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+{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":4310761,"sourceType":"datasetVersion","datasetId":2539169,"isSourceIdPinned":false},{"sourceId":308902,"sourceType":"modelInstanceVersion","isSourceIdPinned":true,"modelInstanceId":262453,"modelId":283576},{"sourceId":309799,"sourceType":"modelInstanceVersion","isSourceIdPinned":true,"modelInstanceId":262901,"modelId":284022}],"dockerImageVersionId":30918,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"# Imports","metadata":{}},{"cell_type":"code","source":"#cropping imports\nimport os\nimport cv2\nimport torch\nfrom torch.utils.data import Dataset","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-30T19:06:29.358975Z","iopub.execute_input":"2025-03-30T19:06:29.359328Z","iopub.status.idle":"2025-03-30T19:06:33.744848Z","shell.execute_reply.started":"2025-03-30T19:06:29.359303Z","shell.execute_reply":"2025-03-30T19:06:33.743691Z"}},"outputs":[],"execution_count":2},{"cell_type":"code","source":"#preprocessing imports\nfrom torch.utils.data import DataLoader\nimport torchvision.transforms as transforms\nfrom PIL import Image\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport math\n#from sklearn.model_selection import train_test_split","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-30T19:06:33.746226Z","iopub.execute_input":"2025-03-30T19:06:33.746718Z","iopub.status.idle":"2025-03-30T19:06:37.255507Z","shell.execute_reply.started":"2025-03-30T19:06:33.746689Z","shell.execute_reply":"2025-03-30T19:06:37.254496Z"}},"outputs":[],"execution_count":3},{"cell_type":"code","source":"# Model imports\nimport torch.nn as nn\nimport torchvision.transforms.functional as TF\n\nfrom torchsummary import summary","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-30T19:06:37.257362Z","iopub.execute_input":"2025-03-30T19:06:37.257865Z","iopub.status.idle":"2025-03-30T19:06:37.270867Z","shell.execute_reply.started":"2025-03-30T19:06:37.257833Z","shell.execute_reply":"2025-03-30T19:06:37.269782Z"}},"outputs":[],"execution_count":4},{"cell_type":"code","source":"#Training imports\nimport torch.nn as nn\nimport torch.optim as optim\nfrom tqdm.notebook import tqdm\nfrom itertools import product\nimport sys","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-30T19:06:37.272655Z","iopub.execute_input":"2025-03-30T19:06:37.273063Z","iopub.status.idle":"2025-03-30T19:06:37.476757Z","shell.execute_reply.started":"2025-03-30T19:06:37.273021Z","shell.execute_reply":"2025-03-30T19:06:37.475798Z"}},"outputs":[],"execution_count":5},{"cell_type":"code","source":"#Training visualization imports\nimport cv2","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-30T19:06:37.477928Z","iopub.execute_input":"2025-03-30T19:06:37.478361Z","iopub.status.idle":"2025-03-30T19:06:37.483226Z","shell.execute_reply.started":"2025-03-30T19:06:37.478321Z","shell.execute_reply":"2025-03-30T19:06:37.481991Z"}},"outputs":[],"execution_count":6},{"cell_type":"code","source":"#Graph imports\nimport numpy as np\nimport matplotlib.pyplot as plt","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-30T19:06:37.484633Z","iopub.execute_input":"2025-03-30T19:06:37.484925Z","iopub.status.idle":"2025-03-30T19:06:37.510265Z","shell.execute_reply.started":"2025-03-30T19:06:37.484900Z","shell.execute_reply":"2025-03-30T19:06:37.508875Z"}},"outputs":[],"execution_count":7},{"cell_type":"code","source":"#Test imports\nimport torch\nimport torchvision\nimport matplotlib.pyplot as plt\nfrom torchvision import transforms\nfrom PIL import Image\nimport os\nimport random","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-30T19:06:37.511381Z","iopub.execute_input":"2025-03-30T19:06:37.511728Z","iopub.status.idle":"2025-03-30T19:06:37.530620Z","shell.execute_reply.started":"2025-03-30T19:06:37.511693Z","shell.execute_reply":"2025-03-30T19:06:37.529370Z"}},"outputs":[],"execution_count":8},{"cell_type":"markdown","source":"# Preprocessing\n### Cropping","metadata":{}},{"cell_type":"code","source":"class TumorDataset(Dataset):\n    def __init__(self, root_dir, save_dir, apply_cropping=True, transform=None):\n        \"\"\"\n        Args:\n            root_dir (str): Path to the dataset directory.\n            save_dir (str): Path to save processed images and masks.\n            apply_cropping (bool): Whether to apply cropping.\n            transform (callable, optional): Optional transform for the images.\n        \"\"\"\n        self.root_dir = root_dir\n        self.save_dir = save_dir\n        self.apply_cropping = apply_cropping\n        self.transform = transform\n        self.data = []  # Stores (image_path, mask_path, save_img_path, save_mask_path)\n\n        #defining paths\n        img_dir = os.path.join(self.root_dir, \"images\")\n        mask_dir = os.path.join(self.root_dir, \"masks\")\n        save_img_dir = os.path.join(self.save_dir, \"images\")\n        save_mask_dir = os.path.join(self.save_dir, \"masks\")\n\n        #to create save directories\n        os.makedirs(save_img_dir, exist_ok=True)\n        os.makedirs(save_mask_dir, exist_ok=True)\n\n        #to get all image files\n        img_files = sorted(os.listdir(img_dir))\n        mask_files = sorted(os.listdir(mask_dir))\n\n        print(f\"Total images found in dataset: {len(img_files)}, Total masks found: {len(mask_files)}\")\n\n        #to match images and masks\n        for img_name in img_files:\n            img_path = os.path.join(img_dir, img_name)\n            mask_path = os.path.join(mask_dir, img_name)\n\n            save_img_path = os.path.join(save_img_dir, img_name)\n            save_mask_path = os.path.join(save_mask_dir, img_name)\n\n            if os.path.exists(mask_path):\n                self.data.append((img_path, mask_path, save_img_path, save_mask_path))\n            else:\n                print(f\"Warning: No corresponding mask found for {img_name}\")\n\n    def crop_image_and_mask(self, img, mask):\n        \"\"\"Applies cropping based on the tumor region, keeping original resolution.\"\"\"\n        _, thresh = cv2.threshold(img, 40, 255, cv2.THRESH_BINARY)  #binary image for contour detection\n        contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n\n        if contours:\n            c = max(contours, key=cv2.contourArea)  #get largest contour\n            x, y, w, h = cv2.boundingRect(c)\n\n            #apply cropping to both image and mask\n            img = img[y:y+h, x:x+w]\n            mask = mask[y:y+h, x:x+w]\n\n        return img, mask\n\n    def __len__(self):\n        return len(self.data)\n\n    def __getitem__(self, idx):\n        img_path, mask_path, save_img_path, save_mask_path = self.data[idx]\n        \n        img = cv2.imread(img_path, cv2.IMREAD_GRAYSCALE)\n        mask = cv2.imread(mask_path, cv2.IMREAD_GRAYSCALE)\n\n        if img is None or mask is None:\n            print(f\"Warning: Could not load image or mask for {img_path}\")\n            return None\n\n        if self.apply_cropping:\n            img, mask = self.crop_image_and_mask(img, mask)\n\n        #save processed image and mask\n        cv2.imwrite(save_img_path, img)\n        cv2.imwrite(save_mask_path, mask)\n\n        #convert to PyTorch tensors\n        img_tensor = torch.tensor(img, dtype=torch.float32).unsqueeze(0)  # Add channel dimension\n        mask_tensor = torch.tensor(mask, dtype=torch.float32).unsqueeze(0)  # Keep mask format\n        if self.transform:\n            img_tensor = self.transform(img_tensor)\n\n        return img_tensor, mask_tensor\n\n# ------------------------------\n# Applying preprocessing to all images\n# ------------------------------\ndataset_path = \"/kaggle/input/brain-tumor-segmentation\"\ncrop_path = \"cropped_images/\"\n\n# Check if dataset exists\nprint(\"Dataset exists:\", os.path.exists(dataset_path))\n\n# List contents of dataset directory\nprint(\"Contents:\", os.listdir(dataset_path))\n\n#initialize dataset\ndataset = TumorDataset(root_dir=dataset_path, save_dir=crop_path, apply_cropping=True)\n\n#process all images\nfor i in range(len(dataset)):\n    sample = dataset[i]\n    if sample is not None:\n        print(f\"Processed {i+1}/{len(dataset)} images\", end=\"\\r\")  # Show progress\n\nprint(\"\\nProcessing complete!\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-30T19:06:41.662801Z","iopub.execute_input":"2025-03-30T19:06:41.663249Z","iopub.status.idle":"2025-03-30T19:08:09.001728Z","shell.execute_reply.started":"2025-03-30T19:06:41.663199Z","shell.execute_reply":"2025-03-30T19:08:09.000411Z"}},"outputs":[{"name":"stdout","text":"Dataset exists: True\nContents: ['images', 'masks']\nTotal images found in dataset: 3064, Total masks found: 3064\nProcessed 3064/3064 images\nProcessing complete!\n","output_type":"stream"}],"execution_count":9},{"cell_type":"code","source":"print(f\"Total cropped images found: {len(os.listdir(os.path.join(crop_path,'images')))}, Total cropped masks found: {len(os.listdir(os.path.join(crop_path,'masks')))}\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-30T19:08:10.787875Z","iopub.execute_input":"2025-03-30T19:08:10.788494Z","iopub.status.idle":"2025-03-30T19:08:10.798172Z","shell.execute_reply.started":"2025-03-30T19:08:10.788444Z","shell.execute_reply":"2025-03-30T19:08:10.796698Z"}},"outputs":[{"name":"stdout","text":"Total cropped images found: 3064, Total cropped masks found: 3064\n","output_type":"stream"}],"execution_count":10},{"cell_type":"markdown","source":"### Data augmentation and resizing","metadata":{}},{"cell_type":"code","source":"def train_val_test_split(images, masks, val_size=0.15, test_size=0.15, random_state=None):\n    \"\"\"\n    Splits images and masks into train, validation, and test sets while maintaining correspondence.\n\n    Args:\n        images (list): List of image file paths or image data.\n        masks (list): List of corresponding mask file paths or mask data.\n        val_size (float): Proportion of samples for the validation set.\n        test_size (float): Proportion of samples for the test set.\n        random_state (int, optional): Random seed for reproducibility.\n\n    Returns:\n        tuple: (train_images, val_images, test_images, train_masks, val_masks, test_masks)\n    \"\"\"\n    assert len(images) == len(masks), \"Images and masks must have the same length.\"\n\n    if random_state is not None:\n        np.random.seed(random_state)\n\n    total_samples = len(images)\n    val_count = math.ceil(val_size * total_samples)\n    test_count = math.ceil(test_size * total_samples)\n    train_count = total_samples - val_count - test_count\n\n    indices = np.arange(total_samples)\n    np.random.shuffle(indices)\n\n    train_indices = indices[:train_count]\n    val_indices = indices[train_count:train_count + val_count]\n    test_indices = indices[train_count + val_count:]\n\n    train_images = [images[i] for i in train_indices]\n    val_images = [images[i] for i in val_indices]\n    test_images = [images[i] for i in test_indices]\n\n    train_masks = [masks[i] for i in train_indices]\n    val_masks = [masks[i] for i in val_indices]\n    test_masks = [masks[i] for i in test_indices]\n\n    return train_images, val_images, test_images, train_masks, val_masks, test_masks","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-30T19:08:12.978123Z","iopub.execute_input":"2025-03-30T19:08:12.978481Z","iopub.status.idle":"2025-03-30T19:08:12.986332Z","shell.execute_reply.started":"2025-03-30T19:08:12.978452Z","shell.execute_reply":"2025-03-30T19:08:12.985079Z"}},"outputs":[],"execution_count":11},{"cell_type":"code","source":"# -----------------------\n# Define Paths\n# -----------------------\nimage_path = \"/kaggle/working/cropped_images/images\"\nmask_path = \"/kaggle/working/cropped_images/masks\"\n\nimages = sorted(os.listdir(image_path))\nmasks = sorted(os.listdir(mask_path))\n\ntrain_imgs, val_imgs, test_imgs, train_masks, val_masks, test_masks = train_val_test_split(images, masks, val_size=0.15, test_size=0.15, random_state=42)\n#val_imgs, test_imgs, val_masks, test_masks = train_test_split(test_imgs, test_masks, test_size=0.5, random_state=42)\n\nprint(\"No of train images = \",len(train_imgs))\nprint(\"No of validation images = \",len(val_imgs))\nprint(\"No of test images = \",len(test_imgs))\n# -----------------------\n# define augmentations\n# -----------------------\ntrain_transform = transforms.Compose([\n    transforms.Resize(size=(256,256)),\n    transforms.RandomRotation(degrees=15),\n    transforms.RandomHorizontalFlip(),\n    transforms.RandomVerticalFlip(),\n    transforms.ColorJitter(brightness=0.1, contrast=0.1),\n    transforms.ToTensor()\n])\n\nval_test_transform = transforms.Compose([\n    transforms.Resize((256,256)),\n    transforms.ToTensor()\n])\n\n# -----------------------\n# custom Dataset class with synchronized augmentations\n# -----------------------\nclass BrainTumorDataset(Dataset):\n    def __init__(self, image_files, mask_files, img_dir, mask_dir, transform=None, num_aug=5):\n        self.image_files = image_files\n        self.mask_files = mask_files\n        self.img_dir = img_dir\n        self.mask_dir = mask_dir\n        self.transform = transform\n        self.num_aug = num_aug\n\n    def __len__(self):\n        return len(self.image_files) * (self.num_aug + 1)  # original + augmented versions\n\n    def __getitem__(self, idx):\n        original_idx = idx // (self.num_aug + 1)  # to get corresponding original image index\n        aug_idx = idx % (self.num_aug + 1)  # to get augmentation number\n        \n        img_path = os.path.join(self.img_dir, self.image_files[original_idx])\n        mask_path = os.path.join(self.mask_dir, self.mask_files[original_idx])\n\n        image = Image.open(img_path).convert(\"L\")\n        mask = Image.open(mask_path).convert(\"L\")\n\n        if aug_idx == 0:\n            image = val_test_transform(image)\n            mask = val_test_transform(mask)\n        else:\n            seed = torch.randint(0, 10000, (1,)).item()\n            torch.manual_seed(seed)\n            image = self.transform(image)\n            torch.manual_seed(seed)\n            mask = self.transform(mask)\n\n        return image, mask\n\n    def show_sample(self, idx):\n        \"\"\"Display original and 5 augmented versions of an image-mask pair.\"\"\"\n        original_idx = idx // (self.num_aug + 1)  # to get corresponding original index\n        \n        fig, axes = plt.subplots(2, self.num_aug + 1, figsize=(15, 6))\n        titles = [\"Original Image\"] + [f\"Augmented {i}\" for i in range(1, self.num_aug + 1)]\n        \n        for aug_idx in range(self.num_aug + 1):\n            sample_img, sample_mask = self.__getitem__(original_idx * (self.num_aug + 1) + aug_idx)\n            \n            sample_img = sample_img.squeeze().numpy()\n            sample_mask = sample_mask.squeeze().numpy()\n            \n            axes[0, aug_idx].imshow(sample_img, cmap='gray')\n            axes[0, aug_idx].set_title(titles[aug_idx])\n            axes[0, aug_idx].axis(\"off\")\n            \n            axes[1, aug_idx].imshow(sample_mask, cmap='gray')\n            axes[1, aug_idx].set_title(titles[aug_idx])\n            axes[1, aug_idx].axis(\"off\")\n\n        plt.suptitle(\"Original & Augmented Images and Masks\")\n        plt.show()\n\n# -----------------------\n# create Dataset objects\n# -----------------------\ntrain_dataset = BrainTumorDataset(train_imgs, train_masks, image_path, mask_path, transform=train_transform, num_aug=5)\nval_dataset = BrainTumorDataset(val_imgs, val_masks, image_path, mask_path, transform=None, num_aug=0)  # No augmentation for validation\ntest_dataset = BrainTumorDataset(test_imgs, test_masks, image_path, mask_path, transform=None, num_aug=0)  # No augmentation for test\n\n# -----------------------\n# create DataLoaders\n# -----------------------\ntrain_loader = DataLoader(train_dataset, batch_size=16, shuffle=True, num_workers=2)\nval_loader = DataLoader(val_dataset, batch_size=16, shuffle=False, num_workers=2)\ntest_loader = DataLoader(test_dataset, batch_size=16, shuffle=False, num_workers=2)\n\n# -----------------------\n# verify DataLoader\n# -----------------------\nfor images, masks in train_loader:\n    print(\"Image batch shape:\", images.shape)  # (batch_size, 1, 512, 512) # 1 is the number of channels\n    print(\"Mask batch shape:\", masks.shape)  # (batch_size, 1, 512, 512)\n    print(\"Image min pixel value:\", images.min().item())  # Should be 0.0\n    print(\"Image max pixel value:\", images.max().item())  # Should be 1.0\n    print(\"Mask min pixel value:\", masks.min().item())  # Should be 0.0\n    print(\"Mask max pixel value:\", masks.max().item())  # Should be 1.0\n    break\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-30T19:08:13.501905Z","iopub.execute_input":"2025-03-30T19:08:13.502249Z","iopub.status.idle":"2025-03-30T19:08:14.126412Z","shell.execute_reply.started":"2025-03-30T19:08:13.502220Z","shell.execute_reply":"2025-03-30T19:08:14.125211Z"}},"outputs":[{"name":"stdout","text":"No of train images =  2144\nNo of validation images =  460\nNo of test images =  460\nImage batch shape: torch.Size([16, 1, 256, 256])\nMask batch shape: torch.Size([16, 1, 256, 256])\nImage min pixel value: 0.0\nImage max pixel value: 1.0\nMask min pixel value: 0.0\nMask max pixel value: 1.0\n","output_type":"stream"}],"execution_count":12},{"cell_type":"code","source":"train_dataset.show_sample(0)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-30T19:08:16.753121Z","iopub.execute_input":"2025-03-30T19:08:16.753498Z","iopub.status.idle":"2025-03-30T19:08:17.746146Z","shell.execute_reply.started":"2025-03-30T19:08:16.753471Z","shell.execute_reply":"2025-03-30T19:08:17.744985Z"}},"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1500x600 with 12 Axes>","image/png":"iVBORw0KGgoAAAANSUhEUgAABJ4AAAIICAYAAAAv/CSOAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuNSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/xnp5ZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOy9d3hc1bX//Z0ZjaY3aUa9y3I37gYMtrGxMWBjcCihBtMCKST8buDehIRQQwi5JOQGSEhCIAk1gCGE7hgXisHYGPcqq3dN0YykUZ3z/uF3be85OqNiLCTw+jwPD9aZM+fsc2avvVfba+sURVHAMAzDMAzDMAzDMAzDMMcZ/Ug3gGEYhmEYhmEYhmEYhvl6wo4nhmEYhmEYhmEYhmEYZlhgxxPDMAzDMAzDMAzDMAwzLLDjiWEYhmEYhmEYhmEYhhkW2PHEMAzDMAzDMAzDMAzDDAvseGIYhmEYhmEYhmEYhmGGBXY8MQzDMAzDMAzDMAzDMMMCO54YhmEYhmEYhmEYhmGYYYEdTwzDMAzDMAzDMAzDMMywwI4nhmEYZtRw1113QafTHdN3n3rqKeh0OpSXlx/fRkmUl5dDp9PhqaeeGrZ7MCMH/76jlzPOOANnnHHGSDdjUJxxxhmYPHnySDeDYRiGYUYN7HhiGIZhvjC7d+/GlVdeiezsbJhMJmRlZeGKK67A7t27R7ppI8qmTZuwYMECOJ1OpKWl4ZxzzsGHH354TNfau3cvdDodzGYzQqHQ8W3oV4zHHntsRJ1D69evh06nw0svvTRibWC0KSgogE6nw+LFizU///Of/wydTgedToctW7Z8ya1jGIZhmBMTdjwxDMMwX4jVq1djxowZWLt2La655ho89thjuO6667Bu3TrMmDEDr7zyyqCv9bOf/QzRaPSY2nHVVVchGo0iPz//mL5/vKmsrMTSpUtRWVmJu+++G//zP/8DRVGwdu3aY7re008/jYyMDAA44R0eI+14YkY3ZrMZ69atQ319fZ/PnnnmGZjN5hFoFcMwDMOcuCSNdAMYhmGYry6lpaW46qqrUFRUhI0bN8Ln84nPfvjDH2LevHm46qqrsGPHDhQVFSW8TltbG2w2G5KSkpCUdGxTk8FggMFgOKbvDgdvvPEGIpEI1q5di9mzZwMAfvSjH6Gzs3PI11IUBc8++ywuv/xylJWV4ZlnnsH1119/vJvMMF8LTjvtNHz66ad44YUX8MMf/lAcr66uxvvvv4+VK1fi5ZdfHsEWMgzDMMyJBWc8MQzDMMfMr3/9a7S3t+NPf/pTnNMJALxeLx5//HG0tbXhwQcfFMepjtOePXtw+eWXw+Px4PTTT4/7TCYajeIHP/gBvF4vHA4HVqxYgZqaGuh0Otx1113iPK0aTwUFBVi+fDk++OADzJkzB2azGUVFRfj73/8ed49AIIBbb70VU6ZMgd1uh9PpxDnnnIPt27cf87vR649MsYqixB03mUxDvtaHH36I8vJyXHrppbj00kuxceNGVFdX9zlP/U6IgoICrFq1Ku7Yjh07sGDBAlgsFuTk5OC+++7Dk08+mfAdrl+/HrNmzYLFYsGUKVOwfv16AEcy3qZMmQKz2YyZM2di27Ztfe6/b98+XHTRRUhJSYHZbMasWbPw2muvxZ1Dv9+HH36I//qv/4LP54PNZsPKlSvR1NQU157du3djw4YNYsmUXPsnFArhlltuQW5uLkwmE8aMGYNf/epXiMVicfcLhUJYtWoVXC4X3G43rr766i+0hJH67oEDB3DllVfC5XLB5/PhjjvugKIoqKqqwvnnnw+n04mMjAw89NBDcd/v6urCz3/+c8ycORMulws2mw3z5s3DunXr+tzL7/fjqquugtPpFG3fvn27Zn2qwbz77u5u3H333SgpKYHZbEZqaipOP/10rFmzpt9nHqzc0NLEf/7zn/jFL36BnJwcmM1mnHnmmTh06FCf6/7pT39CcXExLBYL5syZg/fff7/fdqgxm834xje+gWeffTbu+HPPPQePx4OlS5f2+c6OHTuwatUqFBUVwWw2IyMjA9deey38fn/ceZFIBLfccgsKCgpgMpmQlpaGJUuW4LPPPuu3Te+++y6sVisuu+wy9PT0AADWrFmD008/HW63G3a7HePGjcPtt98+pGdlGIZhmK8CnPHEMAzDHDP//ve/UVBQgHnz5ml+Pn/+fBQUFOCNN97o89nFF1+MkpIS3H///X2cMzKrVq3CP//5T1x11VU45ZRTsGHDBixbtmzQbTx06BAuuugiXHfddbj66qvx17/+FatWrcLMmTMxadIkAMDhw4fx6quv4uKLL0ZhYSEaGhrw+OOPY8GCBdizZw+ysrIGfT/iG9/4Bv7nf/4Ht912G9asWYPk5OQhX4N45plnUFxcjNmzZ2Py5MmwWq147rnncNtttx3T9WpqarBw4ULodDr85Cc/gc1mw1/+8peETrFDhw7h8ssvx4033ogrr7wS//u//4vzzjsPf/zjH3H77bfju9/9LgDgl7/8JS655BLs379fON52796N0047DdnZ2fjxj38Mm82Gf/7zn7jgggvw8ssvY+XKlXH3uvnmm+HxeHDnnXeivLwcDz/8ML7//e/jhRdeAAA8/PDDuPnmm2G32/HTn/4UAJCeng4AaG9vx4IFC1BTU4Mbb7wReXl5+Oijj/CTn/wEdXV1ePjhhwEccQaef/75+OCDD3DTTTdhwoQJeOWVV3D11Vcf0/uU+eY3v4kJEybggQcewBtvvIH77rsPKSkpePzxx7Fo0SL86le/wjPPPINbb70Vs2fPxvz58wEA4XAYf/nLX3DZZZfhhhtuQCQSwRNPPIGlS5di8+bNmDZtGgAgFovhvPPOw+bNm/Gd73wH48ePx7/+9S/Ntg/23d9111345S9/ieuvvx5z5sxBOBzGli1b8Nlnn2HJkiUJn3WocvPAAw9Ar9fj1ltvRUtLCx588EFcccUV+OSTT8Q5TzzxBG688UbMnTsXt9xyCw4fPowVK1YgJSUFubm5g/4dLr/8cpx11lkoLS1FcXExAODZZ5/FRRddBKPR2Of8NWvW4PDhw7jmmmuQkZGB3bt3409/+hN2796Njz/+WDjEb7rpJrz00kv4/ve/j4kTJ8Lv9+ODDz7A3r17MWPGDM22vP7667jooovwzW9+E3/9619hMBiwe/duLF++HCeddBLuuecemEwmHDp06JhrwDEMwzDMqEZhGIZhmGMgFAopAJTzzz+/3/NWrFihAFDC4bCiKIpy5513KgCUyy67rM+59BmxdetWBYByyy23xJ23atUqBYBy5513imNPPvmkAkApKysTx/Lz8xUAysaNG8WxxsZGxWQyKT/60Y/EsY6ODqW3tzfuHmVlZYrJZFLuueeeuGMAlCeffLLfZ1YURfnoo48Uj8ejJCcnKxdffLHS09Mz4He06OrqUlJTU5Wf/vSn4tjll1+uTJ06tc+56ndC5OfnK1dffbX4++abb1Z0Op2ybds2cczv9yspKSkJ3+FHH30kjr3zzjsKAMVisSgVFRXi+OOPP64AUNatWyeOnXnmmcqUKVOUjo4OcSwWiylz585VSkpKxDH6/RYvXqzEYjFx/P/9v/+nGAwGJRQKiWOTJk1SFixY0Oc57733XsVmsykHDhyIO/7jH/9YMRgMSmVlpaIoivLqq68qAJQHH3xQnNPT06PMmzdvUL/vunXrFADKiy++KI5R3/32t78dd82cnBxFp9MpDzzwgDgeDAYVi8US95v09PQonZ2dcfcJBoNKenq6cu2114pjL7/8sgJAefjhh8Wx3t5eZdGiRX3aPth3P3XqVGXZsmX9PrMWg5Ubel8TJkyIe8bf/e53CgBl586diqIc6etpaWnKtGnT4s7705/+pADQ/M3V5OfnK8uWLVN6enqUjIwM5d5771UURVH27NmjAFA2bNgg+tqnn34qvtfe3t7nWs8991yf8cPlcinf+973+m3DggULlEmTJimKcuT3MhqNyg033BD3rn77298qAJSmpqYBn4lhGIZhvurwUjuGYRjmmIhEIgAAh8PR73n0eTgcjjt+0003DXiPt99+GwBERg1x8803D7qdEydOjMvI8vl8GDduHA4fPiyOmUwmkaHT29sLv98vlr4MtIRGi4qKCpx77rm47rrr8Oqrr+KVV17BDTfcEJfZdeONNw4qg+Ott96C3+/HZZddJo5ddtll2L59+zHvGvj222/j1FNPFVk0AJCSkoIrrrhC8/yJEyfi1FNPFX+ffPLJAIBFixYhLy+vz3F6t4FAAO+99x4uueQSRCIRNDc3o7m5GX6/H0uXLsXBgwdRU1MTd69vf/vbccst582bh97eXlRUVAz4XC+++CLmzZsHj8cj7tXc3IzFixejt7cXGzduBAC8+eabSEpKwne+8x3xXYPBMKR+lQi59pbBYMCsWbOgKAquu+46cdztdvfpgwaDQWTFxWIxBAIB9PT0YNasWXF98O2334bRaMQNN9wgjun1enzve9+La8dQ3r3b7cbu3btx8ODBIT3rUOXmmmuuicv8I7mk97BlyxY0NjbipptuijuPlkQOBYPBgEsuuQTPPfccgCNZg7m5uQmzMy0Wi/h3R0cHmpubccoppwBA3LO43W588sknqK2tHbANzz33HL75zW/ixhtvxOOPPy7eFV0HAP71r3/1WQbKMAzDMF832PHEMAzDHBPkUCIHVCISOagKCwsHvEdFRQX0en2fc8eMGTPodsqOEcLj8SAYDIq/Y7EYfvvb36KkpAQmkwlerxc+nw87duxAS0vLoO9F/PKXv4Rer8d9992Hc845B3/961/x1FNP4ZZbbhHn7Nq1Szhq+uPpp59GYWGhWIpz6NAhFBcXw2q14plnnhly24Aj71XrHSZ6r+p3SE4AteOMjtO7PXToEBRFwR133AGfzxf335133gkAaGxs7PdeHo8n7pr9cfDgQbz99tt97rV48eK4e1VUVCAzMxN2uz3u++PGjRvwHgOh9a7MZjO8Xm+f4+pn+tvf/oaTTjpJ1Fny+Xx444034vogtd1qtcZ9V/3bDeXd33PPPQiFQhg7diymTJmC2267DTt27BjwWYcqNwP9tuRcLCkpiTvPaDT2uzlBIi6//HLs2bMH27dvx7PPPotLL720Tw05IhAI4Ic//CHS09NhsVjg8/nEuCM/y4MPPohdu3YhNzcXc+bMwV133RXnQCTKyspw5ZVX4sILL8Tvf//7Pvf95je/idNOOw3XX3890tPTcemll+Kf//wnO6EYhmGYryVc44lhGIY5JlwuFzIzMwc0UHfs2IHs7Gw4nc6443KGwXCSaKc7Ofvo/vvvxx133IFrr70W9957L1JSUqDX63HLLbcckyH40UcfYdq0aaJm0lVXXYWGhgbcdtttcDgcuPTSS7Fp06YBd9YKh8P497//jY6Ojj7GOHCkZs0vfvGLhMY00dvbO+RnkEn0Dgd6t/Tubr31Vs2CzkBfh8lgfq9ExGIxLFmyBP/93/+t+fnYsWMHvMYXRav9g3mmp59+GqtWrcIFF1yA2267DWlpaTAYDPjlL3+J0tLSIbdjKO9+/vz5KC0txb/+9S+8++67+Mtf/oLf/va3+OMf/9jv7olDlZsv8tseCyeffDKKi4txyy23oKysDJdffnnCcy+55BJ89NFHuO222zBt2jTY7XbEYjGcffbZcc9yySWXYN68eXjllVfw7rvv4te//jV+9atfYfXq1TjnnHPEeZmZmcjMzMSbb76JLVu2YNasWXH3s1gs2LhxI9atW4c33ngDb7/9Nl544QUsWrQI77777qjaoZNhGIZhvijseGIYhmGOmeXLl+PPf/4zPvjgA7Ezncz777+P8vJy3Hjjjcd0/fz8fMRiMZSVlcU5XrR2wvoivPTSS1i4cCGeeOKJuOOhUKhPpspg0Ol0qKqqijt26623oqGhAb/4xS/wzDPPYPr06Tj//PP7vc7q1avR0dGBP/zhD33asX//fvzsZz/Dhx9+KN69x+PpszNbV1cX6urq4o7l5+drvsPj/V4pS8VoNIqso+NBIkdbcXExWltbB7xXfn4+1q5di9bW1risp/379x+3Ng6Vl156CUVFRVi9enXc81F2EpGfn49169ahvb09LutJ/dsN9d2npKTgmmuuwTXXXIPW1lbMnz8fd911V7+Op+MtN/n5+QCOZK4tWrRIHO/u7kZZWRmmTp065GtedtlluO+++zBhwoS4paUywWAQa9euxd13342f//zn4niipYeZmZn47ne/i+9+97tobGzEjBkz8Itf/CLO8WQ2m/H6669j0aJFOPvss7FhwwaxmQGh1+tx5pln4swzz8RvfvMb3H///fjpT3+KdevWHVd5YRiGYZiRhpfaMQzDMMfMbbfdBovFghtvvLHPtuOBQAA33XQTrFbrMe++Rpkajz32WNzx3//+98fW4AQYDIY+WRcvvvhin/pDg2Xx4sU4ePAg/vGPf8Qdf+CBBzBx4kSUl5djxYoVcTVftHj66adRVFSEm266CRdddFHcf7feeivsdnvccrvi4mJRx4j405/+1CfjaenSpdi0aRM+//xzcSwQCBzz0r1EpKWl4YwzzsDjjz/ex/kFAE1NTcd0XZvN1sfBBhzJRtm0aRPeeeedPp+FQiGxjf25556Lnp4e/OEPfxCf9/b2Hvd+NRQow0Xuh5988gk2bdoUd97SpUvR3d2NP//5z+JYLBbDo48+GnfeUN69WnbtdjvGjBmDzs7OAdt8POVm1qxZ8Pl8+OMf/4iuri5x/KmnntL8vQfD9ddfjzvvvBMPPfRQwnO03j0AsQsi0dvb22cJYVpaGrKysjTflcvlwjvvvIO0tDQsWbIkLnMtEAj0OZ8cYwO9d4ZhGIb5qsEZTwzDMMwxU1JSgr/97W+44oorMGXKFFx33XUoLCxEeXk5nnjiCTQ3N+O5554T25kPlZkzZ+LCCy/Eww8/DL/fj1NOOQUbNmzAgQMHACTOfBkqy5cvxz333INrrrkGc+fOxc6dO/HMM88cU10ZAPjJT36CV199FVdffTXWrFmDuXPnorW1Fc899xzKysowe/Zs3HfffTj11FNx1llnaV6jtrYW69atww9+8APNz00mE5YuXYoXX3wR//d//wej0Yjrr78eN910Ey688EIsWbIE27dvxzvvvNMn++S///u/8fTTT2PJkiW4+eabYbPZ8Je//AV5eXkIBALH7b0CwKOPPorTTz8dU6ZMwQ033ICioiI0NDRg06ZNqK6uxvbt24d8zZkzZ+IPf/gD7rvvPowZMwZpaWlYtGgRbrvtNrz22mtYvnw5Vq1ahZkzZ6KtrQ07d+7ESy+9hPLycni9Xpx33nk47bTT8OMf/xjl5eWYOHEiVq9efUz1vI4Xy5cvx+rVq7Fy5UosW7YMZWVl+OMf/4iJEyeitbVVnHfBBRdgzpw5+NGPfoRDhw5h/PjxeO2114QjQ/7tBvvuJ06ciDPOOAMzZ85ESkoKtmzZgpdeegnf//73B2zz8ZQbo9GI++67DzfeeCMWLVqEb37zmygrK8OTTz55zNfMz8/HXXfd1e85TqcT8+fPx4MPPoju7m5kZ2fj3XffRVlZWdx5kUgEOTk5uOiiizB16lTY7Xb85z//waeffprQseX1erFmzRqcfvrpWLx4MT744ANkZ2fjnnvuwcaNG7Fs2TLk5+ejsbERjz32GHJycjSzRxmGYRjmqww7nhiGYZgvxMUXX4zx48fjl7/8pXA2paamYuHChbj99tsxefLkL3T9v//978jIyMBzzz2HV155BYsXL8YLL7yAcePGwWw2H5dnuP3229HW1oZnn30WL7zwAmbMmIE33ngDP/7xj4/pel6vF5s3b8Zdd92Ff/3rX3juuefg9Xpx1lln4dlnn0VWVhbmzJmDiy++GB9++KHmO3r++ecRi8Vw3nnnJbzPeeedh5dffhlvvfUWVqxYgRtuuAFlZWV44okn8Pbbb2PevHlYs2YNzjzzzLjv5ebmCqfW/fffD5/Ph+9973uw2Wz4wQ9+cNzeK3DEqbFlyxbcfffdeOqpp+D3+5GWlobp06fHLWsaCj//+c9RUVGBBx98EJFIBAsWLMCiRYtgtVqxYcMG3H///XjxxRfx97//HU6nE2PHjsXdd98tip/r9Xq89tpruOWWW/D0009Dp9NhxYoVeOihhzB9+vTj9uxDYdWqVaivr8fjjz+Od955BxMnTsTTTz+NF198EevXrxfnGQwGvPHGG/jhD3+Iv/3tb9Dr9Vi5ciXuvPNOnHbaaXG/3WDf/Q9+8AO89tprePfdd9HZ2Yn8/Hzcd999A2YqHm+5AY7satjb24tf//rXuO222zBlyhS89tpruOOOO475moPh2Wefxc0334xHH30UiqLgrLPOwltvvYWsrCxxjtVqxXe/+128++67WL16NWKxGMaMGYPHHnssbodENdnZ2fjPf/6DefPmYcmSJdi4cSNWrFiB8vJy/PWvf0VzczO8Xi8WLFgQ108ZhmEY5uuCThmuio4MwzAMM0x8/vnnmD59Op5++mlcccUVI92crw233HILHn/8cbS2tnJx468Yr776KlauXIkPPvgAp5122kg3h2EYhmEYRsA1nhiGYZhRTTQa7XPs4Ycfhl6vx/z580egRV8P1O/V7/fjH//4B04//XR2Oo1y1L8d1adyOp2YMWPGCLWKYRiGYRhGG15qxzAMw4xqHnzwQWzduhULFy5EUlIS3nrrLbz11lv49re/jdzc3JFu3leWU089FWeccQYmTJiAhoYGPPHEEwiHw8O+pIn54tx8882IRqM49dRT0dnZidWrV+Ojjz7C/fffD4vFMtLNYxiGYRiGiYOX2jEMwzCjmjVr1uDuu+/Gnj170Nrairy8PFx11VX46U9/iqQkjp8cK7fffjteeuklVFdXQ6fTYcaMGbjzzjt5G/evAM8++yweeughHDp0CB0dHRgzZgy+853vDFgMnGEYhmEYZiRgxxPDMAzDMAzDMAzDMAwzLHCNJ4ZhGIZhGIZhGIZhGGZYYMcTwzAMwzAMwzAMwzAMMyyw44lhGIZhGIZhGIZhGIYZFtjxxDAMwzAMwzAMwzAMwwwL7HhiGIZhGIZhGIZhGIZhhgV2PDEMwzAMwzAMwzAMwzDDAjueGIZhGIZhGIZhGIZhmGGBHU8MwzAMwzAMwzAMwzDMsMCOJ4ZhGIZhGIZhGIZhGGZYYMcTwzAMwzAMwzAMwzAMMyyw44lhGIZhGIZhGIZhGIYZFtjxxDAMwzAMwzAMwzAMwwwL7HhiGIZhGIZhGIZhGIZhhgV2PDEMwzAMwzAMwzAMwzDDAjueGIZhGIZhGIZhGIZhmGGBHU8MwzAMwzAMwzAMwzDMsMCOJ4ZhGIZhGIZhGIZhGGZYYMcTwzAMwzAMwzAMwzAMMyyw44lhGIZhGIZhGIZhGIYZFtjxxDAMwzAMwzAMwzAMwwwL7HhiGIZhGIZhGIZhGIZhhgV2PDEMwzAMwzAMwzAMwzDDAjueGIZhGIZhGIZhGIZhmGGBHU8MwzAMwzAMwzAMwzDMsMCOJ4ZhGIZhGIZhGIZhGGZYYMcTwzAMwzAMwzAMwzAMMyyw44lhGIZhGIZhGIZhGIYZFtjxxDAMwzAMwzAMwzAMwwwL7HhiGIZhGIZhGIZhGIZhhgV2PDEMwzAMwzAMwzAMwzDDAjueGIZhGIZhGIZhGIZhmGGBHU8MwzAMwzAMwzAMwzDMsMCOJ4ZhGIZhGIZhGIZhGGZYYMcTwzAMwzAMwzAMwzAMMyyw44lhGIZhGIZhGIZhGIYZFtjxxDAMwzAMwzAMwzAMwwwL7HhiGIZhGIZhGIZhGIZhhgV2PDEMwzAMwzAMwzAMwzDDAjueGIZhGIZhGIZhGIZhmGGBHU8MwzAMwzAMwzAMwzDMsMCOJ4ZhGIZhGIZhGIZhGGZY+Fo6nu666y7odLpj+u5TTz0FnU6H8vLy49soifLycuh0Ojz11FPDdg+GYY4PX8aYwDBfRVg2GCYxLB8Mow3LBsNo83WXjVHleNq9ezeuvPJKZGdnw2QyISsrC1dccQV279490k0bEdavXw+dToeXXnpppJvCjFIee+wx6HQ6nHzyySPdlBGlvb0dd911F9avXz9ibairq8OPf/xjLFy4EA6HAzqdbkTbc6LDsnGE0SAba9euxbXXXouxY8fCarWiqKgI119/Perq6kasTSc6LB9HGA3ysXHjRqxYsQK5ubkwm83IyMjA2WefjQ8//HDE2nQiw7JxhNEgG2puuOEG6HQ6LF++fKSbckLCsnGE0SAb5KDS+q++vn7E2jUQSSPdAGL16tW47LLLkJKSguuuuw6FhYUoLy/HE088gZdeegnPP/88Vq5cOahr/exnP8OPf/zjY2rHVVddhUsvvRQmk+mYvs8wXybPPPMMCgoKsHnzZhw6dAhjxowZ6SaNCO3t7bj77rsBAGecccaItGH//v341a9+hZKSEkyZMgWbNm0akXYwR2DZOMJokI3/+Z//QSAQwMUXX4ySkhIcPnwYjzzyCF5//XV8/vnnyMjIGJF2nciwfBxhNMjHgQMHoNfrcdNNNyEjIwPBYBBPP/005s+fjzfeeANnn332iLTrRIVl4wijQTZktmzZgqeeegpms3mkm3LCwrJxhNEkG/fccw8KCwvjjrnd7pFpzCAYFRlPpaWluOqqq1BUVIQdO3bgvvvuw3XXXYd7770XO3bsQFFREa666iocPny43+u0tbUBAJKSko55YDIYDDCbzce8VI9hvizKysrw0Ucf4Te/+Q18Ph+eeeaZkW7SCc3MmTPh9/tx4MAB/Nd//ddIN+eEhmVjdPGb3/wGhw4dwq9+9Stcf/31uP/++/H666+joaEBjzzyyEg374SD5WN0cf311+PVV1/FT3/6U1x33XW49dZb8dFHH8Hn8+Hhhx8e6eadULBsjE4URcEPfvADfOtb30J6evpIN+eEhGVjdHLOOefgyiuvjPtvNDtnR4Xj6de//jXa29vxpz/9CT6fL+4zr9eLxx9/HG1tbXjwwQfFcarjtGfPHlx++eXweDw4/fTT4z6TiUaj+MEPfgCv1wuHw4EVK1agpqYGOp0Od911lzhPa21lQUEBli9fjg8++ABz5syB2WxGUVER/v73v8fdIxAI4NZbb8WUKVNgt9vhdDpxzjnnYPv27cfpTR19tgMHDuDKK6+Ey+WCz+fDHXfcAUVRUFVVhfPPPx9OpxMZGRl46KGH4r7f1dWFn//855g5cyZcLhdsNhvmzZuHdevW9bmX3+/HVVddBafTCbfbjauvvhrbt2/XrE+1b98+XHTRRUhJSYHZbMasWbPw2muvHbfnZvryzDPPwOPxYNmyZbjooos0JwFarqlOB01UZ+zFF1/ExIkTYTabMXnyZLzyyitYtWoVCgoK+nz3f//3f/Hoo4+iqKgIVqsVZ511FqqqqqAoCu69917k5OTAYrHg/PPPRyAQ6NO2t956C/PmzYPNZoPD4cCyZcv6LKtdtWoV7HY7ampqcMEFF8But8Pn8+HWW29Fb2+vaA+NG3fffbdINZXlerD9c/fu3Vi0aBEsFgtycnJw3333IRaL9fczCBwOB1JSUgZ1LjO8sGyMLtmYP38+9Hp9n2MpKSnYu3fvoK7BHD9YPkaXfGhhtVrh8/kQCoWO+RrM0GHZGJ2y8Y9//AO7du3CL37xiyF9jzl+sGyMTtkAgEgkIto36lFGAVlZWUpBQUG/5xQUFCg5OTni7zvvvFMBoEycOFE5//zzlccee0x59NFH4z6TueSSSxQAylVXXaU8+uijyiWXXKJMnTpVAaDceeed4rwnn3xSAaCUlZWJY/n5+cq4ceOU9PR05fbbb1ceeeQRZcaMGYpOp1N27dolzvv000+V4uJi5cc//rHy+OOPK/fcc4+SnZ2tuFwupaamRpxXVlamAFCefPLJfp953bp1CgDlxRdf7PPc06ZNUy677DLlscceU5YtW6YAUH7zm98o48aNU77zne8ojz32mHLaaacpAJQNGzaI7zc1NSmZmZnKf/3Xfyl/+MMflAcffFAZN26cYjQalW3btonzent7lVNPPVUxGAzK97//feWRRx5RlixZIt6Z3PZdu3YpLpdLmThxovKrX/1KeeSRR5T58+crOp1OWb16db/PyBw748ePV6677jpFURRl48aNCgBl8+bNcedQH1q3bl3cca0++Prrrys6nU456aSTlN/85jfKHXfcoXg8HmXy5MlKfn5+n+9OmzZNmThxovKb3/xG+dnPfqYkJycrp5xyinL77bcrc+fOVf7v//5P+cEPfqDodDrlmmuuibv/3//+d0Wn0ylnn3228vvf/1751a9+pRQUFChutztO9q6++mrFbDYrkyZNUq699lrlD3/4g3LhhRcqAJTHHntMURRFaW1tVf7whz8oAJSVK1cq//jHP5R//OMfyvbt2xVFGXz/rKurU3w+n+LxeJS77rpL+fWvf62UlJQoJ510Up8xYSBefPFFzffOfDmwbIxe2SAikYiSnJysfPvb3x7yd5kvBsvH6JSPlpYWpampSdm7d6/yk5/8RAGg3H777YP6LnN8YNkYfbIRDoeVjIwM5Ze//KWiKEdssmXLlg34Peb4wrIxumSD/BV2u10BoCQnJyvnnXeecuDAgX6/N9KMuOMpFAopAJTzzz+/3/NWrFihAFDC4bCiKEcdMJdddlmfc9WOp61btyoAlFtuuSXuvFWrVg3a8QRA2bhxozjW2NiomEwm5Uc/+pE41tHRofT29sbdo6ysTDGZTMo999wTd+yLOp5kZb2np0fJyclRdDqd8sADD4jjwWBQsVgsytVXXx13bmdnZ9x9gsGgkp6erlx77bXi2Msvv6wAUB5++GFxrLe3V1m0aFGftp955pnKlClTlI6ODnEsFospc+fOVUpKSvp9RubY2LJliwJAWbNmjaIoR953Tk6O8sMf/jDuvKFMAlOmTFFycnKUSCQijq1fv14BoDkJ+Hw+JRQKieOkKE+dOlXp7u4Wxy+77DIlOTlZ9I9IJKK43W7lhhtuiGtTfX294nK54o5fffXVCoA4+VEURZk+fboyc+ZM8XdTU1MfWSYG2z9vueUWBYDyySefiGONjY2Ky+Vix9NXCJaN0S0bxL333qsAUNauXTvk7zLHDsvH6JWPpUuXKgCEEXHjjTcq0Wh0UN9lvjgsG6NTNm699ValsLBQ3IsdT18+LBujTzZeeOEFZdWqVcrf/vY35ZVXXlF+9rOfKVarVfF6vUplZWW/3x1JRnypXSQSAXBkmUp/0OfhcDju+E033TTgPd5++20AwHe/+9244zfffPOg2zlx4kTMmzdP/O3z+TBu3Li4ulMmk0ksJ+jt7YXf74fdbse4cePw2WefDfpeg+H6668X/zYYDJg1axYURcF1110njrvd7j5tNBgMSE5OBgDEYjEEAgH09PRg1qxZcW18++23YTQaccMNN4hjer0e3/ve9+LaEQgE8N577+GSSy5BJBJBc3Mzmpub4ff7sXTpUhw8eBA1NTXH9dmZIymv6enpWLhwIQBAp9Phm9/8Jp5//vljSresra3Fzp078a1vfQt2u10cX7BgAaZMmaL5nYsvvhgul0v8TbtcXHnllUhKSoo73tXVJfrBmjVrEAqFcNlll4n+0tzcDIPBgJNPPllz2adazufNmzdgzTdgaP3zzTffxCmnnII5c+aI7/t8PlxxxRUD3ocZPbBsjH7Z2LhxI+6++25ccsklWLRo0TFdgzk2WD5Gr3w88MADePfdd/HEE0/glFNOQVdXF3p6eoZ0DebYYdkYfbJx4MAB/O53v8Ovf/1r3vRpBGHZGH2ycckll+DJJ5/Et771LVxwwQW499578c4778Dv94/qJakjvqsdOZTIAZWIRA4qdSV3LSoqKqDX6/ucO5Rq/Hl5eX2OeTweBINB8XcsFsPvfvc7PPbYYygrK4sTxtTU1EHf61ja43K5YDab4fV6+xz3+/1xx/72t7/hoYcewr59+9Dd3S2Oy++noqICmZmZsFqtcd9Vv7NDhw5BURTccccduOOOOzTb2tjYiOzs7ME/HNMvvb29eP7557Fw4UKUlZWJ4yeffDIeeughrF27FmedddaQrllRUQFAWybGjBmj6TjV6oMAkJubq3mcZOXgwYMAkNDgdDqdcX+bzeY+td/UspeIofTPiooKzS1ix40bN+B9mNEBy8bol419+/Zh5cqVmDx5Mv7yl78M+fvMscPyMbrlY9q0aeLfV155JWbMmIFVq1bhpZdeGtJ1mKHDsjE6ZeOHP/wh5s6diwsvvHBQ5zPHH5aN0SkbWpx++uk4+eST8Z///OeYrzHcjLjjyeVyITMzEzt27Oj3vB07diA7O7tPB7FYLMPZPIHBYNA8riiK+Pf999+PO+64A9deey3uvfdepKSkQK/X45ZbbvlCRSYH257BtPHpp5/GqlWrcMEFF+C2225DWloaDAYDfvnLX6K0tHTI7aDnuvXWW7F06VLNc07U7TaHi/feew91dXV4/vnn8fzzz/f5/JlnnhGTQKLdGY9HEbpE/W2gfkh95h//+IfmNupy5KK/6w0G7p8nFiwbg2ckZKOqqgpnnXUWXC4X3nzzzQEznZnjC8vH4BnpuSM5ORkrVqzAAw88gGg0+qXpuicqLBuD58uSjffeew9vv/02Vq9eHbfhU09PD6LRKMrLy5GSktLHLmSOLywbg2ek5w3giCNu//79w3qPL8KIO54AYPny5fjzn/+MDz74QOxMJ/P++++jvLwcN9544zFdPz8/H7FYDGVlZSgpKRHHDx06dMxt1uKll17CwoUL8cQTT8QdD4VCfTKRRoqXXnoJRUVFWL16ddwAceedd8adl5+fj3Xr1qG9vT0u60n9zoqKigAARqMRixcvHsaWM8QzzzyDtLQ0PProo30+W716NV555RX88Y9/hMVigcfjAYA+O+NQtIHIz88HoC0Tx1tOiouLAQBpaWnHrc8kmuyG0j/z8/NFZERmNA/gTDwsG30ZLbLh9/tx1llnobOzE2vXrkVmZuagv8scH1g++jJa5EOLaDQKRVEQiUTY8TTMsGz0ZaRlo7KyEgDwjW98o89nNTU1KCwsxG9/+1vccsstA16LOXZYNvoy0rLRH4cPH+6TsTWaGPEaTwBw2223wWKx4MYbb+yzLCwQCOCmm26C1WrFbbfddkzXJ6/jY489Fnf897///bE1OAEGgyEuuwg4slXkaKpxRJ5cuZ2ffPIJNm3aFHfe0qVL0d3djT//+c/iWCwW6zPwpKWl4YwzzsDjjz+Ourq6Pvdramo6ns0/4YlGo1i9ejWWL1+Oiy66qM9/3//+9xGJRMS2nfn5+TAYDNi4cWPcddSykJWVhcmTJ+Pvf/87WltbxfENGzZg586dx/UZli5dCqfTifvvvz9uqSdxLH2GnKPqyW4o/fPcc8/Fxx9/jM2bN8d9rrVlLDP6YNnQZjTIRltbG84991zU1NTgzTffjAsAMV8OLB/ajAb5aGxs7HMsFArh5ZdfRm5uLtLS0gZ1HebYYNnQZqRlY9GiRXjllVf6/Ofz+TBr1iy88sorOO+884b8XMzgYdnQZqRlI1G733zzTWzduhVnn332oK4xEoyKjKeSkhL87W9/wxVXXIEpU6bguuuuQ2FhIcrLy/HEE0+gubkZzz33nPBaDpWZM2fiwgsvxMMPPwy/349TTjkFGzZswIEDBwAk9lwOleXLl+Oee+7BNddcg7lz52Lnzp145plnhAd0NLB8+XKsXr0aK1euxLJly1BWVoY//vGPmDhxYpzwX3DBBZgzZw5+9KMf4dChQxg/fjxee+01BAIBAPHv7NFHH8Xpp5+OKVOm4IYbbkBRUREaGhqwadMmVFdXY/v27V/6c35dee211xCJRLBixQrNz0855RT4fD4888wz+OY3vwmXy4WLL74Yv//976HT6VBcXIzXX39dU9G9//77cf755+O0007DNddcg2AwiEceeQSTJ0+O6xtfFKfTiT/84Q+46qqrMGPGDFx66aXw+XyorKzEG2+8gdNOOw2PPPLIkK5psVgwceJEvPDCCxg7dixSUlIwefJkTJ48edD987//+7/xj3/8A2effTZ++MMfwmaz4U9/+hPy8/MHXApM3HfffQCA3bt3AziS2vvBBx8AAH72s58N6ZmYocGyoc1okI0rrrgCmzdvxrXXXou9e/di79694jO73Y4LLrhgSM/EDB2WD21Gg3ycc845yMnJwcknn4y0tDRUVlbiySefRG1tLV544YVjelfM4GHZ0GakZSMvL0+zvu4tt9yC9PR0nje+BFg2tBlp2QCAuXPnYvr06Zg1axZcLhc+++wz/PWvf0Vubi5uv/32Y3pXXwpf+j56/bBjxw7lsssuUzIzMxWj0ahkZGQol112mbJz584+5955550KAKWpqSnhZzJtbW3K9773PSUlJUWx2+3KBRdcoOzfv18BoDzwwAPivCeffLLPNoaJtu5csGCBsmDBAvF3R0eH8qMf/UjJzMxULBaLctpppymbNm3qc57WtpJa0LaUL7744oDPffXVVys2m02zjZMmTRJ/x2Ix5f7771fy8/MVk8mkTJ8+XXn99deVq6++Om77SkU5sl3k5ZdfrjgcDsXlcimrVq1SPvzwQwWA8vzzz8edW1paqnzrW99SMjIyFKPRqGRnZyvLly9XXnrppX6fkRka5513nmI2m5W2traE56xatUoxGo1Kc3OzoihHfscLL7xQsVqtisfjUW688UZl165dmn3w+eefV8aPH6+YTCZl8uTJymuvvaZceOGFyvjx48U51H9//etfx31Xq78qylGZ+vTTT/ucv3TpUsXlcilms1kpLi5WVq1apWzZskWck6hfa8n4Rx99pMycOVNJTk7us83pYPvnjh07lAULFihms1nJzs5W7r33XuWJJ54Y9La/+P+3wtb6jxleWDaOMBplIz8/P6FcqOcdZnhg+TjCaJSPRx55RDn99NMVr9erJCUlKT6fTznvvPOUjRs39vs95vjAsnGE0SgbWiSyyZjjD8vGEUajbPz0pz9Vpk2bprhcLsVoNCp5eXnKd77zHaW+vr7f7400OkVRrQ07gfj8888xffp0PP3007xl+iB59dVXsXLlSnzwwQc47bTTRro5zJfAtGnT4PP5sGbNmpFuCsOMKlg2GCYxLB8Mow3LBsNow7Lx9WZU1Hj6MohGo32OPfzww9Dr9Zg/f/4ItGj0o35nvb29+P3vfw+n04kZM2aMUKuY4aK7uxs9PT1xx9avX4/t27fjjDPOGJlGMcwogGWDYRLD8sEw2rBsMIw2LBsnJidMxtPdd9+NrVu3YuHChUhKSsJbb72Ft956C9/+9rfx+OOPj3TzRiXXX389otEoTj31VHR2dmL16tX46KOPcP/99+MnP/nJSDePOc6Ul5dj8eLFuPLKK5GVlYV9+/bhj3/8I1wuF3bt2oXU1NSRbiLDjAgsGwyTGJYPhtGGZYNhtGHZODEZFcXFvwzmzp2LNWvW4N5770Vrayvy8vJw11134ac//elIN23UsmjRIjz00EN4/fXX0dHRgTFjxuD3v/89vv/9749005hhwOPxYObMmfjLX/6CpqYm2Gw2LFu2DA888ABPAMwJDcsGwySG5YNhtGHZYBhtWDZOTE6YjCeGYRiGYRiGYRiGYRjmy+WEqfHEMAzDMAzDMAzDMAzDfLmw44lhGIZhGIZhGIZhGIYZFtjxxDAMwzAMwzAMwzAMwwwLgy4ubjAYQOWgdDodAKC/8lDqc3Q6nTgWi8XE3+pr0Dn0//7uoyhK3HlDQX1NvV6PpKQkWCwWOBwOeL1euFwuuN1u5ObmIi8vTxwzm80AAKPRCKvVCr1eL7aF7OrqQk9PD3Q6HQwGA/R6PRRFQVJSEvR6PZqbm9HQ0ACr1YqMjAyYzWbo9XqYzWYkJSVBURT09PSgo6MDiqLAYDCgu7sbLS0t8Pv9aGxsRHV1NaqqqlBVVYXGxkaEw2F0d3dDURQoioJYLNbn3SR6T/39pvT7aH1X65jW76Q+pr5+ou/1h7pNsVhsSN8/3hxrH/wqkegZdTod9Hq9+H9SUhKMRiPMZrOQDYPBAJ/PB6PRiOTkZABHf0O9/qjvW6/XQ6/X99lelcYLg8EAg8Eg+mVnZye6urqQnJwsZJDkpre3Fx0dHeju7kZnZyc6OjrQ0dEBAEhOTkZ7ezs6OzvR3d0t5EXNYMcXOk8tS4P5nvweE31fS2bUx9XXSHTOSHAiyEd/0Nxps9lgs9lgMBiQnZ0t+rvT6YSiKDAajTAYDOjq6hLfsVqtsFqt6OnpQV5eHqLRKKLRKNLT09HR0YG0tDQAQCgUQlZWFvx+Pzo7O2G32xEMBmE2m9Ha2opAIAAACAaDMBgM6OzsRGtrK+x2O0KhEFpbW6EoCrq7u6HT6RCNRhEIBIRM9fb2Hpd3oZ5TRrp/jvT9h0s2+htD6HP5d1CPHWq9Tes9yb9hIv0hKSkJdrsdaWlpyM7ORm5uLnJzc5GVlQWbzQaHwwGr1Yquri50dHQgJSVFjPVWqxVGoxG9vb3o7u5GV1eX0HNoLlAUBXq9HkajEZFIBNXV1YjFYsjOzobT6YRer0dycjJMJhMAoKenB52dnejp6UFSUhJisRjC4TD8fj8aGhpQU1ODp59+Gn6/Hz09PUK30Bp3j7Uv96dXqe8xkox0G06UeUP9nKQXeb1eoT8ZDAbxudfrFfaE3PdMJpM4Dhzp6z09PTCZTOJcGs9pnLdYLIhGo+ju7ha6EsltR0cHotEo2tra4mSmt7dX6Exa8jEU1LKU6J3I5w+kayWyKQeyV7XGv4HaPVJ8nWWD+h/ZEBaLBXa7HWazGWazGdFoFAaDQdjOJC/UF8k+p7nCbDbDaDT2+X2pH9N3SR+LxWJxx1taWtDV1SW+R7JAdkpnZyeCwSCi0SgAHDdd6avKYGRj0MXFaZIf7CSrNTgkGlzouPoznU4X56SS7yufSwNtomskcq6QcpOSkoL8/Hzk5+cjOzsbHo8HKSkpsFgsQhkPh8NoampCJBKB2WyGxWJBe3s7mpqa0NLSIozbaDQq3hNNBKTAkFHd29uLpKQk4ZgiITObzXA4HLDZbEhOTobRaITJZILdbofdbofVaoXb7YbNZkN3dzeam5tRW1uLAwcO4MCBA6itrUUoFEIkEkFXV1fcu+pPSaRj/b0rrd82kXI6kNKbqB3q8wdylpFT7+vseNJy4BJav9VgJ3D5/P7QcmCSIpScnAyz2SwUe+rv9DdNDABgMpmE40mW66SkI77vWCwGg8GA3t5e9Pb2ismEBnoy3NPS0hCLxcTATwYLKU7k+JX7RCwWE59T+8kRFY1G0draitbWVnR1dfWZNAbTFxMZXQO95/6MOa17DOb3Hsw9vmy+zkpSImgMNxgMyMnJEYaBzWaDXq+HxWJBb29vnDM1LS1NKE1Tp05Fb28v9Ho93G43uru7xXzR2dmJWCwGh8OByspKRKNRpKamwu/3CweswWCA2+0WTqje3l6EQiFhpPf09CAUCsFoNKKyshJ1dXXo7u5GJBKBXq9HV1cXwuEwenp6hJO2s7NTzG9DHXNHi6NJzUi353jKhtYcTwzkpE70+wzWaJOdKRaLBT6fD4WFhZgyZQpKSkrg9XrR09OD5uZmNDc3o7W1FdFoVDh9gsEgkpKScMYZZ8BmsyEWi6GpqQl+v1+M1e3t7SKoR7oRje00d9C/yQCXdStydJEhYjQa4XA4hPPL7XbD6XRi9+7d2Lt3L/bt24eKigrU1dWJeycKUgwUKNV63/1dZyCn1pfRb79OsjHSaDl6aWy32+1xTiSdTofk5GSkp6eL79McodPpYLVaYTAYEIvFhL5CfV4O5pHOY7Vahd5DAYeuri4R6CD9igxtmpdisRg6OzvR3t4uZNBkMsUF8jo6OoRcJOrT/emZifpYIr13sOcPlmOVL5aN4wcFByjxwmazwW63i7Ga7ASLxSJsaLWs2Gw2eDweOJ1OJCcno6mpCe3t7WKsNxgMwvnU3d0N4IjDqK2tDQCEzUEyRDLQ3d0tHEp6vR69vb3ChgeO9IOenh40NjbC7/cLmaOAdn9zxteV4+p4kjMTBrzoAEqM1r+1nEbqa/Q3WffnvJAdV3q9HjabDZmZmRgzZgwmTJiAwsJCOBwORKNRVFVVobKyEo2NjWhvbxcdr62tTXg4aZIgrykQPzHQv3t6evqck5SUJBSmjo6OOIdULBYTChMZJKTg0z1JAMkb7HQ6YbFYxL3b29tFRlQgEBDPoMVgnIf9nTeQUX4s9xzKNei+o93xNJBzYLDXVk/g/cnXQBGhoTicqC+SAm82m4VjiRR4ytgjp6rFYhHR6lgsBrfbjcLCQmGMkxFNzij6bltbG7q6uoTREIvFEI1GEYvF4PV6UVhYKJxOZGy0tLSgtbUVsVgM7e3tCAaDwklM2Roki3TN9vZ28ZxtbW1ob29He3s7Wltb42T9eKF2lg7mvScyFgfrIO7v+JfJ10lJSoTBYIDJZBIZGx6PRxgUDodDBBroXTidThiNRuh0OmRlZcFkMqGoqAg2mw09PT1ivG9vb0dtbS0URcGOHTvEdXbs2AGLxYLa2lp0dHQgPT0dtbW1Ikuks7MTBQUFCAaD8Pl8yMzMRDgcRnFxMZKTk5GcnAyn0ylkjrJm29raYDAY0NraiqamJnR1daG1tVUYGZFIBN3d3cJ4Ifob40ar0wkY+TZ9Udn4InOL/P3BOpgIOVhFeonb7caECRMwffp0jBkzBk6nE9FoFLW1tSgvL0dNTQ0aGxvR2trax1il6xiNRqFr9vb2CoOYMj5IhugzOVBATia9Xo+Ojg6ROUjjvyyDpGeR/kV6m9lsxre+9S0R3AsGgzh06BBqampQW1uLhoYGkVWoziwfyu8w2O8MZp7u77tfpG981WVjJJANYiA+s1vOCCdjOS0tDVarVfRzmhPIoKZr0HcpaEHzDdkIsVgMmZmZwmnb29uLrq4uRKNRFBUVwWQyIRKJiEA5yYbNZhOyQgG4np4euN1udHR0oKWlBe3t7cLApueizCnSnUgeOjs7hWxS2+X3IXM8+9fxlkF2PA0vNNbLdiz1dxrH7Xa7CGa73W6kpKSgt7cX4XBYJGCYTCY4nU44nU4RBDcajQiHw8LWJ2gOIXkJBoMIhUKibwMQGVaKoqCrqwvNzc2orKwUNibJFfVzsmMikQjC4bCQvY6ODrEig+SDAuRfd750x1MiYVArN/01Tj1QaUXxBlJwtY4ZjUakpKRg4sSJOOWUU5Cfnw8AaGhoQHl5OcrKyhAIBESUV04nlR1XWtcmpxlNKGRcU+eVjVgygOVrkHIEQBjhsrdUnQ0CHHVEkfJGy/7sdrsQ4J6eHkSjUdTX1yMUCoksKPWkcKwM1vF0PAZp2TmpdlqOdGrjQM4EQNtp8EVJFNXu7/cYalYOLZOjqDD1b3I4yX2fjN6kpCQ4HA74fD7Y7XYYDAa4XC7k5OTEReSoDfQfvUeSP0qVpayoUCiEqqoqJCUliSid0+mE2+0W8kbGRVdXF7q6uhCLxdDa2oq6ujqEQiGRjdXU1CQUp0AgIJbhdXR0IBwOo6WlJS6a19/7HIwSkOg8Lae7+rPBOBvl314+Z6QVJOCrryQlgpZ4ms1mZGRkiGVFNP67XC7RJynDyev1wmw2w+l0oqioCD09PSKjNSkpCTt37kRnZycOHjyIPXv2wOv1Yvfu3YhEIgCAQCAgHLo0r2jNUfS707nk6DIajcjIyEBHRwd8Ph8KCgoQi8WQk5MjMm5JoaqpqRFzR0NDg1CoyBFMzip5CVSifj4a+qEWI92uL0s2Bpp3BjMvqXUy4Ej/Sk1Nxbhx4zBz5kwUFhaio6MDhw4dQmlpKWpqatDa2ir0KQB9ljNQIELOvlDrVmRok36k0+lE36Pz1WM16Vakx5HRDxxdhiS3h9pIARUyfhwOB1wul1iWVFtbi8bGRgQCAZHtTvcjnezrwIkiG0NFSw4Iue+STmMwGOBwOODxeERAjgLQFDTu7u4WBjfpMJmZmSLARseTk5MxduxYGAwGWCwWsaKis7MTFotFZJSTU1ZRFLS3twu9h5YJUfCN7AjKiKXVEikpKWhraxMBeHJMJScno62tTQQeaOzv6elBd3e3COCRsU3yq6WTJNJrjuf8cazjHjuehged7shKIBpTyaaQgwJkq2dkZMDj8cBmsyElJQVWq1WsWnA6ndDpdAiHw8Lp09zcjFAohO7ubowbNw4ul0tkcCcnJwt7GDhq12RnZ4uMKJpXaL5QFAXRaBSRSETY3rTKgvp9e3s7AoEAampq0NLSIn4XWSei0jnBYBB+vz9uZcVI96Ph4Lg6nshbONiImHxMy9Gh5VAa6LqDeiBdfIaT0WiEx+NBfn4+xo0bh6ysLHR3d6OyshJVVVXw+/1CkQaOptxR5I2ykMjYVitEsjJFBrUcTZOhAVp+JnV0T247Gc5JSUligmlvbxedlt6tnHJLyzloApIjJ52dnWhpaRHrUeUUwMG8W/XvN9BkoT5PyzgeqiNGK+NjpBW9wTx7IieR+tyBHAn93XewjsBEyJE5ciSZzWbhQLJarXEZeWQwU6QhJSUFLpdLKFVut1tk9zU1NWHHjh0iCkARgVgsJgZiMj7kjCaSw+7ubjQ1NeHgwYNxjlp5/XdycjJcLhe8Xi9SU1Ph8XjgdruFI9dkMkGn08VNHJFIBHV1dfD7/SJ6J6eQk3OqtbVVKFJflEROJq3PhqqEseNpeJGj1pmZmcJYSE1NFcYqyZHP50NSUhLS09ORnZ2NtrY25OfnIzk5GdFoFC0tLdDr9dixYwcOHToEnU6HzZs3i36nVTMg0Viq7j/qsUD+m45ZLBZ4PB4AQFFREcxmM3Jzc0VQxm63i4zBhoYGdHR0CAVLr9cLJa+zs1NE+yhinohjiUwPJyPdjtHieNI6H4h/P7KOk5ycDJ/Ph9zcXHi9XphMJvT29qKpqQkNDQ1xS9NoHCfl3m63w2KxiCAc6ZY07pNeIvd7MkrkejfyvC9/Vw5k0HnUJymIQboYyTLJHGXxyTV16FoUnSdDSa/XC4MnHA6LOeN4BfZGmpFu/5c5bySyRwYbVKXz5DIE5FiyWCxwuVxx2RfAEdvE5/PB6/XC4XDAYrEAOJrxUVRUFKejkwyHw2HR/+RA9ObNm+H3++MyP6xWK8LhMHbu3InU1FT4fD6RjRuJRLBv3z5kZGQgOzsbKSkpcYE7WtJHstHa2goA8Pv9qKmpEQY5zQFkiKuX4VHmFclGf44nrXFHa+wa7Hh2rLYGO56OH/J4bLVa4fV6xThqtVrFcmedTidqH3u9XjidTgBAS0sL6urq0NTUhFgsBovFgurqakQiEeEYam1tFat7YrEYUlNTRUkNID64oChHMgip3iCt0pDrl9Hfubm5OOWUU4RTiq5FdklHRwdCoRAqKirQ0NCAtrY2kRUOQNg3XV1daGtrQygUQltbm6ibRjb+SPen48lxdTwNlPGkZWQPNhtA/R0ZrWuoHTTy37KzJT09HQUFBXC73cJjHw6HEQqF4pxNZESbzWYxadjtduh0uriaTWQwk/dTVo5IoaFlEqRoqZ1YFBkgJay3t1dEzGgioXdAShspR7QGlgSHrklLJGhJBClz9F2q9zFmzBjk5eWhvb0du3btQmlpKcLhcJz3NVF3UBs3Qxn4Ejkfh0qiyWmkhVYdARuKc3YgB1R/qM8b6u8i31Ov18NkMolUU1rOaTQa4Xa7YTQaYbPZ4PP5kJqaKmqPud1ukSouR3xJ3urr61FfX4+DBw/i008/jYsmqPub/Oz0f9l4kL9LRgjJjDrSTdkdVFvK4/GgsLAQZrMZdXV1KCwsRHFxMbKyskQ0pLm5GRUVFaitrUVbW1ucAtXR0YFAICCUrYEiePJxuV1axwf73f6cUomUq5GWDeCrpSQlgpytTqcTqampsFqtQrmhiHRycjLS0tJgt9thNBpx0kkniSWpZCh8/PHHCAQC8Pv9WL9+PZKSksTyB+Bo4IPmDur3QF9lXB0E6a9/JXL609+UvaXX65GSkgJFUTBx4kRkZmbC4/EgLS1NGBGU5VFaWhpXfDYpKQmRSEQscaW5czQz0u0b7bKh1qvMZjOys7MxZswYeL1ehMNh1NTUCMcLZVSQ7uF0OuH1emGz2USQjAIH9B1FUUT2ktlsjsv0Bo46nWTnkVzDiQILNO/QOcDR4B0hX5f6OxnpAIRhT+dRNgkt/7bZbKIOm6IoIkvQ6XQiFouhvr4eVVVVolg/3XO4fpvh7L9fN9lQ62nA0IJ1/Z1LY3ZGRgasVitsNpvQ2Un/J4cSLRuy2+3Iy8tDRkaGyHzq7OwUOs/mzZsRjUbjspL8fj/Wrl0r7ifLFNW1keWVdCRaQk22CfX31tZWsVwpPT0dGRkZSE9PR3l5OfR6PbKzs5GZmSk2VaLMqq6uLvj9fvj9foTDYTEHkD0jb+ZCAfP29nZxnta7HUzwTUvnTfSb0vFEOqbWvbSucSyfDzejfd4gjEajKDkg19mz2WxwOp3w+XzIycmBx+NBV1eXcNJGIhFUVVWhtLQUpaWlqKqqEhl6er1e6BZaATVCXpYtF8GX5UKeD7RwOp3Iy8sTwQYKdLvdbqSlpSEjIwMul0s8Y0tLC1paWoRNTquoent70d7eLnwPlEVI+hMFPQZaYfFVYNgcTwMZQfLNj9VBMZTvUEcCjlS0z8nJQXFxMdxuN8LhMGpra4WyTD+u0WiM60R2ux0A4nbwISVbHkDVu8eRE0ouXkZroUmhkesKkPOIoGvSc1BUgCJ38tpwWsJBRWdpUqMJjmpv0NpV2vGLovB2ux0FBQUYP348srOzEYlE8Omnn2L37t3w+/2iXcdj6dqx/I7y9wbjRBltjietY4nappWJQH8n+ux4Q/2LdnKkDCdaMqfT6WCz2TBx4kTxucfjEbtsyUvZamtrUVNTg6amJoTDYTG40qDa3d3dp1+plQW1Q1lWruSlr/JnAOIcp/0pKXL2lNlsRkpKCnJyclBUVISSkhI4HA6Rjku1derr6xGJREQhQkrrBSCMrP6c5QNF8tTIjjetd9Wfk0vreyMtG8BXR0lSQ/KRlJQkltLRjqfk1FQUBQ6HAyUlJSJjyO12AziyNLS3txf79u3Dli1bkJSUhG3btol6ZGRIy32bfi/Z8TQYR6V6dyG5v9ASVvXYOtDYRIqix+PBuHHjYLVaUVRUBK/XC4PBIJxMjY2NaGhogKIoonA0RQLJGTEa+qEWI92u4RzbB/qdtc6X/5b1D5PJhLy8PEybNg0ZGRkimEDFv8noTE5OFpkVLpcLycnJQummjFLKkpBrylBbZQeVvNEEzUd0LskfRaJJ/wKO/qbkiJKdXXRtIL5uJl2rt7c37rrAUcOZotVdXV3Q6XSi1g5lP06ZMgU5OTkIhULYtm0bDh06BL/fP6jA3hf9nYeD0S4bxxpkI4aqX2mdT7Jhs9lENgc5mKg/6vV6YZPQMmsqQUDZ1tFoFI2NjWhpaRF6zYYNG+IymoCj5TMG2045wKeVPKAO2NGztLW1IRaLiaL7aWlpyMzMRCgUQmpqKtLS0sTSwfb2doTDYZjNZgSDQdTX1yMYDAqZpnq2pEO1tLSgra1N6HWJ2q9+1/0971CCeurvaH3GjqcvBvWl1NRUOBwOABDBudTUVOTn5yMvLw92ux2KoghdoaOjA9XV1Th48KBYpq2uiyTPa4kCasDRwAL1M9m+oLmN+iddV8uRpWWXUMDCYrHAZrNh9uzZmDZtmgje0+7F7e3tIsmFNgILh8NilQfViyLfRDgcRiAQ+Eo7n46r40lrqd1gjaF+GzCAgd7fedSxyDjIysrC7NmzUVhYiKamJuzatQsNDQ2IRqNiWY/FYoHb7YbX60VKSgrMZrP4wam4sJwiSh56dUfQUuTJyUQ1atQ7TVD2kTwZyEKh9e7ouxRZp/NJYZJ3F5O3UqXsLPLq0pap5IEeO3Ys5syZg6ysLFRUVODNN9/E/v37hZNNVtCG8psO5XdMZGAnmjwSGdWjeRLQUuiBxBkqQ3FQaN2jv8lU/pyUbYpAyMX56DOPx4P09HSUlJQII5uKDgcCAbGsoq6uDoFAQLMot1r5USttaseS/HkiZzZ9V22YD0WRlM81mUxiF6YxY8agsLBQ7CQWDofR0NCAqqoq1NfXCwUKAKLRKPx+f1yh8sHeV/2O5M8HGkdl2RmoP420bACjX0nSQqc7UkeAdlbJzs4W47HZbIbL5cKkSZOEEUH1y8j5GolE8PLLL4vgRTAY7HN9Qj0fyJtX0Ln0W5MiJZ8jp4hT8IMCHJQ2LteD6u7uFvME3ZOUO3W/omcmYzwrKwuTJ0+Gz+fDuHHjYDKZ0NHRgfr6eoTDYZSXl6Ouri6u8Ky8PHy0RfRGWj5G0vGk1ccIiggbDAZ4vV7Mnj0b8+bNQ2trKzZv3oyDBw+ira0N0WgUvb29ooYf6VS0YUo4HBZL++VCxLTUTdZ9SKdR61YARJCNMrxl/Yf+rVWjQ50NK1+THFakm5Fji+qhkV5FuynRjmDNzc1oaWkR+iRdw+FwoLCwENOnT0dxcTEaGxvx3nvvYfv27SKj8au0rGKk2ykbe/S3TH92h/ydweqsQzmHHE52u13oUJQpbjQa4XK5RAHklJQU5OXliWVvLS0tCIVCwkbZt29f3E5YdD85mCBvNpSoeLe8ZLW/95HomDp4If/bYDCIGjvkPMvIyEBeXh6ysrKEI01RFBGco8CETqcT8wEVWyb5oaxHdZu03n9/urLsVNM6Rz5Xy+ZQf8aOp8GhNb/Q6gin0ylqMwEQ5Tfy8vKQnp4Oi8WC5uZm7Nu3D/v37xdLOpuamjSdq1qOoES/qyynNCck6t9a+jKN6WqnlZZjip6NSo+kpaUhLy8PeXl5YgxwOBxQFAWVlZUIBAJiWWowGBT6Efkhmpub4zZG+qpxXB1PJNhaEYM+Fx2kAyqRcqRWfLWUI1KKqOL9SSedhLlz58JgMODTTz+N8yx2d3fD4XAgJycHaWlpouAq7dITDodFsTxyUtEkoJWlISvt9H/ZMJA7Ok0IsmJE2R9yVFuu2yRfUz4md3a1cUKKGQkA7XZHHtne3l7U19ejtrYWXV1dIpI9ZcoUTJs2DUajEZ988gnWrVuHxsZG0X5ZWBP9RgP1h/7oT/kdLCNtyGhNburP+nuu/pxFAzmSBrqv+j6kTNtsNrGcjiYJWmpKdZ1IoaiurkZjY6PoP8FgUMgKOWkTPVOiSZ6QU17Vtcu0nj+RIqrVBxLJkpZsARAKY3Z2NgoLCzF27FikpaWJJRQVFRViUqRCuMFgMG73yME6Ugkt5xF9T93WRM8m34cdT18c2qTBbrcLQ1qum1dcXIyMjAzk5+fD5/Ohu7tb1GkKBAJ4//33RdCCggRyf9bqe1q/PQUSyPFDma50PkXUCTLI5bmBlHJSonQ6XZ8dWagd8s5EaiewnB2Snp4Or9eLkpISjB8/XmR90DMfOHBAbC9MSlU0GhUOspaWluO+a+SxMtLyMZyykUgPG+iZyRFDAaozzzwTPp8Pu3fvxrZt21BfXy/0KrPZjPz8fBQUFMBoNIqlBOSgodp45GhSG87qbG4yVLUMQHlMlJfhyTWk5Axy2VCXr5Fo/KfryzWcSPYoe52WbsuGfmtrq9gpjOoMTpo0CbNmzUJmZib27NmDN954AwcPHhRLAb8KDqiRbp9scyTSbfrTQxPNq8eii6nP8fl8oswALSNyOBwYO3Ys7Ha7yPhTlCO75u7YsQNbt27tU3xb3iRCXhok99lE70F+NlpaqqWzD6RXDMYpo/6bMj4cDgcyMzPFDpY5OTkoKSlBTk4Ourq6UFdXB7vdjvb2djQ1NaG5uRnBYFDMjbRCg2rCadUzTOQoUNth9GxyyRLZLqO/tZx2Wu90IL1tJBmNOpVOpxN1Ix0Oh9Cf3G43FEURyR4mkwmtra2oqqrCgQMHUFpaKjZPkXUW+puurb4X/V/LEaXWX9T9XT2PqK+vJU+JrgUgrn/RclZ6/vT0dDidTkycOBGTJk2Coigi+6+5uRm1tbVobm4W8yTJQzgcFj6M0aIvDYbj7njS6uwDGbta52t1GvXnWgaZfJyyMvLy8rBo0SKMGTMGBw8exGeffYaamhphCCYlJSE7Oxvjx4+Hx+OB3+8XW1C3traKHa3kuk3yjiukFFksFlitVlitVlGkmN6L3DE7OjpEWjllgMjFMKnTy/dTP7s80dB91MuJZAGjdpACRoUNHQ4H8vPzcfLJJyMrKwvV1dXYtGkTDhw4gM7OTuGEyMjIwOmnn46JEyeioqIC77zzDrZv3y4ypuRBfKDfNhGDMaQHO5irhX40O57o+EATOqHu94N9L1oOPLldSUlJopAf7X5iNptFRNdut8PlcsHj8cDr9cJut4uC3u+88w7q6+uFc1atHMi/rdyeRAqOWpGQaxXIBWzpGqSkU5RRvjdB8pSohlQix5TWu6UiiIWFhZgwYQKKiopgtVqF8tTY2Ci2bA0Gg6LGAS3FUE96MoN1JsrvSasfDLZfjLSCBIxOJUkNKU0mkwlpaWmiSL7NZoNOp0NaWppYRldcXAyHw4FoNIoNGzagqakJW7ZsEdvuytlDQHxGUyJZIRkgxy8Aka6t0+lE7RsyVMihJY+B3d3dIjtDp9MhKysLbW1tIgARCATgcDgQiUTQ1taGpKQkBIPBODmjGh3kRKVlRXL7acmq1WpFQUEBrFYrSkpKMHbsWNhsNlRXV6O+vh4HDhxAJBIRTlqj0Yju7m4EAgFRA26kI3ojLR/D7Xjqz2DXOi4blPPnz8eZZ56JSCSCDz/8EPv27RN1Mqk4a3FxsaidV1ZWht27d4t5gpb7q/U22pGLMm0pa0Sn06G+vl4o/XJ9P71eL/oM6VYdHR1CX5L1IFrGquWAl/VYdf1AghxLNJdQ0JCK4VJND8r6SE1NRXNzM3bv3o2qqipRC87r9WLq1KmYMWMGenp6sHbtWmzYsEEsQ5INn9HISMuG/FsNZGcMxQ4ZrC6mRl5dkJOTI3aVs1gsSE1NRWZmJgoLC6HT6dDa2opQKITKykocPnwYpaWlaGlp6WP8yu2RdX85cK2Feh5Rlx2Qn1Ue3+Xnle0ReYzvz3GnfodyyY/e3l7Y7XZkZGSgpKQEhYWFyMzMFPLQ2dmJuro6lJWVoampCUlJSSIzqr29XSQBkEOuv7FL3Tfk0iT0rOrnTeS003q39H4SMdKyMZR5Yyi21bFCdZKpcD3VbyooKEBGRoZwzra0tGDv3r04ePAgqqurRRCb2gn0dSSq/QW0dFpe8SQHxmiuUJcHItSbddE96drUv2RfQCLnrCyvakj2qH5mVlYWZs6ciZycHFHeJykpCR0dHWhoaBCZTnLGIM1zVLRfK7g92jjujicgcaRd/kyrEVqfaV0r0QPI9ycFYOrUqVi8eDGSk5OxdetWbN++Ha2trWJLUHI4+Xw+EU0rLS1FdXW12ImBOh51XKpxQ8a40+kUzia5I8sdn75HBcYoha62thaBQEB8JncwUqZkZZ5qNZGxQZ5TACJLSn7fJBjydqYkOOSE8ng8mDZtGqZOnYqkpCRUVFSguroaNTU1qKurE9t5ezweTJgwAaeddhpcLhe2bt2KNWvWoKKiQgiVOsVXy2GY6PfT+mwwCoRW35CNIGD0OJ4G+jyRw40YyCE3VPkCINYc07pj2elEhVKtVivS0tJEUWFaRldfX4+6ujocPny4zzpruncip5vaaSJnKMrLKWhiIUcyRZRp6aiiHN2OVKfTiZ0uKOJOziba1UjeLpjkQzbWqR3qYuVa4xllQOXm5qKoqAjFxcVITU1FV1cXjEYjmpubUV5eLpYZUfRO3tVCi4HGu8EoFYne82CVqy+T0ex4or5Jy+XIYU9ykp+fD7vdDq/Xi4yMDJjNZuzYsQONjY2orKzEhg0bRD+Ux0YgfhcwOcOBjlHGYSwWQ0pKCrq6ukQGr9oYpqXflGGo0+ngcrmg0+lE29vb25GdnQ2z2Yzu7m44nU4hF4qiiILflO1Lu5zqdDoRiDGbzSKDj76r0+nE/WVZoawYs9mMrKwslJSUoKCgANnZ2WhsbERVVZWI2Pn9fvEsVEgzEAggGAz2iXR/mYy0fByrbKidRbLxRSSaT9Q6BB2jen9ZWVlYvnw5Jk6ciEOHDuH9999HdXW1qMGRnJyMoqIiTJkyBUlJSSgrKxN1NEOhkMiYo6w6KrDvcrmQnp4Ou90uMpyo3T09PSLjltpDOhZt9kLGQiAQEJtWyHMCZeXKDilyHFEWk1bpA3m3YQAIBoNx8we9I3n+MplMyMzMxMknn4xTTz0VXV1d+Pzzz0XgMxqNwmg0wuFwoKCgAAsXLkRRURH27NmDd999F7t27RJLtgcqcDtSjLRsaNUkGqh/D3ROf/KWSCeVlw5R0XC32w23242cnByxAYPZbEZNTQ02btwoHE3ybm6J2qzWobQcxrLckm6k3smR+jYZzgDEvakAv/ys8nl0jPQpOViuzs7TygBRj0dUqqG4uBiKoqC4uFgE/6l8gV6vFzomzRPkWKayJ2rZ0LIpEtkIiY4l+ltNf5+PtGwMxuYYjI2udZ7WuVq6pVys3ul0itIEHo8HmZmZIlBH+tHBgwdx4MABHD58WBTgTtQOtVNJ3sWxt7dX2Mtkf9P4bDKZRD0/kgequUbHKfBBdgUA4dQh3YQC7KT3qG3NRDaD+j3KskHLVWmDmszMTOTn5yM9PR02mw09PT3w+/2orKwUu/SpNzmioAs560Yjx9XxRErCsXR4tUe9P0MciPciytcgJcTtduO0007D4sWL4ff7sXHjRhw8eFBE2sjhMmbMGPh8Pvj9fpSWlopIK6X/08BLTiYyMGgXLyqCSQM8rcOUU2MJWamhAbynpwcmk0lsUe1yuVBZWYn169ejurparJWmzkyRPvk9UQo5Gc30buQJgyYGSt+j5yRFyev1orCwECkpKWJioehDVVUVOjs7xfKS4uJinHHGGZg5cyZKS0vx/PPPY+fOnUJAE60v16K/iAU9A0UnEg2Sg5lARlppIwVXC7n/DtbxlEg+5GvJJPodDAaDWC5HWQ8mkwmxWAw2mw3Z2dnIzs6GyWRCOBxGY2MjKioqUFNTI5bJDLTOWJ0JqY5S0DFSwq1Wq+jn9H0qWk47p9D7JEObPP604wtFNGRjgSYIckjJY4cstzSJyTIqF7LVeuc0sRYXF2Py5MkYO3asiH42NTUJZ3ZLS4uoX0AGWH8OIXU68Rch0SQ40goSMLodTykpKWInFVqG7fF4xLr8mTNnwmw2o6GhAfv374ff78f777+PYDAYt0xCjq6qxy15SbVerxdFlykFmzJz1Vv/Ul0+WpIAHHFW0bLY6dOnC4M6JSUFBoMBbW1tCIfD6OnpQTAYFJtOUICFMvJobrPZbEJ51OmOLCsKBAJobGwUARSa++g/UhipD1M2JS3fzs3NBQBkZGTA7XbDYDDEFQqlcYWKS1MWDcnkl8lIy8cXlQ21biUf789Ik79LupXJZMKYMWOwYsUKlJSU4KOPPsKmTZvQ3NwsigFT4XAywAOBAMrLyxGJRKAoiuivlC3odrvh8XiETBmNRlEgmZR86lfkhJUzXxXlaBBNfk5yiGZkZGDMmDFIS0tDOBzGxo0b8fnnn0On08HtdgtZkouFk0OJls9RnyM5bW9vFzoJzSu0Uxc5i2jZXU5ODmbPno2MjAy0tLSgublZ7I5aV1cnsse8Xi/mzJmDBQsWwGAw4M0338SaNWvQ2NgYN0+NJkZaNsjmIAYKVGqdN5RgjhYWi0VkgFNAzGazYcKECUhJSYHX6xXZpOXl5fjss8+wfft2ESRO1Aa53bLxLD8D1cYhHYT+o7oxtBMk6Ue9vb2ilgxdn8br5ORk4QSj+5BNIcsUyZ9cI1CdTS7XsZXtO3ou+f6UvetwODBhwgTMnDkT48aNEw7fxsZGHD58GIFAQCzRbWtrE/U1g8Gg0KP664+JdOL+GMgp+XXIeBrI7tCyy9XBMnmOoX9TUJZsCtJLsrOzxcZefr8fu3btQllZGXp6ekTwQv1eKRhMyLuWaq20ku1itYNH3pWerknOJ3LW0thPywHJKQUcsSPIhm5paRHZRyQnlI0nB63pe1r+Da35lp7ZYrEgJSUFqampyMjIQHZ2NtLT00WB9VAoJBJKaL6k3eubmppG3XxBHFfHk3o3NrUBrOVQ0sqSkgdhUsZFYxJMGLJilJWVhUWLFmHGjBk4cOAA3n//fdTX1wsl3el0Ii0tTRiw0WhUFD+WjUzZ4CXliAZJWm4gZ0/IQqg1kagVJroPDbglJSWw2+2orKwUdRIo4ibXK0jUmeTry+8k7sf8/9vT1tYmlgBRHQYqqE67ksViMbS3t8Pv94tiuLRrU3p6Ok499VTMnz8fXV1deOedd7B27Vr4/f44JUnLmE4UtUmEeuBL5GzR6h/02Ug7ntRKQ38GwLFeP9G15WOyZ13+zSnjiQrfUeZGNBpFMBhEMBhERUUFamtr4ff7E+7WJv+2wNGMDop80DGqu0HPThklGRkZAOILDJMBnpaWBkVRxJapOp1OrHFWGykA4pxGWtFpei80YcgZg3LGkzozSs5ekR2sOp1OOL3Hjh0LvV6PsWPHitT6mpoalJeXo6GhQUwOLS0tccuJ1JO41u+pdi6qHUqJFOlEzqaRVpCA0ed4IvmwWq3IzMwUO5x6vV74fD6MHTtWOEwikQiam5vxwQcfYNu2bSLjSK1gE+qxgGSEdop0Op2YPHmyiLopiiLq4USj0TgHKWUdAUeW3dlsNhQWFqKgoEAsjaXi5W1tbTCZTAgGgyKaSJkfFM0DjirT8pyjKEqcIpmcnCzmv6amJhiNRlRXV6O5uTlu7KeCuADE3EGZAcnJyfB4PCgoKEBWVpbIvqJsFbo2LUen2kDksP2yGGn5OB6yMZg5RsvxRGM0GQ6zZs3CBRdcAKPRiHfeeQc7duwQUVeDwYCcnBw4HA4xP7S3t4uduKif0pIKOQIuZytR/05UZF7WBajNctaDbCAYjUYUFxfjpJNOQlpaGgKBAD777DPs378fwJG5RTaW1cvxCPn66qUb8vvt7OxEIBCA3+8XMmq1WoXBIBsw4XAYNTU1qK+vR29vr3DCTZ48GUuXLsWkSZPw4Ycf4p///Cf2798/LLWfZKfCsTDSsqGV8QQkdqoS6jlT6/OBdCoybsl5TqsWvF4vcnJykJeXh46ODlRVVeHw4cM4ePCgyLZLtKxfy4DW6XRiyR45R+ne6enpon00R8k1OeUAXjQaFcYyBQvlnR7J2UvZiOrMDTmgYDAY4PF4AEDIK23/riiKCJKoNwagOUHWbeR3nZycDK/Xi5NOOgnTp09Hdna2OC8YDKKqqgrV1dVCZ6Id8EKhkAimaP1+WiTqH1q6ldZvNZDcjLRsDHXe0HoHiYKUWn2VoNpFLpdLrASyWCzIzMwUmX+dnZ2oqKjAtm3bhLMJiM8WInueNkMBoLkZl7wCiepIBgIBkdlE7SV7gP4jSK7kVRbJycmifI7X64XT6RQ2AK26CIfDIhOPnLU0B8gbptBx2rlOnZ2nlTEo/x7kFDOZTHA6nRg7dixOOeUUMXcFAgHU1taiqalJ2P+0izjtvt3f6oqR4Lg6ntRrahMN3H1uoPKGazVSy3CXPZg0OBcUFGDlypUoLi7GZ599ho0bN4rtfLu6uoRR3d3dLVLUaPkLec3lDCd5+/jk5GQAiFuaoFXgT23cUnvlYuH0nCQMmZmZOOmkk2AymbBnzx4cPnxYrIsmJZvWgcrXU9+XkFPU1bsN6nRHlv319vaisbERjY2NIvuJdhVITU2FxWIBAJFREgqFxBp0tZKUmpqKDz74AK+99hqqqqpEe7RSbrV++0QOy8E6puTvaU06I+35VTtkiP6caFp/J7rGQEqS/DcZgLTWOjMzE16vF6mpqSLynJSUhNraWuzatQsHDx4Uy8NkpUmWS3U6q1yUWH2MlB1ZaaRaUnRdudAsKe8Oh0MsG6XvU4QOgNh+m3a7kJ1dZDxREVir1RonF5RSS8uMaAcyWk9NETbKBJSXFKmXAZEDSqfTieWpU6dOhcvlQjgcFoXYKVoSCoXE0t9EDtZEBoLaYa/lhFU7x9R9ZKQVJGD0OJ5IobdYLCJrg5ZTJyUlIT8/H8XFxSJ7oqWlBdu2bcPWrVtRX1+Ptra2uOupx2Y5Q4OMAloW4XA4MG7cOKSkpMQpOjU1NcJYoOLclHFBc0RycjJyc3MxZswYZGRkwGKxQKc7UkeEdm2lgsq07TspSbLTk94BoZ5jafkTRfYpNTwWiyEUCqGioqKPM5Wi7jS3GgwGMf7QPDtmzBhMnz4daWlp6OrqQn19vTDgadl7W1ubkMdAICDm6+FmpOVjuGUj0RxDv7vZbMa4ceOQn5+PZcuWobu7G2vWrMFnn30mFOykpCTk5eXB5/MhEokIWSBDlupYUiDP4XDEGQWyo0euRaM1l8t1ZwiaA2TjgeYKh8OBGTNmIDMzE4cPH8bOnTvR1dUFi8UigghUwkC+Ht1b7YSS/1bLN12DIs60Ux1tOU/zLDluyaFMTmXKrMzNzcXSpUsxbdo01NXV4cUXX8Qnn3yC9vZ2YUT1F0wbbDDr6+p40mIwOpKW7qU1p5LzlJbTOZ1OpKeni3o1DocDBw4cQFlZGUpLS1FXV4dIJNJHd1LfR12eg8ZLj8cj+ih9RmNwLBYT9WrIAKe6UgBEYNlsNiMUCuHgwYPCKUrGfW9vLwKBQFy5A3LE0vJBAMKQVr93vV4vdCgqzUE7tVImJMksBSPUBdJlzGYz8vLyMGbMGLhcLkyfPh2pqaloaWlBbW0tQqEQAoGAmNsokE7yRs4zLbuiP/04EYn0rq9DxlOi7wwkI1rXpwwdyhKipI2UlBQUFRXBZDKhqqoK27dvx6FDh9DU1CT0EjkjnEp90FxAQbiuri44nU64XC6kpqbC7XaLYBjpQZQJR3WWaQkpLc2ksbm6ujouyEZ9ke5N7bDb7WIVCAUzdDqdqNtKcyQ5hyggSLvd0/hKATSSIa1MQXWWlPq30ev18Pl8mDNnDgoLC+HxeIRORyspKKGEalNTLTlyfI0GjrvjCdDOsuivs/a5ocb36W+1x1X2Bk6dOhXLly9HSkoKPvzwQ2zatAktLS3ix09LS0NWVhZisRgaGhpE6iYZlKQYuVwuYWioa2iQsi8vxdGCDOZE70hWXMjpk5mZCbPZjPr6ekQiESE4sneWnpfaQ9eQ12vLf/fXNlpiEQqFhMFO78pkMon6PvR+jUYjOjo6xBILUpLGjRuH+fPnY9KkSdizZw9effVV7N69e8AIXSKHSSJFeKjOTPnzkRY4UvC0DH8tZ+1Q5GUw0KBFO0qQMuFwODBp0iTk5+eLtdaVlZXYs2cP9u7di8bGRrG7iDo6JT8bpa9SeispLrTmOhaLic/UTjjZCUsZGLKzSo5IkOJFkwApOnSMHGOU3ku1Fyjl3eVyCWeCyWQSTi6CnKzUBlLqIpEI/H4//H6/iBrSum46Rzbi5We0WCzIzc3FhAkTMHbsWHg8HgSDQRw8eBC1tbUiY4sKjyeKTsjjn7x0k/r6UOSDHU/ayA4Rj8cjsnImTpwo1t0nJSUhFArh3//+N4LBIKqrq+PqE8lKtnocov5LhmgsFhOKU2pqKvLy8hCLHdkhkQz6hoYGEVWmMZqWi9tsNrElb2FhIdLS0tDT0yM2x2hraxO1MkixoWxddX+SkY134GimLcmgnLFINeJkJ2xjYyNqa2tFEXI5S5AUL8qypIK7J510EsaOHQuz2YyOjg6h2FVWVgq5IwctFZqlrMHhHN9HWj6+iAEx2MCNej6iMd1ut+Pkk0/GN77xDbjdbpSXl+PNN9/EwYMH4zLIc3Jy4HQ6EQ6HUV9fL3bgIQOdxlx5GbWsI1Ewj/oVfa6FluNJy0lEulUsFkN6ejpSUlJEbUJynsr1bwCIgIYc9JDnAtL/5HbI71BRFLHErq2tTRjJpKtRYM/tdotNMOjZZcPZZrMhLS0Nc+fOxZIlS6DT6fDGG2/gjTfeQHNzs2jPUHSg4WCkZUO9zCaRwZbos0T0p4fRUmsat91uN9LT00UtJ71ej4aGBrz88suoq6sTfVDdZ+m6dA+j0SiyXmUHl5b+Q58BEHo2LbNTl92Q7QcaO0l/ovlAp9MJZwFle5AsULBNvWKDxnQAokYaLesmZy4FOeTMXLoO1dCl9qs3pCF91Wq1Yty4cZg1axYmTpwodsBraGjAoUOHxM6YFJRQFEVsXED6lDzXaemw8n3Vv7eWXiXLeyJGWjaOdd5Q65PyO1E7qmX9wWazITU1VQTOUlNTkZOTI5ahxmIx7N27F1u2bEFFRUWcXUHXIhtcDgzLuyLSCiGHw4Hk5GShc5DeYTAYhK5PugfZAsDRgAIFDJubm0XflJej0vxH8xUFrcnpT5m5cjketR2uFZyQN3+Rgxv0OZUCIWRnFJ1Hz0ibPI0fPx7jxo2D0+lEMBhEQ0MD/H4/Dh8+HJc0QnI40rYwMIwZT1oXV3diLYcSfSZ/X87ykb9Pg7DNZsPkyZNx6aWXIikpCWvXrsWWLVvEMjLatc7r9aK3t1cURabtGamYF22HrXYqyY6eRFGwL4Ks0MhL6WRjgDo8Hdd6R4naRMflwYScArTcgoSB1k/LTi3yJJvNZpHKSMYyLS3Kz8/H/PnzMWfOHIRCIfzrX//Cxx9/LAwy2YhRo3a4JFKYBmtUJ3rHI0miSSCRI0p+D1qOKfk7WtdWG78mk0lkblCtMofDAZ/Ph5kzZ8JisaCmpgb79u3Dzp07UVtbK2q9JHoGcgpRH6FIh8lkilOU1AqLvPaflA+aJMi5SemhpMTTf1Q7gKLo1G9JubDZbMjMzBRONZfLFbdFK7WFHLqUHk5KEylmwWBQ3J+MIVJoyCimTQDI8UUZV5ShKBslJpNJTBIUfQ+FQigtLUVlZSWCwWCfXTTVv7mWwqTVT9T9Qwt2PMVD9WYo648ycageUVFREQwGA0pLS7F9+3bU1tbiwIEDfRQI9W8lj7U6nU4U76f5hpQRKhgejUah0x1Z+kbjNc1jVEMGgCj073Q6UVhYKHZU9Pv90Ov1aGpqEs6q7u7uPo4l9XI6kk1ZCUyU1UHPQo4nWqqh1+vFbn/hcBhlZWVimS4pmXRteUkrOeEKCwsxe/ZspKSkICsrS2RSUXZgfX09qqurxZIRGicCgUC/DtsvykjLx7EaEIN1OgHxcwkZu3a7HbNnz8aFF14I4Ehh7nfffRf79+8XmaFutxsZGRliYxTKoI5Go2LMc7vdIltcvpdcN0k+rtXvtLK6B4KCHmRI0Fwk63Dyu1JnXNExWS8bSP+juUWuUyVn1lNQg4qp07xjtVqh1+sRDofFkgm73Q6fz4fp06dj8eLFSEtLw/r16/Hvf/8bFRUVfQzqkWCkZUOtI2sZyzIDOeoGuhc5Dqluk8lkQlFREbKysmA2m9HW1oaKigrs3bsX+/btE9kcaruHdAo5EEdZHXI/JdTHaE6h8Z0ynGTDl5yrsv2iDl5QEITKLBDyEjx5GXai96TWQyjQSHJA2br0HKTDycv36Flk/ZDuZzAY4PV6MXv2bCxYsAAFBQUwmUxoamrC3r17UV5eLrI6SK+jerZUi1T+/RONj4kcT4n4OjmetOyNga6nKIqYK2gXNp/Ph5ycHBQUFCAtLU0s/dq9ezc2b94sltbR+Er2A42LZGva7XakpKTA4XCIsdxmsyVM9qA+Y7fbkZqaKgLZwJEMOspGkh1JgUAAzc3NIvkiEomIMZtWTsjBdLqGul4sEF+agMZ02WFF/gb6Pul9VMuMSiLItTLJXlHPNeT/MJlM8Pl8GDNmDCZOnCg2uolEIti2bRv8fr8I0Mk7bMtLUkeC4+p4kot/DfQVWUmXI0eJzlVHZ6mzWq1WnHrqqTj77LPR1dWF9957Dzt27BCRUdqNiyrCt7S0iMipwWBAamqqSH3WQnbAyMjRMHre/iIr/Q1ksqIlGwTqSUo+N1EEhZC9r3LHlaMrlBKoLlgLQBQro9o5NMCQEwqAUPz1er1YsnXqqadi3rx5MBgM2LRpE9577z2Ul5fHKUlD6exaE0WiAVCN/J3R5Hga7ISgNma1Pte6nnyc6rKQMS1n/6SlpSEzMxOdnZ3YsWMHtm3bhpqamjiHkxx5o8lBVpQo28HtdsPn8/UpMgz0rb9BCgk5nshwl/uorKjL9dbIOdTa2hqnXJGjiaLqFGGndHP59ydnlezsolo6pJDJhr/63dLkpdPpxDJd2uKXvkvOJ3VExOFwYPz48SJVtrOzE9XV1SJrhiITZEwnmvzVTnitz/obc9jxdBTKNiWFxW63Q1EU5ObmoqCgAA6HQ9S5+/TTT0W2h3rylg1Zne7oFrkUzNDpdEhPT4fD4RDOJVLI1fIhKzeRSEQ4N+VsRVo+Qc4qMnCpTbJip4UczJCzOCj7l66jHjtp3pNlgXC73bBYLOjt7RXzRygUEs4n2oWIDHmax8igy8vLg8vlwowZMzBx4kRxLcrMraurg9/vR11dnSjUT9m6TU1NYimS/Lt8UUZaPr6obGgZWYkCf6TQ2mw2zJkzB2eccQYMBgM+/vhjVFZWorq6WkSFaVm27GAhJ6nVakV6erqoAyNnYFD/kTPg5D6qdnAOZCzK76g/3Yr+lrPC5bGc+rpat5IDd+R0Uo+tsqFMARd5h0kAYik3zQ/kfJWDKwaDQcg8LQekjMuzzjoL06ZNw4EDB/DSSy/hk08+QTQa7TeoN9yMtGxoOZ5khuKE0ppH6f9JSUli7CUj2+PxwOfzIT8/H62trTh48CAOHTokstzU2c+y3ULGqNyWpKQkpKamis/IgdPT0wOfz4doNIpwOCyyuuk/MoBlpzF9l2rg0JI8Gi/JOKa6gDqdTjjJjif0vABEHRyaWzo7O8UcQdmJpA/KOxLL74/qZ06ZMgUZGRkYN24cYrGYqHFDGSz0/87Ozjh9SnYeD1ZmThTH01CvTb8jlV2h7L/CwkIUFRXB7XaLpcS1tbXYtm2bKOsij33k2CFdKTU1NU5Pon5CATQ5MUTWcwgKsuv1eqHj029OJTCoNhu9I7loPQW1W1tbUV9fL2wamhdNJpOwfeW+RAksVDua5gnKBiQnM819pAeRLkRJMZSpTnqhuq4s0HcH5OTkZKSkpKCkpATTpk1DQUEBent7UVVVhaqqKvj9fvGMVDJH1mG/bI6r46m/5V0DOQ7Uk0Z/k4QckZs6dSrOPfdc6PV6rF27Frt27RLbbtIabIPBIAYhcrRQhobX64XRaIwztOVoGNB3qZhWNFj+biLDL5GBSNeXJwy1Y0u+ljqdXEvpUjv2EhkPsldVfhaKlJCzjrZuJGGQJziKrJvNZlGr6tRTT0V+fj6qqqrw1ltv4eOPPxa7LiUy6PtzKCV6l+rz1O+XGA2Op0QTAX2mNRnKuzLI5wPxz6R2gNIgS6mvVLyVdpUoKipCamoqenp68Pzzz2P37t1ii2hCTummyCzdh3anot0de3p6hIE8mN9SNirke8pKP00uVNeGBn9CjiaQsk+RA5oA6Jqy0UDKHL1fmvxokCdlTu18kw0UAEJxMxgMYpcLiq7RZEXLjOi5aPlKUVERZs+ejZKSEiQlJaGpqQllZWWiQDMtIaJsMPU7VL9PdR9Qnyuj7mcjrSABI+N4IgXEZrOJLdwpwma1WjF27FjYbDY0NTVhw4YNqK6uRlNTU59lanJ/lgtf0rIJWekgJYQUG1L4qR9Sm/R6vdgWl3YcstlscLlcSEpKEktyKHuRIrrUP+l9JsqeVb9vkgvZ8STLoNY15P8T5Oyl65EDjWpwVFVVCecQZVhR5I921bRarfD5fMjNzRUZH+SQqq+vR2trqzDwqqurUVdXh56eI9sMNzY29gmyfFFGWj6GSzbU4wUpy1arFTNmzMApp5yClpYW7Ny5Uyz9pBqPtOsiOVPkIvK0+YjT6QQAzd9DVsKpz/WnY6l1K632q/u13J/lJdpa1yXUWVaJsu3le8uZfKTHqR1PcmYLXZ9qllHtDYqq01xE75WcHsXFxVi4cCFOOukkhMNhPPXUU9i8eXOcAfZl99WRlg3Z2Q8MvMqCzlHrk/Ln6uN6/ZFdRik4QRn+ubm5cLlc2L9/P7Zu3Yry8nJRRF/dV+SSAeT0kZe0Ub2m6dOnx9U/I/ny+XyiaHJzczOampoQjUbFvEEZGmSwklxRcIB0t87OTpFNIi/p0wpkJwpeq9//QLq1VraivGyQMqHk5dVy5hPpY4qiiPma3v3UqVMxduxYuFwusTEFBSEoI53sF7JhWltb4+wu9W8+kIPyeHz2ZTBc8wb1JwoeyxtFZGZmYvLkyUhLS0NjYyN27dqFuro6hEIhUTKAAg1UCoMC2LQyKTc3F0ajUSydlOsp92fTyu2j/8ihQ2Mj9UV1kXLqY7SSh8Zxq9Ual91E15EdUWQn0/JArYCfXn9kyTllrsv2iGxnkbONsgSp35Jc07XVGxzR9cxmM9LS0nDSSSdh2bJl6OnpQUNDA+rq6kRmF8lYa2sr6urqRqT+8WBkI2nAMxIwmME9UUNkA1r+nH4os9mMKVOm4KSTTsL+/ftx8OBBVFVViYgAZT1EIhGxbIdeMO1q53K5AByNxtF91EuD5GKX9AxqJUZWLNRRZPqOOqVcLiomP7NaIVILmByR1rq+llOMjpG3WDa8SVjk34cEltaTpqSkCEVKLlZGy0aoen5tbS0U5cjOY7Nnz8asWbNw7bXXwuPxYP369Whqauoz2amfQ204aymY8gSh1XdGG7JzSa0gJmq/2pGrpVTJSj29D4PBAKfTKbbUpSV1Pp8PqampyMzMhNVqRWVlJTZv3owtW7aIwVZuKxnNclRCLhBrtVpFIT/ZOTKQw1X+TMshSv+ngZTSwJ1Op9j1rqGhQUQHKDoWi8WQmpqK8ePHQ1EU4cCR5VC+L92js7Mzbomr/K7lNssGuByhM5lMojaQz+dDVVUVmpqa4iLqcjQvEongwIEDYu11SUkJHA4HcnNzRfYAjQvyFvJyjQStvt+f4179/Cc61L/T09NFJqDb7YbVakVeXh68Xi+6urqwdu1a1NfXo7y8HIFAQHxf7tfy70zKFM1RVKCVfkPKJqSxVZ1yTQ58itZRnyZZo2KcVqsVEydOhNlsRiAQEMtFgb7zgxxkoPvIBj8Q37fVwRN5fkgUcJEzZSloQXUVSEa8Xi90Oh2am5uFQknR/+7u7rgIYkVFBaqrq2G329HW1obZs2djypQpmDx5Murr64ViSEvFg8Fg3A5+8lx9ovf3RO9AHcyjIqmzZ8/G8uXLYbVasWPHDjFOUaYF1fOiDVnI4WS1WpGTk4O0tDShyAN9l66pnUr0n9qYkI1aebyTHaP0mVofUutWsj4nf4+uJ+skZBCrHWUEXYu+R/+Wz5GXMclztOwIoDGGDGJyQkUiETF+0BLa5uZmYbQ0NjZiwYIFuPLKK2EwGPDZZ5+hra3thO7rWrqR+ngih5N8vvoaRqMRDodD6FJZWVkoKChAQUGBGKfWrl2L8vLyPg4nyvZRBx98Ph8mTJgAh8MhlgDR0kvgaN8xmUxISUmBohzZ1dRisSAvLw95eXmiv7S0tKClpUUUXpadneoANdX2o3IIAOLaDBy1Y9SOTFlGAe2l2lq6HMmRPL9Q4I/mPcr0o0yV1tZWkaEh22IU4A6HwygtLY1bKjV9+nTk5+eLpVi0xNdqtaKurk44GigwQptT9NeHtPqT3I9OJFmT5Ymcr/Sb0AZc5PAoKSlBXV0ddu3ahf379yMcDovEDxon6Tc3GAxIT09HZmYmkpOT4fP5YDAY4upzUX9R61wy8jyh5ZRSy7fskOrt7YXdbkdWVhYyMzNRXV2NyspKcV9aWUU1NGOxIzWiaZd3AKKdNBdqtY8SLwAIvVDu37FYDH6/X7wfynbV6/WiphnVC6TVFfL9YrGY2EWzpaUFDocD06ZNQ3FxMTIyMlBfX4+KigrU19cLWaNaaHJdqUSOV60xcjhlYMiOp0SRBTqmda7W+WoDnZQji8WCqVOnYsmSJTAYDPj000/R1NQktlmmdZhUb4WcTmazWXRyo9EoUs1kxRqId/TIBqpsnMpOInXbafBWD+Ly82tFnekZSWFS30OGDBcthSzRJKDlVJK/q267+reijBmKsjc2NqK1tRV6vR5Op1NsMUnbA9Oa0lNPPRUrV66Ew+HAm2++KaLS8vP3F7HSItH5/Z070vTnUNNSguQJW+v7ashRQ5lIstMpPz8f2dnZsNls8Pv92LJlC7Zu3YqKigqxPEd2OMmp/yR3FKGTd0Gh9OyBfidCK8pM56mdzQBEVCUWi4lU3vb2doTDYTQ3NwvZILlPT0+HyWSC3+8XO4zJhrHs2JLfq5xyKsuD2mkFHF2qJ6f96vVHlkFlZWWJ+lnd3d1obGxEJBIREUe5SHRNTY0Y+ClKREuKKNPJ4XDEZXKplaXBOvIH+9mJABkTtAMLZdq4XC6xNTYtndi8ebNIv5aR5wQyJNXF8EmOgCO7vcgFlOn/tLOVvHspyfyECRMQi8VEYXs5E4/6XFJSklDoZGSnkTwvUX/WcvoS6nEpkQyrxyMyMtrb28X8QY44MuipHlBXVxf27t0rgkRmszlud0pSqNrb2/Hee++hpqYGb775JvLy8mC325GcnIyxY8eKTLXPP/8cAODxeESGpNy2E53+DCU5g3zWrFlYtmwZent7sXbtWpSWloqAHjlSyBAmRzoZDGlpaXA6nUIBBo7WpiE9So4Iy32Qxn3ZoaMO8NExcgxpZVLIz0TGtgzJHgUbtfSrRBlKpC+p9UF15FreLl4O7Mn3ISdBUlKS2MzG5/Ohs7MzLnPW4XDA6XSKZYyVlZUieHH++efjpptuwr/+9S+sWbMGoVBIyKDWb32iGMsD6XtauocWtPzX5XLBbDYjKysLkydPFrur7dy5E9u3b0dVVVWc/kDyJNeGoXIEHo8H2dnZoiwB1TUiZ1Frayu6urpEfRmqqxoMBuMygOgekUhEBNgoeEif0W525KyKxWIoLy9HOBwWY7J6MyJZpmS9id6TlpNYy/mklSlI11DPQVT3jJ7X4/HAZrOJbCUy6k0mk8iYoTpVFLCIRCI4+eSTMXbsWFF4mhx3KSkpOHToEBoaGoSzS6/XxznTB7JV+3Naft2h55bHKo/HI5YF08qiwsJC2Gw27N+/X2xORLVSqXQF6US0BDQjIwMFBQWw2+0iMEfLkeVlygT9DokcS4mcI/3ZJzSfUUDd7Xajrq5O+AeodisFVsxms8iiI/uE5hNZZ1InSPQ3NsvP09vbKzLzKABBtZSTkpJEMJ128CObgp4VACKRCN555x2UlpZi5syZov4TOXppl3IKCvr9/jjdUj1XyP4DLUe12ukuv/tjZUiOp0TOBC2hVp8rP6zWg9MAPmvWLCxevBh6vR779+8XWy+3traKgZo8guRg8fl8oro+ABF5pkFQraDIDiB1dE5GHnxl5WogQ5wGcUrTU/+YdD3ZOSRfU90Oel/0vPQ53UdtJKgNarljyZE8NbROmxxNTU1NIr2VJuimpiZRnLqlpQV+vx+LFy/Gueeei+TkZLz++uuoqqqKyyRTR9nldyW3W/73QIOJ1ndHkkSDTqJzgXgHpdqJKT+n0WgUS4VotxWPx4OioiLhqe/t7cWePXuwefNm7Nq1C8FgME5xlncmkYvpUW0lQl5jrdVH1Mh9Ue5j8jG14kO7QpBjiyY58vpT2+WMEooMlJaWCsOV6gvQvdTvVu5v8oQhGyXqlGw5Sk7tpOhcR0cHLBYLioqKAACpqakoLS2F3+8XmTC0hpy2V6ZJ4/TTT8e4ceOEwdTT0yNqVpGSSvXphuJ4lZ/1RIzWyeh0OiEnVPvCYrEgPz8fxcXFMBgM2LlzJ/bu3SvqCakVZ+oXpESRQU6fZWdnC3miHX4oik3jPRW6p4i3bKAbjUZ4vV4UFRWJWhW0kQMVouzp6UFFRYVw2FAtM3keU88XiaKBdK48R/Q3D8vjkfw5fSZH5CwWizC+yTFMY9Qbb7yBHTt2CIcsGWvkYCWlzu/346OPPoLFYsHevXuRnp6O2bNni93SPB6PcGaRwSFn4pzoJFII6fej5b9z587Feeedh56eHrz33nv49NNPRSFSqlMGQGSQ6/V6pKSkiGV15CQF4nUl9Zivzp6Q5yDZWUr9UJ4rSGfQ0jO1HKR0ffq7P51TnTWlRh2sozbLS0Dk3ZVk45ueX3YCy/MefUZOWKvVKpY3Uv1ECuSRIed0OrF8+XJcddVVsFgsePfdd1FXVxfncNNyEH8d0XKWD/S8/emPycnJwsimpWkZGRmwWCxoaGjA559/jj179oiaNQTNCeR0ono1brdbBDt6enpQWVkJ4KjdoNPpRDBcURRR0Fu2AciZLkPLzmKxGCoqKlBTUwPgSBkA0ktsNhu8Xm9ccWXSWxRF6dNX5fFcK4gtZw/KDmF6d1o6vJbcakEOa9rt1GKxoLW1VRTcN5lMwhlABjrZGlTLyePxoKCgAB6PBw6HAzabDU6nEzU1NWLzA/p9W1paRMaH2g4bDF9nXUr+rWi5LwUXSP9xOp3Izc2F0+lEY2Mjdu7ciWAwKLLWqE4pJYxQADstLQ35+fkiy48Ca+Rs0iowLyOP2TqdLqH9Ln83kQ+CnLSNjY3CliU7l87p7e2F3+9HdXU1nE6nWCWhlg35mJbsqPV2tUNHK6Nc3gCJarXRuED1aWlOkJ1HwWAQW7duxeHDhzF16lTMmjULBQUFyMzMRHNzMyorK0W5B3JG0XyvZauq9UO5jWobSn529XUGGgOIITmeBuMZHowHUv6bOofD4cCMGTNERO6dd97B3r17xdbmpByRtxQ4UnMiLS0NbrcbwNGBjQZgao+6k6g7rXxM7izqDq7OQtL68dSdUZ4ItN6V/H9ZQVO/Sy2DQCtjhlBHrtXvXMupICuRZrNZRG5CoRCMRqPI+KBiyXKR6CVLluCss86CxWLBs88+i8bGRuEUS/TssvAnEgR1+0bjRDCYNsnPqX5mtSOKzpGXvpFyQ4W1MzMzMWnSJGRnZyMUCmHr1q1Yv349ysvL4wqIy1EIcj7R8iNyONFkAPRfL0sdhSYFRT0QycoKkcixRgapXq+H3+8X/Up2qOr1elGPjJzPhOwUTtSv1fXVZCMHQFyEXP2cJLvkKGtvb4fdbodOp4PH48HYsWNF7SaasMg4p8yBjo4OBAIBjBs3DtnZ2ZgxYwYqKytF7Sh5OQtld8oGDytM/UOTq8ViERtKJCUliW1pfT6f2Gr9k08+QW1tbZ86X7LDiWoSOZ1OJCUlIS0tTdQ6o8wlmmvU/1YURTii5PGclDAy6sPhsKj1Rd+juYr6jLwsKNGEL2+x3d9vriWP9H+141XLyCcZlGuxkcOMdvALBoNi6eyVV16JlpYW7Nq1C++++y5CoZCI0lut1rjlv+S86+npgcvlEo5Zm82GCRMmoKurCzt27EBv75Gd1k4Ux9NQ5FjLgWgwGOBwODBv3jyce+656OnpwZo1a/D555+L5ZC03DoWiwkl2GQyCaPabDaLTAwAfXQg4Gjmk7zpBLVf1inUS+jIIKe/Ez0P/Z0oUKieA+QgHfVn+XO101ae89TBCPW5clBPPdfJsqOeT+RM2pSUFCQnJ6OmpgahUAgejwcZGRkwm83CaPjwww8BAAsXLsTKlSvhcrmwevVq1NTU9JsN9nUi0Zil9Zn6PPm3kfUIqqVHu+JSeQKHw4GdO3di//79OHz4cNzmH5SZQDUfY7EYXC4XioqKRPCBdnim3ba0MoZkXUL+T14eLTs5qa6T2+2G0+lEQ0ODmH/oeqFQCJWVlXA4HOjt7RXOG/VyPPX7UgfSSWa0DGQ5oCHrV/0FibUc4fRc7e3totg61Smtra0Vy91lvbS7u1tkfVVXV4vNKU4++WSkp6cjNTUVDocDXq8XFRUVSEpKEhkfAMTcGAwG+5ScGI0B7C8Lel6qFZuamgqXyyUCd+np6cJZTkWsw+EwwuEwAoGAqOUo7waXnJyMvLw8FBUVwWg0IhQKiSX2pD/LBeCpHWpHB4C4MRuIX01Bv6nW5mA0dsvyT/2J5ImuK/eFjo4ONDc3C3mkmk1Ue4kcuIkym+T7qYMOdA+5rbJjV85ONJvNwmdAS2vpmSlwR07rWCyG5uZmbNq0CTU1NZg1axamTZuGnJwcsftwU1NTXBBWLQdyG9XPI68AUx//ovIyaMeTlsNJPbBrnZdIeZKVI6vVirlz5+Kss85Cd3c3Nm7c2MfpRJlOtEuC2+0WqfhyVoTcBrkDysq5lkNH3f7+HDRa35NRp7DSvdXRskTX6c/gpHRS9TmJnGWJrquuaaUWXlq+mJaWJmprWK1WZGVlwWg0oqamRtTcol0ALrjgAixatAitra147bXX0NDQEFebaiAjZyBFeyADaaSQ293fM6h/K62JTx68aC077U5CKd0FBQUYP348MjMzUVNTgw0bNuCTTz5BRUWFiNCRU4cidGRI01IWqgkgD95yv5GzNOhztRKuFTXT6ofy88n3kHe+IoWO/i0P7vQ31b+h66mNcfV91cti5fvKBpJsoMhKmPx85AyjyYCUNofDgUmTJiEQCKCsrAzNzc3iOpTd0draioaGBrS1teHw4cPIzc1Feno6jEajyCCkCYbkkAqZqvuLVr8/kRUo4MiyiYyMDLH8lJZQzJgxAxaLBfv378eHH34odsYh5Z3eI03qAITyRY5eAKLGneygVWcHEerlb3I/pj7T0dGBmpoa0RbZuURyIO/WIs8bsqFLNZ1kZU4rEgf0NZIHMtzk56E+SQoPKWI6nU44Kyg7q7y8HM3NzZg2bRomTZqEvLw8GI1G7N69Gzt37oSiKKKugryhhU6nQzgcxu7du0WR3BkzZsDtdosMNjnj4ERjsE4oWW+xWCyYP38+LrjgAoTDYbz33nvYtm2byCil4IO824/NZoPP5xPOkUSZr4kCWmqdT1bA1SUE6Huy4S1DfY2uJ89H6mwM+TM5qNCf84K+JzubZBlSO3npM7WzKVGwRa1nyp/T1uQ1NTVoaWkR87rZbEZNTQ0qKyvR1dWFYDCI888/H+eeey6SkpLwwgsvoKamJk6vOlFQ61laxxP9HmTUkYOP3ndRURGsViu2bt2KTZs2iTFZduxT5iqNW+QIomVD6j6TKNBMaDmJ5c/oGI2PtOJDXj1A3yXdnIKK0Wg0bpMg4KjTV9an5HdHWe5atpx8Ha3fI5ETNJFTSpYpmgt8Pp9wcDQ0NMQtOQQgNnJpbm5GW1ubCIDMnDkTBQUFIvBBep2su9KzGo1GNDY2CqN7MEGar7suRbUZqaarxWJBRkaGqBvU2dmJw4cPo66uTtQca25uRkdHR5wjhvqQ1+tFbm4u3G63KORNASJZ504kx4R8TKtfqessy8e0rkHIpTOo3dRHZL2CbCO51Ihst8jOWUA7eEF6m9oeoevL56mfQa6JRjvQt7W1icAHBcDpfFoJ0tLSgqamJixcuBAlJSWYM2cODh8+jNLSUmELms1m+P1+ERTXevda/V/L/6PFYGXmmIqLD0Z5VX+u7mykcDgcDpx22mk455xz0N7ejnXr1mHHjh0i6m+xWGA0GsWOdWazWXjJKeUUiF/CBmivP5bX7auhDqLOfiDkNGxC7mzqjq/uiOp3Ig+siQxJtRGvTgWXl0WpHQT9OTlIkBJNHLKwUGHe1tZWNDY2inoFJpMJFRUVIp1169atiMViOPfcc7FkyRL09PTgX//6V5/aBOoO3J9BNJBDc7RwrIZ/omcwGI4UEPd6vTCbzXE7CaWkpIj014aGBnz22WfYvn27WONO70bOdLLZbGIreQBxtdHkvin/7uoMIvn3kaO+aoWdzk8UxZAND3mnJJ/PJ7J95D6sdkSp+7NWe7RqeMgTh5azTL6f/D3188uF+2ndusPhQH5+vsh2CoVCQvmhNeQkowaDAVVVVSI6NGXKFKSnp6OyshKBQEDcLykpSRSWHkyfoc++7sqSGjIEaMMJk8mEnJwcUQ+spqYGBw8eRGVlJcLhcNx6fepbZFCYzWZ4vV54vV4oiiK2PSfImSujnhfkuYPmJLn+k5zhQcvrqD3kmJIdsLIM0vdIpsm5KSsQA2XWahnI8rXV0L3l7bJpzpFlieqW6HQ6tLW14cCBA2KZ4MqVK3HOOefgzTffxKuvvopQKCSicPLcpdMdWcpHBd+LiopE0Il27gQgln7RLmxfV4Y6r8hjsNVqxezZs7F48WL4/X6sWbMGu3fvFgVMaTk9bSSi0x0JdKSnpwvnvlbWBrVFrV+ox1VZQVcHtuRxVr6mPLbL/Vgev+X2yN+X/6YxWquGnxr6vlq3Uuuu9Jm6repr0Xwoy4e6nTQP0KYutbW1qK2tFQWmk5OTUV1djaqqKmEgLFu2DGeffTYURcFzzz2HhoaGr33mk5YeK/+f+qGsfwB9VxKQnUEBCZ/Ph8LCQlFEfP/+/fjss89E/VJ5/LVYLDCZTELvdTqdYsdHMv7oPuoVCOoNS9TtAuIdqLKxKm8UQY4stR5Nz0t17/R6PdLT0xEOh8UmDDTfaOlj1Da1LqQVvJaNZvnz/gxwLeeCnNUVi8WEw9tsNqOoqAgWiwXV1dViSZSc0UvzXENDAzZv3oxIJILTTz8dRUVFcDgccTvHmkwm1NfXIxQKidISlCFCc5XMQA7NrxOUnUSBbbvdDo/Hg/z8fOTl5QnnLO1YS7vWktNJ1pcBiF3k09LSoChKXE0htf5KHIv9Js8LJFMkI5QNJPcv+Xtq20NuB/Xbrq4usbyfdpfs7x0meha5jeoACdA30E1tJGhMUe8G3NraikgkAkVRkJycLGSHxgi/34+tW7eKjSpmzpyJpKQkRKNRJCUlob29XVwrGAwiGAzGZXZSO2RZ0BqzjgeDdjxpCabaMTAYT5jsdDKZTJg+fTqWLFmCSCSCDRs2YOfOnWhpaUEsFhOGRCQSEcV409PTxbaEMrI3le5HHWAwCggN7GqFCThaOEwr3TSRs0uOIqifG0DcZCK/H7VjTMt4TxTVGUiY1RPWQNDA73Q6YbVaRSHc1NRU+Hw+8c4jkQhaW1uxbds2JCUl4YorrsBZZ52FYDCItWvXorW1VRjlclu02qeVypiob43WiWEgR2Kic+n3pIgc7dKRmpqK7Oxs5OXlwel0CufFp59+im3btqGqqgrRaFT8HnItJzKk5foqskKmlmetaLHc5+hvLees7ARSGwvA0SUHdO+uri4YjUbk5eWhsLAQhw4dErvZAYgr+qy+t7ovaznGFEURzjitaLjWb0TXkM9T9zF6Np1OJ3b+o9o+tDNGKBQCAJGKH41GRcF0nU6Huro6uFwuZGdno6SkBDabDYcOHRLLjlJTU6HX69Hc3Jxw8pbbp1bMR6NcHG+oNgEVdqXU++nTp8NgMGDXrl14++23UV9fL1Ks5T5DS9mMRiMKCgpEhlM4HNaMGhNaRrN8XN3H1M4aAGI5nVYmKH1OmUSyY4ruS5lSWnMIoZ4jEhmqajlWOwrk89TXlA0iKoJLxtnevXuF42jChAlYsWIFamtrsXXrVoTDYbHsTo7mA0fmk507dyIlJQV5eXlIS0tDRkaG2PCCaj5FIpE+AZ8THZ3uyLLTyZMnY/ny5YjFYlizZg22b98uHK+U1dfS0oJoNAqr1QqHw4G0tLS4en+JkPUj9fyl1qFoDCZjmuSAaoOp9TV1FFi+TqJ5S92/6bvyv+VrEfL56rbQPELBSLqPTqfrY1io26/WE7XuSZkZbrdb1PZrbm4WgaVoNIra2lr4/X5s2rQJHR0duPTSS7F48WJEIhG8+uqr8Pv9mvrS1wUtx6va6JV1Ey2nR3JyMjwejwi8lZSUiMBEd3e3qItZU1PTJ3BHOlRWVhZyc3NhNptFbVPaJEG9ckDtsAHQR18h/UE9ztJ35AL45KSklR2tra1xejIAkYWdmZmJMWPGoLOzE1u2bEFra6vYAEMOMspjrVZGk9yn5f5Oz0L/18pQlJ9FrVvKehXV/TMYDMKAdjqdItgQCATQ2NgY9y7k5bPNzc3YsmULQqEQTjnlFIwdOxZutxslJSVimXBNTY1wYjU3N8PpdIrvynrw11F2EkGZL263G16vFy6XS4w5+fn5SE1Nhc1mE3W16urqUFtbKxx28rhIWYS0qzbVIyJZHMghruXAT+TUJ9T6vuyotdlsAI7qTkB8TWO1o5r+TeUVkpOTkZOTg4KCAhw6dEgU/ZftCXW/pjbJcxuNCer5gFDr6urnpj5OmX0UGKVlwn6/XwSp6VnJcRaJRHD48GG4XC5MmzYNWVlZopwHOW8tFotomxy41NIfh4tjWmpHJPKMqZUCeTCmTmCxWDBlyhQsWbIEbW1t+M9//oM9e/YIZZKcHbQ7gdPpFEvrErVBPpbI0FTXdgH61neSJxMtQ1XtwZe9rOpOSAJOBYfph5bXqFJbaDcAvV4fV/W/v8lWbqOsgKgjiVrCon52rUmIohFerxfRaFQsn8vJyYHD4UBWVpYoANja2orPP/8cGRkZWLJkCZYvX462tja8//776OzsFGtXE6H1jF8FBho8B3II0rPSzhJUoDcjIwPZ2dnIyMhAWloaUlJSEI1GsX//fuzatQu7du1CQ0ODSB+m4n5Uz4mKZtJuCXJ/0lKQ1DLUn+NU/kzuS4mUQPk6spJPO8K1tLSgrq5OOGzUDjD1NeXrUASHapWo02TlNibqU2rHk9a5WooYPXd7eztisSO1H+hz2taX2tHR0YGmpiYoigKbzYbOzk60t7cjPT0dubm5YvIsLy9HMBgUiqlaUVIzUP/6OkI7gVCGRlZWFsaPH4+MjAy0tbVh79692LlzJw4fPhy3PI6UJXI4UVFNi8WCjo6OOAeuPAZpZVYk+lyr75MB63a7RRvlTChSvrWi3OooHhny8j3k/xMkI+q6NGpDXp21SPeXn1NeqqHV/2neoxoeTqcTwBEn3vbt25GcnIwxY8bgyiuvxIIFC7B+/Xps2rQJnZ2dYtmKrCxWVlZi69atMBqNIgDlcrlE2jllIqjrFXydGMocKOtVY8eOxYoVK2CxWPD2229j27ZtCIfDUBQFHo8HKSkpaGlpEe8xMzMzbpMJ2UCVry3/7uQ4AvpuJgH07YtyxoQ8H8j6iex0oswliujSMerLPT09sFqtSE9PFzuAUZaEoihxQQsyTmg5BRXHl++dyOBR617y+9FyRtOzqs9XG++UWUO7b7a1taGpqUnsjJadnY1oNCqyV7Zs2QKDwYBLLrkE5513Hjo6OvDvf/8b4XC4T1Dv64is86rnanVfov9TAI8Kiaenp4uMjlAohM8//xzbt29HfX29CAJQfRfKpnC73Rg3bhzMZnPc8iHS37WCE7IuJgfaaP6hLFigb9+QsyG0nlF+F7FYLG5jACqUTps3kDzR/CPLqRwgpHNkY57Ok++vnjOo/fLf8jG1w5ag65CTgrKyOjo6kJycLJwghw8fRkVFhaidSe+U3lkkEsH27dtRV1eHwsJCZGRk4OSTT0ZmZiYKCgrE7x4IBPros1RLNJHzg9qt5Tj4KqLT6YTOZDKZxKYdbrcb2dnZyM3Nhc/nE0sSKQh84MABkekEHE3i0Ol0cLlcoj4dzR86nS5up7uB2jSYY/JnWgEKcqTSHEPzBPVt+pz6PcmD2gFEjjaPxyOuQQ5S2Vks60vAkb4vX1ed6CL7FAayx7XeA82D8m6B3d3dccvvyObp7OxEbW0totEocnJyMGPGDIwfPx5utxvV1dUIBoOor6+H3+8XO5jLtbi+LIa81E49uKudTonOB44KsslkQnFxMc4991xYrVaRBh4Oh4XxRutE29vbYTabkZ6eLjya8rXJ+68+ToN8oiiElndeHqCpY8v/1lpuJ38fiE/1lu9Pnkl5O16CjCGLxSKKmqmzPeS2yBEP2WDQUurke6ifWf5cyzsrPxP9Hs3Nzairq0MsFovbBaGxsRGhUAiRSASffvopUlNTccYZZ2D58uUIBALYtm0bgKNLlOQ2qAd/dd8ajLNgtDCYwVbLyUGTQmpqqohAFxYWIi8vD16vV2QG7N69Gx9//DEOHz4sUloBCK899QWHwyGcTupJQEtmZPpTJrT+TjQxq9c0a8lVLBZDTU0NysvLUV9fD6vVCqvVKrzwnZ2dfZyy8v3JwUuGhFZ/Ui8pTNTeRM4p+bg8/tG1uru7hUJEhXlJgWxsbBSTERUMpTpQtNzF6XTC6XQiMzNTKJJUwJ/eUSAQiCtiTe3RMoy+Sk7bY0F20FosFpGtQYrTBx98gF27dokotmzYUjFsnU4nNqcwmUxobm4W58oRLqCvUakeX/uTJXneIMOGlngEg0HRN8iQoT5GcqB1vUSKcn/3l+tfyHMUGUnyc5MDjK6rrkmgzuogpxpdo7e3F5FIRBgK0WgUmzdvRmNjI+bOnYvx48cDAOrq6lBZWSnGK9qogt6V3+/H559/juTkZGRnZ4tlJKQ0dnZ29tl56utEf45m9dxOhkVmZibOOusspKSk4P3338eWLVvEO3M6ncjIyEBXVxfC4TB0Op0oKktLPOWMDLo2cNQ5KRvSWsiOUnXwQHa0aj1Tomel/6vLKciRYbXORG2mCD/t4AocLWZP/ybDQqsdsvxojQfyO1J/T73USm6XbKR4PB60tLQgGAzi0KFD6Onpgc/nQ1ZWFhTlSCYhZZR7vV5cfPHFOPfcc+H3+7F+/XqxEcFgnE9ftblB7XAhtOY7+f+0yYHNZhN9gHQrv9+PgwcPYv/+/SKjmMZBWq6l1+uFExAAgsGg2PGRxmp5LJSdLXRMds5S2+Rxkp5Dbcyqn1mdWSdnO1GQsaOjAxUVFTAYDCIIRjaBuh1AX+eorGdrBRm0HMlqXUgNyasMvR/5MwoC0ee0UyDtJkvBVa1ixx0dHSgvL0d1dTWsViv279+PyZMnY+rUqcjKyhLzitvtRkVFBcrKyqDT6YSDpb29vU+fksecr5KsqJHbbzQakZqaCo/HI4I5cqYTJXUEAgHs2bMHn3/+OVpaWhAIBERfl5c92u12Uf6Dfjua+9va2hCNRkXWII21X8SJJ9sOsj5Ougs5vGh+UM+PiqKITcyAIxl3VMc4JSVFLEWrqqoSzib1u1T/Lds36udK5FAe6vPLfZLmT7PZjNzcXAQCAWEDyu+gs7MTfr8f//nPfxAIBDBr1iy43W5MmDABLS0tcDgcSE5ORjAYhKIoMJlMaGhoEM6nRD6E48mQd7VLdEzLGSO/NNnplJeXhyVLlsBms2H9+vXYvHmzUI7cbjfS0tLEjmlUfE7OdKIBlQZVuS3yj0uTu9w+2ZmizgqSFSv5XvI5akOP2gL0HcxjsSNrimmHNzqflkIRlOYHQERUdLojERtSYOSUP/WAqJ6wZE8wXV/u8PKArxYItVFBuN1uYRTTtqW9vb1iW1Ov14uuri60t7eL3aNSU1Mxfvx4nH/++WhpaUFpaWmfiVbNQEaU+rz+PORfNlq/idbn6t+PJgFyOGVkZCA/Px/jxo0Thf9aW1uxY8cOfPjhhzh48GBcBhM5nSgtMzU1VWwPTNuzy2g5/BI5ZYHB7WQiKzb0n1rZUV+DCuU1NDQIRwBNYhSdptpuycnJcbVH5GurszSoPSTPiRwD8vMnMh7Uf8uGFWU2hsNh2O12ManJ0XgqECs/b0dHh1B+KW1/4sSJ8Hq9YgkrGfMkJ0lJSWhqahKZT+q+Jj/PV1lZGgiDwQCfzyccT0VFRUhLS0NBQQG6urqwdetWvPfee3FLEnQ6nTA+ybggRybtHkLXlvuBloGpNgr6M0Lpt6C+2t3dLZa80lICg8EAj8eDnp4etLa2AjiaZaoVXQO0xxa6byK5lMd5enZ67uTkZCiKIrKuEjmZ+xsXZEVFpzuS3UfL6Ww2G3p6etDU1ISysjLk5+djwoQJWLp0KT7++GMcOHBAFLs2GAxoa2tDb2+vyK6NRCJwOp3IysoSS3HpGUwm09fW8TQYqA/SkvhFixahuLgYO3bswCeffIJQKIRYLAa73Y6srCwRJIpGo6JIsqwn0e9IY6za6AW0nVH9Bfnk78qOW7nPqIMh6j4uL7ehNoTDYTG2kmySbAPxmU56vV4EMdTyJWdVye3Qkjt1EEIroCFH3rWyAwn6rs1mQ2ZmJrq6usTuXbQMLykpCXV1dWhpaUFLSws2bdoEr9eLxYsX4+KLL0ZbWxs++ugj8Xsl0qvUv8NXBbWOojX3qe0M+TzSt2kHu97eXuzduxe7d+9GQ0MDOjo6RD+h4JHRaERGRgbGjBkjHFXUd2iJnayDyLaE/G/ZOUVtVQey5fNleVLbMpTZQPYGBardbjcsFgs6OztFMWh6X3Q+IetKhKzPqPuGLMtaTudEDnB6Vvl4ovMBxL3/3t5etLa2wmKxIDc3FxaLBaWlpUIGKPtJr9fHBVQ7OjrQ3d2N2tpaAEeWa8+ePRvjxo0T4xzZkKWlpQAgdlIlnUrLZv2qyItWW+lvWm7qdDpFbUXSmWgpu9FoRH19PT7//HNs3bpVzLPkzDebzTAYjmyMQuUx0tPT4+zlzs5OtLW1id+F+ro6mJEItd6RaOzsL4isJU/071gsBpPJJPpZd3e32GxJp9MJe4l2VwSO2s6yrUxzEf2tZUeoHckkY1pzQiL9CtC2b7u7u+FwOESgmpxGlOVIYxTtcN7S0oKTTjoJ48aNQ1ZWlhg3GhsbsX//fjFn+v1+YY8Md9//QjWetJCVcbWzhpSjhQsXIi8vD9u3b8f27dtFgSvaJh6A8OSlpKSIAUNW4uX2yD+munPKA7gcKVAPLNQxZScZnSdPAFr3V0+M8nWoLXRvUnTk9nV1dYmoi/yOKZohCy8N7uoOT/eROy8ZxjKyMUOTp/p51QMF/TsrKwt2ux07d+5EY2MjgsGgcJA5HA6kpqaKzK66ujps2LAB3d3dyM/Px8KFCxGNRlFTU9PvoK6lXMjH1YyGiUFuA7UzkZyo+43dbhdbwlIa5dixY1FUVASv14vk5GQ0Nzdj69at+Oijj1BWVoZIJCL6gjzYUMQ7JydHLCmQd5VQo+V06g+t3y1R5FtWTtTOTfW/yYkDHI1E0DVotw0avLUy8mS5kCPT8vum89TPo5YZLUNL/j3lcYAmJXIaGAxHipECENEVn88n0mJlg6inp0fUWKFrzpw5U6QuazkadDqdWGuvjkpoOUG+btCEmZKSgtTUVKSlpaGoqAh5eXkwGAx466238Mknn4jIDb0TeUcPnU4nConLhVcTyaw87soKgmw40DUItUFKxoJOp0MoFMLevXvR2toa147u7m6R+qzVT+n/8hyjDhbIDl95rlGUozvJGY1G8bxyJlZ3d7eIjFNtAfU7oawKuhdB35M/p7oDra2taGlpgdPpRFJSEqqqqtDZ2YmcnBwsXboUubm5ePbZZ7F9+3ahFJIDjJyC9HtSZiBF9Ox2Ozo6OkTtOnpHo2FOGC60HJ80D0ycOBGTJk1CVVUVNm/ejEAgIByNqampMJvNqK+vR0tLi1huYTabAcQ7rWWHrdaYrc7wkD/TaqfaCAG0jQz1/KKlW8m6AbWTdCt1fUxFUeJ2opT7s2z0qx1mWrpuouCF+n3QO6F7qJemawUnLRYLiouLYbVasW/fPkQiEdTX10Ov14vl8rFYTNTY/PTTT5GVlYXZs2fjG9/4BpqamrBv376vbeAh0XwuPy/9PykpSWR00K6NKSkpGDNmDLKzs3HgwAHs3bsXDQ0NovSFTqcTS/VNJhOys7ORk5MDi8WCSCQSt6OpPObKTlBqj9y/tQxJkitZn6HMUJPJJDKq1E406gvAEScLZQSR7mc0GsU8Io/d6uxAWUYSOZq0kHU0LbTmQfm6antKnpvpOI1lVCydatq43W60t7eLzK7Ozk6EQiHx28n9geaMw4cP/3/k/WdzZFl2HQyvdEB6i4R3hUK5rvZmeqZnHnKMSJHUUAwFg/p1+gMKhSh9UTA4E+JQ6hk2p6e72lZVl4f3mUifMInM5wPedbBy4ySqah5yGs13R1QUkLh577nn7LPN2ua47NmFhQVXalmtVlEqlfoaLRNI1DX9rttSHD/5P5PJYGRkBFNTUwgGgygUCpiZmcH169eRTCbx7NkzfPzxx/jkk0+wu7vr5BZ91eHhYVfCefv2bfzRH/0Rer0eHj165HwMno5KXmPmUCQScTbFRSCL/Yy+r/KrPTFS95P6xj55rt+hzgwEAo5PNPOb76TjVcD4RXSD1dUchx3n75MFdnBw4E4lDAaDrpF+IBBwwTi2xmFPzaOjI9y+fRsjIyOuUoAJP9yTwWCw70Ttfy1d8tI9ngYNxG5UCzrR+H/zzTdx8+ZNPH78GP/8z/+McrmMk5MTDA0NoVgsughPvV53jgZPr1NhTYGtSLw617qYCi4pDYpWWWE26L1sOYIyqxpwOkd0jsnIPkdaIya+47vtuFSYD7qnvqfPudY5sJsNQF/vrcXFRXS7Xezu7mJ/f9/148rlcu4EhEajgXK5jK2tLSwuLuKDDz5ApVLBL3/5S3dymV0Ta/BdBOBcNvLxv/2b/h+JRFzWBiP34+PjeO2111yj40AggLW1Nfz2t7/FJ5984holquNLYZxOpzEzM4PR0VEnTLXRny0X0LH5wBdg8KlGvnf3GTF2/XwAiToj1iHm3/X5di59vKz8o9+1JUUA+rKkVAn4QF1ew+ij1l4Hg0GXhUaFFo1GMT09jXA4jEePHrlIO4EnOvubm5vO+Hn99dcxOjrqwENGYbn3gFNQnmD9d2V//H+lQCDgjnlnFk0ikUAymUSn08HXX3+NX/3qV87ZJp+xgTX7ZzHzCTgD/YH+smgS+c0aP77otuoeCz4z8s3TkDY3NwHAjYPp/srTaqTwb9YJV6fW7lEbaaSOpcxghJzgqWa3qMPjc6J1z6jRZ50yHrvMPUIAjP0OU6kUZmZm8NZbb2F5ednNQzQadaUVOzs7+PTTT5HP5/HBBx/g3XffxWeffeYyBzXr6d+aw23JZ4NRnk1NTeFP/uRPkEql8PHHH2Nvb8/ZI4VCAYVCAa1Wy2UIZbNZpFKpc3aKZv8pyOPTD5qZQdtMZbCvBxTJx6/2vZTf+C6+fajz0Ov1nFy1slH1ijaBVQCZ39Ex+3SN/Vz/H+RI6FyqfGA7iStXriAYDOL+/ft9J6PyRDUCsuvr6/jlL3+Jg4MDLC4u4i/+4i9wcHCAZ8+enRvnvyXy2S76P7M5mPXNk7tu376NhYUFlEol3L171x1SwMg+M2GTySSmp6f7gt8KgvNZVjb77CI7/z7AjD/Td9Cgm7XLKaN5MICWRfN/zcTw6TEFbPm/+lFKz+Nln5/hk7++OaLM0JP79D1ZCnt4eOh8wN3dXbe+lUrlHJhN+cHeTczgYFbza6+9hunpacTjcaf/GPw5ODjw9nv6rukTn22sLQnGx8dx8+ZN5PN5XL9+HfPz81hbW8N/+2//Db/+9a+xsbHRF3RivzO2iJiamsJf/uVf4tVXX8X6+joePnzoAlmtVguHh4eOJ3gPPVjCBjaA84d62cAAif4LbQ2+p9oefKbdjz6wiPPDe/sCGiTuEdKgqiiV69RF1jbjZ75EAF5jfWKfjc99Pzw8jGKxiGg0iuXlZZRKJQCnVTC0wXZ3d9Fut13A+p133nG4ytHREXK5nCtBBU4DvOVyGc1m89w8/kvtiZfu8fS8AVjQQEGa2dlZfP/730e328Xjx48d6BQIBJDP55FKpVCv190RmJlMxkXk9LkWtb9IyaphZH/3gT/2uz6Dy7671nra5/kie9prIxgM9p2m4XNq9PmWCX2/+6Jq9h6+a3zj1nWkYxCLxVAsFl3qa6PRcE6dnpZTLpfx5ZdfYmhoCB988AF++tOfYmdnB7/97W9xdHTUZ2wOcqB9UTwVUpdBObyM808HNJ/PI51OOwc6k8lgcnLS1bcPDQ1haWnJnVy3ubnpGmDaPi08HjiXy7mG1QQ4bemMb6wXGRe+udc9owLUGhcU2NZhtteqo8vvPm+v6dgpE5RXOUaboci54/j1IIBBgBUNIipQOtZ6qg3TdxkVisfjSKfTmJqaciXB9+/fx8nJCYaHh12WydDQEI6Pj7G2tubAgJ/97Ge4evUqcrkcut2uO8KWvdVoCDNSY/fDZdkX/1IUDAaRSCRc345CoYBXXnkFo6OjODw8dA2U9/b2AJzxUygUck4F91wgEHDGld7f90zfz9Ygssa3NdjV+da/+fjOkm+vcD8pz9uxkO9tVh6j9zpObRqqY7Z6ScEuBbzJz8CZMWT1FMviUqmU0+mHh4fY29tDNpvFj3/8YzQaDfzmN7/B9vY2YrEYTk5OHMhOm+Dg4MCVIrfbbeecE3h6kYam32VSXamgaDqdxg9/+EPMz8/jq6++wqNHj1zGGU8dCgaDbg7ZV86W4CvwrzLE6gcbkNCxqUOo96Q+8gW1gH5dY8ElPV3OB2yR9O8aHLB7zNpWFnTy2SQ+8MnOh723vovqEx9Iu7u76w6imZ6edqcqMaCnDcgbjQZ2dnawtLSEq1ev4oMPPsDOzo7ryfL/L8EI4Ez3sZwolUq5g1V4RDwAfPTRR1hdXXWNd5ktMzw87ACQubk5LC4uotfruXJU6wP4dC1wxuc+x9d+l9dbcFV5RwNg5Bd1ank/tW989o+9n/Km6gnej39TJ94XkNasLP1cA5w+8MyCBmwzQptIy3b5fTbB3tjYcAGUdDrtsjV0fqm3mPFx7949AEA6nca1a9cwOjqKxcVFbG1tuYNeqI/0nb5LwK3yle59ynlme09PT2Nubg6RSAS7u7v4/PPPcefOHZcdqy0BgsHT0kfamQsLC/iP//E/4u2338by8jIePHjgsmja7bbLONb9wvWg/auBLQVfNPAFnFUTaIKG+hCW52wwYJD//aJr6rPjSD7Q2GYCWl2onw/yf3itfZ5PlvOZBFCDwdN+dNxH29vb6HQ6zrfgydsPHjzA8fEx2u023nnnHRQKBXdImL7D8PCwm0u2PdD3+peglyq10yiPfkayjqWCHDQwp6en8fnnn2N9fd0xViKRcMZRtVrF0dGRS6un8UBBROHgQ+l9Y6Yg00VXA1snlcaRJYuWWodWEVUrcDkv1hDnfROJBE5OTlx6m4IKWgan97DMr/+rYPcBTpbsZ2o4Umjo8+gsp1IppFIplMtlVKvVvhMThoeH0Wq1XH+b3/3ud8hkMvje976Hn//856hWq/j666/dulKp2vca5EBfNufiIvDMCsxYLIaRkRFXW5xMJpHP5zE9PY2ZmRkUCgXEYjE0Gg18+OGH+Oyzz7C/v+9OOQwGg45vg8EgRkZGsLi4iEKhgHa77RxJzcDj75aeF6nzCW9reFsFoPynSseuqwV09G8Xzam9lr9rnw7yE5WZygEbhWfExmZLqrzT/cq51EbU3e5paVEoFMLx8bHrLxQInDb7u3XrFvL5PP7u7/4On3zyCQ4ODhCLxZziYGbI5uYmfvWrX6HRaODnP/853n//fdef4OnTpwDgGmazjJKK3K7Zd4kuAsroULDEbmRkBHNzc3jllVdwfHyMX/ziF/jwww9Rr9fdPRipGxoaQiwWc01mAZxrQAycb1yphoAqZB8Qq/ykPTXUOVcnwn5HyX5XATTL2+Q9n44j0MR7ksc1oq4nmPmMt0Ag4Mo3WP5Go5/j5Fwmk8m++1unmkBsKBRCuVx2/ezY0yqZTOKNN97A6uqqO8JY5UC9XseTJ09w7do1vPLKK7h16xYSiURfRidB38umG/41SAGiiYkJ/PSnP8X777+Pe/fu4Z/+6Z9cL7hwOIxisejKtff39zE8POwi4MBZJqiW+AD9WW1W1pJfnmfIq3z3gViUXVbmk/i5lsWpnWBtUhtkIM9Vq1UnY5mBN8i2ss+2c8DvDALa1PkhWRvKp//Y2yaZTCKTyWBoaMgdac6yqlQq5U4gqlarePjwITKZDH70ox/hpz/9Kfb39/EP//APaLfbfbbtv1XiPPN0UjYPDwaD7mTATqeDR48eYXNzE81mE6VSCY1Gw8lP8hb9DTrStLes/LZ2qdopdt3tGiuv6H7Q79h7KG8P4kn7Ge/ru6fyMe9J3UXHlXYLZTkDXT47Se1B9cms/abjIrDALBhm/8fjcZfpxGwMjq1QKKBSqWBvb8+tF+0gziftIS2LpJ9JOyqRSDhQkc3L2UvY2n3fFfLxYDAYRDwed8CqBqeXl5fxT//0T7h3757rHaeZTsoDh4eHWFxcxN/8zd/g9ddfx8bGBr755hs0m02Xpacljzagp0Ce2irB4OmBWpq5xwxE5XUNIFAnqa+t+8tiDjaZwvr3vjX2YQT6N7XD+Her03xEvaO20SC8gH+/6F7q4zDbLJFI4Nq1a4jH41hdXXWZf9zLzWYTT548cf2z33vvPUxOTrpyyGg0il6v53ruRqNRlEolZ5P9S9LvlfEEDFbMvutisRjefPNNvPHGG9jc3MSnn37qml4GAgGnaMvlMhqNBoLBoHPMgTNGo/Dz9YzRSAMXTRFVH+k9bIbF8wSPCiiL8qqwtY42f2ZpQDqdRjabRbfbRbVaPcf4RH65mXhfVV76PHVEVQj5DDx9Rzun+j66lvw+I9j1et01kh0aGkI0Gu079jqZTKJer+Pjjz9GIpHA1atX8ed//ueoVCpYWlrqAygGgZi+janveJlokOPDfcCTAJnaPTo6ivHxcczMzGBiYgLJZBJ7e3v4/PPPHehE59FmNIyNjeH69esoFAqutI4plqoMrBC1AlvX1UYXLPlAJ47P8r3PsbBIv+95VFS+SLLKAh0DlZPdiwooUCawl4MagQrmaVqwRu90L9sjVpUYcQsGg47H33zzTfz1X/81er0e7ty5g4ODA8Tj8b6SD+A0vf/DDz/Ezs4O7t69i4WFBSSTSczOzqJSqbjed5lMxjVe57ta8Pay0iCZ4iM9+ndiYgILCwuYnJwEADx69Ahff/11X026nmI1NDSEsbExxGKxvgwxwA+6+hxZXwRar+H6+8AkDQb49IOlQQA872HBJ+0xovzNn7kfCIhpth8NTTrjei8C3HRE+H4EmngfNiXX/c6sWM5dIBBANptFLpdDIBBwpZAsmdzf33fHnr/yyivY2trC3t6eM9QIzD558gSPHj3CtWvXXENdZsHxsA7tzfBvlcg/PA3tT//0T/Gnf/qnuH//Pn7xi1+g0Wjg6OgI9XodhUIB2WwW1WrV9daanJx05dh02oHzmToWkATOlxzo3rByxweq6h4l8Xs+Ocq/Wyfagk5qWwFwMp6HVbCURh0gO06bPaVjU+dA31GB5EF7mnabtUVtJJ5jI7ibTCbRarUcyBQIBJx9xT43e3t7+OSTT1AoFPDDH/4Qf/EXf4GVlRXcvXu3DxSwYMZ3kSx/8Wc9DZjrHY/HMTc3h0wmg3v37mFvbw+Hh4eoVquo1+t98rrT6bgTD7vd0+xKAC6Lks6wPteCTNbxB/p7qXJt+Tlwvu8RgHM2MGlQoMLHS/odOy7rzKqeA+DeV4ObHFMsFuvzOZidretiKz7svOk4e72eA4BprzLbn+BfMHiapQnAlZtyTwDoO/1YWxLQwWfQ4vj4GL/61a/Q6/Xw7rvvIpVKObnI0m/g1PayJb0KGF5msrzH4BsBRWY+Kf+yHQplI20EXler1TA9PY2/+qu/wve+9z1sbW3hwYMHfX22lMcsqOLzN22bCyZbaD8nBrxo07MJvE2qsECODSbYZ1rwhDLZlgFSZvvezQY3CAL5ACWgPwCpOlbJ8pfFMQaR9u9kiXw2m3Ul23fv3nV6gyDywcEBtra28Mknn6DX6+Hf//t/j2QyiWAwiLGxMUxNTaHX66FarfbJhVqt9i+qQ37vHk8+h8E3sEgkgoWFBfz4xz8GAHz++efOmWaWAE9lYGYHG19x8dlAWZmBRrMFoHxCnkinBYEGGTQ2S4O/a+O5QYaSkqKhPsT35OTENYqORCKYm5tDNptFvV7HysqKNyPIF8nQSIrPifetkb4riYKH19k5JjJK4ZxOp1Gv11Gr1dBqtVCv113Naa/Xc0JtdHQU9XodX3zxBSYmJvCjH/0IOzs7+B//43+41HAbzfTx2PPAqG+bdEz2HaLRKEZGRpwTncvlMDEx4U6HYMbf48eP8Zvf/AZ37tzB3t6e40uWCwFnxhZ7FxwdHWFjY8NlQNgIlDWeSRZs9RF5ylfXzGwI9o7pdrs4PDx0kSp9f47Hdy/uCVVWaqhQyZBH1IHWum8tHaEBotfzXicnJ65pebd7lq2kcsT2sVHyKRnuUY6RxlEkEsHq6irS6TRu3bqFv/mbv8Hw8DA++ugjtNttl/HYarWcjGo2m3j48CG2trYwMzODH/3oR7h16xauXbuGvb09tFotV3bGLJPvAtike/wivuT18XgcxWLRgfPT09N4++23kUgk8Jvf/Ab/63/9L3f8ONeZPT6Ynp9IJFx2mMrHQWO0+u1FDU7fu9jvqjyz41A5a2Uz+VEj9HxnPsfuH+orGmcKDvN+GgjR74dCIXd08vHxsePlXq/nMmm4lyORiCtJIZjFYAnBKZ5GybTvtbU17O7uYmJiAsPDw2g0GgiHw65HBHUQgaRAIOCMn1arhXQ6jZGREUxMTGB/f985i8FgELu7u31z812k54GxwOncvP7663j//fextbXlmuoHg0E0m02XRXBwcOAi/JFIxB2lTBlNW4ZzbuW26ohe7yyrAOjvjaHtAwY5xNaQtvaM2mf2ezo2C9qofcS/HR8fuybqsVgM09PTGBoawtbWFjY3N/vKOUi+Mh8dl/7sA0Es6T3UdtWAhTok3HPNZrOvpxD3DdDvbITDYddAtlKpIJVKYXR0FA8ePOjL7Pwu7wUfqZxOpVLI5/MOeM5msxgfH8fExISL4geDpyegaX9M/j88PIxCoYB8Pt/H68pXfKbNbiCpowgM7hfLe/d6Z/35LHCqz7P2vM9v0TFYH0HtEz7P57PoezNzVHWK7gvyHf8x68UHDOp+t1m7/McAQ7vdxu7uLoaHh11j92QyibW1NXf64PXr11EsFrGysoKlpSXXu5HgFLNgCaTwfQ4ODrCxsYH79+9jamoKc3NzmJqawtHRESqVCtrtNpLJZN9J0bpW3wWyvgd1bzgcdnZULpdza9rpdFz2JPdDt9vF0NAQ2u22s7f/n//n/8EPfvADVCoVfPHFF6hWq24/KdivPMd1tXPnk6m0Jejf2DlnwNDqF9ovCjYpaXYUf2eGtAKxPlJ/hKSBZs4x35vvoAckqZ58HtmxqE/BOeXnttyc/zNA2Ov1XHm9nvir9unJyQn29/fx+PFjvP/++0ilUhgeHnZtDDhPtOdyudy/eCuDl854sg414DekKaiZCjw2NoY7d+7g6dOnTrkeHBwgl8shHA73pfzxqFCCUz7hrZFdPk+dGp+RMmjSCAINSqsD+lMINUV1EFlByzFaJUVDgqmgPEJex83xqZNtgaWLnCqfk2eNJx2n3QR8Vwv6pFIp5HI5d+oH+z1Fo1Gk02k0m000m00nIFZWVvDJJ5/ggw8+wPvvv4+VlRV8+OGHLrpho5E6hsusAHzzrvNL0IlRh5GREVy9ehUzMzMYHx9HNBpFo9HA3bt38Y//+I948OCBUwgEXSlIY7EYcrkcpqamMDk56RrxAmd8oga4ReOB/oi2CjXlLe4h8j0dXo5Hr2VEwhppvlR/m+qqfGwNF93HqhxpePMZ/Jz3YARDgSmCdgSadCyqpNS5YsmPgtIKmujnOt/8rNlsIhg8PRFkeXkZkUgEr7/+Ov76r/8arVYLd+7ccVmBPLGF49JIKwHfXC6HkZER1wQyFov1GcO6Vy8j2X180Z6Ox+OYmJhANptFNpvF2NgYJicnMTExgXK5jJWVFayvrzujV41i9nMiMMf1teC8jusiUsdAHXLrNPvAWQVa9T6WfHNhwVWOlRFBGgbHx8feiCDvwXfnGHk/PWXR6nNG0drtdh8v9npnDdn5LKsr+Tvnm0YLI7CMlvNgimg0inq97npQ0VFi9iaNz88//xz5fB5/+qd/imKxiOnpaezs7KBSqbieBgTLvsv0PF0XDAYxOjqKH/7wh4jH4/j444+xvb3tMshOTk5QLBaRTCaxvr7uIvsjIyOuWSz5Q8uJfDLb5+hyfBqI47X8u5Xd+l0G2tTB53v59oaNBlsHX5+hTjaPnU6n08hkMn0Zfr69awMxPsdTbbjnlbLZPagBR7XZtE8IS4cY1GP2GmXa2NiYOyWVmdMPHz7E1NQUvve97+Gv/uqvUCqV8MUXX/Tp+e86WR4CTvV1Op12JdWZTAazs7OYn59HoVDAzs4OarWayxRmaS/5nA7a6OgoEomEKzVpNBquXJEyCDifzWrBSF1vBsqtvqBNYe0z1U3kUX2m9uojqby3gJX+3Y6dc6DftaAQ/6Z6otvtunnRe2i2ubXjrM7jOHUvKNDKANLNmzdRKBQwPj6O9fV17OzsoNvtYmxsDIlEAo1GA5VKxR00wmoRls/xcAru7ePjY+zu7mJtbQ3z8/O4ceMGYrEY7t27h/X1dQd86KEtFhi/7KRyywaSmAHearWwurqKJ0+euJJT4Ay8YOlWNBrFD37wA/z5n/85IpEIvvrqK2xvb7u+T+RX6lvqD6C/hY0F8jmn3FvKWwrWEPzgfZiFpaAT31H7rmqvNP5j1pQCVSTfzzaIx7/5wDTlE9pmPJ2YZYjWNwLO6067fhyHygYrz/UdGVTsdk8Po4jFYlhYWMDKyorTKZpJdnBwgIcPH+LDDz/ED37wA8zOziKRSCCfz7seeCzRox3Naot/CV/8pXo86UT5jHgrxCKRCF599VXcvn0bW1tb+PLLL53gZbR/dHQUx8fH2NnZceUnPL1JT2zQaBiNaI10XWQcWbCM1+r/PkOdi8rnWNCHZIEaO4ZByCqd3EajgW636yKTuml5JCWv9yk4/RvHrllbui6+8dn3UMUOnDm+NmLH5nXb29suq+Dg4ADVatWdNlSpVFAulzEzM4Pj42PcvXsXyWQSb775Jn70ox9hdXUVDx8+7BvfICBTf76MQJTPASNgwEjzyMgI5ufnsbi4iLGxMfR6p0eS/vM//zO+/PJLLC0t9R1triekUcmmUikHZFFx03C22XoqzO0eUcOFwJJ1oPkOPGWPkQM1mCjQ1WBSXuM91TFRGuRYDALBFHziHmHatn5XBbUa91RGWsLKSJ9GYILBoIs28zq9t6+ZsvbQ0b4zR0dHePDgARKJBBYXF/Enf/InWF9fx97enitTBc56VR0fH6NSqfQZQixJSiaTODw8dMYElTTpMu4P8sCLjIuHF7BnRy6Xc6cNLS0t4cMPP8THH3/sskU10ymTyWB0dNT1JeLaDQKddHzAeRDKym6VwSoPfaQGl+/e9hmqX1Rv8Vk0BBic0b1CvtGgiJYc8J7qyJBPrAOtxrpNT9d9bYMRdn9zrMzmYxkR99X6+jqazabrDZhKpQDAlZL2ej0Hxna7XZRKJTx69AjvvPMOisWiAxXi8bizJxKJRF/G5b8l4vomEgn84Ac/wCuvvIKlpSU8ePDAXVOr1Vzgp1KpYHd3F4FAAGNjY8jn8y7DgKSGrTpqJN/6WjsBOJ/d4TOwfXLSvh/HxOeo3NUxkQ+tc817EKys1Wo4ODjA0tJSX1kyr1Edpc6TBRXsdbxmEDjlI7VZ9VqdFzreIyMjaDQarj8VAxT5fB6dTgd7e3s4ODjAyMgIWq2WO/nxxo0b+JM/+RNsb29jY2PDzeO/tf3A7CbKgImJCczNzWF6etq1Hnj27BkeP36MjY0NZ2PTjg2Hw65nIMtNAaDdbrtrh4aGXIBLnV3Af6iE+hnaq9XHq3ofDRrwPtbnYMBM94Z1pMmL1ufx2f60F1XvqePNz5Ssv8F2AsFgsK/foPVTKPMpazQzn9/R8u7NzU2XjHDt2jXMz89jcnISwWAQh4eHmJ+fR6/Xw2effebWio3GuZZcL+1NValU8PDhQ8zOzuL111/H+Pg4lpaW+oBCGwD37e/LTFwzZqRpuXyr1UK5XMba2ppr1E7+iEQirvIok8nglVdewX/+z/8Zc3Nz+Pzzz7G3t+fafTSbTceXVo5b29OWuXFvEEiyuojgjX5H22toeZ4lfa7uWw20kBS0UT7Uv+t8amCCe8XuD8oO5ScCUbRF1QbT/USycsaCYAys2L3MNaT+Ghsbw5tvvolwOIzNzU3Xo9PKnf/zf/4PNjc38eMf/xivv/46FhcXMTIygrGxMWxubmJlZQVra2vuvnt7e32Bx9+XXqrUjptQDQSfk0PmYplIJBLBN9984wAJHvU7MjKCYDDoGv8lEgmMj48jlUr1gUFkCq2ntNEH/dk6GTpuFeQqRK3xr+AWP+c7A/5ognU09Hv6HGu48CSsaDSKQCDgsoT4HQplVQx2I/mMPlUq9mcf6KTzZueICC6vpWJhY3hGxylU2I+A70NnqVwu486dO5iYmMD169fxwQcfoFwuY2dn59zc+8CnQcDUt0lWsevPbFoZjUYxPj6OGzdu4OrVq+7I3m+++Qaffvopnj592terhkK90Wg4RzybzQI4dczZeJ817EC/4KajR6NAha/PWLF7in+j8jo4OHCGjwrDQYa78tigKAH/pvxs95dey+vY+FP7u1AxWRCYn7P0QAFUH9hgQWiNtPiMNP3dvgsjJEdHR4jH42i1Wrh37x6y2Sx+9KMfoVqt4s6dO/jd737nIrDM+AgETjPJ1tbW8PTpU8zOziKfzzswhid/2izNy0wvMr5sNotMJuOcimQyiWvXruH27dvo9Xr4r//1v+Krr75yWV+BwFmaMZ2RdDrt0rO5TrY237eGPrJOsNWBKpMp//l3PougoqZwq+FtgVf+b4MfWj5KA4TvbbNV+D0CTjb6rmV8uj7cw/yOlq9ag1z53gdeAXCHTITDYQewJpNJAKcgyd7enuuxsrGxgVqt1tffgeVQfO/NzU388pe/BAAsLCzg6tWrrkSi2z0t9WU29b8l4lyHQiFcuXIF7733HlqtFj777DOUSiUkk0lUKhVnV3W7Xezt7aHT6SCfz7vMcvIUDU8S5Z61DXyAhdoFOj7f7wrWq/Ptk72WT3md73k6J1Y/6M+0SdjHgmWjQP8R9Byb7gGfTLC25CB75CJZx3ehc0hnhP+HQiHE43EkEgmXzceyIADOMSuXy+4wks3NTfz2t79FKpXC22+/jUePHuF//+//7UpjfHb6d5UikYg7AbBYLGJsbAzz8/MuQzYYDGJ5eRlffPEFdnZ2XPCHcrLX6yGXy7n+f1w79isFzkoctT+e+h4+AErJtuYAzsBWjoFyjddYR1SdTJa/qY1l7biLsihI1tby2Wj6DL2Pzdz1AdC8zvpHGhSkT6M6hgGKaDSKarWK4+Nj5zBfu3YNqVQKiUQCCwsLrp1HLBbDnTt3UCqV3Ml0DNpq2ZZmtu/u7uLp06fuNC8GPWjnqg4fNIeXkawtMzw87AI35DNmiq+urvZlOwWDp6cGEyx57bXX8JOf/AS3bt3CxsYGlpaWnC1Vr9edP8fva9CUpMCO+pAKymoAV+0x8jn1HW14PUXa6gQFOWkXn5ycuIxttZOUfKATSfnA6pZBcw/AAbL6eSwWc609mPHtC7hr+fcgP4VBdPo9FtRmSRwbyne7Xdc/W+eNwe1PPvkEe3t7WFtbw/vvv+/kKVtVMNGA+ml/f98Fu3/fvfHSGU8ki6jr58FgELFYDG+//Tbm5ubw6NEjfPPNN26R2QuIdbX7+/uu8z6NUgs6AehbEFX2dmFU0epnvM4CGz6jyToqSqp8LPP7HF/fPHKM3FDtdhuxWMw5n4y48DvWOdbn+YwKVW4+BWGvUzBM392im3ptu93G0NAQisUiOp0Otra2HFDCdySjlstlV3e/vb2Nb775Bn/8x3+M733vey6LgYbgRWt7GZWANYBJkUjEReQLhQIWFhZw7do1TExMIBgM4t69e/j1r3+NUqkEwG+M0/ggmMTy1WQy2RdB4jU8ipzp4haI1XurY0pBz/eg8qYgJB/YSAP5RQEs4PxJPr450/81ImYFuyopVTzcJ8PDw84YtyCgrommuSsYx6wYKzNsKjnHZhskWkdEnXWWFh0dHblU7qWlJczPz+M//If/gNHRUWxvb2NpaQmJRALDw8PO+O31Tvukra+vo1KpOOeRKbM0FCy/fBedjGAw6MBZlkBcuXLF/d/pdJweKZfLrgSbwYhwOIxMJoNcLuf4WY2Fi5Skj08tgGjBe37ORubMsLBE0FKfo/vEOrJ2DKq3NLKskT87fn1X8qPeD+iPQJJsFF/Hqga5BeF0vLwPn0U50Oudlp7y6GVm6h0eHroxsEy73W6jWq0imUxiZGQE1WoV+/v76Ha7WF1dRTKZxMbGhuuJWCwWsb29jWaz6U7y+bd4wl0odHogxfvvv4/FxUV8/vnnWFlZcetbq9UQCJyWFVcqFVSrVQfGMlrtA52A8yfV+UAce73PUbZzbp1Qnz1kAU++qy+45tsrVt5pYIy9rXK5HIaHh9FsNgHAHS6he8f3TnbMPr4fZK/47kOdQmeQesVm37Ikny0oDg8PXWNxArWVSgWNRsMB7Xfv3kU+n8cHH3yAH/7wh1hfX8enn37al9nwXSKfPaQn2FHeT0xMuIy+TqeDlZUV/O53v8Py8rJzwqgzWX65sLCAQqHggmm9Xs9VGwSDZ1nUCoZqRgzJB4jyczrBwNkJoFrqqfrFl4HKaylzfXrEZ19Z59rKeD4LOCtp0vFosIJjVcdcr1P9BuBcEER5nvxu7SXSycmJC7wx+M6yn9nZWXcI1ejoKN555x03v5988gnK5TJarZY7YIc2m5b0Hh0dodFoYGtry52uOjo66vrq8n469u+iPZVIJJDJZNzhG+yFVa/XsbGxgZ2dnb5ydPqd7XYbExMT+P73v4/XXnsNR0dHWF5edr4E5Q11hy9zifNEYASAexb3IK+z1RjcSxrgJv9zLwL9QQxra3OP0h5jMJqf83tWt/H/Qfa02jZWL+netXuDxPY5TMqgjFF/Ru+re8QCYypz1LdXPj88PEQymUShUHB9lKn/dM45r7SrV1dX8fbbb+PNN9/E2NiY66HGsu98Pg/gNPPp/4te+b17PFmwSSciHA5jbm4O3/ve99Dr9fDgwQPU63V3hPLh4SGy2Sw6nQ5KpRI6nY5rusx7+yacf1MG1DHowvuMHTt2Pkcd+EEAG69X5qSz7rtWvzPIqQkEAq5XB2snWTJCw1lT43V8Vgn5nsUNo5uGSsy+p6LSCvDZtVU0mgKH/SMODw9RLpdRr9fd0aWJRAK7u7vY29tDKpVCNBrFyckJHjx4gNHRUdy6dQsffPABnjx5guXlZfccK/zteC8CNb4N8s09gYShoSGMj49jfn7eRdmePn2KTz75BF9//bXLJmKTXAVj2LuAtdTpdBq5XA4AnJJmry2myu7s7DiBYuuhdV9pZMvyEK9jE0GNBg8y/KlM+Bn5T4Epu3fV+FcjZZDjQ2OI70dATA1LXkf+1IwRXst35WdWeegeVYdfyRoqvA+VIT9n+Sn5f2trCx999BEWFxfx/vvvIx6P42//9m/xxRdfIBaLIRKJuH4Uh4eH+PTTTxEKhfDTn/4U6XQas7OzLquDWXD7+/t96/hdMpboLBcKBddrI5lMYmpqCjMzMwiHw7h37x4+//xzbG5uotFooNfrOQUOnGYWjo6OIhgMOgdCI7p8zkXApB2TdaqV2LSTPQ8oq4F+Z1vH4IuO+5xT61RwX+iY+T3KSvIdeZrPtKAZeV+dXX0/fU+Ncun8WcdH393ON9O/1eAjEEuifqOzvbm56UAURqS5zwjGPnr0CHNzc5iZmcHVq1fR6XTw2Wef4fj4GBMTE+j1eqjVat61/a4ReSISieDKlSt4/fXXUa1W8cknn6BUKrkTLpvNpgNBmT2bzWZdc3eST5daw9aCrvZ3vRY4y7ZVR135dBDv6z6z371Iv/v+rjxGwJV9NkKhkMvAVtCN91H+HRSo0ecoCKvvb/WodUY0+8LOg65Dq9VCLBbD1NSUywbhO9Ch48l2+Xwe8Xgc5XIZd+/exZUrV3D79m388R//sSur0SDT8+gy6g7qCGbvJZNJlwEzMzPjykhXVlZcL1k2vg4EAi4g1+l08MYbb+BnP/uZK8Fkg2ldGyvTdH00EKBl+bwWOLMDtMym1+udKz1SPlO7l4G/YPD0sAC+h5bTWH3mA6esHtN9yPuQdzWbFugvk9WMr4vkvYJRfAc+g9/V79hkgmaz6XrSnJycHr5ULpcxPz+PYrGI5eVlDA0NYWFhAePj4/jZz36GVCrlSomOj49RKBQQiUSwt7eHcrnsdBhPNnzy5InLpp6amsI777zjyso7nQ62t7fdetmA52UklVEMTiSTScTjcYyMjODKlStIJBK4e/cuPvnkE6ytrTndTx+l2Wxifn4ef/M3f4N3330Xx8fHuHfvHra3t1Gv19Fut12gl6S+IAOinDeWqXJ8DCwSFGL2EvW68i1wFiSzPdH0nVV/8H/6INp+g7a9vVZ1Gu+pe0qvoU6w9hNBMfWNfdmy/Dv7GbPCibKBz7d6Rd9V7835ZWWRYgYEtYLBIFKplGtFwLI/JohYLKPZbGJ9fd09+6233kKxWMTCwoJb+273tIcU99LvC8z+3qfaDbomFDpt+PfWW29hbGwMd+/exdOnT901NAaZel+v110PGRu9tamdPuPHxyRkWp/RoAJEHXz+PMhAUkagY0FGt5vCRkR8zo8FrTQSbaPR+j5qyCjpM3zOlTWidIPrO1kDzDoi+q7a8JD9iw4PD1Gv17G9vY1CoeDWjafeMSunXq/jm2++wczMDF599VW89dZbLi2aa+kDnHQeLwvpxuPPbHgZDAYxPT2Nd955Bzdu3HClpl9//TXu3r2L3d1dxyO63uztxIhFp3PaTLpQKCCVSjnBnU6nneHZarWwsrLS59RRuFse1L5hPkeD3+XnKlzJA4yGkVdU8NJAsidR8P2swc5xDXLY9dkKUmm6uoJc/J2RL72nXq/OunWEOD8sfSD4x8wWTWfWBswE+yjQWepXr9eRTCZdOjizlhYXF/HBBx9gfX0dpVLJrTebxjcaDVdrvbCw0AeS8dSwWq127ujn7xKxp1MymcT09DRGR0dd6cTW1hY+/PBDPHnypO80FTpSBK04t0A/AKfy0uesKqkusPuSFA6HXWP3o6Mj5xTyOvKUDXAMyqJVvWXBT30PXmP/Rn5Vw0mffRHYZuUODSpmU/HkIiWbxWL1n82K1Kwnm2Wic0BDOJfLOT3ITA82lCXw9NlnnyEajeJnP/sZpqen0Wg08OTJE7RaLQf2X0YH+kXIN27KoFdffRX5fB7379/H0tKSy7hjBDIUCqHRaKDZbCIUOu0HpTLQF3SywCavs6AlPx8E0pNnLGjjixLzcyXKYeoVn83iCywqf2u2o4652z1rXmvlvDa49ZHlV58M0WusrtV973NgqTM1S5j6Np1OY2xsDBsbG2g2my7IlEwmsbe35/p4TUxMIB6Po1Qq4bPPPkOxWMQbb7yBL7/8EqVSydlVqut17PZ9LwPp2GhfZjIZDA8PIxqNYnR01GU90a569OgRHj165GSy8mK3e5odfePGDUxOTjpbSYEhfbb92ZfNwB6QzPBgiRcdTPa3494IBE7L5rTME+i3txV0UvDMZm0A/T6S/k9SP0WBNc2KUrBMdYcGz9SO8+kSu98pJzhGzp3NWrEBj16v19fLqtPpYGNjA7u7u4jFYojH4zg5OUEmk8GVK1cwMzODW7duYWRkBL/73e/w0UcfoV6vY25uDmNjY67XWaPRQKPRcH7IxsYGtra2UCwWkc/nnZxkL1XbvuKykuXTYDDo+jrxfRh8YBk6/QNmbLO36RtvvIHXXnsN4XAY5XIZwOkBUmwqDZytnwKgmt3EDCiC/gQ8mGChvNHr9foyk5UPrc/A8fI9fbYUkyYoR+l/qL4iqU4a5F/zPdSG4ji4F319MEnqx/J3PlvlsWb3Kp7Ba3W+dG/y3kNDQ8jlcu5gMn6n0+lgeHgY+XwetVrNHXakPe34npSPwWAQtVoNv/vd73B8fIwPPvgAU1NT56rO6J8wk/Nlba3fu7m4jziRs7OzuH37Nvb3910DuGw2i4ODA7RaLceEtVoNnU4HmUzGReUYvVWyxoYuChnAIqUWLNL3GIRKDjKQyMzWkOIzNHXVl6Whi6KCl8ogk8m40xrY74nGY7d7dtSxglwcz0WC3Kcc7PjJzDovOo86JxwvNyTHxWytRCKBbDaLVquFarXaZ+yxrKLX67ljHp8+fYqvv/4aP/jBD/D+++/j66+/xpMnT/rG6lu/QQbCt0V20xGRJiiQz+eRyWScYFhZWcGDBw9cQ31NqQbOsnd6vZ6rCyafjI6OuvnL5/O4evWqS8nf2dlBvV53Ar7XO4uwaXQLOAMNKTjU8FFBrfNr0X/lC47d7iv9jqaVcp5IPueBv/uMKuVTft+WK9hrrWOlCsxG5PhsOrC8hkKbz6KCpzFHZaS9IjQllUf3hkIhV1I0MTGB1157DV9++SV+85vfuJ5QTMXt9XqoVqtYX1/HyMgIhoaGkMlk+rKiNDPysjgOL0JsCJ7L5ZBIJDA2NoabN29ibGwMIyMjrgn12tqa63cSCAT6Sod4fDYjaTRYlDdIz5MXPsBHgSP2BNEMRZ8D6zM4OBZV9FYX6V7yjVWBXr0nAAdo6vitfrDA3EVkQViST9f4ghv2XiSbXaPvHggEkM/nEQ6H3RHolKU0Zrln2fyyWCyiWCxibm4O7Xbb7bGTk9OGst+l/WD5jj+HQiGMj4/j5s2baLfbePToEU5OTlxpKcuqCdYxUBGPx/vkpwU17dxYwIYgCIlynLxhAVC7lnrPQeCT8o1tHmv1lo8f+Tzdb7x+amoKxWIRkUjElanVajUHDKitaUEZe399LwV4dZ/YvaB73AZcFIRV205tQ+6Ho6MjbGxsuH42tL+azSYqlQoymQxisRgODg7w9OlTPHz4EG+++SZ+8pOf4OnTp3j8+LF3f172vcHxMrofDJ6Wq+RyOeTzeeTzedy6dQsrKyu4e/cuPvvsM2xtbbnAHPv/NZtNRCIR/OAHP8B7772H9fV13Lt3D41GAycnJ67kV/eHPt86n8CZrtDMW+5D2lCa6UQ7QTOL7H5XnmRmKB1xW0KnthXJ8jD3l11n7dFjwSOf/Ub7hnaqBursu/AdaJMo0KGnovnIOuvq6B4cHGB/fx+9Xg9bW1t48uQJEomEO8mQJZRfffUVPv/8c3cKbjQaxcbGhjt9u9FoOEecdnWxWMTq6qoDY9gbSOfnMpLKDwAuA4b8lkqlXKC6Xq/39RYiSHRycoLZ2Vm8+eabSKfTqNVqLuDT7XbdAWBbW1s4ODhw8om2lg8sabVarr+UzZrlGGnnqw2k68594wOhSPSP1Re2Mp3zZAMovkCG5UsLRtn7ksfVp+YYrA2m3+OYFEdQm1X3kn7G7+iz6CdMTk66BASWnobDYaTTaWSzWeeT84RXglTc8wcHB1hZWekLqhaLRbz22muYmppCu91GrVZzWcTa/+ll98hLZzxZQWkXMxqN4tq1a8jn83j06BE2NzcRj8cRi8Wc40AjgEfGswbVIpJAf1NYffYgcEoXRg16FchW+dsI3aB395HvvtYQUwZUB52bJpFIuNTI8fFxJBIJrKys4N69ew61JPil6CjJOlYWBaei8IFt1snRMVqlq6AFlSfrqWkkUXCxUSPn4OjoyJUHEYlvNpt4/Pgx5ubmcPXqVbz33nvY3Nx00SrN/PKN6bKQGo0cl2YIPXv2DLFYDL3eaVkcyyLIf7aPgBoYCm5Go1HkcjmMjIyg1+uhUChgdnYWQ0NDriEjx3B4eOjmn3tBwUIf6KPC3zqSwWCwD9ixIKZ+prxEA8UCsj4epvJSB5nPIGmqujUEde4USNP14Rh4X6akWsBBv0/QlPtV90MsFjvXY4rPU4CNc8RoVDqddhk6BwcHGB8fx+uvv45vvvkG29vbSCQSrq9Xt3vaUL1erzuAl4qN6fx0yn2A82Uk8hb7EcRiMWSzWYyNjblINgA8fvzYHRdPMI/ZgENDQ5iYmMDMzAw6nY4Dgqzz+iIgC9Cv5OnEA3Dp6AQOVe+RD9RxVh6gw6CAj/IZ78HPFaDVvaiRKspoNfo4BpUlGnHW5+gaqL5UOjk5cQC4Gn0+faf31bmwz9Hvq9PCMfO5wWDQBar29/cd2BSJRNwxv41GA5ubm/j444/R6/Vw7do1vPLKKy6inc1mcXx8jFqtdqnLJCz59iyd7Rs3bmB8fBy7u7uoVCqOLzlHDPAw8zGZTLp+i7yPvb+uJXlGQR8a/+QTzeZUOT+oZ5TldaC/dGAQsKkBNmtX8WcLZqoeA+CMbs4DS9Tv3r2Lx48fu9IDyk3lbd0Tqo/Jswos6di0VEptJguMWUeH9gI/Z3CWciyfz6Ner6NarTqbmuVFBwcHODw8dP3NKpUKPv/8c0xMTODWrVt4++23XXaPgmb2nS4rBYNBxONxV4I9MzOD2dlZXL16Fa+++io2NjbwP//n/8RHH32Evb29Pqc4GAw6kPHdd9/FX/3VX6HZbOLJkycuYs/TUS0AqDxm9Sr50pbO2SAtx097ltfZDFk+jz8z06nb7bpSY6vXdY/4dIjKVNKg4Iidbx/4xGstaKrE/UcdzcCmjpPPsIE+zaC3oIDuNVKv10Oj0cDDhw9RqVRQLBYRjUYxMzODVquFtbU1BAIB14aCe52nXW5vb6NWq2FkZAQTExPI5/NoNBouo07HPQgou0wUCARcKW4gEHAAbTqdxs7OjvO/yNfUp+FwGAsLC5icnHTgAm0JnmCniSOUO+QDgoIKmJPoN6jfSv4cZHvo76wK8AXoeH/LO9aGp62sz1VfhUEBG/DmWHSPaOaP1Q+qy1S3Wb1i/Qy9H5/NBByOnXalfpfvc3Jy4jL6RkdHMTMzg6WlJaytrblgS7FYRKlUQrlcdpgD9Z6t0Gi32+h0Onjy5Ak+//xzV+ZKP6TZbLpezloaa/Ggi+ilezypoatgAIXw6Ogorl+/DuA0Itnr9RCPx10DbSpY9mgZHh52HfU1BdQ6bSqENHpkDRduBCvgfYipva81bKxxZCMMVFSKblqhSfKNk9fzyF/gbKMRcSfIo+UKOi5lVgUJ9BmWXsQRUwayik7nQZUR+56wySOPlqTSZcRB0ezt7W18+eWXyOfzePfdd/HVV1/h/v37AM7QZB2DNQYug8GkY+P+oPJKJpMYGhpy/Fcul/HgwQMsLy/3nWBGouI4Pj5GNBp1mYDZbBZvv/02PvjgA9dYPJFI4OTkBMvLy64eu9VquYiugrMUUABcPTYNBAo1X0qqjWao4apG9kU8pYCl/q7ALNeZEUI12jS6oMCXbU5o70mye48OPAWvvYfKOGbRMGrHazQSp6VWKsiBs6OEWY46OjqKyclJ13Q+GDxNx0+lUnjllVdw/fp17O7uotM5PQWSxicjh4FAwEWxyCcEswiKfFeIzQ9jsZhzkthQPBQK4f79+/jlL3+Je/fu9fW8o8ItFAqYnJx0QQ3gTCbY6PBFZAEn/s9AigIe6girQaGGFNCfjs1rNWt2kHFNIh/pPTTK7JPtvhI4lc822gacj3KrMcg+CfqsQc6GnQ/Lh6rHdY/qfKtBxbkvFosuUssSCO7Hw8NDLC0tIRqNIpPJuJ5Pq6urqFarztnQk8y+a8R5yuVy7iAClk9pk1LOO0/MoXHJ/eJzCnSNaNjzZ/7PMgryo11X/dwGI/gz11udYQteWluC39OIt36P5AOueB/2a9nb23OBl16v58oQOXcK9Op97bPUJtR5A3AOrPPdh++lvK/vrHuEuplEYL7dbvcdYtDr9VxmYDKZdEGQ9fV1fPHFF/jZz36GDz74AF988QUePnzo3kPBM/582XQHeZaBGjrS8/PzuHbtGiYnJ7G0tIT/8l/+Cx49eoRKpdInR7WC4Ic//CH+03/6T8jn8/jwww9dI+parXYOtAfO5LNtq8G5olPI4BBJAxCU99rnSH0Q3sfKZQK55H/yhXVsbfBD5b3qH933mrlEYEi/49tPXAufTaUBBI6FpEATx2z9OMoP1Y2qk+xeUlIQYHNzE/V6HScnp6X309PTWF1dxcbGhiuH4vfZA29jYwPb29sYHR3FyMgIcrkcdnZ2XPmytQMv2/4Azvd30qBToVDA+Pi4O9SGwWn1IdWOCgQCLlOGVTfb29tuHlKpFPL5PMrlsivbAvpthkGke4vf4b7SoJYSZbba1UrkIQDnTryj7tLel3Y81qfmPS04C/QHvDVbkGugbYIUkOM7Kijmk/+qF60NyudTRqmNdXR05EDSbve0ImN8fNzhCuz7mM1mUSgU+pJ/KLu4BpQT3C/VahVPnz7F+vo6isUiJicnAZz6TezlnEwm+4Crf1XgaRBKHolEMDc3h3g8jrW1NWxtbbnUxWaz6aK+fDGCUoou8xm8J5laHWAVIGQwbfplgREFynzGwyAadA0FJhdKFcig71iwikRmYqqvGkLqcPBan9HDOeO7DXIMuPnV2OF39VrruF9EdgwAHDOyDpTCkI7+0NCQy3zqdDp49uyZaxL7+uuvY21tDbVarU+pXUahT9L5Ii/wRIlYLOYiKsPDw1hbW8P6+jrq9XrfkZTcJyyt494YGhpCKpXCO++8gz/7sz/DtWvX3CkD7XYbq6uruHv3LjY2NpxRqqe0Kem6kxfozGlkygc+cR9qqrVer2tlDW3KBuAsMmhrtK3BPgg44Nzo/1RABLC0z4h1ilTBsCTPOsyMNqhi9Y2X4yE4ZYFZZosAcLX2LCPi0cGxWMydGJJKpXDt2jV88cUXqNfriEajbl6Y5dFutxGPx13pJnB2uoiWGL7o/v22KBKJIJ/Puyaf4+PjGB8fd73+ms0mnj59is3NTdfrSiNTw8PDmJmZQS6Xc+WqdCRf9t3VOADOZClBJwZM1MAgcc4VcGSZAflBAVKV4QRRgTO+5r1tHT6AcxltpIuMe/2f1/p0lI3AWSPHAgQWQLO6z7cGPlBYQW3dZzRkhoaGkEgk0Ov1Z5spOLaysoLf/va3yGazWFxcdJHdXu808/O7DDwBcGV2AHDv3j3Xw4bAEmWVGrjMruRnds0py1luAZyBJHqqENdM++DwGRoUsuuon9t7WQdD9wHHxn9qC/p4UR1yC1wC54+2VtvKzom1u+x9+bMdi7WB9PkWMLP30jXm98m3KmtCoRByuRxarRZKpZLL4gkEAi4Knc1mnS18eHiIx48f4/r165ibm8N7772HjY0N1Ov1Pl2rYIqVAZeBgsGgO5QjEolgdHQUV65cQSAQwK9+9St8/vnnePz4scts5Psw0+/g4AA3btzAn/3Zn2F6ehpfffWVO0WbfM6MfRLngvxHZ5R2E3DmFJMUMKTsJNFHoP6gbAP65bHuC20PoHpBnWKfjLUZghoIUVBLwbNB41GygJFer7yj+9ZmQnKfU6/43ldJ7VAFADWbUG1aZur0ej3XK3BnZwfVarWv7xH9EgWlx8bGMDk5iZ2dHTQaDQe2837sL3iZiWA1WwLw5MeTkxPs7+87YA5AHz/S/2afUPZl4lywdE/BIqDff7R8QLK8pL6DD+S0doaCSfw+x68y02aJ8zuqo6zdRj4aZE+prOe7s4G6zVDV6/lsBcB4H19iDZ+vlUSq1xX4tNmNzGALh8MolUpYWlpCOp3G1NQUAoEANjc3XVnd5uYmhoaGnE5U/4cBKls6x+wmBrS2trZQKpXQ6521cdG5fVHb+/c61c4CFZxINjpeXl7Gs2fPsLGxgVgs1mcY6UQGAgHXCJRkHVfgfPSYE0TnmYqDWQGDwB8d6/PIAjjKVFoCxgVjyqIyy/PGoeRTPnY81ujn5+po0zFT5tENZJFnfQ89/tK3YfW5isaSNKMmnU6j1Wq5MgkqwZOTE1ffy7/t7+/jq6++wuTkpOt188033wDAuTKV583jt0GWT1jDHAyeloy89tprDjBaWlrC5uamS1cFzkDbRCLhohOh0Gkz2bGxMbz77rv4y7/8S9y4cQP7+/tOmW5ubuL+/ftYWVlxzjGzFIB+4cffAbj9Ql7QaLCS8pot1/EpfyVtJMh/dFwUoNIxWX6ye8gCXioPrONCnuN+sO+iEQ9erxE65W91rn0ZA9YJ53vzWkYc0um0UxYstczn84hEIiiVSkin0ygWixgdHUWz2ewr1yTwdHBw4DJBstmsc7K1zPCy7ItBFAqdnrxCgIbldsVi0R088NVXX+Hhw4eur4DyXDgcxvj4OPL5PKLRqIvQAed5RnUIcN6wtuA+cAYeayBAgU1rfClfch3UKVbnmWPQ5+iYtDxO95WmtvsMcL2vGl6+6N1FZCPYPvI5z88zPKyx+rz7kbrd0yges6YpN5vNpjvlSiNzExMTmJqaQjabxf7+/ktlvl02olGazWZx69YtZLNZ7O7uuigneVQBJn6PFAwGnV7XzFYtYWCgwspj8iaPNCf5jHXgPHiqgJbPblRnxRrwmtXKCK2PlwcF+6wMuMiu0ustqKROgb6/fn8QsKdzpfLD0qA9Y8tbeYhCp9NxkWtmhSvgzsBJqVTCp59+ip/85Cd4//33cffuXXzxxRfunoOy3y4L9Xpn2U4MVCwsLGB0dBQ7OzvY2NjA6upqX/NjylQAqNfrGB8fx1/8xV/gxo0bePToEe7evesCRZoFA5zvUUZAxsebtozZOqFAfwaRrrsNBPC+HDttJQu82rIjXTPbeoS85nOQ+Vza1apLmH2k70CH2OpSS3wWZRPf2YJhds/49KKdK8o6316xYC+D2slkEgcHB67XEA/8YYPtra0tPHjwAK+88orrcURZurS05MDMUCiEfD6Pvb0973t/m6QyVPugJZNJ5PN5pNNpl8Wi2W1cc/La7u4udnd3EY1GXSBUs8hrtRqq1aoDIbg3uB4vY3Mq+MmxkCxob201BYH0O6p39DvaU03lMO/n003EFhSYpT3G/cDPaGPpffkO6neR7zl2BYUtMcuYPgmzvPW91c4kj7daLayurqLT6eAHP/gBrly54k747XQ6SKVS7iTPXq/n+sgSqGy32316i3vk7t27mJ6edifi7e7uuu/o3h20P73v+EJX4bxQsEwXDocxOTmJkZER1Go1lEoltxkoNNUx4mKrUAwGg30CmgvKBdASOk6+9qBQ48g3fguc2IW3aKkPEeWY+V0V0hrx1tQ4kt2sPrKAkW+singGAgFXwkZmsCmNer1vTnQjqCNOxuZ72VKOQQZoOBx2ipObnYaORpnYOBaAq0m9fv063nrrLaysrLhSPXXe7PgvAymYoo4AcJrpUigUAAArKyt90TkAfeCrZqzE43Fks1m89957+LM/+zPcuHHDlVlsbm6iXC7jyZMn2NjYcIpVI37A+fIFoF/IqzCNxWJ9mYiqzC06r8ARyfKnjQjaI0M5Xl9vBO57Ba/0fciz+rmNogzaZ3YefI6zNUC1/pr38AHTqij1+xqd4Wcss6RCYITt6OjI8YNGShl1q1QqOD4+dkANj4KmM6llGJeVUqkURkdHEY1Gkc/nMTk5iWKx6DL8vvrqK3z00UdYWlryKudsNov5+XnMzs46+cc9AKDP0fbJaSsHrYPHteV+UCNB+V6VLr+jPEL5T55W/WYBXfKHRnaZ4WQjdXymvpO9h31PCxYT0Ff+0nEpwKX38Dn6L2Js+NZR382uicqYQCDgTpXkXuTx5zQC2+02tra2XCYQ+3UcHBwglUq5/l/fNQqFQpiensbNmzcdj9Ewpay2wArXg0EIBqe0DIPBMsv7Vl5dFISyegLwR6ZJlI9alubjKZ9RzufQnuTesgDPIBp0ndVb1tHhGHVvWRttUOSc78jm+Bq80aCNLfHyga/8n7zNTD610cLh09M2aQseHh7i0aNHmJqawquvvopXX30Vjx49coGtQUGjy0LBYNBlqTBYEY1Gnc3EHonaGFznFjhtLn/t2jV3BDgzkzVoTRmvWdkKYKnsJnhB+ck5pLOqwQG1AXxZQvyZRL7X++jf+LmV+7w/7WQ9MEZ1Iu/BsahvoLJWx6jy2dpIuqfomzHzGvDbn7yXLxBh/SzddzpPKofs+IGzFh3hcBi5XM6d6sjsHjZH3tvbw0cffYR0Oo2f//znmJqaQr1ex/LysuspSUB3EHB9WYhzFYlEXIuOeDzu2gSwFw/1Pf27QCCAZrOJra0tVCoVFAoF1Go1Z1MFg6eN+UulEqrVqttDtCH4bB9vvyjpvfg70G+PWb2iMtFnC/H75HnyiC2Tsz3aeE+f/rEZ4KozrRxVXlTfQPeQT05QVwNnAJh9Z4sr0J8A4NYtm826Vi/UGQShfvWrX2F7exudTseVGg8PDwM4BW01u6rZbGJ5eRlbW1uYmZlBLBZzlRoHBweIxWIYGhpyVQkvSi/dXFxJhVIqlcLt27cxNzfnslWoNHQR1LgB4KIPvJZKgeDNycmJO0JbF5v34z18TrBFTi+KuvJ9rCFlIyI6BgXC9N5E3HkSDxle51EdaN1U1rG5SOCdnJw1FWNPICKZuj5Kvk2tCotzRWOKEQzdeHYNfYqUipsovEaYqOw7ndOTdxKJBHZ3d7G0tIQ33ngDb7/9Nj7++GN3wp1ucKWXFXD/WqRorwp1Zn5Fo1FUKhU8e/YMu7u7fZk/5BHyPgV7JpPBjRs38LOf/QypVAq//vWv8bvf/Q6PHz9GtVp1KZA0FmwJG8fFdVNARQFEGjI0jtWwodC0II4Ff/UzdY74ufLHoDRba1gonym/2TXXd+L76JoMIisDfIpL50/JGkj6vy1joPxiqnavd9pgPhQK9ZVLJJNJF2GgY6DrCpyemMN+NzzhkI2Guc/UWLxsFAgE3MmXVIpjY2OYmppyBmur1cLTp0/x7Nkz1Ot1dyoRHYahoSEsLCzgxo0byOVy2N7eBnAmIxiIINgDoM9xVh6yIAvQX0LBfeP7Lr/nA2g4/zQaGHTh9dyL1FtaHsoTCnUMmtKsALfNeNJ51vFpEEFPlKnVauf4V+/n20t0cCxI4XPa7bjsnleZPkiH8PdgMOjKS5PJJFZWVlxvG57a89FHHyGRSOAnP/kJ3n33XTSbTezu7mJ4ePg7CTwFAgHEYjFcuXIFY2Nj2NrachFK2klatkI9S71Cec7UenWsmclnQXHNfLaBPgUtSSqjeY2On2tuDWXN3ggGg+6EHMpM7dnBe9BhpK1I29I6EyTLg4P2q+97gUAA7XbbtYhgjyWrX5WszlEZrpn4HDvnZVD/GBvVV+CQ70D7kk2Tc7mcA82ZTX737l3cvn0b77zzDj7//HPcv3/f7Smf3rtMxBMau93Tk7KoR5PJJDKZDBKJRN/1tFdPTk5PfPzggw9w9epV11iXGeWNRsMB+5otTGCGfM8G9GrXAeiz4ciz2j/J8jvBMz5DyQds8jNeq4FFfkfvTz1hx8WfdR9wv2hGloKien/yHUFAkgaW+Xzeg3LDZknqWKydaMFY1bdWt+g+U31oAXib1c9sLu4dOtYPHjzA1atXXY80OusMbijgcBlJQScFnpLJJCKRiAOOGJQkoE6eazab2N7extraGlqtlgtmA3CtOCqVSl/ZsoKXdiyWdL3Ud1c5bNec1/qCEOpLWH+ZpPe13/PtT/1fdZmCPbqngLPEGOV9XkPdQ35TW8aHZeia0A6kPLE2p+5Z7j32hA4Gg6jX6/jyyy8RCoUwNzfnSrDn5+fx13/914jFYvjHf/xHPHv2DOVyGQcHBy6jmGPW06H39vawurqKyclJXLlyBb1eD9988w3a7TYSiQRisZiTpS9Kv3dzcRKNC56wxYbHnEwKIQo7RurUGWYmDBeTJyJoeiAXgIJEjShrHHFculj6vyUyhmU0Nd7oNDHSoeUtPsOBypKZLGRQa2D7NpUFo3zz3e120Ww23ZGgukE1Mmzf0RLfzaLAZEI9JYf38UUo7fzTwTk4OHBzwDHS0aJRRoXGni6Tk5O4efOm68pPp8nSZXKwVWgODQ250rlCoYDh4WHs7Oxgb2/PNZJXoCIWi2F8fBzDw8NYXV1FJBLB1atX8c477+Dp06f4+7//ezx58sSBEhcpQR9Sb3mKz1UBbjOPBhnmGg3gGlpQUMEt5S1fvyWNKKtisLxqQVmfc83rbLTBdy/+z3lRJWoBWR/5FJr9u743U5Tp8EWjURweHqJUKrm1Pzw8xObmpgME1MEA0BfdpYHEk4wIblxm4Iklh8xs4klTuVwOhUIB+/v7+Pjjj/Gb3/zGlUmpzIzFYkin04jFYn08pEZoKBRyTWW1hxpwvnySpM6kNS5sVIs8C/T3K7PAU6/X63NeqNDJW/yZe0Kv1QCHjZSrca5GtQVolfR3Hnqwv79/bn0ukivqzNj72rkiWcNqkGyyZPUdAKdHisWi6xvYarVQrVZdXzAayCcnJ0gmk45XtJT/u0ShUAijo6NYXFxEJBLB/v6+05cEWRnRphzm56lUyjXIBc6cMN/cqr1GXc394zOYLwL0SdaIVwoEAq5vDwCX4cnTXmlA00608ozllgTaL9JV9rm6/337hHzabrdRrVb7joLXU2OtTBnkUPAaX2Y8r+Wpxfa6QfuF/9NO05IpBbSSySQajQZWVlawu7uLq1ev4q233sLS0pLLJvcF9C4TqYPKjJVwOIxKpeIi8Ursi3h0dIRXXnkF7777LgKBAB4/fuyc73K57EAF4MxPCQQCfWVitN+DwaA7zYtz1u2e9ZZVO8EH5FEv2T5RGoRQ/8PaOgpKWUBJ7w/09wbk/fmO/AxAn/7g7yqr7XgUzNT30iAl+VHBQgXQ+DxfkEb/554atK/Vx7P6Wt+dNihP/6Rs4d7hd8vlMpaXl3Ht2jXE43EUCgWXLaQ2yGUkzm8+n3c9nYrFojukpVqt4p/+6Z9w586dPl+aiRHMFGevRAY3aGPS16VM5j7UINqLjBHAuXUlb1k/wf5dfSsLHtkgucpQq6vUrrK+hvqYFsy039d9R7K+vFY80T+x7Uysb0LwxybSWB+O99O9EggE+nTV2toajo+PsbOzg/Hxcayvr6PVauH69ev4d//u3yEYDOLv/u7vsLe35zKfKc/I7xxHvV7HkydPMDc3h9dff92VcW9ubjqb4WX9jpcqtdOJ0sWJxWK4du0axsbG0Gq10Gq1HGDDCJqm+XFS4/G4OxrcGuAqdCwD0CHjSUPWMOd3SFwwn5BVg4GLpohmKpVym42lLM1msw8M03RnvVe3e5b9FA6HncFo6zX1PUkq4C0dHR15TzehMPFFsiwjq/PCd7FjGFQuyHvo9cofZOJsNuuMOAqyVquF3d1dZDIZBINB17Mmm82iVqvh8ePHmJ6exttvv43PPvsMq6urfRFeSy8i+P6QRFB0aGgI2WwWo6OjCIVCqFQq7lQJpkJHIhHkcjnMzMxgbGwMlUoF0WgUs7OzePvtt3F8fIz//t//O/b29hxvWcDPZ6CQ1LCxRgXQv1/osHBf+RS/IvKWfOCjOjoX1Vnzfxtd0M9UMVhloGNQWaFGj47L/qzgk++eKp/0uz4njn/nWBT8so4xZQmjFScnJ9ja2kK9XncOoAJgnc7pSRNMq00kEs6B07rwyxidCwaDyOVyyGazDkCYnp7G9evXcfXqVQQCAfziF7/AL37xC6ytrQE4XWc6Ep1OB4lEwp0SyeaxXDf2dAiHwy5FXo0QrgXnUmUggHNy0Dd+5RkFxCjzldfomJC3bCo3cJ4H1XFUZ0P5ySd39XefPNRoe6dzegqj1VMvQ4MCGgrkqmPtI2ukKChAR9CCAwRu9/f3+9aXJTBHR0dYXl7G06dPcfXqVbz55pvY399Hs9l0BtZ3gTgPkUgECwsLGB8fx87ODp49e4ZGo+EMbm0zAJxlJ6TT6b4AoDVwfcAI7Qegv7yO91V+0XtoCZ/eU/eW2or8TDP7mFnEZ/Pdua+tbcXfue6UexqEHARoDrIXaF8wU0MDehyzAn18R0u6t2kH6fM1q1+zU1T32PvaPRWNRvtKznRt+AzaXIlEwp2kOz8/jzfffBMfffQRnjx54vbcZc16UqCf+g04zdDY2dnB5uYmGo2GWyMG+46OjpDNZvHuu+8in8+7MiLgrBRFHVquEeeDzhTH0G630Wg0AKCvJx8z+C0A4rNfgP4j2Pk8/d9XYse/+wB/zWS1clj1j86n7lWCM7TzLZ/pfOg9WAHB8ho+h76CAqFAf29R/d2SBSAsqKR2mpVnStSZ5B/aCr4KmlAohGaziSdPnuDq1at49dVXMT4+7gJhemDPZSR9R/rTIyMjGBsbQzQaxdLSEr755ht3UnIodHaIEQC3FwhgU+/ygAItuyKpnia9qA1B3mPfTn6mZPWI2l5qJ9jxKJ/4AgDKyyovdb8CcNiF2vua+aZJMHYteE/7XeDMn1YgCTjzjfhM2yJCdTHpIpnNDKilpSVsb2+77LcvvvgCb7/9Nl599VW89957KJVKePbsmbONCHypjKPfsrGxgQcPHmBqasplBNKeVv/8Rf3xl8p48hm5gUAAIyMjWFxcRCAQcEcZc0KBfuOUk8votTahe96gVXBqSqpvbJbJlBGVKRS5VUMNODWOeByhbsJAIOAMIyuslWl0Q3DTa/8amwHFa+3vyqhHR0cu+sLxhEKnjagZ+VVn/SKwhs4Y14Wf9Xq9PkDPtw6DiNGmTqfj+nJsb2+j0Wg4UK/dbrvGZJyHZDKJbreL7e1t7OzsIJ/PY2ZmBmtra960yMtEKgiZmh0MBl02Srvdxu7uLvb39/v6cRWLRVy9ehXRaBSPHj1CqVRCLpfD3NwcDg8P8bvf/Q47Ozvu3tZItYJWSefJpxRshIsChLzOY4hVWJLXFAixTqZG9BTo5e+6J5S/LDBmlYbdU4ye6bUKbHG8jHpxjyvowPupQ6PzxtJTvrfOt2+ufbJHf+e96vW644FO57RRLBsEbmxsoNPpIJlMOqOSY+50OiiXy9jf38fc3JyrtyaoHYvFEIlEzkVMLgPFYjGkUikkEglEIhHMzs5icXERhUIBvV4PS0tL+PLLL7GystJXVkdKp9Ou1Ion1NC4jkaj6Ha7mJycRK/Xc/0Z1LgA+g3gQCDQ1+BfP1eyfALgnJ4gKYila27vocYz+cqeYqfOjM94siCsglYKkvI+6lypE28NOh8gNcgpVlB0kFzW97Dgso98RiPHHwicRvVisZg7/ZNlrCMjIwiFQlhdXcXXX3+NmZkZ14vgRY2hy0Cqm9PpNObm5hAOh7G0tOT6uzE7g4EbZm/0eqcnxsbj8XPOtE+W8mfuI18fMpXdCgAwc47AD/mAhjKzPLX3A5+lPE3D1mYiUA/49o/qEHV0WbZOm+J5pHZVt9t1wCbtF76/ZtpwzKpX7JhUP9tSCy2foCOspHrMt17AaVZPOp1GtVpFIHAa+O31zhoAcy0ODw+dLfLgwQO88cYbuHbtGl577TUsLy87OesDCS8DqZ0NwIE9e3t7WFpawsbGRh/IEY/H3fivXbuGmzdv4uTktKSYfKpONfW68hh7AVmAk3yi+8E6zuRrX/BCAxIkrrP+zRdU85Xw6f7Q+dLPBtl91mbylfT4iECv2kIaIFHAR/loUJBDP7N2n9p5+r463/xcdZDaS7onyR/dbtf1O+L4aZNtbm5icXER2WwWxWLRnR5JEPoyEm0Iym/aRwTId3d3XeCa80K9yB6IPIFb14Y6QIO2Pl1iydrGPqBV72c/5z24jmrf+QLZXD/1OZR31E/geNQuVB/Fgmuqo7hPLX+rrLRB30Ag4AIEBKl1TjWgQv2inynATN7WPWP1BN9Dx8SqqN3dXWxubuLJkyf4+OOPcf36dczOzuKtt95yfM7Dera2tlAul/tkYKPRwObmJnZ3d5FKpVy7DPLcy2YGvnSpnU4qcGqsszlsqVTC2tqaO7aRi8AIkgJR8XjcpVrT8LmIoTnpNHL0yF8uQjAYdGUnPMqem4xOtC7i8fGxa4TOki4yGIUxjRkbeSZp1hPHoGNTYvo6a3B7vZ5D0333tnPNOn5megGnxhabLqoSHSTIOZdKPkDR97kt6bB/5zvQiOOJJOzjRYNQm/YBcBkewWAQ5XIZd+/excjICGZmZvDNN99gb2+vz4Hxjf0yEI1A8lo2m3X9R+r1ujPEu92uS+llWuTq6ioymQxmZ2cxNDSEpaUl1w9K70+y66ykvGTnx2f4cC+oYU2DhPdXo0rBJRXi6lAMSn3lcy+aQx2nfb5+Zr9nlY86+CTdIwokqSzh9SpIfUrTGlN6rY7V9hgiOMvrOp3T431pDHU6HRweHrp9fXR05P62v7+Pzc1N3Lp1C7FYzF1DR5DlrZeJQqGQ2xfRaBSTk5NYXFx0zcF/9atf4Z//+Z/x9ddfu3IG4Kw58vDwMEZGRgCclVYzk5TvHYvFMDIygs3NzXMZIDoONSYItuq6DSo9sA4mr1fjepDjoPxrgR7+bGWoTw9YgPWisfF5lKvq1HOf2PJaJc6F7l29Tntz0LnWeQbOwGGSrocvWsi9p3uQxiV/1ufyPpSRLBFj9kwmk8Hk5CSePHmCdDp9KU8lUlKZTbtqdnYWR0dH2N7eduDM0dFR30l2fOfDw0PXQ43HPtssC6C/ZJM2ldpVlPvktXg8jpGREeTzeeekKH8ya0IPyeh2T483X1tbc9kmPl7l71xj3RMaeQ2Hw65M2RrctKM6nY6TiZSZg0Bi/azb7fbZVnRYgsHT06EoYzXyrPYeaRCwat/X8v4gZ8K333l6MoHW3d1dl/3GHoDs8Xl8fIxkMolCoYBWq4Xl5WVMTEzg6tWryGaz2N7e7tPTnMvLQqFQqK+/KLM0KpWKy3YikYd5uMAbb7yB0dFR1xMql8s5e5/ry/WkTuHaDWo7oPuI66+gkAUfra1l96HlYX2eArk+UMiCL5QdCo7pWPgdlbNKqpesjLV8TdnC91c7T6+9CIRQu86O4aLfFVSyAT7aUpqFCZwBEOwrSfnA/R6JRFCtVvHNN98gm83i9ddfxyuvvIJer+eAJ1bt+LJPvk0KBALOB6S/m0gk3Ol0e3t7qNfrfbYwA3rs7ZPL5c4BT9b2tXa5j6xut7JRxwycb3fgu/fQ0BDS6TR6vR6q1WofkG/5w7dPNDjNcShf853ssxW8pZ0I9Pe31f1k/W2Vp8FgsK/dgvpX6rOwR6M+3/o6PjtP/27tSJ0jBra3t7dx//59fP/738f169extbWF+/fvIxwOY2JiAul0Gk+fPsX29rY70ZYnHZbLZVy5cgWjo6PI5/PY3993Ov9l6KWAJwtMBIOnTcXn5+ddw0+mvhKRtM0P6TAwNVAnWUmdOS4e70WDQoVcNpt1p+rxWHoaFDSmeC0RuqGhIUxOTqJer2Nra8t1eOdzSRr1sEysG5LGus8xBs6UFVM9h4eH+46J5pyp0uH3OKfapJuCVFMDLePpWFS56cawAIb+TZnX1oRbUuVDYziVd7GS2QABAABJREFUSiGXy6FaraJer7trDg8PXa8XjoHZH+vr6y6LK5vNolwu923YQaDKt0Vce635TyQSGB8fx9DQELa3tx1/0Xkg729vb2N7exvJZBKTk5MIBAJYW1tzAJW+rwpWRdAvokHONMfMe7DWm+CArTUmqMu6cO4HPoNknW11FCxf+UgdhecBVBp9sI6yKhc+KxqNIpVKuXIdnQv93z7XAgEvAo6RfL8raKvGbih0enJPrVZDs9l0qdMsDwCARqOB9fV1VKtVTExMOIODxu/LKoA/BOXzeeRyOSQSCRSLRczPz2NmZgaZTAYPHjzAF198gUajgVgs5owkGiIEnqjws9ks8vk8er0ems0mMpkMpqamkEgksL6+jkql4k58YoNEoN94Voc7EDjNuNAyLMt7FlTyGVG+v9sSZetYWIdU70d5p/yj9/CBUz7DnnOo72uDB/ZeOi7dzwpgAXCG06Boto1EA+czQqwM0dIPayDaklde02w2UalUMDIygqOjI3z55ZeYnp7GH/3RH2FiYgKFQuHSHoetpO81PDyM6elppNNprK+vY3193YHVtDGYKcTysOHhYSwsLGBxcRG1Wg0bGxt9slcDa+qksscHKRgMOl0wNjbmDE2WYxDUoc6gEc2y4V6v506rfO2119zBIbSv2OfTGvwWJFYbSI16/q68S16n3mQAknanOl5qp/CetBEJ1NHhYUDPrs+L2h8+EMIS5Z11WnwgdrvdRqfTcb1cDg8P+yoM2OaCAGW9XnfjXVtbw9LSEjKZDObm5lAqlS6dI63E7HGWlDNbtlwuu7YFnCstOx0dHcW1a9dcvyHKrVQqhenpaaRSKezv77uemQogqp0/KACgdozKVuos5Q3rH1hSvrbgPsdl7Q21AzW72wY39D5Wzuo7WwCMn+k/Pod8xYC52mGDgCarS+yzfPpDHX77XtbGVP3CvarvRLvw8PAQQ0NDKBQKTmZSZsTjcWxubuLTTz9FLpfD7du3EQgEsLu7i1qtdmkPpwgGT8vsmPHEUrtoNIr19XVsbGz0Bfl5MAPXLpPJuGoTS9YfVL/fd721f30ym9dZu0n9Xt0Lh4eHaDQaLguRegyAK7fX+/vAej6H/1t+s3rIftfyny8LT9/ZAmDUp7RHOUb608xKpV7VZAMLNOm4B/lQPvlj36ter+OLL77A4uIipqamsLm5ieXlZdRqNczPz2NhYcElQBBDabVa2NnZQaPRQCKRcBUIzLJ7mZPtXupUO5/RODIygsnJSRweHrpsJ0s0Mgiu5PN5zM/PIx6Po1wuu9O5fA6pCn8tdeNiRqNRTE9PY3Z2FrlczqXWUjFRsdJYbjabru/D8PCw69Sez+exsbGBpaUltFqtvublHAfQX65B5JgGIA0ZAkGaMqeCv9frue/wPqxN96HqVHAHBweuNwJPg9N0bRowuj42muZbVxup8V3D91Znyjrj6lD3ej1UKhXXZJygjKYxc+NqvweuyRtvvIG1tTV8+umnfU6PdWAuA/jE9R0eHnbgTD6fx+joKAC48kE2BqcAbTQaaLVa6PV6KBaLSCaTLnLtAzGUtFEdr7W8BvSDIlYRqCInT9LxI4hhwSP+jUJTUyz1Wby3ZpRYngT8/UNehnzvpTXVTNWnQmA2kSoA5SEL9g7iMV/E3u6dQfuJQLw+h/OXTqfRarXcKSKpVKqvDOvg4AA7OzuoVqsYGxtz+4vNyqnEBu33b4MYCIjFYhgbG0M2m0UsFkO73cb29jZarVZfg101VCORCPL5vHOmmH3Ad5uamsLt27dxeHiI9fV1AKfzyz1EmeFz4iKRiDNkCIAr7yppdJW6h2P1GWK+56mzMIh0DD5Qi6SOgO4xa/iRKHdVJ/p404Kwg95Bn3uRnOJ3CXj4ACj7DB2zGruJRAKBQAAHBweoVCpotVrOEaIDGA6H0Wg0sLe350684/cuK1kZEwicltnNzs4iEolga2sL+/v7LkOcxB5xzCYvFotYWFhAOp3GxsaGA69pI3DNgPN6nI4LjcxCoYCbN29idnbWlfjyBM1ms+l0NfUdANRqNVQqFbevy+UyXnnlFXfozJMnT1CpVBwfaukE91ModHY6E51DbVPAvWczn1Tv0U5iSSD7vinvK9/SkSbooJmkHJsCqYC/5NUX1OPYlCxwys8GOXq8P3XtwcEB4vE4MpkMcrmc6xFIAO34+NiBe3QwO50OlpaWEA6HkclkMD4+jmQyiXK5/FJA2h+SmJVEJ412Yj6fx/T0NFZWVvqqK/geDHBTxwaDQSczeEgBMwMJmKoMs60CfPLd7lcFPynvrKNuv+MjzaTSMag9ZR1soN8Z5bzpuNWe8bVA8fGf3V+s/mB5r/LkReRz9n3P9wW1ffYdSZ9r5ZoPjOJnWh5E3uKc7e3t4fHjx+40sImJCSwvL3vL8C8DMSBMf4Cnb56cnGBjYwOlUqmPH5lt3+l03OFHQ0ND3oCvBSv5PLXhdf3s2vp8RQ0mKCkwq+sEoM9WtnzsA87VfrL+jv2b6hIdiz6H3+V7qJ+jc8LrqBsol6hbKZ/5LvwcQF8QR99DfV7fHrqIrI2luhY41dc8nIE2daVSQaVScaV0ukeY7MIegrZVxcvoj5cCnuzvkUgEU1NTLiuFHfE1SsSu+DQGhoeHsbi4iMXFRZTLZdfolIY/NwcXTZlGj/zr9Xru9LOxsTG0222sra25aAgb8KpjFgwG3ZGsRBY3NzcRDoexsLCA+fl5RCIRbG5uuklVpaZOSbfbdWNXJNMqHLsgdlMzysZNRQbQU2UI2vEoZaa7k2kpdKxiUzCCpE6AXutTNkqq6NQI07Hr+4VCITQaDTx+/Ng5kNqXg0osEAj0HVnMTvxHR0e4cuUKrl69isePH6PZbJ4DUS4L8bhdnqDE0gRGVlgbq6dFMIuj2+261Fga/UB/2r3+70vTVz5T/uKa+BxXNZR4H17r67mh3+MzVbBbY8gCYEB/pEAVl+UdC6jxO4OMORuRUDlCZ4XPYOqobXRphabeV589KNrji4LYbBBdG7tnNZqTyWT6shm0d0m320WlUsHOzg4WFhbcsdLRaBStVsudxnKZItksg8jn85idncXVq1cRDAbx2Wef4de//jWePXuGTqeDer3u5kH7xpDvA4GAa5TIfwsLC4jFYlhfX8fW1paT71T4Krd13dShIfhPx9tmSpF0XRXc1L8PAlP4Dlo+pPSixoTe01fuOgjAVb2lUUb7fB9/6z21PxQNeF/mk50/1eu+sVIn6Wea9UYjjRmBunaBwPmsNZ569eabb+KNN97A+vo6dnd3US6XX2yS/4DkMzbHxsZQKBRcNjbLIsh7nHcagATVHzx4AODUqOR885/t/wicAT5c12Qyibm5OSwuLrrG1Kurq64/IZ+n96LOaDQaDvTg6ZU8bCadTmN+ft5lmTATB+gvfwDOSo01E8s6wRcFKnidApIEtAjcEMyiPUI5S3uROt1Gwvm/b7+qLuQ4rE7Wz/Vn67RZfaT7iSAK7UDazrpfmHmt44lGo5iZmcHo6CjK5bIDDC8j6AScb0rd651WUMTjcZdxR3uU2U2RSARXrlzB2NiY47NgMIj9/X3s7Oy4wDDtel+GhA3E6t8V4FI7gzTITlHSv6uvY99bg1IakOE11h70BQ1sVoa1kezaW4eaY6DfYZvr20xJHftFwKuCdM8jG2DxBXUs0GDBBq6Ryi0dF+UEy5FKpRJmZmYwOTmJQqHgTvC6bMSgGbOdpqenkc1mUSqV+iqQODfMDAyFTg+h8AX8LiLlGbt+qus5t3aufXLG+snWBuCz+J7qh+q6Wz/AEj+3trrlf93P6nepH2HHb4Fg2jP0PzRoqS0PCJ5dBJYp2GXndRCpfNHvqCw7ODjAysoK4vE40uk0pqensbq6irW1NZc9y+vpTxBL0ROjNQv9RfXI793jqdc7rf2fmprC0NCQi4YFg2cpY9rEtdVq4eTkxB3RuLy87NIYtXmYHbwas3z5XC6HhYUFzM7OIhwOY2tryxk0ROO1eRxwZjATWQyHw0in0+64e00f63a7KJVKrleEz0DSGnGOzTIYyYci6984Rj0qneUzZEwtryPo5DNo7AZXx9lucGvM6dpaJlcjgM/WzWidIRpxLCPk9xi5IhjJXl8sJTo8PMSzZ8/w1Vdf4Z133sH8/DwymYyr1dcxXhZiZJQRVpYZZLNZbGxsYG9vD41Goy8qT8FDhc5944us6TpcxEeDgB4fWeNdDWT9X3lcr1GHm9fa5/nGateN4yCwYAWrTwno3xWc4O+q7BQ8oyNC8hkgPuNGjU0dH3nfjsm+pzVodZxas04DIBaLoVAoOGCehhPnqNVqYW1tDbVaDblcDiMjI3j27BmAM6D9ZdJe/7WJzXDHxsYwMjLi+tvt7u5iZ2en7x21fAI4iwydnJwgkUhgYWEBExMTyOVymJ+fR6FQwJMnT7C2ttYX5db9pevJn9WAodPJvakRYQXY+btGqgA/H6kMVcPO8tbvA6D7Itl6PwvM8x0Z/PGd7naRU+9zggc5axZgso64lRs61xynGpQK1PGemUwG6XTalWUyoESAo9Vq4dmzZ/j+97/vMmtotF5mUoBgenoaQ0NDrnxU5ZyCpJqpU6/XsbKygkQi4covuAc4j6qDaFfwkJepqSnMzc0hn8+j0Wjgq6++ckAdS7C1fxzlNkseFMBNJpNIpVLodrsol8vuMJFoNOpO5htkf3DNSJrpzue+CKlDwGADS7dYEki7UHtlWjltx6h72Npe3O92TQetNeeQQJgFp6ze4ftsb287vuh2T0sLOXcA3O+0r4eHh52MnZ+fR6vVwm9+8xsHxvj097dNtKe4jtlsFplMBs1m0zVGBs6CrL1ez50kDADVahXNZhNHR0fY2dlxjZTZdJk9N212kW/N1Mbg78BZD0dfkBc4Xz4WCoX6Mq1ULyjwrnzns3V9wRTlW+53n07ygW0k+8xer+fAZALY7IdLH4XZTzoOH6jFd1XAzwYWdZzW6edn3Cc+51vvYf2YQCDgsscJzFJXqZ27t7eH7e1tzMzMoFgsIp/POz68bKTNxJPJJEZGRtDr9bC8vOxadijIyvmjH2nlC3A+wwk44+NBwWO19X3fv8hf8/EKgHOAjLYA4bUE2/UZPoBW+d6uowUvbRafZiJZ+98CXRas5e/8p7LCBoftXPv8Od5TwT8duwWafbJM91Wvd9pYPxaLIZfLoV6vY39/H6VSqQ/4Pjo6QqlUwurqKl577TWk02lMTk66th+sLHnRAOoLW2KWKYLBIIrFouvfs7m56bJWqESJphJk4MQ/fvzYpWhT0du0a+DMqGb2RbFYxNzcHEZGRjA0NOSOVOVJHmysxgnQbBxmD2gHdipk4FRJMSOLY2C5hr6/z8nU7AmfMTUILCApgHNycuLKAFlewnGwpxOdJm5YG1XRDWgdcxXevjQ5FRyKcjIrJxAIuAi3psKTaOQC6HN0NPoIwJUTMa2e68NU0I2NDdy6dQvT09OYnJx0KYFan+zjy2+DmKXG43zHxsYwPj6OQCCAzc1NV/YAnDW+VocLOIu4WIUMXOyc+gxgPoeCySeofPdQUiHIn5mxlUqlXGkXo+/cb9ZosMaND9AkMKRAjPIFI/o6N9Ywt+CT8oe+P5WWjtUaKYMMPWv8q9K2+0/nzbdHfcAa92QweHr4gpYBpFIp1yOs0Wjgiy++QDgcxh//8R/j5s2bGB4exkcffeT2JWvjLwPxXSORCLLZLJLJpKsp39vbQ6vV6jNktF8GHehA4LSs+9atW5idnUUmk3FBjNXVVSwtLaFcLqNer59zXJXsWnD9aDxrht+ge2gm1aDMMnuPQUarldXkb72eGZI8wY3Xs2REy0f12crHlNU2uGN1Lf/mcxqs06LzYzMIbfTTOuvWOPUBEJxfOvNsUj08PIxkMolgMOhK3OlIkHgE8OzsLNLptGugOmh/XxYKhUIYHR3FlStX0Gg08PDhQzSbTSQSCQBwwbter9eX6s710dNttayM80/9zIzK0dFR3Lp1yx2R3Gw28fjxY+e0Ux5Rv2WzWdegmc4LAybMKAoGg65EmLqfTp/2VuFaM8NQwWCdD1+wwpKVr0C/bqTO7XQ67jACzSrnSYl2Dwx6pnW29HPfWCzp/mG2Akt/WSXAv9Hmoi6jLNjf30cgEEA2m3W9Fxn05XrxvcPhMEqlEu7cuYN8Po/x8XEsLCzg2bNnLuB52YggJvXh+Pg44vE49vb2nL1uHS4Csvv7+wDgMmDpfxwfH6NSqWBvb6+v9NJmMtj5sPKbe0lllJVr+l3yAwMctG8IBlp9QR0wKLBm7TzLt7QnrS3PLDcLlPE5lAv0xxhAZukm55KN3oEz2a8gDnv5qr6wZYJ2PtWf0XWwZXQadPetjQUEVNdRzqi+oH4h/zQaDWxsbODg4ADpdNplb15UIv9tEOUW5z8ejyMej6NarWJpaQn7+/te/5WBAfUBLejBazXAamlQ4MDaCuqDcD0HAVWWOL6TkxMHgHJf6P1899B3toDR8PAwQqGQC9wAZ+0ItArpRe7L/Un5TCLWoL3E+PxBPoaO0ecv2KxwEud7UBBB7+cDpJktmkqlXFUID+6hHVCv110iRT6fx8jICLLZLHZ3d11jeyb8PI9eOgTIFxweHna1++vr69je3nYTrdlOVPbWWGXkyTppnAj+zmOxZ2dncePGDbexmH5+fHzsjtamsib6S4eG4BZ7KvHeTBsjUzNtkY6kMpZF5y0pM/lQViXddHZzUqhqA3VeS0XM8VhjX+9t18xnvA0CrHg9DSIakXq0KMelZSckdYiY6UYAKplMYnh4GK1WC7VazRm8fCaBv93dXezu7mJychLT09O4d+8e2u12X+2tL2LzbRDnIhKJIJ1OY2pqCiMjI9je3sa9e/ewvr5+LiOOWRbsf6MlAbznRREpVRQ0glSR2PX2AccXkeVZKmWWu3KdmK1ykcFujQTyHqOzjJQfHR2h0WggGAy6Phua8cf7MtJGI4f7wQpTG/GySliNHDVUFKi6aA7t/FgQidf7Ihs0dnSOOMf8OZvNIhwOu7555AkagMvLy1hdXXVlnVQCBNQJdn7bFA6HceXKFbz99tsoFototVp4+PAhHj58iGq16taW86L9F2ikh8OnJzm98847mJqawvb2NkqlEvb29vD11187fUB5Q7L7QQFOPlPlKaPsvV6vLztW5XSv13N9/BRA9KVw+yJsmgGlfycPazYK9SR1FGUIS5cBOEDJOjD6jIODgz4e5d9s1NJnrJEsIECdwPJ6ygSb5USinNJ7cZ/QMfHpXWbuEITmutGR5M/8n/3DvvzySywuLmJhYQFzc3N49uyZSyO/rBQMBjE6Ooq5uTnXh4MZsZoVc3x87PoBKg/q3iFR1nB+6GCm02ksLi6iWCwiFAq5zFw6+sxEpx6nPaWlTipfA4GAA1B4ChxLBK2zwDW0JU8+fad8AZwP1A2aRxJ5KxgMuiapfDfOmy2tUyDY6hWOS/eMD3wC/FnK/A5LHAiI0gniGmqTWX0fZp5x39O+Jl/UajVXhseyCK7j1tYWlpeXXTZ5KpW6tMATfQhmCeVyOQCnJ7vWarW+4J1mFOzt7WF3dxeZTAatVssd7MI1L5fLODo6cvY2cLY2vkzui+bG2hb6GUn5m/24otGoA544fu5TK//4jryX1WUM0BAErtfr6HQ6iMfjLjhDXtK+OJzfYDB47rAA1RUMLCqoqfYs9zt5bW9v71z2mN0fWj7J96SuHTTHWpbos/V8c6+/U9dz3QnA89kE9Y+OjvDo0SOMj4/j3Xffxc2bN7G6uoq9vT2XpXYZiBU6mUwGV69exSuvvIJgMIg7d+7g/v37aLVaODw8RLvddiAVZYIF70jWFiH57GGlQfNvbV3VAT7yAY28vwYoaJOpP2SDvbyOve7U3qaeAk7L8sPhsEusUIBIq3vse/p4Wks5+QxmaFJ/+4AhH1n/3IKDqqN0nnzr5AOz+DnlJnAqE2KxmPPrCJBTb+7u7rqT7CYmJjA+Po6trS3Xz/lF6aUyntRBymQymJ+fd1EyRlVUSNDgVeOIoBUX2TpfvIZCAYA7fjsSiWBnZweHh4cuasVMml7vNB2sWq06g4iAFCNDnEg25ubfmYatRxTbCAPJGlB2kX0MagEBu+lsVE8zgEjRaLRvYQcBBz4BYB1wfpdCWJWcGlLBYNA1L7X31u/50FkFVOr1Otrttjt9hYKl0Whgf3/fbVgCh8FgEJVKBRsbG1hYWMC1a9dw584drKysOIfxsgh/4GyNCZak02l0u12srKzg8ePHzphX3uGpOSxBoMK3afoKLur6AGfZU1ScShox8xlHPofYR7y/RmXZY4VKrN1uOxCY76EgFYlKQCOyFP5cV83goKKh4wDA7V8qIi2BUhmjETSdv0HrR9K9YveqKk8auj5Q2c6rL1pkDSi9Rp1vyjh70kWv10O5XMbjx48xMTHhyhCokC9Tarjt+UKniXIaOFOYzO7RzIlkMokrV67gz//8z/HGG2+gVCphe3sbS0tLePLkCZ49e+b6fTCDwQIewPny50FRJQYfWEZEg4HfY6q69mRTcEp5zt5bAWJmiQBnWR/aR4PrXKlU3PzwegJjlBkcL8fHgMvw8DBKpZKLYPG7VhcoWWdB94RmwTIrT8FnnyHk21/WedKx2OdzTrvd076K4XAY4+PjaLVaWF1ddT0DuT9jsZjLcODpZtyX8XgctVrt3DtfBqJemJiYcH0rWXKrQZdOp4NardZXRkEDMhwO98kl8gPXhgBWPB7H3NwcxsfHcXh4iFqthl6v506va7VaqNfrztGiHCKwy0guS5W63dNytVwuh3w+D+B0PRlYikQiODw8dHLdlp2Tvy0QSvJF4vmunAOS5SN+JxgMugAH9w5BHj3AwcfHvMdFfx8UxNDf+X2e2BYIBFCr1dBqtVwPTw2OWhCXWVnMfuS7MKDHTFc6ApQlvV4PiUQCx8fHWF9fx+uvv475+XmMjo6iVCr12amXxb5ioDUej2N0dBTZbNZlzXH9gDN9THt1dXUVExMTWFhYwOrqKjY3N9Htdp3MbjabfXNqnXBfZoB1+khqA/M7GkhWGaa/M6hAm15BNH2+vbe1S6xNyLnQ7A36Qto7jQ4y/zFzndn7BKH4bLYwAfp1HQFN/k31Ed9LgVgNbPiAA5/dNmitrB7R/3XNdF15mnY+n3clmDwBd29vD5OTkxgaGsLW1hbu3buHmzdvolgsukNRVlZWLsXeAODA5XQ6jevXr2NxcRGrq6u4d++eO8GVtmM4HEYqlXL9QAH0rZO1nZX4u/oUPvKBgQry2ZI1XsPPLvJJGHhqt9su6GfHYnUHS+xtoAQ4BZso77Q5u9pYfK5iFLQDyfc6R/TjALg+19SNGjwZ5IfY97CfPU8u++xOJbUJAH8Vh+4/2qQa7Nrf38fu7i6Oj4/7DnnY2dl5KZ/j98p4Ak6PtZ6cnMTs7KxLZy2Xy47JA4Gz3k6MzKixoJkdvK8FrU5OTlAoFDA3N4fh4WFngPOUIzq8LEGhMieDKiNrnyRGEGl00IhmujIFEfuNkOHsmIHzR2bz7zY6Z+fPLpBFT6k0dIP5NpmlixwJ3+c+wa1RCJJ1IC7aPBx3Pp93PR3W1tbc5mczzE6ng2q1ikQi4Y70bLfbDmRjNgSb/K2vr7v5uGxRa86NGuPqlFLRa2YTIw/c7Jxz7gVF8W3kgPPHZ78syMBnaWmkks4vlQcFtTrcdCoYVdDoETMfaQCrsWFLfHzALAW1vht5pNvtOjCG88X7KG+y1JfGqgWg1HDT/av35HV2Dw6KWvgicBbQ0r9ZUjCRRqP2bOL3Dw4OXH+7QqGAsbExJJNJ53RcltTwo6MjPHz4ENFoFLdu3cLR0ZEr59FoPYEBZmtxrpLJJG7cuIE33ngDBwcHWFpawldffYX79+9jd3fXHSShBjuAvj2lPO4DQzhO4Kw/is6h5Q/tnzMo08lHajhYY8KWnVNOquHH/aL8wTHwPgwC0fihoWl53xcE8QGudvwcEwFFAgo04GyqugXUBxmavjmz46BcYvCKuoDZUMBZJH9vbw8rKyu4evUq5ufn8eTJE2xsbFxK4Entqvn5eXQ6HXz++ef49NNPcXh4iEwm4+yiRqOBer3uTsAlXzAQwJI3zQalHKWDPjo6isnJSRfkooxmJjKBp3q9jlDo9CQxnnTDRuOUZ+RF2mIEpViaR6eXJXfMhuL4qFtU52gAzM6R8s/z5tPyD+dAe4CqbLCgtdKg/cL78nfaf1bfWd1Wq9Wwv79/rsyVWXwqzxQUT6VSLqDHk3GZPU7QsFKpIBaLIZVK9QW72u021tfXUSqVUCwWceXKFTx9+rQve+2yONbMlGPpYbvdRiwWw+joKMbGxrCxseF4iGBqt9vF1tYWPv30UzcPCoqQx7R0EfA73Cq/LnLMgTOA5CK7mbKadqBWMKgto4AMibYHe6kwIMLva3BKeUkDAvy+ktqBGsDjc5gAwL1r9c+LZBxaXWv3seouG4TwgRGD9qf+XXWi3oNj5rupnadzpSCdAijPe/YfkhhYYSJFMBhEqVRyAX4NxrB5NIF3BQR9gTlLCpyqLQv0B1t9fiJ950DgrGRYbWSStYcsiNjtdl2Am/tIg7Q2iEFAlLaaktok1kYh/zBpBjizCck/6gORaK9RB7fbbdcagfiCxSUGyRLFGhTItuvkC8iQLsoI1vnVfQjAlfVrkIn6uVarYWlpCZubm7h27RomJycxOjqKpaWlc7LlInph4InKlApsdnYW2WwW6+vr+PLLL7GysuIanVFZMGKmpXZ0RMkoFGD6HDJKJpPBzMwM8vk8er2zMqxyueyOS2bKOXDadDSfzyOfz7smWUyp5fO1gTONZUbjmVIajUaRyWScIaZ14Ip6UiH6mNqnOKwhYcsOSKooqNAYZWB2lI3KXMTIg5SAfb5FjH0RPx/4pOAeFWG9XkcymcTs7KyLxO3t7bm0bvIEj4ROp9MO+GOU6/j4GK1WC4VCAQsLC7h79647peQyKQAVvCyfA+CMHm5cGgYsydOT7ez6qbBRXgHOgxk+PrJOgSU1kBUEUqdSMz/U2OFzGXWkoCWwo5EzCmo6/3Q44vE4crkcQqGQKxkhaZTL8pwaAhSsg1K0Abj9bp1uOxdqfFglC5xF+WiUqJLykVXinAuVRfa79nOOg/1IWHLH+Tw5OcHu7i7W1tZcP7RisYitrS1Xw34ZiA4RDQJG5H1GOnmNznMkEkEul8NPf/pTTE9P486dO/jbv/1bbGxsYH19vY9vLnKYOJd6jYKOXC816NWAVXlMkEMPTwDQF+FS0Jjkk8P2VFeV6xaw0Xe0/6u8CAaDzmjiSZu93lmGlM+5tPdT0usJIAN+4FX3mQ900s85Hxa8G6TDOCcEStjTgk4XS8EJkOg7sdn1ZXGqLfV6p1mdY2Nj7kSutbU19z4sH2y326jVai7bhbIgFothZGQEV65cQTgcxvb2dt/JZbzu+PgYyWTS2VWtVgvNZhORSASlUglLS0tOzmgmUzAYdA485bOCKQS66LDxQIF8Po9MJuMAJ2YXcd2YAaWOXa/Xc2CmOqXW4QHOl7VZsp/x+2pbaVCRfDjIAfY5aoOeoWT5WkFk33hVhigdHx8jk8n06U6Wcuh71ev1PnC21WohFAo5x7NUKmFqagq3b9/GnTt3sLGx8dLBq39tarVarqxe5anaO7RxyENDQ0NoNpvY3d11GUX8Hm0B6m/aDNY2t6Al/6aVCWqDWvmmdrT+z+uoT5ixzcAkwR39jt6Peom6nQFOux98Tn0sFkMmkwEAd9of72fnodc7O0Gcz7VBN86VjlH3hR6AQB/M2nSqVzgnPt9DdbfaZheBxDofdh7pTGtAVfWtBlCOjo6QzWadvX6ZiGuXSqWQSqVcBlej0ehbO8oF+ia0cWjfA2eZ2Jxfm4FnwXEfWYCE3+ceJW8BgzPUdP3VNiM/UI+1220Eg2eZ/Sq3yUucAz0Qg+P32Tt8BoPpBLjIZ9RxHCurMzgWArvMMmVmP30H2k60w/hsBbiVLC6i86VySPeKz+5Umab7mO9iv89qlVAo5HrlcY8cHR3h6dOn+PLLL10CUDqdRiqVwv7+/oXBIKWXbi7e6/WfZvfo0SOsrq6i0+kgl8shEAg4A4mnRtA5DIVOjwqfmJhwPZhYBqfIHjdLPp/HxMQEhoaGXENLZs+USiU3aRSg6sDqwmrzPwCuDr7ZbDokkoaRKhuCbEQ41QHR6ANPXOMG8DmVXFTrVPuiLPY7alwNYjhVONYRt4zF632bf5BQ0Y2hc6vGGO/NDVapVBCPx1EsFnHt2jXXJ4K8wLExw4xNM/W4493dXRSLRczMzCCTyTijmOO4DAAUFXU8HkehUEAul8Px8TE2Nzcdb2h9MlNkKeA5h3Q+VMHaGmMlG4HSNfAZ6UrkK8uvfE4kEkEmk3FGqzba59rRySBQQGdP+VUjJAD6Un65d/R0Gp9RYkmNc/0sEAg4Q5VZmIxo+5x6nT/dP6og9f4qo9SBt9lbdo9aMInvqmuh1/Nn3md4eBjpdNqd2sn7Eezj6aAjIyNIpVKuvOiyOBI0EChfKTs1bZ4BCQYdqBTHx8fx/e9/H8lkEv/0T/+Ef/iHf8Cnn37al71m580nK/m7lXVcb3VIgbPsJ5Vt+pxms+mAZJacAWdRL2bLcv21VE/3q46bB3MQ3FUwBug37FSH+AIC/C4dMj7bdz3/xvv5+Eb3ikYvKaeVh9VB45za/ax7nc/kd7W5rR1Dr9dDq9VymR+5XM6VidG41j3GY9SpE4vFIjY3N12W3GUiltklEgns7++j0Wi4PUG9yJ4dml0KnGXuqNwgYKS9oU5OThCLxZDNZgEAe3t7KJfLyGazaDQa5wIAXBNmnGiWgPaF0PIbXsteNsBpxJ3Zd5T3lAl2L/OeNNKVrH4BBvcfsfvHBwaRd312FfevL+uR88PvWOffRpt13/iAAfuOen91wNhOYm5uDrdu3UKj0cCDBw9chr5m1PBENy1xZlNh7hme3LW1tTUQlP62iLzPviMssd/d3UWpVOqTuYlEAuFw2GXRMqitB9FQXnMuFbji51wn1Q3AmT629roFRUnWQbS2ggJmfEcGW0g+W0EPiLhoLEq0sWl/RiIRFItFB+5S11mH1VdVYO+t+0VtVwvOUv7qXuN8qD1HGWWBLmvz6X3svlYZocC12gG0rRXsttnynBtmFl2WQB6JNiArRjqdDiqViuN/AqwnJ6cHVm1vb6NYLPYBDiob1b4FzvueQH8AVfcQSXW9gvoch/qmCoaQrMz0EQGQYDDoSgcZQCGRlyy/WhvEftbtdtFsNpHJZFAoFFAqlZx+UjBL39VmYbMknddQblNvptNpB2xR56rc8b23T9f45m+Q7tGx8J0HAe6UE8lksq9HGHVytVrFysoK9vb2XAk0m4tflGGl9HuV2uXzeSe4dnd3nTFDQ4Hlago68WWCwaDrg2PL0Dg5PB2PjlS1WsXGxkYf6kjQh5uMBidL7hjpU4cfOHOaT05O3N9KpZIrG0gmk4jFYi6biUKH/YrIzAQM2I+E7+pz9n3Aj25w/VwdAy40o4SaJqqODN/HLap5V/27PlPLp/Re1vm2jK7vaJ1r/kzA7smTJ67/wMzMDJaXl50BSyeTQiOXyyGXyyEYPG12WK1Wsb29jdu3b2Nqagqjo6PY2NgYKFS+LQoGT/upsOY1lUphdXXVHfEO9J8eNaiuXxWBCnYrJKyhqw4A4I/a8dl23mw0gdcT5CDZ7yh/0smmY6EKXPmdoJuCWQBc008tbbUAlG9PKX/yeTwpk33lfO9sQQYbWbCgLveDRgiZDaDvaMmOURsP8u8KZHMtFQjpdDrOwWYZBU+6Y4ZguVxGqVTC6OgoUqmUO+nksgBPoVAIk5OTeOWVVzA0NISPPvoIy8vLffxFAyUcDiOdTjvZm0wmkcvl8Pd///f45ptvnPywxqSC+tYAt/IKGGyYWON7EMhJIFbLhAmiUreQv9Vo4f8cE9+5UCiccxCsXFBAh+83aLyU7Zpmnk6nHcivvKeywoJ5ukd6vZ4DD3kQAHWTfkf1ic69/m9lVCAQcIYbS7D1+eqEUVboe/C5NEgJlnz66aeYmprCe++9h+vXr+PevXuXzoEATt+LJ3el02mUSiWnRxl5J19pFjZ5JZ/PI5fLodPpuEamejiD8gh5UKPY5XLZyRX2HtIGyCytIxjAXlu2z5KV4wBciT0zCdiEWDMPaFPRxmEgR9fUOtrAeb1EUttSDWrKYZK1gVT+K2hKAE/v59Pbup72ZwUufO+i76TP0LGx9KnRaGBmZgbvvPOOy46r1+tOl/Z6p1ljPBGRZR4EHtg3bGJiAleuXMGjR4+cg3FZiM4MgaVYLObeVaProVDIgfatVstllGsbAwUggP7SIZUxPn8E8JdU6jXWNlNAnWPU9eea2qAb+cwGxpT3uL6Wh3SMGlBhyTj3qPovBOs1M9zOgQ8oVblugyqcU7VHNdhswTU7dwr8+cBi+758Bu+na6J7h3xAmamtLvQd+QyWGNKOvGx6g34vbT6e9si/6emhlAdHR0cuIGHtH8tXqluV1F61QLrV9+Q1Lb+35JOFdnwWINFMPVbN0D4fdE+S7k9Sr9dzPEGfNJVKYWxszNnc6q/pfFGv6Sncdp7Ur1H/2udn6Hfte6jc4nf0b4N4lN/RtbVrZrEJHhhAH4+2Xq/XcwG9QqHg7ASCbi9CLw080UjO5/N9QE84HHYGBtPPyPgU+mzqFgwGXR8BbgJtLM3JUHCJhhcROOAsysfnM+NJDXw9flFRbS4ymY1gAA0qGl6cSD5DhRkVBcEwLuQg1M8n0NUoUhCHKbXcrDRAydScU5+jrvfXZ/PvasTz+kE9k8iQg9BwHT8NZR49yggTT7bhUcy2nIX8kkwmHbPztJV2u41KpYJoNIpCoXCu381lIPJaNpvF+Pg4ALisPApedQh9ytMniKyAVCcb6AeurKHL9bKgFHBewA2qBfZ9ZrMZ1JjwRZjVOQ4Ggy5jjanfzE6iYPcJzhcxhikc6/W6E8Dc0/Z99Z4248unsPQ99F2s4vJF4Dgnto8IiYYBP1eFwvuxOSx72ZGnFCSs1WoIh8PIZDKXDnhillsikXAldgQaWPMOnMrY0dFRTExM4Pj4GLlcDouLi9jZ2cE//uM/olKp9DkQui7AeflqAQ8LYvBvtuTFGjkkBWY1y6dWq/VF52lkUd+w94hmJ3LPBQIBl7Jcq9XcvNjoK8ej78N38oG8dMaY+UZQmA2Gm81mX78BnSvVQ/bvvEb1hg8gsoCvNZQsQEg9R53KXo02KML1om7JZDKoVCqoVquu56NGsovFIsbHx136+4tG5P7QFAgEkEwmnV1VqVT6UvLVYbVGI0sO2YNB+7EonwFwQTR1xpklw/syKk2eoTNMOc0scZtJqkCN/sxIPJ9v35tgiU/OkwfIH3b9rD0yCNzhOwJwJ1cS4KLtah0L3oPzovpX5YAP0KBN4LOreD9r7JN8YLq9N09qS6VSmJ6eRrPZRLlcdvzPuWs0Gsjlcn2nONXrdXdK140bNzA1NeUqEC4T8ESHLh6Pu3LtWq2G7e1tl1FAW5lZgaFQyAWQgfNZLiTLo6RBIKLPUdW/D8pWUODLEvefgkDa1kP3uX5H5fMggJN/04Any8VCoZArd1d/Sb/re3/9u+9dSfTLFCSzc+vbo4NsIUvW91AfyK6d2l12jLFYzIHsfCZ1J4Gber3eF2DSQM63TeQ7+skHBwfO/lU7V21dzTwDztutysv8zNoYVj5Z/4TfA9Dn+/B5LyJj1F4atAf0tEXaxT7ygWL8XXmH2eGsRqlWq06O62EynF/qI45TM7VtxZEGIQcBxpbsWvD7+h3r92swx+4tEu0C+hCDwCrNotZADNuwaPIIDwwZhCNYeingiUZCoVBAIpFw5WqKovMltQ8KjRsCC6ztJ/qqqXhU1jR8gLOaYb6gLjj/TgHCtMJOp+MAJU6IXXQKep64xtPH9DQQjonGWrfbdeAanQQuTr1ed+/sK5MgDXIoLCCkAtan2J63ga1RRhrEaNZws2O0TpoPKAkGg66UkZFKrnE0GsXExITL0iAzM3rOppl6vCUbZxLUSSQSfWUSg4TNH5KCwdMymfHxcWSzWezt7fWdtGUbWQJnClE3tHWqBznMyscaibE8dpFSHxTJUwPIV+6ikeRBBog67qroeOx6LpdDKpVyoKI6wD6jx0fqtHJc/F+PSlZAmGPT8fvmwMf//Iyp14OUGOdHsw41G4CkvMB95AP1eJ9KpeLSqPmcXq/nyu2YIZJMJh3we1mciFqths3NTdd4mCCBZkak02nMzs4in8/jyZMn6HQ6GBsbw+HhIb744ou+CLfOPX+2RoR1DEg+Y97SRQ4GdVk8Hkc4HHZgBwFz1UXUY3RubdR9eHjYgVLlchnDw8PI5XKunMYHhtkImpKNZhHIJb9wnDTagLNSPH5HHWKbCaiGOfeqBmYUOLJzZ+fX7h/KHAKo7JXg090aNNL35hjU8aE+OTg4QDwex8zMDLa2tlwJ9GWhYDCIkZERjI+PY2hoyPU+As7kLAN7lOV0WNPpNOLx+LljoHlfnoSmhjUdFTanJj8EAgEHXPOgDJbu8juce3UqfDYN2yMQAOU4NauJfEaeVPCHZdMAXFNZNahVj/GZvnFY54Xf4zzxXdR+vUgP+Rw7/q42Ka9VPWp1gNXD/FmdOa43QZhQKOROZ2NQj7KSgR1WALDtBXtuJRIJlw3MJvsTExMoFArY29u7VHuCTjUdnW739IRqntJJWcNMg+PjY6RSKaTTaQDny+M1gOrTjT7HmWRlFtdVx6r2iwLGvvvyfirT2BeGPlYoFEK9Xj8nBy4al5LaRJQNzOTI5/OIx+MolUp9/cEu8gE4fqtjrW+h13AN9VRe/Y51kH1ldr4AmnXuOR6rY/XvQP/JyrFYDDMzMzg+PsbW1pbz7Xq90ySJcrmMO3fuYHFxEVevXsXm5iaePn2Ku3fveufm2yDaIr3eaQkUD2WxoFC323XgADO9gLM2NMBggIbPsWtmQRDeg2vDhBGCfMBZEFUDAYPsbl9FlH6He6bbPTsdWPnSx5++eylRNjLbqVqtOjCPmAQzrTlP9j527jkWHbvVAzqfPv/E6h+rd+xzFVCyWISVGTo29SW1mozYCv/x4JbZ2VkUi0UUi0WUSqUXbmHw0hlP7NkTjUaxu7vrDBF9Ae2az78xatHtdlGtVh3zUchofSCzZmiI0Ljn/QmAaRMvBbmIXlIQ6cRbJul0Ou6Ulkgk4pqQ0hCh00AGJ/MFg0EHQLGULBAIoFQqnUslvYgGoZ9ESam49H2AM+CCBijJh/D7xqBglJ07O1d2Q1iioOHac16JCnMNWTeaTqdRrVZxcnLieqLQ0NYTb2gYt9ttTE9PY3JyEplMBnt7e14H89uioaEh5PN5dxTr9vY2dnZ2AJxtYPI5M3G0sbhGt6xA8a2dBQB1nXzCRA0gFT4KdtARYMksBSEFkXV0rYE1SLgTdOp0To8PLhQKGBoawv7+vuvHoAah0qD7WoXS6/WcswrAZSCS1AC9yLiyRqJ+rtkDjBIODw+7ufOtG59loxbqnPjAAxtB4liVP1T5dDod1yw0Fos5UOSyAE/kq2g0inK57AIIGh2isX10dIRyuYxEIoFut4uNjQ1UKpVzilnnTvUC0O+48e+qi6yh9SJkgS5+n89m+ZMCTcxC0aw6BcjoTDHzl40/WfOvYyf5gFNLNMqoNxnZDYXOGtLSCAX6jUqVKT7QjXuBQIaOT0vBB/Ge3kdBQ36fgBn1rGYa6xzz79QbNIzsPO/v72NjYwM3b97E+Pi4e/fLRslkEnNzcygUCmi1WiiXy30lctwzNNy5PswO1lJ8Guwq1wl8alYp7TSumR4rzSgynTFep9k0NltUiZ+12213iAsAB2JRD9KOOjo66gO8CBQmk0lEIhF3MIkP6FKZrqQ6SmWHBiPIC5QvFsi2ICdJDXWrA1TWWJ2swIe+g90z9n1oIwNwYAT34fDwMIrFotvvmg3PXqsM4rHp+NDQECqVCvb395FIJFAsFvHkyZNLtTdYNh+NRl0p3e7uLprNZp/8Z6YTcMpf5DXVwVYvkwYBQ7r+PlmstpQNGuq1ml1ieVdlLcevJbDc84PsEr2Hvo+9nvfj/tFTEKlntcRbeXOQvUR+1XK6QCDQd7KVgrlWxj/PL7LvpMFyrqcNKqqd6wMO6W8AQKPRcDaJghaaLaKgsILkl4nC4bAD9rn/7fxwPbkWBIFYZcT3V38B6JdBCmZZcEPnhNfxWvYwY4CNyRw+viXx3rqOWqpKOUqbnHqEthP/Pggc5TN0jdWuOTk5Qa1Ww/DwsCt952FmQH9/MUu0X3Q+rP5R0r6mh4eHff6W3lPvB6BPFyspoKjBFd/etYCXfRbHq7zPtWs2m1hdXcX29jbm5uYwMTGB1dVVd4rf8+ilmosHg0Fks1lMTk4ikUg4o0KJaLKi7YHAWTq4AiVcFBpKms6m3eFZthcKhfq62LM5Hhdb60h1ouyG4rM58dygNPhp8CiCTgOJpXiMqvK5L1LaYo0JH1P6kErgzNALBs9OjCBw4dtcPoVhx2eZTI0mnTMLcJDoMHa73XOK19Z9s/cEm1bTgOD32BuM5Vd0ahqNBnZ2dnD16lUHPq2srDhn4zIATwRjx8fH0e12sba25iL3Ov9cWz1pCMA5QWkNHZ8RpO/O/33KnN+z6LmCV1pyAZwZDBTsg8Av/u8DjSywyUj74eGha9jH69QB5pipFC4CtfS9KSCZfsu/8/Qnvf9F47bvwL0QDoddtJjZOpRF1gmyhibnUBWWdTT4N81UUOdRTxTUdwiFQi7jiTx3mUAnoD8KGg6fNnhmNoPqlaOjIywvLyMUCmFiYgKhUAjr6+vuva0BCvTvIXUK+Bngj3hdtPZ2XfQ6LTGik8d10jIX4Ow4cJ8MJWhydHSEYrGIkZERtNttd4qIjczbfeADpnWsBPzV+CewQBnEYAr1p48fLdjEd9JsF5UbvjHbdRjEm6qfCIzRwGJQiAEoZtDScaDRxnEzaBSLxVzghietqm1xGSgajeKtt97Cj3/8YwSDQfz2t7/F48eP3d/JJ9Vq1YFvJycniEajzjDmfHFN7PHntIOSySSy2Wyfs0mZyd8JUHEtLZDPv/kydG2mpfID+5GEw2Hs7++jUqn0Zbw3m80+Q9yORe0Ya0jzWUo20qtOpQYjeH+f3FSwwBdd1mcMcnRUZltnR99pkL7n/LCPqAKtXL94PI6xsTE3r/wuT3vkOAnyxeNxl/U3OjrqgmYX9dP6QxP7rDL4ODo6inQ6jZGREZTL5b73BODmwVeSqTJJ5ZnPIfX9rJ9RZ9Hmp4+j9pg6dySV6db+4HeZYcB315Pu7Liep+MVtCZRVrNShSdSKS8P8gtUr1IuUxfaEhurr3x2q47Rx2+D9jmvt07zRd/X79LuUKCJ88RDaZgZDJwdtMOTty8DDQ8PI5lMYmRkBPF4HBsbG3j48KED7BU0o/9FnZjJZM71CuSaKlEeXuRj+cB+KytZ4n9wcNAH6lmQkD/7st70WUxe0JO0bWY0x+3b40ocgwYQSFtbW65FBE+EJPjEXkcWZLJyX2U4x28DJQoMa5aXyinVLTp23x7jM+zesOPzzYvqcNpVCmQqzrK1tYXHjx9jamoKExMTSKfT2N3dHTjXSi+V8RQOnzaxTKfTaLfbKJfLTlGR4YhyatRFDUAtO6EAV1RNowjAGbNxw/PoWGvU2oWxJSmWCS0KSMCKEZ9YLIZut4u9vb2+xpiKetOIZ3aOdrK3iz6IgaxgJVOqQaJzQYWnoJ1Fhy3phtbx6PySfErHkgWYaOBY5JvXqvBj2mUqlXIn3BGtbjQaKBQK7n3Y6L3RaKBWqyGTyWBqagrxeByVSuW5QuUPRVQAmUwGpVIJW1tbLitGBaFG8JVUSJJU6PrAChWSPsBThdIg5WwNYO5VvT8/V5DHV8ZlDQjyLfche0zwNDBF5tXBGQTePs8Y1rRe4CwSlEwmXQoy9w9J51P3po3s8J0ZkWfzXvLpIHDMAmM61yQrS5RnIpEIhoeHXaRSo+ocG0Et7qVMJtNneFwGYpkXweRyuYx6ve7kJTM2Njc3US6XMTIy4gwVC6z45OdFcmDQ55aXuIZ23rh22WzW9R3SzAugH2QnyKH35M+8H9es2+0im826AzRYfqzXW7CG/DjonZXP9BrON2UQgQtbBuGLjPH9KBt4apmCVT5Z5AOa1PnSd7HvyDmibqXxyubmPA2NTZL5HQZkCJoHg0Gsr6+j0Wg4gI8R0stCzATNZDLo9Xp9QAHtKZbZqT3DZuxAvxzRIALnkY3vmUnO73CPsT8Ix8P7WGNcgRrSRQa3lvCpXRMIBJxTzRPLarWa4yl+j/3rmOXCMZCoiygPrc7TYJ7aqQrsBwJnWZe0ARWUtHYpeVd5yDpRfM4gGaD3Vl3DsdCx4X24XgxO6D0JRDH7jw4R15DBWe51rnelUkGr1cLIyAiKxSLi8bgr1bkMRHubYGmr1XJRdZUZ1J3MYLHfV0dX/QZrowIXl6PweVwXrg3tJHX2dV31fpZnLJEntc2HkgUCfLaj794qc+lDsCVGNBp12bksWbTj9I1Vy2J13+mcWfmh/MzrfTrXkgXq+JnOm4LENnNLx8cxaVWOBaEIRgBAtVrF4eGhO9joMlAsFkOxWMTi4iIKhQK++eYbPHz4ECcnJxgeHnY+k9qvIyMjmJqaAoC+Vii+9fXp8Yv8COVzGxykPKLsov7VjGn1Kbhv1WclX2WzWaTTaXS7XVfKTZlNOaf2GJ8PnOkKWwGl76U+QK/Xc2X66XTaPZdBc83CUhoE6CgRHFc9RSyB19t59O1pO/+cN9Vv+l46H749Zf+muIxNiGk2m862KhQKGB0dxebm5rl399ELA0+BwGlKbz6fRyaTQbfbdXXD3e5ZeZ2v9I0ps8BZarMKWD2CWo/WZWqkRlg5MdxguiksCq4KQidTJ5mbgQYtyxF4QghLj4LBoDN8NQLIzCsedawlZpqKrkbHIARZGcamqHLOVKDSEVUQSR1nfuZjev5NBbN16tTQ0/vwf2YxqWHmUyQ63wQdksmka25oEV+mjVar1T4HJJVKuZMOG43GuSyrb4sSiQSy2SyGhoZQr9ddE2Q6eCoUGNEFzpcCDHJ+7fopoAr4BRKVzUUgp66VGtR04HgN76WCWq+ngabPUgOfBqGmAtvxKOhkHQxby+/jZzqodKz1+Oh0Oo1AIOCifPocC6zp3KshOajU4qJx8bu83kahdM01c5LrS4B2aGgIW1tbfeAuszlZVsBm0XTaLpIzf2iKRCJIpVKIRqNOrgL9hqmWXQJwURUln8PgI3U0fDRI2fK7+gyuCfUSj8q1yh7oL1mze4H31muYeVOv1/ucbtVhNvCgQM8gkMzytI6Neps8pwCFlv7qXJH/e72eK7uiIehL974IiLXZASTrsFPX0WjV3moEJZh9yPflz8yc1l5RBNlqtVpfL8Zvmwi8ZDIZhMNh7OzsoFwuO2CJWWnMaFJbhnYV50ntAi1nYFlwu93G3t4eNjY2kMlkMDIygu3tbdccnxmdWlZsMxmULpLPweBprzNmOEWjUSSTSWcfDg0NYWRkxIElPHmNgA/tqlqt1mdX+YxlOyblPTqhGugA+gEGq+/UMRnEx6oDL+Ily9e8rzrJ9lrqTAKDNqpu70+ggPYqwSPaCOxZSvnCKD57tbbbbdew+7LoDOBUJiUSCczMzCCbzeLJkydYXl52th+dTq6hZjvRLubfLHDkAz8G2a1WV1AGqV/yPOBH/+6Tf2qHUwYz64bZboNAGo7dBx6oT2TtNwZ8eUAUfTP1KTjPFkCyNj8/Uz+C2XkvQnb89l3tMxRU8lW1cE3sHrX60Z5cR7k6NDTkToCt1+uo1+su0eKyEPdHKpXqy/LTLFGgP5uOgI+epuiTXz5QVn1Zn++hzyGfDQ8PIxaLuTI46mO1ZYkFcD+rb2J/7/V6ffqbJztrHybrp9qxWrCJPGErL8jjzA5jJRTneBBYNwjsVCJ/svRc95jKLpL1da2OU1JZpzazfn4RKd+wdFn3EXXxyckJdnd3USqVcO3aNUxOTmJ5efnCe7u5eqGr/n/EBoU04Nh7Q5W6z0BiZE6NWG4CTXnl5BwdHaFUKmF7exsAkM1mEQwGXSo4J4OGlwoTO4HWkOfnKpiYWcBT90ZGRpxDwB5OZPBut4t4PI7h4eE+A9kyAjeGfq7OLd/XKhIafYr68jsqOBTAI/kAAEtqvL0IAyoT6hzzd64HM9JUqfnGQQeba8i56vXOmqfqvBEI3NvbAwBMTk5iZGTkHKr9bRIzawBgd3fXHWkK+FOOuWmtUW8FJr+vc60OOddbyUYQLHCpew04r6C5xuq0EXTS363TrbytjiujkQRm9bmqeHQPKw/5ohI+ZUfHmf0vGL0mEMjouq/nAgWqZhMoaKblOuqc23fX8Q2SR3ad7fpRdtIoAtDXrJqGtMoFGsB00igrLgupA8laf51rlhLRMInH4+eyDnRdBilgvXaQYwr4exkMkiM0onhqVLPZ7LsHf+Y7aSqyPgM4OyWExNR9BmpshEvv7XsfHzh1Eeik76SOBUFblUd2b7KE3jbWHOSskey62bFZx5yBE/0u9avqPQBOplDmaRNi3efhcNg1Xp6cnMTo6Oil2R+BQMD12BkeHnaZaapnbZ8wlbUElTg/lBGdzukpdMyEjMfjyGazCAQC7tht9pUKBAJot9suuMZT60jWDuC4fUQ9wcwz9hFiM19mqvGwAALSvV7P/Z08QOdex2EDObrXrV2j+4J6yeonXkMdwCi8fq7P0LlQWaS2rE/+WF1w0b5h43DNrPQFRnReGNCjTOEeJSBLAL3T6biMOoJ7sVgMY2NjSKfTXhn0bVEkEnFlLsfHx1heXka5XAZwnv+o79WJ1oxt5RG1QRRwsGRtadXbdBJ9DijJB2b57B69hoBgJpNx78Tv6fh9QJcPULM+h9qSapuydxz/rnPnI+41fkf3FfmKusLKf6VBcw+cDwipHOQ7adanPsP6YCorVH8pSG/tQu6dw8NDjI2NYWFhAblc7lLoDo6VLUr4mdrD1IF2na2ut/cEcG7NBulsn0/LoBgBC/tM9e04l9Y25mfUZQw+sbUPg6v7+/suU1cDDPYdLAil+073sMo/HROTUViuaHWP7mXtQWk/5z5hMMbeR0ntSt86+PYTSd/JJzMGyRGrQ+kzqT+p4FitVsPW1hYikQjGx8eRz+e947H0wjuIThibA9dqNddISifPGt0USjSQeA0FNw1a4NTBYjpbq9XC1taWOylsZGTEIdBszkxnjJNDp9AH5li0Xk/NOT4+dr01Op2Oi5xQeDK9j6QnzgBnKesaQbalB+pAKDDD37nQ3LS+dEWNRGgE0IdwWgbV+wNwvRUUZbVKWb/Pz9QRAM5q0m1EgeRTkMwGSiQSfWWTNIpofBJYrFQquH//PnK5nDv558mTJ31AxrdJCq6wDwcBRJIKJAB9gl8VnRXqlj/0nhdFKgYZIhao1PFxb6qxrmPi2lEQ2r4wnAvlee0xw/ey76wRBp+xNOgddY44NycnJ05BECDWMi/e93nEPUhASw0zrqEKYQrsQQaWXduLjC3ej8+1GXL8rs4tn0sH87L0IgDOSlEZsNjZ2UGj0XBGP0sDFWj08RZwvhSCc22V6qDvWUdO55TP1vuqrH5RWcNn2TGpY8pIF/WllfdWb5AGGepW5l4EvlEOaFauPpNyRbMcqbOV11Vn+IA2Owca0dR303fVPe8zHDmubvc01Z7ZWwTNue9Z+j48PIxqtYrd3V3Mz8+j2+329aD8tikYDCKVSrngGrN7+De+qwVhg8FgX3NgPeZZwUKCDPl83p1kxTYJIyMjyGazyOfzKJfLzh7gdxiQOzk5ccC9GqRqVzGrhtlo7NUJwDkIwGkQETg7gZAlPgTbyI8W7NRMUM6NBQB8jj5/p8NAO9G3DrrXyE/PA1etnWT5m6TyRT/XKLvyvTZb14CDPkuv532o89Q2IrBPPUJdeHx87MokxsbGkMvlsLe3dyFo/4ekYPC0L2QikUC9XndlHcoHBJyZ+ceyQysjrV2qNg7QX8LM+yrZe2rg0AIwJJ8vovfj/xxXMplEPp93mZwk+kfWdrM6TJ+vfGYBBe4TlYEXgaZ2zlTukw85v7YM3Y7Ptwb2GRfpWepLPk+bg/tK8/X5nBe+OzO9kskkSqWSuzdP8ozFYtje3sZnn32G0dFRXLt2Daurq3j27NnA8f2hKBAIuJNGeXKlvrsG8Hiwk54MfxFZPhtkg1uQCEDfvlS/XO3pQWCJj2gzEMSiHmg0Gud4TeWgLzFBbUUFIfnOVhboXAQC5wNfumes/ODYg8Ggq9qi/6R9WClH6EdYW1/nm3JPQSB7nfX3dC0u8qV0jjSwwgoSbTPEf+yTWSqVcHx8jFwuh1wu51vGc/RSpXbJZBK5XM5lodBIIgjEyIu+RDB4lgIMnDlLZCJ+xkbT2WwWo6OjDmQqlUrIZrOYmppCo9HA7u5uX7Sm2+0iFothaGjIgUgkTdPjomrqmDYk47XNZhNra2vI5XLnTj1gyh3RXCo6Rl31vZV8URf+rwa8ElFVRe6V7Pd8YJM15HU8vKc1rtTp4IZIpVIoFos4Pj7Gzs6OK2mi8COqzXH55sCOb2hoyPXfYcNYGlw0sshPrFeen5/HjRs3MDk5iVQqhXq9/lJC7F+LNAuo2z3LAKRQ4fvoJrbrSoFJwQoMTgG3kQaSVfj2d+t8897cIxSKfIYFE3W81oiwhosKeQVK1FDRseh7q2MwSAnq+PR3LdvsdDouCyKVSnn781iyhqc66ZwDRixUaWikRceopAaY/ZuCHiQ6Xr6eKj6ggpmHLwKs/SGJJ+1RcY2PjyMajaJaraLbPS39Yk8TAC7bSUFMn0NggUeSAlgk3Us+h5DX6OcK9hIIpE6zhonvuxYcI+/wHzM8WUamzgyfaZ1V5Rt1WvTdrUxXcM0GIXzOk5IPPLNzp/tQr1cdRf2gkT4e5/6i/Eq5wl5FdDbVyaaBzVNq2XuPQS8bOPm2KRKJIJvNIpPJuLlkT0zKHAIHpG6368DcoaEhV6aq9pQCUL1ez/VTY/S5VquhWq26sgcCeDTeqdMYTOOJxORVgpI0onnsfSAQcFF4znUodNqDY3d3F51OB7lczvVLq1arfY2UuaaUfYMATeCs/MAG+YD+/atzoYAV5flFIIPdb4P2B8egdpvuNR0L/8Z5ZcYhcFa2SFt1kGNh9yVBVzqcBGiAM7uVwQiWnpZKJdy7d8/Z11NTU1heXvY2tP42KB6PY3p6GplMBisrK87es3YzwQMNWHCe1X5Sua08YIFvBWasDcN7s7UIM26op20Gh+oJDZBZcJLlts1m0x1gFAgEXMsAK7NUVlu+tME7y/NKvI4ZEr69wP8vclL5M4E/Agx2XEo6H3bv6th8xO9yrlh1MMjGUz9InXj6dwQB6Fdq4IvgAWXiZSDyJe1bLYGizGUJF9eDyQb2PsB5HTzIjyP55IMCQ5T9BLiBs4wk6jUfP1mA3e71VqvVB8T6wHzgDLDyjVVBJ/prvFYBJCsvfL425YT6PJYoV3hfa7dR56odZf/uA7YGrYN9Nsdpv/Mi37WgNT/n+h4cHKBUKqHVaiGZTLom7M+jFwaemMar6biMNPB31gvzpbrdrusLNTw87BoLW0CIi8IG06lUyjFsvV53mVWa0cSF0nS+YDCITCbjUGsCSkwd57MoxDWqwI3MvkUUTjz2njWp7E9Aw5C9VfgsTf3XRbLREJ9jzs+JSvuiYTaFzjpSSr7ouH5HNw/7bHGOqUCDwbOILOtcrRNGw4nfs+PzlR2q0KQgIfBEMLHZbGJzc9PxHu+Tz+eRzWaxvb19YQ+KPxSlUikXuWVaO+dTQcdA4LQpLnt3AGcCQYEXEgWrL7VXBecgg/gi3uA91EmmsqWCsoKO/GrTv5UsSKrXPs+QGGSY+YQfcD5Krc46x8ITMdlbi46WRut1LypZUI57T4EoKkqruO2+9im/FyH279CIA51rBQnpkLOJsM24+zaJ8zc8PIyRkREnM4H+7C0akHpaoHX8BkWZrAHl402fLKSBPGifEChhkGIQUMVnq3Hi24MKUjKzRHnRt2bqOAwyfnSu+U+/Z79jjTXrKOt9VXfZOfQZafp9gkzU1wRauDfVueN1uu/sM3kdj4ZnVBE4s0d0bOy3V6vVMDU1hWKxiNHRUTx9+vTcibzfBrFJbDKZRK1Wcyeiqt7g/tF1zeVyrtemvscgEJY6ngG6vb09JBIJzM/Pu1PuAoGAO0GMe5AnESWTSZycnKDRaLhMgXQ6jVgs5iLB5C/aBhrV5RrzdD6uVSKR6HN+KefogNOuYtmOfU/ypk8H6j4lKKFgqzrzvpKpQY4R/+aT77y3RrB1TijDT05OkMvlMDU1hcPDQ6ytrbksUH6P7231n91vKgfZT69arfZlnDGgx3kJh08PyXj8+DFmZmYwPz+P8fHxc6DVt0lck3A47Ppoko8TiQRqtRpCoRBSqZQXtAH6ZbyuseUNBWj4uS9wZLPG2KKDNrAtg+cY9J8vcBEMBp2fw5Oi6/W6AyQ5H7zWBwQN4l91fPl969hq5qt12O3+UlCN/MjvW/3Fv11EFtzSPTPoWhJ1RrPZdKB1IBDoO/1Ux0wgPhgMunItDYhyPvRnzXi/yJ7+Q5ICOrQFtbSLGae6LvbQCGu36hyxtzH9MaVBfoXqa5V/NsDFRA5bDeGzzwKBQF/bBdX3Oh4+n2vrA1svstc0i87ek7JV50vlhm8OeA8Lavt4TJNxVKbbubB/9+0Ffb7PlrSBGt94+F3yEU8G5zvE43HEYjEXlMrlcohEIqhUKq4U+nn0wsBTNBpFoVBAKpVyKBedB76sZnjws0wmg1wu1ycMeC1fHjgr0aFgoGO3v7+P3d1djI6OolgsOmFxcHDgjt8lEEKHjM/gyWI8Hc02PrfZThwPn80JZ+kdnXIVjIzW0UjykaKc9hotM7LXEexi9MuWbuncq2NiHY1Bm4PzrRkcJDVS2u02NjY2HHDIrDEanARbFIFWpedTPGpIq9NFQUkAKxwO4+bNmy7TiYIrm826ZsXfNrHEQJ0A8jFwtjYEQdnolddZp08Fmgolkgo0u7bPIx+PKt+ogtDoCRW8Opo+sIz3I1EekFQZ8B7kA2vYk6jEBjm//EyvAfqb6LfbbcfnWm6h/GrnWLPTGAVj5EiB80HzehHpeO1YdP/y3dPpNOLxOGq1GgKBgMtuYmSr3W5jc3MTV65cQS6Xw82bNy/F3gCA8fFxTE1NIRqN4smTJ64PF3D2zkdHRy5aTxlu+cFnOAz6WcFIEvUEf34e6KT7kPtXAS9eo/e3fGRBUe4x3dNq3PiAJX2e6gn9u45BjS77fr5ou143yKnhvUmqWy7iYd6LfdK63a7LGibooMan7ll9FgAHSgLA9va266VHQ7fVaqFSqaBQKCAcDuPo6AiFQgHXr19HsVhEpVLB+vq6O6nW945/aIrH4xgdHUWv18OjR49w//591Go1lwlDm0rlI3tRMuJIwIFkHWg6TkdHR8jlckilUiiXy1hZWcHw8LBLj+92uxgZGek7RY97hjqZ9h/HZEs1ydvU6VpWAJwB6QzcsXVCNpt1WSS8D09P9IFC+q5qQ6iO0CAB0J+VQbtKj03X71s7ht9XJ9lHuk+pK7gGur+09QSzO1OplFtv6h3b/+0inqVM4z5RMJABUfbYWltbQ6fTcTZUJBLB5OQkCoUCSqXSpShFZYkn5WOlUukD7xRA0L8B5+WHOqVAP6iiv1vg3a65ylUCYvQJWD4N9Af1yJ8WBFFArN1uOzBWTw1VWW7tw4tsDz5XgSHKfgsEWLI+kX0e59Q6sDr3OucvQryfBszU/tHnaHYWn6tADPe1r0ekBdm4/wg8WH2pvonvROpviyhDVJbwZ5ZAAWf6XnnP1/pCiXxIGWxBiRe1ddUn5O9M0uCYCCzRl+CaKpbA99X38dk2ahPp+1mQ1WfHqL6g7Le+tdqOJJsxy+9aIFuBOB0/MYRBfpl93vP8PS1l1PnUOQIGt5ywwQz6aGwLQZ+cPlQkEkE+n8fQ0BC2t7ddSf3z6IV3USwWw+joKEKhEJaWlnD37l2USqU+45GRHG7uoaEh5PN5l4oK9EeZfAYShV4ymUQymcT+/j6Wl5fdCU+8bmxszBmxzFBSB5VNW1kSyMmk88nxqqHACaUwCoVCLhWTaZmMqKphpH0ZBglaNc58n3ORqRzVAQHODHJ9RwtYkJTZ9XeLbiqz2zIoHRdPdVCAgllfTInvdrt9RwDrs/SdFeXlu/CeFDZq6IZCpw3MlpaWEA6HcePGDUxPTzvn4jI4DxyHIvMUpNqIbmhoqC9jDDgz1n3rqHSRsPdFIKzAVePAJ4jVyFb0nZGSQWOwgBCfq4Jb3035lvPm40/riNvnW/63AlWNRjXeNDtAjQjNltI9oEbKRWCADxQZ9Hc1EIDTdHGCWjq2Tqfjsgx5XGmr1UKz2UQoFHKnbFJOPnr0CG+++SYmJibw+PHjc2v1bRKdTIIODDRQbgeDp1kVjPZacMUX6bKGrTUYLopG8Z56nV0v6gH2e9AGmVwr7nO9t/3ZgkTUQ/w7/1mQbNCY9H3tHtF3uQhU03uqg8R5GRQt07H5DC7d89qInP2CAPRlIMbj8b5SMpUhOhfUIwwgce51jmgwU76Gw6enxHGvzc7OYmpqCplM5lLoDeAUeIrH404ezs/Po1arodlsOuCHejEQCLg+mMzEtlkBFpgkX/V6p30xOp0OMpkM4vE46vU6nj59itu3byOTyeDg4MCBv2yir5mdXEceFsCyFMozX/CK2aUEYPieLM3j3qLDSRnB5tovcoqU1UH6fAWP7c+cL/u73Wf6HHVgL5Ivg4IkKgeq1apbZwAuI4HzQHvC6m0LWFuHX8dK4l6MxWIus2ZxcRFXr17F3NycAwTZnJylmd8mDQ8PI5lMIhgMolKpuKCLgqFHR0fu4BkNWpD0Z9+eV/mpNoUvq5trrkEH2gjB4Fl2J+faBjbs8zXISnloS4mszaEOrc9ZHOQL+GS28o86zPY6lSO6v/Va3YMXAU4+W0ltT/qQtA90PXiwlVbBUAeo/8c5ZfDB+iS8nqXEmg0InB3wZMvQtU/ot01WDqXTadczl7qPJYQkArnWP1O5wpLCbrfbV70zyMYF/JlE/Ix6S5M1tCSQwDHBWdU1lt8UDFXZbveXvpMdm16jslL3h/ow/MynDywYa/eBymXqTsoHraAYBDopQE3SPWrnWvU+Ax+D9I8l3x5mwgED7fxcfSLFUZj9+SL0wsBTPB53wA+doZGRkT4kUIEcpvwyDVVL8Dhh1rmgE85sKpb2NZtNPH78GPPz80gmky4apwYnDSQ10NgHiHXHGm3yGRqcZE4wxzM8PIxMJuP6VPGkLJ7UpH2lLGBE8iGtgxShClygH3TS7/ki9ipkbYTeorC8nqV9ZFZuCs6Pjo0CmM6JCjjdvPoOqrQI5rFskQKIz2y32zg4OHBp1WTsdruN3d1dTE1NOYNEN8S3SQQnGVXmfmAvBb67NhS26Ll14qzhaEmvGaTofcpC+cJnuNqxqHOhpHxonV8dn42c+kApjSRRsCn/WQOf99YMOR+4BfhPqaBhosASeVbnQkuByLs+x+QiAMpHnGfyL/eTby2A89ES/l0dcN2Lmk59GYjz1Wq1UC6Xsby87BxSjpN7hTytMoTr7ZtnlYXKa7YMkePQ//l9q8z5PeUX4KyXGx0f1XWamWJ5QJ13HQv5Sp+pmSLqENhxq0wfJAPtO+k+Vd3COeAz9Vl27jSixmfYcfqeR2OT+/Hg4MAFlyj/ue4KNiq1Wi0nX23GDcdFhzQUCrljlj/77DPs7u7i5z//eR8gdhmI709A6Nq1a1hbW8OzZ8+cjFPAhuVydh2tM2H/p2Pc7XZRKpUAwM3R5uYmZmZmEI1G3VH10WgUQ0ND7oQ16mr2oonH464huK6D9iaizNRMEOCUFxgZLRQKSCQSODo6QqvVwv7+vuv7qAGQQcEVkgbLdB7UzrR2leoc3UuDnmX3j09fkqw8V71LstkELNEnuMrsAM2i0f+VbDaLlf+2xJDAH8eWTqcxPT2N0dHRvozsb5NYXhcOhx1PcM00G0JPmwXOO6A+4EeddtXpKu9Uftr55N/4bJafck61tFLvYXmFezoQOG39oaWVtJst0MXPrY14EahkM0XsdaoHdMwEhXR/Af06zUf0sTSz195XSfedBvGDwbMToEOhkOMHBuvs+7PcMRaLuX3DwLjub84VwV21OTQrRfXKZWpfkEqlnD9erVZxcnLi+mhqZj6AvvWz1QMkK6cp822VjbWdXgRgtPuAPKf2q2bRUJ/o3qTOV0ASOLON7Th8AC2fbe0utbWA8yWAvne3emUQ6MXv0T7Vk/nsGlxE6tvwOXyGXmPljc0WVhtaf7f+J9eAZXWqO1V/Hh8fu/7cDKK9CL0w8JRIJNyDUqkUbt++je3tbayvrzsDgwzC6CZP5dDB+oSvGtFkPo0uE4wKBAKYnJzsi5AxA6nVarlmtXRi2E+H0TlGkcjUBJIoYBQh5vscHh4ikUi49OVGo4Fms4l6vY5arXbO4PNtAp9BdBFgouii/m4NKOA8MOSbV16nG4v9VOj4+k46sMxuU1RbrVbfcbfa54nXWEXGlHIquWq12nc6oiorjQAxMkEGZ8PYy6AIlpeXsbCwgOnpady+fRtPnjzBwcGB2zOhUMj1tqjX665MUOvQraBTI8EKBQvGWEGqZAWmBSqB8yVFFthUfrbf16whCiuO34JcvIbjIg/YDAsFlchDmiHDa/T9+AwFuziHeh/OnY2k2HJCjlVBXH7fZ4BawEH3qd0DNKRYXsaIj9bT6/UEzvk5DUk1JoPBs1Ou+C6XAZQF4Hq5HB0dYWtryxlFzGggaEZDiRFP3zoMAvd8TqiP13kfX7aTyjZV4gxm6PXW+OG9LWCjZQN6f3037hVV7GpkqfFi34njskCb7h/9u16jfGnvaeWq/q4yguP3kZVLvFafnc/nHS+rfrH3tAAWT7tSB4RNrZPJJAKBAPL5PHK5HKLRKPL5vDulSE9S/baJWbDFYhHhcBjPnj3DxsYGGo1GX0BGo/B0LBQA1f0CnAft+L7kMR7iAgB7e3s4PDx0p94xc4Tf496kvcX+H8z2ZvCNjrcC4Dpu7utEIoFcLodCoYBkMol2u41arYZWq4VarYZ6ve7VUfZ9SKoTLrIzrV2ln3GfqbzXOdR7W4BPPwP6A4JabmLv5wN5qRMoH33vofdSMMt+7gvosUfrycmJ638GnAKA6XQaqVTq0pQTcY93u10X5PU5fApWqO3JDAPKe2sDkAY50z49Q7nMUiQejMHrKae1DYHlf6DfcaVda9tV2DGoXruoFNL3ngrmK7/wetWHFmzwzYX6JlafKMBj9YjvftY+UhtM7edKpeLkkGZQarCKz+M+4nwze5Rzy+8oKMV5YGIDy/XW1tawubmJt99+G7du3cKDBw8Gzv0fikZHRzE5OYnJyUm0Wi383//7f7G+vu72/OHhIZrNpivjVf9d7WSt6gHOQLrnZZpqNo0PQPHtHQXu+TttHeAMAKI+J68OAk5Ubqpsts8gaRCZ9/CB0apDfM+1z/GBmlbeaDWYjs23j3V/6nOeZ6/45sr6Jc/7vr4jsRzyjg2+aBDAlhw+j16qxxOjXaFQCOVyGfV63aXkckEJ4NhJ4KT7EDsLsPAlj4+PXfPNUCiEer2Ox48fu2aCrJHn/ZPJpEPciN7SYSSyrc8iuKHKnQwyNDSETCaDYrGITCaDSCSC/f19bG9v96VGc6MOApV0HrhovkiFMjTnxQpToD9CrQYo/zZIIVnhrvfzlbEA5yMUdhMfHR0hkUggmUy6xvIWgbaO4vHxMfb29lyfqNHRURweHqJcLrv3YpNI3qPdbqNUKjkFlM1mXZmRRlK/LapUKuh0OkilUq60lI1v6QQCcMeesvO/giXA4NIg/s/SBO41bngf+Kl8ZoXlIEHkQ785Lgt2qgAi/9j7W14eZKgPUlJ8pt0bgxSLff9BRg5/t0aRCmp9Z2uo+sj+3QJj9m/kczp1ekiC3pP30TRvrikzhJhNR2OYcm5QNOoPTSyboUN6eHjYBzQEAgHE43H3t0FyxwKi/Lv+ryA5SZ1uKwd9QJ/dj5qtowaOOgL8jO9ldYCV+woqK6iiz1UdQFLDhu+poJOVBxfxrY837d6wpRU+48L3mX2uvrcaagzk6PuQBoFRgUDA7Rka2nT4tASN75LNZjE3N+d6CY2MjPT1wfg2iSfn9no9bG5u4ssvv8TGxgYSiYSTB5wvAqA8EVZPsFQZSz7UPUJetXNPu6haraJcLruenHx2OBxGPp9HIpEAAOco6MlP8XjcgV/8HgN9vAflUzweRzqdRjabRSQSQbVaxe7urtOXAFybBOtUAn7AV20ge73P0aFM0TnScnk+h2Sd1UHOiwb0aKu0223vHraka9VsNl22P0/24/zyOdYpikajyOVy7nMGarnumpUTDoddBhvLPHmiYDabdeP/tkkPYuHphwwWq9PJQDUA1xuNwUwAfRmOg2wQ/s2Ck5TPWgkQDPYfka46i7rZBhPts1Q/2+xuX8BEx64+geUDnz9l58vaY+o3WN9EP1ObzOfo+wKigcBZo/xAIICRkZE+/5FzZB1ku8cBOD+BVQRqc6rs4zvSzmD5sNoBnU7HnbarJ+zqQQkE39nOhY54Mpk8tzZ/aGKGKA990NP5uCeUvzQDjwBbMBh0ySHsf0z9YMFna4tcBH765Bt51u6DQb6yykO7L60uGATO22cwqUU/t/td30vf1dqbvox6Yg0cky/AwbENkj3WT9K/2Z/t7xqg0ut9RHtJ9Sn3hu7zbrfrbBTuZc0mZOXS4eGh0+8vQi8MPDGDKRqNYnNzEw8ePHB9d5iSzZdRAc2sFBUMfEkr5BQAobFPMIkp9gQlDg4OUCwWXdf1YDCIYrGIbDbr6ry1/1IgEHDZUdqPIBA4PaKRDc4Y8SOgwmdXKhXs7++7Joa6yfnevg0A9G8QqyhspgfnQUsG1Jm3qKwaX4qyWqIwImP2ej0XreT3g8Fgn4Nroy3KoFxXziNBJzsu33xQKSSTSWSzWVSrVSf4AbjINWvmqTz4nEQigdHRUWSzWezs7Jxn1j8wcV9wTjhmOkaK5A86ItoCOcovVAQ0uv5f6t7zt9EsSw9/SCoxUxSprMrV1d3T0xPXs7Pr9cIwDKcFDAO2/0UD/mJ/2f1krCfs7OzEnulcqatKOTBHBYbfB+E5fHh0X1X1/LxTmgsIksg33HDuCc8Jl4Un/TP4HP+/32fe4AwZiWqAekYZAnbUoA8xfaVTvkMVgetAJb5LGWJovKFn8H+dc84pGbU30Lwyxd8hoRAF6HqgNnQdPUsEjuihpQIQ2vt8ho94ODs7w+HhIQ4PD7G2thZUIN9W46EUrVYLJycnUyeUAJOUH3qP/b4ICWIgXFsg9Dnv8TTvnSF8H5+hfytApYoGFRXldyoLQgqG56VRfdY9+Lq1VKNDjVRvKOj4/Tt1XFF8OwTGxmIxW7coZdTPP40R8npVTNWhEuon+6Iyh6BBt9u1gr+dTsdOUuT+Uhq8CftDa0oyIpbgkhrUwCSKI5VKTdVTmpubmyqYzWt943zG43GL2KasisVitv8KhQIGgwEajYYpm7Ozs8jn85ibm7NT96inUGegQ5DFnumkY8RjsVg0XhCPx6cinNrtNuLx+JRepZGwKit0LJ62rwMWtOSDp/HQfvfGUkiGhuQe14JAlPZb+xXqq+p3uVzO6CK0nn5snU7H6GNpaQn9ft/oaTwem4FAedhoNAyUOT8/RzabnSqW/bbb4eEhDg4O8ODBA9y+fRsff/wxBoOB1TXsdrsYjUaWEjQYDJDJZKxOGEFP5d06jwqehHhBlGHqU35oqzAah/qallPwkWncPx7AieJJ3n7SPurv0Hc6Vr7Tv1cd8N4ZEwLkeK/KAO5VAqH5fB4LCwtWf4j2FcHE4+Nj7Ozs4Pj42NaK+ozOrY6DmTAejGU/PYin9pXq4fyfzmD9Xg+V0b6wxIry5LfVCBSRv9Lh7R1SrNfG/cCTUEejkaVt8zTkEOAETAPvbLofvK6sLaRT65qozU+aDAFQfH5oT3pQJipa2+t7of0RxQc8wBTVVGfz+1n3qudDPutDv3sTG4eNmAbfT3nqM2que4aCYFwfAk3j8aR+moLGjEJ800CQN5YuBHNOT09xcnJiR9mn02lDvZS5MRxV0Wk13pRIfQqBMrRGo4FGo2HXMVyQqV0XFxdotVoWnsxIAHrheN/Z2ZkZ7Pl8HqVSCalUCrVaDXt7e1b0ll6g5eXlqSOE+/2+ee7JDJVpc1FCm4fNKxwhBV+NB50z3WzKYPm3Egvf5YE+7Yf2j++hMGTfNGKH15AI1TDg8ejn5+dTBp0CFFR2OC56pZPJJAqFAqrVKrrdrkVsEEElgJhIJNDtdlGr1XB6empeXxasfZut0Wjg008/xdzcnCnQWvtK6Z3r5wEYZdBsvFcjnVgHQOkv1EiXiUTCPM98fshLoIo8P/dCXa/lWICwwe8ZeYjZ67XcUyHgh8xUlRF9pvIU5SvKT8hjQrUgosAsD0ioAHrd2EOAgwc+uLfJP1kcOR6PT3nYdA21Xh2N71gshkwmg9XVVaytrRlYfhMUJAAmA/r9Pnq9no2TvJwpdzSsgYlCosq7F9gKgvCaqHQtr3B4YDwKxAImocQUuKQD7i/2V5vyPj7f0yP5ob5fr2ffQlFHSrMEati0VlMo+oq/vTNDn+/nUHmW51PKT7RfXv7onBKo0mgEBe1D66Cyz4MUvI7KNh03NAopJ7TvUbzzj9lYP5JedK4l9wbHwbGzjMBwOLRoczokqLzGYrGpSCnlqaHxe/7JaIR+v2+1PZmCxYiShYUFZLNZnJ+f27UEEDOZDEajkRlpmjKqNUS0uLamvLBvqlexecea1yuj6I104/Uqv//8bz7zutQmBSIATNXwYNSEOvR8VB9lk86PppZ7vZLjUz2QhjFLGSwvL6Pb7aLb7do4u90uOp3OVDqkpm9ms1lz3t4Ehx73AqPbNa1UvfWM1iJ/Zm1GYNop5mV0FMgT0qtCxrcCLer0ZT98BAqv1fsprzg2/+4QSOT5r9eDaAiysV+6z0O8T8fD9/G5XpZ53ZGymWldt2/fxvr6utE3078ODg4wOztrZSnK5TIeP35s4BNtNJUlHlgORbB5PUzXgu+m84G2KSP/VDdWo53vYbZPlKx/G426H+mKfSMvYgo3I4r7/T46nQ5WVlYsKoW6NR2dtJ9fpxv55ulDacyvT5TdqS20x/y1qjMA0+UOvI7ORj1O6V+vDentvl/ehtfPQnShdniIRtnUzlf7PLRXX6e3aD0s0joBetUHuY9D/eL7VSbz2Qz+Ib3Q3tX04te1NwaeGMHByBNuViJfuvBkfAzP5gkpLEjpPXNe6dW/lVnSi8Rr6Ckj6ksQg0rRaDQy8IjRKJ1Ox5QlKrncpIx04hgpuJlSyIULbRivEIQ2qxKWZ+pKZH4xQwJBAR5v3PB6b0CHUGR+znlVguczPCPg9TQomRMdtXG5qfR/HTM9pVo4lrU6tH9nZ2fodDoYjUZIp9PmnXvbjWtAJYh0Qq+6zr8qv7wXwNR8sKkSQwGhoGfIwGYjbXtjnC2kOADTx6964eHvUwUkxEw9Y9VGJuWNSW8YqcLNvz1DDvEMbziQbhVA9QpUqK+8x+9vvSb0Xt+i9iINrMFgYOA3gfPT01NLUaHiMBgMpjzS5AWMVKBhSCD4JjTOPyMONIdfGyMbVUlX5dMbkyEFWX9HAQxvojh6HghMKy7KM9lC71c6VIXL7yN+rs0bqt4bGQJ5/N7RPnD+QnPvebTy8tA+JwgxHo+nFBrfJx07ZRqL6TKdmrU0lLeRV6qB6X+z/h/nk7KcjRGEjUYDJycnuH37Nubn52+EzGBLJpPI5XJTIeoafazAE6+nEa4nRFK/8fxJ1wuY3iuUL3T2xONxW0vKqU6ng2q1imw2O3V0cqPRMBCDUeYsVN5oNBCPx62W0+LiItLptK0rC4gTdKLucJ1epX32eoanfTa/3xTgoVwFrvIDNdL9O7SFjCbPp3x0s9elKJdoEPPeRCIxFangx6Ty2oO+g8HlgTiFQgEnJydmWNJxQYce05+1PirrPN0Ehx4bIzIIRJEOvNHHsTOKGJiO8gOu6sAhugm1kBHLpvNOI191L2AaZPLgqe7XEIDPfkb1i/dEgWl8tge3lF/4iF3NWvHPUYOUoD5puFwuY319HalUCvV63fgJHf/9ft9A9XfeeQelUsn4PA+Vog2jOpq3H3ROfLSI9lPXidkGtBWpJ6kxHovFzPnHunePHj3C2tqa2YV6MvLbanroA9Pl5ubmbB8Mh0OLQInFYhY52el0zGFP0I1yQPcVm+dbXGeuD20SZkQBsDlVu1XfoS3KXlBdR4EQxQOA6Ygpr+/x2hDo6/Uk77jw7XX6mgdwvMPPt5AdwKZjVT1U514d6FGNtjQDgGKxmO1HPw59vwf4CPaOx5OTyPXe8Xhy6iQxn9e1r3Wq3dLSktV4AjA1CUSHyVw5WDLjWCxm+bQ80QiY1FQKTQBwVfHgD4tvUok4Pz9HvV5HOp3G6uqqba5Go4FarYbhcIhkMom5uTmrGdRqtTA/P49isYj79++jWCxidnYWp6en6Ha7Fm1FBTeq2CNw1QPlBYcKP+AqSKRNr1UGrJEeIUNfDRWNproOUfafhxQ/AndMVWT+POeTxUC94RTVeC2BxIWFBZRKJfN8krmzJgEAM1JI/AQKb4KClMvlsLa2ZiCnR9GVcTBiTpVsDQfXuYnFYmakcV4UdGJETKFQQCwWmzrBUekxSpkBrtbH4GekO/3cKwBsIQboGasajSE6YT+iaNPvLR/Kqsww1D8VWDr32hcFtvz9yq886KWFGdXT4BVM/2xdF3rfeKR5IpGwGgTApfLNCAfuRUZ5auj4aDQyBS90YMDbaKVSCefn53j27BlarRaA6ehVghA8yVQ/B67SnRrXqnyyURiGjIsoENUDXNpCyhcwKTrOfqiRyXfqGDzde3mgffTAtG9RMoj3UAZo+kLUvSEZFPV88ibeQyNP0+TYB9372WzWlGIaNtwrjJxhdIafnxBors4V/tChtLi4aDpBt9u1E3YTiQR2dnZwdHT0WqXtj9VisZhF/2iUH3mH8nLKvdnZ2akIGt3/BBSAq847vg+Y3i8KytAYUU9pr9fDyckJCoWCRT+trq6iXq+jXq+bbsealzyQZXNzE3fu3EEqlbJaTo1GYyplxRvwofnR/pN2dHwq27xhEmWUqAzwupgaIcrDQxHqnm94HqF99IY8r9N9ynQxYMLzeY03jvxaaoQYUyN58MtweFmmoN/vW3F4Aps8bbTX61mq3k0AZzUqRfW/0Prz81D0XKi9Cdj0ukYgjPIbmBid1PFIB0zD431eR2SffJ+9TqTX6/+eJkLj1fkCpuUU9xX3hUbk+owUvpcgDR1lxWIRW1tbSKVS2Nvbw8uXL9Hr9RCLxayGJffU8fEx0uk0Hjx4gK2tLXu32lpMqSQPAiayXR0QHIu3iVQH5bi4xwg6Mc2OUeVcS4771q1bWF5eRr/fR6VSQafTuRHAE53wlHdcCwCWOTI7O2uRWhcXF+h0Ojg6OjLHpTp3aIeHeJzSx2g0MmfDaDSaigrTmsd6rwcv/Tp5nUt5vPJfz8vZQrI8FotNpaNf10J2B+fBv1//9vaUB7W16R73AFzIecFrPZil6aBvQoe0E8mPiNfoeFXGKi3Mz88jFouh0Wig2WyaXEmlUiaj0uk01tfXEY/Hsb29jYODg9f2CfgawBONAV9fhhMCTKNfLEBF4UYPXjweN4/L+fm5LUTIEwFM1wpSAuWEUmizL/V6HTs7O5idncXy8jI2NjbQ6/VwdHRkQAYBAk7cxsYG1tfXAQDHx8eo1WpotVoW7eQL/vLdXiFRBe46ZQW4uul4j4YWctwkHFWGeK8Spr5Ho8p8BFSoqXGnHkIyI9YrYroh60rwRwGTEHrMdeZc0qA+Pz83ULPX66HdblvqzdnZmXmtCbxxHojwvynY9c/ZlJlwfCEFlMoRkWule15LRJnPZESZZxac50wmg3K5bEeH09OhgG4UQ6TRxyg/Gi2MPvDG43WMNRTarXvAN29M8D5Vfvx7/5CmTFW9CyEQLGp/eMHJ9aHhTKCI6x+Px62AfKPRMM8yx8136b4nTRM4isfjtkfa7bZ5D8fj8dSR6gpQqjdCo1DfdqPjgfVfKDhVidQIhBD4E6VYR40xCjwCwpFCIUAwCpgM9cUDWiFg1AND+i7vsdU++r3FpmkMfmzsu9a1UJnqFcComi4h0I10x2gMBapDQHcqlcLm5iYA4OjoCK1WaypFgAoNjUzdlx4U4Jg8IMH9o5E1fEY6nUYqlbI0+6WlJezv79+I/aGRsYx+UQBF/yfwREOC8oH8WtONeK/yGWDCd6mjAZMTn/Q6vTcev0yn397exng8xjvvvIOVlRVcXFzgxYsXaDQaFgFHPrSwsIByuYx4PI69vT1sb2+j2WxaRDAjGzwAFAKM/T7zBjSbgnb8Xnm+N4Kot4SMV/2f/VHDLCQTXte8XjUeXzpoKa/9UfAE5qJ0PN+47+gI5hrQCaFR06QRGt7j8djSPnO5nBmxb7Ox2Dn7ohGQCtZxb9DQ9Gvom/LFPyQqOEoX8g4IBUcUrFc65bh4r3fY+efqntC9ct14vcyI+g643hmj11L/LpVKyOVyyOfzdmBApVIxcH9mZmYKSCKPisViVm+PegGdqLQzCWjRIUF+F4vFTF7whNKQjujnkL81WIK8StMz2ZLJJIbDIZ4/f45Wq4UHDx5gdXUVd+/evfKuP3ZjcXEW3C8UCpifn8dwODRQYmZmUgiakYD1eh1LS0tTzpk3BWF1n1FWE/BKJBJWUzkKUFL5oi1KjwKio8H1+uvAVv+/1/lDdkqIbsh7FYDT5/px+nu9w1t1yJAOp31TXYq8Wz9j35mCryU2KA96vZ45q/kcnUPtE9eAwBNPnOWep8ziKZPFYhGVSgW//e1v8dlnnwXXwrc3Bp40jJSTo7m2nCgqNalUCrFYzDY3r1ckTVvIu0klQwtk+QlShYpGG5XKRCKBUqmEu3fvYmZmBrVazZRTbkim2XW7Xezv72N/f98MPDJMRRqB61M1vOHsx+TH68etRol64ICrG1Tv9Zsp5DmJehbvUeNCBSGFHuvM8BqGZ6vh4j1/+j5eS8JlTjfByGw2i2QyaV5XphqpEUcDKplMWsTV225kHprTr03nlkYCazbRM8HrlJEQ3FPhoIyWHo3BYGAeZPWqRbWZmRmUSiVsbW1hc3PTAA4yJIb493o9i/xjqiPfr4V9veKtypePhOB7dN7YlN6VhpVps4XojPSq+zOklCgo64VAqIX2EteY80KPD6OMyFvoweP4fNojn6XzxbHTwKxUKnb0dTweNxCYRgmFAQCrecfjp29CW1paAgDU63U7yU9PA/VgfojW2aJ4r+d/+jmfeR2gFXW/Gg/AVcU9pMiE9oMHPzk+7QMbwRj/nTd4KOPUoFEezv3s94k6Nfi57ocopUojNijr1Zj268ZxU9FnqoLW/WFa9ezsrO2fqBQP/k2jvN1uT42He0frgsXjl170w8NDrKysGH+7CaATAAONGbmrNOrBYxoSpA8aolwz7ncC4R64YBuNRlYjkcAVgCtKtRqeBBkJGN2/fx/lchnJZNIKWFOxZd/Oz8/x/Plz7O3tWUFyAFciMVXH8LyRc+JTKrwupABRiBZ1/3k5o/OifQrpVSo73tTpFRoT7+ezdK3ovNB58kC1NjqFh8Oh6d1c41KphE6nY+vHSHI9NZH7kHv1phQXV6cEI4bIyxkNTNCWwAXXTZvnWbRPFPQNyf4QCKTfKcCvYChBPa9XqN7D8bE/vE/1F6+P62fsg+pa/N7LAX6ussvvCeoboXEqiEt9Y35+Hul02lJw9XTKVquFRCJh9YRarRb29/cNeCaN8T4AljLGTAZGUI1GIwsYGI1GmJ+fR7lcxuzsLA4ODqYcLJxTDYQIzTsd2ARsCJjE43GTK5yLV69eodFo4N69e7hz547p7W+7nZ2d2QEO9+/ft9MoCTiz8D71UKbUtdttNJtNc9CQDpTXA2HHXSwWM92TpRy452jXcC2oy/G5IfvePz8kk0NAD5sHc7xNoHsz9PwonS4UXco+cp9oNCD3LjCJZvTAku5L8irab5lMBnt7e1OlKEKAOOcwVOKBWEcsFsP29rbtM52L8/Nzy5Zg1pLqlPxfIzmpTykGwmcpveTzeSwvL+Orr766uriB9rWky9zcnCk+yhwpkNlYAJNHFpMAVJGioUbkNLTIjN7IZrOIxWLGpMjYufgqBABY2PDZ2Rnu3r1r4BO9rjScKYgbjQaq1aoVrlZFhgTDReEi+ua9DyR2b0SrUhcyWELPDrUoI1k3G5sqS1FNFTIdE78jikpFgIZiqF9+HB50oieByla/37fNm8lkzGjW02EAWHFChv3fFOAJgAlIgrHKpFT5JZhJpd8r4RQWCraqgPAGLb0Y7XbbPteoAzYCYwsLC1haWsI777yD9fV1XFxc4OjoaKouRzKZtGO1Y7HLVBCeUNTtdq3PWvNGoyCjBIjSEz/zihSAqagx3X/8X5m7MnydF29Aq0D1ngg1SEL7SueSz9QxDIdDS+mZm5szAJzP/DpF9/hsMvl+vz/Fl+jZYI4+lQE92eTs7OxKbZC32fL5PAaDAVqtlu0P1qphypCvzQFcBdqjjAOlE+4TXX8P2HxdxTEE9kSBleyDvjvqfQp6qbxRg1j5OOldFQ9VtrSfVA4Ykaf945j8nPnxhJQS35TH+evYL9bz8ZE6nE/KAZU/oTnjWAm2+RNUdM2ZQs/n0MvLAvd+rG+rqUOHQJKGuyu96qkxHqRR3kkDjbxI6Yq/aXAXCgXTlchLCGDxXtLK+fk5jo6O0Ol0sLe3h83NTYtyGA6HqNfrFinOqCZGyCtwwn572uZvfaenTW+0s4Wu0c+9PnJdC+1tyvOQ88O/X/eNd+jpNQAMgCf906HHlJ4oByIbgYrhcGgRJTzVjQAND2/hQQ48vZDRJ8DkFOlUKjV1XPbbbDxNmqmBs7OzBhozBYupdd1uF61WC4VCAalUairdlLTiQR0FqEPN8+co54Re7zMeQjp9SKfRvRaSda+zCzy4Bkw78EJArZcxUeCuOm94Sh3TbbgOtJ8o4+kY5rtJlyyzQr5HJwRtSAJZ6qxjNkqr1UKn00GtVjPdiEA394/Xj6PWj7KGQJOmIume7vV6yGazFu20v7+PWq127Vr8MRrnjryWcn44HFqGBE8TTSaTBkSx1hMjCekUCum1pAHSNJ0V1DFVVmkdJdXPPe9TfShE6yGwMCqqW/UXfsZoLNqOutf4PD6f77gu2lsDSa6zDVQWUUckYM6yEclkEqVSCUtLS0gmk1YzO5FI4M6dO4ZLtFot7O3t4ejoyHQVnRO17zg3TEfO5/NIp9Nmr+vYuEbk+1q6h3PF/7kXzs/Pp8B55WfcQ7Tfs9nsG0fKvjHwxEXwlfTpNSARjceX4XiMaiI45DvOU5wYMsmoDm9gM3RQGRwNMO+xYj/H48saUM+fP8fh4SGWlpasACbf3el07FQ8v/FCIBK/03dwLBoqq03/1znwDDIKyNLwXG1RwkznN2pjKXHxfxVUuq76vhCYEAIL1QDi89kXekpomCuz0rBNFiolYMYNwHVrNptTBfXedlMUW+mS3nlNdaSHXz01Oof0/AOYigrxCDzBHhbJ59r5deI6M4R/ZWXFThwBgJ2dHTvVUQucxmKXdTvW19exurpq4EG1WrU6Hc1m00KUVfH2KYTaFGBVz5QHg0IGb8jo4H7yjftT3+vfFZon3htSYFQYaj88r1LjkOsZFX3kx6njuri4sCK+nBdGN3GNuF9SqRTy+Tzi8bjl/t8U4KnVauHu3btYX1/Hp59+euW0PeU7+j9bKAyZf/OHckYN1pDh+jrQ6ToF34M9Xkn11/m96AV3FJjm+xBSmq8bhxoWKpd0T5DHe9nmDSaV2yqbdSw+Mkflh/JDPZHRrznT8vWzkNNG6wpSZrAfrAmiqUqM0OZ+WF1dxeLiIvb29m4E8ATA9CWmjuv6q+yYn5+fqmno+6/RpYwqACZgFOeK8rTb7VqKDOuCeKA8JPd5UhJPqNI11vqFQHQkoTYf9s9++tQ23S/ULfUeb0CEDG9vpF4HKvg9pvNNRV29wH68vvE7NbzU8cTnMyIj6n6dR8pRRsMBE6MUgBmK6XTa9gCjE7gfB4MB6vU6Op3OjYokPz4+xv7+Pra2tnD//n1sbGzg2bNn9r3OE9c6lGqndoLWRdTsjZBjmPfz/+t0Gi+7QnTg9TfffKRn6D5v0Csget27/fM8DUXpRfxe5Spr5uXzeczMzKDZbJo81FplrOnGunTZbBbAJCqEtiNPySKgk06nzYnGCNV4PI5isYhms4mdnR1UKhVzkJJ+tSZsaD+r/NKoWQI3wKT2pKYsr66u4t69e0in06jVajg5Obl2fv8YLR6PI5PJIJfLYTS6rIGVy+UsTZG6ImWz2qsEc9fX15HP5zEcDi393ct91XE0GpInZHrd3+8lpU9NZfNRfapj697T/RLSY3gv3632lNq1Xvfy+9DbzSG54Odf5YTXUROJhBVcPz8/RzKZxMbGBlZWVixFlE78fr9vtbMzmQyWl5extbWFr776Ci9evAiuDTCRQZSF9XodAMwmCMkQypu5ubkr/daxcL51rXRO/f/kq2+qU32tiCcKWoIBfrJJEFT8PCP0/zPMlyhZyANB7w1zz7vdrhlUnlmqkQ7ANlSv18Pe3t6VsYSUFQVstM/qlQh5t7yC7IlWgaQog0ONaBWo/M35jdpE+h4VULyXHrUQYOc3tp+TUF/VGFHFlvcoEWt+qRZ/VKbmQQS+lzUQ5ufnsb6+jlu3bhl9vU7I/rEao+cUfFN651pQKVRGQiHBvUWFlOvoUy/5LHowPJ3xGu4PRkhks1ncunULd+/eRSwWw8uXL7G7u2v54ARsWYuNUTsXFxfI5/OoVCoYjUZWy2N2dnbKu03wOBQ5p0aA93R4RT+0r5WuQjnWvildqjHlr9XnkBfoNRRmIVrz/WfkAt/HUzLJG7n/1WAKKYA05giycl7j8fiVSAb2ibTT6XRQqVSsVtpNaFSODg8PTYnkvHJvUMHk0djaonhmiFcrX7qOLkJyA/h6NcU8OOn7qP1WpUt/s4Xeq/RB2ggBTp5eGSbNI+7JX4BJZIPKPvZR5yUkW0Lv1bB6nQc+l32i/Ak1Kkq8h3zPyyo6Lk5PT+3AEJU5BPWBy8MoOp0O5ufnkc1mTSmiJzFKBv+x23g8ndLv6VbnU0EO5YkhGUiPNHkXZZM6PFiWIJ1OW30cH9Gnsl37BFxNBVR5zqZ6AK/xgKYHYj3A4/UqBV5fp1d5o0d5r/bPP1fHqXOuhlYoKojzG6J1XUvdz2/Kb3gfG8dO0Ckej9vpywCmosm15irlO/nu6ekp9vb2sLu7i42NjRtz8iP5Cp037LMaOAogAjC9iU3Xk7URx+OxnbTtZThbSK4AYfCPICmN3ignrTalU4084LOjgCTuaUaqeJ7h5YivLXmdw0LpU8dNm45rQf1EC1bTOGZEtjobyIuo92cyGeuXRj7xfXSosrA+5/Xi4sJO1QRgp47n83msrKyg2WxOObX8OnDv8t31eh2NRmOKfshjGVWrAHMou+BtNeqCPERLT3gnz6R9wH2ktrvSSKgYv4LqwLSOe3p6auU3PM8PySXOJ9eD0VkKfrMpP1T54K+JsvsIamrEk+qE+jyfnun1LW06Ln2m/54O/nQ6jUKhYKe8lUollMtljEYj7OzsYH9/36KZZmZmUKlUMBwOkcvlcOvWLWxtbeGdd97BzMwMdnZ2LItL5TKdKKr/tNtt45WhOeL+oi7Fk059VpRiNAyUoM3JxvmlbFRs5HXta0U88SeEuHuAgwqPfu/RSyLeRAc5eWwU3t1uFycnJ1PoKBUFbiKCUYrsskUJdp8CowqSV7T8BlBjOuo9nvFF1R7Q9/BdCiD4/oTCDkPopW4OFWI03D3D8Nd54erb64Q214IhnQwJ5PfsC4CpsG8Fb7iuNKpZrJmb6yY0Rl4pkBQF5A2HQwsXJ+0OBgOrzUChwfkKKcIe5FPFmP3hXHL+stkslpaWkM1mMR6P0Wg0UK/XbX0YtjscDpFOp+2o9MPDQ+zu7iKTyWAwGCCbzWJ5edmKGS4sLNiphh4sZd88cBYysv2+8gKD3/E+Mr2Q8q9zQ6M/SiHkc9Vjqfd4o8nzNDUk2GhIsi4Ff4dSaVSwa92VXq+H4+NjNJvNqbEQzKKhSkVKT+Rk6kzUeP/YrV6vI5fLoVwuW355LpdDLpebiuZSpZqN9BMFJCmf9PyU9/p95K/nuupnXs6pYcs19HJN96AHYEKG5psAHyGA1jffB/IjTRtnU96r8xMFCvFaPx6ulQeA/ftC8kv3DJ9BMF7XU3kYa0kQ3FU9QXkBn8dTb3mSbiaTwcXFBXK53BTI9babAieMWNHwfgWYCfZTUQxFfevcnp6e2gllNPA8EMqobw21ByYGqxbg9vSqIBWV4CjQjC1E+6/T1/z/3pN7XYp0CAjSPe/Ho/Ou71fQSXWqEA15vcnrASHQWVtI3vlrPOgEwA4G4RjUmKYM0tIXjD6fm5vD+vo61tbWTA+/CTWegAkf4N6mI01rOmlTmajr4x2fLNLr2+sAaZXFIR2e10TpN/oef73Ka7/uup5e7mh9Ln1eSG5of5U2dTy8ZzQaWS0n6lQEeViLtdlsTqXQU35zjsl7aAPwHcrHWW+LPETrZjISRE82XFxcxO3bt/Hs2TNcXFyg2+3aaZvxeHyKxnUeaTNS3+WBLTqveuIbowMVeGKU/9tulHF7e3tYWVnB+vq6BVg0Gg2TGyyPw4hW5V3tdntqLEob/FtrBbH8CUs9sB/XAbNKt4xIo61E3UOjzVTX5jO1pp63fZUn6DXcT6RHpW+Vq15/DM0zcYYQr1e9nmWBGGFKemSGAtM0m83m1CFO8fhliZPR6PJwtOHwssTQ6uoq7t+/j/F4bCdeh3QrtbdZH9nLc9/Oz8+naksq7kHdluvPKCnOkZZKoIzSuX2T9rWAJz+gkLKum9d7xNh5j5qxiDS9EVrXhgNkfSc+Q9+v7woh9mTC3qgIKfJRhodfcN1oVAKuMyhU2Qt9z8Vmi1rAUN/4ue+fR6NDCo3vgyprvi+vU5j0GgWd6KX2oJP2LZGYLs7NOdX80uFwaF58btSbYDyMRpcnN/EoeDIrMkavEDA6KJfLWf0CCmumoALTnjBV/vl8v++4HgxtZu46j1WemZlBr9czTw+jlXgM+WAwQC6Xw/LyMrLZLBqNBo6Pj61uRy6Xw3g8NuGjhUwJtngBQH7hARvdN0A4vYrAnBoWaox6L7qmmmi4qAeS9B3A9N5TZZ6KOkOXffOKp1+L8XhsEZrKN5Xu2W/+DVwK6Ha7baHMIWWbSl2hUMDi4qJ5c3u9HhqNxo0qoFytVrG1tYWVlRVkMhmLpCPPVNqmgQFMyxfPf1Wp9PKAYKR61LzCzb9pjGgUrefPHsTk/4w8owxiTRb2TeWfjsErxCHALApkCrWQsaSgDiMcVKnm3iPvCRlQ+iydBzYfZu/7H/U83cs0FPz7fD1Jer/j8Tiq1SpOTk7MMNK1nJ+fN+OFY63Vatjd3cXW1pbxWN/nt9WazSZ2d3exvLw8xau4z5V+6PlXHQCAGdr8W+X12dmZeWBZ34drriC+NvXyM7JY9Q3/bgVUfJ/9fvIKamhPqG7FtQztS17rgSd9lterdBze6Pb94VyE+KgHahmBEpobb9C9bn97oMrvO/JLLeauUdTkNdxHpBtdb+rY3H8EdxlN9KYGxB+jxeNxc5wRyPDAE+dY9XDqsnrwBx0yPkLOgzX6bj4zHo9bZBl1ONVn9J6o9VXnhF5PWvd7mc3rDCpfFFDw4+GPAg4h41XnkPdT5z49PUU+n0exWLQUuEajgcPDQ7RaLZtPzqnyWPIjX3qFwDidZLThGH3DE9oYwcdnECgpl8sYDofY3d21UxupUygQp/WAAZhuzSLolJM6bs4t5RPXJnS69NtqFxcXVguOOqTKS84BQXddTy2Vo7yCTaNDlYdpoIieiAqEQRD9jLYdIy7VTnod2AtM62C6XqH7SH+0UVQXUb0nal94JzT/5vv0c9LV7OysRTmxzhyzFnZ3d9Hr9dBqtdDv95HNZrG6uoqFhQUryt/v95FKpaw+1fHxMbLZLDKZjEXzMXuLNBmSOQCmgjW0qWzjfeT5HLfyutFoZCcnKjire4rRj1HOn6j2xsBTv9+38DoieNy0Cu54FJLXcPHUyCJT1+JbeqpZFAqpE0kGESVI2BSd0+/VYA0JDP+ZKtVRfdPvtD+h63UD6KbVFhU6zDnw/SRh+r7TqA4ZH2QsbF7QRc1HlIAlUWu9Iu9Z13doCCj7xrVRRkrmRwFwnaf+j9VOT0+tsCXXR2mfChL7yvDFxcVFpNPpqRNnSNNsOt/KKDW0G5gwS6LTLADZbDYNgWfYJ4W9FrWlICF4QUapobAXFxfmJeIRuszdp/JKIUOlQr3ioTGxecMmlK6n603wwAsBfu+ZrhpDIYXeG0RMUwvdx7XwY+Hf8XjcIpdarZYVeSZdhJR63ttsNjEcDo0WqExxbahAk7ZoTK6vr2NhYQHHx8dXcu/fdmPqnNZ1A2DRKATnSC/0zkcpeQrWqEJBcAWYTgPy88D/vZzy66K8O5vNIpFIoFgsIpvNot1u2ylpFMz7+/u2/2iwEmRTBU8VYr7H05b2ReXNdWC/GvOxWMzy/JWnKujr3x/F56NAAX2Gzqt/hze89Rm+37xO6z2Nx2PzAM7MzOD58+d2Eh6L1qoRxrXld+fn58hms+j3+3j58qXVxbsJjfKBJ9wsLCxcAe1UtyK9Alejyfw6EoTv9XpWzJSOgygdRg0vfXeUXqV91BaiC/3f01oI1NLv9Tm+PyHZontNeajOk3cYROlznlZCfMIbXtpC3nK/v0N7LEq3Ip9LpVJTqfva9FmqJ3DsNBjJI2jEMk3qJjgtuC79ft+iBACYfFQ9gbyW8oOAu/IBTW3h89lCQLnaI0zN4x7UNVIQV4Eob39oC+0jtWG8YR1Fn1z3qBOVVWeKsj88+OT/jsViSKfTSKVSBrppCjfBIdVB/ThUp+cpygSW6vX6VP068n6uPW08njaXTCYt6r7RaJh8oIylHFAjWhsLnDP6mn0l3yPdca15KuTKygpWV1eRyWSuzOMfu41GlxFP9Xodg8HlwS3/9E//hP39faN5dVYC0+U3qIN4YFJljf7NOaHeQlCbYJI6gdWmBHDlXq3NptdoBgB5qto+bAoMqQ3rHbiams7rlS/6DCQ2rv11+40lNEirmUwGxWLRIqq5JiyIT0cy+8UfjpffMUJ5PL4se9Lv99FqtYyP8308DW8wGFjheD8/HIsfB9db30+9Q/kqQWcNJvAAFNdbgw7epL0x8MQTJrrdrjEcMl0O0AMf+n8IvVcPA/PRyez5WdTksUV5pF7XvAKtRM53eqNZFaAoBYnf+e9VYKlBFAIVogxj9jv03tAGAq4ek61AHZsyay28qaGPem3o7xBAB8AilnStOVYdJ5VkLYTKqv/aRzKuUF7y22osUtjtdo1BEDyNx+NT9c64/hR48/PzU3UZPMP3yokKisXFRRQKBZyfn6NarZrniIAfUXd6/HiiExHq+fn5qSg3KmsEnNgnevkI+mmB0qWlJWO2MzMzForsUXddfx8u60Enbd54VZqhYqF7Tp/p38Xn6f6JMghUeSINaiHYkNHNaxU48YCr7nkKfhXa/FyL0lMQKEBOfpXL5fDw4UMMBgNUKhVzDtyk9vLlS9y6dQuPHj3C48eP8atf/QrApCAhvZikWW8o+kb69zTBCAANK/cGF5vnRd6IBy4FeCaTQblcxne/+10Ak7UYjUamfDOdslgsmreNRk6r1bKUNwK+ngZDzg6vePl+k45UYdS/vTEETKdGhUAK35S3ap8oG1WR5XOoPPp3+/5HjZ2NvJ56Bo/rrdVqqFQqADAV8QHACosreDkaTYqOj0YjFItFJJNJqzvytls+n8f777+PR48eoV6vYzQamWNCASJNUQCuNyIZPcBGo5w8RQ00XS/SA58Tqt0VtV5s3A+eTtg/pVu9NvRc5eee3/JzdeiE+qeywxvVIZ1KdUHlMdxTasir4cMoNa1dwzVQXqaGW2judNza1HiamZkxw4cFalVP1XFSLquMZ3+o73EMmsJ6Exx6jUbDPP2MJlUnMwADLM7Pz3F8fIx4PI6trS3k83mL4uZ4o2hXgQZeF4tdOsIZ5d3v982gVMMZmOZ5IZ1U6UyBGN9IhwoIsJHOQ3yfdEfdmPQboiM+KwQMe3uFqcqMmARghcAJ6qkhyrnWyHM+B4DZFnQw0aglTZL+aJSrPaLBDvV6HeVyGaurq0gmk/jyyy+xu7trOnG5XLai5eoApk7GRrCOc0i7Vh3EAMwhwNqCBCHfdjs9PcXBwQGq1apFomWzWSwuLqLdbk/JSYIWCrCFdIvQvle6SqfTtoaapTI7O4tcLofhcIiTk5Op2rMqj1UG+HdreizpSHmi6vSqdygtaxYD7wuNx/N7jp3Xh+wE7ePZ2RlyuZxF8hUKBZTLZdNnG40GKpWKZbCo/Oj3+zg8PDSwR2tcU2+kLabpeKlUyp5HZ3+n0zFbjvPG+QzZJ/ybPIA1wVgDkDZhPB5HvV43Rzhl4czMzNQBJwq4tdvtN07RfmPgaXFxEe+99x4ePnxoBraGH3JASoxqbHJxPYijAlUrrqvx9ibA0psoSFSU9W+9Pgr99MqGB3+8QeMZPxeSi02jWQ1OPx/avGAMjcsLLCVC9fCQifC99JyNRpcpYIyWIPPnOr+uhRQ+PQExSiCrYqjAE+eo3+/bBo3H4xa9wzSom2BkK1CWy+WQzWbtOGQ1GGhAALAIj1QqNRVirQqHVzzU8COirso36+Ywz3hmZgbZbNbCchl5k8/nkUwmp8BFRh7SiFZwVPcKU5MY3szIxHQ6jXK5jEQigWq1aidOaf9DzTNIfWfoWm8ohwznNzGSQsBy6H3sO4Wc5jtzzVg3i4VcWQ+Ayhn3EPeUB5q0ce8xdZNKGoVEp9OxI8w7nQ5evXplAMhf//VfY3NzE6VS6WuHvv4xmho95Kdat4bFQqlEMS1IwVh9lq4vPXuagukdAHpymj7DC2W2TCaDv/iLv8DS0hLOzs5QqVTMQaKnpi0vL1vxyFgshsPDQzvamLXp+A6NZqPC4U/5YwsBZX6vhACekFeKdMg+ca70Gf45+m7fl+sMKC+LFUBQOed5jPI33q8HkBwcHOCzzz5Dv983jy0BWWBiZHNOKX/m5uZQr9extraGSqVyY4ruA7DoUnr2SZPkzWrM6gEUXv9QnsJ7NWKQ3kzOmTrCQjxU19c7ifi5tlCEakgv0h+ltRBo4t/n9SqO0wNbymO8nPDP9LJGAVs1NFQH9dHG/F4NcT3ZVGsv8f2vc9p5cEHniQYS6dsbUfocrh1BTDUe+J3K/6gDQt5G297eRrlcxjvvvIPvfOc7AC6Bj93dXaNjev1p5DFKgBE6jOwORRp7mlN7gOMnH+H7dB51nTwNKd2FjED/XjblkSGer7RAfuH1nShj27fX6QcLCwsWlR+Px6fkGICptLhYLIZOp2NAkb6X/aL8ZSFy9oH6LMfD/8nzNHWegNXLly8tApwOCZ62zIgkBbz4mzyCDiLuW2Bid5LHsv/MFmDwhR5x/7YaZXm1WsXx8THu37+PBw8eTI1RwRJdE0b/USfVZ7Kp3OFzOD/8jlka8/PzlorZbDan7Oko25107u033RMhx4DvH7/XPehteQW7QrbFdWCTPl/7GI9fRjsR6NMU1JOTE7P/NLVwYWHB+KyOgafe8d2UOSwvRPsqmUyiUCggm80imUyiUqlMzTWda6Rr2jcqixWf4DXcb+PxGAsLC0gmk6jVatjf37focO412o6kn42NDTx48AAA8Pz5c3zyySfB9fbtjYEnKi3q0WHEATA5TYJRKhTCUUqBMlj1imnaAxXkqHpRnukqsUZ5wUJEx+/VG8w+6nWKjKoXJaQMea8vFzukAIVQXe2vF0Ahg94rXOp1VIGk3kZuAi3QrECEKqjq4X6d15N9vM7rEhoHlWP2lWlEPIaVz+NpDlFHRv6xGyN8xuMxVlZW8M1vfhOJRMKOt9S6PESn4/G4neBFb4TSlI8kACapE3wmABwdHSEej2N5eRlra2tIpVJmUFIh4P8UBEzt429gcrKUrr+eZuBr78zNzSGdTmNhYWFKiC0sLBgwQsNcxxZF495Q8cqWCkD2h14y/h9Kq/AtSkH0zQsa3dME+rgWFAbVahW1Ws2MyHj8MkVrMBiYUuY9AsqztN8EudSbSs8f07vocdnb28O9e/ewsLCAVquFg4MDK8R5ExqNa3pHstksWq0WisUiVlZWrD4Yf1QRAK6m1ihfVUCPNTyUxgjw8CQdnszIvaS8UQX/wsIC1tbWsLm5idFohJcvX2J7e9t4IPcGeePOzg4SiYSBzul02or5Z7PZqQMRuDZzc3PmyWcLGSpqgL4J7yWt6AmIqkiGPIX+fr7X86GQ40UNNl03VQD9/tdr/fvYeA2Vst3dXTSbTdu3NKD57EwmY8aN6hbZbBblctlSREJjeJuNwITO1czMjEVwMSJQASkgnK6jgIXXY0ajSQqd1z30/ii6iAI/Q/NIfSQWi5kcUkNB02C4HhrRwftVn/P6hwKV10XR6ue+z7xf+UUIoPB8R39zLKqLMCWI/VejmvpACPjV/0N9ASb1DSkzdf95o3M8Hk+dTMQ9pumpwCRyiIaLAvRvq7EvdEDQ+NJxz83NmQ7FWpWVSsWiVOLxuOmUXEMvh73eQZoFpk/e9hHWfp00fYnPZESm1hAEpmV9yKhmP5TudM+ozcJ7fPP7NCRT/PfchxpBRZCVskuBS0bDM7qMTjAPkFFHpO5CwJRj1/2tEZqMdGJtG65Dp9PB8fExSqWS6RHUwVXWcG7YHx+NzvlXYF9tvHj8Mopqfn4eBwcHOD4+vlGOi0ajgZ2dHfzFX/wFHj16hG63i1evXk3V8iOY0Ol0TO9h+mAul7tCC97RR3rUSDDVoQj89vt90/dVRgETAJ5roTI8CnxiCwHq3o5WAFObjoP3RelQb6IT0DFPMJb1c5lyyoLt3k5j39RG55zyIBgPfBLo5Hyy5hNlKQFWnrLI8iqdTgcnJydT5Qp0LjlWxWIIPHF/MAtHQTfyBQaI0CZiKuH29jaOj4+vnT+2r1VcnMTKRgUpnU5PFX6jcHsTBel1aCYXiETqkU5OpFcqVDh4j4R/F9+jaV3+++sYux+fMnBdOBVIXvn1QiI0Nx6BDQFZGorsnxlSKgk+sY9kvCp0lDCj5iA0Dq84eS8e6UNzkv3c8706Znq8fVHat9V6vZ4ViWMhxvv372N7exu1Wg2DwWWBb6bfAZeeu06nY7U3KJCpUAHT3k1gsi8YZTM3N2ennjHtjkI9kUig3+8beMeUL6VVFhdXQFmVU/4PwEBlrvPFxYUV3SbIQvAqk8kgnU5baDIBOG1RPMFfwx81FNhIm9cpX6Gminmoaag4x6oguzZ68IBLOuDJgMrs9ehSXUuOMQSq0CulBoAqtsPh5emDuVwOs7OzuH//PorFIj799FNUKpUbszcA4PDwELVaDZubm3j06BF+9atfmfCk0Q1MDprQMfs0RW3cK+R5VGzIN8k7crkcisUiarUagKs1VYCr9Zw2NjZw7949AMDe3h6Ojo4wGo0s0uzi4sJqTZyenqJaraLX6xnIlUgk0O12zXnCU30IhDFFRpVfIPrk05AciTL4vdygkapGuspT5bEhulTQSX+zT16+hpwBIScUn0ElX9fOK0utVgvNZhPdbteMUEY7DAYDJJNJSy1mIXIAth6snaC1QELG1x+7kQ4ZIekBA40YZrRFKOXGgydROoI2XWu/Jl6vCoHj1+lVpAtGLKinN9QHnYvQ/6rH+ZQ3b2i+zoDg9x6A1T2m88DvNdqM9+lvnUut66cyXR14GpXm5W1ofthCBhav9ZFK5IMK6LNmkdaqiccv6xKylt1NcOhxnOogIz8FYHM3Pz9v63JxcYFGo4FMJmM14aij+GcDV2mF+hV5OJ2KmjoJXAXJ+SzSQiwWM56vJ27zfR4U9k37xP3u9x6dLeqs93vXg2T+HaF9QtlAQI97TXW8ZDKJweDy+PbT01Nks1nMz8/j+PjYTjnm2Ghw+/0fJcNUpvhU0Hg8bofaEMxiyjX5DfVpjfRR4I82BNOt+UNe5XVMOlGPj48tHfptN65xr9dDtVqdKlPD9eNYuZZqU1L34Fz71FFgwg/VAUA7hetLHaLdblt0jJcZKofUlicAzmu9fqD8zNuZwHT9QQV06GwLzRefEdoTUVGe2jdGWRaLRQAwsJ6FwwFY5BEzIGZnZy1SXnXPRCJh2Ttqg7F0C9eFekEymbRDophptrS0hE6ng0qlguPjY6tnR7vO85eQ04hrTB5H4FfBYYJSHMtgMDA7j3ShdPK69sbAExdFQyL9AFRhIpr3JopPVAsx2+sISL/3UQ9emednXHBNRQgBNqFx6nN9Ohu/izJw9Bl6bQiE0/fqfOqzKQzoSQvVElEGECJI9fZoeDI3hgIXHtjS93gjyoNRfA+VMAoLFihUI4hrxMbNRHT5JihIT548QaFQwPr6OjKZDJ4+fYrt7W07GhPAlHd+MLgs5jk7O4ulpSVLKwKmaVoZIdcslUpZRFG9XsfFxQVu3bqF1dVV8wQx2oEKE0PQyQSpyA0GAytqS9SdoFUI4NFUWH+6mhYUp7HH2lLJZNLoiYpECNxVwC0EkOo8MuVPlX8qR6qIsYUEF2nYC0rSHAW0psVqHjr/rlQqODk5MXpWLwej2tRY1LGGwDYAlvaq3lkCGLyGa7i6uoqHDx9iPB5je3sb1Wr1WmDtj90U6EgkElhZWbH6CwQRRqNL7/b29radDqIeVOBq9Op4PDnAQAEVfsffDHcmkKd8VJVv7ptyuYzNzU2srq6i0+ng6OjIwA2ecsi9m8vlzANIJYGprd1uF3NzcyiXywAuC1Jyn9brdfR6PczNzVnqOnm25/k6Hv1ODQ3P17knqBD4z7lXNPVX+Y4CHNpCAJnS6JsYOCHlJGTIKQjD+pJcc+2bOnj4N+cikUigUChgNBrh8ePH2N3dnUpHeNuNKR/kxXq8sZ4EOxwO0e12cXZ2NuV5VEcREI7U9DpAlI6htMU+6H1R8+VlhRp8VGp9ao3qdlz7kJ4V4s3aH0/boRYyhrwe5YE8YAKgKmDJ/X1dI/2pLKUxRBmokRdvQoe6FzzI6OUc/9cIWQXnyKeUX5LeWFz8JrRQX2dmLk+cJVg7Go0sWosnfHW7XdTrdYtUIW2F6ACY5qXxeNyeNx6PrS6md355XsvPQ3JHHbv67hDo5PulQKUHTCm/2AeVByEQN6RXaSO/4LN5KhidAozyUONZwaBcLmfvohOIaT8e1Pa07AEFrj3HSJ7Hvci5ohxTXuX1Ok2Xpe2gp8Gxz6xvw34CsPIZ1HdDxvzbaLrujIJhXavhcGi6imYicM4pOzqdDkqlku0nfbbySa4RASd1RJEeyUP9Oqrc0HVWcEt/ax9CqdIhfURTKuPxuNWIVlBN9SOOye8JTzc6Rso1ymjq4YPBwOacco6gDUFn3aveGaR9Uwc3T27n3qGjn89lvxYWFlAul5HL5fDy5UscHR0Zj+T6qyPd80DyMmCCYVC+EYRlNDb33Wg0QqlUwoMHD3Dv3j3kcjmzRa/LNtH2xsAT87+puHMjcpJUQdK8aGVUynS06TVKUB64Ue+UXncdoMLmGRyZmPaFxKMKtVdQojaKKt7X5bVyDjSdTRUsPjtkKOt3JCge48hNwJM9VIjovX5OvBCkMUIPAzBJddC58QBc6B3eaOI6cSNrHjfnm3PhDTB+RwHHlImb0MjEGe3U6/Xw6tUri0qh0PTGWqfTMc/jzMzMldxxVczJ+LgWBCWWl5extbUFAKjVaibo+b0eL056YD0d4HJuOZdqiLM2ld6rQiSVSiGbzRozpvDXvU5aojKrTDMEwCgDVIOaTQ1LnR82r8CweYPqOmEX+lwb94xXNqnEKFOnwFBQmuPzyhh/U/EhD1VBweg4zjOBiuXlZaTTafT7fRwdHVkthpuyP548eYJ3330X3/nOd0xYbW9vIx6P22ljBEaBqwUiQwo2MM2PVUnVcZNmuT9Dig+fR8WBniimwnHvKtjNaAHmwVNRZ+QV3zU/P2/A0tLSktWB4t5hQXXuW/I5lXWqqLOpoRxS9pSH6rWUE1SIWH+OnssoGc25YgulzqkhEZKBUbKC+5aRT15Wa61ABZaoJOox8LyOdQEvLi5wdHSEp0+fYjQaoVwuY2Fh4cZEBNKwVsNHjSTlEWdnZyYvOFdAODKIzQNPqn94Y9A/K8pppv+rjKecU+Dd80oAU+/2zb9f+amOl2PV51IGRelVfgz6Lm/gABPAielSUSf3hPQqnRvKNhrABA+1jIS/3z879NuD0X6u1aFHWlLDS+eH9NRqtYyfve02Gl0e562gM9eEuiMAMwY1GpgRGAT4vN7BproKMJHBBOLpwNM5831k4/PVaaX7UfeY7hvu9ShQzL/HG4rKx31QgKdFla0+UlznQGuTjkYj0+MY5URAI5PJ2Ht5chcdOO12+4qO42k0tEfZTwKz1BPYZwK4jHRSWamRJapH0kifmZlBrVa7sjaMACJAQ7o6OzvD/v4+VldX7RTem9SoYzAS5fT0FM1m0/QJ71hSWa02CXlnSP4rXaq95vdSiLfyGh9NpDSgssw/R5+nOobqNF6eXKf3hvQL7wAJyQUAZn8RzGZEJAutM/qJgD+BWS11wufRVqCOwv12cXGBTqdja6i85OLiwgrIEwxl5kw2m8WdO3csqyaTyeDs7MwOG/J1vnSuQvtQZcXFxcUUKDs3N4dSqWRpmuwDMaA3aV+rxhPTAnTDaygkGyMfksmkCdaQUaeKs57Yok29k9cZhL55wEvvJZGoYqcMMkTMbIqA6mdKqFRU+LkyuFBuvjJ8D9ZwY6qSQUHFqBISONfHK5vaT84NmyKtFLQUtircQwJClZhQU0RVjXMdE79nGicNCX+cNoUf0X2GQEeFR/4x22g0QqPRQK1Ww4MHD/DBBx/g+PgYBwcHxqTJqBR87Pf7qFQqKBQKU4oDFSjeFwIzqWwQ7a7X6zg6OrI0RA2t55yqp4ffETTmNawL4/cb+5xMJrG0tGSesOFwaMXMyTjJKAHYkc9amNLTi1eA9N1eABDA0vQgfq971is3USCTb6S3KPQ+CjQLGXgcq6aAqaKpQC7fzVxxHpHqvRvcLxRANPbi8TharRaOj49vVH0nYJKKWq1WDdD2PJTGBIVlNps12mFKtzoG1NjUExhDjQVn2bwRy303Ho9NuRwOh2bwUKgyND2ZTCKRSKDdbhvfVVlDZQGYKDWLi4uIxWJoNBoGIjOff2FhwZR5Gjm6f5WGSedKNyFASiMLSXfeCKLBq3JIPXPaXmdc+z6o8kY5ooAUDW8t3Ms1Jn1wnVijhiANMClUq0anphOz0VAh3/rtb387FVn7tptGdBCIBK7yL9J5v9+fOlVGdQxg2rnljWVdK+WTPrJWn6ufq3GsTeleHZLkVbo3FPAN1btTEFTpl9ez3z59VPtKAzXE4/V5vJbP06hW6lZMO9Ci2zqOUPOGEX9omHiPsr/2Op2Kc6eNhhvnSCO1NIJDjU5ey3mjPKGBc1OAJ+79WCyGYrGIxcVFHBwcmP7bbrcxHA7NGdlqtTAcXtaxPDw8RCKRsBQVAFa7RGW3p2nK31js8mS7bDZ7Je1d9xdwFSDSGklsqvt4ua+0Hmq6ZhrR7aM7+LnXubVvCnxFAVrcx8o/ut2uAVA8xXlhYcF0P9YN5QFFfpy6T5Uu1QgnYMSIM+o6TLlMJBKmb6ohvLS0hIODAzt9kHoogSJ1JtVqtSuylfKI+5SnTXP9ZmYu60PWarU3jur452xc54uLC+zu7uLo6AgbGxsol8vY29szW5B0QJ1DATpmPmSzWdMZOB+eT2okq4KqXhdTBwib5/OaPqeyyDs6dKxe1yBdq4NNaVptRs/7dE/ou0PyTbN2hsOhRTspHdOBQFCKzn4CU8pjqAtplhXfoXuFJShYxmg0Ghn4fnFxgZOTE6tvx/4Vi0Wsrq7iyZMnxi+TySTq9fpUDckoLIX8hbXytFatRkKOx2PU63XTudPp9FSx/jdpX6vGkwpmTTlRxYZEyXQEj+J7gEcVHc/olCj1Xt8vbbrI3hsMYIrBsB+8jyi7Kk5RgIs2NTa4OH4DAxPlRsEwLwCjhJNusEQiYTUraAylUikrLKa5y/p8Ejnnjd8Ph0MzdIie+7V7HfCnz+NYOQ4vZPR6giQ8AYBKoz9dZTgcWv2gWCw2JRTedhuPx5Zne3FxgXK5jJWVFZycnBiQRGBHI72YktNqtbC4uGi1XzwtUHCwVgn3DI/7ZeFAVRgA2Jz6VDddI/afSpJ6YwFYfweDgZ1ct7q6ivPzc6uZQyEGwNZH0/ZIUxq5wMax6r5jn/w1ngEC0/uXc0aa0TBTpeHr6Jg8AHh9HSoPDmq/qbRSIVMj3z+H95GHEOzg9UzzopLJPjL3O51OIxa7LL7MlD/u65vQzs7OsL29jY8++gjvvPMO7t27hydPnmBvbw/5fN68MxRelUrFPCr05OlYOH7yqahinwoiasFLrpF6CqmA5fN5xONx89ZSeWW9JoIjzWbTnBfsG/cO300eqIozeQDvoRLNKDZ6jYGrEaP8TCPootY4ijap2HsZFgIaeL9XLKPkgTpF9DqVdzxtinPPCF3yHyozfq3Yv0wmg1wuh3w+j2q1im63e0VuEsTh2q6srODRo0fY3t7G4eGh8YWbID/Oz8/RarXMm6kedVX0udaMuiGf87ThHUVRACUwXb9Ple4Q7eg79DfvV7AVmAZ0VDcgPfD5UX3jO0J6lW+qa4SeeZ3C7YGfmZkZ5HI5q59DfYtR4HyOnxudaz6TcnM4HJq+RuVc+6F/K3Dgm/+c41adkvKR+40HO3BsGhnKZ/B4bkZHeTDybbWLiwtUKhX87ne/Q7FYxL/5N/8G3/jGN1Cr1bCzs2MAYDweR6FQwHg8NkMPAKrVKkajEdbW1lAoFKbS1H1TgJQyl3RNYEXBWupHlMGaXaDroJ+FwGDgersmpLtwHwETHc7vwZDt5I1rT7/8LGQks3A0rx2Px+Ykoc5JJ4A6Tfw7QvMfAu2o01AeqO5I+hyNLrNt6ATlmml6Oe8vFArIZDLo9XpotVpThZMJNmlpCODSKTs/P49SqYTxeIzDw0O02+1r9cc/VlPQvVqt4uDgAOVy2RxndNppBDDLYVCu9Pt9tNvtKUeyzrHyNPIz6lEeuOY9nrY9P44CItX5BUzvF0/T1GEY4EHHjZeVCuiqDql2LccRpZfrcwkqKY/1BcEZdMMT7waDgZ2GzMbx0GHJ9zabTbuOvJ11eMlTqMt2u10DU8fjMdrtNpLJJFZXV+2AhVarNWU3aFq38hTyKWbndLtdq93GudHoysFggIODA8zOzmJ5ednmmeUz3qS9MfB0fn6OTqeD8/NzSw/gInvUjgoSPQTXKQMeJVUFki3EINlC13uh7r1I+gz+HcrbV4XZ90cNSf4QCdV0N/VAeZRdx6bPCRkTKhh5YgeZfjabRSx26U3XsD7ep8oJP/PzToWEypLm83oj3zevOIXGyaaMgE29I6zfwXuVkbCYsqaP3QTjejy+POq+Xq+j2+0ilUoBgHld2Gh08vNY7DJyq9lsIpvNThmlKlwZ6ZVMJu1YdwAol8soFArodDrY3d1Fu9025YOClBEZeqpNqP9sOq+8liHKTC8i0ysUCgagERwJCQ8CRmxqlABXI4aivB40bJUmlab5PHo5dBxKT7zP8w41xKI85j4s2Bvs+nwFBrSf3nDnGi8sLFiotJ4aMTMzYwqFKpynp6dW4LrT6WB7e9uOs71Jrdls4vj4GK1Wy5Q78jqvUAPT/IjAkndIkLdqeprnc8A0D1JZQMWFQAg95bq2rVbLgCMFb3n8LcELAibabwXbecIMgch4PH7lFDPWWjs7O7NoYn6nRoTOlZeL2vcQYMA5Zy1AjeTQ53hQwStlUTLR/60GPcdA44XzSJrnGociO2kY0PGwtbVlitFgMDDFT0HKxcVFJBIJqz2QTCaNj+ravO3mQWnqT95gZeQXr+V1wHTYPr/T32wexPPOIu8EZPNACRsVTuW7mu7EZ/Ialde8V4FJGjfKrxkZSNrhXud7+HwPqHIsPqVI+YjnGdyfwGWNvYWFBaTTaStYrcXfuZcU5PF7QOsDkv7U+x9ynuj/2teQAacAnsor6gD0mjPCj/yS88e15SlNo9HIjPKbIkPOzs5Qq9VwcHBghtTS0pId6sFIUYIeXBPODetbApMT5pTePG0A0ynx5O109g6HQzu59/z8HEdHR1MgBmmStE5ZEAITPTjk95g6wUhnfKbXufk8tcH0PfwdciTwGZwzdTzycBoFvOhMJY8dDAZ2yA0BQOqi5NG+KaiupTaYmkQZS7DEN9onnEM1qnWeyU/opFJ9jXuCUXHpdHoqZW08vixjsL6+jna7jVevXk2Bam+7ceytVgu1Ws1AMgIkxWLR9j8Aq/tDe/3s7AwnJydWLJtj97Vctd4vMF0SRXlVyDHgP/P2h5cz/jPdU8q/yesVZ/DOKvZV97bOHfdm1P5U3CCVSiGfz5tjiIA0I99brZbZHXweS+B0u100m80pMI9R+go0qSzhO0iLBEQTiYRlNJDHU37Nzs4in8+jWCzaSXe6ZgQNFbjmu6k/0fHrT7QjsEa5kUwmsbW1hdu3byOZTE6VnHiT9rWAJ3oTyDC4qCQCCnGict4zFAKNgPBxf0C0AarX6UJRqIY8W7yHfdJIDjVm1avln+GVch0TI494pHO73Z6q0aLRYr4p6BRSPnTcVMSUaRK5poBQT6gqmVFEofPBtCj1knFuFWX3xrP2UTeYN8pDfVCB6U8W1HsIPA0Gk5pKN8FrTUbSaDTQ6XSQyWQs/QPA1OZVWufYGGnEawhOUSmkYcXTDkajkdWLGY/HOD4+RrPZtOdT0GjaxuvoywMywLTBMTMzY+GVFHCDwQCNRsMK4cXjcastxWeRppTGPS1G7asQAM0+eTDZezmACUjEe7wXN9QPNo0C0GuiQG4F2/ibfJB7xhsmShf0NjBUfTyeFC8nkEieOx6PDTQpFotIpVKW2knFIiRs32ZjJAGFs9Im/6cSQRCNiqxGCfJvrZfC5nmNAh/ARMAyFP/09BS5XA65XM6K/7KPu7u7U2AraU6jnlQwAxMDkF64eDxuhz4sLCwgl8tZOiVBZf4ejy+jTZkSQueNgu9RMknH7BvHr/U6GPHjeYHSmzdKvNzyfMPPv869p/9ut2s15ljbS6MMeb86itgHFtykE4zXqmeXUb98lyqIOzs7QQPlbbWNjQ08fPgQuVwOv/3tb3FwcGA01Gg0LJKUCiN/gGnF+E32+3VAm+pVfm1fd5/KCfIedVx5QNEbxvwsZITT6GeaDKPDPKAcStvT53ggT3UZYHJoBemQe5YOJRZR1nHzx4NCum/4Lh5uQKPBy69QCwEE/nN9L8E9GiHUwSlLQgYdI5kZEaSg501oo9HInN6a2sV+8iAcpuyyXp6ugQI46rgBJgenUA7pXNPQ63Q6xvtJi5lMxk4s1qY6BxvlQmi9lb/zf9KmRmzw2Vx7jebmOLWIuTrI1BGitO/XWZ0dNKypa6ss0/ljXwjiLSwsIJ/PG5DTaDRQrVZt/3AutC4onQepVAozMzOWDkn65PvoBKJOEI/Hjd8zBU7lmv6u1+t2oAedTJoiRec9Zcr8/DxWV1fx3e9+F/l8Hp999hkqlcqN2hsADNg4PDzE2dmZ6RjHx8dTJ9xx7bTkRSx2WSv25OTE9hXXXZ3k/uARlQdKr94ZoPqR8mqV8d5m5P2+edBJAV4PvHpeHwpOUJsjSs4puEZaZc1P2ge0z/TQGeqMTANmDV8WfydNq52kssT3g3POcRCE4vjU+UaHNG0E8qvRaBJRpSc3cs74vJOTE9TrdZMZ5EOkB8rZRCKBcrmMO3fuYHZ2FicnJ2g0Gv/vgSdufG52MmVv/JHRk5FfF7IbUmhCiGlIGeb72Ce9V5USNhrBPtTYI+fX9ee6SR2NRhYJwrQ3PXVN++QFSmisXgFUI3U0mpwWoT+6QUJe6lBTpTUej1sBeQBGzDoGvUeRYm/k+b85bq80q+LKKB2CT8pkBoMBUqkU0um05aAy1PdtNzI3eh7W19ctMksNB25crzCSuQMTD40HarimfMbKygoKhYKBUQpCUlnXFsXQQ/RN5kc6ZB0oekC49xnJwRD2ZrM5lS5JuqBHiV5KvkOFDt/nwWk2vV7HptFyfKcaJqqAqeF+HahN5UjfqbwhRNeh+WTT9dN8bQIoNPibzSaOjo4sfYh7eX5+3oRXIpFAPp+3/qVSKcTjcQuvfd2JS2+rHR0dWQ2y27dvW+oTCyFyn3DOWbRRj/fmnGg9QAp9H+3j6YtyiwBuLBabOoY5m80imUxiOBwamApMwFcCgkpnwCRFUvkgaW8wGFjUBNNs6DXjPQTc+L4o+gemlTylVZWD+rl+p4qahqR7p4+Xg97jzuu8kuTlmcplBZA4Dr3Hy8PQHFAhpnGgdQnJWzUicHZ2Fq1WCzMzM3j//fcxMzODJ0+eXCmy+rYbI5notEqn06b4eQWffIAh90D0EdDaQkBSlLNP50XXhPQaMjqASdoqyywA0aCo12v8uivvo+OC66wREBq55h0m+n/IcaDyjaCTjpf1gqhneUeIN5r8ePV/8oJ2u20RjYziCkWmhKL+FDCIAulULmn0APUGjsHPCx164/HkEIabUnx/PB6bvkcdpFwuo9/vY39/H/V63a6lgU2dlXYIx6/GXciWIF8lKEGAC5hE45AuW62Wpcqos8v33RvCIcDfg06eRoHpNDVPD2xK/15fuQ489n2mfUHAnjKW88eIGoKC3D/8jEess5aW6p6kQe5hyiP2kXM8Hl+m7qjTMhaLWVooQapYLIaDgwNUq1WzF9QZxTmijkDHKJ9HsJIpS4zCPTs7w/HxMXZ2djAzM4OdnR1Ls7sJcgOYyNjz83McHBzg5OQEt2/fxsbGhgFRBA3z+fyV8iys5XtycoJkMokPPvgAtVrNAhgGg0mhdk+rXt572tSmeovfe9w73maPslVUH2FjNLQ//EHpLoQfeJnk+a6CS6lUCrOzsxZBRoCUIP9weFlXbjQaoVgsIp/PIxaLGd0QICL+QBvDy2bOdchRwL1C/kYQjKDS0dERbt++jWw2i729PRweHqJQKFgatU+D5e90Oo2FhQXU63W8ePECrVbLHN3x+GXkFvXW0eiy/mg+n8f6+jqSySRevHiBTz75xPSWN2lfq7h4t9tFr9dDqVTC2toavvzyyyvpdIrC8XMFL7Qp4wwRK5mDT5/g995ToAZzSCFTBsZTDJQJ6bNVCQ8BWXyvGkSj0WWociwWQ6FQQC6Xsxo+fL8SuN8IfLf+9nOjhM+oAb/Z+NsLK21e+KnQAqa9K17hAqZP1FDDmnPplXsPZqjhQk8FT0pj+plf/8XFRTNSG41G5Ckzb6ONRpcF0llraWlpyfqqSL0q6MrcKfCAaSScc0ClmyCVZ6SM2GCdGT6b86/rr3vDA1KhvcDP1QvSbDYBwE42UGOeTJJKCWsk9Pv9SK+G3/9Rxiq/Y3+ASSSZht1q4ztDypeO1+9zNZy1v9dFReq+UmGiz2DetdY1GwwGqFarxrxVIDNnXxVBFtpcXFzE4uIiTk5OrGjmmyqZf8xWqVTMK8JUWZ1TgkCM8rm4uMDx8bEVvaUnh9ep4A015YOzs7MoFotGq7VaDd1uF2tra8jn83b608zMjM0haWYwGFioNACLSFIvO73AvV5vKk2TCksmk7Gi/nzeYDBANps1Wckxkw8UCgWLYvW89Dq5GdovwCTknBHJDK0mMOsVID5blTGVCcp7fN/8Z6F14f0qF/h9yPOXSCRM3jUaDTSbTStIPxwOLQqh2WwafyPPOTg4wNbWlp0IeZP2R7vdttNIc7mcFU9Wx46mvysgwGu0RfE5IBwlrrSka8LvuA6qS3jQQ6P8tOhsyLD3uoSuB69XnYwODgAolUpYXl5GKpWy1Devh3Ac7Nt1TfukNdzYL5XDUWNgC4GlCk7T0CaACOAK6MT5Vp0tCtwKgYkKuLHv3COs0TMej5HP55HP560+zl/+5V/i/fffx7Nnz/DRRx/h6OgI29vb187dH7ONRpen2x0dHWF1ddVOdWLtFOo5Xn5rlGBIzw6lYKrhB0yn/3BeNWKT4EdIh/JAUEi/8PtV/1Y9Q+0WdTR7fu0BJ/0uZFN4+4Dj1tNbmcYITKKbdIzcK3ogCAEeXRu+xzuGOK7R6DKSPxaLTe3vubk5LC8vI5vNolAoWCo6T/XSMhMhPdKDJaQJ6pB0BPlIlF6vh52dHSwvL1uJANp3N6FxXofDIQ4PD7Gzs4Pbt29jaWnJdBJgOvKGoBowCSw4PT3F3t4eyuUyHj16hGq1ilqthtFoZPq+rqHSM1sUoKP91Ouo91Cn8HzV71mfxaMyi7qW9hWYlM9RWeftU34e1bgHqX+zIDv5B9NCqbPxegI8mr7o95yft+ucjhzHcDg57IJ2Atea9UEXFxexurpqp0UTZGTAAO8l7yLgSnBW14Nz6/u6uLiIjY0NjMdjPH36FM+fP586wOd17Y2Bp4uLCxvY8vIyisWi1ZAhuKSgE/NC2WlOnBJUlJdAr1fFRlsU0+b1Ch7pu4FwMU31aKmQUFBF36H9peFAbwbzOZeWllAqlTA3N2feLi8Ao7wRfmPwvRQ8NJQ06ifkPYx6Zqip4kMBpOCFzrPvVwjoCwkB743h5iHTII1RsNAw4hGOmUwG1WrVCrjdJM8cQ35PT0+nhLUqP/xcFW4CaN67xAgjpUPdO7qfzs/PLf2KIdKsiQHAPqMHl1FJ7N91jeuTzWbN464eRfaTkSh6GgIR+X6/PxUKrsalN1qB6fpQfqwUiMocQ8qb7n0fIqzj1veqYqSf+ftCQJRvHJ8aDwpOUACUSiVsb29bvQjSvQoW8loCToPBAKurq8hkMjg/P8f+/r5F5HjBepMajeXbt29jdXUVOzs7puDS0046BS5TsQgOcY8Mh0NT/L1XKGRgsE5IPB63eh/lchmbm5tWX4j7gqCQpq0wrYtprFoAmjyZf1M5SCQSyOVyWF9fN6CNNMw1psFLsITKN/ca19uPJ+p/XXP9zXnRFBDSF/mxKkVU0L281pSVUFNHjQdrQzxGZV9IxihfoBIHXBoE9NpSEatWq1hfX0c6nUa/37c1ZfpitVrFzs6OKY1Re/aP3brdLiqVitX5W19fx7Nnz6bqqrDRkAOulie4bv5CgA8/9wq8jz7jNSFjgv0gXVGZZT99elOUThNqGskaj8fR6/VQqVRQLBZRKBQwPz9vqYhR3vFQ0/d7gJlyju/jvFznmGEL9cG/k8AW9yK/iwIBVJfz+q4CBarvkr9SL11YWECpVLJSAIzmAWBR5MvLy4jFYqhWq1Yn9CZFzjJSulKpWD2Vf/zHf8Th4aGBB1w/pgzpCVA8SZQpMJyjKMCHET+cJ36mzi5vV1y3/koznu94hz3XWPVuBcg0UkSfpxFdfC6fFQWW6rjYuC90/7PQN59BoI60x73PU+9mZ2et/if7SINdZaXaYLFYzOS8gkDz8/NYXFzE1tbW1Gmzo9HlaXcsM0K69rzQ8zHqqAou6/7jD+X9xsYG0uk0Tk5OzC65Cc3TU7PZxPb2Nvr9vtE5T0BlpA6dZEy3m5ubM/203+/js88+w71797C6umrOfdUHSFPergaud2Bo83xd6c0HJ7B5eeV1lSgb/TqwPsp54HUX7jPq3Yxuog1Ou4q6Op2n7XZ7ypb2TgxgwofUJo7H42ab6RpTRuk41RlLnbTf71sZFtrJHIM6ezk/aleGMojYF+1PIpGwKKp+v496vR55wE9U+1oRT61WCycnJ9jc3MTy8jJKpZIxAWWO9Kr6SCUuqCeqKEMppCDpNaokKdHrvfosVTL0Gp3sEHATMlq90CLTZ+QJvdXpdNpyiGl0eAU+tHl900Wfn5+3nGRN2fHC0z/Pz5EfO78LeYKUOYTmV68JMec3+YzpQvV63WiKBluhUEC5XEYicVkwlh6Vm6Igjcdj9Ho91Go1XFxcIJ/Pm/eaTCkWmxw5rQo9Q2IpMKjgUAmOx+NXjkclos7cbYIYNLrIFGnA05DlvtRCsFqAz++Jubk55PN5pNNpKyZJ5Yt5+BzfaDSaiuIheNlsNq3mmTL1KBDWK3Khva/95ng03TT0/Kj94I1kfkflPapFKZ2cR84LDWRgcrz7aDQyYKJSqeDFixfo9XoWHcax8fCARCJhXkimbt26dQvlchnNZhM7OzsWLRSlZL7NNhgM8NFHH2Fra8tCkRcXF7G7uzslP7Qxsq5YLCKTySAej1tUhfLyqHXQmkWx2GX+OgCsra1hc3PTgJ5MJoPRaGSh/TRmNbSa61Gv16ei0dToIT0xz5+ptqoMMh01lUoZQEva1bQFf1pSSJ55WvZGtX7vDWaOh8aDyj3SUMggDu0Vb0RrXz24rM/zfdbrVd7x3byP3jneR8XNgzKxWAzlchlLS0s4OTmxSKKb1BjJsbe3h0ePHmFzcxNLS0vY3d01eUGHFQFZTbML7ffrQB3VVXwEm14TAkSiHATcD/R4kh68/uf1uCg+ze/1/dyLBwcHSCaTlpaYSCRMB4oCEkLNj3t+ft6epwCf30M6/tcBDryWRjrluUaBhPZq1Bii9nMoMoa0QxmvzyBfjMcvo8iXlpbMYUoH0U3aJ8PhELu7u/j5z3+OUqmEDz/8EN/85jcN6EilUjg8PLSoQfJw8gRGz9MID8lr4GqtFU3h9jaK10W0KZ14/qbXeEAzpIPo80iTjCKnPORe1jTiKGdiaM9F/U1+o7RLXjQcDk1WUY6cnp6i2+0il8tN1awsl8t2EhdTFNkXdU62Wi30ej07RGJpacm+JwjC9y4tLWF2dtYKIfvIR+4BNdJZK4wy2+vjqksMBgPTz0aj0VT9zJvSlD76/T6ePn1qkUvZbBaHh4fG1/r9vjnDmLZKQIEpWO12Gx9//DHeffddpNNpc8opQAhclS9etnP/eFrzdq6neQ+aUrZr2hltfZXxwGRvUC+gHatAb2jtQvvBOzMJdrIshNILD2bgM+g4ZRABZRWDRFgMXPukpRqAabmuAK/2kxgAIwIJHinYzP4z+Ie2CO1HdTYxUEHtabVD2Z/hcGjOjFQqhaOjI1Sr1a9ddP9rFRdvt9s4OjpCo9HA4uIiVlZWsLOzY0TNRaKnQRUkBYfYVPnR70IGMBlLlDD2ihQniROoC0Gl2zN6r3y/jsmoAq2GEImC81apVIx4Qh4THXNIsKnQ44aiAulRTG3q1Quhuf6d+mxV5PneKGbj5zBKoYz6PBabhBDqxqRCy2MbWa1/e3vbCgR+XaT1n6NxXpgeVKlUsLKygnQ6bZFcvI5pPWpYjUYjK6jIiCJlTvTecw140gi9PgSYRqORGSZqVNJTRC8gjzPnOhAtJ5KvNJVMJlEqlVAoFCxHHID1N0SHwEQBGAwGFqHg91xIOfJGje4x3kOmHwId2R//bM6pMuYo72OoL1HGlv+e32l0iQdlKbBKpRKSySQ+++wz1Go1U6IpHAAYgEgwnyeSjUYjo69Xr16hUqkYoK37+yY1emz0pDpgko6dzWYtkpH0U61WkUwmce/ePeRyOTQaDYsGocLqeZry4/Pzc6RSKSwuLlqUVLFYxPz8vKU1NptN1Ot1K85Ig4NRuwpsKJ0TFKByQBolcESP0507d5DNZtHpdEwG8F7uT63xNBgMLMoqCtj08vI6o5uy0TscuE986i3lhTdYQ33xtBYyWFVR9Qac31cq+0MGOddAFSeCHvTw6rtSqdQUeMdnhvSRt9FOT09Rq9Wwv7+PO3fuYG1tDcvLyzg6OjIAH5iOgtFor5ADy8tgP04PLnq+p4q/PisEckU5mvR7IFyLio4CNRr9WLjv6GWlktxoNADADEdVurVd58zTdzJSI5lMWjFkGhgKSOgzVa/S9/lxqKGkqUq83o83tNdUn/VN11qBLUZoVioV7O/vm55OHYIyKJ/PW+FbOqduCvDENR0Oh6hWq9jd3cUHH3yAu3fv4vDwENVqdYr3MHVK5aCeIMVak755UI/zzQh1OtT8erF5nhaiuSiAJ/S/OjeiDH19h+oaoRbiAaH38tmaPtvpdEwv4T4Yj8cWkat7iDVG6RwjiBSPx6cOCAjJEjorx+NJairLS1D3YbodAGxvb2Nvb+8KwKp7i/uB4FSxWMTFxQW2t7ctFV6jTiibeYBOoVDA3t7eVGHxm6BXhehCT6EDJlFwWg6Ga0La5t+MHjs4OMDCwgIWFxetBpS2kM6uckflq66vRr8qn/bgqr6HNgz/D+nb3hbWFDRGz0U5NqLAWb9PCbTyfdQxuAeoX/G5c3NzlpqpY6OsZ0YUx+bHwj1A25b2GouGa7kWla+09/y4/L6go5P95rP05HP2g2moejgNPx8MBmi1WhYEEtIPotrXAp46nQ729/dxcnKCBw8eYGNjA48fPzb0VBF4KkgEEnRxuECcdK9w8ns1EBVciQKftL6GNw69QhDF+EM1QzRfnotGBdj3hyDC2dmZ5aLTkGDxcV0gbhodB5saAGoQDIdD1Ot1M9gUMVWGrgTo6wmErlGEmYSn3jT+vq7vClB5RU3HpYZ/IpEwcEWFO+eKR2gvLi5aOhuF0dfJK/3nbJy7arWKo6MjLC4uWl6wppgpwk3ByBRDeofm5uZMCaQRrFEVZLKcJxpiVNIV5PDfE/gCJoAWPR9q3HCdCXJlMhlj5DzBQT1ABJZUoSEQpqCTpx1V3D1denAoBH5SiGmEVSglkS3EP3TPhJQ57S9bCDzV79Sg4ju45jMzMygUCri4uMBnn32Go6MjWxsaO+fn5xZtRsWXedr9fh9zc3NYXFzEYDDAixcvUK/Xp/hKlFB9m63f76PRaODo6Ajvv/8+fvCDH+Dw8BCVSgXxeNxqWTE8mDTD2oJa8JD06YFM/Z+RoDyQoNPp4OHDh1hdXUW73bbCtOpppZDVOhUKXKhyxeZTIZjyyPUnnxqPx0gmk6bQ0aOkKavxeNwKG3PfeGEeZdREKW+UGarsUBnX/aNj0P3H+VYlR2V2CEwO7Se+iykRBPFCHlXfqF/Mzc3ZoQpMURyNRqY48X0XFxfIZrP41re+hWQyiV/84hd2op3XNd5mo8OFhZJXV1fx6NEjc+ipwqd8TXk0cDWCSI0Sv0Zca91Hfp34vRouofd4WqHx5k+/Uj1OQXnWbPMKvuoT8XjcdMlkMolCoYBMJoN2u21gsvKF14Fq/Ix6naa9sg9vwj85dg98s+kYFHjidarj+nv9e/gc/V/fEwKlRqPJiXDkJer4ZGpnPB63VG/VOW5K43r2ej0cHh7aAS7f+MY38PHHHxtIy2uTyaRFDZOGGY2Tz+ct4sU3nWf+hGyWqD4qYKuN+yNq/UKfRTm1OBeMXFdniPaXtP862gnxa+qyfBajlTwI7hvlAg1l1mrVMgx0Xqos4XXscyqVMh2IsnRpaQkPHz7ExcUFjo6OsLOzY4epKLigDkbVpQqFAh49eoTZ2Vn86Ec/MrCF/CeRSEwBkplMBhsbG5idnbWj4l8HYv8xm/Ib/tDuZCoybXCusepYLO9BgISyJhaLod/vTx3UoU31WPJ7ghex2OSke5VPChp5p5J3WF0HiGp/Qtf7Mi6hvnsbRb8L9UffQx2DdrfuRa03SPnGWq4EvQnS6HMVbNJ14me0idPpNLLZrIFPlIcMciFAzrRYtaWpe+ppykz/U97KKFHuc+rC1L3Yv3Q6bdGI9XodjUYjWJLnuvbGwBMVxUajgcPDQ9y/fx+3bt3C+vq6nQJEo1Q7oGHLIaRe0U/9TBdAU+q8oaogkyo0ej8wXTSbmyYWi1lBPEbPqDGvxfG4sETjGdlEpcVHU5AwstnsVEX469ISvDGjSmNIOadw4E8oYsU/2yuL+j3X2Bd903eGnhn6TAWfouC+kSlxoygSzvuWlpZw+/ZtpNNpq4PDiJebkmoHwJTXRqNhgBnXRSOTfDoNvTKtVgvtdhsrKyvIZrN2/KunYf7NlB0CEqQRhnsyYkNPASIjAiaKs38uMIncIWMrlUrI5XKWOsTrSOf0zqvywzQl7jW2EN1440j7EGJoXtn37/Dvus4jGBIyfC7vUdAh9BxvAHpjQhU7epkODw/x8uVLK06YzWat+GMikbDThrhHeALbeDy21MdarYYnT54YXVH4fh3vwx+r1et1PH78GN/85jdNkaMRQJCIXhuOgeH6x8fHpjhRUQopDmosz87OWo29arVq3htGG7HuHgBL5RmNRgbM8rlRTfmaKgv6PZX2WCw2ddoiFTXuY6/EANPKpSpMb6L8qtGhvxnZwb3JmmOMnvPOGr1f51n7xT6pYu7BXA/Gcr9yrvksldMhz52mm6nyq8YHPe+MJovH41PpWDdpX3DN6/U69vf3sbKygq2tLWxsbKBSqQCYBoB0fjStgL+pU9CBxKbrwbn2AKK263QypXt9Fp/BQqsArLYLv6N+wrVnNCcdFInEpFiqjpdGDetJFItFO4XSn2IVajpHHI/XqQaDgdXmYMS6p2+vr3rHHK/1Oi7H7KOZPVAWAgq9TqTvoqxVwEH/54m0fl/NzMygXC5jfX0dg8EABwcHaLVatr9uEvBEHYmgw/7+vp0cTP1bAQcaTAQlCSowijSZTBqvUTAHmJ5rAlY6p6E18vqtPtNnYUQBUH5/Kg15nqrOaLVT6DgBpnVFb1RrU7nigRXtK3mK/1uNUjoGaNT2ej2zmwaDgaWyA7Doe412JK2ORiMkk0lbx2KxiNXVVdRqNTx79gyVSmUq4lUzW9QWYj/prEgkEqhUKqhWq6ZL8IR2gq0EoUqlEtbX13F+fo7d3d2pyJ+bID88LxiNRqhUKtjb28OdO3dw69YtvHr1yg70URopFArmdKbeRZ2UmRE8KU6dvVwvlRt0MvBUOabrso/sGzChX8+rVK8OAUNqo/jveK9Gyet1Ol/A1chbr8PpsxU443hJdyqj+F7WXQZg0YDU6alrap1n0ifXh89LJC4P2uI7eB9P9dXgHuqPwCQwRkEyjps4BusLA5eR+dQjGOigY2U0sQecGVDRarVwfHz8B9U+e2PgiS/u9/s4OjpCrVZDsVjE/fv3DRHWEx60croyeSU+RShDAtd76RSA8i2KqQJXI39CHggv6AnCcHMRSWRdDn7nw924KRm+1mq1LHpBFW99pxcK8fgkH515oVR4VNHT6xleTCIKgXA6PhWGqvRwjnVTeEXK3xtaL85HyJOthgjnlH3W/iYSlznJd+/exa1bt6zGA2vd3JRT7VQZ6ff7ODw8RLvdNoZMYEFPmgidasYwZa4nFUEV/pzTfr9vp34tLS0ZQ4nH45ZzS4Y9Ho/NGMhkMhgOh2g2m3YcqHqASe9kmOl0GsVi0U4S6nQ6htyrIqERU5wLX0xSm1d4rtvTXjEi3XkQWUNXo4xzpTv/Hm8sKG17YBmARdOwRhBBOfZZ+YP3trCeGflmKpVCKpXCaHQZvcECnel02tZFjSx6tVqtlnk09Oemtl6vh1evXqFcLiOZTGJ1dRXVahWdTgfJZNKANtasIk+lgFdlPASuABPeQY8R6YMh0JxrPRURmIAAWpSf60V5pe/k/yEeydSgZDJpXl5VuDT6g00dB/p5lHGgAJE3bvx+IhCXTCZtvzENmAYa0ww8eBYCWRXg9N/peqjyqTKfsob72csrPzZ9T6vVMjCPzyaIlkwmLYKmUChgbW0Nsdjlkdukg5u0P9j3Wq2G7e1t3L9/H6VSCbdv38bz589RrVYNUCaPYfooaZHzo8ooldmoFEvqN9fxTOWxXi8LRYNwP1GOAZM0WspCnvC7sLBgfJNAIh0l+j7uLxpHwOT0SIKKPmUhap7poGGUmQKRfm9TSec8ksdqCwEIfh/ybxqupHldO73X7+2Q7qU0HAVexOPxK6AT23h86bhgaiedXqQxX4fkbTeOlcDjycmJpQrG43HTzxV4YkQcDcfR6DIStdfrIZ1OW/09Lz8UuAnpzAqwMyXG80KvN/B+BWy0eSOZffb6ja4tARfdK54W9L3XAbIhfZ76S+iZXrb4PnDuKEsI6OrBO+rI17pRCmwXCgVsbW0hn89jb28PP/3pTwHAnE8MFFA5EDpsKB6/PCzg2bNnODo6Mt6hzgrvFGFmAKOeb5LMAKblI3A5xlarhadPn+IHP/gBPvzwQ5ycnODLL7+0fcFC1NwbqpsqQMET7CmztTYdo6HIe+kYPDk5Mced2hRKfx5w8fLGA52e97FRhvF7pth5kEznR+ctBDTrs0Pf6R5hLVVG7hEA7vf7pmMxCGc4HCKfzyOTyWA8Hhv4zeAA8isFkwHYO2j/0ZZSBwYBsFQqNRXcQ9nudUvuDb6TdacPDg7QbDYtvZzjVSCL/dP6cnSW8SCOr6NbvTHwRCO23++jUqng4OAAhUIBm5ubWFlZweHhoU2I1mEgE/UKJzuogBRw9bQGTiaje64bXBRj1OcC02HZ7XZ7qgK9bip6ollQTCM9gIlHjkqRnkCm0SwkTC6i92zoNRyDFmjmdyEhQ+WQaL2eiqZNr9cWEi7qYdF+eiUtao45R34NOR9q+Ph6JgrkjUYjC3nNZrM4ODiYinj6ugXN/hjt/Pwcx8fHljZXKpXw6tUrSxVSZVY9tTS8Op0ODg4OLKdXFR3+0GDc399HMpnEysqKMYxisYhYLIZ6vW4pcaenp2YEEzwmE6IyTyOFBjNTBbmfGfI8NzeH8XgSoQZM6tJoRAfXObQnPb1FraFX5vg/54oGJk9Do6ITJVSu+ywKQI3aN5yzZrOJbrdrJ88xspG8gcJD30NBCUxOJVJhrMCJF74EphghQCWMiqn286btDQDY39/Hixcv8M477+DOnTv44Q9/iHg8jmfPnk1Fr6iXi/TO4o40Mmjc+qaOAIJN9PaxECQNeG+Ee4Na106VKSqnvpFGk8kkNjY2LOomlUqZ4kHaoIFHxRCAFcZVQ9gDByEjKGRcqDIJwDzPWisAgKWhALC6F9xLof2i+ytkcKn8YN/9elLJZ188kMim/IF0QFBdi8RyjmdnZ3F6eoq5uTncv38f2WwWv/nNbyydVYHLm7A/qFT2ej1Uq1VUq1XcuXMH6+vrKJVKVmScwH6320WtVjOgR8FLnSeNQiCNh5TqKAVf50a9oGw0SkK0p9EQVK5pbDIiIpPJIBaLmQLOdxD44N4luABMHCOqZ3Bu9L18N/c1x6DR3KEjonkdx0Z9kOMjv/Ggqv/bz6H2kc8KAX2h5uc2tE8UbOb8MOLEG2RMi1leXsb9+/eRz+ctVfvs7OzGnWgHTIPX7XYbe3t7aDabWFlZweLiIl69emURNJwXRgww4oNy8+joyKK9ZmZmDIDkmtM5SLpUgJx9CDm0r+u3d3ZH6ebA1RQ7dThrH4CJ/RGiBX0/7w/ZRUrrSpf6bn0vdUQdI2U2wRzOI2s5stYhgdDxeGwpbpxj8nPqzMViEblcDqPRCF9++SWePXtmslBBbQ9ChBpBR8payjXlF+w3ZZNmJWhNn5vSQuDz+fk5dnZ28PjxY9y6dctsjbOzM7MjyQ+oFxEUZwkARuawphYw4auUNdQ9gemoHZX32vxnHuxSHhcC8UONtAhMSobQsaC6tPJd1ZlCe0EB3ZBc0P5w7ynARXCH80e9hGm/TBUvl8vodDqWAu31JdIebYlut2uFv3VMuVzOavQBMBuE86FygWtAO5SBBfV63Woa6hrSUaoRjZy/XC5nTqRqtfoHOSneGHgiund6eop6vY6DgwPcvn3bwiAfP35sRjENr2azaQirRkRwoXQSPYPjNfxO/9fmhTLwZsi89w4Bk7oXZIT0jBB0ohKj4YbeQ8z3xONx80rqKTzczDQuCoWC5W42m03bxDS0/LyFxkWGQHCO0VbXAXH8PPSdzjeJ1ntD/HMUpAo1r2hxzhqNBtrt9hQgowJweXkZa2trGI1GqFarFhGkxdDedvO0e3x8jOPjY9y5cwff/va3rZghlSDShjd8z8/P0Ww2LQJGn8+moF6lUjFjemZmBr1eDzMzM9jY2MDGxgZ6vR6azSZarRbS6bSdEsYIPIJIwHThuUwmY/nJsVhsqj4EU8L0pCVGafA5qgRHrY+CUyHGpSAMn+OFiB4HS8WCJz3w/Z5WX8dLor6/zjhj2hIwbVRr7QVVdiiEdP05D+QtnGtG7Zyfn1vU5eLiIt59912sra3hk08+sZPhvFL7OsX4bTQqoAoab25uIhaLYW9vD+12G8AkIpBAabfbNY9dPp8PFhNVPj4ajSwNlSeysoiurhfrOTFVUaNyuDbqYVJQS+dXv0ulUiiVSkin02YAzc7OotlsTkUTEIRShU3rLnnFzBu81xmvauSQJim/9Z2MlGUqGkHpRCJhcpvzpJ7P0LvV0NExkTa9h1DHoyAbr9G0Cb6XxeXVMGCjHBwMLk8k4r0acs7rbkoj/zo/P0ej0cDe3h7W19dx9+5dPHr0CF999ZXVIiMP6XQ6VidOeR2fp7KYc+lpx4M1IV4RxQvV8IzSIfTZAKxGTCqVMrpivQs9lRWYRN5p43daOJr8k3oWFe5UKoVisQgAFmVB3ttut6+kDvD5GhF3cXFh9MqUA1902wN+IXCCc6vzGwKeQg7BEEjqQVryCh1PLBabOmae+43vnZ2dxe3bt7G5uYnz83O8evXK6mbeROBJ5X+/38cXX3yBzc1N/NVf/RW++93vYjwe46OPPrLx8pCWlZUV7O3tmb7DAx+Ay71EOUIghIes+Cgxz3/ZQkayTyMK8chQ+QBdO7+e+hzVtbmuSl+MlgauRm2xX57ueJ3aGgpo+5Td0HNIj0zTyuVyyGazaLVaBhSqjpTJZCwKRKPmb926ZREc7XYbOzs72N3dRafTmQKFmWJJw/06kIJzzbQkle103LHWKXBZ3+nOnTvI5/P4/PPPsbOzExnh+7aaByip6/b7fasPeHR0ZDoU6VwDGqjbDwYDFAoFrK6uotPp4OTkZCqTROlQQVhgQs9eV/H6C6/VZ/Ia/pDmrgOwuG6a0qaBFtR1qOewz0rnIXmpe0nnNbQXvQOG1+k+oX0CwIAoymw6QfksdeKo84CgFXUfAGYnz8/Po1wu20nvtOeazSaePXuGg4ODqdqJdEYAQD6fR6FQQKvVws7ODo6Pjy0whnsrm80inU5bZCIdpQSGa7UaPvvsM+zv709FW71pe2PgScMQeVJbrVbDrVu38ODBg6kwRk7i+fk5Wq2WoeG8XxsXPkpoK6OOUnBCoIcy6BDxXPc3j2nl5OsR9FxM3Zh+synzBqaFEUO2SahEJv21vN6HJPox6vv5Q4VdFXlPHFFE4kEnfa9XpjzQpwzdMx9Fm3kP6yFRADDcnkxpYWEBa2tryOfzlo7Ak++Yk3oTvBAKysViMTQaDTx79gzvvvuuAa+ebubm5pDNZqeYIdN8aFhoKLf3mHJ99/f3cX5+jnv37qFUKpnnnPuK6YqcLwBTChYAQ78574xEY0QNcGk4MGXIR9kA00UdQ4CnBy69F90r1H7PKqgQi8XMY64neDBahBEb+lzftO/83++zNzVQNbKA6+iFLH84Xs7vcDjExsbGFCjAyDiNHqUHIhaLYWNjAw8fPsRoNMKzZ89QrVav8ByO4aa1wWCAx48fY3193YqIMuKGoBNBD03ZIbhYqVRMGIaKxHJdGSpPg340GhnIX6/X0e12ra6BRh5qiLJX8BXspKBWeaXAh3q9dG9o/QuecgdM6FS9aHym0qJPgws5ZzgHfB8BGk33YaNsJX1pFFatVrPr8vm81VRRmaR7Vvuh/Qdg/IKAE/e47htez3lXAwOYKJnkfzxp8/DwcAqYJvB0//59VKtV/OIXv7CIzZsEOgGT6DnKtFqthm63i/X1ddy5cwerq6vY2dmxcTNyjKCNgoMageSV61BTfhxlJHgARI3Z1xl8fLauMSNjCT7zfqbjeWXfv0Npj/2g4UF6H41GaDQatu/4DM5dKM2DY9Xxcy8zop2pE95h4uUY+xaiaf7v5zhqffguvc/rWxrlSwCu2WyaLKGTk/OXTqctirzVaqHVatn8qYP1pjQ//oODA/zyl7/E6uoq3n33XUudHgwGyGQyUyfYJZPJK2nT7XYb1WrVdDACdXyPlrZgU54V2htq0Ib0dU8D/Cx0vdedo+aDUVnUx0ivGr3r+d11toR3pPAafqeRyN5eIX+iA71arWJ9fR0zMzN49OgR1tbWrI4YgSca1ZQrCwsLODk5QaPRMH1AT8wirRMQ9ql2UY18oNfrTaVfAhMwinPDdKNsNotut4vnz5+jXq9P2Vo3sXE8tVoNnU4HH374oe2Fk5MTC4Dgtaofj0YjSzstl8uW4cC59UC58iHl7SGQU38D01HSXvdXW99fo6AMG0vZENRRZySdGQpqRukpug91HNo/b9d4O1kdZ7S7qMfT8cm9Sv21UChgbm4O7XbbaJvPpd7KGtEERxcXF5HL5SwbhZknrHt6fHxs4LoCydQrE4mEHabDk4B1fzPwYGlpCXNzc1Y7mDblvXv3sLW1hU8//RS//e1vUavV/qA98cbAk3qCeDrRyckJNjY2sL6+jtu3b+Px48d2zC0JiNcyPIvP0kX0YJO+0xuxarCGjFzvjWN7E++/egE5VhIMNwO/Cyl1KoTInFWxUuGkSqI/mU2NcL2HDJMKvAo1fqbh6OyD3+Aco59PHYNXSv313iMUmgddA//9+fk5arUaer0eMpkMgImniQwon8+jVCphfn7eitYxXJdg4E0RBMoo+/0+/umf/gmzs7P48MMPAcDCKjOZjKWL8NhSYFp51tpPXsnhOxgdMxxeFqkm8y2Xy3ZUfKfTsbliTQTWEWJtIBqEjKohzV1cXFhdKHqUiYCPx2NTAJh3HPLq6v6jQe+BVaWPKLBHaW40GhkYpieN0BtKJZPgk1e0PB1GKX2+H56O/bp4ZdErkMrjyB/i8Tg2NzexsbGBk5MTizqh4FJhQcCCSsKLFy8AXB4prF680DhvWmu1WnY8MU+N+eyzzyxijbyPqWG87uLiwgpm3r59G4VCwfYVMA1ypNNpi6ro9XooFAoolUoW/q+pNhoBQc+nOhra7bZFUrBGDNOmdd+yEURIpVJYWVkBAKu71m63DQgDJodYeCUu5GDQvQOEDV7+PRqNbL+enp6i3+9PgWC6VxlhSQVfx0R50uv1LAXd89zXgU7ABOQGpmWPB0pVAaWnjzKB68NUoUKhYCn+i4uLyOfzFkr+3nvvYWFhAR9//LF5rP083ZRGnq/GVjKZxHvvvYcnT57gyZMnpiBS54nFYsYvcrmcrQ2AK7oHcNUw5jxoxDmf7+mMLWREqxHH70KpOLFYzCKZWBvQ61v6Hk9LIT5Oncp/BmAK1CLNKtjJvnq9JxQBpnzYO4D0GVGgppd5CvSF3udlCN8T0mf12RxnrVZDq9UyhxKBJT57eXkZW1tbiMViODo6QqPRsEghBaluWiNtjUYj1Go11Go1LCwsoFgsWm0Vgv10dieTSatXw6jLi4sLHB8fI51OY3NzEw8ePMDR0REODw9NR/G6wOvAQtKBgpGqW4cAST4nCgzy32sfNIsiHo9bGiv1MU1h03t98/vMR7Rwz9BYVgBOm+paw+HQ9E8AKJVKWFtbw/vvv29zRAfyYHBZdJynJx8eHlrad8jGUiftm+o58XjcQCfKfu4pdTyRb7L21P7+vhUW9/zpbTdPM9Qf2u02Xrx4gX/1r/4V3nnnHezs7ODg4MActd1u1/YG07KAyYnDrOuqNZpDEZCqB5Pv+PXS31x3b78D0wfDAJO9pLqN16/Jq6iv6QmGrKmrhe6jbAs+3zfdp7yf79A5UFve950/emgNaZGlQTKZjNHbcDg02tc0SNpeBKq4DwkOFgoFjMdjW+tWq3UllZy6FHkGT05mYXDKZtZZZbYF9+pgMMD6+jo2NjYwHo+xt7eHVqs1pUt8nfa1gCcuAhVZHr+3vLyM999/H5999hkODw+n8j+pnDebTaTT6am8/RCK7Bm7F7bXGaj+WXpf6G8/PkXV0+m0ReUAMK+SMrvQ/95o1e9UwdJNGDVO/TwkuPTZZA58rh4RrPcpqKUeHC8g2TySHWL01ym4Gt2inkbmuKrRo5Eic3NzWFlZwfLyshVqIyBDgygkAN92I82fnp7i1atXuHXrFtbW1uwEM46Rc0RGosybkTuxWMwiX4Aw6KEpi5988okBwWtra1aMvVqtThWu7na7VsydUXc09OiNpsFH5Y3pC0xXYJ0VGrJsahh5Q5qf+2KwIdDGKz8EX9R7pYYE0XqtV8MUJxV62kKKmVcK9bcH1rwRR4NZFVCvOGrECo8lPT09NeWf12pak3pDKEyZLsZC+yGBeFMbFdNWq4X19XU8evQIo9EIr169mqJpRkAyvRaY1CPqdrvI5XJX6In/M7KB6aJM02LtstnZWXS7XeOVjPRZWFgwryf/Ho/HVkOIIC1TmZWfc30YyqxGdqfTQbvdnipoC0yUGvUih0CnkDfRK3oqFylntSClN1ZVBnEOmbarp4xSAWKKm/cehloImOX79V7v+NBx83P2jQY1eRK91VwTBaxYc/Ho6MiO6r6J+0LrtJyenqJSqWB7exu3bt1CoVDAw4cPUSqVUKlUpmSepn6R/4WAFCCsEymY6XUqzytD+pYCTKo/aHS6OttmZi6LmdKJ5J0VXqe6bgz6eSglSvvDvqpOxc94Pfvh5RjHoZEVlJFR/VFZERUB4PvOaz3Q5O9VORLiC/F4HM1mE/V63QwlOp3YksmknVBLo5+6PJ1PN72Nx5e1WY+OjjAajazGyfHxsRnK9NYzSpvAt57ktLu7a3pDLpdDvV5HvV43fuNlqrYo45n943fq1PC2QRTopPTr+6DgjhrGemQ6AThNZ/Z2io5J9xz3rIK2TPvxehTvU71M0/Z40FGz2cTh4aFF/icSCYvsZP9J0x500PFrVEsoE4TgG+ebnzNLR/cBeSeNf+oZXLfj42O8fPkSx8fHU7LopskPNvIxAmb7+/u4f/8+Njc38fHHH1upBk29U9tiPB6j2WxaeQKW+gjpuDoHBGo1uiaKrj0P9v3XvRRyvnF85+fnUycSM+JP7/Mn9sXj8akodO1XlN3Bpjq91k/kd9pnYKJ7qS3L76jrt1ot2yfcX9RDuS/0VPRWq2XrxUOhUqkUFhcXkUgk8OLFC7x48cKARdoOlLMqMxQkV9moKbAq52ZmZnD79m1861vfwt27d3F4eIhXr17Z/P8hetUbA08UkqPRyBb+8PAQ+/v7WFpawt27d/HgwQM8efLEiJuMl4MYDAYWPcEOR7XQYPz1IWINKcNRQJA2Vaa58dQo8LWWNCJBn6tAje+vV+ioKHtwx/ctxIQ5Zn6vodSJRMLqUxEo9GBVSNm5bj3Um8p3esCJ4+d3nFMNgeQ9RIFp6DD8j8I1mUxifX0di4uLVi+METwEPq8zfN5mI8Czu7uLw8ND3Lp1CxsbG9jd3bUQcCLzTBkisEB0W5UHhmySvnnteDyeykvudDp4/Pgx9vb2sLW1hfv37+Ob3/ympTPu7++jVqtNRVcAEwCLTJRMW0HLfD6PeDyOw8NDbG9vG/CknifSIZkYGa6GMtPQ4d7xdMG/1SjQQpT0kvlaCloX6/T01EK0qexwXUIePe1DyKBWoeeFsP72SmaIxzB9LpFI2OkXPNWNngd6b2OxmHlvUqkUTk9PkU6n8Y1vfAObm5v4p3/6J+zt7U0Jlz+Fdn5+js8//xzZbBb/+T//Z3z/+9+3E/oY0stQZZ/iEotd1rhpNpsGKnI+vaeeyii9mppqpifaEcSjokIDGpg2Dr1hSLogz2P9M4Ypn52dGbiey+UMEKMM9carX0M1LsgXVQnycoP0zWg/PSKXz44CenTMs7OzSKVSlrLDRmVV59k7GrSpocR3qDKmwCqfxet0Hig/CLKShghmsOg8HRIPHjzAo0eP0Ol08Mtf/tJCz2/i/qDByDRH1nk6OjpCJpPB4uIiSqUSFhYWrI4dZQDpWmUA5X8oZVNTsqJ0DHXmqAHs5bu+K6SX0Dvs96X2SxVhL5P4fjX2QoZLSEf0e0kBYt9COg/H6vkqC/C2Wi0Dw0OOwOuayhLVE1WH47hUVwMmc6f7Sh2IZ2dnqNfrOD09tfpFLLrN9/CkR5aQIF+kkUL5fVMNbAA21v39fVSrVZRKJayvr1tqMOsBzs/PI5PJWGQHAWlGGLTbbTx79gwAcO/ePWQyGZMFId2Wjeutpyoq+ONBKbYoPT605/i3Po9/0/mip2WTLzDdjiUR+Bw6cTz9+P5pHVvKSADBqGrVV3q9nkVgAldryLEEhM6f39t+jf0aUA6oHGc/qEdz/HwedWWCiQq4U4Zz/i4uLuzwEp7ezPGEbMib2KiTNxqNKXv77OzM9AKmfBWLRXOI0VY8Pj5GsVi0A1m8TqW8lLTk9QHg+vkK7S0PavrrudYsUUC9hqCTyjbl/3Sg8ToAUxFcob0ITIOc/JzvI+1wfkI6EG0QniTOsjK0XZnlRD2fti9tPuqH1Btp9yaTSWQyGYve73a7ePnypdX1olOK/DxUO4pzQHyDe0sPaGEgCPdUtVrF/v4+yuUyDg8PjdeqTvx12hsDT/1+3yaczI+duX37NlKpFJaXl5HP5817z2tnZmauKP6h2hzKXL0S4hVsHagidjoJ3qul3j0FRtgnBdd8rQ+vbGlILT/3/dF3q9HNa0JeMb+R9XMSUEg5Uw/AcDhEs9k0xV77FeVx0bn3QjN0j1eK2BcffaC1VuLxOIrFouXdMxSXfafXkUDH8vKy5cgy3I8h4TftRLuQQtztdnF4eIjBYGAnsNTrdaM7RdEp7C4uLlAul/Hhhx+i3W7j+fPnNie8h/vQ03kikbATFB4/fozt7W07Pezi4gJ37tzB8vKyIe56shrBL01bIq0vLi4im83i+fPn2NvbM6Vb9w+bhlxz/b0iyzRJnTfSizJ+VSZY9JgGFDCdJgJMlBOCCTTUGM4a8myQ1kPGid+rbAow8Xv1kKsAVLrWRjCx3++jVqsZr4zFYga4qIJLT8fS0hJu375tXo5ms2lCmX1hu4mGNpvWCdza2kI6nbYII/JAAgsADAChElWv1+0ezq/uAdIhgY14PI5Go4H9/X3cu3fPQoY7nY6tg08HoxJLvk0vqXqylUYI2GQyGdtLvV4PuVzOUv88gBV6jvIFYAKgkc5CqUlca3r+tEg4r/HOA9/4HPaTEYPcUxqtR3nmmxoD/tkcI5+j6eJ6jSq27AvTHZlGSeCKvIg1Aufm5vDuu+9iZWUFL1++NMP7pgKzVEDVeD05OcHOzg7K5TKy2azVOWS0HI+Ep0LaarVQKBTsFC/KC9IJeTWAKR0uBKSGjFIPQHFvKK/nHqMsoRHLPUQl3hum2peQl1t5rH8XP9fGsXojX2Wl59HAZL+r7kZjlHNEBwgja0P98LqSvkPHpf0OOfMoN/zccI7VsOf6sG4HDxxhbRG+L5FIYGVlBRsbG5idnbWoU56YpCfV3rTm9enBYID9/X3s7e1hZWXFwFke984Il0QiYbVuNBqH/OLs7Aw7OzsYjUYGUo3H46nILwVG9X5mRRCg944EIJwqR3mivI40EFUqhNczepaHYTAKQmmKPIKpM8DkxCstxqxyjH1lfwje8L1Ko2orUB4RuFBnvfLx1/Fe5Ts6Z8BErxuPx1dOggYmUWw0ptUWor6YyWSQz+dRqVTMoOYJ7QTpqG/cvn0b8XgcX331lfXrpoOxui4abKDgI9eLJ6Z1Oh0DQ9SmDcnkkF3oeSubAh/+upDuFNIVvIOaupSe+EvnNuWQB22BiT5FvsjMD/I6BX1DffU6mAYA6PXadz3AJpVKYWtrC9lsFicnJ6hUKmi1WhZdrydhE2zSeeGJg0tLS5ifn8fGxgZSqRTq9ToeP36Mg4MDs6Op+7GF9DWuC/une5n8BJg+zZn84uLiAvV6HS9fvrRghj90T3xt4IkvovK/v7+Pw8NDbG5umneOebocHL1fDOdlHQ+mK3ilh0SnaCh/h5QGZbohIEgbCYYEqwqGIvEa1q4GsUfyta9qTEdtSjZVBtVr5a/3Iel+83smwTFSkfLzpI3X06jwhoC/1iulHvAaj8dTxJ5MJs1wjMViyGaz5lkajUaoVCpot9s290rI2WzW0lU0TUXTwG5a8+s3HF7WXzo5OcH6+jpWVlZsH3G+GRbJ9BGGYp6dnSGfz2NpaQn1en0KQAwJCNKoHp/c6XTw+9//Hnt7ewBgKXjr6+vY3Nw0QIch9gSaFhYWsLq6ajWe5ufnUavV7DlklAAstFlTesgn+BkwiVrgj4K6flw8FpUANxmfApvAxIhSxknFkUZOr9fD2dmZRZF5AEr3jPbFA2Hsq/adY1XAOkQH/IxjjMVilirUaDTMYGZdEp4I02g0jD54KszGxgYWFxfx5Zdf4quvvrJ++70bMiBvUhuNRjg4OMAnn3yCcrmMjY0NfPDBB6hWq3a4AwU/w/OVRxJ8TiaTBrbyeuWtmpLZbDZRKBQAwIppq4D1KX583vz8vBV17Ha7qFarU9FR4/EYyWTS6qGxUenRmhs0WKigqEEBTE70Ip0yooX8QkFbziMblQbWNFF5HbpeZYrn62z+JDpvHPvnq4wOOScUpA0Z5h5AJSi4v7+P4XBogAt/CPixjzxJsNVq4Wc/+xmOjo5utNGgKfKse9Jut3FycoJ2u41CoWC6VaVSsWjyROKyBuJwOLS6YSzYT0XUg0t8T5Qe5UFr0q9XxvVa1SH0+G6NcuXzVIf0PFjBHh9FFTICQk2dId6g0ObH4J+pfdbo2na7bSenRT03tD9Uf/V94OfqpPD9VqcTr6FOfXZ2ZoA3MDH6KLt0rPPz8+YAG41GVluHenqv17tWB7wJTftWqVTwD//wDygWi1hfX8f6+jq++OILc1zyFGE6MHk4zdzcHAqFAmZnZ+1U5d3dXSwvL2NxcdH4CjAdzcz0Xfaj0WhYvRYFyUO6cmgMup4+koRN7Y7hcGh2FXUd1WcUKOIe6Ha7pqcQcFDA3gcA6Hupz2sfeT0jg2g7aU013dOcw6hAAq938XoPPIUcBwpIMWpP14zP532qnxHU4D3kO5ubm7h9+za++uor7OzsTO2Hm6pTeR223+/jo48+wje/+U2sra1hc3MTL1++nAIT6cCnnkP9nzyFgKW2ECiufeBcE/AlD9KAjxB/06YgLzCJHNLTfknLBFNVp9B+6tyQdlmrkhkELLHgaZApeZQplFvc6xyLNp+Gd3FxgefPn1t9pK2tLYxGI6sblkwmrXA4IzKBiU2VyWRQLBaxtLRk9fp6vR4++eQTvHjxwhyL1A2Vvr1zjynIvEdPkT87OzMQLxab1Irmc8/OzrC+vo579+7h4uLCHHoaHft1daw3Bp5o0HJg9JDU63VUKhWsrq6iXC5jbW0NL1++NA8DU4Xm5uasRgO9czROfbSBR/08wwkRbkiZ8NeSWJjiwuN31WChskGhpUStHjFP7MpIPUp8nSBSwMqHWnvjnM/STc2NrR7EUJ/4f8jzQCWeyLJ/33WMQg10MgZGOZXLZTOyYrEYisWiCfxSqYRSqWQMz4MRzM0nOk1vHo0v9QDehOaVCTamTty6dQu3bt2yE7WIIBNwYtpdPB7H8fExPvnkE6ysrJgCH1o7r9jSaCUwR2Odeeq1Wg0vXrywU2BYgI+hqgRjNUeY4eiVSsVCydWblUwmzRjUdVFlSA1NBaOAaXpljj4VIzV0vaEDXAWXqYj4Y5EZAXh6eoqlpSWk02mbfz+nvv/cXwqQ8z3x+KS4tHq+Kdj1mfo3lblerzd1Ykq32zWwdnZ21hTMROLy9IpyuYz3338fg8EAv/3tb3F8fHyF/qL+v2mNivuXX36J27dvW1QdI/9oPNFry1Bj8pper4eDgwMAQKFQmPKiqZFNBZsAEPnIwsICYrGYRc/kcjnzSNFTSCHNouIsxsg9A0y8TATAgMtC4gyJ5n5SmmQefuhUTuXd5Kc0djyvU/6stUuoYEYBSt4o0N9qvADh2md+nv3nUXKGawLgSu017jMqMz5ySh1AlA/D4dDqcXG/fOtb38Ly8jJ++tOf4kc/+pHRjHeQ3JSmtMootW63i/39fRwfH6NUKlndPp5gynFTGX358iX29/exsLBge6lWq9kpkUA4OjOKTwMTR4Y2jSbid8Ph0CJs5ubmzDk0Ho9NHun9qpgrCOYjL9gHyjNtquwqrZE2okBUdXz49/FdHlzjPtK58XqH/s2+UZ5yrUKgAq/X/npnITAxaLhXGMFL0ImOpOPjYzQaDRwcHFj0pvKBZDKJ5eVlS7PrdDpWg05TsW5aC4GT1N9///vfY2VlBf/xP/5HPHz4EM+ePbN5obNLQVp6+7WIMmV4r9ezNHe1dWhwUh5Tj6GOpYCoN8K8LQBM81LvfA7Nfzwet9qcGiGpkR4hsFZpazi8rIvJ/lJ+EShW3Zv98wY2x04DlREoNGi9nsO9qHuK71CAzMspT/u0A9QJr3POKCh1AiqfisViUymUlP1MSZyZmbHSHeVyGePxGE+ePMHJyYnZJje9KWg/Gl3Wy/zd736HtbU1vPfeezg8PDTgn9eTr/BeHvjgwc7Qu3QtuB6UGXqaHDDhcUwPB6bpzL+H639+fo5Wq2UlP2jn0ubw9q32T9+rTcuXEIBR+mfTeVF5E9UYkT4cDi0bh86B7e1t1Ot1rK6uYmtrC5ubm6anEYMgTZL/EOSOx+OWOXN2dmanLAKwsgd+32l0M+eDfc9kMlhZWcH6+jr29vYs24IngOp8UkeNxWJYXV3F4uIinjx5Yocw6Fx/3fbGwJMCIZwsHnF/cHCAu3fvIp/PY2NjA4VCwU7uGQ6HVrxvMBigXq/j+PgYd+7cwdLSkuVsKtNVsEkN69d5EVRZ8t47Ns19poeHCpUi+37xVEEOeQbZP16rjNej97xPFeGQYqjXe+BLx+UZuxoTFBwh5F/n10dIqaLD6/S3fxfnih7nXC6HxcVFY/q5XM6OTU2n01hfX8fS0hIODg6mCqzyOUzzII3VajUDI7yQu0nNz32v18PLly/xwQcfoFwuY3FxcSqKQRtDQRlNCODKNaH38V1k9mSqGpZM5aXRaFgapkYOJBKTo8sJ+JAuON/eAFBAhh5VBXQoUHgfkXT/nHg8bgoABVfIiNB5DfEE0oTWzKL3H4CF36s3R41e8g81aDg3/h2aMkKvI/kdDSrd334cGo3FsaphpEotDdKNjQ0sLS1hZ2fHaukB4ejOr+uBeBuNyn6r1UKtVsPa2hoePXqEbrdrqQJc31wuBwDmEKCh3u/3LeVOw7MV4NSaDycnJ9jd3cW9e/dw69Yt1Go1A/Yo+Hu9HorFIlqtFsbjy1NDNOedyjrTvjgW1oQgP6NnLZ/PY2FhAdVqFfV63QB0pQtNv9C0HzbuQ9KW8nzuGyo8oVSjkFwMydLrZKw+g+9X54zKDJVzIUNG9xcwiUCjI0rBIi10zuiO8/NzHB0dodvtYnV1FYPB5elu9+/fR7FYxM7Ojq0f203cD7pPNVWE9c4uLi6QTqeRz+enQFnWGSqXywCA58+fY3d3F/l8Hu+99x4KhQK2t7ctRZX82xukUfLcG518Bnm+9lvXU2nSg04cY0hX8UCS6lTqEFTaYp/0f3WMKI3yOy9X2Gftq9K1dyL4NdN7dN4IBlD+qS7I50fRpneujEYji/rM5XIolUom37PZLNbX11EoFDAcDlEqlawWGuUI37ewsGBgOOUPownIW25qU71KeSZPeG00GiiXy1hZWcH29rbJCa7v/Pw8crmcRVDwFOD5+XkDkagfeFBH15AyJQRwhgD90HdspAFPl3o9nXB0mACTNH2NdoqaL/8/ZYvuK+pLqqvpteyrRgeFHMbqJPD7VPe1lzGhMVA/pSOSDgbdtxrlERo/ZeFwODQ6p65J8JKRgr1ez9Kaa7Uanj17Zo5LbTfF7vD8W0FZgoKff/45vv/97+P+/ft48uQJ9vb2pqJY6LCh3aA2qepMvqnuofuBQJZmz4TS8bWpTNHmM444TgLGLMER1T+dJ78vx+PL1DvyVLV7OBY/PtI0n68OI9UJta4mHY6j0cgOfSgWi1NF9mOxGDKZjD2TNmOj0UC/37doZgbIaAAQdSXlc9TBtO/KS3g63nA4RKVSwenpqdmdDETgyY9cx3w+j5WVFcRiMRwcHKDdbl+RgV/X3nhj4MlPOnOgz8/PcXJygkajgbW1NZRKJUs5IBLebrdRLpdx+/ZtAMDR0REWFhbw/vvvY2VlBcfHx3ZqCxdTFaSQsalNjUX+75E/v0EpbNRIVQLV4lvem6CM228YMjoVJgraEfll03Fp3xUk4rv5Ll+3KaREhgSgfqdGdkh58wxWBVVIWKpRUCgUUCgULOd+ZmbGop3i8ThyuRxGo5GlyGikDAArfJfL5Yy+mG6mwIYf801p6vW6uLjA/v4+Dg4O8P7772N5eRmVSgXxeNzC4mmg0thm6DJzhF8HPgETutaaNCGPhTI4MjLts++/j7rj51w/GoyxWMyEOAvFK/Pmszxdafi6j3AKKWve6A6lbnDsjLajosn5UONWjasoWlJlJxaL2RxrHSEajMqDFExgU0FB2lceo8/kfaenpygUCnj06BGGwyF+/vOf2wlwTBf7/yME3lYbj8c4ODjAT3/6U2SzWfz5n/85bt26hWfPnllRbgo/0gn5NhVlCuWtrS0TjvSSKViuxmWtVrN8edb/mJubQ6lUMhBjOByiUChMFd5lRBOBEC3Qy/VkpAFphTVGEokEKpUKTk5OrC9UPqjwq8ziM6gUetCWdE4FIQRW8To2T4te9ngZqU4LIBxBy/9DYID+9u9XBYq833sjeS9TWsgzeQ9/SP+rq6vY2NjA4eEhvvjiC5ycnACITru/CU3nnFEJLJjearVwcXGBXC6HpaUl5PN5tNttA51evHiBwWCAjY0NFItFbG9vW22o7373u7h37x4+//xz7O/v2wmOfs29wQJMR2EDV+t2qW7GZ1GWaBQBP+dvNRbV2afXaTQDm9fr1KnBvvAeb8zzPh23vkv1mhAda/PGsgdV/bqq4a6fqwyIanw+ADupjMXm6cTNZrN2SufMzAxWVlawubmJg4ODKccvn8fMg8Hg8uCQWq1mzlcfiXzTmqc5lQGHh4fY29vDt7/9bWxsbFiaKh3MFxcX5iTIZDLGrwGYMUbdiToXEI5M8gBpaA1DeksUQKTvUXuHOkC73bYIee4ZRtxqdEpI5l/3TmBiZ5GvUr6Sn4YcYsC0082Dqeow8PJXx+ib2mjqEOW1Hhj28x6Se+QTBFlHo5Gd2tbtdk1/JZh/7949ZLNZ/OQnP8Hu7u6UTXLTmncgKLDIffHVV1/h17/+Nf7mb/4G7777Lg4PD602GHUYylN18rTb7am6V6GI01BUjYKapFNN8eJ8st8hu1y/YwACQWQ9cU0Bdb6fzesnXufhd9S7aLsywkdBN9WDgGk6XFhYsBM1yWMo4yjnVM9hQIH2a35+HktLS1PAN39z3lWX5L20uzStPQT0ss/cD6enp9jd3cXe3p6dfsqIfkaR0z4CLk85Zqr/9vY2nj59OhXQ4Of1TdvXinjSBVQvCZE5npaRy+WQyWSsEFi9XsfBwQG2trbw8OFDZDIZtFot7O7u4nvf+x4++OADvHr1Cjs7O1MFXkOeghD4pMawKu4aIaSblIIWmITIKSNThuONFm18nlfMfD0b9oWGIo1NKlmqIPhn698eEKICo+/3ypMfm4JHfj7JpClYtU/+3Qr0aR89UDE7O2tV+MmICoUCqtWqKT6cA64RC/TG45cFgY+Pjy3cUg2Nm9ZCRtx4fHlM6e7uLt5//33cvn3bivLrKSMspM3GWh8saAe83oDSNVCD1H/v5y5KgWLTddb1PT8/R6PRsO+0hgAFjjJhbfQ0aC6y1tPw7/b7k89QI9kbMTMzM5a21uv1AExOovH7QkEor8SxXwzBV+CTY1PFy8+ZH4/fp/x/PL4MYyewrwDi1tYWbt26hePjY3z++efodDq2R68D5W96GwwGqNVqFt1B0JpF+TVygrUBKczpSWIk39LSEhYXFw1s5P2cG+6ver2OTqeDs7MzbG1tYX5+HvV63Z47NzdnKSiM7AUuhT2jrIbDoXmh1CvLz1m7bmtrywC2arVqtEdZwOcq+MRGw8LLEjaCVx5MAHBlX0SBTpRt6qVU3u8VXG2ehkM078GKqO95DTDhMdwLCi4zTZhrQ6/i6uoqvv/97yMWi+FHP/rRVP2zP6WmUb2MTi0UCpa2rp7IZrNp4OTGxgbS6TRevnyJ3/3ud7h//z7+9b/+1/je976HZ8+e4eOPP8aLFy/QbrdNhgLTjjJdI5UVjL4kXSifU7Cc/yto4lsopc6Dk7xOdQ41anmvOkaACQ2Sb14HpCgtetkSSlviPSF5dB2IFKJ53ashUE3Hy1TjQqFg4CPTOQhEMYqcuhV1TJVjjJai80/1KurDfwoALf9WntdoNLC9vY1vfetbuHfvHrrdLj7//HNbFx5KQD5HfYqpc3fu3MHMzAwODg4MlFJa41p4GvVGb4hPXve/pxnuLUZZa8F37htG6UTRnAJGUe8PgaQ0trXshs8s8GBvlF3im7cVfKP85H6m44e2CHmPd7wA0/oUm8p8gil0XGSzWdOLWc+r0+mgWCziW9/6FlqtFj755BM7mOYm2hnAVZpT3Zfr3+l08Jvf/Abf+9738ODBAztwiDyStUWZpk5QmlHgq6urU7qyOjl17X0fuI4EnKJohv3lOzxtxuNxLC4uXtHZ/T5k033JPax95DUhXgJMp3Vq00goXke7jNHyWtKB42JT/Z59UDCK9ZK8nRXFV3idOgv0maE9Tpl/cXGBZnBXZO8AAP0aSURBVLNpTq18Po9isWipi9wntEc3Nzfx4Ycfotvt4qc//anVCtP5C73vde1rAU+6gIPBZR2kbDaLfr9v6Fm5XMbS0pIV8mWI6M7ODs7Pz63WzcuXL/Hq1SsUi0X8zd/8Db7zne9gZ2cHX375peVEqtcfmC4mrM0TvAde9H56mRWw8QALn6n3akqeggp+w2ufFA3WzRAiIjWmieaqEucVHX7nATH/7OuUIq+Ya5/9HPiNo/PF9wBAp9MxL382mzVlh5u0WCxibm4OOzs72NnZAXApeFgXgjVVMpkMBoMBqtUq2u22CUeewKII+U1oior7z09PT/H06VN88MEHuHfvHpaWlrC3t2feYQIZ6i1gpCALSNLg0EgbKlV6n1ciGErumXXIyADCSrSCKkr/wASUicViFv2hY9e9pco0DWalbQ86hQyYKJrXfnMdyAtyuRzy+bz133uCfV99P1SQ8n4fdejnMUSX3Cf0ODMSi0ouFTBNoTs7O0OpVMK3v/1tLCws4JNPPsH29raNTSMV/HtvqtKkjSDRj370I6RSKXzve9/Dd7/7XTSbTavhREWSx2LT8OZ80pPEtCIaFD4KiLTKEw8JHK2trWF5eXmqpkAsFrNiz5QZWg8EwFRI8vz8vBWKPD09RbFYRKlUwvz8PD777DNLFQZgBf0JZnKP5/N5nJ+f2/eq/Pt9oOkR3MuvM4Qo/1ZWVkwxZaozeYvuC3+v7g+/d4GrnkYv21RJ0f76yBCOiaehNptNS6Vj2iI9k/Ss0oHEkHbqDn8Ke0Ab9zyPHz85OUGpVEK5XLZIck3VPDs7w97enp1uyWPmf/zjHyOTyeDf/bt/h+9973v4l//yX+KXv/wlnjx5gmaziePjY9RqNavp6GWIB3oIPpFO+BnljMo+L2t89JQ65riH1SFG2lOAgZ95/QS4Sm+kLTWYlL/rsz3Qwz7yfy2S7vVKLwNCeprOlzcQ9XdoznUcjEjhWmm5gvH4Mh14PL5MIeGpSZSxwKWOlc/nLeKHQLimI18HHtzERrro9/t2wuudO3fQbrexs7Nj+pMeFsE1YR0alnNYWlpCqVSaqrmoAIZ/r09X898D01kHpI2Qfh3ioaPRyGrPkF7j8bgZ4Tp+/zfv99Hg+t7Qb8+/WUNGT3bUvl4H7OocXMeD1fGo96lMIH/5OjTKuaUMHQwGlpFBOmBEHN9J/c7bd8rPbppMCfWR4xuPx3j58iV+/etf47//9/+OR48e4eTkBN1uF7lcDvPz88hkMlZjlk638/Nz1Ot1LCwsoFQqTfGgWCw2lSWhNqQHIZQ+vC1J+vR2MXm8jol06OkvhA0AEz07qkXpy9QpqV/onNKuou7PMRBc07F73h6yw7mv+QwdN+eS71Y5GovFLPI+pPuFmjofut2uObeoD+rJesBkT87MzGB5eRmzs7N49eqVHfDCZ/7/sb/fGHjSQZCoibh1Oh0Lb2WqFYEnhoINh0NTdAqFgh3l+PHHH2NjYwP/4T/8B/z7f//v8ed//uf4+OOP8bvf/c5Ah3a7bUWutHmDT3ONVSHyoaEEdrziQWLSDeA9b2q88l0+9cYDRzSW1bvM5hV84Cpir4xOlRgfqq7oLb9Xo4vX6fzp871nRzcLQSEP2GnII+e63W6jVqshmUzaUeKj0cjCnRm10Wg0LFdX14iGGI+p5UbRtJbQ3LzN5g1+/3+lUsH29ja2traQSqUQi8XM4NM5V2bCEOF8Pj/FbFiPhuGwFKxqZJNxkt4ULAkpIiHl2DNRT7ekAy/8vOdWP6ORGAKl3kSp8AzWM3k/No7b7zN/nSr++jy9NpTqpHsu5GVQg57POT8/R7VaRavVmrpWU1SYhjk3N4eHDx/i4cOHePnyJT766CN0Oh2bb+9JYj9uyr54k0ZwYXd3Fx988IEVjyTNqycpm81iNJrUUwIu90Sn08HOzg5qtZqdmhnlRSLw2e128fz5c+zt7eHevXtIp9OYn5+3qCvWnxoMBjg4ODAv12AwQCqVQiKRMDCA889ceRqEn3/+uYHMPqWY13PvkR9w7TXtQdeX3nvvkfVKC/8ej8fI5/NmeG5sbGBmZgZPnjyZAqs510r7+u7rlJsoMMp7KpVWfeQqv1cDzUc1qgJMHjQ3N4eNjQ3k83n8/ve/x89//nM7ZekmR3H4xnUgnfT7fQNTl5eXrSAo6/9pWDwLlJI+T05O8LOf/Qzj8dhSLUqlEu7evYtKpYKDgwM8fvwYL1++tOi8kMGsIBPBJ68zALgS8s/951OUvGOPuoMaITQWucY8tdADMgrMkG/qHqDc0/foXHuer3QeUqjVWAIwxddD/FYdKhyX90qH6FOfD8AiKPP5POLxuBmL+XzeQO9CoYC9vT28evXKUmVUNi8sLCCXyyGRSKDZbJouTj2ef9/kFpLt5BdPnjzB3/7t3+Iv//IvUa1Wp1KEtIYL65nwu36/j8PDQ4zHY4uWJc/nXlLjzusZyutoL1Dn8Eah1634WRT4BEzTAtddxx6aozcpzRA1p3y29p3zQMBBHZGve66CAEqPlM26j9l8tK3XK/0cvs7o5j0EVmjLKH3cvn0bq6ur+OUvf4lXr15diSS/yc3Le/6OxS5PqPv888/RarXw6NEj7O/v47PPPpuqccYDUoDJKbanp6doNpvI5XL2GdP4Qo4wlcdq/4b0er8f9Nk6Bg9yhPaF1//1e48LhJrSKcfFKGqfraF6GoFhlR1Kjwr6su8eTFLHmzYF9HQOCRTR+UA61neEnOAc0/n5OXq9nkW5cr4Z3UTglTbL4uIi1tbWMBwOsbOzY7W4dU3+0PbGHIqD0wnWnMRms4lOp4PFxUWsr6+jXC7bCV6actPr9UwAM9Llo48+AnC5oP/qX/0rPHr0CA8ePMCrV69Qr9exu7uLZ8+emSeHTN0P3Cu/uhBUGFSZV7CE13BS9XdIkfZGJxU3GtYKyKiixOf6vivzVIWKiKgqc6qocbw+xU2JPWS8hAAvPk+9n5wXVtrXcfjTLPib4Zqx2GUKGdMjGMX06aef4vHjxxiNRmYA8l4isMBl9JSepEblNsrQf5vNK6++b51OB8+ePcOtW7csooV0l0wmMRpd1jIhgKRCmga4HhnLd9DwoqLlFRgyHdI5oy5C4JP/W8egxn/oewoaz2TVsCBDCxm5aiB4YzdK0dG0UL2Pwi+kkPiwWe2/viMK1Pb7MKQwURhQadPncG+0Wi0DWXnaDHPY9TSkjY0NvPfeexiPx/jpT3+K58+fX5lzbTdpT3yddnZ2hhcvXmB7ext37tzB2tqaRXwwfZv14gCYx5r8gA6QhYWFKZDPKyQKPvFUIxbZXVxcxHA4xPr6OlZXV60O1HA4RCaTsRPt+J5kMmkgAemKe+3TTz+1ApFME/YKFMF13ZOkQUY88XM2dW54Puh5vzow6NFMJpPY3t7G4eGhHQ3P61T50+fqM5UP8HPd9+xHCEQO7TnKId7vQTim6ycSiamT+2q1GobDoRUU/6u/+iukUin86le/wsnJyZV+3tSm+pTKctIU6+WVSiV88MEHODg4wNHRkd1PHki6mJ2dxdnZGTqdDg4PD/GTn/wE7XYb//W//ld84xvfwAcffIC9vT2srKxgeXkZ2WwWjx8/Nj1NDzvQ/nlFmrKdOhW9th608vw4xE/Z1JjgnuaeUKeh6mBROht/qw6j92l6mY7VO/NC66UpRzoWfs/3qxyjN133LteL9Tr4LKaFAzCAuV6v2xHimUwGS0tLljrM9LqnT5/ixYsXxt8YKU7gKZPJIBaLodlsotlsmi7NY8VvcvMAuze0ut0uvvrqK2xtbWF9fR0bGxuWxgLAxuqPUgcugb1qtWq6FKOKQqBilLxVWvBgq7czvEOXn+nzCTDS0CeNRPHhkC7v+bLv9+uAI7UFgOlI8OvujXqX1xvVKahNnXv80T2jc+BlineOdjodi2IrFotYWFhApVJBInFZA3QwGGB5eRnf+ta3AAC/+tWvLB05JH9DdtPbaCF9nc3L0levXuHXv/41/vqv/xoffvghTk5OTEYy2oUOr2KxiNPTU5ycnKDVaqHRaFjUk2ZS0NYIZR+QZqP6HOL92vzeIM/kPbRrfGaC7ll9tuo3aiton7S/mt3EcfMeymY+N2qM/rf+HaJbf63aEJQ5/EzrUHm+wjXlmNQm1MMkCGABl3Y8Dy6Ixy9LRiwuLuLWrVsolUr4/PPP8fLlS7P1Q2Db121fC3jSpgbmeDy29IWZmRncunULd+7cwc7OzhQ4Qi8WAQcScKvVwpdffmnK5l/+5V/iW9/6FnK5HCqVCtbW1pDNZvH8+XMzzpmS4BFwLpJOiCK6zDlVolEiUCUppEB7w143GheaqRl6vYYPKjMnKMTvddMosqzj0k2hG0HXRjeaPl/nyc8Z36toKNeKxMw11Ov9fFAZpaeu0Wggm80imUxif38fv//979FoNCzslZ4U4LIGz/LyMhYXFzEajdDpdOyIZh8BcBMEAFtoA2r/BoMBtre38eLFC6vLQDomTWhOuwpaBVK10QutAoF94ec+7Y59CT2PjXQfNb/ar6jvfZg0j+D149J3hvpBRY6KVzweR6lUQi6Xw5dffolOp2O1lzhW9sE/X40m/c6vnVdqQ2vrU06Aq9GICnbzeRpFk06npwwjRrKMx2M7sej999/H6uoqnj17hk8++cRysH20S6jdpP3xunZxcYGvvvoKv/rVr5DL5XDnzh0cHx/j6OjI0t0U+GaKt95/dnaGVqtltM55AnCF/3E9NE2oXq9bJNCzZ8+QSCSwtraGWCxmqRhnZ2col8vodrtWKLLRaNg6Hx0dmTGnILKuBdeNdRKBq4dEeK8zlTzly54HRgE+o9HIDLNGo2HFdJXvhsB8r1iEQGAfAaPX+qZKIxVHHbPun0KhgNFohO3tbbTbbeRyOavxpVGvlLeZTMZqIrH9KUQ7ecWUnlTO0eHhIT777DM8fPgQq6uruH//Pp4+fWq1zQjQ6ClFwCSd8/j4GD//+c8BwGqake+wVkyv18PR0REuLi6smLHqPyHvthbGJ3/zirgq96qTKU2rEe3By5CRSdBI6UflDTCtN6kCz+YjrNnI03m/T2VQgFkVet0XfD/3pteTFNximq3ez2cSKNb90Ww2sb+/j7m5OTuZiAD4/v4+fvvb36JarZrjQiPQuF6sx0on3tnZ2dR+usktBAQAk/mv1Wro9/tYXV21OqLdbtfSC9vtNgBMyRIAll5UqVSwuLiIZDJ5rZ6pBqEarlxDH33u+b9f6xCfpY6v0X5+L14n35VPa/SGn08Fb/mZ9o/v9u97HXCl/Qitm4JPvk/67JDN4gFiNh1HPH4ZBXp0dITT01Nks1ksLS2ZgyqXy1kfHj58iHK5jI8//hh7e3vWB9+vrzPuf+4WBYB6cA+4nGOC0MlkEonEZX0nTdsEYIcVMBup3++jVqvZybx8ltqw3lZRB5z2Q/k5ML1WPnNC51/v8Tq97kPWlB0Oh1hdXcWDBw8Qi8Xs8JlOp2POKg8+eb1Jv6es04AX8nfdvzrXfl08LXkb3+tKXj7SdlJbUN9HvdA7VTgvegKgrpXPzGJ/af/n83mcnZ3h+fPndiiOH9sfCj59rVPtPEGox/ns7MyO8y0Wi3j33Xfx4sULVCoVi1pR7xwn6vT0FN1uF81mE5988olFT/3VX/0VlpaWEItdHqXNqBmeeESPsHrBPWOlYUFlgsCFZ7R+IoFpEMUvkmfEBIM4R1oVXp+tz9CCnJ74rkOLudA+H1lBrRBT53yrIFEBx7VNJpPWN0YV8G9GuPF5Ok/az1gsZiGcVBCXl5cxHo/x0Ucf4ZNPPrE5oxHO+3g88OLiIprNpr2XkQmacnlThABbSLDy70QigVarhcPDQyuyzzpOGjXhGRWZCI/OVXoEJkybtE0lk1FQnikQ3CCTVkDUA1JRYNrrGI0KF02h4HfKeL3yxvHrHk2lUlhZWTE+MDs7i729vSnFnO9TcOl1/Qvd6z/3/3PvsumacS8REFSgjZ4EFtRPpVJYWlrCaDSyiCemehEQuHfvHt599100m0387Gc/w97eXuQYPJisv/9U2mAwwOHhISqVClZXV/Hw4UO0Wi2rQ6QGZrlcxtnZmaUskm5ZSJT04w1ORt4B00qxhpGrkcki1dvb2xZ1xZoDFNCUbxwDn6eKDX97j5FvuoYcL/eRV+b0Ht1jIdBgPL6sNVer1awYMRUylRMeRNXG6/Q9fP91tObv80CAAlHARAF++fKlHV6QTqctzaTRaFgkQ7lcxre//W2cnZ3hf//v/42XL19GAnA3sXmFG7gEjTqdDrLZLKrVKp48eYKZmRk8ePAAt2/fxsrKCk5OTqacTkxxp2HB/zOZDI6Pj/GP//iPAIDvfOc7JptLpRLeffddNBoNjMdjiyhn3UA1nNUxRm9pqKafV8gVGOL31EWURkM8W2WDRgzp+zQ6WA+K8dGwngb5fH2W0mAUkBUyrvyz2E/qn6Rdfk79kPczC4AppJpKqgAIC8NWq1UrBruysoKLiwv8/ve/x2effWa6F6M22M9isYhisQgAVluQuoVGkf8pNK9bcV7r9TqePXuGb3/727hz5w5KpRKePn1qp5cxzSqVSmE8Htsc8X46LRYWFsw49/JV6Znf0bgDJnVYaONwDX2Kvtf9Q/aC6haen6nhqnuHB3Ssr69b4WzWuTo8PES/359K/dQ+AVd5s/aN8s4Dvfws1E+/ZsrnrgNPonRPbaq7Kq9ilGCtVkOn00Emk8HKygrG47E5hgg2Pnz4EN/+9rfRbrfxs5/9zACaUPtDjex/jhYCPYBpoIO02Ov18MUXX+DP/uzPsLq6ilu3bmFvb8+cm4VCAfV63bJKZmYuC9gTnFYHleroUWupTmC1WdQuiNJbdY95/dzTF/e+NjobO52OBUywjhtb6N3eac/rVMZoP1Sv91G3ug7X6XjXNeUhWmtNHSbq1BiPJ45Er/dxT9CG1O+pXxJsZzAP5+P4+BivXr2yz0Nj+0P2xdcuLq4vZFjw+fk5Tk9Psb29jfF4jG984xtYXFzExsaGAUX0vtA4ACanGbCI6/n5Ob744gsbxOrqKoBLY3l9fd2QPyqk9Op5MEnRPxp/jHRiH3xTRFE3LjcJo7OU4fooJQJP3hvmNyj/13exee+YKl76TI/uc430dyw28WYosOG9cD5tg2PQgt/sAxuFkM//pSeVRWAXFhawsbGBpaUlfPbZZ/jFL36Bk5MTzM/P27rzvbOzs1hfX8fdu3dRLpfR6/WmNmBIQbopgkBbiClzvQ8PDxGLxfDhhx9iOBzid7/7neVbAxPaJGjHcHHN7b8uxFO9EbyOgsCHjIYUDG9Uhhh7aP94RqSfew+0v09/q8eZ/WRUUyKRQLvdRrVaxdHRkTFT32elCe81DvWbfda/NVxYhSfn2BswIWPaCwnyofH4snByLpdDPB5HrVYz/phITI5I5bHJjPrzY/CAmO/Pn1obj8fY2dnB3//93yOTyeD9999HuVzGr371K3z11VdT0X2cGypInFcK4Ha7bal0DCUnPyef1qZAla4v1/3s7MzC08mXPD1EAX7qIdOUJQ8YqWxRJYvXaUi1X+PQngx50hgdw2hLKmpeiYvqox9X6N2vA31CfEKV0cFggKOjIzx9+tRSINfW1rCwsICjoyMzHsrlMv7sz/4M7733Hl69eoWXL19O6Rl/Ci3Ek7TAPJVmyoi1tTU8ePAA+/v7U3WVKLPPzs4sspXKdyKRwMnJCT799FNTMoFL/erdd9/FgwcP0O128ezZM9PlNP1dHYW65tQn+H41oq9TuLkfvF7hZY43ev2e1KaGuAeN/PV8t/ITHROfx36qrhaiWTX2uF/U2cmU6lgsNnVYgNezeOAAeQV1V22aaswDXF6+fInf/OY3qFarlv6rqbqzs7Mol8tYXV218hbtdttKGei1N7lFGbrUUUejEV6+fIkvv/wS9+/fx507d/Db3/4W9XodKysrmJ2dNeAln88bEEO9VU+Ro62h7+a7PM3T/mAfgGlHr9KO2k5KdwCu8F82Hx3BZyrwr1Fuc3NzWF5etrXu9/tmPCpgprzd98W/F5g2/rl/+D3H5tMMvRzz8+nH6tebv9XG0v7x3Zp1wnRjAonFYhHZbNZOs02n0wCAfD5vQPyPf/xjfPXVV1P89Lo+3YQW1ReddzohvvjiC/zsZz/Dv/23/xbvvfceDg8P8erVKzvZLJPJTDkHFhYWkE6n7QCShYUFLC4uApjWdzwdkn9pVCn1rZDOEmUzqJ3sv1c9nzqN0uDBwQHa7bZFhfKwEe+0D5UVUD1IbZBQIz1qIIeCZlGADD/Tfa8lFNg3jXDXvnnHt/ID3b/qROGzFcPhulB3JjbDuW40Gjg8PMTe3t7UHv5/ISveGHjygpcd6fV6lgrFEL1er4fFxUXcvXvXwsI9ykbwiZEAZAjNZhNffvkl0uk0bt++DeAy4uH+/ftYWlqyeid6VCM9RlwQReVDII8urkYN8Tolcu9x1oUmCMDnqFGhIE2IQYQMbd3ASuzqMWEhMF6jQsCH46owIGijBnIIyGJkkYIXFK6aV8p+6fvoLcrn81bQkZELlUoF/+f//B988cUXtiaMFOCGyWazWFtbQ6lUmkrt0xphUcbdTWpRAnY0GuHk5ARPnz7Fo0ePsLGxYelT+XzejkQejUbmpeLeKBQKU+CUrnmUx0xP5PGh1rxHaU4jdlSI8HpV/q8bM69nXz2zDDFIvZ/7jArlYDDAzs4OqtWqHSfNYnj+PT61gnMVAgJ1rhR41vng9/wdUhJ1LCEjnmOo1+tot9uYmZkx44/HsGYyGTvq+vT0FPl8Hg8ePEAymcRHH32Ep0+fmgdWedn/K0FwE9p4fBk5++rVK7x48QJ3797FycmJncDFYroETebm5pBOp20f8DS6zc1NrK6uIhaLYWdnZ2ofkEeqAeGNU9ZU0z0T8rj5yFmuu1eiPK3p7xB4o/LKK/JsHkwN8XV+TllI/gzAvGP8XveoykA/Zg9Oe+Mi1Nfr+s/naGOKGOugFYtFLC0todVqWYRoPB5HsVhEuVxGo9HA3/3d3+Hp06dXQOE/xcZ90G63EYvFkE6nTS4WCgV85zvfwfHxsaWxq5ym4sgjsnmC0fn5OXZ2dpDL5bC+vm6pRa1WC++//z5u375tQEQmkwGAqXpP3GPUszz4qXzIG9CeH7Ipz9ZUc+pV1KmUN6s3Wmmb71Jjmv8r4OuBM76Lqbl6DfulBgjTnzgnIWcer+X17DeBAc5H6LRZzh/fzfHPzs5auilTS6kf/+pXv8Lvfvc7nJ+fI5FIWBQjn1koFHD//n1sbGxMAfcLCwtotVpTEQ03uYWMUP95vV7H7373O/zwhz/E/fv3cevWLXzxxRe2zlw30gj/Vv1ZTzJ9nb6j/FlBHY1OuE7v5v8e/CEtqpzwfFaBHrbZ2VnUajX8wz/8AzKZDHK5HE5PT7Gzs2O2g+470i73ktpD2lc/93x3FK9XQ9gDsyGQwf+v86X3qb6qYNTMzIzRMXXm4XBo0bNMM+W14/HYTgtlVCl553Wgx01qCu55PqxyOR6/PO31F7/4BTY2NvAXf/EX+Bf/4l+g1+vZAU/ZbBYnJye4uLhAKpUyp97FxQU6nQ6Oj48t24B8hnxMo/3YL+/I1j6z6ffa1yg9gc3vFdWV+G5GOnU6HbTbbcv0UFvVz6E+W/eo8grvNOH7KWdC+hGf7+nJ2z3aB+9AY/SWOiw0EEYdPio3+ExGM/n6aWrb00mytraGXC5nh+8wIjpke/+htsfXinjSxkHRy8bCq5lMBvl8HrlcDnfv3sUHH3yASqViXmlFCXkSCwCrDzUzM4Nms4kXL16Yp4ghxnfu3EEul5sqXJ5KpQBMTvEigsfFUELzDF6VGuAqQfMZShwkOFV6/PckTN2IfrE0pcF74BVAUkWa4cIApoAkn3/KflNx03GoQRHycOtG1nkgwer9XH8FFRYWFszTsrS0hNu3b+P8/Bx/93d/h5/85Cc4OzvDwsKCbQJVNDc2NnDv3j3LLWVKpc6HZ7Q3sakQAKbTZk5PT/H06VPs7u6iXC5jfX0djx8/xvn5Oebn57GwsIDT01MzEln4rdPpTOVZUzHXdAs2MhM2rj2vV4DV38s+K/CpXraoxn2te8KDQP56/c0WMlQY7dbr9ZDL5UxhVloPMcWosfl36d9vonT4+k7q3dQaaMAExNjf37eiwJlMZqreViwWQz6fx/z8PE5PT5FOp/H+++9jY2MDL1++xE9/+lPs7+9bP9Wouo7x/ykCUuTf29vb+PzzzzE/P49yuYxarYZut2sKBL3M5IkLCwvodDo2n6urqzg9PbUCmcqL2VSJBSZAE9/hPWuqbHvwT40UNQa8l0llTNT4da8qDZPuPE1G7TE+z8sE9psODAX0Q56t6/qr90QpJB4c8yCV/u3lbz6ftzQJeqyBy9S7Dz74AH/1V3+Fzz//HJ9++qmBuH9KwFMIQAQuQZ9+v4+5uTm0Wi2LDM5kMnjw4AGOj49xcHBg0Sre8CJP7Pf7Zkicnp5if38fqVTKwKhXr14hHo9jcXERxWLRamKQJlRZ5R7wgIvKE/Vue2+wH6dGLOj3fJ5Ggfp0Br2O/ytf9AYAv+ePpssxtUr1DL3H62985nVOCgAGXmgKA99Jh6tP21N9kjxufn4e2WzWTrVLp9N4+PAhFhcX8Q//8A/48Y9/jFqtZnoVHRTj8diinTY3N1EqlVCr1czI0CjoP4UWpfNRD+Ua7uzs4De/+Q1+8IMf4Ac/+AEGgwFevXplB+R0u11ks1ksLy+j1Wqh2Wzaenc6HdsvCgCG+hDSEUIGpu+3lyseKKUOFWWk67u4J7mO8XjcTijkPTw9N6SXRs2z8n4FMYGrjv3QegBhWeLnJko2qN0VeodeT73Lz5OPQOMeY32jW7duYX5+Hk+ePEGlUrH9rpE/r9Ox3nbTeQ31VXnz9vY2fvzjH+PBgwd49913UavV8Otf/xrn5+fI5/OoVqs4PT21yCYCsGqDEMRT/Zf7Q+eNzdOtz9bgterEirJN9bkegPW0onUHFXAKySFdZ+73KJBYcQ9gIps8zfNvtbv9PlDHv28+qCDkzInFYlPlVHTudC5jsZhlAQyHQwPlyDOZDTAYDLCysoLvfe97mJ2dxVdffYWDg4MrmIDOw+t4SVT7WsXFFaDh/6PRZY0S1o2Ym5uz0L2ZmRl885vfxP7+vhkAFLrj8aROESeh3+9beNzh4SHS6TQ2NzcxHA6xv7+PdruNYrGIdDqNYrFo3hot1AxMh2jrxvAMPxRyp54RndiQkuE9XGRaHkFl80q2MnRFqPk/GSoBOKYm+lpVIYHENDhuEn4Wj0+KH6pxpQw8pHiFxqCbknNJQ5uGQbFYxE9+8hP87d/+Ler1OjKZzFQ9Im6UXC6HlZUVLC4uIh6/rP1UqVTs6EdGPnlivylCQRm//63XsFjb//yf/xP/7b/9N/zN3/wN5ubm8Jvf/AaZTAbr6+vY2dnB2dkZisUiZmdnUa/Xsbe3h0QiYcfJR4FvSj9eifFeEM9I/Hj4uYJOVMZ0zPpuFfohRccLkDeZV432i8VilipEpZ5No7U8uBz17Kj+KOP2XgW/p9WDyJQKLezabDZRqVRwcXFhwBmN/vPzc8zMzFixy9FohIcPH+L73/8+xuMxfvnLX+LLL7/E2dnZFWNH+xnq900GZ6Ma1/s3v/kNRqMRfvjDH+Lhw4fodDp4/vw5BoOB5aMzrSCVSpny3Wg08OzZM7TbbYvs0OKKIeCaf1OB0GjPubm5K8ZZFGCrgJMqVF45jHJq8N0+jVpr4rzOqOE9UTIhnU4jnU5ja2sLc3NzePnypRVS177rM/RZfg94A8mP3/fX8y69jvuIRzkDl+lg6XQaJycn2N3dRbfbRTqdxsbGBj788EOjlXa7fcVDflNkw+tayFhginU6ncbBwQF++ctfArgshFssFvGd73wH+/v7VuRe53U0mkQ+XVxcoF6vo1QqmVOvUqkgk8kgnU7baZKHh4dIpVJWj0hPVlOwlH1Vx5l/N/9WQEfTLqIcGSEFW0+eC+lUwDQN+f3jryegRQWcKdyMRuLzFJxS2vRR8vq/RoRTFwQmkeHky7xO9TIdszpo+Q5Gdg4GA6vT8vTpU/yv//W/8PjxY3sno8g5J4x2Wl1dRSKRsAMN2CevG9zkFgJ6+LkCDJVKBf/jf/wP1Ot1/Kf/9J/wwQcf4OjoCMPhcColjcXda7Wa3d/v99FsNi0KRIFVXVeve6suG5IP2ryDQg3F0FjVyFRgVJ+nKaMeONJsDS9z/N/X6dRe/1BHJj/zeiXf5w15/d5fz98KyPnSECqb2JfRaJIJQPA8l8vZydms38Qo2jt37qBWq+GnP/0pKpXKlAPmTwF08i1KN+CYz8/P8cknn+Dv//7v8V/+y3/BN7/5TRwfH+OTTz4xftjtdi1KltFydILU63WkUimz8cirgMlpu9fxEs/bfVP7JKSX6z3eMefBYZ4WHI9fnuRLnuftgRD9h5zhvp8agBJ1rzo6OH5vT/v5idonoXRoP9eer9DGHwwG2NvbswO9mI49MzOD5eVlLC0toVqtYmFhAT/84Q+xtbWFjz76CP/3//5fO3TEj19//yF75I2BJx0smwq7ZDKJbreLJ0+eIJ/P44MPPkCpVMK9e/fwve99D5VKBc+ePZsSyDS8OGHdbtfSJy4uLnBycoJcLmfHxbbbbTSbTUtVYRFl1tzwXitt3qPmx0RQhwbN/8fef4fHdV3n4vA7gzK9oXcCIEGAvYhVhVSzJKvYUmQ7cVdc4uQmN/GTOPfmOvbPRbmOHV/7OrFsx04cV93IsS1ZxbJsFUqkqEJSFKvY0TswA8wMZgZ1zvcHvrW5ZuOcAUARAmSt93n4EBicOWefc/bae613NVrE9ONIMKigIP1upqTr3zP7uy5kpOzQOSkMnAxaWlDp+ennpMlLTCgtpnT/3MPGFR6ujPDNiStYdB98UyODD4CKXsvPz8fKlStRV1eH1tZWPPXUU4hEIvD5fLDb7cqTS+eiduk8zS+VSmF4eFiF+3MvLH+uS8241hcC3bCkz3t6enD06FGsXLkSmzdvRkdHh1oYvF4vIpEIgGmP/8TEBGKxGGKxmFKUCbpHjjZybhjohq+ZNyHbfei/z7Zw8uvo3ghd0TBb6OkZcaadZJ7mAp2PPwez+9GJSv1ezRZPTkhZ3av+TMl7TFE4JFuTk5MqEoc6eVI6KnUUonz6qakplJSUYOvWrSgvL8eePXvwwgsvIBqNZiiF2QizbIrjmwVkcLa1taG8vBxbtmxBbW0tYrEYIpGIWjOIgHS73RlRcYlEAj09PcrQoL0h27zXnym9T77O83QjPZRZH7+VcsMVH/6u6DNS6rhjwEwB0z+z2nfof76u2+12vPbaa+qZ8XPwZ2Dm9eMKlq5EmdU64Ofh1zC7F/IeUl0S+pyKyFM9lpqaGuzcuRPl5eXYu3cvXnjhhazh4EsZZroIgUoYUKTSmTNnkJ+fr2ogbt68GbFYDC0tLQCgCvPT+yI5MgxDpWkB090bS0pK4PP5MDU1heHhYfT19cFut6sIcorWyc/PV44i3fsLzKxLRvOHdCnS0Sjdn9Z0Ps/oMzKQyXCnc5vpc/xZceKBfufRGHw/pGsT6USKOekZemQVh91+Ma2E60rkeOMyxmsxUbQal30z8sDsb5RWTu+hvLwcTU1N6O/vx/3334+XX35ZjYvIQpI9qglWU1MDv9+v6tQNDQ0pfYqn2S11QzubvsfngM1mw8jICE6ePIlt27ahvr4ezc3NaGtrU45cet+8tgrVK43FYuqZ0r5B71Q3cPkcAC6uYZxo1MkpOo4/bzMDWNedOMzIV74ek11G+5fT6VSlSThRYxYBwsdA4zaD2dj4+XVnjxUZZ2bHcPKOyxPfD4mMIpml/xOJhIqM9Xq9mJycRH9/v8okyM/Px4oVK5Cfn4+9e/eipaVF2Rb0z4okWSr2htnc4USE/hk9q2QyiWeffRY+nw+33HILtm/fjnA4jObmZng8HsTjcXR2dqKqqkplMFG30+HhYYRCIVWcn4hM3f7l75/LSzZwm0F31vH75M5BfX7y+ZJOT3fypTrDNEae/qyniprpzjrZqttBOlGpyzEFeej8A42Rj4M70fnfOOnNn5e+33LimT8X0iFycnLg9XpVoE5eXp6qkTo6Oorq6mqUlpYiEong9OnTquC82T2+XjtjXhFPZg+OlBtiSSORCF577TXk5OSgqakJoVAIjY2NqpBfKpXC+Pg4BgYGMlKt0um08vTQZKEc1GAwCLfbjcnJScRiMbXBkgDQYs9DQLnhzRcxPtH4AkbV/Cl1g4gY7iXgCjx/yVxYzJQgviDwMegePg46Bxmx5O3inkMCKXk0UXk6XjqdhsvlgtvtVp4RWljpvnlxNt37ZmXk6CQDdR3MyclBXV0d6uvrceHCBTz88MM4evSoegdEGpDCR9116uvr0dDQgJKSEhXdQJ0XqFaF/hzfLNDHPDk5iWQyiePHj2PTpk2oq6vD8uXL8eqrryojgQriUSeaZDKpCiYHAoGMOWwWDs4JJ7NnZkYwZlN2rBQfq9QfqzQ7XbExW8R0+SFDgYpGUvoI7wZE85lDN/J1mMkeH4++kXCvKkEPN+dGdDqdxvDwsHqXlBJGbeEpYtPr9SKVSsHv96OpqQnV1dVobm7Gnj170NnZmaE88GvoZJnZc34zgu6lt7cX+/btg8fjwfbt25GXl4cDBw4oBZrWZlr7c3Nz1Z4wNTWFaDSqPDw8p5+eJ80P3dPJSRVO1BOhzyM4+PumucOjCPgaT/JmpozNRfayvVOumJjtQ/QzRbPQnCQylM7P90Q+fjPPHR+3mXJuNt65KvREgvh8PgwODmJwcBAOhwPBYBBve9vbsGvXLrS0tODnP/85Ojo6Mu6R4824XxAmJy92potGo+jo6IDX64XL5UJFRQVWr14NYDoSlAqqUstoei9keJLuRancw8PDKCgogN1uV0WVx8fHMTw8rPQJ7sTT55OZwco9raTkT0xMqGh4MgDI2cjTvnUnha5T8etne59mOhU3xrkzDzB3uPG9hD9HPYKcd9EDoDrX0b1xo0M3psyeIV8zaGz5+fkqYrOoqAibN29GIBDAb37zG+zfvx9TU1Oq26bNdrH1N0XR5ufnY2xsTI2DiooT6URpWW9WGSHQvCFnwdTUFNrb23Hy5Elcd911WLduHdLpNNra2tQzpojZ/Px8pFIpAFDREbFYTBFPLpdLPSMiHvlcAjINfHrW3CikY8he0fUM+rt+P/SzmT7C9ymSDz5fSc8kp53dbs9439wu4uc0I4L0Y/ToCoK+t2VzyFshW5Q6QX+WJL8ULTs6Ogqfz6fIlGg0qo5ftmwZGhoa0NzcjMOHD2c4tbMREXPZh98o6LqfTjTxn7ntmpOTg/7+fjzzzDOorKzEtm3bcPXVVyORSKCjowNut1tlJ5WUlCjiLplMqnS74uJiABftS8C8zinfE7Lpp/xvZnoM/1mXC7o3IlMoktHv98Pj8cBmsynin2om6tfViRUzmeTkFs03s3lgdp/6nmS2P5FtbvUMzP7GbSwzpxDtOSMjIxgbG4PL5VLvk3gBu306u8jpdKKpqQlutxtHjhxRhfZnC6S5VMyruDiBK3P0M1dswuGwaj+dm5uLwsJCbN++XS38ZHD19/dnsIH0ACcmJlTnAWqd7Ha7lUJACg2REbRo0EZvZZBxYdCVaVIU0um0Ir7ocz2NTj+fvoDrk1TfLMwmrM4a02TlESyGkRmWrUdHkRHGPR9Op1Plq9P7oir2pKjwouk6k8w3IbM5YLPZFLGVn5+P6upq1NXVoaurC7/85S9x+PBhANMbOm16FF3mcDiwfPly3HTTTbj++uuRl5eH1tZWNDc3o6OjQ9UriEajSCaTGcK+FBUlfZOyWlxpvvT19eHFF19ERUUF1qxZg+7ubgwMDMDpdCpiJRAIIBgMYmRkBOFwWHXWoo5ouodBJ0k5+DvjihF/3/pzNVuc9XNyBYifG8gkuHQDgistZkYynZM8L8FgUBVXHR4eRktLi6oTp6fNck+C2Vwxuw+zn/l39U2UGyd8zFSgMZ1Oq+KGNtt0kWAq3Nvf34++vr6MtLu1a9di8+bN6O3txcMPP4yTJ08qcj6b58hKeX2zwYzASCaTaG9vx7p161BaWor6+np0d3cjmUyqjZc6eRFJOzU1pULrU6mUalZAqZlE5tP84HuBvs4BF6Mb8vLykJeXB4fDodZQnWSieaend9P96B4kAjdOdEN8Loq42bMk0PgozYTq5umRk3Q/+pislCa+7+gGltlYzPZD/b7GxsZU1I7X68Xg4CC6u7tV9EZRURHWrFkDj8eDM2fOoK+vL+ucfzPLAwDVsMVut6vuMoYx7eyrrq5WzVZeeukl9Pb2qsgiAIqwd7lcmJqaQl9fH3w+H/x+P6LRKOLxuGoEQsdTdBPNUx7lNxenFIAMOaD1kCLVSe4o0oT2HCKT9XPqRgmQGYGXzQFiZpDTtYGLuh3JBh3HZZTkhEewAsjoSsrLANA/0hnpmvMxVEg/oNpOlGK/ceNG+Hw+PPPMM3j44YcVsU7OOZLhnJzprm1FRUUoLS1FIBBAOj3dUbe1tRWxWAyGYaiO1PRslrqsmBmeHFzvsdlsiMfjOHDgAFauXImmpiZMTU0hEokgGo1mdEWlZ5hOp1WELKUcUWYFpSrptbjMIhEA65Qys31a11GsdC19n9HJfz5H+Tmo/Ek0GlWkjO6o5Gu07sjk90DH68YztznoGE7K8b2E7zNmTn2rNYU/EyL9OBlERP3IyAgcDgdKSkowOTmJgYEBFTlYUVGBHTt2IB6P48knn1QlEHR9ORtRMh8SbaFhpffpejv9THOlvb0dDz/8MHJzc7Fq1SpceeWVePjhh1V0KnVApDWO9iGy3ansBV87aK3Tn6XuRMi2Dlrpufw9m5FBdF4iVKqrq+F2uzEwMKDIV/ouT93mY9H3ELPr8GP1sZJcWgWr0Pi5A1InlfTr0O/8fHQsl0P9f7o3qnNqs9lQUFCgdCqyIWl8q1atwrp16xAOh3H48GEVGKTPKxrb67U35pVqZ7UgAtOLXTQaVZ6k5uZm5Xmoq6tDZWUlduzYAbvdjldeeWWGx5hSUPLz81VHAqoZFYvFEAqFMow0IqF4CDifVLqHm798K5IIuNhFjRZOInOcTqcSIFJYOFmjg6KwdCWG/50vohy0EfAQdatNhyv/PEydNhAAirSh36nGgZUxQ9fngsTnAP8ejxKrq6tDU1MT2tvb8fjjj+OVV14BAEUM0KZO77axsRG33XYbdu7ciby8PJw8eRKnT59GZ2cn+vv7kUqllAHJjfylqiDpbLn+N34MRZudOHECTU1N2Lx5M5qamlS9Dp/PpzoXUYFQWkR6e3tht9sRDAYzFgJOVnIjz+yZ6UqL7j3TDWYav26sAhfntZmBSeexivLg/9PPNJ95tInNZkMkElGFEHnoNF+Xsimm/H7NFD1dmSKYrSUEXfHk5N/Y2Bii0SgmJiZU62uK3CQPHBUab2howI4dO5CTk4PnnnsOhw4dUjnqetqIDisSbanKiRXMlKexsTGcOXMGFRUVWL9+PdavXw8AaG1tzYhwBaCKx9JayFvDU8dIilIg7xiADMOSj4PeJT1/Pp8pTY0XmeSySGS+VcoPr6/HYUU0ZTPIac3Xj+PrANUHiUQiGR1lCWQoc+KW5FA39PUIDr638vHxPUcnqWjcXBklRYnSJylCY3JyUnU8veKKK1BaWornnnsOTz31lCrmv5SMgcsJityjgvcDAwNobm5Wz7ukpASrVq1CYWEhysvLsW/fPlUTjuSDIozGx8fVP9o/KCogFotlpE7wPd+KlODzWjcq+Lzh+wufe+R8Ir3OjPQi6Iq17iSzGpP+N1oDaD6aEaY80ov0OPrcMAxFQFMdrampKRU5RdcgIotHjul6lU5y8yhlqjHkcDhUMfHCwkIcOHAAP/vZz9DS0qL0KioCTOl4TqcT69atw0033aQifXp7e3H+/Hn09fVhfHwcqVRKydabgXQCrFOKdOKEyELDMNDc3IwDBw5g+fLlaGxsRHd3N44ePaqcFRSFTHtAMBhU10gmkwiHw8jLy1NdhXXCRzfE6P1zIp+nYer6h26Qc/2dr5VctnQDn8uczWZTtXNra2tRU1ODRCKBc+fOKZuCMkZ4nRour7OlR1kRlXxcHHyMZBPpNXJo/Fx/5eD7C99z6fxEllBtwFAoBJfLhd7eXoyNjSEnJweFhYWq2+Gjjz6Kjo4OjI6OZui9VmQmv/elACtdgP9upgfSvJqYmEBfXx/a2tpQVlaG2tpaNDQ0qIAOyizw+/2q/Ec8HlelDChli2xlndTh19UDBqyeKZcB/jd+fmAmCUnXAKbnxPDwMF577TVlnxcUFMDn86lmVZw8NnOm8PNdCnTbyep8XG8y41ZInmkf5/uHGRHFQUQsNQtxu90IhUJK73U4HPB6vaqZUWNjI/Ly8nD48GHl0NfJZB1WRPpcMC/iyWxC8ItTZzu7fbqgbnNzs/peRUUFiouLcfXVV6OgoAAHDx7E0aNHlQHGmXDaGKnej8vlQigUUil31C7WMIyMQtVmUQ76i+HCYWaociOTK2Dk7SBvOU9nMwMn1mgz0SM/+DPlE5MWcDo/Z5PNwt9JOaJnyIkoYlTpOvR9uke+eVp51ilSgN4TKVW5ubnwer1wOp0qrPvs2bN46qmnVLolddOx2WxqsXK73Vi7di22bt2K6upq9PT0oKenB62trWhpaUFfX5+KdIvFYhmF1bIZYEsB+tjMFiHC1NQUwuEw9u3bh5qaGjQ2NqK9vR3Nzc0q6o660JSUlKCkpETVwYrFYigoKFBpoWTIckWI5rnZoscVF90Y5IoIV2ro72ZEKTCzYwU/r9k4dKKLKyX0XkkZdLvd6O/vV90uSVbNvN6GYd6GXlcS6e/8b/zv+nHc0KFrmXnpiRyPxWJIJBKw2+0IBAIIhUJwOBwIh8MZaRQlJSW47rrrYLfb8eSTT2LPnj2qTTonXPX7Mfv9zWJEzAU018LhMA4ePAiPx4ONGzeivLwcyWQSfX19GV4ZqldCayHVZqKIkaqqKhWSzdOLzQxcTgCRx5vIJdqUOSGjvxP6p0chmoHPX/o+jcFMyaLf+ZzQCVFOENMY6L5JPvTx8LWdyAkdureOPzMal75G6OsMn7M8JT6VSmFwcBDj4+MIBoMYGxtDPB5HMBhEeXk5br75ZmzduhUXLlzA/fffnzXF7vcJVLuMoiWpvbXX64Xdbkdpaanq0EQ6UUdHh0o74mv51NSUSiOi6IdkMolkMqkcUqRT6eSmTuZYrZNAZkQIYE5OptPTdWiozp3L5cowvAncKWLmMNOVXzOdiqclcB1IJwjoe6TfcOOWxgJApXnzdF2SCV63lF+Xyw49X75f8fsip6Pf78e6detQUlKCZ599Fo8++ihaW1uVk5b0Y7r/8vJybN++HX/wB3+ATZs2YWBgAMeOHcPZs2fR3t6OeDyO0dFRDA0NKQLizbRf6GQ1/W+13qRSKRw8eBArVqzAhg0bsHHjRoyOjqK5uVlFblRWViIvLw/d3d2IRCKoqamB1+tFb28votEoWltbUVRUhIqKCuXQ4DoSf398LuqGG59DnHDioPvRDVIAM/YSPsc4uWWzTWc1dHd3Y2hoSHVULC0tVZ0P9ZpmXBfjY6Xz68a/2ZzJFrHB/262r9D6ROPR9Tqza/HrUJpwMplUskFlXYjgLikpQWVlpdIpuO42VxnQbcbFghnpZ/U3K4TDYRw5ckSVxOGdxkmm+DzjXXApiICvdYB5NCp3UvFj9J/5cVbP2Ezn4NFH9D0eQZtKpZCXlweXy6VsSX2u0Zps5Xw2kzt9vnP7gl+Dr/v693RnHzDTKUnn48Q1h/673T4dhTs4OIhIJIKcnBwUFxcjPz8f4XAYY2NjKCkpUevQihUrUFdXh87OThw4cEAFepg5M/VrXereMe/i4vpF+UM2DAPRaFQ9bCpURgxrRUUFQqEQrrnmGtTV1aGsrAwHDx5Eb2+vuilaxCcnJzE6Oqq6DVBkgB5BQcdyDx0fHzCzOKrZoq4rwmbnIoXMTChIeeGKnpVA8u/wCcontb4o0t/0zUz3UNN56Th+v1zh4ccRzEIHeYFbUmTpuVM6YjKZxNjYGPr7+9Hd3a2KyPP6Ak6nE4YxXb9o9erV2LlzJyorKzE2NoahoSF0d3ejq6sLAwMDSCQSqg5FLBbLWFTeTEoSX0jNxk2LUWtrKw4fPowbb7xRKYvDw8NwuVyKvEin0wgEAspLSZEc3FtHC6jORNPnROpwpQkwJ12slAc6RieZ+CKun0v/2Urh4iQLyRKlNfGCkTR+TpLx81ix8LrcZpNRM0PL6j749ahV+dDQkDKiyWNE3diIOPd4PCgsLERTUxOCwSBOnjyJ559/Hv39/RnkhdnCz8dltlm/2WRFB7+ndHo6UufcuXPweDwqF90wDHR1dSlnBa1JVKeAK07ZFAcOvtZMTU2pPYcMcuCiV52OMzOWdQWJ5JAIIP1YK9KfGwdmz4d+1uVVJyxp/eZkMj0PSrUyDENFpNDf+T3ojh0z2eGEltm96+Ae7r6+PoTDYbhcLpW6DwA+nw+VlZWora1Ff38/9u/fj97eXlP5nA+WggExF5DnkogQSimJRqPo6+tDVVUVKisrUVhYiF27diEQCGD//v04ffq0IpTIqKB3QMX3c3NzUVBQoJxsOpnJYWZ8WpHgZvsIyaFO2hIBxaOh9GP0vY3vF/q8ovFxncqKnDSrY0H7m65bUbSUbuQT6UTfpfmur9X0HdKryKlIxLZhGCoCx+VyoaioCDU1NRgbG8PPfvYzvPzyy4jH43A6naogOjVWcDqdWL58ObZt24YNGzbA7/fj4MGDOH36NJqbm9Hd3Y1wOKwaNESj0VkjW5Ya+JyczdCmdc5ut6O9vR0//vGPcffdd2Pz5s244YYbYLPZcOLECeTm5qqi+xQdQKU9aL+Ox+MYHBxEfn4+ysrK1PM3jIvpp7SG6jo2MJMkMZMZbkeZyZlO3PK1mR/P12gilKnpCdXJozlMMsT3FzOHBpdrMyeLLj9m8ssJG6t114zUMZNts72EGlLwdzI0NISxsTHVHf3KK69EaWkpnn/+ebS2ts5IsZttXEtZn9Llwoqc4O9kbGwMx48fR01NDe666y7s3LkTiURCyUEkEoHT6YTX64Xf78fk5CT6+vrQ2toKr9eLsrIylcJJ8qbr43y+zLbe6CQUlwV+n5y01XU5ikqkezaMizWOqM4g75TKCTaz58jPTZ/zIBezPc3suZvtpTo5Rzqn2fzW36sZMcVlPxKJYGBgQBHOwWAQsVgM8XhcdYKmzulr166FYRh4+eWX0dnZabon6gTt69Wd5kw8WRl09DlNvPHxcdV5iBaAZDKJwcFB9PX1oaysDBUVFSgvL8ett96KqqoqvPjii7hw4YJSNGlTBaDaCpPXr6ioSC2YtHjqC7PZBDAjm6wWc/172RQX3aOnkz5mDO1cFzGra1pNZv14TpLxZzYb+D1RNA0RGxSpQYY0ef+pC2F3d7ciqCiXnPLpi4uLsXbtWmzatAnl5eVIp9MYGBhAR0cHWltb0d/fj0QioVo+k4HO75Xfz1I0HMzerdlY6ZipqSkkk0lV62njxo3o6urCiy++CJttumg7ES9lZWUIhUKKmKM0PFJiSQm2ejacLLKaWzrMFkCzRTMbOAFKihk/n+79o3lKqbqUBkJrCr8eGUx8o+JGvBVpk00O9Geje+E4kcufs8/nQ0FBAWKxGC5cuIBIJAKHw4FQKKRq1g0NDanIUK/Xi4KCApSWlqKrqwtPPPEEzp49a5pWOp/5vhTl4lLA7z0ajeLgwYMYHR1FRUWFagPb0dGhCCJqbgBkRi4ZhqH2D7fbPWPz5tEZ+pweGxub4X3lzgEgk8DUFXOdfJ6NLOHnMUtHIHCyi86pE7D0Pz8XgQrOkjyNjo6qFHdeg4c/Q/36+pj5dc08n9xY5+emqJuRkREVWUbRzsXFxVi3bh12796tZOTQoUOKBLR6lrPtsbOtWUsNExMTGBwchGEYKCgowOTkJDo7O5FIJFT3u8nJSZSWluLKK69EUVERiouL8eqrr6Kvry/jXERe9fT0ID8/H2vXrlUpODyCmzsqzIiebHsd36+58coVdSB72QP6vv67Pt+5Yagb8jr06EYrY4EIYronABnEHf1PSjqXa7N7ovMQgcUdRfQ3WsOAaY99NBpV0UpnzpxBOp1WpMfU1JRKGw6FQli/fr1y5gHAhQsX0N3djQsXLqCzsxPRaFRFyhEp/2aErvuaOVu4kU1zob+/H/v27UNOTg6uueYabNq0STk6XS4XfD4fCgsL0d/fr76Xn5+vOunG43EVZVhQUJCh15OebGYgA9kNbn38/PscZIzyz/n+QFEfNB7KduCOCzLACSTfZjJh9nyJwOLkAr+2bk/R/kT7j05i8fNzubIirPgYOdLp6U6EIyMjcLlcGQ5bt9uNlStXYteuXVixYgUOHjyIZ599dkYXVB1mpLrZz0sB2YgZs7WQr0NjY2N45pln4PP58O53vxuxWEzVRSLyiZwT1PArFovh2LFjGB4eRnFxsSorAGR2Y9Pfk77eWq2/dB6dvNefO4+65jYAfZ+uQX8n54u+RtAz1OWA/ul7Cz8vjU1/H9mIY7P9gc7PU7t1OSQZ0nVD2qvGx8dVd1OymYLBIIqKihRpODExgcLCQnXNpqYmVFZW4tVXX8XBgwdVzT/6u5ms6nv7pWBeXe2yCSkf6MTEBIaGhjJSEyh1jsIhq6qqUFJSgu3bt6OgoAD79+/HqVOnEA6HM2pjkPHZ09ODiYkJrFixAoWFhSrHnj8cWkjNCn/NttHqkwTINDJ0cFZSV6j1Rdsskmg2cEHTF1/OjupMLcGKZDJbtPXv60YDz6nOzc2Fx+NRChIppLFYDP39/RgZGVEECJEhlF+9YcMGbN68GeXl5ZicnFT1iiikmaKcwuEw4vF41nc2m/dkMWCmhAPZI1HoPZJiVFVVhdWrV6OzsxPnzp1TczAajSIUCqluDWQoer1eJSO0IPFoQDNlmMNsDnMZ4HOPZI23ttXPo98vv0c9UoSTxjpoYdVJKn4v+njmKuNcLvR3ZGX80LH8GXEFjNaD3t5eNDc3Y2BgQG3YVB8iFoup9c3n86GqqgrXXHMNamtr8Ytf/ALHjx9X6WJmSpoOsw3u9w383iYmJtDV1YW2tjalAOfk5CjigtYnqvVELWQpYoSiCXTDWZ9X/GducPNwbP53fd5x+aPrcHKKvONWc00nT62eC63x+nm4LOtKII3fMAzVJZMUF5rPZsSBfr9WitRsiiXf14lQpDocFLlB+7rP58P69etx1113oaSkBF/4whdw7NgxFRmTTd5nk4U3o+FN5BMplFxRJaLe6XQiFAqhvr5eERyHDx9GZ2enIvNoHZuami447vf7sWzZMuUNJgOT5helWMyFLDKLUDAzeuhYfW8xIw343/VzmF2TjjEDP6/ZODiZrOtgwMV0Xqv700lYM3ngzjySJZfLpeoLUU3OZDKJgYEBtLe3q/dLzjyqT1RQUIDVq1dj27ZtqKmpUc48KlvQ29uLkZERtfe8mUknwDrtw2wf5Hv05OQkLly4gNzcXFXTpqmpCYlEAqlUSnV8ikQiSKVS8Hq9yM/PVwYdOfdisRh8Pl8GCaRHk+uyYCYTZmPXx60bevr/+v5PMs0/19dgrk9xA5e+o9feNQwjI8WKR2TwMfI0cX2v0Iue0/PQ0735Psn3F05m63si2ZpDQ0NqfyfSJCcnB5WVldi1axeWL1+OV155BU888YTq/DkX+8JMh18KepbV3KCfZ7OLSH+gmkj79u3D7t27sWnTJvT39yMSiSAcDqu6qhUVFQgEAqpgeyKRQGdnpyq3YrbP68SrbpvregOfKzQ+7iy3egd8Hc1G8tLababv6eBzkM93+r4+b4GZDhnaQ7i+w20I/mzofx6xpd8zvze+xnCHONUBpu5+oVAIbrdbpZZSPcV0Oo26ujqsXr0a0WgUL7/8MiKRiCkfwH+/XPb2vCKeOPSJrx9LETATExMIhUIwDAPhcDhjQ6eOd01NTXA4HAgEAjh8+DC6u7sV4cHrU1AKyvj4OAoLC1VIvt1uz2Bd+Th0JdpK2ecLv5lCpH9G0F88QVdc6DNarGmRpY2CCAY+Zn0D4+PXNxWze9Dv0+z3bBOKT0KKYqJaTjycOJlMor+/X9XrIvIRmC4sXlhYiJUrV2Lt2rUoLy9Xc6GrqwstLS2KsIpGo+jv71eKF4cZoae/i6WC2ZhgnXShOX3mzBns27cPN910k+q8QQZ1IpHAwMAAiouLEQwGEY/HVQ0sqjtG84uMbdpY+JwwW2x1z7FOqOjzkc9js7/z6Ar6nCs03NAlhYbLUTqdVrXidA8F3Quvv0PHkcFktikQ9FREHnJr5pHhiqR+T/Qs6FlFIhF0dnaqsPySkhKUlpbC5XJhZGREeZJycnJQVFSErVu3YsOGDThy5AieeeaZDKJEXzvMyDy6vtnfrT57s4KeeW9vLx555BFcc801KCoqQnl5Odrb2zPSTrkBQOl3Y2NjqjNLKBRSSjona/m8MEvdJlgpBmYyww0SnUwiQpbfo5mhbQYar1mtNrquvm9RdAZdl4rc82O4oqXfr+4N141sM/IAyGxCQPJKjgpa68mQHhkZUTWeQqEQli1bBr/fj1dffRXnzp3LKOj8VsTk5CQikQjGxsZUW2uKCnc6nQgGg6rzYl1dnUqV2Ldvn5ITMrqoOOz58+eRSqVQXV2NQCCA0dFRVXyZO7eAmUYgV86tlFbAPI1G/ztBn38EM52KG7e0D/D0ITPjhu93HFbjpr/NxZGnn0eXY92ZR+l71L2Op/8MDQ2hp6cHiURC/Y32yry8PJSWlmLr1q3YuHEjKioqMDExgXA4rCLIKWp8aGgIfX19qgv0mxl8ndKfsxloztjt06U/zpw5gxdffBHl5eXYvHkzkskkTp8+rZxBgUBAyUggEFC6LnUAjEajqsMuyQ8noPh84N2qdJ2V67LcKZGNpNKNUF33ovPqe5l+Hto36FoU5aDvV3RN+hsfN8mR1T5Fx/HSI/rz0fctq88I+v3E43EMDAwgHo+rursUtZmXl4eCggJs374dtbW12L9/P5566in09/dn6Ff6fszHboWloFeZ6cRm71ufaxx8znV2duKRRx7Bu971Ltx4440YGBjASy+9pEhrOq6mpgZOpxPNzc0YGRlR6Xikt3LbwWrMfK+gn0k/ouM4oWZFMHNdx+FwIJ1Oq2AHToySbUD7CtmzZufTr8kJMd1OymZrk1zz9cpMbyRCajZHo9l1+F5C9t/Q0BB6e3uRm5uL6upqFBYWoq+vD/39/Ypcz83NxY4dO7B7924cO3YMDz30ELq6ulTdN31dzUZuzmbrWuF11XjKBnq5VBw5FArBZrNhaGhIhaUSG5efn4/q6mplbB46dAgdHR3qoZKBCUwbdxMTExgdHUVZWRn8fj9GR0cxMTGhjAl9IvEXOhsRA5iHkpttDNmMbQIXNG7UkHJI5ybDiFLZKHeff48bFHrBPzOihsZrZjhbbSy6l4GfKycnJ8P7OT4+rpQa6sZG9wdMd5kqLi5WNShCoZBSjigEnIxx2kTezMqRvnDNlXwCphWJ0dFRHDp0CNXV1aivr1dGNT1vnnMdCoXQ19enFCEqPEvX5tF6NltmTSY+H3SihpOo+oJv5sHg/+sKvZmBSnNaj5bSj9E9HdQ5kT9XvS6InmJn5jHTFQ49BYnGwskL3TNupvCm09Ph3lSLhVKKqYhvd3e3mtvBYBDbtm3D5s2b0dPTgyeffBLRaFQZ1Pq80Y15Mxml496ssjMX0FoYDodx/vx5tb44nU6cP38+I1LW4/GotAKeLkHRBfQZ97JxcEInm8JkBi4nulKtK01cQTIjb8zAPcfcg0jXpfujtEJKWSbln98Pgf9uZpDrxoh+DK9bpT9Pei9UmJcXviRnhsPhwMTEBCYmJpCfn49gMIirrroKO3fuxEsvvYRf/vKXiMViilyYL36fZCOdTqu0yLGxMYRCIQDTnYRpPhDhXV5ejmuvvRZOpxP79+/HmTNn1HfJQBsfH0dbWxtGR0dRW1uripaTU49HT+vGDY2Hk0X6eqkfT+exOo7vP/o+Sd/Via7JyUk4HA6lU1EK+8jICAzDgMvlgtPptNQJda82nYPLqx7Voe+HsxkOPDWbdFuSU8MwVBFoYDotqq+vT7XC5sZSfn4+QqEQmpqasGHDBlRXVyOdni6Y3NnZidbWVvT29iIej6taH29mvYpDN0izEfRmRMLIyAgOHTqEuro63HDDDdiyZQuGh4fR09ODdDqt6gOGw2FV34/KHVDDm+HhYRURpUdZ6HYC/ztfY/n4dXJUB9c7uF5vZtdwhx0V1k6np1M0KbWKE2LARXKICISxsbEZnU/NxsUNf34srRl0v5wc5vfOnXdctqxkn843NTWFoaEh5bggIpY6SxKRu2rVKtTV1eHFF1/E008/rVrEc+M6G0lsRWwuBeLJDGbybUVQ8XdAeufevXsRCARwxx134G1vextGR0fx6quvIh6PY3h4GABQUFCA8vJypFIptLS0YGhoCH6/H8Fg0NLO5nOIzxGuW9O4zH42+52f1zAMVfIlJydHrfW0P/I0QN7RjuaBmb1D+wH/rj4v9bFz/sHs/rPpjHMhnXSyi9tqhjEd7EOFwQOBAPx+v6qhzLPBamtrsWbNGgwPD+P5559X2WQ6kcRl1Oz9vB6d6rIRT2bKKnCxHTB5a3w+n6pPQAWni4uL4fF4UFlZid27d8Pv92P//v1obm5WxgIpSbm5uYjH46omVEVFhermQoSW/jDMFg2zScBfrq7sEGZTiswMVWBa+XY6nSgoKMD4+Dh6e3vVRkd1sagSP7HHfr9fjZ8r+xQuR7WweH6rrhRZwYoFt/qckwtU24lIp2g0mpGCQooeRedQat7ExAQikQja2trQ1dWlNnKq6ZRIJLKO2WqsSw26cmRlePK5Sorl4OAgnn/+eVRUVGDDhg3KyB4aGlJRhE6nE8XFxaq1KaURUadFMkipiJ7e2UgHzR2eBmMGPl5dsaDz6M+A5IGurUdJUPQPedopTNQwDDW3KZqRkwaUjsPrDtB4dAKQK/tW74b+Tvehk3EEHmpO92S32zEyMoLBwUFMTU2hsrISy5cvh8PhQG9vL7q7uxGPx2Gz2eDz+bBp0ybceOONSKfTePTRR3Ho0CFT0slMcdY/0//G/261yb2ZQRtsa2srCgoKcPXVV2P79u2oqqrCs88+i0gkglAohNzcXCQSCYyPj8PlcsFun65PR9EhDocjI9LJzCPFDQV613prWzOlLht5y8EJTsC8QL+VYaXvO3zOOhwOlJWVIZ1Oq85/ZIjopLguN/p5dSOBf86dLmb7DYW2k/yPjo6it7cXqVRKyYLT6UQgEMDExASi0ShcLhf8fj+2bt2KO+64Aw6HA7/+9a/R3NycIXPzXfuX6l5xqTAMQ3n30+m0Kv5KJFEymURhYaGKHLvqqqtUmun58+fVOksdigzDQE9PD8bGxlBTU4NgMAiHw6HIW5vNlkH46fOer526UWFFaOr3w8/J68+YySVF7JGCPTw8jIGBAZVuE4vFlN5JHvFgMJiRFsLljp4N7Tn8GP14fk9mMDOYzWSVDAGSHyLHU6kU+vv7lcFA9wsAbrcbJSUlWLFiBRoaGlBYWIiJiQn09vaitbUVra2tGBgYUNGd5Nj7fZn/Zob0bMcDmVHavb29eOyxx5Cbm4srrrgCV155JU6dOoUzZ87AbrfD6/VieHgYZ8+eVTVSSkpKkJubi3A4rArzV1dXw+fzZURa0DU5mWnmtJ6Ljq4fq6/b/Fo0R2gcZGRT2jl1Q6Z5Sd3IqIi62+1GQUEBbDYburq6VNt50rH4nsdJIrOxEsh5oxNTnDDWCUSztZ07NKjhVDgcxsTEhJJdm82GsbExuFwuVFdXY+XKldiyZQui0aginXg9Nqu5wufXUrY35rIHWhFnuk5B7ycSieDxxx9Hfn4+br/9drzrXe9CXl4eDh8+jEgkgqGhIXR1daGkpAShUEg1KSAi1izrSAcn3/lYuI7O54E+d8zmCc19LlNU3ofmMZ2bOlmSDe33+9V+QRlZfCx0TdrPaE6THHA9nOYWv0fukKHf+d7AbQh+TQIna/nf9XNSmZqRkRHk5eUhGAwinU4rcpb2mbKyMmzfvh1erxe//e1vcfr0aSUXZrJhJgNm9ux8ccnEk5VCbHZMOp1WBcKpPgEPd0yn00opKCoqwpVXXqlajZ87dw4jIyPKGwpATXDaAMrKylRLWa7sEszGaeaZ0FlKK6PBzOtNk17/G1cqcnJyUF1dDb/fjyNHjuDcuXOq6wR5F7m3Qj8nGSnE7NvtdlUE1syrYgWr92a24FLdFMMwlHfa6XQiGo2qMFcCvVPqyBIIBFT3A6fTiba2NrS3tyuSLZlMYmhoCJFIRLX21ckYK6NrKcNqwzIj9XTScmJiAs3NzXj55ZdxzTXXYOvWrfB4PDh06JAqoNjT04OSkhIUFBQolpsUBzqPTsBw5ZkXouQLqJlhrC+ENB/0sc/VGORKBC3SnPCiyEZe5BaY3rBo3tM6wg13bjybKaa68sSfEydMzTZkfVPgGxw9u5GREVW8mor3DQwMqMKupNBu3LgRN910E/Ly8vDYY49h3759inDV573ZfNGfs9m9WpHHvy8gA+2VV15BYWGhSmn0er0qopYKwxLZ4vF4YBgGEomEKrJYVFSUUbCRlALuweYRcbMp3LrBrc9FK2KUX8NMKdOdChz8GGB6ziYSCbS3tyvHBDdu9TQMrtDo+0a2eWQlJ1zxo7S4ycnpTo7UxjsvLw8ejwehUEil1w0PD2NsbAyFhYUoLCzE+vXrkZOTgyeffBLd3d0ZnnPBRZCzYnR0FIWFhbDb7Th9+jTC4TBqa2tRVVWF8fFxeL1ebNiwAXa7HT6fD6dPn8bAwIAiWvLy8mAYBmKxGDo6OjA5OakKyvJIHCuim2BmcOufm5H6ZjqV2dzkdT8oYmj16tWqQUd/f79SxMnoIJ3JLC2KdCdqIsBTnbk+ZEb06zKj7x+6nPPPaZ8DpsmkvLw8Ve8ymUyqrnOcHCe9inRlt9uNyclJFUHe3t6uoptIP/t9Ip0AzPpO+N/0tZTPwfPnz+PHP/4xBgYGcOutt6KxsREvvfQSnn32WbWGk15KBA1wcV0jYtPv96vud/z6ZgYiHz9gPuf5/egGsB6dTcdy+4IcM+l0WkUwERFNdfS4UUz6VyKRQCQSgc12sUwG73DKi4rrMq+TYvp9mkW30LFWBjd9n+Y+dX4cGBhQ3boovY5qnNK+EgwGUV1dDY/Hg+PHj2N4eHhGpBMnL+arLy0FebIag5keru/3Zj/T8xwcHMQjjzwCr9eLXbt2KefPoUOHMDw8jPb2doyNjamI/vHxcRXpX1BQkBHdw0HPfi7PWh+j1TprNg+JawBmpr7yZ5SXl6cCWThxxceeTdfgY9D3Oa7X8bXIbO7R9bhMmsk7vw4FGJDdRPWSac8oKiqC3+9HPB5XmUhU+qO6uhoFBQU4deoUDhw4oGoG0ruh9WSh8boinrIxx2bGN4XYj4+PIxAIwG6348yZM4hGo6iqqkJFRQWKiorgdruxbt065OTkwOFwoLm5GYODgxgbG1OV2yllh4r1UtqdzWZTJAZd12qiAtaTi092fRGlv3Mjnj7jZBsZMTSBaEMIBAIoKyvLqIvEoRvHdE6zeiDUYpkbz3zizoUV54aDvmmT8OTn58Pj8WBychLt7e1oaWlRbTSJDDAMQ3X98Hq98Pl8WLZsGYLBINrb29HZ2ak6F5LngpRfum+rzUv/bKka17rCqi/yOrnAFXEinhKJBJ5//nl4PB7s3LkTVVVVsNlsOHjwoFpgACgFlMLp6R3R/OOGsq740rzV55XVPfFIH1LQdU+wPvfMlHBSQEi+DMNQ3hT6LD8/X3m0+fdpjqdSKTXndbm2UvbpMzpGNyB0OaF5bZaKp4PqaOTk5KC0tBQejwcDAwPo6upS6UGhUAgbN27EnXfeifLycjz22GN4/PHHEYlEFNms34P+M42Lw2xOmZFRv08wDEPV3Th16hScTie2bNmCHTt2IC8vDx0dHcjNzUV5eTnsdjsikQgKCgpQUVGhPNbUcdDv988gUs3kRk81050UfP2lY/T3qHu/6N3pRBe/Dje4ObiSpBMyFOHEn5cewWEWlaX/bvbc9bnFDXm+D9HYACijZmpqukudz+dTrY3JSE4kEvB4PKivr8d1112H6upq/OhHP8Kzzz6r0oTeqnWdZsPExIQyrsjAotTtcDiM8vJy1NbWqtbJPp8PoVAIR48eVSl2ZLhRPcGuri6lxLpcLqW/zcVY4+9J14V0vUpP2+ZkkL7WmZFflE5E9d7i8bhKu7BaR3U9CbhYHsDhcMyoS0PH0vw2k1ku+7M9HzqP3W6Hx+OB1+tVUU6kz9I56LxOpxMlJSUIBoNKf8zPz0dLSwtaWlowODiIZDKpGvj09/crXev3CVxvMDOyAfM0PP4ZnSMcDuPpp59GWVkZNm/ejLVr1yKRSODAgQOqoDhFyPp8PlXSIBaLIZlMoru7G16vF9XV1cjNzVX6MJCpJ8ymh+vzXK/fROMno9BMRzZbd4nwt9JlyElvt9uVo1sH1/n49czGzckl3WjWCeVsxBTdIxHiHo8HExMTqlYNGdKUWktBCVR7KxAIAACOHDmCV155BWNjYzPSZq3mDoe+1i11mJGy87lPWjN7enrwX//1X0gmk7jxxhvxjne8A263WwVLdHR0YHx8XDXOGRgYQH9/P3JzcxEIBGbs01w/MlsP9ffCgyjoeJ7ZwNduOi8v3g3MbE5Bn5GNRc7LcDiccQyvR5kN2eYFBYTQuPl85/oV2e/8PnRnN78e3zvp/ux2e4bjzufzobi4WGXHjI+PIycnB6FQCNu2bUNDQwPGxsbw/PPPz9hraH3R9Vuze+fv51LkY17E01wvYiYA9Pvk5KRKG+JKK3XpisViKC0tRWFhIdasWaM6dxw7dgx9fX1IpVIZ4dM0gWihovB98uRdCjHBX4RODvAiZfxezZRy+pkM/PHxcbS3tyMejysijRZNs43GzAvNBYoMVv4Zr4rPx8ENI53V1DckIiao1o7T6YTP5wMA9PT0oK2tTXVHmZiYUMQRhTAGg0GsWrUKK1asgGEYaG1tRUdHh6otQRsiFUnlz2ou7ybb74uJbIuq2TGcKODHUdrJvn37EAgEcMUVV+Cqq65CKpXCa6+9hlgspgr+UZg0RXJQ5AdwMZVH33T5tTihRGMyW3TNirXyRZrmL59XOgGqbxZmixttPNkKueoGPP+bmdeCk7f8Hq0iWOh4HqKrX5OuMzU1pZR+nvbR1tamIqCCwSA2bNiAt7/97aiursbzzz+Pxx57DAMDAzOMo2zEa7a5pB+z1AjZ1wNdZoCLEXAXLlzAyMgIPB4Prr76agQCATz++OPo6+uDw+GAz+dTUVB2ux3BYFBFpw0ODiqlhULF6Rp8TeSKPMHKC80JWfouvVcr7xtXYsyIH11OSLHRyR99nvO/8fXfKqWPzpGNHDPzbvNxUPpDbm6uMoJHRkaUkV1XVwe/36/WuMHBQaRSKfh8PgSDQdx2221Yv349HnnkEezZswcjIyOmz0AwDf7sR0ZGMpxAVAyZIozLy8sRCoWwfPlylYb3zDPPoLW1NeN7lGJHdemIfLLb7Sra1Grt0dcfs/1Z3wf4d6y8rVyn4XMxkUjg9OnTyM/PV/U/qUiqLktmexvXh+x2u4oKofPT/szvR3da0Oe6A0YnSEg/s9vtyqB2Op3o6upCR0cHenp6FLnHjRCq6UjkR1VVFTweD5qbm5U+aRjTNaIGBwdVBNzvK+biWDHbK/laS3/v7e1Vnc527dqFK664AvF4HGNjYxkNXHw+n3r+tMcnEgnVKa+kpARTU1MZhZi5g81sDedGNtdXzPRx+hufi3yt5jLEHQB6JzkdVMpAj7QwW9/Nnrtu2JN9xO+R3zMdx89ptecQER4Oh1UdWQAqPZDsPJLZwsJCXHXVVVi7di1aW1vx8ssvKwKd23N0D2aOU52wNMNS1K2yyYSZjWpmh3A9vr+/H0eOHEFTUxNWrVqFtWvXqv2aupGPjo6q+k7Dw8Po6+uD3T5dE82MgOVzjJNQZnONr99c5+MRe1x2dNngskUgW0gP4KD/af7SOWnseu1YTsyY6UNm85zDTH7085np/pzAI5BzKZVKIT8/H0VFRZiamu5WS3oXlfdYu3YtAGDPnj24cOGC4lH0cep6pT6WyzH/50w86WSS1UTPxrTySRWPxxXpQi+cPDU1NTWora2F3+/HypUrVQ2oV199FR0dHUilUoqsooLDtFkEAgEUFhbC6XSqlDW9doo+bjMh1A1xfcGif7pgAJmTkU8Sw5ju5kbhz7xYMp/QROhQPqqZQqMv2HSPFAGle/XonmiMfMx6Yb/c3Fzl+fN4PKouV1tbG1pbW1X4MU9/zMvLg9frRUlJCTZt2oTNmzcDgGLJyRNJqYX086USR5fKtC4k9DmlK+JzGTN9h+qAPfbYY7DZbFixYgXe9ra3IT8/H8ePH0c0GlWF5Fwul1J60uk0SktL4fP51BzhbLtOHNEcMVvs+D3pCoZVFwb9vvlnOjmkG+9cQcj2XPl49Y2An2+2cZmF4urviKch8s2JjGsydEju4vE4otEoRkdHVTvTiooKrFmzBmVlZejq6sKxY8dUpCPJpE46c5k383LOZR4tRQXpUmB1L+n0dFOGvr4+HDp0COvXr0ddXR0aGhqQSqUwPj6uIgVIaQoEAmhoaFAGW0dHB5xOp+oAQvsR75KlzxudmNJlnM8V3XA1835zI9PMuNBlkNZyvrbrx5ADgitZujGk7+H6ec32C92A4vdF8kTteikE3263o7y8HMXFxfD7/Wp/oroK+fn58Pv9qK6uxuTkJF566SXlqdZl+1KwFPeKhQCRD9S5KRAIwOVyqWLB7e3tKC4uxvLly9HQ0IA77rgDOTk5ePjhhxEOh1U6WjqdVnUzSakNBoMIBoMqrYjSns0MZzNCE8hcg/U9ieYOT7E209E4eWSzTdd16enpUcVkqbMV181o/tCY9RqGOlHM9ye73T5jfyLj3mazZTj+OHSnBqWRUxQ/dUyjGo6Dg4MZ0WoUjeJwOBTxVF9fj9raWjidTnR3d6suhVx//n0nnQDzOWX2+1wM26mpKZw9exaJRAJ5eXnYunUrKioq0NbWphwW1LWZ6glRIeXR0VFEo1GcOHECtbW1CAaDGfUoCXqkAofuhDOzrfR5zMsLmK3dtL5yOeT7GM1pHlVI3+FrP53PirTSdRZ+v2brNp1TJwW4M5/eid1uV0Y11XMisrawsBA5OTkYHh5WHe0KCwuxc+dO7NixA62trfjtb3+Ljo4OtZ7psDKqrZ6/fo9LFXPV+bhOq5MvOTk5GB8fx5EjR5CTk4O7774bGzduhM/nU+UjqMwKrXM223QTk3A4rJwUwEwSJtsz1HUVnSTjRD6HWaCF/jM/h/53fj06lh9vZhvp+pNO2vK6y2ZjpWP55/o5rAgtwvj4uKqxnJ+fr4JD6LOcnBz4fD5s3boV1157LWKxGE6cOIEXXnhBlT7i74Q/G6vnx/F65GHeqXazsWFz/W46nc5QkoLBIPLz8xWDTTmj1dXVqKysxM0334yysjI8//zzaG5uVqHlFCJKNQpIUfL7/fB6vUoh4XVhdHadK/lWihNXsPmxBKvFmbOxvD4O5Sfr9Xb4JOaedtpsdMNF9z4So2u2sJgJEQkzEU6kGPn9fpXXPjw8jM7OTnR3dytvIo8oI8OhoqICjY2NqK+vRyKRwLlz51SNrng8nlGri0/6SzWQl5phbUa6mnmkrBZIPg/t9unw556eHjz66KNobGzE9ddfj127dsHlcuHEiROqHgTvkphIJNDR0YFQKKQMBa5UkOLOlQAzcKPWbNGlsXPvg75oc+hzjv9v9hyy/U3/TIe+aPN0WF1Z0uVdV1LoWelklM02XQuBop0oZYtSHAKBAEpKSlBXV4etW7fiiiuuQEdHBx588EEcOHBApQOTDJltMGZrrZnMmBnWv2/Gttm90AY/NTWF48eP43vf+x5uuOEGbN++HQUFBTh69Cj6+voyam6Nj4+joqICJSUlyM/PR19fH8bGxhCLxVSaKskLraVmyrjZuLiixP/R++TvRI9Oog5JVu9Xhxn5pEdB6caPGaGrk798XLpCpyvlZoYHRaHwNHIqdl5UVKTWHNoP3G43AoEAdu/eje3bt6OlpQU//vGPVaH+10s68bG9VUBh9vF4HMFgEH6/H4ZhqIKrFPG3Zs0a7N69G4lEAi+88IIqKky6GXUYNIxpRwjVEvT7/cjLy1PELDe0rRRy/W+0X3DP8lz0KT7vac7TeuxwOJQzj8hjGoduGNPf6Xx876XrW+lS+nrAZYAbbzReihp3OBwqQhmYjrY5d+4cIpGIIo94JgClzhcXF2Pz5s248sorMT4+jkOHDqnuhFRzaHJyEolEIiOC/K2AbCSU2XrHf6b5Rx26nn76aZSXl2PLli1wu91IpVKIx+MYHx9XTVyKiopQVFSkuqZSVGBXVxcMw5jRXVgnloCZaXF65J/VmOl3np5Kc91qrdfJKV0m6Xg9vZQcFzy9iY9Hd3jrDgh9jDRuTuZyUpbOTfpQMplEOBxWJRi8Xq+qGZufn4/+/n5VSNntdmPLli249tprceLECTz66KNoa2tTER1Wdgbfr7nuakamZXsnSwlmhAXBjGTjn/O1mYi/gwcPIhqN4s4778T69etx1VVX4fDhwwCm9alIJKLShROJhCKeiISl8+p2BzC7vU1zm6/RcyFFzHRhui/goszRfORrNf9f38t0MtVs39IdKlaEMz+nmR6mn0+/RypVE4lEFMHkcDgQjUYRi8VU4fTVq1fj6quvRjKZxKOPPorW1lYMDw+r2qd8Hco2Z3S7y8qenSted1c7q8k727H08/j4uCqCGAgElCGRSCTUxI7H41i7di2uu+46lJSU4LnnnsPhw4dVFXoilailLm3AsVgMbrdbLVZcUQIwQ2nQPV0EMwHR78lq8ulKO10/FAqhrKxMFRbnUQ+GMV0Mt7y8HOn0dB2rsbExFf1kthllY+mtvCx0HClH5K32+/0IhUIYGxtDe3u7qlVDGwoPZae83hUrVmD9+vWoqqpCTk4Oenp60N3djVgspu6ZanRZEQlmxpbVZjyX+bYYMFsE9Q0tG/T5OD4+jo6ODnR1deH06dO46aabcMstt2DVqlV48skn0dzcrLyeTqdTeXy7u7sRDodRXFyMoqIi5cEmz5c+NiCTTOWf63OKf5eOp7lB5Gq2++VGMi3+/Lo0FiAz5FU3Hvjf6O9c0TEzjkkmaQ3g3m/9nKSEccKY/kapWkNDQ/B6vTAMQ0UNUHHLpqYm7Nq1C7W1tTh16hQeeughHDp0SBVdNttA9c+tlKVs5NNSlY2FACkmY2NjOHPmDACgpKQETU1Nqovm6OgonE4nXC6Xkg0qSG4YhkpHAqbbBVMtOwJfx60ifvh8MyMy+bzWDVgePs6PsyJx6Xpm6zoAlc5Mih7fu/Sx6WHk+vqjGzf8WB4xSGOZnJxEd3c3hoeHYRiG6sC5ZcsW+P1+dHR04LXXXkNPTw9sNhtKS0tRU1ODG2+8EbFYDE8//bQK2V/KCv5SRzqdVgWFiaAIBoOYmppCKpVCMpnE6OgoNm3ahHe+853w+/3Yu3cvzp8/r/Z33u2G/tH5nE6ncuzx6AnuLDMzCvT0CBprNvLfLLqWyxp1OKVI97GxMaRSKbXe0zymOm/UgXRychJut3vGXqEbN2aFo7mxro+N7oVIMWrvTt02qUhvT0+PSpPj0eMA1HfKy8uxYcMGrF69GolEAq+99hrOnTunUljJmUfRXCIz0zDbR610Y/pbc3Mz7r//fkSjUWzYsAG33norXC4XLly4gL6+PvT19SGRSKg01eLiYhQXF6v6pa2traojJL2LbMS5/ncrx5Kup/G5yvcbq3NxOTDbZ8yMeX3/o+/YbJn117gtZabz6XsQJ6T0tHR+LSKdDMNAIBBAeXm5ikhua2vDyMiI6mC5cuVKbN68GYcOHcIjjzyimofoBJyVTaH/zp9VNl1sqcFqrLOtCWb6PXd+v/baaxgcHMSOHTvwB3/wB/D5fEofHhwcxMjIiApYyM3NRXd3NwYHB+HxeBQp5XK5VCd2PR1TB9eD6T2YBYxwhzJ9ppOwHPx4LmOk49N1+XzP9py4w0UnjPjeZva8zfYMft9ctnVSeWRkBP39/YjH47Db7UpfpehM6mq3fv167N69G06nE48++ihOnjw5I+iD3082my1bIMKlYF7EUzY2VT/G7DtmA6ZFjgr2jYyMIBQKKaZ6ampKKUmrV69WxTGDwSBefvll1QKYFCUyPsmDTC+DvEdUmJy/WDKa9fHpkUfAxYVWD3flL1H3AvAxkUeKUgKnpqZUyChtELSw5+fnIxAIIDc3F319fRk5rmaGqpmgmEU56QYHEUjUCcpmm26p2tPTo6IEeHg9nTc3NxcFBQVYt24dNm7cqDrodHZ2qu51vHYXvSd+XRqPbkTPRlzwe1wqyEYAzhX6vdG/qakplXo3OTmJrVu34pprrsHU1JQKuU+lUnA4HHC73bDZbCpdjzoe5eTkZLQ95QuumRJkNi4rBp+/B92zwI/XiSDaKMyenf5c+Zh0RYf+nu0c3HvCo0M4+MZFx5FMkneZaj9Q16Tx8XE1t4PBIOrq6rBlyxZcccUVCAQCeP755/HQQw+pvGor0sls3Prf9fdhhkude29WkHykUimcPn0aTz31FLZv345Vq1ahuLgYe/bsQVdXFwKBAHJychCNRjEyMgK/34/y8nIAFxUop9MJp9Opzm2WZgPMnNu6x9osykl/L3oEiP49fm6zemRmSgmBKy1E4ui13jh05wqdi5NkdA76nBPPwPTeyAt2OhwOFBUVKcM5Ho/j1KlT6O/vx/j4OAoLC9HY2IgtW7bgxIkTeOaZZ/Daa69l7KGC1wdKwU4mk4jFYqq4O61DDocD69atwzXXXIOCggI8++yzOHXqFIaGhpQeQg4j0hEcDkdGqQNqTU0OBZpDpI/pzgT+M/+fd84y20/0dZCcibzAOK8tRvdI50un06pWj81mQyQSyTCCAHPj34yYpd8BczKXojpsNhtcLpcqV0C6EdU5pbQ6ivSg7wUCAaxcuRJNTU2or68HADQ3N6v6mhMTE6qYuFVNxLcSzPRFK/JJf4d8zTt79ix+8pOfYGhoCLfeeiuKi4tx+PBh/Pa3v0Vvby+Gh4cVoRsIBFBQUICqqirV9GV4eFjtIXxN5TqFLgdW0X1mx+jGsa476/PWSq8z049m0xu4HOpz30o304kA7hzhmR50fCqVUjVM7XY7XC6XKmKdk5ODoaEhlVrkcDhQXFyMtWvXIj8/XwUj6AWTre7Jityb7TkshX1Jf49mY9bvyYx4zUYk8LnV19eHp59+GitXrsSWLVtQXl6OZ555Bq+88goGBgZUEXuqW0e1nCORiCrZwh0VVnWFae/Xm6OY7SEc/N50GeMwc2KTXmPmNNfnOZ9X3G7Rs5ayjYHfC5dV/l74d3NypjutRqNR9Pf3q659lM1CzVdycnLg8XjQ0NCAq666CvX19Th58iSeeOIJ9Pb2qmYTenaKvibyMWZ71q8Hl5xqZwUrA0mf4GaCMz4+jqGhISQSCYyMjKjuaKlUSr1IyqXevXs3fD4fDhw4gAsXLmR0vqHUury8PBUqTpE69BlPdaMXaxUaZzaB9EWTjqP70UkrIsFo8aYcTK4wUWFJm82GWCyGU6dOIRgMwuFwIC8vz7QmDTfoqRg4PU9dGeHjpVDXqanpbjbESCeTSQwNDamURar7QJ0h6LtUUHHdunXYtm0bQqEQhoaG0NnZia6uLuWRi8ViGUXE9YV9NmXB6rOlCk5o8rkwGwmQbZOjc46PjyMcDuN3v/sdRkdHsXPnTtx22204ceIEzp49i5aWFoyOjsLj8WQUg41EImojLyoqQllZGQKBAFKplOoQpxvD+uIHzCwSzhdg+jt9l5NaZvdoppQQSI6sSDF98+DnteoOR8dyGSJZ4YQofYc2RjKmo9GoSmukv7vdbkxNTSnvW2FhIerr63Httddiw4YNGBwcxE9/+lMcPHhQdWOh+5sPrJQhM0LqrQpOPu3duxcDAwO46667UF9fjw0bNiCVSqG7u1sRRmS0+f1+lJWVwWazIRwOq4LjBQUFyM/PnxEZp0cM6oYNHw+HXitJV/rMDF1SwLh3kPYoPid0JSeb4kzjoPvRjXp9PHzO8j2Ny+DU1BTC4TBisZgiKCj8u6ioCE6nE0ePHkU8HkdnZ6fqQLR582Zce+21SKVS+O53v4v+/v4Mhe71Itv7eKuBDIHx8XGEQiHlkKOU+ZqaGjQ1NcHr9aK0tBSvvPKKelfA9PMjomRiYkI1EiG9imoYud1uuN1ulapDtYqsopaAmSkeelqFlU7Fo2VHR0cRiURU0eHi4mIVDWQY087Nvr4+jI+PqzpjTqfTUk4JpO/wv+mGP42JR8+S0ex2u2G3T3fWpK5cqVRKRYBzco72FJfLhVWrVmHHjh1YtmwZJiYmVAHyoaEhVY5idHQ0IzWPxmY1199MelQ2mO17ZkQKkD1imB/L19KBgQE89dRTKCkpwdVXXw232414PI49e/ZgaGhI7SWxWAyGYai6Q5TGOjw8rBx9wEXiSCefrIgOfc6b3Qs/J8kLOcis9AJ9v6LvkV6vr/1cznQZ1GHlkOSgvYzXTyQ9mZ5bIpFQtW3dbreKVM7Ly1M1n0i/DYVCuP7667F+/Xrs378fp0+fzuhgZ7U/8udhpk+ZGeL8mKUCPn4rAmousmJFTNGxVOolkUjgP//zP9Hf34+3v/3tuP322+F2u3Ho0CEVvUl2u9vtVpGYY2NjGBoawtDQkCoJQtGfdA2q38WbIekEDY/Os9JFrO6T5nc2Aot0GZ3k5c/GjOA3kw0al9l1+Oe6ncTtCwoQoOdHe0dOTo4inch2IQdQbW0tbrjhBtTW1uLll1/G7373O/T09GREZ+k6KP9Mt9fMCFmz5ztf2Iw5fnu20HerBR6w3gSybZAUQlZYWKjqDZGHura2FuXl5bDZpiNzDh8+jGPHjqG3tzejZgo9MCqWTcUdeS0jr9cLj8ejlCRKBXu9Bh0nDGg8lFaXTCYzFnZSgmhBJgLJbrerjnJUf0SPuCKPGXXGo/NQhBKxr1aMP40tGo0q5ppqDRAxobOvLpcL5eXl2LRpE9atWwe3243e3l6cOXNGhQCOjo5iaGhIGSOzKZ06GTUXxWI2FvyNgi6sc00TMTM2symRfD4HAgG87W1vw6ZNm9Db24vDhw/jwoULytNL84DmNBkAAODxeFBWVoZgMAhgJsmqE0d8/li1aQcyw03NcvzN5qAe8cRT8ICZYd5mz48rPfw6Zgs6yaXdbldRkclkUj0fwzCUMcbrZwDTHvb8/Hzl3acC+S6XC4WFhVi1ahVuuOEGNDQ04PDhw/jNb36D48ePq2KvZga1/o7NNgM6Tv+ZrzH697gxt9i43OSYlQHFSXWPx4NNmzZh69atWLZsGdrb23Hs2DF0dHSo9G2bzaZSUScmJpRh53A4UFlZCb/fP2P+cQJG99px0oTPQf65lcxz4hfIlEP6nO47m1KjK0j6NXWCiXvlubdPV/7od7pnkhdyMFCtRTKeQ6EQ/H4//H4/XC4XRkdHce7cOUxMTMDj8WDVqlW4+uqrce7cObz44ovo7OxUHrnXu57PVc+Y7W9vBF6PbOhe2Llej9Lpg8EgioqKUFlZierqapSUlKC4uBh2ux0tLS148cUXcfLkSdUtjo+X1uq8vDxlTNAc8vv9KC4uhtvtxvj4uHJg0RyZLcLDCnrBVsMwVP2dsbGxjL2GFHHS9WhuUwdLv9+viCeSlXQ6jYGBAaWk0/ccDgcAZBQq1vcjTk5Reh0Za0NDQxgeHkYqlVKkEa8/Q88tFAph1apVKCwsxMaNG1FUVISRkRG0tbWhq6sLfX19iEQiGB4eVgSU2fu9XHN6qcqGmS6gf4frk9x4NNOpODjxuXz5crz73e9GU1MTcnJy8Pjjj2P//v0qy8Jms8Hr9aKyshJerxfd3d0YGBhAbm4uSktLUVBQoNZpMp71gsL8fx30PTIsdcKK7xVWkapmeoAZsUVjy6YvcKJqPtAdlhzxeFwRTmS75eXloaqqCgUFBYqcSKVS6O3tVcRxTU0Ndu3ahbKyMrz00kvYs2cP+vv7FRltphPNF9nskMXWq3QbQycw52vDWhFuuqwRob5jxw684x3vQHl5OV599VXs2bMH7e3tGQ5ut9utCHJa/4ksp27PVD6GauCRjavbhzziW59HVqSnmUyY1UezSrUzO6duG9Fnul5F1+fR5lZj43tHbm6uahYViUQUp0G1F4m3oCARACgtLVXZR9deey3q6+tx4MAB1a2T9t1shHQ26Pepfzbf8wHzIJ50ZZlfxIwR04kn/lL0G8hmROTn5yMYDCIQCMDj8SAUCqGoqAihUAilpaWqDtKZM2dw4MABnDt3DtFodEbqHE0CUpJoQXM4HCgsLERhYSHy8/NVdA9XDvT7pfGSwmBlXJAQjYyMKOWL2F1KhyJyh5R6IsMCgQDcbrfKk/X7/apdO0U/0YSisHeKDKNUEV5skndVAaZr1JBSNDAwgHA4jNHRUSUolErEPSo2mw3BYBD19fVYvXo1VqxYgdzcXLS3t6O5uVkxsiMjI4hGoyoKzezd6gsIn19mG1Q2A30pEU9mSrXZoj7XTcFKjnJyclBSUoLt27ejrq4Ovb29Ko2FcuN9Pp9aoCYmJpCbm6vmtt1uV3UKSAHXjWI9+klXWAh6wXurRclMQdINaPpdX+B4CodO4Jgt+nQu/fr8uiQLlEpCRhInSykykqICKYSeSNW8vDzU1NRg06ZN2L17N4LBIJ577jn8+te/Rk9PjxprNpLATDnWn5+uWOj3bgZafxYbl5N4ms2wItmgdxcKhfDud78bGzduRCQSwW9/+1ucPn1apf7m5+ejvLwcgUAAIyMjaG9vV8Stz+dTdWP0iDir2hbZlB9O8vB7MZu7ZqQT34u4zFnJEo3TMAyV7pNMJhGPxxV5SulI+fn56lyceOLj4/VoIpGIGhN5Cckz7ff7VcQYpWpTpExubi7WrVuHrVu3Ip1O44c//KFKj3i967iujM9FtVmqxrV+jNkewp1PXCchzBbq7/F4UFFRgbKyMjidTrjdblRXV2PFihUoLi5WHbteeuklnD9/Xr1/fdykt9B6Sk7DYDCYUd8jnU5nFCPnc43IeXK6cc+3fm/j4+OIxWIqcojmt8vlQjqdVjWtSD9zuVyqMDE58Xw+n6pl6fV6FUnU3d2tPPW0B/DUdYqooGh12id59MnU1BSGhobQ29ur6pAaxnQaEXUT4vsspQytW7cOmzdvVs+tq6sLFy5cQEdHBxKJhNLXKHJtobFUZYMbh3M1mnRkM9K5EbpixQqsWbMGd999N2w2G5566ins27dP1RGi2qsVFRXIzc1VpFReXh5KS0sznHvcsDWzFXT51p0C3OjV742+p9+X1X6kp2eafX+u+/ZsJAd3/Nts0/UYKaulv78fyWRS6WN2ux2BQAA1NTUoKChQ9ReJ/A4EAqrItd/vx29+8xu88soryuFKz3CuurbZfWc7jrAUiCeCGaHKwSPvsiGbjUWgJl60j7/rXe9CY2MjTp48iWeeeUZ16MzJyUFhYSG8Xm/G+kiRqbFYTAVcUIMRqpWqN8wyA42Ny1I2IojrX9yGIhnRs5cuhYzhf6O/644S3bbhuh09j7GxMXR1dWFwcFCt8+TgoeYZpFMFg0E0NTWhpqYG9fX1KCwsxAsvvKCi/qmkihnfYnWv87Ez3hDiiV/YatB8U9DZdNqU9ZBp/Vj+cOjFuN1uRThR95KioiIsW7YMNTU18Pl8iMViOHnyJA4cOKDaZZsRUKTc8M3f5XIphcTtditFSl9gyPPH8/gBZNRAop+JDCJPrsPhUGMnRZ82LyKQeDoeRRdRyKnH40FRUZHa0Fwulwp5t9lsKjqDzs0jNsbGxpBMJtVCTqkR8XhcKUK0Kei1mGy2aUa6qqoK69evR0NDg+osQV4eSquj+inc80DzRJ+8/G9m88nM8DYz0JcS8cSf2WzH8/sxexb8eJ2sJYW1oKAAN954I7Zv347Ozk7s2bMHzc3NSimnqAMAcDqdqv4FkbOBQADFxcVq0TcjibkMmBm3ehg5YG2Am/0NuOjNpo1tNu+FWWQU9y6YpXYQ6D7JixiJRDA4OKieGT0rirSkDk52u12lO5LxXlRUhLe//e245pprkEql8Oijj+LZZ59FLBabQRaY3bu+3mWD2ebBz2O2oSy2bACXP+LJ7Pz6vXNHw4oVK7Bz506sX78e58+fR0tLC44cOaKUWbvdDofDgZKSErjdbkQiEbVpFxYWoqSkRBnDOvh1eZi2mTyYpVfwMdP59PdmRqDq4DLI1xDar2pra1FdXY2+vj40NzfPSLmjfYuuT3sWjYXateseQ26Al5SUKMeOYRgYHh5WbchpH6upqUFpaSl6e3uVs8IsEnAusJKd+ZxrqRrXl3KeS7kX6kZL9TcKCwtRXl6OsrIylJeXw+12o6+vD0eOHMGRI0fQ2dmp9Cq6Lidf+HhIUSbSnq7ByXxOQHHj0zAMRf7oOtXIyIiKcKKGGmTYGoaR4TTknY+JjCZnHq3xpaWlKC0tRVVVlRo/yQClNlBaIY+OJRkg5yK1fqemE+T0ozGRI4+ej91uh9frRUNDA9auXYva2lqlI3Z0dODs2bNKt+KpSGb1SOk6ZvPC6m+zYanKhhkpot+n1RprZqSbkU+0LqbT03XBdu/ejbvuugtutxsvvvgi9u/fj1gshkQioboSkm1CadyGMV0Ym5zmdB0qqk06j1k0AndOADOJDj3FyCzFTidVrHQ0iqii5gORSERFX/Bnpj9ffh2zd0URgy6XC36/X0WIUwRgNBpV9dlIjr1eL5YvX46ysjL09vbitddew8jIiJLXlStX4rbbbkN/fz+efPJJnDlzJiNl1UwH4uObzebgsCKjdJ14McDvx2wu68cAMxudANZR9Rw6UcLJlIqKCtxyyy245ZZbkEgk8Lvf/Q7PPvusqmHn8/lQUlKCYDAIj8cDu326i+S5c+cwNDSkSKaCggK131AB7GzkJ49+tdlspnObr5O68447MQBkBJCYPQv9OVmtN1bf13kR+i4fH5UsIFuE9kkqh0Np2/F4HJOTkwgEAgiFQqirq8PatWtRXFyMV199FU8++aSqA2hGwlqti9nmgpmMzyY32fC6iCe+sOmT3Ozv2VKQZhMKWpxCoRACgYDySIdCIdWhqKysDHl5eejs7MRrr72G48ePo6enR3X9onvQJ46e3kbtb8lTR8o0KRnAzJofpChRWCG9dBJUOi+l+NDPnAnmEVbpdFpFSHEvoN1uV3UUyHtHRdPJSKDIDSrKTvUcUqkURkdH1SZF9RnIA2m2oJJxvWrVKmzYsAFlZWVIJBJob29HW1tbRk0uCic3mxf0LMwMbyvixUpgdOFebOPajHjiv1spO3M1Fsw2UTL6iIC9+eabsXPnTpw7dw5PP/20KjhOyk9hYSECgQDy8vIwPDyM7u5uVUCWUsW8Xq/ySukGMBE9tCHM1YtiBp2oojlL9XZGR0dViCkVsuXPieRAj2Di4+Gypb8XUqqowxClh5KBEQgEUFRUpGqBkLFDKQ6Tk5PKi75u3Tp85CMfwYULF/Dwww/j8OHDKvJQD/vO9l5ne1783vT5ZKY403GLLRvAwhNP/Bo6OUuROAUFBdi2bRuuueYa5Ofn4/nnn8eBAwfQ19enDES3242SkhIV0TYyMgJgutMdRfJQXUD92nwumqUWmK1ZfIw6+WKm2Orrp5XCz9eJsbExOJ1OrFu3DuvWrYNhGDh16hReeuklRKNReDwe1RWMlDC73a4KWJJs8rFTKhEAZRA4HA6UlpYCACKRCLq7u5FMJhVx63Q6UV5eDqfTiY6ODrS2ts6JcLLaC/TneqlYqsb1GwXSJ3hEEDVvKS0tRXV1NSoqKgAAHR0dOH78OI4dO4aenh5V2Bowlz8ikuhn0qWoriYZ4DabDRUVFRlrOukipFORcQlcXP+5XsQjusmo11PMKZLJZrNl6GC5ublwu93YtGmTcsJQlBOl19lsNqVXkR7F9wSK8Cadi5wf3CHJ37XD4UBZWRnWr1+PDRs2IBAIYHBwEC0tLcjNzUV/f78inaLRKOLxeAaBNpuRQJ+/nvm9VGVD152sjPD5XIe+x20Uboh6PB6sXLkS1113HdavX4/h4WF0dnaipaUFZ8+eRW9vr9IhAKgCy4lEQqWfUldV6rRNZBQ5n4FMUkN3UJMOTePk0PUpHpHLHXK6HgVMZz9QqQC73a66mHEbha5B6T5WRBQ582jsbrcbOTk5iEQiaGtrU5kUJJcej0dF/C1fvlyl14XDYezduxdjY2Mq86Oqqgrbtm3D0NAQ9u3bh+7u7oyaTvo7pfGZkQGzzRUzHYt/vtiR5HPZN7KtCzpRwo/nf7MiGGkNBqadF9deey3uuusuuFwufPOb38TZs2fVu6YO7eXl5Uqfp0wbKntA+1BhYaHqmqc76swcezQWYGa9JJIDIm5yc3NVQ6CysjK4XC709PSohgA80GQ2Z5/+92xrMumCVnUOaQ0Ih8PK4Un2vdvtxuTkJHJzczExMYFoNKrsorKyMmzbtg3r169HLBbD8ePH8dJLL6lz6Paifh9mc1u/l2wE1BtGPM3187kybGYKpBkRQZ+TwUutfElZopz9iooK1NTUoKSkBADQ2dmJU6dO4cSJE+jt7VWROFa3zD1u9DP9o3FRWJ6uQNEYadGliCmKNqLvUn0eCqkDoDx/nBQiZYueAQkenzicgeafU1qDWZogMcHkRTTL/SbFrLCwEA0NDVi3bh3q6upgs9nQ0dGB5uZm9PX1YWRkRHkwKHLKDLOxpXNZRK2ERP95McAXbH1+W819YGYUkBmBwJUN+p0TuaQ4h0Ih3HjjjbjxxhvR3d2N3/3udxneIIqMq6qqQn5+vlr4Y7GYIh65d8rv9yuyid8LV3BsNut8f/qeWUiwfgx5L5qamtDY2IhwOIzjx48jHA7D7XarDYTX6uCGvtV6wcFlhOR5YGBAdYvMyZlut11SUoJQKASn0wm73a42BKqvQfWDioqKsHXrVuzevRsnT57Eww8/jPb29ozUOiuilM8Hq83fbJ5YzXkhnjKvZUY+UXvy3bt3Y/v27cjPz8err76K48ePo7e3F7FYLCPcmd5/PB5HPB5HOp1We47D4VDyAVz0rvF7Jdk0q1egG+c87cIs0kl/h2bv3uwaJNd1dXWqO9bIyAiOHj2KJ598EtFoFHl5eapeidU8pD2R72vkiCEDipQ6SgWy2+0qRZzCw8PhMCKRCJLJZMY9Z3uHZuO5nOv9Utk7Fhuk+BcUFMDv9ysSqqioCLW1taomIHVmO336tHLsUV1I7mHmaxeP3tB1KjqGSCTuYCP5Jc8vN8J5vSWn06m6XpHO5HA4VJQRAFUngxdLJ7mlvZfmMkVf8OMoWoMiyIkU0ztoEdHEdTWu/JOjaM2aNdi0aROqq6sxMjKC1tZWtLa2YmBgAIZxsbsXRTkRzPSKhcJSlQ2uZ+nHznXMVnaIDtJh6JiSkhJcf/31uOOOO1BUVIRwOIyDBw/i5ZdfRktLCwYGBtQ+QiSMntZGRig5jblBTPOO1lsqg8BrrPF9g5+Tzkvj5k5DTupyfQ+YlpXGxkasXr0aNpsNp06dwqlTpzAyMpKhb/Fr872PrpGbm4uioiIAUOmzVNKDDHyuq3i9XpSVlamGBhUVFRgdHcXZs2fR1tamDG5ynFx99dXo7+/Hf/zHf6hgAr73zmcezFWGrPT4xSaesgVxzPcZ6DrTXIg6mgc0J4LBIK699lrs3r0bJ06cwMsvv4zBwUGVEu12u9HQ0ICysjIUFhZidHQU/f39aG1tRX9/v1rTc3NzEQwGlQ7OnXw0p3UnHx+nTszS+sxJVurEXlxcjLNnz+K1115TZA7dG0/15k52XQ7oc7omvRdyNPCoQb4PkEOP6vCGw2EMDw+rCMuKigoUFBTAZrMhkUhgeHhYrS0UKHD11VfjyiuvRHt7O15++WWcOHEC4XBYOSj4WDmy8TNmx83G8cznb4R5d7XLdhErw0r/2QxzIbbohRKTSkY1FcOmgtjDw8MoKipCSUkJCgsLsWLFCpw+fRqnTp3CwMCACpcmRYnGRROIGxFmufy08ExOTirPL4EWZdp4iGml89Gk8vv9Kq0tJydHsZlUD2pqakq1KebRTzQ+fs+0CNKz4qQSTXLa/LhHkStG9H0yqqqrq7F27Vo0NjbC7/djZGQEHR0daGlpQTgcVql1pBhZGbjc+LZ6x3MhDvTzLXVYKUb8Z77oc/JKP15/dvz7tDhS/ZpUKoWbbroJt956K5xOJ06ePKlkhQzMqqoqhEIhANNKB3lvyZMbi8WUF9zlcmUU4+eeYPJamZFPVouVnqpDXoyKigpUVVWhuLgYgUAAExMTOHr0KFKpVIYM0fF6TRg99U4vjM43EGpNSrWwyDNXW1uLZcuWIS8vT9VHGxkZQVdXF2KxmEp3raiowJVXXomrrroKPT09+PGPf4yhoSEAF1OG9XnPCQIrb4kZcUk/68+Rf0//WT/urQq+rtP6unfvXjQ3N2P9+vVYv349GhsbceTIERw+fBiJREKlH5OnjsjYZDKpUnyoVlogEEA6nc6IOKX5yQ1P/h51MlFXpDiyrancyCA5onNzoignJwexWAwtLS2YnJzEsWPHcO7cOVUDRw9p1/c6wzBUehRFfdF6QIoV7bsUnQEAgUAAPp9P1RscHh5W9U8IcyFdFopwEmQinU6rIvGpVErpFWNjY4jH42hvb0dBQQGKiopQXl6uDMXTp0+js7NTtc7Wm5HwNZnmKd/jeCQ4OcsoMoq+bxiGMsppXvOIDiqQ7nQ6VSoa1WyiKGwqxOr1elXzFU4apdNpJfs0NlqrSe/kHehobGaOPDPSNC8vD8FgECtXrsS6devQ1NQEp9OJ/v5+nD17Vj1DImWj0ahKRdLxVpcDKyeLGcz20Gy2BjcQCeRsttmmnVW/+c1vMDIygsbGRlRXV2Pjxo0q6pNIQ/rncDhUByqal1RTMh6PIxaLqeiO3NxctWbSXOdj5+s03zNIxwfMdTHeGZXuhXedpDRzn8+HRCKhor5tNhv8fn9G2RGKViouLlbXpWun02mViks1yXjZDiKcSZZ9Ph/KyspUh7Pe3l50dHSgs7MTY2Nj8Pv98Pl8aGxsxJo1axCNRrF//34l42aOtbnYmFYOD7N5ZaWPLzZmG0M2eeC6qX6slf2lywU9e1rDI5EIHn/8cVy4cAEf+9jHUFFRgb1796KlpUV1F+3u7kY6nUZxcTFWr16NqqoqlaZM2RnpdBrDw8OIx+Mq64ATXEBmHVia72bvjohL+tlms6Gurg7r1q1DaWmpsjsoA4TXT9MbSXBCSyejzZ4xJye548Uwpjs4UioiZVSQHkapiYWFhcjNzVUBHtFoFHb7xZIQ1157LbZv347m5mb86le/Qnt7u8peyja/5/KZfi9zOW6+uKTi4tmMndnYNavP6PO5fJ//np+fr9LvyFtFoawFBQWoqKhAcXExEokEOjs70dvbi76+PvT29mJgYCAjysjqnulnrpATeJQUP5bSC3TWljaXgoICldpEhgqRA5QWR5tEOp1WJBv3WvAaCJxMIiVJJ5bMDGL6OScnB6FQCPX19airq0NNTQ38fr9iY/v6+lTtgpGREdWNIlsXQLNFzMyDwJ+vldBYEZd8010smM0TwlxJtbkQbVayQfMyJ2e6hfnmzZtx++23w+Px4Le//S2OHj2qPLWpVCoj7YVInMHBQQwMDGRsADabTXmT6R+lnZKSNTY2pgrn86Kx+r1zcEOdlPVgMIja2lpUVlYCAI4fP47nn38eiURCdb/gRV2pXoZhGKqWCJCZ+82VMDIMSMZIIaKiyw0NDdi9ezfKysrQ2dmJEydOoKWlBf39/SpdKRQKobGxEbt27UIgEFD51M3NzQAyO4np70zf3LORj3NZU62+o8vJYssG8MZHdWRbKyhNLBAI4MYbb8TGjRvh9/vx6quvqs53vA07kSu0DpNTgOad3W5HcXGxIuwDgYBS0HkRYbNIJq44maUh0zE0doIe9cr/xmuSlZSUIBKJoKOjA/F4HA6HA319fUpGeLdGOi8Z/EQ0EfFExgoZRSRDAJSxzL30DQ0NyM3NxcDAAA4fPqzkda4G4xuFxb7+Gy0bc4HNZlPRTz6fT71TimALBoPKKHS5XJicnER3dzfOnj2L9vZ2FdVmVjBeXxs5+UTQI6IAKKWbdCr+OemABQUFqiU3cDHKiYoZU/QTGQU0J3lqEjlUdLKMdzwGLhZn5o4GM92GxrZs2TJlQPv9fqRSKXR2diqPPxkXVF9HJ/AWA0tZNnTnTbbv6+9lNn0sm55G16W5uGzZMtxyyy3YsWMH+vr68MQTT+D8+fOqhlEymVQR6VTjjHf5Iv2JCEzabzweD4qLi5Xzg4xKPgad4DVzapCMEcnEz5FIJFTDgMrKStTV1cHtdiMWi6mSAl6vVzkDHQ6Hiv6jOoGcdEomk+pzXTelruTUoIVqX9lsNkVaE0lM0bLkCHQ6nWhra1MdNnmmRrY5akUk6TZQNlvE7JzA4hcX122ObDb16z0/P5eVTHK7+KabbsJNN92E/Px8HDt2DEePHsXg4KCKjK2oqMDtt9+O6upqnD59GgcPHlQlccjOJf1L3wtoDCQn5DTmc47WdE7E0HdWr16NXbt2IRQKYXBwEK2trejp6VG2CNkFeuQUrfP6/XNSjJqWUfMvuo9EIqGcH2Tb8+70tJZQ+Y7CwkLY7XZ0d3ersVG0eVVVFa677jqsXbsWR48exa9+9Sv09PRk2F58rDrZamWL033wTA2reZHNVrH6bMZ55ks8mX32ejcoK8GxMsD0B0gLNRUwoxfp9XqVkRwMBlFeXg6v15tRo6irq0t56oisMWOACTyCgsakL1RcodJr5hBBQJ0eaEJRO2IijXhNAzJQuJLDPWy68qN7Q/h9cEOIDDG3242qqiqsWrUKK1euhM/nQyqVQl9fH/r6+hCLxTA6OopEIoHBwUFEo9EMA8yMlLR6f7MRMVZziX9XP2YpKUhmcwGYea9m853Y9LnOe7NxUIRGY2Mj3v72t6OgoACHDx/G0aNHVXH50dFRpRAXFRWhuLgYU1NTaG9vR2dnp1oweeE9WhTJi1BYWIhQKJThnebeX/KYc8+A3W5X6X4OhwPxeBz9/f3o6+tDMplU8hqNRlUKB38uZGRQehD3uJCBoDP+XPa4YkabFhXqr6urw6pVqwAAJ06cwJEjRzA8PIz8/Hx4PB4UFhZi06ZN2LhxI6LRKJ5++mkcOHAAsVhsxqY01/moj1GfN1Zk0lzWR8JiGy/A0jGu+VyhtICysjKsXr0aW7duhWEYOHPmDJqbm3H27FlVfJzmMYVik1LB0+hobpeUlCAej6vmD2bh2DQWHp1Hcxe4WOhSV+CBmRGkNptNEQN5eXmorq5GIBBAMpnEK6+8oopVUhFXShEnJYO+T2P0er0Z8kqeeJI9u92uvPXksSP5LyoqQkNDA9xuNwYGBpRRPTAwkDH2y6EYXy4s9vWXimyYIS8vT6WXkj5FpE9OznRX1crKSpXmNjU1pd57V1cXwuGw0hV4aoqVoWf1O/+MzzduWNN6zhu4kLySQcGLe/M0O9KZyLnBuwWT7kX/sinaui7k9/uxYsUKNDY2qgY4Y2NjGBwcxODgICKRiOqOSo1ZqN7aUsBijyObbPD6S7N9f7Z91gyzGdl0jtzcXJSWluKmm27Cddddh7GxMbzwwgsYGhpS5QKSyaRK5bfb7SrqjqKOSM9JJpNK1zaM6a7E5Eyk7mB8H+F7CNf9CXqUXiKRUISXPpc5oUaGMznl6TOqi2YYBgYHB2fYGPx3my2zuQB1OvV4PKp509TUFNra2lSHQC7DhYWFqK6uRldXl6olS/qomb41l/ep/12XV36c/h19ri0l4ulSvz+bLWaG2UhZ0ifq6+txyy23YPXq1ejr68Phw4dx6tQpRKNRTExMoL6+HlVVVZiamkI8HleEDNXKo8hbqsnHnXW6LkzrPM1/PZKV9g0AqttkcXGxigZPp9OqADrdFznpad/ixA0np7gdT2mxVNJnYmJClR6gfZDGQPfk8XhQUlKiOqva7XbVqIJkwm6f7kC+fft2bNy4EYODg9i7dy9Onz6t5JBnN1m969neJbeVrKC/9zeEeLJasPWJYEUQ6MfMdj2zxT/bxKeuCLS4kffXZrOpCCiPx6OqwdvtdgwODqKrq0tFQA0ODiKRSGRMOP26/FlwA8DsdzOG1GwD4d/RU+HMFLHZmMlsBBAwPfkLCgpQW1uL5cuXq1aMNtt0OPGFCxdUgdiJiQnVDW0+rXytDGP972bzIZvSQJ/PRVDeCHDBncvGZkUkZCMuzO7dSo6oTk15eTluvfVWrF+/Hm1tbRgcHMRLL72EwcFB5QUOBAKqo87k5CQikQj6+voyuhcRycjrB5AngkKmSTniNTJ4cUpaVJ1OJy5cuICuri4Vjk0GASmTRDIRwWrmNedj4c+Ovwf+PvhGQdGIPp8PhYWFKpVvYmJCzfGJiQlV52zt2rW44oor4PV6cfDgQTzxxBPKE2GVJjUbss19HdmIzNnO8ftMPM3l2Vl9j6dNe71ebN68GQ0NDdi2bRtGRkawb98+nDhxAi6XS3VIJaOX5jMp9ZS2ZhiGioogZwcZ7mb7BAe9J1K+Kf+f1+Og1G6qHUiFWPPy8pRnvKOjQ9Vu6+rqyiC3SP7IIHC73WqsANQ1CfR8yHPIQ9xp/Hl5edi5c6dKrQuHwzh37hyOHDmCaDQ6r3m+GFjsMS1l4olAUa68mQlFlvPaLlVVVQgGg7DbpzsXhcNhtLe3o729XTmwuMMKyNzL6HdgZgS0vr7zn/UID12n4l5g/fwE2lPoGP6P/m5m7OrjJCO7srISTU1NWLNmDQoKCpBMJtHT04O2tjYMDw+riMGhoSHVUn4prNUcS1k2+Puz2hN1mN2PmR1jpbubXZ+Odbvd2Lp1K/7oj/4IRUVFSKVSeO655/Diiy9mRHtQ9A/VsSFyyTAMldY6MDCg9GwilyjimrIkpqamOyzqz4B0dV5wmfSUkZGRGVGnZJTTvkaGu54qTjLG697w8/C9lM5Jzkrabyj7g2oBDg8PY3R0VB1L+6XP54NhGHj55ZcRi8UyZHA2GbEiVKzeudkxZrbIUiOeSN+YC8xscp1suFSYfZ/ISb/fj3Xr1mH37t0oLS1FS0sLjh49ira2NkSjUaWDANPPnHQTXj6EUp+Bi3OP1nT6mWfd6DYSJ2hJb+O2N+0NDocDK1euRGNjoyJ5KUuEOyGIzOX2B5UqoXIMQ0NDyM3NVTJKkeE2m011pyMbKRQKobi4GBMTExgZGVEOCWA6ep3SDbdt24ZVq1bh+PHjeOKJJ9DV1ZVRWF/fj/ielM0OpZ+tuBazfZn/bobLTjzN9cJ0XDahn+9ktzLWCfyhU4QGKUqUZ025ymRwFhYWqvDP8fFxDA4OorOzEz09Pejt7VU1l/jiza/DF3EzRtZMEHgL3tkWSPqcR43wRdjsufIx6NenBb60tBQrVqxATU0NKioqVNHQSCSC/v5+5aWOx+Oqzg2PctLHZ/V+si3gsy3+s32ff7bYChuXjbluCNmUJTMht1KGrGSCQjgLCgpw5ZVXYtu2bSp888CBA+jo6MDIyIiKfiorK8Py5ctRW1uLZDKJs2fPqkJ10WhUFV/mLbB15YSMECoESxuQPtZYLJZRH4oTWWRYkxFP9wIgI8KERxLS9TmhQLJK5BeNj8JhaXwUDUJFNIlg83g8qK+vx6ZNm7Bs2TJ0dXVhz549OHnypPJQmi3s813XrBRcXVHQ36/ZhqIbc8DvN/F0qdD3MloXCwoKcNNNN8Hj8aCsrAw2mw09PT04ePAg2tvbkUqllCJEewulQRDIg0ZpPdSmmsgpp9OJiYkJlWZAc9Tlcqm9imSMCCjqojg1dbHFNc3VyclJxONx1SWODBa+H1E7e5vNpkgDkh+6fzoXJ7uAiwouyTqRt9XV1bjiiitQWFiIpqYmnD9/Hs899xyeeeaZDHJhsY3X2bDY41tqspENRHDSHKK0GY/HozrBkYOvtLQUXq9XeX0HBwdVDReqs0nODzOvshVJyz8HZnbtomOy6VP0PX3N1GG23prBZrOpKI3a2lo0NTWhrq4OoVAINptN1Vhra2tTe+ro6Cii0agyvhd7HpphsceUTTbmmmp3KfqmGRmVbVxk0Obk5KC8vBybNm1CKBTCtm3bkJubi/379+PAgQMqOoFqFBUWFqKiogKhUAgOh0NFFA4MDOD06dPo7e3NSOkk/YaXGzDTGc10Lk4eAZmdgQGojAsinng0Ie07tE9QXSi6Z5JBu92OwsJCFUFL64XNNt1YghyZFFFPhviWLVtU05uenh6cO3cO7e3tMyJls70T/l7mYoeYrS38+NnOsdjE0+XaN2Y7j9lzsLJF+HE01yjSb/ny5diwYQOCwSC6urrw0ksvIRKJqPIFk5OT8Hg8CIVCKnNpcnJSRQBShg/Z0ABUTUAi7c3sbTqe5hw5mdPptPo+6SqUKUU2CJBp19N9l5WVAYDq5s6bTujPgewJr9eL/Px8uFwu1NfXK0d/fn4+0uk0Tpw4gebmZkxMTKi9taKiAldddRVKS0sRCASwd+9e7NmzB+FwWEVdZXsPum2kz2ueYZNtrdfXw9nIystKPPEXYDW42Vix2RZ0/TzZYLWg8J/pRRPDSIoSGQ3EPoZCIZSXl8Pv9yujgdqst7e3q6KPFBZNXeroOtkWe/433iGCJnu2DVTfNGgimxmYVmQFGVVlZWWoq6tT5EJBQYFKpxseHlb3G4lElLFDn1PIrdm49M9me0dm78rqnFbn1c+x2Ma1Pu/MBFX/mcPq3q0+Mzs3/50r12R01tbWwuv14tprr1X1iSgUnOqFuVwuVFdXq7an5D0j4mlkZEQtlGQ4mHXx4c+Bz1X6mVKQeMcJkg3+M18USWYIpCiRDPEUVl5onH6n2iB5eXnKu0AFj+kZETFAaXcVFRWIRCJ49dVX8dprr6li5CTD+iask0HzgRmxrG/wVuudmYzwcS423gjjej77BjBT5mgO5eXloaamRkU/JZNJnDt3DufOnVOGIq3/Ho8HLpdLGQx+v18V56dwaZq7PBya5jlFHFF3Vmq7PTo6CrfbDZfLhaGhIbhcLpUq5PV60dvbq4yArq4uGMbFWmk2m03NZU4UhUIhRbY6nU5V84OO4XWfUqmUkiVget/yer0AgA0bNmDDhg1wu91YvXo1YrEYnnrqKTzwwAMqTH4pzLm5Yikb10sVNIdo3lNXYZ/Pp+TI6/WioqJCpX5SoftEIoFIJKKiy3t6etDR0YHTp0/PSQfQ91recYjLlxXMDPHZdBsOvn5QdFN5eTlWrVqFFStWKBLBMAwV8cVrY1IhXYr+WsqyspRlYy7EEz+PbniZOXX0vdtsT7Ha3zkBSo6tTZs24X3vex/Kyspw6NAh7N+/H8lkUnVRTaVSCIVCqK2tVQbpqlWrkJOTg8OHD+PFF19EJBJBfn6+qgvF67xy5wHPgOBj4ePjehXpS2QneTyeGXWgyGlH+wRvCEN7DD1bIqY8Hk9Gt0ebbToihaKt6DtOpxPFxcWoq6vD1Vdfjfb2drzwwgs4c+aMqnOm65P0/K3ejZnOmc3OmE1vy0ZeL7bczrZvzFUfmu182Qi4uYyBjrHZpp1eVVVVqKiowOTkJDo6OpBMJpXTi0ggKp1TVlamdBXeuMFmu1ijj9c+5tfkY83Ly1M2Cs+k4KnUemaFXhuK3y/X//kxpD9S1BZFqnu9XhWt6HK5UFVVBY/Hg9HRUYTDYTQ3N6vi5sRNrFy5Ejt37oTP50M8Hse+fftw+PBh1QCE7o2P2az2m9U7pjHrdeL0d29ly5odP9vnGWOZK/GUzSie7waVzVieL7tmNT6d8STPHHnnfD6fMl6phWNZWRnKyspU0Uzy/sZiMVX8rr+/H93d3arTFQ/HM5sM2e5N/4zX3tAJJvIuAMj4G78ON558Ph+qqqpQWVmputAUFxcjNzdXkWi9vb3o7u5W3VPoHycbKJ3E7NnO9lm2e50Pw2r2d37OpbQJ6J5UwmwKLf1N3wStNkOd3KTP9J9pTpDSUVpaiq1bt6KpqQnRaBRHjhxBV1eXIpIMw1BeayoASfn4lDpDBfNo3hPzTwsiJ4t4TQ0Aiuylv/PoI5JVPZrJMIwMI9mKzKNzUVFkOh9fkCkclmrU+P1+AFBeiZKSEpSWliKdTuP8+fNoa2tTShNXXPk70N+fPi6z3/U5rCvFZuefC/TvLrZsAAtrXM9nf5htzeFKtMfjwYYNG7Bx40bV5jmZTGLfvn1oaWlRnYmoBkZJSYnqBDk1NYVEIoG+vj6luJO8UBQfvW/uLQegiFFKY43H44oAopx/vbU2nYc+CwQC6ncK6SYZ4x29eHFlLi9kiNNeGAwGcf311ysvXH5+PoaGhvCtb30LnZ2d6OvrU10d32xYysb1UgfVPSPSiYgoPueojqDf74fT6URBQQGCwSAMw1CRPpFIBP/1X/+Fnp4exOPxDEcG30/MwNc7M0OBr/26sUCyR8bHbHoO6ZHUeaixsRENDQ2orKyE3+9XRdbJWUkNWEj2KZViKabVmWGpywZf82Ybq9meOlfZy6bP8WNoTtF5c3JyUFNTgxtuuAGbN29W+vW+fftw6tQp5cQmkr+mpgbr169HWVkZent7ce7cOQwNDcFmsynSksgnwzAyjHL+PCjiSI9Ip9RYbpDT3kJ2A90rj3DlhrpZKjaXM9KvSNZ4h1WysZYtW4b6+noUFRVhbGwM/+///T9cuHBBtYvnz9dK/7fSmaze3VxsSX6+2ebTUpeN+XxvNn1zLrbLbOB6e25uLpYvXw6fz6ci4Oi9k55FUXUej0c5LegYPfqO7BZu79NYae7xKD7gYrMhAKqxVyqVUsQx6WqcLOWywUleqkvGSxiQ3FHDGbfbreQymUyiq6sL8XhcdRKn75aWlmLjxo1obGzE4OAgnnvuOVX+hHMNZvbDXGxyfZ+czb7OBivbe1GIp0tlWmfbEPSHnO1YOl7/G6UfkaLEo6BIiQqFQioayufzobKyEj6fD8DFTj+jo6MYGBhAOBzG8PAwYrGY8uRFIhFEo9EMw4QrT7MZPySgnMjSFSnaMChFg/LFCwsLVb2dYDCIiooKeDweVUuA2gv39fWpjn4kYFRxf2RkBKlUKiOqy+o9ZMNcjjN7j3NRIPTvLbYSZ8Ykz1cO5nJuYPYwY/04XTGghbK6uhqrV69GKBRCJBJBa2uriuYgjxXJCnUxcrvdGeGptCBTuCkpQTzslOYy/c470NEc5uQYfYcUHZ46x70SfHPh3bkojJbGQM9B7wJJoe3ULtjhcMwgmXnuuBXhlG3ezlU54uedTQ7mM69mW2/eKCx14snMOUAEqNfrRUNDA9797nejoqICPT09eOaZZ9Db24v29vYMxSknJwdVVVUqOojmGRVqnZycRFdXl7pOMplEfn6+KuSvk81mCgZ5ummM1GnI4XAoOff7/Wo81MqbFCaq2UbnJMKXxuvz+VBaWgqn04nbbrsNlZWVSllMp9PYs2cPnn32WQwNDaG5uXlGePmbDYstH29m4olAkaKUbkcpo/Q51XbJy8tDYWEhysrK4Pf7kZubq5wbqVQK/f39qiA5kTaRSESl6eidfc0MRd0hwfdiswgKMlTy8/NVtB7/jArHUpethoYG1NTUqHulYrB9fX2qRAF156I9J5FIKEfeXOtjLgUsddngJA9HNpKBE/XZdEezPV4nMfTr8XHR/4YxXf9p48aNuPXWW1FWVobx8XGcOXMGhw8fVmQrraNutxuFhYXweDzK4RaLxTIKKNO8orRt3iGL5EJPdSb9ikfC8k7A/Bha6zlBy/UvmtM66au/E5KjnJwcbNiwAdu2bVNFncPhMM6cOYNTp07hxRdfzEiT1Z/pbGSR/j2zY6x0tkud40tdNvhx+jzXvzubjcHfrRnhavU9M3DZcLlcKCoqQklJidJfSHcnopXS6/icJruXd4vn9gMvE0D/gEw7gWdw0Z5CBc6JLKX5zh33JHtkf1B0LwWy2Gw29T9xCHb7dAdJivKNxWIzutpRaY8tW7bA6/XipZdewqFDhzA8PJyRFsiJZKs9z2p9ykYszoVzmes5F5x4muv3LoVMsILVQ5rPeIhkonQG8tDx7nI0aUKhkPIUUHcrqkBPyhYP96biYtRKlUJkqZgkGdRkaPB8U7ouFY81DEPVpiKD2efzqTar3ANH3yMDmroZJZNJpbzR9YlcIoOIWr+adfW71OdvZmzPlzSZK5bSJqAvzvqGOBspNdvfOOZ63zoxRuN0OBwoLS1FdXU1gsGgavlJHQwTiYSaEzabLWPBpoWVcpf11FGav/qc4h4J8lzoRgF5I/hc0z3XlBoEQClfXEmihZqULX7/NptNNR+gUNZ4PI7BwUFVh4C/C7PN1opMynbspXyfPtO/M9scmQvR/UZhqRrXXBZ1meVKc15eHlauXIna2lrs2LFDdV48fPiw6pBKdTvIS+ZyuVSEaXl5OYLBIHJzc9HV1YWcnBxEo1F0dXXB6/UilUphZGREdWt0uVxIp6fbAdN6DlyM/AsGg2qOEvHEO6Vw5Y7uhROvJH9U+zA3NxcrVqxQys/OnTvhcDhU2mBHRwd++tOfIhaLobu7W6Wc/j5gse9jqcrGpYDWdCpxoNctI1KK5IrSEAoKCrBu3Trk5uaqdZmv7ZTyPzw8rPaniYkJpVuR3FGNMjIa6HeSDdojqDYb1WErKChAUVERnn32WYyNjaGgoADFxcUoKipSkb9UfJmKxg4MDGBgYEA58/r7+xVxRWQBdWvSnSBvFiz2eGeTDV7gdy4OG/53s7Xf7BzZHHr8M13H4sY6/SstLUVZWRkaGxuxY8cOTExM4NixYzhy5Igytnn0Bjm+0uk0gsFgRko27+DLIzBoX9B1KO7A4+OiY+laPEKcni8RWnROkit+bgBqnA0NDSgpKVFO/NzcXMRiMbS2tqpsEaohS/ZQtmetv8dsOtkb5YRe6rKhHzebfa3bJVYkg9U7MbuGTtKakYqkh/h8PpSVlaG2tlbVULpw4QI6OztnzHPSzYCLUX18nSfdn6ec8tpOnGAl0J5BUeCcxKJnwwlYimCic3s8HgBQZWk8Hg/sdjui0SgikQhGR0fVuSkamK5bWFiI+vp6FBcXo6+vD0ePHkV3d7fSJWkcZnLCn7nZuzM79lJseLPvZCOyZsNlJZ7malCbbQJzhdkm83pIMTIsiHWkTnhUv4MUGSpMzIuPUYtQSu8pLi5WtTT0BZ+DDAISCvJEc4aVJjt5tym9glItSPkiJYfIJaohQBMdgCpmSYJLhS0pwokKlc31+dOzs2K/52NUz3bcbMSVzuYvBqyIp9meUTYCgh9vxmTPRWzpeLPv6N5Ct9uN0tJSLFu2DJWVlfB6vRgeHkZHRwf6+vqQSqVmdHPgoAWaFnSuwHCliNeTIbkBoOYygSvqRGhxxYkTSlyOdAWMxkOFb6mrpdPpRDQaxcGDB00LvJox/Px5ZiMX+ef6Yj8bqW72M33vUub5YssGsPSN62zvj9ZpmveFhYXYvn076uvrsXHjRiQSCRw6dAgHDx5UZC0vNg4A9fX1KCsrQyqVQk1NDZxOJwYHBzE8PAyv16vWcofDgXA4rIphJpNJVXeQlClyRvC6GzyiyjAMJJNJtV+R942Opw5kOTk5qK+vV8X23/e+98Hr9WJkZAT9/f0YGxvDD3/4Q7S1tSGZTKK1tfUNeRdvNN4sBsSbETxqiJq9kMJOnxMJRV5vKi5Ljj5qc81TNWhv4XunWToEN76JbKU9CoBy9pF8UCMZ2lso+jedTiMWi6Gnp0elzlGkO62vXOeKxWIZteDerFjssc8mG7pePZuuyI+ZzY7Idu9m+mq2seq6ltPpRENDA66++mrU19crAjMej+PChQsqvZ/mMOlIZOQ6nU44HA6kUqkZjgaKsOURSrz8ABG0NCaKjCUHhq4/8agSTqYtX74cXq8XRUVFCIVCKpK2qqoKq1evRiKRQG9vr4oe379/P06ePJmRVmUG/b1YOeIWG4s9hsu9b+iywGUr2/zW7Rizc1mNVyegqEN2KBRCKBTC1q1bUVFRgVQqpYj8SCSiUk6npqZUtgVwsXM1T/OkOc7tCU5c0X5AehBw0RYhJzeXMXKqANM2Ctf1xsfHVd0+ch7S73QdcrR4vV4YxnQ0pN/vx+DgoKr1RHY7J1Ivdb5l42TMMBfbVT/W6hxZx3U5iads35sLITXfMcw2sXXoi5r+HSKYyDtH/6gVKDd2udFst9tVkXKKCqENgn+Pt6AncoobKjTxuWeaijmTR2JqagrxeDyjZgiFCBI5BVxkSCl/lXJn6Z+VF24uZF421tvq2Vqd38zAN0O2ebKUNgGd3eeYK9Nsdv45CbPFc5wLUUtKucPhQFlZGdatW6dCo4mAam5uRlFREaamptDT06O8vDSPdA8HcJH44KQLpcSR8sPJV+CiHJIsUYoF9ziUl5ejoKBAedNJeSJPO5HCPGQ9EomgpaUFXV1d6O3tVf/0ZzbbAmu10c71/cxFmcr2ruYjB4stG8DSMK5nk6Fs5BNwURGjKL9gMIiNGzdiy5YtcLlcqhtPLBZDV1eXKnw5MjKS4UEOBoNYtmwZ0uk0AoEAcnJyMD4+DrfbrdL2yGCm7nQkJxR2DUCRS7w2GzfMiXAio9ztdmPnzp0wDANr1qzBypUrFSk7MTGBSCSCF154AePj4/jtb3+r6r4tBeJyIbHY8rEUZOONAFfwaY2mehj5+fnwer1qLSejgdLwKM2BSiMQYUU6FRU7540jSH+i6BBqPc0jyimSkMiiuro65OXlZRRAj0ajymnH05coin1iYgJjY2OIx+OqYDQv/vpmxmLfw1yIJ75PztUpN19jbC5jmovezMdIulYgEEBtbS0AIBAIwOVyYXh4WEUEURQRpQIlk0lFHJGDD0BGYWZKywMySxIAFx16nMyiBky8KLhhTKc0bdiwQdW8AaCyPG655RblAKH9Z2pqCkeOHMHvfvc7hMNh1ZSJDHmrtOw34x6z1GXjjbiulZ48my5ldjwnvEhOGhsbsXXrVqxcuRLLly9HSUmJSi+lKNcjR47g1VdfVb8nk0llkxDhBFwkULkzgcDlaHJyMiN9Vbdr9FI49I93eKTIKiqBEAwGUVJSgoqKCpVW3tPTo7KQOjo6EA6Hlf3Oz68/TzMbUv9srgR6tndn9tl8z5UNr7vGk5WBO1d2zOw88xnDfIiS2Y7RSQNOElFqHqXl0f/AxRoHRCZxhpOMZy5YZECTt1r3LvCJT4aEYRgqXc9mm46EotBAOo6McopwIoKJ/nGv+WzPYDbMlVyaj4E+G1liRXgt9salCz2972wkmtVn/DtmC8pspJ8Oq8XDyitB//Ly8lBSUoKGhgasXr0a9fX1KCgowNjYmJp74XAYkUgEiURCtZqPRCIYGhrC6OioMggAqIKBhmGoFCRe94k8bhRVRUY4GQ886tDlcqGpqQnbt2+HYRjKsHa5XMooSKVSGBoaQmdnJ86fP4+zZ8+io6MD/f39qv6G2eKeDZdCHM5GWvHjrDbq16PkLLaCBLw5jGuzvYs/O76Gk4JB9fV8Ph9uuOEGrFmzBhMTEzh69CgGBgbQ0tKiWkKTQkNpcfQ/1Rf0+Xyq0KzP50MsFoPdbld7AaX30b6hr4s2m00VbaZIkUQigR07diAYDMLr9eKqq66CzWbLaIrxL//yL0gkEujv78fp06ffyEe+JLDY8vFmkI2FAF/P3W43ysvLVVoOAFXHg+8T5NAjvYvmPU+ZIA83dbjjewnXs+x2u2rFTalDRP4SScXr3PA28OTII287kU2L3WL9cmOpy4YeUT1XG+VSneCXU1Y5CUV7C9Xk8/v9qqYmd1oDF4t3j46OqvoxVEKD5KS8vFyRsACU49rhcGDlypXK2U1kEHWgdLlcKC8vV8Z9Tk4ONm7cqIolc0fGkSNHEIlE0NPToxotJZNJtLS0oL29XT1Hq/30zY7Fvpc3875B84jLLZ9fwMUsB8o+KiwsRHFxcUazrJKSEjVfyUlHcz2VSqlSIV1dXXj55ZeRTCZVhhPfO4i0ikajGBkZAZDpaOT7EJWpofGRfObl5SEUCqGqqgorVqxQnYeXLVuGkpISGIaB1tZWHDp0CCdOnFARjXRtApcb/rzM5Gm2ZzyfOZqNeJrveReceJrt+MshnPN9ENkiTS6VpOIbBLVLJKWJfqeuebzFKf2NpwiR0sNT6nSFhQshZ1U5g2uz2TKinUgZos2EGzpmRu2lGNFmz0l/VrMRG3M5bj5YisRTtjk712eun2M+3oW5eBzmOi5KiQsEAqiurkY0GgUwrdxUVVWhqqoK5eXlql4Sec6SyaT6LtXpoC4Oa9asUXVqSOHitaOoJkBvby/S6TQqKipULTUigqempnDhwgUMDQ2ptIehoSFV9J+81VSU1qrGBu90MRthbvWMFnv+ZcNiK0jA4ipJ2daXbERuNs8Sd1CQERwIBNDY2IhgMIhVq1apVAiq/9TX16ciMYiUpTWa9gAilHh3U1L0yZtNvzudTkxOTqKiogKVlZXweDzYsWOHSs9rbGxUNaJyc3ORSCTwxBNPwDAM7N+/H6+++iqA6RShtzIWWz7ezAbE5YLdble6E0WIUzQUGd8AlBOCojVIh+I1NklGeFcuTiABMNWpbDYbXC6XKmNgGIZKpaCojlQqpXQt3jjm9xWLfW+zyYaua13qNWZzEM5FV75UPY8fy8dCpTz8fj8SiYTqBldcXKzmP639FOE0MjKCcDis9CtyBlJtGSKeyDgnMnZsbEzpVVS0mWTmySefzChwTHJw/vx5HDx4cEah/8WeM28UFvs+32r7Bic9ya52OBy44oorcNVVV8Hn86GgoAB+v1/VFaRnNDU1hY6ODsTjcRQWFqK0tBQAlO5F+8Dx48fR3Nys9h2qn0xd6aamplRB/JKSEtWtla7FU1wLCwuRSCTQ0tKCkydP4vz58+jp6VGpdwQuM7NxHfxZcGQLVrAifmcLGpnt2tmOWzDi6XKRStmuNZshzY2D+Sz6cyGpZjsH3yh4eB11QOEpe1wAgIs1Z3TFh9py88KBRDLxbl7AxTS6iYkJpQjRpNc7IfH7msv9zsX4no1Mmg+yjcnsWKtokcWEGUlpdUy2CBgrgzcbmToXzGVOz/f75DkgwtXtdqOkpASVlZWoqKhARUUFQqGQ8liUlpbC7/cDANrb21XkFLVK1bs1WMkA1RIYGBjA9773PZXSRN5oOm62Ivm/j144MyyF+1ts4mk2j3e2ucCdBmbnIIWIwrVzcnLg9XqRl5eHFStWYM2aNRgaGoLT6VRRqD09Paqo+OjoKPx+P7q7u+H1etVcrqqqQjgcVvtKOBzG9u3bVcTs9u3b0dPTg9raWtTV1Sljori4GNFoFM3NzfB6vfjP//xPdHd3Y2xsDEeOHLnMT/fNj8WWj7eaATEbiEgiA4OnUnMdC0CG04I3qSDlH4DaX3RHHC9qDEzrVJRGTul13JFH513KTobLjaUuG1Z6l9l6rjsN5qIbZLNzsulxcxm7Pi5+DjNbixoJUQmB+vp6jI6OIicnBytWrMDKlSuVznX06FHYbDbVHY90MMMwcPz4cdWBi2Tn7Nmz+NWvfpUxDsKxY8dUDR3BRSx12XirgDqOUlYSDwwhh8WaNWvwrne9S+0pev1ZijikOrC8ZhrZGpFIBFNTU8jPz0dBQQEmJiYwMDCArq4uDA0NIRwOo729Hb29vZiamkJZWRlaW1sxNDSkGnnxNYjXbsoW7DLXYBv6fTa7UF9vrK6hHzubDq1/bzbMmXgSCAQCgUAgEAgEAoFAIBAI5gP77IcIBAKBQCAQCAQCgUAgEAgE84cQTwKBQCAQCAQCgUAgEAgEggWBEE8CgUAgEAgEAoFAIBAIBIIFgRBPAoFAIBAIBAKBQCAQCASCBYEQTwKBQCAQCAQCgUAgEAgEggWBEE8CgUAgEAgEAoFAIBAIBIIFgRBPAoFAIBAIBAKBQCAQCASCBYEQTwKBQCAQCAQCgUAgEAgEggWBEE8CgUAgEAgEAoFAIBAIBIIFgRBPAoFAIBAIBAKBQCAQCASCBYEQTwKBQCAQCAQCgUAgEAgEggWBEE8CgUAgEAgEAoFAIBAIBIIFgRBPAoFAIBAIBAKBQCAQCASCBYEQTwKBQCAQCAQCgUAgEAgEggWBEE8CgUAgEAgEAoFAIBAIBIIFgRBPAoFAIBAIBAKBQCAQCASCBYEQTwKBQCAQCAQCgUAgEAgEggWBEE8CgUAgEAgEAoFAIBAIBIIFgRBPAoFAIBAIBAKBQCAQCASCBYEQTwKBQCAQCAQCgUAgEAgEggWBEE8CgUAgEAgEAoFAIBAIBIIFgRBPAoFAIBAIBAKBQCAQCASCBYEQTwKBQCAQCAQCgUAgEAgEggWBEE8CgUAgEAgEAoFAIBAIBIIFgRBPAoFAIBAIBAKBQCAQCASCBYEQTwKBQCAQCAQCgUAgEAgEggWBEE8CgUAgEAgEAoFAIBAIBIIFgRBPAoFAIBAIBAKBQCAQCASCBYEQTwKBQCAQCAQCgUAgEAgEggWBEE8CgUAgEAgEAoFAIBAIBIIFgRBPAoFAIBAIBAKBQCAQCASCBYEQTwKBQCAQCAQCgUAgEAgEggWBEE8CgUAgEAgEAoFAIBAIBIIFgRBPAoFAIBAIBAKBQCAQCASCBYEQTwKBQCAQCAQCgUAgEAgEggWBEE8CgUAgEAgEAoFAIBAIBIIFgRBPAoFAIBAIBAKBQCAQCASCBYEQTwKBQCAQCAQCgUAgEAgEggWBEE8CgUAgEAgEAoFAIBAIBIIFgRBPAoFAIBAIBAKBQCAQCASCBYEQTwKBQCAQCAQCgUAgEAgEggWBEE8CgUAgEAgEAoFAIBAIBIIFgRBPAoFAIBAIBAKBQCAQCASCBYEQTwKBQCAQCAQCgUAgEAgEggWBEE8CgUAgEAgEAoFAIBAIBIIFgRBPAoFAIBAIBAKBQCAQCASCBYEQTwKBQCAQCAQCgUAgEAgEggWBEE8CgUAgEAgEAoFAIBAIBIIFgRBPAoFAIBAIBAKBQCAQCASCBYEQTwKBQCAQCAQCgUAgEAgEggWBEE8CgUAgEAgEAoFAIBAIBIIFgRBPAoFAIBAIBAKBQCAQCASCBYEQTwKBQCAQCAQCgUAgEAgEggWBEE8CgUAgEAgEAoFAIBAIBIIFgRBPAoFAIBAIBAKBQCAQCASCBYEQTwKBQCAQCAQCgUAgEAgEggWBEE8CgUAgEAgEAoFAIBAIBIIFgRBPAoFAIBAIBAKBQCAQCASCBYEQTwKBQCAQCAQCgUAgEAgEggWBEE8CgUAgEAgEAoFAIBAIBIIFgRBPAoFAIBAIBAKBQCAQCASCBYEQTwKBQCAQCAQCgUAgEAgEggWBEE8CgUAgEAgEAoFAIBAIBIIFwe8l8fT5z38eNpvtkr77wx/+EDabDa2trZd3UAytra2w2Wz44Q9/uGDXEAgElwdvxJogELwZIbIhEFhD5EMgMIfIhkBgjt932VhSxNPJkyfxgQ98AJWVlXA4HKioqMD73/9+nDx5crGHtih49tlnYbPZ8Itf/GKxhyJYovj2t78Nm82G7du3L/ZQFhXJZBKf//zn8eyzzy7aGHp6evB3f/d3uO666+Dz+WCz2RZ1PG91iGxMYynIxtNPP42PfOQjWLlyJdxuN+rr6/Gxj30MPT09izamtzpEPqaxFORj7969eMc73oHq6mo4nU6UlZXhlltuwf79+xdtTG9liGxMYynIho6Pf/zjsNlsuP322xd7KG9JiGxMYynIBhFUZv96e3sXbVyzIXexB0B48MEH8d73vhcFBQX46Ec/irq6OrS2tuL73/8+fvGLX+CBBx7AXXfdNadzfeYzn8Hf/d3fXdI4PvjBD+KP/uiP4HA4Lun7AsEbifvvvx+1tbU4cOAAzp8/jxUrViz2kBYFyWQSX/jCFwAA11577aKM4cyZM/jKV76ChoYGrFu3Di+++OKijEMwDZGNaSwF2fif//N/IhKJ4N3vfjcaGhrQ3NyM++67D4899hiOHDmCsrKyRRnXWxkiH9NYCvJx9uxZ2O12/Omf/inKysowNDSEn/70p9i1axd+/etf45ZbblmUcb1VIbIxjaUgGxyHDh3CD3/4QzidzsUeylsWIhvTWEqy8cUvfhF1dXUZnwWDwcUZzBywJCKeLly4gA9+8IOor6/HsWPH8A//8A/46Ec/invvvRfHjh1DfX09PvjBD6K5uTnreRKJBAAgNzf3khemnJwcOJ3OS07VEwjeKLS0tOCFF17A17/+dRQXF+P+++9f7CG9pXHFFVcgHA7j7Nmz+Ou//uvFHs5bGiIbSwtf//rXcf78eXzlK1/Bxz72MXzpS1/CY489hr6+Ptx3332LPby3HEQ+lhY+9rGP4Ve/+hX+/u//Hh/96EfxqU99Ci+88AKKi4vxjW98Y7GH95aCyMbShGEY+Mu//Et86EMfQmlp6WIP5y0JkY2libe//e34wAc+kPFvKZOzS4J4+upXv4pkMonvfe97KC4uzvhbUVERvvvd7yKRSOCf/umf1OdUx+m1117D+973PoRCIVx99dUZf+NIpVL4y7/8SxQVFcHn8+Ed73gHurq6YLPZ8PnPf14dZ5ZbWVtbi9tvvx3PP/88tm3bBqfTifr6evz4xz/OuEYkEsGnPvUprFu3Dl6vF36/H29/+9tx9OjRy/SkLt7b2bNn8YEPfACBQADFxcX47Gc/C8Mw0NHRgXe+853w+/0oKyvD1772tYzvj4+P4//7//4/XHHFFQgEAvB4PLjmmmuwZ8+eGdcKh8P44Ac/CL/fj2AwiA9/+MM4evSoaX2q06dP413vehcKCgrgdDqxZcsWPPLII5ftvgUzcf/99yMUCuG2227Du971LtNNgNI19XBQqzpjP//5z7F69Wo4nU6sXbsWDz30EO655x7U1tbO+O7/+T//B9/61rdQX18Pt9uNm266CR0dHTAMA/feey+qqqrgcrnwzne+E5FIZMbYfvOb3+Caa66Bx+OBz+fDbbfdNiOt9p577oHX60VXVxfuvPNOeL1eFBcX41Of+hSmpqbUeGjd+MIXvqBCTblcz3V+njx5Etdffz1cLheqqqrwD//wD0in09leg4LP50NBQcGcjhUsLEQ2lpZs7Nq1C3a7fcZnBQUFOHXq1JzOIbh8EPlYWvJhBrfbjeLiYgwPD1/yOQTzh8jG0pSNn/zkJzhx4gT+9//+3/P6nuDyQWRjacoGAMTjcTW+JQ9jCaCiosKora3Nekxtba1RVVWlfv/c5z5nADBWr15tvPOd7zS+/e1vG9/61rcy/sbxnve8xwBgfPCDHzS+9a1vGe95z3uMDRs2GACMz33uc+q4H/zgBwYAo6WlRX22bNkyo7Gx0SgtLTU+/elPG/fdd5+xefNmw2azGSdOnFDHHTx40Fi+fLnxd3/3d8Z3v/td44tf/KJRWVlpBAIBo6urSx3X0tJiADB+8IMfZL3nPXv2GACMn//85zPue+PGjcZ73/te49vf/rZx2223GQCMr3/960ZjY6PxZ3/2Z8a3v/1t46qrrjIAGM8995z6/sDAgFFeXm789V//tfGd73zH+Kd/+iejsbHRyMvLM1599VV13NTUlLFz504jJyfH+Iu/+AvjvvvuM972trepZ8bHfuLECSMQCBirV682vvKVrxj33XefsWvXLsNmsxkPPvhg1nsUXDqampqMj370o4ZhGMbevXsNAMaBAwcyjqE5tGfPnozPzebgY489ZthsNmP9+vXG17/+deOzn/2sEQqFjLVr1xrLli2b8d2NGzcaq1evNr7+9a8bn/nMZ4z8/Hxjx44dxqc//WnjyiuvNP7lX/7F+Mu//EvDZrMZf/zHf5xx/R//+MeGzWYzbrnlFuOb3/ym8ZWvfMWora01gsFghux9+MMfNpxOp7FmzRrjIx/5iPGd73zHuPvuuw0Axre//W3DMAxjZGTE+M53vmMAMO666y7jJz/5ifGTn/zEOHr0qGEYc5+fPT09RnFxsREKhYzPf/7zxle/+lWjoaHBWL9+/Yw1YTb8/Oc/N33ugjcGIhtLVzYI8XjcyM/PN/7kT/5k3t8VvD6IfCxN+YhGo8bAwIBx6tQp43/9r/9lADA+/elPz+m7gssDkY2lJxuxWMwoKysz/vEf/9EwjGmb7Lbbbpv1e4LLC5GNpSUbxFd4vV4DgJGfn2/ccccdxtmzZ7N+b7Gx6MTT8PCwAcB45zvfmfW4d7zjHQYAIxaLGYZxkYB573vfO+NYnXh65ZVXDADGJz/5yYzj7rnnnjkTTwCMvXv3qs/6+/sNh8Nh/M3f/I36bHR01Jiamsq4RktLi+FwOIwvfvGLGZ+9XuKJK+uTk5NGVVWVYbPZjC9/+cvq86GhIcPlchkf/vCHM44dGxvLuM7Q0JBRWlpqfOQjH1Gf/fKXvzQAGN/4xjfUZ1NTU8b1118/Y+w33HCDsW7dOmN0dFR9lk6njSuvvNJoaGjIeo+CS8OhQ4cMAMaTTz5pGMb0866qqjL+6q/+KuO4+WwC69atM6qqqox4PK4+e/bZZw0ApptAcXGxMTw8rD4nRXnDhg3GxMSE+vy9732vkZ+fr+ZHPB43gsGg8fGPfzxjTL29vUYgEMj4/MMf/rABIEN+DMMwNm3aZFxxxRXq94GBgRmyTJjr/PzkJz9pADBefvll9Vl/f78RCASEeHoTQWRjacsG4d577zUAGE8//fS8vyu4dIh8LF35uPnmmw0Ayoj4xCc+YaRSqTl9V/D6IbKxNGXjU5/6lFFXV6euJcTTGw+RjaUnGz/72c+Me+65x/jRj35kPPTQQ8ZnPvMZw+12G0VFRUZ7e3vW7y4mFj3VLh6PA5hOU8kG+nssFsv4/E//9E9nvcYTTzwBAPhv/+2/ZXz+3//7f5/zOFevXo1rrrlG/V5cXIzGxsaMulMOh0OlE0xNTSEcDsPr9aKxsRGHDx+e87Xmgo997GPq55ycHGzZsgWGYeCjH/2o+jwYDM4YY05ODvLz8wEA6XQakUgEk5OT2LJlS8YYn3jiCeTl5eHjH/+4+sxut+PP//zPM8YRiUTwzDPP4D3veQ/i8TgGBwcxODiIcDiMm2++GefOnUNXV9dlvXfBdMhraWkprrvuOgCAzWbDH/7hH+KBBx64pHDL7u5uHD9+HB/60Ifg9XrV57t378a6detMv/Pud78bgUBA/U5dLj7wgQ8gNzc34/Px8XE1D5588kkMDw/jve99r5ovg4ODyMnJwfbt203TPnU5v+aaa2at+QbMb34+/vjj2LFjB7Zt26a+X1xcjPe///2zXkewdCCysfRlY+/evfjCF76A97znPbj++usv6RyCS4PIx9KVjy9/+cv43e9+h+9///vYsWMHxsfHMTk5Oa9zCC4dIhtLTzbOnj2Lf/7nf8ZXv/pVafq0iBDZWHqy8Z73vAc/+MEP8KEPfQh33nkn7r33Xvz2t79FOBxe0impi97VjgglIqCsYEVQ6ZXczdDW1ga73T7j2PlU46+pqZnxWSgUwtDQkPo9nU7jn//5n/Htb38bLS0tGcJYWFg452tdyngCgQCcTieKiopmfB4OhzM++9GPfoSvfe1rOH36NCYmJtTn/Pm0tbWhvLwcbrc747v6Mzt//jwMw8BnP/tZfPaznzUda39/PyorK+d+c4KsmJqawgMPPIDrrrsOLS0t6vPt27fja1/7Gp5++mncdNNN8zpnW1sbAHOZWLFihSlxajYHAaC6utr0c5KVc+fOAYClwen3+zN+dzqdM2q/6bJnhfnMz7a2NtMWsY2NjbNeR7A0ILKx9GXj9OnTuOuuu7B27Vr8+7//+7y/L7h0iHwsbfnYuHGj+vkDH/gANm/ejHvuuQe/+MUv5nUewfwhsrE0ZeOv/uqvcOWVV+Luu++e0/GCyw+RjaUpG2a4+uqrsX37djz11FOXfI6FxqITT4FAAOXl5Th27FjW444dO4bKysoZE8Tlci3k8BRycnJMPzcMQ/38pS99CZ/97GfxkY98BPfeey8KCgpgt9vxyU9+8nUVmZzreOYyxp/+9Ke45557cOedd+Jv//ZvUVJSgpycHPzjP/4jLly4MO9x0H196lOfws0332x6zFu13eZC4ZlnnkFPTw8eeOABPPDAAzP+fv/996tNwKo74+UoQmc132abhzRnfvKTn5i2Ueeei2znmwtkfr61ILIxdyyGbHR0dOCmm25CIBDA448/Pmuks+DyQuRj7ljsvSM/Px/veMc78OUvfxmpVOoN03XfqhDZmDveKNl45pln8MQTT+DBBx/MaPg0OTmJVCqF1tZWFBQUzLALBZcXIhtzx2LvG8A0EXfmzJkFvcbrwaITTwBw++2349/+7d/w/PPPq850HPv27UNrays+8YlPXNL5ly1bhnQ6jZaWFjQ0NKjPz58/f8ljNsMvfvELXHfddfj+97+f8fnw8PCMSKTFwi9+8QvU19fjwQcfzFggPve5z2Uct2zZMuzZswfJZDIj6kl/ZvX19QCAvLw83HjjjQs4cgHh/vvvR0lJCb71rW/N+NuDDz6Ihx56CP/6r/8Kl8uFUCgEADM645C3gbBs2TIA5jJxueVk+fLlAICSkpLLNmesNrv5zM9ly5YpzwjHUl7ABZkQ2ZiJpSIb4XAYN910E8bGxvD000+jvLx8zt8VXB6IfMzEUpEPM6RSKRiGgXg8LsTTAkNkYyYWWzba29sBAH/wB38w429dXV2oq6vD//2//xef/OQnZz2X4NIhsjETiy0b2dDc3DwjYmspYdFrPAHA3/7t38LlcuETn/jEjLSwSCSCP/3TP4Xb7cbf/u3fXtL5iXX89re/nfH5N7/5zUsbsAVycnIyoouA6VaRS6nGETG5fJwvv/wyXnzxxYzjbr75ZkxMTODf/u3f1GfpdHrGwlNSUoJrr70W3/3ud9HT0zPjegMDA5dz+G95pFIpPPjgg7j99tvxrne9a8a/v/iLv0A8HldtO5ctW4acnBzs3bs34zy6LFRUVGDt2rX48Y9/jJGREfX5c889h+PHj1/We7j55pvh9/vxpS99KSPVk3Apc4bIUX2zm8/8vPXWW/HSSy/hwIEDGX83axkrWHoQ2TDHUpCNRCKBW2+9FV1dXXj88cczHECCNwYiH+ZYCvLR398/47Ph4WH88pe/RHV1NUpKSuZ0HsGlQWTDHIstG9dffz0eeuihGf+Ki4uxZcsWPPTQQ7jjjjvmfV+CuUNkwxyLLRtW43788cfxyiuv4JZbbpnTORYDSyLiqaGhAT/60Y/w/ve/H+vWrcNHP/pR1NXVobW1Fd///vcxODiI//zP/1Ss5XxxxRVX4O6778Y3vvENhMNh7NixA8899xzOnj0LwJq5nC9uv/12fPGLX8Qf//Ef48orr8Tx48dx//33KwZ0KeD222/Hgw8+iLvuugu33XYbWlpa8K//+q9YvXp1hvDfeeed2LZtG/7mb/4G58+fR1NTEx555BFEIhEAmc/sW9/6Fq6++mqsW7cOH//4x1FfX4++vj68+OKL6OzsxNGjR9/w+/x9xSOPPIJ4PI53vOMdpn/fsWMHiouLcf/99+MP//APEQgE8O53vxvf/OY3YbPZsHz5cjz22GOmiu6XvvQlvPOd78RVV12FP/7jP8bQ0BDuu+8+rF27NmNuvF74/X585zvfwQc/+EFs3rwZf/RHf4Ti4mK0t7fj17/+Na666ircd9998zqny+XC6tWr8bOf/QwrV65EQUEB1q5di7Vr1855fv6P//E/8JOf/AS33HIL/uqv/goejwff+973sGzZsllTgQn/8A//AAA4efIkgOnQ3ueffx4A8JnPfGZe9ySYH0Q2zLEUZOP9738/Dhw4gI985CM4deoUTp06pf7m9Xpx5513zuueBPOHyIc5loJ8vP3tb0dVVRW2b9+OkpIStLe34wc/+AG6u7vxs5/97JKelWDuENkwx2LLRk1NjWl93U9+8pMoLS2VfeMNgMiGORZbNgDgyiuvxKZNm7BlyxYEAgEcPnwY//Ef/4Hq6mp8+tOfvqRn9YbgDe+jlwXHjh0z3vve9xrl5eVGXl6eUVZWZrz3ve81jh8/PuPYz33ucwYAY2BgwPJvHIlEwvjzP/9zo6CgwPB6vcadd95pnDlzxgBgfPnLX1bH/eAHP5jRxtCqdefu3buN3bt3q99HR0eNv/mbvzHKy8sNl8tlXHXVVcaLL7444ziztpJmoLaUP//5z2e97w9/+MOGx+MxHeOaNWvU7+l02vjSl75kLFu2zHA4HMamTZuMxx57zPjwhz+c0b7SMKbbRb7vfe8zfD6fEQgEjHvuucfYv3+/AcB44IEHMo69cOGC8aEPfcgoKysz8vLyjMrKSuP22283fvGLX2S9R8H8cMcddxhOp9NIJBKWx9xzzz1GXl6eMTg4aBjG9Hu8++67DbfbbYRCIeMTn/iEceLECdM5+MADDxhNTU2Gw+Ew1q5dazzyyCPG3XffbTQ1NaljaP5+9atfzfiu2Xw1jIsydfDgwRnH33zzzUYgEDCcTqexfPly45577jEOHTqkjrGa12Yy/sILLxhXXHGFkZ+fP6PN6Vzn57Fjx4zdu3cbTqfTqKysNO69917j+9///pzb/uL/3wrb7J9gYSGyMY2lKBvLli2zlAt93xEsDEQ+prEU5eO+++4zrr76aqOoqMjIzc01iouLjTvuuMPYu3dv1u8JLg9ENqaxFGXDDFY2meDyQ2RjGktRNv7+7//e2LhxoxEIBIy8vDyjpqbG+LM/+zOjt7c36/cWGzbD0HLD3kI4cuQINm3ahJ/+9KfSMn2O+NWvfoW77roLzz//PK666qrFHo7gDcDGjRtRXFyMJ598crGHIhAsKYhsCATWEPkQCMwhsiEQmENk4/cbS6LG0xuBVCo147NvfOMbsNvt2LVr1yKMaOlDf2ZTU1P45je/Cb/fj82bNy/SqAQLhYmJCUxOTmZ89uyzz+Lo0aO49tprF2dQAsESgMiGQGANkQ+BwBwiGwKBOUQ23pp4y0Q8feELX8Arr7yC6667Drm5ufjNb36D3/zmN/iTP/kTfPe7313s4S1JfOxjH0MqlcLOnTsxNjaGBx98EC+88AK+9KUv4X/9r/+12MMTXGa0trbixhtvxAc+8AFUVFTg9OnT+Nd//VcEAgGcOHEChYWFiz1EgWBRILIhEFhD5EMgMIfIhkBgDpGNtyaWRHHxNwJXXnklnnzySdx7770YGRlBTU0NPv/5z+Pv//7vF3toSxbXX389vva1r+Gxxx7D6OgoVqxYgW9+85v4i7/4i8UemmABEAqFcMUVV+Df//3fMTAwAI/Hg9tuuw1f/vKXZQMQvKUhsiEQWEPkQyAwh8iGQGAOkY23Jt4yEU8CgUAgEAgEAoFAIBAIBII3Fm+ZGk8CgUAgEAgEAoFAIBAIBII3FkI8CQQCgUAgEAgEAoFAIBAIFgRCPAkEAoFAIBAIBAKBQCAQCBYEcy4ubrPZFnIcAsElY7HLlIlsCJYqFls2AJEPwdLFYsuHyIZgqUJkQyAwh8iGQGCOuciGRDwJBAKBQCAQCAQCgUAgEAgWBEI8CQQCgUAgEAgEAoFAIBAIFgRCPAkEAoFAIBAIBAKBQCAQCBYEQjwJBAKBQCAQCAQCgUAgEAgWBEI8CQQCgUAgEAgEAoFAIBAIFgRCPAkEAoFAIBAIBAKBQCAQCBYEQjwJBAKBQCAQCAQCgeD/196dR0dR5+sff3pJOp2dJQRCZEfWGxhQQYwgKAIOiKjgIMOmwmXUkVEcHfGoCDpyvY5cFxAVhvHoyIgOiAgoEnYVFI5wQTDggrIJJJANsnV3/f7wB1elgSSk861Ov1/n9NHD0vV0Og9V+XTVtwAgJBg8AQAAAAAAICQYPAEAAAAAACAkGDwBAAAAAAAgJBg8AQAAAAAAICQYPAEAAAAAACAkGDwBAAAAAAAgJBg8AQAAAAAAICQYPAEAAAAAACAkGDwBAAAAAAAgJBg8AQAAAAAAICQYPAEAAAAAACAkGDwBAAAAAAAgJBg8AQAAAAAAICQYPAEAAAAAACAkGDwBAAAAAAAgJBg8AQAAAAAAICQYPAEAAAAAACAkGDwBAAAAAAAgJBg8AQAAAAAAICQYPAEAAAAAACAkGDwBAAAAAAAgJBg8AQAAAAAAICQYPAEAAAAAACAkGDwBAAAAAAAgJBg8AQAAAAAAICQYPAEAAAAAACAkGDwBAAAAAAAgJBg8AQAAAAAAICQYPAEAAAAAACAkGDwBAAAAAAAgJBg8AQAAAAAAICQYPAEAAAAAACAkGDwBAAAAAAAgJBg8AQAAAAAAICQYPAEAAAAAACAkGDwBAAAAAAAgJNymA9idy+WS03nmfC4QCMjv9xtIBAAAEH7cbreaNGmijIwMeb3e07++cuVK5eXlyefzybIsgwkBAEAoMHg6C4/Ho3bt2mnAgAFq1arVGb+fnZ2tefPm6ejRowbSAQAAhAen06mkpCTdcsstGjdunFq3bq2YmJjTv7969Wrl5+drwYIFeu+991RWVmYwLQAAqG4Oq4IfLTkcjlBnsQWXy6VOnTpp4MCBuuuuu1S/fv2grz0QCGjhwoWaO3euPv30UxUUFBhIC0nGPx2NlG4g/JjuhkQ/YF+m+xEJ3YiLi1Pr1q2VkZGhv/zlL2rRooU8Hs9Z/3xeXp5eeuklvffee9qyZYvKy8trMC1OoRtAcHQDCK4i3YiIwZPT6Qx6udwpHo9HSUlJ6tatm9q3b6/f/e53at269TkPjiTJ7/fr+PHjWrRokd555x2tX79excXF1R0f58FOAAjOdDck+gH7Mt2PcOlGdHS0oqKifvFrbrdbF1100S/OWvo5p9Op4cOHq0WLFurQoYPq16+vpKSkCm3P7/dr7969WrBggd58803t2rWLpQ1qGN0AgqMbQHARN3iKj49Xs2bNfvFrTqdTHTp0UJs2bc769zp16qSMjAw1aNBAcXFxVXqteXl5mj59umbMmMEp4jWMnQAQnOluSPQD9mW6H3buRnR0tGJiYtS1a1f179//jCUHvF6vunXr9othksPhkGVZp1/XuT7wqwjLsvTNN99owoQJysrKuqDnQuXQDSA4ugEEV+sHTy6XS8nJyUpPT1fHjh01cOBAXXrppWcc7NSpU0eJiYlnfR6Hw1Etr2/fvn269957tWjRIgUCgQt+PlQMOwEgONPdkOgH7Mt0P+zWDa/Xq6SkJLVr105DhgzRFVdcocaNG6tevXpyu80tCbp+/Xrdcccd2r17t7EMkYZuAMHRDSC4Wjt4io+PV/fu3dWiRQvdcMMNuuyyyxQfH3/eS+Nqwo4dO5SZman8/HzTUSIGOwEgONPdkOgH7Mt0P+zUjYYNG2rSpEnq37+/0tPTlZycbDrSaZZlafbs2br77rv5UK+G0A0gOLoBBFeRboTVXe0cDoeaNGmiiRMn6tZbb1VcXJzi4+NNx/qFZs2aafjw4ZozZ458Pp/pOAAAAEGdWvx7ypQp6t+/vy0+wPs1h8Ohvn37qnv37vrkk09MxwEAAFVwYRfg1yCn06kuXbqc/tQrNTXVdkMn6aezse644w5lZGSYjgIAABBUXFycJkyYoDfffFODBw+25dDplJYtW2rixIlKSEgwHQUAAFRB2AyemjdvrhkzZujaa6894+4qdtO5c2eNHj1aLpfLdBQAAIBfiI2N1dNPP62pU6eqXbt2puOcl8PhUP/+/XXVVVeZjgIAAKogLAZPbdu21fPPP6/u3btf8F1SaoLL5VJ8fDzX4QIAAFuJjY3VyJEjNXLkSMXGxpqOU2Eejyes8gIAgP9j+zWe0tPT9dBDD6lfv36cQQQAAFBFDodD11xzjR5++GEuWwMAADXG1qcPeb1ePfDAAxo6dGjYDZ1M3/UAAADg59LS0jRp0iRddNFFpqNUmmVZHFsBABCmbDt4crvdGjRokH7/+9/L6/WajlMpeXl52rx5M7f9BQAAthAdHa3hw4ere/fupqNUyY8//qjs7GzTMQAAQBXYdvDUrFkzjR8/XsnJyaajVNqePXu0evVqBk8AAMAWUlJSNHjwYEVHR5uOUiUbNmzQl19+aToGAACoAlsOnpxOpwYNGqTevXuH3QLd5eXlWrhwoXbv3m06CgAAgJxOp8aMGaMePXqYjlIlhw8f1pw5c+Tz+UxHAQAAVWDLwVPdunU1YsSIsLiD3a8dOnRIixYtYh0CAABgC16vV7fddltYHldJ0ieffKKtW7eajgEAAKrIlkcgY8aMUUZGhukYlRYIBLRq1Sp99913pqMAAABIkkaOHKn09HTTMark1Jnk+fn5pqMAAIAqst3gKS0tTf3795fb7TYdpdICgYC2bdvGqeAAAMA2vv76a5WVlZmOUSV+v1+bN282HQMAAFwA2w2eYmNjVadOnbBb20n66U58Y8aMUUxMjOkoAAAAkqT169ersLDQdIwq8Xg8mjBhgukYAADgAthu8LR3715t2LAhbO8I5/V6w3JoBgAAaqfy8nK9/vrrpmNUmdfrNR0BAABcANsNnnw+nzZu3KjS0lLTUQAAAMJeVFSU6tSpYzpGlRQVFWnVqlWmYwAAgAtgu8GTJGVlZamgoMB0DAAAgLDn9/u1b9++sFznqbCwUEuXLjUdAwAAXABbDp4KCgq0YsUK0zEAAADCns/n01tvvaUdO3aYjgIAACKQLQdPJSUlev7557Vz507TUSqtuLhYlmWZjgEAAHDavn379M4774TdWU8nT57kuAoAgDBny8GTJO3Zs0dr164Nq0XGS0tL9dZbb7E+FQAAsJXi4mK98cYb2rZtm+koFRYIBDR//nyVlJSYjgIAAC6AbQdP+fn5euWVV/TVV1+ZjlJhq1ev1rx58+T3+01HAQAA+IX9+/friSee0MGDB01HqZBVq1bppZde4rgKAIAwZ9vBkyT97//+r15++WXl5+ebjnJex44d04svvqjDhw+bjgIAAHAGy7KUlZWl9957z/aXrxUVFWnmzJn68ccfTUcBAAAXyNaDp0AgoLfeekvLli2z9SV3paWlmjNnjlatWmX7AzkAABC5Tpw4occee8zWZ5SXlZVpzpw5WrFiBcdVAADUArYePEnS4cOH9be//U05OTmmowRlWZY2btyoefPmqbi42HQcAACAc8rJydHf/vY3FRYWmo4S1LZt2zR37lydPHnSdBQAAFANbD94kn46APmf//kf2y0uWVRUpCVLluiZZ55Rdna26TgAAADnFQgE9MYbb2jZsmW2OqOotLRUWVlZeuqpp/Tll1+ajgMAAKqJw6rgEYfD4Qh1lnNKS0vTfffdp+HDh6tevXryeDxG8xQVFWnGjBl64YUXlJuba+tLAWs70wfNprsBnI3pbkj0A/Zluh926EabNm00ePBgDRw4UF27dpXX6zWWq7y8XDNmzNCzzz6rI0eOGH9/Ipnpr70dugEEQzeA4CrSjbAZPElSTEyMWrRooauvvloDBw7UZZddpsTERDmdNXviVnFxsV588UVNnTpVRUVFNbptnImdABCc6W5I9AP2ZbofdumG0+lUbGysunbtqjFjxqhnz55q3rx5jeYrKyvTzJkz9dhjj9n28r9IQjdQVcnJybr00ksVExOjkydPauvWrSovL1diYqISExPl8/n0zTffhO2dKukGEFytGzyd4nQ61aBBA11++eW65ZZbdOONNyoqKqpGtl1YWKiXXnpJzz33XNjcjri2YycABGe6GxL9gH2Z7ocduxEbG6t+/fpp1qxZatiwYci3Z1mWTpw4oXnz5unpp5/W/v37Q75NnB/dQGW4XC55PB7Vr19fI0eO1L333qvo6GiVlJTo22+/VWFhoVwul9LS0hQIBJSdna1NmzbpH//4h3JycmRZVtgMougGEFytHTz9XMuWLTVnzhxdeeWVcrlcId1WSUmJ3nzzTf35z3/WsWPHQrotVBw7ASA4092Q6Afsy3Q/7NqN6Oho3XLLLZoyZYpatGgR0m1t2LBBr732mt59913b3kQmEtENVITD4VD9+vU1ePBg9e3bV7Gxserbt2+FlkPx+Xz69NNPtWLFCh04cEALFizQiRMnaiD1haEbQHARMXhyOp26+OKLNXXqVA0ZMkRut7vatxEIBFRQUKDZs2drxowZOnr0qPF/ePB/TL8Xdu0GYLobEv2AfZnuh5274Xa7NXbsWE2fPl1169at1ucuKytTbm6u1qxZo6lTp2rPnj0KBALG3w/8H9PvhZ27gZ9ER0erb9++mjx5stq1a6c6depU6XlKS0t18uRJzZ49W9OnT1dBQUE1J61edAMILiIGT6d07txZs2bN0uWXX15tz2lZlr7//nutW7dO77//vt5//30VFxdX2/OjerATAIIz3Q2JfsC+TPfD7t1wuVwaNWqUpk6dqvT09Gp5zoMHD2rWrFlavHixdu3aFTaX10QauoFzcblcmjRpku6//36lpKRUy3OWlpZq2rRpeuaZZ1RaWlotzxkKdAMILqIGTw6HQx06dNCjjz6qgQMHyuv1XtDzFRcX66OPPtKTTz6pr776SoWFhcb/sUFwpt8Xu3fjbOLi4hQdHS2Xy6WWLVsqISFBl156qTp37ixJysrKUnZ2tnbt2qUuXbooJydH27dvt/UBAX7JdDek8O0Haj/T/QiHbkRFRSkzM1NPPvmk2rdvr6SkpCo9j2VZ2rx5sx577DFlZWWprKysmpOiOtENBONwOBQXF6f27dtr6dKlql+/frU+f05OjmbOnKlnn33Wtmc+0Q1UVXR0tLxer5KTkyVJJ06cUG5urvHvqeoSUYOnU1JSUjRhwoTTtwau7LpPgUBAJ06cOH1Z3aFDh0KUFNXFdGHDpRuneL1eXX311frtb3+rpk2byu12q3PnzqpTp46cTufpu0QGAgGVlpbqk08+UevWrXXy5Em9//77evnll/X1118bfhWoCNPdkMKvH4gcpvsRTt1o1KiRrrrqKj3wwANq27atYmJiKvx39+7dq2XLlum5557T7t27Q5gS1YVu4NdiYmI0cOBADRo0SFdddZUuuuiikLxPhYWF+vOf/6y3335bTqdTeXl58vl81b6dqqIbqIx69eqpefPmiouL08CBA9WyZUtdeumlkqTs7GxNmDBBOTk5ys/PN/69daEicvAkSR6PR40bN9Ydd9yha665Rg0bNjy9AJ7H4/nFa7EsS4FAQIcOHVIgENDq1av12muv6fPPP1dRUZHBV4GKMl3UcOlGTEyMrrrqKl1//fUaOnSo6tSpU+nBrM/n08aNGzVt2jStWbOGT61tznQ3pPDpByKP6X6EWzecTqdSU1OVmZmp9PR0eTwe9e/fXw0aNFDdunVPnw115MgR5efnn14s+JNPPtHWrVs5WzaM0A2c4nA4VK9ePd1333268847lZCQcPoDylDJz8/X0aNHJUnHjx/X2rVrtXjxYm3btk2FhYUh3fb50A2cT2xsrK699lo5HA6NGDFCmZmZcrlcqlu37hnd+e6777Rv3z6tXLlS5eXl2rdvn9avX68DBw6E3aXoETt4+rlmzZopOTlZbrdbV155pVJTU5WRkaG2bdtKkj799FPt2bNHH3zwgUpKSrR3717l5eWZDY1KYSdwfklJSRo3bpzuv/9+paamXtBznVr77MUXX9Ty5cu1e/duW30ahf9juhtSePQDkcl0P8K9Gw6HQwkJCfJ4PGrXrp1atmwpSdqyZYv279+v48ePG/8ao2pMv2/h3o3axOl06pZbbtHLL7+shIQEIxksy1JOTo7+/ve/a9q0aUbvfkc3cC516tTRPffcozvvvFOJiYlnnPByPkVFRdq1a5dmzJihtWvX6uDBgyFMW70YPP2Ky+WS0+mU1+s9fZr4iRMnVFpayg/OYYydwLk1bNhQTzzxhIYPH67Y2Nhqe96SkhIdPHhQ69at0/Tp05WdnV1tz43qYbobkv37gchluh90A3ZFN3BKt27dNG3aNPXp06fSZ8lXt5MnT+rWW2/V4sWLjWWgG/g1l8ul1q1bq3fv3hoyZIgyMzMveK3poqIibd++XY8++qjWrl2r8vLyakobOgyeEBHYCZzbPffco//6r/+q1JoclWFZllavXq1HHnlEmzZtCrtTQ2sz092Q7N+PqnI4HLIsSw6H4/T/S/b4mqNiTL9XtbUbCH90A9JPS5csX75cvXv3Nh3ltI0bN2r48OHau3evke3TDfyc0+nU4MGDNXXqVLVq1araf9b67rvvNGTIEG3btq1anzcUGDwhIrATCM7pdCojI0PPPfecevbsGdJtWZalL774Qrfffru2bdtm/D3BT+zwPti1H1URExOjjh07KiYmRt26dVN+fr48Ho9at26tgoICHT9+XLt27dLatWtVWlqqQCBgOjLOwXQ/alM3ULvQDbjdbvXv31/z5s2r9rvXXYjS0lLNnj1bL7zwgr755psa3z7dwCkdO3bU8OHDdfvtt1/wMibn8q9//UuTJk2y/WV3FeqGVUGSePCw5cM0068/2MPhcFht2rSx1q9fb/l8vhr5OpSVlVlZWVlWjx49LKfTafxrwMN8NyzLnv2o7CM+Pt5q1qyZ9Yc//ME6cOCAdfz4ccvv91uWZZ3+r8/ns3w+n3XkyBFrypQp1u9+9zsrKSnJ8nq9Vnx8vOVwOIy/Dh6/fJhm+vXz4HG2h2mmX38kPxwOh5WQkGCNHDnS+u6770x/KwSVm5trPf/881b9+vXpBo8afzidTqtDhw5WVlZWjbzne/futYYNG2bFxsYaf+3nelQEZzwh7FXwWzhk7NQNl8ultLQ09erVS0OHDtV1110nt9tdY9u3LEtZWVm6++67WfPJBkx3Q7JXPyrD5XKpadOmSkxM1JQpU5SZmamEhARFR0ef9+/6fD75/X4dPHhQubm5iouL05QpU7Rjxw4W47cR0/0I126g9qMbkatZs2aaPXu2rrzyympdF7S6+Xw+bdiwQaNGjdK+fftqbLt0I7IlJCQoIyNDM2fOVMeOHWtk3TO/368vvvhC9957rzZs2BDy7VVVRbrB4Alhj52AFBcXpzZt2qhfv34aMGCAOnfurPj4eCPZ/H6/Vq5cqccee0zbt2/XyZMnazwDfmK6G5I9+lEVDRo00Pvvv6/4+Hi1a9fugp/v6NGjWrlypV599VV9/PHHKi8vt8X7E8lMf/3DtRuo/ehGZHK73brzzjv19NNPy+PxmI5zXidPntTvf/97LV68uMYubacbkcntdqtRo0a699571aNHD3Xr1q3GMyxZskRTpkzRV199pZKSEtst58DgCREh0ncCTZo00YMPPqhhw4YpOTm5Rs9wOhvr/9/6dtGiRXrhhRe0c+dO2/0DGQlMd0My34/K8nq9atOmje6++26NHTtWTqez2p47EAiopKREb7zxhubOnasvvvgiLO5UUluZ7ke4dQORg25EJo/Ho8mTJ+vRRx81HaXCPvnkE40YMaLGFhunG5HH6XTquuuu01//+le1a9fO2M9ZgUBABQUFWrZsmT788EN9/PHH+uGHH2xzHMngCREh0ncCHTt21Ntvv622bdsazRGM3+/XkiVLNGHCBB0+fNh0nIhjuhuS+X5UhsPh0MSJE/WHP/xBzZs3V1RUVEi2U15erq+//loPP/yw1qxZI5fLpby8PC7Bq2Gm+xFO3UBkoRuRx+Fw6IorrtBrr72mFi1amI5TYX6/X4MHD9bSpUtrZHt0I/I0bNhQs2fP1sCBA2vk0rrzsSxLBQUFys7O1ooVKzRr1iwdOnTIdKwKdaP6PsoFUOPcbrduvvlm2x4kuFwuDRo0SKNGjQqL07YRuRwOh/r06aPx48fr4osvDtnQSZKioqLUrl07vfPOO1q3bp3Wrl2rAQMGcEAJADAiPj5eDzzwgG2PJ8/G5XKpX79+7D8REh6PR6NHj7bN0En66Xg1KSlJl112mSZPnqynnnpKCQkJpmNVCIMnIIx1795dY8aMqdCCx6a4XC7ddttt6tq1KwcGsK3k5GTdfvvt1bKeU0U5nU517NhRbdu21bhx49SkSRPFx8fX2PYBAJCkm2++Wf369TMdo0r69eunlJQUjjFR7S655BKNHTvWNkOnX3M6nRo0aJB69OhhOkqFMHgCwlTDhg01ceJENWnSxHSU82rbtq0mTZqkjIwM01GAoMaPH6+bb77ZyLZPrR/w+uuv66GHHrL1IBkAUPv06tUrbPc9F198sf7973+rUaNGpqOgFvF6vbrvvvvUpk0b01HOqW7duurTp48t1vg9HwZPQBiKiorSyJEjde2114bNJzwDBgww9oM9cC4pKSnq2bNnSC+vOx+Xy6XMzEyNHTuWAS0AAJVQnTcCAWJjYzVmzBhde+21pqNUyPDhw3XFFVfY/mdCWgqEoZYtW+r2229XYmKi6SgVFhMTo9jYWNMxgDNcffXV6tKli+kYcjgcatSokWbNmqUhQ4bY/gACAFA7fPjhhyosLDQdo0rKy8u1cOFCHTx40HQU1BI9evTQU089FTbLH6Snp+uee+5Rw4YNTUc5JwZPQJiJiopS7969w24BSMBukpKSNGLECD366KO22llfeumlmjx5Mp/gAgBqxIoVK8J28JSdna1//vOfpmMAxjgcDtWtW1dxcXGmo5yT/S8GBPALHTp00MSJE41eFgSEu5SUFF1//fV69dVXbXlmkcfjsWUuAADsZPbs2Tp8+LDpGIBRXbp00TXXXKNvv/1WgUDAdJyg+DgVCDMdO3ZUq1atTMcAwlZaWpr++7//W08++aRthzutW7fWH//4R9MxAAARoLy8XN9++63pGJW2YcMGrVy5UpZlmY4CGJWYmKjf/va3qlOnjukoZ8XgCQgjbrdbN9xwg21v63kulmXp5MmTpmMggjkcDnXs2FHTpk3T6NGjlZqaajrSWUVFRSkpKcl0DABABCgqKtJ7770XVgOcQCCg/fv36+jRo6ajALbQr18/DR061LZLNdgzFYCgEhIS9Jvf/MZ0jCo5efKkXn/9ddMxEMFSUlL07LPPasyYMaajnJfD4VCTJk2UkJBgOgoAoJZLTEzUrbfeatuzgIM5duyY3n33XeXn55uOglomJycnLC/fjIqKUp8+fRQdHW06SlAMnoAwct1116lBgwamY1SJ3+9Xp06dTMdABIuKilLjxo1t+0nQzzmdTl100UXyer2mowAAarmoqKiwumlNUVGRnnnmGS1dulR+v990HNQy2dnZ2r59u+kYVdKlSxe1adPGdIyg7H/0DeC077//XsXFxaZjVEl8fLyuv/56Lh+CMZMnT1b79u1Nx6iw4uJilZeXm44BAKjl/H6/8vLyTMeosI8//lhz585VUVGR6SiohX7zm9/o8ssvNx2jStLS0mw7RGbwBISRjRs36ssvvzQdo0pcLpd69eqlDh06mI6CCHXo0CHTESrlmmuu0fTp07mDJQAgpLp166ZGjRqZjlEhP/zwg1544QXl5OSYjoJaKDY2VjfffLPq169vOkqVeDweDRs2zJbrATN4AsKIz+fTX//617C87liSGjVqpNGjR8vtdpuOggjTuHFjXXHFFaZjVIrX69Wtt96qIUOGmI4CAKil4uPjdd1114XFsdnRo0c1efJkLV++3HQU1ELx8fGaNm2a7rrrLtuuk3Q+fr9fO3fuVCAQMB3lDAyegDCzefNmffbZZ6ZjVInb7VZmZqbatm1rOgoiSExMjEaNGqXMzEzTUSotNjZWjzzyiEaNGmXLT68AAOGtadOm6tOnj+0XFj906JAmTZqkxYsX2/KHaoS/Fi1aqH///mE7dLIsS19//bWWLVtmyztUMngCwkx+fr5eeOEFHTlyxHSUKmndurVuueUW7taFGpOYmBi2w06n06mOHTtq9OjR6ty5s+k4AIBaxu12y+PxmI5xVnl5ecrOztb8+fO1fPly1nVCSDgcDt10001q2bKl6ShVtnHjRmVmZmrLli2mowTF4AkIM4FAQOvXr9eoUaP0+eefm45TaVFRUbruuutUr14901EQIZxOp9LS0hQfH286SpVlZGQoPT09LO7IBwAIH+Xl5SooKDAd4wyWZSk7O1u33XabBg8erClTprCuE0LG4XAoJSXF1kPYcykvL9fbb79t65sE2P9iXgBnKCkp0UcffaTY2Fi99NJLSk1NNR0JsK2LL75YvXv3Nh3jgtSvX19/+tOftGHDBuXm5pqOAwCoJXbu3KlXXnlFM2fOtMWHGwUFBdqxY4c2b96sFStWaOnSpaYjAba3Zs0aLVq0yNaXoTJ4AsJUIBDQBx98oMcff1xPPPGE6tatazpShRUWFsrv95uOgQiRk5Nj+7UrKqI2vAYAgP2sX79eGzduVNeuXWvsjI+ysjLl5+fLsiwVFhZq7ty5sixLu3bt0ueff66cnBz5fL4ayQKEs5ycHM2aNUv79u0zHeWcGDwBYay4uFjz589X/fr1NWnSJCUlJZmOdF7Hjh3Tyy+/rIMHD5qOggjh9XpNR6gWiYmJSkhI4IwnAEC1ys7O1oMPPqjnnntOXbp0qbbn/fUCx6tWrdKuXbskSQcPHtT69etVVlamsrIybd26tdq2C1SWZVnauXOnCgoKlJiYaDpOhe3fv19vv/22PvzwQ9t/qM/gCQhzeXl5evbZZ+X1evWnP/3J1j9k+3w+LVu2TEuWLLH9P46oPQYNGlQrzhbas2ePra/dBwCEJ5/Ppw0bNmjVqlXq0KHDBZ/1tGPHDq1evVqLFy+W9NNZ+k6nU7t379bhw4dP/xpnNMEuLMvSwoULlZmZqaFDh9ristNzCQQC+uabb/Twww9rzZo1Ki4uNh3pvBxWBe+1VxsO2lE7mb5dpF26kZqaqrvvvlt33323kpOTTccJ6tixYxo2bJiysrJMR4kIprsh2aMfXbt21aZNm+RyuUxHqbLi4mLdddddmjdvnukotYbpftihG0AwdCNypaSk6KWXXtJNN91U6b8bCASUnZ2t3bt3a8aMGVq7dm0IEppFN2q/bt26adGiRWrUqJHpKOf0/fffa/To0Vq/fr0t1nWqSDc44wmoJQ4fPqzp06crOztb999/v9LT01WnTh05nU75/X5b/NC9evVqffbZZ6ZjIMIMGzYs7A/WXC6XYmJiTMcAANRiR48e1aOPPqpAIKCMjAw1bty4QneEPX78uDZu3KgFCxbovffe4+xchK0vv/xS+/bts+3gKRAIaM+ePXr88cf18ccf22LoVFEMnoBa5MSJE3rzzTe1fft2XXTRRRo0aJB69uypFStWqHv37urUqZOioqLO+Hs1cTppUVGRXnnlFRUWFoZ8W8DPzZ8/X/Hx8Ro1alSFDqDtaPv27dq0aZPpGACAWm7nzp0aN26cUlJSNHjwYI0bN06lpaX6j//4j198iGNZlnJzc/XVV19pyZIleu21105fRgeEK8uytG7dOl1yySW2utzOsqzTl8Q+/vjj2rBhQ9gtW8Kldgh7nPZ6dl6vVw0aNNCRI0fk9XrVq1evM86aSEtL04ABA876OuLj49WqVSvl5eXJsiylpaVVah2p4uJiZWdn65VXXtHf//53lZaWXtBrQsWZ7oZkn34kJCTojTfe0PXXX286SqX5/X6NGDFCCxYssMV7WluY/lrapRvAr9ENnOJ2u5WUlKTk5GSNHz9ezZs3P/17xcXFevzxx5Wfn6/8/PyIWK+JbkSGxo0b6/7779eNN96otLQ0ud1VP1fnbGcknWuoVVpaqgMHDqiwsFApKSnasmWLNm/erI8//libN29WQUGB8e/FX6tIHgZPCHumixfu3XC73YqLizvr7ycmJqpDhw5KTEzU7t27ddNNN2nYsGFq1arVOf/R9Pv92rNnj9555x3985//1DfffKPy8vJQvAScheluSPbqR5s2bfT888+rb9++tsp1LpZlKSsrSxMnTtTOnTtNx6lVTPcjXL4HEXnoBoJxuVy/OO47dQZGJKEbkSM+Pl5dunTRf/7nf6pPnz5KTU0979ff7/fr2LFjSkpK0v79+3X48GG9++67Z5yZ1KhRI40fP175+flav379GQuDf/vtt/roo4/k8/lUt25dbd26Vbm5uca//86FwRMigukSRko3HA6HLMtSVFSU6tevr4ceekhXX321mjRpcsafLS0t1VtvvaVp06YpNzeXgZMhprsh2asfDodDl19+uf7yl79o0KBBpuOc1/Hjx/XBBx/o2Wef1ebNm03HqXVM98NO3QB+jm4AwdGNyBMTE6MOHTpo+vTp6tmzp6Kjo4P+uW3btmnJkiVavny5mjRpok8//VRHjx5VSUnJGX/W4/GoadOmKisr06FDh84YTPn9/rC7jI7BEyICOwEzYmNj1bx5c7Vq1eqMr0FxcbE+++wzHT9+3FA6SOa7IdmvHx6PR127dtWrr76qNm3a2GLR/WDy8/M1YsQIbdy4Ubm5uabj1Eqm+2G3bgCn0A0gOLoRuTp37qzXX3/9jCVLCgsLtWrVKv3rX//Sli1bjH+PmMLgCRHBdMHpBuzKdDcke/bD4XAoNTVVDz30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of images train_dataset = \", len(train_dataset))\nprint(\"Number of images in each train_dataset = \", len(train_dataset[0]))\nprint(\"Total = \",(len(train_dataset)*len(train_dataset[0])))","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-30T19:08:20.381978Z","iopub.execute_input":"2025-03-30T19:08:20.382362Z","iopub.status.idle":"2025-03-30T19:08:20.401045Z","shell.execute_reply.started":"2025-03-30T19:08:20.382330Z","shell.execute_reply":"2025-03-30T19:08:20.399991Z"}},"outputs":[{"name":"stdout","text":"Number of images train_dataset =  12864\nNumber of images in each train_dataset =  2\nTotal =  25728\n","output_type":"stream"}],"execution_count":14},{"cell_type":"code","source":"print(\"Number of images val_dataset = \", len(val_dataset))\nprint(\"Number of images in each val_dataset = \", len(val_dataset[0]))\nprint(\"Total = \",(len(val_dataset)*len(val_dataset[0])))","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-30T19:08:20.650767Z","iopub.execute_input":"2025-03-30T19:08:20.651098Z","iopub.status.idle":"2025-03-30T19:08:20.674677Z","shell.execute_reply.started":"2025-03-30T19:08:20.651073Z","shell.execute_reply":"2025-03-30T19:08:20.673335Z"}},"outputs":[{"name":"stdout","text":"Number of images val_dataset =  460\nNumber of images in each val_dataset =  2\nTotal =  920\n","output_type":"stream"}],"execution_count":15},{"cell_type":"code","source":"print(\"Number of images test_dataset = \", len(test_dataset))\nprint(\"Number of images in each test_dataset = \", len(test_dataset[0]))\nprint(\"Total = \",(len(test_dataset)*len(test_dataset[0])))","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-30T19:08:20.926114Z","iopub.execute_input":"2025-03-30T19:08:20.926511Z","iopub.status.idle":"2025-03-30T19:08:20.947909Z","shell.execute_reply.started":"2025-03-30T19:08:20.926470Z","shell.execute_reply":"2025-03-30T19:08:20.946910Z"}},"outputs":[{"name":"stdout","text":"Number of images test_dataset =  460\nNumber of images in each test_dataset =  2\nTotal =  920\n","output_type":"stream"}],"execution_count":16},{"cell_type":"markdown","source":"# Model","metadata":{}},{"cell_type":"code","source":"DEVICE = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n\nclass DoubleConv(nn.Module):\n    def __init__(self,in_channels,out_channels):\n        super(DoubleConv,self).__init__()\n        self.conv = nn.Sequential(\n            nn.Conv2d(in_channels, out_channels, 3, 1, 1, bias=False),\n            nn.BatchNorm2d(out_channels),\n            nn.ReLU(inplace=True),\n            nn.Conv2d(out_channels, out_channels, 3, 1, 1, bias=False),\n            nn.BatchNorm2d(out_channels),\n            nn.ReLU(inplace=True),\n        )\n\n    def forward(self, x):\n        return self.conv(x)\n\nclass AttentionBlock(nn.Module):\n    def __init__(self, F_g, F_l, F_int):\n        super(AttentionBlock, self).__init__()\n        self.W_g = nn.Sequential(\n            nn.Conv2d(F_g, F_int, kernel_size=1, stride=1, padding=0, bias=True),\n            nn.BatchNorm2d(F_int)\n        )\n        \n        self.W_x = nn.Sequential(\n            nn.Conv2d(F_l, F_int, kernel_size=1, stride=1, padding=0, bias=True),\n            nn.BatchNorm2d(F_int)\n        )\n        \n        self.psi = nn.Sequential(\n            nn.Conv2d(F_int, 1, kernel_size=1, stride=1, padding=0, bias=True),\n            nn.BatchNorm2d(1),\n            nn.Sigmoid()\n        )\n        \n        self.relu = nn.ReLU(inplace=True)\n        \n    def forward(self, g, x):\n        g1 = self.W_g(g)\n        x1 = self.W_x(x)\n        psi = self.relu(g1 + x1)\n        psi = self.psi(psi)\n        return x * psi\n        \nclass AttentionUNET(nn.Module):\n    def __init__(self, in_channels=1, out_channels=1, features=[32, 64, 128, 256]):\n        super(AttentionUNET, self).__init__()\n        self.out_channels = out_channels\n        self.ups = nn.ModuleList()\n        self.downs = nn.ModuleList()\n        self.attentions = nn.ModuleList()\n        self.pool = nn.MaxPool2d(kernel_size=2, stride=2)\n\n        # Down part of UNET\n        for feature in features:\n            self.downs.append(DoubleConv(in_channels, feature))\n            in_channels = feature\n\n        # Bottleneck\n        self.bottleneck = DoubleConv(features[-1], features[-1]*2)\n        \n        # Up part of UNET\n        for feature in reversed(features):\n            self.ups.append(nn.ConvTranspose2d(feature*2, feature, kernel_size=2, stride=2))\n            self.attentions.append(AttentionBlock(F_g=feature, F_l=feature, F_int=feature // 2))\n            self.ups.append(DoubleConv(feature*2, feature))\n\n        self.final_conv = nn.Conv2d(features[0], out_channels, kernel_size=1)\n\n    def forward(self, x):\n        skip_connections = []\n\n        for down in self.downs:\n            x = down(x)\n            skip_connections.append(x)\n            x = self.pool(x)\n\n        x = self.bottleneck(x)\n        skip_connections = skip_connections[::-1] #reverse list\n\n        for idx in range(0, len(self.ups), 2):  #do up and double_conv\n            x = self.ups[idx](x)\n            skip_connection = skip_connections[idx//2]\n\n            if x.shape != skip_connection.shape:\n                x = TF.resize(x, size=skip_connection.shape[2:])\n\n            skip_connection = self.attentions[idx // 2](skip_connection, x)\n            concat_skip = torch.cat((skip_connection, x), dim=1)\n            x = self.ups[idx+1](concat_skip)\n\n        return self.final_conv(x)\n\ndef test():\n    x = torch.randn((3,1, 512, 512)).to(DEVICE)\n    model = AttentionUNET(in_channels=1, out_channels=1).to(DEVICE)\n    preds = model(x)\n    print(f\"Test shape = {x.shape}\")\n    print(f\"Prediction shape = {preds.shape}\")\n    summary(model, (1, 512, 512))\n\nif __name__ == \"__main__\":\n    test()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-30T19:08:24.238057Z","iopub.execute_input":"2025-03-30T19:08:24.238430Z","iopub.status.idle":"2025-03-30T19:08:35.237202Z","shell.execute_reply.started":"2025-03-30T19:08:24.238400Z","shell.execute_reply":"2025-03-30T19:08:35.236104Z"}},"outputs":[{"name":"stdout","text":"Test shape = torch.Size([3, 1, 512, 512])\nPrediction shape = torch.Size([3, 1, 512, 512])\n----------------------------------------------------------------\n        Layer (type)               Output Shape         Param #\n================================================================\n            Conv2d-1         [-1, 32, 512, 512]             288\n       BatchNorm2d-2         [-1, 32, 512, 512]              64\n              ReLU-3         [-1, 32, 512, 512]               0\n            Conv2d-4         [-1, 32, 512, 512]           9,216\n       BatchNorm2d-5         [-1, 32, 512, 512]              64\n              ReLU-6         [-1, 32, 512, 512]               0\n        DoubleConv-7         [-1, 32, 512, 512]               0\n         MaxPool2d-8         [-1, 32, 256, 256]               0\n            Conv2d-9         [-1, 64, 256, 256]          18,432\n      BatchNorm2d-10         [-1, 64, 256, 256]             128\n             ReLU-11         [-1, 64, 256, 256]               0\n           Conv2d-12         [-1, 64, 256, 256]          36,864\n      BatchNorm2d-13         [-1, 64, 256, 256]             128\n             ReLU-14         [-1, 64, 256, 256]               0\n       DoubleConv-15         [-1, 64, 256, 256]               0\n        MaxPool2d-16         [-1, 64, 128, 128]               0\n           Conv2d-17        [-1, 128, 128, 128]          73,728\n      BatchNorm2d-18        [-1, 128, 128, 128]             256\n             ReLU-19        [-1, 128, 128, 128]               0\n           Conv2d-20        [-1, 128, 128, 128]         147,456\n      BatchNorm2d-21        [-1, 128, 128, 128]             256\n             ReLU-22        [-1, 128, 128, 128]               0\n       DoubleConv-23        [-1, 128, 128, 128]               0\n        MaxPool2d-24          [-1, 128, 64, 64]               0\n           Conv2d-25          [-1, 256, 64, 64]         294,912\n      BatchNorm2d-26          [-1, 256, 64, 64]             512\n             ReLU-27          [-1, 256, 64, 64]               0\n           Conv2d-28          [-1, 256, 64, 64]         589,824\n      BatchNorm2d-29          [-1, 256, 64, 64]             512\n             ReLU-30          [-1, 256, 64, 64]               0\n       DoubleConv-31          [-1, 256, 64, 64]               0\n        MaxPool2d-32          [-1, 256, 32, 32]               0\n           Conv2d-33          [-1, 512, 32, 32]       1,179,648\n      BatchNorm2d-34          [-1, 512, 32, 32]           1,024\n             ReLU-35          [-1, 512, 32, 32]               0\n           Conv2d-36          [-1, 512, 32, 32]       2,359,296\n      BatchNorm2d-37          [-1, 512, 32, 32]           1,024\n             ReLU-38          [-1, 512, 32, 32]               0\n       DoubleConv-39          [-1, 512, 32, 32]               0\n  ConvTranspose2d-40          [-1, 256, 64, 64]         524,544\n           Conv2d-41          [-1, 128, 64, 64]          32,896\n      BatchNorm2d-42          [-1, 128, 64, 64]             256\n           Conv2d-43          [-1, 128, 64, 64]          32,896\n      BatchNorm2d-44          [-1, 128, 64, 64]             256\n             ReLU-45          [-1, 128, 64, 64]               0\n           Conv2d-46            [-1, 1, 64, 64]             129\n      BatchNorm2d-47            [-1, 1, 64, 64]               2\n          Sigmoid-48            [-1, 1, 64, 64]               0\n   AttentionBlock-49          [-1, 256, 64, 64]               0\n           Conv2d-50          [-1, 256, 64, 64]       1,179,648\n      BatchNorm2d-51          [-1, 256, 64, 64]             512\n             ReLU-52          [-1, 256, 64, 64]               0\n           Conv2d-53          [-1, 256, 64, 64]         589,824\n      BatchNorm2d-54          [-1, 256, 64, 64]             512\n             ReLU-55          [-1, 256, 64, 64]               0\n       DoubleConv-56          [-1, 256, 64, 64]               0\n  ConvTranspose2d-57        [-1, 128, 128, 128]         131,200\n           Conv2d-58         [-1, 64, 128, 128]           8,256\n      BatchNorm2d-59         [-1, 64, 128, 128]             128\n           Conv2d-60         [-1, 64, 128, 128]           8,256\n      BatchNorm2d-61         [-1, 64, 128, 128]             128\n             ReLU-62         [-1, 64, 128, 128]               0\n           Conv2d-63          [-1, 1, 128, 128]              65\n      BatchNorm2d-64          [-1, 1, 128, 128]               2\n          Sigmoid-65          [-1, 1, 128, 128]               0\n   AttentionBlock-66        [-1, 128, 128, 128]               0\n           Conv2d-67        [-1, 128, 128, 128]         294,912\n      BatchNorm2d-68        [-1, 128, 128, 128]             256\n             ReLU-69        [-1, 128, 128, 128]               0\n           Conv2d-70        [-1, 128, 128, 128]         147,456\n      BatchNorm2d-71        [-1, 128, 128, 128]             256\n             ReLU-72        [-1, 128, 128, 128]               0\n       DoubleConv-73        [-1, 128, 128, 128]               0\n  ConvTranspose2d-74         [-1, 64, 256, 256]          32,832\n           Conv2d-75         [-1, 32, 256, 256]           2,080\n      BatchNorm2d-76         [-1, 32, 256, 256]              64\n           Conv2d-77         [-1, 32, 256, 256]           2,080\n      BatchNorm2d-78         [-1, 32, 256, 256]              64\n             ReLU-79         [-1, 32, 256, 256]               0\n           Conv2d-80          [-1, 1, 256, 256]              33\n      BatchNorm2d-81          [-1, 1, 256, 256]               2\n          Sigmoid-82          [-1, 1, 256, 256]               0\n   AttentionBlock-83         [-1, 64, 256, 256]               0\n           Conv2d-84         [-1, 64, 256, 256]          73,728\n      BatchNorm2d-85         [-1, 64, 256, 256]             128\n             ReLU-86         [-1, 64, 256, 256]               0\n           Conv2d-87         [-1, 64, 256, 256]          36,864\n      BatchNorm2d-88         [-1, 64, 256, 256]             128\n             ReLU-89         [-1, 64, 256, 256]               0\n       DoubleConv-90         [-1, 64, 256, 256]               0\n  ConvTranspose2d-91         [-1, 32, 512, 512]           8,224\n           Conv2d-92         [-1, 16, 512, 512]             528\n      BatchNorm2d-93         [-1, 16, 512, 512]              32\n           Conv2d-94         [-1, 16, 512, 512]             528\n      BatchNorm2d-95         [-1, 16, 512, 512]              32\n             ReLU-96         [-1, 16, 512, 512]               0\n           Conv2d-97          [-1, 1, 512, 512]              17\n      BatchNorm2d-98          [-1, 1, 512, 512]               2\n          Sigmoid-99          [-1, 1, 512, 512]               0\n  AttentionBlock-100         [-1, 32, 512, 512]               0\n          Conv2d-101         [-1, 32, 512, 512]          18,432\n     BatchNorm2d-102         [-1, 32, 512, 512]              64\n            ReLU-103         [-1, 32, 512, 512]               0\n          Conv2d-104         [-1, 32, 512, 512]           9,216\n     BatchNorm2d-105         [-1, 32, 512, 512]              64\n            ReLU-106         [-1, 32, 512, 512]               0\n      DoubleConv-107         [-1, 32, 512, 512]               0\n          Conv2d-108          [-1, 1, 512, 512]              33\n================================================================\nTotal params: 7,851,197\nTrainable params: 7,851,197\nNon-trainable params: 0\n----------------------------------------------------------------\nInput size (MB): 1.00\nForward/backward pass size (MB): 2287.97\nParams size (MB): 29.95\nEstimated Total Size (MB): 2318.92\n----------------------------------------------------------------\n","output_type":"stream"}],"execution_count":17},{"cell_type":"markdown","source":"# Training","metadata":{}},{"cell_type":"code","source":"# Hyperparameters\nLEARNING_RATE = 1e-4\nBATCH_SIZE = 16\nNUM_EPOCHS = 20\nLOAD_MODEL = False\nDEVICE = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n\n# function to save model checkpoint\ndef save_checkpoint(state, filename=\"my_attention_checkpoint.pth.tar\"):\n    print(\"=> Saving checkpoint\")\n    torch.save(state, filename)\n\n# function to load model checkpoint\ndef load_checkpoint(checkpoint, model):\n    print(\"=> Loading checkpoint\")\n    model.load_state_dict(checkpoint[\"state_dict\"])\n\n# function to calculate IoU\ndef calculate_iou(preds, targets):\n    intersection = (preds * targets).sum()\n    union = preds.sum() + targets.sum() - intersection\n    return intersection / (union + 1e-8)  # Adding epsilon to avoid division by zero\n\n# function to check accuracy, return Dice score, IoU score & validation loss\ndef check_accuracy(loader, model, loss_fn, device=\"cuda\"):\n    num_correct = 0\n    num_pixels = 0\n    dice_score = 0\n    iou_score = 0  # IoU tracking\n    total_loss = 0\n    model.eval()\n\n    with torch.no_grad():\n        for x, y in loader:\n            x = x.to(device)\n            y = y.to(device)\n\n            logits = model(x)  # Raw logits (no sigmoid yet)\n            loss = loss_fn(logits, y)  # Compute loss before thresholding\n            total_loss += loss.item()\n\n            preds = torch.sigmoid(logits)  # Convert logits to probabilities\n            preds_bin = (preds > 0.5).float()  # Thresholding after loss\n\n            num_correct += (preds_bin == y).sum().item()\n            num_pixels += torch.numel(preds_bin)\n            dice_score += (2 * (preds_bin * y).sum()) / ((preds_bin + y).sum() + 1e-8)\n            iou_score += calculate_iou(preds_bin, y)  # Compute IoU\n\n    avg_loss = total_loss / len(loader)  # Compute average validation loss\n    avg_dice = dice_score / len(loader)  # Compute average Dice score\n    avg_iou = iou_score / len(loader)  # Compute average IoU score\n\n    print(f\"Accuracy: {num_correct}/{num_pixels} ({num_correct / num_pixels * 100:.2f}%)\")\n    print(f\"Dice Score: {avg_dice:.4f}\")\n    print(f\"IoU Score: {avg_iou:.4f}\")  # Print IoU score\n\n    model.train()\n    return avg_dice, avg_iou, avg_loss\n\n# function to save predictions as images (Restored Original Version)\ndef save_predictions_as_imgs(loader, model, folder=\"saved_images/\", device=\"cuda\"):\n    os.makedirs(folder, exist_ok=True)\n    model.eval()\n    for idx, (x, y) in enumerate(loader):\n        x = x.to(device=device)\n        with torch.no_grad():\n            preds = torch.sigmoid(model(x))\n            preds = (preds > 0.5).float()\n        torchvision.utils.save_image(preds, f\"{folder}/pred_{idx}.png\")\n        torchvision.utils.save_image(y, f\"{folder}/gt_{idx}.png\")\n    model.train()\n\n# function to train model\ndef train_fn(loader, model, optimizer, loss_fn, scaler, val_loader):\n    loop = tqdm(loader, desc=\"Training\", leave=True)\n    total_loss = 0\n    val_loss = 0  # To store validation loss\n    \n    for batch_idx, (data, targets) in enumerate(loop):\n        data = data.to(device=DEVICE)\n        targets = targets.float().to(device=DEVICE)\n\n        # Forward\n        with torch.amp.autocast('cuda'):\n            predictions = model(data)\n            loss = loss_fn(predictions, targets)\n            total_loss += loss.item()  # Add loss for this batch\n\n        # Backward\n        optimizer.zero_grad()\n        scaler.scale(loss).backward()\n        scaler.step(optimizer)\n        scaler.update()\n\n        # Compute validation loss on one batch for quick monitoring\n        with torch.no_grad():\n            val_data, val_targets = next(iter(val_loader))  # Get a validation batch\n            val_data, val_targets = val_data.to(DEVICE), val_targets.to(DEVICE)\n        \n            val_logits = model(val_data)  # Get raw outputs\n            val_loss = loss_fn(val_logits, val_targets).item()  # Compute loss directly on logits\n        \n            # Convert logits to probabilities AFTER loss calculation\n            val_preds = torch.sigmoid(val_logits)\n            val_preds = (val_preds > 0.5).float()\n\n        # Update tqdm loop to display training and validation loss\n        loop.set_postfix(train_loss=loss.item(), val_loss=val_loss)\n    \n    return total_loss / len(loader)  # return average training loss\n\n\ndef main():\n    print(f\"Device used : {DEVICE}\")\n    model = AttentionUNET(in_channels=1, out_channels=1).to(DEVICE)\n    loss_fn = nn.BCEWithLogitsLoss()\n    optimizer = optim.Adam(model.parameters(), lr=LEARNING_RATE)\n\n    if LOAD_MODEL:\n        load_checkpoint(torch.load(\"my_attention_checkpoint.pth.tar\"), model)\n\n    check_accuracy(val_loader, model,loss_fn, device=DEVICE)\n    scaler = torch.amp.GradScaler('cuda')\n\n    best_dice_score = 0  # Track the best Dice score\n    best_iou_score = 0 # Track the best IoU score\n    best_checkpoint = None  # Store the best checkpoint\n    train_losses = []  # List to store training losses\n    val_losses = []  # List to store validation losses\n    iou_scores = []  # List to store IoU scores\n\n    for epoch in range(NUM_EPOCHS):\n        print(f\"\\nEpoch {epoch + 1}/{NUM_EPOCHS}\")\n        \n        train_loss = train_fn(train_loader, model, optimizer, loss_fn, scaler,val_loader)\n        train_losses.append(train_loss)  # store training loss\n        \n        # validate and get Dice score, IoU, and val loss\n        dice_score, iou_score, val_loss = check_accuracy(val_loader, model, loss_fn, device=DEVICE)\n        val_losses.append(val_loss)  # store validation loss\n        iou_scores.append(iou_score)  # store IoU score\n\n        # Save model if Dice score improves\n        if (dice_score+iou_score)/2 > (best_dice_score+best_iou_score)/2:\n            best_dice_score = dice_score\n            best_iou_score = iou_score\n            best_checkpoint = {\n                \"state_dict\": model.state_dict(),\n                \"optimizer\": optimizer.state_dict(),\n            }\n            save_checkpoint(best_checkpoint)  # Save the best checkpoint\n\n        # if Dice score stops improving, break training\n        elif (dice_score+iou_score)/2 == (best_dice_score+best_iou_score)/2:\n            print(\"Stopping early as average Dice+IoU score did not improve.\")\n            break\n\n        # to save some sample predictions\n        save_predictions_as_imgs(val_loader, model, folder=\"saved_images/\", device=DEVICE)\n\n    print(\"Training Complete. \\nBest Dice Score:\", best_dice_score)\n    print(\"Best IoU Score:\", best_iou_score)\n\n    # to save final best checkpoint after training ends\n    if best_checkpoint:\n        save_checkpoint(best_checkpoint, filename=\"best_attention_model.pth.tar\")\n\n    # to save losses and IoU scores for later use\n    np.save(\"train_losses.npy\", np.array(train_losses))\n    np.save(\"val_losses.npy\", np.array(val_losses))\n    np.save(\"iou_scores.npy\", np.array([score.cpu().item() for score in iou_scores]))# Save IoU scores\n\nif __name__ == \"__main__\":\n    main()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-30T10:42:41.008104Z","iopub.execute_input":"2025-03-30T10:42:41.008402Z","iopub.status.idle":"2025-03-30T13:05:19.508398Z","shell.execute_reply.started":"2025-03-30T10:42:41.008379Z","shell.execute_reply":"2025-03-30T13:05:19.507454Z"}},"outputs":[{"name":"stdout","text":"Device used : cuda\nAccuracy: 29232789/30146560 (96.97%)\nDice Score: 0.0000\nIoU Score: 0.0000\n\nEpoch 1/20\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Training:   0%|          | 0/804 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"1d351c07e9104d1a82be83224bfd27a7"}},"metadata":{}},{"name":"stdout","text":"Accuracy: 29580606/30146560 (98.12%)\nDice Score: 0.6322\nIoU Score: 0.4719\n=> Saving checkpoint\n\nEpoch 2/20\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Training:   0%|          | 0/804 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"7bf478976bd74ed3a1e685fe71421c68"}},"metadata":{}},{"name":"stdout","text":"Accuracy: 29678691/30146560 (98.45%)\nDice Score: 0.7548\nIoU Score: 0.6107\n=> Saving checkpoint\n\nEpoch 3/20\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Training:   0%|          | 0/804 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"7c7481aad0254ea791e1a4e44c1beb0d"}},"metadata":{}},{"name":"stdout","text":"Accuracy: 29735315/30146560 (98.64%)\nDice Score: 0.7734\nIoU Score: 0.6366\n=> Saving checkpoint\n\nEpoch 4/20\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Training:   0%|          | 0/804 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"2150da1edf26437d8418d0e3d1fa7f5c"}},"metadata":{}},{"name":"stdout","text":"Accuracy: 29751748/30146560 (98.69%)\nDice Score: 0.7810\nIoU Score: 0.6471\n=> Saving checkpoint\n\nEpoch 5/20\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Training:   0%|          | 0/804 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"7ba90c2059e94cbf82d895a426a6989c"}},"metadata":{}},{"name":"stdout","text":"Accuracy: 29777255/30146560 (98.77%)\nDice Score: 0.8021\nIoU Score: 0.6742\n=> Saving checkpoint\n\nEpoch 6/20\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Training:   0%|          | 0/804 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"ce0cf59ef6dd44ff9b168f6164c06aa7"}},"metadata":{}},{"name":"stdout","text":"Accuracy: 29785364/30146560 (98.80%)\nDice Score: 0.8166\nIoU Score: 0.6932\n=> Saving checkpoint\n\nEpoch 7/20\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Training:   0%|          | 0/804 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"299fc43b26cd408f8fda55dc5259306a"}},"metadata":{}},{"name":"stdout","text":"Accuracy: 29772727/30146560 (98.76%)\nDice Score: 0.8111\nIoU Score: 0.6859\n\nEpoch 8/20\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Training:   0%|          | 0/804 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"71b0616aaa3841dba253ff8f183b7177"}},"metadata":{}},{"name":"stdout","text":"Accuracy: 29771415/30146560 (98.76%)\nDice Score: 0.8085\nIoU Score: 0.6824\n\nEpoch 9/20\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Training:   0%|          | 0/804 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"d26bb7c15eb54282aacb2c0e8f15e88c"}},"metadata":{}},{"name":"stdout","text":"Accuracy: 29805450/30146560 (98.87%)\nDice Score: 0.8283\nIoU Score: 0.7109\n=> Saving checkpoint\n\nEpoch 10/20\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Training:   0%|          | 0/804 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"a524a17f27724bc6b056b8b61736eb59"}},"metadata":{}},{"name":"stdout","text":"Accuracy: 29788089/30146560 (98.81%)\nDice Score: 0.8109\nIoU Score: 0.6845\n\nEpoch 11/20\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Training:   0%|          | 0/804 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"f660b78129cf4b6d942648b4f20e8457"}},"metadata":{}},{"name":"stdout","text":"Accuracy: 29800722/30146560 (98.85%)\nDice Score: 0.8233\nIoU Score: 0.7041\n\nEpoch 12/20\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Training:   0%|          | 0/804 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"8067e1d533f844e39606c6571f7e96fc"}},"metadata":{}},{"name":"stdout","text":"Accuracy: 29798476/30146560 (98.85%)\nDice Score: 0.8248\nIoU Score: 0.7057\n\nEpoch 13/20\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Training:   0%|          | 0/804 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"db3988b0c19c43efb16e3942355dcfeb"}},"metadata":{}},{"name":"stdout","text":"Accuracy: 29799177/30146560 (98.85%)\nDice Score: 0.8238\nIoU Score: 0.7045\n\nEpoch 14/20\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Training:   0%|          | 0/804 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"e5d13827e01a465f85076fb322fdf56a"}},"metadata":{}},{"name":"stdout","text":"Accuracy: 29794647/30146560 (98.83%)\nDice Score: 0.8250\nIoU Score: 0.7058\n\nEpoch 15/20\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Training:   0%|          | 0/804 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"804d7ddc30ee4403be1f86d5a59c2c6c"}},"metadata":{}},{"name":"stdout","text":"Accuracy: 29814130/30146560 (98.90%)\nDice Score: 0.8328\nIoU Score: 0.7159\n=> Saving checkpoint\n\nEpoch 16/20\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Training:   0%|          | 0/804 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"d9ac635a7eee4fb8a37089f76a71912c"}},"metadata":{}},{"name":"stdout","text":"Accuracy: 29812823/30146560 (98.89%)\nDice Score: 0.8332\nIoU Score: 0.7177\n=> Saving checkpoint\n\nEpoch 17/20\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Training:   0%|          | 0/804 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"8b1c939059f54d819c86ca6c5d2420b2"}},"metadata":{}},{"name":"stdout","text":"Accuracy: 29810188/30146560 (98.88%)\nDice Score: 0.8306\nIoU Score: 0.7133\n\nEpoch 18/20\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Training:   0%|          | 0/804 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"9eef14d83366418587953fb32052758c"}},"metadata":{}},{"name":"stdout","text":"Accuracy: 29815457/30146560 (98.90%)\nDice Score: 0.8420\nIoU Score: 0.7297\n=> Saving checkpoint\n\nEpoch 19/20\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Training:   0%|          | 0/804 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"17bdfbd729de49939408ad4e86e84869"}},"metadata":{}},{"name":"stdout","text":"Accuracy: 29800722/30146560 (98.85%)\nDice Score: 0.8252\nIoU Score: 0.7062\n\nEpoch 20/20\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Training:   0%|          | 0/804 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"0c2469976e3d4aa2b9b3a7fc601b0308"}},"metadata":{}},{"name":"stdout","text":"Accuracy: 29808780/30146560 (98.88%)\nDice Score: 0.8332\nIoU Score: 0.7171\nTraining Complete. \nBest Dice Score: tensor(0.8420, device='cuda:0')\nBest IoU Score: tensor(0.7297, device='cuda:0')\n=> Saving checkpoint\n","output_type":"stream"}],"execution_count":30},{"cell_type":"markdown","source":"### Graphs","metadata":{}},{"cell_type":"code","source":"train_losses = np.load(\"train_losses.npy\")\nval_losses = np.load(\"val_losses.npy\")\niou_scores = np.load(\"iou_scores.npy\")\n\nprint(f\"Train Losses : {np.array(train_losses)}\")\nprint(f\"Validation Losses : {np.array(val_losses)}\")\nprint(f\"Train Losses : {np.array(iou_scores)}\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-30T13:44:32.275726Z","iopub.execute_input":"2025-03-30T13:44:32.276092Z","iopub.status.idle":"2025-03-30T13:44:32.283564Z","shell.execute_reply.started":"2025-03-30T13:44:32.276065Z","shell.execute_reply":"2025-03-30T13:44:32.282867Z"}},"outputs":[{"name":"stdout","text":"Train Losses : [0.29439181 0.13851315 0.07882122 0.05222124 0.03914297 0.03161604\n 0.02660512 0.02347179 0.0192256  0.01943492 0.01847355 0.01739236\n 0.01762157 0.01576635 0.01539082 0.01485899 0.01454    0.01458085\n 0.0136678  0.0137299 ]\nValidation Losses : [0.18871058 0.10077019 0.06206867 0.04718326 0.03634143 0.03136616\n 0.03073411 0.03150512 0.02650444 0.02937338 0.02746068 0.02750215\n 0.02791927 0.02665629 0.02655249 0.0265265  0.0280345  0.02601606\n 0.02862861 0.02853104]\nTrain Losses : [0.47190723 0.61067069 0.63660771 0.64713681 0.67420888 0.69319999\n 0.68591678 0.68243021 0.710895   0.6844539  0.70405847 0.7056849\n 0.70450044 0.70575321 0.7158969  0.71770269 0.71329182 0.7296949\n 0.70624506 0.71707368]\n","output_type":"stream"}],"execution_count":132},{"cell_type":"code","source":"train_losses = np.load(\"train_losses.npy\")\nval_losses = np.load(\"val_losses.npy\")\niou_scores = np.load(\"iou_scores.npy\")\n\nplt.figure(figsize=(10,5))\n\n# training & validation loss\nplt.subplot(1,2,1)\nplt.plot(train_losses, label=\"Training Loss\", color='blue')\nplt.plot(val_losses, label=\"Validation Loss\", color='red')\nplt.xlabel(\"Epochs\")\nplt.ylabel(\"Loss\")\nplt.legend()\nplt.title(\"Training vs Validation Loss\")\n\n# IoU scores\nplt.subplot(1,2,2)\nplt.plot(iou_scores, label=\"IoU Score\", color='green')\nplt.xlabel(\"Epochs\")\nplt.ylabel(\"IoU Score\")\nplt.legend()\nplt.title(\"IoU Score Over Epochs\")\n\nplt.show()\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-30T13:07:27.861425Z","iopub.execute_input":"2025-03-30T13:07:27.861718Z","iopub.status.idle":"2025-03-30T13:07:28.170519Z","shell.execute_reply.started":"2025-03-30T13:07:27.861696Z","shell.execute_reply":"2025-03-30T13:07:28.169670Z"}},"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1000x500 with 2 Axes>","image/png":"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\n"},"metadata":{}}],"execution_count":34},{"cell_type":"markdown","source":"# Training prediction batch-wise visualization","metadata":{}},{"cell_type":"code","source":"saved_images_path = \"saved_images/\"\n\nsaved_images = sorted(os.listdir(saved_images_path))\n\nfig, axes = plt.subplots(10, 2, figsize=(20, 20))\n\nfor i in range(10):\n    pred_path = os.path.join(saved_images_path, f\"pred_{i+10}.png\")\n    pred_mask_path = os.path.join(saved_images_path, f\"gt_{i+10}.png\")  # Ground truth mask\n\n    pred_img = cv2.imread(pred_path, cv2.IMREAD_GRAYSCALE)\n    mask_img = cv2.imread(pred_mask_path, cv2.IMREAD_GRAYSCALE)\n\n    if pred_img is None:\n        print(f\"Warning: {pred_path} not found!\")\n        continue\n    if mask_img is None:\n        print(f\"Warning: {pred_mask_path} not found!\")\n        continue\n\n    axes[i, 0].imshow(mask_img, cmap=\"gray\")\n    axes[i, 0].set_title(f\"Ground Truth {i+10}\")\n    axes[i, 0].axis(\"off\")\n    \n    axes[i, 1].imshow(pred_img, cmap=\"gray\")\n    axes[i, 1].set_title(f\"Prediction {i+10}\")\n    axes[i, 1].axis(\"off\")\n\nplt.tight_layout()\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-30T13:09:10.210147Z","iopub.execute_input":"2025-03-30T13:09:10.210428Z","iopub.status.idle":"2025-03-30T13:09:12.948695Z","shell.execute_reply.started":"2025-03-30T13:09:10.210408Z","shell.execute_reply":"2025-03-30T13:09:12.947828Z"}},"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 2000x2000 with 20 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q1fz96iENwDezdPvQd7crFarsWXLFpd/T3v16uXx10aj0YrWunfvbuTk5BT6u/39998bQUFBHo+RVjqb2Ww2HnjgAePQoUOGzWZz+d+ef8rJyTF+/PFHo0mTJh5/7bTLN0exZkMp0LRpU1mtVrf03bNnT0nSxIkTFR8fr9zcXLdcB4DrmM1mRUREXHJ/bm4uQ2dRZJGRkZowYYLq169frNc1vOipeT8/P8XExMhms+no0aMF9ptMJvn4+DAdGgBAklS5cmVVq1bN02EAKEHKly9/ySlrKleu7FWfreFacXFxmjhxosLDw4vlej4+PurQoYOuvfZadevWTfHx8cVyXbhP0ce7oNhYrVa3DVsOCAjQAw88oP/973+aNGmSGjduXOTpMAAUj9zcXO3fv7/QfdnZ2Zo+fTpDEFFkcXFxql27drFf9/fffy/zC8xHRUVp2LBhWrx4sdavX69XXnmlwNBjPz8/Pf300/r+++/VokULD0UKAChJAgMDFRwc7NI+T506pY0bN7q0TwDFJzU1tdAHzOx2u+bOnav09HQPRIWyoHnz5sVWaPi7KlWq6Nlnn+WeZBlAsaEU+OWXX9y+YEpUVJQGDx6spUuXauzYsapevTrzshYiMjJSt99+u2rVqnXJpwgAd7Pb7Zo2bZpWrVqVbzSSzWbTokWL9OWXX3owOpR2ISEhxf7+ZhiGdu3aVWafwDKbzWrfvr0WL16siRMnqm3btqpYsaLi4uLyjVKyWq0aPny4Xn/9dd1+++3q06ePU/OgAgDKhjNnzighIcFl/eXk5GjixIk6fPiwy/r0FjVq1NCQIUM0atQo3XLLLfL19fV0SPBSS5cu1bp16/JtMwxDX3/9tSZNmuShqFAWeHKWhDZt2nik0AEXc3S+JZWAuaG8tYWGhhq//fbb1U57VmR2u93Yu3evMXjwYOZ9///N39/feOihh4z4+HgjMzPTOHr0qDFz5kyjTZs2hsVi8Xh8NO9sERERRp8+fYyZM2caX3/9tfH4448b5cqV83hctNLdGjVqZCQnJxfb3xzD+Guezu7du3v8tburRUREGDt27CjwutPT04177rnH8PPzM6KiooxHH33USE1Nzdu/e/duIzo62uPxX2wAvJun34O8uVksFuN///ufS76POTk5xqhRowxfX1+Pv67S1Mxms9G3b1/jjz/+yFvHKisry3j99dcNq9Xq8fho3tmqVKlijBs3zli0aJGxcOFC44knniAfpDndWrRo4bZ1Y6/k6NGjRmRkpMf/D2iFN0dRbCgl7Y477jASExOL9MtaVDk5OcbYsWMNs9ns8dfvyWYymYznn3/eyMjIKPB/dO7cOWPAgAEej5Hm3c1sNnv97ynNdS08PLzQG+PulJqaajRu3Njjr91dzcfHx1iwYEGhrz0lJcX48ccfjR07dhjZ2dl525OTk40xY8aUqKI/AO/m6fcgb2/dunVz+uZPYmKi0b9/fwoNRWht2rTJ90DARdnZ2eSDNBqtTLXIyEjjwIEDTv29Kaqvv/7aMJlMHv8/oBXeHMXY/FJi4cKFGjp0qBITE4vtmj4+Prr33nsVExNTbNcsicxms2666Sb5+/sX2BceHq6mTZsy5RQ8ym63syA0XCY1NVW7du0q1mueOXNGJ0+eLNZrFqfc3Fx9+umnhU6JGBoamrcgWlZWlvbv368ffvhBffv21UsvvaTU1FQPRAwAKGn+97//afbs2UWecnDbtm3q27evZsyYUebXSHKHO++8s9B1M6xWq6655hoPRAQA7nHu3DktX77cI9desmRJmZ1a15sw6XwpYbfb9d133yk7O1vPPvusKleurPDwcAUFBV1y8RSTyeT0XM9VqlRRu3bt9PnnnzvVT1l17NgxffPNN7wZAigzbDabduzYoXvvvbfYrpmRkVHmb3z8+OOP+vXXX9WuXbu8bYZh6OzZs9q6davmz5+vX3/9VUeOHNH58+fL/P8HAODq5OTk6JlnntGuXbvUu3dv1alTRwEBATKZTAXWDcjNzZXNZtOff/6pEydOaOHChZo9e7ZOnTrloehLvwoVKlxyX2RkpEwmEzkhgDLBMAz9+uuvGjx4cLE+WLtv3z799NNPxXY9uA/FhlLEbrfrhx9+0LJlyxQSEqKoqChVqVJFISEhhR5fsWJFtWvXTi1atFCVKlWKVHiwWCzq16+f5s2bp/T0dGdfQplTsWJF3XbbbVq7dq1sNpunwwEAl9iwYYOys7OLbdHDQ4cOlfkn+LOzs3XmzBlJf32AP3LkiD7++GN99913OnTokLKysjwcIQCgpEtKStK4ceP0wQcfqFq1avL395efn59atWqV72/2jh07dPToUR07dkwXLlxQTk6OB6MuG44dO3bJfY0aNZLFYlFubm4xRgQA7rNixQolJCSoYsWKxXK9rKwsjRw5Un/++WexXA/uRbGhlDEMQ5mZmcrMzFRiYqL27Nlz2eM/+eQTValSRd9++62aNm1apGvWqVNHISEhXl1suNQTpj4+Purfv78++uijMj0FCADv8vvvv+vUqVOqVq2a26+VnJys5cuXe8VUYKdOndLKlSu1atUqzZw5U3/88QdPQQIArlp2drYOHDiQ9/XmzZs9GI13OHv27CX3ValSRdHR0eSDAMqMP//8U6NHj9bEiROdnjHlSjIzMzVx4kR9//33br0Oig/FhjIuNzdXR44c0Y8//ljkYsOOHTuUnJzs2sBKEZvNpu+//17dunWT1WotsD8sLExhYWF8uARQZpw4cUJPPvmkJk6cqEqVKrmsX7vdrvT0dCUlJSkhIUGnT5/Whx9+qJ9++qnM33S32+168cUXlZOTwxRJAACUMrt375ZhGIVOKWI2m91+Mw4AipNhGJo9e7YGDx6sRo0aubz/rKwsJSQk6JdfftH06dO1du1aRuGVIRQbvIBhGPryyy81ePBgRUZGXvX5K1eu9PrpHb7//nsNHz5cLVq0KLAvKSlJ586d80BUAOAedrtd3377rWw2mz7++GNFR0dfdR+GYSgjI0PHjh3T7t27tWPHDu3YsUMHDx7U8ePHlZaWpqysLK+acuDChQueDgEAABTB6tWrtW/fPsXGxhbYd+zYMSUkJHggKgBXIyAgQLfddpuqVKmiY8eOaf369UpKSvJ0WCVWcnKyXnnlFX322WcKDw+/6vMNw5Ddbte5c+eUkpKikydPaseOHVq9erWOHDmi3bt3KyUlpcw/dOaNKDZ4id27d2vQoEGKi4tT8+bNVbNmTUVHR8vf3/+yC74kJCRo1apVxRhpyXTu3DlNmzZNNWrUULly5fK22+12LV++PG8ebgAlV61atdSpUyeFhoZK+mtKm2+//VYpKSkejqxkMgxD33//vbKysjRp0iTVrFnziudkZGRo3759Wr9+vTZv3qwdO3bojz/+0Llz57yqqAAAAMqWM2fO6MUXX9S4ceNUtWrVfDn0vn37vGI6SKA0CwoK0oQJE9SvXz9ZrVbl5uZq+/btuvfee/NNS4f8FixYoMGDB+vjjz92qOCQnZ2tP/74Qxs3btT69eu1fft2nTx5UgkJCcrNzfX6B5m9hclwsIRUnCuQF4XJZJLJZJJhGFTFLsNkMsnPz0+RkZGqW7euGjVqpBtvvFF16tRRdHS0AgMDFRISoqysLC1atEjvv/++tmzZwocn/bVYdsuWLTVw4EBVrVpV4eHhWrFihd577z2eZAFKuGuuuUZfffWVrrvuurxh7rm5uVqyZIkeeOABCg6XYTKZ1LhxY/Xt21cdOnRQnTp1FBAQIMMwlJOTo/T0dJ06dUrLly/XggULtGXLFqWkpPB3owzi8xXg3Up6PggUh8qVK2vgwIFq3769JCktLU1PPPHEFddSBOBZ//nPf/TGG28UmPIsPj5ed955pw4fPuyZwEoBk8mknj17asyYMapevbp8fPI/t26z2XT8+HF99dVX+v7777Vt2zalp6eTD5ZBjuaDpb7YEB0drT59+qh69eoqX768Lly4oE2bNmnTpk3av38/UxY4wGw2y8/PT8HBwfLz81O5cuWUnZ2t/fv3M2daIUwmk3x8fOTj46OsrCzeQIESzmQyady4cXriiScK7Dt//rxuvvlm7dy50wORlS4mk0lhYWG69tpr1aJFC6Wnp2v//v06deqUTp8+TYHBC1BsALxbSc0Hy5Urp969e6thw4aKj4/Xpk2btHv3bqWnp3s6NJRhFotF0v9NEwKg5AoMDNTatWvVpEmTQvcPGzZMH330UfEGVQqVK1dON954o1q2bKnmzZtLknbu3Kn169dr3bp1PITrBbyi2NC8eXO99dZbatu2bb7qpN1uV1pamj766CM9//zz/PEHAC9mtVq1cOFCdezYscC+3Nxc9erVS/Pnzy/+wIBShmID4N1KWj4YFBSkAQMGaPjw4apXr15efBkZGdq9e7e+/PJLTZw4kYenAMDLRUdHa/PmzapatWqh+7/55hv16tWrmKMCSh9H80HzlQ8peUwmk7p3765vv/1W7dq1KzAMymw2KzQ0VD179lSFChU8FCUAoCSw2Ww6ceJEoftyc3OVlpZWzBEBAABnmEwmvfDCC3r//fcVGxubrxASEBCg5s2ba8yYMerZs6cHowQAlARnzpzRihUrCt1nGIbWrVtXzBEBZVupLDb4+PioWbNmioyMvOxxkZGRuu6664opKgBASWS32zV//vxCF6Pau3evNm/e7IGoAABAUfn5+alDhw4FHjr7O4vFIn9//2KMCgBQEhmGoRdffFFff/21bDZb3vbc3FytXr1as2bN8mB0QNlTKosNOTk5euONNzRw4EDt3r1bSUlJSk1NVXZ2tjIzM3XgwAGNHTtWt99+u3755RdPhwsA8LAVK1Zo2bJl+balp6dr5syZSk5O9kxQAACgSDIzMzV58mRlZ2cXut9ut2v69On6+uuvizkyAEBJdPToUQ0cOFBPPfWU1q1bp2XLlumBBx5Qly5dlJiY6OnwgDKlVK/ZIEkVKlRQ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P+6oAwB4zOeff66ZM2fm6PcdPXpU//3vf9W7d2/t2bPHi9kVH2+88Yb+/PPPXJ8QSUlJ0auvvqquXbtqw4YNXsiu6EhOTta6devctv3Nmze79eY2AABcxWKcnOHJ05MRValSRffcc48qVKigXbt2af78+dq/fz9zNLiBxWJReHi4QkJCVL58eWVlZenYsWM6c+YMP+8r0LNnT3311VcKCAhw2z6Sk5N1ww03aNmyZW7bh7sFBQWpcePGCg4OliSlp6frjz/+UGJiopczA0oef39/VahQQdHR0QoJCVGVKlUUHR2t0qVLq1q1aoqIiFCZMmWy/y4cOnRIsbGxWrhwoVs71CicmBQUKNm8MTmtv7+/+vbtmz2nwJo1a7Rr1y6P51HclS5dWldddZVat26d/ST1n3/+qUWLFmn9+vXc6Oeknj17auHChfLz83PpdpOTk9W9e3etXbvWpdsFgH/y8/NTaGiogoKCVL16de3cuVPGGKWlpfFkFSQ53x8stMUGoKgJCgrSZ599phtvvNGt+/n000915513FslCkJ+fn9566y0NGzYs+wkNu92uzZs3a+zYsdqyZYt3EwRKAB8fH9WsWVPXXXedrr/+ejVv3lxhYWGyWq1Ozwvz448/6oYbblB6erqbs0VhQrEBKNnoDwKX5u/vr/fff1+33HKLSz8v8+fP19ChQ4tN0ad8+fKaOHGiqlatmr0sMzNTn3zyiZYsWeLFzFDc/ftzWVKvbf39/VWnTh01atRINWvWVKNGjSRJkZGRqlevnmw2m0JDQ3Xu3DlJ0smTJ7V3717FxcXp7bff1h9//OHN9OFFzn5mmG0WcJGUlBRNnjxZjRs3Vq1atdy2nyZNmigwMLBIPkZrsVhUu3ZthYSEZC/z9fXVVVddperVq1NsyAeLxaKAgADZ7XZlZGR4Ox0UYlarVbVr19aDDz6oPn36KCoqKt/DIqWnpzOkEgAAwD+kp6dr0qRJatasWfaXdwV1YSir4lJokKQ77rhDDzzwwEXLbTYbxQa4jMViUXBwsKpVq6a2bduqTJky6tixY44+zMaNG/XUU08pLS3Ni5l6TkBAgAYOHKhbbrlFbdu2zfG9TG7KlSuX/d8mTZpIkrp3767evXtrx44dbs8XRRfFBsCFdu/erQcffFAzZ85UaGioW/ZRoUIFlS5dukgWGxwOR64Tp61YsUIrVqzwfEJFjI+PjypXrqzw8HBZrVbVqVNHrVu3VqtWrZSSkqJly5Zp5syZOnLkiLdTRSFisVhUtmxZjRkzRrfffruqVKlSoO2dPXtWL774olJTU12UIQAAQPFw6tQp3XTTTfrhhx9UuXLlAm9v8eLFWr9+vQsyKzwufIH5T3a7XRs3bvRCNkVHhQoVNHDgQGVkZOjXX3/Vvn37ZLfbFRQUpOjoaElSfHy8Dh8+XGLv2Jf+HnGiadOmGjVqlFq2bKmaNWsqMDAw17adOnXStm3b9Pnnn3s4S8+rVKmS3nvvPfXo0cPpp9lzEx0drQEDBlBswKUZJ0kiCMKJ8PX1NaNGjTI7duwwWVlZzn7EnHb48GFTvnx5rx/nlYbFYjEtW7Y0f/31V47j2b17t2nevLnX8yvsUa1aNfPee++ZI0eOmKSkJJOUlGQyMzNz/CztdrvZtm2bGT58uAkMDPR6zoT3w2q1miFDhpidO3e67Hy0detWExYW5vVjIzwfAEo2b5+DCKIoxfDhw01iYmKBPnNZWVlm+PDhXj8WV0ZgYKDZuHFjjuPMzMw0X375pQkNDfV6foU1AgICzJIlS4zD4TAOh8OkpKSYnTt3mm3btpl9+/aZ9PR0k5GRYU6dOmVeeuklc80115igoCCv5+3JCA0NNddff71ZsWKFSUtLc/pz9uSTT3o9d3dHxYoVzYoVKwp0Pvqn3bt383ktoeEsig0E4YawWCymfPny5p577jHLly83f/75pzl58qRJSUkxDocjXyf0C3766Sfj7+/v9WO80qhdu7bZu3dvjmM5dOiQadWqlddzKwpx5513Grvd7tR7JDU11cyZM8dUqFDB63kT3o3u3bub2NjYAp1z/i0lJcVcc801Xj82wvMBoGTz9jmIIIpSWCwW06VLF/Pee++Zb775xvz+++/m999/N9988012bNmyJdebQRwOhzl16pR55ZVXit0Xxm3atDEpKSnZx3r8+HEzatSoItm/9WRUqlTJnD171unzdWZmpnn55ZeNxWLxeu7ujqioKDNhwgSzbds2k5GRcUV/17Kyssy4ceO8fgzujMjISLN8+fIr+rlcTlJSkmnatKnXj43wfDiLYgNBuDn8/f1NRESEqVq1qmnXrp0ZM2aM+eyzz8wff/xhEhMTr6j4kJaWZm688UavH1N+4vrrr89xJ/62bdtMly5dSsQFkCuiY8eOJj4+3un3SmxsrKlRo4bX8ya8Fw0aNDD79u1z+j1zJV577TVjtVq9foyEZwNAyebtcxBBFOUIDg42wcHBOZaVKlXKjBgxwmzcuDHHF/Dx8fGmQ4cOxa6fVK5cueynGux2u1m4cKGpU6eO1/MqCmGz2czixYuv6Jx98uRJU7FiRa/n7q4ICAgwI0eONHv27Mn3DZ0bN24s1k9sh4WFmc8++6zAN7zmpl+/fl4/PsLz4SyKDQThhbBaraZUqVKmZcuW5sEHHzTffPONOXDggElMTLxoaJwL0tLSzBdffGFCQkK8nn9+on///iYrK8tkZGSYH374wdStW9frORWlsNlspm/fvmbGjBlm7969l33K4a+//jLlypXzet6EdyIkJMT8+OOPTl8MXKktW7aY0qVLe/04Cc8GgJLN2+cggiiuERQUZFq1amWmTJli3n77bTNkyJBiV2iQZEaPHp19Pvn4448Z9vUKIyYmxjz//PNmy5Yt5vjx45c9Z6ekpJiWLVt6PW93REhIiPnkk0+u+EmGfzpy5Ijp0KGD14/FXeHn52fefPNNtwztbYwxX375pbHZbF4/TsKz4SyLMc7NHGOxWJxpBiAffH19FR4erooVK6p69epq2LCh6tatq6pVqyopKUlnz57VV199paVLlyopKcnb6eZL/fr1NXnyZC1fvlxffPGFEhMTvZ1SkeTj46Ny5crpqaee0q233iqbzZbj/GyMUWJioqZNm6YXXnhBWVlZXswW3lKpUiVt2rQp1wn4XGH69OkaO3ZsrhO+o/hy8pIRQDFFfxBAQcTExOi2225TXFycZs2apdOnT3s7pSIpMDBQ5cqV06xZs9S2bds82/3+++/q0KGDzp8/78Hs3C8oKEhvvfWWbrvtNlmt1nxt4/jx47rpppu0cuVKF2dXeDzyyCOaMmWKfH193bL9vXv3qmnTpkpJSXHL9lE4OdsfpNgAFFJWq1V+fn7KysqSw+EoFl/qWa3WYnEchUFYWJi6dOmimJgY1axZUz4+PjLGaPv27Vq1apW2bdumzMxMb6cJLwkICNDq1avVokULl287PT1dgwcP1tdff+3ybaNwo9gAlGz0BwGg8KhSpYoefvhhNWrUSNLfNzDWq1dPPj4+OnTokCZMmKClS5d6OUvXslqtuuuuu/Tmm2/KZrPlaxslodDQqlUrff/99ypTpozb9kGxoWRytj+Yv08nALdzOBxKS0vzdhouRaHBdRISEjR//nxJuujJBsButyshIcHl2z1y5IimTp2qJUuWuHzbAAAAAJxz5MgRjRs3Lrsv6OPjo4oVK8pisSg+Pl7x8fHeTdANqlWrpmeffTbfhYbk5GQ99NBDxbrQIEm9evVya6FBkrZs2aL09HS37gNFF8UGACjiKDDg3zIzM/W///1PMTExqlq1ar63k5WVpXPnzungwYPasGGDPvjgA23bto33HAAAAOBl5u95WCX9fWPf4cOHvZyRe5UqVUqBgYH5WvfgwYMaPXq0fv75ZxdnVfjMmTNH48aNc3nBITExUefOndOCBQv06quvym63u3T7KD4YRgkAgGLIarWqRo0aevDBBzVo0CBFREQ4vW5cXJx+/vlnzZ49W1u3btXJkyeVmppKkaGE4/cPlGz0BwEA3hQUFKQlS5Zccq6K3KxatUq33nprsS/GXGCxWHTjjTfq2WefVe3atfO1DYfDoZSUFJ08eVK///67Fi5cqK1bt+rYsWNKTEykX1BCMWcDAACQzWZT27ZtNWLECDVr1kw1a9ZUcHBw9oRqxhhlZmbq/PnzOnHihL777jvNnTtXf/zxB/N+IAc6FUDJRn8QAOBt119/vWbOnKmQkBCn2p88eVK9e/fW77//7ubMCp/o6Gg9//zzGjRokHx8fC7b/kKBYdmyZZo+fbqOHDmigwcPKi0tjacYIIliAwAA+Aer1aqQkBDVqFFDzZo1U8uWLeXj46M///xTu3fv1qFDh3Tq1CnFx8fzpTJyxfsCKNnoDwIAvM1qtapXr14aMmSIOnXqpMqVK+faLj09XcuXL9czzzyjNWvWeDjLwiMkJET9+/fXfffdp6ZNm15UdHA4HPr999/1448/at++fVq/fr3279/PTWfIFcUGAACQpwt/1/kC2XuCg4PVrFmz7PFUExIStGnTJiUlJXk5s9zxXgFKNvqDAIDCwmKxqEqVKho1apRuvfVWlS1bVgEBAXI4HNq1a5cef/xxffvtt0xi/P+Fhoaqf//+GjRokJo2baqgoCDt3btXK1eu1FNPPaXz5897O8USyWazqWnTpmrZsqWaNGmilStXavPmzdqzZ0+h7HtRbAAAACikmjZtqmnTpqlt27by9/eX9PfE3mvXrtXkyZO1bt06L2d4scJ4wQvAc+gPAgAKozJlyqhOnTqqXLmy0tPT9csvvyguLs7baRVKFotFZcqUkc1mU3x8vNLS0rydUolVpUoVvfrqq+rVq1eOic/Pnj2riRMn6tNPPy10/S+KDQAAAIVQTEyMvv32W9WpUyfX13fv3q2uXbvqyJEjHs7s0grbxS4Az6I/CAAAUHBlypTRwoULdc011+T6enJysrp06aL169d7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\n"},"metadata":{}}],"execution_count":37},{"cell_type":"markdown","source":"# Predict any image from test dataset","metadata":{}},{"cell_type":"code","source":"# Load trained model\nDEVICE = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n\n# Initialize UNET model (Ensure UNET class is defined/imported before this)\nmodel = AttentionUNET(in_channels=1, out_channels=1).to(DEVICE)\n\n# Load the checkpoint from Kaggle dataset\ncheckpoint_path = \"/kaggle/input/attentionunet-dummy/pytorch/default/1/best_attention_model.pth.tar\" #when using downloaded\ncheckpoint = torch.load(checkpoint_path, map_location=DEVICE, weights_only=True)\n\n# Load model state\nmodel.load_state_dict(checkpoint[\"state_dict\"])\nmodel.eval()\n\n# Define Preprocessing Transform\nval_test_transform = transforms.Compose([\n    transforms.Resize((256,256)),\n    transforms.ToTensor()\n])\n\ndef predict_single_image(img_path, mask_path, model):\n    \"\"\"\n    Given an image path, this function returns the original image, \n    predicted mask, and ground truth mask.\n    \"\"\"\n    # load original image & mask\n    image = Image.open(img_path).convert(\"L\")  # Convert to grayscale\n    mask = Image.open(mask_path).convert(\"L\")  # Convert to grayscale\n    \n    # transform image\n    input_tensor = val_test_transform(image).unsqueeze(0).to(DEVICE)  # Add batch dimension\n\n    # model prediction\n    with torch.no_grad():\n        pred_mask = torch.sigmoid(model(input_tensor))\n        pred_mask = (pred_mask > 0.5).float()\n\n    # convert Tensors to Numpy\n    original_np = np.array(image.resize((256,256)))\n    pred_mask_np = pred_mask.cpu().squeeze().numpy()\n    inv_pred_mask_np = (pred_mask_np > 0.5)\n    inv_pred_mask_np = np.where(pred_mask_np == 1, 0, 255)\n    mask_np = val_test_transform(mask).cpu().squeeze().numpy()\n\n    # create Cropped Tumor Image (White background, only tumor visible)\n    tumor_only = np.where(pred_mask_np == 1,original_np,255)\n\n    # IoU (Intersection over Union) Calculation\n    intersection = np.logical_and(pred_mask_np, mask_np).sum()\n    union = np.logical_or(pred_mask_np, mask_np).sum()\n    iou_score = intersection / (union + 1e-7)  # Add small value to avoid division by zero\n\n    # Dice Score Calculation\n    dice_score = (2 * intersection) / (pred_mask_np.sum() + mask_np.sum() + 1e-7)  # Avoid division by zero\n\n    print(f\"IoU Score: {iou_score:.4f}\")\n    print(f\"Dice Score: {dice_score:.4f}\")\n    \n    fig, axes = plt.subplots(1, 4, figsize=(15, 4))\n    titles = [\"Original Image\", \"Ground Truth Mask\", \"Predicted Mask\",\"Tumor Cropped\"]\n    images = [original_np, mask_np, inv_pred_mask_np, tumor_only]\n\n    for i, ax in enumerate(axes):\n        ax.imshow(images[i], cmap=\"gray\")\n        ax.set_title(titles[i])\n        ax.axis(\"off\")\n\n    plt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-30T19:37:54.838233Z","iopub.execute_input":"2025-03-30T19:37:54.838626Z","iopub.status.idle":"2025-03-30T19:37:55.055431Z","shell.execute_reply.started":"2025-03-30T19:37:54.838596Z","shell.execute_reply":"2025-03-30T19:37:55.054380Z"}},"outputs":[],"execution_count":79},{"cell_type":"code","source":"# -----------------------\n# Test on a sample image\n# -----------------------\n\n# choose a random test image and mask\nrand_idx = random.randint(0, len(test_imgs) - 1)\nimg_name = test_imgs[rand_idx]\nmask_name = test_masks[rand_idx]\n\nimg_path_test = os.path.join(image_path, img_name)\nmask_path_test = os.path.join(mask_path, mask_name)\n\nprint(f\"Testing on random image: {img_name}\")\nprint(\"Image path : \", img_path_test)\nprint(\"Mask path : \", mask_path_test)\n\npredict_single_image(img_path_test, mask_path_test, model)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-30T19:37:58.420543Z","iopub.execute_input":"2025-03-30T19:37:58.420945Z","iopub.status.idle":"2025-03-30T19:37:59.109567Z","shell.execute_reply.started":"2025-03-30T19:37:58.420911Z","shell.execute_reply":"2025-03-30T19:37:59.108254Z"}},"outputs":[{"name":"stdout","text":"Testing on random image: 556.png\nImage path :  /kaggle/working/cropped_images/images/556.png\nMask path :  /kaggle/working/cropped_images/masks/556.png\nIoU Score: 0.7645\nDice Score: 0.9047\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"<Figure size 1500x400 with 4 Axes>","image/png":"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\n"},"metadata":{}}],"execution_count":80},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null}]}
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