{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.11.11","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"nvidiaTeslaT4","dataSources":[{"sourceId":21755,"databundleVersionId":1475600,"sourceType":"competition"}],"dockerImageVersionId":31011,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":true}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":" # <center><b>Claude Monet Paintings and Generative Deep Learning</b></center>","metadata":{}},{"cell_type":"markdown","source":"# INTRODUCTION\nThe aim of this work is to build and train a generative adversarial network (GAN) using the Monet Paintings dataset available at Kaggle. GANs consists of two or more neural networks. There is a generator network that creates images and a discriminator network to train the generator. The discriminator classifies the images as real or fake. These are called adversarial networks because they are competing. The generator is working to maximize the chances that a mistake is made by the discriminator, and the discriminator is trying to minimize the chances of making a mistake. The task is to generate 7,000 to 10,000 images that are in the style of Monet’s paintings and fool the discriminator. \n\n**Citation:**\n\nAmy Jang, Ana Sofia Uzsoy, Phil Culliton. (2020). I’m Something of a Painter Myself. Kaggle. https://kaggle.com/competitions/gan-getting-started\n\n**GitHub Repository:**\n\n","metadata":{}},{"cell_type":"markdown","source":"# LIBRARIES","metadata":{}},{"cell_type":"code","source":"import os\nimport random\nimport shutil\nimport numpy as np\nimport itertools\nimport torch\nfrom torch import nn\nimport torchvision.utils as vutils\nimport torch.nn.functional as F\nimport torch.optim as optim\nfrom torch.autograd import Variable\nfrom torch.nn import BCEWithLogitsLoss\nfrom torch.utils.data import Dataset, DataLoader\nimport torchvision\nfrom torchvision import datasets, transforms\nimport torchvision.models as models\nimport matplotlib.pyplot as plt\nfrom PIL import Image\nfrom typing import Tuple","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-05T21:43:48.344617Z","iopub.execute_input":"2025-05-05T21:43:48.345164Z","iopub.status.idle":"2025-05-05T21:43:48.349899Z","shell.execute_reply.started":"2025-05-05T21:43:48.345138Z","shell.execute_reply":"2025-05-05T21:43:48.349206Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"# IMPORT DATA","metadata":{}},{"cell_type":"code","source":"# Input data files are available in the read-only \"../input/\" directory\n\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    print(os.path.join(dirname))","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true,"execution":{"iopub.status.busy":"2025-05-05T21:43:50.755655Z","iopub.execute_input":"2025-05-05T21:43:50.755923Z","iopub.status.idle":"2025-05-05T21:43:57.793432Z","shell.execute_reply.started":"2025-05-05T21:43:50.755901Z","shell.execute_reply":"2025-05-05T21:43:57.792787Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## Dataset Directories","metadata":{}},{"cell_type":"code","source":"monet_dir = \"/kaggle/input/gan-getting-started/monet_jpg/\"\nphoto_dir = \"/kaggle/input/gan-getting-started/photo_jpg/\"","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-05T21:49:54.407066Z","iopub.execute_input":"2025-05-05T21:49:54.407366Z","iopub.status.idle":"2025-05-05T21:49:54.411354Z","shell.execute_reply.started":"2025-05-05T21:49:54.407345Z","shell.execute_reply":"2025-05-05T21:49:54.410681Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## Make a Subset of Photos\nThere are 7028 phots and 300 images of Monet paintings. To ensure the datasets are balanced and the models can be trained in a timely manner a random subset of 300 photos will be used. ","metadata":{}},{"cell_type":"code","source":"photo_subset_dir = \"/kaggle/working/photo_subset/\"\n\n# Create a directory for the subset \nos.makedirs(photo_subset_dir, exist_ok=True)\nall_photos = os.listdir(photo_dir)\n\n# Randomly select 300 photos\nsubset_photos = random.sample(all_photos, 300)\n\n# Copy selected photos to the subset directory\nfor photo in subset_photos:\n    shutil.copy(os.path.join(photo_dir, photo), photo_subset_dir)\n\nprint(\"Subset of 300 photos created.\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-05T21:49:57.577900Z","iopub.execute_input":"2025-05-05T21:49:57.578456Z","iopub.status.idle":"2025-05-05T21:49:59.188796Z","shell.execute_reply.started":"2025-05-05T21:49:57.578431Z","shell.execute_reply":"2025-05-05T21:49:59.188108Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"# IMAGE PROCESSING","metadata":{}},{"cell_type":"markdown","source":"# Create PyTorch Class for Datasets\nFor loading and processing images from the directory to comply with PyTorch's data loading pipeline.","metadata":{}},{"cell_type":"code","source":"class CustomImageDataset(Dataset):\n    def __init__(self, root: str, class_idx: int, max_size: int = -1, transform=None) -> None:\n        \"\"\"\n        Initialize the dataset.        \n        root: image directory.\n        class_idx: image labels.\n        max_size: maximum number of images to load from the directory.\n        transform: transformations to apply to the images.\n        \"\"\"\n        self.paths = [os.path.join(root, img) for img in os.listdir(root)]\n        random.shuffle(self.paths)\n        self.paths = self.paths[:max_size] if max_size > 0 else self.paths\n        self.transform = transform\n        self.class_idx = class_idx\n\n    def load_image(self, index: int) -> Image.Image:\n        \"\"\"\n        Load an image from the dataset at the specified index.\n        return: PIL Image\n        \"\"\"\n        try:\n            image = Image.open(self.paths[index])\n            return image\n        except Exception as e:\n            print(f\"Error loading image {self.paths[index]}: {e}\")\n            return None\n\n    def __len__(self) -> int:\n        \"\"\"\n        Return the total number of images in the dataset.\n        \"\"\"\n        return len(self.paths) # Total number of samples\n    \n    def __getitem__(self, index: int) -> Tuple[torch.Tensor, int]:\n        \"\"\"\n        Retrieve an image and its label.\n        return: Tuple(transformed image tensor, class label).\n        \"\"\"\n        img = self.load_image(index)\n        if img is None:\n            return None   \n        if self.transform:\n            img = self.transform(img)\n        return img, self.class_idx    \n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-05T21:50:03.150804Z","iopub.execute_input":"2025-05-05T21:50:03.151089Z","iopub.status.idle":"2025-05-05T21:50:03.158029Z","shell.execute_reply.started":"2025-05-05T21:50:03.151069Z","shell.execute_reply":"2025-05-05T21:50:03.157403Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## Image Transformation\nImages will be resized to 256 by 256. Then they will be randomly cropped to produce some variability. Pixel values will be normalized to have a mean of 0.5 and a standard deviation of 0.5 for each color channel.","metadata":{}},{"cell_type":"code","source":"# Data Transformations\ndata_transform = transforms.Compose([\n    transforms.Resize(int(256 * 1.12), Image.BICUBIC),\n    transforms.RandomCrop((256, 256)),\n    transforms.ToTensor(),\n    transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))\n])\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-05T21:50:07.784267Z","iopub.execute_input":"2025-05-05T21:50:07.784532Z","iopub.status.idle":"2025-05-05T21:50:07.788895Z","shell.execute_reply.started":"2025-05-05T21:50:07.784513Z","shell.execute_reply":"2025-05-05T21:50:07.788251Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"# Create Datasets (use photo subset directory for photo dataset)\nmonet_dataset = CustomImageDataset(root=monet_dir, class_idx=1, transform=data_transform)\nphoto_dataset = CustomImageDataset(root=photo_subset_dir, class_idx=0, transform=data_transform)\n\n# Data Loaders\nbatch_size = 16\nnum_workers = 2  \n\nmonet_dl = DataLoader(dataset=monet_dataset, batch_size=batch_size, num_workers=num_workers, pin_memory=True, shuffle=True)\nphoto_dl = DataLoader(dataset=photo_dataset, batch_size=batch_size, num_workers=num_workers, pin_memory=True, shuffle=True)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-05T21:50:10.018372Z","iopub.execute_input":"2025-05-05T21:50:10.018637Z","iopub.status.idle":"2025-05-05T21:50:10.025693Z","shell.execute_reply.started":"2025-05-05T21:50:10.018615Z","shell.execute_reply":"2025-05-05T21:50:10.025024Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"# DATA EXPLORATION","metadata":{}},{"cell_type":"code","source":"print(f\"There are {len(monet_dataset)} images of Monet's Paintings\")\nprint(f\"There are {len(photo_dataset)} images of photos\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-05T21:50:13.193524Z","iopub.execute_input":"2025-05-05T21:50:13.194403Z","iopub.status.idle":"2025-05-05T21:50:13.198901Z","shell.execute_reply.started":"2025-05-05T21:50:13.194367Z","shell.execute_reply":"2025-05-05T21:50:13.197961Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"monets = next(iter(monet_dl))\nphotos = next(iter(photo_dl))","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-05T21:50:32.676044Z","iopub.execute_input":"2025-05-05T21:50:32.676701Z","iopub.status.idle":"2025-05-05T21:50:33.967313Z","shell.execute_reply.started":"2025-05-05T21:50:32.676680Z","shell.execute_reply":"2025-05-05T21:50:33.966544Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"# Inspect the first batch of images from each dataloader\nmonet_images, _ = monets  # Separate images and labels\nphoto_images, _ = photos\n\n# Check the image dimensions \nprint(\"Dimensions of Monet image:\", monet_images[0].shape)\nprint(\"Dimensions of photo:\", photo_images[0].shape)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-05T21:50:36.172545Z","iopub.execute_input":"2025-05-05T21:50:36.173294Z","iopub.status.idle":"2025-05-05T21:50:36.178660Z","shell.execute_reply.started":"2025-05-05T21:50:36.173266Z","shell.execute_reply":"2025-05-05T21:50:36.177756Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"monets_imshow = []\nfor monet in monets:\n    if monet.dim() == 4:  \n        for img in monet: \n            if img.dim() == 3:  # Ensure image is a tensor \n                img = img.permute(1, 2, 0)  # Tensor [C, H, W] to [H, W, C]\n                img = img.numpy() \n                img = img * 0.5 + 0.5  # Undo data normalization\n                monets_imshow.append(img)\n            else:\n                print(f\"Skipping img with unexpected shape {img.shape}\")\n    else:\n        print(f\"Skipping tensor with shape {monet.shape}\")\n        \n        \nphotos_imshow = []\nfor photo in photos:\n    if photo.dim() == 4:  \n        for img in photo:  \n            if img.dim() == 3:  # Ensure image is a tensor \n                img = img.permute(1, 2, 0)  # Tensor [C, H, W] to [H, W, C]\n                img = img.numpy() \n                img = img * 0.5 + 0.5  # Undo data normalization\n                photos_imshow.append(img)\n            else:\n                print(f\"Skipping img with unexpected shape {img.shape}\")\n    else:\n        print(f\"Skipping tensor with shape {photo.shape}\")       ","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-05T21:50:38.784495Z","iopub.execute_input":"2025-05-05T21:50:38.784787Z","iopub.status.idle":"2025-05-05T21:50:38.834927Z","shell.execute_reply.started":"2025-05-05T21:50:38.784765Z","shell.execute_reply":"2025-05-05T21:50:38.834294Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## Display Examples of Monet Paintings and Photos","metadata":{}},{"cell_type":"code","source":"def display_images(images, title, n_images=4, figsize=(15, 5)):\n    fig = plt.figure(figsize=figsize) \n\n    for i in range(n_images):\n        plt.subplot(1, n_images, i+1)\n        img = images[i]\n        if torch.is_tensor(img):\n            img = img.permute(1, 2, 0)  \n            img = img.numpy()  \n        plt.imshow(img)\n        plt.axis('off')\n\n    fig.suptitle(title, fontsize=16)\n    plt.show()\n\ndisplay_images(monets_imshow, 'Monets')\ndisplay_images(photos_imshow, 'Photos')","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-05T21:50:42.569402Z","iopub.execute_input":"2025-05-05T21:50:42.569690Z","iopub.status.idle":"2025-05-05T21:50:43.217571Z","shell.execute_reply.started":"2025-05-05T21:50:42.569671Z","shell.execute_reply":"2025-05-05T21:50:43.216779Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"# GAN MODELS","metadata":{}},{"cell_type":"markdown","source":"## Generator Function and Architecture\n\n### Purpose of Generator\nThe generator analyzes the images, identifying the key attributes and modifying some of the attributes by adding noise to them. Its goal is to produce images that are indistinguishable from the real paintings. \n\n### Generator Architecture \nThe generator uses an encoder -> bottleneck -> decoder architecture. The network is made up of fully connected Conv2d layers to extract image featuresl, followed by instance normalization layers to help stabilize the model. The Conv2d layers also add padding ensuring the output has the same dimensions as the input. LeakyReLU activations are used because they allow for negative inputs and are therefore more versatile and appropriate for distinguishing between images. Lastly a Tanh activation output layer scales the pixel values between -1 and 1. Since images are normalized to the range -1 and 1, the Tanh activation ensures that the pixel values of the generated images are within the expected range. \n\n","metadata":{}},{"cell_type":"code","source":"class Generator(nn.Module):\n    def __init__(self):\n        super(Generator, self).__init__()\n\n        # Encoder, Downsampling\n        self.encoder = nn.Sequential(\n            nn.Conv2d(3, 64, 4, stride=2, padding=1), \n            nn.LeakyReLU(0.2, inplace=True),\n            nn.Conv2d(64, 128, 4, stride=2, padding=1),  \n            nn.InstanceNorm2d(128),\n            nn.LeakyReLU(0.2, inplace=True),\n            nn.Conv2d(128, 256, 4, stride=2, padding=1),  \n            nn.InstanceNorm2d(256),\n            nn.LeakyReLU(0.2, inplace=True),\n            nn.Conv2d(256, 512, 4, stride=1, padding=1),  \n            nn.InstanceNorm2d(512),\n            nn.LeakyReLU(0.2, inplace=True),\n        )\n\n        # Bottleneck \n        self.bottleneck = nn.Sequential(\n            nn.Conv2d(512, 512, 4, stride=2, padding=1), \n            nn.InstanceNorm2d(512),\n            nn.ReLU(inplace=True)\n        )\n\n        # Decoder, Upsampling\n        self.decoder = nn.Sequential(\n            nn.ConvTranspose2d(512, 512, 4, stride=1, padding=1),  \n            nn.InstanceNorm2d(512),\n            nn.LeakyReLU(inplace=True),\n            nn.ConvTranspose2d(512, 256, 4, stride=2, padding=1), \n            nn.InstanceNorm2d(256),\n            nn.LeakyReLU(inplace=True),\n            nn.ConvTranspose2d(256, 128, 4, stride=2, padding=1),  \n            nn.InstanceNorm2d(128),\n            nn.LeakyReLU(inplace=True),\n            nn.ConvTranspose2d(128, 64, 4, stride=2, padding=1),  \n            nn.InstanceNorm2d(64),\n            nn.LeakyReLU(inplace=True),\n            nn.ConvTranspose2d(64, 3, 4, stride=2, padding=1),  \n            nn.Tanh()\n        )\n\n    def forward(self, img):\n        enc_out = self.encoder(img)\n        bottleneck = self.bottleneck(enc_out)\n        dec_out = self.decoder(bottleneck)\n        return dec_out\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-05T21:51:44.891795Z","iopub.execute_input":"2025-05-05T21:51:44.892587Z","iopub.status.idle":"2025-05-05T21:51:44.901224Z","shell.execute_reply.started":"2025-05-05T21:51:44.892563Z","shell.execute_reply":"2025-05-05T21:51:44.900523Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## Discriminator Function and Architecture\n\n### Purpose of Discriminator\nTakes the modified images from the generator as input and classifies it as real or fake. \n\n### Discriminator Architecture\nThe core block of the discriminator uses a similar architecture as the generator. There is instance normalization, Conv2d Layers and, LeakyReLU activations are used for the same reasons as they were in the generator.  Spectral noramlization was also added to improve stability. The discriminator uses sigmoid activation as the output to produce a probability as its purpose is to perform binary classification.  \n","metadata":{}},{"cell_type":"code","source":"class Discriminator(nn.Module):\n    def __init__(self):\n        super(Discriminator, self).__init__()\n        \n        def discriminator_block(in_filters, out_filters, normalization=True, stride=2):\n            layers = [nn.Conv2d(in_filters, out_filters, 4, stride=stride, padding=1)]\n            if normalization:\n                layers.append(nn.InstanceNorm2d(out_filters))\n            layers.append(nn.LeakyReLU(0.2, inplace=True))\n            return nn.Sequential(*layers)\n        \n        # Apply spectral normalization to improve stability\n        self.model = nn.Sequential(\n            spectral_norm(nn.Conv2d(3, 64, 4, stride=2, padding=1)),\n            nn.LeakyReLU(0.2, inplace=True),\n            spectral_norm(discriminator_block(64, 128)[0]),\n            nn.LeakyReLU(0.2, inplace=True),\n            spectral_norm(discriminator_block(128, 256)[0]),\n            nn.LeakyReLU(0.2, inplace=True),\n            spectral_norm(discriminator_block(256, 512, stride=1)[0]),\n            nn.LeakyReLU(0.2, inplace=True),\n            spectral_norm(nn.Conv2d(512, 1, 4, padding=1))\n        )\n        \n    def forward(self, img):\n        return self.model(img)\n\ndef spectral_norm(module):\n    \"\"\"Apply spectral normalization to a module\"\"\"\n    return nn.utils.spectral_norm(module)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-05T21:51:54.482091Z","iopub.execute_input":"2025-05-05T21:51:54.482383Z","iopub.status.idle":"2025-05-05T21:51:54.489035Z","shell.execute_reply.started":"2025-05-05T21:51:54.482364Z","shell.execute_reply":"2025-05-05T21:51:54.488208Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## Training the GAN\nThe networks are trained until the discriminator can no longer distinguish between the real and synthesized images. This will be done by adjusting the model’s weights with the discriminator loss function (loss_D) penalizing the discriminator for misclassifying images, and the generator loss function (loss_G) penalizing the generator if the discriminator can detect that the images are fake. The parameters of both networks are updated using an Adam optimizer. ","metadata":{}},{"cell_type":"markdown","source":"### Function to Show a Subset of Images as They are Being Generated","metadata":{}},{"cell_type":"code","source":"def show_generated_img(fake_images, epoch, batch):\n    \"\"\"\n    Display images during training.\n    \n    fake_images: Tensor of generated images\n    epoch: Current epoch number\n    batch: Current batch number\n    \"\"\"\n    # Undo normalization \n    fake_images = (fake_images * 0.5) + 0.5\n    img_grid = vutils.make_grid(fake_images[:6], padding=2, normalize=True)\n    \n    # Plot\n    plt.figure(figsize=(8,8))\n    plt.imshow(np.transpose(img_grid.cpu(), (1, 2, 0)))\n    plt.title(f\"Epoch {epoch}, Batch {batch}\")\n    plt.axis('off')\n    plt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-05T21:51:58.236933Z","iopub.execute_input":"2025-05-05T21:51:58.237489Z","iopub.status.idle":"2025-05-05T21:51:58.241805Z","shell.execute_reply.started":"2025-05-05T21:51:58.237467Z","shell.execute_reply":"2025-05-05T21:51:58.241222Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## Training Parameters\nThe network will be trained using a learning rate of 0.0002, beta1 set to 0.5 and beta2 set to 0.999. Beta1 sets the decay rate for the moving average of the gradient and beta2 controls the decay rate for the moving average of the squared gradient.","metadata":{}},{"cell_type":"code","source":"# Initialize models\ndevice = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n\ngenerator = Generator().to(device)\ndiscriminator = Discriminator().to(device)\n\n# Binary cross-entropy loss function\ncriterion = nn.BCEWithLogitsLoss()\n\n# Optimizers \noptimizer_g1 = optim.Adam(generator.parameters(), lr=0.0002, betas=(0.5, 0.999))\noptimizer_d1 = optim.Adam(discriminator.parameters(), lr=0.0002, betas=(0.5, 0.999))","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-05T21:52:01.009352Z","iopub.execute_input":"2025-05-05T21:52:01.009627Z","iopub.status.idle":"2025-05-05T21:52:01.210420Z","shell.execute_reply.started":"2025-05-05T21:52:01.009608Z","shell.execute_reply":"2025-05-05T21:52:01.209836Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"### VGG Network\nThe VGGLoss function uses a pre-trained VGG network to compare images based on their features rather than just pixel values. The VGG network was trained on ImageNet for classification tasks. This will be used for calculating perceptual loss, helping to generate sharper Monet-style images.","metadata":{}},{"cell_type":"code","source":"class VGGLoss(nn.Module):\n    def __init__(self, device):\n        super(VGGLoss, self).__init__()\n        vgg = models.vgg19(weights=models.VGG19_Weights.IMAGENET1K_V1).features[:29].to(device)\n        for param in vgg.parameters():\n            param.requires_grad = False\n        self.vgg = vgg\n        self.criterion = nn.L1Loss()\n        self.weights = [1.0/32, 1.0/16, 1.0/8, 1.0/4, 1.0]\n        \n    def forward(self, x, y):\n        x_vgg, y_vgg = self.vgg(x), self.vgg(y)\n        loss = self.criterion(x_vgg, y_vgg)\n        return loss","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-05T21:52:03.937588Z","iopub.execute_input":"2025-05-05T21:52:03.937857Z","iopub.status.idle":"2025-05-05T21:52:03.943092Z","shell.execute_reply.started":"2025-05-05T21:52:03.937837Z","shell.execute_reply":"2025-05-05T21:52:03.942363Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"### Monet's Paintings 1st Training","metadata":{}},{"cell_type":"code","source":"# Training loop Monet Paintings Take 1\nnum_epochs = 225\ndisplay_interval = 200  # For printing generated images\n\n# Lists to hold training history for plots\ndiscriminator_losses_m1 = []\ngenerator_losses_m1 = []\n\ncriterion_gan = nn.MSELoss()  # For adversarial loss\ncriterion_cycle = nn.L1Loss()  # For content preservation\nvgg_loss = VGGLoss(device)  # For perceptual loss\n\nfor epoch in range(num_epochs):\n    for i, (real_photos, _) in enumerate(photo_dl):  # Load real photos\n        batch_size = real_photos.size(0)\n        real_photos = real_photos.to(device)\n        real_monet = next(iter(monet_dl))[0].to(device)\n\n        # Generate fake Monet-style images from real photos\n        fake_monet = generator(real_photos) \n\n        # Train discriminator\n        discriminator.zero_grad()\n        output_real = discriminator(real_monet)\n        output_fake = discriminator(fake_monet.detach())\n\n        # Ensure labels match discriminator output\n        real_labels = torch.ones_like(output_real, device=device)\n        fake_labels = torch.zeros_like(output_fake, device=device)\n\n        loss_real = criterion_gan(output_real, real_labels)\n        loss_fake = criterion_gan(output_fake, fake_labels)\n        loss_D = (loss_real + loss_fake) / 2\n        discriminator_losses_m1.append(loss_D.item())\n\n        loss_D.backward()\n        optimizer_d1.step()\n\n        # Train generator\n        generator.zero_grad()\n        fake_labels = torch.ones_like(output_fake, device=device)  # Trick discriminator\n        output = discriminator(fake_monet)\n        loss_gan = criterion_gan(output, fake_labels)\n        \n        # Content loss to help preserve structure\n        loss_content = criterion_cycle(fake_monet, real_photos) * 10.0\n\n         # Perceptual loss to help preserve details using VGG net\n        loss_perceptual = vgg_loss(fake_monet, real_photos) * 5.0\n\n        loss_G = loss_gan + loss_content + loss_perceptual\n        generator_losses_m1.append(loss_G.item())\n        loss_G.backward()\n        optimizer_g1.step()\n\n        if i % display_interval == 0:\n            print(f\"Epoch [{epoch}/{num_epochs}] Batch [{i}/{len(photo_dl)}] \\\n                  Loss D: {loss_D.item()}, Loss G: {loss_G.item()}\")\n            show_generated_img(fake_monet, epoch, i)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-05T21:52:06.548045Z","iopub.execute_input":"2025-05-05T21:52:06.548398Z","iopub.status.idle":"2025-05-05T23:22:36.395446Z","shell.execute_reply.started":"2025-05-05T21:52:06.548371Z","shell.execute_reply":"2025-05-05T23:22:36.394419Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"# Plotting Discriminator and Generator Losses\nplt.figure(figsize=(10, 5))\n\n# Plot Discriminator Loss\nplt.plot(discriminator_losses_m1, label='Discriminator Loss', color='red')\n\n# Plot Generator Loss\nplt.plot(generator_losses_m1, label='Generator Loss', color='blue')\nplt.title(\"Discriminator and Generator Losses During 1st Monet Training\")\nplt.xlabel(\"Iterations\")\nplt.ylabel(\"Loss\")\nplt.legend(loc=\"upper right\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-05T23:23:31.717613Z","iopub.execute_input":"2025-05-05T23:23:31.717951Z","iopub.status.idle":"2025-05-05T23:23:31.952761Z","shell.execute_reply.started":"2025-05-05T23:23:31.717925Z","shell.execute_reply":"2025-05-05T23:23:31.952045Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## Results From Training \nThe discriminator loss measures how well the discriminator is distinguishing between real and generated samples. High discriminator loss means the discriminator is not differentiating between real and fake images very well. The generator loss measures how well the generator is fooling the discriminator. A low generator loss indicates the generator is successfully creating images that the discriminator cannot easily differentiate from real ones. The discriminator loss did decrease rapidly for the first few epochs then gradually decreased after that. Based on visual inspection the image quality did improve dramatically by the end of training. \n","metadata":{},"attachments":{"031d78b5-c850-4bea-b82b-70ca1e14efa5.png":{"image/png":"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"},"c5b9cb5e-d180-4d3b-9930-b711cbb342cd.png":{"image/png":"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"},"d8a76cb2-34d5-48c0-8ddd-7b631b5962c5.png":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAdQAAABvEAYAAAAFze0tAAAMPmlDQ1BJQ0MgUHJvZmlsZQAASImVVwdYU8kWnluSkEBoAQSkhN4EASkBpITQAkgvgo2QBAglxoQgYi+LCq5dLGBDV0UUOyB2RLGwKPa+IKKgrIsFu/ImBXTdV7538s29f/45858z584tA4DGaY5IlItqApAnzBfHhQbSx6ak0kk9AIE/MgDAhsOViJgxMZEQg8Hz3+3dLegL7bqjTOuf/f/VtHh8CRcAJAbidJ6EmwfxYQDwCq5InA8AUcZbTM0XyTBsQEcME4R4kQxnKnCFDKcr8H65T0IcC+ImAFTUOBxxJgDqVyFPL+BmQg31PoidhTyBEAANOsR+eXmTeRCnQWwLfUQQy/QZ6T/oZP5NM31Ik8PJHMKKuchNJUggEeVypv2f5fjflpcrHYxhDZtaljgsTjZnWLc7OZMjZFgN4l5helQ0xNoQfxDw5P4Qo5QsaViiwh814kpYsGZAD2JnHicoAmIjiEOEuVGRSj49QxDChhiuELRQkM9OgFgf4kV8SXC80meLeHKcMhZamyFmMZX8BY5YHlcW65E0J5Gp1H+dxWcr9TH1oqyEZIgpEFsWCJKiIFaH2EmSEx+h9BldlMWKGvQRS+Nk+VtCHMcXhgYq9LGCDHFInNK/JE8yOF9sS5aAHaXEB/OzEsIU9cGauBx5/nAu2FW+kJk4qMOXjI0cnAuPHxSsmDvWzRcmxit1PojyA+MUY3GKKDdG6Y+b83NDZbw5xG6SgnjlWDwpHy5IhT6eIcqPSVDkiRdlc8JjFPngy0EkYIEgQAdS2NLBZJANBK29db3wn6InBHCAGGQCPnBUMoMjkuU9QniMB0XgT4j4QDI0LlDeywcFkP86xCqOjiBD3lsgH5EDnkKcByJALvwvlY8SDkVLAk8gI/hHdA5sXJhvLmyy/n/PD7LfGSZkIpWMdDAiXWPQkxhMDCKGEUOIdrgh7of74JHwGACbK87AvQbn8d2f8JTQRnhMuEloJ9ydJJgn/inLMaAd6ocoa5H+Yy1wa6jpjgfivlAdKuN6uCFwxN1gHCbuDyO7Q5alzFtWFfpP2n+bwQ9XQ+lHdiaj5GHkALLtzyPV7dXdh1Rktf6xPopc04fqzRrq+Tk+64fq8+A54mdPbBF2CGvGzmAXseNYHaBjp7B6rAU7IcNDq+uJfHUNRouT55MDdQT/iDd4ZWWVlDhXO/c4f1H05fMLZc9owJosmiYWZGbl05nwjcCns4VcpxF0V2dXdwBk7xfF4+tNrPy9gei1fOfm/wGA76mBgYFj37nwUwAc8IS3/9HvnC0DvjpUAbhwlCsVFyg4XHYgwKeEBrzTDIAJsAC2cD6uwAP4gAAQDMJBNEgAKWAizD4LrnMxmApmgLmgGJSC5WAN2AA2g21gF9gLDoI6cBycAefBZXAV3AT34erpAi9AH3gHPiMIQkKoCA0xQEwRK8QBcUUYiB8SjEQicUgKkoZkIkJEisxA5iOlyEpkA7IVqUIOIEeRM8hFpA25i3QgPchr5BOKoWqoDmqMWqMjUQbKRCPQBHQCmolOQYvQBehSdB1aie5Ba9Ez6GX0JtqOvkD7MYCpYnqYGeaIMTAWFo2lYhmYGJuFlWBlWCVWgzXA63wda8d6sY84EafhdNwRruAwPBHn4lPwWfgSfAO+C6/Fm/DreAfeh38jUAlGBAeCN4FNGEvIJEwlFBPKCDsIRwjn4L3URXhHJBL1iDZET3gvphCzidOJS4gbifuIp4ltxE5iP4lEMiA5kHxJ0SQOKZ9UTFpP2kM6RbpG6iJ9UFFVMVVxVQlRSVURqsxTKVPZrXJS5ZrKM5XPZE2yFdmbHE3mkaeRl5G3kxvIV8hd5M8ULYoNxZeSQMmmzKWso9RQzlEeUN6oqqqaq3qpxqoKVOeorlPdr3pBtUP1o5q2mr0aS228mlRtqdpOtdNqd9XeUKlUa2oANZWaT11KraKepT6iflCnqTups9V56rPVy9Vr1a+pv9Qga1hpMDUmahRplGkc0rii0atJ1rTWZGlyNGdplmse1byt2a9F03LRitbK01qitVvrola3NknbWjtYm6e9QHub9lntThpGs6CxaFzafNp22jlalw5Rx0aHrZOtU6qzV6dVp09XW9dNN0m3ULdc94Ruux6mZ63H1svVW6Z3UO+W3qdhxsOYw/jDFg+rGXZt2Hv94foB+nz9Ev19+jf1PxnQDYINcgxWGNQZPDTEDe0NYw2nGm4yPGfYO1xnuM9w7vCS4QeH3zNCjeyN4oymG20zajHqNzYxDjUWGa83Pmvca6JnEmCSbbLa5KRJjynN1M9UYLra9JTpc7ounUnPpa+jN9H7zIzMwsykZlvNWs0+m9uYJ5rPM99n/tCCYsGwyLBYbdFo0WdpajnGcoZlteU9K7IVwyrLaq1Vs9V7axvrZOuF1nXW3Tb6NmybIptqmwe2VFt/2ym2lbY37Ih2DLscu412V+1Re3f7LPty+ysOqIOHg8Bho0PbCMIIrxHCEZUjbjuqOTIdCxyrHTuc9JwineY51Tm9HGk5MnXkipHNI785uzvnOm93vu+i7RLuMs+lweW1q70r17Xc9cYo6qiQUbNH1Y965ebgxnfb5HbHneY+xn2he6P7Vw9PD7FHjUePp6VnmmeF522GDiOGsYRxwYvgFeg12+u410dvD+9874Pef/k4+uT47PbpHm0zmj96++hOX3Nfju9W33Y/ul+a3xa/dn8zf45/pf/jAIsAXsCOgGdMO2Y2cw/zZaBzoDjwSOB7ljdrJut0EBYUGlQS1BqsHZwYvCH4UYh5SGZIdUhfqHvo9NDTYYSwiLAVYbfZxmwuu4rdF+4ZPjO8KUItIj5iQ8TjSPtIcWTDGHRM+JhVYx5EWUUJo+qiQTQ7elX0wxibmCkxx2KJsTGx5bFP41ziZsQ1x9PiJ8Xvjn+XEJiwLOF+om2iNLExSSNpfFJV0vvkoOSVye1jR46dOfZyimGKIKU+lZSalLojtX9c8Lg147rGu48vHn9rgs2EwgkXJxpOzJ14YpLGJM6kQ2mEtOS03WlfONGcSk5/Oju9Ir2Py+Ku5b7gBfBW83r4vvyV/GcZvhkrM7ozfTNXZfZk+WeVZfUKWIINglfZYdmbs9/nROfszBnITc7dl6eSl5Z3VKgtzBE2TTaZXDi5TeQgKha1T/GesmZKnzhCvEOCSCZI6vN14Id8i9RW+ou0o8CvoLzgw9SkqYcKtQqFhS3T7KctnvasKKTot+n4dO70xhlmM+bO6JjJnLl1FjIrfVbjbIvZC2Z3zQmds2suZW7O3N/nOc9bOe/t/OT5DQuMF8xZ0PlL6C/VxerF4uLbC30Wbl6ELxIsal08avH6xd9KeCWXSp1Ly0q/LOEuufSry6/rfh1YmrG0dZnHsk3LicuFy2+t8F+xa6XWyqKVnavGrKpdTV9dsvrtmklrLpa5lW1eS1krXdu+LnJd/XrL9cvXf9mQteFmeWD5vgqjisUV7zfyNl7bFLCpZrPx5tLNn7YIttzZGrq1ttK6smwbcVvBtqfbk7Y3/8b4rWqH4Y7SHV93Cne274rb1VTlWVW122j3smq0Wlrds2f8nqt7g/bW1zjWbN2nt690P9gv3f/8QNqBWwcjDjYeYhyqOWx1uOII7UhJLVI7rbavLquuvT6lvu1o+NHGBp+GI8ecju08bna8/ITuiWUnKScXnBw4VXSq/7TodO+ZzDOdjZMa758de/ZGU2xT67mIcxfOh5w/28xsPnXB98Lxi94Xj15iXKq77HG5tsW95cjv7r8fafVorb3ieaX+qtfVhrbRbSev+V87cz3o+vkb7BuXb0bdbLuVeOvO7fG32+/w7nTfzb376l7Bvc/35zwgPCh5qPmw7JHRo8o/7P7Y1+7RfqIjqKPlcfzj+53czhdPJE++dC14Sn1a9sz0WVW3a/fxnpCeq8/HPe96IXrxubf4T60/K17avjz8V8BfLX1j+7peiV8NvF7yxuDNzrdubxv7Y/ofvct79/l9yQeDD7s+Mj42f0r+9Ozz1C+kL+u+2n1t+Bbx7cFA3sCAiCPmyD8FMNjQjAwAXu8EgJoCAA3uzyjjFPs/uSGKPascgf+EFXtEuXkAUAO/32N74dfNbQD2b4fbL6ivMR6AGCoACV4AHTVqqA3u1eT7SpkR4T5gS+zX9Lx08G9Msef8Ie+fz0Cm6gZ+Pv8LsvR8QQqczIcAAAA4ZVhJZk1NACoAAAAIAAGHaQAEAAAAAQAAABoAAAAAAAKgAgAEAAAAAQAAAdSgAwAEAAAAAQAAAG8AAAAAF48b5AAAQABJREFUeAHsXQl8FEXW73BfQoSAMQQynsQzwaCi6GbcQxGBBFy5RDMcn5xuwirixQbERQEF4oqIB0k4VlgPElDBA5koKCKBRDzwWBiQNQiI4RQQzPfq/atqwkya7kmGBLT7/X7T093VVa/eXUdXGYZzOBRwKOBQwKGAQwGHAg4FHAo4FHAo4FDAoYBDAYcCDgUcCjgUcCjgUMChgEMBhwIOBRwKOBRwKOBQwKEAKFA76RIBZzSNiRXQ7IyYswU0bmR5jo4hqFsvpo2AO/rEJAko+rTkawFlZdVN4KSLBVzVEfU4//yS7QK2+JISBFyeGHOWgHbxJT8I2OKrdvwuSCJo3CSmtYDb+5XsEFBUFG48TpX6hrteVvmB/5clxrQV0D6+hI//+qzec57/viiQxEd8fExLAddeB3vw1cbfFxXs19ZMr+A3mkdB3/r1gr6tD9meJXUTUKtWTH0BnVNiWgmoa8A+7tplH9PwpEy6TEB0NPxf6l8hH58WCetdHfbbbi2SLhdwayro9VMp6LV/v933rdKdavW1wjdcz6u73jUlbydbfsLGj0rGb5W1K6da/JTUXkB7GddcEl/yPwGbfeGir5NP9VLAzJ9WLxbmpSWdK6BevZh2Av7aLaaFgF2l8IMHwuZfzDE4/kktI0LAzCzjZwEvvmzUEvDACOOogO93Gr8IeOFl44iAf05B+q8/MRoKyGyG589nG98LqF37+OxP/hUMfGKiUVvACy8B/y7Jx5fcMdFoIKBzwP3jU53Uq6YGQaso4DEoDYFy3bonp8zqr2/SlQLOjj459THPNekiARfEG3UFPDfNKBPQJ838DefJ75ECCMjiXMYhAc/MhL0YmP57pIWdOpvplQr8kMeEKcYxAU9l28lTpAmyE+w3/vIHo5GAOdOMXwW072g3v3Clgz1u1MioI2DKY/Bzj2Tq/KvVfutSzf8wvW5PAZ4XxpsnrOSTGqovAqTatRGYt4yqJPaVf62a6l1d8oaOpJjYIIKcbPkJKrAqNyoRz1TJrlSivKpUr4J3If+XJsIePj/NOCCgZ9jjmiB7XAEuzq2qU8DMn1Y95zDncIZB0Ksf2nvzFyH32GqP63WtoAgZGfqG/JOUKOBAGQK77qnqOXqY+nuS2gm4pDPSlZWd3AaXKt38jIbqM9nAY5I/sDB/xXkSRgpAjt5YEcYsQ8oKcjk+M+kKAdnZIb3sJP7dUAD2YVQG5DWvxuT1dCG4mV4hsLkkXvkJu/UxsxPgy4cr0MPcz2M3v3CnQ31ucOO8aXO483fyOzEF4Mc9HshXLx13nPit0/fpyZI31fCA/r74u/WHp4pdqayEgo+TM9HRMCPsfDSzx5XF13nvxBQw86cnfqv6nyZdLWDnZuCblFj9GKDEOoXrBUyfbheBwmIB83KA+Fn+ljWPuF50CQR+RDpGVt8vKPxMwPwclb/u0eMRr0GDMfJ1pBQjtrPnAZ+dplO74MAaNMBI2T33YyS3WRneP9+Fctb7dLp6BkGvPuiJamgg/1kS/zaxyCdtMHrwI8uMwwLWbkG6BTlJZwioU8e4RMCtXY19Aq5JEbka9V7PNfYIeP9Do5WAHl0wEh3twkhuPQPpSmX9vtgIPPsMAR3vHqAFgEeqB6Qb9QU8m4V63J0OfDYUA/85s4Hng6OQbx0DPWsPT1L0xX1/fYFf9r+NZgJ69kP5rSKRrsSHnpIbU+RISFbhFwI2FGn+8ohCvz5Id0EC6PVuPvj6Wh74PSsb97vIwI5GHnhkZXYuRqyIn9wzfddglN8uAc8/0PIBfkVHo54DhxqNBXxZhPr/MQX3X8wq3CCggqnRPBPgaISmQ8CfpKsE9EjV+fFMgZ1bwK/pUws3Cti7F/W2IRfcgXODGyNxNDLPI/i1DMh99kLID/E74AgXv0GHQ4eSrhVQvz7k4La+oG+HZPA3Nwt4rLfPTyXvbQ2CwSMhb+2agf4HDIwwZeeCbn09mBHweZGxV8Dy9/D87r9DHn4sRbrZz1jpR+HHAp6XenltR8hH7yHQh5X5xtcCFr2uyWmCXyEfD4/X6QL/8EyRXwzkq0b0KBDmkdW/pAD/LEm3z4rU61byA/1q2Rz53JkGPhyOgFy8ugDn3n1gF0hMubz5C0DflpHQr8434XluLvi2yafL5ymd1FHIcp4k9fDTYtBJ8eWaBPD94B4jWsCUp4wdAgbdCf41jyz8RMCk6bbtsJlesZ08agBfhaX52dJOsP+g/HhmTkMDgTvZEbazDaXcPfx44YcCDh+2K/fmGOFJ0qUCeqZCXv+QAr4Rf9ju+d9GoNupI56Xs98W+hIojwg4r0gE32gElOn4zR7IT/ZM6PHl7VGOZwj061WpbzSCwng9+RXwTWuA6/w8YPq/7bhP9pP9CdlJpt9ViZCv5nHI79HRyL9bV6TvlIxrkntl/7nCFdRXfkoDOUwbAvl9ZhLkecQY4PNRAeR3bo6iIOxefw/wSYqDXdgVYRwUMGUi+H5TF+gJBeIsD8tywJ8DBvzNG3mWesgzvQ4dsmtvFH7qHC4+q/wCzydb3kDXmS+CH0s/AD/qyJkLYzJA1/mv4Dx4sJYfpneJlJ9BQ8HX1V7I6XVuyEnTMsjPg349jE8iaNoU/vq2nkh3QRz4WrwF8R3FP+wfG/jwPDEF8jhvodFEwBkNcJ2SgufLC3Besxry4o9nIFf24zfU09quIK6LiAgsr7Lxk+I77GznVPibTgmo5449oCt9gsRxyNcbCz8X8G1QvAA9I/xlfAH78fcM6HfLZsgnaxbige3bdbk8NfoEfvR8g2DG86BzubiN7dHWc0CHNpvx/OT7GSt7Dj58/gXspP04VtFDndUUVrv2AXbLnI6F+wQcPWpl3wo3CThyRPLTNE5VeKoz8qV2llUcXlm7zAYvPh7yNag39GB3BPxSXZfCo6bOFFGH6WAFuk0GeMvzwYicbGG+kuJbRKFn/MxI3J8519gl4InJMKgxCVDU56ZYYsMB0+yZ2vBxoPePSSDo2S79PuPTSjZ4yLFzg+naZP2cA6EnJuD65QV4Pycfin+NP12cQfDqO7i/sxTp582C4Vu6AgoT/ymed08Bo8eloz4khzw1IzIR19d1RKA4yIN86JenHlPAwoHECA/o0zsF9VuWj/tTp8FhZMmp2O8XwwHc4oHgkkMxqy/XM6oV8kuRDakH04H/pQkojxrS3GEwfZrGi/88/Rgc3c8G6EdTwbkB/coiKHqTJsBv8nj9Htd30pOGS8DWrajfy0tQDgX8bJAfHYt8HslEw3RYBugS60I9hkh+jU5H/fb4cL9JpC7H5h8o+AAP+NM5BQp4zxCUFxeHfPPydXYWcqHrzfR6JBMB6JjxoM9+Yrg4Wvo7bnDD/xsufqsc2aHMfRZ0WuUFH1/JBX9XrYf+UQDBhw1+srx37wq6REUaPwoY8xjy6+BGQ1I51sZlkI/UFNXAR/n0nOV5WDoCT5I/Dpgr0A/W32aRsA9pkk9XdIR8P3Q3+DRxmtFGQK/+QhuNOHP8FFksz2zwO7ignw2lXFHDlen5pNYDu/Kj6cKBXpRLTJQxzugQV/ipgHLfuHIAfWOyDkj4ets26MOFrrIXBGzeEoT/boPgnbcRMHg8CHTqRcJ+vrME/EmR9w8ZhUsE/PornjeNRL2+9YXNDgchaHGD5eEEdkK9zvS4Iw30WFkAOejiAf79+6pkuLYr9/ot/Uc3dHhK8ZB00Ok+2eA64FMJ9ZRmtlsV2G+b8qgDGLaPNLWc/dj9E6Fn96YjABswDOVe2RF6NNyDM32yIgNUNATi+kC/RqZBr2JceK+1tDt3peH6PumHPvbCDndywU68+TLod0gHvsj/X9Ms68sZX+XHj+k3WjZMiwtgB8nv87dzLaMQoHdLBT4D0tBxcs8ElNc3DfXp1w/0f+tN1HeDF+nzJP/fedOuHtq1N8jf/2tZb5t89ud4/L9qk7fzDIKS78HnuVnwt195jRIBTz0HrGJjg+SH5Zvkh+3i0DTYmcmZsL/fyYZldw/45PHrIccD07KQjjrM0eEwA3yck41zcgLKfU/mc7sH/L8wHh1m64rAt8tcyOd6N56HIX5TbLCyK2GOn3TDlOk5Or1wnYCx41GvW+QAxz3p0MvGDRSapmeON25xg/7kp9h+EJ2YbwUfqfds+1Eze8z+6999qt3PWMQxGOBwLYY8hRrHKurQWcXDYYpHbNu3ciiE/tdG3MaZhmqXz2gK//HeUviDp16EPC7LA47NQkc1zG+Er4HKCvPIRBic/+QhYKKGDQvE2bFQzJRUnOsbaNiNug8NryM+EGqvcUWhAOrJCjjQo95MBpLdPMh/fo4aSYLger3qtcIiAVt9uF5XoO4HnVkhX1kKgx0TCYWfOh4OkXou2ABf6kJD5D0vAsu1smevQ3sjVsBnFyNg/LgY5/d9SD95Onp+p2TAsCxeVnH55UaGeMRj4pTCNQIWSTp+I0c6X8kv/FLAm3kwICu8wLdtM7P6At/vtyFwWFMMw7bKixHczPHgz/xcmY9L48cGbOos0GWlF+V1TUU+xB4eEW0eZewX8DN18eEo/EYAfUy9VcD5F+Ku2102S8C7smedAnI2rItz4BA9KZqu7CjIIbLBmpGrRiBQP8Ij1IPLycgEX17P1z1ZnM+LsyA3NKWPR6joG0V1mMiFcaYACvzZEbd3IxCbmw3+vpYHvD8tUtkEnTnfqvNbNzTY0F7tRkOxr9SLZDcCvyU5kN8LzgUfbfCT6aXUb0ym0ULAyOHgf7oMoKlWXA/VIC9XS25w7i1Vd7T8cYBQgX7wjIwnpoMPFLCyXLmaQS7/di/4RnLOekgdXHbxUwiYnRn/tT6MGOXmgD75uZDHti79Wqjyw/L71CQ0fDt7tN3iQJ7kmp9fK+XmXBf08fbBoO+jk9YlCQheZK5wm4CfDwKv5yWefdIgz8eOAe/tPpz7p2j8ubzEBDSUX82rqh3W+Yb6x8RO6Ia0yo87Ep/LRYP/bS/wpZEc5lfbuJDlXuUbeGb99aRD7hbkarvA8rtM+wuNH4+8V2C/7coj4z8wDfWZOwt27ReKNMXxpxtw/s88yOGiBbimX/YHDz4GPzd8QOFHAryJoMd2nUzNlIA8bZENARqJ5+MtL/TojQLYqS996FB6KQdyNzcXeLV1WdaX9TDvFV1wjEEwcJAa2YJ+7pP2oXUs/Dv5S7ZTDzxgbBPQszvKpbic44YWkcfT/5gBOT5cqu/b1EPUo24d1PcE9kZXAH8s622XzwH56stqkjddD7Y3RyQfjhrKfoBPq1cHyQ/b4cIi0E/ZqclyJsnsHKSn+IobXG3jdL2YfzfKhtNeA3L14y7ECRt94O8XW+C/98iR1AP6df2H/cMefWkWz+gE6g/rVXD8ph7rs4VdMStP+y9+P4T4iTuib0yAH6MOdnUwvVZJ+3LQgH4Wm8cL6j22S0u8iCf/NR23+9wB+l7owsjqJXItDht+1Mwec/x2UDaYT76fgT1vLmeenSCOoZVFjLIz7g85jlX0k2fNz3DFI/wtt7V9C0DD/qXdODxUu8x6nCJnPBT50B74bpv2I9whssNnH9GTkzJ8DdRA/FhBD8mAqZ6BgPnSOBi4H30QlInj0BAbPR4GMGNUYDb6mhlwdaJ2bGyAj/2qn7MB8V/q++wYyeEFHjwlcegoKPhHMgBatgKB8K1yyle7eChEtEtPQVD5/GQQfLYBi0M1b450VD5PWTnmU8n0mQPFCvDgwOeYbuDp9OoPT3U94lOX+swKS/HNcY6TnprVlxXSrHzqSed8yokDpz8vHvcnyB7/OS/guoJ8NGLyDysAfVzN9W5oRNwuoHkLnYwdy6piyIPLpe8zX4mO/LwCfuqENv8wnWJl4tYu/dYmg2DNWlwTHRlPwsNCLuBQDsqGgvsa0CPehZ6nNeshn1HRupzAP+HiN+NLi6Ow3LdwAY+pj8OB/XNc2QwBfQZCHjbJDg5rfh7fkBk+AO8/lA76/GepWuUysFqW10o/zfSD5eVi2YO+qljbB576dNcABJwvzTtp+LHckR6wYSZ7pY4Q5Qf4qRHT9bJjp3cq+PPHZNib13JQzuA0jBhcFIeOvc83qmJNzxzg5Eo9vEk2dJPliEORFx0VF7kxM4FGWpmu64t1fmxPqmCHdUbV9IftAPGF6018CVXuzdBkuhDd+FzOnrEdrMDucLnl0sl8bcsjBzKXuGAf1EinYeD9LT7IRz3ZsAosnzogAg+mSwVug/EPTg45owZLhQfZP6ZvOftvUl/Y5aMVFFw+Y/L77P8pP26YNY4E3ybLmRi7SvH8E2/5t074P0Q9tPTHZoWZ1Ns2n83yrW55M8ND3Q9VfliuSA85vignJ3w9MxczRoan6SnMHK+RHHOc9Jq/Q0OVb3bmciL8T83iGQs/7c/A5F+gXVHJzMoLNX7i/Ofno8P6atkBTnEl69n1ybA7T49XxYZ6RkOCOvr52C07AugTKZYzaz9qWV51+RnG90I5Q89uHFOBfeO4iuST5aecfJpVNEzxSNjsmxmeduNw6LN9u8zxTnIy6FUBPY+LwyNkh4UZkifvfhAn9QgmK2odGRCUC9gULtyyL/c6G6LgkU8wsFYDnBfLKTvdPGqZc90jzoHTP9JV9kFnnuK2ai0cHTlaLj+1p07Hgkl48shbA5e+zwpAeLLDLGf4eGR3bDoCYQqAub6pPcCwB9KNzQI+XInyfvbBMWfejyF9Ghrn98eMReBM36gqw8o9U7X95StEFB6BgQALQi0itDw431p+wnJ+ETKw8d/W5bFDLXdflRNYX6ZXbfntXTk6qHJZYcvd5/pMlVN8ZuSi4X7kkA5kuFwa0eJyyqShpG/65LZFyPZLD/AslR0Vydep4mBIz3OBX8u9+r76ww6O8LV7MF0Jf1bUcvRgPJd40UGiphpRphcKoG9NWV7IsO0UsGYN+GouFxgRa+uC/NGUPx5BuPpPoMvCHNRr1BhTtMPFb5dB8Mka0H+fDw2ef44B/ZtHRdwlICMd9Y6JBh+s+YkAg9SQ+b/SC/lvdyXqRf0LLEdXdMD9/aWod6xL15fl4RzZ0Cxn16z0AyNUXvDjvnTVI4yZDJcnYiTG0x8Nr79lWOKnEQr4o/SF9b2cvLPc0HWgHoQqP6o4phN9g83v06JtzPe3CmAvns/H+d5x0KsPCtRrVmfV0wk5L5AN4HnZoNvkGeATySGX97T8lm/uPJ0vNxhCsMNmegU5DqaXLijgD/P/V+1AlZ3AN39RUZAroj93EJTTX5WN4luocq/eDzxzg+cdSaeeaXqKJ/ONZvhw/crJr7KrAfbbtjzyCMhiL+zLqHQ1YwP25Do35PnPnVFuObnkb4nJvwQeTE+iE9ejHL2UHDO9yuWj3g/0C0oPAuXepL7Qj9p+fD43CMr5feYflctyRn6fD7KHnN9XPsws+OAD+FsVkNaN1DMNuF4UMDG9GkVihgpN9QxVD63sjaJH4Nmk3rb5HJifuq5ueVMBONOhkUt/asXbSNBuC2byw3JPfrdUQK1IhT74RXxVeqgeKPvA+c3JhT/Y5EMDKuEcjIAHbn9E/orp0cal1/hgPxzngpzUL1PZ45rkO1BureI3lQHrM+FtZVdUesX/wPI4nxDiJ5UfNzDe8KJ8+kaU9bP7zXpmg0oX4hn2gwZQ1MGfDqxZJ2fqWfpR8N/cHlebn+G1Wz6JsB3HVJYPik7qbGUfbMYjyC4E+6b0JTBOVXgFnhlP67gNeldnu37dyi6zfL+TD3mkGYTqU0y57Rv0jsw86w2t+VNDh24BqI+HI94RMO5hCPANbhiSZrzraUz0mo+xH86Pu7D/2qh7gTelY8XetRv7fLaJRsX7D4XDPVbHOEfArH/B8LnikP8jjyNA6yvnvD+RtW6cgM2+QHqU7BbwyxHsZ3pgDwj3+BjsV6emDifI7WSiDexz+O2ZYNzgmxDAtUuMiRPw3ltwtHePjOGjkxvlndkA91cWF24V4H1P7PYaE71rD/AdLQPje4ehXhRwssB98RnODzwEvDq4UP4nxdifzufDfrFjRuC9P7hjmgv4ZgsCb/dVoPNfOoOOu3diP9emEp+7MuAY6h8Cvv/7AfQdcS/Sx0WivA1yRG9Ykq6vK4Zg/Q1wMCMTUH58IvY3KixGvdLkoi7XuVFfus+OqJ5chOP+DOR3wYVIf3Yk6BQXjanac2RPYZoH9U+9GYbylbtBl2+/QwD66GOo11mRCFSu6ox63PV/qNeVVyGAG+EBnme5QKf3lpfsFLBvb6BcINClZfQZ3/vlCDzxmfdTpG/Y2BG+V4By7nsY+zaeI/HvI799HTOq8L8CNm5A/R8ZZyYXqPeGItRr/kzIc91I6XDlSMGzs7APr+rh9GMN+bv7rqryGyO9b8uR/41yMYoMuXjCAxNR4vrV+PblP6+iPhcnQl5OwE+W5x9uAD3HDUE+teojYKwfbZwrYMoEfEN+4GfkN+5x6H1XN9LXbwB6X+mGfu48E/dvTTbVD96/dtNX4PstXUHfx5/Ae+fHQ54eegBydFUino+THQHB+AXux6wDXQ7ASE/Z8F/iAl1ohJHlhL59ZMdBenCugDWyQbnkLbvyA3wNA3L77SZc9x2GDq8R/2e0F0CLYfBia7QdEgfiGemQ7yOH1ftW55jzBPyyBw3dAw0wcv7aS5DvnT+ATq3qIBDKeUnlF3OVgO+2WtnhiJcFHD5qqlfcgXTHrcjX7Qb/N28p4SN4ylrM1QJo5gHX25Om7QQ3ZL57CXI06H7wpbEBPdwuFxMh+8cOtW2k+BLX2L3MCzn52lLuVb0Dz8jf9wP4PnAw8KLF/fhITsS5jdw/e6ss5+ZOKLec/eaAifwG6425POJTCJrJwPLXUzZEH5sO/p3lwicRY0dj8Y5RcpExt5y6f+wY/IjXi4Yc+VtugIyQfqGe9As7I0DXkX2gL01dMecI8MlFlYYNwntkH1nfCj8GPgPk/U7umCgB64pB755/qri+nW+QdHIj3Y6foOfkDzggv2Mo6FEmG7LLByD9P/LQYXbjH+Rz3DaoPkyXxfmQg7Ob4DwyA+m++hz694oMqMztOPxp6U68Z+6PZcFBJ1M/bZPPgXZHFVDt8sYBdp0y+P1/PAp6Nm0Ffv38U5D8nC04WCrt4MjpoGOD0phIASV7QM+hGciH4g2Wk3cKYB/UopjpGZC/vp1hV0dkwN+1jizZJuDtAsQd0ecg/7FD4O87dceZ4mD24xe6YE++zod+Dhmj4xmb8RveP3YI79892MquoD7F8pvdEfV1eVWKn2jRTvYz48eB3r0Gg47D+iM+6ZyKuG25aXwDekWeKfV6KOSTFtXjo3NX6M0D42H/v/kKem3Dj7If3707yB6z3Ly2RMVbJ9vPFK4SsMkHevwg4/rgOAZ8XCG/cc8ci3pbx7Gwm/7Fp9DRRCPNbK/N7YNtOvKMsF8PSz173NS+cVyxWsbVQ24H//xxKvD0L3Kl7QYrko24jdtfLjnD9A/Wdpnl8ulJaH9d5gI9pk6EPPxJLkp6QSLkt74BP7J0Wcl3AiqY0aMQ/q2c1UiP7rkOsWK6B55XU6VFVtSiDKoHwCI/CGqDBrrngFfBohFBkyMpVkDDRnqRHJN0v7XbumdbVgwjHrRfYMCB+3Xr6h7RwOeXCYoTvWtov1Q1MwD1aesykzsruVDvqSnfOj+1mmdAvavrUtNf6oNZuVb81PVS/GK9okU1TA6Vn1qMSemH0k+T1yxvK30OTBgqfoHvV/barvwE5q9niAQ8UPYv4LbtS81vHhFp0iTwRbv5q3RKrgPzCfe1xjtM+qLzs5B7s3povvLMjxi28mznbeZXWXk0k28zPE/3+9ouSP+Ma9rvVK1CHlBB5W8Dbus1KrTdtenvA/MJ9Vrhqf2DhV00y7+65c2Mjmb42b2v7T2vFvuyXAyzaVPYE9Ijpk/7RNDrzRW4TzPP5KHTyRFdpG8Vreij0pmdNR/UyI9F/GaWz8m6D7v/tNz2MCFR6bsa+YT83j8O9fB4rPDQdo7rSd922zxUuWbJdb4m9lg/ryY/o8uzaX/N6hXu+5Z0lPRRftTKvoWKn4qz1HugU3Acrp6HeoYcRker+F1dh5pPuNPT3AfncCjgUMChgEMBhwIOBRwKOBRwKGBNgaSLBHRJxUjonGkY0XoqFyOFnxdhJPQSOQJTrwwzOU6w/Zd1kadFCtUwAV12H8UI1Ms5oA+NAPLIHa2qzp+0uROwSv7Au/XikqdFLR0kHQpUDwWcBmr10NkpxaGAQwGHAg4FHAo4FHAo8JuhAGZEXZGIBtif3WiYRjbDN8i02N1nAt7I+81U2GZF1AgxGqg3/hlTdC+Lw9Rh2veYp8LPfcFpmNokqJPMoYBDAYcCDgUcCjgUcCjgUMChgEMBhwIOBRwKOBRwKOBQwKGAQwGHAg4FHAo4FHAo4FDAoYBDAYcCDgUcCvyuKVD7d137aqg8Ppa/qiNWrz3/fKzuusVXDUXXaBGY4tI8Cquh9euF1T3XF9UoUlS4xitWcKRJI6w+2bgRViusU6dkl4DDh9VH8fo5r3JI6VoLoFVamwioVx/Xt/fDKmxFIddPffyO1fnu6BOTJKDoU7PVIEOlH76JqVcvpp2Av3bDqoC7SrEa94H9arsnrKL3UynqEbgtQKilhp5ebSeDVbrbxQO/8OvJqVLf0ClUuTfUN1FYTbN7CuT5l0OwQz+VVi5X562apgAWyYiPxyqg114HfVH771Yfdo59OZ7Wvzf7omr/e623rj8vXhQc59n1a0h3ZUex50KM65Y/Ix7Zvkutpmv1XOFxupzVfupVjZ/M6muX7mbvO/dPDQqU20Dt1ECoprDQ3wyECQGsgpWYiG8yXngJ3yJ0SQ5T9qdsNmoVMyA4YQoWTXgq+5RBmLeruPJSLFu+4RPw5c2Xsdz2Bedq/HkZ7pu7Av/tO/ENycwp+NYmupXRVECrKCzbPyhNrT4Xcj15Wf0H07FM+fPZxvcCaJ+6cB1niC3Ue/XDNy/zFyHb2GidfSOxnMPtKVi84cJ4fb9G/nSU20R1Pnl6UkP1Dbd9sc0eXgb/lm6Q23mLsK1NfKLt952ENUoB1cGgOszQEKD9Inl7omdmwr8MNN8//GRj79iX4yn8e7MvqvY1VG9VfGXPVd1VwF6cZ+7X8D6t4suLJ3XujO33Wsn9YFd8YPW8svWurvcC7ZcuN0zx04n5Z053jYfzx6HAqUwBJeDocXkx7A0pGJhn5HLjkzJPZVqEEzfQ9ZJ4jBAeKAtn3uHIC/xeviLpKgFTTPmChueuzUjf3xOOssvngRH21rGgU1lZpRu65TOt4H/S1QJ2ynokOQ2UCmh0Mm6dbPtiF2c0cL7YrFfftPuik65GKaACVMhRr1SFDOzEqAzwNW+Ful9TZ8e+1AzlTxX7UjO1r3qp0J83qqw/lY3zoMcfrkB8cW1HVSPcj4qyeq7Sn6pnM/sVLnzDxb9w4ePkE14KyI20aeoj72dFIyg8cpTSGSNMZzRDz/vaYtzfXVpYJGClV48I1BVjS4MGY4TpSCk21J49D6uVnXM+eobShmDZ7Wcmoed3xBhs+PxRQeF6AXNzVLUs8+UNb2vXAV4Dh2K57i+LUN4f5QazL2Zh5KteA+B1y03YuJ624eINwWctxEbm+/YDn6UfAJ86Bgz+mIzCTwRMmm6FD/DfuQuK2KAB6HbP/dh4ulkZ6EEbNvOx3oez+S8aKjfI1fBoJIlH2Gig+xcB2QtR3hcbdYOJNxBPikN9dkVg9bwpE41mAiKbAx+iE79PU1A5/VWJGFFrHocRwEdHA89uXZG+UzKus7JAn6++wAbyPboYewU0iARfG0aK8TnjjPOboefv6dzCDQJ8PvDjqAG5Ca6vbbryfljW9AguweIOy/kxA3Lyq3lilY7p508Hx9GpI+jUZ0hhsYC75Yb09vUJ9P5mo0aA5fuiS2B41Qbo7xdgNcT5OTqdyR/gFR8PuRnUGxsv744AP+q61GvIn/Y35fIGD4b85+dBvtYX2ZZDuf8w+DygP+qj7MbzctuBI4dM9fWY4MDcszGCHb8A6RpKuZk9H/im3oL827hQD5r6yz3OXVKA9+xZqMehQzgPSYecf6Dti1l9kb5kO/AeNBR2arUXcnGdG/eblkFPHny88EMBNAVcTumqsn1h+l0cj/r07Q18mrnAv+wszQ+2z1dKefMMAT6v5kLve6ZBT/8+pHCTgCNHFJ/1mflM+hhwqKlWmBFw12CU3y4B9Sf68Sqc83PUa1ZyYXwr4OtvjbYCBo8EPdtJP3LAMNtuAnJbty7KqTq/Nb5yf1PwaVCQn9L224qfPxkEmzbBrvbsBzq1ioSclfhgT29MAd2eyir8QsCGItjpNrGQo7TBoEdkGeR47RaUvyBH4avOsI/dUiEHM7JR3rKcpEsFHDDA918M6A3ZG95fmhqwPLL6F6kXWVJ+PivS+bIcUSDMetd7CN5fmW98LWDR64X7BBwNFhSZgWNfBCcc+6LlSe0HW0U/ovJTZ21f2c6HED/ataecblY29LKLG3btkUzoxWx/HKMQkme7cZ5Ox/FWrz7Kr0HfZ+WgvPvHIS67zI3sBw6Bfp8ZDTwuk6sjBz+HHX0jTzdsTfTZOFdA+w6wH+Z+A/FqVCszO4n3Ke4uE2DtJ409Am682dR+1ReWp3Q78jWLn2hA4ITx7b9mBfGP4/v5C1GPqzsqugOf7H+Har8V+2GPO6fCXnZKgL3fsQd8+q8P8cnXGws/F/CtP55TGTjnSlGgltqAGoz2LkUuOfPA4K1bcD1fTg1sEQnDcaZsoMyca+wS8MRkOMyYBDDquSl476qOyGe4B4IyWjZMiwvA2JxsBI4to2znywIYKwO4IWnIZ3Q6AtU9Pgg8BQ51BCz/CIHAUzNgCPbJBuqTM43zBJR8j3Rzs4D3V16jRMBTz9nGR5GdDensmahvaSkChX9MQvlnu1QyszOmQjRpgvcfyYQBGjMe9dsvtwNqGa0DF85oQJoRLeCeCTAEfdPQYO/XD+W0jsb5rjSc70tHPT/2IsDtJKeS0BTXwwIOGciHGsTcMP7XNCh0bAye3ykD/0czEWg1M3C/oxt0fNOyJ9IuXe3SA/Wqwu/PQnIT3TD0d3kCz6hfI5cq4fgpwNdJAzjIo5+rjefZkFvrk3pPn5nut8kAc3k+Gi6kJ3JDcp0u4A/kgjZC54b0e0uB91Mvgs/L8pCc+HXcQQ1UdgAj0/BejMsu3VFe8yi8//bLkPcX5gHfegYMOE1ZttJXnoLa5nGko4YWO9prk/F+ixaQw24p0Ot70qEfjaV+k75z/otewvObUoHPB377cpkIFaKlHgTXF/pAesL2Ymga7ODkTOT7nQ/X3T2wb56+ms5VtS+Ml8uFcubMlB1L04AP8Z0DvlXrdQOH+UYNVO4QJHvKZ/pkQHVg8bkuET7Eg6e8v7wEfKOGDHfIPDoWjviRTARawzLsyoURJ6B7V+AVFYl9/sY8hvp0cJtix9suhI/ftu0MN2BJb6z42VCEcCqAS5F0p6n5zKdLE7TcM1+mT9P15PeemIDrlxdAL3PyoW/XJOt0gX/YLr31Jvi8wYvHeQWQk3fe1MkZ7w4udBBShyEf1HBle/6kxgP0SPOg3Cs6Ip+H7ob8TZxmtBHQq7/ON+CPlnvHvpDFdOzL8eIRbFdt24vjMwq4CiF+DNWest+bPF4XeEBo0KQnDZeArVv1/cA/duM8tsetoqFf5fyayo/1aMZU6Pd+2cCZnws7snwZ9NT8eWj6fAK/wfuxtuyHck8Qz7NfsO8n4S8rsF8/Co/w7ivwMxXET2yPqWOOjxPEt2b847jr0LtBdK+k/Ybdo4Yp29nR6YXrBIwdD/92SwriDYpL2I82bqDY65zDQ4FaGGFJbI/AsIULgnPgIBi8cjXuU9zDCvfO2zinyJ7d+gYaMKPuQ4PliA+KtddAQyl/ukYzxiAYOEj1IKEcajCyg28dazffsjkCCj9Gegog2RHPyFU984VfCnjbC/z79IABOF+O5F4uG1ItjMIlAn7l8Nb49YjE46hRuE3Azwft4oOeMBkXGN08qM/8HIwk0ogOByxer6aD2Z8zDQLC56CA9m403OdmQ9Ffy0M9Py0CndeuBp0feMDYJqBndwTSpB9sQFtEgs60KBFfb5GBdq6k01teNADeKED+X/oKNwp4KQf5zM1F/du6kM8mOWK1TtL1La8aYUZ9R47Cexe5gDeNCJkdLEc25IcbLmX7LelhVo7d+9yT9z/pID6UAXrgmeRaHlpuOIBcvEzd1+d9QqNC0Cf9ovzD/HpkIuj7nzzQ92cDPZxnxwYm19dsQFN6gg9FPozofrdNywHL4Q6fSo/7q1cj/+3qtiGk0JYc8hsU0DK+y73oOdy9CxmNnwKD/rdhuE/yynyvQF9XFxK86sV76wpwNgzoz/btkM+PiiH/633Q8zk50O8XFgL/Ji6UM3Ec6jU3B3r3k+Rr62iz+oJOhXJjecKP8ZwsR55m5yB/0l+mb9s4lLNvb5XtCzvS2z1oCH4h9W/vXsxQyc+Dw9vtAz16/xWOcNECRR9jh4AHHwOdhg8IdT89NHzVN8dud9ksAe/KEedt22CfF+eg3p4U23LBgUyERHNMptFCwMjhkMv0YRr/gD/h5rdd+w1/sn+fJT+5Z/z7bfCHa4oh96u8kJ/M8dDP+bmgW1tXQPWkf3llKfgYE4l0U8cHpZM39Eg4j4jSTA+Wv8Ol+r56kf3nWh9GbHNzkH9+rpRXl0oGfaAOTP72y9UM+P7tXviBFV7IIXU8mx2OfSEJcOxLoHiY2VXb9iIwQ3XNfjnvFXUposcTxo+h2tP9BsHPR1X+yn5q/64eyDPivGZSP6zjPNjxrT687vdrKtvj/QjNzGL89x9ScaPVc9v6zA05c78BfP4i43vzeL5stoB1xdqPW/lJNZMn0H6VFBIcrgO/XkH8xN8yW8e3gnsV8o9n8G2RcZKf7qBnJew3NzxvTIC9pA5xdXDcs0rGKwflzKDiIvXYOYeHArXQ87p+HQKiT71QlAdGwxGn9cb9GeMQGB48iIbnpXFwgD/6wHgy3GsEjB6PgC5jFBy+1n8TbA/5kD+N2HFPjo18VU7ctCTFZgcdOPWSpoox9JE9HMkdoRALc5FeBVAqswrOdvFhw3K1NDANDNT7mB8hHhHyX1ZQEt/S9OUr9zUIYOJdoM+a9eBLVDQabDSCBAMhRyZ2lSLdJ96g/NUU1cAHTD9qmFd4UA88KyDxJfDgcilgkkdZjoBi2YCgDgc+6hMhTA6bdC3LFnBQMuoE9DApxvZtps9OHxztZ0WBZ8hRBXIcQAddHvfEhqBP+kWTP2wgSU84QKxnkohuMz+TkyE3fv7oF47Tlwg/f1h//PWzLYcs9zRyxB1EsS5Vjn6fn+8pVfeBX7C+6ufco1wB3pBffz7qBR5xM5NflYjkmI9apvVVKU3pxuXTzALGr5ahp6JW1b5wvrFy4/bWLo2H+sPytcqLcl1ySlGgHTlWAcFUBhZnlidaLIvLaWhE3C6geQv9FsvFqmLIncul+coJzPWx8FMBr+Yh3+EDgP9D6bj+z1I9pVgXFPAnXPy2aWcibhNAM4vt8pPlrgKyc4cVyQnjX85u8icRQ0fBnn7khf9ZtgINwltTA2pf9UvWc8KD61POXjC/L3ZBD1cVa7/NDe+7BqCh+tI8UwQc+1IBaRz7oolSWT+iMwj4g/z8jingMS7LxY+h2tMK8zvBTW4wX52IOCyEOM/Mr52gKFuP7Ooz26sT+A2bdlLjBPusL/Ufvu/3k/q+2R+z+IkHaEKIb83yN6N7qPab5XB+PuKcq91qtWrY8+uT4R+fHm+GhnO/ahSohSmiERFoqJbIqUFvFyCw+NeLCEz+7mcAC9BiOdWom0cxTE+pYoH/h1yVtLYfu88NAipHHexA6ZLzowDSbr7qfXVmw1GuHBbATp1gSLq4y54TMCULDjtSTg2kb015SghdqwYkK1gjl55KyYH36/KbTqt6rpI9UBQwc49Vak+FHgIWChQ4vwYufT/gD3roqOed36epD9xjePWfoAgL5UjGqDF4jc5soL7ygW8ffAB+qRHwupG6x48VjOjMBsFPfl08N4DK3WfFpmumS7n76gV+3lhdGREeAXFxwPN72dCjkVsOaChQC8zHJp8jBgtoW2ZFjysKBURE4BusKxLVtUbQ7A/ThfjCDak6Zqkk/pSOp4iUS8f0p/oFNuR5ynUI+sT8LhfQ8rdu5fREYab0RF0HnpmP78ipoTe4lRzrKcmML+HPekffSquD5Z7KZzpQA4y/+bUhh/zt8eJcvNfZg4bbTXLkn6Y2sbwNH6KK0edAfVUPFD0D5ZH5VEt2yJSjE8sXyWcg/VV+6qzkUF0H1FfdhrySHSkVQOWpQ+kD14fKD5d94fzfKEaDhRwf26NyfOEGz3kug2cS0JRfVV+FF8tZnXICqR6YnFW9lbyxnK38EPapVHaAJF+n32Z+UPlst5Z77coF6vG3DOS70gs5aHcl7BW1f7n8KzrocgL/hIvfNu0MRno6sfQbZTb8BeNPcsJyXIF9DLR3bDfGpqNBSA1BlqfUHqDPA+mB1Q+6Zr5Rg5hHIhpFYoaK0i+SRyWf6kVl7wPxwIwPL/h5XzrsJS1ix9+kXp6ImTme/iqboLNjX4JIwjcc+wK6KPsSqh+pmKrS79I3j+qwih9ZD5ZI/2fDnjK+v+oGsJrCDj8WFaWK1efdBsGqtbBnIcR5Zn5NZaz8MvuxCjr2zZ7b1Wcrv2HXTip8OT8bflKlN7Nfii4V+m/r+BZ8aDxPFRPEP5V/YDwRqv1WBbDff8OL+IlmdrGd7X4z2kdveVUy5xxeCtSOiRbQqiUaEtOeBuM9curZoJ7YNzEtA/vnbd2Cb4yWv41AzhUHR/vI43DYffsgYH0iC2jemoZzshsjfDt+Qj5x0Qj07hiKALOsjnGWgFlPocFlnm/EawLauNBgGOFB4HaWK6a5gPeWQ4DoGwIW/CFDIxYJGJyO64hDOLtT8d5/vwLenxfB0f/jUQRSTVthkY9Z91jVEyMGX/mwf+OBPSj/8TGop5rKmiC3z4g2sN/kqmLsQ7hju2In9rNT3/bOn4ly60aCnm1kgP7sLNBx5/8kvo9j5PnGP0g6yuxucIOPvgdQH08DjCA3dcWcI8D3FfIdNgh8b5eI/Upp6jQboAHyfid3TJQAmtrBDZs28uP9OzOwr2KZ/Ei8R2/Q8ZmsEj42bsS+nqNHACG3G/tdbd6Cb51eX2xFV9SPBs6Yj+b0iHhFQIMmKOezDRGvCpi3APuHqSmnisq0mAgvhpLmQX0GZKC+rVzg15fFMY0EfPcd8H8oE292SUVg1zgS+9kWyZGlAbfi/T+4IX/fbAHdf/ifbX1iet/SFeUQ39iw7toNehG92RD2H4pyjtVBvd7M99cI/2JqCdi0FVMqL28Nuk2diCn8f5KLh12QCH2tb4CvB9sj36GpwLveIejlhwtxnTvXVA6/MghWrTZaCriwLd57fDrkKuWvqMeE8ZDrdvFm+gp6NmsKfO8fBTqTPJ4rYJ38Nvyux8Cvy13Ib/XHaOjcmYLaX+/G/S1bQLfz5UiRsi9GHejnQdnQGz5d1Rd8Ly0G3iOnI1BvUIp96Er2AK+hGahPnPz2fsHHuN+na6XtC+vTM/9Avpe3gbwMHAl7fKWUg01FhWsFZM2CPN5zL/B0u9FgOXYM+9Z6vYHyoK7RoCH7ywHciAzgTXzmY9m7kIfvdoCejz4GfpwVCTt8VWfI313/h/ca1MPZXB+R37mxSDdOdqjVqg9860dj0Y4pEwL3+VUdKqD/g2Orym8s6vaspT8B3deVAl8rf7HjMOh/603Qm/hE+MdCuYhgWhrodZ0bfKT7bL/u7BPDRyc36H5mA5S7UvqB9724H/wLeb7UBTkZmQH92D4D+fbMBL0vcSH/9VKO7/DjwXq0pgDy/s5bwJvsDeP1+BMo8fx4+IeHHoB9oU9TAg7HvggL49iXALGQHZrkt7hDhOwLd+TZ9yOIg+iTgoADcj96FG7biB+5wfbMZCzaeFmcpT29OoaAZgTyJzmeNNib1JuhB68tUfuPKrRKdgv45YjtOI+kJablt2dCzwbfpP1anIic3nsL/qpHV9iLXjLebiz98oavYD9uNX2OeOuTVVb6jHhxxEgzvxFzlYDvtlrFYxF5AmimD3dApI+z8pOIL94pgN2KlQNDZL/Y7nz1OeSk25+Af7n4iTtkvy62jG+5429BQ/C5237NP25IfvQl8qe1NbiDleIJ3l92/Q3Id2SCbfvN8kzxBDe0x49Deb0Gox7D+iOe75wKfi5fHig3Sn6cc+UoEIEA5s8ygLnaDQF8aioY3Lw5GEIjKjwyOjwNU3n7DlDFoeeCFkvh1cJKd5vN4Vfp7Z6rmm/SGQJohOFCAfXqqSlqaoqZ+uZA4ZMUK6BhI/0Nqnogz3bxUT05UJhatSDI9eoYsQJ+NKWPHunij8hpijL3bJ11tvFfAd9vC1xdUS9CcIlBQIZW9TDKkRW12mhANSp9mXSFgAmZUPizZMA0YSwM/Pcl+DYq9CmHZnQNmR68Kl8r+a2hv+Ff6QpX8sWq6lMliw16DSNZtDiQT8CuXYZLQFSU/tYv6A3cCJXuKhvV84wZCz/+uC5JQFmZev5bO4fdvrD8tozCaoM/H4I+7d9fXXTTI7jc43xmJL6BLtEdaHblQi+6x4EfzQTgDheSO16tPTgQrbb68eIb5n4qVH7axVvTlTsIGjdBoPPrUXwz+lPw1HWTjK38k8lrprdhp1pKvuzcZZrQ5IFjX0wIE6bbocqjlXwofleXfbFrL8JErqBs7NZXf7LBq1iXlQXGWUEZyxuVjfPM8qvqfVVf2NnQ9VmVbxaPqeeVPVvJZ2C+duPbyvIvsDyzawxoPJ2NDvbns9CwVd+ykj/hhmuPPmgnbfchvsrJMcvPuR8aBWQDlZbb5pGcy13oYaA51zyFib5t5B6JPyajJ2aBXGTnPW9oxTipT3cKJHUU8IRuoMIQ3qE7Kk73+oULfzgKR5/CRU8nH4cCDgUcCjgUcCjgUMChQHVRAA3k2rUxUrz7KBqiL+egnbSiAANPTSMxcOdOwGr1A+8OHPiqLnx/q+XUxtD0u29h5HTrj2iYXh6HKVkNz0TPQfYsjEB+sva3SginXhVTAPtyXRSPp5dfipHhg6WY2rBrD6bo0Jx852AKOPrkCIJDAYcCDgUcCjgUcCjgUOD0pEDJTwLKyhDPzXkRDdK6tfEpTGIcpmb/eBirCU/4p9MwPT357GDtUMChgEMBhwIOBRwKOBRwKOBQwKGAQwGHAg4FbFFATvGlb594MZZbujpzqG3R7ZRNhDnzlyVi5Dsm8lRbZQxTJ+rVwyImPbpgUQLvauwn+IPlSCy+kYiJxZTzm/+MKeifbYTcfrzajDFqdd+IOwXcJLcf2roRU5W/2Gj2XlXvq2+ege9tf3X0q6oUdd4XFNBTkHhfy67d0MO7QW6TtMkXLjugvi3G1KYIa+LzYiWHj0DeI2phxsVtqVgtfvaccK1RYI2Ik6ImKBAuuasJ3J0yq48CsCvx8fik7MJ4LDa5OK/6MDi9SjLTK/3NKK8d0KMr4r0Xc0Ktnf5mmNesuKk7ZlT6NhZ+JuDLkxYfhYqnk/7kUEDtxgK+r1qNOLXmZ0bWwse9j03BYhaT5aql4SMClrM/Ozp8OTo5VUSBpIsEXBCPgPC5aRC0PmkVpa3Re7w9Sa9+aFjOXwRcaD9GiwMKFCf3hZ0xAQHzFh8W83rrI23ATfLBtjV/SsY3BbnTkCypo0ny8N3mBkSrKATsg9L0R/3hK8HJ6fdIAV7t8JZu0IN5i/BJRnxi2O0Ar8751Scg8aNTcH7+ZTSIS3bifL9crZvu86IR/86HXj4otxt7Ptv4XgB90+McJ5UCNeVvwy53J5VKTuY1RQHtx3nbpGdmwk4MTK8pfE71cs30SjcouQITpiCOfyrbbn2C7ATb57/8AfHRnGnwK+1PfnxkF+HfeDo98FJT9WwkOH97Cvz5hfKTvppCxl+uXGV21iz/rTD/45HZF14Kc65OdgEUKPxSwDcbcfttb8DjU+YSI6XzctCQ/slnGzHelqNnKgJgn9xv9V0vAvPzWpbNFfBZsVl+GCml9Hx87cP55P+iR3OzD6uiXn8Drn9RO7yffAScEn6TFNAjDrwM/nc+Vclw2QG9iigvkpeZBf0ZMgD69lwWVvM+ZhSuE3DPeDxPvQF6Tfvx8kjqUy8qvJxzNVGghvxtuOSumqjkFFNDFIDdoo5lHvGjfUud44QUMNMrPROFGxbPTDphJhU9DLATeqYd3//GV9Erzr3wU0B3FPBq9xMmhL8EezkWrhbQcwD003zbM3u5hS9VHfSU/HIIgT9NHePtDmjbGe45p31MeTXfObMQYH+kp1DqFj83HAYNRmBypBRThWfPA4rU4877JnVxY6P3R+QqsFvPwcfGbTbj+afFKO+AgZHcaxLw/OAeTA2b8pSxQ8CgO4Fvc7kNwqTpVnggcNq5S29/cEDs8HdbX+DZIRnl5GZh+fXPvzCaCejZD89bReJ5iQ8jfjemyJ6qLGwTsKEokBUVT2GNlvso1ZMb1ZeWFn4s4PkcbJR+bUfk23sI6L0y3+Blzxe9rpY9R7r+HuCTFIcAcFcEtqOZMhHbUhw5gh6Qozbm4gFz5HtWNOjerw/qeUEC+PJuPqZ4vJaHEcqrOiL/tCHoaSPDyD2hI8bg/Y8KQO+5OYoueioPB9KDemNbmt0RCHDrulQ6szN6XLvLfWv7pIAvvxpQ7DF7IJckBwMF9Pfg/gnowwb4qC5Ob5fAd4bKfXn3KTnOMSIFHPwZ+0IGyw3quz5IDlQBqH+njsC7zxA00O8eALonJWKK04B08P3ZLLx3dzros6EY8j5nNuj94Cjwv44BfB6ehKkYhw5p/rA+3nIT0jU18P6shXBAG2UHBuk5b7vRORXldkoA33fIfW3/64M9+Hpj4ecCvt1oJaeqvtg/ePBI4NuuGco/YKD8h8frdPIP7EJbF3rSB3iOfz4nB3Q7eAjnQUMNHjlc64X+vO21xIu3v2rfAe97hiAwejUX+tNT2rftEcCz7mbQ4/0CbKe13At5GizxaqHtzvF4Ej15BsMD40D3BmXQh5cWotyunZH+jGbQK9ofkxt+q1Yi/bCR0P/iItB7SZ5VvZRdQP5+edZ48X5z9u2Afk/+0fl/YRA8PT3wudk15DtrOvAnu6IO1ruLLoF/GSFHVonOPIVsfo5KZteeq/SBZ+yn2rQpVle8rSfofUEc7GTxFvip0lLYrfffxT6+R38x02/Qt2Q78iH544BwtRf8uk5uy9a0DHL14ONqey/b/qaV+NhBfeoQ7CeA5+JllvaZ/TatHh7ob9mPz85FPrT9BM/ouGsw6tUuAfX4QPNB20Ne1X/gUNDxyyLYoz/K/ZRfzILdKQq2exZyl3SVgB5yX2nKj0fcd26BPk6fWrhRwN69kJ82sahP2mDQPbIMeKzdAru7IAf2g/bhZP/SORnnWgbsavZCpAv+hAP5h9H+Xis4Xr++mRwpP6H1ggPSE/hbtU1eW2FRg+0p5CFb2rG+Hsgf7ee+V8Dy9/D87r+Dfj+Wgr6znzn+05pgebMbl2i9M8HPzN7r97gDi/ppOb4k+3mlgF6pkNO/pAD/LNkx9pmWMyv5QfzWsjnyuVPuB3w4AnLx6gKce/eB3FGYxPHL/AWQr5aRsMudb8Lz3FzwbZNP4a3jEZbzJBknnfz41TSu430+yf6zHikszc96lwEzO6HiI95ntKHc55bi9noCGsr4/GHbdk7JvTlGeBL2eKSNQXBFh5DjVY6L6BMys3YN06e2bDeZ20fY1XoNkE9wPAZ93Lcf8rf0A8h7HRXXZi6vdbYAAEAASURBVOi4lu36xfGoR9/esNvNZLyULfVjfRHsypUyzqwgzmE5//sQ3U6QDIE8xMYi38GDgUd+nuJbZe2rFb/tPidLLg92ZC1kQ8qdLBXCgENY+REC7YREBMJnyg3rZ841dgl4YjIIHpMARXluCgR6sj8g5YbhpCdBiH/3geH0eGAQ6kXi/XeW4HmKvH/I0D1FbNBoWWdWyG/lN1Y28FD14/fmPgsGrPJCcF7JRXmr1sNxuxbjfop0dDRFjQXy0gTQgxqYLLjT5RRRlXm5Myt2VCs4yO4pMIjj0o83iM0iQcc0D9Jd0REB1EN3I1CeOE2ol9GmV38obrdUlDAgDQ32eyYg375pCCD69SuHQSX+Pv0YFOVnA4o1MwuO45VFaHA3aYJMqYHK9R/uAZ6jZcO0uADv5WRD4FtGAe8zmqJ+7y0F32hEhXtOl+Uhv2bWuHKD5K2lyH+dD+c1PizrPeOFKtOHDW9HWa+4ONRv5nN6n0ILudEBcUBN9BQcdhzXdQS9Bnl0MqbDFYnQkxEeyFfvFJS/LB/3p06D48zKgn68Xww5ucUDOR40VNOZA57lH0k6zwDd98kG6pMzVblITw1TTj86HSNgY8dDnm6R3+bekw4+NW5gV06NOAHduyKfqEjwZ8xj0J8OblV+4LmwSMBWH+hzsBT4356GAIdGnosF0LfJvA/zFXHIv0BO6bbWH5RHhlvJLZ+7+ANZTvCBG/QYOw7y5Q9IQO9WLqzWt8EXiL++Zn5+6EV97x+H+1u3Qu/flA0Myp8Dsk9WIxD/cRfq0z4OfF672ja9dcGnyR9uQNwmA8/l+ZB3shfxAlpE2fYrVtVl+k6T+9VRRw7vJz1lBvg/Jxvn5ATIE+2TbaHf4M+FfSAfQ9Pgt+hTGG7AfefDdXcP9NPTV6NnlS83FMnf8P6o5n4C+dmwz2zHKvC3LoOA5JDl8+UloDsF/GyXHh0LeXwkEw3TYRmoV6wMgIakQR9Gp6P+e3ygR5NIXU+bfxBAUQcU17dzCjoq7xmC8sjusnzk+UfU2I8+IUcUXl4APuXk4/1rkrVfYn1+JBP2Ysx44LufWh7iaOnvIMEN/2+Y7K/O0ILfx/sJG/y0sKdoSKqOxMZl8N+pKaqBDzmn5ywXw9KxJkX44pLK2ntNL/WH/VAHFxr2DaVcUcOV6fmkjrPsyo+mC8dtUS6DPynqEIeRoa90By3izhuTVQcsrmmfZrYfF7rKXhCweYtCU593GwTvvF3t8atGoIp/rOyEyp47UO+QHbgrC2BHu3jAl/627dzxcq8y959PWjzCRYQQr14sPJCN9gTb/RPYR5Y7GtiyisfOMwhKvke6uVmwx195jRIBTz0He+xywT7OmSn92DSkI//J5axaD72gjjw+ThDnsH2tSw2Yig5qoLJcjEyDfY1xVdm+VlRMJe75G6hcgR99qudLjfTA0H3shQJTzyenS5Hn+gZ6rEbdhwDriA8V3Ct7pg75FE5qGWacDzbA/edzwaA+aWjZHzuG6+0+nPunqPdRbmICDM2reXbxQODTXPaoXu2GIaceR2ZwshuBypIcGJwz7oeDW1MMR77KCzpkjoeBn58LAaERH5MDBo828mUF/1iOlLwv6Tp5OvJ7YjroSg1MBCrNkP/f7sV7K7wwlKQw3GO/djXo+sADxjYBPeVH7ERG7slrEXLAoNFnwZw6CwK60gs6dE0FHcjPM360ITEb7rxX9HsxBsHAQehpmZUDulCDiOnaOhb8S5EjGEWyofHdNtUzg/rv8On8TP6oEQngc9gAnQ77IC/791eaPown9bBywNQrpex5AQMHQv4PHtQBMz8/gdwwXS44NxD94ztWaAQk8ODyF72ub/MMgYlTMHK3KA90/EaO3L+Sj6k+b+aBPyQfHGC2bQZ527cXhqxPD9D1/PMhF5fLhlcLXQwC1RsTQEcKONXBcrSqAJcH5YhncZFtOWV8SF74GJNptBAwcjjwTR8mH5ifWF+enQ0+R7tgeK/tiJ51ashzB9qqYi0PHJja0B+W70ULdMFM5wcfwwjQ8AGQxwIX6pkn7cDINLWoFuh8XXLZPAFL/QG0zhB/ZD5e6NFGHxx5j15ouPywC/gflR0Gd/SBYz4/Hvl/ugU9piXbbdM7oPxT/pLl65GJqOd/pHxThxg3RM6OtWvPNV/MKszl3OgG3fcauiOA5Yf4ws+/2AI7S+7PSr95pOGAF/hRg5T932TZcz1bjvB7vbB3beNs2w3Ol/yNlZ+wa5/3iy6Un0nAcCh/a2wVcP6FuOt2l80S8K6c6UIBOevt4hzg70mBPSF/w/Wk+nJDYYbc//zh8ehQIj8R6sHlZGSivq/nH9+T/+IsyP0Nbv2Nosqf7eQrS6FXMZHAd+p440wBv/6KwK29Gx2jc7PB99fygPenRSqboHOY7K9tfis/YZefdu0p10M1yMvVkkdM9paqO2GPS+zipxAwOzP+a33oEM7NAZ/zZVxYLs4KVX5Yfp+ahIZvZw9GgppFwk8qPb5Wys25LtiF2wfDXz06aV2SgLKyQLQLtwn4+SDun/z41dLeBSJodW1iJ3S8ot5ne/lcrpqpBHtAM0eYXyHYOSX3Kt/AM3cUnYR4JNR41Wa7pmyOgMKPTe0jf2r3ttcqHtP05gbvERk3HzW0fLF/uN2DuPsLn+p4gv3Nz0Mct9sHcvb+K/TmBHHON8IjHNgfSH7ELatXg6/b/Y+ral/9OVXpXx3Lt9mBF8uRq6g4NFialMGxU4OWRzgmjlP5aIPNAWQjdTv4zIFC7gtwOA9nwsFQg5HvF8lvC0eOQ08CjbRyj8T6Yp0Rj6hcGmeJB7/XTo4MqhHiqY+rqZHKAETcISBSTknsZKA8XZoBx3dIjqBSYGN1sIL/Kht4x3xByRmvi2UPyaxiOBBqmMgDASw1DDmAoTMCIzkiNU42mD+RdFJvVeLM+Z8Xj/reKkfOR44FXybIkQLKlw3T0aPAw6ycQ/LbEqIPO8jkZORzLPgFVkyiD+cbITssgpNZ3uERksaRIdOHAwXVoXSjO2KAgLZxKG+LDETpY3Hmow25MUOU+Ub15/qWS8QzAo4dhWEpd1/9Zfk+4oODVTfpzIaLephlgKAXXeL8aQo036epwTxjYWEuGgAZaToHpvf8fOCzeBECwltToXfXy5HFJ8fr9DblFPK7exf0uNEA6OX0TPAlLR2rGV97mQ6cdQH4g/f3yal9FKhwPUcOQQC6Q9Z7/Cj9mk28UM+6dVA/9TZ1hAUezI/HZkEeV3wUMUIAdVQxPd/LNwtYArPBdXYWAu60NLx/jgt0+Od4BM6D5ZRumvLL9vWFHJ2P3XrpF07TPxyYkL3g+pIeckBhw55bVZfpOTMXIyfD07CP8+FS8IPszU8CXnsFHZOXXGpbv9leBIsN+Et+gcslu8f6HqrduMbcT9i1z2Z0YfrSInRsxxoaEbcLaC57rGgEn+3BqmLwoZ9HZ3OcfSa6VfVgfY6VubR26ew2GQRr1orxBOM8smtMP5cLU1WHjoLeTpoGPJetgJzcOwodHVPlJz7ua8CHmY8hcFuzHv768otQzk+6oabLDZP9rRy/b5EzWMz9reqIt7Knuj52/4QpLqmqvTdFl+VOxVnKP1PqEOVHdRgiflzvxfu95RoW5Of4eC0HdmFwGuKV1nGQq8c3muKnHlRX/KrKq+kz24lyfKmUnaugEicpHoE9qFcH+llBuXyL/A/7IWW3Q/A/JvYx5HjMDDWOO2LjEC+Us5cqPdOfZoKy33El4PavCyzjHPV+4Jn5QP2bLNeGHKCggRqe8lwJ+xqYfyWvrVtabBg6ueHA3s5HwLhYDvl386gAVzdMObD+h5wS5HdsqOgZTcHAqCg0bL/bBsdTIA3IvGwwZPIMlLcwBwHm09lIN3eeric3TGzgwd/4fBIBQdzng0H65xjVAIy4S0BGOgKWmGg0GGrLgEmNCOlSZUO3gvvlkvBf2YDA1MDarsDHcKCLvajvfekYKbokHiNHlydiZNDTH++NklNpv5INlg8+gGCqhlPdSN1DyAJG+LHAWbMXijxVNkRn5CIAOHIIgqoUV019qOPvYvncIIjwE4I7JOiS+VKL1d5oQIulMB7UM66m8nUTk19r1QJ/qX+E32tg3UBlOaT0HFjUD6BnCPRhfAhPzoe+zeIAcJEXhmxRNuSzUSPDJeCTNbblJojB8gYHiERH5ks5frCBq0UVkgePJBFd1ME9nREuOFb/bfCL8GcDRfcZ/06dkK6Lu+w5AVNkAylSTjWhbxsuE0DX6uD33vCC/rScONOl+80YQX7Lq5LZlVPk/7cM4LdS0rPdleAzxcMc4NM3IVYH02vGJATUt3qQvK6hp1yr95l/NvSH6Uz0Uke0mCRPUzsDDtijT1YD/4+80NvnFkE/s+cFJDe/ZL2fNw/8vt4NPrWLQ8PosYnQL5rRwR047d0IRKlDRB1266XSc3kkB0zfcnJiYgeUnYD9oxHcUA9uSNaV9rG2oaeyB+YTiA83DMvZC5Ve2Qu79ly9Z3ZW9Wa6zMkFHzbJRdUSztEzL0i7Q9JvliPyC6UCavn1iAOEcvoYar5WfoKf27DPbHHLtimyKH+L6y89kOtS2SGQfJ1KB/08zwU5X+7V99Uf5jfV2+6h6B/of9heLfHCz9IUa3VcaBDQFDUeqaUAeKeANWvQsTY2HQ2hu2SHV2oP1OOBdMhxWxfknj6h4Bk9V/8J/Ka4ge0I+QWzI1z2t1L8tuYnOlbSZUfkCewp03V/Keod69LVZXk4R3aAl3OvVvJm0/5U2d4r/6X0RyGu/DM3pMvZ7VDlR+XHdoj8PL8/ScY5bxXAbz6fj/O942CXPyhQr1mdqy1+VYiY6RXkOMS49FdqieBQdkLF5dAnojvHZeX8iXpB8S1UuVfvm53DHI8gfqBvRdVhFa9W1v8E2sdQ4zHVYcR62cil4mSg/UYx4rKr3dC3cnEy6ynZbf4Ejqb82oxzFDmCzlw+8Zvj7Fry2+Mq2NegAip3oxYqtmOXPBtocOZmw0BmZcMhzMlCIEX7VPG3ESvfx/0FOSh2/iI4lLXrkc+SAjiMH+QqwRSAscF8S67uWN9vMXkK6Wz5zdAir+qZg6K8MAsObVkOesRokQd12MSj8F0Bx8rA6NHyW7veHmSzdSfu08gpG0aiA597pMBhXuGGAlOgyYeaEtraBYG5ORX3/b+4Hx0Nh0HfFrGiXyPTu906JTdInp6Ea+o5ZgHb8CXo+sQ0jIBl56D+7+ZD4aiHm4fe33sX6Uig2HANkosBXN4R+d0oR0I7SsFOTNTlBv7h96mhwg59fjYavtOmAJ9dPtDjYdnhMCRTv86LSQ29Gz28f5WLGzR3Aa+B8tui1/MU/8D/rz/BFOVly1FOExccx+A0vaiILgB/0GCnufV8/NmN882SL/QtJXeI2KVP93Fo+F/igkPqkQa8Zs8C3oluOKw33wCeF1+O+pvLDXpcP98IvCr4ZYNOi0OxAahvoCOH+Mh4D5IdEPQey8PQwXAUN8mZBOdI+vRNAZ3pW1k2aH9w43yDG3qyW8oB9SvwSPAXmyAXHeUiKBe7gVmq7EFOSIRc/p8HfFj2EdJv+hLy+84KyD0tFmBXTll+aMo/H//JxvmO/mjgFvoMXqxo1fsygekJDWRazInp9b4XCbNnBb1gFy8OUIYM1e/vE1+/0VR5s4P1n75hZL1dnKOniJqlD7gP/Hftgj69kQODPyv3+CmNc6Rez8kKeF3KgbVdgDwkuyGfLtmR0S8FgfuFy5BvBXaAGwLDM+DYXp4ZVL7JDb3dATvg4emwD9Rw+U7AuLFB+suB52A/3Vnehw7X9oLpfKbEmxZ1sGnPLUeyWd9ohIQd+LPym9MVi6BXWzcndRTwRKaeYsV4mOs39ONMOQJJesT+6tZk7RfYfl7nBtn+6DZ8Atq2tbIb6KD4UTYsTuAn7Npn/tZup7QDgf621sOwF38fD7s3ZRo6RP+ZCT9zfQrs3t2j4f/JvrC/vkja8zvTYLfo0w2TQ9sLfl6B3DGdJ8pF9a50o/xpssEwTcYZvXroKW7sDzu5k64QkC2f0+KJLL9P5aI+KqAam25sEfDgP0D3xgb0b06w3VD4h8v+8vYccZb81n7CLj/hL6YD3RPYU9az97zS3rsh5x+uwHUHaf/VJxODpuP+CeTNrl2tpL2H/reKRr26yRk/iS5tz5g+/eWnNxRnXS3gRmnnQpAfxWfuCPzPa5CL7YYYrzc2LZgHf/T2YtDjWx861he+pl6zfT7J8Sv2bT+7NfCpQK+4geTpjTiKFjXi406PKf4ug2DHDtS7nJ3gBtp1R2HXSe+Zv2TneJEe8jN8dHLjPsUdbPdj7cu9GUIs5ychHoHfH6SLtYpXeSCLPnFifMzbNYivyL+Y2Uf2P7RoJsuxjXiM+bdOTrFV8VzmFMQfb81AOW/moB5LlsI+03ZCXE6BV38SFmqcIwmDeIHKZXt7ro43YWcbycUBK2FfNeHD/AcCGRurtxmwyB+OqXmUWU86FKZuXbP89PNzxWe5ajEef6Eqf/+div+pdGZ4qLd0eYmCNfRNwilygO4to8zQUR8tq/rhunbtoMDQLAOL+xBUPz1AJxpJDNOhGu5KDtR1mLI3Tjp9mCAkx6eY3Cj6aboynn6+YWpt4yY6HS8G8LQcKaZFz9gB0aJWlwtoF4/63T8O/PF41HvqrNKra3VWcoj3GjRQdkQ9D/Ws9Nnue2Z42X1fpUPH3EPjIP+0+nIlDz2jJOB91ItmkqhVOgOeB16Gq14qX1WuGX4qXU2fFf+VvbPCRy3GgQ6tl+XiS02bIp+YWNCxfSLk803ZAUOLuMkD/A6/focr30C7g3z9eh5UDxP50vrJq6ZW//7k6pMa1Kety4y/Gk8180YtYqL4JWfiaLvDdpnyM6m3os/JPtvltxU/db145ou1PVX5aT2Q8ZSyN5Wtt5n9CRW/ypYf+J5d+Ql8z8zeKTsTmN7uteZ3NcWvdvGySqfxDpO+6PxCjI/Al/DHI1b1t3qu5MLMPlm+L+kKuvjtdGA8pvJJihXQ0DTeVnqo4lz13sk6q3prPa8h+0pj+c7hUMChwG+dAqpDAyPIu4+ip/BlOYV+RQF6/GiVbB5ZcCdgFd6Bd5t9M/pboRcaNPdmYGSJtg3gHvcjBmaMpA34rdTzt14PjPB2SYV8q43m1Ujb50Xocb4kEXJfrwwj3cHbHv3W6eTUz6GAQwGHAjVNASceqWkOnB7l0xwZ53Ao4FDgt04BTDGlxYH4G4OL2uBMy8fz1BDavoWneJQZv5eGqeY3T9Wh1T556jQtwsZTWGkfWuc4rSigV7nmKVo3ym8VD5ViihR1PPBUSFoDkQ+nYXpaMddB1qGAQ4HfFAWceOQ3xU6nMg4FHAo4FHAo4FDAoYBDAYcCDgUcCjgUcCjgUMChgEMBhwIOBRwKOBRwKOBQwKGAQwGHAg4FHAo4FHAocNIpUDuwBLWoRExbAb16xkQJqNegZIeA/+ll7APfq+y1+hgZ5fXrVcIHrYIlDyzecmtqTCsBP5UCj/371fNT5YyPoePjY1oKuPa6kh8EfLWxuvHD3P569WLaCfhrt5gWAnaVAp8D+08VeqrtdGLOEtAuHvjRqnJhPk6V+oa5WlXOTusd61WdOiU7BRw5bDdj/T7biWC9tZuPk+63TQH1rVFMnIDuKTFnC/jlUMl2ARXsT1nD5FCLWMS0FnB7P/ibIu2Pqore6WKfq1rPqr5/qvjTqtbDeT80ClRXXBAaVr+f1Gpxspg2Arp2jYkWcKmMazf5YA+PHrWiCBY/uiwRcX37eMT1//U5ccOJKefI//H00d+gIpCPc+GbnRkT8E0aNRh4OeO3PlICd/zrlb9Sq0QhhwlT8A0YLZ8ceDQSy17cnoJFXGgD9Bo+VMClV9Xi1U+Jbry4yjMzQa+BNfcNG2830KsfvqWj7X/4oI3a1XFK0bNjIuStc7JCL+znGqovDDFt03KqHvzt5ZgR+AZ16EC7aNrWW7sZOumqhQI1Jo+8T9st3eBP5i2CnYxPrJZKV6YQ3jaiVRTs0qA0tTplZbKq8J1TzD5ju5fqX81X0eaU96cK0d/JuablAWSuhrjgd8LPkKvJ28ssWKq3weJv+mlNBt527SHzfYVlQXo7Mk7/3DSsddEnzYkbjufEifXMkf/jqUVXcMSjMvT+ZErg5DLvannvoBereAPlXSK3tzhAq7Sc2gd6mDwe4N0rVWGr6cfbduStUPdr6oz9w3ZuRo9M0qkbENYUgU5SucrwgO4vBne4nKRy7WarljPHtgQ/bobc/nfz8Q7EOrfTTW+ta/TbTHGqyCM69L7YrFfb/W2S23atThX7DL68UWP+6nTxp7YZe5onrGl5OM3Jd9qijwGo1rHwF9s2q4qoEVV0JAVvA6nSBZ4R/4zP1PsYywRO3ABCOHoWKDEVX9fByGn3VPRw90nBhsa/GhCkMXuwwfSk6UnDBPRIheD9UW6wvHMLNkSfPhUb2u/dq4pJukpAj1Rs+HqC9LzxNs0Y4J4a9TY1mLmhFxsLfAYPxgbB+Xm4LpEbyA4aim0FVnsxAksbpvMqpU3L0AP+4OOFHwo4fFjtD4ZtNG7riXQXxGGD5uIt6CEqLUXP0fvvBm6vgRGIbqkYIZ2RDTyW5WDfxAMG6PCLge0qCH/eZ44asDyy+pcU4J+VVbhewGd6yhjoeW1H4N97CN5fmW98LWDR64X7BJhPqUADIz4eeA3qbewTsDsCdK/rUhQ1oyfwWV+EBgtt2Msj5jSiyWcaYOfVL7MXIt0XG5EP7dfK/BrQH3Q8oxnk53m5gfqRQ7geOBT0/rJIywGvljr3bNQzfgHSNZT8nz0f+KbegvzbuPAejeTzxsddJB1nzwL9Dx3CeUg6RgI/KACec3PM6ltp+eF9+K7qCDm55SaUR9so8uq3sxaC//v2g99LPwC/6yg9ytB6xHJ9cTzq07c38GkmN0jOlvJB/EgQcGVHPPcMgTy/motyeqahnL8PwWp4R44oPluezzII+vWC3D+RCzwfyTQ2C7i5O95/I88yHxO9Ve+B/jbqeZFosjwwDvRsUAZ8XlqIenftjPxIvlivC+Uqu6tWIv2wkdCb4qLCzwUsMcUb+ts5FXLXKQEzDHbswfv/9UHevt6IfL7daKWXRhsBV3QAH9OGwA49Mwl8GTEG9fhIy6OmyyUCExpZ5x7mQYNxPlKK+s6eh3PtOqb6w/L2YhbwrtfgtJHHo6JmwTPD1JRag0cu7xqM+rdLQP1Inz8TMD9H04/3YzO3U8a3Ar7+1mgrYPBI8KWdtE8HDKtVfGFPaf9bxrfPkMJiAXcPQABH+s92KAR+c4ZhsM9qv8JLDIJbu8LOX5MCPXg9F3bvXS/k9qxoyF+/PpDzCxKgP+/mg56v5UE/Z2Xjfhc37D/ZAbbPs3MNHuktKTEOCLitL+jRIRnl5QbYqTaxyCdtMOgdWQa7vXYL8FIb3ysukn9kPTgF/SnbXZqpxf4tpTPqpfzb2mLc311K60ETrPSiHjb0me1XCPHKtWIHwvr1zehv7BHw+RdGKwE9usAvRLuAXz0DfFLxzOJlVZYHjmN27rLSUzRooqOt7FfhBgH+qfOqIQS8e/VRcQHkZ1YO5Dp0OVMSZxrfMF/mRKC8P5ci3mkciW3GHh0HPbnDg+fnx0EPsmbAT+zehefm8RDkZKtP789rob8aX5ZD87hQpbOyc1Z0Qz5rvDg/nAk5OsOF98Znor6bR8EenDMNHYzzFho8M+aMBrAvKSnQk+UFoNv7XtjJo8HbWJrEDci3XBxQX3jq9wsK1whY7kU8PdgDPFtEqngK18G/VnyBnTtBnKr8LNvBL78000PIp4rXqmB3ubz5C+HPr+6o5B96nv1vo5mAnv3Aj1aR0JMSH+h/Ywrq81RW4RcCNvjbF2xn7cc9wZSs2Tu1IGhvLUUF1/lwXuPDdhMzXoCgDvBAcTunwDHeMwQEjItDQyYvX1Uj1PTqvYrP1EDlbTBGpqH8GGmAW0sHPDQNijE5E/h858N1dw8UzdNX58sCPy0L6eoYCNCnzIBAzMnGOTkBDao6lCDg+Fnk+NabSLfBi6d5BcjnnTd1ap4i0cEFgW4YifvUcGXFfHKaSoeAJ03S9YqOyOehu4HfxGkIgHv1V+kDz3CMtNE8NyDfW4r8n3oRDZllMlBvFvBaMD11zxgHzI9kIoAbMx5ysF8amJbRKK95FPjx9ssIxF+YB0NEDpG353g+G/jHygbXkDTkMzodDnKPD/LW5nGko4YWB0TXJuP9Fi0gT91kR8k9cmpJ40j9PivyopegqDelAp8PCpBPTrZ2kFzz4PrCgduXH01n5uvyjySdZ4Du+2QD9cmZxnkCSr4HnnOzUM5XXqNEwFPPAS+XC/WeM1PK3zSkW56P+qxarx0K408NVObLcA/OXfwdB9yBUJcIH+LBctwrTcrjRNBvUQ74OKLKU9NDridPNf7Qi/rfPw612boVdHlTBlZjx6Fh+clqdIT9uAty0j4OAfHa1WZUAP/IQDP/RqcXrhMwdjzev0UG+CRnjEfjBqHpJTVYFH9YLkfLhmmxXx65Q6JlFPI9MxJ0njnX2CXgicmwUzEJqO9zUyz1hxtO5KB+K/LIdH95CehCHXfcMHh0LPj9SCbkaViGXTtlxAno3hX8jYqEHxvzGOSrg9tUTrqJOQS1uHSj1nUyQBjkOT59CPzmwKDq9lmXz/V69R3YnZ2luD9PdtQtXQG7QQESH08/Bvv8swG7ODML9HxlkaYj+9XJ43X+3BCd9KThEkD6x/5q7rOQs1VeyPkrudpO8cyqpk2NhgKemIB8Xl6A93Lygec1yTr/wD+nmj9VDUJusHiXAt2ceaj31i24ni8/mWkRaVufWaLs+xtNJgv6o6HoWgw6d0+BvI9Lh/5EGOB/Mxl/hEEebOqppf1iv9VE4qVrawD/VrJhWy4uUEkqKWda3s3iG7anzb2gW4EX8eODmapYyDvJNdv3B8dBH6KibMdDKiOb+mvb/9i1c1Z0446OLd8hDliQCzqU+lDvJ6YZ5wqY0xx0ud0DPl0YjwbiuiLo/2Uyrrneraob8pn92Xt+f89x4SafzuegiJhauYz9Ajb47+sE+GObL8zPE8SpSk4t9FAPfHHxVdAztjuH3oWclZN/5l9UK9ihFBn/PZgO/lyaAL9JYSDL93R/+0I1TG3GPQFkPGUua6kRRjiywwYE7rAPIzO0GBEb2IxMNCBezz9+xObFWSDMDW79DWuo6U1IgZ6J1avBiO06FXq0C+XG69QgZUGaLHt0Z+cgvdcLQ9I2Tr/IPd83uhEQ7jV0oMuKsFGO0H2xBT1ee2QAoN82dL25J/GYgfwPl+r7KikbvLU+9GTk5kDx8+VIVVuXSga69U2TjqYZ6P63e0HnFV4EFBTQmh0seClyJLjIB7p8t0316CD/HT71uhk9jTMF/PorGkzt3eh5mpsNOr2Wh4Dj0yLkQw1mpuNyr+pBxP3xU0CPvw3DfWowMF+IP6zgM3LVyEXhagGvevHeugKcDQM9qtu3o9yPivHeeh/em5MDxX1Bjqw1caGcieNQr7k5qO9PciSsdbRZfUOVH5Szby/K79MD5Zx/PuhwuRv1bmEULhFAdGSgAU2Wg6NG4TYBPx/UBp47Sr7wqRkHkDeaGcABwG4f6NH7r7LhuEDRx9gh4MHHQKfhAwJH+HU6kz/Qzz+4gf9eH/h+5RXQ+3VbUF5nN6Yenucyycb6NhtacmQ26wk+UWDAATPpIctLj16Qgx92Ab+jsiPgjj5wQOfLEY5Pt8BRlvgNRCCGTNcbE6Bf1EGiDpbjVVL+DsqRteIi0MeGXnL98l5R2RkxAgYOQn1m5cBuUgcGy0HrWOhDipyBUd9Aj+io+9DAPuJDoLnXKJsjoPBjU/35Uuz4+bb3tJdHNVLFBHS7y2YJeFeOOG/bBvotzoF+eVJs2yn2PxSg8zEm02ghYORw6F/6MPkg6KT1lxtOi5cFJQiV32Gyz7rhyeVf6oI9fE/aX7KzrDcd2mMkZecOXE+dhfNKGXB3TYUeEV14pJo6GjnQ+5kUC4e2J/81CJrJjs+r3Wjo9PVAjpPd6MBdkgP9vuBc9T6ev7IU5cZEgn9Tx+vnAX+03zxV/CnPPEpsDzq1kB3hBw5Cz1auxn0KBNmvvfO2bX2eXUawrljrs0W8ohu+3PF8AvqznT3jfsQLH8uZJe9Lfzl5OvzcE9OrLA9bDYLzLwT7rPXU0v/LkecAcTDUSCPu++OCwHShypltu8Ed7PsPBZYHf0sztdivU3x83GEdD4Wsv9zQsOF/QrVz7IeC9RN6SPuj8/MDhyCnZYaKe7RdZLk9cFzt+YLptif4foh3QOePV8P/5uXAXo9M058Wcn2vSy6bJ2CpHhCruBhrvljJKfTq8yL45RPoIdtlsoNshytvd1H/LbGoj1/+gef322B/1hQj7lzlhX5njkdcM192LJRrX4Qa91RMyBq/W8sSAzaEkm5Ga5dOv8kgWLMW1zRCyALsckGwQkivMzT5IwP9oKcssNRQDDz4PtkZNvDlqsfXM+XUpeFpmJrbU075+9UwfhLwmj/gDMy3stds2AgfNjzk4NTBAczFsudpVTEEkRpcPFXxrgFQkJfmqeRBZ843ORmBQAV04OdUL6ZfRAP9fgA9EfAcPIjn7muQX7xcLGvNevAzKhpn6rHhBkSsS+Wn32c5KdewP658wiPwYH5UgDf4GtRBAHpQw++EB8khH7VM66tftyk/mPJXl7ln1KUp8GyIkjuiAbVQjiiogFjnHvyHy4uNA/3K6ZFKyfpDIxVMF5ecghpIN3IkVTpoxgHjsbgA8kiLZ7Eh21wEOflGdtQMS6t0MaHW87iCsrOAV1oa6ExTeJku/xwPug1OR2Cc1ht0ysk57vWKLlje5+fj/atlR9qtqTD01yejAfS0P5C2q5fQo6MVFem/d8gH+pIdaizg0jiU96NP6ztPYRo9HvTPGKXfNdGf34w8Mp1J/pi/DY2I2wU0b6Hrz/RdVQx6uWTDzNpOYYrZq3nId/gAyMlD6bj+z1I9pVgXFPCH8alAzULld5jsM+xuu3gEKNEuMfGTp34qtNlvfbbB+F5A8+awk+fJDpwJ6ZDzOS+Y+gmVjzpz/WmKK3fcqoba1McxNfif48pmCOgzEHSlEY69AoaOQjkfeSHHy1ZAT0nPwn0wXU+CP+UR5PXroK+fyob9A6NBB7I3bCdnjNP+LlR9tulvIKch0J/5RH6Cp1we8wWRmxsQVZCHEPVUl29iv/Rzsz9mcUEl5Uzzi8s7QXxjho/ZfY53bMRDnC4E/bXpf2zbuUrSzazapvdZvm3EQaYZyAfcQfjYLPjrIeMiRgjoJT8pfC9/XZKAsjLTbOzyRWVgJqeh2sGq6pnCx0z+Of8K/BLTi+wh079ceyfUuEeVf4qd/TVixtaR31LWd2k8mVFLvAiwaAqsOi40COibAG6wEIF2ClizBgY2hPQsIIQGG9oKBFwRnvHzo4serdqGUSqgln+kkRlM+TDe5dLziAnd5/zm5MKhbvJhxCPhHPQk2di+ht8nQeGe30aRGHGkqSmqPFW+ohMLCpUbWD/01HtBv/vS9cfjPLJweSJGVjz9VTZBZ3aY78ipoTSCLRez0ovdsKEjfnLTqoG/wRZAT3ybQT0v3PCiqW08EnT1n0CfhXIEY9QYfIOwOBcBU2cPAuWb5Iirqv/wIUF4cg8T8SnwYPyIP1yPcnxnehE/FT3VeywnlI75WI6v6rk6K3lS1wH1Vbdtyw8bhk6dUO8u7rLnBEyRDalIOdWSvjW9TABdq4CBy23kUnxBuW8UI4CjhhKnL8cXlofzXAg0aMqvqq9CONog8E89xzcbF8jFxdRULpXYf8bIKTlIlgPqGeVvoOfmYCR7YZ46oyHwbBYC3EEePVXGn9Xx/xSdA+Wa5X+JlEsb9VS5Mr3mySnj17vB/3Zx6Dh6bCIC3uZS79q74aC3+NTrlmfm4xte0IFG6lnOut+MAOYtr37frl5yvelbUXV8bhBE+AWZ6U2XPDWJOkz4TB0DfO7mAV9uTdUjJhzw/iN4inWg/pyi8qjIYHpWesh2hvSXG1YrP4Q9pillbA+Sr9Pv8zXpA/sX+gaJvz21tlPQq79lIN+VXilHVyJ/av9y+fTtsNmh7FKgnQmV32Gyz/g2/MOVqMfPPsht5v3QT5pCzFPAxoyF3pJ9YDpPlZ+8zMiF3tC3Vqo+bFdpZg7jV7ZNkUHnx99cbXodz/f5oC//HKPsQcRdAjLSEQ/ERKP8sem6Y5X1P7UH8HggWJ5VgerM+J4C/pTtK+kvN1RLDMjd2wVoiP/rRdiJv49XaIesz2wvbcQrLoPgkzW26c/0IzvDI+K1XRo/9aeq8sD5fOmxq6eqWH0OtF/6gckfpX+BcQHLeehyZtduQK8o/mP70EAuGkpTedVaKGzP1QAD+W3WExvxEK/tEIL+2vQ//9/elcBHUWT9DmdQFiIEiGMgIyqwHhBEBc8M665GBBLxAkUTjpXTTVAQEDWJuBziAnFFDCokHCsqCgEPUI5BQDkMJIsieMCAfAYFMQGUY8V8Ve9fVRN60umeZBIQq9/vNz3dXV316l+v3nt1dJVjPecUN6q3NcNRzmyGT5kH0wfkhzd3q29qST/HuKFf65ao10jfMLmEP6duw69h+t/sN4gQGBnctB58fOKFXM9YiPo4a64/Iot/TsvF/LpZTitUDyuud+FPR0YCR4aPWf5JLpn+ID4ZrubDAk/YBQd+jzm+M+S6JqYgsG/dSIEOHw5D1sqN/Ty/2g0+FwuH87EnsK/RhcIR75mK90YOy/uG0/at2K902w4IpoPwtN/SiCFIx+PB/nO7dmN/zEYinSGpMNB1jmEfvaICVJShU9GQCy9yRXAqLAb/A1NR0DER2Mf1w9V4n31jRxUxJRWGt1e8i44hqdin74KIwr2cmGGyOMDf5aJCDk1Fxdk3Den2SEPFusyNeLcIPh9IAh43eFwtOW0U/Hy4DPjd3hXvT3gOybIpjKSoxozG/pRsionpcNXgtHMPprC1vQDvTx6Hb4RvTkC8l8RKhQMcfmmP+wPFVMM6xyDAH78OfHLmoMFfO0IoItFQfCnL2MFp3XqjCadWLfDehKkIl3AX8B6bAblhDSJSjEOSkV4zt6sRp5UrXNGc2BQyUmCjhgG/1rHAZbP4dvOh8SiftkIO12+A4XgwATDc6EE6u3ejPC4WI9EPDES8Ri3Izy+ioTd4akXlB/HN34Bzz65hCzmxkTwoYOH4ecQiY9/sgAKRU0Oeega4NBDfELz4FK7bNoeC7jsU+4xd7cH9nfl5n3LKzMI+ZI8OB74eMdXu5EnsQ+b1ui7itOJNOErnnF94gNNarxQTNeWeyuG1lxGubgTSW70a8bBFNMSB+30GIL3rPbjd4RrgvGIF5JBNdZbhLeotyi33Laf5lPEV0vHLL8h3ezfwYVPDaUrrrm9Qn6IigO+7uYXfcfp8u3zf6oz3botHPchIR7z39Ef5DeoNfRWfKPMJuS3YZFcvIY9DxZTROA8Myg8/QT/FRKF+SHksqcWXpjKaZT0PB9gdA36enoD89OoJ3J/LDHubU3O3Vf0BvuwbQZK/AQPPFHm0wh8OHsOH9C7T48Q30zt0LF0OHL4VU1OfGQ/90CwCOF0TD7350N/xXngdnOdNt9RT5JC3jEa49JFIp0ZddCjWjcI3VZPGFn7JKbAnHvLHtl8ie3iTB3qL2UFyEOI7Iz4H5U18vDAR5XuFG/xUQD+TQ/jOMti5fQeA1wjRAB8+CHwuE4tJrVwOeb80FvVvlLBPl7TCe+cLe8rkkxbdmC1mFiQlQ64Sb4ND+Pat4Perb3E/NRXlN3oc8r9lPb7lfuMt6I2n05Gu1BvnhaOerS3AfrcfefFe4O8ZY09pv8emTcD3lBdgL5KTUX79emA/8aRU1G/2TSp9A7jiA8hhOfV5URgjNmOGyjEl3c5fwTfTH4gR3B1i8cZA/FEeH61DOY0eg3K6StjLTQXQ7z5fpeWB/JAFDyOdr8W3itb1FOldfY2V/jLbESkRqiFo9gto/+SVy1AuDw8NVs6g11mHDMVbjt6g8tyxHXqnWxzwHfQY9E+zluCT7YZA8dQOR/5enAK+WuVY+UN5Pk6F36GeHCi2rb+0r/jOHc7szzWCH2s9h0V2MtKscEP92/YZ8jlmBPJ3nQdyXlwM/PLFDKvI5pDfJwcg/9d3x5mNf1DHF2s3RHLaHoZ8DhD+GvPvaL/1tatRnx64E3j6/X3Yf/aJjThQ334sRvg6xzCDY95r8rnV2XWI0+69lfVT89ZxOlQMvr8vttWDBHAl9C51PH/yBXBka+5Qw5/h5ua0pTPkcWg7yEWbWODDFo0kO8NmnFFHAGtfkB5j96k8mF9Mz+39Hqt6aYXzGXdfzgWXPVJqpM6C02DDW0RT6dvyI2Y0xN+cpa7pI2JXNBRj+1j0SL23SvUk26Qst+uwCeb4Mfhgq8FV8AD/UVGyZ0te20Uny1FOHVPlK1eNtIhA9vjIcrYIdtbcVrhSxs85R2bMasqgnXzI8laLOMgIHZ7lyJvky+Fr1R4s2HzKfJkZlfUy2PwivhdmQV7bxSp+aP/i1mIEelQ66gtzSE2HDG+6XelLOSIl61+wEUockK/TL4/B8m8OD/zDwzGTJHBfTomTnZ5Sz8UMBZQfWyztNB9SH6tyI/7YaqdBHlKv2OkN6HH/zAqznMhkcb92bcmXvC/P6jmNYPvjU88lznIGD612zhoEQR4yX0G+Zhk82HqL8H/14NOfMelK34h9znF9owe7E7w2y5xwZeuzOT55bYe/DGd3Dpk8yPKmXQoC66kdHxV9rvRDkHLmVG9IvlCvatZEefr3MZf1V4Yzn1FOkZF2/pCUc7v6K+O3kmOneq6iuMn0zWeJi8KJRpibRtnl2xyP3bWqhwQsW1W9gofTcrGL3mk9DFU9s+PH7nll/R67+KvreRljxdWVdPWkg6mQXRLR8zN7CnognhfbobCRLuppuEyMNNYpwVSeJzKqhzudikZAI1AVCEgDinp/8Ff0JL6Zjfq/ajV6ihtEYKqipx1GLvo+rBaLqQqmdJwaAY3AGYkAGgJs2x0aOW/rxogF+3adptQdKMII2V/iMFNivlj0b6X3jMyMZkoj8DtDAANIw1NR3zq0w4yXEwY+5Unq8zvLzmlj92zze9ik5rP7wNTHr7Zj6tjy1chtiyhM2WopFq3ZQLvd5RVkZZ3daOjcaQT+GAgU/sSppARTlGa/KqZm1US9jxX72f14HFMax/5TN0z/GHKhc6kRKAsB6InlyzAVd8+PcJTbxsBRrncepjLOykIH9qZPy4pD39MIaAQqhgCmstYXnwYwa01rvIwdD//9+PGKxfrHe0v7PX+8Mtc51ghoBDQCGgGNgEZAI6AR0AhoBDQCGgGNgEZAI6AR0AhoBDQCGgGNgEZAI6AR0AhoBP4oCKhvUOW2B5jism49No5l2zHoo1wE1EfRtAz53Yl8MxAjauZstcFxuW9X38MzjU98xH1NJ0ylqheO7U9We/EtQttYyGFEBL5BsF4FsqoQVIsf0XLfd9+F+pCdHer0zpT8hjpfOr7fFwJW8q6+aWlgMOraDVOlt+ajvu70VXUuK6snUL/YKvVUj2PbYEr3u8uxLcp3e+2eV3X+Qh2/VTmGOp1QxScXXUH53PZXfOv52Xbo2w3rQ5XO2RaPXJQJuN3RFVOPX80+2/LpND/Ag227hG1i5H4w9q9HG4x+PGj4ON3aHX6HbztWjf1iu30EoQ2hFmOi1Vf/Go9tV+Zmn2n1uqrbC2dafkNbytax6Xp9KjZswx1xnMOXE7k/AQ4I2yhaH2UioAyqfEqLLD0utq95eRY2TK8Zsm97pYNotZqbZMN8rm4+zelbXUMBx8ZicapXXsPiNV3iTg3fKRaGN950/9RQVXpFDnnTSPDRL0mu4lY1aVZ/fq1WS62a/P1xY/3d4Gwl7/X5zry3d8PiMXMX4tugNrFVXaKV1RN4n63KTNtCxMdj+4imYnuwVWvsnld1/iobv6VdsCrHIBO0jD/IeKyCq22wqONg2ljIF9vXmOzpsk/QMXFFlcuZFX9n6n25Ki34GzsJ25w8H7Cq8JnKf5XxRfV8eia253v1TfgVo4dg+43v9mPRq1feRAfIPydBL3y5yfieU9enTl1Es32FV42taP7gX7DV2Gkf2Enjwd/TaSq+ENVrFV9l/1R1e+E05beq9Z4V7LpeWyGj7ztCQDqa6HF/VRkEGNILojFCWVIS6oaMdKSQ/j2JdsyeLj7t+DI/R75eFNt/TPQrYnNAfV0lCKDD491VVRK5jlQhcLbgjHxs26VWRVc5rNo/FdUT0MMfr4K+vk45nLgfGWn3vGpzVfnYg7ULwaZY5fFTAQxLhb2aovQ/toFrbLtdR7D5OdvCA7fLxDZZP5ecbfkLNj/QT2y/WNMBv+znEnSIdFf+E/RC72Q5YqX0AW2TdF+yKZpquwS/nT0479xVbQnrhAiBqtZ7djDren0qQmGo2GyfONrotX9/9ODkLkKw/9uHKQ99B6IHim3YS1Mo2AbBtLFsoxiMMD0zAu9364rw18fhOjMzbxunrflQCM2iEP99PfH+Je0QfnkuplS8LdI1DCiO+ERMAb2+HcL/UIwew2986CH7cjuman29XTkiJ3mIewfgvbW5xpecFr6jst3CYNR/KHrMWjdEz+3PhtX2MrIBip7d99eA/1oGzjmZ4Ct7Pnq89hUiP+3ag78hYmT1I7GR+rxsyYdUkMCzQwx6/g6EGb9wmjQOqwbe2gUbBM9fiPiXZqMcZgq83vXjRYr1guiQ8yn2iwUf/frjfKII5TtzLqb67T8g82U+o8KHhwOXR0chXw1L8H6sBzht8QLHtInA456eKJd6BuLPygZezaMRT1J/lF9ECTY0/nQ3ws3PVvv5XWYwurOrcZjTtQmI950cbFz90cdGU053dAHuUWJDYzYziOS7SORv23bw2XMApto83Ad8sA27/8epTwrk7KVM5PvhFPCztQD8z54JPh8fhniZ3PzM6YmJCidKz59f8DfrP0ZDTj3uQ/pNI/B+oQ843ZIges6Drl+o72w7Bdo4/qFk8DE2HfHNzMEIGStP6sF8qD/Sb90Oz9coOUa5sn0caVsGph/O5fRFPvL/lwTcfzUTU/WY3jAdduWE8lwupnzb6w01FZR60pMGAPcXJyI/Q0aivn6yGvHOyQ42vGQf+F3aBvWx173Ap6Eb9W5WJuLfkm+HM3Dx+WS88iz3t4Oc3N0L8V8Vh/LP8cffjkuiA1zkfsY2eg8OGttvjuyAX94VX7T/4X934fmoYdADTJ4Jb7YtAB0Hi1FPMqfC0F7bCfIafyvqeU4O8AmcGhwyPUH7dY5Kh/yNEQ2f18X2QgtzIQdsZI7kNvA57NC7i1DPWcPWyp60NBi1vwp4JA+AHXwrB/qkRxLk7hGxoX1kUyv9ifdr1kJ97DcQcrvei3Rv8OB+gxLE//gE6IdbbkN8gXYB+qhon2U5ktz0ToY8Vdzu2OGTd5jTr79K+ZFn1VCgkdIxKSiH34TeXZQLeVm53hbXSIPR7V2UvqEpkft3A/+pk6GPjh5Fuom3Q/6auxGejdSS3HZJgDzMzEJ6x47hPCAF+DB9t4XTnGzJv/kMHNgUcqo3FZcDpLP/gNJL9MnQ7beCjwYGcMp6HX7K9u3AsXUb5GvzF3n5nM5Vn2yZ+ZTXjvUX+RPsExyH+lTF79BfkA0x6E02U4rkgU3oI7s663XgwexvJQ/ZQAV+ve7AJ0OLld8ko0c5frQK8pAjtiGMiQH+9YS/98SEvI85HT/uVE/L+K3O2O+zRyLq+U1iBiMrRhpJ7eZBuba80Eo/Kztqo99l+tDLV8ZCv7AZk8c5fVUMf2PWdNidtu0t5Zn4+tcO8JsUDj6roL1AGQ60R6p+BCuXodJ71/CdkO9ItNQ71C5iesTGv8zbwOnlbFku8mxXrx3XX6d2n3Cx96slf9V9FlN8WQOVHOWhSVAQLjcYuSAK54eScH4sBQpxgxcG83oxZeq9N1FgxwylaEjh/HsK3pO/L4yH4WZ2gww/m5JB+4wtWIih9fr1VcOUKsKIlLzNnJ7MQLy3i4bGoylI/9xwCGxSMvi+shMaeGMehkIaN8Vozume3kYMp+5dEU9kBPY9HDkeFfEqj+Qw4HyRwajwO1TEOZnI/w6vUcjp+RkB4SnfdwvDtyIXCj57luwZRv66JeK9Pkn4ZvXRseCrVxIM6333wdAuew+OyFYvwi9ajfx9+F5AuqHmU264Topg+hzjAKfnngVfrnbAYcakAD7MN+j9mdORD9bwo+XDn5oIeTnfrYITbk1Fg4c5eCQf18Wp5/V40/a5sbh+cz7ez85FuV/rD0fl/NaHuL+/COHnCgfk/VVQxG3+i+fdE4B7upBrZhioARkh9sW9oRPkqF8y4mG/NCWNKXiqL0PEFMJ7E5C/pbm4P3kKHM1MMeXoowKU2+3JkKN+A5FuGfmlfEqHNkEYbjaFnBygy9tBnlhDmhyYqUHXL/D3bIbKD+V34r8MN6c9e5C/N5cgnc/yUc7PPIl6+nQaGhKDUoFLtGiYDRDlNSIF+SsWU/XqR6h0zH9sygkOA2uA0WGvNxCOOVSEy+Bk8DdCNEwLVkOeWD2kjcWbRAYbHvl2uxHv7Okoz0lTgA+r51Q+67aAb6bwST7KwRkMBP6SwzDnJeC4zov8LMhR8dNG9Q2Yx8oPB7jY6D01tYgc/DLkHQkF/lIHxwdL4ajcIxo84f5wR/jXnmz/SKrXLdxwOAMbpuqFUOkJcnCnTQZuR0RH5rwcyPOKpaj31s8d2xNinDVMpLzRmX2qQPllZpU6bJrch3TL0Z+EO7OzZO8GJgHPZ9MgZ9/6cN09GXo3uZelXfiRW7TlCyCPgeUYKrsTHD6qdP1/aMr4svdRHzf7cN7ogz2e9goCloPrnwxGfa9DOcYnoAPy0QHAizUoCH/Z0G3cGNfdElB/mN9A5XRuhNJT1FGx8DU8vzUR9XaNX19QxwzriCv3KIdfh3KA8mHfUJIcrPgE9u35acjnYdFA/df0ctko52HQ+ovicq5PIRfnRdjJu/TzUA5Pp6HBPTIDcnAkDFloYoN3ORmt7CNqYDyQBHu3VvhbXZJRHr17qeiD0tPqLfWHN3OooUPyxzpEjnJ6THSs/uyTAW31s41+V/HIBhrZ+74pKKdR41A/hqeg46vPIIS3k+eYnqgnoW8v2OaXGAxCLqnDpPL+Nux6H9HOKEfvSP+N7FAZ/iX5vw2t/SJZYKZz0PXXoVxgwMiBX23ip7oua8BxWC96LPepdHF/Sz4EmfU4kkPCesDpWCZGvN5djYr1hS9vO6fXshFuTg4Ev4VbRUgO2+QsCPZaL8J1TYRiYnqJRmwaiW/+bmkH4JijKw9yYNatxuUvYsSzIB+KjjXs6H13Q7z3j+HoiV3lhaJhipMcAaH/jJFpRmNOQweDjxRRMWVi/rNa7IgUyQkDhuxXI28vp6O/+EOKf8Tn0+PyNnF6YxHCswY5Ce750Wi4fLoehmf0aGMvpx7i43zm4NH7jSPydnI6cQINupOiR+14kbpvSjjkfJKhT0hEOdY10LAb9hj4P+ED/4eMK/M4hUlgFVfouZQVsVsycJiXjZEj1sNEjoLXK19AT+EeH643i3KWT0udqSGw4H3IkUuU6+QM1aChDo/L3ZDTlV6MsDO8Sf6uas+XRDCiP7sU8rGhAOePfAj/7FSMoExKhVwvXloqZfyl9EuNyP9gMBo3KW8jp4WivL8SI50LcvO+4PTeIsgZk0eSwxYNrfIrF28RjlsB5GGdFyNTaRmQo3k5Ih634s9UbjGuAABAAElEQVRp/aKGw9Ff5Xtq/889BqOLW+G+x1OSxWm5GEHYuxfpLc6GA5WcoHAlOWGONBnsaUI/PJGB/LF6bjoclxP1CO//AeXmQG9QuS9aoJJzGYz69oMey8oG/8zRo/JjMw2CDU/67/5kvLdN6LtDh5BP1oNMHRcHfUj/3ruwGE8gzqqeKkbxRzl4ZNg6elDve4l6E+dBg2dJNtK/pKVjXGz0nuKHHKQy5N3Ep7xU9ZgcuqczoA8GpKgefWpI9LkX+uPfYoaBfNt/DrWegFwePoQGCxuZo3I7ckzya/fcsT2h+rZwvsoJ6YHHxyOdwX1w/2+iw9Zaf5bM5LS5ADixekT16VkxUj4zG/LK9CQ1XFrEKP1Pjk4pu1CYx+h4LUu9Rd+MhcDukN52YG8VMKf+kSNQ0G/HhV087kO+jhyBXJeDK8nzoFnQ2+/kKjwomVezUH6dPdCbdcOBxycF0E9bhJ6fnQ35eOV14FvfDbkYlw59MScb8fwkOjhkR/2peaGrUMnB7BJGRw6Dr553IP2LL0Y+2npQ/o3LYMDhrWD1V7D60aG/wL9oN+qXHEEHX3sPOgznzEI5sRl0ZEf+m+8wV6EPRh3jM3IwwvWBF/WRzWggu9EiJmg9bcUhzZRLFh0m83OUHFO9Xqr8H1v9bKPfVfLEf98k5GeO2M/3f//D85s74/zGXLv6l/cJJ28s8Ah9e8E2v8HKZaj0HuGcmmard6ge1K5l6V8WcE/uuamqXJz+Cbb+OpULmT7JR6BfLR+frnMNlTAxqPxWdRuOHTOE5kM22Mz36ZrJPTW0/NGjwC4SU1LGih6c2a8ExE98zMuFourowZD3nYmI78Y4KOoXMlSyZLgvFSMb6wqUofmc/3uoD9J9bS6mdry1CBWUORDkCLIpRiRQb7yvVg1TEYfoDzmux3zgu44Bxcx6cOGIiBFcNtJA4TZ5Q5Rq8NGY+aSe38tjwPePPoUrNcRGZEBBpQ6zTIgUSUexGi9reJO8nGQeozjIEPgv5W2USxnydshgNHAY5OATYTCWroLDzuSDKjCb8kTxRrnVFBwZ8U8Go8+2YhGrRo0QjqVPBvOkTwZTZyqfMvggR/5kGRVFvEm4nQiMj/hj9eIUxcHeITksIx1y/Mu4T+kfE/FUoH6pDJr+UD2KjoJc1jPC7ufUyO8RUb1cVwB5cLvV21SuDEd6XkZ5qoDiT7DlRDg41RuBUwpPTZ7VQ5Jzhhv0nXU50oulwlO5RcdAL13gPjVedkXywkY8qTzdYsprQCjrG/Q+W5yO5LexG3IyeQI6TP6ZXjKNU8++iH+n6ACxx8Wx3rOSd2uO8YTK5405qkHYymCU1JvXVuPQ5R501G22djhDrSfs+LV77tCewK6Y5f2kv8IGqz9JvvyvKzbpPqvvJFel6rsKYPpjVY7kEIfA7jjFx8SW40uSp3JwJf0RLaIrVQ93Gow2fooHTM8SDkxPAdeigPQpnRMBt0+9Ifx3owYzYBaHHb8O5SDsbk61xcyYnmKmWFwnNNxeFzMowiyYcHA7WP0VrH50mM+SWZx+ERnxXIvyaeOGXt64BXY8MspBjqonCOHA6h/5s8x/C1ZPW3FJ9ShOdDyUqvdUTmb5Z5FY1GvH+p0aape5ga+/wwXv7/ahHOqIhpU5/VJ6TeYH8iGv/GfUN/+1/Bdse8Eiv0Hb7VDpvWD1jvRvrfxLiYvTc5D117Fc2PnVTvmronB+i0cAsEsqCP9tCATTJyQwZShIcvhK3SdDyq6pgErdp/gni6lL03LQsDhxTDVkKX410pkPB+BdMcWNbXdDFaL7bWoEVwKCnn8vHMfHUtRHxjSloW0sRvySe2OI/B+pqIhrvchP66vhcDM/nHpCr7xKRhtwlgJH+TjHLafs4v1aS1V4aggFjiiiYSoN3TAx9XCHD1NK16yBAyId09oRamSB0mMKjHrWzolAjyObGmp1hIpPqtiLxRSXbsmyo0D1IJJBeirFig3jIKd1nwJn5ggQvok9VHjKF1P41GMa7lb3SXEz+TPLFY1AP5mChjLreCA5S7wD5Tk6xdjF6eO1SO+oD/KSNkpNnaL3Rz4JuapVC+8x+aQRxZr+9CUjkg9zRwsp2hrs4ztxULw1/BWG4gsThsB/W6VHcl7qvkzHnF/Cq6aBelKqHsl0K1q/KJ2SvTIahQ/d+CIZfBaJDpW4G2Q4yPlFbpTXCq+6L/9QQ4Pxa3dUqJwc6A0qp1r+Lt3PDUal6iGN/DAcSa5ZPST82Ld/8rALT/K2REzlZR1nNPWPfVstD9JDDB8ySGzKL8n3b6oBLHHGt0SRYoqxfJmd3Zw2bYTcH/ZhBOWfI/Feo8iwhzilpmAk1RWF+O1xwTdOrJoSP2ut9Z6UQ7O8SxbpfSa3JJfsLA70/DMHhurBxAzoqRdnQW4X5shwludQ6wmZEOWHFS/lh42kmQ+r5w7tCRrkTJ7kQduLMb0ij2D1J+kVVn+KONWIkNFAz7F0zHqDyqMMu1BuOYbA7jjFR2XA4g/5GQwuiq+uW4UiHMrBlXBY4kU9iPN3BFHHCJtaT/aENSj2c9q4EXaA4WnGT6ZjJe+SIeh7eRV4lvHIJxWVg/MMRtcTKkZJF0/JDE6TMqEHIsSU5FoG9A67lnyZ7YDkw3wOVn8Fqx8dyntYf04tSqBH2FR0munS8WbUU/atOMnvsJFyZpb8ZlJem7Nlda3CU76ZnFH5M3/D6iC9xuSO7IRfv6ngUn6C1dMqAtMfKukPxUh+jyQ1tZX4YDMuqHxLqS2Leu3YryX/cbEXenpYCvy5GDf8zBs8sA9/jbfVazIb0h5UVXvBIr9B223iNwR6L1i9Q/gwebLyLyWO5rNVvQ6y/jqWCzu/2sxfNV/XhIB29qDgh6SKinzMRcf+MFTYoT1hSBq4XRdy8omPpAf1w3utY10tOOVtgID3Efev97giObEpTFTxa4uPqkelwpBc0goV4/wIxBMTBUV1RDQ8MpJx/57+uD+ot6spp/hEVxNOK1agwhVsQrq3d0W4Cc8Bx4vbgO8xo6EQr4nF8/SReF6jLhyqulF8yQuj5aSxhV9yKikxl4OrOSfWw0mC8tQzUKQNmiJc6w04MxypYh046LqAU/MoGMjeA8HfyVrKgUU8E2Bob7kJfMlkWTwkqIvFoh7n10e8Q1MRbsfnhXQELiIQMj4vNBhl/RsOkzsG5fT0BDievXqiI+O5zM3pnHb5zHgVHuT0vxOuZpx+Lkb5TxjpOp+TnDrcTmwnE2WgPL8+D/nrfyvkg8lVDKeVyyAHDw+FXF7vQXrniYbG2oK8PZy8K11RnA4Ug98RokNi+CDguWw14t/2Gc6jx4Cvq9xIf1NB4Q+cfD7gOHII3rvJ42rE6avd6PDwXIP8/y0e5XJwvyuaUwPBz0OiHtUV9ej/voccDBmO8DERSG+r6EEe1EHl1+1itKUz5GxoO6TfJtbVmFNeAfKVlIT4bvAgv+w+DLB9/aLFl2aLGQpJych/4m2oJwseBi5ff4v68sx45KtZBDpSrolHug/9HeVw9TWof0OSwWczN3BauaJwPyc21dJ0FJ7g9NtvduWEkcOVy5HOpbHArRy9QfXOLUbsb/KgoffDT5A3pldopOOBgchfieiguHQ28IwTHSLlhCdH+sVn+Rdwxp+uiIE89h2KfFwt6v3O/LxPOWVmuTpy+uUXfCOXnHQqzm8vMeMj9Q702/eivqSmQg5GjwOMW9bjm/w33nKMCzng33eGfKQPQDyBeg8N98cGm+Ud5d8oAnww+0Dx1TnmOo/Th6sKD3A6ftxVl9Nn24DPgw+ggTB4SOEhTr/KoSiTNBhGqPUE6tUdXSGn7NtY6jg514Ad2roD5cUWT6MOz8DnCL9pHXAox55QR8+QodADHjEl++RJ6A+v13UNp2/32OnPsEWc2EggOXop6dAv4UWuCE6FxcB7YKrSG2RPP1yN62jRcPHbBZRzt5vN5Qi782WBsF8VtjuQ43dy7fCBfLNPOUwHpvizb9zIvg0fjvy1EvqX6VcqrwSx2GIZuJL937YD5ffYE/A7LhT+Q0/xbfzIYeBzfyHwfPxJXLcV6azfAP32YALYu9EDudm9G3b7Yjf4k/rCqHX+e5zeXVw4g5M/U7ATjw6vrBxAn2wuAh4DBoYt5NRfzDQLEx35nkTw9c0O4PS368GJxwO+d+2GX8A+fTIdsKO+byA3bZvb6i/yX0aIGVJspI/kvRz92MxglPU87IS1vwD5YwPapEfmTUf9qB0B/JqLjoSXssIWcAqvj2x8tjXsLU5z50OuDh4wZU9d4hvXOnXCPuSU/gT0O/OnqH41JO/AFbVxQ+H3nH48oBYfoucP90d4pi8o5D6xKCez55T/FhHoeF/qRTl8uRtyZa2nFWOmP4jf9z346tsfdoItqklHXCzOzWPhP+0R6dx2PdIt5Y9Qg5b5QYSntV+LhhKbeUP1rodoiI6fCrvYzM0/8DH2PDkCi/sMe8RKnqutvUB49wjUY5Tf+M4CJ3u5pIAr+iD8U4sq6m9D3ywQHdTl6B0aqS7aj/Kw9i/BT+Av9MmIIXjir9eQs9y3gqu/N4lFzsqRi2L+9XFGmpVfXbiP00feQE7P0jtqZFDkDwqC7f8kr2lxnhfE9iPtYuWiJnJ1K7w/Kh09BMnJ8j15luHltTzLKZ94Lzwc4djiUEEeHaI51VP8Bvm6Ci4XC5A9Z7iuWVPyqQKKP8GmG2x4c3rmazmSI/k1P7e7ViNItMpmQzES3CTSaXyq3GiRmMaRaiTXImGZf4mzRbCz7rZd/ZIZRr2rXVt9MygfiLPC+2reh32+9Yi96b1gL52Wk9N8BZt+RcNLPWMnX3Y4W6Wv3hP1xTKc6XmAPr2Oa5S6dVV50iJRwes9q/TlfaWfSV7824bI507PldUTTtNxGk6Ws9PwVuEqqz8t4w3SHkl5lXq3snYnVPhY5c/qvhwhg15o4Zb5sQp/pty3kwOpjwPq8SX8I6RzRYOt8rmR5SblofIxnhqDVT5lOUk/R5WfXHX01GgM8FnOjDFT+Oq+dKqnrfhScixWP1b20KTXrd5XOIoZPcDLXr/L8reK92y7L+VcyV9Lfid4f1uVF5XP6dM7svxkvszl5VQulF/g0K82p1PV12wM+sw4AHTNmujxPPgrerLezEaPz6rV6JFoEIEeEE87rPrX92G1yMuZkQ3NhUZAI6AROOsRQAcRW02RpjKNGY+RO+Y/Uw/9/b2wWBD7NEMfGgGNgEZAI6AR0AhoBIJEoIzJ9kHGEKLg6lsmmmrx5+aYYsCW+aYh/Stj4PiwKbC0nL5umIYIdh2NRkAjoBGoIAL/txdTDbd6oaf/MUg3TCsIpX5NI6AR0AhoBDQCGgGNgEZAI6AR0AhoBDQCGgGNgEZAI6AR0AhoBDQCGgGNgEZAI6AR0AhoBDQCGgGNgEZAI6AR0AgEIGD5DSq+Ca1TB6t63dEFq3x61/NtZvMKvt8ntx3BVNx16+2mdqlvlmiVvnrh2BB7tTeAI5sboYrHJhn9uIoQUPvN0iptd98FucnOtkrOSg6x6t2B/UYDTl274RvlrfmQK7ZaXYgP+TE5pjLGi1Xw2PL1tBroO0uRj8BVK0PMRkB0WKShTRusjtiqDfa/WrwoIGAV3cBiGK5orHJ421+xKuBn21EebF9VmrJvrx+qiL2AaM/Ucgxg9HdyQy1eRau0351o0DYbM2erDderKR9nCh/VlN2QJYP6ECW2LfprPOz73OyQJWCKSK01YaG3Yd+viMXq4K6IgG3lTPGF6rK6cQgV32daPFb2WvqNoeL396LH5aI8ho/Trd1hD33bsUr9F9tDhUdl45GLWsG/qemPjtYYYJ/WfcmpqCjvMCe7/cb9r5/uf2drewGrobNtNMm/ioiA33f6V9tVckT+/R1dob9fza6oHFh/g0rbKdxzHxzOeQuRAHM45UHLKd+fAEeUbTBvcUCRxMZiEY1XXsOiGl3Yvg7BHaGKJ7hUdeiQI0COSdNINGj6JclV8CzTsZJD2m/y9m74NnnuQmwX1EYsz24ZW8Uf0DYm899HOj8WQY4fTsHy32PEtkUVj97uTenYqdXb2vIuohg3+HlxOupXX7FMvV1slX+ODiqWPimiaWNRDrt94GPZJ1Ccgxba6YeKcoL98SqwuvBpLseK5veMfY+2N3o8BR0kL88yvuPEFrur4kN1jMh0ThMfMvnf21mtEkv1YdJ41NOn06o8HxZ6u8OfOV3SBvp0xhToj55JVc3PacOhqjN2uuK3steh5sdKj5MeeOKotJOhTtYuvgC7RPrwbzdh8c/ZU2An23eyiyfY5wH6MNgIaJuaa29Avdu+Cf7Ne2/iOmWI4ea0/EPUl49XwR/vGPJ8BMu2Vfg/Rnuhk9imMT7o9pQVbhW9rzpiKIKxk7CN1fOzKhqffM+ygap6Uqln/CeffEGe89Zz6tHHruWOkaX8fLy31ivfD/YcqniCTVeHDy0C6FHZ5cvbxOnGzrj+n+U+iVZyqEYKySB96wstl/7Y0AN3QTT2n7rKnfc5pzVedNzcehv2cZv4L/8bVfTvXL5+9QMPgI/ONyD/rEFIDcQluVWUqnW0pBd6JMKQ+XwYuV7uRYP5oiYl2Zz+VsNOP1gnYPOERq5Zh5fD44wpR4f8/m6C0f6wz79aXfwqB5Ac1LFjVbrVzIdK93f6B3qX7dNLPfAzc6orG1Z6O+8LTl9tBx8feKuNHwKi+nGorvxVdzpW9jpUfNjq8ZPcNf52t7SToUrXcTwmu4R6tsyLmVZf+RzH4zCgpT50+L4MhhHddxdBH+T7YNdXebHv9pMZ8L89nZGPL3xogOQ4tr8yneo6n+3tBdSzGdl5Gzk9nlFduFqlo2ZM0cDlixOtwgV7n81RxIGeETZVkBz+fvdiCuXBMOM4p9puFU7uo0cVsX9/KILcRXBQt+Sj5yI8HIL+6ChM1WlYAsFmG2DTscWHs/VvsPHIfX+wUfTdvZDeVXGYspCTqfiT+21dZjBiG7Yf5nRtAsK9k8O3rTWKP/r41KnNUW5U2DoGwrGpDhs4vZyNofbrOqHC3jsAq1quzcWUiIXvyCkRCNc7Ge93iMGU6QNhxi+cJo3DKsYnTmCqWmcPyoH1jFB5sH6E/3Ga9TrysW276jGjhkK//uh5PlGEfM+ci3D7Aza0Bq5sShdtB9F3ILbt+SIf5fyXBNx/NRP5qROOeG+/FXw3ENtIZL1u/MRp506F0yGDUXgEeuLrRRjUk3pxQ5THCzlQGD4f5Oz6TuCz5wBUtIf7SElwKocyPOL5VV1iZK97Ivjo0A4PDhYjncypUOjXdkIDM/5WlGtODvDyTw1GD2xLN95/Ig3l9Sc3yjEjDXKfnYMG2Q9iw+9hqeCndTvgt2Y1FP+8bKe4n6pYDQPl3C0RcjBtFuJfmt3hck4/G+CLte9p6jwLT/tQ3pMIvv6WAD4zhfx/JjqKWLh2nOzlVgEr/ih8SX56JoCf30S6I4txPW9BWDKntDTgmLsI9wv32codyft5YsP2QPkHGykjoV+6eFBf2MgPOSYzlZxJvh2XI8nrd4XYh5DVU9Jvfv0B+T9UBFwfTMLz42Eol7fm43xvT8hTmIFw8+aj57xJhJ28KX7FvqVWegz66fNtwdY7Ff81HRjdkajqO03h2r8bcjR1ct52TocOqfAkT1fGAl82Y4bswVfFRkNOs6aDz1JTvgi3P18G3NnG86S3PvLXA6l/WxiM+g8FPq0bQi5+NuDQPRFgcJVjeowj+/4ayHUtKXepwDd7vuQb5WPNhwxnp0cRT81akLd+A8Hvei/wuMGD+w1K0FH0+IS8jzkdPy7jN5870H5zDRpA797dA+9fEgM7ULAb+raoCHZzx3rg27PCehp4bhcNP1bvSW+wjiVqmN4k6i+TV2rws+cdOV3khjz0Ska+Ps/n2t04tGIlwj38CN7/sQgddi9NhT5pFoXn9/VEeVzSDuGW50IPvr1I4UFy4tfb6j6N5PzKGMKh+KFyZ/WO5PWkeD7zFfB59BjSHTgUb+XnK4dbRmQ62+FgCu5YX0Lum0SCzz69kf8/Cfl+OQdyc+KYrR4kffTFF1Z6QPkzpMftcZf7q/Ja56TeObUPQdtrM7DiGulZ+0fQN9EuBC/DHpM9+rYYenhyDOrt0gRpJ6U82OXLaMmp/VV4P3kA5P+tHMhZjyTo9UcGSH9NZgflnjUL5R1olxAfk/d6nOoZym7RLhX1RP17QukP6Du2jRf5d2X4X9Qhd/gI+AnUhxgAmDhV8hfc2XK8wEC9/no3Pq3qbsiZXXIXDrtylLiF2s8Ntr1ghYf6BI1m+j3UH+VWjj9HerTidgH151YP0rkuDvJzqLhkFqfJmWEPcrohDvrkZtEumLsUcn5dG+iRegb0QZZojzSPRjxJ/WGvIkpgtz/djXSKxQzATu1QnnNfN2hmy5/CcZ2QgPdXrJYDDHbyqOwM+QdMzklPW6Hs/H4NGOg/NYAjsfJ9ZIT1iNPIzFJhUBqaYmQbAVPFGpqE91xuFYAMzMzpytCSYXlqIuI93x9OvWDxJ9h4CJg5L8FQrfMi/QU5KJB1W5RjEGMweutD8L2/CKnPzUK491dBEbb5L553T4AgpKcAcGYXKT8NI1BgSckId2UnOBhjHobAjJtiNOd0T2/VwKCE+iThG61HxyLeXklwVO67DxW9fn3w/XQaCnxkBgzaEWGQm0QhXebAEz7T5xgHOD33LBSoqx34nDHJAlXRwIx2I/0BSYh/RApwK/YBh6YRuF7xiZCHacjnYfH+v6Yrg0G4P5gCeXgmDRWCyQvd7+RBPO+tUlMASHBv6ASc+iVLPismh/LtUmdSGB8sRQW7R3QIhPsDHDEYHShC/lu4zQ1TFZA6KnZ/i3zNzwGuRQKf56YYLk6796CevLkE5cEagJS/Z55Eg/HpNCjOQanIbzm4U8OsfoRKX/4hQ7TsPcgF286DjkWrIW8fvieDAeer3HBoWAcBHczQUDn8a4oM51RuZfiAMymyZe9DbjaLntSNPmz/NO0VhC9DP5ADUU7+yXA38djJP8rj2QzF1888x2wE281pzx51X/5xWo42+gMNw/0HUT8i3eiAuSoGCnyHagBAwd8SB8f96+243iu2Y2nlLnmF067dkr2Asx0f1EPZpgvK1b7eyfjhOPQR+io+AR1zjw6AXMbEoD4sUiPxytEgfNnUcdI3o8Yh3PAU4NFnkIxfnUmO7xYdIyty8V72LOjfxpFc+xox3bsinsgIyM3I8cD1Ko+Kx/znIoNR4XeQ8zmZqGc7vEYhp+dnmIMjfms+HOtRqs8XiIbXwCTolWfTgBubuUH6pnsy9G9yrwA+zDeoI2lKJt5n/cPooJwGuZ89C+e4dtC3LaKQj0roaZE+75agjgmqhwNSwO9jA6Cvf/ZJNtHx+o0YQTm3BPYuMUF1XJDDzJ6T/R+UIt/D+YXxCH/UgH6Yngk9uGChsm+nvmB7pfgh3M4R9qd7HPT23r3g68cDArc4pLfqA6uIneIg33eqL2G/GkUClw/eBA6vzIX8s47tE5zYFHg7PSjtgI0eUP4MMeoAd4f1Lrj8Bus3SlT9Z6f+EfRNOfaY7NKc5yAHgXbSab7A2dWiYTg4GfGxT9KoXNhAAZ1rswI1HVQfHNglkoMHkiCnbBtFqv9dkqHPe/dSfhB1GJXjfwWrD03sOru81oMO6UdTwRfrIKf6/3ga5HnQMNUwvYyHYB3pdJwGPzfY9oIVANTuceDPhcou0EDP8jVg5xYP5KJRw80dOJWUoOH4nZgpxwb66DghOvpZhwl1zLOGrTzIj3puLC7fnA+5ys6FPbk2DgMg74uR8vuTIc9s7RKa0bg5Hx0oV7ihp270OJZHmX6IzzVg8BNET26+DyNN3+6VPXQQyB98Ml3cX78eDsU+eVv0CDUUjnE3MQIxLxuAsMVjSLC9XvWCxR/0rDiPRzka1FPf0QPD0EukH+dBA3BJNvLZcTYE4HI3GoArvXAkP10Pw3JVeyOa02eXogJuKMD5Ix/CPzsV+Dw3FflhDUzqaXE3RMH+YzjCr/IiHdaQJIeSxU/8jR5t7OXUQ3wszxpOVLEaRxjncfrtNyis9h70yM2ZBUeC9TyTwfpvPgQqQYyo1TXQUBz2GNI54UM6h4wr8ziFhZlhVvklRcscLIp3Wg7y90QGplp94IWA9rwD+bz4YvDZVjQ4G4seGzbiSPxvFuGXeVXPHfWQDx0GB+7PbuS7TSvkZ/FSM1/BymHA++KGkjcyBE9nAI8BKaoHmXqm+9wLHP+daRnPTq56T56EnP98DOFLDOB3+JCxh9PFrfC+x1OSxWn5auk4wYFeLOQuOcEW9/w8Rmu9Zn5kjyPk+qQBnI4XqfvyBcL7U1/eNk452ZDn3ByEb+GWwRzLrXrh1D9qhIgUIxsoIoV43Ad+jhyx0g92+YeiXTfDVv6pg+Eo66LDkfcVp5+PqCkm8oF8bleO3xiMGooOunL0BznIl7SEHDw/ER0B8clKX6EH34fn14n6y0bgqX7c3x/14JmJyvCY+HSsx+AgOa530COXtoE8pgrH4p3cU+Xn1SzIRWfhkLBvi0me+iYhP3OyoB/kVPybO4P9N+aasiH02dPjoAfeECPnrMFCcnJ+NPiQamlkmtGY09DBwCclsMEry3EJL2GmH4lOGODvVyNvL6ejvwTNB+For0dLZnLaXAAcmL6k954VMxJmZoMPZtfIoWwRE8CH+QbJwy0e6MFDhmpgUX3aLsp1227UI6/Q9yzdCupplTw5wsnim/n5Oar8qcN16WoVTv6h8pcdo/ImO1N4NpPAfJCDPjkLeofpMWq4d01EvWblTXaSNeAqelC9H5cJ+9rKg46/jp0g3+3FYiF5Xsgpm7JrdQSLA/ktDuw8pXdPb9T3FcKvOChmMGVMgnywfYLpExHmD1jYX+SPjVjb+TNSHznFnRxqB/XOaX5J3p37jVbF4dQ/grxa2+O8Tzgdr2VpJ53mi/BcOF/x+4PB6PHx8CsG95H2Rj2Xf5zaJarnM3LQ8cL8LJIDNiOD6luLGOVfkJ4rx/8KVh9KPp2eqZ4zfURyyPw14nOZ6MDc60M0qX6/6jT5ubC/otlhVKLdQTMR5Fo6Dvw5Wiw2z6+fK2gXlFxTfZqcCT3fO1mOTEMuWIOf9P/UHO4l5uXvEfhvDtTbsnxJnha8D33sioDdnZwhH6M8f1aX6g/5zcXq0qk8qhdC/KcGDH6cGEJmDrD5oIrym3AIwliLShwEgPITxRTDjsJQsGD03kn2ojioYvov5e2AMyneIOIhwWCCRfE3FlNxJ0/AlI5/ppdM49SzLwqoTjrCRbnVlGDJAPVkfLYVi3w0aoRwjF/qmTvpk8HUmQTqUtHTsK4ABTkuHeeH+sDQvDYXDve5ERCIZ8VIARvBo56aTV4Z36mG1XMt+G0jFqHZuAUGPzIKDe7LY2DwfvSpdGku+ogMCHTqMBmv5fmUcvWXC6Yc1CZ1btRmUzhJYcd1gkP1uhiRloauVOxUDn75wTeIBQWoWGzklY664cDBH07FQPxUQA5VBKY/VNHemAM5ZPlrxSmpN6aqXe5RPUam1xxfUvmzRcMo3/WMsPs5NWqs3qf6sa4A5eR2q/sWuKvnofpD6Rwz0PAo1eHrVG4ry4dZP8j4LPLvWP5lPKE6O9UfZKh3+k4dMd0iHPF7xbe4f4mDg/p2NnDvnwT5+3MM5O1z/0irmf8g+VCvO6131GCIFq9d4Fbv7zQYbfwU12zEneJj8koOx2Vu6B02gigO5H+3GGGrU0vetzyTnjvmQz2oY+D9txYhncF94ACNScH1G++rKVaWEVbwgYmPoPUoOfhl6C26z+oZyQcbYbE7KNz0HIzAD05SU03J7jE9RXbo7QUqGov6ErSepnof50E5lMoH8e/X/yrdYP+Qvr1IdISMFSPus1+BHSuVXrDxivDoePupCPb4pXTE+4Swp38X8jMjxzb6YHFwqi+pfl3eDvYu2i35UHqNnrOpdfKwKFfUAwf+jNBH8DPscXdc75zml/gPgb2mDgN7/0jCVuGz03yRHJvrA2sYV9VBdpLpD+q4qmMEXa+rii/Slz/55LfhkB+2OwDxm9QLduF6D5/XYlx0e9fT5udSvepogJ9KtDtIPirgz4XKLtAqyQvfwcBWTQMdt3d2g12Jciu7K8ub6n8ZYkmfYgwcBnn6RHR8LF2FeO9MlK/bnilfYaddHmugofRhLgSP9aDTNzKNI9WUTCo45odQk4V9WyoPygAzyCQg7HyQ07pPoWBZDzc1bBJ7yOCigSimHIa71X3zn2DjcRuMNm1EPg77wOc/R2JoulFk2EOcUoXB/DYR/B31Ib9po9QQNvXwj3wSCr9WLfAbZvAJocaRmoH80tTLxV4YpMdS8O3fZW0wNa5tLBy85N7I3rCRcAx2+DDysmYNBE82qGtHoCf4soHAjU2BpSmkHW+GoL2ejfdZPKTQF4upId2SMQXjzkQ1AkOL6TxlmnplBrnUNTlGrELIgxT09dejXLt4SmZwmpQJXCPE1F/27dcVnNi1PKjCnCuvDHyDyKYOkuL9TiyisyUf+WDyQvfZWR6kECshhyRv/vhUzxSV68QM9Ky+OAsVdaG9IyP5onzVDIc8sBFreZAjufZj3C8SDnjcDfIx8nmRG/Kxwqvuyz9m3OV9q7NUhNSzeY6Ql6aigczyTXwyeZUHGRJ2TR03pe4HJbcysjLOVO+ZXqD46roDQpj1gzmAKf/oCW3htpV/ive3X2V0sv7CsEdaj9BYlSPTHo70B9Url2qogU+2uAw16CaKKZ/LVkN/vJyL8/B0yNua1ZJfy3NF+XBa74jPJV40zNgUUnlQxw37ZoV6aJmjtJ/Txo2oL0y/Uf0ZlgI9E+NGOd3ggdz/NR44+OsdGliBMzegt2qEQ2/8IxXvrxUjCK2vRn1h/TtUj6+8SrIXcJYdnSQH57ilvcL7tZaq8FQ/rfkIWo+SQ870ZBGnGia9x+oX4VsKB8WI6Q/pPRae+J+dAz3IOj62cGp3IfTWkSOmt0QHcCX0NNXXD7PRYdIjSdl3wpvpNcqf37wjP0eKwJ+/wQU7e6HomC0VnvIzWdSDaTmQe/atpdTzhM95EWpmD4VneJn0NsIzfEh/lYEn6T82Ukv83uyBnbpAzIja5QvAzXwjWByc6kuambM4B/ywmRV03CpmUkg9PXiAmR3gVKpc3QYjB/6M1EcOcUdHCHMLKHw59c5pfitqrwMA4Dcc+EexXPOwmXVWelzGS/ljjrvZTjrNF8kVkz950LZZzB+0OyjdcuwSyTmLl/zoMuRa6o9g/S8LfQj5qxUGv/TKWFXv7PJB9a5Uh7Y5PNltNgVaHlS/5Yieg3KkNWxC6OeSPKwT+rcS7Y6K+nMhsgtyrRrY4ZfEN88vL4T/tkCMXEvQ2ZnaZUyOqB6Wkley10+mqIEywifxDtT70aZ2wWEf9FVzt5phSH5AjBvx1y2BHxNEe4DwYHyZ/c5SrAfzt6arBqede9Bib3sBDMTkcfhG6WaxaM4lschgXcMVyemX9jAQA0WDr84xhM99Fw5NkfgmZMJI1/mc5FSqdmJZ5CjD1ZTTuoLCfZx+2CeZLjzI6X8nXM04/VyMCm0dDxyitfkAZOsOhE9NhSIbPQ7xbhH7t76e4YridKAY+RkhHKXhg5Af5mBShdv2Gc6jxyC+q9yuJpw2FRT+wMnnc7XgtHMH3mM9SPTehOeQ3sVt4LiPGY0e39+Og5+nJsBBvOUmhC8R2e7sgWCuWgHH4IWRcIRqRwgBEiOwL2VhkYNPPsZzdwzy8fQEGLpePRH+uczN6ZwCDTYczZs8KKchyeC/mdvViNPKFcgv+5aP8jNgYNhCTv1FAz9MOByeRLz3zQ7w2ygC+D+Y6orhVFKM6zvuBV8vZhbSsX27qzmnkUPw/k0epPvVbnyLlrvYsRye52J0pDPyOzAe/NY5xu+6zvtwVeEBTsePu+py+mwbRiwefAAO+OAhhYc4/cqGjMo+VIOHFPaYEYj/Og/kubgYFTgvD29/9yMcrWfGu6I5NYtAR8Q18XC0Hvq7i46rr7HCvXA/JzZ12OJwXcDpcqE4hqZCXvZNA1890iAHl7mRzpYC4MK+dSH+b/C4WnLauBrl9eEy4G8tt+AncF9XdMAwA0WKaPhwpN9K1I+vdoPP5lEo/yGpSI+VC+FyaDVwGjgK75eSO8p3rRqIb9708uX/yy+hb5KTIK+Jt6G+vb3EjKNtOVKH2BYxQ+H/frTUH5v5eoZvvCWLB3L79U5c9xpk7OI05O9Ge07s21NafI1tk0GOUmoK+DrB5kSXfRR+yamkBHrxe6H3ytBjgg/I4V88jusd6dttOyAPjz0B/XWhqLc9xTfSI4flfcNp+1aUI/tWlsq5h9j3d/xUGKxmbkxxf3IEPjFIeQS5YnqMDOeBg0oOSP56D0Q8J2uh/I98j3JOH4n3atQFTnWjsEjJpLESDzNa0B+1RYfMU88gvQZNEa71Bsd8XGgwyvq3nR4NW8SJjThTwyYlHR2P4UWuCE6FxcjHwFTwERMB+/jhatgJttiR6UC5jUmDPUhJhbz1ike9HSL05wURkK9jYVb6Img9Tfp80TLko29/yCdbxIqOuFicm8fC7u7ZDf7YpzxUnukTUJ5dPQjHZsJQuV7tgT39SkyBZjOsKPwooZ8uaQW9dL6Qs5go4PlDKuR2cCzwY/qB/IStg3D9yEVIp3Us6sNagee+fcD1yBHok4tFufwnp/B7TqW+BUcEAb/g1/e9YxzIIV/0OuTXWl/yDwWMb3Z8bTTh1KoF6smEqUgn4S7gMjYDfkTrNlblmreO06Fix3qABOfSWDvcgev3naGP00VDObDeoR5+s902vz9yi73tS8f2+kIXo/eXFn7LyT8iye+6LqwbZusfkR5akwu+Bg1Bfvz2GLjmiw7wNmLVfWYnSe53fI768o54v5xyJId/yFCUm0d8MnbyJOTO6w0QKHHD1ZETm1pOer+UXaIBhW9fQ/n0G4X6cK4BOdwn/KSHUtHQaCH8vf8I/djrBlv/i+RTTgkvpQ+pYSLrw2dbw97iNHc+7NDBA+Z8oOMwORl89klF/lu4IYftYsHvYIHnjWLG4uMZ+ORt6VLH5UgNoND5uRhZ3OFz2l5Afspod/xUyOjkSTz/odjWnyN/psM1wKnydkGWB3Bm5UZ6tMddWCzpkcGFMzixRezkIrUk16OGwQ9kepL87pXLoFcfHgp7wka46TgvHPfXivbWR15XY05RF8KePTkA+uj67jizjkfqMGnlhh57ezT4ueeIM3n82/VI1+ORfgT8/4J83K/ELwQ1Kkq2qOV1sFGqkQ3R8wVgm/hHZh1GGGw8cEhr10ZPP+txszg6RHOqd05FF28wRyvzZ74vr2U6sudazjGXU43VfbGKpxxRkuUg4zGfgU+joHE1x2O+lukCz3PY6hQ4zFPwOlzJaWwa+JgxCw2Y5tEyf/K9YM9S7hQfNGLLVh8O8kCDvHUb9CROSQvydcfBwW94ONKpwP6cDlOScuswuG0wO7m1jSBEAYKVf1XP5aqwoeKDIrbXHzI5NXNB3hBnWS9Ntx1fqvzJkQPTmxWtd7InXemXbhz5GmV06Z+aYKjkROk7qs+svkiDe2pytlchrwe0yEfo9ajMiFzUBvrxTbFoVIMGkBNXNHBoHws9whaVI37YIjQ2h9KPJDDWelpGo8qf4mfpSjtoJWfSfovVh5Uds+DPbHchx36+JB8VPSv+aTXi3FUVtTMqHoc4SH6d1gPkOzJSpiPfD/ZspwdkfHa4V7TeOc6vsM9KHoO010quhD6S5Sr5lvl0epZybRXeab6s3re6r8qrknZJ4UgR+uuP2f+SfFjlF/lkI/jVdNiVY7B2XrIt7al8X943n6XelPVBlrPdewHxSPtEq9hXnT9nTldey/zKa6dn5YfKmbCXcg+FrYVjcSAdZgdacqpZU8qLWW8FK48WyQV9u9TYcNDv6hc0AkaHTpyeS0NPTjOxKu4DfU4XNGgwsOXZacrNmPHoCaovprDd3wuLHexTI/ani0+drkagMgicafWuMnn5I7zb4c+cuiSix3r2FIwEPS+2HWEjINRjfZmYqVSnBN8uBm6380fAqnQepWNkXMzp9ZcxU6K2Gz39/xHbg83PLv2O/q8R0AhoBDQCv38Eav7+s6BzcDoQwDctf26DtNtejik0vxRhisSBYkzdrv6GIKb6MK5oqk6LRpiaMGkivvEKnPJ8OrDTaWoEKorAmVrvKpqfP8p7+OTgq+2Ymrp8NfLNtpGhb9NaxqCDbwPWhizIyvqj4GKXz8ITnH77DVPfWrZHx+PKXEwtZNso6EMjoBHQCGgENAIaAY2ARkAjoBHQCGgENAIaAY2ARkAjoBHQCGgENAIaAY2ARkAjoBHQCGgENAIaAY2ARkAj8MdAQG1XEuTH7WcbOvIjdHxszFY1O0MP+dE3+Lwt8dSpf1XH9O8Fn6pD4MyKGd/cXhGLxRlu9UjuztRykt8I42P8OD+/tFF221i1yrTMiMUZcs8Wc6P3eidbBFO3z1Q8FINn2Z9gy+dsyX512VG1qAUtYpSQiPrU0i1xtNIL8nllz0iPLep0DaebPZWNr7Lvq0VRaFGT/snSPlY23jPt/equV3LV9g4dOf09WS6qcrpwAT/O7YQVn9oeWCGj72sEzhwE/Ks30sbs9ydgWW62UfRZfigDT6tINolU2W1gMGoaiW8Y+yXJVdnU89P0J2B12O8MRn+76dRFN9p3qnL2zlB8qjzfZ1gCWHTlkjb49nfGFCx3zrY1kYdNOQXIk3yvis5wrGJjsRjMK6/hW7Iucacm10lsQxVvuu8PhfrIVjWkZdgnjYe+ejrNH8Linw0eFm/p20EiUOHyCTKd0x3c0lGvLjtan29gdns3LLY0dyG2B2kTa6sXKgkcGqaXxyLdl6dgO60efr1Tyfidvh6APy0y9XgKtit5eRa3jsZ3Nc+aNTaqu15BX7MOetrOIj4e5dxUbHO2ao1VOQWUi1XASt23txO20Wt7YAuRDqAR0AicJgSkAoajfk/iaWLDcbJwDN5dZX4BhuvjVegxvy/Z/Fxfn90IoEc5Iw3bjsya5TS3VvLk9P2KhkO9e3EW5HaifcPSIiGMmHT24Lxzl0Uwffs0IXC2lo/s2EG9e9VxfauqYkA93rZLrRIsEqqoXnDKJ3B4VmwvNq3acLDCH/bvgmjIXUkJ9EtttmHu2XVUV71SfgXNULlOdXzjfqS/Q1/Aa1UuZxf6OjcaAY1AdSJQCwYuOhobb/fvj5GJ3EW4LtyHkZl+AzFSt96LDV9v8OB+gxKMND4+Ie9jTsePSwWKkRI2EkI9m2ygljYOniU2vD43Aj1zPW7FCNDiZdgQNmmAQRsPv5mTt5HTCq8EQ/XM1eZv9OuP904Ugc+Zc7FK6/4DyA8bEaVtRvr0Bp9/aih6fHPARzsxksMMK204vjQbU2R/NpB+0T7c7zkAqwU+rLZNQfyXtgH/ve5FuIZu5HNWJvjYki+nMiIcyxf1rL84ET3dQ0YC509WI/ycbJlP8xnpZc1CProIh5yNGJ3kNDMH6f9qYNn9egbwZ89pdch6BtJ5wl8+Yp9V9Ije3QvvXxWH8DmKfzMf8hoG6vpOZnzgEHWIBb59UoDjS5l47+EUrFK5tQDlMHsm8Hh8GNKtZYCfJyZiG5hjxxR+VN6334pwbFtA2rA763Vsw7B9u+KL9rOLT0S617eDPLENlwmnb3yQhy+3533O6evt4JcZXnp+r5C7tbnGl5wWvpN3mNOvDNiyDzS03G7wNSgJfEW4kc53u/HWXDfO3fOBy7kR2Fj6mXSU6wPJeO/iGOCZOQ38HTwA/nonI/4OMdhe4UCYQRt/TxqXt5PTiROQr1/DzFxalhPNGChDnmgD7T0XIr3mosF3sBjynzkVDsi1nYBr/K3IZ47Y5mGnLyB9sY8Y5PbRUZDPhiXI58VuhN/iA47h4Uj3np7Ao56BepGVLeNF/eyRiPhuSkA8LNs0kipDWZ8t8SAHrPJyi5QjIsBXn4HAZ63X+BOnhDjjECdfMc6vzjDO49SwAfLbd6BxLqcv8lFP/pKA+69mQl989TWf12E0eKg/4m/dDnK7ZnXeZ5zmZSN/bIo36bPr4oDToWJs9D05M+xBTjfEga+bPTi/+grS/WF/RfWBRNyufDBjpU4doymnO7pAnqNEfaljoPyLipDfxUtRrvf1hLxd0g75WZ6L/L69qLr1Dfg9fAT8vb8G/NUyUC9GpgL3eQtw9ttRZQ/kvoiXGYzu7Goc5nRtAvL9jqhHy73IV7Mou/xL3JFeGWqKRr78egFTNC9yg/8Hk1D+J4XemPkK8nf0GNIdOBTx5+cD73cXqfTkH8QvNnSvIXB4JBV6rklDyGdmFvT8ueGVTVc2QC3xP8ElJdu/qi/Vgz9fBj07RIysfqTqi8yGU79Chjef1T6dP/MaFGhPjWJOn28zGnLqcR/Kq2kEyr3QB/m+JQF4PZ+Zt43T1nyZjl29kuHszpiKfUei0i/kH+3fjXKfOjlvO6dDh+A/jEpHOV7hQbx9B4CP86Jgd/3y4KxcVq5HvpMHwF98KwfpspH3Y5weGQA9ec99wCXQ3kFPsf2aya/x2wngO+s/weJraQ9o30i2TR3Jt3O/DfWWzTwkXBPioa+k3/lpAe4fLMrL58Tsgj40AhoBWwRYy5EfrIFKFX9oEhSTSzgOFwhDOTAJFe7ZNDhO3/pw3T0Ziia5FxyQ+vXRcHw6DYpsZAYU75EwKKbzt6Pisykj1NB4LB0Ks9cAhDtuQGEvXwXDcnksFCDbaJYUxvQ5xgFOzz2LdF3tUPFnTIKhaRSJfHzwJhTfK3PxHnOAyICxqT9HOS17D3xu9VL2jUWrjR85LV+A+G7oBP76JeO5YagGCfE9e7poKExB+BW5UMDrtkBRNY/Ge0zRUQNrsGiIjBAN04LVyG/2LOSz1BRjmaA8U7k8myEv4UhO/Jfh5rRnj7pP+XsgCQ20tavBX5dk4Nu7lwpHDZE5L8ERWecFfwtEQ5fxLzZkV+HFH/VNDyngQHxQvlfGAv8hYmrQvQmIf2ku7k+eAoclMxPl8FEB+Lw9Gfz0G4hyZBvUU8NjxSfg//lpkMvDooH6r+mSP4RnDVMKPyIlbzOnJzPQYXC7cAAfTQF/54ZDnpKSEd+VnZD+mIdR3uOmGM053dNbxm8+K4eG5PH9VeAv+3XIwYQMxPtUGq4bTsV5tRf15fE0FR85UGybBJKnx9PBf2Qk4u8mRvT7JBlRnB4di/z0SoKhvu8+FY/pj205WckTOVDz7gOf94iGcbg/9iMGowNF4KOF2O82sGGqXiB8Zk5H+cuGx1MTgdf5bhWOOrDYRuKEA3NYqMOANbDEoRwrej4gBXLzmOjw+dknw1mdbfGg7YgqL7fQM8xBqcfpsSSU5z/F/sDfF6NePpViNOY0agTyGy06tgaIfI9IwXvFPuBcPwJy++YSxP9ZPuTpmScR39Np0EuDUo2fOC0XU+9u8eB5o4abO3AqKeETQo363/kQX8MSdDx8uxflEbw+kHg7Lh/CJbIp6kf3BOQvPQX5CTOgrxtGIN4XxuP6qAF5mJ6J/CxYqOxMiMrNsb65yGBU+B3KZ04m+N7hNQo5PT8DfJdhRyVQMQajtz5E/vcX4fbcLNiN91ephik9cJB/Ga/Dc94GTqyjjjqAzxF6tHscGtB796KB8uMB1Ne4OIRb9YFt9OhA9KBe/s+AnN4oOkBWfxKydB3hX4pb0it3J6C8mH0mfcTsrXkDexu/olSMZf+1safoWHIvBq6so4r4YlORSf9f3g58Mf+EcJw6RSbiuF7JFyzOkKs+wt7FJ6Bj5NEB0D8xMeBnUa56nQYSpk0GP0d8kPN5OeBzxVIVTv5xVC5X+/0gyif7tINwYO4nddQlnEB05dg7Kzsh9QrFa4+vrT0gRpz7baqDooRbTu/7yEf2XOC3Zzeu5y3EubHQb7jSvxoBjUD5CNSAgVoverj2qdBwYPLEBuKsQUoK4lkxwjYzGwrW64UBaBEDRfPbb3D423vQ8JojGoRvL0JP1+YIOMBshJYaOocNjCj9ow96alP6QBF+7UP8dyUi3QRxrmugp2zYY2jonPDB4B8S+17ee0AoUq8ciUKGMiaBz38MUiNP1HN3UozAHC/KK+R0vBYM7eJARUwK6P5kGO5tPtnjiB4xlh9ymA76kN69dyHcogUKUJfBqG8/NTIk8o98XiAatCq0/w81DI7+Km/kfcXp5yN5SzgxvOVBjv2MHDgEH3iBGxvxJkPYIkY19MkAdfTAAeyVjOdssRoawVmSDb4vaSmjlWeVHjXwy8CH0ln4jgxv/MBp3CSMhC8UI/JfiR7jBbl5X3B6bxHkYZUX8tCiIcrt8CEY0J53QNFffDHKta0H5dhYJQPcb2mHhgFz7OVBjse61bj8xUCHSUE+4mMNPRqRcjfEe/8Yjg4Mxgc5cKxDxOqg54P6IZ4NXsjtF9sR/y7hAB7wqdep4+DIMXUt/siRYuTzuP8xjbR/uh5yPXq0sZdTj+7AiTUYKV/Whs62nKzkaX0eo6N1gMPToqE9IKWDHPmhkcA+90Ku/i1Gxv1sy3/ogZcNjW5CvuZlq/ySI8H0hjhQf/b4cLlZlJd8ys40YpycArzn55xaf5cGhi/1Kv9ri0eo5Pa/XJN95EW9+l44nGMzUN8nTQX/r2SjwXVXMuSclTPpVaZfydGdlgM5eiID5f2DUMgeT0kWp+VixsXevagvi7NRH5ITgMvJk7ienIn4eifLb+1Rz5kDSOlMzamsPlAwOywf5Pe7vZCvDQU4f+RDfp+dCnvz3FTRkZWF81rRsdM1EbiFGai3rCMyVOVGMyrs9Y2SI+ooYf40pf+rkbeX09FfrOyoaniS3rjcjfyuFPaJlT91GF3V3mjBaf8PjvOvCiDIP1T/x2UC/1YedHB07AR73T4WcpfnBZ+//GIbO9nRJUIP/nsqwvd8AHqqlRsjzJe14d1bxpGKp2uHfwCfpCefHpe3idMbwv6wDg9q0Jwf7dSvuDKPUxgTvFMPx/WH/IY/jYL8biwALuu8kPe0DPAzL0fYP7dKxWG9UuGt/pCfkZqG8n4nV+lPCv9qFvQS+1SiLacY96n2l7kXxP+RY0p/m9KxLReS74Xz1WvkFzw+HvEN7oN8r42ys3dWdkLpFfJ/7PFV/Fr5MVRPg/DbaCZEbHuUb2MxsPPzL7Dra9fjPuuAID3/oX2HjwJK/9EIaARYF5Y4hMGVl+pMCo415MwH3Wd+NzV4aogGgDRonmuheNq40YDYuAWKLlIoohLhwP3mM0eL6zVeKO46JWg4XR4Dx+tHHxTSuHQ0fEZkwFFIHYb4LyuBAxbtlvEqQ0uKtlj0XMunZZxJkVjlNzoG8V+g4lcx0HtsRJLwcLcTDoxqWKpwp/w5JkY0/MVwyuPKXFB5svIhQy0VJBvhIUUuFenkCWhg/TO9ZBqnnn3B/06fZdJW+JDCP2mdX2oAnwiMl8qF9byTPIUZmHrDvh0i6ilGQOM6oePgdTHSW8pfoHzOy0W5dBSG9s5E5PvGOMjNCxkqPzTSeqkbBmRdgZInclQf6gND/tpcFd78h/BsLqbKMUfVfFD5M/mu6EGOybkRMGjPjoccsZFL6gDZ5HUcrVU52UVADeo35gAf5qC04pTUG1NTL/fA4ducbxkNGfiOwtFlDWpy6E+aOlL8lyoewq2MekflFSc6Jko9J3kpIx4VoemPFR4hkltTamLkr5QcUDprxFQv1tEmD8KH5YPkuFR+KN/RUZCDekbY/Zwa+XtmKPy6Asi32y2jk1PU0dFS08CI7Z3dUK+j3OgQ3C06HEOgD4ItH9I/LJ80onvSp/iWOLeApQAADcBJREFUf0j+LhJT5camoB7PfgX6oVT5h6jcgtY3kk+rM5VLKTVI+q210LtRbjXiIt+nke/PtmJRn0aNoH8c5F++H+QZU0h/KgL+L6UD1yeEnvl7CuRtRk6Q0argaKizDhQ6WIct6cuoqKpOVzFg9Yf0J7O3JK/MHpI9cuBXWMVH+iSI+kNyXUp+Zbwkx8xOkz4r5QcEW69kfOYzyV+0uFvKb9lpMNr4KR4w+0v5KaVHzPFU9JryXUqvUTysI00ewdo7KzsRLL5W9gD1t1QFloyWPpfy22hq95bNsM//FR1qo0fAz0q6F/enpSs/tHQ0+r9GQCNQLgJ+jSgVJCk0/204mMzRKeJUwz+yRIoiTCg29g0KLXffQnyTx6aA0ohhx5thoF4XPf3DRipuyFGp51ZTLuQD4uMKNxoc83MxgrJYTFntlqyW8advBdhIFxkaNnWO4lsShoZqfLL8Jgs9w2wKISmkwQNkMsrhoR7gcyJUODIMLP9kWEvhQPldIqbysoaQ/MZORkiG5iI3DD+bUkT81KwlHxufcyrVE0sNMIYfKegazJO3OOCIK4Upp6Qhf2yxAuqhZPFQfKX4ldFRvtl9N6dNG6EwD/sQ/p8jEV+jyLCHOKWmAE9XlHw94GyFDznaNfz5pZ5q9s2IPKgHPcyN8vHfRjkw/iWfZGiuvx7hunhKZnCalAl+2Td+lD779ovwZ9fyoPfe9SLcPvENcffbYBiWeWUwMULuhXw9liJ7+DHS0TYWI/PJvVX4Mv+sXA3cbxczBaKjVY86jVCd41avkcE7cgThw0UDnE3lpW9B2ZRAKjfmMNHBvsWkg9UTyucOH6Z0r1mDBobsWKgdoUYqSU4ZfpROKVytyslGntRIHJXfxAyMCL44Cw2ehTngr5zfgwajdZ+iPFkDnuQzsYd6g9Jn+SWcwt3qvuSXHEmWH3mQPvowG3qoR5LSFxQva+iR3FlXHxkN8GT4mOt1qORWJST+EN+so0EexC/Ta5TP17LlbXWmhj3Ts/Kghsvaj1E/ioRjHXeDfIx4LhJ6coVX3lffThO+L4lvvV5eCH20wD+VL1T6INjyofJn5Uv6oKZb8q3O9Hyy+JRkWg7k7sQxVW6kJ5jeJ/msWaTeqy59IxvYxOc5bjVltCUfq2arxtJ9JmfSju4yGH28FvXhqA/1NG2U1OPIx8gn0TCtVQvv2+dfjezJ9Ei+WLrysNIL8jnZvclZqD83e8DvBWKEd5dPBgv2DPvMGuTyIAd+42Z5CX1SiXQt8Ed9qLVUpUP1p5S9lQ+kvaWzA79Cvmc+B1t/qHxY/aZ6Xkq/yXgpX6XuB1uvZDzmM9WXJV7Y9bh26jF1PLJPkUhPsAbyfk4bN6rnpKeYOSc5qmuvYK3KhfRrzeUqXvpkhcn5KUcQ9s7KTgSLr4zHbA8oH0H4bZQfJmck54XCrn2wGvb636/C/3gkQ2ZX1lv4HVfGymv5XJ81AhoBPwI14eh29sCBGZIKQ1rnmOt8TkUFMFxDp8JxDy9yRXAqLIbiGpgKwxATgffXb8D96ZPQoK0tpvQ2FyNCL2Uh3P9+hSF+eCC+/XTFuOi4KhbvF/owpWPO665rOH27B/G5Y/De0xOg6Hv1BH/PZRpfc/LuNZpwatUCBn/CVDxPuAt8js0opOP7fa4LOF0uHMahqUh3x+fIf7ebYbhv8rgacfpqN/K/5C3E07Y58tF3qCuK09Ue3N+Zn/cpp8wsxD9iGKCO86Bh+MNPwDUmCvw9MBDpltQ6/31O7y0unMHJX0CujpzYyDRNJUlOQoMm8TY0bL99Den2GwVczjXAzz6xONBDqUi3RQRvNhgHl3qRry93I55UsajF6HFIcct6fMP5xlt+Dk7952rOaeSQsvHxXAO8/xYPvg7ud0VzahAOvBg/ZDDrHkN5/9/3cNiGDEd4JkfkcM1fjVR7JoYt5NRfjKSECUfVk4j0v9mB+M6PwnsZ6Ujnnv7AdVBvV1NO8YmuJpxWrIBDWLAJ79/eFeEmPIf0Lm6DBuyY0YX7OR1jlvvUw9WMk8+HfN4cD0P0r+fB/4VRiO+SWOCbk4VvWr/+GgasWxzCD3oM+W7WErGzRXrIUNYOx3n5eYj/qZ5wLG65CfdLBDOsvlKDdH0B8j/gfjxoHYv8sm+QyWAn3RlQTi0NRhs+DpAn6mB5ewnyffiQqy6nz7Zh8YoHH4ADM3hI4SFOv7Iu97KPwoOc/ncCOP1cDBwmjITcy6n6bJEyaohGGSiXr89D/vrfCoeJ5SOG08plKM+NnwOPvv3BN1v0hI64WJybxyK9PbsLv+f033wzd1Utt8jfh6tRLr2Tkb+r24Cv80T+LmuH8vhXJsqJ4UANqyHJuN/MDX2zckXel5yKfkI4ttgXlecz41GfmkVAnq6JR3oP/b3wAKejakom9MCO7ZDLHndhsaRHBkv9Uvglp5ISxM++kaWOkgroA9J/vu9ty4fsSXFnhEtojfSucqP8NxUU/sDJ54NeuDQWfI9KhTxc0gr1+3xhZ5j+JAc+qjPK+a+dEL4a9A01MD4Xi5499QzSbdAU5X30J8ir346Cz3eWwX7sO4B8jEjFefgglPsysXjPyuVO8x+2iNMPqUhvsNAf0m5vHYT69MhFwMevF4Dzvn04HzkCebpYdBz+Jwf1h8mNzeFqzCniPJTj0IGoX00i8Fp8V+RrdAZm6Hy1Q0ZX6XTJ/tQWM7dK4U8JtN6AdJh+pAbIgYOww82jRL0cCL5O1jIu5JT1bzu/YnM6p10+yb88O60/KP9VYs2JtCeRfptY4JcnZlQkJYG/Gzyot+w+2QOmT0jOK6H3yP5t24H4H3vC1YLThaIe9UwFPyOH5X3DaftWdNQ+lIzwbC0CknfmV0Ry2roD8sG+VTYdKP8yyoX01p8/QT484tOikychB16v60JOdcNgF5+aYGnvaIBgQwbKdUBNZSfcLkZbOuP9oUK/OsCX+Loz0M+j+/FCr9j7bcDv07eQv8nZsMfJArd+PVDOSamwD3t2h73FSY4of7YV13Pnw+4eDMDVBLO+1AhoBCqCgBzZkFOY5Iiq+oZNRIqRpiti0YN0cJcceQoYEbNgQo74yfQsgqmRKrseqg7RnOqxVSOCOzAC1iRSLdoR3OtBh5ZT0cx4Bh2ReEHFRyPfDYVjUdHYQv+ezCf4ZPteSr4v4Vtsn1tfXdNI+gti25J2sapc6Jua1m0gh6PSIV/McJgOGd502/El4o2Kki8gvX27ZA+pui9GWCC/rmh1n0aC/e+r+xS+fn0p5/JbQlm/ZLiKnlX5y29MTRHJkRDkY0qa6bHjSzlSBFwaipkKrN5041RqhN0mRlmPJX6y3sp4bV6vtsfQZ9vVth+4Lucbc4ecQc7Cw1EerEPG4SH1pV1wJQ8V1AehLh9zuZr1gF1+gn3uVN/IeKX8yWunZ/mend2o6vyr8rqcr8+au0rqF6f5kOGU3JAetpfzkKVbQbst+TafZT0JVi/JeBQOFaw/Mh7zWeFFq9S7KNfcXzHLh/k987WKh/hrEThzzfxCBa+lfAf7uqwPEn8pj6Gyd8Hy4zQ8/Ie/erDK8Zh0Ze/EN724vtGDRa9emyXjxXtsZp8+NAIaAUsEwiyfVNEDOFodOyH6VZ+UZHM6t4ZabbKK0tXRnl0ISAOGkYmDYkT+TTEVlPVYUw90AzEF3NMOI/V9H5aLTFUVGjBUxSXoee5yLab4rFtfVemFKl40pNjqhTSCPWY8eoJZPwBN0bq/Fxa1YFOn9VEuAmjY796Fka2hw/CN85JF5b6kH2oEqhgB2QA3Lub0+suYKVLbjRH8/4htbuZnh5qN05VuqPOh49MIlIUAGpps2zayk23dGMlla2LQyPOBIsyU+0scZliwRf7oWOktKy59TyOgETgVgZqnXlbdlRwBgOPbKxkO3A5f2LucmkQU7uMUODWv6jjSMf+eESj8iRObokhTd2e/igZp7ZqYChkr9hX98Ti+dRv7zypvmFKPKVuciQzVwWMwTJFNMFV1wzpMLS+16vIZBj5wZEzR1NsWjTCVatJELHqyy3eGsXvGsaO2haBvuo6KfV0j6gHXgnxMaQucMn7GZUQzdFYiUHiC02+/YQppy/boiFqZi9Vk2XZXVXScrnSrKDs6Wo3AKQhAvy9fhim+e35Ew7RtDL61rnceOoBmZaFhuunTU17WFxoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEagSBP4fYiTUTqgtkWIAAAAASUVORK5CYII="},"76343676-d201-4ac1-9af2-b94b878f7d11.png":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAdQAAABvEAYAAAAFze0tAAAMPmlDQ1BJQ0MgUHJvZmlsZQAASImVVwdYU8kWnluSkEBoAQSkhN4EASkBpITQAkgvgo2QBAglxoQgYi+LCq5dLGBDV0UUOyB2RLGwKPa+IKKgrIsFu/ImBXTdV7538s29f/45858z584tA4DGaY5IlItqApAnzBfHhQbSx6ak0kk9AIE/MgDAhsOViJgxMZEQg8Hz3+3dLegL7bqjTOuf/f/VtHh8CRcAJAbidJ6EmwfxYQDwCq5InA8AUcZbTM0XyTBsQEcME4R4kQxnKnCFDKcr8H65T0IcC+ImAFTUOBxxJgDqVyFPL+BmQg31PoidhTyBEAANOsR+eXmTeRCnQWwLfUQQy/QZ6T/oZP5NM31Ik8PJHMKKuchNJUggEeVypv2f5fjflpcrHYxhDZtaljgsTjZnWLc7OZMjZFgN4l5helQ0xNoQfxDw5P4Qo5QsaViiwh814kpYsGZAD2JnHicoAmIjiEOEuVGRSj49QxDChhiuELRQkM9OgFgf4kV8SXC80meLeHKcMhZamyFmMZX8BY5YHlcW65E0J5Gp1H+dxWcr9TH1oqyEZIgpEFsWCJKiIFaH2EmSEx+h9BldlMWKGvQRS+Nk+VtCHMcXhgYq9LGCDHFInNK/JE8yOF9sS5aAHaXEB/OzEsIU9cGauBx5/nAu2FW+kJk4qMOXjI0cnAuPHxSsmDvWzRcmxit1PojyA+MUY3GKKDdG6Y+b83NDZbw5xG6SgnjlWDwpHy5IhT6eIcqPSVDkiRdlc8JjFPngy0EkYIEgQAdS2NLBZJANBK29db3wn6InBHCAGGQCPnBUMoMjkuU9QniMB0XgT4j4QDI0LlDeywcFkP86xCqOjiBD3lsgH5EDnkKcByJALvwvlY8SDkVLAk8gI/hHdA5sXJhvLmyy/n/PD7LfGSZkIpWMdDAiXWPQkxhMDCKGEUOIdrgh7of74JHwGACbK87AvQbn8d2f8JTQRnhMuEloJ9ydJJgn/inLMaAd6ocoa5H+Yy1wa6jpjgfivlAdKuN6uCFwxN1gHCbuDyO7Q5alzFtWFfpP2n+bwQ9XQ+lHdiaj5GHkALLtzyPV7dXdh1Rktf6xPopc04fqzRrq+Tk+64fq8+A54mdPbBF2CGvGzmAXseNYHaBjp7B6rAU7IcNDq+uJfHUNRouT55MDdQT/iDd4ZWWVlDhXO/c4f1H05fMLZc9owJosmiYWZGbl05nwjcCns4VcpxF0V2dXdwBk7xfF4+tNrPy9gei1fOfm/wGA76mBgYFj37nwUwAc8IS3/9HvnC0DvjpUAbhwlCsVFyg4XHYgwKeEBrzTDIAJsAC2cD6uwAP4gAAQDMJBNEgAKWAizD4LrnMxmApmgLmgGJSC5WAN2AA2g21gF9gLDoI6cBycAefBZXAV3AT34erpAi9AH3gHPiMIQkKoCA0xQEwRK8QBcUUYiB8SjEQicUgKkoZkIkJEisxA5iOlyEpkA7IVqUIOIEeRM8hFpA25i3QgPchr5BOKoWqoDmqMWqMjUQbKRCPQBHQCmolOQYvQBehSdB1aie5Ba9Ez6GX0JtqOvkD7MYCpYnqYGeaIMTAWFo2lYhmYGJuFlWBlWCVWgzXA63wda8d6sY84EafhdNwRruAwPBHn4lPwWfgSfAO+C6/Fm/DreAfeh38jUAlGBAeCN4FNGEvIJEwlFBPKCDsIRwjn4L3URXhHJBL1iDZET3gvphCzidOJS4gbifuIp4ltxE5iP4lEMiA5kHxJ0SQOKZ9UTFpP2kM6RbpG6iJ9UFFVMVVxVQlRSVURqsxTKVPZrXJS5ZrKM5XPZE2yFdmbHE3mkaeRl5G3kxvIV8hd5M8ULYoNxZeSQMmmzKWso9RQzlEeUN6oqqqaq3qpxqoKVOeorlPdr3pBtUP1o5q2mr0aS228mlRtqdpOtdNqd9XeUKlUa2oANZWaT11KraKepT6iflCnqTups9V56rPVy9Vr1a+pv9Qga1hpMDUmahRplGkc0rii0atJ1rTWZGlyNGdplmse1byt2a9F03LRitbK01qitVvrola3NknbWjtYm6e9QHub9lntThpGs6CxaFzafNp22jlalw5Rx0aHrZOtU6qzV6dVp09XW9dNN0m3ULdc94Ruux6mZ63H1svVW6Z3UO+W3qdhxsOYw/jDFg+rGXZt2Hv94foB+nz9Ev19+jf1PxnQDYINcgxWGNQZPDTEDe0NYw2nGm4yPGfYO1xnuM9w7vCS4QeH3zNCjeyN4oymG20zajHqNzYxDjUWGa83Pmvca6JnEmCSbbLa5KRJjynN1M9UYLra9JTpc7ounUnPpa+jN9H7zIzMwsykZlvNWs0+m9uYJ5rPM99n/tCCYsGwyLBYbdFo0WdpajnGcoZlteU9K7IVwyrLaq1Vs9V7axvrZOuF1nXW3Tb6NmybIptqmwe2VFt/2ym2lbY37Ih2DLscu412V+1Re3f7LPty+ysOqIOHg8Bho0PbCMIIrxHCEZUjbjuqOTIdCxyrHTuc9JwineY51Tm9HGk5MnXkipHNI785uzvnOm93vu+i7RLuMs+lweW1q70r17Xc9cYo6qiQUbNH1Y965ebgxnfb5HbHneY+xn2he6P7Vw9PD7FHjUePp6VnmmeF522GDiOGsYRxwYvgFeg12+u410dvD+9874Pef/k4+uT47PbpHm0zmj96++hOX3Nfju9W33Y/ul+a3xa/dn8zf45/pf/jAIsAXsCOgGdMO2Y2cw/zZaBzoDjwSOB7ljdrJut0EBYUGlQS1BqsHZwYvCH4UYh5SGZIdUhfqHvo9NDTYYSwiLAVYbfZxmwuu4rdF+4ZPjO8KUItIj5iQ8TjSPtIcWTDGHRM+JhVYx5EWUUJo+qiQTQ7elX0wxibmCkxx2KJsTGx5bFP41ziZsQ1x9PiJ8Xvjn+XEJiwLOF+om2iNLExSSNpfFJV0vvkoOSVye1jR46dOfZyimGKIKU+lZSalLojtX9c8Lg147rGu48vHn9rgs2EwgkXJxpOzJ14YpLGJM6kQ2mEtOS03WlfONGcSk5/Oju9Ir2Py+Ku5b7gBfBW83r4vvyV/GcZvhkrM7ozfTNXZfZk+WeVZfUKWIINglfZYdmbs9/nROfszBnITc7dl6eSl5Z3VKgtzBE2TTaZXDi5TeQgKha1T/GesmZKnzhCvEOCSCZI6vN14Id8i9RW+ou0o8CvoLzgw9SkqYcKtQqFhS3T7KctnvasKKTot+n4dO70xhlmM+bO6JjJnLl1FjIrfVbjbIvZC2Z3zQmds2suZW7O3N/nOc9bOe/t/OT5DQuMF8xZ0PlL6C/VxerF4uLbC30Wbl6ELxIsal08avH6xd9KeCWXSp1Ly0q/LOEuufSry6/rfh1YmrG0dZnHsk3LicuFy2+t8F+xa6XWyqKVnavGrKpdTV9dsvrtmklrLpa5lW1eS1krXdu+LnJd/XrL9cvXf9mQteFmeWD5vgqjisUV7zfyNl7bFLCpZrPx5tLNn7YIttzZGrq1ttK6smwbcVvBtqfbk7Y3/8b4rWqH4Y7SHV93Cne274rb1VTlWVW122j3smq0Wlrds2f8nqt7g/bW1zjWbN2nt690P9gv3f/8QNqBWwcjDjYeYhyqOWx1uOII7UhJLVI7rbavLquuvT6lvu1o+NHGBp+GI8ecju08bna8/ITuiWUnKScXnBw4VXSq/7TodO+ZzDOdjZMa758de/ZGU2xT67mIcxfOh5w/28xsPnXB98Lxi94Xj15iXKq77HG5tsW95cjv7r8fafVorb3ieaX+qtfVhrbRbSev+V87cz3o+vkb7BuXb0bdbLuVeOvO7fG32+/w7nTfzb376l7Bvc/35zwgPCh5qPmw7JHRo8o/7P7Y1+7RfqIjqKPlcfzj+53czhdPJE++dC14Sn1a9sz0WVW3a/fxnpCeq8/HPe96IXrxubf4T60/K17avjz8V8BfLX1j+7peiV8NvF7yxuDNzrdubxv7Y/ofvct79/l9yQeDD7s+Mj42f0r+9Ozz1C+kL+u+2n1t+Bbx7cFA3sCAiCPmyD8FMNjQjAwAXu8EgJoCAA3uzyjjFPs/uSGKPascgf+EFXtEuXkAUAO/32N74dfNbQD2b4fbL6ivMR6AGCoACV4AHTVqqA3u1eT7SpkR4T5gS+zX9Lx08G9Msef8Ie+fz0Cm6gZ+Pv8LsvR8QQqczIcAAAA4ZVhJZk1NACoAAAAIAAGHaQAEAAAAAQAAABoAAAAAAAKgAgAEAAAAAQAAAdSgAwAEAAAAAQAAAG8AAAAAF48b5AAAQABJREFUeAHsXQl8FEXW73BfQoSAMQQynsQzwaCi6GbcQxGBBFy5RDMcn5xuwirixQbERQEF4oqIB0k4VlgPElDBA5koKCKBRDzwWBiQNQiI4RQQzPfq/atqwkya7kmGBLT7/X7T093VVa/eXUdXGYZzOBRwKOBQwKGAQwGHAg4FHAo4FHAo4FDAoYBDAYcCDgUcCjgUcCjgUMChgEMBhwIOBRwKOBRwKOBQwKEAKFA76RIBZzSNiRXQ7IyYswU0bmR5jo4hqFsvpo2AO/rEJAko+rTkawFlZdVN4KSLBVzVEfU4//yS7QK2+JISBFyeGHOWgHbxJT8I2OKrdvwuSCJo3CSmtYDb+5XsEFBUFG48TpX6hrteVvmB/5clxrQV0D6+hI//+qzec57/viiQxEd8fExLAddeB3vw1cbfFxXs19ZMr+A3mkdB3/r1gr6tD9meJXUTUKtWTH0BnVNiWgmoa8A+7tplH9PwpEy6TEB0NPxf6l8hH58WCetdHfbbbi2SLhdwayro9VMp6LV/v933rdKdavW1wjdcz6u73jUlbydbfsLGj0rGb5W1K6da/JTUXkB7GddcEl/yPwGbfeGir5NP9VLAzJ9WLxbmpSWdK6BevZh2Av7aLaaFgF2l8IMHwuZfzDE4/kktI0LAzCzjZwEvvmzUEvDACOOogO93Gr8IeOFl44iAf05B+q8/MRoKyGyG589nG98LqF37+OxP/hUMfGKiUVvACy8B/y7Jx5fcMdFoIKBzwP3jU53Uq6YGQaso4DEoDYFy3bonp8zqr2/SlQLOjj459THPNekiARfEG3UFPDfNKBPQJ838DefJ75ECCMjiXMYhAc/MhL0YmP57pIWdOpvplQr8kMeEKcYxAU9l28lTpAmyE+w3/vIHo5GAOdOMXwW072g3v3Clgz1u1MioI2DKY/Bzj2Tq/KvVfutSzf8wvW5PAZ4XxpsnrOSTGqovAqTatRGYt4yqJPaVf62a6l1d8oaOpJjYIIKcbPkJKrAqNyoRz1TJrlSivKpUr4J3If+XJsIePj/NOCCgZ9jjmiB7XAEuzq2qU8DMn1Y95zDncIZB0Ksf2nvzFyH32GqP63WtoAgZGfqG/JOUKOBAGQK77qnqOXqY+nuS2gm4pDPSlZWd3AaXKt38jIbqM9nAY5I/sDB/xXkSRgpAjt5YEcYsQ8oKcjk+M+kKAdnZIb3sJP7dUAD2YVQG5DWvxuT1dCG4mV4hsLkkXvkJu/UxsxPgy4cr0MPcz2M3v3CnQ31ucOO8aXO483fyOzEF4Mc9HshXLx13nPit0/fpyZI31fCA/r74u/WHp4pdqayEgo+TM9HRMCPsfDSzx5XF13nvxBQw86cnfqv6nyZdLWDnZuCblFj9GKDEOoXrBUyfbheBwmIB83KA+Fn+ljWPuF50CQR+RDpGVt8vKPxMwPwclb/u0eMRr0GDMfJ1pBQjtrPnAZ+dplO74MAaNMBI2T33YyS3WRneP9+Fctb7dLp6BkGvPuiJamgg/1kS/zaxyCdtMHrwI8uMwwLWbkG6BTlJZwioU8e4RMCtXY19Aq5JEbka9V7PNfYIeP9Do5WAHl0wEh3twkhuPQPpSmX9vtgIPPsMAR3vHqAFgEeqB6Qb9QU8m4V63J0OfDYUA/85s4Hng6OQbx0DPWsPT1L0xX1/fYFf9r+NZgJ69kP5rSKRrsSHnpIbU+RISFbhFwI2FGn+8ohCvz5Id0EC6PVuPvj6Wh74PSsb97vIwI5GHnhkZXYuRqyIn9wzfddglN8uAc8/0PIBfkVHo54DhxqNBXxZhPr/MQX3X8wq3CCggqnRPBPgaISmQ8CfpKsE9EjV+fFMgZ1bwK/pUws3Cti7F/W2IRfcgXODGyNxNDLPI/i1DMh99kLID/E74AgXv0GHQ4eSrhVQvz7k4La+oG+HZPA3Nwt4rLfPTyXvbQ2CwSMhb+2agf4HDIwwZeeCbn09mBHweZGxV8Dy9/D87r9DHn4sRbrZz1jpR+HHAp6XenltR8hH7yHQh5X5xtcCFr2uyWmCXyEfD4/X6QL/8EyRXwzkq0b0KBDmkdW/pAD/LEm3z4rU61byA/1q2Rz53JkGPhyOgFy8ugDn3n1gF0hMubz5C0DflpHQr8434XluLvi2yafL5ymd1FHIcp4k9fDTYtBJ8eWaBPD94B4jWsCUp4wdAgbdCf41jyz8RMCk6bbtsJlesZ08agBfhaX52dJOsP+g/HhmTkMDgTvZEbazDaXcPfx44YcCDh+2K/fmGOFJ0qUCeqZCXv+QAr4Rf9ju+d9GoNupI56Xs98W+hIojwg4r0gE32gElOn4zR7IT/ZM6PHl7VGOZwj061WpbzSCwng9+RXwTWuA6/w8YPq/7bhP9pP9CdlJpt9ViZCv5nHI79HRyL9bV6TvlIxrkntl/7nCFdRXfkoDOUwbAvl9ZhLkecQY4PNRAeR3bo6iIOxefw/wSYqDXdgVYRwUMGUi+H5TF+gJBeIsD8tywJ8DBvzNG3mWesgzvQ4dsmtvFH7qHC4+q/wCzydb3kDXmS+CH0s/AD/qyJkLYzJA1/mv4Dx4sJYfpneJlJ9BQ8HX1V7I6XVuyEnTMsjPg349jE8iaNoU/vq2nkh3QRz4WrwF8R3FP+wfG/jwPDEF8jhvodFEwBkNcJ2SgufLC3Besxry4o9nIFf24zfU09quIK6LiAgsr7Lxk+I77GznVPibTgmo5449oCt9gsRxyNcbCz8X8G1QvAA9I/xlfAH78fcM6HfLZsgnaxbige3bdbk8NfoEfvR8g2DG86BzubiN7dHWc0CHNpvx/OT7GSt7Dj58/gXspP04VtFDndUUVrv2AXbLnI6F+wQcPWpl3wo3CThyRPLTNE5VeKoz8qV2llUcXlm7zAYvPh7yNag39GB3BPxSXZfCo6bOFFGH6WAFuk0GeMvzwYicbGG+kuJbRKFn/MxI3J8519gl4InJMKgxCVDU56ZYYsMB0+yZ2vBxoPePSSDo2S79PuPTSjZ4yLFzg+naZP2cA6EnJuD65QV4Pycfin+NP12cQfDqO7i/sxTp582C4Vu6AgoT/ymed08Bo8eloz4khzw1IzIR19d1RKA4yIN86JenHlPAwoHECA/o0zsF9VuWj/tTp8FhZMmp2O8XwwHc4oHgkkMxqy/XM6oV8kuRDakH04H/pQkojxrS3GEwfZrGi/88/Rgc3c8G6EdTwbkB/coiKHqTJsBv8nj9Htd30pOGS8DWrajfy0tQDgX8bJAfHYt8HslEw3RYBugS60I9hkh+jU5H/fb4cL9JpC7H5h8o+AAP+NM5BQp4zxCUFxeHfPPydXYWcqHrzfR6JBMB6JjxoM9+Yrg4Wvo7bnDD/xsufqsc2aHMfRZ0WuUFH1/JBX9XrYf+UQDBhw1+srx37wq6REUaPwoY8xjy6+BGQ1I51sZlkI/UFNXAR/n0nOV5WDoCT5I/Dpgr0A/W32aRsA9pkk9XdIR8P3Q3+DRxmtFGQK/+QhuNOHP8FFksz2zwO7ignw2lXFHDlen5pNYDu/Kj6cKBXpRLTJQxzugQV/ipgHLfuHIAfWOyDkj4ets26MOFrrIXBGzeEoT/boPgnbcRMHg8CHTqRcJ+vrME/EmR9w8ZhUsE/PornjeNRL2+9YXNDgchaHGD5eEEdkK9zvS4Iw30WFkAOejiAf79+6pkuLYr9/ot/Uc3dHhK8ZB00Ok+2eA64FMJ9ZRmtlsV2G+b8qgDGLaPNLWc/dj9E6Fn96YjABswDOVe2RF6NNyDM32yIgNUNATi+kC/RqZBr2JceK+1tDt3peH6PumHPvbCDndywU68+TLod0gHvsj/X9Ms68sZX+XHj+k3WjZMiwtgB8nv87dzLaMQoHdLBT4D0tBxcs8ElNc3DfXp1w/0f+tN1HeDF+nzJP/fedOuHtq1N8jf/2tZb5t89ud4/L9qk7fzDIKS78HnuVnwt195jRIBTz0HrGJjg+SH5Zvkh+3i0DTYmcmZsL/fyYZldw/45PHrIccD07KQjjrM0eEwA3yck41zcgLKfU/mc7sH/L8wHh1m64rAt8tcyOd6N56HIX5TbLCyK2GOn3TDlOk5Or1wnYCx41GvW+QAxz3p0MvGDRSapmeON25xg/7kp9h+EJ2YbwUfqfds+1Eze8z+6999qt3PWMQxGOBwLYY8hRrHKurQWcXDYYpHbNu3ciiE/tdG3MaZhmqXz2gK//HeUviDp16EPC7LA47NQkc1zG+Er4HKCvPIRBic/+QhYKKGDQvE2bFQzJRUnOsbaNiNug8NryM+EGqvcUWhAOrJCjjQo95MBpLdPMh/fo4aSYLger3qtcIiAVt9uF5XoO4HnVkhX1kKgx0TCYWfOh4OkXou2ABf6kJD5D0vAsu1smevQ3sjVsBnFyNg/LgY5/d9SD95Onp+p2TAsCxeVnH55UaGeMRj4pTCNQIWSTp+I0c6X8kv/FLAm3kwICu8wLdtM7P6At/vtyFwWFMMw7bKixHczPHgz/xcmY9L48cGbOos0GWlF+V1TUU+xB4eEW0eZewX8DN18eEo/EYAfUy9VcD5F+Ku2102S8C7smedAnI2rItz4BA9KZqu7CjIIbLBmpGrRiBQP8Ij1IPLycgEX17P1z1ZnM+LsyA3NKWPR6joG0V1mMiFcaYACvzZEbd3IxCbmw3+vpYHvD8tUtkEnTnfqvNbNzTY0F7tRkOxr9SLZDcCvyU5kN8LzgUfbfCT6aXUb0ym0ULAyOHgf7oMoKlWXA/VIC9XS25w7i1Vd7T8cYBQgX7wjIwnpoMPFLCyXLmaQS7/di/4RnLOekgdXHbxUwiYnRn/tT6MGOXmgD75uZDHti79Wqjyw/L71CQ0fDt7tN3iQJ7kmp9fK+XmXBf08fbBoO+jk9YlCQheZK5wm4CfDwKv5yWefdIgz8eOAe/tPpz7p2j8ubzEBDSUX82rqh3W+Yb6x8RO6Ia0yo87Ep/LRYP/bS/wpZEc5lfbuJDlXuUbeGb99aRD7hbkarvA8rtM+wuNH4+8V2C/7coj4z8wDfWZOwt27ReKNMXxpxtw/s88yOGiBbimX/YHDz4GPzd8QOFHAryJoMd2nUzNlIA8bZENARqJ5+MtL/TojQLYqS996FB6KQdyNzcXeLV1WdaX9TDvFV1wjEEwcJAa2YJ+7pP2oXUs/Dv5S7ZTDzxgbBPQszvKpbic44YWkcfT/5gBOT5cqu/b1EPUo24d1PcE9kZXAH8s622XzwH56stqkjddD7Y3RyQfjhrKfoBPq1cHyQ/b4cIi0E/ZqclyJsnsHKSn+IobXG3jdL2YfzfKhtNeA3L14y7ECRt94O8XW+C/98iR1AP6df2H/cMefWkWz+gE6g/rVXD8ph7rs4VdMStP+y9+P4T4iTuib0yAH6MOdnUwvVZJ+3LQgH4Wm8cL6j22S0u8iCf/NR23+9wB+l7owsjqJXItDht+1Mwec/x2UDaYT76fgT1vLmeenSCOoZVFjLIz7g85jlX0k2fNz3DFI/wtt7V9C0DD/qXdODxUu8x6nCJnPBT50B74bpv2I9whssNnH9GTkzJ8DdRA/FhBD8mAqZ6BgPnSOBi4H30QlInj0BAbPR4GMGNUYDb6mhlwdaJ2bGyAj/2qn7MB8V/q++wYyeEFHjwlcegoKPhHMgBatgKB8K1yyle7eChEtEtPQVD5/GQQfLYBi0M1b450VD5PWTnmU8n0mQPFCvDgwOeYbuDp9OoPT3U94lOX+swKS/HNcY6TnprVlxXSrHzqSed8yokDpz8vHvcnyB7/OS/guoJ8NGLyDysAfVzN9W5oRNwuoHkLnYwdy6piyIPLpe8zX4mO/LwCfuqENv8wnWJl4tYu/dYmg2DNWlwTHRlPwsNCLuBQDsqGgvsa0CPehZ6nNeshn1HRupzAP+HiN+NLi6Ow3LdwAY+pj8OB/XNc2QwBfQZCHjbJDg5rfh7fkBk+AO8/lA76/GepWuUysFqW10o/zfSD5eVi2YO+qljbB576dNcABJwvzTtp+LHckR6wYSZ7pY4Q5Qf4qRHT9bJjp3cq+PPHZNib13JQzuA0jBhcFIeOvc83qmJNzxzg5Eo9vEk2dJPliEORFx0VF7kxM4FGWpmu64t1fmxPqmCHdUbV9IftAPGF6018CVXuzdBkuhDd+FzOnrEdrMDucLnl0sl8bcsjBzKXuGAf1EinYeD9LT7IRz3ZsAosnzogAg+mSwVug/EPTg45owZLhQfZP6ZvOftvUl/Y5aMVFFw+Y/L77P8pP26YNY4E3ybLmRi7SvH8E2/5t074P0Q9tPTHZoWZ1Ns2n83yrW55M8ND3Q9VfliuSA85vignJ3w9MxczRoan6SnMHK+RHHOc9Jq/Q0OVb3bmciL8T83iGQs/7c/A5F+gXVHJzMoLNX7i/Ofno8P6atkBTnEl69n1ybA7T49XxYZ6RkOCOvr52C07AugTKZYzaz9qWV51+RnG90I5Q89uHFOBfeO4iuST5aecfJpVNEzxSNjsmxmeduNw6LN9u8zxTnIy6FUBPY+LwyNkh4UZkifvfhAn9QgmK2odGRCUC9gULtyyL/c6G6LgkU8wsFYDnBfLKTvdPGqZc90jzoHTP9JV9kFnnuK2ai0cHTlaLj+1p07Hgkl48shbA5e+zwpAeLLDLGf4eGR3bDoCYQqAub6pPcCwB9KNzQI+XInyfvbBMWfejyF9Ghrn98eMReBM36gqw8o9U7X95StEFB6BgQALQi0itDw431p+wnJ+ETKw8d/W5bFDLXdflRNYX6ZXbfntXTk6qHJZYcvd5/pMlVN8ZuSi4X7kkA5kuFwa0eJyyqShpG/65LZFyPZLD/AslR0Vydep4mBIz3OBX8u9+r76ww6O8LV7MF0Jf1bUcvRgPJd40UGiphpRphcKoG9NWV7IsO0UsGYN+GouFxgRa+uC/NGUPx5BuPpPoMvCHNRr1BhTtMPFb5dB8Mka0H+fDw2ef44B/ZtHRdwlICMd9Y6JBh+s+YkAg9SQ+b/SC/lvdyXqRf0LLEdXdMD9/aWod6xL15fl4RzZ0Cxn16z0AyNUXvDjvnTVI4yZDJcnYiTG0x8Nr79lWOKnEQr4o/SF9b2cvLPc0HWgHoQqP6o4phN9g83v06JtzPe3CmAvns/H+d5x0KsPCtRrVmfV0wk5L5AN4HnZoNvkGeATySGX97T8lm/uPJ0vNxhCsMNmegU5DqaXLijgD/P/V+1AlZ3AN39RUZAroj93EJTTX5WN4luocq/eDzxzg+cdSaeeaXqKJ/ONZvhw/crJr7KrAfbbtjzyCMhiL+zLqHQ1YwP25Do35PnPnVFuObnkb4nJvwQeTE+iE9ejHL2UHDO9yuWj3g/0C0oPAuXepL7Qj9p+fD43CMr5feYflctyRn6fD7KHnN9XPsws+OAD+FsVkNaN1DMNuF4UMDG9GkVihgpN9QxVD63sjaJH4Nmk3rb5HJifuq5ueVMBONOhkUt/asXbSNBuC2byw3JPfrdUQK1IhT74RXxVeqgeKPvA+c3JhT/Y5EMDKuEcjIAHbn9E/orp0cal1/hgPxzngpzUL1PZ45rkO1BureI3lQHrM+FtZVdUesX/wPI4nxDiJ5UfNzDe8KJ8+kaU9bP7zXpmg0oX4hn2gwZQ1MGfDqxZJ2fqWfpR8N/cHlebn+G1Wz6JsB3HVJYPik7qbGUfbMYjyC4E+6b0JTBOVXgFnhlP67gNeldnu37dyi6zfL+TD3mkGYTqU0y57Rv0jsw86w2t+VNDh24BqI+HI94RMO5hCPANbhiSZrzraUz0mo+xH86Pu7D/2qh7gTelY8XetRv7fLaJRsX7D4XDPVbHOEfArH/B8LnikP8jjyNA6yvnvD+RtW6cgM2+QHqU7BbwyxHsZ3pgDwj3+BjsV6emDifI7WSiDexz+O2ZYNzgmxDAtUuMiRPw3ltwtHePjOGjkxvlndkA91cWF24V4H1P7PYaE71rD/AdLQPje4ehXhRwssB98RnODzwEvDq4UP4nxdifzufDfrFjRuC9P7hjmgv4ZgsCb/dVoPNfOoOOu3diP9emEp+7MuAY6h8Cvv/7AfQdcS/Sx0WivA1yRG9Ykq6vK4Zg/Q1wMCMTUH58IvY3KixGvdLkoi7XuVFfus+OqJ5chOP+DOR3wYVIf3Yk6BQXjanac2RPYZoH9U+9GYbylbtBl2+/QwD66GOo11mRCFSu6ox63PV/qNeVVyGAG+EBnme5QKf3lpfsFLBvb6BcINClZfQZ3/vlCDzxmfdTpG/Y2BG+V4By7nsY+zaeI/HvI799HTOq8L8CNm5A/R8ZZyYXqPeGItRr/kzIc91I6XDlSMGzs7APr+rh9GMN+bv7rqryGyO9b8uR/41yMYoMuXjCAxNR4vrV+PblP6+iPhcnQl5OwE+W5x9uAD3HDUE+teojYKwfbZwrYMoEfEN+4GfkN+5x6H1XN9LXbwB6X+mGfu48E/dvTTbVD96/dtNX4PstXUHfx5/Ae+fHQ54eegBydFUino+THQHB+AXux6wDXQ7ASE/Z8F/iAl1ohJHlhL59ZMdBenCugDWyQbnkLbvyA3wNA3L77SZc9x2GDq8R/2e0F0CLYfBia7QdEgfiGemQ7yOH1ftW55jzBPyyBw3dAw0wcv7aS5DvnT+ATq3qIBDKeUnlF3OVgO+2WtnhiJcFHD5qqlfcgXTHrcjX7Qb/N28p4SN4ylrM1QJo5gHX25Om7QQ3ZL57CXI06H7wpbEBPdwuFxMh+8cOtW2k+BLX2L3MCzn52lLuVb0Dz8jf9wP4PnAw8KLF/fhITsS5jdw/e6ss5+ZOKLec/eaAifwG6425POJTCJrJwPLXUzZEH5sO/p3lwicRY0dj8Y5RcpExt5y6f+wY/IjXi4Yc+VtugIyQfqGe9As7I0DXkX2gL01dMecI8MlFlYYNwntkH1nfCj8GPgPk/U7umCgB64pB755/qri+nW+QdHIj3Y6foOfkDzggv2Mo6FEmG7LLByD9P/LQYXbjH+Rz3DaoPkyXxfmQg7Ob4DwyA+m++hz694oMqMztOPxp6U68Z+6PZcFBJ1M/bZPPgXZHFVDt8sYBdp0y+P1/PAp6Nm0Ffv38U5D8nC04WCrt4MjpoGOD0phIASV7QM+hGciH4g2Wk3cKYB/UopjpGZC/vp1hV0dkwN+1jizZJuDtAsQd0ecg/7FD4O87dceZ4mD24xe6YE++zod+Dhmj4xmb8RveP3YI79892MquoD7F8pvdEfV1eVWKn2jRTvYz48eB3r0Gg47D+iM+6ZyKuG25aXwDekWeKfV6KOSTFtXjo3NX6M0D42H/v/kKem3Dj7If3707yB6z3Ly2RMVbJ9vPFK4SsMkHevwg4/rgOAZ8XCG/cc8ci3pbx7Gwm/7Fp9DRRCPNbK/N7YNtOvKMsF8PSz173NS+cVyxWsbVQ24H//xxKvD0L3Kl7QYrko24jdtfLjnD9A/Wdpnl8ulJaH9d5gI9pk6EPPxJLkp6QSLkt74BP7J0Wcl3AiqY0aMQ/q2c1UiP7rkOsWK6B55XU6VFVtSiDKoHwCI/CGqDBrrngFfBohFBkyMpVkDDRnqRHJN0v7XbumdbVgwjHrRfYMCB+3Xr6h7RwOeXCYoTvWtov1Q1MwD1aesykzsruVDvqSnfOj+1mmdAvavrUtNf6oNZuVb81PVS/GK9okU1TA6Vn1qMSemH0k+T1yxvK30OTBgqfoHvV/barvwE5q9niAQ8UPYv4LbtS81vHhFp0iTwRbv5q3RKrgPzCfe1xjtM+qLzs5B7s3povvLMjxi28mznbeZXWXk0k28zPE/3+9ouSP+Ma9rvVK1CHlBB5W8Dbus1KrTdtenvA/MJ9Vrhqf2DhV00y7+65c2Mjmb42b2v7T2vFvuyXAyzaVPYE9Ijpk/7RNDrzRW4TzPP5KHTyRFdpG8Vreij0pmdNR/UyI9F/GaWz8m6D7v/tNz2MCFR6bsa+YT83j8O9fB4rPDQdo7rSd922zxUuWbJdb4m9lg/ryY/o8uzaX/N6hXu+5Z0lPRRftTKvoWKn4qz1HugU3Acrp6HeoYcRker+F1dh5pPuNPT3AfncCjgUMChgEMBhwIOBRwKOBRwKGBNgaSLBHRJxUjonGkY0XoqFyOFnxdhJPQSOQJTrwwzOU6w/Zd1kadFCtUwAV12H8UI1Ms5oA+NAPLIHa2qzp+0uROwSv7Au/XikqdFLR0kHQpUDwWcBmr10NkpxaGAQwGHAg4FHAo4FHAo8JuhAGZEXZGIBtif3WiYRjbDN8i02N1nAt7I+81U2GZF1AgxGqg3/hlTdC+Lw9Rh2veYp8LPfcFpmNokqJPMoYBDAYcCDgUcCjgUcCjgUMChgEMBhwIOBRwKOBRwKOBQwKGAQwGHAg4FHAo4FHAo4FDAoYBDAYcCDgUcCvyuKVD7d137aqg8Ppa/qiNWrz3/fKzuusVXDUXXaBGY4tI8Cquh9euF1T3XF9UoUlS4xitWcKRJI6w+2bgRViusU6dkl4DDh9VH8fo5r3JI6VoLoFVamwioVx/Xt/fDKmxFIddPffyO1fnu6BOTJKDoU7PVIEOlH76JqVcvpp2Av3bDqoC7SrEa94H9arsnrKL3UynqEbgtQKilhp5ebSeDVbrbxQO/8OvJqVLf0ClUuTfUN1FYTbN7CuT5l0OwQz+VVi5X562apgAWyYiPxyqg114HfVH771Yfdo59OZ7Wvzf7omr/e623rj8vXhQc59n1a0h3ZUex50KM65Y/Ix7Zvkutpmv1XOFxupzVfupVjZ/M6muX7mbvO/dPDQqU20Dt1ECoprDQ3wyECQGsgpWYiG8yXngJ3yJ0SQ5T9qdsNmoVMyA4YQoWTXgq+5RBmLeruPJSLFu+4RPw5c2Xsdz2Bedq/HkZ7pu7Av/tO/ENycwp+NYmupXRVECrKCzbPyhNrT4Xcj15Wf0H07FM+fPZxvcCaJ+6cB1niC3Ue/XDNy/zFyHb2GidfSOxnMPtKVi84cJ4fb9G/nSU20R1Pnl6UkP1Dbd9sc0eXgb/lm6Q23mLsK1NfKLt952ENUoB1cGgOszQEKD9Inl7omdmwr8MNN8//GRj79iX4yn8e7MvqvY1VG9VfGXPVd1VwF6cZ+7X8D6t4suLJ3XujO33Wsn9YFd8YPW8svWurvcC7ZcuN0zx04n5Z053jYfzx6HAqUwBJeDocXkx7A0pGJhn5HLjkzJPZVqEEzfQ9ZJ4jBAeKAtn3uHIC/xeviLpKgFTTPmChueuzUjf3xOOssvngRH21rGgU1lZpRu65TOt4H/S1QJ2ynokOQ2UCmh0Mm6dbPtiF2c0cL7YrFfftPuik65GKaACVMhRr1SFDOzEqAzwNW+Ful9TZ8e+1AzlTxX7UjO1r3qp0J83qqw/lY3zoMcfrkB8cW1HVSPcj4qyeq7Sn6pnM/sVLnzDxb9w4ePkE14KyI20aeoj72dFIyg8cpTSGSNMZzRDz/vaYtzfXVpYJGClV48I1BVjS4MGY4TpSCk21J49D6uVnXM+eobShmDZ7Wcmoed3xBhs+PxRQeF6AXNzVLUs8+UNb2vXAV4Dh2K57i+LUN4f5QazL2Zh5KteA+B1y03YuJ624eINwWctxEbm+/YDn6UfAJ86Bgz+mIzCTwRMmm6FD/DfuQuK2KAB6HbP/dh4ulkZ6EEbNvOx3oez+S8aKjfI1fBoJIlH2Gig+xcB2QtR3hcbdYOJNxBPikN9dkVg9bwpE41mAiKbAx+iE79PU1A5/VWJGFFrHocRwEdHA89uXZG+UzKus7JAn6++wAbyPboYewU0iARfG0aK8TnjjPOboefv6dzCDQJ8PvDjqAG5Ca6vbbryfljW9AguweIOy/kxA3Lyq3lilY7p508Hx9GpI+jUZ0hhsYC75Yb09vUJ9P5mo0aA5fuiS2B41Qbo7xdgNcT5OTqdyR/gFR8PuRnUGxsv744AP+q61GvIn/Y35fIGD4b85+dBvtYX2ZZDuf8w+DygP+qj7MbzctuBI4dM9fWY4MDcszGCHb8A6RpKuZk9H/im3oL827hQD5r6yz3OXVKA9+xZqMehQzgPSYecf6Dti1l9kb5kO/AeNBR2arUXcnGdG/eblkFPHny88EMBNAVcTumqsn1h+l0cj/r07Q18mrnAv+wszQ+2z1dKefMMAT6v5kLve6ZBT/8+pHCTgCNHFJ/1mflM+hhwqKlWmBFw12CU3y4B9Sf68Sqc83PUa1ZyYXwr4OtvjbYCBo8EPdtJP3LAMNtuAnJbty7KqTq/Nb5yf1PwaVCQn9L224qfPxkEmzbBrvbsBzq1ioSclfhgT29MAd2eyir8QsCGItjpNrGQo7TBoEdkGeR47RaUvyBH4avOsI/dUiEHM7JR3rKcpEsFHDDA918M6A3ZG95fmhqwPLL6F6kXWVJ+PivS+bIcUSDMetd7CN5fmW98LWDR64X7BBwNFhSZgWNfBCcc+6LlSe0HW0U/ovJTZ21f2c6HED/ataecblY29LKLG3btkUzoxWx/HKMQkme7cZ5Ox/FWrz7Kr0HfZ+WgvPvHIS67zI3sBw6Bfp8ZDTwuk6sjBz+HHX0jTzdsTfTZOFdA+w6wH+Z+A/FqVCszO4n3Ke4uE2DtJ409Am682dR+1ReWp3Q78jWLn2hA4ITx7b9mBfGP4/v5C1GPqzsqugOf7H+Har8V+2GPO6fCXnZKgL3fsQd8+q8P8cnXGws/F/CtP55TGTjnSlGgltqAGoz2LkUuOfPA4K1bcD1fTg1sEQnDcaZsoMyca+wS8MRkOMyYBDDquSl476qOyGe4B4IyWjZMiwvA2JxsBI4to2znywIYKwO4IWnIZ3Q6AtU9Pgg8BQ51BCz/CIHAUzNgCPbJBuqTM43zBJR8j3Rzs4D3V16jRMBTz9nGR5GdDensmahvaSkChX9MQvlnu1QyszOmQjRpgvcfyYQBGjMe9dsvtwNqGa0DF85oQJoRLeCeCTAEfdPQYO/XD+W0jsb5rjSc70tHPT/2IsDtJKeS0BTXwwIOGciHGsTcMP7XNCh0bAye3ykD/0czEWg1M3C/oxt0fNOyJ9IuXe3SA/Wqwu/PQnIT3TD0d3kCz6hfI5cq4fgpwNdJAzjIo5+rjefZkFvrk3pPn5nut8kAc3k+Gi6kJ3JDcp0u4A/kgjZC54b0e0uB91Mvgs/L8pCc+HXcQQ1UdgAj0/BejMsu3VFe8yi8//bLkPcX5gHfegYMOE1ZttJXnoLa5nGko4YWO9prk/F+ixaQw24p0Ot70qEfjaV+k75z/otewvObUoHPB377cpkIFaKlHgTXF/pAesL2Ymga7ODkTOT7nQ/X3T2wb56+ms5VtS+Ml8uFcubMlB1L04AP8Z0DvlXrdQOH+UYNVO4QJHvKZ/pkQHVg8bkuET7Eg6e8v7wEfKOGDHfIPDoWjviRTARawzLsyoURJ6B7V+AVFYl9/sY8hvp0cJtix9suhI/ftu0MN2BJb6z42VCEcCqAS5F0p6n5zKdLE7TcM1+mT9P15PeemIDrlxdAL3PyoW/XJOt0gX/YLr31Jvi8wYvHeQWQk3fe1MkZ7w4udBBShyEf1HBle/6kxgP0SPOg3Cs6Ip+H7ob8TZxmtBHQq7/ON+CPlnvHvpDFdOzL8eIRbFdt24vjMwq4CiF+DNWest+bPF4XeEBo0KQnDZeArVv1/cA/duM8tsetoqFf5fyayo/1aMZU6Pd+2cCZnws7snwZ9NT8eWj6fAK/wfuxtuyHck8Qz7NfsO8n4S8rsF8/Co/w7ivwMxXET2yPqWOOjxPEt2b847jr0LtBdK+k/Ybdo4Yp29nR6YXrBIwdD/92SwriDYpL2I82bqDY65zDQ4FaGGFJbI/AsIULgnPgIBi8cjXuU9zDCvfO2zinyJ7d+gYaMKPuQ4PliA+KtddAQyl/ukYzxiAYOEj1IKEcajCyg28dazffsjkCCj9Gegog2RHPyFU984VfCnjbC/z79IABOF+O5F4uG1ItjMIlAn7l8Nb49YjE46hRuE3Azwft4oOeMBkXGN08qM/8HIwk0ogOByxer6aD2Z8zDQLC56CA9m403OdmQ9Ffy0M9Py0CndeuBp0feMDYJqBndwTSpB9sQFtEgs60KBFfb5GBdq6k01teNADeKED+X/oKNwp4KQf5zM1F/du6kM8mOWK1TtL1La8aYUZ9R47Cexe5gDeNCJkdLEc25IcbLmX7LelhVo7d+9yT9z/pID6UAXrgmeRaHlpuOIBcvEzd1+d9QqNC0Cf9ovzD/HpkIuj7nzzQ92cDPZxnxwYm19dsQFN6gg9FPozofrdNywHL4Q6fSo/7q1cj/+3qtiGk0JYc8hsU0DK+y73oOdy9CxmNnwKD/rdhuE/yynyvQF9XFxK86sV76wpwNgzoz/btkM+PiiH/633Q8zk50O8XFgL/Ji6UM3Ec6jU3B3r3k+Rr62iz+oJOhXJjecKP8ZwsR55m5yB/0l+mb9s4lLNvb5XtCzvS2z1oCH4h9W/vXsxQyc+Dw9vtAz16/xWOcNECRR9jh4AHHwOdhg8IdT89NHzVN8dud9ksAe/KEedt22CfF+eg3p4U23LBgUyERHNMptFCwMjhkMv0YRr/gD/h5rdd+w1/sn+fJT+5Z/z7bfCHa4oh96u8kJ/M8dDP+bmgW1tXQPWkf3llKfgYE4l0U8cHpZM39Eg4j4jSTA+Wv8Ol+r56kf3nWh9GbHNzkH9+rpRXl0oGfaAOTP72y9UM+P7tXviBFV7IIXU8mx2OfSEJcOxLoHiY2VXb9iIwQ3XNfjnvFXUposcTxo+h2tP9BsHPR1X+yn5q/64eyDPivGZSP6zjPNjxrT687vdrKtvj/QjNzGL89x9ScaPVc9v6zA05c78BfP4i43vzeL5stoB1xdqPW/lJNZMn0H6VFBIcrgO/XkH8xN8yW8e3gnsV8o9n8G2RcZKf7qBnJew3NzxvTIC9pA5xdXDcs0rGKwflzKDiIvXYOYeHArXQ87p+HQKiT71QlAdGwxGn9cb9GeMQGB48iIbnpXFwgD/6wHgy3GsEjB6PgC5jFBy+1n8TbA/5kD+N2HFPjo18VU7ctCTFZgcdOPWSpoox9JE9HMkdoRALc5FeBVAqswrOdvFhw3K1NDANDNT7mB8hHhHyX1ZQEt/S9OUr9zUIYOJdoM+a9eBLVDQabDSCBAMhRyZ2lSLdJ96g/NUU1cAHTD9qmFd4UA88KyDxJfDgcilgkkdZjoBi2YCgDgc+6hMhTA6bdC3LFnBQMuoE9DApxvZtps9OHxztZ0WBZ8hRBXIcQAddHvfEhqBP+kWTP2wgSU84QKxnkohuMz+TkyE3fv7oF47Tlwg/f1h//PWzLYcs9zRyxB1EsS5Vjn6fn+8pVfeBX7C+6ufco1wB3pBffz7qBR5xM5NflYjkmI9apvVVKU3pxuXTzALGr5ahp6JW1b5wvrFy4/bWLo2H+sPytcqLcl1ySlGgHTlWAcFUBhZnlidaLIvLaWhE3C6geQv9FsvFqmLIncul+coJzPWx8FMBr+Yh3+EDgP9D6bj+z1I9pVgXFPAnXPy2aWcibhNAM4vt8pPlrgKyc4cVyQnjX85u8icRQ0fBnn7khf9ZtgINwltTA2pf9UvWc8KD61POXjC/L3ZBD1cVa7/NDe+7BqCh+tI8UwQc+1IBaRz7oolSWT+iMwj4g/z8jingMS7LxY+h2tMK8zvBTW4wX52IOCyEOM/Mr52gKFuP7Ooz26sT+A2bdlLjBPusL/Ufvu/3k/q+2R+z+IkHaEKIb83yN6N7qPab5XB+PuKcq91qtWrY8+uT4R+fHm+GhnO/ahSohSmiERFoqJbIqUFvFyCw+NeLCEz+7mcAC9BiOdWom0cxTE+pYoH/h1yVtLYfu88NAipHHexA6ZLzowDSbr7qfXVmw1GuHBbATp1gSLq4y54TMCULDjtSTg2kb015SghdqwYkK1gjl55KyYH36/KbTqt6rpI9UBQwc49Vak+FHgIWChQ4vwYufT/gD3roqOed36epD9xjePWfoAgL5UjGqDF4jc5soL7ygW8ffAB+qRHwupG6x48VjOjMBsFPfl08N4DK3WfFpmumS7n76gV+3lhdGREeAXFxwPN72dCjkVsOaChQC8zHJp8jBgtoW2ZFjysKBURE4BusKxLVtUbQ7A/ThfjCDak6Zqkk/pSOp4iUS8f0p/oFNuR5ynUI+sT8LhfQ8rdu5fREYab0RF0HnpmP78ipoTe4lRzrKcmML+HPekffSquD5Z7KZzpQA4y/+bUhh/zt8eJcvNfZg4bbTXLkn6Y2sbwNH6KK0edAfVUPFD0D5ZH5VEt2yJSjE8sXyWcg/VV+6qzkUF0H1FfdhrySHSkVQOWpQ+kD14fKD5d94fzfKEaDhRwf26NyfOEGz3kug2cS0JRfVV+FF8tZnXICqR6YnFW9lbyxnK38EPapVHaAJF+n32Z+UPlst5Z77coF6vG3DOS70gs5aHcl7BW1f7n8KzrocgL/hIvfNu0MRno6sfQbZTb8BeNPcsJyXIF9DLR3bDfGpqNBSA1BlqfUHqDPA+mB1Q+6Zr5Rg5hHIhpFYoaK0i+SRyWf6kVl7wPxwIwPL/h5XzrsJS1ix9+kXp6ImTme/iqboLNjX4JIwjcc+wK6KPsSqh+pmKrS79I3j+qwih9ZD5ZI/2fDnjK+v+oGsJrCDj8WFaWK1efdBsGqtbBnIcR5Zn5NZaz8MvuxCjr2zZ7b1Wcrv2HXTip8OT8bflKlN7Nfii4V+m/r+BZ8aDxPFRPEP5V/YDwRqv1WBbDff8OL+IlmdrGd7X4z2kdveVUy5xxeCtSOiRbQqiUaEtOeBuM9curZoJ7YNzEtA/vnbd2Cb4yWv41AzhUHR/vI43DYffsgYH0iC2jemoZzshsjfDt+Qj5x0Qj07hiKALOsjnGWgFlPocFlnm/EawLauNBgGOFB4HaWK6a5gPeWQ4DoGwIW/CFDIxYJGJyO64hDOLtT8d5/vwLenxfB0f/jUQRSTVthkY9Z91jVEyMGX/mwf+OBPSj/8TGop5rKmiC3z4g2sN/kqmLsQ7hju2In9rNT3/bOn4ly60aCnm1kgP7sLNBx5/8kvo9j5PnGP0g6yuxucIOPvgdQH08DjCA3dcWcI8D3FfIdNgh8b5eI/Upp6jQboAHyfid3TJQAmtrBDZs28uP9OzOwr2KZ/Ei8R2/Q8ZmsEj42bsS+nqNHACG3G/tdbd6Cb51eX2xFV9SPBs6Yj+b0iHhFQIMmKOezDRGvCpi3APuHqSmnisq0mAgvhpLmQX0GZKC+rVzg15fFMY0EfPcd8H8oE292SUVg1zgS+9kWyZGlAbfi/T+4IX/fbAHdf/ifbX1iet/SFeUQ39iw7toNehG92RD2H4pyjtVBvd7M99cI/2JqCdi0FVMqL28Nuk2diCn8f5KLh12QCH2tb4CvB9sj36GpwLveIejlhwtxnTvXVA6/MghWrTZaCriwLd57fDrkKuWvqMeE8ZDrdvFm+gp6NmsKfO8fBTqTPJ4rYJ38Nvyux8Cvy13Ib/XHaOjcmYLaX+/G/S1bQLfz5UiRsi9GHejnQdnQGz5d1Rd8Ly0G3iOnI1BvUIp96Er2AK+hGahPnPz2fsHHuN+na6XtC+vTM/9Avpe3gbwMHAl7fKWUg01FhWsFZM2CPN5zL/B0u9FgOXYM+9Z6vYHyoK7RoCH7ywHciAzgTXzmY9m7kIfvdoCejz4GfpwVCTt8VWfI313/h/ca1MPZXB+R37mxSDdOdqjVqg9860dj0Y4pEwL3+VUdKqD/g2Orym8s6vaspT8B3deVAl8rf7HjMOh/603Qm/hE+MdCuYhgWhrodZ0bfKT7bL/u7BPDRyc36H5mA5S7UvqB9724H/wLeb7UBTkZmQH92D4D+fbMBL0vcSH/9VKO7/DjwXq0pgDy/s5bwJvsDeP1+BMo8fx4+IeHHoB9oU9TAg7HvggL49iXALGQHZrkt7hDhOwLd+TZ9yOIg+iTgoADcj96FG7biB+5wfbMZCzaeFmcpT29OoaAZgTyJzmeNNib1JuhB68tUfuPKrRKdgv45YjtOI+kJablt2dCzwbfpP1anIic3nsL/qpHV9iLXjLebiz98oavYD9uNX2OeOuTVVb6jHhxxEgzvxFzlYDvtlrFYxF5AmimD3dApI+z8pOIL94pgN2KlQNDZL/Y7nz1OeSk25+Af7n4iTtkvy62jG+5429BQ/C5237NP25IfvQl8qe1NbiDleIJ3l92/Q3Id2SCbfvN8kzxBDe0x49Deb0Gox7D+iOe75wKfi5fHig3Sn6cc+UoEIEA5s8ygLnaDQF8aioY3Lw5GEIjKjwyOjwNU3n7DlDFoeeCFkvh1cJKd5vN4Vfp7Z6rmm/SGQJohOFCAfXqqSlqaoqZ+uZA4ZMUK6BhI/0Nqnogz3bxUT05UJhatSDI9eoYsQJ+NKWPHunij8hpijL3bJ11tvFfAd9vC1xdUS9CcIlBQIZW9TDKkRW12mhANSp9mXSFgAmZUPizZMA0YSwM/Pcl+DYq9CmHZnQNmR68Kl8r+a2hv+Ff6QpX8sWq6lMliw16DSNZtDiQT8CuXYZLQFSU/tYv6A3cCJXuKhvV84wZCz/+uC5JQFmZev5bO4fdvrD8tozCaoM/H4I+7d9fXXTTI7jc43xmJL6BLtEdaHblQi+6x4EfzQTgDheSO16tPTgQrbb68eIb5n4qVH7axVvTlTsIGjdBoPPrUXwz+lPw1HWTjK38k8lrprdhp1pKvuzcZZrQ5IFjX0wIE6bbocqjlXwofleXfbFrL8JErqBs7NZXf7LBq1iXlQXGWUEZyxuVjfPM8qvqfVVf2NnQ9VmVbxaPqeeVPVvJZ2C+duPbyvIvsDyzawxoPJ2NDvbns9CwVd+ykj/hhmuPPmgnbfchvsrJMcvPuR8aBWQDlZbb5pGcy13oYaA51zyFib5t5B6JPyajJ2aBXGTnPW9oxTipT3cKJHUU8IRuoMIQ3qE7Kk73+oULfzgKR5/CRU8nH4cCDgUcCjgUcCjgUMChQHVRAA3k2rUxUrz7KBqiL+egnbSiAANPTSMxcOdOwGr1A+8OHPiqLnx/q+XUxtD0u29h5HTrj2iYXh6HKVkNz0TPQfYsjEB+sva3SginXhVTAPtyXRSPp5dfipHhg6WY2rBrD6bo0Jx852AKOPrkCIJDAYcCDgUcCjgUcCjgUOD0pEDJTwLKyhDPzXkRDdK6tfEpTGIcpmb/eBirCU/4p9MwPT357GDtUMChgEMBhwIOBRwKOBRwKOBQwKGAQwGHAg4FbFFATvGlb594MZZbujpzqG3R7ZRNhDnzlyVi5Dsm8lRbZQxTJ+rVwyImPbpgUQLvauwn+IPlSCy+kYiJxZTzm/+MKeifbYTcfrzajDFqdd+IOwXcJLcf2roRU5W/2Gj2XlXvq2+ege9tf3X0q6oUdd4XFNBTkHhfy67d0MO7QW6TtMkXLjugvi3G1KYIa+LzYiWHj0DeI2phxsVtqVgtfvaccK1RYI2Ik6ImKBAuuasJ3J0yq48CsCvx8fik7MJ4LDa5OK/6MDi9SjLTK/3NKK8d0KMr4r0Xc0Ktnf5mmNesuKk7ZlT6NhZ+JuDLkxYfhYqnk/7kUEDtxgK+r1qNOLXmZ0bWwse9j03BYhaT5aql4SMClrM/Ozp8OTo5VUSBpIsEXBCPgPC5aRC0PmkVpa3Re7w9Sa9+aFjOXwRcaD9GiwMKFCf3hZ0xAQHzFh8W83rrI23ATfLBtjV/SsY3BbnTkCypo0ny8N3mBkSrKATsg9L0R/3hK8HJ6fdIAV7t8JZu0IN5i/BJRnxi2O0Ar8751Scg8aNTcH7+ZTSIS3bifL9crZvu86IR/86HXj4otxt7Ptv4XgB90+McJ5UCNeVvwy53J5VKTuY1RQHtx3nbpGdmwk4MTK8pfE71cs30SjcouQITpiCOfyrbbn2C7ATb57/8AfHRnGnwK+1PfnxkF+HfeDo98FJT9WwkOH97Cvz5hfKTvppCxl+uXGV21iz/rTD/45HZF14Kc65OdgEUKPxSwDcbcfttb8DjU+YSI6XzctCQ/slnGzHelqNnKgJgn9xv9V0vAvPzWpbNFfBZsVl+GCml9Hx87cP55P+iR3OzD6uiXn8Drn9RO7yffAScEn6TFNAjDrwM/nc+Vclw2QG9iigvkpeZBf0ZMgD69lwWVvM+ZhSuE3DPeDxPvQF6Tfvx8kjqUy8qvJxzNVGghvxtuOSumqjkFFNDFIDdoo5lHvGjfUud44QUMNMrPROFGxbPTDphJhU9DLATeqYd3//GV9Erzr3wU0B3FPBq9xMmhL8EezkWrhbQcwD003zbM3u5hS9VHfSU/HIIgT9NHePtDmjbGe45p31MeTXfObMQYH+kp1DqFj83HAYNRmBypBRThWfPA4rU4877JnVxY6P3R+QqsFvPwcfGbTbj+afFKO+AgZHcaxLw/OAeTA2b8pSxQ8CgO4Fvc7kNwqTpVnggcNq5S29/cEDs8HdbX+DZIRnl5GZh+fXPvzCaCejZD89bReJ5iQ8jfjemyJ6qLGwTsKEokBUVT2GNlvso1ZMb1ZeWFn4s4PkcbJR+bUfk23sI6L0y3+Blzxe9rpY9R7r+HuCTFIcAcFcEtqOZMhHbUhw5gh6Qozbm4gFz5HtWNOjerw/qeUEC+PJuPqZ4vJaHEcqrOiL/tCHoaSPDyD2hI8bg/Y8KQO+5OYoueioPB9KDemNbmt0RCHDrulQ6szN6XLvLfWv7pIAvvxpQ7DF7IJckBwMF9Pfg/gnowwb4qC5Ob5fAd4bKfXn3KTnOMSIFHPwZ+0IGyw3quz5IDlQBqH+njsC7zxA00O8eALonJWKK04B08P3ZLLx3dzros6EY8j5nNuj94Cjwv44BfB6ehKkYhw5p/rA+3nIT0jU18P6shXBAG2UHBuk5b7vRORXldkoA33fIfW3/64M9+Hpj4ecCvt1oJaeqvtg/ePBI4NuuGco/YKD8h8frdPIP7EJbF3rSB3iOfz4nB3Q7eAjnQUMNHjlc64X+vO21xIu3v2rfAe97hiAwejUX+tNT2rftEcCz7mbQ4/0CbKe13At5GizxaqHtzvF4Ej15BsMD40D3BmXQh5cWotyunZH+jGbQK9ofkxt+q1Yi/bCR0P/iItB7SZ5VvZRdQP5+edZ48X5z9u2Afk/+0fl/YRA8PT3wudk15DtrOvAnu6IO1ruLLoF/GSFHVonOPIVsfo5KZteeq/SBZ+yn2rQpVle8rSfofUEc7GTxFvip0lLYrfffxT6+R38x02/Qt2Q78iH544BwtRf8uk5uy9a0DHL14ONqey/b/qaV+NhBfeoQ7CeA5+JllvaZ/TatHh7ob9mPz85FPrT9BM/ouGsw6tUuAfX4QPNB20Ne1X/gUNDxyyLYoz/K/ZRfzILdKQq2exZyl3SVgB5yX2nKj0fcd26BPk6fWrhRwN69kJ82sahP2mDQPbIMeKzdAru7IAf2g/bhZP/SORnnWgbsavZCpAv+hAP5h9H+Xis4Xr++mRwpP6H1ggPSE/hbtU1eW2FRg+0p5CFb2rG+Hsgf7ee+V8Dy9/D87r+Dfj+Wgr6znzn+05pgebMbl2i9M8HPzN7r97gDi/ppOb4k+3mlgF6pkNO/pAD/LNkx9pmWMyv5QfzWsjnyuVPuB3w4AnLx6gKce/eB3FGYxPHL/AWQr5aRsMudb8Lz3FzwbZNP4a3jEZbzJBknnfz41TSu430+yf6zHikszc96lwEzO6HiI95ntKHc55bi9noCGsr4/GHbdk7JvTlGeBL2eKSNQXBFh5DjVY6L6BMys3YN06e2bDeZ20fY1XoNkE9wPAZ93Lcf8rf0A8h7HRXXZi6vdbYAAEAASURBVOi4lu36xfGoR9/esNvNZLyULfVjfRHsypUyzqwgzmE5//sQ3U6QDIE8xMYi38GDgUd+nuJbZe2rFb/tPidLLg92ZC1kQ8qdLBXCgENY+REC7YREBMJnyg3rZ841dgl4YjIIHpMARXluCgR6sj8g5YbhpCdBiH/3geH0eGAQ6kXi/XeW4HmKvH/I0D1FbNBoWWdWyG/lN1Y28FD14/fmPgsGrPJCcF7JRXmr1sNxuxbjfop0dDRFjQXy0gTQgxqYLLjT5RRRlXm5Myt2VCs4yO4pMIjj0o83iM0iQcc0D9Jd0REB1EN3I1CeOE2ol9GmV38obrdUlDAgDQ32eyYg375pCCD69SuHQSX+Pv0YFOVnA4o1MwuO45VFaHA3aYJMqYHK9R/uAZ6jZcO0uADv5WRD4FtGAe8zmqJ+7y0F32hEhXtOl+Uhv2bWuHKD5K2lyH+dD+c1PizrPeOFKtOHDW9HWa+4ONRv5nN6n0ILudEBcUBN9BQcdhzXdQS9Bnl0MqbDFYnQkxEeyFfvFJS/LB/3p06D48zKgn68Xww5ucUDOR40VNOZA57lH0k6zwDd98kG6pMzVblITw1TTj86HSNgY8dDnm6R3+bekw4+NW5gV06NOAHduyKfqEjwZ8xj0J8OblV+4LmwSMBWH+hzsBT4356GAIdGnosF0LfJvA/zFXHIv0BO6bbWH5RHhlvJLZ+7+ANZTvCBG/QYOw7y5Q9IQO9WLqzWt8EXiL++Zn5+6EV97x+H+1u3Qu/flA0Myp8Dsk9WIxD/cRfq0z4OfF672ja9dcGnyR9uQNwmA8/l+ZB3shfxAlpE2fYrVtVl+k6T+9VRRw7vJz1lBvg/Jxvn5ATIE+2TbaHf4M+FfSAfQ9Pgt+hTGG7AfefDdXcP9NPTV6NnlS83FMnf8P6o5n4C+dmwz2zHKvC3LoOA5JDl8+UloDsF/GyXHh0LeXwkEw3TYRmoV6wMgIakQR9Gp6P+e3ygR5NIXU+bfxBAUQcU17dzCjoq7xmC8sjusnzk+UfU2I8+IUcUXl4APuXk4/1rkrVfYn1+JBP2Ysx44LufWh7iaOnvIMEN/2+Y7K/O0ILfx/sJG/y0sKdoSKqOxMZl8N+pKaqBDzmn5ywXw9KxJkX44pLK2ntNL/WH/VAHFxr2DaVcUcOV6fmkjrPsyo+mC8dtUS6DPynqEIeRoa90By3izhuTVQcsrmmfZrYfF7rKXhCweYtCU593GwTvvF3t8atGoIp/rOyEyp47UO+QHbgrC2BHu3jAl/627dzxcq8y959PWjzCRYQQr14sPJCN9gTb/RPYR5Y7GtiyisfOMwhKvke6uVmwx195jRIBTz0He+xywT7OmSn92DSkI//J5axaD72gjjw+ThDnsH2tSw2Yig5qoLJcjEyDfY1xVdm+VlRMJe75G6hcgR99qudLjfTA0H3shQJTzyenS5Hn+gZ6rEbdhwDriA8V3Ct7pg75FE5qGWacDzbA/edzwaA+aWjZHzuG6+0+nPunqPdRbmICDM2reXbxQODTXPaoXu2GIaceR2ZwshuBypIcGJwz7oeDW1MMR77KCzpkjoeBn58LAaERH5MDBo828mUF/1iOlLwv6Tp5OvJ7YjroSg1MBCrNkP/f7sV7K7wwlKQw3GO/djXo+sADxjYBPeVH7ERG7slrEXLAoNFnwZw6CwK60gs6dE0FHcjPM360ITEb7rxX9HsxBsHAQehpmZUDulCDiOnaOhb8S5EjGEWyofHdNtUzg/rv8On8TP6oEQngc9gAnQ77IC/791eaPown9bBywNQrpex5AQMHQv4PHtQBMz8/gdwwXS44NxD94ztWaAQk8ODyF72ub/MMgYlTMHK3KA90/EaO3L+Sj6k+b+aBPyQfHGC2bQZ527cXhqxPD9D1/PMhF5fLhlcLXQwC1RsTQEcKONXBcrSqAJcH5YhncZFtOWV8SF74GJNptBAwcjjwTR8mH5ifWF+enQ0+R7tgeK/tiJ51ashzB9qqYi0PHJja0B+W70ULdMFM5wcfwwjQ8AGQxwIX6pkn7cDINLWoFuh8XXLZPAFL/QG0zhB/ZD5e6NFGHxx5j15ouPywC/gflR0Gd/SBYz4/Hvl/ugU9piXbbdM7oPxT/pLl65GJqOd/pHxThxg3RM6OtWvPNV/MKszl3OgG3fcauiOA5Yf4ws+/2AI7S+7PSr95pOGAF/hRg5T932TZcz1bjvB7vbB3beNs2w3Ol/yNlZ+wa5/3iy6Un0nAcCh/a2wVcP6FuOt2l80S8K6c6UIBOevt4hzg70mBPSF/w/Wk+nJDYYbc//zh8ehQIj8R6sHlZGSivq/nH9+T/+IsyP0Nbv2Nosqf7eQrS6FXMZHAd+p440wBv/6KwK29Gx2jc7PB99fygPenRSqboHOY7K9tfis/YZefdu0p10M1yMvVkkdM9paqO2GPS+zipxAwOzP+a33oEM7NAZ/zZVxYLs4KVX5Yfp+ahIZvZw9GgppFwk8qPb5Wys25LtiF2wfDXz06aV2SgLKyQLQLtwn4+SDun/z41dLeBSJodW1iJ3S8ot5ne/lcrpqpBHtAM0eYXyHYOSX3Kt/AM3cUnYR4JNR41Wa7pmyOgMKPTe0jf2r3ttcqHtP05gbvERk3HzW0fLF/uN2DuPsLn+p4gv3Nz0Mct9sHcvb+K/TmBHHON8IjHNgfSH7ELatXg6/b/Y+ral/9OVXpXx3Lt9mBF8uRq6g4NFialMGxU4OWRzgmjlP5aIPNAWQjdTv4zIFC7gtwOA9nwsFQg5HvF8lvC0eOQ08CjbRyj8T6Yp0Rj6hcGmeJB7/XTo4MqhHiqY+rqZHKAETcISBSTknsZKA8XZoBx3dIjqBSYGN1sIL/Kht4x3xByRmvi2UPyaxiOBBqmMgDASw1DDmAoTMCIzkiNU42mD+RdFJvVeLM+Z8Xj/reKkfOR44FXybIkQLKlw3T0aPAw6ycQ/LbEqIPO8jkZORzLPgFVkyiD+cbITssgpNZ3uERksaRIdOHAwXVoXSjO2KAgLZxKG+LDETpY3Hmow25MUOU+Ub15/qWS8QzAo4dhWEpd1/9Zfk+4oODVTfpzIaLephlgKAXXeL8aQo036epwTxjYWEuGgAZaToHpvf8fOCzeBECwltToXfXy5HFJ8fr9DblFPK7exf0uNEA6OX0TPAlLR2rGV97mQ6cdQH4g/f3yal9FKhwPUcOQQC6Q9Z7/Cj9mk28UM+6dVA/9TZ1hAUezI/HZkEeV3wUMUIAdVQxPd/LNwtYArPBdXYWAu60NLx/jgt0+Od4BM6D5ZRumvLL9vWFHJ2P3XrpF07TPxyYkL3g+pIeckBhw55bVZfpOTMXIyfD07CP8+FS8IPszU8CXnsFHZOXXGpbv9leBIsN+Et+gcslu8f6HqrduMbcT9i1z2Z0YfrSInRsxxoaEbcLaC57rGgEn+3BqmLwoZ9HZ3OcfSa6VfVgfY6VubR26ew2GQRr1orxBOM8smtMP5cLU1WHjoLeTpoGPJetgJzcOwodHVPlJz7ua8CHmY8hcFuzHv768otQzk+6oabLDZP9rRy/b5EzWMz9reqIt7Knuj52/4QpLqmqvTdFl+VOxVnKP1PqEOVHdRgiflzvxfu95RoW5Of4eC0HdmFwGuKV1nGQq8c3muKnHlRX/KrKq+kz24lyfKmUnaugEicpHoE9qFcH+llBuXyL/A/7IWW3Q/A/JvYx5HjMDDWOO2LjEC+Us5cqPdOfZoKy33El4PavCyzjHPV+4Jn5QP2bLNeGHKCggRqe8lwJ+xqYfyWvrVtabBg6ueHA3s5HwLhYDvl386gAVzdMObD+h5wS5HdsqOgZTcHAqCg0bL/bBsdTIA3IvGwwZPIMlLcwBwHm09lIN3eeric3TGzgwd/4fBIBQdzng0H65xjVAIy4S0BGOgKWmGg0GGrLgEmNCOlSZUO3gvvlkvBf2YDA1MDarsDHcKCLvajvfekYKbokHiNHlydiZNDTH++NklNpv5INlg8+gGCqhlPdSN1DyAJG+LHAWbMXijxVNkRn5CIAOHIIgqoUV019qOPvYvncIIjwE4I7JOiS+VKL1d5oQIulMB7UM66m8nUTk19r1QJ/qX+E32tg3UBlOaT0HFjUD6BnCPRhfAhPzoe+zeIAcJEXhmxRNuSzUSPDJeCTNbblJojB8gYHiERH5ks5frCBq0UVkgePJBFd1ME9nREuOFb/bfCL8GcDRfcZ/06dkK6Lu+w5AVNkAylSTjWhbxsuE0DX6uD33vCC/rScONOl+80YQX7Lq5LZlVPk/7cM4LdS0rPdleAzxcMc4NM3IVYH02vGJATUt3qQvK6hp1yr95l/NvSH6Uz0Uke0mCRPUzsDDtijT1YD/4+80NvnFkE/s+cFJDe/ZL2fNw/8vt4NPrWLQ8PosYnQL5rRwR047d0IRKlDRB1266XSc3kkB0zfcnJiYgeUnYD9oxHcUA9uSNaV9rG2oaeyB+YTiA83DMvZC5Ve2Qu79ly9Z3ZW9Wa6zMkFHzbJRdUSztEzL0i7Q9JvliPyC6UCavn1iAOEcvoYar5WfoKf27DPbHHLtimyKH+L6y89kOtS2SGQfJ1KB/08zwU5X+7V99Uf5jfV2+6h6B/of9heLfHCz9IUa3VcaBDQFDUeqaUAeKeANWvQsTY2HQ2hu2SHV2oP1OOBdMhxWxfknj6h4Bk9V/8J/Ka4ge0I+QWzI1z2t1L8tuYnOlbSZUfkCewp03V/Keod69LVZXk4R3aAl3OvVvJm0/5U2d4r/6X0RyGu/DM3pMvZ7VDlR+XHdoj8PL8/ScY5bxXAbz6fj/O942CXPyhQr1mdqy1+VYiY6RXkOMS49FdqieBQdkLF5dAnojvHZeX8iXpB8S1UuVfvm53DHI8gfqBvRdVhFa9W1v8E2sdQ4zHVYcR62cil4mSg/UYx4rKr3dC3cnEy6ynZbf4Ejqb82oxzFDmCzlw+8Zvj7Fry2+Mq2NegAip3oxYqtmOXPBtocOZmw0BmZcMhzMlCIEX7VPG3ESvfx/0FOSh2/iI4lLXrkc+SAjiMH+QqwRSAscF8S67uWN9vMXkK6Wz5zdAir+qZg6K8MAsObVkOesRokQd12MSj8F0Bx8rA6NHyW7veHmSzdSfu08gpG0aiA597pMBhXuGGAlOgyYeaEtraBYG5ORX3/b+4Hx0Nh0HfFrGiXyPTu906JTdInp6Ea+o5ZgHb8CXo+sQ0jIBl56D+7+ZD4aiHm4fe33sX6Uig2HANkosBXN4R+d0oR0I7SsFOTNTlBv7h96mhwg59fjYavtOmAJ9dPtDjYdnhMCRTv86LSQ29Gz28f5WLGzR3Aa+B8tui1/MU/8D/rz/BFOVly1FOExccx+A0vaiILgB/0GCnufV8/NmN882SL/QtJXeI2KVP93Fo+F/igkPqkQa8Zs8C3oluOKw33wCeF1+O+pvLDXpcP98IvCr4ZYNOi0OxAahvoCOH+Mh4D5IdEPQey8PQwXAUN8mZBOdI+vRNAZ3pW1k2aH9w43yDG3qyW8oB9SvwSPAXmyAXHeUiKBe7gVmq7EFOSIRc/p8HfFj2EdJv+hLy+84KyD0tFmBXTll+aMo/H//JxvmO/mjgFvoMXqxo1fsygekJDWRazInp9b4XCbNnBb1gFy8OUIYM1e/vE1+/0VR5s4P1n75hZL1dnKOniJqlD7gP/Hftgj69kQODPyv3+CmNc6Rez8kKeF3KgbVdgDwkuyGfLtmR0S8FgfuFy5BvBXaAGwLDM+DYXp4ZVL7JDb3dATvg4emwD9Rw+U7AuLFB+suB52A/3Vnehw7X9oLpfKbEmxZ1sGnPLUeyWd9ohIQd+LPym9MVi6BXWzcndRTwRKaeYsV4mOs39ONMOQJJesT+6tZk7RfYfl7nBtn+6DZ8Atq2tbIb6KD4UTYsTuAn7Npn/tZup7QDgf621sOwF38fD7s3ZRo6RP+ZCT9zfQrs3t2j4f/JvrC/vkja8zvTYLfo0w2TQ9sLfl6B3DGdJ8pF9a50o/xpssEwTcYZvXroKW7sDzu5k64QkC2f0+KJLL9P5aI+KqAam25sEfDgP0D3xgb0b06w3VD4h8v+8vYccZb81n7CLj/hL6YD3RPYU9az97zS3rsh5x+uwHUHaf/VJxODpuP+CeTNrl2tpL2H/reKRr26yRk/iS5tz5g+/eWnNxRnXS3gRmnnQpAfxWfuCPzPa5CL7YYYrzc2LZgHf/T2YtDjWx861he+pl6zfT7J8Sv2bT+7NfCpQK+4geTpjTiKFjXi406PKf4ug2DHDtS7nJ3gBtp1R2HXSe+Zv2TneJEe8jN8dHLjPsUdbPdj7cu9GUIs5ychHoHfH6SLtYpXeSCLPnFifMzbNYivyL+Y2Uf2P7RoJsuxjXiM+bdOTrFV8VzmFMQfb81AOW/moB5LlsI+03ZCXE6BV38SFmqcIwmDeIHKZXt7ro43YWcbycUBK2FfNeHD/AcCGRurtxmwyB+OqXmUWU86FKZuXbP89PNzxWe5ajEef6Eqf/+div+pdGZ4qLd0eYmCNfRNwilygO4to8zQUR8tq/rhunbtoMDQLAOL+xBUPz1AJxpJDNOhGu5KDtR1mLI3Tjp9mCAkx6eY3Cj6aboynn6+YWpt4yY6HS8G8LQcKaZFz9gB0aJWlwtoF4/63T8O/PF41HvqrNKra3VWcoj3GjRQdkQ9D/Ws9Nnue2Z42X1fpUPH3EPjIP+0+nIlDz2jJOB91ItmkqhVOgOeB16Gq14qX1WuGX4qXU2fFf+VvbPCRy3GgQ6tl+XiS02bIp+YWNCxfSLk803ZAUOLuMkD/A6/focr30C7g3z9eh5UDxP50vrJq6ZW//7k6pMa1Kety4y/Gk8180YtYqL4JWfiaLvDdpnyM6m3os/JPtvltxU/db145ou1PVX5aT2Q8ZSyN5Wtt5n9CRW/ypYf+J5d+Ql8z8zeKTsTmN7uteZ3NcWvdvGySqfxDpO+6PxCjI/Al/DHI1b1t3qu5MLMPlm+L+kKuvjtdGA8pvJJihXQ0DTeVnqo4lz13sk6q3prPa8h+0pj+c7hUMChwG+dAqpDAyPIu4+ip/BlOYV+RQF6/GiVbB5ZcCdgFd6Bd5t9M/pboRcaNPdmYGSJtg3gHvcjBmaMpA34rdTzt14PjPB2SYV8q43m1Ujb50Xocb4kEXJfrwwj3cHbHv3W6eTUz6GAQwGHAjVNASceqWkOnB7l0xwZ53Ao4FDgt04BTDGlxYH4G4OL2uBMy8fz1BDavoWneJQZv5eGqeY3T9Wh1T556jQtwsZTWGkfWuc4rSigV7nmKVo3ym8VD5ViihR1PPBUSFoDkQ+nYXpaMddB1qGAQ4HfFAWceOQ3xU6nMg4FHAo4FHAo4FDAoYBDAYcCDgUcCjgUcCjgUMChgEMBhwIOBRwKOBRwKOBQwKGAQwGHAg4FHAo4FHAocNIpUDuwBLWoRExbAb16xkQJqNegZIeA/+ll7APfq+y1+hgZ5fXrVcIHrYIlDyzecmtqTCsBP5UCj/371fNT5YyPoePjY1oKuPa6kh8EfLWxuvHD3P569WLaCfhrt5gWAnaVAp8D+08VeqrtdGLOEtAuHvjRqnJhPk6V+oa5WlXOTusd61WdOiU7BRw5bDdj/T7biWC9tZuPk+63TQH1rVFMnIDuKTFnC/jlUMl2ARXsT1nD5FCLWMS0FnB7P/ibIu2Pqore6WKfq1rPqr5/qvjTqtbDeT80ClRXXBAaVr+f1Gpxspg2Arp2jYkWcKmMazf5YA+PHrWiCBY/uiwRcX37eMT1//U5ccOJKefI//H00d+gIpCPc+GbnRkT8E0aNRh4OeO3PlICd/zrlb9Sq0QhhwlT8A0YLZ8ceDQSy17cnoJFXGgD9Bo+VMClV9Xi1U+Jbry4yjMzQa+BNfcNG2830KsfvqWj7X/4oI3a1XFK0bNjIuStc7JCL+znGqovDDFt03KqHvzt5ZgR+AZ16EC7aNrWW7sZOumqhQI1Jo+8T9st3eBP5i2CnYxPrJZKV6YQ3jaiVRTs0qA0tTplZbKq8J1TzD5ju5fqX81X0eaU96cK0d/JuablAWSuhrjgd8LPkKvJ28ssWKq3weJv+mlNBt527SHzfYVlQXo7Mk7/3DSsddEnzYkbjufEifXMkf/jqUVXcMSjMvT+ZErg5DLvannvoBereAPlXSK3tzhAq7Sc2gd6mDwe4N0rVWGr6cfbduStUPdr6oz9w3ZuRo9M0qkbENYUgU5SucrwgO4vBne4nKRy7WarljPHtgQ/bobc/nfz8Q7EOrfTTW+ta/TbTHGqyCM69L7YrFfb/W2S23atThX7DL68UWP+6nTxp7YZe5onrGl5OM3Jd9qijwGo1rHwF9s2q4qoEVV0JAVvA6nSBZ4R/4zP1PsYywRO3ABCOHoWKDEVX9fByGn3VPRw90nBhsa/GhCkMXuwwfSk6UnDBPRIheD9UW6wvHMLNkSfPhUb2u/dq4pJukpAj1Rs+HqC9LzxNs0Y4J4a9TY1mLmhFxsLfAYPxgbB+Xm4LpEbyA4aim0FVnsxAksbpvMqpU3L0AP+4OOFHwo4fFjtD4ZtNG7riXQXxGGD5uIt6CEqLUXP0fvvBm6vgRGIbqkYIZ2RDTyW5WDfxAMG6PCLge0qCH/eZ44asDyy+pcU4J+VVbhewGd6yhjoeW1H4N97CN5fmW98LWDR64X7BJhPqUADIz4eeA3qbewTsDsCdK/rUhQ1oyfwWV+EBgtt2Msj5jSiyWcaYOfVL7MXIt0XG5EP7dfK/BrQH3Q8oxnk53m5gfqRQ7geOBT0/rJIywGvljr3bNQzfgHSNZT8nz0f+KbegvzbuPAejeTzxsddJB1nzwL9Dx3CeUg6RgI/KACec3PM6ltp+eF9+K7qCDm55SaUR9so8uq3sxaC//v2g99LPwC/6yg9ytB6xHJ9cTzq07c38GkmN0jOlvJB/EgQcGVHPPcMgTy/motyeqahnL8PwWp4R44oPluezzII+vWC3D+RCzwfyTQ2C7i5O95/I88yHxO9Ve+B/jbqeZFosjwwDvRsUAZ8XlqIenftjPxIvlivC+Uqu6tWIv2wkdCb4qLCzwUsMcUb+ts5FXLXKQEzDHbswfv/9UHevt6IfL7daKWXRhsBV3QAH9OGwA49Mwl8GTEG9fhIy6OmyyUCExpZ5x7mQYNxPlKK+s6eh3PtOqb6w/L2YhbwrtfgtJHHo6JmwTPD1JRag0cu7xqM+rdLQP1Inz8TMD9H04/3YzO3U8a3Ar7+1mgrYPBI8KWdtE8HDKtVfGFPaf9bxrfPkMJiAXcPQABH+s92KAR+c4ZhsM9qv8JLDIJbu8LOX5MCPXg9F3bvXS/k9qxoyF+/PpDzCxKgP+/mg56v5UE/Z2Xjfhc37D/ZAbbPs3MNHuktKTEOCLitL+jRIRnl5QbYqTaxyCdtMOgdWQa7vXYL8FIb3ysukn9kPTgF/SnbXZqpxf4tpTPqpfzb2mLc311K60ETrPSiHjb0me1XCPHKtWIHwvr1zehv7BHw+RdGKwE9usAvRLuAXz0DfFLxzOJlVZYHjmN27rLSUzRooqOt7FfhBgH+qfOqIQS8e/VRcQHkZ1YO5Dp0OVMSZxrfMF/mRKC8P5ci3mkciW3GHh0HPbnDg+fnx0EPsmbAT+zehefm8RDkZKtP789rob8aX5ZD87hQpbOyc1Z0Qz5rvDg/nAk5OsOF98Znor6bR8EenDMNHYzzFho8M+aMBrAvKSnQk+UFoNv7XtjJo8HbWJrEDci3XBxQX3jq9wsK1whY7kU8PdgDPFtEqngK18G/VnyBnTtBnKr8LNvBL78000PIp4rXqmB3ubz5C+HPr+6o5B96nv1vo5mAnv3Aj1aR0JMSH+h/Ywrq81RW4RcCNvjbF2xn7cc9wZSs2Tu1IGhvLUUF1/lwXuPDdhMzXoCgDvBAcTunwDHeMwQEjItDQyYvX1Uj1PTqvYrP1EDlbTBGpqH8GGmAW0sHPDQNijE5E/h858N1dw8UzdNX58sCPy0L6eoYCNCnzIBAzMnGOTkBDao6lCDg+Fnk+NabSLfBi6d5BcjnnTd1ap4i0cEFgW4YifvUcGXFfHKaSoeAJ03S9YqOyOehu4HfxGkIgHv1V+kDz3CMtNE8NyDfW4r8n3oRDZllMlBvFvBaMD11zxgHzI9kIoAbMx5ysF8amJbRKK95FPjx9ssIxF+YB0NEDpG353g+G/jHygbXkDTkMzodDnKPD/LW5nGko4YWB0TXJuP9Fi0gT91kR8k9cmpJ40j9PivyopegqDelAp8PCpBPTrZ2kFzz4PrCgduXH01n5uvyjySdZ4Du+2QD9cmZxnkCSr4HnnOzUM5XXqNEwFPPAS+XC/WeM1PK3zSkW56P+qxarx0K408NVObLcA/OXfwdB9yBUJcIH+LBctwrTcrjRNBvUQ74OKLKU9NDridPNf7Qi/rfPw612boVdHlTBlZjx6Fh+clqdIT9uAty0j4OAfHa1WZUAP/IQDP/RqcXrhMwdjzev0UG+CRnjEfjBqHpJTVYFH9YLkfLhmmxXx65Q6JlFPI9MxJ0njnX2CXgicmwUzEJqO9zUyz1hxtO5KB+K/LIdH95CehCHXfcMHh0LPj9SCbkaViGXTtlxAno3hX8jYqEHxvzGOSrg9tUTrqJOQS1uHSj1nUyQBjkOT59CPzmwKDq9lmXz/V69R3YnZ2luD9PdtQtXQG7QQESH08/Bvv8swG7ODML9HxlkaYj+9XJ43X+3BCd9KThEkD6x/5q7rOQs1VeyPkrudpO8cyqpk2NhgKemIB8Xl6A93Lygec1yTr/wD+nmj9VDUJusHiXAt2ceaj31i24ni8/mWkRaVufWaLs+xtNJgv6o6HoWgw6d0+BvI9Lh/5EGOB/Mxl/hEEebOqppf1iv9VE4qVrawD/VrJhWy4uUEkqKWda3s3iG7anzb2gW4EX8eODmapYyDvJNdv3B8dBH6KibMdDKiOb+mvb/9i1c1Z0446OLd8hDliQCzqU+lDvJ6YZ5wqY0xx0ud0DPl0YjwbiuiLo/2Uyrrneraob8pn92Xt+f89x4SafzuegiJhauYz9Ajb47+sE+GObL8zPE8SpSk4t9FAPfHHxVdAztjuH3oWclZN/5l9UK9ihFBn/PZgO/lyaAL9JYSDL93R/+0I1TG3GPQFkPGUua6kRRjiywwYE7rAPIzO0GBEb2IxMNCBezz9+xObFWSDMDW79DWuo6U1IgZ6J1avBiO06FXq0C+XG69QgZUGaLHt0Z+cgvdcLQ9I2Tr/IPd83uhEQ7jV0oMuKsFGO0H2xBT1ee2QAoN82dL25J/GYgfwPl+r7KikbvLU+9GTk5kDx8+VIVVuXSga69U2TjqYZ6P63e0HnFV4EFBTQmh0seClyJLjIB7p8t0316CD/HT71uhk9jTMF/PorGkzt3eh5mpsNOr2Wh4Dj0yLkQw1mpuNyr+pBxP3xU0CPvw3DfWowMF+IP6zgM3LVyEXhagGvevHeugKcDQM9qtu3o9yPivHeeh/em5MDxX1Bjqw1caGcieNQr7k5qO9PciSsdbRZfUOVH5Szby/K79MD5Zx/PuhwuRv1bmEULhFAdGSgAU2Wg6NG4TYBPx/UBp47Sr7wqRkHkDeaGcABwG4f6NH7r7LhuEDRx9gh4MHHQKfhAwJH+HU6kz/Qzz+4gf9eH/h+5RXQ+3VbUF5nN6Yenucyycb6NhtacmQ26wk+UWDAATPpIctLj16Qgx92Ab+jsiPgjj5wQOfLEY5Pt8BRlvgNRCCGTNcbE6Bf1EGiDpbjVVL+DsqRteIi0MeGXnL98l5R2RkxAgYOQn1m5cBuUgcGy0HrWOhDipyBUd9Aj+io+9DAPuJDoLnXKJsjoPBjU/35Uuz4+bb3tJdHNVLFBHS7y2YJeFeOOG/bBvotzoF+eVJs2yn2PxSg8zEm02ghYORw6F/6MPkg6KT1lxtOi5cFJQiV32Gyz7rhyeVf6oI9fE/aX7KzrDcd2mMkZecOXE+dhfNKGXB3TYUeEV14pJo6GjnQ+5kUC4e2J/81CJrJjs+r3Wjo9PVAjpPd6MBdkgP9vuBc9T6ev7IU5cZEgn9Tx+vnAX+03zxV/CnPPEpsDzq1kB3hBw5Cz1auxn0KBNmvvfO2bX2eXUawrljrs0W8ohu+3PF8AvqznT3jfsQLH8uZJe9Lfzl5OvzcE9OrLA9bDYLzLwT7rPXU0v/LkecAcTDUSCPu++OCwHShypltu8Ed7PsPBZYHf0sztdivU3x83GEdD4Wsv9zQsOF/QrVz7IeC9RN6SPuj8/MDhyCnZYaKe7RdZLk9cFzt+YLptif4foh3QOePV8P/5uXAXo9M058Wcn2vSy6bJ2CpHhCruBhrvljJKfTq8yL45RPoIdtlsoNshytvd1H/LbGoj1/+gef322B/1hQj7lzlhX5njkdcM192LJRrX4Qa91RMyBq/W8sSAzaEkm5Ga5dOv8kgWLMW1zRCyALsckGwQkivMzT5IwP9oKcssNRQDDz4PtkZNvDlqsfXM+XUpeFpmJrbU075+9UwfhLwmj/gDMy3stds2AgfNjzk4NTBAczFsudpVTEEkRpcPFXxrgFQkJfmqeRBZ843ORmBQAV04OdUL6ZfRAP9fgA9EfAcPIjn7muQX7xcLGvNevAzKhpn6rHhBkSsS+Wn32c5KdewP658wiPwYH5UgDf4GtRBAHpQw++EB8khH7VM66tftyk/mPJXl7ln1KUp8GyIkjuiAbVQjiiogFjnHvyHy4uNA/3K6ZFKyfpDIxVMF5ecghpIN3IkVTpoxgHjsbgA8kiLZ7Eh21wEOflGdtQMS6t0MaHW87iCsrOAV1oa6ExTeJku/xwPug1OR2Cc1ht0ysk57vWKLlje5+fj/atlR9qtqTD01yejAfS0P5C2q5fQo6MVFem/d8gH+pIdaizg0jiU96NP6ztPYRo9HvTPGKXfNdGf34w8Mp1J/pi/DY2I2wU0b6Hrz/RdVQx6uWTDzNpOYYrZq3nId/gAyMlD6bj+z1I9pVgXFPCH8alAzULld5jsM+xuu3gEKNEuMfGTp34qtNlvfbbB+F5A8+awk+fJDpwJ6ZDzOS+Y+gmVjzpz/WmKK3fcqoba1McxNfif48pmCOgzEHSlEY69AoaOQjkfeSHHy1ZAT0nPwn0wXU+CP+UR5PXroK+fyob9A6NBB7I3bCdnjNP+LlR9tulvIKch0J/5RH6Cp1we8wWRmxsQVZCHEPVUl29iv/Rzsz9mcUEl5Uzzi8s7QXxjho/ZfY53bMRDnC4E/bXpf2zbuUrSzazapvdZvm3EQaYZyAfcQfjYLPjrIeMiRgjoJT8pfC9/XZKAsjLTbOzyRWVgJqeh2sGq6pnCx0z+Of8K/BLTi+wh079ceyfUuEeVf4qd/TVixtaR31LWd2k8mVFLvAiwaAqsOi40COibAG6wEIF2ClizBgY2hPQsIIQGG9oKBFwRnvHzo4serdqGUSqgln+kkRlM+TDe5dLziAnd5/zm5MKhbvJhxCPhHPQk2di+ht8nQeGe30aRGHGkqSmqPFW+ohMLCpUbWD/01HtBv/vS9cfjPLJweSJGVjz9VTZBZ3aY78ipoTSCLRez0ovdsKEjfnLTqoG/wRZAT3ybQT0v3PCiqW08EnT1n0CfhXIEY9QYfIOwOBcBU2cPAuWb5Iirqv/wIUF4cg8T8SnwYPyIP1yPcnxnehE/FT3VeywnlI75WI6v6rk6K3lS1wH1Vbdtyw8bhk6dUO8u7rLnBEyRDalIOdWSvjW9TABdq4CBy23kUnxBuW8UI4CjhhKnL8cXlofzXAg0aMqvqq9CONog8E89xzcbF8jFxdRULpXYf8bIKTlIlgPqGeVvoOfmYCR7YZ46oyHwbBYC3EEePVXGn9Xx/xSdA+Wa5X+JlEsb9VS5Mr3mySnj17vB/3Zx6Dh6bCIC3uZS79q74aC3+NTrlmfm4xte0IFG6lnOut+MAOYtr37frl5yvelbUXV8bhBE+AWZ6U2XPDWJOkz4TB0DfO7mAV9uTdUjJhzw/iN4inWg/pyi8qjIYHpWesh2hvSXG1YrP4Q9pillbA+Sr9Pv8zXpA/sX+gaJvz21tlPQq79lIN+VXilHVyJ/av9y+fTtsNmh7FKgnQmV32Gyz/g2/MOVqMfPPsht5v3QT5pCzFPAxoyF3pJ9YDpPlZ+8zMiF3tC3Vqo+bFdpZg7jV7ZNkUHnx99cbXodz/f5oC//HKPsQcRdAjLSEQ/ERKP8sem6Y5X1P7UH8HggWJ5VgerM+J4C/pTtK+kvN1RLDMjd2wVoiP/rRdiJv49XaIesz2wvbcQrLoPgkzW26c/0IzvDI+K1XRo/9aeq8sD5fOmxq6eqWH0OtF/6gckfpX+BcQHLeehyZtduQK8o/mP70EAuGkpTedVaKGzP1QAD+W3WExvxEK/tEIL+2vQ//9/elcBHUWT9DmdQFiIEiGMgIyqwHhBEBc8M665GBBLxAkUTjpXTTVAQEDWJuBziAnFFDCokHCsqCgEPUI5BQDkMJIsieMCAfAYFMQGUY8V8Ve9fVRN60umeZBIQq9/vNz3dXV316l+v3nt1dJVjPecUN6q3NcNRzmyGT5kH0wfkhzd3q29qST/HuKFf65ao10jfMLmEP6duw69h+t/sN4gQGBnctB58fOKFXM9YiPo4a64/Iot/TsvF/LpZTitUDyuud+FPR0YCR4aPWf5JLpn+ID4ZrubDAk/YBQd+jzm+M+S6JqYgsG/dSIEOHw5D1sqN/Ty/2g0+FwuH87EnsK/RhcIR75mK90YOy/uG0/at2K902w4IpoPwtN/SiCFIx+PB/nO7dmN/zEYinSGpMNB1jmEfvaICVJShU9GQCy9yRXAqLAb/A1NR0DER2Mf1w9V4n31jRxUxJRWGt1e8i44hqdin74KIwr2cmGGyOMDf5aJCDk1Fxdk3Den2SEPFusyNeLcIPh9IAh43eFwtOW0U/Hy4DPjd3hXvT3gOybIpjKSoxozG/pRsionpcNXgtHMPprC1vQDvTx6Hb4RvTkC8l8RKhQMcfmmP+wPFVMM6xyDAH78OfHLmoMFfO0IoItFQfCnL2MFp3XqjCadWLfDehKkIl3AX8B6bAblhDSJSjEOSkV4zt6sRp5UrXNGc2BQyUmCjhgG/1rHAZbP4dvOh8SiftkIO12+A4XgwATDc6EE6u3ejPC4WI9EPDES8Ri3Izy+ioTd4akXlB/HN34Bzz65hCzmxkTwoYOH4ecQiY9/sgAKRU0Oeega4NBDfELz4FK7bNoeC7jsU+4xd7cH9nfl5n3LKzMI+ZI8OB74eMdXu5EnsQ+b1ui7itOJNOErnnF94gNNarxQTNeWeyuG1lxGubgTSW70a8bBFNMSB+30GIL3rPbjd4RrgvGIF5JBNdZbhLeotyi33Laf5lPEV0vHLL8h3ezfwYVPDaUrrrm9Qn6IigO+7uYXfcfp8u3zf6oz3botHPchIR7z39Ef5DeoNfRWfKPMJuS3YZFcvIY9DxZTROA8Myg8/QT/FRKF+SHksqcWXpjKaZT0PB9gdA36enoD89OoJ3J/LDHubU3O3Vf0BvuwbQZK/AQPPFHm0wh8OHsOH9C7T48Q30zt0LF0OHL4VU1OfGQ/90CwCOF0TD7350N/xXngdnOdNt9RT5JC3jEa49JFIp0ZddCjWjcI3VZPGFn7JKbAnHvLHtl8ie3iTB3qL2UFyEOI7Iz4H5U18vDAR5XuFG/xUQD+TQ/jOMti5fQeA1wjRAB8+CHwuE4tJrVwOeb80FvVvlLBPl7TCe+cLe8rkkxbdmC1mFiQlQ64Sb4ND+Pat4Perb3E/NRXlN3oc8r9lPb7lfuMt6I2n05Gu1BvnhaOerS3AfrcfefFe4O8ZY09pv8emTcD3lBdgL5KTUX79emA/8aRU1G/2TSp9A7jiA8hhOfV5URgjNmOGyjEl3c5fwTfTH4gR3B1i8cZA/FEeH61DOY0eg3K6StjLTQXQ7z5fpeWB/JAFDyOdr8W3itb1FOldfY2V/jLbESkRqiFo9gto/+SVy1AuDw8NVs6g11mHDMVbjt6g8tyxHXqnWxzwHfQY9E+zluCT7YZA8dQOR/5enAK+WuVY+UN5Pk6F36GeHCi2rb+0r/jOHc7szzWCH2s9h0V2MtKscEP92/YZ8jlmBPJ3nQdyXlwM/PLFDKvI5pDfJwcg/9d3x5mNf1DHF2s3RHLaHoZ8DhD+GvPvaL/1tatRnx64E3j6/X3Yf/aJjThQ334sRvg6xzCDY95r8rnV2XWI0+69lfVT89ZxOlQMvr8vttWDBHAl9C51PH/yBXBka+5Qw5/h5ua0pTPkcWg7yEWbWODDFo0kO8NmnFFHAGtfkB5j96k8mF9Mz+39Hqt6aYXzGXdfzgWXPVJqpM6C02DDW0RT6dvyI2Y0xN+cpa7pI2JXNBRj+1j0SL23SvUk26Qst+uwCeb4Mfhgq8FV8AD/UVGyZ0te20Uny1FOHVPlK1eNtIhA9vjIcrYIdtbcVrhSxs85R2bMasqgnXzI8laLOMgIHZ7lyJvky+Fr1R4s2HzKfJkZlfUy2PwivhdmQV7bxSp+aP/i1mIEelQ66gtzSE2HDG+6XelLOSIl61+wEUockK/TL4/B8m8OD/zDwzGTJHBfTomTnZ5Sz8UMBZQfWyztNB9SH6tyI/7YaqdBHlKv2OkN6HH/zAqznMhkcb92bcmXvC/P6jmNYPvjU88lznIGD612zhoEQR4yX0G+Zhk82HqL8H/14NOfMelK34h9znF9owe7E7w2y5xwZeuzOT55bYe/DGd3Dpk8yPKmXQoC66kdHxV9rvRDkHLmVG9IvlCvatZEefr3MZf1V4Yzn1FOkZF2/pCUc7v6K+O3kmOneq6iuMn0zWeJi8KJRpibRtnl2xyP3bWqhwQsW1W9gofTcrGL3mk9DFU9s+PH7nll/R67+KvreRljxdWVdPWkg6mQXRLR8zN7CnognhfbobCRLuppuEyMNNYpwVSeJzKqhzudikZAI1AVCEgDinp/8Ff0JL6Zjfq/ajV6ihtEYKqipx1GLvo+rBaLqQqmdJwaAY3AGYkAGgJs2x0aOW/rxogF+3adptQdKMII2V/iMFNivlj0b6X3jMyMZkoj8DtDAANIw1NR3zq0w4yXEwY+5Unq8zvLzmlj92zze9ik5rP7wNTHr7Zj6tjy1chtiyhM2WopFq3ZQLvd5RVkZZ3daOjcaQT+GAgU/sSppARTlGa/KqZm1US9jxX72f14HFMax/5TN0z/GHKhc6kRKAsB6InlyzAVd8+PcJTbxsBRrncepjLOykIH9qZPy4pD39MIaAQqhgCmstYXnwYwa01rvIwdD//9+PGKxfrHe0v7PX+8Mtc51ghoBDQCGgGNgEZAI6AR0AhoBDQCGgGNgEZAI6AR0AhoBDQCGgGNgEZAI6AR0AhoBP4oCKhvUOW2B5jism49No5l2zHoo1wE1EfRtAz53Yl8MxAjauZstcFxuW9X38MzjU98xH1NJ0ylqheO7U9We/EtQttYyGFEBL5BsF4FsqoQVIsf0XLfd9+F+pCdHer0zpT8hjpfOr7fFwJW8q6+aWlgMOraDVOlt+ajvu70VXUuK6snUL/YKvVUj2PbYEr3u8uxLcp3e+2eV3X+Qh2/VTmGOp1QxScXXUH53PZXfOv52Xbo2w3rQ5XO2RaPXJQJuN3RFVOPX80+2/LpND/Ag227hG1i5H4w9q9HG4x+PGj4ON3aHX6HbztWjf1iu30EoQ2hFmOi1Vf/Go9tV+Zmn2n1uqrbC2dafkNbytax6Xp9KjZswx1xnMOXE7k/AQ4I2yhaH2UioAyqfEqLLD0utq95eRY2TK8Zsm97pYNotZqbZMN8rm4+zelbXUMBx8ZicapXXsPiNV3iTg3fKRaGN950/9RQVXpFDnnTSPDRL0mu4lY1aVZ/fq1WS62a/P1xY/3d4Gwl7/X5zry3d8PiMXMX4tugNrFVXaKV1RN4n63KTNtCxMdj+4imYnuwVWvsnld1/iobv6VdsCrHIBO0jD/IeKyCq22wqONg2ljIF9vXmOzpsk/QMXFFlcuZFX9n6n25Ki34GzsJ25w8H7Cq8JnKf5XxRfV8eia253v1TfgVo4dg+43v9mPRq1feRAfIPydBL3y5yfieU9enTl1Es32FV42taP7gX7DV2Gkf2Enjwd/TaSq+ENVrFV9l/1R1e+E05beq9Z4V7LpeWyGj7ztCQDqa6HF/VRkEGNILojFCWVIS6oaMdKSQ/j2JdsyeLj7t+DI/R75eFNt/TPQrYnNAfV0lCKDD491VVRK5jlQhcLbgjHxs26VWRVc5rNo/FdUT0MMfr4K+vk45nLgfGWn3vGpzVfnYg7ULwaZY5fFTAQxLhb2aovQ/toFrbLtdR7D5OdvCA7fLxDZZP5ecbfkLNj/QT2y/WNMBv+znEnSIdFf+E/RC72Q5YqX0AW2TdF+yKZpquwS/nT0479xVbQnrhAiBqtZ7djDren0qQmGo2GyfONrotX9/9ODkLkKw/9uHKQ99B6IHim3YS1Mo2AbBtLFsoxiMMD0zAu9364rw18fhOjMzbxunrflQCM2iEP99PfH+Je0QfnkuplS8LdI1DCiO+ERMAb2+HcL/UIwew2986CH7cjuman29XTkiJ3mIewfgvbW5xpecFr6jst3CYNR/KHrMWjdEz+3PhtX2MrIBip7d99eA/1oGzjmZ4Ct7Pnq89hUiP+3ag78hYmT1I7GR+rxsyYdUkMCzQwx6/g6EGb9wmjQOqwbe2gUbBM9fiPiXZqMcZgq83vXjRYr1guiQ8yn2iwUf/frjfKII5TtzLqb67T8g82U+o8KHhwOXR0chXw1L8H6sBzht8QLHtInA456eKJd6BuLPygZezaMRT1J/lF9ECTY0/nQ3ws3PVvv5XWYwurOrcZjTtQmI950cbFz90cdGU053dAHuUWJDYzYziOS7SORv23bw2XMApto83Ad8sA27/8epTwrk7KVM5PvhFPCztQD8z54JPh8fhniZ3PzM6YmJCidKz59f8DfrP0ZDTj3uQ/pNI/B+oQ843ZIges6Drl+o72w7Bdo4/qFk8DE2HfHNzMEIGStP6sF8qD/Sb90Oz9coOUa5sn0caVsGph/O5fRFPvL/lwTcfzUTU/WY3jAdduWE8lwupnzb6w01FZR60pMGAPcXJyI/Q0aivn6yGvHOyQ42vGQf+F3aBvWx173Ap6Eb9W5WJuLfkm+HM3Dx+WS88iz3t4Oc3N0L8V8Vh/LP8cffjkuiA1zkfsY2eg8OGttvjuyAX94VX7T/4X934fmoYdADTJ4Jb7YtAB0Hi1FPMqfC0F7bCfIafyvqeU4O8AmcGhwyPUH7dY5Kh/yNEQ2f18X2QgtzIQdsZI7kNvA57NC7i1DPWcPWyp60NBi1vwp4JA+AHXwrB/qkRxLk7hGxoX1kUyv9ifdr1kJ97DcQcrvei3Rv8OB+gxLE//gE6IdbbkN8gXYB+qhon2U5ktz0ToY8Vdzu2OGTd5jTr79K+ZFn1VCgkdIxKSiH34TeXZQLeVm53hbXSIPR7V2UvqEpkft3A/+pk6GPjh5Fuom3Q/6auxGejdSS3HZJgDzMzEJ6x47hPCAF+DB9t4XTnGzJv/kMHNgUcqo3FZcDpLP/gNJL9MnQ7beCjwYGcMp6HX7K9u3AsXUb5GvzF3n5nM5Vn2yZ+ZTXjvUX+RPsExyH+lTF79BfkA0x6E02U4rkgU3oI7s663XgwexvJQ/ZQAV+ve7AJ0OLld8ko0c5frQK8pAjtiGMiQH+9YS/98SEvI85HT/uVE/L+K3O2O+zRyLq+U1iBiMrRhpJ7eZBuba80Eo/Kztqo99l+tDLV8ZCv7AZk8c5fVUMf2PWdNidtu0t5Zn4+tcO8JsUDj6roL1AGQ60R6p+BCuXodJ71/CdkO9ItNQ71C5iesTGv8zbwOnlbFku8mxXrx3XX6d2n3Cx96slf9V9FlN8WQOVHOWhSVAQLjcYuSAK54eScH4sBQpxgxcG83oxZeq9N1FgxwylaEjh/HsK3pO/L4yH4WZ2gww/m5JB+4wtWIih9fr1VcOUKsKIlLzNnJ7MQLy3i4bGoylI/9xwCGxSMvi+shMaeGMehkIaN8Vozume3kYMp+5dEU9kBPY9HDkeFfEqj+Qw4HyRwajwO1TEOZnI/w6vUcjp+RkB4SnfdwvDtyIXCj57luwZRv66JeK9Pkn4ZvXRseCrVxIM6333wdAuew+OyFYvwi9ajfx9+F5AuqHmU264Topg+hzjAKfnngVfrnbAYcakAD7MN+j9mdORD9bwo+XDn5oIeTnfrYITbk1Fg4c5eCQf18Wp5/V40/a5sbh+cz7ez85FuV/rD0fl/NaHuL+/COHnCgfk/VVQxG3+i+fdE4B7upBrZhioARkh9sW9oRPkqF8y4mG/NCWNKXiqL0PEFMJ7E5C/pbm4P3kKHM1MMeXoowKU2+3JkKN+A5FuGfmlfEqHNkEYbjaFnBygy9tBnlhDmhyYqUHXL/D3bIbKD+V34r8MN6c9e5C/N5cgnc/yUc7PPIl6+nQaGhKDUoFLtGiYDRDlNSIF+SsWU/XqR6h0zH9sygkOA2uA0WGvNxCOOVSEy+Bk8DdCNEwLVkOeWD2kjcWbRAYbHvl2uxHv7Okoz0lTgA+r51Q+67aAb6bwST7KwRkMBP6SwzDnJeC4zov8LMhR8dNG9Q2Yx8oPB7jY6D01tYgc/DLkHQkF/lIHxwdL4ajcIxo84f5wR/jXnmz/SKrXLdxwOAMbpuqFUOkJcnCnTQZuR0RH5rwcyPOKpaj31s8d2xNinDVMpLzRmX2qQPllZpU6bJrch3TL0Z+EO7OzZO8GJgHPZ9MgZ9/6cN09GXo3uZelXfiRW7TlCyCPgeUYKrsTHD6qdP1/aMr4svdRHzf7cN7ogz2e9goCloPrnwxGfa9DOcYnoAPy0QHAizUoCH/Z0G3cGNfdElB/mN9A5XRuhNJT1FGx8DU8vzUR9XaNX19QxwzriCv3KIdfh3KA8mHfUJIcrPgE9u35acjnYdFA/df0ctko52HQ+ovicq5PIRfnRdjJu/TzUA5Pp6HBPTIDcnAkDFloYoN3ORmt7CNqYDyQBHu3VvhbXZJRHr17qeiD0tPqLfWHN3OooUPyxzpEjnJ6THSs/uyTAW31s41+V/HIBhrZ+74pKKdR41A/hqeg46vPIIS3k+eYnqgnoW8v2OaXGAxCLqnDpPL+Nux6H9HOKEfvSP+N7FAZ/iX5vw2t/SJZYKZz0PXXoVxgwMiBX23ip7oua8BxWC96LPepdHF/Sz4EmfU4kkPCesDpWCZGvN5djYr1hS9vO6fXshFuTg4Ev4VbRUgO2+QsCPZaL8J1TYRiYnqJRmwaiW/+bmkH4JijKw9yYNatxuUvYsSzIB+KjjXs6H13Q7z3j+HoiV3lhaJhipMcAaH/jJFpRmNOQweDjxRRMWVi/rNa7IgUyQkDhuxXI28vp6O/+EOKf8Tn0+PyNnF6YxHCswY5Ce750Wi4fLoehmf0aGMvpx7i43zm4NH7jSPydnI6cQINupOiR+14kbpvSjjkfJKhT0hEOdY10LAb9hj4P+ED/4eMK/M4hUlgFVfouZQVsVsycJiXjZEj1sNEjoLXK19AT+EeH643i3KWT0udqSGw4H3IkUuU6+QM1aChDo/L3ZDTlV6MsDO8Sf6uas+XRDCiP7sU8rGhAOePfAj/7FSMoExKhVwvXloqZfyl9EuNyP9gMBo3KW8jp4WivL8SI50LcvO+4PTeIsgZk0eSwxYNrfIrF28RjlsB5GGdFyNTaRmQo3k5Ih634s9UbjGuAABAAElEQVRp/aKGw9Ff5Xtq/889BqOLW+G+x1OSxWm5GEHYuxfpLc6GA5WcoHAlOWGONBnsaUI/PJGB/LF6bjoclxP1CO//AeXmQG9QuS9aoJJzGYz69oMey8oG/8zRo/JjMw2CDU/67/5kvLdN6LtDh5BP1oNMHRcHfUj/3ruwGE8gzqqeKkbxRzl4ZNg6elDve4l6E+dBg2dJNtK/pKVjXGz0nuKHHKQy5N3Ep7xU9ZgcuqczoA8GpKgefWpI9LkX+uPfYoaBfNt/DrWegFwePoQGCxuZo3I7ckzya/fcsT2h+rZwvsoJ6YHHxyOdwX1w/2+iw9Zaf5bM5LS5ADixekT16VkxUj4zG/LK9CQ1XFrEKP1Pjk4pu1CYx+h4LUu9Rd+MhcDukN52YG8VMKf+kSNQ0G/HhV087kO+jhyBXJeDK8nzoFnQ2+/kKjwomVezUH6dPdCbdcOBxycF0E9bhJ6fnQ35eOV14FvfDbkYlw59MScb8fwkOjhkR/2peaGrUMnB7BJGRw6Dr553IP2LL0Y+2npQ/o3LYMDhrWD1V7D60aG/wL9oN+qXHEEHX3sPOgznzEI5sRl0ZEf+m+8wV6EPRh3jM3IwwvWBF/WRzWggu9EiJmg9bcUhzZRLFh0m83OUHFO9Xqr8H1v9bKPfVfLEf98k5GeO2M/3f//D85s74/zGXLv6l/cJJ28s8Ah9e8E2v8HKZaj0HuGcmmard6ge1K5l6V8WcE/uuamqXJz+Cbb+OpULmT7JR6BfLR+frnMNlTAxqPxWdRuOHTOE5kM22Mz36ZrJPTW0/NGjwC4SU1LGih6c2a8ExE98zMuFourowZD3nYmI78Y4KOoXMlSyZLgvFSMb6wqUofmc/3uoD9J9bS6mdry1CBWUORDkCLIpRiRQb7yvVg1TEYfoDzmux3zgu44Bxcx6cOGIiBFcNtJA4TZ5Q5Rq8NGY+aSe38tjwPePPoUrNcRGZEBBpQ6zTIgUSUexGi9reJO8nGQeozjIEPgv5W2USxnydshgNHAY5OATYTCWroLDzuSDKjCb8kTxRrnVFBwZ8U8Go8+2YhGrRo0QjqVPBvOkTwZTZyqfMvggR/5kGRVFvEm4nQiMj/hj9eIUxcHeITksIx1y/Mu4T+kfE/FUoH6pDJr+UD2KjoJc1jPC7ufUyO8RUb1cVwB5cLvV21SuDEd6XkZ5qoDiT7DlRDg41RuBUwpPTZ7VQ5Jzhhv0nXU50oulwlO5RcdAL13gPjVedkXywkY8qTzdYsprQCjrG/Q+W5yO5LexG3IyeQI6TP6ZXjKNU8++iH+n6ACxx8Wx3rOSd2uO8YTK5405qkHYymCU1JvXVuPQ5R501G22djhDrSfs+LV77tCewK6Y5f2kv8IGqz9JvvyvKzbpPqvvJFel6rsKYPpjVY7kEIfA7jjFx8SW40uSp3JwJf0RLaIrVQ93Gow2fooHTM8SDkxPAdeigPQpnRMBt0+9Ifx3owYzYBaHHb8O5SDsbk61xcyYnmKmWFwnNNxeFzMowiyYcHA7WP0VrH50mM+SWZx+ERnxXIvyaeOGXt64BXY8MspBjqonCOHA6h/5s8x/C1ZPW3FJ9ShOdDyUqvdUTmb5Z5FY1GvH+p0aape5ga+/wwXv7/ahHOqIhpU5/VJ6TeYH8iGv/GfUN/+1/Bdse8Eiv0Hb7VDpvWD1jvRvrfxLiYvTc5D117Fc2PnVTvmronB+i0cAsEsqCP9tCATTJyQwZShIcvhK3SdDyq6pgErdp/gni6lL03LQsDhxTDVkKX410pkPB+BdMcWNbXdDFaL7bWoEVwKCnn8vHMfHUtRHxjSloW0sRvySe2OI/B+pqIhrvchP66vhcDM/nHpCr7xKRhtwlgJH+TjHLafs4v1aS1V4aggFjiiiYSoN3TAx9XCHD1NK16yBAyId09oRamSB0mMKjHrWzolAjyObGmp1hIpPqtiLxRSXbsmyo0D1IJJBeirFig3jIKd1nwJn5ggQvok9VHjKF1P41GMa7lb3SXEz+TPLFY1AP5mChjLreCA5S7wD5Tk6xdjF6eO1SO+oD/KSNkpNnaL3Rz4JuapVC+8x+aQRxZr+9CUjkg9zRwsp2hrs4ztxULw1/BWG4gsThsB/W6VHcl7qvkzHnF/Cq6aBelKqHsl0K1q/KJ2SvTIahQ/d+CIZfBaJDpW4G2Q4yPlFbpTXCq+6L/9QQ4Pxa3dUqJwc6A0qp1r+Lt3PDUal6iGN/DAcSa5ZPST82Ld/8rALT/K2REzlZR1nNPWPfVstD9JDDB8ySGzKL8n3b6oBLHHGt0SRYoqxfJmd3Zw2bYTcH/ZhBOWfI/Feo8iwhzilpmAk1RWF+O1xwTdOrJoSP2ut9Z6UQ7O8SxbpfSa3JJfsLA70/DMHhurBxAzoqRdnQW4X5shwludQ6wmZEOWHFS/lh42kmQ+r5w7tCRrkTJ7kQduLMb0ij2D1J+kVVn+KONWIkNFAz7F0zHqDyqMMu1BuOYbA7jjFR2XA4g/5GQwuiq+uW4UiHMrBlXBY4kU9iPN3BFHHCJtaT/aENSj2c9q4EXaA4WnGT6ZjJe+SIeh7eRV4lvHIJxWVg/MMRtcTKkZJF0/JDE6TMqEHIsSU5FoG9A67lnyZ7YDkw3wOVn8Fqx8dyntYf04tSqBH2FR0munS8WbUU/atOMnvsJFyZpb8ZlJem7Nlda3CU76ZnFH5M3/D6iC9xuSO7IRfv6ngUn6C1dMqAtMfKukPxUh+jyQ1tZX4YDMuqHxLqS2Leu3YryX/cbEXenpYCvy5GDf8zBs8sA9/jbfVazIb0h5UVXvBIr9B223iNwR6L1i9Q/gwebLyLyWO5rNVvQ6y/jqWCzu/2sxfNV/XhIB29qDgh6SKinzMRcf+MFTYoT1hSBq4XRdy8omPpAf1w3utY10tOOVtgID3Efev97giObEpTFTxa4uPqkelwpBc0goV4/wIxBMTBUV1RDQ8MpJx/57+uD+ot6spp/hEVxNOK1agwhVsQrq3d0W4Cc8Bx4vbgO8xo6EQr4nF8/SReF6jLhyqulF8yQuj5aSxhV9yKikxl4OrOSfWw0mC8tQzUKQNmiJc6w04MxypYh046LqAU/MoGMjeA8HfyVrKgUU8E2Bob7kJfMlkWTwkqIvFoh7n10e8Q1MRbsfnhXQELiIQMj4vNBhl/RsOkzsG5fT0BDievXqiI+O5zM3pnHb5zHgVHuT0vxOuZpx+Lkb5TxjpOp+TnDrcTmwnE2WgPL8+D/nrfyvkg8lVDKeVyyAHDw+FXF7vQXrniYbG2oK8PZy8K11RnA4Ug98RokNi+CDguWw14t/2Gc6jx4Cvq9xIf1NB4Q+cfD7gOHII3rvJ42rE6avd6PDwXIP8/y0e5XJwvyuaUwPBz0OiHtUV9ej/voccDBmO8DERSG+r6EEe1EHl1+1itKUz5GxoO6TfJtbVmFNeAfKVlIT4bvAgv+w+DLB9/aLFl2aLGQpJych/4m2oJwseBi5ff4v68sx45KtZBDpSrolHug/9HeVw9TWof0OSwWczN3BauaJwPyc21dJ0FJ7g9NtvduWEkcOVy5HOpbHArRy9QfXOLUbsb/KgoffDT5A3pldopOOBgchfieiguHQ28IwTHSLlhCdH+sVn+Rdwxp+uiIE89h2KfFwt6v3O/LxPOWVmuTpy+uUXfCOXnHQqzm8vMeMj9Q702/eivqSmQg5GjwOMW9bjm/w33nKMCzng33eGfKQPQDyBeg8N98cGm+Ud5d8oAnww+0Dx1TnmOo/Th6sKD3A6ftxVl9Nn24DPgw+ggTB4SOEhTr/KoSiTNBhGqPUE6tUdXSGn7NtY6jg514Ad2roD5cUWT6MOz8DnCL9pHXAox55QR8+QodADHjEl++RJ6A+v13UNp2/32OnPsEWc2EggOXop6dAv4UWuCE6FxcB7YKrSG2RPP1yN62jRcPHbBZRzt5vN5Qi782WBsF8VtjuQ43dy7fCBfLNPOUwHpvizb9zIvg0fjvy1EvqX6VcqrwSx2GIZuJL937YD5ffYE/A7LhT+Q0/xbfzIYeBzfyHwfPxJXLcV6azfAP32YALYu9EDudm9G3b7Yjf4k/rCqHX+e5zeXVw4g5M/U7ATjw6vrBxAn2wuAh4DBoYt5NRfzDQLEx35nkTw9c0O4PS368GJxwO+d+2GX8A+fTIdsKO+byA3bZvb6i/yX0aIGVJspI/kvRz92MxglPU87IS1vwD5YwPapEfmTUf9qB0B/JqLjoSXssIWcAqvj2x8tjXsLU5z50OuDh4wZU9d4hvXOnXCPuSU/gT0O/OnqH41JO/AFbVxQ+H3nH48oBYfoucP90d4pi8o5D6xKCez55T/FhHoeF/qRTl8uRtyZa2nFWOmP4jf9z346tsfdoItqklHXCzOzWPhP+0R6dx2PdIt5Y9Qg5b5QYSntV+LhhKbeUP1rodoiI6fCrvYzM0/8DH2PDkCi/sMe8RKnqutvUB49wjUY5Tf+M4CJ3u5pIAr+iD8U4sq6m9D3ywQHdTl6B0aqS7aj/Kw9i/BT+Av9MmIIXjir9eQs9y3gqu/N4lFzsqRi2L+9XFGmpVfXbiP00feQE7P0jtqZFDkDwqC7f8kr2lxnhfE9iPtYuWiJnJ1K7w/Kh09BMnJ8j15luHltTzLKZ94Lzwc4djiUEEeHaI51VP8Bvm6Ci4XC5A9Z7iuWVPyqQKKP8GmG2x4c3rmazmSI/k1P7e7ViNItMpmQzES3CTSaXyq3GiRmMaRaiTXImGZf4mzRbCz7rZd/ZIZRr2rXVt9MygfiLPC+2reh32+9Yi96b1gL52Wk9N8BZt+RcNLPWMnX3Y4W6Wv3hP1xTKc6XmAPr2Oa5S6dVV50iJRwes9q/TlfaWfSV7824bI507PldUTTtNxGk6Ws9PwVuEqqz8t4w3SHkl5lXq3snYnVPhY5c/qvhwhg15o4Zb5sQp/pty3kwOpjwPq8SX8I6RzRYOt8rmR5SblofIxnhqDVT5lOUk/R5WfXHX01GgM8FnOjDFT+Oq+dKqnrfhScixWP1b20KTXrd5XOIoZPcDLXr/L8reK92y7L+VcyV9Lfid4f1uVF5XP6dM7svxkvszl5VQulF/g0K82p1PV12wM+sw4AHTNmujxPPgrerLezEaPz6rV6JFoEIEeEE87rPrX92G1yMuZkQ3NhUZAI6AROOsRQAcRW02RpjKNGY+RO+Y/Uw/9/b2wWBD7NEMfGgGNgEZAI6AR0AhoBIJEoIzJ9kHGEKLg6lsmmmrx5+aYYsCW+aYh/Stj4PiwKbC0nL5umIYIdh2NRkAjoBGoIAL/txdTDbd6oaf/MUg3TCsIpX5NI6AR0AhoBDQCGgGNgEZAI6AR0AhoBDQCGgGNgEZAI6AR0AhoBDQCGgGNgEZAI6AR0AhoBDQCGgGNgEZAI6AR0AgEIGD5DSq+Ca1TB6t63dEFq3x61/NtZvMKvt8ntx3BVNx16+2mdqlvlmiVvnrh2BB7tTeAI5sboYrHJhn9uIoQUPvN0iptd98FucnOtkrOSg6x6t2B/UYDTl274RvlrfmQK7ZaXYgP+TE5pjLGi1Xw2PL1tBroO0uRj8BVK0PMRkB0WKShTRusjtiqDfa/WrwoIGAV3cBiGK5orHJ421+xKuBn21EebF9VmrJvrx+qiL2AaM/Ucgxg9HdyQy1eRau0351o0DYbM2erDderKR9nCh/VlN2QJYP6ECW2LfprPOz73OyQJWCKSK01YaG3Yd+viMXq4K6IgG3lTPGF6rK6cQgV32daPFb2WvqNoeL396LH5aI8ho/Trd1hD33bsUr9F9tDhUdl45GLWsG/qemPjtYYYJ/WfcmpqCjvMCe7/cb9r5/uf2drewGrobNtNMm/ioiA33f6V9tVckT+/R1dob9fza6oHFh/g0rbKdxzHxzOeQuRAHM45UHLKd+fAEeUbTBvcUCRxMZiEY1XXsOiGl3Yvg7BHaGKJ7hUdeiQI0COSdNINGj6JclV8CzTsZJD2m/y9m74NnnuQmwX1EYsz24ZW8Uf0DYm899HOj8WQY4fTsHy32PEtkUVj97uTenYqdXb2vIuohg3+HlxOupXX7FMvV1slX+ODiqWPimiaWNRDrt94GPZJ1Ccgxba6YeKcoL98SqwuvBpLseK5veMfY+2N3o8BR0kL88yvuPEFrur4kN1jMh0ThMfMvnf21mtEkv1YdJ41NOn06o8HxZ6u8OfOV3SBvp0xhToj55JVc3PacOhqjN2uuK3steh5sdKj5MeeOKotJOhTtYuvgC7RPrwbzdh8c/ZU2An23eyiyfY5wH6MNgIaJuaa29Avdu+Cf7Ne2/iOmWI4ea0/EPUl49XwR/vGPJ8BMu2Vfg/Rnuhk9imMT7o9pQVbhW9rzpiKIKxk7CN1fOzKhqffM+ygap6Uqln/CeffEGe89Zz6tHHruWOkaX8fLy31ivfD/YcqniCTVeHDy0C6FHZ5cvbxOnGzrj+n+U+iVZyqEYKySB96wstl/7Y0AN3QTT2n7rKnfc5pzVedNzcehv2cZv4L/8bVfTvXL5+9QMPgI/ONyD/rEFIDcQluVWUqnW0pBd6JMKQ+XwYuV7uRYP5oiYl2Zz+VsNOP1gnYPOERq5Zh5fD44wpR4f8/m6C0f6wz79aXfwqB5Ac1LFjVbrVzIdK93f6B3qX7dNLPfAzc6orG1Z6O+8LTl9tBx8feKuNHwKi+nGorvxVdzpW9jpUfNjq8ZPcNf52t7SToUrXcTwmu4R6tsyLmVZf+RzH4zCgpT50+L4MhhHddxdBH+T7YNdXebHv9pMZ8L89nZGPL3xogOQ4tr8yneo6n+3tBdSzGdl5Gzk9nlFduFqlo2ZM0cDlixOtwgV7n81RxIGeETZVkBz+fvdiCuXBMOM4p9puFU7uo0cVsX9/KILcRXBQt+Sj5yI8HIL+6ChM1WlYAsFmG2DTscWHs/VvsPHIfX+wUfTdvZDeVXGYspCTqfiT+21dZjBiG7Yf5nRtAsK9k8O3rTWKP/r41KnNUW5U2DoGwrGpDhs4vZyNofbrOqHC3jsAq1quzcWUiIXvyCkRCNc7Ge93iMGU6QNhxi+cJo3DKsYnTmCqWmcPyoH1jFB5sH6E/3Ga9TrysW276jGjhkK//uh5PlGEfM+ci3D7Aza0Bq5sShdtB9F3ILbt+SIf5fyXBNx/NRP5qROOeG+/FXw3ENtIZL1u/MRp506F0yGDUXgEeuLrRRjUk3pxQ5THCzlQGD4f5Oz6TuCz5wBUtIf7SElwKocyPOL5VV1iZK97Ivjo0A4PDhYjncypUOjXdkIDM/5WlGtODvDyTw1GD2xLN95/Ig3l9Sc3yjEjDXKfnYMG2Q9iw+9hqeCndTvgt2Y1FP+8bKe4n6pYDQPl3C0RcjBtFuJfmt3hck4/G+CLte9p6jwLT/tQ3pMIvv6WAD4zhfx/JjqKWLh2nOzlVgEr/ih8SX56JoCf30S6I4txPW9BWDKntDTgmLsI9wv32codyft5YsP2QPkHGykjoV+6eFBf2MgPOSYzlZxJvh2XI8nrd4XYh5DVU9Jvfv0B+T9UBFwfTMLz42Eol7fm43xvT8hTmIFw8+aj57xJhJ28KX7FvqVWegz66fNtwdY7Ff81HRjdkajqO03h2r8bcjR1ct52TocOqfAkT1fGAl82Y4bswVfFRkNOs6aDz1JTvgi3P18G3NnG86S3PvLXA6l/WxiM+g8FPq0bQi5+NuDQPRFgcJVjeowj+/4ayHUtKXepwDd7vuQb5WPNhwxnp0cRT81akLd+A8Hvei/wuMGD+w1K0FH0+IS8jzkdPy7jN5870H5zDRpA797dA+9fEgM7ULAb+raoCHZzx3rg27PCehp4bhcNP1bvSW+wjiVqmN4k6i+TV2rws+cdOV3khjz0Ska+Ps/n2t04tGIlwj38CN7/sQgddi9NhT5pFoXn9/VEeVzSDuGW50IPvr1I4UFy4tfb6j6N5PzKGMKh+KFyZ/WO5PWkeD7zFfB59BjSHTgUb+XnK4dbRmQ62+FgCu5YX0Lum0SCzz69kf8/Cfl+OQdyc+KYrR4kffTFF1Z6QPkzpMftcZf7q/Ja56TeObUPQdtrM7DiGulZ+0fQN9EuBC/DHpM9+rYYenhyDOrt0gRpJ6U82OXLaMmp/VV4P3kA5P+tHMhZjyTo9UcGSH9NZgflnjUL5R1olxAfk/d6nOoZym7RLhX1RP17QukP6Du2jRf5d2X4X9Qhd/gI+AnUhxgAmDhV8hfc2XK8wEC9/no3Pq3qbsiZXXIXDrtylLiF2s8Ntr1ghYf6BI1m+j3UH+VWjj9HerTidgH151YP0rkuDvJzqLhkFqfJmWEPcrohDvrkZtEumLsUcn5dG+iRegb0QZZojzSPRjxJ/WGvIkpgtz/djXSKxQzATu1QnnNfN2hmy5/CcZ2QgPdXrJYDDHbyqOwM+QdMzklPW6Hs/H4NGOg/NYAjsfJ9ZIT1iNPIzFJhUBqaYmQbAVPFGpqE91xuFYAMzMzpytCSYXlqIuI93x9OvWDxJ9h4CJg5L8FQrfMi/QU5KJB1W5RjEGMweutD8L2/CKnPzUK491dBEbb5L553T4AgpKcAcGYXKT8NI1BgSckId2UnOBhjHobAjJtiNOd0T2/VwKCE+iThG61HxyLeXklwVO67DxW9fn3w/XQaCnxkBgzaEWGQm0QhXebAEz7T5xgHOD33LBSoqx34nDHJAlXRwIx2I/0BSYh/RApwK/YBh6YRuF7xiZCHacjnYfH+v6Yrg0G4P5gCeXgmDRWCyQvd7+RBPO+tUlMASHBv6ASc+iVLPismh/LtUmdSGB8sRQW7R3QIhPsDHDEYHShC/lu4zQ1TFZA6KnZ/i3zNzwGuRQKf56YYLk6796CevLkE5cEagJS/Z55Eg/HpNCjOQanIbzm4U8OsfoRKX/4hQ7TsPcgF286DjkWrIW8fvieDAeer3HBoWAcBHczQUDn8a4oM51RuZfiAMymyZe9DbjaLntSNPmz/NO0VhC9DP5ADUU7+yXA38djJP8rj2QzF1888x2wE281pzx51X/5xWo42+gMNw/0HUT8i3eiAuSoGCnyHagBAwd8SB8f96+243iu2Y2nlLnmF067dkr2Asx0f1EPZpgvK1b7eyfjhOPQR+io+AR1zjw6AXMbEoD4sUiPxytEgfNnUcdI3o8Yh3PAU4NFnkIxfnUmO7xYdIyty8V72LOjfxpFc+xox3bsinsgIyM3I8cD1Ko+Kx/znIoNR4XeQ8zmZqGc7vEYhp+dnmIMjfms+HOtRqs8XiIbXwCTolWfTgBubuUH6pnsy9G9yrwA+zDeoI2lKJt5n/cPooJwGuZ89C+e4dtC3LaKQj0roaZE+75agjgmqhwNSwO9jA6Cvf/ZJNtHx+o0YQTm3BPYuMUF1XJDDzJ6T/R+UIt/D+YXxCH/UgH6Yngk9uGChsm+nvmB7pfgh3M4R9qd7HPT23r3g68cDArc4pLfqA6uIneIg33eqL2G/GkUClw/eBA6vzIX8s47tE5zYFHg7PSjtgI0eUP4MMeoAd4f1Lrj8Bus3SlT9Z6f+EfRNOfaY7NKc5yAHgXbSab7A2dWiYTg4GfGxT9KoXNhAAZ1rswI1HVQfHNglkoMHkiCnbBtFqv9dkqHPe/dSfhB1GJXjfwWrD03sOru81oMO6UdTwRfrIKf6/3ga5HnQMNUwvYyHYB3pdJwGPzfY9oIVANTuceDPhcou0EDP8jVg5xYP5KJRw80dOJWUoOH4nZgpxwb66DghOvpZhwl1zLOGrTzIj3puLC7fnA+5ys6FPbk2DgMg74uR8vuTIc9s7RKa0bg5Hx0oV7ihp270OJZHmX6IzzVg8BNET26+DyNN3+6VPXQQyB98Ml3cX78eDsU+eVv0CDUUjnE3MQIxLxuAsMVjSLC9XvWCxR/0rDiPRzka1FPf0QPD0EukH+dBA3BJNvLZcTYE4HI3GoArvXAkP10Pw3JVeyOa02eXogJuKMD5Ix/CPzsV+Dw3FflhDUzqaXE3RMH+YzjCr/IiHdaQJIeSxU/8jR5t7OXUQ3wszxpOVLEaRxjncfrtNyis9h70yM2ZBUeC9TyTwfpvPgQqQYyo1TXQUBz2GNI54UM6h4wr8ziFhZlhVvklRcscLIp3Wg7y90QGplp94IWA9rwD+bz4YvDZVjQ4G4seGzbiSPxvFuGXeVXPHfWQDx0GB+7PbuS7TSvkZ/FSM1/BymHA++KGkjcyBE9nAI8BKaoHmXqm+9wLHP+daRnPTq56T56EnP98DOFLDOB3+JCxh9PFrfC+x1OSxWn5auk4wYFeLOQuOcEW9/w8Rmu9Zn5kjyPk+qQBnI4XqfvyBcL7U1/eNk452ZDn3ByEb+GWwRzLrXrh1D9qhIgUIxsoIoV43Ad+jhyx0g92+YeiXTfDVv6pg+Eo66LDkfcVp5+PqCkm8oF8bleO3xiMGooOunL0BznIl7SEHDw/ER0B8clKX6EH34fn14n6y0bgqX7c3x/14JmJyvCY+HSsx+AgOa530COXtoE8pgrH4p3cU+Xn1SzIRWfhkLBvi0me+iYhP3OyoB/kVPybO4P9N+aasiH02dPjoAfeECPnrMFCcnJ+NPiQamlkmtGY09DBwCclsMEry3EJL2GmH4lOGODvVyNvL6ejvwTNB+For0dLZnLaXAAcmL6k954VMxJmZoMPZtfIoWwRE8CH+QbJwy0e6MFDhmpgUX3aLsp1227UI6/Q9yzdCupplTw5wsnim/n5Oar8qcN16WoVTv6h8pcdo/ImO1N4NpPAfJCDPjkLeofpMWq4d01EvWblTXaSNeAqelC9H5cJ+9rKg46/jp0g3+3FYiF5Xsgpm7JrdQSLA/ktDuw8pXdPb9T3FcKvOChmMGVMgnywfYLpExHmD1jYX+SPjVjb+TNSHznFnRxqB/XOaX5J3p37jVbF4dQ/grxa2+O8Tzgdr2VpJ53mi/BcOF/x+4PB6PHx8CsG95H2Rj2Xf5zaJarnM3LQ8cL8LJIDNiOD6luLGOVfkJ4rx/8KVh9KPp2eqZ4zfURyyPw14nOZ6MDc60M0qX6/6jT5ubC/otlhVKLdQTMR5Fo6Dvw5Wiw2z6+fK2gXlFxTfZqcCT3fO1mOTEMuWIOf9P/UHO4l5uXvEfhvDtTbsnxJnha8D33sioDdnZwhH6M8f1aX6g/5zcXq0qk8qhdC/KcGDH6cGEJmDrD5oIrym3AIwliLShwEgPITxRTDjsJQsGD03kn2ojioYvov5e2AMyneIOIhwWCCRfE3FlNxJ0/AlI5/ppdM49SzLwqoTjrCRbnVlGDJAPVkfLYVi3w0aoRwjF/qmTvpk8HUmQTqUtHTsK4ABTkuHeeH+sDQvDYXDve5ERCIZ8VIARvBo56aTV4Z36mG1XMt+G0jFqHZuAUGPzIKDe7LY2DwfvSpdGku+ogMCHTqMBmv5fmUcvWXC6Yc1CZ1btRmUzhJYcd1gkP1uhiRloauVOxUDn75wTeIBQWoWGzklY664cDBH07FQPxUQA5VBKY/VNHemAM5ZPlrxSmpN6aqXe5RPUam1xxfUvmzRcMo3/WMsPs5NWqs3qf6sa4A5eR2q/sWuKvnofpD6Rwz0PAo1eHrVG4ry4dZP8j4LPLvWP5lPKE6O9UfZKh3+k4dMd0iHPF7xbe4f4mDg/p2NnDvnwT5+3MM5O1z/0irmf8g+VCvO6131GCIFq9d4Fbv7zQYbfwU12zEneJj8koOx2Vu6B02gigO5H+3GGGrU0vetzyTnjvmQz2oY+D9txYhncF94ACNScH1G++rKVaWEVbwgYmPoPUoOfhl6C26z+oZyQcbYbE7KNz0HIzAD05SU03J7jE9RXbo7QUqGov6ErSepnof50E5lMoH8e/X/yrdYP+Qvr1IdISMFSPus1+BHSuVXrDxivDoePupCPb4pXTE+4Swp38X8jMjxzb6YHFwqi+pfl3eDvYu2i35UHqNnrOpdfKwKFfUAwf+jNBH8DPscXdc75zml/gPgb2mDgN7/0jCVuGz03yRHJvrA2sYV9VBdpLpD+q4qmMEXa+rii/Slz/55LfhkB+2OwDxm9QLduF6D5/XYlx0e9fT5udSvepogJ9KtDtIPirgz4XKLtAqyQvfwcBWTQMdt3d2g12Jciu7K8ub6n8ZYkmfYgwcBnn6RHR8LF2FeO9MlK/bnilfYaddHmugofRhLgSP9aDTNzKNI9WUTCo45odQk4V9WyoPygAzyCQg7HyQ07pPoWBZDzc1bBJ7yOCigSimHIa71X3zn2DjcRuMNm1EPg77wOc/R2JoulFk2EOcUoXB/DYR/B31Ib9po9QQNvXwj3wSCr9WLfAbZvAJocaRmoH80tTLxV4YpMdS8O3fZW0wNa5tLBy85N7I3rCRcAx2+DDysmYNBE82qGtHoCf4soHAjU2BpSmkHW+GoL2ejfdZPKTQF4upId2SMQXjzkQ1AkOL6TxlmnplBrnUNTlGrELIgxT09dejXLt4SmZwmpQJXCPE1F/27dcVnNi1PKjCnCuvDHyDyKYOkuL9TiyisyUf+WDyQvfZWR6kECshhyRv/vhUzxSV68QM9Ky+OAsVdaG9IyP5onzVDIc8sBFreZAjufZj3C8SDnjcDfIx8nmRG/Kxwqvuyz9m3OV9q7NUhNSzeY6Ql6aigczyTXwyeZUHGRJ2TR03pe4HJbcysjLOVO+ZXqD46roDQpj1gzmAKf/oCW3htpV/ive3X2V0sv7CsEdaj9BYlSPTHo70B9Url2qogU+2uAw16CaKKZ/LVkN/vJyL8/B0yNua1ZJfy3NF+XBa74jPJV40zNgUUnlQxw37ZoV6aJmjtJ/Txo2oL0y/Uf0ZlgI9E+NGOd3ggdz/NR44+OsdGliBMzegt2qEQ2/8IxXvrxUjCK2vRn1h/TtUj6+8SrIXcJYdnSQH57ilvcL7tZaq8FQ/rfkIWo+SQ870ZBGnGia9x+oX4VsKB8WI6Q/pPRae+J+dAz3IOj62cGp3IfTWkSOmt0QHcCX0NNXXD7PRYdIjSdl3wpvpNcqf37wjP0eKwJ+/wQU7e6HomC0VnvIzWdSDaTmQe/atpdTzhM95EWpmD4VneJn0NsIzfEh/lYEn6T82Ukv83uyBnbpAzIja5QvAzXwjWByc6kuambM4B/ywmRV03CpmUkg9PXiAmR3gVKpc3QYjB/6M1EcOcUdHCHMLKHw59c5pfitqrwMA4Dcc+EexXPOwmXVWelzGS/ljjrvZTjrNF8kVkz950LZZzB+0OyjdcuwSyTmLl/zoMuRa6o9g/S8LfQj5qxUGv/TKWFXv7PJB9a5Uh7Y5PNltNgVaHlS/5Yieg3KkNWxC6OeSPKwT+rcS7Y6K+nMhsgtyrRrY4ZfEN88vL4T/tkCMXEvQ2ZnaZUyOqB6Wkley10+mqIEywifxDtT70aZ2wWEf9FVzt5phSH5AjBvx1y2BHxNEe4DwYHyZ/c5SrAfzt6arBqede9Bib3sBDMTkcfhG6WaxaM4lschgXcMVyemX9jAQA0WDr84xhM99Fw5NkfgmZMJI1/mc5FSqdmJZ5CjD1ZTTuoLCfZx+2CeZLjzI6X8nXM04/VyMCm0dDxyitfkAZOsOhE9NhSIbPQ7xbhH7t76e4YridKAY+RkhHKXhg5Af5mBShdv2Gc6jxyC+q9yuJpw2FRT+wMnnc7XgtHMH3mM9SPTehOeQ3sVt4LiPGY0e39+Og5+nJsBBvOUmhC8R2e7sgWCuWgHH4IWRcIRqRwgBEiOwL2VhkYNPPsZzdwzy8fQEGLpePRH+uczN6ZwCDTYczZs8KKchyeC/mdvViNPKFcgv+5aP8jNgYNhCTv1FAz9MOByeRLz3zQ7w2ygC+D+Y6orhVFKM6zvuBV8vZhbSsX27qzmnkUPw/k0epPvVbnyLlrvYsRye52J0pDPyOzAe/NY5xu+6zvtwVeEBTsePu+py+mwbRiwefAAO+OAhhYc4/cqGjMo+VIOHFPaYEYj/Og/kubgYFTgvD29/9yMcrWfGu6I5NYtAR8Q18XC0Hvq7i46rr7HCvXA/JzZ12OJwXcDpcqE4hqZCXvZNA1890iAHl7mRzpYC4MK+dSH+b/C4WnLauBrl9eEy4G8tt+AncF9XdMAwA0WKaPhwpN9K1I+vdoPP5lEo/yGpSI+VC+FyaDVwGjgK75eSO8p3rRqIb9708uX/yy+hb5KTIK+Jt6G+vb3EjKNtOVKH2BYxQ+H/frTUH5v5eoZvvCWLB3L79U5c9xpk7OI05O9Ge07s21NafI1tk0GOUmoK+DrB5kSXfRR+yamkBHrxe6H3ytBjgg/I4V88jusd6dttOyAPjz0B/XWhqLc9xTfSI4flfcNp+1aUI/tWlsq5h9j3d/xUGKxmbkxxf3IEPjFIeQS5YnqMDOeBg0oOSP56D0Q8J2uh/I98j3JOH4n3atQFTnWjsEjJpLESDzNa0B+1RYfMU88gvQZNEa71Bsd8XGgwyvq3nR4NW8SJjThTwyYlHR2P4UWuCE6FxcjHwFTwERMB+/jhatgJttiR6UC5jUmDPUhJhbz1ike9HSL05wURkK9jYVb6Img9Tfp80TLko29/yCdbxIqOuFicm8fC7u7ZDf7YpzxUnukTUJ5dPQjHZsJQuV7tgT39SkyBZjOsKPwooZ8uaQW9dL6Qs5go4PlDKuR2cCzwY/qB/IStg3D9yEVIp3Us6sNagee+fcD1yBHok4tFufwnp/B7TqW+BUcEAb/g1/e9YxzIIV/0OuTXWl/yDwWMb3Z8bTTh1KoF6smEqUgn4S7gMjYDfkTrNlblmreO06Fix3qABOfSWDvcgev3naGP00VDObDeoR5+s902vz9yi73tS8f2+kIXo/eXFn7LyT8iye+6LqwbZusfkR5akwu+Bg1Bfvz2GLjmiw7wNmLVfWYnSe53fI768o54v5xyJId/yFCUm0d8MnbyJOTO6w0QKHHD1ZETm1pOer+UXaIBhW9fQ/n0G4X6cK4BOdwn/KSHUtHQaCH8vf8I/djrBlv/i+RTTgkvpQ+pYSLrw2dbw97iNHc+7NDBA+Z8oOMwORl89klF/lu4IYftYsHvYIHnjWLG4uMZ+ORt6VLH5UgNoND5uRhZ3OFz2l5Afspod/xUyOjkSTz/odjWnyN/psM1wKnydkGWB3Bm5UZ6tMddWCzpkcGFMzixRezkIrUk16OGwQ9kepL87pXLoFcfHgp7wka46TgvHPfXivbWR15XY05RF8KePTkA+uj67jizjkfqMGnlhh57ezT4ueeIM3n82/VI1+ORfgT8/4J83K/ELwQ1Kkq2qOV1sFGqkQ3R8wVgm/hHZh1GGGw8cEhr10ZPP+txszg6RHOqd05FF28wRyvzZ74vr2U6sudazjGXU43VfbGKpxxRkuUg4zGfgU+joHE1x2O+lukCz3PY6hQ4zFPwOlzJaWwa+JgxCw2Y5tEyf/K9YM9S7hQfNGLLVh8O8kCDvHUb9CROSQvydcfBwW94ONKpwP6cDlOScuswuG0wO7m1jSBEAYKVf1XP5aqwoeKDIrbXHzI5NXNB3hBnWS9Ntx1fqvzJkQPTmxWtd7InXemXbhz5GmV06Z+aYKjkROk7qs+svkiDe2pytlchrwe0yEfo9ajMiFzUBvrxTbFoVIMGkBNXNHBoHws9whaVI37YIjQ2h9KPJDDWelpGo8qf4mfpSjtoJWfSfovVh5Uds+DPbHchx36+JB8VPSv+aTXi3FUVtTMqHoc4SH6d1gPkOzJSpiPfD/ZspwdkfHa4V7TeOc6vsM9KHoO010quhD6S5Sr5lvl0epZybRXeab6s3re6r8qrknZJ4UgR+uuP2f+SfFjlF/lkI/jVdNiVY7B2XrIt7al8X943n6XelPVBlrPdewHxSPtEq9hXnT9nTldey/zKa6dn5YfKmbCXcg+FrYVjcSAdZgdacqpZU8qLWW8FK48WyQV9u9TYcNDv6hc0AkaHTpyeS0NPTjOxKu4DfU4XNGgwsOXZacrNmPHoCaovprDd3wuLHexTI/ani0+drkagMgicafWuMnn5I7zb4c+cuiSix3r2FIwEPS+2HWEjINRjfZmYqVSnBN8uBm6380fAqnQepWNkXMzp9ZcxU6K2Gz39/xHbg83PLv2O/q8R0AhoBDQCv38Eav7+s6BzcDoQwDctf26DtNtejik0vxRhisSBYkzdrv6GIKb6MK5oqk6LRpiaMGkivvEKnPJ8OrDTaWoEKorAmVrvKpqfP8p7+OTgq+2Ymrp8NfLNtpGhb9NaxqCDbwPWhizIyvqj4GKXz8ITnH77DVPfWrZHx+PKXEwtZNso6EMjoBHQCGgENAIaAY2ARkAjoBHQCGgENAIaAY2ARkAjoBHQCGgENAIaAY2ARkAjoBHQCGgENAIaAY2ARkAj8MdAQG1XEuTH7WcbOvIjdHxszFY1O0MP+dE3+Lwt8dSpf1XH9O8Fn6pD4MyKGd/cXhGLxRlu9UjuztRykt8I42P8OD+/tFF221i1yrTMiMUZcs8Wc6P3eidbBFO3z1Q8FINn2Z9gy+dsyX512VG1qAUtYpSQiPrU0i1xtNIL8nllz0iPLep0DaebPZWNr7Lvq0VRaFGT/snSPlY23jPt/equV3LV9g4dOf09WS6qcrpwAT/O7YQVn9oeWCGj72sEzhwE/Ks30sbs9ydgWW62UfRZfigDT6tINolU2W1gMGoaiW8Y+yXJVdnU89P0J2B12O8MRn+76dRFN9p3qnL2zlB8qjzfZ1gCWHTlkjb49nfGFCx3zrY1kYdNOQXIk3yvis5wrGJjsRjMK6/hW7Iucacm10lsQxVvuu8PhfrIVjWkZdgnjYe+ejrNH8Linw0eFm/p20EiUOHyCTKd0x3c0lGvLjtan29gdns3LLY0dyG2B2kTa6sXKgkcGqaXxyLdl6dgO60efr1Tyfidvh6APy0y9XgKtit5eRa3jsZ3Nc+aNTaqu15BX7MOetrOIj4e5dxUbHO2ao1VOQWUi1XASt23txO20Wt7YAuRDqAR0AicJgSkAoajfk/iaWLDcbJwDN5dZX4BhuvjVegxvy/Z/Fxfn90IoEc5Iw3bjsya5TS3VvLk9P2KhkO9e3EW5HaifcPSIiGMmHT24Lxzl0Uwffs0IXC2lo/s2EG9e9VxfauqYkA93rZLrRIsEqqoXnDKJ3B4VmwvNq3acLDCH/bvgmjIXUkJ9EtttmHu2XVUV71SfgXNULlOdXzjfqS/Q1/Aa1UuZxf6OjcaAY1AdSJQCwYuOhobb/fvj5GJ3EW4LtyHkZl+AzFSt96LDV9v8OB+gxKMND4+Ie9jTsePSwWKkRI2EkI9m2ygljYOniU2vD43Aj1zPW7FCNDiZdgQNmmAQRsPv5mTt5HTCq8EQ/XM1eZv9OuP904Ugc+Zc7FK6/4DyA8bEaVtRvr0Bp9/aih6fHPARzsxksMMK204vjQbU2R/NpB+0T7c7zkAqwU+rLZNQfyXtgH/ve5FuIZu5HNWJvjYki+nMiIcyxf1rL84ET3dQ0YC509WI/ycbJlP8xnpZc1CProIh5yNGJ3kNDMH6f9qYNn9egbwZ89pdch6BtJ5wl8+Yp9V9Ije3QvvXxWH8DmKfzMf8hoG6vpOZnzgEHWIBb59UoDjS5l47+EUrFK5tQDlMHsm8Hh8GNKtZYCfJyZiG5hjxxR+VN6334pwbFtA2rA763Vsw7B9u+KL9rOLT0S617eDPLENlwmnb3yQhy+3533O6evt4JcZXnp+r5C7tbnGl5wWvpN3mNOvDNiyDzS03G7wNSgJfEW4kc53u/HWXDfO3fOBy7kR2Fj6mXSU6wPJeO/iGOCZOQ38HTwA/nonI/4OMdhe4UCYQRt/TxqXt5PTiROQr1/DzFxalhPNGChDnmgD7T0XIr3mosF3sBjynzkVDsi1nYBr/K3IZ47Y5mGnLyB9sY8Y5PbRUZDPhiXI58VuhN/iA47h4Uj3np7Ao56BepGVLeNF/eyRiPhuSkA8LNs0kipDWZ8t8SAHrPJyi5QjIsBXn4HAZ63X+BOnhDjjECdfMc6vzjDO49SwAfLbd6BxLqcv8lFP/pKA+69mQl989TWf12E0eKg/4m/dDnK7ZnXeZ5zmZSN/bIo36bPr4oDToWJs9D05M+xBTjfEga+bPTi/+grS/WF/RfWBRNyufDBjpU4doymnO7pAnqNEfaljoPyLipDfxUtRrvf1hLxd0g75WZ6L/L69qLr1Dfg9fAT8vb8G/NUyUC9GpgL3eQtw9ttRZQ/kvoiXGYzu7Goc5nRtAvL9jqhHy73IV7Mou/xL3JFeGWqKRr78egFTNC9yg/8Hk1D+J4XemPkK8nf0GNIdOBTx5+cD73cXqfTkH8QvNnSvIXB4JBV6rklDyGdmFvT8ueGVTVc2QC3xP8ElJdu/qi/Vgz9fBj07RIysfqTqi8yGU79Chjef1T6dP/MaFGhPjWJOn28zGnLqcR/Kq2kEyr3QB/m+JQF4PZ+Zt43T1nyZjl29kuHszpiKfUei0i/kH+3fjXKfOjlvO6dDh+A/jEpHOV7hQbx9B4CP86Jgd/3y4KxcVq5HvpMHwF98KwfpspH3Y5weGQA9ec99wCXQ3kFPsf2aya/x2wngO+s/weJraQ9o30i2TR3Jt3O/DfWWzTwkXBPioa+k3/lpAe4fLMrL58Tsgj40AhoBWwRYy5EfrIFKFX9oEhSTSzgOFwhDOTAJFe7ZNDhO3/pw3T0Ziia5FxyQ+vXRcHw6DYpsZAYU75EwKKbzt6Pisykj1NB4LB0Ks9cAhDtuQGEvXwXDcnksFCDbaJYUxvQ5xgFOzz2LdF3tUPFnTIKhaRSJfHzwJhTfK3PxHnOAyICxqT9HOS17D3xu9VL2jUWrjR85LV+A+G7oBP76JeO5YagGCfE9e7poKExB+BW5UMDrtkBRNY/Ge0zRUQNrsGiIjBAN04LVyG/2LOSz1BRjmaA8U7k8myEv4UhO/Jfh5rRnj7pP+XsgCQ20tavBX5dk4Nu7lwpHDZE5L8ERWecFfwtEQ5fxLzZkV+HFH/VNDyngQHxQvlfGAv8hYmrQvQmIf2ku7k+eAoclMxPl8FEB+Lw9Gfz0G4hyZBvUU8NjxSfg//lpkMvDooH6r+mSP4RnDVMKPyIlbzOnJzPQYXC7cAAfTQF/54ZDnpKSEd+VnZD+mIdR3uOmGM053dNbxm8+K4eG5PH9VeAv+3XIwYQMxPtUGq4bTsV5tRf15fE0FR85UGybBJKnx9PBf2Qk4u8mRvT7JBlRnB4di/z0SoKhvu8+FY/pj205WckTOVDz7gOf94iGcbg/9iMGowNF4KOF2O82sGGqXiB8Zk5H+cuGx1MTgdf5bhWOOrDYRuKEA3NYqMOANbDEoRwrej4gBXLzmOjw+dknw1mdbfGg7YgqL7fQM8xBqcfpsSSU5z/F/sDfF6NePpViNOY0agTyGy06tgaIfI9IwXvFPuBcPwJy++YSxP9ZPuTpmScR39Np0EuDUo2fOC0XU+9u8eB5o4abO3AqKeETQo363/kQX8MSdDx8uxflEbw+kHg7Lh/CJbIp6kf3BOQvPQX5CTOgrxtGIN4XxuP6qAF5mJ6J/CxYqOxMiMrNsb65yGBU+B3KZ04m+N7hNQo5PT8DfJdhRyVQMQajtz5E/vcX4fbcLNiN91ephik9cJB/Ga/Dc94GTqyjjjqAzxF6tHscGtB796KB8uMB1Ne4OIRb9YFt9OhA9KBe/s+AnN4oOkBWfxKydB3hX4pb0it3J6C8mH0mfcTsrXkDexu/olSMZf+1safoWHIvBq6so4r4YlORSf9f3g58Mf+EcJw6RSbiuF7JFyzOkKs+wt7FJ6Bj5NEB0D8xMeBnUa56nQYSpk0GP0d8kPN5OeBzxVIVTv5xVC5X+/0gyif7tINwYO4nddQlnEB05dg7Kzsh9QrFa4+vrT0gRpz7baqDooRbTu/7yEf2XOC3Zzeu5y3EubHQb7jSvxoBjUD5CNSAgVoverj2qdBwYPLEBuKsQUoK4lkxwjYzGwrW64UBaBEDRfPbb3D423vQ8JojGoRvL0JP1+YIOMBshJYaOocNjCj9ow96alP6QBF+7UP8dyUi3QRxrmugp2zYY2jonPDB4B8S+17ee0AoUq8ciUKGMiaBz38MUiNP1HN3UozAHC/KK+R0vBYM7eJARUwK6P5kGO5tPtnjiB4xlh9ymA76kN69dyHcogUKUJfBqG8/NTIk8o98XiAatCq0/w81DI7+Km/kfcXp5yN5SzgxvOVBjv2MHDgEH3iBGxvxJkPYIkY19MkAdfTAAeyVjOdssRoawVmSDb4vaSmjlWeVHjXwy8CH0ln4jgxv/MBp3CSMhC8UI/JfiR7jBbl5X3B6bxHkYZUX8tCiIcrt8CEY0J53QNFffDHKta0H5dhYJQPcb2mHhgFz7OVBjse61bj8xUCHSUE+4mMNPRqRcjfEe/8Yjg4Mxgc5cKxDxOqg54P6IZ4NXsjtF9sR/y7hAB7wqdep4+DIMXUt/siRYuTzuP8xjbR/uh5yPXq0sZdTj+7AiTUYKV/Whs62nKzkaX0eo6N1gMPToqE9IKWDHPmhkcA+90Ku/i1Gxv1sy3/ogZcNjW5CvuZlq/ySI8H0hjhQf/b4cLlZlJd8ys40YpycArzn55xaf5cGhi/1Kv9ri0eo5Pa/XJN95EW9+l44nGMzUN8nTQX/r2SjwXVXMuSclTPpVaZfydGdlgM5eiID5f2DUMgeT0kWp+VixsXevagvi7NRH5ITgMvJk7ienIn4eifLb+1Rz5kDSOlMzamsPlAwOywf5Pe7vZCvDQU4f+RDfp+dCnvz3FTRkZWF81rRsdM1EbiFGai3rCMyVOVGMyrs9Y2SI+ooYf40pf+rkbeX09FfrOyoaniS3rjcjfyuFPaJlT91GF3V3mjBaf8PjvOvCiDIP1T/x2UC/1YedHB07AR73T4WcpfnBZ+//GIbO9nRJUIP/nsqwvd8AHqqlRsjzJe14d1bxpGKp2uHfwCfpCefHpe3idMbwv6wDg9q0Jwf7dSvuDKPUxgTvFMPx/WH/IY/jYL8biwALuu8kPe0DPAzL0fYP7dKxWG9UuGt/pCfkZqG8n4nV+lPCv9qFvQS+1SiLacY96n2l7kXxP+RY0p/m9KxLReS74Xz1WvkFzw+HvEN7oN8r42ys3dWdkLpFfJ/7PFV/Fr5MVRPg/DbaCZEbHuUb2MxsPPzL7Dra9fjPuuAID3/oX2HjwJK/9EIaARYF5Y4hMGVl+pMCo415MwH3Wd+NzV4aogGgDRonmuheNq40YDYuAWKLlIoohLhwP3mM0eL6zVeKO46JWg4XR4Dx+tHHxTSuHQ0fEZkwFFIHYb4LyuBAxbtlvEqQ0uKtlj0XMunZZxJkVjlNzoG8V+g4lcx0HtsRJLwcLcTDoxqWKpwp/w5JkY0/MVwyuPKXFB5svIhQy0VJBvhIUUuFenkCWhg/TO9ZBqnnn3B/06fZdJW+JDCP2mdX2oAnwiMl8qF9byTPIUZmHrDvh0i6ilGQOM6oePgdTHSW8pfoHzOy0W5dBSG9s5E5PvGOMjNCxkqPzTSeqkbBmRdgZInclQf6gND/tpcFd78h/BsLqbKMUfVfFD5M/mu6EGOybkRMGjPjoccsZFL6gDZ5HUcrVU52UVADeo35gAf5qC04pTUG1NTL/fA4ducbxkNGfiOwtFlDWpy6E+aOlL8lyoewq2MekflFSc6Jko9J3kpIx4VoemPFR4hkltTamLkr5QcUDprxFQv1tEmD8KH5YPkuFR+KN/RUZCDekbY/Zwa+XtmKPy6Asi32y2jk1PU0dFS08CI7Z3dUK+j3OgQ3C06HEOgD4ItH9I/LJ80onvSp/iWOLeApQAADcBJREFUf0j+LhJT5camoB7PfgX6oVT5h6jcgtY3kk+rM5VLKTVI+q210LtRbjXiIt+nke/PtmJRn0aNoH8c5F++H+QZU0h/KgL+L6UD1yeEnvl7CuRtRk6Q0argaKizDhQ6WIct6cuoqKpOVzFg9Yf0J7O3JK/MHpI9cuBXWMVH+iSI+kNyXUp+Zbwkx8xOkz4r5QcEW69kfOYzyV+0uFvKb9lpMNr4KR4w+0v5KaVHzPFU9JryXUqvUTysI00ewdo7KzsRLL5W9gD1t1QFloyWPpfy22hq95bNsM//FR1qo0fAz0q6F/enpSs/tHQ0+r9GQCNQLgJ+jSgVJCk0/204mMzRKeJUwz+yRIoiTCg29g0KLXffQnyTx6aA0ohhx5thoF4XPf3DRipuyFGp51ZTLuQD4uMKNxoc83MxgrJYTFntlqyW8advBdhIFxkaNnWO4lsShoZqfLL8Jgs9w2wKISmkwQNkMsrhoR7gcyJUODIMLP9kWEvhQPldIqbysoaQ/MZORkiG5iI3DD+bUkT81KwlHxufcyrVE0sNMIYfKegazJO3OOCIK4Upp6Qhf2yxAuqhZPFQfKX4ldFRvtl9N6dNG6EwD/sQ/p8jEV+jyLCHOKWmAE9XlHw94GyFDznaNfz5pZ5q9s2IPKgHPcyN8vHfRjkw/iWfZGiuvx7hunhKZnCalAl+2Td+lD779ovwZ9fyoPfe9SLcPvENcffbYBiWeWUwMULuhXw9liJ7+DHS0TYWI/PJvVX4Mv+sXA3cbxczBaKjVY86jVCd41avkcE7cgThw0UDnE3lpW9B2ZRAKjfmMNHBvsWkg9UTyucOH6Z0r1mDBobsWKgdoUYqSU4ZfpROKVytyslGntRIHJXfxAyMCL44Cw2ehTngr5zfgwajdZ+iPFkDnuQzsYd6g9Jn+SWcwt3qvuSXHEmWH3mQPvowG3qoR5LSFxQva+iR3FlXHxkN8GT4mOt1qORWJST+EN+so0EexC/Ta5TP17LlbXWmhj3Ts/Kghsvaj1E/ioRjHXeDfIx4LhJ6coVX3lffThO+L4lvvV5eCH20wD+VL1T6INjyofJn5Uv6oKZb8q3O9Hyy+JRkWg7k7sQxVW6kJ5jeJ/msWaTeqy59IxvYxOc5bjVltCUfq2arxtJ9JmfSju4yGH28FvXhqA/1NG2U1OPIx8gn0TCtVQvv2+dfjezJ9Ei+WLrysNIL8jnZvclZqD83e8DvBWKEd5dPBgv2DPvMGuTyIAd+42Z5CX1SiXQt8Ed9qLVUpUP1p5S9lQ+kvaWzA79Cvmc+B1t/qHxY/aZ6Xkq/yXgpX6XuB1uvZDzmM9WXJV7Y9bh26jF1PLJPkUhPsAbyfk4bN6rnpKeYOSc5qmuvYK3KhfRrzeUqXvpkhcn5KUcQ9s7KTgSLr4zHbA8oH0H4bZQfJmck54XCrn2wGvb636/C/3gkQ2ZX1lv4HVfGymv5XJ81AhoBPwI14eh29sCBGZIKQ1rnmOt8TkUFMFxDp8JxDy9yRXAqLIbiGpgKwxATgffXb8D96ZPQoK0tpvQ2FyNCL2Uh3P9+hSF+eCC+/XTFuOi4KhbvF/owpWPO665rOH27B/G5Y/De0xOg6Hv1BH/PZRpfc/LuNZpwatUCBn/CVDxPuAt8js0opOP7fa4LOF0uHMahqUh3x+fIf7ebYbhv8rgacfpqN/K/5C3E07Y58tF3qCuK09Ue3N+Zn/cpp8wsxD9iGKCO86Bh+MNPwDUmCvw9MBDpltQ6/31O7y0unMHJX0CujpzYyDRNJUlOQoMm8TY0bL99Den2GwVczjXAzz6xONBDqUi3RQRvNhgHl3qRry93I55UsajF6HFIcct6fMP5xlt+Dk7952rOaeSQsvHxXAO8/xYPvg7ud0VzahAOvBg/ZDDrHkN5/9/3cNiGDEd4JkfkcM1fjVR7JoYt5NRfjKSECUfVk4j0v9mB+M6PwnsZ6Ujnnv7AdVBvV1NO8YmuJpxWrIBDWLAJ79/eFeEmPIf0Lm6DBuyY0YX7OR1jlvvUw9WMk8+HfN4cD0P0r+fB/4VRiO+SWOCbk4VvWr/+GgasWxzCD3oM+W7WErGzRXrIUNYOx3n5eYj/qZ5wLG65CfdLBDOsvlKDdH0B8j/gfjxoHYv8sm+QyWAn3RlQTi0NRhs+DpAn6mB5ewnyffiQqy6nz7Zh8YoHH4ADM3hI4SFOv7Iu97KPwoOc/ncCOP1cDBwmjITcy6n6bJEyaohGGSiXr89D/vrfCoeJ5SOG08plKM+NnwOPvv3BN1v0hI64WJybxyK9PbsLv+f033wzd1Utt8jfh6tRLr2Tkb+r24Cv80T+LmuH8vhXJsqJ4UANqyHJuN/MDX2zckXel5yKfkI4ttgXlecz41GfmkVAnq6JR3oP/b3wAKejakom9MCO7ZDLHndhsaRHBkv9Uvglp5ISxM++kaWOkgroA9J/vu9ty4fsSXFnhEtojfSucqP8NxUU/sDJ54NeuDQWfI9KhTxc0gr1+3xhZ5j+JAc+qjPK+a+dEL4a9A01MD4Xi5499QzSbdAU5X30J8ir346Cz3eWwX7sO4B8jEjFefgglPsysXjPyuVO8x+2iNMPqUhvsNAf0m5vHYT69MhFwMevF4Dzvn04HzkCebpYdBz+Jwf1h8mNzeFqzCniPJTj0IGoX00i8Fp8V+RrdAZm6Hy1Q0ZX6XTJ/tQWM7dK4U8JtN6AdJh+pAbIgYOww82jRL0cCL5O1jIu5JT1bzu/YnM6p10+yb88O60/KP9VYs2JtCeRfptY4JcnZlQkJYG/Gzyot+w+2QOmT0jOK6H3yP5t24H4H3vC1YLThaIe9UwFPyOH5X3DaftWdNQ+lIzwbC0CknfmV0Ry2roD8sG+VTYdKP8yyoX01p8/QT484tOikychB16v60JOdcNgF5+aYGnvaIBgQwbKdUBNZSfcLkZbOuP9oUK/OsCX+Loz0M+j+/FCr9j7bcDv07eQv8nZsMfJArd+PVDOSamwD3t2h73FSY4of7YV13Pnw+4eDMDVBLO+1AhoBCqCgBzZkFOY5Iiq+oZNRIqRpiti0YN0cJcceQoYEbNgQo74yfQsgqmRKrseqg7RnOqxVSOCOzAC1iRSLdoR3OtBh5ZT0cx4Bh2ReEHFRyPfDYVjUdHYQv+ezCf4ZPteSr4v4Vtsn1tfXdNI+gti25J2sapc6Jua1m0gh6PSIV/McJgOGd502/El4o2Kki8gvX27ZA+pui9GWCC/rmh1n0aC/e+r+xS+fn0p5/JbQlm/ZLiKnlX5y29MTRHJkRDkY0qa6bHjSzlSBFwaipkKrN5041RqhN0mRlmPJX6y3sp4bV6vtsfQZ9vVth+4Lucbc4ecQc7Cw1EerEPG4SH1pV1wJQ8V1AehLh9zuZr1gF1+gn3uVN/IeKX8yWunZ/mend2o6vyr8rqcr8+au0rqF6f5kOGU3JAetpfzkKVbQbst+TafZT0JVi/JeBQOFaw/Mh7zWeFFq9S7KNfcXzHLh/k987WKh/hrEThzzfxCBa+lfAf7uqwPEn8pj6Gyd8Hy4zQ8/Ie/erDK8Zh0Ze/EN724vtGDRa9emyXjxXtsZp8+NAIaAUsEwiyfVNEDOFodOyH6VZ+UZHM6t4ZabbKK0tXRnl0ISAOGkYmDYkT+TTEVlPVYUw90AzEF3NMOI/V9H5aLTFUVGjBUxSXoee5yLab4rFtfVemFKl40pNjqhTSCPWY8eoJZPwBN0bq/Fxa1YFOn9VEuAmjY796Fka2hw/CN85JF5b6kH2oEqhgB2QA3Lub0+suYKVLbjRH8/4htbuZnh5qN05VuqPOh49MIlIUAGpps2zayk23dGMlla2LQyPOBIsyU+0scZliwRf7oWOktKy59TyOgETgVgZqnXlbdlRwBgOPbKxkO3A5f2LucmkQU7uMUODWv6jjSMf+eESj8iRObokhTd2e/igZp7ZqYChkr9hX98Ti+dRv7zypvmFKPKVuciQzVwWMwTJFNMFV1wzpMLS+16vIZBj5wZEzR1NsWjTCVatJELHqyy3eGsXvGsaO2haBvuo6KfV0j6gHXgnxMaQucMn7GZUQzdFYiUHiC02+/YQppy/boiFqZi9Vk2XZXVXScrnSrKDs6Wo3AKQhAvy9fhim+e35Ew7RtDL61rnceOoBmZaFhuunTU17WFxoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEdAIaAQ0AhoBjYBGQCOgEagSBP4fYiTUTqgtkWIAAAAASUVORK5CYII="}}},{"cell_type":"markdown","source":"# COMPETITION SUBMISSION","metadata":{}},{"cell_type":"code","source":"import zipfile\nfrom PIL import Image\nfrom tqdm import tqdm\nimport io\n\nphoto_dir = \"/kaggle/input/gan-getting-started/photo_jpg/\"\ntest_dataset = CustomImageDataset(root=photo_dir, class_idx=0, transform=data_transform)\n# Make sure batch size and num_works are consistent with what the network was trained on\nphoto_dataloader = DataLoader(test_dataset, batch_size=16, shuffle=False, num_workers=2)\n\n# Set the device\ndevice = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n\n# Output zip file path\nzip_filename = '/kaggle/working/images.zip'\n\ndef generate_monet_images(photo_dataloader, generator, num_images=7000):\n    \"\"\"\n    Generate Monet-style images from photos and save directly to a zip file.\n    \n    Args:\n        photo_dataloader: DataLoader containing photo images\n        generator: Trained generator model\n        num_images: Number of images to generate (default: 7000)\n    \"\"\"\n    generator.eval()  # Set generator to evaluation mode\n    \n    count = 0\n    with zipfile.ZipFile(zip_filename, 'w', compression=zipfile.ZIP_DEFLATED) as zipf:\n        with torch.no_grad():  # Disable gradient calculation \n            for batch in tqdm(photo_dataloader, desc=\"Generating images\"):\n                # Move input to device\n                real_photos = batch[0].to(device)\n                \n                # Generate fake Monet images\n                fake_monets = generator(real_photos)\n                \n                # Process each image in the batch\n                for fake_monet in fake_monets:\n                    if count >= num_images:\n                        break\n                    \n                    # Denormalize from [-1, 1] to [0, 1]\n                    fake_monet = (fake_monet * 0.5 + 0.5).cpu()\n                    \n                    # Convert to numpy array in uint8 format \n                    img_array = (fake_monet.permute(1, 2, 0).numpy() * 255).astype(np.uint8)\n                    \n                    # Create PIL image\n                    img = Image.fromarray(img_array)\n                    \n                    # Save image to zip file \n                    img_byte_arr = io.BytesIO()\n                    img.save(img_byte_arr, format='JPEG', quality=95)\n                    zipf.writestr(f'monet_{count:04d}.jpg', img_byte_arr.getvalue())\n                    \n                    count += 1\n                    if count >= num_images:\n                        break\n    \n    print(f\"Generated and zipped {count} Monet-style images.\")\n    return count\n\n# Generate 7,000 Monet-style images\nnum_generated = generate_monet_images(photo_dataloader, generator, num_images=7000)\nprint(f\"Submission file created: {zip_filename}\")\nprint(f\"Total images zipped: {num_generated}\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-05T23:24:10.737118Z","iopub.execute_input":"2025-05-05T23:24:10.737391Z","iopub.status.idle":"2025-05-05T23:25:10.007500Z","shell.execute_reply.started":"2025-05-05T23:24:10.737373Z","shell.execute_reply":"2025-05-05T23:25:10.006663Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## Generated Images ","metadata":{}},{"cell_type":"code","source":"def show_generated_images(images, num_images=5):\n    # Denormalize images\n    images = (images * 0.5) + 0.5\n    images = images.clamp(0, 1)\n\n    num_images = min(num_images, images.size(0))\n    plt.figure(figsize=(3 * num_images, 3))\n    \n    for i in range(num_images):\n        plt.subplot(1, num_images, i + 1)\n        plt.imshow(transforms.ToPILImage()(images[i].cpu()))\n        plt.axis('off')\n    \n    plt.tight_layout()\n    plt.show()\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-05T23:25:57.840627Z","iopub.execute_input":"2025-05-05T23:25:57.840921Z","iopub.status.idle":"2025-05-05T23:25:57.846412Z","shell.execute_reply.started":"2025-05-05T23:25:57.840896Z","shell.execute_reply":"2025-05-05T23:25:57.845695Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"# Sample batch of photos\nphotos = next(iter(photo_dataloader))[0].to(device)\n\nwith torch.no_grad():\n    fake_monet = generator(photos)\n\nshow_generated_images(fake_monet, num_images=6)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-05T23:26:06.821061Z","iopub.execute_input":"2025-05-05T23:26:06.821765Z","iopub.status.idle":"2025-05-05T23:26:07.667031Z","shell.execute_reply.started":"2025-05-05T23:26:06.821738Z","shell.execute_reply":"2025-05-05T23:26:07.666149Z"}},"outputs":[],"execution_count":null}]}