717e-08, 1.01290206e-04,\n",
       "       2.15887173e-02, 3.96459368e-03, 3.96459368e-03, 3.96459368e-03,\n",
       "       3.11686431e-06, 1.13032165e-02, 9.69905045e-04, 5.96059114e-04,\n",
       "       1.94992204e-02, 3.96459368e-03, 1.77093418e-02, 6.87800840e-03,\n",
       "       1.90539526e-03, 1.54183373e-02, 2.11396139e-03, 4.56444705e-03,\n",
       "       2.19210440e-03, 1.10974043e-01, 2.57803075e-03, 1.44588390e-04,\n",
       "       6.28652991e-04, 2.04857481e-02, 2.50580184e-04, 8.37099130e-06,\n",
       "       1.43559085e-04, 3.12041737e-02, 3.27473811e-03, 1.34272102e-02,\n",
       "       1.16293875e+00, 4.68738174e-01, 1.38720964e-02])"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get influencers using cook's distance\n",
    "(c_v,_)=model_v.get_influence().cooks_distance\n",
    "c_v"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-44-36b4ce833475>:3: UserWarning: In Matplotlib 3.3 individual lines on a stem plot will be added as a LineCollection instead of individual lines. This significantly improves the performance of a stem plot. To remove this warning and switch to the new behaviour, set the \"use_line_collection\" keyword argument to True.\n",
      "  plt.stem(np.arange(len(cars1)),np.round(c_v,3))\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the influencers using the stem plot\n",
    "fig=plt.figure(figsize=(20,7))\n",
    "plt.stem(np.arange(len(cars1)),np.round(c_v,3))\n",
    "plt.xlabel('Row Index')\n",
    "plt.ylabel('Cooks Distance')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(76, 1.1629387469135126)"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Index and value of influencer where C>1\n",
    "np.argmax(c_v) , np.max(c_v)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reimprove the Model by dropping influencers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "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>HP</th>\n",
       "      <th>MPG</th>\n",
       "      <th>VOL</th>\n",
       "      <th>SP</th>\n",
       "      <th>WT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>49</td>\n",
       "      <td>53.700681</td>\n",
       "      <td>89</td>\n",
       "      <td>104.185353</td>\n",
       "      <td>28.762059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>55</td>\n",
       "      <td>50.013401</td>\n",
       "      <td>92</td>\n",
       "      <td>105.461264</td>\n",
       "      <td>30.466833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>55</td>\n",
       "      <td>50.013401</td>\n",
       "      <td>92</td>\n",
       "      <td>105.461264</td>\n",
       "      <td>30.193597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>70</td>\n",
       "      <td>45.696322</td>\n",
       "      <td>92</td>\n",
       "      <td>113.461264</td>\n",
       "      <td>30.632114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>53</td>\n",
       "      <td>50.504232</td>\n",
       "      <td>92</td>\n",
       "      <td>104.461264</td>\n",
       "      <td>29.889149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>140</td>\n",
       "      <td>19.086341</td>\n",
       "      <td>129</td>\n",
       "      <td>121.864163</td>\n",
       "      <td>42.618698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>175</td>\n",
       "      <td>18.762837</td>\n",
       "      <td>129</td>\n",
       "      <td>132.864163</td>\n",
       "      <td>42.778219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>238</td>\n",
       "      <td>19.197888</td>\n",
       "      <td>115</td>\n",
       "      <td>150.576579</td>\n",
       "      <td>37.923113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>295</td>\n",
       "      <td>19.833733</td>\n",
       "      <td>119</td>\n",
       "      <td>167.944460</td>\n",
       "      <td>39.423099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>236</td>\n",
       "      <td>12.101263</td>\n",
       "      <td>107</td>\n",
       "      <td>139.840817</td>\n",
       "      <td>34.948615</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>78 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     HP        MPG  VOL          SP         WT\n",
       "0    49  53.700681   89  104.185353  28.762059\n",
       "1    55  50.013401   92  105.461264  30.466833\n",
       "2    55  50.013401   92  105.461264  30.193597\n",
       "3    70  45.696322   92  113.461264  30.632114\n",
       "4    53  50.504232   92  104.461264  29.889149\n",
       "..  ...        ...  ...         ...        ...\n",
       "73  140  19.086341  129  121.864163  42.618698\n",
       "74  175  18.762837  129  132.864163  42.778219\n",
       "75  238  19.197888  115  150.576579  37.923113\n",
       "76  295  19.833733  119  167.944460  39.423099\n",
       "77  236  12.101263  107  139.840817  34.948615\n",
       "\n",
       "[78 rows x 5 columns]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Discard the data points which are influencers and reassign the row number (reset_index())\n",
    "cars2=cars1.drop(cars1.index[[76]],axis=0).reset_index(drop=True)\n",
    "cars2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model - Re-build, Re-check and Re-improve - 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Rebuild the model on the new data\n",
    "model_v=smf.ols('MPG~VOL+HP+SP',data=cars2).fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([6.00643020e-02, 3.01041792e-02, 3.01041792e-02, 4.55080735e-03,\n",
       "       3.77482934e-02, 3.33316639e-03, 3.01041792e-02, 9.28389740e-04,\n",
       "       9.28389740e-04, 4.61059555e-04, 3.54160247e-03, 1.09873207e-01,\n",
       "       3.22440506e-03, 3.54160247e-03, 6.59414666e-03, 3.54160247e-03,\n",
       "       5.57007771e-04, 1.09873207e-01, 5.57007771e-04, 3.78932297e-08,\n",
       "       5.04661895e-04, 9.57788156e-03, 1.83209795e-04, 9.55901302e-05,\n",
       "       1.79088663e-03, 7.99583159e-02, 1.22180702e-03, 5.04661895e-04,\n",
       "       3.78767603e-02, 9.39011700e-04, 5.75354249e-03, 1.18961136e-03,\n",
       "       4.60491856e-04, 1.91177808e-04, 1.06997298e-03, 3.27955217e-07,\n",
       "       3.51409910e-04, 4.65109638e-03, 4.65109638e-03, 1.41554819e-02,\n",
       "       2.26815289e-06, 1.39669054e-04, 2.32345177e-03, 2.64657278e-03,\n",
       "       1.18239375e-04, 7.03324096e-04, 6.98268531e-05, 1.71230492e-04,\n",
       "       2.01317340e-02, 3.78431859e-03, 3.78431859e-03, 3.78431859e-03,\n",
       "       2.55792400e-04, 8.49775841e-03, 5.67355078e-04, 1.40690206e-03,\n",
       "       1.79864879e-02, 3.78431859e-03, 1.74655273e-02, 1.01826433e-02,\n",
       "       1.74963865e-03, 1.74540180e-02, 3.57307052e-03, 5.35421993e-03,\n",
       "       2.09765152e-03, 4.89710946e-01, 1.69919316e-03, 8.83433898e-05,\n",
       "       3.87334917e-04, 7.72511987e-02, 9.84759906e-05, 1.11976130e-09,\n",
       "       7.64701489e-03, 3.63812427e-02, 2.26910494e-03, 5.37814088e-02,\n",
       "       1.08345921e+00, 9.70715401e-03])"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Recheck influencers using Cook's distance\n",
    "# Get influencers using cook's distance\n",
    "(c_v,_)=model_v.get_influence().cooks_distance\n",
    "c_v"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-50-095030186e9a>:3: UserWarning: In Matplotlib 3.3 individual lines on a stem plot will be added as a LineCollection instead of individual lines. This significantly improves the performance of a stem plot. To remove this warning and switch to the new behaviour, set the \"use_line_collection\" keyword argument to True.\n",
      "  plt.stem(np.arange(len(cars2)),np.round(c_v,3))\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the influencers using the stem plot\n",
    "fig=plt.figure(figsize=(20,7))\n",
    "plt.stem(np.arange(len(cars2)),np.round(c_v,3))\n",
    "plt.xlabel('Row Index')\n",
    "plt.ylabel('Cooks Distance')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(76, 1.0834592065958668)"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Index and value of influencer where C>1\n",
    "np.argmax(c_v) , np.max(c_v)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "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>HP</th>\n",
       "      <th>MPG</th>\n",
       "      <th>VOL</th>\n",
       "      <th>SP</th>\n",
       "      <th>WT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>49</td>\n",
       "      <td>53.700681</td>\n",
       "      <td>89</td>\n",
       "      <td>104.185353</td>\n",
       "      <td>28.762059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>55</td>\n",
       "      <td>50.013401</td>\n",
       "      <td>92</td>\n",
       "      <td>105.461264</td>\n",
       "      <td>30.466833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>55</td>\n",
       "      <td>50.013401</td>\n",
       "      <td>92</td>\n",
       "      <td>105.461264</td>\n",
       "      <td>30.193597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>70</td>\n",
       "      <td>45.696322</td>\n",
       "      <td>92</td>\n",
       "      <td>113.461264</td>\n",
       "      <td>30.632114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>53</td>\n",
       "      <td>50.504232</td>\n",
       "      <td>92</td>\n",
       "      <td>104.461264</td>\n",
       "      <td>29.889149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>140</td>\n",
       "      <td>19.086341</td>\n",
       "      <td>160</td>\n",
       "      <td>124.715241</td>\n",
       "      <td>52.997752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>140</td>\n",
       "      <td>19.086341</td>\n",
       "      <td>129</td>\n",
       "      <td>121.864163</td>\n",
       "      <td>42.618698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>175</td>\n",
       "      <td>18.762837</td>\n",
       "      <td>129</td>\n",
       "      <td>132.864163</td>\n",
       "      <td>42.778219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>238</td>\n",
       "      <td>19.197888</td>\n",
       "      <td>115</td>\n",
       "      <td>150.576579</td>\n",
       "      <td>37.923113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>236</td>\n",
       "      <td>12.101263</td>\n",
       "      <td>107</td>\n",
       "      <td>139.840817</td>\n",
       "      <td>34.948615</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>77 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     HP        MPG  VOL          SP         WT\n",
       "0    49  53.700681   89  104.185353  28.762059\n",
       "1    55  50.013401   92  105.461264  30.466833\n",
       "2    55  50.013401   92  105.461264  30.193597\n",
       "3    70  45.696322   92  113.461264  30.632114\n",
       "4    53  50.504232   92  104.461264  29.889149\n",
       "..  ...        ...  ...         ...        ...\n",
       "72  140  19.086341  160  124.715241  52.997752\n",
       "73  140  19.086341  129  121.864163  42.618698\n",
       "74  175  18.762837  129  132.864163  42.778219\n",
       "75  238  19.197888  115  150.576579  37.923113\n",
       "76  236  12.101263  107  139.840817  34.948615\n",
       "\n",
       "[77 rows x 5 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Reimprove the Model by dropping influencers\n",
    "# Discard the data points which are influencers and reassign the row number (reset_index())\n",
    "cars3=cars2.drop(cars2.index[[76]],axis=0).reset_index(drop=True)\n",
    "cars3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model - Re-build, Re-check and Re-improve - 4 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Rebuild the model on the new data\n",
    "model_v=smf.ols('MPG~VOL+HP+SP',data=cars3).fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([6.67624758e-02, 3.14966307e-02, 3.14966307e-02, 4.41723601e-03,\n",
       "       3.97043587e-02, 3.18490107e-03, 3.14966307e-02, 2.72885950e-05,\n",
       "       2.72885950e-05, 4.23158478e-04, 3.36657172e-03, 1.11242286e-01,\n",
       "       2.48821721e-03, 3.36657172e-03, 6.02019366e-03, 3.36657172e-03,\n",
       "       4.76170508e-04, 1.11242286e-01, 4.76170508e-04, 8.82063701e-08,\n",
       "       4.85657000e-04, 9.04771072e-03, 1.03596157e-04, 2.90455670e-05,\n",
       "       1.62817845e-03, 8.44546582e-02, 1.41130179e-03, 4.85657000e-04,\n",
       "       2.35932141e-02, 7.74080941e-04, 5.13295810e-03, 8.85600593e-04,\n",
       "       3.71445242e-04, 3.34592443e-04, 6.55775719e-04, 6.50001470e-06,\n",
       "       5.18707563e-04, 5.17386941e-03, 5.17386941e-03, 1.14762595e-02,\n",
       "       1.77539300e-05, 2.94570648e-04, 2.60372905e-03, 3.42589309e-03,\n",
       "       2.95070478e-04, 8.57428219e-04, 1.22100386e-04, 2.68649147e-04,\n",
       "       1.72755037e-02, 4.28555597e-03, 4.28555597e-03, 4.28555597e-03,\n",
       "       3.62914824e-04, 7.40875771e-05, 2.07146665e-04, 9.39876467e-04,\n",
       "       2.64875146e-02, 4.28555597e-03, 2.35370832e-02, 1.44439561e-02,\n",
       "       7.54244071e-04, 2.22909760e-02, 3.09042324e-03, 4.99166459e-03,\n",
       "       1.19956980e-03, 8.77455699e-01, 3.43158228e-04, 4.26655624e-04,\n",
       "       5.78576323e-05, 4.17874337e-01, 1.77853331e-03, 8.86482535e-04,\n",
       "       1.10013827e-02, 4.26552900e-02, 3.21392777e-04, 2.18671336e-01,\n",
       "       1.01193346e-01])"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Recheck influencers using Cook's distance\n",
    "# Get influencers using cook's distance\n",
    "(c_v,_)=model_v.get_influence().cooks_distance\n",
    "c_v"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-55-67901c574f95>:3: UserWarning: In Matplotlib 3.3 individual lines on a stem plot will be added as a LineCollection instead of individual lines. This significantly improves the performance of a stem plot. To remove this warning and switch to the new behaviour, set the \"use_line_collection\" keyword argument to True.\n",
      "  plt.stem(np.arange(len(cars3)),np.round(c_v,3))\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the influencers using the stem plot\n",
    "fig=plt.figure(figsize=(20,7))\n",
    "plt.stem(np.arange(len(cars3)),np.round(c_v,3))\n",
    "plt.xlabel('Row Index')\n",
    "plt.ylabel('Cooks Distance')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(65, 0.8774556986296687)"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Index and value of influencer where C>1\n",
    "np.argmax(c_v) , np.max(c_v)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "As (Cooks distance = 0.877) < 1, stop the Model deletion diagnostics and finalize the Model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Final Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_model=smf.ols('MPG~VOL+HP+SP',data=cars3).fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.866963611185906, 409.41530627195084)"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_model.rsquared , final_model.aic"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "The model's rsquared value is 0.8670. Thus model accuracy is improved to 86.70%"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "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>HP</th>\n",
       "      <th>VOL</th>\n",
       "      <th>SP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>40</td>\n",
       "      <td>95</td>\n",
       "      <td>102</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   HP  VOL   SP\n",
       "0  40   95  102"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# say New data for prediction is\n",
    "new_data=pd.DataFrame({'HP':40,\"VOL\":95,\"SP\":102},index=[0])\n",
    "new_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    46.035594\n",
       "dtype: float64"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Manual Prediction of MPG\n",
    "final_model.predict(new_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     45.428872\n",
       "1     43.992392\n",
       "2     43.992392\n",
       "3     43.508150\n",
       "4     44.085858\n",
       "        ...    \n",
       "72    20.679595\n",
       "73    23.666406\n",
       "74    19.212878\n",
       "75    12.198598\n",
       "76     9.161202\n",
       "Length: 77, dtype: float64"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Automatic Prediction of MPG with 86.70% accurcy\n",
    "pred_y=final_model.predict(cars3)\n",
    "pred_y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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