{"cells":[{"metadata":{"_uuid":"8c112e74e9585c34c2b24abe4495cca41621eb2e"},"cell_type":"markdown","source":"# Machine Learning Engineer Nano degree Capstone Project\n"},{"metadata":{"_uuid":"6ae915e70cadac33bdcd0aa219a7e7c2292aeac2"},"cell_type":"markdown","source":"One of my primary areas of focus, and in fact the reason I decided to do the Machine Learning nanodegree originally, is Image processing medical image scan . the last part for this course was Deep-Learning and CNN –this part is important part for me. I interesting of medical image on the last a few years the detection of diseases by CNN or NN became more important to make diagnoses easy and  safe more time  . \nCNN use X-ray Dataset of machine learning, computer vision and various other \n"},{"metadata":{"_uuid":"366200fe51f64b013ac50f25db6865a30b46ac5b"},"cell_type":"markdown","source":"******************************************************************************************************"},{"metadata":{"_uuid":"9c12cf1f0eb4a0e7ea3058945f10d1471b361aea"},"cell_type":"markdown","source":"in this Project i have 14 categories for all diseases of the chest using Xray images this is the first\nnormal scan for any place make scanner also first thing the doctors orderd it when he need to check by\nfirst one dignoses \n"},{"metadata":{"_uuid":"f2587ec1b991e27b823a954199655321234fb67c"},"cell_type":"markdown","source":"I tray for this project to segmentation the diseases and make analsyses on it alse learn the machine \nhow to recognice the diseases by NN and Cnn by vgg16-network Model technics"},{"metadata":{"_uuid":"beaac03ebafef3a004a05bb8632bd24b19ce8b43"},"cell_type":"markdown","source":"*****************************************************************************************************"},{"metadata":{"_uuid":"e9109f92c8cb203c068d857917e2d717bc6b6ab3"},"cell_type":"markdown","source":"import libraries"},{"metadata":{"trusted":false,"_uuid":"8b3306e872337b8c7eaeaad698799c9fabae1a0a"},"cell_type":"code","source":"import pandas as pd\nimport numpy as np\nimport os\nfrom glob import glob\nimport random\nimport matplotlib.pylab as plt\nimport cv2\nimport matplotlib.gridspec as gridspec\nimport seaborn as sns\nimport zlib\nimport itertools\nimport sklearn\nfrom sklearn import model_selection\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.model_selection import learning_curve\nfrom sklearn.model_selection import KFold\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.model_selection import StratifiedKFold\nfrom sklearn.utils import class_weight\nfrom sklearn.metrics import confusion_matrix\nimport keras\nfrom keras.models import Sequential\nfrom keras.optimizers import SGD, RMSprop, Adam, Adagrad, Adadelta\nfrom keras.layers import Dense, Activation, Dropout\nfrom keras.utils.np_utils import to_categorical\nfrom keras.models import Sequential\nfrom keras.layers import Activation,Dense, Dropout, Flatten, Conv2D, MaxPool2D,MaxPooling2D,AveragePooling2D, BatchNormalization\nfrom keras.optimizers import RMSprop\nfrom keras.preprocessing.image import ImageDataGenerator\nfrom keras.callbacks import ReduceLROnPlateau, ModelCheckpoint\nfrom keras.models import model_from_json\nfrom keras import backend as K\nfrom keras.layers import Conv2D, MaxPooling2D\nfrom keras.applications.mobilenet import MobileNet","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"c84fc51c7b780bafb1bc16bda07a84a096104cac"},"cell_type":"markdown","source":"read the path of the images"},{"metadata":{"trusted":false,"_uuid":"0e920be478d49e0442a2b43449472004d99a6a2e"},"cell_type":"code","source":"PATH = os.path.abspath(os.path.join( 'sample','images'))\n\n#PATH = os.path.abspath(os.path.join('sample/images'))#read the path of the images\n#SOURCE_IMAGES = os.path.join(PATH,'sample', 'images')\n","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"5d8ab4db43e7f1c5ad82a9dcfc585c46d6ba089b"},"cell_type":"markdown","source":"Show the pathes of images"},{"metadata":{"trusted":false,"_uuid":"5ffa98aa45c02fbf44a9ae16489f3d3d41ffe966"},"cell_type":"code","source":"images=glob(os.path.join(PATH,'*.png'))\n\nprint(images[0:5])#print first 5 images","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"984d85a2981723d8a481ad75e566bb7dd37672b5"},"cell_type":"markdown","source":"view the csv file"},{"metadata":{"trusted":false,"_uuid":"1c8b3b2afa932002d7c3a2e97a5211bfc0ca4e74"},"cell_type":"code","source":"labels = pd.read_csv('sample_labels.csv')\nlabels.head(10)\n","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"bcd58f860ea8575b8c96a46c6bda3484f10b212b"},"cell_type":"markdown","source":"view sample of deaseses xray image"},{"metadata":{"trusted":false,"_uuid":"d77945b9dc300d09fe04ccfa6bca14860a3bd8b7"},"cell_type":"code","source":"multipleImages = glob('sample/images/**')\ni_ = 0\nplt.rcParams['figure.figsize'] = (10.0, 10.0)#command can be used to modify multiple settings in a single group at once \nplt.subplots_adjust(wspace=0, hspace=0)#width+hight   5*5\nfor l in multipleImages[:25]:\n    im = cv2.imread(l)          \n    im = cv2.resize(im, (128, 128)) #the size of h+w of the image \n    plt.subplot(5, 5, i_+1) #.set_title(l)\n    plt.imshow(cv2.cvtColor(im, cv2.COLOR_BGR2RGB)); plt.axis('off')\n    i_ += 1","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"6856afba685d03538b74eff2eceea574051cb2fe"},"cell_type":"markdown","source":"*******************************************************\n*******************************************************"},{"metadata":{"_uuid":"6d329c9f9eaff393f55a7e27393f7ea0309a6b71"},"cell_type":"markdown","source":"Another Way to Read and Import the Data"},{"metadata":{"_uuid":"705d4fa522288e63290f95fe8d41a5ad8d2fcb12"},"cell_type":"markdown","source":"****************************************"},{"metadata":{"_uuid":"773ce9f742e25f749914847ae35a29c0c1a7249e"},"cell_type":"markdown","source":"import libraries"},{"metadata":{"trusted":false,"_uuid":"99ef60491f2b3388aa0d38912a1d56222f91f016"},"cell_type":"code","source":"from sklearn.datasets import load_files       \nfrom keras.utils import np_utils\nimport numpy as np\nfrom glob import glob","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"57054ddc69d81b6bead54436fb4b603a24d64534"},"cell_type":"markdown","source":"i try to separate the image and rarange it like cnn project number 6"},{"metadata":{"trusted":false,"_uuid":"f2c7515eab4f17cece0a77ab3a5ad0a23c7a6f1d"},"cell_type":"code","source":"# define function to load train, test, and validation datasets\ndef load_dataset(path):\n    data = load_files(path)\n    Xray_files = np.array(data['filenames'])\n    xray_targets = np_utils.to_categorical(np.array(data['target']), 133)\n    return Xray_files, xray_targets\n\n# load train, test, and validation datasets\ntrain_files, train_targets = load_dataset('sample/images/train')\nvalid_files, valid_targets = load_dataset('sample/images/valid')\ntest_files, test_targets = load_dataset('sample/images/test')\n\n# load list of xray names\nxray_names = [item[20:-1] for item in sorted(glob(\"sample/images/train/*/\"))]\n\n# print statistics about the dataset\nprint('There are %d total Xray categories.' % len(xray_names))\nprint('There are %s total xray images.\\n' % len(np.hstack([train_files, valid_files, test_files])))\nprint('There are %d training xray images.' % len(train_files))\nprint('There are %d validation xray images.' % len(valid_files))\nprint('There are %d test xray images.'% len(test_files))","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"2de67ad0a415b069dc8e96b294e95c8a2c8f4854"},"cell_type":"markdown","source":"Read number of the image but unforationtaly when i decompressed the image some image faild to extarct\nbeacuse the acual number of the images 5000 images "},{"metadata":{"trusted":false,"_uuid":"c448df5b9be95e57f7ff59374a5f0590eaf1274f"},"cell_type":"code","source":"import random\nrandom.seed(8675309)\n\n# load filenames in shuffled human dataset\nchestXRay = np.array(glob(\"sample/images/*\"))\nrandom.shuffle(chestXRay)\n\n# print statistics about the dataset\nprint('There are %d total human images.' % len(chestXRay))","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"6565e0cb63a93b0b54f216960bbd38256114e230"},"cell_type":"markdown","source":"# visualize the dataset according of partitioning  of the diseases"},{"metadata":{"_uuid":"4229ab355ae93b686b2478ec5eba099503723b50"},"cell_type":"markdown","source":"Like this sample i token it from this paper"},{"metadata":{"_uuid":"1d271bb35f81ea8f6783348e68c686dd73ba84bb"},"cell_type":"markdown","source":" \nhttp://openaccess.thecvf.com/content_cvpr_2017/papers/Wang_ChestX-ray8_Hospital-Scale_Chest_CVPR_2017_paper.pdf\n"},{"metadata":{"_uuid":"862d58c8c8efc96f93b4b5ecbaf201afe4209973"},"cell_type":"markdown","source":"![image.png](attachment:image.png)","attachments":{"image.png":{"image/png":"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"}}},{"metadata":{"_uuid":"30b2b20d42a5bd6f534244cf71a63d124dc984a2"},"cell_type":"markdown","source":"1-Atelectasis\n2-Cardiomegaly  3-Effusion 4- infiltration   5-  Mass  6-Nodule  7-Pneumonia 8-Pneumothorax 9-Pleural_Thickening 10-Edema  11-Consolidation 12Fibrosis 13-Hernia 14-Consolidation"},{"metadata":{"_uuid":"7389840a9d0c2be27bd7bfd89da6aa5ea7054e43"},"cell_type":"markdown","source":"There are 15 classes (14 diseases, and one for \"No findings\") in the full dataset, but since this is drastically reduced version of the full dataset, some of the classes are sparse with the labeled as \"No findings\"\n\nHernia - 13 images\nPneumonia - 62 images\nFibrosis - 84 images\nEdema - 118 images\nEmphysema - 127 images\nCardiomegaly - 141 images\nPleural_Thickening - 176 images\nConsolidation - 226 images\nPneumothorax - 271 images\nMass - 284 images\nNodule - 313 images\nAtelectasis - 508 images\nEffusion - 644 images\nInfiltration - 967 images\nNo Finding - 3044 images\n"},{"metadata":{"trusted":false,"_uuid":"4d8ba7527ab24e0c149713e42deb6a101b075b09"},"cell_type":"code","source":"#drop unused columns\nlabels = labels[['Image Index','Finding Labels','Follow-up #','Patient ID',\n                 'Patient Age','Patient Gender']]\n#create new columns for each decease\npathology_list = ['Cardiomegaly','Emphysema','Effusion','Hernia','Nodule','Pneumothorax',\n                  'Atelectasis','Pleural_Thickening','Mass','Edema','Consolidation',\n                  'Infiltration','Fibrosis','Pneumonia']#Make list of all diseases\nfor pathology in pathology_list :\n    labels[pathology] = labels['Finding Labels'].apply(lambda x: 1 if pathology in x else 0)\n#remove Y after age\nlabels['Age']=labels['Patient Age'].apply(lambda x: x[:-1]).astype(int)\n\nplt.figure(figsize=(15,8))#size of the figure\ngs = gridspec.GridSpec(8,1)\nax1 = plt.subplot(gs[:7, :])\nax2 = plt.subplot(gs[7, :])\ndata1 = pd.melt(labels,\n             id_vars=['Patient Gender'],\n             value_vars = list(pathology_list),\n             var_name = 'Category',\n             value_name = 'Count')\ndata1 = data1.loc[data1.Count>0]\ng=sns.countplot(y='Category',hue='Patient Gender',data=data1, ax=ax1, order = data1['Category'].value_counts().index)\nax1.set( ylabel=\"\",xlabel=\"\")\nax1.legend(fontsize=20)\nax1.set_title('X Ray Segmentation',fontsize=25);\n\nlabels['Nothing']=labels['Finding Labels'].apply(lambda x: 1 if 'No Finding' in x else 0)\n\ndata2 = pd.melt(labels,\n             id_vars=['Patient Gender'],\n             value_vars = list(['Nothing']),\n             var_name = 'Category',\n             value_name = 'Count')\ndata2 = data2.loc[data2.Count>0]\ng=sns.countplot(y='Category',hue='Patient Gender',data=data2,ax=ax2)\nax2.set( ylabel=\"\",xlabel=\"Number of decease\")\nax2.legend('')\nplt.subplots_adjust(hspace=.5)","execution_count":null,"outputs":[]},{"metadata":{"trusted":false,"_uuid":"c034460648e991eead82208e214fb3fcefcbcdec"},"cell_type":"code","source":"df=labels\ndata=df.groupby('Finding Labels').count().sort_values('Patient ID',ascending=False)\ndf1=data[['|' in index for index in data.index]].copy()\ndf2=data[['|' not in index for index in data.index]]\ndf2=df2[['No Finding' not in index for index in df2.index]]\ndf2['Finding Labels']=df2.index.values\ndf1['Finding Labels']=df1.index.values\n\nf, ax = plt.subplots(sharex=True,figsize=(15, 5))\ng=sns.countplot(y='Category',data=data1, ax=ax, order = data1['Category'].value_counts().index,color='b',label=\"Multiple Pathologies\")\nsns.set_color_codes(\"muted\")\ng=sns.barplot(x='Patient ID',y='Finding Labels',data=df2, ax=ax, color=\"r\",label=\"Single Pathology\")\nax.legend(ncol=2, loc=\"center right\", frameon=True,fontsize=20)\nax.set( ylabel=\"\",xlabel=\"Number of Patients\")\nax.set_title(\"Comparaison between Single or Multiple Pathologies\",fontsize=20)      \nsns.despine(left=True)","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"9c375382e3ee4ec6b599c9e4d4bbb5e8e49d0c50"},"cell_type":"markdown","source":"Convert annotated .png images into labeled numpy arrays. Discard all images with more than one pathology.\n\n"},{"metadata":{"trusted":false,"_uuid":"468c642eb07a96f581acd67a9becd673ea5a81ab"},"cell_type":"code","source":"df=labels\ndata=df.groupby('Finding Labels').count().sort_values('Patient ID',ascending=False)\ndf1=data[['|' in index for index in data.index]].copy()\ndf2=data[['|' not in index for index in data.index]]","execution_count":null,"outputs":[]},{"metadata":{"trusted":false,"_uuid":"2e4b7f63eee5a0c1bd6604913bb99fba07125bee"},"cell_type":"code","source":"df[:5]","execution_count":null,"outputs":[]},{"metadata":{"trusted":false,"_uuid":"450f7018f80504f2715255ed3c92e2c629c7f4e4"},"cell_type":"code","source":"df1[:5]","execution_count":null,"outputs":[]},{"metadata":{"trusted":false,"_uuid":"6cf717fa351a51d1136bf8fcb5e8fc4478d778d3"},"cell_type":"code","source":"def proc_images():\n    \"\"\"\n    Returns two arrays: \n        x is an array of resized images\n        y is an array of labels\n    \"\"\"\n    #all labels of segmentation diseases\n    NoFinding = \"No Finding\" #0\n    Consolidation=\"Consolidation\" #1\n    Infiltration=\"Infiltration\" #2\n    Pneumothorax=\"Pneumothorax\" #3\n    Edema=\"Edema\" # 7\n    Emphysema=\"Emphysema\" #7\n    Fibrosis=\"Fibrosis\" #7\n    Effusion=\"Effusion\" #4\n    Pneumonia=\"Pneumonia\" #7\n    Pleural_Thickening=\"Pleural_Thickening\" #7\n    Cardiomegaly=\"Cardiomegaly\" #7\n    NoduleMass=\"Nodule\" #5\n    Hernia=\"Hernia\" #7\n    Atelectasis=\"Atelectasis\"  #6 \n    RareClass = [\"Edema\", \"Emphysema\", \"Fibrosis\", \"Pneumonia\", \"Pleural_Thickening\",\n                 \"Cardiomegaly\",\"Hernia\"]\n    x = [] # images as arrays\n    y = [] # labels\n    WIDTH = 128\n    HEIGHT = 128\n    for img in images:\n        base = os.path.basename(img)\n        # Read and resize image\n        full_size_image = cv2.imread(img)\n        finding = labels[\"Finding Labels\"][labels[\"Image Index\"] == base].values[0]\n        symbol = \"|\"\n        if symbol in finding:\n            continue\n        else:\n            if NoFinding in finding:\n                finding = 0\n                #y.append(finding)\n                #x.append(cv2.resize(full_size_image, (WIDTH,HEIGHT), interpolation=cv2.INTER_CUBIC))      \n            elif Consolidation in finding:\n                finding = 1\n                y.append(finding)\n                x.append(cv2.resize(full_size_image, (WIDTH,HEIGHT), interpolation=cv2.INTER_CUBIC))\n            elif Infiltration in finding:\n                finding = 2\n                y.append(finding)\n                x.append(cv2.resize(full_size_image, (WIDTH,HEIGHT), interpolation=cv2.INTER_CUBIC))\n            elif Pneumothorax in finding:\n                finding = 3\n                y.append(finding)\n                x.append(cv2.resize(full_size_image, (WIDTH,HEIGHT), interpolation=cv2.INTER_CUBIC))\n            elif Edema in finding:\n                finding = 7\n                y.append(finding)\n                x.append(cv2.resize(full_size_image, (WIDTH,HEIGHT), interpolation=cv2.INTER_CUBIC))\n            elif Emphysema in finding:\n                finding = 7\n                y.append(finding)\n                x.append(cv2.resize(full_size_image, (WIDTH,HEIGHT), interpolation=cv2.INTER_CUBIC))\n            elif Fibrosis in finding:\n                finding = 7\n                y.append(finding)\n                x.append(cv2.resize(full_size_image, (WIDTH,HEIGHT), interpolation=cv2.INTER_CUBIC))\n            elif Effusion in finding:\n                finding = 4\n                y.append(finding)\n                x.append(cv2.resize(full_size_image, (WIDTH,HEIGHT), interpolation=cv2.INTER_CUBIC))\n            elif Pneumonia in finding:\n                finding = 7\n                y.append(finding)\n                x.append(cv2.resize(full_size_image, (WIDTH,HEIGHT), interpolation=cv2.INTER_CUBIC))\n            elif Pleural_Thickening in finding:\n                finding = 7\n                y.append(finding)\n                x.append(cv2.resize(full_size_image, (WIDTH,HEIGHT), interpolation=cv2.INTER_CUBIC))\n            elif Cardiomegaly in finding:\n                finding = 7\n                y.append(finding)\n                x.append(cv2.resize(full_size_image, (WIDTH,HEIGHT), interpolation=cv2.INTER_CUBIC))\n            elif NoduleMass in finding:\n                finding = 5\n                y.append(finding)\n                x.append(cv2.resize(full_size_image, (WIDTH,HEIGHT), interpolation=cv2.INTER_CUBIC))\n            elif Hernia in finding:\n                finding = 7\n                y.append(finding)\n                x.append(cv2.resize(full_size_image, (WIDTH,HEIGHT), interpolation=cv2.INTER_CUBIC))\n            elif Atelectasis in finding:\n                finding = 6\n                y.append(finding)\n                x.append(cv2.resize(full_size_image, (WIDTH,HEIGHT), interpolation=cv2.INTER_CUBIC))\n            else:\n                continue\n    return x,y\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":false,"_uuid":"9f282f142ee7b3871546f878935397adc7e232e5"},"cell_type":"code","source":"","execution_count":null,"outputs":[]},{"metadata":{"trusted":false,"_uuid":"677c138a9eab8350c80186b2dac9695441db95e5"},"cell_type":"code","source":"\nx,y = proc_images()\ndf = pd.DataFrame()\ndf[\"images\"]=x\ndf[\"labels\"]=y\nprint(len(df), df.images[0:10].shape)\nprint(type(x))","execution_count":null,"outputs":[]},{"metadata":{"trusted":false,"_uuid":"9f1e268a013927f9375fefa387e4c69d0a337578"},"cell_type":"code","source":"dict_characters = {1: 'Consolidation', 2: 'Infiltration', \n        3: 'Pneumothorax', 4:'Effusion', 5: 'Nodule Mass', 6: 'Atelectasis', 7: \"Other Rare Classes\"}\n\nprint(df.head(10))\nprint(\"\")\nprint(dict_characters)","execution_count":null,"outputs":[]},{"metadata":{"trusted":false,"_uuid":"446747f2f4e17d1b2501d12502ac921d7c628a66"},"cell_type":"code","source":"def plotHistogram(a):\n    \"\"\"\n    Plot histogram of RGB Pixel Intensities\n    \"\"\"\n    plt.figure(figsize=(10,5))\n    plt.subplot(1,2,1)\n    plt.title('Representative Image')\n    b = cv2.resize(a, (512,512))\n    plt.imshow(b)\n    plt.axis('off')\n    histo = plt.subplot(1,2,2)\n    histo.set_ylabel('Count')\n    histo.set_xlabel('Pixel Intensity')\n    n_bins = 30\n    plt.hist(a[:,:,0].flatten(), bins= n_bins, lw = 0, color='r', alpha=0.5);\n    plt.hist(a[:,:,1].flatten(), bins= n_bins, lw = 0, color='g', alpha=0.5);\n    plt.hist(a[:,:,2].flatten(), bins= n_bins, lw = 0, color='b', alpha=0.5);\n   # plotHistogram(x[1])","execution_count":null,"outputs":[]},{"metadata":{"trusted":false,"_uuid":"a4fd89b257d36c69645e286ae00380999b947f48"},"cell_type":"code","source":"plotHistogram(x[1])","execution_count":null,"outputs":[]},{"metadata":{"trusted":false,"_uuid":"57117a315eca586eb437074e1232c3715bd7b581"},"cell_type":"code","source":"x=np.array(x)\nx=x/255.0\nplotHistogram(x[1])","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"ad394101d1fec5724c81b9d7238b9a4d0eaf865e"},"cell_type":"markdown","source":"Describe distribution of class labels\n\n"},{"metadata":{"trusted":false,"_uuid":"7e2e7335330ffdc91251012f956a53e2446868bc"},"cell_type":"code","source":"lab = df['labels']\ndist = lab.value_counts()\nsns.countplot(lab)\nprint(dict_characters)","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"502cfd5c68bee4de7828f985e80319ff1e4540c3"},"cell_type":"markdown","source":" use a CNN to predict each ailment based off of the X-Ray image."},{"metadata":{"trusted":false,"_uuid":"d9eee9ab8c6de8de4b3da786e823f3d7dc5f40a7"},"cell_type":"code","source":"","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"9be115e9c4439a26c7deaceef5bff687605c58e2"},"cell_type":"markdown","source":"In order to avoid having a biased model because of skewed class sizes, I will modify the class_weights parameter in order to give more weight to the rare classes. In this case the class_weights parameter will eventually be passed to the model.fit function."},{"metadata":{"trusted":false,"_uuid":"38881318e0df503fe416c583f206bcf4e0e8ebb4"},"cell_type":"code","source":"from sklearn.utils import class_weight\nclass_weight = class_weight.compute_class_weight('balanced', np.unique(y), y)\nprint(class_weight)","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"371779fae83e57f769ee508a718f1cdb630cd26b"},"cell_type":"markdown","source":"Functions  Learning Curves and Confusion Matrix\n"},{"metadata":{"trusted":false,"_uuid":"bc29610402c73650994a6fafe882a6051c06c1e8"},"cell_type":"code","source":"\nfrom keras.callbacks import Callback, EarlyStopping, ReduceLROnPlateau, ModelCheckpoint\n\nclass MetricsCheckpoint(Callback):\n    \"\"\"Callback that saves metrics after each epoch\"\"\"\n    def __init__(self, savepath):\n        super(MetricsCheckpoint, self).__init__()\n        self.savepath = savepath\n        self.history = {}\n    def on_epoch_end(self, epoch, logs=None):\n        for k, v in logs.items():\n            self.history.setdefault(k, []).append(v)\n        np.save(self.savepath, self.history)\n\ndef plotKerasLearningCurve():\n    plt.figure(figsize=(10,5))\n    metrics = np.load('logs.npy')[()]\n    filt = ['acc'] # try to add 'loss' to see the loss learning curve\n    for k in filter(lambda x : np.any([kk in x for kk in filt]), metrics.keys()):\n        l = np.array(metrics[k])\n        plt.plot(l, c= 'r' if 'val' not in k else 'b', label='val' if 'val' in k else 'train')\n        x = np.argmin(l) if 'loss' in k else np.argmax(l)\n        y = l[x]\n        plt.scatter(x,y, lw=0, alpha=0.25, s=100, c='r' if 'val' not in k else 'b')\n        plt.text(x, y, '{} = {:.4f}'.format(x,y), size='15', color= 'r' if 'val' not in k else 'b')   \n    plt.legend(loc=4)\n    plt.axis([0, None, None, None]);\n    plt.grid()\n    plt.xlabel('Number of epochs')\n\ndef plot_confusion_matrix(cm, classes,\n                          normalize=False,\n                          title='Confusion matrix',\n                          cmap=plt.cm.Blues):\n    \"\"\"\n    This function prints and plots the confusion matrix.\n    Normalization can be applied by setting `normalize=True`.\n    \"\"\"\n    plt.figure(figsize = (5,5))\n    plt.imshow(cm, interpolation='nearest', cmap=cmap)\n    plt.title(title)\n    plt.colorbar()\n    tick_marks = np.arange(len(classes))\n    plt.xticks(tick_marks, classes, rotation=90)\n    plt.yticks(tick_marks, classes)\n    if normalize:\n        cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]\n\n    thresh = cm.max() / 2.\n    for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):\n        plt.text(j, i, cm[i, j],\n                 horizontalalignment=\"center\",\n                 color=\"white\" if cm[i, j] > thresh else \"black\")\n    plt.tight_layout()\n    plt.ylabel('True label')\n    plt.xlabel('Predicted label')\n\ndef plot_learning_curve(history):\n    plt.figure(figsize=(8,8))\n    plt.subplot(1,2,1)\n    plt.plot(history.history['acc'])\n    plt.plot(history.history['val_acc'])\n    plt.title('model accuracy')\n    plt.ylabel('accuracy')\n    plt.xlabel('epoch')\n    plt.legend(['train', 'test'], loc='upper left')\n    plt.savefig('./accuracy_curve.png')\n    #plt.clf()\n    # summarize history for loss\n    plt.subplot(1,2,2)\n    plt.plot(history.history['loss'])\n    plt.plot(history.history['val_loss'])\n    plt.title('model loss')\n    plt.ylabel('loss')\n    plt.xlabel('epoch')\n    plt.legend(['train', 'test'], loc='upper left')\n    plt.savefig('./loss_curve.png')","execution_count":null,"outputs":[]},{"metadata":{"trusted":false,"_uuid":"e9ea48366827142b5dff9d62e387c007657ff0a4"},"cell_type":"code","source":"","execution_count":null,"outputs":[]},{"metadata":{"trusted":false,"_uuid":"ec6ace9db5ec16097c63f593cca8e382ab4b7cb9"},"cell_type":"code","source":"X_train, X_test, Y_train, Y_test = train_test_split(x, y, test_size=0.2)\n# Reduce Sample Size for DeBugging\nX_train = X_train[0:4370] \nY_train = Y_train[0:4370]\nX_test = X_test[0:1748] \nY_test = Y_test[0:1748]","execution_count":null,"outputs":[]},{"metadata":{"trusted":false,"_uuid":"25988d255adf1ff15b76e73bbd9b4f1d0b4c83ea"},"cell_type":"code","source":"# Encode labels to hot vectors (ex : 2 -> [0,0,1,0,0,0,0,0,0,0])\nY_trainHot = to_categorical(Y_train, num_classes = 8)\nY_testHot = to_categorical(Y_test, num_classes = 8)","execution_count":null,"outputs":[]},{"metadata":{"trusted":false,"_uuid":"b64697149e1f47f7adcb8c6447a8c8d56aae0dfc"},"cell_type":"code","source":"# Make Data 1D for compatability upsampling methods\nX_trainShape = X_train.shape[1]*X_train.shape[2]*X_train.shape[3]\nX_testShape = X_test.shape[1]*X_test.shape[2]*X_test.shape[3]\nX_trainFlat = X_train.reshape(X_train.shape[0], X_trainShape)\nX_testFlat = X_test.reshape(X_test.shape[0], X_testShape)\nprint(\"X_train Shape: \",X_train.shape)\nprint(\"X_test Shape: \",X_test.shape)\nprint(\"X_trainFlat Shape: \",X_trainFlat.shape)\nprint(\"X_testFlat Shape: \",X_testFlat.shape)","execution_count":null,"outputs":[]},{"metadata":{"trusted":false,"_uuid":"9c9a4e54d67f2974abc4f7e66dad53659f5d1b08"},"cell_type":"code","source":"from imblearn.over_sampling import RandomOverSampler\nros = RandomOverSampler(ratio='auto')\nX_trainRos, Y_trainRos = ros.fit_sample(X_trainFlat, Y_train)\nX_testRos, Y_testRos = ros.fit_sample(X_testFlat, Y_test)\n\n# Encode labels to hot vectors (ex : 2 -> [0,0,1,0,0,0,0,0,0,0])\nY_trainRosHot = to_categorical(Y_trainRos, num_classes = 8)\nY_testRosHot = to_categorical(Y_testRos, num_classes = 8)\nprint(\"X_train: \", X_train.shape)\nprint(\"X_trainFlat: \", X_trainFlat.shape)\nprint(\"X_trainRos Shape: \",X_trainRos.shape)\nprint(\"X_testRos Shape: \",X_testRos.shape)\nprint(\"Y_trainRosHot Shape: \",Y_trainRosHot.shape)\nprint(\"Y_testRosHot Shape: \",Y_testRosHot.shape)","execution_count":null,"outputs":[]},{"metadata":{"trusted":false,"_uuid":"115576c142d7423cee924ae65e4b87e2a708d353"},"cell_type":"code","source":"for i in range(len(X_trainRos)):\n    height, width, channels = 128,128,3\n    X_trainRosReshaped = X_trainRos.reshape(len(X_trainRos),height,width,channels)\nprint(\"X_trainRos Shape: \",X_trainRos.shape)\nprint(\"X_trainRosReshaped Shape: \",X_trainRosReshaped.shape)\n\nfor i in range(len(X_testRos)):\n    height, width, channels = 128,128,3\n    X_testRosReshaped = X_testRos.reshape(len(X_testRos),height,width,channels)\nprint(\"X_testRos Shape: \",X_testRos.shape)\nprint(\"X_testRosReshaped Shape: \",X_testRosReshaped.shape)","execution_count":null,"outputs":[]},{"metadata":{"trusted":false,"_uuid":"5e7d9ef52560cfd9c04c2daba1cdeff2664fd310"},"cell_type":"code","source":"dfRos = pd.DataFrame()\ndfRos[\"labels\"]=Y_trainRos\nlabRos = dfRos['labels']\ndistRos = lab.value_counts()\nsns.countplot(labRos)\nprint(dict_characters)","execution_count":null,"outputs":[]},{"metadata":{"trusted":false,"_uuid":"0bd9544fc2e98537194ad66116222ef8f841ca81"},"cell_type":"code","source":"from sklearn.utils import class_weight\nclass_weight = class_weight.compute_class_weight('balanced', np.unique(y), y)\nprint(\"Old Class Weights: \",class_weight)\nfrom sklearn.utils import class_weight\nclass_weight = class_weight.compute_class_weight('balanced', np.unique(Y_trainRos), Y_trainRos)\nprint(\"New Class Weights: \",class_weight)","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"69c0db38b83e1b564343c8635df36a1ee647f66c"},"cell_type":"markdown","source":"# VGG16Network"},{"metadata":{"_uuid":"a194dfdebefc67fe82aa7f2dfbc432e7c9b36472"},"cell_type":"markdown","source":"VGG is a convolutional neural network model proposed by K. Simonyan and A. Zisserman from the University of Oxford in the paper “Very Deep Convolutional Networks for Large-Scale Image Recognition”  . The model achieves 92.7% top-5 test accuracy in ImageNet  , which is a dataset of over 14 million images belonging to 1000 classes.\n\nIn this short post we provide an implementation of VGG16 and the weights from the original Caffe model converted to TensorFlow  .\n\n\nIMAGE CLASSIFICATION TASK\nArchitecture\nThe macroarchitecture of VGG16 can be seen in Fig. 2. We code it in TensorFlow in file vgg16.py. Notice that we include a preprocessing layer that takes the RGB image with pixels values in the range of 0-255 and subtracts the mean image values (calculated over the entire ImageNet training set).\n\n\nMACROARCHITECTURE OF VGG16\nWeights\nWe convert the Caffe weights publicly available in the author’s GitHub profile using a specialized tool. Some post-processing is done to ensure the model is in agreement with the TensorFlow standards. Finally, we arrive at the weights available in vgg16_weights.npz.\n\nClass Names\nIn order to associate the outputs of the model to class names we have the mapping available in imagenet_classes.py.\n\nFuture Content\nWe encourage you to get familiar with this model since it is widely used and will be the baseline for future content on knowledge transfer, guided backpropagation and other interesting topics on convolutional neural networks.\n\n"},{"metadata":{"_uuid":"6713e1f916acf98e50733c24d4539948822c503e"},"cell_type":"markdown","source":"![image.png](attachment:image.png)","attachments":{"image.png":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAdYAAAEUCAYAAACWOhflAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAMUhSURBVHhe7J0HoBxV3fafbbf39J6Q0Lt0pYmAIhZsKPauL+prFws2bFhesaGgiIifiCAIigIqvUtPCC295/a+fXe+/+/snbBcbvoNaeeBye7Ozs6cmTtznvP824kUi8UgEonIw8PDw8PDY+sRHXr18PDw8PDwGAV4YvXw8PDw8BhFeGL18PDw8PAYRXhi9fDw8PDwGEV4YvXw8PDw8BhFeGL18PDw8PAYRXhi9fDw8PDwGEV4YvXw8PDw8BhFbHNiDYJA2WxWuVxuaE0J61sfIp1OD73bPGzp8QqFgvL5/NCnzQP7ZOEYmwN+Q5vKfxe2c31t4Te0dUvAPocfD4zUjhBbc7wNnQvfbenf2MPDw2NHxjatvETnef3116u3t1eLFy/W9OnT9Z73vMet//vf/67BwUE9/fTT2m+//fT2t79dYTuSyaT+53/+R7/85S9VW1vr1m0K6MBvuukmdXV1ueNNmjRJH/rQh9x3f/3rX93xFixYoDlz5uid73ynYrGY+86ugX7xi1/ogAMO0EknneTWbSquu+4698ox2f9HPvIRVVRUuHUbwj333KNnnnnG/S6TyehTn/qUEomErrnmGnce8+bN00tf+lK9/vWvX3ddILivfe1rOuuss1xbNwf33XefnnrqKXV3d6u/v1/nnHOOqqurdeedd2rhwoXq6Ohwf5dPfOITqqmpcb/heN/5znf0qle9SkceeaRbt6mANP/yl7+4Y6xdu1avfvWrNWvWrKFvpfvvv1833nijvvnNbw6t8fDw8NhFALFuKxhpBp///OcDjmHkGhx11FHB3Llzg7vvvjuwDtWttw49OOyww4JFixa537DOyDE49NBDAyMAtw4Y2QSPP/64+z6EEdm63wEjjuCLX/yi29bIOTjuuOPcsYykgi9/+cvut0ZkweGHHx48+eSTQ78Kgvnz5wevfe1rgxtuuGFoTQlGwkEqlRr6VGoD7ecVGPEEp556arBy5cqgp6cnMPJ5XnvWByO3wIg9MEJ1+3r3u98d/OEPfwhuvfXW4IILLnDbLFmyJNh///3ddQth5OjO6ZFHHhlaUwLnQltCmMp01yoEx7OBiruefPeOd7zDHY9rz3vWmbIM3vrWtwZXX3310K8CdxwjxMDId2hN6e/zxBNPuLaH4Bz4W5f/bX7yk58ENuhw637/+98HNpAY+iYI+vr6gq9+9auuTR4eHh67GrapKXjs2LHaZ599nOKqqqpySg4lM3XqVO27775uG9RRPB53JkNgnbYaGxvV0tLiPoeIRqN67LHHnAK2ztqp4B/+8IfrfgfGjBmzbr8cD7WL+h0/frz23HNP1w4UVNgOgIJDsR1yyCHuczmMAGQEISNXp+b+9Kc/yUjMtQXwSns4TxTmXnvtpQkTJrjvNgTahhqlPajmpqYmp3ZR9Cygvr7enaeRlvu8Zs0a1x7OYzja2tqc4kb5Yrr9zW9+o9bW1qFvS8d7yUte4trLtW5ubnb74tq/7GUvc+1gPcfkegH2uXz58nXXMwTborJ/9atfuWPRvksuucRZAvgO8De58sor3XEeeOAB2cBJRx99tPuOc8JagWUg3N7Dw8NjV8I2JVaI7v3vf797b8pRs2fPlqkwzZgxQ295y1tcx4rpFlKDMEITrilb95tysK2pK0eof/zjHx3hYSaFuEOMGzdOpv4cWd1+++3u+CeccIIj1ve+971uG9bTBggDU+dtt92ml7/85SN28pDRK17xCv30pz/Vr3/9a2eqDdsdorKyUg899JAji1e+8pXu88YA0WHqZn+c77Jly3T66ae76/PGN75xnamc84N0IbC77rpLJ5544ojt5Bw5n4svvlgXXnihZs6cqZNPPnno29LxPvjBDzoiDY/HeTDIoB1cr2effdZdf1PgjqD5e/F+pOOZanZ/s5/97Ge66KKLnMn9Na95zdC3JTMwx2CwcOCBB+qKK65w+wO8YlbeHBO/h4eHx86EFyUqGKWJTw0ypJMPwTrU4g9+8ANHcvjkUH10ynTOKCY6+RAQwGtf+1pde+21jsAOPvjgoW+eD9Tjvffeq5///Ofr/KiQ1cMPP+za8qMf/cipVvyLkE1nZ6d6enqcSkPJlQNypS3/+c9/9LrXvW6dWgWoL75D9eH7/P3vf++Ou6lYsWKFLrvsMqc2ISdAOyF/2nHuuec6YvvHP/6hKVOmaPXq1c4/ymuoLENArqhGFgYDIxEiKvbyyy93AwXUZIilS5c68uN6MThhsMNghO0ZyOAj5bjlOPbYY93fh2uKD7YcoQrn2kGg+ND//Oc/u+Pwt+V7FDj7ZN8eHh4euxK2ObHS8T744IP66Ec/6syoixYtcusJpiFw6cMf/rB7Zf3ee++tJUuWuO3oeFmPGTYEZEPnf95552nixIkuIAlyK8fcuXMdYZ999tlatWqVU3rgv//9ryNVgoseffRRp9zYB7/neBA8nT5BPCH4DnUMMRDsw8CgnNDYJ0FXAKJGgdLuTQGkSuAT14VBBUoOUr311lsdcaKwUdOoPoJ+IDjaCZnR9vIBAOZY1CqDjje84Q3ufbmJHHA8zLMoV8gO8gSQ3Q033ODawSCBa4epnv1zPP4eLKjZEChojoFCJxgtNAuHYPCE+mZ/gMERRM56rAgEUbEwkOH4nLeHh4fHLgMjD+vXtg0IwNlnn30CI6bggAMOCEzBBEZeLgCI9QTnsJ73BNIAApJ+9rOfBXvuuWfw7W9/OzDV5NYTXPONb3zDBSIB68gDU3vBzTff7D4D9n3IIYes268RdWCE6YKQ5syZs64dRxxxRGCkO/SrIPj73/8enHjiicEHPvCBwMh3aG0QXHXVVYEprXVBOQ888EBg6todGxCwdP755wf/+te/XFs+9KEPueCojcFIKzBVGZg6X9fOf/7zny44yUh0XfuPPvpod96A4CTaQ9s/9alPuWsb4te//nXw73//272nrby/8MIL3WfA8UxVumsaHu+WW25xQU0EQ/GZ9fwdCKAKYYOK4KUvfakLMuJvBtj/JZdc8rxALxsABBdddNHzgpdY961vfcsd57Of/WxgA4Khb0pBUUbkgaleFyy1Le9BDw8Pjxcb2zzdBjVWDoJk1rc+BN+xDcBsSPv4jHqrq6tz6wHrUJChv25Tj8f+QhMxKD8ept7Q3ItaRmWVX5+u7l41NTbYNqV1/BblxSvm3PL9bghhUFIIfkcb7O8xtGbD7QyvC+AahCkyIVCcDQ0NQ59GPh4ovy6gfL/ruy4DAwPumpdfl5HagMomOAwzNmo+BOcYnufwc/Tw8PDY2bFNiXVXQ74Q6I75/Tpu3zpVJF4U9/QmA7NrubkWUsRvTPAQ4LvQNAsgPSKQfRCRh4eHx+jCE+tm4O6n+zV3yaA+eMoEVcR3nGuG+vvWt77lFD0KG5VJsBU+1y9/+csuhenHP/6x850CSBVfLttsSnqQh4eHh8emY8eSXTsw1nTndNUDvaqqjGtHG4cQJU0g1ve//30X2EXqDrm1qFEibwk0+va3v+2+CyONCYgqN797eHh4eIwOPLFuAjL5QH+4p1fpnBREdiwyInKaFB/yhSFMzL/ksn72s591ypVc0zPPPFOTJ092nylyQfT18MIPHh4eHh6jA0+sGwGxOzfNHdATK3OKRGPqThJ4M/TldgYmXeopf+ELX3DBQZiEUaSf/OQnnYK9+eabXT4pOaeANCOW973vfe6zh4eHh8fowxPrRrCoLWfEmjJSjShXCNQzmFMpTnb7A1KlUhMkCv7whz84JXr44Yevi6CGREMlSyGKz3/+888r0uHh4eHhMbrwxLoBDGaKuuK+AaXzEbtSEQWRqHI7gFrFpPvPf/7TpbdQcQk88sgjTo1SAIJ0mN/+9reuwhLbkGrzve99zxWdIPXFw8PDw2PbwRPrelA0Wfr3R5Na3lU0QiXf0lbuIEFLVKnCzEu1JNQoOauoUfyqBCShZN/85jc7vyq4+uqrXY4tNX49PDw8PLYtPLGuB3OX9uj2p0uz2qxjVmzAplq3JyhV+H//93/69Kc/7eol41c9//zz9a53vUvTpk1zZRAh11DJUlyf1BpKOfq0Kg8PD49tD0+sI6CrL6uf/vE+5YslmQohRdylYtl+5ETRB/JR3/rWt7oZbCD9q666yhXOZ4aelStXuvrJ4Yw1VD367ne/61JtmMnGw8PDw2PbwxPrMOQKRf31v33KV00ygVoi1vDFqdbtqPpQnkT/hmr0mWeecTPhMJEB5ReZJehzn/ucI1FImAkLIGFfBMLDw8PjxYMn1mG47+k2PbCoU5HKaCn61/FoiUydJXjo/YsNZqdhFhpIFAVN4QcmeqeyEgFKzBd7yimnuMIPgOAmVCsz0Hh4eHh4vHjwxFqGJUZeP/njDUqms8q48N9yErX320mxMu0aftVPfOITqq+vd1G+TGFHgBL1fu+55x5HtFRcAkyBh0kY9Vo+f6yHh4eHx7aH73WHgCn1ez8+X4N9/crlM0rUjHEKdZ1qtSVK4NKLTKz4USlJeNJJJ2nOnDlu3Y033uhMwqeeeqrzq1JN6TOf+YwjUfJXKW2IkiW4ycPDw8PjxYUnVgORtZf+v0v07OL5GtscVTbVpliiREqlSNpSABOvUceyLx7uuOMOR5avec1r3GcmY6c28Mc//nEXIYwflfeYgyFhclfZNiRhDw8PD48XF55YDfOfeVyX/fESxStyal2zVJm+dIlCjUyf87OiWEuxwS8WmOf1z3/+s4vyRY0y5+nXv/51t1BV6corr9RLXvIS7bPPPm57clsZJIQk7OHh4eHx4mO3J9bBwQH94rffVk9vhzrau031xRWNVxqRPVdsH15FqZZE64ujWJk7lfxU/KTU+4Uw8atSwpBUmwceeMAVinjLW97iBgCLFy92SvZTn/qUnzjcw8PDYztitybWQrGgX17yUz3+xFzVNVRJQUL5bJ9qmmsVRAIjLKdXodQhZ6v9M7RuWwKT7hVXXKGjjz5as2fPdutuueUWZ/p99atfrdbWVv3+9793dX9RsgQ3/ehHP3ImYZSsh4eHh8f2w25NrHfec6v++Jffa2AwbSpVpvSMbHNJ5YyoHIE6hRouJbNw8CIoVmr+okbf8IY3uM+k2kC0qFfUKRHClDNsbGx0JEwJw+OPP14HHXSQ297Dw8PDY/thtyXWjs42feeCbyqVS6lQkPr6BzSY7FdvxzJTffVDpl+0Kq+hSuV9iWe3Fdrb210U8Be/+EUX+RtG+UKqTFzODDaHHnroOhJFyXZ0dLhCEB4eHh4e2x+7JbHm8jld8IsfatnK5coVcsrliqqoqDEiiykaKSqb7VKU+sCGkFSdUuX/bahYczlr1wUXuGAl8lXB7373Ox155JHab7/99Nhjj2nBggVu4nKwevXqdak227JdHh4eHh6bjt2OWDGd/u2G63TtX/+qfC6r6spqFbJFFQsRBbbEVKv25Qtsw6HKS06foltL72wHQ+tHH0T5Mp/qIYcc4j7fddddWrJkiSuwT93fSy65ZF1wEn5VpoJjUvMxY8a47T08PDw8tj92O2JdvmKFfv6Ln6qyOq6gGCiTziJHVTTVGonVKF41U/UNe6kYKxiRcnmMTsvUYMk8PPrAr/r000/rbW97m/u8atUqXXrppfra177mjklwEpOWU3CfwQEki5L1flUPDw+PHQu7FbGm0in98tKfqy/Vo1i1kWQx7kg1Ea9Q3lRrtLpZlWPnqGXKnm77SFAsXSEjshJKlDrairWzs9OZfJkKDr8q0b/UASbKt6GhwQUuUfDh8MMPd9uHqTYhCXt4eHh47DjYbYi1aCR53T/+rGtvuF69SWmgb1C11bVGngnlTa1ms3lV1bSoYeIcI04jWWY6j5Tmt4nyDx+3gVQlP5XqSZDk2LFjnRq97LLLdPDBB7viD/PmzdPcuXP1zne+023f1dXlJjWnZCEk7OHh4eGxY2G3IdYly57RVddfrsbGyapvmi1lEurvH1RqMCmEaUWiyi5GUS1jGjXQ3a5YpM1INTOkUYkG5l1pGU1+pVg+07odc8wx7vPDDz+sJ5980vlVqV/8q1/9yvlRKyoqXHDTN77xDadsIWEPDw8Pjx0PuwWxJlMD+saPvqDerrRqG6s0dvwE5TJxU4cVRpJxJQdTqqyqUGZgjQZ6nlJ+YKWW3ff/1LHsMfs1+ashqRqCoTKHowDU6P3336+PfOQjjrgpYYgaPffcc933+FXf8573aNKkSU7JUhQCn+phhx3mvvfw8PDw2PGwyxMrptbfX3WxFi1erJqaJmULA8qmu4wcY6qqrldj01hVV9com0urp7dV3aufVn/rPM27/Z8aWLPM9oBCRbGW9jeUhbPV6Ovr029/+1sX5Uv1JNr5ne98x5EsapT5VJubm3XUUUe57TEHQ8ShSdjDw8PDY8fELk+sdz9wiy6/8reqr5+lmsZpqjACy2cyqmtscGUM44mI8vmcKiriqqqIKNmxSoncoA6YvZeam1rWEWlIrKNhCC4UCrrwwgtdZaUpU6Y4NUoEMGqUMobU/aXwwwc/+EGnZPGrUieYohFVVVVDe/Hw8PDw2BGxSxNrb3+3LvnjT5XJ9mqwOEYpI8Vkf2BnXWtqtU65XJ9i8Zwpxpjsf0UjNUrEEgqSPZoxa7oSNdVuPy7FBj61f0bDDPyPf/zDFYA44YQT3Gf8qqjRd7/73a7SEiULIdHq6mrnVyVC+L3vfa8zCXt4eHh47NjYZYkV0+o//321KiuiRqKVyg52KNm13BRqlSLRiOKxoinUqOpralRTVe2IlaL82Wxcs6ZMdWUOHaEOKdQhXt1qUPDhP//5jz7wgQ+4zwMDA86v+tnPftaZhAlWYgabkESvueYaZxo+7rjj3GcPDw8Pjx0buySxUhvpr3+7Vtf9/Rq1tJgaLUbVteJJDfZ2qqGuTpF8r1KmSrPJgl2AuBqaqhVLFJVLZ1U7Zk+ddMLRKuQoxB93F8hFBJckq9v/liKcCu6cc85xajSfz+u8885zJt/p06frX//6lyorK/Xyl7/cbT9//nzddttt+sQnPuFI18PDw8Njx8cu2VsvXrxIv/ndb5RKZdU/kNaksRNVX1uhtrU9Wtvap77utSrksy6FpaG6UZFY4EyuldW1qq6JOhVZUYn/tWJoj0bWQUm9ruPYzUQ4nyrF8vGrAtToxIkTdeyxx2rlypW68cYb9f73v9+RaE9PjzMJf/WrX3Xt9PDw8PDYObDLESs1dL/zw2+4KkvptKlONainb0Az9mpWU+M4xWvmSLlAiSqptjGiwcGc2y6XKWhwoFNxI8DO7l4pZiQas8vjiPQ5JnXvtsDRihpFpYZqlFzV22+/3RXcTyaTbgYbzMHMp0pwE8X4zzrrLE2dOtVt7+Hh4eGxc2CXIlaia/9y/RV66pm5ihkptrd3acGCZcrki2rt7Fd/Jq3p+71E/YP9isejSmVTSmUCDfal7NdRU4YJxUyl1tQ0KIjE3P5C82/UyJV3W6JWQzWKXxWS7u/v1w9+8ANXPYko39/85jd65StfqRkzZrjtCW6ChF/xile4zx4eHh4eOw92KWJds3al7rzvX+rp7tHq1a0a7A+0ZkWX0pk6FQstKuSyyvS3mVptUjEfKBJUKV4RUSwaVTQaN+JMqK1tjeobmrR82XLlsrl1hApKwUy8cR83CShoCj387//+r1Oj+FUxCaNGp02bpnvuucfltJ522mlu+4ULF+q6665bl9/q4eHh4bFzYZfpuZOppP745z+odW27qVEjzFiVEaOMyGDBSiX708oZgXWselgTpowzdWrfp6JKVFSaOqxUsVhQJBFXdV2LBnMFrVqxRFn77fMnids8GzB+1YsuukinnHKKZs+e7dahRuPxuFu3fPlyV2CfYCamgsO3+93vftfNaOPzVT08PDx2TuwSxOpMwH+7WouXL9KyZaucsqyuiauytsapy+6eDkWDohLxiHq7F6p1zULlMmk3VVx3V7spxkEjYiPVqhpVNI7X3AUrlEr2q6K22fb+nDzlXRDhkm2aZL377rud2RczL1i2bJmuv/56N2sNwVIUieB9GJz0s5/9TK9//es1c+ZM99nDw8PDY+fDLkGsjz7xpB56/EEtWPiMU4mRWESDA12qrq1SIV9QTW29CsW8YqZIe9q7FBTyrvB+X2+vqcReU5AVbnabVDKj6ubJWtveq2KQV03jOONQU622wKVFI9USpW5cua5Zs0Z//vOfXcF8FCoE+/Wvf90V0cckfPnll7v5VPfbbz+3PSUMCVp63ete5z57eHh4eOyc2OmJtaevR1f9/e8aGEw6Ek0kKpROZ12qTXV1VI1NDcaD/Rozfrri1S2qMlWay+WVzWeVzmaUL8aUqIw5X2i80hRqrksdHa3KBxVKVNU7ImXBJBy+35hiZVaaH//4x86vWltb68gedXrGGWe4fNUHH3zQBTRR0hAwtypKlllsyiOQPTw8PDx2PuzUxFosBrryhmv09LPz1NXZqdoaU6Z5KigFSqbTRpYD2me/OaqIFo3skqqoq3dKlApLkWhMuYJcJHBldUIxU611TY1aNvd2xROmTI1Uo/HY0HGyCgICmYxcHe+tX7Filv5//+//uZq/e+21l1tHqg2Tl7/mNa9Ra2urK77/mc98xgUnhSULIWEmNffw8PDw2LmxUxPrXQ/M1w03/UdBvkeNdTXq7u5SX8+AGhtqVVdfa2qxUh2dq9TQZISaSZtajSo9mFW0GFEsVqWaKtRsUlXVVUasgZFfjxJGnk2NcVXXVJsuLbrjpPtWqwBj25qgmDPydKtHxEMPPeTUKL5S1CclDP/yl784IuUzEcJUUmpsbHRKFr8qua3777//0B48PDw8PHZm7LTEunrNWl198z2qSuRUU5nQnNnTVVWT0PTpk+ykUJpFxeNF5YuYiLNGahm1rl1rqjPu/KsQZzxWUG1VlZqaq1TfUGf7qlVNba2WL7nHvjNpahtGbOnraHUToQf8MNnulOtI6DTVTE4qJIpflRKGVE/Cz4pJmPlUmUs1JFEKRLS3t+vMM890nz08PDw8dn7slMRKINLFV1yvjoGiqdOEEWdpLtWISck99ppkr3HV11UpnwvUMqZBcVWpsb5ZFZGiKio45cBIsFWpzKAz3abSg6ZSm22/WQ32LVY62aYxzeOUyWZUyKVVU99iYtXIOtOrA+q7FA0KpYaUAVMv1ZMw6aJG2S8F9V/2spc5IkXJLl261JEoynXFihX64x//6Gax8X5VDw8Pj10HOyWxPjz3Ti1uzyuX7jPlWaOGhmpFEyjUSiWTGY2b0KwJE8dqzNhmI61qDWZq1NfTr6gRcqGQVb6QV7FQUGNzrXoHetW6pl8D/YNqX7NYbasWKBKtVjJdcAUligGRwhPtQhXVEulQS898p2SH48orr9TBBx+8To3eddddLjIYIu3u7tYf/vAHfexjH3N+1bBoBCbhpqYmt72Hh4eHx66BnY5Yl7e26a//ukG1zdNVmQiUSafV0jxGvf196h3MqK2jS13dXaYYI47YCoVaI7JArV3SwGCgaCRhe4k4Ii2a8szkCspnIsqmM4rmi0a+garrpyqVI1UnrQxBT9W1yg20anZhgdTbXmpIGR577DE9/fTTrsA+6hMfKyZh0msAJMpcqxMmTHB+VYKXDj/8cB1yyCHuew8PDw+PXQc7FbGmskVd+Z9H1do2oHyxR9lsm5rq6xSrjCqXjRuBkpvap8pqqaOt3ZTigBFon4pGvgcccbRaJkwxMi2WFhOd6UEpHqu0JWEKNmckXTS1GtXMvU9QVdMk+97Y2BAzsq0bmK+atrlKx6uHEm9K6Ojo0CWXXLLOr4pJmCjf0K+KkiU6GCIFlDCkUMTb3vY299nDw8PDY9fCTkWstz68RG09Rpw1tVr+9P1KFFLaczYpLRHl0lJdw1hTn4FSqUH19CQV5ONavmyp8vmMersWqyKRcybgKKk2mbySgyll7TWdTOF2dZOgK1GrnoFuJSqqVMz0q4YUnoF2NXY8oKpIoL6qOjtciVjxozJJ+Tve8Q43GTn43e9+p0MPPdQtTzzxhObOnbuORKkJTD7r5z//eSUSKGcPDw8Pj10NOw2xPrt6QI+siKm2olfpgQ5lTIlOnzJRnZ0dKuRjRpoNahzTrMlTJuuAgw8y0pMjzVyyvsSDhaTyuX5nquVjNBrYyfM+UG2dqdZ4QnWNdapvMlUbHaea+gZle1crURVVde+jmhB0qzduZJuodO0BV199tZtb9ZhjjnGf7733Xj377LPO7EvdX0iUqeCYvBy/KoFKX/nKV9aRsIeHh4fHroedglgHU0n944GFysbqXIWlVF+Xpk+dpJaWmCnKarW1dYoi+k1VEY0dU6/OnlaXLtPc0qgx46YYORaVMhXa2dHmtoNpq+ur7X2gwD7XVFfYa0TZbEpV1Y2aMPNoJeLVWrnwMfWteUzj+ue6gKVUZYOp2rhr07x58/Tf//7XTUwOSLX59a9/rS984QtOyTKf6nve8x6NHz/efSZ4CRV74IEHuu09PDw8PHZN7PDECind9eh9auvHf9mj6obJWrGyXfXVKXV1L3bqc82aVVq2aqkmTaxVtDKtJYtXq683rWJQZSeYUf9gj3p7OpwqpTQhSjVP7eC4vYsESqfz6unrd77Tpgm1mjJzvH0nNTY0qv2pO9Wc61SmqlmR2joj3Er19va64CTUKLPSMBXct771LX30ox91AUp///vfNW7cOB111FHuHB599FHNnz/fKVkPDw8Pj10bOzyxLlixQrff94gy+ayU7VJcfWpqqtfkSc2mSquNbAO1tnYpncxqMEnAUqf6u9NGyPhdU0qluo0kExroTyo5OOiINFEZVTQSda+RSFxRI1hKPjDjzdJnFqh90X80OLBMVRUxxfMZNTePVc2UWaqsqFIhyLv8VNJoJk2a5Ij/0ksvdWk2lDGk7u9tt92m973vfc7s3NXVpZ/+9Kf60pe+5EzCHh4eHh67NnZoYu0cLOrW+R3KFCaYUqxRJL1W6e5lyhZSWrxoqSJGngsXP6vq2mpNnzrZTqZG7WuTqqmoVRAtqqenXdQLHhwYVE1NneqIIE7ESkX40zkljDghy3Q6qfo66gzHVGvKdM1T92vZk3eoZ/XTmjJ5kopNY4wU613FpbvvvNPV9KXwA3jkkUdcqg1qdNCI+wc/+IHzpTKfKkqWVBvMxZiEPTw8PDx2feywxJovSjfOy6k/V6dEyxwVYjWqrkhqxeJ5KuYT2mPmHuob6FVHN3WC6zVmTKMRaZ8G+3Pq6e5zaTSJyoSp1AFFTY421DfK2FbFQqBMKmf7KLrKStW2Tb6QUy6fVn3zONWPnW4qM6+8kWR3R6cWLnxUxeomxaJRrV69UgNG0h/5yEecGu3p6XFRwZiESbXh/dvf/nanZAHTxkGoxx9/vPu8qSDQiX0PB35c0nnKQUnEp556ykUcbykovUgRi+FgHYODcpBexPEwh28pmHhg+O851pNPPvmCdjBY4Xgofw8PD4+dATsssT60rKglHYOKRNOKmKqsqa7U8kWPKj2Y1rTJU1UoDmrBgiXKZa3jN+WaziS1fMVKI4nSlHENjQ0uOKm/N6nMQEarVq5Qp5FCTNQKjpgCrTIFW69YLOLmb0XFVhgDNzZXaOa+B9r3ppCjCRXTHYpWVqgQ5HTPXXfr3HPPdWqUuVPPP/98Z/IlMvg///mPM/Uee+yxrv2oWGoB43eFhDcFkNgtt9yib37zm7rqqquG1pbmdr322mud8qUsYgjUMsdYuHChm3LugQceGPpm04AZ+x//+IebI5bgqhDMHXvdddfpne98p9ra2obWSvfff79uvfXWLT4exTHuuOMOdzwGHSEg1JtvvtmdG6lIXEtAoQ1mBiLC+q9//auLuvbw8PDY0bFDEuvK7kC3PSsVsr3q7Wx3NX4T+bWKZPuMDCeoqblGnT3tMnrU5Ilj1NLconmPPWXkx3Rxeec/TQ32Kp/JGyHXGpEWjYiLqoglFJhijcZiblq5vu4BpwBJuYkZifYP9Kh37eNaseQZI+wBpfo7VG1KFAK66cYbnTJlPlU+U/gBZYoahRButO9RsgQzoSypG0xAEyS8qUD1sr+ZM2c+T5kSEPWqV73KfQ85hfj5z3+u2bNn67Wvfa1e+cpX6ic/+cm671F6zPFarjjJq2UJAeGfcsop2mOPPZ53PCZiP/30091vw/1xztQ2ZluOR27uV7/6VTfAAMlk0k3WXt4+lCZ5vCEo5/jSl75UU6dOdao8xGWXXaaWlha9+tWvdgOVr33ta07V0v7m5mZXXIMZgDyxenh47AzY4Yg1lZNufrL0WhSqM65CvEb5/qfUUF+tmoYq9afa9Njj8zWYHNRiI7WFixY6fynRvVROqqyoVCFX0JgxLUYIBduPkUhQtM6aeVgjyuaMRIwospmsqbMk3ypvipVI4FyqX8nu1UZiRsb5pA7Yd389/thjOuTgQ3Tccce5NkIYVFD60Ic+5AgMQkPBVVdXO6JhKrizzjpLEydOdNtvDigcAQGVg8+sH658qe40a9Ys9x5VN2bMmHXb1NTYNTNiZG5YSJHIZFQopF2OioqKF+yXz8OPx/sPfvCDjlgBpmfyccO2cjzI8PLLL3fXAAInzzfcPsRI54cSP+igg9x7TMTslwHKkUce6a4rA5SbbrrJEa+Hh4fHjo4diliJzL13UaDlplid7kk0WM/faFKuXun2haqujJrSXKFoPKs9Zs5yJQM7OwaNfAPts980jZ8wRmOaG5QcTNrvI8oVoq7gvglYQ8Spx6rKCrfEYlFTxAUjTyPYdNGZhKO2JCrHarCnS8VCWo31dUr2p9TW2rbOr4qZlAAlonwhUur+nnzyyesI7oYbbnAk84pXvMJ93paAjFB0+D0xmX7qU59aR4a8vuENb3Az7dDWv/3tb27mHdToloJJBlCWTNbOHLPf+c53nke+r3vd69ykAt/97ncdqdKeTTnePvvs4wYhkDWqmP1CvlzT0047zdVivuiii7bKr+vh4eHxYmGHItYl7YHuXUymaQmB8orW1KsmmlKqv1vt7cs10NdhitSUYS5jarFPLU1E2xZMlSXU3dmptrYOU68VSmcyyhaqHIG6rt92SlpNTV21GpvqjRQrrfOOKWfkms1QzD+voqnk7u4+TZ55sBFuXlMnz9CCZxboa1/9murr650ChFQp/DBt2jTn30SxYjYF+FUhVpQkiuvFwNq1a3XxxRe7lJ7hkceQE4oRhc13DES2FvhcGUwQ7QyJooZDQLKQ4TPPPOP8zgwwNhUELXEe+F+5tuwXczozAkHS5513nr73ve8Nbe3h4eGx42KHIdaBjHTTU6Vo4HXEWkwrm8woke/Rmo4+tRlxkh4ztnmCmseMd2bFqVMnWIeeUG9fUvW15LbWKBaPqaq6Qi1jGp2JFDMvilXRoinZgtKplFOyHIhKTCheXIM1dXFlbdt0qtNItKBnnpqvj370I5oxY4ZrDz5EyAI/KIE1qDZMlRAKBAvZnHPOOc68ujWAVMoJK8TwdShHlNyJJ57oCA9VWo7HH3/cmX8JTMJMfMUVV4y4X7C+45WvRxn/8pe/dMdDXTL5QDkYWFxzzTWulCMFMjBDhz7YcgzfL/vCfH7EEUc43yvmZL7HV43iZZDC4CWcks/Dw8NjR0bs61//+jfKzXnbA8Zr+ue8ohZ3WjusLeu63CCnIFKpfM9TWrlisSIFzLVRxSI1eubJJdYhD9iPmVs1rkR1VMsWLzXCrFSyv0fVtZXqNOKBMfG3st8qU6k1NZUldRoUVBmvdMFMRQg3Eqi6oUr5bJ16O5apmE3q3We9Ux/58IcdcS5evNgpKiJ2CdAhIhg1hQkTEsD8eeqppzq/4JYCRUzADqUSIZWUDQAwk0KgBEutXr3akRtkQ+AUwUt33323m/v13//+tzPVhr5KBhT8BvXM9vvtt5+L5mUAEEYxk4tLlShMrShGApD23ntvtw0BRZA1ipgBDL+hZCMqneNheqZEYzhrD7+FuAnw4ni0e/ny5a4d/BZwnRiccH6kCXHMAw44wBE/UcEEJ7HfOXPmuPrLzAoEUUO8fIePFcL28PDw2JERMZIItjexzl8d6JpHjeAgVWPVov0DuQZGdsr3qrrtdi1b9oQJzg5TsGnFa2dr4RP3asEzj6qlsU4tzeOMHLNavmS1Kc6Ycslel3eaYY5VUzsFU6GReFS1dTWqq69RNpVXIchqoIfApagq6yoUq4wolohrzPg5ajMS32/2Prrm6msdSeBXxV9IFCzBPxAMCvCNb3yjI13Mv6hDfJnDA3O2FyAxBgDDTdIoSNahrKlrzHmMBkY63vrasDmgvahYrABERXt4eHjs6NjuLNA1KN3ytHXCJU+og+N5SNXW1qhL/b3L1TJ+inr6etXSVKPqsfuosqpCtbX1dgJRTZhQr+bGZqWTGdsL/lbyUk2l2tlh5n2O7DDZptx2yWTKOnxTupVx12HX1FabWi2qt3OJ6qtqdeHPf+lIFWJAGRKYA6ned999TjkSGASpUsIQEywm4e1KqqZuRWqLETxLxFRo7JZbYDf39YoVKxz5E62LQkUx8v7OO+90eaSAlBtqGrNd+cL2KGIU9frAtRhOoCOt21zwe8zvnlQ9PDx2FmxXxYo/9S+PBHq29Tm1CtCrTrOaqox0/kcr5/1bTZP2MuXYp9riSrVGjtET//qh6k2BxqJ5jZ843hg0pnvvekBVVfX2vqCu7k7Fo3HlSbHBwhyLulKEaVSsHSMXpOzkjVQrreMPjJ6rIspnyHWN60ffvUBvfetbXVtI86AQArmVmEa//vWvu4nMCWZCSRFpC6liat1u4MJ9//vSwIDU3FxaZypaVID64x+1YOFC/d///Z/23HPP0ndDwHxLqhDFGohixme6YMEClzdbDlJ1GEBgjt1e94qHh4fHzoLtSqz/XVrUzU9FnKq0RjyPWPk3klmhroU3a+2yx1Q/rlbVtS9RLPWkcnVH6PY/navx4xtNZSXV2DxBK5ctU3rQ5K/idlKB2to7jbnhHHJXKbhP/mTElE+FGupr1dXfoWLWRK3xajRSoWhFVJlkWu9+23td5C9+RQo/kEMJ+aBe8R++973vXefHhGCJgn3zm9/sPm83UKnIyM8aaCdjw4ZnnpG+/GVp8mTlL7jA+VkxZVNMIgRmWs4TRYqvmFQkqhsxcODcQzCYwGRMahGTD3h4eHh4bBjbzXa5ule6Y8EQmRqvh6RasgjbenvNDKzSmDF7qGXsJBVTCU2c0KRcxd4q5HOqqYkb2VUZicYUMWUrI1DMufWmSvt6+2RrXYASJuUgKBpNF53vtpDPajCdMv6JKc7sNaZq7Wtlkzntv/eB+va3v+2IhQAeiPNzn/ucI1XUHFWDQlIlyIZ6vtudVE2NimhgI05HqtQYJi3FCBIrAIOC17/+9c8jVUDwEoFFRNsSHEUKDX7XclLFNEykMzm8KHQPDw8Pj41juxBrOodfNXDVlUI4c21IsPhXI1ll+9YqFu1TpGKCUppsJFirxqnHGOO2aebsOo2dUK1IrKCBVJsRQtz544rF0lRwmHiZlDyRqHBnWWuky/fsHl9hzIgVsuV4xUJRddV1+tlPfrYu1xMiJWqW6NYHH3zQpdecccYZ7rtVq1Y58ykKdrsimZQuukj63/+lpFHp4hkR6qyznFq93drNuQ4vVgGRktJC+7FW/O53v3NVlYaTJ/mjlHAM55X18PDw8Ng4XnRihdgeWBpoGZOYOHUavvKNLby3JVpIKR5v1truvCbOOU6zD3qlEmMOVN3YKUr1LFNTU1wZU56RaKCBfoKR0kols05x7b3Pni6QKG7viyZHExUJZTI5R6CYmQlIQqVWVVW43+WzeZ33jfNcugqgUDwBSvhZUaWkg3z84x93ATT4VUmtwbRKFaLtBkj0ssukE0+U5swprbvmGpnEl045Rat7e3XNpEnOzFtu6ieFh+hmJhOgwAMkS2AWqTPlwESMTxW1uqNEOnt4eHjsDHjRe8xlnYHuXQKFQqL4ViHU5zp+JiKHB6LxalVP2kcTZ8xWNrVWqqjRQKxWiaDTJGa7NbxJ9bUtampsVF1tg6uUNHnSNCPRQGtaVyiXyxr3FFy6DeSazeZcIX7SN9g/ZmFqBkfsv7ef9XY33RsERPQsOZwQD35Ign7wq5I/CSFjMiXH8sADDxxq8XaCkb8z+w5VfdJTT0m33ipjQqWzWf3g5z/XZ029lqtQ2v+b3/zGFbQnXxXyZABBrd5y8mWKNkzIX/nKV55nGvbw8PDw2DheVGKlutLNTwduFhrotIRSh+7I1FrDqyM+JUwh5hTN9mr12qQiiTrbMqZU18MKCq0a0zLN1GZGFYm4GurrjDCLLtcxl0+qb3DQCKHSFZOgMDyz3cSjJVMpAUwcEiJmovQ95+ztij6gRtmWMnqoUQgJcy8lAQ877DDXRqKDKRQRRgxvNxgZWuNKJmAuVjot/fjH0ic/qWJVlX7/+9+76kjDC+Bj0qZoA35hijNQRYlJ2ctTYiBfrgFlGydPnjy01sPDw8NjU/GiEWvBmPT2BYHa+ktWTBC+Akeo9hqzf6juGzMCjGT7lQ1qNeuAE1VV3WAEKdVEB5GbWrF8sX2OqLa+SsnUoO2rqKVLnzXCpNJS0Zk8x48fp6qqSqPjqPM1YtIkd5UDMctNlZH1hT+/0M2mgjrFr0rlJEzCqDnyPN/1rne59lHxiFJ9FIHYrirOyN8FJ33+88zvBhOWUm3e8AaZDHXmW3JUmdqtHMzpSlTvl7/8ZUekF1xwgZudp7xABNcAvypVnSBmDw8PD4/Nx4tGrM+2So+vwsw7xKAG3mIUjrDwfmh9NGrKMhIom+xQorpF0YpqW2vrVDDi7VYum1YiVq3qynpFYph3TX3af/19A6qtqXOEjQKFACkgwWf8q5iBIQ8qMaUHs/ri576yrgQhhIQafcc73uFK6FFdiRxV9kF0LMXhiRAerUpFWwRO5De/kQhGCtXojTeWXk87zZE/s8PgDy5XobSfCGf8rfiFSathTtRQiYegOAQFI/Crenh4eHhsGV4UYu1OSv96inQX6BF+GGJQEBLq0CqmeCt9LCrd066BdNwpU/yxsSClTH+XujsyWrOqTblMXitXrtVgf9qYM6GWMWPV2dnlVCtm4TWr17iyhs7sa7tgphv8rYE15PWnn+EiYQEKD7X6eVOBEC9q7t3vfrdTbnzG5/qSl7xEhxxyiNt+u+Gee3CAMj9b6bMNBHT99UzMqoyRJ7O/UKyCoKRyYBomupm6vlRZonrUcL8q6UWcN5HC5Kx6eHh4eGwZtjmxUlnwX08H6s+EpGr/wpOOLG2hBUNvHanaq4MRYLx+umqap9rXEed/TbXeqf7OFWqsb7R95dXcNNaUaESFDD7UuKprqzU4kHLHyONbjcbc/uBx/K0lz26gPabP0Q++/wNnGsanSBGI//mf/3FTq1GekML6oZJ9+OGH3TRoBDdtVxj568orpbPPRtKXShiaCtVnPiM1NLiZZGgzBFoO2j9v3jy9733vc+SJOZiCEeUlArkGFIs488wzX+CX9fDw8PDYPGxzYn1kRaCFbSVSDbn0OdhaI8HSROR8VyoYUTINR1U5Zi83BRyRwrFIVsseu079/Ws1bmK9Jk0bp0RlRvV1dWpv7dJgckCpdEq5bE6VplbxpQZBzH5vitfeo1QJcEpEKvXjH12wTo1eeumlbjoySIlKS6TaoFZpC9Gx+FWpPERlou0Gpl7Dj/rRj0qk+OBXtXaRVmNMqkceecSZsZkUoBxUTaLOMek1ECmRvgQuhbPNhGCGG0zer3zlK4fWeHh4eHhsKbYpsa7tC3TnQuMBCLSMUPGfAlbRgHCBaEOFGZgqS1TWu43IVa2KplRZmXXKs6uzXZ2dHS6tJpstqramwREn+aiYmQMI1IikyMzlBgKXXPWlQqBzPv9FV/gBMH0ZfkXMovhVyU8lzQZTKH5JpoYjwGd47dwXFYw0fvc76YgjpAMOKK27/faSSfj1r3dmbFJoiO4tD6oiwpmqSR/+8IddqhB+VfyrJ5xwwtAWJVAbOJyc3cPDw8Nj67HNiDWTx68aKB1OiII4HXoLwnxVonOJ9uVbXtxi/4Sf+I44nCDbplSqTwMDWVVXNLuJzNesbbfvY6qorFBVJXOpuuLA9vuiovGIEQ3kWpCrEWw7OfUVp+ojH/6IfR9xU8FhFiUgCZMwqSeYe8P5Pq+99lqXbnL00Ue7z9sNDz8sLVkik6Olzx0d0m9/66KCc6ZcUaQjVU1iHlMClGg/5IlflXzcchA5jQkYRR5WnPLw8PDw2DpsE2LFxHrX0/1a3lMiSbfOlpA03QJ12ivEWVqHJ3VoIwjVFkjXBKoqYgU32XlVRUzTp87QtGnjFI9XacbUvbRy+Soj1qip1lojyLgRaFT5QkRZE6sD/RTllyPVSeOn6oIf/2SdGqUmMGoUsyh1f1l//PHHu+1Js7nllltcFO12rTrU3S1deqmM/UslC/GrUlz/a19zs9j85S9/cVPZEVhVDqZ5I7oXvzGVon7xi1+4c2H6tRBESEPK1AoePuuNh4eHh8eWY5uwxqPzHtc9j61wbOpUKqQ5RJ4QJy+oSEeq7hdD3z33yS2YjMlrJZ812r9Mk8fvYWq1XstWLFFra6/WtnYYiUo5I8qobdjS0uQij1GwNTWNzs/KfgJckr+40Ck4ACGhRjEJLzE1ePPNNzuTKSSKX5VqSwQ0bdd8VTsnV/SByGWmgsMkjFKF/Pfe25E/vtXQHxyit7fXRfdSNYmUG3zEkCcEXA6K8BPMNDzf1cPDw8Nj6zDqxErVox9d/Asl80N5lI5ZQanzR6lCqBx5XRSwI1wUbGgALplzY/a5KZHRxMo+pXp71NjQ4PimqyepxvoJam/vdnWCu7p71WPf19ZW2X4LbhJ0CvBDRrlcXp/55GfXqVHSTe666y6nViGWn/3sZ67SEooVFffTn/7UmYSJDN6u+OtfpVmzpLCG7/33S8uXS2ee6aomoULxqw6P7sUvjMkXJQ55Yj04hSCnMqxdu9blu+JXLc939fDw8PDYeowqsRIw88e/Xqu17f2qaZgAQ5YWXobeO5NvSKjArRv67NaVCDYWC1RfkdfhM6TZ9QP2VdYIoc1ItUeZtBFuY52qauKKRauMFKtsXc4IttuIJqZ0MqOBgR4jyrxOOelUV+iB41JQn0IJYYDSxRdfrJNPPtmpOQjouuuuc1PEDZ8N5kWHkb8eekh65ztLF8aI0BWGOOccFY1IIX/SZ4YXq0CJU0WKWsDUPCba9+yzz3bnHoLJzYkSZuL24fmuHh4eHh5bj1El1jvvu1N/uf6Pqq+jWlL8ObE6hHVq1b1/rrN32xHNay+OBKJFNcczmtmQVV2u201gPnXKHDU0jNPK1SuVz2W0dNkCZ+Lde5/9FUtQaB9Cjqm6qkZFU551dbVKDWYcmX7iE59wRISSO+uss5yau+2225yPkRJ+4XdEzrLtdvWr9vXJmFP6whekiopSCUPyVamGZEQK+ZMqFObZhkCJ33777c6vmk6nXVASirQ8KInBAxWlTjrpJM0JZ8Tx8PDw8BhVjBqDrFqzSuf/+Lvq7VntlGUmmxqauYYZbErblAknR7Lus1tn29lrYCvYtj5R1Mv3SujwParV092qiRMmaNrUOdp3732VG5QKxQplcnENDmTUP9CtsWPGGtlMVmNTrSqqSlPFDfT26/DDj9CNN97olCkLEb9hoA8Rsag2iIbvKAN4xBFHbN981Xy+5Fd9//tljS2tY2q4vfaSMakjT0ovfuADH3iBCsUvTOUo2s/54FcdXuyBHF3KHm73ydk9PDw8dmGMGrHecsctWmFqkqIMldWNxpOmtoYIEw5wRSDca4kQ+NeRQ0muuv9KKTiB9h0vTW+Kqkr4S6s0afIEmSjVYH+/keh0NY3bSxWJGsViEa1atdDIol3VNXE1t9Sqty9jijavXCbLjl1pw3ApV6IcG/9k+B2BSuVktV3wt7+5Ccpdzip45BFp3jyZpNaAqfaLLrrIlSwc7leFVN/0pjdp1qxZjnghWkzc5cCvSmlDShZu16AsDw8Pj10co0asXV09rgBDcjCi7u4+1dbV2M4pjl9SrSwlMg0XPkG8JeUa+l0rY0XtOS5qqtSo1uTrxPETFRh5DAz2uwjent5W9fe12c/sWMkBtYxpVDqdVSweUUdbt8aM28Ntn81mho67k2DRIunuu6V3v9v+KnYxKGGISfjrX1/nV6Wy0rRp04Z+UALFHbiWp512misWQWlDUmvKyZeUG+oIY+ZuJsLYgFkYkzGvBG2RglQOPg8MDDji3lxwPPbLb3lfjnC/HHNLwKCBoLPydnEefGYZfh74/clZ3tLjeXh4eGwuRo1YKxIowkqlrOOrr6u3jmxQuZ5nrQfP20GGiDUk0zKgYFnPNyxN1RG3ZPPMnRpVY319SWlG6TjpsHOOfJODfaZMixrsy9ur1NI0RhMmTTQ1Zko5oNh+ich3CuBXveCCUr4qpmj8qqZC9aEPOb8qQUgEGg2fym3hwoWOWIlqhsCoHPWZz3xGDQ0NQ1uUQNlGpsIrz3fF94xJmPrAREgTKR2CeWeZeICoYkzlm0OutANTNfvm9Z///OfQN3JT8dEWfMEU5NhcsuN3V111lVPuzDYUEjRR3ByPClqY/kOQkkRVKn5HChJk7+Hh4bGtMWrEWtfUrJr6Sa76UWfXKj1671+09OkHrFNGlZZIM7TEjmRydWvsH1JsYvZ9oVCqluQmKzfm7B1s1bPPLlZvf4cKRtbdPR2qqKxSLJpQNpcxPoqrrbNVPZ2rHVknKmJDO93BQWdvREF5QmcGBqTakO7z0peakF3kij0QYFUOfMREOGPaJZIZpUqVpb3wx5bh0UcfdWUbw3llQ0CWmIsxLTPRO5HEYOXKla4iFfmxL7XjkxdbTkgU9S//jFp8iAjmIfAdwVEETuHDfj3nZSA/mBKL73znO92xKCFJqckQFLUoJ3AIk5KTIah7DEnSLvb97LPP6h//+If7junvGFB83dT9a17zGrcO9U7qEduTaoXK9cTq4eHxYmDUiDVRacTasp+qaqZqsLNX8++7Xc0TDlc0XvLnOVVqRMfrc/7Uodhge4+SjanoJji3F1sfUSzO+qJaO1bq1tvvVEvzbHX19qh/IOOiXXOmaotBwUi1QitXrVR1jZFsus8I3gg3EXX73+Fx882lmo1hrqmpOt16q/Txjytl6o88W0y4I1VNetWrXqW9995bDz74oJtAAPVZDvyqkNn3v//9Ef2qmItZv2zZMkfUgOnzDjzwQEfIKD6ijMtzXdknBBeaWPHvDt8327OOlB9UJaDEIulBzLRz//3366Mf/agqKyvdd4B9MUkAipe2/JggrjKgwk899VRnvWAhSIs2AI6Hn5zjsR+AyidYjeNRSIO0o3Ifu4eHh8e2wqj1NLFYlSbN3FsHHX26JkyZqP0POFLjZ+3nVGNIquVm4HXvHKm6N45UK6MFFUy5RCNFR655U7zznppnxD1VjWMaNX32nkoP9qm5pc62jyljiok81vqGJiUHky63NVegwzUC39EVCn5VTKVGnA6QAibhc89VYGSBuXSkqkmUW8TXSNWk1tZWZ7YlIrh8IAHpQE4Q40h1gCEmiGe//fZzag7VCiBoVDLkij/2nHPOWUdg4NWvfrWrWoU5FvMqM+JgZg4ByUGCED7H4PcMBFatWqXVq1e79fiJv/SlL7njhjjuuON06KGHusIXDBpQ3+UpRezrPe95j3tPdDTky7E55+nTp7v0IQYfFM2AnNmGc+H8+J6o73KF7OHh4bGtMHrEansa7GtTTWO1urvWKF+IKojE7AAlUi0XC6jVEvCD8l8J9ZWBxtXhH6WDZruSSe9hU3EV1WO1snWVxk09UJWJnAZTpm5jCTU2Nrop4xyn2O/S2aSisQoXSPXcnndAQCq/+pX0qU+V8lUxg55/fqkoxNSpjjwxjQ6vmgSR/uEPf3DmUL6nZCFF+LkOIRhQXHnllY6Qw5l8hgNTLORF8f5jjjnGzUOLuoSEmRAd8zJmZYr3o1JDQGTMkIPqhMDKSRVQFQpSxid80EEH6e6773ZmXEgPkmOGHYiViQGWU0mqDJieMfHyNx+epxuC6fEohEEwF8SPqRpCZr8HHHCAU9kQKteDdvA6e/ZsR7RPP/300F48PDw8th1GjVhzuV4lYiktW3ifokHBVGPG1mXdEZyS4n/Hc0OEx3vMwbywmEIdV1tU7VAwa2A/JACpu79H7Z0D6k/Zuni14pUVjjgLxTo1NDUrnc4oUVHpZrupqqxTPlPQhPHkgEaMzJ8zYe5QQElT9/ekk6Qw19TIwtUEPvlkp+4oBIHaLFehqDSqRlE5CcKguAWkccghhwxtUQL+SgKQqH9c/vtyMPEAvlsAyUKEmGbxR+IPBShVCLHcDI3KhNSYFQhCJhipPAiJwhvsG9BeKlzxe8gaEgQMCDBDlytptsXsjU8UVYwiLlfKAFK9/vrrnXKlHZA75xkGLOHvRTEzWCDQC7Mwgwz2w/GGV6ry8PDw2BYYNWLNZAaMUAfVXFOheIURYKLWdWauW3f+VLeZe13X2fNSWuE+jq+JKm/CLWtLTzbiRNyq1k5HsBMnTFO2UKtYfqmS/RlbF1X/QJ8rCBFnInPbOJs2wgpiylgn7Y49amc3yiCtBrPvq15V+oySYo7VodloCLohGAfVGAKCIEIXwkBJ4jvED/qOd7zjuetpgLwgvuF1hIcDEzNEBBHiMz3vvPOcX/SMM85wEcP4KCFNCBQ1GAKFTIAQKhECRH1SdzgE5ln8nbfeeqsLgqIdDAIgbMot4mvFdA2BhpMiAFQ4ipWFc2Sw8DvmoR0CShg/6W9tQEJAVFjk4thjj3VEisLneGxDZaqjjjpK48ePd9W08Bvjp97u9Z89PDx2C0SMkIL1qZrNwTU33azfXX2l6qqatWR5n058w6fVOHPfEndGA+c/de/tWBwuTIdhbSEoqsI44KjJgXoygSY5c3BBs5pMWd11my79/e81/eDXavrEfi197FrdddtS7XfMm7T6mRs1mMyofU27DjxkPxULEa1Yvsr2l7MTCzR1/DTdccdzaSQf+chH9J3vfMd18KSBdHZ2rouWDadao67wNgXmT0y+P/qRTMqVTMKf/KSbDq44c6YjLlQopFUO2nbTTTc5AoT4UK4QcHm9XwYX+DRf97rXOZ/lxoDPkUpMEB/KMgT7YT1KMyR35mylTCJ5ohBnOUJlGoLfY/6F8IaXVGS/+EuHzx/LgKI8mAkM3+/6gGJmvxxr+GCE9ex3eAqSh4eHx7bCqGm65GBW0USgivqxqp9ygAoJ6xCNOUuFH6BQg73Q2ZUil0oEy4eovSE3tSMVKJkLtLQnUCoX0crevBatWKMps4/RtH32U+uy+abIiqobO1UN40hNKaiQY8krky4YyQ66Sk1NY+pVVRk35byDVRjCZAqhQqSQKpL8Jz+RMaEzCZNeAmkS/VoOSArVBblh6kSRkrM5vIj+n//8Z82YMWO9ftXhQNGi4oaTV9T+RuNXrVLd3LnSvfe6Zebq1e614tprZSMStx1txQeLcqbiU7hgosVsS97qPffc49QvJM59gB8XtV2+PQtpPOF78k7ZB+3ifhm+/+EL5mDawUCpHByPAC1Pqh4eHi8mRo1YIcmB3kGNn7KP9j70JDVPmgqPuvUsjmTdmvB9CY5j7d+KeNSINaL+bETtRrCDRqzPtCfVPZhTw/RDraGBVi59Un39KR185MuVL/aquqbaOt9KVdnr2tVrtXLZSuWiTcrbb2MxU71lvr/tDkj0l7/EVurmU3W44YbS62tf68iTkoPDSxZirqVqEkoaZYkpldKF1DUuB2RFoBCBTFudVoLP0o6jpUvXLR+h3bfcIn3+83bXRJ1yJZKYHFmChda3YGbmvCA50nqIJKaC1kjbskDIRDizX0CRiiuuuGLEbcMFUiZ9x8PDw2NHwKgRa1VNg5KpOrV2ZDV1zt6KRePWmZKxajDVAZGiPuhgnWodAu/4Ft9qJh9RMh9VphBVdyaiNa2rVIzVaNKcA5TQoLLpvCnSmLq6WtW2er7r3Ht7exSNxxwZ5fOB9jnsVNVUVqm3p9+47LnjbHeYcnMVlkITrxGII9ZPfEIZOw+KPUCew9XV5Zdf7qJpKYIA2aBq8U9yHUOgAgn8oVgEZtatAilARmb6ylekt7993RI74wyqR0gHHugmS8D/SnQwRE7lo5EWyB9zLqZ3FCtKm4As/MIjbc+CSsWHjPkWIiZamSpLI23L8ta3vtVFSqPSN+RT9vDw8HixMGrEmkn26/DjTld1y1QV2e3zIn7tX+O4kAzcS9kS2JIzYsXvmi9G7NU4KFNUT9tKZW2/sWhB3aufVDRRo4FkUR1d3WpuGKv+gaxtW1QQLWIUVn1Ti1qaEs7Hmsnkn0fg2xUdHdJVV8lkVenkjWz0gx9In/40lQ9c8A/lBvfZZ5+hH5RAYQPMqUxpR94qkbKQbzmBcI74Pt/ylre8YDabzQbFHDBNU1qx3DzMdSQ1CBO1HeO+++93Chtf7vpARC4+YHzBtJcZdyDifffdd2iLF+Kpp55yEcVhzinFLVDwI+XhhiB6GpM4+/bw8PDYETBqxNrZukLpvtWqr+x1HXFpNpsSucKqUBzLELcaSmvcOt4ZuxZhWFvB5xwEW4xpycInlR3sUaq/S5lgkmLVY7XPIa9UaqBdFYlqNTaON3VTrVwhqXR6UE8+8A9VVMRVVW3K7bmDbT+QMvK977mIX+r+Oj/rz39eMgkbyVA1CfMnyqtchZI7isL79re/7YgJkkGhlUfSgmuvvdYRz3C/7GYDUzXkSQnCYcfQv/9dUttvepPabFDwx6uvdlG26zM5Q/YoaCKMMVvjIyVaOSxvOBLw13K+BF+hVjEfE7m8oXljUfAEdEG+vqrSrgWsMFT14v7GR88Sugc2FQQoUuoTqwe/Z9CGBWVTQUETcqbx4fP7NWvWuPUE53E/k+aFqyYEbeYYxDoQI1Cehuaxe2HUeqPK6jo9O/c2ZToeVsIUI+bC8D8AZzxHG8//juAl1pG7WkJgqregRGWN9j7qDFVEU+o24p65/wmaud9xahzXolWLn3UVmioqqtXc1Ki6mlrFY8x+ktFAX8oVj9ghYAThpoHbb7/SZ9JqiAQe8quSekJKSzkx8EBSNYni+BRBIHcTcyqpKOWgCD/Ewmw2Ww38p4Dc2nIsWUJUlPTFLzrCPN86j49+6lPrZskZCWFeKZHN5MiyLSp0QyAaOpxDlnrFpMtsaLBAHisd75e//OUXlFT02PlBeUpqUBMNTyoV5S4huhAjWaOGr+N3kCKpX9SVJj4hfM7Ydvj2w9dxH5IGxrFJ9wrveQiWNDVKhZYTNbEAFGXhOcVaE9ay9tj9MHrDfGO1wG7aJYueUT5vozh3f7L70o2KGC2h9LlEtCVqZeF+5pvQgFzIZdW6tk2T57xEseRy5Y1qJ8+aqamz9lN321JVVMWViFeqqoo6sXHFIpV2tKiR7izl8gVl8hkXQbtdQRF56yAUTixuROoKQ3zmM8raoIDSffgoy6N7ebD/9Kc/rYvufeaZZ1xQEjPFlAPTMLPZUBqwPMVki4C/l06AVKNy5UenQRTzZz+rwFQxgUhHm2qlotH6QDlEckeZcYcBAuTHsiEipgPC9Et+LFWXbr75Znde61OhKAY6rre97W1OEXvsesBqgfsAUsP9gW++fI5hBptM3B8SIc8Jg7MQFAWhdjbPGPELVPLiNUzpgqT5TJoXQHkymIXQQ7At6W24YLjXwviFKVOmuIkkhkfTM8jl3iS3m0Eiattj98ToEashHomqtnGCkWiJIt2r40n7x93/KNESmE/V5bLaV9TdLwcG4qBvtarqWlSpfi1bMFf1Y6ZroKddHd05xe2/gu2osiKi6irm4EzZcSuNjKarubbGdlBQvpCzfY/q6W0ebISrSy8tkRU+UUxG554rfe1r0lB070hVk/CpkjpC1SQedjoLzK7lQUkQVmhq3Wq/qhG0m10H1TvU6TjQYRmRinzYffd16oER/Bve8IahDV4I2ovJGlIlBxbfMcqT+sDrA6UN8ZMSCUxnWB4BvT6wPUFewydzB5jj6HQxK5OixGdANSnMeVgImCJvc810nBsDAK47HS0KBjAgIOWHIDP+ppi0NxfUR8ZkiQmRafFoG/vletNerlEIFBLnQTsoGBJWs9rVwH3N35jrDmFxr5e7SiAunhVSsyBVSngSFBcCKwb3HmBqRWIYygMDQ3KEuLmG/A0gX+pKh4AkUcxYhohm5++xITAgJk6Cvx2kH8605LH7YdSYZ8LUvZWLNmjtmifV17rIiLNgnFoiWFB6KELjb4lw+cat5b19YPTJ5yCXVKF/rZomzFTb8rlKF2rVPPlwVdeN04Rp+2rC2GoXdTxr9lRFK4xoE3FF4nkNpPo175G71T8wqDEtY9eNZl904FdF6Z19dsmvGpIUATb24IUzrgyvmkSnTIdJtSLUGqRKgBDqtRxhEX46l60C7cJUTd7rnnsOrRwC87OuWiW95S3q6+93UcAQ3vrMrlxrOic6q/3339/5VVGvGyPicOo7Rv+QCPWLN0bE//73v52CGUnRQlCY4xiY0GGifGkbFZuo6MS0dfjqyqe6ox2hcgmBCbu8pCLqg5xY9ovPm8ED+6UDBfwt97RryHUK7zte2U856HSHkyEdN9HeRDcz5R6WFtpDLWVItDw/F/LFz047iIpnQBIeb1cEflIqfw2P+OY+pOALJlksIvjZR7KKMLAijmEkKwtR65AvpE3JzeFFVYhOx1JERD5EjPrdEFC4kDEDLH6zoZgCj10bo0asDfUtmjzzYPV29WvB3DsUZJKOMEMyRbyWlGwJ65SrY9Kh19Jb5XMpre7JqGrMeMWUV/OMo9Uy6ygj1hpVVFeps/VpVSRipgTTRq4zrIPJKZPKqc8ItaZ5sioqKpW1jqlE7C8y6OQo8YfiGj+eKKSS/5LR7lBqCKrsfe97n+swCVIKF6pCEQFMx4k6omoQJFW+DYXkIQ/8sltt6oYU7BiuQEU5aCvlBI3gs6aeiDqmE8PPuz4QtAGJEJ2MOsSMR1nG9RFxqLrxwzLKxxeGee5Nb3rT0BYvBGotVMTrM38z4KAdEDWRwuyXY5HriqIgWhlCKlcv/E3Yb6huaQfnXO4/Y5+sx3LAftkf5IfpGhM5+bT4fSGBcLAEiTJDURh0A1GzLYOOckDIECTXIiQHAtLw1Q2vUEX78fHRDgYKEDLnsyuCAQNqdX1WGQZugOtH5bSRBhiQKtdspGeFARXfUx6T68i9Uw7mEw4Dlvg7kP61IXCfMRDgb4eViXvEY/fEqBHr6mWLFaudpJZpr1TaBv/9XaUZUYIhwlyXfuP+ee7VNcBeeSRYx+psIar6iXu7Yvs9qZjGzNhfUetIulqXKp/q1mAvZfHyKuT61dnR6zqwhD049TUNGjN+in1XaTf5C4MTXhTQOTOyNRWi884rLeSEnnOOMwljskKZou7w34QLs9XQWVL7lg4b0xPBTd/61reetx05rJDq8HzXzQYdBkFJpPyEoxpgnYO+/e2SCds6ecyuKMDhJutyYCIjejL0q0JK1OwtrzE8HASU0OGhyBlgoFb5/foGC/wtuSaQz4YULfvgGobKgeuF2mHiAtQxipiOrzy1CYvAaaed5syCqETIkIIT5dcYhRgqEK4JAwj+XrSfvxdKHRMx6icEgwqUNeZdUokwTXMsCLEcXAcmXqDjZnBVrpSHg0A12gpQ0WedddY6v+GuBgYMWHdGSrcikh5XA88NlhQsQJjkhwMLB26J4eBvhgJlIgnuVe4ZLESQbQjuEf6G4cAstL7QLgiXwRav4W8IdGJh4ESaGW3y2D0xasQaieQVi2R19PFv1OyDj9eylcucKg27bPc69IF+nPSasu7cPvOPe6fq2mYjyKmK2jaT5xylaKLS1f5NFWtMiQ6YWql2nXZtTZ1WrV5lo8kaRaIR9Q8mle5bq1giGBrFbwdipY7uQQeV/JYEU7AQETxEMhSGhyx5iMsXombx72DehFwwXQ3fhoXi9xMmTHD72mLYQMTVKzZFaRdzaKWBP4Idw3p+2YGeV5BifaBTITqSETpqC1XI9G3Dp5MrB+TFAAMTMCSCKQ/CGF6isRwoATq4DeXOgtA8DPlxnSA27gX8rqyjWhQdahi5HAIfHD429j98ggAQ7hczNPuj4wSYIjHJsz/8rpieIfUQ+IopRcmMPAwOQlIMwba0EcIPFehcSkmuB2E7uB4QKkp3VwUDIkgPM+xwMAhBUXLPcR0wBQ8vaQkwyb4qnOyiDFiD8NFDqFgYsA4wOGIwGwK3AWkzl19+uZu+kWAogOUIpUvbIFysFYAa2pjyecYJqhvpuB67B0aNWJOZnB697UYj0wpNmD5He8zZ34izFJzk/ikjVT6Ec7JyUw+tcuAlQucRYT7XqBINLU718n72/sepripQMRuxTrbRtkkoOZhXdVVcmXROtS3TVVVjo9t4hUu/Kfdfvqhw51u2DIM75xGWcoz0PctWA/IkMhl/73C/KtWhMAO/+c1OVUPk5JUOL7ofAqIggAZSYO5V1AXznqLm1gesCyhvSBUiZeo7ikZAxusDRIw6Q5lsyjXALE1ny/aURETd4NfErE50J20m8KUcKEb8peQNo77LJ2EPQd1j1CXXhAAziB6fJ2TMvhksYD5mfQgGDvh3OV86c5RrOWgHlaXKgZraEGgn1xHLBcE15cfblcAAk0kyRhpwQYLlSp1tRxp0QaxsC7gHuBcAZM0gtRz4WcuDl3AnQKbve9/7nP81vPfYhnbhV+c1tH6QZ47LJFy2OrDQY6fFqBFrXaON0vY7WnXjJ6izo9M64yojSSNH63zD0oblXSL9ezncd/xjC40ifrjIr2xDoobJdQ0iRfUuv1+5YkFjJ+1thFpvqjbuFERdTYPGjp+mPfY7Qk31YzR+XLMSCV/i7gWwEbhaW6Uyk6UDc7BecolLrTE961QdnQYBO+sDpjdIj+IWqDUICwJZn2kSdYZfldE/ZRqZlBwyHl4coxwoYtKK2O+GIoVDQIoQFX5oOjp81ahPyAqfHH5UXsvNsfiEMc2jQIjkRFVidi43yULQmJkZCKBkIFE6c1KiULHslyAklE8YaAPh4VPFdM058nvaRxRrCDpfBhZ0+ihVJkXA7M6xsRjg/+U6QfwApYpKxTLA+ZHatD7zucfzwTVkIOLhsa0xasQaxCo165DjFaupdhWROrp7rLNEedli/Bgqrhd2oCMwLL+xF/JSI4H9awuqtZDpVeuqxWrrbHOVl+pr600pHegKRARGB71ty5VK9mqwv1vpzKA7tkcZCFQisIpiDUMmRQcIxFSkWz9hgqtUgxk1TFcYCagvfIqYPgHExAh+QwFOKC3MdQQo8Qp58/v1KWKImDlWX/GKVzgi3hSgnAlEwrSOeTqc1xYlyiAAUysmX3xrISAxfHWhyRElg1IpD17CN0oKT7hftgcU8cAHzX7ZnlmHyu9xTIPMUQvw2UKu5WCwgNLCH8fghOuIT5BzRzXjNuCcwrZQiQpfMO1AkWMCHQnlvsJysH59320Kyq9JORhAD4923hTwO/bJKyp8uFof/pntuC4ca1dV6h47P0aNWFvGTdbkWXspZrscO2GSps6YbuxoN75j1aGNjP54MFhKJGurWBCmfL2uQ+KTfc9b+wfFGzGVGk2vVbxmvIqxZnWtXWwPpFRdW6tCkFc6l9Fgb5eemfeIkWtSgT2kfiRfBvx+3/8+TLDO37sOkC0BQYcf7maeYVSPWh0pnQVARPgqIa0xY8a4PEF8XRsiYlQhAUoQEn97lCsmtg35VVHE+LPKA4I2BlIkUJHhAukByPXlRx+tk4491uUPl4NBBH6xcrCf8uAlIk/DfUK84T64RvhnIVDOvzwthPuvPEgKsE8ULAo39MWiUjFXso8wXxnVzwAA8ySvYWnH4efHpO7lQA1DvCh8nrNy8JnCGiMF+WwMmLAJ6sJXHLa7HAwsuCeGH3Nj4L7AR01QGgr82WefdevxWxJZjv+5nFwJesN6QLQwgwt+7+Gxo2HUJjq/Z1lBdy0uGCWayoxHFLd3mfSgdTSVSgwpkucO8xyBxq3v5lkslUAsmX1ZT5swBds7U6y2KtutJf/9kwYy9ptIVKlVt6ixeZqy2S4tWrRYa1Z3KBYZq0iiUoVUqyPisS1T9O+bh0r1GfB7bPOJzukErDNwfszwhI1AXPqKARMeHSudcTno7DD9oYAgLvxnBAWFHW0IzgEf5WYFMHGBaQ+pG29969DKIZAScPnl0g9/qD5TMvgPMaWub/90nJg3UZmkBpH+g3JFJQ7PNQyBQqKjp5PElxr6Ivn9+u49TKAQN37eDZGvg5Fvq+272UhrferXDSw4V4LKjGAJSqHjXl+b1weCWzDfYirmvL7yla+8IFd1Y8B1QfALCh5TexhYtbltQYFjukZBh+C6YuomsAezc/ngiNQjVDembIgsBG3hngwHErSP5wFSD39PKgpWCogVYisftOKP5x6A1MnjDf+mVDFCXYaDC+4d7nF8lOGxSFciehsLAgE/4XrIlP3SViwo+DtZh1WE+4+BHNee9WEg2caA/58BAPedh8e2xKgpVuVTiuazLjrX5Y/as7X0mfkmWItOtK7jUkMpcCkkUUPYuQ7rZNmTW2VLYWC5kgMppVNFVcYKWrx0uRKJvPr70spnIsplo6qsa3TF/2vqWhRNVK17wHd7EPZP5OIb3zi0YgjWcVlPK335ywoSCWd2JadvQ6RNh0vnSJoH5rjQnLs+UqAzxd+J3xBShYhHKo5RDjpQ1A8kv1FSJcL5F7/QBDuHCkjTlPCIC/mxVEuyjhtyJFUD9YZy3tQFczJtJv0D1YaCI7J0pG03tFCYAMWKGRi/LNWDILyRtl3fgp8VAoRYysHnkQYXKH/U3UipSpieOT4kyKAO4uJvW07KbDOS75zrQLAY5vrhf08i98NUIwCx4/Mevh9MuhwXX3Joamab4YPKsChEeM6Qu7dKeeyIGDVibV82300d50gzn7H+Lql4kFHcHgb8o5Ajz13p4YMwSw+h2969hWyHEH4XLkFBA+3zNWXOARo3eYYGu1Zowthp6mjvsr6y3zrKdjU0Tlbj2Kmqqk5o8ow91NHVoWxu10yc3yxAnpRWxCdof4t1sE4ZlaoPftD5Vekc6bjCCMqRQMdMBwyRsi1EjC9yQ0QMiRKUg9IJI41RohuKNP6dqXvMqvgWNwiU+NVX43h0ZmzrcUdeSMPA3H322a4TpyYsZmjaTSe9KQvtJTgLfynFAiBD9sVEASNtv74F1URuJYoRpUtbSMdBqY20/UgLwBe7IcVfDgiY9hKwNdL2RDTzdyT/mIESZu+RykUOB38r9otpfKRcU9YxOIJcye9kW1wB5cQKeWLmxofOYAOLEvsdCRA9gW/8huheiNirT48dEaOnWKnNq1IwwTOP3aO2RU+qsXmsMqleZ4bjcR7+vKxTrIZ1D7y98I7PrOJ9EKSUG2hVIVJlnVqtViyap7HjmrRkWbcG+pMq5AMb8Q5q7KRZ6u3uUH9/jxF6VMGONNH59gDkaR233v/+UmnFclxzTaky1LHHOtWEaRyTYrlKKQeKAoXHpAH4BPFx0ckff/zxQ1u8EJgOUVeYJSEmyABFzO/XB0x1tAdFvFGQMsOCOX99BEM1HXJ2TdGa7HLqGeU83BS/MWCuZTABIaL+iMZFPW2OYuJ6MLAIZ+RB8ZKaNNxPujGgKPG7bihXuByYWjFbM5kDZmIKGOBLLwc+Y/7GRGkT2bwphI0pmn3iD8WVQWUqVGk5MUKipGNx3SHF4QMqiotA5ChiyJX7amPBVeSw4lLB/Dy8MpWHx46AUSPWvt5ePXr7dcqn+vXY3deqdcED6li5QE88xLyEz68k4whzyByMD9Xlu6JY7YF87nEufc+2hXxWra0D6h3MKdW+QGPHNGrl2hU68LATlEwPqramSnX2YNY0m3IqpNXf2a7KRIUR925sJqJzs87HLn7Jt0oh93AheOW221wgU//goCNMUkzoIFFTIy34zoiaJWAGXxqqEvMfJDjS9ph8SZOhYhE+bYgIYoFERtqeBTMzneWGcmfXwdSN85cSZbshckOtW8dOkY5HbYD3tKnmTSLtMkBGmDDxv6NSKeLPICT0B24KIK1ypcx+CKja3AnaITD+TgT6bCo4BmRJZDOkR6BWeeoSbUOp8vfEmlA+68uGwN+VNCL2G9bzHT5oor38XTG9E+Q2PI8XIg1zS/Hj4jstdyvQ3nKiJmWGQSDR1xAw77cnaBt/y63B1v4e8DdE8YfARM+64YFm61sPaAfflV/vzcX2vhac1/Bz43yIOB++b7Zj/fDzDa/R1lyHUSPWgb41evSuv2vx3IeU7x/Q4mce0l03XKyGukbFrZMs+Uufo03Tk89TrI5ErTUl0i19BryNFvNq64urwQgiUehToqpa+UJCbW0rNX5Co8aNIcUjUH1DpeKVEesU+jR50kTrnHfjeTpRq5hJAWZQUwzrls9+tlRi0QYjdHqoBgoeoCrWtxAIQ54nf0OCj4gGJqdzpG1ZMBPjs6ND54amY6Uz53Wk7VkIRkERbih31oEHx0hbTKW3AfXrJhJYsUJ629vU2dWlS428P/ud72yWysTnh2+VkogodCos0U6iczcHFJKYPHmyG5gQ+crAAaJen4VgJPB3IuCK4LX1/Y59Qzb8nVB1BIFxXNrL7zl3yIn1gM6DQQ/qF2Kl4hekjSou76DYL9sxmOBviDrF1IvPFvXNAAv1WE6cDJa4r/AHQ8IMmAjSKq+QRMEOygKSC8w9RsAe+0OVcn9xzbnfaDudHdYPTPLcJ5SY3J6KlUEDAxKqhm1JJ4xrBTM5AWjlpLi54O9ETAL7AgxgcdkwkMEqghUC8DdiEE0wGGlcYcUoXAWY6vk9FhW+31xQ6IRBMRatLQEWFAbrBKuFfvbNAYMyzpeBPIO1EAy+CKzknLinKfICqJiFBe3vf/+7+z68Jwnko+9iXwQobkkKmYP9Ueye2Hr8/Ne/CmYfdmxw8nu+Grzuw+cHR736rGDvw14WvP3r1wYX3J0PLri3aEsh+Ml99np/IfjZA/ng5/fb8kDBXm2xz7+w9xf+txD88sHScuF/88GF9vrzWxcF3/v7/OC7l14bfO+C7wcf+PQHg4996cPB+z75geAdHz4tOOX0lwZveOdbgjedfU5wzMmHBKe++YTgtDecErzilBOHWleCXfSgvb3dvTcFElx++eXuPXj00UcDuxmHPm0F0ukgeN/7gqD8ur73vUNvguCKK64I7I869Ok52B88sA7DvbcbPbBON7AbzH0uB+ewdu3aoU8bQC4XBJ/7XBAkk0MryvCpTwXB6tXu7UMPPRSYknLvN4QPfOADQ++CwB7WwAh56NPIMJUXnHvuuUOfaMrn7JJs+F5jv0YKQ582gCuvDOxiDX1YD9asCYL3vCcIursDI/bAiDG4//77h77cNPA7I9XAHkr3md9bx26X1q7tZsDUu/u72cMf2GAj+PSnPx1YJzf07abBRtbunnjggQeG1pTu2UsuuWTo05aDNg3HSPfe5sJU7wuuFfc251IO6/wCI9JROeaGMH/+/MA676FPW49uu7d4bo0MXnBvz507N1i+fPnQJ7qDYvCf//wn6OvrG1pTuj7WcQfHH3980NPTM7S2BO6Vf/3rX+4eDGFEGFjHP/TpObDOFHzw29/+1n3+wQ9+EFxzzTXuPfce7QPvs37JSMe95/nlngRs+8Mf/tC18ZFHHnHt3FxwXrTjzDPPHFrzHGyA5dpRjttuuy2wAcDQp9I9yDNx+umnu3Mvhw3iXD9VDhuwPe/6ck/ZQCWwQe+65xUYmQaXXXaZe89+aB/H+tCHPhQ888wzbr0N3AIbULj78HWve92658EGClv8fI2aYs3n8urr7dDCx/+lzvblytioI1ZZr1TaRh9ECpcpUV6cJZhXFr5z756P8DfxqibVjZ+qZYse0rJVy9TR3qYBG6EUg4iymbwG00nVjJspFXpsFD1RdfVT1NeXt0HDlkt5jx0UTz4pMTvMBuoXO7X+ve+5gheBqWR8jJgrN5RnOxIY+doz4vIsUXiMqEmD2py0GIo+oA5Y8DdSiB9f4/Bc2g2BNmCKJ7KaiOLnAaXEqLq9ffMXahL39zv/JqqF1JdwoXRj+ef1LURYl/trUWHhd4z2Of/y7QlgK9+GhSAuVHQY1IRiKf9+UxeUL0r6xQIR6+tzWVDtC7XIeWGxwWLBPVQe5MVvsQCM5M/mWnDtsDoY4blrjOIaXiaR8+XcCUALgRoL87JpI9YGTJ74xEMXAG4dXBooZe4tTPjkmXMcrCqbCywHw6O4Q7Bvzh/3EOeCeqRN5RH/3IMjBcABrB2kQqI2eRbw6/O5PGgSSwxuhOHgN2HhF/bP34B7lmsUui34W5H6xnfcm+F9yO9Iy+OYm4vNS5zbABKJClcJaTDZ5/ye0brp2ueIQ7XXoUc6o26YowrXcRu98GaCcEsEzAbht84LW1GnWDathH2ZykaVzER10D4n6Jm596mQj6u2vk6zDzxG99zwW02Yajdepke5gl3I9fyhPXZSEIhknRXT2dndP7RyBOBXZTaeww/Xk/Pnu4Aa/L2bA0yPEDJ+UUyQvFLlaHNMj3SoTDBA5CodHfmfmKw2tzg7AV1EE2OyesFzY+0U1a82ZBIfCdaB6B//cL72gnVqtJNONuxUNgV0kphwifjGBEeULibIadOmDW2xacAkiQkOtwT7xNSO/3lzBjBca0zV/J0wfZcDfzH7DcG2DCTCCOttATp55lXmbwYBQCIbSjEbDkz9BPphHqfgBwMSIqrLZ4zivoQcKaACaYUwxbXO3cF+GKhw/gTKEbhG4B5ZAOF14Lfcl5hxMbtzDQmwGy3wt6Tt7JcYC4iKY22qSwbXAG4oBio8B5hteRY3FofBccqvBdee8+V6YCIO1/PK9eU7fhP+jTgug77ydZuKUSNWbt54vF7jpu6rvV/ySu135HGqsE4o7vJJnWg1soRcI8/zrdJg6gKXVj13Ak7BmqwtjRViqowUNb6lWssGs9pjv6NUP/0INa16SJHKscrkAhV4buKNqmlo0uJH52nWAS9XsbM0X6PHLgA6xgsuKOWj0nGWdZTPg5GoFixwkcB0FnRKX//6110nXd65bgg8YOFEAYzwL7/8cud7xE+5qfsAjMz5PSlM+Azp+JmLlweVZVPAA4/Ph4HB8I4oam2Zcd11JR96mWLZKKxD1Ve/ShknNxsTnWyYGrM5Pl/UAMRKBxeWY8SHh/99U0HHR8AUxSE4NhMWUPAestjUzoxrid8X8hppYMB+ue5YLBg80EYKw5QX3N8WQI1yDALfuA83t3Om3URUMzDDFz1ckeFL53whSwYnDPpC3zcKFUCeKEn2RcAXCgw/NylO7A/Sg/hJmWKbsGQmKXWb294NgeNQExtVzN9iU0k1BPcYcQD8NiwMsjHQfpRweC14diFL1nHdGJgAXsutD+GzCafx/G7JdRg1Yq1vGKf6MdN16IlnasZBL1FN81jHpqU0Vf4rkSpNpqHPdSzPKVUI1t7am9Jn3ruPtj6f7VZHZ5fyQb0mz9xfsZoGU7BFdfd12zGq1LN2lWbMPljLFz6sKTP20qyDD9WiO0vOeY9dANb5O4VFkYf1RYJCGAsXuskEAiPSbxuhYiZDRW0OGMHTkZH+QfUg1BzlBofPiLMhQM6Yln7/+9+7DgvSgtwxCW8O6DQJTBmuwsCet96qA+0cN4tUee6IFkfhWgcD4WPypsOinZsKzg3TJLWPMRujRui4N4dU6QNIxyI3mFKFBDqRyoSa2ZzOjOAcVD1/s5FAZ0qKFRHM/A2YFnBzVfX6wDk815c9BwiNYCAIABcC14eI8OGmXDDS7wHBXww0SPUiyIb9lU9YwT3J4BFAFJhMIQLcBeEE7ag7CI3zxmICyZKzzCCI4DnIhECwcHsU2uYG5oVY37WA0Gg/bcEkDHHzNxle/3t9vwcM4rBqMCgggA9iZgA2Esr3QTog9zjg3FDMBEdSVYxBCISK+ZtriWmY+5fBHoMifrepqWfDMXqKNZ9VNFGj5slTTaniNzBSXHd+KNGhtwZOvPSZf4Y2srcQb+k3pR8TOcwWkUJGCWU1Z7+jtXJFr+bs9RJ19vcqSBe1cs1K1VTPNOqNq38gqeRgWrV7H6F4LLCbZjeOCt7VwOjy7LOlDc3HCulah2FPjnsY6NwwxQ2vA7wxUKQgLE4B2ZCegylqc0AKCWQRKigeZlQAI/fNAcelY3wBrKOpplMdmnx9k/HEEzIGk40WlPr+9/Uj6+Q+Z2qYUfymgpE80bvU6sWPilqkc36B/3cjQO1ilmMSAqIwiQxn4LE5BI8ChZxRMcyN60DHSiTskCIBZxiRft86zWetM/0YneX6JiFfvrx0TTehDRQ/ocOHrHAbcB6h6mEQRj8Xmn8xXWL5YAL98Fpz7bgGdPaQJiQQVsbiukAi+PRRogwa2IbBB509YD0LgwpUF9YNCBICZ0DH/UeVNO47wHUlVY6oYdqMqRkwkEFJQr6YWrmWm0smDEbxU3JuXAsizEMfKtHIDHAp18oxMAtj1mWwGG6D6wXLCQMDzpsUsXAwySDuoYcecteQdvNMYMUhTiHcBtMuf3+uaThLFLneXH8G1gwqeCaxQtFG9sH1YSCHz/UDH/iA+9uFM2NRhpPB8YamwNwQRq1W8B+u+aN+dvG1OuGsr2rS3ge6Pwy3JjWAEf3xaMms+/xD8aFEshH73ilXt0aKue0CNSbyal3yhJrrKtXf06mGSFJj9n+5Hn/yMS278yI9u2CpgsqpetW7PqViJq8nb/+TDnjZ6Zrc0qj//OUSXXrJb9iRw25VKxjzBw8Us9YMN5tQhekLX5A90c6Jz3lzs28IPHwE3gBuah7uDRUo4CZmpB4qNFIuqOyzoXuN/VI0f/hk4A6oVQoHYApeH/Ab2jXDDMy1x0/Ew7jRazUMpHTwQGH+5cHjb7ax6zMcdCaM0sPfYe5EeW6OjxZgBkTtlPvWbKgt6/1KKVMjBGysF9ybdm72R1HB/vbfs/tymnWArxrpem8AmLTpIOmM6ARRrtwbm2Pe47rS4ZHeAfibc93Lg3A2BoiLdBfUBh05QTgUmziOAdbtt8tk6dCWJVxtCuS/1oF//2UvGznP0EjSGIBpmIZWbBgosXJ1VH7+fMe9Xn6/M9CD3MJ1/JbtQrg+s4zQ2b58n+H2w69zeTvC/bOO3/OevxVgm9AsyrrhbQuPtzl/xxDlbQDl58l3vB9+vA1di+HfsZRfm/XtMwTrw+1HuhaAa8F+Od/yfa9v/eZg1Ij1t1dcrPN/9GsddcZXdegrXmMNsn1y4vZfFPXpFo4DkQ6Zgt33gO/cm9IFca+l7fZvyeuJR++z99VKZlLaZ2JEY/c4Sjffe6tuv/J8Far3UV1ts05429lqWzBPy//7T338c1+y0UZOv/rR13TF5X8o7djgiXUInlg3iB2eWDFt2/2iWbOGVmwimAcWlWKjeCJEMSuikjbn+aeDQtVArpjzKJTByP557dsEoPa4zscee6xTGvg9h088vjHg16WjhFzpAB2x2rkch8ne7jWTIENbloDSRgmGKul5IAgMvzOkYvd5wbqnO7uNiJ7jiu2KnlygMyZElbA/1dJUoAUlC/B2R9q4bKxd5mOaSm6+e+yapTY9DGFEZGyfY8J9FnLqW/6wCtmtO+FCdlA14+aoduII1p9tgFEj1osuu0jn/+Rinf7uCzTnqONcMX5Ykz3zNiTO5wYA4R3LqKNEuu5PM/Qas3UVJlsPbErrqaceU1/G1ubSdsGT2vPwU3XRb76t+f+9W6d/4HwN9A5qxoFHac2TD6k216mTX3Gq2ro7ddH3P6+rr/jz0HE8sa6DJ9YNYocnVu4lTIZDJsFNxmWXleoqG5lh/oKQuJc25/nH5EYEMGZNBscEhnFPhikNmwp8upgiUZhEbVNYgnPdHPC8EDVLG8BlppwPs/vtQJ6tzfybu0Ii3/iGdNVVCn70I12+qugIbErVpl+bbYV5/YGeGJBuPCzmSOtzTxd0pJHO9m4Zg49fLC/qq7OjesvEqK5vLTpi3btuy1tG1sgFS4v6+pyo3jYpqrUPXalk27Oqat7yQLNCLqWVd16o/d55qRpnHjm0dttiy3TuCMhli5o+fV/FGSRGiyqiOPnTl/43QKDujXtlAvN138CnRqbhA45/NGGkGrN1yxY/qYpIQQuNXIN8UZXVjVrd1qEnHrhd3Z39iuZz2vMlL7Pt4xo/vlHHHPMyLVq4SD3JnApDZg8Pj10Om0GGG8LmDqpHYxA+WhjelqBYVB5CZQCIYt2cBbPxkGJuy9ouVgZaa6+P9gXbfYFU964t/ckvW1nUGhu7PzbCdi/2cpeR6H61EdWZyO/NSRcuD9RnanOkbTd1uakj0DjjkAqjB9TqyrsvVm6gUwOr5m7x0rPgDtVO2l+xxIuXfjlqxBqNxNTSPF59axcq1b7cBRsFbso4WNMWR5ylbd0651Pld6xwa90LS5Xzx5qKVU7Llj6rusq4xo2fqj322kfNEyZr0fxH1VBTq/qW6epse8Z+EbPfBaoOelQYWKNiPmvku0Y5T6weHrsVAky5jY2bv5T53jC3Yob85X4xXbgDLNOMDyqso6RvrLNmfnGP6IjbvdjLObOiqrXLHbeOHSI8qjGiX+w78rabunxgSkQ1tk/+BhETS40zj9LeZ/5Ue735x1u8TDrqXSVSjY5arO5GMWrEWl3Tomkz99KYmgq1P/2wuhbNV6yQdEwZFtx3S0merlsH+RZyuRLp2j+8JOzCYhrOZzJqGTdWC5Yu1SFHHauGlvFa3W2yftEjqq1v0LGveqOKQUyJdKct3arNdquvr0tTZs1SbXW1aqo3vUi6h4fHbg5StYaittuzgW5oC/T3HWB50hTryS0RIzDXdeq+npG3e7GXO7oCrUgboQ65rLtyds3aiyNuu6nLg30yYo3o1LElasoNdqrjiX9u1dK3/CHbU9T5WF8sjBqxztpjXzU1T1B9Q4NqE1Lfime1/LF7VMxljD8JYLKNjEx5idq/JkoNgXKZtH1CnZY83hBsrhBVzL7P27rxU/fTuOn7avqYWtu8qNrmqRozrkXR2mmatsfBmj5pmvIrH7MLeKvSvV2KJJqVi1Rp7dInVORgHh4eLwRWo7IozC2FC0LcSozGPgCpFtEtiGh1GBwszZb0gQ+owYTNJ2dEnUlyR1g+Nyui08aVOrPTx0d0XHNkxO1e7AXz9E/2jarRGL/KmOR/pkc1qXLr2naQjWt+uHdUlY6ZIpp24idUUTduq5aGGUdo9mu+aYLVDvAiYdSINZ0eNHrM21JUIh43tWi7HjCiI6zaiBUSRY86Tcr/QcEYNKWY/a6CoZh7uIqKGuNSA7gmntO4hhpXeGKPPfYzJRxVQ2VM1Ym4ps3YRy8/44OKJ6pV0b9WdUG/+tYs0gN3/VfZfETdgykpVqHq2hGi/zw8PKT77y+ViNwKUFeVSj5bA1IhKMtHxO7WgGA5lv2mTpWuuKJUjWpzFiKmyZGeNs0pw0MaIjq6acdYCAwqpR9KEypG3mZ7LCebqtx/KFAJ4XRg/cjbbc7yBjvX2TVDJ2uon3KQGmYesVXL2P1PU1XLtq2yNRyjRqxdna3KpjMqFI0wMelGoq7qSGW8qGK0AJeWXK0GXlpXPKEn7vi7Ev0LterJe22ljZ5tsQGPbRtoUkNMYypsNFRtJJuIuMnM6+KBFj0zXynV240WV0tFTrMmNevZ+U9oxZIV6m3rUMEIGxP0xNkHKvYijlA8PHYaGAHpyiupSj60YvNB2g15qKTcbA0oeAA5h4U0tgRhkYjPnHOOKojsJReWqOnNWUi1ecUrhva4Y+E5mtmxsC3atW3O9cW/gqNGrKnBQSO/nCnOmClOI9Ii5FrU0w/8RxWBjUYJSHLnF6iQG1T30/dr7dw71frsg7r/+t9rsHOtawyKlpzXeiPTlupAVUaupO5kilFlIzGlB/vVtWyhBpbMU016pZYsWaz58xcon0krHo+psUqaPbFBDY3jt8Pl9PDYwYHJ00jIzcnrAhu2DNdee62bFYTScFsKKgBdYeqS9J2tAQUqTj31VM0kr5cqVbRpc5dXv3pobx4eW49RI1YmM29rX+mIkdQXGQmaztTcm6/UHX++WEF/hx2MahmBUque1Jh4VtFslx6591bV2OvaxU+ZCo04vygRZtm8VF8dU/eAqeG0KdxkQYu686qurFZNzwp1P3KH5t19q25/8CnN3O9AVVTElYpWqLkiorH1tWppaFlnPvHw8BgCM/+QJ7wVBegpX0fd1ve///1DazYf+Xze1WCmLOKIBRs2EZTRI++bkooeHjsKRo1YSYfpHxh0NznBCNE4Bt3AiLCoNU/epbuvvlip9lWK5JLqW/6kJo5pUSHdryIRwcW8keyAKVV7DaSqWKCBbEGdKWltKqIOI9bVyYj6czHV1depKRFVdayotatWq6+/Vy895kgVCkUVExVGyAWlsxScoMDEUOM8PHYhFIpF5VCdFPnYnOWqqyTmgT35ZBvgRlxhhi/Y+s1ZqDuLGZji+5R8gyApujLSthtaKPwPGVKTlapJzAQ00nYbWqgDTX1XyNnDY0fCqBFrhZHaxPGTFY9FlcsauZJDGhjZBQXVGsn2LH1MT9z5N62ed7emtNSr2pRlEVNUsaCsEeuCB/+jTMdyo2ICmKRkLqolvZTHMt0b2IKUNdJtroyqpsrUsBFnVTymtpXLVF1VoVQqq3R/t9K5vLpSRBnbxqMUbejhsaOAYJ+frVmjee94h/TJT27e8r3vSeee68r2MYsHhdqpTLU5C5WkKB1I8XPImVl7KNo+0rYbWijCHhaop4IXs62MtN2GFo590UUXbdYEAh4eLwZGjVhzuQFVGemhVuNGskV7TaeSRDm4dRWJQB2LHtLTd9+gyU3Vytt6Rrs5U5h5JVToXaN7rv+DqdeM0oWI+oyXswXoMVDbgse15JG7VcyntHQuM7oX3X5j0ZiyqbSWLVvuRtGxTNK9pvPWhkJS6YxJXQ+PXQiU4iTo6CWveY1EGcHNWShBOURCqERmVaEU4eYsTLdWXsqS2UhG2m5jC/sIA5ZQnRD1SNttaKE0KCUwPTx2NIwasba1Ldfj5K0S3Gufo5GoIihWe1+MFJQrFJVP9irV16FCruBG3mwZTyS0xz6HGslmlOlaoWVz7zN1mlPBfh+YKo0U0nripqv0z//3K616/D7NfeBuPbVwpQJTq/GKSiPmQCtXtw6ZnmNOpPb2dOqin5ynJYsW0DSP3RVbmcIBGPyNBihUv7VYtGiRm/6Kqcc8PDx2XIwasQ4O9CgWySkomsa0pWg0lzc1CtM5hWmvzvJrhEqt32KhNDWPcadq6ptlVGu6taiBFfO08KG7qJxsnyJa+uDdyrauVF/Hat3wu5+pv2dAy1o71WlitK0/65Txf265Xfkgqqrmserq7taF//ct3X7TtSrkt74z89hJscAGVUwdthUgXoAC+KVB4JaDdBImedgaUPz+ggsucPNJksbm4eGx42L0TMHZvLo624xMjcyMLYuoVSNPo1I7COG5pihtHdMwtXX1OoWK2VZBQdn+HlcwP5MaULJzrfKdy+yzqY1iQT3PPqqayoi6+/rV0dOrFWvWKNnXq2Skygi5RdUVUS1fsVRrOruVM5V79TV/1YP3/MdoHcU7aqfnsTMBpfrzn0t77TW0YvPBoI+p0fBFbumcjIBZZJjlZ3PmGR0OiJ15S1//+tc7U6yHh8eOjVFjntqaBiPLotLZjHJGrgV8p0ackCodAx0VREpVpZ7BlKsHQXRj3shz7iN3ucnQyXvNpAfUumqx2pc+Ywo4q1isqIqKhCqqatXeY0o3n9NgR5t9F1UsHld9ba0am+o1mEsrncnr4YfuU2VVpWYfd6rqx4wvNc5j94HdZ26+UqrobIX/jZQSptQjwGZLgeIlcpU5S2u3ohjDLbfc4p6fk08+eWiNh4fHjoxRI9bACHPazANVX9/gJh/Gx4oKLRRK6TcoVtg0Zgq1tz+pTLbgypit7eyx7SOKJGKKJipV3zRG+VxWi/97m9YuelJN48YZYQdqaahXg3VOpX1JCUzJ8YQj7kRFlWbtsY8WLXxG6VSvirGEphx8lCN4j10I/O0xy25o+e9/S5NVQ0KR0qBucxfuscsuu8xFwDIfLp9H2m5jyw033OAm7z7ggANc80faZmNLMpnUv//9b1dEYUeass3Dw2P9GLWJzi+8+Dd6YmlKLeMnKR6LqJDLq6N1mRY/dqt1CIGryEQHFY3XqmHCLB20xxjde+8dWt3Wr0JmQGPGNGnylBmatedBpnr7le7vUzKoUh0lEVcs0aLejPrTSVVnB0V5yqNOOk1rslndfuN1qp+yh5FvXisWz3U+18bJ07X/K9+gHiPn/xBFOQQ/0fkQmHz7C1/YuSY6t+vjihsMFROgjB3+9OnlplEChFavLl3r+nqXwrFgwYLNLrv36KOP6otf/KJOOeUUd4+Qs7m5k6X39/e7PE9K7THQPPfcczU4OOjWbQ4o+fdbu5fI9/Tw8Ng5MGrEetElv9VjT7erZdJMJeKmVrN5ta5drGVP3OU8rPipivhUYzWqHjtTcybVau5jD2owG5dyA+obGNSee8zUvgce7Yh1oLvVhvgFdXZ1qbkYVXftdPWvfFZxZVSVT+mI40/S2kxO9911u8ZNm6NnnnzI1HFaA+msGseMUdOUmarPZ3TrTTeXGmjwxDqEnZFYy4Cl4zOf+Yy7RrMoYxeC+4vC8kaqWwNIsa6uboNt3RiIAsb1sbWBRn19fWpo8NMfenjsTBg1UzBRi/++6a+uOERn+1plkn3OlJUvFJXJUcrQDsY/thiTqzeZVlVljXU+ERXt9xONCBO2vrImYR1Jk5pbxilfzKmtda1tm1QmXq14bYMSDePdhK2rFi1SZUWFZu65v1YtX2gknHH+2rraamUH+hTN9qhiKwuEe+x4wOpBUQDI93mkClCDW0mqoN72sbWDTXIzRyN615Oqh8fOh1Ej1rrGsRozZbYzdS1Z9IweePAB6wULpr4K6uobVKEYuGIQgfVXzIDTN5B2I/qaukZVVlZpMJVTRVW1ElW1iscTSlRUatyk6UaWUfWYmg1M8SaaJiiwbbPZggo9vYpFq1Xb2KjunjZljNBjiaiqjFg5bqK6aMfe+jxGjx0Lt99+uxvE+dqwHh4eOypGjVibxs1Qw9gZ7v3U2ftq/OQp9g51Gle2GHFKtqOr2xFs0Yg1k8u7SYljFHYwtq2srnGJOYEq3VyqqXTGpfBEiCLuH7Q9mRqJRVXM51WdqFLT5Gl63RvfoI9++P0aM3acjI1VU12pqKlZCLunt4eju/Z47BogdeXqq692BRK2JgXGw8PDY1ti9HqnGOXJmNum9D4aZYYbmQqtV/PY8e59ysgV8zDkGhjnuXQbI0G2xWzGHK6DqbTyiitR02DKM+aCntK5nJQZUCE1KGVJq8np6NecofrqqPacMVXHHX+i6hpqFORzrsQh+26qrFONqV6PXQP4VfHRUiOWMnoeHh4eOypGj1hh1AgFH/CDGWm6V1OnEZRmQrFY3Mivyb427WlkyWw00XilItEK29YINmOEWsirf6BHOSPe/nRR1Q0tSlQkXEnE/rbFKuC37e/RvocdqWhVpb75nR9o/rzHdcpJJ6u+oc72GyifyhgZJ9RcO07FwKuaXQHcR5dffrmOPPJIF/jl4eHhsSNjFJknoqBYqu9bsPekvWCKLdXv5bOJzVzeBYVQ8hAipkhEEfVKpSb7nM2mbFtWsn1EeVbahpRGjKZ6VEz3uiCo4057tX79hys199lFuu76v+ngA/fT5EkzFYkbSdsZReMJ1dS1KMq8sB47PUh/Wbp0qd7whjcMrfHw8PDYcTFqxFpIJxXJYYY1oqSUoSlSF1hpRBkNjFDtLQX3bQNbVTDFmnez1USClPObEqxkUtPVDub3UePXSCTuCBZWzg72K9nXo4Nferwp2qIWrmo1wh3UrXfe6jyzM6buqXhViyqMVPfYc28detgxGjdu83IPPXY84Fe9+OKLXV7p5uajenh4eGwPjBqxrl29SB1rltgOY1q+8Cllkr3GjIGS/T3q62wrEa4Rqr2UyNWWZH+nutcuMSU6qEgha9+jZvNKJ5MaHOi3DY1UI0abRs78rr6hUTP32lvLVthx8rbf9lXq7OjQwmcX6oD991MQbVBNbZNOPvl0nXrK61y0scfOC3JBf/KTn+jss892KTAeHh4eOwNGjVghsVjMFKeRaWAkmcuaejXVKuVUtPdE6g4aYWIipkB/1DizKhFTXVVMFdGC2lctUG11lZqbmuFSFznsyJiFeW5M/h5yzIm67fZ/qq+3S/3tK2zXpoRjlVq4ZImOOPwQ9/7Vr36j3nTGW1RdXUMQscc2AH+TFwN//vOfXfH6gw46aGiNh4eHx46PUaOeSDSuYjSqAh5WTLr2H/0v6yOxhEutGUt0MKZefmBfYiqujEeNUCvVXBtXIh5TbW2DqmuqjRgrVHR1hk2tmpKN1jVq7JSJevLJ+Rrs71Y+M6h4IqKXnfx6dXQnNWv6NH3k/e/Qxz78YVVXVauuLqIKI26PjeDppxnFDH3YOBggzZs3b+jTpqGrq8tVYtoccAwqUZ155pluUOXh4eGxs2AUNV1eUUgziKhQLAUpUYTfhKcj0mw2p9SgKVb7j8/5fM6l0iRimHulWGl+G7fU1NRp6tTpSlTgYy2qYKuPOOkU/eum6zSmuckRNjr2sCOP1vTZh6m9s0OZVFrvOfMNbrabnO17fNOWzyay22DpUunXv7ZLvunE9Y9//MMR3qYCIv7lL3/p0mU2FT09Pa7OL2UQvV/Vw8NjZ8PoKVYjO/pndlgi1qgJobytLNp3BedfTRjzMusNpkSigakdTKWmmJEkv4VwSdMhYKmyototcG1FZZUmjxujuY/8V7ls1ikg9v+qV52hFYufUn9fv9o6+pTN5NXbn9bYpmplc6adiT72GBl9fdIPfiB9+cubTKzPPvusbrvtNr35zW8eWrNxXH/99W5O03333XdozYYBETPVGrWJ+Z2Hh4fHzoZRI9agaATqCDJQIZdz5mD8pIVc2pjSlGuQ1+BAL5LWkTAHZhsULgoT/2w0ErP1EeVN3Q4MDBpREtAUaPzkWbaLtKvGFLftunu6FY/H1Ns7oM7V87Vq5Wr1JQeUzNm+bZ/9fUl1dpk63nQL5+6Hiy+WzjhDGjt2aMWGQWF6Jtum+P2mqkhmlqHAPyS5qbj22ms1Y8YMHX744UNrPDw8PHYujBqxUix8zz33ckQ4tmWMJk6aaOqjaGo0r6oK+zeXVS4zYFsa+dmCmnVFJFC2UYpARF3AU1fnWrW2rtS8uf91NYch16OPPk7333uXMXGgyspKI9ReNTbUqm3tahXS/cpk+jXe1E02X1R7a4eWrFitgWTWTQCwW8OUva64QvrDH56/YMqFUE8+2QZCEZcn+gdbzxykvI60PPHEE3rta1+radOmOVWJSXik7cLluuuu0zPPPLMuTYZp3kbarnz573//6yKB3/e+97l2eXh4eOyMGDVibWxo1JjxkGmg6VOnq6m52Zl6m+pr1dzYoJqaak2cQPAStt6Sn7Wnr1er1rbaa1Jr2zuVTg8auQ6aci0om+61zTLW0ebV09mqttbVRsgRN2sIAU31dbVKDnRq771na79991F9dZ3Wrlqrp6wz7x8cNPLtc2bj3RbM9PKhD7mp4YRJtXx505ukT33K/vpRzZ49W2eddZYrwHDXXXc58+tIy1e/+lXj4ZPdrk8//XQdcsghI24XLkz/9tOf/lQTJ050v0G1Ml3fSNuGy/HHH69vf/vbbv5SDw8Pj50Vo0aslVXVqqlttL46qrr6FsUTlSXzsBMeBTdlHLPWoGhRPBBsRSIuE5lKZtKuHjDTySUSVQrs+97+QSXTaSPoFrW1r1AubwrX1ieMWCku0dXVbfvO6R3veK8dM24KNa2HHn5EXb2d6unq0erVy1yJxN0WXPijj5aYBWb48pGPyEY6bjPq7h5xxBFau3at820ya8xIy9ve9ja3PWC6tpG2KV/e+MY3OqIMcdhhh424XfmCUoWQPTw8PHZmjBqxYtKlM8evWozGFI0lHBGGAUQQaimal+AmTMEENZkGdTPcxFRRWS1q+xZsXTKVVmVtvb2PafKUqerp7nQ/hKirKo2wbUctLU065ZRX2W9rNNkU8h333qc1a1dr0Aj5rttv0Y03XK/BQUzPHhtCWIQBRdnc3Dy01sPDw8NjSzFqxDo0r01JoToupd5v0RGoI1KI0QixvOCDsa9TsvyE6GBe0+kM3zpSjsYqVN/UrMHkgAtwYidEA1Od6VWvepUOP/I4PfHUM6a2OvT0M88onUmpo71N7WuXq3XtSiWTSRrisQH89a9/dQoU066Hh4eHx9Zj9BTrOtIkNAk3akmVhuvtHyNLfKuOdUvf2Ssz3SQSlYrHUaIRDaZSyuazymcy9rmogcF+TRg/Xn29vY54KysqdNCBB+ptb/uwEXBcy5avUkdnp/oHek19ZbR29TLdeddtuv/+u5U1ovVYP+bOnesCht7znveUBjoeHh4eHluNUSNWJ1ONGB1xGonST5co1j4W3SpXGoKiEKVtUbfR0gw09rt4Iq5MNm2ES85r4NRm2+rlGujt0rSpU9XXZ8Qai6ipuVHvf///KB9UaumSFXr66aeVL+SMVNNKGymvWr7MfptSOjmo5OCgO77HC0Eu8K9+9St9+ctf9sFCHh4eHqOI0SNWiJNCELbApKhUNBC1gUum4KIK+VIRfqdgIVD7ninemD+VVZlcxm3rJjzv69ZAT4cG+3tUkahwCre6pkZHH3O8EpXN6ujq1n3336+e3m5TwjnlcjllTKEuXba0dHw7Or/xeCG4Lj/+8Y/1zne+00Xjenh4eHiMHkZRsRoca5aIMzQFk/ZCDuPgYFKd3b2l74z4nHolcMkUKyqWovyQaj6fV3d7m/X+OTW1NNu6vAaGlCdEMGv2gaZE03rASJVgJUjVlU/MFTRgJNwPEVcmtO/++7vUHI8XAr8qFZT22WefoTUeHh4eHqOFUfWxFt20byV+hWGLhbxSGVOhtiJratVNau625Vv+CYObUJxZYpPUtmalitlB1dXWqL6hyQUxdXd36fDDX6LTX/MWFzH8+NxHtXz5UqXTKdXX1dt+CHYyxZpK2bqk9tt3fx11+JFqaGikIR5loGjDPffco6OOOmpojYeHh4fHaGL0iNUWShUCCjxg6gXVNbUut5WvnAnYlClpM5BsxGQqpQnzxawz5fL7QqZPzY11bvq4CePGKZ1Kqr6+Th/72GeMoON6cv48PfPUk0olKXmYUU11tSNwCv67ACc7FlGu+UyWA7o2eJRAWcKf//zn+uxnP+uL23t4eHhsI4wasRbzGaWTvaZM03r43v+ode0ax2t1DfWKxkqF9/F7omhdreBIRJkMBRwiGjd+oiZPmW4Em1NzQ7XzpeZyeVVWJFRZGdc73/0eNTVPcso1l0kaweZdoBMz5OSNkFGrKN+OjnY11De6GrWrVq8yJVwid4/SoOZnP/uZK6A/ZcqUobUeHh4eHqONUSPWBU89rqeffNzVBE72tDo/KnoxVyi4ACY6dhfMVMC/ymteM2ftpf32P1iTJk3XmAlTVGXqtbu7V6lcUWkjzQZTrW8/6x0aN26G+geSmvv4Y7r/gfu1Zs1aR7yoVKowBUasBE1RwrCqqsoVhujo6nDH9Cjhb3/7m6uydMIJJwyt8fDw8PDYFhhFU3DW1GWVKhKVmjZ5snstTVIOiRacOZggI0jWvjDVWVQ8Ua3Va1uNTAeUSZviTadUW9ekTM6UZiShCROn66UnnG7qNK+58x7X6tWr1dvfY8q24FJsCGyCoAPyY02x9vf1mmKtU1NTgyN2VzrRw033dvfdd+sDH/iA+xtgEibdhgkNPHZfpNNpG6Su2eRlyZIlSqV2nNxwUvJoE+exuaBvIFByW4GKZvRX4dLW1ubcXRsDgZ6tra1u+/b2dmeJC8G1D7/r7Ox06zh31rFsy/Px2DyMGrFWVNco5uoD203rTL3kpxYVi5YqK3GDOAVpC7WAXcCRfYNPNFvMuSnhivYbooSDrL23bebsf5iwFs+bN1eLFi10N1FdbV2JoJ1fFROw7WXIb2tHseMWddqrXqXJk6Y876bcXcEE40w0/j//8z+qrq52HcoPfvADffjDH1ZdXd3QVh67G7gvvve97+n888/XD3/4w40uX/rSl/T617/eBsHdQ3vY/oBcPvaxj7mAvI0BcisntquvvtpNLDEaYNAx3Do2ODjoZmx6+9vfrgceeEA33XSTyxm/4447hrYYGRDkd77zHb3//e/X448//jyy5HxJk3vHO96h+cxQZejo6NA3v/lNXXLJJb7S3A6EUSPWygoj1jjpLYFyRqiRSMwp1jWrl7v5VZnCDaWJITheUemiefPWyY8dN1ETbKmMJaBFPf3UPCPRZxSvrFZNfYs62tdq2dLFdtMMuCIQ2SGfKmZgSJXjVVQk7IUSiDGnmletWquenr7dXrFy/gQrMRvNHnvs4R5+Um2Y75TC+x67JyCY//u//3MTI1AnmvcbWiAE7iWmDNyRgt5oz1577bVJz/mll17qppsMwUxNH2EyilEAUygOV4vU3eYYuKYYkLz73e/Wxz/+cfeKEl0fmG3q4IMPdufG78tTBqdOnermKR4/fvy6CS5Y99a3vtWdC1N3euwYGDVijVHoIR4zBYoYjSBIhUU3gEqNZOvqGzRj5mxNnTxFzU31Sg30KZ/Oqre7S88+/ZSNwB63jj9iI7C1Jn8rtMec/aVsv5YvW+pyYClX6My/BCqRumOLMauLKkaxAgaNtGPChEmqtht6dy/Td+uttzoyDad7wyRMCUNG0R67JyChiy++WNOnT9frXvc694xsaME0+Y1vfEMf/ehHteeeew7tZWQwQxIT1d9yyy1uCkLA8f71r3/p3nvv1X/+8x9H6qheqn5xL7Ld9ddfbwPhHrf+iiuucIM/TKkEIV5++eVauXKl+vr69O9//9ulirEMJ1M+81uOBWjHX/7yF7ee7f/f//t/TjU+8sgjrg0oR+YYDvHwww+7dfweFQhQmr///e/ddnxH7vdI2NRYDky4XPfQBYMF7p///Kfb95133rnJ+xkO/k4eOxZGjVgJIrJHUZl0St093S6thkjfppaJ2nPv/TRt6gzFo3GtWblUrasWKZ3q1+JF862zf8q2Ldq2k129YNSslHBzui5f9JSWLF6oZcuXuYeBUSGRwC5giQpP0YgSRqyYnLm5MB8nTPmOHTtGhx52qFOwuytWrVrlApboELk2mIlQr5/85CdVMzRlnMfuBTpuCA2igCQfeuihjS5f//rXncXjmGOOGdrLyMBnjyLDEoKK/NOf/uSO97WvfW3d1IS4InBD1NbWOrPmn//8Zx166KGOkK+66iqnuJiMA3KjzCa/5z4eN26cmzA/tLQwdzD7LwcxHKjEa665xn1mW7aBWDnGpEmT9NKXvlT77ruv2zcVxyBwwAAU0j766KP1kpe8xCl0zoe0PUysECJ530TV01baVeqLSgvHKP9cTpAMFohvuOyyy5xJHaIOleV3v/td92xyXAYeLOtD+T49dnyMGrFGIkT9Rt2N1dnZDa+qp7tH02fsrZ6uTq1dtUIZI8Xq+iZVGBlSfpB0mDl77KUqI9M1q1fY6LhX8ViFBmz0WswM2Mix1R6AFjU01tt+S4QKeQaYgO0AVYm4vZQijkuVm2z/NVUuqGnipAlGurtnriZBDnRgn/70p1VfX+8e/AsuuEBvectbfKrNbgwGpyg5zI2oOFTShhYUH4R12mmnbVQVofgwW2KaxIyJXx/yxEx65JFHOhPyfvvt5wgM9QkJQsD4+XmPSoRUMZsSkASBoVg/8YlPOHKdN2+e255jMBMT/stysqF9EyZMGPpUmmc4DJhkIAmZQmioRdbxPccDf/zjH535le9aWlqcesaHSdt4fjCZY9Lle4iS7yHciy66yC1cq9/85jfuPdYAFHYIzu3YY491JmDUaqio8cGi1FHm9913nyP6DQWGoZ5dP2fn5GNHdnyMGrEmBwfcDYsZOF6BGVbKJgeU7OtVPpt2uayTpu+jsZP2tBs6YQQat4ctrvb2NVq9aql6ezvtt4HdwDXK2r76O9vsRksqm8mW/KlGDph/CVLiBquwBzUetwfHiDWfyzjiJbCJ6eTw786cvodrw+4Grg0PPeZf/Krg5ptvdp3Lcccd5z577J6A3FCqWC0+85nPbHRh4nkIaFPAdpg2Q7KDKCEiyAvyAAy6+Rz6aUNiKwcExiT5KGtUI+QGIYYWK+CCGG39cLIv3x/HZEA5HDwLYXtCNDU1uUh5QPv5XWjVgciGA7LEEoRCZ3n5y1/uggN5TzAVA4vhYD8MaEJVCtGzHxTyiSee6GaYOuCAA9x3w8G1xGwO5syZ44g7vM6AtvvyrTsWRo1Yc3bTc6NHI1FVVdfaGlJrMqY+25ypFsKNRCuNBFPKpgad4qQeU3KwQ13dna7sIZOcB0aKhDEVUmkXuZjLkqNKJHGJUG1XimMCTuADCuyBy6vJVG1Nbb1qbTnwwAM1pmWs7dvULA7f3Qw8uDxor371q91nzGY33nijzj777BE7CQ+P0QDmVpQk5leidLnnID+ijn/xi19o2bJlzl+KmZX7cOHChc7nj/pjhqrly5c7IgX4flFor3zlK93nsWPHuuAc9r1o0SKn9L71rW+tSzN59NFHHRliuuWVfWF+RV2yPcCEjEpHKQIUMIoaM+/nPvc5p7ifeuoppyhf9rKX6aCDDnLt41liW/bJe44VEvyGwLaQIX0Y0zPSd3GNnnzySWeK53hE/6J0Fy9e7CwJKFbUOe2gXbS3/Nmlf6VdZ555plPHPNsMFBiooKw9dhxEisWicd7WS7uf/epi3fPIGjU01emJx+/R/oe8XMueuE19pjzzpjI5Qj5SYaQYVSGTVK6QUoUpztr6Gj05/1m1jJuomubJWrrwWY2NFnXcy05UrKXFBSzl8hl12qiNdqJQ62oqbYQWF2URMRO//BWnasEzC/W3v12rT9hNOJjM2HZR/f2Gv+of//xHqYEGHk5uZh5UggZ4sN71rne57x577DFn0vnf//1f93mLYQ+SDV+l3/4W+1RpnY389bvfubd0DnvvvbcbqZYDQsT89KEPfciNznnYv//977sRfDk4h/POO+95Zq8QjGy/8pWvODMwCoJO5JxzznGpEt4E7EHnjtLC174pCgeCxPdJWgrmR1wL5557rvN5jgS2gUAhN3ycoTKFJCBNnjsWyAZCBES48j1gv/hhaSeRs3wO+ybWkTJDMBX+UlQs9zfPMKQzefJk98q+iP7FtMrzgGmXY6JyIUeeA45Bigzt5HsGAOyL/XNdUJzsi32zHuXNc8h+UcUcn+9DYCFCcYbnC8JzpP3sk/MEkCGKmevDPjkG7eRcaQvHCAcY5eAcQvLkWrAfTOqobUzMo9GHe4weRk3CkFNKTio3XFVlwv7Q+FuLRowoUdvAlmK2XwP9HersXqu+3h4N9ieVTmWtFXFNnbW3GpvGuxukErWZLzi/68Jnn7L9UMDfFKv9F49TXziqou20zm60l5/0Ch1z9NGuZnAum7EHIamWxjobET7ott9dQMdBMAQmPEiV68UD/5rXvMaTqsdWA1XJPQUJrQ88+6hGzJXlJAOpMJMS5AAgKsiABXIJ30N4gD6A35STBe+5jxmUhsE/BEHxO/y6IdHxO8zdkBQ+2fCYHIfP/IZt2Re/Dc+H9fwOwgv3BTmzDYNYnine87vw+xBvetObnGm3HOE5QtL8nvazcH04h3DAzDH4THsBx2Gb4Uu5Ig33g1+Y9pZfJ48dA6NGrNT/JdeGUWDKyBIzbcEeRNQq+azJTMrItF+9PZ2KV0dUVVNlo7+ouru61ThmqpK5uBY8NdfWJYyYK6VYxPlely9fYgoua/soONNxwkiVEVt9Y4OOP/EER6pPPfGMHn7oYSUqEnr0scdVXZXQwsULrEG7B7FyPUgnILqQhxSgvjEtnXLKKe6zh8eWAlMl5lwihEPy83gO+Eo9uXmUY9SINcq8qkaU2WxBiao6R4Qu57SQV9ZItbOrVUQCx2xkF7PRLPmmuaJ9l8+rZdpBWrlihcnetAtKSgZ5Daqo1aZYe3u73Sw2hCUkTK1CxlXVNTrmpS/VcS87Tk/PX6qrr7pGbe1rFBQDe21Tf7LoCknsLsCMTedH0AfApHXllVc6s/ZIASIeHpsKzJkUicClEKo/Dw+PDWPUiJVyhph/o0ack6dOU65QVDqTVuuaVUa2GVVWVZh6zapoA7tAFcqkc0plTYHWT9TgQL/qmsZo3ISJikcKylTElDYVlkwOatbM6c7ESyGIikTcRsw1LrjgxBNO0Px5z+qqq67QmrXUMO13o0b8H9V11ZoxfaaYQH1XB2kJBEAQFII5CpWKb/YLX/iCz1f1eAHwQRJE9Lvf/W6jCwE1FC8g5QWTo4eHx6Zh1Ih17PhJ1rEnbI9RJWrGKK9KNyl5Kp0U867m8jlnmKUWcCSSUD6IqqZhohFui9YsfVKTpu2h/Q84REF20JRvwgUpNDQ06dhjjzMyJYesQpU11TrssCP08hNfrnmPPavrrvur1ravUDo96PywUPYes5iLNa/99j3AVLNr2i4LgpzIF6S4fugronQb4fthqo2HRwgGnp///OfX+Qo3tuy///767W9/6/yjHh4em45RI9aKylplTKWmcgllg1oV8lKiokrxRMLNaMNsM1RCQlXFTHlW1TQrlcyobdVya0TGVGaLbVsjSvOjM/v6e1yua0d7lxKxqBFwpV5y+BE66RWv0PwnFuiv112j1WuWKpMadBF4HR2dLuUHc/AjD/1XFRWVLlVnh0KxKN1999CH9QNVQXTlhoBflQR+CDSMMKY8HFGFJNl7eIwEqg+deuqpm7SQ9kJxh10ZVCQj8C8EAVoeHluLUSNWRSsVRGttqVTU7s2+ZL8C/K6mYONGqJhxa2pqFa+sNJKNazCd10B/qwqFfjWNnaT6xma1r11p+zE1W8gpm00Zmcadj6cYFHTwwQfp5JNO0VNPkMf2V7W3L1faSDWdJPdrtavylDaFLCPmQiGldvtdNvf8RPDtjuuvl/AlbwA85Mw6sjEzLrl11D195zvf6ZQIflWIliT14VGLHh4jYsECpnnZ9OWSS2QP3tCPd34QaPnTn/7U+ZAZqJLmQlxCmOvq4bGlGLUeGLJkCXIZrVmz3NRkq6JVjQrsEKhW7LJRZyqutBs3r6TdvPnMoCqNcGft9RJletv01Lz/Gi2SJBO4ScvHjh9nyjPqlC7RrY8/Ol9//9t1amtf6fy3yXRSy1etUbupVUiU0eeyZStcPuiihQts9PnCyivbDc8+W1Krb3rT0IoXgocbUy6VXNaXKwjoAKhMQ0AJFgAS1qljylRTYSqCh8cGsXixjFWkiROZJmbjy1NPSeefDxsN7WDnB4F9zBIT5tES8XzCCSdsUo6vh8eGMGrEyiw2g4M9WrJ4gTo7O1Rf06hY5VhbL2VNhRXypiQjVUYCcSX7UyrkBu0Zzau5rkVTp87QE/f/yxRstzKZpBEMRfWjOvGEVyhjhFlXW6/HHlmof//7ZnV2rTZVl1TKSLSnP2PkWjL3Mvok8bp5TLPe8573GbGvcubnHQKYmn7xC+mTn3Qz96wPVGqhWgxFz9cHyJdRNiQaRmkSaEJVF/LaPDw2ijVrpB/8QPrSlyTKXB599IYXKg2tXSuddBJsNLST54OYCFwRFF6gxi9zibKOykfhe8AgkIpGVB/ilfuZhYpEFP1nO4juwQcfdPsaDralcMX999+/bt9ExIegH2C/DK55LTft4l7huBwrNP+Wp8lQrGGiDTQ4Bt9TvYlCDFSJonpSON8p37MuPAa1fqmY5OERYtSIta+3Q8uXPatsIa3a+rpSYmu8VvEK/KZR1VXWKlFZZ0o1ZWq0X0Exp6rqelVUViteHFR3x1Ll8lnljUipriTmb83ljYeqtGzpSt1627/U3dWqXC5lBN6n5pZmJTNEHqeMQEtRSgRI9fT2as3abrV1tMP22wc8ZL///XMLo/3XvU6aPt09+H//+9/dLBflC5Wg6JCoNcpIms6F3NTh21HujLJmzMsIIOMVK1a4AvseHhsFVX2+9S3pc5+TpmxC4RAjFF12mXTeedIG3BPcs9yvF154oVN+t99+u6vSBHFBhBSnBxSaYJYXCjlgdYFA2QbLC5HtPAOsIw+7vMhECLZlAE2FMp4RKg8RBR9OkUgbIDyKMvCsEHwFeE6uvvpqd1x+TwU2XsvB8ahcRpwC7hSmuaOtKFhIlmL9gLKGHAfrELm9tIk4Dw+PEKNGrOSaEmBUazdbVU21Iom4cqYm6+qbVF1VrWlTZroJz9OpAUXyaXfjRo1ss0FWfV2r7LM9XAQ62Qjz6CMPs2e4ylRpSgcdeKCRZYfWti610WyP3cD9OurwQ9XWmXQEWzQydgxqA09my1m+bIWR8O1KpQfdg/aiA0V60UXSscdKL3tZabGHU694hfuagBDmQyVlqHyhQhKdDx0FnQxlCTFLDd+OsnJ0KjzMlH1jlg/Web+qx0ZBbjeTe0MoN9wg/eQnG17+7/9K5l9IdcyYoZ2MDMiUCkhYTcIZbqhmRHAdRUsgOUCEMWUVUXpUJ0KlAqoiEeHONHMMFKkgtr68WSKWcZVQ/5c0oLPOOsuRNKlmDD4plMJvTzKFTU1dVDJ+VGaZgVgpdk98AiUOy8E+wwpHkOnMmTNdhaOwglKojJl9h6IQtIPzZp8+Ct+jHKPWG6MsK6prFYtX2fCVnFapstivbKpfMbtJu5P2UEdiCowIKX8YTVS6nNfevh6tWr5ILc3j7Sat0YEHHqRjjjrSTVSesO+Zsaazs82NTvuNWE887mX2AEW01B6KgpGninCqaWIjFkbNK5Yv1JJlC43Qq+3mbxpq3YsITtweRs2Z89xC9SPWGxjlUjqNsm/lC51BmNYAafIgj7QdRSAYWdNZYBKmRikPuYfHRuEeykrp858vWVA2tuBa4J6cPHloBxtHuX+SASLgfg6BamTBdQFhkTIW+jghWqKWMfNSB3dTgRUoLITC+9D8y3sQDrDD4vl85rtNGXiP5G+l7ZiKKYCP28aTqsdwjBqxRq2zjyeq7EGxm9Vu2Fi2R32tTyiT6lV/Kqfla9aqSCWmfMZIMKZY1B7wQtFFDLe3rlHenoV8rqAzXvtaG21OUk1tjSZNmqCFzy60h6Dopo4768y3qL5uvG696z5Tv6mS2djOgGOjlvfZa7YOPGA/I55AH//ohzTRRpK7IugQmCSaUX5oEvbw2CggH1ORbuAHGWxsIWipjBQ3BPyP+BlRdczsgm+S4iX4TDH/Umie+AGUKioTdUkkO+oP9Yjp+Bvf+IZzhTCp+Kc+9ann+U6Hg1lxULtYba666ipXxAL1yEATtwrfEyXPzDAMRNnfTTfd5LbHrMtzw+AVXynETttoD4ROmzDt8oqqJUo4nCOW7xkM4N/FZM16XreLdcxjh8WoEWvEyJIApUh2ULFcnwqDHUaaeVOrFJtOKNXfpXyGOQ/zitc2lkaNKM4gp46uNnveqzVr5kztNWdvLVjaqoI90JMmTlQmm3HbUti/zhTx7Xc/qO7eLhWMVFlPecRaI+HjXnakvvCZT+v0007X5z/7vzrkgIOdkt0VQSAF6TaYwDw8dgRANu94xzscKUJKvJIKhh8T0zCzNbH+i1/8ojPFQrZUB6OAPS4O0suYuQlyZMpDip6U55cOB8XqMTUTvAQhsw+U8fve9z437zCzRaF+CfIDxxxzjCNZpmvjGN/85jedGsXUC5nTtjDVDeWMomVOY3LCOQdUKm1iAEGMBK4bTM1M3k4dZQYMHh4hRo9Y7aaOBVlFB1sVyfWqtxOFGtGYCdPV1bZakSCvXGpQ8apaJWzJZshB7bWbNqXUYJ86WtfqtfZArWrt19NLVqmqukEJu/EnTZlgBFrU0Uccpq7OAT067wnl7AEoFvOKxqNqaKjXW9/8Wn3sIx9SU12DpkyYoEnjJqoiYqrYlO6uBh5+Umvwq44U3OHhsU2AWdXIZ32A6CA0yAz/JkTHZ2ZtYR3+TSJuIS3W8xm3CO/xa1KIgoV7GkXL95DWSCC6F0UKsUJ+lDENQT+ESwVy5vflZmimlnvVq17l3C6YjnEfhW1hH7haeI+fGKLnOxZcLeF2+GEhV2anoTAL23K+tMXDI8SoEWtQyKg6ZsSa79X8B293kbrNLWOdis1kk6Yw87ZRUZVVNYpHE/Z5wKXopAYHXbWkmbOmq755ku548AlnKs4FCfX0JvWylx7rTMH19Y362023K5My1WskHUtENc1I93/P/qDe9sY3q6ayzs1uQ8WleDSuIuS7i5ln8BEx0sbsNdJ8rB4e2wT4LC+9lNnCNxrEtK2BlYoAP4L2Qh/uiwkImWhn/KpYjTAj80yiyj08QowasVZEAqW7VmvtovnKDPaaGk2qo6Ndg6ZSI0z5Zupyqo0Y4zHMLBlVxhNuknKiiRMV1Xrd696o2++fr6R9LqqgvI2QmQEnkahyBSKeeHKxlixfaERto2Zr9T5776kvfOaTOu7ol9rRmQfWRqCmUjH/4reN24gyUrnrKDo6lOuuu8490IcccsjQWg+PbQwGp9dcI1GN6N3vtkdt1LqMLQIKFPMt5mSCn7YHULqoW8zdmIg3NEetx+6JUXtK+rvWqHPBg2qpNGqzG498UyoiUXRfQUSTps2wkWajkV9Uxdyg6uvqXcAShHjs8cepqz/Qmq4ejW9pMCKt0Kypk9Td1aFrr73GKbWHH3vUmY0rq6t0+GEH6dwvfkF7z97LnnumkouVgiwQqPbC2whm0jIz0M4O8vseeOABvetd7xpa4+GxBYAoMetu6kK1MFJlzj6bMN+hnXh4eGwIo0ashWSPptrIrdpUZmVVrXKmPHP5gipMjVbU1Gj6rDl2tMBIMqUgm1ND8zhVmBptaG7Uy172ct390HyNba5TKp21RkVUmYiqr7tdSxcvchHB6WxSNXXVes3pp+iTH/sfTRwz3raKOp9MxAg6xpR1RqRBMa9EZYXqTA0zt+uuACIRQ78qvh0Pjy0G5Pjd75ZyUze2UNSBkocUkyBNx8PDY5MwasTaUFuvcU1NypuCrKiqV09Pt1OM1AeeuseeijPbjBFkpJBTJp10ajWdTumEE07S3CdXqmDistKUajQRM1INdPThByibKyphvyMvrbo6ofe88y167Wmnq7GuyVRvwZlkUMAcJ7BtqNxEcMT4ceM1beo0xUwN7+zg3Emcf/Ob3+yCLzw8thhYcC64QPryl6UvfnHjCxWa7N7bUMUlDw+PF2LUiLUqEddgql9dQUwDqaQiQ1F35JeOnzhJqf4+dXR0K2PfZXMp5dKDGjtmjKpqxmtJa6fq7eEtBDkjQ+nUYw/TtAnjlUpl1Nvfb+siOuP0V+rIQ15i6jTiYinw9YQmYPoLgpkmT52imTP2UGW8UiuWrrDj7GDTxm0BbrjhBpceQBUmD4+tBsrT7ieWwJZi1QaW+gYVa+tUDJhkQ8rYc1fA3bIBkBdK+UDSb0YCbh1KHK5cudJ9JjeU2r1hMYfdAZwr12l45acNgbrJ/Ib8WfJ7mfVrY9eMQTnXmShq8oqJpC4HucWsZ+E9IJ+Xz7Rtd/qbjDZGjVizRpQdmYz6IzF7eAoKInFFY3HV1DWobdVaLbCHp6O9XenMoCPK1jXLdfAhh2vxqg7jyLhiyqq6KqE9po7V7OmTbJBcrYcevk+tbat1zFFH6NWnnqaKWKWL+iVn1oSxi/plBhtC3WfOmqmG+iatXdNqN9JyVVmHULWTj7RJPqde6Yc//GEbPOw6/mKP7Q/48Y+ri/rKgoK+vnDjC9u9e25Bbdn1MysFG6688kpXvITOeSRAuBR0wAoDIIlPfvKTrgjDzgoCCyG9TQWExYD5xz/+8dCa58DAg4HGcECQ5PlSo5iBCbWUv/SlLzmCXR9oF6UkST2iljKzYpWDiGZqJlPvOKx+xf6IeqYesifWLcfoEWtQUCZIKJO1P2g04cyw4yZPd6py2eJnNNDfq0KO/NOivRa0z977aCCbKBGwipo+dZLGNtfr5JcdpgiTohuRTJzYpAP330efOPujaqirV31dnZFolaqq8fcUVVVZoalTp7lanZ2mhpcsWqL+vn5V2kh8yh6znGLeWUH1Gh48EupRrB4eowWo8Zq1RXXYs3ru7Ji+vJHl87NssGxqdW0mUHwDAzyqJ5Gzev7557uo2ZHAvUxOaAgi3Hl+twYQyHCMtG5LsL79lK9H3VHtaTjW91sKU5ATO1L/xMDjtttuG/r0HKiLTK7tYYcdptNOO81NukG8xbe//e2hLZ5DeFz6Xq41ZM20m8NLL5Lny9+JClRhzjA5wOQgv/a1r3Xt9NgyjBrzRIKo+nOBYpV1isUrVFFVoykzZqu3q12pgS4VC1nlC3lnU6qsqtbkafuoo2dQyXRWzc11xDXpiAP3Uk2iNDk698ZrX3u6PvepT6upoVEViQp3o9SaCmXSdKoyTbUbIpPO2Oh4mXq7e23X9vTbcz955kw7xs4b5MPg45JLLnHVXbxf1WM0QZf7r46injGB+PEZUdXGjOysF1jfkrDn6aIVRR3UENHhjesnVcyNVDVCGaFcKfP31a9+1ZkWyfdEXVFcf33gnr/xxhvdYBL1RyGUX//617rlllvWS1BYdNiGBWILTZ9/+tOfdMUVVzhVh+rC3Hzeeee52r5UTWJ7ShtCOD/5yU9cTuy///1vtz6cLIBj3nHHHbrssstcYf/QVIqyY91vfvMbN9sNCg9yo50ocVQh7eC3/O7yyy9/npn12muvde1j+rqtAQNvSkhS7CIEJRnDWbCYym59121j8NaxrYc9OqODvP0NBxVTLmqjnGhc46fNUE1VXD1tKxWLYLItqsicrEauLZNnajAfUdHUKqOiOiPLqoqo9phamtwbAmammyMOPUJjWlqc+uWPDbE2NzVr1vQ9rOExN5MND4grpRixNUbILRPGq2UDk4TvDGBeS0qsUVXGw2M0cW93oBvbA314WkRpG+QOFDa8XLqy6Aj2bZM23FWgplA7VCJioY41NYCpUoRSouQfxLI+8HyjXq+//nrXJ7BAHqwbqaNnX8yAQyUlAvt4ZoieZ+o5Sg2+7W1vc2UTqRc8ZswYR7C4VfgOhcx0cvQntA2CJB+VOAbUNqCeMHnjzERFG5g+jj6MmsPk0LIecylZCS9/+cud8jv11FNdBSpI9R//+IcrOYoS/NGPfuRqI2N9IveW9qI22R/gFaXKQvlE2hp+ZgkBUYbT11EkhjxazhMwEGH/lG5861vf6sg19GMPB/vZUtL12DSMGrEO5vIqxKqx0KqpvlGTpkxR3pRqqq9TtbXkpsbshikqXlmj2qZJGsjk7YGJqaWhVtl0Sqccd5iqTJWSQuNuOHvoixRrsr8/N0FdXa1mzdrD9lWvtWvWqtVGjtx0VG0qVViybeymnj57zogP4s4CzEr4qEit4cH38BgtpOyx+uzTBXVYX/3FZ4v65FMbXj44r6jH+gOdPT2q+EYeKYgQsqBYAuUAWcIyf5h/N+bO4JmFnPEjQgrkbUN2kOJIoEYwlZcwY7INNX6Zh5W5VKlKxrPDdHV//etfHflRNnHfffd1baIEISqWY1LFiYIT7IPShQzUAYQMKNxPW9iG71CaDBw4TwiTko3sk2wESjTSd6FcaRu/xYdMG1H0DC44J9rDlHNhP4VPlXlgWajihKoOPzONXuh/ZntMyNRkZgDA4CAcrKDeH3vsMbevf/3rX27Ku/X5SDmH0CdMO0OCD7Ez9587CkaNWAumUrO5QPGgqAn1tYpmB5Ue7FXORmAVVZWqqqlVYETaPG6Km6OVVJq6alOiQVZHHbKXxjc32F5Kf9CKSiNYa1m+WFBNdY0b5Y0bN179fQMuOClJNaehP76NvdzNwU+nzJjplO7OClQqpjBIlQfVw2M0UWXP1EsaI7r0gJh+uwnLeXtGNbUyotgW9LM8n+HAkI4b5bopYL5iTLiYVsvNnMOB6mTmHMy5gGApyBFlGKq8kGRDrI8wRlqP0uQYFOFHYeKWgTgZPKCkASZelGLJdRWos7PTmcNR7tRF5rdnnnmmm1oO0ma7kCQhvVA1ooCZf5mFYKIzzjhj3WcGDCPVIYbYOU8G4lxb9k8d43DiAOZsHmk6SY6JDzc8Z4ieaxeSK+3iPNd3rTw2DaNGrJWVtaqqrFZxoE/NxnOp3k71241NBG/jmPFGeBWqMeVKQFM+H7EbNK5ZMyZo9h6T9dKX7OvMvfxx+cOiQCvsBp46bbrGj5vgwsTb7SZOmbINbwD+8OSu8op5ecLkqU6x7szAx8ODwTysHh47E3hGMT2iJCEYVBlBMMytipkWE+c999zjzLXMzoT6w1+JeoIYUJsAwoBYQtW7PkBebHfppZc6Iub3mGMxv15zzTUukArfLhGuECBtQz1yTMgPXyg+SczVtAlywTdM/4IJmennIGl8t/hfSXNBdZ9zzjn63e9+547JAiBhzoEZdVCwkBrXgMhf/LqoSUia2XVQwqQj8VtULGk0mwJ+wzE4J/y6XBtMzxwDEzfXjQE514PrjVoGkChqnW0wT1944YXO3I5SByeeeKIzdRNtzO/w/6LIPbFuHSJ2IwWjcRF/9NOLdd75FypRyGiPllpFxjSobfUKdXV3afKsvbVq6QLttc8Bqmmaqt5kXnvNmqCmhjodtv8cHbzPbCUgViPVWCyqSVMnu5HhgCnUjvYO06QFVVfVqGAKllSemA2hGakyHyslDZtspDpnv/1LyrUMTFWFuSYEZiZGhJiCeGC4+cMSgZhRuNn/93//131+scGxubEJ8tiZo5k9dlygjz72ZEE/2Semik24xZ4dDPSXtYG+PNsUmX3+3NMFfXGPmMatJ1g0VGDl/QmmSp5l1BVkCzmVbxe+BwQOzZ4925EFvtCRFNdwQDbsG99mCFRkqOLCtqzvmOtD+DtUL+0uJ3kGCajl8v1zTERBuboc6bdYpSBsrgO/gfTKn3e+wxT+0Y9+dGhNCeVtDo/JIADChyRRq4C2oagh+A2da7iPEAx0MI8zqOfv5bF1GLUeHKIr5DKKJCrVnc2or7fb3Xz8/Si0z43U0DxBuUKg5qY6NdsIq6G6UnOmTVFk6G/PDRaPJ5RJZbVqxUr19qB4Tb3aPlGxKFQWbh5uKny0RBhPm7XH/2/vXGPjqtMz/sw5Z64ej2/jcXwf27E3CSQkQNluFrYo4VJQt2rKh5IPRQoU1AhQIaHqFyrRfkjFlosAgYhYKr7AF9JsS0VpG1YtoK5AK5VVJViskISlWSBKnMS3uZ4z0/f5zwyYYMcOnMQ+yfuzjmbm3MaW58xz3vf//p/3G6IaJHjnzDtZFiSoqCorkdNlYMqtpZMXgl/WZ35hU3zMtZ9KmUcyd7/GcwoABYUVukzfLkVUCUVrrqgSCkNDWBrM955nWxrw3GdGzhxPPvP8fM8zU7bzHcshHgohH7n9zOud52kUJM1lvt+Nx1IIG6JK+LsxJd7Yb+5xc5cz4TnWr1+vouoTvn2Ls+iIYyqhsIPJQh5Tp0/JxeKZdnH5qdPoHRhGrihi6NhoTTbJhyKEqzesQTIRlyPln81zyD+cFcGTPFYEmJ853vGx4tfcMhPZh1XAEmib/bsHBtAkd31BhXfbLPmnCQS/fBRlpTEtgvo3H3t4MGuh+Tzdv1Ik9uzZY0SFBTqXKvxOa6RpleDim7BS+ZywLZGli4pXFPErm3QMo0teNK0dPcb3l+lfGuWn25tlaaFOwrJrd1GmEClim1RvSISXqV8KqCi0RLquaSVX8WqRKiuMU+0dyHSvqr9/MOE8NzZMZgGDoqw0ChXg7w57+JNuC+uS34x0/IQ35hwrVJSg41/EKuJpWWG4hWm4xRzy+YJZzyrd7Mj3kC+xJ2sElZKLeDyCazatQ5yVrwxGRTsrEt06Es3yuZlCI6JKseVP2SvL9opJ/zJlRIFNyAWYXb1a3jO4U1JY7MCqPs47U5QLQcEDDuerOJRbfPm0UMXPjlXwe+0WftB6fkVVUS4mfBNW02VGIk4KK6PMYrFgRHB49RjC0ZQsCYky5cIulbHpshG0ijCyUKmR4WXUytSv4zTK9OVWucLIV8RUfkqmUEnEVX7YyLw/4O5KLBZgBR6LpXgDoSjnG37Krm8P4b8mqjhwYvHlf6eAvxyycFNaP5+Kci74KKw0dJhG1S2iVCrCdctINCWw9vIrURHRLZeZzvXQlWkVYR2DbcQkBEfUlFNtwmwZJ/vRR5jzVx2IMEuEykiVgsq9PUa2Itrpri50BNhdieOqTz31FO68884FJ8Aryvngjl4Lfz6wtOVBEdU/lf1VVhXl3PBNWIuFSZRzE7V0rYgsi5Mu33AVTpycgcWqXoqlY+H671+BGCNSuVqprY7lyG/BmJTp4JAx4Gc+2KvkZH0UkaiNvoH+2qRl2IjF4hgYGa4dHEAYxdNZia4wnJytKMuFmz+Nmc8/WHCZrS+N15O/+SXcYs0cQVGUhfFNWCsVF55EqhRJGkUkU+2IxttQtR3k8kXYjoO1q3vQn2mXfeq9Wo2FofzYHJ/lSYooFidQKhdQqsbNfqkUHUtsiV5FlLwKsqtHEI4Et+sCJ8Rz0XFVZTnxijP45D9+gokP/g0nf/3mostv//un+PUr98hx/rR3o0k/jRZ4k6koFxv+pYIl8mQK17bCKJdcDGRHIa9QKDMatRGNWLhybMDMZbMdW/ZjxFk1Y6YUTVb5WuUJOHZMtodFbJskKLVwcuI08rN5EdwSeiRyDbLBPiduMwVM4wrON1OU5aBSzuOTAz9BZuM2DN6wGwNb/uKsS2bTH6NSmkVz30ZznX9XaIxAr1ua1/M64Hx3FvIpysWCb8LanGpFSC46W5ZEcxKZ7j7YkRhcj2X0VWNb2NKcMtXDIVYAy35Mi1JfwwxXPQ9etYCq1Sx6G0aTCHCxyCk2NJuYNBaHPYP99XcLHnRloe/nzp07jfOToiwHFbeET//zabSNXo/U4O/U1y5MaeaERLaPYmDrbkSav/LdnQ9+xhv+vby2CR/pJkTHoQYNtySa7tPXll1kaCPI4wmHkxrn4H5fzgagCU19H8J1PC+Feu77cZ+55+LzxnZFuRD4JqyimIhFExJ9esa6sBoK4/R0zlT0jg31oL8rjUxnu2wvmSrY2secjityMXCuamUWlVCrxK8hRGNRVLwqIlELbekO9Pb1Y2ztGmMWEUR4Ub/66qvGy5RzVhVlWZDP4ZF/34P8iUMoz07g2Pv7zr78zz4c+pe/Ru/mP0NTZqx+kvmh1y47ydAX95lnnjF2oTScZ4aGfrz0CX7uueeMENL3lvZ59K+l6xgN9+mBS1tPiiQ9e7dt22Z6qr733nvmZpTet0wfM9vT6OtKT2B63LIHLHuics48fX/5/jt27DCvaTrB36FhnK8oFwLfhJVVwLaIa2dXFzozPZg4PWuM9zMdKfSKoLa2NiMScYyVl2U7CDWmn8qTakjuKt1TEtrGKbVwZL+CXIDpTFqi3DaJgFsQrduhBRG2i6LxN3s46tQaZbmgMUvui4+QXv9j2NEk7EjTWRe3MIlYWx+a+zfWz7AwbLrNm0c+sq8pPXApjPy804yf3r+sLaBosmsNq+FvvPFG9PX1mSI+GtkzNUxLPVrrMaq97rrrjAsTI15+b7DXKC0CGd0SFgDyRpW2fuxTSkN72gTee++9xvSeAstWcTSnV1cz5ULim7BSLlyvjE1XXS1CGYEdjqE1mUCbLLQtbBdhZeG+xR8rZFI0vOhYLexVi7CtqNxQhxGJReCWK4jEOUfVwqlTk4gkgjtftXHXvnv3bvXhVJYVDtVEWlahY93vI33ZLYsubaM/kpvgpbUvpBjecccdprkFP+vs3MLoda6TEj//NERZCF4rjCz5vcBajMaxLHSkNy/htkZql40z2FSc25nNYjTMbXzO7jT79+83vsN6M6tcaHwT1lI+h8FsVj7I/Th2/JQIq41ENIJcoYjsQBfCNMmv1s0fKvJBr8qjVzKp47A3LdFq0sxZjUVjyMvdKg2tQ3AwuHrIXDhBhGNCTz75pGllxf6MinKxwnQsBaxRnEcB3bp1K8bHx01KloLJ9m3XXHONEVCuY9qXMLrlOrZ1Y2qY6ymSDUtUvuZ2Xk+MXvmcY6979+7FbbfdZqJf7s/MENvWMaJl6piNLR599FGTiub+inKh8E2xWOm7+Yc/wkcHP0G5aiHVFEOhXMLgwCpk2F6pUvMCZXETDSE4yFqt5GRdBeVKmI3hEE80yYVTQjKVhFsso00umKiJXIMJezHyS4OpMEUJMmam+VkKgLJyU82erBz3pAAyjcvULsdKX375ZZMmZi9TtoVj2pbbWQnMyJN9Vfnd8PHHH5vzcLx18+bNZkz14MGDJk1MgeY4Lgv/OD5LIX3kkUeMgPI8dDCjKDMV/Nprr5n0MIujbrnlFtNPlRG0olwofOvH+rPXXscrr/wTxo8eRzgax0h/RsQWuP0PbkJLImLGVaOmU428l+kTV0HVnUIk0mYMJeBZaM904pRcnO0ixE1NSaR7vluUt5z9WJkGe/zxx/HEE0/o1BplZSAiNv6PD2J029/L9bh4IWDu+EEc/9U/Y/DGh3D68C9w8qOfI3vTXxnP74WgUJ75fdKoyD3b98xS9pmPb3ucopxP/EsFF10c+r8v5KKLmrFVWhdu3XwVktHavDca7NMMgpEtoQew7bTIfbCNiisXhYgu28xFIw6SyWZ0rMqY/YIIKxPZCo5Ny1VUlaAzffRXOPHBv2Jw666ziiqZT+C4bjHhW8o+8/Ftj1OU84lvwsoULuyIiUp7u9uxcd0osr0ZE40a5yS5s6QphOe6Eqxy/qplLAxZxMQfz3PltYeW5laE4zEz3zWI8O958cUXceutt6K3t7e+VlGCSe7EIXzxy1cwuGUX7OjXG3krijI//kWsIpaenC7d3oTRoV4M9XaLmIrWWo4RUVuEsuSK+IrwsISYrkqWE0bFY3s4C52d7RLVRhFyHKRaW+pnDR4s4uAYE6cSKMpKozwzgU9//rhxXlps+e0v/gH5icMYkEg13FSrylUUZXF8E1aRS6Q7UrhsbACb1o7VIlCvSg2V6JMt4SwWBcMKO1zBSiZzHNM4LFKKROKYmppFV2+PWR9EOHGdLjL33XdfYCuZlYsYudZGfvy36Lzij9C54Q8XXVZdvR1rt+9FNKUV7YpyLvj27R8Jh7FhzRB+ePUViIbltBKthkVELdsywkoBZXcbpoRd+hwKbBknV7sZb/386OcYGh35cgw2aHBqAIuVOBmdc/AUZSUS7xhCU9eaJS3NvRtk/2z9SEVRlopvwppuT+H7V65HPBIRTa01LaeIWqZFXM0Igmb7rufJNgldqx4qIrBOJIzpqWn0ZQeQbP5qMnnQeOGFF3DDDTeY6QSKoijKpYtvwjo80IfWRFwEVGS1SmF1JEJ1TKTKdDC713AbI1RTxSf7MMrzRFwpqJnvOLVmOXnnnXfM38I5c4qiKMqljW/CGgvbsCVW5QmZ6mW0OrcMvjHmWC6VUZFtxWLtkeuzo8Nf2zdIcFyVk9/vv//+mquUoiiKcknjm7CaE0lEyukmtm0ZkTHRqolYLePhacRV9LNcdjGbzxlj7f7hLGIBHZPk30oLt7vvvvtrnqiKoijKpYtvwmoqfS3biI1BolHzIK/L5ZIRVUay7IAzNTOFRDyGzkwG6a5gGkEwIue4Kjtu0IBcURRFUYhvwkoZ9Uy0apvuEjR4aKR/GbU2otXpaYpqrXNF3/BgYFPA7777rmmRRRNwRVEURWngX8Raj1AbItoYb2TRUiTKlnC0PSwiGo2JsCYwODJs1geR48ePmwbLDzzwQH2NoiiKotTwNWJtRJ+NSLXsecZxyfXceq/EKmzHQUemCx2dabNP0GD7KRrr09C/0SNSURRFURr4JqzUVI47Mg1sTCDqokqxpW1ho/diIpHA0MiQeR40+HexAphtrHRcVVEURZkP/yJWCVmN8QORB4oqC5f4YnY2h3AkDCfs4HuXrzPzW4PI+++/b3pF3n777YEdG1YURVHOL76OsbKLTcimbaEIKguZREALhaK8CW0LPYlUR5Bsbq4fECymp6exd+9eY1nIqFxRFEVR5sPXiJXG+4zjGMyxQriYLxjjfXoFd3Zl0J8NZhUwx1X37NmDnTt3IpMJbp9YRVEU5fzjm7DSFMLhPNb6XFXKZ1u6HSHHQqKpCWsuW/dlUVOQ4Ljqvn37MDo6io0bN9bXKoqiKMr8+Kh0ITN3lQGpMYkQoV09NorsUNZ0rQmqu9L4+LgZW92+fXt9jaIoiqIsjH+pYPoEs0VcyMbk1BQ60mmJYB309vZgVXd3fa9gMSV/x9NPP42HHnpIW8EpiqIoS8I3YWVFMMV1anIKZddDYaZgvIPD4Uggx1Xpbfzss8+aCmAdV1UURVGWin+p4Cpw8tSk6VgTTySRz+XhVurG+ysQjp2ejddff93YLl577bX1NYqiKIqyOL6pHitnS6USwmx0LqLV2d2FZGplTq1hNPrWW2/VX32Tw4cP48CBA7jnnnsCWXClKIqiLB++qQadluLxmHnOuaojYyu3x+obb7yBDz/8sP7q68zMzOCxxx7Dww8/bNraKYqiKMq54JuwUkJDEqnSVWn9hpXrrnTo0CG8+eab2LFjR33NV7Ca+fnnn8e2bdvQ1dVVX6soiqIoS8c/YbXY0BwYWj2EltaW2soVBv2K2Zh8165d81b5vv322+Zxy5Yt5lFRFEVRzpWQRGlVP1K24x9+hBPHT+B3r/3Bly3jlpu77roLw8PD9VfA/v37jYPSzTffbMZQX3rpJWOoT44dO4YjR44YMwhNASuKoijfFt+E9TeHj5hWcCvJC5iNyPP5fP0VcPToUVPlyzR1LpfDZ599Vt8CzM7OorW1FYODg/U1iqIoinLu+Casbtk13WsURVEU5VLGN2FVFEVRFMVPgwhFURRFUVRYFUVRFMVPVFgVRVEUxUdUWBVFURTFR1RYFUVRFMVHVFgVRVEUxTeA/wetUFLqfhkT0wAAAABJRU5ErkJggg=="}}},{"metadata":{"trusted":false,"_uuid":"e2dc7ff4cadc09b9512cb094591ede61841ad160"},"cell_type":"code","source":"def runCNNconfusion(a,b,c,d,e,f,g,h):\n    # In -> [[Conv2D->relu]*2 -> MaxPool2D -> Dropout]*2 -> Flatten -> Dense -> Dropout -> Out\n    batch_size = 128\n    num_classes = f\n    epochs = g\n    #img_rows, img_cols = X_train.shape[1],b.shape[2]\n    input_shape = (128, 128, 3)\n    model = Sequential()\n    model.add(Conv2D(filters = 32, kernel_size = (3,3),padding = 'Same', activation ='relu', input_shape = input_shape,strides=h))\n    model.add(Conv2D(filters = 32, kernel_size = (3,3),padding = 'Same', activation ='relu'))\n    model.add(MaxPool2D(pool_size=(2,2)))\n    model.add(BatchNormalization())\n    model.add(Dropout(0.5))\n    model.add(Conv2D(filters = 16, kernel_size = (3,3),padding = 'Same', activation ='relu'))\n    model.add(Conv2D(filters = 16, kernel_size = (3,3),padding = 'Same',  activation ='relu'))\n    model.add(MaxPool2D(pool_size=(2,2)))\n    model.add(BatchNormalization())\n    model.add(Dropout(0.5))\n    model.add(Conv2D(filters = 8, kernel_size = (3,3),padding = 'Same', activation ='relu'))\n    model.add(Conv2D(filters = 8, kernel_size = (3,3),padding = 'Same',  activation ='relu'))\n    model.add(MaxPool2D(pool_size=(2,2)))\n    model.add(BatchNormalization())\n    model.add(Dropout(0.5))\n    model.add(Flatten())\n    model.add(Dense(1024, activation = \"relu\"))\n    model.add(Dropout(0.5))\n    model.add(Dense(8, activation = \"relu\"))\n    model.add(Dropout(0.5))\n    model.add(Dense(num_classes, activation = \"softmax\"))\n    # Define the optimizer\n    optimizer = Adagrad()\n    model.compile(optimizer = optimizer , loss = \"categorical_crossentropy\", metrics=[\"accuracy\"])\n    datagen = ImageDataGenerator(\n        featurewise_center=False,  # set input mean to 0 over the dataset\n        samplewise_center=True,  # set each sample mean to 0\n        featurewise_std_normalization=True ,  # divide inputs by std of the dataset\n        samplewise_std_normalization=True,  # divide each input by its std\n        zca_whitening=False,  # apply ZCA whitening\n        rotation_range=40,  # randomly rotate images in the range (degrees, 0 to 180)\n        width_shift_range=0.4,  # randomly shift images horizontally (fraction of total width)\n        height_shift_range=0.4,  # randomly shift images vertically (fraction of total height)\n        horizontal_flip=True,  # randomly flip images\n        vertical_flip=False)  # randomly flip images\n    datagen.fit(a)\n    history = model.fit_generator(datagen.flow(a,b, batch_size=32),\n                        steps_per_epoch=len(a) / 32, epochs=epochs, class_weight = e,  validation_data = [c, d],callbacks = [MetricsCheckpoint('logs')])\n    score = model.evaluate(c,d, verbose=0) \n    plot_learning_curve(history)\n    plt.show()\n    plotKerasLearningCurve()\n    plt.show()\n    print('\\nKeras CNN #2B - accuracy:', score[1],'\\n')\n    Y_pred = model.predict(c)\n    print('\\n', sklearn.metrics.classification_report(np.where(d > 0)[1], np.argmax(Y_pred, axis=1), target_names=list(dict_characters.values())), sep='')    \n    Y_pred_classes = np.argmax(Y_pred,axis = 1) \n    Y_true = np.argmax(d,axis = 1) \n    confusion_mtx = confusion_matrix(Y_true, Y_pred_classes) \n    plot_confusion_matrix(confusion_mtx, classes = list(dict_characters.values()))\n    plt.show()\nrunCNNconfusion(X_train, Y_trainHot, X_test, Y_testHot,class_weight,8,1,1)","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"940186cae17206e96e17cad6f70e0791d9098291"},"cell_type":"markdown","source":"# (IMPLEMENTATION) Test My Algorithm on Sample Images!\n"},{"metadata":{"trusted":false,"_uuid":"8a9f5f69c73d4d7dbfa3bb1efec902c988a3a2c4"},"cell_type":"code","source":"def xRay_detector(img_path):\n    prediction = ResNet50_predict_labels(img_path)\n    return ((prediction <= 268) & (prediction >= 151)) \n\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":false,"_uuid":"8ce74e83b7a7dbd567645cb0e7c6f75fabae6806"},"cell_type":"code","source":"## Load the cell\nsample_files = np.array(glob(\"sample_pictures/*\"))\nprint(sample_files)","execution_count":null,"outputs":[]},{"metadata":{"trusted":false,"_uuid":"29529ba9644b80b3b1be3bf7eedd7adbee90a747"},"cell_type":"code","source":"","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.6.6"}},"nbformat":4,"nbformat_minor":1}