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en_cons_anomalies/Swisscom_withLabels_Training.ipynb
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Swisscom_withLabels_Training.ipynb
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			{
			"cells": [
			{
			"cell_type": "code",
			"execution_count": 1,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": [
			"import numpy as np\n",
			"import pandas as pd\n",
			"import seaborn as sns\n",
			"\n",
			"import matplotlib.pyplot as plt"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"## Let's learn some models from the images previously created "
			]
			},
			{
			"cell_type": "code",
			"execution_count": 2,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": [
			"import os\n",
			"from PIL import Image\n",
			"from sklearn.model_selection import train_test_split"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 3,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": [
			"%matplotlib inline\n",
			"sns.set(style=\"ticks\", font_scale=1, context=\"talk\")\n",
			"sns.set_style(\"white\", {'axes.grid' : False})\n",
			"plt.rcParams['figure.figsize'] = (27, 6)"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Import images from the files where we previously saved them in."
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"We import only Good images, and Bad images, in a form of a 3 channels array. It is originally in RGBA format, so 4 channels, but the last channel (opacity) is useless, as it is always 255. So we shall simply discard it. "
			]
			},
			{
			"cell_type": "code",
			"execution_count": 4,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": [
			"good_path,bad_path = 'Swisscom_LABELED_images_GOOD/','Swisscom_LABELED_images_BAD/'\n",
			"\n",
			"Good_images,Bad_images = [],[]\n",
			"# r=root, d=directories, f = files\n",
			"for r, d, f in os.walk(good_path):\n",
			" for file in f:\n",
			" # extract all images files\n",
			" if '.png' in file: \n",
			" station_name = file.split(\"_\")[1]\n",
			" year = file.split(\"_\")[2]\n",
			" month = file.split(\"_\")[3].split(\".\")[0] \n",
			" file_name = os.path.join(r, file)\n",
			" # import the image from the file name and convert in array\n",
			" I = np.asarray(Image.open(file_name))\n",
			" # we exclude the last 4th channel in the image\n",
			" Good_images.append((station_name,year,month,I[:,:,:-1]))\n",
			" \n",
			"for r, d, f in os.walk(bad_path):\n",
			" for file in f:\n",
			" # extract all images files\n",
			" if '.png' in file: \n",
			" station_name = file.split(\"_\")[1]\n",
			" year = file.split(\"_\")[2]\n",
			" month = file.split(\"_\")[3].split(\".\")[0] \n",
			" file_name = os.path.join(r, file)\n",
			" # import the image from the file name and convert in array\n",
			" I = np.asarray(Image.open(file_name))\n",
			" # we exclude the last 4th channel in the image\n",
			" Bad_images.append((station_name,year,month,I[:,:,:-1]))"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Put images in nice format for the CNN later, with 1 to label good images, 0 to label bad images. "
			]
			},
			{
			"cell_type": "code",
			"execution_count": 5,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"text/plain": [
			"(2590, 1545)"
			]
			},
			"execution_count": 5,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"len(Good_images), len(Bad_images)"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 6,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": [
			"# put images in good format\n",
			"good_images_format = np.array([Good_images[el][-1] for el in range(len(Good_images))])\n",
			"bad_images_format = np.array([Bad_images[el][-1] for el in range(len(Bad_images))])\n",
			"# put them together, with labels\n",
			"images = np.vstack([good_images_format,bad_images_format])\n",
			"labels = np.hstack([np.ones(len(good_images_format)),np.zeros(len(bad_images_format))])\n",
			"\n",
			"# Normalize pixel values to be between 0 and 1\n",
			"images = images / 255.0"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Try to plot an example image, with RGB components. "
			]
			},
			{
			"cell_type": "code",
			"execution_count": 17,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": [
			"#im = Good_images[311][-1]\n",
			"\n",
			"#fig = plt.figure()\n",
			"#plt.subplot(1,4,1)\n",
			"#plt.imshow(im)\n",
			"#plt.title(\"image\")\n",
			"#plt.subplot(1,4,2)\n",
			"#plt.imshow(np.array(im)[:,:,0])\n",
			"#plt.title(\"R\")\n",
			"#plt.subplot(1,4,3)\n",
			"#plt.imshow(np.array(im)[:,:,1]) \n",
			"#plt.title(\"G\")\n",
			"#plt.subplot(1,4,4)\n",
			"#plt.imshow(np.array(im)[:,:,2])\n",
			"#plt.title(\"B\")\n",
			"#plt.show() \n",
			"#plt.close(fig)"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Plot multiple images"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 21,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"image/png": 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\n",
			"text/plain": [
			"<Figure size 1440x360 with 16 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"class_names = ['bad', 'good']\n",
			"\n",
			"seed = 12\n",
			"# keep 25% for testing\n",
			"test_size = 0.25\n",
			"train_images, test_images, train_labels, test_labels = train_test_split(images, labels, test_size=test_size, random_state=seed)\n",
			" \n",
			"fig=plt.figure(figsize=(20,5))\n",
			"for i in range(16):\n",
			" plt.subplot(2,8,i+1)\n",
			" plt.xticks([])\n",
			" plt.yticks([])\n",
			" plt.grid(False)\n",
			" plt.imshow(train_images[i], cmap=plt.cm.binary)\n",
			" plt.xlabel(class_names[int(train_labels[i])])\n",
			"plt.show()\n",
			"fig.savefig(\"SwisscomImages_exLabels.png\",dpi=300,bbox_inches=\"tight\")"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"## Let's go with CNNs\n",
			"\n",
			"Original resolution is 24 x 28 x 3. We want something dividible by 2^x, with x layers of pooling. So lets say 3 layers; we want to pad left and right to have 32 x 32 x 3, like classic CIFAR images...!\n",
			"\n",
			"For this: use zeroPaddingConv2D\n",
			"\n",
			"When doing CNN, I can pad like I want!"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 22,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": [
			"from tensorflow.keras import layers, models, preprocessing\n",
			"from sklearn.metrics import roc_curve, auc\n",
			"from sklearn.metrics import confusion_matrix\n",
			"from sklearn.metrics import accuracy_score, precision_score, recall_score\n",
			"\n",
			"plt.rcParams['figure.figsize'] = (15, 8)"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"PROBLEM DU LOL faisant crasheer le kernel quand je lance le training: \n",
			"\n",
			"- OMP: Hint: This means that multiple copies of the OpenMP runtime have been linked into the program. That is dangerous, since it can degrade performance or cause incorrect results. The best thing to do is to ensure that only a single OpenMP runtime is linked into the process, e.g. by avoiding static linking of the OpenMP runtime in any library. As an unsafe, unsupported, undocumented workaround you can set the environment variable KMP_DUPLICATE_LIB_OK=TRUE to allow the program to continue to execute, but that may cause crashes or silently produce incorrect results."
			]
			},
			{
			"cell_type": "code",
			"execution_count": 23,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": [
			"\n",
			"# to fix it then...\n",
			"import os\n",
			"os.environ['KMP_DUPLICATE_LIB_OK']='True'"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Try a first CNN model"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Let's first build a function that Compiles and Trains the model, showing the accuracy and recall and specificity and ROC curve."
			]
			},
			{
			"cell_type": "code",
			"execution_count": 24,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": [
			"def CompileAndTrainCNNModel(model,images, labels,epochs,version=\"CNN model\"):\n",
			"\n",
			" # nous utilisons la train_test_split fonction de scikit pour séparer la data en training/testing\n",
			" seed = 12\n",
			" # keep 25% for testing\n",
			" test_size = 0.25\n",
			" train_images, test_images, train_labels, test_labels = train_test_split(images, labels, test_size=test_size, random_state=seed)\n",
			"\n",
			" # ------ Compile and Train ---------\n",
			" model.compile(optimizer='adam',\n",
			" loss='sparse_categorical_crossentropy',\n",
			" metrics=['accuracy'])\n",
			"\n",
			" history = model.fit(train_images, train_labels, epochs=epochs, \n",
			" validation_data=(test_images, test_labels))\n",
			" \n",
			" # ------ ROC curve and other metrics. Let's use scikit functions for that. ------\n",
			" # extract test probas \n",
			" test_pred_probs = model.predict(test_images)\n",
			" # extract also test classes for later \n",
			" test_pred_class = np.array([np.argmax(el) for el in test_pred_probs])\n",
			"\n",
			" # extract also training classes to have training metrics \n",
			" train_pred_probs = model.predict(train_images)\n",
			" train_pred_class = np.array([np.argmax(el) for el in train_pred_probs])\n",
			"\n",
			" #confusion matrix\n",
			" confMat = confusion_matrix(test_labels,test_pred_class)\n",
			" \n",
			" # specificity\n",
			" specif = float(confMat[0,0])/float(sum(confMat[0,:]))\n",
			" \n",
			" print(confMat)\n",
			" print ('Train/Test recall: %.4f' % recall_score(train_labels,train_pred_class),\"/ %.4f\" % recall_score(test_labels,test_pred_class) )\n",
			" print ('Train/Test accuracy: %.4f' % accuracy_score(train_labels,train_pred_class),\"/ %.4f\" % accuracy_score(test_labels,test_pred_class) )\n",
			" print ('Test specificity: %.4f' % specif)\n",
			"\n",
			" # false positive rate, true positive rate, thresholds using the probas for class 1 only (teh scikit function works like this)\n",
			" fpr, tpr, thresh = roc_curve(test_labels,test_pred_probs[:,1])\n",
			" # area under the curve\n",
			" roc_auc = auc(fpr, tpr)\n",
			" \n",
			" # plot the actual roc curve\n",
			" plt.subplot(1,3,1)\n",
			" plt.plot(fpr, tpr,label= \"\".join([ version,': AUC=%.2f'% roc_auc]) )\n",
			" plt.plot([0, 1], [0, 1], color='gray', linestyle='--')\n",
			" plt.xlabel(\"False Positive Rate\")\n",
			" plt.ylabel(\"True Positive Rate\")\n",
			" plt.title(\"ROC curves\")\n",
			" plt.legend(loc=\"lower right\")\n",
			" \n",
			" # PLOT the loss function, in train and test, with epochs\n",
			" plt.subplot(1,3,2)\n",
			" plt.plot(range(len(history.history['loss'])), history.history['loss'], label=\"train\")\n",
			" plt.plot(range(len(history.history['val_loss'])), history.history['val_loss'],label=\"test\")\n",
			" plt.xlabel(\"Epochs\")\n",
			" plt.ylabel(\"Loss\")\n",
			" plt.title(\"Loss curves\")\n",
			" plt.legend(loc=\"upper left\")\n",
			"\n",
			" plt.subplot(1,3,3)\n",
			" plt.plot(range(len(history.history['acc'])), history.history['acc'], label=\"train\")\n",
			" plt.plot(range(len(history.history['val_acc'])), history.history['val_acc'],label=\"test\")\n",
			" plt.xlabel(\"Epochs\")\n",
			" plt.ylabel(\"Accuracy\")\n",
			" plt.title(\"Acc curves\")\n",
			" plt.legend(loc=\"upper left\")\n",
			" \n",
			" return (train_pred_class,test_pred_class)\n",
			" "
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"First architecture: classic CONV-POOL-CONV-POOL alternance with increasing number of filters. "
			]
			},
			{
			"cell_type": "code",
			"execution_count": 88,
			"metadata": {},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"_________________________________________________________________\n",
			"Layer (type) Output Shape Param # \n",
			"=================================================================\n",
			"zero_padding2d_21 (ZeroPaddi (None, 32, 32, 3) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_85 (Conv2D) (None, 32, 32, 32) 896 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_44 (MaxPooling (None, 16, 16, 32) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_86 (Conv2D) (None, 16, 16, 64) 18496 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_45 (MaxPooling (None, 8, 8, 64) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_87 (Conv2D) (None, 8, 8, 128) 73856 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_46 (MaxPooling (None, 4, 4, 128) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_88 (Conv2D) (None, 4, 4, 256) 295168 \n",
			"_________________________________________________________________\n",
			"flatten_21 (Flatten) (None, 4096) 0 \n",
			"_________________________________________________________________\n",
			"dense_42 (Dense) (None, 64) 262208 \n",
			"_________________________________________________________________\n",
			"dense_43 (Dense) (None, 2) 130 \n",
			"=================================================================\n",
			"Total params: 650,754\n",
			"Trainable params: 650,754\n",
			"Non-trainable params: 0\n",
			"_________________________________________________________________\n"
			]
			}
			],
			"source": [
			"# initialize a first model\n",
			"model0 = models.Sequential()\n",
			"# need to add an extra zero padding layer, 4 on each width side, 2 on each height side\n",
			"model0.add(layers.ZeroPadding2D(padding=(4, 2), data_format=None,input_shape=(24, 28, 3)))\n",
			"# 1st conv layer, with 32 filters of size (3,3)\n",
			"model0.add(layers.Conv2D(32, (3, 3), activation='relu',padding=\"same\"))\n",
			"# 1st pool layer, divinding by 2 the dimension\n",
			"model0.add(layers.MaxPooling2D((2, 2)))\n",
			"# 2nd conv layer, with 64 filters of size (3,3) \n",
			"model0.add(layers.Conv2D(64, (3, 3), activation='relu',padding=\"same\"))\n",
			"# 2nd pool layer, divinding by 2 the dimension\n",
			"model0.add(layers.MaxPooling2D((2, 2)))\n",
			"# 3rd conv layer, with 64 filters of size (3,3) \n",
			"model0.add(layers.Conv2D(128, (3, 3), activation='relu',padding=\"same\"))\n",
			"# 3rd pool layer, divinding by 2 the dimension\n",
			"model0.add(layers.MaxPooling2D((2, 2)))\n",
			"# last conv layer, divinding by 2 the dimension\n",
			"model0.add(layers.Conv2D(256, (3, 3), activation='relu',padding=\"same\"))\n",
			"\n",
			"# flaten the images to prepare for the dense layers\n",
			"model0.add(layers.Flatten())\n",
			"model0.add(layers.Dense(64, activation='relu'))\n",
			"# finl dense softmax layer, with 2 classes so 2 dimension, to have probabilities at the end\n",
			"model0.add(layers.Dense(2, activation='softmax'))\n",
			"\n",
			"# model architecture\n",
			"model0.summary()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 89,
			"metadata": {},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"Train on 3101 samples, validate on 1034 samples\n",
			"Epoch 1/20\n",
			"3101/3101 [==============================] - 12s 4ms/sample - loss: 0.6676 - acc: 0.6134 - val_loss: 0.6531 - val_acc: 0.6354\n",
			"Epoch 2/20\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6436 - acc: 0.6256 - val_loss: 0.6279 - val_acc: 0.6306\n",
			"Epoch 3/20\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6360 - acc: 0.6272 - val_loss: 0.6246 - val_acc: 0.6451\n",
			"Epoch 4/20\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6263 - acc: 0.6398 - val_loss: 0.6223 - val_acc: 0.6441\n",
			"Epoch 5/20\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6194 - acc: 0.6453 - val_loss: 0.6294 - val_acc: 0.6383\n",
			"Epoch 6/20\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.6153 - acc: 0.6533 - val_loss: 0.6279 - val_acc: 0.6364\n",
			"Epoch 7/20\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.6094 - acc: 0.6540 - val_loss: 0.6244 - val_acc: 0.6354\n",
			"Epoch 8/20\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5896 - acc: 0.6637 - val_loss: 0.6440 - val_acc: 0.6209\n",
			"Epoch 9/20\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5835 - acc: 0.6743 - val_loss: 0.6237 - val_acc: 0.6480\n",
			"Epoch 10/20\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5606 - acc: 0.6933 - val_loss: 0.6484 - val_acc: 0.6393\n",
			"Epoch 11/20\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.5479 - acc: 0.7043 - val_loss: 0.6262 - val_acc: 0.6257\n",
			"Epoch 12/20\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.5212 - acc: 0.7156 - val_loss: 0.6531 - val_acc: 0.6373\n",
			"Epoch 13/20\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.4870 - acc: 0.7407 - val_loss: 0.7089 - val_acc: 0.6267\n",
			"Epoch 14/20\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.4487 - acc: 0.7578 - val_loss: 0.7270 - val_acc: 0.6344\n",
			"Epoch 15/20\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.4163 - acc: 0.7820 - val_loss: 0.7585 - val_acc: 0.6248\n",
			"Epoch 16/20\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.3729 - acc: 0.8062 - val_loss: 0.8675 - val_acc: 0.6083\n",
			"Epoch 17/20\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.3525 - acc: 0.8191 - val_loss: 0.9408 - val_acc: 0.6325\n",
			"Epoch 18/20\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.3124 - acc: 0.8359 - val_loss: 0.9961 - val_acc: 0.6383\n",
			"Epoch 19/20\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.3004 - acc: 0.8442 - val_loss: 1.0511 - val_acc: 0.6605\n",
			"Epoch 20/20\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.2595 - acc: 0.8617 - val_loss: 1.0686 - val_acc: 0.6180\n",
			"[[147 234]\n",
			" [161 492]]\n",
			"Train/Test recall: 0.9814 / 0.7534\n",
			"Train/Test accuracy: 0.8559 / 0.6180\n",
			"Test specificity: 0.3858\n"
			]
			},
			{
			"data": {
			"image/png": 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\n",
			"text/plain": [
			"<Figure size 1944x432 with 3 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"train_pred_class0,test_pred_class0 = CompileAndTrainCNNModel(model0,images, labels,20,\"0th CNN model\")"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"##### We see that:\n",
			"- we detect TP quite well but TN very badly! (recall is good but specificity is horrible). That is also due to the unbalanced classes issue. \n",
			"- And there is clear overfitting. There are probably too many epochs: the test loss quickly starts to go up. We should technicaly stop to train when it goes up! Stop at the valley where test and train loss start to diverge (like the old school bias-variance train/test accuracy plot)"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Note also: if we train the same model again, it starts from the previous training...! That's why it starts from a better accuracy. "
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"See the classes predicted by the model..."
			]
			},
			{
			"cell_type": "code",
			"execution_count": 73,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"image/png": 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\n",
			"text/plain": [
			"<Figure size 1440x864 with 36 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"seed = 12\n",
			" # keep 25% for testing\n",
			"test_size = 0.25\n",
			"train_images, test_images, train_labels, test_labels = train_test_split(images, labels, test_size=test_size, random_state=seed)\n",
			"\n",
			"class_names = [\"bad\",\"good\"]\n",
			"for i in range(36):\n",
			" plt.subplot(4,9,i+1)\n",
			" plt.xticks([])\n",
			" plt.yticks([])\n",
			" plt.grid(False)\n",
			" plt.imshow(test_images[i], cmap=plt.cm.binary)\n",
			" plt.xlabel((class_names[int(test_labels[i])],test_pred_class0[i] ))\n",
			"plt.show()"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"### Try other architectures...!"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"- model 1 was: CONV --> POOL --> CONV --> POOL --> CONV --> FC --> FC\n",
			"- model 2 will be VGGnet like: CONV --> CONV --> POOL --> CONV --> CONV --> POOL --> FC --> FC"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Stack two conv layers before the pooling layer. But be careful: every CONV layer reduces the dimension by 2 and every pool divides it by 2! So we cannot just add any layer...!"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 86,
			"metadata": {},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"_________________________________________________________________\n",
			"Layer (type) Output Shape Param # \n",
			"=================================================================\n",
			"zero_padding2d_20 (ZeroPaddi (None, 32, 32, 3) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_79 (Conv2D) (None, 32, 32, 32) 896 \n",
			"_________________________________________________________________\n",
			"conv2d_80 (Conv2D) (None, 32, 32, 32) 9248 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_42 (MaxPooling (None, 16, 16, 32) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_81 (Conv2D) (None, 16, 16, 64) 18496 \n",
			"_________________________________________________________________\n",
			"conv2d_82 (Conv2D) (None, 16, 16, 64) 36928 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_43 (MaxPooling (None, 8, 8, 64) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_83 (Conv2D) (None, 8, 8, 128) 73856 \n",
			"_________________________________________________________________\n",
			"conv2d_84 (Conv2D) (None, 8, 8, 128) 147584 \n",
			"_________________________________________________________________\n",
			"flatten_20 (Flatten) (None, 8192) 0 \n",
			"_________________________________________________________________\n",
			"dense_40 (Dense) (None, 64) 524352 \n",
			"_________________________________________________________________\n",
			"dense_41 (Dense) (None, 2) 130 \n",
			"=================================================================\n",
			"Total params: 811,490\n",
			"Trainable params: 811,490\n",
			"Non-trainable params: 0\n",
			"_________________________________________________________________\n"
			]
			}
			],
			"source": [
			"model2 = models.Sequential()\n",
			"# need to add an extra zero padding layer, 4 on each width side, 2 on each height side\n",
			"model2.add(layers.ZeroPadding2D(padding=(4, 2), data_format=None,input_shape=(24, 28, 3)))\n",
			"# 2 conv layerw, with 32 filters of size (3,3) \n",
			"model2.add(layers.Conv2D(32, (3, 3), activation='relu',padding=\"same\"))\n",
			"model2.add(layers.Conv2D(32, (3, 3), activation='relu',padding=\"same\"))\n",
			"# 1st pool layer, divinding by 2 the dimension\n",
			"model2.add(layers.MaxPooling2D((2, 2)))\n",
			"# 2 conv layers, with 64 filters of size (3,3) \n",
			"model2.add(layers.Conv2D(64, (3, 3), activation='relu',padding=\"same\"))\n",
			"model2.add(layers.Conv2D(64, (3, 3), activation='relu',padding=\"same\"))\n",
			"# 2nd pool layer, divinding by 2 the dimension\n",
			"model2.add(layers.MaxPooling2D((2, 2)))\n",
			"model2.add(layers.Conv2D(128, (3, 3), activation='relu',padding=\"same\"))\n",
			"model2.add(layers.Conv2D(128, (3, 3), activation='relu',padding=\"same\"))\n",
			"\n",
			"\n",
			"# flaten the images to prepare for the dense layers\n",
			"model2.add(layers.Flatten())\n",
			"model2.add(layers.Dense(64, activation='relu'))\n",
			"# final dense softmax layer, with 2 classes so 2 dimension, to have probabilities at the end\n",
			"model2.add(layers.Dense(2, activation='softmax'))\n",
			"\n",
			"# model architecture\n",
			"model2.summary()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 87,
			"metadata": {
			"scrolled": false
			},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"Train on 3101 samples, validate on 1034 samples\n",
			"Epoch 1/20\n",
			"3101/3101 [==============================] - 18s 6ms/sample - loss: 0.6659 - acc: 0.6201 - val_loss: 0.6516 - val_acc: 0.6315\n",
			"Epoch 2/20\n",
			"3101/3101 [==============================] - 18s 6ms/sample - loss: 0.6496 - acc: 0.6282 - val_loss: 0.6341 - val_acc: 0.6364\n",
			"Epoch 3/20\n",
			"3101/3101 [==============================] - 18s 6ms/sample - loss: 0.6451 - acc: 0.6275 - val_loss: 0.6282 - val_acc: 0.6315\n",
			"Epoch 4/20\n",
			"3101/3101 [==============================] - 18s 6ms/sample - loss: 0.6364 - acc: 0.6301 - val_loss: 0.6269 - val_acc: 0.6354\n",
			"Epoch 5/20\n",
			"3101/3101 [==============================] - 18s 6ms/sample - loss: 0.6307 - acc: 0.6340 - val_loss: 0.6301 - val_acc: 0.6248\n",
			"Epoch 6/20\n",
			"3101/3101 [==============================] - 18s 6ms/sample - loss: 0.6272 - acc: 0.6314 - val_loss: 0.6254 - val_acc: 0.6393\n",
			"Epoch 7/20\n",
			"3101/3101 [==============================] - 17s 6ms/sample - loss: 0.6195 - acc: 0.6424 - val_loss: 0.6257 - val_acc: 0.6538\n",
			"Epoch 8/20\n",
			"3101/3101 [==============================] - 17s 6ms/sample - loss: 0.6129 - acc: 0.6504 - val_loss: 0.6208 - val_acc: 0.6460\n",
			"Epoch 9/20\n",
			"3101/3101 [==============================] - 17s 6ms/sample - loss: 0.6117 - acc: 0.6411 - val_loss: 0.6382 - val_acc: 0.6364\n",
			"Epoch 10/20\n",
			"3101/3101 [==============================] - 17s 6ms/sample - loss: 0.6052 - acc: 0.6459 - val_loss: 0.6216 - val_acc: 0.6518\n",
			"Epoch 11/20\n",
			"3101/3101 [==============================] - 17s 6ms/sample - loss: 0.5982 - acc: 0.6617 - val_loss: 0.6211 - val_acc: 0.6509\n",
			"Epoch 12/20\n",
			"3101/3101 [==============================] - 17s 6ms/sample - loss: 0.5951 - acc: 0.6617 - val_loss: 0.6322 - val_acc: 0.6538\n",
			"Epoch 13/20\n",
			"3101/3101 [==============================] - 17s 6ms/sample - loss: 0.5859 - acc: 0.6691 - val_loss: 0.6213 - val_acc: 0.6509\n",
			"Epoch 14/20\n",
			"3101/3101 [==============================] - 17s 6ms/sample - loss: 0.5732 - acc: 0.6714 - val_loss: 0.6239 - val_acc: 0.6451\n",
			"Epoch 15/20\n",
			"3101/3101 [==============================] - 17s 6ms/sample - loss: 0.5619 - acc: 0.6791 - val_loss: 0.6348 - val_acc: 0.6383\n",
			"Epoch 16/20\n",
			"3101/3101 [==============================] - 17s 6ms/sample - loss: 0.5471 - acc: 0.6914 - val_loss: 0.6415 - val_acc: 0.6373\n",
			"Epoch 17/20\n",
			"3101/3101 [==============================] - 17s 6ms/sample - loss: 0.5343 - acc: 0.6998 - val_loss: 0.6483 - val_acc: 0.6248\n",
			"Epoch 18/20\n",
			"3101/3101 [==============================] - 17s 6ms/sample - loss: 0.5262 - acc: 0.7049 - val_loss: 0.6553 - val_acc: 0.6267\n",
			"Epoch 19/20\n",
			"3101/3101 [==============================] - 17s 6ms/sample - loss: 0.5080 - acc: 0.7104 - val_loss: 0.6818 - val_acc: 0.6402\n",
			"Epoch 20/20\n",
			"3101/3101 [==============================] - 17s 6ms/sample - loss: 0.4742 - acc: 0.7359 - val_loss: 0.7481 - val_acc: 0.6074\n",
			"[[170 211]\n",
			" [195 458]]\n",
			"Train/Test recall: 0.8307 / 0.7014\n",
			"Train/Test accuracy: 0.7717 / 0.6074\n",
			"Test specificity: 0.4462\n"
			]
			},
			{
			"data": {
			"image/png": 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\n",
			"text/plain": [
			"<Figure size 1944x432 with 3 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"train_pred_class2,test_pred_class2 = CompileAndTrainCNNModel(model2,images, labels,20,\"VGG like model\")"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"##### Theres a bit less overfitting but still a lot of work to do. "
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"### Let's try to tackle the unbalanced problem. \n",
			"\n",
			"1) Undersampling the majority class: we take as many good images as there are bad ones.\n",
			"2) Oversampling\n",
			"3) Use another loss function to adapt to the unbalanced effects?"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 11,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": [
			"# put images in good format\n",
			"good_images_format_under = np.array([Good_images[el][-1] for el in range(len(Bad_images))])\n",
			"bad_images_format = np.array([Bad_images[el][-1] for el in range(len(Bad_images))])\n",
			"# put them together, with labels\n",
			"images_under = np.vstack([good_images_format_under,bad_images_format])\n",
			"labels_under = np.hstack([np.ones(len(good_images_format_under)),np.zeros(len(bad_images_format))])\n",
			"\n",
			"# Normalize pixel values to be between 0 and 1\n",
			"images_under = images_under / 255.0"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Same as model 1, but with undersampled data."
			]
			},
			{
			"cell_type": "code",
			"execution_count": 91,
			"metadata": {
			"scrolled": false
			},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"_________________________________________________________________\n",
			"Layer (type) Output Shape Param # \n",
			"=================================================================\n",
			"zero_padding2d_22 (ZeroPaddi (None, 32, 32, 3) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_89 (Conv2D) (None, 32, 32, 32) 896 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_47 (MaxPooling (None, 16, 16, 32) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_90 (Conv2D) (None, 16, 16, 64) 18496 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_48 (MaxPooling (None, 8, 8, 64) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_91 (Conv2D) (None, 8, 8, 64) 36928 \n",
			"_________________________________________________________________\n",
			"flatten_22 (Flatten) (None, 4096) 0 \n",
			"_________________________________________________________________\n",
			"dense_44 (Dense) (None, 64) 262208 \n",
			"_________________________________________________________________\n",
			"dense_45 (Dense) (None, 2) 130 \n",
			"=================================================================\n",
			"Total params: 318,658\n",
			"Trainable params: 318,658\n",
			"Non-trainable params: 0\n",
			"_________________________________________________________________\n",
			"Train on 2317 samples, validate on 773 samples\n",
			"Epoch 1/20\n",
			"2317/2317 [==============================] - 6s 3ms/sample - loss: 0.6948 - acc: 0.5093 - val_loss: 0.6828 - val_acc: 0.5576\n",
			"Epoch 2/20\n",
			"2317/2317 [==============================] - 4s 2ms/sample - loss: 0.6790 - acc: 0.5585 - val_loss: 0.6755 - val_acc: 0.5563\n",
			"Epoch 3/20\n",
			"2317/2317 [==============================] - 5s 2ms/sample - loss: 0.6677 - acc: 0.5978 - val_loss: 0.6641 - val_acc: 0.5873\n",
			"Epoch 4/20\n",
			"2317/2317 [==============================] - 5s 2ms/sample - loss: 0.6642 - acc: 0.5939 - val_loss: 0.6635 - val_acc: 0.5770\n",
			"Epoch 5/20\n",
			"2317/2317 [==============================] - 5s 2ms/sample - loss: 0.6497 - acc: 0.6254 - val_loss: 0.6629 - val_acc: 0.5873\n",
			"Epoch 6/20\n",
			"2317/2317 [==============================] - 5s 2ms/sample - loss: 0.6447 - acc: 0.6275 - val_loss: 0.6586 - val_acc: 0.5977\n",
			"Epoch 7/20\n",
			"2317/2317 [==============================] - 5s 2ms/sample - loss: 0.6345 - acc: 0.6405 - val_loss: 0.6553 - val_acc: 0.6093\n",
			"Epoch 8/20\n",
			"2317/2317 [==============================] - 5s 2ms/sample - loss: 0.6217 - acc: 0.6513 - val_loss: 0.6790 - val_acc: 0.5343\n",
			"Epoch 9/20\n",
			"2317/2317 [==============================] - 5s 2ms/sample - loss: 0.6164 - acc: 0.6603 - val_loss: 0.6672 - val_acc: 0.5873\n",
			"Epoch 10/20\n",
			"2317/2317 [==============================] - 5s 2ms/sample - loss: 0.5983 - acc: 0.6698 - val_loss: 0.6848 - val_acc: 0.5731\n",
			"Epoch 11/20\n",
			"2317/2317 [==============================] - 6s 2ms/sample - loss: 0.5693 - acc: 0.6828 - val_loss: 0.6748 - val_acc: 0.6119\n",
			"Epoch 12/20\n",
			"2317/2317 [==============================] - 6s 3ms/sample - loss: 0.5563 - acc: 0.7013 - val_loss: 0.6546 - val_acc: 0.5951\n",
			"Epoch 13/20\n",
			"2317/2317 [==============================] - 5s 2ms/sample - loss: 0.5245 - acc: 0.7199 - val_loss: 0.6623 - val_acc: 0.6171\n",
			"Epoch 14/20\n",
			"2317/2317 [==============================] - 5s 2ms/sample - loss: 0.4888 - acc: 0.7410 - val_loss: 0.7036 - val_acc: 0.6184\n",
			"Epoch 15/20\n",
			"2317/2317 [==============================] - 5s 2ms/sample - loss: 0.4620 - acc: 0.7583 - val_loss: 0.7507 - val_acc: 0.6248\n",
			"Epoch 16/20\n",
			"2317/2317 [==============================] - 5s 2ms/sample - loss: 0.4162 - acc: 0.7820 - val_loss: 0.7683 - val_acc: 0.5977\n",
			"Epoch 17/20\n",
			"2317/2317 [==============================] - 5s 2ms/sample - loss: 0.4046 - acc: 0.7885 - val_loss: 0.7861 - val_acc: 0.6093\n",
			"Epoch 18/20\n",
			"2317/2317 [==============================] - 6s 2ms/sample - loss: 0.3637 - acc: 0.8157 - val_loss: 0.8906 - val_acc: 0.5511\n",
			"Epoch 19/20\n",
			"2317/2317 [==============================] - 5s 2ms/sample - loss: 0.3330 - acc: 0.8321 - val_loss: 0.9647 - val_acc: 0.6003\n",
			"Epoch 20/20\n",
			"2317/2317 [==============================] - 5s 2ms/sample - loss: 0.3061 - acc: 0.8416 - val_loss: 1.0167 - val_acc: 0.6106\n",
			"[[294 104]\n",
			" [197 178]]\n",
			"Train/Test recall: 0.7538 / 0.4747\n",
			"Train/Test accuracy: 0.8485 / 0.6106\n",
			"Test specificity: 0.7387\n"
			]
			},
			{
			"data": {
			"image/png": 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\n",
			"text/plain": [
			"<Figure size 1944x432 with 3 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"# initialize a first model\n",
			"model3 = models.Sequential()\n",
			"# need to add an extra zero padding layer, 4 on each width side, 2 on each height side\n",
			"model3.add(layers.ZeroPadding2D(padding=(4, 2), data_format=None,input_shape=(24, 28, 3)))\n",
			"# 1st conv layer, with 32 filters of size (3,3) \n",
			"model3.add(layers.Conv2D(32, (3, 3), activation='relu', padding=\"same\"))\n",
			"# 1st pool layer, divinding by 2 the dimension\n",
			"model3.add(layers.MaxPooling2D((2, 2)))\n",
			"# 2nd conv layer, with 64 filters of size (3,3) \n",
			"model3.add(layers.Conv2D(64, (3, 3), activation='relu', padding=\"same\"))\n",
			"# 2nd pool layer, divinding by 2 the dimension\n",
			"model3.add(layers.MaxPooling2D((2, 2)))\n",
			"# last conv layer, with 64 filters of size (3,3) \n",
			"model3.add(layers.Conv2D(128, (3, 3), activation='relu', padding=\"same\"))\n",
			"\n",
			"model3.add(layers.MaxPooling2D((2, 2)))\n",
			"# last conv layer, with 64 filters of size (3,3) \n",
			"model3.add(layers.Conv2D(256, (3, 3), activation='relu', padding=\"same\"))\n",
			"\n",
			"\n",
			"# flaten the images to prepare for the dense layers\n",
			"model3.add(layers.Flatten())\n",
			"model3.add(layers.Dense(64, activation='relu'))\n",
			"# final dense softmax layer, with 2 classes so 2 dimension, to have probabilities at the end\n",
			"model3.add(layers.Dense(2, activation='softmax'))\n",
			"\n",
			"# model architecture\n",
			"model3.summary()\n",
			"\n",
			"train_pred_class3_under,test_pred_class3_under = CompileAndTrainCNNModel(model3,images_under, labels_under,20,\"model3_under\")"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"##### IT does improve the specificity. But the accuracy stays pretty much the same. And there is still overfitting."
			]
			},
			{
			"cell_type": "code",
			"execution_count": 92,
			"metadata": {},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"_________________________________________________________________\n",
			"Layer (type) Output Shape Param # \n",
			"=================================================================\n",
			"zero_padding2d_23 (ZeroPaddi (None, 32, 32, 3) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_92 (Conv2D) (None, 32, 32, 32) 896 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_49 (MaxPooling (None, 16, 16, 32) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_93 (Conv2D) (None, 16, 16, 64) 18496 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_50 (MaxPooling (None, 8, 8, 64) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_94 (Conv2D) (None, 8, 8, 128) 73856 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_51 (MaxPooling (None, 4, 4, 128) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_95 (Conv2D) (None, 4, 4, 256) 295168 \n",
			"_________________________________________________________________\n",
			"flatten_23 (Flatten) (None, 4096) 0 \n",
			"_________________________________________________________________\n",
			"dense_46 (Dense) (None, 64) 262208 \n",
			"_________________________________________________________________\n",
			"dense_47 (Dense) (None, 2) 130 \n",
			"=================================================================\n",
			"Total params: 650,754\n",
			"Trainable params: 650,754\n",
			"Non-trainable params: 0\n",
			"_________________________________________________________________\n",
			"Train on 2317 samples, validate on 773 samples\n",
			"Epoch 1/20\n",
			"2317/2317 [==============================] - 9s 4ms/sample - loss: 0.6910 - acc: 0.5244 - val_loss: 0.6908 - val_acc: 0.5149\n",
			"Epoch 2/20\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6927 - acc: 0.5244 - val_loss: 0.6812 - val_acc: 0.5692\n",
			"Epoch 3/20\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6842 - acc: 0.5572 - val_loss: 0.6758 - val_acc: 0.5886\n",
			"Epoch 4/20\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6765 - acc: 0.5844 - val_loss: 0.6771 - val_acc: 0.5602\n",
			"Epoch 5/20\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6681 - acc: 0.5939 - val_loss: 0.7000 - val_acc: 0.5395\n",
			"Epoch 6/20\n",
			"2317/2317 [==============================] - 9s 4ms/sample - loss: 0.6583 - acc: 0.5995 - val_loss: 0.6660 - val_acc: 0.5744\n",
			"Epoch 7/20\n",
			"2317/2317 [==============================] - 9s 4ms/sample - loss: 0.6548 - acc: 0.6249 - val_loss: 0.6639 - val_acc: 0.5770\n",
			"Epoch 8/20\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6496 - acc: 0.6180 - val_loss: 0.6857 - val_acc: 0.5343\n",
			"Epoch 9/20\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6309 - acc: 0.6310 - val_loss: 0.6730 - val_acc: 0.6041\n",
			"Epoch 10/20\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6282 - acc: 0.6405 - val_loss: 0.6531 - val_acc: 0.5951\n",
			"Epoch 11/20\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6058 - acc: 0.6655 - val_loss: 0.6846 - val_acc: 0.5809\n",
			"Epoch 12/20\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.5885 - acc: 0.6595 - val_loss: 0.7106 - val_acc: 0.5964\n",
			"Epoch 13/20\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.5795 - acc: 0.6832 - val_loss: 0.7118 - val_acc: 0.5783\n",
			"Epoch 14/20\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.5373 - acc: 0.7087 - val_loss: 0.7222 - val_acc: 0.5873\n",
			"Epoch 15/20\n",
			"2317/2317 [==============================] - 9s 4ms/sample - loss: 0.5136 - acc: 0.7385 - val_loss: 0.8060 - val_acc: 0.6197\n",
			"Epoch 16/20\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.4907 - acc: 0.7462 - val_loss: 0.7534 - val_acc: 0.6028\n",
			"Epoch 17/20\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.4461 - acc: 0.7756 - val_loss: 0.7425 - val_acc: 0.6184\n",
			"Epoch 18/20\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.4039 - acc: 0.7989 - val_loss: 0.8393 - val_acc: 0.5511\n",
			"Epoch 19/20\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3692 - acc: 0.8140 - val_loss: 0.9225 - val_acc: 0.5990\n",
			"Epoch 20/20\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3272 - acc: 0.8330 - val_loss: 1.0874 - val_acc: 0.6106\n",
			"[[325 73]\n",
			" [228 147]]\n",
			"Train/Test recall: 0.6744 / 0.3920\n",
			"Train/Test accuracy: 0.8256 / 0.6106\n",
			"Test specificity: 0.8166\n"
			]
			},
			{
			"data": {
			"image/png": 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\n",
			"text/plain": [
			"<Figure size 1944x432 with 3 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"# initialize a first model\n",
			"model4 = models.Sequential()\n",
			"# need to add an extra zero padding layer, 4 on each width side, 2 on each height side\n",
			"model4.add(layers.ZeroPadding2D(padding=(4, 2), data_format=None,input_shape=(24, 28, 3)))\n",
			"# 1st conv layer, with 32 filters of size (3,3) \n",
			"model4.add(layers.Conv2D(32, (3, 3), activation='relu', padding=\"same\"))\n",
			"# 1st pool layer, divinding by 2 the dimension\n",
			"model4.add(layers.MaxPooling2D((2, 2)))\n",
			"# 2nd conv layer, with 64 filters of size (3,3) \n",
			"model4.add(layers.Conv2D(64, (3, 3), activation='relu', padding=\"same\"))\n",
			"# 2nd pool layer, divinding by 2 the dimension\n",
			"model4.add(layers.MaxPooling2D((2, 2)))\n",
			"# last conv layer, with 64 filters of size (3,3) \n",
			"model4.add(layers.Conv2D(128, (3, 3), activation='relu', padding=\"same\"))\n",
			"\n",
			"model4.add(layers.MaxPooling2D((2, 2)))\n",
			"# las4 conv layer, with 64 filters of size (3,3) \n",
			"model4.add(layers.Conv2D(256, (3, 3), activation='relu', padding=\"same\"))\n",
			"\n",
			"\n",
			"# flaten the images to prepare for the dense layers\n",
			"model4.add(layers.Flatten())\n",
			"model4.add(layers.Dense(64, activation='relu'))\n",
			"# final dense softmax layer, with 2 classes so 2 dimension, to have probabilities at the end\n",
			"model4.add(layers.Dense(2, activation='softmax'))\n",
			"\n",
			"# model architecture\n",
			"model4.summary()\n",
			"\n",
			"train_pred_class4_under,test_pred_class4_under = CompileAndTrainCNNModel(model4,images_under, labels_under,20,\"model4_under\")"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"###### Specificty is getting goood, but the recall has reduced!"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Let's try taking the pooling layers. Just to see (and to follow advices from new trends). To reach 8M parameters!"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 100,
			"metadata": {},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"_________________________________________________________________\n",
			"Layer (type) Output Shape Param # \n",
			"=================================================================\n",
			"zero_padding2d_31 (ZeroPaddi (None, 32, 32, 3) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_121 (Conv2D) (None, 32, 32, 32) 896 \n",
			"_________________________________________________________________\n",
			"conv2d_122 (Conv2D) (None, 32, 32, 64) 18496 \n",
			"_________________________________________________________________\n",
			"conv2d_123 (Conv2D) (None, 32, 32, 128) 73856 \n",
			"_________________________________________________________________\n",
			"flatten_30 (Flatten) (None, 131072) 0 \n",
			"_________________________________________________________________\n",
			"dense_60 (Dense) (None, 64) 8388672 \n",
			"_________________________________________________________________\n",
			"dense_61 (Dense) (None, 2) 130 \n",
			"=================================================================\n",
			"Total params: 8,482,050\n",
			"Trainable params: 8,482,050\n",
			"Non-trainable params: 0\n",
			"_________________________________________________________________\n"
			]
			}
			],
			"source": [
			"# initialize a first model\n",
			"model5 = models.Sequential()\n",
			"# need to add an extra zero padding layer, 4 on each width side, 2 on each height side\n",
			"model5.add(layers.ZeroPadding2D(padding=(4, 2), data_format=None,input_shape=(24, 28, 3)))\n",
			"# 1st conv layer, with 32 filters of size (3,3) \n",
			"model5.add(layers.Conv2D(32, (3, 3), activation='relu', padding=\"same\"))\n",
			"# 2nd conv layer, with 64 filters of size (3,3) \n",
			"model5.add(layers.Conv2D(64, (3, 3), activation='relu', padding=\"same\"))\n",
			"# last conv layer, with 64 filters of size (3,3) \n",
			"model5.add(layers.Conv2D(128, (3, 3), activation='relu', padding=\"same\"))\n",
			"# last conv layer, with 64 filters of size (3,3) \n",
			"\n",
			"# flaten the images to prepare for the dense layers\n",
			"model5.add(layers.Flatten())\n",
			"model5.add(layers.Dense(64, activation='relu'))\n",
			"# final dense softmax layer, with 2 classes so 2 dimension, to have probabilities at the end\n",
			"model5.add(layers.Dense(2, activation='softmax'))\n",
			"\n",
			"# model architecture\n",
			"model5.summary()\n"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 101,
			"metadata": {},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"Train on 2317 samples, validate on 773 samples\n",
			"Epoch 1/20\n",
			"2317/2317 [==============================] - 26s 11ms/sample - loss: 0.7935 - acc: 0.5304 - val_loss: 0.6792 - val_acc: 0.6093\n",
			"Epoch 2/20\n",
			"2317/2317 [==============================] - 26s 11ms/sample - loss: 0.6774 - acc: 0.5736 - val_loss: 0.6631 - val_acc: 0.6003\n",
			"Epoch 3/20\n",
			"2317/2317 [==============================] - 27s 12ms/sample - loss: 0.6720 - acc: 0.5917 - val_loss: 0.7468 - val_acc: 0.4864\n",
			"Epoch 4/20\n",
			"2317/2317 [==============================] - 28s 12ms/sample - loss: 0.6759 - acc: 0.5792 - val_loss: 0.6626 - val_acc: 0.5744\n",
			"Epoch 5/20\n",
			"2317/2317 [==============================] - 28s 12ms/sample - loss: 0.6673 - acc: 0.6025 - val_loss: 0.6644 - val_acc: 0.5912\n",
			"Epoch 6/20\n",
			"2317/2317 [==============================] - 28s 12ms/sample - loss: 0.6653 - acc: 0.5909 - val_loss: 0.6618 - val_acc: 0.5796\n",
			"Epoch 7/20\n",
			"2317/2317 [==============================] - 28s 12ms/sample - loss: 0.6640 - acc: 0.6098 - val_loss: 0.6654 - val_acc: 0.5705\n",
			"Epoch 8/20\n",
			"2317/2317 [==============================] - 28s 12ms/sample - loss: 0.6623 - acc: 0.6008 - val_loss: 0.6887 - val_acc: 0.5408\n",
			"Epoch 9/20\n",
			"2317/2317 [==============================] - 28s 12ms/sample - loss: 0.6566 - acc: 0.6029 - val_loss: 0.6596 - val_acc: 0.6016\n",
			"Epoch 10/20\n",
			"2317/2317 [==============================] - 28s 12ms/sample - loss: 0.6461 - acc: 0.6180 - val_loss: 0.6707 - val_acc: 0.5964\n",
			"Epoch 11/20\n",
			"2317/2317 [==============================] - 28s 12ms/sample - loss: 0.6353 - acc: 0.6314 - val_loss: 0.6871 - val_acc: 0.5770\n",
			"Epoch 12/20\n",
			"2317/2317 [==============================] - 28s 12ms/sample - loss: 0.6189 - acc: 0.6461 - val_loss: 0.6658 - val_acc: 0.6028\n",
			"Epoch 13/20\n",
			"2317/2317 [==============================] - 28s 12ms/sample - loss: 0.5977 - acc: 0.6612 - val_loss: 0.6752 - val_acc: 0.6016\n",
			"Epoch 14/20\n",
			"2317/2317 [==============================] - 29s 12ms/sample - loss: 0.5770 - acc: 0.6703 - val_loss: 0.6970 - val_acc: 0.5783\n",
			"Epoch 15/20\n",
			"2317/2317 [==============================] - 28s 12ms/sample - loss: 0.5436 - acc: 0.7018 - val_loss: 0.9535 - val_acc: 0.5912\n",
			"Epoch 16/20\n",
			"2317/2317 [==============================] - 28s 12ms/sample - loss: 0.5346 - acc: 0.7035 - val_loss: 0.7891 - val_acc: 0.5589\n",
			"Epoch 17/20\n",
			"2317/2317 [==============================] - 28s 12ms/sample - loss: 0.4913 - acc: 0.7303 - val_loss: 0.7581 - val_acc: 0.5977\n",
			"Epoch 18/20\n",
			"2317/2317 [==============================] - 29s 12ms/sample - loss: 0.4586 - acc: 0.7497 - val_loss: 0.8984 - val_acc: 0.6028\n",
			"Epoch 19/20\n",
			"2317/2317 [==============================] - 28s 12ms/sample - loss: 0.4160 - acc: 0.7695 - val_loss: 1.1102 - val_acc: 0.5757\n",
			"Epoch 20/20\n",
			"2317/2317 [==============================] - 28s 12ms/sample - loss: 0.3846 - acc: 0.7890 - val_loss: 1.0046 - val_acc: 0.5485\n",
			"[[198 200]\n",
			" [149 226]]\n",
			"Train/Test recall: 0.8556 / 0.6027\n",
			"Train/Test accuracy: 0.8097 / 0.5485\n",
			"Test specificity: 0.4975\n"
			]
			},
			{
			"data": {
			"image/png": 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0z9b01aBNmzZl7969lp9Dhw5ZZhOuX78ed3d3atSowQ8//MCBAwfYu3cvBw4cYP78+Xz11Vd8++23lgTJ3xmNxkdKWKS3zUpWfZNu3boxa9Ysrl27xqlTp4iPj8+wGsRoNNKwYUPGjh2b5T3TJ5GULl2aTZs2ceTIEXbv3s2BAwdYvHgx/v7+LF26lKeffvqR3kVERKQg2LZtG0ajkStXrtCuXbtM16Oioti1a5dlW8d7jRc86pjC44xFQNb9h6zGIqpVq4a3tzcBAQEMGDCAgIAAywSJ/43jtddeu+uZpFWqVAHSEiMtW7Zk165d7N+/n8OHD3Pw4EFWrVrFmjVrsLW1faR3ESkstDJDpBAZMmQI7dq1Y8+ePSxbtizDtW7dunHlyhV279591/arV68mPj7eckAVpC0BvXz58l0TIbdv3+b777/n9OnTWSYyIG0fbICgoKBM1/z8/FizZg2Q1sFITk7OdP8HZWNjQ4cOHdi7dy9//PEHFy5csMyEgLSZm5C2qqNZs2YZfqytrTEYDNja2hIZGclPP/2Em5sbgwcPZsmSJQQGBtK+fXsOHDjA+fPnHzgmERGRgi798/PSpUuZrqWfJVW6dGmSk5M5ceIEMTExlrOoDh06xKRJkwgNDWXr1q0YjUZOnz5NaGgo7dq1Y+bMmezfv5+5c+cSHR1t6RNkpWzZslnuF71//37eeOMNbt++bRmseJz+RKdOnbCysmL37t0EBARQoUKFDAMP5cqVIy4uLlNfonbt2kRHR+Pg4ADA+fPnuXDhAk2bNmXq1Kn88MMPrFq1CoCvv/76geMREREpiDZv3ozBYGD27NksXLgww88rr7wCpG01da/xgg8//JDFixc/UJ2sPGi7rMYiUlNTuXPnzoO+Ll27duXo0aOEhIRw6NChLMciHB0dM/UfnJ2dMRqN2NvbExcXx9GjRzEYDPTu3ZtPP/2UwMBAhg4dyrlz5zh48OADxyNSWCmZIVLIzJgxA1dXV+bNm5fhC//IkSMpX748U6dO5cyZM5naHTp0iLlz51K/fn169OiRoZ2zszNTp04lLCwsQ5ukpCQmTZpESkoKo0ePvmtMPj4+uLu7s379+gwdhF9//ZX169db9oH08PDg3LlzGWaAbtu27aHev2vXrty5c4ePP/4Ye3v7DHtzNmvWDDs7O/7zn/9YztUAuHHjBqNHj2bOnDkYDAYOHTrEP//5T/bs2WOp4+joSPXq1YGsZ2KIiIgUViVKlMDHx4fvv/8+Q18gOTkZf39/bG1tad68OZGRkfTr149FixZZ6lhZWVGnTh3Ln41GI0OHDuW9997L8Ix69epZ6txNq1atuH37Njt37sxQvmzZMvbt24ebmxslSpQA4Ny5c5brsbGx7N+//4Hft2TJkjzzzDPs3LmTH3/8McNgBEDbtm05d+4c+/bty1D++eef89prr3HhwgUgbfblpEmTMszqrFWrFjY2No88Q1RERKQguHLlCr///jtPP/003bt3x9fXN8PPqFGjKFGiBIcOHQKgRo0abN26ldjYWMs9QkJCWL58Obdv36ZUqVL3rZOVB23n4eHB5cuXSUxMtNTZs2fPQ23t1KVLF0wmE++++y4pKSkZ+g8+Pj6UKFGCr7/+mri4OEt5bGws48aNw8/PD2tray5cuMCgQYNYu3atpY6trS21atUCNBYhAtpmSqTQ8fDwYOLEibz11ltMmzaNpUuXAuDg4MCXX37JyJEj6du3L127dqV+/fqkpqZy5MgRduzYQa1atZg/f36GD8jixYvzySefMHbsWDp37kyPHj2oVq0at27dYuPGjYSEhDBs2DA6dOhw15hsbW2ZPHkyb7zxBgMGDKBbt27ExcWxfPlyvLy8LHtMd+nShaVLlzJ27Fhat27N6dOnCQgIyPJ8jLt56qmnKFeuHHv37qVz586Ww0YhbUXGhAkTmDVrFv369aNbt26kpqayatUqkpKSeOONNwBo06YNlStX5s033+T06dNUrFiRS5cusXLlSp555hmqVq36UP9NRERE8ru5c+dm+MxM17FjR8vKgn/+85/07t2bAQMG4OTkZFmZOXXqVIoWLUrRokXp2rUrq1atIiEhgQYNGhAZGcmKFSvw8PCgY8eO2NraMmTIED7//HPGjBlDy5YtSUxMZPXq1Tg4ONCrV6+7xti/f3/WrVvH+PHjGTRoEJUrV2bfvn0cOnSI9957D2tra3x9fZk5cyYzZszg2rVr2Nra8t133+Ho6PhQfx9du3bFz88PIMMWUwCjRo1ix44djB07lv79+1OtWjWOHTvGpk2baNWqFa1atQLStqycOnWqpZ9kNpvZtGkTSUlJDBw48KHiERERKUjSD/7u3bt3ltdtbGzo1asXX3zxBZs2bcLPz48RI0bQq1cv+vTpg5WVFStWrKBo0aKWQ7ofpE5WHqRdly5deOeddxgxYgTdunUjKCiI7777zrKi4kGUKVOGxo0bs3fvXurXr5/hkHAbGxveeustxo0bR8+ePenduzd2dnasWbOG69evM2fOHIoUKUK9evVo1KgRc+fOJTQ0FG9vb0JDQ1mxYgVVqlShadOmDxyPSGFlMN9rE1wRyZcmT57Mhg0b2L17d5ZnP5jNZgYNGsSxY8eYPXs23bt3t1yLjY1l9erVbN26laCgIKytralSpQrdunWjV69ed90q6vLly/j7+3PkyBHCwsKwtramTp06DBkyBF9f3weKe/fu3SxatIhz585RtGhRWrZsyb///W/LQeOJiYl89NFHbN26lbi4OOrVq8eUKVOYOHEiPj4+vP/++wB4e3vTo0cPy+9/N3fuXL744gs+//xz2rZtm+l6QEAA/v7+nD9/Hnt7e2rXrs2YMWNo2LChpc7169eZP38+P/30E7dv36ZEiRK0b9+esWPHPtKB5SIiIvlRep/ibvz8/Bg2bBgAp0+fZv78+Rw9ehSTyUSNGjUYPnx4hn5AYmIiixcvZuvWrYSGhuLg4EDTpk0ZP3685fBNk8nE8uXLWbduHVevXsXa2pqnnnqKV199FR8fn3vGGxkZybx589i1axcxMTF4eXnx0ksv0bFjR0udI0eO8NFHH3H27Fnc3Nzo27cvVapUYfz48Za+06effsqCBQvu2peKjY2lWbNmVK1alfXr12e6fvv2bebPn8+ePXuIioqibNmydOrUiZEjR1q2mQLYuHEjy5cvJygoCJPJhI+PDy+//DLNmze/53uKiIgUZO3btyc8PJyDBw9ib2+fZZ1r167h6+tLpUqVCAgI4NixY8yfP5+TJ09iZ2dH48aNef311zMkBR6kTlbu185kMvHZZ5+xdu1awsPDqVGjBhMnTmTp0qXEx8dbtods27Yt5cqVu+t2kd999x1vvfUWU6dOZciQIZmuBwYG8vnnn3Pq1CmsrKyoVq0ao0aNok2bNpY6kZGRLFiwgL1793Lz5k1cXV1p3bo1r732mmUFqsiTTMkMERERERERERERERHJ17RZq4iIiIiIiIiIiIiI5GtKZoiIiIiIiIiIiIiISL6mZIaIiIiIiIiIiIiIiORrSmaIiIiIiIiISKG1ZcsWOnfuTN26denYsSMbN268Z/2IiAj8/Pxo0aIFTz/9NKNGjeLKlSsZ6qSmpjJv3jyeffZZ6tWrx8CBAzl58mQOvoWIiIg88QeA16pVC5PJhLOzc16HIiIikiNiY2OxsrLizJkzeR1KoaS+hIiIFHYFuS8REBDA+PHjGTp0KC1btmTXrl18++23fPLJJ3To0CFTfbPZzMCBAwkODub111+nWLFizJ8/n9u3b7N582ZcXV0BePvtt9mwYQMTJ06kbNmy+Pv7c/r0aTZt2kSFChUeOk71J0REpLDLjv5EkWyMp0AymUw84fkcEREp5MxmMyaTKa/DKLTUlxARkcKuIPclPv74Yzp27MiUKVMAaNmyJVFRUXdNZly5coVff/2V2bNn0717dwC8vLzw9fVlz5499OjRg6tXr7J69WreeustBgwYAECLFi1o3749//nPf3j77bcfOk71J0REpLDLjv7EE5/MSJ/1cPTo0TyOREREJGc0atQor0Mo1NSXEBGRwq6g9iVCQkIIDg5mwoQJGcrbt29PQEAAISEhmVZRJCUlAeDk5GQpS1+NERkZCcBPP/2E0Wikffv2ljq2tra0bt2affv2PVKs6k+IiEhhlx39CZ2ZISIiIiIiIiKFzqVLlwCoXLlyhnJPT08ALl++nKlNjRo1aNKkCQsXLuTixYtEREQwc+ZMHB0d8fX1tdzX1dUVd3f3TPe9fv06iYmJOfE6IiIiT7wnfmWGiIiIiIiIiBQ+MTExAJnOoUhfdREbG5tlu+nTpzNixAg6deoEpK26WLhwoWUVR2xsbJZnW6TfNy4uDnt7++x5CREREbHQygwRERERERERKXTSz6AwGAxZlltZZR4SuXjxIv369cPNzY2FCxfy5Zdf0qZNG1599VXLFlB3O9vibs8TERGR7KGVGSIiIiIiIiJS6Li4uACZV2DExcVluP6/vvrqKwCWLl1qOSujefPmDBw4kPfee4/169fj7OxsuUdW981q1YaIiIg8Pq3MEBEREREREZFCJ/2sjODg4AzlQUFBGa7/r+vXr+Pl5WVJZEDaSouGDRvy559/AlClShUiIyOJiorKdN/y5ctja2ubre8hIiIiabQyQ0RERCQXmEwmoqKiiI2NxWQy5XU4hY6VlRXOzs64urpmuW2IiIg8eTw9PSlfvjzbt2/nueees5Tv2LGDSpUqUbZs2UxtKleuzIYNG4iKisqQ0Dhx4gTlypUDoFmzZgD88MMP9O3bF4Dk5GT2799PixYtcvKVSEhIIDo6mqSkpLtudyWPTv0JEZH8TckMERERkVxw/fp1YmJisLW1pUgRdcGyW3JyMmFhYcTHx1sGm0RERMaMGYOfnx+urq60bt2aPXv2EBAQwNy5cwGIiIggODiYqlWr4uzszLBhw/j+++8ZPnw4I0eOxN7enk2bNvHzzz9b2pQrV44ePXowc+ZM4uPj8fT0xN/fn6ioKEaMGJFj7xIREcGNGzcwGAzY2dlpsD0HqD8hIpK/5Ztv0mfPnqV3797s3r2b0qVL37VeXFwcc+bMYceOHcTHx9OoUSPefPNNKlWqlHvBioiIiDyEuLg4YmJi8PDwwMPDQweD5gCz2cytW7cIDw/Hzc0NR0fHvA5JRETygZ49e5KcnMzSpUtZs2YNFSpUYPbs2XTq1AmAffv24efnx/Lly2nSpAnly5fnm2++4cMPP2Ty5MlYWVlRvXp1/P39LSsyAGbMmEHRokVZvHgx8fHx1K5dG39/fzw9PXPkPRISErhx4wYuLi6UKVMGa2vrHHnOk079CRGR/C1fJDMuXbrEqFGjSE1NvW/d8ePHc+rUKSZNmoSTkxMLFixg6NChbN26NcvDu0RERETyWnR0NFZWVhQvXlyJjBxiMBjw8PDgzp07REVFafBBREQs+vfvT//+/bO81rNnT3r27JmhzMvLiy+++OKe97S1tWXKlClMmTIl2+K8l+joaAwGgxIZOUz9CRGR/C1P1ySmpqaycuVKevfuTVJS0n3rHz16lP379zN79mx69OjBP/7xD7766itiYmL45ptvciFiERERkYeXmpqKjY2NtoPIYVZWVtjY2DzQBBkREZGCJCkpCTs7OyUycoH6EyIi+VeefqM+duwYc+bM4cUXX2TixIn3rX/o0CGcnJxo3ry5pczd3Z3GjRvz448/5mSoIiIiIo/MZDJp8CGXWFtb64B1EREpdMxmsyZF5CL1J0RE8qc8/ST08vJi165djB079oG+4F+6dAlPT89MdStWrMjly5dzKkwREZFcEx6VwM2I+LwOo8A6e/YstWvXJiws7IHbzJ49m2HDhuVcUCIiIvdgNqZiSk7I6zBEREREMkhJNZGYnL9WqeVpMsPDw4PixYs/cP3Y2FicnZ0zlTs5OREbG5udoYmIiOS63b8EM2zGDoa/u5P1ey/kdTgFzsOcwZVuxYoVLF26NAejejKYzea8DkFEpEAym4xcW/o6wQtHkxJ5I6/DEckz6kuIiOQv54MieHHmDka+t4vkFGNeh2NRoNYo3uvDTcstRUSkoAqPSsD/+5M9N/qHAAAgAElEQVTM+/a4pczerkgeRlSwPOwZXAA3btzg3//+N++++y4uLi45HGHhtnfvXt54443Hvs/69evx9vZ+qFU1IiIFXXLYZZJvBmOKjyby0Pq8DkckT6gvISKSv/xyJowpnx8mMiYJKytDXoeTQYHKADg7OxMXF5epPC4uLssVGyIiIvmd2Wzm6+8C+PPYZmwMyQA841OaTs0q53FkBcfDnsEFMHfuXM6cOYO/vz81a9bM4QgLt2XLlhEaGvrY92ndujWrV6/G3d09G6ISESkYEoLPWP4cc3IvKVE38zAakbyhvoSISP6x80gQM/1/JjnFSCl3R977V3NsbfLP+Y8Fatpn5cqVCQwMxGw2YzD8NysUFBRE5coa9BERkbxnMpkJCosmJTXzgYH7fr3K5gOXLL8XMaRQ2T4YV5sYbK2grF0YXj7N6dWmam6GXOCln8FVvHhx1q9/sFmtI0aMoEqVKlhZWbFw4cIcjlAehLu7uwYfROSJk/g/yQxMRiIPb6BEx1F5F5BIAaa+hIjIozObzXy3+w9WBJwDwKu8K9NGPIObi30eR5ZRgUpmtGjRgi+++ILDhw/TvHlzACIiIjh69CijRqnDJyIiuSsiOpGfT4dhNP13G8RFG07yIFv+uljHUNkhCFurtPMdbiW706JVO/q3r5VT4RZaHh4eD92malUljLLDkCFD+PnnnwHw9vZm+fLlDB06lBkzZvD555+TmprKvHnzaNSoEatXr2b16tVcunQJk8mEl5cXL7/8Mu3btwfStobw8/Nj//79lC5dmsmTJ3Pr1i06dOjAkiVLuH79Ol5eXkycOJGWLVvm5WuLiGQLs9lEYshZAOzKVCUp9E9iftuDW/NeFCn68J9tIgWR+hIiInnPaDKzeMNJth2+AkD96iXw+2djHO1t8jawLOTrZEZERATBwcFUrVoVZ2dnGjduzNNPP82ECROYOHEixYoV49NPP8XFxYUBAwbkdbgiIlJInbhwi33HrmL6W5Ziz9GQR7ibmbbVk4gOuwhAkSI21G/SmmrVa1KtQrFsiFYKklSjifCoxLwOg+Ku9hSxfvjdR6dNm8bkyZMxGo1MmzaN8PBwIG0brxkzZhAXF0fdunVZvnw577//Pq+++ioNGjQgKiqKJUuW8O9//5v69etTqlSpLO9/4sQJQkNDee2113B2duaTTz7h1Vdf5ccff9RZJyJS4CXfDMaUGAtAiS5jCF31Nsa4SCIDN+LRfkQeRycFSUHuT6gvISKSt5JTjMxZeYzAU2nb/bV+qjyv9muATZH8eTpFvk5m7Nu3Dz8/P5YvX06TJk0AWLBgAe+//z4ffPABJpOJhg0bMm/ePFxdXfM4WhERKegSk1Iz/L754CX2Hgsh5EbsfdtWKPXfs5sc7W0Y07seZYo7ZaiTkpLCd999w9WQtCRI2bJl6dWrl5bDP6FSjSZGz95DaHjm88ByW5niTnz2RtuHHoBIn3BiNBqpX78+R44cAWDQoEH84x//sNS7evUqI0aM4OWXX7aUlStXjp49e/Lrr7/SsWPHLO8fExPDhg0bqFChAgCOjo4MHjyYI0eO4Ovr+7CvKSKSryQGnwbA2sUdmxIVcG36PBG7lhFzfBfFmvWiiItbHkcoBUFB70+oLyEikndi45OZ6f8zpy+lJZJ7tK7KsM618t2h3/8r3yQzevbsSc+ePe9b5urqyqxZs5g1a1ZuhiciIoXc+8t+4dDJ6/esU9LdEZ8qxTOUFXe1p0+76jjY3f8j1d6uCO5ublwNCeGZZ57B19cXa+v8c5CWSHapXr16ht+nTJkCQHR0NJcuXSIoKMgyWJGSknLX+5QoUcIy+ABQunRpABISErI7ZBGRXJd+XoZDxdoYDAaKNvgHkYc3YIqPJuqnjRR/7oU8jlAk76gvISKSs25HJjBtSSDBYTEADO9Wm+7P5v/tmPNNMkNERCSvXLoWdc9ERpcWlXnKuySNapbCYHi4GQpGoxErKytLu86dO1O3bl28vLweK2Yp+IpYW/HZG20L7LYQ97xf8YxJv+DgYP7v//6PwMBAbGxsqFKlCjVq1ADSDpq7GwcHhwy/p///yGQyZVusIiJ5wWw2k/BXMsO+Ytp5WVa29hR75nki9nxN9K87cG3agyLO2oJS7q2w9ifUlxARyTnBYdFMWxzI7ahEilgbGNf/KZ59qnxeh/VAlMwQEZEn0u5fgvn5TBgAh0+GWsqHd6tNrcr//fJUopgDbkXtH+kZ4eHhrF27liZNmlC/fn0AbG1tlcjIZX8/gys/KWJtRSl3x7wOI0eZTCZGjhyJnZ0da9eupWbNmhQpUoQ///yTTZs25XV4IiJ5IuX2VUzx0cB/kxkARRu2JzJwI6aEGKKOfE/xdkPzKkQpQAp7f0J9CRGR7HPmcjjvfHmE2IQUHOyK8Oawp6lXvUReh/XA8udJHiIiIjnos7UnmPftcQ6fDM2QyKhUpihdWlShekU3y8+jJjJOnjzJ4sWLCQsLY/v27SQm5v1suSfVvn376NevH6dPn87rUAql+22VdufOHS5fvkzfvn2pU6cORYqkzaX58ccfgXvPphQRKazSt5iydiqGTfFylnIrWwdcm3QFIPrYdoxxUXkSn0huUl9CRCR3BJ4K5a0vDhObkEIxFztmjW5eoBIZoJUZIiLyhAkLjyMg8Irl9ya1S+NRzIEKJZ3p1LzyQ28j9XfJyckEBATw22+/AeDi4kLPnj2xt3+0pIg8nAc9g+t/ff311zkdVqHm4uLC0aNHCQwMJDY2NtP14sWLU65cOZYvX07JkiVxdnbmwIEDLF++HID4+PjcDllEJM8l/HX4t33Fmpn6Hq6NOhL10yZMiXFE/bwF9zaD8iJEkVyjvoSISM4LCLzCF+tOYDJDWQ8n3h7ZlNLFnfI6rIemlRkiIvLEMBpNvPbxPsvvY/vUY+qLTXi5Z106t6jy2ImMGzdusHjxYksio3r16rz88stUqlTpse4rkp+98MIL2NjY8NJLL931AM7PPvuMkiVLMmnSJMaNG8eJEyf4/PPPqVKlCseOHcvliEVE8pbZbLaszLCvUCvTdSs7R1wbdwEg6ug2jAkxuRqfSG5TX0JEJOeYzWZWbj/HZ2vTEhnVKhTjg1daFshEBoDB/ISvx2vUqBEAR48ezeNIREQkp8UlpNB/6jYAHOysWTmjEzZFsiev/9tvv7FlyxbLgd/PPfccTZo0eewESXbQZ13OepC/36CgIAA8PT1zJaYnmf6uRSS/S4m4TsjnrwBQ/qWPsS2Z+d8rY0IswQv/hTkpnmIteuP+7IDcDjMD9SVy3v3+jvX5lrv09y0ihYHRaOKzdSfZcSTt37SGNUoyeWhj7O3yZrOm7OhPaGWGiIgUeimpJkJvx/HGggOWslmjW2RbIgPA0dERo9GIm5sbw4cP55lnnskXiQwRERHJXxL+WpVh5eCMTYkKWdaxdnDGtVEnAKJ/2YYxMS7X4hMREZGCLzE5lfe++sWSyGjXuAJTX2ySZ4mM7FKwoxcREbkPo9HEK3P2cO1WxkEAj2IOj31vs9lsSVhUr16dnj17Ur16dezs7B773iIiIlI4/XeLqZoYDHefWOH6dBeiftmCKSme6F+24dayT26FKCIiIgVYdFwy73z5E+eC7gDQp101hnTMfE5XQaRkhoiIFEqHTlzn7JUI7kQnZkpkzP93a1ydHz3hYDabOXToECEhIfTv39/SIahTp85jxSwiIiKFX2JQ+uHfte9Zz9rRBddGHYk8vIGon7fg+nRnrOwccyNEERERKaBuRsQzbUkgV2/GYjDAqO516NyiSl6HlW2UzBARkULDbDbjv+UMP58OzZTAAJg9tgXVKrg91vZSsbGxbNiwgUuXLgFw/PhxnnrqqUe+n4iIiDw5UqJukhp9GwCH+yQzAFyf7krUL9swJcYSdXQ7bs175nSIIiIiUkBdCY1m2uJAIqITKWJtxcRBDWler2xeh5WtlMwQEZECL9VoYspnhzh7JSLTtdpViuNkb0ONSm7Uqlz8sZ5z8eJFNmzYQFxcWqKkYcOGWo0hIiIiDywxKG2LKYOdI7al7n+wsLWTK0Ubtifqp++JOvI9ro07YmX7+FtlioiISOFy6s/bzPQ/QnxiKk72RXjzxSbU8fLI67CynZIZIiJSIJ27EkFQWAwAQWHRmRIZ/XyrU6eqB/WqlXjsZxmNRvbt28fBgwcBsLOzo2vXrtSuff8ZlSIiIiLpEoP/2mKqfA0MVtYP1Ma1STeij27HlBBD9LEfKNa0e06GKCIiIgXM4ZPX+XDFMVKNJtyL2vP2yKZUKlM0r8PKEUpmiIhIgWI2m/nPpt/5/sClLK9PGtKIOl4eFHPJnkO4o6OjWbt2LSEhIQCUK1eOXr164ebmli33FxERkSdHwl+Hfzt4PviEiCLObrg0eI7oX7YSdeR7ijbqiJVN9vRzREREpGD74acrfLb2BCYzlC/pzNsjm1LSrfCesaVkhoiIFCiXr0dnSGSUdHfE+q8DuBvXKkXL+uWy9Xk2NjZER0cD0Lx5c9q0aYO19YPNpBQRERFJlxodTuqdMADsK9Z6qLbFmnYn5tcdGOOiiDm+E9enu+REiCIiIlJAmM1m1u65wPJtZwGoXrEY00Y0paiTbR5HlrOUzBARkXzrdmQCN+/EZyi7fC3K8ueJgxry7FPlczQGBwcHevfuTWJiIlWrVs3RZ4mIiEjhlRjy13kZNvbYla7yUG2LuLjjUr8d0ce2E3l4Ay4NntPqDBERkSeUyWRm6ebTbPrxIgANqpfAb9jTONgV/qH+wv+GIiKSrxlNZn46FcrtqIQM5VdvxrI98Mo922b3KgyA27dvs2XLFrp3706xYsUAKF8+ZxMmIgWd2WzG8NcKqfx8TxGRvJTw1+Hf9uW9MVg//FfxYs16EH18F8a4SGJ+241r407ZHaJInlFfQkTkwaQaTcxffZy9x64CaeMi4wc8hU0RqzyOLHc8GW8pIiL51q/nbvD+8l/4z6bfM/zcL5HRvF5ZrKyy98vJb7/9xuLFiwkKCmL9+vWYzeZsvb9IYbR3717eeOONbL3n8ePHGTVqVLbeU0Qkr6WvzHjYLabSFSnqgUu9tgBEBm7AnJqSbbGJ5CX1JUREHkxicirv+v9sSWR0alaJfw9q+MQkMkArM0REJA9FRCcy48sjlt8rly2a4boBA+0aV6BT88qZ2haxzr4P66SkJLZt28bJkycBKFq0KL6+vprJJfIAli1bhtFozNZ7rl27lj///DNb7ykikpeMcVGk3E4beHiYw7//rlizHsSc2I0xJoKYE3so2rB9doUokmfUlxARub/Y+GRmfHmEs1ciABj4D2/6/8P7iRu3UDJDRETyxJXQaL7ded7yu49XcWaNbpHrcYSGhrJ27VoiItI6BN7e3jz//PM4ODjkeiwiIiJSOCUE/3VeRhFb7Mo8+hlcNsVK4lLnWWJO7CHy8Hpc6rfFYG2TXWGKiIhIPhQelcD0JT9xJTQagwFGda9D5xYPd/5WYfHkrEEREZF8ISXVyPvLf+GVOXs5dOK6pXzS4Ea5GofZbObIkSN8+eWXREREYG1tTYcOHejXr58SGSIPaMiQIQQGBvLzzz/j7e3NkSNHuHPnDlOnTqVp06bUrVuXAQMGcOzYsQztDh06RN++fWnQoAGNGzdm9OjRXLyYdnjd5MmTWbt2LdeuXcPb25v169fnxauJiGSrxL+SGXblqmEo8njJh2LNe4HBitTo28Sc3J8d4YnkGfUlRETu7frtWCYtOMiV0GisrQxMHNTwiU1kgFZmiIhILoqOS2b4zB0kJv93GbmtjTX9fKvjVtQ+V2MxGAzcvHkTo9GIu7s7vXv3pkyZMrkag4jZmEpqTEReh0ERF/dHOox22rRpTJ48GaPRyLRp06hatSqDBg0iPDycCRMmUKJECb799luGDRvGypUrqVu3LiEhIYwePZpevXoxYcIEoqKimDt3LqNGjWLnzp2MHj2aqKgoTp06xYIFC6hYsWIOvLGISO5KDD4NgH3FR99iKp2NW2mcfVoRe2ofkYfX4VK39SP9Gy6FR0HuT6gvISJydxevRjJ9yU9ExiZhZ2vNlH8+zVM1SuZ1WHlKPR4REck1O44EZUhkTH3haZr45F0CoUOHDjg6OtKiRQvs7OzyLA55MpmNqYQseo3UO2F5HQpF3EpTYdQnDz0AUbVqVZydnTEajdSvX5/vvvuO8+fPs2bNGurUqQNAq1at6N27N3PnzsXf35+TJ0+SmJjIqFGjKFWqFABlypRh9+7dxMXFUbFiRdzd3bG1taV+/frZ/q4iIrnNmBBD8s1gABwe8fDvvyvWvCexv/9IauRNYk8fwKVum2y5rxQ8Bb0/ob6EiEjWTl28zcylR4hPTMXF0Yb/G/EMNTzd8zqsPKdkhoiI5IrTl8JZtvWM5fcFE9vgWaboPVpkL5PJxMGDB3FycqJhw4YA2NjY0K5du1yLQaSwCwwMpFSpUtSsWZPU1FRLeZs2bVi0aBHJycnUq1cPOzs7evfuTYcOHWjVqhVNmjShbt26eRi5iEjOSQw+C5jBqgh25apnyz1ti5fDuVZzYk8fIPLQOpx9WmGwss6We4vkJfUlREQg8FQoH644SkqqieKu9swY2ZSKpXNv/CQ/UzJDRERyxbkr/1363rVllVxNZMTExLBhwwYuX76MtbU1FSpUoGTJJ3tppuQ9g3URKoz6pMBuC5GVyMhIwsLCqF07621U7ty5Q/ny5VmxYgWLFy9m7dq1LF++nKJFizJw4EDGjRuHwWB47DhERPKTxJC/zssoWxUrm+xbCVqseS9iTx8kJSKU2DOHcPFplW33loKjsPUn1JcQkSfdziNBLFjzGyYzlCvhxIyRzSjp7pjXYeUbSmaIiEiuKuZix8judXLteX/++ScbNmwgPj4egKeeegp3dy3NlPzBYF0Em2KFJ7Hm4uKCl5cXs2fPzvK6m5sbAHXr1mXBggUkJydz7NgxVq9ezRdffEGtWrVo3759boYsIpLjEoLSkhnZtcVUOtsSFXCq2ZS4s4eJPLgW51rNtTrjCVWY+hPqS4jIk2zdngt89deOFlUrFGP6iGdwddaW2P/LKq8DEBGRJ0uJYg658hyj0cjOnTtZuXIl8fHx2Nvb07dvXzp16kSRIsrli2QXa+v/Dpw1btyY69evU7JkSerUqWP52b17N19//TU2NjZ8/fXXtG3bluTkZGxtbWnatCnvvPMOAKGhoZnuKSJSkJkS40i+cRkA+2xOZgC4tegNQEr4NeLO/ZTt9y8stmzZQufOnalbty4dO3Zk48aNd607efJkvL297/qT7ujRo1leHzVqVG68UqGivoSIPOnMZjNLN5+2JDLqVfPg3ZebKZGRBY3miIhIjjOazBw7dzPXnnfnzh3WrVvHtWvXAKhQoQI9e/akWLFiuRaDyJPCxcWFo0ePEhgYiK+vLytWrOCFF16wHMq5b98+/P39GTt2LAaDgWeeeYYPPviAMWPGMHjwYKytrfn222+xs7OjTZs2lnvevn2b/fv3U7NmTW0LJyIFVuLV82A2gcEK+/I1sv3+tiU9cfRuQvz5I9w5uAanmk0xGDRn8X8FBAQwceJEhg4dSsuWLdm1axdvvPEG9vb2dOjQIVP90aNH079//wxlQUFBTJ48mb59+1rKzp8/j6OjI/7+/hnqFi2qPc0flvoSIvIkMxpNfLrmN3b/EgJAs7plmDioITZFlJTNino5IiKS4348fpVTF28DYGWV83vY3rlzx5LIaNGiBcOGDVMiQySHvPDCC9jY2PDSSy9x/PhxVq5cSb169Xj//fcZOXIkBw4c4K233uKVV14BoFq1aixatIjY2FgmTJjA2LFjiYyMZOnSpXh6egLQr18/KlSowJgxY/j+++/z8vVERB5LQvBpAOzKeGFllzOrUy2rM26FEH/+5xx5RkH28ccf07FjR6ZMmULLli15++236dixI5988kmW9StWrEj9+vUtP3Xq1GH58uXUqFGDN99801Lv3LlzVKtWLUPd+vXrU6VKldx6tUJDfQkReVIlpRiZtewXSyKj/TOeTBrSWImMe9DKDBERyXG3IxMsf+7UrHKOP69KlSo899xzlC5dWl8oRXJYvXr12Lt3b4ayWbNm3bNNs2bNaNas2V2vV6xYka1bt2ZLfCIieSkxOG27CPuKNXPsGXalq+BYrRHxF45y58AaHL2b6ADkv4SEhBAcHMyECRMylLdv356AgABCQkKoUKHCPe/x7bffcubMGVavXo2tra2l/OzZs9SsmXP/XZ8k6kuIyJMoLiGFd5Ye4fSlcAD6+lZncIca+gy/D63MEBGRHPNH8B0G/V8Ay7edBcDb0422je79hfFR3Lp1iy1btmAymSxlzZo1UyJDRERE8owpOZGk0IsA2FesnaPPKtaiDwDJN68Qf+Fojj6rILl06RIAlStnnEyTPnv/8uXL92wfFxfH/Pnzef7556lbt66l3GQyceHCBcLCwujRowc+Pj60bt2apUuXYjabs/ktRESksLkTnYjfZwctiYyXnvdhSMeaSmQ8AK3MEBGRHJGSamTet8eJjku2lFUo6ZKtzzCbzRw/fpyAgABSU1NxcXHh2WefzdZniIiIiDyKxGvnwWQEDNhXyNkZ/PZlq+Lg1YCEi8fTVmdUa6QBESAmJgYAZ2fnDOVOTk4AxMbG3rP9unXriI6OznSo9+XLl0lMTOTy5ctMmDABNzc3du/ezQcffEBsbCyvvvpqNr6FiIgUJmHhcfzfokBCw+OwtjLwWv8GtGmY/ZM+CyslM0REJNtFxiQx4r2dJCUbATAY4P0xLfCu6JZtz0hKSmLLli38/vvvALi6umolhoiIiOQbiUFpW0zZlqqEtb1Tjj/PrUUfEi4eJznsIgkXf8WxasMcf2Z+l75K4u+JnfRyK6t7b1axcuVK2rVrl2llR6lSpViyZAk1a9akRIkSADRt2pTExESWLFnCiy++mCmBIiIi8mdIJG//5yciY5OwtbHG75+NaVSzVF6HVaBomykREcl2AYFXLIkMgDeHPU2tysWxts6ej53r16+zaNEiSyKjZs2avPzyy/fd81gKv7Nnz1K7dm3CwsLuWS8uLo63336b5s2b06BBA1566SWuXLmSO0GKiMgTIfGvw7/tK9bKlefZl/fGoXI9AO4cWKPtjgAXl7RVwX9fgREXF5fhelbOnTvHlStXeP755zNdc3Z2plWrVpZERrrWrVuTnJx83+2rRETkyXP8/E2mfH6QyNgknB1smDmqmRIZj0ArM0RE5JGYzWYuXo0iPiklQ/mJC7f5btcflt8/ndiGSmWKZtszf/rpJ3bt2oXJZMLa2poOHTrQsGFDbaUgXLp0iVGjRpGamnrfuuPHj+fUqVNMmjQJJycnFixYwNChQ9m6des9BzZEREQehCk1mcTrFwBwyOHzMv6XW8s+JFw+QdL1CyRcPoFjlfq59uz8KH1FRXBwMN7e3pbyoKCgDNezsm/fPhwdHbPcwvT8+fMcO3aMPn36YGNjYylPTEwEwM0t+1Yji4hIwbfvWAjzvj2O0WTGo5gDM0Y2pUIpfe98FEpmiIjII9n040W+/P70Pev0bF012xIZACkpKRw9ehSTyYSHhwe9e/emVCnNZHjSpaamsnr1aj766KMMAwp3c/ToUfbv38+SJUto1aoVAI0aNaJdu3Z88803jBw5MqdDFhGRQi7p2gUwpiXX7Svm7HkZ/8u+Qk3sPWuTGHSaOwfW4FC53hM94cPT05Py5cuzfft2nnvuOUv5jh07qFSpEmXLlr1r299++w0fHx9sbW0zXQsKCuLtt9+mVKlStGvXzlK+bds2ypcvT7ly5bL3RUREpMDasO9Plm5OGzupVKYo0196huKuDnkcVcGlZIaIiDyQkBsxrN1zgcTktC/mh0+G3rP+8628GNYle7dVsLW1pXfv3vzyyy906NAhyy+X8uQ5duwYc+bMYfjw4ZQqVYqpU6fes/6hQ4dwcnKiefPmljJ3d3caN27Mjz/+mCPJDCsrK1JSUu5fUR6b0Wh8oKSWiEhOSt9iyqZEBawds29ix4Nwa9GH0KDTJF09R9K1P7Av733/RoXYmDFj8PPzw9XVldatW7Nnzx4CAgKYO3cuABEREQQHB1O1atUM51z88ccfWa7KgLTtpHx8fHjrrbeIiIigdOnSbN68mT179vDpp5/mSALJysqK5ORkzGbzE52gyi3qT4jI4zKZzCzdfJpNP14EwMerOG++0ARnB/3b8jiUzBARkfs6eOIas5cfzfJap2aV+FevejnyXJPJxMGDB6lduzbFixcHoEyZMnTr1i1HnicFk5eXF7t27aJ48eKsX7/+vvUvXbqEp6cn1tbWGcorVqxIQEBAjsRob29PbGwsERERuLu758gzJG1AKikpSVuFiUieSwhOO/w7N7eYSmfv6YOD11MkXDwO6NyMnj17kpyczNKlS1mzZg0VKlRg9uzZdOrUCUjbTsrPz4/ly5fTpEkTS7vw8HCKFs06EWVra8uSJUuYN28eCxYsICIigmrVqrFgwQJ8fX1z5D2cnZ0JCwvj1q1beHh43Pfwcnl06k+IyONKSTUy79vj/Hj8GgDN65ZlwsCnsLWxvk9LuR8lM0RE5J62HrzEFxtOZSjr3Dxtf2F7W2s6N6+SI8+Njo5m/fr1BAUFcfbsWYYPH06RIvrYksw8PDweqn5sbGyGmZfpnJycMh0Qml08PDxISkrixo0bREZGZkqkyOMzGo2WgYeH/d+EiEh2MhtTSLp6Hsi9w7//l8FgoHTvSRgTYijiogQ6QP/+/enfv3+W13r27EnPnj0zlZ84ceKe93R3d2fGjBnZEt+DcHV1JT4+nvDwcO7cuYONjY36EzlA/QkReVzxiSm899XPnLhwG0gbP3mpex2srbSqLjtoVEhERO4qPEA/kFgAACAASURBVCohQyKjaZ0yvD64ITZFcvaL0x9//MHGjRtJSEgA0vY7FskuZvPdZ6nm1CxHw/+zd9/hUZZp+8e/M5MyaQRCTyGEFnoTASkSUaQrBlF0rYsru2J5QVwFf6/r4trWVV9cWcsqsKzoIh3BsBEwKKJ0ASlBICGhhBbS+8zz+2PMSAxowMw8STg/x+Gxzj3lOedYJJO57vu6LBYiIiI4c+YMRUVFOJ1Oj1znSubr6+v+4kHtN0TETMUnDmGUlQDmFDMALD6+KmTUMVarlYiICOrXr09OTg5lZWX6POEB+jwhIr9GZk4Rf/7nNxw+ng3APSM6cOvgtvr7pBqpmCEiIpUkH8lk4drv2bQnw702qEckU++6yqPXdTgcrFmzhm+++QaAgIAAbr75ZmJjr+xez1K9goODOXr0aKX1/Pz8C57YqC4Wi4XGjRt77PVFRKRmKDziajHlGxaOT3ADk9NIXRMUFERQUJDZMURE5CeOnc7jmXe/5lRmAVarhUfGdeeG3i3MjlXnqJghIiIVrN9+lL/N31Zp/Y6hni0oZGZmsmjRIk6ccA0Wb9GiBWPHjr1or2KRyxUTE8PXX39daYDmkSNHiImJMTGZiIjUBUU/zMsw61SGiIiIeFfykUxmvL+JnPwS/P1sPHXP1fTq0NTsWHWSJkaJiIhbUXFZhUJGUIAv94zowEfPDSeised2rANs27bNXci49tpruffee1XIEI8YMGAAOTk5bNy40b2WmZnJ1q1b6devn4nJRESktjOcDoqO7gPAHu394d8iIiLiXVv3neTptzeSk19CvSA/XvhDfxUyPEgnM0RExO2d8+ZjdGgZxkuTBmD10pCq6667jjNnztC3b1/tjpdqlZmZSVpaGm3atCE4OJirr76a3r17M2XKFKZOnUr9+vX5+9//TkhICHfccYfZcUVEpBYrzkjBKCkCIEAnM0REROq0NZvT+PvCb3E6DZqEBTLjwWs8vhH0SqeTGSIiAsDOA6dZsyXNffv38V09Wsg4efIkO3fudN/28fHhjjvuUCFDql1SUhK33347e/bsca+9+eabDB48mL/+9a889dRTNGvWjLlz5xIaGmpiUhERqe3KW0z51G+CT71GJqcRERERTzAMg4/XHGDmgh04nQatwkP52yMDVcjwAp3MEBEREjam8I/Fu9y3HxzThVYRnvlS1zAMtm3bxn//+1+cTieNGzcmPDzcI9eSK098fDzx8fG/uBYaGsqLL77Iiy++6M14IiJSxxWluQrn9hZqMSUiIlIXOZwG/1y2m1VfpQDQrW0jpt/Xm0C7r8nJrgwqZoiICEnbj7r/vVOrhgzp3cIj1ykqKuKTTz5h717XrsX69et75DoiIiIi3mY4HRSlu+ZlqMWUiIhI3VNS6uDVD7excdcP8z57RPA/43vi66PmR95iejFj5cqVvPXWW6SnpxMREcHEiRMZM2bMRR+fmZnJK6+8wpdffklJSQk9evRg2rRptGzZ0nuhRUTqkJTj2exNyQTgmi7NmXbv1Vgs1d9e6ujRoyxevJisrCwAOnXqxKhRo7Db7dV+LRERERFvKzmVhrMoHwC7ihkiIiJ1Sl5hKX+ZvYk9h88CMGZQa+4f1clrc0bFxdRiRkJCAlOnTuWee+5h4MCBrFmzhieffBK73c6wYcMqPd4wDCZNmkRaWhpPPPEE9evX54033uCee+7hk08+UZ9rEZHLMOeTH+cIdGrVsNoLGYZhsHHjRtatW4fT6cTHx4fhw4fTo0cPjxRNRERERMxQlO46eWoLaYhP/aYmpxEREZHqcja7kD+9+zVHMnIB+O3oTtwS18bkVFcmU4sZr732GsOHD2f69OkADBw4kOzsbGbOnHnBYkZqairbt2/n5Zdfdp/eaN26NTfccAPr1q3jlltu8Wp+EZHayOFwcvBoFg6nAcCZ7CL3fXE9I6v9eqdOnWLt2rUYhkHjxo259dZbadKkSbVfR0RERMRMhUdcG0QCojtpw4aIiEgdkX4yl2fe/ZozWYX42Cw8dnsP4q6KMjvWFcu0YkZ6ejppaWlMmTKlwvrQoUNJSEggPT2dqKiKfzCKi4sBCAoKcq+Vn8Yob1siIiKVncosYNOeDJyGwXvLv7vgY+4Z0YHQYP9qv3bTpk2Ji4sjOzubYcOG4euroVgiIiJStxiG4Z6XYY/qYHIaERERqQ7JRzJ59p/fkFdYSoC/jWn39qZHrDZnmsm0Ysbhw4cBiImJqbAeHR0NQEpKSqViRvv27enTpw+zZs2iVatWNGjQgJdeeonAwEBuuOEG7wQXEalldn5/mv/39saffUxIoC/d2zWulus5nU62b99Ojx49sNlsgOvknXYoioiISF1VeuYozoIcAOzRnUxOIyIiIr/WqXMFPDd7E3mFpdQP9udPv+tLm8j6Zse64plWzMjNdfUYCw4OrrBefuoiLy/vgs979tlneeCBBxgxYgQAfn5+zJo1q1LhQ0REXP7vo+0VbseE1yM02J9HbutOWD3X8G2rxVItQ6uys7NZvHgx6enpZGdnc/311wOokCEiIiJ1WlGaq8WULag+vmHhJqcRERGRX6OopIwX5m4mO6+EkEBfXn54AOGNg3/5ieJxphUzDMPVq/2nX3CVr1ut1krPOXToEOPHj6dFixZMnz4du93Oxx9/zKOPPsp7771Hr169PB9cRKSGKywuY39qJoYB/1i80z0To2lYILP+OBh/X5tHrrt//36WL19OUZHrek6nE8MwVMgQERGROq8wzTX8296igz77iIiI1GKGYfDmxzs5dDQbqwX+eHcvFTJqENOKGSEhIUDlExj5+fkV7j/f3LlzAZg9e7Z7Vkb//v258847eeGFF1iyZIkHE4uI1A7PvLOR/UfOVVqfdu/VHilklJWV8dlnn7F582YAAgMDGTNmDG3btq32a4mIiIjUNIZhUPTD8G97C7WYEhERqc2WJh1i/Y6jANw/ujPd22lGRk1S+fiDl5TPykhLS6uwfuTIkQr3n+/48eO0bt3aXcgA18mOq666ioMHD3owrYhI7XHstKsobLVa8LFZ8bFZeH3yIFp7oLfj2bNnef/9992FjJYtW/L73/9ehQwRERG5YpSdO4EjPwuAABUzREREaq3t+0/xr1WuDQrXXRXJzde2MjmR/JRpJzOio6OJjIxk9erVDBkyxL2emJhIy5YtCQ+v3Gc0JiaGpUuXkp2dXaGgsXPnTiIiIrySW0SkpjIMg7PZRTh/aNf3x7t60b+b53o2G4bB0qVLycjIwGKxMGjQIAYOHHjBNoEiIiJSNxhOB0ZZKVY/u9lRaozCI64WU9aAEHwbR5qcRkRERC7H8TN5/PWDrTgNaBNVn0njuqt1ZA1kWjEDYNKkSUybNo3Q0FDi4uJYt24dCQkJvP766wBkZmaSlpZGmzZtCA4O5r777mPFihVMmDCBBx98ELvdzvLly9m8ebP7OSIiV6LsvGLu+tNqr17TYrFw0003sWDBAm666Saio6O9en0RERHxvtOr/kHeng2E3zUDe2Ss2XFqhPLh3/aoDlgs2tQhIiJS2xQUlfKX2ZvJLyylfrA/0+/t7bF5o/LrmFrMiI+Pp6SkhNmzZ7Nw4UKioqJ4+eWXGTFiBABJSUlMmzaNefPm0adPHyIjI/noo4945ZVXeOqpp7BarbRr1445c+bQr18/M9+KiIhp9qVk8sc3v6yw5u9no1VE6EWecfkyMjKw2Ww0btwYgCZNmjBp0iSdxhAREbkCGE4H+Xs3gqOMnO2JKmb8oOiH4d8B0WoxJSIiUts4nQavf7Sd9JO5+NgsPHXv1TRuEGB2LLkIU4sZAOPHj2f8+PEXvC8+Pp74+PgKa61bt+btt9/2RjQRkRrvv9+k8ubCnRXWXp88iPBGQQTafavtOoZhsGXLFhITEwkLC+N3v/sdvr6u11chQ0RE5MpQeuYoRlkJAAXfb8VwlGGxmf4rpalKs05RlnMGAHuLjianERERkUu14LNkvvkuA4AHb+lKp1YNTU4kP+fK/uQpIlJLORxOjp/Jr1DIaB/dgBcnDcDHVr3FhcLCQlasWMH+/fsBKCsrIzc3l7CwsGq9joiIiNRsxScOuf/dWZRHUdpeAmK6mpjIfOUtpqz+gfg1UctNERGR2uSb707wYWIyAMOuacnwa1qaG0h+kYoZIiK1jGEYPPH3L/k+Pcu9NrhXFP8zvke1D6dKT09n8eLFZGdnA9ClSxdGjhyJv79/tV5HREREar7zixkA+Qc2q5jxQ4spe1QHLFb11hYREakt0jJyeO3DbQB0jAnjwTFdTE4kVaFihohILbJlbwZb9p2sUMgIDfbjt6M7VWshwzAMNmzYwOeff45hGPj6+jJ8+HC6d+9e7QUTERERqR3KixlWezDOojzykzfT8MYJV/Rng8LyYoZaTImIiNQaeQUl/GXOZgqLHTQKtfPUvVfj66MW2rWBihkiIjXYB6v3sX3/KQAcToPDx7Ir3P/MhD50b9ek2n/o7tixg3Xr1gGuId+33nqre+i3iIiIXHkMRxklJ1MBqH/NGDI//wBH7lmKTxzCHt7G3HAmKcs5S9k5V49tewsN/xYREakNHE6DV+Zv48SZfPx8rEy/vzcNQuxmx5IqUjFDRMRkOfklTPhLIkUljio/p1VEKL07NqNXh6Ye2Q3ZrVs3duzYQbNmzbjxxhvdw75FRETkylRyOh3DUQpAcOdryd31OaVnj1GQvOmKLWaUt5iy+NrxbxZjchoRERGpin9/ute9afTh27rTNqqByYnkUqiYISJikr0pZ9mXksncVXt/8bHjrm9LkN1VUIhuXo9eHZpWaxaHw0FaWhoxMa5fxG02G/feey8+PvoxISIiIj+2mLIF1ccWEkZQbB+yNi4h/8Bmwq77jcnpzOFuMRUVi8Wmz0wiIiI13frtR1n8+UEAxgxqzXVXRZmcSC6VPnGJiJhg7so97h+g5/vLxH5YftIxKqppiEePPGZlZbF48WKOHTvGfffdR4sWLQBUyBARERG38mKGX7NWWCwWAn8oZpSeOUrJ2WP4NYwwOaH3FaXtAdRiSkREpDY4dDSLNz7+FoDu7Rpz30jNu6qN9E2ViIiXOJ0GJaUOjp7Oq1DIaBIWSM/YJjw0tqvXB2ju27ePFStWUFRUBMDRo0fdxQwRERGRcuXFDP/mrd3/awsJw5GbSUHyJvz6xZsZz+vK8rIoPXsMgAAN/xYREanRsnKLeX7uZkpKHTRrGMgf7+6FzaaB37WRihkiIl5QUFTKo68mcTKzoML6w+O6MbRvS6/nKSsr47///S9bt24FICgoiFtuuYXWrVt7PYuIiIjUbEZZKSWnjgA/FjMsFgtB7XqTs201+cmbqX+FFTOK0vcBYPHxw7/5lTkzREREpDYoczh5ad4WTp8rxO5n4//d34eQQD+zY8llUjFDRMQLPl5zoFIhI7xREEN6R3s9y5kzZ1i0aBEnT54EICYmhvj4eIKDg72eRURERGq+ktNp4CwDfixmAATF9iFn22qKj39PWc5ZfOo1NCui15W3mPKPaIfFx9fkNCIiInIx7y3/jj2HzwIw+Y6eRDevZ3Ii+TUuuZixbt06kpKSOH78OFOmTCEgIICvv/6asWPH4u/v74mMIiK1ltNp8NK8LXy9+4R77ZVHB2K1WGjRLASr1bttpYqKinj//fcpKirCYrFw3XXX0b9/f6xWHa8UERGRC3MP/w5ugE9ImHvd3qIjVnswzqI88g9sIbTXMLMiel15MSNA8zJERERqrMRNR1j1VQoAtw9pR7+u4SYnkl+rysWM0tJSHn30UZKSkrBarTidTiZMmEBqaiozZsxgyZIlvP/++4SGhnoyr4hIjZCZU8RL/9rC6azCn33cmZ/cf/+oTrSPDrvIoz3Pbrdz7bXX8s033zB27FjNxxAREZFf9NN5GeUsNh8C2/Yib3cSBQc2XTHFDEdBLiWn0gCwt+hgchoRERG5kP2pmby1eCcAfTo1484b25ucSKpDlbfivvXWW6xfv54ZM2awdu1aDMMA4MYbb+Tpp59m//79zJo1y2NBRURqkjWb09iXmsmZrMKf/ed8f37wGuKv835P5ZMnT1JWVua+3bdvX/7whz+okCEiIiJVcrFiBkBQu94AFB7Zg6Mwz6u5zFI+LwObD/4R7cwNIyIiIpWczS7khbmbKXMYRDUNZsqdPb3eGUM8o8onM1asWMHYsWMZN24c586d+/EFfHy4++67SUlJYe3atUyfPt0jQUVEaopjp/NY8vn37tuT7+jxC8+w0Ll1Q5o0CPRssJ8wDINNmzbx2WefcfXVVzNsmGu3pMViwW63ezWLiIiI1E7OshLXzAwuXMwIaN0di48fRlkJBQe3EdJlkLcjel15iyl7eFusvmq1LCIiUpOUlDp4Ye5mzuUWE2T34en7+xBo13yruqLKxYyMjAw6d+580ftjY2NZtGhRtYQSEampCopKeX7OJvKLymgQ4s/rkwfRMDTA7FiVFBQUsHz5cg4cOADAwYMHKSkpwc/Pz+RkIp6xcuVK3nrrLdLT04mIiGDixImMGTPmoo/fv38/r7zyCtu2bcPf359Bgwbx+OOP07RpUy+mFhGp+UpOHgGnAwC/ZpWLGVZffwJadafgwGbykzddEcWMwrS9ANij1GJKRESkJjEMg38s3smBtCwsFnji7l5ENA42O5ZUoyoXM5o2bcrhw4cvev+uXbto3LhxtYQSEamJnE6D1z7cTvrJPHxsFqbd27tGFjKOHDnCkiVLyMnJAaBbt26MGDFChQypsxISEpg6dSr33HMPAwcOZM2aNTz55JPY7Xb3iaTzpaWl8Zvf/IZGjRoxY8YMQkNDmTt3LnfccQfLli2jXr16JrwLEZGayT38O6QhPsH1L/iYoNg+FBzYTOHhb3GWFtfp0wrOonxKTqYCYI/W8O/a4lI2PTz11FMsXbr0oq+VnJwMQFlZGW+++SZLly4lKyuLTp068dRTT9G1a1ePvAcREflln2w4zNot6QDcM6IjV7XXZrW6psrFjFGjRvGvf/2LQYMG0aGDaweKxeLqNTZ//nyWLl3K/fff75mUIiI1wH8+S2bTngwAfh/flQ4x5g3yvhCn08mGDRtISkrCMAx8fX0ZOXIk3bp1MzuaiEe99tprDB8+3N3qcuDAgWRnZzNz5swLFjPmzZtHWVkZc+bMITw8HHDNkhk2bBjvvfceU6ZM8Wp+EZGarCTj4vMyygW2vQosVozSYgoP7yQotre34nld0dH9YDjBYsUeGWt2HKmCS9308NBDDzF+/PgKa0eOHOGpp57itttuc689//zzLF26lKlTpxIeHs6cOXO47777WL58OVFRUR5/XyIiV7riUgc5eSVk5xeTk1/C8dN5vL/C1QpyYPcIxpows1Q8r8rFjEmTJrFz504mTJhAWFgYFouFZ599lqysLLKysujSpQuTJk3yZFYREdN8vfs4HyW6dmEN79eSoX1bmhvoAlavXs2WLVsAaNasGbfeeisNGzY0OZWIZ6Wnp5OWllapADF06FASEhJIT0+v9IVCSkoK7dq1cxcyAPz9/enSpQvr169XMUNE5Dw/N/y7nC0gBHt0J4pSd5N/YHOdLmaUt5jyb94aq1/NO6ErlV3qpocWLVrQokUL922Hw8Fzzz1H+/btefrppwE4evQoCxYs4H//93+54447ABgwYABDhw7lvffe489//rMX3pmISN3hcBrkFZSQk1/+TzHZeT/eLi9Y5OQV/3C7hOISxwVfKya8Ho/e1t29CV/qlioXM/z8/Jg9ezbLli0jMTGR9PR0HA4HnTp1YvDgwYwbN04tTESkTjqSkcPrH20HoGNMGL+7uYvJiS6sT58+7Ny5k+7duzNkyBB8fKr8V7xIrVXeAjMmJqbCenR0NOAqXPy0mNG8eXO+//57ysrKKvx3cvToUdLT0z2cWESk9nCWFlNy2vX34s8VMwCC2vWmKHU3Bd9vxXA6sFht3ojodUVHfhj+3aKjyUmkKi5n08NP/ec//2Hv3r0sWLDA/Z3HN998g8PhYOjQoe7H+fn5ERcXR1JSUrW/DxGRusQwDJYmHWTz3pNk/1CcyCsowWlc/mvarBbqBfnRsnk9Hh7XHbu/vg+pq6r8/+zx48cJCwsjPj6e+Pj4Svfn5uayc+dOrr766moNKCJipryCEp6fs5nCYgeNQu08de/V+PpYzY4FuHaJ5ebmUr++q391w4YNefjhhwkJCTE5mYj35ObmAhAcXHGoW1BQEAB5eXmVnjNmzBgWLVrE008/zWOPPYa/vz/z5s1zFzhERMSl5GSqq6USVShmxPbmbOL7OAtzKUrbS0DLmrn549dwlhRSnOEqoge00LyM2uByNj2cLz8/nzfeeIObb765wiyMw4cPExoaSlhYxbaz0dHRHD9+nKKiIux2e3W9DRGROmX1N0eYs3Lvzz4m0O5DaJA/9YL8CAnyIzTYj3pB/oQG+VEvyI/QYNd99YL8qBfsT5DdRycxrhBVLmZcf/31vPLKK4waNeqC9//3v//l+eefZ8eOHdUWTkTETA6nwSvzt3HiTD6+Plam39+bBiE145eSc+fOsXjxYgoLC3nwwQfx93cN2lQhQ640huHavvPTD67l61Zr5eJjr169eOGFF3jxxRdZtmwZFouFIUOGcMcdd7Bw4ULPhxYRqSXKW0z5hDbGFljvZx/rU68R/s1bU3ziEPnJm+tkMaMwZRc4Ha55GVHtzY4jVXA5mx7Ot3jxYnJycpg4cWKF9by8vEqvef7r5ufnq5ghInIBx8/k8f6K7wDo3q4xfTs1o16QP/WC/X4sTgT515hNpFLzXLSYcezYMZYuXeq+bRgGiYmJpKamVnqsYRisW7fO/WWaiEhd8O9P97J9/ykAHh7XjbZRDUxO5LJnzx4++eQTiouLATh06BAdO6rVgVyZygt4P/0yIj8/v8L9PxUfH8/NN99MWloaISEhNGrUiGnTprlPOomICBRXYfj3+QJj+7iKGQc20/DG39a5HZK5u9cDEBDTBas9yOQ0UhWXs+nhfPPnz+f666+vdLKj/PlVvZ6IiLg2jP7fRzsoLnHQMNTOk3f3IjhQIwvk0ly0mBEeHs769evZvXs34PphnJiYSGJi4gUfb7VamTx5smdSioh42Zc7jrH484MA3HRtKwb3avELz/C80tJSVq9ezfbtrvkdwcHB3HLLLbRq1crkZCLmKf9yIS0tjdjYWPf6kSNHKtx/vkOHDvHdd99x8803V7h/7969KgyKiJynKsO/zxcU24dzSR/iyDlDScbhKj+vNnAU5FLw/TYAQrpcZ3IaqarL3fQAsH//flJTU5k6dWql+4KDg92vcaHXvdCpDRGRK93SpIPsS80E4LHbe6iQIZflosUMi8XCnDlzyM7OxjAMbrjhBqZPn871119f6bE2m4369evrGKWI1AmHj2XzfwtcLfO6tmnEb0eZ3xP51KlTLFq0iNOnTwPQunVrxowZo1+U5IoXHR1NZGQkq1evZsiQIe71xMREWrZsSXh4eKXnJCcn88c//pGePXu6+2Rv2rSJ/fv3c99993kruohIjeYsKaT0zDEA/KpYlPBtGIFvWDilmcfJT95Up4oZeXs3gLMMi18AgbG9zY4jVXQ5mx7KJSUlERgYyKBBgyrd16pVK7KyssjOziY0NLTC60ZGRroHhYuIiEvK8Wzmr94PwMj+MfSIbWJyIqmtfnZmRnBwsPuLsnnz5tG6dWsaNmzolWAiImbIzivm+TmbKCl10CQskD/e3QubzdxejSdOnGD27NmUlZVhtVoZPHgw/fr10/F1kR9MmjSJadOmERoaSlxcHOvWrSMhIYHXX38dgMzMTNLS0mjTpg3BwcHExcURGRnJlClTeOSRR8jMzOTFF1+kW7dujB492uR3IyJSM1QY/t2saqdALRYLgbG9yf56GfnJmwiLu9ODCb0rb1cSAMEdrsHqq/bKtcXlbHoo9+2339K5c+cLFib69esHuGaH3nbbbQCUlJSwfv16BgwYUM3vQkSkdistc/Dah9spczgJbxTEfSN1Gl4uX5UHgPfu7dp9kpOTQ0FBAU6n032fw+EgPz+fb775RjsaRaTWcjic/PXfWzl1rhB/Pxv/7/7ehAab/8tq06ZNiYyMJCsri7FjxxIZGWl2JJEaJT4+npKSEmbPns3ChQuJiori5ZdfZsSIEYBrZ+W0adOYN28effr0ITAwkPfee4/nn3+eyZMnExAQwIgRI5g8eTI+PlX+aCQiUqe5h3/Xb4ot4OKteH4qKLYP2V8vo/TMUUrOHsev4cW/LK4tSs4cpfiEq/1ocNc4c8PIJbvUTQ/lDhw4cMFTGQARERHccsst/OUvf6GgoIDo6Gh3Z4sHHnjAK+9LRKS2+CgxmdQTOVgtMPnOntj99TuXXL4q/+k5efIkf/zjH9m8efPPPk7FDBGprWav3MOug2cAV//GmPDQX3iG5+Tl5bl/mbJarYwdOxYfHx+18xO5iPHjxzN+/PgL3hcfH098fHyFtZiYGN577z1vRBMRqZUudV5GOf/wNtiCw3DkZVJwYDN+14zxRDyvytudBIBPaBPsUR3MDSOX7FI3PZQ7e/Ys9erVu+jrzpgxg3r16vHuu+9SUFBAp06dmDNnDtHR0R5/TyIitcW+lEwWr/segLGD29I+OszkRFLbVbmY8de//pXNmzczYsQI/Pz8WLp0KRMnTiQzM5PExESKi4uZO3euB6OKiHjOuq1prPjiMAC3Dm7LwO4RpuQwDINvvvmGtWvXcuedd7qHe2s2hoiIiHjT5RYzLBYrQe2uJmf7f8lP3kT9Wl7MMJwOcnevByC4yyAsFnPbj8rludRNDwA7d+782df08/Nj+vTpTJ8+vVoyiojUNUXFZbz+0XacBsSE1+OOG9ubHUnqgCp/Evv6668ZM2YMr776Kk8//TQWC/+QygAAIABJREFUi4WBAwfy3HPPsWzZMgIDA/nss888mVVExCMOpJ3jzYWuX1auat+Eu4abs+MuPz+fjz76iMTERBwOBxs2bDAlh4iIiFzZnMWFlJ49Dlx6MQMgMNa1u7342AHKcjOrNZu3FR75DscP7yFELaZERESqbM7KPZw4m4+PzcqUO6/C10cbAuTXq/KfopycHHr27Am4dgiHh4fz3XffAdC8eXPGjRvHunXrPJNSRMRDzuUW8cLczZSWuQZRTb2rFzar9wdrp6am8s477/D9967jlz169Ljo7jERERERTyo+eRgwAPCr4vDv8wVEd8JqDwKg4MCW6ozmdeWDv/0j2+PboJm5YURERGqJ7ftP8enGVADuGtaels0v3rZP5FJUuc1UaGgohYWF7tstWrQgOTnZfTsqKoqMjIzqTSci4kGlZU5enLuFs9lFBPjbePr+3gQH+Ho1g9PpZP369XzxxReA67j6qFGj6NKli1dziIiIiJQrbzHlG9Yc2w9FiUthsfkQ2OYq8r77gvwDm6h31dDqjugVzuJC8pM3ATqVISIiUlV5BSXMXLADgA4twxgT18bkRFKXVPlkRs+ePVmyZAm5ubkAtGvXjk2bNlFcXAzA7t271dNdRGqVfy7bzb5UV9uAKXdeRYtm3t0pYBgGH374obuQ0bx5cyZOnKhChoiIiJiqvJjhdxktpsoFxvYGoDD1OxxF+dWSy9vy93+NUVqMxeZLcId+ZscRERGpFd5espvMnCLsfjYm39HTlO4XUndVuZjxhz/8gZSUFAYNGsS5c+e47bbbOHnyJPHx8fzud7/j448/Ji4uzoNRRUSqz+qvU0n4OhWAO2+MpW/n5l7PYLFYiI2NBaBPnz789re/JSwszOs5RERERM5XcpnDv88X2KoHFh8/cDooOLituqJ5Ve7uJMBVmLFexgkVERGRK82GncdYv+MoABNu6kzzRvr5KdWrym2mOnbsyMcff8xHH31EgwYNaNCgAbNmzeK5555jx44dDB8+nCeeeMKTWUVELtmho1nM/+9+iksc7jXDgH2pZwHo27kZtw+J9VqesrIyDMPA19fVzqpXr16Eh4cTERHhtQwiIiIiF+Msyqc08wQA/s0uv5hh9bMTENONgu+3UJC8mZDO11ZXRK8ozTpF0ZE9AIR0iTM3jIiISC2QmVPEPxbtAuCq9k0Y2jfa5ERSF1W5mAEQGxvLs88+674dFxdX4TRGaWlpdeUSEflVvtp1nLcX7yIrr/iij4lqGsLkO3pi9dKRx8zMTBYtWkTz5s0ZPXo04DqdoUKGiIiI1BTFGYd/+DcL/s1iftVrBcX2dhUzDu3AWVqM1df/1wf0krzvXG1AbUH1CWjVzeQ0IiIiNZthGPz942/JLSghOMCXR27rjsWi9lJS/apUzMjPz8cwjJ+dibF9+3aeeeYZVq5cWW3hREQuVWFxGVv3neSv/95aYd3Px8ot1/04dCrQ34frr25BoN07A793797NypUrKSkpISMjg759+9K4cWOvXFtERESkqtzDvxuGY/UP/FWvFdi2F1isGKVFFKbsIqjd1dUR0eMMwyDvhxZTwZ2vxWK1mRtIRESkhkvclMbWfScBeGhsNxqGBpicSOqqny1mfPrpp/zjH//g0CHXB9qoqCgeffRRRo0a5X5Mfn4+f/vb31iwYAGGYXg2rYjIL5izcg8JG1Pdt5s1DOSx23vQMaah105gnK+kpISEhAS+/fZbAEJCQoiPj1chQ0RERGqk4mqYl1HOFlgPe4sOFB3ZQ37y5lpTzCg+luxutRXSNc7cMCIiIjVcxtl83l+xG4Bru0cwsIe6T4jnXLSY8cknn/DEE09gt9sZMGAAAQEBbN26lSeeeAKbzcbw4cPZsWMHjz/+OMePH6dFixb8+c9/9mZ2EZFKzmQVAhDgb6NpWBCP3Naddi0amJLl5MmTLFq0iDNnzgDQtm1bbr75ZoKCNABLREREaqbqLGYABMX2oejIHgq+34LhdNSKUw65u9YD4Nc0Br8m6vctIiJyMQ6nwf/9ZweFxQ7C6vnz+7FdzY4kddxFixnz58+nUaNGfPzxx4SHhwNQVFTEpEmTePPNN2nUqBEPPPAADoeDiRMn8tBDD+HvX3t6oIpI3WAYBqkncigtc7Jmcxpb9rqONQ7t25IJN3U2Ldf+/ftZvHgxZWVlWK1WbrjhBvr27auekSIiIlJjOQrzKMtyfZaqrmJGYLurOZs4G2dhLkXp+wmI7lQtr+spzrIS8vd9BehUhoiIyC9Z8cUh9hw+C8Ajt/UgJNDP5ERS1120mHH48GHuuecedyEDwG63M2nSJO68806mTJlCs2bNePXVV+nc2bwvDEXkypCZU8SmPRk4Hc4K6/9c/h0OZ+UWd5FNQrwV7YKaNm2KzWYjJCSEsWPHasi3iIiI1HjFGa5TGVis+DVtWS2v6RvaBL9mrSjJOEx+8qYaX8woOLAFZ1E+WG0EdxpodhwREZEa68iJHOZ9ug+AYde0pFeHpiYnkivBRYsZubm5REVFVVovXwsNDeXDDz+kXr16nksnIgLsT83kib9/WeXH/3Z0J27s08KDiS6srKwMHx/XX6sNGjTgN7/5DY0bN8Zut3s9i4iIiMilKikf/t0oAqtf9Q3uDIrtQ0nGYQqSN2EMub9Gn1TN2+1qMRXYuge2oFCT04iIiNRMpWVOXvtoO2UOJ80aBvLb0TV7s4LUHRctZhiGgdVqrfyEH76oe+CBB1TIEBGPKy518ObCbyusRTWteOoi0N+HP4ztSkTjYGw2K74+lf/u8iTDMNi4cSPbtm3jd7/7HQEBrl/+L1QQFhEREampqnteRrmg2N6cW/8RZTlnKDmZgn+zVtX6+tWlLC+LgkM7AAjuEmduGBERkRpswWfJHD6WjcUCk+/oSYD/Rb9iFqlWl/0nrWlTHR0SEc+a/ckeliYddN8OtPsw539vJNDua2KqivLz81m6dCmHDrl++f/iiy8YOnSoyalERERELl3xicMA+Der3mKGb6MofBo0o+xcBvnJm2psMSNvzxdgOLHagwlq28vsOCIiIjVS8pFMFq77HoD4uDZ0jGlociK5knh3+7KIyCX4ZvcJ979bLPDMhL41qpBx+PBh3n77bXcho2fPngwePNjkVCIiIiKXzlGQQ1n2KaD6T2ZYLBaCYvsAkJ+8uVpfuzrl7XK1mAru2B+LT835zCkiIlJTFJWU8fpH23E6DaKbhfCbYe3NjiRXmJ89mfHxxx+zcePGCmslJSVYLBbef/99VqxYUeE+i8XCCy+8UP0pReSKsXXfSdZsScMwDDJziwAYd31bhl8TQ+MG1de7+ddwOp0kJSXx5ZeuOR7+/v6MGjWKzp07m5xMRERE5PKUt5iqzuHf5wuK7UP2N8spPZ1GaeYJfMOaV/s1fo3ik6mUnEoFILhrnKlZREREaqp/rdrLsdP5+NgsTLnzKnx9bGZHkivMzxYztmzZwpYtWy5434YNGyqtqZghIr/Wu8t2c+JMfoW1VhGhNaaQUVRUxIcffkh6ejoA4eHh3HrrrTRo0MDkZCIiIiKXr7yY4dc4Cquvf7W/vn9EW2xB9XHkZ5F/YDP1+95c7df4NfJ2fQ6Ab1g4/uFtTU4jIiJS83x74BQrN6QAcOfQ9rSKCDU5kVyJLlrMWLt2rTdziIhQUFTqLmR0b9uYiCbBNAy107tjM5OT/cjf3x9/f9cv+Ndccw3XX389Npt2IoiIiEjtVpzhmpfhV83zMspZLFYC2/Umd0ci+cmbalQxw3A6yNvjOnEb3DUOi8VicqIr2+TJkxk1ahTXXnstvr5q9yUiUhPkFZYy8z87AIiNbkB8XBuTE8mV6qLFjIiICK8EWLlyJW+99Rbp6elEREQwceJExowZc9HHO51O3nnnHRYtWsTp06eJjo7m97//PSNHjvRKXhHxjMPHsnnstST37et7tyCuZ6R5gc7jdDqxWl0jhiwWC2PGjOHEiRO0aaMf3iIiIlI3lJ/MqO55GecLinUVM4qPHqAs7xw+wTXjZGvhoW9x5GcDFkI6X2t2nCveli1bWL16NSEhIdx4442MGjWKPn36qMgkImKify7bzZnsIvz9bEy5oyc2m8YwizlM/ZOXkJDA1KlT6d+/P7NmzaJ37948+eSTrF69+qLPeeGFF/jHP/7BXXfdxTvvvEO3bt14/PHHWb9+vReTi0h1+mLH0QqFDICubRqZE+Ynzp49yz//+U8OHDjgXgsKClIhQ0REROqMsrwsHDlnAM8WMwJadsbiHwgYFBy4cDtjM+TudrWYsrfsjE9oY5PTyJdffsmcOXMYNmwYa9eu5f7772fgwIG8+OKL7Nq1y+x4IiJXnI27jrNuq6vV9v2jOhHeONjkRHIl+9mZGZ722muvMXz4cKZPnw7AwIEDyc7OZubMmQwbNqzS49PS0pg/fz4zZsxg3LhxgKvNS2pqKl9++SWDBg3yan4RuXyzP9nDms1HMAzXccVyTRoEMOuJwdj9Tf3rCYCdO3eyatUqSktLWbFiBY899piOuouIiEidU5Lxw/Bvqw2/ptEeu47F5ktgm57k79lAfvJm6vW80WPXqipHYR4FB7YCENIlztwwArhOQvft25e+ffvypz/9iQ0bNpCQkMDy5cuZN28ekZGRjBo1itGjR9OqVSuz44qI1FnFpQ6+2H6UOSv3AtC9XWNG9Gtpbii54pn2bWF6ejppaWlMmTKlwvrQoUNJSEggPT2dqKioCvetWbMGu91eqQ3VBx984PG8IvLrnckqZM/hswAsTTpY6f7h17RkYnxXbFZzj5CXlJTw6aefsnPnTgDq1atHfHy8ChkiIiJSJxWf+GFeRuMWWH38PHqtoNg+5O/ZQGHqbpxF+VjtQR693i/J37cRw1GKxddOUPs+pmaRymw2G4MGDWLQoEGkpKTw97//nU8//ZS33nqLt99+m27duvHAAw9www03mB1VRKTOyDibz6cbU1mz+Qi5Ba7Np0EBvjx2ew+1/BPTmVbMOHzY9YE5Jiamwnp0tGsnUEpKSqViRnJyMjExMWzcuJFXX32VgwcPEhkZyf/8z/8wYsQI7wQXkctiGAZ/fPNLTp8rrLA+7JqW9GjXmGYNg2gVEWpSuh9lZGSwaNEizp51FV1iY2O56aabCAwMNDmZiIiIiGd4Y15GucDWPbDYfDEcpRQc2k5wp4Eev+bPyd2VBEBQ+75Y/QJMzSKVHTx4kNWrV5OQkMDhw4ex2WzExcUxevRoLBYL//nPf3jkkUd4+OGHmTRpktlxRURqLafTYHvyKVZ9lcK2/ScxDNe6j81C/64R3HZDWxrV189JMZ9pxYzc3FwAgoMr9lkLCnLtzMnLy6v0nMzMTE6cOMH06dN57LHHiIyMZOHChUyePJmwsDD69u3r+eAictnKCxnBAb74+lgJbxzMhNGdakRLKYBt27aRkJCAw+HAZrMxZMgQevfurZ0HIiIiUqd5s5hh9QsgIKYrBQe3kZ+8ydRiRmnmcYqPJQMQ0jXOtBxS0aFDh0hISGD16tUcOuT6s9mzZ0+eeeYZhg8fTv369d2PHTFiBLfddhtz585VMUNE5DLkFZSwZksan36Vyomz+e71RqF2hvVryY19omkQYjcxoUhFl/wN4rp160hKSuL48eNMmTKFgIAAvv76a8aOHYu/v3+VX8f4ocT30y8Jy9et1sqzyUtLS8nMzOTtt9/muuuuA1wzMw4fPsybb76pYoZILTH9/t50aV0zBnyfz2az4XA4CAsL49Zbb6V58+ZmRxIRERHxqLLcTBx5mYB3ihkAgbG9KTi4jYJDO3CWlXi8tdXF5O5aD4CtXiPs0Z1MySCVjRw5EoB27doxefJkRo8e/bOfy5s1a0ZJSYm34omI1AmHjmax6qsU1u84Rkmpw73etU0jRvaPoU+nZthslb+bFTFblYsZpaWlPProoyQlJWG1WnE6nUyYMIHU1FRmzJjBkiVLeP/99wkNrVqbmJCQEKDyCYz8/PwK958vKCgIm81G//793WsWi4V+/fqxaNGiqr4VERE3wzDcRdVu3bpRVlZGly5dLqk4KyIiIlJblZ/KwOaDX+MWXrlmUNurOWN5B6OkiKKU3QS2vcor1z2fYTjJ250EQEjna7FY9IVNTfHggw8yevRo2rZtW6XHv/7669hsNg+nEhGp/UrLnHy16ziffpXCvtRM93qAv43BvVowol9LWjSrZ2JCkV9W5U9sb731FuvXr2fGjBmsXbvWfYLixhtv5Omnn2b//v3MmjWryhcun5WRlpZWYf3IkSMV7j9fdHQ0TqeTsrKyCuulpaVqAyNSQ329+zhvLvyWNxfuNDtKBU6nky+++IIVK1a41ywWC7169VIhQ6QWWrlyJSNHjqRr164MHz6cZcuW/ezjMzMzmTZtGgMGDKB3795MnDiR1NRU74QVEalBijPKh39HY/Hx9co1bUGh2KPaA5CfvMkr1/yporS9lOWcASBYLaZqlClTphAUFMTf/vY3srOz3evvvvsuL730knu2XTkVMkREft6ZrEI+SNjHb59L5NX529yFjKimwfw+vitznxnK7+O7qpAhtUKVT2asWLGCsWPHMm7cOM6dO/fjC/j4cPfdd5OSksLatWuZPn16lV4vOjqayMhIVq9ezZAhQ9zriYmJtGzZkvDw8ErPGThwIO+//z4JCQmMHTsWgLKyMr788kuuusr7u3lE5OeVljn52wfbKClzVlgP8DN3RkZeXh5LliwhJSUFgLZt29KxY0dTM4nI5UtISGDq1Kncc889DBw4kDVr1vDkk09it9sZNmxYpccbhsGkSZNIS0vjiSeeoH79+rzxxhvcc889fPLJJ1U+ZSoiUheUeHFexvmCYvtQlLaX/O+30MjpwGL17hfS5YO//cPb4tcwwqvXlp934MAB7r77bvLy8hg1apT753JOTg4ffvghq1at4sMPPyQqKsrkpCIiNZdhGOw+dIaVG1LYtCcDp7O8rb+Fvp2bMbJ/DF1aN9LmcKl1qvyNYkZGBp07d77o/bGxsZfc6mnSpElMmzaN0NBQ4uLiWLduHQkJCbz++uuAa9dkWloabdq0ITg4mGuuuYZBgwbxl7/8hYKCAlq2bMmHH37IsWPHePXVVy/p2iLieQ6n013I6NGuMSFBfrRoGkLrSPO+KDx48CDLli1zt7Tr1atXlY+wi0jN9NprrzF8+HD3hoqBAweSnZ3NzJkzL1jMSE1NZfv27bz88suMGTMGgNatW3PDDTewbt06brnlFq/mFxExi2EYXh3+fb7Adr05+9kcnAU5FB1NJqCF9zaWOEuKyN//NaDB3zXRq6++SlBQEAsWLKBly5bu9alTp3L77bdz77338re//Y2ZM2eaF1JEpIYqKCrl863prNqYSvrJXPd6/RB/hvaJZtg1LWlUP8DEhCK/TpWLGU2bNuXw4cMXvX/Xrl00btz4ki4eHx9PSUkJs2fPZuHChURFRfHyyy8zYsQIAJKSkpg2bRrz5s2jT58+ALzxxhvMnDmTd999l+zsbDp27Mjs2bN/ttAiIuY4dPTHY+F3De9AuxYNTMvicDj4/PPP+eqrrwCw2+3cdNNNdOjQwbRMIvLrpaenk5aWxpQpUyqsDx06lISEBNLT0yvt3CwuLgZcs7jKle/6zMrK8nBiEZGaw5GbiSPf9feet4sZvvWb4Nc0hpKTKRQkb/JqMSM/eRNGSRHYfAjq2P+XnyBe9e233/LQQw9VKGSUi4qK4q677uK9997zfjARkRrMMAxWfZXCvE/3UVj8Y3v+Di3DGNk/hn5dw/H10Xwoqf2qXMwYNWoU//rXvxg0aJD7y7/yo0jz589n6dKl3H///ZccYPz48YwfP/6C98XHxxMfH19hzW638+STT/Lkk09e8rVExHvKHE6eeWej+7bNat7RxezsbBYtWsTRo0cBiIyMZOzYsdSvX9+0TCJSPco3Wvx01lZ0dDQAKSkplYoZ7du3p0+fPsyaNYtWrVrRoEEDXnrpJQIDA7nhhhu8E1xEpAYoP5Vhsfni19j7LXuCYntTcjKF/OTNhN1wn9daXZQP/g5q2wtbQIhXrilVZxiGe+PBxe4vKiryYiIRkZrtbHYhbyz4lu3JpwDw87UR1zOSkf1jaBWhFrpSt1S5mDFp0iR27tzJhAkTCAsLw2Kx8Oyzz5KVlUVWVhZdunRh0qRJnswqIjWc02lQUFTKO8t2syP5lLvFVMvm9YgJN+8HqMVicQ8KHDBgAHFxcRoUKFJH5Oa6jk4HBwdXWC8/dZGXl3fB5z377LM88MAD7tOgfn5+zJo1S/23ReSKUl7M8GvaEovN+zPNgmL7cO6LBZRln6LkZCr+zWJ++Um/UlnOGQpTdgMQ3CXO49eTS9etWzcWLFjA+PHjqVev4jDa/Px8Fi5cSLdu3UxKJyJSs3y18zizFn1LbkEpAIN7RfHAzZ0JCfQzOZmIZ1T5E6ufnx+zZ89m2bJlJCYmkp6ejsPhoFOnTgwePJhx48bh56f/UESuVE6nweMz13PwvNZSAFYLPPu7vlhNPJlRr1494uPjsVgstG7t3RYKIuJZhuEaZPfT3bzl61Zr5aPUhw4dYvz48bRo0YLp06djt9v5+OOPefTRR3nvvffo1auX54OLiNQAZs3LKOfbuAU+9ZtSlnWS/AObvVLMyPvuC8DAGliPwNY9PH49uXQPP/wwd911F6NGjWL06NFER0djsVhIS0tj1apVnD59mhdffNHsmCIipsovLOXdZbtZtzUdgJBAXybd2p3+3cJNTibiWVUuZpw4cYLmzZtfsPWTiMi53KJKhYwHbu5Mh5ZhNAz17nCp06dPk5iYyJgxY9y7s9u0aePVDCLiHSEhrvYgPz2BkZ+fX+H+882dOxeA2bNnu2dl9O/fnzvvvJMXXniBJUuWeDDxLzuQdo4lnx/kN8PaE9VU7U9ExDMMw6A4w9xihsViISi2D9mbVlCQvImwa2/36PUMwyB3VxIAwZ0GmnIaRX5Zt27dmDNnDi+//DKzZ892b1AAV6vIF198kR49VIgSkSvXd4fO8PpH2zl1rhCAnrFNePT27l7/7kXEDFX+9DZ48GB69erF6NGjGTp0qPuXfxGRn3r6/t50bdOIQLuvV69rGAbffvstCQkJlJaW8sknn1x0Jo+I1A3lszLS0tKIjY11rx85cqTC/ec7fvw4rVu3rvBZxmKxcNVVVzFv3jwPJ/5ln29N56tdx8nOL+bFhwaYHUdE6ihHzhmcBTmAecUMwF3MKDl1hNJzGfg2aOaxaxUfP0jp2WMAhHSN89h15Nfr1asXCxcuJDMzk2PHjuF0OmnevDlNmjQxO5qIiGlKyxzMX72fJUkHMQzw87Fy/+hOjOwf47W5UyJmq/IY+4ceeoizZ8/yzDPPMGDAAB566CESEhJ+djCXiFw5HM4fd0xFNQ3xeiGjuLiYpUuXsmLFCkpLSwkNDaV///5ezSAi3hcdHU1kZCSrV6+usJ6YmEjLli0JD698zDomJobvv/+e7OyKp8l27txJRESER/NWRe9Ori/yvjt0loPpWSanEZG6yj3828cP30aRpuXwj2iLLag+AOc2LMJZ4rnBzuWDv/2atMCvqedbWsmvFxYWRpcuXejWrVuFQkZmZuYlvc7KlSsZOXIkXbt2Zfjw4SxbtuxnH+90Onnrrbe4/vrr6dq1K6NHj2bVqlUVHrN161ZiY2Mr/TNx4sRLyiYiUhVHMnJ4fOYXLP7cVchoExnK/02JY9SAVipkyBWlyiczHnnkER555BGSk5NZtWoVq1evZvLkyQQFBTFkyBBGjx5Nv3799B+QyBXo+Ok8Jr601rzrHz/O4sWL3b/UtG/fnptuuomAAB2xFLkSTJo0iWnTphEaGkpcXBzr1q0jISGB119/HXB94ZGWlkabNm0IDg7mvvvuY8WKFUyYMIEHH3wQu93O8uXL2bx5s/s5ZurerjHRzUI4kpHL8i8O8fhvrjI7kojUQT8O/47BYrWZlsNitRHc+VqyN60gb9fnFKbupuGQ+wiK7Vutv1saZaXk7d0AuAZ/6/fWmq18VmdBQQFOp9O97nA4yM/P5+DBg3z33XdVeq2EhASmTp3KPffcw8CBA1mzZg1PPvkkdrudYcOGXfA5L7zwAgsWLGDKlCm0b9+eVatW8fjjjxMcHMygQYMASE5OJjAwkDlz5lR47k+HlouI/BpOp8EnGw7zr1V7KS1zYrXArde3Y/yQWHx9qrxHXaTOuOQmoeW7DaZMmcJ3331HQkICa9euZfny5TRs2JANGzZ4IqeI1FBJ24/y6vxtFdYa1/dOEcEwDDZt2sRnn32G0+nEZrMxdOhQevXqpV9QRWo4wzA4evQoUVFRAKSkpPDxxx/j4+NDfHz8BdtDXUx8fDwlJSXMnj2bhQsXEhUVxcsvv8yIESMASEpKYtq0acybN48+ffoQGRnJRx99xCuvvMJTTz2F1WqlXbt2zJkzh379+nnk/V4Ki8XCmEGtmbngW7789hj3juxIIy/9vSoiVw6zh3+fLyzuTiy+fmR/vRxHzhlOLf4bATHdaDh0An4Nq+fEXMHBbTgL88BiJbjTtdXymuIZ//znP3nttdfw9fUlODiYc+fO0axZM7KysigsLMRut3P33XdX+fVee+01hg8fzvTp0wEYOHAg2dnZzJw584LFjLS0NObPn8+MGTMYN24cANdccw2pqal8+eWX7mLG/v37adu2Ld27d6+Gdy0iUtmZrEL+7z/b2fn9GQCaNQxk8h096RjT0ORkIub5VRPPioqKcDqdGIaBYRj4+GiAmsiVwDAM/p2wj817MjiSketerx/iz/tPD8HP13u7+44cOYLT6aRhw4bceuutNGvmuT7LIlI9MjIymDBhAn5+fixdupQzZ85w++23k5Pj6t3+wQcfMH/+fDp27Fjl1xw/fvxFZ+TEx8c3EglZAAAgAElEQVQTHx9fYa1169a8/fbbl/8mPGxQz0j+9ek+snKLWbnhMPeN6mR2JBGpQ2rC8O/zWXx8CRt0ByFdr+Ns4mwKDm6jMGUnR9+dQmifUTQYcCtWv19X1M39ocVUQKtu+IQ0qIbU4ilLliyhffv2/Pvf/+bcuXMMGTKEefPmER4ezoIFC3juuefo1q1blV4rPT2dtLQ0pkyZUmF96NChJCQkkJ6e7t5YUW7NmjXY7XbGjBlTYf2DDz6ocHvfvn106NDhMt6hiMgv+2LHUf6xeBf5haUADOndggdu7uz1lt4iNc0lVx+2bdtGQkICiYmJnD59mpCQEP4/e3ceV1WdP378dRcuy2UHRXZEVHDDBZc0FVe03LVcxnSmcmra9es01cz8ZmqcrCabLKeaLE1LJ1NzF1fcUnPfRVABWQXhApcL3P38/rh6jXBBBS7g5/l48ODezzn33DcWnHPP+/N5vxMSEvjHP/5B9+7d6yJGQRAczGS28OfPD5Cea6svrzdaqu0zfkBUvd9sk8lkjBo1Ch8fH+Lj41GpVPX6/oIg3J+PPvqIvLw83njjDQB++OEHtFotH3/8MR07dmTGjBl88sknDTrZUNeclApG9GnJd1susOVgBhOHtMXVWUwaEQShdphLC2yrFADnwEgHR3OTk08LWkx8i/LUIxRtX4S5pIDSg2vRnd2L3+Dfoo65v7LGlvJSKi4dB8CjY3wtRy3UtpycHGbNmoW7uzvu7u54eXlx9OhRxo4dy5QpUzh27BhLliy5bYmoX0pLSwOotuIzPDwcsK0M/XUyIyUlhZYtW3LgwAHmzZvHpUuXCAkJ4bXXXrOv+rRarVy8eBEfHx/Gjh3LxYsX8ff3Z9q0afzud78Tq8QFQbhvukoTX6w+zZ4T2QB4qlW89ERnHukY6ODIBKFhqPGn4n/+859s27aNgoICVCoV/fv3Z9SoUfTr10/cQBSEJiw1s5iko1kkZ9y6yd74AVF0at2Mrm2b33J7bbJarezbt4/mzZvbZ0G5uroydOjQOn9vQRBqz/79+5k+fTpPPvkkAElJSQQGBtpvSjz55JN89tlnjgyxQRj2SAQ/7LxIud7M9sNXGNXX8bOnBUFoGuzNv52ccaqlMk61Sd2mO64tO1H68zpKDqzBUqahYM1HuJzYjv/QZ1A1C737QX5Bd/4nsFqQO7vh1kZMwGvolEolarXa/jw8PJyUlBT78549e9a4x1VZmW0Vubu7e5XxG8fX6XTVXqPRaMjLy+Ott97i1VdfJSQkhJUrVzJz5kx8fX3p1asX6enp6PV60tPTmTVrFj4+PuzcuZMPPvgAnU7HK6+8cs8/tyAIwqmL1/j4f8cpLNUDEBcTwCtPdsbH08XBkQlCw1HjZMayZcvo2bMnr776KkOHDq12MSAIQtMhSRKb9qdz7EIBR5Pzq2z707Q4exmpqBBvfOvppFpWVsaPP/5IRkYGzs7OBAYG4u3tXS/vLQhC7SorKyMkJASAoqIizp07Z69JDbYkpdlsdlR4DYaXuzOD4kJJPJjB+r1pPN4nEoVczPQUBOHB2ftltIh0aPPvO5E7OePT90ncO/anaPtiKlKPoM84Q/ZX/4dX98fx6fskcuealZ4qO70HAHVMb+ROznUZtlALWrVqxYkTJ+zXBi1btqzS7Fur1WI0Gmt0LEmSAKqtlLgxLpdXb55rMpnQaDR88cUXDBgwALD1zEhLS2PBggX06tWLgIAAFi5cSExMDM2aNbPvo9frWbhwIU8//bS4ZyIIQo0ZTRa+TUxm7Z7r52eVgmdGdWBYr3Cx0ksQfqXGyYw9e/bYT9KCIDRtl7NL+e+aM1XG/L1c6B0bxKOx9T977+LFi6xdu5aKigoAYmNjxYcDQWjEgoKCSE1NBWDTpk0A9psFAPv27bMnOx52o/pFkngwg3xNBYfO5tG7U5CjQxIEoQm4kcxQNYB+GXfj5B1AiyfeoOLSMQq3LcJcfJXSQ+vRnduH36DpqNs/escbPcZrmRiv9wfx6BRfT1ELD2LcuHG8/fbbGI1G3nnnHQYOHMirr77KggULiIyM5JtvviE6OrpGx/Lw8ACqr8AoLy+vsv2X1Go1CoWCPn362MdkMhm9e/dm1apVgG2lR79+1RvJx8fHs3LlStLT0+nYsWPNfmBBEB5q6bmlzFt2zN6PtE2YN7OmdCO4mbjnIQi3cttkxpEjR2jVqhW+vr4AZGRkkJGRcdcDir4ZgtD45RbevNjv3SmQXh0CGdDt3pbz1waLxcLOnTs5ePAgAC4uLowePbrGH14EQWiYRowYwWeffcaVK1c4dOgQgYGB9O3bl8zMTN5991327Nlj76fxsAtp7kH3dgEcOZ/P2j2XRTJDEIQHJkkSxryG0/y7ptyiuhES0ZHSn9dTsn81Fl0xBes+xuXENvwTnkXVPPyWrys7vRsApU8LnEPENWRjMHnyZK5evcqyZctQKpUMHTqUxx9/nAULFgC2RMLs2bNrdKwbvTIyMzNp27atffzKlStVtv9SeHg4VqsVs9lcpaS2yWSyJ85SUlI4duwYTzzxBE5ON5vx6vW20jA+PqLJvCAId2axSqzbc4lvEy9gtliRy2VMGtyGJwa3QamovmpMEASb2yYznnrqKf71r38xcuRI+/M7zXiRJAmZTEZycnLtRykIQq2TJImjyfkUaCqqjF8rqWT1rksAyGTw5vQejgiP4uJiVq1aRW5uLgBhYWGMGzcOLy8vh8QjCELteemll1AoFGzcuJGuXbvy+uuvo1Qq0el0HD16lOeff57p06c7OswGY2z/KI6czyc5Q8OFKxqiw30dHZIgCI2YufgqVoPt+s+5RcNp/l0TcqUKn0cn4N6xH0Xbv6Ei5RD6zPNkfzUbz7jh+PabiNzlZq8FyWpBd3YvAB4d+4tSHY1EcXExM2fO5OWXX0aptN2ymDdvHpMnT6akpIQuXbrg5+dXo2OFh4cTEhLCli1bGDJkiH1827ZtREREEBRUfZJA3759+frrr0lMTGT8+PEAmM1m9u3bR7du3QBbMuTtt98mICCAQYMG2V+7efNmQkJCCA5ueL1oBEFoOK4WlfPx9yc4l1YEQJC/mllTutJWXOcLwl3dNpkxd+5cOnfubH/+7rvvios/QWgiTGYLf/vyZ85cLrzjfr07Om4GcG5urj2R0bdvX+Lj429Z01YQhMbpD3/4A3/4wx+qjMXExHDw4MEqMxwF6NDKj8hgL9JySlm35zLR08SHHEEQ7p+9+bfKBSe/xrnay8mrOS0mvE5F2kmKtn6NSZOL9sgmys/vx3fgU7hfT1xUpp/GoisGwL1jfwdHLdTU2LFjeeKJJ3jxxRerjMfFxd3X8V588UXefPNNvLy8iI+PJykpicTERHsTcY1GQ2ZmJlFRUbi7u/PII4/Qv39/5syZQ0VFBRERESxfvpycnBzmzZsH2MpJdejQgb/+9a9oNBpatGjBhg0bSEpK4tNPPxX3TgRBuCVJkthyMINFG86hN1oAGPZIBM+MbI+Lc407AQjCQ+22vyljx46t8nzcuHF3PJDFYrHfeBQEoWE7fqGgSiIjNODXtWIlencKYuqwmPoN7Bfat2/P1atXadmyJZGRjWvWoCAINVNZWYmrq615a3FxMZs3b0ahUDBs2DC8vb0dHF3DIZPJGNu/FfOWH+fA6VzyNRUE+Lo5OixBEBqpm82/WyGTNe6JIm6RnXGd8RGlhzdQ/NMqLOUlXNvwKdoT2/FPeJayM7sBcAlrh5N3gGODFWpMo9HUar/OcePGYTQaWbRoEStXriQ0NJT333+fxx57DIDdu3fz5ptvsnTpUnr27AnAJ598wvz58/nyyy8pLS2lXbt2LFq0iA4dOgCgUqlYuHAhH3/8MQsWLECj0dC6dWsWLFjA4MGDay12QRCajmvFlXz6wwlOpF4DwNfThZef7ExcjDg/CcK9kEmSJNVkx5iYGP71r38xYsSIW25ftWoVc+fO5dixY7UaYF27Mbvj6NGjDo5EEOrP7mNZzFt+HIA5z/cmtnXtfVi4XwUFBZw+fZpBgwaJmUyCUMsa2rlOq9Uyc+ZMtFotK1euRKfTMWrUKPLy8pAkiWbNmrF8+XJCQ+u/V8/9qI9/X5PZyox3t1NUqmd0v1Y8O7pDnb2XIAhNW+53/w/9lXN49RyF3+CmU9LPrC2kaMcSypMP2AZkclvNVKsF/8dfwLPzoDsfQLij+ryW+POf/8yFCxeYP38+ISEhdf5+DUVDu14TBKF2SJJE0tEsvlx7hgq9GYD4biE8N6Yj7m6qu7xaEJqW2jjX3XZlRn5+vr3pLth++Y4cOYLZbK62r9VqZcOGDeIGpCA0YBaLlX0ncygs1ZOWUwrYZgI4OpEhSRLHjx9ny5YtmM1mvL2973sJuSAIjcPHH3/MoUOH+P3vfw9g74/z+uuv06FDB/74xz/y8ccf20s5COCklDPi0UiWbDrPtkNXmDy0LWpXUY5LEIR7I0lWDHlpADgHNq2Vr0pPfwLG/R+V6UMo3PY1psJskECmVOEe84ijwxPugVwuJy0tjYSEBMLCwvDz86tWblYmk7FkyRIHRSgIglAzxVo9/1l1ikPnrgLg5a7ixQmxPOLAkt6C0NjdNpnh6+vLF198QUZGBmC7WFixYgUrVqy47cGeeuqpWg9QEITacTQ5374a4wal0rGlBfR6PRs3buTcuXMAeHt706JFC4fGJAhC3UtKSmLq1Km88sorAOzYsQM/Pz+efvppAH7zm9+wePFiR4bYIA3rFc6K7SlUGsxsO3SFsfFRjg5JEIRGxqTJQzJWAuAc2MrB0dQN15adCHn2Q0qPbKbsxHY8Og9G7ixK8zUm+/fvx8fHBwCDwSDKWQuC0CjtO5nD56tPU1ZhBKB3p0BeGB+Ll7uzgyMThMbttskMJycnFi1aRHZ2NpIkMX36dJ577jn69OlTbV+5XI6vr6+oay8IDUyBpoL3vz2CRmugsKTSPt4mzBuZTMZjvSMcFltOTg6rVq2ipKQEgHbt2jFy5EhcXFwcFpMgCPWjqKiI1q1bA1BWVsbJkyftdasBfHx8qKysvN3LH1rubioG9whj40/prN+Xxqi+kSgUjbvevSAI9etGvwy5sxtKn6Y7gUSmcMK712i8e412dCjCfUhKSnJ0CIIgCPdNW27kix9Ps+9kDgDurk48P64T/boEi4o2glALbpvMAAgKCiIoyLb0ae7cucTFxTWa+tWC8DCSJInUzGJKdbbM/6b96aRmllTZp1OUP//8Q/WkZH2RJImDBw+yc+dOrFYrSqWShIQEunXrJk7sgvCQCAgIICsrC7CtyrBYLMTHx9u3Hz9+nMDAQAdF17CN6tuKTfvTKSypZP/pXPp1eXhqiQuC8OCM15MZqsDG3/xbEARBEBqaQ2fzWLDqFCVlBgDiYgJ46YlY/LxcHRyZIDQdd0xm/NLYsWPrMg5BEB6Q3mDmbwsPcj5dc8vtMyd3QS6T0aVt83qOrKrKykoOHjyI1WrF39+fCRMmEBAQ4NCYBEGoXwMGDGDJkiXodDo2bdqEl5cXAwcOJD8/n4ULF7Ju3TpeeOEFR4fZIAX6q+nVIZCDZ/JYs+cyfTs7boaXZDZRvO8HnHwD8Ygd6JAYBEG4NzdWZjTVElNC0zBt2rQa7bd06dI6jkQQBKFmyitNLFx3hp1HbBO2XJ2VzBjdgcE9wsSkTUGoZbdNZsTExPDBBx8wcuRIAKKjo+/6CyiTyTh//nztRigIQo0kHcuqkshwdVYAoJDLmTy0LQPjwhwVWhVubm6MHTuWs2fPMmzYMFQqlaNDEgShnv3xj3+ksrKSVatWERAQwN///ndcXFxITU1l2bJljBo1yt4cXKhuTP9WHDyTx6WsEs6na2gf6eeQOIoP/EjJgR8BcPILwiUk2iFxCIJQM5LVguFqOgDOLUR5YKHhys7OrjZmtVopLi7GYDAQHBxsL1cpCILgaMdTCvh0xQkKS/WArRrGqxO70NxX9GsShLpw22TGmDFjCAsLq/JcZBMFof4Va/XojZZq46mZxXzx42n7c12lyf54znO9iW3TrF7iuxur1cr+/fvp3LkzHh4eAERGRooeO4LwEFOpVMyZM4c5c+ZUGY+Ojmbv3r00a9Yw/n41VDERvrQJ8yY1s4S1ey45JJlhLMq1JzIAChP/S/DT/0KmqPGiX0EQ6pmpKBfJZLvRIlZmCA3Z7XpmWCwWdu7cyV/+8heeeeaZeo5KEAShqkqDmcUbzpF4MAMAZ5WC3z3ejuG9WyKXi/unglBXbvuJc+7cuVWev/fee3UejCAINiazhRMp11i39zKnLxXe02sHxoU2mESGVqtl9erVZGZmkp6eztSpU5HLRX1mQRBsSkpKOHDgADk5OTg5OREYGEifPo7r6dNYyGQyxvSP4oNvj3Lo3FVyC3UE+bvX2/tLkkThli/BYkah9sZSXoqxIJPSI5vx7jWq3uIQBOHe2Jt/u7ij9BYlPoXGR6FQMHToUE6dOsWHH37IihUrHB2SIAgPqbOXC5m/4gRXiyoA22Sj1yZ1IahZ/V2TC8LD6oGmz5lMJvbv349cLqd3794olWI2niDUhv9tS2Hlzos12rdtuA/j4qMAcFLK6dS6YSQyUlJSWLduHZWVlYCt4a8kSQ6OShCEhmL58uX861//Qq/XV/nb4OzszOuvv85vfvMbB0bX8PXuGEgzH1euFVeyYW8az43rVG/vrTu3D33GGQCaPf4CFZePoz22heK9K3Bv1xulp3+9xSIIQs0Zrt7slyFW3AuNWUREBN99952jwxAE4SFkMFn4dnMy6/ddRpJAqZDz1PAYRvdvhUKsxhCEelHj7IPRaGTOnDlkZ2ezaNEijEYjEydO5MKFCwC0atWKJUuW4OfnmLrNgtDYXcjQsGzrBQxGC8kZN3tf+Hg4M/3xdnSKqp6kUDnJ8XJ3rs8w78psNrNjxw4OHToEgKurK2PGjKFNmzYOjkwQhIZix44dvPPOO7Rr145nn32WyMhIJEkiLS2NxYsXM2fOHIKCghgwYICjQ22wFAo5o/pG8vX6c2w/ksmUYdF4uNV9DyJLpQ7Njm8AUEf3wq11N5xDoym/8DOW8hIKty2ixYTX6zwOQRDu3c3m36LUp9B4GY1G1q9fL+47CIJQ71Izi/lo+XFyrukAiArx4rXJXQlv4engyATh4VLjZMaCBQv44YcfGD9+PABr164lOTmZadOmERMTw3vvvcf8+fN555136ixYQWhKJEki55oOk9nK7mPZ/Lj7UrV9nhjUmmmPtXNAdPenqKiI1atXk5eXB0B4eDjjxo3D01Oc3AVBuGnhwoW0a9eO77//HpXq5g34mJgYhg4dysSJE/nqq69EMuMuhvYMZ/nWFCoNZrYczOCJQXWfNNbsWoalvBSZygW/IU8DoHBR4zfktxSs/ZiKlEOUpx5B3aZ7ncciCELNSVYLxuvNv1WiX4bQwE2bNu2W40ajkfT0dLRaLS+//HI9RyUIwsNKbzSzYnsqP+66iFUChVzGpKFtmTCwNUqFKKMtCPWtxsmMxMREJkyYYG/WuXXrVjw8PHj99ddRKpVkZWWxcuXKOgtUEJqapZuTWZVUvZSUj4czj/dpiauLkoHdQh0Q2f3bv38/eXl5yGQy+vXrR79+/USPDEEQqrlw4QKzZs2qksi4wcnJidGjRzN//nwHRNa4uLk4kdArnLV7LrPxp3TG9I/CSVl3f3P12SmUndgGgG//ySg9b86KVbd7FNdTSVSmn6Zo29e4RnRErnKps1gEQbg3psJsJLMREM2/hYYvOzv7luMKhYLIyEhGjBjBlClT6jkqQRAeRkeT8/n8x9MUaGy9McJbeDBzcldahXg7ODJBeHjVOJlx9epVOnfuDEBlZSVHjhwhPj7e3icjMDAQrVZbN1EKQiOXllPK1p8zsFhv1oXf+vOVavtNHtqWyUPbNto6xgkJCWg0GuLj44mIiHB0OIIgNFAqlcreT+dWysvLUSgU9RhR4zXy0UjW70tDo9Wz72QOA+PqJgkuWcwUJn4BgCqgJZ5xw6tsl8lk+CXMIHvhTMyl1yjZvwrfAVPrJBZBEO6dvfm3mydKz4bRX00QbicpKcnRIQiC8JArKq1k4dqz7D+dC4BSIWP8wNZMHNwGJ6X4nCIIjlTjZIa/vz+FhYUA7Nu3D6PRSHx8vH17SkoKzZs3r/UABaGhM1usd93ny7VnOJdWdMtt4+KjeGJQa5ycFDg7Na6TYn5+PiUlJbRt2xawNe797W9/69igBEFo8Lp3786yZcsYN25ctWuH/Px8li9fTrdu3RwUXePS3NeNPp2C2Hcyh3V7LjOgW0idJMRLj2zCWJAJyPB/7Hlk8urnK5VfEN69x1Gy7wdKfl6Pe4d+qJqF1XosgiDcO3u/jBai+bfQOOTm5rJ8+XJmzJiBl5cXYCtTqdFoePbZZ0XPDEEQ6oTFYmXT/nS+25JMpcECQKcof54f14nQAA8HRycIAtxDMqNnz54sWbIEZ2dnli1bhqurK4MHD0ar1bJ69Wp++OEHJk2aVJexCkKDYjRZeH3BPi5nl97T6/p1CbY/9nRTMSa+Fe710LS1NkmSxNGjR9m6dSsKhYLf//734gOFIAg19tprrzFx4kSGDx/OmDFj7Cu50tLSWL9+PRaLhVdffdWxQTYiY/q3Yt/JHNJySzl9qZDY1rU769pceo3ivSsA8OyWgEtQ1G339e49Ft3ZvZiLr1KY+CWBT72DTCbKDQqCo4nm30JjkpqaylNPPYVOp2PEiBH2ZEZpaSnLli1j48aNLF++nNDQxlWSVxCEhi01s5jPVp+y3+PxclfxzKgOxHetm8lCgiDcnxonM9566y3y8/N5//33cXNz4x//+Aeenp4cO3aM999/n+7du/PSSy/VZayC0KD8vy8P3nMi42/P9iIuJqCOIqofer2e9evXk5ycDICnpycmk8nBUQmC0Ji0adOGJUuWMGfOHJYtW1ZlW4cOHfjLX/5CTEyMg6JrfNqE+dCupS/n0zWs3XO51pMZhVu/RjIZUKi98Y2/c41yuVKF/7Dfc/V/76DPSkZ3ejcesQNrNR5BEO6NZDFjzM8ARL8MoXGYN28earWaFStWVCldO3v2bCZOnMj06dP58MMPRX8tQRBqRXmliW8Tk9l8IB3pemXwhF7hTH+8HR6NbOKpIDwMapzM8PT0ZPHixWg0Gtzd3e1NO2NiYlixYgWxsbF1FqQgNESZV2/2iHn9qTj8vO7c6NTbw5kgf/e6DqtOZWdns2rVKkpLbUmcDh06MGLECJydnR0cmSAIjU2nTp344YcfKCoqIicnB0mSCA4Oxt/fn59//pmlS5cybdo0R4fZaIzp34rz6RqOJueTlV9Wa8vgy1MOU3HxCAB+Q59G7qK+62vcImNRt+tD+fn9FO1cilvr7ijcxLJ8QXAUY2E2ksU28cQ58PYrqwShoTh58iQvvPDCLXvwhYaGMnXqVL766qv6D0wQhCZFkiR+OpnLwnVnKC4zABAR6MkL42OJaenr4OgEQbidGiczbvDy8uLs2bPk5OSgUqlo0aKFSGQIDwVJkvhm43kOnMlFhgxdpe1D4Z+mxfFobPBdXt24SZLE/v37SUpKQpIklEolw4cPp0uXLmK5pSAID8TPz69ambrExER++OEHkcy4Bz3aBxLopyavqJx1ey/z0hOdH/iYVmMlhdu+BsA1sjPqmN41fq3f4N9RcfkE1soyNEnf0mzECw8cjyAI98eQdwkAhdobhYe4OSM0fJIkYTAY7rhdr9fXY0SCIDQ1eYXlfPHjaY6nFADgrFIwZWg0o/pFolSIEqmC0JDdUzJj165dvP322+Tn5yNJkv0mZvPmzfnb3/7GwIGijIDQdM1dcoSDZ/KqjTf3cXNANPUrKyuLnTt3Arbf9wkTJtCsWe2WMREEQRDun0IuY1S/SP675gy7jmbx1PAYvNwfbNVc8d4fsGgLkSlV+A+bcU/Ja6WHD77xUyja+hVlp3biETsAl1BROkwQHOFGvwxVi0gxCUVoFGJjY1mxYgWTJk3C09Ozyrby8nJWrlwpJlQKgnBfTGYLP+66xA87UjGarQD0bN+C34/t+FDc2xGEpqDGyYyjR4/y8ssv4+fnx8yZM2nVqhWSJJGWlsby5ct55ZVXWLp0KV27dq3LeAXBYY6cv2p/PHFIG5p5u9HC143Wod4OjKp+hIWF0bNnT0wmE8OGDcPJycnRIQmCIFSxceNGPv/8c7KysggODua5555jzJgxt9z3jTfeYM2aNbc9VkpKSl2FWacGdQ/juy0XKK80kXgwg0lD2t73sQz5GZQe3giAd5/xOPm0uOdjeHYdiu70Lgx5l7mW+CUhz/wLmeKeFwULgvCAjPbm36JfhtA4vPTSS0ydOpURI0YwcuRIwsPDkclkZGZmsmnTJq5du8bcuXMdHaYgCI3MmUuFfLb6FNkFOgD8vV15bmxHenUIdHBkgiDcixp/ovz0008JDg5m1apVeHhUrXs8ZcoUxo8fz+eff87ChQtrPUhBaEj+OLUb/bqEODqMOmW1Wjl9+jSxsbH2GXwJCQliNp8gCA1SYmIis2fPZtq0afTt25cdO3bwpz/9CRcXF4YNG1Zt/xdeeIFJkyZVGbty5QpvvPEGTz75ZH2FXetcnZUM6xXO6l2X2PRTOuPio1A5Ke75OJJkpXDzFyBZcfILxrvX6PuKRyZX4D/8OXIWv4HpWialhzfi/citE0yCINQNyWLCUHAFEMkMofGIjY1l8eLFvP/++yxatAjpRkdeIDo6mrlz59KlSxcHRigIQmNSqjOwaMM5ko5mASCXyxjdrxWTh7bF1VlMtBGExqbGv7WnT5/mxRdfrJbIAHB3d2fChAkikSE0OQvXnWHviRwAzBbbRbS7m8qRIdW50tJSVq9eTVZWFnq9nl69egGIRIYgCA3WRx99xCI5ougAACAASURBVPDhw3nrrbcA6Nu3L6WlpcyfP/+WyYywsDDCwsLszy0WC//4xz+Ijo7mz3/+c73FXRdG9o1k7Z7LlOgM7DmezZCe4fd8jLLj2zHkXgTAf/hzyJT3vxrPObAVnt2GoT26meJ9P6Bu1xsnr+b3fTxBEO6NsSALLGZAJDOExiUuLo6VK1ei0WjIycnBarUSGBhI8+biHCIIQs1YrRLbD2fyzcZz9p6nbcN9eHFCLC2DvBwcnSAI96vWUpAymQyTyVRbhxMEhyoqrSQ5Q8P6vWnVtjX3cXVARPUjOTmZ9evX2xvqVVRUODgiQRCagtzc3Hvav7y8vMb7ZmVlkZmZyaxZs6qMJyQkkJiYSFZWFqGhoXc8xvfff8/58+dZsWIFKlXjTlj7ebnSt0swu49ls3bvZQb3CLunZLRZV4Jm13cAuHeKxzW8/QPH5Nt/EuUXDmLRFVO0dREtnnzjgY8pCELN2Jt/u/uiFM2/hUYkNzeX5cuXM2PGDDp27AjAwoUL0Wg0PPvss/j5+Tk4QkEQGrKMPC2frTpFcoYGALWrE9Mfb0dCz3DkcjFRUxAasxonM2JjY1m1ahVTpkzBza1qUxydTsfKlSvtFxmC0FidSCngZOo1ftx9qcr4iD4tiWnpS1Azd0KaV1+d1NiZzWa2bdvGkSNHAHBzc2Ps2LFERUU5ODJBEJqCgQMH3tMNdUmSarx/Wpot6dyyZcsq4+HhthUJ6enpd0xmlJeX88knnzB69Gg6depU4xgbsjH9WrH7WDaZV8s4kXKNrtE1n8Wq2fENVkMFcld3/AZOq5V45C5q/Ib8joI1H1Fx8QjlKYdRt+1RK8cWBOHODPZ+GZEOjkQQai41NZWnnnoKnU7HiBEj8PKyzaAuLS1l2bJlbNy4keXLl991soIgCA8fk9nC8q0prNl9CYvVVl0jvmsIT49qj4+Hi4OjEwShNtQ4mfHSSy8xbdo0RowYwdSpU4mIiACwNwDPz8/n7bffrqs4BaHOfb89hWVbLlQbbx/px+9Gtr+vuuONQWFhIatWrSI/Px+w3RAcO3bsLUvKCYIg3I8xY8bUWam6srIywFby8pfUajVgm3BxJ6tXr0ar1fLcc8/VSXyO0CrEm05R/py+VMjaPZdqnMyoSD+F7tw+AHwHPoVCXXvL79UxvXE9tZPKtFMUbvsa15Ydkaua7kpHQWgoDKL5t9AIzZs3D7VazYoVK+z3HQBmz57NxIkTmT59Oh9++CHz5893XJCCIDQ4GXla5i07RkaeFoAgfzUvjI8ltk0zB0cmCEJtqnEyIy4ujk8//ZR33nmHDz74wH5TQpIkmjVrxr///W97bX1BaAwkSeKfiw9z6uI19EZLlW2hAe70aNeC6Y+3a9K9IiRJYsWKFRQWFiKTyYiPj+fRRx9FLpc7OjRBEJqQ9957r86OfaMp6K//Vt8Yv9vfs2XLljFo0KBqKzsau9H9W3H6UiEnUq9xJU9LeKDnHfe3mo0UbbH1PnMJjcEjdmCtxiOTyfBPmEH2lzOxaAsp3rcSv0G1s/JDEISqJIuZ8tQjaI8mYsxPB0QyQ2hcTp48yQsvvFAlkXFDaGgoU6dO5auvvqr/wARBaJCsVol1ey+zdHMyZosVuQyeGNSGJwe3abKTUgXhYXZPPTMGDRpEfHw8586dIzs7G4Dg4GDat2+PUllr7TcEoV5otHoOnbtabfyVJzvfV8PUxkgmkzFy5EjWrFnD2LFjqzTEFQRBaAxurCL79QqMG3037rTK7MKFC2RkZDB79uy6C9BB4qIDCG7mTs41HWv3XObVSV3uuH/JgTWYNHkgV+A//PfIZLWf1HbyDcS7zziK966g9NAGPDr2R9X84TjfCkJ9MOuKKTuxA+3xbVh0Gvu4qnkELmEP3v9GEOqLJEkYDIY7br/R408QhIdbQXEFH//vBGcuFwIQ6Kdm1m+6Eh0u+kQJQlN11wyEyWTi0qVLmM1moqKicHV1pVOnTk2mrrTw8Lo+aReAFyfE4uvlQngLTwJ83W7/oiYgLy8PNzc3e+3ZsLAwXnrpJRQKMWNBEITG58aKiszMTNq2bWsfv3LlSpXtt7J7927c3Nzo379/3QbpAHK5jNH9W/HZqlPsPp7NtMdi8PG8dZ1gY1EOJQd+BMC71yhUzeouse39yFh0Z/dh0uRyLfFLgqb9o04SJ4LwsJAkCUP2BUqPJlJ+4RBYzbYNMjluUd3wjBuGa8tO4vdMaFRiY2NZsWIFkyZNwtOz6srC8vJyVq5cSWxsrIOiEwShIZAkiT3Hs/nix9OU623nvoRe4TwzqgOuzmKytSA0ZXf8Df/mm2/4z3/+Y5/tqFKpmDJlCv/3f/8nVmIITUqn1v4E+bvffcdGTJIkDh8+zPbt2wkKCmL69On2BIZIZAiC0FiFh4cTEhLCli1bGDJkiH1827ZtREREEBQUdNvXnjx5kg4dOqBSqeoj1Ho3oFsI325OpqzCyKb96UwdHlNtH0mSKNyyECxmlF7N8X70iTqNSaZ0wn/YDPKWv40h+wJlp5Lw7Dy4Tt/zYWY16ik7vZuyE9tQePjhO+A3OAdEODqsemU1GTAX5+PkF4RM0XQ+v1iNenTn9qE9ugVjQYZ9XO7qgUfnQXh2TcDJu2b9cgShoXnppZeYOnUqI0aMYOTIkYSHhyOTycjMzGTTpk0UFBQwd+5cR4cpCIKD6CqMfLb6NPtO5gDg5a7ilSe70KN9CwdHJghCfbjtFf3atWt57733CA4OZvTo0cjlcg4dOsQ333yDxWLhrbfeqpUANm7cyOeff05WVhbBwcE899xzjBkzpkavzcvLY8SIETzzzDO88MILtRKP0HTpKk1kF5Tx//57gEqD5e4vaEIqKytZt24dKSkpgG1Gk06ns6/OEARBaMxefPFF3nzzTby8vIiPjycpKYnExET+/e9/A6DRaMjMzCQqKqpKo/DU1NQmuSrjBheVksf6RLBieyqbD2QwYVBrXFRVL/10Z/eizzgDgP+wZ5E7Odd5XK4tO+HeoR+6s3vRJH2LunX3Wm02LoC5rBjt0c1oT2zDWnm9BFvBFXIun8AjdgA+/aeg9PBxbJB1yFKpo+LSUcpTDlOZdhLJZEDh7mO7yd9lCEpPf0eHeN9Mmjy0x7ZQdnoXVn25fdw5MArPuGGo2/VBrmyaCVrh4REbG8vixYt5//33WbRokb0PFkB0dDTvvfceXbrcuXyiIAhN08nUAj7+/gRFpbZScz3ateDlJzvj7VH317CCIDQMt01mLF++nM6dO7NkyRKcnW1/FCRJYubMmaxYsYLZs2c/8EzGxMREZs+ezbRp0+jbty87duzgT3/6Ey4uLgwbNuyOr5UkibfeeqtajWxBuJUKvYln/7md8kpTtW1qFyW+HrcuvdEUZGZmsnr1arRaLQAdO3bk8ccft/9eC4IgNHbjxo3DaDSyaNEiVq5cSWhoKO+//z6PPfYYYCsn9eabb7J06VJ69uxpf11RUVG18hVNzeO9W7I66RJlFUZ2Hctm+CMR9m2WSh1FO74BQB3dC7eobvUWl++g6VRcPIq1UkdR0rc0H/lSvb13U2YsuELJoQ3ozu0Di63kgkzhhLp9Hwy5lzAVZlN2Kgnd+QN4PzIar56jkKuaxjWQWVtEeeoRKlIPUXnlHFirTlyx6Iop+WkVJft/tJVf6paAa2Rsoyi/JFktVF4+SenRRCrTTtjHZQon1O364NltGC7BrR0YoSDUvri4OFauXIlGoyEnJwer1UpgYCAA69ev55133mHjxo0OjlIQhPpiMFlYuuk86/elAeCiUvDs6I4M7RmGTCZzcHSCINSn2yYzLl++zKxZs6rc8JTJZPz2t79l69atpKWlER0d/UBv/tFHHzF8+HD7Ko++fftSWlrK/Pnz75rMWL58OWlpaQ/0/sLD45uN56slMuY83xu5TEZYCw9cmmBNRavVyk8//cTu3buRJAknJycee+wxYmNjxcleEIQmZ9KkSUyaNOmW28aNG8e4ceOqjZ86daquw3I4H08X4ruGsONIJuv2XCKhZzhyue0coNn1HdYKLTKVC35Dnq7XuJTu3vgO+A2FWxaiO70Lj9gBuIoGxfdFkiQq009Remg9lWk3/5+Wu3ni2TUBz27DULp7I1ktlJ3YjmbvCqwVWor3rkB7Yju+8VNw79i/UdzU/zVjUQ4VKYcpTzmEIfdilW0ypQrXyM6o2/bAuUUkunM/UXZqJ5byUiouHqHi4hGU3gF4dh2KR6cBDXJ1kKWijLJTO9Ee34q5pMA+rvT0x7NbAh6xgxpk3IJQm3x9ffHw8GDnzp189tln7N+/H7PZLMrk1oAkSSBZkcnFv9XD5mJWMXtP5NC9XQAdW/k3+s//aTmlfLjsGFn5ZQC0Dfdh1pSuTb5UuCAIt3bbO7iVlZV4eHhUGw8JCUGSJPss7/uVlZVFZmYms2bNqjKekJBAYmIiWVlZhIaG3va1H374IfPnz2fGjBkPFIfQtFmtEpn5ZSQezLCPLf1bAt4ezo3+hH43hw4dYteuXQAEBAQwYcIE/P0bb1kFQRCEh4X25E6Ktn6FKiACdZseuLXpjso/5L6PN6Z/K3YcySTnWjlbD10hLjoAN20GZSe2A+DbfzJKT7/aCr/GPLoMoez0bgy5FylM/JKQZz9EpnCq9zgaK8lsQnduHyWHNmC6lmkfd/ILwqvHSNw79q9SNkwmV+DZbRju7ftScnANpYc2YinTcG3DAkoPb8Jv8HRcIzo64kepMUmSMOZdpjzlEOWphzEVZlfZLndR49Y6DnWbnrhGxlZZdeLbPByffk9SnnIY7fGt6K+cw1ySjybpWzR7/od7TG88uw7FOSTa4deIhrzLlB7dQvn5n5DMRvu4a8tYPLsNw611N3FzUngonD17ljVr1rBx40a0Wi2SJOHv78/48eOZOHGio8Nr8Ap+nEd56hHU0T3xihveIP6+CXVv/+lcPlp2DKPZyto9lwkN8ODx3hEMiAvFzaVxXWdZrBJrdl9i2ZZkzBYJuVzG5KFteWJgaxSKxjcJQxCE2nHbZIbVar3lie7GDAiL5cF6DtxYVdGyZcsq4+Hh4QCkp6ffMplhtVp54403GD58OP369XugGISmTW808+q83eQW3qwn/PsxHfHxbBrlFO6mW7dunDhxgoiICIYOHYpS2fRWnwiCIDRF1soyJLMRQ04qhpxUNLu+w8kvCLc2PVC37YlzUNQ9zaIPD/SkS5tmnEi9xmerTiHHyh89NxKkhHxZM5ad9sXnykn8vFzx9XTBz8v25evpgqdaVas3PiRJokJvRltupKzCSHn0BDxz38NUmM3upV+T7PkI2nIjTgo5oQEehAZ4ENbCgxZ+ahRycQMGbLP1tce3oj2aiKW8xD7uEt4er56jcIvqesf/P+QuanwHTMWjy1A0u5dRfu4njPnp5C37O26tu+M76ClUfsH18aPUiGS1oM88T3nKYcpTD2PRFlbZrnD3Rd22B25te+Aa1v6OTb5lCifc2/XBvV0fjIXZaI9vRXd6N1ZDBbqze9Gd3YuqeRgeXRLw6NgPubNbXf94gC0xZSzMwpB3mbJTSRhyUm/G7OyGR6d4PLsNa1D/XQShrhQVFbFu3TrWrFnDpUuXkCTJfh56+eWXee6558TnmhqSLCawmik/v5/y8/tRNY/AM86W1G4qJQaFqtbtvczX688iSeDmoqRCbyYrv4wv1pxhyebzDIwL47HeEYS1aPhlVvM1Ffz7f8c5l1YEQHAzd2ZN6UqbsKbb80sQhJpx2FVAWZltedgvG3ECqNVqgNv2wliyZAlZWVl88cUXdRug0KgdOX+VHUcyqyQyAnzdeKxPyzu8qnGzWCzk5eUREmKbvatSqXj22WcfuLeNIAiCUL+8eo1G1aKlrXxO6mEsZRpMRbmUHlxL6cG1KNTeuLXpjrpND1wjOiJT3n2W3dThMaTnaSkpM9DfJZkgZQlWCb4r7U5m0bXbvk6pkOPr5YKfp4v9+41Eh5+XK75eLlitEmUVRsrKjfYkhfYXj8sqTLbH159brFKV9xjrFk28SzKBOUl8c94DjbV6yQAnpZzgZu6EtfAg7HqCIzTAg0A/9UMzM8+kyaP08EbKTu9CMhlsgzI57u364NVzFM6Bkfd0PCfv5gSMmYm+++MU7fgGQ3aKrfzS5eN4dk3Ap++TKNyqr9KuD1aTgcr005SnHLreW6Wsaux+Qajb9sStTY97Tu7doPIPwX/oM/jG/wbd+Z/QHtuG8epljAWZFG1diGbXt7i374dntwScAyJq5eeSJAmLrgRjQQbGgisY8zMwFFzBVJRTrceHU7MwvOKG496hL3KVa628vyA0VGazmaSkJH788Ud++uknzGYzKpWK/v37M2TIENq2bcuECROIjo4WiYx70Hzc/1F+fj/ao1sw5F3CWJBB4eYv0OxcinvsQLy6JeDkG+ToMIVaYLVKfL3hLOv32iYNx0T48uff9UCj1bNpfzq7jmVTabCwaX86m/an0ynKn8f6tKRX+xYN7jpKkiSSjmbx3zVnqDTY+n891juC341sj4tK/P4LgnCXZEZJSQm5ublVxkpLSwHQaDTVtgEEBdXsZChJtg+yv57td2NcLq/+BzUtLY2PP/6YTz755JYlsAQBIPeajne+PlRl7L0XH6VVsFeTndVZXFzM6tWryc/PZ8aMGTRv3hxAJDIEQRAaIZlMhlvLWNxaxuKX8KytrE7qYcpTj2C6lomlvISyE9spO7EdmcoFt1ZdbYmNqK4oXNS3PGabMB++/fswygpyubb4ezCDLrwvA4P7odHqKSrVX/9eiUarx2yxXY+ZLVYKNBUUaCrq5GdVKuQcVPYgjkzcZeXMaHGKk6GTMZisZOaXkZ1fhtFsxWS2kpGnJSNPW+31Ic3d7Ss4QgNsyY5AfzXKBvbh/H5IkoQh+wIlP6+nIvUIcP362dkNzy5D8Or+GErPBysh6RLchqBp/6T8ws9okpZiLilAe3QzurN78O4zAa+44TVKmD0IyWLGWJCJIfcilRmnqbh84mbC5jrnwFa4te2Jum3PByq79mtylQuenQfj2XkwhtxLttUa535CMuopO7GNshPbcA5ui2e3oahjeiNX1uzayrbaIrta4sJacftSvXI3T1zDO+AZNwyX0HaiHIzw0Ojbty8lJSW4u7szZMgQhgwZQv/+/e0THXNychwcYeMkV6rw6DQAj04D0OdeQnsskfJz+7EaKtAe3oj28EZcI2Px7DbctqpPlK9rlAwmCx8tP8aB03kA9O4UyKwp3XB2UuDl7sxLT3Tmt4+3Y8eRLDYfSCevsJzTlwo5fakQfy8Xhj0SwdBe4fh4OH61TqnOwGerT9l/Fh8PZ16Z2IW4mAAHRyYIQkNyx2TGu+++y7vvvnvLbbNnz642JpPJOH/+fI3e+EYy4tcrMMrLy6tsv8FisfDGG28wbNgw+vTpg9lstm+zWq2YzWYxS+MhpTeambPoEDnXbP/vFJZU2rdFBnvRp1MQ7SPrvxZ4fTl//jzr16/HYLB96M/IyLAnMwRBEITGTSaT4RwUhXNQFL7xUzBp8ihPPUJF6mH0WReQjHrKkw9QnnwA5ApcwzvYylG16X7LPhjlu5eC2YjC3YdOT8yg8y2SHzdWWtxIchSV6tGUVlKk1VdJfJTqDEi/WGTholLgqVbhoVbh4abCU63C063qc49fjHmqVbioFMhkMnTJzSj48UOC9Jfp0smIOronYKuVXKCpICu/jCtXtWTll5GZX0ZWvg6jyYLZcrskh4zgZjeSHJ72BIersxJnlQJnJwXOKkWDTXhIVgvlF36m9NCGKo2tlV7N8OoxAo/YQcida2+2vkwmwz3mEdSt4yg9mkjJTyux6svR7FyC9tgWfAdORR39SK3cXJckCXNJPobci+hzL2HIvYjxanqV3hC2oOS4hLdH3aYH6rY9HjhpUxPOQVE0C4rCd9B0dGd2oz2+DVNRDoacFK7lpFC0fTEenQbi2XUoTr6B9p+nymqLgisY8jNuudrilz+bk38wzs0jUDUPRxUQgap5BAp3b5HAEB5KxcXFuLm5MXLkSHr27En37t3tiYzasnHjRj7//HOysrIIDg7mueeeY8yYMbfd32q18t///pdVq1Zx7do1wsPDef7553n88cft+5jNZhYsWMCaNWsoKSmhffv2vPHGG3Tq1KlWY68NLkFRuAS9jGXQdMpOJaE9tgVz6TUq005RmXYKpVczPLsm4NF5EAq3hl+CSLAp1Rn45+LDJGdoABjVL5KnR3aoNonT3U3FmP6tGNU3khOpBWzan87R5HwKS/V8t+UC329PoXenIEb0iSQ6wsch56JjF/KZ//0Jists9zUe6RjIixNi8XJ3vssrBUF42MgkSZJuteHNN9+8rwPOnTu3RvtduXKFoUOHsmDBAoYMGWIf37x5MzNnzmTXrl1VVnlkZ2czaNCgOx4zJSXlnuONi4sD4OjRo/f8WqFh2LAvjS/Xnqk27uvpzOK/JiBvoqsxTCYTW7du5dixY4CtRNvYsWNp1aqVgyMTBKGhEee6uuWof19LeSnlF49SkXqYyrRTttrYv+Ac2Op6n40eOPmHUpF6mPxVHwDQfOws3Nv1eaD3N1usFGsNyOXgqVbhpLz/GZ2SJHH1+39SmXYChYcfoc/Pv2NpHatVoqC4gsz8MjKvltmSHFe1ZBXoMBhv19dNAqpeEyjksirJjZvflbcZr/7dSalAqZChVMpxUspRKm5+v/H4VuMyGUhGPRZ9GdbKcqx6HZZKHebiPLTHt2EuvVn+yzmoNV49R6KO7lUvM2ctFVqK961Ee2wLSFZbDCFt8Rv8W1yC29zjscow5F7EkHsJfe5FDHmXbrs6QeHug3NwG9RtuuMWFeewMlc3SJKEPvMc2mNbKU85VCU54RLREZlMhiE/486rLVw9UAVE4Nw8/Gbiwj+0zle7CEJtq8tz3c8//8zGjRvZtm0bZWVlyGQyOnfuzNChQ+33CgYNGsR//vOfu94TuJXExERmzpzJtGnT6Nu3Lzt27OD7779n/vz5DBs27JavmTNnDitWrGDWrFlER0ezadMmVq1axX//+1/69+8PwNtvv82aNWuYPXs2QUFBLF68mHPnzrFu3bpb9v+8m/q8npCsFiouHUd7bAuVaSft4zKFE+p2ffDsNgyX4NZ1Hodw//IKy/n7woPkFpYjk8Ezozowul/N7wVcLSpny8EMth26QlnFzWvIyCAvHuvTkv5dg+ulrJPeaOabjefZtD8dAFdnJb8f05FB3UNFgl8QmqDaONfdNplRHwYNGkTnzp2ZN2+efey1114jOTmZrVu3VtnXaDTeMlkxYcIEJk+ezPjx4+nYseM9xyBu8DRuWfllvPBBkv35zMld7I/bR/oT4Fs/jRvr27Vr11i1ahUFBQUAREZGMnbs2Go9aARBEECc6+paQ/j3tRorqUw7ZVu1cfEoVn3Vla9KnxZIxkos5aW4RnahxaQ/N7gPiKbiq2R/ORPJbMS90wDUreOwmo1IJiOS+fqXyYjVbEAym6qMSWbj9X0NGPV6zAYDZpNtP7nFiEIyI0PCiBN6SYlBcsIgOaGXnDBUef6Lx9zcpr/F/iYUgAw5VlxlRtxkRtxkBtzk17/LDKhlRlyvP1fLDLhdf66+vl0hu/1luARccYrignt3St1CUTkpcVLKUTkpcFLKbYkUJzkqpQKVUo6TkwKVk+3xjX1USgUqJ9vzG6tj7mWSh7EoB83Ob6m4eMQ+pm7XB98BU3Hyrr4K1Goy2Mop5V60JS5yL2EuvnrLY8tULjgHtsI5qDUuQa1xDmp9y9VEDYVZV0zZyZ2UndiO+VdNyAH7agtV8/AqKy4U7o6Z4SoIta0+znVGo5E9e/awYcMG9uzZg8FgQCaTERERQUZGBh988AEjR4685+MOGTKEDh068O9//9s+9tprr5GSkkJiYmK1/TMzM0lISOCdd97hiSeesI9PnTqV6Oho/vKXv5Cdnc3QoUP561//yuTJk+3xJyQk0K9fP95+++17jtNR1xMmTS7aY1spO70Lq/5mz0nnwFZ4xg1H3a5PjUvsNXXJ6RqMZgudovwd+rc9NbOYd77+mVKdEZVSzqzfdKNPp/vrf2IwWdh3IodNB9K5lFViH1e7OjGkRxjDe0cQ5H//9xlMZgsarQFNqR5NmR5NqZ7iMttK32Ktnsz8MopK9QC0a+nLzMldaeFXuyuzGqqKS8coPbQBmVKF3EWN3NnN9nW7x9efy5ycxbVFI2XVl6PPvoA+KxlD/hU8uwxB3baHo8OqV7VxrnNoXaYXX3yRN998Ey8vL+Lj40lKSiIxMdF+kaHRaMjMzCQqKgp3d/fbJiuaN29+X4kMoXEymix8te4s+ZoKjqcU2MdH9Y1kYFyYAyOrHzqdjoULF2IymZDJZAwcOJA+ffqIk5kgCMJDTK5yRR3dC3V0LySLGX1WMuWph6lIPYK59Jr9hrJMqcJ/2LMN8pzh5NMC7z7jKd7zP3Snd6E7veu+j6W4/mV3/cd1wYSLzARUVn/RPbIiwywpUMnMd9+5JseToFJSUSE5k2wKYo8+hkKrJ+QD3DohcK+UCjl+Xi74e7vi7+WKv7etkbu/980xL3dne8JD5RdMiyffoDLjDEU7lmDMT6f8/H4qUg7j2eNx3Nv3xZifjiHHVjLKWJBx69JKMrntJn9Qa5yDonAJbo2TX3Cjqs+udPfB59EJePceS8XlE5Rf+Bm5i/r6iosInJqFiJt9gvCAVCqVvWeGTqdj69atbNiwgSNHjiBJEn/605/48ccfmTBhAkOGDKlRf8CsrCwyMzOZNWtWlfGEhAQSExPJysqqtopix44duLi4VCtD9d1339kf//zzz1gsFhISEqrEHx8fz+7du+/jp3ccJ98g/Ib8Dp/+k9Gd+wnt0USMBRkY8i5zbcMCinYsQpuxRQAAIABJREFUwaPzIFuJPe+Ht3fB7mNZzFt+HIDocB9+O6K9Q8pZHzqbxwffHcNosuDhpuKvT/ckpqXvfR/P2UnB4B5hDO4RRmpmMRt/SmPfyVzKK02s3XOZtXsu0zW6OSP6tKRrdIC9hJXRZEGj1VOsNaC5Xor011/FWn2VVR/VSXRVZRDlItGxT29GDOvRZPuc/po+9xL5qz+sXmazJmRy5C5uyJ2vJzpcqiY+FG5eeHTsj9KrWe0HLtwTs64YfVYy+sxk9FnJGPMzuNEDD0CfcYbAaXNwCYpyWIyNkUOTGePGjcNoNLJo0SJWrlxJaGgo77//Po899hgAu3fv5s0332Tp0qX07NnTkaEKDcjJi9dIPJhRZczfy4UZYx6OhJa7uzs9evTg7NmzjB8//r6WMAuCIAhNl0yhxDWiI64RHZGGPI0xP4Py1MPos5LxjB2Ek08LR4d4W969RlOZcQZ99gXkShUypQqZ0/XvSmfk9sc3xp1ss9nsY8727Tf3te2DXI5k1GM1VmI16JGMlbbHt3guXR+zPdZXK+EFIEe6dSJDoUTu4o7MWQ3O7uCs5v+zd9/xUZXZ48c/d3rapPcOhBp6gCRI7woKARFdRazrd117hV3dte7qrrr6U1dZRUFF6UgLICC9Iy10SEjvfUqm//6YEEECBkgySXjer5cvkzt37j2BMMk85znnOFTuOJTu2JTu2JXuWBXuWOVuWBVuWGQaTDI3LJIKqx0sVjtai52xVhtmqx2zxYal9v9mix2z9dfPLVY7JosNi9X52IX/my3O5/6W1WansMxA4VUGustlEv7eziRHoI8b/j5uBHi749/vaQJLD6I88iMOfTmVu5ZTuWt5vddQ+ATVJi6cVReqkFhkyrbR81qSyfGIS8AjLsHVoQhCm+bp6cnkyZOZPHkyxcXFrF69mpUrV7Jr1y52796NVqtlz549v3ud9PR0AGJjYy85Hh0dDUBGRsZl76dOnTpFbGwsO3fu5L333uPs2bNERETw9NNP161VpKen4+3tjZ+f32XXzcvLo6amBo3G9QOVr4VMpUHbeyRevUZgyjlF5YFU9Cd2YzdW177m/4h7hz5oE8bh1q5Xi9wY0VT2Hi/ggx8O1n1+MrOclz/ZTv+uIUy/tQvRoc0zZ2T1dmeLbbsDQvzd+fsjSYQHNl53ho5Rvjx7T18euj2e9XsySd11nuJyI7+cLOKXk0UE+rrhplZQVlmDzni1JEX9PNyU+GnV+Gk1+Go1dLSn0y1zm/PBg9vJOReAW2QXNJFd0ER1QRkQgSS1zPlmN8JaVUrhon/isJpR+ATh0bE/dpPB+V+Nvu5jW+3H2H7z+6bDjt2ow27U1X8DoGp/KmH3v9Wif+9vay7MhavJOu5MYGSfwFKWf/mJkgx1SDts+gqsVSUULn6XiIf+hdzDu/mDbqVcPjF72rRpTJs2rd7HUlJSSElJuerzr2dOhtD6OBwOTpwvo7jcyOmscgBUChkTBrVDkiQGxLftF+ji4mL8/f2RyZw/yIcNG8bAgQNxc2u84Z+CIAhC2yNJEuqQWNQhsb9/cgsgKZSE3XvtrTmamsNmwV6bCHHUJjnsZiMOi9m5G07jidzNC5mbpzOB0gIWeBwOB1abvS65UaEzUVpZQ0mFkZJKI6UVv35cUmGkpnbWiM3uoKjcSFG5kRP1XFfFWIa7nWCEJg2VZMUid8PmF4NHZEcCOnRFExYn3owJgtCoAgMDmTFjBjNmzCAzM5MVK1awatWqBj23uroa4LJ2vBcGjOt0ly8GlpWVkZ+fz6xZs3jqqaeIiIhg0aJFPPPMM/j5+ZGYmIhOp6u3xe+F6+r1+laXzLhAkiQ0kZ3RRHbGOtLZYq/ql3XYqsswnD2A4ewBAm79P7S9R7o61GaRdq6Ed+buw2530C7Mm/tu7cIP609xKqucvccL2H+igOEJUdwzpjOBvk3z/txudzBvzXGW/HwWgI5RPrzyYCI+Xk2zUcDbU82dIzqSMiyOfccLWL0jg0Oniykur7+y1Zmk0NQlKi7851v7f39vDT5e6stmcBQs/ImLt1fYqkrQHduG7pgzwSFz86r9XuyKJrIL6pBYJLnLlzFviN1iomDRP7HpypHU7oTc9RdUARFXf47V/GuSo8aA3XTxx5cmQOw1emqyjmHTV5A//zXCpr+Fwuv6K3eEK3M47JiLsuoSFzVZJ7Dpyi47T1KoUIfHOZN0kV3RRHREpnLDXJxN7tcvY6supXDpe4Te82qr//5uLuJPSWgVjqWXMvPTHZccc9MomDG+m4siah4Oh4M9e/bw008/MXToUAYNGgSAXC4XiQxBEARBaCaSXIncTYnczbUDqa+FJEkoFc4B5R5uSny1GmLD6k8yOBwODDXWusRGSUUNpbUfl1bW1B031Fgxo2StsQc/GzvjITNTZveAYglOgceOIjpEmIiL9KVDpA9xET4E+rq1iOSOIAhtQ3R0NE888QRPPPFEg86/MCL0t69DF45f2Cx2MYvFQllZGZ999hnDhg0DICkpifT0dD7++GMSExO50ujRK92vtbq4xZ7+9F7Kt/yApSQHY8bhmyKZcS6ngjfm7MFstRMW4MHfH03E10tD385B7E7LZ+7qE+QW69iwL4stB3MYf0s77hwRh5d747UdNFts/OeHg2w7lAvAgG4hPP+HvmjUTb+cJ5dJJMaHkhgfSk5RNbvTClApZPh5a/D1ciYpfLUa1MprbxtpM1RjOOds2xV4x1OoAiJqF4Sdu9pt+krsxmoMp/dhOO2c3SUpNWgiOtYuCndBHd6xVVV+Ohx2ilf8P8wF6SDJCJ707O8mMgBkChUyTxV4+jboPjU5J8n/7jWsFUXkf/8GYfe93qp+h22pHDYLpvz0X79Pc05dNqcQQKZ2r/se1UR1QR3SHkmhvOw8VWAkQROeoHDJv6jJOkbpxnkEjH6wOb6UVk8kM4QWrdpg5r9LjtT94Abw9XIOO7p1YIzrAmsGBoOBH3/8kdOnTwNw9OhRkpOTkctbT39pQRAEQRBaPkmS8HBT4uGmJDrkyq0yDDWWX6s7KoxkFVZzNqeCczkVGE029EYLh8+UcPjMrwOytR6qusRGh0gf4iJ98NNq2sxCnyAILZuXl3MB77cVGHq9/pLHL+bh4YFcLmfgwIF1xyRJIjk5mcWLFwPOSo8L16jvuvVVbbRmkkyOZ+ckrJUllG34GnNhhqtDanK5xTr+9r9dGGqs+HtreOOPyfh6OattJEkiqXsY/buGsGFfFvPXnaSsysSyzWdZv/s8U0Z0ZMKgdte1yH+xaoOZt77ay7H0UgBuGxjLIxO7u2SuRESQF1OGN96CuP7ETrDbkFQaPDoNQKZUow5ph3e/23A4HFjK8qnJPl63cGytKMJhqcGYcQRjxhHnRWQK1KHt0UTVLhxHdEbu1nL/7ZVvWYD+5C4A/Ec9gHv73k1yH01EZ4KnvEjBwn9iKc6iYMHbhN7zKjKV2BB7PUwFGZRtnEtNzql6Z5zIPX0vSl50RRUY2eC5cB6dE/EZOJmKHUuo2rcadWh7vLoPaewvoc25rmRGYWEhBQUFtGvXDrVajUKhqHdHgyBcq9JKI8czyvj3t/uRySSstkt3vLQL9+bDZ4e6JrhmlJmZyZIlS+rKonv16sW4ceNEIkMQBEEQBJdx1yhx1yiJDL50McNud5BbrONsTgVnsys4k13BudxKzBYbVXpzXa/tC3y91JckODpE+tQtEAmCIDSmC7MysrKy6NSpU93xzMzMSx6/WHR0NHa7HavVesmQcYvFUpeIbdeuHRUVFVRWVuLt/WvVW2ZmJhEREQ0aTt4aXWhbaSkrwG4yIlO3zcXR4nIjr3y+k0qdGS93Fa8/mkSQn/tl58nlMsYkxjCkTwQrt6WzeNMZ9DVW5q4+zqrt6dw9ujMj+0Uil1/7ellhmYHXvthFdqEzEffA+K5MGtqhzWwGuNBK6kIi42KSJKHyD0PlH4a2l7MCyFpVWtfOx5h1HEtxFtitmHJPYco9VTvHS0IVFIkmsisenRNxi2k5c1V1aduo2OFMhnr1GY02YVyT3s+9fW+C7niSomUfYMo9TeHifxEydWa9FQLCldmtZgoXv4O1srjumMI3BE1kV9xqk2gK35Ab+nfpO/guTPnpGNMPUrLmM1SBkahD2jVG+G3WNSUzDhw4wFtvvcWJE84OunPmzMFmszFr1ixefvnlumFYgnAtbDY7+04Usu1gLlsvqsCw/yaRMf3WLiTGhzZ3eM3Kbrezbds2tmzZgsPhQKVScdttt9GjRw9XhyYIgiAIglAvmUwiMtiLyGAvhvV1DtK12ezkFOk4k13OmewKzuZUkJFXhcVqp7zaxL7jhew7Xlh3jQBvTV1iIy7Sl7hIn0Zt0yEIws0pOjqaiIgI1q5dy6hRo+qOr1+/npiYGMLCwi57zqBBg/jyyy9JTU1l8uTJAFitVrZt20bfvn0BSE5OBmDdunVMnToVALPZzJYtW7jlllua+styGVVQTO1HDsxFmWgiO7synCZRqTPx6uydFJcbcVPL+fsjiURdpWoRQKNScOeIjoxJjGHRxtOs2p5BaWUNHy86xPItZ5l+a1cS4xu+4Hk2u4LXv9xNebUJhVzGM3f3ZnDv329H1FpYKouoyXauK3p2G9Sg5yi0/nh2uwXPbs5/XzZjNTXZJ+sSHKb8c2C3YS7KwlyURdWBtfgOvQef5BSXJ4Bqck9TvOoTADQx3QkY/VCzxOTZdSD2Gj0lqZ9jzDhM0Y8fEjTpmQZXDQhQtW+NM5EhkxM4/nHcYnqg8GpYu6+GkmRygiY+Te6cF7FWFFK4+F3CH3wXufvVX3duZg1OZhw5coQHHniA0NBQ7r//fubOnQuAt7c3CoWC559/Hg8PD4YMEeUwQsPpDGaeeG8zJRWXD5JqH+HN9Fu7IpckOsf63XCJZmuwcuVKDh06BEBoaCiTJ0/G39/fxVEJgiAIgiBcG7lcRnSoluhQLSP7RwNgsdrJKqjibE5FXYLjfF4VNruDksoaSioL2J1WUHeNUH8P4qJ+TW60D/dulh7hgiC0LY8//jgzZ87E29uboUOHsmnTJlJTU/nggw8A58DvrKwsOnTogKenJ0lJSQwZMoQ333wTg8FATEwM8+fPJzc3l/feew+A8PBwJk2aVHdOdHQ0X331FZWVlTz88MOu/HKblNzNE4V3ENbKIkwF6W0umWGosfD3L3aTU6RDIZfxlwcG0DGq4QuXWg8VD90ez4Rb2vHdupP8fCCbnCIdb3+9l87RvswY341u7a7+/n7/iULembePGrMNDzclf32gP/HtA270S2tRdGnbAZB7eOMWe30bN+VuXnh07IdHx34A2M01mPLOUJN1Av3pvZgLMyjfPB9bdRn+ox902QK+tbKYwkXv4LBZUPqFEpzyXLMOedb2GY29Rk/Zz9+iP7mLklQPAm59zOUJntbAZqiiYscSALR9xzRp+ye5mychd75E7tczsVYWU7TsfULufkUknq6gwf+CPvzwQyIiIli6dCkGg4Gvv/4agO7du7NixQruvvtuPv/8c5HMEK7Jhn3ZlyQyQgM8uGNQO4YlROKuufnK3xISEjh69CgJCQmMHDkShUK8YRcEQRAEoW1QKmS0j/ChfYQPYxKdx8wWG+fzqy5pUZVVUIXdAfmlevJL9Ww96KzclUkQFaIlrnb2RlykL9GhWpQK0e5WEIQrS0lJwWw2M2fOHBYtWkRkZCTvvPNOXWeJzZs3M3PmTObNm8eAAQMA+Oijj/jwww+ZPXs2lZWVdO3alTlz5hAfH1933ddffx2tVsvs2bMxGAx069aNr776iujoaJd8nc1FFRyDtbIIc+F5V4fSqMwWG299tZez2RXIJHjxvgR6xgVe17WC/Nx55u4+TBzSnnlrTrD/RCEnM8t5+ZPt9O8awvRbuxAdevmu63W7z/PpkiPY7Q6CfN34+yNJl7V2bO0cDge6Y1sB8Oh6S6Mt1spUGtxiuuMW0x2fgZMoXvkJumPbqDqwFpu+gsA7nkKmaN6KT7vZSMHCf2LTVyDTeBA8daZLBnH7JE/CVqOjctdyqg9tQObmif/w+5o9jtamfNsi7CYDMo0HvrdMbfL7qYKiCRz/OEXL3sd4/ihlP3+L/4j7m/y+rVGDV0oPHjzIn/70JzQaDUbjpbvoPT09mTp1Kh999FGjByi0XSfPl/HlirS6z997avA17XpoC2w2G0ajsW5AXHh4OH/+85/x8fFxcWSCIAiCIAhNT6WU0zHK95LfAWtMVs7lVnImu4IzWc42VfmleuwOOJ9fxfn8Kn7amwU4EySxYVo6RvrWVXGEB3oic8FwVEEQWq5p06Yxbdq0eh9LSUkhJSXlkmMajYaXXnqJl1566YrXVKlUzJo1i1mzZjVqrC2dOiQWw+m9mNrQEHCbzc673+znyNkSAJ6Y2ouk7jfe4jo2zJu/PZzI0XMlzF11nFNZ5ew9XsD+EwUMT4jinjGdCfR1w+Fw8O3akyzccBpwdql49aFE/LRtb56UuSgTS3E2AJ7xg5vkHpJcSeAdTyL39KVyzwr0J3djM1QRfOfLyDUeTXLP33I47BT9+CHmovMgyQhKeQ6Vf3iz3Ls+fsPuxW7UUX1oA5W7liPXeOKTPMll8bR05tI8qn5ZB4DPwCnI3ZsnCeXZdSCmgnQqdy2ncvcK1CHt61qrCb+6pm3fVxtiZTKZsNvtNxyQcHMwW2y8P/+Xus/HJcXcdImMsrIylixZgsPh4MEHH6yrwhCJDEEQBEEQbmYatYJu7fwvacVRbTA7kxvZ5ZzJclZwlFXVYLHaOZ1VwemsCtjhPNdNraBDRG31RpQPHSN96x3cKgiCIFw7VbBzCLi5OAuHzXrDLXMOnCxkwU+n6RkXyORhHZq9naDd7uCjhYfYc8zZ5vCh2+Pr2iP+lrkoE4fdds3Debu3D+BfTw5i19F85q05Tm6xng37sthyMIfxt7SjorqGnw/kANC3cxAvTe+HWxttq6hLc1ZlKP1CUYe2b7L7SJIM/5H3I/fypWzDXGqyjpM376+ETvsrCm3Tt/Iu3zwfw+l9AASMeQj32J5Nfs+rkSSJgHGPYq/Roz+5i7Kfv0Wm8UDbZ7TLYjIXZ4MkoQpoefNgyjbNA7sNhU8Q3k08rP23/Ibeg7kgA2PGYYpXfYIyIAJ1cEyzxtDSNfjVsWfPnqxatYrp06df9pjBYGDRokV07969UYMT2qbyqhpmvL4Oe+18bw83JY+l3FwDrtPS0li5ciVmsxmAjIwM4uLiXByVIAiCIAhCy+TlrqJPpyD6dAqqO1ZaaeRMdgWna6s3zmZXoDNaMJqsHD1XwtFzJXXnRgZ7khgfSlL3UDpE+Ihe0YIgCNdJHeJMZmCzYi7Jue5FNofDwcpt6Xy5Ig27A06cL+OnvZnMGN+NIb3Dm+V12uFw8OXKNDbtd1YKTB3ZkYlDLl9gdzjsVOxYSvmWHwAH7h364jfsXlRBUQ2+lyRJJPcIY0C3EH7am8X3609SVmVi2eazdeeMHhDNnyb3QC5vm+0THQ47umPOeRme3QY3y9+xz4DbUXj6UrTiYyzFWeR+PZPQu19BFRjZZPesPrKZip3LANAmjEPbd2yT3etaSDI5QXc8RYHJgDHjMCWps5FpPPDsOrBZ47DqKijb9A26o5tBJids+ltowlvOepgx81hdIspv2L1IiuZtge8cCP6McyB4ZRGFi99xDgR3QYuylqrByYwnn3yS++67j3vvvZcRI0YgSRJHjhzhzJkzfPPNN+Tl5fHaa681ZaxCG2Cy2Fi6+WxdIgPg+T/0vWlaAVgsFlJTUzl48CDgbNGWkpJCbGysiyMTBEEQBEFoXfy93fD3diMx3tkKxOFwkF+qr6vcOJNdzrncSkxmG9mFOrILz7Bo4xkCfNxIjA8hqXso3WL92+yikSAIQlOQe/kjc/PCbqzGXJhxXckMq83OZ0uPsG53JgBhAR4UVxgprazhve8OsGZHBo9MjCcusmm7NyzccJoVW9MBGJccw71jLx9objPqKF7xEYazB+qOGc4ewHD2Fzx7DMVv8F0ovBs+W0MulzE2KYahfSJYsS2dJT+fwVBj5d5xnZk6omObTrbXZB3HVl0KgGf8oGa7r2e3QcjctRQufhdbdSl58/5KyNSX0UR2afR71WSfpHjNfwFwa9cT/1EPNPo9boSkUBI85QXy57+OKfc0RT9+hEztjnv73k1+b4fdRtX+VMq2LsBhMjgP2m0Ur/qY8If+1ewzTerjcNgp3TAXAHV4Rzy6JLskDrm7F8FTXiRv7iysFUUULf8PIXfNEgPBa0kOh8Px+6c57dixg7/97W/k5ORccjwwMJBXXnmF0aNdV550vRISEgDYv3+/iyNp2xwOBz+sP8X89acuOf7pi8Pb3ECrKykqKmLx4sUUFxcD0KFDByZOnIiHR/P0bBQE4eYlftY1LfHnKwgtl81m52xOBbvTCth1NJ/cYt0lj3u5K+nX1ZnY6N0pCLVSvEkUhPqIn3VNrzX9GefPfw1jxhG0/W4jYPSD1/TcaoOZf87dVzefYmDPMJ6e1puKahNfrTrGziP5AEgSjEiIYvqtXfBtgtkRq3dk8NnSIwAM7hXOc/VssjQVZFC45F9YKwoB8Oo9GrfYHpRvmY+lNM8Zp1yJNmEcPskp19VXX2+0UG0wE+Lf9tcFilf/l+pDG1CHxRH+wD+b/f6mgnQKfngLm74CSaEiaOLTeHQa0GjXt1QUkfvVS9gNVSj9wwib8c9mm9FxrWzGavK+eRVLcRaSUk3oPa+iibg8mddYjFnHKF33BeYi58wzmZsn2r7jqNixBBx2vJMmtoih5NVHt1C8wjkPOuz+t5r0z6QhdGnbKPrxPwD4JKfgN+wPLo2nMTTGz7prasI3cOBAfvrpJ44dO0Z2djZ2u53w8HDi4+Pr+v0LQn1Sd52/LJFx54i4myaRkZWVxTfffIPVakUmkzFixAiSkpLa9K4LQRAEQRAEV5PLZXSK9qNTtB/339aV7MJqdh3NZ1daPmezK6g2WNi0P5tN+7NRq+T06RREUvdQ+nUJxtPd9TsEBUEQWiJVcAzGjCOYC89f0/Nyi3W8/sVu8kr0AEwb1Ym7R3dCJpMI8Vcw8/7+HDlbzP+Wp3E+v4oN+7LYcSSPaaM6MmFQO5SKxkk4b/4lh8+XORMZfTsH8fTdfS5LZFQf3kTJ2v/hsJqRFCoCxj2KV49hAHh06k/14U2Ub12ATVdO5Z4VVB/agHfSJLz734ZMqW5wLB5uSjzcmreNjSvYrWb0J3YCzVuVcTF1SDvCZrxNwfdvYCnLp3DJvwkY8zDavmNu+Np2k5GChf/AbqhCpvEkZOqsFpvIAJC7eRF696vkzfsL1opCCha8Tei9rzf6bAZrdTllm+bVzUoBCa/eo/Abeo8z+edwULFjMZW7V+DRaQCa8I6Nev9rYbeYKNs8HwCPLkkuT2SA89+KKf8slXtXUbFzKaqQdnh2SXJ1WC53zRkISZKIj48nPj6+KeIR2pj8Ej3z159k84Ffq3lShnZg1IAowgM9XRhZ8woLCyMgIICamhomT55MRETLG3AkCIIgCILQ1kUGexEZ7MXUkR0pLjey51g+u47mk5ZeislscyY6juYjl0l0bx9AYvdQEuND8Pd2c3XogiAILYY62DkA21yYgcPhaNAmvcOni/nHvH3ojRaUChlP3dWbIX0uf1/co0Mg/3lmCOv3ZPJN6kmqDWa+WnWctbszefj2ePp1Db6hTYH7jhfwn+9/weGALjF+vHx/P5SKX9sNOqwWStZ/SfXBnwBQ+AQTPOXFSxZ5JZkcbe9ReMYPpnLvaip3LcNuMlC++Tuq9qfiO3gqXj2Hi5YwFzGe/QW7yQCSDI8uzTuj4WJKn2DCpr9FwYK3MeWfpWTtbKy6MnwHT7vu7yuH3UbR8g+wFGeBTE7w5OdR+oU2cuSNT+HlS+g9r5I376/YdOUUfP8GYdPfbJTYHTYrlfvXUL51IQ6zEQB1WBwBYx5GHdah7jzfQVMwnNmHuSiT4pUfE/7wv13Wbqpy72psVSUgV+A37F6XxFAfvxHTMRVmUJN5jOKVH6MKCEcV2PB5PW1Rg9tM1Tf4uz7z5s27oYCaW2sq5WxtjqWX8vIn2y85Njwhkmfu7uOiiJqXwWDA3d297vOKigo0Gg0aTeOXyAqCIFyN+FnXtMSfryC0flV6M/uOO1tRHTxVhNlqv+TxTlG+DKidsxERdHNUFgvCxcTPuqbXmv6MzSU55Hz+FACRj3+K0if4quen7szgs2VHsdsd+Hip+esD/ekU7fe796k2mPl+/SlW78jAXjt4s3fHQB6+I56oEO01x30svZRXP9+J2WonNkzL23+6Bc+LqiKslcUULvk3pnznUG73Dn0JvP1J5G5X34hpM1RTsXMplfvXgM0KgNI/DL+h9+Leqb/oyAAULH4Xw6k9uLXrRejdr7g6HOzmGgqXvofx3C8AePUcQcCtf7yuBFTpxrlU7l4BQMCtj6HtPapRY21q5qIs8r55BXuNDoV3EGHT30Sh9b/u6xkz0yhZ9wWW4mwAZO5a/Ib9wZngky6fU2YqSCf3q5fBbsM78Q78RzRs/bkx2fSVZH36OA6zEe8Bt+M/8v5mj+FqbPpKcua8iK2qBIVviHMgeAuu/LmaZm0z9ds5GQB2u53y8nJMJhPh4eHExbWc6fOC6205eOn3zNSRHRkzINpF0TQfh8PBrl272Lx5Mw888AChoc6sto+Pj4sjEwRBEARBEOqj9VAxol8UI/pFUWOy8supInal5bPveCF6o4VTWeWcyipn3poTRAZ7khgfytA+Ede1mCYIgtDaKf1CkRQqHFYz5oKMKyYzbDY7X648xsptziHbsWFa/vrgAIJ83es9/7e83FU8OrE7YxOj+d+PaRw6XczB08U88d5mxg+M5e59LEF1AAAgAElEQVTRnRrcEvBcTgWvf7kbs9VOaIAHrz2adEkiw5B+iKLl/8FurAZJhu+QafgkT6p38fW35O5e+I+8H22/cZRvXYDuyBYspXkULnkXdXhH/Ibfi1tUtwbF2RbZavR1A9Rd1WLqt2QqDSF3vkTxms/QHfmZ6sMbsekrCEp57prahFUd2liXyND2H9/qEhkAqqAoQu6aRf7817BWFpH//euE3ffmNc+AsVaVUrpxLvrjO2qPSGj7jsF3yDTkble+ljqkHT7JKVRsX0TlnpXOdlMRnW7gK7p25VsX4DAbkbl54jNwcrPeuyHkHt6ETHmRvLl/wVpeUDsQfGaDXp/aogYnMzZt2lTvcZvNxsaNG/nrX//KQw891GiBCa3fhZoftUrO/NfHoboJBirq9XqWL1/O2bPOnRxbtmxh2rRpLo5KEARBEARBaCiNWkFyjzCSe4RhtdlJO1fCrqP57E4roKyqhuxCHdmFZ1i08Qzd2vlza3IMSd3DLmlTIgiC0JZJMjmqoGhMeWcwFWTg0TnxsnP0RgvvfrOfX04VATCgWwjP/aEvbuprn7caFaLl9UeT2He8kC9WpJFfomfFtnR+PpDDfeM6MzoxBrnsytUPucU6/va/XRhqrPhpNbzxx2R8vZwdExwOOxXbl1C+dQHgQOauJWji07jH9rzmOJXeQQRNeAKfAbdT9vN3GM4ewJR7mvxvXsW9Q1/8hv0BVVDb3+D5W/qTu8BmRVKo8OjYeAO3b5QkVxA4/nEUXn5U7FiC4ewB8r/7OyFTZyJ3//3NCsasY5SkzgbArX1vl1QUNBZNRCeCp7xIwYJ/YCnJoWDBW4T+4W/IVL/fZtNhs1K5bzXl2xbiMNcAoA7v5GwpFdquQff3vWUyhtP7MBed/7Xd1DUklW6EuSSHqtq2cr633Pm7lViuog5tT8Ctj1G88v9hPPcL5VsX4DfkbleH5RI3PLVbLpczevRoDh8+zL///W8WLFjQGHEJrdj5/Cq+TT3BmexyAPp3DbkpEhkZGRksXboUnU4HQJ8+fRg7dqyLoxIEQRAEQRCul0Iuo1fHIHp1DOKPk3pwJrucXUfz2X44j8IyA8fSSzmWXoqPZxoj+0cxNimGYL+G7TgWBEFozVQhsZjyzmAuzLjssfwSPW/M2U12ofO98eRhHZh+a9fLhmxfC0mS6N8thN6dAlm5LZ0ffjpNtcHMp0uOsGbneR6ZGE+PDoGXPa+kwsgrn++kUmfGy13J639Mqnudthl1FK/4qK5qQB3ageDJz6Pwvvw610IVFE3IXbMwZh2jbNO3mHJPYzh7AMPZX/DsMQTfwXeh9A66oXu0Jrq0bQC4d+yHTN2yZlBJkuQcRu3pS+m6LzHlniZv3l8ImfYKSp8r/x1ZygsoXPwvsFtRBkQQPPGZVj8jxb1dL4ImPk3Rsvcx5Z2hcPG7hEydhaS48oB64/mjzpZSJc7OLDJ3Lf7D78Ozx9BrqhqQ5EoCJ/yZ3K9ewlKWR/mWH5qt1VPZxnngsKPwDWmUYfBNyavHUEz5Z6nan0rF9sWoQ9rj0am/q8Nqdo22fSgmJoaTJ0821uWEVmzu6uPsOVZAWZUJcJbtt2V2u51NmzYxb948dDodKpWKyZMnM2HCBJTKK7/oC4IgCIIgCK2HTCbRKdqPGeO7MXvmSF57JInE+BBkElToTCzedIZH3v6J177Yzd7jBdjsDRpNKAiC0Cqpg2MBMP0mmZF2roTnPtxKdqEOhVzi6Wm9mTG+2w0lMi6mVMhJGRbH5y+PYFT/KCTJuaHyL//dyT/m7qWgVF93bqXOxKuzd1JcbkSjkvP3R5KIrm0PaCpIJ3fOC3WJDK8+o52zAm4wkXExt6huhN3/NsFTXkTpHw440B3ZTPZ/n6B0w9fYDNWNdq+WylpVSk3mMQC84oe4OJor804YR9Dk55DkSiyleeR9PRNT4fl6z7XX6ClY+A/sxmpkbl6ETJ2JrJXOL/gtzy5JBIz7IwDGjCMULv8Ah9122XnWqlIKl75H/nd/dyYyJBnahFuJ/L+Przgb4/eoQ2LxHTgFgMo9K6nJafo1ZmPGkbrXAP/h9yHJW/4anv/IGWgiuwBQtOIjzCWXj4Vo6264MgPAbDazYsUK/P2vf0CM0LrVmK0cOFHE0s1nOJ1VUXf8/tu6MqJfpAsja1p2u5158+aRmZkJQFhYGJMnT8bP7/eHmQmCIAiNZ9WqVfz3v/8lOzub8PBw/vjHPzJx4sQrnm+32/n8889ZvHgxxcXFREdH89hjj3Hbbbc1Y9SCILRWMplEn85B9OkcREmFkXW7M1m/5zxlVSb2nyhk/4lCAn3dGJMYzej+0fhqNa4OWRAEoVGpapMZtuoybPpK5B7ebNibySeLD2O1OdB6qJg1oz/d2jXNOpGvVsOTd/VmXHIM/1uexonzZew84px1NGloB24bGMsbc/bUJlVk/OWB/nSM8gWg+vAmStb+D4fVjKRQETDuj3j1GNokcUqShEenAbjHJVB9+GfKty7Apiujcs9Kqg5txCdpIt79bkOmaps/J3THt3OhfZdbu2tv3dWcPDsnIb9HS+HCf2LTV5D3zSuETHkRt5judec47DYKl33gXMCXKQie8gJK3xAXRt34tL1HYq/RUbbpGwyn9lCy5jMCbvsTkiThsFmo3LOK8u2LcVhqW0pFdHa2lAqJveF7+wxMQX96L+bCDIpXftKk7aYcdhulG+cBoInsgnunltMC7WokuYKglOfJnfMCtuoyChe/Q/gD7yBT3zyVwQ1OZkyfXn/vN7PZTEZGBlVVVTzxxBONFpjQuny/7hRLN5+95Ngzd/dmeEKUiyJqHjKZjJiYGDIzM0lMTGTkyJHI5a27tFAQBKG1SU1N5fnnn2f69OkMGjSIDRs28NJLL6HRaK7Y7u/tt99mwYIFPPvss3Tu3JnVq1fz3HPP4enpyZAhLXfXmCAILU+Ajxt/GNuZu0Z1ZO+xAlJ3nufQmWKKy418m3qS79edIql7KLcmxxLf3h9JapzdyYIgCK6kCooCSQYOO8aCDBYeV7Ksdk0gKsSLVx4cQIh/0+9Wj4v05Z0/38KWg7l8veoYpZU1LNxwmsWbzmC3O5BJ8MK9fenVMQi71Uzp+jlU1/bHV/iGEDz5BdTBMU0epySTo+09Es/4QVTtW03FzmXYTQbKN8+nat8atH3G4NV7FAov3yaPpTldaDHl2SUZSd4o+6mblFtUN8Kmv0X+D29gqy4j//s3CbrjSTy7DgSgdOM8jOkHAQgY92ibHezukzQRe42Oip3LqD68CZnGE7d2vShd/wWW0jwA5B4++A2/D8/uQxrtdxtJrnC2m5rzYm27qe/xHzmjUa79W7qjW+ra5PmNnNGqfj9TePoQPPkF8r55BUtpHkUrPiJ4yos3zUDwBr+S5OTUX7Yil8tp164d48eP55577mm0wITWpbjCCIBGJcfbU82jk7rTv2vbyk5fYLVakclkyGTOF4nBgwcTGxtLdPTNN8hLEAShJXj//fcZN24cs2bNAmDQoEFUVlby4Ycf1pvMyMrK4rvvvuP111/nzjvvBCApKYnz58+zbds2kcwQBOG6KOSyusHhucU61u46z4a9WeiMFrYfzmP74Twigz0ZmxTD8IQoPN1afisDQRCEK5Ep1Sj9w7CU5LBu9VaWZTrfD/ftHMSL9yXgrmm+1zhJkhjaJ4LEbiEs/vkMy34+i9lqB+DPd/YiuUcYlsoiipb8G1P+OQDc4xIIvP1J5M3cHkimVOOTnIJX71FU7FxK1b5UbPoKyrctoHzHYjw6DUCbMBZNZNdWtbhaH3Nxdt1isWf8IBdH03CqoCjCZ/yD/O/fwFKSQ9Gy97HpypEUKqr2rgLAO/F2tL1GuDjSpuU79A/YjDqqD/5E5Z4VVO5Z4XxAkqFNGIff4LuapL2WOjgG31umUL51AZV7VuHRaUBdW6XGYreYKNv8PQCe3QahCevQqNdvDprwjgSMfYSS1f/FcHofFduX4DvoTleH1SwanMxYvHixaJ0j1GvrwRy2HcoFYGjfSB6f0rJLB29EaWkpixcvJi4ujuHDhwPO6gyRyBAEQXCN7OxssrKyePbZZy85PmbMGFJTU8nOziYy8tJ2hxs2bECj0VzWhurbb79t8ngFQbg5hAd68tDt8dw7rgs7DueyZud5TmWWk12o43/L05i7+gRDeoczLjmGuMi2tQtXEISbh8M3CkpysJdkAtHcPrgdD06IR95I8zGulUat4N6xXRjVP5qV29LpGOXD4N4RGM4dpOjH/2A36kCS4TtkGj7Jk1y6i1nu5oX/iPvx7jeeqgOpVB3aiN1Qhf7ETvQndqIKikLbdxye8YOQqVrW0OyG0qVtBUDhE4Q6vJOLo7k2Cm0AYdPfpGDhPzHlnKT0p68A5/e1e4e++A2717UBNgNJkggY+wj2Gj36EzsBZzsm/zEPN3k1k09yCvpTznZTRSs/JuKR9xu13VTl7hXYdGVIciW+w1rvxnxtr5GY8s9R/ct6yrcuQBUSi0dcgqvDanINfuVOSUnh008/bcpYhFZq55H8uo8jgzxdGEnTOnLkCLNnz6agoIAdO3ZQUVHx+08SBEEQmlR6ejoAsbGX9mi9kGTOyMi47DmnTp0iNjaWnTt3cvvtt9O1a1dGjx7NmjVrmj5gQRBuKmqlnOEJUfz7ycF8+OxQxibFoFHJMVts/LQ3i2f/s5Vn/rOFn/ZkUmO2ujpcQRCEBjt5vozVJ5yDgSMU5Tw+pSeP3NHdZYmMiwX7ufPwHfEM6hVG+bZFFPzwFnajDpm7lpC7/4rvwMktph2LQuuP37B7iXricwJvfwJ1WBwA5qIsSlI/J/OjRylZ/yXm0lwXR3ptHA47umPbAefO99ZYZSJ38yL0nldx79i/9ogDZWAUQROfQZLdHO3FJZmcoDuexG/kDIJSnif0vjeapy2bXEHQ7U+ATIG1vICyzfMb7drW6nIqdi0HQNv/NpTeQY12bVcIGP0g6ohOgIOiHz/EXNsGrC1rcGVGWVkZAQEBTRmL0MpkF1azcls6p7PLAegc7cuEQe1cHFXjM5vNpKamcujQIQC8vLxISUnBx8fHxZEJgiAI1dXVAHh6XppM9/BwljzrdLrLnlNWVkZ+fj6zZs3iqaeeIiIigkWLFvHMM8/g5+dHYmJi0wcuCMJNp124N49P6ckD47vy84EcUndmkFlQzdnsCj7KPsSXK9IY3i+KMYnRRIdoXR2uIAjCFW0+kM1HCw8Ri5YxWgiSVzGgb8tqM20z6ihe8RGGswcAUIfFETz5eRTalrmuJVOo8Oo+FK/uQzHlnaXywFr0x7bjMBmo2reGqn1rcIvtibbvWNzj+rb4xXRTzimslUUAeMYPdnE010+mVBM8+XnKty7EXJiB/9iHkalbZ6XM9ZLkSnwGTGj2+6qCovEddCflW76nau9qPDoNwC2q6w1ft3zrDzgsNcjctfgmpzRCpK4lyZUEp7zgHAiuK3cOBJ/xzzb9fdrgZMaECRNYsGABycnJRERENGVMQgtmstiw2x0cPFXEP+buu+Sxbu3a3kDDgoICFi9eTGlpKQAdO3bkjjvuwN3d3cWRCYIgCAAOhwPgsp8/F45fmG90MYvFQllZGZ999hnDhg0DnDMz0tPT+fjjj0UyQxCEJuWuUXLbwFhuTY7hxPkyUneeZ/vhPPQ1VlZuS2fltnS6xPgxNimagT3DUStb9oKVIAg3D7vdwfx1J1mw4TQAtoAIsIOEA3NxFprwji6O0MlmrCZ3zktYKwoB0PYZg/+oB5AUrWNWkTqsA0Fhf8Y24n6qD2+k6pd1WCuKMGYcxphxGIU2AK8+Y9D2GoHcw9vV4darurbFlCo4FlVA615DlGRy/Ibe7eowbko+SRPRn9qDuSCd4lWfEPHwe8hUmuu+nrkoi+rDmwDwHTS1SWZ+uILCy5fgyc+T983fsJTkULzqY4JSnm9za7QXNDiZIZPJSE9PZ8yYMURFReHv73/ZAoEkScydO7fRgxRcy2azcyqrnKU/n2XPsYJ6z5kwqB3jb2lbVRlpaWksX74cm82GTCZj1KhRDBgwoM2+GAiCILRGXl5ewOUVGHq9/pLHL+bh4YFcLmfgwIF1xyRJIjk5mcWLFzdhtIIgCL+SJImusf50jfXn4Tvi2bgvi7W7M8kv0XPifBknzpcxe3kaw/pGMDYxhuhQUa0hCIJrfb36OMs2nwWgV1wgL01PoPTLldiqSjAXpLeYZIbu2HasFYVIciUBtz6GV4+hrg7pusjdvfBJmoj3gAkYzh2kav9ajOkHsVaVUL75O8q3LcCzSzLahHGow+JazFqFw2apm7HQmqsyBNeT5AqCJjxBzpcv1Lab+o6A0Q9d9/VKN84Fhx2lfxja3qMaMVLX00R0JmD0g5SsnY3+5G4qdy3Dpw1UntSnwcmMHTt24OvrHE5nMpnIy2v7PbgEp0+XHGH9nsx6H0voEszL9/drkzvGAgMDAfD19WXKlCmEhYW5OCJBEAThty7MysjKyqJTp18HC2ZmZl7y+MWio6Ox2+1YrVZUKlXdcYvF0mLeBAqCcHPx9lSTMiyOiUM6cPRcCet2Z7LraB56o4VV2zNYtT2DLjF+jEmMZmDPMDSqBr+NEwRBaBRF5QZWbjsHwKj+UfxpSk8Uchm64FgMVSWYCi6fU+YqNVnHAHDv2K/VJjIuJsnkeMQl4BGXgKUsn6pf1lF9eBP2Gj26tK3o0raiCmmPd8JYPLoObNRBydfDcO6Qc9g6Ep5dB/7u+YJwNaqgKHwHT6V883yq9q3Bo3MiblHdrvk6hnMHMaY728f7DZ+OJG97v0t59RntHAh+eCNlP89HFRyLe/verg6r0TX4b27Tpk1NGYfQgmUXVl/y+R8ndadTtC+ebipCA9pGSdYFNpsNudyZmAkODuaee+4hPDwctdq1vwwIgiAI9YuOjiYiIoK1a9cyatSvu2vWr19PTExMvYnoQYMG8eWXX5KamsrkyZMBsFqtbNu2jb59+zZb7IIgCL8lk0n0jAukZ1wglTpTvdUa//tRVGsIgtD8Fm08g9XmwE+r5rGUHijkzk4dqpBYDGf2YS4879oAazkcDmqyjgOguY4Fz5ZO6ReK/8gZ+A65G13aNqoOrMVcmIG54BzFqz6hdONcvHoOR9tnDEpf18wx0R3bBoAmJh6F1t8lMQhti0/SRAyn9mDKP0fxyk+IeOT9a2o35bDbKNs0DwBNdDzucQlNFapLSZKE/9iHMRdnYco7Q9HyDwh/8F2XvRY0lSsmM2bOnMm0adPo2bNnc8YjtEA6oxmAe8d25q5RnX7n7NbJ4XCwY8cOjh07xoMPPohS6eyl2a5d22qdJQiC0BY9/vjjzJw5E29vb4YOHcqmTZtITU3lgw8+AJwDv7OysujQoQOenp4kJSUxZMgQ3nzzTQwGAzExMcyfP5/c3Fzee+89F381giAITheqNSYNdVZrrN11ebVG52hfxiTGcEsvUa0hCELTKSozsGGvs+p1yvCOqC7qzKAOjgHAXJyFw25z+WBqS2kuNn0lAG7RNz4suKWSKdVoe4/Eq9cITLmnqNq/Ft2JXdiNOip3r6ByzyoCxz/e7JUpdpMRw2nnfFXPboOa9d5C2yXJ5ARO+LOz3VRFIWU/f0fAmIa3m6o+/DPmoixAwn/E/W26Gl+mUBE8uXYguL6SwsXvEHb/P25o1khLc/lUzFrLli0jKyurOWMRWqDv1p4ku1D3+ye2Yjqdjm+//ZaNGzdSUFDAzp07XR2SIAiCcA1SUlJ47bXX2L59O48//jh79+7lnXfe4dZbbwVg8+bN3HXXXRw7dqzuOR999BHTpk1j9uzZPP7445SXlzNnzhzi4+Nd9WUIgiDUS5IkenQI5MX7Evj61TE8ML4bYbXV0Sczy/lwwUFmvLaOz5ce4Xx+lYujFQShLVq06UJVhoYxidGXPKYKcbb0dFjNWEpyXRHeJS5UZcjctSgDIl0cTdOTJAlNRGeCJj5N1BOf4zvkbuRe/uCwU5L6Oebi7GaNR39qDw6rGUmuxLNzYrPeW2jbVIFR+A66C4Cq/WswZqY16Hl2s5HyLd8D4Nl9COrQtr9pWaH1JyjlOZDJMRdlUbz6UxwOh6vDajRi+45wVQdPF9V9HBfp68JImsa5c+dYtmxZ3aDYvn37kpyc7OKoBEEQhGs1bdo0pk2bVu9jKSkppKRcOvxMo9Hw0ksv8dJLLzVHeIIgCI3CWa3RgUlD2ztna+zKZOfRPPQ1VlbtyGDVDlGtIQhC47q4KuPOEXGXVGUAKLSByDSe2Gt0mAozUAVFuSLMOsbaeRmayC5tevd1fRSePvjeMgVtwjhyv3gOa2UxRcvfJ+yBd5ApVL9/gUagO7YVAPe4BGSattWWXHA9n6Q7attNnaV41YV2U25XfU7Frh+x6SuQFCr8ht7TTJG6nltUN/xHzqB0/Zfoj++gMrQ9Pol3uDqsRnHFygxBuNjtg9rRp3OQq8NoNDabjQ0bNvDtt9+i1+tRq9VMmTKF8ePH17WYEgRBEARBEISW6EK1xgu/U63x2dIjZBaIag1BEK7fwo2nsdoc+HtrGD0g+rLHJUlCdaHVVKFrh4A7HA5qMp2VGW7RbW9eRkPJNR4ETXwaJBnmoizKNs5rlvtadeUYM44C4BkvWkwJje9CuynkCqwVRZRt+vaq51urSqnc/SMA3gNuv+lmuGgTxuHZfSgAZZu+xZBx2LUBNZKrbtXZv38/Npvtmi44ceLEGwpIaJl8vNrOAGy9Xs8PP/xATk4OAOHh4UyePBlf37ZXeSIIgiAIgiC0bRdXa6SdK2XtrvPsPJqPvsbK6h0ZpO7MYMKg9tw7tjMatajUEASh4ZxVGc7243cOv7wq4wJ1SCw1mWmYClybzLCWF2DTlQFtc/j3tdBEdMZ38F2Ub/meqv2puMX2xKNjvya9p/74DnDYkWk8cG/fp0nvJdy8VIGR+A2eRtnP31J1YC0enRNxi+le77llW37AYTUj9/DBJ+nmW6+WJImAcY9iLs7CXJBO0bLageA+rXuz+lV/m124cCELFy5s0IUcDgeSJIlkhtDiaTSaul5xycnJDB8+HLnctUPKBEEQBEEQBOFGSJJE9w4BdO8QQKXOxKb92aTuOk9+iZ4ft55jV1o+j0/pSZ9OrfsNrCAIzWfhxtPY7M6qjFH1VGVc8Gtlxvm6tSFXuNBiSqbxdHm7q5bAJ3kSxowj1GQdo3jVx6gffr9Jd6br0rYB4NE5CUkhOl4ITcc78Xb0p/ZgyjtD8apPiXj08nZTpoIMdEd+BsB38F3I1FdvR9VWyZRqgqe8QO6cl7Abqihc/C5h97+FTNl6N61fNZkxdepUevXq1VyxCC1IZkEVm/ZlU1RmcHUojeLiX6jkcjmTJ0+mtLSUDh06uDgyQRAEQRAEQWhc3p5qJg3twIRB7Vjy8xl+WH+aojIDf5u9i+EJkTx0ezxaj+bpny4IQutU2MCqDAB1sHOgrr1Gh7WqGKW3a5KmF4Z/O+dliK7qkkxO0B1PkfPFs9iNOopWfEjoPX9DkjX+Zk5zaR6m/LMAeMYPbvTrC8LFLrSbyv3ieayVRZRt/IaAcY/WPe5wOCjbOBdwoAyMxKvXCNcF2wIovYMInvQs+fNfx1yYQcmazwi8/clWO1foqsmMhIQEJkyY0FyxCC3EnrR83vxq7yXHrvaLS0tXUlLCsmXLGDt2LJGRkQD4+vqKtlKCIAiCIAhCm6aQy7hrZCeSu4fxyeLDHEsvZdP+bH45WcSjE7tzS6+wVvtGVhCEprXooqqM0YlXrsoAUAaEI8mVOGwWzAXnXZfMyKwd/h3d1SX3b4kUWn8Cx/+ZwkX/pCbzGBU7l+F7y5RGv48uzTn4W64NQBPVpdGvLwi/pQqIwHfINMo2fUPVL+vw6JJU127KeO4XjOed81v8h09vkgRea+MW0x2/EdMp2/A1urStqEPb491/vKvDui4iVS3UsdsdfPD9L5clMkYPiGZI7wgXRXVjDh06xOzZs8nLy2PZsmXXPANGEARBEARBEFq7yGAv3v6/gfxpcg/c1AoqdCbe/XY/b8zZQ0mF0dXhCYLQwhSU6n+tyhjREaXi6guBkkxe19bJ5KIh4JaKIqxVJQC43eTzMn7Lo2M/tAnjACjfuoCanJONen2Hw4HumLPFlGe3W0RVjNBsvAdMQB3eEYDiVZ9gNxlx2G2U1g69d4vtiVv73q4MsUXx7j8ez26DACjdMBdjZpqLI7o+4hVGAKC8qoY7XljBpv3ZdceSuoey9J3xPDG1V6sbAG4ymVi2bBk//vgjFosFrVbLxIkTxWwMQRAEQRAE4aYkk0mMS47l0xeH079rCAD7jhfyp3c3sXpHBna7w8URCoLQUizaeAab3UGAt4bRAxo2e0IVHAuA2UVDwGtq52VIave6GR7Cr/xGTHcmnBx2ipb/B1uNvtGubco7g7W8AKBuoVQQmoMkkxM4/nEkuRJrZTGlm+ZRfXADlpIcQMJvxHRRgXoRSZIIuO3/UAXFgMNO4dL3sFYWuzqsa3bFZMakSZOIihIDk24W//7uwCWfP3tPH2bN6P+7OzBaovz8fGbPns2RI0cA6Ny5M4899pj4fhYEQRAEQRBuegE+bvz1wf68eF8CPp5qjCYrny09wsxPt5NdWO3q8ARBcLGCUj0b99VWZYz8/aqMC9QhtckMF1VmGDNr52VEdBYtZeohU6gImvgskkKFtbKYkjX/xeFonCT2hcHfysAo1CKRJDQzVUAEvkPvBqD6l/WUbvoGAK+ew8X3Yz1kSjXBd76IzM3TORB8yb+wW82uDuuaXDGZ8Y9//IOePXs2ZyyCC5VW/lpe/r9ZIxnWN9KF0Vy/ffv28eWXX1JWVoZcLmfcuHFMnToVNzc3V4cmCIIgCIIgCC2CJEkM6hXOJy8OZ0Q/5+/9x7DkZ7wAACAASURBVDPKePK9zSz46RQWq93FEQqC4CoLN5yuq8oY1b/hGwIvVGZYq0qwGZo/MXqhMsMtWrSYuhJVYCT+ox8EQH9iF9WHNt7wNR12G/oTOwDwihdVGYJrePcfjzq8EwAOsxFJqcZ3yDQXR9VyKX2CCZr4LEgyTPnnKEmd3WjJzeYg2kwJl/jTlJ6E+Hu4OozrZjabsdls+Pn58dBDD9G/f39RUiYIgiAIgiAI9dB6qHh6Wh9efzSJYD93rDY73649ybP/2cLprHJXhycIQjMrKNXXtZ6+lqoMAFVQNOB8793c1RnWqlKsFYUAaKLE8O+r8eo1Eo8uSQCUrv8Sc0nODV3PmHEEm74SAI9ut9xwfIJwPSSZnMAJf0ZSqADwSZyIwsvPxVG1bO7teuI37A8A6I78TNWBdS6OqOFEMkOgqMxAbnHj9Ut0peTkZEaNGsWjjz5KaGioq8MRBEEQBEEQhBavd6cgPn5+GBOHtEcmwfn8Kl74aCtf/JhGjcnq6vAEQWgmdVUZPm7XVJUBIFNpUPqHAWAqPN8E0V1ZTZazxZSk1KAOades925tJEki4Nb/Q+EdiMNqpmjZ+zfUYkaXthUATeT/Z+/O46KstweOf2YGhmFfRFDZXHMB3HdFXBPUUrHSsvRXWlq2uG+35dqtm5jiekvTzLQsc8lKQ829NCt3S0ELZBEBAWWHgZn5/YEzOQGuwICe9+vlq5nvPM8zZxCDmfM95zTH2tmjosIU4o6pa9WjzvDZuPUaiUu3oZYOp0Zw7jz47+TmD6spSDhn4YhujyQzhNm8DCtlzali0Ov1HDx4kB9++MG0plAo6Nq1KzY2NWtguRBCCCGEEJaksbFizKMBvP9qD+rXdUJvgG8O/sWE+fs4Hp1q6fCEEJUsOT2XPderMp7o0+Su5mcaB29XdWVG/vUWUxqfpihUVlX63DWRSmOPx5CJoFCiTY0jY8+6u7qOXltAbvSvADgE9KjIEIW4K7b1A3HpGoZCZW3pUGoEhUJB7UETsK7tC3odKZvnU5yVbumwbkmSGYKr2QWm2x1a1LFgJLcvOzubdevWsW/fPg4fPkxsrGWGjAkhhBBCCHE/ecjXlYWTgnk6tBlWKiWpGXm89dHPLPziOFm5NWtApBBG27ZtY+DAgbRs2ZLQ0FC2bt160+O/+eYbmjZtWurP22+/bTrm6NGjZR4zbty4yn45leKr3efRX6/K6HuHVRlGxqqIwuSYigztlozzMjS+Mi/jdmm8m+HaYzgAWUe/J/f8b3d8jbwLv2EoKgCllWl3txCiZlGqbanz2HSUGnt0uddI2fw+huIiS4d1U5KyfsAVaItJTs8D4JUnWuPiWP0rGv7880++/vpr8vJK4u7QoQM+PjVzYLkQQgghhBDVjZVKyfC+TekaWI9lG09yNjaDvUcTOB6VygtDAuneup7MpRM1RmRkJFOnTmXUqFEEBQWxe/duZsyYgUajISQkpMxzoqKi8PPzY968eWbr7u7uptvR0dHY2dnxySefmB3j5ORU8S+ikplVZdzhrIwbGSszitKT0BcVorSu/M8XinOuUpSeBICtJDPuiEvXoeTHnqYg/g+ubPsfNmMXYOVU67bPz/n9RwDsGrdBZetYWWEKISqZtVtdPAa/RvKG9yhMukDazlXUHviipcMqlyQzHnDvfvKr6XZ1fzui0+nYu3cvhw8fBkCj0fDoo4/SvHlzC0cmhBBCCCHE/cfH05H3XurOjiMXWbPtLNdyCpn32VF2/+ZBu+Ye+NVxwq+OU43YECUeXBEREYSGhjJ79mwAgoKCyMzMZPHixeUmM6Kjo/H396d169blXjcqKoomTZrc9JiaYsMPN1RldLi7qgwAG88GJTcMerSp8Wi8mlRQhOUzzcuwUmNTr1GlP9/9RKFU4TH4NRJXTUafn03qt0uo+9SbKJS3TmbpcjPJizkJSIspIe4Hdo3b4Ro8gqsHviD75G5s6jbCqe3Dlg6rTBZPZmzbto0PP/yQhIQEvLy8GDduHEOGDCn3+CtXrrB48WIOHTrEtWvXaNCgAc8//zyhoaFVGPX9I+lKjul2yya1LRjJzV27do1NmzZx6dIlAHx8fAgLC8PFxcXCkQkhhBBCCHH/UioVDOjagI4t6vDh5tP8ejaZ49GpZnM0XBxs8K3jiF9dJ/yu/9fX0xE7jfSsFpaVkJBAfHw8kydPNlvv378/kZGRJCQklFnlHxUVxahRo2567XPnzt0XG+sup+Wy99iNVRl3341cZe+MytENXXYG2pTYKk1m2Hg3lT75d8HKqRa1B04gZVM4BXG/c+3nrbh2G3bL83LOHQa9DoXaFrvG7aogUiFEZXPpFkZhcgx50b+QtvNj1B5+aLybWjqsUiyazLjTck+tVsvYsWPJzs7m1VdfxcPDg507dzJx4kR0Oh2DBg2ywKu4P7w2vA2ebnaWDqNcxcXFpKaWvGHq3r07vXr1QqmUkS9CCCGEEEJUBXcXW15/riOHz1xm/7EE4pKzSU7PxWCAazmFXPuzkNN/ppmd4+Fqi28dJ+rfkOTw9nC46xY2QtypmJiS2Q0NGjQwW/fz8wMgNja2VDIjNTWV9PR0zp49S0hICAkJCXh7e/Piiy+aNl7q9XouXLiAq6srQ4cO5cKFC7i7uzNq1CieffbZGtWGzTgro7brvVVlGNl4NiAvO4PCKhoCbhz+bevbokqe735k37QjTu1CyDq2g6sHvsTWL+CWH2AaW0zZN+tcJe3EhBCVT6FQ4vHIK1xKv0RRWiIpm9/H67n3sXJ0tXRoZiyazLjTcs+DBw8SFRXFxo0badmyJQDdunUjKSmJlStXSjLjDuTkaTnzVxoFWp2lQ7kt7u7uPProo9jZ2dGwYUNLhyOEEEIIIcQDR6FQ0K1lPbq1rAeUzN9LTMnh4uUs4pKziE/OJi45i/TMAgBSr+aTejWfo+dSTNdQKhV41bbH93qLKmOSo04te1TKmvMBsKgZsrOzAXBwcDBbt7e3ByAnJ6fUOVFRUQAkJiYybdo0bGxs2Lp1KzNmzECn0zFs2DBiY2MpKCggNjaWyZMn4+rqyp49e5g3bx45OTm8+uqrlfzKKoZZVUafe6vKMFJ7NiDvz2Nokys/maHLy6LoSkn8Gklm3BO3vqMpSDiLNjWe1K0L8Rq7AJXGvsxji64mU3gpGgCHgKCqDFMIUcmUNrZ4PjadS5/MRJdzlZQt86n39L+rVeWbxZIZd1PuaW9vz/DhwwkMDDRbb9iwIceOHav0mO8nb3/8C+cuZpjuV7cihytXrrBv3z6GDBmCWq0GICAgwMJRCSGEEEIIIYw0aisa+7jQ2Me89WtOnpa464mNuMtZJbcvZ5GTX4RebyAhJYeElBwOnUoynWNro+Kp/s0Y3KNRjdrVLqo3g8EAUOp7yrheVrV/QEAAy5cvp0OHDqYkSPfu3UlPT2fx4sUMGzYMT09PVq5cSfPmzaldu6Rdc5cuXSgoKGDlypU899xzpRIo1dGG3dGmqow+FVCVAWBTp6QKRpsah0Gvu635C3fL2GIKlRU29Sq/pdX9TGmlxmPIZC6tnk5x5hXSIlfgMWRSmf8/zvnjJwBUDq7Y+snnNELcb9S1vPB49FVSNs6lMDGK9B/W4B7yvKXDMrFYMuNuyj27dOlCly5dzNaKioo4cOAATZrID647kZKRC4BGraKeuwOtqsm8DIPBwIkTJ4iMjKS4uBgbGxsGDx5s6bCEEEIIIYQQt8nBTo1/w1r4N6xlWjMYDGRkFRCXnE18chZxl0uSHfEp2RRqdeQX6vj42z+Iu5zNS4+1qpAd4kI4OjoCpSswcnNzzR6/kZubG7169Sq1HhwczOHDh8nIyMDNzY0ePUoPPe7ZsycbN24kNja21CbM6iYpLYd9xxKBiqvKAFB71gfAUKylKOMyanfvCrluWYwtpjT1mkirowqgru1DrYefI+375eSePUR2g5Y4te5rdozBYCDn94MAOLToVqnJKiGE5dg/1AGXoCe49uNXZB3bgWvPp8qt1qpqFktm3E25Z1nmz5/PxYsX+d///lexAd7H9HoDGVmFAEx4vDU921beLxd3orCwkG3btvH7778D4OzsTNu2bS0clRBCCCGEEOJeKRQKajnbUsvZlrZNPUzrer2B5IxcvtgZzf7jiez+LZ7L6bnMGt0BZwf5cFLcG+Pmyfj4eJo2/XsGQFxcnNnjNzpx4gR//vknjz/+uNl6YWEhVlZWODo6Eh0dzbFjx3j88cextv679UZBQUmLNVfX6tVfvCzGWRkeFViVAWDl4onSxg59YR7a5NhKTWYUxJVUZmh8/SvtOR40jq37kh9zityon0nftRqNdzOzv0NtcixF6ZcAcAgondATQtw/XIOu/xzU61HaVJ85yxbb7nI35Z7/PG7evHmsWbOGMWPG0Ldv35seL/723zW/WjqEUpKSklixYoUpkdG8eXPGjx9fqjpHCCGEEEIIcf9QKhXUc3dg8lNteTq0GQB/xKQzZfFB4pKzLBydqOn8/Pzw9vZmx44dZuu7du2ifv361KtXr9Q5J0+e5PXXXzfNzoCSgd87d+6kbdu2WFtbExcXx5w5czh48KDZud9//z3e3t54eXlVzguqIGZVGX0rrioDSj7jUXuWJIkqcwi4Lj8HbWpJUkrjJ/MyKopCocB9wHisnNwxFBWS+vVC9MVa0+M5f5R8z1vXqoe6jswzFeJ+plAocesxHLeeT1arFqAWq8y4m3JPI61Wy8yZM9m+fTtjxoxh+vTplRfofeLMn2kcOp2EwWDglz+STetNfS27Y8RgMHDkyBF2796NXq9HpVIREhJCu3btqtU/FCGEEEIIIUTlUSgUDO/bFG8PRyLWHyclI49pS35k+jPtad/c09LhiRpswoQJzJo1C2dnZ3r27MnevXuJjIxk4cKFAGRkZBAfH0/jxo1xcHAgLCyMdevW8fLLLzNx4kTs7e1Zv34958+f5/PPPwdK2kkFBATwxhtvkJGRQZ06dfjuu+/Yu3cvS5curfbvZTf88HdVRu/2FVeVYaT2rE9B/B9oKzGZUZBwDjCAUoXGq+ktjxe3T2XrgMeQSSStewNt6kUy9q7D/eExGPQ607wMB/8e1f77XAhxf7JYMuNuyj2hJPkxbtw4jh8/zuzZsxk9enTlB3sfiFh/jLTMArO1maM6UNfdsv3ODAYD0dHR6PV63N3deeyxx/D0lDcrQgghhBBCPIi6tayHp5sd76z+hfTMAv7z8RGefSSAwT0aygdn4q6EhYWh1WpZvXo1GzduxMfHh/DwcAYMGADA/v37mTVrFmvXrqVTp044Ozuzbt06FixYwHvvvUdOTg4BAQGsWbOGVq1aAaBWq1m5ciWLFi1i2bJlZGRk0KRJE5YtW1btu0YkpeWw/7ixKqNppcynMQ4BL0yOxWAwVMq/3YLr8zJs6jZGqdZU+PUfdBqfZrj2GM7VA1+Q9dv32NZvidLaBl3OVQAcAoIsHKEQ4kFlsWTGjeWe/fr1M63frNxTp9Px4osvcurUKSIiIggNDa3KkKu9Am0x8ckls0gWfXmchJTSc0esVEo6+dfBw82Ojv6WTxoolUrCwsI4dOgQffr0Qa1WWzokIYQQQgghhAU19nYhYmIw76z+hQsJ1/j4299JTM1m3NCWMhhc3JURI0YwYsSIMh8LCwsjLCzMbM3Ly4uIiIibXtPNzY233367wmKsKqaqDDc7erevnLbOxjZT+vxsdNkZWDnVqvDnyL8+L8NWWkxVGpeuQ8mPPU1B/B9c2fY/NF4PAWDj1RRr1zoWjk4I8aCyWDID7rzc88svv+TXX39l+PDh1K1bl5MnT5qupVAoTLskHkQGg4FJCw+QmFr+4HSFApZO7Ym3R/ktvCqbXq/n4MGD1K9fn/r16wPg5OQkiSkhhBBCCCGEiZuThvcmdGfxlyf48eQldh6J49KVHGaN7oiTvWyAEuJuJF3JYf+xBACe6FOxszJupHb3BpUV6IopTI6p8GSGviDX1MJKhn9XHoVShcfg10hcNRl9fjZ5fx4DpCpDCGFZFk1m3Gm5586dOwHYsGEDGzZsMLuWSqXi7NmzVf4aqou9RxPKTGT869mO2GusAfB0s8PDzXLT57OystiyZQtxcXEcO3aM8ePHY29v2TZXQgghhBBCiOrJxlrFtKfb4ePhwPpd0fz+VzpTFx/kjTGd8PG03AYtIWqqDbvPozeAh5sdfTpUTlUGgEJlhbq2L9rkGLQpsdg/1KFCr1+QGAUGPSiUaLybVei1hTkrp1rUHjiBlE3hJQsKJQ7Nu1o2KCHEA82iyQy4s3LPtWvXVlVYNUpRsY5FX54w3V/wWg98PR1RW6tQKqtHX9nz58+zdetW8vPzAfD398fGxsbCUQkhhLhfbNu2jQ8//JCEhAS8vLwYN24cQ4YMKff4b775hunTp5daHzlyJG+++WZlhiqEEOIOKBQKnuzfDG9PRxZ9cZzL6blMXXKQGc90oG0zD0uHJ0SNcemGqozhfR/CSlW5LdtsPOujTY6hMOVihV87P75kI6tNnYYobWwr/PrCnH3Tjji1DyXraCT2TTuhsne2dEhCiAeYxZMZ4u5l52mJuZTJ68sPm9Z6tPaiiY9LtRmOp9Pp2L17N0eOHAHA1taWwYMHmw19F0IIIe5FZGQkU6dOZdSoUQQFBbF7925mzJiBRqMhJCSkzHOioqLw8/Nj3rx5Zuvu7u5VEbIQQog7FNTaC083O9795BcysgqZs+pnxg4OZFD3BtXmvY8Q1dmGH6LRG0o6NlTWrIwbGedmaJNjK/zaBXElw781Mi+jytR6+Dnsm3XGpk5DS4cihHjASTKjhjrzVxqzPzhUan38sJbV5pf5jIwMNm3axOXLlwHw9fVl2LBhODk5WTgyIYQQ95OIiAhCQ0OZPXs2AEFBQWRmZrJ48eJykxnR0dH4+/vTunXrqgxVCCHEPXjI15WIicH8Z/Uv/JWYyUdbz5CQks0LQwMrfZe5EDXZpSs5HDieCFRNVQZg+tC7ODMVXUEuKk3FtJjWa/MpvPwXIPMyqpJCocTWL8DSYQghBPIbXw1UUFhcKpGhtlKy9q3+ONpVn2F4f/31lymR0aNHD0aPHi2JDCGEEBUqISGB+Ph4Hn74YbP1/v37ExMTQ0JCQpnnRUVFSZWgEELUQLWcbZk7oTvdWtYDIPLni7z10c9k52ktG5gQ1diXN1Rl9KqCqgwAtYcfULLR0jisuyIUJEaXzMtAgcaneYVdVwghRM0gyYwaKL+w2HS7dZPafDv/UTaHP4Krk8aCUZXWvn172rVrx6hRo+jVqxdKpXy7CSGEqFgxMTEANGjQwGzdz88PgNjY0m+eU1NTSU9P5+zZs4SEhODv70///v3ZunVr5QcshBDinmnUVkx/pj3D+z0EwOk/05i6+CCJqdkWjkyI6icxNZuDVVyVAaC0scXarQ4AhRXYaqrg+rwMtWf9Cqv2EEIIUXPIp8s13AtDA6tNW6mUlBR++ukn032FQsGgQYNKfcAkhBBCVJTs7JIPrhwcHMzW7e1L3tzm5OSUOicqKgqAxMREpk2bxooVKwgMDGTGjBls3ry5kiMWQghREZRKBU+HNGfKyHZYWylJSstl6pIfORGdaunQhKhWNuw+j94AdWpVXVWGkWluRgUOATcmMzR+0mJKCCEeRDIzQ9wzg8HAsWPH2LlzJ8XFxbi5udGihQziEkIIUfkMBgNAqcS+cb2sqsCAgACWL19Ohw4dTEmQ7t27k56ezuLFixk2bFglRy2EEKKi9GzrTd1adrzzya9cyy7k36uO8MKQQAZ2kw1VQliqKsNI7dmA3HOH0abEVMj19EWFFCRdAMDWVz5zEEKIB5FUZoh7UlBQwKZNm9i+fTvFxcW4uLjg7Oxs6bCEEEI8IBwdHYHSFRi5ublmj9/Izc2NXr16larmCA4OJiUlhYyMjEqKVgghRGVo6udGxGvBNKjnhF5vYPmW0yzfchqdTm/p0ISwqA0//F2V0bNd1VZlANjUuV6ZcSURffG9z7UpvHQedCVttzU+kswQQogHkSQzaoiiYh2X03K5nJZLytU8S4cDlLTnWLFiBWfPlpR5+vv7M27cOLy8vCwcmRBCiAeFsZVhfHy82XpcXJzZ4zc6ceIEGzduLLVeWFiIlZVVmQkQIYQQ1VttV1vCXw6ic0BJj/7th2L598oj5MhgcPGASkjJ5uAJY1VG0yqvyoCSuRYAGPQUXUm45+vlG+dlePiispPf14QQ4kEkbaZqgKJiHePm7uHK1XxLhwKUtO44fPgwe/fuRa/XY2VlRWhoKG3atKk28zuEEEI8GPz8/PD29mbHjh3069fPtL5r1y7q169PvXr1Sp1z8uRJ5s6dS2BgIM2aNQNAr9ezc+dO2rZti7W1dZXFL4QQouLY2lgxa3RHPttxjo17LnDywhVemb+PcWEt6RxQ19LhCVGlvtpTUpVRt5Y9vdp5WyQGKwdXVPYu6HKvUZgci03dRvd0vYL4PwDQ+Mq8DCGEeFBJMqOaO3A8kQMnEstMZHi42VGnll2Vx5Sdnc3BgwfR6/XUrl2bxx57DA8PjyqPQwghhACYMGECs2bNwtnZmZ49e7J3714iIyNZuHAhABkZGcTHx9O4cWMcHBwICwtj3bp1vPzyy0ycOBF7e3vWr1/P+fPn+fzzzy38aoQQQtwLpVLBqAEt8PZw5H+bTpGWWcC7n/xKl8C6jBsaSC1nW0uHKESViLucBcCIhx9CZYGqDCN1nQbk/3UCbUrsPV3HUFxE4aWSeRmSzBBCiAeXJDOqsfTMfOZ/fsxsbdGkYJzsbQBwdbKxSKmok5MTjzzyCLGxsYSEhMgOViGEEBYVFhaGVqtl9erVbNy4ER8fH8LDwxkwYAAA+/fvZ9asWaxdu5ZOnTrh7OzMunXrWLBgAe+99x45OTkEBASwZs0aWrVqZeFXI4QQoiL0bu9DiwZufLDpFCfOX+HnM5c5ef4Kowc0J6RrA1RKqSgX97epI9uRlJZLJ/86Fo3DxrMkmVF4j8mMgqQLGK7P3ZDh30II8eCSZEY1lptfZLrdtqkHbZt50Mjbpcrj0Ov1/Pzzz7Rr1w6NRgNAQEAAAQEBVR6LEEIIUZYRI0YwYsSIMh8LCwsjLCzMbM3Ly4uIiIiqCE0IIYSF1Kllz5wXunDgeCKrvv2dzBwty78+w77jibz8eGvq13WydIhCVBrfOk741rH897jaOAQ8JQ6DXodCqbqr6xRcn5dh7e6Nyt65wuITQghRs8gA8GrsQsI10+1JT7ZlcI976y95NzIzM1mzZg27d+/mu+++w2AwVHkMQgghhBBCCHE3FAoFPdv58MH0PvTr6AtAdNxVJkbsZ+33Zyks0lk4QiHubzaeJckMQ1EBRVdT7vo6pnkZPlKVIYQQDzJJZlRT17ILWfTlCdN9pQXKoKOioli+fDkJCQkAODs7SzJDCCGEEEIIUeM42at5dXgb/vtiN7xq26PTG9i45wKvvL+Pk+dTLR2eEPctK1dPFOqSWTV3OzfDoCumIDEaAFs/SWYIIcSDTJIZ1ZBeb+Dtj4+Y7vdo44WTvbrKnr+4uJjIyEg2bNhAQUEBdnZ2PPXUUzz88MMolfItI4QQQgghhKiZAhu7s2RKL4b3ewgrlYLL6bm8seJnItYfIzOn0NLhCXHfUSiU2HjWB6AwOeaurlF4+S8MRSX/PmX4txBCPNhkZkY19HtMmqnFlFKp4LXhbarsudPT09m0aRPJyckA1K9fn6FDh+LkZPlem0IIIYQQQghxr9TWKp4OaU6P1l4s23iKcxcz2HcskaPnUhnzqD+92/ugUMiAcCEqitqzAQUJ59CmXLyr840tpqxc62Dl6FaBkQkhhKhpZJt9NZOVq+VfHx423f/PuC6ore9uQNbd2LNnD8nJySW9ZXv25JlnnpFEhhBCCCGEEOK+41vHibkTujPhsVbYa6zIztOy6MsTvL78MElXciwdnhD3DfX1ygxtSuxdta7OjysZ/m0rVRlCCPHAk2RGNWIwGPhg0ynTff+GtQhs5F6lMQwYMIB69eoxevRogoODpa2UEEIIIYQQ4r6lVCoI6VKfD2b0oXuregCc/jONl+fvY8PuaIqK9RaOUIiaz6ZOyRBwXW4mupyrd3SuQa+jIPEcABqZlyGEEA88+aS6GolPzubQ6STT/f+M61Lp5c3JyclcvHjRdN/BwYGxY8fi5+dXqc8rhBBCCCGEENWFm5OGGaM68OaYTtR2taWoWM9nkVFMXLifc7EZlg5PiBpNXdsHlCVdzu90CHhhciwGbQEglRlCCCEkmVGtFGiLTbenjGyHtVXltZcyGAz89ttvrFq1io0bN5KdnW16TPrDCiGEEEIIIR5EHVrU4X/TejMkuBFKRcmGs+nLfuSDTafIyS+ydHhC1EgKlTVqd2+gJDlxJ0zzMpw9sHKuXeGxCSGEqFkkmVGNHPk92XS7S2DdSnue/Px8Nm7cyPfff49Op0Oj0ZCfn19pzyeEEEIIIYQQNYWtjRVjHg1gwWvBNPJ2BiDy54tMmLeHQ6eS7qrnvxAPOvX1VlN3WplREFeSzJAWU0IIIQCsLB2AKHHpSg6b9l4AQKEAZSUVRyQkJLB582YyMzMBCAwMZODAgdjY2FTOEwohhBBCCCFEDdTYx4UFr/bgu59i+WzHOTKyCpm79je6BNZl4og22GmsLR2iEDWGjWd9coDClIu3fY5Br6MgoWRehrSYEkIIAZLMqDaycrSm28+ENq/wFlMGg4GffvqJffv2YTAYsLa2JjQ0lNatW0tbKSGEEEIIIYQog0qlZEhwI7oG1uXDLac5ei6Fn89cJjE1hzee60Rdd3tLhyhEjWCszCi+moy+IBel5tb/drSpcegL8wDQ+EplhhBCCGkzVS3EXc7i9F9XTPeHBDeu8Oe4cOECe/fuxWAw4OHhmOtbOAAAIABJREFUwfPPP0+bNm0kkSGEEEIIIYQQt+DhZsebYzrx8uOtsFIpSEjJZvKiA5y6cOXWJwshsPGob7pdmHrxts4piD8LgMqxFlYunpUQlRBCiJpGKjMsLDk9l5fn7zNbq4z8QpMmTQgMDMTGxoaHH34Ya2spiRZCCCGEEEKI26VQKOjfuT7eHo689+mvZOZoefOjn3lhcAADujWQjWJC3IRSY4+ViyfF11LQply8rbZR+deTGbZ+/vLvSwghBCCVGRZ35erfg7cd7awJ7VIfK9W9/7XodDr++OMP032FQsGQIUMYOHCgJDKEEEIIIYQQ4i75N6xFxMRgGtRzQq83sPzrM/xv0ymKivWWDk2Ias3mequpwuRbDwE3GPSmygxpMSWEEMJIKjMsKL+wmNkfHjLdX/+fARVy3WvXrrF582YSExPR6XS0bNkSAKVScldCCCGEEEIIca88XO2Y93IQC788zuHTl9l5JI7E1Bxmje6As4ONpcMTolpSezYgN+oI2tsYAl50JRF9fjYAGhn+LYQQ4jr5dNuCzsdfNd2uW6tiBsedO3eOFStWkJiYCMDVq1dvcYYQQgghhBBCiDulsbFixjMdeKp/MwD+iEln8qIDxCZlWjgyIaonG8+SygztlQQMuqKbHpsfX9JpQmXvgrVb3UqPTQghRM0gyQxLMvx9c/5rPe7pUsXFxWzfvp2vvvqKgoIC7O3tefrppwkODr7HIIUQQgghhBBClEWpVPDkw02ZOboDNmoVqVfzmb70Rw6fTrJ0aEJUO+rrbabQF6O9knDTYwuuJzM0Mi9DCCHEDSSZUQ0oFeBkr77r89PS0li1ahVHjx4FoGHDhowfP55GjRpVVIhCCCGEEEIIIcrRrWU93n8liNquthRodbz36W98sSsavd5w65OFeECoHFxR2TsD3LTVlMFgMM3LsJV5GUIIIW4gMzNqOJ1Ox2effUZmZiYKhYJevXrRvXt32bkgTAwGA2lpaRQUFKDXy1BCIe4XSqUSjUaDu7u7/D9fCCGEqAYa1HMm4rVg5q79jT9i0lm/M4q4y1lMHNEGjY289RZCoVCg9qxPfswpCpNjcWxV9nFF6ZfQ5Za0a5N5GUIIIW4klRk1nEqlIjQ0FGdnZ5599lmCgoLkQy1hYjAYuHTpEmlpaRQV3bwnqRCiZikqKiItLY1Lly5hMMiuTyGEEKI6cHG04T/jutK/sx8Ah04nMWPZT6RezbNwZEJUD2rj3IyU2HKPMVZlKO2csHb3rpK4hBBC1AyyPaQGunz5Ms7OztjZ2QHQtGlTGjVqhJWV/HUKc2lpaWRnZ+Pp6Ymbm5ulwxFCVLCMjAxSUlJIS0ujdu3alg5HCCGEEIC1lZIJj7Wifl0nVn7zOzFJmUxedIBZozvi37CWpcMTwqKMQ8ALUy5iMOhRKErvsTUO/7b1bSGbNYUQQpiRygwL0RbpeHfNL3d0jsFg4MiRI6xatYpvvvnGbCeuJDJEWQoKCrCxsZFEhhD3KTc3N2xsbCgoKLB0KEIIIYS4gUKhYFD3hrz9fBccbK3JzNHy+vJD7PolztKhPZC2bdvGwIEDadmyJaGhoWzduvWmx3/zzTc0bdq01J+3337bdExxcTGLFi0iODiYVq1a8dRTT3H69OnKfik1nnEIuEGbT/HVlFKPGwwGCuJKKjOkxZQQQoh/kk/ALeTcxQzyC3UAuDnb3vL4vLw8vvnmG86fPw9Aeno6ubm5ODg4VGqcombT6/WoVCpLhyGEqEQqlUrm4QghhBDVVKuHahMxMZj/rP6FhJRsln51krjLWTz3iD8qlewtrAqRkZFMnTqVUaNGERQUxO7du5kxYwYajYaQkJAyz4mKisLPz4958+aZrbu7u5tuv/vuu3z99ddMnTqVevXq8cknn/B///d/fPPNN/j4+FTqa6rJrF3roLDWYCgqoDAlFmu3umaPF19NRpeTAYBGhn8LIYT4B0lmWIhO/3dVxTvju9702Li4OLZs2UJWVhYArVq1YsCAAajV6kqNUQghhBBCCCHEvanrbs/8V4OY//kxfjubwrc/xhCfnM30Ue1xtJP3dJUtIiKC0NBQZs+eDUBQUBCZmZksXry43GRGdHQ0/v7+tG7duszHExMT2bBhA2+88QZPPvkkAN27d6d///6sWrWKOXPmVM6LuQ8olCrUHn4UXopGmxwLzc0/DzG2mFJqHFB7+FoiRCGEENWYbAWpYjqdnjXb/mDDD9EAWKkUeNUuu7pCr9dz4MABPv30U7KysrC2tmbIkCEMGTJEEhlCCCGEEEIIUUPYaaz517OdeKx3EwBOXrjClMUHSUjJtnBk97eEhATi4+N5+OGHzdb79+9PTEwMCQkJZZ4XFRVF06ZNy73ukSNH0Ol09O/f37SmVqvp2bMnBw8erJjg72M2dYxzM0oPATcO/9b4NC9znoYQQogHm/xkqGK//5XO5n1/cja2pGzS3ta63GMPHjzI/v37MRgM1KlTh3HjxtGqVauqClUIIYQQQgghRAVRKRWMHtiCKSPbobZScjktl6lLDnL0XOm5AaJixMTEANCgQQOzdT8/PwBiY0t/mJ6amkp6ejpnz54lJCQEf39/+vfvbzZnIyYmBmdn51KzCf38/EhKSpJ5Zregvj4EXJtysdRjBXEllRkaP2kxJYQQojRJZlSxwqKSORkqpYJB3RowbWT7co/t2LEjTk5OdOzYkTFjxlCrVq2qClMIcYOlS5fSosWd/TI9c+ZM+vXrZ7pfXFxMy5YtSw0RbNOmTUWHe0/+GXdVmjt3Lk2bNiUiIqLMx28VW79+/Zg5c2ap9VOnTjFlyhSCg4Np2bIl/fr14+233yYl5e4+OEhLS2PKlCl06tSJdu3aMXnyZK5cuXLL8/r161fmIMmMjAzTMRs2bCAkJITAwED69+/PmjVrMBgMN7mqEEIIIWqanm29eW9Cd9ycNOQVFPP2x0fYtPeCWStiUTGys0sqX/45a9Le3h6AnJycUudERUUBJa2kpk2bxooVKwgMDGTGjBls3rzZdF5Z8yuN183Nza24F3EfsvGsD4Au5yrFOddM60XXUinOSgPAVoZ/CyGEKIPMzLAQtbWScWEtzdZ0Oh1paWl4enoCYGdnx4svvohGo7FEiEKIChQbG0thYSHh4eHUr1/ftK5USk4ZSpI93377LQ899BCbN2/mlVdewdq6/Mq12/Xpp58SHh5O165dmTZtGrVr1+avv/5i1apV7Nq1i88++8zs7+N24hwzZgx5eXn8+9//pri4mAULFjB27Fg2b96MlVXZP1Zzc3NJSEhgypQpdOzY0ewxJycnAFatWsX777/PI488wr/+9S8uX77MokWLuHTpEv/617/u+msghBBCiOrnIV9XIib24L9rfuV8/DU+3X6WQ6eTeDGsJQ/5ulo6vPuGcVOIQqEoc72s38UDAgJYvnw5HTp0MCUsunfvTnp6OosXL2bYsGHlbjYp7/mEOWsPX1AowaBHmxKLlUPJBq+C6/MyFDZ2qK8nPIQQQogbSTKjimiLdKz65nei46+W+fjVq1fZvHkz6enpjB8/HmdnZwBJZAhxn4iKikKpVNK/f39sbW0tHU61s3//fjIyMliyZAkjR45kz5495Q5kvF3Hjh1j7ty5jB492qxio1OnTvTp04fBgwfz73//mzVr1tz2Nbdv305UVBTff/89jRo1AqB58+YMGjSIXbt2MWDAgDLPi46OxmAw0KdPH9N5N9LpdKxYsYLg4GDmz59vWvf09GT8+PGMGDGizPPE37Zt28aHH35IQkICXl5ejBs3jiFDhtzWuZcvX2bQoEGMGTOGl156qZIjFUIIIUrUcrblvZe689HWM+w8EsefCdeYuuQg/TvXZ9SA5jIcvAI4OjoCpSswjJUTxsdv5ObmRq9evUqtBwcHc/jwYTIyMnBwcCiz+sK4VlbVhvib0kqNurY32tR4tCmx2DUqSWbkx12fl+HdDIVSZckQhRBCVFOSzKgiR36/TOTPF033HW74xfSPP/7gu+++o7CwECjpv1ndWs+I+0uxTk96puX7uNZy1mCluvPKhN69e/PYY4+Rnp7Od999h16v59FHH2XatGksWbKELVu2ANC3b1/efPNNbGxsALh27RpLly5l3759XLlyhSZNmjB+/HizgYCFhYVERESwbds28vLyCAkJKbPF2w8//MCHH37IhQsXcHZ25pFHHmHSpEmo1WW/6Tx37hy+vr73nMiYOXMmx44d44cffjCtJSYm0qdPH+bNm8fgwYPZsmULb731Fp9++invvfceUVFRuLu788wzz/Dcc8+ZzsvMzGTu3Lns3bsXvV7PE088gV6vL/WcX331FWvWrCE+Ph4PDw9GjBjB888/b9pxNnPmTFJTU/Hy8uL777+nSZMmfPHFF8yaNYuvv/6a6OjoW76uLVu24O/vT/v27WnVqpWp3dK9+Pjjj3FxcWHSpEmlHvP09GTmzJmkpKRQXFxMcnIyffr0KfdaQ4cOZe7cuRw6dIjGjRubJRaM9w8cOFBuMuPcuXPY2NiUWwWSnp5OVlYWPXv2NFvv0KEDer2eH3/8UZIZNxEZGcnUqVMZNWoUQUFB7N69mxkzZqDRaG75fWQwGJg9e3aZbSaEEEKIyqa2VvHy463p1c6H5VtOc/FyFjt+vsihU0n836AW9O3gi1Ipu/zvlnFWRnx8vNlA77i4OLPHb3TixAn+/PNPHn/8cbP1wsJCrKyscHR0pGHDhly7do3MzEzTRkTjdb29vct9TyD+pvZsgDY1nsLkv+eWGCszbP2kxZQQQoiySTKjCiRdyeH9z46Z7j/WuwmdA+pQVFTEjh07OH78OFCye2Po0KE0bNjQUqGKB0CxTs9L4Xu5nG75Pq51a9nzwYzed5XQWLVqFb169WLx4sX89NNPrFq1isOHD9OsWTPmz5/P0aNHWb58OY0aNeK5554jPz+fp556iqysLF577TU8PDz47rvveOWVVwgPDzft4J42bRo//vgjkyZNws/Pjw0bNvDdd9+ZPfd3333H1KlTGTJkCBMnTiQ+Pp6IiAgSExNZunRpmfFGR0ejVqsZM2YMx48fx8rKitDQUKZPn14pO7eKi4uZPHkyzz33HFOmTGHjxo2Eh4fTvHlzunTpgl6vZ+zYsVy6dInp06fj4uLCqlWrOHPmDHXr1jVdZ8WKFSxcuJDRo0cTFBTEmTNnWLJkCRkZGWbVDr/88gudO3dm2bJlFBQUoFAoeOmllxgxYsQtY01PT+fgwYNMnz4dKEkczJkzh7i4ONNwxjtlMBj46aef6Nu3rymZ9U837tr38PBgw4YN5V7PONwxJiamzDe9vr6+ZQ6QNIqOjsbFxYXJkydz6NAhdDodPXv2ZPbs2dSuXZtatWphY2NDUlKS2XkJCQlAScJKlC8iIoLQ0FBmz54NQFBQEJmZmSxevPiWyYz169ebhoMKIYQQluLfsBaLJgWz/VAsn+2IIjtPy9KvTvLDL3G8OKwVDb2cb30RUYqfnx/e3t7s2LHDbPbarl27qF+/PvXq1St1zsmTJ5k7dy6BgYE0a9YMAL1ez86dO2nbti3W1tZ07doVgJ07d/LEE08AoNVqOXDgAN27d6+CV1bzqT0bwJkDaFNKfocuzkqn+FrJTDuNrwz/FkIIUTZJZlQynU7Pwi+Om+53a1mP0QNbkJqaysqVK01DYxs1asSQIUOkHFWI2+Tq6sr777+PUqmkU6dObNiwgaKiIubPn4+VlRVBQUHs3buXkydPAiU7///66y82btxIy5Yl82qCg4PJzMw0zSmIiYlh586dzJkzx/QhfFBQEI888ojpg2qDwcD8+fPp1asX4eHhpnjq1KnDhAkTOHbsGO3atSsVb1RUFDk5OTz++OOMHz+e33//naVLlxIbG8vatWsrvK+uXq/nlVdeYdiwYQC0bduWH374gX379tGlSxcOHjzI6dOnWbVqFUFBQQB06dKF3r17m66RnZ3Nhx9+yMiRI5k1axZQ0i/Yzs6O8PBwRo0aZXoDWFxczJw5c/D29jad7+vri6+v7y1j/fbbbwEYNGgQAAMHDuS9997jq6++Ytq0aXf1+q9evUphYWGZb1DLolarad269S2Py87OpnHjxqXW7e3tTTv8yhIVFUVaWhpNmjThmWeeISYmhiVLljBq1Ci+/vprNBoNjz76KOvWraNJkyb06tWLpKQk3njjDdRqNXl5ebf1Oh5ECQkJxMfHM3nyZLP1/v37ExkZSUJCAj4+PuWeO3/+fBYvXszzzz9fFeEKIYQQ5VKplDzaoxHdW3ux+ts/OHAikai4q0xauJ8B3RowMqQ5Drb3PlPsQTNhwgRmzZqFs7MzPXv2ZO/evURGRrJw4UIAMjIyiI+Pp3Hjxjg4OBAWFsa6det4+eWXmThxIvb29qxfv57z58/z+eefA+Dl5cXQoUN55513yMvLw8/Pj08++YTMzEzGjh1ryZdbYxiHgBdlJKMvzCffOC/DWoNNHdngKYQQomySzKhEeQVFjHnnB3LyiwCwUimYMao9V69eZeXKlRQXF6NUKunduzddu3aVIWGiSliplHwwo3eNbjMFEBgYaBrYp1QqcXV1pUWLFmYDmF1cXMjKygLgt99+w8/Pz5TIMHrkkUc4ePAgMTExHD16FMCs3ZBxzsXy5cuBkp35ycnJTJgwgeLiYtNxQUFBWFtbc/jw4TKTGQsXLsTZ2dlU3t6hQwdq1arFtGnTOHz4MN26dburr8PNtG3b1nRbrVbj5uZGfn4+AEePHsXGxsaUyACws7MjODjYVC124sQJ8vPz6d27t9lr7d27N//97385cuQIYWFhpnNvTGTciS1bttC1a1esrKxMf189evRgy5YtvPbaa6Yy/dv5f6TxGJWqpMeuTqe77ThufI3/pFQqTd9vZcVhMBhuOsz99ddfx2Aw0KpVKwDat29Po0aNeOqpp/j222954oknmDlzJoWFhcyYMQODwYCDgwNTpkxh5cqVMmflJoxVFf+smDFW9cTGxpaZzNDr9cycOZPQ0FB69OhR+YEKIYQQt8nNScPUp9vRv7MfH245TUJKNtt+iuWnU0k8O8ifXu285b3jHQgLC0Or1bJ69Wo2btyIj48P4eHhpvag+/fvZ9asWaxdu5ZOnTrh7OzMunXrWLBgAe+99x45OTkEBASwZs0a0+9yAG+//TZOTk589NFH5OXl4e/vzyeffHLXlcUPGrWn8Xc3A9rUOAriSpIZGp+mKFTyUZUQQoiyyU+ICnY1q4BrOSWzL348ecmUyACY/kwHFAoFrq6uBAQEcPHiRYYNG3bXHwAKcbesVEo83ewsHcY9sbe3L7V2sw98MzMzcXd3L7VuXMvOziYzMxP4u6WQUe3atU23r127BsAbb7zBG2+8Uep6qampZT5/x44dS60Z5yNERUVVSjLjn18PpVJpmomRmZmJq6trqXPKeq03ztm40Y2vtayv7e04c+YM58+f5/z583To0KHU47t37za90bS1tUWr1ZZ7raKiItNrdnZ2xt7evlTbphsZZyQ4ODiY5o6Uxzgzw8HBoczZCrm5uTetrPtnEg2gXbt2ODo6EhUVZYrj/fff56233uLy5cv4+PigVqt59913zXoxC3PZ2dlA6UGbxv9HlDcL49NPPyUhIcGUqBRCCCGqm8DG7iyZ0pNvD8bwxa4ormUXsvCL4+z6JY4Xw1riV9fJ0iHWGCNGjCi3/WlYWJhpg46Rl5cXERERN72mWq1m9uzZpjaX4s6obB2wcvagODOVwuQYChKuD//2lXkZQgghyifJjAoUdTGDGct+RG8o/dh/X2hNwEN1TPdDQ0PR6/VoNJoqjFCIB5eTkxPnzp0rtW78QN7V1dX04X5aWhqenp6mY4wf6gM4OjoCMGvWrDIrMMpKEKSnp7N37146d+5stkO8oKCg3HPKo1AoSlUb3E0LIldXVzIyMjAYDGY7+8p6rQsXLixzZ7uHh8cdP+8/bdmyBQcHB/73v/+V2mE4depUvvzyS1Myw93dnYyMDIqKirC2Nm+xUFxcTFpamllSpXv37vzyyy8UFhaWOTdjzZo1fPDBB0RGRlK3bl02bdpUbpzGv6MGDRpw/vz5Uo/Hx8eb7dS7UV5eHpGRkfj7+5v6LkNJNUdRUZHp2vv27cPFxYU2bdrQpEkToGRweHFxMS1aSN/g8hgMJT90//n9Y1wvq2ImJiaGRYsWsWTJEtP3uRBCCFEdWamUhPVqTI82Xqz69ncOnUrij5h0Xo3Yz6NBDXny4abYaaT1lKiZ1J71Kc5MJT/mJEXpJZuQbCWZIYQQ4iburr9LBdq2bRsDBw6kZcuWhIaGsnXr1psen5uby5w5c+jWrRtt2rTh+eef5+LFi1UT7C3EJGWWkcgwENykiK1freXEiROmVbVaLYkMIapQx44diYuL4/Tp02br27dvp3bt2vj5+dG5c2cAduzYYXbMvn37TLcbNWqEm5sbly5dIjAw0PTH1dWV+fPn89dff5V6boVCwZtvvslnn31mtv7999+jUqnKTIqUx97enoyMDLMKhWPHjt32+UZdunRBq9WyZ88e05pWq+XQoUOm+61atcLa2prU1FSz11pcXMzChQtNM3/ullarZfv27fTt25fOnTvTqVMnsz+DBg3il19+Mc0r6dixY6mYjfbv309RURGdOnUyrT377LNcu3aNxYsXlzo+KSmJzz//nJYtW+Ln54darTZ7jf/8Y6yg6969OxcuXDAbGP3nn38SExNjGgT5TzY2NoSHh7Ns2TKz9T179lBQUGCq2lm/fj0LFiwwO+bTTz/F0dHR7HUJc8ZkxD8rMHJzc80eN9LpdMycOZOQkBC6detGcXGxqcWYXq+/absxIYQQwlLcXWyZOaoDc17ogldte/R6A1sP/MWL4Xs5eCLRlMQXoiaxqVPSairvz5I2tworNTb1GlkyJCGEENWcRSszIiMjmTp1KqNGjSIoKIjdu3czY8YMNBoNISEhZZ4zadIkzpw5w/Tp07G3t2fZsmWMGjWK7du3V5vdlfXc7VnwWg/y8vLYEbmN2JiSDzePHj1K69atb9pXXQhROYYOHcq6det46aWXeO211/D09GTbtm0cPHiQd955B6VSiZ+fH8OHD2fBggVotVqaNWvG1q1biY6ONl1HpVIxceJE5syZg1KppEePHmRmZrJkyRKys7PL3EHv5ubGyJEjWbduHQ4ODrRv355jx46xfPlyRo4ceUd9dXv16sW6deuYPXs2jz32GOfPn+eTTz4xzYi4XV26dKF79+7Mnj2btLQ06taty9q1a8nIyDBVXLi5ufHcc8+xcOFCcnJyaNeuHUlJSSxcuBBHR0dT9UB54uPjycjIKHew9u7du8nMzGTgwIFlPj5kyBBWr17NV199xYwZM2jfvj29e/dm1qxZxMTE0KZNGwoLCzl16hRr1qwhJCTELDHUpk0bJkyYwLJly4iJiWHw4MG4uLgQFRXFxx9/jFKp5P3337+jr9uAAQNYvnw5Y8eOZcqUKRgMBhYsWECTJk0IDQ01HXf27FnUajWNGzdGpVLx4osvMnfuXN555x169+7N+fPnWbp0KX369DElKp5++mleeOEF5s2bR1BQEHv27OHrr7/mjTfeqDY/36oj46yM+Ph400wawDSQ/Z+zNC5fvsypU6c4depUqQ0US5cuZenSpWb/5oUQQojqpG1TD5ZO7cXX+/9iw+7zZGQV8P5nx9h5JI7xYS3x8ZTfGUTNcePcDAAb76YoVFJpJIQQonwWTWZEREQQGhpq6jEZFBREZmYmixcvLjOZcfToUQ4cOMDKlStNwzrbt29Pnz59+OKLL3jhhReqNP7yKJUK0lKT2LJli6mXd5s2bQgJCZFEhhAWYmdnx2effcaCBQuYP38++fn5PPTQQyxdupSHH37YdNxbb72Fu7s769atIzMzk6CgIMaPH8/SpUtNxwwfPhwHBwdWrVrF+vXrcXBwoEOHDkyePNls5sSNZsyYgaenJ5s3b+ajjz7C09OTV199lbFjx97R6+jWrRszZsxg3bp17Ny5E39/f5YtW1ZuD+CbWbZsGfPnz2fRokUUFhYyYMAAnnjiCfbv3286ZtKkSdSuXZv169ezfPlyXFxcCAoKYvLkyWW2brrRBx98wNdff13uB8ObN2/G1dW13IqGpk2b0rx5c7Zs2cKkSZNQq9UsWbKE1atXs23bNlauXAmAj48Pr776KqNGjSp1jVdeeQV/f38+//xz3n33XbKysqhbty4hISG88MILd9wqS61W88knn/Duu+/y+uuvo1ar6datGzNnzjQbPv/yyy/j5eXFunXrgJIqEQcHB9auXcvGjRtxdnZmxIgRvPLKK6ZzgoODCQ8PZ8WKFXz++ef4+voSHh7OkCFD7ijGB42fnx/e3t7s2LGDfv36mdZ37dpF/fr1qVevntnxHh4eZbYUe+yxx3jyyScZNmxYpccshBBC3AtrKxVP9H2I4LberPrmDEd+T+b0n2m8umAfQ4IbM7zvQ2hspKO0qP6MlRlGtr7SWlUIIcTNKQwWqkdNSEigb9++LFq0yGw3a2RkJBMnTmT37t2lerQvXryYTz/9lN9++81sF/ILL7xAXl5eqRYut6N9+/ZASaLkXn1/OJYPN5+imWsGDroEoOSDr0GDBhEYGHjP1xfiThl3Jt/Jzn8hRM1yO//OK/JnXXW0ZcsWZs2axciRI+nZsyd79+7liy++YOHChQwYMICMjAzi4+Np3LhxuYPamzZtymuvvcZLL710x89/v399hRBCVG+/nU3mo61nSE4vmaPm7mLL84MD6BJYt9RMqbslP+sq34P4NTYYDMQtfBZ9fskm0LpPv42tn8zMEEKI+1VF/KyzWJmAsd/4P9s/GD+MMfZI/+c5fn5+pdqp+Pr6lnm8JTS0jTMlMurWrcu4ceMkkSGEuCVj3/4pLRTiAAAgAElEQVSb/dHr9ZYOU4hqKSwsjDlz5vDTTz8xYcIEfv31V8LDw03D4/fv38/w4cP5448/LBypEEIIUfE6tKjDsmm9eerhplhbKUm7ls97n/7GnFVHKNDKLChRfSkUClN1hkJljY3XzdvYCiGEEBarPTW2X/rnDkl7e3ug9CBP41pZOyrt7e3LPL6q2dlYkaZ1w9X6Gl06d6Zv37533MdeCPHgSUxMpE+fPrc87uWXXzZrSySE+NuIESPKbbcWFhZGWFjYTc+XORlCCCFqMhtrFU/2b0bPdj58tPUMR8+lcCwqleNRqXRtWe/WFxDCQmzqNiY/9jQ23k1RWqktHY4QQohqzmLJDGN3q3+WvRrXy5otcbOOWNVhFkXnwLqkXu1EQ89utA9saOlwhBA1RHk9/Ms6TgghhBBCiPLUdbfnzTGdOHouhYuXs2jbTH5/FNWbc6dHQKnEoUV3S4cihBCiBrBYMsPR0REoXYGRm5tr9viNHBwcSExMLLWem5tbbg/sqqRRW/FE34csHYYQooZRq9XSjk4IIYQQQlQIhUJBhxZ16NCijqVDEeKWVHZOuAU/aekwhBBC1BAWK2cwzsqIj483WzcOMv3nLA3jWkJCQqkKjbi4uDKPF0IIIYQQQgghhBBCCCFEzWexZIafnx/e3t7s2LHDbH3Xrl3Ur1+fevVK9/Xs3r07WVlZHD582LSWkZHB0aNH6dq1a6XHLERNo1Qq0el0lg5DCFGJdDpdtWi1KIQQQgghhBBCCFGZLNZmCmDChAnMmjULZ2dnevbsyd69e4mMjGThwoVASaIiPj6exo0b4+DgQIcOHejYsSOTJ09m6tSpuLi4sHTpUhwdHXnySSlLFOKfNBoNOTk5ZGRk4ObmZulwhBAVLCMjg8LCwjJbMwohhBBCCCGEEELcTyyazAgLC0Or1bJ69Wo2btyIj48P4eHhDBgwAID9+/cza9Ys1q5dS6dOnQBYtmwZc+fOZd68eej1etq1a8eiRYtwdna25EsRolpyd3ensLCQlJQUrl27hkqlsnRIQogKotPpTIkMd3d3S4cjhBBCCCGEEEIIUakUhn8OoHjAtG/fHoCjR49aOBIhKofBYCAtLY2CggL0er2lwxFCVBClUolGo8Hd3R2FQnHTY+VnXeWSr68QQoj7nfysq3zyNRZCCHG/q4ifdRatzBBCVD6FQkHt2rUtHYYQQgghhBBCCCGEEELcNZkYKoQQQoj/b+/ew6Kq9j6AfwEFFEQkQFPBC8eBFNGRERNBS0QxoLxi3lDDW1neL3g9XlIKNTsIpmZoSlDeIBRMk8xSjprVISzzqBgXxV6FUCAVkPX+wct+HbkIyDB7nO/neeZ5nLXXnv3ba9h7/Zy1915ERERERERERLLGwQwiIiIiIiIiIiIiIpI1DmYQEREREREREREREZGscTCDiIiIiIiIiIiIiIhkjYMZREREREREREREREQka420HYC2FRQUQAgBlUql7VCIiIg0Ij8/HwYGBtoO45nFXIKIiJ51zCU0j/kEERE96+ojn9D7OzMMDQ2ZlBER0TPNwMAAhoZ63+VrDHMJIiJ61jGX0DzmE0RE9Kyrj3zCQAgh6ikeIiIiIiIiIiIiIiKiesdLK4iIiIiIiIiIiIiISNY4mEFERERERERERERERLLGwQwiIiIiIiIiIiIiIpI1DmYQEREREREREREREZGscTCDiIiIiIiIiIiIiIhkjYMZREREREREREREREQkaxzMICIiIiIiIiIiIiIiWeNgBhERERERERERERERyRoHM4iIiIiIiIiIiIiISNY4mEFERERERERERERERLLGwQwiIiIiIiIiIiIiIpI1DmbU0uHDh+Hr6wsXFxcMHjwYcXFx1dYvLCzEqlWr0KdPHyiVSkyZMgV//PFHwwQrQ7Vtv1u3bmHZsmV4+eWXoVQqMWzYMBw5cqSBopWn2rbho7Kzs+Hq6ootW7ZoMEL5q20blpaW4qOPPoKXlxdcXFzg7++PhISEBopWfmrbfrm5uVi8eDE8PDzg5uaGadOm6fV58FEXL15Ely5dcPPmzWrrsS/RL09znqeGUVJSAhcXFzg6Oqq9lEqltkMjVH1uPXXqFIYPH45u3bqhf//+iIyM1FKEBFT9PXl7e1c4thwdHZGbm6ulSIl0D3MJ+WMuIX/MJ3QD8wn900jbAeiSI0eOYP78+QgMDISnpyeOHz+ORYsWwdTUFD4+PpWuM2fOHKSmpmLhwoUwMzNDeHg4AgMDkZCQgGbNmjXwHmhXbduvqKgIkydPRn5+PmbOnAlbW1scPXoUs2fPxsOHD+Hn56eFvdCuuvwNlhNCYMmSJSgoKGigaOWpLm24bt06fPHFF5g7dy6cnJyQkJCAefPmwdzcHP369WvgPdCu2rafEAIzZsxARkYGFixYAEtLS4SFhSEwMBCHDh1C8+bNtbAX8pCWloZp06ahpKTkiXXZl+iPpznPU8O5du0aHjx4gPfffx/t27eXyg0NeZ2QtlV1bv3pp58wffp0DB48GLNmzcKPP/6I0NBQCCEQFBSkpWj1V1XfU2FhITIzMzFv3jy4ubmpLbOwsGjIEIl0FnMJ3cBcQt6YT+gG5hN6SlCNDRgwQMyePVutbNasWcLHx6fS+j/88INQKBTi5MmTUllOTo7o3r272LZtm0ZjlaPatt/XX38tFAqFSElJUSsPCgoSr776qsbilLPatuGjoqKiRN++fYVCoRARERGaClH2atuG6enpwsnJSezdu1etfOzYsWLNmjUai1Ouatt+aWlpQqFQiNjYWKksIyNDKBQKcfDgQY3GKlfFxcUiKipKKJVK4ebmJhQKhcjOzq6yPvsS/fI053lqOPHx8cLJyUn8/fff2g6F/s+Tzq0TJkwQI0eOVFsnNDRUqFQq8eDBg4YOV2896Xv68ccfhUKhEFeuXNFilES6jbmEbmAuIU/MJ3QD8wn9xiHfGsrMzERGRgYGDhyoVj5o0CCkpaUhMzOzwjqnT5+GmZkZ+vTpI5VZWVmhZ8+e+O677zQes5zUpf3MzMwwatQodO3aVa28Y8eOyMjI0Gi8clSXNnx03Q0bNmDNmjWaDlPW6tKGx48fh6mpKYYMGaJWHhUVhWXLlmk0XrmpS/s9ePAAQNnxXK78boy8vDwNRitfP/74IzZs2IA33ngD8+fPf2J99iX642nO89SwLl68CHt7ezRp0kTbodD/qe7c+uDBA5w/f77SY+vu3bv46aefGjJUvfakPvDixYswMTFRu0qZiGqOuYTuYC4hT8wndAPzCf3GwYwaSktLAwB06NBBrbxdu3YAym4RrGyddu3awcjISK3c3t6+0vrPsrq0X+/evbF69WoYGBhIZcXFxTh58iQ6deqkwWjlqS5tCJTN9xAcHIzBgwejb9++mg1S5urShpcuXUKHDh2QnJyMV199FZ07d8bAgQORmJio+YBlpi7t5+TkhF69eiEiIgJXr15Fbm4u3n33XTRt2hQDBgzQfNAy5ODggOPHj+Ptt9+u0D9Uhn2J/qjreZ4a3qVLl2BsbIygoCAolUr07NkTK1as0PtHOWpTdefWzMxMFBcX89iSgSf1gZcuXYKlpSXmzp0LlUoFpVKJOXPm4NatW1qIlkj3MJfQHcwl5In5hG5gPqHfOGdGDeXn5wMAzM3N1crLrzaurMMpKCioUL98HX3roOrSfpXZsGED/vjjD0RERNRvgDqgrm346aefIjMzE1u3btVsgDqgLm2Ym5uL7OxsLFmyBLNmzULbtm2xb98+zJkzB1ZWVnjxxRc1H7hM1PVvcOXKlZg8eTJeeeUVAICxsTEiIiJgZ2enwWjly9raulb12Zfoj/rqK0nzfv/9dxQUFGDkyJGYPn06Lly4gM2bN+PatWvYvXu32oUY1DCqO7fy2JKPJ/WBv//+O27fvo1OnTph/PjxSEtLk+baio2NhampaQNFSqSbeL7THcwl5In5hG5gPqHfOJhRQ0IIAKjQoZSXVzZJU/myyujbpE51ab/H661fvx67du1CUFCQXl7RXZc2TEtLw4cffoiwsDBOEoy6tWFxcTFyc3OxdetWvPzyywDK7hpKS0tDeHi4Xg1m1KX9rl69itdffx329vZYsmQJTE1NsXfvXsycORM7duyASqXSfOA6jn2J/njavpIazqZNm9C8eXM4OjoCAHr27InnnnsOCxYsQHJystpj4Uj7qjq2yvHYko9ly5ZBCIFu3boBAFQqFRwcHDBmzBjEx8cjICBAyxESyRtzCd3BXEL3MJ/QHcwnnm0czKih8h+CHx9pLSwsVFv+KHNzc2RlZVUoLywsrPQq22dZXdqvXFFREYKDg5GQkICgoCAsXLhQc4HKWG3b8OHDhwgODoaPjw/69OmDkpISaVlpaSlKSkrQqJF+nQLq8ndoZmYGIyMjtWTSwMAA7u7u2L9/vwajlZ+6tN+uXbsAAJGRkdJcGX369MGYMWOwbt06HDx4UIMRPxvYl+iPp+krqWG5ublVKHvppZcAlF0Jxh8g5KWqY6v8PY8t+XBxcalQ5urqimbNmuH333/XQkREuoW5hO5gLqF7mE/oDuYTzzYOG9ZQ+TPxHp94Oj09XW354+tkZmZWuKo2PT290vrPsrq0H1DWKUyaNAlHjhzBkiVL9HYgA6h9G2ZnZyMlJQVxcXHo0qWL9AKAzZs3S//WJ3X5O2zXrp00+POo4uJivbv1ty7td+PGDTg4OEgDGUDZYJCrqyuuXLmiwWifHexL9Edd+0pqWDk5Odi3b1+FSVTv378PAGjRooU2wqJq2Nvbw8jIqMKxVf6ex5Y8/P333zhw4ECFHxmEECguLuaxRVQDzCV0A3MJ3cR8Qjcwn3j2cTCjhtq1a4e2bdviq6++Uis/duwY2rdvj9atW1dYx8PDA3fv3kVycrJUlpubi/Pnz8Pd3V3jMctJXdrv4cOHePPNN5GSkoIPPvgAEyZMaKhwZam2bWhra4v9+/dXeAHA6NGj9e6uAqBuf4eenp4QQuDIkSNSWUlJCb7//nu4urpqPGY5qUv7dejQAZcvX8adO3fUylNSUtCmTRuNxvusYF+iP+pyjFHDMzAwwIoVKxAVFaVWnpiYCCMjI73rG3SBiYkJVCoVjh07pjYwfPToUTRr1gzOzs5ajI7KmZiY4P3330d4eLhaeVJSEu7fv1/pVcxEpI65hG5gLqGbmE/oBuYTzz6jlStXrtR2ELqiWbNm+Oijj/DXX3/BwMAAO3fuRGxsLP75z3+iU6dOyM3NxaVLl2Bubg5jY2O0adMG586dQ3R0NCwtLXHjxg0sWbIEQgisW7dO7yacqW37xcTEIDo6GiNHjoSbmxtu3rwpvf7880+0atVK27vU4GrThk2aNEHLli0rvMLDw+Hl5QU/Pz9t745W1Pbv0M7ODqmpqfj8889hZmaGu3fvIjQ0FBcuXEBoaChsbW21vUsNqrbt17FjR+zbtw8nT56EpaUlrl+/jrCwMJw4cQIrVqxAp06dtL1LWnXx4kUkJSVh0qRJ0iOj2JfotycdY6R9TZo0QV5eHj777DOUlpaitLQUX375JcLCwjBmzBj4+/trO0S9V9m5tVWrVti6dSuuXr2KJk2aIC4uDh9//DHeeecd9OrVS8sR66fHvydDQ0M0atQIu3fvxp07d9CoUSMkJSVh7dq18PT0xLRp07QdMpFOYC4hf8wldAPzCd3AfEIPCaqVmJgY4e3tLZydncXgwYNFbGystOzAgQNCoVCIM2fOSGV5eXkiODhYqFQq0aNHDzFlyhRx9epVbYQuC7Vpv/HjxwuFQlHp64UXXtDWLmhdbf8GH6dQKERERERDhCpbtW3De/fuiffee094eHiIrl27ilGjRomzZ89qI3RZqG37XblyRUybNk0olUrh6uoqRo8eLU6fPq2N0GWnvL2ys7MrlLEv0V/VHWMkD0VFRWL79u1i0KBBwtnZWXh5eYlt27aJhw8fajs0EpWfW4UQ4tixY8LPz0906dJF9O/fX3zyySdaipCEqPp72rt3r/Dz8xMuLi7C09NThIaGinv37mkpSiLdxFxC/phLyB/zCd3AfEL/GAjx2EO4iYiIiIiIiIiIiIiIZIRzZhARERERERERERERkaxxMIOIiIiIiIiIiIiIiGSNgxlERERERERERERERCRrHMwgIiIiIiIiIiIiIiJZ42AGERERERERERERERHJGgcziIiIiIiIiIiIiIhI1hppOwAiXbd582aEh4dXWycuLg4vvPBCjT+zf//+aNOmDfbs2fO04dVIZftgYGAAU1NTtGvXDkOHDkVgYCAMDet//LN820lJSWjbti0AoLS0FDdu3JDenz17FoGBgQgJCcGwYcPqPYbKODo6Vlpubm4OOzs7DBs2DOPHj4eBgUGdPj8zMxN2dnZPEyIREZFsBAcHIzY2tto6Xl5e2LJlSwNFpK6hcysiIiKqPeYTRPQkHMwgqifTp09Hx44dK13WunXrBo6mbh7dByEE7t27h6SkJISEhCAzMxPLly+v9216e3vD3t4eVlZWAICCggJMnDgR/fr1wzvvvAMAcHBwQGhoKHr06FHv269Ox44dMX36dLWy7OxsHDx4EGvXrsX9+/cxderUWn9uUFAQbGxs8N5779VXqERERLKwePFitGjRotJlzz//fANHQ0RERLqI+QQRVYWDGUT1xN3dHb169dJ2GE+lsn0YNWoURo8ejejoaEydOhUtW7as1206OTnByclJep+Xl4fU1FT069dPKrO2tsZrr71Wr9utiaq2O27cOPj4+GDHjh2YOHEijI2Na/W5p06dwtChQ+srTCIiItkYMGCAdGclERERUV0wnyCiqnDODCKqlqGhIXx8fFBaWoqUlBRthyML5ubm8PLywp07d5CWlqbtcIiIiIiIiIiIiJ55HMwgakBCCMTExGDEiBFQKpXo2rUrfHx8sH37dgghqlzvzp07CA4OxksvvQRnZ2cMGDAAGzduxIMHD9TqXblyBTNmzIBKpUK3bt3w+uuv4/vvv3/quMvnhSgpKZHKLl26hLfeegsqlQouLi4ICAjA8ePH1dYrKirC2rVr4eXlBWdnZ/Tr1w+rVq3CnTt3pDqbN2+Go6MjsrKycPbsWXh5eQEAwsPD1codHR1x8OBBFBUVoWfPnhUe/wQABw8ehKOjI3744QcAZXNvREZGwsfHB87OzvD09MS7776LgoKCp26Tpk2bVihLT0/HokWL0LdvXzg7O8PNzQ3Tp0/H5cuXAQBZWVnSXByxsbFwdHTE2bNnNR4rERGRnPTv3x9Lly7Fvn374OXlhe7du+P111/HmTNnKtQ9f/48Jk6cCKVSCaVSicDAQKmff1RKSgqmTJmCnj17olevXpg6dSouXbpUod6hQ4fg6+sLZ2dnDBo0CDExMWrLa5pzERERkXYxnyDST3zMFFE9yc/PR25uboXyZs2aoXHjxgCADz/8EFu3bsXQoUMREBCAwsJCxMXFYePGjbCxsany0UOzZ8/Gb7/9hsDAQNja2uLnn3/G9u3bkZeXhzVr1gAoG1wYM2YMrK2tMW3aNDRu3BiHDx/G1KlTsXHjRrzyyit13rfyZKBLly4AgF9++QWBgYEwNzfHpEmTYGZmhi+//BIzZszAihUrMHbsWADA6tWrcfjwYQQGBsLOzg6XL1/GZ599hvT0dERGRlbYjoODAxYvXoyQkBB4e3vD29sbVlZWuH79ulTH2NgYAwcORHx8PPLz89GsWTNpWWJiIp5//nmoVCoAwNKlSxEXF4ehQ4di4sSJuHr1KmJiYvDTTz8hJiYGJiYmdWqP0tJSnDp1Ck2bNkX79u0BALdv30ZAQADMzc0xbtw4tGjRAhcvXsTevXtx9epVHD16FFZWVggNDcXChQuhUqkQEBAABwcHjcZKRETUkO7evVtpPgQAzZs3h5GREQAgOTkZ8fHxGD9+PGxsbBATE4PJkycjMjISbm5uAICkpCS8/fbbsLe3x5tvvgkA2LdvHyZOnIiwsDDpAojyHyhsbW0RFBQEU1NT7N69G4GBgThw4ID0mIrU1FT897//xbhx42BlZYXPP/8cK1euhI2NDQYMGACgZjkXERERaRbzCSKqkiCipxIWFiYUCkWVrzNnzgghhCgqKhI9evQQc+bMUVs/Pz9fODs7i2nTpkllL7/8shg3bpwQQojbt28LhUIhduzYobZecHCwmDBhgvR+3LhxYsCAAaKwsFAqKy4uFmPGjBHu7u7iwYMHT9yHr7/+WuTk5IicnBxx+/ZtkZqaKlavXi0UCoWYMWOGVH/kyJGie/fuIjs7Wyq7f/++GDp0qHBxcRE5OTlCCCFcXFzEqlWr1La1adMmMWzYMFFQUKC27czMTCGEEJmZmUKhUIiwsDBpnTNnzgiFQiEOHDgghBDi3//+t1AoFCI2Nlaqk5ubKzp37izWr1+vtk5MTIza9r///nuhUCjErl27qmwPIYRQKBRi1KhRUnvk5OSIW7duiV9++UXMmzdPKBQKERERIdXftm2bUCgU4sqVK2qfs2HDBqFQKMSFCxfUPnvRokUV9q+usRIREWnbokWLqs2HFAqF+O2334QQZXlOed5RLicnR6hUKhEQECCEKMth+vbtK/r16yfy8/Olenfu3BGenp7C09NTFBUVCSGEGDFihOjTp4/Izc2V6qWlpQknJyfx/vvvS9t0dHRU64+zsrKEo6OjWLBggRCi5jkXERERaQbzCSJ6Et6ZQVRPFi1apDaRdbnyssaNGyM5ORnFxcVqy//66y+Ym5vj77//rvRzmzVrhqZNmyI6Ohpt27aFp6cnmjZtipCQELXPOHfuHMaPH4/79+/j/v370jJvb2+EhIQgNTUVrq6u1e7DjBkzKpQZGRnBz88Pq1atAlB2B0JKSgpGjx6NVq1aSfVMTEwQFBSEuXPnIjk5GX5+fmjVqhUSExOl2yotLCwwe/ZszJ49u9o4nsTNzQ0tW7bEV199hSFDhgAAjh07hpKSEvj7+0vvDQwM0K9fP7UrOjp37gwbGxt8++23mDBhQrXb+fnnn9G7d+8K5W3atMHSpUsRGBgolU2dOhXDhw/Hc889J5Xdv38fhoZlT/Or6vutr1iJiIjkYP369bC2tq50mb29vfTvjh07SlcvAoCVlRVee+01REVFIScnB9evX8fNmzcxf/58mJubS/UsLCwwbtw4bNy4ERcuXIC9vT1SU1MxadIktGjRQqrXoUMHHDhwAM8//7xU1r59e+kuU6CsP7eyssLt27cB1CznIiIiIs1jPkFEVeFgBlE96dKlC3r16lVtncaNG+Pbb79FUlISrl27hvT0dGn+CFHFnBnGxsZYvXo1li9fjpkzZ8LY2Bhubm4YOHAghgwZAhMTE2RmZgIA9uzZgz179lT6OdnZ2U/ch0cHZAwMDGBmZgYHBweYmZlJdcof+dShQ4cK65c/MunGjRsAgJUrV2L27NlYvHgxli9fju7du8Pb2xvDhw9XezxUbRkaGsLX1xd79uyRHjWVmJgIhUIhzUmRkZEBIQReeumlSj/j0X2qiqOjI4KDgwGUDRjt3r0bly9fxoIFCzB48OAK9YuLi7Fp0yb8+uuvyMjIQFZWFh4+fAig7NFUVamPWImIiOSgR48e0mMYqvOPf/yjQlm7du0ghMD169eRlZUFoPJ8o2PHjgDK8g0jIyMIIdCuXbsK9Tp37qz2/tELDsqZmppKF5rUJOciIiIizWM+QURV4WAGUQMRQmDBggU4fPgwXF1doVQqMWrUKPTs2fOJV937+/vD09MTx48fx8mTJ5GcnIxTp04hOjoa+/btk34wHzt2rNpVCY+qrJN/XE0GZKoadAH+/wf78jlCevfujRMnTkiv06dPIyQkBLt27cLBgwdhZWX1xJiq4u/vj8jISCQlJcHDwwM//PCD2h0fpaWlMDMzQ3h4eKXr1ySBaN68Odzd3aX33t7eCAwMxNy5c2FgYAAfHx9p2YULFzB+/HiYmprC3d0dw4cPR+fOnZGRkYHVq1dXu536iJWIiEiXlOcKjyrPZ8p/UKhK+bLGjRtLuUf5nZDVqUmdJ+VcxsbGT/wMIiIiahjMJ4j0DwcziBrI+fPncfjwYbz11luYNWuWVF5SUoK8vDzY2dlVul5hYSEuXryITp06YcSIERgxYgSKioqwfv167N69G6dOnYKzszOAss760R/fAeDKlSvIyspCkyZN6mU/2rRpAwBIS0ursOzatWsAgFatWqGoqAgXL15Eq1at4OvrC19fX5SWlmLnzp0IDQ1FQkICxo8fX+c4OnfuDAcHBxw/fhyFhYUoLS2Fr6+vWpzlbWNhYaG27tGjR2FpaVnrbRobG+ODDz6Av78/li5diq5du0rtERoaCmNjYyQkJKgN0mzduvWJn6uJWImIiOQsIyOjQll6ejqMjIzQtm1b6erGJ+UbLVu2lNZ93Pr169G8eXNMnTq1RjHVJOfq379/jfeRiIiINIv5BJH+efJwIhHVi7y8PAAV75DYu3cv7t27h5KSkkrXu3z5MsaOHYv9+/dLZcbGxtKtjkZGRrC1tYWzszNiY2Px559/SvWKi4uxZMkSzJw5s8rPry0bGxs4OzsjPj4eN2/elMqLioqwc+dOGBsbo0+fPsjLy8OoUaOwbds2qY6hoSG6du0q/bsyRkZGAKp/LFM5f39/nD59Gl999RVcXV2lgQUAUnLw0Ucfqa3zzTffYObMmTh06FAN91hd69atsXDhQhQUFGDlypVSeV5eHqysrNQGMvLz8xEbGwvg/68OAcr2/dH901SsREREcpWamor//Oc/0vvbt28jPj4eL774Ipo3b44uXbrAxsYGMTExKCgokOoVFBQgOjpaykdatmwJJycnJCQkqNXLzMzE7t27pedX10RNci4iIiKSD+YTRPqHd2YQNRClUglzc3OEhITgxo0bsLCwwNZhQZoAAAPgSURBVNmzZ5GYmAgTExMUFhZWul63bt2gUqmwadMmZGdnw9HREdnZ2YiKikLHjh2lCaqXLVuGCRMmYPjw4Rg9ejQsLS2RkJCAlJQUzJs3T20Sq6dVvq0RI0Zg9OjRMDMzQ3x8PH799VcsW7YMFhYWsLCwgL+/P6Kjo3Hv3j0olUrk5eUhKioK1tbWlc45AQCWlpYwNDTEN998g9atW2PgwIFVxuHn54cPP/wQ586dkyYoL9evXz94eXkhMjISWVlZcHd3x/Xr1/HZZ5+hdevWCAoKqvP+BwQEIC4uDt999x0OHToEf39/9O3bFx9//DFmzZoFDw8P3Lp1C/v375eSnke/XysrK5w7dw579+6Fh4eHRmMlIiJqSMePH68253jttdcAlP2nfsqUKZgwYQJMTU0RHR2N0tJSLFy4EEDZIx+WL1+O2bNnY/jw4RgxYgQAYP/+/fif//kfhIWFSRdGLF68GJMnT8bw4cMxcuRIGBoaIioqChYWFpgyZUqNY69pzkVERESaxXyCiKrCwQyiBmJtbY3t27djw4YN2LJlC4yNjdGhQwd88MEH+OWXX6TRfmtra7X1DAwMEBERgfDwcJw4cQJffPEFmjdvjoEDB2LWrFnSsxaVSiViYmKwefNm7Ny5EyUlJejQoQPee+89DB06tF73pXxbYWFhiIyMRGlpKZycnBAREaE2Z8eaNWtgZ2eHhIQEJCQkoEmTJujduzfmzJlT5XwZTZo0wZw5c/DJJ5/g3Xffhb29fZVx2NnZQalU4sKFC2rzVwBl7favf/0LO3bsQFxcHE6cOAErKyup3R5v59owMDDAmjVrMGTIEKxbtw4eHh5455138PDhQyQmJuLEiROwtbWFu7s73njjDfj6+uLMmTPw9vYGAMyfPx8bN27EmjVrpM/RVKxEREQNKSQkpNrl5T8+dO/eHb6+vtiyZQvy8/OhUqkwb948ODk5SXUHDRqEyMhIbNmyBREREWjUqBG6deuGtWvXQqVSSfVefPFFfPrppwgLC0NERARMTEzQs2dPLFiwADY2NjWOvaY5FxEREWkW8wkiqoqBqG42HCIiIiIionrUv39/tGnTBnv27NF2KERERKSjmE8Q6SfOmUFERERERERERERERLLGwQwiIiIiIiIiIiIiIpI1DmYQEREREREREREREZGscc4MIiIiIiIiIiIiIiKSNd6ZQUREREREREREREREssbBDCIiIiIiIiIiIiIikjUOZhARERERERERERERkaxxMIOIiIiIiIiIiIiIiGSNgxlERERERERERERERCRrHMwgIiIiIiIiIiIiIiJZ+1+O5qAiTOKCIAAAAABJRU5ErkJggg==\n",
			"text/plain": [
			"<Figure size 1944x432 with 3 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"train_pred_class5_under,test_pred_class5_under = CompileAndTrainCNNModel(model5,images_under, labels_under,20,\"model5_under\")"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"##### Taking out the pooling does not seem to make it better.\n",
			"\n",
			"Lets try an even bigger one, with orioginal data, and with exrta FC and dropout layers. Damn 17M parameters. Its gonna be long a little"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 113,
			"metadata": {},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"_________________________________________________________________\n",
			"Layer (type) Output Shape Param # \n",
			"=================================================================\n",
			"zero_padding2d_40 (ZeroPaddi (None, 32, 32, 3) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_158 (Conv2D) (None, 32, 32, 16) 448 \n",
			"_________________________________________________________________\n",
			"conv2d_159 (Conv2D) (None, 32, 32, 32) 4640 \n",
			"_________________________________________________________________\n",
			"conv2d_160 (Conv2D) (None, 32, 32, 64) 18496 \n",
			"_________________________________________________________________\n",
			"conv2d_161 (Conv2D) (None, 32, 32, 128) 73856 \n",
			"_________________________________________________________________\n",
			"conv2d_162 (Conv2D) (None, 32, 32, 256) 295168 \n",
			"_________________________________________________________________\n",
			"flatten_39 (Flatten) (None, 262144) 0 \n",
			"_________________________________________________________________\n",
			"dense_79 (Dense) (None, 64) 16777280 \n",
			"_________________________________________________________________\n",
			"dropout_10 (Dropout) (None, 64) 0 \n",
			"_________________________________________________________________\n",
			"dense_80 (Dense) (None, 128) 8320 \n",
			"_________________________________________________________________\n",
			"dropout_11 (Dropout) (None, 128) 0 \n",
			"_________________________________________________________________\n",
			"dense_81 (Dense) (None, 2) 258 \n",
			"=================================================================\n",
			"Total params: 17,178,466\n",
			"Trainable params: 17,178,466\n",
			"Non-trainable params: 0\n",
			"_________________________________________________________________\n",
			"Train on 3101 samples, validate on 1034 samples\n",
			"Epoch 1/20\n",
			"3101/3101 [==============================] - 113s 36ms/sample - loss: 0.6771 - acc: 0.6108 - val_loss: 0.6621 - val_acc: 0.6315\n",
			"Epoch 2/20\n",
			"3101/3101 [==============================] - 108s 35ms/sample - loss: 0.6621 - acc: 0.6246 - val_loss: 0.6570 - val_acc: 0.6315\n",
			"Epoch 3/20\n",
			"3101/3101 [==============================] - 108s 35ms/sample - loss: 0.6599 - acc: 0.6227 - val_loss: 0.6561 - val_acc: 0.6315\n",
			"Epoch 4/20\n",
			"3101/3101 [==============================] - 108s 35ms/sample - loss: 0.6643 - acc: 0.6246 - val_loss: 0.6529 - val_acc: 0.6315\n",
			"Epoch 5/20\n",
			"3101/3101 [==============================] - 108s 35ms/sample - loss: 0.6616 - acc: 0.6211 - val_loss: 0.6545 - val_acc: 0.6315\n",
			"Epoch 6/20\n",
			"3101/3101 [==============================] - 108s 35ms/sample - loss: 0.6580 - acc: 0.6230 - val_loss: 0.6494 - val_acc: 0.6315\n",
			"Epoch 7/20\n",
			"3101/3101 [==============================] - 108s 35ms/sample - loss: 0.6525 - acc: 0.6237 - val_loss: 0.6426 - val_acc: 0.6306\n",
			"Epoch 8/20\n",
			"3101/3101 [==============================] - 108s 35ms/sample - loss: 0.6512 - acc: 0.6221 - val_loss: 0.6395 - val_acc: 0.6344\n",
			"Epoch 9/20\n",
			"3101/3101 [==============================] - 106s 34ms/sample - loss: 0.6493 - acc: 0.6246 - val_loss: 0.6353 - val_acc: 0.6344\n",
			"Epoch 10/20\n",
			"3101/3101 [==============================] - 106s 34ms/sample - loss: 0.6493 - acc: 0.6285 - val_loss: 0.6376 - val_acc: 0.6364\n",
			"Epoch 11/20\n",
			"3101/3101 [==============================] - 108s 35ms/sample - loss: 0.6504 - acc: 0.6269 - val_loss: 0.6397 - val_acc: 0.6325\n",
			"Epoch 12/20\n",
			"3101/3101 [==============================] - 107s 35ms/sample - loss: 0.6456 - acc: 0.6301 - val_loss: 0.6441 - val_acc: 0.6335\n",
			"Epoch 13/20\n",
			"3101/3101 [==============================] - 110s 35ms/sample - loss: 0.6484 - acc: 0.6295 - val_loss: 0.6517 - val_acc: 0.6335\n",
			"Epoch 14/20\n",
			"3101/3101 [==============================] - 109s 35ms/sample - loss: 0.6442 - acc: 0.6330 - val_loss: 0.6523 - val_acc: 0.6296\n",
			"Epoch 15/20\n",
			"3101/3101 [==============================] - 110s 35ms/sample - loss: 0.6428 - acc: 0.6311 - val_loss: 0.6282 - val_acc: 0.6431\n",
			"Epoch 16/20\n",
			"3101/3101 [==============================] - 108s 35ms/sample - loss: 0.6444 - acc: 0.6227 - val_loss: 0.6514 - val_acc: 0.6306\n",
			"Epoch 17/20\n",
			"3101/3101 [==============================] - 110s 36ms/sample - loss: 0.6470 - acc: 0.6295 - val_loss: 0.6423 - val_acc: 0.6344\n",
			"Epoch 18/20\n",
			"3101/3101 [==============================] - 109s 35ms/sample - loss: 0.6554 - acc: 0.6308 - val_loss: 0.6392 - val_acc: 0.6373\n",
			"Epoch 19/20\n",
			"3101/3101 [==============================] - 110s 35ms/sample - loss: 0.6455 - acc: 0.6311 - val_loss: 0.6403 - val_acc: 0.6315\n",
			"Epoch 20/20\n",
			"3101/3101 [==============================] - 109s 35ms/sample - loss: 0.6399 - acc: 0.6337 - val_loss: 0.6527 - val_acc: 0.6132\n",
			"[[163 218]\n",
			" [182 471]]\n",
			"Train/Test recall: 0.7093 / 0.7213\n",
			"Train/Test accuracy: 0.6204 / 0.6132\n",
			"Test specificity: 0.4278\n"
			]
			},
			{
			"data": {
			"image/png": 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\n",
			"text/plain": [
			"<Figure size 1944x432 with 3 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"model8 = models.Sequential()\n",
			"# need to add an extra zero padding layer, 4 on each width side, 2 on each height side\n",
			"model8.add(layers.ZeroPadding2D(padding=(4, 2), data_format=None,input_shape=(24, 28, 3)))\n",
			"# 1st conv layer, with 32 filters of size (3,3) \n",
			"model8.add(layers.Conv2D(16, (3, 3), activation='relu', padding=\"same\"))\n",
			"model8.add(layers.Conv2D(32, (3, 3), activation='relu', padding=\"same\"))\n",
			"# 2nd conv layer, with 64 filters of size (3,3) \n",
			"model8.add(layers.Conv2D(64, (3, 3), activation='relu', padding=\"same\"))\n",
			"model8.add(layers.Conv2D(128, (3, 3), activation='relu', padding=\"same\"))\n",
			"# last conv layer, with 64 filters of size (3,3) \n",
			"model8.add(layers.Conv2D(256, (3, 3), activation='relu', padding=\"same\"))\n",
			"\n",
			"\n",
			"# flaten the images to prepare for the dense layers\n",
			"model8.add(layers.Flatten())\n",
			"model8.add(layers.Dense(64, activation='relu'))\n",
			"model8.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"model8.add(layers.Dense(128, activation='relu'))\n",
			"model8.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"\n",
			"# final dense softmax layer, with 2 classes so 2 dimension, to have probabilities at the end\n",
			"model8.add(layers.Dense(2, activation='softmax'))\n",
			"# model architecture\n",
			"model8.summary()\n",
			"\n",
			"train_pred_class8,test_pred_class8 = CompileAndTrainCNNModel(model8,images, labels,20,\"model6\")"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"##### This has not converged yet! We need more epochs. We'll run it at lunch! LOUL. "
			]
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"## Ideas to improve?"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Ideas for further improvements, specially to reduce overfitting: \n",
			"\n",
			"\n",
			"- Try to play with the learning rate / add momentum?\n",
			"- Dropout after FCs to regularize? Or in between CONV? (Dropout appears to be useless for conv layers, according to most people) \n",
			"- Batch normalization after the CONV and/or FC layers, before non-linearities. May help to regularize\n",
			"- Early stopping\n",
			"- CREATE MORE DATA with augmentation and other techniques? with the ImageDataGenerator class from Keras.\n",
			"\n",
			"Also:\n",
			"- Visualize activations. \n",
			"- Use CNN to extract features, then build anoter linear ML algo on top. "
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"### Regularize 1: Let's try to add dropout (in the dense layers AND conv layers, after)"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Like model , but with dropout. "
			]
			},
			{
			"cell_type": "code",
			"execution_count": 107,
			"metadata": {},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"_________________________________________________________________\n",
			"Layer (type) Output Shape Param # \n",
			"=================================================================\n",
			"zero_padding2d_34 (ZeroPaddi (None, 32, 32, 3) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_132 (Conv2D) (None, 32, 32, 32) 896 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_61 (MaxPooling (None, 16, 16, 32) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_133 (Conv2D) (None, 16, 16, 64) 18496 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_62 (MaxPooling (None, 8, 8, 64) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_134 (Conv2D) (None, 8, 8, 128) 73856 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_63 (MaxPooling (None, 4, 4, 128) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_135 (Conv2D) (None, 4, 4, 256) 295168 \n",
			"_________________________________________________________________\n",
			"flatten_33 (Flatten) (None, 4096) 0 \n",
			"_________________________________________________________________\n",
			"dense_64 (Dense) (None, 64) 262208 \n",
			"_________________________________________________________________\n",
			"dropout_1 (Dropout) (None, 64) 0 \n",
			"_________________________________________________________________\n",
			"dense_65 (Dense) (None, 2) 130 \n",
			"=================================================================\n",
			"Total params: 650,754\n",
			"Trainable params: 650,754\n",
			"Non-trainable params: 0\n",
			"_________________________________________________________________\n",
			"Train on 3101 samples, validate on 1034 samples\n",
			"Epoch 1/20\n",
			"3101/3101 [==============================] - 12s 4ms/sample - loss: 0.6674 - acc: 0.6259 - val_loss: 0.6576 - val_acc: 0.6315\n",
			"Epoch 2/20\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6570 - acc: 0.6253 - val_loss: 0.6352 - val_acc: 0.6315\n",
			"Epoch 3/20\n",
			"3101/3101 [==============================] - 13s 4ms/sample - loss: 0.6477 - acc: 0.6230 - val_loss: 0.6361 - val_acc: 0.6315\n",
			"Epoch 4/20\n",
			"3101/3101 [==============================] - 12s 4ms/sample - loss: 0.6406 - acc: 0.6253 - val_loss: 0.6256 - val_acc: 0.6315\n",
			"Epoch 5/20\n",
			"3101/3101 [==============================] - 13s 4ms/sample - loss: 0.6314 - acc: 0.6208 - val_loss: 0.6317 - val_acc: 0.6238\n",
			"Epoch 6/20\n",
			"3101/3101 [==============================] - 12s 4ms/sample - loss: 0.6277 - acc: 0.6295 - val_loss: 0.6263 - val_acc: 0.6402\n",
			"Epoch 7/20\n",
			"3101/3101 [==============================] - 12s 4ms/sample - loss: 0.6154 - acc: 0.6469 - val_loss: 0.6315 - val_acc: 0.6412\n",
			"Epoch 8/20\n",
			"3101/3101 [==============================] - 12s 4ms/sample - loss: 0.6092 - acc: 0.6479 - val_loss: 0.6195 - val_acc: 0.6354\n",
			"Epoch 9/20\n",
			"3101/3101 [==============================] - 12s 4ms/sample - loss: 0.5999 - acc: 0.6588 - val_loss: 0.6167 - val_acc: 0.6383\n",
			"Epoch 10/20\n",
			"3101/3101 [==============================] - 12s 4ms/sample - loss: 0.5874 - acc: 0.6579 - val_loss: 0.6266 - val_acc: 0.6441\n",
			"Epoch 11/20\n",
			"3101/3101 [==============================] - 12s 4ms/sample - loss: 0.5904 - acc: 0.6662 - val_loss: 0.6359 - val_acc: 0.6402\n",
			"Epoch 12/20\n",
			"3101/3101 [==============================] - 12s 4ms/sample - loss: 0.5655 - acc: 0.6782 - val_loss: 0.6540 - val_acc: 0.6518\n",
			"Epoch 13/20\n",
			"3101/3101 [==============================] - 12s 4ms/sample - loss: 0.5443 - acc: 0.6895 - val_loss: 0.6394 - val_acc: 0.6170\n",
			"Epoch 14/20\n",
			"3101/3101 [==============================] - 12s 4ms/sample - loss: 0.5373 - acc: 0.6940 - val_loss: 0.6759 - val_acc: 0.6074\n",
			"Epoch 15/20\n",
			"3101/3101 [==============================] - 12s 4ms/sample - loss: 0.5072 - acc: 0.7156 - val_loss: 0.6913 - val_acc: 0.6325\n",
			"Epoch 16/20\n",
			"3101/3101 [==============================] - 12s 4ms/sample - loss: 0.4832 - acc: 0.7452 - val_loss: 0.7359 - val_acc: 0.6335\n",
			"Epoch 17/20\n",
			"3101/3101 [==============================] - 12s 4ms/sample - loss: 0.4492 - acc: 0.7665 - val_loss: 0.7041 - val_acc: 0.6412\n",
			"Epoch 18/20\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.4081 - acc: 0.7859 - val_loss: 0.8640 - val_acc: 0.6180\n",
			"Epoch 19/20\n",
			"3101/3101 [==============================] - 12s 4ms/sample - loss: 0.3869 - acc: 0.7943 - val_loss: 0.8236 - val_acc: 0.6248\n",
			"Epoch 20/20\n",
			"3101/3101 [==============================] - 12s 4ms/sample - loss: 0.3518 - acc: 0.8207 - val_loss: 0.9932 - val_acc: 0.5986\n",
			"[[205 176]\n",
			" [239 414]]\n",
			"Train/Test recall: 0.8575 / 0.6340\n",
			"Train/Test accuracy: 0.8500 / 0.5986\n",
			"Test specificity: 0.5381\n"
			]
			},
			{
			"data": {
			"image/png": 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\n",
			"text/plain": [
			"<Figure size 1944x432 with 3 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"# initialize a first model\n",
			"model7 = models.Sequential()\n",
			"# need to add an extra zero padding layer, 4 on each width side, 2 on each height side\n",
			"model7.add(layers.ZeroPadding2D(padding=(4, 2), data_format=None,input_shape=(24, 28, 3)))\n",
			"# 1st conv layer, with 32 filters of size (3,3) \n",
			"model7.add(layers.Conv2D(32, (3, 3), activation='relu', padding=\"same\"))\n",
			"# 1stpool layer, divinding by 2 the dimension\n",
			"model7.add(layers.MaxPooling2D((2, 2)))\n",
			"# 2nd conv layer, with 64 filters of size (3,3) \n",
			"model7.add(layers.Conv2D(64, (3, 3), activation='relu', padding=\"same\"))\n",
			"# 2nd pool layer, divinding by 2 the dimension\n",
			"model7.add(layers.MaxPooling2D((2, 2)))\n",
			"# last conv layer, with 64 filters of size (3,3) \n",
			"model7.add(layers.Conv2D(128, (3, 3), activation='relu', padding=\"same\"))\n",
			"\n",
			"model7.add(layers.MaxPooling2D((2, 2)))\n",
			"# last conv layer, with 64 filters of size (3,3) \n",
			"model7.add(layers.Conv2D(256, (3, 3), activation='relu', padding=\"same\"))\n",
			"\n",
			"\n",
			"# flaten the images to prepare for the dense layers\n",
			"model7.add(layers.Flatten())\n",
			"# DROPOUT\n",
			"model7.add(layers.Dense(64, activation='relu'))\n",
			"model7.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"# final dense softmax layer, with 2 classes so 2 dimension, to have probabilities at the end\n",
			"model7.add(layers.Dense(2, activation='softmax'))\n",
			"\n",
			"# model architecture\n",
			"model7.summary()\n",
			"\n",
			"train_pred_class7,test_pred_class7 = CompileAndTrainCNNModel(model7,images, labels,20,\"model7\")"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Let's put dropout in conv layers to see what happens. "
			]
			},
			{
			"cell_type": "code",
			"execution_count": 116,
			"metadata": {
			"scrolled": true
			},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"_________________________________________________________________\n",
			"Layer (type) Output Shape Param # \n",
			"=================================================================\n",
			"zero_padding2d_43 (ZeroPaddi (None, 32, 32, 3) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_169 (Conv2D) (None, 32, 32, 32) 896 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_68 (MaxPooling (None, 16, 16, 32) 0 \n",
			"_________________________________________________________________\n",
			"dropout_16 (Dropout) (None, 16, 16, 32) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_170 (Conv2D) (None, 16, 16, 64) 18496 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_69 (MaxPooling (None, 8, 8, 64) 0 \n",
			"_________________________________________________________________\n",
			"dropout_17 (Dropout) (None, 8, 8, 64) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_171 (Conv2D) (None, 8, 8, 128) 73856 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_70 (MaxPooling (None, 4, 4, 128) 0 \n",
			"_________________________________________________________________\n",
			"dropout_18 (Dropout) (None, 4, 4, 128) 0 \n",
			"_________________________________________________________________\n",
			"flatten_42 (Flatten) (None, 2048) 0 \n",
			"_________________________________________________________________\n",
			"dense_88 (Dense) (None, 64) 131136 \n",
			"_________________________________________________________________\n",
			"dropout_19 (Dropout) (None, 64) 0 \n",
			"_________________________________________________________________\n",
			"dense_89 (Dense) (None, 128) 8320 \n",
			"_________________________________________________________________\n",
			"dropout_20 (Dropout) (None, 128) 0 \n",
			"_________________________________________________________________\n",
			"dense_90 (Dense) (None, 2) 258 \n",
			"=================================================================\n",
			"Total params: 232,962\n",
			"Trainable params: 232,962\n",
			"Non-trainable params: 0\n",
			"_________________________________________________________________\n",
			"Train on 3101 samples, validate on 1034 samples\n",
			"Epoch 1/20\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6754 - acc: 0.6092 - val_loss: 0.6732 - val_acc: 0.6315\n",
			"Epoch 2/20\n",
			"3101/3101 [==============================] - 9s 3ms/sample - loss: 0.6650 - acc: 0.6246 - val_loss: 0.6579 - val_acc: 0.6315\n",
			"Epoch 3/20\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6607 - acc: 0.6250 - val_loss: 0.6603 - val_acc: 0.6315\n",
			"Epoch 4/20\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6591 - acc: 0.6246 - val_loss: 0.6570 - val_acc: 0.6315\n",
			"Epoch 5/20\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6600 - acc: 0.6246 - val_loss: 0.6618 - val_acc: 0.6315\n",
			"Epoch 6/20\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6577 - acc: 0.6246 - val_loss: 0.6585 - val_acc: 0.6315\n",
			"Epoch 7/20\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6539 - acc: 0.6246 - val_loss: 0.6576 - val_acc: 0.6315\n",
			"Epoch 8/20\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6557 - acc: 0.6243 - val_loss: 0.6511 - val_acc: 0.6315\n",
			"Epoch 9/20\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6501 - acc: 0.6230 - val_loss: 0.6543 - val_acc: 0.6315\n",
			"Epoch 10/20\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6499 - acc: 0.6237 - val_loss: 0.6471 - val_acc: 0.6315\n",
			"Epoch 11/20\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.6447 - acc: 0.6240 - val_loss: 0.6625 - val_acc: 0.6315\n",
			"Epoch 12/20\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.6489 - acc: 0.6208 - val_loss: 0.6436 - val_acc: 0.6315\n",
			"Epoch 13/20\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6436 - acc: 0.6243 - val_loss: 0.6542 - val_acc: 0.6315\n",
			"Epoch 14/20\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.6385 - acc: 0.6224 - val_loss: 0.6428 - val_acc: 0.6315\n",
			"Epoch 15/20\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6386 - acc: 0.6233 - val_loss: 0.6380 - val_acc: 0.6315\n",
			"Epoch 16/20\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6351 - acc: 0.6343 - val_loss: 0.6498 - val_acc: 0.6315\n",
			"Epoch 17/20\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6349 - acc: 0.6321 - val_loss: 0.6421 - val_acc: 0.6315\n",
			"Epoch 18/20\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6406 - acc: 0.6330 - val_loss: 0.6405 - val_acc: 0.6335\n",
			"Epoch 19/20\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6388 - acc: 0.6346 - val_loss: 0.6338 - val_acc: 0.6354\n",
			"Epoch 20/20\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.6380 - acc: 0.6317 - val_loss: 0.6484 - val_acc: 0.6296\n",
			"[[ 8 373]\n",
			" [ 10 643]]\n",
			"Train/Test recall: 0.9928 / 0.9847\n",
			"Train/Test accuracy: 0.6337 / 0.6296\n",
			"Test specificity: 0.0210\n"
			]
			},
			{
			"data": {
			"image/png": 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\n",
			"text/plain": [
			"<Figure size 1944x432 with 3 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"model10 = models.Sequential()\n",
			"# need to add an extra zero padding layer, 4 on each width side, 2 on each height side\n",
			"model10.add(layers.ZeroPadding2D(padding=(4, 2), data_format=None,input_shape=(24, 28, 3)))\n",
			"# 1st conv layer, with 32 filters of size (3,3) \n",
			"model10.add(layers.Conv2D(32, (3, 3), activation='relu', padding=\"same\"))\n",
			"# 1stpool layer, divinding by 2 the dimension\n",
			"model10.add(layers.MaxPooling2D((2, 2)))\n",
			"model10.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"# 2ndconv layer, with 64 filters of size (3,3) \n",
			"model10.add(layers.Conv2D(64, (3, 3), activation='relu', padding=\"same\"))\n",
			"# 2nd pool layer, divinding by 2 the dimension\n",
			"model10.add(layers.MaxPooling2D((2, 2)))\n",
			"model10.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"# last conv layer, with 64 filters of size (3,3) \n",
			"model10.add(layers.Conv2D(128, (3, 3), activation='relu', padding=\"same\"))\n",
			"model10.add(layers.MaxPooling2D((2, 2)))\n",
			"model10.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"\n",
			"\n",
			"# flaten the images to prepare for the dense layers\n",
			"model10.add(layers.Flatten())\n",
			"# DROPOUT\n",
			"model10.add(layers.Dense(64, activation='relu'))\n",
			"model10.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"\n",
			"model10.add(layers.Dense(128, activation='relu'))\n",
			"model10.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"\n",
			"# fin9l dense softmax layer, with 2 classes so 2 dimension, to have probabilities at the end\n",
			"model10.add(layers.Dense(2, activation='softmax'))\n",
			"\n",
			"# model architecture\n",
			"model10.summary()\n",
			"\n",
			"train_pred_class10,test_pred_class10 = CompileAndTrainCNNModel(model10,images, labels,40,\"model10\")"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Interesting.... It seems to not have converted still, needs more epochs... but the specificity is stupid bad..."
			]
			},
			{
			"cell_type": "code",
			"execution_count": 118,
			"metadata": {
			"scrolled": true
			},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"_________________________________________________________________\n",
			"Layer (type) Output Shape Param # \n",
			"=================================================================\n",
			"zero_padding2d_45 (ZeroPaddi (None, 32, 32, 3) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_175 (Conv2D) (None, 32, 32, 32) 896 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_74 (MaxPooling (None, 16, 16, 32) 0 \n",
			"_________________________________________________________________\n",
			"dropout_26 (Dropout) (None, 16, 16, 32) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_176 (Conv2D) (None, 16, 16, 64) 18496 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_75 (MaxPooling (None, 8, 8, 64) 0 \n",
			"_________________________________________________________________\n",
			"dropout_27 (Dropout) (None, 8, 8, 64) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_177 (Conv2D) (None, 8, 8, 128) 73856 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_76 (MaxPooling (None, 4, 4, 128) 0 \n",
			"_________________________________________________________________\n",
			"dropout_28 (Dropout) (None, 4, 4, 128) 0 \n",
			"_________________________________________________________________\n",
			"flatten_44 (Flatten) (None, 2048) 0 \n",
			"_________________________________________________________________\n",
			"dense_94 (Dense) (None, 64) 131136 \n",
			"_________________________________________________________________\n",
			"dropout_29 (Dropout) (None, 64) 0 \n",
			"_________________________________________________________________\n",
			"dense_95 (Dense) (None, 128) 8320 \n",
			"_________________________________________________________________\n",
			"dropout_30 (Dropout) (None, 128) 0 \n",
			"_________________________________________________________________\n",
			"dense_96 (Dense) (None, 2) 258 \n",
			"=================================================================\n",
			"Total params: 232,962\n",
			"Trainable params: 232,962\n",
			"Non-trainable params: 0\n",
			"_________________________________________________________________\n",
			"Train on 3101 samples, validate on 1034 samples\n",
			"Epoch 1/100\n",
			"3101/3101 [==============================] - 12s 4ms/sample - loss: 0.6756 - acc: 0.6111 - val_loss: 0.6707 - val_acc: 0.6315\n",
			"Epoch 2/100\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6641 - acc: 0.6243 - val_loss: 0.6611 - val_acc: 0.6315\n",
			"Epoch 3/100\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6626 - acc: 0.6246 - val_loss: 0.6541 - val_acc: 0.6315\n",
			"Epoch 4/100\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6590 - acc: 0.6250 - val_loss: 0.6559 - val_acc: 0.6315\n",
			"Epoch 5/100\n",
			"3101/3101 [==============================] - 12s 4ms/sample - loss: 0.6594 - acc: 0.6246 - val_loss: 0.6566 - val_acc: 0.6315\n",
			"Epoch 6/100\n",
			"3101/3101 [==============================] - 13s 4ms/sample - loss: 0.6552 - acc: 0.6246 - val_loss: 0.6560 - val_acc: 0.6315\n",
			"Epoch 7/100\n",
			"3101/3101 [==============================] - 12s 4ms/sample - loss: 0.6539 - acc: 0.6237 - val_loss: 0.6440 - val_acc: 0.6315\n",
			"Epoch 8/100\n",
			"3101/3101 [==============================] - 12s 4ms/sample - loss: 0.6483 - acc: 0.6240 - val_loss: 0.6396 - val_acc: 0.6315\n",
			"Epoch 9/100\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6555 - acc: 0.6250 - val_loss: 0.6448 - val_acc: 0.6315\n",
			"Epoch 10/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.6495 - acc: 0.6240 - val_loss: 0.6396 - val_acc: 0.6315\n",
			"Epoch 11/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.6533 - acc: 0.6282 - val_loss: 0.6490 - val_acc: 0.6306\n",
			"Epoch 12/100\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6488 - acc: 0.6262 - val_loss: 0.6478 - val_acc: 0.6315\n",
			"Epoch 13/100\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6456 - acc: 0.6327 - val_loss: 0.6378 - val_acc: 0.6306\n",
			"Epoch 14/100\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6432 - acc: 0.6301 - val_loss: 0.6439 - val_acc: 0.6393\n",
			"Epoch 15/100\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6431 - acc: 0.6256 - val_loss: 0.6404 - val_acc: 0.6257\n",
			"Epoch 16/100\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6473 - acc: 0.6246 - val_loss: 0.6361 - val_acc: 0.6277\n",
			"Epoch 17/100\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6454 - acc: 0.6282 - val_loss: 0.6411 - val_acc: 0.6286\n",
			"Epoch 18/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6394 - acc: 0.6343 - val_loss: 0.6370 - val_acc: 0.6306\n",
			"Epoch 19/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6423 - acc: 0.6330 - val_loss: 0.6411 - val_acc: 0.6315\n",
			"Epoch 20/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.6404 - acc: 0.6311 - val_loss: 0.6332 - val_acc: 0.6344\n",
			"Epoch 21/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6420 - acc: 0.6314 - val_loss: 0.6372 - val_acc: 0.6364\n",
			"Epoch 22/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.6367 - acc: 0.6279 - val_loss: 0.6290 - val_acc: 0.6296\n",
			"Epoch 23/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6394 - acc: 0.6311 - val_loss: 0.6385 - val_acc: 0.6364\n",
			"Epoch 24/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6351 - acc: 0.6292 - val_loss: 0.6340 - val_acc: 0.6315\n",
			"Epoch 25/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6339 - acc: 0.6324 - val_loss: 0.6319 - val_acc: 0.6354\n",
			"Epoch 26/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6304 - acc: 0.6314 - val_loss: 0.6358 - val_acc: 0.6393\n",
			"Epoch 27/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6316 - acc: 0.6369 - val_loss: 0.6288 - val_acc: 0.6431\n",
			"Epoch 28/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6288 - acc: 0.6343 - val_loss: 0.6403 - val_acc: 0.6431\n",
			"Epoch 29/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.6292 - acc: 0.6375 - val_loss: 0.6346 - val_acc: 0.6364\n",
			"Epoch 30/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.6262 - acc: 0.6404 - val_loss: 0.6269 - val_acc: 0.6460\n",
			"Epoch 31/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6306 - acc: 0.6330 - val_loss: 0.6316 - val_acc: 0.6422\n",
			"Epoch 32/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6213 - acc: 0.6443 - val_loss: 0.6413 - val_acc: 0.6335\n",
			"Epoch 33/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6234 - acc: 0.6359 - val_loss: 0.6319 - val_acc: 0.6402\n",
			"Epoch 34/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6217 - acc: 0.6453 - val_loss: 0.6309 - val_acc: 0.6402\n",
			"Epoch 35/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.6202 - acc: 0.6453 - val_loss: 0.6335 - val_acc: 0.6373\n",
			"Epoch 36/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6203 - acc: 0.6466 - val_loss: 0.6292 - val_acc: 0.6344\n",
			"Epoch 37/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6157 - acc: 0.6430 - val_loss: 0.6218 - val_acc: 0.6364\n",
			"Epoch 38/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6225 - acc: 0.6421 - val_loss: 0.6247 - val_acc: 0.6412\n",
			"Epoch 39/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6192 - acc: 0.6388 - val_loss: 0.6251 - val_acc: 0.6277\n",
			"Epoch 40/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.6199 - acc: 0.6459 - val_loss: 0.6263 - val_acc: 0.6393\n",
			"Epoch 41/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6199 - acc: 0.6343 - val_loss: 0.6205 - val_acc: 0.6373\n",
			"Epoch 42/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6178 - acc: 0.6479 - val_loss: 0.6244 - val_acc: 0.6325\n",
			"Epoch 43/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6189 - acc: 0.6356 - val_loss: 0.6220 - val_acc: 0.6344\n",
			"Epoch 44/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6121 - acc: 0.6514 - val_loss: 0.6272 - val_acc: 0.6412\n",
			"Epoch 45/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6162 - acc: 0.6414 - val_loss: 0.6213 - val_acc: 0.6364\n",
			"Epoch 46/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.6098 - acc: 0.6530 - val_loss: 0.6212 - val_acc: 0.6431\n",
			"Epoch 47/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.6186 - acc: 0.6427 - val_loss: 0.6254 - val_acc: 0.6315\n",
			"Epoch 48/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6142 - acc: 0.6440 - val_loss: 0.6226 - val_acc: 0.6344\n",
			"Epoch 49/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6062 - acc: 0.6498 - val_loss: 0.6229 - val_acc: 0.6393\n",
			"Epoch 50/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6142 - acc: 0.6443 - val_loss: 0.6154 - val_acc: 0.6354\n",
			"Epoch 51/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6057 - acc: 0.6533 - val_loss: 0.6175 - val_acc: 0.6460\n",
			"Epoch 52/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.6054 - acc: 0.6530 - val_loss: 0.6188 - val_acc: 0.6422\n",
			"Epoch 53/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.6108 - acc: 0.6520 - val_loss: 0.6144 - val_acc: 0.6393\n",
			"Epoch 54/100\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6025 - acc: 0.6620 - val_loss: 0.6225 - val_acc: 0.6451\n",
			"Epoch 55/100\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6046 - acc: 0.6417 - val_loss: 0.6167 - val_acc: 0.6344\n",
			"Epoch 56/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.6100 - acc: 0.6524 - val_loss: 0.6186 - val_acc: 0.6383\n",
			"Epoch 57/100\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6089 - acc: 0.6475 - val_loss: 0.6219 - val_acc: 0.6431\n",
			"Epoch 58/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.6033 - acc: 0.6530 - val_loss: 0.6205 - val_acc: 0.6383\n",
			"Epoch 59/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.6017 - acc: 0.6530 - val_loss: 0.6138 - val_acc: 0.6393\n",
			"Epoch 60/100\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6024 - acc: 0.6543 - val_loss: 0.6225 - val_acc: 0.6412\n",
			"Epoch 61/100\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.5999 - acc: 0.6566 - val_loss: 0.6295 - val_acc: 0.6383\n",
			"Epoch 62/100\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6011 - acc: 0.6550 - val_loss: 0.6207 - val_acc: 0.6344\n",
			"Epoch 63/100\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.5990 - acc: 0.6437 - val_loss: 0.6204 - val_acc: 0.6412\n",
			"Epoch 64/100\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6022 - acc: 0.6585 - val_loss: 0.6202 - val_acc: 0.6441\n",
			"Epoch 65/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.5974 - acc: 0.6546 - val_loss: 0.6132 - val_acc: 0.6364\n",
			"Epoch 66/100\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.6011 - acc: 0.6533 - val_loss: 0.6200 - val_acc: 0.6431\n",
			"Epoch 67/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.6011 - acc: 0.6582 - val_loss: 0.6134 - val_acc: 0.6422\n",
			"Epoch 68/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.5898 - acc: 0.6637 - val_loss: 0.6152 - val_acc: 0.6422\n",
			"Epoch 69/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.5931 - acc: 0.6617 - val_loss: 0.6157 - val_acc: 0.6431\n",
			"Epoch 70/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.5970 - acc: 0.6588 - val_loss: 0.6191 - val_acc: 0.6451\n",
			"Epoch 71/100\n",
			"3101/3101 [==============================] - 11s 4ms/sample - loss: 0.5953 - acc: 0.6508 - val_loss: 0.6074 - val_acc: 0.6451\n",
			"Epoch 72/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.5938 - acc: 0.6550 - val_loss: 0.6190 - val_acc: 0.6402\n",
			"Epoch 73/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.5905 - acc: 0.6562 - val_loss: 0.6088 - val_acc: 0.6451\n",
			"Epoch 74/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.5853 - acc: 0.6579 - val_loss: 0.6076 - val_acc: 0.6422\n",
			"Epoch 75/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.6000 - acc: 0.6485 - val_loss: 0.6327 - val_acc: 0.6460\n",
			"Epoch 76/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5849 - acc: 0.6614 - val_loss: 0.6143 - val_acc: 0.6460\n",
			"Epoch 77/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5893 - acc: 0.6611 - val_loss: 0.6153 - val_acc: 0.6383\n",
			"Epoch 78/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5945 - acc: 0.6662 - val_loss: 0.6179 - val_acc: 0.6422\n",
			"Epoch 79/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5962 - acc: 0.6608 - val_loss: 0.6122 - val_acc: 0.6460\n",
			"Epoch 80/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5852 - acc: 0.6666 - val_loss: 0.6141 - val_acc: 0.6373\n",
			"Epoch 81/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5918 - acc: 0.6550 - val_loss: 0.6193 - val_acc: 0.6460\n",
			"Epoch 82/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.5897 - acc: 0.6575 - val_loss: 0.6159 - val_acc: 0.6441\n",
			"Epoch 83/100\n",
			"3101/3101 [==============================] - 11s 3ms/sample - loss: 0.5862 - acc: 0.6656 - val_loss: 0.6101 - val_acc: 0.6354\n",
			"Epoch 84/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5812 - acc: 0.6782 - val_loss: 0.6055 - val_acc: 0.6499\n",
			"Epoch 85/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5886 - acc: 0.6559 - val_loss: 0.6144 - val_acc: 0.6441\n",
			"Epoch 86/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5827 - acc: 0.6572 - val_loss: 0.6072 - val_acc: 0.6431\n",
			"Epoch 87/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5862 - acc: 0.6649 - val_loss: 0.6184 - val_acc: 0.6412\n",
			"Epoch 88/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5846 - acc: 0.6633 - val_loss: 0.6115 - val_acc: 0.6373\n",
			"Epoch 89/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5851 - acc: 0.6591 - val_loss: 0.6082 - val_acc: 0.6460\n",
			"Epoch 90/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5827 - acc: 0.6556 - val_loss: 0.6145 - val_acc: 0.6383\n",
			"Epoch 91/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5782 - acc: 0.6649 - val_loss: 0.6080 - val_acc: 0.6470\n",
			"Epoch 92/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5802 - acc: 0.6656 - val_loss: 0.6156 - val_acc: 0.6518\n",
			"Epoch 93/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5840 - acc: 0.6646 - val_loss: 0.6144 - val_acc: 0.6422\n",
			"Epoch 94/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5801 - acc: 0.6675 - val_loss: 0.6058 - val_acc: 0.6451\n",
			"Epoch 95/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5823 - acc: 0.6617 - val_loss: 0.6168 - val_acc: 0.6383\n",
			"Epoch 96/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5836 - acc: 0.6649 - val_loss: 0.6166 - val_acc: 0.6480\n",
			"Epoch 97/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5721 - acc: 0.6662 - val_loss: 0.6068 - val_acc: 0.6489\n",
			"Epoch 98/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5865 - acc: 0.6646 - val_loss: 0.6081 - val_acc: 0.6431\n",
			"Epoch 99/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5788 - acc: 0.6656 - val_loss: 0.6104 - val_acc: 0.6451\n",
			"Epoch 100/100\n",
			"3101/3101 [==============================] - 10s 3ms/sample - loss: 0.5827 - acc: 0.6704 - val_loss: 0.6157 - val_acc: 0.6451\n",
			"[[ 35 346]\n",
			" [ 21 632]]\n",
			"Train/Test recall: 0.9768 / 0.9678\n",
			"Train/Test accuracy: 0.6711 / 0.6451\n",
			"Test specificity: 0.0919\n"
			]
			},
			{
			"data": {
			"image/png": 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9HyIiIoXV34ta/1XOZ2vObtCgoCB27dpl+9q3b59tNeHatWvx8fGhVq1abNu2jaioKHbt2kVUVBTz58/nP//5D59//rktQfJ3ZrP5jhIWOWPzktfcpFu3bsyYMYOzZ8/y448/kpaWZrcbxGw207BhQ0aOHJnna+YsIqlQoQIbNmzg4MGD7Ny5k6ioKBYvXszSpUtZsmQJjz322B3di4iISGGwZcsWzGYzp06dok2bNrmuJyYmEhERYTvW8UbPC+70mcL/8iwC8p4/5PUs4sEHH6RmzZqEh4fz9NNPEx4eblsg8dc4Ro0add2apNWqVQOyEyPBwcFERESwZ88e9u/fz969e1m1ahWhoaG4urre0b2IFBXamSFShAwYMIA2bdoQGRnJsmXL7K5169aNU6dOsXPnzuuOX716NWlpabYCVZC9BfTkyZPXTYRcuXKFL7/8kqNHj+aZyIDsc7ABTp8+nevaxIkTCQ0NBbInGJmZmble/1a5uLjQoUMHdu3axa+//sqJEydsKyEge+UmZO/qaNq0qd2X0WjEYDDg6upKQkICX3/9NaVKlaJ///58/PHHHDhwgPbt2xMVFcXx48dvOSYREZHCLufzMzo6Ote1nFpSFSpUIDMzkx9++IHk5GRbLap9+/bx6quvcv78eTZv3ozZbObo0aOcP3+eNm3aMG3aNPbs2cPcuXNJSkqyzQnyUqlSpTzPi96zZw/jx4/nypUrtocV/8t8olOnTjg5ObFz507Cw8OpUqWK3YMHX19fUlNTc80lHnnkEZKSkvDw8ADg+PHjnDhxgqCgICZPnsy2bdtYtWoVAJ9++uktxyMiIlIYbdy4EYPBwMyZM/nggw/svl588UUg+6ipGz0veOedd1i8ePEt9cnLrY7L61mEyWTi6tWrt3q7dO3alUOHDhEbG8u+ffvyfBbh6emZa/7g5eWF2WzG3d2d1NRUDh06hMFgoFevXrz//vscOHCAgQMHcuzYMfbu3XvL8YgUVUpmiBQxU6dOpUSJErz33nt2v/APHTqUypUrM3nyZH7++edc4/bt28fcuXOpV68ePXr0sBvn5eXF5MmTuXDhgt2YjIwMXn31VbKyshg+fPh1YwoMDMTHx4e1a9faTRC+++471q5dazsHskyZMhw7dsxuBeiWLVtu6/67du3K1atXeffdd3F3d7c7m7Np06a4ubnx73//21ZXA+DixYsMHz6c2bNnYzAY2LdvH88++yyRkZG2Pp6enjz00ENA3isxREREiqqyZcsSGBjIl19+aTcXyMzMZOnSpbi6utKsWTMSEhJ46qmnWLRoka2Pk5MTtWvXtn1vNpsZOHAg06dPt3uPunXr2vpcT4sWLbhy5Qo7duywa1+2bBm7d++mVKlSlC1bFoBjx47ZrqekpLBnz55bvt9y5crRpEkTduzYwVdffWX3MALg8ccf59ixY+zevduufeHChYwaNYoTJ04A2asvX331VbtVnQEBAbi4uNzxClEREZHC4NSpU/z000889thjdO/enbZt29p9DRs2jLJly7Jv3z4AatWqxebNm0lJSbG9RmxsLMuXL+fKlSuUL1/+pn3ycqvjypQpw8mTJ0lPT7f1iYyMvK2jnbp06YLFYuGtt94iKyvLbv4QGBhI2bJl+fTTT0lNTbW1p6SkMHr0aCZOnIjRaOTEiRP069ePsLAwWx9XV1cCAgIAPYsQAR0zJVLklClThnHjxvHaa68xZcoUlixZAoCHhweffPIJQ4cOpU+fPnTt2pV69ephMpk4ePAg27dvJyAggPnz59t9QJYuXZp58+YxcuRIOnfuTI8ePXjwwQe5fPky69evJzY2lkGDBtGhQ4frxuTq6sqECRMYP348Tz/9NN26dSM1NZXly5dTvXp12xnTXbp0YcmSJYwcOZJWrVpx9OhRwsPD86yPcT0NGjTA19eXXbt20blzZ1uxUcjekTF27FhmzJjBU089Rbdu3TCZTKxatYqMjAzGjx8PQOvWrfH39+df//oXR48e5YEHHiA6OpqVK1fSpEkTatSocVv/n4iIiDi6uXPn2n1m5ujYsaNtZ8Gzzz5Lr169ePrppylWrJhtZ+bkyZMpXrw4xYsXp2vXrqxatYpr165Rv359EhISWLFiBWXKlKFjx464uroyYMAAFi5cyIgRIwgODiY9PZ3Vq1fj4eFBz549rxtj3759WbNmDWPGjKFfv374+/uze/du9u3bx/Tp0zEajbRt25Zp06YxdepUzp49i6urK1988QWenp639efRtWtXJk6cCGB3xBTAsGHD2L59OyNHjqRv3748+OCDfPvtt2zYsIEWLVrQokULIPvIysmTJ9vmSVarlQ0bNpCRkcEzzzxzW/GIiIgUJjmFv3v16pXndRcXF3r27MlHH33Ehg0bmDhxIkOGDKFnz5707t0bJycnVqxYQfHixW1Fum+lT15uZVyXLl148803GTJkCN26deP06dN88cUXth0Vt6JixYo0atSIXbt2Ua9ePbsi4S4uLrz22muMHj2akJAQevXqhZubG6GhoZw7d47Zs2fj7OxM3bp1efTRR5k7dy7nz5+nZs2anD9/nhUrVlCtWjWCgoJuOR6RospgvdEhuCLikCZMmMC6devYuXNnnrUfrFYr/fr149tvv2XmzJl0797ddi0lJYXVq1ezefNmTp8+jdFopFq1anTr1o2ePXte96iokydPsnTpUg4ePMiFCxcwGo3Url2bAQMG0LZt21uKe+fOnSxatIhjx45RvHhxgoODefnll22FxtPT05kzZw6bN28mNTWVunXrMmnSJMaNG0dgYCBvv/02ADVr1qRHjx62n/9u7ty5fPTRRyxcuJDHH3881/Xw8HCWLl3K8ePHcXd355FHHmHEiBE0bNjQ1ufcuXPMnz+fr7/+mitXrlC2bFnat2/PyJEj76hguYiIiCPKmVNcz8SJExk0aBAAR48eZf78+Rw6dAiLxUKtWrUYPHiw3TwgPT2dxYsXs3nzZs6fP4+HhwdBQUGMGTPGVnzTYrGwfPly1qxZw5kzZzAajTRo0ICXXnqJwMDAG8abkJDAe++9R0REBMnJyVSvXp3nn3+ejh072vocPHiQOXPm8Msvv1CqVCn69OlDtWrVGDNmjG3u9P7777NgwYLrzqVSUlJo2rQpNWrUYO3atbmuX7lyhfnz5xMZGUliYiKVKlWiU6dODB061HbMFMD69etZvnw5p0+fxmKxEBgYyAsvvECzZs1ueJ8iIiKFWfv27YmLi2Pv3r24u7vn2efs2bO0bduWqlWrEh4ezrfffsv8+fM5cuQIbm5uNGrUiFdeecUuKXArffJys3EWi4UPP/yQsLAw4uLiqFWrFuPGjWPJkiWkpaXZjod8/PHH8fX1ve5xkV988QWvvfYakydPZsCAAbmuHzhwgIULF/Ljjz/i5OTEgw8+yLBhw2jdurWtT0JCAgsWLGDXrl1cunSJEiVK0KpVK0aNGmXbgSpyP1MyQ0REREREREREREREHJoOaxUREREREREREREREYemZIaIiIg4tE2bNtG5c2fq1KlDx44dWb9+/Q37WywWFi5cSJs2bahTpw5du3Zl8+bNdn1SU1OZPn06rVu3pkGDBgwYMIAjR47czdsQERERERERkf+BkhkiIiLisMLDwxk3bhzNmjXjgw8+4LHHHmP8+PFs3br1umOmT5/Ohx9+SP/+/Vm0aBF169bl5ZdfZs+ePbY+r7/+OqGhoQwZMoT58+fj6urKs88+S2xs7L24LRERERERERG5TaqZISIiIg7riSeeIDAwkLlz59raRo8ezfHjxwkPD8/VPyYmhvbt2zN16lR69+5ta+/fvz+1atVi8uTJpKen06BBA4YPH87IkSOB7J0aTZs25fnnn7e1iYiIiIiIiIjjcC7oAApaQEAAFosFLy+vgg5FRETkrkhJScHJyYmff/65oEO5LbGxscTExDB27Fi79vbt2xMeHk5sbCxVqlSxuxYREYG7uzvdu3e3a1+xYoXt+6ysrFyf/Z6enri5uZGQkHDbcWouISIiRV1hnUsUJppPiIhIUZcf84n7/pgpi8WCNqeIiEhRZrVasVgsBR3GbYuOjgbA39/frt3Pzw+AkydP5hpz/Phx/P392b9/P926dSMgIIB27dqxZcsWWx9vb2969OjBsmXLOHLkCImJicyZM4fU1FQ6dep023FqLiEiIkVdYZ1LFCaaT4iISFGXH/OJ+35nRs6qh0OHDhVwJCIiInfHo48+WtAh3JHk5GSAXCsUixUrBmSv6vi7+Ph4zp8/z6RJkxg1ahSVK1cmNDSUMWPG4OPjQ5MmTQAYM2YMQ4cOtR1FZTAYmDZtGg0aNLjtODWXEBGRoq6wziVybNq0iYULFxIbG4uvry/Dhg3LtYvzrywWC4sWLSIsLIzLly/j5+fHCy+8QOfOnW19UlNTmTdvHjt27CAxMZFHHnmEV155hTp16txRjJpPiIhIUZcf84n7PpkhIiIijilndaLBYMiz3ckp9wbTrKws4uPj+eijj2jdujUAQUFBREdHs2DBApo0aUJcXBx9+vTB1dWVOXPmULp0abZt28aUKVPw9PS8o90ZIiIi4pjCw8MZN24cAwcOJDg4mIiICMaPH4+7uzsdOnTIc8z06dNZvXo1Y8eOpVatWmzevJmXX34ZLy8vWrZsCcDrr79OZGQk48aNw8/Pj6VLl/Lss8/y5Zdf5joGU0RERPKHkhkiIiLikLy9vYHcOzBSU1Ptrv9VsWLFMBqNNGvWzNZmMBho2rQpYWFhAISGhnLhwgV27Nhhe9gQFBREcnIyb775Jh06dMgzUSIiIiKFz7vvvkvHjh2ZNGkSAMHBwSQmJjJv3rw8kxkxMTGsXLmSqVOn2nZwBgUFcerUKaKiomjZsiXp6emEh4czfPhw+vXrB0D9+vVp2rQpGzZsYOTIkffuBkVERO4j+k1dREREHFJOrYyYmBi79tOnT9td/ys/Pz8sFgsmk8muPSsry7bD49y5c5QtWzbXqslHH32U+Ph44uPj8+0eREREpODExsYSExNDu3bt7Nrbt29PdHQ0sbGxucZERETg7u6e6xiqFStWMHnyZCB7XvH3Yt2enp64ubmRkJBwF+5EREREQMkMERERcVB+fn5UrlyZrVu32rVv376dqlWrUqlSpVxjgoODsVqthIeH29pMJhNRUVE0bNgQyE6CXLlyhVOnTtmN/f777/Hy8qJEiRL5fzMiIiJyz0VHRwO5F0D4+fkBcPLkyVxjjh8/jr+/P/v376dbt24EBATQrl07tmzZYuvj7e1Njx49WLZsGUeOHCExMZE5c+aQmpqq4ypFRETuIh0zJSIiIg5rxIgRTJw4kRIlStCqVSsiIyMJDw9n7ty5QHbB75iYGGrUqIGXlxdBQUG0bNmSadOmkZaWRtWqVVm1ahVnz55lzpw5APTq1YtPP/2UoUOH8uKLL1K6dGkiIyNZv34948aNw8XFpSBvWURERPJJcnIygN0OCsg+lhJyH2UJ2XOL8+fPM2nSJEaNGkXlypUJDQ1lzJgx+Pj40KRJEwDGjBnD0KFDbUdRGQwGpk2bRoMGDe7mLYmIiNzXlMwQERERhxUSEkJmZiZLliwhNDSUKlWqMHPmTNuqx927dzNx4kSWL19O48aNAZg/fz7z5s1j8eLFJCYmEhAQwJIlSwgMDASyV1N+9tlnvPPOO0ybNo3MzEyqVavGu+++S+fOne/avVgsFhITE0lJScFisdy197lfOTk52XbWqOaJiIgAWK1WANtRk39vz+vzIisri/j4eD766CNat24NZNfMiI6OZsGCBTRp0oS4uDj69OmDq6src+bMoXTp0mzbto0pU6bg6el5V3dnXLt2jaSkJDIyMmz3IflH8wkREcemZIaIiIg4tL59+9K3b988r4WEhBASEmLX5u7uzvjx4xk/fvx1X7N8+fLMnj07X+O8mXPnzpGcnIyrqyvOzpqC5bfMzEwuXLhAWloavr6+BR2OiIg4AG9vbyD3DozU1FS7639VrFgxjEYjzZo1s7UZDAaaNm1KWFgYAKGhoVy4cIEdO3bYanAFBQWRnJzMm2++SYcOHe7Kg/D4+HguXryIwWDAzc1ND9vvAs1CIfJPAAAgAElEQVQnREQcm8P8Jv3LL7/Qq1cvdu7cSYUKFa7bLzU1ldmzZ7N9+3bS0tJ49NFH+de//kXVqlXvXbAiIiIityE1NZXk5GTKlClDmTJlcq0Qlf+d1Wrl8uXLxMXFUapUKTw9PQs6JBERKWA5tTJiYmKoWbOmrf306dN21//Kz88Pi8WCyWTC1dXV1p6VlWX7/D537hxly5a1JTJyPProo2zatIn4+HjKlCmTr/dy7do1Ll68iLe3NxUrVsRoNObr60s2zSdERBybQ6Txo6OjGTZsGCaT6aZ9x4wZw9atWxk3bhwzZ87k4sWLDBw40HYWpoiIiIijSUpKwsnJidKlSyuRcZcYDAbKlCmDk5MTiYmJBR2OiIg4AD8/PypXrszWrVvt2rdv307VqlWpVKlSrjHBwcFYrVbCw8NtbSaTiaioKBo2bAhkJ0GuXLnCqVOn7MZ+//33tiOK8ltSUhIGg0GJjLtM8wkREcdWoDszTCYTq1evZs6cObdUbPPQoUPs2bOHjz/+mBYtWgDZKx/atGnDZ599xtChQ+92yCIiIiK3zWQy4eLiouMg7jInJydcXFxuaYGMiIjcH0aMGMHEiRMpUaIErVq1IjIykvDwcObOnQtkH90UExNDjRo18PLyIigoiJYtWzJt2jTS0tKoWrUqq1at4uzZs8yZMweAXr168emnnzJ06FBefPFFSpcuTWRkJOvXr2fcuHG39HzjdmVkZODm5qZExj2g+YSIiOMq0N+ov/32W2bPns0//vEPxo0bd9P++/bto1ixYnZnV/r4+NCoUSO++uqruxmqiIiIyB2zWCx6+HCPGI1GFVgXERGbkJAQ/u///o+9e/cyYsQIvvnmG2bOnGkr0r17926eeuopjh49ahszf/58+vbty+LFixkxYgRXr15lyZIlBAYGAtm1Nj777DPq1KnDtGnTGDFiBIcPH+bdd9/l+eefvyv3YbVatSjiHtJ8QkTEMRXozozq1asTERFB6dKlWbt27U37R0dH4+fnl+thwAMPPGC3BVRERKSwsFqtnI9LxWy22trcXIyU89H5vPczs8WCUQ8sRERE8kXfvn3p27dvntdCQkIICQmxa3N3d2f8+PGMHz/+uq9Zvnx5Zs+ena9xioiI40jPMGE0OuHirN/LHEmBJjNutyBWSkoKXl5eudqLFStGSkpKfoUlIiJy12VkmTkRc5UP1xwh9mLuuk/PdQkgpPWDBRCZFLSryelcSUinvI8HxYu5FXQ4t8RqtaoWiIiIiNwxzSVExJGkXMti6PQdlPR24/1xj2N00r9PjqJQpZasVut1r2m7pYiIOLoLcal8dfgMXx0+Q68Jm5j44T5bIsMJs62fwQDubgW63kAKUGZW9pEGaemF45zmXbt23XDl6q1au3YtNWvW5MKFC/kQlYiIiBQWmkuIiKM5fT6J5LQsYi+mkJKWWdDhyF8UqiclXl5enDlzJld7ampqnjs2RERECtp3xy5x5lIymSYLyzb/nEcPK5U84vAvHk+//oPw8vbGxdmIl0f+F46UwiFnG3OWqXCc07xs2TLMZvPNO95Eq1atWL16NT4+PvkQlYiIiBQWmkuIiKNJSv0zgZGR+b//+yT5p1AlM/z9/Tlw4ECu7YenT5/G39+/ACMTEZH7XXqGiUyThcwsMzsPxXAxLo0d38Rct39JbzcqlHQm0Oc8p06eIeMaHD50gG7dut3DqMURORuz5zgmc+FIZuQXHx8fPXwQERGRO6a5hIjkl+S/7MbIyFIyw5EUqrOZmjdvTlJSEvv377e1xcfHc+jQIZo2bVqAkYmIyP3k2Ol4FoR+z7zPDzPv88P0mbSJ3pM20+/1cJ57czsrwo/lSmRUrVicqhWL076JH1/O7sbUZ2tSwfwDp05GA1C/fn06duxYELcjDsbFmD09M5mtWCzXP2LTEQwYMIADBw7wzTffULNmTQ4ePEjNmjVZvXo1rVq1onnz5hw6dAiA1atXExISQr169ahTpw49evRg27Ztttf6+9EQEyZMYPDgwYSGhtKuXTsCAwN58skniYqKKpB7FRERkfynuYSIOKLkv+zMSM8sHMf/3i8cemdGfHw8MTEx1KhRAy8vLxo1asRjjz3G2LFjGTduHCVLluT999/H29ubp59+uqDDFRGRImpjVDTfHrto+/nbY5duaVzdB8tQrpQnQ54MxNM9+9goi8XCrl27bL9Eubq60qVLF2rXrp3/gYvDM5ktxCWm27eZzMT/0ebhasTFxXjX4yhdwh1n4+2vcZkyZQoTJkzAbDYzZcoU4uLiAJg7dy5Tp04lNTWVOnXqsHz5ct5++21eeukl6tevT2JiIh9//DEvv/wy9erVo3z58nm+/g8//MD58+cZNWoUXl5ezJs3j5deeomvvvoKb2/v/+meRUREioq85hMF4U7mE5pLiIgjstuZoWOmHIpDJzN2797NxIkTWb58OY0bNwZgwYIFvP3228yaNQuLxULDhg157733KFGiRAFHKyIiRdEHYT+w9cCpPK85Gw0E1/MFslfRB9fzpWKZYhidDFQu52V3JCJAVlYWK1asICYme9dGpUqV6Nmzp7bD36dMZgvDZ0ZyPi61oEOhYulifDj+8dt+AJGz4MRsNlOvXj0OHjwIQL9+/WjXrp2t35kzZxgyZAgvvPCCrc3X15eQkBC+++676+5KSk5OZt26dVSpUgUAT09P+vfvz8GDB2nbtu3t3qaIiEiRU9jnE5pLiIgjSk7Lsn2frmSGQ3GYZEZISAghISE3bStRogQzZsxgxowZ9zI8ERG5D8UlXrNLZLSsX5nSJdwB8CnhTsegqrjexqp5FxcXSpYsSUxMDE2aNKFt27YYjXd/1b3IvfbQQw/Z/Txp0iQAkpKSiI6O5vTp07aHFVlZWbnG5yhbtqzt4QNAhQoVALh27Vp+hywiIiIORHMJESlI2pnhuBwmmSEiInKvHT5+iXdWHCI1/TpnYFr/rFfwYp96tGvsd9vvYTabcXJysu3S6Ny5M3Xq1KF69ep3FLMUHc5GJz4c/3iex0JciEshPcNCCW9XSnm73/VY7vSYqeu+XunSdj/HxMTw+uuvc+DAAVxcXKhWrRq1atUCwGq9fl0QDw8Pu59z/h5ZLPdXcXQREZHrudF84l7Lz/mE5hIiUpCSUv9aAFw1MxyJkhkiInJfsVqt/PeXi+z57gxfHT57S2OKebjQor7vbb9XXFwcYWFhNG7cmHr16gHZNTKUyJAczkYnyvt45r5gtZKUloW3p0ve1wsRi8XC0KFDcXNzIywsjIcffhhnZ2d+++03NmzYUNDhiYiIFHrXnU8UEZpLiMi9lpL21wLg2pnhSJTMEBGRIi8908SvMVc5fPwyYZEncl0vU8KdUX3rX3d81YolcHe9vY/MI0eOsHnzZjIzM9m6dSu1atXC3f3ur7CXosHZOXtVo8nk+KsGjUYjZvP1J/hXr17l5MmTvP7663aF7r/66ivgxqspRUREpOjTXEJEHI2OmXJcSmaIiEiR9J9NRzl8/DIA0ecS8+zj7elK83qV6N6iOpXKeuXL+2ZmZhIeHs7333+f/R7e3oSEhCiRIbfF5Y9kRpbZ8ZMZ3t7eHDp0iAMHDpCSkpLreunSpfH19WX58uWUK1cOLy8voqKiWL58OQBpaWn3OmQRERFxIJpLiIgjsVqtJKWqALijUjJDREQKtfikdKYtOUhc4p9F/JJSMzGZr79Cq1mdSgwLqZ3vtQguXrxIaGgocXFxQHbhwieffBJPz6K77V/ujpzzpk1mKxarFac/znd2RM899xw//PADzz//PLNmzcqzz4cffshbb73Fq6++iqurKzVq1GDhwoVMnz6db7/9lmeeeeYeRy0iIiKOQnMJEXEk6ZlmTH9ZVJaRqZoZjsRgvc/34z366KMAHDp0qIAjERGROxHxTQzzVh++7vWnnngILw9Xyvt40iSwgq3oX377/vvv2bRpk63g9xNPPEHjxo3v2vvdDn3W3V238ud7+vRpAPz8bq2IfGaWidMXslcm+lXwxtXF+D9Gef+43T9rERG5Oc0l7r6b/Rnr8+3e0p+3yP3r0tU0Bk/bYfu5SzN/hoXUKcCIio78mE9oZ4aIiDg8q9XK2cspmMxWLl1NY8+3Z2w1Bc5dzn7gW8LLlSFP1rYbV923BFXKe9+TGD09PTGbzZQqVYpevXpRqVKle/K+UvSYUxOxJl2hmMGLVKsbJrNFyQwREREREZF7IDk10+5nHTPlWJTMEBERh5WeaWLVtuOs2/3bTfuW8nanVYPK9yCqP1mtVtvOi4ceeoiQkBAeeugh3Nzc7mkcUrRYsjIAK55OmaSa3cgqBEXARUREREREioK/Fv8GyMhSMsORKJkhIiIOa+q/D/Lj71fyvOZsNNDyj+SFk8FAm0YP3LO4rFYr+/btIzY2lr59+9oSGrVr177JSJGbMzi7AOBiyE5imApBEXAREREREZGiIPkvxb8he5GlOA4lM0RExOGcPJfI5I/2k/SX7Z2PP1qFfh1q4e7qjIuzEx5uBfMRlpKSwrp164iOjgbg8OHDNGjQoEBikaIpJ5lhxARYtTNDRERERETkHkm+9redGTpmyqEomSEiIg7FYrHmSmTMGhnMw/4+BRhVtt9//51169aRmpoKQMOGDbUbQ/Kdweia/b9YMWLRzgwREREREZF75O81M5TMcCxKZoiIiMNIzzBx9nKKXSJj+j+bUatqqQKMCsxmM7t372bv3r0AuLm50bVrVx555JECjUuKJoOzM2AArLgYzJi0M0NEREREROSeSEr7ewFwHTPlSJTMEBERh5BlMjPs7Z3EJ6Xb2t4e0ZxHqpUuwKggKSmJsLAwYmNjAfD19aVnz56UKlWwCRYpugwGJzA6gzkLZyxkmK12xeZFRERERETk7si1M0MFwB2KkhkiIlKgTGYLc1d9x39/uci1jD9XPJQp6UHVisULMLJsLi4uJCUlAdCsWTNat26N0Wgs4KikqDMYXbCas3AxmLFas/+euDjrvzsREREREZG7KTktuwB4KW83riZnkK5jphyKkhkiIlKgTsQk8NX3Z+3aPp7UlrIlPTAanQooqj95eHjQq1cv0tPTqVGjRkGHI/cJg7ML1kxwJnvinGVSMkNERERERORuS/7jmKkyJT24mpyhmhkORskMEREpMIkpGby6IMr28+BugTxctRQVShcrsJiuXLnCpk2b6N69OyVLlgSgcuXKBRaP3J8MztlFwF0M2RNnRy8CfjeOwdLRWiIiIvcPzSVExFHkHDNVpqQHJ2ITyMg06d8TB1LwS15FRKRIMZstnDyXSPTZvL9+OHGZmcv/y5yV3zJ0RoRtnG9ZL55sUY2afj4FFvv333/P4sWLOX36NGvXrsVqtRZYLHJ/Mzi7AGA0WDBgJcuBi4Dv2rWL8ePH5+trHj58mGHDhuXra4qIiIhj0lxCRBxJzs6MsqU8ALBYcejfx+432pkhIiL5JuVaFk9P3nJHY98d3aLAVjpkZGSwZcsWjhw5AkDx4sVp27atVl5IgTEYs5MZBqw4Y3bonRnLli3DbM7frddhYWH89ttv+fqaIiIi4pg0lxARR2GxWEm5ll0zo2xJD1t7RpYZVxcd++sIlMwQEZF8cf5Kqt1Oi1vxxGMPYDAYaF63Ep7uLncpshs7f/48YWFhxMfHA1CzZk2efPJJPDw8bjJS5O4xGJ0BA2DF2WDBZNIuIRERERERkbspNT2LnAMaypb0tLWnZ5jx9rzOILmnlMwQEZHbYrVa+evpS0d+u8yvMQl8Gv6LXb9FE9pQ3Mstz9cwOhnwcCvYjyCr1co333zDjh07MJvNGI1GnnjiCR577DHtyJACZzAYMDi7YjVl4Gwwk+6gOzMGDBjAN998A2QnApcvX85DDz3EnDlz2LlzJ6mpqTzyyCOMGzeOhg0b2sbt27ePefPmceLECZydnWnUqBEvv/wy1atXZ8KECaxbt872mjNmzCAkJKRA7k9ERETuLs0lRMSR5NTLAChT0t32fUaWqSDCkTwomSEiIrfs/JVUJnywl/ik9Ov2Kentxif/esLht2AaDAYuXbqE2WzGx8eHXr16UbFixYIOS+4zVrMJU3J8ntfMqUlYMlMxWlIxWYuR6X7triXanL19/tgNcnumTJnChAkTMJvNTJkyhRo1atCvXz/i4uIYO3YsZcuW5fPPP2fQoEGsXLmSOnXqEBsby/Dhw+nZsydjx44lMTGRuXPnMmzYMHbs2MHw4cNJTEzkxx9/ZMGCBTzwwAN34Y5FRESKjhvNJ+6lO5lPaC4hIo4kKe2vyYw/T2tIz8zfo/DkzimZISIiuVitVr7+6Ty7vzuDi/HPpMSew2euO8a/UnEeeqAUw3vWxcmpcOxs6NChA56enjRv3hw3t7x3kYjcLVazidhFozBdvXDTvk7A9f/2/e+cS1WgyrB5t/0AokaNGnh5eWE2m6lXrx5ffPEFx48fJzQ0lNq1awPQokULevXqxdy5c1m6dClHjhwhPT2dYcOGUb58eQAqVqxoW335wAMP4OPjg6urK/Xq1cv3exURESlKbmc+cbfdyXxCcwkRcSQpadn1MlycnSjxl5MmMpTMcBhKZoiIiM03Ry+waW80h3+9fNO+M4Y3s31ftVIJvDwKpubFrbJYLOzdu5dixYrZtqi7uLjQpk2bAo5MpOg4cOAA5cuX5+GHH8Zk+nMrduvWrVm0aBGZmZnUrVsXNzc3evXqRYcOHWjRogWNGzemTp06BRi5iIiIOALNJUSkICX9ccyUt6crzkYnnI0GTGarkhkORMkMEZH72JlLyRw7dZWNe6PJzDJz5lJKrj4lvd14LKCC7WcnJwNtHq1Crao+9zLU/0lycjLr1q3j5MmTGI1GqlSpQrly5Qo6LLnPGYzOVBk277rHQliy0m2rLC+YS+JTohhenncnaXinx0z9XUJCAhcuXOCRRx7J8/rVq1epXLkyK1asYPHixYSFhbF8+XKKFy/OM888w+jRo1WzRkRE8t2mTZtYuHAhsbGx+Pr6MmzYMLp3737d/haLhUWLFhEWFsbly5fx8/PjhRdeoHPnzgC8//77LFiw4LrjIyMj8fX1zff7yMvN5hP3Un7MJzSXEJGClPzHMVPFi7kC4OZixGQ2kZ6pmhmOQskMEZH71HfHLzFl8YE8r/lXKk5wPV/aNfaz21pZGP3222+sW7eOtLQ0ABo0aICPT+FJxEjRZjA641Iy78Sa1WwGU/Zk2tlcEquXFy7F3fPs6yi8vb2pXr06M2fOzPN6qVKlAKhTpw4LFiwgMzOTb7/9ltWrV/PRRx8REBBA+/bt72XIIiJSxIWHhzNu3DgGDhxIcHAwERERjB8/Hnd3dzp06JDnmOnTp7N69WrGjh1LrVq12Lx5My+//DJeXl60bNmS3r17ExwcbDcmISGBUaNG0bhx43teh+1G84nCRnMJESlIOQXAcxaRubk6k5puIiNLOzMchZIZIiL3EavVyvaDp/n5ZDyRh2JzXX+2cwC+ZYvx2CMVMRaSuhfXYzabiYyMZP/+/QC4u7vTrVs3Hn744QKOTOQWOTmBwQhWM86YSUs3Ucrb6nCrDY1GI2Zz9uS+UaNGfPXVV5QrV852hjXAe++9x7lz55g5cyaffvopS5cuZevWrbi6uhIUFERgYCDh4eGcP3/e9poiIiL54d1336Vjx45MmjQJgODgYBITE5k3b16eyYyYmBhWrlzJ1KlT6d27NwBBQUGcOnWKqKgoWrZsSYUKFahQoYLduBEjRlCyZElmz56Nk5PT3b+xIkRzCRFxFDk7M7w9/9iZ4Zr9b4kKgDsOJTNERO4TVxKu8friA8ReTLZrD67nyyv9GzrcA9L/xdWrV1mzZg1nz54FoEqVKoSEhFCyZMkCjkzk1hkMBgzOLlizzLgYzCRmmLgQl0aF0p4O9ffV29ubQ4cOceDAAdq2bcuKFSt47rnnbEU5d+/ezdKlSxk5ciQGg4EmTZowa9YsRowYQf/+/TEajXz++ee4ubnRunVr22teuXKFPXv28PDDD+tYOBERuSOxsbHExMQwduxYu/b27dsTHh5ObGwsVapUsbsWERGBu7t7rmOoVqxYcd332b17NxEREcybN4/ixYvn3w3cJzSXEBFHkfxHAfCcY6bc/0hm3I81MywWK7M+PUTqtSz+b2gQTg6y4FXLBUREirjElAxGvhPJc29ut0tkPBZQgcHdHuHVAY861IPR/HD16lVbIqN58+YMGjRIiQwplAzO2dubi/1RKiPlWhYX4tKwWK0FGJW95557DhcXF55//nkOHz7MypUrqVu3Lm+//TZDhw4lKiqK1157jRdffBGABx98kEWLFpGSksLYsWMZOXIkCQkJLFmyBD8/PwCeeuopqlSpwogRI/jyyy8L8vZERKQQi46OBsDf39+uPefz5uTJk7nGHD9+HH9/f/bv30+3bt0ICAigXbt2bNmyJc/3sFqtzJo1i8cee+y6x1bJjWkuISKOIjnVfmeGu2v2PoCM+7BmRszFZPYdOcf3Jy7bCqM7Au3MEBEp4r7+6QKnL9jvxnh9cGMaBVS4zojCr1q1ajzxxBNUqFCBatWqFXQ4InfMYMzOYrg4WShdwp24xHRSrmVBXCrlSxfDyQESkXXr1mXXrl12bTNmzLjhmKZNm9K0adPrXn/ggQfYvHlzvsQnIiL3r+Tk7Dmwl5eXXXuxYsUASElJyTUmPj6e8+fPM2nSJEaNGkXlypUJDQ1lzJgx+Pj40KRJE7v+kZGR/P7777z22mt36S6KPs0lRMRRJNmOmfqjZobL/XvMVPTZRCD7z6KEl2sBR/MnJTNERIooi8WK1WolI+vPFQTvvBRMLb+iV/z68uXLHDx4kE6dOtnOKL7RLzcihYXBOXvSaDVlUqq0G8AfCQ0TzgnXKFvKsyDDExERcWjWP3Yy/n0Xck57XrUtsrKyiI+P56OPPrIdWRQUFER0dDQLFizIlcxYuXIlAQEBBAUF3Y1bEBGReyjlOjUz7scC4DnJjGq+JRzqNA8lM0REiqD//nyBWZ8esls9UKW8d5FLZFitVg4fPkx4eDgmkwlvb29atmxZ0GGJ5JucY6awWsBixqe4OxaLlavJGSSlZuJTwh2jioyKiIjkydvbG8i9AyM1NdXu+l8VK1YMo9FIs2bNbG0Gg4GmTZsSFhZm1zchIYGDBw/yyiuv5HfoIiJSAGwFwIv9rQB4xv13zNSfyQzHOrJbyQwRkSLCYrFy+kISpy8kM2flt7mu+1XI/ctaYZaRkcGmTZv46aefAChRooSOlJIiJ+eYKQCrKQuD0ZlSxd1ISMnAYoWUtCxKeLkVYIQiIiKOK6dWRkxMDDVr1rS1nz592u76X/n5+WGxWDCZTLi6/nmsRlZWVq6VqVFRUZhMJjp27Hg3whcRkXsoy2ThWkb2gtBcNTPus50ZVquV6HN/JDMqFS/gaOxpKZ+ISBFwNSmdV9+P4qU5u+0SGVXKe/H2iOa881Iw4/o1LMAI89e5c+dYtGiRLZHx8MMP88ILL1ClSpUCjkzuhk2bNtG5c2fq1KlDx44dWb9+/Q37WywWFi5cSJs2bahTpw5du3bN88zkzz//nI4dO1K7dm3at2/P8uXL79Yt3DGDkxM4ZU+greYsAIxOTnh5ZCc5HKkQm4iIiKPx8/OjcuXKbN261a59+/btVK1alUqVKuUaExwcjNVqJTw83NZmMpmIioqiYUP7+fQPP/yAr68v5cuXvzs3ICIi90zOrgz4s2aGe84xU/dZzYxLV6+Rei37989qviUKOBp72pkhIlLInb6QxNR/f82lq9fs2iuU9mTKkCDK+xSdM/WtVitff/01ERERWCwWjEYjHTp0oGHDhg51hqPkn/DwcMaNG8fAgQMJDg4mIiKC8ePH4+7uTocOHfIcM336dFavXs3YsWOpVasWmzdv5uWXX8bLy8t2DNnSpUuZNWsWw4YNo3Hjxhw4cIC33noLFxcXnn766Xt5izdlcHbFmmnCavpzcl28mCvJaVmkZ5rJyDLbCtOJiIiIvREjRjBx4kRKlChBq1atiIyMJDw8nLlz5wLZBb9jYmKoUaMGXl5eBAUF0bJlS6ZNm0ZaWhpVq1Zl1apVnD17ljlz5ti99vHjx6lRo0ZB3JaIiOQzu2TG34+Zyry/jpmKPpsAgKuLEd9yjnXKh5IZIiKF2Pe/XmLGsv+Slm7C3dXIy/0aUvfBsjgbDbg4F72Hm1lZWRw6dAiLxUKZMmXo1auXVsIVce+++y4dO3Zk0qRJQPZqycTERObNm5dnMiMmJoaVK1cydepUevfuDWQX7Tx16hRRUVG0bNmS1NRU5s+fz7Bhwxg9erStz9mzZ9m3b58DJjNcsGaCxZRla/Nwc8bF2Yksk4Wk1EzKlvQowAhFREQcV0hICJmZmSxZsoTQ0FCqVKnCzJkz6dSpEwC7d+9m4sSJLF++nMaNGwMwf/585s2bx+LFi0lMTCQgIIAlS5YQGBho99pxcXEEBATc83sSEZH8l5z6150ZfysAfp/tzPj9j3oZVSt6Y3RyrIWjSmaIiBRS274+zcI1P2C2WPEp7s7rgxtTvbJjFWbKb66urvTq1Yv//ve/dOjQwe4cYyl6YmNjiYmJYezYsXbt7du3Jzw8nNjY2FxHi0VERODu7k737t3t2lesWGH7fu/evaSlpfHMM8/Y9fn7asv85OTkRFZW1s075jXWxQ0LYM3KwGq1YjAYMBgMFC/mSlxiOsmpmZQu4Y6TdicBYDabcXFxuXlHERG5b/Tt25e+ffvmeS0kJISQkBC7Nnd3d8aPH8/48eNv+LpbtmzJtxhvxsnJiczMTNtcQO4uzSdE7j85OzM83JxxNmZXZnBzyX50nn6fJTMctfg3qGaGiEihY7FYWbb5ZxaEfo/ZYsW/UnHmjGpRJBMZFouFr776iri4OJSSgQ0AACAASURBVFtbxYoV6datmxIZ94Ho6Gggd3FOPz8/AE6ePJlrzPHjx/H392f//v1069aNgIAA2rVrZ/ew4fjx45QsWZLz58/Tt29fAgMDadmy5V2tmeHu7k5GRgbx8fG3Pdbg8keBb4sJLH9Ooot7umIAzBYradfuLFFS1MTHx5ORkYG7u3tBhyIiIpKvvLy8yMzM5PLly1gsloIOp0jTfELk/pSUmv07Vc4RU/CXmhn3WQHwk7ZkhmPVywDtzBARKVQyssz8P3v3HRhFnf9//LklvYcUEhKSEJr0KiBGQBTBwiGeHp6I+rVwfrlmO07O353t/J53X72vHSx49jvFhiKKNEUBkV5DS0gC6dlkk03bNr8/ZmeSTQ8mJCTvx1/J7Ozw2YhkZt7zfr/++d5uvt+XC8CEC2J5YOF4Av173lND5eXlfPTRR2RlZXHkyBFuv/12zGb5tdWbVFRUAOrFe31BQUEA2Gy2Ru+xWCzk5eWxbNkyfve735GQkMAHH3zAPffcQ2RkJJMnT8ZiseBwOLj77ru54447+N3vfsfXX3/NX//6V4KDgxs9ndkRoqKiqK2tpaCggLKyMkymto+BUxQFd3U1oGCsPoXBVPf/u73agdPlJrvSSFBAz/t3oD1cLhe1tbWEhIQQFRXV1csRQgghOlRYWBhVVVWUlJRQWlqKj49Pu84nRNvI+YQQvZfN05kRGlh3XVUXAN57MjOstlqKrTUApEoxQwghxNkqq6jl8dd/4GhWKQBXTU3hzp+NwGTqeU12x44d45NPPqG6Wg01157EF72LoigAjUYpaNuNxsZ/9x0OBxaLheXLlzNjxgxAzcPIyMjg+eefZ/LkyTgcDiorK7n33ntZuHChvk9ubi7PPfdcpxQzDAYD/fr1o7i4mJqamnY9UWkwGKjJScdVZcUvNgW/+LqgUVuVnb3HiwC4ZGwC1bVOCkurKKuoJS4qiKS+oR3+WborHx8f/caDjN8QQgjR0xiNRvr160d4eDjl5eU4nU7p0OgEcj4hRO+ljZnS8jKgfgB49+zMcLmVDs+00EZMGQ3Qv2/3Cv8GKWYIIcR5Iaeggkde3U6BpQqDAe6YO4Jr0gb0uBNsl8vF+vXr2b59OwABAQH87Gc/Y8iQIV28MtEVQkLUE6eGHRiVlZVer9cXFBSEyWRi6tSp+jaDwcBFF13EqlWr9H0Apk2b5vXetLQ0Nm3aREVFRZPH/qkMBgPR0dFn9d7iI+soP/QlAdVjiJsyU98e38/Ns59mYbXZWbvLitOl6K/5+ph4+5HZBPjJ6Z4QQgjRUwQFBennMkIIITpOeWVTxQz1Wqo7BoDvSi/g0dd+YMHlQ7hxVsfdM8nMVYsZ/WJC8PftfteSPe9xXiGE6GH2HS/igWe/pcBShZ+viWW3XsjcS1J7XCHDYrHw2muv6YWM/v3786tf/UoKGb2YlpWRnZ3ttT0rK8vr9fqSkpJwu904nd5twA6HQ/9/Ruv0sdvtjfaBxp0g3YFfXCoAtfkZemcKgI/ZyKUT+gPohYwB8WGYTQbsDhc7Dxec+8UKIYQQQgghxHlG78yol5nh56N2ZrjcCg5n9+qGW/1tBm63wpa9pzv0uCc9nRndccQUSDFDCCG6tfU7svjLy9uorHESEeLH3/77YiaPiOvqZXWKXbt2kZeXB8All1zCLbfcQmho7xmRIxpLSkoiISGBL7/80mv7unXrSE5OJj4+vtF70tLSUBSFtWvX6tucTidbtmxh/Pjx+j4Aa9as8Xrvpk2bGDJkSKOMju5AK2a4q8pxlhd5vbbg8sFcN2Mgd80byWt/upxn7pvO2CExAGzZd+acr1UIIYQQQgghzjcVVZ4A8MDGAeDQvULAbdUO9nnGDecWVeJ0dVyhRRszlRLfPYsZ3a9XRAghBG63wjtfpfP++mMAJMeF8v9un0RMRGAXr6zzzJgxg+LiYiZPntzkE/eid1qyZAkPPvggYWFhTJ8+nY0bN7J27Vr++c9/AmpHT3Z2NgMHDiQ4OJgpU6Ywbdo0Hn/8caqqqkhOTubdd9/lzJkzPPXUU4Da9XPjjTeyYsUKzGYzY8aMYc2aNWzfvp0XX3yxKz9us3yiEjCYfVGcdmrzTuITFqO/Fujvw61XD/fa/+LR/fjxcAG7jhRQVeMg0L93h4MLIYQQQgghREvqOjPqrp386hcz7E6CA7rHddXOw/m43GpnvsutkF9SSULMTx+VXFPr5EyROua5u3ZmSDFDCCG6GbvDxTP/3sO3e9UnqscNiWHpogk97mZkQUEB+fn5jB49GgCz2cyNN97YxasS3c38+fOx2+2sXLmSDz74gMTERJ588kmuvPJKADZv3syDDz7Im2++yaRJkwB49tlneeaZZ3j55ZexWq0MGzaMlStXMmLECP24f/7zn4mLi+P999/npZdeIiUlheeee46ZM2c2uY6uZjCa8O2bQu3po9jzTsLQKS3uP2l4X8wmI3anmx8PFzBtXMI5WqkQQgghhBBCdK284kqe/2Avs6ckkzamX5veU9FEZkb9zIjulJux7WCe1/c5BbYOKWacyi9Hm2qcIsUMIYQQrbHaavnr6zs4csoCwOwpyfzq2pGYTD1nKqCiKOzatYuvvvoKt9tNdHR0k+OChNAsWLCABQsWNPna/PnzmT9/vtc2f39/li5dytKlS5s9ptFoZPHixSxevLhD19qZ/OJSqT19lNq8k63uGxTgw/ihMfxwKJ/v9p2RYoYQQgghhBCix6iqcbDnWBFjB0c3+eDn1zuy2H+imKpaZ5uKGYqi1HVmNDNmqqabFDNqHS52pRd6bTtdWAG0PJJcURT2HCsiNjKQftFNj1bWRkxFhQcQWi87pDuRYoYQQnQD+SWVfP5dJt/sOU1ZRS0GA9x29XDmTetZQd81NTV89tlnHD58GIDw8PAuXpEQ5w+/vp4Q8Dw1BLy1fxsuHh3PD4fy2ZVeKKOmhBBCCCGEED3Gv78+xsebT3BN2gDumjey0eunC9VRSeW22jYdr8buwulSWxLq38T38ypmOH/KkjvM3qOF1NpdGI0GRg2MYu+xIv3ztmTttlO89OF+QgJ9WP7Hy5osVmR08/Bv6AbFjM8//5yXXnqJnJwc+vXrx+LFi5k3b16z+1ssFv7xj3+wZcsW7HY7Y8eO5cEHHyQ5OfncLVoIIX6i6lon2fnleLr3eObfe/RfPr4+Ju6/aRxTRvasboXTp0/z4YcfUlZWBsDw4cO5+uqr8ff37+KVCXF+0EPAa2w4ywrwiejbaB/F7aLyyFZsh7cyNLgPsT6BFDiC2HEon+njE8/1koUQQgghhBCiwx3JLAEg3TPVoqGcggoAyj2jo1pTUW+/+p0ZZpMRo9GA2610mzFT2oipEQP6MCylD3uPFemftznZ+eW89ulBQA06f29dOouvHdVoP62YMUCKGU1bu3Yt999/P4sWLSItLY3169ezdOlS/P39mT17dqP9FUVhyZIlZGdn88ADDxAeHs6zzz7LokWL+OyzzwgL674/aCGEADWYad0PWby99kizv1Sf/PXFDEzoOR0LiqKwdetWNm7ciNvtxmw2M2fOHMaOHdujuk6E6Gw+feIx+PijOGrUEPB6xQy3o5aKvRuw/vAZTmtdy/EfQwzstyeS/qNLihlCCCGEEEKI857brZCVr968zymowO1WMBrr7i04XW7yiisBteOi1uHCz8fU5LE05VX1ixl1He0GgwE/HxPVtc5zPmYqp6CCbQfyuHRCIlHhAQC4XG52HMoHYMrIOMKC/QC1E6W57n2H08X/vrMLu9ON2WTE6XLzxdZTXHlRComxdTkbLpebrLxyAFLiu+899i4tZjz99NPMmTOHZcuWAZCWlobVauWZZ55psphx6tQpdu/ezZNPPql3b6SmpnLZZZexceNGrr322nO6fiGEaI8DJ4p5+ZMDnPL8cmjI39fE0kUTe1QhA6CwsJANGzagKArR0dH8/Oc/JyYmpquXJcR5x2A04dc3hZqcI9TmnSR42FQAas4cI//9/8Fdpf3bYiAgdSz2wiyoKGGMbzaUvEPeJ2eIm/ebrvsAQgghhBBCCPETFZZWUV2rjnyqsbsoKqsmNjJQfz2vuBKXW9G/L7fZiY4IaPGY2sOmRqOh0Xhef1+1mFHrODfFDLdbYc33mfzr80PYnW6++iGLJ5dcTFR4AAczSqiocgAweUQctmr16+paJ5byGvqENf6cb35xhMzccowGeOSuyTz/wT7yiit5dfVBHrlzCqA+hPrW2iPYnW4AUhOkmNFITk4O2dnZ3HvvvV7br7jiCtauXUtOTg6Jid5PENbWqnPOgoKC9G1aN4Y2tkQIIbqbAksVr392iO/35+rbLpvYn5tmD/WaUWgyGnpU0LcmNjaW6dOnY7VamT17Nj4+MrdfiLPlF5eqFzMAnLZSClb9XS1kmMyEjJpB2KS5+PaJR3E5sez/jkOfvUOCyULV4S0oP1uCwdD6vzP/+foobrfCgllDpINKCCGEEEII0W00fEA0O7/cq5ihhmHXKa+sbbWYUVJWDUBkiJ9XlweAv68ZqKX2HGRmlFireebfe9hzrEjfVmip4qHlW/nbkovZfkAdMTUoMVwP6TYawK3A6QJbo2LG7qOFfPKNeu14w2VDGDUwmtuvGc7jr+9gd3ohO48UMOGCWN5ff4wPN50A4IrJScREBNJddVkxIyMjA4CUlBSv7UlJSQBkZmY2KmYMHTqUSZMm8cILLzBgwAAiIiL429/+RmBgIJdddtm5WbgQQrRRTa2TVRuP89HmEzg81e2hSRHcOW8kg/tHdPHqOo/b7Wb37t2MHTsWk0lt5UxLS5MbokJ0AL+4gQDY8zNQXA4KP34al60Ug28A/W77G75RCfq+BpOZPmOnc2BnJQmFKzEoLpy2MnxCIlv8M04XVvD2l+kATB4Z161bjIUQQgghhBC9S1ajYkYFE4fVjeBtGIZtbUNuRpGnmBHdxE18LQS8tTFTG3dmk51fwU2zh+JjbnmsVVOOZll45NXteufFzImJTBoexz/e3smZIhv/b8VWvYNkysg4QM1cjY0MIq+kkpzCCkYPjtaPV15p5//e2w2o96IWXD4YgAuH92X0oCj2HS/mtdUHyc4v16//Lh4dz93XjW732s+lLitmVFSoVbLg4GCv7VrXhc3WdAr7ww8/zB133MGVV14JgK+vLy+88EKjwocQQnQVRVH4Zvdp/rXmMCXWGgD6hPlz69XDmTa2X4++qW+1Wvnwww/JycnBarUyc+ZMgB79mYU4l3zjBgDgrq2i4ON/UpN9GICYa37jVciob+zYofCV+vVbH3zHzYuuxsfcfHfGiZy6btdDGSVSzBBCCCGEEEJ0G5kNixkNwq8bhmG3JQS82FPM0LIp6tOKGS0FgDucbp57fx9Ol5sAfzO/uGxIq39mQ//++hgVVQ5CAn359fWjuWhUPAB/XDSRJ/61w6sjRStmACTEBqvFjAafe+POHEoragnwM3HfTeP1SSAGg4Hb547g909v5nShjdc/V68pJw6L5d5fjsdk7N73b7psnomiqLPLGt7g0rYbjY2XdvLkSX7xi18QERHBCy+8wGuvvcaMGTP47W9/y86dOzt/0UII0Ypj2aX84bktPPXubkqsNfiajfzi8sEsXzqT6eMSevRN/fT0dJYvX05OTg6gdmho/6YLITqGT2QcBl/1BLvq6A8AhE2ZR9DQSc2+Z/K4ATiM/gBkHs/k4Ve26bNVm3LitFX/+lBGSUcsWwghhBBCCCE6xKlc9aa+NrY7O9+7uJHToDOjvLK21WMWtVTM8NE6M5ofM1VircbpUidyrNpwnBJrdat/ZkOFpVUA/OLywXohA9ROivt+OR7tdlJibDAJMXXB3drXDTtSdqUXADB1VD/69gnyei0lPoxZk5P170cNjOKPiya2+NBbd9FlnRkhIeoPumEHRmVlpdfr9f3rX/8CYOXKlXpWxtSpU/nlL3/JE088wUcffdSJKxZCiOZZymt484vDbPgxR982dXQ8t1093Gt2Y0/kdDr5+uuv2bFjBwCBgYHMmzePQYMGdfHKhOh5DAYjfnEDqMk6BIB/0ggip/+yxfcYjQaComKxF2YRYaxk04lilj6/hYfvmNLk7NiTZ+o6Mw5nWlAUpUcXYoUQQgghhBDnh1qHi7xi9V7y1FHxrN12ipxCG263gtFoQFEUzjTMzLC1pzPDv9FramYGLQaAa8UQUMdRvbX2CL9fMK7VP7e+0nJ1skdkaOM1pI3th8Pl5p2v0rlh5mCv1xJj1KlH9bNCamqdHDypPpg2/oKYJv+8hbOHciKnlPAQf/5w8wR8fdo/GqsrdFkxQ8vKyM7OZsiQutabrKwsr9fry83NJTU1VS9kgNrZMX78eN58881OXrEQQjTmcLr49NsM3l9/lOpa9RdbSnwod84bycjUqC5eXecrKSlh1apV5OfnA5CcnMz8+fObLEgLITqGf78h1GQdwhQSSey192Iwtn7SaQ6Lxl6YxaVDA9lywEB2fgV/eWUrLzxwqVehwu1WOFmvM8NSXkOBparRkzxCCCGEEEIIca7l5Ffg9gyAuGRsP9ZuO0Wt3UVhqXrNUmKt0e/NJMYGk1Nga3XMlKIoejEjOrzxw6j+bRgzVeTpqtBs+DGHq6amMCixbXmpdodLz8poqpgBcOmERC6d0DhmITFWvf9iKa+lstpBUIAP+08W43S5MRoNjBncdDEjLNiPf94zvU3r6066rHckKSmJhIQEvvzyS6/t69atIzk5mfj4+EbvSUlJ4fjx41itVq/t+/bto1+/fp26XiGEqE9RFLYfzGPJ3zfxxprDVNe6CA3yZcnPR/PPe6b3ikKGoih8/PHH5OfnYzAYmD59OjfffLMUMoToZGFT5hEx/SbiFz6KKahteRbmUPXfpL5+NTz0X+pIqpwCG9n53k8t5ZdUUl2rtk8bPbNSD2daGh2vrKKWM0VN55sJIYQQQgghRGc4lafeEw4P9uOC5EjMnhwI7bpGy40wGmBoUiTQemaGrdqhh3tHt5CZUVPbUjFDLYYMTAwnOS4UgFc+Odjm0dulFXWjsCJC/dr0Hk1CTF0etdadseuIOmLqguRIggN82nW87q5LB2EtWbKEzz//nEcffZRvv/2Whx9+mLVr1/K73/0OAIvFwt69e/VRVLfeeismk4nbb7+ddevW8e2333LfffexY8cOfvOb33TlRxFC9CJZ+eX8ecU2/vr6DvJKKjEZDfzsklRWPHgZs6ckd/uwpI5iMBiYO3cukZGR3HLLLUybNq3JvCMhRMcy+QcRMXU+PpFxre/sYQ6LBsBZXsy4ITH60z77TxR77XfitDpiKsDPxJhB6nsOZ3rnZjicbv7w3BZ+/Y+NZJzxfsBECCGEEEIIcX6z2mr51d828NS7u7pdDuapPPVmfXJcKCaTUb+Rr4WAa7kRsX2CiAxTr3msrWRmFNcbEdViALij+cyMQk8xIzYykDt+NgKAI6csfLcvt/UPRd2IKYDIkKY7M5oTHOhLeIhaAMkpsKEoCrvSCwEYP7TprozzWZfedZo/fz6PPPII3333HUuWLGHHjh08+eSTXHnllQBs3ryZX/ziFxw6pM6FTkhI4L333iMqKoo//vGP3HvvveTl5fH666/r7xFCiM5SUWVnxUf7+e1Tm9l7vAiAcUNjeO7+GdzxsxE9rtrdlPz8fIqKivTvY2JiWLJkCUlJSV24KiFEa/RihrUIg8Ggd48dOOldzNBGTA3oF86I1D5A42LGrvQC8koqcboUNu8+3dlLF0IIIYQQQpxDPxzK50yRjc27Tje6XuhqWmdGkqf7ob9nxJIWAp7j6UxIjAnRA8Jb68zQ8i58zEbCgn0bvV4XAN76mKno8ABGD4pm8oi+APzr80MtZm1oLJ5iRqC/GX+/9qdCJNTLzThTZKPAoq5n/NDYdh+ru+uyzAzNggULWLBgQZOvzZ8/n/nz53ttS01NZfny5ediaUIIAYDL5ebLbad456t0fYZhv+gg7vjZSCZc0PN+MTRFURR+/PFH1q1bR2RkJHfeeSc+PmrxRroxhOj+tDFT7hob7tpqRg6M4ps9pzl4slgPy4O6zozUhDCGpajFjJwCG1ZbLWHB6tM+G37M1o+7/UAet109TALChRBCCCGE6CG0UU0AH6w/zqiB0V24Gm+n8tSihTbKqX9fTzFD68woUDszEmKCCQ1Sr19aK2bo4d9hAU1e12jFhZYyM7TOjJgINXPjtmuGs/NIAYWl1fxwMI9Lxia0uAatMyOinV0ZmsSYEA6eLOF0oU3vyogM9SMlPvSsjteddXkxQwghurN9x4p4+dMD+vzFQH8zN84awlVTB+Bj7h038aurq1m9ejXp6ekAOJ1OKioqiIyM7OKVCSHaSuvMAHCWFzFqoFrcqKhykJVfTkp8GIqicNIzNiq1XziDEsMxm4w4XW6OnLIweUQcZRW1/Hi4QD9WXkkl2fkV+pNRQgghhBBCiPNb/Vy9vceLOJZdyuD+bQuy7kylFTVYbWphIjneu5iRU2DD7Vb0zIjE2GDC6nVm1H+AqyEt7yI6ovGIKWg9AFxRFL27QztGfFQww1L6sP9EMelZpa0WMyyezIzmwr9bkxBb15lh93SCjBsS2yMfOusdd+KEEKKd8ksqeeJfO3hoxVay8yswGOCKyUms+ONlzJs2sNcUMnJyclixYoVeyBg5ciSLFy+WQoYQ5xlTcDgY1WdYnNZi+vYJJCrMOzejwFJFZbXafTYwIQxfHxODEsOBuhDwb/acxuVWCPI36/Nktx3MO6efRQghhBBCCNF5tJFN2n3wVRuPd+Fq6pzKVddlNECiZ7xU/75qUcPucJFxxqoHaSfE1o2ZcrsVqmoczR5X78xoIi8D6o+Zajozo7zSrhcQtM4MgKHJ6n2To1mWVj+bxerpzGhn+LcmIUb9eeSVVHEwQx0TPP6CnpeXAVLMEEIIL1U1Dt5Yc5i7n9zItgPqDbrhA/rwz99P49fXj9FDlXo6RVHYsmULr7/+OlarFR8fH+bOncu1116Ln1/v+BkI0ZMYDEbMoerYKGd5sZqb4enOOOApZmh5GX6+Jvp5ToaHpagn4FpuhjZi6pKxCVw0Sg0g1/6tFEIIIYQQQpzfKqsdFHturF998QBAPd/XChxdSRsxFR8drBcY+vYJ0h823XqgLmw7ISZEHzMFLY+aKmqtmOHrGTPVTPaF1tkB3t0dQ5LUbpaMM1a92NEcS4X6Mz/bzoxEz/Wb263gcLoxGg2MGSzFDCGE6JEUReFQRgmffHOCu5/cwKqNx3G63ESFB/CHmyfwP/89ldSE8K5e5jm1Z88eNm7ciKIoxMTEcOeddzJ27Nge2aIoRG9hDlOLF05rEYA+aupgRgkut6LnZQyID8PkacEeNkAtgJzIKeNIpoVMz9NQMycmMnmEWszIOGOl0BMwJ4QQQgghhDh/1c/LWHD5EOKjgoDu0Z3RMC8DwGQ06OHX3+9TixkRIX4EB/gQWi/Mu6ViRqudGb4tB4AXlanXQgF+JoIDfPTtQzyjuZwuRX9wrDlaZsbZFjOiwv31cVgAQ5MivNbSk0gxQwjRq2XllzP3/tX88YXveG31ISzltfj6mPjlFUN5aemlpI3p1ytv4I8ePZqEhAQmTJjAHXfcQXR09wn8EkKcHXOo+v+xs1ztxBjpCfKrrHaQmWvlpBb+3S9Mf88FntZol1th+cf7ATVMb3D/CIal9NFbt7fLqCkhhBBCCNEL1Nid/L/lW3nzi8NdvZROkeXJy4gM9Sc0yJfrLh0EwDd7zpBfUtmVS2uymAHQP1b9PrdYXZ82csnPx6Tf4Lfaaps8ptutUGL15F00U8xoLTNDC/+OCg/0un8UFuxHXB+1GHQ0u+VRU6Xl6voizrKYYTDUFXUAxg+NPavjnA+kmCGE6JWstloeeXU7v/7HJq/t08clsHzpTG6cNQR/Tythb+ByucjMzNS/N5lM3HLLLVx11VX4+PTMar4QvU3DzozYyEBiPG3QB04Uc8LztFD9TrSQQF+SPKF6GZ5w8JkT+2MwGDAZDUwa3heQ3AwhhBBCCNE7HDhRzN7jRXy46QSKonT1cjpcdoFaMNCCtWeMTyQqzB+3W+HjzSe6bF0ul1vvGmlUzPCsVaOFYQP6w1fNdWaU2WpxutT/js0XMzzZgy43Lpe70evamKmYJgLEtVFT6VmlTR5bO661UgsAP/ux3gmxdT+H8UN75ogpkGKGEKKXSM+y8OKqfTz/wV6e/2AvC//yJTuPFOivB/iZefexOdx303ivGYe9QVlZGf/617946623yM7O1rebzb2nmCNEb6B3ZniKGYCem7FxZw4VVeoJfmpCmNf7hqX00b82GmDG+AT9+8kj1VFThzNKmn3aSQghhBBCiJ7C4nmC3u1Wms1QOJ9lezoztAKBj9nItdMHArB+R3aLQdqdKbe4EodTLSQkx3tfrzQsZmj5EQChwWpxoLlihjZiCloPAIemczMKS9UxU9H1wr81Qz3FjKMtFDPKKmrR6mIRIWfXmQF1nzsixI8B/cJa2fv8JXeqhBA9VlWNg8zccrYfzOOTb042u98tVw1j3rRUzKbeV989cuQIq1evpqZGnc94+vRp+vfv38WrEkJ0BnOYp5hRYUFxuzAYTYwaGMWGH3P0lm1fs5H+sd4XA8NSIlm77RQAY4bE0Ces7iR/zKBo/H1N1Nhd/Hg4n8suTDonn0UIIYQQQoiuUGar0b+utbt63EQHvZgRW9f9cNmF/Xn988PYnW52pReSNqZfp69j1cbjvPdVOqMGRTNtbD/snkJGgJ+5UQdEo86MmMadGdZmihla+HeAn5mgZjIm/OplUdTYXQT6e++nHaPpzgx1bG9xWTUl1mqvaymNpbzu71SfsLMvZsycmMix7FKmjUvo0ePSe9b/cUII4fH22iP8Z/2xRtvN8hYZlQAAIABJREFUJgMXjYoH1F9WP790EH09Mwx7E6fTyVdffcXOnTsBCAoK4tprryU1NbWLVyaE6CzamCkUN64KC+awaEakRnntkxwfiqlBYVcLAQe4bEJdsVNRFHx9TIwfGsv3+3PZdkCKGUIIIbqnzz//nJdeeomcnBz69evH4sWLmTdvXrP7u91uVqxYwapVqygqKiIpKYlf/epXXHXVVV77/fvf/+aNN97g9OnTxMfHc9NNN7Fo0aLO/jhCiC5UVl7XjVxd6yQs+OzHAnU3tmqHfmM9qV6BINDfh9GDotiVXsj2A3nnpJix7UAudqebnUcKvKZqJMeFNrpRHxsZhK/ZqBc8Eus9nFU3ZqrpLvLWwr+hYTHD2ej1Iq0zo4ljJMeH6mtLzypl6qjG+2jh336+JgL8zv5WfZ+wAB76r0ln/f7zhRQzhBA9iqIoPPLqdnalFzZ6bd60VBZdeQE+ZlMT7+w9iouLWbVqFQUF6glBSkoK8+fPJzg4uJV3CiHOZ+bQusKFs7wYc1g0MRGB9O0TSH6JegJePy9DExMRyKIrL6DEWsOUUepYqYIP/5eaM8eImfsbJo+M4/v9uew5Vkh1rfMnnYALIYQQHW3t2rXcf//9LFq0iLS0NNavX8/SpUvx9/dn9uzZTb7niSee4D//+Q/33nsvQ4cOZc2aNdx3330EBwczbdo0AF5//XX+/ve/s3jxYiZNmsS2bdv461//io+PDzfeeOO5/IhCiHOotKLupnhNM4HQ56vs/HL968QG3dpTRsaxK72QH48U4HC6Ov2+SkWVOs6qX3QwBZYqnJ6sitQmxieZjAYSYkPIOGMlwM/k1d3QWmaGlnfR0rjx+t03DUPAax0urDa75xiNx0yZTUYGJoZzONPC0axSpnoerq3P4vk7FRni36M7KjpKu682N27cyObNm8nNzeXee+8lICCAbdu2cd111+Hn13OqkUKI89PHm094FTJ+v2As08cnYjQgvxSAmpoaXnvtNWpqajAYDMyYMYOpU6diNPa+EVtC9DZGHz+MgaG4q8pxWIvwT7wAgJGpUeSXqHk5A5soZgBcP3Ow/rW7torK9G0A5L33GCMuuxOzyYDD6Wb7wTxmjE/s5E8ihBBCtN3TTz/NnDlzWLZsGQBpaWlYrVaeeeaZJosZ2dnZvPPOOzz66KNcf/31AEyZMoVTp06xZcsWpk2bRmVlJc8++yyLFy/m97//vb7PmTNn+P7776WYIUQPVmarX8xo/JT++UwbMRUV5t9o5NKk4XG8sGof1bVO9h0vZsIFsZ26Fpsnz2/hnKGMGRzD9gO55BTYmDe96WkS/fuqxYx+MSFe937CgjyZGbaWMzOaC/8G786MhsUMrSsDmi+IDEmK9BQzLE2+rnVmRPyE8O/epM13rxwOB3fffTdLlizhww8/5Pvvv8dqtXLkyBEeffRRbrrpJqxWa2euVQghmlVZ7WBXegGvf35Y3/b44ouYObE/JqNBChke/v7+XHLJJYSGhnLrrbeSlpYmhQwhepG6EPBifduogXUdG0096dSQoyS37hu3i/J1y7k94SgGFFZvyUDR0uuEEEKILpaTk0N2djazZs3y2n7FFVeQkZFBTk5Oo/esX78ef3//RmOo3n77bR566CEAvvvuO6qqqvjlL3/ptc9TTz3F888/38GfQgjRnZTWyzeoqe1hxYwCLfw7tNFr4SF+DEtRx89uO5DXqetwuxVs1WpnRkiAL8EBPlx2YRK3XTO82YDstNH98DUbuaTBCKzWOjPaMmbK12xEu6XUuJihvt9oNNAntOm1DfGEgJ/IKdM7TOqz6MWMs8/L6E3afAfrpZde4ptvvuHRRx9lw4YN+oXqrFmz+NOf/kR6ejovvPBCpy1UCCGak19SyaJHvuLhV7br266fOYjRg6O7cFXdR0FBAU5n3UnW5MmTufvuuyXoW4heSMvNcFqL9G3jhsYSGepPUt8QkuIaX7g0ZLeoxQyjfzABA8YAMKxiO7cEfcvJHAuHM5t+4kgIIYQ41zIyMgB1rGp9SUlqxlNmZmaj9xw9epSUlBS2bt3K3LlzGTZsGLNmzeKLL77w2ic8PJy8vDwWLFjAiBEjmDZtGm+++WYnfhohRHfg3ZnRM8dMNQzU1kweoY6c/eFQHi535z3AVFnjQHs+KsRTjGjNhcP78v4TV3Ht9IFe21vLzNDCu6OaCObWGAwG/D3dGQ27cbT39wnzb5Q9qBnqKWbYnW5O5ZY3el0rZjRXDBHe2lzMWL16Nddddx3XX3+91zgps9nMzTffzA033MCGDRs6ZZFCCNGU0vIaHl/5A3c+sR67o+4kYkhSBDfPuaALV9Y9KIrC9u3befnll1m/fr2+3WAw4O8vvySF6I3MYZ7OjPK6YkZokC+vLLuM/7t3OuZmTsDrc5ScAcAnqh99f7GM0HFXADDWL4vhPqf59NuTZ7U26egQQgjR0Soq1KeMG2bDBQUFAWCz2Rq9x2KxkJeXx7Jly1i4cCGvvvoqw4cP55577mH79u36Ptr0ilmzZvHKK68wc+ZM/vrXv/LRRx918qcSQnSVGruTqpq6m9k9rjPDM2aqf2zTxYwpI9VihtVmJ/1U5z3AVFFV10URHOjTwp7emiomaAHtlTVOHE7vrgiH001phVpIaGnMFICfj5rU0LCAVdhC+LemT1iA3vmR3sSoqVLpzGiXNmdm5OfnM2LEiGZfHzJkCKtWreqQRQkhRHOqa528vfYIa7edavSLKNDfzEtLZxIe7Nfrx0pVVVXx6aefcuzYMQBOnDiB3W7H17dtTzUIIXomH72YUey13den7QF+DovaVu4TGY/BaKLP7DupyT2OPT+DeFMZXx/MI7+kkr59gtp8zI07c1j+0X5uuWoYV01Naf0NQgghRBtohfKG1wba9qbGrTocDiwWC8uXL2fGjBmAmoeRkZHB888/z+TJk3E4HFRWVnLvvfeycOFCfZ/c3Fyee+455s+f35kfSwjRRcoqvJ/ur+5BnRkVVXY93Ly5zozYyEAGxIeRkWtl64Fchg/o0ylrsXnCvwFCAn/aPYzQep0dFVV2IusVDCzlNXoHSEsB4FCXm1HraHrMVEwT4d/1DUmKoLismqNZpVx9sfdrlnJPALhkZrRJmzszYmNj9RbNpuzfv5/oaBnpIoToXB9tOsHqLRmNChm3XT2c//3tJUSG+mM09u5CRlZWFitWrNALGaNHj+auu+6SQoYQAnNo3Zips+2E0DIzfPvEA+oNIh/P1wkBVSgKfLal+XPGhhRFYdXGY1TXOnn54/3sO17U+puEEEKINggJUW/INezAqKys9Hq9vqCgIEwmE1OnTtW3GQwGLrroIo4eParvAzBt2jSv96alpZGbm6t3hAghepb6I6YAantQALjWlQGQ2ExnBsBkT3fG9gN5ndZZrXVmmE11453OVv1iRsPcDC0vA6BPa50ZzY2Z8hQzWiuGaKOmjmaVem13uRX971VzeSDCW5uLGVdffTX/+c9/2Lp1q75Ne7rhnXfe4eOPP2b27Nkdv0IhhAByCipY/tF+tuw9rW+bPj6B+24az7uPzWH+jIEt/sLtDdxuN99++y1vvPEG5eXl+Pj4MG/ePObNmyeFDCEEUFfMUOw1uGsq2/1+RVFweDIzfCLj9e0+EepFTWqoeiL+9Y4sKqsdjQ/QhKz8CnIK1JtMbgX+8fZO/aJACCGE+Cm0rIzs7Gyv7VlZWV6v15eUlITb7fbKnAO1Y0O7B6Jlbtjt9kb7QONOECFEz1Ba3qAzo7bndGZoeRnREQEE+jc/2ukiTzGjsLSajDPWTllLhafoEBLo+5P/PQ0O9NXDu60NilFa3kVokC9+rXSqa0WVRgHgZZ4xU611ZvSPBCCvpNJrHeW2Wtye/JFIGTPVJm0uZixZsoQxY8Zw++23c/XVV2MwGHj44YeZPHkyjz32GMOHD2fJkiWduVYhRC/lcrn5fyu2sub7TM4UqTffrpicxH2/HM/0cQk/ue2wp/jyyy/ZtGkTiqLQt29fFi9ezOjRo7t6WUKIbkTLzADvEPC2clVYUBzqybfWjQHgE9kXgBBXGf6+JqprXaz7IatNx/x2j1qkjgrzJzjAB6vNzpNv/ojD2XMuDoUQQnSNpKQkEhIS+PLLL722r1u3juTkZOLj4xu9Jy0tDUVRWLt2rb7N6XSyZcsWxo8fr+8DsGbNGq/3btq0iSFDhjTK6BBC9AwNOzN6UmZGa3kZmv59Q4iLUrvTth3M65S1VHjGTAV3wL0ek9FAcIAWAt50Z0ZUK10ZAP6+alJD/WKG263ox2gtcyM1IQyzSa2q1O/O0MK/ASLDpJjRFm3OzPD19WXlypV88sknrFu3jpycHFwuF8OHD+fSSy/l+uuvlyd/hRAdzlbt4I6/fu31hO/sKclcOz21C1fVPU2aNIl9+/YxZswYLr/8cszmNv8TL4ToJYyBoRjMvihOO87yYvz6ti+fQuvKAIPejQF1nRlKlZUrxsfy6bZcPvsug7lpA5oM4tMoisJ3e9VjzpiQyLCUPjz62naOZpfyyqcH+e/rpCArhBDip1myZAkPPvggYWFhTJ8+nY0bN7J27Vr++c9/AmqYd3Z2NgMHDiQ4OJgpU6Ywbdo0Hn/8caqqqkhOTubdd9/lzJkzPPXUUwD079+fG2+8kRUrVmA2mxkzZgxr1qxh+/btvPjii135cYUQnais3o1naDxy6HyWXeApZvQNbXE/g8HAlBFxfLT5BNsO5LFw9gUdvhZbldaZ0fbw75aEBvlSUWVvVMwoakN4t0bLGKwfAF5aUYPTpXZVxLQyZsrXx0RqQjhHs0o5cLKYC4f39RzD86CY2UhwQMd83p6uzXe6cnNziYyMZP78+U2GWVVUVLBv3z4mTpzYoQsUQvRuT72zy6uQ8bclF3dayNT5xuVyUVFRQXh4OAB9+vTh17/+dZOzf4UQAtSLD3NYFI6S3LPqzHCUnAHAHB6NwVx3su0TWVfYmDM8kNXb1fmx3+w5w6UTEps93snTVvJK1I67tDH9SIkP48ZZQ3n3q3TWbj3F8JQ+TBuX0O51CiGEEJr58+djt9tZuXIlH3zwAYmJiTz55JNceeWVAGzevJkHH3yQN998k0mTJgHw7LPP8swzz/Dyyy9jtVoZNmwYK1euZMSIEfpx//znPxMXF8f777/PSy+9REpKCs899xwzZ87sks8phOh8pQ07M7pxAHhxWTV9wvzbPKaprZ0ZAJNG9OWjzSfIzq+grKKW8JCODa6u8NwD6qgpHKFBvpwpaqozQy1OtaWY4d9EAHj90bitjZkCGDUwiqNZpew/Uaxv0zozIkL8ZERhG7V5zNTMmTNZv359s69/9dVX3HXXXR2yKCGEAHjzi8PsPFKgf//iHy6VQoZHaWkpr7/+Om+99Ra1tXUnVFLIEEK0xhyqjppylre/mGEv0fIy+nltNwaEYPRTT+DDlDKmjlLHdryx5hBVNc1nZ3y7Vy2OJMYGkxynPgX2i8sGM35oDABrvs9s9xqFEEKIhhYsWMC6des4cOAAX3zxBfPmzdNfmz9/PkePHtULGQD+/v4sXbqULVu2sH//fv79739z4YUXeh3TaDSyePFiNmzYwIEDB1i9ejWzZs06Z59JCHHulVU0LGZ0z86MtdtOcdtj63jny/Q27W+11eojtPr3bf2eQlK97o1CT3dDR6qfmdERwoI9Y6YaFKPaM2aqqQBwrZgREuhDgF/r/QKjB6rXYZm5Vr2wUqoVMyQvo82a/UmfOXOGjz/+WP9eURTWrVvHqVOnGu2rKAobN27Ez69jK3FCiN6hqsbBe+uOYqvyvuG1/se6oL7HFk/p9QHfmkOHDvHZZ5/pRYyTJ08ybNiwLl6VEOJ8oYWAO63FTb6uuJzkf/A3UNz0vf5Brw4MPfy7T5zXewwGA+aIOOz5J3GU5nPbNXP48UgBlvJa3lt3lNvnjqAhRVH4bp9azEgb3U9/EsloNHDF5CR2pRdy4nQZDqcLH3PLgXxCCCGEEEJ0Nu3Gs8EAigI13TQA/Jgnk+G7fbksnNP6GChtxBTQpvsuQQHqzfvqWifFZdUM7h9x9ottQoVnzFRwh42ZUu9XNxoz9RMzM/Tw7/DWuzIAhqZE4mM24nC6OXCymKmj4inx/J2S8O+2a7aYER8fzzfffMOBAwcA9SJ13bp1rFu3rsn9jUYj99xzT+esUgjR45wurKCwtJrXPzvEqbzyFvddOGcoYwbHnKOVdV8Oh4Mvv/yS3bt3AxAcHMy1117LgAEDunhlQojziRYC3tyYqZqcI1Sf3ANAdfYhAgeM0V9zNNOZoW7rqxYzLHnERARyw8zBvLX2CKu3ZHDZxP4kxXnP3z2aVao/zXTxGO/jXZCsduE5nG5O5Fi5ICXybD6qEEIIIYQQHUbrXugT6k+xtYbqbhoAXunpjD5TZGvTGKgszz2ZmMjANnUYgFoAyCmo0Lsb2qu80k5esY0hSY3P87UHXTtyzJT2Z2pq7E69aNK2YoZnzFS9Ykah51omupW8DI2fj4kLkiPZf6KYfceLmDoqXi+QSTGj7Zr9G2owGHj99dexWq0oisJll13GsmXLmpz/aDKZCA8Px99ffvBCiOa53Aobf8zm2ff3NrvP9HEJ1B8TGBMRyLXTBp6D1XVvhYWFrFq1iqIi9eZjamoq8+bNIzg4uItXJoQ435jDPJ0Z5U13ZlRn7qv7OmOfXsxQnA69ANKwMwPqQsCdpfkAXDs9lQ0/ZpNbXMnKD3ew9Jo4AvoP0zswtBFTKfGhjZ4ACw/xo190EGeKKjmcWSLFDCGEEEII0eW0sOa4qGCKrTVeN7a7k/q5o4czS7jIMwK2ORlnrACk9gtr858R7SlmFJ1FMcPucHH/s9+SV1zZZC5quRYAHtSxY6aslXVjpuoXYdpSjPDzaX7MVFuLGQCjBkWx/0Qx+4+r12Kl5eqaIkJl2lFbtVhuCw4O1m+Uvfnmm6SmptKnj8yrF0KcnfU7snj+g31NvvbAwvFcPLofRqMEHjWUl5fHypUrcTqdGI1GLr30Ui666CIJhxJCnBWfiL4AuGylOCtKMYd4t4VXZdQrZtQrbDhK80FxA+Dbp+nODACHJU/93mxi8bWj+Msr2xhdtIb8t7PpM+t2wiZeicut8L02YmpM42OB2p2hFjMsXHe2H1YIIYQQQogOUF3r1IsXffsEcuAkVHfTzIzKmvrFDEvrxYxctZiREt/2YobWzXA2xYxPvjlJXnElAMdzyhoVM2xaMaPDxkw17szQihlGg9pp0xo/bcyUo35nRvvGTIGam/E26ZwpslFircZS4enMCJEGgbZqW+8Q6GFX5eXlVFVV4Xa79ddcLheVlZVs376dW2+9tcMXKYQ4/5VX2nlxVd1NsdSEMJbdciExkW3/R7+3io2NJSEhgbKyMq677joSEhK6eklCiPOYX/xAjP5BuGsqqTq2g9DxV+ivuSqt2PPrQrfthVk4baWYgyP0vAyD2RdTSONOCa0zw1VZhttejdE3gHFDY7hoRAzDzqiFi4LvVnMqbDwl5XYsnqeQmitmDEuJZP2P2Rw5ZcHtVqTYLYQQQgghukyp56YzQFxUEAC13bWYUa8z41BmSYv7Ol1usvLUzIx2dWZ4uhHaO2bKUl7DBxuO6d9rY5Y0breCzbP+kICOGjNVl5mhKAoGg4EDJ9WfS2yfIEwmY6vH0APAa+tnZqifPSay7Z0ZAxPDCfAzUV3rYt/xIgkAPwttLmYUFBTwhz/8gR07drS4nxQzhBBNeW31QdyK+vXEYbH8+fbJXbugbs5ms+mdcUajkeuuuw6z2Szj/IQQP5nB5EPgoAnYDnxD5dEfvIoZ1acOAAoGsy8YjCiOGqoz9xMyclq9vIx4DIbGJ/w+kXWjpxyWfPz6pgBw65QQqj9UT/rNVUW8+drHHHOq+w5MDKdvn6Am1znM84RWRZWdM0W2NoURCiGEEEII0RnKKupGFPWNVM9fq7tpAHj9YkbGGSvVtc5mszByCipwutQH1ge0o5gRFXZ2xYy3vjhCTb3xXJYK72JGVY0DxXPvqOMCwNWiiMPp1n8W3+w+DcDFo1vuWtHomRmezoxDGSX6zzkmou0P6ZpNRoYPiGLnkQK+25eL06V+2D5hcq+nrVovPXn8/e9/Z8eOHVx55ZXMmzcPRVG46667+PnPf05oaCh+fn689957nblWIcR5xOF0s2rjcZa9+D3X3PcpG3fm6K/dMHNwF66se1MUhW3btvF///d/ZGRk6NuDg4OlkCGE6DBBQyYBUJ11EFd1hb5dGzHl3384AUnD1X08o6bsWjGjibwMAGNgKAZf9aLG4cnNAAiwZnrtd5F/3ZNYV09NaXaN8VFB+nzbw608USaEEEIIIURn0vIygvzN+s3xGrsTRbvz3k0oiuJVzHC7FdJPWZrd/+RpdcRUSKBvu26oR3vGTFnKa/RiSGtO5JSxYWe2+n5PZ4fF6l3M0PIyoOMyM0LrHae80k76qVIKLOqIqOnj2jb5wl8bM2V3Yqt28NS7uwB16khqQni71jN6kJphuDu9UN8WIWOm2qzNxYxt27Yxb948nnrqKf70pz9hMBhIS0vjscce45NPPiEwMJCvv/66M9cqhDiP/N+/d/PGmsMcOOkdMPvfPx/N0GQJcm1KZWUl7733HuvWrcPlcvHdd9919ZKEED1UwIAxGHz8wO2i6rh6Iq4oCtWZez2vjyIgZRSghoAriqKPmfKJbHoslMFg0PM4nKV5+vba0+kAGAPUzoqx/qd54w9TePMvVzBzYv9m12gwGLjA8/vicKb3BVhpeQ1Pvvkj3+453ez7u9uFpRBCCCGEOH+VecYBhYf44e+nPqWvKGB3tu1G/k+RnmVh5WeHqKh3o7851bVOfSqGj1m97dvSqKnM3Lrw7/bkckZ5ihGK0rgg0RRFUXh19UEUBZLjQpmblgp4j+8CsFXVFWJCAjunmLFpt/qw7YD4MPr3DW3TMfQxU3YXL67aR1FpNb4+Ju6/aTymdo7DHT0oGgCX5z+UyWjwWqNoWZuLGeXl5YwbNw5QnxCOj4/n4MGDAMTFxXH99dezcePGzlmlEOK8kVtkY/W3Jzl4su6X5YjUPlw/cxArHpzJnCnJXbe4buzUqVOsWLGC48ePAzB27FgWLFjQxasSQvRURh8/AlPHAlB5dDsAjpIzuCrUokFgyhgCBowB1AwMR1F2XTGjT/Ot2NqoKS0EXFEUanLUYkb41Osw+geD24Xx5Hdtmgs7LEUdNXWkQTHjzS+O8N2+XJ56dzeHMhpfnJ04XcZtj63jb2/82OqfIYQQQgghRGtKbWpnRniIv/6UPkBNbefmZrjcCv94aycfbz7B8o/2t7p/ZXXdekYNVDsADme00JlxRi1mtGfEFNQFgEPbQsC/35+rn7ffMXcEUeHqtYCWo6fRCjZmk0Ef7fRTBfiZMXtyMSzlNXy3V72umT6+7XmkWjHD4XSzZa+aB3jnz0aQENP+UbhJfUO9CjXhIX6SD9gObS5mhIWFUV1d95ezf//+HD16VP8+MTGR/Pz8pt4qhOgF9h0v4pr7PmXx3zbwyqcHsXieWrhr3kj+578vZtGVw4iPCu7iVXY/brebTZs28cYbb1BRUYGvry/z589n7ty5+PpKZV4IgM8//5yrrrqKUaNGMWfOHD755JMW93e73bz00kvMnDmTUaNGcc0117BmzZpm97fZbMyYMYM//elPHb30bi1oiJpdVJ2xD7e9muoMtSvDFByBT3QiPn36YQpRiwm2w9/jrioH1MyM5midGdqYKWdZAa7KMgACU0YRPGo6AOV71qMorT/FdkGK2pmRV1Kph+MVWKrYtEt9msrtVvj7Wzux2uouggosVTz66nZKrDV8vz+XotL2zfHtSoq7e85dFkIIIYTo7bTMjIgQP/zr5U/Uz3/oDLvTCyj0nM9+u+dMo4d8GqqsqetsuHC4em5+NMuCo4kOErdb0TszUtpZzPDzMendBK3lZtiqHby2+hAAk4b3ZfTgaH2sUmW1Q8+hAKjwdGYEB/q2q1OkJQaDQR9fu3n3aSqq7BgMcMnYpjvOm+Ln411YmTIyjismJ53VeoxGg15oAgn/bq82FzPGjRvHRx99REWFOld58ODB/PDDD9TWqv8zHzhwQA+rFUL0Ll//kMVDy7d6bTMaDYwbGsNFo5qerS7UJ5bfffddvv32W0Dtclu8eDEjR47s4pUJ0X2sXbuW+++/n6lTp/LCCy9w4YUXsnTpUr788stm3/PEE0/w4osvsnDhQlasWMHo0aO57777+Oabb5rc/3/+53/Izc3trI/QbQUOHAdGM4rTTtXJvXpeRkDKaAwGAwaDgYCU0QBU7F2vv69tnRlqMaMm5wgARr9AfKITCR17OaAWOaozDzR7HMXloDJ9OylRfvh62uMPe2b9frjpOC63mwmhhcT427GU1/DUO7twuRVsVXYeeXWbPtMYYO+xwib/jO6m6uQeTv3vzZRt/7SrlyKEEEIIIRrQihnhIX5eHQOd3Zmxdtspr+9fXX0At7v5car18zImXqAWM+xONyfPlDXat7C0iqoadf2p7SxmQF13RmudGcs/3E9xWTW+ZiP/dY2ayxdZ7wa+9tASQEWl2pnRUSOmNFrhZdsBtYN8ZGoUfcICWnqLl/r/zSND/fn19WN+UrFFy80A6CPFjHZpczHj7rvvJjMzk2nTplFaWsoNN9xAQUEB8+fP58477+T9999n+vTpnbhUIUR3dLqwgmff36t/Hxbsy/I/zuTTf8zlkTuntOuXQ29jMBgYMmQIAJMmTeK//uu/iIyUPBEh6nv66aeZM2cOy5YtIy0tjUceeYQ5c+bwzDPPNLl/dnY277zzDn/+85+57bbbmDJlCo8//jgTJkxgy5Ytjfb/5ptvWLt2LSEh7W8PPt8Z/YMISFGLp7ZDW6jJVp+WChhx1COdAAAgAElEQVQwWt8n0PO1q1J9YssUFIbJP6jZY2rFDJfNgtteo4+Y8ksYgsFgxDcqAf/+wwCo2LOu2eOUfreKgg//Qdm6FQzqHwGoIeAl1mq+/iGbSb4nuNn8Jfcl7gZgz7Ei3v0qncdf30FOgQ2zyUhirPrfdO/xonb+ZLpGZfp2FEcttkOSlySEEEII0d1o2Q4RIf5enRnV9s4rZhRaqth5pACAedPUjIlj2WV800JunFbM8PM1ER0RQFyUeu5+uInRrNqIKT9fE/HR7X9AXQsBb6kzY9OuHH29t/9shP7nRIT66fuU1hs1ZavSihk+7V5PS7RihlYImtGOEVOgFjC0DJJ7bhz7kzMuRnlyM0A6M9qrzcWMYcOG8f777zN37lwiIiJITU3lhRdeoKamhj179jBnzhweeOCBzlyrEKKbOZxZwt1P1mXlzJ6SzFsPz6bfWfwS7C2cTicOR92TEhMmTOCOO+5g9uzZmM3mFt4pRO+Tk5NDdnY2s2bN8tp+xRVXkJGRQU5OTqP3rF+/Hn9/f+bNm+e1/e233+ahhx7y2ma1WnnooYd44IEHCA1tW/BbT6ONmqo6+gOKQ72ICEgepb+uhoDXPXHU0ogpALNnzBSoo6ZqPOHf/okX6NtDPN0Zlcd+xGkrbfI4lelqjkfl0R8YmaheJB3JtPDR5hM4XW4uDsxQ11eWyTUXqe3d768/ps/h/f2CsVw1NQVQxyC29PRad6HljDgsuRJeLoQQQgjRzZTW68zwNRvRIg5qaztvzNRXP2ShKBAZ6sctVw0jbYw6FumNNYeb7QjRxkwF+avFgGGesa2HmsjNyPAUM5LjQtsdYg2tFzPySyp56UM15+PCYX29MlT9fc0E+av3QCz1OzM8xZiO7swIC6ornviYjUwZ2fJ1TUPBgb48cfdU/vGbNMYMjvnJ64mPCiIqTC1iREoxo13aXMwAGDJkCA8//LD+/fTp09mwYQM7d+7k6aefJiBAnsAWorcosVaz9Pm6p0fjo4L41fxRHTbTsCeyWCysXLnSazyOwWCgX7+2z2kUojfJyFBvWKekpHhtT0pSb15nZmY2es/Ro0dJSUlh69atzJ07l2HDhjFr1iy++OKLRvs+9thjpKamsmDBgk5Y/fkhaPBEMNSdDvrGJGMODte/NwWG4tu37uffWjHDFBSOwUc9Ga/NPY6jWH0Kyz9haN2fOXQyxoAQcLuw7d/U6BhOa5H+PlxORvqoRauTZ6x8uS2LCKON/kb1CTXF5WDh1AgGJdat+ZarhjFtXAJjB6tPO1ltdk7llbf+w/iJyravJvuFu7EXZp3V+7WAdcVeg6uZIo8QQgghhDj3FEXxyswwGAz4eULAO6szw+F0s+4H9bzy8klJmE1Gbr1qGD5mIyXWGj7afKLJ92mdGUEBajFjeIqagXc4s6TRAz5aMWNAfPtHTEHLY6ZcLjdPvbOL6lonESF+/PYXjccyaR0JXsWMqs4dMwVqloj282mPocmRDE3umGkaBoOBm2ZfwJCkCNLGtK+w0tu1qZhRWVmJzWZrcZ/du3dz7bXXdsiihBDdW1WNg1sfrRsPMnVUPMv/OPOsKvm9xYEDB1ixYgV5eXns2bOHoqLzY+yJEF1Jy+lqmMkVFKS2Sjd1bmKxWMjLy2PZsmUsXLiQV199leHDh3PPPfewfft2fb+vv/6aDRs28Pjjj/fqIqwpKMyra6L+iClNYL1tLeVlgHpSroWA2w54MkqMZvziB+r7GM2+BI9IU/c5vLXRMapO7vH6PqJkLwaD2hJud7iYHJTt9brbcpo/LprIxGGxLLryAq6bof5ZcVFBREeoF1h7j3X+v7nlu7/CWVZIeb18kbZy26u9ChhaYUMIIYQQQnS9yhqnHqAdHqI+4R/gp2YodFYA+A+H8iirqMVogCsmJQMQExnItdPVc90PN52gqLRxEUErZgRrxYwBajHDVu0gp6DCa1+9mHEWeRlQr5jRxDr+s/4Y6Vnq+e3vbxxHWLBfo320jgRthBfUZWYEd9KYKYDp49o3YqqzXHZhf/73t5eQENP7Rh7/FC0WM7744guuvvpqJkyYwMSJE5k1axaff/651z6VlZU88sgjLFy4kJMnT3bqYoUQ3cOx7LobLjERATxw84RefTOwJXa7nU8//ZSPPvoIu91OSEgIixYtIjo6uvU3C9HLaaN2Gv77om03GhufxjgcDiwWC48//jg33HADF110EU8//TRDhw7l+eefB9SCx1/+8hf+8Ic/kJDQPU5ku1LQ0En611rgd331t7XWmaHuo+ZmaOHffnEDMPp4X7wEXzAVAHtBZqMb91UZag6TKUjttnBkH+KC2LrAvbTQM1772wtOERMZyJ9vn8z1Mwfrf18MBgNjPLNomwoBz8y1kpXfMR0biuLGWV4MQE3WwXa/XwtM178vkWKGEEIIIUR3UVbvZntEiHoDXuvM6KwA8LVbTwEwcVhf/QEdgJ9fOoiIED/sDhdf72jcEWxr0JkRFxWkF2AOZdblZpRV1OodET+1mFFRZaemXodKda2TDzYcB+Bnl6QybkjTY5m0n2X9zgxbVeeMmdK6QIIDfBg/NLZDjy3OrWaLGZ999hn33nsvp0+f5uKLL+byyy/HZrPxwAMPsHbtWgD27NnDNddcw3vvvUdCQgIrV648ZwsXQnQNu8PFi56ZhwDP3DdDOjKaUVBQwCuvvMLeveqNuUGDBrF48WKSk5O7dmFCnCe0UO6GHRiVlZVer9cXFBSEyWRi6tSp+jaDwcBF/5+9M4+PqjzU/3f2SWayk40khH1HXFAWRXADRbCKG7YutXpblaoVbbn13utVf1avbdVqad1at6otCu4QioAKKCKggKwC2TeyJ7Nv5/z+OHPOzGSBhIQkwPv9fPpp5qzvjCFzznne53mmTWP//v0APPzwwwwbNoxrrrmGYDBIMKhceMuyrP18KmEbPQ19XALG5EyseaPbrLfmjsaQOACd0YwlZ8RRj2dKzYp5HR0xpWLJHYkhQbFoO/du0pbLoSCeIuU7JuX869FbbSBLTE9W+iTyrQ5sHuVnc6YSf+WvjXVqRHN6OGpqd1ED/kBk1lxRZTP3PfMFDzy7nsaom6djJeRsgpDyu+OvKSXk7ppIEmisin0tnBkCgUAgEAgE/Qa1LwPQHAZxqphxHGKmymsc7DyoTJS5bNrgmHVxFiMThg8A2u+q0GKmwp0ZOp1Oi5ratjcywUd1Zej1OvKzj60/MFpkqW+OXFMfLGsiGFKcLAtmjepw/9RwZ0R0AbjjOBWAnztxIBefPYh7rj9DK/IWnJh02Db71ltvMWDAAN555x0GDlRm4Xm9XhYuXMiSJUsYMGAAt99+O6FQiF/84hfcddddWCxtLUMCgeDkodnp46aHV6H2kibZzZp1URDLvn37WL58OcFgEL1ez8UXX8yUKVOEg0Ug6AJqV0ZpaSmjRkUugktKSmLWR5Ofn48kSQSDQczmyGyeQCCg/fv797//DcD48eNj9l2+fDnLly9n7dq1p5Rjw5iQQt6df0anN7RxUADojCZy/+Np5KAfoz3l6MdLaSVmtCOQ6HR6bKOn0LJlJa69m0g592oAvOX7kf3KTVn8iLPxVR7AsWMd4zjIyEEjuTGzGg6BMSmDhNMvov7ffztiR8XEsDPDHwixt7hBe/3aij2EJJmQP8RXOyu5/LyhR31fRyLYHOv88JTuxj56aqf3V8u/tdfCmSEQCAQCgUDQb1D7MhLiTdqDcOtxjJkq2FQMQGZqPGe0UzatCiot4UimaLQC8LjII9/J47P4cmcl3+ypZsP2CqafnkNhpSJm5GbYsZgMbY7TGdISreh1IMlQ1+ghJ12JB95XopSN52UmHPGZUWqi8j5iOzPCzgxbzzozEuLN3LvgjB49pqBv6FCKKiwsZMGCBZqQAWC1Wlm4cCGHDh1i0aJFZGVl8a9//Yv77rtPCBkCwUmMPxBizTel/PcLX2lCBsCDPz2n7wbVz8nMzMRgMJCSksLPfvYzpk6dKoQMgaCL5Ofnk5uby6pVq2KWr169msGDB8dco6hMnz4dWZY1FylAMBhkw4YNnHXWWQAsW7aszf/S09O56KKLWLZsGRkZ7dugT2YMcQnoLfEdr7faOiVkQCRmSqU9ZwaAfcw0IDZqylOo9GWYMwZjTEjBNu48AOSag/zfLaNJa1BcG/Zx52LJHAwoheGS19XuOZLsFs02r/Zm7DhQy3f7DvNj25dcF7+JDdsr2t23KwSbYzs5vCW7u7R/RMzQhV8LMUMgEAgEAoGgv6B2OiSHY5EArMcpZqqospmVXxYDcOnUwejbScJQ+x+anb4261oXgIPSEXHmaOUe5y/vbqem0d3tvgwAg0GvxTfVNrm15fvDXRmj8498/9A6ZkqSZFyesDMjrmfFDMHJQ4fODIfDQV5eXpvl6rKkpCTefvttEhOPzYokEAhODBxuP/c+/XmbQqcXf3sRAwfYO9jr1CQYDGI0Kn9WU1JS+MlPfkJ6ejpWq/UoewoEgo5YuHAhv/3tb0lKSmLmzJmsW7eOgoICnnnmGUDpvygtLWX48OHY7XamTp3KjBkzeOyxx3C73QwePJi3336biooKnnrqKQAmTJjQ5jxms5mUlJR21wm6hiklImaYUgdisLV/g2TJHYXBnkrI2YAz7M5wH1Ji+eKHK7Om4vLHY7AlE3I1Ub/mdYKNSreEbex5mJIi3UP+2rJ2HSAAp49Ip7Cime0HarlJknntk93kGuqZbFG63raV76W+eRJpSXHt7t8ZAk2xYoani70ZqnhhGTgcX+UBAo2HkUNBdIYOL9UFAoFAIBAIBL2E6sxISYhM5D4ezgxfIMQf39pGMCSRnWZjTquIKZUkVcxoz5nRqgAclKipXy04g7v/+BnNTj9Pv/2tJiAM64aYAUpvRn2zl9om5XiyLGtixqijiBlqAXiLy08gKOHzB5HCE2h7ugBccPLQoTNDluV2izXVB3W33367EDIEglOAlV8WxQgZIwclc98NZwohIwpZlvnyyy/561//iscT+azy8vKEkCEQdJP58+fzyCOPsHHjRhYuXMg333zDk08+yZw5cwD4/PPPuf7669m9OzIT/rnnnmPBggW89NJLLFy4kMbGRl555ZU2sVKC44PBnoIuHFdl6cCVAeGoqTFTAHDt3UTQ0Yj/cBEAcUMVMUOnN2Abqzg43Ps3A2BKz8OckY/easOYqOQF+2uKOzyP2ptxqLyJVV8Xc7C8mQxDpNNigqmUL3d2zwmhOjO00vLaMkKu5k7vrzoz4ocr7iFkiUBT29JygUAgEAgEAkHvo4oZydFiRtiZ4elBZ8ZrH++mtNqBXq/j/p+cSby1/Qf6iWrMVHvODK8yntb7piRYufd65Rp7d2E9VXWKs3nIwO6JGenhEnC1v+Nwg5um8LhG5acecd+UxMjn2eTwaRFT0PMF4IKTh2Oe7pWZKZrfBYJTAacn8mXy+19OZ8yQI38ZnWq4XC7ef/99Dh1SZviuX7+e2bNn9/GoBIKTiwULFrBgwYJ2182fP5/58+fHLLNarSxevJjFixd3+hzr1q3r1hgFEXQ6HZbs4XhLdxM/7PQjbmsfM42WLSvxHy6iZetKZX9zHNbcSEeKfdx0WrasjLwee54W22fOyCfYUoevnd6MQGM1equNsUPTMBn1BIISL3/wPQBnZsvgULY7zVTGu99VcMX0Ycf8ntXODNvoKTh2rEMO+pXejHCU1pGQvC6kcGF43JAJNH25HDkUIFBfgTmtbZSaQCAQCAQCgaDnCIUkvtlzmIHpNvKz2p+03diumKE6M3pGzNi69zCffKlM7Pnx7FFHFAJUZ4bLGyQQlGIKrduLmVI5e2wWl587hBXh80D3YqZAcWZARMxQXRlxFiN5mQlH3Fd1ZkAkykulpzszBCcPor5dIBB0irPHZgohoxWFhYW88MILmpBx5plncuGFF/bxqAQCgaDvybhqEVk3/A+2ozzMV6OmAJq+/giAuCGnxcQrWQaOwJgc6TGxh3s0QBEzAPw1pTHH9VUVUvbCvVS9+TBmo56x4e+vYEhGr9cxIT1y05lmcNJSfki7ATsWVDHDlDYQS85IoPO9GdHl36bUHIzhzpHWpeACgUAgEAgEgp7n029Kefy1b/jlHz7j7j9+xrJ1B6hpcMds0xR+0J4S1ZkRZwl3ZvRAzFSjw8uz/1K648YNTeOaC0cecXu1ABygxRVxZ8iyfEQxA+DWeeMYlKWIDBkpcd12QKjODLUzY3+pImaMHJSMoZ2+j2jirSZNFKpv9uJwK7FZRoNOWy4QtOaIzox33nmHr776KmaZ3+9Hp9Px97//nY8++ihmnU6n4/HHH+/5UQoEgl5HlmW+P1THB18c6uuh9DskSeLzzz9nw4YNAFgsFubOnSsibAQCgSCM0Z6M0X5kVwZEoqZatqwEKWyJH3p6q2102MfPoGnju1hyR2FKydLWaWJGbSmyLGuODcf2NSAF8dcUE3I1c/rIDHYcqAPgknMGYWrZQHTC8GnmUjbuqOTKGV13Z8iyTLBZObYxKYO4/PF4S3Z1ujcj0KiIFnqrHUN8AqbUbAK1pQTqu19MLhAIBAKBQHCysXzdAf79dQn/c9vko8787wxlhx3az8VVLRSv2MPrK/Ywe0o+d109Eb1epzkzojszLN0oAH/mn9+yYXvkWk+SZEKSjC3OxKIfn3lUESAxyrXQ4vJr3W8+f4hQuHTC3oGYYTEZ+M+bz+bF93dy4aS2XcldJdqZIcsy+4obgKNHTKmkJFqpqnPR6PBq0Vj2eLN2XS8QtOaIYsaWLVvYsmVLu+s2btzYZpkQMwSCE5smh4+yGge/e2WzlrOokpka30ej6l94vV7efvttysrKABg4cCDXXHMNKSlHLrYSCAQCQfuoUVMq8cPOaLNNynlXY0xIbbNOFTNkn5tgSy2mpAzkUBDnvk3aNv7aEs4ZO4R/FOzFYjKw4JKROF5WOjKMKVkEG6s5zVTKBzsqjknMCLmakYPhWWRJ6eitNgACdeUEnU0Y7clH3D9Qr4gZprAjw5yWgxvhzBAIBAKBQCBoj9WbS6iqd7F5d3WPiBn14SLsM0amk5NhZ+P2SpqcPv79dQk6nY4755/WbmdG3DEWgDvcftZtLWt33cJrJpKRcvRnLwnxZvQ6kGRojurNcHkjMeEdOTMA8jITeOyOc7sw6o5JT1HEDI8vRJPDR2GF0ht3tPJvldSwmNHQ4kUKCzGiL0NwJDoUM9auXdub4xAIBH3MM//8tsMv1FH5Kdw6d1wvj6h/YrFYsFiUC5ipU6dy0UUXYTAI+6NAIBAcK2rUVMjZgGlALsak9Dbb6AwmEs+c1Wa5KTUbDEYIBfEfLsGUlIGnaKfWQQFKGfegcybyh7unY4szkWzw0uJXblqTp/yIuoIXGWhsoq6slJoGNxkdiPeypNyo6vSxf/PV8m8AU1I6OqMZndGMHPTjLd2NfeyRbxRVZ4YqZpi0mKnulZILBALBicp9993H3LlzOf/88zGZOn4YJxAITk2aXcokElVg6C4Nzcp14ZjBqdwwezS3XzGeVz7ezUcbClm1qZhQSNLcDtExU0dyZgSCEnodGAxt0/1LqyNOkP++9RyM4b6LlARrp/sr9HodCTYzzU4/zc6I3zi689TWQXl4T6M6MwC+3l2tfVajBnVOzFDdLo0tPgxhN0ZCvPjbL+iYDsWMnJycXhnAJ598wvPPP09ZWRk5OTn84he/4Morr+xwe0mSePHFF1m2bBm1tbXk5+dzxx13cPnll/fKeAWCk5F1W0vbFTLu//GZ5GYkMCw36ZS2+EmShF6vXGDodDquvPJKqqqqGD58eB+PTCAQCE58dDo9iWfNpvGLf5Jw2gVd29dgxDwgD//hIvw1JdhGno1zT6x7WO3TGBm+oYqOf7KPP5/G9UsJuZo4zVzKlzsruWpm27/tsixTvfR3eMv3k/sfT2NKztTWqX0ZeqtNc2VYc0fhKf4eT8muo4sZDa3EjHDpd8jZiORzo7cIZ6RAIDi12LJlC6tWrSIhIYFZs2Yxd+5cJk+efErfjwgEAoVgSNI6IXpMzAg7M1KTFKHCYNBz+4/G4/WHWL25hE+/iXSzxTgzOigA9wdC3PX7deh0sOTXF2IxxU6EKa1WJt0MSI5j8vjsYx53os1Cs9NPiysiZriixYy4I4bx9BhJNgtGg55gSGJjODore4AtptfjSKife0OLF0v4MxXODMGR6J3f7A4oKCjggQce4Oabb2b69OmsWbOGxYsXY7VaufTSS9vd5/HHH2fp0qUsWrSI0aNHs2LFCu6//37sdjszZszo5XcgEJwc/O3DSEnp7T8az4wzcmO+pE9l6uvrWbZsGRdccAEjRyolXDabTQgZAoFA0IMknzsf+9hpGKP6MDqLOSNfETNqS5ECPlz7NwNgTBxAsKUOf21sOXigvlJbrzdbiR95Do7vVnOaqZSV2yvaFTP81YV4CncA4D6wlaSzI5NoVGeGMTHiKLHmj8dT/H2nSsDbiBmpOTHrLNldj74SCASCE5kNGzawefNmVq5cyaeffsry5ctJS0vj8ssv5/LLL+e0007r6yEKBII+Qi2IBmhyert9PFmWI2JGYsR1odPpuOuaifj8Ib74rjy8DJKiuiqsHRSAV9Q6ORwuED9Y1sS4oWkx61VnhlrCfayovRnNUQXgqphhNhkwGXsnQUKv1zEg2Up1vZtdh5Qeuc5GTAGkht0ujQ4v9ni1M0M4MwQd06dixtNPP81ll13Ggw8+CMD06dNpbm7m2WefbVfMKC0t5a233uLRRx/l2muvBZSYl+LiYjZs2CDEDIGgk3y3v4ZDFc28vmIPCfFm7YJg8rgs5p47pF0r5KnIjh07WLFiBYFAgI8++oh7771XWN0FAoHgOKDT6TGlDjymfc0ZgwDw15TgPvgtst8LegPJ0+ZTt+ol/HVlyLKETqd8t6nxTaY0RTSwjVLEjMHGWqrLqyjYVMxlUwfHnMOxa732s6/qUMw6TcxIjogZcfnjaQQC9RUEHY0YE9q/oQu5HUhepzKeFEXMMMQnoI+zI3mcBOorhZghEAhOOXQ6HVOmTGHKlCn87//+Lxs3bqSgoIAPP/yQN954g9zcXObOncu8efMYOnRoXw9XIBD0Ii1RkUrR8UrHitMTIBCUgFgxA8Cg1/GrG87A6w+yeXc1GSnxMc9KrKozwxdElmXNPRbdYVFY0dxWzAgXjg/qZt9Hkl0RM6I/E7X71N5LrgyV9OR4quvdhBOmGN3JiClQCsBBiftSY7yEM0PBV3mQpk3vk3zetVgyB/f1cPoNfSZmlJWVUVpayqJFi2KWz549m4KCAsrKysjLy4tZt2bNGqxWa5sYqjfffPO4j1cgONGRJJmCTcXsOlTHxh2RHO7omQ03zRkjhAzA7/ezcuVKduxQZuEmJiYyf/58IWQIBAJBP0QtAQ/UV+LYsQ6AuCETseYrXU+y30uwuQ5Tcoa2HUScEHGDx6OzxKP3uZlgLuOvy+KobXRz02Vj0Ol0yFII1+5IdFVrMSPQpMRMGZMytGWWgcPQmSzIAZ/SmzHuvHbHrvZlRI9H+TkHX8V+/KI3QyAQnOIYDAZmzJjBjBkzKCoq4s9//jMrV67k+eef54UXXmDixIncfvvtXHzxxX09VIFA0AtERyr1RMyU2pcBkbijaIwGPYtvnsS/vy5heF5yzDrVmSHJSkeGORwn1RQlLqhl2NGozoz8bjozkmxKmkZ7zoz4XurLUBmQHPvZjcpP7fS+qYnh9+H00RQWgoSYodC4cRnuA1vQW+JJn7uwr4fTb+gzMaOwsBCAIUOGxCzPz1duSIuKitqIGfv372fIkCF89dVXPPXUUxw8eJDc3Fx+9atfMWfOnN4ZuEBwgvL1ripeeG9nzLK8zARkWebHs0czcICN/KzEPhpd/6G6upply5ZRX18PwKhRo7jiiiuIjxeZ5QKBQNAfUcUMZAnPoW8BsI87L7YcvKYkImaosU7hbgqdwYRt+Fk4d2/gvJRqvqoeybtrD1DX5OHu684gULKTkKtJO1+grgLJ70FvVsoOgy1hZ0ZUcbnOYMKaM1KJmirf37GYERZWDLYkrW9DGVs2vor9BOoruv35CAQCwYnMwYMHWbVqFQUFBRQWFmIwGJg5cybz5s1Dp9Pxr3/9i7vvvptf/vKXLFwoHvQIBCcD7679gb3FDfzmpklYzbGPLaPFjBaXj5AkY9Afe59OfThiSq/XaeJAa0xGA3PPa+sCix6bxxfUxIwYZ0ZlrJgR/cB+UDefvySGnRnRDhVVzLDF9baYESkBN5sMDB7Y+femOjMkGSpqFMeyKABX8FUrz86DjoY+Hkn/os/EDIdDUSLtdnvMcptNuZFzOp1t9mloaKCqqooHH3yQe++9l9zcXN59913uu+8+UlNTmTJlyvEfuEBwAvL5tjKeevtb7fU5Y7M4a0wGc6YNOcJepx7btm2joKCAUCiEwWDgkksu4ZxzzhFlgwKBQNCPMdiS0ccnIrmVMkWd0Yxt5Dno9AbMabn4a4rx15ZhG3k2cihIoOkwQEysVfyoyTh3byAnWMa8SWl8vLWez7aV09jiY2HmNwCYM4fgP1wEyPiqi4gbNBZZlgk2KWKGKcqZAWDOGoKn+Hv8NSUdjl0VVowpseWP6tjU9QKBQHAqcejQIQoKCli1ahWHDiluuDPPPJOHHnqIyy67jOTkyOzoOXPmcN111/Haa68JMUMgOAmQZZl/rd6PPyjx3f5apk6IvUaKdiFIsiJoqNFEx4LqzEhNsKDvoiiixkyB0puRpI4xSsworW4hEJQwGZUEDDViCpTJpd1BFV9a2nFm9LaYkR4lZozIS8bYhcSPtKh4L48vHJMlnBmE3C2EHMok25Cz6Shbn1p0WcxYt24dn3/+OZWVlSxatIi4uDg2bdrE1VdfjcXS+Sh2ekQAACAASURBVMJgWVaC1Fo/JFSX6/Vtf/EDgQANDQ288MILXHDBBYDSmVFYWMiSJUuEmCEQtKK63sV/PL4mZtmMM3J54Maz+mhE/RuDwUAoFCI1NZVrrrmG7Ozso+8kEAgEgj5Fp9NhzsjHW/w9APEjzkJvUW6ozBmD8NcUEwiXgAeaakBSShpVZwZA/LDT0VttSF4XP7JsJumyubxZsI89BypxNm1GDySedSlNm94n2FiNr+oQcYPGInmcyAHlJjjamaGcezAA/primBzlaNSYqeiIqeixBRoqO9xXlkI4vvsUc+ZgrLmju/SZCQQCQX/m8ssvB2DkyJHcd999zJs374jX5VlZWfj9R87O/+STT3j++ecpKysjJyeHX/ziF23iq6ORJIkXX3yRZcuWUVtbS35+PnfccYc2NoCtW7fyk5/8pM2+M2fO5MUXXzza2xQIBO3gD0r4wx0WjY62Bd/RzgxQoqa6JWao5d/tREwdjThL5JGq1x+MGZNKMCRTdtjB0BxF6lAjpjJS4mL2PxaS2nNmeBUxw97LMVPpKZEki1Fd6MsARXgxGfVadwlAohAz8B0u0n4OuRr7cCT9j07/ywkEAtxzzz18/vnn6PV6JEnitttuo7i4mEcffZT33nuPv//97yQlJR39YEBCgqJAtnZguFyumPXR2Gw2DAYD5557rrZMp9Mxbdo0li1b1tm3IhCcEnh9QR5+eVPMsiumD+U/rpzQRyPqn0Q/JJo4cSLBYJAJEyZ0SZwVCAQCQd8SLWbYx06PLE8Pl4OrYka4g0JnMGFMHKBtpzfHkXbxT6n95C+49n7F3KvPpXjiQLx7N6AP+ZUoqjFT8RTvJNhYjT/cmxFsrtGOEV0ADmglfZLXRailro3YoYynfTHDHHZmyH4vIWcjxoS2ucPNW1bQsOZ19FY7+ff+DZ1R2PEFAsHJwc9//nPmzZvHiBEjOrX9M888g8Fg6HB9QUEBDzzwADfffDPTp09nzZo1LF68GKvVyqWXXtruPo8//jhLly5l0aJFjB49mhUrVnD//fdjt9uZMWMGoMRgx8fH8+qrr8bsm5goonsFgmPFHXYWQPudGO2JGd2hvtkDQFpS3FG2bIsl2pnhixIznLFjKqxo1sSMMrX8uwcivlVnhsPt1+K2nP0gZmpUftfEDJ1OR0qilZoGt7bMLmKm8FdHixktyFIInb7j77pTiU77fp5//nm++OILHn30UdauXas5KGbNmsV//dd/sW/fPv7yl790+sRqV0ZpaWnM8pKSkpj10eTn5yNJEsFgMGZ5IBAQMTACQZgWl5/6Zg9v/XsfFbUubflrD80SQkYUkiSxfv16PvroI22ZTqdj0qRJQsgQCASCEwxLlpJjrLfEEzf8DG25JmbUVygRU+GOCmNqVpubAftpFxA39HQA6la9xJyz0plkUXJq5byJGKw2LNnDAPBVK2JGICxm6MxW9NbY6FRTWo7S2QH4Dhe3GbMsyx2KGcaULEC5tg20UwIe8jhp2rgcAMnrxFO0s802AkFvIYeCeEp2IwW6X8QqEAAsWrQIm83GH//4R5qbI3nzL730Ev/3f/+nddupHEnIAHj66ae57LLLePDBB5k+fTqPPPIIl112Gc8++2y725eWlvLWW2/x0EMPceuttzJ16lQee+wxJk2axIYNG7Tt9u3bx4gRIzj99NNj/jd0aNtsfYFA0DlUZwFAY3tihrOVmOHs3neP5sxI7Lozw2IyoD6K9PpD2vLm1mJGVG+G6swY1M2IKYh0ZsgyON3K59JXMVPZA2wk2szEWYyMG5rW5f1TE2KfwYgCcPDH3D/IhFxty+RPVTotZnz00UdcffXVXHvttTEP+oxGIzfddBPXXXcda9eu7fSJ8/Pzyc3NZdWqVTHLV69ezeDBgxk4cGCbfaZPn44syxQUFGjLgsEgGzZs4KyzRGyO4NRlT1E9T7+9jXn3f8hPHirgp4+u5oMvDmnr//f2Kcc00+Bkxel08uabb/LZZ5+xfft29uzZ09dDEggEAkE3sI87j5Tzryfzmt+gN0ZufkwZecoPoSCBxmpNGIjuy1DR6XSkz7kDnTmOkKuZAd+/yShTNQDfBhQRQxUzAvWVSD43wWa1/DujzcQancGIeYBy/vZ6M0KuJmS/p93x6E0WjEkDtHO1pmnT+0jeiLvZuW9Tm20Egt6ieetKqt58iIZ1/+jroQhOEn744QeuuuoqXn31VaqqIt1BLS0tvP3221x55ZWUlZV16lhlZWWUlpYya9asmOWzZ8+msLCw3eOsWbMGq9XaJobqzTff5L//+7+113v37mXUqFFdeWsCgeAouL3RcU1tY6aiOzOgrXDQVbojZuh0Oq03I9aZoQgLiTblmrSwIkrMOKx0vA3K6r6YkWSPPJtVHSt9JWZYTAb+8usLeX7xhTHj6iwprT5/4cyIjZkC0ZsRTafFjOrqasaPH9/h+lGjRlFbW9ulky9cuJBPPvmERx99lPXr1/Pwww9TUFDAvffeCyiF39u3b9eiqKZOncqMGTN47LHH+Mc//sGGDRu4++67qaioEGVfglMWry/I4iUb+Wxbebvrfzx7NJPGZPbyqPovBw8e5IUXXqCoSPlimDRpUqct7AKBQCDon+j0BlKmX0fc4FgHojExHZ1ZuTny15ZGiRntZ68bk9JJu+hmADyHvkOPjEsys/wHKx5fEEtmxDnsqy6MKv9uGyEFSvwVtJ5ZpRBd7m1KyWqzPlICHitmBJtraflmhbJNWg4A7h++QQ4FEAj6gkBdBQD+mtKjbCkQdI6nnnoKm83GihUrGD060gn0wAMPsGLFCkwmE3/84x87dazCQsVh1zr5IT9f+fus3hNEs3//foYMGcJXX33FFVdcwdixY5k1axYrV67UtpEkiQMHDlBdXc1VV13F+PHjmTlzJq+88oqWYiEQCLqOy3MUZ0YPx0xpBeDHIGYAWM2KC9fTjjPj9JHK9WFhRTOSJNPs9Gn9Fj0hZkS7F9Rz9pWYAZCcYDnmSbTRJeBGg67bfSI9RcjdghSefNSbSAFfmwlNojcjQqd/OzIzM7ULgfbYuXMn6ent38h1xPz58/H7/bzyyiu8++675OXl8eSTTzJnzhwAPv/8c37729/yxhtvMHnyZACee+45nn32WV566SWam5sZO3Ysr7zyyhGFFoHgZOZ3r30T83rW5HwuOjuPZLsFk9FAeopwZACEQiE+++wzvvzySwCsVitXXHEFY8aM6eORCQQCgeB4odPpMKcPwlfxA/6aEu2mwBwWAdoj4YxLcO79Suvg2BEcgtMns/67cmZPGYwpdSCBhkp8VYfwNykxU+31YQCYM/Phe6UEvDWqmGGwp6I3t72BNqUNxFO0A2/pHiSfRys1b1j/L+RQAIM9hazrfkvZ879E8rrwFO8iftgZbY4jEBxvJJ+ScR3yOPp4JIKThe3bt3PXXXcxePDgNuvy8vK48cYb+dvf/tapYzkcyu+l3R4bBWiz2YC2HZ6gTKqsqqriwQcf5N577yU3N5d3332X++67j9TUVKZMmUJRURFer5eioiIWLVpESkoKa9eu5fe//z1Op5N77rmni+9aIBBArDPjSGKGXq9DkuR2t2lNaXULyz87yFUzhzM4O9JVIUkyDeH9j6UAHMBqMYLDhy9cAO71BfGFhY0zR2Ww/rsKPL4ghxvc1DVFHornZXRfzDAZ9disRlzeIM3hz0X9/Hq7ALy7RDsz7PHmflElEHI7KF1yJ4b4RPLu/DM6Q+8JLP6aEpCVQnS9JV5xhDuFmKHS6f8Sc+fO5fXXX2fGjBnawz/1l+utt97i/fff59Zbb+3yABYsWMCCBQvaXTd//nzmz58fs8xqtbJ48WIWL17c5XMJBCcbb6zcw/YfIo6o5xdfSG4PfCmebDQ3N7Ns2TLKyxX3Sm5uLldffTXJycl9PDKBQCAQHG9UMcNX8QOh8E1AezFTKjqdjvTL76T85UXIfh+BIdPg+xArvypm1uR8LNnDCDRUsvmLr7H5ahloAGNyRrvHsmQMBiDQUI3k98aIFsHG9vsyVKz542jZWoCv6hDlf7ufjB/di85kwbnzCwBSzr8eU2o2ltzR+Mr34dr3tRAzBH2CKmZI7pY+HongZEGWZXy+jh9QyrKM19s2fqajbYE2D8bU5Xp927CKQCBAQ0MDL7zwAhdccAGgpEQUFhayZMkSpkyZQmZmJi+//DJjxozRJnVOnToVr9fLyy+/zM9+9rM2AopAIDg6bm9sAbgsy9q/X1mWaQk7ELLTbFTUOjvVmbFs3QE+21aOPxBi8c1na8ubXT4kSflbkHbMzgwlZsrjUwSM6PGMGZKKxWzA5w9RWNGsxWZlpsYrIkgPkGi34PIGaXEqn5VaAB4f1z+cDZ0lNTESTZXQTyKm/HVlyAEvwWYvgcZqzANye+/c4fJvQ0IaxoRUfJUHRMxUFJ3+7V64cCE7duzgtttuIzU1FZ1Ox8MPP0xTUxNNTU1MmDBBRD0JBL3AVzsr2VVYz8cbYp1Sj995rhAyOkCn02lFgeeddx4zZ848alGgQCAQCE4OzBlKCbinZLe2rCMBQVufnEnOz/6A5HEwNZjOe99voLCimQNlTejjstEDyb4q7DrlprRjZ8bg8E8y/tpSrDkjtXXqeNQoqtbYRk0h7ZJbaVj3JsGmw1S+8d8YEwcAMqa0HBImXgiAfcxURcz44RsGXPbzNsXmAsHxRvIpM01DHkfMQyeB4FiZOHEiS5cuZcGCBSQmJsasc7lcvPvuu0ycOLFTx0pIUO6PWjswXC5XzPpobDYbBoOBc889V1um0+mYNm0ay5YtAxSnx/nnn99m35kzZ/Luu+9SVFTEhAkT2qwXCARHxhXlzPAHQnh8QeLDLgOfP4Q/qMxWH5SVoIgZnXFmHFYcWiXVsaK7GjEF3XBmhGOmVGdGdIdHaoKVIdmJ7Ctp5FBFkyY09ETElEqSzUxVnYtmlx9/UCIYUj6fvoiZ6g7Rzoz+Uv4teV3az4G6il4VM9S+DEvWENSW+ZBLiBkqnRYzzGYzr7zyCh988AGrV6+mrKyMUCjEuHHjuPDCC7n22msxm/vHL5xAcLJS2+jhide3tFn+qwVnMH5YWh+M6MQgMTGR+fPno9PpGDZsWF8PRyAQCAS9iDldETOQlBlzeqsdfXziEfYI75emuDdGyTKDsxMprmrhxfd3oq9xcGc8pBsikTolLWbGtXMMQ3wiBnsqIWcD/sPFmpgRcjXjqzgAgHVo+24KnU5H0jlziRt8GjUf/gl/TQnBZiXWKvXCmzTRwjZqMvWfvorkbsFbuqdNb4hAcLyRfOGbfSmE7HOjs9r6dkCCE55f/vKX3HjjjcydO5d58+aRn5+PTqejtLSUFStWUFtbyxNPPNGpY6ldGaWlpTFl3SUlJTHro8nPz0eSJILBYMwzjkAgoIl1+/fvZ9u2bVx77bWYTJGHhqpjJCUlpYvvWiAQQKwzAxR3hipmRPdlDMpKYNP3VUcVMyRJprxGETMra10EghImo+LIUsu/TUY99mN8+B9xZgS18QJYzAasFiNDcpLYV9JIUWWLts2gzB4UM8Jl281OX0zfiO0Ei5lK7edihr++HBuTe+3cqjPDnDmYkEsR4UIiZkqj02JGVVUV2dnZ7UY/CQSC44/XF+Rnj63WXudl2slKs3HHVaeRkRrfhyPrf9TW1rJ69WquvPJKLQ93+PDhfTwqgUAgEPQFmpgRxpSa3aWZ4zqdjsumDeb55Tv5obQJC8nI8RB9hOVbGhnXwf2NOTMfj7NByb4N4z64DZDxykZWFFq4fsQRxp8xiJxbn6Thi3/SvPlj4oefRfyISdp6Y1I6loEj8FUewLV3kxAzBL2O6swAxZ2hF2KGoJtMnDiRV199lSeffLJNofbo0aN54oknOOOMzsXq5efnk5uby6pVq7jkkku05atXr2bw4MEMHNg2dnD69On8/e9/p6CggKuvvhqAYDDIhg0bOOusswBFDHnkkUfIzMzkoosu0vZduXIlubm55OR03M0kEAg6xtVKzGh0+BiYrkS2NbsiwkV+ljIxpdnpO6IrsK7Zo3VYhCSZylon+eHeDFXMSE20HrOrUI2L8vrVmClFcFFFhmE5SQAUVjQRCCp/ywZlHX1STWdJtCkP/luc/hgx41jFmb4iJSG6M6N/jF2brAEE6sp77byyFMJfWwqAJXOodg8R7IGYKX9dObUfPYd10FjSLv5pt4/XV3RazLjwwguZNGkS8+bNY/bs2SQlJR3PcQkEgihCksxvlmzQXifbLTx3/wUYDW0zXk9lZFlm+/btFBQUEAgE+Pjjjzvs5BEIBALBqYHBloQ+PlHL8zelddyX0REzz8zltU/24PEFGTYkE6N+IKFGpUzcLxvYUuTi+4N1TBg+oM2+lszBeA59h+9wsbbM9YPistwXGMi2Hxq4fvaRz68zmki76GZSpl+Hzmhqc8NtGz1FETP2byZt9m0iakrQq6idGaCUZZpSsvpwNIKThUmTJvHuu+/S0NBARUUFkiSRnZ1NRkb7HUVHYuHChfz2t78lKSmJmTNnsm7dOgoKCnjmmWcApfC7tLSU4cOHY7fbmTp1KjNmzOCxxx7D7XYzePBg3n77bSoqKnjqqacAJU5q/Pjx/M///A8NDQ1kZWXx8ccfs27dOv785z+LuDWB4Bhxe4Ixr6OdF6ozw2jQMXCAIpyHJKUnoqPZ/OWHYyPmSqsdETGjOSJmHCtxmpgRGzOVEhYzhobFjIaWyPvo0Zgp1ZnhauXMOMHEjESbGYNeR0iS+6UzI1Bf0WvnDdRXIAeV33Vz1hBC7mag+86MQGM1VW89QsjZgK+6iJSZP0Zv7B+fdVfp9JPQu+66i/r6eh566CHOO+887rrrLgoKCo5YzCUQCHqGoopmiioj+Y4vP3ixEDJa4fP5eP/99/noo48IBAIkJSXF5NwKBAKB4NQl2p1xpPLvjoi3mvjf26fw8ysn8Ngd04jLibj9nIYkQMc/V+9v/9zhTgx/TQmyLCEF/bgKtwOwy59HRa2z3f3aQ2+2titU2EZPAZQsXW/5vk4fT3D8kWWZQEMVcjjm7GRDliVkf8SZIXlECbigZ0lNTWXChAlMnDgxRshoaGjo9DHmz5/PI488wsaNG1m4cCHffPMNTz75JHPmzAHg888/5/rrr2f37ki30nPPPceCBQt46aWXWLhwIY2NjbzyyiuMHz8eUGK4X375ZS6++GKWLFnCXXfdxcGDB1myZEmMA0QgEHSNts6MSK+FKmYk2swkJ0QKo48UNVVW44h5XXI48j1VH3ZmpB1jXwYocVIA3nABuCpmqCJDflYien1E3NTpIDfDfszna02S3Rw+r1/r5DAZ9ZhNJ9bEFr1eR0r4v2l/ETNCMTFTFTEuweOJLxwxpbfaMCalY7ArsYUhV9MxjyHYUq8JGQDIEsGG6h4Zb1/QaWfG3Xffzd13383+/ftZsWIFq1at4r777sNms3HJJZcwb948pk2bJmYgCATHgZAkaT//4Z7pmpVRoFBZWcny5cu1m5rRo0dzxRVXEBcX18cjEwgEAkF/wJwxCG/JLuDYnBkA44amMW6o0k9lyR6Gc9d6ABIzsqAOvj9UF+POONzgprLWyZh0RcyQ/R6CTTUE6ivRBf1Iso49gRxcfj8Ot79bN26mlCzMWUPxVxfi2vc1cYPaa/AQ9AXOnZ9R+8lfSJx0GQNm397Xw+lx5KiIKVCcGQJBT6B2dbrdbqSoe6FQKITL5eLgwYPs2rWr08dbsGBBh47t9qK0rVYrixcvZvHixR0eMzU1lUcffbTTYxAIBEenvc4MlYiYYdHEAnWbvA56KNS+DJXS6sj3VL3qzOiGmBFnjnVmNGlihnJdZzYZyMuwUxI+b1aqTSsN7wkSbcrn0OKKxEydaK4MldGDU9m4o5Lhucl9PRQg1pkh+72EHPUYE9u6sHsa/+FIX4ZOp8NgUz4POeBD9nvRWbr2nCvobKLqrYcJNtegM1lBlpCDfvz15ZgzBh39AP2QLv8LGjVqFKNGjWLRokXs2rWLgoIC1q5dy4cffkhaWhobN248HuMUCE5J6po81DV7+P0/tmrLhgwUEW8qsiyzefNmPv30UyRJwmAwMHv2bCZNmiSEVYGgD5FlmfLycvLy8gAoKirinXfewWg0Mn/+/HbLNgWC40l3nRmtsWQP035Oyc5ljDuVvcUN/KNgL+dNHMj67RXsL1Gs4DfOHsE5BhNyKIC/pgR34Q4AioMDcMnKzXNFjZPRg1O7NSbb6KmamJF2yc/E92A/QelHAU/x9308kuOD5G8lZniEmCHoPi+//DJPP/00JpMJu91OY2MjWVlZNDU14fF4sFqt3HTTTX09TIFAcIz4AyEkWW73ob7LGxsz1RglZqiuh0SbGaNBT0K8CYc7cGRnxmHleyneasTtDcaIGWpnRlo3YqbUAnC1M0MdY7RzZGhOkiZm9GTEFER1Zrh8mqvlRCv/Vrn/J2dxy+VjyUrrH91b0WIGgL+uolfEDNWZYclU7pmN9oi4E3Q2Yu6CmCH5vVT/81ECDZXoDCayrvtPGtb9A1/VIQJ1vRed1dN0K6fG6/UiSRKyLCPLMkajmC0uEPQEsiyz4ssibv1/q/n1cxuobVRuFM0mAwa9eDgRTUlJCZIkkZaWxu23387ZZ58tHuAIBH1IdXU1c+fO5Z577gGgrq6O66+/nldffZWXX36Z+fPns2fPnj4epeBUw5KliA86oxlTana3j2fOHAw65TLalJzOj2ePAmBvcQMvf7hLEzIA3l9fjGGAIuz5Dhfj2P8NAN8H8rTv9NazBo+F+OFnAhByNBBsqe328QQ9g6/qEIASNRUKHmXrEw/J64597RYxU4Lu89577zF69Gi++uorli5diizLvPHGG2zdupWHHnoIn8/HxIkT+3qYAoHgGAgEJe76/Tp+/vgaPL6234vusLvAbFSuszqKmYKIYNDo9NIRFeFrrHPGKX1OVfUuAkFFeIguAD9W1NQM9b00tyoABxiaE3kY3dNihuoACYZk7bnRiVb+rWI06PuNkAGxBeAAgfrjXwIuyzL+cM+eOUsRM1RnBkDI1bXeDNcP3ygF4noDGVc/QNzgCZgG5ALg74X3c7zospixbds2HnvsMc4//3xuuukmli9fzjnnnMMbb7zBZ599djzGKBCcMhRWNHP/s19wxQMf8cJ7O9usX3zTJNGVEYVOp+OKK65g6tSp/PznPycrSxROCgR9zdNPP01VVRU33HADAO+88w4tLS386U9/Yu3atWRnZ/Pcc8/18SgFpxqW7KEMuPwuMq/+NXqT5eg7HAW9OQ7roDHKsXNGMXFEOhNHKDO1EuJNzJ6Sz3/deg4WswGXJ8BhWXFdOHeth/BNSFX8CMYMUZZ3pTejI8wDctEZlJtXf3hGl6BvCblbCDaHhSUpRKDxxM0m7gjJHytmCGeGoCeoqKjgRz/6EXa7nby8PJKSkti6dSsGg4Ef//jHzJkzh9dff72vhykQCI6BuiYPhxvcNDp8mtAQjTvszBiYrvRKtB8zFRYz7NY220TjcPu12KdpExRnriTJlNc4CYYkzUXRnZgpVczwqTFTjtjODIChOYnaz4M6iMM6VpJskfNU1imfZ7xVTDTvCSRPKzGjF5wMwZZaJK/y31F1ZuiMJvRxyr+HkLOpa8cLX4dasoZiGzEJAFNaDtA77+d40enf8N/97nesXr2ampoazGYzM2bM4IorruD888/HbO4f5SwCwYnM1r2HeeRvX7dZft3FI7n2ohE9mqt4oiJJEhs2bCAjI4MxY5SHSHFxccyaNauPRyYQCFS+/PJLbrnlFq677joA1q1bR3Z2NpdeeikA1113HX/961/7coiCU5TE0y/q0eNlXftbgi11mNMV18V/3TqZ8hoHg7OTMIVnE86enM9HGwr5psrEZQYIhh9m14YSGDVxDB5/iF2H6ntEzNAZjJgz8vFVHcRXXYht1ORuH1PQPVRXhkqgrgJzeDbcyUJrZ0ZIODMEPYDRaMRmi8zOzc/PZ//+/drryZMn88wzz/TF0AQCQTdxuP3azy1RP6uoUUk56XaKq1piYqaiOzMg4sxQ3RCtUSOmACaOGIDNasQVjppKiDejdil3y5kRjpny+EKEJJkWVzhmyh55Tjo0JxmTUU8gKDGsh/sgEqPOU1mrPHw/UTsz+huqM0Mfn4jkbukVJ4M6IUlnMGmiAyjuDMnjJOTsmjNDFT+i3R3mNOVaNFBfgSxL6HQn3oTpTj8dfeutt5g8eTL33nsvs2bNwm63H89xCQQnNbIsU9fkRQ5/e67dWsbb/96nrTebDNxx1QTOHpsVk7V4KuNwOHjvvfcoLi7GYrGQnZ1NcnL/KIYSCAQRHA4HubnKBVJ9fT27d+/m2muv1dbHxcURDJ58USuCUw+9JU4TMgDiLEZG5KXEbHPljOGs/KqIg64EiEzKY1cgl3Mn5rCvpAHomZgpUOzovqqDwpnRT2gtZvjryrBxcolMrTszJOHMEPQAw4YN47vvvtOuH4YMGRJT9t3S0oLf3/7DS4FA0L9xeiIF3w5X7L/jQDBEICgBMDBdETSbHD5kWUan02lCgRqtpD4r6ciZoV5fpSVZibeaGJSVyN7iBkoPO8geEBFMuydmRJwZTrcfKSyQJCdEjmmPM/HQbZNxegIdFpV35/wWswGfP0RVvRAzehK1M8OaMxL3ga294mRQ+zLMGYPQGSKP7I32FAJ15YRcXXNmqLFUhqjeDdMARSSRg36CzXWYkjO6O+xep9NixhdffEF6evrxHItAcFLj8QX5R8Fe6ps9fLWzqsPtTh+RzkO3T9FmdQrgwIEDfPDBB7jdyuy/iRMnCkFVIOinDBw4kB9++AGAFStWAHDBBRdo6zds2KCJHQLByU56ShwXnJXHxi2xWc6lpmHcOihFm51YVeciJMndoTu/wAAAIABJREFU7sWyZA3FAfgO942YEXI14z64Ddu489AbhXO7jTOj/sS183dE63JMETMl6Anmz5/PI488gt/v59FHH+XCCy/k3nvvZcmSJQwdOpTXXnuN0aNH9/UwBQLBMeCMdma0EjPcUeXfuRnK/X4wJOHyBLDHm9uJmQqLGR10ZqjODPVYg7ISFDGjuoXhYYdEnMVAfDcKszVnhj8UI6ok2WOvg04fefweGCfZzNT4PfjCJeQnamdGf0KWJSSfMmHDkjMK94GthFxNhDxODHHH71mUv6YEAHM4YkrFYFcmTAW7GDOlOTPskQlXppQs0BuUCNT6ipNLzNiyZQvDhg0jNVXJ8i0uLqa4uPioBzz77LN7bHACwYlMSXULVXUuln66H6NBz76So9vBrrt4JDdeOloUWIcJhUKsXbuWTZs2AWC1WvnRj34kbl4Egn7M3Llz+etf/0pJSQmbN28mOzub6dOnU1payuOPP84XX3zBf/7nf/b1MAWCXmP+BcNZs6WUxlA8KQY3bslEzrjT0et15ETdqNc0uGNmCR4L6o1PyNFAyNWMwZbU7fF3hbpVL+Ha9zWBxsOkzryhV8/dH/FVFwJgSEgl5GjAX3fiFi12RBtnhluIGYLuc8MNN1BdXc1bb72F0Whk1qxZXH755SxZsgQAu93OAw880MejFAhOTgLBEF/uqOS0Eendcix0RIwzo1XMlBoxBZHODIBGh494q0lzcqhihtpLcTRnRl6G4oZQ+ypKqx09Uv4NijMXlC6O2iblO1Gng8T43pvUkWi3UNMY+T4Wzozuo8RoKjYba+5IbXmgvgJD7qjjdl6148KUEtsHq8ZEdTVmKhje3hgVM6UzGDGlZBGor8BfV078sDO6M+Q+oUMx46abbuIPf/gD8+bN014f6QGravvau3dvz49SIDiBkGWZD9cX8vePdnW4zYWT8ki0mbl06mBtFmacxRhTEnWq09jYyLJly6isrARg0KBBzJ8/n6Sk3n0wIxAIusYvf/lLDAYDn3zyCWeeeSa/+c1vMBqNOJ1Otm7dyh133MEtt9zS18MUCHqN3IwEpk0YSFlhGikGN3sDOUw9XYmnykyJx2jQEQzJVNQ6uy9mZAwCnR5kCV91Ya/enMjBAO5D3wHgKdwOp7iYEXQ2EWqpA8A+/nyaN31wQmcTd4TkUzszdIBMyN2i3RcKBMdKY2Mj9913H3fffTdGo/LI4qmnnuKGG26gqamJM844g7S0tD4epUBw8iHLMn/653es317B2WMzeei2KT1+Dqe745gptyfizMhOi1wTNTl8JNktWoST2pmREhUz1d53T3lN2JkRFjEGZSn/X13vojocyZSWFNet96MWgAMcblC+ExPizRgMvfddn2SLFU6EmNF91L4MAGNSOgZ7CiFnI/66cqzHUcwIOZUIWkNCasxy1VnR1QJwNZYqOmYKwDQgl0B9BYETdKJNh2LGE088wemnn669fvzxx8VFqUDQCb4/VBcjZMRZDHh8IX48ezSDshKYOj4bfTdjJE4FKisrNSFj+vTpzJw5E73+5Ln5FwhOZu68807uvPPOmGVjxoxh06ZNmEzi4lpw6nHNRSN4YteZNEo2tujPZP4Q5SGcwaAne4CNssNOymucTBqT2a3z6E0W5eakthRfdVGXxIyQq5maj5cQbK5h4E3/D0N84tF3isJbsR85oMyM9FUXIvk96M3de0BwIuOvDkdM6Q3Yx55L86YPkAM+gi11mJJOPDt/R6hihuI+qQdZQvK5MVi7J8wJTm2uuuoqrr32WhYuXBizfNKkSX00IoGg/yDLMnIocFziHD/bVsb67Uok4o4favEHQphNhh49x5EKwFVnhk6nCAIJ8WYcbj+NDi8piZGJn607M/xBCY8vGBMX5Q+ENHEhEjOlXNtIMuw8qEw4UJ0ZUsCH3tT1yaVqzBSgCSS9PUm19fls3YjN6ktkWVYe1sshbZnOHNela4qj/XeUpRDodEedWBIdo6m32DANyCXkbOx2ZKgsy8hBf7tjlEMBQq5mAIxtxIywM8PVeWeG5Pcg+73h/WN7/cxpObg5cSNQOxQzrrrqqpjX8+fPP+KBQqGQ9uBRIDgVcXsDfPjFIXYX1WvLfnr5WK6+cEQfjurEZdy4cVRXVzNkyBCGDh3a18MRCARdxOPxEBenPMhsbGxk5cqVGAwGLr30UpKTk4+yt0BwcjE8N5m8kSN4b18Sc88dEtONkZNup+ywk4ranikBt2QNJVBbiv9wYaf38deUUP3OE5q13bV/M4lnXNKl83oKd0ReyBLe8h+IHzqxS8c4mfBVKZ+/OX2QUhSvZhPXVZxkYoYSa2FKyVTEDJQScCFmCLpDQ0OD6OsUCDrg8LIn8RTtJOe2P2JOG9hjx62qc/HCezu11/6gxP6SRiYMH9Cl48iyzEcbCslIiWfqhOw2611HKAB3h8WMOIsRvV5HSqIFh9tPk8MX06+REB/bmQHQ5PTFiBkVtU7ksJNDLd1OSbBgjzPh9AQorFAeGqcmWvEU7aTqX78j6ezLSLv4p116v2oBOEScGcm9LGYkniTOjLqCF3F892nsQr2BrGv/k/jhZx51f+feTdS8/zQpM24g5dy2z7D9NSVUvLIY27hzyZh39xGPFStmxGFOy8Fb/H23nQx1K57HuWs9A295HEt27HOuYFSElCEh1n1oVJ0ZrhZkKYROf3SRMdrF0daZoZSA+09QMaPT05zHjBnDJ5980uH6999/nyuvvLJHBiUQnIi8tWofb6/ez44DisKfk24TQkYXqKmpYc2aNcjqFQdw0UUXCSFDIDjBaGlp4bbbbuPmm28GwOl0cvXVV/PYY4/x8MMPM2/ePMrKyvp4lAJB7/PAjZO4+7rTueXysTHLc8KZ0BU1PSVmKL0ZvurOlYC7fthCxesPakIGgLd0T5fP6ynaEfO6M8eQZRlf1SGkoP+o255oqOXfluxh6AwmLfv4ZOvNUJ0ZxuRItnPI3dJXwxGcJMybN4+lS5dSXn5y/XsRCLqLLMu4D36HHPDh2vd1jx03GJJ46u1teHwhUhMtDAzHXu44UHuUPdtyoKyJv324iz++tY1gSGqz/ojOjHDMlCpKqKJAo8NHs1PZNs5i0NwiqjMD2vZmlB92ho9l1OKodDqdFjWlkppkxVP8PUhBHN9/EfM8ojNYLe05M3qvLwPaihknYgG4LIVw7trQdoUUwl34XaeO4fz+C5Al3Ae3tbveffBb5FAA587Pteu0jlA6M0BniUenN2BK65mH/+6DW5FDgTbXzaB03qm0cWZonRcyIVfnrrPUiKnY/RXMabkASO6WE/K6rUNnxuHDh7XSXVD+aG7ZsoVgMNhmW0mS+Pjjj0UMleCU5fNvy/loQ2QG5HkTB3LxOYP6cEQnDrIs8+2337Jq1SqCwSDJycnCQi4QnMD86U9/YvPmzfz85z8H0LpvfvOb3zB+/Hh+/etf86c//Ymnnnqqj0cqEPQu9jgTsybnt1muRh+ouc7dxRwWM4KN1UheF/p2ZsjLsoS/ugjnno00f/0xIGNIHED80NNxbF+Dp2R3l3oPQm6H5kQwpQ8iUFuKt+zoPXqOHWupW/E88cPPIuv6Bzv/Jk8AosUMOPGziTtCVsUMezI6oxk56Bcl4IJuo9frKSwsZPbs2QwaNIi0tLQ2cbM6nY7XX3+9j0YoEPQNkscJkvJMzlu2BzhygkpnWfrpD+wvUWaF/2rBmWzbV8OH6w9pUUxdoeyw8h3gD4RwuPyktCrYdnbCmWGzKo8qUxKUfaOdGWpfBoDZZCDeasTtDbYVM8LXVXkZCTHXM4OyEtlTFHlonJpoJVSuuDQkdwuB+grMA3I7/X4tJgM6HcgyVNeHnRkJfRszFW/t8FFvv8VfXYQcUCKRBv70CQzxiTRueAfn918QbD7676EsS3jLlWvPaFEgmmDU8qav3iPz6l93eLyQVxHDVKep6mQINtUgBf3HFPMWHSMVbGn7ntTx6a029ObYfzfRzoqQsxFjQmxsVHuoTg+91d5mvKo4A+FS8y7Gy/Y1Hf6Gp6am8sILL1BcXAwoFwtLly5l6dKlHR7spptu6vEBCgT9HV8gxBsrI7MPb507lvkXCEdGZ/B6vXzyySfs3r0bgOTkZLKyso6yl0Ag6M+sW7eOG2+8kXvuuQeANWvWkJaWxs9+9jMAfvKTn/Dqq6/25RAFgn5FTroyQ7DR4cPtDcREJBwLlswh2s++mmLiBo3TXnvL99Hy3ad4Dn2n3UwBWHJGknnNbwg5G3FsX0PIUU+w6bDmJjganuKdgIzOaCZ52lXUfvgsvoofkIMBdMaO34/juzUAuA9uw1Oyi7j88V18t/2ToKNRK3C0ZCkO0xM9m7gjVGeG3mpDH5dAyFFPyHPizfAT9C++/PJLUlKUBzU+n0/EWQsEYaLz8r3l+zsdNxPNwbIm/rFqLz6/0ksgyzL7ipXvrCtnDOOMURkEQxIfrj/ED6WNXb42UR/oAzS3J2ZEF4C36cyIdWaoPRmNDi8tLkWsaO1CSLJbFDHDGStmlIUdrznhSSMqgzJbOTMSrYTckWsib+meLokZOp0Oq1npSfX4lPH3dszUyVAA7glPgjEmZWDNGQkoUZ1AjHu4IwJ15YrYBwSdDciy1KYXI+iIRMK79m3GX1fe4X9rtQBcb1HEDNXJgCwRbKjCnNF2gtLRCDoi/37be0+qCNO6/BsUQQKDEULBTvdmqDFTrSOmQInOMiSkEXLUK6XmeWM6dcz+Qodihslk4pVXXqG8vBxZlrnlllv4xS9+wbnnnttmW71eT2pqqoiDEZySfPD5QWoblbzg00emCyGjk1RUVLBs2TKampQ/sGPHjmXevHlYrdaj7CkQCPoz9fX1jBih/B10OBxs376dOXPmaOtTUlLweDx9NTyBoN8RfZNdXuNk5KCjz7Q6EnpLPMaULIKN1firizQxw19XTuU/HgIpUqpoTMnCPmYaydOvRW80Y4hPRG+JR/K58ZbuaSNm+OvK8ZbvI+G0C2Ienqh9Gda8McQPUXoy5FAAX9XBDm+OAk01+CoPaK8bv/gX1pv+30nh9PZp5d9G7WbXFL5ZPvlippS/53pzHAZNzBDODEH3WLduXV8PQSDol0Rn4Ms+N/6aUi1esrO8//lBvt1X02b50IFJ3DxH+c4eNzQNvV5HSJLZU9TApDGZnT7+4YZI14AqQETjjBIwPL4QgWAIk1G5ptCcGXGxMVNNzmhnRuyD+2S7hao6V8fOjFbiReuYqbQka8wED2/ZXhLPnHXE9ygFfNR88CcsWUNJmX4tFrMRjy9yfdXnBeC9IGbIoQA1Hy/Bf7g4Zrklezjp8xa2W7DdtPkjfJUHSb/8TvTmuJh1qqPXOihy3WhMVPpa2nMxtMZbGuUIDgWR3A4MtqSYbWIdGzJNm97vsDtD7cz4/+y9eZgU9b22f1fv20zPyjArM2yyCS4oAqKgRsVgokajySG8eXPMcoyJMRpN/OU9SYwJmmhyPJqjiR4TPYIikMWjISoaBRVBVHYYlhmYfe2Znul9qfr9UV3VXb3MwiKgdV+Xl0x3dXX1LN1V3+fzPI/icDbmFSFY7EiRIJHe1qMSM1KfPzaQKWYoYkt6xBTIopnJWUBsoIdYyvtAtK+Dnn88ifu8xTgmnqt9voQzI738W8FSUklwsFczaJPz51oxmdIlt5wy5+lDeo8qKiqoqJALhZYvX87s2bOprq7+WA5MR+dUp6c/SCwu0tyZzLj+/EUTTuIRnR5IksSmTZt4/fXXEUURk8nEFVdcwbnnnnvKvDHq6OgcPWVlZWonxvr164nH4yxcuFC9/8MPP6S8PLMMUEfn00q+00Kew8JgIEJr97GLGSD3ZsT6OjS9Gf3vrAUxjjGviIK51+CYcDbmIm1xqGAwYqueKjslmvaQN+sS9T5JEuWS8L4OYn2dFC36l8Ttkpr7ax8/C6PTjbm4gmhvG8GmvTnFDP8+Oc5WiSYKNe8l2LANx4Szj/n1n2yUiCnLmHGqM0WZ/BODg8T93owL7NMV1ZlhdWB0yAtEesyUjo6OzokhtSAY5AXg0YoZ3f2yCD1rUgnTx8uLxSajwCWzq1VRwWEzM6m6gPojfWw/0D1KMSPpzBjwZ3ZipcZMKdsUu+WF7YDqzEjETCnOjIEhxIxEpFOqmBEXJbWLrDrdmZEmZhTm2+gMaMWM4Qge2kZg/xYCB7ZSMP867BYT/SSf/+MWM/JTOjpMRgGreXRunaNhcOdb+He/nXF7tKeF/HOvUN0VCmI0jOf1/wFJxFY9Fffsxep9kiQlxYyU80aTu1R+bHAQMRLKiF5KJf3nFhvszTjXUsQCa9UUwi378O3aSOFFN2J2j8nYn9KZYbA5AFlMsBRXEm4/eNSRoanOkGzRWUrMlNFVnHGffHshsYEeVaQA6Nv4AsGGjxBDvgwxQxE9TM5MZwaAubiKYOMOzaDN4M4N2X+unnaKP/NVNXbrZDPiILVrr732RB6Hjs5pQ1yU+NkTm/hov1ZJvXBWxag+5D+tBINBNm3ahCiKlJSUcP3111NWpn/fdHQ+KSxatIinn34an8/Hyy+/jNvt5pJLLqGzs5MnnniCv/3tb9xyyy0n+zB1dE4pqsa42HvYcxxLwMfj37uJcIfcYxH1tOFLXJgUXfwljUiRjm3cdAIHPyDUtFtze6h5H7G+DkCerMs761LMhWOJetrUiTl7wpVhq55GtLdNLgGfnz3P27/nHQDyZl1CpLeV0OGdeN58Dvv4s0774YaI2peRdK2nZhNHelqwfwLFDEMib/l0LJLUObVYtmzZiLZ75plnTvCR6OicWqQW+oLcm+E+76ocW2enb1DuJbhwViVXzq3Nud2sSaXUH+ljx4HR9WakihlKabdCNCYSisQ1tw0GoqqY4Vc7MxRnhi2xn7AaI5UuFKhiRkrMVHdfgEhMLh+vSnNmFLis6hCJy27GajZqCpVj3m5iAz2qKyAbkd7E4q8kEg8MaErAlef4OHGn9Ig47eYTfh4liXH63/0LIJ/7OSafD0D/2y8Q93uJdDRmiBmRriaQ5J9JoH6zRsyI9rYiJs4dNGJGys8gNtAzZPxXMEPM8KhRn8oxK86mgnnX0rPu98QHPXjfe5GSK27O2J+Y6MxI7Z4zl1QRbj941C7b1M4OMRzI6LaLD+R2ZkAyLkp5H5DiMQIHtgIQ7e/M2F6Jo8oWMwWyMwOSEaiSGMe7Sfm5zsQxeY66rbV8/CkjZMAQYsbUqVP51a9+xdVXXw3AlClThv2DEASBPXv2DLmNjs7pzFsftvDgig+y3jdjQu4PO50kDoeDa6+9ll27dnHllVdisYy+OElHR+fU5Qc/+AHBYJA1a9ZQVlbGT3/6U2w2G/v372fFihV87nOfU8vBdXR0ZCpLZTGjpTspZvgCEda8cYALZpQzpTb7RU0uLImLt2hPC2I0LF9wSiImdymuGRcN+VhbIpYq1t+luZj37XwruVE8Ru/6PzH2hh+qEVNGZ4FqubfVTGNw23pCLfuy5nlH+zpU94Jz6jxcRhNth3cS6ThEoH4LzilzOF2RJCmj/BvAYLFhcpcS83YT7WnBPm56rl2cNkjxGFJMXqgSrHLMFKDHTOkcMy0tmQtFoijS19dHOBymsrJSjbTU0fk0kRozBXK0jiRJmrW6Lk+AHQe7uejsKixpE/qSJOHxymJGkXvoeOeZE0t4Yf1+Gtq8DPgjGY6IbESicXoT+4dMZ4YvmOnUSC0BDyRcG+nOjLgo0ZY4R0o/jkJXpjOjJTEcYjIKjC1yaLYXBIGasXnsbuil2G1DjITU4mmFUNNeXDMW5HydqZP5cb8Xm0W7tOrO+3jXOBw2EyajQCwuqULQicS/773EgItA8eVfU0WGYMNHBA5sJdzZmPGYSMptwSO7iQcH1fMGxVVhcORrhj+MeYVgMIEYI+btzilmRL1dxJUoKsEgi0xpJeBxv1cVU8wFY3DP+Rye9X9icNvrFMy/HlPagn8yZirp7FGOLdp7dD1O6ccUG+jBkiIQKGJHTjHDKbu3FWdGsGm3epxiYAAxHMBgTf6+Jzszsru+ldcT6+9GjIYJHNhK1NMOQPFnvoal9NRNZsopZlxzzTXU1NRovj7dp6R0dI6Vla/s03x911dmc8a4Qqxm48duJTxdEEWRd955h7POOou8PPnDavz48XrHjo7OJxSLxcJ9993Hfffdp7l9ypQpbNiwgdLS0pN0ZDo6py5Kb4bizJAkif94/iM27+7g7+828qvvXERtef6I96eWgEsigYMfMJgQIgrmXotgHNqYbR1bh2CxIUVCBI/sJu/MixGjYfx73wXAVnsmocM7Cex/n0DD9mTEVN1M9VpByTuWIkEinUc0DgUA/145YsroLMBWPQXBYMQx8VwCBz/As+E5HJNnqwJItgLHU5n4oEedmEsVM0C288e83cmJztMcpS8DtM4MURczdI6RXJ0Z8Xic119/nR//+Mf867/+68d8VDo6Jx9lEdNaPoFw+yHi/n5i/Z2ajqvfrdnOh/VdROMSi9OcF/5QTHUsFOUNLWZMqS3CbDIQjYnsPNjD/FkVQ24P0NUX0Hyd3pmRWv6tbpPSoRFIKwBXXBeQLBbPGTOV4sxo7pQ/h8pLXBiNmecQteX5sphRYNeUfyudY8HmPUOLGSkdA/GAF5vl5DozBEEg32nFMxBS+zLifi8D29bjmr4Ac0FmjNLRIkkS/e/8GQDHGedrBAZLWR2BA1uJdGSKGRqBQxIJHPiAvJkLATQRU6nrzoJgwJRfJA/YDFECHmqW1+kEix3LmBrCLfWaSCfQuiKMecXkn30Z/e+sRQwOMvD+SxQtWqrZXnGeGq1JsSHVyXA056fpxxT1dquDQJIkDVkADkmHhRIfFajfot1fX4fGjaJ2ZuSKmVJ/dhLR3taUn+ucU1rIgCHEjOXLl2u+vv/++0/4wejonMo0tHpp65FVzzPGFfKLf5v/sWQRns4MDAywdu1ampqaaGxsZOnSpRgMp8+ChI6OztHT39/Pu+++S2trK2azmfLycubPn3+yD0tH55SkslQWM9p6/IiixJsftrB5txzpFAzH+flTm/nNbReNeHDC6HRjzCsmPthL7ytPql0ZQ8VLKQgGI7aqKQQbthFq2kPemRcTOLBVvqgzGCm75nY6//wgoaY99L72VEbEFIDZPQZTfgmxgR5CzXsyxAxfQhhxTp2rihaFF99E4OAHRLub6frLbxAjIaK9coRV3lmXUnrVt0b02odDkiRAOmECiRLthdGUcSFoKakk2PAR0Z7WLI88/RDDyZJXg9WRdGboMVM6Jwij0cjll1/O9u3befDBB1m1atXJPiQdnY+VWEIst9WeSbSvEzHkI9S0RyNmtPXIgxEtnZnCct9A0oGguB5yYTUbmVpbxI6DPWw/2D0iMSM1YgpgIC1mKlXMKHbb6PWGNM6MZMyUvFSZ77RiEECUkvvId2qP253FmXGoRRYoqsu0fRkKSy6swzMQ4nMLxhP3Jxe5nVMuwLvpr0P2ZkiSRCRFzBD9A9isyWOymAzYrSNO9D9u5DstGjHD8+ZKBretJ9rTwpjP33bcnid46EMiXYcBKJinjRJV+lsi3U0Zztx0gcNfvzkpZjRl9mUomPJLVbdwLtTHV52BweYkTH2mMyMhJAhmKwarA0EQcJ93FX0bVjG4480MMSOuOjOSTgdLqTzwL8Ui9L+9hsIFX8x5TNnIcGak9GaIQR9SXP79N+Vl78wwJRwWcX8/kiTizxAzOlUxQxLj6vlYrpgpo7MAg82JGPLj3fJSzp/rqcgxncVHo1HefPNNNmzYQCwWO17HpKNz0glFYrT3+DX/fe+3b6r3X33heF3IGIb6+noef/xxmpqaALkUWF5A0NHR+aSzcuVKFi1axB133MFDDz3E/fffz2233cb8+fNZsWLFyT48HZ1TjqqEMyMSjbO/qY8//HUnANPHF2O1GOnyBPjln7YQTUxTjgTlgjLuly/o8+d8nvue/pB///27hKPxoR6qRk0pvRlKxJRjwtkYnW6KP/M1EAxEe1qQIvLCSKqYIe9jGgDBJm0EbdTTTiSx4O+cOi/leMfjnDIXkOMLgg3biHm7QBIZ3P5P9QLvWJAkiY7n76P50X87YQvu4faDAFjH1CIYtVEPygTc0WYtn2qkOzPUAnDdmaFzgqmtrWXfvn3Db6ij8wlDmbQ25RVhqzoDyCw+VnoqerxB0vEkxAxBGJl7YOYkOWpyx4HcU/GpZIgZOWKmLCYDxYmYq9RtAgkxw5FYkDcaBPLTjjOXMyMYjhGOxtl+oJsN2+TP2el12ReFq8bkcc9Xz2fGhBL1PEkwW3FMOBuAaHcz8UD2z7L4YK967gOZzgx3nvWkpNq4EyXgTrsZSYzjr98MHH0kUjYkSaLvnbWAfN5nq5ioud+ScAZLsYjGvSKJcSJdRwDUfo1gwzbESIjYQK98vkcOMSNRAj60M2OP+nhFCIilCwcpEU5JJ7F8vhv39SHFtOeZWTszisrVuNa+Davo3/xizmPKRsYxDXSn3Jd0beR0ZiQcFnFfH+G2g8R98v4MiWESpdsOEoMliVgtU46YKUEQ1Kgp5VzfXjcz4+d6KjJiuTASiXDffffR0tLCU089RSQS4cYbb1RPIiZMmMDTTz9NcXH2NwsdndMFXzDKN365nsFAZp4jgN1q1Iu+hyAWi7F+/Xo2b5Y/PO12O9dccw2TJ08e5pE6OjqfBNavX8+9997LtGnTuPnmmxk/fjySJNHQ0MAf//hH7rvvPioqKli0aNHJPlQdnVOGscVODAYBUZR44Jn38Qej5Dst/HDZeexp7GX50++zp9HDY2u3850vjqwg2zJ2vFoKaHQW0F16Hlv2vAfAhg9b+MyccTkfax83jT5k4SHceZjAoY8AcJ15MSALJXlnXcbgR6/KzzWmBlOe9kLJVj0V364GsgI/AAAgAElEQVQNhJq1ed4+JWLKVYSteormMUWXLZMvHg0mzMUVmPKK8LzxPyDGiPS0Yi2rHfZ1D0V80EOwYRsAgQNbR+RUEcMBor1tWMonjOj7HumShzgsWY5ViWKID/YihoMYrPZRHP2phxLBAGCw2jHYlQLwwdMuHkzn9CESifDiiy/q6w46n0pSM/BtNdMIHPxAI2ZEY3GCYXnQuLc/lPF4xZnhdlmzxi+lM2tSKc+u20drt5+e/iAlBUN/bilRUAqZYoa8YOxymMlzyIvvqesu/kTMVGrvQ4HLqnFd5BIzQI6X+u1zHyJJMKm6gKvm1w37GpWYKaPDjbViktrREGrZh3PyeRnbR9LclXG/F5s16cQ8WfHjpQWyg6Ao30aoea86WJC6YH6shJr3EG6pB6Bgfub0vsldisHmQgz5CHc0qk6GqKdd7dgqvPAGAgc/QIpFCDZsU4dVBLNNHcTR7DPR3ZbLmREPDKodJrbqqapDNl04yBbhlNpNEfN5MBck1/nEkPy7nNqZAVC65NuI4QCBA1vxrH8ag9lG/jmXZz22VDQxUk43cb9XI9Corg2DCaMze7Ss0n0hRcP4drwJgLm0GnNRBYH6zZoS8NR+HaVrIxvm4irCrfvVr08HVwaMQsx49NFHeeGFF/jCF74AwF//+lf27t3LsmXLmDp1Kvfffz8PP/ww99577wk7WB2dE83Bln4+qu/KKWQ4bCYeuXORat3T0dLb28vatWtpb5dLg8aNG8d1111Hfv7Ic751dHROb5544gmmTZvG888/j8WSvNiYOnUql19+OTfeeCNPPvnkiMWMl156iccee4zm5mYqKyv55je/yTXXXJNze1EU+f3vf8+aNWvo7u5m3LhxfOtb3+Kzn/2suo3P5+N3v/sdr732Gj09PVRXV/OlL32JL33pS3o/mM5JwWwyUFbkoL3HT0+iOPPfvjCTgjwr82ZWsHTxFJ5dt4/XtjRRNSaP6xYNPzGl9mYA7gs+x9ttyUigFzc2cNn5NTl/363lExBMFqRYhJ5//AEkEYPVgWPSbHWbooVfwr/3HcSQH3vdWRn7UJwZYmCAaG+rupDvT42YSlvsNrvHUP4vP1W/liSJ/vf+hhgYINLRcMxiRqS7Sf13sGn3iMSMzrW/Jti4g/xzr6T4ipuHfY9QLqizZQ2bi5O50pHe1tNi8m0oFDFDMNsQDEbVmYEkIoYCGO3Z4z10dIZj2bJlWW+PRCI0NjYyMDDAd77znY/5qHR0TgwxbzeR7mbNbeaSSs3CKoAUi6rT4kZngTqBHvW0E/P1YXIVasSDoZwZRflD92UoTKoqwG41EQzH2HGwh0tmD52j3+mRzzWsFiPhSBxvWmeGss7iclhUUUI55lhcJByRnaNKAThAYZ6Vw+3JfbhdVnmiv78Tc2mNxmHym5Uf0OsNYbMYuXPpuZhGINjE/YkoHqcbg9kq95G01hNq3ptVzIim9V6lF4DncrzEBvuQYmFNJNjx5IuXTaYw38qVc2vxv/+c5vjEaBiDWXtckiQR6TqCubgCg2lkheVKp4K1crLqakhFEAQsZbWEjuySC78TQzBKxJTB6sAytg77uBkEG7fjr9+MwSILZLaqyZpYKoXhnBmqmGcwYa2YqPaWZUQ6qc6MpBCeKmzEB5NihhSPqaXwqTFTAILRxJjr7qBz1S8JHt5Jz7o/IFhs5CUcG7lIjZGyVp5BYP8WTcxU8vgKcw6DpJaUD+6SnRTOyXPU/WqcGYnvAwYThiHOx5QeEPm4JmMbN2PI13GqMGIxY926dVx//fVqoecrr7xCXl4ed911FyaTiebmZlavXn3CDlRH50RzsLmf2//jLc1tf/jRZZoPwDynWfNBpaPlnXfeob29HUEQuOiii7jooov0jgwdnU8Z+/bt4/vf/75GyFAwm818/vOf5+GHHx7RvtatW8edd97JsmXLWLBgAevXr+fuu+/GZrNx5ZVXZn3ML3/5S1atWsX3v/99pkyZwssvv8wdd9yBy+Xi4ovlE+rbb7+dHTt28N3vfpfx48fz7rvv8vOf/5zBwUG++c1vHv2L19E5BipLXbQnurkWnFXJhbOSFxdfvHQyTe2DbNjWyh9f2o3damTxvKGnDW010xJZuA7yz7mcA2uTk5uH2wfYdaiXMyeWZH2sYDRjqzqD4OGd6gSec9p8zcWu0ZFP2XV3Mrjjn7gv+HzGPszFlRgc+YiBAfreXo193AwEg1G+uAVc0+ZlPCbjOAQBa1kdwcbthDsbyRv2EUOTKmaEjuwZYkuZcPshgo07ABj44B8gGCi+/Gs5BQ0pFiWauJA0l2Qu+Bgdeer3JNrTcvqLGRF5oUxxmBgdyeEVMTioixk6R01LS/YoNqPRyPjx41myZAlf/vKXP+aj0tE5/sQDgzT/4XakiFZ4EIxmqm99TBMPE/P3qf82uQowuUvVwYNQ8z5cU+eqEVMguzDicVHjwPAMyOLCSMUMo9HA9PHFbN3byUf1XSMQM2SRe2JVAbsbehnwRzTuTH+iM8NlN5Pn1DozlPJvQDM8WphyrAZBvq9r7QME9r9P2Rd/hGPiuVjMRiLROM2dstjzzWvPpKJkZJ9BSWeG/Blmq5mqihnZSO+9ige82N0pMVOuzGsgMRah9b/vQAwFqL7ld5jyj7+zrLzEybKrpiFJEk1pXQqxgV4sxdrOk8D+9+lc8wDmkioqlt6L0ekecv++XRtVd2vBvOtyD8QkxIxw52H1tnCn7JawlNUhCALOM84n2LidwMEP1OikbBFTACa34szozejhgKSYYa2YgMFsVcUKMeTTiDhKZ0aqgGEwW1UnSaqTQ+s8TcZMqbeZLJTd8EPan7uXcEs93S8+gnXseE0ZejqpMVK2qoSYMZDpzMgVMQXaIm8l6sx5xhw14jTal+rMSJR/uwqGHMRRYqZg6J/rqcaIV2U7Ojo46yx56ioYDPL++++zcOFCTCZ5F+Xl5QwM6GVvOqcvHZ7kxKLLbmb+rArKSzLfuHRyc8UVV+DxeFi4cCG1tbUn+3B0dHROAhaLhWAwcxJMwe/3YzSOrHPoN7/5DYsXL+aee+4BYMGCBXi9Xh5++OGsYkZTUxMrVqzg3nvv5YYbbgBg7ty5HD58mI0bN3LxxRezd+9eNmzYwH/8x3+wePFidZuBgQGeeOIJXczQOWmMG5vH1r2dFORZ+dZ1MzX3CYLAd286m35fmB0He/ivtTswGQ1DRkUZ7S5qbn0cSRIxmK0caO7T3P/ixkM5xQyQxZDg4Z3q13mJ6bpU7HUzsdfNzLhdOWZ7zTT8+97Dv/tt/LvfTh5bXjHWypHFT1rKagk2bieSclF8tCgRUAAxbxcxb7c68ZcN7/svy/8wmiAeY2Dr38FgoPiyr2a92It62tV84lwXtJaSKkJNezImO09H1AgGqzy1qGQ2A8SDg5gpPynHpXP688Ybb5zsQ9DR+VgINu1ShQwhMTAgxSJI8SiRjkZME5NihiY2xlWIYDRjrZhEqGk3oeY9CTEj6YQQJVm8KC1MRkMpMVOFeSOPQjp3yhi27u3kzQ9bOHNiCZcPce7RmYiZmlQtixnRmEgoElcLsQcTMVN5Dgv5Dq0zQ+nLAHCkxUwpuBwWjAaBULMcdx/pPIxz0mwK8qx0JYSU+bMquPS8mhG/PmWCXVnMt1VPxbvpr4TbD2V1NESUz+9EHFXc78VaOrQzI9LVpHZzhFr24Zo2f8THN1oi7YeIp0UyxQa6M8SMUIssAkR7Wmh/7ueUL/0ZRlv29S9//Wa6XvxPQD4/dEw6N+fzW5QS8I5GVchSnBnKfY7Jc+AfTyKG/IiJou3cYkbiPE0Sifv61Ngp9XU0a8vD090WhiL5XCSbM0PZXhYzkmKD4oACcn5PDBYb5Tf+f7T89w+I9XfSv+kvjLk6t2MwNUZKKemOD/YhxaMIRrP6/KYhxAzBZMZgdyEG5eMzuUuxjK0jHlIixXqS+0u8X5ic2cu/Fex1M7FVT8WYXzzkz/VUY8Qj0yUlJfT0yH8QGzduJBKJsHDhQvX++vp6xowZc9wPUEfnRBMIRVnxj338Y9NhQM5gfO6+q7j1hszIBB0tnZ2d1NfXq19brVa++tWv6kKGjs6nmPPOO48VK1bQ1dWVcV9nZycrV67k3HOHP1Fqbm6mqamJyy/XZpBeccUVNDQ00NzcnPGY9evXY7PZMmKonn32WX784x8DsqX6xhtvZO7cuZptxo8fz+DgIH192gVfHZ2Pi89fPIHPLRjPT2++ICMPGsBqNvL/vjaH6ePli7BHVm/jja1NGdulIpjMGMxWAqEoLV3yhc+Vc2sB2Ly7g45ef87HpsYHmArGYK2aknPbXBRedBPOqfOwVk7GVDBGXqgRDBRc8LkR9yko+cnhzsNI0sgL0LOhlE8qBBMF59mI+frw7X4HgJIrblYjqQa2vITn9WeQJClz/z3y+5JgseecrFNKwH27NuL55wr89VuI+U7P9x0pkiZmmK3qYtyJKljX+fTQ1tbGgw8+iNfrVW974okneOCBB+jt7R3ikTo6pw+hpsRCbM006u5+jrq7n8NcJC86R1MiYyApZghmWzKaJ7GAq+zHm9ZR0ZsWNeUZHF3MFMDlc8YxMzH88OjqbWz4KLsY7wtG1U6MydVJESY1+sqXcGE4U50Z/izOjNSYqfykOJDvtMgL4Ik+COWzRhFnSgrs3Hr9rFFNl4sJkUEVMxLF6ohxTZeAguLMsCbclXG/F7s11ZmRRcxI9DgAqkP1RKEUf5uLKzAqfRNZIppSp/gjnY10PH+f6rhMJdCwjc6//AYkEUtZHWU3/HDIczhrmbxQL4Z8xAa6kSRJdWkocaGmvELtUIvBlHPIJVW8SI1lAhAjIbUjw149Td23un2K2yK1AFyz/8TXqbFU8VCKM8OW2+FjsDnVjgnfzg1E+zOvfzOfvxBTgbJ2Lqm3x1RnxtCunVR3huOMOXKJtxJdJonqzzruTzozhsJgtlKx7D7Krrn9tOo6G7EzY86cOTz99NNYrVZWrFiB3W7nsssuY2BggLVr1/LCCy9w0003nchj1dE5IWzc1srzryUX5G1WPUZqOCRJYuvWrbzyyisYjUa+8Y1v6CV8Ojo6AHzve9/jxhtvZPHixVxzzTWquNnQ0MCLL75IPB7ntttuG3Y/DQ3yiWldnTZKZ9w4eRqssbGR6mqt1b2+vp66ujreffddHnroIQ4ePEhVVRXf+973uOqqqwCYNm1a1n6v9evXU1paSkHB0Cd8OjonisI8G1+/5swht7FZTfz7v87hp0+8x97DHh5+/iN2N3iwmAzEJQkkeYJyzgztRPzBln6UtfevLJ7K+3s66PWGePmdRv71c9mzca2VkxCMZqR4FNeZC4/Kdm4prabsujvUryVJAjGOYBz5uZYl0f0hhQPE+ruOOmtaEuNqn4VgtiJFw4SO7CHvzIVZtx/48FUQYxjsebhmXETeWZciSSK+HW/i3fwilrLaDLdKROnLKKnK+f2yVU5m8MNXiQ300P/un9XbDXYXJncZ5sIxmArKcE2br07unaooMQyKmAFgcOQTH+hB1MUMnWNg//79fOUrX8Hn87FkyRLcbnmR0ev1smLFCl566SVWrlyZcR6go3O6kT5VDmAqLCPqadOU+YI2NkbBVjMV3pHFejEcYMCn7ahI781QnRmjEDMsZiM//toc/t/v36X+SB+/WfkhVrMx41yjM2VAYlJN8hi9vjBlRfLnxFAF4P4UZ4Y9hzPD7bJqFuGVz5rPLRjP36RDfOOaM3E5Rtb/oKDETBkc8vuM0Z6HubSGaHcToea92GuT52bxoE91cthrphFu2Uc84NWsIRVkcb2EUwSMcMcJFjP2yxFTzjPmEGreR3ygJ0MEgGS/gq1mGqGmvYRb99Pxwv2M/eKPEEzy9z/Uso/O1Q9APIa5pIryL/2/nE4FBXNJpXr+GOloRBAMqvhkSelzc55xPuFWeR3OWj4+wwGjYDBb1YjOmLcbqpPDNeG2AyDGAQFr4nbBaFa3VwQKMRxUHVDpwyaKmKGJmUq4RRAMCJah/1byzryYvo2riA968L73N0qu/HrW7WIpMVep7pCYtxtzQZl6rEM5M0B2ZSnns84zzpcfk18CBiOIcaJ9nZiLKlLeL3KXf5/OjFh2ueeee5gyZQoPPPAAHo+Hn//85+Tn53PgwAEeeOABZs2axa233noij1VH57gRi4t8WN/Fn/95kEdXbwfk6YCLz67i367LHpegIxMKhVi9ejV///vficfjOJ1OotHo8A/U0dH5VDB58mSefvppJkyYwIoVK/jFL37BL37xC5577jnq6ur405/+xNSp2W3EqQwOyie9Lpd2GsbplE+gfT5fxmM8Hg/t7e3cc889LF26lCeffJLp06dz++2389577+V8rqeffpotW7bw9a9//bTJCdX59OKwmfnp1y9gck0BogSvbj7CS+80su7dw6zbdJj7n9mqTj4qHGiSL7yrxrjId1r47Hz5YvK1zUcIhuVJyLgosWlnG8/8fQ9P/e9u/vvlevaWXEpfwRQcZ19xXI5dEIRRCRkA5qJyhMQFbvgYphmjnna1INE1QxYhcjkzpFiUwQ9fASD/7M/IjgPBQOlnb1FjtQIHtmY+R+Li0jxEZrLrzIsp+8Jd5J/3WawVk+QIK+RiyEjHIfx7N+Hd9Fc6Vi3P6v6QJJGeV5+i7+01I33pJwwxrO3MAHkRCOQFHx2do+Whhx7C6XTy8ssvM2VKcuHqzjvv5OWXX8ZsNvPggw+exCPU0Tl2xHBAjVBMFTOUEuJYmjMjllhET+3RsFWeAYIBJJFQS32GM6OnP6T5erQF4Ap2q4mf3nwB4yvcxEWJ+5/Zyrb92il0pS/DZjFSVuRQu0e1zoyUmKmEM8MXjBIXJQIJocNuNWI0JM/HC/OSx5rvtBDtTyk5DspixkVnV/HQbRdzxrihF4KzoRSAp8bx2FXHi7ZfK9qb7Muw1chOACkaxmZIukqyOzOS5y/HIzYzF5HeVvVcxDF5jupqSO1mAHm4RBGF8s+7ipKrvgVA6MguDv/6X2hc/kUal3+R9v/5d6RYBFNBGeVf/smwvRoAgsGIZYwc8xXuPJwUb4wmTQSn84w56r9zRUwpmPJLs74OxZFkGVOjEVkUsUAREFIjpDJjpuSv45rODFnMMNgcw14bCiYzBYnuuMHtb6jxTunEU2KuBJNZFRkUoSnmG5mYofz9Gxz52BKuacFgVOO4lJ+r4uQyDhMzdboy4quJ/Px8/vjHP+LxeHC5XGqx59SpU1m1ahWzZs06YQepo3O8kC/S96pRC6mcMa6QO5eePhlxJ4OWlhbWrFmj2r1nzJjBkiVLsFpHnrmpo6PzyWfmzJm88MIL9Pb20traiiRJVFZWUlJSwnvvvcczzzzDsmXLhtyHsoiXfgKp3G4wZM5jRKNRPB4Pjz/+OIsWLQLkPoyGhgYeffRRLrjggozHPPvssyxfvpzFixcPe0w6OqcKDpuZn31jHs+/Wk+nx48gCBgEgS17OojGRLbu62LhOckLxgPN8gXNpGr5guaKC2p5/tV6/KEYr24+gtNmZs0bB2jtTj8/GgOM4do3W/na1SfnYki+KB5HuHW/vBgwZe7wD8qCUv4tmG3kzVzI4EevEuvrIDbQm1HE6dvzjpxtbTCSf26yn0cwGHFMmk2wcQfhtoOZz5HizMj5egQDzilzcE6RL+KlWJRI1xGife1E+7uIdjfj272RuM9DzNulLmophFv2M5Do8nCdeRFm98mL+c3mzFAKVMWg7szQOXq2bdvGLbfckjW6trq6Wh1Y0NE5nQm11Ms9S4IhGW0EmBIOxJzOjJTFSYPVjrmkkmh3M5GeZrw+bVdEasxUMBwjGI4DUJQ/+ut3l8PCvd+cyw9/9zYtXT4eWb2dJ++5TD1XV8SMscVOBEEg32nBMxDSihlB+d8uu1kVMyQJ/MEo/kTMlN1qTn1aCtJipmJ9SUEhHhgc9etIRZJENarK4MxXb7fVzmDgw1cINu9FDAfUzznlc97oKsRclHSm2KXk9zm9M0MS45qYy7i/n9hgnyYO6XgRSERMGfOKsFZMUBe4M+KZAgNIUVnYMheMxTqlDikaove1PwHaQQpTfgnl//LTYRfZU7GU1RFuP5RwZsi/H5bSGs1Ai7moHHvdTIKHd+Ec5tzO5C4h0nGIaFpcVqhZFpvSxRBTXhGRzkbVbaEKFYIhI3Yp6cxI6cxIDGRkK//ORt5Zl9H39hrE4CAD779E0aKlGdukd2KY8kuI+/rknotYVHUZDVUADmCtmIRv1wbyZi7SlKGbC8vk89qE2BfPIn5+khh1no7b7WbXrl20trZisVgYO3asLmTonBYEwzFeersxQ8gwmwzUjM3j29frv8e5kCSJd955hzfeeANJkjCZTCxevJizzz5bn2LW0dHJSXFxcUYE3bp163jhhReGFQ7y8uTp3nQHht/v19yfitPpxGg0Mn9+slRPEATmzZvHmjXaKWZRFPn1r3/NU089xZIlS3jggQf09zOd0wqX3czNn9dGRN373+/x/p5ONu9q14gZ+xPl35MSGdb5TgsLz63m1c1HePJvuzT7mFpbhMNmwmQ0MBiIsKfRw1/fOsjcGeVMrRv9xOPxwFJWK4sZxzDNqCwkWEqrsZZPQDDbkKIhQk17cM1YoG4nSRLeLS8B4Jw6N0PosFZMAuQC8bjfq04pSmKcaG8bMLQzIx3BZMZaMVHN3pbEOP79W5CiYcLtDRliRqgtmd8dbj1wVGJGzNtNxNOGoy73ua9S2jkUipghpMZM2WU33bEuMGmPRcSz/mkwGCm6ZOlplemsc3RIkkQ4HB7y/lAolPN+HZ3TAaXE2jJmnEYUVuIUY32dmvdiddI6bXHSlFdMtLuZ+KCHAb82irGnP7nIrkRMwehiplJxu6zc9ZXZfPehN+nyBGjqGGRcuSwCKD1cSqSU26WIGcm/5cGAEjNlUWOmAAb8YbUA3GnXLlOmigP5ToumS+RY+5nEoE8WlACjI+k6cIw/S3ZOxmMEDn2kFnYrzgxzcaXGpWCLJzsW3C5tzFXU044U0zpmIp0NmPKO/yCtf58sZjgnn48gGJLOjDQRIPV7qPy+uc9fgmPyecQGkov6giBgKZ+AwTS66C7r2DoGSThqE7+/1rK6jO3Krr8bMeTPONdKJ5soI8VjhBKdJopLRsGY1oOh9lE43RoBAJJOjfhgn/r3pg5rDNGXkYrBYsN9/hL63noO79Z/4J57bUYcVzytE8PkLiHcdoCYt1t1ZaQeTy7yZy/GPn5WRuyquWAsQbarP9tYlli6TxKjEjP++c9/8rOf/YzOTu2b6pgxY/jJT37CJZdcckIOUkfnWNh5qId7/usdzW3nTSvj0tk1zJ5WhtVszPFIHYXm5mZef/11QP57v/766yktLT3JR6Wjo/NJRunKaGpq4owzktNqR44c0dyfyrhx4xBFkVgspjpIQXZspC7KRaNR7rjjDl555RW+9rWvcdddd+lChs4ngjnTy3l/Tycf7OsiGotjNhnpHwzT3ScvZkxOybC+esF4Xt0s/z0ZBFhwVhU3XDpJXZQAOZbzjoc30NDq5eFVH/LwHYs0500bPmphy+5O/u/V0yh2J6OGjjfWssRF8QhypgOHPkIwWbCPm665PdIlOzMsY8YhGE3Yqs8g2LCdYNNujZgRat6rlnO6z/tsxv4tZbVgMIEYI9R2AOek2UDC1i/KU6VDOTOGQzAY5YnGln2E2w/imqqdVkx1hITbDqgLLCNFisdo+59/J+btonzpz7CPy+xM6d/0V/o3/ZWxX/yhGmGQDfVi35ISM5VwZhzPAvBQ8z5VYLLXzZQXmXQ+0cyaNYtVq1Zx0003kZ+fr7nP7/ezevVqfaBS57RH7cuo0U6VmwtlEVuKRYj7+pIFxX5FzMg1We5RXRAmo4FYXKTXmxQwPKliRt7RiRkAteX5lLht9HhDfLCvUz1vUJwZipihOC+UY5IkSY2ZcqUUgAMM+qNqZ4bDpnVm5DksGA0CcVEi32kl2pLZmXG0xBPl34BGnDBYHdhrZxI89CH++s1JMSO1G8tsQzBZkGIRSm1RnHYzBS4rBWnfWyViSrA6MLtLiXQdIdx5GMfE4ytmxAZ6CbfL5wjOKbIbXRUBBnqRJFEdBlAWvA2OfE1UpLmgLGOI4miwJDq/4gM9hKLhxG2Z124Giw3DMJ0UQNa4rHBHI1Ji3+nnKrliprK5SxThQ4pHEYODGB35ameG0ebI2D4X+edeSf+mvyBFggxsXUfhhddr7k8vIE/+bLo1EVfDdVwIgoCluDLjdtXR1deJGAkiRUIj2t/pyojHWrZu3cp3vvMdJEni9ttv53e/+x2PPPIIt99+O4Ig8N3vfpcPP/zwRB6rjs5R8egL2zJuu/S8GubPqtCFjBFSU1PDnDlzOOecc7j55pt1IUNHR+eEM27cOKqqqvjHP/6huf3VV1+ltraWioqKjMcsWLAASZJYt26delssFmPjxo2ce27yguGee+7h1Vdf5Uc/+hF33323LmTofGI4f3oZgiC7UXcelC/cDiRcGUaDQF1F8kK9tjyf73zxLL6waCKP//Ay7lx6rkbIAHkx5Hs3nY3JKNDa7efZdfLCSzQm8vifd/DrZz/grY9aePmdo+uyaGzz8o1frmfdu0M/Xr0o9nk0Cw+pSJKE563n6Xj+PtpX/ixjClGJmVJynG01stgRSunNkCQJ73t/A2QHhq1ycsbzGEwWrGXjgETxZIJoTzMAgsmiXqAeLdbyCfIxtx/KuC/1OUOtBzLuHw7//veJeeWc83CW/QMM7nwTMTioTnjmQu3MSLnYN9qVmKnj58wINiTP5Qe2rhtiy6NHjIYJte5HEuMnZP86o+PWW2+lq6uLJUuW8Otf/5oXXniB1atX89BDD3H11VfT2trKd7/73ZN9mDo6RzOlQQkAACAASURBVI0Ui6rv57Zq7VS5KWUxOXWCXpm0To+NSZ1C9yYKwMeVyw7m1AJwRczIc1gwm47e4SZFQvzfws2cZT7MB/uSvRmZYobsqFDEjHA0TiwuuyBcDjNWsxGrRV6PGQxECATlgQCnzczAtvV0//1xpHgUg0FgTGKfpQV2TZeIFIsgRnO7uIZDEYggKcYrKJ0OgYMfIsVkoSWS4swQBEGN/DLH/Tz148/wyJ0LNX0fAOHOBgCsZbXqgn5kBMMZ/n2b6X7pv9TBgWG3T0RMGewu1algcssiAGKMuC95/hRL9CqkT/cfLyylNYD8fVDOB7I5M0aKWXVmdKuRw4oYaCoYk+HsMKaVeiddEZliRqrAoWyviBmGYcrONc9pd6nRpN73X0aMJMVDMRZRvw9GNWYq+ZqU5zXYXTmL0IdD7drp71RdXKA7M3jkkUeorKxkzZo1GdEOX/7yl/nCF77AY489xhNPPHHcD1JH51gIhJNlTMtvmU9poUP9gNXJjiiK7Nixg1mzZqmLfFdccYW+4Kejo/Ox8u1vf5sf/ehHuN1uFi5cyBtvvMG6dev47W9/C8iF301NTUycOBGXy8XcuXO5+OKLue+++wgEAtTW1rJy5UpaW1t56KGHAHjzzTd58cUXueSSSzjrrLPYtk0reE+bNk3j6tDROZ0ozLNxRk0h+4708d7uds6ZMob9ifLvuop8LGlDHJfPGTfsPusq3Nz4mTNY8Y99/G3DIabUFvHihkPsaUxOke1v6juq431tSxPtvX5WvLKPyy+ozVgAULCUVqsFp+HOxozJfEkS6X3tT2qXBGIcf/1m3Ocvkb+MhNQLd/kCG+w10+kDor1txHx9mFyFDG5/XS32ds+5OudxWysmEW4/pBEWIj0pCxyGYxuWUcSMcPshbcSI30usP7lwFOloQIrHRlWqPvBBUiBOF3xAFnSU26N97UPuSy3ItKTETDmUAvATI2YEDnxAtL/zuEyOptL7ypMMbn+Dkiu/rulJ0Tk5zJo1iz/+8Y888MADPPXUU+riFcCUKVNYvnw5Z5999qj2+dJLL/HYY4/R3NxMZWUl3/zmN7nmmmtybi+KIr///e9Zs2YN3d3djBs3jm9961t89rOZji2QYzGvvvpq5s2bxy9+8YtRHZvOp49wxyE1eig9799gtmJ0Fcp5+n0dUDMNSZJyFvqmTqF7ffI+x1e4OdTipdcbIi5KGA0CngF50b/YffSuDADfrg1UDWznaoeL5Y11BEJRbBYTXSmdGQDuhPNCEVgUVwagRkzlOSyEI0EG/JGkM8NqoPeV/0aKRbDXzcI1dS633Xg2uxt6OW9KMS0vJ2OQQHZnGI5yiEDty7DnZXx2OyefR8+63yNFggQP78BWe6b6GWwukSfjjU63GjuZn+YoUVAiMi1ldZgLxuDjTTl+acjjGqTrxYeRomFM7lIKF9ww7GtRhjMcE85RX4uyYA6yA0Dp6VBK1I/3Z6mCwWLDXFyRUpguYCkb/pwzF4ozQ4qEEEN+jHZXSl/GtMztFYHP14ckiSnOjMwIJ4MjX40Uiw/2Qlkt8dDoOjMU3OcvwbvlJcTAAMGGbapDJtV5keHM8Pao0V6j6SVJx6Q4uqJhwimxrJ/6AvAdO3bw7W9/O2tGtcvl4vrrr9eFDJ1TgvojHg409/P8a/WYTUb1w/MHS89lxoSSk3x0pz5er5e1a9fS3NxMKBRSC3N1IUNHR+fj5rrrriMSifDUU0+xevVqqqureeCBB7jqqqsAWZj40Y9+xDPPPMOcOfL01H/+53/y8MMP84c//AGv18u0adN46qmnmDFDjlJ55ZVXAHjjjTd44403Mp7zrbfeYuzYEzOlpKPzcTBnRjn7jvSxeVcH37p2purMUPoyjobrL5nEe7vaOdTi5f6n31dvP3NCCTsP9XCguR9RlDDkECNy0dwpL3h7fRH2NvbmPE8zmK3JgtMOrZghiXG6X34c3w7579lgdSCGA/j3vaeKGZHuZpRCS8sY+WLaWjFBjYcINe3BXFxJ7yv/DYDjjDk4p87LedzWiknwwT8Itx1UxQbFmXEsEVPq/hNihhgOEOvrUEtGlfgIedpRQopFiHQ1YS0fP6L9RnpaCB1JdqRkEzPEkE+NJoj2dWbcr9k2mzNjBDFT0f5Ouv78EPYJ51B08U1DPkc8MEC4XZ5qxWAEMc7AB69QfOnQvUujRcndDjRs18WMU4TZs2ezevVqPB4Pra2tiKJIeXk5Y8aMvidm3bp13HnnnSxbtowFCxawfv167r77bmw2G1demf3n/ctf/pJVq1bx/e9/nylTpvDyyy9zxx134HK5uPjiizO2X758OW1tbaM+Np1PJ6EmearcXFSOKcvktLlwLHFfn/o+LAZ9apRhZsyUImb04QuGAYEJlW5eA0RRon8wRLHbrnZmFOYd3eS3QrhDfk/OM4SIxSW2H+hhck0BkZjsusgVM+ULJsUMl11e+M93WOjpl8WMQKIAvMQcVIWeSEcDTJ3L9PHFTB9fTKS3Te24UIgHBo7aEam4PVMjphSMTje26imEmvbg37dZXlBPPLelWP6sVz/zhnCNKhGZ1rF1mArk969YX4emWDwd7/svqxFK/vrNIxIzoh5ZoFCGNkAuiDfYXIghn/yZn3CcKr9XygL4icAyti7ZMVJUromkHC2pP9/YQA8Gm0PtnEkXAyFFtBDjxP3ejL6KVARBwOQqIubtSnFmJGI07aMTM0yuQmwVkwg17yXUvFcVM2KpMVIpBeBA4lzucM7jGynmlJ9lqEX+3hhszlH3nZwujLoAPBeCIBCNRoffUEfnBBGNidz2m3/S3OnLen9pge7GGI69e/fy4osvqoV6gcDILI06OjqfXkZ74a4UeI+Um266iZtuyr7Ydd1113HddddpbrPZbNx9993cfffdWR+zfPlyli9fPqpj0NE5nbhgxliefnkPnoEQB1v6OdAsT3JOqj76ySw5buocbv/tm8TiEnariTu+fA5VZXl86/7XCYRitPX4qBqTOfQ0FC2dyen9TTvbhxw6sZbVEe1u1kwzSmKcrr/+Fv/eTQDkn3MF9onn0PnCckLN+4j5+jG5Coh0y90gRmeBuvAgGM3Yqs4geHgngQNbCb/1HFIsgqmgjNIl3x5yiMNaKZeAiyE/UU87luIKIokc7dGUf+fCXFyBYLEhRUKE2w+pYkYo0ZdhGVtH3N9PfNBDqHX/iMWMgQ9e0XydWqSp3tafFDhifR05i8AlScramaEUgItBnyafO5Xe9U/LzpauIxTMu3bISIVg4w5AQjBZcM+5mv531jK47XUKL7rxqKMYsr0WRdhJCkY6J5u2tjZWrlzJ17/+dc4880wAnnjiCTweDzfffDPFxSNf9PnNb37D4sWLueeeewA5ltLr9fLwww9nFTOamppYsWIF9957LzfcIC8izp07l8OHD7Nx48YMMeOtt95i3bp1WQc/dXSyofZlZFmIhcQic/NeYv3yonPcn3RA9sVtdB/qYcb4YjnqSJnmjkdxEMaPjbrK5OJ8r1cWMzyDCTHjKMu/FdTFeSGGkTgf7OvUlF6PySVmBJIl2IqYkeeU/z8YSDozCkmK4eldWcr3A4MREOT4pGPozRhKzAA5airUtAf/gfex180EQLDY1e+58rh4ILuYER/sVeOFLGV1alwSQLjzMPaaTFeBGA4ysPXv6teRzkai/V2YC3ILuZIkqW4LU1p0lMldSkQRMxIoUV0nKmYK5PM2/+63gex9GaPB4MhXB1Bi3m4Eg1H9vqZ3zoA2Tio+6Mnoq8i2vUbMUJyno3RmgPw3rYgZqccAsgNIERdSBZpQS33i+I5ezDBY7BidBcT9/YQTQs8ntS8DRiFmzJo1izVr1vDlL38Zh0O7KOzz+Vi9erV6kqGjczJo7hzUCBljix0EwzGWXTWN8hInU2o/uX/Ix0osFuPVV1/l/fflaUuHw8G1117LxIkTT/KR6ejonOpccsklo3Ju5VoY09HROT5UjcmjstRFa7eP/93YoC4iTK45tvOg2vJ87vrKbN7b1cENl06iakweoijhtJvxB6McaO4flZgRCEXpSSkmfXdnOzd/fkbO9wdLWR3s2qCWcwN433tRFTIK5l1L4cJ/gXgMwepACgcI7N9C/jmXa8q/U7HVTCd4eCe+XRvkG4wmyq67E+MwGcnmonLVARJuO4C5aKw6fXg8nBmCYMA6dgKhpt2E2w/hmn4hkOzLsFZMJO73EqjfnLhteCeBGAkyuPPNxOMnEW47oCnSVEhd7Egvn01FikUg0S+RmimtdGYgiYkoCO3vRKhlH4FErjfxGOHW/dhrc19DBhq2A2CrmYb7vM/S/97fEEM+fLvfJv+sS4d93SNBDAyoE7DyokefGsWhc3LYv38/X/nKV/D5fCxZsgS3W14w9Hq9rFixgpdeeomVK1dSXV097L6am5tpamri+9//vub2K664gnXr1tHc3Jyxn/Xr12Oz2TJiqJ599tmM/Xu9Xn784x/zgx/8QE+q0BkRkiSqk9O5xAxzgVLmKy86qxn4goGf/GkXbZ4g93/7QqaPL9a8R7sNAfxxG+XFTuxWE8FwDE9HJ96Od6jqPMglNj8zgx14t3aSN+OiUXUCAEjxmDogAOAQInywt5Pp4+VFWLfLgt0qLzMqnRlK9NVgImbKbjVhNBo028idGfL9bikpTkTS4piU74fJXYoUDRP39R1TrKEiQhgd2cUMx+Tz6X3tj4iBAQa3vw6AJdGXAUkxQ8zhzFDFGKNJLg03mjAVlBHr7yTS2ZhVzBj48BXEkB/BZEEwWxCDPgL7t6hu02yIgQHVVWlOc1uY8kuIdDYSG5AHGMRISO0KOZFihiWlI8NaVntM+xIEAVN+CVFPGzFvN/FEf4zR6cZclNmjaLA5NeKHIlrlEjNMeUWESYoOR9OZoWCrmQbv/plwRyNiJIjBYs8qphhsTnVwRRGXsnV6jAZTYZksZiT+bj6pEVMwCjHj1ltvZdmyZSxZsoSlS5dSW1sLQENDAytXrqSzs5Of/exnJ+o4dXSGJTVL9bG7Lxn1dOCnlZ6eHtasWUNnpzzlUFdXx7XXXqtPFuno6IyIa665RhcndHROMS6YMZa1/zzIWx/JbgGbxUhV2bF/rs89s4K5ZyYvGg0GgUlVBWw70M2B5n4WnTv8wqJCa7fWSdvTH+RgS3/OOCxrYqov2tuOGAkS6+/Gs+F5QHZkFC1aKm9oMuOceC6+3Rvx73tPFjPSyr8VbOO0iwgln/naiFwOgmDAWjGJYON2wm0HsFVPVRfDj4czA+SoKUXMgERURcKZYauYRDwwkBAz9o9of75dG5HCAQSThcIFN9Cx6peIIX9GzEW6wBHta8968a9ETIHWmZFaoCoGBzVihiRJ9L7+jGY/wSO7cooZkiSpfRn28WdhdLpxTZ2Hb9cGBrauI2/W6MT0XERTekhAdmeY8s475v2OBkmS6H3lSaK9rZgKyjAVjMFcMAZb9VQ1iuLTxEMPPYTT6WTVqlXqugPAnXfeyY033sj/+T//hwcffJCHH3542H01NMiROHV12sngceNkcbOxsTFDzKivr6euro53332Xhx56iIMHD1JVVcX3vvc9NepS4ec//zkTJkzgpptu0sUMnRER6WpSF0ttWRazIRn/E004EZTyb8maR1ub/P7b0Opl+vhiTeZ/gSFAW7yIPKeFkgIbzZ0+LNteoLd7O+cBOIB26G2HaHczJYu/Mapjj/a2QjzZSeoQwnR6Q2zZLS/GpnaT5ifcGr5ghLgo4Q/KoobLkeyWyEv8e8AfUbtOXfFkeXHc36/2WoHWURD3eYj7+hBPoDPDXDAGS1kdkc7GhFNQ+zlvcAztzFDEGEtpjdpvZR1bR6y/M8N1AnJRtHfz/wKQd87lSJEQg9vWa3rAsqH8nsjHnCZmJErAlWGFWMq2poIT6MxIcWNYjqH8W8HkLpXFjIFuVdyzVk3Jeh6gOJZifR1yLFoiHiyXWGBSC8Pl7opjEjMqJwMCSCKhlv04xs+SuzjSnl8QBPk1dTdnHMfRYi4oI9xSrw6bfFLLv2EUYsbs2bN55JFHuPfee/nVr36l/sJIkkRpaSm//e1v1Wx9HZ2TTWHesVknPy1IksSqVavo6elBEAQWLlzIhRdeiMGQGQmgo6Ojk43777//ZB+Cjo5OGnOml7P2nwdR5jwmVBXkLNc+VibVJMSMHCXgsbiIyZh5XqG4afOdFvKdFlq6fGza2Z5TzLCoU30S4Y4Gel/7E8RjmArHUpTWn+CccgG+3RsJHtlFPDhIpEueIk3NkQbZoaBM7jmnzSfvnMtH/LqtFRMTYsZBtS8Dg+m4TTmqJeAdh+Tyyv4uNVLBWjGReED+d7S3jXjQhzER75QNSZLU4m/ntPlYypKCTczbrXGspC/sRz0d2GumZ+xTiZgCNGKIIeU44oFBzCnX5YH9W+SLbMBaPpFw+0FCR3bnPO5oTzNxnzzN6Bg/C4D82YvxJRw64dZ6bFVTcj5+pMS8aWJG20Gckz9eMSPSfiilnH2nertgsVHznT8M6xb6pLFt2zZuueUWjZChUF1dzdKlS3nyySdHtK/BQflvxeXS/o04nfL31OfLjCj2eDy0t7dzzz33cNttt1FVVcXq1au5/fbbKSoqUtc9XnvtNV5//XX+93//Vx/s0BkxoZQIGFOOAmbls0QMDCCGA+okvY+keNzVJ78Pp2b+uw0BXHYzJqOBYrddFjMGZOegR3QxKFqpzDdgCnTj27eJ4iv+NaP4eijSF+DL86DTK0dFAowtSr5XKTFTkiRHTCnOjDx7MpIqL7FNqjPDEUn2CwBEOhoxTUwUVye6HsyFY5ESospxiZnK4cwAOWoq1SFiLq5U/63GTPmzH4MayVWmXdj373tPLQZPxbf9n/LP2mCiYM7niHQdZnDbekJNe4n7vTlFF8WxYrDnZSzApxZNp24rmCwndLHb6Min8OIvEe3rUCO6jgVF2I95ewgneq6yOVvU7fOKZTGj7aDmtqzHmrg93ZlxNJ+9BpsTS1ktkc5GQs17cIyfleLM0D6/Kb/kuIoZGRFjesyUzKWXXsrChQvZvXs3LS3ypFdlZSXTp0/HZDpu9Rs6OqMiEIpy31NbaO46envhpxVBELj66qv5y1/+wrXXXktNTc3wD9LR0dHR0dE5pZk8rpACl5V+n+wWOJa+jOFQ9t3Q6s0QLtZtOsx/rdnObTeexWXnayOeWhLnbdVleUyrK2L16wfYtLOdZVdlvzA12vMw5ZcQG+ih5++/T8Q6CYy5+lYMFu0Qi33C2QhmK1I0zOC219WpzfSYKYPJQunVtxJuO0DhghtHtRhprZB7M8KdjYQTCxLmorHq5OWxoogZUiREtLdNXfQQLDbMxZWY3BEQDCCJhNsPakrR0wm31KuCjvvcKzG63OoUbzRNzEgvBVemYNORcokZZiuC2YYUDWkWmCQxjuefKwD555N/9mfoXPMrQm0HEKPhrP0XgYQrw5hXhLlEnpy3VkzCWj6BcPshvFvXHR8xI4sz4+NGmaoVzFYcE88h1t9FuP0QUiREpPMw9nGZgtInGUmSCIfDQ96vdPyNZF9Axt+3cnu2Ia5oNIrH4+Hxxx9n0aJFgNyZ0dDQwKOPPsoFF1yAx+PhJz/5CXfddRdVVcfHkaXz6SDUvAeQI6Zyfe6kTtdH+zrUSfSuUNLVoIgZkMz8dxsCan9FiduOgIg1LA8brPafz55oFb+6bgqmF+9BDAwQatmXVbDORTgt9unMajvbvBAX5b+nsuIUZ4YzKVoM+CNqAXiqMyPfkezV8CcKwC2h3ozndEw8R/5eKL0QBWXqZ4wi7h8NasxUDpEAZDGjL+EEBbCUZBEzAgNZe6JUZ0ZKzJIibES6m5HiUQSj/P2QxDj9m/4KQN6ZF2PKL8boyEew2JEiQfz73yf/7MuyHuNQHRiqCJBwXiqfN6bCshMuwhZeeP1x25ciyoRa6lWnQ66YNkgKA8pnumCxY7BmLyE35csiQ2zQgxiLIMXl39WjcWYoxyWLGXsT+810ZqS+JoVjKQCHzIixT3LM1LDj19FolL1797Jz506CwSBGo5GZM2dy1VVXcdVVVzFr1ixdyND52AmFYzy2djtX3/E3bvz//s7OQz30D8onvHkOC1bLyKcLPm20t7fj9SZtkDU1Ndx66626kKGjo6Ojo/MJwWgQOG9a8oJmcg63w/FAcVJEYiJH2lMWryWJtW/IHQ/r32/OeFxzovy7aoyLeYnoqpYun3p7Nixq1JQ8ZeqesyTrhazBbMUx4WwA+t/7m3yjYMgaAeWaNp/iy76a8wI3F4qYQTyGTym4LBl5zNZwmArHqiJBuP1Qsi9j7AQEgxGDxY6lVH6+cOuBnPuJ+froe3uN/NjyiVgrJiIIhpQJxzTxwpseM5VdzEg6MwSENDHJqJaAJ3+Wg9teVwWookVLE9EqgtqbkY1goi/DXneWuuAiCAL5sxcD4N+7SZ2qPRZUN0piOjncflATX3s0SJJE8MhuYr7+4TcmGfthLq6k7Lo7qfzar9RFjain/aiOIXhkN71v/I/GRXO6MGvWLFatWsXAQOa0s9/vZ/Xq1cyaNWtE+1Kic9MdGH6/X3N/Kk6nE6PRyPz589XbBEFg3rx51NfL7qKf/vSnTJgwgeuvv55YLEYsJi/ESpKk/lvn+CPFosQTU9OnI5IkDVv+DYnC40SEX7S/U+0I6A4nBYIuT/JvW1m4dQsBtYeiuMBGgSGAETlypicu/64XVlSpsT/++i2jOv5ImjNjUplF87USMyVGw6R0gstiRiBLzJRSEu6LEAzHAAlTQHYQKJ+BiiAgSRIx1ZlRpsYa5op4Sic22Jfx3j4SZ4a5tBpzUXny65RzCfVxkoiYJqrEg4PqZ6p1bNIRqZZhizEiKVP5vt1vy05BwUDBPLmvRzCZVSHHr/RNZSFVoEhHWTBXoiXV7+EJjJg6EShxWYqQIVhsGpEoHUU4UFwW/z975x0nR3Vn+1NVndP05BwURjkLoYQQCAQIkAHBEmwjg43BC8YYgx/gtdnFGGxYWDB+zzYOWBgvwQgMQiAERpYQSQJJKKJRnpxz567w/rh1q6vjtDQzmqD7/Xz0+cx0dVVXz2iqu3/nnnNSuR7oNtnfq/2tAadWAA5ESsmD9YehSGHN8RF7DgZXtJjR75ipGDFrNBeApxQz1qxZg0WLFmHVqlW49tprsWDBAjz22GPsxZkx5Ly++Qje+eRE3O133zAbT951bsI4gzMdRVGwbds2/PnPf8Zrr70GSZK0bYLAxB8Gg8FgMEYTC6ZFPnhXlg3eyqzsDAsynWRwcrg2Mrg9XNuFZnXQcqSuC5IkR+1HY6ZK850YV5KB3EwytPlkb0PSx9JnLhuzi5G59Iak97VPJDEw1JVhzCxIuPr/VDE43NqAIKx2cgxUXwZABqda1FTjUQTUmARz0XjtPubiCWR7Q7SYIYeD8OzbisaXHkbNM7fCf2wXAMA192LtPkYtdiJGzFBXblK3Bo30iIV2ZvBma9zKTp4OmFQxQw750bn17wAAx4ylMOdXQLA6tcfwV++LP344iEANWb1sGxftOrFPWQzOYAJkKeG+J4vYTZ4j7e6Q/Z6oTPFTwX9kJxr/9iDq/nAX/CmitChUUDG687Tb6PAs3HnyYoaiKGh96zfo/vQN+I7uOun9h5rvf//7aGlpweWXX47//u//xt///ne8+uqrePLJJ7Fy5UrU1dXhBz/4QVrHol0ZNTU1UbdXV1dHbddTXl4OWZbj5h7hcFj7/75x40Zs374d06ZNw9SpUzF16lTU19fjtddew9SpU7UkC8bAoSgy6v58L2p+c+uACJlDgdjdog02U4kZHMdp7gyxsxmiGjPVK0eE9+aOSHcRHYK6eb/mzMh1W5HNk9daBRw6ZCI0Z7ossE88GwDgq9qWtnirKEpcIXeJm4dBiLwG5GfZIHm7Uf30d9Dywk/gUrXuHm8QHjVmyqGLmaLuDeoktXFBcGHiurKpcX80qknydEERiSBizCwAr3YyyWkUgHdtews1z9yC7k//od0mh4NQQuRnKDiSixkcx8E2cT75hheiXDN6R0esqBKJkeJgyo84IAVHpvY6Se8jero094d98sKoUmu7+tj+E3uSitOpBAr9wFzsbtMWKcSu4h/uxLoYLCUTU0akxQkHKYQCvWMi3Bq5dvfHmQEAihhCsPEoxN7OhOdg1D0nTjBq/6dPldgOlNHcmZF04vvGG2/gV7/6FVwuF77xjW/gxhtvREVFBdasWYPHH398wE5g/fr1uOyyyzBjxgysWLECb7zxRtr7NjY2Yu7cufjtb387YOfDGN4oioK/vnMAL71Xpd32tSVj8dCtC/HKI5di2VllKMw5szJl08Hv9+OVV17Bu+++C0mS4PV6E+bDMhgMBoPBGB3MnZSHFQsrcN2FE1CQPXjvjTiOw4QysvJLL2Zs/bJe+zoYklDdFBk2hEUZje1kpVxpnhMcx2GhKr7Q3O1EWOggn+ORu/L7KcUJW+VcEqWkElv+PRDohQUAMA2gmAEAJipm1B9CqOmY+piVuscnXwcaDmvDKMnXg/o/3YOWN58m5dmKDN7igHvRVXBMX6rta0ggZshBP2Q/eX9IB/tiZ2PCQZccVMsxdRFTFMHm1M4l2HAE9X+5H5KnE5xgRJZOgLKo0UmJejMCtV+pQysO1ororG3eYIK5ZCK5nyp49Aexi/wMbONmgzOSyRstXj9V/DVEZJH9HjS++HP0fPlBH+dAxAxDIjHjFJwZ4Y5G7Xerz3cfKcycORN/+ctfkJ+fj+eeew4PPvggfvazn+GPf/wjXC4XnnvuOcyePTutY5WXl6OkpATvvvtu1O3vvfceKioqUFRUFLfPkiVLoCgKNmzYoN0miiK2bt2KuXPnAgDWrl0b9y83NxcXXHAB1q5di7y8vLjjG2X15gAAIABJREFUMvqH5OlGuK2OxK+p0XkjjUANcWVwZlufr0taCXhnk7ZavFu2YmI5ec3t9YXgCxCBgDq53LwXGQ7VmZFhRQ6visqWDIgQYLcYYDYK2oBc7G6NEyiSIXa3aMN0OowXRD+mjIlE4xRk29WIPD/CrTVYZDsBICZmyqovAI92duTwkRkFXZQgdjYRR0FXxClocOudGX13ZvgOfwEA8Hz1qXabvjg8lTMDAFyzl0NwZMI5/byoOEl6DgDiBDYayWXMKgRviohQHMdp5djBpuOQ/L1oeukhiF0t4AQjMhdHRzPZxs0hUVSSCN+RnQnPL5VAoUVLgixYoPeN7VcY7lBHKcVSmrwvA4iPbEoV4WRwRESGUGtE+D5VMcPgyNR+vt6qbYAsJjwH6jYh2zL7Hfsl2DO09zEAYLCPXmdG0nyoF198EbNmzcLzzz8Ps5lcDBVFwd13341XXnkF9957L0wmU7Ld02LDhg249957sXr1aixZsgT//Oc/cd9998FiseCSSy5Jua+iKPjJT37CBrJnGG9tPYZXP4isPvv6RRNxw8X9z8odzdTU1OC1117TbNrTp0/HZZddpv1dMxgMBoPBGH0IAo/br0kvhqW/VJa6sW1/Ew7XkmGLLCv4aHe0w6KqugNji8mwoLHNA1nN1y7JIytFF04vxLqtx3C0rhstHT7kZcUPya3jZiPr/G/AmF0Ci+pKSAZvtsE2ZiZ8R3YAAIy5gyFmTIBXNxgZSGcGQGKhgGjnhUUnoFiKiZgh+3ogdjXDkJGLljefJsNvXoCt8iw4py2FbfwccAZj1LETiRn6r60VM9C9fT3koA+y36MJFBRZXc3KJRIzrGS4493/Ebo/WwcoMsDxyF5+c9Qwwlo+FT2fv52wN4NGTJkLx8U9NgBYS6cgcGKvlj1/qiiKjLBaAG7ILIC5cCwCNQcQbDwCx5TFfeydHP2KXMgi2t7+LcLt9cg6/xsJV5JqESEZkUFUf8QM//E9AMhgYzCEvNPBWWedhVdffRUdHR2or6+HLMsoLCQ/k3Xr1uHnP/851q9fn9ax7rjjDjzwwAPIyMjAeeedh02bNmHDhg146qmnAJDC75qaGowfPx4OhwMLFy7E0qVL8Ytf/AI+nw8VFRV48cUXUV9fjyeffBIA+UwVi8lkQmZmZsJtjP5D42UAjNioKS1iqo9V5UAkMkbsbEJYXdndK1txxZJxeLyaDOdbO/0oLzRGYqZ4n+Z2yHFbkSMQMcNjICu0szLIoNOYWwZDZgHEziZ4q7ZFxSAlg0ZMcQYTLEWV8B3ZATngwdxJedhzpA08Rx7T3xARCRZxX+I9lKHbE0Jvgpgpfa8GAO18eatDE7wBINh8QnPMCXY3eJMlbTFD7ygJNZ+AHPSBN9uixIdUnRkA+V2U3/WnuNs5XgBvdZJ4opjzoD+vRFFIpvwx8B/bjUDdQTS99AuEWmoAXkD+1T+Ou2bzZiusY2bAd2QHvFXb4Jh6TtR2ORzUxK5EAgWNlhQ7mxDubI4I3SNOzMgGwAEg7x9TOZsi99d9n8KZwRmM4G0uyL4ehNrU6C/BQFygp4ildAo8nU3wHPhEdw6xYkZu0m2nAsdxMGbmkf9POENjpo4ePYqVK1dGDTw5jsNNN92EUCiEY8eO9fvB/+d//gcrVqzAT37yEyxZsgQPPfQQVqxYgV//+td97vviiy8OyDkwRg5efxh/fiuycuvmy6cyISMFsizjww8/xJo1a9DT0wOj0YgrrrgCV111FRMyGAwGg8FgDBi0N6O6qReBkIiq6k60dZFhd0UhGTYcrI5kENe2kMVIZpOAHDdZrTh5TLYWjfHpvsTDW47j0Va6DIGC9AaFWiwEToMzg+NhzI5f4d2v46vODIpgd0PQiQHG7GItUz3YcBidH63VRIC8r92Jgmv+D+yT5scJGUAfYoZggLk08h47UcyRHFBX5yboGuFV8UHsaQMUGcacEhTf9MuomCsAKXszaPm3dWxiQY7mUYdaatIqf+3c+nfUPnuXJlxQJE8XIJEVk0Z3nk5ASu3MCNQeRPXT30HPjo1x2xRF0Urhsy+6GVa1v6X7szfR9m78MEyRJYjdbdo5UIyZZHAvdjZBUeS4/VLhP0HEDEvF9LhC2pFGVlYWJk2ahMbGRvzsZz/DsmXL8MQTT+D48fRWkwPAqlWr8NBDD+Gjjz7CHXfcge3bt+Oxxx7DpZdeCgDYvHkzrrvuOuzfH/ms+cwzz+D666/HH/7wB9xxxx3o7OzEc889h2nTpg34c2Skh6jGMwHpRQsNRyLl36lXlQORYXOorQ5Q3XCyxYVFMwphNJC/a1oCTmNy7HwIGRayLSfDgmzVmdEcViOmnETM4DhOc2ek25tB455MeeXadV72e7B0Tgnys2xYdlYZDAIfdU3OUHow23QipgA8MiCOd2aQfY3ufAgWu+ZWCzWf0DkKiOirP4dU10ixu1XrTYAiI1BHUj5oLBQnGLXX0lNBKwFP4sygLgw9Wgl40zFSUM3xyLvyh8RVmgAbjQU7uhOyGrVFEXVxkPoILD2R8uyDgEzixg1J7jtc4QRjZDjPG+LcsbHEihd9lWtTdwbtMREs9n45Jazq+xSph7y+kxgpR/Q5OTIB9TU6thz8VNGipngDeOvoTa1J+s7G7/cnLMMqKSmBoigJy7hOhtraWtTU1OCiiy6Kuv3iiy/GsWPHUFsbXxSo3/eJJ57Aww8/3K9zYIwMvP4wjjd04/qfvqOt4jtvbglWnZ/64nWms23bNvzrX/+CoijIz8/HrbfeilmzZvXbusZgMBgMBoOhZ3wpWfEpywqO1Xdj624SMTWmyIXz5xK3QpVOzKjTlX/zPHlfIvCc1vPxWRIx41h9N+5+egse+H8fp5XxbZ9wNniLXV1FmtrJcSqYC8ZqH0IN7jzw/VjBlwhDRm5UfjIp7468j+N4Qfsw371tPbq2vgoAcJ21Ao6pS/o8NgBI3i5tMEIH/caMXAgWuxYjIibozZBDVMyId2ZE3BccMuavRPG3H084dCC9GURk0vdKhDsatB4S69hZcfsBal8IT0IG6ErnZCiKgu5tbyHcVgfv/o+jttF4J4D8TLSekqajUGQJyejZ8S4kbxe6v3gnbpvk6dTiSyylU1Bw7QNwzSFCTu/uD6BIYtz9aQRFopgpRQxpGfvpoMgSAmqXSGxE10hj3759ePjhh3HOOefg7rvvxpYtW+B2u3Hbbbfh/fffP6ljXX/99Xjvvfewd+9evPPOO7jyyiu1batWrUJVVRXmz48IoBaLBffddx+2bt2KPXv24OWXX8bZZ5+d8jE2bdqERx555OSeJCNtRJ0zQx6BzgzJ241wO3Et0kFnKujQXl9IPGZcGQSBR57aM0VLwPWD2ywjWUxgtxqRZyCLB054yGLGLFckgoaKGeHWGoQ7kvdVUai7wVQwBoKFDGXlgBfZGVb86T+W467riXArxzgULrTsQ48noHVmOHXODJvFAIGPvK7lGtWyZlXIoV1ZwabjuvJvso26AKHIKf8/xMZo0dcMKj7w9ox+zUgSiRlyOIhwW33Uc9BjihE4ci/7dzgmL0r6GPbKeQDHQwkFEDi+N2obdfZxBhMEZ+KV+PR1WYt15HgY3bkJ7zucobFM5qJxffagCXY3iJND3bcPsYCKCeE20plxquXfFEtp9MJrwZkV9/+M4wXtvAbCmQHo/j7sGSN+MUMqksZMybKc8A+aFgXry4NPBeqqiC3cKi8nxTjHjx9HaWlpwvO6//77sWLFCpx77rn9OgfG8Gbf0TY88NuPE25bsbDi9J7MCGTu3LnYtWsXKioqcNFFF8FgSPrnzmAwGAwGg3HKuOwmFGTb0NTuw6GaTnysihlLZhVjYjn5kFbf6kGvLwSnzRQp/86LXjg1a0IuNn5WjaN1XZBlRRM6KPuOkdVtje1edPYGo4YyiRBsThTd9CtAEuPiBgYC3mSBKbcMoZYTMOXEf27pL7QE3K+6FPR9GRRLUSUCJ/aSlZ3qfbIv/Fafx9ZHG0g9beCzijRnBt1mdOcj6Ovpw5kRL2Y4Z10IRQzDWjENlpLULmpL+VSEWqoRqCEDFkUKo+UN4tIXHJlJ48R4oxnmonEI1lUhUHtAK7NNhOTp0nLeg03Rjgsq4PA2F3iTVRNdlFAA4fYGmHIT/17pyt5wWx2kgBeCLldbG5zxAkw5JeB4Ae5FV6Fn50ZAlhDubIrqVwnHCCra15n5oJEa4Y7GuLzwZASbjmuDPduYkSdmtLe3480338Q//vEPHDlyBIqiaHOJO++8E7fddhv7XHOGohf1pMDIixunQ3ROMGousFQkWmU/axbZLzfThvpWL5o7iXDB6+JkXCDXO47jkC2Qn1NDkFyrM3Wvm+biSgiOTEieTnirtsO9MCLwJUJzGuSP0Qb3iX4PNG7JmFOCcFsdigxdcHV8Ba+fiA/6zgyO4+C0m9DVSwrA84SIMwMgiwZ8VdsQaj6uuQxpyXVUX4WvB0KS8mTqKKHEihl99WX0Bd1fXwAeajpGIhbV5xCLMasQgisHUk8bsi++Bc6Zy1I/hj0DlpKJCNR+Bd/xL6McHJpjxZ2XdHitX8AAkAgmToh3bQ53zIXjEKw/BNv4xA4WPZxggGDPiDznPsQMup2WzJ9qX4Z2vMxCCHZ3n49vLhoPsactTuA6Vczq+yZzgniz0cSQyTS9veQi5XBE22zsdvIfJlkXxvPPP4/a2lo88MADg3uCjCFl6676hEIGxwG//T/LokqmGARJklBXV6d9bzKZcMstt+DSSy9lb/gZDAaDwWAMKjRqav1Hx9HRQ4YSS2YVY1xJhiZKHKohq0trW1RnRn7054DyAjKY8AclLTpDT3VjJLqipik9l7gpu2hQOwPoytZkcUj9RR81lcjdoBc4eKsT+avuSWtAYXBma66SsCpiaGKGSxUzaGdDQmeGOkBL1JlhsSPznGv6FDIAwFpGInsC9Ycgh4No/+CvqjDDIe9rP4gqWo3fVy0Q76MEPNweeX8cO9SizgxjBnFEGNz5WgwEFYhiEXs7IOriqmIjsoLNpJjYlFOiDd8EVw44ExkianncMecg2N1RK015g0lbhXoyvRm0L8OYVRgljgxnRFHEe++9h+9973tYunQpHn/8cVRXV2Pp0qV45JFH8Oqrr0JRFEyaNIl9rjmDiY6ZGnlihl8dopuLxieM/4vFkJEL6Ho1gooBMycTITRf7ZWizgy/yMMjk+uHXSE/G8nvgRXk9bhdIoP+LJc+Rp6HfQIRgr1V21Kei+Tt1sQkU/4Y7TqZ6PcgqRFg1vJp6HZPBABM6vkEsuqodMRES+mjpmgsVsSZUQGARP9QV0tszBQAyCniBqnATFbqA8H6w1DEsCY+9NWX0ReJnBl+tejdmFWU8Pgcx6P4W4+i+DtPIOOsFWk9jkV7zYt2I4pa+XfyDoxYMXyklX9TspbdiMJvPgT3gq+ldX99tFSfMVMx2/srZnAcF9XrkSxGKvfyO1C0+hdxXSinin3SfBSt/gVyr7hrQI43XEn5TqCrqwsNDdF2s+5u8gfa0dERtw0AiorSy4ql1vBY9we9nefjdZZjx47h6aefxjPPPJMwAosxevjDmxHrnN1iwIO3LECu24bczFPPMhzNdHZ24rXXXkNzczO++93vIi+PfCAzmQY27oDBYDAYDAYjERPK3Nj6ZT2a1cHK+FI3CrLJB8ExRS4cretGVXUnZk/IQ31rYmdGUY4dRgOPsCijurFH259S3RgRMGqaejFrQh6GGveSf4Nz1gWD4vwAYsSMmA4NQC2RNZigiGHkXfnDtIfXnGAgK3J72zURQxMz3JHBPnDynRknA+nNACCJ6Nj0Anq+2ACA/FytfbgKLGVTgE9eJ06EoD/puYTUqA+ADH30TgoqJNDnHHHD7Eaw4QicM86PO16gvirq+2D9YdjUXgxAF8WiixbhOA6m7BIEG48g3FoH6HSeyDnEr8I2ZhVC7G49OTFD15cxUliyZAm6urrgcDiwfPlyLF++HEuXLtUWOtbX1/dxBMaZgDTCY6boELqv4mIKxwswZORqw+qQ0QmjgYgbeZmqmKEK/z2eILplGxx8EFaRDPbpfgDQJpPXW9qZQbFNnI+enRsRrD8Esbcj6epx6soAx8OUV6YdO9HvgcZMCbYM9I5fjowvqlCEFlQamnBYLIxyZgCREnAjRDhBjkcH87RbArIIWXWB0G28wQTOZIESCqQsAacitmvOxejc+goUKYxg49GIM6O/YoYtXszQit5T/K4NruyTeu9gKZsMfAyEWqq1EnMgsuAglUBBhXFKsm6N4Q5vNMNann5vkcGZhVDTUYDjIdhdKe8bKzb0V8wAyO/Me/BT9VwS/655sy3ta0I6cBw/oMcbrqQUMx599FE8+uijCbfde++9cbdxHIcDB1KvjKFQMSLWgeH1eqO2UyRJwv33349LLrkEixcvhihGskZlWYYoimyVxijgt6/txrZ9TZrNcGZlDv7ruwthEEZv1lt/OXDgANatW4dgkPzMTpw4oYkZDAaDwWAwGKcD6sygLJlZrH09oSxTEzPauvwIhkhcbWl+9Pt9QeBRVuDE0bpunGjswXy1QwMgfRzVOjdGTfPwKH/lOG7QhAwAsI2bA/uUxTDlliWM0BDsGSj61qOAIicUO1JhyMhNLGaoQw9jFhmM6AdilEhnRv8+7As2J0x55Qi1VGtChqViOjLPuabPfS0lE4m7RJERqDsYJSjo0TszABL/YVUH/TRmSt9VYS4cT8SMxsQl4MG6aDEjEOPMCKnl36b88qjbjblEzIh1ZoS71Rx4d/z7d2NmIfzH96QtZsjhoDZE60sMGk50dnbCZrNh5cqVmD9/PubNm6cJGQwGRRzBMVNy0K8JnZqImwZ8Rh6gXoNNuj6EvKxoMaPbE0K3bEMxOmEMkaE67VLwySb4FLUzIyNazLCWTwVvsUMOeOE7tB2uuZckPA96XTNmF4E3mrVBr+T3REXBAZGYKd7mhClrEo58mofxxhYst+7F4d7CBM4MIm5k8ZHfqVF1XwjOLPA2V1QPh174FWwuiCnEDMnXo4lg1nGz4Nm/FeGOBgRqDwy8M0M9niJLCNYdBKAKEAOEpVj/mlelveaJXaozI4VAYYxZ6EB/vqMdKs4JjkxwOpdTqvtS+vv+BkBazgzGqZF0+n/VVVcN6gPTroyamhpMnDhRu726ujpqO6WxsRG7d+/G7t278cYbb0Rt+81vfoPf/OY3qKqKfmPJGN6ERQm+gIjNO+vwpzf3JbzPt1dOY0JGEsLhMDZu3IgdO3YAIBFtV111FcaNO7kPsgwGg8FgMBj9ZVxxBngOkNVe7nNmRdzak8ozseGTE6iq6dRECIHnUJgT/0GxvMCliRl6mjt8CIQinX01TcNDzBhsOIMR+Vf9KOV9zKeYs2zMyEWw7iDE7jbI4WAk15l2ZqirPCVvd5zzgXZQ9NeZAUR6MwASA5J3xV19Dh3IY9tgyh+DUNNRBGoOpBAzolf1B3ViRmzMFAAtyz7YfByKFI6L7aJ9GYIzG1JvO4INh6EoMjiOhxwKaMKDOab0lfaq0HJRSqw7RI9Bi/pKT8wI1B4EJBEAd1KrV4eaNWvWYP369Vi/fj1eeuklcByHWbNm4aKLLsLy5cuH+vQYw4SRHDMVqD9EOhQ4ngixadINF+hV1pUbuUbQAvBuTwiBoIhubxBdMrlN8ZFIR9qlQF0ZAOK6pjjBANv4ufDs+xDeqm1JxYxgE+m8pf0PNGYKsgglHNRi9IBIzJRgcyHDasbrgekYb/wAE41NyOR9sJmjx5AuOxFactR+D04waoNfjuNgLhgD/7Hd5HujJUp8EKwuiF0tkP2JxYxoR0k5LKWTEe5ogL/mK0jeiIOkP8Q6M0Kttdpr5ECukOfN1shrXu1XsI2bDUWWEO4iCxFSCRTCKImZOlno80wVwUWJd2bEx2ieLKa8cvAWB+SAZ8S6YYYrScWMX/7yl4P6wOXl5SgpKcG7774b9QblvffeQ0VFRVxcVV5eHtauXRt3nGuuuQY33HADrr766kE9X8bA0tTuxd1PbYHHH064/btXTsOEskyMLe7fC8topbW1FWvXrkVLC/nwM3bsWFx11VVxHTQMBoPBYDAYpwOL2YDSfCeqm3oxqTxTi8AAoJWAe/1hfLaPDGULsu0JF6xUFJIYgOqYToxYcaOmuTduNSjj5KCihdjdCrGnTbudDvaNmRFnTLizKUo0kYPJOzNOFmvFDPR8/g7A8SQqy5HZ90503/IpCDUdhT9Fb0aIigeCAZBEbSinyJL2vKOcGbSbRBIRaqmJcrzIYgjBRrJ/xrxL0bHpBcgBD8IdjTBlFyPUWgOAKHqmvIqo8zCqpd/h9gYosqQJNuEUYoYpi3wmDnc2Re2TDBoxZS4cm7QMdziyYMECLFiwAA8++CC2bNmCt956C1u2bMHOnTvx2GOPoaKiAhzHweeL79JhnBnIQT8UtasHgBY5NFII1JJrlCmvPO66+dZWck1ZuSS+KLraa9FS6cyuyLCVdmYAxJ3R7QmhWyG3UdFHVOOH2qTIjCDTGenMoNgnzodn34fwV++H5PdAsMbPFGLj83hL5D5ywANeFTMUWdKEJsHmgstuwqFwAUSFh4GTMc7WrfVoUagzI4f2ZcQUWZvyI2KGMTM/6nWf9mZISTozQmrElDGrELzRDEvZZPTu/gDBuoPgDMQh0lf8UF9QcUUJ+Yk7Tn09EhxZCeMD+4OlbLImZgCA2NsOyCS1JpVAwRtMUWXUtER9tOOcuQxywAv7pPl93jfWZStY+j9b43gBeVf9SC0tn9Pv4zEiDGku0x133IEHHngAGRkZOO+887Bp0yZs2LABTz31FADSy1FTU4Px48fD4XBg+vTEuZ95eXlJtzGGJ4druuKEjPlTC3D5OWNQmu9EdgbrxkiGx+PBH//4R4TDYXAch2XLlmHx4sXswzyDwWAwGIwhZfn8cqxZvx9XL6uMur0oxw6H1QiPP4ytX5JV8qX5iT8kUjGjvtWLUFiCyUiGt1TcsJoN8AdFeP1hdPQE2HvGfqCJGT2tWsQUOF5bncjbXFoeebgrWsxQqDPD1H8xw1Y5F1kXrIYxq0hzTKSLpXQKure9hWDDEcjhYFSBNkAcJLS01jZ+LnxV2xBSxQgyBCJuH72QYHBmQXBkQfJ0INh4NErMCDUe0wZHjunnoeuTf0AOeBCsP0TEDDWKRXBmQ7BFiwkmVcxQpDDErmYYs4qgSGFIPSQCJdGqTerMgCRC7GlPGEWlx3+c9A6OpIgpPSaTSevM8Hg82LhxI9566y18/vnnUBQF9913H15//XVcc801WL58OesHPIMQdX0ZACCNsM4MrUMhJnaovtWDP7xB/m4nlLk18R8gfbL7WnhMUj/mCw63ti3TaYFB4CBKClo6/ejxBtElq9FP6jUvrMYPtavODItJgM0SXzxuHTtL7V4KwXfkCzinnxe1XQ75EW5XHWfq64Be8JD8Hq1gWg54iQMFAG91wmU3QYKARsmNUkMHys1dcY9POzOyBSJIxK6i17vcYgf2go28Z0gWM6XF/qnnTZ0SctAHqK9j/XZm6Jwisq8n6nc90DMaS+kk9Gxfr5WYU8EK4KIchokwuHIiYsYZEjMlWB3IOu+GtO7LWxza3wH5fmCiDm1jZ8I2duaAHIsRYUjze1atWoWHHnoIH330Ee644w5s374djz32GC699FIAwObNm3Hddddh//79Q3majEHEaTPi/957Pl5/bCV++u35mDUhj30o7QOHw4Gzzz4bGRkZuPnmm3HOOecwIYPBYDAYDMaQc8W54/D6YyuxQNd1AZCYiInlZLW9L0AGwbF9GRQqZsiyglpdLwZ1ZsybnK+t6jxToqYGi4iY0a4NRAyubG31P8dxmjtD7Ij0ZiiKHHFmDEAMA8fxcC+4AvYJ8056Xy3CQxYRbDgctz3U3qB97Zi2BAAQ7miAHPRBVKM5AMQVp1N3hu/ozqjbA2oOuiGzAAaHG+biSvV20ptBI03M+RVx52LIyNVWAodaiVtE7G4DdXIkcmYY3XkkIx3oszdD8vUipLpOrBUjU8zQ43A4cPXVV2PNmjXYvHkz7r//fkyePBmffvop7r33XixZsmSoT5FxGpF0EVMAEVQVWUpy74FDUWT4q/dr17zE2/dFlT/H3UcKI1hPrk+W0ui+jOMNkf0274yOoKtr8eBoT0Sg1bvWeJ5Drq4EnHZmAIDY2wlFkbViaK38OyZiSjuWyQLr2FkAAG/V9rjtoRad40y9tukHvfoScL2oINhcsFuM4HkO9RIRaYr56N8jADjVDo2IMyN60G7SCemxQ/i+xIzINXmMdmzBER0nJNjdcfudDHoxQ/R2p1X+fapYSsgxaYk5jRIzuLLBGeKFKj30dY63OgdsUD+a4DguKmqK/YyGN0NeRnD99dfjvffew969e/HOO+/gyiuv1LatWrUKVVVVmD8/uSWoqqoKt99+++k4VcYgIPA8ygtdMBqG/L/isKa1tRWyLGvfn3/++bjttttQWlo6hGfFYDAYDAaDEU2yBRb61aYAUJKXWMxwO83aKk19tFS1+vX4UjcKs8kHzHRKwD/4vAbrtiYucj7T0Qb4soRAwyH1tuiBOh0chXUl4EooCDrY4k1DuwhJsDlhzC0DAC3aQw/tp+BtrqgBf7D5OES1HFdwZII3RK/wd0w9BwDgO7xDKwkHIn0ZlhIS/GIpnkCOp5aAR8q/K+LOheMFGLOLyf3U86IRU+B4GJzxRfKcYNBEjr7EDH/1PgAKOIMJ5tJJKe870sjNzcVNN92E1157DRs3bsTtt98Ot7t/A0jGyELsjR+Cy6fBndG55WU0/u1BtG/6a8LtvkOfo/Fv/4nm159Meoxg4zFttbcl5m9TL8pv/bIeohT5zL/jYHNURFTs0J32ZrR0+NDtDWpiBmR/LvbvAAAgAElEQVQRUm+H5vrqAhn4x/Zl6LFPJDM3/9FdkMPBqG10OG9w5WjxdRwvgFPjsvT9JbI/8nwEqxM8z8FlM6FOJEJMnhKJNKREnBnkOLGChTGrEJyRnHtsPBJvdcU9rnYu4SDCqqBNBRGO4+LcMf0tAOdMVq1bKVh/CJKHdJYMhphhcLhhVOMHA7UHtNexdDowYvuwGPHoS8AHIkaTMXiwCTJjSAiJg7+KYjSgKAo+++wz/P73v8fHH3+s3S4IAqxW5mBhMBgMBoMxMqDODEqymCmO4zR3BhUzQmEJDa1kyFFR6EJZARmm1PYhZrR2+vHrV3bhj2/s08QQRgSDrhCUCgGxDgU6INGLGbTYFBgYZ0Z/sZaRlc4JxQy1/NuUUwLBYteeT6jpOMJqtFYiR4R94nwIjkxAkdGzYyMA8r48WE/FDFLga1bFjFBrDeSgT13BHMmVj8WUS0vAawEgMohyZYMTEidAU3dMXyXg/uOkL8NSOilOnBlNlJeX484778TGjRuH+lQYpxEqZugH+oPdmyH5e9G9/W0AQFAVMmMJNhwBQFxbipi4D1QTAzIL4jqB9GJGtyeELw9FHGM7vmpBCEYcdS+AtWI6LOVTo/al3VTNHT70eENaATh5zIOgorNiJ9f1VGKGrXIuwPFQxBD8R7/UblfEMLo/f1u9z1lR+wjqynVJ93ugpdqc2aY5BZx2k+bMcMrdcRFhTrsJHBRkU2dGzLCd43hkLvk3mIsnwjYxeqGzoHVmxDtjQi3VWuSVPqoqVmSIjQQ8WTiOA68KIt6DnwEgq/pNeWX9Om4y6Pn7a77SXpvTESgc05fCXDgOGWdfPijnNRqIdmawPtrhDBMzGKeVmqYe3PXkZjz98q6hPpVhj8/nw8svv4yNGzdClmXs3bsXksREIAaDwWAwGCOPCWXRA5xkzgxAVwKuChA1zb2Qlci2MjWiqq+Yqd2HW6Co++mjPFIRCkto7jgzSoZ5kwW8GtEh0hLqGDGDDkjEJGIGNwCdGf3FQsWMuiooUvQwkTogjNmkr8JcQAp2g41HteecKGecEwxwzbkIAND75T8hh4MQu5q1KBkqZliKKgFwgCLDs/8jKOEAeZz88oTnSkvA6XmJKQQVbZ8sGvWVXMyQw0H4Dn8BYHRETDEYsUhqZ4Z+QCz5B1fM6Pl8g/Y3He5shkJfUHRoQq8sIdRam/A4VGiNjZgCgJrmaKF9ixo15Q+K2HeMPGfbOd9A4Tf+K64TiJaAt3T60OMJwqeYIXOGqMeEYIDZTYTrVGKGYHXCWjENAOA9tE27vXfvFhLxxQvIWHhF1D502KsXlSR/j3Y8SobDhHoxS3sdp2XiFKfNhAzeByNHhIdEg3n3witRfNOjMDii3SmRmKn49wO0/Jt0GEVKvvViBm9xaK6K/kB7N7SIqZJJUSXmAwl1lgTrDiKsRkCmUzRuzq9A8bcf15yHjHgMLGZqxHBKf13Nzc3YvXs3ent7EQqFouJvGIxkfLavEXf8979wTPdhsrKM2YMTUV1djd///vc4dIhY1mfNmoVbbrkFgiAM8ZkxGAwGg8FgnDwOq1FzY+S4rbCaE69CB4DyGGcGFTVcdhPcTrPmzKhp6kk4XKJ8eSgSZ1GdZr/Gw3/ehlseeR/Pvr4H4TPASWxwxTgxkokZPe3aquPh5sygA0JFDGmrpCnhdjIYNOWQeCda5h1sOgZRjY9KJiQ4Zy8HeANkvwee/R9pEVOc2aaJErzFDqN67J6d75HtRkvSyA9aAh5uqyOZ9tSZkZF8EEXFjHBHQ9L7dH20FpKnAxAMsE9emPR+DMZIhTozjFlFAE9ePwYzZkoO+dH9xdva90o4ADlBLwN1VwGRfgY9iiJr1w5rTLxRWJTR0Eqew8Lp5O/8032N8AdF7D3SBlGSwfMcZk6Ivi5T8qiY0eFHtzcEgINkIUN1fy0RM4zuPFy1bAJmVuZg+fzUTgHbBOJ68B3+AookQpEldH36DwCAY+qSOOGXV0vA9TFTVFTQiwcuuwlBGLXujmBT9M/JZTdpfRlAanE3Fvo4Ssgf54zR+jIKop1yptxSLUJIsLswEGjHUZ0ggxExRdGXmFNh6Ewp9B5s9HGPAhMzhjXJP0UkYMeOHXjkkUfw1VdEbXzuuecgSRJ+8pOf4P7779eKuxmMT/Y04NVNhyHpMh+PN0S/+N957SxcOG9wrHcjFVmWsXXrVmzZsgWKosBkMuGyyy7DjBlshRWDwWAwGIyRzaTyLNQ2ezRnRTKoM6OzN4huT1ATNSoKXeA4DmUFZLs3IKKjJ4DsjPjoTUVRsOdIJK4jnbLwbk8Qu9V91n98HAerO3Df6nkoyB69H2gNGTkINUU6RYxJxAxAQbirGaackoiYwRsGZEVrfzE4M2HKK0eopRreQ59rgx5FErUCXNpVQXPTw+0NWmFsssGZwZEJx5RF8Oz7ED1fbNDKvi3FlVpJOvl+AsJtddpQyZRXnnRFrjGHxEwpYghid2vEHZKGMyPc1QJFlqIeGyAuj67P1gEA3AuuZHnojFEJLQAXnFkQrHZI3u5BjZnq2fU+ZL8HnGDUHF/hzqa4fgV6jQHiHQcAEG6t1c4zdsDd0OqBpNoVbrhoIj4/0IxgSMK2fY04cII838kVWXBYE19nacxUlycIg6D2VdncgL8dYdUlYnDn46zJ5F9f2CfMQ/vGP0IOeOGv2Q/Z71FdeRzci66Kuz8d9upFJZk6M6LEDOIoqRezkCf0at1CFKfNhDEu0tPB2eM7jFLB6xwgkr83amU9dWbExv5xvABzyST4j+7UHBX9JbbPJLaXYyChJeaSJ9Ijw677A0N0zNTQL9ZgJCdtZ8aePXtw8803w+v14lvf+pZ2e0ZGBgwGA+69915s2bJlUE6SMfJ4ffMRHKntwvGGHu0f5azJ+XjryStw0fxy8HziksgzlbfeegubN2+GoigoLCzErbfeyoQMBoPBYDAYo4JV54/HOTOLcP3yiSnvV1bgBO0Rr27q0ZwZ1LFRnGvX3kMmc1zUNPeiszeo+77vzoy9R9ugKADPc+A54EhdN+76n834eE/yFfEjnVjxInawL7iyNcGCxqlQMYM3W5MWvp9ubBPmAQB8h7Zrbp1wZxMgE3cNdU/QmCkosrbKOlHMFMV11goAZEjp2f8RAMBSHF3gS3sztO8TlH9TjJn5gNqNEW6t69MdAkTEDMiSJn5QFEVB27t/AGQRBnc+3ItXJT0OgzGSEdWYKYMzS4s3GqyYKUUMo1sVCJ2zl2txfPruIPr4ekEl1nEAkF4DgAy7Yx1bVGS3mg2oKHThrMnkOrB5Zx12HCR/63MnJb82UDEDAESJXPcER1bUfU5myG1wZcNcRERb38Ft6Pr4NQCAbeLZmqtMj/Z70MdMqddVXtdDQQu+69TejFDzsejj8ByuPZtEUZqzC9M+XwBRYoSkc84osoRQK+kwinVmANCilmJ7SE4VvcjFCUaYC8YNyHETkajEPJ0CcEbfWIongjOaYS6qHBaLNRjJSVvM+PWvf42SkhK8+eabuPXWW7U3idOnT8e6deswbtw4PPvss4N2ooyRw/++exBV1Z0AgLOnFOCWK6Zp//796hn44fWzh/gMhy9nnXUWBEHA/Pnz8e1vfxvZ2dl978RgMBgMBoMxAijJc+K+1fMweUxWyvtZTAbNDXGioQfVTRFnBgAYDQIK1e3JHBe7dSWqANDU7kMgKKZ83N2HSSzV9HHZ+Plti+B2muELiPjV859jZ1VLyn1HKtGxUhwMruj3nhzHw6DGV9AybTnoBwAtpmM4YFfjUcIdjdp5htVeCs5o1srOBasThhjxIpWQYC6q1KKpFFXEMZdEi3GWGDHDlELM4HgBpuwiAECg8YjWwWFMkXduyMgFVDdGOKY3w7PvQwSq9wMAci6+JS5Tn8EYDSiypP2tGJzZuq6GwYmZ6t3zL0ieToAX4F7wNe3vU9S5MMj30eJGqOUEFCU6gj2gxj1ZyibHib/Vqshelu8Ex3E4by5xbu2sakGL2t2UylGRlWGBELM41JSRE/X9ya7Yt09aAADo+fIDUqANIHNRYpFUi5lKIGYI1ogzIyNWzGitgyyGoo7FeWh/0MmdL2+xAaoTTh8DFm6vh6I+RqwzAwCc05ei/O6/IPPc60/q8ZKhF1XMxZVa+flgEdX7YXWwSKQBwuDKRvldf0LR6l8M9akw+iBtMWPXrl1YtWoVLBZL3EXY4XDg2muvxeHDhwf8BBkjjy276rSvL1lYjivOHaf9u3TRGGQ42JtsiiRJ8HgiL/7FxcX4/ve/j0suuQQGw0mlwDEYDAaDwWCMGqhwsfdoGzp6glG3AdB6M2qbk4gZqjAxR7eqtbalr8JwMkyZWZmLmZW5eOZH52mPuXVX/ak8jWGPXswQHJkJVyKa8kiZdeeWl+HZt1XnzBg+YoapYAwEVbDwVm0HAIRUUcOYXRwV+2QuHBvZkeM1oSMRHMfBdZY+SpmDRY2bohhzSsCZIsW6qcQMcn8ysPQf2andlkpQ4XhBG6aGOyNihuT3oOOD5wGQAaRt/JyUj8tgjFQkT5fWRSA4s7RiXtmfXhfSyaDIEro+exMA4Ji2FIaMXE0QCHdFixdhrS+DzMeUUCBK4FAUJVIInaj8WxXj6evZvMn5sFsMoFVQWS5L1OteLALPITczOmbRmhV9PUunGFqPfeLZ5AuZiP/WMTNhLhqf+PG130NkniFrnRnxzox6UV3IoMgIt9REHYv+3E62+4HjBU1UkXT/H6hLhrc44rqgtPO3uQbMXajv3hjMvoxEj2E8SQGIkRrebAMnsFnccOekCsBNpuTZdcFgkBWBM6L42rljMW8Ku7Amo6OjA8899xxefPFFiGJkpaDbzUrRGQwGg8FgnNnQAc4XXxFHBMchqmtDXwIeiyTJ2HuUiBnnzipGhsOk3jf54Kulw4fGNrLKd2YlGXxkuiw4X10pu+doW9J9RzL6AnCDO/HAJ+u8r8OQWQBFDKHlzafRs+NdAMNLzOA4DnZd1BQQcWaY1L4MiqkgImYYnFl9Di0cUxZrMTOmvLK4583xghbNAo7XxJ9k0LiWYCMpK+cEIwRH6vf/kRJwImYoioKOTS9A8naDM1mQvfzbKfdnMEYyNGIKIM4MgQ6vT8GZEQxLWg9TIrxffaLribiSPCZ1p8U4M+j3pvwKcEYiaOqjpsTuVq3rI9GAO1bMMBkFLJpRpG2fOymvz2G7PmrKIPCwuJP1HqWHMasIxtxS7ftU0XWRmKnI7yESMxXfmdGrWAErcTAEY3oztH6jUyiypv0c1L0DRPpLTPkVpyUOUe/MOB1ihr7E3MDKvxlnIGmLGTNnzsT69esTbvP5fHj11Vcxffr0ATsxxsihodWDTV/U4u6nt+D7/70JrZ1ktVZf5Y5nMvv27cOzzz6LhoYGNDY24vjx+HxNBoPBYDAYjDMV2o8hSmSxVEGWHRZzZOhcnk+21zT3avG3lMO1XfCrkVIzK3NRrhaGJ+vXACKuDLvFgHElkcHyjPFklWtLhw/NauzHaEK/YjXZ6lVjZgGKb/4VrBXks56orkbmzfHF60OJfQJZURxsOAyxtwOhNtWZEZP1btaLGWmsWuYMRrjVmBX7lMUJ70OjpoxZhX1GPVFnhnYOGblJC8O1++jEDEUS0fb279D75T8BAJnnXhcXD8ZgjCaoIMCZrODNVl3M1Ml3Zjz7+h7c+cS/8OLGgwm39+7eBEDtiVCFUCoIxMZKaW6CrAKY8omIqS8BpxFTnNkGU15Z1L5hUUJjOxEByvIjg//z5kauV3Mn9X190osZGQ4TjDHXglSur2Q4pi4BQIbylrLknRJazJTOmSH542OmXI7IomhDbgWA6J+Tv+aA9ruMvT6mg6CWgOudGf5q8rOPcuINIlRw5kwWWEpS94INBBwvwDpmJgDAnCBGi8EY7aTtnfnBD36AG2+8Ed/85jdxwQUXgOM47NmzB4cPH8YLL7yAhoYGPPTQQ4N5roxhSCgs4UdPb4E3EJ9BnOmyJNjjzCYcDmPDhg3YtWsXABLRtmrVKowZw16AGAwGg8FgMChjYqI1ygujF8nQlay+gIj27gBy3JHBOhUminMdyHFbUZbvxJ4jbQldHJF91L6M8TlRGeRjijNgtxjgDYjYe6QN+WeXJTvEiIS3OsAZLVDCgbgycD2C1YmCG36G9vfXoOeLd8i+wyyj21I2BbzFDjnghe/Qdq07g5Z/U6LFjOTPWY97/ko4Ji+C4MxMuN0152KEWmvhnHFen8eKLdJNZ9hoUgdlodZaNL3yKPzHdwMAHNPORca8y/rcn8EYyYiqmGFwkpiiREP0dNlzhFzrX36/CjPG52DauEgsk+Tvhf/EPgCkU4FCxQzJ2wU5FACvxsrR2CljZgEEWwaCdVUINp3Q9guo5d+Wkong1N4bSl2LB7JMhHj6egYA08bmYPHMInh8Icyd3Pe1IS9LJ2bYzRCckU4qwZF1Sj067gVXwJhZAGvFjJSuBkHXXaIoMhRJhBIKkG06Z0ZFoQvTxmXDbjHCXuJBd83uKAdL1yevAwDMxRP6dLYlgrpAaGeG2N2KUNNRAIBt/FknfbxTwZhZgIKvPwjB4jhtrsWcS74L+6T5sKlCPoNxJpG2mDF79mw8++yz+M///E889thjAICnnnoKAJCbm4unnnoKCxYsGJyzZAxLRElGY5tXEzLcTjO6eoNYfelkFOU60lpJcCbR0tKCtWvXorWVfMAeP348rrzyStjtw+uDIIPBYDAYDMZQk59th8koIBSWAEScGpSiXDt4noMsK6hp6o0RM8iwamYlGVKVFUZcHIlQFAV7jkT6MvQIPIepY3Ow/UAT9h5tw4WjTMzgOA6mvDIE6w/BmJv6uXG8gJyLvwNzwRj07HwPzpkXnKazTA9OMMA2fi48+z5E946NUMJkqBYbMyXYMyC4ciD1tMGYkf7nlVTuB4MrGwX/dl9axzFmFZBCb5n8305HzKDODKm3HX41csd9zr8h89zrTkuECoMxlNCYKSpm0K6Gk42ZCosSWtQUCUUB/uelnXjmnvPhsJKuIN/hHYAigzOYYB07S9tP7+ASu5q1gTuNRjK4C2htRowzg/ZlxMcO0b4nm8WA7IzIIlCe53D/6nlpP6f8rMhrn8thgkEnuJ5KZBNArqWOJC40PdQhAyiQg35NyACiY6YMAo9f3n4OAMDzFXFbhlpOQJElhFqq4T9KFnq6F606peuZ5sxQxQxv1TbtHCylk076eKeKTXVKnC4Ee4bmomEwzjROqtVk8eLFeP/997F//37U1tZClmUUFxdj2rRprKz4DCMQFPHvj29CW5dfu+2R7y1CWUHygqozmZqaGrzwwgsQRRE8z+OCCy7AwoUL2YcPBoPBYDAYjAQIPIeyAieO1HYBAMYUZkRtNxoEFOXYUdfiQU1zr1b0HQiJ+OoEWcU7awIRJmj0aWunH75AGDZLdMl1TXMvOntJyXismAEA08dna2KGoiij7v1b3td+gEBdFRyTF6V1f+fMZXDOXDbIZ3Vq2CbMg2ffhwi3quWyHK/Ff+hxL7gCPbveg31Kes95IOEEI4xZhVqnhzGNqKuo58ALyL3s3+Gccf5gnSKDMaygMVOCkwiKWszUSTozGtq8Wrm2QeDQ2unHb9fuxo+/ORccx2lDcOu42VGOBsGRCc5ggiKGEO5sgimvHIoYhtRDRBZjZj54syqweLsg9naC43nNHZayLyPf2a/XlKiYKbsZnGAEb3NB9vXAcJJ9GScLb40sypT9vZCDkdmQvgBcjzm/AgCghIMIdzZprgxjbhlslXNP6Ty0zgw1ZspbRXqT7JVnxTliGAzG6OCkFQiO4zBt2jRMmzZtMM6HMULYcbAlSshwO81RFkdGNEVFRcjJyUEgEMDVV1+NkpKSvndiMBgMBoPBOIMZU+jSxIzYmCmARHPUtXii4qMOHO+AKMngOWC6Gh9SrovwqGnuxaTyrKjj0FiqLJcZJXkOxEKP09rpR3OHDwXZo8tVa8wqTDjwH4nYxs4GBAMgEee4MbMAnGCMu1/GvEuRMe/S0316GqacEk3MSMuZ4cqBuagSYncL8q68W+svYTDOBJLGTJ1kZ0ZDK7m/2STgOyun4rev7cHWL+tx1uQ8nDczH/5jXwIA7BOjY3s4joMhMx/h1lqE1c6gcHcLAKKMGDLzYbBnao6rUPMxKKIawy0YYC4aH3cu1CnY38WgsZ0ZAGDMyEPQ1wNjVlGy3QYEwRJ5vZQDXkj098HxSWMIDZn54ExWKCE/vPs/hverzwAAmYtW9dkdlAx9zJTk7dYcMbaJ80/peAwGY/iTtpixevXqtO7317/+9ZRPhjE8kWQFu6paUNfiwdpNhxAWZfh0HRlP3b0UJXkOWEzMnaPH5/PBZiNvLgwGA6677jpYLBZYLKxLhMFgMBgMBqMvaLSUycCjMCdeZCjLd+ETNEbFR+1RhYmxJW44bGSw47CZkOWyoKMngJqmBGLGIRJLNaMyN+EK2YqiDNitRnj9Yew90jbqxIzRBG+2wloxA/6jOwEAxpiIqeGCvpTcmNG3mMFxPIpuehSQZXAC+8zFOLOIODNozBR5PVDEEGQxBN5gSrqvnroWMmwvznHgkoUV2HGwBdv2N+H3r+/BBMUJRQwBvJCwZ8HoLkC4tRaiGi2llYHzBhic2eB4AaacEoRaqhFsPqH1N1iKKhOeHxXh9X0Zp0J2hkWLXHTZyeNkLfsmPPs+HHQHHWe2AhwPKDIkvwey6owQbM6kwgTH8TDnVyBQ+xU6P34NgAKDO79fLjnqApF8PfAe/oJEhZkssI6ZccrHZDAYw5u03wnV1dXF3SbLMjo7OxEMBlFcXIzKysoBPTnG8GDzjlo8/fKuhNvOmVmE8SXu03xGwxtFUfDpp59i8+bNuPnmm1FYSFa6ud3s58RgMBgMBoORLgunFeKtrcewYFphVCk3hQ6BjtR24ed//gwTyjLx2T4yYJoVExdVVuBER08A1TEl4JIkY9+xtoT7UASew7Sx2di2vwl7jrZh+fyTLyhlnD7sE+ZFxIyc4SlmmHJKta8NacRMAWQICOHUVi4zGCMVUZTiOjOoMwMAZL8XvDM9MaOhlXRsFOc5wHEc7rx2Fg4/+S909ARx6KMPUAHAWj4VgjVePKf9E2FVxKB9GUZ3nhZlZCoYg1BLNUJNxyF2twBIHDEVCktobCPnQmMQTxVB4FGQZUNDmxfZGaQ/w1ox/bS4tzjVgSH7eyEHPFpnBW9N/ZxM+WOIe0JWu1cXXtmvOCjBRmIoJV8vfGpUmG3cnLRFLgaDMfJIW8zYtGlTwtslScIHH3yAn/70p/jOd74zYCfGGD7QPEeDwMNpM8JmMeLSxRWYPSEPpf188R1teL1evPHGGzhy5AgAYMuWLbj++uuH+KwYDAaDwWAwRh55WTb86T+WJ90+uSILBoGHKMn4/EAzPj/QrG2j5d+UsgInvjzUqr2vpRyu69Icx4n6MijTx+dg2/4m7DsyOnszRhO2CfOADX8AoMCUMzyjXS3lU8GbbTBmF0cNZhkMRoSwKOFHj7+LuxXSaRTpzNB1NQQ8gK70OhX1asxUUS7ZP8Nhxs0rp+Gp//0ceZ7DAA/Yk0QT0f6JiJjRpN4eESPN+WPgwWYE6qogeUlEYiIxo77VA1nt7uivMwMAbr96Jr442IzFMwc3VioRETHDq4kZgi11dJa5YIz2teDI7Hf/Dy0AhyzCp0WFsYgpBmM002+PqiAIuOiii7B792488cQTeOWVVwbivBjDhO37m/D6ZjKYryx14/E7lwzxGQ1fjh8/jtdffx0eD3mTNGfOHFxyySVDfFYMBoPBYDAYo5MctxW/v/8CfHmoFYdrO3GophPVTb0oznVgypjsqPuWq7nksWIG7csozrUjx21N+lgzxhNxpK07gMZ2L4oSxF4xhgcGRybci1chUHsQ9gln973DEGBwZKLsrj+BEwxMGGMwklDb7IG/sw1QAw4MMTFTwMn1ZlAxoyQ3sv+SmUX4eEMnbAgBAGxJrhlG1UEldrdCkSWIXc1RtwPEcQAAkqdDvYWDUFiJ3722G4U5dlxx7jhwHIdq9XXIbjUiy9X/COqZE3Ixc0JyMX4wESwOiEBUzFQ6zgxKxvyvgTPE9xqdDLxePJElQDDANn5Ov47JYDCGNwMWuFlRUYG//e1vA3U4xjBh37F27evJFVkp7nnmIssyNm/ejK1btwIATCYTVq5ciWnTpg3xmTEYDAaDwWCMbvKzbLh4QTkuXkCin8KiBIPAxw2I6erXjp4APL6Q1qex53CkLyMV5QUuOG1G9PpIbwYTM4Y3Wed9fahPoU94o3moT4HBGNY0tHng5n0AABkcBDuJE+IMRnBGM5RwEJI/PTGj1xdCj5cIFkU6MUMQeKwo7gTqgRNiLhyiBYlabKgzA7IEsadd58wo0O5jzq+I2seUX4HPqrrxzicn1HMI48YVkyN9GfnOES9m6svYJV83gEjsUzJMeWWwjpsDJeSHa05y92W6xDpBrBUzwJttSe7NYDBGAwMSuhkKhbBu3TpkZ2f3fWfGiCAQErFm/X78Q3VllOY7cfPKqUN8VsMPWZbx17/+VRMyioqKcNtttzEhg8FgMBgMBmMIMBqEhMMhfS45XRW772gb9hwhYsbsPla18jyHaeOIO2PvkfaU92UwGAxG/2ls8yJDFTO6JSuaOwPaNho1JQe8aR2LujIAoFgnZiiKjKzurwAAu0Ol2vwjFqM7l5RdAwh3NkLsIp0YRp2YwVvsUR04ltJJ+OJgJP7w7/88hLWbDmsOwYGImBpqtN+D3wPJFykATwXHCyi8/j9QtPoX4E3JHZHpwhnN4HT9GCxiisEY/aTtzFi9enXC20OhEI4fP46enh7ceeedA3ZijKGjszeAbz/8PkRJ1m5jrozE8DyPiooKVFdXY8GCBbjwwp3Obu8AACAASURBVAshCKdeXsVgMBgMBoPBGHhsFiNyM61o7fSjprkX40oy8MwrJFt7fKkbZ08p6OMIwLRx2fh0byP2Hm1lvRkMBoMxyDS0ejVnRrdiw5FddbjuwokAAMHqgNTbkXbMVH0LuZ/baYbdGok1CjYcgezpBADsDZWh+7NqXHfhRLid0c4pTjDC4MqG2N2KQO1BKCJxeRh1nRkA6YOgEVTmksnY9QkRPbJcZnT0BPH82wdgMhBRZDSIGbSvQgp4IPvT68wYaDiOA291QuptBzge9gnzTuvjMxiM00/aYkZdXV3C2wVBwNixY3H55Zfj618f/nZeRt+sWX8gSshYOrsEN18+ZQjPaHghiiJ4ngfPkzch5557LsaMGYPy8vIhPjMGg8FgMBgMRjLK8p1EzGjswQsbvkJjuxcGgccPr5sNQejbsD5jPHFvdPQE0dDmjVrdy2AwGMON9vf/gu4v3gUUue87ny44DvZJC5C78vvgdavpAUDsaUPza0+AM1mQf9U9aGz3YgoVM2QbNu+ow7UXTCDDa7U3I92YKerMiL1u9+7eBAAwZJcgEMhGyBfGuq1HsfpSMv+oa+nFoZpOzJ2UD0NmAcTuVviP7db21zsxANIH4T34GQCgUShCt4e4/x6+bRH+/NZ+7DzYgpBIfh/l+ad36D8YRBwyEWcGf5rFDIAIKFJvOywlE7U4MgaDMXpJW8xYu3YtsrLY6vzRzqGaTmz6olb7/pl7zsOYIvZiQGlvb8fatWtRWVmJZcuWASDuDCZkMBgMBoPBYAxvygpc2HGwBZ/ta0R7D4krueGiiSgvTG/wUpbvhMtuQo83hE/3NuKaZZWDeboMBoPRLwINhwFZHOrTiEYBvAc+hhIOIv/qH4MTyEhK9HSh8X8fQrijAQDQ+NLDaG89R4uZ6pJtqGvx4Gh9N8aXuDUxI21nRgIxo+vTN9C7630AgHP6UqwcOw4vbjyItz8+DrvFiK2763G0jvRAnDOzCN/OzkcAexFsOAwAEBxZcd031jEz0bnlJZiLKrGtRu3oyLGjrMCFB741D//1x8+wX+0lHQ3ODO33oI+Z6qMAfDAwF4xBqPk4nDOXnfbHZjAYp5+0xYxVq1bh2muvxe233z6Y58MYYl545yvt62+umMSEDB179uzB22+/jVAohJaWFsyZMwdut3uoT4vBYDAYDAaDkQbl6uCorZsIGeNKMrDq/PFp78/zHOZPLcD722vwtw1fYWxRBuZMSlQVy2Awhhvr16/H7373O9TW1qK4uBi33XYbrrzyyqT3l2UZzz77LNauXYvW1laUl5fje9/7Hi677DLtPr29vXjqqafw/vvvw+PxYMaMGfjxj388bPoTC294EMGGw1CGkTMjWFuFzq2vwHf4C7SsewZ5V9wFOehD00tEyOAEIxRZQqjpKK5FL2x8kOxocwM+YMvOuhgxI73OjIZWcr/iXOIk6P7iXXRseoEcesI8uBd8DZcHZfxj82H4AiLWvH0gav+dVS347gr1eq/+PI2Z+ahu6sFPf/cJzp1TjO9eMR2W4kqUfO83MDjc2PHsFwCAuZOJe8NiMuDB78zHn97ch9xMGzJdllP8KQ4fBLUAXOxu1YSz0x0zBQA5K26Da95lMOWxRaYMxplA2mJGR0cHcnJyBvNcGENMtyeILw+3at9fsqBi6E5mGBEKhbBhwwZ8+SXJVXY6nVi1ahUTMhgMBoPBYDBGEPpVsAaBw13XzYYhjXgpPd/52jQcru3CicYe/PL57fjl7edgfGnkPWFzhw9fHmrB4hlFcNhMKY7EYDBOFxs2bMC9996L1atXY8mSJfjnP/+J++67DxaLBZdccknCfR599FG88sor+NGPfoRJkybh7bffxj333AOHw4GlS5cCAH74wx/i4MGDuOeee5CXl4c1a9bgxhtvxLp161BaWno6n2JCeJMF1orpQ30aUdjGzAQ4Dp0fvgzvgY/RKhgRbqtDqKUG4A3Iv+bHkPy9aF33G4wztmj7lY4pBdqAD3fV4abLp0KwElEinZgpWVbQoHNm9O7ZjPaNfwQAWMfORP5V94ATDHDagFXnV+J/3z0Il92ExTOLMLMyF796/nP4AiLaZGfUAM2QmY+3Pj2BLk8Q6z48hovnl6OswAVTdhF6vCEcqiFdHHN1orfNYsQPrpvdz5/i8EGLmQr6Irf1UQA+GHCCAeb8itP+uAwGY2hIW8xYuXIlXnnlFSxatAglJSWDeU6MIeDVDw7hrzpXxrcum4IMh/n/s3ff4VGWWQOHf1OSSZn03gslQELoLYCASBeUYGFdV3fFtqvrp64rwrpNXV1XRXF1rQsW1FVQQcEAIr0X6SWUdNJIn/RM+f6YzCSThBAgYUhy7uvycvK87XkRJzPvec45rRzRPeTm5rJixQoKC82poL179+aWW27BxcXFzjMTQgghhBCXI8zfDbVKgd5g4s5JMVeUgezq7MDfHhjJH/+9jQvFVfz9w9288thYAJb/dIaf9mVgMJrYevA8LzyccNlNwssra3lr+WH6RXkz64Yelz0/IURzixYtYtq0aSxcuBCAsWPHUlpayuLFi1sMZmRkZPDZZ5/x3HPPcfvttwMwatQo0tLS2LZtG+PGjePo0aNs376dN998kylTpgAwZMgQRo4cyddff83jjz9+7W6wk/EccxvG2ipKd6+i/Ohm86BCif+tj+PScwgAZ1Lz8Dz6lfWYvv16wL5sispqOHr2AhGXUWaqoKTK2qcisPI0Fza8DYBTWF8CbpuPQt3QEPzOm3ozblAofl7O1mB3sK8r2QUVnC52oHEnUQfPQA5sbwi4rNh4hifvMs//YHI+JhM4qpXE9ei6i4KVzs17R6lcpLqHEKJjtTmYoVQqSUlJYcqUKYSHh+Pj42NtgGyhUCj4+OOP232Sov0ZDEbW780gM0+HAvhuW4rN9lH9g+wzsevIsWPHWLlyJQaDAaVSyaRJkxgxYsRlfykVQgghhBD256RR8+RdQ8gpqLis8lJN+Xg48/cHRvH0v7dRUl7DH9/chq6yFoPRZN3nyNkC9hzPZWTc5X2m/mbzWXYcyWb3sRxuHBaO1tnh0gcJIS4qMzOTjIwMnnzySZvxKVOmkJSURGZmZrMsig0bNuDk5NSsDNWyZcusr3v16sWXX35J3759rWMODg4oFApqamo64E66DoVCgfeNv8JUW03Zz+sA8Lv5EbR9R1n3Oec6iMzKc9zqcgBQEBAZRd/Iak6mFbHpQBb39Wp7MMPSL8NBaYRdn4LJiCaoB4F3LmzW80KhUBDk62ozNqCXH9kFFRw4b7IJZpSrPckpaChzteXgee6a0odAH1cOnMoDoH9PXzQOqjb/2XQ2KifbYIZC7djsz1QIIdpbm/Oqd+zYgZeXFwEBAdTU1JCdnU1WVpbNP5mZmZc+kbA7g8HIg//8if+sOMz321JsAhm3juvBd6/OsmmM1V35+fkB4OXlxbx58xg5cqQEMoQQwg5Wr17NjBkziI+PZ9q0aaxcubLV/Y1GI++88w4TJ04kPj6emTNnsmbNGpt99Ho9b7zxBuPGjWPAgAHcddddHDlypCNvQwhxHRg7MIQ7bup92eWlmgoLcOPP80bgqFZSUl6DwWjC19OZ386JZ3CMuaTIku+PU6dve6366ho9STvTADAYTRxMzm/9ACHEJaWkmL/rRkVF2YxHRJhr66empjY7Jjk5maioKHbu3MmsWbPo168fkydP5ocffrDu4+TkxMCBA9FoNBgMBtLS0pg/fz5Go5FbbrmlA++oa1AoFPhMvR+/mY8S9Mu/4RY/3mZ79oUKNlXHstN3Dv5z/oDa3ZfxQ8wVQnYdzcHo4Ay0rcyUJZhxo1cmhvJiUKrwT3wKpaZt1Rbie5kzK46kV6Bs1Nz6VJF5bbCnVoOvhxNGo4lvN5/FaDTxc/3795A+AW26RmelbBLMUNqhX4YQovtpc2bGxo0bO3Ie4hoqLKsmv6ihpmF8T1+cNWr8vJz55dQ+3fqBvcFgQKUyr5wICAjgrrvuIiQkBI1GVhcIIYQ9dFSd63/84x98++23PPXUUwQHB7N06VJ+/etfs2rVquuizrUQ4vrXL8qHP/1mBKu2nWNkXBA3DQvDQa0iLtqHQ69dIKeggjU7Url1XEO5qJyCClZtPcfo+GD697QtPbJhXwblVXXWn/edyGXswBCbfUwmE1/9dJr0HB0qpQKVSoFKqaRvpDc3DQ/v2BsWohPS6XQAaLW2D11dXc2r78vLmz8MLyoqIicnh4ULF/J///d/hIaGsnz5cp544gm8vb0ZOXKkzf4vvviiNWvjscceo0+fPh1xK12OQqHELX5Ci9tyCs0ZD6bwQWj7mLNfxgwI4b1vjlBVoyezxIQWcwNwk8nU6jOM8xfKUWJkjPIwGEAbNxYHT/+L7t9U//oyUbV6I3XO3qiqzH+n9mWZg9WD+/jTI8SDD1Yd48e9GQzpG0BpeS0AQ/q2/TqdUdMyU/Zo/i2E6H4uGsxYsGABc+fOZcCAAddyPuIae+uPE4gIlF84JpOJHTt2cPz4ce677z4cHMwp/dHR0XaemRBCdG8dUec6KyuLL7/8kj//+c/84he/AGDMmDFMmTKFDz/8kL///e/X7gaFEJ3a4D7+DO5j+7AqPNCdaaMiWbMjlf/9mMyEIaF4aDUcOXuBf368D11lHRv3Z/DmHyYQ6FPfxNZoYtXWcwB4aB0pLa9l/8l8DEYTKmXDQ7qfk/NZlnSq2TzW70knvpcv/l7S102Ixkwmc/m3pg+7LeNNS2cD1NXVUVRUxLvvvsuECeaH7aNGjSIlJYW33nqrWTBj9uzZTJ48mS1btvDvf/8bk8nEo48+2hG3021YGnYHNyr55O7qSHigO2k5ZWSWGOgLYDRgqqtG4eh80XOdzy9ngGM67oYSQIHnqNmXNRcPrYaoYHdSs8soMrnjBygcnTmQYg64DOnjz/B+gfzvx9PoKmtZ/L+D1rkH+3btihcKtSOo1GDQA6CyQ/NvIUT3c9H86m+//ZaMjIxrORdhB125fmNblZeXs2zZMn766Sdyc3PZuXOnvackhBCChjrXkydPthmfMmUKKSkpLZa3bK3O9bPPPgvA7t27MRgM1oadAI6OjowfP56tW7d2wJ0IIbqbX0yOwdVJTUVVHV+sT2btrjT+8t4udJXmzIuqGgNv/O+gtc/GnmM55BaaM6ef/IW5gayuspbk9CKb8/64x/z9LMjXlUnDw7lxaBiWWIfl4Z8QooGbm/nhatMMjIqKCpvtjbm6uqJSqRg9erR1TKFQkJCQQHJycrP94+LiGDFiBE8//TSzZ8/mgw8+wGAwtOdtdCtVNXqKdea+I037V/QM9QTg3AW9dcx4iVJT5wvKmex0FACXmOE4+oZe9pzie5pLUKdXmIMmdc6+1OpNKBUwKMYfJ42aW24wL4Qsq7BkZXTtElNg/v+icd8MlbMslBVCdLyrKxYrRCd37tw53n33XWst1SFDhpCQkGDnWQkhhICOq3OdkpKCh4cH3t7ezc6bnZ1NdXV1e9+KEKKb8dBqmDs5BoA1O1J5e8VhDEYTkUHuPHq7OfP9eEohq7aYszFW1v97WL8ABvfxJyLQ/IB134k86zlLy2vYczwHgLmTYnjszkE88YvB+HqaH67lFVVdm5trQldZy6qt57hQbJ/rC9Eay2eIpgs109PTbbY3FhERgdFoRK/X24zX1dVZMzxSU1NZsWKFNcPDIjY2lurqakpLS9vtHrqbxk21m2Y29AwzBzNO5TQ0WTdUV3AxNXUG/MrPEKwuAcArIfGK5jSgvm9GUkEojpEDOOZmblbeO9wLNxdHAGaMjsJZ01D8ZEifrl1iyqJxqSmlZGYIIa4BCWaIbslgMLBhwwaWLVtGRUUFGo2G2267jZtvvtlaYkoIIYR9XW2d67vvvpsPP/yQ2NhYnnjiCXbv3m09ruk5G5/XslpTCCGuxozR0TarikfEBvLyo2OYMjKSaQmRAHyadJJ1u9M5mWbOwJg9ricAw/oFAua+GRabDmShN5hwcVKTEB9kHff3NpeWyiuyz3vXqi3n+HDVMT754YRdri9EayIiIggNDWXt2rU24+vXrycyMpLg4OBmx4wdOxaTyURSUpJ1TK/Xs23bNoYMMWdOnT59mj/96U/s2bPH5tjt27fj7++Pl5dXB9xN92AJZjhr1HhoHW229aoPZmSVNGS+GOt7WLR4rgvlTHI6AoA6rD+a4J5XNKfYaB+USgUFei05gx5kbbYPYJt9oXVxZHr9e7ujWklcD9+WTtXlKJ0afs+pXDzsOBMhRHfRagPw/fv3X3Z6ZNOyDuL6kl1QzoK3t9t7GnZVUVHB//73P7KysgAICQlhzpw58oFTCCGuMx1V57rpKspLXU8IIa6Eg1rJ/905iHe+PszI/kH8YnIfa/+L+26O5VDyBXIKK3hr+SEAeoR6ENfD/IBsWL8AVmw8Q3qujryiSvy9nPlxr3kl+bhBoTg5NnyNM/fJKCTfTpkZ2fUPHhuvphbievLII4+wYMECPDw8GD9+PBs3biQpKYnXX38dMC+EyMjIoGfPnmi1WkaNGsW4ceN44YUXqKysJDIyks8//5zz58/z2muvATBhwgRiY2OZP38+TzzxBD4+Pnz//fds2rSJV155RT5LXIXsgvp+GX6uzf4cI4PcUSkVGIxKjA7OKOuqMLaSmXHh1CGi1AUA+N5w2xXPycXJgd5hnpxKL2btrnTr+13T7IvbJ/ampLyG/j18u01Jb9syU5KZIYToeK0GM7766iu++uqrNp3IZDKhUCgkmHGdKSqr5rXPDlBYWk1RWRVVNbbBKRen7peF4OTkZH1glZCQwI033ohK1T0+aAghRGfS3nWuV6xYAZgzPVrKvrCMtZS1IYQQVyI22oe3/nhjs3EnjZonfjGYZ97eRn3bDG4d19P64C4mwhs3F0d0lbXsP5FLr3AvMnLNq48njQi3OVdgfWZGfnFlB97JxRWVmUvzFeukRJ+4PiUmJlJbW8uSJUtYvnw5YWFhvPzyy0yfPh2AzZs3s2DBAj755BNGjBgBwJtvvsnixYt5//33KS0tpV+/fixZsoS4uDjA3Gvrww8/5I033mDRokUUFxcTExPDf/7zHyZOnGi3e+0KLIGCIB/XZtscHVREBLmTcr6UWoUTTlRhqG65Z4axthqnI18DkK0MIioi9qrmFd/Lj1Ppxeytz5jz1GroEeJps4+rswOPzx18VdfpbGzLTEnPDCFEx2s1mHHHHXcwcODAazUX0Y4MBiNGk4k9x3I4cragxX3+/sAo3F0dW9zW1ViCbQAqlYo5c+ZQWFhIz55XlmYqhBCi4zWucx0TE2Mdb2uda0fHht9xjetcR0dHU1JSQmlpKR4eDenw6enphIaG2hwnhBAdpW+UN3Nu7MXyn87g7+XMmAEN5W5USgVD+/qz6UAWe0/mkZpTBphXJVsa4Fo0lJmyTzCj2BrMqLH5zC3E9WTu3LnMnTu3xW2JiYkkJtr2UnBycmL+/PnMnz//ouf09vbmueeea9d5djflVXWolAqbXhOWbK9gv5YXl/QK8yTlfCkVRkecaLkBuFFfS97yf+JacR6jCc76jmPMVb43xff05asNp60/D4rxQ6mU9ztl48wMCWYIIa6BVoMZQ4cOZebMmddqLqIdpJwv5Z8f7yOn0HbFqadWw11TzA+C4nr4EhbQfdL/CgoK+Pbbb5k6dSphYWEAeHl5SVkpIYS4zjWucz1p0iTr+KXqXP/3v/8lKSmJOXPmAM3rXCckJACwbt067rjjDgBqa2vZsmULY8aM6ejbEkIIq19O7UtEoDu9wjxRq2xL5w3rF8imA1kcOVOAg9q8bdKI8GbBAkswo6ismjq9AQf1tc04LtaZG/HW6Y1UVOvROne/zG8hxOUrKKnid//aiI+HE288Od5alinHUmbKt3lmBpiDGet2p1Naq8JHSbMyUyaDnvyvX6Uq7SgAX1WOJCKs/1XPt2+kNw5qJXV6IwBDG/XL6M5sykxJA3AhxDXQajBDdC4rt5zjv98da3Fbv2hvpiU0X8Ha1R06dIgffviBuro6vv32Wx555BEpKSWEEJ1IR9S5DgkJYfbs2dZ9IiIiWLp0KaWlpdx///32vF0hRDejUioYNzi0xW2DYvxRKRXoDUb0BiNqlZLxg8Oa7Rfg5WJ9nV9cRchFVjN3hOoaPVU1euvPxWXVEswQQrTJgVN5VNXoycov56d9GUxPiKKqRk9RmTlAGnSRYIYlO620zgE0YGiUmWEyGsj/7k0qzx4AYFXVUHbV9GZCyNVnDDg6qOgb6c2RswUoFeb3aNGkzJSzZGYIITqeBDO6kGPnbMtJPXr7ACIC3VEqFfQI8bjIUV1TTU0NP/zwA0eOHAHA3d2dW2+9VQIZQgjRyXREnWuA5557Dnd3d95//30qKyuJjY1l6dKlRERE2OU+hRCiKa2zA7HRPtaSsaP6B7VYItbHwwmlUoHRaCKvqPKaBjOKmvTJKNHVdKsMcCHElUtOL7a+/nrTWaaMiLD2ywAI9m35vSw80B0HtZJKk/n90NioZ0bhj0upOLEDgKp+N7NxuzdKBfTv4dsucx4eG8iRswXE9fDFzUXKkgIonRqCTipn6TsnhOh4Fw1mzJ49m/Dw8IttFtexGwaG8MdfDbX3NOwmJyeHFStWUFRUBECfPn2YNWsWzs7Odp6ZEEKIK9ERda4dHR1ZuHAhCxcubNe5CiFEexrWL8AazJg0vOXvZiqVEj9PZ/KKKsm/xn0ziutXUFt/libgQog2OtUomJFfVMnWQ+dxrC+T56xR46FtOVjgoFYSFexO5QUN0FBmqrYwm7L9awHwGDmLrZVDgHNEh3qibafAw81jovHQaujfw6ddztcVOPqaswsdfEJQqGS9tBCi4130neall166lvMQV2HNjlQ+W3uKiuo6ADzdNHaekf3s27ePdevWYTAYUKlUTJ48mWHDhkkjQiGEEEII0emMHRjCio1nCPbVMqCX30X3C/B2MQczii8dzPj3V4c4cCqPhb8eTu/wq+sh1zR4YemfIYQQrSmvqiMzTwdAoI8LuYWVLP/pDOPry+4F+7m2+h2+Z6gnlfnmAIWlzFTprm8BE2pPf7wn3M3hN7cDMKBn+2RlgLk04PiLlAbsrjRBPQi+9x+o3S/+O0oIIdqT8tK7iOuVyWQiv7iSpJ2p6CprMRpNAAT6tFxbsjuora3FYDDg7e3NvHnzGD58uAQyhBBCCCFEp+Tj4cwnf53KS4+MQam8+Gda//q+GXmXyMzILaxg/Z50Ckur+cfSPRSWVl3V/IrKmgQzyiQzQwhxaWcyzFkZSgU8PncwAJl5OpJ2pQEQdIlnGr3CvKhqVGZKX1aA7ugWADxHzaai2kBKVgkA8a0EgkX7cArtg9pdslWEENeG5IB1QtW1ej5fl8y3m8/ajN80LJwbh4URG9V9f4kkJCSgUCgYMmQIGk33zVARQgghhBBdQ2tBDAt/b3Mw41Jlpjb/nGV9XVRWw4sf7eWl343B0eHK+so1LzN1+ZkZdXoj329LISLIjSF9Aq5oHkKIzsVSYio80J3YaB+G9g1g/8k8CkrMAdbgS/T+6RXmyWaj+fu+vlJHye7vwGhApfVCGz+evacKMZpArVLQL9K7Y29GCCHENSXBjE7ko9XHOZFaxMm0ombb1Colk0aE068bBTKMRiPbt2+npqaGSZMmAaBQKEhISLDzzIQQQgghhLh2ArzNveFay8wwmUxs3J8JQGy0DydSCzmdUcJbyw/xxC8GX1E289VmZphMJv6z4jAb9mXg6qTm8+entyl4I4To3JLTzc80YiLMpe5un9iL/SfzrNsvlZkR6q+lTu0EgKm2Ct3BHwHwGDELpdqRw2cu1J/fGyeNPPYSQoiuRN7VO4m8okq+3nS22fik4eHcNrEX7q4atM4OdpiZfeh0Or755hvS0tIA6NmzJ1FRUfadlBBCCCGEEHZgKTNVrKuhps6ApoVMi+SMYnIKzI1yH5rdn4PJ+SxdfYJNB7KIDPIgcULPy75uSX0mhlqlRG8wXnZmxtebzrJhXwYAFdV6inXV+Hg4X/Y8hBCdh8lkIrk+M6NPhDlrol+UD7HRPhxPKQTMPTNao1Ip8fb1gQpQYMKkr0XppMV9kHmR45GzBUD79ssQQghxfZBgRiehNxitr2eP70mvUE9GDwjuliuXzp49y7fffktlpXnl2bBhwwgLC7PzrIQQQgghhLCPAO+GB38XiisJ9Xdrts+m+qyMqGB3ooI9iAxyJzWnjM0HsvhozXGCfF0Y1T/4sq5rycyICHLjXFapNbjRFjuPZPPxmhM2Y3lFlRLMEKKLyy6ooLyqDmjIzAC4Y2Jv/pqyC5VSQcglykwBBAf7w5mGn92HTUepcaa4rJqMXHNzcemXIYQQXY80AO+EbrkhmrGDQrpdIMNgMPDjjz/y2WefUVlZiZOTE3fccQfTp09HrZa4nBBCCCGE6J68PZxQ1X83yC9q3tS7Tm9k26HzAEwYYl4EpFAoePT2gfQK88Rkgn99up8Dp/KaHduaYp05mBEd7AFAaUUNhkaLsC7mTGYxr33+MwB9I71xdzU38r1UA3MhROdnKTHl6uxgE7QYFOPH43MH8fSvhuKhvXT/y7CIQOtrhYMTHkOnAw1ZGRpHFb3DvVo8VgghROdl92DG6tWrmTFjBvHx8UybNo2VK1e2uv+FCxd49tlnmTBhAoMGDSIxMZGkpKRrNFv7KNZV8/In++w9DbsqKSlh6dKl7Ny5E4CwsDAeeugh+vbta+eZCSGEEEIIYV8qpQI/r/q+GcXNAwL7T+ahq6xDqYBxg0Ot4xoHFX+9fyRhAW7oDSZeXLqXo+cK2nRNvcFIaXktAD1CzMEMkwlKK2pbPa5EV8MLS/ZQW2cg0MeFP/1muLU+fm6hBDOE6Ooszb9jwr1sIajf+gAAIABJREFUFmgqFAomDgsnIb5tGWI9IgMwmOqPjxmHysWckWbplxEb5YOD2u6PvIQQQrQzu76zJyUl8dRTTzF69Gjefvtthg8fzvz581m7dm2L+9fW1nL//fezc+dOHnvsMd566y3i4uJ4/PHHWb169TWe/bWx/2Qe9/xtHanZZdYxJ8ful4Wg1+vJz88HYMyYMfz617/G09PTzrMSQgghhBDi+mDpm5FXWNFs26YD5hJTA3v74+3uZLPNQ6vhhYcTCPJ1pVZv5Pn/7uZU/crp1pSWN5SUig5p+Fx+qSbgm3/OpKisBmeNmr/MG4mHVkOAT/3ci5rPXQjRtSSnWfplXF3WRIifG9uNAzldF8g7p0PRVZoDqZbMjHjplyGEEF2SXZ+KL1q0iGnTprFw4UIAxo4dS2lpKYsXL2bq1KnN9t+6dSunTp1i+fLlxMfHAzB69Giys7P54IMPuPnmm6/p/DtSia6G3/3rJ3SVdTbjz9wzDNdu1OjbwtfXl1mzZuHi4kJ0dLS9pyOEEEIIIcR1JcDbHBDIL7YtM6WrrGXfiVwAJgxtuc+ct7sTLzycwDNvb+dCcRV/+2A3r/x+LGEBzXtvWBQ1ClqEBWhRqxToDaZLNgE/mGxeNT06Pth6fsvcpcyUEF1bdY2etJxSAGLqm39fKaVSQdxt9/OPpXsx6Or42we7ePT2gdb3kQHSL0MIIboku2VmZGZmkpGRweTJk23Gp0yZQkpKCpmZmc2OcXV15c4776R///4249HR0WRkZHTofK+lOr2Blz7eaxPImDIygu9fu4XRAy6vKV9ndeHCBb766itqaxvS1OPi4iSQIYQQQgghRAuswYwmAYFth86jN5hw1qgYGRfY0qGAObPjhYcT8HbXUFFVxxfrk1u9XnGZOWjhqFbi6uyAp5s546NEd/HMjNo6A8fqy1gNiml40GhpYC7BDCGuveoaPVt+zuK5/+5m3gvrWfT5AQ6cykPfhv43rTmdUczvX93Ee98ewWA0AXAmq4T6l/QOv/pKC8P6BfKHXw5BqYDTGSX86Z0dgLkfR1R9+TshhBBdi90yM1JSUgCIioqyGY+IiAAgNTWVsDDblUOjRo1i1KhRNmN1dXVs2bKFXr16deBsO15xWTU1dQbKq+p49p0dVFTrrduWPDvZWgO3qzOZTBw8eJCkpCT0ej0ajYZbbrnF3tMSQgghhBDiuuZvyW5o0jNj037zIrGE+OBLlqsN9tVy74x+vP7FQXYeyaawtAofj5a/h1gyM7zcnVAoFHi5aSgoqWo1M+NEaiG1eiMKhe2q6cD6uReWVKE3GFGrpM69EB2pTm/k4Ol8tvycxZ7judTUGqzb8g9kselAFu6ujoyMC8JD62jdpnFUcdOw8Iu+L1ikZpfyl/d3UVFVR1pOGTW1Bh69fSDJ9f0yQv21aF0cWz1HW40dGEJNrYHFXx60Lgjt38MHVaN+HEIIIboOuwUzdDodAFqt1mbc1dW8Kqe8vLxN53n11VdJS0vj7bffbt8JXgMGo4kf96Tz9orDF91n/j1Du00go6amhtWrV3Ps2DEAPDw8GDx4sJ1nJYQQQgghxPXP0jOjRFdDTZ0BjYOK1OxSa7PdGy9SYqqpsQNDWPr9CUrKa0jamcbd0/q2uJ8laGHpwWH5d2vBDEuJqR6hnnhoNdZxS88MowkuFFcR5OvaprkKIdrOaDRxPKWQLQez2Hkk26YShFqlZGhff/pEeLP/VB7HzhVSVlHL+j3pzc6zdlc6Lz8yxhpAbSozT8ef39tJRVUdDmoldXojP+7NwFmjtmZf9bnKElNN3TQ8nOpaPe99exSQElNCCNGV2S2YYTKZcwsVCkWL40pl66txTCYTr7zyCh999BHz5s3jpptu6piJdqB3vj7Mut3NPxxY/PORMcRG+1zDGdlPdnY2K1asoLjY/GWrb9++zJo1Cycnp0scKYQQQgghhAho9GAxv6iSsAA31uxIBSDET0v/Hm1rhuugVjFlZARfbjjN2t1p3DmpNw5qVbP9LI2+Pd00Nv9urQH4wdP5AAzqbfug0dfTGaXCHMzIK6qQYIYQHWDxlwfZuL+hnLdCAf17+DJucCgJ/YOsmRJzbuzFheIqth06z9FzBTblppLTiygoqeLZ93byz0fGWIOYFrmFFfz5vZ2Ultfi5uLIS78bzZodqSTtSuO7bSlYkiVirrL5d0tuHhONk6OaE6mF3DQsvN3PL4QQ4vpgt2CGm5u52VvTDIyKigqb7S2pra3lmWeeYc2aNcybN4+nn3664ybagdJyyqyvI4Pc+f0dA/F00+CgUuLl3j0e4ptMJnbv3s2GDRswGo2oVCqmTp3KkCFDmgW6hBBCCCGEEC3zcneyNuHOK6rEy92JzT9nAXDzmKjL+mw9LSGSFRvPUFpey7ZD57lxaPMHg5YyU5aHmV5urWdmFJdVk5pt/v4zKMbfZptapcTX05n84ipyC5v3zTCZTJhM5oa/Qogrc+i0OTMqMsidm4aHM2ZA8EXLRfl5OZM4oSeJE3rajB89V8Df3t9FToE5aPHS78bg7upITZ2B/SfyWLr6OIWl1bg4qXnuwVFEBLnzcGI8VbV6Nh/IsvbL6IhgBpgzNG4aLoEMIYToyuwWzLD0ysjIyCAmJsY6np6ebrO9qfLych566CF+/vlnFi5cyL333tvxk+1gd0/tw52TYi69YxdkMplITk7GaDTi6+vLbbfdRkBAgL2nJYQQQgghRKeiUirw83Qhp7CC/OJKzl8op6bWgLNG1eYSUxY+Hs4kxAez7dB5vt+WwoQhYc2CIcU6S88Mjc2/L5aZceiM+UGqk6OqxRIzAd6u5BdXNWsCXl2r58k3tqJUwEuPjMGtnersC9HdlFfWAnDP9L4M6xd4Refo38OXhb8ZzgtL9pCRq+Mv7+8kItCdXUdzqKox9/10dFDxl3kj6RlmbvCtVCp4/M5B1NQa2HU0B62zA+GB7u1zU0IIIbodu3VWi4iIIDQ0lLVr19qMr1+/nsjISIKDg5sdYzAY+O1vf8vhw4dZtGhRpw5kmEwm8us/qHfnFUZKpZLExESGDx/OAw88IIEMIYQQQgghrpCl1FRuYaW1xNSEIWG4ODlc9rlmjokG4GxWqbVpb2PWnhlulswMjc14UweTzSWm+vf0xUHd/GtoYH3fjKbBjJOpRWTm6UjP1fH+yqOXfR9CCKipM1CrN5eLutqA4JA+Afzx7qEolQrOZZWycX8mVTV6lEoFQ/sG8I/fJjQrl61SKfnj3UOYNyuOhb8eLs25hRBCXDG7ZWYAPPLIIyxYsAAPDw/Gjx/Pxo0bSUpK4vXXXwegqKiIjIwMevbsiVar5X//+x979+7lzjvvJCgoiEOHDlnPpVAoGDBggL1u5bK9veJwq83xuiqj0cjWrVuJjIwkMjISAHd3d6ZNm2bfiQkhhBBCCNHJWRrybj6Qaf2uMWN0yxnvl9In0oseoR6cyyrl++0p9IlsyKYwmUwUl5nP79WkzFRVjZ7qGj1OGrXN/gfrS9wM6m1bYsrCEojJK6qwGT+d0RBI2Xwgi4T+wYzqH3RF9yREd2XJygDQulx+cLOphPhgnvjFYN775ggRQe7cMCiE0fHBeGg1Fz3GQa3i1nE9rvraQgghuje7BjMSExOpra1lyZIlLF++nLCwMF5++WWmT58OwObNm1mwYAGffPIJI0aMYN26dQB8+eWXfPnllzbnUqlUnDhx4prfw5U6kVpofd34i0FXVlZWxjfffEN6ejoHDhzg4YcfxtVVmvsJIYQQQgjRHvy9zfXvLYGM+J6+V1zORaFQMHNMNG/87yA7Dmdz38wqa319XWWdtSmwV5MG4AAl5TUENgpmpOWUUVI/p0Exts2/LRqCGbaZGaeaZIX8Z8Vh+kV5t/rQVAhhS1dZZ33dXqXaxg8OZfzg0HY5lxBCCNFWdg1mAMydO5e5c+e2uC0xMZHExETrz5988sm1mtY1c8/0vvTv4WvvaXS406dPs3LlSqqqqgCIjY1Fo5EvIEIIIYQQQrSXAC8Xm5+vNCvDYuzAEJZ8f5yyilo27M2w9vlr3BfD0gC8cTCjuKyGQJ+GRUsHk81ZGX5ezoT4aVueu7d5/9LyWqpq9Dhr1JhMJmtmxi8mx7Bq6zlKymt455sjPHPPsKu6NyG6k8aZGa7OV5+ZIYQQQtiL3XpmCLMrqV/bmRgMBtatW8cXX3xBVVUVzs7OzJ07l6lTp6JW2z2WJoQQQgghRJdhKTMF4OvhxIjYK2vya+HooLKuvN5/Ms86bmn+rVSAe32GhJOjGhcntc12i4Onzf0yBvX2b9ZI3CLAp2Hult6CeUWVlFWYH8KOjg/m/llxAOw4nM22Q+ev6t6E6E4smRnOGjVqlTwGEkII0XnJbzHRYYqKivjvf//L7t27AQgPD+fhhx8mJibGzjMTQgghhBCi6wloFMyYlhCFqh0eWg6KMfe4OJ1RTHmV+YFoUX2/DA+txqaRb0tNwGvqDBxPKaw/V8slpizHOtY3Bs8tNPfNsDQed9aoCA1w46bh4QztGwDAO18fsVltLoS4OMv/K27t0C9DCCGEsCcJZogOc+7cOXJycgC44YYbuPfee3F3v7KavUIIIYQQQojWebs7MaxfABGBbkwZGdEu54yL9kGtUmI0wZEz5nJRljJTlubfFp71TcAbZ2YcP1dInd6IUgEDel08mKFQKKyZJZa+GZYSU73CvFApFSgUCh69fQBOjip0lbVs3J/ZLvcoRFdnyczQtlO/DCGEEMJepM6P6DBDhw4lLy+P2NhYoqKurl6vEEIIIYQQonUKhYK/zBvZrud00qjpF+XNkbMF/JycT0J8MEX1wQrvJsEMS2ZGSaPMjL0ncgHoFe51ycbDAd4uZOWXW4MZyfXBjN7hXtZ9fDycGT8kjLW70kjalcbMsdEXLV0lhDArr5LMDCGEEF2DZGbYQX5RJZl55faeRrvLy8tj+/bt1p8VCgU333yzBDKEEEIIIYToxAbXl5o6mJyPyWSipL7MlFejpt/QENwort9uNJrYdTQbgFFxQZe8jqVpeF5RJXV6IynnSwHbYAbAtFGRAGTll3OsvoRVa7YezOKVZfutZbKE6G4kM0MIIURXIcGMa+xMZjHz/vGj9efGNWY7K5PJxP79+/nwww/56aefOHHihL2nJIQQQgghhGgnlr4Z+cVV5BRUWDMzmpeZsvTMMG8/nVFs7a8xqv+lgxkBjcpMpWaXUqc3AhATYRvMiA7xsI6t3ZnW6jlNJhMfrDzG1oPn2bA3/ZJzEKIrsvTM0DpLZoYQQojOTYIZ19g/P95n8/Pw2EA7zaR9VFdXs2LFCtasWYNer8fT0xMPDw97T0sIIYQQQgjRTiKD3PHUmgMVB5PzrT0zvJtkZnhZe2aYAxg7j+ZYjw/2017yOg3BjAprvwxfT+dm5aygITtj59Fsm7JWTRWWVlNSbt5+7NylsziE6IrK6zMzLlXqTQghhLjeSTDjGqqq0ZNfXAWAu6sjX704o8UP5p1FVlYW7733njUTIzY2loceeoiQkBA7z0wIIYQQQgjRXpRKBQNjzM27f06+YM22aJqZ4eVu6ZlRjcnUqMRUG7IyoCGYUVVjYP/JPABimpSYshgzMARXZwf0BhMb9mVc9Jznskqsr0+kFmI0mto0F9G1rF69mhkzZhAfH8+0adNYuXJlq/sbjUbeeecdJk6cSHx8PDNnzmTNmjU2+5SXl/Pyyy9z0003MXDgQGbOnMnnn3+OyXT9/R3TSc8MIYQQXYQ0AL8Gln5/nCPnCjib2fBB+v/uHISzpnP+8ZtMJnbu3MnGjRsxGo2o1WqmTZvGoEGDpPmeEEIIIYQQXdCg3v5sPpDFoTMXqK0zAC01ADf/rDeYOHqugNxCcyPvNgcz6ntmABw8fQFo3i/DQuOgYuKwML7bmsK63Wkkju+JsoUSvpa+G2DuG5CRpyMyyL1N8xFdQ1JSEk899RT33HMPY8eOZcOGDcyfPx8nJyemTp3a4jEvvvgiX375JU8++SR9+vRhzZo1/OEPf0Cr1TJu3DgAnnjiCY4cOcJjjz1GdHQ0O3fu5Pnnn0en0/HQQw9dy1u8JOmZIYQQoqvonE/TO5HC0iq+2Xy22XjTuq+diU6nY+vWrRiNRvz8/Ljtttvw9/e397SEEEIIIYQQHWRgb3NmhiWQAQ09MiwaNwRfsyMVgCBf1zYHD7TODrg6O1BRVWfNoGjte9PUkZF8tzWF3MJKDp25YG1U3ti5RsEMgGPnCiSY0c0sWrSIadOmsXDhQgDGjh1LaWkpixcvbjGYkZGRwWeffcZzzz3H7bffDsCoUaNIS0tj27ZtjBs3jpMnT7J161beeOMNpk2bZt2nrKyMDz744LoLZlh6ZkhmhhBCiM5Oykx1sO2Hs62v50zoybO/Gc53r87CQ6tp5ajrm7u7OzNnzmTw4ME88MADEsgQQgghhBCii/N2d2oWBGiameGu1WBJjth9LBeAhP5Bl5W9bSk1BebyVj1CL96PLyzAjf49fAFYuyutxX0swQy1yvzV91hKy30zahoFaTqDbzad4Z+f7Ot0877WMjMzycjIYPLkyTbjU6ZMISUlhczMzGbHbNiwAScnJ2699Vab8WXLlvHss88C5moFd955J6NGjbLZJzo6Gp1OR3FxcTvfyZUzGIxUVusBycwQQgjR+Ukwo4NUVNVx6HQ+H646Zh2bOTaaEXGX92H+emA0GtmxYwfV1dXWsbi4OGbOnImDg6zsEEIIIYQQojtonPng6uyAo4PKZrtKqcC9ftGWJbOirSWmLBoHMyID3XFybL2YgKUR+J7juRSWVtlsKy2voaDEPHbDIHNfv+PnCpv1NPh4zQnuWLiG1dtTLmuu9mIwmvjkh5PsOJzNvhO59p7OdS0lxfzfNCoqymY8IiICgNTU1GbHJCcnExUVxc6dO5k1axb9+vVj8uTJ/PDDD9Z9+vXrx3PPPYenp6fNsRs2bMDPz6/ZuD2VV9VZX2ud5fu7EEKIzk2CGR0gv7iSe59bx5/f22Udm3VDND4eznac1ZUpLS3lo48+YsOGDXz//ffXZTMzIYQQQgghRMcbVN8EHMDbveVM88alpnw8nOgVdnnldQMb9c3o3YbSvCP7B6F1dsBoNLHvRJ7NNku/DKUCbh5jfphdUl7D+Qvl1n3Kq+r4blsKRqOJ91cetTYtv56VltdgqA8WpTQpoyVs6XQ6ALRarc24q6v571l5eXmzY4qKisjJyWHhwoXcfffdfPjhh8TGxvLEE0+we/fui17r448/Zu/evTzwwAPX1QLGxsEMN8nMEEII0clJMKMDpOeUUVPbkO7bM8yT+2fF2XFGV+bUqVO8++671tRbDw8PCWYIIYQQQgjRTfWL8sFRbf4KaWn23VTj8VH9g1psyt2axpkZMeGXXt3uoFYyqD5j5MCploMZIf5u9Az1xN3V/CD32LmGUlOb9mda+4CYTPDqZz+TnF50WXO+1orKGjLmU7PL7DiT65/l+2vT4IJlXKls/kikrq6OoqIiXnjhBe644w4SEhJYtGgRffr04a233mrxOsuWLeOll15i2rRp3HPPPe18F1dHV98vA0ArPTOEEEJ0chLM6ECOaiWf/HUKrz12w3W1MuNS9Ho9SUlJfPnll1RXV+Pi4sJdd93F5MmTW/ywJ4QQQgghhOj6HB1UxNX3qPD2aDmY0bgpeEL/4Mu+hk0wI8K7TccM6WMOZhw+c4E6vdE6bglm9Aj1QKFQEBvtA8Dx+r4ZJpOJtbvTABgdH0ygjwu1dQaeX7KH3MIKTCYTpzOK+WDlUZ58Ywv7T9oGS+yluFEwIy1bMjNa4+bmBjTPwKioqLDZ3pirqysqlYrRo0dbxxQKBQkJCSQnJ9vsazQaefnll3n++eeZMWMGr7766nX33b+80pyZ4aBWomlSGk4IIYTobFovQCquikKpwMu95Q/516vCwkJWrFhBbq659mpkZCSzZ8/G3d39EkcKIYQQQgghurq7psSgVCqYOSa6xe2WMlPuro70i2pbMKKxPhFeeLtr8PV0JsRPe+kDaOjlUVVj4FRaEf17mgMu586XANAjxNxEPC7ah11Hczh2rgCTycSJ1CIycs1liG6f2AuNo4o/vrmN0vJann13J0qlgpyCCut1Xv/iZ959ZqLdS/U0zswoKK1GV1lr9zldryy9MjIyMoiJibGOp6en22xvLCIiAqPRiF6vx9Gx4c+1rq7OJlBRV1fHH/7wB9atW8d9993H008/fd0FMgDK6zMz3Fwcrsv5CSGEEJdDltl3AF1l3aV3uk799NNP5ObmolAoGD9+PL/61a8kkCGEEEIIIYQAzNkSf71/JL3DW+5nkRAfjK+nM7dP7I1KdflfN7Uujvz32cm8+tgNbS5R5eXuRHR9wMJSaqqyuo7s+kBEjxBzuSpLVklBaTV5RZWs3ZUGQK8wT3qEehLq78az941ArVKSV1RpDWSEB7rhrFFRVlHLsqSTl31P7a2orMbm51TJzrioiIgIQkNDWbt2rc34+vXriYyMJDi4efbQ2LFjMZlMJCUlWcf0ej3btm1jyJAh1rGFCxeyfv16FixYwPz586/bQIHl+YRWAl5CCCG6AMnMaGcZuWW8/sXP9p7GFZs+fTqlpaVMnjyZiIgIe09HCCGEEEII0Yn0Dvdi6Z8nX9U51FcQBBnSx5+U86UcOJXPr2+OJTW7DEu7v6j6QEdEkDuuTmoqqvXsOprDjiPmZt/TRkVazxMb7cMz9wzl601n6RflzbjBoUQGubNq6zn++91x1u5KY/KICHqEXrqfh0Wd3sAnP5ykd7gXYweGXPa9NdW4zBRAyvky4nv6XWRv8cgjj7BgwQI8PDwYP348GzduJCkpiddffx0wN/zOyMigZ8+eaLVaRo0axbhx43jhhReorKwkMjKSzz//nPPnz/Paa68BsHnzZr777jtuvPFGBg4cyKFDh2yu2a9fP5usDnuyZGZonaVfhhBCiM5PghntLKVRAzZLuvP1LDc3l+rqaiIjIwHQarXcf//91+2qEiGEEEIIIYRoakifAJb/dIa0nDIKS6us/TICvF2sD3FVSgX9on3YdyKPL9afok5vxNVJ3SzAMCIuiBFxQTZjN4+J5se9GWTk6nj3myO8/OjYNmeOrN2Vzsot51CrzM3K2/JQ+ei5AjBhLZnVWFGTYIZkZrQuMTGR2tpalixZwvLlywkLC+Pll19m+vTpgDkwsWDBAj755BNGjBgBwJtvvsnixYt5//33KS0tpV+/fixZsoS4uDgA1q1bB8DGjRvZuHFjs2tu2bKFwMDAa3SHrdNVmTMzpBSZEEKIrkCCGR1EqVSw4N5h9p7GRZlMJvbv38+6devQaDQ8/PDD1uZnEsgQQgghhBBCdCZ9IrysWRcHTuU39MsI9bDZL64+mFFVYwBgwtAwnDSX/lqsVil5eHY8C9/Zwan0Yjbuz+Sm4eFtmttP+zMA0BuM7DiczZSRrWfAr9h4ho/XnEClVLD0z5Ob9WG0BDNcnNRUVutJa7SgTrRs7ty5zJ07t8VtiYmJJCYm2ow5OTkxf/585s+f3+IxL730Ei+99FK7z7Mj6CyZGS6SmSGEEKLzk54ZHcRT63jdBgWqqqpYvnw5P/zwAwaDAScnJ6qqquw9LSGEEEIIIYS4IiqVkgG9zaWWDpzKs2ZmWHppWFj6ZlhMbVRi6lL69/TlhkHmLI6P1hynvOrSvRJTs0s5l9WQObH558yL7msymfho9XE+XnMCAIPRRFZ+ebP9LGWmBtbfb0aejjq9sc33IbqX8krJzBBCCNF1SDCjm8nMzOS9997j5Elz47r+/fvz4IMP4u9//ZfEEkIIIYQQQoiLGdInAIBDpy+QkasDGpp/W0SHeODkqAKgX5Q3EYHul3WN+2bG4qxRUVpey5c/Jl9y/5/2mYMXjmrzV+9j5wrJL65stp/BaOKt5Yf5etNZm/G8Itt9jUYTxTpzA3DL/eoNRrLydTb7rd6ewtP/3kZ+UfNrie6lXDIzhBBCdCESzOgmTCYT27ZtY+nSpZSWluLg4MCsWbOYPXs2Go3G3tMTQgghhBBCiKti6VlYWa3HYDR3/+7RJDNDrVIybnAoSqWC2yf2vuxr+Hg4M2dCLwA2H8iyXqcleoPRmolx28TeeGrN37u2/Jxls5/BaOLVZftZvycdgEnDw4kJ9wJoFvgoq6i1XrNXmKe1/0Zqo1JTldV1fLTmBCfTiqzltkT3pZPMDCGEEF2IBDO6iTNnzrBx40ZMJhP+/v488MADDBo06LothSWEEEIIIYQQl8PX05nIoIZMCy83TbN+EwC/nTOAz/4+laF9A67oOuMGhwJQUl7DqbSii+534GQepeW1KBTmAIWlRNWmA1mYTA1BkB92pLL9cDYAs8f35Pd3DCTQxxVonplRrGto/u3t7mQto9W4CfiuoznU1BpwUCvp39Pviu5RdB3lVfWZGW1oPC+EEEJc7ySY0U306tWL/v37M3ToUO6//378/ORDrRBCiM5h9erVzJgxg/j4eKZNm8bKlStb3X/VqlXExMQ0++e5556z7lNRUcGLL77IhAkTGDx4ML/61a84cuRIR9+KEEKIDjakT0P53B6hni3uo1Iq0F7FKvVAH1eigs1Bk93Hci6630/7zVkZA3v54evpzPgh5iBIZp7OmkmRX1TJJz+Ye2TcNCyc39zcD4VCgb+3MwAXim17GxaWmoMZapUCd1dHIuvn0bgJ+Mb6646IDZQH2N2cyWSyZmZczd95IYQQ4nqhtvcERMcwGAycOnWK2NhYABQKBbfeeitKpcSvhBBCdB5JSUk89dRT3HPPPYwdO5YNGzYwf/58nJycmDp1aovHnDp1ioiICP71r3/ZjPv6NjR9/ctf/sLGjRt56qmniIiIYOnSpdx777189913hIWFdeg9CSGE6DiD+/gwF86kAAAgAElEQVRb+040bf7dnkbFBZGaXcbuYzncNzO2WcZ7aXkNe4/nAjBxWDgAPUM9CfHTcv5COZsOZBIV7M7bKw5TXWvA213DvFvirOcJ8HYBIK9JmSlL829PNycUCgVRQeZ7TMkuxWQyUVBSzdFzBQDcOFR+n3V3VTV6jPVlydykZ4YQQoguQIIZXVBJSQlff/01WVlZGAwG4uPjASSQIYQQotNZtGgR06ZNY+HChQCMHTuW0tJSFi9efNFgRnJyMrGxsQwcOLDF7dXV1SQlJfG73/2OX/7ylwAMGjSIhIQEVq1axaOPPtoxNyOEEKLD9Y30QevsQHlVHX0ivDrsOiP7B/H5+mRyCytJyykjKtg2cLLlZ3M/DVcnNSP7BwHmBWYThoSybO0pth7MIiLQjZ+T8wF4OHGATRaFn5c5mFFQUoXBYESlMn+XK6ovM+VTXz7LkiFSVlFLUVk1m3/OxGQCD60jg2IaslRE91Ren5UB0jNDCCFE1yBPt7uYkydP8t5775GVZW4qV1xcbOcZCSGEEFcmMzOTjIwMJk+ebDM+ZcoUUlJSyMzMbPG4U6dOERMTc9Hz1tXVYTQa0Wq11jEXFxc0Gg0lJdIoVQghOjMHtZK/zBvJI7cNuOKeGG0RGeRuzZ7YfbR5qamf9pl/R40dFIrGQWUdt/TbKCqr4e0VhwEYHR/MqPqAh4Xl3EajicKyhj4ZRfVlprzczc3EwwPdUCnN2Ryp2WVsOmD+HjhuUChqlXzd7+50lbXW11JmSgghRFcgn27aUbGumtc+O2CXa+v1etasWcNXX31FdXU1rq6u3H333YwbN84u8xFCCCGuVkpKCgBRUVE24xEREQCkpqY2OyY/P5/CwkJOnDjB1KlTiY2NZcqUKTZ9Ntzc3Jg9ezYff/wxR44cobS0lNdee42KigqmT5/egXckhBDiWugb5c3UUZHNSj+1J4VCYQ1A7D6Wa7PtbGYJKfUNuScOsy31FOjjSt9IbwD0BhNaZwcemt2/2fn9PJ2tr/MbNQEv1tUAWBubO6hVhAW4AbBhbwaZeToAJgyRElOiITNDqQAXjRTmEEII0fnJb7N2tPd4nvW1p5vTNbtuQUEBK1asIC/PfP3o6Ghmz55ts+JUCCGE6Gx0OvMDmaa/z1xdXQEoLy9vdsypU6cAyMrK4o9//CMajYaVK1cyf/58DAYDc+bMAeCJJ57gwQcf5PbbbwfMD6VeeOEFBg8e3GH3I4QQomsZGRfEyi3nSMkuJbewgkAfV+r0Bv791SEAwgLciAlvXupqwpBQTqYVATBvVpw1MNGYo4MKb3cNRWU15Dfqm1FUn6Xh3eiYyGB30nLK2HEk23rdHqEd1y9EdB66KnNmhquzA0plxwX3hBBCiGtFghntyGA0Wl8/c8+wa3NNg4Fly5ZRWlpqrsE6YQJjxozp0FVIQnSUiooKysrK0Ov1GBv9/ySEaE6pVOLk5ISvr2+Xfc83mcwNK5ven2W8pV5QcXFxvPvuuwwbNswaBBkzZgyFhYUsXryYOXPmUFhYyB133IGjoyOvvfYaPj4+rFu3jr/+9a+4uLhIdoYQQog26RPpjadWQ0l5DbuP5XLruB4sSzpFSnYpSgU8ctuAFn9Hjx8SxoFT+fh7uzTL3GjMz8uForIa8oqqrGMtBTOigjzYTJb15wlDQrvsZwNxeXT1mRlSYkoIIURXIcGMDhDqryXI1/WaXEulUjFt2jSSkpKYM2cOYWGSTiw6H6PRSHZ2NjqdDqVSiYODAyqV6tIHCtGN1dXVUV5eTk1NDSEhIV3yoYWbm7lsRtMMjIqKCpvtjXl7ezNhwoRm4+PGjWPnzp0UFRWxfPlycnNz+fHHH62/N0eNGoVOp+P5559n6tSpLQZKhBBCiMZUSgXDYwNZvyed3cdyiApy55vNZwG4fWJvYqN9WjzOWaPm2ftGXPL8AV4uJKcXc6E+M8NkMlFcZi4z1TiYER3ibn2tUMD4wfKdUJiV1/fMcHNxuMSeQgghROcgwYxOKCcnBw8PD1xczE3hYmJi6NGjB2q1/OcUnVNpaSk6nQ5fX198fHzkIaIQbVRUVEReXh4FBQX4+fnZezrtztIrIyMjw6ahd3p6us32xg4ePMjZs2et5aMsampqUKvVuLm5kZ2djZ+fX7MFAEOHDmX16tUUFRXh6+vb3rcjhBCiCxrVP4j1e9I5kVrIa5+b+yfGhHsxd3LMJY68NP/6JuB59T0zdJV16A3m7GUvN411v6jghpJS/Xv44ufljBDQ0DNDMjOEEEJ0FfLEsBMxmUzs3r2bDz/8kFWrVlnLbAASyBCdWnl5OY6Ojvj6+kogQ4jL4O3tjUajobq62t5T6RARERGEhoaydu1am/H169cTGRlJcHBws2MOHTrEs88+a+2dAebsr3Xr1jF48GAcHByIioqioKCAtLS0ZsdqtVo8PKTOuBBCiLYZ0MsXZ40ak8ncnNtZo+IPvxyCWnX1n2ktwQxLzwxLiSkAb4+GzAwPrYYQP3NlgEnDw6/6uqLr0FkyM5wlmCGEEKJrkCfgnURlZSWrVq3i9OnTABQWFlJRUSFNvkWXYDQaUavVXbJMjhAdTaVSdekeM4888ggLFizAw8OD8ePHs3HjRpKSknj99dcBc3ZKRkYGPXv2RKvVkpiYyKeffsqjjz7K448/jqurK59//jmnT5/ms88+A+C2227j008/5cEHH+T3v/89Pj4+bNy4kZUrV/LUU0/h4CClGIQQQrSNg1rF0L4BbDt0HoAHb41vt5LD/vUZFheKqzAYTdZghlKpwMNVY7Pvn34zgoxcHQnxQe1ybdE1lFeZMzOkzJQQQoiuQoIZnUB6ejrffPMNZWVlAAwYMIDp06fj6CirK4QQQnRtiYmJ1NbWsmTJEpYvX05YWBgvv/yytUn35s2bWbBgAZ988gkjRozAw8ODTz/9lNdee42XXnqJ8vJy4uLi+OijjxgwYABg7rXxxRdf8Morr/DCCy9QW1tLdHQ0ixYtYsaMGfa8XSGEEJ3QjNFR7Dqaw41Dw1pt6H25/L3MmRkGo4nismqK64MZnloNSqXtIqCwADfCApr3khLdmyUzw1WCGUIIIboICWZcx4xGI9u2bWPLli2YTCYcHByYMWOG9WGMEEII0R3MnTuXuXPntrgtMTGRxMREm7GQkBAWLVrU6jkDAgJ49dVX222OQgghuq/YaB9WvDQDVTuUlmrMUmYKzH0zLJkZjUtMCdEaS88MN+mZIYQQoouQYMZ1bOvWrWzZsgWAwMBAbrvtNnx8fOw8KyGEEEIIIYQQjbV3IANA46DC001Dia6G/OJGwQw3CWaItim39MyQzAwhhBBdhHTavY4NHz4cd3d3hg8fzrx58ySQIYS4pH//+9/069fvso555plnmDRpUovbTp48SWxsLLm5uc22bd++nTlz5jBgwABuvPFGlixZckVztjh9+jQxMTGMGzcOg8HQbPuePXuIiYlh//79LR7/n//8h5iYmGbjJSUlvPnmm9x8880MHDiQ0aNHM2/ePHbu3HnFc/3444+ZNGkS8fH/396dx9WU/38Af1WkdCs1kSWSuDXJEgkpDRUZsmQfyr4bsi/DWGeylCH7TJMtNWTJkt3Y+5kRxjbGICrUGKUVref3R997xtUt7V31ej4ePR76nM85930+bve8633O59Mcffr0EQvP+Xn37h1WrlwJe3t7tGzZEv3798eVK1fk+hw6dAhmZma5vpYuXVrkWImIiOjTJVs342X8G7xOSgMA6OlUy28XIlHy/9bMkPDJDCIiqiD4ZIYSycrKwqtXr2BoaAgAqF69OiZMmAANDd55Q0RlLyIiAuPGjUNmZmaubTdu3MD48ePRrVs3TJ06FdevX8eqVasgCAJGjRpVpNfbv38/mjRpgkePHuHChQvo3LlzcU8Bjx49wpgxYwAAHh4eMDMzQ2pqKg4cOIARI0ZgwYIFcHd3L9Qx/fz8sGbNGkyePBlNmzbF/v37MXHiRAQEBMDKyirP/Tw9PXHjxg3MmjULderUQWBgIMaPH4/g4GCYm5sDAP766y8YGxtj1apVcvsaGBgU8syJiIioIqilVx1/RyXg5eu34pMZn+nw90P6uPSMLKSl59wgpK3JYgYREVUMLGYoidevX2P//v2Ii4vD+PHjoaurCwAsZBBRmcvMzMSePXvg4+ODqlUVP5Lu6+sLCwsLrF69GgDQsWNHZGZmYsuWLXB3d4e6euF+YcrIyMCRI0cwcuRInD17Fnv27Cl2MSMjIwPTpk1DtWrVEBgYCH19fXGbs7MzZsyYgRUrVqBTp04wMjIq0DHfvHmDLVu2YOTIkZg4cSKAnHMfNGgQNm7cCD8/P4X7Xb16FefOncP27dvRvn17ADlP3/Xq1QuXL18WixkPHjxA06ZN0bJly+KcOhEREVUQhv9bN+Ple2tm6LGYQQWQ8r+nMgBAwmmmiIioguA0U0rg3r172Lp1K54/f453794hIiKivEMiohLSuXNnbNq0CcuWLYONjQ2sra2xdOlSvH37FitXrkTbtm3Rtm1bfPPNN0hLSxP3S0hIwLJly9C5c2c0a9YMbm5uOHXqlNyx09LS4OXlhQ4dOsDKygrz5s2TO4bM6dOn4ebmhmbNmsHOzg4rV65Eenp6njFfv34d3t7eGDlyJGbOnJlre1paGsLDw9GlSxe59q5duyIpKQk3btwA8N+0UAcOHPjoOF24cAFxcXFwcHBAz549cfHiRbx48eKj+33smH///TemT58uV8iQ8fT0xODBg/H27VsAgLu7u8IpnmRfAHDr1i0kJyfLnbuKigqcnZ3xf//3f3mO6+nTp2FiYiIWMgBAXV0dx48fx+jRo8W2v/76S+FUWURERFQ5yRYB/+f1G7yWrZnBYgYVQPKb//JSFjOIiKii4JMZ5SgjIwMnTpwQ//AnkUjQp08fNGrUqJwjI1IemVnZiEt8V95h4DNdDVQp4sKOfn5+6NSpE9atW4fLly/Dz88PYWFhMDc3h7e3N8LDw7FlyxaYmppi5MiRePv2Lb766iskJSVh6tSpqFWrFo4cOYKvv/4aK1euRO/evQEAs2bNwqVLlzBt2jQYGxtjz549OHLkiNxrHzlyBDNnzkTv3r3h6emJqKgorFmzBs+ePcP69esVxmtqaoozZ87gs88+U1iIiI6ORkZGBkxMTOTajY2NAQBPnjxBu3bt0LRpU+zZswcNGjT46Bjt378fFhYWaNKkCQwNDeHl5YXg4GBMnTq1QGOsyMWLF6GmpgY7OzuF2+vXr48FCxaI3y9atAgpKSn5HlNWbP7wc9rY2BiZmZmIjo6Gqalprv0ePHgAqVSKgwcPYsuWLYiOjkbjxo0xb948scDx8uVLxMXF4c8//4SLiwuio6NhZGSECRMmiP/nREREVLnU0vtfMSMuFdlCThuLGVQQKW/eezKD00wREVEFwWJGOXn58iX27duHf//9F0DOHw979+4NiURSzpERKY/MrGxMXPkrYuJSyzsU1PlMC5vmdC5SQUNPTw+rV6+Gqqoq2rZtiz179iAjIwPe3t6oUqUK7O3t8euvv+KPP/4AABw4cACPHz9GcHAwmjdvDgBwcHBAYmIiVq9eDVdXV0RERODkyZNYsmQJBg0aBACwt7eHq6srnjx5AgAQBAHe3t7o1KkTVq5cKcZTu3ZtTJo0CdevX0fr1q1zxfux9RmSk5MBINfnlZaWFgCIBQGJRFKg6ZLi4uJw8eJFzJkzBwCgo6MDJycn7Nu3D5MmTUKVKkW7VMXGxkJPTw/Vq1cvUP/GjRt/tI/s3GTnKiP7PjVV8Xs1Pj4eT58+xd27dzFt2jTo6urC398fY8aMweHDh9GoUSP89ddfAIBnz55h1qxZqFatGkJCQjBnzhxkZWWhb9++BToPIiIiqjhkC4DLChkAFwCngkn535MZmtXUULUKJ+UgIqKKgVe0cvD69Wv89NNP+Pfff6GqqgonJycMGTKEhQyiCqpZs2ZQVc35uFVVVYWenh4sLS3l/khfo0YNJCUlAQCuXbsGY2NjsZAh4+rqilevXiEiIgLh4eEAAEdHR3G7qqoqunbtKn4fERGB2NhYdO7cGZmZmeKXvb09qlatirCwsCKdjyDk/DatoqKicLvsXAvq0KFDAHIKNklJSUhKSkKXLl3w8uVLnD9/XuyX1+vlRU1NDVlZWQXun5WVJTdOH34BOeeuKI6PjUlGRgZevXqFzZs3w9XVFR07dsTmzZtRo0YNbN26FQBgaWmJLVu2YOfOnXB0dISdnR28vb1ha2uLdevWFerciYiIqGKQPZkho6IC1JCwmEEfl/y/JzMk1flUBhERVRx8MqMcyP6Q+fTpU/Tt27fAC88SVTZV1FSxaU7nT36aqQ/v4gcATU3NPPsnJiYqfDpC1pacnIzExEQAyLUWRM2aNcV/JyQkAAAWLlyIhQsX5jrey5cvCxB9btra2gCQa0om2fey7QV18OBBZGZm5lqDAwB++eUXODk5AfhvzDIyMnL1k7W//xRGvXr1cP78eaSmpir8PwCAmJgY1KlTBwAwfPhw/P7773nG+eDBA2hra0MQBKSmpsoVoGVPZOR17lpaWqhdu7bcehiamppo1aoVHjx4ACDn/7JTp0659nVwcEBYWBji4+MVrv1BREREFZdGtSrQlagjMSXnLvsakmpQK2JOSpVLytuc94w2p5giIqIKhMWMMhIXFwd9fX3xrt1u3bohOzsbGhqc75QoP1XUVGGoX7BpgioKHR0d3L9/P1e7rPigp6cHPT09AMCrV69gaGgo9pEVMID//rA+b948hdNJyY5RWA0aNICamhqioqLk2mXff7iWRn5u376Nv//+G9OmTYOVlZXctkOHDuHgwYN49uwZjIyMxELNP//8o/BYsbGxckUgOzs77Nq1C5cuXYKLi0uu/s+fP4ejoyMmTZqEr7/+GkuWLMlzmigZ2blFRUXBwsJCbI+MjIS6ujrq1q2rcD9jY2OFxaOMjAzxunDz5k08evQI/fv3l+uTlpaGKlWqFLpIRERERBVDTb3qYjFDj+tlUAH992QGF/8mIqKKo9xv6Th69Ci6d++O5s2bo1u3bggJCcm3f2pqKpYsWYIOHTrAysoKY8aMwdOnT8sm2CIQBAFhYWHYtGkTbt68Kbarq6uzkEFECtnY2CAyMhK3b9+Waw8NDUXNmjVhbGyMdu3aAQBOnDgh1+fcuXPiv01NTaGvr4/nz5+jWbNm4peenh68vb3x+PHjIsVXrVo1WFtb49SpU+L0SgBw8uRJaGtrw9LSssDHOnDgADQ1NeHh4YG2bdvKfY0YMQLZ2dkIDg4GkLPWR4MGDXKdMwC8ffsWly5dQtu2bcU2Ozs7NGnSBOvWrZMr8sh4e3tDRUUFX375JYCcRb3fH6cPvwDAysoK1atXx8mTJ8XjCIKA06dPo02bNlBXV3znm729PeLi4nD16lWxLTk5GTdu3BALTX/88QcWLFggrp0BANnZ2Th58iRatWqFqlX5iygREVFlZPjeVFNc/JsKSrZmBosZRERUkZTrkxnHjx/HzJkz4eHhAXt7e5w5cwZz5syBhoaGwrtoAWDatGm4c+cOZs+eDS0tLWzYsAEeHh4IDQ1VurtWU1NTcejQITx8+BAAEB4ejpYtWxZ6Pnkiqlz69OmDXbt2YeLEiZg6dSoMDQ1x9OhRXLx4EcuXL4eqqiqMjY0xcOBA+Pj4ID09Hebm5ggJCRGnLAJy1ozw9PTEkiVLoKqqio4dOyIxMRG+vr5ITk6We7KgsCZMmIARI0Zg2rRp6NOnD27evImff/4ZM2bMEKeDSklJwaNHj9CgQQOF0yOlp6fj2LFj6NSpk8JFups0aYKmTZti//79mDx5MqpWrYoZM2bA09MTkydPRu/evSGRSBAdHY0dO3YgKysL48ePF/evUqUKVqxYgVGjRqFv377w8PCAmZkZ4uLisHfvXly9ehXffvstTE1NC3zempqaGDlyJDZt2gQ1NTW0aNEC+/fvx71797Bz506xX2xsLGJjY2FhYQF1dXX07NkTAQEBmDFjBmbMmAF9fX1s2bIFWVlZGDVqFADAzc0Nu3btwuTJk+Hp6QktLS0EBgbi77//xu7duwscIxEREVUstfRZzKDCS/nfkxnaXDODiIgqkHItZqxZswbdunXD/PnzAeTcuZqYmIh169YpLGaEh4fjwoUL+Omnn9CxY0cAgLW1NRwdHREUFISxY8eWafz5efr0KQ4cOIDk5GQAOXfzuri4sJBBRB9VvXp1BAQEwMfHB97e3nj79i2kUinWr18vt67EokWLYGBggF27diExMRH29vYYP3481q9fL/YZOHAgJBIJ/Pz8EBgYCIlEgjZt2mD69Oly62sUVvv27bF+/Xr4+vpi0qRJMDQ0xOzZszFy5Eixz7179+Dh4QEvLy+4ubnlOsbp06eRmJiI7t275/k6vXr1wvfff4+zZ8/CxcUFLi4u8Pf3h7+/PxYsWICUlBQYGBjA1tYWEydOzLUGkaWlJfbt2wd/f3/s3r0b//zzD7S1tWFubo4dO3aIT7gUxuTJk6Gmpoa9e/fCz88PjRs3xqZNm+Sm8goODsaGDRtw9uxZGBkZQV1dHdu3b4e3tzdWrVqFd+/ewcrKCrt37xbX7NDV1cWuXbvg4+MDLy8vpKSkwNLSEtu3b0eLFi0KHScRERFVDIZ6/621pqfDxb+pYJJlT2Zo8skMIiKqOFSE9+cIKUPR0dFwcnLC2rVr0a1bN7H9+PHj8PT0xJkzZ1C/fn25fdatW4cdO3bg2rVrUFNTE9vHjh2LN2/eICAgoNBxWFtbA8gplBTXsbAn2Lz/Fsz14iHJigaQM51Ujx49xClKiCi3yMhIADnrChBR4RTk56ckr3WUG8eXiIhK0+9/xmLZz78BACb0bY4vbQu+PllJ4bWu9JX0GE9bewGPohMwvLsF+nZuUiLHJCIiKo6SuNaV22MCERERAHIvFCv7Y8yTJ08U7mNsbCxXyAByFqNV1L88NNKMFAsZderUwbhx41jIICIiIiIioiLhmhnFV9i1OrOzs7F582Y4OjqiefPmcHV1RWhoaJ79AwIC4OzsXNJhF8t/a2ZwmikiIqo4ym2aKdn0SxKJRK5dS0sLQM5c6x9KSUnJ1V+2j6L+Za16tSp4la4PvaoJaN+uHZycnHIVXoiIiIiIiIgKqpZ+dVRRU0VmVjYM9XOvM0b5K8pand9//z327NmD6dOnw9zcHKGhoZgxYwYkEgkcHBzk+p4+fRorVqwQpw5VFipQAQAY1GABjIiIKo5yK2bIZrdSUVFR2K5obYn8ZsRShrUo2jWrg5ev26KRYQdYN2tU3uEQERERERHRJ06zWhXMdm+N+MR3MKmrW97hfHIKu1ZnVFQUdu/ejaVLl6J///4ActaLe/r0KS5duiQWMxITE7Fhwwbs2rULOjo6ZXdCBfT1gJZ4EPUaLaW1yjsUIiKiElNuxQxtbW0AuZ/ASE1Nldv+PolEgmfPnuVqT01NVfjERlnTUK+CAU7S8g6DiIiIiIiIKpD2zeqWdwifpOjoaERFRWH69Oly7V27dsXx48cRHR2da63OM2fOQENDA71795Zr/3CNzp07d+LUqVP44YcfcOHCBVy/fr10TqKImjU2QLPGBuUdBhERUYkqt8cZZGtlREVFybXLFjL9cC0NWVt0dHSuJzQiIyMV9iciIiIiIiKiyqkoa3U+ePAAJiYmCAsLQ8+ePWFhYYEuXbrg2LFjcv169OiB06dPo1u3bqUUPREREX2o3IoZxsbGMDIywokTJ+TaT506hYYNG6Ju3dx3ntjZ2SEpKQlhYWFiW3x8PMLDw2Fra1vqMRNR6VBVVUVmZma+U8kRkWJZWVlKMdUiERERkbIpylqd8fHxiImJwfz58zF06FD4+fmhadOmmDZtGq5evSr2MzExgbo6F9cmIiIqS+U2zRQATJo0CfPmzYOuri6++OIL/Prrrzh+/Dh++OEHADlJRFRUFBo3bgyJRII2bdrAxsYG06dPx8yZM1GjRg2sX78e2traGDx4cHmeChEVg0QiQWxsLP79918YGBjwD7NEBRQfH4+0tDSFUzMSERERVXZFWaszIyMD8fHx2LJlCzp16gQgZ82MiIgIbNiwAe3atSvlqImIiCgv5VrMcHNzQ3p6Ovz9/REcHIz69etj5cqV+PLLLwEA58+fx7x587Bz5060bdsWALBhwwasWLECq1atQnZ2Nlq3bo21a9dCV5cLoRF9qnR1dfHmzRvExcXh9evXqFq1KtTU1Mo7LCKllpWVJRYyDAw4HzIRERHRh4qyVqeWlhbU1NTQoUMHsU1FRQW2trbYt29fKUZLREREH1OuxQwAGDRoEAYNGqRwm5ubG9zc3OTadHV14eXlBS8vr7IIj4jKgKqqKurVq4caNWogKSkJmZmZyM7OLu+wiJRa1apVxULGh3cbEhEREZH8Wp1mZmZie35rdRobGyM7OxuZmZly00hlZGQw5yIiIipn5V7MICKS0dLSEuevJSIiIiIiKo731+p0dnYW2/Nbq9Pe3h4///wzjh8/jr59+wIAMjMzcenSJbRu3brMYiciIqLcWMwgIiIiIiIiogqpsGt1tm/fHg4ODli+fDnevHmDhg0bIjAwEM+fP4ePj085nw0REVHlxmIGEREREREREVVIRVmr09fXF+vWrcOPP/6IxMREWFhYwN/fH5aWluV5KkRERJWeiiAIQnkHUZ6sra0BAOHh4eUcCRERUengta50cXyJiKii47Wu9HGMiYiooiuJa51qSQVDRERERERERERERERUGljMICIiIiIiIiIiIiIipVbp18xISUmBIAjiYy5EREQVTXJyMlRUVMo7jAqLuQQREVV0zCVKH/MJIiKq6Eoin6j0T2aoqqoyKSMiogpNRUUFqqqV/pJfaphLEBFRRZKQ5xYAACAASURBVMdcovQxnyAiooquJPKJSr8AOBERERERERERERERKTfeWkFEREREREREREREREqNxQwiIiIiIiIiIiIiIlJqLGYQEREREREREREREZFSYzGDiIiIiIiIiIiIiIiUGosZRERERERERERERESk1FjMICIiIiIiIiIiIiIipcZiBhERERERERERERERKTUWM4iIiIiIiIiIiIiISKmxmEFEREREREREREREREqNxQwiIiIiIiIiIiIiIlJqLGYQEREREREREREREZFSYzGjkI4ePYru3bujefPm6NatG0JCQvLtn5qaiiVLlqBDhw6wsrLCmDFj8PTp07IJVgkVdvz+/fdfLFiwAJ06dYKVlRXc3Nxw/PjxMopWORV2DN8XExOD1q1bY9OmTaUYofIr7BhmZ2dj8+bNcHR0RPPmzeHq6orQ0NAyilb5FHb84uPjMW/ePNjZ2cHGxgbjxo2r1J+D77t//z6aNm2K2NjYfPvxWlK5FOdzvrLJzs5GUFAQXF1dYWVlBScnJ3h5eSElJUXsc+fOHbi7u8PKygp2dnZYs2YNMjIyyjFq5TZ58mQ4OzvLtV2+fBl9+/ZFixYt0LlzZ/j7+5dTdMrt2rVrGDx4MFq0aAE7OzssW7YMqamp4naO48cFBQWhW7duaNmyJVxdXXH48GG57RzDvOWVUxRkzPg5WfEwlygc5hMlj/lE0TGfKD7mE0X3KeQTaosXL15c4ketoI4fP44ZM2bA1dUVEyZMQFpaGtauXYsmTZqgcePGCveZPHkywsLCMGvWLHz55Zc4d+4cgoKC0K9fP1SrVq2Mz6B8FXb80tPT4e7ujsePH2PKlCno378/kpOT4ePjAxMTE0il0nI4i/JVlPegjCAImDJlCh4/fox27dqhTZs2ZRS1cinKGH733XfYvn07xo0bhxEjRiApKQlr165Fs2bN0LBhw7I9gXJW2PETBAGjRo3C7du3MWvWLLi6uuLcuXPYvXs33NzcoKGhUQ5noRwiIiIwevRoJCcnY8SIEZBIJHn25bWk8ijO53xl9NNPP2HVqlVwc3PDuHHj0LBhQ+zYsQM3btxAr169EBkZicGDB8PIyAhz5sxBw4YNsXnzZsTHx8PBwaG8w1c6hw4dwtatW6GrqwsPDw8AwI0bNzBq1CjY2NjA09MT2tra8PX1haamJlq1alXOESuPP/74A8OGDYOlpSXmzp0LqVSK7du349GjR3BxceE4FsCePXuwaNEi9OnTBxMnTkR2djZWr16Nxo0bo0mTJhzDfOSVUxRkzPg5WfEwlyg85hMli/lE0TGfKD7mE0X3yeQTAhWYk5OT4OnpKdc2depUwcXFRWH/a9euCVKpVLhw4YLYFhcXJ7Rs2VLYunVrqcaqjAo7fqdPnxakUqlw69YtufZRo0YJPXv2LLU4lVlhx/B9AQEBQseOHQWpVCps3LixtEJUeoUdw8jISMHc3FzYu3evXPuQIUOEZcuWlVqcyqqw4xcRESFIpVLh4MGDYltUVJQglUqFAwcOlGqsyiojI0MICAgQrKysBBsbG0EqlQoxMTF59ue1pHIpzud8ZZOdnS20adNGWLx4sVx7aGioIJVKhT///FOYP3++4ODgIKSlpYnbd+/eLXz++edCbGxsWYes1GJjY4U2bdoIHTt2FJycnMT2YcOGCf3795fru2rVKsHa2lpuXCu7IUOGCEOGDBGys7PFtoCAAMHR0VF48+YNx7EABg4cKLi7u8u1ffXVV8LQoUMFQeB7UZGP5RQFGTN+TlY8zCUKh/lEyWI+UTzMJ4qP+UThfWr5BKeZKqDo6GhERUWhS5cucu1du3ZFREQEoqOjc+1z5coVaGlpoUOHDmKbvr4+2rRpg4sXL5Z6zMqkKOOnpaWFgQMHolmzZnLtjRo1QlRUVKnGq4yKMobv7+vt7Y1ly5aVdphKrShjeObMGWhoaKB3795y7QEBAViwYEGpxqtsijJ+aWlpAHJ+nmV0dXUBAAkJCaUYrfK6fv06vL29MXLkSMycOfOj/XktqTyK8zlfGaWmpqJnz57o0aOHXHujRo0AAFFRUbhy5Qo6deoEdXV1cbuLiwuysrJw+fLlMo1X2S1YsAAdOnRA+/btxba0tDSEh4crfE8mJSXhxo0bZR2mUoqPj0d4eDgGDx4MFRUVsX3IkCE4c+YMVFVVOY4FkJaWJpcvAECNGjWQkJDA92Ie8sspCjpm/JysWJhLFB7ziZLFfKLomE+UDOYThfep5RMsZhRQREQEAMDExESu3djYGADw5MkThfsYGxtDTU1Nrr1BgwYK+1dkRRm/9u3bY+nSpXIf4hkZGbhw4QKaNGlSitEqp6KMIZAz/+fcuXPRrVs3dOzYsXSDVHJFGcMHDx7AxMQEYWFh6NmzJywsLNClSxccO3as9ANWMkUZP3Nzc7Rt2xYbN27E48ePER8fj+XLl6N69epwcnIq/aCVkKmpKc6cOYPJkyfnuj4owmtJ5VHUz/nKSiKRYMGCBWjdurVc+5kzZwDk/KzFxMTkGk99fX1IJBKO53uCg4Nx7949LFy4UK49OjoaGRkZfE9+xN9//w1BEKCrqwtPT0+0bNkSrVu3xqJFi/Du3TuOYwF5eHjg0qVLOH78OFJSUnDixAmcP38evXr14hjmIb+coiBj9vbtW35OVjDMJQqP+UTJYT5RPMwnSgbzicL71PKJKiV6tAosOTkZAHLNaS6r9r2/MJRMSkqKwjnQtbS0FPavyIoyfop4e3vj6dOn2LhxY8kG+Ako6hju2LED0dHR2LJlS+kG+AkoyhjGx8cjJiYG8+fPx9SpU2FkZITg4GBMmzYN+vr6aNeuXekHriSK+h5cvHgxRo8ejS+//BIAoK6ujo0bN6J+/fqlGK3yMjAwKFR/Xksqj5K6VlZmt27dwo8//ggnJyfo6OgAyD2eAH9+3vf8+XN4eXnBy8sL+vr6ctv4niyY+Ph4AMDcuXPh7OyMzZs348GDB1i7di3S0tIwcOBAABzHj+nevTuuXr0KT09Psa1Pnz4YPXo0bt68CYBj+KH8coqC/Pzm1UfWr7KO66eMn9slg/lE4TGfKD7mEyWD+UThfWr5BIsZBSQIAgDIPSXwfruqau6HXGTbFFHUvyIryvh92G/16tXYvn07Ro0aVSnv6C7KGEZERGDt2rXw9fWFtrZ26Qep5IoyhhkZGYiPj8eWLVvQqVMnADlPDUVERGDDhg2VqphRlPF7/PgxBg0ahAYNGmD+/PnQ0NDA3r17MWXKFPj5+cHa2rr0A//E8VpSeRT3WlnZXb9+HePHj4eRkRGWL1+O9PR0ALnHE8gZU45nzjjMnz8fDg4O6Nq1q8LtgOIxBPielMnIyAAAtGrVCosWLQKQkysIgoCVK1diwIABADiOHzNhwgTcvHkT8+bNg4WFBW7duoVNmzZBIpGIN0RwDAuuID+/+fXh5+SniblE8TGfKDzmEyWD+UTJYD5RspQxn2Axo4Bkfwj+sJqUmpoqt/19EokEz549y9WempqqsFpVkRVl/GTS09Mxd+5chIaGYtSoUZg9e3bpBarECjuGWVlZmDt3LlxcXNChQwdkZmaK27Kzs5GZmYkqVSrXR0BR3odaWlpQU1OTW69ARUUFtra22LdvXylGq3yKMn7bt28HAPj7+4trZXTo0AFfffUVvv/+exw4cKAUI64YeC2pPIpzrazsjh07hrlz56Jhw4bw8/ODnp6eOG6K7gR68+YNxxPA7t278eDBAxw5ckTME2S/jGRmZub5npR9zzHMIbsz7cPpPO3s7LBixQrcuXMHAMcxPzdu3MDly5fh5eUFNzc3AICNjQ10dHTw7bffol+/fgA4hoVRkJ9fWR7Bz8mKg7lE8TCfKBrmEyWD+UTxMZ8oecqYT7DkVECyeb8+XHg6MjJSbvuH+0RHR+e6qzYyMlJh/4qsKOMH5PwgjBgxAsePH8f8+fMrbSEDKPwYxsTE4NatWwgJCUHTpk3FLwBYv369+O/KpCjvQ2NjY7H4876MjIw8K9MVVVHG78WLFzA1NRULGUBOMah169Z49OhRKUZbcfBaUnkU9VpZ2W3btg3Tp09Hy5YtsXv3btSqVQtAzi+EhoaG4vjJxMXFISUlheMJ4OTJk3j9+jXs7OzEPCEkJARRUVFo2rQpwsPDoaamlus9KfueY5ijYcOGACDevSsju8PSyMiI4/gRL168AJBzN+r7ZE9w3r9/n2NYSA0aNPjomPFzsuJhLlF0zCeKjvlEyWA+UXzMJ0qeMuYTLGYUkLGxMYyMjHDixAm59lOnTqFhw4aoW7durn3s7OyQlJSEsLAwsS0+Ph7h4eGwtbUt9ZiVSVHGLysrCxMmTMCtW7ewZs0aDBs2rKzCVUqFHcNatWph3759ub4AYPDgwZXuqQKgaO9De3t7CIKA48ePi22ZmZm4dOlSrkXiKrqijJ+JiQkePnyIxMREufZbt26hXr16pRpvRcFrSeVRlJ+xyi44OBgrVqxAt27d4Ofnl+uunw4dOuDcuXNyvxSePHkSampqsLGxKetwlc6SJUty5QmdOnVC7dq1sW/fPri4uMDa2hqnTp2SK6iePHkS2trasLS0LMfolYepqSnq1auHY8eOybWfO3cOVapUgZWVFcfxI2S/5F67dk2u/Y8//gAANGrUiGNYSNWqVSvQmPFzsmJhLlE0zCeKh/lEyWA+UXzMJ0qeMuYTaosXL15cokeswLS1tbF582a8fv0aKioq2LZtGw4ePIhFixahSZMmiI+Px4MHDyCRSKCuro569erh999/R2BgIGrUqIEXL15g/vz5EAQB33//PTQ0NMr7lMpUYccvKCgIgYGB6N+/P2xsbBAbGyt+/fPPP6hdu3Z5n1KZK8wYampqwtDQMNfXhg0b4OjoiB49epT36ZSLwr4P69evjzt37uCXX36BlpYWkpKSsGrVKty9exerVq0S79ipLAo7fo0aNUJwcDAuXLiAGjVq4Pnz5/D19cW5c+fw7bffokmTJuV9SuXq/v37OHv2LEaMGCE+mslrSeX2sZ8x+k9cXBxGjx4NQ0NDzJgxA3FxcXK5grq6OiwsLODv74/w8HDo6uri/PnzWL16Nfr37w9XV9fyPoVyp6enlytPuHz5Ml6+fImZM2dCU1MTtWvXxpYtW/D48WNoamoiJCQEP/30E77++mu0bdu2vE9BKaioqKBmzZrYtm0bnj59ColEguPHj2Pjxo1wd3eHs7Mzx/EjatWqhb/++guBgYHQ0NBAWloaTp48CR8fH7Rv3x5jxozhGH6EopyiIGNmYmLCz8kKhrlE4TCfKD7mEyWD+UTxMZ8ovk8inxCoUIKCggRnZ2fB0tJS6Natm3Dw4EFx2/79+wWpVCpcvXpVbEtISBDmzp0rWFtbC61atRLGjBkjPH78uDxCVwqFGT93d3dBKpUq/Pr888/L6xTKXWHfgx+SSqXCxo0byyJUpVXYMXz79q2wYsUKwc7OTmjWrJkwcOBA4bfffiuP0JVCYcfv0aNHwrhx4wQrKyuhdevWwuDBg4UrV66UR+hKRzZeMTExudp4Lam88vsZo/8cPHgwzzxBKpUKISEhgiAIwrVr14T+/fsLlpaWgr29veDj4yOkp6eXc/TKa86cOYKTk5Nc26lTp4QePXoITZs2FTp37iz8/PPP5RSdcjt9+rTQu3dvwdLSUnBwcBA2bdokZGVlids5jvlLS0sTfHx8BAcHB8HS0lLo2rWrsH79eiEtLU3swzHMm6KcQhAKNmb8nKx4mEsUHPOJ0sF8ouiYTxQP84ni+RTyCRVB+GASbiIiIiIiIiIiIiIiIiXCNTOIiIiIiIiIiIiIiEipsZhBRERERERERERERERKjcUMIiIiIiIiIiIiIiJSaixmEBERERERERERERGRUmMxg4iIiIiIiIiIiIiIlBqLGUREREREREREREREpNSqlHcARJ+69evXY8OGDfn2CQkJweeff17gY3bu3Bn16tXDrl27ihtegSg6BxUVFWhoaMDY2Bh9+vSBh4cHVFVLvv4pe+2zZ8/CyMgIAJCdnY0XL16I3//222/w8PCAl5cX3NzcSjwGRczMzBS2SyQS1K9fH25ubnB3d4eKikqRjh8dHY369esXJ0QiIiKlMXfuXBw8eDDfPo6Ojti0aVMZRSSvrHMrIiIiKjzmE0T0MSxmEJWQ8ePHo1GjRgq31a1bt4yjKZr3z0EQBLx9+xZnz56Fl5cXoqOjsXDhwhJ/TWdnZzRo0AD6+voAgJSUFAwfPhwODg74+uuvAQCmpqZYtWoVWrVqVeKvn59GjRph/Pjxcm0xMTE4cOAAvvvuO7x79w5jx44t9HFHjRqFmjVrYsWKFSUVKhERkVKYN28e9PT0FG6rU6dOGUdDREREnyLmE0SUFxYziEqIra0t2rZtW95hFIuicxg4cCAGDx6MwMBAjB07FoaGhiX6mubm5jA3Nxe/T0hIwJ07d+Dg4CC2GRgYoFevXiX6ugWR1+sOHToULi4u8PPzw/Dhw6Gurl6o416+fBl9+vQpqTCJiIiUhpOTk/hkJREREVFRMJ8gorxwzQwiypeqqipcXFyQnZ2NW7dulXc4SkEikcDR0RGJiYmIiIgo73CIiIiIiIiIiIgqPBYziMqQIAgICgpCv379YGVlhWbNmsHFxQU//vgjBEHIc7/ExETMnTsXX3zxBSwtLeHk5AQfHx+kpaXJ9Xv06BEmTZoEa2trtGjRAoMGDcKlS5eKHbdsXYjMzEyx7cGDB5g4cSKsra3RvHlzDBgwAGfOnJHbLz09Hd999x0cHR1haWkJBwcHLFmyBImJiWKf9evXw8zMDM+ePcNvv/0GR0dHAMCGDRvk2s3MzHDgwAGkp6ejTZs2uaZ/AoADBw7AzMwM165dA5Cz9oa/vz9cXFxgaWkJe3t7LF++HCkpKcUek+rVq+dqi4yMxJw5c9CxY0dYWlrCxsYG48ePx8OHDwEAz549E9fiOHjwIMzMzPDbb7+VeqxERETKpHPnzvjmm28QHBwMR0dHtGzZEoMGDcLVq1dz9Q0PD8fw4cNhZWUFKysreHh4iNf59926dQtjxoxBmzZt0LZtW4wdOxYPHjzI1e/IkSPo3r07LC0t0bVrVwQFBcltL2jORUREROWL+QRR5cRppohKSHJyMuLj43O1a2tro2rVqgCAtWvXYsuWLejTpw8GDBiA1NRUhISEwMfHBzVr1sxz6iFPT0/8+eef8PDwQK1atXDz5k38+OOPSEhIwLJlywDkFBe++uorGBgYYNy4cahatSqOHj2KsWPHwsfHB19++WWRz02WDDRt2hQAcPv2bXh4eEAikWDEiBHQ0tLCoUOHMGnSJHz77bcYMmQIAGDp0qU4evQoPDw8UL9+fTx8+BC7d+9GZGQk/P39c72Oqakp5s2bBy8vLzg7O8PZ2Rn6+vp4/vy52EddXR1dunTB4cOHkZycDG1tbXHbsWPHUKdOHVhbWwMAvvnmG4SEhKBPnz4YPnw4Hj9+jKCgINy4cQNBQUGoVq1akcYjOzsbly9fRvXq1dGwYUMAwKtXrzBgwABIJBIMHToUenp6uH//Pvbu3YvHjx/j5MmT0NfXx6pVqzB79mxYW1tjwIABMDU1LdVYiYiIylJSUpLCfAgAdHV1oaamBgAICwvD4cOH4e7ujpo1ayIoKAijR4+Gv78/bGxsAABnz57F5MmT0aBBA0yYMAEAEBwcjOHDh8PX11e8AUL2B4patWph1KhR0NDQwM6dO+Hh4YH9+/eL01TcuXMHf//9N4YOHQp9fX388ssvWLx4MWrWrAknJycABcu5iIiIqHQxnyCiPAlEVCy+vr6CVCrN8+vq1auCIAhCenq60KpVK2HatGly+ycnJwuWlpbCuHHjxLZOnToJQ4cOFQRBEF69eiVIpVLBz89Pbr+5c+cKw4YNE78fOnSo4OTkJKSmpoptGRkZwldffSXY2toKaWlpHz2H06dPC3FxcUJcXJzw6tUr4c6dO8LSpUsFqVQqTJo0Sezfv39/oWXLlkJMTIzY9u7dO6FPnz5C8+bNhbi4OEEQBKF58+bCkiVL5F7rhx9+ENzc3ISUlBS5146OjhYEQRCio6MFqVQq+Pr6ivtcvXpVkEqlwv79+wVBEIT/+7//E6RSqXDw4EGxT3x8vGBhYSGsXr1abp+goCC517906ZIglUqF7du35zkegiAIUqlUGDhwoDgecXFxwr///ivcvn1bmDFjhiCVSoWNGzeK/bdu3SpIpVLh0aNHcsfx9vYWpFKpcPfuXbljz5kzJ9f5FTVWIiKi8jZnzpx88yGpVCr8+eefgiDk5DmyvEMmLi5OsLa2FgYMGCAIQk4O07FjR8HBwUFITk4W+yUmJgr29vaCvb29kJ6eLgiCIPTr10/o0KGDEB8fL/aLiIgQzM3NhZUrV4qvaWZmJnc9fvbsmWBmZibMmjVLEISC51xERERUOphPENHH8MkMohIyZ84cuYWsZWRtVatWRVhYGDIyMuS2v379GhKJBG/evFF4XG1tbVSvXh2BgYEwMjKCvb09qlevDi8vL7lj/P7773B3d8e7d+/w7t07cZuzszO8vLxw584dtG7dOt9zmDRpUq42NTU19OjRA0uWLAGQ8wTCrVu3MHjwYNSuXVvsV61aNYwaNQrTp09HWFgYevTogdq1a+PYsWPiY5U6Ojrw9PSEp6dnvnF8jI2NDQwNDXHixAn07t0bAHDq1ClkZmbC1dVV/F5FRQUODg5yd3RYWFigZs2aOH/+PIYNG5bv69y8eRPt27fP1V6vXj1888038PDwENvGjh2Lvn374rPPPhPb3r17B1XVnNn88vr/LalYiYiIlMHq1athYGCgcFuDBg3Efzdq1Ei8exEA9PX10atXLwQEBCAuLg7Pnz9HbGwsZs6cCYlEIvbT0dHB0KFD4ePjg7t376JBgwa4c+cORowYAT09PbGfiYkJ9u/fjzp16ohtDRs2FJ8yBXKu5/r6+nj16hWAguVcREREVPqYTxBRXljMICohTZs2Rdu2bfPtU7VqVZw/fx5nz57FkydPEBkZKa4fIeSxZoa6ujqWLl2KhQsXYsqUKVBXV4eNjQ26dOmC3r17o1q1aoiOjgYA7Nq1C7t27VJ4nJiYmI+ew/sFGRUVFWhpacHU1BRaWlpiH9mUTyYmJrn2l02Z9OLFCwDA4sWL4enpiXnz5mHhwoVo2bIlnJ2d0bdvX7npoQpLVVUV3bt3x65du8Sppo4dOwapVCquSREVFQVBEPDFF18oPMb755QXMzMzzJ07F0BOwWjnzp14+PAhZs2ahW7duuXqn5GRgR9++AH37t1DVFQUnj17hqysLAA5U1PlpSRiJSIiUgatWrUSp2HIT+PGjXO1GRsbQxAEPH/+HM+ePQOgON9o1KgRgJx8Q01NDYIgwNjYOFc/CwsLue/fv+FARkNDQ7zRpCA5FxEREZU+5hNElBcWM4jKiCAImDVrFo4ePYrWrVvDysoKAwcORJs2bT56172rqyvs7e1x5swZXLhwAWFhYbh8+TICAwMRHBws/sF8yJAhcnclvE/RRf5DBSnI5FV0Af77g71sjZD27dvj3Llz4teVK1fg5eWF7du348CBA9DX1/9oTHlxdXWFv78/zp49Czs7O1y7dk3uiY/s7GxoaWlhw4YNCvcvSAKhq6sLW1tb8XtnZ2d4eHhg+vTpUFFRgYuLi7jt7t27cHd3h4aGBmxtbdG3b19YWFggKioKS5cuzfd1SiJWIiKiT4ksV3ifLJ+R/UEhL7JtVatWFXMP2ZOQ+SlIn4/lXOrq6h89BhEREZUN5hNElQ+LGURlJDw8HEePHsXEiRMxdepUsT0zMxMJCQmoX7++wv1SU1Nx//59NGnSBP369UO/fv2Qnp6O1atXY+fOnbh8+TIsLS0B5Fys3//jOwA8evQIz549g6amZomcR7169QAAERERubY9efIEAFC7dm2kp6fj/v37qF27Nrp3747u3bsjOzsb27Ztw6pVqxAaGgp3d/cix2FhYQFTU1OcOXMGqampyM7ORvfu3eXilI2Njo6O3L4nT55EjRo1Cv2a6urqWLNmDVxdXfHNN9+gWbNm4nisWrUK6urqCA0NlSvSbNmy5aPHLY1YiYiIlFlUVFSutsjISKipqcHIyEi8u/Fj+YahoaG474dWr14NXV1djB07tkAxFSTn6ty5c4HPkYiIiEoX8wmiyufj5UQiKhEJCQkAcj8hsXfvXrx9+xaZmZkK93v48CGGDBmCffv2iW3q6urio45qamqoVasWLC0tcfDgQfzzzz9iv4yMDMyfPx9TpkzJ8/iFVbNmTVhaWuLw4cOIjY0V29PT07Ft2zaoq6ujQ4cOSEhIwMCBA7F161axj6qqKpo1ayb+WxE1NTUA+U/LJOPq6oorV67gxIkTaN26tVhYACAmB5s3b5bb59dff8WUKVNw5MiRAp6xvLp162L27NlISUnB4sWLxfaEhATo6+vLFTKSk5Nx8OBBAP/dHQLknPv751dasRIRESmrO3fu4I8//hC/f/XqFQ4fPox27dpBV1cXTZs2Rc2aNREUFISUlBSxX0pKCgIDA8V8xNDQEObm5ggNDZXrFx0djZ07d4rzVxdEQXIuIiIiUh7MJ4gqHz6ZQVRGrKysIJFI4OXlhRcvXkBHRwe//fYbjh07hmrVqiE1NVXhfi1atIC1tTV++OEHxMTEwMzMDDExMQgICECjRo3EBaoXLFiAYcOGoW/fvhg8eDBq1KiB0NBQ3Lp1CzNmzJBbxKq4ZK/Vr18/DB48GFpaWjh8+DDu3buHBQsWQEdHBzo6OnB1dUVgYCDevn0LKysrJCQkICAgAAYGBgrXnACAGjVqQFVVFb/++ivq1q2LLl265BlHjx49sHbtWvz+++/iAuUyDg4OcHR0hL+/P549ewZbW1s8f/4cQP1z5gAAAx1JREFUu3fvRt26dTFq1Kgin/+AAQMQEhKCixcv4siRI3B1dUXHjh3x008/YerUqbCzs8O///6Lffv2iUnP+/+/+vr6+P3337F3717Y2dmVaqxERERl6cyZM/nmHL169QKQ80v9mDFjMGzYMGhoaCAwMBDZ2dmYPXs2gJwpHxYuXAhPT0/07dsX/fr1AwDs27cPL1++hK+vr3hjxLx58zB69Gj07dsX/fv3h6qqKgICAqCjo4MxY8YUOPaC5lxERERUuphPEFFeWMwgKiMGBgb48ccf4e3tjU2bNkFdXR0mJiZYs2YNbt++LVb7DQwM5PZTUVHBxo0bsWHDBpw7dw579uyBrq4uunTpgqlTp4pzLVpZWSEoKAjr16/Htm3bkJmZCRMTE6xYsQJ9+vQp0XORvZavry/8/f2RnZ0Nc3NzbNy4UW7NjmXLlqF+/foIDQ1FaGgoNDU10b59e0ybNi3P9TI0NTUxbdo0/Pzzz1i+fDkaNGiQZxz169eHlZUV7t69K7d+BZAzbuvWrYOfnx9CQkJw7tw56Ovri+P24TgXhoqKCpYtW4bevXvj+++/h52dHb7++mtkZWXh2LFjOHfuHGrVqgVbW1uMHDkS3bt3x9WrV+Hs7AwAmDlzJnx8fLBs2TLxOKUVKxERUVny8vLKd7vsjw8tW7ZE9+7dsWnTJiQnJ8Pa2hozZsyAubm52Ldr167w9/fHpk2bsHHjRlSpUgUtWrTAd999B2tra7Ffu3btsGPHDvj6+mLjxo2oVq0a2rRpg1mzZqFmzZoFjr2gORcRERGVLuYTRJQXFSG/1XCIiIiIiIhKUOfOnVGvXj3s2rWrvEMhIiKiTxTzCaLKiWtmEBERERERERERERGRUmMxg4iIiIiIiIiIiIiIlBqLGUREREREREREREREpNS4ZgYRERERERERERERESk1PplBRERERERERERERERKjcUMIiIiIiIiIiIiIiJSaixmEBERERERERERERGRUmMxg4iIiIiIiIiIiIiIlBqLGUREREREREREREREpNRYzCAiIiIiIiIiIiIiIqX2/5zVu57v1oLZAAAAAElFTkSuQmCC\n",
			"text/plain": [
			"<Figure size 1944x432 with 3 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"model10 = models.Sequential()\n",
			"# need to add an extra zero padding layer, 4 on each width side, 2 on each height side\n",
			"model10.add(layers.ZeroPadding2D(padding=(4, 2), data_format=None,input_shape=(24, 28, 3)))\n",
			"# 1st conv layer, with 32 filters of size (3,3) \n",
			"model10.add(layers.Conv2D(32, (3, 3), activation='relu', padding=\"same\"))\n",
			"# 1stpool layer, divinding by 2 the dimension\n",
			"model10.add(layers.MaxPooling2D((2, 2)))\n",
			"model10.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"# 2ndconv layer, with 64 filters of size (3,3) \n",
			"model10.add(layers.Conv2D(64, (3, 3), activation='relu', padding=\"same\"))\n",
			"# 2nd pool layer, divinding by 2 the dimension\n",
			"model10.add(layers.MaxPooling2D((2, 2)))\n",
			"model10.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"# last conv layer, with 64 filters of size (3,3) \n",
			"model10.add(layers.Conv2D(128, (3, 3), activation='relu', padding=\"same\"))\n",
			"model10.add(layers.MaxPooling2D((2, 2)))\n",
			"model10.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"\n",
			"\n",
			"# flaten the images to prepare for the dense layers\n",
			"model10.add(layers.Flatten())\n",
			"# DROPOUT\n",
			"model10.add(layers.Dense(64, activation='relu'))\n",
			"model10.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"\n",
			"model10.add(layers.Dense(128, activation='relu'))\n",
			"model10.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"\n",
			"# fin9l dense softmax layer, with 2 classes so 2 dimension, to have probabilities at the end\n",
			"model10.add(layers.Dense(2, activation='softmax'))\n",
			"\n",
			"# model architecture\n",
			"model10.summary()\n",
			"\n",
			"train_pred_class10,test_pred_class10 = CompileAndTrainCNNModel(model10,images, labels,100,\"model10\")"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Ok it converted. But the specificity is craszy bad. So lets try the same strategy with the undersampled data to see what happens. "
			]
			},
			{
			"cell_type": "code",
			"execution_count": 121,
			"metadata": {
			"scrolled": true
			},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"_________________________________________________________________\n",
			"Layer (type) Output Shape Param # \n",
			"=================================================================\n",
			"zero_padding2d_48 (ZeroPaddi (None, 32, 32, 3) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_184 (Conv2D) (None, 32, 32, 32) 896 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_83 (MaxPooling (None, 16, 16, 32) 0 \n",
			"_________________________________________________________________\n",
			"dropout_41 (Dropout) (None, 16, 16, 32) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_185 (Conv2D) (None, 16, 16, 64) 18496 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_84 (MaxPooling (None, 8, 8, 64) 0 \n",
			"_________________________________________________________________\n",
			"dropout_42 (Dropout) (None, 8, 8, 64) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_186 (Conv2D) (None, 8, 8, 128) 73856 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_85 (MaxPooling (None, 4, 4, 128) 0 \n",
			"_________________________________________________________________\n",
			"dropout_43 (Dropout) (None, 4, 4, 128) 0 \n",
			"_________________________________________________________________\n",
			"flatten_47 (Flatten) (None, 2048) 0 \n",
			"_________________________________________________________________\n",
			"dense_103 (Dense) (None, 64) 131136 \n",
			"_________________________________________________________________\n",
			"dropout_44 (Dropout) (None, 64) 0 \n",
			"_________________________________________________________________\n",
			"dense_104 (Dense) (None, 128) 8320 \n",
			"_________________________________________________________________\n",
			"dropout_45 (Dropout) (None, 128) 0 \n",
			"_________________________________________________________________\n",
			"dense_105 (Dense) (None, 2) 258 \n",
			"=================================================================\n",
			"Total params: 232,962\n",
			"Trainable params: 232,962\n",
			"Non-trainable params: 0\n",
			"_________________________________________________________________\n",
			"Train on 2317 samples, validate on 773 samples\n",
			"Epoch 1/100\n",
			"2317/2317 [==============================] - 11s 5ms/sample - loss: 0.7072 - acc: 0.5002 - val_loss: 0.6932 - val_acc: 0.4618\n",
			"Epoch 2/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6936 - acc: 0.5063 - val_loss: 0.6930 - val_acc: 0.4851\n",
			"Epoch 3/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6941 - acc: 0.5080 - val_loss: 0.6940 - val_acc: 0.4851\n",
			"Epoch 4/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6926 - acc: 0.5088 - val_loss: 0.6911 - val_acc: 0.5744\n",
			"Epoch 5/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6912 - acc: 0.5274 - val_loss: 0.6908 - val_acc: 0.5511\n",
			"Epoch 6/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6879 - acc: 0.5369 - val_loss: 0.6885 - val_acc: 0.5576\n",
			"Epoch 7/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6938 - acc: 0.5192 - val_loss: 0.6917 - val_acc: 0.4994\n",
			"Epoch 8/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6883 - acc: 0.5404 - val_loss: 0.6879 - val_acc: 0.5809\n",
			"Epoch 9/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6865 - acc: 0.5537 - val_loss: 0.6819 - val_acc: 0.5821\n",
			"Epoch 10/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6878 - acc: 0.5486 - val_loss: 0.6859 - val_acc: 0.5834\n",
			"Epoch 11/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6879 - acc: 0.5585 - val_loss: 0.6809 - val_acc: 0.5951\n",
			"Epoch 12/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6801 - acc: 0.5645 - val_loss: 0.6815 - val_acc: 0.5783\n",
			"Epoch 13/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6817 - acc: 0.5460 - val_loss: 0.6851 - val_acc: 0.5395\n",
			"Epoch 14/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6801 - acc: 0.5658 - val_loss: 0.6752 - val_acc: 0.5731\n",
			"Epoch 15/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6797 - acc: 0.5593 - val_loss: 0.6748 - val_acc: 0.5627\n",
			"Epoch 16/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6825 - acc: 0.5637 - val_loss: 0.6759 - val_acc: 0.5860\n",
			"Epoch 17/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6747 - acc: 0.5896 - val_loss: 0.6659 - val_acc: 0.5977\n",
			"Epoch 18/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6814 - acc: 0.5688 - val_loss: 0.6820 - val_acc: 0.5589\n",
			"Epoch 19/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6783 - acc: 0.5801 - val_loss: 0.6777 - val_acc: 0.5964\n",
			"Epoch 20/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6743 - acc: 0.5939 - val_loss: 0.6811 - val_acc: 0.5550\n",
			"Epoch 21/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6731 - acc: 0.5818 - val_loss: 0.6759 - val_acc: 0.5796\n",
			"Epoch 22/100\n",
			"2317/2317 [==============================] - 9s 4ms/sample - loss: 0.6770 - acc: 0.5757 - val_loss: 0.6799 - val_acc: 0.5614\n",
			"Epoch 23/100\n",
			"2317/2317 [==============================] - 9s 4ms/sample - loss: 0.6713 - acc: 0.5896 - val_loss: 0.6645 - val_acc: 0.5860\n",
			"Epoch 24/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6732 - acc: 0.5969 - val_loss: 0.6710 - val_acc: 0.5770\n",
			"Epoch 25/100\n",
			"2317/2317 [==============================] - 9s 4ms/sample - loss: 0.6701 - acc: 0.5870 - val_loss: 0.6737 - val_acc: 0.5744\n",
			"Epoch 26/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6763 - acc: 0.5788 - val_loss: 0.6760 - val_acc: 0.5847\n",
			"Epoch 27/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6682 - acc: 0.5939 - val_loss: 0.6756 - val_acc: 0.5809\n",
			"Epoch 28/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6722 - acc: 0.5814 - val_loss: 0.6712 - val_acc: 0.5744\n",
			"Epoch 29/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6681 - acc: 0.5796 - val_loss: 0.6770 - val_acc: 0.5744\n",
			"Epoch 30/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6642 - acc: 0.6021 - val_loss: 0.6669 - val_acc: 0.5847\n",
			"Epoch 31/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6643 - acc: 0.5943 - val_loss: 0.6727 - val_acc: 0.5821\n",
			"Epoch 32/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6694 - acc: 0.5900 - val_loss: 0.6685 - val_acc: 0.5809\n",
			"Epoch 33/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6704 - acc: 0.5943 - val_loss: 0.6706 - val_acc: 0.5873\n",
			"Epoch 34/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6650 - acc: 0.5960 - val_loss: 0.6676 - val_acc: 0.5692\n",
			"Epoch 35/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6568 - acc: 0.5973 - val_loss: 0.6697 - val_acc: 0.5796\n",
			"Epoch 36/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6632 - acc: 0.5991 - val_loss: 0.6724 - val_acc: 0.5809\n",
			"Epoch 37/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6602 - acc: 0.6038 - val_loss: 0.6691 - val_acc: 0.5899\n",
			"Epoch 38/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6616 - acc: 0.5995 - val_loss: 0.6673 - val_acc: 0.5925\n",
			"Epoch 39/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6556 - acc: 0.5973 - val_loss: 0.6626 - val_acc: 0.5834\n",
			"Epoch 40/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6583 - acc: 0.6025 - val_loss: 0.6719 - val_acc: 0.5537\n",
			"Epoch 41/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6601 - acc: 0.6055 - val_loss: 0.6753 - val_acc: 0.5576\n",
			"Epoch 42/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6602 - acc: 0.6055 - val_loss: 0.6735 - val_acc: 0.5550\n",
			"Epoch 43/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6528 - acc: 0.6060 - val_loss: 0.6679 - val_acc: 0.5847\n",
			"Epoch 44/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6555 - acc: 0.6176 - val_loss: 0.6685 - val_acc: 0.5834\n",
			"Epoch 45/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6581 - acc: 0.6034 - val_loss: 0.6728 - val_acc: 0.5899\n",
			"Epoch 46/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6543 - acc: 0.6077 - val_loss: 0.6661 - val_acc: 0.5834\n",
			"Epoch 47/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6528 - acc: 0.6120 - val_loss: 0.6639 - val_acc: 0.5899\n",
			"Epoch 48/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6506 - acc: 0.6094 - val_loss: 0.6661 - val_acc: 0.5977\n",
			"Epoch 49/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6484 - acc: 0.6047 - val_loss: 0.6657 - val_acc: 0.5666\n",
			"Epoch 50/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6454 - acc: 0.6163 - val_loss: 0.6660 - val_acc: 0.5718\n",
			"Epoch 51/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6497 - acc: 0.6202 - val_loss: 0.6639 - val_acc: 0.5977\n",
			"Epoch 52/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6474 - acc: 0.6042 - val_loss: 0.6648 - val_acc: 0.5834\n",
			"Epoch 53/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6465 - acc: 0.6206 - val_loss: 0.6645 - val_acc: 0.5925\n",
			"Epoch 54/100\n",
			"2317/2317 [==============================] - 9s 4ms/sample - loss: 0.6490 - acc: 0.6060 - val_loss: 0.6587 - val_acc: 0.5964\n",
			"Epoch 55/100\n",
			"2317/2317 [==============================] - 9s 4ms/sample - loss: 0.6523 - acc: 0.6021 - val_loss: 0.6575 - val_acc: 0.6054\n",
			"Epoch 56/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6458 - acc: 0.6077 - val_loss: 0.6535 - val_acc: 0.5938\n",
			"Epoch 57/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6435 - acc: 0.6176 - val_loss: 0.6636 - val_acc: 0.5860\n",
			"Epoch 58/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6393 - acc: 0.6090 - val_loss: 0.6648 - val_acc: 0.5886\n",
			"Epoch 59/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6405 - acc: 0.6193 - val_loss: 0.6615 - val_acc: 0.5783\n",
			"Epoch 60/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6419 - acc: 0.6094 - val_loss: 0.6571 - val_acc: 0.6041\n",
			"Epoch 61/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6408 - acc: 0.6228 - val_loss: 0.6607 - val_acc: 0.5821\n",
			"Epoch 62/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6372 - acc: 0.6189 - val_loss: 0.6604 - val_acc: 0.5860\n",
			"Epoch 63/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6387 - acc: 0.6163 - val_loss: 0.6639 - val_acc: 0.6016\n",
			"Epoch 64/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6379 - acc: 0.6077 - val_loss: 0.6642 - val_acc: 0.6003\n",
			"Epoch 65/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6376 - acc: 0.6215 - val_loss: 0.6539 - val_acc: 0.5886\n",
			"Epoch 66/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6345 - acc: 0.6176 - val_loss: 0.6555 - val_acc: 0.6119\n",
			"Epoch 67/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6346 - acc: 0.6314 - val_loss: 0.6621 - val_acc: 0.5886\n",
			"Epoch 68/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6344 - acc: 0.6353 - val_loss: 0.6573 - val_acc: 0.6067\n",
			"Epoch 69/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6315 - acc: 0.6388 - val_loss: 0.6601 - val_acc: 0.5990\n",
			"Epoch 70/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6252 - acc: 0.6362 - val_loss: 0.6551 - val_acc: 0.5938\n",
			"Epoch 71/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6292 - acc: 0.6370 - val_loss: 0.6559 - val_acc: 0.5899\n",
			"Epoch 72/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6354 - acc: 0.6163 - val_loss: 0.6593 - val_acc: 0.5886\n",
			"Epoch 73/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6227 - acc: 0.6487 - val_loss: 0.6499 - val_acc: 0.6145\n",
			"Epoch 74/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6259 - acc: 0.6262 - val_loss: 0.6502 - val_acc: 0.6028\n",
			"Epoch 75/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6178 - acc: 0.6474 - val_loss: 0.6547 - val_acc: 0.5912\n",
			"Epoch 76/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6185 - acc: 0.6401 - val_loss: 0.6585 - val_acc: 0.5860\n",
			"Epoch 77/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6179 - acc: 0.6331 - val_loss: 0.6607 - val_acc: 0.5783\n",
			"Epoch 78/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6203 - acc: 0.6439 - val_loss: 0.6601 - val_acc: 0.5821\n",
			"Epoch 79/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6111 - acc: 0.6647 - val_loss: 0.6547 - val_acc: 0.5873\n",
			"Epoch 80/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6225 - acc: 0.6478 - val_loss: 0.6587 - val_acc: 0.5964\n",
			"Epoch 81/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6128 - acc: 0.6383 - val_loss: 0.6478 - val_acc: 0.6248\n",
			"Epoch 82/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6174 - acc: 0.6470 - val_loss: 0.6621 - val_acc: 0.5899\n",
			"Epoch 83/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6021 - acc: 0.6573 - val_loss: 0.6589 - val_acc: 0.5964\n",
			"Epoch 84/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6176 - acc: 0.6396 - val_loss: 0.6512 - val_acc: 0.6093\n",
			"Epoch 85/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6140 - acc: 0.6409 - val_loss: 0.6540 - val_acc: 0.6003\n",
			"Epoch 86/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6127 - acc: 0.6478 - val_loss: 0.6470 - val_acc: 0.6067\n",
			"Epoch 87/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6069 - acc: 0.6577 - val_loss: 0.6568 - val_acc: 0.5990\n",
			"Epoch 88/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6099 - acc: 0.6418 - val_loss: 0.6485 - val_acc: 0.6106\n",
			"Epoch 89/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6047 - acc: 0.6560 - val_loss: 0.6522 - val_acc: 0.5821\n",
			"Epoch 90/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6195 - acc: 0.6534 - val_loss: 0.6566 - val_acc: 0.5666\n",
			"Epoch 91/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6128 - acc: 0.6474 - val_loss: 0.6508 - val_acc: 0.5951\n",
			"Epoch 92/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6071 - acc: 0.6461 - val_loss: 0.6506 - val_acc: 0.5990\n",
			"Epoch 93/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6099 - acc: 0.6422 - val_loss: 0.6507 - val_acc: 0.6054\n",
			"Epoch 94/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.5922 - acc: 0.6621 - val_loss: 0.6573 - val_acc: 0.5873\n",
			"Epoch 95/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.5988 - acc: 0.6560 - val_loss: 0.6576 - val_acc: 0.5744\n",
			"Epoch 96/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6069 - acc: 0.6413 - val_loss: 0.6532 - val_acc: 0.6067\n",
			"Epoch 97/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.5946 - acc: 0.6595 - val_loss: 0.6576 - val_acc: 0.6080\n",
			"Epoch 98/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6000 - acc: 0.6599 - val_loss: 0.6547 - val_acc: 0.6093\n",
			"Epoch 99/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.5912 - acc: 0.6677 - val_loss: 0.6624 - val_acc: 0.5873\n",
			"Epoch 100/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.5998 - acc: 0.6577 - val_loss: 0.6573 - val_acc: 0.5990\n",
			"[[296 102]\n",
			" [208 167]]\n",
			"Train/Test recall: 0.5436 / 0.4453\n",
			"Train/Test accuracy: 0.6858 / 0.5990\n",
			"Test specificity: 0.7437\n"
			]
			},
			{
			"data": {
			"image/png": 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\n",
			"text/plain": [
			"<Figure size 1944x432 with 3 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"model11 = models.Sequential()\n",
			"# need to add an extra zero padding layer, 4 on each width side, 2 on each height side\n",
			"model11.add(layers.ZeroPadding2D(padding=(4, 2), data_format=None,input_shape=(24, 28, 3)))\n",
			"# 1st conv layer, with 32 filters of size (3,3) \n",
			"model11.add(layers.Conv2D(32, (3, 3), activation='relu', padding=\"same\"))\n",
			"# 1stpool layer, divinding by 2 the dimension\n",
			"model11.add(layers.MaxPooling2D((2, 2)))\n",
			"model11.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"# 2ndconv layer, with 64 filters of size (3,3) \n",
			"model11.add(layers.Conv2D(64, (3, 3), activation='relu', padding=\"same\"))\n",
			"# 2nd pool layer, divinding by 2 the dimension\n",
			"model11.add(layers.MaxPooling2D((2, 2)))\n",
			"model11.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"# lastconv layer, with 64 filters of size (3,3) \n",
			"model11.add(layers.Conv2D(128, (3, 3), activation='relu', padding=\"same\"))\n",
			"model11.add(layers.MaxPooling2D((2, 2)))\n",
			"model11.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"\n",
			"# flaten the images to prepare for the dense layers\n",
			"model11.add(layers.Flatten())\n",
			"# DROPOUT\n",
			"model11.add(layers.Dense(64, activation='relu'))\n",
			"model11.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"\n",
			"model11.add(layers.Dense(128, activation='relu'))\n",
			"model11.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"\n",
			"# fin9l dense softmax layer, with 2 classes so 2 dimension, to have probabilities at the end\n",
			"model11.add(layers.Dense(2, activation='softmax'))\n",
			"\n",
			"# model architecture\n",
			"model11.summary()\n",
			"\n",
			"train_pred_class11,test_pred_class11 = CompileAndTrainCNNModel(model11,images_under, labels_under,100,\"model11\")"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Set dropout rate at 20%"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 308,
			"metadata": {},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"_________________________________________________________________\n",
			"Layer (type) Output Shape Param # \n",
			"=================================================================\n",
			"zero_padding2d_49 (ZeroPaddi (None, 32, 32, 3) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_187 (Conv2D) (None, 32, 32, 32) 896 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_86 (MaxPooling (None, 16, 16, 32) 0 \n",
			"_________________________________________________________________\n",
			"dropout_46 (Dropout) (None, 16, 16, 32) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_188 (Conv2D) (None, 16, 16, 64) 18496 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_87 (MaxPooling (None, 8, 8, 64) 0 \n",
			"_________________________________________________________________\n",
			"dropout_47 (Dropout) (None, 8, 8, 64) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_189 (Conv2D) (None, 8, 8, 128) 73856 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_88 (MaxPooling (None, 4, 4, 128) 0 \n",
			"_________________________________________________________________\n",
			"dropout_48 (Dropout) (None, 4, 4, 128) 0 \n",
			"_________________________________________________________________\n",
			"flatten_48 (Flatten) (None, 2048) 0 \n",
			"_________________________________________________________________\n",
			"dense_106 (Dense) (None, 64) 131136 \n",
			"_________________________________________________________________\n",
			"dropout_49 (Dropout) (None, 64) 0 \n",
			"_________________________________________________________________\n",
			"dense_107 (Dense) (None, 128) 8320 \n",
			"_________________________________________________________________\n",
			"dropout_50 (Dropout) (None, 128) 0 \n",
			"_________________________________________________________________\n",
			"dense_108 (Dense) (None, 2) 258 \n",
			"=================================================================\n",
			"Total params: 232,962\n",
			"Trainable params: 232,962\n",
			"Non-trainable params: 0\n",
			"_________________________________________________________________\n",
			"Train on 2317 samples, validate on 773 samples\n",
			"Epoch 1/100\n",
			"2317/2317 [==============================] - 10s 4ms/sample - loss: 0.6951 - acc: 0.5119 - val_loss: 0.6895 - val_acc: 0.5692\n",
			"Epoch 2/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6874 - acc: 0.5451 - val_loss: 0.6776 - val_acc: 0.5899\n",
			"Epoch 3/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6821 - acc: 0.5568 - val_loss: 0.6744 - val_acc: 0.5757\n",
			"Epoch 4/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6822 - acc: 0.5598 - val_loss: 0.6760 - val_acc: 0.5821\n",
			"Epoch 5/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6767 - acc: 0.5727 - val_loss: 0.6642 - val_acc: 0.5731\n",
			"Epoch 6/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6692 - acc: 0.5883 - val_loss: 0.6740 - val_acc: 0.5640\n",
			"Epoch 7/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6720 - acc: 0.5978 - val_loss: 0.6734 - val_acc: 0.5770\n",
			"Epoch 8/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6599 - acc: 0.6202 - val_loss: 0.6663 - val_acc: 0.5796\n",
			"Epoch 9/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6581 - acc: 0.6176 - val_loss: 0.6756 - val_acc: 0.5679\n",
			"Epoch 10/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6588 - acc: 0.6116 - val_loss: 0.6695 - val_acc: 0.5834\n",
			"Epoch 11/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6569 - acc: 0.6267 - val_loss: 0.6650 - val_acc: 0.5796\n",
			"Epoch 12/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6502 - acc: 0.6254 - val_loss: 0.6591 - val_acc: 0.5990\n",
			"Epoch 13/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6432 - acc: 0.6232 - val_loss: 0.6630 - val_acc: 0.5964\n",
			"Epoch 14/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6468 - acc: 0.6258 - val_loss: 0.6579 - val_acc: 0.5899\n",
			"Epoch 15/100\n",
			"2317/2317 [==============================] - 9s 4ms/sample - loss: 0.6410 - acc: 0.6249 - val_loss: 0.6681 - val_acc: 0.5433\n",
			"Epoch 16/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6314 - acc: 0.6202 - val_loss: 0.6600 - val_acc: 0.5821\n",
			"Epoch 17/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6289 - acc: 0.6461 - val_loss: 0.6635 - val_acc: 0.5653\n",
			"Epoch 18/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6177 - acc: 0.6530 - val_loss: 0.6481 - val_acc: 0.6106\n",
			"Epoch 19/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6095 - acc: 0.6526 - val_loss: 0.6647 - val_acc: 0.6016\n",
			"Epoch 20/100\n",
			"2317/2317 [==============================] - 9s 4ms/sample - loss: 0.6079 - acc: 0.6547 - val_loss: 0.6452 - val_acc: 0.6197\n",
			"Epoch 21/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.5962 - acc: 0.6573 - val_loss: 0.6528 - val_acc: 0.6210\n",
			"Epoch 22/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.5876 - acc: 0.6672 - val_loss: 0.6557 - val_acc: 0.6041\n",
			"Epoch 23/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.5873 - acc: 0.6629 - val_loss: 0.7647 - val_acc: 0.5731\n",
			"Epoch 24/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.5765 - acc: 0.6746 - val_loss: 0.6586 - val_acc: 0.6248\n",
			"Epoch 25/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.5589 - acc: 0.6940 - val_loss: 0.6495 - val_acc: 0.6339\n",
			"Epoch 26/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.5606 - acc: 0.6845 - val_loss: 0.6658 - val_acc: 0.6067\n",
			"Epoch 27/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.5486 - acc: 0.6923 - val_loss: 0.6757 - val_acc: 0.6080\n",
			"Epoch 28/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.5328 - acc: 0.6966 - val_loss: 0.6552 - val_acc: 0.6235\n",
			"Epoch 29/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.5190 - acc: 0.7177 - val_loss: 0.6647 - val_acc: 0.6106\n",
			"Epoch 30/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.5200 - acc: 0.7130 - val_loss: 0.6744 - val_acc: 0.6158\n",
			"Epoch 31/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.5045 - acc: 0.7212 - val_loss: 0.7048 - val_acc: 0.6003\n",
			"Epoch 32/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.4965 - acc: 0.7272 - val_loss: 0.6606 - val_acc: 0.6171\n",
			"Epoch 33/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.4825 - acc: 0.7402 - val_loss: 0.6789 - val_acc: 0.6093\n",
			"Epoch 34/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.4756 - acc: 0.7285 - val_loss: 0.6881 - val_acc: 0.6261\n",
			"Epoch 35/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.4629 - acc: 0.7410 - val_loss: 0.7363 - val_acc: 0.6184\n",
			"Epoch 36/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.4631 - acc: 0.7454 - val_loss: 0.6945 - val_acc: 0.6171\n",
			"Epoch 37/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.4498 - acc: 0.7523 - val_loss: 0.7237 - val_acc: 0.6028\n",
			"Epoch 38/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.4357 - acc: 0.7656 - val_loss: 0.7508 - val_acc: 0.6145\n",
			"Epoch 39/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.4354 - acc: 0.7613 - val_loss: 0.7617 - val_acc: 0.6132\n",
			"Epoch 40/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.4306 - acc: 0.7760 - val_loss: 0.8112 - val_acc: 0.6145\n",
			"Epoch 41/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.4192 - acc: 0.7760 - val_loss: 0.7693 - val_acc: 0.6261\n",
			"Epoch 42/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.4123 - acc: 0.7773 - val_loss: 0.7713 - val_acc: 0.6274\n",
			"Epoch 43/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.4067 - acc: 0.7803 - val_loss: 0.7889 - val_acc: 0.6235\n",
			"Epoch 44/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3943 - acc: 0.7859 - val_loss: 0.8061 - val_acc: 0.6184\n",
			"Epoch 45/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3874 - acc: 0.7881 - val_loss: 0.7704 - val_acc: 0.6210\n",
			"Epoch 46/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3680 - acc: 0.7976 - val_loss: 0.7930 - val_acc: 0.6067\n",
			"Epoch 47/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3776 - acc: 0.7976 - val_loss: 0.7810 - val_acc: 0.6223\n",
			"Epoch 48/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3690 - acc: 0.8028 - val_loss: 0.8334 - val_acc: 0.6158\n",
			"Epoch 49/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3681 - acc: 0.7984 - val_loss: 0.8439 - val_acc: 0.6067\n",
			"Epoch 50/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3497 - acc: 0.8123 - val_loss: 0.9209 - val_acc: 0.6041\n",
			"Epoch 51/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3667 - acc: 0.7967 - val_loss: 0.8798 - val_acc: 0.6235\n",
			"Epoch 52/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3568 - acc: 0.8071 - val_loss: 0.8314 - val_acc: 0.6041\n",
			"Epoch 53/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3576 - acc: 0.8079 - val_loss: 0.8942 - val_acc: 0.6145\n",
			"Epoch 54/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3228 - acc: 0.8282 - val_loss: 0.9305 - val_acc: 0.6274\n",
			"Epoch 55/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3627 - acc: 0.8114 - val_loss: 0.8968 - val_acc: 0.6171\n",
			"Epoch 56/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3585 - acc: 0.8161 - val_loss: 0.9131 - val_acc: 0.5990\n",
			"Epoch 57/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3357 - acc: 0.8166 - val_loss: 0.9011 - val_acc: 0.6145\n",
			"Epoch 58/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3271 - acc: 0.8230 - val_loss: 0.9445 - val_acc: 0.6235\n",
			"Epoch 59/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3212 - acc: 0.8213 - val_loss: 1.0473 - val_acc: 0.6106\n",
			"Epoch 60/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3117 - acc: 0.8386 - val_loss: 0.9877 - val_acc: 0.6223\n",
			"Epoch 61/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3303 - acc: 0.8161 - val_loss: 0.9047 - val_acc: 0.6054\n",
			"Epoch 62/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3161 - acc: 0.8222 - val_loss: 0.9812 - val_acc: 0.6054\n",
			"Epoch 63/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3200 - acc: 0.8226 - val_loss: 0.9216 - val_acc: 0.6106\n",
			"Epoch 64/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3297 - acc: 0.8256 - val_loss: 1.0098 - val_acc: 0.6041\n",
			"Epoch 65/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3121 - acc: 0.8334 - val_loss: 1.0001 - val_acc: 0.6210\n",
			"Epoch 66/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.3065 - acc: 0.8338 - val_loss: 1.0073 - val_acc: 0.6145\n",
			"Epoch 67/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3144 - acc: 0.8351 - val_loss: 0.9773 - val_acc: 0.6197\n",
			"Epoch 68/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2937 - acc: 0.8377 - val_loss: 1.0162 - val_acc: 0.6132\n",
			"Epoch 69/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3147 - acc: 0.8308 - val_loss: 0.9983 - val_acc: 0.6274\n",
			"Epoch 70/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3075 - acc: 0.8382 - val_loss: 0.9092 - val_acc: 0.6274\n",
			"Epoch 71/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2983 - acc: 0.8412 - val_loss: 1.0184 - val_acc: 0.6261\n",
			"Epoch 72/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3095 - acc: 0.8325 - val_loss: 1.0076 - val_acc: 0.6067\n",
			"Epoch 73/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3025 - acc: 0.8312 - val_loss: 1.0271 - val_acc: 0.6054\n",
			"Epoch 74/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2973 - acc: 0.8407 - val_loss: 1.0904 - val_acc: 0.6210\n",
			"Epoch 75/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2894 - acc: 0.8394 - val_loss: 1.0625 - val_acc: 0.6119\n",
			"Epoch 76/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3167 - acc: 0.8226 - val_loss: 0.9534 - val_acc: 0.6119\n",
			"Epoch 77/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2907 - acc: 0.8442 - val_loss: 1.1199 - val_acc: 0.6067\n",
			"Epoch 78/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2870 - acc: 0.8369 - val_loss: 1.0907 - val_acc: 0.6145\n",
			"Epoch 79/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2800 - acc: 0.8481 - val_loss: 1.2384 - val_acc: 0.6119\n",
			"Epoch 80/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2996 - acc: 0.8433 - val_loss: 1.0861 - val_acc: 0.6145\n",
			"Epoch 81/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2866 - acc: 0.8399 - val_loss: 1.1305 - val_acc: 0.6145\n",
			"Epoch 82/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.3033 - acc: 0.8347 - val_loss: 0.9203 - val_acc: 0.6016\n",
			"Epoch 83/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2754 - acc: 0.8567 - val_loss: 1.1202 - val_acc: 0.6184\n",
			"Epoch 84/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2861 - acc: 0.8472 - val_loss: 1.0371 - val_acc: 0.6119\n",
			"Epoch 85/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2728 - acc: 0.8429 - val_loss: 1.1382 - val_acc: 0.6235\n",
			"Epoch 86/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2625 - acc: 0.8520 - val_loss: 1.1105 - val_acc: 0.6171\n",
			"Epoch 87/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2910 - acc: 0.8468 - val_loss: 0.9914 - val_acc: 0.6132\n",
			"Epoch 88/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2899 - acc: 0.8507 - val_loss: 1.0336 - val_acc: 0.6210\n",
			"Epoch 89/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2694 - acc: 0.8563 - val_loss: 1.1552 - val_acc: 0.6197\n",
			"Epoch 90/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2831 - acc: 0.8541 - val_loss: 1.0313 - val_acc: 0.6158\n",
			"Epoch 91/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2690 - acc: 0.8619 - val_loss: 1.2259 - val_acc: 0.6145\n",
			"Epoch 92/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2512 - acc: 0.8615 - val_loss: 1.2312 - val_acc: 0.6248\n",
			"Epoch 93/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2719 - acc: 0.8623 - val_loss: 1.0981 - val_acc: 0.6132\n",
			"Epoch 94/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2641 - acc: 0.8524 - val_loss: 1.1488 - val_acc: 0.6067\n",
			"Epoch 95/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2638 - acc: 0.8563 - val_loss: 1.1384 - val_acc: 0.6093\n",
			"Epoch 96/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2810 - acc: 0.8481 - val_loss: 1.1105 - val_acc: 0.6132\n",
			"Epoch 97/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2777 - acc: 0.8546 - val_loss: 1.0728 - val_acc: 0.6261\n",
			"Epoch 98/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2712 - acc: 0.8628 - val_loss: 1.1068 - val_acc: 0.6326\n",
			"Epoch 99/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2723 - acc: 0.8658 - val_loss: 1.0412 - val_acc: 0.6080\n",
			"Epoch 100/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.2713 - acc: 0.8546 - val_loss: 1.1165 - val_acc: 0.6248\n",
			"[[292 106]\n",
			" [184 191]]\n",
			"Train/Test recall: 0.7829 / 0.5093\n",
			"Train/Test accuracy: 0.8895 / 0.6248\n",
			"Test specificity: 0.7337\n"
			]
			},
			{
			"data": {
			"image/png": 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\n",
			"text/plain": [
			"<Figure size 1800x1080 with 3 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"model12 = models.Sequential()\n",
			"# need to add an extra zero padding layer, 4 on each width side, 2 on each height side\n",
			"model12.add(layers.ZeroPadding2D(padding=(4, 2), data_format=None,input_shape=(24, 28, 3)))\n",
			"# 1st conv layer, with 32 filters of size (3,3) \n",
			"model12.add(layers.Conv2D(32, (3, 3), activation='relu', padding=\"same\"))\n",
			"# 1stpool layer, divinding by 2 the dimension\n",
			"model12.add(layers.MaxPooling2D((2, 2)))\n",
			"model12.add(layers.Dropout(0.2, noise_shape=None, seed=None))\n",
			"# 2ndconv layer, with 64 filters of size (3,3) \n",
			"model12.add(layers.Conv2D(64, (3, 3), activation='relu', padding=\"same\"))\n",
			"# 2nd pool layer, divinding by 2 the dimension\n",
			"model12.add(layers.MaxPooling2D((2, 2)))\n",
			"model12.add(layers.Dropout(0.2, noise_shape=None, seed=None))\n",
			"# lastconv layer, with 64 filters of size (3,3) \n",
			"model12.add(layers.Conv2D(128, (3, 3), activation='relu', padding=\"same\"))\n",
			"model12.add(layers.MaxPooling2D((2, 2)))\n",
			"model12.add(layers.Dropout(0.2, noise_shape=None, seed=None))\n",
			"\n",
			"# flaten the images to prepare for the dense layers\n",
			"model12.add(layers.Flatten())\n",
			"# DROPOUT\n",
			"model12.add(layers.Dense(64, activation='relu'))\n",
			"model12.add(layers.Dropout(0.2, noise_shape=None, seed=None))\n",
			"\n",
			"model12.add(layers.Dense(128, activation='relu'))\n",
			"model12.add(layers.Dropout(0.2, noise_shape=None, seed=None))\n",
			"\n",
			"# fin9l dense softmax layer, with 2 classes so 2 dimension, to have probabilities at the end\n",
			"model12.add(layers.Dense(2, activation='softmax'))\n",
			"\n",
			"# model architecture\n",
			"model12.summary()\n",
			"\n",
			"train_pred_class12,test_pred_class12 = CompileAndTrainCNNModel(model12,images_under, labels_under,100,\"model12\")"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"##### At least its not overfitting that much!! But the recall became very bad...! LOL. "
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Maybe we need more data: AUGMENTATION?!"
			]
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"### SAVE MODELS."
			]
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"### IMPORT MODELS"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 11,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": [
			"from tensorflow.keras import layers, models, preprocessing\n",
			"from sklearn.metrics import roc_curve, auc\n",
			"from sklearn.metrics import confusion_matrix\n",
			"from sklearn.metrics import accuracy_score, precision_score, recall_score\n",
			"\n",
			"plt.rcParams['figure.figsize'] = (15, 8)\n",
			"# to fix it then...\n",
			"import os\n",
			"os.environ['KMP_DUPLICATE_LIB_OK']='True'"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 20,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": [
			"# Recreate the exact same model purely from the file\n",
			"model3 = models.load_model('my_model3.h5')\n"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 21,
			"metadata": {},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"_________________________________________________________________\n",
			"Layer (type) Output Shape Param # \n",
			"=================================================================\n",
			"zero_padding2d_22 (ZeroPaddi (None, 32, 32, 3) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_89 (Conv2D) (None, 32, 32, 32) 896 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_47 (MaxPooling (None, 16, 16, 32) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_90 (Conv2D) (None, 16, 16, 64) 18496 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_48 (MaxPooling (None, 8, 8, 64) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_91 (Conv2D) (None, 8, 8, 64) 36928 \n",
			"_________________________________________________________________\n",
			"flatten_22 (Flatten) (None, 4096) 0 \n",
			"_________________________________________________________________\n",
			"dense_44 (Dense) (None, 64) 262208 \n",
			"_________________________________________________________________\n",
			"dense_45 (Dense) (None, 2) 130 \n",
			"=================================================================\n",
			"Total params: 318,658\n",
			"Trainable params: 318,658\n",
			"Non-trainable params: 0\n",
			"_________________________________________________________________\n"
			]
			}
			],
			"source": [
			"model3.summary()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"### Let's try augmentation to create more data. "
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Let's look at possible augmentation techniques from data generators."
			]
			},
			{
			"cell_type": "code",
			"execution_count": 12,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": [
			"plt.rcParams['figure.figsize'] = (5, 5)"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 13,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": [
			"def plotImage(data_generator,images):\n",
			" \"\"\"\n",
			" Plots 4 images generated by an object of the ImageDataGenerator class.\n",
			" \"\"\"\n",
			" data_generator.fit(images)\n",
			" image_iterator = data_generator.flow(images)\n",
			" \n",
			" # Plot the images given by the iterator\n",
			" fig, rows = plt.subplots(nrows=1, ncols=4, figsize=(18,18))\n",
			" for row in rows:\n",
			" row.imshow(image_iterator.next()[0])\n",
			" row.axis('off')\n",
			" plt.show()"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Rotating"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 34,
			"metadata": {},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"rotation\n"
			]
			},
			{
			"data": {
			"image/png": 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\n",
			"text/plain": [
			"<Figure size 360x360 with 1 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"data": {
			"image/png": 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			"text/plain": [
			"<Figure size 1296x1296 with 4 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"vert Flip\n"
			]
			},
			{
			"data": {
			"image/png": 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\n",
			"text/plain": [
			"<Figure size 1296x1296 with 4 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"horiz Flip\n"
			]
			},
			{
			"data": {
			"image/png": 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\n",
			"text/plain": [
			"<Figure size 1296x1296 with 4 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"# example index of image\n",
			"ind =49\n",
			"image_ex = images[ind:ind+1]\n",
			"\n",
			"data_generator_rotation = preprocessing.image.ImageDataGenerator(rotation_range=90)\n",
			"data_generator_bright = preprocessing.image.ImageDataGenerator(brightness_range=(0.1, 0.9))\n",
			"data_generator_verticalFlip = preprocessing.image.ImageDataGenerator(vertical_flip=True)\n",
			"data_generator_horizontalFlip = preprocessing.image.ImageDataGenerator(horizontal_flip=True)\n",
			"\n",
			"plt.imshow(image_ex[0])\n",
			"\n",
			"print(\"rotation\")\n",
			"\n",
			"plotImage(data_generator_rotation,image_ex)\n",
			"\n",
			"print(\"vert Flip\")\n",
			"\n",
			"plotImage(data_generator_verticalFlip,image_ex)\n",
			"\n",
			"print(\"horiz Flip\")\n",
			"plotImage(data_generator_horizontalFlip,image_ex)"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Vertical flip and horizontal flip. "
			]
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": 12,
			"metadata": {},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"WARNING:tensorflow:From /Users/assoulin/anaconda/envs/py37/lib/python3.7/site-packages/tensorflow/python/ops/resource_variable_ops.py:435: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\n",
			"Instructions for updating:\n",
			"Colocations handled automatically by placer.\n",
			"WARNING:tensorflow:From /Users/assoulin/anaconda/envs/py37/lib/python3.7/site-packages/tensorflow/python/keras/layers/core.py:143: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version.\n",
			"Instructions for updating:\n",
			"Please use `rate` instead of `keep_prob`. Rate should be set to `rate = 1 - keep_prob`.\n",
			"_________________________________________________________________\n",
			"Layer (type) Output Shape Param # \n",
			"=================================================================\n",
			"zero_padding2d (ZeroPadding2 (None, 32, 32, 3) 0 \n",
			"_________________________________________________________________\n",
			"conv2d (Conv2D) (None, 32, 32, 32) 896 \n",
			"_________________________________________________________________\n",
			"max_pooling2d (MaxPooling2D) (None, 16, 16, 32) 0 \n",
			"_________________________________________________________________\n",
			"dropout (Dropout) (None, 16, 16, 32) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_1 (Conv2D) (None, 16, 16, 64) 18496 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_1 (MaxPooling2 (None, 8, 8, 64) 0 \n",
			"_________________________________________________________________\n",
			"dropout_1 (Dropout) (None, 8, 8, 64) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_2 (Conv2D) (None, 8, 8, 128) 73856 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_2 (MaxPooling2 (None, 4, 4, 128) 0 \n",
			"_________________________________________________________________\n",
			"dropout_2 (Dropout) (None, 4, 4, 128) 0 \n",
			"_________________________________________________________________\n",
			"flatten (Flatten) (None, 2048) 0 \n",
			"_________________________________________________________________\n",
			"dense (Dense) (None, 64) 131136 \n",
			"_________________________________________________________________\n",
			"dropout_3 (Dropout) (None, 64) 0 \n",
			"_________________________________________________________________\n",
			"dense_1 (Dense) (None, 128) 8320 \n",
			"_________________________________________________________________\n",
			"dropout_4 (Dropout) (None, 128) 0 \n",
			"_________________________________________________________________\n",
			"dense_2 (Dense) (None, 2) 258 \n",
			"=================================================================\n",
			"Total params: 232,962\n",
			"Trainable params: 232,962\n",
			"Non-trainable params: 0\n",
			"_________________________________________________________________\n"
			]
			}
			],
			"source": [
			"model20 = models.Sequential()\n",
			"# need to add an extra zero padding layer, 4 on each width side, 2 on each height side\n",
			"model20.add(layers.ZeroPadding2D(padding=(4, 2), data_format=None,input_shape=(24, 28, 3)))\n",
			"# 1st conv layer, with 32 filters of size (3,3) \n",
			"model20.add(layers.Conv2D(32, (3, 3), activation='relu', padding=\"same\"))\n",
			"# 1stpool layer, divinding by 2 the dimension\n",
			"model20.add(layers.MaxPooling2D((2, 2)))\n",
			"model20.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"# 2ndconv layer, with 64 filters of size (3,3) \n",
			"model20.add(layers.Conv2D(64, (3, 3), activation='relu', padding=\"same\"))\n",
			"# 2nd pool layer, divinding by 2 the dimension\n",
			"model20.add(layers.MaxPooling2D((2, 2)))\n",
			"model20.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"# last conv layer, with 64 filters of size (3,3) \n",
			"model20.add(layers.Conv2D(128, (3, 3), activation='relu', padding=\"same\"))\n",
			"model20.add(layers.MaxPooling2D((2, 2)))\n",
			"model20.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"\n",
			"# flaten the images to prepare for the dense layers\n",
			"model20.add(layers.Flatten())\n",
			"# DROPOUT\n",
			"model20.add(layers.Dense(64, activation='relu'))\n",
			"model20.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"\n",
			"model20.add(layers.Dense(128, activation='relu'))\n",
			"model20.add(layers.Dropout(0.5, noise_shape=None, seed=None))\n",
			"\n",
			"# fin9l dense softmax layer, with 2 classes so 2 dimension, to have probabilities at the end\n",
			"model20.add(layers.Dense(2, activation='softmax'))\n",
			"\n",
			"# model architecture\n",
			"model20.summary()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 13,
			"metadata": {},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"Train on 2317 samples, validate on 773 samples\n",
			"Epoch 1/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.7038 - acc: 0.4890 - val_loss: 0.6929 - val_acc: 0.5149\n",
			"Epoch 2/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6950 - acc: 0.4912 - val_loss: 0.6930 - val_acc: 0.5175\n",
			"Epoch 3/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6933 - acc: 0.5201 - val_loss: 0.6924 - val_acc: 0.5149\n",
			"Epoch 4/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6939 - acc: 0.4985 - val_loss: 0.6935 - val_acc: 0.4851\n",
			"Epoch 5/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6923 - acc: 0.5214 - val_loss: 0.6930 - val_acc: 0.4851\n",
			"Epoch 6/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6931 - acc: 0.5058 - val_loss: 0.6917 - val_acc: 0.5744\n",
			"Epoch 7/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6901 - acc: 0.5369 - val_loss: 0.6938 - val_acc: 0.4851\n",
			"Epoch 8/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6935 - acc: 0.5097 - val_loss: 0.6933 - val_acc: 0.4851\n",
			"Epoch 9/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6893 - acc: 0.5291 - val_loss: 0.6938 - val_acc: 0.4851\n",
			"Epoch 10/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6911 - acc: 0.5192 - val_loss: 0.6869 - val_acc: 0.5731\n",
			"Epoch 11/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6896 - acc: 0.5395 - val_loss: 0.6834 - val_acc: 0.5718\n",
			"Epoch 12/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6891 - acc: 0.5434 - val_loss: 0.6835 - val_acc: 0.5653\n",
			"Epoch 13/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6887 - acc: 0.5503 - val_loss: 0.6857 - val_acc: 0.5718\n",
			"Epoch 14/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6891 - acc: 0.5399 - val_loss: 0.6816 - val_acc: 0.5834\n",
			"Epoch 15/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6918 - acc: 0.5283 - val_loss: 0.6860 - val_acc: 0.5964\n",
			"Epoch 16/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6858 - acc: 0.5589 - val_loss: 0.6792 - val_acc: 0.5783\n",
			"Epoch 17/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6856 - acc: 0.5619 - val_loss: 0.6798 - val_acc: 0.5614\n",
			"Epoch 18/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6823 - acc: 0.5710 - val_loss: 0.6867 - val_acc: 0.5162\n",
			"Epoch 19/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6793 - acc: 0.5654 - val_loss: 0.6734 - val_acc: 0.5744\n",
			"Epoch 20/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6799 - acc: 0.5641 - val_loss: 0.6808 - val_acc: 0.5666\n",
			"Epoch 21/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6792 - acc: 0.5697 - val_loss: 0.6738 - val_acc: 0.5705\n",
			"Epoch 22/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6778 - acc: 0.5818 - val_loss: 0.6784 - val_acc: 0.5627\n",
			"Epoch 23/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6774 - acc: 0.5757 - val_loss: 0.6773 - val_acc: 0.5731\n",
			"Epoch 24/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6732 - acc: 0.5883 - val_loss: 0.6712 - val_acc: 0.5821\n",
			"Epoch 25/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6731 - acc: 0.5857 - val_loss: 0.6761 - val_acc: 0.5640\n",
			"Epoch 26/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6719 - acc: 0.5727 - val_loss: 0.6758 - val_acc: 0.5834\n",
			"Epoch 27/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6778 - acc: 0.5844 - val_loss: 0.6749 - val_acc: 0.5653\n",
			"Epoch 28/100\n",
			"2317/2317 [==============================] - 9s 4ms/sample - loss: 0.6756 - acc: 0.5878 - val_loss: 0.6842 - val_acc: 0.5136\n",
			"Epoch 29/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6740 - acc: 0.5839 - val_loss: 0.6748 - val_acc: 0.5770\n",
			"Epoch 30/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6632 - acc: 0.5960 - val_loss: 0.6719 - val_acc: 0.5731\n",
			"Epoch 31/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6678 - acc: 0.5809 - val_loss: 0.6737 - val_acc: 0.5640\n",
			"Epoch 32/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6548 - acc: 0.6012 - val_loss: 0.6644 - val_acc: 0.5860\n",
			"Epoch 33/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6640 - acc: 0.5913 - val_loss: 0.6685 - val_acc: 0.5860\n",
			"Epoch 34/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6637 - acc: 0.5986 - val_loss: 0.6700 - val_acc: 0.5744\n",
			"Epoch 35/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6661 - acc: 0.5831 - val_loss: 0.6703 - val_acc: 0.5783\n",
			"Epoch 36/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6650 - acc: 0.5831 - val_loss: 0.6697 - val_acc: 0.5821\n",
			"Epoch 37/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6541 - acc: 0.6016 - val_loss: 0.6657 - val_acc: 0.5847\n",
			"Epoch 38/100\n",
			"2317/2317 [==============================] - 8s 4ms/sample - loss: 0.6610 - acc: 0.5947 - val_loss: 0.6620 - val_acc: 0.5938\n",
			"Epoch 39/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6528 - acc: 0.6064 - val_loss: 0.6662 - val_acc: 0.5731\n",
			"Epoch 40/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6565 - acc: 0.6098 - val_loss: 0.6634 - val_acc: 0.5847\n",
			"Epoch 41/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6603 - acc: 0.5999 - val_loss: 0.6693 - val_acc: 0.5925\n",
			"Epoch 42/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6578 - acc: 0.6008 - val_loss: 0.6622 - val_acc: 0.5951\n",
			"Epoch 43/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6540 - acc: 0.6133 - val_loss: 0.6595 - val_acc: 0.6080\n",
			"Epoch 44/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6529 - acc: 0.5900 - val_loss: 0.6622 - val_acc: 0.5977\n",
			"Epoch 45/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6539 - acc: 0.5921 - val_loss: 0.6627 - val_acc: 0.5977\n",
			"Epoch 46/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6487 - acc: 0.6120 - val_loss: 0.6676 - val_acc: 0.5899\n",
			"Epoch 47/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6521 - acc: 0.6094 - val_loss: 0.6606 - val_acc: 0.5951\n",
			"Epoch 48/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6463 - acc: 0.6068 - val_loss: 0.6631 - val_acc: 0.5886\n",
			"Epoch 49/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6459 - acc: 0.6094 - val_loss: 0.6683 - val_acc: 0.5692\n",
			"Epoch 50/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6526 - acc: 0.6047 - val_loss: 0.6617 - val_acc: 0.5951\n",
			"Epoch 51/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6443 - acc: 0.6232 - val_loss: 0.6684 - val_acc: 0.5834\n",
			"Epoch 52/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6449 - acc: 0.6029 - val_loss: 0.6597 - val_acc: 0.5977\n",
			"Epoch 53/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6380 - acc: 0.6211 - val_loss: 0.6644 - val_acc: 0.5809\n",
			"Epoch 54/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6393 - acc: 0.6258 - val_loss: 0.6583 - val_acc: 0.6093\n",
			"Epoch 55/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6366 - acc: 0.6120 - val_loss: 0.6625 - val_acc: 0.5938\n",
			"Epoch 56/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6393 - acc: 0.6090 - val_loss: 0.6640 - val_acc: 0.5899\n",
			"Epoch 57/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6384 - acc: 0.6163 - val_loss: 0.6620 - val_acc: 0.5938\n",
			"Epoch 58/100\n",
			"2317/2317 [==============================] - 8s 3ms/sample - loss: 0.6370 - acc: 0.6224 - val_loss: 0.6560 - val_acc: 0.6003\n",
			"Epoch 59/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6385 - acc: 0.6219 - val_loss: 0.6624 - val_acc: 0.5925\n",
			"Epoch 60/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6497 - acc: 0.6098 - val_loss: 0.6639 - val_acc: 0.6106\n",
			"Epoch 61/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6343 - acc: 0.6185 - val_loss: 0.6600 - val_acc: 0.5951\n",
			"Epoch 62/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6443 - acc: 0.6090 - val_loss: 0.6690 - val_acc: 0.5886\n",
			"Epoch 63/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6393 - acc: 0.6107 - val_loss: 0.6579 - val_acc: 0.6028\n",
			"Epoch 64/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6384 - acc: 0.6271 - val_loss: 0.6571 - val_acc: 0.5977\n",
			"Epoch 65/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6331 - acc: 0.6211 - val_loss: 0.6596 - val_acc: 0.5990\n",
			"Epoch 66/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6367 - acc: 0.6094 - val_loss: 0.6706 - val_acc: 0.5731\n",
			"Epoch 67/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6272 - acc: 0.6271 - val_loss: 0.6609 - val_acc: 0.6041\n",
			"Epoch 68/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6357 - acc: 0.6211 - val_loss: 0.6606 - val_acc: 0.6028\n",
			"Epoch 69/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6276 - acc: 0.6319 - val_loss: 0.6651 - val_acc: 0.5718\n",
			"Epoch 70/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6379 - acc: 0.6267 - val_loss: 0.6588 - val_acc: 0.5925\n",
			"Epoch 71/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6280 - acc: 0.6245 - val_loss: 0.6703 - val_acc: 0.5666\n",
			"Epoch 72/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6353 - acc: 0.6262 - val_loss: 0.6588 - val_acc: 0.5847\n",
			"Epoch 73/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6296 - acc: 0.6249 - val_loss: 0.6625 - val_acc: 0.6003\n",
			"Epoch 74/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6312 - acc: 0.6293 - val_loss: 0.6590 - val_acc: 0.5990\n",
			"Epoch 75/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6289 - acc: 0.6241 - val_loss: 0.6646 - val_acc: 0.5977\n",
			"Epoch 76/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6189 - acc: 0.6331 - val_loss: 0.6623 - val_acc: 0.6041\n",
			"Epoch 77/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6122 - acc: 0.6465 - val_loss: 0.6569 - val_acc: 0.5990\n",
			"Epoch 78/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6284 - acc: 0.6301 - val_loss: 0.6629 - val_acc: 0.6080\n",
			"Epoch 79/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6221 - acc: 0.6323 - val_loss: 0.6524 - val_acc: 0.5860\n",
			"Epoch 80/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6228 - acc: 0.6319 - val_loss: 0.6579 - val_acc: 0.6080\n",
			"Epoch 81/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6164 - acc: 0.6431 - val_loss: 0.6552 - val_acc: 0.6003\n",
			"Epoch 82/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6225 - acc: 0.6327 - val_loss: 0.6579 - val_acc: 0.6003\n",
			"Epoch 83/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6196 - acc: 0.6409 - val_loss: 0.6618 - val_acc: 0.6003\n",
			"Epoch 84/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6249 - acc: 0.6331 - val_loss: 0.6564 - val_acc: 0.5964\n",
			"Epoch 85/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6167 - acc: 0.6388 - val_loss: 0.6621 - val_acc: 0.6054\n",
			"Epoch 86/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6125 - acc: 0.6375 - val_loss: 0.6501 - val_acc: 0.6119\n",
			"Epoch 87/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6169 - acc: 0.6323 - val_loss: 0.6527 - val_acc: 0.6171\n",
			"Epoch 88/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6151 - acc: 0.6487 - val_loss: 0.6598 - val_acc: 0.5977\n",
			"Epoch 89/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6139 - acc: 0.6331 - val_loss: 0.6508 - val_acc: 0.5977\n",
			"Epoch 90/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6159 - acc: 0.6521 - val_loss: 0.6537 - val_acc: 0.5964\n",
			"Epoch 91/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6039 - acc: 0.6470 - val_loss: 0.6555 - val_acc: 0.6028\n",
			"Epoch 92/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6119 - acc: 0.6457 - val_loss: 0.6598 - val_acc: 0.5821\n",
			"Epoch 93/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6091 - acc: 0.6431 - val_loss: 0.6602 - val_acc: 0.5925\n",
			"Epoch 94/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6050 - acc: 0.6435 - val_loss: 0.6506 - val_acc: 0.6067\n",
			"Epoch 95/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6121 - acc: 0.6340 - val_loss: 0.6612 - val_acc: 0.5705\n",
			"Epoch 96/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6093 - acc: 0.6500 - val_loss: 0.6574 - val_acc: 0.5977\n",
			"Epoch 97/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6104 - acc: 0.6426 - val_loss: 0.6572 - val_acc: 0.5977\n",
			"Epoch 98/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6089 - acc: 0.6474 - val_loss: 0.6524 - val_acc: 0.6054\n",
			"Epoch 99/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.6025 - acc: 0.6465 - val_loss: 0.6517 - val_acc: 0.5899\n",
			"Epoch 100/100\n",
			"2317/2317 [==============================] - 7s 3ms/sample - loss: 0.5978 - acc: 0.6612 - val_loss: 0.6504 - val_acc: 0.5834\n",
			"[[291 107]\n",
			" [215 160]]\n",
			"Train/Test recall: 0.5291 / 0.4267\n",
			"Train/Test accuracy: 0.6793 / 0.5834\n",
			"Test specificity: 0.7312\n"
			]
			},
			{
			"data": {
			"image/png": 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\n",
			"text/plain": [
			"<Figure size 1080x576 with 3 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"train_pred_class20_under,test_pred_class20_under = CompileAndTrainCNNModel(model20,images_under, labels_under,100,\"model20_under\")"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Rerun models on augmented data (the images are augmented online)"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 22,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": [
			"datagen = preprocessing.image.ImageDataGenerator(\n",
			" featurewise_center=True,\n",
			" featurewise_std_normalization=True,\n",
			" rotation_range=20,\n",
			" width_shift_range=0.2,\n",
			" height_shift_range=0.2,\n",
			" horizontal_flip=True)"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 27,
			"metadata": {},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"Epoch 1/20\n",
			"97/97 [==============================] - 6s 60ms/step - loss: 1.1854 - acc: 0.6214\n",
			"Epoch 2/20\n",
			"97/97 [==============================] - 5s 53ms/step - loss: 0.6673 - acc: 0.6204\n",
			"Epoch 3/20\n",
			"97/97 [==============================] - 5s 55ms/step - loss: 0.6591 - acc: 0.6246\n",
			"Epoch 4/20\n",
			"97/97 [==============================] - 6s 58ms/step - loss: 0.6561 - acc: 0.6246\n",
			"Epoch 5/20\n",
			"97/97 [==============================] - 6s 62ms/step - loss: 0.6565 - acc: 0.6246\n",
			"Epoch 6/20\n",
			"97/97 [==============================] - 6s 63ms/step - loss: 0.6567 - acc: 0.6246\n",
			"Epoch 7/20\n",
			"97/97 [==============================] - 6s 65ms/step - loss: 0.6517 - acc: 0.6246\n",
			"Epoch 8/20\n",
			"97/97 [==============================] - 6s 63ms/step - loss: 0.6516 - acc: 0.6246\n",
			"Epoch 9/20\n",
			"97/97 [==============================] - 6s 63ms/step - loss: 0.6496 - acc: 0.6246\n",
			"Epoch 10/20\n",
			"97/97 [==============================] - 6s 63ms/step - loss: 0.6485 - acc: 0.6246\n",
			"Epoch 11/20\n",
			"97/97 [==============================] - 6s 63ms/step - loss: 0.6495 - acc: 0.6246\n",
			"Epoch 12/20\n",
			"97/97 [==============================] - 6s 62ms/step - loss: 0.6492 - acc: 0.6246\n",
			"Epoch 13/20\n",
			"97/97 [==============================] - 6s 60ms/step - loss: 0.6441 - acc: 0.6246\n",
			"Epoch 14/20\n",
			"97/97 [==============================] - 6s 62ms/step - loss: 0.6473 - acc: 0.6246\n",
			"Epoch 15/20\n",
			"97/97 [==============================] - 7s 69ms/step - loss: 0.6455 - acc: 0.6246\n",
			"Epoch 16/20\n",
			"97/97 [==============================] - 8s 80ms/step - loss: 0.6388 - acc: 0.6262\n",
			"Epoch 17/20\n",
			"97/97 [==============================] - 8s 79ms/step - loss: 0.6467 - acc: 0.6246\n",
			"Epoch 18/20\n",
			"97/97 [==============================] - 7s 68ms/step - loss: 0.6449 - acc: 0.6246\n",
			"Epoch 19/20\n",
			"97/97 [==============================] - 6s 62ms/step - loss: 0.6417 - acc: 0.6240\n",
			"Epoch 20/20\n",
			"97/97 [==============================] - 6s 62ms/step - loss: 0.6394 - acc: 0.6237\n"
			]
			},
			{
			"data": {
			"text/plain": [
			"<tensorflow.python.keras.callbacks.History at 0x1a4cf78a58>"
			]
			},
			"execution_count": 27,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"datagen.fit(train_images)\n",
			"\n",
			"# fits the model on batches with real-time data augmentation:\n",
			"model3.fit_generator(datagen.flow(train_images, train_labels, batch_size=32),\n",
			" steps_per_epoch=len(train_images) / 32, epochs=20)"
			]
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"### Regularize 2: Let's try to early stopping."
			]
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"### Visualize what CNNs learn: activations and weights "
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"We need to use the Model class from Keras to be able to produce multiple outputs and in particular return the activations at each layer of the model. "
			]
			},
			{
			"cell_type": "code",
			"execution_count": 128,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"text/plain": [
			"[<tensorflow.python.keras.layers.convolutional.ZeroPadding2D at 0x1ad1ae2940>,\n",
			" <tensorflow.python.keras.layers.convolutional.Conv2D at 0x1ad1ae2320>,\n",
			" <tensorflow.python.keras.layers.pooling.MaxPooling2D at 0x1ad1b172e8>,\n",
			" <tensorflow.python.keras.layers.convolutional.Conv2D at 0x1ad1b173c8>,\n",
			" <tensorflow.python.keras.layers.pooling.MaxPooling2D at 0x1ad1b17b00>,\n",
			" <tensorflow.python.keras.layers.convolutional.Conv2D at 0x1ad1b17630>,\n",
			" <tensorflow.python.keras.layers.core.Flatten at 0x1acc390c50>,\n",
			" <tensorflow.python.keras.layers.core.Dense at 0x1acc390fd0>,\n",
			" <tensorflow.python.keras.layers.core.Dense at 0x1acc3c7a58>]"
			]
			},
			"execution_count": 128,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"# example: the model3 we trained. It has 9 layers, including the first ZeroPadding layer. \n",
			"model3.layers"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 129,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": [
			"# Extracts the outputs of the layers\n",
			"layer_outputs = [layer.output for layer in model3.layers[:]]\n",
			"\n",
			"# Creates a model that will return these outputs, given the model input\n",
			"activation_model = models.Model(inputs=model3.input, outputs=layer_outputs)"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"When fed an image input, this model returns the values of the layer activations in the original model. Let's consider an example image and run this! model3 has been trained on images_under so lets recreate the test/train samples. \n"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 151,
			"metadata": {},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"_________________________________________________________________\n",
			"Layer (type) Output Shape Param # \n",
			"=================================================================\n",
			"zero_padding2d_22 (ZeroPaddi (None, 32, 32, 3) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_89 (Conv2D) (None, 32, 32, 32) 896 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_47 (MaxPooling (None, 16, 16, 32) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_90 (Conv2D) (None, 16, 16, 64) 18496 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_48 (MaxPooling (None, 8, 8, 64) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_91 (Conv2D) (None, 8, 8, 64) 36928 \n",
			"_________________________________________________________________\n",
			"flatten_22 (Flatten) (None, 4096) 0 \n",
			"_________________________________________________________________\n",
			"dense_44 (Dense) (None, 64) 262208 \n",
			"_________________________________________________________________\n",
			"dense_45 (Dense) (None, 2) 130 \n",
			"=================================================================\n",
			"Total params: 318,658\n",
			"Trainable params: 318,658\n",
			"Non-trainable params: 0\n",
			"_________________________________________________________________\n"
			]
			}
			],
			"source": [
			"model3.summary()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 132,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": [
			"seed = 12\n",
			"# keep 25% for testing\n",
			"test_size = 0.25\n",
			"train_images_under, test_images_under, train_labels_under, test_labels_under = train_test_split(images_under, labels_under, test_size=test_size, random_state=seed)"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 303,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"text/plain": [
			"1.0"
			]
			},
			"execution_count": 303,
			"metadata": {},
			"output_type": "execute_result"
			},
			{
			"data": {
			"image/png": 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\n",
			"text/plain": [
			"<Figure size 720x720 with 1 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"plt.figure(figsize=(10,10))\n",
			"# example image\n",
			"ind = 190\n",
			"plt.imshow(test_images_under[ind])\n",
			"test_labels_under[ind]"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Be careful: we need the tensor, not the image: "
			]
			},
			{
			"cell_type": "code",
			"execution_count": 304,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"text/plain": [
			"9"
			]
			},
			"execution_count": 304,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"img_tensor = np.expand_dims(test_images_under[ind], axis=0)\n",
			"\n",
			"# Returns a list of nine Numpy arrays: one array per layer activation\n",
			"activations = activation_model.predict(img_tensor) \n",
			"\n",
			"len(activations)"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Then we have the activations for each layer. In each layers the activation tensor has as many channels as there are filters. "
			]
			},
			{
			"cell_type": "code",
			"execution_count": 305,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": [
			"plt.rcParams['figure.figsize'] = (25, 15)"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 306,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"text/plain": [
			"(1, 8, 8, 64)"
			]
			},
			"execution_count": 306,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"activations[4].shape"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 307,
			"metadata": {
			"scrolled": false
			},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"ORIGINAL IMAGE\n"
			]
			},
			{
			"data": {
			"image/png": 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\n",
			"text/plain": [
			"<Figure size 1800x1080 with 3 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"ZERO PADDING\n"
			]
			},
			{
			"data": {
			"image/png": 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\n",
			"text/plain": [
			"<Figure size 1800x1080 with 3 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"CONV1\n"
			]
			},
			{
			"data": {
			"image/png": 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			"text/plain": [
			"<Figure size 1800x1080 with 32 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"POOL1\n"
			]
			},
			{
			"data": {
			"image/png": 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\n",
			"text/plain": [
			"<Figure size 1800x1080 with 32 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"CONV2\n"
			]
			},
			{
			"data": {
			"image/png": 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02z99Q8liNgD01Bnv/LNBt7DqObMWAAAAAKAGDGsBAAAAAGrAsBYAAAAAoAYMawEAAAAAasCwFgAAAACgBkYH3QCkrHG0Fa/9e/sG3cbQGPnv/q2AHsmyWDhpvFDyJogUbHjomfIHJic7Su0jR3rczeDc8+TXO2o7TnvDADrhpUw15uPOrf+hUDtlpDOvERHn/tHf7agtPra+dNusVVLMy3vIR0qe3y7ZsKzWTdalXtZDl1OmJn7cuZNX3/LF0m3nd2wrFr79ze69ATBUnFkLAAAAAFADhrUAAAAAADVgWAsAAAAAUAO1vFxbs9mMvJHHzJaHBt1KcvJGO5rN5qDbWBXkuHfkuH/kuHfkuH+azWbkeR5Pzfx+8YEti4NpKCFy3D9dj8dzj5Q/4S+VXGwz73IBzwRsv7zzWp/NJX7vkuP+ee54HHHpFVOFetbleq/54h0dtUa728ZL76P09Wrw32OhpIeZbt+rTrhGbd6ej2ZzoQddcSLvj3vH8bi/ZLk38sZyLnherpbD2kajEe1ox9RJ5Rea5+VrNpvRaDihuh/kuHfkuH/kuHfkuH8ajUa02+2Ympo44ZET77Ncctw/jsfLN3Xy0raT4/557ngckTWmXnrjiFg/1uOGhsHapX2vajYX5LhPHI97x/G4v2S5N6rIcZbnCX/EDgAAAAAwJHxkAQAAAABQA4a1AAAAAAA1YFgLAAAAAFADhrUAAAAAADVgWAsAAAAAUAOGtQAAAAAANWBYCwAAAABQA4a1AAAAAAA1YFgLAAAAAFADhrUAAAAAADVQ62HtXXfdFZdffnm8/vWvj0svvTQ+97nPDbqlFXnkkUfivPPOi6effrpQf+CBB+LKK6+M888/Py666KLYu3fvgDqkF+SYFMgxKZBjUiDHpECOSYEckwI5rqfaDmunp6fjxhtvjAsuuCA+9alPxfbt2+PDH/5w3H333YNu7WXZv39/XHPNNbG4uFio79u3L6699trYsmVL7N69O6644orYtWtX7NmzZ0CdUiU5luMUyLEcp0CO5TgFcizHKZBjOU6BHMtxCuS4xjnOK3TnnXfml112Wf5Lv/RL+dvf/vb8s5/97Mve18UXX5zfcMMNhdr73ve+/O1vf/tK2+yrhYWF/NOf/nT+xje+Md++fXt+9tln50899dTzj1999dX5O9/5zsJzdu3alW/bti2fm5vrd7vkclxGjoePHHeS4+Ejx53kePjIcSc5Hj5y3EmOh48cd5Lj4VRVluW4vjmu7MzaKifyMzMzcfDgwbjkkksK9R07dsT+/ftjZmamqrZ77qtf/WrcfPPN8a53vStuvPHGwmNzc3Px4IMPlv49Dx06FPv27etnq4QcdyPHw0WOy8nxcJHjcnI8XOS4nBwPFzkuJ8fDRY7LyfHwqSrLclzvHGd5nudV7Ohtb3tbbN26NW699dbnazfccEM8+uijMT09vax9ve51r4t2ux2Tk5PRaPxsntxqteLo0aOxdu3aGB0draLtnjv+z5tlWSwsLMTs7GxMTU1FlmXRbrfjyJEjHX+fPM+j2WzGxMREjI+PV9pPs9mMRqMRDz/8cKX7TYUcl5Pj4SLH5eR4uMhxOTkeLnJcTo6HixyXk+PhIsfl5Hj4VJXl+++/P37zN38zsiyLqamp5+tyvHJV5LiSf/njE/kPfOADhfqOHTtieno6ZmZmYuPGjUveX7vdjsgjjh461vFYFo2Ybc5FxNxK2x6ILBpx5Nmjhftlf58sGjF/dCHmjy5U+vp5I492tCvdZyrkeOnkuL7keOnkuL7keOl6leOsUf7LV3m7mFk57k6Ol87xuL56kuOIOHp0vlgfyyLGx+NoqxXRaj1fnxzrzHTWZd/d6r2W5xGjIxFTkxGRH448f66XqcmIiKORnxCt5+qzkbdnO/Y1l4901LKs/Nyq+dmxjkbabTku43i8dI7H9VZllg8fPhwREXk7j+YzRwqPyfHK5I08Wu3WS2/4IioZ1u7fvz8iIjZv3lyob9q0KSIiDhw4sKyD35o1a2LuyHxs3L+1ivZ4gZktD8XUSZODbqOW5Hh4yHF3cjw85Lg7OR68kVNPLa23fvCDwn057k6Oh4ccd9eTHM+14vRTdhbqj+1cU7r971+xu6N26sh8yZYR67OlX+FvIToHoOuyzkFpq2S7bka6jIsXTpzWdnn9iIhP/Xh7R+3VY8+Ubrvn5t8o3G9+8d/G1LqJl2pzVXI8Hh6Oxy+uyiw/fzZquyHLFZvZ8tCK91HJNWuPT+RfeOp0RMTk5HP/yZrN5rL2l2WD+lyU1UyOSYEckwI5JgVyTArkmBTIMamoMsvr16+vrjEqV8mw9oXXhyirN7r8Kl3Xppa5PVRBjkmBHJMCOSYFckwK5JgUyDGpqDLLJ56dS71UcpQ5PpE/cYp/5MiRwuNLbsrBjwGQY1Igx6RAjkmBHJMCOSYFckwqqszypk2bnCVeY5Vcs/b4RP7gwYNxzjnnPF9/4oknCo9DnfUix+3JkXjiD3+pUJv8wlTptmWX3xqd7XKdrJJy1i7ftmxNgsZiZzFbxvWv827vT0qO9e2R8m8A372s8wX/0n8rPySd9B+/vNTWVj3HY1Igx4N34rVpWT45JgW9yHGWR4z+qLiYzWvf+z9Lt/3f3tt5DdfV5siVf620PrJ26dfTXe0cj0lF1VmemJiIucXy64AzWJV8JLRp06Y4/fTT4+677y7U77333jjzzDPjtNNOq+JloKfkmBTIMSmQY1Igx6RAjkmBHJOKqrM8NjZWZXtUqJIzayMirr/++rjppptiw4YNceGFF8Z9990X09PTceutt1b1EtBzckwK5JgUyDEpkGNSIMekQI5JhSyvDpUNa9/xjnfE/Px87N27N+64447YuHFjfPzjH4/LLrusqpeAnpNjUiDHpECOSYEckwI5JgVyTCpkeXWobFgbEbFz587YuXNnlbuEvpNjUiDHpECOSYEckwI5JgVyTCpkOX2WMQQAAAAAqIFKz6wFik4anY+v/NrvFWqX/dMrS7ed/4UNHbXx7zVLt81HOz9nyRbb5U1kWWdtrmTFx7LtIiIaJZ/pjHT5nCcvWZW2y35/cs4pHbXFv/3D0m2PzP9qsfBn3yx/fXpiakMr7nny64Xa5s//o9JtN/9hZ23s3gd70VYt7N/15o7alg99aQCdAMCQWJtH45NHCqW5xTNKNx29+GA/Oqq1yf/nT5a03aEtixHrJnrcDQD94MxaAAAAAIAaMKwFAAAAAKgBw1oAAAAAgBowrAUAAAAAqAELjEEPtfKIb8zPFmt/8XjptiN/UfL8xkjpttlISX18rLyJsgXCyvbZ7fll2iULiUVE++jRzv2Olh9mzvy9zm2/c7R8cYlTHy4uPPaTLq9PbzSPTsRfuf7qQu3szy5tsYvUWUwMAJZncmQh7jp7ulD7jW+9vXTbuX40BAA148xaAAAAAIAaMKwFAAAAAKgBw1oAAAAAgBowrAUAAAAAqAHDWgAAAACAGihfph2oxHw+Grf/4MITqrNL30G7VVrOS+r5wvzS99tH+Vz5Or7tI0c6aq/+/zaUbpsdOmHbNfmK+2IZFhZj3Wf/ZNBdAAAJWMizuPvoeKF2wc89XrrtfTHZj5YAoFacWQsAAAAAUAOGtQAAAAAANWBYCwAAAABQA4a1AAAAAAA1YIEx6KE8IhbaI4NuY3i0u9SzrK9tAADQO/N58f3xQu79MgAc58xaAAAAAIAaMKwFAAAAAKgBw1oAAAAAgBowrAUAAAAAqAHDWgAAAACAGhgddAOQsiwiJhqLg26jlrKx8c5anpdum0+M9bodAAD6ZCRrF+4/u7i2y5bl7w0BIGXOrAUAAAAAqAHDWgAAAACAGjCsBQAAAACoAcNaAAAAAIAasMAY8OIaI521dmvFu81GSj4rarc7axERIyf00M5W/PoAAPRfFhGT2Xyh1n1B3pL3oQCQOGfWAgAAAADUgGEtAAAAAEANGNYCAAAAANSAYS0AAAAAQA1YYAx6qJ1H/HB+8oTq3EB6eaHG+vUdtfbhw6Xbjmw4qaPW+slPVtxDNj7eUcsbPj8CAEhbHo0sL1Semt3QZdtm79sBgJoxGQEAAAAAqAHDWgAAAACAGjCsBQAAAACoAcNaAAAAAIAaMKwFAAAAAKiB0UE3APTfgRt/qaN21r95onTbxe98tzdNjI91lFprO2sREaNHZk+o5KXbAQBQb3lk8YPF9YNuY0n+yf6vl9Y/tuUNfe4EgNXEmbUAAAAAADWw7GHtI488Euedd148/fTThfoDDzwQV155ZZx//vlx0UUXxd69eytrEqomx6RAjkmBHJMCOSYFckwK5JhUyPLqtqxh7f79++Oaa66JxcXFQn3fvn1x7bXXxpYtW2L37t1xxRVXxK5du2LPnj2VNgtVkGNSIMekQI5JgRyTAjkmBXJMKmSZJV2zdnFxMT7zmc/ELbfcEmNjndeU/OQnPxnnnntufOITn4iIiLe+9a2xuLgYt99+e1x11VUxPj5ebdfwMsgxKZBjUiDHpECOSYEckwI5JhWyzHFLOrP2q1/9atx8883xrne9K2688cbCY3Nzc/Hggw/GJZdcUqjv2LEjDh06FPv27auuW1iBQeQ4yyLWjiwUbnWQ5Z23b73njNLb9377LR23xuRk6W1ZFhc7blmel9/mFwq31by+mOMxKZBjUiDHpGAg748j4udHmoXbj+YmS2+D9oc/+tXSG/XieEwqZJnjljSsPeuss+ILX/hCvOc974mRkZHCYzMzM7GwsBCbN28u1Ddt2hQREQcOHKioVVgZOSYFckwK5JgUyDEpkGNSIMekQpY5bkmXQTjllFO6Pnb48OGIiJiamirUJ396ll2z2Xy5vUGl5JgUyDEpkGNSIMekQI5JgRyTClnmuGUtMFYmz5/7feQsy8pfoLHil4Cek2NSIMekQI5JgRyTAjkmBXJMKmR5dVnxV3P9+vUR0TnFP37/+ONQZ3JMCuSYFMgxKZBjUiDHpECOSYUsry4rHtaeccYZMTIyEgcPHizUj98/8XoaUEdyTArkmBTIMSmQY1Igx6RAjkmFLK8uS7pm7YuZmJiIbdu2xb333htXX33186dk33PPPbF+/frYunXripuEXlttOT7jo19c0fPbFfTQeubZjlq20CrfeG6+eH+sggYStNpyTJrkmBTIMSnoZY7n8+LCOetG50u3O/ayX6Ea3/qVuQF3wEo5HpMKWV5dKrmoxXXXXRf79u2L97///XH//ffHbbfdFnv27Ilrrrkm1q5dW8VLQM/JMSmQY1Igx6RAjkmBHJMCOSYVsrx6VDKsffOb3xy7d++Oxx9/PK6//vq4884740Mf+lC8+93vrmL30BdyTArkmBTIMSmQY1Igx6RAjkmFLK8eWX58Sbka2bZtWzSfORIb9zuNu2ozWx6KqZMn48EHHxx0K8nbtm1bHG0djV/5128q1J980+EBdVR/2S+fV1of+e4PC/e/PfXfY/KktXLcB47HveN43D9y3Dty3D9y3Dty3D/btm2Lxfbh+L/+qHgZhH/3vV8r3f5HF/ykH20lQY77x/G4d+S4v2S5N2a2PBQREd987JGXvY9KzqwFAAAAAGBlVrzAGNBdFnmcMt4s1J4cUC8v208vXF5QwQn52cTEivcBAMBwmW2Pxu889tcKtX/6mv+3dNtb43X9aAkAasWZtQAAAAAANWBYCwAAAABQA4a1AAAAAAA1YFgLAAAAAFADhrUAAAAAADUwOugGIGVZREyNzJ1QHS/fdqyz3vi5k8t3vLjY+fw1a5be2PhYZ63dLt00L9u2i2x+oWS/eem2rVdu6KjNnbqudNvvXXpWsaf/fP+SewIAoD7arUY8+diphdpHWr9Ruu0r4lv9aAkAasWZtQAAAAAANWBYCwAAAABQA4a1AAAAAAA1YFgLAAAAAFADFhiDHlo8NhIPvPdXC7VGfK1023xhvqPW+t73e9JXLcx8p6NUvvRaxJrNby7cP1a+ZhkAPXbPk18v3N9+eTagToBhNTLXjl/8ZweKxVNeUbptqw/9AKxm+ZrROPjRtxRqj/zm75Zu+5d/57qO2qm3f6knfa12zqwFAAAAAKgBw1oAAAAAgBowrAUAAAAAqAFPx3s/AAAgAElEQVTDWgAAAACAGjCsBQAAAACogdFBNwBJW2xF4/6vDbqLoXfqvyquMDmzZTFi7cSAugFYvXb8whsL95ub/yymTh5QM8BQytvtaH3v+8XiifcB6IvGQh6b/uP3CrVzF3+rdNuNt3+xHy3V2sirXlla7/i+tkLOrAUAAAAAqAHDWgAAAACAGjCsBQAAAACogVpes7bZbEbeyGNmy0ODbiU5eaMdzWZz0G2sCnLcO3LcP3LcO3LcP3LcO3LcP3LcO3LcP3LcO3LcP3LcO3LcX81mM/LI44n8rkI9/89Z6fYzWxb70VatZY3yc17zyfbP/txol26zHLUc1jYajWhHO6ZOmhx0K8lpNpvR6BIuqiXHvSPH/SPHvSPH/SPHvSPH/SPHvSPH/SPHvSPH/SPHvSPH/dVoNKLdbsfk1JqlPWGNRb6XooocZ3me5xX1AwAAAADAy+QjCwAAAACAGjCsBQAAAACoAcNaAAAAAIAaMKwFAAAAAKgBw1oAAAAAgBowrAUAAAAAqAHDWgAAAACAGjCsBQAAAACoAcNaAAAAAIAaMKwFAAAAAKgBw1oAAAAAgBqo9bD2rrvuissvvzxe//rXx6WXXhqf+9znBt3SijzyyCNx3nnnxdNPP12oP/DAA3HllVfG+eefHxdddFHs3bt3QB3SC3JMCuSYFMgxKZBjUiDHpECOSYEc11Olw9oqv8jT09Nx4403xgUXXBCf+tSnYvv27fHhD3847r777go77p/9+/fHNddcE4uLi4X6vn374tprr40tW7bE7t2744orrohdu3bFnj17BtQpctydHA8POe5OjoeHHHcnx8NDjruT4+Ehx93J8fCQ4+7keLhUlWU5rnGO84p8/vOfz88555z8Yx/7WP7Hf/zH+Uc+8pH87LPPzqenp1/W/i6++OL8hhtuKNTe97735W9/+9uraLdvFhYW8k9/+tP5G9/4xnz79u352WefnT/11FPPP3711Vfn73znOwvP2bVrV75t27Z8bm6u3+2uenJcTo6HixyXk+PhIsfl5Hi4yHE5OR4uclxOjoeLHJeT4+FTZZbluL45zvI8z6sY+r7tbW+LrVu3xq233vp87YYbbohHH300pqenl7Wv173uddFut2PNmjUxNjb2fH1hYSFmZ2djcnIyGo1aX8Hhea1WK44ePRrj4+PRaDRidnY2pqamIsuyiIg4fPhwTExMxPj4eMdz1q1bFyMjI5X202w2o9FoxMMPP1zpflMhx+XkeLjIcTk5Hi5yXE6Oh4scl5Pj4SLH5eR4uMhxOTkePlVleWZmJi6++OLIsiympqaer8vxylWR49EqGpmZmYmDBw/GBz7wgUJ9x44dMT09HTMzM7Fx48Yl7y/P84g8Yu7IfMzFfOGxLBpx9NCxKtrumywasXBs8fk/H3n2aOGx+aMLMX90oeM5xw7PVt5L3sijHe3K95sCOX5xcjwc5PjFyfFw6FeO84nRiNHxODJX/JqvXzPXsY9WJR9tL03WpZ7/9MF1kxERz/W4bjKinR/+6YPHH5uNVvsFmX3+OUeitcTIzR4uf4uYjxbfzOZ5Hu22HJdxPH5xjsfDoWc5ProQc7HwwgfkeIXkuDvH4xcnx8Ojyizv378/IiLydh7NZ44UHpPjlckbebTarRXto5Jh7fEv8ubNmwv1TZs2RUTEgQMHlnXwm5iYiLkj87Fx/9Yq2uMFZrY8FFMnTQ66jVqS4+Ehx93J8fCQ4+76leMfXPvm0u2/8pF/1VH78/nyN6wLeecZB42sfLI7Ep31RkltpMvzW3nnGLfddbTb6Uhe/ravrK///fy/Ur6Pt/5i4f4PvvUfYmpyYsk9rCaOx8PD8bi7nuT46EKc8Z2/XKjnc50fkrE8ctyd4/HwkOMXV2WWDx8+HBERWbshyxWb2fLQivdRyTnNx7/ILzx1OiJicvK5/2TNZrOKl4GekmNSIMekQI5JgRyTAjkmBXJMKqrMckVXRKVHKhnWHv8iH78exIn15V7n4sT9QD/IMSmQY1Igx6RAjkmBHJMCOSYVVWZ5/fr11TVG5SoZ1h7/Ip84xT9y5Ejh8SU3NSQXMSYtckwK5JgUyDEpkGNSIMekQI5JRZVZPvFSCtRLJdesPf5FPnjwYJxzzjnP15944onC40vl4McgyDEpkGNS0K8cn3r7l0rrO25/w7L2n6ZDpdU1d32lWNiyGBGuWVvG8ZgU9CLH+fhIfO8f/nKhfurXjpRun33pfy5r/6vJd256S+F+/l++OaBO6q8XOZ7a0Ip7nvx6ob7jNO8f6K0qs7xp0yZniddYJe/6Nm3aFKeffnrcfffdhfq9994bZ555Zpx22mlVvAz0lByTAjkmBXJMCuSYFMgxKZBjUlF1licmfOBeV5WcWRsRcf3118dNN90UGzZsiAsvvDDuu+++mJ6ejltvvbWql4Cek2NSIMekQI5JgRyTAjkmBXJMKqrM8tjYWMzFfA+6ZKUqG9a+4x3viPn5+di7d2/ccccdsXHjxvj4xz8el112WVUvAT0nx6RAjkmBHJMCOSYFckwK5JhUyPLqUNmwNiJi586dsXPnzip3CX0nx6RAjkmBHJMCOSYFckwK5JhUyHL6rFQAAAAAAFADlZ5ZCwAAAN1k7YjJ77eKtS/9zwF1M7z+/Ld/t3B/+91ZRFgsqF+az47EjtO2DroNIFHOrAUAAAAAqAHDWgAAAACAGjCsBQAAAACoAcNaAAAAAIAasMAYAABL8v7HHincv+lvtgfUCTC02nlMPd4slPIBtTLMNt/17sL9iYXfi5PGB9QMAJVyZi0AAAAAQA0Y1gIAAAAA1IBhLQAAAABADRjWAgAAAADUgGEtAAAAAEANjA66AQCAQXj6/W8preclH2W/+pYv9rib4XDd/VcV7k8sfjrGrD4OLEcW0V4zemKJ5Wr5VwNIlTNrAQAAAABqwLAWAAAAAKAGDGsBAAAAAGrAsBYAAAAAoAYsMAYArErtsUF3MISsZwNUIB8pHkwcWpYvWzzhXy0fTB8AVM+ZtQAAAAAANWBYCwAAAABQA4a1AAAAAAA1YFgLAAAAAFADhrUAAAAAADUwOugGAAAGoTFXXl9c198+hsnIROuEiuXHgeXL2o4dK5VPtIuFbDB9AFA9Z9YCAAAAANSAYS0AAAAAQA0Y1gIAAAAA1IBhLQAAAABADVhgDABYlfKRLg9YpAWgtzIH2hWzRhtAspxZCwAAAABQA4a1AAAAAAA1YFgLAAAAAFADhrUAAAAAADVggTEAYFVqTXR5wKItXeX+bYAKtMeL5wx1W++RF+G0K4BkOcQDAAAAANSAYS0AAAAAQA0Y1gIAAAAA1IBhLQAAAABADRjWAgAAAADUwOigGwAAGITRY+X1kbm8v40s0bN/500dtQ2//+W+9pA1Tvi3yfr68gAc13IABkiVM2sBAAAAAGpg2cPaRx55JM4777x4+umnC/UHHnggrrzyyjj//PPjoosuir1791bWJFRNjkmBHJMCOSYFckwK5JgUyDGpkOXVbVnD2v3798c111wTi4uLhfq+ffvi2muvjS1btsTu3bvjiiuuiF27dsWePXsqbRaqIMekQI5JgRyTAjkmBXJMCuSYVMgyS7pm7eLiYnzmM5+JW265JcbGxjoe/+QnPxnnnntufOITn4iIiLe+9a2xuLgYt99+e1x11VUxPj5ebdfwMsgxKZBjUiDHpECOSYEckwI5JhWyzHFLOrP2q1/9atx8883xrne9K2688cbCY3Nzc/Hggw/GJZdcUqjv2LEjDh06FPv27auuW1gBOSYFckwK6p7jrN15q4MNjx/tuPVb69ho4Rb56l3gpu45hqUYTI6zyBvFG8uXtbLCLeq5NmZfOB6TClnmuCUNa88666z4whe+EO95z3tiZGSk8NjMzEwsLCzE5s2bC/VNmzZFRMSBAwcqahVWRo5JgRyTAjkmBXJMCuSYFMgxqZBljlvSZRBOOeWUro8dPnw4IiKmpqYK9cnJyYiIaDabL7c3qJQckwI5JgVyTArkmBTIMSmQY1Ihyxy3rAXGyuT5c79vkWXlv77SaKz4JaDn5JgUyDEpkGNSIMekQI5JgRyTClleXVb81Vy/fn1EdE7xj98//jjUmRyTAjkmBXJMCuSYFMgxKZBjUiHLq8uKh7VnnHFGjIyMxMGDBwv14/dPvJ4G1JEckwI5JgVyTArkmBTIMSmQY1Ihy6vLioe1ExMTsW3btrj33nufPy07IuKee+6J9evXx9atW1f6EtBzckwK5JgU9DPH+Uj5LWt33mrhy9/ovPVZNjtSuK3m1cdfjOMxKehZjrOI9mhWuLF82UJWuFHO8ZhUyPLqUslFLa677rrYt29fvP/974/7778/brvtttizZ09cc801sXbt2ipeAnpOjkmBHJMCOSYFckwK5JgUyDGpkOXVo5Jh7Zvf/ObYvXt3PP7443H99dfHnXfeGR/60Ifi3e9+dxW7h76QY1Igx6RAjkmBHJMCOSYFckwqZHn1yPIXnj9dE9u2bYvmM0di436ncVdtZstDMXXyZDz44IODbiV5ctw7ctw/ctw7ctw/3XL81AffUrr9+KHOt0Y//2++1JPehs23PvWrhfvjv/vv46SJCTnuA8fj3nE87p9t27ZF88hcvOrMv1uoj9/j3365HrvtTYX7Y//m3zke94njce84HveXLPfGzJaHIiLim4898rL3UcmZtQAAAAAArMzooBsAABiEU78+V1pvTfgsu5uf3/STwv1mo3a/oAXPGzl5Q2m99cyzfe6EEy2uGyncHx9QH8Ps1LN/WLj/7IjjMUAq/DQCAAAAAFADhrUAAAAAADVgWAsAAAAAUAOGtQAAAAAANWBYCwAAAABQA6ODbgDgpZzz4Fjh/pP/MBtQJ0BKGovt0vqaP/9OR22x180Mib9+xjcK9/+w0RpQJ/DSPv/w/aX17TddV7if/8k3+9EOP5W181j/F88Uao4ky/ejb5xauD/Syvx0D5AIZ9YCAAAAANSAYS0AAAAAQA0Y1gIAAAAA1IBhLQAAAABADbgEOVB7nzztTwv3tzcsMAasXOP+r5XWLSbW3b+f/vXC/ZHFb8eakQE1Q0REZBMTpfV8bq7PndTPjtPeUFp/RXypcL+5ZTFiXfm/I9XLW61o/fmjg25j6L3ihHXxDlulDSAZzqwFAAAAAKgBw1oAAAAAgBowrAUAAAAAqAHDWgAAAACAGjCsBQAAAACogdFBNwDwUk5czbm55aGYOnlAzQCsYpum5wr3n1zIIyYG1AwREZHPzb30RqvUob/1ptL6Sf/py33uBKr3in/3pcL95pbFiHUOyP2SZVmMnHRSodY6dGhA3QyvH/2jNxfu5w98c0CdQL04sxYAAAAAoAYMawEAAAAAasCwFgAAAACgBmp5zdpmsxl5I4+ZLQ8NupXk5I12NJvNQbexKshx78hx/8hx78hx/8hxhZ58pHA3zxei2VwcUDOrixwvX/618msfPrulmFnH4/6R496R4/5pNpuRZ3k8cWrxusH5KfmAOhpeHdeobc1Hs7kwmGZWIcfk3sgb7RXvo5bD2kajEe1ox9RJk4NuJTnNZjMaDSdU94Mc944c948c944c948c906zuSjHfSLHFTphESbH4/6R496R4/45nuPJqXWDbiU5zeaCHPeRY3JvVHE8zvI89/EPAAAAAMCA+cgCAAAAAKAGDGsBAAAAAGrAsBYAAAAAoAYMawEAAAAAasCwFgAAAACgBgxrAQAAAABqwLAWAAAAAKAGDGsBAAAAAGrAsBYAAAAAoAYMawEAAAAAasCwFgAAAACgBmo9rL3rrrvi8ssvj9e//vVx6aWXxuc+97lBt7QijzzySJx33nnx9NNPF+oPPPBAXHnllXH++efHRRddFHv37h1Qh/SCHJMCOSYFckwK5JgUyDEpkGNSIMf1VOmwtsov8vT0dNx4441xwQUXxKc+9anYvn17fPjDH4677767wo77Z//+/XHNNdfE4uJiob5v37649tprY8uWLbF79+644oorYteuXbFnz54BdYocdyfHw0OOu5Pj4SHH3cnx8JDj7uR4eMhxd3I8POS4OzkeLlVlWY5rnOO8Ip///Ofzc845J//Yxz6W//Ef/3H+kY98JD/77LPz6enpl7W/iy++OL/hhhsKtfe9733529/+9ira7ZuFhYX805/+dP7GN74x3759e3722WfnTz311POPX3311fk73/nOwnN27dqVb9u2LZ+bm+t3u6ueHJeT4+Eix+XkeLjIcTk5Hi5yXE6Oh4scl5Pj4SLH5eR4+FSZZTmub46zPM/zKoa+b3vb22Lr1q1x6623Pl+74YYb4tFHH43p6ell7et1r3tdtNvtWLNmTYyNjT1fX1hYiNnZ2ZicnIxGo9ZXcHheq9WKo0ePxvj4eDQajZidnY2pqanIsiwiIg4fPhwTExMxPj7e8Zx169bFyMhIpf00m81oNBrx8MMPV7rfVMhxOTkeLnJcTo6HixyXk+PhIsfl5Hi4yHE5OR4uclxOjodPVVmemZmJiy++OLIsi6mpqefrcrxyVeR4tIpGZmZm4uDBg/GBD3ygUN+xY0dMT0/HzMxMbNy4ccn7Oz4/nptvx9z83AsfiCwbi6NH54tPWGy97N77IYtGLBxbfP7PR549Wnhs/uhCzB9d6HjOscOzlfeSN/JoR7vy/aagJznOI+aOzMdcFDObRSOOHjpWSd/9IsfDoX85ziKLkTh66MSvbyWf//VMX3Lc5Zt9dsJno3nIcTe9el8x22rHbOtn7yuyVkTWGI+jx4pf81go/upU3TgeD4eevT+ebcXc7M/e+7bHsoix8WjOF7/mU+NzcaJsOX+BHmpkEVOTERHP9Tg1GRH54Th+mHzusdnI27Mdz8njSLRLItco+ct1OyVlLh85Ybs82mU7pSc5ziPiWN6OYy/4OS9r5BFrx+JIez5eeEgZyzp/zlvM6zM8yNaOxkK0I6Id2drRONKaLTw2H62YXzzW8Zxj+XxEybeaPO8Mct4u/5/bOFbcgeNxdz07Hi+0Y27hZznOx/KINWNxpDUf8YLoln4N63JAjoiYGH/uaJy3IybG4/DCfOGx2chjdn6u4zlHWosRrc4gZ1nnwVeOq1Fllvfv3x8REe08j0Nzxa9vo2VeERGRr+kcmWazL/1zQt7Io9Ve2ZyykmHt8S/y5s2bC/VNmzZFRMSBAweWdfCbmJiIufl2vOrMv1uoj86W/2Ub939tOe2uajNbHoqpkyYH3UYt9STHR+Zj4/6t1TVJRMjxi+lXjrPR8m8f+WK9h1z90HjDueX17/24cP/bk/fF5NTafrQ0dHqR49lWO0Z+412F+obHy99XTN3xJ8tpd1VzPO6uJ8fj2VZsWveO4uu88+TS7e+46hMdtZO7nCHTWuEHbWNZ537bXSalCyWvtZzR20KX/b56dKqj9v3WkdJtP/mjNxXu/9erH4k1I3Jcphc5Ppa3Y+63/l6h/qozf1y6/aW/0HlW0pd+tLlky/JB53K0S6Zn7RXuMyKiUTK46uY7P+78/zz/1LrSbV/73uL3Ksfj7npyPF5ox8lv+PuF+pGdz5Zu3/z2ho5ae22XQU4FmeubLjPVta882lFb+HbnMToi4qwbv1y4L8cvrsosHz58+Lk/jI/Hwrv/fuGx19zw5c4nrELf/fBbOmq/8PEvvuTzZrY8tOLXruRjyeNf5BeeOh0RMTn53H+yZrNZxctAT8kxKZBjUiDHpECOSYEckwI5JhVVZrmiK6LSI5UMa49/kY9fD+LE+nKvc3HifqAf5JgUyDEpkGNSIMekQI5JgRyTiiqzvH79+uoao3KVDGuPf5FPnOIfOXKk8PiSmxqSixiTFjkmBXJMCuSYFMgxKZBjUiDHpKLKLJ94KQXqpZJr1h7/Ih88eDDOOeec5+tPPPFE4fGlajQaMbZ2If7mrfcU6rf/2ytKtz/t/mXtHkr1IsdU454nv164v/1yn2Z3068cH/zw9tL6+oOdv05zyhcOlO+87Fdvup2pUHaN3LLr43b7f7ecMyCW8StBi999srPYZZGaxaeeLr7MFosndNOTHI/mMfXW7xfq/+O9f1S6/Wv+xt/vqI39Rfk1A7OFzlo+1lmLiMjKLulc9t+gWwR79Ntqv/Y3Oq/9P9Klicd/pfpFylLVixxn7XZkB75bqL9mb/kCIBf9/Ac6amMndy46FhExOtZ57cSyBWIiIhYWOhdRbLc6a8v57cqsUb5xo9F5nBwZ6dLXwc5rHG7+r+V/30/9h39ZuH93Vn4tRXqT48bRxTj7t75SqI+86pWl23/5Va/vqOXf+OayXnPJvS2x1ktnxExHrf1rb+hzF+npyfuK+cVY/wfF63qu/4MVNpqIpz7YeZ3Pjbe89HU+eWlVZnnTpk2RZVlkxxZdo7aLpVyftlcq+f6zadOmOP300+Puu+8u1O+9994488wz47TTTqviZaCn5JgUyDEpkGNSIMekQI5JgRyTiqqzPDExUWV7VKiSM2sjIq6//vq46aabYsOGDXHhhRfGfffdF9PT03HrrbdW9RLQc3JMCuSYFMgxKZBjUiDHpECOSUWVWR4bG4u5mO9Bl6xUZcPad7zjHTE/Px979+6NO+64IzZu3Bgf//jH47LLLqvqJaDn5JgUyDEpkGNSIMekQI5JgRyTClleHSob1kZE7Ny5M3bu3FnlLqHv5JgUyDEpkGNSIMekQI5JgRyTCllOnxWQAAAAAABqoNIza6u0cGws/vDDlxZqp91pBUFYjXacVlwFt7nloZg6eUDNEBER7/07/6W0/sAzr+2ofSteV7ptVrJUeN7ISrfNSz5azMs2LX966bZZ5yLjERHR6FwUvav1B/9SR23+n/yodNsLTi3u+Km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			"text/plain": [
			"<Figure size 1800x1080 with 64 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"print( \"ORIGINAL IMAGE\")\n",
			"# original image: 3 channels\n",
			"for i in range(3):\n",
			" plt.subplot(1,8,i+1)\n",
			" plt.imshow(img_tensor[0,:,:,i],cmap='viridis')\n",
			"plt.show()\n",
			"\n",
			"print( \"ZERO PADDING\")\n",
			"# first layer activations (Zero padding): 3 channels \n",
			"layer = 0 \n",
			"for i in range(3):\n",
			" plt.subplot(1,8,i+1)\n",
			" plt.imshow(activations[layer][0,:,:,i],cmap='viridis')\n",
			"plt.show()\n",
			"\n",
			"print( \"CONV1\")\n",
			"# SECOND layer activations (CONV1): 32 filters => 32 channels \n",
			"layer = 1\n",
			"for i in range(32):\n",
			" plt.subplot(4,8,i+1)\n",
			" plt.imshow(activations[layer][0,:,:,i],cmap='viridis')\n",
			"plt.show()\n",
			"\n",
			"print( \"POOL1\")\n",
			"# Third layer activations (POOL1): 32 filters => 32 channels \n",
			"layer = 2\n",
			"for i in range(32):\n",
			" plt.subplot(4,8,i+1)\n",
			" plt.imshow(activations[layer][0,:,:,i],cmap='viridis')\n",
			"plt.show()\n",
			"\n",
			"print( \"CONV2\")\n",
			"# Third layer activations (POOL1): 32 filters => 32 channels \n",
			"layer = 3\n",
			"for i in range(64):\n",
			" plt.subplot(8,8,i+1)\n",
			" plt.imshow(activations[layer][0,:,:,i],cmap='viridis')\n",
			"plt.show()\n",
			"\n"
			]
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"### Also a cool idea: use the Conv/Pool Layers as feature extractor for another ML method. \n",
			"\n",
			"The Conv only extract the features from images and dont predict anything. We can therefore use these features to feed them in another beloved algorithm, should we want it to. \n",
			"Only to do is: \n",
			"\n",
			"- remove the last softmax layer \n",
			"- the \"prediction\" of the model will be features (as many as the number of nodes in the last FC layer)\n",
			"- train a linear classifier on these features like linear SVM."
			]
			},
			{
			"cell_type": "code",
			"execution_count": 57,
			"metadata": {
			"scrolled": true
			},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"_________________________________________________________________\n",
			"Layer (type) Output Shape Param # \n",
			"=================================================================\n",
			"zero_padding2d_11 (ZeroPaddi (None, 32, 32, 3) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_34 (Conv2D) (None, 30, 30, 32) 896 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_23 (MaxPooling (None, 15, 15, 32) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_35 (Conv2D) (None, 13, 13, 64) 18496 \n",
			"_________________________________________________________________\n",
			"max_pooling2d_24 (MaxPooling (None, 6, 6, 64) 0 \n",
			"_________________________________________________________________\n",
			"conv2d_36 (Conv2D) (None, 4, 4, 64) 36928 \n",
			"_________________________________________________________________\n",
			"flatten_11 (Flatten) (None, 1024) 0 \n",
			"_________________________________________________________________\n",
			"dense_21 (Dense) (None, 64) 65600 \n",
			"=================================================================\n",
			"Total params: 121,920\n",
			"Trainable params: 121,920\n",
			"Non-trainable params: 0\n",
			"_________________________________________________________________\n"
			]
			}
			],
			"source": [
			"model5 = models.Sequential()\n",
			"# need to add an extra zero padding layer, 4 on each width side, 2 on each height side\n",
			"model5.add(layers.ZeroPadding2D(padding=(4, 2), data_format=None,input_shape=(24, 28, 3)))\n",
			"# 1st conv layer, with 32 filters of size (3,3) \n",
			"model5.add(layers.Conv2D(32, (3, 3), activation='relu'))\n",
			"# 1st pool layer, divinding by 2 the dimension\n",
			"model5.add(layers.MaxPooling2D((2, 2)))\n",
			"# 2nd conv layer, with 64 filters of size (3,3) \n",
			"model5.add(layers.Conv2D(64, (3, 3), activation='relu'))\n",
			"# 2nd pool layer, divinding by 2 the dimension\n",
			"model5.add(layers.MaxPooling2D((2, 2)))\n",
			"# last conv layer, with 64 filters of size (3,3) \n",
			"model5.add(layers.Conv2D(64, (3, 3), activation='relu'))\n",
			"\n",
			"# flaten the images to prepare for the dense layers\n",
			"model5.add(layers.Flatten())\n",
			"model5.add(layers.Dense(64, activation='relu'))\n",
			"# model architecture\n",
			"model5.summary()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 58,
			"metadata": {
			"scrolled": true
			},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"Train on 2317 samples, validate on 773 samples\n",
			"Epoch 1/20\n",
			"2317/2317 [==============================] - 4s 2ms/sample - loss: 0.8629 - acc: 0.4903 - val_loss: 0.6960 - val_acc: 0.5304\n",
			"Epoch 2/20\n",
			"2317/2317 [==============================] - 3s 1ms/sample - loss: 0.6933 - acc: 0.4981 - val_loss: 0.6940 - val_acc: 0.4722\n",
			"Epoch 3/20\n",
			"2317/2317 [==============================] - 3s 1ms/sample - loss: 0.6932 - acc: 0.5140 - val_loss: 0.6959 - val_acc: 0.5213\n",
			"Epoch 4/20\n",
			"2317/2317 [==============================] - 3s 1ms/sample - loss: 0.6928 - acc: 0.4838 - val_loss: 0.6938 - val_acc: 0.4722\n",
			"Epoch 5/20\n",
			"2317/2317 [==============================] - 3s 1ms/sample - loss: 0.6937 - acc: 0.5114 - val_loss: 0.6948 - val_acc: 0.5201\n",
			"Epoch 6/20\n",
			"2317/2317 [==============================] - 3s 1ms/sample - loss: 0.6931 - acc: 0.5002 - val_loss: 0.6980 - val_acc: 0.5149\n",
			"Epoch 7/20\n",
			"2317/2317 [==============================] - 3s 1ms/sample - loss: 0.6933 - acc: 0.4989 - val_loss: 0.6949 - val_acc: 0.5045\n",
			"Epoch 8/20\n",
			"2317/2317 [==============================] - 3s 1ms/sample - loss: 0.6928 - acc: 0.4959 - val_loss: 0.6952 - val_acc: 0.5162\n",
			"Epoch 9/20\n",
			"2317/2317 [==============================] - 3s 1ms/sample - loss: 0.6934 - acc: 0.4881 - val_loss: 0.6931 - val_acc: 0.4825\n",
			"Epoch 10/20\n",
			"2317/2317 [==============================] - 3s 1ms/sample - loss: 0.6930 - acc: 0.4886 - val_loss: 0.6956 - val_acc: 0.5213\n",
			"Epoch 11/20\n",
			"2317/2317 [==============================] - 3s 1ms/sample - loss: 0.6930 - acc: 0.5002 - val_loss: 0.6936 - val_acc: 0.5291\n",
			"Epoch 12/20\n",
			"2317/2317 [==============================] - 3s 1ms/sample - loss: 0.6930 - acc: 0.5002 - val_loss: 0.6934 - val_acc: 0.5408\n",
			"Epoch 13/20\n",
			"2317/2317 [==============================] - 4s 2ms/sample - loss: 0.6936 - acc: 0.4959 - val_loss: 0.6942 - val_acc: 0.5162\n",
			"Epoch 14/20\n",
			"2317/2317 [==============================] - 3s 1ms/sample - loss: 0.6929 - acc: 0.4950 - val_loss: 0.6942 - val_acc: 0.5175\n",
			"Epoch 15/20\n",
			"2317/2317 [==============================] - 4s 2ms/sample - loss: 0.6932 - acc: 0.4994 - val_loss: 0.6942 - val_acc: 0.5201\n",
			"Epoch 16/20\n",
			"2317/2317 [==============================] - 3s 1ms/sample - loss: 0.6930 - acc: 0.5024 - val_loss: 0.6961 - val_acc: 0.5149\n",
			"Epoch 17/20\n",
			"2317/2317 [==============================] - 3s 1ms/sample - loss: 0.6928 - acc: 0.5041 - val_loss: 0.6933 - val_acc: 0.4709\n",
			"Epoch 18/20\n",
			"2317/2317 [==============================] - 4s 2ms/sample - loss: 0.6932 - acc: 0.4981 - val_loss: 0.6951 - val_acc: 0.5213\n",
			"Epoch 19/20\n",
			"2317/2317 [==============================] - 4s 2ms/sample - loss: 0.6933 - acc: 0.5041 - val_loss: 0.6943 - val_acc: 0.5162\n",
			"Epoch 20/20\n",
			"2317/2317 [==============================] - 3s 1ms/sample - loss: 0.6930 - acc: 0.4855 - val_loss: 0.6958 - val_acc: 0.5149\n",
			"[[398 0]\n",
			" [375 0]]\n",
			"Train/Test recall: 0.0000 / 0.0000\n",
			"Train/Test accuracy: 0.4950 / 0.5149\n",
			"Test specificity: 1.0000\n"
			]
			},
			{
			"data": {
			"image/png": 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\n",
			"text/plain": [
			"<Figure size 720x576 with 1 Axes>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"train_lol,test_lol = CompileAndTrainCNNModel(model5,images_under, labels_under,20,\"model1_under_20epochs\")"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"The \"prediction\" is the features, 64 features like the siz of the last FC layer. "
			]
			},
			{
			"cell_type": "code",
			"execution_count": 63,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": [
			"CNN_features = model5.predict(images_under)"
			]
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"### Try to use ONLY the VERY GOOD and VERY BAD images."
			]
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"### Try to train things weekly"
			]
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"### Try with Migros data, labeling ourselves the examples!"
			]
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"### Try representations like circles? "
			]
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"### ALSO: use a pretrained network? VGGNet or ResNet?"
			]
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
			"collapsed": true
			},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"Story:\n",
			"\n",
			"1- We tried with images first, because thats why you showed us. It works \"alrght\" but not great. \n",
			"\n",
			"2- We though of using another method TS with fourier and clustering. We use a simple supermakret stable data to have a proof of concept. --> It works with supermarket data! And localized anomalies as well. \n",
			"\n",
			"3- We try this method with Swisscom: it doesnt works! So it may seem that Swisscom data is a little complex for this method. \n",
			"4- Apply CNNs \n"
			]
			}
			],
			"metadata": {
			"kernelspec": {
			"display_name": "Python (py37)",
			"language": "python",
			"name": "py37"
			},
			"language_info": {
			"codemirror_mode": {
			"name": "ipython",
			"version": 3
			},
			"file_extension": ".py",
			"mimetype": "text/x-python",
			"name": "python",
			"nbconvert_exporter": "python",
			"pygments_lexer": "ipython3",
			"version": "3.7.2"
			}
			},
			"nbformat": 4,
			"nbformat_minor": 1
			}

en_cons_anomalies/Swisscom_withLabels_Training.ipynb1c61f53d4b24master

Swisscom_withLabels_Training.ipynbView Options

en_cons_anomalies/Swisscom_withLabels_Training.ipynb
1c61f53d4b24master

Swisscom_withLabels_Training.ipynb
View Options