Lipizian_LOO_DT49.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import necessary libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.tree import DecisionTreeClassifier,export_text\n",
    "import seaborn as sns\n",
    "from sklearn import tree\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.feature_selection import SelectKBest, mutual_info_classif\n",
    "from sklearn.feature_selection import SelectPercentile\n",
    "import pickle\n",
    "from treeinterpreter import treeinterpreter as ti\n",
    "from sklearn.metrics import accuracy_score, classification_report"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\Users\\alexatopal\\AppData\\Local\\Temp\\2\\ipykernel_26096\\4216163439.py:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  all_anatomy_LR=all_anatomy_LR1.append(all_anatomy_LR2).sort_index()\n"
     ]
    }
   ],
   "source": [
    "# loading and converting anatomical data\n",
    "all_anatomy_LR1=pd.read_excel('.\\Lippa_data.xlsx','Anatomy', index_col='ID')\n",
    "all_anatomy_LR1=all_anatomy_LR1.drop(['Timestamp', 'Horse', 'Temperature'], axis=1)\n",
    "all_anatomy_LR2=pd.read_excel('.\\Lippa_data_25ijs.xlsx','Anatomy', index_col='ID')\n",
    "all_anatomy_LR2=all_anatomy_LR2.drop(['Horse'], axis=1)\n",
    "all_anatomy_LR=all_anatomy_LR1.append(all_anatomy_LR2).sort_index()\n",
    "all_anatomy_LR['Sex']=all_anatomy_LR['Sex'].replace(['M','G'],['1','0'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\Users\\alexatopal\\AppData\\Local\\Temp\\2\\ipykernel_26096\\3685161432.py:4: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  kinematics_all=kinematics1.append(kinematics2).sort_index()\n"
     ]
    }
   ],
   "source": [
    "# loading and converting kinematic data\n",
    "kinematics1=pd.read_excel('.\\Lippa_experiments.xlsx','Kinematics_all', index_col='ID')\n",
    "kinematics2=pd.read_excel('.\\Lippa_experiments.xlsx','Kinematics_all_new25', index_col='ID')\n",
    "kinematics_all=kinematics1.append(kinematics2).sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\Users\\alexatopal\\AppData\\Local\\Temp\\2\\ipykernel_26096\\3200758263.py:9: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  housing=housing1.append(housing2).sort_index()\n"
     ]
    }
   ],
   "source": [
    "# loading and converting housing data\n",
    "housing1=pd.read_excel('.\\Lippa_data.xlsx','Housing and work', index_col='ID')\n",
    "housing1=housing1.drop(['Horse', 'Timestamp', 'School horse', 'Housing', 'Equine activities', 'Pasture', 'Number of caretakers', 'Box openess', 'Injury history' ], axis=1)\n",
    "housing1['Type of work']='no'\n",
    "housing1['Type of work']=housing1['Type of work'].where((housing1['Type of work']=='no')&(housing1['Work']==1), 'riding')\n",
    "housing2=pd.read_excel('.\\Lippa_data_25ijs.xlsx','Housing and work', index_col='ID')\n",
    "housing2=housing2.drop(['Horse'], axis=1)\n",
    "housing2['Work']=housing2['Work'].replace(['yes','no'],[2,1])\n",
    "housing=housing1.append(housing2).sort_index()\n",
    "type_of_work=housing['Type of work'].unique()\n",
    "housing['Type of work']=housing['Type of work'].replace(list(type_of_work), [0,1,2,3]) #no=0, riding=1,in training=2,show=3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\Users\\alexatopal\\AppData\\Local\\Temp\\2\\ipykernel_26096\\668016361.py:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  digital_measurment_of_head=digital_measurment_of_head1.append(digital_measurment_of_head2).sort_index()\n"
     ]
    }
   ],
   "source": [
    "# loading and converting digital data\n",
    "digital_measurment_of_head1=pd.read_excel('.\\Additional data 24 horses.xlsx','Head anatomy', index_col='ID')\n",
    "digital_measurment_of_head1=digital_measurment_of_head1.drop(['Horse'], axis=1)\n",
    "digital_measurment_of_head2=pd.read_excel('.\\Lippa_data_25ijs.xlsx','Additional anatomy', index_col='ID')\n",
    "digital_measurment_of_head2=digital_measurment_of_head2.drop(['Horse'], axis=1)\n",
    "digital_measurment_of_head=digital_measurment_of_head1.append(digital_measurment_of_head2).sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\Users\\alexatopal\\AppData\\Local\\Temp\\2\\ipykernel_26096\\3084490103.py:6: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  whorls_of_head=whorls_of_head1.append(whorls_of_head2).sort_index()\n"
     ]
    }
   ],
   "source": [
    "# loading and converting whorls data\n",
    "whorls_of_head1=pd.read_excel('.\\Additional data 24 horses.xlsx','Whorls',index_col='ID' ) \n",
    "whorls_of_head1=whorls_of_head1.drop(['Horse', 'Number of whorls', 'Whorl2_Rotation', 'Whorl2_Height', 'Whorl2_Lateral location'], axis=1)\n",
    "whorls_of_head2=pd.read_excel('.\\Lippa_data_25ijs.xlsx','Whorls',index_col='ID' ) \n",
    "whorls_of_head2=whorls_of_head2.drop(['Horse', 'Number of whorls', 'Whorl2_Rotation', 'Whorl2_Height', 'Whorl2_Lateral location'], axis=1)\n",
    "whorls_of_head=whorls_of_head1.append(whorls_of_head2).sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# loading transformed fear data\n",
    "fear_max_sum=pd.read_excel('.\\Lippa_experiments.xlsx','Fear_max_sum49', index_col='ID')\n",
    "fear_max_sum=fear_max_sum.sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Number of horses')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# target features = maximum from sum of repetition divided to two classes.\n",
    "y=fear_max_sum['binary'] \n",
    "tt=fear_max_sum['binary'].value_counts()\n",
    "plt.figure()\n",
    "sns.barplot(x=tt.index, y=tt, palette=['orange', 'blue']);\n",
    "plt.xlabel(\"Binary label\") \n",
    "plt.ylabel('Number of horses')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    27\n",
       "1    22\n",
       "Name: binary, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y=y.sort_index()\n",
    "y.value_counts()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_initial=pd.concat([all_anatomy_LR, kinematics_all, housing, digital_measurment_of_head, whorls_of_head], axis=1)\n",
    "\n",
    "#remove features that correlate with each other \n",
    "\n",
    "empty_list=[]\n",
    "# LEFT+front measurements\n",
    "corr_list_left=[\"FH10L\", \"FH11L\", \"FH12L\", \"FH13L\", \"FH14L\", \"FH16L\", \"FH18L\", \"FH19L\", \"FB08\", \"FB10L\", \"FB11L\", \"FB12L\", \"FB13L\", \\\n",
    "            \"FB15L\", \"FB16L\", \"FB18L\", \"FB19L\", \"FB20L\", \"FB21L\", \"FB22L\", \"FB23L\", \"FB24L\", \"FB25L\", \"FB26L\", \"FB27L\", \"FB28L\",\\\n",
    "            \"FB29L\", \"FB31L\", \"FB32L\", \"FB34L\", \"FB35L\", \"FB36L\", \"FB37L\", \"FB38\", \"FB39\", \"Walk_DV power\", \"Trot_Stride lengh\",\\\n",
    "            \"Work\", \"HMPF1\", \"HMPF2\", \"HMPF3\", \"HMPF4\", \"HMPF6\", \"HMPF22\", \"HMPF23\",  \"HMPF25\", \"HMPF27\", \"HMPF31\",\\\n",
    "            \"HMPF34\", \"HMPF35\", \"HMPF39\", \"HMPF37\", \"HMPF41\", \"HMPF43\", \"HMPF45\", \"HMPF47\", \"HMPL2\", \"HMPL11\", \"HMPL12\",\"HMPL15\"]\n",
    "\n",
    "# RIGHT+front measurements\n",
    "corr_list_right=[\"FH10R\",\"FH11R\",\"FH12R\",\"FH13R\",\"FH14R\",\"FH16R\",\"FH18R\",\"FH19R\",\"FB09\",\"FB10R\",\"FB11R\",\"FB12R\",\"FB12R\",\"FB13R\",\"FB14R\",\\\n",
    "            \"FB15R\",\"FB16R\",\"FB18R\",\"FB19R\",\"FB20R\",\"FB21R\",\"FB22R\",\"FB23R\",\"FB24R\",\"FB25R\",\"FB26R\",\"FB27R\",\"FB28R\",\"FB29R\",\"FB31R\",\\\n",
    "            \"FB32R\",\"FB34R\",\"FB35R\",\"FB36R\",\"FB37R\",\"FB39\",\"FB40\",\"Walk_Speed\",\"Trot_Speed\",\"Type of work\",\"HMPF2\",\"HMPF3\",\"HMPF5\",\"HMPF7\",\\\n",
    "            \"HMPF20\",\"HMPF21\",\"HMPF24\",\"HMPF26\",\"HMPF30\",\"HMPF32\",\"HMPF33\",\"HMPF36\",\"HMPF38\",\"HMPF40\",\"HMPF42\",\"HMPF44\",\"HMPF46\",\"HMPF69\",\\\n",
    "            \"HMPR2\",\"HMPR11\",\"HMPR12\",\"HMPR15\"]\n",
    "\n",
    "# LEFT + additianal right + front measurements\n",
    "corr_list_left_add=[\"FH10L\", \"FH11L\", \"FH12L\", \"FH13L\", \"FH14L\", \"FH16L\", \"FH18L\", \"FH19L\", \"FB08\", \"FB10L\", \"FB11L\", \"FB12L\", \"FB13L\", \\\n",
    "            \"FB15L\", \"FB16L\", \"FB18L\", \"FB19L\", \"FB20L\", \"FB21L\", \"FB22L\", \"FB23L\", \"FB24L\", \"FB25L\", \"FB26L\", \"FB27L\", \"FB28L\",\\\n",
    "            \"FB29L\", \"FB31L\", \"FB32L\", \"FB34L\", \"FB35L\", \"FB36L\", \"FB37L\", \"FB38\", \"FB39\", \"Walk_DV power\", \"Trot_Stride lengh\",\\\n",
    "            \"Work\", \"HMPF1\", \"HMPF2\", \"HMPF3\", \"HMPF4\", \"HMPF6\", \"HMPF22\", \"HMPF23\", \"HMPF45\", \"HMPF25\", \"HMPF27\", \"HMPF31\",\\\n",
    "            \"HMPF34\", \"HMPF35\", \"HMPF39\", \"HMPF37\", \"HMPF41\", \"HMPF43\", \"HMPF45\", \"HMPF47\", \"HMPL2\", \"HMPL11\", \"HMPL12\",\"HMPL15\",\\\n",
    "            \"HMPF30\", \"HMPF32\", \"HMPF69\", \"HMPR2\", \"HMPR11\", \"HMPR12\",\"HMPR15\"] \n",
    "\n",
    "# # RIGHT + additianal left + front measurements\n",
    "corr_list_right_add=[\"FH10R\",\"FH11R\",\"FH12R\",\"FH13R\",\"FH14R\",\"FH16R\",\"FH18R\",\"FH19R\",\"FB09\",\"FB10R\",\"FB11R\",\"FB12R\",\"FB12R\",\"FB13R\",\"FB14R\",\\\n",
    "            \"FB15R\",\"FB16R\",\"FB18R\",\"FB19R\",\"FB20R\",\"FB21R\",\"FB22R\",\"FB23R\",\"FB24R\",\"FB25R\",\"FB26R\",\"FB27R\",\"FB28R\",\"FB29R\",\"FB31R\",\\\n",
    "            \"FB32R\",\"FB34R\",\"FB35R\",\"FB36R\",\"FB37R\",\"FB39\",\"FB40\",\"Walk_Speed\",\"Trot_Speed\",\"Type of work\",\"HMPF2\",\"HMPF3\",\"HMPF5\",\"HMPF7\",\\\n",
    "            \"HMPF20\",\"HMPF21\",\"HMPF24\",\"HMPF26\",\"HMPF30\",\"HMPF32\",\"HMPF33\",\"HMPF36\",\"HMPF38\",\"HMPF40\",\"HMPF42\",\"HMPF44\",\"HMPF46\",\"HMPF71\",\\\n",
    "            \"HMPR2\",\"HMPR11\",\"HMPR12\",\"HMPR15\", \"FB12L\", \"HMPF23\", \"HMPF35\", \"HMPF39\", \"HMPF45\", \"HMPL12\", \"HMPL13\", \"HMPL17\"]    \n",
    "\n",
    "\n",
    "#left column of corr matrix\n",
    "corr_list_feature1=[\"FH10L\",\"FH11L\",\"FH12L\",\"FH13L\",\"FH14L\",\"FH16L\",\"FH18L\",\"FH19L\",\"FB08\",\"FB10L\",\"FB11L\",\"FB12L\",\"FB13L\",\"FB15L\",\"FB16L\",\"FB18L\",\\\n",
    "           \"FB19L\",\"FB20L\",\"FB21L\",\"FB22L\",\"FB23L\",\"FB24L\",\"FB25L\",\"FB26L\",\"FB27L\",\"FB28L\",\"FB29L\",\"FB31L\",\"FB32L\",\"FB34L\",\"FB35L\",\"FB36L\",\\\n",
    "           \"FB37L\",\"FB38\",\"FB39\",\"Walk_DV power\",\"Trot_Stride lengh\",\"Work\",\"HMPF1\",\"HMPF2\",\"HMPF3\",\"HMPF4\",\"HMPF6\",\"HMPF20\",\"HMPF21\",\"HMPF22\",\\\n",
    "           \"HMPF24\", \"HMPF26\", \"HMPF30\", \"HMPF32\", \"HMPF33\", \"HMPF34\", \"HMPF36\", \"HMPF38\", \"HMPF40\", \"HMPF42\", \"HMPF44\", \"HMPF46\", \"HMPF69\",\\\n",
    "           \"HMPL2\", \"HMPL11\", \"HMPL12\", \"HMPL15\", \"HMPR2\", \"HMPR11\", \"HMPR12\", \"HMPR15\"]\n",
    "\n",
    "#right column of corr matrix\n",
    "corr_list_feature2=[\"FH10R\",\"FH11R\",\"FH12R\",\"FH13R\",\"FH14R\",\"FH16R\",\"FH18R\",\"FH19R\",\"FB09\",\"FB10R\",\"FB11R\",\"FB12L\",\"FB12R\",\"FB13R\",\"FB14R\",\"FB15R\",\\\n",
    "        \"FB16R\",\"FB18R\",\"FB19R\",\"FB20R\",\"FB21R\",\"FB22R\",\"FB23R\",\"FB24R\",\"FB25R\",\"FB26R\",\"FB27R\",\"FB28R\",\"FB29R\",\"FB31R\",\"FB32R\",\"FB34R\",\"FB35R\",\\\n",
    "        \"FB36R\",\"FB37R\",\"FB39\",\"FB40\",\"Walk_Speed\",\"Trot_Speed\",\"Type of work\",\"HMPF2\",\"HMPF3\",\"HMPF5\",\"HMPF7\",\"HMPF22\",\"HMPF23\",\"HMPF45\",\\\n",
    "        \"HMPF25\", \"HMPF27\",\"HMPF31\", \"HMPF32\",\"HMPF33\", \"HMPF34\",\"HMPF35\",\"HMPF38\",\"HMPF39\",\"HMPF37\",\"HMPF41\",\"HMPF43\",\"HMPF45\",\"HMPF47\",\\\n",
    "        \"HMPF71\",\"HMPL13\",\"HMPL12\",\"HMPL17\",\"HMPR11\",\"HMPR12\",\"HMPR13\",\"HMPR17\"]\n",
    "\n",
    "unique_features = [\n",
    "    \"Age\",\n",
    "    \"Trot_Speed\",\n",
    "    \"HMPF38\",\n",
    "    \"FB35R\",\n",
    "    \"HMPF16\",\n",
    "    \"FB16L\",\n",
    "    \"FH10R\",\n",
    "    \"FB15L\",\n",
    "    \"HMPL5\",\n",
    "    \"HMPR1\",\n",
    "    \"HMPF73\",\n",
    "]\n",
    "best_of_the_best=['Age','Trot_Speed','HMPL5','FB16L','FB35R','FH10R','HMPR1','HMPF38']\n",
    "\n",
    "# use of important features identified by DT models with an accuracy >0.8 determined at the first stage of the study\n",
    "\n",
    "# 1.step : removing \"unique_features\" list\n",
    "# 2.step : removing \"best_of_the_best\" list\n",
    "\n",
    "remove_bad_features = [item for item in X_initial.columns if item not in best_of_the_best ]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_initial=X_initial.sort_index()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rs_list=list(range(1, 15000))\n",
    "# 1 stage:             \n",
    "full_corr_list=[empty_list, corr_list_left, corr_list_right, corr_list_left_add, corr_list_right_add, corr_list_feature1, corr_list_feature2]\n",
    "# 2 stage\n",
    "# full_corr_list=[remove_bad_features]\n",
    "\n",
    "def split_by_hand(Features,goal,number):\n",
    "    y_test=goal[[number]] #chose a value from y\n",
    "    X_test=Features.iloc[[number]] #chose a value from X\n",
    "    y_train=np.delete(np.array(goal),(number)) #remove test_instance from the set\n",
    "    X_train=Features.drop(Features.index[number]) #remove test_instance from the set\n",
    "    return X_train, X_test, y_train, y_test\n",
    "\n",
    "max_acc=0\n",
    "number_of_horses=len(X_initial)\n",
    "\n",
    "#loop through different lists of features\n",
    "for corr_list in full_corr_list:\n",
    "    X=X_initial.drop(corr_list, axis=1)\n",
    "    print(len(X.columns))\n",
    "    max_acc=0\n",
    "    \n",
    "    #loop by parameters random_state\n",
    "    for rs in rs_list:\n",
    "        accuracy_list=[]\n",
    "        prediction=[]\n",
    "        selection_features=pd.DataFrame()\n",
    "        \n",
    "        #LOO CV loop\n",
    "        for test_instance in range(number_of_horses):\n",
    "\n",
    "            X_train, X_test, y_train, y_test=split_by_hand(X,y,test_instance)          \n",
    "                \n",
    "            DT_model=tree.DecisionTreeClassifier(criterion='gini', random_state=rs, max_features='sqrt') \n",
    "            \n",
    "            DT_model.fit(X_train,y_train) \n",
    "        \n",
    "            y_predict=DT_model.predict(X_test)  \n",
    "        \n",
    "            prediction.append([y_test[0], y_predict[0]])\n",
    "            \n",
    "            if (y_predict[0]==y_test[0]):\n",
    "                accuracy_list.append(1)\n",
    "            \n",
    "            feats=pd.DataFrame(index=X.columns, data=DT_model.feature_importances_, columns=['Important'])\n",
    "            selection_features=pd.concat([selection_features, feats])\n",
    "        \n",
    "        if sum(accuracy_list)/number_of_horses>max_acc:\n",
    "            max_acc=sum(accuracy_list)/number_of_horses\n",
    "            random_st=rs\n",
    "        print('Random_state=', rs,'set=', len(X.columns), \"Accuracy=\", sum(accuracy_list)/number_of_horses, file=open('output_DT49.txt', 'a')) \n",
    "    print('Random_state=', random_st,'set=', len(X.columns), \"Accuracy=\",  max_acc, file=open('output_DT49.txt', 'a')) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy= 0.9795918367346939 Random state= 5005\n"
     ]
    }
   ],
   "source": [
    "# accuracy for the defined best random_state parameter\n",
    "print(\"Accuracy=\", max_acc, 'Random state=', random_st)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 1235,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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tWPsteXinKv9cLhdz5syJMWPGfOI+q1atioMPPjiefPLJOPXUU3c4Jm1/AEgo57P9d6XF/2kOOuig6N27d6xYsULyB4Bd0fwZeavfmjVr4p133ona2tqSfif5A0AHsWnTplixYkXL59WrV8fSpUujV69e0atXr7j22mtj7NixUVNTEytXrowrr7wyDjnkkBg5srRpCskfABKKFar8Fy9eHKecckrL58mTJ0dExLhx42LWrFnx4osvxr333hsbNmyIfv36xWmnnRbXX399ydMKkj8AJFTq2f7Dhw+P7a3D/+1vf1uW80j+AJDQMe6Dazvu8weAjFH5A0BC2l/pK/kDQMJn5Va/naXtDwAZo/IHgIRK3erXXiR/AEiw2h8ASBWVPwAkpH3Bn+QPAAlpn/PX9geAjFH5A0BC2hf8Sf4AkGDOv530PvArlQ4BOpzGW8+sdAiQSeb8AYBU6TCVPwB0FNr+AJAxKV/vp+0PAFmj8geABG1/AMgYq/0BgFRR+QNAQnOlA2hjkj8AJBRD2x8ASBGVPwAkNKf8Rn/JHwASmlPe9pf8ASDBnD8AkCoqfwBIcKsfAGSMtj8AkCoqfwBI0PYHgIxJe/LX9geAjFH5A0BC2hf8Sf4AkNCc7tyv7Q8AWaPyB4AEz/YHgIxJ+Uv9JH8ASHKrHwCQKip/AEhozpnzB4BMSfucv7Y/AGSMyh8AEtK+4E/yB4AET/gDAFJF5Q8ACZ7wBwAZY7U/AJAqKn8ASEj7gj/JHwAS3OoHABljzh8ASBWVPwAkmPMHgIxJ+5y/tj8AZIzkDwAJzWUcpViwYEGcfvrp0a9fv8jlcjF37txW3xeLxbjmmmuitrY2unbtGiNGjIiXX3655OuT/AEgoZgr3yhFU1NTDB48OGbMmLHN72+88ca4/fbb484774znn38+unfvHiNHjowPPvigpPOY8weADmL06NExevTobX5XLBbjtttui6uuuirOOOOMiIi47777orq6OubOnRvf/OY3d/g8Kn8ASChn279QKERjY2OrUSgUSo5p9erVsXbt2hgxYkTLtqqqqhg6dGgsXLiwpGNJ/gCQUM7kX1dXF1VVVa1GXV1dyTGtXbs2IiKqq6tbba+urm75bkdp+wNAG5oyZUpMnjy51bZ8Pl+haD4i+QNAQjkf75vP58uS7GtqaiIiYt26dVFbW9uyfd26dXHUUUeVdCxtfwBIaM6Vb5TLgAEDoqamJubNm9eyrbGxMZ5//vk4/vjjSzqWyh8AEir1hL9NmzbFihUrWj6vXr06li5dGr169Yr9998/Jk2aFDfccEN87nOfiwEDBsTVV18d/fr1izFjxpR0HskfADqIxYsXxymnnNLy+W9rBcaNGxf19fVx5ZVXRlNTU1x88cWxYcOGOOmkk+Lxxx+PLl26lHQeyR8AEipV+Q8fPjyKxU9ecZDL5eK6666L6667bpfOI/kDQEI5F/x1RBb8AUDGqPwBIKGcq/Q7IskfABIqNeffXrT9ASBjVP4AkJD2BX+SPwAkNKc8/Wv7A0DGqPwBICHtC/4kfwBISHfTX/IHgI9Je+Vvzh8AMkblDwAJnvAHABnjVj8AIFVU/gCQkO66X/IHgI+x2h8ASBWVPwAkpH3Bn+QPAAnpTv3a/gCQOSp/AEhI+4I/yR8AEsz5A0DGpDv1m/MHgMxR+QNAgjl/AMiYYsob/9r+AJAxKn8ASND2B4CMSfutftr+AJAxKn8ASEh33S/583+dcOKx8b3vXxRHHT0oamur41vfvCR+8+gTlQ4L2tX/eGF1PLXyrXjlvabId9otBtfuFd8/8XNx4N7dW/b51Utr4rHla2PZW43RtGVrLPhPw6NHvnMFo6YtaPuTCd26dYuXXloWV0yeVulQoGL+8Pp7ce6R/eO+b3wxZo0ZEh82F+PSuX+Iv27Z2rLPB1u2xgkH7BPfOXZABSOFXaPyJyIinnyiIZ58oqHSYUBFzRjzhVafrx3x+Tj1XxriP95qjCH77h0REd8++oCIiFi85t12j4/2Y7U/QEZt2vxhRERUddHWz5q0P+RH8gfYhuZiMW5esDyOqt0rDtlnz0qHQztLe+Vf9jn/1157Lb7zne9sd59CoRCNjY2tRrGY7n9lAZ8tdfOXxYp3NsWPRh1R6VCg7Mqe/N9999249957t7tPXV1dVFVVtRqFLe+VOxSAnfKj+cvi96vfjrvOOiaqe3SpdDhUQLGMfzqiktv+Dz/88Ha/X7Vq1aceY8qUKTF58uRW2/arParUUADKqlgsxvSG5fHUyrfirrFDYt+qrpUOiQpJe9u/5OQ/ZsyYyOVy223T53K57R4jn89HPp8v6Te0re7du8VBBx3Q8vmAA/aLI444LN57b0OsWfNmBSOD9lM3f1k8tnxt3Pq1wdG9c6dY31SIiIg9852iS6fdIyJifVMh3nl/c7y64f2IiHh5/abovkenqOnRxcJAPjNKTv61tbUxc+bMOOOMM7b5/dKlS2PIkCG7HBjt6+gvHBG/eWx2y+e66VdFRMT9P/9V/OMlV1YqLGhXD/55TUREXPTrJa22Xzvi8/H1w/tFRMT/+vOa+Omi/9fhvPBXiz+2D599zSlfh1Zy8h8yZEgsWbLkE5P/p3UF6Jie+f3zUbXnwZUOAyrqj9/7yqfuc8lxB8clx/m7knZpz2IlJ/8f/OAH0dTU9InfH3LIIfH000/vUlAAQNspOfmffPLJ2/2+e/fu8aUvfWmnAwKASkv7s/095AcAEjrqLXrl4sU+AJAxKn8ASHCfPwBkjDl/AMgYc/4AQKqo/AEgwZw/AGRM2p9Uq+0PABmj8geABKv9ASBj0j7nr+0PABmj8geABPf5A0DGNEexbKMU06ZNi1wu12oMHDiw7Nen8geADuTzn/98PPnkky2fO3Uqf6qW/AEgoZL3+Xfq1Clqamra9Bza/gCQ0FzGUSgUorGxsdUoFAqfeO6XX345+vXrFwcddFB8+9vfjldffbXs1yf5A0BCsYx/6urqoqqqqtWoq6vb5nmHDh0a9fX18fjjj8esWbNi9erVcfLJJ8df/vKXsl5frthBnmFYtefBlQ4BOpw3p4+udAjQIXWbcEebHv+0/qPKdqxHVjz0sUo/n89HPp//1N9u2LAhDjjggLjlllviwgsvLFtM5vwBIKGcT/jb0US/LXvttVcceuihsWLFirLFE6HtDwAfUywWyzZ2xaZNm2LlypVRW1tbpiv7iOQPAB3EFVdcEQ0NDfHKK6/Es88+G2eeeWbsvvvucd5555X1PNr+AJBQqRf7rFmzJs4777x45513ok+fPnHSSSfFc889F3369CnreSR/AEio1ON9f/nLX7bLebT9ASBjVP4AkNDcMe6CbzOSPwAkpDv1a/sDQOao/AEgoVKr/duL5A8ACZI/AGRMB3ntTZsx5w8AGaPyB4AEbX8AyJhKPeGvvWj7A0DGqPwBICHtC/4kfwBISPucv7Y/AGSMyh8AErT9ASBjtP0BgFRR+QNAQtrv85f8ASCh2Zw/AGRL2it/c/4AkDEqfwBI0PYHgIzR9gcAUkXlDwAJ2v4AkDHa/gBAqqj8ASBB2x8AMkbbHwBIFZU/ACQUi82VDqFNSf4AkNCc8ra/5A8ACcWUL/gz5w8AGaPyB4AEbX8AyBhtfwAgVVT+AJDgCX8AkDGe8AcApIrKHwAS0r7gT/IHgIS03+qn7Q8AGaPyB4AEbX8AyBi3+gFAxqS98jfnDwAZo/IHgIS0r/aX/AEgQdsfAEgVlT8AJFjtDwAZ48U+AECqqPwBIEHbHwAyxmp/ACBVVP4AkGDBHwBkTLFYLNso1YwZM+LAAw+MLl26xNChQ2PRokVlvz7JHwASKpX8H3jggZg8eXJMnTo1/vCHP8TgwYNj5MiR8dZbb5X1+iR/AOggbrnllrjoooviggsuiMMPPzzuvPPO6NatW9x9991lPY/kDwAJxTKOQqEQjY2NrUahUPjYOTdv3hxLliyJESNGtGzbbbfdYsSIEbFw4cKyXl+HWfC3cdPKSodAfPQ/aV1dXUyZMiXy+Xylw4EOwd+L7Plw8+tlO9a0adPi2muvbbVt6tSpMW3atFbb1q9fH1u3bo3q6upW26urq2PZsmVliyciIldM+82MlKSxsTGqqqpi48aN0bNnz0qHAx2CvxfsikKh8LFKP5/Pf+wfkm+88Ubsu+++8eyzz8bxxx/fsv3KK6+MhoaGeP7558sWU4ep/AEgjbaV6Leld+/esfvuu8e6detabV+3bl3U1NSUNSZz/gDQAeyxxx4xZMiQmDdvXsu25ubmmDdvXqtOQDmo/AGgg5g8eXKMGzcujjnmmPjiF78Yt912WzQ1NcUFF1xQ1vNI/rSSz+dj6tSpFjXB/8ffC9rLueeeG2+//XZcc801sXbt2jjqqKPi8ccf/9giwF1lwR8AZIw5fwDIGMkfADJG8geAjJH8ASBjJH9atMdrJOGzZMGCBXH66adHv379IpfLxdy5cysdEpSF5E9EtN9rJOGzpKmpKQYPHhwzZsyodChQVm71IyIihg4dGscee2zccccdEfHRU6X69+8fEydOjB/+8IcVjg4qL5fLxZw5c2LMmDGVDgV2mcqfdn2NJACVJ/mz3ddIrl27tkJRAdBWJH8AyBjJn3Z9jSQAlSf5066vkQSg8rzVj4hov9dIwmfJpk2bYsWKFS2fV69eHUuXLo1evXrF/vvvX8HIYNe41Y8Wd9xxR9x0000tr5G8/fbbY+jQoZUOCypm/vz5ccopp3xs+7hx46K+vr79A4IykfwBIGPM+QNAxkj+AJAxkj8AZIzkDwAZI/kDQMZI/gCQMZI/AGSM5A8AGSP5A0DGSP4AkDGSPwBkjOQPABnzfwAtFV7LSbp6vwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# confusion_matrix for the defined best random_state parameter\n",
    "prediction=np.array(prediction)\n",
    "sns.heatmap(confusion_matrix(prediction[:,0], prediction[:,1]), annot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[27  0]\n",
      " [ 1 21]]\n",
      "Precision= 1.0\n",
      "Recall= 0.9545454545454546\n"
     ]
    }
   ],
   "source": [
    "# precision and recall for the defined best random_state parameter\n",
    "compare_matrix=confusion_matrix(prediction[:,0], prediction[:,1])\n",
    "print(compare_matrix)                                        \n",
    "precision=compare_matrix[1][1]/(compare_matrix[1][1]+compare_matrix[0][1])\n",
    "print('Precision=', precision)\n",
    "recall=compare_matrix[1][1]/(compare_matrix[1][1]+compare_matrix[1][0])\n",
    "print('Recall=', recall)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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>Important</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Age</th>\n",
       "      <td>0.256684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FB16L</th>\n",
       "      <td>0.197802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FB35R</th>\n",
       "      <td>0.120596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trot_Speed</th>\n",
       "      <td>0.207335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HMPL5</th>\n",
       "      <td>0.217582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age</th>\n",
       "      <td>0.204545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FB16L</th>\n",
       "      <td>0.197802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FB35R</th>\n",
       "      <td>0.127448</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trot_Speed</th>\n",
       "      <td>0.252622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HMPL5</th>\n",
       "      <td>0.217582</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>245 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Important\n",
       "Age          0.256684\n",
       "FB16L        0.197802\n",
       "FB35R        0.120596\n",
       "Trot_Speed   0.207335\n",
       "HMPL5        0.217582\n",
       "...               ...\n",
       "Age          0.204545\n",
       "FB16L        0.197802\n",
       "FB35R        0.127448\n",
       "Trot_Speed   0.252622\n",
       "HMPL5        0.217582\n",
       "\n",
       "[245 rows x 1 columns]"
      ]
     },
     "execution_count": 1237,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "selection_features[selection_features['Important']!=0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Age           49\n",
      "FB16L         49\n",
      "FB35R         49\n",
      "HMPL5         49\n",
      "Trot_Speed    49\n",
      "dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "forplot=selection_features[selection_features['Important']!=0].sort_values(['Important'], axis=False)\n",
    "\n",
    "sf_list=list(forplot.index)\n",
    "tt=[i for i in sf_list if sf_list.count(i)<0]\n",
    "unique=list(set(tt))\n",
    "for i in unique:\n",
    "    forplot=forplot.drop(i, axis=0)\n",
    "print(forplot.value_counts(forplot.index))\n",
    "plt.figure(figsize=(5,3))\n",
    "plt.scatter(x=forplot['Important'], y=forplot.index, color='darkblue', alpha=0.5)\n",
    "plt.title('Decision Trees ' + 'Feature Importance for LOO')\n",
    "plt.xlabel('FEATURE IMPORTANCE')\n",
    "plt.ylabel('FEATURE NAMES');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "best_of_the_best=['Age','Trot_Speed','HMPL5','FB16L','FB35R','FH10R','HMPR1','HMPF38']\n",
    "#use important features were indiacted from DT models with accuracy >0.9\n",
    "remove_bad_features = [item for item in X_initial.columns if item not in best_of_the_best ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Modeling on the FULL dataset\n",
    "X=X_initial.drop(remove_bad_features, axis=1)\n",
    "DTall_model=DecisionTreeClassifier(criterion='gini',  max_features='sqrt', random_state=5005) #use the best random_state\n",
    "\n",
    "DTall_model.fit(X,y)\n",
    "pickle.dump(DTall_model, open(\"DT_model49.pkl\", \"wb\"))\n",
    "\n",
    "feats_=pd.DataFrame(index=X.columns, data=DTall_model.feature_importances_, columns=['Important'])\n",
    "\n",
    "entities49=list(X.index)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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>Important</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Age</th>\n",
       "      <td>0.252327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trot_Speed</th>\n",
       "      <td>0.214055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HMPL5</th>\n",
       "      <td>0.213889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FB16L</th>\n",
       "      <td>0.194444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FB35R</th>\n",
       "      <td>0.125284</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Important\n",
       "Age          0.252327\n",
       "Trot_Speed   0.214055\n",
       "HMPL5        0.213889\n",
       "FB16L        0.194444\n",
       "FB35R        0.125284"
      ]
     },
     "execution_count": 1241,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feats_[feats_['Important']>0].sort_values('Important', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "feats_for_plot=feats_[feats_['Important']>0].sort_values('Important', ascending=False)\n",
    "plt.figure(figsize=(6,4))\n",
    "#Plot Searborn bar chart\n",
    "sns.barplot(x=feats_for_plot['Important'], y=feats_for_plot.index)\n",
    "#Add chart labels\n",
    "plt.title('Decision Trees Classifier ' + 'Feature Importance')\n",
    "plt.xlabel('FEATURE IMPORTANCE')\n",
    "plt.ylabel('FEATURE NAMES');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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EERGRt1rmjBniPf60MGyWTBkT/VCaO2d2/B754+3j+1Lii0/xoi6xtpm9eOUai1es4dc5CwgMCqLDF4O4fGwXtrY2cfpmc86S4LhPzz17L/efFLL1D3iMP4+fG1twSEisflFRUTzw8k5yP/jvtc+e9fmxJld4eITxcTo7Oz5q3piPPmycogTK66D3kG9Ys3Eb1tZWrFr4G0UKFUj2GObm5qxYMJMm7bpy685dOn/5VazzGZzS881Xffj2x58BSO/w30ymdHa2/8XSrUO84/fp0ZGjrqe4dOU69zwfxCki/Kxd+w/RsfdgoqOj6dnpE4b27Zns+xEREUlLSqKIiMhbzczULNHzYWEpK+D6KhUpVIDvRw6meNHCdOw1iIfePmzdvY+WTT544bGjDTEzDX6b+j1dP22b7H45smXlxsn9LxxHailTshjjvx7Cwn/+5dKV6/zw00zG/zyLqhXL0bFtK1o3b4h9unRpHWaSDB39I/OXrMDc3Jy/f58Wqx5NcrkUyIfr7vXMmv8XW3bu5c5dT+zt01GjcgWG9O3Jrn0xS7xyZneOtQwpW9b/EiKF8udNYOz8xsd373kmmEQ5cuIkrTv1JiwsnPatmvHrj9+m+H5ERETSipIoIiLyTno6Q8XLx5fQ0LAE61d4PNkeNlMCM1pepbYfNqbnoJGEhIRy9fqteNvc93yIS4F8CZ6D2PeSNVMmLl+9gced+8mKJWummPopD719CQsLx8rq+UVvn8qUwYnL3OD+w4S3c34aa3I52Kfjqz49+KpPDw4dc+XPv/9l5brNHDhyggNHTjBg1He0aFKfju1aUatqJUxNEy8Pt3zNRgZ/80OKYpn63agULwUaN3kav8xZgKmpKfOnT6JJg9opGudZDvbpGN6/F8P794pz7unytgplYteJKeqSvJkvCRVfPnX2PM0/7UFQcDBNGtRh/rSJz33tRUREXkf67SUiIu+kUsWKGh8/LTD7/06dPY/fI38ASpd4z3j82Q9/BoPhJUUYl6mpKTbWMbvqWFrGvwRp/5Hj8R4PDg7B7cw5IPa9vP+kZszWXXuTFUu50sUxNzcnIiKCnfsOJqtv6eIx1z+QQKwAh465JmvM+FR5vxy//zwejzMH+P2n8VR5vyzBISEsXbmOhh91plCF2nw74WeuXL+Z4BihoWE88PJO0U9oaFiK4v7lt/nGnWtmTBxD+5ZNUzROUkVERLBmU0yx3/atYl+rasXyxgRZQq/Ts7v+5M6ZI97zTdp15ZF/ALWrVWLZ3GmYm+t7PBEReTMpiSIiIu+kjBmcqFW1EgBTZsyNt83EX+cAMcVJny0q62D/33KQR/4BqRLPiZNn8A9IvCbJtt378fV7BEDJYkXibTN30bJ4x5k1fzFBwcGkd3SgbvUqxuMd2rbExMQE19NnWfrvukSv/zShBGCfLh0tGtcH4JsffyI4OCShboSEhMZaNvXhk3479x3ipPv5OO1Xb9zK9Vu3E40lOdLZ2dH5kzbsWbcM9wNbGPxlD7JlzcLtu/eZ8MtsilVpQM1m7eNNBnVs34pwz8sp+knJ9sbzlyxn6JgJAEweO4LuHdo/p8eL++GnWdy550mRQgWMBYefcrBPR5P6McdmzlsUb/+nx8uULEaWzBljnbt1+y6N2nbGy8eXyhXKsmrhb8matSQiIvK6URJFRETeWaOH9sPU1JS9h47SY8AIY4FUv0f+DB39I/+u3wzAmKEDYvVL7+hA9ieFTxcu+zdVYlmxdhOFKtSm/4ix7DlwhKAnu9oAeD70YsqMuXzyeX8AihctnOAuPMEhITT/tAcXr1wDYmZSzJ6/mG8nxBQNHfxld2xsrI3t3ytc0LhFcff+w/luynQ8n1lm4/fIn3VbdtCqUy+GjP4x1rV+GPUVTukdcT9/iTotPmX3gcPGLZCjo6M5d/EK43+eRZFK9bj/4L/lObWqVqJqxXJER0fzUefe7D141Nhn1YatfD5wJI4O9il7IZ+jcMH8/PjNEK677WXVot9o3qgeFhYWHD7uxqbte17KNZNq5brN9B4SUydkzLAB9O/ZJcl9b3rcwdLZBUtnF+Pr+ax5fy1j6b/reOjlYzx29cYtvhz6LeN/nomVlSW//zw+3iLLo4f2w8rKkt0HjjDo6++NyTQfXz96D/mGo66nAPh6cJ9Y/R54edOoXRfu3POkTMlirFsyF7tnCtWKiIi8iTSXUkRE3llVK5bn5++/ZsCo71i47F8W/bOK9I4O+Ac8Nm7tOqz/F7Rp3ihO3y6ffMQPP81k6JgJjJ00jUwZnADo+3kn+n3eOdmxmFuY88g/gNkLljB7wRIAHB3sCQsPj7UspGD+vKxYMBMzs/gL5v4y/lu+HPItJas3Ir2jA0HBIcata5s0qMPg3t3j9Jk4ehhBwcHMX7KC76ZM57sp00nv6EB0dDQBjwON7Tq2iz2zIl+eXKxbMpc2nXvjduYsH7TphKWlBfbp7Ah4HGS8LsSulWFiYsKfM6ZQ+8OP8bh7j/qtO5DOzo7IqEhCQ8MoX7oEtatXZvL035P9OiaVmZkZTRvUoWmDOjz08mHxijVYp/EMiVHfTzb+vZs9fzGz5y9OsO1t90PJGvvw8ZP89WQLa1sbG0xMTAgKjknUpXd0YNGsqQluNVzUpSB//DqRrv2GMmPeImbNX0x6Rwce+QcY4x07fCDNPqgbq9/cRcu4+mQJ0PWbHhSvmnAh5BepHyMiIvIqKYkiIiLvtF5dP6N86RL8/Nt8Dhw5gY/fIzKkd6Ri+TL06d6BujWqxtvv68F9sLO15e9V67h2w4Nbd+4CKV/e892IQTSqW5Mtu/Zx9MQpLl29jo/fI0xNTcjunIUSRQvTrGE9OrZrlWARXICq75dj38Z/+GHqTA4cOY6pqQnFirjQ5ZM2fNmtQ7zJF3Nzc36b+gOftP6QuX8t49AxVx54eWNqakqBvLkpVfw9GtWtSevmDeP0rViuNGcPbmX2gsVs2LqLS1ev88j/MY4O9hTKn5dqlSrwUfNG5MkVu1ZGnlw5OLptDWMn/cqGbTvx8XtEzmzOtG7eiJEDejNlZvxLrF6GLJkzMqh3t1d2vYRER/9XXycp20Ynx2dtWxAdHc2xk2e47/kQg8HAe4UL0aheLfr37IxzlsyJ9m/boglFXAowdeY89h48gpePH5kyOFGpQhn69egc785BTxMs8PwttFNaP0ZERORVMzG8yop4IiIiT7i5uVGuXDmObltNmZLF0jqcN56lswsAl4/tIm/unGkcjcjLc/LMOSo2aImrqytly5ZN63BEROQdo5ooIiIiIiIiIiJJoCSKiIiIiIiIiEgSKIkiIiIiIiIiIpIEKiwrIiKSim7fvU+Vhq2T1efQln/JlSPbS4pIRERERFKLkigiIiKpKCoqKtk7q0RFRb3wdcM9L7/wGCIiIiKSOCVRREREUlHe3DmV0BARERF5S6kmioiIiIiIiIhIEiiJIiIiIiIiIiKSBEqiiIiIiIiIiIgkgZIoIiIib6hC5Wtj6ezC3oNHU23MvQePYunsQqHytVNtTBEREZG3hZIoIiIi8sY6ePQErTv3ImfxytjnKc57leszbMwEfP0epdo1oqOjqdb4IyydXbB0dmHc5GmJtt936Bgfdf2SXCWqkC53MfKVqU6nL7/i9LkLCfa56XHHOH5iP94+vql2XyIiIpJ82p1HRETkDZU/by6srC2xtbFOtTFtbaxxKZiPHM5ZU23Ml2XOn0vpP3Ic0dHRmJqaks7Olqs3bvHzb/NZsW4Tu9f+TZ5cOV74OvP++odjbqeT1Pa7KdP5bsp0AExNTXF0sOf+Ay/+/ncd/67fzPxpk2jbokmiY2TNnCnBc6am+v5LREQkLSmJIiIi8obaunJRqo9ZoWwpzh7YmurjpjbXU+4MGPUd0dHRdO/QjvFfDyG9owOnzp7n054DuXLtBu279+XQln8xMTFJ8XUeevnwzY8/kSdnDkLDwnjg5Z1g29UbtxoTKJ93/JixwweQMYMTfo/8+X7qDKbPXUi3/sMoWawIRQoVSHCc2+6HUhyviIiIvFz6OkNERETeOOMmTyMqKooq75dl5qRxpHd0AKB08fdYMX8mZmZmuJ4+y9rN21/oOsPGTsDvkT+Tx43A2soq0bbfTZkBQNWK5ZgxaSwZMzgB4JTekanfjaJujSqEhYUzdlLiy4FERETk9aUkioiISBoLeBzI8LETcalQB/s8xSlYrhb9R4zF28eXRctWYensQr2Wn8Xpl1Bh2f/vs2bTNuq0+IRMhcqSoUAZ6rT4hC0798Yby5tQWNbvkT/b9x4EoG+PznFmmrxXuCANalUDYNmqDSm+zt6DR1myci0NalenReMGiba9/+AhZy9cAuDLbh3jbdO3RycANmzbyePAwBTHJSIiImlHSRQREZE05O3jS7XGH/HT7D+4efsOpqam+Pg9YvaCJVRt1AYfP78XGn/c5Gm07dqHw8dPAhAYFMSBIyf48LPPWbF2U2rcwit38JgrkZGRmJiYUKd65Xjb1KlRBYC9h46k6Brh4eH0GT4aS0sLfvr+6+e2v333vvFxoQJ5423jUjA/AGFh4Rw86pqiuERERCRtKYkiIiKShvoOH8vFK9fI4JSelX/Owu/aKfyun2LbykVERkXx4y+zUzz26XMXmPDrb4z/eggPLx3H+4obV0/soXa1ShgMBgZ/8wORkZGpeDevxsXL1wBwzpIZp/SO8bZ5WnPEx/cRXt7J39Hmp9l/cOnKdQZ80RWXAvmS1Tc6Kjre41FRUcbHFy5fTbB/9SZtyViwDA55S1CkYl16DBjByTPnkhWDiIiIvBxKooiIiKSRy9du8O/6zQAsmD6J5g3rGXdfqVWtEiv/nE3A45Qv+/APeMxXfXrwVZ8e2KdLB0DunNlZNPsnrKws8XzolaozIp4uL0ruT3KXDnk+9ALAOWvmBNs8e87TyytZ49+4dZsff5lNrhzZGNG/V5L65MqRzfj4wpVr8ba5+MxxzwcJx3TU9RRmZmYYDAau37rNwmX/Urlh6xdKqImIiEjqUBJFREQkjazfshOImTXRqF6tOOfLlHiP2tUqpXh8CwsLhvTpEed41syZKF+6BADnL11J8fj/L1NGJ7JmzpTsn0wZnZJ1naDgYABsrBMu9GprY/Nf+6DgZI0/cNR3hISEMmnMCOzsbJPUJ1vWLBQr4gLAtDl/YjAY4rT5adYfxsePg4JinbO2tqJXl0/Zs+5v/K6d4uGlE/jfOMOedX9TrVJ5oqOjGT3hZ/5avjpZ9yIiIiKpS1sci4iIpJEz5y8CUOX9sgm2qfJ+OXbuS9mWt3ly5TDOQPl/2Z2zAvAo4HGKxo7P4a2rUm2stLJ641Y27dhD3RpVaN2sYbL6Duv/BR17DcLtzFk+7tGfMcP6UyBvbm7evst3U6Zz+LgbFhYWRERExCmG65wlM7/+ODrWMVNTU6q8X46tKxbSoE1HDh515ZvxU/m0zYfGGUsiIiLyauk3sIiISBrx8Y0pGuucJUuCbZyzJLxk5XmyZ0143Kfb9UZERKR4/LRiZxszOyQkNCzBNsEhIf+1T+JsksCgIAZ/8wMWFhb8/MM3yY6rfcumDOn7OQCrNmyhZPVG2OUqRrEqDVi2aj2dP25DqWJFAHB0sE/yuBYWFowZOgCAe54PVR9FREQkDWkmioiIiLxRniaWEqsr8uCht/FxtiQmoqbOnMede5706d6RnNmdCfy/JTdPl+iER0QQGBSEqYkptrY2sdr8MOorPqhdg3mL/+Gk+zlCQ8IokC83nT5uw8etmhnrvxTKnzdJMT1VoUxJ4+MbHnco92Q5loiIiLxaSqKIiIikkYwZYmqBeD58mGCbp0VU3wSVP2jFnXueye6XM7tzspYCFXGJ2XnH86EXj/wDSO/oEKfN0yKumTI4kSljhiSN63HnHgAz5i1ixrxFCbabNG0Ok6bNIU/OHFw5sTvO+RpV3qdGlffjHPf1e4TH3ZhrVChTKkkxiYiIyOtFSRQREZE0UvK9Ivz97zoOHz+ZYJvDx91eYUQvxtvHjwde3s9v+H+eLi1Kqqrvl8Pc3JzIyEh27T9Mq6YfxGmz60kdmZpVU16YN7WtWLsJg8FA8aKFKV7UJVl9j588Y3ycN1eO1A5NREREkkg1UURERNJI0w/qAHDh8lW27toX5/zpcxfYtf/wqw4rxa6c2E245+Vk/8Q3myMxTukdaVCrGgAz5i2MsxPOxSvX2LbnAADtWjZJ8rh/TJuYaJx5csYkL74e3CfZcd/zfMD3U2cA8FU8OybFt5vPU5GRkYybPA2IWcpUpmSxJF9XREREUpeSKCIiImmkcMH8tGwSM4uic5+v2LBtF9HR0QDsO3SMNp1642Af/+4677pvvuqLmZkZB46coO+wMfg/2WXo9LkLfNT1SyIjIylXqjgfNqofp2+3fsOwdHahXsvPUjWmB17ejPphCifPnCMsLByA0NAw/l2/hVrNPuaBlzdNP6jLJ62bx+lbv1UHJk//nfOXrhr/DkRHR3PkxEkate3C/iPHARg3fCBmZmapGreIiIgknZbziIiIpKEZE8dy7tJlLl+9QauOX2BjY42piSlBwcEUzJeH4f17MXzcRKysLNM61NdKudIl+OWHb+g/chy/L/qbeYv/IZ2dLQGPA4GYOit/z50WZyvhlykkJJTJ039n8vTfMTExIb2jA/4Bj41JkaYf1GXpnF/i7Xvr9l1G/TCFUT9MwcLCAgd7OwKDgo3JGDMzM74d0o/On7R5VbcjIiIi8dBMFBERkTSUOVMGDm5aycAvupInZw6ioqLI6JSeL7t14MCmFVhYxHzfkZwtcd8VPTt/ws7Vi2n6QV0yOqUnLDycAnlzM6BnF07sXEfe3DlfaTyZM2bgm6/6Uq1SebJmzkRgUDBZMmWkcf3a/PPHdFYtnI21dfz1X8Z/M4Run7WlZLEiODk6EPA4CAtzC94rXIienT7h2I41jBjQ65Xej4iIiMRlYkhsEa6IiMhL4ubmRrly5Ti6bbVqPCSia9+hLF6xhlGDvmT00P5pHY5Imjt55hwVG7TE1dWVsmXLpnU4IiLyjtFMFBERkdeUx517rN64DYC6NaqkcTQiIiIioiSKiIhIGrpx6zZfDB7FUddThISEAhAREcGWnXv5oE1HgoKDKVeqONUqVUjjSEVEREREhWVFRETSUFh4OPOXrGD+khVAzPa9gUHBREREAJDdOQsLZkxOyxBFRERE5AklUURERNJQruzZmPDtMLbt3sfV67d46OODlaUlhQvmp3H9Wgzo2YVMGTOkdZgiIiIigpIoIiIiacrOzpZBvbsxqHe3tA5FRERERJ5DNVFERERERERERJJASRQRERERERERkSRQEkVEREREREREJAmURBEREZGXxtLZBUtnF2563EnrUERERERemJIoIiIiImno/oOHZCpU1phw2nvwaIJto6OjWfj3v9Rt8SlZCpfHIW8J3qvSgKGjf8Tbx/cVRi0iIvJuUhJFREREJA199e14Ah4HPrddWFg4LT77nB4DR7D/yHGCgkOwtrLi6vWb/DJnAWVqNeXC5auvIGIREZF3l5IoIiIiImlkx96DrFi7iQplSj637fBxE9myax8WFhZMnzAGnytuPLx0gvOHt1O7WiUeeHnTulMvwsPDX0HkIiIi7yYlUURERETSQFhYOP1GjMXO1paJo4cl2vaBlze/L1oGwFd9etCz8ydYW1sBUDBfHlYsmEXGDOm5euMW85eseOmxi4iIvKuURBEREXlJwsLC+eW3+VRt1IZMhcpil6sYuUtWpWKDlgwbM4GzFy7Hab98zUY6ffkVZWo1/a/mReX69B02JsHirDc97hjraQAcdT1Fi88+J9t775OxYBkatO7IoWOuxvZ+j/wZ8d1kilSsi32e4rhUqMP3U2cQERHx3LEPHDlO80+6k+2990mfrxRVGrbmr+WrU/waPfDyZvi4SZSq0Zj0+UrhlL805es254efZvI4MP4lLgGPAxk3eRrl6zbHKX9p0uUuRr4y1anepC2jJ/7yxhSxnTjtN65ev8mIgb3ImT1bom13Hzhi/PPp061jnPMO9uno1K41AEv/XZf6wYqIiAgA5mkdgIiIyNsoIiKChm07cfBoTPLC1NQURwd7Hnr74PnQi5NnzmFmbsb4r4cY++zYe5DPvhhobJ/e0YGoqGiu3rjF1Ru3+GfNBjb+/QcVypZK8Lrrtuzg4x79iYyMxD6dHY8Dg9hz8AgffOTGpmULKFwwP/Vbd+DC5auks7MjKiqam7fvMG7yNG7fvcecn8YnOPbKdZvp0GsQUVFRpHd0ICw8nBOn3OnWbxjHXE8zfeKYZL1G+w4do02X3jzyDwDA2tqK6Khozpy7yJlzF1m2ej1bVywku3NWY59H/gFUb9qWS1euA2BmZoaDfTrueT7k7v0HHHU9RQ7nrHze6eNkxfKqXbl+k8kzfqdQgXwM6NmFe54PE21/+849ANI7OpA5U4Z427gUzAfEJNGCgoKxs7NN3aBFREREM1FERERehr9XrefgUVcyZ8zAmr/mEOhxlgcXj/P4ljvnDm3jh1FfUSBv7lh97NPZ0b9nZ/Zt+Af/G2fwvHCMx7fccd29nsb1a/PIP4DOfYcSHR2d4HW79RtG549bc/fsYbyvuHHNdS/VKpUnLCycIaN/pPfQbwDYv3E5vtdO4nv1pDGRs2DpSk6fu5Dg2L2++poP6tTg6ok9PLx0ggcXjzN8QC8A5ixcyrLVG5L8+ty4dZtWnb7AP+Ax/T7vzOVju/C/cQb/G2c4uGkF75ctxaUr1+nSZ0isftPnLuTSlesUzJeHXWuWEHT7HA8uHifgpjtuuzcwYmBvsmbJlOQ40kr/EWNjZir98A2WlpZJ7pfYn31UVMw5g8HApavXXzhGERERiUszUURERF6C425nABjwRVca169tPG5hYUGh/HkZ0vfzOH1qVHmfGlXej3XM1NSUEkULs/yP6bxfvyXnL11hz8Ej1KleJd7rli9dgpmTxhmf58qRjUWzfqJAuZq4nTmL+4VLnD2whXx5cgExsz++6tODHXsPsGv/YdZu2k6pYkXjHTtXjuysmD8DCwsLIGYJybjhA/H28WXeX//w3ZTptG/ZNEmvz+iJvxDwOJAxwwYwcmBv43EzMzMqlC3F+qXzKFOrCbsPHOG422nj7JvjbqcBGDNsANUqVTD2s7KypHhRF4oXdUnS9Z9Vr+Vn7Dt8LNn9AMI9Lz+/0f9ZvmYjO/YepEWTBtSvVS1JfXLlzA7ELGW6e9+THNmc47S5eOWa8fH9B17JjktERESeTzNRREREXgJ7ezsAPB+mzodZS0tL6taISZwcdT2dYLvBX/aIcyxndmcK5s8LQJvmjYwJlGfVrl4ZgPOXEt4id8AXXYwJlGcN6ROTELpy7QbuFy4lfBNPBAeH8O/6LVhYWNCne9z6HgBO6R35oE4NAHYdOGw8bm+fDki91xXAycmRrJkzpegnuQIeBzJk9I/Y2tgwZezIJPerVbUi5uYx33398tv8OOe9fXxZuOxf4/PHQUHJjk1ERESeTzNRREREXoIPatdgyoy5zJi3CB8/P9q3bEbViuWwT5cu0X4PvXyY8ccitu3az7Wbt3gcGBRnCYfng4TrZxQrUije41kyZeDKtRuJnM8IgH9AQIJj16j8frzH8+XJRe4c2fG4e49T7ucpUbRwgmMAuJ05S0REBGZmZhSr0iDBdoFBwQDcuetpPPZB7RqsWLuJkd9P5ur1m7Rq2pCK5UpjY2Od6DUTs2L+zBT3Ta7RE37m/oOHjB0+kNxPZpckhXOWzHT+uDXz/vqH6XMX4WBvT/cO7cjolB7X02cZOOp7QkLDjO1NTF5G9CIiIqIkioiIyEtQs2pFvh7chx9/mc3SletYunIdpqamlCxWhKYN6vB5p49xzpI5Vh/3C5f4oHVHvH39jMccHeyxtorZyjYwKJig4GCCgkMSvG62rFniPW5magaAc+bMiZ6PiIhMcOzszvGPDZDNOQsed+/h7eObYJunni41iYqK4oGX93PbB4f8d78d2rXk4LETLFi6kt/+XMpvfy7F3NycCmVK8mGj+nT7rC2ODvbPHTMtnDxzjt/+XErBfHkY1KtbsvtPGTuS6zc92LX/MN9Nmc53U6Ybz5mZmTF13EgGjPoOgPQODqkWt4iIiPxHy3lERERekm+H9OPswa2MHT6QejWrYmNtzSn383w/dQbvVW7A7meWqQB8PmAE3r5+FC9amK0rF+J/4wxel1257X6I2+6H6NezMxBTOPRNFm2ImVmTI1tWwj0vP/fnj2kTjX1NTEyY89N4Tuxax4iBvalWqTxmZqYcPu7G8HETKV71gzhbR78uvvp2PFFRUXw3cjARkREEBgUZf4JDQo3tQkJDCQwKIiwsPFZ/W1sbNi6bzx/TJtKwTg3y58lFwXx5aNO8EXvW/R2r9s7T5VsiIiKSujQTRURE5CUqkDc3Iwb0YsSAXkRERLBr/2FG/TCFM+cu0rXvUK6e2IOZmRm3bt/F9fRZAFYtnE3e3DnjjOXl7fOqw4/lnufDeOMCuP9ki95MGePffvdZWTPF1BJ56O1LWFg4VlZJ353mqZLvFaHke0UACAkJZeP23Yz8bjI3b9+h11dfs3/j8iSP9VHXLzly/GSyYwC47X4oyW09nmxT/HGPfom2a/5pTF2bDm1bxkogQcyMkw5tW9Khbcs4/dZs2gZApgxOcXZ+EhERkdShJIqIiMgrYmFhwQd1alAwf16KVqrH3fsPuHbTA5cC+bjn+QCAjBnSJ5io2HsoZTvIpJb9R47HG9tNjzt43I1JEJQu8d5zxylXujjm5uZERESwc9/BWDMoUsLGxpo2zRuRwcmRhh915vjJM4SEhCa5Toqfn3+SlhW97pav2QhAuyTukCQiIiLJpySKiIjISxAeHo6lZfwzLGysrYyPQ8NiioE+LTjr6+ePl7cvmTPFntGxZOVarly78ZKiTZpf5yygfcumcXbomTpzHgAuBfM9t6gsxNxri8b1WbluM9/8+BO1qlbC1tYm3rYhIaGYmpoaZ6sk/rrGJE2io6OJiIwk/hHj2rF6cRJbvpgrJ3YneO6mxx1c3q8DwPZ//6Jm1YrJGnvnvoP8u34L1tZWfJnAjkciIiLy4lQTRURE5CXo0nconw8cyY69Bwl8ZrvZS1ev02PACCCmJkixwjG75bxXuCDZsmbBYDDQ6cvB3Lp9F4jZDvi3BUv4YvAoMjilf+X38axbt+/Svkc/bt+9D8DjwEDGTvqVOQuXAvD14L5JHuuHUV/hlN4R9/OXqNPiU3YfOExUVBQQkwQ5d/EK43+eRZFK9bj/zG5EDdt2ZvA3P3Dw6AlCn9mN5uSZc/QfOQ6AiuVK42Cf+C5Ib6I9B47w65wFXL/lYdyxycfXj59n/0HrTr0xGAx8N2IQBfPlSeNIRURE3l6aiSIiIvIShIaFsWLtJv78eyUmJiakd3QgNCyMkCcFRG1tbPhj2kTMzGJ2xTE1NWXimOF06j2YHXsPUqhCbRwd7AkKDiEyMpKaVSpSqUIZJv76W5rd0+wp39Oh1yA2bN1FekcHAh4HGhMfPTt9QvtkLCPJlycX65bMpU3n3ridOcsHbTphaWmBfTo7Ah4HERERYWxr8sx+vQGPA5k+dyHT5y7E1NSU9I4OBAYFER4e0z5TBidmTfkule749eJx5x5DRv/IkNE/YmFhgZ2tDY/8Y7akNjMzY/TQ/vTv2SWNoxQREXm7KYkiIiLyEnw/cjCVy5dl94HDXLtxi/sPvTAYDBQqkI+61SszoFdX8ueJXfyzfcumODk6MGnaHNzOnCMyMoqiLgX4uFVz+vfszI+/zE6ju4nRpnkjnLNkYuKvv3H8lDtWlpa8V7ggvbp+Fm+h0+epWK40Zw9uZfaCxWzYuotLV6/zyP8xjg72FMqfl2qVKvBR80bkyZXD2GfO1B/YtGMP+w4d46bHHTy9vDA3M6dQkXw0rFuTgV90JUvmjKl526+NKhXL0bdHJ/YdPsbtu/cJCg4mb66c1Kxakd5dP6NMyWJpHaKIiMhbz8Twpu+TKCIibyQ3NzfKlSvH0W2r9eHvNfZsrY5wz9dz62B5t5w8c46KDVri6upK2bJl0zocERF5x6gmioiIiIiIiIhIEiiJIiIiIiIiIiKSBEqiiIiIiIiIiIgkgZIoIiIiIiIiIiJJoN15REREJEF5c+dUQVkRERGRJzQTRUREREREREQkCZREERERERERERFJAiVRRERERERERESSQEkUEREREREREZEkUBJFRETkNbJo2SosnV2o1/KztA7ltVOv5WdYOrvE+rnpcSetw3pjjZs8Lc7ruWjZqrQOS0RE5LWm3XlERETkjeJgnw4ba2sAzMzMYp0LCQll4/bdbN21j+Mnz3DT4w5R0VFky5KFKhXL8mXXDlQoWyreceu1/Ix9h48lKYZ5v06gY7tWL3YjT/gHPGbt5u3s2HuQE6fcuXPvPiYmJuTMno1aVSvSt0cnihQqkOp909nZkTVzJgB8H/kTERGRKvcjIiLyNlMSRURERN4oP333NR3bx5/AaP5pD/YeOmp8bm1thZmpGTdv3+Hm7TssW7WBscMHMKzfF3H6Ojk5GpMK8QkOCeFxYBAAZUoWe8G7+E+Fuh9y8/Z/M2rsbG2JjIrkyrUbXLl2g0X/rGLW5O/o0LZlqvYd1Lsbg3p3A5KXQBIREXmXaTmPiIiIvDUiIiMoVCAfE0cP49yhbQTcdMfv+ilO7tlI3RpViI6O5pvxP7Fh2644fVfMn8lt90MJ/jSsWxOAUsWLUqJo4VSNuWzJ4sycNI5rrnvxu36KR9dPs3/jcsqULEZYWDifDxzJqbPnU7WviIiIJJ+SKCIiIvLWGP/1ENz3b2Zgr24Uyp8XABMTE4oVKcTqRXMo6lIQgF9mz0/WuAGPA1m/dSdAvLM6XsRfs3/iyLZV9OjYnlw5sgExy5QqlivNxr//IEumjERFRTH994Wp2ldERESST0kUERGReNz0uJOk4qVXb9zC0tkFq2yFuX33vvH47bv3mTz9dxq360KRinWxz1OczC7lqNG0HTPnLSI8PDzZMT0vnr0Hj2Lp7EKh8rUTHGPvwaO0796PvKWrYZerGNnee59mH3eLd2bGm6jK++UwNY3/7Y21tRVtmjcC4KT7uWSNu3LdJkJDwzA3N6d9y2YvHOezqlWqkOC5TBkzGGfAnHSPO5vkRfqKiIhI8imJIiIiEo+8uXNSsVxpAFas3ZRgu39WbwCgasVyxpkAAF99O55RP0xhx96D3HvwEFsbG/wDHnPkxEkGfv09Tdp3S1EiJaUMBgNDR/9I/dYdWLVhC/c8H2JjbYWP7yO27t5Pq45fMHDUd68snrSS0Sk9AFFR0cnqt3jFGgAa1K5OlswZUzmqxP0Xc9Qr7SsiIiJxKYkiIiKSgLYtmgCwfO3GBNs8TbC0/bBJrONFXQoy7cfRXDy6A/8bZ3hw8Tj+N86w9PdfyZEtK3sPHWXKzHkvL/j/8+ucBfwyZwE5szszf/okfK664X3FDd9rJ5k95Tsc7NMx84+/jMmCt9W+w8cBKFakUJL73Lh1m4NHXQH47KMWLyOsRD0t+JqcmFOjr4iIiMSlJIqIiEgC2jRvhKmpKafPXuDS1etxzrtfuMT5S1cwNzendbNGsc6NGdafL7p8Sv48uTExMQHAxsaaNs0bsfT3XwGY99eyl38TwCP/AMZOmoadrS2b/lnAZx+1wD5dOiBmm9tun7Vj9pTvAZg0bU6yxh43eZpxmVFyf/YePPr8C6Si0+cusHbzdoBkbU+8ZOVaDAYD6R0daPZB3ZcVXrw2btuN6+mzQPJiftG+IiIiEj9tcSwiIpKAbFmzUKPy++w5eITlazbyzVd9Y51fviZmhkrtapXInClDksetXKEs6R0duHPPk7v3PcmRzTlV4/5/qzZsISg4mDbNG1GkUIF427Rs0gArK0suXrnG/QcPyZY1S5LGTmdnl+i2wImxtLRIUb+UCA4OoVPvr4iKiqJU8aJ0/fSjJPddunItAB992BgrK8uXFWIcng+96PXV1wA0rlfLWN/kZfcVERGRhCmJIiIikoh2LZuw5+ARVqzdFCeJsvLJUp52LZrG2/fg0RP8vmgZR0+c5P5DL0JCQuO08Xzg9dKTKEdOnAJgy8595CpRJcF2ERGRANy5ez/JSZRBvbsxqHe3F47xZYqOjqZz3yGcv3QFB/t0/DX7JywskpbAOXzcjas3bgGvdilPSEgobbv2wfOhF7lyZOP3n398JX1FREQkcUqiiIiIJKJlkw/oN2IcF69c48z5i5R8rwgAx91Oc+2mB1ZWlnzYuH6cfhN+nc23P/5sfG5hYUEGp/RYmMf86vXy8SU6Opqg4JCXfg+eDx4CEBgURGBQ0HPbB8eT7HmT9R7yDWs2bsPa2opVC39LcDZOfJ7WiCmYPy+VK5R9SRHGFhERQbtufThy4iQZM6Rn/dI/klzM9kX6ioiIyPMpiSIiIpKIDE7pqV+zKpt27GH5mo3GJMrTYrMf1KmBo4N9rD7uFy4xZmJM3ZMvOn9Cnx6dKJgvT6ytd/OXrcGde54YDIaXfg/RT64xfEAvxg0f+NKv9zoZOvpH5i9Zgbm5OX//Po0aVd5Pct+wsHBWrtsMwKdtPnxZIcYSFRVFx95fsWXXPuzT2bF+yTzeK1zwpfcVERGRpFESRURE5DnatmzKph17WLl2E9+PHIzBYDB+uI5vKc+ajduIjo6mRuX3mTZhTJzzUVFR+Pg9SnYcZmZmREVFERoWFu95/8eP4z2eJVPMTITbd+4l+5rP89OsP/h59h8p6rt8/oyXOrtj3ORp/DJnAaampsyfPokmDWonq/+Gbbvwe+SPiYnJK0miGAwGeg4axb/rNxtnzZQvU/Kl9xUREZGkUxJFRETkOZo3rIuNjTXXb93muNtpQsPCuXv/AXa2tjSpH/eD+T3PBwCUK1U83vGOuZ2Otz7K86R3tMfH9xH3PB/EuyTl6U4s/69iudIsXrGGXfsPExkZibl56v36DwwK4oGXd4r6hodHpFoc/++X3+bz/dQZAMyYOIb2LeOvW5OYp0t5qleqQN7cOVMzvHgN/uYHFv2zCgsLC/6ZN52aVSu+kr4iIiKSdNriWERE5DnS2dnRuF5MsmT52o3GXXmaNayLra1NnPYOT7YPvnTtRpxz0dHRfDdleoriKF6kMAAbtu6Kc87vkT8LlqyIt1/rZg2xs7Xl/oOHTJ4xN9Fr+D3yT1ZM3w7pR7jn5RT9vKwP+vOXLGfomAkATB47gu4d2id7DC9vX7bt3g+8moKyoyf+wox5izAzM2PRrKk0qlfrlfQVERGR5FESRUREJAnatmgMwMp1m1m1YcuTY03ibVu7emUANm3fzS+/zScsLByAmx53+LhHf/YfOY6drW2yY2jV9AMA5i3+h8Ur1hAeHjOu6yl3GrXtQtiT5/8vU8YMjB0+AIDRE35m4KjvuHHrtvF8YFAQO/YepHOfr/i4R79kx/U6WbluM72HfAvAmGED6N+zS4rG+WfNBiIiIrC1saF184ZJ6lOofG0snV0YN3lasq71y2/z+fHnWZiYmPD7z+Np3Sxp13vRviIiIpJ8Ws4jIiKSBI3q1sLBPh1378cs1XFK70iDWtXibftBnRo0rFODLbv2MXTMBIaPm4SDfToe+QdgamrKjIljmPjrHIKCg5MVQ7fP2rLon1W4nj5L175D6TloFFaWlgQGBZE7R3Z++v5ruvQZEm/ffp93xu+RP+N/nsXMP/5i5h9/YZ/ODjMzM/wDHhsL3Nas8mYvAxn1/WSio6MBmD1/MbPnL06w7W33QwmeW7x8DQDNG9XD/snMopdl2NiJAJiamjLyu8mM/G5yvO1yZnfm8NZVqdZXREREkk9JFBERkSSwtrbiw0b1+Wv5agBaNK6PpaVlvG1NTExY+ecsJvz6G8tWrefWnXuYm5nRsE4NBvbuRu1qlZn465xkx2BpacmWFQv5fup0Vm/YhqeXF+kd7fnsow/5dkg/zl28kmj/0UP782Hj+sz6YzH7Dh3l/kMvwsLDyZndmRLvFaFBrWoJzq55U0RH/7fbUUprtVy4fBW3MzH1ZZK6lCcyMhJvXz8AypQslqzrPU1gRUVFJRqztZVVqvYVERGR5DMxvIq9FUVERP6Pm5sb5cqV4+i21cn+0CnvpnotP2Pf4WPM+2UCHdu3SutwYjnqeorqTdryXuFCnNyzARMTk7QOKVle59f2/508c46KDVri6upK2bIvb3cnERGR+KgmioiIiMgL2nfoGABD+n7+xiVQREREJOmURBEREZE3SvcBw7F0dsHS2YWbHnfSOhwADhw5Tt5cOWn3Bi2HGjd5mvF13Hf4WFqHIyIi8kZQTRQRERF5Izg5OZI1c6ZYx8zMzNIomtjWLkl86+jXUTo7uzivp7W1aqeIiIgkRkkUEREReSOsmD8zrUN4qwzq3Y1BvbuldRgiIiJvFC3nERERERERERFJAiVRRERERERERESSQEkUEREREREREZEkUBJFRETkHVWv5WdYOruwaNmqtA5FRERE5I2gJIqIiIjIC4iMjGT63IVUbNCSDAXKkNmlHLWat+ev5avTOjQRERFJZdqdR0RERCSFwsLCafpxN/YeOgqAjY014RHhHDrmxqFjbuzad4j50ydhYmKSxpGKiIhIatBMFBEREZEUGvHdJPYeOko6Ozv+njuNR9dP8+j6aaZPGIO5uTlLVq5l9vzFaR2miIiIpBIlUURERERS4O59T35f9DcAk8cOp3WzhpiYmGBubk7Pzp8wqHc3AMb/PIuwsPC0DFVERERSiZbziIiIvEUOHDnOnIV/c+iYKw+8vHG0tydPrhw0rl+bTu1bkytHtiSNs+/QMVZt2MJR11PcueeJn78/GZ2cqFS+DP0+70TViuXj7RcWFs7sBYtZsXYTl65eJyQ0jIxO6cnmnIVaVSrSoV0rihd1idVnz4EjzJz/F8dcT+Pt64edrQ2ZM2WkdPGiNG9Uj3Ytmr7w6/IyrNm4jfDwCDI4padD25Zxzvft0YkpM+by0NuHnfsO0rh+7TSIUkRERFKTkigiIiJvgejoaL76djwz5i0yHnN0sCc4JJQTp9w5ccqd6Ohovh3S77ljBQYFUa/VZ8bnDvbpsDC34P6Dh6zeuJU1m7YxY+JYenRsH6tfREQEDdt24uBRVwBMTU1xdLDnobcPng+9OHnmHGbmZoz/eoixz5w/l9J3+Bjjc/t0doSGhXHl2g2uXLvBvkPHXtskyt7DxwCoWrEclpaWcc5nzZyJYkUK4X7+EnsPHlUSRURE5C2gJIqIiMhbYOK0OcyYtwgTExMG9upGv887kd05KwA3Pe6weuNW7NPZJWksUxNT2jRvxGcftaBqxfI4OtgDcM/zAdPnLmLqzLkM/Po76tasQv48uY39/l61noNHXcmcMQNzf/mRBrWrY25uTkREBDdv32XNxm1kcHI0tg8KCmb4uEkADO3XkwE9u5ApYwYAvLx92X/kOFt27k2V1+dluHj5GgBFXQom2KZIoQK4n7/ExSvXXlVYIiIi8hIpiSIiIvKGe+jlw4+/zALg+5GDGdL381jn8+bOycBe3ZI8nq2tDUt//zXO8ezOWfnxmyE88vfnj8XLWbhsFWOHDTCeP+52BoABX3SNNevCwsKCQvnzxonr/KUrBAUHU7hQfr4fOTjWucyZMtCq6Qe0avpBkuMG2HvwKPVbd0hWn6e+HtwnSTN1nvJ86AVAtiyZE2yTLWuWmLZe3imKSURERF4vSqKIiIi84VZt2EJoaBjZnbMwsFfXl369hnVr8sfi5RxzPRXruL19zEyXp8mF57G3TwdAQEAgwcEh2NravHBslpYWZM2cKUV909klbabOU0HBIUDMtsYJeXouMCg4RTGJiIjI60VJFBERkTfcMbfTANSpXgVz89T51R4eHs78JStYtWEr5y5exs8/gMjIyFht7j+InSz5oHYNpsyYy4x5i/Dx86N9y2ZUrVgO+3Tp4r1GwXx5KJA3N9duelC9aVt6dfmUujWqki9PrhTHXblCWW67H0pxfxEREZHEKIkiIiLyhvPy9gEgV87sqTJewONAGn7UiROn3I3H7GxtyZDeERMTE8IjIvB75E/wk5kYT9WsWpGvB/fhx19ms3TlOpauXIepqSklixWhaYM6fN7pY5yfWfpibm7OwllT+ajLl7ifv0TvId8CMUtg6tWsSueP21C9coVUuaeXwc7Whkf+EYSEhCbY5um5dHa2ryosEREReYlM0zoAEREReb2M/2kmJ0654+hgz8JZU/G8cAy/66e4c/Ywt90P8ffcmHopBoMhTt9vh/Tj7MGtjB0+kHo1q2Jjbc0p9/N8P3UG71VuwO4Dh2O1f79sKS4c3s786ZP4uHVzcufIzv0HD/lr+WrqtvyUvsPGvIpbTpGnCaH7iSxfSkrdFBEREXlzaCaKiIjIGy7LkxogHrfvpsp4qzZsBWDquFF83KpZnPMPvX0T7V8gb25GDOjFiAG9iIiIYNf+w4z6YQpnzl2ka9+hXD2xBzMzM2N7W1sbPvuoBZ991AKAS1evM2PuIuYsXMqchUtp1rAuDWpXT1Lsh4+70bZrnyTeaWwDe3VjUO+kF+At4lKAi1euJbrzztNzRQoVSFFMIiIi8nrRTBQREZE3XMVypQHYtf9wnLolKXHX8wEAZUsVj/f83oNHkjyWhYUFH9SpwT9/zIgZ+/4Drt30SLRP4YL5mT5xDFUrlgNg3+FjSb5eeHgED7y8U/QTGBSU5OsA1Kz8PgAHjpwgPDw8zvkHXt6cvXA5pm3ViskaW0RERF5PSqKIiIi84Vo1/QAbG2vuP3jIz7Pnv/B4Dk922bl87Uacc5ev3WDpv+vi7RdfIuEpG2sr4+PQsLDnto/pE7OzTdiT9klRs2pFwj0vp+gnOdsbA7Ro0gBLSwt8/R6xZOXaOOdn/vEX0dHRZMmUkTrVqyRrbBEREXk9KYkiIiLyhsuUMQMjBvQC4OvxUxnx3WTuPZlNAnDT4w7fTZnO7wv/TtJ4tatVBmD42IkcOXESg8FAdHQ0W3fto3HbLsbkxv/r0nconw8cyY69B2PN6rh09To9BowAIEe2rBQrXAiAzTv3UqNpOxYsXcHtu/eN7R8HBjJ15jx27ovZZad+raQt5XnVcmRzpmenTwD46tvxrN64FYPBQGRkJHMXLWPKjLkAjBzYGysry7QMVURERFKJaqKIiIi8BYb27YnnAy9mzV/M1JlzmTpzLukdHYiMjDImNL4enLRaIaOH9mf7ngPcvH2HGk3bYWtjQ7QhmtDQMLI7Z2Hy2BF06zcsTr/QsDBWrN3En3+vxMTEhPSODoSGhRl3qLG1seGPaRNj1UM5cuIkR06cNJ63tLTgkX+A8XyPju2TXA8lLYz/eghnzl1k76GjtOvWF1sbG6KiowgLi5ll82mbD+nV9bM0jlJERERSi5IoIiIibwFTU1N+Gf8tLRo3YPaCJRw5cRJvXz8ypHfkvcIFadKgDh3btUzSWIUL5ufAphWMmfgruw8cJjAoiBzOWWlUrxYjB37JhctX4+33/cjBVC5flt0HDnPtxi3uP/TCYDBQqEA+6lavzIBeXcmfJ7exfe1qlVkwYzI79x7kpPt57j94SMDjQLJmzkS5UsXp+llbmjeslyqvz8tiZWXJ5uULmDV/MYtXrOHKtZtYWVpStmRxundoR4e2SXvNRURE5M1gYohvf0IREZGXzM3NjXLlynF022rKlCyW1uGIyBvi5JlzVGzQEldXV8qWLZvW4YiIyDtGNVFERERERERERJJASRQRERERERERkSRQEkVEREREREREJAmURBERERERERERSQIlUUREREREREREkkBJFBERERERERGRJFASRUREREREREQkCZREERERERERERFJAiVRRERERERERESSQEkUEREREREREZEkUBJFRERERERERCQJlEQREREREREREUkC87QOQERE3m0XrlxL6xBE5A2ifzNERCQtmRgMBkNaByEiIu8eDw8PihYtSnBwcFqHIiJvGFtbWy5cuEDu3LnTOhQREXnHKIkiIiJpxsPDA29v7xcaw9PTk7Fjx3Ls2DHatGlD//79sbW1TaUIReRFBAcH8+uvv7Jy5UoqVqzIt99+i7Oz8wuPmylTJiVQREQkTSiJIiIibySDwcCiRYvo168f9vb2zJ8/nwYNGqR1WCISj23bttG1a1cCAwOZNm0aHTp0wMTEJK3DEhERSTYVlhURkTfOgwcPaNmyJZ07d6ZFixacPXtWCRSR11iDBg04e/YszZs3p1OnTrRq1YoHDx6kdVgiIiLJppkoIiLyRlm5ciVffPEFZmZmzJkzhxYtWqR1SCKSDKtXr6Znz54YDAZ+++03WrdundYhiYiIJJlmooiIyBvB19eXTz/9lI8++oiaNWty9uxZJVBE3kAtW7bk3Llz1KhRgzZt2vDZZ5/h5+eX1mGJiIgkiWaiiIjIa2/z5s1069aNkJAQZsyYwSeffKJ6CiJvOIPBwNKlS+nTpw+2trb88ccfNGzYMK3DEhERSZRmooiIyGvr8ePHfP755zRu3JhSpUpx9uxZPv30UyVQRN4CJiYmfPrpp7i7u1OiRAkaNWpEz549efz4cVqHJiIikiDNRBERkdfS3r176dy5M15eXvz000/06NFDyRORt5TBYGDu3LkMGjSILFmy8Oeff1KjRo20DktERCQOzUQREZHXSkhICAMHDqRWrVrkzp2bM2fO8PnnnyuBIvIWMzEx4fPPP+fMmTPkzJmTWrVqMWjQIEJCQtI6NBERkVg0E0VERF4bx44do2PHjty8eZMff/yR/v37Y2qqfL/IuyQ6OppffvmFkSNHki9fPhYtWkSFChXSOiwRERFAM1FEROQ1EB4eztdff03lypWxt7fn5MmTDBw4UAkUkXeQqakpgwYN4uTJk6RLl47KlSvzzTffEB4entahiYiIaCaKiIikrTNnztCxY0fOnTvH6NGjGT58OObm5mkdloi8BiIiIpgwYQLjxo2jePHiLFq0iBIlSqR1WCIi8g7TV3wiIpImIiMjmTBhAuXLlycqKopjx47x9ddfK4EiIkYWFhZ88803HDt2jMjISMqVK8eECROIiopK69BEROQdpSSKiIi8cpcvX6Z69eqMGjWKQYMGceLECcqUKZPWYYnIa6pMmTKcOHGCQYMGMWrUKKpXr86VK1fSOiwREXkHKYkiIiKvTHR0NNOnT6d06dJ4e3uzf/9+JkyYgJWVVVqHJiKvOSsrKyZMmMD+/fvx8vKiVKlSzJgxg+jo6LQOTURE3iFKooiIyCtx69Yt6tevT79+/ejWrRunTp2iSpUqaR2WiLxhqlSpwqlTp+jWrRt9+/alfv363Lp1K63DEhGRd4SSKCIi8lIZDAbmz59PiRIluHLlCjt27GD69OnY2dmldWgi8oays7Nj+vTpbN++nStXrlCiRAkWLFiA9ksQEZGXTUkUERF5ae7fv0/z5s3p1q0bbdq0wd3dnbp166Z1WCLylqhXrx7u7u60bt2arl278uGHH+Lp6ZnWYYmIyFtMSRQREXkp/vnnH4oXL87x48dZu3Yt8+fPx9HRMa3DEpG3jKOjIwsWLGDt2rUcO3aMYsWKsXz58rQOS0RE3lJKooiISLLcuHGDQYMGJXjex8eH9u3b0759e+rWrcvZs2dp3rz5K4xQRN5FzZs35+zZs9SpU4d27drx8ccf4+Pjk9ZhiYjIW8bEoMWjIiKSDM2aNePcuXNcv349zrkNGzbQo0cPwsPDmTVrFu3atUuDCEXkXWYwGPjnn3/o3bs3VlZWzJs3jyZNmqR1WCIi8pbQTBQREUmyXbt2sWHDBiZMmBDreEBAAN26daNZs2aULVuWs2fPKoEiImnCxMSE9u3bc/bsWcqUKUPTpk3p3r07AQEBaR2aiIi8BTQTRUREkiQ6Opry5ctjZWXFoUOHMDExAWISK126dMHX15dffvmFrl27Gs+JiKQlg8HAH3/8wcCBA8mYMSMLFiygdu3aaR2WiIi8wTQTRUREkuSvv/7i5MmTTJ06FRMTE4KDg+nXrx9169Ylf/78uLu7061bNyVQROS1YWJiQvfu3XF3dydfvnzUqVOH/v37ExwcnNahiYjIG0ozUURE5LmCg4NxcXGhSpUqLF++nMOHD9OpUydu377NxIkT6dOnD6amysuLyOsrOjqa6dOnM3z4cHLnzs3ChQupVKlSWoclIiJvGL3jFRGR55o6dSpeXl6MHTuWESNGUK1aNTJkyMCpU6fo16+fEigi8tozNTWlf//+nDp1ivTp01O1alVGjRpFWFhYWocmIiJvEM1EERGRRHl6elKwYEFatWrFqVOnuHjxImPGjGHo0KGYm5undXgiIskWGRnJpEmTGDNmDEWLFmXRokWUKlUq3rZRUVGcOXOGMmXKvOIoRUTkdaQkioiIJKp79+4sXbqU8PBwihUrxqxZs7C1teX69etcu3bN+N/79+/z559/Ur58+bQOWUQkSU6fPk3Hjh25cOECo0ePZtiwYXGSw5cuXaJIkSKsXbuW5s2bp1GkIiLyulASRd4oHh4eeHt7p3UYIm+1TJkykTt3bgD27t1LrVq1AMiePTthYWH4+PgY29rb21OgQAEKFChAoUKFGDx4MJkyZUqLsEVEUiQsLIyxY8cyceJEypcvz6JFiyhcuLDxvMFgoH79+ty5cwd3d3csLCwSHEvvU0T+8+z7CZG3iZIo8sbw8PCgaNEiBAeHpHUoIm81W1sbLly4SO7cuZk6dSpff/01RYsWpXTp0uTPn58CBQoY/5sxY0btxiMib4UjR47QqVMnPDw8mDBhAn379jXWezp9+jRlypRh+vTpfPnll/H29/DwoEjRooRo5x8RAGxsbbl44YISKfLWURJF3hhubm6UK1eOOYPaUjhX5rQOR+StdOm2Fz1/Wo6rqytly5ZN63BERF6p4OBgRowYwbRp06hVqxYLFiwgb968AHTt2pX169dz9epVHB0d4/R9+j6lyfDfyJjb5RVHLvJ68fG4zMYJX+j9hLyVVBFQ3jiFc2WmVIEcaR2GiIiIvGVsbW359ddfadGiBV26dKFEiRL8/PPPdOvWje+//55//vmH8ePHM3HixATHyJjbBedC8RepFRGRN5/2pBQREREReUbt2rU5c+YM7dq1o0ePHjRt2hSAIUOG8Msvv3Dz5s20DVBERNKMkigiIiIiIv/HwcGBefPmsX79etzc3ChevDh58+YlQ4YMjBgxIq3DExGRNKIkioiIiIgIcOHCBSZNmsTy5cs5ceIEfn5+NG3alLNnz/LBBx/QpUsXcubMybJlyzh69GhahysiImlANVFERERERIjZhWf8+PH4+/sbjzk5ORl3JGvRogXbt2/HxMSEzp07c/78ee1QJiLyjlESRUREREQEaN++Pe3bt8fX15fr169z7do143+fPg4ODsZgMHDx4kW2bt1Kw4YN0zpsERF5hZREERERERF5RoYMGciQIQPly5ePcy4sLIybN2/i5uZGgwYN0iA6ERFJS0qiiIiIiIgkkZWVFYULF6Zw4cJpHYqIiKQBFZYVEREREREREUkCzUSRt1rvX1by9y6357Zb/0N3qpXIb3zu1HxkvO2sLc3J6mTP+0Xy0KNJJSoUyR1vuw2Hz3Hg7HXcrtzlnrc/PgFBmJqYkDNzeqqXzE/PplUolDNzvH0nLN3BxGW7Eo23QfnC/PNtpyT3tbO2JEcmRyoXy0vPZlUomjtrouO/7R74Pea3dYfYeuIitx/6AZAtgwMViuTmk7plqVo8f6z2/kGhbDpynl2nrnDyyh3uevtjggk5MjtSrUR+ejWvgkvOLMmOIzo6mkPnbrL1+EWOnL/FlbteBIdF4JTOhpIFsvNp3XK0qFYiwf5NR87l4NkbiV5jXJdG9G1ZPdmxiYjI689t7Tx2zBgGQOlmXWjQb0oaR/RuCQt+jMepA3hePonn5VN4XjpJSIAvAD3/Oomjc/zvE/09PZjToUySrzN0u0+yY4sIDebYihlc3LsGf08PLKxsyFKwBOVa9qRgpQ+SPZ6I/EdJFHknWJib4ZTOJtHz8bG3tcLG0sL43C8whFsP/Lj1wI+V+04zvltjvmheNU6/bxds5oZnzC9RExMTHGytCAwJ5/IdLy7f8eKvbSeY1rcV7Won/AvU2tIcB1vreM+lT+ReAExNTcjkYGd87hMQbLz23zvdmDWgDa1rlEp0jLfVthOX+HzqP/gHhQJgaxXz53vlrjdX7npjZmoaJ4lSo/90PJ4kWyAmKRUZFc3Vu95cvevN3zvd+OXLFrSvUzZZsUz+ZzcT/t5pfG5uZoqNlQUPHwWyw/UyO1wvs3zPKf4c9jGWFgn/c/3/f0+f9fT+RETk7XNuxz/Gxxf3rKFur/GYWVimYUTvFo+T+1g9pmOy+5mYmmHnlPiXLyEBvkRHRZK1UPLfr4UE+PH34KZ437wIgIWNHWFBAdxy28stt71U/nQw1TvH/4WhiDyfkijyTni/SG42jO+R7H4TejTlk7rljM+jo6M5c/0+Q39fz/GLHnyzYDMN3y9KXucMsfq1rlGK/NkyUum9POTMnB4LczOioqJxvXKHbxds5uiFW/SbvoryhXNRIHumeK/dslpJZg1ok+yYAXJkcuTMvKHG5xGRURw6d4NBs9Zy/b4P/WespkbJAmROny5F47+pjl64RccflxAWEUm3xhX58sNq5MuWEYCHfo/Zc/oa4RGRcfpFRkVRumAOOjYoT/1yhcmZOT1RUdG4XbnDkDnrOH3tHn2mraJYXmdK5M+e5HgioqLIYG/LJ3XL0rJ6SUrlz46ZmSkP/R7z88q9/Lb+EJuPXWDcom18361xguP8/99TERF5+/neucr9i244ZM2FU4783HLby7Wj23Cp1jStQ3un2KbPjLNLaZxdSuOQNRdbpvZ7bh+HLDn4cvmFBM+HBvozq917REdFUqxeu2THtHlKH7xvXsTOKQvNRs0ld6lqRISFcPSfaRz6axKHl0wlW+GyFKysnaVEUkI1UUSSwdTUlNIFc7Bo+CcAREZFs8Ptcpx2oz6rz8d1y5IvW0bjLBczM1PeL5Kbf77tRDobS8Ijo/h33+lXEreFuRk1SxXk98FtAQgKDWf94XOv5NoA5295cvra3Vd2vfhEREbRb/oqwiIiGflJPaZ88aExgQKQxcmetrVK81n9uDsxzP2qHbt/+pIuDSuSM3N6IObPs0KR3Pw7tguZHe2Iio5m9rpDyYrpwyrFOTV3CN91bUzZQjkxMzM1xvJjj6Z8Vi8mMTJ/81FCwiJSeOciIvI2Orc9ZhZK0Votea9OzJcu53YsT8uQXql754/je+damsZQoFJD+qy4SJsfllGt03DylauVKuNe3LuGyPBQTM0teK9O62T1vX/JjauHtwDQZNgscpeqBoCFlQ3VOg6jaO2Y8fb/OT5VYhV5FymJIpICzhkcyGBvC0BwaHiy+jraWZM/W8zsE0/fx6keW2LKueTC3sYKgEu3H77Ua/kHhTJ/81HqDp5F1b7TOHT25ku93vNsPHKey3e8yJUlPQM/qpmsvlWK5UvwXEYHO+qXj9mh4fS1e8kat0T+7NjbWiV4vn2dmOVeIeERXL7zcv+8RETkzWEwGDi3cwUARWu3xqVaU8wtrbl+bDshAX6J9o2KCOfwkqnM61qRqY2zM7Pde2yc1Bt/Tw88Th9gUv2M/PZZ6QT7e5w+wNpxXZjVvhhTGjkzvXUhVoxsa/zg/jIF+T3k2IoZ/NGtMov7N8Tn1sWXfs3EmJrFvxz8RT1NkOUrXxfb9PHPWE7Ihd2rAciUtwh5y9WOc7586y8A8Lp+zrjcR0SSR8t5RFLggd9jfB8HA5D/mdkMSeEbEMy1e94A5Mma4TmtU5fBYMCAAYCo6OiXMv7+M9dZvMOVDYfPERIeM3vCysIc54z2qX695Fi1/wwAzSsXxzyV3/Q8TahFp/Jr6vRkXICoaEOqji0iIm+u22cOEfDgNhnzFCZLgeIA5H+/HpcPbODi3tWUadY13n4RYSGsGNGWO+4xMyfNLCyJCA3m3PZ/uH50OzW6fZPgNQ0GA7vnfMuJf2cZj1na2hMS4MuN4zu5cXwnZVv0oN6XE1LxTiE6KpJrR7fjvnUJ149uJzoqZtmthY0dNo7JSzC8CR7dv8ndc0cBKN4g+Ut5bp85CECeMvF/YeTsUgardI6EBfrjcWo/mfIWSXmwIu8oJVFEksFgMHD2xn2GzFkPQIHsGfmgwvN/+RgMBnwCgjh59S4/LN5OUGg49jZWfFwn4cKye89co1zPqdzxeoS1lQWFcmSiYYUidG9S+bmFZRNy4tJtAkNiZs7kTcUEzm2vR/y905WlO9249eC/b8DKFMzBx3XL8lHN0imOObWcuHQbgBL5s3HB4wGT/t7JfvfrBIaEkzOzIw3KF6F/6xpkdUp+sufpDjlF86TurkdPx7UwN0uwdg7A9NX7+e6vbfgEBONoZ03J/NlpXaMkbWuVTvWEkYiIpL2ny3aK1m5lPFa0TmsuH9jAuR3LE0yiHFw0kTvuhzCzsKJBv8m8V68tZuYWeF45zebJfdgzd0yC1zzx72xO/DsL+8zZqdHlawpWbYyVrT3hIYFc2L2K3XO+xW3NXLK5lKFY/eR/+P9/Ph6Xcd+6lHM7lhPk+yDmoIkJuUpVo0SD9rhUb46ljV3ig7yBzj6ZhWJtn56ClZJXs8RgMOB7+woAGfMUjreNiYkJGXIW5P5FV3w84i5JF5HnUxJF3gnHLnpQuGP8az87fVCBkZ/Wj/fc8LkbGLtwq/G5X2AIEZFR2NtY0a52GcZ2bpjgzj4Ai7Ydp/+M1XGO58qSnj++ak+WRD6w3/P2x8zUFHtbKwKCQ3G9fAfXy3eYv/kYS0Z9RplCORPs+/8io6I4eDamsCzEfChvWb1kkvvHJywiko1HzrNkhyt7Tl8l+slMiaxO9nxUsxSf1Cv33K2Uk7Kdc0L+f1vqxISERXDfNwCIWcY0YOZqQsMjsbO2xMzUhGv3fJi97iD/7jvNv2O7UDxftiTHseX4RU5ejan38nHd5O3Ok5jgsHCmrdoPQNNK7+FoF/9OTQAXPR5ibWmOjZUF3v5B7Dp5hV0nr7Bw63H+/rojGRxsE+wrIiJvlsjwUC7vXwdA0Vr/JVEKVGyApa09984fx+/udZxyxP4dGRYUgNvaeQDU+eI7SjT81HjOuVAp2oz/h3ldK8V7zdBAfw4snICFtR1tJ/xLxtwuxnOWNuko1bgjVnYOrPu+G0eW/ZLiJEpY8GMu7lmD+9Yl3Dt/3Hjc0TkPxeq3o0SDjxPcNvipTZO+5Oz2ZSm6fmLbEr8q558kyIrUbJHsnZbCgx8TERozUzpdhoTfg6XLGHMuyE9LhUVSQkkUeSdEREbx8FFgvOceB4cl2O9xcFi850PCIwgMCeNRYEiiMxdsrCzIkj4d0QYDPgHBGAwGsmd04MfuTSlfOFe8fQrkyMT3XRvTpNJ75MqcHjMzUwKCQ1l74Czf/rmZ+74BtBu3kEMz+pPJMf7dde56+8dKGvkEBBuX75iYmDDli+bkyOSYYNyJOXPtHot3nGDlvtP4PQ4BwNLcjA8qFuGTeuWoV7ZQkmc/2NlYkSWFOwQllrz6fwHBocbHv/y7jxyZHJk9oA1Vi8fUOtlz6iq9f12Jp+9jOk9cyuEZA5I0/gO/xwx4kiRrUL4w9cvF/61PSgz5bR13vB5hb2PFtx0/iLdN9RL56VC/PHXKFDLutHTPx5+5G44wffV+jl30oPPEpaz7oXuqxSUiImnryqHNhAUF4Fy4TKxEibmlNS5Vm3B2+zLO7VhOtU7DY/W7cWI3kWEhWNk5ULJRhzjj2mfKTtFarTiz+a845y7tW0dEaBCFa7aIlUB5lku1pphZWOHjcZlAH0/SZXRO8j3dPnMI9y1LuLR/PRGhQQBYWNvhUr0pJT74hFwlq2JiYpKksazsHJ67fXBCTEzTdvbmnbNHeHT/JgDF67dPdv/wkCDjY3OrhL98MbeyjdNeRJJOSRR5J1Qtni9FWxzP7N861taxAcGhXL3rzU8r9rDxyHkOnbvB2u+7UyKBmQsf1SzNRzVLAzGzIQ6fv8noP7fw2fjFfFilOL8PboulhXmcPv/PwdaaDg3KU7pQDuoNnoWXfxAz1hxgTKf4p3lGRxviTRrZ21qxYnRnKhbNk8RXILaVe0/TY+o/xuelCmTnk7plaVOjdIpmO/RtWZ2+LaunKJbkiH6mnojBYOD3wW2p/F5e47HaZQoxvW9rPhr7J9fu+bD+8DlaPWemTkhYBB1+XMIDv8fkyOTIjH7Jq56fmNlrD7J0pxsAP/VuEWcL7aeGfVw3zrHsGR0Z3ekDcmVJz+DZa9nvfp0drpepVy7+N70iIvJmMe7KUzvu752itVtzdvsyzu9cESeJ4nX9LADOhcskOMMhZ/GK8SZR7l2ImRVy/dh2ZrYtmmBs0VExtdAee91NchLlyN8/s2/+9zFPTEzIWaIKJRq0p3DND7G0Sf4XLXW//JG6X/6Y7H6vg6dLeZxyFiD7exXSOBoRSYh25xFJBgdba8oWyslfIz6l0nt58HscwjfzNyWpr42VBXXKFGLzhM/Jk9WJtYfOMmfD4WRdv0S+bLSuUQqArccTrqieK0t6/NaNx2/deB6u+o7DM/rTvnYZHgeHMWDGanwDgpN13afCIyONjzM72tGqekmaVyn+2i8XsbP5781iiXzZYiVQnqpXzoVCOWLqjuw7nfiWiRGRUXScsITjFz3IYG/LyjGdjTNBXtSy3ScZ9eTv1OhOH9CmZqkUjdOl4fvkzuIEJP53RURE3hxBfg+56bobE1NTitRsEed8nrI1sU2fmUf3b3Ln7NFY54L9fYHEl3nYOcV/LsgnpiZJREgQQX4PE/wxPJn1GhEWkuR7ioz4b5fD9M55KFq7JYWqNklRAuVNFhkeyqV9Mcuui9dL2XKoZ2vERIaFJtguMiw4TnsRSTrNRBFJARMTE9rVKsOR87fYe/oafo+DY+2kkph0NlZ8XKcsE/7eydKdrsmeiVHWJSd/73LD40HiWxg+ZWFuRpHcWZk98COCQsNZf/gcA2auZtGIT5/f+f/UK+vCkHa1WbrTjbve/oz+cwvjFm2jdpmCfFK3LI0rvoeVxev3z4q9jRXpbCwJDAmnYI6EC7QWzJGZK3e9uevjn2CbqKhoPp/6DztcL2NvY8WKMZ0p8pzaL0m14fA5+vz6LwaDgQGtazKgdfK2Yn6WiYkJZQvlwOOhH7ceJu3vioiIvN4u7F5l3J1m9sfFE217bsc/5CxeMVWuazDEJEcqfzKI6l1GpcqYTxWv346woADO71zBo/s32T5tCLtmf03Byg0p3uBj8pWv89K2En6dXD28hbBAfzAxSXFNGUtbeyys7YgIDSLwaTHeeAT5xtRCsUskoSYiCXv9Pu2IvCFyZP6vpshNT98kJ1EAnDM4AHDL89V+uP2hexO2HL/I+sPnOOB+PcmFWZ/K4mTPyE/rM/zjuuw+dZUlO1zZdPQCO1wvs8P1Mo521rSqXpJP6pZLsObLs6av3s+M1ftTdC+LRnya5GVJJiYmuOTMgtuVO0luHx+DwUC/GatYc/As1pbmLP26A2WTUeA3MTvdLtNt8jKioqPp2qgiozvFXwdFRETeXU+XeyTFxb1rqNv7R8wtrQCwdYxZGproh2u/+M/ZOmUGIOBh0n6PJkf6bHmp2+sHavUYw9XDm3HfvIQbrru5tG8tl/atxS5DVt6r+xElGnycpO14d84cwcW9a1IUS4cZO3DIkiNFfV/U0z/bXCWr4pAlZe8tTExMyJCrIA+unE5w5x2DwYDvnasACda3EZHEKYkikkL3fQKMj82TUeQUwOPJzIBnl5kkldvlmDcwT5dqJEeuzOlpW7M0S3a68sOS7Wye0DPZYwCYmppSt6wLdcu64Pc4mOV7TrF4hytnb9xnwZZjLNhyDJecmWlfpyztapcme8b4i9gGhYQlWPD3eSIio5LVvkbJArhducPVu94Jtrl61wuIeZ3iM2LeBpbudMPC3IyFwz9NdhIqIYfP36Tjj0sIj4yiba3STPmi+QuPaTAYcLsSs2tQ7izpX3g8ERFJW943L/Lw6hlMTE3pvuAYNg7x18sCWPB5NR573ePa0a0Urh7zOyVz/piZK56XTxEVER5vXZQ7547FO172ouU5t/0fbrrtJToqElOz1P8IYWZuQeHqzSlcvTmPve9xdtsy3Lf+zaN71zm+YgbHV8wga6FSlGjwMUXrtE7w/sOCAlK864whOnnvLVJLkJ8XN0/E7FZY/AW3h85VsioPrpzmltveeM97Xj5F6ONHAOQuXe2FriXyrlISRSSF1h06B4CNpYWxlgbEbCec2O40fo+D+ftJ0dBK/zeTwmAwJFp9/txNT1btPwNA/fIp2wnmy5bVWLLTlSPnb3Hw7A3jDjUp5WRvS89mVejZrAqnrt5l8Y4T/LvvDJfveDFu0Va+X7yNWqUK8m3HBpQqEPvbneGf1GP4J/Ve6PpJ9VGtUvy6ah/uN+5z6NwNqhSLfd87XC9z5UmCJb4irD8s3s6c9YcxMzVl7uC2NEjh6///Tl+7S/vvFhEcFkGzysWY1b9NknYgeN7flUXbThiTdQ3KP/+bOxEReb093bY3R7GKOGVP/Hd3oSqNcVs7j3Pb/zEmUfKVr425pTVhgf6c2bKEMs26xOoT6OPJxT2r4h2vcI0P2fP7GIJ8H3B02a9U/nRwgtcOffwIa/v0ybizuOwzZafyJ4Oo/MkgPE4fxH3rEi7vX8+DK6d5cOU0u3//lgIVG1Dr87Gkz5Y3Vt/GQ2fSeOjMF7r+q3Zh979ER0ViYW1L4Rov9kVK0dotOfHvLLxvXuCW217ylI29NNh19W8AZM5fjEx59P5AJCVUWFYkme54PWLQrDXsdIuZJtmhQXmsLS2M51fsOU3HH5ew7cQl/IP+K+oVEhbB5mMXaDR8Dvd9AzAzNWXQR7VijX3o3A3ajF7A6gNn8Hpmhsbj4DCW7HCl+ah5hEVEktHBlj4tUvbtQdHcWalbNiZJ8POKPSkaIyGlC+ZgyhcfcuHP4cwd3I6apQpgMMCuk1c4dPZmql4rud7L40y7WqUB6PnTCg64XwdikhF7Tl2l7/R/AShTMAcNK8R+UzFzzQGmLN+NiYkJM/q14sOqJZJ83QPu13FqPhKn5iPj1LG5cseLNmP+JCAolHrlXJj3VTvMzJL2z/Iv/+6j3/RV7D19lcCQ/7bhvufjz/eLtzF4dkxxuirF8qZawkdERNKGITqa87tWAjFbCT9PoSdtrh/fSUhATEFZKzsHyjTvBsDu377m7La/iYqM2U3nwVV3Vo5sl+AWv7aOGaneZSQA+/8cz46Zw3l0/5bxfHhIIDddd7Nhwhes/a5LvGOkVO5SVWkydBa9l52jwYCfyFakHFER4Vw+sAGv6+dS9VopEezvY/wJDfyvplpo4KP/jj+Z+ZGQp0t5klpQ98CiiUyqn5HfPisd51y2wmUpWKURABsm9sLj9EEgpnDtwb8mc35nzN+j6p1HJuX2RCQemokikojhczcwduFW4/PAkDCCwyKMz2uXLhhnm2EDBtYfPsf6wzG/2O1trTA3M8U/KNS41a69jRXT+raizP/V0zAYYOfJK+w8eQWAdDaWWJibxeqbPZMji0d8ShYn+xTfV9+W1djpdpmdJ69w6updShdM3fW/1pYWtKlZijY1S+Hx0I+lO1xxzpjyeFPLlF4fcv2+D8cuetBs1DzS2VhiMEBQaMzOAPmzZeTP4Z/EmeHxzYLNAJiamDD6zy2M/nNLvOPnyOTIrp++THI8v/67D2//IABcL9+mRLdJCbb9/xowYeER/LX9BH9tP4GJiQkOtlYYgIBnEncVi+ZJUQFhERF5vdw6tY9A7/tA0pIouUpUwcYxIyH+PlzYvYqyH3YHoFqn4dy7cIK7546yaXIftv4yGDMLS8KDH2ObPhO1eoxh688D413qU77VF4Q+fsShJVNwWzMXtzVzsbRNh4mpGWFBATFvYoBcpV7OEhErOwdKN+lE6Sad8L51EfctS7FKF/9y4VdpRpv464os7FXb+Nghay6+WHwq3nZPl2nBiy/learR4On8fa8p3jcvsuyr5ljY2BEVHmYsSlz508EUrNzwOaOISEKURBFJxOPgMB4H//ctv7mZKVnSp6NE/uy0rVWaNjVKYmoae+ZAg/KF+an3h+w7fY1zNz15+CiQx8FhONpZUyhHZmqXLkinD94nW0aHONd7L48zYzs35Mj5W1y6/RDvgCAeB4fhlM6GIrmz0rBCETo0qICjnfUL3VfNUgUpmT87Z67fY+ry3fw18rMXGi8xubM4vbIlO89jZ23Jxh97MHfDEZbvPcXVu15ERxt4L48zzasUo9eHVXGwjfvaGp68MYyKjk60houVZfL+SY1+Mi6A3+PEt4P8/xowH1YrQWR0NEcv3OKmpx++AUFERkWTPaMDpQrkoHWNkrSoWiLJM1tEROT1dW7HcgCyFiqVpKKjpmZmFKzcEPctSzi34x9jEsXC2pZ2k1ZzbPl0zu1YTsDDO1hY2+JSrSnVOg3nwZMP89YJJCeqdRpOoapNcFs7l9unDxLo+wBDRDj2mbKTpUBx8pWrTZHarVLprhOWKU8Ravcc99Kv8yo8XaaVLlM28pRJ+a58z7JxcKLD9O0cWzGDi3vX4O/pgaWtPVkLlaRcy54UrKTi9SIvwsRgeOZdvMhrzM3NjXLlyrHn5y/j1NYQkdRx+tpdag2ciaurK2XLlk3rcERE3hhP36d0nLUL50Kl0jqcFDmwcAKHFk+mWP12NBk6K63DkTeY55XTLOpdR+8n5K2kryhFRERERN5xYUEBnNmyGIC8qTQjQkTkbaQkioiIiIjIOyAqIpx1P3Tn1sl9hIfELE81REdz5+wR/hnakkDv+9hnzoFL9WZpHKmIyOtLNVFERERERN4BBkM0F/es5uKe1QBYpXMkMiyUqIiY+m+WtvY0G/k7Fta2aRmmiMhrTUkUEREREZF3gJm5JfX6TOT68Z343LpE8CMvTExNccpZgHzlalPhoz44Zs2V1mGKiLzWlEQREREREXkHmJiaUvbD7sbdekREJPlUE0VEREREREREJAmURBERERERERERSQIlUUReAyW7T8Kp+UgOuF9PtTEPuF/HqflISnaflGpjioiIyNvvt89KM6l+RjxOH0i1MT1OH2BS/Yz89lnpVBtTRCQtqCaKiLwWDp+/yYzV+zl+0YOA4DByZHKkccWiDPqoFk72qbNLQHR0NB8MncOJy7cBGNa+DsM/qZdge9+AYH5euYeNR85zzycAB1srKhTJTd+WNaj0Xp6Xdl0RERFJW3fOHuHYihncO3+CsKAA7DPnoFCVRlT6eCA2Dk7JHs/n1iUu7V/P/Utu+N6+SvAjLyLCQrBxyICzS2mK129P4RrNnztOoO8DXFfP4dqRbfg/8ADAPlM2shetQPEGH5O7VNVkxyYiyaMkishrIJ9zBqwtzLGxski1MW2sLCiUIxPZMjqk2pgvyx+bjjD09/VERxswNTXBztqS6/d9mLHmAKsOuLN5wufkzpL8Nyz/78+tx42JjOe56elLkxG/c88nAAB7Wyt8Hgez6egFthy/yNQvPqRzw/dT/boiIiJpLX22vJhbWmFhZZNqY1pY2ZAhV0HSZcyWamO+LCfXz2fHjGEYoqMxMTXFwtqOR/euc3zlTC7uXc0nP29K9i5Glw6s58DCH43PLaztMDUzJ8j3AdeObOXaka0UqtqY5qP+wMzCMt4xrh3dzoYJPQkL9H8yRsyXTL63r+J7+yompmZKooi8AkqiiLwG1n6f+lXyy7nk4tjsQak+bmo7eeUOw37fQHS0gU4fVGBsp4Y4prPB/fo9uk5extW73nSesJSdU3tjYmKS4ut4PQrku7+2kStLesLCI3n4KDDBttHR0XSasJR7PgEUzJGJ+UPaUyJ/dvwDQxi9cAsLtx5nyJx1lC2Uk5IFsqfadUVERF4H7SevSfUxsxUpR/f5R1N93NR2/9JJdswYjiE6mlJNOlGz+2is0zny4Ko7637oht+da6wd15kOM3Yk631J5nzvUbP7aHKVrELG3C5Y2cV8yfXY+x5ua+dxdNmvXDm4iSPLfqVqhyFx+t89d4w1YzsRFRFGmWZdKd+mN07Z8wEQ5PeQm257iYoIT50XQUQSpZooIpKmfvx7J1HR0VQsmoefe7fAMV3Mt14l8mfnrxGfYmZqysmrd9l45PwLXeebBZt5FBjC+G5NsLJMPH+87tA5zly/h5mpKYtHfkaJ/DGJEsd0NvzcuwXvF8lNZFQ0E/7emarXFRERkbR1cNFEDNFR5ChWkQb9p2KdzhGArAVL0HLMIkxMzfC8fIorBzcma9xCVRpTsV0/shctb0ygANhnyk7Nbt9SrF5bAM5u+ztO36jICDZP7UdURBjVOo2gfr/JxgQKgJ1TForV/YiSDT9NyS2LSDIpiSKSigKCQ/lmwWZKdZ+Mc+tvKdFtEkN+W4dPQBBLd7ri1HwkTUfOjdMvocKy/99nw+FzNB7+O7nbjyVXuzE0Hv47210vxRvLm1BY9lFgCLtPXgGgV/Mqcb7RKZI7K3XKFgJg5d7TKb7OAffr/LP7JHXLFKJp5WLPbb9q/xkA6pYtROFcWWKdMzExoVfzmKmyO9wu4x8YkmrXFRERSU1hQQHs/n00czqUYWrj7Pz2aSm2Tx9KsL8P7luXMql+Rv4eHLcOR0KFZf+/z+UDG1g6qCm/fJiXn5vnZumgplw/tiPeWN6EwrKhjx9x03U3AOVbfRHnfUmmPEXIV74OABd2/Zuq13Z2KQ1AkO+DOOeuHNyE7+0rOGTNRaWPB6TqdUUk+ZREEUklPgFBNBgymxmr9+Px0A9TExP8Hgczb9MR6g6ehW9A8AuNP2HpDjr8uIRjF2OKiAWGhHP4/E3ajVvE6gNnUuMWXrnD528SGRWNiYkJNUsVjLdNrVIFANifwp2LwiMiGTx7LZbmZkz4vFmS+hw4e/3JteOPqWapApiYmBARGcXhC7dS7boiIiKpJdjfh8X9PuD4ihn4e3pgYmpKSIAfJ9f9wV996hMS4PdC4x9YNJE1Yztx99wxACJCgrjjfpiVX7fn4t41qXAHr96ds0eIjooEExPylKkRb5s8ZWsCpOrORQB3zx8HwNE5d5xzF/esAsClWjNMzTSrVSSt6f9CkVTy1ey1XLrthZO9DTP6tqbh+0UwNTVl/5lr9PplJVOW707x2O437nP0wi3GdGpI10YVsbe14rbXI/r8upJ9Z64zYu5GmlUuhrmZWSre0ct3+bYXAFmd0pE+XfzF61xyxswE8X0cjLd/IJkc0yXrGtNXH+DyHS8GtqlJwRyZntve61Egfo9jZpcUzp0l3jZO9rZkdrTj4aNALt9+SMMKRV74uiIiIqlp+7Qh+HhcxtreiUZfTaNgpYaYmJpy69R+Nk36ksNLp6Z47IfX3Ll77ig1u4+mdLMuWNnaE/DwDpsm98Hj1H52zhqJS7Wmb9wHfh+Py0DM8hhr+/TxtsmY2wWAkABfgh95Y5s+5b/jw0OC8Pe8xan1C7i4ZzUAZT+MWyfv3oUTQMySIu+bFzn41yQ8Th8gPDgQhyw5yV+xPhXb9SNdhqwpjkVEku7N+pdN5DV19a43aw6eBeC3gW1pUL6w8Vz1kgVYOqoDtQfPTPH4AUGhDG5bi/6t//tWJFfm9Mwd3I6S3SfzwO8xR87folqJ/Cm/iWeU7D6J2w8fJbtfrizpOTNvaJLbP/B7DEBWJ/sE22TN8N+5B37JS6Lc8vRl6vLd5MjkyOC2tZPUx/NJTM+Ny8meh48CeegXt1BsSq4rIiKSWnzvXOXSvrUANBk2mwIV6xvP5SldnVbjFrPoy7opHj8sKIDKnwyiYrt+xmMOWXLSbOTv/PZpaYJ8H3Dn7BFyl6qW8pt4xm+flSbgQfJ3uXPImosvFp9KcvvAJ0tp0mV0TrDNs4mKIL+HyU6iREdFMqVh3GSHmYUVlT4eQOlmXWMdjwgLIdDHE4jZJnnrzwOJDA99sruPGX53r+G66hoXd6/iowkryZJfy4dFXjYlUURSwaajMUVPC+fKHCuB8lTJAtmpUaIAe05fTdH4FuZm9G9VM87xLE72lCmUgyPnb3HB40GqJVEyOdgRFh6Zon7JERwaU0Xe2jLhrZ1tn9n2OSg0eVXnh/6+npDwCH7o1hg76/i3C0woJgCbROJ6uh11YGhYqlxXREQktVw5tBmImTXxbALlqawFS5K7dHVuue1N0fim5ha8/0wC5Sk7pyxkK1yGO2eP4H3zYqolUWwdMxIVHvf3bVL6JUdEaMzSa3NL6wTbmD+z7XN4SFCyYwIT7JxiZrqGBvoTFRGGiakpFdr0puyH3ePUYQkLCjA+PvLPrzhkzkHjoTPJVTKmPtsttz1snPQlQb4PWDuuC13nHcTMPOH3LyLy4pREEUkFZ2/EfENQsWieBNtUei9PipMoubOkx97WKt5z2TLGVHj3DwpN0djx2fXTl6k2VlpZf+gs205colapgnxYtcRbf10REZGnvK7HzI7NUaxigm1yFq+U4iSKY9bcWNnGP1szXaZsAIQF+qdo7Ph0nPn83fDeFKZmZny5/AIAhuhoHt2/ydHl0zny98+c3b6MNj/8E2s2iSE6+r/OBgNNR8whZ/FKxkN5y9Wm0VfTWTmyLX53r3H5wAaK1mr5yu5H5F2kwrIiqcA3IOabiMSWf2RxSl4tj2c5Z3BI8Jy1Rcy3DZGRUSkeP63YPpmlERoekWCb4LD/ziV1VkdgSBjD523EwtyMiT2bpigmgJBE4gp5Elc66/+SWy9yXRERkdQS4u8LgF0iNTKezoZIicSWu5hbxPxejIpK/ozWtGZhbQtAZHjCX0xFhv23K5+lTfJm4P4/E1NTnHLkp+HAn3m/bV8Cve+zcWKvWImTZ6+RpUCJWAmUp/JXqEuGXDHF8G+d3PdCMYnI8ymJIiJp5mnS6cEzdUj+38NnzjlnSDhJ9azpq/dzz9ufro3eJ3tGRwJDwmL9GAwx7cIjowgMCSM47L8lPM5Oz9ZgSSSuRzG1UJ6t2fIi1xUREZG09bTeydMaJPEJ8n1ofJxYkiq5yjTvBoDX9XN4XjltPG5pa4/Fk0SKU84CCfbPkDMmiRLodS/VYhKR+Gk5j0gqyPCkFkjiyYC4BUhfV3UGzeSud/Kn4ebI5JispUAuuTIDMQVj/QNDcIxnh56nO/hkdLAlYxJrrjwtijtn/WHmrD+cYLufV+7l55V7YxXEzZw+HU72Nvg9DuHy7YfUKVMoTr9HgSHGJIpLzsypcl0REZHUYuOYAYCgJ4VS4xPk9zDBc6+bRV/W5XEKkgP2mbMnaynQ0513gvweEhroj3U6xzhtfG7H7OBj45gx2TVXEvPs7B5/z1tkK1wGABMTEzLmdsHz0smkDfR/NVVEJPUpiSKSCornc2bFXjh2wSPBNkcv3HqFEb0Y74AgY5IgOawsk/dPSuX38mJuZkpkVDR7z1yjeZXicdo8rSNTPZWK5iZFteL5WX/4HHtOX+OL5lXjnN97+ioGgwELczMqvZf3lcUlIiKSFJnzF4edK7l7/liCbe6ePfoKI3oxwf4+KUr6mFnGX08uITmLV8LUzJzoqEhundxL4erN47S5+aSOTGoVzX3K3/O/95AW1rG/NMpTpgael07id+dagv1978S8X3LImjNV4xKRuJREEUkFjd4vyug/t3Dx9kN2uF6mXjmXWOfdb9xn75mEf/G9bl7V7Ij06WyoU6YQ205c4rd1h2hWuVisqvSX7zxk18krALSuUSrJ484a0IZZA9okeP7pFs7D2tdh+Cf14pxvXaMk6w+fY6fbZS7feYhLzv/WjRsMBn5bfwiAemVdcLT7r4L/i15XREQkNRSs3JC9c8fgc+sS14/vJH+F2NsZP7x2llun3pzaGcnZpvhFWNunJ2/5Olw/ug3X1b/jUq1ZrPclPh6XuXliFwBFa7dK1tjRUZGYmiX80evEv7MAMDUzJ3vR8rHOvVfnI47+M42H19y57X6YXCUqxzp//fhOfG/HJFHyV9D7C5GXTTVRRFJBoZyZaV4lppJ6z5+Ws/nYBaKfFAU7ePY6n/7wF/Y2yfs25F0x/OO6mJmacvj8TQbPXmvcZcj9xn06jF9CZFQ0ZQrmoEml9+L07f3LSpyaj6TpyLmpGlOzysUomT87kVHRdBi/BPcb94GYHZAGz17LkfO3MDczZfjHdZ8zkoiIyKuXMVchXKo3A2DjhC+4eniLsVipx+mDrBr9GZYJ7K7zrqvaYSgmpmbccT/M9mlfGbcYfnjtLKvHdCQ6KhJnl9IUqtokTt9Nk75kUv2M/D047gyWP7pXwW3tPB7d/29mssFgwOvGeTZN7sOpDX8CMbVRbBycYvXNnK8oxeq1BWL+PD1OHzD2v+m2h81T+gLg7FKaApU+ePEXQUQSpZkoIqlkaq8PuXDrAVfuevPJ939hY2mBqakJQaHh5M+WkcFta/Ptgs1YWeh/u2eVKZSTiZ83Zejv61mw5RgLtx3HztqSx8FhAGTP5Mifwz6J9U3Qy2ZqasrC4Z/QZMTvXL7jRY3+07G3tSIoNJzoaAOmpiZM7tmckgWyv7KYREREkqNBvyl437yA7+2rrPr2U8ytbDAxMSUiNIj02fNT+ZNB7Pl9NGYWSdv57l2RrXAZ6vWZwI4Zwzi14U9Ob1qEhbUd4cExde/sM2fnw28WJPt9id+da+yYMQwY9j/27jsqquML4Ph3l96rCBbsvWDvvfduNNYYjdFY0ixpJqYnRlPMzyTGaIy9994r9gKCoqAgIL132GX39wdCJIAU0QW8n3M4B9+bmb1vRXzv7swd9AyMMDQ1R5WcmG0noAY9XqHL1M9z7d9z1g/EPPLl0e3LbJozOKPYrBZUKRk7RFpXqM7gT1e/0PslIV5W8jQnRDGxtzLn6OK3WLz5BLtdPQiNisfOyoKxPZrzwavd2XwyoyDYk8s/RIbJ/dpQv6ojv+44y5W7/sQnpVLN0ZZ+revz/itdsLEwfeExVXW05ewvs/lx6ykOXLpNUGQcthamtKrrzKyhnWhTv8oLj0kIIYQoKFNre8b/ehTXdYu5e3YPiVGhmNrY0ajPGNqPn4/nsS0AGOVSPPVl13Tg65SrVp/LW34l6M5VUhPjsa5QjZpt+9J2zHs5ZooUxNDP1+F/4wyBnpdIiAwhOS4KPX1DbCvXokK9FjTs9SrOLjnrsGUyNDHj1R/3cn33X3ge20JUoA9arYZy1epTu+NAWgybhpGZ5bNcthCigBRabeamm0KUbNevX6d58+ac+mkGLjUq6jqcQpv+01Y2nbzBvNHd+FDqYYgSyu3+I7q8u4xr167RrFkzXYcjhBClRuZ9yoTfTuBYq+B1vHRl/6K38Dy6mXbj5tJh4ge6DkeUMSHebqx5q5vcT4gySWqiCPECBITHsPeCJwCdXWroOBohhBBCvMziwgK5d3YfAFWaddZxNEIIUbpIEkWIYvIwJIq3/7eDK17+JKeqAFCp0zl67S6DP/6LxJQ0mtasSLsG1XQcqRBCCCHKupjghxz68R2Cbl9BlZoMQLpaxYPLx9g0dwiqlEQcazfJsdOLEEKIp5OaKEIUk1S1mjVHrrLmyFUgY/vexJQ0VOp0AJxsLfnjvZG6DFEIIYQQL4l0VSruB9fifnAtkLF9b1pyIhp1xgc95naO9J//uy5DFEKIUkmSKEIUk4r21nwxqS/Hr9/jflAkEbEJGBnoUatiOXq3rMOMIR2wszTTdZhCCCGEeAlYlKtIl6mf43vlONGPHpAUE4GegSF2lWtRo3UvWox4C1MrO12HKYQQpY4kUYQoJmbGhswa2pFZQzvqOhQhhBBCvOQMTcxoNXImrUbO1HUoQghRpkhNFCGEEEIIIYQQQogCkCSKEEIIIYQQQgghRAFIEkUIIYQQQgghhBCiACSJIoQoEJtBH2Ez6CP8Q6N1HYoQQgghyrhFPe1Y1NOO2BB/XYcihBDZSGFZIYQogtNuPhy/7s1170ACwmKIiE1Ao9XiaGtJ2/pVmdK/Dc1qVcq1r39YNHtdPTnjfh8PvxDCYxIwNtCnegU7+rSsy5sD22FjYfqCr0gIIYQQJVVSbCT+N88Rcu/G4y830pLiAZh3NDLPfv5u59g0Z3CBXsPK0Zk3194olniFKMskiSKEEEXw07bTnHa7n/VnSzNjklLS8AuJwi8kis2nbvDJuF68O6Jztn7+odE0mboYrVabrW9Ccipu94Nwux/EP0eusOXTiTSqXuGFXY8QQgghSq7bx7dy4vePC91PT98QMxuHp7ZJjAkHrZbyNRsXNTwhXiqSRBFCiCLo0aw2g9s3pG39qlR1tMXY0ACNRsPth6F8vf4ohy578cWaw7SqW5n2Datn9VOnawDo26oeY7o3o2PjGliZGZOSpuLg5TvMX76XkKh4Xv1qLZd/fxdTI0NdXaIQQgghSgwFFuUq4Fi7CY61mqDUN+D0X5/n26tig1bM2HInz/OR/vdYObktAA16jiq2aIUoyySJIoQQRTBzaMccx5RKJQ2rObHmg7G0fusnfEOi2Hj8RrYkip2lKWd/mUWDqo7Z+hobGjC0Q2McrC0Y8NEKHkXEsuvcLcZ0b/7cr0UIIYQQJVuzwVNoMezNrD8HelwslnE9j24GwMTKjuqtehbLmEKUdZJEEaIAUlVq/tp/kZ3n3LkXGE5KmhpbC1McbS3o2Kg6r3ZvRv0qjtna7794m0OXvfDwCyYoIpZUlZoKdlZ0aVKTt4d1wrm8TY7X8Q+NxuWNHwCI3vMNV7z8WbzlJFfvBqBSp9OkZkU+GtuTNvWrABCTkMxP206zx9WD4Mg4yttYMLZHM94d0QUDfb2nju3q6ctP205z/V4gKWkq6jqX543+bRjdrVmR3qOw6Hj+t+scR6/exT8sGoVCQTUnOwa1bcC0Qe2xMDXK0ScuKYXfdp1j/6U7+AZHolKnY29lRkV7Kzq71GR8zxa5vk8lnYG+Hg2qOuIbEkVIdHy2c1bmJliZm+TZt33Dajg72OAfFo3b/SBJogghxEtInZbKjT0r8Tq9k0h/b9RpKZhY2mJu54izSwca9nqVctXqZWvv7XqA+xcPEXbfk/iIINLTUjG3r0DV5p1p/cpsrBydc7xObIg/y8c3BTLqagTdvoLrhh8JvnOVdHUajrWb0GHiR1Rq2BqAlPgYLm76mXtn9xIfEYy5XXka9hpDm1ffQU/f4KljB9y6wKWNPxN89zrqtBTsqtSh2eApNOw5ukjvUWJ0GFe2/cb9S0eICw0AFNhUqEbtjgNpPuxNjEwtcvRJTYzjyvbf8Tl/gOggXzTpKkys7LAsV5EqzTrTuM+4XN+nkkCpp5d/o0LSarXcPrENgHpdh+X4OxRC5E6SKELkQ6VOZ8iClVy8/RAApVKBpakx4bEJhEbH43Y/CD09JQsn9snqc/KmD5N/2JTV3srMmHSNlgfBkTwIjmT7GTe2fz6J5rUr5/m6By7e5rVFG1GnazA3MSQ+OZWztx4wZMFKtn8+idqVyjHo47/wCgjD3MSQdI0G/7Bovt1wnMDwWJbOGpbn2LvO3WLK4s2kazRYmRmTqkrnuncg03/expW7ASyZXrACZJnOezxg7NfriE1MAcDYUB9NugYP32A8fIPZdsaNXV9OxsnOMqtPbEIyveb9wb3AcAD0lEosTI0IjoonKDKOK3cDcLKz5PW+rQsVS0mQkqbC/UEwAFWKkASytTTFPyyadI2muEMTQghRwqWrVWyZPyxrpoFCqcTIzJKkmHASo0IJ9XZDqadH5ymfZfXxu36KvV9PeaK9FRpNOjFBD7gZ9IA7J3fwyrdbcaqbd2Le2/UAu798HU26GkMTc9KSEvC/eY7NnkN55btt2Fauxaa5g4l8eBcDEzO0mnRiQ/w5v+Y74sIC6fv+L3mO7XV6N3u/eQOtJh0jcyvUaamE3L3BgUUzCLpzlV6zFxfqPfJ3O8/OheNJTYgFQN/QGK1WQ9gDD8IeeHD7xDZGLdqJhb1TVp+UhFjWze5NVID34/dJDyMzCxIiQ0iICCbozlXM7ZxoOnBSoWIpzfxvniUuLBCgyMksIV5GkkQRIh/bTrtx8fZD7K3M+N/s4XRvVgt9PT1U6vSMXVYueGJjnn0nFQsTQ94a3J7B7RvhUqMCRgb6aDQa7viH8eXaIxy+4sW0n7Zyadk7KJW57zQ+/ZdtjO3RnE/G9cTO0ozA8BimLtnChdt+fLLqABXtrQA4smgaLes6k5KmYvneCyz85xBrj17ljQFtaVTNKdex3162kx7Na/PDtEFULmdNXFIKS3ecYcmWU6w6eIm29asyorNLgd6fhyFRvPrVWhKS05g+qD3TBrajsoM1Go2Wm/cf8cGf+7h6L4BpP21h91dTsvr9sdeVe4HhVHey49fZw2hTrwpKpZJUlZr7QRHsPHuL8jY5P0UqyWISkvH0C+GHzSfwD4tGT6lkUp9WhRojOj6JOw9DAajnXP55hCmEEKIEu3NiG4EeFzG1tqfvnF+p1qIbSj190tUqYkP88T63D2PL7Al6QxNzWgyfTp1OgylfszH6hkZoNRoiHnpxZtVX3L94mH3fT2fKyoso8rjvOLBoBo16j6XjpI8wtbIjLuwR+757k8BbFzjxxydYOlQEYNwvh6hQvyXqtBSu7fyT0399zq1D62g+5A0cajTMdezDP71D9VY96DlrEZYOlUhNjOPyll+5sOFHbu79m0oN21K/2/ACvT8xwQ/Z8elY0pITaD5sGi2Gvoll+cpoNRpCvW9ybNmHBHtdY//30xn9w66sftd2LicqwBvrCtXpO2cplRq0RqFUok5LJfrRA7xO78Tc9ukFWMuazKU89lXr4li7iW6DEaIUkSSKEPm4ei8AgBlDOtC7Zd2s4wb6etSoYM87wzvn6NO+YfVsdTAgo15Gg6qOrPlgDJ3f/R9e/mGcvfWAzi41c33dZjUr8dNbQ7L+XKmcNSvmjKLR5EXc9HmEp18IV357lyqOtkBGTY23h3fi5E1vTrvdZ/8FzzyTKJXsrVn74disJT+WpsZ8Mq4XEbGJ/HP4Ct9vOl7gJMpX648Sn5TKx2N7MGdUt6zjenoKmteuzNaFr9Fu5i+ccX/AtXsBWbNvMt/Xj8f1pF2Daln9jAz0qV/FMdvyqIIa8NEKznv4FrofZCxxKopTN30Y+umqHMftLE35dfZwGubxd5CXH7eeIlWlxtzEkMHtc78ZFUIIUXYFeV0DoOXwt6jRulfWcT19A2wr1aD16Ldz9HF2aY+zS/tsxxRKJeWq1WfIp6v5562uRPh54X/zLFWa5bxvAXCs05Te7yzJ+rOlQ0UGfric38e6EOrtRrjvbaasuoS1U8aSYn1DY1qPmo3ftZM8vHGGe+f355lEsXSoxJDP/slaLmJkZknHSR+TFBuJ2/5/OL/2+wInUc6u/oa0pHg6vPYh7cbO+fd69fRwqtuckd9sYdUb7fG/eZZgr2tZs2+C72S8rx0nfUTlRm2z+ukbGlGuWr1sy6MKauP7gwhwP1/ofvD0bYlfBFVKEnfP7QWgQfdXdBqLEKVN7qloIUSWzFoeoVHx+bQsGEMDfbo8TpxcuRuQZ7vZw3IWLq1ob0WNCnYADGnfKCuB8qROjWsA4OUflufYM4d0yFEzBeDdxwkhn0cRePqFPOUqMiSlprH7vAcG+npMHdgu1zbW5ib0aF4bINuWwMX9vgLYmJvgYG1epK+iMjTQw8HanHJWZiiVCgCszIz5YlJfujetVaixzrjd5/c9rgDMHdUNe6uixyWEEKJ0yqzlkRAVWizj6RkYUqVpxv/vQXeu5tmu9SuzchyzKFcRm4oZHwrV7Tw4K4HypCpNOwEQ6eeV59gtR7yVa72N1qMyEkLRgfcJ9739lKvIoEpJ4u6Z3Sj1DWg+ZGqubYwtrKnWsgcAD2+cyTpuaJbxviYW0/ua+VpmNg5F+tK1e+f2oUpORKFUUr/HSF2HI0SpIjNRhMhHj2a1+WX7GZbvu0BUfBIjOrvQpl7VXAulPik8JoHl+1w5ft2bB8GRJCSnotFos7V5WgKhXpXcl3LYW5nh8ygiz/PlHj94Z9YnyU37htVyPV7F0ZZK5awJDI/h1oOgHDvI/NdNn0eo1OnoKZW0nPZjnu0SU9IAeBQRm3WsR7Pa7Dx7i4X/HOJ+cASD2zWkRR1nTIyKXtRs7Ufjity3qNo1qMbdNR8BkKZSc/N+EF+sOcyMX7az7ug1Nn4y/qmFZDPdD4pg8uJNpGs0dG9Wm1m57P4jhBCi7KvWsjuXNi/l2q4/SY6Lon63EVRs2DrXQqlPSowO5/quP3lw5TgxQb6kJSeg/U9traclZuyr5j4Tw8y6HNGB9/M8b2pdDoCUxNhczwNUbtw+1+PWTlWwdKhEXFggoT7ulKtWP88xAEK83dCoVSiUevw1Ke+aaWnJiQDEhT/KOlatRTe8Tu3k9F+fEx14n9qdBlGhXgsMjPL/PzovQxeuKXJfXctcylOlSScs7CvoOBohShdJogiRjw6NqjN/dDcWbznFllM32XLqJkqlgoZVnejbqi6T+rbOUbvD0y+EwZ/8RWRcUtYxSzNjjA0y/sklpqSRmJJGUmpanq/raGuZ63G9x2uZy9vkPktBTy9jNoQqPf0pY+d9I+Zka0FgeAwRsYl5tskU+njnmXSNhrCYhHzbJ6eqsr5/tVszLt5+yNqjV1l54BIrD1xCX09Js1qVGNC2ARN6tcTKzDjfMUsSQwN9WtV1ZteXr9PvwxVcuO3HV+uO8sO0QU/t9ygilmGf/k1EbCLNalVi9fxXUSgULyhqIYQQJYmzSwfajZ/HhfVLuH18K7ePb81YmlO9ITXb9qHJgNcwt83+QUq47202zR1Ccuy/S0SMzCzRN8z4fzQtORFVSiKqlCTyYm6X+wcnCmXGzNW8Zk9k1ljRqNWFHjvzXFxYIEkx+S9vyZxFotWkkxid94zbTOqU5KzvG/Z6lUCPS9w6tI4be1dxY+8qlHr6ONVpRq0O/XHpNwEjs9zvvcqa+IhgHt7MmKXToJcUlBWisCSJIkQBfDCmB6O6NmX7WXdcPXy57OWP+4Mg3B8EsWz3OdZ/NJ5OLjWy2s9aup3IuCTqV3Hk2yn9aVk3+wyLr9cdZfGWk2i1ub1a6ZE5s6aCnSWef39QqL4KhYKls4YxdUBbdp/34LyHL9e9A7ns5c9lL3/+t/MsO798vUi1UXRNX0+PSb1bccXLn00nrz81iRIek8CwT1fhHxZNXWcHtn72GuYmT5/lJIQQomzrMGE+DXq8gtfJHQS4u/Lo9hXCfNwJ83HnyrZlDPt8XdYyGoCDi2eRHBtJuWr16Tb9ayrUb5lthsXZ1d9wYf0SSvuNR+bMGnN7J97a6FGovgqFgr7v/0LzoVO5e2Y3Ae6uBHtd59Htyzy6fZkrW5fxyvc7ilQbpbS5fXwrWo0GQ1Nzarfvr+twhCh1JIkiRAFVc7Jjzitd4ZWuqNTpnHa7z+drDuPhG8z0n7fi/tc89PSU+IdFc8MnY/roxk/G45zLFrfhsfnP2nieQqLic40LIPjxEiN7K7N8x8msJRIem0iqSo2RQeF/pTSs5pRVfDU5VcXhK158tvoQ/mHRvPO/nRz5YXqBxxr/zToue/kXOgYga0lOccmc7ZOQnEZ4TALlcqm7EpuQzPDP/uZeYDhVHW3Z+cXr2Fqa5mgnhBDi5WNToRptx75P27Hvk65W8fDGGc789QVhDzzYv+gtpq3L2Oo4NjSAkHs3ARj2xXqsHJ1zjJUUE/GCo88uITIk17gyzwGYWtvlO46pTcbSoaSYCNRpqegbFv5DB4fqDXCo3gAAVWoy9y8e4fRfC4kN8efwT+8wbunhAo+1c+EEgm5fKXQMADO23ClSv+LgeWwLALU7DMTAWO47hCgsSaIIUQQG+nr0aF6bGhXsaPbmEoIi4/ANiaJmRXuCI+MAsLUwzTNRUdQdZIqLq6dvrrH5h0YTGB4DQKPq+a+PbVKzEvp6SlTqdE7d9Mm2e1FRmBgZMKRDI2wsTBiyYBXXvANJTlUVuE5KdEJygZYVvQj+YTFZ35uZGOY4n5iSxsgv/uGWbzAV7CzZ/eXkPJdwCSGEeLnp6RtQvWV3bCpWZ8XEFiREBBMT7IttpZokRAQDYGJpm2eiwt/t3IsMN4eAW665xhYb4k9cWCAA5Ws2znccx9pNUOrpo1GreHjjdLbdi4rCwMiEup0HY2Jhzeb5wwi+ex1VanKB66SkxMcUaFlRSRLi7UaEX0YCp6Es5RGiSCSJIkQ+0lRqDPOYYWFs+O/DfUpaRr2PzIKz0QnJRMQm5NhhZfPJG/g80u0nQst2n2d4J5ccO/T8siNjfWytivb5FpWFjGsd2LYBO8/d4su1R+jYuDqmRjkTBpAxy0SpVGTNVinI+6rRaFGlp2NCwZIo+755o0DtnpU6PR19vZy7G2VKValZeeAiAI2rV8jxnqSq1Iz7eh1XvPwpZ2XGri8n55lwE0II8XJJV6WhZ5D7/6WZNU4A1GmpABg+LjibHB9NUkwEptb22fp4HttCdOB9dOnqtt+p13V4jh16Lm1ZCoBt5Zr5FpWFjJ2LanUYwN3Tuziz6iucXTrkOZNClZqMQqHMmq3y1Pf1cdJEq9GgUauggEmUV5fsKVC7kiSzoKxl+cp5FvwVQjydbHEsRD6m/byVWUu3c/KGNwnJqVnHvQPDmbl0O5BRE6Sec0aRt7qVHXC0tUCr1TJ1yRb8w6KBjO2A/zpwkbf/txMbi6JXgi8O/mHRvPb9hqxZJ/FJqXy74RirDl4CYN7o7gUe67MJvbE2N8HTL4T+H67gjNt90tMz1ixrNBru+IeyePMJmr25ONtuREMWrOLDFfu4cNsvKwEF4Hb/EfOW7wWgZZ3KWJqWvOKyF28/ZPAnf7Hr3C0inlialaZSc9b9PoM+/otbvhmfDM4b3S1b3/R0DVN+2MQpNx+szU3Y8cXr1KpU7oXGL4QQouTav+gtDi6Zjd+1k6Ql//t/TGSANwcXZ2xDbG7vhH2VjNmf9lXqYGZbHrRa9n37JrGhAUDGdsA39qzk0I/vYGyh20R9bKg/u7+cRFxYxnLn1KR4zv3zHTf3/g1Au3HzCjxW58mfYmxhTfgDTza8N4CHN86geVxMX6vREOHnhev6xfw5oXm27Yw3zx/G8d8+ItDjIuq0f3cwDPF24+j/5gNQoV6LEltcVqvRkBQbmfWVmhiXdS6v4/+lSVdz5+QOABr0eEWK2AtRRDITRYh8pKap2Xn2FuuOXUOhUGBlZkxqmprkxw/+pkYG/PbOCPT0MnKSSqWSLyf1Y+qPWzh50weXKT9gaWZMUkoa6nQNHRpVo1XdKvy49ZTOrumXGUOZsngzBy97YWVmTHxSKumPi7W93rc1Izq7FHisKo62bPl0IuO+WcdNn0cMXrASQ309zE2MiE9ORaV+YpegJ/6vjk9O5Y+9rvyx1xWlMuN9TUxOI+1xeztLU36aMbRYrvd5OOP+gDPuDwAwNzHEUF+fuKQU1I8TSIb6enwxqS/922T/ZO3inYfsu3gbyPjZGv7Z33m+xtCOjfjujYHP6QqEEEKUROq0FLxO7eTWofWgUGBsboU6LRV1asZOMwbGpvSfuwzl4xmRCqWSrm9+yb7v3sTv+imWj2uCkZklqpQkNOlqKrt0oGL9llzc+JPOrqn3uz+z95s38LlwCGNzK1IT49FqMv6/bzJwEvW7DS/wWNZOVRjx1SZ2LpxAqLcbm+cNRc/AEEMTc1KT4jNmkmR6IkmQlhjPtZ3LubZzOQqlEiMzK1QpiaSrMnZKNLGyo/e7unuP8hMXFsjy8U1zPfe/EbWzvq/cuH2eM2QeXDlOUkw4AA16jCr+IIV4SUgSRYh8fDqhN63qVuGM+30eBEcSGhWPFi01K9rT2aUGM4d0pKqjbbY+Izq7YG1uwk/bTuF2P4j0dA11KjswsnMT3hrcniVbTuroajIM6dAIBxtzftx6muveARgZ6FHXuQJv9G/D6G7NCj1ey7rOXP79Pf7af5FDl+9w71E4sYkpWJoZUbOCPW0bVGNoh0Y4O/z7SdjSmUM5cvUu5zwe8DA0mrDoBPT1lNSoaE/P5nWYOaRDrsVYSwKXGhX57e0RnHa/j9v9R4RFJxCXlIKZsSHVnOzo0Kg6r/VuSY0K9jn6ap/YGSE5TZWVjMtNXGJqnueEEEKUTZ1fX0DF+q14eOMMMUG+JESFglaLTaUaVG3amZYjZ2DtVDVbn/rdhmNsYc3FjT8T6u2GJj0duyp1qN9tBC2GT+fChh91czGP1e08GDNbBy5u/Ilgr+voGxphV6UOzQZPoWHPwtflqFC/JVP+vsT13X/hc+EQUQHepCTEYmRmiW2lGlRq1Ja6nYdgVb5yVp/e7/3Mg8tH8Xc7T2zIQxKjwlDq6WNTsQbVW/Wg5YgZmNmU7ZmhmQVlK9RrgW2lGvm0FkLkRaHVlvK9zsRL4/r16zRv3pxTP83ApUZFXYdT6viHRuPyxg8ARO/5RsfRiJLK7f4jury7jGvXrtGsWeETakII8bLKvE+Z8NsJHGsVfEZnWRUb4p81c2Le0UgdRyNetBBvN9a81U3uJ0SZJDVRhBBCCCGEEEIIIQpAkihCCCGEEEIIIYQQBSBJFCGEEEIIIYQQQogCkCSKEEIIIYQQQgghRAHI7jxCvCScy9tIQVkhhBBCvBBWjs5SUFYIUSbJTBQhhBBCCCGEEEKIApAkihBCCCGEEEIIIUQBSBJFCCGEEEIIIYQQogAkiSKEEEIIIYQQQghRAFJYVggd2XD8GjN+2U77htXY980bug6nRBnw0QrOe/hmO+a2Yi7O5W10FJHufbfhGN9vOpHt2LK3hzOme3MdRSSEEKI0uXV4AwcXz6Jy4/a8umSPrsMpUTa+P4gA9/PZjr259gZWjs46ikj3DiyagcfRTdmOjV68G2eXDjqKSIiSQ5IoQogSy8LUCBNDAwCUSkW2c8mpKg5f8eLYtXtc8w7APzSadI2W8jYWtKlfhakD2tK8duVcxw0Mj2H7GXeuewfg5R9GeGwC8UmpWJub0KCqI8M7ujCmezP09J7PZL3zHg/4Y48rl738iUlIxt7KjPYNqzNrWEcaVXPKtY+ZiREO1uYARCcko1KnP5fYhBBCiJeVoakFBkYmACiUegXqs/uLSdw9m5GUathzNP3mLSvWmNRpqQS4nSf43nVC7t4g+O4NEqNCgfyTGsF3r+PjepBgr+vEBPuRFBtBuioNU+tyVKjXApf+E6jarEuufY3MLDGzcQAgKTYCrUZTrNclRGkmSRQhRIn13RsD8pxp8coXqzl369/ZKsaG+ugpFfiHReMfFs22M258PLYn743skqPveQ9fFv5zKFtfY0N9ImITOe12n9Nu91l37CpbPp2IlblJsV7T9xuP893G40BGYsjS1JiQ6Hi2nr7J7vO3+P3dkQzr2DhHv1lDOzJraEcg95k6QgghhHg23d/6hka9xxS4/YMrx7MSKM9LpP89tn40skh9b+77h1uH1mX92dDUAlAQH/6Iu+GPuHtmN00Hvk7P2T/k6Nt9xrd0n/EtAH+Ma0JcaECRYhCiLJIkihCiVFKpNdSsaM/EXi3p27oeNSrYo9Vq8QoI46MV+znl5sOXa49Qr0p5+raql62vc3kbPhzTnfYNq9GgqhPWjxMlUXFJrD9+jS/WHOaylz8frzzA/94eXmwx73X1yEqgTOrTik/G9cLW0pSYhGS+33icP/a68tbP22hYzZHalRyK7XWFEEIIUbzUaSkc+998DE0tMLdzJCrA+7m9lpG5FY61XHCs3QTHOk3Z89UUtJr8Z6RWbNAKh+r1qdSoHbaVamBgbIpWqyUm2I+LG3/i1qH13Ni7Cqd6zWnYc/Rzi1+IskaSKEKIUmnhxD60qlsZpfLfJTcKhYJ6zuXZuGA8Xd9dhldAGMt2ncuRRGlbvypt61fNMaatpSmzhnYkPimFHzafZPtZN358azCGBsXzq/K7jRk1TdrUr8KPbw3JOm5tbsK3bwzAyz+MU24+fLv+GH/PL/gnYUIIIYR4sS5s+ImYIF+6TvsKH9eDzy2J4lC9AbN33EehUOTf+D8a9xmb45hCocCmQjX6vr+U6Ee+BN5yxePIRkmiCFEIkkQRLz3/0Ghc3siYxvi04qUPgiJpPm0JCoUC97/mUqmcNZBRX2PbGTfOuN3HNySK4Mg4jAz1qVPZgRGdGvNa71aFfgi3GfTRU+M5d+sBAz/+i8oO1rj/NS/XMc7desBf+y9y2cufiLhELEyMaFqrEpP7tc6RVCiN2tSvkuc5Y0MDhnRoxHcbj+N+P6jQYzepWQmAlDQ1MQnJONhYFDnOTCFRcdx+GALAmwPa5dpm2qB2nHLz4eBlL+KTUrEwNXrm1xVCCFGyxIb4s3x8U+DpxUujHz1gxWstQaFg2jo3LB0qAhAX9og7J7bx8MYZYoL9iI8IRt/QCLsqdajXdRhN+r+GnoFhoWJa1NPuqfH4u51j05zBWJavzLR1N3Mdw9/tHDd2r+TR7cskxUZiZGqBY52mNB34OjXb9ilUPCVdVKAPl7f8in3VujQf8gY+rgef22splM9vM1XH2i4E3nIlITL0ub2GEGWRJFHES8+5vA0t61Tmyt0Adpxz553hnXNtt/2MGwBt6lXJSqAAfLxyP3tcPYGM2homRgbEJCRzxcufK17+7L3gyfaFk4ptNkN+tFotC1YdZNnuc1nHLEyNiIpP4vj1exy/fo+pA9ry/dSBLyQeXbGxMAUgvQiF0C57PQTA1MiAco+LuT6rwPDYrO9rVLTPtU2tiuUASFWpuXjHj57N6xTLawshhCg5rBydqVCvBUF3ruJ1aietR7+da7s7J3cAUKlhm6wECsCJPz7m3tm9AOgbGmNgbEJKfAxBt68QdPsK987t55VvtxY6kVJUWq2Wk8s/5er237KOGZpakBwXhe+V4/heOU6zIW/QY8Z3LySeF+Ho0rmkq1LpMfN7lHql83FKq9USdOcqANaOeX8wJYTIqXT+qxeimA3r2DgjiXIm7yTKjnPuGW07ZS/6WaeyAz9Mq0GPZrWpUt4GhUKRtXPMxyv3c+6WL0t3nGHOqG7P/ToAftt9nmW7z1HB3ooF43vRv3V9LEyNSEhOZfsZdxb8fYA/912gaa1KjO7a9IXEpAuujwuv1qtSvkDtU9JUBIbHsuXUDX7deRaAyf3aFGn6bH40eSR2nkz43PUPkySKEEKUUXW7DCPozlXuPCWJ4nV6JwD1ugzNdtzOuQ49Z3WkWsvuWDlWQaFQoEpN5v7FI5z442MC3M5xactS2o2d89yvA+Dq9t+5uv03LMpVoNOkT6jZvh9GphakJSdw5+QOTi7/lOu7VuBUuykNeo56ITE9T7cfzwKq13V4qdzuNzUxLmMmzdZlBN2+AkDTwVN0HJUQpYskUYQAhnRoxMerDnDLNxjvwHBqVSqX7bynXwhe/mHo6ykZ0r5htnMfje2ZYzwTo4zlJE52lvSZv5y/D195IUmU2IRkvt1wDDNjQ3Z+MSlbcVJzEyMm9m6JpZkRry/axM/bThUqifLdhmN8v+lEkeLa+/UUOjSqXqS+RXHLN5h9F28D8Gq3Zk9t22DSdwRFxmU7pqdUMqlPSxaM71VsMVUqZ5X1/d2AcFxqVMzR5l5geNb3odHxxfbaQgghSpa6nQdzcvknhN2/RWSAN3aVa2U7H+57mwg/L5R6+tTpNDjbuY6vfZhjPAMjE+p2HoyFvRPr3+mL2/5/XkgSJSUhlnP/fIeBsRmvfLcdO+faWecMTcxx6TcBIzNL9nw1mYubfi5UEuXcmu9xXbuoSHHlt/VvUaUmxnFy+acYmJjRZernxT7+85K1NOw/DE3N6TL1C2q0znkvK4TI2/NbZCdEKeJoa0n7BtUA2HHWPcf5zGOdGtfA3qrgyzta16uClZkxQRGxBEXG5t/hGe129SAxJY1eLerkubvLwLYNMDLQ525AOCFRcbm2yY2ZiREO1uZF+jLQ1yuuS8xXUmoaU5dsJl2joVE1Jyb0ynnT8CR7q4wYTY0Mso6N69Gc91/pWqxxO9paZs2K+X3PebRabY42S3ecyfo+Pjm12F5bCCFEyWJu50jlxhn1sbxO7cxxPnMpj3OTjpha574ENDcVG7TCyNyK+PAg4iMKXxOssO6e2YMqJZHqrXtmS6A8qXaHAegZGBHpf4+EyJACj21oYoaZjUORvvT0n89SpjMrvyQxKpT24+dhYe/0XF7jeVDq6We9N5nLj/QMjGg/fj71uxXfLoRCvCxkJooQjw3v5MLZWw/Yec6d+a92z3Zu5+MkyvD/LOXJdOG2H38fvMyVu/6ERsWTnKbK0SY0Kp4Kdla59C4+V7z8ATh67S51JnyTZztVesa2eI8iYnG0tSzQ2LOGdmTW0I7PHuRzpNFomPbjVrz8w7AwNeKvuaPyTYSc/nlm1vePImL5c98Fft9znp3nb7H2g7F0cqlRbPG9N6ILbyzZzE2fR0z6fiMfjetBNUc7/MOi+W7jcS57+WOgr4dKnf5clhEJIYQoOep1HY7/zXN4ndpJ+/HZi8R7nd71uM2wXPsGelzk5r6/Cbp9lYSoUNSpyTnaJESGYmFfodjjflLQnYzlIA8uH2XZK3kXrdekZ9wXxYc/wtzOsUBjtxo5k1YjZ+bf8AUJvnuDm/tXY+dcm+ZD39R1OIVi5ejMjC13ANCkpxPpf5fza77n5PIF3Dq8nhFfb8lWd0cI8XSSRBHisUHtGjB3+R7uBoTj4RtMw2oZnzBcuxeAb0gURgb69G/TIEe/JVtO8dW6I1l/NtDXw8bCBAO9jIf3iLhENBotSalpz/0aQh4vAUlITiMhOf/XS07Nmewpzd79bRd7L3hibKjPxk/G5zkbJy8V7a34/LU+VHawZu4fe5j64xau/vEe5ibFs0vOiM4uePqF8PP20+x29WC3q0e28+N6NOf2w1CuewdiZWZcLK8phBCiZKrdYSBHf51HpP89wh544lA94x4j2OsaMUG+6BkYUbvDgBz9Lmz4kbN/f531Z6W+AcYWNujpZ8yoTIqNQKvRoEpJeu7XkPh4VxdVciKq5MR826tySfaUBlqNhiO/vI9Wo6HHzO+z3uvSSKmnR7lq9Rny2T/s/vJ17p7ZzZGlcxjx1UZdhyZEqSFJFCEes7EwpWuTmhy5epcdZ92zkiiZS3l6NK+d48HW0y+EbzYcBWByv9ZMG9ie6k62KJ/Yjq7B698TFBFLLqs3ip1Wk/Ei77/ShU/GFV89j9Lgk5UHWHPkKvp6Sv6eP4b2DYteg2V8zxZ8svIAodHxHL9+j8HtGxVbnJ9N7E2P5rVYffgK7veDSE5TUd3JjrE9mjOycxMaT8lY/13DqeDTt4UQQpQ+JpY2VG3elQeXjuB1ckdWEuXO4+U91Vt1x8gs+2zRcN/bnPvnWwCaDnyd5sPexKZC9Wzb4P4+phHx4UHA87/x0GozCqK3HfMeHSd9/NxfT1c8jmwk1NuNmu364lS3GWnJCdnOazUZM3w1GnXWOUOT4tnd73lqOmgyd8/s5sGlIyTFRmJqZafrkIQoFSSJIsQThndy4cjVu+w8d4tPJ/RGq9Wy69ytx+dyLuXZd8ETjUZL+4bVWDxtcI7z6ekaouMK/0mQnlJJukZDiir3mSJxiSm5Hs/cjvfJ7XSLy687z/K/x7vWFNaaD8fSut7z2z7vuw3HWLb7HEqlgt/fGUmflnWfaTwjA31sLUwJjorDLyS6mKL8V/uG1XNN8kTHJ2X93TWvU6nYX1cIIUTJUq/rsIwkyulddJq8AK1W+8RSnpy1Ku6d24dWo6Fy4/b0nP1DjvOa9HSS4wr//5ZCqYdWk446Lff7i9TE3GuomdpkFOKPCwss9Gvm5/LW/3Fl67Ii9R3y2T9UbNCq2GKJfXx9Pq4H+XlQ3vczt49v4/bxbQDMOxpZbK//vDy5tCo22E+SKEIUkCRRhHhCv9b1MDE0wC8kimv3AkhJUxMUGYeZsSG9c3kwD368q0vTmrmvI716LyDX+ij5sTIzJio+ieDIuFyXpNzweZRrvxZ1KrPp5A1Ou/mgTk9HX6/4CqMmJqcSFpOQf8NcqNTpxRbHfy3bdS5r16Al0wYzorPLM4+ZmJJGRFzGtGQzk+dTnC43O866o9VqqV/FkfpVCrZmXAghROlVq11f9I1MiAn2I9jrGuq0VBIigjEwNqNG65wzSuMjggFwrN0k1/GCva7lWh8lP8bmViTHRZEQEZxrgdiQezdz7VehXgs8j27G7/ppNOnqrKKlxSEtOZHE6LAi9U1XP/8l1GVBXKh/1vcGJmY6jESI0kWSKEI8wdzEiN4t67DrvAc7zrqTkqYGoG/repga5XyYtjDNqJXh/SgixzmNRsP3G48XKY76Vctz7pYvBy/fobNLzWznYhKSWXv0aq79hnRoxGerDxESFc/P288w55Wueb5GTEIy1uYmBY7pgzE9+GBMjwK3fxHWHLnCJ6sOAPD15H681qdgnzrll2Basf9CVuKnzXOcQfOk4Mg4Fj1OBr09vNMLeU0hhBC6ZWhiTo3Wvbh7Zjd3Tu3MmglSs11fDIxNc7Q3MrUAICrQJ8c5rUbD+TXfFykO+2r1CXA7h8+FQ1Rp1jnbuZT4GNwPrsu1X51Ogzn150ISo0K5tOkX2o59P8/XSImPwdjCusAxdZgwnw4T5he4/fOUXywb3x9EgPt5GvYcTb95RZs9U9w06ekolMo8C9VrtVqu7lgOgImVHbaVauXaTgiRk2xxLMR/DOuYsWxn17lb7Hlc+DPz2H9l7txy+IoXy3adI1WVkXTxD41m0qKNuHr6YWZc+JkMg9o1BOCfw1fYdPIGaY/HveEdyNBPV2W9zn/ZWZrx8dieAHy97ijz/9zLw5CorPMJyamcvOHNmz9u4bXvNxQ6rpJk17lbvPvbLgA+HtuDtwZ3KHDf/h+u4Oftp7kXGIZGo8k67hscyYJVB/hybUah4H6t62XVxnlS4ymLsBn0Ed9tOFaomMOi4/n8n8O43X+U9XeYkqZi9/lb9Jm/nLCYBPq2qscrXZoUalwhhBClV70uQ4GMHXnund2b7dh/VWmakWS/f/EwV7b9hjotFYDYEH92f/U6AbcuYGBc+BkFdToOBMDtwBo8j24mXZUxkyP47g02zx9Guio1136mVnZ0nPQRAGdXf8OxZR8QE/ww63xacgJ+106y77tp7P5yUqHjKkv+GNeERT3tOFeERFdKfAxJsZFZX5lSE+NyPQ4ZOyGtmdEdjyMbs213rUlPJ9jrGjs+HcuDyxl1/dqOeQ9lMc5eFqKsk5koQvxHzxZ1sDA1IujxUh1rcxO6N809O9+jWW16NK/NsWv3+GTVAT5dfRALEyNiE1NQKhUsmTaYH7edIjGlcNNKJ/Zqycbj17nh84jpP21l9q87MDLQIyE5jUrlrPnujQFM+2lrrn2nD25PTGIyP2w+yZ/7LvDnvgtYmBihVCqIS0pF+7jCbYdG1QoVU0mz8J9DaB4X0l2x/yIr9l/Ms+3dNR9l+3NwVByf/3OYz/85jIG+HhYmRqSkqUh6Yreirk1q8se7rxRrzClpan7efpqft59GoVBgZWZMXFJK1nX0bVWPVfNGF+trCiGEKNmqt+6JoakFCY+X6hhbWFOtRbdc21Zr2Z3qLXvw4MoxTi5fwKkVn2FoakFqQiwKpZKesxdzceNPqFLy3ynnSS79JuBxZCMh926yf9FbHPzxbfQMDFElJ2LpUInub33L/u+n59q3xbBppMTH4Lp+Mdd3reD6rhUYmpqjUOpl1FJ5fN9R2aXgH3aI7FZP70JcaECO4zs/G5/tz/+twxLq7caBHzK2idY3MsHA2JS0pPisJBkKBa1GzqTFsGnPJ3AhyihJogjxH8aGBgxo04CNJ64DMLBtAwwNcv+nolAoWP/ROH7ceoqtp90ICI9BX09Jj+a1mTWkI51cavDjtlOFjsHQQJ+dX05m0abj7HH1JCw6HkszE0Z1bcqHY3pw52HoU/t/OKYHA9rU5899Fzjn4UtoVDzpKg0V7CxpWM2Jbk1r5VootzTRPLHdUWFrtfz29giOXrvHhdt+PIqIJSImAX09JVUdbWlaqyIjOjWhX+t6ufZVp6cT9bhYcOMaudfCyYudlRkfvNqd0273eRAcSVR8EuWszGlSsyJjuzdj4OMZSEIIIV4e+obG1G7fH4+jmwCo1X4Aega5z2JVKBQM/XwtFzb+xO3j24gLC0Cpp0/1lj1oOXIGVZp24uLGnwodg56BIaMW7eT82kXcO7uXxOgwjM2taNhjFO0nfkCE352n9u8w8QNqte/P9d0rCHA7T0JUKFpVGhb2FXCo0ZBqzbtSt+uwQsdVVmjS1STHZswMLl/zxdx/mds5MuiTlfhdP02I13USokJJiY9G38gY20o1qdiwNS79JryweIQoSxRa7YvYeFWIZ3f9+nWaN2/OqZ9m4FLIh1dRugz4aAXnPXxZ9vZwxnRvrutwsrni5U+veX9Q19kB11/fznOt8fP0PN8ft/uP6PLuMq5du0azZs2KdWwhhCjLMu9TJvx2Asdaz17kXLw4mTVN+s75lUa9xxT7+EG3r7Du7T7YV63LpD/P6eTe4Vn8Ma4JcaEBjF68G+cCzigK8XZjzVvd5H5ClElSE0UIIQrhvKcvAO8M71zqboKEEEII8eIFuLsC0HqUbj58EUIUL1nOI4QosWb8sp0Zv2wHwG3FXJzL2+g4InD19MPZweaFL4f6bsOxrK2chRBCCFH8Di6excHFswB4c+0NrBydi2XcgFsXsHJ0pl4pWtJ0YNGMrCVmQojsJIkihChxbMxNcLA2z3ZMqSwZn9xs+XSiTl7XzMQox3tibGigk1iEEEKIssTYwhozG4dsxxTK4tutZsTXpS8ZYWRmmeM90dMv/I6TQpRFkkQRQpQ4az8ap+sQSpxZQzsya2hHXYchhBBClDlDF67RdQglTvcZ39J9xre6DkOIEklqogghhBBCCCGEEEIUgCRRhBBCCCGEEEIIIQpAkihCCCGEEEIIIYQQBSBJFCHKgAEfrcBm0EdsOH5N16EIIYQQ4iWw8f1BLOppx63DG3QdihBCvFBSWFYIIR5Tp6fz1/6LbDp5g/tBESiVSuo5l+e13i0Z3a2ZrsMTQgghRBkSdPsKQV7XCbl3nZB7N4kKvA9aLe3Gz6PDhPm6Dk8IkQdJogghBJCqUjNi4d+cu+ULgImhAWkqFZfuPOTSnYeccrvP7++MQKEoGVstCyGEEKJ02/rRK6Qmxuk6DCFEIUkSRQghgM9WH+TcLV/MTQz53+zhDGrXkHSNhn8OX+GDFfvYfPIGzWpVYuqAtroOVQghhBBlgL6RCbaVa+JYqwmOdZpyffdfhHq76TosIUQ+JIkihHjpBUXG8vfBywB89Xp/BrdvBIC+nh6T+7XhUUQsP207zeLNJ5jYuyVGBvKrUwghhBDPZvqGWyj19LL+fPv4Vh1GI4QoKHkSEKKEcvX0ZdXBS1y8/ZDwmAQszYxxdrChd8s6jOnenErlrAs0znmPB+w+78HVuwE8ioglJiEZW0tTWtV1Ztqg9rStXzXXfqkqNX/tv8jOc+7cCwwnJU2NrYUpjrYWdGxUnVe7N6N+Fcdsfc663+fPfRe4ei+AyLgkTI0MKGdtTqPqTvRvXZ/hnVye8V15PvZd8CRNnY6NhQmvdmua4/y0ge34ZccZwmMTOXXTh94t6+ogSiGEEOL5Crh1gZt7/ybQ4yJJMeEYmVliWb4yNVr3plHvMVg6VCzQOP5u57l3dg9Bd64SHx5ESkIMxhY2VGzQihbDplGpYZtc+6nTUrmxZyVep3cS6e+NOi0FE0tbzO0ccXbpQMNer1KuWr1sfR7ePMv1XSsIunOV5LgoDIxNMbW2p3zNxtRq1496XYc98/vyvDyZQBFClB6SRBGihNFoNHy0cj/L917IOmZpZkxyqorr3oFc9w5Eo9HywZge+Y6VkJzKgI/+yvqzhakRBvp6hETFs8fVk70XbrNk+iAm9WmdrZ9Knc6QBSu5ePshAEqlAktTY8JjEwiNjsftfhB6ekoWTuyT1WflgYvM+WPPv69lYkSqSo3Powh8HkVw/pZviU2iZNZBaVu/Koa5zDJxsLGgnnN5PP1COHfrgSRRhBBClClajYYTv3/MtV1/Zh0zMrNElZJMyN0bhNy9gVarKVCx07TkBDbNGZT1Z0NTC5R6BiRGhXLv7F7undtHr9mLaTLgtWz90tUqtswfRqDHRQAUSiVGZpYkxYSTGBVKqLcbSj09Ok/5LKvPjb2rOLp07hOvZU56WirRgfeJDrxPgNv5Ep1EEUKUTpJEEaKE+XHbaZbvvYBCoWDmkA5MH9QeJztLAPxDo9nj6oG5iVGBxlIqFQzt0IhRXZvSpn5VrMyMAQiOjOOPva4s3XGGD/7cR9cmtajqaJvVb9tpNy7efoi9lRn/mz2c7s1qoa+nh0qdjn9YNHsveGJjbprVPjEljc9WHwLg3RGdmTGkA3aWZgBExCbg6unH0at3i+X9eR7uBYYBUKeyQ55talcuh6dfCHcDw19UWEIIIcQLcXHjTxkJFIWCViNn0nzom1jYOwEQG+LP3bN7MTQ1L9BYCoWSOp2H0LDnKCo1bIORWcY9THxEMNd2Lufyll85/tuHVG3eBWunqln97pzYRqDHRUyt7ek751eqteiGUk+fdLWK2BB/vM/tw9jSJqt9WnIip/5cCECb0e/QYsRbmFrZAZAUE0HALVceXD5WDO+OEEJkJ0kUIUqQ8JgElmw5CcCnE3rxzvDO2c47l7dh5tCOBR7P1MiQVfNezXHcyc6Sz1/rQ2xCMv8cucL6Y9f4eFzPrPNX7wUAMGNIh2yzLgz09ahRwT5HXF7+oSSmpFG7Ujk+ndA72zl7K3MGtWvIoHYNCxw3wLlbDxj48V/5N8zF/NHdCjRTJ1NIVDwAjrYWebZxtMm4CQyLji9STEIIIURJlBgdzoUNPwLQ+fUFtB79drbzVo7OtBo5o8DjGRibMviTlTmOW9g70eWNhaQkxOJ+YA23Dm+g42sfZZ0P8roGQMvhb1Gjda+s43r6BthWqpEjrsiHXqhSErGtXItOkxdkO2dqbU+djoOo03EQheHvdo5NcwYXqk8m2ZZYiJeHJFGEKEF2u3qQkqbGydaSmUM6PPfX69miDv8cucLVuwHZjluYZsx0CY0qWMIgs31cUgpJqWmYGhk+c2wG+no4WBfsU6//MivgTJ1MSakqAIwNDfJsY2KUcS4xJa1IMQkhhBAl0b2ze1CnpWBu50jLQiRLiqpGqx64H1hD0J2r2Y4bmWZ8kJEQFVqgcQwft09NjEOVkoSBsWk+PfKnp2+ImU3es1KfGo+J2TO/vhCidJAkihAlyLXHyYzOLjXQL6ZiY2kqNWuOXmXPeQ/u+IcSk5CMOl2TrU1IdFy2P/doVptftp9h+b4LRMUnMaKzC23qVc1KlvxXdSc7qjna4hsSRa+5fzClXxu6NqlJlSeWCBVW63pVuLvmo/wbCiGEEKLIMmeAVGnWGaVe8TwapKvScD+4lrtn9xDh50VKfAyadHW2Non/SZZUa9mdS5uXcm3XnyTHRVG/2wgqNmydlVz5L5uK1bGuUI2YIF/Wvd2HpoMmU7VZF6ydqhQ57ooNWjFjy50i9xdCvBwkiSJECRIemwhQ4J138hOXlMLQBau47h2YdczM2BAbcwMUCgVp6nRiEpJJSlFl69ehUXXmj+7G4i2n2HLqJltO3USpVNCwqhN9W9VlUt/WlLf596ZGX0+PP98fxfhv1+HpF8K7v+0CMpbHdG1Si7E9mtO+YbViuabnwdTIgFh1OilpqjzbJD+erWJm/OyzbIQQQoiSIikmAgBLh0rFMl5qYhyb5w8j5O6NrGMGxmYYW9igUChIV6eREh+DKiUpWz9nlw60Gz+PC+uXcPv4Vm4f34pCqaRc9YbUbNuHJgNew9y2fFZ7pZ4+Az74g50LJxD+wJMjP78HgJlteao170qjPmOp3LhdsVyTEEI8SZIoQpRhP2w+yXXvQCzNjFk8bRA9mtXGxuLf6a6n3XwYsmAVWrQ5+n4wpgejujZl+1l3XD18uezlj/uDINwfBLFs9znWfzSeTi41stq3qFOZa8vfZ4+rJyeue3Phth+B4TFsPHGdjSeu83rf1iyZXrR1xs+bo60FsYkpWbVRchP6uBbKk8kjIYQQQmTnun4JIXdvYGRmSc/ZP1CtRXdMnigI+/D6aTbPH4ZWm/Peo8OE+TTo8QpeJ3cQ4O7Ko9tXCPNxJ8zHnSvbljHs83VUadopq32Fei2Y+s9V7p3di++1EwTeukhcWCAeRzfhcXQTTQZOotfsxS/kuoUQLw9JoghRgmTWAAkIjymW8fac9wDg2yn9Gdm5SY7z4TGJT+1fzcmOOa90hVe6olKnc9rtPp+vOYyHbzDTf96K+1/z0NNTZrU3NTJkdNemjO7aFADvwHD+2OvKqoOXWHXwEv1a16N7s9oFiv3SnYdM+HZ9Aa80u5lDOzKrEAV4a1dy4G5AOPeesvNO5rnaT9nBRwghhChtzKzLARAXGpBPy4K5d3YPAN2mf039biNynE98PPMlLzYVqtF27Pu0Hfs+6WoVD2+c4cxfXxD2wIP9i95i2rqMrY4zGRib0qDnKBr0HAVAZIA313Yu5+bev7m5929qte1HtZbdChT7I8/L7Pp8YkEvNZuWI2fQauTMIvUVQpQuyvybCCFelBZ1KgMZM0TU6enPPF5wVEatkyY1K+Z6/tytBwUey0Bfjx7Na7PmgzEABEXG4RsS9dQ+tSqVY8n0wbSpn7E++byHb4FfT6VOJywmoUhficmpBX4dgA6NMpYauXr6kqZS5zgfFh3P7YchAHRsVL1QYwshhBAlmVO9FgD4XT+do25JUcRHBAPgWLtpruf93c4VeCw9fQOqt+zO4M9WA5AQEUxM8NPvJewq16LX7MVUatgGgAD38wV+vXR1GonRYUX6Skt++gdTQoiyQ2aiCFGCDG7fkE9WHiAkKp7/7TqXYyvhwrIwMSIqPgmfRxHUr+KY7ZzPowi2nLqZa780lRpDg9x/PTy5g01mDZGntQcwedwnNZcERV46NKpO9J5vCtz+WQxo24AFqw4SHZ/M5pM3Gd+rRbbzf+6/gEajpZyVGZ2fWMIkhBBClHZ1Og3i5PIFJEaFcmXrshxbCReWkakFyXFRRAV6U65avWznogJ9uH18a6790lVp6BnkXndM39A463t1Wmq+7Z/so1YV/IMVZ5cOzDsaWeD2QoiXk8xEEaIEsbM04/1XugLwxZojfLb6EMGR/+6c4x8azfcbj7Pq4KUCjZf5wL9g1UEue/mj1WrRaDQcu3aPoZ+uwtgo98THtJ+3Mmvpdk7e8CbhiVkd3oHhzFy6HYAKdpbUc84o8Hb02j16zfuDtUeuEvjEUqT4pFSW7jjDKbf7AHRrWquA78SLVcHOitf7tgbg45X72evqgVarRZ2ezt+HLvHL9jMAzBnVDaOnJIuEEEKI0sbUyo62YzKKsp5e9SWnVizMmk0CEBviz/m1i7ix9+8Cjef8uGbJqT8/49HtK2i1WrQaDQ+uHGfL/OHZEiJP2r/oLQ4umY3ftZOkJSdkHY8M8Obg4lkAmNs7YV+lLgAPLh9l3dt9cD+4jriwR1ntU5PiubTlV/xunAagWvOCLeXRhbTkBJJiI7O+0tUZHzapU5P/czzvwvdCiBdPngaEKGHeHdGJ0Og4Vuy/yNIdZ1i64wxWZsakazQkJKcBMH90wW4IPhzTg+M3vPEPi6b3vD8wNTJAo9WSkqbGydaSbyb3Z/rP23L0S01Ts/PsLdYdu4ZCocDKzJjUNDXJj2eemBoZ8Ns7I7LVQ7ni5c8VL/+s8wb6esQmpmSdf61PqwLXQ9GFha/1wcMvmHO3fJnw3QZMjQxI12izZs+M6tqUN/q30XGUQgghRPFrM/odEqNCub77Ly5v+ZXLW37FyNwKTboa1eNlKu3GzyvQWB0mfoDf1RPEhviz/u0+GBibotVoUKelYG7nSLfpX3Fg0Ywc/dRpKXid2smtQ+tBocDY3Ap1Wirq1GQgo/ZJ/7nLstVDCbp9haDbV7LOK/UNSE2IzTrv0v+1AtdD0YVjv87H4+imHMcz/w4yjV68G2eXDi8yNCHEU0gSRYgSRqlUsujNQQxs24C/Dlzkspc/kXFJ2JibULdyeXq3qsuY7s0KNFatSuU49sN0vll/lNPu90lMTsPJzpJeLeowd1Q37gaE5drv0wm9aVW3Cmfc7/MgOJLQqHi0aKlZ0Z7OLjWYOaQjVR1ts9p3bFydP94dyambPrg9CCIkKo74pFQcrM1pUrMiE3u1pF+b+sXy/jwvRgb67PzidVbsu8imkze4HxSBoYESlxoVmNSnFaO7Few9F0IIIUobhVJJj5nfU6vDAG7sWckjz8skx0VhYmGDfZW61GzTm4a9Xy3QWHaVazHu1yOcW/0tD2+cQZWSiLmdEzVa96Tt2DlE+t/NtV/n1xdQsX4rHt44Q0yQLwlRoaDVYlOpBlWbdqblyBlYO1XNau/cpCP95/+O3/VThHq7kxAZQlpSPGY2DpSv3QSXfuOp1a5fcbw9QgiRjUKb2/5iQpRA169fp3nz5pz6aQYuNXIvlCqEeDZu9x/R5d1lXLt2jWbNJHEkhBAFlXmfMuG3EzjWctF1OELoVIi3G2ve6ib3E6JMkpooQgghhBBCCCGEEAUgSRQhhBBCCCGEEEKIApAkihBCCCGEEEIIIUQBSBJFCCGEEEIIIYQQogAkiSKEEEIIIYQQQghRAJJEEUIIIYQQQgghhCgASaIIIYQQQgghhBBCFIAkUYQQQgghhBBCCCEKQJIoQgghhBBCCCGEEAUgSRQhhBBCCCGEEEKIApAkihBCCCGEEEIIIUQBSBJFCCGEEEIIIYQQogD0dR2AEIV1NyBc1yEIUWbJvy8hhHg2kf73dB2CEDon/w5EWSZJFFFq2NvbY2pqwps/btF1KEKUaaamJtjb2+s6DCGEKFXs7e0xMTVl/3fTdB2KECWCiamp3E+IMkmh1Wq1ug5CiILy9/cnIiJC12E8s4CAAMaMGUOnTp346quvUCgUug5JFNG9e/eYMGECQ4cOZf78+boOp1jY29vj7Oys6zCEEKLUKcn3Kd9//z07d+5k7dq11KpVS9fhiCLSarV8/PHHnD17lo0bN1KpUiVdh5QnuZ8QZZUkUYR4wdLS0mjfvj3R0dFcv34dS0tLXYckntFvv/3GjBkz2LlzJ0OGDNF1OEIIIUQ2O3fuZNiwYfz2229Mnz5d1+GIZxQXF0fTpk2xs7Pj3LlzGBoa6jokIV4qkkQR4gWbM2cOS5cuxdXVlRYtWug6HFEMtFotw4cP59SpU9y8eVM+dRFCCFFi+Pv706RJE7p27cq2bdtk9msZcfXqVdq1a8c777zDokWLdB2OEC8VSaII8QIdOHCA/v37s2TJEt577z1dhyOKUXR0NE2aNMHZ2ZmTJ0+iry8lp4QQQuiWWq2mS5cuBAQEcPPmTWxsbHQdkihGP/74I++//z4HDx6kT58+ug5HiJeGJFGEeEGCgoJwcXGhVatW7N27F6VSdhgva86fP0/nzp356KOP+OKLL3QdjhBCiJfcggUL+Pbbbzlz5gzt2rXTdTiimGk0GgYOHMiVK1dwc3PDyclJ1yEJ8VKQJIoQL0B6ejq9evXizp07uLm5Ua5cOV2HJJ6Tb775hk8++YTjx4/TtWtXXYcjhBDiJXXixAl69OjBV199xUcffaTrcMRzEh4ejouLC/Xq1ePIkSPo6enpOiQhyjxJogjxAnz99dcsWLBAHqxfApIwE0IIoWthYWG4uLjQoEEDDh8+LA/WZZwkzIR4sWQ9gRDP2blz5/jss8/45JNPJIHyEtDT02Pt2rWo1WomTpyIRqPRdUhCCCFeIhqNhtdee4309HTWrl0rCZSXQLdu3fj444/59NNPOX/+vK7DEaLMk5koQjxHUVFRNGnShCpVqkix0ZfMwYMH6devnxQRFkII8UItWbKEOXPmSLHRl8yTRYRv3LiBra2trkMSosySJIoQz4lWq2XYsGGcPn0aNzc3KleurOuQxAs2d+5cfvnlF86fP0/Lli11HY4QQogy7sqVK7Rr1453331Xtr19CWVuZ92lSxe2b98u21kL8ZxIEkWI52TZsmXMnDmTXbt2MXjwYF2HI3QgLS2NDh06EBkZyY0bN7C0tNR1SEIIIcqouLg4mjZtir29PWfPnsXQ0FDXIQkd2LVrF0OHDmXZsmW89dZbug5HiDJJkihCPAc3b96kdevWTJ06lV9//VXX4QgdevDgAU2bNqV///6sX79ePhUSQghR7LRaLWPGjOHAgQPcuHGD6tWr6zokoUOzZs1ixYoVXL58mcaNG+s6HCHKHEmiCFHMEhMTad68OcbGxly8eBFjY2NdhyR0bPPmzYwePZpVq1YxadIkXYcjhBCijFm1ahWTJ09m06ZNjBo1StfhCB1LSUmhTZs2pKamcvXqVczMzHQdkhBliiRRhChmr7/+Olu2bOHatWvUqVNH1+GIEuKNN95gw4YNXL16lXr16uk6HCGEEGXEnTt3aN68OWPHjmXFihW6DkeUEHfv3qVZs2aMHj2alStX6jocIcoUSaIIUYzWr1/PuHHjWL16NRMnTtR1OKIESUpKokWLFhgYGHDx4kVMTEyynY+OjsbGxkZH0QkhhCiNkpOTad26NWq1mqtXr2JqaqrrkEQJsnr1aiZNmsT69esZM2aMrsMRosxQ6joAIcoKHx8fpk2bxrhx45gwYYKuwxEljKmpKZs3b+bevXvMmTMn27mUlBQcHR05efKkjqITQghRGr3//vt4e3uzefNmSaCIHCZOnMjYsWOZNm0aPj4+ug5HiDJDkihCFIPU1FRGjRqFo6Mjv/32mxQPFblq1KgRP/30E7/99hs7duzIOm5kZISpqSkXL17UYXRCCCFKk+3bt/P777/z888/06hRI12HI0oghULB77//Tvny5Rk9ejRpaWm6DkmIMkGSKEIUgw8//JBbt26xefNmLCwsdB2OKMHefPNNhg8fzuTJk3n48CGQcZPToEEDPDw8dBydEEKI0sDPz4/JkyczYsQIpk6dqutwRAlmYWHBpk2bcHd358MPP9R1OEKUCZJEEeIZ7du3j59++olFixbRrFkzXYcjSjiFQsGKFSuwsrJizJgxqNVqABo2bChJFCGEEPlSqVSMGTMGa2trVqxYIbNfRb6aN2/OokWL+PHHH9m/f7+uwxGi1JMkihDP4NGjR7z22msMGDCAt99+W9fhiFLCxsaGjRs3cunSJRYuXAhkJFG8vLyykipCCCFEbj777DMuX77Mpk2bsLa21nU4opR4++23GTBgAK+99hpBQUG6DkeIUk125xGiiNLT0+nevTve3t64ublhb2+v65BECXbixAkePnzI2LFjMTQ0BOC7777jo48+4ujRo+jp6dG1a1fu3LlD3bp1dRytEEKIkujYsWP06tWLb7/9lvnz5+s6HFHKRERE4OLiQp06dbLuPYQQhSczUYQooq+//pqzZ8+yYcMGSaCIfN28eZPJkydTt25dVq9ejVqtZt68eXTv3p1x48bh4OAAIEt6hBBC5Co0NJTx48fTo0cP5s6dq+twRClkb2/P+vXrOXXqFN9++62uwxGi1JIkihBFcPbsWT7//HMWLFhA586ddR2OKAXee+893N3dadq0KZMmTaJBgwZs3ryZf/75B41Gw/vvv4+Dg4MkUYQQQuSg0WiYOHEiGo2GNWvWoFTKLbwomi5durBgwQI+++wzzp49q+twhCiVZDmPEIUUGRlJkyZNqF69OsePH0dfX1/XIYlS5vr163z66afs37+fBg0aMGzYML788ktq1qyJi4sL27Zt03WIQgghSpAffviBefPmcfjwYXr16qXrcEQpp1ar6datG76+vri5uWFra6vrkIQoVSSJIkQhaLVahgwZwrlz53Bzc6NSpUq6DkmUYhcvXuTTTz/l6NGjlC9fntDQUKpUqYKfn5+uQxNCCFFCXLp0iQ4dOvD+++/z3Xff6TocUUYEBATQpEkTOnbsyM6dO2WXJyEKQZIoQhTCr7/+yuzZs9mzZw8DBw7UdTiijDhz5gyffPJJ1rTa1NTUrOKzQgghXl4xMTE0bdqU8uXLc/bsWQwMDHQdkihD9uzZw+DBg/n111+ZOXOmrsMRotSQJIoQBXTjxg3atGnD9OnT+fnnn3UdjihjtFotGzduZPXq1Rw+fFg+ERJCiJecVqtl1KhRHDlyhBs3blCtWjVdhyTKoLfffps//viDS5cu0aRJE12HI0SpIEkUIQogPj6e5s2bY25uzoULFzAyMtJ1SEIIIYQow1asWMHUqVPZsmULI0eO1HU4ooxKTU2lbdu2JCYmcu3aNczNzXUdkhAlnpT2FuIJfn5+qFSqHMdnzpxJUFAQmzZtkgSKEEIIIYpFcnIygYGBOY57enoye/Zspk6dKgkU8VwZGRmxadMmHj16lOuSHpVKJbXahPgPmYkixGNJSUnY29uzadMmBg0alHV87dq1TJgwgTVr1jB+/HgdRijy4u/vT0REhK7DEOKlYm9vj7Ozs67DEKJUW7hwIXv27OH69etZx5KTk2nZsiUAly9fxtTUVFfhiZfImjVrmDhxImvXrmXcuHFZx/fs2cPo0aOJiIiQn0UhHpO9WYV47M6dOyQnJ+Pk5JR17N69e0yfPp0JEyZIAqWE8vf3p169eiQlJek6FCFeKqampty5c0cSKUI8g2vXrmW77wB49913efDgAVeuXJGHVvHCTJgwgWPHjjF9+nRat25NrVq1AHB0dCQ5ORkvLy+aNWum4yiFKBkkiSLEYx4eHgDUq1cPyFgjOnr0aCpUqMCyZct0GZp4ioiICJKSkli9bDH1atXUdThCvBTuePvw2ow5RERESBJFiGfg4eGRbbnO1q1bWb58OX/++ScNGjTQYWTiZbRs2TIuXrzI6NGjcXV1xcjIiPr16wMZP6uSRBEigyRRhHjMw8ODatWqZRXUmj9/Pp6enly8eFGKbJUC9WrVpGljueEUQghROsTHx+Pn50fDhg0B8PX15Y033uCVV15hypQpOo5OvIwsLCzYtGkTbdu25YMPPuCnn37C3NycqlWrZn3YKISQwrJCZPHw8Mi6kdmzZw+//PILixcvpmnTpjqOTAghhBBlze3btwFo2LAhKpWKV199FRsbG/7880/Z5l7oTLNmzfjhhx/4+eef2bt3L5DxMypJFCH+JUkUIR7z9PSkQYMGBAYGMmnSJAYNGpRVpVyj0bBp0ya+/PJLHUcphBBCiLLA09MThUJB3bp1WbBgAdeuXWPTpk1YWVkBEBAQwAcffJCt6KwQz8MXX3zBpk2b0Gg0AMyaNYuBAwcyadIkAgMDadCgAZ6enjqOUoiSQ5IoQgCxsbEEBARQr149xowZg6mpKatWrQJg586duLi48Oqrr3L37l1kQyshhBBCPCsPDw9q1KjBuXPn+P777/nmm29o3bo1wcHBzJo1i5o1a7Jy5UpSU1N1Haoow7RaLffu3ePVV1+lSZMm7Ny5E4C///4bY2Njxo4dS/369fH39ycuLk7H0QpRMkgSRQjIyq67urpy/vx51q9fz6VLl2jRogXDhg3D0dERV1dX1q1bJ1NshRBCCPHMPDw8qFmzJuPHj6d3795MmDCBOXPmUL16ddavX8/ChQvx9fWlbdu2ug5VlGEKhYJ169bh6uqKg4MDw4YNo2XLlly6dIn169dz7tw5XF1dAWQ2ihCPSWFZIci4kVEqlfz555+MHz+e+fPnc/HiRTp27MipU6fo3LmzrkMUQgghRBni4eGBkZERWq2WunXrUqNGDZRKJfPnz+fdd9/NWtYjxIvQtm1bjh07xunTp1mwYAH9+/enbdu2jBs3jj///BOlUomHh4ck9YRAZqIIAcCVK1fQarVYWlqyZs0atFotR44c4fTp05JAEUIIIUSxioqKIjg4GD8/PxITE1mxYgWzZs3C19eXhQsXSgJF6Eznzp05ffo0hw8fJj09nTVr1mBpaYlWq+Xq1au6Dk+IEkGSKEIAhw4dQqvVUrlyZfbu3cuFCxfo2bOnLN0RQgghRLE7ffo0APr6+kybNg1fX1++/fZb7OzsdByZEBlLfHr16sXFixfZu3cvlSpVQqvVcuDAAV2HJkSJIEkUIYDZs2ezZMkS3NzcGDBggCRPyrDJs+dh6FiLHkPH5tu2VosuGDrW4osfluY412PoWAwda2HoWItaLbrkW3B40sy5We1NKtbNcX7Npu1Z55/8sq7WmAbte/HW3E+4fdc7Rz8//8CstqfPX8r3mjJlvg9P+3r7w88LPF5Z9vuqddn+rp/FrTt3mfDWe1RxaY9FlQbUbN6Zt+Z+gn9gUK7tn/z7LcjXf+X1c/XkV5PO/Z7pmoQQhdeuXTtGjRqFj48PS5YswcHBQdchCZGDQqFgwIABuLu7s2TJEmbPnq3rkIQoEaQmihDA3LlzdR2CKMUeBj7i3MUrdGzbKtfziYlJ7DpwpMDjlS9nn/V9ZHQM3vd98b7vy5rNO1i19AdeGdL/mWPOZGZqirmZaa7nLCzMi+11SqvQ8Ag+/e7HYhlr7+HjjJk6m9TUNBQKBRbmZvg/CuKvtZvZtucgBzevpnmTRtn66OnpZft5yE1kdAxqtZqmjRvk2cbAwABb69yXB9jb2hT+YoQQz6R8+fJs2rRJ12EIUSBKpZL33ntP12EIUWJIEkUIIZ6Bc8UK+D8KYsP2PXkmUXYdPEpiUlJW2/wE3LqQ9b1KpeLE2QvMmLsA/0dBTHlnPu1bN6eik2OxxP/u9Ml8Olc+WcrL3M++ITYunpZNG3PlhnuRxwkMCmbC9PdITU1jYJ8eLFv0BY4O5bjv95BJM+dy8eoNXpk8A49zRzAxMc7qV7miU7afh/+KiY3D2aUdarWacSOH5NmubYumHNu5vsjxCyGEEEKIDKU+ieLv709ERISuwxCiRLC3t8fZ2VnXYbxUhg3ow29/r2XHvkP8/PUCjIyMcrTZsG0XAKOHD2LR0j8KNb6BgQG9u3Xin9+W0HXwq6SkpLJ2y04+eHt6cYRfYsTExnH24hUG9u6u61CynDx3gU079jKgd3eaNKz/TEmURUuXk5iURPUqlVn/x88YG2f8nNSoWoVtf/9Og/Y9CXgUzJ9rNvL2m5MKPO62PQdISUnFwMCA0UMHFjk+UXBy3yHEv+S+o/jI7xZR1pTl3w+lOoni7+9Pvbp1SEpO0XUoQpQIpibG3PG6W2Z/YZVE1taW9O3Rhd0HjnLg2CmG9u+d7XxIWDgnzl7AqbwD3Tq2LXQSJVP71i2oVMGRwKAQbrh7FkfoOqfVajl57gKrN25j14Ej1K5RrcQkUdLS0pj1wUKMjY1Y8sXHrN2ys8hjaTQatu89CMDUiWOyEiiZHMrZ8eqwQfyxej2bduwtVBJl3dZdAPTq2pFy9lKQ8nnz9/enTt16pCQn6ToUIUoEYxNT7nrdkfuOZyTPNKIsKsvPJaU6iRIREUFScgq/Dq9JLXsTXYcjhE55RyQza7sPERERZfKXVUk2Zvhgdh84yobtu3MkUTbt2Et6ejqvDOmPnlLvmV7HqbwDgUEhxCckPNM4uvYw4BFrNu9g7eYd+AUEZh2v6lxZh1Fl98P//uSezwMWzJlNtSrPFpfnXW/CI6MA6NapXa5tunVqxx+r13Pd3YP4hAQszPOvR/PgoT+ul68BMP6Voc8UoyiYiIgIUpKTqPnGr5g45SzkK8TLJDnYG58Vs+S+oxjIM40oa8r6c0mpTqJkqmVvQqMKUgBRCKEb/Xp0wcbaikPHTxMTG4e1lWXWufWPl/KMGT6YuPhnS34EPAoGwMrSMp+WBbdpxx7WbNpOcFg4FuZmNKhTi6EDevP6mFcwNS2+G7mUlFR2HTzCPxu3ceLshazdjBzs7Rg9bCATRg+ncf2cuxbpwn2/h3y/9A+qOVdi7sypzzye1737QMYuB/Vq1ci1Td3Hx7VaLXe9H9CiaeN8x123ZRcANtZWDOjV7altb9/1xqVTXx489MfQwIBqVSrTq2snZk6ZQAXH8oW4GgFg4lQL8yqN8m8ohBCFIM80QpQOZSKJIoQQhXXh6g0qN2r71DaZswfyY2RkxIhBfVmxZhPb9hxgyvjRAHh6eePmcYd6tWvStHGDQm1B/F+Hjp8mJCwcgJYFeMAuKB/fhxgaGmBmakJUdAxnL17h7MUr/PnPRnat+5PqVZ7t04Prbh6s3riNzbv2ER0TC2TUeenTvTMTRw+nX48u6Ovn/V+Rn38gtVt1LdJrj39lKCuXLip0v3c+/IKUlFSWfPVJjqU3RRESFgZkJDtyq5kDGbOMstqHhxdo3MxaOyMH9cPQ0PCpbSOioomKicXK0oK4+ATcPb1w9/RixZqNrPvjZ3p361Sg1xRCCCGEeNlJEkUI8VJSqVSEhhdfAbcxwwezYs0mNmzfnZVEyZqFMmJwkccNCQvnyMmzzP/8OwAszM2KZelG08YNaNOiKX17dKGikyMKhYKIyCj+2bSdz3/4BS/v+wwe9wZXj+3J88E/L5FR0WzYvpvVG7dz67ZX1vHGDeoyYdQwXh02qMD1OwqyxW9erCwtCt1n256DHD55hn49ujCgV/HUZ0lMSgbA5CkJGdMnduRJSMy/3sb5S1d58DAAgPGj8v55cHJ04LN5bzNsQB9qVquCgYEByckpHDh2knkLvyXgUTCjJs/kwuEd1Ktds6CXJIQQQgjx0pIkihDipdSpbat8t3yt1aILDwMfFWi8dq2aU825EucvXeNhwCMqV3Ri0449KBQKXh02qFCxGTrmXmvBwtyM9ct/KZYCojOnTMxxzN7OlvdnvEHDenUYOGYyd70f8M+m7UydOKZQY1dp0p60NFXGmLY2jB42kPGjhtG0UYNCx5nfFr/FKT4hgbmffY2RkSFLvvrkhbxmUWUWlK1VoxqtmzfNs13PLh3p2aVjtmMmJsYMH9iX1s2b0KrHYCKiovlqyf9Yv/zn5xixEEIIIUTZoNR1AEIIURYoFApGDx+EVqtl4449nHa9RGBQCB1at8C5UoVCjVW+nD3ly9nj6FCOqpUr0b51Cz54ZzpuZw7Sp3vn53QF/+rdrROd2rYC4MDRk4Xun5lAUSgU9O/VjVeGDChSAuVF+3zRLzwKDuX9t96gRtUqxTau2ePaMskpqXm2eXJHBnMz06eOl5KSmrXbz7iRQ4ocV6UKTkybNA6AwydOo9FoijyWEEIIIcTLQmaiCCFEMRk7Ygjf/vQbG7fvweeBX8axIjzkvqiZF0/Tomljzly4jK9/YP6N/2PVrz+wesNWzl68wj+btvPPpu3UqlGN8a8MZdzIIVSq4PQcIn423g/8WLZyLRWdyjNj8ngSEhOznU9TZSSGtFpt1jkTY2P09PLfccnRIaPeSXRMLKmpqbkuj8qsdwPg5OCQ4/yT9h4+TkxsHAqFgrEjhuT7+k+TWV8nLj6ByKho2SZZCCGEECIfkkQRQohiUrtGNVo0aczVm+74+D7EyMiQ4QP76jqsF27cyCGMGzmE+34PWb1xO+u37sT7vi+ffvsjC7//ma4d2jB+1DCG9O2V7w5AAY+CaddnWJHiGDm4Hz9+taBAbYOCQ0lPT+dRcCgVG7bJs53/oyBsazQB4Oj2dXRu3zrfsevW/nfnHS+fB7g0qJejjZf3vzv41K5Z7anjrd+6E8hYklbYWU5CCCGEEOLZyHKeUqD1T9ep+NkFXH1ji21MV99YKn52gdY/XS+2MYUQMPZxEVmVSkW/Hl2LVNy0JLh6wx2AqpUrFnmMGlWr8OWH7+Fz9TR71v/F0P690dfX4/gZV16bMQdnl3a8+d5HnL90Nc8x0tPTCQ2PKNJXbFx8kWMvTg3q1KKcnS0AJ8645tom83hzl0ZYmOe9vWVYeCRHTp0DKJYCw1ce/z2bm5lhZ2vzzOOJsuH6vNZcmFyRWK/cf16LItbLlQuTK3J9Xv6JRyFE6SXPLeJlIDNRRKlw+WEcf7gGcS0ggfhUNU6WRvSua8OsjhWxMTUo8rhRSSr+d/YRh72iCI5Lw8JIn+aVzZnevgItnS2L8QrEy2LU0AH4BwYBMHxQHx1HkzutVotCocjz/NFTZzlz4TIAfXsUbXvhJymVSvp070yf7p2JiIxiw/bd/LNpB7due/H3hq38vWErNao6M3PKRGZMmZCtb1XnSqSFeD9zDPnp3L71U1/nix+W8tWSX6lSqSLeV08VamylUsmIQf34/e91/PnPBt56fVy2JT3hEZFs3LEHyPj5eZpNO/egVqsxNTFh2MCn/3zl9/ccFBLKH3+vAzLq4CiV8rmKEJnivC8TdOgPEh5cQ50Uj5GtEzZNelOx/ywMzIuecFQlRPFo//+IunmYtKhg9E0tMK/enAp9pmNZq2UxXoEQQlfkuaXskzumUqCKjRE17I0xMSi+vy4TAyU17I2pYlO4rUt14Z/LIQz/25PDXtFEJakw1FPiF5XCctdgev7uTmBM3sUan+ZhVAo9f3dnuWswflGpGOopiUpScdgrmmGrPFl3NbSYr0S8DOztbPl+4Qd8v/ADWjVr8kJfOzY+nojIqDy/Eh9vnbt+225efWM2+4+cIDrm30+KIqOi+fmPVYycNAOAmtWr8tqrI4o1Rns7W2ZPncS1E3txPbidqRNexdrKkvt+/vy9cWuxvtaLVqtFFwwda/HFD0tznJs7aypmpqbc9/Nn3PR3s7bXfvDQn5GvzyAmNo5KFRyZOuHVp75G5q48Q/r3wtzM7KltHwY8omP/kfyzcRuBQcFZx5OTU9i5/zBdBo4mIioaExNjPnl/ViGvVpRlRuWqYOxYA6Xh05fbFYbS0ARjxxoYlSu+os3PS8jJf/D8fjjRNw+jio9CaWBISpgfwUeW476wJ6kRha8VBZAS/hD3hT0JPrKc1DA/lAaGqOKjiL55GM/vhxF6el0xX4kQL548t8hzy8tAZqKUAlteK/5dLZpWsuDMrLy3xSwp3B4lsOCgLxotjG3uwMc9q2Bloo9HcCLTt97jQWQKUzffZf/URk/9xPW/NBotU7fcIyQujep2xvw+sjYNncyITVbz9dGHrL8Wxsf7fWlS0ZyGTk9/UBGipBjx2vSnnp/1xkSWfPkJmvR0tu89mLXDi6WFOXp6esTExqHVagGoV7smO9cux9j4+d2wtGjamBZNG7P4i4/Zsf8QV667PbfX0rVKFZxY8/uPjJk6m90HjrLn4DEsLcyzlhxZW1myddVvmJgY5zmGp5c3N2/dBgq+K8+laze5dO0mkLG1samJCTGxcaSnpwNgY23FP8uW0KBu7ttqi5dTg7lbin1Mi+pNafr1mWIft7gl+Lnhu2EBaDU4dB5LlREfo29qRaK/B/f+mE5K6APu/j6VRp/sL9R9h1aj4d5vU0mLDsG4fHVqT/sdM+eGqJNiebjta8JOr8d3/ceYV22CWZWGz/EKhXi+5LlFnlteBjITRZRoi08GkK6Bls4WfD+wOlYmGXm/hk5mrBxdBz0luAUlcsgrqlDj7r8ThUdwInpKWPVqnaxfOFYm+nw/sDotKlug1mhZcjKg2K9JCF3r3L4Nn817m15dO1K1cqXHO84k4WBvR88uHfjthy+5dGQX1as4v5B4jI2NGDN8MD99/ekLeT1dGdi7O66HdjBq6AAcHcqRnJKCc8UKTBk/iqvH99K8SaOn9l/3uKBsRafydOvYLt/XK1/Onh+/+oQRg/pRu2Z1jI2MiI2Lx9LCnFbNXFgwZzbuZw+9kG2zhSgtAnYtBk06FjVbUn389+ibWgFg5tyQOjNXglKPRD83om4cKtS4Udf2k+jvAUo96sxchZlzRqJE39SK6uO/x6JmC7TpagL2LCn2axJCvBjy3PLykJkoL1B8ipqfTwey/3YUYQlp2JsZ0LOODe93qczRe9G8t+s+batasm1S9gxu65+uExiTytbX6tOumlXW8c03wrL1OXgnkhUXgrkdkoRGq6WhkxkzO1akW62ca3ddfWMZufo2layNuPRus+d+7UURk6zmzP2MpQZT2jjlyNjWdjClcw1rTnjHsNM9gr71Cr41555bGVPpu9S0plY502znFAoFU9o6cTUgnpM+McQmq7N+CYrSb+XSRaxcuqhAbZ9W++LYzvWFfu2n1d2YMHo4E0YPL/SYRakZUqVyRT5+b2ahX+tl9unc2Xw6d/ZT2xSkVkqjenVY+/tPRYrh2wXz+HbBvAK3NzExZuaUicycMrFIrydKP3VyPIF7fybq2n7SYsIwsLTHpklPKg96n2i3o9z/+z0s67Slwbxt2fpdn9ea1MhA6s/dilXdfxN2Yec2Z+sTef0gwUdWkBR4G61Gg5lzQyr2n4lNo245Yon1cuX2DyMxsqtEs0WXnvu1F4U6MYbY2xmzZZx6Tslx32FaoTbWDToTc+sEERd3Ytes4LuvRVzOqHtk3bALphWyz/xSKBQ49ZhCvM9VYm6dRJ0Um5W8EUJX5LmlcOS55eUiM1FekKhEFQP/8uAP12ACYlJRKBREJ6tZfTmU/ituEZ2kfqbxl5wMYMqme1wNyJganpim4dLDeCas92KPR0RxXMILd9k/DrVGi0IBHarnfjPR8fFxV7+4Qo2d2b5jdetcz3eoZolCAap0LZf9S8YOH0IIIURBqeKj8Ph6IMGH/yA1IgCFUoE6MZrQE6u59VV/1InRzzR+wO4l3Fs2hfj7GbtraVITife+hNcvE4i4sqc4LuGFi/O+jDZdDQoFVvU65NrGqn7HjLZ3C7dzUWZ768f9/8uyXgdQKNCmq4j3vlyosYUobvLcUnjy3PJykTTVC/Lhfl+8w5OxNtHnxyE16FnbBqVSwXnfWN7Z6cPSM0UrUgbgGZLIFf94Pu7pzISWjpgb6fEoJpV3d/lw3jeOzw760a+eHfp6BV97VxL4hCcD4GBugHUeGdVa5TKK3kUnqYlMVGFnln/F64gEFTHJGb/8a5fLvWiejakB9mYGhCeo8AlPomcd2fpTCCFE6eG77kOSg73RN7OmxqQfsXHpiUKpJNbrPD4r3yFwX84CyAWV6O9JvM8VnEd8jGOXCeiZmJMa+QifVe8S53Uev42fYdesHwq90nWbmRzsA4CBpQP6Zta5tjFxyphFok6IRhUfiYFF/p8mq+IiUCfGPO5fO9c2BuY2GFjYo4oLJynYBxuXnoW/ACGKiTy3FJ48t7xcStf/bqXU/Yhk9nlGArB0WE261/73B7t9NSv+frUufZe7F3n8uJR0ZneqyFsdKmYdq2htxLIRtWj903XCElRc9o/LNqXuWWRO0yuswk7BC41XAeBgbphnGweLf8+FJaQV6JdRaELaE/3zbu9gnvHLKCxBVZBwhRBCiBIhOeQ+kVf3AVBzylJsGnfPOmdVtz11Z/6N+5cFX4ryX+nJcVTsP5uKfd/KOmZkV5FaU5dxfV5rVLFhxHlfzrYU6FlkLi8qrMIuHVLFZuxuYWjtkGebJ8+lxYYVKImSFvvvrhkGTxnbwMoBVVw4qtiwgoQrxHMhzy0Z5LlFPI0kUV6AI4+LB9UqZ5LtF1Gmhk5mtK9mxdkHsTnOFYSBnoIZT/wiylTO3BCXCuZc9o/nXlhysf0ysjPVJ1WtKVK/wkhWZeweYfyULdKe3D4tMa1gMSU90c5Y/2lj6z0eN71A4wohhBAlQdTNI0DGrIknEyiZzKo0xKpee2Jvny3S+Ao9Ayr2nZHjuKFVOcyruRDvfZnkoHvFlkTRt7BDoyr8Q5B+ARIcT0pPzfgkWWmQ9y5ZT277rElJLNC4mtSkf/s/ZWw9I5PHcRRsXCGeB3lu+bdfYchzy8tFkigvwO3QjP88W1a2yLNNK2eLIv8yqmRthLmRXq7nHC0zMp6xKc+2dvFJB95sXGxjCSGEEKJ4JQVkbIVtUbNlnm0sarYqchLFyL4SeibmuZ4ztHYEQJ1UtHua3DRecKDYxhJCPJ08twiRPyks+wJEJT2e3vWUKVjlnjL1Kz+OFnn3NXqcsVRrtEUeX1cyM6opqrwztclPnDMzLNiPs+kT7VKekpnOzCibGeb+i14IIYQoiVQJGZ8kP23piKFVuSKPn5koyY3SwAggo0BrKZM5E0SjSsmzjSYtOet7pbFZgcZVGv27m8bTxs6cCaNnVLBxhXge5LmlaOS55eUiSRRRYpV//Ms77Im1gP8V/sS6v/IF/IX+ZLuw+LzXDWaOXf4pv+yFEEIIUTYYWJUHIC0m75okqtjwrO8NH7fPz5PtVE8bOy68UOMKIUoOeW55uchynhfA1vTxP6qn/uDn/Q+upOm33J2guMLHW8HSsFBT6mo+rkAdlqDKc89z78eVsG1N9bEtQHEmAPvHVbNjktV4hyfTuaZ1jjYxyWrCE1XZ4hBCCCFKAwNzW+DpD+xpTyQDSjr3L/uRFhVU6H6GthUKtRTIxKkmAKq4MNRJseib5qzJkBzsDYC+uS0GFrYFGtfA0h59M2vUiTEkB3tj3bBzjjbqxJisJEpmHELogjy3ZJDnFvE0MhPlBahfPmMaZ+Ze6Lm58pRzJU1kkprwBFWhvyILuad8K2dL9JUKtFo455v7usuzD2IACl18ql1Vy8f9cx/33INYtNqM4letnPNeEyrE81arRRcMHWtx+nzBd5jIz+nzlzB0rEWtFl2KbUwhRMlhWrk+APH3r+bZJt7nyosK55mp4yMzdq0p5Jc6PrJQr2NZq1XGtsxaLbG3z+XaJuZxHZnCFs21rJPRPvZO7nVoYu+cA60WhZ4BFrVaFWpsIYqTPLfIc4vIn8xEeQF61rXlq6P+3AtP5qR3NF1rZa907RmSyLkiFmfShcJs9/UsrE306VzTiuP3Ylh5MZh+9WxRKP7dM94nPJnTPhnv25BGhavAP7iRPQfuRHHKJwaf8ORsWVutVsvKi8EAdK1pjaWx/DMRQpfOX7rKj7+v5NLVG8TGx1O5ghMDe/dg/tvTsLWxLpbX0Gg0dBrwCpevuwHwyfuz+HTu7Dzbn3G9xK9//cPFKzeIjo2lnJ0tndq15r23puDSoF6uffz8A6ndqmu+sQR5XsLermCfcAuRG9smPfHf+hXJQfeIvnUSm0bZf+4SAzwzHtpLicJsU/ws9M2ssWrQmRj34wQfW4lt837Z7juSg32I9TwNgF3rIYUa2771YKKuHyDG4xTJwT7ZZptotVqCj60EwLpRV/RNLZ/9YoQoInluKRp5bnm5yEyUF6CmvQn96mfcEM/a4cORu1FoHhdMuuAXy+sb72KRR5Xql937XSqjp4RLD+P5cJ8vcY+rdXuGJDJ5013UGi0uFczoUzfnA8c7O32o+NkFRvztmeNcv3q2NHQyQ63RMnnTXTxDMrYTjEtR8+E+Xy77x6OvVPB+18rP9wKFyEf1qs7UrlkdU5O8t8UsLFMTY2rXrE71qs7FNubzsnz1eroPHcveQ8eIiIrGyNAQH9+H/PTHSlp0H8jDgEfF8jp/rd2UlUDJz5eLf6XHsHHsPnCU8MgozExNCQ4NZ+P2PbTvO5wtu/bnO0b5cvZ5fimV8l+zeDYmjjWxbd4PAJ+/ZhF18whaTUZBwti7F7j76+vomcinlbmpPPh9UOoR730J33Ufok6KAzIST3eXTUabrsasqgu2Tfvk6Ouz8h0uTK6I56IROc7ZNuuHmXNDtOlq7i6bTGJAxr2JOikO33UfEu99GYWePpUHvf98L1CIfMhzS9HJc8vLQ1JVL8h3A6pzNyyJ+xEpTNpwF2MDJUpFxt7fVW2Nmd2pEl8eeYihniL/wV4iLhXN+bJvNT454Mvaq6GsvxaKmaEe8akZFaidLA1Z/krtbJneglAqFfz5Sm2G/e2JT0QyvX53x8JIj8S0dDRaUCrg6/7VaOgkFfKFbh3etqbYx2zZzAWPc4eLfdzidu3mLd75+Es0Gg1Txo/im0/mYW1lyU2P24x98x287/syesosXA9tL/TvgCeFhUey4NsfqVKpIimpqYSGR+TZduf+w3y5eCkAUye8yucfvIudrQ3RMbF8teRXfl3xD5PfnkfjBnWpW6tGnuME3LpQ5HiFKIjq478j6dFdUkLuc/fXSSgNjUGhRJOahLFDVSr1n83DrV+i0JcihE8yr+pCtTFf4rv+E0JPrSX09Hr0jM1IT85YvmBo40Tt6csL/TtHoVRS+60/8fx+GMnBPrgv7IWeiQXpKYmg1YBCSbWxX2NWpeHzuCwhCkWeW4pGnlteHvJx1wtiZ2bAvjca8WY7JypZG6HRaLEx0ef11o7se6Mh+sqMf0wyBSunia0c2T6pAb3q2GBjqk9auoaqtkZMbevE0emNqWxTtE/oq9gac3R6Y6a2daKqrRFp6RpsTPXpXdeGHa83YFwLqY4vhC598cMvpKen065Vc5Yt+hJrq4wp7k0a1mfrqmXo6elxze0Wuw8efabXmf/5d0THxPLDFx9hbGT01LZfLv4VgPatW/C/RV9gZ5sxzdnG2oolX35C907tSE1N4/NFvzxTTEI8KwMLOxp9vA+nXm9iZFcJrUaDvpkNjt1fp+HH+zJqf4AsHcmFY9eJNJi/HZsmvdA3t0GjSsPIoSpOvabSeOFRjO2L9mmvcbkqNF54FKdeUzFyqIpGlYa+uQ02TXrTYP4OynceV8xXIkTRyHNL0clzy8tBodVqS99G3I9dv36d5s2bc+jNRjSqYK7rcJ7J2zt82OYWzrudKzGnm0zFEoV3KyiBPstvce3aNZo1ezHrP0uCzN8Dl47somnjBroOJ09x8fF88+Myduw7THBYGOXt7enfqxsL5sziwNGTTHnnAzq1bcWxneuz9avVogsPAx9xdPs6OrdvnXV8zabt2frsOnCEpX/+jbunFxqNliaN6jFv1jT6dM+5C8Tp85foOXwcVSpVxPvqqed96UUSHRNLxYZtUKvVbFyxlOED++ZoM3jsFA4eP82wAX3Y9NevRXqdzPeiV9eO7Nu4Kuv9zq0mSnBoGFVc2gOw4c+ljBiUM6YDR08yZPxUjIwMCfK8hIX5v/83PVkTJS3Eu0jxlhQ33D1p3WvIS/v7ptGnhzCv0kjX4TwTn5VvE+66jUoD36XykDm6DkeUQgkPb3Hriz4v3e+B56G0PdPIc4vIT1l/LpGZKCXAo5hUDtzJqCDfsUbhqjULIUq+iMgoOvQbyY+/r8QvIBClUklkdAy//72O9n2HExkd80zjf/HDUl55fQYXrtwAICExkXMXrzJ43Bts3V3w7T1LkvOXr6JWq1EoFHTrmPsuGN06ZSQ0TrsWrehkWloaMz/4FENDA378akG+7QMe/bvFaq0aVXNtU7tmdQBSU9M4f+lakeIS4nlLjXxE5LWM3w1W9TvqOBohRGkizy1CSBLlhfGPTmHu7vtcC4gnWZWxLk6VruGEdzSv/ONJUpoGlwpmtK4i02qFKGtmfbAQL+/72NpYs23170TfdyP6gRtHtq1FnZ7Otz//VuSx3Tzv8N0vv/PNJ3MJu3uVCO8b+Fw9TdcObdFqtby/4CvU6sJt01cSeN27D4CjQzlsrHO/ScusORIZFU14ROG2MgX48feV3PV+wDvTJlO7RrVC9dWka3I9np6envX9nXs+efbv2H8kdjWbYFm1IXVbd+ONdz7ghnvOYnJCFFVKuD/3V88l/v410tOSAdCoVUTfOoHn4lfQpCZhVtUFy9qt8xlJCPGykecWIZ5OFrK9IGlqLRuuh7HhehgA1iZ6JKZpUKVnrKZytDBg6bBaugxRCPEc3Lvvy/a9BwH4+9cf6NujS9a5Lh3asG3177TtPazI48fGxfPBO9OZM3Nq1jHnShVY8/uP1GzRmZCwcM5fupZtKdCzyFzuUliFXToUEhYOgGP5cnm2efJcSHgE5ewLvmWg78MAvv35NypXdOLDt6cXqE/lihWyvr/j7ZPr8jEv7/v/xhQanudYl67dxNrKkjSVigcPA3jwMIC1W3by2by3+fCdtwp8HULkRatOI+zsBsLObgBAz9QaTWoi2nQVAAbWjtSaslSXIQohSih5bhHi6SSJ8oJUsDJkQa8qnPSJwTcymchEFYZ6Cmram9C9tg1vtnXC1sxA12EKIYrZ3kPHgIxZE08mUDI1bdSArh3acPyMa5HGNzAwYO4TCZRM5cvZ06JJY85fusrtu97FlkSxt7MlJTW1SP0KIzEp45NzE+O8C7CZmpj82z4xqVDjv/vxFyQnp7Bo4YeYmZkWqI9TeQca1K2Np9c9li5fzavDBuWosP/jb39lfR+fmJDtnLGxEdMnjWPU0AG4NKiHmZkpGo2Gi1dv8Mk3izl38SqfffcTlSo4Mf6VoYW6HiH+y9C2AlVGLiDG4yTJob6o4iNR6Bti4lQTm8bdcer1JgYWhft3KYR4OchzixBPJ0mUF8TUUI9p7SswrX2F/BsLIcoM99teALRr1TzPNu1atShyEqVK5YrZipc+qYJjRqX2mLi4Io2dmwuHdxTbWLqyc/9hDhw7RfdO7XItWPs089+exoTp73Hd3YNX35jNwvnvUKOqM34Bj/hy8VIuXLmOgYEBKpUqR4LF0aEcv3z7WbZjSqWSdq2ac3jrGnqNmMD5S1dZ8M0Sxo4YjFIpK25F0ekZmVKhzzQq9Jmm61CEEKWMPLcI8XRyhyaEEM9RZFQ0kPEAnRdHB/sij1+hvEOe54yNDAFQqUpfTRQz04xZJskpKXm2SUpO/rd9AWeTJCQm8v6CrzAwMOCnrz8tdFyjhw5k7qw3Adix7xCNO/bBrHJ9GrTryaYde3nt1RG4NKgHgJVlwdeKGxgYsHDeOwAEhYRKfRQhhBBCiBJKZqIIIYQocTKTTk+rKxIaFpH1vdNTklRPWrLsLwKDQpg5ZQKVKjiSkJiY7bxWm7HeO02lIiExEaVCiampSbY2X388h95dO/LXus3cuOVJSnIqNapVYeKrw3l12CBqtegCQK3qVQsUU6aWTRtnfe/rH0jzJqV7C10hhBBCiLJIkihCCPEc2dnaAP8WSs1NyBPJgJKube9hBAYFF7pfpQpOhVoKVLd2xs47IWHhxMTGYW2Vc1aHl3fG7jf2tjYFrrni/7go7v/+WsP//lqTZ7tFS/9g0dI/8iyI26ldazq1y1lnJio6Bv/HWyG3bOpSoJiEEEIIIUTpIUkUkaXiZxcAuPhOUyrb5F3MUQhRcI3r12Xj9j1cuHI9zzYXrlx7gRE9m4jIKELDC5/0MTYyKlT79q1aoK+vj1qt5sRZV4YN6JOjzYnHdWQ6t29T6Hiel62796PVamlYrw4N69UuVN8rN9yzvq9auWJxhyZEiXRhcsbPetPvL2JsX1nH0QghygJ5phHPmyRRhMhDVKKK835xuD9K4GZQAreCEolPTQfg0edtn9rXOzyJA7ejuOAXh1dYEtFJaswMldQsZ0K/enZMbFkeE0O9F3EZQscG9O7Oh18u4s49Hw6fOEPvbp2ynXfzvMOJsxd0FF3hFWab4mdhY21Fry4dOHDsFP/76x+G9u+drVCrl/d9jpw6B8CooQMKPO7KpYtYuXRRnuczt3D+5P1ZfDp3dqFiDgoJ5asl/wNgzsw3cpzXarU5is1mUqvVfPHDL0DGUqbctk8WQpR9qvgo4rzOk+DnToLfTRIf3iI9OR6Atiufvr185PWDxHldIMHvJmnRwajio1AoFBjZVcSybnuceryOiWPNF3EZQogSLjQ+jc6/3sx6ttn6Wn3aVbPScVSlhxSWFSIP290jmLblHr+dD8LVNy7rl0x+LvjF0uV/biw6EcDZB7FEJKowM1QSl5rOtYAEvjzykF5/uPMotvDbxIrSp07N6gzt3xuA12bOYd+R42g0GgDOuF5ixMTpWFrkvrvOy27BnNno6elx7uJVZs3/jNi4jAcJN887jHz9LdRqNc1dGjG4b88cfSfPnoehYy16DB1brDGFhkfw8deLueHuSerjrZ5TUlLZvvcgXQaOJjQ8ggG9uzNm+OAcfXsOG8cPvy7n9l3vrJ+BzC2O+77yGmcvXgHgiw/eRU9PkqxCvIwiLm7n3h/TCDr0G3FerlkJlIJ4uPUrQo6vJOH+NdKig1EaGKFRp5Ec7EPoyX9w+6wn4Re2P8fohRClxcJDfgV+thE5yUwUIfKgAJwsDXGpYEbjCuYY6Cn4+qh/vv1U6VoM9BQMbGDHcJdytHa2wMRQj8TUdLa7h/PVkYc8iEzhjU132T+1UZ6fTIuy43/ff47nXW/u+Txg2IRpmJgYo1QoSUxKoma1Knzw9nQ++OJ7jB7vpiMyNG/SiJ+/XsDbH33Bn2s28te6zZibmRIXnwBApQqObFyx9IX+G0pOTuGHX5fzw6/LUSgUWFtZEhsXn5UUGdC7OxuW/5Jr34cBj/j468V8/PViDAwMsLQwJyExkdTU6RgucAABAABJREFUNAD09PT4dO5sXhsz8oVdjxCipFFgaOOEWVUXzKs2RqFngP+2rwvU077VYIwdqmJZqxWGthVR6hug1aST8OAGD7d+RbzPFe6vnoN59aaYlK/+nK9DCFFSnbkfwx6PSJpWNOfGowRdh1MqSRJFiDxMau3IlLZOWX++/DCuQP1q2JtwdlaTHGswzYz0mNDSEVNDPd7e4YNbUCIX/OJk6txLoJy9HecPbOObH5exY98hgsPCKFfOltdeHc6CObNZv20XULgtcV8Wb742lob16rDkt7+4dPUGcQkJ1KjqzMDePfjgnenY2li/0HjK2dmyYM5sTp5zxefBQyKjY3Cwt6OZS0Mmjh6eNesoN98smMeJs65cueFGSGg40bFxGBkaUqNqFTq2acnU18bQqF6dF3g1QoiSxrH7JJx6Tsn6c5z35QL3dR46L8cxhVIPi5otqPv2Gq7NaYEmNZGIS7upPOjdYolXCFG6pKo1fLTfF1NDJQt6V2HYKk9dh1QqSRLlsVS1htWXQ9jrEYlPRDIpag02JvqUtzCkXTVLXmniQN3yptnaH/KK4tjdaG6HJBIcl0aqWoOjpRGdaljxVvsKuRYyCohOoc3PN4CMuhrXAuL55Uwg1wMTUKVraVzBjHndKtPSOeNhKiZZzbKzj9h/O5KQ+DQczA0Z1bQcMztWxEBP+dSxLz2M439nH3HjUQIpKg11HEx4rZUTI5sUbCvQ/wpPSGO5azDH70UTEJOKQgFVbY3pV8+ON9o6YW6Uc/p5fIqaPy8Ec8grCr+oFNTpWmzNDKhgaUjH6la82syhxBZ80lMW7dPtilZPL6A5uKEdc3ffJy1dy63gREmivCSsLC34fuEHfL/wgxznbrjfBjKW/vxXXjVIJowezoTRw5/6mnnV/+jcvjVpId4FiLpkaN+6Be1btyhUn/xqn+Qlv5ovZmamLJgziwVzZhV67JGD+zFycL9C9xNll0aVSsiJ1URe2UtyiA+atBT0zW0wtC6PZZ12OLR/BdNKdbO1j7pxiGi3YyQG3CYtOhiNKhUjG0es6neiQt+3ci3O+n/27jwsyuoL4Ph3ZtiGfQdBcd/3fV+zNNPStLTSstV2rX6273u271mpZVmWZWlpWpm5ryhuKILs+w4DDLP//hhAiQEBwQE5n+fheeR973vnzgCvc8/ce05pdhKHH7MmYB6+LAXNmXCSf3+fothDWIwG3Nr1oc30R/HsPBgAY3E+KRs/Jid8A/q8dJy8AwkYOZvQKfejdHCsse/C0/tI2fgRRXGHMetLUYd2pdWE+QSMqN8KK31BFml/LiXv6BZ02UmgUOAS2A6/gVNoNfFOVOqq2yGNWg1pf35O7uFNlGbGYzEZcfTwxcknBK8eowkcfUOTTWKrUDbOVj4HV0/UQe0pTjyOoSCjUR5DNA0ypzm/ljanOddHO1KIyynliYlhhHjKCuj6kiAKYDCZmfN1JPsTrftOlQrwdFGRXWwgs8jAsbRiHJQKnry8bcU1288UcO+a6HPaO2CyQHxuKfG5paw7ls2qed3p39qj2sfdfCqXBT+exmi24O6kokhnYndcIbO/juS7eT3o5K/muq9OcDpLi5uTEpMZkvJ1vLU1mZQCPW9d07Havn87kcN9P53GZAYvFxV6k5mIlGIW/RLDoWQNr02t2zLOPfEF3P59FAWl1r1zLg4KTGaITC8hMr2EX49l88MtPQg+54+xQGvk6i+PE5OtBUClBA9nFRkaPemFeg4lFxHs6cTNg4PrNJbmzlGlxM1Zhb7EiNlssfdwhJ0lJqfyy4bNAFw2ZoSdRyOEuFjMRgORb89BU77SQKFEpfbEUJiNoSCT4oRjKFQOtJ31ZMU1BZHbiV56b0V7B1dPMJsozYynNDOe7P3r6P7QKjw69K/2cXMPb+b0pwuwmI2oXNwxlRZReGo3kW/NpsfD36Fu1YkTb16HNvU0Smc3sJjQZSeRvO4t9LkpdJz/VrV95xz4jdOf3wdmEypXL8xGPcVxEcQsW4TmzCE6zHutTq9RQdQeoj66HVNJgfUpO7qA2URJUiQlSZFk7/uVHo/8gJPP2fcRxpICjr96Ndo0awl0lCpULh7o8zPQ56VTFHsIJ59ggsfdXKexNHeGoly0GbEAOPuH2Xk0orHInOb8WvKcJjZHy8c7U+jg58Jdw1uRodHbe0jNlgRRgF+OZbM/UYOfmwPvTO/EuI7eOKgUGExmkvJ1/BGZi7e68kvl7qzkzuGtmNrTj96t3HB2UGI2W4jKKuH1v5P4+3QeD66NYdv9/VBWs6Jh0S8xzO4fyGMT2uDr5khKgY4Hfo5mX4KGFzbHV0QH19/Ri4FtPCg1mFm+L41X/krk+0OZ3Do0mJ7Bbjb7fnT9GcZ38uHVq9oT6u2MptTIJ7tS+WB7CisPZDC0rSfTe/vX6vVJzCvl1u+iKNKbuGNYK+4YFkxrb2fMFjiaWsQzf8RzOLmIB9dG8+P8sxUllu1NIyZbSztfF96Z3pHBbTxQKhXojGbickpZfzybQPeWFwGNKqvWA9D1nE8CxKUrLiGJNz74jFtvnEWfHt1Rq10wGAxs2b6bh556keKSEgb27c2oYYPtPVQhxEWSve8XNNH7cfDwo9Ot7+DdaxwKlQNmowFdThK54X/g4OZd6RqlizutLr8Tv0FTcWvbG6WjMxazmZLUKJLWvk7ekb+J+fJB+r28DYXSdu2AmGWLCBw1mzYzHsPRwxddbgrRnz+AJnof8T+8gJNvCAC9nlyPR8eBmA2lpP29nMSfXiFzx/cEX3Yrbm1sV4868/Wj+PQeT/ubXsXZLxSjVkPqH5+QsuEDMv5diWeXofgPnV6r16c0K5GoD2/FVFpEq8vvIHjiHTj7tQaLmaL4o8R//wxFsYeJ/vJBei7+seK6tL+WoU2LwSWwHR1vfQePToNRKJWYDTpKM+LIPrAeJ8/AWo2hubNYLBiLcimKP0LSL0sw60pQubjXe1WQaPpkTlOzlj6neWpDHDqjhZentMfJQerLXAgJogCHk60JdRYMD2FiF5+K444qJR381Nw3OrTKNcPbeTG8XeVtGEqlgu5BbnwxuwuTlx4lKlPLrvhCRnewvV2jb4g7b0w7Gz0N9XLmo5mdGfLuIY6mFnMyo4TtD/QjrGxpmIujkntHhbLtTAE7YwvYdDK32htOqJczX87pUrE8zsPFgccuCyOn2MCq8Eze3ppU6xvOki1JaHQmFk9ow6KxrSuOqxTQv7UH387tzmUfR7ArrpDDyZqKSHV5oqJHL2vD0LZncz04OyjpFuRKt6C6fxIya8UJ9sTXLjfJf52vLPHF8tbWJABCvJwYJVt5WgSdXs/yVT+yfJX1jb6PtxdFxSUYDAYAQoKDWPHRm/YcohDiIiuKtS5VD7liAT59J1YcVzo4og7qQOiU+6pc49V1OF5dK/9fplAqcWvdnS73fsHRFyajTY2i8NQuvHqMtvm47u370uHmNyq+d/YNpfNdH3Ho0SEUJxylJPkk/V7ZjkuA9f9opaMLoVfeS8GJbRSc3EnuoU3VBlGc/ULpcu+XFVt+HNQehF37GIaiHDK3rSJp3du1DqIk/bIEk1ZDm+mLaT1t0TlPWIVHh/50X/QtEc9eRuGpXWhiD1esvimKs76ubWY8imeXoRWXKR2dcW3djbBztkfV1oklsyiMql8p+vOVJW4MGdu/I/brxVWOO/u1pvOCT3Dyqt8WCNH0yZymZi15TrPueDbbzxQwpbsvYzt51+txxVkSgsK6HAsgo6hhljQ5OSgZVXaTOZRUfWm6e0eFVDkW4uVMe1/rDWZaT7+Km825yifeUZkl1fZ914hWVfYXAtxfdvOMzSnlZEZxDc/CSqs38XtkDo4qBbcPtb1EzVvtwPjO1hv1ztizN4Py/YSZGsN5H6e2vNUOBLg71uurKfgxIpONkbkAPDupnUSBW4g2Ia14/dnHmDB6BGGhIWhLS3F2cqJX9648+uDdHNyynm6dq1/KKoS49KjU1jfn+gbKT6F0cMKrxygANLGHqm0XMvneKsecfUNwCWwPgN/gaRUBlHN5dbf2XZISVW3fra64q0rOFIDQK+8HoDQjluLkkzU8CyuTTkvOwd9RqBwJnni7zTYObt749B4PQOHJnRXHVS7WHCmGgszzPk5tObh54+gZUK8ve1A6qXH0DMDBww/Kqpc5+QTTbs4LuHcYYJcxiYtD5jTVa8lzGk2pkRc2xaN2VPL85HYN9hxaMlmJAozr5M3HO1NZvi+dvBIjM/r4MyTM02ZSoXNlFxlYti+Nf2Pyic8tpUhn4r8pLjJruIl1DbS9lcPfzZHYnNIazlt/bIWl1df2Ht7WdpWPMB8XQr2cSCnQczythO5BtqO+5Y6mFWMwWVApYfSHEdW2K9Zbx5JaqKs4Nq6TN+uP5/DqXwnE5Wi5qqcfA1q7o3asf9K0L+c038oVB5M0PPF7HABzBwUxraefnUckLhY3N1cevvcOHr73jvM3FkK0CN69xpH6x8ekb1mOsSgP/2Ez8Ow0xGai1HMZCrNJ+3sZ+cf/pTQzHlNpEVjMldroawgguIba/n/U0dOf0ozYas87eFo/6TVpq//k1LOr7U9HXQLCcPINRZ+bQknicdxad6+2D4DihKNYTAZQqoh40vaKGgCTzjpx0uWmVhzz7jWOnAPrSfjpVbQZcfgNugr3DgNQOalrfMyadL3vy3pfaw8Bw2YQMGwGACa9Fs3p/ST89DJRH9+O78Cr6HzXRygdmv7WA1F3MqepXkue0yz5J4kMjYFHJ7Qh1LvmAhiidiSIAoxo78XD41rz/vZk1h7NZu3RbJQK6BHsxhVdfZg3KIhAj8r/2ZzMKOb6ryLJLcttAdbETc5lKwuK9SZK9GZK9JXf2JwryMP2f2DlVWGqizSW70c01pCUtLq+y8+lFOjJKT5/NLU84ZDJDFlF52+vNZx9vtf3C+BAoobvD2Xy9YEMvj6QgYNSQb9Qd67s7suNAwPxdGkZv4InM4q5ZdVJSg1mLu/qwytT2tt7SEIIIezIq9sIWl/9MMm/v0/23rVk710LCiVubXrg0+8KgsbNw8mrcu6O4uSTRL55Pcai3IpjKrUnSkfrm2KTrhizrgSzrvpPdZ28g2weL68KU93qCYXC+v7GYjLaPF9T3+Xn9LkpGDQ51bYpV7E6x2zCUJh13vZmvbbi3wEjr0cTc4DMHd+TsfVrMrZ+jULlgHv7fvj2v5LAMTdaE/K2EConNd69xuLRaRBHnptIbvgG0v8eQMjku+09NNEIZE5TvZY6pzmWWsTXB9Jp5+vC3SOrrhgS9dM0f9p28Mj4NszsG8C6Y9nsTSjkYJKG42nFHE8rZunuVJbf0K1iORvAI7+eIbfESPcgV56f3I6BbSpHI5dsSeT97Sk099orlrInEOzpRPgjA+t0rUKh4K1rOnLb0GB+P5HD3oRCIlKKOJik4WCShs92p7L65h6VyqxdimJztNyw8iT5WhPD23ny2XVdcFDVr3yyEEKIS0ebax4hYPhMsvevozBqL5ozBylOPE5x4nFSNy+l2wPLK7bRAJxZ8QjGolxcW3en3Zznce84sNIKi8RflpDy+/tn//NursomVE4+wQx8K7xOlyoUCjrOf4vgy24j5+DvFEbtpSguAk3MQTQxB0nd/Bk9HlldqXR0S6BycSNgxHUkr3+bzF0/ShDlEiZzGtta6pzm+U3xmMzwxMQwjCYLRtPZVT/nBopKjWaKdSYcVIqKAJqongRRztHO14WFY1uzEGuJsJ2xBbz6dyKR6SUs/CWG/Q8NQKVUkJyv40iqdQnpihu62qwJnl2LiGhjytDoq61VXh6J9XM7/546/7LIcU6xAZ3RXK8/qh7BbvQoSxalNZj4+3Q+r/yZQFK+jsXrz/Dbnb1r3dcdq6M4WMOezJpELB5Ur+suREq+jtlfR5JVZKB/qDtf3dgNF0e5MQkhhLByCWxH66kLYepCzEYDBSd3kvjzq5QkRRKzbCEDluxHoVShy06mOP4IAF0fWIGLf5sqfRk02Rd7+JXo8zNsjqv8HICjx/m3sjp6WbcOGQpzMBt0FStt6sKtTQ/c2vQArFta8o/8TcJPr6DLTuLM14vp/dRvte4r6uM70MQcrPMYAAa9G1Gv6xpD+UohXXaCnUciGpvMaapqqXOa5ALra7Tgx9M1tpv37SkArusXwHszOtVrXC2JBFGq4ahSMr6zD+391Ix8/zDphXric0vp6K8mrdD6y+jj6lDtH3V9sy03lL0JGptjS8orJaXsj6lXq/NHS/uGuOOgVGAwWdgRW1Ap03d9qB1VTOvph7fagTlfRxKRUoTWYKr1nsJ8rbFWS/CagqwiPbNXRpJaoKd7kCvfzO123j2pQjRHTsGdATi9fyvtwlqfp7UQojpKB0d8eo9HHdSew0+MRJ+XTmlmPOrgjujz0wBwcPepNlBReKp+FWQaiub0XptjK81OQp9rrVLjGtbrvP24t+2LQuWAxWSgIHJHpepF9aFyUuM3eBoObt5Evj2HorgITHptrfOkGIvza7WtqKnT5VirAyqda84dIS4tMqexkjmNaEgSRAH0RnO1VVJczjmuM1qXPJVnvs7XGskpNlSJfv58JIvYnNJGGm3tfL4nlem9/apks/5klzX5Wkd/l/MmYAJrNuoru/vy24kcXv87kZHtPFE72b45aA0mlIqzS8Bq87qaLWA0WaCWiaZ/utV2WcWmJl9r5IaVJ4nLKaWDnwvf39wdH9emUSFICNG4EpJS+GXDZv7duYejkafIyMrBxdmJTh3acdXlE7j/jpvx9fGusY9jJ6N488OlbNu1j9z8fIL8/bliwmgeX3gvYa1lT/OlwGzUV5vcU+l4dsJgNliTG6pcrNV8jMX5GDQ5VVZ0ZO35mdKM2EYabe2k/vk5fkOmV6nQk/rHJwC4BHc8b1JZAJXaHd8BV5Jz4DcS176OZ7eRqJxtBzxMei0KhbJitUqNr6tT2etqMdeY2+W/ej76U63b2ovFZEShqv5tvaEoj8xdawDw7DzkYg1LXGQyp6leS53T7Huo+opcSXmlDHvPWhZ+zfwejGhvu4S1qEr2FQALf4nhkV9j2H4mn2Ld2X1iMdlaHv41BrDunyvPLN0lQE2QhyMWC9z/czTJ+dY3OFq9ia/2p7N4/Rm81faNTyXn61jw42lSCqxjK9KZeOufJFYesC6nfXic7U+xbHny8jC81SpOZpRw7YoT7IwtwFS2X9lsthCVWcJ725IZ+f5hMjVnM3fPWRnJs3/EsT+hkNJz9twdSy3i6Y3WKjUDWrvj0UQTMZnNFnKLDRVfhef8blQ6Xlr5jViJ3sTNq05yMqOENt7OrL6lBwHukgVfiJYgPjGZLkPG8+jzr7Hx739JTk3HVe1CcYmWw0dP8PLbH9J/3FVEHI+sto/fNm9hxORrWb32N9Izs3B2ciIxJZUvv/mBQZdNIzzi2EV8RqKxxHy5kJgVj5B/Yjum0rPlObXpMcSseBiw5gQpr5ajDumCo1cQWCxEf34/uuxkwFoOOP2frzjz1WIc3Lwv+vM4ly47mdOfLkBXturEpC0i6de3yPh3JQBtrn641n2FzXwSlas3JcknOfHGtRSc3InFbP1/2GI2U5ISRfJv73H48ZGVqhFFvjWHuO+fpTB6P2bD2clfUcIx4lY9DYB7hwE4lJWYbmosZjMGTW7Fl6nk7CqAc48bSyqvDsjau5aoj+8k7+iWSudMei25EX9y4vUZGPLTQaki9KoHLtrzEReXzGlq1lLnNKLhyU8aazR2/fEcVh/OQqEALxcVpUZLxR+J2lHJezM6VWSYVioVPDupHff/HM32MwUMffcQni4qSvRmjGYLw9t5MqiNBx/uSLHbc1pydUfu++k0f0bl4eWiQqMzYSr7m795cBDTe/vXuq8wHxdW3tSd21dHcTS1mNlfR+KkUuDmrKJIZ8JgOptqSqE4mzBVozOxbG86y/amo1SAp4sDJXoT+rL2vq4OLLm6Q8M84UaQUqCriM7+V+8lZ/dGD2/nWSmavCEyl/CkIgBySwxc9Xn1E567R4RIpmwhLiHlCdumTrqMm2dfy/hRw/Hy9KC0VMdvm7fw0FMvkpaRycxb7ubYjs24ulb+dD05NY2b73kYnU7PtMkT+XjJiwQHBnAmPoFb71/M3oOHuf72+zi+80/UattLr0XzYDboyDmwnqydq0GhQKX2wmIsxay3TvyVTmo63fZeRdUchVJJu9nPEv3F/RREbufQY0NRqT0x60uwmIx4dh2OR6dBpGz40G7PqeMtSzj9+X3kHfkTldoLU6kGygIfQeNuxn/o9Fr35RIQRvdFK4n66HaKE44S+dZsFA5OqFzcMGmLrCWQyyg4+97DVKoh/e9lpP+9DBRKHFw9MelKsBitEyIHd1863LKkYZ5wI9DlpnD4sWE2zx1cdDbfgmfX4ZVXyFgs5B7aSO6hjQCo1B4olCprQKWsBLbKxZ2O89/CvV3fxnsCwq5kTlOzljqnEQ1PgihYsxUPauPBztgC4nNLySgygMVCBz8XRnfwYsGIENr6Vn6zOr23P14uKj7akcLRtGKMZgudA9Rc28efO4e34oPt9rvZAEzr6Uege08+3J7C4ZQinFRKurZSM39IK67rZ7t8YU0GtvFg+wP9+Gp/On9G5XEmW0thqREPZwc6+LkwrK0n03r50fqc2uNvXd2RLafz2B1fSFK+jqwiPSqlgm5+Lkzo7MOCESEVSZ4uJeZzqiIU680U11ASrrwWvRDi0uDv68PBf36jd/eulY67uDhz3TVTCA7057IZN5GUksZP6zdy85yZldot+WApxSUldGjbhlWfvYeLi/We2rFdW35a8Sk9R15OUkoan6/8noULbr1oz0s0vLCZT+DRaRAFJ3dSmhmPoSADiwVcgjrg1WM0IZMW4BLQttI1/kOno3L1ImXjRxQnHMViNqJu1Rn/YdfS6vI7SdnwgZ2ejZXf4Gn09AokZcOHFMUdRunghDq0K60mzCdgxHV17s+j40D6vbKd9K1fkRfxJ9q0MxhLCnFQe+AS1AHPLsPwGzwNZ/+zuZg6zn+LvCNbKIzajS47CX1BFgqlCpfQbvj0nkDIpAU4etZ+0tVc+PSdSId5r1NwcifFyScxFGZjKi3CwdUTdatOePUYQ9CYm3DyCbb3UEUjkjnN+cmcRjQEhcXSfOvgHTp0iIEDB7JpQW96h7jbezh2d+6+tpQXhtt5NOJiO5ZaxOSlxwgPD2fAgOr3P15qyu8D+/78lf59Ln7OHJ1Ox6crVrFm3QaiYmLRlurw8/GmVXAg40YMY97sa+nVvUul9uv++JsNf/3D0ROnSElLp1Sno3WrYC4bM5JH7rvTZnLW8m0iAPr0aPaFH+a1dz9h36Ej6PV6BvbtzfOPLWLEEGvZvrz8ApZ8uJRfft9ESnoGrQIDuXnOtTz24N04OjrW2PfOvQdY8sFSDkQcRastpUfXztxz21zmXT/D5mtwvsSyGVnZvPvpMv74+18SklKsJUjbhzHjqkk8eNd8PNyr3r8LNRre+2wF6zf9xZm4RAxGAwF+vrQOacWEMSO49Ybrmm0S2y6DxxOflMx9t8/j3VeerThuNptp03s4WTm5vP7sYzx87x1Vrn3w8ef57KtVDOzbmz2b117MYVdy+OgJhl4xvcXeb3o/uwn3trWvwnApK81Oqlg5MXyZfSdb4uIqSjjGsRcnt7j7QGOQOU1lMqdp/i71eYmsRBFCiHoyGAxMvn4+u/ZZt3cplUq8PD3IzM4hPTOLw0dPoHJQ8erTiyuu+XvbLubevaiivbeXJyaTmZi4BGLiEvjh19/Z8P1yBg+ofrn1+k1/c8OdD2I0GvFwd0NTVMy/u/Yy6bqb2bh6BV07deTymXM5eToGdzc3TCYz8UnJvPjmBySlpLH0nVer7fun9X8w756HMJlMeHt5otPrORhxlNsffJT94RF8+MYLdXqNtu/ex6xb7yW/wLpH38XFGbPJzNETpzh64hSrf/mNzWtWEhIcVHFNfkEho6deR1S0NUmmSqXC08Od1PRMUtIy2BceQWhwEHfdcmOdxtJU+Pp4E5+UjMlUeZXaiahosnJyAZgwZoTNayeMGcFnX63i0NHjaIqKbAaghBBCCCFE45HEskIIUU/fr/2NXfsOEuDny6/ffE5R4gkyTh1Ek3CcE7v/4pWn/kfHdmGVrvFwd2PhglvZ/vuPFMQdJf3kATQJxwnf+jtTLh9PfkEh8x9YjNlc/Taw2x98lPk3zCTl+F6yow9zJnw7o4YNQqfTs/i517j30WcA2LHhR3LPRJAbE1ERyFnx3RqOnDhZbd/3/O8pJk0YQ8zBbWRGhZNx6gCPL7oHgKVff8fqX36r9esTl5DEtbfcTUGhhgfvms/p/VspiDtGQdwxdm38iSED+hIVHcut9y+udN2HX3xNVHQsndq35Z9fv6M4KZKMUwcpjD/Goa0beOKhewkKrPsS3qYgNy+fE1GnAejZrXOlc6dOnwGs+7C7d+5o8/puZcctFktFkEkIIYQQQlw8shJFCCHq6cChIwAsuvs2plw+vuK4o6MjnTu0Y/EDC6pcM2bEUMaMGFrpmFKppHf3rvy47COGXD6dyKho/t21lwmjba9GGNSvNx8veani+zahrVj5yTt0HDiWQ0ePc+xkFMd3bqZ9W2vGehcXZ/53/138vW0X/+zYzbqNf9G3p+0yo21CQ1iz/OOKLT+eHh68+PjDZOfk8uU3P/DSWx8yZ8a0Wr0+z73xLoWaIp5/bBFPPnRfxXGVSsXgAX357btl9B93FVt37uHAoSMVq2/KX9fnH3uIUcMGV1zn7OxMr+5dKm2Pqq2JM25i+579db4OrFucGsob73+GTqfH3c2Na6dOrnQuPdNaYcTH2wtnZ2dbl9MqKPBs+6ysBhuXEEIIIYSoHVmJIoQQ9eThYd1KkZ7ZMJNZJycnLivbxrEvPKLado/cd2eVY61DWtGpQzsAZl19ZUUA5VzjR1v3FUdGVR8UWHT3bVVypgAsvt8aEIo+E8exk1HVXl+upETLz79twtHRkfvvuNlmGx9vLyZNGAPAPzv3VBw/+7pm2ryuPnx8vAgK8K/XV0PZunMPH3zxFQBPPXwfAf5+lc4Xl2gBULvYDqAAuJ5TkaeouKTBxiaEEEIIIWpHVqJcQtr4uEjyJSEuoknjx/DWR5/z0ZcrycnLZ86MaYwcOvC8eSoys3L4aNnX/PnPDs7EJ6ApKq6yfSc9o/rATM9utldiBPr7EX0mrsbzAAWFhdX2PWb4EJvH27dtQ1hoCIkpqUQci6xSfea/Dh09jsFgQKVS0XPEFdW2Kw8EJKekVRybNH40a9Zt4MmX3yQmNoFrp05m6MB+F1TSd83yT+p9bUOIjo1n7oJFmEwmJo0fYzNprBDNkYt/G0koK4RoUDKnEU2dBFGEEKKexo4cytOPPMBr733Cdz+t47uf1qFUKunTsxtTr7iMu265geD/5O44djKKSTPnkZ2bV3HMy9MDl7LtG0XFJRSXWL+qc+6WjnOplNbFhcHVrJ4oP28wGKvtOyTYdt8ArYIDSUxJJbss+WlN0sqCQCaTiYys7PO2L9FqK/49b/a17Nofzorv1vDZV6v47KtVODg4MLh/H6658nJunzsbL0+P8/bZVCSnpnHV7FvJysllUL8+fP/lBygUiirt3FzVAGhLddX2VaItrfi3u5trww9WCCGEEELUSLbzCCHEBXh28YMc37WZFx5/iIljR6J2cSHiWCQvv/0hPYZfztZztqkA3LXoCbJz8+jVvSubf1pJQdwxsk4fIunYHpKO7eHBBfMBa+LQ5sxssa6sCW0VhD49+rxfyz5YUnGtQqFg6TuvcvCf33jioXsZNWwQKpWSPQcO8fiLb9Br5BUcP3naXk+tTjKzcrhy9nzik5Lp0bUzv333Je5ubjbbBgdaA1h5+QXodLYDKeduHWsVWH3ASwghhBBCNA5ZiSKEEBeoY7u2PLHoXp5YdC8Gg4F/duzhqVfe5OiJU9z2wGJiDm5DpVKRkJRC+JFjAKz9+jPahbWu0ldWds7FHn4lqemZNscFkJZuzVHi7+d73n6C/K2rYTKzc9HpdNUmSq1Jnx7d6NOjGwBabSkb/trKky8tIT4pmXv+9xQ7NqypdV/X3XYvew8crvMYAJKO7Tl/IxvyCwq56oZbiYqOpUPbNvzx41f4+fpU275bl7OVd07FxNpM/nsq+mwFny6d2tdrXEIIIYQQov4kiCKEEA3I0dGRSRPG0KlDW7oPm0hKWgZn4hPp0rE9qekZAPj5+lQbqNi2u34VZBrKjr0HbI4tPjGZxJRUAPr17nHefgb264WDgwMGg4Et23dXql5UH2q1C7OuvhJfHy8mX3cLBw4fRastrXWelLy8glptK2ooxcUlXH3THRw5fpLQVkFsWrOy2m1Y5Xp27UyAny9ZObn8s323zSDKP9t3AzCwb+/z5t4RQgghhBANT4IojeiHw5k8/OsZhrfz5Kdbe9p7OE3KrBUn2BNfObnl3kX9aeNT/8SRzd2iX2JYE1E5meia+T0Y0d7LTiMS56PX63FycrJ5Tu1y9ne5tGxrRvmkNzcvn6zsnCrVWVb9tI7oM3GNNNraeX/pcubMmFqlQs/bH38BQJdOHc6bVBasz3X6lCv4af1GnnntHcaNHIZrWc6P/9JqS1EqFRWrVWrzuprNZgxGA2pqd8/4+5dVtWrXEHQ6HbNuvYe9Bw8T6O/HpjUrqw2anUupVDLr6il8uuJbPv/6O+69bW6lFTxZ2Tl8v3Y9ALNnTG208YvmLXPnD5xZ8TCeXYfT89Gf7D2cJuXEklkURlVeWdb/jb24+FetZtZSxCxbRNbuyqv6eixeg1e3EXYakWiKZE5TvUt1TvP21iTe+Te50rF3pndkdn/ZSgwSRBF25uGswsXRmppHqaycaNFstrAnoZAjKUUcSS3mSEoRSfnWyej5/ogLS41sOpXL9pgCIlKLSCvQgUJBiKcTI9p7ceewVnQKsD2hawgp+Tre357MvzH5ZBcb8FY7MLK9F/eNCqVbkO1kkJ7OKgLcrRPXnGID5uadEqNFuPWBR3FzVXP99KsYNqh/Ra6LqJhYHn76JcCaE6Rn184A9OjaiVZBgaRlZHLLfY/w6Vuv0LZNKCUlWlb+sJbFz7+Kr483uXn59npKJCSlMOfOB3nvlWdpE9oKTVER73yyjKVffwfA04/cX+u+Xnnqf2zZvotjkaeYMP1GXnv2UcYMH4JKpcJsNnPy9BnW/fEnS7/6jm2//VARaJh8/S30792Ta6dOZmDf3riUlfw9fPQEC598AYChA/vh6dH0ksuaTCbm3vMQW7bvxsfbi40/fkXXTh1qff3iB+5i5Q9rOROfyNx7HuKjN14kKMCf2IREbnvgUfILCmkdEsxdN9/QiM9CiEubSu2B0tE6wVEobacHNOm0pG76lJyDv6HLTkTppMYtrBetJt6OT9/LG3xMZoOOwqg9FMVFUBR/hKK4IxgKrKsXzxfUKIqLIPfwZoriIijNSsCoycFs1OPo6Y9HhwEEjr0J7x5jbF6rUnvi6GlNgG7Q5IDFbLOdEKJmNc1pqnPXD1FsiLQm67+uXwDvzejUKGPLLTHw0Y4UNp/KJa1Qj4ezAwPbuHPPyBAGh3navMbN6ey8JF9rxGCSicm5JIgi7OqFK9tVGwzR6Exc/1Vkvfq94tOjFQEXAFcnJSazhdicUmJzSlkTkckb0zpyXb+AGnqpn8PJGm785iSFpSbAelPN0BhYezSbjZE5LJ3dlYldquZFeHFKe16cYs1xMPTdQyTnV1+hQzQNpToda9Zt4Kvvf0KhUODt5UmpToe2rIKKq1rNsg+WoFKpAOtKgzeef5xb7n2Ev7ftovPgcXh5elBcosVoNDJ2xFCGDR7AG+9/arfn9OlbrzDvnof4ffMWvL08KdQUYTJZf5cX3HIjc2ZMq3Vf7du2Yf2qL5g1/14OHT3OpFk34+TkiIe7O4WaIgwGQ0Xbc6vVFGqK+PCLr/nwi69RKpV4e3lSVFyMXm9t7+/rwydvvdxAz7hh7d4fzrqNfwHW34+rZt9abdvrrpnCOy8/U+lY65BWrPz0HW6860HWbfyL9X/8jaeHOwWFGgC8vTxZs/yTCyr3LERL127OCwSOml3teUNRHifemIk2NQoApbMbJq2GgsgdFETuIHTqQsJmPNqgY9KmRXPy3ZvqdW3Gtm/J3PF9xfcqtQegQJ+bSk5uKjkHfydo/C10mPtqlWvb3/gi7W98EYBDjw5Fl5NcpY0Q4vxqmtPYsjU6ryKA0pgScku5dsUJ0gv1gHVekltiYPOpPP6KyuO1qR2YOyioynV3jwzh7pEhgO3VNi2dBFFEk+bqpKR3Kzf6hLjTN8SNl/9KrLgJ1MRgttAnxI0bBwQxoYs3oV7OmMwWIlKKeGpDHMfSinlkXQzdg1zp1cp2pYz6KNGbuGN1FIWlJga2ceeDazvTzteFTI2ex3+PZfOpPO77KZrtD/QjyMP2dgXRfLz85CMMH9SfrTv3cCYugbTMLCwWC507tuey0SNYdM9tdGgbVumaOTOm4ePlxZIPPuPQ0RMYjSa6d+nEDddOY+GCW3ntPfsFUABmXX0lwYH+vPH+ZxyIOIqzkxM9unbmntvmMu/6GXXub+jA/hzf9SefrviW3zdvISomlvyCQrw8PejcoR2jhg3muqun0LZNaMU1S99+lY1//8v23fuIT0wmPSsLB5UDnbu1Z/JlY3no7tsJDPCr4VHtx3zOEjKttrQioGZLeWDkv6ZNuozdm9ay5IPP2L57Pzl5eYSFhnDFhNE8vvBewlqHNPi4hRBnnVnxMNrUKBw9A+i84BO8uo3ApNeS+scnJK9/h5Tf38e9fT98+13RoI+rcvXCvW1v3Nr1xb1dX04vvQfMpvNe59FxEK6tu+PZZSguQR1ROauxWCzoshJI3vAhWTtXk7H1azw69CdgxHUNOmYhRN2VGsw8vTEOD2cVQR5OxGRrG+VxzGYLd/14mvRCPR38XPj0ui70auVGgdbIK38lsCo8k6c2xNEv1L1B50MtgQRRRJPl6aIi6okhlZbEvbU1qVbXfjKrM0PbVl6eplIqGNjGg+/mdWf8x0fILjbw5d60Bl069/X+dNI1BrxcVCyf0w3/smVwgR5OfDyrM5d9fISEPB0f70ipWHUimq/uXTrRvUsn/nf/XXW6btKEMUyaYHtp9bOLH+TZxQ9WOd4urDX69Oga+z1f3o+b58zk5jkzzzu+UcMGM2rY4PO2K3e+cXl5evD4wnt4fOE9tepvYL/eDOzXG3ig1mNoKsaOHHre16M2enfvyjefvtsAIxJC1EVRXAR5EX8C0OmODyq20aic1LS55hG0GbHk7PuVpF+WNGgQxbV1DwZ/cKLSqjyW1u7awNFzqhxTKBS4BLaj061vU5oZj+b0XjJ3/ShBFCGagA93JBOfq+O5SW35Myqv0YIoG07mcjytGJUSlt/Qlc4B1pQCXmoH3pjWgahMLQeTNLy9NYkVN3ZrlDFcqlpEECUpr5Rh71lLW9aU6CcuR8uoDyJQKGDfQwMI9bLuw08p0PHr0Wx2xhWQkFtKukaPs4OSzgFqpvfyZ+6gIJwcbO+prU7oc3tqHM/uuAKu+yqS1t7O7HtogM0+dscV8NX+dMKTNOSUGHF3VtEvxJ2bhwRxRdfzlyBt6hQKBYrabSms4r8BlHP5ujkyobM3P0ZkcTytuJ6js23dcWt52hl9/CsCKOXUjirmDQri5b8SWX8ih+cnt6v1nkkhhBDNS2l2EocfGwbUnLxUmxFHxJOjQKFgwJJ9OPtaV2XpclPI3vsrBSd3UpqVgD4vHaWjM+qQzvgPnU7Q2LkoHeq2onHP7aE1jqfg1G4i37wOZ7/WDFiyz2YfBad2k/7PV2jOhGPU5KBSu+Perh9B429u8JUZ9pC9fx0A6pCuePesGuwOufxOcvb9SknySUpSonANPX+i7dqoLjdLQ3Bv2xvN6b0YCjIb7THExSFzmubvTLaWT3el0jVQzW1DW/FnVF6jPdb6Y9aqhOM6eVcEUMopFAruGN6Kg0katsbkU6A14qVuEaGBBtF4d+wmpI2PCwNaW6tirC+b5Nry6zHruSFhHhU3G4DnN8Xz6t+JbD9TQIZGj9pRSWGpifCkIp75I54bvzmJ3njxEnFZLBZe2BTPdV9FsiEyl3SNARcHJXklRrbG5HPrd1E8s9G+FT6aOh9X603C1IDZWzWlRo6VBWVGd/C22WZ0R+vxrCIDp7MaJ+oshBDC/lz82+DewTphyNm/vtp2Oft/BcCj05CKAApA/OrnSfz5VQoit6PPz0DppMakLaToTDjx3z3DyXduxGw8//bWhmKxWIj/4QUi37yO3PANGPLTUTq5YCzKI//4VqI+vJW47545f0dNXHn1Hq8eo2yed2vXF5WrtWpewandF21c9WWxWNDEHgLA2T/sPK1FUydzmubvyQ1x6IwWXp7SHgdV436Yurssj0l185JR7T1RKMBgsrA/0fYWY2Fbiwk3XdPLn0PJRaw7ns19o0NttvnthDVad3Uv/0rHuwSoGXlVe8Z38ibMxxmFQoHWYOLv0/k8vymePfGFfLIrlUVjz1/CsiF8vieNz/ek0crTiccnhjG5my/uziqKdSZ+PZbNS38msHxfOn1D3ZnVt+ETp14K9pbdVLoG2q6UUx/nLsXrXE3ln07+Z49HZ2urrdQjhBCi+fMfcg1FsYfI3r+O0Cn32WyTvf+3srZXVzquDulC+24j8e49Hmf/MBQKBSa9lvwjfxP/w/MURu0h9Y9PaD1tUWM/DQDS/vyctD8/x8mnFWHXPo5v/8mo1O6YSovJ3vcrCWteIn3Lctzb9SVgxKyLMqaGZrFY0KbFAOAa0sVmG4VCgTq4A0Wxh9GmXfjWvcZi1GooTT9D6ubPKDoTDkDwhPn2HZRoEDKnab5+OZrFztgCpvf2Y0R7r0Z9rOwiA/laI2D9udvi4+qIv5sjWUUGYrJKuLxr1cIXwrYWE0SZ1suPFzbHcyK9hJhsbaXJLMDJjGKiMrU4KBVM61k5YeHiCVUj92pHFdN6+hHs4cT0Zcf59mDGRbnhFGiNvLU1CVcnJatv7lGpTK+bs4qbBgXh4aLinjXRfLQjpU43HFv1wGtrzfwejX4zaCh/ReVxJNW6YuT6/g13Q84sOltppLqksS6OSrxcVBSUmsjSXLxPEIUQQlx8foOnEf/DC5QknUCbHoM6uHIOruLkk2hTo1CoHPAbXLnyVdj0xVX6Uzmp8Rs8DSefYI6/Np2Mbd9elCCKsaSApHVvoXR2pccjq1G3Ovs8VC5uBI29CZWrB9Gf3UPKxo/qFERJWvc2yevfqde4zlf6t65MWg1mvfUDEUev6qtsOHpZK1kYCrIa7LEbQsXWsP9QubjT9vpn8OlzmR1GJRqazGnOrynOaQpLjby4OQE3JyXPXNGuwfv/r4yis/OMQA/HatsFuluDKOfOY8T5tZggSpCHE8PaebI7rpD1x7J5eHzlvcDrypa9jWzviZ9b9b9o/zU4zAMvFxVphXrSCnW08nQ+/0UXYENkDiV6M9N6+lW62ZxrSnc/nB1iiM7SkqHR17oKzLn1wOvKUdU8doZlavQ8uv4MAJd18WZC54aLuJboz2bQd6lhP6naUUlBqYli/cVbLilETWqTtFYIUXdO3kF4dh1G4andZO9bT5trHq50Pqcs/4Znt5E4etS+4pRHp8GoXL3Q56Why0vD2adVg477v3IObsCsK8Fv8LRKAZRz+Q2YQoyDM9q0aPT5GTh5Vy2ZaYvK2Q1Hz/p9oKF0qN97luqYdSVn+3aqvoy4ysn6/suka9i8ahdKoXKoeC2NxXlYTEYUDs60vvph/IfWvbqaaJpkTnN+TXFO8/rfiWQWGXjmirYEezZ+hc6Sc+YZNc9LVAAU689fCUyc1WKCKADTe/lbbzgncqrccMqXvV3T29/WpexPKOSbgxmEJ2nIKDJQaqg6Ac7UGBr9hhOeZN2v9k90Hv3ePFhtO4PJmusjtUBX6xvOufXAL0Vag4k7fogis8hAiJcT71zTcFV5hBBCCFv8h0yn8NRucg5UDaJkHyjfynONzWsLo/eT8e83aM6EYyjIwKyvWjLbUJDZ6EEUTdl2kLyj/3DwoX7VtrOYrJ9k6nJTax1ECZl8NyGT777gMQprHp5B70YAYDGbKEk9TfK6d0j48UUyd/5A94e+qZR3RzRfMqepWVOb0xxJKeKbgxl0DlBz+7Bgew9HNIAWFUSZ0sOXpzbGEZ2lJTK9mB7B1nrYh5M1xOfqcHZQcGX3qhmgP9iezBtbzpbWdVQp8FY74FiWDCin2IDZAiWGxo/glS+1Ktaba7WSQWvjxtgSGUxm7vrhNOFJRfi4OrBqbvcq1XMulKuTquLfpUYz7iqVzXblPxM3p+axekcIIUT9+Q6cQtyqp9CmRVOcFIlbmx4AaGIPo8uMR+HgjO+AK6tcl7zhA5LWvlHxvULliIObNwqV9f8ugyYHLGZM56yeaCzlVV3MumLMtVh9Ub4lprlROp/NU2YrYFXOVPb8VM5ujT6m+lIoVbi17k7X+77g9KcLyDn4O7HfPEH3hSvtPTTRAGRO03yYzRYe/z0WswVentL+oq3edz1nnlFaQ7JgbdnP2s3J9rxF2Naigig+ro6M6ejFltP5rDueU3HDKS9LO76TN54ulV+SkxnFvPmP9WZzy+Agbh/Wiva+LpVK0w56O5y0Qj2Whiv0Ui1z2YM8OCaUxy6TLOu1YTJbuP/nGP6JzsfdWcW3c7vTpQETypYLPCcok6HR4+5cdWliqcFMQan1ZhVYy2i6EEKI5svR3QevnmPIP7qFnP3rKoIo5Vt5vHuPx8HVs9I1xcknSfrlTQCCxt9Cq4m34xLYvlIZ3PD/DUKfl8bFePNhsVjfgIde9SBh1z7W6I9nLyq1B0pnV8y6khrLAZefc/SuPm9KUxI0YT45B38n/+gWDJpcHD0urZKxLZHMaZqPNUeyOJpazKRuPvQPdadYVzlAVV4p1GS2VJxzc77wgEaQ+9l5RqbGQPdqFgdmlQWzarvKR1i1qCAKwPTe/mw5nc9vx7N5YmIYFouF305Ybzi2lr39EZmL2QLD23ny6tQOVc6bzBbyyjIf14VKCSYz6Iy271Iane0IsL+b9Rc8pUBX58c8n892pfLZ7tR6XfvF7K4MDvNo4BFdOIvFwv/WneH3Ezm4OChYcUNX+oW6N8pjnZvYKyZbS0f/qkGU2lTwEUIIcWnxHzqd/KNbyD7wG2Ezn8BisZBzsGwrz9CqW3lyw/8AixnPrsPpMPfVKuctZhPG4ry6D0SpArMJi8H2ewiT1naJSydP6/sjXW5K3R/zPFI3fUbq5s/qdW3X+77Ao9PgBhuLtfJOR4oTjlVbecdisaBNjwXAtVXnBnvsxnTu1qrSrAQJolwiZE5TvaY0p0nOtz6/zafy6PLq/mrbrT2azdqj1q1YKS8Mv+DH9Xd3xFvtQL7WSHSWlrGdvKu0ydcaySq2BlGqy0sjbGtx+wkmdfXFxVFJQp6Ow8ka9iVoSC/U4+qk5PIuVZOMppdVUOkTYnvJ5qHkIpt7Cc+nPDqcVk2FliMpRTaPl9eG3xlbgNHUsGHiYr2JrCJDvb4Mpqa5xO65P+L5MSILR5WCz2d3bdQKQh4uDvRuZf092XGmwGabnbHW4wHujnS2EWQRAmDl6p9xCu7MxBk32XsoTc7EGTfhFNy50ld8Yv0y8F8q5DVp+nz7TULp5IIuKwFN7GE0p/ehz0tH6eyKT5/Lq7TX56cD4Na2j83+imIP1bjdpDrlK170eWm2+40/YvO4e4cBABRE7sRiqvskqyYmXTGGwqx6fZmNDV9NwrOrdfKSH7nT5vnihKOYSvKtbRuwMlBj0mWfvR+oXJruFiRRNzKnqd6lOKepjxHtrPf8HbHVz0ssFuu2riFN8MPwpqzFrURxc1YxsYsPv5/IYd3xHHRle8QmdfVFbWMvmHvZcqoz2VXfrJjNFt75N6nK8droFujKnvhC/jqVy+gOlSf2+Voj3x+yvYx0Wk8/Xv4rgQyNgY93prCwhhJk+Voj3ura/4gfGd+GR/6TnKo5W7IlkWX70lEp4aOZnbnMxn8oDW16b3+OpRXzy7EsHh7XGt9zsqKXGsx8c9D6xvjqnn6Vlk8KIerG08MdtYu1eobqP/mHzGYz23fv52DEUcKPHCc84hjxSdZJxJfvvc7Nc2ZW269Op2Nb2bUHI44RHnGMtAzr/fivn79l7MihjfSMrOP+5oe1rPxhLcdORlGq09E6pBVTL5/Aow8uwN/P9qfHPj5eBAVYP3XMyMputPGJ+lO5uOHTZyI5B38nZ/86zGUrQXz7TUJlY+unysU6uSjNOFPlnMVsJmld/UoCu4Z2ozBqD7kRf+HVY3Slc8bifDJ3fG/zOr9B00hY8zKGggxS/viY1lMXVvsYxuJ8HNy8az2mNtc8QptrHql1+8bmP+Qa0v78HG3KKQoid1R5ndL++hIA19bdcQ3pYo8hVmIxm0ChRKGw/Z7CYrGQ9tcXADi4+6IO7ngxhycakcxpqteU5jTnG8usFSfYE1/Idf0CeG9Gwxa9uKa3PxtP5vJvTD4xWdpKq00sFgvL9loD6ra2f4matbiVKADX9LKWEfztRA4bIq3L3q7ubbu04Kiym8Hfp/NYuju14gaVlFfKgjWn2ZdQWClxT21N7WF9vFXhGfx0JAt9Wb9HUoq4YWUk+mqioL5ujjxaVuN9yT9JPLMxjsS8szfDYp2J7WfyeeDnaBb8eLrO42pqCkuN5BYbKr7Ktg1SojdVPm6uHMFeujuV97enoFDA29d0YmrP2peOBAh9bg+hz+3hh8PV74m25ebBQQR7OJKvNXHb6igScq0/m6wiPff9dJr4XB3uziruHSXZ8YW4EO+89DRJx/aQdGwPbUIrVyYp1BRxxax5PPnym/z82x8VAZTaOBl9hqk33Mbzb7zH75u3VARQGptOp2P63Lu486En2LH3AMUlWlycnYmJjee9pcvpP+4qTp6OsXntmuWfVLwWounyK6vAk3PwN3LCN5Qdu9pmW68eowDIO/I3qZuXVgRdSrOTOP3ZAgpP76uUBLXWYxg0FYCM7avI2v0TZqP1k+Oi+CNEvn0DZoPtT5IdPXwJm/EoAEm/LCHuu2cozUqsOG8qLSb/xHaiv3iA058uqPO4mhL39v3w6TcJgOgvF1IQZf27MhtKSVr/Ltl71wLQpuz1+K9Djw5lz+2hJK17u86PbSzOx6DJrfgqZ9JqbB4HayWkYy9NIXPXj+jOWWFkMZvQxB4m6sP55B/7B4DWUx9EoZTkkZcSmdO0DEPfPUToc3t4e2vdAl1TuvvSq5UbRrOF21dHcSLdmhi8sNTIE7/HsT9Rg4NS0WQCTs1Jiww5Tejsg4ezivRC65sFb7WKcR29bbYd38mbCZ29+Sc6nxc3J/Dynwl4OKsoKDWhVMBrUzvw4Y4USvR1289348BAfozI5EhqMQvXxvC/dWdwUiko1psJ9XLixSvb8+Ba22+Y7xzeigKtkfe2J7N8XzrL96Xj7qxCpYBCnakiGdTwdp42r29Obvs+ij3xhVWOP70xnqc3xld8v3dRf9r4uFR8/9KfCQAoFfDKXwm88leCzf5DPJ3YuMD2cun6cHVS8eWcrtz4zUkOJGoY8f5hPF1UaMp+Li4OCj6e1fmi1IcXoiVzc3Wlf58eDOzbmwF9e/HkS0tIScuo1bXeXp4M6NOLAX17Mahfb25asAiTqXErFTz+4hts+mcbjo6OvPPSU9wyZxYuLs7ExCVw3+Jn2LpzDzNvuZuIbRtxcpL7R3Pk02cCKrUH+jzrikSVqzfevcbZbOvdazzevSeQf+wfEn58kYQ1L6NSe2AqKQCFkg7zXiNlw4fo6liZJ3DMjWTu+pHi+CPELFvIma/+h8LBCbOuGCffUNrf+CIxXz5o89pWl9+JsbiA5N/fI33LctK3LLeumFGqMGkLKxLclm+Hac463vo2J96IR5saReSSWSid3bAYdRVbmUKnLsS33xUN/rhHX5iELqdq0Dfqo9sqfT98WeXcNMUJRzmz/CEAlE4uKJ1cMZUWYSkLkqFQEDLpHlpdfmeDj1nYl8xpRE2USgWfX9+Fa1ecICZbyxWfHsXDWUWx3oTZUjZPuqo9vVrJNr+6apFBFBdHJZO7+7ImIguAK7v74eRgO/KqUChYNqcrH+5IYe3RbFIKdKiUCiZ09mbBiBBGdfDiwx11T7Tm5KBk9S09eOffZDZG5pBVZMDTxYFZfX343/g2nMqs+Y3R/ya0YXJ3X1bsS2NPfCEZRQb0ZgutPJ3oEeTGuE5eXNPLdn34lqD8pmsyn806bYuzjZ97xjl7OutzU+nf2oO/7unLB9uT2RqTT3aRgUB3R0a08+L+0aF0C2r4ykBCiLO8PD3IiTmM8pxKJi8ueb9W1/bp0Y2MUwerXRrfGDKysvl85WoA/nf/nSyYfzYXTqf2bVmz4mO6Dr2MmLgElq9aw923Sq6c5kjp6IJv/8lk7V4DgN/AK1E62A6IKRQKut6/jJQNH5K9dy26nBQUShXevScQMmkBXt1HkbLhw7qPwcGJHo+sJnn9O+SEb8RQmIWDqyc+I2bR5pr/UZJyqsbr20z/H74DJpO2ZQWFUXswFGRgMepx8mmFW5seePUch/+QqolymxtHdx96P72B1E2fknPwN3TZiahc3HFr25tWE2/Hp2/VPDYAFpMRQ5F1pYhb294XZaxO3kF0vvtTCiJ3UhR3GENBJsbifJSOLjgHd8Sj02CCxtyEW9teF2U84uKSOc2lz2iykFtincv0rse8pK2vC3/d04cPt6fwZ1QuaYV6fFwdGNTGg3tGhjA4TAJU9dEigygA783oVOt9Z04Oyhr3s+17aIDN47P7BzK7f/Xl7zxdHHh+cjuen9yuyrkR7b3Om5m5Vys33p7esHvnmpqfbu1Zr+suJKv13rKVLxM6e9MzuH6R2dbeziy5WvYdN3fxicl0GTIegNP7t9IuzPZ+3Zi4BHoMn4hCoSDm4LaK7SVJKWmsXruerTv3EBufSEp6Bi7OznTv0onZ06dy581z6ryqwCm4c43j2bZrH5fPnEvb1qFEH/zXZh/bdu3j0xXfsvfgYbJycvH0cGdQ394suPVGpl5xWZ3G0xQpFIp6B0HODbxcLFt37sFgsL5Buv/2m6uc9/Tw4JbZ1/LOp8v47ud1EkRpxjrd/h6dbn+vVm2VDk415gsZsGSfzeOBo2YTOGp2tf06uHrSbs7ztJvzfJVzXt1GVFnl8F9uYb3odGvdt6o0NypnNW2ueZg21zxc62uK4o9g1pWgDulabaClJtX9TGuidHDCf/DV+A+2vTVMXPpkTtO8nW+ucyS1iBK9ma6Bai7vWr/8jr6ujjw3uR3P2fj5iPppkTlRhKhJ+fahB0ZL3pKWrl1Ya4YO7AfAmnUbqm33wy/WUqUjhw6slJ/jf8++wlOvvMXf23aRmpGJq1pNQaGGvQcP89DTL3HVnNvQ623nIGgMFouFR597jctnzmXt75tITc9A7eJMTm4em7du59qb7+ahp168aOMRVknJ1jKM3l6eBPjb3svepZO1HOW+8AiKi+u2hUMIcXEURu0FIHTKfRd1NZsQ4tJV/uHufaNC5b7ShEgQRdjVw7+eqUjimpRX93KNjWFfQiGDwzwY0vbiLm9b9EtMxWtRXlNe2N/1068C4Mcagihr1m20tr1maqXj3bt04oPXnufUvi0UxB0j49RBCuKO8d3nHxDaKohtu/fx1sdfNN7g/+P9pSt4b+lyWocEs/zDN8mJOUx29GFyz0Tw6Vsv4+nhzsfLvuHbNb9etDGJs8zm6ssqludksVgsRMXEXqwhCXFJOrPiYfbcHsqe20Mpza5fRRJbCk/vxdm/TbPa0hSzbFHFa2ErH4sQonYaa06zN6GQNt7OF31L09tbkyqej638lC1di93OI+zLW+1AgLtjpWNNpeTv1vv72eVxPZ1VVV4TR5XEOe1t1tVTWPzcaxw5fpKomFi6lq0IKHfsZBSRUdE4ODgwc9rkSueef2xRlf7UahdmXX0loa2CGDttNl9+s5onH7qvMZ8CAPkFhbyw5H3cXF3Z+MNXdOt8druZu5sbt8+djaeHBzctWMiSDz5j7nXTa933i29+wMtv1z0/AzR+2eDmoE3rEMBaVSglLZ3QVsFV2pyKPlvq9mJVDBLiUuPg5o2jZ0ClY4oG3MLXfdE3DdbXxaJSe1Z5TZQOjtW0FkL8V2PPab6Z273B+qoLN6eq8xIXR5mXlJMgirCLL+d0tfcQmpwXp7TnxSnt7T0M8R+tggIZM3wI/+7ay4+/buCZ/z1Q6fyPv1pXqIwfNazarRi2DB88AG8vT5JT06udODektb9vorikhFlXT6kUQDnXjKuuwNnZiVPRZ0jLyKRVUPX7n8/l7uZKUED9PiFxcpI36+NGDsPBwQGj0ch7ny3nzReerHQ+OyeXr1f/XPG9prj4Yg9RiEtC1/u+tPcQmpz2N75I+xtlG6cQ9XWpzmnuHhnC3SND7D2MJkuCKEIIcR6zZ0zl3117WbOuahDlp7JtPrOnT7V1Kbv2HeTzld+z7+Bh0jKz0GqrLvFMz8hq9CDK3oOHAdi0ZRttelef4M1gsJbwTE5Jq3UQ5eF77+Dhe++48EG2UMGBAcy/YSZffvMDH37xNZ4eHtwxbzZ+Pt6EHznOQ0+9hLb07BY/2RMthBBCCGE/siZHCCHOY8ZVk3B0dORU9BmORp4tAXrg0BHOxCfi7OzENVOuqHLd6+9/yvhrbuD7n9cTm5CE0WjC18eboAB/ggL8KyrBFJc0fqLQ9Axr+cOi4mIysrKr/SrPy1FiI9gjGs9bLzzFhNEjMJvNvPTWB7TtOxL3sJ6MnTabIydO8ubzT1S09faUcoRCCCGEEPYiK1GEEOI8fH28uXzsSDb+/S8//rqBPj26AWeTzU6aMBYvT49K1xw7GcXzb7wHwN3zb+L+O2+hU/u2lUrodhgwmuTUdCyWxn8OZos1OPL4ont48fHal+wUF4erq5oNq5fz3c/rWfPrBk6fiUWpVNKvd08WLphPUEAAi8oqJ3Xq0NbOoxVCCCGEaLkkiNJMzFpxgj3xhbwzvWONddqFEI3j+hlT2fj3v/y0bgMvP/kIFouFn9Zbq/LY2srz64Y/MZvNjBk+hA9ef77KeZPJRE5efp3HoVKpMJlMlOpsV3Aq0GhsHg/0t+YsSUpOq/Njns87n3zJu58uq9e1Py7/mOGDBzTwiJonlUrFvOtnMO/6GVXO/brxTwD8fX3o2E6CKOLiOLFkFoVRe+h46zsEjppt7+EIIZoJmbeIS50EUUSLYjRZ+Gp/Oj8dySI2R4tKqaBroCs3DQziun4B5+9AtFhXT56IWu1CbEISBw4doVSnIyUtAzdXV666fHyV9qnpGQAM7NvbZn/7Dx2xmR/lfLy9PMnJzSM1PcNmgtjwI8dsXjd0YF++XfML/+zYjdFoxMGh4W7/RcUlZGRl1+tavd7QYOO4lJUnMJ49w3buHSFE06Q5E05R7GGK4o9QFH+E0oxYsFhoffXDtLnmEXsPTwjRhMm8pemSIIpoMXRGMzd9c7Ki1rmLoxKDwcyBRA0HEjXsiM3n/RmdJGmjsMndzY0pE8fz829/8OO6DZSWJfqcNvkyXF3VVdp7ursDEHUmtsq58rwX9dGrWxe27d7H75u3MGH0iErn8vILWLFqjc3rZk67ksdfXEJaRiZvfvQ5Tyy6t9rHyMsvwMfbq9Zjenbxgzy7+MFatxd1s2X7Ln7+7Q9cXJy5745b7D0cIUQdnHx3LiZtob2HIYRoZmTe0rRJYlnRYrzyZwJ74gtxc1Ky9PouxDw1hOinhvLqVe1xUCr4+Ug2X+1Pt/cwRRN2/fSrAPhp/UbW/r6p0rH/Gj/aWgFn419bee+z5ejKtt/EJyZzw50PsmPvAdxcXes8hmunTgbgy29/4Ns1v6LX6wEIjzjGldfPR1f2/X/5+/nywuOLAHju9Xd56KkXiUtIqjhfVFzM39t2Mv/+/3HDnc0/IFJQqCE7J7fiqzxhblFxic3j58rLL6jUpqJPjcbm8XLxick4BXfGKbgz23btq9N4/925l/eXriA2IbFiTDm5ebz76TJm3nIPFouFl554hE7tZSuPEM2J0skF9/b9CRp/Cx1vfQe3tn3sPSQhRDMg85amTVaiiBYhrVDHNwet2yuem9SOqT39AHBQwS1Dgkkt1PPRjhTe25bCjQODcHaQ+KKo6srLxuHp4U5KmvV3ycfbiyvGjbbZdtKEMUyeMJZN/2zj0edf4/EX38DTw538gkKUSiUfvfECb7z/WZ0r89w+93pW/rCW8CPHuO2BxSx4+EmcnZwoKi4mLDSEd15+hlvv/5/Nax+861by8gt59d2P+XjZN3y87Bs83N1QqVQUFGqwlGW4HTtiaJ3G1BTNvOVutu/ZX+X4oqderEjQCnB6/1bahbWu1GbIxGtISE6pcu2s+fdU+l6fHt1Ao4XE5BQWP/cqi597FUdHR9xc1eQXWD99UqlUPPfoQhYuuLXBHk8IcXEMfOsgCqWq4vvsvWvtOBohRHMg85amT4IodrQvoZCVB9LZn6ghu8iAh4uKNt7OTOziw/X9Awn1cq5VP3viC9hwIpdDyRpSC/UUaI34uDowsI0Hdw5rxZC2tsth6oxmvtqfzm/Hc4jJ1lJqNOOjdiDIw4kR7T25vl8g3YIqf1K+K66AFfvSOZSsIbfEiKujEj83R3q1cmNyN1+u6e1/wa9LY/gjMhe9yYK32sHmHsI7hgXzyc4UsosN7IgtYGIXHzuMUjR1Li7OXHPl5Xzz4y8ATJ9yBU5OTjbbKhQKfvrqE15//zNWr11PQnIqDioVkyeM5aF7b2f8qOG88f5ndR6Dk5MTm9Z8zctvf8gvv28mPSsLby8P5l43nWcXP8iJUzVP7J97dCHXTLmcT5Z9w/bd+0jLzEKn19M6JJjePbpxxbjR1a6uETVLz7SWkXZxcaZ7l051unbE0EE8cOctbN+zn6SUNIpLSmjXpjVjRw7l3tvm0b9Pz8YYsmiBCk/vI/3flWii92MozEal9sDZvw0+fSYSOOp6nH1Da9VPQdQecg9uQBN7CH1uKsaSAhzcfPDoNJBWl9+JZ+chNq8zG3Sk//MVOQd+Q5seg1lfioO7D07eQXh2HUHgyOtxbd2t8mOd2kX6lhVozhzCWJSL0tkVRw8/3MJ64dt/Mv5Dr7ng16WxnBtAEaI5k3nLxSPzlqZPgih2YDZbeH5TPMv2nV2C5emiQmswE5FSTERKMWYLPDK+zXn7KtaZmLUisuJ7D2cVDioFGRoDGyNz+eNkLq9d1YF5g4MqXWcwmZnzdST7E62VPJQK6xiyiw1kFhk4llaMg1LBk5efXTr+9f50ntwQV/G9u7MKndFMbE4psTml7IkvbLI3o/L9hEPbeuBkI1ob4O5E10BXTmaUsDtObkaiess+WMKyD5bUqq2Tk1ON+UKiD/5r8/jNc2Zy85yZ1fbr5enBmy88yZsvPFnl3NiRQ8+7QqJfrx58/u5rNbZp7v7+ZVW9r63u53I+5Stf5s+ZRWCAX52u7dS+LW+/9HS9HleI2rCYzcSvfp70LWcraanUnpj1WorjIiiOiwCLuVbJTk2lxUQumXVOPx4oVA4YCjLIDd9I7qE/6DD3NYLGzat0ndloIPLtOWiiy1aJKZSo1J4YCrMxFGRSnHAMhcqBtrPO3tvSt35N3Ldnv1e5uGM26CjNiKU0I5bCqD1NOogiRHMn85aLT+YtTZ8EUezgwx0pLNuXjkIBd48I4Y5hrQj2tH6anZRXyobIXNyda/fJhVIB03r6MatfAEPCPPB0sf5I0wv1LNubxie7Unn2jzjGdPSira9LxXW/HMtmf6IGPzcH3pneiXEdvXFQKTCYzCTl6/gjMhdv9dlfjxK9iZf/SgDg/tGhLBjeCl83RwByig3sTSjkn9N5DfL6NIbobC0AnQOqz0HROUDNyYwSorO0F2tYQohLyI7d+3FwcODhe++w91CEqCJl44fWAIpCQciku2k18Q6cfIIBKM1OIjd8AyoX99p1plDiN3gaAcNn4dF5CA6u1k+O9XnppP29jNRNnxD3/bN49RyDS8DZSU32vl/QRO/HwcOPTre+g3evcShUDpiNBnQ5SeSG/4GDm3dFe5OuhIQ1LwMQOuV+Wl2xAEcPXwAMmhwKo/aSd+yfBnh1hBDVkXnLxSfzlqZPgigXWXaRgQ+2JwPwxGVh3De68rLZNj4u3D0ypNb9qZ1UfHZ9lyrHgz2deOqKthSUGlkVnskPhzN59LKwivOHk4sAWDA8pFL00lGlpIOfusq4ojJLKNGb6eSv5omJYZXO+bk5clUPP67qUbdPXnfHFXDdV5Hnb2jDw+Na1yriXS5TY022GeTuWG2bQHfrfwhZRVJyVYim7o5Fj3PHoscB23lNLjaTycSeg4e47popF30sE2fcZDP/ixDlDIXZJP9urQgWdu0ThE65r9J5F/82hEy6u9b9qZzVdLm76nZEJ59g2l73FMaSAjK3ryJz5w+EzXi04nxR7GEAQq5YgE/fiRXHlQ6OqIM6VBlXSUoUZl0J6ladCJv5RKVzjh5++A26Cr9Bddt+WHBqN5FvXlena8pJWWLR0si85SyZt4hzSRDlIvs9ModSo4VgD0cWjKj9Tae+JnT2YVV4JofKbj7lPMoixhlFtit5/JeHs/VXRaMzotWbUDtd+B5fR5WSgBpuDjVxq+Pjlxis1S5cHKtPvKQuO1esN9VrTEKIxufj40VQQOXltyqV/XMOqFQqsqMP2+Wxm+prIpqOnIO/YzGU4ugdTMikBY3+eD69J5C5fRVFsYcqHVepPQDQF2TUqh+HsvbGEg0mnRaVc9Vy8nWldHDE0bNqjoHaUDm7XfDjC9GcyLzlLJm3iHNJEOUiK4+kjupgXYbWEPRGM98dymRDZA5RmSUUaE0YzZZKbTL/c9MZ18mbj3emsnxfOnklRmb08WdImGe1y/Ha+brQzteZ+Fwd0748zvwhwYzp6EWYj4vN9rUxOMyDiMWD6n29EKLlWbP8E3sPocmR10ScT1GcNcDn3WMUClXDvPUzG/Vkbv+OnPANlKREYSopwGIyVmqjz8+s9L13r3Gk/vEx6VuWYyzKw3/YDDw7DUGltr2NyCWwHc6B7dBlxnP81WkET5iPV48xuASE2WxfGx6dBjPo3Yh6Xy9ESyLzlrNk3iLOJUGUiyyn2LrkKtTLdkWPutKUGpmzMpKIlOKKY65OSrwdHVAorImY8rUmSvTmSteNaO/Fw+Na8/72ZNYezWbt0WyUCugR7MYVXX2YNyiIQI+zY3RQKfhwZmfuWB3FyYwSHvstFoAgD0fGdPRmTv9AhrWznU27KXB1VFJgMlFqMFfbRlt2rq7RYiGEEKIpMxTmAOBUy8o752PUaoh8e441GW0ZpbNrWT4TBWajAVNJPmZ95RLuXt1G0Prqh0n+/X2y9661lvtVKHFr0wOfflcQNG4eTl6BFe0VKgc63/khUR/dQUnySWJXPgaAo1cQ3j3HEDhqDp5dhzXIcxJCVCXzFvuQeUvTJ0GUZu69bclEpBTj6aLi1avaM66TNz6uZ5ea7YgtYM7XkVhsXPvI+DbM7BvAumPZ7E0o5GCShuNpxRxPK2bp7lSW39CNUR28KtoPaO3Brgf7s+FkLtti8tmXUEhKgZ41EVmsicji5sFBvDa1w0V41nUX6OFEQamWjBr2DWaVRb0DPeq3VE8IIYRoCZJ/e4/iuAhUak/az30V717jcHQ/m6egIHIHkW/PAUvVdx9trnmEgOEzyd6/jsKovWjOHKQ48TjFicdJ3byUbg8sx6v7qIr2Hh0G0P+1XeSGbyD/xDYKT+9Dn5tC1u41ZO1eQ9C4m+kw79KuNibEpULmLbUj85amT4IoF5l/2V665AJdg/S3ITIXgOcnt2NGn6p7fMsjyNVp5+vCwrGtWYg1+rsztoBX/04kMr2Ehb/EsP+hAaiUZ5fvqZ1UzOobwKy+1seKydaybG8aKw9ksPJABpO6+TKuk3etxn4gUcOdP0TV7on+x90jQuqUyKqzv5roLC0xWSXVtqnIhO1/4XuuhRBCiKbC0dOaM0eXk9wg/eWGbwCg3ZznCRg2o8p5gyanxutdAtvReupCmLoQs9FAwcmdJP78KiVJkcQsW8iAJftRKM9+uqpyVhMwYhYBI6xllbXpMaT9tYyMf1eS8e9KfPtPwrvXuFqNXRNzgKiP76zlM60sZNLdhEyufQJeIZo7mbecJfMWca7qs9WIRjGgtXXf787YAowmW3HWukkvy97cN8T2fuLdcQW17stRpWR8Zx++mN3V2nehnvjc0hqv6eSv5rWpHRgSZk3+Vl7XvDYMJjNZRYZ6fdU1idLwsiV7exM06I1Vl8ZlFek5lWG9UY1o71XlvBDN2cQZN+EU3JmVq3+291CEEHbg3nEAAAWRO6vkLakPfV66td92fW2eLzi1u9Z9KR0c8ek9nq73flHRd2lmfI3XqIM70WHea3h0HgJAYdSeWj+e2WjAUJhVry+Trvj8DyDEJUTmLWfJvEWcS1aiXGRTe/jxwuYEMjQGlu5OrVKSq67cnVXklRg5k6OlW1DlWuJnsrX8fDTb5nV6oxknB9sxNJdzjuvK/nBrag9ns0frbPyhV2dEey9SXhhe6/YX4soevrz0ZwL5WiM/H8nihoFBlc4v35eO2QL+bo6VlgIKIUQ5o9HIpyu+5ds1vxJ9Jh6VSknPbl24fe5s5l1f9dN4IZoKv4FTSfjhBQwFGaRuXlqllHBdqdTuGIvy0KafwbV1t0rntOlnyN5rO2BrNupROtjOraB0PJvw0WzQnbf9udeUt68Nr24jGL4spdbthWjJZN5ylsxbxLlkJcpF5uvmyMIx1hvQa1sSeeXPBNILz2agTsor5Z2tSaw8kF6r/kaVRR9f2pzAwSQNFosFs9nC1ug8blgZWenGcq6Fv8TwyK8xbD+TT7HubHQ0JlvLw7/GANaa7V0DrTe4f6LzufrLY3wfnkHKOUv6inQmPt2Zwo5Ya+S4tkviLrZWns7MG2y9AT2/OYGNkTlYLBaMJgvfHMjgk52pACwaG4pzDTddIUTLpNPpuPL6+TzyzCscPnoCk9mEtrSU3fvDuf3BR7n1/sVYbOR/EKIpcPTwJXTqQgAS175GwppXKlaTAJRmJ5G07h3S/11Zq/7Kc5YkrHkJTcxBLBYLFrOZvGNbiXz7hkoBkXPFfLmQmBWPkH9iO6bSs6s6tOkxxKx4GAAnn2BcQ62fLOcf/Ydjr15Nxo7v0eWeDXyYtEWkbPqUgpM7AGq9lcceTKXFGDS5FV/mspVAZr228nFjzdsYhLAHmbfYh8xbmj5ZiWIH948KJVNjYMX+dD7Zlconu1LxclFhNFsoLstG/fC41rXq638T2rDtTD5J+Tqu+fI4akclFouloqb785PbseiXmCrX6Yxm1h/PYfXhLBQK8HJRUWq0VGSBVjsqeW9Gp0r7CsOTighPKqo476RSUFB69kY2d1BQk70ZATx1eVsi00vYE1/InT+cRu2oxGyxoDNaJz4z+/ozf0iwnUcphGiKnnhpCdt278PdzY0v3nuNa6dOxmQysezbH3jo6ZdZ9dOvDO7fh3tvn2fvoQphU+iV92PIzyT9nxWkbvqE1E2foHL1wmIyYi7bptL66odr1Veb6f8j//g2dNlJHH/tGpROamsgxVCKo3cw7eY8T8yyRVWuMxt05BxYT9bO1aBQoFJ7YTGWYtZbl+ArndR0uu29SvlQis6EU3QmvOK8wsEJU8nZJf9BY+c26SBK3KqnyNq9psrx1E2fkrrp04rveyxeg1e3ERdzaELUisxb7EPmLU2bBFHsQKlU8PJV7bmyhy9f7U8nPElDbokRb7UDXQJdubyLD9f3r5psyZZO/mp+u7M3b/6TxM7YAkr0JoI9nbissw+LxrbmdDUJiZ6YGMagNh7sjC0gPrfUmv3ZYqGDnwujO3ixYEQIbX3PfpI0sr0nH1zbie1nCjieVkS6xkCRzkSAuyN9Qty4aWAQk7r5Nsjr01icHZSsvrkHK/an89ORLGJztDgplfRu5crcQUFc1692r7kQomVJSUvn85XfA/DmC08wc9qVADg4OLBg/k0kpaaz5IPPePXdj7l97vU4Ozvbc7hC2KRQKml/08v4DryS9H++QhMTjrEoFwc3b1xDu+DT93ICRl5fq77UwZ3o/fRvJP3yJgUnd2LSleDkHYxPn8toPW0RJamnbV4XNvMJPDoNouDkTkoz4zEUZGCxgEtQB7x6jCZk0gJcAtpWtPfsPpJOd3xAQeR2ihKOY8hPx1RahKNnAG7t+hA05iZ8+09qkNdHCGGbzFvsQ+YtTZvC0ozXHx86dIiBAweyaUFveleToEiIluJYahGTlx4jPDycAQMG2Hs4F035fWDfn7/Sv09Pew/notm59wBLv/6O3fvDycjKxsvDg7ZtWjPl8nHcMmcWbUJbVbSdOOMmtu/Zz5fvvc7Nc2ZW6mf77n2s/X0z+8IjSE5NI6+gAD8fH4YN6s+Dd81n5NBBNh9fp9Px6YpVrFm3gaiYWLSlOvx8vGkVHMi4EcOYN/taenXvUumaf3fu5ePlK9kffoTs3DzcXNUE+PvRr1cPrr5yIrOnT234F6oBfPzlSh56+iV8fbxJPLILJ6fKORoysrJp23ckZrOZX7/5nCmXj7fTSC+ew0dPMPSK6S32ftP72U24t+1t7+EIYVdFCcc49uLkFncfaAwypxGXmkt9XiIrUYQQohkxm83879lX+OjLs7kLvDw9KNGWcjDiKAcjjmI2W3h28YPn7auouJiJ186t+N7Twx1HB0fSMjL5ZcNmft34Jx+98QJ33nxDpesMBgOTr5/Prn0HAVAqlXh5epCZnUN6ZhaHj55A5aDi1acXV1yz9KtVPPD48xXfe7i7UarTEX0mjugzcWzfva/JBlG27dkHwMihg6oEUACCAvzp2a0LxyJPsW3XvhYRRBFCCCGEaKkkiCKEEM3IGx98xkdfrkShUPDQPbfz4F3zCQm2Jh+LT0zmlw2b8XB3q1VfSoWSWVdPYe510xk5dBBentaSf6npGXz4xde8/fEXPPT0S1w2diQd2oZVXPf92t/Yte8gAX6+fPHe61wxfjQODg4YDAbik1L4dcNmfH28K9oXF5fw+ItLAHj0wbtZtOBW/P2sy2izsnPYsfcAm7Zsa4iXp1GcOn0GgO5dOlXbplvnjhyLPMWp6Kp7uYUQQgghxKVDgihCCNFMZGbl8Np7nwDw8pOPsPiBBZXOtwtrzUP33F7r/lxd1Xz3+ftVjocEB/HaM4+SX1DIsm9/4OvVP/PCYw9VnD9w6AgAi+6+rdKqC0dHRzp3aFdlXJFR0RSXlNC1cwdefvKRSucC/P24dupkrp06udbjBti2ax+Xz5x7/oY2PP3IA7VaqVMuPTMLgFaB1e8/bhVkPZeeZbs8oxBCCCGEuDRIEEUIIZqJtb9vorRUR0hwUJ2CJfU1+bKxLPv2B/aHR1Q67uFh3a9dHlw4n/L2hYVFlJRocXVVX/DYnJwcCQrwr9e17m6udWpfXKIFQK22XbbVes76nIqKbSfFE0IIIYQQlwYJogghRDOxv2wFyITRI3BwaJjbt16vZ/mqNaz9fRMnTp0mr6AQo9FYqU1aRuVgyaTxY3jro8/56MuV5OTlM2fGNEYOHYiHu+1keJ3at6VjuzDOxCcyeur13HPrTVw2ZiTt27ap97iHDx5A0rE99b5eCCGEEEKI+pAgihBCNBNZ2TkAtGnd6jwta6dQo2HydfM5GHG04pibqyu+3l4oFAr0BgN5+QWUlK3EKDd25FCefuQBXnvvE777aR3f/bQOpVJJn57dmHrFZdx1yw0En7P1xcHBga8/eZvrbr2PY5GnuHfxMwC0Cgpk4tiRzL9hFqOHD2mQ59QY3FzV5BcY0GpLq22j1Vpfo7quchFCCCGEEM2L0t4DEEIIYR+vvvMxByOO4uXpwdefvE36yQPkxR4h+fheko7t4fsvPgDAYrFUufbZxQ9yfNdmXnj8ISaOHYnaxYWIY5G8/PaH9Bh+OVt3Vl4lMmRAP07u+ZvlH77JDTOvJiw0hLSMTL758Rcum3ETDzz23EV5zvVRHhBKq2H7Um3ypgghhBBCiOZPVqIIIUQzERjgB0BiUmqD9Lf2980AvP3iU9xw7dVVzmeWrXypTsd2bXli0b08seheDAYD/+zYw1OvvMnRE6e47YHFxBzchkqlqmjv6qpm7nXTmXvddACiYmL56IuvWfr1dyz9+jumTZ7IFeNH12rsew4c4vrb7qvlM63soXtu5+F776h1+25dOnIq+gynos9U26b8XLfOHes1JiGEEEII0TzIShQhhGgmhg7sB8A/O3ZXyVtSHynpGQAM6Nvb5vltu/bVui9HR0cmTRjDD8s+svadlsGZ+MQar+naqQMfvvECI4cOAmD7nv21fjy93kBGVna9vuqa/HXs8KEA7Nx7AL1eX+V8RlY2x0+etrYdOaxOfQshhBBCiOZFgihCCNFMXDt1Mmq1C2kZmbz76bIL7s+zrGrO6TOxVc6dPhPHdz+vs3mdrUBCObXL2Qo2pTrdedtbr3EGQFfWvjbGjhyKPj26Xl91KW8MMP2qK3ByciQ3L59VP1V9TT5ethKz2Uygvx8TRg+vU99CCCGEEKJ5kSCKEEI0E/5+vjyx6F4Ann71bZ54aQmpZatJAOITk3nprQ/5/OvvatXf+FHWCf/jL7zB3oOHsVgsmM1mNv+znSnXz68UEDnXrQ88yl0PPcHf23ZSVFxccTwqJpY7Fz0OQGirIHp27QzAH1u2MWbq9az4bg1JKWkV7TVFRbz98Rds2b4bgMvH1W4rz8UW2iqYBbfcCMD/nn2FXzZsxmKxYDQa+WLl97z10RcAPPnQfTg7O9tzqEIIIYQQopFJThQhhGhGHn1gAekZWXyy/Bve/vgL3v74C7y9PDEaTRUBjacfeaBWfT336EL++ncH8UnJjJl6Pa5qNWaLmdJSHSHBQbz5wpPc/uCjVa4r1elYs24DX33/EwqFAm8vT0p1uorqNa5qNcs+WFIpH8reg4fZe/BwxXknJ0fyCworzt9585xa50Oxh1efXszRE6fYtnsfs2+/H1e1GpPZhE5nXWVz06zp3HPbXDuPUgghhBBCNLZLIogSna09fyMhLnHyd9AyKJVK3nv1WaZPuYJPV3zL3oOHyc7Nw9fbix5dO3HVFRO4efa1teqra6cO7Nz4E8+/8R5bd+6hqLiY0OAgrpw4nicfuo+Tp2NsXvfyk48wfFB/tu7cw5m4BNIys7BYLHTu2J7LRo9g0T230aFtWEX78aOGseKjt9iybReHj50gLSOTQk0RQQH+DOzbi9vmzubqyRMb5PVpLM7Ozvzx41d8svwbvl3zK9Fn4nF2cmJAn17cMW8O866fYe8hiotImxZt7yEIYXfyd9Dw5L2cuFRc6r/LCout2pXNRGJiIt27daWk7NNPIVo6V7ULJ09FERYWdv7Gl4hDhw4xcOBA9v35K/379LT3cIRoEQ4fPcHQK6YTHh7OgAED7D2ciyYxMZGu3bpTqq1bcmIhLlUualeiTp1sUe87GoPMacSl6FKelzTrlShhYWGcPBVFdna2vYciRJPg7+9/Sd6ohBCiKQgLCyPq1El53yFEGXnf0TBkTiMuRZfy/aFZB1HAetO5VH84QgghhGha5H2HEKIxyL1FiOZDqvMIIYQQQgghhBBC1IIEUYQQQgghhBBCCCFqQYIoQgghhBBCCCGEELUgQRQhhBBCCCGEEEKIWpAgihBCCCGEEEIIIUQtSBBFCCGEEEIIIYQQohYkiCKEEEIIIYQQQghRCxJEEUIIIYQQQgghhKgFCaIIIYQQQgghhBBC1IIEUYQQQgghhBBCCCFqwcHeAxBCiIZwMjrG3kMQosWQvzchhBBCtFQKi8VisfcghBCivhITE+nevTslJSX2HooQLYqrqysnT54kLCzM3kMRQgghhLhoJIgihGj2EhMTyc7OtvcwGszLL7/Mxo0b+fbbb+nQoYO9hyMuwPr163nhhRd45ZVXmDx5sr2H06D8/f0lgCKEEEKIFkeCKEII0YT8+OOPzJ49my+++II77rjD3sMRF8hisTB37lx+++03Dh8+TMeOHe09JCGEEEIIcQEkiCKEEE1EXFwc/fr148orr+T7779HoVDYe0iiARQWFjJgwAB8fHzYtWsXTk5O9h6SEEIIIYSoJ6nOI4QQTYDBYGDOnDn4+fmxdOlSCaBcQjw9PVm9ejVHjhzhySeftPdwhBBCCCHEBZAgihBCNAFPP/00hw4dYvXq1Xh5edl7OKKBDRo0iDfeeIO3336bjRs32ns4QgghhBCinmQ7jxBC2NnmzZuZPHkyb775Jv/73//sPRzRSCwWC9OmTWPfvn0cOXKEkJAQew9JCCGEEELUkQRRhBDCjtLS0ujbty8DBw5kw4YNKJWyQPBSlpWVRb9+/ejWrRt//vknKpXK3kMSQgghhBB1IO/WhRDCTsxmM/PmzUOlUvH1119LAKUFCAgIYNWqVWzdupXXX3/d3sMRQgghhBB1JO/YhRDCTt544w3++ecfvv32WwIDA+09HHGRjBs3jmeeeYbnnnuOnTt32ns4QgghhBCiDmQ7jxBC2MGePXsYPXo0jz32GK+88oq9hyMuMqPRyIQJE4iPjyciIgJfX197D0kIIYQQQtSCBFGEEOIiy8vLo3///oSGhvLvv//i6Oho7yEJO0hKSqJv376MHTuWtWvXSllrIYQQQohmQLbzCCHERWSxWLjzzjspKCjgu+++kwBKC9amTRtWrFjBr7/+yieffGLv4QghhBBCiFqQIIoQQlxES5cu5eeff2bZsmW0bdvW3sMRdnbNNdfwwAMP8PDDDxMREWHv4QghhBBCiPOQ7TxCCHGRHD16lCFDhnD77bfz8ccf23s4ookoLS1l+PDhaLVawsPDcXNzs/eQhBBCCCFENSSIIoQQF0FxcTGDBw/G0dGRffv24eLiYu8hiSYkKiqKgQMHcv3117N8+fJK5/Lz84mLi6N///52Gp0QQgghhCgn23mEEOIiWLhwIQkJCaxevVoCKKKKrl278sknn7BixQpWrVpV6dyPP/7I2LFjMZvNdhqdEEIIIYQoJ0EUIYRoZKtXr2bZsmV8+OGHdO/e3d7DEU3UzTffzLx587j77ruJiYmpON62bVs0Gg3x8fH2G5wQQgghhABkO48QQjSq2NhY+vXrx9SpU1m1apWUsRU10mg0DBw4EA8PD3bv3o2zszMpKSm0bt2adevWcfXVV9t7iEIIIYQQLZqsRBFCiEai1+uZM2cOAQEBfPbZZxJAEefl4eHB6tWrOX78OE888QQAISEheHt7c+LECTuPTgghhBBCSBBFCCEayVNPPUVERAQ//PADnp6e9h6OaCYGDBjAkiVLePfdd/n9999RKBT06tWL48eP23toQgghhBAtngRRhBCiEfzxxx+89dZbvP766wwaNMjewxFNmNFoZO7cuXz66afo9XoAHnzwQaZOncr8+fNJSUmRIIoQQgghRBMhQRQhhGhgqamp3HzzzUyZMoVFixbZeziiiVOpVKjVau677z66du3K8uXLMZlMrFixAhcXF2666Sa6d+/OqVOnMBgM9h6uEEIIIUSLJkEUIYRoQCaTiXnz5uHo6MhXX32FUim3WVEzhULBF198wbFjxxg0aBC333473bt3Z9OmTaxcuZIdO3YQERGBXq+vVLVHCCGEEEJcfPLuXgghGtDrr7/O1q1bWbVqFQEBAfYejmhGevbsyZo1azh8+DDdu3dn3rx53H///cycOZOvvvoKQJLLCiGEEELYmQRRhBCigezatYvnnnuOp556ivHjx9t7OKKZ6tevH+vXr2ffvn20adOGNWvW4OrqCsD+/fvtPDohhBBCiJZNYbFYLPYehBBCNHe5ubn079+fNm3a8O+//+Lg4GDvIYlLxM6dO1m8eDF79+6le/fuREZG2ntIQgghhBAtlgRRhBDiAlksFmbOnMm///5LREQEYWFh9h6SuMRYLBZWrVqFj48PV111lb2HI4QQQgjRYkkQRQghLtAnn3zCfffdxy+//ML06dPtPRwhhBBCCCFEI5GcKEIIUQsajYb169dXOX7kyBEefvhh7r//fgmgCCGEEEIIcYmTlShCCFEL77//Ps8++ywFBQUVx4qLixk4cCAuLi7s3bsXFxcXO45QlEtMTCQ7O9vewxBClPH395dtjkIIIS4ZkvlQCCFq4dixY3Tq1KnSsQceeIDk5GTCw8MlgNJEJCYm0r1bN0q0WnsPRQhRxlWt5uSpUxJIEUIIcUmQIIoQQtTC8ePH6dWrV8X3q1atYsWKFXz11Vd07drVjiMT58rOzqZEq+XTuyfRJdTX3sMRosU7nZLLPZ9tJjs7W4IoQgghLgkSRBFCiPOwWCycOHGCmTNnAhATE8Pdd9/NTTfdxM0332zn0QlbuoT60rddoL2HIYQQQgghLjGSWFYIIc4jMTGRoqIievbsiV6vZ86cOQQHB/Ppp5+iUCjsPTwhhBBCCCHERSJBFCGEOI/jx48D0KtXL5544gmOHj3K6tWr8fDwAGD37t1MmzaNL7/80p7DFEIIIYQQQjQyCaIIIcR5HD9+HA8PD44ePco777zDkiVLGDhwIOHh4UyZMoWRI0cSHx/PgAED7D1UIYQQQgghRCOSIIoQQpzH8ePH6dy5M7feeitTp05lwoQJzJgxg0GDBhEbG8vq1as5cuSIBFGEEEIIIYS4xEliWSGEOI/jx4+TkZGBQqHAwcGBfv360b59e77++mtuvPFGHBzkViqEEEIIIURLIO/8hRCiBiaTiePHj2M0GlEqlYSHh/P5559zyy234OjoaO/hCSGEEEIIIS4iCaIIIUQNEhISMBqNuLu78/rrr3PHHXfg7Oxs72EJIYQQQggh7ECCKEIIUYP27duzYsUKZs2ahbu7u72HIxrY/Uv/ZPXOk+dt9+uTMxnVvXXF9/7z3rfZzsVRRZC3G4M7t+KOy/syqFMrm+1SczXsOplCRFwGh2MzOJ6QRYneSBt/Dw6/e1utx7/x4Bm+2xHJ4dgM8opK8XF3oUOQN2N7teG+KQNRO1X+b77/Q8tJytaweMZQHrt2WK0f51JkNlvYHZXCn4fj2Hc6lZi0PEp0BnzcXejTNoAbxvTkmqGdq73+RGIW+6PTiIjN4HBcBlEpuZjMFuaM6s5HC664oLFp9UaW/XWE3w7EEJ2WS4nOiJerMz3D/Jk9qjvXj+xWpbx6YlYhAx5eUevHyP5mYaXvv98eyQNf/FXjNd1C/dj5+tzaPxEhhBDiEiRBFCGEqIFCoWD+/Pn2HoZoZI4qJT7uLtWed1LZzsPuoXaqFKjIKyolIauQhKxCft4Txcs3jWHBpP5Vrvt44yGWbo6o93hL9Ubu/PgP/jgUC4BSocDT1YnMgmIy8ovZE5XCjWN6oPb1qPdjXOre+nUfS37ZV/G9g0qJ2smBzIIS/j6awN9HE1izuwPLH5iCk4OqyvX3Lf2T44nZDT6urIISZry2llMpOQAoFNbfsxyNlu0nkth+Iom1e6L45qFplcalUioI9HKtse/colKMJjN92gVW26amvwVfj+r/RoQQQoiWQoIoQgghWrzBnVux/qlZdb7u1bljuWFMj4rvzWYLRxMyeWLlNg7EpPHc9zuZ1L8D7QK9qlzbLtCLfu2D6Nc+kOxCLR9tDK/1497+0UY2H46jXaAXz80ZyeV92+Pi5IDOYORUSi7r90Xj7Cj/xdfEaDLj6+7CnNE9mD6sM33bBaJSKsksKOb93w6ydHMEmw7F8tKPu3jpxjFVrndQKekV5k+/DkH0ax/EpkOx/H0k/oLH9cQ32ziVkoOLo4ol88dz7bCuuDg5oNHqWP73UV5es5stRxP4bNNhHpw6qOK6UD8PIj+6s9p+C4p19HzgC4wmmD2qW7Xt6vu3IIQQQrQU8g5LtFiJiYlkZzf8p4hC2Iu/vz9hYWH2HkaLplQq6Nc+iBULr6LXA19iNJn552g8t03sW6ndizeO5pW5Yyu+/3HXqVo/xo87T7L5cBzBPm5seOY6grzdKs45OzrQt10gfWtYadAUFBTr2B2VwpUDOthtDNOGdOaBqYPwUDtVOh7o5cYrc8dSpNWzanskX205xpOzRlTZGrX5+dmolGdXKB2OzbjgMekMRjaGnwFg0dWDuXFMz4pzHmpnFk4bTFxmAd/+e4INB89UCqKcz6/7TlNqMOGoUjJzeNcLHqsQQgjRUkkQRbRIiYmJdO3WnVJtib2HIkSDcVG7EnXqpARSmoBgbzd83V3ILSqlWGescv7cyXddffC7dcXKY9cOqxRAaeosFgs7IpNYtS2SDQdj6NTKx65BlN5tA2o8f/2o7qzaHolWb+R0am6VwNSF/Ayrk1+sQ2801Ti+Pm0DgROU6Ax16vvHXdbcPxP6tMXfs+ZtP0IIIYSongRRRIuUnZ1NqbaETnd+iLpV9YkDhWgutGnRxHzxANnZ2RJEaQIy8ovJLSoFoENQ1a089RWZlM2plByUCgXXDGke966k7EK+3x7J6h0nScwurDgeFtBwr0tj8D0nL4jJbL4ojxng6YrayQGt3sixhCwm9a8aZDqakAmcPwh0rvjMAvadTgNgzujuDTNYIYQQooWSIIpo0dStOuPetre9hyGEuERYLBaOJ2bz+MqtAHQI9uaKfu0brP+DMekAtA3wxM3FkU//OMR32yOJy8jHxcm6lWf+Zb2ZNti+AZZSvZEN4Wf4btsJtkcmYbFYjwd4qrl2eFduHNODnmG1DwLYw+5TKYA10WqnYJ+L8phKpYIbRvdg+ZajvLf+ACG+7ufkRNGzYstRVm07gaerE49MH1Lrfn8oq0Dl7eZsMzBzrqiUXEY+/g3xmQU4qlS0C/RkQp+23HlFP1r5SIUyIYQQQoIoQgghWrwD0Wn0uP8Lm+fmje/FEzOH2zz35LfbeOnHXRXf5xWVYjCZcXdx4vqR3XhuzigcbVR2qa+4jHwAvN1dmPfu7/wZEVdRmaewRM+2E0lsO5HErZf15s35ExrscWsrIi6D77ZFsnZvFPnFOsAahJjYtx03jOnBFf3a41BNpSOoe5neczVEaeFyJToDH26wbpuaMqgjnq7ODdJvbTw7ZyQpuRo2H47jwS/+ZuGXf+Ohtv58VUoFk/p34NnrR9KxDoGdNWU5d6YP7WKz0tC5cjRa8opK8XR1QqPVczwxm+OJ2Xz1zzG+uO9KLuvT7kKenhBCCNHsSRBFCCFEi2cwmckssJ0jqUirr/Y6jVaPxsb5UoORolIDBcW6Bs1bUqi1BiYi4jKwWOCuK/rx6LVD8XZzIVej5eU1u1m59TgrthxjQIfgSpWDGkuuRsua3af4blskJ5LOJuvuFebPnNE9mDWia61zcNSmTG91GjLQ8djXW0nO0eDu4sQz149ssH5rw93FiS/vn8ILq3fy5V9HsFigsMT6O2a2WCgu1ZOt0dKllv3tjUohPrMAqHkrT7CPG4/PHMbVgzvTPsgLRwcVWr2RvyLieOa77aTkFHHr+xv4+8Ub6BLqe6FPUwghhGi2JIgihBCixRvRLbReZV0/vPPySoEKjVZHdFoe760/yMbwM+yJSuGXx6+lVx3yV9SkPDWHxQJjerbh1XlnK/z4eqh557bLiEzK5mBMOh9sOHhRgii9HlxWkQzVz0PNzOFdmTO6O33qUSHofGV6L4bPNh3m+x3W7S9v3zbBZnnqxnQ6JZcb3l5HSm4RC6cOYs6YHoT6upOQWcBnmyNYte0E+07/wvIHpjC5Fol5f9hpXYXSMdibQZ1aVdtufO+2jO/dttIxtZMDVw/pzKBOwYx/+ntyNFqW/LKPL++/8sKepBBCCNGMNXxqeSGEEKKF8lA7M6BDMF8vvIphXULIKyrl2e93NFj/bi6OFf++4/K+NtvcdUU/AKJT80jLK2qwx65OeQBFoYBJ/dszY1iXegVQmoIfd57kme+2A/Ds7JEXvRSw0WRm3nu/kZBVyGPXDuWZ2SPp3MoHV2dHurfx5/07JjJ3XE/0RhOPr/wXnaFq5adzleqNrN8fDcDsUfVPKBvi68FtE/sAsOVoPGazpd59CSGEEM2dBFGEEEKIBqZQKLhuZDcAtp9IIq+sUs+FCj5na1B1yU47tTp7PC238YMonyy4ghHdQgH4bnskV774I0MXf8276/eTmqtp9MdvKBsOxvDAF39hscDCqYN4cOqgiz6Gf44lcCY9H4UC7iwLhv3X3ZP6A5Cco+FYQlaN/W06HEtBiQ6FAq4v+32srwEdggDrFrbcIu0F9SWEEEI0Z7KdRwghhGgEoX4eFf+OzyzA55ySufXVta65KBQX/JDndf2o7lw/qjtxGfl8tz2SH3ae5Ex6Pq+s2cNrP+1ldI/WzBndg6sGdcTV2bHGvlJyNFz+3Op6jWP60C6VtjfVxT9HE7jz402YzBZuvaw3z8y+uHlQykWn5gHg567G3cXJZpuwAM+KfydmFda4Rae8Ks+Ibq1p7e9ZbTshhBBC1J4EUYRo5g49OhRdTjI9Fq/Bq9uIBumz4NRuIt+8Dme/1gxYsq9B+hSipTl3K41jDRVp6mJY1xCcHVXoDCZi0vNsJviMTsur+Hcbv4s3cW4f5M1T143giZnD+edYAqu2nWDz4biKikEeaieuHtKZG0Z3Z1jXUJt9mMyWahP8nk9hia5e1+2NSmH++7+jN5q4bmQ3ltwyvl79NARlWdArt6gUrd6I2qnq27SUnLOre9zVtgMtAFkFJWw9lghYKxddqEOxGYB1S5mvu/qC+xNCCCGaKwmiCCGavcLo/aRu+oyi2HCMJRqcfVvh028SoVc9gKN77cuA/pehKJeUDR+RG7EZfW4aDq4euHcYSMjke/DsPLgBn4G4FP1+IAawJuc8d4vNhfBQOzOpX3vWH4jhiz8jmDKwY5U2X/wZAUCfdoEE1LPSzYVQKhVM7NuOiX3bkaPRsmbXKb7fbq3cs2rbCVZtO0H7QC/umtSvypaVsABPsr9ZeNHGeiQ+kxvfWU+J3sjUQR356K7LUSguwvKdavQMsyYgNlssfLftBLfbyHvzzb8nAGsOmv7tg6rt6+c9URhNZlydHJg2pFONj2uxWGp83ml5RSz/+ygAE/u0Q6m032skhBBC2JsEUYRo5pwD2qJwdEbp1HCfDCqd1LgEd8TJO7jB+mws6Vu/Jm7V02Axg0KJysWN0sx40v5cSs6B9fR6/Fec/VvXud/SrAROvHEt+rx0AFRqDwyaXPIiNpN35C86zHuNoLFzG/rpiEtASo6Gd9cfYMvRBADmju2Jy39WFBiMJgrPKY1cXHq2hG2O5my+CWdHVZVtHY/PHM7miDh2RCbz5DfbqpQ4Phhj/Z1dPGNotWPU6oyVHue/HJRKvNwuvGSwn4eauyf35+7J/TkUm8532yL5Ze9p4jILWLXtRLV5Py6G6LQ8Zi/5lcISPRP7tOXz+65Epaz9iqESnQGt/mxi1/IEuzqjqdJr6+7iiLNj5Z+//7z3garVnUZ2D6VziA/RqXm8sHonRrOZG8f0wEPtTI5Gy+ebI1i6+TBg3b5UU5CsfCvPVYM7Vbs1qFxStoa7PvmDm8f3YlyvMEJ8rVvRtHojW47E8+x3O8jRaFE7OdT4eyWEEEK0BBJEEaKZ67n4xwbv06NDf/q/sr3B+21oRfFHiPvuGbCYCRx7E21nPYWDqxfFicc5/dk9lGbEEvXpXfR+ekOdPl22mM2c/uQu9HnpuAR1oMvdn+IW1gtjSQEJP71C5rZVxK16Cvd2/XBr26sRn6Fo6p78dhsv/bir4vsirZ6ScybW43qF8eycUVWu2xedxvRXf65yPCWniK73fl7x/ZxR3flowRWV2nQJ9eWju67gvqV/8vmfEXz51xG83JwpKNZhtlirpjw5azhX1lD+9qON4Xy0Mbza873C/Pn3lZuqPV8fAzoEM6BDMC/fNIbfDsRw6Ex6g/ZfVx/+fpDssmBHeGwG/RYtr7btVw9exZAuIZWv3xDOm79U3e74y97T/LL39Nl2/wmU1ESlVLL8/inMfOMXMgtKeOrb7Tz17XbcXZwoKj0bdOvbPpC35k+otp9TyTkVSWdn1zKh7MGY9IoAnNrJAbWTAwUlOkxllXi83Zz57J7JdGvtV6v+hBBCiEuVBFGEEM1W0q9vgdmER6fBdJj3RkWgxC2sF13vX8aR5yZSHH+E3MOb8BtwZa37zQ3fQHHicVCq6Hr/clxDOgPg4OpFh3lvoE2JQhNzkKT1b9PtgRWN8txE86DR6tGcs6LEQaUk0MuV3m0DmDWiGzOHd22UrQ8zhnWhS4gPH24IZ+fJZHIKtfh5uDC4cwgLJvVjZPe6r766WFycHLhuZLeK6kX2cm6Z3vNVT9KbzI09nArd2/iz87W5fPnXEf6MiONMej4lOgM+7i50b+3HNUM6M298L5wcVNX2Ub4KpZWPO2N6hp33MQO8XHl17lj2RadyIjGb7MISCrV6PNROdAz24bI+bZl/WW8CvdzO25cQQghxqVNYLBbL+ZsJcWk5dOgQAwcOpPezm3Bv29vewwHAqNWQ/Nt75IZvQJ+fiaOnPz79LqfN1Y+Qd+Qvzqx4GM+uw+n56E+VrqsusWzmzh8qXZNz6A/S/vyCkuRILGYzbmG9CL3qfnx6V/00szkkljUW53Pwob5YTEa63LMUv0FTq7Q5+d488o/9g+/Aqyp9un8+UR/fSe6hjXj3uYzuC1dWOZ9z4DdOf3Y3CpUjg947goOr1wU9l4ZQlHCMYy9OJjw8nAEDBth7OHZT/re95aUb6Nsu0N7DEaLFOxKfyWXPfN/i701CCCEuHQ1TLkAIcUEMmlyOvzKNtM2foctOQqFUYCzOI+Ofrzj28lUYi/PO30kNkta9zemP70Bz5iAAZl0xmuh9nHr/ZrIPrG+Ip3DRFUbvx2IygkKBV/eq2yUAvHqMtraN2l23vsvae5dd/1+e3UeBQoHFZEATvb9OfQshhBBCCCGaL9nOI0QTEPftE2jTonFw86bjre/g0/dyFEolBad2EbNsEcm/f1DvvosTT6CJOUDYrKcIHnczKrU7upwUYpY/ROGpXcR//xx+A6agUDWv24E2zVr5xNEzEAc3b5tt1K2s23CMRXkYNDk4epx/L7+hMBtjcX7Z9V1stnF098HRwx9DYRYlaTH49L287k9ACCGEEEII0ew0r1mTEJcgbfoZcg7+DkCnOz7Ap89lFee8uo2k2/0rOPpS7fN5/JdJW0joVQ8SeuW9Fcec/ULpfNfHHHp0KIaCTAqj91faCnQhyrcX1VVdtw4ZCjIAcPKufsvGuef0BZm1CqLoy/oFcKyhb0evQAyFWRgKMmszXCGEEEIIIcQlQIIoQthZbsSfgHXVxLkBlHJubXvh1X0kBZE76tW/QuVI6JX3VTnu5BWAe/u+aKL3o0093WBBFAcPP8wGXb2uqwuTzlpVQ+noUm2bc8s+m0uLa9WvWVdy9voa+lY5q8vGUbt+hRBCCCGEEM2fBFGEsLOSpEgAPDoNrraNR6ch9Q6iOPu3RqV2t3nOyTsYAGNJQb36tqXPMxsbrC8hhBBCCCGEaEoksawQdmYoygVq3jri5BVQ7/7LAyW2KB2dAawJWpuZ8pUgZkP1pUnNem3Fv5UutSvNqXR2PXt9DX2Xr4RROUvJTyGEEEIIIVoKCaIIIZolR68gAPT51eckMRRkVfzbqaz9+ZzbzlBT34VZdepXCCGEEEII0fzJdh4h7MzR3ReoecKuPycY0NQdfWkK+tzUOl/n5BtSp61A6ladADAUZmIsKcDB1atKG21aNAAO7r44evjWql9HT38c3LwxFuejTYvGu9fYKm2MxfkVQZTycQghhBBCCCEufbISRQg7c23TAwDNmYPVttHEHLhYw7lgRk2OtWpNHb+Mmpw6PY5n5yHWsswWCwWRO222yS/LI1PXpLmeXa3tC07azkNTcHInWCwoVI54dB5Sp76FaEj9H1qO/7z32Xmy7hWxqrPzZDL+896n/0PLG6xPIYQQQohLhaxEEcLOfPtdTuKal9Gmnibv2FZ8eo+vdL446YR10t5M1KVM8YVwcPPGq+dY8o9uIe3vZfgOnIJCoag4r02LoeDENgD8hk6vU9/+Q68h99BG8o//izYtptJqE4vFQtrfywDw7j0eB1fPC38yQoh62xuVwscbD3EwJo1CrZ4QX3euHNCRh64ejI979RW2qnM6JZf1B6I5dCaDmPQ8sgtL0OqM+Hqo6dsukDmju3P1kM4Nfm3/h5aTlK2p1RjXPTmTkd1b1/m5CSGEEOLC/Z+9+w6PssoeOP6dmpn03hMChN57VywooFiwoLtrQVTsBVddXXXdnx17r1hXAbsUkWah904gJCQhvSeTZDJ95vfHhEBMYRISJuD5PA/Pk7y3vOcdQsic3HuurEQRwsv00cmEDpsKQPpHd1O+awUupxMAQ+pGUt+8CZU+wJshdloJlz4AShXVaZvJ/N8j2GurAHfiKfXtWbgcdvySBhE6ZHKjsenz7mPjrDj2z72yUVvo0Kn4JfbH5bCT+vYsjDn7AbDXVpH5v0eoTtuCQqUm4ZIHOvYBhTiBpMggkmNC8NW23+9EfLVqkmNCSIpsvEWus/l41R4ueeY7lu3IoKzajFatIrPIwDvLdnD2v78kp7Sq1XMu3prO899tYsWuTDIKK3E4XKhVSooqjazYlclNb/7M9a8twWp3tOvYsAA9kUG+zf45+nesVavoE9+6I+GFEEII0X5kJYoQnUC3656nNi8Vc+FhUt+ciVKrA4USp6UWXWQS8Rfdw5FvnkKh1no71E7FP2kQXf/2FJlfPkbR719Q9MeXqHR+OEzu3+ZqQ2Loefv7DVaoeEKhVNLzjg/Y/8J0TAXp7HnyAlT6ABxmI7icoFDS9e/P4Nelf0c8lhAe++GRK9p9zqHdo9k09/p2n7e97cwo4pEvfsfpcnH9Of35z4zxBPn5sPdICTe/9TOHCyuZ+cZSVv73mlZ9D+iTEMYTM8Yxrnc8PeNCCNC7TzErKK/ho5W7eX3JNn7efpjXF2/jwctHtdvYVf93bYtxXfjkQrYfLuT8QUmEBug9fh4hhBBCtC9ZiSJEJ6AJCGPAv5cQc8FsfMLicTmdqP1CiD7vJvr/e4m79gfI1pEmRJ9zA/0e/o6QwReg9g/BabPiE5lEzAW3MvDJlejCE9o0ry6iCwOfXEnMBbfiE5mE02ZF7R9CyOAL6ffw90Sd/Y92fhIhRGu88P0mHE4Xo3rG8PLMcwnycycsBnSJ4PP7LkalVLArs5iftx9u1bxTh3XnnouHMyw5uj4JAhAT6s/jM8Zx9bjeACxYm9KuY1uSXlDB9sOFAFwzvk+rxgohhBCifclKFCE6CbVvIEkzniBpxhON2ozZewH31p8/a64GSeT4GUSOn9HiPZNnvUbyrNcaXQ/qPZYx8/I8iLpzCOwxksBWFnht7tmPp/EPJWnGf0ia8Z+TiE6IE6s2WXjpxy0s3pJOkcFIRKAvFw7pykPTR7NiZyZ3f7iSsb3jWPTvhtvPjtbR+PHRKxh/XI2M+WtSGoxZui2dd3/Zyf7sUpwuFwO6RHDftBGcPyipUSzrDuRy2bPfkRAewM5Xb+roR2+TSqOZ3/dlAzD7wiGNVpr0igvjnAFdWLU7i+82pHLR8PY7RWtw1yi+Xn+QokrjKRv79boDAIT665g0OKnV9xVCCCFE+5GVKEJ0cpayPMq2u4/+Deo7wcvRCCHaW1m1iQuf/Jq3f95BdmkVSoWCihoz81bt4YL/LKC8xnxS87/w/SZueH0pW9MKADCabWxKzefal3/ix82H2uMRTrlNqfnYHU4UCjirX9Orzc6uu96eJxcBbKl7HRMjWl8zpi1jXS4X32w4CMD0Mb3QqFWtvq8QQggh2o+sRBGiEzCXZJO39E0iJ1yDb0JfVFo9TrsNw4G1ZH71OE5LLX5JgwjsOerEkwkhTisPffobh/LLCfHX8frN5zN5SDeUSgVrU3K464MVvPLTljbPvS+7hC1pBTwxYxwzzxtIgF5LbmkVd3+4krUpuTz6xR9cPDwZter0+p3KofxyACKD/Aj2a/oEnp5xoQCU15gpraolPNC3zfczmm0cKTHw6eq99YmnmycN7PCxAOsP5tWf2nP1+N6tjFwIIYQQ7U2SKEJ0Ai67leK1X1G89isAVL7BOC1GXA4bAJrgaHrc/IY3QxRCdID0ggp+2pIGwDuzL2DS4K71bRP6JvDFfdM4/4kFbZ6/qtbKnEtGcM/Fw+uvxYcH8v4dkxly/ycUG2rZdCi/wVagk9GaY3qP19qtQ0e3w0QF+zXbJyroWFuxofVJFLvDSfSNbza67qNRce/Fw5l5XvOJkJMZ+2dHt/L0jA1laLdoj8cJIYQQomNIEkWITkAbGkuXqx6nct9vmIoysVWXoVBr0cckEzLwPGIumI0mINTbYQoh2tmyHRmA+w3y8QmUowYmRTKhbzx/7M9p0/walZK7j0ugHBUZ5MeQrlFsOpRPam5ZuyVRwgL0WGyNj+/1ZFxr1FrsAOi1zW9t0fsc+xHHaLa1OiaFAiKD3IkXQ60Fi82BUqHgjilDuXnSoBZP/DmZscczWe0s2pIOwAxZhSKEEEJ0CpJEEaITUPn4Ejv5NmIn3+btUIQQp9D+7BIARvaMabbPqJ6xbU6iJEQEEqBv+mj06BB/wP0mv72c6Jje04lKqSTlrVsAcDpdZJUYeHPJdl5dtJUFaw+w4J+X0C8xot3HHm/ptnRqzFaUCgVXjZMkihBCCNEZnF6boIUQQogzSHm1u2hsS9tSIltoO5HoFsbqNO5VHDaHs83ze4tv3SoTk7X5VS+mutUqAH46zUndT6lU0C0qmFdnncddU4dRUFHDHe+twOl0dejYr9e5C8pO6BtPbGjAST2DEEIIIdqHJFGEEEIIcVo5mnRq6ajgYkNto/7tYVZdUdj9OaXszirusLGFlUb+2O8+xnnG+D5tiFQIIYQQHUG28wghhBBeEhrgPlmmxWRAC22dzflPzCe/vKbV42JD/Vu1FahnrLtGVLHBiMFoIcjPp1Gfoyf4hAXoW11zpSXHr+45UmJgSLeoDhn77fqDOJwu/HQaLhqe3LZghRBCCNHuJIkihDhpG2fFATDkhU3owhO8HI0Qp49+iRF8uyGVrWkFzfbZ0kJbZ1NWbWqwAsRTPprmC8Q2ZXSvWNQqJXaHkzUp2Uwb0aNRn6OrONqraO5R2aVV9R/7+bRum1Brxn6z3r2VZ9rw5JPejiSEEEKI9iNJFCGE6EDGI/so/O1TDAfWYzUUo/LR4xMaR2CvMUSfNxNdRBdvhyi8aPLQbvx3wTpS88pZvSeL8wYmNWjfd6SENW0sKusNrTmm+GQE++k4Z0AiK3dl8f7yXVw8PLnBiTdp+eX8ttedRJk+pmer5rY7nKhVze92fnfZTgDUKiXDkxsWBD6Zscfbe6SE/TmlAFwtW3mEEEKITkVqogghRAfJXfwae56eSvHa+VhKs1FqfHCYqjFm76Ng5YdUp2/zdojCy3rEhDBthHurxu3vLueXHRn1BUfXH8jlutcWN3u6zl/dQ5ePRqVUsCk1nwc//Y2qulOG9h0p4frXl2B3OBncNZKpw7o3GnvX+ysIv+51Lnnm20Zt4/71BfNW7uZIsaH+msvlIiWnlLs/WMGnv+4FYNb5Awnx17Xb2OMtXHcAgPiwACb0bd+VNEIIIYQ4ObISRQghOkD+8vfI+fFFlD6+JFz2IBFjr0TjH4rL6cBSlkv5zuX4hMmbIwEv3ngOB3LLSC+o4B+vLkavVaNUKDBabHSNCuL+S0bw5IJ1rd7ycqYb0i2K566byL8+/51Pf93L57/tw0+nodpkBdx1Vj6++6IGK1Q8cbiwkoc//x1wbzPy12kxmq2YbcdOArp6XG+evGZ8u449yuF08v3GVACuGte71fELIYQQomNJEkUIIdqZqSiD7O/ngkJJ73s+I6j32Po2hVKFLqILsRfc6sUIRWcSHujLiidn8NKPW1i8NY2iylrCgvT87ay+PDR9NF+vd69KCPRtXDz1r+6m8wfSNyGMt37ewba0AqrNVrpGBjF5WDfmXDKyxdUezfni/mms3Z/D5rR8CiuMlFeb0KpV9IgNZHj3aK6Z0JdxzdRZOZmxR/22N7u+roxs5RFCCCE6H0miCHGSnDYLhb9+StnWxZgK03Fazaj9Q9AGRxHYayyR467GN753g/7lO3+hYvcqjDkpWCsKcNos+IREE9T3LGKn3NFkcVZzaQ47Hx4NwJh5eVQf3k7uktepydiBy27DL2kgCZc9RGCPEQDYjZXk/fw2ZduXYq0oRBscScS4GcRNvQulWtPi3FWHNpP381vUZO7EaTWjj+tFzLk3EjH2qja9RlZDCQUr3qdiz2ospTmgUKCLTCJs2FRizr8Fld6/0Ri7qZqCFR9QvvMXzMVZuBx2NAGhaENiCeo7gcgJ13baIrYFKz/CZbcQPnp6gwSKEM0J9PXh//42gf/724RGbXuySgD31p8/a64GybVn9eXas/q2eM+3Zl/AW7MvaHR9fJ94Sr+415OwO4XRveIY3SuuVWOae3aAKUO7MWVotzbFcjJjjzp/UNJp9foLIYQQfzWSRBHiJDjtNlJevobqtC3uCwolKn0gtqpSbIZijEf2olCp6XLlo/VjDClrSHv/jvr+at9AcDowF2dhLs6idMtP9Ln/SwK6DWn2vuU7l3Po3dm4nHZUOn8c5hqqDm4g5aUZ9J3zFfqYZPa/eBWm/EMoffzA5cBSmkPuTy9hLc+j+40vNTt32dbFHPrgTnA6UPkG4bRbMWbuIn3efVQf3kG3655r1WtkSN1I6luzcNS6awQoNDpwOqjNSaE2J4XSzT/S94GFaEOi68fYaw3se/YSTAXp7gtKFSpdANbKIqwVhdRk7EAbEk30xOtbFcupUrZ1EQBhI6Z5ORJxusstrWLJVve/g7P7J3o5GiGEEEIIIUkUIU5C6eYfqE7bgjogjOSZrxDcfyIKlRqn3YalLIfy7ctQ+wU3GKPU+RMz6RbChl+MX5cBKDU+uJxOavNTyfn+eSp2ryL9o3sY/PQfKJRN135On3cfkeNnkHD5w2gCQrGU55H2wd1Up20ma+F/0YbGAtD/0UUEdB+G02amYNXHZH/7DMVr5xN93kz8Evo1Offhzx4iZMA5dP37s/iExWE3VZO/7B3ylr5B0e+fE9hzFOGjLvPo9TGXZJP65kwc5hpiJt1M9Pk3u+uAuJzUZO0ha/7j1GTsJO2je+j34Nf14wpWzsNUkI4uMonuM18hIHkECqUSp82CuSiT0q2L0AZGehTDqWYqysBeUwGAX2J/ynetIH/5+9Rm78PlcqGP7k74qEuJPvdGlJrWbzUQZ54jxQZeXbyVf5zdj36JEei1amx2B3/sz+GRz3/HaLExuGskY1q52kIIIYQQQrQ/SaIIcRJqMtzHVcZeMJuQQefXX1eqNeijuhE39c5GY4J6jSGo15gG1xRKJX7xfeh5x4fs+e9kTPmpVB1cT1Dfxkv7Afy7DqLb9S/Uf+4TGkePW99ix0MjMR7ZQ23uAQY/swZdhPs310qNjrgpd2DY/weGA+so3/FLs0kUn7A4et7xUf2WH7U+gMTpD2OrKaP4jy/J+ellj5MoOT/MxWGqJuGyB4mfdt9xD6wioNsQ+tz3P3Y9cR5VB9dTnbGzfvVNTab7dU24/CECe46qH6bU+OAb35vE47ZHeWr/3CupSt3Y6nHg3uLkKXNxVv3HJesXkvOje9WPyjcIl6UW45E9GI/soWzbEvrMmY9aH9CmmMSZw2p38L/f9/O/3/cDEOzng9Fsw+ZwAhAd4se7t13ozRCFEEIIIUQdOeJYiJOgqnsDbDUUtct8SrWWoL7uUxuqM3Y02y928h2NrvmExqKL7Aq4t5EcTaAcL6iPe+7avNRm54654NZGNVMA4qbcBYC5KANj7oEWnsLNYTFRtm0JCpWG6PNnNdlH7RdMyIBzAKg6sK7+ukrnrpFiMxSf8D6eUvsFowmMaNOf1nDUVtd/nPPTywT2HsvgZ9cy8s0URr59kK5/fwaFSk1Nxk6yvnq83Z5PnL5iQwN48prxnNUvgfiwAMxWO1qNir4JYdw3bTh/PPN3esSGejtMIYQQQgiBrEQR4qQE959I/rK3KVz9MfaaCsJHX05g8sgmC6Uez1ZVSsGqeVTu+x1zcRYOcw24nA36WFtIIPjG9WryuiYwHHNRRrPt6sBwABymqmbnDvzTKpmjdBGJaEPjsJbnUZu9D7/4lk+NMB7Zg8thA6WKXY82vaIGwGExAmApz6+/Ftx/ImVbF3Hk22cxFWUSNvwi/LsNRaXVt3jPlvS686M2j20N13F/j2rfIHrdOc9d9wb3iqDoc2/EUp5P/rK3Kdn0PQnTH8YnJOaUxCY6Jz+dhrsuGsZdFw3zdihCCCGEEOIEJIkixEkI6j2W+EvmkLvkdUo3fU/ppu9BocQvoS8hgy8gauJ1aIMa1u4w5h4g5cWrsdeU119T6QNRatzHlzosRpyWWpyW2mbvqw2OavK6QqkCaHb1hELhXnzmcthbPffRNmt5Hrbqsmb7HFW/OsfpwFZVcsL+Tqup/uOIcVdTnb6V4rXzKfrtM4p++wyFSo1/18GEDplC5Fl/q09MdDYqnV/9xxFjr2wyzphJN5O/7G1wOqhK3UTE6MtPZYhCCCGEEEKINpIkihAnKeHSB4gYcwWlW36iKnUT1Ye3YczehzF7H/nL36f33R/Xb6MBOPzJA9hryvGN70PSNU/i331YgxUW2T/MJW/J6+ByeeNx2o/THb82JJphL21v1VCFQkH3G18i+rybKNu2hKrUTdRk7qI6fRvV6dvIX/4efR9Y0ODo6M7i+CSULqrpo061QZGo9AE4TNVYKwpOVWhCCCGEEEKIkyRJFCHagS4yifiL74WL78Vpt2E4sI7s756lNieF9Hn3MnTuFhRKFZbSXIxZuwHodfcn6MITGs1lqy491eE3YK0sajKuo20AmoCwE86jCXJvHbJVleG0WepX2rSGX0Jf/BL6AuCwmqjcvYoj3z6DpTSHw589yIB/L/Z4rtS3b6Y6fVurYwAY/uouj/vqY3qAQuF5EkyhaFNMQgghhBBCiFNPkihCtDOlWkPIgHPQR3Vl5yPjsFYUYi7OQh/dHWule9WB2j+k2URF1cG2nSDTXqoPbWoyNnNpDtZy9yk1von9TziPf5dBKFRqXA4bhpS1DU4vaguVVk/YiGmo/YJJefkaajJ34bCaPK6TYjdWerSt6GSpfHzx7zqEmowdmIsymuxjrSzCYXIXoPUJk2NrxZkt/LrXAdjxykwSIzrnNjwhhBBCCE9JEkWIk+C0W1GqtU22KTW6Y/1sFgBUOvdpPnZjJbbqskYrOko2ftfsG+9TJX/FB4SNvKzRCT35y94BQBfd/YRFZQFUen9Ch06hbOtisr9/nsDe41D5NJ3wcFhNKBTK+tUqLb6u2rrX1eVssbbLn/V76FuP+56siDFXUJOxg5IN3xJ/yQON6qIUrJoHgELtQ1DvcacsLiGE95VVm1iXksuuzCJ2ZhSxO6uYapMVgNIv7m31fPuzSzjviQXY647ElmSVEEII0bHkiGMhTkL6R/eS/skDVO5fg8NsrL9uKkwn/ZM5gLsmyNHTcvSxPdEERYHLRdoHd2EpzQXcxwEX/vophz99ELVf8Cl/juNZSnM59O5sLHWrThymGnJ+fImi3z8HIOGSOR7PlXjFo6h8g6nNPcD+F6ZjOLAOl9MBgMvppDYvldzFr7HzX+ManEaU8tI1ZM5/gqq0LTht5vrrNUf2kvnlYwD4dxuKuu6I6c4m8qy/oYtMwm6sJPXtmzEVZQLuZFrhr59SsOIDAKLPvcGjrVFCiDPHN+sPMuutn3lz6XbWHcitT6C0hcvl4p+f/FafQBFCCCFEx5OVKEKcBKfNQtnWRZSsWwAKBSp9EC67GafV/cZfqdWTfNNr9afmKJRKkmY8QdqHd2FIWcOOh0eh0gfitNbictgJ7DWGgOTh5C1902vP1P2GuRz64E4qdq9ApQ/CYa6GusRH1MTrCR91mcdz6SIS6XPf56S+NQvjkT2kvDQDhVqLSueHw1TjPgK5joJjtUEc5moKV82jcNU8UChR+wbisNTisrvfbKj9Q+l2w9z2eeAOoFRr6XX3p6S8eBVVB9ez69HxqHyD3X/Pdc8QPPA8Eq94xMuRCiFONYUCYkP9Gdw1isFdI1GrlPzfwvVtmuuL3/ezNb2Aod2i2JFR1M6RCiGEEKIpkkQR4iQkXvEIAcnDMRxYh7k4C5uhCJfLfSpLUN8JxF44G11ElwZjwkddhso3iLyf38J4ZA8upx19TA/CR08nZtIt5C19w0tP4xY2Yhr9giLJW/omNZk7Uaq16ON6EXPujUSMvarV8wV0H8bgZ9ZQ+NunVOxagangMPbaKtT6AHRR3QjsOZqwEdPwCY+vH9P9xpeo2L2aqtQNWEpzsBpKUChV6OJ6EzLgXGIvnI0mMLw9H7vd+cb2YND//Urez29RsXsFlvIClBodvl2HEDl+BhFjr0KhlMWAQvzV3DxpELMvHFL/+abUvDbNU1Zt4qmv1xMT4s8Dl43k7694XmhbCCGEEG0nSRQhToJvbA98Y3sQN+WOVo0LGXAOIQPOabIt4dIHSLj0gUbXdeEJjJnX8g/bJ6r7ETl+BpHjZ5wwvsCeowjsOeqE/Y46UVxq30DiL7qH+Ivu8Wg+/6RB+CcNAjzfOtQZaQJCSZrxBEkznvB2KMJLLDY781bt4cdNh0grqMBstRPiryM6xJ/xfeK5dkIf+iSEN+j/8/YMlu/MYH92KfnlNVhsdmJC/ZnYP5G7LxreZL2L7JIqhs75BHDX1diWXsDLP21he3ohVruTwV0jeeTKMYzqGQtApdHM64u3sXhrOgUVNUQF+XHtWX25b9pwNGpVi3NvTM3j9UVb2ZFRhNlqp1d8GDdPGsSM8SeuldSUYoORd37eycrdmeSUVKFQKOgaFcTFI5KZfeEQAvSN6yNVmyy8s2wny7YfJrPIgM3hJCxAT1yYP2f3S+TvZ/frtHVBVO2UPP3PV2upqDHzwR2T8dM1XUNKCCGEEO1PkihCCCFEB7DZHVzx/A9sOpQPgFKhINBXS2mViWJDLXuyilGrFDwxY3z9mN/3ZXPL28vq+wf5+eBwusgsMpBZtJfvNx7im4cuY2j36Gbv+/P2w8x682fsTif+Oi01ZivrDuQy/fnv+eahy+kRE8Jlz31Hal45fjoNDqeL7NIqXvh+E7ll1bx+c/Mnaf20OY1b31mGw+kiyNcHi93Bzowi7nx/BdvSC3jxxnNb9RqtP5DL9a8twVDrLr6t06hwOl3syy5lX3Yp321M5ft/TScmxL9+jMFoYfL/LSQtvwIAlVJBgF5LYWUNBRU1bEsvJDrEj5nnDWxVLKeTDQfzWLDuAOP6xDN9TC/WHcj1dkhCCCHEX4YkUYQQQogO8N3GVDYdyic8QM8bt07i3AFdUKuU2OwOskurWLrtMMF+ugZj/HVabps8hEtH9mBgUgQ+GjVOp4uDeWU8/fUGVuzK5Pb3lrPxhetRKhVN3veuD1bwt7P78uiVYwkL0JNXVs3sd39hU2o+j3+1hrhQd0HmX/5zNcOTYzBb7XywYhf/t3A9X/6xn1smDaJ/l4gm577/41WcNzCJuTdMJD48kGqThTeXbOeVRVv5ZPVeRveK44oxvTx6fY4UG/jHq4upMVuZfeFgZl84hITwAJwuF7szi3nkiz/YfriQO95bzg+PXFE/7v3lO0nLr6BrVBBv3DKJUT1iUSoVWGx2Mgor+XFzGlFBfh7FcDqy2R089OlvqFVKXrh+orfDEUIIIf5yJIkihBBCdIDthwsBuGPqUC4Y3LX+ukatont0CPdcPLzRmHF94hnXJ77BNaVSQd+EcD699yLOfWw+B/PKWHcgh7P6JTZ53yFdo3h55nn1n8eFBfDBHZMZdN/H7M4sJiW7lE1zr6dLZBAAOq2aey4ezu/7slmzP4el2w83m0SJDwvgs3svqt/yE6D34dGrxlJabeLz3/Yx9/tNHidRnv12I9UmK49cMYYHLhtZf12lUDC0ezQLH7yU8Y/8j7Upuew4XFi/+mZH3ev66JVjGdMrrn6cj0ZNn4TwBtujPHXJM9+y4WDbapO05Vjik/HuLzs5mFfG7VOG0DteTvcSQgghTjWpaiiEEEJ0gKO1PIoqjSfo6RmtWsXZ/RMA2JZe2Gy/uy8a1uhabGgA3aKCAbh0VI/6BMrxzurrnjs1t6zZue+YMrRRzRSAe+sSQocLK0nJKW3+IerUWmws2pKGRqXk1gsHNdkn2E/HeQOTAFizP6f+ur/eB2i/1xUgxF9HZJBvm/6cSjmlVbz0w2aigv146PLRp/TeQgghhHCTlShCCI+K1gohWufcgUm8sWQ7H6zYRXmNmSvG9GJUz9gmC6Uer8RQy4crdrF67xEyiyqpMdlwulwN+rSUQOjdzEqMiEBfDhdW0qeZ1QvhgXqA+vokTRnbO77J610ig4gPCyC3rJq9R0roe4LVILuzirE5nKiUCkY9+Hmz/Yxm9zHoeeXV9dfOG9iFHzcf4v8WriejsJJpI5MZnhyDXtv2H2k+u/fiNo89lf71+e/UWu28fNN5J/w6EkIIIUTHkCSKEEII0QHG94nnwctH8cpPW/hm/UG+WX8QpUJBv8RwJg/txo3nDiAquGHtjpScUi5/7nvKqk311wJ9teg07v+ujWYbRouNWout2ftGBzddD+RoDZXIZuqFHD01xuZwNj93SPO1RqJD/Mgtq6a0ytRsn6OOJoEcThfFhtoT9jdZ7PUfXzOhD5sO5fPlH/v5ePUePl69B7VKydBuUUwd1p3rz+lPoK/PCec83fy8/TDLd2YyplccV43r7e1whBBCiL8sSaIIIYQQHeTh6aO5elxvfth0iA0H89iaVsDeIyXsPVLCO8t28MV90zirX0J9/3s+XElZtYm+CWE8/fezGdGj4QqL577dyMs/beFPC1NOO06n+wFiQvzZ+8asVo1VKBS8fvP53HrBIBZtSWf9wVx2ZhSxJa2ALWkFvLNsB989fHmbaqN0Zo9+8QdKhYInZoyjxmxt0Ga2Hksymaw2asxWtGoV2ia2XgkhhBDi5EgSRQghhOhAXaOCmXPpSOZc6j5ZZU1KDk8tXM++7FLufH8Fu16biUqpJKe0il2ZxQD87/5LSIwIbDRXSdWJV210pMIKY5NxHW2DY9uCWhJRV0uktKoWi82Oj6b1P470S4ygX6K7AK7JamfFzkz+u2Ad2aVV3P/xan75zwyP57rh9SVsTStodQwAKW/d0qZxrZVb5t7SNOX/vm6x37h//Q+ABy8fxcPTpW6KEEII0d4kiSKEEEKcIhq1ivMGJtEtKpgR//yMgooaMosMJMeEUFBeA0Cov67ZRMX6A7mnMtxGNqbmNRlbdklV/Zv8Ac2c7HO8wV2j3Mc9O5z8sT+nwelFbaHXqrl0VA9C/H2Y/vwP7DhchMlq97hOSkWN2aNtRUIIIYQQkkQRohMqXreQw5/MIbDXGPo99K23w+lU9s+9kqrUjQ2uDXlhE7rwhGZGnB5yfnqZ3EWvNLjWfeYrRI73/LfponOx2h3NbqfQHffm3mJzb8U4Wii0wmimtKqW8MCGJ798vf4ghwsrOyZYD727bAfTR/dsdELPm0u3AZAcE3LCorLgftaLhnfnp81pPPP1Bsb3icfXR9NkX5PVjlJB/WqVFl/Xuj5Olwu7w4GnP+Ys+veVHvXzppaOUl53IJfLnv0OgB2vzGw2CSeEEEKIkydJFCHEaUmlD0Cp0QGgUDZ9WrvDYiL/l3cp27YYS2k2Sq0ev8T+xJw/i5BBkzo0PquhmIJV86jYvQpLqft4Vm1INAHdhxEx7mqCeo1p+Dw+fmgC3b/BtxsrcTmaLxwqTg93vLcCPx81l4/uyfAeMfjr3EmStIIKHv3id8BdE6R33Wk5veLCiAr2o6jSyG3vLufVWeeREB5IrcXGgrUpPP7VWkL8dVTUmL30RJBdWsVNb/7M89dPJC4sgGqTlbd/3s4nq/cC7i0knnri6nH8sS+b/TmlTHvmW/4zYzzj+sShUipxOl0cyi9n6bbDfLx6D8ueuLo+MTD9+e8ZlBTJtBHJDO4aVZ+Q2p1VzMOf/w7A8ORoAvSds7is0+miwnjs77DKdKy+yfEFhTUq5RlZIFcIIYQ43UkSRQhxWkq65r8trtKw1VSw/4UrMOWnAqD08cNhqsaQshZDylriLr6XxMsf6pDYKvasJu3Du3HUGtz31rprRJgLD2MuPIxCqWqURImdfBuxk28Dml5tI04/FpudHzcf4ss1KSgUEOTrg8XmwFRXBNRXq+bt2ZPqT8VRKhX8398mcNu7v/D7vmyG3P8Jgb5aai127A4n4/rEM7JHDK8u2uq1Z3r1pvO59Z1l/LIzgyBfH6pNVhx1RWJnnjeAK8b08niuLpFBLPjnpVz/2hJ2ZxYz/fnv0apV+Os0VJusDU4JUiiOjasxWXl/+S7eX74LpUJBkJ8PRrMNq90BQFiAnlduOq99HrgD5JZVM3TOJ0229brjg/qPx/aOOy1WyAghhBB/NZJEEUKckQ5/MgdTfiqawAh6zH6HoN5jcVhN5C97h9xFr5C35HX8uw4mdPAF7Xrf6vStpL59Cy67hahzbiD2glvRRSYBYDWUYDiwFpfN2vIk4ozw+NXjGNEjhrUpOWQWGSiqNOJyuegeHczZ/RK5Y+pQkiKDGoy5Ykwvgv18eG3RNvZkFeNwuOgVG8oVY3tx++QhvOLFBArApaN6EBnsy2uLtrIjowgftYpe8WHcPGkQM8b3afV8w5Nj2DT3euat2s0vOzJJKyjHUGsh0NeH7tHBjOkVx6WjepAQfmx7yquzzmflrkzWH8wju8RAsaEWtVJB9/gwzh+UxB1ThtYXrhVCCCGEaG+SRBFCnHFqMndRsWsFAMk3v0FQ77EAqLR6Ei59AFNRBmWbfyTnh7ntmkRx2m0c/vSfuOwWEi77J/HT7m/Qrg2KIGL09Ha7n+jcesaF0jMulHsuHt6qcecNTOK8gUlNtj08fXSTJ64kRgS2WDMDTlz349qz+nLtWX1PGN+YXnGMeTDuhP2OOlFcgb4+3H/JSO6/ZKRH8w3pFsWQblEe37+z8eTvqrXG94lv9zmFEEII0TRJogjRAnNpDjsfdr9haal4qakok12PjgeFgqFzN+MT6n6DYSnPo3TTjxgOrMNccgRrRSFKjQ/62B6Ej7qMqLP/gVKtbVVMG2fFtRiP4eAGUl68Cp+weIbO3dzkHIaDGyj89VOqD2/HXl2GSu+Pf9Jgos65vt1XZnhD6ZafANDH9iK431mN2mMn3ULZ5h+pzT1AbV4qvnGeb0FoScXOXzAVpOMTFk/c1LvbZU4hhBBCCCFE59F0NUYhBAC68AT8uw0FoGzLomb7lW35EYCA5JH1CRSArAVPkv3dsxhS1mCtLEKp1eMwVVFzeDtZXz3OgVf+htN+6rZ2uFwushb+l5QXr6J8+1JslYUotTrsNRVU7vuN1DdnkvnV46csno5ytJ5IUN/xTbb7JQ1C5eveRmE4uKHd7lta9zUSOmwqCpXkqIUQQgghhDjTyE/5QpxA+MhLqcnYQemWn4ibemeTfUq3LK7re0mD6/rYnnTtPY7gAefgE56IQqHAYTVRuXsVWQufpCp1I/nL3iF+2n0d/RgAFKz4gIIVH6ANiSFx+r8IHTIZld4fh9lI6eYfOfLNUxSu/hj/pEFEjD09Cxq6XC5MBekA+Mb2bLKPQqFAH92NmoydmArS2u3e1Rk7APBL7E9tXiq5i17BcHADDrMRn7BYQgaeR+yUO9EGRbbbPYUQQgghhBCnjiRRhDiBsBHTyFr4X2pz9mMqTEcfndyg3Zh7AFN+KgqVmrAR0xq0JV72YKP5VFo9YSOmoQ2JZt9zl1H0x/9OSRLFXmsg56eXUPr40veBBehjjj2HSudH1Nl/R+UbQNp7t5P381utSqLk/PQyuYteaVNcfR/8pr5mSXtwmKpxWt3HhGpaSFZogtw1FWyGkva5r9WErbIQAFP+IQ5/9hAumxmljy8KpRJzUSYFKz+idPNP9JnzFX4JJ649IYQQQgghhOhcJIkixAlog6MI7DWaqoMbKN28iIRL5zRoL6urvxHYexyagDCP5w1IHoHKNwhrRQGWigJ8QmLaNe4/K9u2FKellrAR0xokUI4XNnQq6WofTAVpWCuL0AZ7VrxR5eOHJjCiTXEp1Zo2jWuO01J7bG6trtl+qrpjhx0WY7vc12Gqrv84b9nbaENiSZ71GoF1RxkbUtaSPu8+bIYiDr17K4P+77d2f3YhOkJHFEIVQgghhDhdSRJFCA+Ej7yMqoMbKNvaOIlSuvXoVp5LmxxblbaFot+/oPrwdmyGIpxWc6M+NkNxhydRqg9vB6Biz69su39ws/1cDhsAlvJ8j5MosZNvI3bybScd42nN6Tz2sctFj1vfIrDHsdNGgvudRfeZL3PwtX9gLsqkfMfPzX7NCCGEEEIIITonKSwrhAfchUI1mArSMOak1F+vztiJpTgLhdqH0KFTGo3LXfoG+5+/nNJN32MpOYLL4UDtF4wmMMK9ckPh/ifoOG71REexGYoBcFqM2KpKmv2Dy50MOLol5nSj9PGt/7iphNVRjrrnU/n4tc99dcfm8U3o1yCBclTIgHPQRXcHwHBgfbvcVwghhBBCCHHqyEoUITyg8Q8hqN9ZVO5ZTdmWn+rrWRzdyhM84BzUvoENxhhzD5Dzw4sARJ1zAzHnz0IX2RWF8ljucvs/h2OtKACXq8OfwVWXHIm76B4Spz/c4ffzFpU+AKWPL05LbX3iqClH2zTB7VPkVaXzR+njh9NiRB/drdl++ujumAsPu//ehRBCCCGEEKcVSaII4aHwUZdRuWc1pVsXk3jFI7hcLsq21W3lGdV4W0b59mXgchLYawzd/vFso3aX04HdWNH6QJQqcDpw2SxNNh9fm+N42sBwACzlea2/5wnk//Ie+cvfa9PYXnd+SEDyiHaLxX3yTneMR/Y2e/KOy+XCVJgBgG9Mj/a7b2wPjJm72mU+IYQQQgghROcjSRQhPBQ6+EKUWh2WkiNUZ+zEZbNgrShE6eNLyMBJjfpb605q8esysMn5ajJ2tLjdpDlq30DsNRVYKwqaLBBbk7W7yXH+3YZSsuFbDCnrcDnsKFTt98/fUbdFqC2cdlu7xXFUYK8xGI/spTJlXZPtxiN7cNRWuvu248lAQX3GY8zcVZ+gaYqp8DAAPmHx7XZf8dcyf00Kd3+4krG941j079PzKPKOcskz37LhYMNE8Y5XZpIYEdjMiDOfvCZCCCFE+5IkihAeUun8CBl4PmXbllC25SecdStBQgdfiMpH30R/fwDMRYcbtbmcTnJ+atuRwL5xvalK3Uj5rpUE9Z3QoM1urKR47fwmx4UNn8aRb57GZigib9nbxF/c/GkbdmMlar9gj2NKuPQBEi59wOP+HS185KUUrPgAU95BDClrG71OBSs/AsA3vg++sT3b7b4Roy4nf9nb1Obsp+rQZgJ7jmrQXrH3N8x1SZTgAee0232FEA0F6LXote4fcVRKRYM2p9PF+oO57MwoYndmMTszisgurQLgzVsmce1ZzR8/brHZWX8gj50ZRezMLGJnRhFFle4Tvn589ArG9+mY5Oia/dn8uiebHRmF5JZWU1pVi9PlIjrEn9E9Y7lp0kCGdotucmyIv47IIHetqGJDx9ffEkIIIc50kkQRohXCRl7qTqJsW1y/giJs5CVN9g3qO56CFe9TsXsV+cvfJ/rcG1FqfDCX5nDk6/+j6tDm+todrYph+MVUpW6kaM2X+CcNJGzkJSjVWmqydpPx+b9w2qxNjtMEhJJ4+UNkLXiSnB/mYqsqJWbSLegiEgFwmI1UH95OyYZvsBmK6fvPha2KqzPx7zqYkMEXUrFrOWkf3UuP2W8T1GsMTpuZvGXvUrrpewASLn+oyfE7HhqFpSyX+EvmtCo55Bvfm4gxV1Cy4VvSPryb5FmvEdR7LC6XC8OBtRz+xD2XX9IgQgY1Xr0khGgfz/7j7GaTIdUmK5c/932b5j2UX8HVL/54EpG1zWuLt7Fmf07954G+WmotdrKKDWQVG/h6/UH+fdUY7p3WeGvkZ/deXP9x+HWvn5J4hRBCiDOZJFGEaIWQgeei0gdgrXBv1VH5BhPcf2KTfYP7n0PwgHOp3PsrR77+P4588zQqfQCOWgMolHS77jnylr6JpZVJlMiz/kbx+q8xZu0mfd69HP70nyjUWpwWI9rQOLr+7f9I/+ieJsfGTLoFu9FA7pLXKFz9MYWrP3avmFGqcJiq6gvcBvYa06qYOqPuM19m/wtZmPJTSZl7JUofP1x2Cy6HHYC4i+8ldPAF7X7frv94DnNxFtXp20h58SqUPn6Aqz5ZpotMotftH6BQKFqeSAjRYfx8NAxIimBw1ygGd43kvwvWU1BR49HYIF8fBnWNZHDXSIZ0i+Lmt5bhcHZscfDzBiZxycgejOkVS5eIIHRaNU6niwO5pTz77UaW78zkqa83MDw5hnEdtBpGCCGEEG6SRBGiFZQaHaFDJlOy4RsAwoZNQanWNtlXoVDQ66555C19033EcVkeCqWK4AHnEnvhbIL6jCdv6Zutj0Gtpe8DC8hd9Apl23/GVlWC2jeQkLFXknDpP6nNO9ji+ITL/kno0MkUrP6EqtSN2AxFuOxWtCEx+CX0JajfRMJHNi6Ue7rR+Icw4LGl5P/yLmXbFmMpzUal88evywBizp/V7EoQl8OOraYcAL8uA1p9X5WPL/0e+o7CXz+hZOP37hooLie+8X0IHTqVmAtuQa0POKlnE0K0XaCvlswPbkd53DafF77b5NHYfgnhpL83+09J0GXtHGFjd04d2uiaUqmgX2IEn95zEWMf/oLMYgML1x2QJIoQQgjRwSSJIkQrJc96jeRZr3nUV6nWtlgvZOjczU1ejxw/g8jxM5qdV+0bSNI1T5J0zZON2oJ6j2XMvJZP4PFL7E/yzJdb7HMmUPnoSbh0DgmXzvF4TE3WbpyWWvSxvdq85UahUhMz6RZiJt3SpvHi9JBdUsXQOZ8ALRfqzCiqZOQ/P0OhgF2v3kRcmDuJlldWzXcbU1mzP4esYgMFFTX4aFT0ig1j+pie3HDuALRqVatiOrpdo7l41h3I5bJnvyMhPICdr97U5BzrDuTy8crdbEkvoKzKRIBey5BuUcw8byCThzZ/fPfpQqFQ0NaFYEpl51tBplGr6JsYTmaxob4+ixBCCCE6jiRRhBDiOFWp7t9Ix029U7bciBYlRgQyPDmabemF/Lj5EPdcPLzJft9vTAVgVM/Y+gQKwGNfrmHx1nQAdBoVeq2aSqOFrekFbE0vYMm2w3zz0GWtTqS0lcvl4on5a3l32c76awF6LeU1ZlbvOcLqPUe4ZdIgnrt+4imJR3jGbLWzN8t9OpqcuCOEEEJ0PEmiCCFOS4c/mcPhT9wrTIa8sAldeEK7zFt1aBM+4QmnfEtTzk8vk7uobSc2Ce+5fHRPtqUX8sOm5pMoP25KA2D66IYnQfWMC2Vu34mcOzCJLhGBKBQKTFY7K3Zm8tiXa1h/IJc3l2zngctGdvhzALz7y07eXbaT2FB/HrtqLFOGdSdAr6XGbOX7jYf4z/y1fLhyN0O6RXH1+D6nJCbRvEqjmZScMl76cTPZpVWolApuPLf1WxCFEEII0TqSRBFCnFbUfsFoAiMaXFMole02f5/7vmi3uVpD5ePX6LmUWp1XYhGeu3RUTx7/ci17j5SQVlBBj5iQBu0pOaUczCtDrVJyycgeDdoeuaJxAWe9Vs2lo3oQE+LH1Ke+4bPf9p6SJIrBaOGF7zbh56Phu4cvp0dsaH2bv07L9ef0J9BXy81vLeO1xdtalUR54ftNvPhD01sXT6Qjjw0+Hf2xL5srXvih0fWwAD2v33w+/RIjmhglhBBCiPYkSRQhxGml150feTuEDhE7+TZiJ9/m7TBEK0UH+zG2dxzrDuTyw8ZUHpo+ukH7D5sOATChbzzhgb4ezzuyZyxBvj7kl9dQUF5DTKh/u8b9Z4u2pmG02Lh0VI8GCZTjXTw8GR+NikP55RRWGokO9vNobj8fDZFBnj/78bSq9kuQngm0GhWRQb64XC7Kqs04XS6CfH148prxnDuwi7fDE0IIIf4SJIkihBBCnITpY3qx7kAuP25Oa5RE+bEuiTJ9dK8mx25KzePTX/eyLb2QokojJqu9UZ/CSmOHJ1G2pRUAsGp3Fn3v+rDZfja7E4D8smqPkyh3XTSMuy4advJBCsb0iiPlLXfBaqvdwe7MYp76ej13f7iSL9fs58v7LyHIz8fLUQohhBBnNvkVjxBCCHESpo1IRqNScii/nP3ZJfXXdxwuJLPYgI9GxUXDuzca9+qiLVz89Ld8uyGVrGIDdoeTEH8dkUG+RAb5oqwrbFxrsXX4Mxw91cVotlFsqG32j9PlcsfURLJHnFpatYoRPWL4/l/TGZEcw6bUfJ79doO3wxJCCCHOeLISRQghhDgJIf46Jg5IZOWuLH7YdKi+LsX3datQzhuYRKBvw9UBKTmlPPet+ySom84byK0XDqZbVHCDI3QH3juP/PIaXKfgGZx1N5lzyQgevWrsKbijaC9qlZIbzu3P1vQCFqw7wAs3nOPtkIQQQogzmiRRhDgD7J97JVWpG+k+8xUix8/wdjhC/OVMH92Llbuy+HFzGo9dPQ6Xy8VPm+tO5RnTs1H/JVvTcbpcjO0dx9wbG7/pdTidVNSYWx2HSqnA4XRhsTW9UqSq1tLk9Yi6miW5ZdWtvueJvLV0O+8s29GmsZ/ecxEje8a2c0RnnqNbq4xmGyWG2vq/TyGEEEK0P0miCCEEUH14OzUZO6nJ2k1N1m7MRRngchF/yRwSLn3A2+GJTm7KsG7otWqyig3sOFyI2eagoKIGPx8NFwzu2qh/QYV7+8zgrlFNzrc9vbDJ+ignEuTrQ3mNmYKKmiYLxO7OLG5y3LDu0Sxcd4A/9udgdzhRt2NBV6PFvUWoLawOZ7vFcSbLLj2W/PLTabwYiRBCCHHmkySKEEIAB179Bw5TlbfDEKcpf52WCwZ35actaXy/6VD9SpDJQ7vh69P4TW2AXgtAekFFozan08XcNh4J3CchnPUHcvllRyZn9Uts0FZpNPPF7/uaHHfpqB78d8E6iiqNvLFkG3Mubf5Y5UqjmWA/z4/ffnj6aB7+U8Fd4bkTJbUsNjufrN4DwIAuEU1+vQkhhBCi/UhhWSGEAJRaHf5dhxB1zg10n/kKfl0GejskcZq5fLR7285Pm9NYvCW9wbU/O6tfAgArdmXyzrId9UmX7JIqZr31MxtT8/Brw5vhS0YkA/D5b3v5et0BrHYHADszirjihR/qP/+zsAA9j1w5BoBnv93II5//zpFiQ317jdnK73uPcPt7y7npzZ9bHVdnU1VroazaVP/naMFco8XW8LqzcUWaSqO5QZ/m5vyz7JIqwq97nfDrXmfdgVyPY910KJ/Ln/uOnzanUVp1bEWP1e5gbUoOlz/3PXuPuAsaP3jZKI/nFUIIIUTbyEoUIYQAhr20DYVSVf956abvvRiNOB2dPyiJAL2WgooaAIL9fDh3YJcm+543sAvnD+zCqj1HeOKrtTw5fx0Bei2GWgtKhYIXbzyH1xZvxdjKk3muO6c/89emsCuzmDveX8G9H61Cq1FhNNuIDwvg2esmcsd7y5sce9vkIVQazbz80xY+XLmbD1fuxl+nRaVUUGWyUJdnYFyf+FbF1Bn949XFbDiY1+j6vz7/nX99/nv95ztemUliRGCDPuc89hU5pY1rx1z/2pIGn5d+cW/7BAusTcllbYo78eKn0+CjVlFlsmKv2+6kVat48prxTG3iFCghhBBCtC9JogjRSVUd2kzh759TnbYFW1UpKn0APuEJhAw8n8jxV+MTGufRPIbUjZRvW0p1xg6s5fnYaw2o/UIISB5GzKRbCOzR9LJ9p81C4a+fUrZ1MabCdJxWM2r/ELTBUQT2GkvkuKvxje/d8F4H11O4+hOqD+/AXlOO0scXTUAYfon9CR0ymfBRl57069JRjk+gCNEWOq2ai4Z1Z8G6AwBcNDwZrbrpryuFQsHn90/j1UVb+XbDQXJLq1GrlJw/sAt3TB3GWf0SeG3x1lbHoFWr+P5f05n7w2aWbE2n2FBLkK8PM8b14eErRnMgt6zF8f+6YgwXDU/moxW7WH8wj6JKI1a7i9hQf/olRHDuwC7Nrq4RLTt6jLROo6JXE/VqmjMoKZK3bp3Emv057MkqodhgpMpkxc9HQ1JUEOP7xHP9Of3pHh3SUaELIYQQ4jiSRBGik3E5nWQteJLC1fPqr6n0gTitJoyZuzBm7gKX06Nipw6zkZS5Vx43TwAKlRqboYjy7T9TvmMZ3f7xHFETr2swzmm3kfLyNVSnbXFfUChR6QOxVZViMxRjPLIXhUpNlysfrR9T+NtnZP7v2OcqnT9OmwVzUQbmogyqUjd26iSKEO3hrdkX8NbsCzzqq1WrWqwXsvPVm5q8fu1Zfbn2rL7Nzhvo68PTfz+Lp/9+VqO28X3iT7hCYkCXCF6/ZVKLfU53i/595Yk7NaO5v5cT2XDQvZLkb2f1a9XpOQF6LddM6Ms1E5r/OxdCCCHEqSNJFCE6mbyf33QnUBQKYi+8jZjzb0YbEg2AuTSH8u1LUen8PZtMoSRsxDQixlxJQI+RqH3dy9KtFYUUrJpH/i/vkDn/CYL6nYUu4ti2g9LNP1CdtgV1QBjJM18huP9EFCo1TrsNS1kO5duXofYLru/vsNRy5JunAYibehcxF8xGE+D+Tautuoyq1E1U7P21HV4dIYQ4PW04mIdapeSui4Z5OxQhhBBCnARJogjRidiqSsld8gYAidMfIW7qnQ3adeEJxF54m8fzqXz09LztvUbXtSHRdLnq39hrDRSv+ZLidQtJvPyh+vaajJ0AxF4wm5BB59dfV6o16KO6NYqrNi8Vp6UWfUwyiVc80qBNExBG2PCLCBt+kcdxAxgObiDlxataNeYoOZZYiL+2uz9cyd0frgSarmtyqjmcTrakFXDZqB6nPJZLnvm2yfovQgghhGgbSaII0YmUbVuCy2ZGExxN7IWzO/x+IQPOpXjNl9Rk7GhwXaUPAMBqKPJoHnVdf3ttNQ6LCZWP/qRjU6o1aAIj2jRW5eN30vcXQpx+Qvx1RP5pq4xKqfBSNMfHoCTzg9u9cu/O+poIIYQQpytJogjRidRkuleABPcdj0LVPv88nXYrxWu+omz7UmrzUnHUGnA57A36WCuLG3we3H8i+cvepnD1x9hrKggffTmBySNR6ZveRqSLTMInMglLcRb7np1G9Lk3EtT3LHQRiW2OOyB5BMNf3dXm8UKIv57P7r3Y2yF0OvKaCCGEEO1LkihCdCK2KvfJGVoPT945EbupmpSXr3EXo62j9PGtq2eiwGm34aitxGmtbTAuqPdY4i+ZQ+6S1ynd9L37uF+FEr+EvoQMvoCoidehDYqs769Qqelxy5ukvnUztbkHyPj8YQA0QVEE9zuLyPHXENir6eKZQgghhBBCCHG6kCSKEGew3MWvYczchUofSNd/PEtw/4lo/I8dg2lIWUvKy9eAy9VobMKlDxAx5gpKt/xEVeomqg9vw5i9D2P2PvKXv0/vuz8mqM/4+v4B3YYy5Ln1lG9fSuX+P6g6tBlreR4lG76hZMM3RE28nm7XPXdKnlsIIYQQQgghOoIkUYToRDSB4QBYynLbZb7y7UsBSLrmSSJGX96o3VZd1uJ4XWQS8RffCxffi9Nuw3BgHdnfPUttTgrp8+5l6NwtKJSq+v4qHz0RY68kYqz7+FBTYToFK+dR9PvnFP3+OaFDLiS4/0SPYq9O30rq27d4+KQNxV54G7GTPS/AK8Rf1dGio2/eMqnFY5OFEEIIIYSbJFGE6ET8uw+lZMM3GFLW4XLYT7ouirWi0D1v0qAm2w0HN3g8l1KtIWTAOeijurLzkXFYKwoxF2ehj+7e7Bh9dDLdrnuO2ryDVKdtoSp1o8dJFKfdhq2qxOP4juewGNs0Tggh2sLucDJv1W4WrjvI4cIKVEoFfeLDuP6cAcwY38fb4QkhhBCiHUkSRYhOJGzYxRxZ+F9shiLyl7/f6Cjh1lLp/bHXVGAqPIxvfO8GbabCw5Ru+q7JcU67FaVa22SbUqM71s9mOWH/48cc7e+JoN5jGTNPjuUUQnRuFpudq1/8ifUH3CsI9Vo1NruTzYcK2HyogD/2ZfP27AtQKOREHCGEEOJMoPR2AEKIYzQBocRdfC8A2d8/x5FvnqlfTQJgLs0h56dXKPz9c4/mO1qz5Mg3T1Gdvg2Xy4XL6aRi72+kvHxtg4TI8dI/upf0Tx6gcv8aHOZjqzpMhemkfzIHAG1INL5xvQCo3PMre5+9hKK187GUH0t8OEw15P3yLoYDawE8XoXiDQ6zEVt1ef0fZ90JRk6rqeF1u83LkQohOpP/LljP+gO5+Ok0fHz3VLI/uoPsj+5g7g3noFYp+Xr9Qeat2uPtMIUQQgjRTmQlihCdTNyUu7BVFlP46yfk//IO+b+8g8o3CJfDjrNum0r8JXM8mivhsn9Sue8PLKU57HvuUpRavTuRYjOjCY4m6ZonSZ93X6NxTpuFsq2LKFm3ABQKVPogXHYzTqsZAKVWT/JNrzWoh1JzeDs1h7fXtyvUWhy1hvr2qLP/0amTKJlf/puSDd80up7/y7vk//Ju/ed9H/yGoN5jT2VoQohOqqC8hk9/3QvAU387i0tG9gBArVJw0/kDyS+v5rXF23j5x81cN7EfPhr5sUsIIYQ43cn/5kJ0Mgqlkq5/f5rQYVMo/PVTqtO3Y68pR+0XjG9cT0IGTSJi3NUezaWPTmbAY4vJ+eFFDAfW4bDUog2OJmTgecRPu4/a/ENNjku84hECkodjOLAOc3EWNkMRLhfooroR1HcCsRfORhfRpb5/YJ9xJN/8BoaUNdQc2YetshCHuQZNYAR+SQOJOuvvhA65sF1eHyFEyzam5vHJ6j1sPpRPicFEoF5LQkQgFwzuyt/O6ktcWIBH86w/kMvirelsSy8gv7yGSqOFEH8dI3vEMPvCwYzu1fRR7BabnXmr9vDjpkOkFVRgttoJ8dcRHeLP+D7xXDuhD30SwhuMWZuSw0crd7MtvZDyahO+PhrCA/UM6BLJ1GHdmD6m10m/Lh1hybZ0rHYHIf46rpnQuPbJrRcO5o0l2ympMvHH/hwuGNzVC1EKIYQQoj1JEkWITiqo9ziCeo/zqG+/h75ttk0fnUzP299v+h6B4U3WHfGN7YFvbA/iptzh0f3V+gAixlxBxJgrPOrfGSXPeo3kWa95Owwh2szpdPHYl2v4YMWu+muBvlpMVjs7M4rYmVGE0+Xi4emjTzhXjdnKpc8eq5kUoNeiUSkpqjSyeGs6S7al8+KN53LjuQMajLPZHVzx/A9sOpQPgFKhINBXS2mViWJDLXuyilGrFDwx49jx6B+v2sNDn/1W/7m/TovFZudwYSWHCyvZcDC30yZRjtZBGd0zFq1a1ag9MsiPPvFh7M8pZV1KriRRhBBCiDOAJFGEEEKIM8Bri7fywYpdKBRw55RhzJ48mJgQfwCyS6pYvDUdf53Go7mUCgWXjurBjPF9GN0zlkBfHwAKKmr4YPku3ly6nUe/+IOJ/RNJigyqH/fdxlQ2HconPEDPG7dO4twBXVCrlNjsDrJLq1i67TDBfsdqMRnNNv67YB0A900bzu1ThhIWoAegtKqWjal5rNqV1R4vT4c4lF8BQK+40Gb79IgNZX9OKYfyy09VWEIIIYToQJJEEUIIIU5zJYZaXvlpCwCPXz2Oey4e3qA9MSKQO6cO9Xg+Xx8N8+6a2uh6TIg//7lmPJVGC1/8vo/5a1J45Mox9e3bD7sLYd8xdWiDVRcatYru0SGN4krNK8NosdEjNoTHrm648i480JdpI3owbUQPj+MGWHcgl8uebfrksRN58PJRHq3UOaqo0l2nKirYr9k+UcG+ABQbatsUkxBCCCE6F0miCCGEEKe5xVvTMNscRIf4cccUz5MlbTVpUBJf/L6PbekFDa4H6N1HnR9NLpzI0f5VtVZqLTZ8fTxbKdMSrUpJZJBvm8b6tfL+tRb3aV06bfM/Th19JqPZ2qaYhBBCCNG5SBJFCCGEOM1tP1wEwNn9ElGrlO0yp9Xu4H+/72PRlnQO5pZRWWvB7nA26FNU2XB1xbkDk3hjyXY+WLGL8hozV4zpxaiesfXJkj/rGhVM18ggMosNTPnv19x0/kAm9k+ky3FbhFprZM9YUt66pc3jhRBCCCFaIkkUIYQQ4jRXWuVOZsR7ePLOiVSbLEx//gd2ZhTVX/Pz0RDi54NCocBqd1BptNSvxDhqfJ94Hrx8FK/8tIVv1h/km/UHUSoU9EsMZ/LQbtx47oAGW1/UKiXv3T6Z619fwv6cUh745FfAvT3mnP6J/O3sfozt3fQpQJ2Br48GQ60Fs9XebJ+jr5GfrulEkhBCCCFOL5JEEUIIIUQDL/24hZ0ZRQT6apl7wzmcNzCJEP9jBWHX7M9m+vM/4MLVaOzD00dz9bje/LDpEBsO5rE1rYC9R0rYe6SEd5bt4Iv7pnFWv4T6/sOSo9n60g0s2ZrOr3uPsCk1n9yyahasO8CCdQeYed4AXrzx3FPy3K0VFeyHodbS4valo7VQjtZGEUIIIcTpTZIoQgghxGkuItD9Bj2ntKpd5lu8JR2AZ/5+NleO7d2ovaTK1OL4rlHBzLl0JHMudR97vCYlh6cWrmdfdil3vr+CXa/NRKU8tu3I10fD1eP7cPX4PgCkFVTwwfKdfLJ6L5+s3suUod05d2AXj2LfciifG99Y6umjNnDHlKHcddEwj/v3jA3hUH55/Sk9TUmrO5WnZ2zzJ/gIIYQQ4vTRPhunhRBCCOE1w5KjAfhjf06juiVtUVBRA8DgrpFNtq9LyfV4Lo1axXkDk/jknovq584sMrQ4pkdMCC/eeC6je8YCsOGg5/ezOpwUG2rb9Mf4p+1JJzKuTzwAG1PzsNodjdqLDUZScsoA91YnIYQQQpz+ZCWKEEIIcZq7ZGQPnvhqLUWVRt5ZtqPRUcKtFaDXUl5jJr2wgj4J4Q3a0gsq+HbDwSbHWe0OtGpVk23Hn2BjsdlP2P/4MWZb4wRFc8b3iaf0i3s97n8yLh6ezH/mr6OixszX6w7wj4n9G7R/tGI3TpeLiEB9gy1MQgghhDh9yUoUIYQQ4jQXFqBnzqUjAHjq6/X8d8G6+tUkANklVcz9fhOfrN7j0XwT6t7w/+erdWxNK8DlcuF0uli9J4srX/ih2SN973hvBfd+uJLf9x6h5rgjfdMKKrjnw5UAxIT40zs+DIBVu7KY8t+v+d/v+8grq67vX22y8ubS7fyxPxuAcwd4tpXnVIsJ9WfmeQMAeOzLtSzZmo7L5cLucPLpr3t5Y+l2AB64bBQ+Gvm9lRBCCHEmkP/RhRBCiDPAvRePoKiylo9W7ubNpdt5c+l2gnx9sDudGM3ubSoPXj7Ko7n+dcUYftt7hOzSKqb839f4atU4XS7MNgfRIX48/fezuPP9FY3GWWx2ftx8iC/XpKBQQJCvDxabA1Pd6TW+WjVvz57UoB7K1vQCtqYX1Ldr1CoMtZb69hvO7e9xPRRveGLGOPZll7L+QC43vrEUX60ah8uFpW71zNXjejPr/IFejlIIIYQQ7UWSKEIIIcQZQKlU8Pz1E7loeHc+XrWHLWkFlFebCPHX0TsujAuHdOXaCX09mqtHTAjLn7yG57/dyJqUHIxmGzEhfkwa3JUHLh1Jal2x1D97/OpxjOgRw9qUHDKLDBRVGnG5XHSPDubsfoncMXUoSZFB9f0n9Ivnndsu5I992ezJKqaw0ki1yUpkkC+DukZy3cT+TB3WvV1en47io1Hz3cOX89HK3Sxcd4CMwkq0KiWDkiK54dwBzKgrliuEEEKIM4MkUcRfmqkgzdshCNEu5GtZHDWhbwIT+npWf2PRv69stq1HTAjz7p7aZFtEkG+TdUd6xoXSMy7U45osAXofrh7Xm6vHNT4B6HSiVim5bfIQbps8xNuhCCGEEKKDSRJF/CWFh4ej0/uS/uHd3g5FiHaj0/sSHh5+4o5CCCGEEEKINpEkivhLSkxMJPXgAUpLS70dihDtJjw8nMTERG+HIYQQQgghxBlLkijiLysxMVHecAohhBBCCCGE8JgccSyEEEIIIYQQQgjhAUmiCCGEEEIIIYQQQnhAkihCCCGEEEIIIYQQHpAkihBCCCGEEEIIIYQHJIkihBBCCCGEEEII4QFJogghhBBCCCGEEEJ4QJIoQgghhBBCCCGEEB6QJIoQQgghhBBCCCGEBySJIoQQQgghhBBCCOEBSaIIIYQQQgghhBBCeEDt7QCEEEKI9nYor9zbIQghkH+LQgghzjySRBFCCHHGCA8Px1ev5/b3lns7FCFEHV+9nvDwcG+HIYQQQrQLhcvlcnk7CCGEEKK9ZGdnU1pa6u0wOkRGRgb/+Mc/mDp1Ko899pi3wxEn6amnnmLZsmV8+eWXdO3a1dvhdJjw8HASExO9HYYQQgjRLiSJIoQQQpwGTCYTI0eOxOl0snXrVnx9fb0dkjhJtbW1DB8+HLVazebNm9Hr9d4OSQghhBAnIIVlhRBCiNPAnDlzSE9PZ+HChZJAOUP4+vqycOFC0tLSeOCBB7wdjhBCCCE8IEkUIYQQopP79ttvee+993j99dfp37+/t8MR7WjAgAG89tprvPvuu3z33XfeDkcIIYQQJyDbeYQQQohOLCsri8GDB3PBBRewcOFCFAqFt0MS7czlcnHVVVexevVqdu3aRZcuXbwdkhBCCCGaIUkUIYQQopOy2WycffbZ5Ofns2vXLoKDg70dkuggFRUVDBkyhNjYWP744w80Go23QxJCCCFEE2Q7jxBCCNFJ/ec//2HLli0sWLBAEihnuJCQEObPn8+WLVt48sknvR2OEEIIIZohSRQhhBCiE1q5ciXPP/88zzzzDKNHj/Z2OOIUGDNmDE8//TTPPfccq1at8nY4QgghhGiCbOcRQgghOpmioiIGDRrEwIED+eWXX1Aq5XcefxVOp5MLL7yQffv2sWvXLqKiorwdkhBCCCGOIz+VCSGEEJ2I0+nk+uuvB+CLL76QBMpfjFKp5IsvvsDpdHLDDTfgdDq9HZIQQgghjiM/mQkhhBCdyEsvvcSKFSv44osvZBXCX1R0dDRffPEFy5cv5+WXX/Z2OEIIIYQ4jmznEUIIITqJTZs2MWHCBP75z3/y3HPPeTsc4WX/+te/ePnll1m3bh2jRo3ydjhCCCGEQJIoQgghRKdQWVnJkCFDiI6OZs2aNXLErcBmszFhwgSKiorYtWsXQUFB3g5JCCGE+MuT7TxCCCGEl7lcLm699VYqKir46quvJIEiANBoNMyfP5/y8nJuvfVW5PdeQgghhPdJEkUIIYTwso8++ohvvvmGDz/8kK5du3o7HNGJdO3alY8++oivv/6aefPmeTscIYQQ4i9PtvMIIYQQXrR//36GDx/ODTfcwHvvveftcEQnNXv2bL744gu2bt1Kv379vB2OEEII8ZclSRQhhBDCS2praxk5ciQKhYItW7ag1+u9HZLopI5+rQBs3bpVvlaEEEIIL5HtPEIIIYSX3H///WRkZLBgwQJ5Uyxa5Ovry8KFC8nIyOD+++/3djhCCCHEX5YkUYQQQggv+Prrr/nggw944403ZHuG8Ei/fv14/fXXef/99/nmm2+8HY4QQgjxlyTbeYQQQohTLDMzk8GDBzNlyhTmz5+PQqHwdkjiNOFyubjmmmtYvnw5O3fulELEQgghxCkmSRQhhBDiFLLZbEyYMIHi4mJ27txJUFCQt0MSpxmDwcDgwYOJiopi7dq1ciS2EEIIcQrJdh4hhBDiFHr88cfZvn078+fPlwSKaJOgoCDmz5/P9u3beeKJJ7wdjhBCCPGXIkkUIYQQ4hRZsWIFL7zwAs8++yyjRo3ydjjiNDZ69GieeeYZnn/+eVasWOHtcIQQQoi/DNnOI4QQQpwChYWFDBo0iCFDhvDzzz+jVMrvMcTJcTqdTJkyhV27drF7926io6O9HZIQQghxxpMkihBCCNHBnE4nF154Ifv27WP37t1ERkZ6OyRxhigqKmLQoEEMHDiQX375RZJzQgghRAeT/2mFEEKIDjZ37lxWr17NF198IQkU0a6ioqL43//+x6pVq3jxxRe9HY4QQghxxpOVKEIIIUQH2rhxIxMmTODhhx/mmWee8XY44gz16KOPMnfuXNauXcuYMWO8HY4QQghxxpIkihBCCNFBKioqGDJkCLGxsfzxxx9yFK3oMDabjbPOOouCggJ27dpFcHCwt0MSQgghzkiynUcIIYQ4SfPnz2f16tUNrrlcLm655RYMBgNfffWVJFBEh9JoNMyfP5/KykpuueUW/vw7stWrV7NgwQIvRSeEEEKcOSSJIoQQQpykJ598kiVLljS49sEHH/Ddd9/x0UcfkZSU5J3AxF9KUlISH330Ed9++y0ffvhhg7bFixfz5JNPeicwIYQQ4gwiSRQhhBDiJJjNZtLT0+nXr1/9tb1793Lfffdx++23c8UVV3gxOvFXc+WVV3Lbbbdx7733sm/fvvrr/fr1Iy0tDbPZ7MXohBBCiNOfJFGEEEKIk3Dw4EGcTif9+/cHwGg0MmPGDHr06MHLL7/s5ejEX9Err7xCcnIyM2bMoLa2FoD+/fvjdDpJTU31cnRCCCHE6U2SKEIIIcRJOPrb/r59+wJw3333ceTIERYuXIher/dmaOIvSq/Xs3DhQjIzM7nvvvuAY1+fx69OEUIIIUTrSRJFCCGEOAn79u0jMTGRwMBAFixYwEcffcSbb75Jnz59vB2a+Avr27cvb775Jh9++CELFy4kKCiIhIQESaIIIYQQJ0mSKEIIIcRJ2LdvH/379ycjI4Nbb72Va6+9lpkzZwKQlZXFTTfdhE6nIysry7uBijNaVlYWOp2OWbNm1X+t3XTTTVxzzTXceuutZGRk0L9/f0miCCGEECdJkihCCCHESdi3bx99+vThmmuuISIigvfee4+8vDxuv/12evbsydKlS5k7dy5dunTxdqjiDNalSxfmzp3LkiVL6NmzJ7fffjt5eXm89957hIWFce2119KnTx9JogghhBAnSeFyuVzeDkIIIYQ4HVVXVxMYGMiUKVNYuXIlixYtYvny5bz33nv4+/vz0EMPceedd+Ln5+ftUMVfhNFo5O233+aFF17AaDRy2223ceGFF3LJJZcwadIkli1bRnV1Nf7+/t4OVQghhDgtSRJFCCGEaKPNmzczevRoACZOnMjmzZvRarU88MAD3HvvvQQGBno5QvFXVVVVxeuvv85LL72EzWZj1KhR/P7774D763bkyJHeDVAIIYQ4Tcl2HiGEEKKN1q1bB4BSqWTbtm3MmTOHzMxMHn/8cUmgCK8KDAzk8ccfJysrizlz5rB161aUSvePfUe/boUQQgjRepJEEUIIIdpo69atKBQKbr/9djIzM3n66acJCQnxdlhC1AsJCeHpp58mMzOT2267DYVCwZYtW7wdlhBCCHHaku08QgghRBvZ7XaMRiNBQUHeDkUIj1RWVuLv749arfZ2KEIIIcRpSZIoQgghhBBCCCGEEB6QX0MIIf6SsrOzKS0t9XYYQnQK4eHhJCYmejuM0558XxFnIvn+IIQQDUkSRQjxl5OdnU2f3r2oNZm9HYoQnYKvXseBg6nyRukkZGdn06t3H8ymWm+HIkS70ul9ST14QL4/CCFEHUmiCCH+ckpLS6k1mXnzimR6hOu9HY4QXpVWauLu79IpLS2VN0knobS0FLOpluRb3kQf08Pb4QjRLkwFaaR/eLd8fxBCiONIEkUI8ZfVI1zPgFh/b4chhDiD6GN64N9lgLfDEEIIIUQHkSOOhRBCCCGEEEIIITwgSRQhhBBCCCGEEEIID0gSRQghhBBCCCGEEMIDkkQRQgghhBBCCCGE8IAkUYQQQgghhBBCCCE8IEkUIYQQQgghhBBCCA9IEkUIIYQQQgghhBDCA5JEEUKIM9SoV3cQ95+NbMg0tNucGzINxP1nI6Ne3dFucwohOpcdD41i46w4DAc3tNuchoMb2Dgrjh0PjWq3OYUQQghvUHs7ACGEEKKjbDlSxXsb8tmeU0O1xU5MoA8X9g7h7glxhPhq2jxvea2Nt9bmsfxgOQVVVgJ81AxL8Of2cbGMSAxsxycQQnhDVdoW8n95j5qM7dhrq/EJjSFk8IXEXXQ3Gv+QNs9rqyknb+lblO9ajrW8ALVvAP7dhhE7+XYCe4xoxycQQgjRUSSJIoQQZ6guIT74qBXoNe236FCvUdI9XEd0gLbd5uwon20p5LGfM3G6QKkAP62KrHIz728oYNG+Mn6c1Z/4YJ9Wz3uk3Mz0T/ZTWGUFIMBHRXmtjeUHK1iZWsFzF3fjH8Oj2vtxhDhlfCK6oND4oNTq221OpVaPLro72uDodpuzoxT+9hmZXz4GLicolKh0fpiLsyhY8T5lWxfR/18/4hMe3+p5zSVH2P/CdKwVhQCo9AHYqsup2LWcit0r6Xbdc0Sd/Y/2fhwhhBDtTJIoQghxhvr6xn7tPueQ+ADW3D2k3edtb7vzanh8mTuB8vdhkfx7UheC9Gr2FRi5/ZtDZJSZuXVhKktvHYBCofB4XqfTxa1fH6Kwykq3MB3vXtWT/jF+GEx2nll5hC+3F/PvpZkMjvOnf4xfBz6hEB2n34Nft/ucAd2GMOSZNe0+b3urydpN5lePg8tJ5Nl/p8uV/0btG4Qxex+H3rsdc1EGqe/eyoDHlrbqe4fL6eTQO7dirShEF9WNnre9i19if+y1Bo58+wzFf3xJ5pf/xj9pMH5d+nfgEwohhDhZUhNFCCHEGeel33JwOGFEYgAvTOtGkN79O4P+MX7Mu6YXKiXszjfyy8HyVs279EA5+wqMqJTw8bW96hMlQXo1L0zrxvCEAOxOFy//ltPuzySE6Hg5P74ETgcBySPodt0LqH2DAPBL7E+vu+aBUoUxazflO39p1bzl25dizN4HShW97voYv0R3okTtG0S3614gIHk4LoednEUvt/szCSGEaF+SRBFCiE6u2mznqeVZjH51B92e2sTIV7bz76UZlBttLNxZTNx/NnLlJ/sbjWuusOyfxyw7UMb0j/fR+9kt9HxmM9M/3sevaRVNxnI6FJatNNlZc9j9zDePjmn02+Kekb6c3T0YgB/2lLZq7kV73f0nJgfTI8K3QZtCoeDmMTEA/JZeicFkb0v4QrQbu6marK+fYsfDo9k0uxvbHxxJxpf/xlZdTvG6hWycFcf+uVc2GtdcYdk/jynbsYx9z09ny1292XxHT/Y9P52Kvb82GcvpUFjWbqzEkOJeLRMz6eZG3zt8Y3sS3O9sAEo3/dCquUu3LAIguP9EfGN7NGhTKBTEnH8zAJV7f8Ne237FwIUQQrQ/SaIIIUQnVm60Me2jfby3oYCcSgsKhYIKk51PtxRx0Yd7qag9uTfqL/+Ww80LDrEtpxoAo9XJ5iPVXP/lQRbta12CobPYkl2F3elCoYDx3YKa7DOh7vqGrKpWzX20/4RuwU22j+8aiEIBNoeLLdnVrZpbiPZkqy5n3zPTKFj+HpbSHBRKBXZjBUW/fsrepy/Cbmw6UeqpnJ9e5tDbN1N9eBsATouR6rTNHHz9ekq3LmqPRzjlqtK24HLYQaEgqM/4JvsE9Z3g7pvaupOLjvYPrhv/Z4F9xoNCgcthozptS6vmFkIIcWpJTRQhhOjEHlmaSVqJiWC9mlcu686kniEolQrWZxq474d03liT2+a59xca2Zpdzb8nJXL9iGj8fVTkVVq4/8d01mdW8Z9lWUztE4Za5fm+/84gvcQEQKS/hmB90//N9YhwF8ysqLVTZrQR5nfik3pKa2xU1q0u6RnRdMHNEF8N4X4aSmpspJfUMqlX20/xEOJkZP7vEUwFaaj9guk+8xVCBk1CoVRiOLie9Hn3kbvkjTbPbczeT3X6VhKv/DfRE69HpffHUpZH+sf3U3VwPVnz/0PY0KkoVKfXj5mmgnQANIGRqP2Cm+yjj3GvIrHXVGCrLkMTEHbCeW1VpdiNlXXjezbZR+MfgiYgHFtVCbUF6YQMmtT6BxBCCHFKnF7/uwkhxF/I4VITS/aXAfDG9GTO63nsDfm4rkF8cm1vpry/p83zV5kd3HNWHHeMj6u/Fhfsw9tX9mDUqzsorrGxJbuKsV2bXs3RWqNe3UFupaXV4+KDfdh8/1CP+xdV2wCI9G/+BKHI404XKq6xepREKaqxHje++f6R/u4kSnGNzZNwhWh3psLDlG1bAkDyzW8QMvC8+rag3uPofdcn7HlqSpvnd5iqiLvoHuKm3FF/zScsjh63vs2Oh0ZhMxRTlbaFoN5j2/4Qx9nx0CgsZa1PGPuExTN07maP+9sMRQBogyOb7XN8m9VQ7FESxVo3L4Cmhbk1QZHYqkqwGYo9CVcIIYSXSBJFCCE6qRV1RU97ROgbJFCO6h/jx7iuQazNaNv+eY1KwZ3HJVCOivDXMijWny3Z1RwqNrVbEiXMV43F7mzTuNYw2RwA6Fo42vn4Y5+NVs9iqj2un07d0tyqunkdHs0rRHsr37UCcK+aOD6BcpRfl/4E9RmHIWVtm+ZXqDTETbmz0XVtUAT+XQdRnbYFU/6hdkuiqAPCcNpan4BVe5DgOJ7D4l7FptTomu1z/LHPTrPRo3mdltpj41uYW+Wjr4vDs3mFEEJ4hyRRhBCik0opcv/gPSIhoNk+IxMD2pxEiQ/2wd9H1WRbdKB7pYbB3H7FUX+ePbDd5hJCNK82JwWAgOQRzfYJSB7Z5iSKT3g8Kr1/k23a4GiAdi2OOvDxn9ttLiGEEOJkSWFZIYTopMpr67altLB1JKKFLSsnEh3Q/FifupUWdqerzfN7y9GVIGZb8ytMTMe1+Wk9+6/Q97h+5hZW1BxdCeOnbTpBJURHs9W4V7G1tHVEGxTR5vmPJkqaotT4ALgLtJ5mjq4EcdrMzfZxWk31Hyt1fh7Nq/Q5dpJXS3MfXQmj8vFsXiGEEN4hSRQhhBBnlKi6pFPxcTVM/qzkuHolUR4moo7vV1zdfL2To3NHtZCkEkJ0PpqgKACslc3XJLEZSuo/1tb1P5Hj+9lamruqpFXzCiGE8A7ZziOEEJ1UqG9dMqDFN+zNJwo6m6nv7yG/qvXxxgZqW7UVKLnu5JziGhsGk52gJk7oSas7wSfUV02oB0VlAcLrTvupNNlJKzFxdnJwoz6VJjslRluDOIQ41TT+oUDLb9itxyUDOrs9T03FWp7f6nHa0NhWbQXSxyQDYKsqxl5rQO3buB6UqSANALV/KJqAUI/m1QSGo/YLxm6sxFSQRnD/sxv1sRsr65MoR+MQQgjROclKFCGE6KT6RrmXgG/LqW62z9YW2jqbslo7JTW2Vv8pq23dtoCRiYGolQpcLliX2XRdhrUZlQCtLpo7NimwbnzT867LMOByuYv2jkxsvpaNEB3JN6EvANWHtzXbpzp966kK56TZq8vcp9a08o+9uqxV9wnsMdJ9LLPLhSFlXZN9KuvqyLS2aG5gL3d/w4Gm69AYDqwDlwuFSkNAj5GtmlsIIcSpJStRhBCik5rUO5SnV2ZzqMTEb2kVnNOj4Qk9+wuNrGtjUVlvaM0xxScjWK/m7OQgVh+qZN6mAqb2CUWhUNS3p5eY+CPd/bpdNqB1p3dcOiCcnw+U83t6JeklpgarTVwuF/M2FQBwTnIwgTr5L1Z4R+jgSWR/8zSm/ENU7P2NkAHnNGg35ux3v2k/TbTmmOKTofYLJqjf2VTuWU3BqnmEDpva4HuHqSAdw/4/AAgbdVmr5g4fdSnlO36mct/vmArSG6w2cblcFKyaB0DwgHNQ+wae/MMIIYToMLISRQghOqnkcD1T+7qXi9/9fTorUstx1hV63Zhl4Kb5qQQ0c7rOX90DExNQKWHzkWoeWZJJVd0pQ/sLjcxakIrd6WJQrB+Tezdejn/fD+nE/WcjV36yv1Hb1D6h9I/xw+50MWtBKvsL3UeRVpntPLIkky3Z1aiVCh44J6FjH1CIFuijkwkdNhWA9I/upnzXClxOdzFkQ+pGUt+8CZVeVko1JeHSB0CpojptM5n/ewR7bRXgTjylvj0Ll8OOX9IgQodMbjQ2fd59bJwVx/65VzZqCx06Fb/E/rgcdlLfnoUxx/39xV5bReb/HqE6bQsKlZqESx7o2AcUQghx0uTXZEII0Yk9f3E3UotrOVxqZuZXqeg0SpQKqLU6SQrVcc9Z8Ty14ghaleLEk/2FDIrz56kpXXns50y+2FbEl9uL8NOqqLa4T86JCdTy/tU9G/yW2RNKpYIPru7J9E/2k15q4oJ39xDgo8JodeB0gVIBz1zUlf4xcrqG8K5u1z1PbV4q5sLDpL45E6VWBwolTkstusgk4i+6hyPfPIVCLQWQj+efNIiuf3uKzC8fo+j3Lyj640tUOj8cJvfWSW1IDD1vf7/V3zsUSiU97/iA/S9Mx1SQzp4nL0ClD8BhNoLLCQolXf/+DH5d+nfEYwkhhGhHshJFCCE6sTA/DUtuGcDssTHEB/vgdLoI0au5aVQ0S27pj1rp/kFeto40dsPIaL6b2Y8LeoUQ4qvG6nCSFOrDrWNiWHn7QBJCdG2at0uojpW3D+TWMTEkhfpgdTgJ8VVzYe8Qvr+pH/8YLidrCO/TBIQx4N9LiLlgNj5h8bicTtR+IUSfdxP9/73EXfsDZOtIE6LPuYF+D39HyOALUPuH4LRZ8YlMIuaCWxn45Ep04W1baaaL6MLAJ1cSc8Gt+EQm4bRZUfuHEDL4Qvo9/D1RZ/+jnZ9ECCFER1C4XC6Xt4MQQohTaceOHQwbNoxfZg9gQKy/t8M5Kfd+n863u0u4/+x4/nmubCERrbc3v4bJ7+9l+/btDB16aurWnImOfl8Z8MQv+HcZ4O1wTih93r2UbPiW+Gn3k3DZP70djuikao7sZe//TZbvD0IIcRxZiSKEEKepvEoLPx9wnz4xoXvrTpkRQvx1WcryKNvuPvo3qO8EL0cjhBBCnF4kiSKEEJ1YdoWZB386zPacakw2dz0Pm8PJr2kVXP3ZfmqtTgbF+jGqiyzJF0IcYy7J5vCnD1J9eDsOqwkAp91Gxd5f2f/S1TgttfglDSKw5ygvRyqEEEKcXmQTvRBCdGJWu4uvdhTz1Y5iAIL1KoxWJzaHeydmdICGN6b38GaIQohOyGW3Urz2K4rXfgWAyjcYp8WIy2EDQBMcTY+b3/BmiEIIIcRpSZIoQgjRicUGaXn8gi78ll5JZpmJMqMNrUpBcrie83qGMHtMDKF+Gm+HKYToZLShsXS56nEq9/2GqSgTW3UZCrUWfUwyIQPPI+aC2WgCGh/xLYQQQoiWSRJFCCE6MV+titvGxXLbuFhvhyKEOI2ofHyJnXwbsZNv83YoQgghxBlFaqIIIYQQQgghhBBCeECSKEIIIYQQQgghhBAekCSKEEIIIYQQQgghhAckiSKEEOKkxf1nI3H/2UhOhdnboQghzhAbZ8WxcVYc5tIcb4cihBBC1JPCskIIIUQ7KzfaWJ9VxZ68Gnbl17A330i1xQFA3n/HtDg232Bh05EqduXVsDvPyP5CIyabk/hgHzbfP/RUhC+E6IQMKWup3P8HNZm7sJTlYqsqxeVyoQ2OIrDHSKLPvRH/roO9HaYQQpzxJIkihBBCtLPv9pTy5C9ZbRr73oZ85m0qbN+AhBCnvbyf38JwYF395yp9IC5rLZaSI5SUHKFk43ckTn+YuKl3eTFKIYQ480kSRQghhGhnCiAmUMugWD8GxvqjUSl4ZmW2h2MVdAnxYVCcP4Ni/Sk12nh3fX7HBiyE6PSCB5xD2PCLCeg5Cl1EIkqNDpfTSW3eQXJ+mEvF7pVkf/cc/t2HEdSr5RVvQggh2k6SKEIIIUQ7mzkqmpvHxNR/vuVIlcdjn7iwC/+dklT/+Xe7S9ozNCHEaSr2wtsaXVMolfgl9KXnHR+y6/GJWIqzKFn/jSRRhBCiA0kSRQghTpLF7uTTLYUs3ldGeqkJs91JiF5NVICWsV0DuXpwJL2jfBv0/+VgOatSK0gpNFJQZcVidxId6MNZ3YO4Y1wsCSG6RvfJqTAz+rWdgLuuxvacal5fk8uO3BpsDhcDY/146NwERiQGAlBpsvP22jyWppRRWG0l0l/LjCER3DUhDo1K2eLcm49U8dbaPHbm1WC2OekVqefGkTFcNTiiTa9RSY2V9zcUsPpQBTmVFhQKSArVMbVPGLeMicHfR9VoTLXZzgcbC/jlYDlZ5WbsDhehfhpiA7VM6BbEtUMjm3ydOgOVUuGVseLM4bRZKPz1U8q2LsZUmI7TakbtH+Kuf9FrLJHjrsY3vneD/uU7f6Fi9yqMOSlYKwpw2iz4hEQT1PcsYqfcgS48odF9zKU57Hx4NABj5uVRfXg7uUtepyZjBy67Db+kgSRc9hCBPUYAYDdWkvfz25RtX4q1ohBtcCQR42YQN/UulGpNi3NXHdpM3s9vUZO5E6fVjD6uFzHn3kjE2Kva9BpZDSUUrHifij2rsZTmgEKBLjKJsGFTiTn/FlR6/0Zj7KZqClZ8QPnOXzAXZ+Fy2NEEhKINiSWo7wQiJ1zb5OvU2SnVGvzi+2ApzsJmKPZ2OEIIcUaTJIoQQpwEm8PJNZ+lsCW7GgClAgJ1KkqNNoprbOwtMKJWKnh0Upf6MWsOG7jjm7Tj+qtxuCCr3ExWuZmf9pby5XV9GBIf0Ox9lx8sZ/bXh7A7XfhrVdRYHGzIrGLGZyl8dV1fksP1XPXpfg6VmPDTKnE4IafSwku/5ZJnsPLSpd2bnXvx/jLu/PYQDicE6VRYHU525Rm574d0duRW89zF3Vr1Gm3MMjBrfioGs7uwqk6twOGElMJaUgpr+XFvKQtv6Et0oLZ+jMFk55KP9pFeagJApYQAHxVF1VYKq6zsyK0hOlDL9SOiWxWLEKcDp91GysvXUJ22xX1BoUSlD8RWVYrNUIzxyF4UKjVdrny0fowhZQ1p799R31/tGwhOB+biLMzFWZRu+Yk+939JQLchzd63fOdyDr07G5fTjkrnj8NcQ9XBDaS8NIO+c75CH5PM/hevwpR/CKWPH7gcWEpzyP3pJazleXS/8aVm5y7buphDH9wJTgcq3yCcdivGzF2kz7uP6sM76Hbdc616jQypG0l9axaOWoP7kTU6cDqozUmhNieF0s0/0veBhWhDjn2PsNca2PfsJZgK0t0XlCpUugCslUVYKwqpydiBNiSa6InXtyqWzsBpM2PM3geAz2mYBBJCiNOJJFGEEOIk/LC3lC3Z1YT5qXnlsmQmdg9GrVJgczjJqbSwLKWcYH3Db7X+PkpuGRPDxf3CGBDjh49aidPpIrWkludX5bDqUAX3fJ/OH3cNRtnMqoT7fkhnxpBIHj43gVA/DXkGC3d/l8bmI9X8d3kWsXUJiUU392dYQgBmm5OPNxfwzMps5u8oZuaoaPpF+zU590OLDnNOcgjPXtSVuGAfqs123lmfzxtr8vh8axGjugRy2YBwj16f7AozM79Kpcbq4ObRMdw8Opr4YB+cLtiTX8Pjy7LYmVvDPd+n8fWN/erHzdtUQHqpiaRQHa9c1p0RCQEolQosdieZZWYW7Ssl0l/bwp2FOH2Vbv6B6rQtqAPCSJ75CsH9J6JQqXHabVjKcijfvgy1X3CDMUqdPzGTbiFs+MX4dRmAUuPjrpeRn0rO989TsXsV6R/dw+Cn/0ChVDZ53/R59xE5fgYJlz+MJiAUS3keaR/cTXXaZrIW/hdtaCwA/R9dRED3YThtZgpWfUz2t89QvHY+0efNxC+hX5NzH/7sIUIGnEPXvz+LT1gcdlM1+cveIW/pGxT9/jmBPUcRPuoyj14fc0k2qW/OxGGuIWbSzUSffzM+YfHgclKTtYes+Y9Tk7GTtI/uod+DX9ePK1g5D1NBOrrIJLrPfIWA5BEolEqcNgvmokxKty5CGxjpUQydhd1YSW3uQXIXv+pejaNUETXxOm+HJYQQZzRJogghxEnYmVsDwOwxsZzfM6T+ukalpFuYnjsnxDUaMyYpiDFJQQ2uKZUK+kT58eGMnkx+fw+pxSbWZ1UxoVtQo/EAg2L9eWHasRUhcUE+vHVFD0a+uoM9+UYOFNWy5u7BJNZtd9FplNwxPo4/DhtYl2HglwPlzSZR4oJ8+OianvVbfgJ0ah4+L5Eyo40vtxfz8m85HidR5q7Oodri4MFzE7jv7Pj66yoFDIkP4H//6MN5b+9ifWYVO3Or61ff7Mxzv64PnZfAqC6B9eN81Ep6R/nSOyrRo/sf78pP9rMxy/PaJMc70bHEQrSnmgz31rrYC2YTMuj8+utKtQZ9VDfipt7ZaExQrzGN6mAolEr84vvQ844P2fPfyZjyU6k6uJ6gvhOavK9/10F0u/6F+s99QuPocetb7HhoJMYje6jNPcDgZ9agi3D/+1NqdMRNuQPD/j8wHFhH+Y5fmk2i+ITF0fOOj+q3/Kj1ASROfxhbTRnFf3xJzk8ve5xEyflhLg5TNQmXPUj8tPuOe2AVAd2G0Oe+/7HrifOoOrie6oyd9atvajLdr2vC5Q8R2HNU/TClxgff+N4kHrc9ylP7515JVerGVo8D9xantqhMWcOBl69tdF3tH0r3mS/jl9C3TfMKIYTwTNO/ihBCCOGRgLpaHkU11naZT6tWMr4ucbIjp7rZfneMj210LTbIh66h7qTJtH5h9QmU443v6p47tbi22blvHRvTqGYKwF11CaGMMjMHiowtPIWbyepgSUoZGpWCWaOa3nYTrFdzTg938mldxrEEx9EaKcXVthPex1PBejUR/po2/RHiVFLp3clEq6GoXeZTqrUE9R0PQHXGjmb7xU6+o9E1n9BYdJFdAQgbMa0+gXK8oD7uuWvzUpudO+aCWxvVTAGIm+I+jtdclIEx90ALT+HmsJgo27YEhUpD9Pmzmuyj9gsmZMA5AFQdfySwzl0jpT1rhqj9gtEERrTpT1sp1T51c4SDwv29WuUbRJerHiO4/8R2ejIhhBDNkZUoQghxEiYmB/P2unw+3lxIRa2dyweGMzIxsMlCqccrrbExb3MBv6dXklVupsbiwOlq2Ke4hcRMr0jfJq+H+2nIKDO30O7+tl9VV5+kKWOOW/lxvMQQHXFBWvIMVvYV1NInqumVLEftKTBic7hQKWHCm7ua7We0umPJr7LUX5uYHMyifWU8u/IImWUmLuoXxtB4f/Sall/Xlnx0Ta82jxXiVAruP5H8ZW9TuPpj7DUVhI++nMDkkU0WSj2eraqUglXzqNz3O+biLBzmGnA5G/SxtpBA8I1r+t+IJjAcc1FGs+3qQPfKNIep+ZVegc2cFqOLSEQbGoe1PI/a7H34xfdpdg4A45E9uBw2UKrY9WjTK2oAHBZ3otdSfux48OD+Eynbuogj3z6LqSiTsOEX4d9tKCqtvsV7tqTXnR+1eWxbBfYcxfBXdwG4a8tk7SH7++c5/MkcitctpPc9n6D2bXoVoxBCiJMnSRQhhDgJY7sGMWdiPK+vyeX7PaV8v6cUpQL6RvtxQa8QrhseRWRAw9odB4qMXP1pCuW19vprgToVPmr3bxSNVge1Vie11oZvfo4XFdB0PZCjJ7s0t3riaI0V+58zNh7MfbQtz2ClzHjiFSJF1e4kkMMJJTUn7m+yHXveqwdHsDW7mvk7ivlsaxGfbS1CrVQwOM6fKX1C+duwSAJ18l+YODMF9R5L/CVzyF3yOqWbvqd00/egcB9lGzL4AqImXoc2qGHtDmPuAVJevBp7TXn9NZU+EKXGB3AnFZyWWpyW5lehaYOjmryuULqTl82tnlDUrYZwOexNtrc099E2a3ketuqyZvscVb86x+nAVnXi47+dVlP9xxHjrqY6fSvFa+dT9NtnFP32GQqVGv+ugwkdMoXIs/7mLsh7GlGqtQQkD6fvAwvY98J0qtM2k/3DXLr9/RlvhyaEEGcs+QlUCCFO0gPnJHDFoAh+2lvKpiNVbMupZl+BkX0FRt7fkM/H1/au36ID8MCPhymvtdMnypcnJycxLKHhCou5q7N5fU0ezac5Tg+uugeIDtSy/YFhrRqrUCh46dLu3DQqmiX7y9h0pIpdeTVsy6lmW041723IZ8H1fRscHS3EmSTh0geIGHMFpVt+oip1E9WHt2HM3ocxex/5y9+n990f12+jATj8yQPYa8rxje9D0jVP4t99WIMVFtk/zCVvyevH/mGeruoSwNqQaIa9tL1VQxUKBd1vfIno826ibNsSqlI3UZO5i+r0bVSnbyN/+Xv0fWBBg6OjTxcKlZqos/9BzeHtlKz/RpIoQgjRgSSJIoQQ7SApVMe9Z8dzL+5jj9dlGHh2VTYphbXc+0M6W+4fikqpILfSwu589zLzT67tRUITdUtKPVjl0ZGKqq1NxnW0DSDM78R1QsLrVsOUGW1Y7M76lTat0Tfaj751BXBNNgerDlXyzIoj5FRaeHDRYRbfMsDjuW5ekMq2FurMtGTXg8PbNE6Ik6GLTCL+4nvh4ntx2m0YDqwj+7tnqc1JIX3evQyduwWFUoWlNBdj1m4Aet39Cbomjri1VZee6vAbsFYWNRnX0TYATUDYCefRBLm3DtmqynDaLPUrbVrDL6FvffFVh9VE5e5VHPn2GSylORz+7EEG/Huxx3Olvn0z1enbWh0DUL8lp71og921p5wWI7aqUnfNFCGEEO1OkihCCNHONCol5/QIoWuYnnGv76SwykpWuZnu4XoKqtxJiBBfdbOJiraeINNeNh2pbjK2nAozeQZ3/P1jTrwCZFCsP2qlApvDxdoMQ4PTi9pCr1ExrV8YwXo113yWwq68Gkw2h8d1UipNdo+2FQnRGSnVGkIGnIM+qis7HxmHtaIQc3EW+ujuWCsLAFD7hzSbqKg62LYTZNpL9aFNTcZmLs3BWu4+pcY3sf8J5/HvMgiFSo3LYcOQsrbB6UVtodLqCRsxDbVfMCkvX0NN5i4cVpPHdVLsxkqPthWdCpbSnPqPlT4t16wSQgjRdpJEEUKIk2C1O9E2s8JCd9x1i91d79qedm0AAC+OSURBVOPoaT6VJjtlRlujFR3f7S4ho8zcQdF65oON+Vw2IKzRCT3vrHcXaOwerjthUVlwn7AzpU8oi/eX8fyqbMYlBaLXNp3wMNkcKBWK+tUqnryuThfYHS7w8PCcb2c2ffSqEJ2N025FqW66NpFScyzB6bS5izGrdO7TfOzGSmzVZY1WdJRs/A5zUUYHReuZ/BUfEDbyskYn9OQvewcAXXT3ExaVBVDp/QkdOoWyrYvJ/v55AnuPQ+XTdMLDYTWhUCjrV6u0+Lpq615Xl7PF2i5/1u+hbz3uezJcDjsKVfM/tjttFgp/+wwAv8T+zb4mQgghTp4ccSyEECfh3h/SeeDHdNYcrsRoOXbiTXqpiTk/pgPumiBHT8vpGaEnKkCDywV3fZdGbqX7TZDJ6uDTLYU8uOgwwXrv5rdzKy3M/voQeQZ3bDUWBy/9msPnW91L7udMbPo33U15dFIiwXoVB4pqmf7JftZlGHDU1TRwOl2kFtfy2h+5jHt9J8XVx04juubzFJ5YlsmWI1WYjys4uze/hsd+zgRgaLw/AZ20uKzT6aLcaKv/U3Xc10aD6+bGb9ZsDmeDPkdPL3K6Gs55/NebOLOkf3Qv6Z88QOX+NTjMx44TNxWmk/7JHMBdE+ToaTn62J5ogqLA5SLtg7uwlOYC7uOAC3/9lMOfPojaL/iUP8fxLKW5HHp3Npa6VScOUw05P75E0e+fA5BwyRyP50q84lFUvsHU5h5g/wvTMRxYh8vp/vfgcjqpzUsld/Fr7PzXuAanEaW8dA2Z85+gKm0LTtuxZHXNkb1kfvkYAP7dhqKuO2K6M6lK28L+F6+mbOviBgV4nXYrhoPrSXnpampz9gMQP+1+b4UphBB/CZ3zp08hhDhNWOxOFu0rY8HOEhQKCNKpMNtd9W/89Rolr12eXH9qjlKp4IkLk7jruzTWHDYw6tUdBOpU1Fqd2J0uxiQFMjwhgDfX5nntmeZe0p07vz3EitQKgnQqqi0OHHV5jOtHRHHZAM/32SeG6Pj8732YtSCVPflGZnyWglalwM9HRY3Fgc1xrMilQqGo/7ja4mDepkLmbSpEqYBAnZpaqwNrXf9QXzVzL+nWPg/cAfIMFka/trPJtgFzj9VPGJMU2GiFzNbsaq76NKXRuHyDtcHYqwZH8Nrlye0UsehMnDYLZVsXUbJuASgUqPRBuOxmnFb3G3+lVk/yTa/Vn5qjUCpJmvEEaR/ehSFlDTseHoVKH4jTWovLYSew1xgCkoeTt/RNrz1T9xvmcuiDO6nYvQKVPgiHuRrqEh9RE68nfNRlHs+li0ikz32fk/rWLIxH9pDy0gwUai0qnR8OU437COQ6Co59X3GYqylcNY/CVfNAoUTtG4jDUovL7k7gqv1D6XbD3PZ54A5QdXA9VQfXA+7tOkqNFoepun7ljEKtpctVjxE6dLI3wxRCiDOeJFGEEOIkPHJ+IsMTAliXYSCr3ExRjQ1cLrqF6ZjQLYjZY2PpEtqwvshlA8IJ0ql4a20eewqM2J0uekTomT4wnFvGxPDGGu8lUACm9Qsj0r8fb67JY2deDVqVkl4xem4cGcNVg5s+4rQlwxICWHP3YD7dUsiK1AoOl5qoMtsJ8FHTLUzH6C6BTOsfRnzwsQKRL13SndWHKtiQVUVOpYWSGisqpYLeYTrO7RHC7LGx9YVrhTjTJF7xCAHJwzEcWIe5OAuboQiXC3RR3QjqO4HYC2eji+jSYEz4qMtQ+QaR9/NbGI/sweW0o4/pQfjo6cRMuoW8pW946WncwkZMo19QJHlL36QmcydKtRZ9XC9izr2RiLFXtXq+gO7DGPzMGgp/+5SKXSswFRzGXluFWh+ALqobgT1HEzZiGj7h8fVjut/4EhW7V1OVugFLaQ5WQwkKpQpdXG9CBpxL7IWzO20xVv8uA+l+06sYDqzDeGQftqpiHKZqlD5+6CK6ENh7LFFn/x19VOdNLgshxJlC4XKd7mfdCSFE6+zYsYNhw4bxy+wBDIj193Y4nUJOhbl+5UTef8d4ORpxKu3Nr2Hy+3vZvn07Q4cO9XY4p62j31cGPPEL/l08PzXqTGYuzWHnw6MBGDPPu8lh0TY1R/ay9/8my/cHIYQ4jtREEUIIIYQQQgghhPCAJFGEEEIIIYQQQgghPCBJFCGEEEIIIYQQQggPSBJFCCGEEEIIIYQQwgNyOo8QQggSQnRSUFYI0a504QlSUFYIIcQZR1aiCCGEEEIIIYQQQnhAkihCCCGEEEIIIYQQHpAkihBCCCGEEEIIIYQHpCaKEEJ0Mgt3FjPnx8OMSQrk25n9vB1Op3LlJ/vZmFXV4Nqm+4aQEKLzUkTeJ6+J8FTxuoUc/mQOgb3G0O+hb70dTqeyf+6VVKVubHBtyAub0IUneCmi9pHz08vkLnqlwbXuM18hcvwML0UkhBCnP0miCCGEOO0E+KjQadyLKZVKRYM2p9PFxiNV7M6rYXe+kd15NeRUWgB45bLuzBgS2ey8FruTjVlV7MqrqRtfQ1G1DYBvbuzL2K5BHfREbgeKjLy9Np8NWQYqTXbC/TRMTA7m3rPiiQv2aXJMsF5NhL8GgJIaW4fGJ8SZTqUPQKlxJyAVyqYXbDssJvJ/eZeybYuxlGaj1OrxS+xPzPmzCBk0qd1jqs1Po3z7Emoyd2EqPIytqgyn1YTaPxT/pAFEjL2KsOH/396dx0dZ3f3/f82eyb6SDcJiWETZFxVRwaqggmhFS+vW3tVCf7ZiscttvW219dZftVqrrVtdqN5WLW6oKG5oAdmDIBAMBEgICdmTySSZzP79Y0IgZgITTAjR9/PxyOPBXNc513VmIBPmnXM+Z1b452OLwRKfBoCvqZ6gX+8RIiJfl0IUERHpc+6+eFCnYYjT7efqxfnHdd3dVS6ueWHn1xnacfvgy1oWLNmF2xfEYIBYq4lSh4cX8yp5Z0cNL10/kjHZsR36PT1veNufs3+/tsN5EYncoHl3H3WWhrexjh1/uhJXWQEARlsMfpcTR/4qHPmryJ61kJwrft2tY6rNW0bJm39ue2y0RWMwmfA6KqjbWkHd1o9IGjeTYQsex2i2tuubNXMBWTMXAOFn24iISNcpRBERkW+caKuRUZkxjM6KZUxWDPd8uJ/yBk9EfROiTIxq7TcmO5afLtmFP9Cz4y1zuLn5td24fUFmjEji/581hH5xVopqW7jl9d3klTRy4ysFrPz5WOwWU88ORkQ6tee5RbjKCrDEpzF0/mMkjJiC3+Oi7L3HOPDWQ5S+81diB48leexF3XbP6P6nkjP3DuKHn4k9cyhmexwA7rqDlK9YTNm7f6Pu8+WUvvt3Blz2i267r4iIhKcQRUREvlHio0wU3D653TKfP39SElHfkenR7PjvSRgMhmM37kZ/W1VKsyfAwCQbj80d1rZUaVByFM/OG8E5j35OmcPDCxsr+MmUrBM6NhEJady3hbotHwCQe+MjJIyYAoDJamfAnNtwVeylZv2blLxxf7eGKMnjZoQ9bkvKZOCVt+OpO0j12teo+uzfClFERE4AhSgiIp0oqWvhzIc/B45eqHNfjYupj2zBYID1vxhPdkKodkWpw82bX1Szep+D4toWyp0ebGYjQ9PsXH56KtdOTMdq7tomaYeWa3Q2njX7HFy1OJ/+iTbW/2J82Gus2edg8YZy8kqc1DT7iLWZGJsVy/WT07loeHKXxnMyMhgMHG8G8tX6KidCIBDknfwaAK6flNEWoBySGmvhilGp/HNjBW9uq1aI8g3QUl3C5785Ezh68VJXxT62/HYqGAyMv389tuRsANy1pVSvexPHztW0VBXjqSvHaLFhzxpK6hmXk37etR2WdRzL2h9nH3U8ji/XkP/AVdhS+jP+/vVhr+H4cg3lKxbj3JOHz1mDyR5L7KCxpE+/vltDhd5SvWEpAPas4SSedm6H81kX3kTN+jdpPrCT5tICorOHd2jTE2IHjaF67Wt4HJUn5H4iIt922uJYRKQTA5KiGN8/VIPire01nbZ7c1vo3OScuLYABeCu5UXc+9F+Vu5xUOH0YLcYaWjxk1fSyJ3vFfGDF3bi8fXwOpEjBINB7l5exFWL81mWX0u500uU2Uhds49PCuv50b8KuPPdfSdsPBJSUNVMTZMPgKlDwheuPeeU0PEvDjbR6PafsLFJz4hKHUDskFDIWbPhrU7b1Wx4E4C43MltAQpA0ct3sf+1e3Hkr8RTX4HRasfvaqBxTx5F/7qTnQ/9gIAvsuVr3SEYDFL0yt3kP3AVtXnL8NaXY7RG4Wuso377JxQ8+iP2/evOEzaennKonkjCyKlhz8cMGoMpOvS96vhyzQkbl7NwE0Cf30lIRKSv0EwUEZGjmHN6KpsPNLJ0ezU3n5Mdts3bO6oBuOz01HbHh6XZOfvSwUzPTSQnyYbBYMDl9fPRrnruWl7E2qIGHvusjFvP69/jzwPgqbUHeWrtQTLjrfz3BTnMHJFMrM1Ek9vPm9uq+eMHxTy7vpwx2bHMHZN2QsYkoWK2AAYDDE2zh20zNDUagGAQCqtdjA1TYFb6ltTJc2jcu5nqDUvJvuTmsG2qN7zd2vaydsftWcMYPOJsEkdNx5aag8FgwO9xUb/1I4peuYuGgrWUvfcY/Wff2tNPA4CDHzzFwQ+ewpqUSc53/5vkcTMx2WPxtzRRvf5Nipf8kfKPnyV20BjSpsw9IWPqbsFgENfBQgCis4aFbWMwGLBnDKFx7+e4Du7u0fH43c20VBVT8ekL1GwMBXEZ5/+wR+8pIiIhClFERI5i9ukp3P1+ETvKmymsdpGb2v5D7s6KJgoqXZiNBmafltLu3K/Oz+lwPbvFxOzTUsiIs3L5M9v5v00VJyREcbh8/PmTEqKtRl6+fiS5R3xYj7GZuGZiOnFRJn66ZDd/W1XapRDlwU9KeOjTA8c1rhOxbfDJrrJ1C+WEKDO2TpZ39YuzHG7feOJmGEjPSZk0m6JX7qa5ZAeu8kLsGbntzjcd2ImrrACDyUzKpNntzuVc/qsO1zNZ7aRMmo01KYPt911OxX/+74SEKL5mByVL/4zRFs3I217Gnnn4eZiiYkg/7xpM0XHsfuKnlL77ty6FKCVLH+TAWw8d17hG/mpJW82S7uB3OQl4QoGnJaHzbdItCekAeB1V3XbvQ4J+H+t+MrDDcYPZRvYlPyN9+g3dfk8REelIIYqIyFGkx1k5c1A8a/Y18Na2ahZNbz9demnrUp6zB8eTEmMJd4mwJuXEkRBl4mCDh4MNbjLjbcfu9DUsy6+h2RNg9mkp7QKUI11yago2cyG7q1xUOD2kx0VWUyHGaiItNvLnfiSLSatKm72h5TlfrYVyJPsR55o9J24JmPQca2I68cPPpOHLNVSvf4sBcxa1O1/TWn8jfsTZWOJSwl0irLjcSZiiE/DUHcRddxBbUma3jvurajYtI+BuJmXS7HYBypFSxl9CodmG6+BuPPUVWBPTI7q2yRaDJf74ZsUZzcf3ntSZgLv58LWt4etjQSjMAvC7m7r1/gAYDG2vh6+5gaDPDQYjWTN+QsZ3fnjCC2KLiHxbKUQRETmGy09PDYUoO2o6hCiHlvLMGZUarisbiht4YVMFeSVOKhq9tHg7fgCudHp7PETJK3ECsGJ3HWMf2NRpO68/CIS23I00RFlwdhYLzlaxU5GuSp18OQ1frqFmY8cQpXrjoaU8c8L2bdi9gYpPX8C5Jw+vo4KAp6VDG6+jssdDFOeePADqvljBpl+M7bRd0B+aceWuLYs4RMmauYCsmQu+9hi/KQxGExP/sgWAYCBAS1UxZcsfp3TZo1StWcKIhS8QM2Bk7w5SRORbQCGKiMgxXDIymTve3cfuKhf55U2MzIgB4PMDTopq3djMBi4+teOuNo+sPMCfPj68ta7FZCDRbsZiCv22sKbJSyB4eCZCT6psDH2AafIEaIpgJoMrTNgjPSPaYgIIG7AdcuTfR7RVs3e+KZInXMK+F+/AdXA3TSX5bR+AnXs/x11ZhMFsI3n8xR36HVj2CCWv/6ntscFkwRyTiMEUmn3hddZAMID/iNkTPcXbuiNMwN1EIILZF4eWxPQ1Rlt025/DBVaH+Fufn8kW06PjMRiN2NMHc8oN92OOjqds+eMUPn0Lo3//AQaj3iNERHqSQhQRkWNIirZw7ikJfLyrnqXba9pClKWtO/ZMz00kPqr92+nOiiYeWBEKUG6YlM6Pz8xkcHJUuy10Jz6Yx8EGD8Fgzz+HQOtNbjk3m998p2OtFuk9h+qdOFp8uH2BsHVRDoVgAOmxXdu6Vk5eltgkEk47l/ovPqZmw9K2EOXQUp7EUdMxR8e369N0YCclbzwAQPr0G8i84MdE9Rvc7oNz3i8n4qk7yIl4cwkGQwFf9qW3kPPd3/T4/XqLyR6H0RZNwN3cFhyFc+icJbHzuindLWP6Dylb/jjNB3bStH8bsYPGnLB7i4h8GylEERGJwOWjUvl4Vz1vb6/m9gtyCAaDvL0jFKKEW8rzXn4tgSCcNSiee2cN6XDeHwhS5/J1eRwmI/gD4PaF/3Dk7GT729SY0AfvUoe7y/c8lic+K+OJNWXH1fcf3xvOpJy4bh5R33JoR55DO++cltHxN9iFR+zgc0pq+Jo20jelnnE59V98TPXGt8m58naCwSA1m1qX8pzRcSlPbd57EAwQP/wshlx7b4fzwYAfX1Nd1wdiNEHAT9Ab/j3C73KGPW6ND73/uWtLu37PYyhb/gRl7z9xXH2H3/wP4nInddtYQjvvnEJT8bZOd94JBoO4yvcCEJ05tNvufSyWI5ZHtVQVK0QREelhClFERCIwY3gyURYjxXVuPj/gxO0LUt7gIdpq5MJhSR3alztDO6iMzgo/pXvzgcajLt/oTHyUmbpmHwednrAFYreWNobtN75/LK9urWL1Xgc+fxCzqfsKEDZ5/FQdMVOiK7x+LRsanhZNSoyZmiYfq/Y4woYoq/bWAzAmK4ZYm+kEj1B6UvLYGRitUbirinHu/Zyg142nrhyjLZqk0Rd2aO+pLwcgZuDosNdr3Lv5qMtNOmOOjsfXWIen7mDYArGNRVvD9osdMp6qNa/iyF9N0O/DYOq+/1r63U14G45vl5uA7/jek44mfvhZNBVvoz5/ddjzTcVf4G+uD7Xtxp2BjsVdc3jZaE8vIxIREYUoIiIRibGZuGBYEu/sqGHp9hrcvtCH/xnDk7FbO36oPfRBd091xw8zgUCQhz4t6XA8EiP6RbO2qIEPv6zlnCHttwaud/l4aXP4aeazT0vhng+LqXB6+fvqUhYeZVvlepePRHvkPx5umz6A275ScFciZ2zdHnvxhgpe2FTOj87IaLekp6bJyxtftBYwPj18AWPpu0xRMSSNvoCaTe9Qs2EpgdaZIMljZ2CydQxKTVGxALRU7OlwLhgIULL0+LYEjs4eQUPBWmq3fEjCyHPanfM11VO56qWw/VImzqZ4yT14HRWUvvd3+s9a2Ok9fE31mGMSIx7TgDm3MWDObRG372mpk+dw8IOncJV+iSN/VYfX6eCHTwMQ3f9UorOGddt9jxVOHfzgKQAMJjOxQ8Z3231FRCQ8VZ4SEYnQnNND24y+vaOGZfmhpTyXjQq/9ejU1oDjo111PLmmrC10KalrYf6SXawvbjiuAqGzRobu92JeBa9urcLTet2tpY18//l8PJ3M7EiOsfDr80O1UO5fUcKd7+5jf93hgKfJ7Wflnnp+/tpu5v97V5fHdbJpaPFR2+Rt+wq0rn5q9vjbHw90XBZV72rf9xCn2x/2+CEldS1k/34t2b9fy5p9ji6N9+ap2URbjRTVurn51d1UNYZmMhXXtvDjlwtwtPjJjLdy3aTIdjWRviWldQeemk1vU5O3rPXYZWHbJoycCkDd1o8oe//JttClpbqEXU/Mp2HX+nZFUCMew8RZAFSsfJGqNa8S8IX+DTYWbSX/we8T8HrC9rPEJZNzxa8BKHnjfvb9605aqva3nfe3NFG/YyW7//Fzdj0+v8vjOpnEDh5L0tgZAOx+eiGOgrUABLwtlLz1F6rXvQ7AgNbX46s2//oM1v44m5KlD3bpvlvunE75isXtXtdgMEjTgZ0UPvsLKj59AQjVyLHEdpwZKSIi3UszUUREInT+0CTibCbKG0IfJhLtJqadkhi27fTcRM4fmsiK3fX84f1i7vmgmDibCUeLH6MB7ps1hEdXldLs6VqNkh9M6Me/t1SytayJha8X8sule7CaDDR5AmQnWPnDxYO55fXCsH1vOisTh8vHwysP8Oz6cp5dX06szYTJAA1uf1sNyrMGxYft35f810sFrC1q6HD8f94t4n/eLWp7vO7WcQxIimrXZsYTX3CgvuPfy3+9VNDucendZ3XPYIGsBBt/v3IoC5bs4r2dtSz/spY4m4mGllCNm4QoE8/MG47doqU830RJo8/HZI/DUxdaqmOKTiTx9Glh2yaePp3EUedTv20Fxf/+A8VL7sFkj8Pf7ACDkSHX3Ufpskdxd3Fnnn7n/oDKz/5NU9FWCp9ZyJ7Fv8RgthJwN2FNzmbwD/5A4dO3hO2beeFN+JocHHjnYco/fpbyj58NzZgxmvC7GtoK3MYP777vmd5yyo8eZMefinCVFZB//1yMthiCPjdBf6jGVfashSSPvahb79lSsZd9L94BgMFswxQVg9/dTNB7OAhPPetKBl51Z7feV0REwtNMFBGRCEVZjMw8Yivji09NwRpmJxUIFSF8Zt5wFk3rz6DkKExGAyajgfOHJvLS9SO5duLxzSiwmo28fMNIbjork+wEKwZCdVJumJTO8vmjyYw/+s4tvzx/AMvnj2beuDQGJtnwBYK4vAEy461cMCyJey4ZxFNXd9809G+Tita6MFFmA8PSuj4T4KIRySz7ySguH5VCv1gLLd5QMHbNhH58+NMxjMmO7e4hy0nCaIkiedzMtscpEy7GaA7/vWwwGBj+s2fof9kiovoNwmA0YTCaSBx1PiNve4n08649vjGYrYy87WUyL7wJa3I2GAyYo+NJn34Do3+3HGtS5lH7D7j8l4z+3XLSps7DljaQYMBHwOPCmpRJ0pgLGPSDexj206eOa2wnE0tsEqP+Zxn9L7sNe9YwCPoxRcWSMPIcRtyyuG1WzlcF/T68jbUAxAwc1aV7Dv/5c2R858fEDByNOSYRv8sZ2uI4M5e0s69m5K9fZeiNj2A0W7728xMRkWMzBIMnYnNNEZGTx+bNm5kwYQLL549iVJY+mPYlc5/bwdqiBh66/BS+N+7EbSEaib+tKuW+j/Zzw6T0sDsynQjZvw8tLwg3w6Yz28oamfnkNvLy8hg/XvUUjteh95VRv1tObBc/JEvv23H/XBoK1nLKjx6i39Tvdfv1nXvy2H7vZdizhjPmDx9jMHRfce9IHc9zbCzexrY/zNT7g4jIETQTRUREpBusK2rAbDTw07OzensoInKSaShYB0D2JTf3SoAiIiLdRzVRRESkz1n05h4WvRnanaQrsy56ij8QZFOJk8tOTznhYzk0O0dEvr49zy1iz3OLABj3p3VEpXbPzmMNu9ZhSx1AamsR4ROlZOmDHHjr+HZsEhGR8BSiiIhIn5FoN5MW237dv9HY+7/VNRkNfPnbyb1y75P1NRHpS8wxiVji09odMxi7b8L2qbe+0G3X6gqTLabD8zJaezd0FhHp6xSiiIhIn/H0vOG9PYSTjl4Tka9v+M1P9/YQekTWzAVkzVzQ28MQEflGUU0UEREREREREZEIKEQREREREREREYmAQhQRERERERERkQgoRBER+Yab+9wOsn+/llc+r+ztoYhIH7Lj/rms/XE2latf6e2hiIiInDRUWFZERCQCPn+QxRvKeXVrFXtrXJiMBob3i+aaCelcNTbt2BcQkW8d5548Gvd+TmPRVhqLttJSsReCQfpftogBc27r7eGJiMhxUIgiIiJyDG5fgGte2MnaogYAoixGvN4AG/c72bjfyaq99fz1ilwMBm0tLCKH7fzLtfhdDb09DBER6UYKUURERI7hfz8oZm1RAzFWIw9dnsulI5PxB+DFvAp+914Rr22tZlx2LD86I7O3hyoiJxGjNQp7xinEDBpN7KAxlK9YTFPxF709LBER+RoUooiIiBzFwQY3L2yqAOD3MwYx67QUAMwmuGFyBmUNHv62qpSH/1PKDyakYzOr3JiIhEz48yYMRlPb4+p1r/fiaEREpDsoRBER6YPWFzfw/MZyNux3Ut3oJS7KxIBEGxcMS+Lqcf3ITrBFdJ21RQ6W7ahl8wEnZQ0eHC4fSdFmJgyI46YzM5k8MD5sP7cvwOIN5by9vYbCahctvgBJdjPpcVamDI7n6rH9GJEe3a7PZ/scPLe+nM0HnNQ2+4i2GEmJsXB6ZgwzRyQzZ1Tq135desJ7+bV4/EES7eawtU9uPDODx1aXUt3kZdVeBxcMS+qFUYpEpmHXeso/fR7n7g14G6ox2eOwpQ4gafQF9Jt6Nbbk7Iiu4yhYS+2mZTj3bsZTW4av2YE5Jom43AlkXngT8UMnh+0X8LopX7GYmo1v4yovJOBpwRybhDUxnfjhU+h39tVE9x/R/l5ffkb5x8/h3LMZX2MtRls0lrgUYnJOJ3ncTFLPmPO1X5eecmSAIiIi3wwKUURE+pBAIMhdy4t4Zn1527H4KBMub4AtpU1sKW0iEITbpg845rWa3H7mPpff9jjOZsJsMlDh9PJufi3v7azlvkuHcN2k9Hb9vP4A8/6Zz4b9TgCMhtAYqpu8VDZ62XawCbPRwG8vHNjW558byvntsn1tj2NtJty+AHtrWthb08LaooaTNkQ5VAfljIFxWMPMMkmLtTK8XzQ7K5pZs08hipycgoEARS/fRfnHz7QdM9njCXhcNO3bQtO+LRAMRFTs1N/SRP79c4+4ThwGkxmvo4LavHep3fweQ669j/Rp17XrF/B5yX9wHs7dG0IHDEZM9ni8DdV4HZU0FW/DYDIzcO5v2/qUf/JP9v3f4cemqFgCXjctFXtpqdhLQ8HakzpEERGRbx6FKCIifcijq0p5Zn05BgMsmJLFjWdmkhFvBaCkroVl+bXE2iL7zafRALNPS2Hu2DQm58QRHxX6kVDe4OGZdQd57LMyfvfePs49JYGByVFt/d7YVs2G/U5SYsw8dHku005JxGwy4PUHKKl3815+LYn2wz9emj1+7vmwGICfnZPN/LMySY6xAFDT5GVdcQMrdtV1y+vTE3ZXuwAYmhbdaZuhaXZ2VjSzu8p1ooYl0iWl7z4aClAMBrJmLCDzghuxJmUA0FJdQm3eMkxRsZFdzGAkZdJs0s6aS9zQyZijQzPWPHXlHPzoGcqWP8a+l35HwmnnEpV2OEytXv8Gzt0bMMelkPujh0g8fRoGk5mAz4u7poTavPcwxyS2tfe7mylecg8A2Zf8jMyL5mOJSwbA66yhoWAdddtWdMOrIyIiEjmFKCIifUR1o5dHVh4A4Pbv5HDzOe2n3Q9IimLB2VkRX89uNfHE1cM6HM+It3LHRQNxtPh4Ma+SVz6v5NffyWk7//mBRgDmn5XVbtaFxWRkSIq9w7gKKptp9gTITbVz+wU57c6lxFi4dGQKl45MiXjcAGv2Obhqcf6xG4axaFr/iGbqHFLp9ACQHmvptE2/2FCQVdXoPa4xifQkb0M1B955BICc795O9iU3tzsflTqArBkLIr6eyWZn2IInOhy3JmUw8Ko78DU7qFz5IpWrXyHnil+3nW/c+zkAWRfNJ2nMBW3HjWYL9vQhHcbVXFpAwN2MPTOXnCtvb3fOEpdCysRLSZl4acTjBnB8uYb8B67qUp9DtC2xiIiAQhQRkT7jnfwaWnxBMuIszJ8SeVhyvM4fmsSLeZVsbg1NDolrnelS0eiJ6DpxttCPGqfbh8vjx279+jUCLCYjaUcJNY4mpov3b/YGgNC2xp2xt55r8viPa0wiPalm0zsEvS1YEjPImjG/x++XNOp8Kle+SOPeze2Om+xxAHgcFRFdx9za3tfsxO92YbLZv/bYjGYLlviOtY0iYbLFfO37i4hI36cQRUSkjzg0A2TqkNDyme7g8QX41+ZKluXXUFDZjMPlxxcItmtT+ZWwZFpuIn9fXcaz68upa/ZxxehUJufEd7qMaFByFIOSbRTVupn99HZ+ODmDc09JICcpKmz7SEzKiWPLryYed3+Rb5PGfaEZIIkjp2Iwdc9//QI+D5Ur/0VN3jKaSwvwNzsI+n3t2njqK9s9Tjx9GmXv/Z3yj5/F11hH6plXEJ87GZM9/DKiqH6DsPUbhLuyiO33zibj/B+SMPJcotJywraPRFzuJCb+Zctx9xcREVGIIiLSR9Q0hZaKZCdYu+V6zhYf857PZ0tpU9uxaKuRRIsZgyFUQLbe5afZE2jXb8rgBBZN689fVx7g9S+qef2LaowGGJkRw0XDk7huYjr94g6P0Wwy8OiVQ7nx5QJ2VjTzm7f3ApAeZ+HcUxKZN64fZw4KvwvQySDaYsTh99PiDXTaxtV6rquzXEROBG9DDQDWCHfeORafy0n+g/NCxWhbGW3RrfVMDAR8XvzN9QQ8ze36JYyYQv/LFnHgnb9Sve710Ha/BiMxA0aSNPYi0qddhzWhX1t7g8nM0JsepeBvN9J8YCd7n/8NAJaEdBJPO5d+U+cRP/zMbnlOIiIikVKIIiLyLfXwfw6wpbSJ+CgT9146mGm5iSRFH14is2qvg3n/zCcYpu9t0wdw5Zg0lm6rZl1xA5tKnGw/2MT2g008uaaMZ78/gqlDEtraj+8fx2e3jGPZzlr+U1jP+uIGSh0elmypYsmWKq6flM59s4acgGfddf3irDhaXFQcpd5JVetsnX5xx7fESKQvOfD2wzTt24LJHs/ga+8l8fRpWGIP10dy5K8i/8F5EOz47jFgzm2knXUl1RuW0lCwDueeTTTt307T/u2Uvf8kI37+LAmnTm1rHzdkPOPu+4zavGXU7/gPDbvW46ktpWrNEqrWLCF92vUMue6+E/K8RUREQCGKiEifkdpaA+SAw90t11uWXwvAXTMHccXojjUCDs186cyg5CgWntefhYRmraze6+Dej/aTX97MwjcK2fCL8ZiMh5cd2a0m5o5JY+6Y0L0Kq108s+4gz2+s4PmNFcwYkcy03MSIxr5xv5ObXimI7Il+xYIpWV0qwDs01c7uKheFVc2dtmnbwSf169dsEOlulvjQ9uHumgPdcr3avGUADJp3F2lnXtHhvNdZc9T+Uf0G0X/WQpi1kIDPi2Pnava/di/NJfkUPrOQ8fdvwGA8PKvLZLOTNmUuaVNC2yq7ygs5+OEzVHz6PBWfPk/yuBkknj4torE7CzdS8PebInym7WXNWEDWzMgL8IqIyDdT51XyRETkpDK+f6huwOq9Dnz+cPNDuqa8ddeZMVnh6xGs2eeI+FoWk5HpQ5P4x/eGh67d4KGotuWofXJT7dw3awiTc0LFI9cWNUR8P68/QFWj97i+ulr89azWpUbrip14fB2X9FQ1eviyIhSwTBmc0OG8SG+LPWU8AI781R3qlhwPT1156LqDxoQ97/hyTcTXMpotJI2azvD/7x9t126pLDpqH3tGLkOuu4+4oZMBaChYG/H9Aj4v3oaq4/ryu5uOfQMREfnG00wUEZE+YtbIFO5+v5gKp5cn15R12Eq4q2JtJuqafeypcTEiPbrduT3VLl77ojpsP48vgNUcPoOPOuK4uzVwOFp7OLzrjTtMQNGZKYMTKL37rIjbfx0Xj0zmjx8UU+/y8drWKr4/Ib3d+WfXlxMIQmqMpd0SJpGTRcqEWRS/cjdeRwVl7z/ZYSvhrjLZY/E11uEq30N0/xHtzrnK91C97rWw/QI+D0Zz+JpORsvhQtMBr/uY7Y/sc6h9JBJGTOGsZ0ojbi8iIvJVmokiItJHJMdYWHhuKDi57+P9/O8HxZQ3HN45p6SuhYc+KeH5jeURXW9q66yJP75fzKYSJ8FgkEAgyCe76/j+8/ntApEjLXyjkNveLGTlnnqa3IdndRRWu1j0ZiEAGfFWhvcLBTMrdtdz2dPbeCmvgtIjliI1uv08vrqUVXtDM14iXcpzomXG27huUig4uev9Yt7NryEYDOLzB3lhYwWPrS4D4NbzsrEdJSwS6S2WuGSyZy0EYP/r91G85H/bZpMAtFSXULL0Ico/fT6i6x2qWVK85I84CzcRDAYJBgLUbfuE/Ae/3y4QOVLh0wspfO426nesxN9yeFaHq7yQwucWAWBNyiA6OzSjrf6LFWy79zIqVr2Eu/Zw8OF3NVK6/HEcO1cBRLyUpzf4W5rwOmvbvgKtM4ECHlf7476jL58UEZGTh2aiiIj0IT+bmk2l08tzG8p57LMyHvusjIQoE75AkKbWXXQWTesf0bV+ef4A/rOnnpJ6N3Oe3o7dYiQYDNLiC5IRZ+GumYO49Y3CDv3cvgBvba/h5c+rMBggIcpEiy/YtnuN3WLk4Sty29VDyStpJK+kse281WTA0XI4gLl2YvpJG6IA3HHhQPLLm1lb1MBNr+zCbjESCAZx+0LLqq4ck8oPJ2f08ihFOpd98c/w1ldSvuI5ypY/RtnyxzBFJxD0+wi0LlPpf9miiK414PJfUr/9P7irS9h+3xyMVnsoSPG2YEnMYNC8uyh85tYO/QJeNzUb36Jq9ctgMGCyJxD0tRDwhJb+Ga12cv/r4Xb1UBr35NG4J6/tvMFsxd98eKlh+nnXntQhyr4X76BqzZIOx8uWP07Z8sfbHo/81RISRkw5kUMTEZHjpBBFRKQPMRoN3HPpYC4emcziDeXklTipbfaRaDczrF80Fw5L4upxHYvEhpObauftm0bxwIoSVu910OzxkxFv5TtDk7j1vP7s6qSQ6u0X5DBxQByr9zooqm0J7VoTDDIkJYpzhiQwf0oWA5MP/yb67MHxPPLdXFbucbD9YCPlTi+Nbj9psRZGZ8VwzYR0ZoxI7pbXp6fYzEZevn4kz20o59WtVeytcWE1GhmVGc21E9O5amxkr7lIbzEYjQy+5h6SJ1xM+YrFOAvz8DXWYo5JJDp7GEljLiTt7KsjupY9I5dR//M2JW88gGPnavzuZqyJGSSN/g79Z99Kc9musP1yrryduNyJOHaupqWyCK+jgmAQotKHkDDyHLJmzCcqbWBb+/hTzyb3xkdw5K+ksXg73vpy/C2NWOLTiBk0mvRzryF53IxueX1EREQiZQgGw+w/JyLyDbZ582YmTJjA8vmjGNVJUVWRb4ttZY3MfHIbeXl5jB8/vreH02cdel8Z9bvlxA4c1dvDEekWjcXb2PaHmXp/EBE5ghZvi4iIiIiIiIhEQCGKiIiIiIiIiEgEFKKIiIiIiIiIiERAIYqIiIiIiIiISAQUooiIiIiIiIiIREAhioiIiIiIiIhIBBSiiIiIiIiIiIhEQCGKiIiIiIiIiEgEFKKIiIiIiIiIiERAIYqIiIiIiIiISAQUooiIiIiIiIiIREAhioiIiIiIiIhIBBSiiIiIiIiIiIhEwNzbAxAR6S27q129PQSRXqfvg+7lOri7t4cg0m3071lEpCOFKCLyrZOamkq0PYqfv1bY20MROSlE26NITU3t7WH0aampqUTZoyn8x897eygi3SrKHq33BxGRIxiCwWCwtwchInKi7d+/n+rq6t4ehshJITU1lZycnN4eRp+n9xX5JtL7g4hIewpRREREREREREQioMKyIiIiIiIiIiIRUIgiIiIiIiIiIhIBhSgiIiIiIiIiIhFQiCIiIiIiIiIiEgGFKCIiIiIiIiIiEVCIIiIiIiIiIiISAYUoIiIiIiIiIiIRUIgiIiIiIiIiIhIBhSgiIiIiIiIiIhFQiCIiIiIiIiIiEgGFKCIiIiIiIiIiEVCIIiIiIiIiIiISAYUoIiIiIiIiIiIRUIgiIiIiIiIiIhIBhSgiIiIiIiIiIhFQiCIiIiIiIiIiEgGFKCIiIiIiIiIiEVCIIiIiIiIiIiISAYUoIiIiIiIiIiIRUIgiIiIiIiIiIhIBhSgiIiIiIiIiIhFQiCIiIiIiIiIiEgGFKCIiIiIiIiIiEVCIIiIiIiIiIiISAYUoIiIiIiIiIiIRUIgiIiIiIiIiIhIBhSgiIiIiIiIiIhFQiCIiIiIiIiIiEgGFKCIiIiIiIiIiEVCIIiIiIiIiIiISAYUoIiIiIiIiIiIRUIgiIiIiIiIiIhIBhSgiIiIiIiIiIhFQiCIiIiIiIiIiEgGFKCIiIiIiIiIiEVCIIiIiIiIiIiISgf8HP4SEx2AoaDkAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1400x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(14,12))\n",
    "_ = tree.plot_tree(DTall_model, feature_names=feats_.index, class_names='01', filled=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "|--- Trot_Speed <= 2.96\n",
      "|   |--- FB35R <= 62.25\n",
      "|   |   |--- class: 0\n",
      "|   |--- FB35R >  62.25\n",
      "|   |   |--- HMPL5 <= 4.08\n",
      "|   |   |   |--- class: 1\n",
      "|   |   |--- HMPL5 >  4.08\n",
      "|   |   |   |--- FB16L <= 21.88\n",
      "|   |   |   |   |--- class: 0\n",
      "|   |   |   |--- FB16L >  21.88\n",
      "|   |   |   |   |--- class: 1\n",
      "|--- Trot_Speed >  2.96\n",
      "|   |--- Age <= 17.00\n",
      "|   |   |--- class: 1\n",
      "|   |--- Age >  17.00\n",
      "|   |   |--- class: 0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "tree_text = export_text(DTall_model, feature_names=list(X.columns))\n",
    "print(tree_text)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.5"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}