{ "cells": [ { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "p6M192uAL7dB" }, "source": [ "

Data and Scripts
for Hydrological Streamline Detection Using a U-net Model with Attention Module

\n", "

\n", "$Zewei$ $Xu^{1,2}$; $Shaowen$ $Wang^{1,2}$; $Lawrence V.$ $Stanislawski^{3}$; $Zhe$ $Jiang^{4}$; $Nattapon$ $Jaroenchai^{1,2}$; $Arpan Man$ $Sainju^{4}$; $Ethan$ $Shavers^{3}$; $E. Lynn$ $Usery^{3}$; $Li$ $Chen^{2,5}$; $Zhiyu$ $Li^{1,2}$; $Bin$ $Su^{1,2}$\n", "

\n", "

\n", "$^{1}$$Department$ $of$ $Geography$ $and$ $Geographic$ $Information$ $Science$, $University$ $of$ $Illinois$ $at$ $Urbana-Champaign$, $Urbana$, $IL$, $USA$
\n", "$^{2}$$CyberGIS$ $Center$ $for$ $Advanced$ $Digital$ $and$ $Spatial$ $Studies$, $University$ $of$ $Illinois$ $at$ $Urbana-Champaign$, $Urbana$, $IL$, $USA$
\n", "$^{3}$$U.S.$ $Geological$ $Survey$, $Center$ $of$ $Excellence$ $for$ $Geospatial$ $Information$ $Science$, $Rolla$, $MO$, $USA$
\n", "$^{4}$$Department$ $of$ $Computer$ $Science$, $University$ $of$ $Alabama$, $Tuscaloosa$, $AL$, $USA$
\n", "$^{5}$$School$ $of$ $Geosciences$ $and$ $Info-Physics$, $Central$ $South$ $University$, $Changsha$, $Hunan$, $China$
\n", "$Corresponding$ $Author:$ $nj7@illinois.edu$\n", "

\n", "\n", "---\n", " \n", "**Notebook Structure:** \n", "[1. Introduction](1_Introduction.ipynb) \n", "2. Codes \n", " [2.1. Data Preprocessing](2.1_Code_Data_Preprocessing.ipynb) \n", " [2.2. Model Training](2.2_Code_Model_Training.ipynb) \n", " [2.3. Interpret the Result](2.3_Code_Interpret_the_Result%20.ipynb) " ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "ecT7lcyjL7dF" }, "source": [ "---\n", "\n", "### Interpret the Result\n", "\n", "This notebook contains the code that we used to extract statistics and evaluate the result of CNN training. " ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "dm5i6L5dL7dH" }, "source": [ "---\n", "\n", "The cell below is to initiate the function that will be used to extract trainging and validating statistics during the CNN training. " ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "colab": {}, "colab_type": "code", "id": "cvYmdu1Oehkp" }, "outputs": [], "source": [ "root=\"/home/jovyan/shared_data/data/unet_streamline_detection/\"\n", "m='v2'\n", "aug = '_aug'+m #+sys.argv[1] #'v2'" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "colab": {}, "colab_type": "code", "id": "vzN0Nez5L7dI" }, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import itertools\n", "import os\n", "import pickle\n", "from itertools import chain\n", "from skimage.io import imread, imshow, imread_collection, concatenate_images\n", "from skimage.transform import resize\n", "from skimage.morphology import label\n", "from sklearn.metrics import confusion_matrix\n", "\n", "\"\"\"\n", "plot_history(): reads Keras result and ogenerate figure of Loss, Dice Coefficient, and Accuracy.\n", "\"\"\"\n", "def plot_history(history):\n", " loss_list = [s for s in history.keys() if 'loss' in s and 'val' not in s]\n", " val_loss_list = [s for s in history.keys() if 'loss' in s and 'val' in s]\n", " dice_list = [s for s in history.keys() if 'dice' in s and 'val' not in s]\n", " val_dice_list = [s for s in history.keys() if 'dice' in s and 'val' in s]\n", " acc_list = [s for s in history.keys() if 'acc' in s and 'val' not in s]\n", " val_acc_list = [s for s in history.keys() if 'acc' in s and 'val' in s]\n", " \n", " if len(loss_list) == 0:\n", " print('Loss is missing in history')\n", " return \n", " \n", " ## As loss always exists\n", " epochs = range(1,len(history[loss_list[0]]) + 1)\n", " \n", " ## Loss\n", " plt.subplot(1,3,1)\n", " for l in loss_list:\n", " plt.plot(epochs, history[l], 'b', label='Training loss (' + str(str(format(history[l][-1],'.5f'))+')'))\n", " for l in val_loss_list:\n", " plt.plot(epochs, history[l], 'g', label='Validation loss (' + str(str(format(history[l][-1],'.5f'))+')'))\n", " \n", " plt.title('Loss')\n", " plt.xlabel('Epochs')\n", " plt.ylabel('Loss')\n", " plt.legend()\n", " \n", " ## Dice Coefficient\n", " plt.subplot(1,3,2)\n", " for l in dice_list:\n", " plt.plot(epochs, history[l], 'b', label='Training Dice Coefficient (' + str(format(history[l][-1],'.5f'))+')')\n", " for l in val_dice_list: \n", " plt.plot(epochs, history[l], 'g', label='Validation Dice Coefficient (' + str(format(history[l][-1],'.5f'))+')')\n", "\n", " plt.title('Dice Coefficient')\n", " plt.xlabel('Epochs')\n", " plt.ylabel('Dice Coefficient')\n", " plt.legend()\n", " \n", " ## Accuracy\n", " plt.subplot(1,3,3)\n", " for l in acc_list:\n", " plt.plot(epochs, history[l], 'b', label='Training accuracy (' + str(format(history[l][-1],'.5f'))+')')\n", " for l in val_acc_list: \n", " plt.plot(epochs, history[l], 'g', label='Validation accuracy (' + str(format(history[l][-1],'.5f'))+')')\n", "\n", " plt.title('Accuracy')\n", " plt.xlabel('Epochs')\n", " plt.ylabel('Accuracy')\n", " plt.legend()\n", " plt.show()\n" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "IMjg-AMKL7dN" }, "source": [ "# **Plot the Result**\n", "\n", "The plot is generated based on the log of the trainging and validating processes which contains the statistic of training and validating phases." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 370 }, "colab_type": "code", "executionInfo": { "elapsed": 925, "status": "ok", "timestamp": 1583962920866, "user": { "displayName": "nattapon jaroenchai", "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj9i_TMlYzv27Vkas3v5qWkW7ZdTBQme3RVKqYp7c4=s64", "userId": "17092454241854925654" }, "user_tz": 300 }, "id": "5MweThWWL7dP", "outputId": "191013c6-99cc-43c5-fc45-7451540183b6" }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "infile = open(root+'result/history_augn2_attention2.pickle','rb')\n", "new_dict = pickle.load(infile)\n", "infile.close()\n", "plt.figure(figsize=(20,5))\n", "plot_history(new_dict)" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "ZUkUL2T6L7di" }, "source": [ "---\n", "\n", "### Confusion matrix\n", "\n", "The code below is used to generate the confusion matrix of the testing dataset. " ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 365 }, "colab_type": "code", "executionInfo": { "elapsed": 7216, "status": "ok", "timestamp": 1583963259820, "user": { "displayName": "nattapon jaroenchai", "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj9i_TMlYzv27Vkas3v5qWkW7ZdTBQme3RVKqYp7c4=s64", "userId": "17092454241854925654" }, "user_tz": 300 }, "id": "uy6Qwl17MgSi", "outputId": "70ef4ffe-272f-4ce0-929d-9b44953e7526" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Confusion matrix, without normalization\n", "[[5971553 48444]\n", " [ 161798 110017]]\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import copy\n", "import random\n", "import sys\n", "import numpy as np\n", "\n", "buf =30\n", "\"\"\"\n", "plot_confusion_matrix(): prints and plots the confusion matrix. Normalization can be applied by setting `normalize=True`.\n", "\"\"\"\n", "def plot_confusion_matrix(cm, classes,\n", " normalize=False,\n", " title='Confusion matrix',\n", " cmap=plt.cm.Blues):\n", "\n", " if normalize:\n", " cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]\n", " print(\"Normalized confusion matrix\")\n", " else:\n", " print('Confusion matrix, without normalization')\n", "\n", " print(cm)\n", "\n", " plt.imshow(cm, interpolation='nearest', cmap=cmap)\n", " plt.title(title)\n", " plt.colorbar()\n", " tick_marks = np.arange(len(classes))\n", " plt.xticks(tick_marks, classes, rotation=45)\n", " plt.yticks(tick_marks, classes)\n", "\n", " fmt = '.2f' if normalize else 'd'\n", " thresh = cm.max() / 2.\n", " for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):\n", " plt.text(j, i, format(cm[i, j], fmt),\n", " horizontalalignment=\"center\",\n", " color=\"white\" if cm[i, j] > thresh else \"black\")\n", "\n", " plt.tight_layout()\n", " plt.ylabel('True label')\n", " plt.xlabel('Predicted label')\n", "\n", "preds_test_mod = np.load(root_path+'result/preds_test_total_augn2_attention2.npy')\n", "\n", "dim = np.load(root+'data/reference.npy').shape\n", "numr = dim[0]//(224 - buf*2)\n", "numc = dim[1]//(224 - buf*2)\n", "count = -1\n", "for i in range(numr):\n", " for j in range(numc):\n", " count += 1 \n", " temp = preds_test_mod[count][buf:-buf,buf:-buf]\n", " if j == 0:\n", " rows = temp\n", " else:\n", " rows = np.concatenate((rows,temp),axis = 1)\n", " if i == 0:\n", " prediction_map = copy.copy(rows)\n", " else:\n", " prediction_map = np.concatenate((prediction_map,rows),axis = 0)\n", "prediction_map = prediction_map[:,:,0]\n", "# fig= plt.figure(figsize=(20,15))\n", "# plt.imshow(prediction_map*255,cmap='gray',vmin=0, vmax=255)\n", "# plt.show()\n", "\n", "#print(np.unique(prediction_map))\n", "\n", "# mask\n", "mask = np.load(root+'data/mask.npy')[:prediction_map.shape[0],:prediction_map.shape[1]]\n", "[lr,lc] = np.where(mask == 1)\n", "\n", "# Read reference data\n", "groundtruthlist = np.load(root+'data/reference.npy')[:prediction_map.shape[0],:prediction_map.shape[1]][lr,lc]\n", "predictionlist = prediction_map[lr,lc]\n", "\n", "# print(np.unique(groundtruthlist*255))\n", "# print(np.unique(predictionlist))\n", "# print(type(groundtruthlist))\n", "# print(groundtruthlist)\n", "# print(type(predictionlist))\n", "# print(predictionlist)\n", "\n", "cm = confusion_matrix((groundtruthlist).astype(int), predictionlist)\n", "plot_confusion_matrix(cm,classes=[\"Non-streams\",\"Streams\"])\n" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "sPyoCJSiL7do" }, "source": [ "The cell below will calculate 3 statistics that can be used to evaluate the performance of the model. " ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 125 }, "colab_type": "code", "executionInfo": { "elapsed": 20428, "status": "ok", "timestamp": 1583963331049, "user": { "displayName": "nattapon jaroenchai", "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj9i_TMlYzv27Vkas3v5qWkW7ZdTBQme3RVKqYp7c4=s64", "userId": "17092454241854925654" }, "user_tz": 300 }, "id": "BZ6Ruo7_L7dp", "outputId": "aa98c065-cb36-4995-8363-74ed70664699" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "F1 score of stream: 0.5113787429463879\n", "F1 score of nonstream: 0.9827008985507533\n", "Precision of stream: 0.6942843980537798\n", "Precision of nonstream: 0.9736199672903116\n", "Recall of stream: 0.40474955392454426\n", "Recall of nonstream: 0.9919528199100431\n" ] } ], "source": [ "# Statistics\n", "from sklearn.metrics import f1_score, precision_score,recall_score\n", "#print(f1_score(groundtruthlist, predictionlist, average='macro'))\n", "print('F1 score of stream: '+str(f1_score(groundtruthlist, predictionlist,pos_label=1)))\n", "print('F1 score of nonstream: '+str(f1_score(groundtruthlist, predictionlist,pos_label=0)))\n", "print('Precision of stream: '+str(precision_score(groundtruthlist, predictionlist,pos_label=1)))\n", "print('Precision of nonstream: '+str(precision_score(groundtruthlist, predictionlist,pos_label=0)))\n", "print('Recall of stream: '+str(recall_score(groundtruthlist, predictionlist,pos_label=1)))\n", "print('Recall of nonstream: '+str(recall_score(groundtruthlist, predictionlist,pos_label=0)))" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "EAUIFi-qL7du" }, "source": [ "The cell below is the code that show the result compare to the reference dataset " ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 831 }, "colab_type": "code", "executionInfo": { "elapsed": 1516, "status": "ok", "timestamp": 1583963334715, "user": { "displayName": "nattapon jaroenchai", "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj9i_TMlYzv27Vkas3v5qWkW7ZdTBQme3RVKqYp7c4=s64", "userId": "17092454241854925654" }, "user_tz": 300 }, "id": "KVULITnHL7dv", "outputId": "551a429d-a5ff-49bf-d7b8-2dbb3ebead81" }, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAABIoAAAMuCAYAAAB2O+iDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjMsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+AADFEAAAgAElEQVR4nOzde/B/W13f99c6HEOswYoXGOTggIbaoh3NcIaitl5qoySdCKZlijYRIpNjFJ3EmIwQWzVpMSSZ1oQYGY+XAGpkaKiBWCEiUYypIBylchH0KIjHQ8C7xEQQXP3j89n81m/99n2vvdZ7rfV8zHzn9/t+vp/L2mvvz17v/V6X7bz3AgAAAAAAAG4rXQAAAAAAAADYQKIIAAAAAAAAkkgUAQAAAAAA4IpEEQAAAAAAACSRKAIAAAAAAMAViSIAAAAAAABIIlEEAAAAALdwzj3NOeeDn/c7537JOfctzrk/fuB9v9w594vX9/udlGUGgBRuL10AAAAAADDsyZLuk/QgSV8s6VnX/3/N1jdyzn28pLslfb+kvyTpD9IVEwDSYEQRgOoFPX6PDB77Zufcf1uuVAAAoBFv8N6/xnv/Su/9V0n6UUlPd87tuZZ6tKQHSHqB9/4nvfevP1Iw59wDnHN0/gNIikQRgFZ9kyQSRQAAILWfkfThkj42fNA59yjn3Pc7537dOfc+59wbnHNfHPz9+ZJ+/Prrq66dXM8P/v6XnXP/n3PuD5xzv+Gc+27n3EdHn+Gdc892zj3TOfd2Se+X9F9e//axzrnnOed+7fr5b3XO3RW9fuhce/y1rL/nnLvfOffceDqdc+4jnHPPuU63e59z7t85517inHvo2m2eEpTjM51zL3bOvdc5927n3LOuf3+Cc+5nnXO/75x7nXPusdHrv8A598POuXc55/6Dc+5Nzrmvc849IHreO5xz33et23uvdfszzrnPWyoj0DOyzwCScs490Hv/vtLlAAAAOMkjJf2upN8cHnDOPULSayW9R9LXSvp1Sf+TpJc4557kvX+ZpP9N0j2SnivpGboknH79+vrnSPq669/+pqSHS/rfJX2qc+4zvfcfDD7/aZJ+WdLfkPT7ku53zn2kpH+rSwLrmyW9XdIXSnreNTb7x9E2fK+kH5D05yV9xvU1v61LR5ucc39M0islfbqkvyvpNZL+0+t7PljSu1du85IXSHqhLtPxnizpW5xzHyXpz0p6tqR/L+nvS/oXzrlP8t6///q6T5T0Kkn/WJfpe3det+HjJD0z+ozPkfRYSd8g6X2Svl7Sy51zn+a9f9uKMgL98d7zww8//Oz60aVB9pI+VdK/0qUxf+n1b39el6DiP0j6HUn/l6RPiF7/pZJ+9vq635X0RklfEfz9xyX9+MjnvkPS84Pfn3YtxyOvv/uRn28uXV/88MMPP/zww089P0F88cm6dLA/WNKXS/qApK+OnvvduiRKPiZ6/JW6TF0bfv/vru/5ucFjj5T0QUnfGL32s67PfVLwmJd0v6QPj577v+qSMHl09Ph3SvoNSbdH2/S3o+f9kKRfCH7/8uvzvmimflZt80LdfmPw2O26JJ3+UNKjgse/6Prcz5l4L3d97Tfokuy6LfjbO3QZdfUJwWMPkvRbkr639DHGDz9Wf5h6BiCFl0p6tS4N+bc65/6KpJdIeouk/1HSV+iSTHq1c+5BkuSc+68lfd/1dU/SpRfpOyV9VILyfMb13+df//8Zkr4rwfsCAID+vFWX5MVv6ZIc+Q7v/bdFz3mCpB+W9LvOuduHH1060j7tOuJnyp/WZUmQ749e+1pJvyfps6Pnv8J7/x9HPv+1kt4+8vkfI+kx0fP/n+j3N0r6hOD3L5D07/z8qKAj2zx4+fAf7/0HJN2rS8Lq7cFz3nr99xHDA865hznnvsM59yu6JIL+UJcRWB8l6SHRZ7zGe//O4HPeq8v2f4YAjGLqGYAUnuu9/0eS5Jz7E7okjv6p9/7Lhyc4514r6RckPV3SP5T0eEm/473/a8H7/EiKwnjvX+Ock6Rf896/JsV7AgCAbn2xLnc9+zhJf13SVznnXuu9f2HwnIdI+rLrz5iP0SXpM2ZIbNw789rQuybe40/qkjBZ8x6/Ff3+PkkPjJ7/axPvFX7m3m0e/Hb0+/snHpOkPy5J10XEXybp43UZ3f5WSf9Rl47HbxieF3j3yOe+W5fpfQBGkCgCkMIPBv//DEkfqWuvWPD4fbo05J+tS6LodZIe7Jz7PkkvkvST3vvfyVReAACAtd7kvb9Xkpxz/1rSz0n6B865l3jvf//6nN+U9G8k/b2J97h/5v2HtY6+QLcmScK/D/zEc94j6a9OfMbWtXh+Q5fR4HOObPMRn6TLmkR/0Xv/fcODzrk/N/H8h048tpQIA7pFoghACmHP1tAr9qMTz/1tSfLev9o592RJX6Nrosk592pJf917/3NnFRQAAGAv7/37nHN/U5fR018l6R9c//QKXTrL3jwyLWzJKyX9kS7r6LxyZ9FeoUtM9U7v/Xt2vkfoRyQ9xTn357z3/3LmM/du8xH/yfXfD42ecs59mKT/eeL5j3fOPcJ7/6vX5z5I0n+vW6ffAbgiUQQghbBna+j1epqkN488970fepH3/1zSP79OV/tcXXqkXuGcu8N7/0e6LMo4Nr/9o0ceAwAAOJ33/mXOuddJ+hvOuW+7Jkm+UdJPS/oJ59y36bKI8oN1GZXzieF0/JH3+yXn3N+T9G3OuU/WZf3GP9BlTZ4/Lem7vPc/tlCsb9XljmP/xjn3rbqMIPoISf+5pP/Ge//EjZv5fZL+sqQfcM79XV3WP3qQLnc9+4fe+7ce2eaDfl7Sr0h6tnPug7okjL525vnvlvQjzrlv1o27nn2ELnehAzCCRBGA1P5fXZJBf9J7/4I1L/De/3tJP+Sc+0RJ/0iXOe2/rksQ8D845/6Yv94O1Tn32boEKkver8stYgEAAFL7X3RZtPmvSPpW7/07nXPDLdq/RZf1jH5T0pt0uQX8LO/933LO/bykZ1x/vKRf1eUW8L+44vW/65z7TF2SN1+vy/o7v6NLwuglWzfOe/+HzrkvkPRNku66/vubkv6trusbHd3mvbz373fOPUnSt0l64bU83yPpnbrcGCX2al3upPstku7Q5WYrf8Z7/wtnlRGonfN+bIorACy79sx8k6QPu96pYnj8KyT9E13uNPZySb+rS8DyObrc7v6fOef+ji7zw39Mlznsd0j6O5Le673/U9f3+TxJ/1rS9+tyB7NH6bKI5MMk/Qvv/dOuz3uapH+qy61U33F97Gd1SRR9jS7T3e733p81Vx4AAADGOOfeocs6mH+hdFmAmtxWugAA2uO9/w5JXyTpkyV9ry7Jor+tyyjGN1yf9lpJj9RlqPQrdZl29mpd5owP7/NjuvTU/VeS/qWkvyTpL+jSQ7bkqyX9/vV1r9OlNwwAAAAAMIMRRQAAAB1wzj1Bl+m9D9BlzZPnFC4SAJyKEUXAPiSKAAAAGuece4CkX9BlYdz7dBlp+SXe+7cULRgAADAn+9Qz59wTnHNvc87d65x7Zu7PBwAA6NDjJN3rvf/l680BXiRp612QAABAB7Imiq69Wf9E0p+R9BhJX+Kce0zOMgAAAHTo4brcQWlw3/UxAACAm9ye+fM+1JslSc65oTeLYc8AAADncSOP3bT+gHPuLt1Y+P+xw+OPfexjdc8995xYNAAAUMhveO8/Ln4w99QzerMAAADyu0/SI4Lf75B0f/gE7/3d3vs7vfd3ho/fc889Yk1LAACa9CtjD+YeUbTYmyVN92gBAIA2ee/HYgSk8zpJj3bOPUrSr0l6iqQvLVskAABgUe5E0WJvlnTp0ZJ0tyQ55+jCAgAAOMB7/wHn3FdL+leSHiDpe7z3b974HnKOfB4AAK1zOYcSO+du1+XWrJ+vS2/W6yR96VygQqIIAID2MaLIljj+IkkEAECT7omnnEuZRxSl6M0CAAAAAADAObKOKNqDEUUAALSPEUW2jMVfjCoCAKA5oyOKct/1DAAAAJWy3sEIAACOI1EEAACARc45OedIFgEA0DgSRQAAAAAAAJBEoggAAAAbMaoIAIB2kSgCAADAaixoDQBA26pPFNGjBQAAkB8xGAAAbao+UUSvFgAAQF5D/OW9/9APAABow+2lC3DUEJiQMAIAAMgnjL1IFAEA0I5mRhTRmwUAAJAf8RcAAG2pPlEkXZJFYcIIAAAAedFpBwBAG5pIFIUYYQQAAJAfnXYAALShuUTRgIQRAADA+cK1ikgWAQBQv2YTRdKtU9IIWgAAAM4xxFokiwAAqFtziaKxoISEEQAAwHniu89yN1oAAOrVVKJoqQeLRa8BAADOMRZjEW8BAFCfphJF0o1k0FxgsuY5AAAA2I/OOQAA6tRcomiLIVlEAAMAAHDc1BQ0Yi0AAOrRdaJIIoABAAA40971iobOPGI0AADyajpRtDaw2LLQNcEKAADAvLF4aU8MRYceAAD53V66AGfZugbR8Py412t4D9Y0AgAAWDYWM81N9x8bcRTGZGuXCgiTStx1DQCA/ZpNFO2xJaggCAEAAFgvTCCFMVT82FiMtRRzhYkk4jMAAI5peuqZdHyo8nCHtJTvucbUZzCqCQAA1GAqZplb8HpvRxzJIQAA0ml6RFHq6WI5g5CpzyIQAgAA1u1ZAiDVZzLqGwCAY5ofUSQxCgcAACC3qbWKzv5M1pUEAOCY5hNF9CgBAAD0h2QRAAD7NJ8oGhAsAAAA5FVqdA8jiwAA2K+6RNGeBr/0qCKCFAAA0LNSsRDJIgAAtqsuUSTtTxaVDFIAAAB6ZCEOIlkEAMB61SWKwluo7kGgAAAA0I+jsSMAAL2pLlEk0eADAADUpmTcZmFUEwAAtagyUSTtSxYRJAAAAORnoZOP9YoAAFin2kSRlC/oIKgAAAA4xsqdyEp/PgAA1lWdKJK2J4ssBCgSQQoAAOiThRuMEIcBADCt+kSRdH4P1RlT1pgGBwAAkB8xGAAA85pIFA3WJoviAIFeJQAAgL4Q/wEAMK6pRJG0bTiz917ee3M9SwQuAACgdaXjHSvLEQAAYE1ziaIWWEtcAQAAnKFkosZiZyEAABY0mSjaOgWN3iQAAIA8hgRNyTiMGBAAgGlNJoq2IFAAAAAoo+SIHkYTAQAwrtlE0ZpRRcPfWwkUSHYBAADLpqZ7lZ6CBgAAbmg2UbRVCwsatpLwAgAA7ZlKEjGqyLbh5i/hDwCgbbeXLkApU41cbQsbtjYqCgAA9KlkDFZb/HemsRiZugGAvjSdKBpGCVnrvUqple0AAABtWnuDkWG0Su7YpoVR5UfF2098CQB9a37q2ZZ58KUXtmY4LwAAaEk48nkp+VA6OdFjDBbGnsM+Kr0fAADlNZ8oii31VFm4VSsAAECvSsZgvSSLwtFbJIcAALFuEkVb1vKhsQQAADiuppiqprIeESbDekmMAQC26SZRtEepHi0a7Ru4wwYAAHXbEtuUTta0HocxzQwAsEY3iaKaGv6ayppC3LM1lhgikAEAADm0GIfFaxEBADCnm0TRoJaGv8UgZcpUwNLL9gMA0Lra4prwLmw1Yy0iAMAet5cuQE61BSnS8uLbrQm3ddj22vYZAACoX7zAdU3xWI1lBgDY0d2IorUsNKxDz08riZKt2zHsAwv7AgAAHLM2prE2midMGFkp05R4BBEAAHt0lyiqMfFiLWACAAA4k7Xb1YdTt0rFZHOfyRpEAICUuksUxZYaeisJmrg3y0KZtiJwAQCgbzXdAW1KiSTW1GfFCSKrdQYAqEuXiaIwSJlrUOP1ckoLe7PCHi0LZQMAAFhrS+xiMc4pkZCJ41ISRACAs3SZKBqsnSdvtfG1Wi4AAIApW0bkEOvcWk/cxQwAcLZuE0V7GlZ6tAAAAI6ztgbRXrmnn/V2N1wAQBndJookFoneg7oCAAAp1RpbnJ3siu9gxggiAEAuXSeKpHZG5OQIsujFAgAAKa2JKyzfsfasZBF3MAMAlNR9omiw1MBbbqhzDd+2XAcAAAAlnBWHEXcBAEohUbSR5R6ts3rcrG4zAACABSmTRYzgBgCURqLoigYZAACgjBY7pfZsU4v1AACoD4miQNg419xQpyw7vVoAAOAsYZyxFL9Yj83C7RjKGv67dAOVcOFq5LVm/wBAT0gUTRibxlVDwz0WbO1t9EgSAQCAs4QxxlKyqJZ4JL5D2RBPhgkgkhG2xAuHs38AgETRTeLkUC1BSexoj9bwvFq3HwAA1KfVC/U4IWb5Lm49GeLhMInX6jEIAFuRKNLNCaI1jXcNjcdUj9bwN2l6O2rYPgAA0Ia1nXStJVjCzjs66PKKY+JQGDe3dLwBwBYkikbMBSI1N+Jxj0mr2wkAAOowFW+0foEebzdxVx5jo4imMLoIQM9IFF2NNRZLCw62opVFvAEAQP16SZrE6xYRgx0TL7kw9iNtO75IFgHo1e2lC2DV0mibVhqMeGhtL8EZAACwI556FS4CHWoxTgnjyngaHvHZOmOdnqnqjFgZQI8YURQYS/60khCas+ZOHD3UAwAAyI8L71vXlpRuTX4Qi80bq8PU7y0REwPoA4miGb01CPHw53i7e6kHAACQH3HGDWM3JZGoozE5FwJnoWsAvSBRFBibUjbX8LTYQIzdKY0eLQAAcCZGFS0jWXSzkjEp+wJA60gU7dRLQBOvF0DDOI96AQAgHdrVmy2N/u5FvF5QiXpgIXIALSNRNGLLyb6HhiGe603DOI66AAAgnV465fbqqX7iu5eFsWnJ5BmdqABaRaIoMtXozt0BrUdh49x7wog7YQAAkEbP8cRaZyzWbFkcY41t+5kLWa9BsghAa24vXYAajK1dhJtvXRv28PRgy1pWAABgGfEWwqTQWCec5XgrThZZLisALGFE0QQClXV6awTj0VO99eoBAAA7jo7stjYqPEy21BpjMboIQAtIFI3Y0ijRCPQhnl5Wa/ACAEAthnaXWGtenJhYW1+WR75YLNMWrOcJoHYkig6gEbghde+JpTqNE0QAAOAccTvL6Ix1tiaLLCaJWlvGgIWuAdSMNYpWmDu5x8miVhq3PVKuVWSlHnvfpwAAlNbjWoh7hHUzF7taSBL1dJMY1i4CUCMSRSstndRZgPFibK783gaxZEDIvgQAoLya16opLU5MpIjNUpWpZBlKSRkjA8DZSBQlRm/XrXdDO/I+OfTUqwUAQC3ohNtvaiqahVFEPcdX8agvkkYArCJRNCFMdmx9DcaHP1trAMcaZxJ9AACgJZZiGyvlsGAsaUT9ALCCxaxnDCfrrQkgkkU37F3IL1cdxsPZaaABALCFuKpulm5QYhWLXgOwhkRRYtwJbdyeBMyZ9ce+AQDAPjpw0hji0jPj03iaG1Or1rM6+h5Av5h6dgLuhHZcjjpjvwAAgJaNxTop49M4ERQmiYiz1iFJBMAiRhRtsLUHhhP+uBy9Wkufyb4BANTMOfcO59wbnXNvcM69/vrYRzvnXumc+8Xrvw8Onv8s59y9zrm3Oee+sFzJ92EkcFpr46B4dNBYDBdO4x/+T5y1LK5DALCERNFKR07gBDc3nD0EeU0gQ2MMAGjE53nvP917f+f192dKepX3/tGSXnX9Xc65x0h6iqRPkfQESd/unHtAiQLvQbudVnib9qUfSaNxFDHVMUOnJXUIwCoSRSdjcbob4t6mo9YkhGiEAQAdeaKkF1z//wJJTwoef5H3/n3e+7dLulfS4wqUD0ZMjQIifgIASAcTRb0Ne5b2JXxoZG+Ymisf/n+qN2ttUggAgA54ST/inLvHOXfX9bGHeu/fJUnXfx9yffzhkn41eO1918eqQqdbemviJuKrtFgCAUANUixm/Xne+98Ifh+GPT/HOffM6+9fHw17/nhJP+qc+8+89x9MUIYswkX69r6WhuFm4fDn8LFBmBBiHjcAAB/yWd77+51zD5H0SufcW2eeO9Zw3hLQXBNOd408t7gjMRgAANjmjKlnTQx7PmuhZYKcWy2NCGKxPwAAbua9v//673sk/aAuMdW7nXMPk6Trv++5Pv0+SY8IXn6HpPtH3vNu7/2dwZpHABLiOgBALY4mipoZ9hyfuM8YZst6RdsxrQwAgJs55z7COfeg4f+SvkDSmyS9TNJTr097qqSXXv//MklPcc490Dn3KEmPlvTTeUt9HKOK0ALiWQA1ODr1LPmwZ6mOoc97T/LhVKsttyalUQEAAFcPlfSD19jgdkn/zHv/Cufc6yS92Dn3dEnvlPRkSfLev9k592JJb5H0AUnPqGnqf80YEY0BSU4ANTmUKAqHPTvnbhr27L1/155hz9f3u1vS3ZLknMtyVt3SgB9t7Lf2iBFcAACAgff+lyV92sjjvynp8yde82xJzz65aFnUlHxhFBRCNRyzACAdmHrW67DnQYpGn8ABAABgm3AqP7EUasDsAAC1OTKiqOthz6lGFdFwAAAALAtjpjhZRCwFqzg+AdTIWe+JyTX1bI2pE/3eBqCGodM0bgCAHLz3NDaGWIq/BnMxidV4pYZYD+exelwCQOCesbudHr3rWVem5pkfWdhaYgoaAADAUS3EU0ynawf7EUDNuksUHT1pp+4VsN7LMDWCCgAAwIoa1y0ayhr+1LgduNWwL63H+QAwpbtEUYoT9hkNd03BQE2NXk31CgAApi3dQSyMT7a0/yWSMuGUtPAnfCx8HurBdDMALeguUWRRrmDAetCUUu3lBwAAt1q6AN8ziiN3UmbtaBNGpNSHJBGAVhy561m3WmsAxhZarH0bay8/AADYLxx9tCYmWBqtdLQsEqODWkeSCEBLGFGUSKq1j84cCTN3xzYaNgAA0JI9CZqzYrB4qhnaQhIQQGtIFBmSO3Cw1PNBAwsAAFIbEjNr4oyzYqItI5tQH/YvgBaRKDImx/BkGjQAANCbtbHVGTEYMVfb2L8AWkOiKJGaGgiLZbVYJgAAUL8tI6jP6LAjxmkXI+IBtIpEkUEEFNNokAEAwFpx3LBlLcijMQcxS9sYoQ+gZSSKjDrz7hs1o14AAMBa8QihqRFDQwIp1cU/SYQ+sH8BtOr20gVo2dHFooekSIpGKOfC1TmCIwIwAACwRhwrDPFVmCwaiyeOxmHEKO2ydEMYADgDiaITpWpAUjRGuRuzlEmusfcGAADYY2tn09Z4hpHPbSNJBKAHTD0zLsWiirkDlqHMNKIAAMCSrUkiRhMhlnuEPgCUQKKoAkcaJHo9AAAA9tuyPiJxF1IgSQSgNBJFFdnTaBCsAAAAXKQYqQ2c6eg6nBzbAFIgUVQJAhuEOA4AANhnT0y1ZlQRbTP2Cu+655w7lCSikxhACixmnUGqk3aOW8PTwAAAgNadFVMRQyG29jg7euyQqASQEiOKTnTWLdzPbAgIcOrAfgIA4Jg9yaKp53ORjjHhtUD4EzoygihGfAggFRJFlcnRABDsAACAXhwd8XFWxyDqNndcTCWNjn4WAKRCoqhSjCoCAAA4Zs96RWPPJXZCqETykGMQQEokik501gmbhgAAACCNLcmi+Lms7YhQigWpAcACEkUVyzXMlOGsAACgZXuTRb0lA4gJp5VKEPV4HAI4H4miSu0ZKn30swAAAFq1J1nUE5JEANAPEkUVOztZREAAAAB60mMCaA0W7LaJ0UQAzkKiqHJnNg40PAAAoEd0lt1AksimM4/RYa0lAP26vXQBAAAAACtIiNyKOpmXM6lyVuIu3gb2OdA3EkUAAADADq1O/QmTBi1u3xly1lPKz2JfAxhDoggAAADYyDnX5PQcppptk3s00Rn7hX0NIMYaRditxDBbAAAAC4bYpMUYpdbEQY59MazfE67jk6O+zti2VkfEATiORFEDSvVo5fpcGjEAAGDFWILAcrJoS9lqjrlyLO4cT9MafnJJPeWs1n0N4HxMPWtIiaHCZ38WjRgAALBgKs4aOs4sxiy9JYnOKH9rU/Fa2x4A52BEUeVav30ljRgAALBiKi6xPLJoKZaymuRaK0fio9a6iZEkArAWiaKKjQ1/jR9He9i/AADYU2McVnvi4Ozy17Qvl9S+rwHkxdSzStXY81Njma2hDgEASGssGTDW1g5TzOba4VruhNZC0iDXNtRaR2uPawAYQ6KoMkuNYjhPfu55JVgqCwAA6NvUhfRSHLWm08Zqx048Gr1WOeJcq/twDYvXAQDqQqKoMmtO+GFvVs2NHG5WQw8lAAAWbRldEU4hC+Oo4f9La/pYW9w63nYLZTqi5yRIyiRlz/UIYBlrFDWKk35baMwBANhu7KYfa29pPpUwCt977WtLK3Er9zMciYe23gHOmrXJH5JEAFIgUWTEmQ2SxcYO29GYAwCwXngxvDdREr9uywV2+JwSsVhryYAU27NlP7RSb7EhmdTq9gFIg6lnmU0NfT7jZL3UEwYAANCiM+Keo++ZMxYjSXSrWhYanzO3oPqabeN6AMBaJIoyKbl4YAsNY2u2NNTsOwAAykuRpMi1CPPZn5FTa9tzprk6IkkEYAsSRRnQwOEojh0AANaxekGcY6S31W3fK3UMPTcipybxNoQ3sQGAFEgUncxSYxTercNKmc5kOUHX034AACCXnBfKa9rysTugxXdRS6XVuCL1NrUWg1mOdwHUi8WsT2Q1qx8Pf25dT9sKAECvSl0wL8UYS9OBUpWhtUTBmds0tyxDqbpcOhbiv4cJyNb2PYDySBSdzMqJe+xuHa2uXTSVGLK2ra3WPwAAuZVKEsXx1dzz4uekKmuLsUSObRrbJ6XqcmnqWPz3vXfxA4C1mHp2kloa7daG3y6xtq2t1H8L2wAAqFupdmhsetnc82gv1+mhnuIE51RnZw91AcAWEkUnsDpXeCqQsVbOI44M/y4l7NGKy1cioFxz/J7VKwoAwFYWOufWJoukm9v2o8kjqzHnUTmSahaOG0nNxuQA6kai6CRWT/RbApmaWGnsUyqxTeFnhsfIXFlaOo4AAPWxMpV7TTmm4rC1Caap92xViXj1rM9jpBCAmpAoSixH78fR9281WVSzqeAy5/4Z65UMH2u11xIAUDcLSSJpfTniNn9Nu0obfI41t5g/UueMwAZQKxJFlUk1FNdK79tRW7ahpsbZyr5hODQAoAY1tlFrRnVfPIoAACAASURBVOv2nCA6M1adWsR6KXG0Z9RXj/sOQP1IFFUoVYNT+6KKe+4wktva+h1bN+rMsvc4fB0A0B5LccyWtnsuBosXNLayfbWbuyPuWB1P7Zvwb/HIa/YVgFaQKEIzDdvSnUZKOLo4ZcqeKYY/AwBwvqNxFe1zemNrQknb6zpcvmHu/QGgdiSKEqqxkbAw6mavtXVdwz4ZWzR67A5o4b8MfwYAwJat60DWGDvWZCpmIpEHAPNIFCVSa7Jl0GqgYnWb9txFbCpxxPBnAECPrLd1S+WrubMupz37mal7AHAMiaKEaIhuZT2IKyVFnTD8GQDQK+tt3ZYkkPVtqQkJIgBIg0QRNg+TXiucKkVjfQ7qFQDQG+ujcOK1cNaMKiJW2o+p9gCQHomiBGjcb9RB3JND3QAAgNRqiC3CqeFMQUuLG3QAwLlIFK0w18C3kgg5EqSM3aGrhToBAAC21JhQWdtxRvJjGXUEAHncVroANZhLElm2p3x7XjNWP+HaOdbrCQAA1KPW5MCaeMg5N3onVNx8046wngAA6ZEoOshyI7W1bGcFJpbrCAAA4GxLMdbU7dt7ShbNbeswIouYEgDyIFG0U08N9161NujsWwAAkNrW5E8vyaJwMe/h/0wxA4CySBQdQKM1rea6WTPVsPWgDQAAa1pYF3LrotatJ4vikUJjU+9q3+c1aPX4ArAfi1njJkfvvGG9MR8LMsfu2BYKF6EkaAEAAEdtSXqFI21aij/m4s2WthMAasSIIozamixaO82sdI/FnsAjXpSb4AUAAOy19e5na15TG2IqO1pLQAJIg0TRDqWTHWc72ljE9RPPNy9Vf2sXSZxLetGQAgCAs/QQZ7AwtR2tX9MA2I9E0U49NG57Gw+rdTNWrrkerTiIsbpdAACgLmumvG95TS0YvWIP+wPAGBJFGJViVFGYhLHYCLE4NQAAdegxwTAVm9Qas/S4DwGgViSKMOtoMBLf4tRK0ohgBQAA5LZ2On5rU+CJu+ypNeEIIA8SRZiUukG3EiCEwcraBSWtlB0AANRnbKR1b7EFiQk7iG8BLCFRtFGPPSJ7Gnara/vM3UlkaiqapfIDAIB6rJmKvyfOqi3pMhZroQySRADWIFGEWb00ImEAQ5IIAAActWatxrk4Y25R6xrVWu4WsS8ALCFRhFVK9gCl+ux4xFD8vlZHQQEA0LOaR3OnKHdri1qjnJq/SwDyIlEE81I1aEvrATAUFwAAW2q8sB06o7aUe2lR67nOrVqQ2AKAepAowqK988qngpj4jh97rXl9/Jyl19QYeAEA0KIaEwtndDqt6eSybmodSACATSSKNui5YTsr4DlSp2vKFM/vn0teAQAAW2rqwDmSJMr1mhLG1moi7gIA20gUrTQMIa6lUT7D1KKKqV+T2lJPHFPOAADAEWfGEnPT2CzEWVPCKXhj60CmGF2O9ahrAFvcXroANejpxLpmTn3K9QJSB1Q1rmUAAADqdXaSqEZL8djWZBGxXRrUI4C1uksU7U0k9HJiXTuda6u43lPdBSR+n6Fnbez9w0BubFFIkkwAAGCLHKOS17y3pRhmS1mslBnHMDofaE93U884ge23t1frrDrfMgw7bsDi19baYwcAQItqaJdzXRwz4gaWkSQC2tTdiCJMW9MDdKQRKNXbNfW5luf1AwDQO6sXnjkvjIdYZWwkdFwmq/WFdnHcAe0iUYRVjiZUciZlhs9ZCuTW3A0NAABAKjdyYiwpFF6g0/GFJWccHySJgLZ1N/VsKxrei1QNgZX6DO/CQSMHAADmnJUk2hMXlR4lPfc5VuI83Crlsct+BtpHomgFEgkX4fDn8Cc013AcrcctjRL7DAAApDB2i/czPsO6eCTTFGIwW846ttjPQNu6mXq2Z5pRDY12SnvueDY2/DmHuUBlTa8ajRsAAFiSIxacWoco/Pva9znb3Gf0FjfXhNFEALbqZkTRnhNkb8mEXHc1O+NzphZ57G0fAgDa4Zz7Hufce5xzbwoe+2jn3Cudc794/ffBwd+e5Zy71zn3NufcFwaPP9Y598br357rKmkcS1+Q5l60euxnTfks4M5XfWE/A+3rJlEkaVWj27PSPVFbsRg1AKBxz5f0hOixZ0p6lff+0ZJedf1dzrnHSHqKpE+5vubbnXMPuL7meZLukvTo60/8niaVatvD0dKlp5st3fUsd7JobMmBHHUFG1jAGuhHV4kinGNrkJKqgWGOPACgZd77n5D0W9HDT5T0guv/XyDpScHjL/Lev897/3ZJ90p6nHPuYZI+0nv/U/7SYL8weA0m5Ioh9kz73/LaMzGKaJ+cyb2UiR1LI9gAnI9EUQUsn5gJDgAAyOqh3vt3SdL134dcH3+4pF8Nnnff9bGHX/8fP25Wybgn54iJFFP3c93tLE4KMYqoH4waA/q0mCjqfX586WJauNVpjtcDAIBDxgIWP/P4rW/g3F3Oudc7516ftGQ7lIi/aohlpsp4ZtnD91575zOUl+KYYNQY0K81I4qer47nx+ceHjp26/mze4uOvnepefIAAHTo3dfpZLr++57r4/dJekTwvDsk3X99/I6Rx2/hvb/be3+n9/7O5KWuhMUL4qXRHGevo7R1kW1Myx0rH9lXJImAvi0minqfH5/z5Bg3wLka4xSfkzNZRE8WAKBjL5P01Ov/nyrppcHjT3HOPdA59yhdOuV++jo97b3OucdfR3N/WfAaGBfHPLmmmo19No7JOX0r1UwB9j/Qr9t3vu6m+fHOuXB+/GuC5w3z4P9QG+bHO+fu0mX0ESqSc+QTDVgaBIEAYJdz7gckfa6kj3XO3SfpmyQ9R9KLnXNPl/ROSU+WJO/9m51zL5b0FkkfkPQM7/0Hr2/1lbqMEP9wSS+//sC4LW30EIOxcLFNOeOtVDEy8SHQt72JoimH58dLl6HPku6WJOdcsZaq1EV07Y3zGfVGYii92o8zAGid9/5LJv70+RPPf7akZ488/npJn5qwaM2x1iaWiEHDOiDeSqfEsZViyhmAvu2969lp8+MtsdRIWipLbiSJ0qNOAQC4mYU28chi0UdGdpMkOlfu0URHX88xAGBvooj58Ser9QSdeq0iGqzzUKcAANixJeaZi7PWxmDhzVNYqLodTDkDkMLi1DPmx6MEerbOU9u6RLWVNwfqBADasiVJNDdyaM2oImKsfEqsTXTktRwPAAbO+jzUkmsUldDKiXrvdowdj7XXhSW1HV8kRG5V2z4E1vLec1Ab0tsakSXbmz3n9bnyTv2NBFFeudvro7E3xwTQrXu893fGD+6deoYT1XSinuvR2vo+YUPF8OfzUK/1sp7YB4AalTy3HrlID2OnpefEn0N7cq5aki+1lBNAfqnveobOLDUsSz10c71bjCZJq6agkMBlGd8PAEin5F1u9y5cHb5H/Le59w5fSzuSVsn4Ze1i5vFzOAYAjCFRhGKWGlMarnRqSrzUVNacCOwAoD1nncvXvi/T0dKpKX6poYwAymLqmSE1jfgI7bm7Rvia+PVrhlJjvZoCl5rKmhNJIgBAakNbwnS0dEq2z0vrVhFfA9iCEUXG1HgBODciaGxefIxG6zw1JF5IggAAQj20AymnfaVoR3uo8zNZnMbHaDEARzCiCMnM3bFsroGKe7JozNKoqT5ZwHwaiVQAOE8L59i4Dd06eqSFOijJcpKI2ArAXowoQhJr7rqx1FAx9Dkdy0ki9u961BUAnM9iW7lXvKDxUvy1dgFkjLNWd4wiQqu2ftc4/o8jUbTAYi+BVUt32QitqVfLyQ7LrNeb1XIBAFCjOKYau4vs2OPh84l3t7MUb1kqCxCbS/JMna+Wnrf0eSRNjyNRtIADa5u19bW2d4v634Z6AwBgvdrbyzUjgrbcNr32+sit9OLVFsoBjJlbkiT8e4rE0NLn8F3Zh0SRIa0euOGi1q1uI3AGpmMCAJasHRE095y1NyDBRemYlv0Ei7YsrJ/r2B1LGvG9WYfFrJHMmmGFay94WXxvOytBA7dfTa/0PgUAtC+8AQnt+LTSF5pW4j20KVwMf8uC+DXcxZgO2G1IFCGJNSeDtV9OvrzbWQoaSPIBADAvdTu59oYhayxNCUF5xFk4w9jd8ubOA/EoxLWvK8l6+SwhUYRk1s6TX/M+WM9CkoiT7fnWLvYHAMBexGC20fYjpyHxEyaEwtFGcXIofN3wXIusl88KEkVIji9dPuFJunQZcL6wwZZubqwBAJizZUpZ3N6gPAsdg2jb3Bpm8c2G1o5itHoOsV4+C0gUIamzvnR8ie0iYMlvrM5JGgEAjhrr/KFduaF0XRBzoaStndPWj1fr5SuNRBGSW3MS2dPQlm6crbFQHxbKgIup4b8AAOxlqU0p3RlSckQP8VYapY+hM6XsMEz5XjWMTLRevlJIFCG7rQsqMtTWLvZJeSSHAACpTLUnpS+krMSCJZNEpbe9di3WY5zQOTqzY+ti1mtZTha1dDykdnvpAqBde9eumTqRtHiC38vqyRb58D0AAGw1XLBtnT5ydtyR4mYoZyoVd7EO5HHhvqu9LseOw7GFpOPRQGtneqR4r6XPqX0f9IREEU4TByPxyWHp9+E9QiRIbrYn4AMAANjizHijlo7A3OUj5j2ulmNrydZEzdj109JowbmFrMPn7j0PWB5VhHEkinCqMLBYuzr+1O+hlCf+GhMtYYY/Z9lbaXABAOiZhdiHmGJa6rqxsL9zq+H42pI4ObIdS0mate+d4vrD4rForTxWkChCEWMnrDChNHUyO6NHq7aTQ6mGr4YGFwAAzDvSs58iBiOemJeifnoeuWF1qlm8T4aynXEDoDFTszS21tGRZBGjiupCoghZrDmZrB0maemk3xvqHgCANpRYq4gk0bSpDtS1zx/TWz2XPr6WFpUOH1/7XTprW1KMUDqSLOrt2KwRiSKcLl4IbWldovB1GFdiNBH7o31TAU3uMnCsAcC59iR9jiSJSl/AWzY1AmbpblbU5c1Kxg/xftmy7k+tSBa177bSBUAf5hZCW7OCP8rhRN62seTQmjXFzsKxBgA2HVmT5MjrSzszDhq7HfkgfCxOGtVal2cosWZn/PmDcDpZD/to7lpuDaah2caIImQzdvczy3NVSZBQB60aG94OAOhPjiSIVG+SKIetSzPghtLrdg563kd7RxZZvgbEBYkiZDV1ErGYkLBWnhKog7qluMMFAKA9ey7Qtrym9lFEOXCRfEyuY2xqFgTH9g2lF8jHOUgUoTgyyttwMsWSsbnyHDcAAOnmC+y18dfai3ISROtQT8fkTBKF/+b4zFrtiTe5BrSNRBFQES74MWZpCDTHDABAOu8Cm8THdtTVdiUSNuyn9Y4ki6hne0gUoTgyycB+9HIBANaYSuasuUhbuoPt2PsCKZ19nHFznXRIFrWBRBFON5cIIkkEbEMgAwDYauoie8vUj/C5w0UdSaLtuCDe7szjjLgqrb3TyUgW2XNb6QKgHVN3UppavDr+u6WkkaWyAIP41ri93H4VALDfmovsLcmi+C62tEPbEWeud3aSKI6pOJ7T2Jssgh2MKEIyc+uijH3x479bajQ5UcESppcBALZae4G9Jwabm4qGadTXNmevqYVzhOcHjvV6kSgCAEOmghcaWgBAaM3F7pltRziyqNULwpTb1Wodne2sOmNfnMvaIABsR6II2U01lKXmptJwwwp6GgGgLWfFGGe0F3vLyuiBZfFt1qmnZSQZbqh1HSXWHaobiSJkY3Uuu7Xy5EKwYgv7AwDadNaFkqX2gtED07hT3H5nTTmrod7j79PY8VMLkkV1YjHrTpx9QgnnqU9Ze4Ko7eSXS+rhz1IdDWVP2B8A0JYzF+BNKcX7tZosSrFNU+t4lqqvIW6Pf1pWU+w7dvOSUA3bMKiprLgZI4pwWMoTb6tBhkWcuO2gpwUA2pbqPE+MZNuWKUJjyaIcsUCPMUetSaKW9Hjc1Y5EEZKo+Yvf44mrt+21ioAfANp3dA2fXImEsLOOOOFiSwfm3rrLOSWtlpi3x1H0tZRzDwYC1ImpZ5046wt69iKNOUyV39oJrcWGAzeGFQMA2rV1qlE4HWhq+skZGPV0s7OTRLEzp6TVsl9IErWJZFF9SBR1JuUXtJZeiT1a3jbYwDEGAH2Jbycfi9eKKdmRsDdebLFdW9qm1Bf5ZySLekhEhOLvkWW1lDMVkkX1IFHUkdQNz1knNAsL/Fk9WXNybYPlYwwAcK44YTSWHCrZRjCqaLuzFhc/Wo81JUykNPGRhUTrWjXtmxR62c5WsEZRZ47Ok8+lZDmt18sa1vdvz3oLngGgN3Pn+aFtjtelaanNriXWXLLUXp/dnu+pxy2LabeopmOutyTRYDiue9vuGpEo6lDY8Ay/W8Rc1v2s7tOe5b6rCQAgnxbP8Ucu5lqO4eLtyrHA+Jp9YT2uX3LkeKlt22srb2q9bndtSBSh+94H4EwtXjwAAG44ctFntWc9VaLH6vattXRr+1xlWOrgbSXxsKX8ORN2KbWyr9A+EkUdqu0EVXuQcSbqxrbavmsAgH04z9+qhSlocdlLjZJaWgi91vo9qrbtJi5ETUgUdaLWrDvWYdSKPQQDANCHved5y1OzhrIdTfK0MAXNUgxNTHFR4zFFXIjakCjqRK0npRYCjDOF+7XWfdwaknYAgLUsthPhBW2PMdhYO17zqKjW1JxwqbHM6NdtpQsAG6wHAtbKl7o8e96PhIQtY7c3BgCgRqmnW1mL45bQjue19vioOUkE1IZEEcyz1hic0asUL1Q49bnhz/AYyiNBBADYopYRKinKGI7KqUEN+6VnNe6fWo59IESiCKZPXmHZLJczhakkw1ICCWXRuwUAaE0cdxyNQ2rtSCEGy6PGY2OrHrYRbSFRBEk2T15Wp1adPWe/p+RYKywdnwAAHBG3ab22ccOor1qTXDUai3vD0fQ17gdiedSKRBGqOulaOdmeVWdhI2hlWzGNfQQAaBVtHEqrfWo/o85RM+56BrN6u9vGniQRDU85NP4AgF6EMVnL7V5Pcac14TFmdVbBFj18X9A2RhTBvPhE22IjHg+npVGxrcVjEACQRw1tyDCCY+pW8TVsw1bx6BVisTJqn/IX3wUXqBUjimBaD6OKap1z3bqx/ULDDwDoxVg72HKnnUT7XlILMVYL2wAMGFGEqrQWoMTTzbbc9p5GKB96hwAAKVlvS5bikB468pBPCzFWC9sAhBhRhCqMnXxbOyEPQReBlw1TQ+4BAGjZ2pHOLa1bxOjuclo5hqQ2tgEYkCiCeUMgMpx842RRrY371JBuRhPZ0FLgAgDAGeKR3rW1mXTOlVVrDB9rZTuAEFPPYN5cI97aVDRpe5DV0rZbQ6MPAOjJ3piixnis9luvA8CZSBTBtDU9VDUGJ0vWbO+a52K7mkepAQBsqyFW2dv+hXdKs76dtY6AAoBcSBTBrC2NeI23bF3aLoKX/AgcAQBn6mH0Si0xWev7AXlYPsaBI1ijCKZtacTHApPagwDuKpJf7ccMAACltXzzERzXyjHRynYAYxhRhOaEvXWWkyyWywYAAJBCLSOMkBfJFcA2RhTBpBSBRDxP3lqDtKY84Vo5BFcAAKBGcbLIWkwG7GX5WJ66drBcZthBoghNi4c+WzwxTpUrPrlbLHtLSMQBAHCusBOvZFwzlKP12KqHbSzFet1a7ShHPUgUoRvhej/WTppxY2O1nK2y3tgDANAK1l/Mgzo+j9W4kU5mpESiCF2Jp3FZOYGOlcNK2QAAQD9yXASHI3rGEhpnf34vSRSLsaTVJMuS8JixWP5a6xV2kShCl3IOfV76jPhvvQQvVlDfAACUMdZxd3a7bK2zEHbVMkKHJBHOwF3P0K1ci0TvOXFzss+L+gYAIH97WOqGHbT7ZdTUORcmFMM7KltDkghnIVEEk3Kd8MZG84Q/uZT4TAAAgNJyJot6ibMsb2cNSY1aRp2RJMKZSBShe+E0tPAxKW1DO/deYW8FJ3wAANCTMPYJ1y1K2ZFWy8V/Kta203Lyaoy1+ovVVp+oD2sUAVdxg5Dirhxhpt96g9MjGlkAAGwIF7iO71Q7lixae4t764sQ12pu/Z6phcprqn+Lo3U4lpETiSKYZvEkbQn1cxz1BwDAhaUOlLkbj4SJo7UjhWjv04nrPNxPW/cL1qE+kRtTz4AFR4KmHLeXxT6WgmEAAKzIEVtMtcHxKJSppQC2TtcnXkpnLGER7qdWllPI9T1YM7WSJBFKYEQRMGNuuPMSRvvktaYRrXkINAAAZ7ISt4wtBSBNt/MplgrAtmlNY3+3cOxYN5cgXXoN9YvcSBTBtFzZ/LnPWTNPPnzumvdEWuH+iOue4BEAgHkl4patnzeVEKKd329q3afweJiqc+LcaUs3sNn6HtQ1SiBRBKwQJ4jGEkJjf8f5xuo8nie/dsFLAAB6UluSJW7bY3QWrbc0QouYdrs1I9eX6pUEEawgUQSTLDbsSwkhTuZprU3sTA1/jvcR+2cZQSEA9KPWc3486iVObDACZtnSvu+5g+3oNchSAmguEVfrdxJtIlEEc6yfJJfmwvfasB61J7Cb63VhH6zDuk0A0B/rsdaSqUWvp1jsgDxLqoWRaz02Uti67WunRMadl2N3i+u53mELiSKYUstJci5ZZL3stZia3jf3XGzHEH0A2K/GzqFaYq01aqz/klra92dae1wtJYjWJOOY5gerSBTBjBpPkjWW2aK187V7HZ67NxBeO1ooXgx86fkAgDq11CHA3c6mLd2kBekcrc+x0UW96G17a0OiCCbUeNHf84k9pTXz5Ifnhc/tpb7Pmiu/9rN7qWcAaJ2VczrJnTKs7H+Mm7qzcqv7rJbjsZZynoFEEYqrMUkUGuvR6vmkssfeRat7kWKuPAAAVqRs04m5lhEXbBePsM5Rh/Fx3GJndO3XfT0hUYRiWpviEp7IW9ieHFpr/EpL/Z1i3wAALIvvgLb0vF7atbFt7WXbj5hKDpVKbkyNMhp73mBuEe2SWrvu68FtpQuAPlmZQpSqd4AT3nY9BWw57flOsR8Am5xz3+Oce49z7k3BY9/snPs159wbrj9/Nvjbs5xz9zrn3uac+8Lg8cc65954/dtzHV/6pGoYrWGljGe0/Vvez0o9nCm+AQjx1jpDPYVxVPh7qTqMyxCWI16eYer6Kv57Tr0uHdECEkUoxsqJwko5etJDoFabuUAEQDHPl/SEkce/1Xv/6defH5Yk59xjJD1F0qdcX/PtzrkHXJ//PEl3SXr09WfsPdGoXqZ6hBfDVkdV5EaSaJ3a6mkumRUnkuLHcyaMSBDVjUQRsqvtZLwFCZD1Wj0GUgp7A+eOrV4uAoDeeO9/QtJvrXz6EyW9yHv/Pu/92yXdK+lxzrmHSfpI7/1P+cvJ4oWSnnROiWFV6+3D1AVxr1gKYb2ejpOcCaNwhFatejo2xiwmihj2jFal/vJzSK/T+0l3rbgXZmntBQBd+Wrn3M9dY7QHXx97uKRfDZ5z3/Wxh1//Hz9+C+fcXc651zvnXn9GoZFfvMZKL+baxRbrIr7ob3EbUxkbedZbHDWWMOKYQWzNiKLni2HPSMjSyfiMefKcbMd7KXpukLeingDMeJ6kT5L06ZLeJen/uD4+dsLwM4/f+qD3d3vv7/Te35mioLDBSltiYUR56c8/w1SCqMVtXWsqFh/rhOu5nuJ66P36BTdbTBQx7BnYhgz9+CJ6Y4/jViSJAMzx3r/be/9B7/0fSfpOSY+7/uk+SY8InnqHpPuvj98x8jgSsXq+thR/lCjL1IVvSxfEY/FVK9t2xFgsTny1rKXvRio9Hy9H1ig6ZdgzkMPZJ0F6KW5FXcwjiAGwxrXzbfDFkoalAV4m6SnOuQc65x6ly+jtn/bev0vSe51zj79O+/8ySS/NWmgUwSiBPkwtXoxbOyipl2WcMzDYmyg6bdizxBx55JGrsejxhBsmPXrb9jFzQ6C5bSiAKc65H5D0U5I+2Tl3n3Pu6ZL+/nXNx5+T9HmSvlaSvPdvlvRiSW+R9ApJz/Def/D6Vl8p6bt0Gen9S5JenndLUFqptmVo40q1b3OjimpnYSqfRWMxF/HVNuFSGsTx/bp9z4u89+8e/u+c+05JP3T9NcmwZ+/93ZLuvr4/R2djaNja1mpAdtRUHVA3AKZ4779k5OHvnnn+syU9e+Tx10v61IRFQyVKxlyMkkUpHHPH9djRjZvtGlHEsGccUfrkXSpoav1kG/caDg1M6f1tRev7HwBgS8l2x1KSiAve9jH65RxHv7/sj7otjii6Dnv+XEkf65y7T9I3Sfpc59yn6zJ97B2SvkK6DHt2zg3Dnj+gW4c9P1/Sh+sy5Jlhzx0qnTgodcIKh3BaCJrOEm9by9uaAvUDAEit9J2v4rtwWWnrLJUlBTrkLiwlJYGWOOuZPqaetaN0Y2ahISldB2dpdbuOKh2sAzXx3vMlMYT4a52z2784dplrV6y0OWGdWIsPrJXnqNa2Z8nU96GnOsjtyDFW+/FZe/k3uMd7f2f84K41ioCaWGtEcpx0OjqxmUZvHwC0K/X5fW6Nv7FYZmzBXivCqeiW2kFr5cF6w35jillevX9net52EkXIovSXzMoXPNcUtFJDza3Uc0kELwCArZY6tcYet9zmWi6bVH/MYiXWyNUZuzSSzlqnMG5Y812z+n3sZemQKbsWswbWKv3lstKQhsaGjw8slneNHk+eY+Lb3HM7VgDAWi23F5bim1bquXSMEa9FdcY+XpMEim+igrpY32etnC/2YEQRZu251bmVOfKWyhCbaswslhXjpo5z9iEA9CNFZ1hLvdVTsY3Fi8Ha691CR2w8FXIpqTM3XTJe22rsOWvLVvN+tWjv9LO5776168UpPR9PJIpwi6Nz3q18max/sXuf81uzMBCKe9HYpwDQD24fvZ6l9nGs/bZSNuumkkFhkmfuuI6TQXEMFT9vC6tJyRYcuW6J92st+qKTuQAAIABJREFUUwV7P5ZIFOEmtXxxW2IpcNrDykk0V7AXf0eYKw8A2KPVtmJueywlZsba79JlWqPUcbP2c9eW66yEQZwsqmGf1mLrPpsaeVbTPqmprKmRKMItev5C5NZKz4eVYybuIUxdrjXvW3NjCADIo9UkkTTd9s2NJBl7HqZZTRJtddZ2xKObOKbSCa9dlq5haluEHzcjUYQP6eFEanUbrd3idms9la7XsZ6jseBgav57+Lqx96NnCgAwZu0dfcb02p6MbbeFxBlLAoyzsG/2SrHmEW41NrIoXpahlXpuaVu2IlEESXamD+Vg7Qs/1oidUcY4SZIqUCs1KmopuTaVEJpLKk19zt59UdM8bADANmPr3Kx9HW5GnWyTI5ZtKX5hhFF6U3H32N9q1crMj71IFBm29kR29ETeUkOwlsWehakRLWe8/9S8/KML1OWy5Zjd8pwzgofwQsLKsQYASGOsNz3WY5w1ppZ20HI5cx1LluvgiN4v/IEtSBQZtvUEPXbiWzscusXGYE5rwyKPOpJkbGWe/FnvGb5vr983AGhdqgV+YYPlGDHXSKKWWd6/FvUev/Z6vNxWugA4Zu3JfBjREP/sHUVSq1qGRdbU45GznLU3VOH3rZb9CwDYr9cLjBh1UJeW9xdx2Da911Mtsy3OQKKocmtGDIUJofgHdtR4Usl1DLV4y/makoGW7VkfBABy6PHcVHsbffYyANb1ss3xmkXEEuOmFqxGH5h61rjaG+yeTK1rUGIfblkfi8UUUQrHBgCrOD/VzdKU8TDWOnPphN6SAKwnNi+uiy2L97dYf1u+d60scUKiCDCuxInG2onNWnlS4a5o+1hcjB4ABpzX6zV2R9WSCZT4jrVnfcbgzJt71IAbkFxMncPW1klrcdre46L244ipZw1gGtl2tfWa5AgOLLJevhQYzrsP5z0AlnF+qpOl/TaVJEpZxjAhEK/j2WtcYukYyC3VUg8trsm5dXtaOI5IFDVk7CTfs6lGrrZ6OfNEW0Nd1FDGo4bvLnPkl9XeOwMALaMNS2MsSZS6g2QpIdB7XNLrdqc8znpPFtWORFGD6GlvT28nJqmvbR3w3Z3GUHAAqFvNo1RylXuqrSvV9sWLPvei17j7jONsTV3WVM9rj42atmkKaxQBlbAWYJ09HY6EAKT25rkDaJuldroEa7FKCrm2aSz+sVCXY8miHtrjntYrOnsbW0u8rR1tV/txQ6IIzWrlZGTRGQ0KCQHEOCYA1Kjn81XLF05jC13vee1c4mnsPXNcwKd+biss3f3uDLm3q6X6s3J36DORKELTav5yWu2Vy9XrAEgcDwDq0+pF5ZLWtzse6bM3RlubcDoz3qr9Aja3FkYXTZW91u3B+UgUNazmk1kqLdZByW2ymLhCm1r87gLoQwsXlXu1sr3xYtJr1gyyPtqaGO4Yqx24e7Se1EUaLGbdML7802o92efcp3H95GhUOGYhEcwCqF9ra3L0bkj8zY0kShXDTH3GkWMpvnMa8dZ+NX+ne1tnqpRWOgoYUYSm1f4FnXLk5BM2EHPDn3MOT6250UVaLTSsACD1PbKoVmMX0WG8NLaIbaqRPvHnTD137+dxDB5X83d6zfGFfcauY1qoYxJFQIWOnHyWkkGlWCoLyuE4ANCSmi8sezO3j6ZipzVJozWdYWsv4rnYL6/WWQkDjpu0Wv4+kigCjIvnyY89nqMM4b8pPpc7WmHQciMLALVfWG7RW0Isjs+OTEtbW29bj6dejr2cajvGOQbOVdvxsBaJIsCQLQsmTj3/jDLF5Th6Yd9bIIlpJIkA9KCHc1ztCbGh/Hv2VRwjnb2/t5bV+vFHXHiOtXfYwz41n+/WIFGEZi2dDC2eLJcCjfj3vfPk59YpWipX+Lo9DXvrJ1VsZ/G7CABb0b5hYCXxUcMxaaWuWkNHXB4t1y93PQMMWtuwx3evWLorR/z43OJrS3fG4I4uOIpjBwDQGivxUQ2JgtJ11DrL+74VLR/DjCgCjNp6ch+bGrZ3Ff6t8+S39gbRcPWN9akAtIpzGqTxu6PFf0/hjOUBcqulnDVpOXlhSe3TbZeQKEKzah/KWsstUFs/SSItkkQAWlR7zIGLI+sUjb3XmFR3wQvjrzg5VMOxSOx4jtoShS1o9fzP1DPAoBZPNtweGMP+n5vSCACoU0sX/mduS8qpaXF7Wts+IBZIq4Uk0dwSGhZZmWp6BhJFAE7XQsOFY1psQAEA7ckRq5zxGYwm6lsLsXa4DTVvRytIFKFJrYxcqakhnVtAmxM+pLqDFwDAPM7x26WO82rYBy0kNJBe7dcLtZZ7DmsUAUbVtPbP1CKKtZQf5yEgBNC6VjqnkNfeG4LUjJggvdrXfuSYsIsRRYBxtSZbOPGDYwAA+lNr3FJCyvVNrNc7McF5ah2JwzFhGyOKAMNqHZXDCR8DjgUA6Esr5/1cI31SxHrh6KTwMWsslgn5kSCqA4kiNKunobw1YH/0pcYEJwDsRRuHI4ZEz5FjKH6tpWPSUllqM5f8OzPWSnVXvqn34Xiwj0QRmlTrSJyW0SD0g54iAD3hXNeWMH7MneBI9XlWEjPEA+vE1yzxlMSlKYqpRpLNXTutfd/4+3O0TLWw8p1LiUQRgKTCJF2KHjLUhf0NALbluKhsQe7Fplvq5OwpQXDU2PE19R1dU5/D+8XvsebYOmNkWw9aXZieRBFQgdpOPPFc+drKDwBAq8LRCXtGEExdxLbS1o91eOV0tB5LJZumRsVg2tK0rD37Mk72hN/zNfuE/bZPS4neAYkiwLhaTzwp7+QBW+YuEgAAdZi7IDySROJCc79UMV/ufcAIov3OqLOto5CAMSSK0KQWL1gJvpDL3Fz58BasUxcSBIwAULc95+9aO7Ysqinmq6mslqz9rlC/KOW20gUAerTUUxerfXQODVw9xkYLTR2vQ9JoeF74+9itegEAqFHOtqymmIkkxj5rO9Rqj/9701qynEQRmmW54Qovrre8BjhTGLjEyZ8lY8+JA5whcdRSIwoAaFupi/Wjnxe2uWeUnbb8mLVxPcmiurTUUUqiCMBpWjhJ9mYqcNmbqJwacQQAaBNt/3FH28qxjp8z0J7nQbKoLq18L0gUoVmcTG1o5WQJ9iUAYF6r7URN20WnjC3xyK690/VIFtWn9n1FogioTO0nHdjEOgMAgKOIUexKuW/Yz+vEI7uOJvCI0+rRwr4iUQRUpObehLPXp6mxTqyg7gAAqbRwgTS1DTW3lyn2SxjHtbCfczijnmo+DntT8766vXQBgDO0tup8zeK7aJ21XwhYjqH+AACYFnfWtdhuTt3htOVtPsuZ8e6RKWxY72gd1349SqIIqExNJ525Hjkat3JqOX4AALCmpjgsFHfcrfkbI4j2ObvOSBbVpdb9RKIIqFStJ51aA6wWEOwBAM5C227fWAw2FxsQL2yXK9YiWVSHmvcTiSIAWRFIllVbIwUAqAdtjE3hfomTReyz4+LYNled1pyE6EmtneQsZg1UKJwnX+OJh8YsvxqPEwBAHbhQrRP77LjS8VXNN7qBbSSKgEodvcVmabUmuWrElDMAANKpdYTAgHggrSEmLxWbkyyyrdb9QqIITaJny7bwhFnrybMWJIkAAGfqNeaqPVnUmhL7wtL+J1mE1FijCEBWc3faQDqsPwAAOBttOEor1SFmsSOO5CVSYkQRmtNjz1bNjQKNWlrxlL7evgsAgLxoZ1BKzmRNGF9ZTBKFiKttiGPy2vYLI4qAypFoQcxq4AIAaAexB3IrdXex8POsJ4m4Lkgj5cADq8fKEhJFaEqPo4kGPW87LggMAAA5WL9YzqnW+GtIKFgue+nE0Fg5LNfXoIZ927oWzpEkitCMni+S6T1ACw0SAMA+2psbhviLi/K0Sh9jYzE1+7cfqa6paj9mWKMITan9CwmsVdNceQBAG2hvbkVdpFX6GIs/v9Qt74+qscyWUH8kitAIenLqx4iofYZjn+MfAJAD7c24GuMYayPSLSaJYF+qY5jRgTdj6hmqZ6mBK63Wk5u1QMW60oEUAKAvtNHziGOOK32b+xKfDTuIrW9FoghN4EtNkNIy5soDAEqj3VlWa4edlXLnLIOVhbItqyV5kmrxbuvbmRtTz1A1Kw2bFbUniyyWPVwLqNTnSzc3XhzzAIBcLLbNFtXaNg/lLhnv5P7cMLZi+v6twmOButmuletTRhShWq18Cc9QY91YTHKVbiSZKw8AKIUpOX3KHUPmjLVKx3U1qa2OjowqSrnGUUtIFKFKNSZCcrGYcNnC0r4tnSAqWQYAQJ+YkrNfqikwuYXlzrmgb67EDXHVOi0k0vYeu3u3ueXzJYkiVKfmJEhONQYqPWu5oQEA1CG+UCTm2qfmGCxXsih3kqjW/ZFLC/WUq7O8l8QjiSJUpeaGF8ty92RZ0ULjDNt6+04BWK+Xi55cah/ZLaWLx8aOrZzHG/HVOq3VU46Yp5W6msNi1jBvOHlxobNezT2BpfdxzjoLg7DS2402lV6MHYBtYRtEO5RWjefelEmcsdFp8SLSZ2ot+XGW1upp77SzNd/X3jqzGVEE83r5MqbWQo9Wq+i9xZmYxghgjbUxQk8XRqnUGIOlHNVd+mYcHLPbUFfLWkuorcGIIlSjpy9mSrUFKiXlCCxy9qahL2OjhzjGAIxZe9FT8whlC2qrt3h/70l4lb6gJkm0HnW1TuljuhQSRUDDaj6hlQiuctVXzfsFNsXTR0hEAhiE7emeKc8ki7arua72JossTKcn8QFp/4i+mr+3ZyBRBHSgthNfi418b/OakU9t328A+cXrw2xFsmi7IWFSc52tSRZZSBBhux5i0i3fvbG6OHrerB1rFAEwaQhKWjgxt7IdsKXn4AXAemGS58j5otc7k+5Vaz3FyaEwCTR24W1pG1uKHXHM0SQtMRYjioDm1dwLWHtPnFRvoAjbCGAAbJGqLa05pjhqSJqEP62KF6GO11dkinPdWj52UyDGumBEEdCBFhIuNSJJBADIZamdT9Ue9TKyaOnmAK3eQCDehl72d0nU7Xm21i1JohtIFAEdqbEhCpNctZUdAICU9iSDzmj7a0webO0wW3tHuKnPqKVe1qhlf9fYKVqqzJb3YypbFmIPX4MLEkUAzKslQAHO1GLPNYBpUxc4e3rHz1DLOSjnujotj+C2vm2Wy7Yk53eJWHocdXIrEkXIjhMU9qg1WVRbeWETo+qAfqT+vvdy3hgbFVDq3NlynY/FNSVjnZrbx9zJrZqTaWchTp9GoghZ8WUsx3pP0Bq1JYtaqHPYUcMxD2A763eSKm1PO1pqKsncLeRb2Kdjcc3we8ltrLluSWKWQ4w+j0QRDpv7knEyWsa82G1qShbRAGEvppkB7cuVIKqhvVwytx6QtW0bK4+1Mh4xliyiYwy1aum7mRqJIqwWBhp7LmJaCFRSyN1z2GK915Qssl4+2MbxA7Qt/I6fcaHdwgX81HnQ2vmxhpgklantzF0HtR/bOfV0fMbipLLVJLM1t5UuAOwaLsTDL1N4cR7+YFlcl7nqb2weeQusHnfx9wbYigAGA+fcI5xzP+ac+3nn3Judc3/1+vhHO+de6Zz7xeu/Dw5e8yzn3L3Oubc5574wePyxzrk3Xv/2XMcBBiChqc7kXJ8LLImvYzGPRBFGxcmgwZEvVq9fyLEEUc7Pbl24jVaSNCRRsRdJIkQ+IOnrvPf/haTHS3qGc+4xkp4p6VXe+0dLetX1d13/9hRJnyLpCZK+3Tn3gOt7PU/SXZIeff15Qs4Nwc1YxBYtou3abum7meK72+NooqnBDb3VwxEkiiDp5gvsHk8mZyp5Ymp9P4a9V1PDSnMiEEcKrX9vsZ73/l3e+5+5/v+9kn5e0sMlPVHSC65Pe4GkJ13//0RJL/Lev897/3ZJ90p6nHPuYZI+0nv/U/5yonph8BoUcva0s/hzaKPONTfNr6e6zzXdsYXrlbnyp7om6+nYG9DplgZrFEESX6SetLavpxaNLNUwtla/yIOgBkucc4+U9KckvVbSQ73375IuySTn3EOuT3u4pNcEL7vv+tgfXv8fPx5/xl26jDrCyXIveFzT2n6t6q3uz9zeXpIfqZJEPR13Uhtrs1mwOKKI+fEAakUjAYviEZy9BnJYzzn3JyS9RNJf897/3txTRx7zM4/f/ID3d3vv7/Te37mvpNgjV1vFyKI85m5a0kvdj434TqW1NnMsqZGyzlqpJ+S3ZuoZ8+OBhvQWpOTSS71iv6n1ypgzjznOuQ/TJUn0/d77//v68Luv08l0/fc918fvk/SI4OV3SLr/+vgdI4/DiFzngN4SFrnN7cfezvVnTq1ssR6HOkqVCOttBBvSW0wUMT8eQK1yDz2lQcaUqQXtOWYw5zry+rsl/bz3/v8M/vQySU+9/v+pkl4aPP4U59wDnXOP0qVT7qev09Te65x7/PU9vyx4DTrDeQe5hOt0plqUuUVxApfv6DGtHie5bVqjKMf8eADn6rHxObtXhV4bACf5LEl/UdIbnXNvuD72tyQ9R9KLnXNPl/ROSU+WJO/9m51zL5b0Fl1GhD/De//B6+u+UtLzJX24pJdff1AYFzToRZgs2hMz9ZJEaX37ztbLcZLD6kRRPD9+pvIPzY+/fhaLKQKJ9RqMnr2AZ6/1im1YWBF7eO9/UuPxkyR9/sRrni3p2SOPv17Sp6YrHY4qfUFDJwdy2xuTlf6u1KbXeINzWlpr1ijKPj+exRSB9Ho+cZ65qGL4/gAAbFGq/aDdOs9Y3fZ64T4mnIq2pV44ZrehvnDUmrueMT8eQPXiefKp5srTEGPJWQlKAPWy0H6kbA+xjHq+WdyJN1U/1Ft5tewDRm+ntWbqGfPjATQlxXQ0GiJsVfqiEIANltoPLqzyCJMitAU3xHdGi+unpylnfBfTGOqxh2PmbM76Aemcs11AoCKcOG+2NwDpKXDBMXzn1vPeU1GGEH+dx+J5wWKZWhHWLfHDsvjatKe6SvE9POO7XNP5ge/YLveMLfmzao0iAO2wnhzO6chUNBogLOG7BqAmnLPOR+ywbIjNhv/3wur3z2q5xpAkSmv1Xc8AtKOmnoEcxpJFU/VTU4OJshhGDmAK7TAwbWg7x9rQlr83LW9bLnEdTo1QI6m0jEQR0CmC1JstzZMfHo+fCwDAFiSRgXWm7iA3Fp/VHJulKv9Z55Ua6nZNcnFsBkHPUx2XkCgCOpRiMeeWxb0NY38D1uJ7BmCMxXODxTKhP3PHYLxYcZwg6PX47Xn712773N/nEk1b3qclJIqAzoTzvunRnMfwVBzB9wvAFAtt8Nh069JlAtaIvz81H78pk7M9x6lHt31q9Fr8t5462kkUAR3r4SSXwtSC19Qf5nCLVgCWza3Fx3nrPLQNx8wlg3qt07MSZDUm3lIaO57CpGTrxxuJIgBYYW1PAzDoPcACANyKtmG/qREeQG49xP63lS4AANSq5qHOOBdJRABr0H70gRHJ6cR1NzXquwapynzm8WT5WO1pGlgJJIoA4ACSRZhC4AJgDueItGpKFtRSTkvmEgLOORPrfu3BeQBWkSgCgINIFgEA9qj14tYiy21xmAywXE6rttRVj/Xa4zbjfCSKgM7QmJyDwA8DjgEAW3HeSKOWkSWMItluTZ3NxWLWj4m9zprqbrm+aho9WDMWswaARMJ58gSBfWJtIgBb9XQXnVys3VlsqiyWymjV0TqKEwpjCYa59w+fb21f1X78zNXt1LpexFn5MKIIABJiZBEIXgDUahiR0wIrixzPrauD9MI4bC5JFN85LXx+/Hv8nvHfS8jx2TmO0ThunqpXywm7VjGiCAASo3cYALCVtVEwLSg50rd0gqpna79LY6NY5kaszD1/6jlnSDmqxsJxGid1p0bfhckkzpPnI1EEdIYTaz4E/f2wEGgBaAPtRlolk0WMMj5mb73tfd3W42MqcXTmcZYqSbRl2tfRzxjrQN2TYItHgXGePBeJIgAADuACAEAqNSzEXKPcyaL4c6Y6juhQmrbne3D2+jVL+2rqOIuTMuHvW8p8dPvWTt+aS3BOnaPWbG/8/z3ljh/nu3MeEkVAZzip5rcn2Jkadrvl+dhmaeHE2N6ABwDmkDw4x9nJIhJ86cyNPJl7jXRee7y05tXU546NqlnzvLly7LGnftZOzYvrZSwhOvW3vbiBzPlIFAEdoacyv7nAYe5va5IT8WvWfC7mTS2CedawbACYwgVQemdcXK4ZpbHU0cO+vuFIXZxdh2v271hCaUuiZK7Tas/2pUyglVqYfW4UE8mi85AoAjrARa09a4b8zv19qVGscaTL0nGac1u27gOCFAAp0bFznpQXlynvxEQ7sp+F70q4/47EBnMjdbaUZeo9W8O58jwkioDGjQ15JRhpX029LGuSWkt3Fll6jzOCiLFRRtbrGkA9GGlynqVRH2ts6ZBZupiNy9PzPt+7jlPJOpuKuY6WKU44za0N1FNyKMa58hwkioAOjC2oiLqFjeJUcDD2ty37/swGd2tAMzdPfup9c64hVFNiDgAwPnJjy4LC8XukKg8xWp3i/Zf62NizNlBviMHSIlEENIhGox9rRozt6eFaGsFzRIogas0c/9w9sySLAKRGT3keS+fvnkdrWFDT9+CsKelj71VDfeRCDJYeiSKgEWuDGHqq2jEVNCwtqrj1vYfXHkm85A6ySwUJjNgDgDpNXWgyHQx71JTcqsVSfbJuZFokioCGpJgnj/rFwUmqOfKSjeH51hEcAkiNc0oeKdYuAkJ8d1ErEkVA5ejpwpiz1ufZOkKp1+OSZBGAVOjgyevM+t7S0UL7cUOtxz/f3XSoy/xIFAGV4mSJJWctrLh0d7KUn1U7gn0AKZB8zuuMi9K1dzbjgvhWtR/3xEZ55byZSctuK10AANvEQcbwA0zJeXxwPN4QLzAOAEdxLjnfmTdDoI1Mz/p3Ymy9K5yP79lxjCgCKpEqaKGR6hO9K2XQMwwgFc4n57LURlooQ02s11c8wruk3u7gx0jM/UgUARVJcaIj0OwX+74M6h1AKlzwpMfC1chl6xTSLbHD0nuOHedjI55b+g5M3ckQ65AoAjo0dgt1AOciUAEAWyyNIkI/5pIzY8mhNUmgqWN5Lt4fe9/Wrg/orNuPRBFQgTMuMDlx9okpaGXQqwWgF7Wd50qUlcXJMZUc2nNMHE00bXmvPe9pAd+37UgUAUblSOKQLOpTOOSYRjMfvm8AelFDhwRtYDtq2pdjHUcpy57jvWrr+CL+2oe7ngHGcFcz5ETDmR91DqBlYdxi/XxnvXxoUy3fjylcl/SBRBFgxFiCCEBb+F4D6MUQy4wtmFtaWJ6SZbNWL7WqsW2tPVmUW4p6sngusoxEEWBIqQQRJ80+1RhYtYLvHIBeWLsgHuuUK1E22uA0aq7Hmstem3CWhpVzkXUkigADSp6waKT6RoOZH985AL0pfd4bRhKMrZ1UOpEVlo32GDXJfbyWPo/0hkQRYAQnP5RCsqgM6hxAT0q3NXPrPpaMwViPEjWq/XglMbuMRBFQGCcpWMGxmE/tARYA7JWzrdl6d6YS7WD8mbTFwLlIzK5DoggwwMLJisCkbxaOwR7RowWgJzmneY1NM5tToh2MP5O2uE/EAfOonzJIFAEFWTnxEZhAKj8toDelF1IFgFZtTRIBpRAHrMN3OT8SRUBm4YKFDH0EwDkAANLbe24tsUAv08/6VnMccPaxumXq6Nb3xTwSRUBGY7dktYSTJlAO3z8APTg7/qn9XMoIE9TC4rXMWjWXPRcSRUAmDIMGMIXzAoBenJUACdd8q/2cWnv5sR3T/8ugzqeRKAIyqGGameWyIR8ClbKoewC9SHm+SzViu2QsxPkfUp3HQY1llrj2WUKiCDhZrSdP9I3jtgyCFuD/b+/uQu7bzoPQPyPZsQa12GItuzvhGGoEk4C7pyEGCuLn6bY3aS+EXaHphbBLSQ9WhEPrzalCoKC1ULGBVEtSUUNAS0NI1FgqIqRJd0pMuhtzujXB7maToB4x9SKadHjxruWee/7nWmuutebH+Pj94OX//tf7NeaYc83xzGc+cwxaN57I/57xppUqolNtNxb3pcZjuMY2M89jezcAelDLSfRYTVJLe1mHqiIA1jaMNc6NOeMxaTyHz1oT3e4dCxmL+1XC8XetGtsc4drnHBVFsCInHmomQN2ePgd6dKwyGn4cTa0ItmaSaM/JpKf+pnGhLzVeN9TY5jHvs0epKIIVONlQO3cyt3fscwlmgPMXn2uPT1tULU39zfEYYCxmaCo+uOb42GLFwRrjF++zaRJFsLAWnpWv9UTPspTjbk+wAjDPlsmbrZz6e8bivgzjr6mKuqnv39taN7tK2LZeSRTBQlpIEEW4UAUAGNo6UTOuKtqjDeyvtmsLldFtMUcRTLg2UVLbiXwOySIiJA73os8ByjCeM2mLv3fq9XtXiVtDiW1qwThRWIva2stpEkUw4ZqTXItJopa2BWrj/QfwUgJi+HF8vQelPmI0pdR21a7Wm3W1tpuXkyiCBbQ6QDrJc+RY2JYgC+jZ8dGV8SpoLd6cm3Jp+0oZHzxiBO2SKAImGfg52nOpYACIiEeSRj0ouapITLC+2vu49vb3TqII7tDDCbCHbQQAKMmlmzR7xWfDxwBLSVq1qub+rantKuOmSRTBHVo/qagk4cixcJ9bJ8gH6E1vcxGdc2rsHb6+ZT+NHwlkfR5F38bUfGi9kyiCO/RwIhEIcORYuJ2+A5jPzYmXnFsFbcuEkaoLblHDe3h4XDvGXyJRBAAA7G54UemCbR7VPW2rOUFXU7u9jx4lUQR36OWO17HstfXthJIIWIAWXPs4h3PfNDFYn2qPwb2f6yVRBHfq5QTYy3ZyWa3BCgDbmZr0eDwPyPhjKtYw5uwfg9kH++rlxnRJ9HXEY3s3AKjH8a7G3gEL+zGp4nY8ggHUbHzeuuU8NqymcB68/Bh0BR16AAAgAElEQVTSmv2k//flvbCdS4m5XvpfRREAFMaqMgAPnAcfzOmHNfrKzaFy7LXaXa+O/d3rZNcSRTDTpZNyTyfsnraVl7PvAWAfp6p61xqbx48Osr/xandso8ebdxJFwFV6O0nycoKT7XncD+iZ8988S8dnkkRlE49tp9c+liiCK/X+vOpRrydNXrqr4hjYjv4GetZbjHXJ2lVFkkR1kCxaX899LFEEM50bLHsbSHvbXk7znPy29DfQE+e7eZaKy6ZWqqNs9tP6eu1jiSK4Qo/Pp54jgOub5+S35fwDwFrjwDBBZKyBR/UW60oUATcRRHBkFQ4A1uBmxHVu7SdVRHBej+8NiSIA7uYO5LZcNAG9GN+McP6bdusYLEnUBu+LbfTUzxJFwM1MsMuYY2J9gnmgN8ebEcPFFHofa+7d/mMfutFTP/tvG71VOEoUAUBlJOSAnvV+YXzv9qsiapO4YH3D98ywyrHF5PVjezcAajZ1QjDoAgCsp7ULsi31liTqJVZ3A2lbp95H595fc/ZPScemRBFcwQkY5jmWs7OeY1Con4GeOO/drvUk0fHYOBWv95BMGe/j4fa2ut+3di7+uvRo7KkEUon7RqIIuFupJzgAoH6tX9zf6pr4q/VY7XiMXNrOlvtgmAgbJ4iGc1KxjHPJomuUuk8kigBYVA937EqhqghomWqI0665+K9tTJ47rjk+HnWqH8aVLvrrPj3EuiazhgX1eNLtcZu5rIcBtCT6GmiVVblOu3UelJLNTXwNEx6Oj3mGfVX7cVKKlvtRoggW1PLJAm7hPbE+QR9An8bn/XPjQU3JlFOrSEkQLUPcsIzWjz+JIlhQ6yeMcww2jA0DkeHx0eoyonvq+dwDtMkYcdo4YTL1CNbUXDWlO7UdU49M1bRdJdKPXGKOIgBWMzWxouAEgDkkwR81Z46ZmuajOVUVdfx8ahs83r4M/cg5KorgCr2uonCJC3/OGZaHTwV6jptlCPiAVpR6Ltu7IvY4f8+cmLOmuPS4TadWkDq1LaUeJ7XRj0yRKIIrDQezcwNbbySLuOTcEqKOGwAi5lXMbOnco09bjl2X/ta5eYlaHGNb3rYtlfI+q1XLN+kkioBFtHqSHAaIrW7j3o7JVv17P/0ItGDvi9epcX9cHbtlouJSJVGtFe/39l3J21YbsQNjEkXAXY6BVEuVVVN3D/e6g9gTSQ6AvpUwBozH/jkJmjXbfc3vPve9JfTt0JKVY6VtW23csLtfi30nUQTcrLTy8CWcuns4/H9L21uiFgdbuEVK6bUppV9KKX0mpfRcSukvH17/sZTSb6WUPnn4+K7Bz/xoSun5lNJnU0rfOXj921NKnz587aeSExmF2vvQvHacX+tG0rWTUZ9LWpUWuywZP55aHY3b6L/rtfoYpFXPgJu0nCRqaZtq447W/Ry/TflqRPzVnPOvppR+X0R8IqX0kcPXfjLn/LeG35xSekNEPB0Rb4yIb4mIf5lS+iM5569FxLsi4pmI+OWI+FBEPBURH95oO+Cims/9w/Pu1BLv17jn54cXrCWNBedWNltCSdtas1OLjOjfy4Z910p/qSgCrnYuoVL7hX4rJ/fa1XwMwVJyzi/mnH/18PmXI+IzEfHEmR95W0S8L+f8lZzz5yLi+Yh4S0rp8Yj4+pzzR/PDm+vnIuK7V24+XK2FMXiJ6p3SKoDuMY4ZW9muVk09cikmm6e1Y1uiCLjK3PmIDCrcqrWBFpaQUvpDEfFtEfGxw0s/lFL6VErpZ1NK33B47YmI+M3Bj71weO2Jw+fj18d/45mU0rMppWcXbj506dr5hVqLnSSJ6meOzuu10k8SRcAs1wwQtd2BaK1UtAW1V6bBklJKvzci/klE/HDO+b/Fw2Nk3xoRT0bEixHxE8dvnfjxfOb1l7+Q87tzzm/OOb95kYZDx26JKZasJNp7DG1toZOejR+t3PvYKllLx/vFRJGJFIGp1b8uKTlZNBzkzEtUthKPH9hSSulV8ZAk+oc5538aEZFz/mLO+Ws559+JiJ+JiLccvv2FiHjt4MdfExFfOLz+monXgRXNvemx9FhXU0xjEuo6SPr1Z05F0XEixT8aEW+NiHccJkuMeJhI8cnDx4ciHplI8amI+OmU0isP33+cSPH1h4+nltsUYA33JFJKHFCGgYi7XWU77pthECmQpCeHG2p/PyI+k3P+24PXHx982/dExK8dPv9ARDydUvq6lNLr4iHW+njO+cWI+HJK6a2H3/n2iPiFTTYCuLhsfUuxyNyxempVN2N8Peyr9l1c9ewQXLx4+PzLKaXZEylGxOdSSseJFD8fh4kUIyJSSseJFK24AYVq7XEsAUmdxsdga8clnPEdEfF9EfHplNInD6/9tYj43pTSk/Hw+NjnI+IHIiJyzs+llN4fEb8eDzf63nFY8Swi4gcj4j0R8ep4iL3EXxSnxfP7uaqiVuOQU6vAnfu+Ulds4+XG+9a+mtZC31xMFA2NJlL8jniYSPHtEfFsPFQd/f/xkET65cGPHSdM/J8xYyLFw995Jh4qj4CdtBa8TFVG1X4C79m9yw9DDXLO/yam5xf60JmfeWdEvHPi9Wcj4k3LtQ6W1frcdHtcOG79N8eP9UdcP0YfjwNjex3sq0e1ci6bPZn1VhMpRphMEfa2ZBl0CSdL8xC1ZXxs7n18AcA5PcUfU8ur38LYXj4V+m2blSgykSL0oeU5YHoK0nphnwJQi+Gce+PX1/p7S5kzT+CS8aMERD1u2VfjuSeXnIeyhGOmlSqrOauemUgROtLjhIrUSzAJQG1qiU9OTTh96gJ/yfhxuKAFZbt0bJw6VqY+bk0gHb+vlGuYFo7bOXMUmUgROrD2CW2vk3cpAwbrMQEmAKWrYUGNqTadmttxq7kCjev1mNpXp46TU8nFU8fYnPdLKcdKKwnOVPpGpJTKbiBUaOqCeu15fHqYxJF9mYuqbjlnO64g4i/20Oq4fSruWntbrxkXLRLBPW45nu+N20o+X5TctgmfmJob+qpVzwBqUdkJmgUMS5btewD2tvcN+XFlw6X2GDvZ0njerluOPzHfeiSKoEPDwKG25eLd8eIcySIASlBKleupmA9KcM8x2cojXqWSKIJOnVp9o2TXPN8vGOrXpWPbsQHA0q5ZzWzr2MtNFNa253FV2nFdWntuJVEEHSt5QsWIy0HXnEnx6JPjAIAtXTvubD1Oqb6gRaUd18e2tJAsesXeDQDKsPbJ7JoT+anlMy/9/tpPyABA21q4gISSlJIsqmFlw2uoKAI2dQyQTKgIAADc63htsef1w3je19of95QoAjazxOoGAAA1KuGiUQwG2yil0ulWHj2Dzu0xoSIAwFDNF1S1GD6mX9uCJnBJiYmZEts0l0QRdGyvu0qSRQDAWMvxQUkXi+Z1pGUlvddqJlEEnRMoAACsr7SYq+Zqh7Xoj7qV9h6rmUQRdKqEgbCENgAA+2v5Ak+8U4cS5pDifiXuwxrPARJF0LESVgao8cQJADCHyaPrUGKS6DiPlFi5bqUdV3NJFAG7MaEiANC6Ui8US0yObK3UJcyPbXJjtQ2lHV9zSBRBh0oaEA2CAECLSoq3eFSJ1V5TiStxMnt4bO8GAESYUBEA2M84BikpebCmXpNZJSWJ5hx7xzh5qt0lbQvtkCiCzkjGAAC83LhqYxgvXXsBXsuF+zD5UHpbl1TS/rmmLeembChhW2iLRBF0pKSBEQCgNFMx0pz46ZhsqS3W6i1ZVOL+ubYtJbWddpmjCDpjcAEAmG9qjpjhilS1JomOellcpLT903JfUz8VRdCJ0gejXu5kAQD1Gc8Rc3xt/D21GieLat6WKSUlie55rBG2oqIIOlDS4HhO6cksAIDhiq2taXW7IsrYtmFMXkJ74BSJImhcLUmiXsqeAYC6nFptqmUtxWKlVUiV1BY4xaNn0LDagprWy54BgHrUFkctZTjfUu1K2g6xLTVRUQSNq3FAmpo0EgBgK70miYZqj8PsQ7idRBE0qvbBXbIIANhTzwmG2uOw0pJEqomojUQRNKi0wfFWtbcfAKhPrcmRpdU+f2QpcaQkETWSKIJGtTQg1RicAAD1aimOukeNq3OVlJgRw1IriSKgaLWXPgMA9RBvTDtOcF1rddGeSklawTUkioDiGWABgLW18uj+mo4VRhJG0DaJImhQqwGOgAQAWEuNj1ntRcX3ZfqGmkkUAVWofUJFAIDaDWOwEpNFJc1PFNHuzVvaJ1EEVMOdPgCAcojLppWWsIJrPbZ3AwCudXw2fvwaAADrORVvlTC/UynJmZIqrOBWKoqAqpVY9gwA0JqpG3XH18VjD0pImMESJIqAKg0HYMEJAMC+VBM9KKUdcA+JIqAJw+VamaZvAIDWlBLflJSsgntJFAHNKSVgKIk+AQC2sMcKtXsnaMRZtEaiCKjSqQF570ChRJ6XBwC2cO98Rcck09yfLSlBI84qT0nHR20kioAqnQtCjo+gGRwkiQCAZc2Jr4Zx2jj5c+nnh8mmU39/+Pv2jnE8clYm1wH3kSgCqnVuUDZgSxIBAMu59sJ7Kv6Ykyy65mt7xziSEY8q4WatGPh+j+3dAIBb7T0I1cAACQB9GMZFS4//t154X6oMuuVrpcU2pbWnBHuvgLd3G1ogUQRU7VJV0ZpBU8kk0QCgL+PHvZaOe7b+fVPVQ2tt2y1KaQePsl/uJ1EENO2eCRVrZ5AEgP6MY59744G9Yqipdo9vAnKf1pJdjo3lmKMIqJoB4VH6BABYIgFQ6mM8JcyDU7tWk0QtbdOeVBQBXZhzB2o8sMwZcEp7tM0gCQAM3ZMQKL2CZ6+4p+Q+6Zn4dzkSRUCVbgkM5iy1OvdvlZYgGiqtPQDAPkpP9NxiuE3DeYuO/9+yHbVqqZrITdJ1SBQB1VpyQDgGGreszlHKYNtaIAgA7KvU2GKcLIqIzRJGpcR9vMT+WJ5EEVCVNQOAS79z6uulBVAGSgBgaM7NsKNxpc7x81JNVXjPmb+o5G1qwRbJtBqOz5pJFAHVKWlAaLGkGwBoz9TF+zWP3Zfm1ikB7qk8Uk102dqxcQ3HZgskigAWsPecRQIXAOCU8Vw+U18fqu0m2DVVU1s/qsby7K/1SRQBLGQYeAz/v7bagjkAYHvXLgBSY3xxzY2zccJoTiVSKwmKaxJrtzr1+699DJJ9vGLvBgDU7lSCaM4z8ku3AQBgKTVdrN8af43juCk19UMJpvp0uF+On4/7dfh6SmnyY/x7WYeKIqAaNdzJuSVZVPo2AQB9qi1GGc9bdGoeo/HPnKsKb/nxtDVj62FV2rnqovF+mbu4TA3XBTWTKAJYwLhEe3gn5Jx7n493RwUAWFpL8cW5eSTHcdipuZxaTEhs8XjhpUfc7unXFvdJSSSKABYy567VqZ+5J2FkoAQAllZzfHGpkuVo6lGmqXhOVVF5v5t1SRQBVajtzta1kwTekjAy+AIATFsiRhonjfZe5XZptU5azvokioAq1DiQjdt8y5Ktp36mtr4o0dwlgo/f20JACAA9WOJx/vHvaDEOEE9yikQRwIrOrc4w9drx+4fPyE89Tz/8Xm53rrz81PcBAG05dZPolp+rxdrxpCRU3SSKgCq0UNFx3IY5y6+em1Dx+HVucyow0qcA9Gxq5daex8apldDGn9e+su3aSaLSt5/TJIqA4rV0R2LOo2jDSqJelmfdmj4EoAZrTzR87nVj5aOGfXLpUfWS49c12+b4aYNEEcAGlp5QkduUHLQBwJQ1Lrwv/U7j5ctdszjJVGXWpe/fI8Zb82+KWev3ir0bAMDLjSe0nlPazHyCFwBqMawuXjoWuJQkEnvcZmr6gHGV+NG5vl6r/7eoJqJ+KooACjQ1l9GpuYqU+AJA2+ZWp8wxp4KlxtVmSzPVx+f6/VKyaMk4TzURl0gUAcXrNVg5tdrZqddMen1ej8cQAG2ZW5Vy6yNl49/R+4TWW7o05xFsSaIIKMacVcF6dk2gMAwaBRgmVgSgXeeSR9dWtYy/Llm0vyX7f+3Hzhwn7TBHEVCE8d2w47PcxwHHwHOdNec0qI0kEQC9mYoB5j5yRjnWiOXW2Me9x5otUlEE7G7Ohby7FLcZT6Z47c8CAHW6JwYYE4ftZ7gfS94HJbeN60kUAbuakyTyONp9bhm4zwWWNQUCqokA6NkWi16sNeFySfZO0iyVLFrjUcK9+4Z1ePQM2N2cwUWyaFvjZVxPLetag1rbDQAlmLNSV81xwiWlbNdS7Vgyphabt0tFEbCbawcXEypuT18DAOdiMLFC+87F7PZ/m1QUAbu69bEo9lFTZVct7QSA2tQwZ06rtqwGGk5FMFVpbv+3S0URsLl7npWvKVHRstLn/im9fQCwlbUeNeptjC0hMXZqFbRr23XpmDi1n/fefrajogjYlAv4+tVyB6mGNgLA2pZKEvWcMFhjmfp7HNtzjMluXd1u6meOCbFa4j3WIVEEbMqA05ZSAqahEtsEAHtaciLk3pUUZyx5A9bjhAxJFAGbWmJw9fhZGUoLJE49Rw8ALKfnOKykKpupKqdb94v4iTFzFAFQFStvAMC+eluJttTE2PCxs/EjaONE0qUV63rZl8wjUQRsaukJFQ1q+xruz7X3hbtdAFCOLWOAEpS6jeNkUcSjVdan5jAav9bzZOW8nEfPgE0tPaFiqXd4ejIOSm6dUPGcngJRAKhFT/FYyds4jo/Gk1EP/z/+ODpViUSfJIqAzS09oaKBbH/jQCRimf0yvEMmSQQAt1kzVtozHlvj5lTNbumLqcSRGBuJIqBqkgflmCpBvyfAUEUEAPfbYhzdeqx2I2l9kkV9kygCmmAQK8OcZNGcu3+SRABQny3isb1ihNJjkjXat3eySHy/H4kioHrHu0kGk3JMJYvGCSKrlwEAc+1dRdRrnLl1smit+S65jlXPgGb0tlRrqcarb5xanlVlEQAwh3hgnrVi4TVvyLpxWCYVRUBTzi0BynamBvbxHcBzK3CsNTk21CSl9LtTSh9PKf3blNJzKaW/fnj9G1NKH0kp/cbh328Y/MyPppSeTyl9NqX0nYPXvz2l9OnD134qib4hIh5dsdNYU5a9q4iOnDIf3Pv+OPV+u7QiG9uTKAI2tcUjYgaWctyzr6eWehXA05mvRMSfzjn/sYh4MiKeSim9NSJ+JCJ+Mef8+oj4xcP/I6X0hoh4OiLeGBFPRcRPp5Reefhd74qIZyLi9YePp7bcECjFqaRQyzcmtqq2Xrr/VBGV5dx0AufMSQpRHokioFmtBXq1WXNSRehBfvDbh/++6vCRI+JtEfHew+vvjYjvPnz+toh4X875Kznnz0XE8xHxlpTS4xHx9Tnnj+aHE+PPDX4GmjOeD++aC9VWx5mtqqXu7b+pfUU5xu+ZqePq0nuOOkgUAU0yEAEtSCm9MqX0yYj4UkR8JOf8sYj45pzzixERh3//4OHbn4iI3xz8+AuH1544fD5+ffy3nkkpPZtSenb5LYHlTD2+MvyYmitv7oXq1jeZtkrebFktdWsFcA1JBTchXzLcP+P3n4qh+pnMGoBVmWAcbpdz/lpEPJlS+v0R8fMppTed+fapN1o+8/r4b707It4dEZFScjVE0S6NK/eMOy2PWVtu29zxv5bqoXECsmRbtrH0vuA2FyuKTKQIwK2c5mEZOef/GhH/Kh7mFvri4XGyOPz7pcO3vRARrx382Gsi4guH118z8TpUae2xZcuqkS3m39sjuTH3b9WSJDqqpZ1wrzmPnplIEVhMiyXdAGtIKX3ToZIoUkqvjog/GxH/LiI+EBHff/i274+IXzh8/oGIeDql9HUppdfFQ6z18cPjaV9OKb31cJPu7YOfAQZaSwSUnIgpuW3nDCuLoFUXE0UmUgTWsOWEigZyoFKPR8QvpZQ+FRG/Eg9zFH0wIn48Iv5cSuk3IuLPHf4fOefnIuL9EfHrEfHPIuIdh0fXIiJ+MCL+XjzEZf8+Ij685YYA/TlVLdXCZNW1tnsN4uw2zZqj6FAR9ImI+MMR8Xdzzh9LKb1sIsWU0nAixV8e/PhxwsT/GTMmUgTaNl4lYe2B1pLqZajheX4oTc75UxHxbROv/+eI+DMnfuadEfHOidefjYhz8xsBO9hqfNxrHD7GYeN4rJWYoMT4ZsvYd3xTtrS+4HazVj3LOX8t5/xkPDzT/pY1J1KMsOoGsDzJIgCgN6WsOjVe0awFrWzHElTxt2dWouhoq4kUc87vzjm/Oef85mvaB9Rh67sOBvJ96X8AanGMUba44O3torrFeKDkbdr6+JIsasucVc9MpAgsRmkqAFCqreOTrR4725OYb3t79fmxYsxk3/WbM0fR4xHx3sM8Ra+IiPfnnD+YUvpoRLw/pfSXIuI/RsRfiHiYSDGldJxI8avx6ESK74mIV8fDJIomUoSO7J0kKvE5cgCgLOY3pBV7z00l9q5XKv0kmFIqu4HAbCVMYmjA2od+55KcswOkIOIverfFuLXlRNZHe47Fe98w7NHe8Vcpxx5nfWJqyp+r5igCuEcpExiWniAHAPbVWlVRCfPHDB9Log/D2N9+r8ucR88AAAC6s3dFxpJKehyohDa04FzyZZig2buvz81btHfbmCZRBHSlpCCpN/ocgJq0GDOUUNFTUgKjRpce59py5b5rnGqr46BMEkXApkobtNhGCYEpAFxrXAnRwgXtcZtK2JaW+nUNp2Knc/01/lrJ8Zf9Xi6JIqA7khb7KSUwBYC5hhUwtSU2So53xv1aS59uobbjjPaYzBrYxannlHtrQ08EOwDU7Dgxby03nI7Jl1Pj7/ARpb0nueal/bBGkqiG45WySBQBmythBYQS2gAA1Kn0ZNGlCp2pGGjv7RknSnozTERKnrE3iSJgNyUkakpoQ2/0NQCtKHFMm9umqcTE3jfwJEiWp0+5hUQRsKsSBq+9g6OelLC/AWAJJcYP9zy2VNIYXVKf1k5fcguJIoCYnqgSAOCcS8mirWKKpea2Ga/ytocSE3C1KykJSB2segZsoobVG6y+AQBca5hcGcYOw8mip35mKUvHLKe2Z0tTCStxGWxHoghY3aUk0dSEkIIBAKAW1yQ29q7YmaOEybrHSTdJI9iORBGwiUsDegkByZG7WADQtjWqZYaVyZdWHDtVbTT+ualYZKuba8d2lhADnUoaldC20pW0H6mHRBGwqmuSPyUNYFOl4wBAOa69+B2P52skG+a26VSccfz5qdhjTtJoDaUlGcxhBOuTKAJW09LdntKCJADoyal5fu69IbVEdcq9FchTVUTnHlvbMh4pqeJ7ivhsPn3FNax6Bh3Z6pn41kqC3bkCgH0N44mU0v/+//Hz4WtTPzvna/eM8+f+xi2/65av9caKtfM5briWiiLowDhps+az7S0liIa2nhcAAHi5ax/puuV3XxvH9JCgGFYVlRb3lLJi7dor2y3BXEVcQ6IIGjc1sJ+aKPHegaPUIGJJJlNchkAFgBLdsjR8D+NZ6Y+g3bLfliIWpEUSRdCwuQPXnGqZuXMD9DRITvVPT9t/q9KDTQD6NjfpsPdYtvXfL7myKGKfZFHJ/XGKm3XMYY4iaNw1A8H4Of/jYDscBKee5V/yufxa9b79t9g7wAaAU4ax0KXv60np8zZuvRrc8G/WoKa2si8VRdCYe1feGDKZ4vXcpZlHVREANaihimaPv1nyGL5FZVHJxwQsQUURNESFz76svnE9/QRA6abG995vDNWQLBomjJbUQpKo5H1HGSSKoDE1D1otWGqZ3R44VgGoxfjRfMpPFkWslzCqOYapue1sR6IIYAWCSQBoU0kX2sMKp/HH1m0o2VI38WrYVliCRBE0Yu+Ba++/XzJ9c5pkGgDcZpj8GC9IskcbSnfvFAEtPHLWMlM/LEuiCBpi4CpPTQEUAFCXc4mhrWKPmuLPe6cIqGlbeyKJtzyJImAxTs7TTHINALSstgrha2PWmrZtjtr21xyuQ5YlUQQN6H3ljRqY5BoA2ILqinmuTZbozzK5DlqHRBGwGhU0j1pzudZa6Q8AWMaeSaIaq1TmtFkiokzH2NG+WYdEEbCI4cX++KK/tqBhC6qLAKBOLk5PazVZ1Ko9Vslbgqq59T22dwOAdpybTFFQ9Sj9AQD1OSYWShzHxyuhMd9Un7Xcj8PtqilWlyTahooiYHVO5ABAK2qpvtiznbX00dFUrFrbNtyjtkp31xbrkygCVlNrOSsAwJRaqi72vPCvoX9OGceuNW/LtWrY1lrefy2QKAIWJTnELQz6ANCW2mLBYSwyXK0WeiRRBJUraRAuqS3USaIRgBrUkETYs4019M+U2h7B6olqom1JFAFQBIM/ADWQRGhbz8miEleAq2mi7ZZY9QxYzKXBxUmeS8YrcDheAKAtp2LFksb8EhMmWyolButxrqhSqCgCoFg9B2kAULvhOD5+tPw4D9Dxo8THz0tqy1ZKq6iSJNqHiiKoWCnZ/qHe78CwHMcSACVR3XCbcXLolGGCooSqo57jkGHibq/jvcTrnJ5IFAGbctIHAGjfMdlwbdw3fgx9+NoeybpeY9epZNE9ibMe+7BmEkXA4nq+A8Pyeg3QACiP8eh694zj45/butKl95h22N/D14bmJO9uSTh5r+1Loggq5yKalvUeoAHArUqIEdcax/ferp5cqgybsy9OJYimfraE4xaTWUP1Sj2Rltou6iRZBADztXyxvcdNpBIn2t7aEts+nsD81PewP4kiAIpW2uobAFCylpNEQ1slboZ9uVaSqvQYp+SV6ViHRBFUqoYTdA9BCtuQLAJgT7WNPyW1d43kyrAiZY+E0ZJ/r6R9dcm432mXOYqgYhIx9GQYmNwbdHrvAHCtWsaO8QTEpbR7jUqnrZIWa1cVlbKP5jKHZPskigCoyjA4qS2wAqAeS9yY2EOJ7V57vL404TJwHY+eAVC9koJhANpR242Jc8uYt25qKfc1iT1omUQRANWZmpfA5GZW8JQAABRgSURBVIoALO3c6kwlKfFRsz3s8SjaPVRBUSqJIgCqdCqwkiwCoBfjBNFaEy7XZMvJlu/5Gy3snxa2gWnmKIIKOSkDAPRNBdFpW8zRNHzUbWofzPn7te+72tvPaSqKoDKCAgCAdZV+U+6YnDgXD4oVt3sEbfh3pqq8hh/jn61Z6e8TbidRBBVqYWCBJXgvALCWUseYay/Oe72Y32r/jedNnEoKnfp+KJVHz6ASNQ4mNbYZAOhXLZXbc9u3xSNYPLjmmBkmi0o/1s6pue2cp6IIKlLLyhsRkkQAQF1qSRJdq9dkUQ3bXPu+qbntnCdRBBWo8SRcU1ILAOjbnDl/SnBLBUrtVSv32Prxs1t/tsZYn7ZJFAEAADRsOMEy5ZEsojQSRcCqer2DBQBQgmGlVE/JiBqTLzUl9MT4bZMogkq0dDKuZQCkDi29NwDYXi+PZvWYLIqoZ3t7TehRJokiKFwLwUvt7QcA2NsSyYPeYrIaEy+97SPKJFEEBTqWnbaQJDpqZTsoT03BHwDcY6l4qqexs9YYtKd9RHkkiqBQNay8ASXwPgGgdUvePOx13Kwp8VJTJVQNbeR6EkXAZoaBiUEFANhbDdXbS7dRDFaHYbKo1EmuS3/vcDuJImBTx0qpGleioFwCFQCuUdMj/msliXqKw2rYz6eMJ7nuab+xH4kiKEwtQcsSJIsAALZxjLl6nt6g5riz5IRRSW1hGY/t3QCAnpJjAMB+hsmSHvW63RHt3KAcT+XQ8z5lPSqKgF0Z3ACANZU8x8tWTiUUeu6TWlzaR3vvQ7F8mySKAGiCQAWAKcP5EXscK04liWpaWatXl45X+5C1SBRBQXosHzWwsQbHFQBTjA8vV8PKWpw3XCRmr/3XymN9vESiCApQ08obS+p9ngCW51gC4JSa445hIueaC/I58eW42soFf3nm7JMSjmvJxnZIFMHOag5altDrdgMA26sx7piKFde6IC91Va2l1Fj5cs0xu+fx3eujna2y6hkUoMeTao8VVGyjxiAQAKaMk0RbJ4soRy2x8zEOq6GtnCZRBDvqdQA2eLAFxxkARzXGXJfGsXNfW6pi3Vhahhpvgjl26ubRM2BTtQ1yAEAbarpoXeIie4mfrzFBwf5UpdVPogh2VlPQspRrt7nV5+RZjwAFgFpX8iqxvSW26R6tbU+JxGJ1kyiCnfR40rxlm4c/02OfcTsBCgBTc/uUrMRFTlobT1vbnpLp63pJFMGOSgoCttLjNrMfAQpAn4bn/dpijxLb29p4Wuv21NbeiPl9PawArLESsDUSRbCDHk98S21zj33HfWoNBgG4T4kJl5q1Np7WNgdTzcfz8NgZPy1w/Djuj+EH+5Eogp30dPJbuoy6lgGdcvT0fgPoXa1xwtKrRK3RD60liyLqXFGsVlMJI0mhMkkUwcYMRNc5NXDoR64lEAToR+8Xnmtuf4vJoojyt6f09s0xVTlEmSSKYCO9P2t7z0BwaiDpuT+5jWQRQNtqPcfX1u7WkkUSFutr7ZhpnUQRbEj2/D76jSU4jgDaVut5vrZ2X7rwr/EmaantHVbilNrGOWo7xnsmUQQbqPmEXprxAKNvgVallH53SunjKaV/m1J6LqX01w+v/1hK6bdSSp88fHzX4Gd+NKX0fErpsyml7xy8/u0ppU8fvvZTSbROg5ae46dmW8VH4zlnpiYnriVhVOqxMz6ua+rTKbUnu3rx2N4NgNYtPZEzjw4wAkOgUV+JiD+dc/7tlNKrIuLfpJQ+fPjaT+ac/9bwm1NKb4iIpyPijRHxLRHxL1NKfyTn/LWIeFdEPBMRvxwRH4qIpyLiwwGNqPnCc41JrMfVPlvOWTT+W1u2ZQk1xJXDZFHpbaVOKopgA72fwNe4c6CyCGhdfvDbh/++6vBx7mT3toh4X875Kznnz0XE8xHxlpTS4xHx9Tnnj+aHk+XPRcR3r9l22EON8dbS8cv4951alnwNl/p/y7bcqrRj6Fw/mfOHNUkUAdUaz/dkoARak1J6ZUrpkxHxpYj4SM75Y4cv/VBK6VMppZ9NKX3D4bUnIuI3Bz/+wuG1Jw6fj18f/61nUkrPppSeXXxDYEW1jv9rVdhMVfSUkgAZtqXkhFFJzu07ySLWIlEEK3LS3oZkEdCqnPPXcs5PRsRr4qE66E3x8BjZt0bEkxHxYkT8xOHbp64m8pnXx3/r3TnnN+ec37xI42FDpSRCrrXWI2fnvmdtc/5G6Qmj0tpzTm1zQVEHiSJYWa2BS23GySKDJdCSnPN/jYh/FRFP5Zy/eEgg/U5E/ExEvOXwbS9ExGsHP/aaiPjC4fXXTLwO7GTtR86mbBGTXvs3SlwRuNYqnZL6cI7a+rc3FxNFVtyA2zj5veTYF3s/Gw9Qk5TSN6WUfv/h81dHxJ+NiH93mHPo6Hsi4tcOn38gIp5OKX1dSul1EfH6iPh4zvnFiPhySumth9jr7RHxC5ttCDBp7UfOuF0pfXlL4q0GtbSzZ3NWPbPiBlypllUdtjDsiy1WZ7DkJtCQxyPivSmlV8bDzb3355w/mFL6BymlJ+Ph8bHPR8QPRETknJ9LKb0/In49Ir4aEe84xF8RET8YEe+JiFfHQ+wl/oLK3RrvrB2nHmOxFuLgVrYDrnUxUXRYHeOmFTci4nMppeOKG5+Pw4obEREppeOKGwIVmiJJ9KhjX4yfn14zQIlQ1QXULef8qYj4tonXv+/Mz7wzIt458fqzEfGmRRsI7ObWWEqMNJ+bj+tyrVS2WXMUbbniBrTAie/B1F2YLZ9Dtx8AgNYsccNt7SSIGAzqNitRtOWKGxGWZ4VWlLDyBgBASe6Nf5a66aZiZh59RI+uWvVsqxU3LM8K7VP6DAD0qqSKG7HYaaWtyAZbmbPqmRU3AACA4khy3EcSBJgyZ9UzK27ATIKV62y1EhoA0C4xBMCyUukXtimlshsII5Ie17NSHJBzdgIoiPiLGtQYc5Xa5uE1YYntA1bziakpf66aowhgDQISAID9mIsHGJIoAopg5Q0A4Fpih+XoS+BIoggWZIC9j2QRADBXbRUwYhygFhJFsLDaghYAgJrVlIApOU48tq2m/gTWIVEEFEeAAgDMUXLipUb6E4iQKILFSG4sY3g3S58CAC0odbUzgCkSRbAgAcAy9CMAcA03l+43vEmnP6FvEkVAkTwnDwCcc0xslH6DqaZYJqUkBgMkimAppQcptdKvAMDYMYlRS5xQejvHSaHS2wusS6IIFuTOy/L0KQAwRTJjGbUl3YD1SRTBggywy9KfAMBYbTeRSo5nJImAKRJFQPFqCwgBgHVIbCxPXwJjEkUAAEA1JDa242Yd9EmiCCjWcSWTlNLLlmwFABgTJyxLQg76JVEEFGscoAhYAIApYoTrzU2sScBBfySKAACA4l1KWEgWXU+fAVMkioCinHvEzB0tAOibxAbA+iSKgGKcW8lEYAgAsIzjPJDXfD/QD4kioCgSQgAA67k26TNcWATow2N7NwDgGtfeAQMA6NG5xM4tsdQwWSQWg7ZJFAHVcDcLAPpk/J9vzWTO8Xe6cQdt8+gZUAQBBwDAMpaMqaaSdMebdxJ40CaJIgAAgAYsfeNtWEE0TgqNvyZxBO3w6BkAAFA8lcenbfW42amvDduhShzqp6II2J2AAgA4RZXKeVtOMH1pXxxXSAPqpqII2MUw0JgbUAgUAaBfbiydtkW/mMga+qGiCNjEMMlzS5IIAOjPMSkhXpi2x000E1lD+1QUAasb33kS7AEAl0zFD6pZXrJnX4znLbJPoC0qioBVLRnEnFt5AwDogxjgJXv3xbmJroF6SRQBq1kjaFB+DgD9EgO8pJS+OMZmkkXQDokiYHHDpVHXCmIEJADQrnNjfE0xwJrtrKUPgPpIFAGr2Gr1DUESALRlzrw3vccAJvkG1iRRBCxq66BNgAQA7WlpfF86Nip1Qu/ek3fQEokiYDFWvgAAljBn4YoaEhNLT/Zc+vZuQR/A+iSKgMWUUgItgACAeg3jiTljeunjfk8rg62dvOuhD6EEEkVAc2q4wwgAnDcnwVLKTapLlkgWDR856znOqWF/Q+0kigAAgCK1lBQYLiN/baJnmCSqoU/WSGSVOjcTtEiiCFhEaXe2VBUBQDtaGtOHVUG3PlpXcsLknoTYKZJEsC2JImARBm8AYA0txhhz52GqdaGQ4TbdmzCSJILtPbZ3AwDWIqgAgDYcK1RaG9svJYtq3t5h24/Jomu3p8V9DjWQKAIAAKrQauKgpW069ajcrckiYHsePQMAAIonwVCHU1VSl+ZmOr4+/AD2oaIIAACoQquPoLVmmBQa7qtLySL7FcogUQQAAFRDsqgep/aVfQdl8+gZcBPlwAAAAO2RKAJu4k4QAACXHKuKgHpIFAEAALAaySKoi0QRAAAAq5MsgjpIFAEAAFVRoVKf4YpnQNkkigAAgCpJOtRFsgjq8NjeDQAAALiWqqI6HffbqX1nwRTYn0QRAAAAm5lKBh0TR8d/JYxgPxJFAABAtXLOkgoNsA+hHOYoAgAAqiS5ALA8iSIAAKBq5ioCWI5EEQAAUC1VRQDLkigCAAAAICIkigAAAAA4kCgCAAAAICIkigAAgAaY0BpgGRJFAABA1UxoDbAciSIAAKB6kkUAy5AoAgAAACAiJIoAAAAAOJAoAtiBCTcBAIASSRQBrGwqKWQeBQAAoEQSRQALkhQCAABqJlEEsCBJIQAAoGYSRQAXmE8IAADohUQRwAWqhAAAgF5IFAEAAAAQERJFAAAAABxIFAEAAAAQERJFAAAAABxIFAEAAAAQERJFAAAAABxIFAEAAAAQERJFAAAAABxIFAEAAAAQERGP7d2AGX47Ij67dyM69gci4j/t3YjO2Qf7sw/2pf/3t/Y++D9W/N0AAFyhhkTRZ3POb967Eb1KKT2r//dlH+zPPtiX/t+ffQAA0I8aEkUAAGzrP0XEfw/VfHtSTbkv/b8v/b8v/b+vLft/sqpboggAgJfJOX+TSrJ96f996f996f996f99ldD/NUxm/e69G9A5/b8/+2B/9sG+9P/+7AMAgE4UnyjKOQtOd6T/92cf7M8+2Jf+3599AADQj+ITRQAA7EKCcF/6f1/6f1/6f1/6f1+793+xiaKU0lMppc+mlJ5PKf3I3u1pWUrp8ymlT6eUPplSevbw2jemlD6SUvqNw7/fMPj+Hz3sl8+mlL5zv5bXKaX0symlL6WUfm3w2tX9nVL69sN+ez6l9FMppbT1ttTqxD74sZTSbx3eB59MKX3X4Gv2wYJSSq9NKf1SSukzKaXnUkp/+fC698FGzuwD7wP+N5Vk+9L/+9L/+9L/+9L/+yqh/4tMFKWUXhkRfzci/nxEvCEivjel9IZ9W9W8P5VzfnIwadaPRMQv5pxfHxG/ePh/HPbD0xHxxoh4KiJ++rC/mO898dB3Q7f097si4pmIeP3hY/w7Oe09Md1fP3l4HzyZc/5QhH2wkq9GxF/NOf/RiHhrRLzj0M/eB9s5tQ8ivA8AALpWZKIoIt4SEc/nnP9Dzvl/RMT7IuJtO7epN2+LiPcePn9vRHz34PX35Zy/knP+XEQ8Hw/7i5lyzv86Iv7L6OWr+jul9HhEfH3O+aM55xwRPzf4GS44sQ9OsQ8WlnN+Mef8q4fPvxwRn4mIJ8L7YDNn9sEp9kFHVHVvQ0X3tlR070s1975Uc++rxkruUhNFT0TEbw7+/0KcD2C5T46If5FS+kRK6ZnDa9+cc34x4uGCIiL+4OF1+2Yd1/b3E4fPx69znx9KKX3qEMwcB0r7YEUppT8UEd8WER8L74NdjPZBhPdB11R1b05F93beEyq69/SeUM29J9Xc+6qukrvURNFUVixv3op+fEfO+f+Mh6DwHSmlP3Hme+2bbZ3qb/thee+KiG+NiCcj4sWI+InD6/bBSlJKvzci/klE/HDO+b+d+9aJ1+yDBUzsA+8DVHXvS0X3SlR070s1975Uc++rxkruUhNFL0TEawf/f01EfGGntjQv5/yFw79fioifj4fA44uHAzEO/37p8O32zTqu7e8XDp+PX+dGOecv5py/lnP+nYj4mXgpALcPVpBSelU8JCj+Yc75nx5e9j7Y0NQ+8D4gVA5vSUX3/lSy7k8V68ZUc++rlkruUhNFvxIRr08pvS6l9LvioezqAzu3qUkppd+TUvp9x88j4v+KiF+Lh/7+/sO3fX9E/MLh8w9ExNMppa9LKb0uHsrdPr5tq5t0VX8fTuRfTim99fBc6tsHP8MNjgmKg++Jh/dBhH2wuEN//f2I+EzO+W8PvuR9sJFT+8D7gFAltiUV3eVSRbkNVawbU829r5oquR9b45feK+f81ZTSD0XEP4+IV0bEz+acn9u5Wa365oj4+cMcWI9FxD/KOf+zlNKvRMT7U0p/KSL+Y0T8hYiInPNzKaX3R8Svx8Ozlu/IOX9tn6bXKaX0jyPiT0bEH0gpvRAR/29E/Hhc398/GA/Pe786Ij58+GCGE/vgT6aUnoyHk+3nI+IHIuyDlXxHRHxfRHw6pfTJw2t/LbwPtnRqH3yv90H3VA5vZFjRnVJ6WUV3zvlFFd2buLa/VVEuKOf8xePnKaWfiYgPHv6r/1dwrprbe2B9pyq5B18v6j2QHh5tAwCgdymlxyLi/4uIPxMRvxUPVd5/0Q27ZR2quF+Rc/7y4fOPRMTfiId+/8855x9PDyvOfWPO+f9JKb0xIv5RPCSTviUeJp19vZt11zk88vHBnPObDv//m3Flfx9upv7f8fDYyIci4u8cJ6DlvIn+f/z42FNK6a9ExB/POT+t/5d3qPp9b0T8l5zzDw9e9x7YwJn+L/Y9UGRFEQAA21PVvRkV3RtT0b0v1dy7U829r+oquVUUAQAAABAR5U5mDQAAAMDGJIoAAAAAiAiJIgAAAAAOJIoAAAAAiAiJIgAAAAAOJIoAAAAAiAiJIgAAAAAOJIoAAAAAiIiI/wVcyrjL4QXXoAAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Generate prediction map\n", "from osgeo import gdal \n", "import numpy as np\n", "import copy\n", "import matplotlib.pyplot as plt\n", "\n", "fig= plt.figure(figsize=(20,15))\n", "\n", "# Plot the map\n", "prediction_map = prediction_map*mask\n", "plt.subplot(1,2, 1)\n", "plt.title('result',fontsize = 16)\n", "plt.imshow(prediction_map*255,cmap='gray',vmin=0, vmax=1)\n", "\n", "reference = np.load(root+'data/reference.npy')\n", "plt.subplot(1,2,2)\n", "plt.title('Reference map',fontsize = 16)\n", "plt.imshow(reference*255,cmap='gray',vmin=0, vmax=255)\n", "plt.show()\n" ] } ], "metadata": { "colab": { "collapsed_sections": [], "name": "2.3_Code_Interpret_the_Result .ipynb", "provenance": [] }, "kernelspec": { "display_name": "Python 3", "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": "3.7.6" } }, "nbformat": 4, "nbformat_minor": 4 }