Contrastive_Multimodal_Learning.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/gpfs/home/zli288/my_cool_science/lib/python3.9/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n",
      "/gpfs/home/zli288/my_cool_science/lib/python3.9/site-packages/umap/distances.py:1063: NumbaDeprecationWarning: The 'nopython' keyword argument was not supplied to the 'numba.jit' decorator. The implicit default value for this argument is currently False, but it will be changed to True in Numba 0.59.0. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\n",
      "  @numba.jit()\n",
      "/gpfs/home/zli288/my_cool_science/lib/python3.9/site-packages/umap/distances.py:1071: NumbaDeprecationWarning: The 'nopython' keyword argument was not supplied to the 'numba.jit' decorator. The implicit default value for this argument is currently False, but it will be changed to True in Numba 0.59.0. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\n",
      "  @numba.jit()\n",
      "/gpfs/home/zli288/my_cool_science/lib/python3.9/site-packages/umap/distances.py:1086: NumbaDeprecationWarning: The 'nopython' keyword argument was not supplied to the 'numba.jit' decorator. The implicit default value for this argument is currently False, but it will be changed to True in Numba 0.59.0. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\n",
      "  @numba.jit()\n",
      "/gpfs/home/zli288/my_cool_science/lib/python3.9/site-packages/umap/umap_.py:660: NumbaDeprecationWarning: The 'nopython' keyword argument was not supplied to the 'numba.jit' decorator. The implicit default value for this argument is currently False, but it will be changed to True in Numba 0.59.0. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\n",
      "  @numba.jit()\n",
      "2023-09-11 01:32:59.128158: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 AVX512F AVX512_VNNI FMA\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
      "2023-09-11 01:32:59.346495: I tensorflow/core/util/util.cc:169] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
      "2023-09-11 01:32:59.353672: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /gpfs/runtime/opt/python/3.9.0/lib\n",
      "2023-09-11 01:32:59.353692: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.\n",
      "2023-09-11 01:32:59.388374: E tensorflow/stream_executor/cuda/cuda_blas.cc:2981] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
      "2023-09-11 01:33:03.563555: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /gpfs/runtime/opt/python/3.9.0/lib\n",
      "2023-09-11 01:33:03.564715: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /gpfs/runtime/opt/python/3.9.0/lib\n",
      "2023-09-11 01:33:03.564725: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from tifffile import imread\n",
    "import matplotlib.pyplot as plt\n",
    "import torch \n",
    "from torch.utils.data import DataLoader\n",
    "import tqdm\n",
    "import clip\n",
    "from PIL import Image\n",
    "from torch.utils.data import DataLoader\n",
    "from torch.utils.data import Dataset\n",
    "import torch.optim as optim\n",
    "import torch.nn as nn\n",
    "from sklearn.metrics import f1_score\n",
    "import umap\n",
    "from sklearn.metrics import f1_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"Kather_train.csv\", index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'An H&E image patch of adipose tissue.',\n",
       " 'An H&E image patch of background.',\n",
       " 'An H&E image patch of cancer-associated stroma.',\n",
       " 'An H&E image patch of colorectal adenocarcinoma epithelium.',\n",
       " 'An H&E image patch of debris.',\n",
       " 'An H&E image patch of lymphocytes.',\n",
       " 'An H&E image patch of mucus.',\n",
       " 'An H&E image patch of normal colon mucosa.',\n",
       " 'An H&E image patch of smooth muscle.'}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "set(df['caption'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'ADI', 'BACK', 'DEB', 'LYM', 'MUC', 'MUS', 'NORM', 'STR', 'TUM'}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "set(df['label'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ADI: 10407 images\n",
      "BACK: 10566 images\n",
      "DEB: 11512 images\n",
      "LYM: 11557 images\n",
      "MUC: 8896 images\n",
      "MUS: 13536 images\n",
      "NORM: 8763 images\n",
      "STR: 10446 images\n",
      "TUM: 14317 images\n"
     ]
    }
   ],
   "source": [
    "root_folder = \"NCT-CRC-HE-100K\" \n",
    "\n",
    "for sub_folder in os.listdir(root_folder):\n",
    "    sub_folder_path = os.path.join(root_folder, sub_folder)\n",
    "    \n",
    "    if os.path.isdir(sub_folder_path):  \n",
    "        # Count the number of '.tif' images in the sub-folder\n",
    "        num_images = len([f for f in os.listdir(sub_folder_path) if os.path.isfile(os.path.join(sub_folder_path, f)) and f.endswith(\".tif\")])\n",
    "        \n",
    "        print(f\"{sub_folder}: {num_images} images\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "texts = [\"An H&E image patch of adipose tissue.\" for _ in range(10407)]\n",
    "texts.extend([\"An H&E image patch of background.\" for _ in range(10566)])\n",
    "texts.extend([\"An H&E image patch of cancer-associated stroma.\" for _ in range(11512)])\n",
    "texts.extend([\"An H&E image patch of colorectal adenocarcinoma epithelium.\" for _ in range(11557)])\n",
    "texts.extend([\"An H&E image patch of debris.\" for _ in range(8896)])\n",
    "texts.extend([\"An H&E image patch of lymphocytes.\" for _ in range(13536)])\n",
    "texts.extend([\"An H&E image patch of mucus.\" for _ in range(8763)])\n",
    "texts.extend([\"An H&E image patch of normal colon mucosa.\" for _ in range(10446)])\n",
    "texts.extend([\"An H&E image patch of smooth muscle.\" for _ in range(14317)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['An H&E image patch of smooth muscle.', 'An H&E image patch of smooth muscle.', 'An H&E image patch of smooth muscle.', 'An H&E image patch of smooth muscle.', 'An H&E image patch of smooth muscle.', 'An H&E image patch of smooth muscle.', 'An H&E image patch of smooth muscle.', 'An H&E image patch of smooth muscle.', 'An H&E image patch of smooth muscle.', 'An H&E image patch of smooth muscle.']\n",
      "100000\n"
     ]
    }
   ],
   "source": [
    "print(texts[90000:90010])\n",
    "print(len(texts))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded 100000 images.\n"
     ]
    }
   ],
   "source": [
    "root_dir = \"NCT-CRC-HE-100K\"\n",
    "subfolders = [d for d in os.listdir(root_dir) if os.path.isdir(os.path.join(root_dir, d))]\n",
    "\n",
    "tif_files = []\n",
    "\n",
    "# Sort subfolders to ensure consistent order\n",
    "for subfolder in sorted(subfolders):\n",
    "    subfolder_path = os.path.join(root_dir, subfolder)\n",
    "    \n",
    "    # Fetch and sort filenames in the current subfolder\n",
    "    for filename in sorted([f for f in os.listdir(subfolder_path) if f.endswith('.tif')]):\n",
    "        tif_files.append(os.path.join(subfolder_path, filename))\n",
    "\n",
    "# Use Image.open() to load images and store them as PIL Images in a list\n",
    "image_list = []\n",
    "for tif_file in tif_files:\n",
    "    with Image.open(tif_file).convert('RGB') as img:\n",
    "        image_list.append(img.copy())\n",
    "\n",
    "# Print the number of loaded images\n",
    "print(f\"Loaded {len(image_list)} images.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=224x224>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image_list[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "model, preprocess = clip.load(\"ViT-B/32\", device=device, jit=False)  # Must set jit=False for training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "processed_images = []\n",
    "for img in image_list:\n",
    "    processed_img = preprocess(img)\n",
    "    processed_images.append(processed_img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100000"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(processed_images)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataloader_images = DataLoader(processed_images, batch_size=100, shuffle=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1000/1000 [01:23<00:00, 11.98it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(100000, 512)\n"
     ]
    }
   ],
   "source": [
    "image_embeddings_initial = []\n",
    "                      \n",
    "total = len(processed_images) // 100\n",
    "pbar = tqdm.tqdm(total=total, position=0)\n",
    "with torch.no_grad():\n",
    "    for images in dataloader_images:\n",
    "        images = images.to(device)\n",
    "        image_embeddings_initial.extend(model.encode_image(images).detach().cpu().numpy())\n",
    "        pbar.update(1)\n",
    "    pbar.close()\n",
    "image_embeddings_initial = np.array(image_embeddings_initial)\n",
    "print(image_embeddings_initial.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataloader_texts = DataLoader(texts, batch_size = 100, shuffle=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1000/1000 [00:42<00:00, 23.68it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(100000, 512)\n"
     ]
    }
   ],
   "source": [
    "text_embeddings_initial = []\n",
    "total = len(texts) // 100\n",
    "\n",
    "pbar = tqdm.tqdm(total=total, position=0)\n",
    "with torch.no_grad():\n",
    "    for captions in dataloader_texts:\n",
    "        idx = clip.tokenize(captions, truncate=True).to(device)\n",
    "        text_embeddings_initial.extend(model.encode_text(idx).detach().cpu().numpy())\n",
    "\n",
    "        pbar.update(1)\n",
    "\n",
    "    pbar.close()\n",
    "\n",
    "text_embeddings_initial = np.array(text_embeddings_initial)\n",
    "print(text_embeddings_initial.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(100000, 512)\n",
      "(100000, 512)\n"
     ]
    }
   ],
   "source": [
    "image_embeddings_initial_norm = image_embeddings_initial / np.linalg.norm(image_embeddings_initial, axis=1, keepdims=True)\n",
    "text_embeddings_initial_norm = text_embeddings_initial / np.linalg.norm(text_embeddings_initial, axis=1, keepdims=True)\n",
    "print(image_embeddings_initial_norm.shape)\n",
    "print(text_embeddings_initial_norm.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(100000, 3)\n",
      "(100000, 3)\n"
     ]
    }
   ],
   "source": [
    "reducer = umap.UMAP(n_components=3, random_state=0)\n",
    "embeddings_images = reducer.fit_transform(image_embeddings_initial_norm)\n",
    "embeddings_texts = reducer.fit_transform(text_embeddings_initial_norm)\n",
    "print(embeddings_texts.shape)\n",
    "print(embeddings_images.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10, 8))\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "ax.scatter(embeddings_images[:, 0], embeddings_images[:, 1], embeddings_images[:, 2], color='b', label='Image Embeddings')\n",
    "ax.scatter(embeddings_texts[:, 0], embeddings_texts[:, 1], embeddings_texts[:, 2], color='r', label='Text Embeddings')\n",
    "ax.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 275,
   "metadata": {},
   "outputs": [],
   "source": [
    "class ContrastiveDataset(Dataset):\n",
    "    def __init__(self, image_embeddings, text_embeddings):\n",
    "        self.image_embeddings = image_embeddings\n",
    "        self.text_embeddings = text_embeddings\n",
    "        assert len(self.image_embeddings) == len(self.text_embeddings), \"Mismatched embeddings lengths!\"\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.image_embeddings)\n",
    "\n",
    "    def __getitem__(self, idx):\n",
    "        return self.image_embeddings[idx], self.text_embeddings[idx]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 276,
   "metadata": {},
   "outputs": [],
   "source": [
    "batch_size = 100\n",
    "model, preprocess = clip.load(\"ViT-B/32\", device=device, jit=False)  # Must set jit=False for training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 277,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1000\n",
      "20000\n"
     ]
    }
   ],
   "source": [
    "train_dataset = ContrastiveDataset(processed_images, texts)\n",
    "train_dataloader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True)\n",
    "num_batches_per_epoch = len(train_dataloader)\n",
    "print(num_batches_per_epoch)\n",
    "total_steps = len(train_dataloader) * epochs\n",
    "print(total_steps)\n",
    "optimizer = optim.AdamW(model.parameters(), lr=5e-5, weight_decay = 0.0001)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 278,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(tensor([[[ 0.9084,  0.8647,  0.9960,  ...,  1.4486,  1.4486,  1.4632],\n",
       "          [ 1.0252,  0.8647,  0.9668,  ...,  1.3026,  1.4340,  1.4194],\n",
       "          [ 1.2150,  0.9668,  0.9814,  ...,  1.4632,  1.5216,  1.5654],\n",
       "          ...,\n",
       "          [ 1.6384,  1.6384,  1.6384,  ...,  1.6384,  1.6384,  1.6092],\n",
       "          [ 1.6384,  1.6384,  1.6384,  ...,  1.6384,  1.6384,  1.6092],\n",
       "          [ 1.6384,  1.6384,  1.6384,  ...,  1.6384,  1.6384,  1.6092]],\n",
       " \n",
       "         [[ 0.1089, -0.0112,  0.0488,  ...,  1.0243,  1.1294,  1.1744],\n",
       "          [ 0.2289,  0.0939,  0.1689,  ...,  0.9793,  1.1744,  1.2495],\n",
       "          [ 0.4841,  0.3190,  0.2740,  ...,  1.1894,  1.3395,  1.3845],\n",
       "          ...,\n",
       "          [ 1.5946,  1.5646,  1.5496,  ...,  1.5946,  1.5946,  1.5946],\n",
       "          [ 1.5946,  1.5646,  1.5496,  ...,  1.5946,  1.5946,  1.5946],\n",
       "          [ 1.5946,  1.5646,  1.5496,  ...,  1.5946,  1.5946,  1.5946]],\n",
       " \n",
       "         [[ 0.9799,  0.8945,  0.9656,  ...,  1.5913,  1.6624,  1.6766],\n",
       "          [ 1.0510,  0.9941,  1.0510,  ...,  1.5913,  1.7193,  1.6766],\n",
       "          [ 1.2358,  1.1363,  1.1363,  ...,  1.6909,  1.7193,  1.8188],\n",
       "          ...,\n",
       "          [ 1.8188,  1.8331,  1.8331,  ...,  1.8188,  1.8188,  1.8615],\n",
       "          [ 1.8188,  1.8331,  1.8331,  ...,  1.8188,  1.8188,  1.8615],\n",
       "          [ 1.8188,  1.8331,  1.8331,  ...,  1.8188,  1.8188,  1.8615]]]),\n",
       " 'An H&E image patch of adipose tissue.')"
      ]
     },
     "execution_count": 278,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_dataset[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 279,
   "metadata": {},
   "outputs": [],
   "source": [
    "loss_img = nn.CrossEntropyLoss()\n",
    "loss_txt = nn.CrossEntropyLoss()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "metadata": {},
   "outputs": [],
   "source": [
    "def convert_models_to_fp32(model):\n",
    "    for p in model.parameters():\n",
    "        p.data = p.data.float()\n",
    "        p.grad.data = p.grad.data.float()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 281,
   "metadata": {},
   "outputs": [],
   "source": [
    "def assign_learning_rate(optimizer, new_lr):\n",
    "    for param_group in optimizer.param_groups:\n",
    "        param_group[\"lr\"] = new_lr\n",
    "\n",
    "\n",
    "def _warmup_lr(base_lr, warmup_length, step):\n",
    "    return base_lr * (step + 1) / warmup_length\n",
    "\n",
    "\n",
    "def cosine_lr(optimizer, base_lr, warmup_length, steps):\n",
    "    def _lr_adjuster(step):\n",
    "        if step < warmup_length:\n",
    "            lr = _warmup_lr(base_lr, warmup_length, step)\n",
    "        else:\n",
    "            e = step - warmup_length\n",
    "            es = steps - warmup_length\n",
    "            lr = 0.5 * (1 + np.cos(np.pi * e / es)) * base_lr\n",
    "        assign_learning_rate(optimizer, lr)\n",
    "        return lr\n",
    "    return _lr_adjuster\n",
    "\n",
    "# lr_scheduler = cosine_lr(optimizer, base_lr=0.01, warmup_length=5, steps=100)\n",
    "# current_lr = lr_scheduler(3)  # This is effectively calling _lr_adjuster(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "metadata": {},
   "outputs": [],
   "source": [
    "scheduler = cosine_lr(optimizer, 5e-5, 300, total_steps)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 283,
   "metadata": {},
   "outputs": [],
   "source": [
    "current_directory = os.getcwd() \n",
    "checkpoint_dir = os.path.join(current_directory, 'checkpoints')\n",
    "if not os.path.exists(checkpoint_dir):\n",
    "    os.makedirs(checkpoint_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 287,
   "metadata": {},
   "outputs": [],
   "source": [
    "# loading the checkpoint \n",
    "checkpoint_files = [os.path.join(checkpoint_dir, f) for f in os.listdir(checkpoint_dir) if f.endswith('.pth')]\n",
    "latest_checkpoint = max(checkpoint_files, key=os.path.getmtime) if checkpoint_files else None\n",
    "# returns the last modification time of that file\n",
    "\n",
    "if latest_checkpoint:  # check if latest_checkpoint is not None\n",
    "    latest_checkpoint_path = os.path.join(checkpoint_dir, latest_checkpoint)\n",
    "    if os.path.exists(latest_checkpoint_path):\n",
    "        checkpoint = torch.load(latest_checkpoint_path)\n",
    "        model.load_state_dict(checkpoint['model_state_dict'])\n",
    "        optimizer.load_state_dict(checkpoint['optimizer_state_dict'])\n",
    "        start_epoch = checkpoint['epoch'] + 1\n",
    "        training_losses = checkpoint['training_losses']\n",
    "else:\n",
    "    start_epoch = 0 \n",
    "    training_losses = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 288,
   "metadata": {},
   "outputs": [],
   "source": [
    "# training_losses = []\n",
    "\n",
    "epochs = 20\n",
    "\n",
    "for epoch in range(start_epoch, epochs):\n",
    "    train_loss_this_epoch = 0\n",
    "    \n",
    "    for i, batch in enumerate(tqdm.tqdm(train_dataloader, desc=f\"{epoch}/{epochs}\", position=0)):\n",
    "        optimizer.zero_grad()\n",
    "        \n",
    "        step = num_batches_per_epoch * epoch + i\n",
    "        scheduler(step)\n",
    "        \n",
    "        images_batch, texts_batch = batch\n",
    "        images_batch = images_batch.to(device)\n",
    "        texts_new = clip.tokenize(texts_batch, truncate=True).to(device)\n",
    "        \n",
    "        images_embeddings = model.encode_image(images_batch)\n",
    "        texts_embeddings = model.encode_text(texts_new)\n",
    "        \n",
    "        images_embeddings_norm = images_embeddings / images_embeddings.norm(dim=1, keepdim=True)\n",
    "        texts_embeddings_norm = texts_embeddings / texts_embeddings.norm(dim=1, keepdim=True)\n",
    "        \n",
    "        \n",
    "        logit_scale = model.logit_scale.exp()\n",
    "        # print(logit_scale) # tensor(100., device='cuda:0', grad_fn=<ExpBackward>)\n",
    "        \n",
    "        logits_per_image = logit_scale * images_embeddings_norm @ texts_embeddings_norm.t() # cosine similarity\n",
    "        # (batch_size, embedding_dim) @ (embedding_dim, batch_size) = (batch_size, batch_size)\n",
    "        # each row corresponds to an image\n",
    "        logits_per_text = logits_per_image.t()\n",
    "        # each row corresponds to a text\n",
    "        \n",
    "        # logits_per_image, logits_per_text = model(images_batch, texts_new)\n",
    "\n",
    "        ground_truth = torch.arange(len(images_batch), dtype=torch.long, device=device)\n",
    "        total_loss = (loss_img(logits_per_image, ground_truth) + loss_txt(logits_per_text, ground_truth)) / 2\n",
    "        \n",
    "        total_loss.backward()\n",
    "        train_loss_this_epoch += total_loss.detach().cpu().numpy() \n",
    "        # using .item() is more memory efficient for scalars comparing to .numpy()\n",
    "        \n",
    "        # new_lr = scheduler(step)\n",
    "        # print(f'[Train - this batch] epoch: {epoch}, batch: {i}, new learning rate: {new_lr}')\n",
    "        \n",
    "        convert_models_to_fp32(model)\n",
    "        optimizer.step()\n",
    "        clip.model.convert_weights(model)\n",
    "        \n",
    "    print(f\"train_loss_this_epoch is: {train_loss_this_epoch}\")\n",
    "    training_losses.append(train_loss_this_epoch)\n",
    "    \n",
    "    checkpoint_path = os.path.join(checkpoint_dir, f\"model_epoch_{epoch}.pth\")\n",
    "    torch.save({\n",
    "        'epoch': epoch,\n",
    "        'model_state_dict': model.state_dict(),\n",
    "        'optimizer_state_dict': optimizer.state_dict(),\n",
    "        'loss': total_loss,\n",
    "        'training_losses': training_losses\n",
    "    }, checkpoint_path)\n",
    "    \n",
    "    # Deleting previous checkpoints\n",
    "    if epoch > 0:\n",
    "        previous_checkpoint_path = os.path.join(checkpoint_dir, f\"model_epoch_{epoch - 1}.pth\")\n",
    "        if os.path.exists(previous_checkpoint_path):\n",
    "            os.remove(previous_checkpoint_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 291,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  8%|▊         | 777/10000 [02:10<25:48,  5.96it/s]\n",
      "100%|██████████| 1000/1000 [01:48<00:00,  9.18it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(100000, 512)\n"
     ]
    }
   ],
   "source": [
    "image_embeddings_trained = []\n",
    "                      \n",
    "total = len(processed_images) // 100\n",
    "pbar = tqdm.tqdm(total=total, position=0)\n",
    "with torch.no_grad():\n",
    "    for images in dataloader_images:\n",
    "        images = images.to(device)\n",
    "        image_embeddings_trained.extend(model.encode_image(images).detach().cpu().numpy())\n",
    "        pbar.update(1)\n",
    "    pbar.close()\n",
    "image_embeddings_trained = np.array(image_embeddings_trained)\n",
    "print(image_embeddings_trained.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 292,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1000/1000 [00:42<00:00, 23.62it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(100000, 512)\n"
     ]
    }
   ],
   "source": [
    "text_embeddings_trained = []\n",
    "\n",
    "total = len(texts) // 100\n",
    "pbar = tqdm.tqdm(total=total, position=0)\n",
    "with torch.no_grad():\n",
    "    for captions in dataloader_texts:\n",
    "        idx = clip.tokenize(captions, truncate=True).to(device)\n",
    "        text_embeddings_trained.extend(model.encode_text(idx).detach().cpu().numpy())\n",
    "\n",
    "        pbar.update(1)\n",
    "\n",
    "    pbar.close()\n",
    "\n",
    "text_embeddings_trained = np.array(text_embeddings_trained)\n",
    "print(text_embeddings_trained.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 293,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(100000, 512)\n",
      "(100000, 512)\n"
     ]
    }
   ],
   "source": [
    "image_embeddings_trained_norm = image_embeddings_trained / np.linalg.norm(image_embeddings_trained, axis=1, keepdims=True)\n",
    "text_embeddings_trained_norm = text_embeddings_trained / np.linalg.norm(text_embeddings_trained, axis=1, keepdims=True)\n",
    "print(image_embeddings_trained_norm.shape)\n",
    "print(text_embeddings_trained_norm.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 294,
   "metadata": {},
   "outputs": [],
   "source": [
    "reducer = umap.UMAP(n_components=3, random_state=0)\n",
    "embeddings_images_trained = reducer.fit_transform(image_embeddings_trained_norm)\n",
    "embeddings_texts_trained = reducer.fit_transform(text_embeddings_trained_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 295,
   "metadata": {},
   "outputs": [],
   "source": [
    "unique_texts = set(df['caption'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 296,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ee+/hX//6F2bOnIkff/zRp89KQgghka29vd1lXJGYmOhxf2+/24L9ne4Lb/qW//nPf7Bo0SIUFhbi4YcfhtFoxPPPP49jjz0WO3bsEILLwRpnbt26FR9//LHQH1u3bh1OP/103HbbbVi/fj2uv/56GAwGPPLII7jiiivw/fffC3+7efNmGI1GXHfddUhISMAff/yBZ555Bvv27cPmzZuF/T777DMsXLgQEydOxLp162AwGHDllVciIyPDpT3+nL9vvvkGNTU1uPzyy5GamiqUMiwrK8Nvv/3mkizmTX/H37Fhb7w59yeccAKuv/56rFu3DgsWLMCUKVPQ2NiIZcuWYd68ebj22muFx3Iu+5qTk9NnG4xGo9vxvV6vF83orKqqwsUXX4wlS5bg0ksvxWOPPYYzzjgDL7zwAu68805cf/31AI5cPxdccAEqKipEsyHtdjtOOeUUzJw5E4888gi+/PJLrF69GjabDffee6+wn7fnf9WqVbj//vtx2mmn4bTTTsPff/+Nk08+GRaLRXQcBw8exPHHHw+bzSb0wV966SWfZsY+9NBDkEqlWLFiBdrb2/HII4/gkksuwe+//y7s8/zzz+OGG27Acccdh5tvvhl79+7FggULEBcXJ3qPvvzyy7jxxhtx3nnn4aabboLJZEJJSQl+//13XHzxxX22RSaT4e6778Zll13WZ/Y5/zpOmzYN69atQ1NTE5566ils27YNO3bsgF6vF/a12WwoLCzEsccei8ceewxKpVL4nT+fEYSIsCFow4YNDADbvn27sG3RokUMAHvwwQeFbQaDgSkUCiaRSNg777wjbN+9ezcDwFavXi1sM5lMzG63i56ntraWxcTEsHvvvVfY9vjjjzMA7KOPPhK29fT0sLFjxzIA7IcffmCMMcZxHBs9ejQrLCxkHMcJ+xqNRjZixAh20kkn9XqMNpuNmc1m0TaDwcBSUlLYFVdcIWojAJaQkMBaW1uF7f/73/8YAPbJJ58I2yZNmsTS0tJYW1ubsO3rr79mAFhWVlav7XGmUqnYokWLhJ+vvPJKlpaWxg4fPiza78ILL2Q6nY4ZjUZh2x133MGkUin76aef2ObNmxkA9uSTT4r+bunSpcyXy3fOnDkMgNt/S5YsEfZbvXo1A8CuueYaYZvNZmPDhg1jEomEPfTQQ8J2/vpxPM4ffviBAWAZGRmso6ND2P7ee+8xAOypp55ijPl2/hcsWMBiY2NZXV2dsG3Xrl1MJpOJXoOioiIGgF1//fWiY7/44otdrmf+PVJbWytsy8rKYgDYTz/9JGw7dOgQi4mJYbfccouwbdmyZUwikbAdO3YI21paWlh8fLzoMf/73/+6vA+9NWfOHDZ+/HjGGGNr165lANhff/3FGPvnmn700UeF/ZcvX84AsK1btwrbOjs72YgRI1h2drbw3uXPz8iRI0XXHGP+f0a4w1+/u3btYowx9vHHH7OYmBh25plnsoULFwr7HXXUUezss88WfnZ3fsaPH8/mzJnj8hz8vvPmzRNdSzfffDOTyWTC+/nQoUMsOjqanXzyyaLPsmeffZYBYK+99pqwLSsrS3Rd8+bMmSNqw/bt2xkAtmHDhl5fB8YYa29vZwDYWWed1ee+jP1zPV911VWi7StWrGAA2Pfffy9qrzfXLn8++M9hR/xjfPnlly6/c75WGGOssLCQjRw5UvjZm+u9ubnZ43XDf/bwKioqGAD2zDPPiPa7/vrrmVqtFtq0detWBoC9+eabov2+/PJLt9s9PW9zc7PHfU488UQ2ceJEZjKZhG0cx7H8/Hw2evRoYZu335PevA8d92eMscmTJ7OpU6eKtjm/lvyxOH4HMsbY2WefzRISEoSf//rrLwaALV++XLTf4sWLvXpfE0IIiVx8v8vdP8b+6ac69o28/W7z9zvd0fz5813Gb56+45z7fd72LTs7O5ler2dXX3216PEOHjzIdDqdaLu/40zHsYHj8cTExIj6yy+++CIDwFJTU0VjsTvuuMOlb+2uf7du3TomkUhE466JEyeyYcOGsc7OTmHbli1bXNru7/lz1563337bpY/rbX/Hl7FhX5z70L6c++7ubjZq1Cg2fvx4ZjKZ2Pz585lWqxW9xoy5xg96w7/PPP379ddfhX35Pv4vv/wibPvqq68YAKZQKETt4K8fx7EC//5dtmyZsI3jODZ//nwWHR0t9KG9Pf/8mGz+/Pmi99edd97JAIheA36M+/vvvwvbDh06xHQ6ncv17DxO4/vbeXl5orjRU089xQCw0tJSxhhjZrOZJSQksGnTpjGr1Srst3HjRgZA9JhnnXWWy/vQG47jd5vNxkaPHs2OPvpo4fidxyMWi4UlJyezCRMmsJ6eHuFxPv30UwaArVq1StjGn5/bb7/d5Xn9/YwgxFHElG3hOS58odfrkZubC5VKhQsuuEDYnpubC71ej5qaGmFbTEyMcPfRbrejpaUFarUaubm5opISX375JTIyMnDmmWcK22JjY3H11VeL2lFUVITKykpcfPHFaGlpweHDh3H48GF0d3fjxBNPxE8//eR2Og5PJpMJWXocx6G1tRU2mw3HHHOM2xIXCxcuRFxcnPAznyXKH2NjYyOKioqwaNEi0QKaJ510EsaNG+exHd5gjOGDDz7AGWecAcaYcKyHDx9GYWEh2tvbRW1es2YNxo8fj0WLFuH666/HnDlzcOONN/rVBuDIlK1vvvnG5d/y5ctd9nW8TmQyGY455hgwxnDllVcK2/nrx/E64V122WXQaDTCz+eddx7S0tLw+eefA/D+/Nvtdnz11VdYsGABhg8fLjxeXl4eCgsLRc/JP7bza+Xu+DwZN26ccG0AR7JlnY/xyy+/xKxZs0SzG+Lj44XpUTz+bvCnn34Kq9XqdRuc3XTTTYiLixMWWnTn888/x/Tp03HssccK29RqNa655hrs3bsXu3btEu2/aNEij3fs+/sZ4Q7/Wv70008Ajtz5njZtGk466SRs3boVANDW1oadO3eKXvf+uOaaa0QZKccddxzsdjvq6uoAAN9++y0sFguWL18uyqS4+uqrodVqg15rvKOjAwBE74ve8Nfz//3f/4m233LLLQDg0l5vrt2+jBgxwuV9BUB0rfCZZnPmzEFNTQ3a29sBBO56540ZMwaTJk0SZXfZ7Xa8//77OOOMM4Q2bd68GTqdDieddJLos3Xq1KlQq9VuZz35orW1Fd9//z0uuOACdHZ2Co/f0tKCwsJCVFZWCtMnvf2e5PX2PuQzkXjHHXec1+fS3d+2tLQI1+CXX34JAEKWEW/ZsmVePT4hhBDy3HPPuYwp+tLXd1uwv9N91Vff8ptvvkFbWxsuuugiUXtlMhlmzJghtDeY48wTTzxRVDplxowZAIBzzz1X1Ofktzu+3o59kO7ubhw+fBj5+flgjAmlOw4cOIDS0lJcdtllUKvVwv5z5szBxIkTRW3x9/w5tsdkMuHw4cOYOXMmALjtR/XV3wnE2NATb889ACiVSmzcuBHl5eWYPXs2PvvsMzzxxBOisW1/XXPNNW7H987X1bhx4zBr1izhZ/56OOGEE0TtcHed8G644Qbh//nZ9BaLBd9++y0A788/PyZbtmyZ6P3l7rx8/vnnmDlzpqgiQVJSksu4uzeXX365qB66cxzozz//REtLC66++mpRtv4ll1wiih8BR8Y7+/btc1v+11t89nlxcTE++ugjt/v8+eefOHToEK6//nrRGhLz58/H2LFj3Y5bPc1O9eczghBHEVW2JTY21mWFcZ1Oh2HDhrlMg9LpdKLaVBzH4amnnsL69etRW1srqk+XkJAg/H9dXR1ycnJcHm/UqFGinysrKwEcCR540t7e7vKB5WjTpk14/PHHsXv3blGwxl0ZCecvJ/5x+WPkO0GjR492+VtPgQ9vNTc3o62tDS+99BJeeuklt/scOnRI+P/o6Gi89tprQo1vvpa2v1QqFebNm+fVvs6vl06nQ2xsrMt0TJ1O51KHDnB9HSUSCUaNGiXU0fL2/JvNZvT09Hg8L3ynCDhyDqVSqcsUN770hDfcdWLi4uJE74W6ujpR54PnfI3PmTMH5557LtauXYsnnngCc+fOxYIFC3DxxRe7lHjpjU6nw/Lly7F69Wrs2LHD7Xuirq5O+MJzxJfkqKurw4QJE4Ttnkqt+PMZ4U5KSgpGjx6NrVu3YsmSJdi6dSuOP/54zJ49G8uWLUNNTQ3Ky8vBcZzfwXNv3+PO10N0dDRGjhwp/D5YtFotAKCzs9Or/fnr2fm6Sk1NhV6vd2mvN9duXzxdF9u2bcPq1avx66+/utSSbG9vh06nC9j17mjhwoW48847sX//fmRkZGDLli04dOgQFi5cKOxTWVmJ9vZ2JCcnu30Mx8/W/qiqqgJjDPfccw/uuecej8+RkZHh9fckz5f3oS/nsrf3glarFa4t5+d3vtYIIYQQT6ZPn+5xwVB3vPluC/Z3uq/66lvy45kTTjjB7d/zfb9gjjPdjdkAIDMz0+12x9e7vr4eq1atwscff+zSx+CTI/i2u+sjjBo1StR2f89fa2sr1q5di3feecdlX749jrzt7/gzNvTE23PPKygowHXXXYfnnnsOhYWFXq+B1ZfRo0d7Nb735zoBAKlUipEjR4q2jRkzBgBE43tvzr+n90NSUpLLONfTGNef8b2nMaLzNS6Xy11q+q9cuRLffvstpk+fjlGjRuHkk0/GxRdfjIKCAq/bAxwJzN9333249957sWDBApffexq3AsDYsWPx888/u7TVUwkof889IbyICp7LZDKftjOHRQwefPBB3HPPPbjiiitw3333IT4+HlKpFMuXL+81Q9wT/m8effRRl/rkPMe7287eeOMNLF68GAsWLMCtt96K5ORkyGQyrFu3DtXV1S77e3OMwcIf66WXXuoxWOxc9/err74CcOSue2VlZa91pYPB3esVyNfQ2/PvvDBisAXyGCUSCd5//3389ttv+OSTT/DVV1/hiiuuwOOPP47ffvut1+vbGV/7fO3atXjyySd9boszT9mu/nxGeHLsscfiu+++Q09PD/766y+sWrUKEyZMgF6vx9atW1FeXg61Wo3Jkyd7fwABbqMzTzer7Ha7x+fpi1arRXp6Onbu3BmQtjgLxPG7uy6qq6tx4oknYuzYsfj3v/+NzMxMREdH4/PPP8cTTzwhvJcDeb3zFi5ciDvuuAObN2/G8uXL8d5770Gn0+GUU04R9uE4DsnJyXjzzTfdPobzQN1X/PGtWLHCbVY+8E9n29fvSV/fh94K5fcdIYQQ4o43323B/k73xHnRUl5f36f8d/t//vMf0fosPMcs1mDpb9/dbrfjpJNOQmtrK1auXImxY8dCpVJh//79WLx4cb/H9/6cvwsuuAC//PILbr31VkyaNAlqtRocx+GUU05x255wGN97e+7NZrOwQGd1dTWMRqOoLnWwBWOM5yxU79++BPIY8/LyUFFRgU8//RRffvklPvjgA6xfvx6rVq3qdZa4uzbdfffdWLx4Mf73v//53A5njrNf3T2XL9tpvEA8iajguT/ef/99HH/88Xj11VdF29va2kTZyFlZWdi1axcYY6Kgj/OKxvwdYK1W63U2tHN7Ro4ciQ8//FD0PKtXr/b5sfh2A//cRXZUUVHRr8fk8at72+12r461pKQE9957Ly6//HIUFRXhqquuQmlpqWiaXyAy0YPJ+XVkjKGqqkq4SeDt+U9KSoJCofDqvGRlZYHjOFRXV4vu0vp7/pxlZWW5XaHb3TYAmDlzJmbOnIkHHngAb731Fi655BK88847ovIofeGzz9esWeP2BkxWVpbb49y9e7fw+1A57rjjsGHDBrzzzjuw2+3Iz8+HVCrFscceKwTP8/Pz+xxU+XvN869BRUWFKHPCYrGgtrZWdB3GxcWhra3N5THq6upEf+trm04//XS89NJL+PXXX93OXnBuL8dxqKysFC3q2dTUhLa2tn6d0/68hp988gnMZjM+/vhjUeaCp6m3vV3vvj7/iBEjMH36dLz77ru44YYb8OGHH2LBggWiTPacnBx8++23KCgo8GnxIG/x5zsqKqrPz29vvydDjb+2amtrRVk/nj7DCCGEkIEQ7O90d/07i8WCxsbGfj0eP55JTk7utY8QzHFmf5WWlmLPnj3YtGkTLrvsMmG7c/kdvu3ejH38OX8GgwHfffcd1q5di1WrVgnb3b1m3grm2NDbc89bvXo1ysvL8dhjj2HlypW4/fbb8fTTT4v2CefxPcdxqKmpEbLNAWDPnj0AIGRne3v+Hd8PjuOq5uZml6znrKysoL9vHK/x448/Xthus9mwd+9elyRHlUqFhQsXYuHChbBYLDjnnHPwwAMP4I477hCVWOnLpZdeivvvvx9r164VlTx2bFNFRYXL7IaKioqQju1J5Iq4muf9JZPJXO5Cbd68Waj1yissLMT+/fvx8ccfC9tMJhNefvll0X5Tp05FTk4OHnvsMXR1dbk8X3Nzc5/tAcR3xn7//Xf8+uuv3h2Qk7S0NEyaNAmbNm0STQv75ptvXOpF+0omk+Hcc8/FBx984Dbr1PFYrVYrFi9ejPT0dDz11FPYuHEjmpqacPPNN4v+RqVSAYDbAF84eP3110XlKd5//300Njbi1FNPBeD9+ZfJZCgsLMRHH32E+vp64ffl5eVCdj6Pf2znjkggMrUdFRYW4tdff0VRUZGwrbW11eUuu8FgcHnP8Fn2/cmoX758OfR6vWhFc95pp52GP/74Q3T9d3d346WXXkJ2drbf9RT9wZdjefjhh3HUUUcJN4GOO+44fPfdd/jzzz+9KtmiUqn8ut7nzZuH6OhoPP3006Lz8uqrr6K9vR3z588XtuXk5OC3334Trfj+6aefoqGhwaVNgPfvw9tuuw0qlQpXXXUVmpqaXH5fXV2Np556CsCRcwq4Xr///ve/AUDUXm/153PD3Wdte3s7NmzYINrPm+udz7Dx5fkXLlyI3377Da+99hoOHz4sKtkCHMlSstvtuO+++1z+1maz+f0ZmZycjLlz5+LFF190O7h2/Pz29nsy1PgM+vXr14u2P/PMM6FoDiGEEAIg+N/pOTk5wjo8vJdeeslj5nlfCgsLodVq8eCDD7pd74XvIwRznNlf7vp3jDGhH8pLT0/HhAkT8Prrr4vGbD/++CNKS0tF+/pz/ty1B/BvHBfMsaG35x44EqN47LHHsHz5ctxyyy249dZb8eyzz+LHH38U/Y2/Y51ge/bZZ4X/Z4zh2WefRVRUFE488UQA3p//efPmISoqCs8884zofLs7L6eddhp+++03/PHHH8K25uZmj9nt/XHMMccgISEBL7/8Mmw2m7D9zTffdAnmO5erjY6Oxrhx48AY83nNJz77vKioSBQ749uUnJyMF154QRQ3+OKLL1BeXt6vcSAh/qLMcy+dfvrpQjZ0fn4+SktL8eabb7rUvlqyZAmeffZZXHTRRbjpppuQlpaGN998U7gLx99RlUqleOWVV3Dqqadi/PjxuPzyy5GRkYH9+/fjhx9+gFarxSeffNJrez788EOcffbZmD9/Pmpra/HCCy9g3LhxboOx3li3bh3mz5+PY489FldccQVaW1vxzDPPYPz48f1+TN5DDz2EH374ATNmzMDVV1+NcePGobW1FX///Te+/fZbtLa2AgDuv/9+FBUV4bvvvoNGo8FRRx2FVatW4e6778Z5550nBNSmTp0K4MgCKIWFhZDJZLjwwgt7bUN7ezveeOMNt7+79NJL/To+Z/Hx8Tj22GNx+eWXo6mpCU8++SRGjRolLBzry/lfu3YtvvzySxx33HG4/vrrYbPZhPNSUlIiPOekSZNw0UUXYf369Whvb0d+fj6+++67gGdT3nbbbXjjjTdw0kknYdmyZVCpVHjllVcwfPhwtLa2Ctf4pk2bsH79epx99tnIyclBZ2cnXn75ZWi1WuE8+kKn0+Gmm25yOyXs9ttvx9tvv41TTz0VN954I+Lj47Fp0ybU1tbigw8+8DiNayCMGjUKqampqKioEC1IOHv2bKxcuRIAvAqeT506Fc8//zzuv/9+jBo1CsnJyR7rDLqTlJSEO+64A2vXrsUpp5yCM888ExUVFVi/fj2mTZsmeg9cddVVeP/993HKKafgggsuQHV1Nd544w2Xmok5OTnQ6/V44YUXoNFooFKpMGPGDI9llnJycvDWW29h4cKFyMvLw2WXXYYJEybAYrHgl19+webNm7F48WIAwNFHH41FixbhpZdeQltbG+bMmYM//vgDmzZtwoIFC0SZEd6aNGkSZDIZHn74YbS3tyMmJgYnnHCCx9qEAHDyyScjOjoaZ5xxBpYsWYKuri68/PLLSE5OFgWTvbneFQoFxo0bh3fffRdjxoxBfHw8JkyYIKrH7+yCCy7AihUrsGLFCsTHx7tk98yZMwdLlizBunXrUFRUhJNPPhlRUVGorKzE5s2b8dRTT+G8887r87X597//7TJ9ViqV4s4778Rzzz2HY489FhMnTsTVV1+NkSNHoqmpCb/++iv27duH4uJiAN5/T4ba1KlTce655+LJJ59ES0sLZs6ciR9//FHIIArnzCdCCCFDV6C+0z256qqrcO211+Lcc8/FSSedhOLiYnz11Vf9nh2m1Wrx/PPP41//+hemTJmCCy+8EElJSaivr8dnn32GgoICIeAYzHFmf4wdOxY5OTlYsWIF9u/fD61Wiw8++MBtveMHH3wQZ511FgoKCnD55ZfDYDDg2WefxYQJE0Rt9+f8abVazJ49G4888gisVisyMjLw9ddfo7a2tt/HGMyxobfn3mQyYdGiRRg9ejQeeOABAEfGtp988gkuv/xylJaWCsktU6dOxbfffot///vfSE9Px4gRI9zW+3b0999/ux3f5+Tk9DnL1RexsbH48ssvsWjRIsyYMQNffPEFPvvsM9x5551CORZvz39SUhJWrFiBdevW4fTTT8dpp52GHTt24IsvvnB5L9522234z3/+g1NOOQU33XQTVCoVXnrpJWRlZYniAP6Ijo7GmjVrsGzZMpxwwgm44IILsHfvXmzcuNFlLb+TTz4ZqampKCgoQEpKCsrLy/Hss89i/vz5osU3vcXXPndMygOOzHh9+OGHcfnll2POnDm46KKL0NTUhKeeegrZ2dkuiZWEDAg2BG3YsIEBYNu3bxe2LVq0iKlUKpd958yZw8aPH++yPSsri82fP1/42WQysVtuuYWlpaUxhULBCgoK2K+//srmzJnD5syZI/rbmpoaNn/+fKZQKFhSUhK75ZZb2AcffMAAsN9++020744dO9g555zDEhISWExMDMvKymIXXHAB++6773o9Ro7j2IMPPsiysrJYTEwMmzx5Mvv000/ZokWLWFZWlrBfbW0tA8AeffRRl8cAwFavXi3a9sEHH7C8vDwWExPDxo0bxz788EOXx/SGSqViixYtEm1rampiS5cuZZmZmSwqKoqlpqayE088kb300kuMMcb++usvJpfL2bJly0R/Z7PZ2LRp01h6ejozGAzCtmXLlrGkpCQmkUhYX5fynDlzGACP/3irV69mAFhzc7Po7729fn744QcGgL399tvsjjvuYMnJyUyhULD58+ezuro6l7/39vz/+OOPbOrUqSw6OpqNHDmSvfDCC0JbHfX09LAbb7yRJSQkMJVKxc444wzW0NDgcq7590htba2wzfmadzxG52t8x44d7LjjjmMxMTFs2LBhbN26dezpp59mANjBgwcZY4z9/fff7KKLLmLDhw9nMTExLDk5mZ1++unszz//dHmOvl5XnsFgYDqdzu01XV1dzc477zym1+tZbGwsmz59Ovv0009F+/DnZ/PmzS6P7e9nRG/OP/98BoC9++67wjaLxcKUSiWLjo5mPT09ov3dnZ+DBw+y+fPnM41GwwAI58Td553jsf7www+i7c8++ywbO3Ysi4qKYikpKey6664T3leOHn/8cZaRkcFiYmJYQUEB+/PPP91eC//73//YuHHjmFwuZwDYhg0b+nw99uzZw66++mqWnZ3NoqOjmUajYQUFBeyZZ55hJpNJ2M9qtbK1a9eyESNGsKioKJaZmcnuuOMO0T6M+Xbtvvzyy2zkyJFMJpOJXp/ezufHH3/MjjrqKBYbG8uys7PZww8/zF577TXROfL2ev/ll1+E97Lj+9Ld+5lXUFDAALCrrrrK00vKXnrpJTZ16lSmUCiYRqNhEydOZLfddhs7cOCAx79xfF53/2QymbBfdXU1u+yyy1hqaiqLiopiGRkZ7PTTT2fvv/++sI+335P9eR+6e32cP9c8fX67ez91d3ezpUuXsvj4eKZWq9mCBQtYRUUFA8AeeuihXl8zQgghkctTv4vHj70c+0O+fLcx1v/vdEfz5893Gb/Z7Xa2cuVKlpiYyJRKJSssLGRVVVUsKytLNG7ztW/5ww8/sMLCQqbT6VhsbCzLyclhixcvdukD+TPOdNcfB8CWLl0q2uZp7Ouu77Fr1y42b948plarWWJiIrv66qtZcXGx2/7sO++8w8aOHctiYmLYhAkT2Mcff8zOPfdcNnbsWJe29vf87du3j5199tlMr9cznU7Hzj//fHbgwAG/+jvejg37snnz5n6d+5tvvpnJZDL2+++/i/7uzz//ZHK5nF133XXCtt27d7PZs2czhULBALjEEhzx59nTP8e/9dTH9/b64d+/1dXV7OSTT2ZKpZKlpKSw1atXM7vd7vK43px/u93O1q5dK/SZ586dy3bu3OnyXmSMsZKSEjZnzhwWGxvLMjIy2H333cdeffVVl3PtbX/b3WcUY4w9/fTTQmxp+vTpbNu2bWzq1KnslFNOEfZ58cUX2ezZs4XYRU5ODrv11ltZe3u7y+vQ1+vK469bd9f0u+++yyZPnsxiYmJYfHw8u+SSS9i+fftE+3j6fGXM/88IQhxJGKOK+APhySefxM0334x9+/YhIyMj1M0hJOCWL1+OF198EV1dXX4v+EcIIQOtqKgIkydPxhtvvIFLLrkk1M0hhBBCSBibNGkSkpKSXOqkEzIUcByHpKQknHPOOS4liAmJRFTzPAh6enpEP5tMJrz44osYPXo0Bc7JkOB8jbe0tOA///kPjj32WAqcE0LCnvNnGHDkJrdUKsXs2bND0CJCCCGEhCOr1SqqBQ0AW7ZsQXFxMebOnRuaRhESQCaTyaXe/uuvv47W1la6xgn5/6jmeRCcc845GD58OCZNmiTU2d69e3dAF3YgJJRmzZqFuXPnIi8vD01NTXj11VfR0dGBe+65J9RNI4SQPj3yyCP466+/cPzxx0Mul+OLL77AF198gWuuuQaZmZmhbh4hhBBCwsT+/fsxb948XHrppUhPT8fu3bvxwgsvIDU1Fddee22om0eI33777TfcfPPNOP/885GQkIC///4br776KiZMmIDzzz8/1M0jJCxQ8DwICgsL8corr+DNN9+E3W7HuHHj8M4772DhwoWhbhohAXHaaafh/fffx0svvQSJRIIpU6bg1VdfpYxNQsigkJ+fj2+++Qb33Xcfurq6MHz4cKxZswZ33XVXqJtGCCGEkDASFxeHqVOn4pVXXkFzczNUKhXmz5+Phx56CAkJCaFuHiF+y87ORmZmJp5++mm0trYiPj4el112GR566CFER0eHunmEhAWqeU4IIYQQQgghhBBCCCGEOKGa54QQQgghhBBCCCGEEEKIEwqeE0IIIYQQQgghhBBCCCFOKHhOCCGEEEIIIYQQQgghhDih4DkhhBBCCCGEEEIIIYQQ4oSC54QQQgghhBBCCCGEEEKIEwqeE0IIIYQQQgghhBBCCCFOKHhOCCGEEEIIIYQQQgghhDih4DkhhBBCCCGEEEIIIYQQ4oSC54QQQgghhBBCCCGEEEKIE3moG0AIIYQEit1uh9VqDXUzCAmIqKgoyGSyUDeDEEIIIYQMIRzHwWKxhLoZhARMsMdNFDwnhBAy6DHGcPDgQbS1tYW6KYQElF6vR2pqKiQSSaibQgghhBBCBjmLxYLa2lpwHBfqphASUMEcN1HwnBBCyKDHB86Tk5OhVCop0EgGPcYYjEYjDh06BABIS0sLcYsIIYQQQshgxhhDY2MjZDIZMjMzIZVSJWcy+A3EuImC54QQQgY1u90uBM4TEhJC3RxCAkahUAAADh06hOTkZCrhQgghhBBC+s1ms8FoNCI9PR1KpTLUzSEkYII9bqLbTIQQQgY1vsY5dQDJUMRf11TLnxBCCCGE+MNutwMAoqOjQ9wSQgIvmOMmCp4TQggZEqhUCxmK6LomhBBCCCGBRP1LMhQF87qm4DkhhBBCCCGEEEIIIYQQ4oSC54QQQggJK4sXL8aCBQsC/rhbtmyBRCJBW1ubx302btwIvV4v/LxmzRpMmjQp4G0hhBBCCCGEkP6iMdPAoeA5IYQQEiLB6vAMlLlz50Iikbj8u/baa0PdtIBZsWIFvvvuu1A3gxBCCCGEkIhEY6bwN9THTPJQN4AQQgghg9fVV1+Ne++9V7RtKC3eqlaroVarQ90MQgghhBBCyCBFY6bBjTLPCSGEEAd79uzBF198gcrKygF/7rlz52LZsmVYvnw54uLikJKSgpdffhnd3d24/PLLodFoMGrUKHzxxRfC39jtdlx55ZUYMWIEFAoFcnNz8dRTT4ke12az4cYbb4Rer0dCQgJWrlyJRYsWiTI4OI7DunXrhMc5+uij8f777/fZZqVSidTUVNE/rVYLANi7dy8kEgnee+89HHfccVAoFJg2bRr27NmD7du345hjjoFarcapp56K5uZml8deu3YtkpKSoNVqce2118JisfjU3s8//xxjxoyBQqHA8ccfj71797o8x8aNGzF8+HAolUqcffbZaGlpEf3eeQoin/ny2GOPIS0tDQkJCVi6dKloVffGxkbMnz8fCoUCI0aMwFtvvYXs7Gw8+eSTAADGGNasWYPhw4cjJiYG6enpuPHGG/t8rQkhhBBCCAkHNGaiMZOjoT5mouA5IYQQAqC1tRWnnHIKcnNzcdppp2HMmDE45ZRTYDAYBrQdmzZtQmJiIv744w8sW7YM1113Hc4//3zk5+fj77//xsknn4x//etfMBqNAI50iIYNG4bNmzdj165dWLVqFe6880689957wmM+/PDDePPNN7FhwwZs27YNHR0d+Oijj0TPu27dOrz++ut44YUXUFZWhptvvhmXXnopfvzxR7+PafXq1bj77rvx999/Qy6X4+KLL8Ztt92Gp556Clu3bkVVVRVWrVol+pvvvvsO5eXl2LJlC95++218+OGHWLt2rdftbWhowDnnnIMzzjgDRUVFuOqqq3D77beLnuP333/HlVdeiRtuuAFFRUU4/vjjcf/99/d5PD/88AOqq6vxww8/YNOmTdi4cSM2btwo/P6yyy7DgQMHsGXLFnzwwQd46aWXcOjQIeH3H3zwAZ544gm8+OKLqKysxEcffYSJEyf256UlhBBCCCFkwNCYicZMETlmYoQQQsgg1tPTw3bt2sV6enr8epzCwkImk8kYAOGfTCZjhYWFAWqpq0WLFrGzzjpL+HnOnDns2GOPFX622WxMpVKxf/3rX8K2xsZGBoD9+uuvHh936dKl7NxzzxV+TklJYY8++qjocYcPHy48t8lkYkqlkv3yyy+ix7nyyivZRRdd5PF55syZw6KiophKpRL9e+ONNxhjjNXW1jIA7JVXXhH+5u2332YA2HfffSdsW7duHcvNzRW9LvHx8ay7u1vY9vzzzzO1Ws3sdrtX7b3jjjvYuHHjRL9fuXIlA8AMBgNjjLGLLrqInXbaaaJ9Fi5cyHQ6nfDz6tWr2dFHHy1qW1ZWFrPZbMK2888/ny1cuJAxxlh5eTkDwLZv3y78vrKykgFgTzzxBGOMsccff5yNGTOGWSwW9y+sg0Bd34QQQgghJLIFol9JYyYaMzEWfmMmxoI7bqKa54QQQiLenj178NVXX7lst9vt+Oqrr1BZWYnRo0cPSFuOOuoo4f9lMhkSEhJEd9hTUlIAQHRX/rnnnsNrr72G+vp69PT0wGKxCNPm2tvb0dTUhOnTp4sed+rUqeA4DgBQVVUFo9GIk046SdQWi8WCyZMn99reSy65BHfddZdoG99Gd8fE/875mByPBwCOPvpoUR3AWbNmoaurCw0NDejq6uqzveXl5ZgxY4bo97NmzRL9XF5ejrPPPttlny+//NLzAQMYP348ZDKZ8HNaWhpKS0sBABUVFZDL5ZgyZYrw+1GjRiEuLk74+fzzz8eTTz6JkSNH4pRTTsFpp52GM844A3I5dcsIIYQQQkh4ojETjZkc94mkMRON0gghhES86urqXn9fVVU1YB3BqKgo0c8SiUS0TSKRAIDQiXvnnXewYsUKPP7445g1axY0Gg0effRR/P77714/Z1dXFwDgs88+Q0ZGhuh3MTExvf6tTqfDqFGjet3HXfudt/HHE+z2BoK7c+RL+zMzM1FRUYFvv/0W33zzDa6//no8+uij+PHHH10emxBCCCGEkHBAYyYaM/liKI2ZKHhOCCEk4uXk5PT6+746OqG0bds25Ofn4/rrrxe2OXZsdTodUlJSsH37dsyePRvAkeyQv//+W8i0GDduHGJiYlBfX485c+YMaPs9KS4uRk9PDxQKBQDgt99+g1qtRmZmJuLj4/tsb15eHj7++GPRtt9++81lH+cOs/M+vsrNzYXNZsOOHTswdepUAEcGEs51IBUKBc444wycccYZWLp0KcaOHYvS0lJR9gUhhBBCCCHhgsZMNGbytI+vBtuYiYLnhBBCIt6YMWNQWFiIb7/9Fna7Xdguk8kwb968Acug6I/Ro0fj9ddfx1dffYURI0bgP//5D7Zv344RI0YI+yxbtgzr1q3DqFGjMHbsWDzzzDMwGAxCRoNGo8GKFStw8803g+M4HHvssWhvb8e2bdug1WqxaNEij89vNBpx8OBB0baYmBjRlLv+sFgsuPLKK3H33Xdj7969WL16NW644QZIpVKv2nvttdfi8ccfx6233oqrrroKf/31l2iBGgC48cYbUVBQgMceewxnnXUWvvrqqz6nH/Zl7NixmDdvHq655ho8//zziIqKwi233AKFQiG83hs3boTdbseMGTOgVCrxxhtvQKFQICsry6/nJoQQQgghJFhozERjpkgdM0kH/BkJIYSQMPT2229j3rx5om3z5s3D22+/HaIWeWfJkiU455xzsHDhQsyYMQMtLS2ijAoAWLlyJS666CJcdtllmDVrFtRqNQoLCxEbGyvsc9999+Gee+7BunXrkJeXh1NOOQWfffaZqEPpzssvv4y0tDTRv4suusjv4zrxxBMxevRozJ49GwsXLsSZZ56JNWvWeN3e4cOH44MPPsBHH32Eo48+Gi+88AIefPBB0XPMnDkTL7/8Mp566ikcffTR+Prrr3H33Xf73fbXX38dKSkpmD17Ns4++2xcffXV0Gg0wuut1+vx8ssvo6CgAEcddRS+/fZbfPLJJ0hISPD7uQkhhBBCCAkWGjPRmCkSx0wSxhgb8GclhBBCAsRkMqG2thYjRowQdWz6q7KyElVVVRg1alRYZ0/4g+M45OXl4YILLsB9990X6uYMefv27UNmZia+/fZbnHjiiT79baCvb0IIIYQQEpkC2a+kMRMJNH/GTEBwx01UtoUQQghxMHr06CHXAayrq8PXX3+NOXPmwGw249lnn0VtbS0uvvjiUDdtSPr+++/R1dWFiRMnorGxEbfddhuys7OF+omEEEIIIYQMZjRmIv4aTGMmCp4TQgghQ5xUKsXGjRuxYsUKMMYwYcIEfPvtt8jLywt104Ykq9WKO++8EzU1NdBoNMjPz8ebb7454KvCE0IIIYQQQrxDY6aBNZjGTFS2hRBCyKBGZS3IUEbXNyGEEEIICQTqV5KhLJjXNy0YSgghhBBCCCGEEEIIIYQ4oeA5IYQQQgghhBBCCCGEEOKEgueEEEIIIYQQQgghhBBCiBMKnhNCCCGEEEIIIYQQQgghTih4TgghhBBCCCGEEEIIIYQ4oeA5IYQQQgghhBBCCCGEEOKEgueEEEIICTiJRIKPPvoo4I+7ePFiLFiwoNd95s6di+XLlws/Z2dn48knnwx4WwghhBBCCCGkv2jMNDhQ8JwQQggJAYlE0uu/NWvW9Pux9+7dC4lEgqKiIq/2c/fvt99+6/fzh5vt27fjmmuuCXUzCCGEEEIIIT6gMdPAoTGTZ/JQN4AQQgiJRI2NjcL/v/vuu1i1ahUqKiqEbWq1esDa8u2332L8+PGibQkJCQP2/MGWlJQU6iYQQgghhBBCfERjpoFDYybPKPOcEEIIAWAsacbBJ//Cvju24sADv6Hj+3owOwva86Wmpgr/dDodJBKJaNs777yDvLw8xMbGYuzYsVi/fr3wt1dccQWOOuoomM1mAIDFYsHkyZNx2WWXAQBGjBgBAJg8eTIkEgnmzp3ba1sSEhJEz52amoqoqCgAwJo1azBp0iS89tprGD58ONRqNa6//nrY7XY88sgjSE1NRXJyMh544AGXx21sbMSpp54KhUKBkSNH4v333xf9vqGhARdccAH0ej3i4+Nx1llnYe/evcLv7XY7/u///g96vR4JCQm47bbbwJj4nHR3d+Oyyy6DWq1GWloaHn/8cZd2OE9BlEgkeOWVV3D22WdDqVRi9OjR+Pjjj0V/8/HHH2P06NGIjY3F8ccfj02bNkEikaCtrQ0AUFdXhzPOOANxcXFQqVQYP348Pv/8815fZ0IIIYQQQgYze4cZrZsrsP+ebdh35884vKkM1oPdQXs+GjPRmCkcUPCcEEJIxOvefhCtb+2GrckIMIDrtKLj6zq0vr8nJO158803sWrVKjzwwAMoLy/Hgw8+iHvuuQebNm0CADz99NPo7u7G7bffDgC466670NbWhmeffRYA8McffwA4kh3R2NiIDz/80K/2VFdX44svvsCXX36Jt99+G6+++irmz5+Pffv24ccff8TDDz+Mu+++G7///rvo7+655x6ce+65KC4uxiWXXIILL7wQ5eXlAACr1YrCwkJoNBps3boV27Ztg1qtximnnAKLxQIAePzxx7Fx40a89tpr+Pnnn9Ha2or//ve/oue49dZb8eOPP+J///sfvv76a2zZsgV///13n8e0du1aXHDBBSgpKcFpp52GSy65BK2trQCA2tpanHfeeViwYAGKi4uxZMkS3HXXXaK/X7p0KcxmM3766SeUlpbi4YcfHtDMF0IIIYQQQgYS12PDofXFMO44BGblAI7BtLsVh9YXwdpsHPD20JiJxkwDhhFCCCGDWE9PD9u1axfr6enp199zNjvbf++vrGHlT27/WQ52BbjFrjZs2MB0Op3wc05ODnvrrbdE+9x3331s1qxZws+//PILi4qKYvfccw+Ty+Vs69atwu9qa2sZALZjx45en5ffT6FQMJVKJfrHW716NVMqlayjo0PYVlhYyLKzs5ndbhe25ebmsnXr1gk/A2DXXnut6PlmzJjBrrvuOsYYY//5z39Ybm4u4zhO+L3ZbGYKhYJ99dVXjDHG0tLS2COPPCL83mq1smHDhrGzzjqLMcZYZ2cni46OZu+9956wT0tLC1MoFOymm24StmVlZbEnnnhC1La7775b+Lmrq4sBYF988QVjjLGVK1eyCRMmiNp+1113MQDMYDAwxhibOHEiW7NmjZtXNbD8vb4JIYQQQghhzP9+ZceWBtZwu5sx0x1bWcvmigC31hWNmY6gMZN7wRw3Uc1zQgghEc3WagLXbfX4e/PeDkSlqAasPd3d3aiursaVV16Jq6++Wthus9mg0+mEn2fNmoUVK1bgvvvuw8qVK3Hsscf2+znfffdd5OXlefx9dnY2NBqN8HNKSgpkMhmkUqlo26FDh0R/N2vWLJef+QV5iouLUVVVJXpcADCZTKiurkZ7ezsaGxsxY8YM4XdyuRzHHHOMMA2xuroaFotFtE98fDxyc3P7POajjjpK+H+VSgWtViu0v6KiAtOmTRPtP336dNHPN954I6677jp8/fXXmDdvHs4991zRYxJCCCGEEDKUmGvbAHdVLTkGc1XbgLaFxkw0ZhpIFDwnhBAS0aQxMr9+H2hdXV0AgJdfflnUwQEAmeyftnAch23btkEmk6Gqqsqv58zMzMSoUaM8/p6v5ceTSCRut3Ec5/VzdnV1YerUqXjzzTddfjcQi9X42/6rrroKhYWF+Oyzz/D1119j3bp1ePzxx7Fs2bJAN5UQQgghhJCQk8TKjxR/dtNllsTSmInGTK6GypiJap4TQgiJaDJtDKJH6Nx+I0qipYjNG9gV1FNSUpCeno6amhqMGjVK9I9f1AYAHn30UezevRs//vgjvvzyS2zYsEH4XXR0NIAji8eE0m+//ebyM5+tMWXKFFRWViI5OdnlOHU6HXQ6HdLS0kQ1AW02G/766y/h55ycHERFRYn2MRgM2LPHv1r1ubm5+PPPP0Xbtm/f7rJfZmYmrr32Wnz44Ye45ZZb8PLLL/v1vIQQQgghhIQr5eRkt4FzAFBNTR3QttCYicZMA4mC54QQQiJe/LmjIVUf6TxBKgEkAGQSxF84dsAzz4EjC7OsW7cOTz/9NPbs2YPS0lJs2LAB//73vwEAO3bswKpVq/DKK6+goKAA//73v3HTTTehpqYGAJCcnAyFQoEvv/wSTU1NaG9v7/X5WlpacPDgQdE/k8nk93Fs3rwZr732Gvbs2YPVq1fjjz/+wA033AAAuOSSS5CYmIizzjoLW7duRW1tLbZs2YIbb7wR+/btAwDcdNNNeOihh/DRRx9h9+7duP7664WV2wFArVbjyiuvxK233orvv/8eO3fuxOLFi0VTI/tjyZIl2L17N1auXIk9e/bgvffew8aNGwEcybYAgOXLl+Orr75CbW0t/v77b/zwww+9TuMkhBBCCCFkMIsdEwdVfvqRH6SSI/8AxObGQT0rbcDbQ2MmGjMNFAqeE0IIiXjyRAVSbzkG+rNHQTU9FdqTs5B62zQoxg1s1jnvqquuwiuvvIINGzZg4sSJmDNnDjZu3IgRI0bAZDLh0ksvxeLFi3HGGWcAAK655hocf/zx+Ne//gW73Q65XI6nn34aL774ItLT03HWWWf1+nzz5s1DWlqa6N9HH33k93GsXbsW77zzDo466ii8/vrrePvttzFu3DgAgFKpxE8//YThw4fjnHPOQV5eHq688kqYTCZotVoAwC233IJ//etfWLRoEWbNmgWNRoOzzz5b9ByPPvoojjvuOJxxxhmYN28ejj32WEydOtWvdo8YMQLvv/8+PvzwQxx11FF4/vnnhZXjY2JiABzJUFm6dCny8vJwyimnYMyYMVi/fr1fz0sIIYQQQki4kkgkiDszB0nXHw31selQz0xD4uXjkbBoPCTygQ8v0piJxkwDRcL4CvKEEELIIGQymVBbW4sRI0YgNjY21M0hQ9QDDzyAF154AQ0NDQP6vHR9E0IIIYSQQKB+JQm2UI2ZgOBe37RgKCGEEEKIk/Xr12PatGlISEjAtm3b8OijjwrTJwkhhBBCCCEk0kXKmImC54REKMYYrFYrTCYT5HI55HI5ZDIZpFKpUJ+KEEIiVWVlJe6//360trZi+PDhuOWWW3DHHXeEulmEEEIIGUCMMXAch56eHgBAVFQUZDIZZDIZjZkIIREvUsZMVLaFkAjEcRwsFgvsdjvMZrPQ8ZNIJJBKpUKnUC6XQyKRUMeQhDWafkiGMrq+CSGEkNDgk43sdrswdgL+GTM5JiBRMJ0MBtSvJEMZlW0hhAQEYwx2ux1WqxWMMUilUiHbnDEm/N5mswlBcz6IzncMKZhOCCGEEEIIGco4jhMC53yw3HEMxCcj8YlIFEwnhJChi4LnhEQIx8wJAELAnMcHxaVSqbA/Yww2mw1Wq9VjMJ3fn5BQo4lUZCii65oQQggZOI7JRBzHuYx1+IC4TCYT9geOBNPNZjMsFgsAUDCdhDXqX5KhKJjXNQXPCYkAfLY53wHkO269fbj4Ekx3rP1HwXQy0KKiogAARqMRCoUixK0hJLCMRiOAf65zQgghhASHu2QjiUTS55gJgDAW4sdMjDGYzWZRZrpjaUxaZ4qEAn/Tx2Kx0LiJDDnBHDdR8JyQIYwPdttsNgDwq5PWVzCdf3znDAsKppNgk8lk0Ov1OHToEABAqVTSYIQMeowxGI1GHDp0CHq9XhjsEEIIISTw+DIszslGjhhjffYxHUtcOgfTTSaTsA8fTHeczUv9VxJscrkcSqUSzc3NiIqKorE6GRIGYtxEC4YSMkTxdfo4jgMAt7XK+U5iIL40+U4hx3FCx1IikVAwnQwIxhgOHjyItra2UDeFkIDS6/VITU2lATUhhBASBO7WhHL+zuUz0t2VcenP8zmOmwAKppOBZbFYUFtbK1x/hAwVwRw3UfCckCGG74i5K9PiLJDBc0/tcK6r7hhMl8vl1CkkAcUPfggZCvjp3YQQQggJPOcyLe6SjRz3C0Tw3N1juwumu1tnisZNJFD4OAAhQ0Wwx00UPCdkCPG2A8jvW1NTg0OHDkGn0yEuLi6opQEcg+nuMtP5jiF1CgkhhBBCCCHB4phs5Dgu6W3/YAXP3T2X8z+pVOpSHpOC6YQQMnAoeE7IEMF3AO12e5+dKbPZjJKSEhiNRgwbNgxdXV0wGAwwm83QarVCIF2n0w1YMN1oNMJsNiMlJUW0ACl1CgkhhBBCCCGB4LwmVF+Bc/5vBip47u65HbPSgX/KvFAwnRBCBgYtGErIIMfX6bPZbH2WaQGAw4cPo6SkBAkJCTj66KNFncCenh4YDAYYDAY0NjbCarUKwfS4uDhotdqAdRj56Yi87u5uHDx4EPHx8bBYLG47hRRMJ4QQQgghhPSH85pQg2EtJj64z7eVD6bz4z/+93yZF8fSmDRuIoSQwKDgOSGDmHOZlr7qm1dWVqK+vh55eXnIyMgAY0xU60yhUEChUCA9PR2MMVEwfd++fbDb7UKJl7i4OGg0moAG0/kyLvyEGL4Wm9lspmA6IYQQQgghxGe+rAkV7jwF0202G6xWq0sw3bE05mA9ZkIICTUKnhMySPELI3rTATQajSguLgbHcZg1axbUajUAoLeqTRKJBEqlEkqlUgi0G41GIZheX18Pxhj0ej30er0QTPenU8a3h38MPjOdgumEEEIIIYQQX/mSbDQY+RJMdyyNORiy7gkhJFxQ8JyQQcaxTh+/gExvHcCDBw9i586dSE9PR25ubr9rmEskEqhUKqhUKgwbNgyMMXR1daGtrQ0GgwF1dXUAIATS9Xo91Gp1QDqn7oLp/D+z2Sxkz1MwnRBCCCGEEAL4tiZUbwZT1nZvwfTu7m5UV1dj/PjxLmMmCqYTQohnFDwnZBDhOA42m82rzAm73Y7y8nI0NTVh4sSJSElJCWhbJBIJNBoNNBoNMjMzwRhDZ2cnDAYDWltbUVNTA6lUKgTT4+LioFQqPbbXlw6pYwdWJpO5BNMdM9P5DAu5XD7kMk0IIYQQQgghYnxNcKvV6lWy0VDmGEy3Wq04fPgwJBIJrFZrrwlIFEwnhJB/UPCckEHAsU4fY6zP7IfOzk4UFxdDLpcjPz8fCoUi6G2USCTQarXQarXIysoCx3FCML25uRlVVVWQy+WiYLpCoRAdR29lZPp6bk/BdJPJJOzDB9NpVXpCCCGEEEKGnqFepsUf/OsglUpFmen8ONNqtQr7UTCdEEL+QcFzQsKccwewt8A5YwwNDQ2oqKhAdnY2cnJyQtbRkUql0Ol00Ol0yM7OBsdx6OjogMFgQFNTE/bs2YPo6GghmG6z2QL23N4G050X0qHONSGEEEIIIYOTL2tCRTI+GQv4Z0zk+Lu+gulyuZxeW0JIRKHgOSFhjOM4NDU1QSaTQavV9tpJsVqt2LlzJ9ra2jBlyhQkJCR49RwD1fHhS7jo9XqMGDECdrsd7e3taGtrQ2NjI9rb2yGRSFBeXi4E1GNjYwPy3J6C6RzHUTCdEEIIIYSQQcxxTSiAss390Vsw3WKxCLN5ncdN9HoTQoYyCp4TEob4On02mw11dXXQ6/XQ6XQe929ra0NRURHUajUKCgoQHR3t03MBAxdE58lkMsTHxyM+Ph4AcODAAdTX1yMqKgr79+9HeXk5FAqFUOIlLi7Op+PqTW/BdLPZDJPJJExnpGA6IYQQQggh4YkP7HIcByA4i3tyHIe9e/eCMYb4+HhoNJqIGRN4G0x3LvMSKa8PISQyUPCckDDjrkyLp1rgjDHU1taiuroao0aNQnZ29qDtqPAdrlGjRgEAbDYb2traYDAYUFdXh7KyMiiVSiGQrtfrgxJMB/5Zld5ut8Nut4sWIKVgOiGEEEIIIaHlGMQNZpmW7u5uFBcXgzGG6Oho1NfXA4BoHSeVSjUoxgSBaKNjMJ0fo3IcB4vF4nHMRMF0QshgR8FzQsII3/Fw7ABKpVK3wXOz2YySkhIYjUZMnz6918z0wcLxOOVyORITE5GYmAjgSFkaPpheW1uL7u5uqNVqoeOq1+sRFRUVkHY4rkrPt8txNgD/e3fTFaljSAghhBBCSPAwxtDR0QGr1QqVShW0wPmBAwdQVlaGYcOGYeTIkUKt8M7OThgMBrS2tqKmpkYoT8kH05VKZViPCRxrnvvDcSYv/7gABdMJIUMPBc8JCQN8YNZqtYIxJuoAuss8P3z4MEpKSpCQkIDJkydDLh/8b+W+OlBRUVFISkpCUlISAMBisQjB9OrqahiNRmg0GqHTqtPpAva6eAqm22w2WK1WCqYTQgghhBAyAPhs8/r6epjNZkycODHgz2Gz2VBeXo5Dhw7h6KOPRnJysjAzWCKRQKvVQqvVIisrCxzHCcH05uZmVFVVQS6Xi0pPKhSKgLcxHPUWTDebzbBYLABAwXRCyKAz+CNuhAxyHMfBZrMJZVqcMyccg+ccx6GyshL19fXIy8tDRkZGxHY0oqOjkZycjOTkZABHMvENBgMMBgP27NkDk8nkEkx3rNfnD1+C6VFRUUKnkN+fEEIIIYQQ4j3HWaD8LF1PpS390dnZiaKiIkRHR6OgoACxsbG97i+VSqHT6aDT6ZCdnQ273Y6Ojg4YDAY0NjaioqICMTExomB6TExMwNsdjhyD6Y7rTDHGXILp/JhJLpdTaUxCSNih4DkhIeJYp4+fOueuk8AHz41GI4qLi8FxHGbNmgW1Wu13G8KtU+JPBzgmJgapqalITU0FAJhMJiGYXl5eDovFAq1WK3RatVrtgAXTAfcZFhRMJ4QQQgghpHfOa0JJpdKAB88ZY2hoaEBFRQWys7ORk5PTr766TCYTxhsAYLfbhdmy+/btw65du6BUKkVlXgK1jlO4cxzvOgfTTSaTsA8fTKd1pggh4YKC54SEAB9YtdlsAHpfFZ6vq/fLL78gPT0dubm5AQv68o8fDgLdjtjYWKSlpSEtLQ2MMfT09Agd1wMHDsBms7kE0wMVzPYUTOdXpe/s7ITZbEZ6ejoF0wkhhBBCCPGAL23pvCiou9KW/WW1WlFWVgaDwYApU6YgISEhII8LHAkSJyQkCI9ps9mEMUldXR3KysqgUqmEMUkg13FyFi7jPh4F0wkhgwUFzwkZYHy2OV8zr7eAqd1uR2trK4xGI44++mikpKQMYEuHDolEAqVSCaVSifT0dCGT32AwoK2tDfv27YPdboder4der0d8fDzUanXQgund3d1oaWlBUlKSkJkukUgoM50QQgghhBCIk42c14QCAhc8b2trQ3FxMVQqFfLz8z2WVAlUsFYulyMxMRGJiYkABnYdJ14wyt0EgrfBdOd1piiYTggJNgqeEzJA3NXp6+1LvrOzE8XFxbBarUhNTY2IwPlAdeQkEglUKhVUKhWGDRsGxhi6u7uFMi/19fVgjImmU6rV6oB1yhxXnQfEJXw8BdPlcjl1CgkhhBBCyJDX15pQgP/Bc8YY9u7di8rKSowePRrZ2dkh6Wv3to5TRUUFzGZz0NZxCneegun8AqQmk0ko4UPBdEJIMFHwnJAB4K5On6cvdOd6e3a7HRzHDWRzQyKUHRyJRAK1Wg21Wo3MzEwwxtDV1SV0XGtrayGRSETBdJVK1e82O3f0+QwKx9/zwXSLxSIE250XIKVOISGEEEIIGSq8XRMK8C94brFYUFJSgu7ubkyfPh16vd6PVgeW8zpOjqUn+XWcdDpdUEpPhjvn64EPptvtdtjtdpjNZlGSEgXTCSGBQsFzQoKM4zhYLBavss2tVit27tyJtrY2od5eZWWlUBudDAyJRAKNRgONRoPhw4eD4zghmN7S0oKamhpIpVJRMF2pVAY0M92bYLpzmRfqFBJCCCGEkMHIOdmot8A5//v+JBi1tLSgpKQEer0e+fn5XtcXD1U/W6FQQKFQiNZx4hN8fC09OdTGCp7WmbLb7cI6V3l5ecIsXsfZvEPttSCEBBcFzwkJEv6Lm8+c6Ctw3tbWhqKiIqjVahQUFAirrgdyMZxwF67HKZVKodVqodVqkZWVBY7j0NnZidbWVjQ3N6OqqgpyuVy00I9CoQhKMJ1/jfibMp4yLCiYTgghhBBCBgPHNaG8zRL2dYzEGENVVRX27t2L3NxcZGZmDrq+suM6ThkZGULpST4zPdilJ8OdYzCd4zh0d3dDIpHAZrPBarUKv3eumU7BdEJIXyh4TkgQ+Fqmpba2FtXV1Rg1apRLvb1ICZ4Ppg6LVCqFTqeDTqcDcGRh146ODhgMBjQ2NqKiogLR0dEuwXRH/T1ex7p/AAXTCSGEEELI4OTrmlCOpFKp12Mkk8mE4uJiWCwWzJgxA1qt1p9mhw3H0pP8Ok7OpScdZ8tqNBoA4ZuwFAx8TXTgn8x0d8F0x9KYkVIGhxDiPQqeExJgfLa5Nx1As9mMkpISGI1GTJ8+XQjGOoqU4DkweDtyMplMCJQDR66B9vZ2GAwG7N+/H7t370ZMTIywD78oaCD0Fkw3m82wWCwAQMF0QgghhBASNnxJNnLH2zHSoUOHUFpaiuTkZEydOhVyef9DIOE+VnFXerKzsxMGg0GYLQsA5eXlSEhICPhs2XDjbpFZd2VeKJhOCOkLBc8JCRD+i5evT95XB/Dw4cMoKSlBQkICJk+e7LEjFynB86HUaZPJZIiPj0d8fDwAwGazCcH0hoYGdHZ2QiaToaKiQsgE4cv0+MsxmO64Kj1jzCWYzncK5XI5LaRDCCGEEEIGhC9rQnnS1xiJ4zjs2bMHDQ0NGD9+PNLT0/1p8qAcjznOls3OzobZbMa2bdugUChw8OBBl9mycXFxiI2NDXWzA8Kb89VXMB1wn4BEwXRCIg8FzwkJAL5OH79oTW910ziOQ2VlJerr65GXl4eMjIw+F8MZjJ21/hiqxymXy5GQkICEhAQAQG1tLVpbWyGVSlFXV4eysjKoVCpRmRdvFy/qi+O16BxMN5lMwj58MJ1WpSeEEEIIIcHg65pQveltjGQ0GlFcXAyO45Cfnw+VSuVPs4cMfqZqdnY25HK529mysbGxomB6oBJ8QsHXa8tTMN1qtcJisQi/p2A6IZGHgueE+IExJgqc99UBdOzIzZo1C2q1us/niKTgeaSQSqWIiYnB6NGjAQBWq1WoTVhTU4Pu7m6o1WpRMN2fKaaOKJhOCCGEEEIGmr9lWpxJJBIhcclRY2MjysrKkJ6ejtzcXCFgTFy5my3LLz4a7ASfYAvE+NldMJ0f+/OZ6c7BdLlcTmMmQoYgCp4T0k++dgD725ELdvA8XILzkdzJiIqKQnJyMpKTkwEAFotFCKZXVlaip6cHGo1G6LjqdLoBD6Y7r0pPwXRCCCGEENIXx4AjY6zXGbq+cB7D2O12lJeX4+DBg5g4cSJSUlL8fo6hytPYTy6XIzExEYmJiQCOJPjwwfRgJ/gEQ6DHKvyYiOd4bbvLTOfHTTRmImTwC99POkLCGP8labfb+wwi8h25pqamfnXkpFKp26yKoSgcgvjhIDo6GikpKcK1YjabhWB6RUUFzGYztFqtUC9dp9MFLKvGUzCdX4DUZDIJq9ZTMJ0QQgghhHjivCZUoALnwJExEj926OrqQlFREeRyOQoKCqBQKALyHJEuKioKSUlJSEpKAnBkTMIH0ysrK2EymVwSfMIl038gxpXeBNOlUqnLAqQ0ZiJk8KHgOSE+4Ov02Ww2r8q0dHZ2ori4GHK5HPn5+f3qyIVLZniwRVIngs+68VZMTAxSU1ORmpoKAOjp6YHBYEBbWxvKy8thsVig0+mEDBCdThew2nvOgxw+mG6322G322E2m4WOIQXTCSGEEEII4LomVKDrQvNlW/bt24fy8nJkZWVh1KhRVH86iGJiYkQJPiaTSUjwcRyTOCb4RNL5cAym8+N3d8F055rpNGYiJPxR8JwQL/lSpoUxhoaGBlRUVCA7Oxs5OTn97jhESvCceE+hUEChUCA9PR2MMSGYzi/2Y7PZhGB6XFwcNBpNwIPpzgvpOAfT+TIvjrX/qGNICCGEEDK0+bomVH/Z7XZYLBbs2bMHkydPFkqNEM8CfR5iY2ORlpaGtLQ0YUzCZ6YfOHAgqGOSvviarBRojjN5+fYAR4LpFovFYwISBdMJCU8UPCfEC/yq8N50AK1WK3bu3Im2tjZMmTIFCQkJfj13JAXPI+U4A0kikUCpVEKpVCIjIwOMMRiNRiGY3tDQAI7jXDqugeqUeQqm22w2WK1WSCQSWCwW2O12xMXFiWr/UceQEEIIIWToCPSioJ60t7ejrKwMjDEUFBQgJiYm4M/hjPqtvXMck/AJPo5jkvr6ejDGhKz0uLg4qNXqiHld+wqmWywWAKBgOiFhioLnhPTCsU4fY6zPDmBbWxuKioqgVqtRUFCA6Ohov9sQKcFz6hQEhkQigUqlgkqlwrBhw8AYQ3d3t9BxraurAwDo9Xqh8xrIjqu7YLrBYBBq/vO/d679F0lTOgkhhBBChhpf1oTqL8YY6urqUFlZifT0dDQ2Ng5I4HyoGah64M5jkq6uLmFMUltbC4lEIpSdjIuLg0qlCuh1E87jS3fBdP6f2WymYDohYYaC54R4wHEcbDab12VaamtrUV1djVGjRiE7OzugwchICJ5HkoGcRiiRSKBWq6FWq5GZmQnGGDo7O4UplY4dV77zGsiOq2PHMCoqym1muuOq9BRMJ4QQQggZPPjyfVar1atko/6yWCzYuXMnOjo6cMwxx0Aul6OxsTHgz0OCQyKRQKPRQKPRYPjw4eA4Tgimt7S0oLq6GjKZTBiTxMXFQaFQ9PtaGmzjZ8dZuTKZzCWY7ljmJSoqitaZImSAUfCcECeOdfr4IGdvX0hmsxklJSXo6enB9OnTodPpAtqeSAqeR8pxhpJEIoFWq4VWqxU6rp2dnTAYDGhubkZVVVVAO66A+Lx6KvPCL6QDuM+woGA6IYQQQkh4GagyLQaDAcXFxdBqtcjPz0d0dDS6uroGdOxAAcrAkkqlwpgkKysLHMeho6NDmLG6Z88eREdHi8YksbGxoW72gOktmG4ymYR9KJhOyMCg4DkhDpw7gH0Fzpubm1FaWoqEhARMnjwZcnng31KREjynL/nQkEql0Ol00Ol0yM7Odum4VlZWQi6XuwTTfdFbpn1fwXTKTCeEEEIICT++rAnVX4wx1NTUoKamBmPGjMHw4cOF5wnFGGmwj1fCuf1SqVQoKzlixAjY7Xa0t7fDYDBg//792L17N2JiYkRjkt5K9oR6wdBA6yuY3tHRge7ubmRmZorGTRRMJyQwKHhOyP/nS50+juNQWVmJ+vp65OXlISMjI2hfSpESPAco8zwcuOu48sH0xsZGVFRUICYmRrTYT19ZIL50Xt0F0/n3ptVqFfZx7BTK5XLqFBJCCCGEDADHNaGA4GWbm0wmlJaWepzdG0ljpEAbDK+bTCZDfHw84uPjAQA2m00Ipjc0NGDXrl1QKpWiYHpUVFSIWz1wnIPpJpMJra2tyMjIEDLTpVKpy4xeCqYT0j8UPCcRj6/TV1tbi+TkZMTExPT6hWI0GlFcXAyO4zBr1iyo1eqgtm8gOobhcGc+1M8/kMLh9faWYwkX4EiWUVtbG9ra2oQskNjYWNFiP85ZIP4cL7+4qONj8cF0PjNdKpUKQXS+YzhYXl9CCCGEkMGC74NxHAeg71m6/eXN7F5+jDSY+tWk/+RyORISEpCQkAAAsFqtojWcdu7cCbVaLYxbbDZbRF0X/HoD/Cxd/r1ht9tht9thMpkomE6IHyh4TiKaY5mW3bt3Iz4+vtcs2sbGRpSVlSE9PR25ubmioF6wSKVSoYNKSKjJZDJRx9VmswkdV3dZIHq9PqCDGl+C6VFRUbQqPSGEEEKIn/hs84MHDyIuLi5os/58md3Lb6fgeWSKiopCUlISkpKSABxZUNZgMKCtrQ1VVVUwGo2QyWSoqqoSxiQDMXYPFef3gafSmHww3XkBUsfZvPR+IsQVBc9JxOI4DhaLRajTJ5VKPWZ42+12lJeXo6mpCRMnTkRKSsqAtTOSpiRGynEOJXK5HImJiUhMTATgmgXS3d2NqKgoREVFobm5GXq9PqBTKh2D6fz14y6Y7lwznTqFhBBCCCF945ONzGYz/v77b5xwwglB6Uf19PSguLgYNpvNq9m9jkFBQqKjo5GSkiKM0/fu3YtDhw7BarWioqICZrMZWq1WSPDRarVDKpje102k3oLpfJY+P65yns1L4yZCKHhOIhD/JWG1WoXpTfwXibsM787OThQXF0MulyM/P9/nxRL9FSnBc/pSHhrcZYFUVFSgu7sb1dXVMBqN0Gg0QokXvV4fsIV2Hev+AeJgusViEWVYUDCdEEIIIaR3zmtCBcvBgwexc+dOpKWlYezYsV4FNR0zz4l3Iqm/K5fLERMTg7y8PABHbs4YDAYYDAYcOHAANpsNOp1OCKZrNJqgXuPB5usMDE/BdJvNBqvVKgqmO87mHcyvESH+oOA5iSgcx8Fms8FutwMQL3DjHKRmjKGhoQEVFRXIzs5GTk5OSL4sghk8NxqNKC8vR1RUFOLj4xEXF4fo6OigPBf5RyRNL42OjoZSqURUVBTGjh0Ls9ksdFwrKythMpmg0WiEQHogp1T2Fkw3m82wWCwAQMF0QgghhBAHjhmp/CxdXiDLSdrtdlRUVODAgQOYMGECUlNTvf5bCp73X6S8Zo79eYVCAYVCgfT0dDDGYDQahTIvDQ0N4DhOGIvwwfTBNB7gOM6v9lIwnZDeUfCcRATHush84NL5y8Ux89xqtWLnzp1oa2vDlClThPrOoRCs4HlTUxNKS0uRnJwMmUyGuro6lJWVQaVSIS4uDvHx8QHNCvZGpHTkIo3jzYKYmBikpqYKgyOTySQE03fv3g2LxRK0KZWOwXTHhXQYYxRMJ4QQQgiBeE0oAC4LCgYqeN7V1YXi4mJIpVLk5+dDqVT69PcUPCe96e26kEgkUKlUUKlUGDZsGBhj6O7uFsYkdXV1ACAE0uPi4qBSqcJ6PBDo5Ky+gumA+zETBdPJUEXBczLk8R/yNpsNgOdV4fkgtcFgQHFxMTQaDQoKCkKeiR3o4DnHcaioqMD+/fsxfvx4JCQkCBklVqtV6DRUVVWhp6dHyAqOi4uDTqcLWm24cO6MBAMd7xGxsbFIS0tDWloaGGOiYDo/pdI5mB6oTpnjZ4G7YLrzQjq0Kj0hhBBChjK+tCU/NnCXbBSIccn+/fuxa9cuZGZmYsyYMf3q21Hw3HeR1n/19nglEgnUajXUajUyMzPBGENnZycMBgNaWlpQU1MDqVQqjEfi4uKgUCjC6vUM9sxmT8F0x3WmJBIJBdPJkEXBczKkOdbpc/ywd0cikeDAgQM4ePAgRo8ejaysrLD4Qgxk8NxoNKK4uBiMMcyaNQsqlUq4cwwcqVednJyM5ORkAOKs4PLyclit1iFVGy5UIq2T721nTiKRuJ1SyS9Aum/fPtjt9qBdg70F000mk7APBdMJIYQQMpQ4Jhs5rgnlTCKR+JV5brPZsGvXLjQ3N2PSpEnCGjn9QcFz0ht/rguJRAKtVgutVousrCxwHIfOzk60traiqakJlZWVkMvlLsH0UBrosqDugul87IWPLzgH0+VyOY2ZyKBFwXMyJLmr09fbB7XZbIbJZMLhw4cxffp06HS6AWxt7wIVPOfLtKSnpyM3N9erDHLnrGC+NpzBYEB9fT0YY6JOg7/T2ajzOzTxgzBfOU6pzMjIEKZU8sF0/hp0XHw0kPUJvQ2mO69KT8F0QgghhAwWva0J5cyfzPOOjg4UFxcjJiYGBQUFiI2N7XebgX/6aYGswR4paMzlG6lUCp1OB51OhxEjRsBut6OjowMGgwGNjY2oqKhATEyMaFwcExMzoG0M9Zpa/JjIsT18MN1dZjo/bqIxExksKHhOhpy+6vQ5a25uRmlpKaRSKcaMGRNWgXPgn05qf78Qncu0pKWl9asd7mrDdXV1obW1FS0tLaiurvbrDjx9cQ5dgerMOU6pdLwG+cV+amtrIZFIglaf0FMwneM4IZgulUpd6v9RMJ0QQggh4cabNaGcOa4R5cvzNDQ0oKKiAiNGjEBOTk5A+2YUCCaeBKv/LZPJhLEGcGRGRXt7OwwGAxoaGrBr1y4olUphH71eH/RSsKEOnjvzJpgulUpdFiANp2MgxBEFz8mQwnEcLBaLV9nmHMehsrIS9fX1yMvLw759+8Lyw9pxSqKv7ePLtHAcJ5RpCWS7NBoNNBqNMJ2to6MDra2tLnfg4+PjERcX12enIZI6v+F4rQVLsDpzjtfg8OHDwXGcEEx3rE/oGExXKpVBD6bb7Xa0tbVh3759GDduHAXTCSGEEBJWvF0TypmvwWqr1YqdO3eira0NU6dORXx8fL/bHIj2kMgxkNeFXC5HQkICEhISABy57tva2tDW1oa9e/eiq6sLKpVKFEyPiooKaBsYY0FbmywQvA2mO9dMpzETCRcUPCdDAh+w4jMn+gpOOQeV1Wo1Dhw4EJadr/7W8zt06BBKS0uRmpqKsWPHBv3LlA9S6vV6AP/cgW9tbUVdXR3KysqETkN8fDz0ej3k8n8+giLpizEcr7NgGqjjlUqlbusTGgwGNDc3o6qqCnK5XBRMD+RiP461/+x2O4xGIyQSCex2O+x2u8sCpI61/yLp+ieEEEJI6DiuCeXrDX1fMs8NBgOKi4uh0WhQUFAQlMxbCp77LpL6nKE61qioKCQlJQk1/S0Wi1B2srq6GkajERqNRhiP6HQ60bi4P8It87wvjsF0/j3MJ0I6jpkomE7CBQXPyaDna5mWxsZGlJWVudT+7s80xIHga/Cc4zjs2bMHDQ0NmDBhQp9lWoL1BeTuDjxfL72qqgo9PT2iToO/dQ9J+ApVZ86xPmF2djY4jhOmVDY1NWHPnj2Ijo4WMkACudgPf8x8GRd+m+N6DHzQ3LlmOgXTCSGEEBJovq4J5Y43NcYZY6itrUV1dTVGjRqF7OzsoPVrKHhOPAmn6yI6OhrJyclITk4GcGS9NX5cXFFRAbPZDK1WK4xJdDqdz4lvgy147shxJi9AwXQSnih4TgY1Ptvcmw6g3W5HeXk5mpqaMHHiRKSkpIh+H66dL1+C5z09PSgqKgLHccjPz/eqTMtAHXNUVJSo02AymYROw65du4Rpo3v37kV8fDzUanW/Fpkk4SdcOnNSqVRUn9ButwvB9AMHDgR0sR/+M8mRu1Xp+WnTVqtVFEx3rP1H7wNCCCGE+MPXZCNP+low1Gw2o7S0FN3d3Zg+fXrQ15IK1/FbuKPXLLRiYmKQmpqK1NRUAEfG8PwaTuXl5bBarUIwPS4uDlqtts/xQLiMtwLBXTCd/2c2m2GxWAD8M95SKpUUTCdBR8FzMig51+nrqwPY2dmJ4uJiyOVy5Ofnu80uHeyZ5wNdpsVfsbGxSEtLQ1paGhhjaGtrw44dO9DZ2Yn6+noACNrCj+FgKB1LX8K1MyeTyRAfHy/U3/S02I/jdejtlGO+fFRvKJhOCCGEkGDzZU2ovvQ2XmppaUFJSQni4uKQn58f8JrO7niTCU8iU7iOP9xRKBRQKBRIT08HY0wIphsMBuzbtw92u100HtFoNC7HNpiO11ee1pk6cOAAWltbMX78eLelMWmdKRJIFDwngw5fp4/vKPVW4sBxdffs7Gzk5OR4DDyFa+ZCX8FzxzIt48ePR3p6+kA2LyAkEgmUSiUACF9+fK3qlpYWVFdXQy6XizKCA1VeIxSGcufGncFyvM6lhmw2m1Cf0LFuv2Pn1dPAkOO4fk2F7i2YDsDtdEUKphNCCCHEma9rQnnDXbCa4zhUVVWhrq4OY8eOxbBhwwas3xeu4zdC+osfFyuVSmRkZIAxhu7ubiGYXldXB+CfJDO9Xg+1Wj1oxluB4Bj/4cdF/LjJZDIJ+/DBdH7cRMF04g8KnpNBw3FFZm8yJxxXd58yZYoQEPNkMGae96dMS7hyPJcSicRl4Uc+I7ixsVFUXiM+Pt6njGAy8AZrZ04ulyMxMRGJiYkA/qnb39bWhtraWuzcuRNqtVrouOr1eiGY7q5si688BdMdV6WXSCQUTCeEEEKISKDKtDhzLtvS09ODkpISWK1WzJw5ExqNxu/n8Kc9pG+DsU/eH4N1/OFMIpFArVZDrVYjMzMTjDF0dXXBYDCgtbUVNTU1wvubD7Qrlcohcex94ZOVPGWmOwfTndeZomA68QUFz8mg4GsHsD+ruw+24DlfpiUlJQV5eXlhX6bFH861qvnyGq2traKMYD6Qrtfr/V6xnATOUOm8Otftt1gsQhZIdXU1jEajsAguX1IqkNwF0/kbinxmunMwXS6XD4nXnhBCCCHeccw2D/Qi5I6Z5+EwFqHMcxJpJBIJNBoNNBoNhg8fDo7j0NnZiV27dqG7uxvbt293mbEdGxs7JMcDnpKVPAXTOY4TgulSqdRlRi8F00lvKLpEwh4fHLLb7X1+oDmu7j569GhkZWV5/QEYzp0vx7ZxHIfKykrU19cP2jItvfHmHDiX1+Azgg0GAyorK2EymYQgZlxcXL9WLA+2SPpiHirBc2fR0dFISUkRFh82m83Cddjc3AybzYY///wzaNchn0HBcwymu8tM5zuGQ/FcEEIIIZHOeU2oQAfOgSMBJ7vdjvLycuzfvx/jxo0L6VgknMdv4SxSXrNI6PNKpVLodDooFAokJSUhLS3N7Yxtx7KTsbGxoW52QHg707e3YLrZbIbJZKJgOukTBc9J2OLr9NlsNq/KtJjNZpSUlKCnp6dfq7uHa+Y58E/benp6UFxcDJvNhlmzZkGtVoe6aQHjzxeTc0awyWQSgpi7du2CzWaDTqcTyryo1eqQlraIlA4rb6gGz53FxMQgNTUVqampiI2NRVdXFxITE2EwGFBeXg6LxQKtVisKpgfyOvQmmC6VSl0WII2Ec0MIIYQMZc5rQgWrn8txHGpraxETE4NZs2aFvGTkQAbPbTYbWlpaoNPpqFzkIBCp4y3nGdt2u10Ipu/fvx+7d+9GbGysKDN9sF7P/FoOvnK+scgH0+12O+x2O8xms9sFSINxQ5IMHhQ8J2HJ1zItzc3NKC0tRUJCAiZPntyvkh3hnLkgkUjQ0tKCqqqqgE+NHIpfALGxsUhLS0NaWhoYYzAajUIwvb6+HgBEd99VKtWQfB3CRaQEzx0xxiCXy0XXYU9Pj1Az/cCBA8JNHb1ej/j4eGg0mpAE051rpkfauSKEEEIGK1/XhPLHgQMH0NraCr1ej2nTpoXFGivuFjANho6ODhQVFcFms8FisQhr3lC5yPAWSX1aT+MtmUyG+Ph4xMfHAzhyE6itrU1YfJQvf+p4PfNrOIU7juMC8t7ztM4Un8jJ/965ZjoF0yMLfcqTsMPX6fOmA+hYwiQvLw8ZGRn9/gCTSqVC3eBwwnEcOI5DRUUFJkyYMOTKtDgL9A0MiUQClUoFlUqFYcOGgTGGzs5OGAwGtLS0oLq62qUunEKhCGgbIl0kBs+dpxFKJBIolUoolUpkZGS43NTZt28fOI4TZkjExcUFfIaEYzDdsQyUxWIRZVhQMJ0QQggJf8FaFNSZzWZDeXk5Dh06hLi4OCQkJIRF4BwIfvITYwz79u3D7t27kZ2djWHDhomCj3y5SH5mYXx8PLRabdi8Pu5ESr8uXJPigsXbLGy5XI7ExEQkJiYCEJc/rampQXd3NzQajZBoFs43h/gFQwPNUzDdZrPBarV6DKaH8/ue+C883wUkIjnW6eM//Hv7MDQajSguLgbHcQEpYTJQmQu+4Mu0MMZw9NFHIzU1NdRNCpqB6shJJBJotVpotVpkZWWB4zi3deH4xUeDNZUtUjquvEg73r46sO5u6nR3dwud17q6OjDGRDMk1Gp1wF5Hx7p/fHsBCqYTQgghg4Eva0L5o7OzE0VFRYiOjkZ+fj6qqqrCarwklUqDFiS12WzYtWsXDh8+jClTpiAuLg4Wi8VlzRt+ZmFrayv2798PjuOC1n8jvomk172/yUrO5U/5NZza2trCfi0xb2ue+8uXYLpjaUwKpg8tFDwnYYHjONhsNq8zJxobG1FWVob09HTk5uYG5AM8mJ2v/mhubkZJSQlSUlJgNBqDtrBHJHUq3HGuC2ez2dDe3o7W1lbRVDY+mB6Iu+/hdJ0NhEjNPPflc0kikUCtVkOtViMzMxOMMXR1dQnB9NraWkgkEuEaDHS5IXfBdP6f2WyGxWIBAAqmE0IIISHk65pQ/jyPY8Z1Tk6OsKBeOPVjg5V53tXVhR07dgg3DWJjYz3eNFAoFFAoFEhPTxeSIVpbW4X+m+NYIz4+PixmuIbTOQyWSDhGR4Eabzmu4QSI1xLj13BynCkbypkW/a157q++gumA+zETBdMHNwqek5ByrNPHf+D39qHPr+7e1NSEiRMnCnf8AyFcFgx1LEUzbtw4ZGRkYMuWLRHTAQj1ccrlciQkJCAhIQEAYLFYXKZm8nff+amZ4XL3PVxFavDcn3qBEokEGo0GGo0Gw4cPB8dxLuWGZDKZqD6hUqkMaDDd3ar0fDDd00I6tCo9IYQQEhwDVabFarWirKwMBoMBU6ZMEfrEQPjN1A1G8PzAgQMoKytDVlYWRo0a5VPAyzEZgu+/dXR0wGAw4ODBg9izZw9iYmKEccRgXqyRhJdgjbec1xLjZ1rwC5DyazjxY5JAr+HUm4HKPO+Lp2A6v84UQMH0oYCC5yRknDuAfQXOOzs7UVxcjKioKOTn5wf8rn04LBhqMplQXFwMq9UqKkUTDm0LtnANuEVHR4umsjnefS8rKxN1GPhFH/s6lkgLJkfa8QKBP2apVAqdTgedTgcAosFYU1MTKisrRbX79Xo9FArFgATTTSaTaJ+oqCghoE7BdEIIIcR/vqwJ5Y/29nYUFRVBqVQiPz8fMTExot+HY+Z5oIL5jklakyZNQlJSkt+PKZVKodfrodfrMWLECNjtdrS1tYlmuNLio8ETSX3QgRhv9bWGU319fVDLTjoLVs1zf7kLpvMJo3xmukQiEQXT5XJ5WB4L+Qd9MpOQ8KVOH2MMDQ0NqKioEE0bDLRQZ57zZVqSk5Mxbtw4UTZzMIPnfAAsXIRTW9xxvvvu3GEAIOowBLK0xmAVicHzYGdCuBuM8cF0vnZ/dHS0aCHcQJZ+8hRMt9ls+PHHHzFz5kxER0e7XUgn0q4FQgghpL8c14QCgpdtzhjD3r17UVlZiVGjRmHEiBFun0cqlQrBn3AQqDFSd3c3ioqKIJVKPSZpBeJ1l8lkLjNc+XHEnj17YDabg774aKT0wyJt/BGK43W3hpOnspP8v0DOlA2XzPO+8PXQeY7BdIvFIoyrKJge3ih4TgaUr3X6rFYrdu7ciba2Npdpg4EWqmmIHMehqqoKdXV1QpkWZ6EO7A+Ewfjl4K7D4FxawzEbOC4uLizqHA60cL8hEgwDXYPPsYQLcCR7il8Id//+/di9ezdiY2NFN3acs8n8wXf6+PdxVFSU8LnFZ6bztVIpmE4IIYT0jQ+u8GOAvmbp9pfFYkFpaSk6Ozsxbdo0oS/hTriVbQlEJvzBgwexc+dOZGRkIDc3t88F3wMpVIuPRkrfPJL6mOGQhd1b2cnm5mZUVVVBLpeLrml/ZsoOluC5M2+C6VKp1GUB0lCf30hHwXMyYHyt02cwGFBcXAyNRoOCgoKg14MLxTRET2VanEVC2ZahQCKRQKvVQqvVIisrCxzHCQFMPhs4JiZGCLpbLJaIqHMYaZkfQOg7sDKZDPHx8YiPjwdwZCHctrY2tLW1oaGhAbt27YJSqRRNEw7EtcgPqB2zJRwz0zmOg9lshslkomA6IYQQ4gb/fVlbWwuVSoW4uLigfTe2traiuLgYer0eBQUFfa7XEo5lW/rbHo7jsHv3bhw4cCDga2n112BcfDRchdN1OhDCcbzlWHYyOzvbpezknj17/JopG6oFQwPN22C6c830cDvfQx0Fz8mA4DhOuHuekpLSZ5mW2tpaVFdXY/To0cjKyhqQD4aBzqRwLNOSl5fXa327SAqeD6XjdOzgAkcCmO3t7aisrERHRwd+/vlnqFQqYcGgoVrnMBw7c8EWbpkQcrkciYmJSExMBHBkVg+/EO7evXvR1dUlDND5a7E/C57a7Xa3mXHO2/hgut1uh91u97gAabCy7AghhJBw5JhsdPDgQaSkpAg3wgP9PNXV1aitrUVubi4yMzO9+r4Nt9mw/R0jGY1GFBcXgzGG/Px8KJXKILTOP7T4KPHFYAgkuys76W6mrGMwvbdrOtTJSsHiGEznP984joPFYhGSkHp6epCamkrB9AE09KI0JKzwwRGr1YqWlhYwxpCamupxf7PZjJKSEvT09GD69OnC4ngDYaAyKRzLtOTl5WHYsGF9/k0kBM8j4cNeLpcjISEBTU1NUCgUyMjIEAKYlZWVMJlM0Gg0ojqHjnehB6tIDJ6H+zFHRUUhKSlJWAzLYrEI12J1dTWMRmO/FrDy9qaBp1Xp+bJe/O+da6ZTMJ0QQshQ5bwmlEwmC0qg2mQyoaSkBCaTCTNmzIBWq/X6b8NtTNKf9hw6dAilpaVITU3F2LFjB01f2znwyCfl0OKjnkVSnzHcxx7ueJopy68lVlZWBpVKJSrz4pjcE27JSsHgOJMXgDAjZf/+/YiPjxclIFFmenBF9qcpCSqO42Cz2YQyLTKZDBaLxeP+zc3NKC0tRUJCAiZPnjzgX/YDkUnBl2mxWCyYOXMmNBqNV38Xbh1VEhjR0dFITk5GcnIygCPXB7/ASllZGWw2G3Q6nRBM12g0g/JLcDB25vw12Dpzztei2Wx2e2OH77zq9Xq3g02O4/o1CPUUTLfZbLBarR6D6YPpNSaEEELc8bQmVDDGJvzM16SkJEyZMsXn8dZgzjznOA6VlZWor6/H+PHjkZ6eHuTWBReflOPr4qOR0iePtLHzUBhv9TZTtra2Fjt37hTdIOJvNEYSvloCPyZyzEw3m81CvI2C6YFHwXMScI41mvgPcT7o4a6z5diRycvLQ0ZGRkje2MEOUB8+fBglJSVITEzE1KlTfeqsRkLwnD/nQ/04exMbG4u0tDSkpaWBMQaj0Sh0guvr6wFAdOddpVINii/BodCZ89VgmDrZm5iYGNECVvyNnba2NlRUVIgGZHq9HjqdDjKZLGCdWF+C6Y4L6Qzm15wQQkjk6W1NqEAGqjmOw549e9DQ0IBx48YhIyOjX48TbguGetseb9eZGsy8XXzUbreju7s7YIuPhqtIG38MxeN1N1OWHxtXVlbCYrGgoqICiYmJiIuLE8YjQ53jeMsxM91xnSnGGMxms8fSmJF0Iy1QKHhOAooPbthsNgDiOrfuOoB8vTmO40LekQlWJgXHcaiursbevXu9LtPiLJjBc/rQHHjedG74RUVVKhWGDRsGxpiwWnlLSwuqq6shl8tFNeHCddGgodiZ68tQq8HneGMH+GdAxi+Ga7VaodVqERMTI9xADWQgu69gOuA+w4KC6YQQQsIVX9rSMdvcUaDGJoEcb4XbgqHetOfw4cMoLi5GcnIyxo0bFxHBNcDz4qOtra3YvXs3KisrafHRISQSxlvON4h+/PFHpKSkwGg0ory8HBaLRUju4YPpQ3Es0NtMX8f4m3Mw3WQyCfvwwXTH2bxD/frxFwXPScA41ulzDHLwnDuAjY2NKCsrQ3p6OnJzc0PekQlGJkV/y7S4a1s4dVSDKVKO01cSiQRarRZarRZZWVngOE5YYKWxsREVFRWIiYkRFgwKp0WDIqEz52ywlW3xlfOAjA+mHzx4EBaLBT/99JNQciguLg4ajWZAgun8qvQABdMJIYSEJ8dkI36mmrt+UiCC5wcPHsTOnTsDNt4Kx8xzT2MHxhiqqqr8SmAaKhwXH62rq8PEiRMBwGXx0XAcR/gjksYfkTjeYowhKSkJKpVKCA7zyT0HDhwQlUANxngkVHyZ6UvB9MCh4Dnxm6c6fc74DqDdbkd5eTmampowceJE4c5hqAU6k8KfMi3OIiV4Th/Q3pNKpUJHAIDbRYNUKpXQCQ7lokGR2pkbCp0zb0gkEiiVSiiVSqFTlpeXJyo5xBgTFrniO6+BvCbcBdP5G7p8ZrpEIhEF0+VyecRdl4QQQkLLeU2o3gIU/gTP7XY7du/ejcbGRkyYMAGpqan9brNzm8JpTOJpjGQ2m1FcXAyz2exXAtNQxPeXtFqtV4uPxsfHQ6fTDbrFR8PpOg02Phgaaf1ax2QliUTiktzjWAK1oaFBKF3Ej6EHa+mi/q4xBXgfTHe3ztRgfK0CaXB9ApKw01udPmdSqRQWiwW//voroqKikJ+fH1bTwwKVSeGc5RCIGu5UtoX0xd2iQe4WfHRcNGggZ3tE2nU21Mq2eIvvzDmXHOrq6hKux7q6OgAQLT4a6M4r3+njOQbTLRaL0HHkO4V8xzASzxkhhJDg87QmVG+kUqlQCtMXXV1dKCoqgkwmQ35+PpRKZX+b7bZN4ZZ57tye1tZWFBcXIy4url+Lokai3hYfdVzrhk/K4RcfJeGBjxNEUj+Wf997ug7dlUB1HI/U1tZCIpEMyvXE7HZ7wMbxnoLp/AKkJpMJUqnUZUZvJAbT6ZuE9BvHcbBYLL1mm/MYYzAYDOjo6EBOTg5ycnLC7gs3EJkUJpMJJSUlAc9yCLeOajBFQpbAQGQGREdHIzk5GcnJyQAgmsZWVlYmmsYWHx8f8ExgR5GeCRFJ3GVCSCQSaDQaaDQaZGZmiur3t7a2oqamBlKpVNR5VSqVAx5Ml0qlLguQRtp1SwghJPB6WxOqNzKZzKf+P2MM+/fvR3l5OYYPH47Ro0cHvC8SbrNhHdvDGENNTQ1qamqQm5uLzMxM+h73oK9z2Nvio/v27RNl8MbHx4dl0DGSxh+RGDznj9mX8iWO4xGO49DV1SVaT0wmk7msJxaOrynHcUErq+T8/cQH0+12O+x2u2gB0kgLplPwnPiMf/PwmRN9vVGsVit27tyJlpYWKJVKjB49egBb6z1/A9QtLS0oLi5GQkJCwLMcgt1RDZcPunBpx1DkuOCj8zS2+vp6AAjKnfdInUYYiccMeHfTwF39fj6Y3tzcjKqqKsjlctH1GOjOq7fBdOea6ZF4TgkhhPRfX2tC9caXsYnNZkNZWRlaWlowadIkJCUl9bfJAWvTQODHSBaLBSUlJeju7sb06dOh0+mC+nyRxtPio3wGL19Oks9MD6fZ5ZEgEoPn/OdQf4+ZL13kOB7p6OiAwWBAU1MTKisrERUVJcySDafr2pea5/7ytM4UX7aZ/z1f5sWxNOZQux4peE584kuZFuDIIiTFxcXQaDQYN24campqBqqpPutvZygYZVoC1bbBKFKOM5RfJu6msfHBS/7Ou1wud7nz7u9zRpJIzTzvT2dOKpVCp9NBp9MhOztbWAy3ra0NTU1N2LNnD6Kjo12C6YHkGEznP4P42VWeMiwomE4IIcQTb9eE6o23JSXb29tRXFwMhUKB/Px8xMbG9rfZAWvTQJFKpTCZTPjll1+g1WqRn5+PqKioUDdrSHNcfHT48OGioGNjYyMqKirCYvHRSEpkieTgeaDGW/wsWH4dALvdLoxHHK9rx/FxTExMQJ7bV/7UPPeXp2C6zWaD1Wp1CaY7lsYc7NcnBc+J1/hsc2/LtNTW1qK6uhqjR49GVlYWWltbw6qz5Ywv2+LLFy2/GI3JZArqYjSREjwf7B+og5W7TOD29vaAdIIjsTPHf45EYvA8EJ05x8VwHTuvztejYyZIIAMFjnX/AAqmE0II8Y2vyUae9JXlzRhDXV0dKisrMXLkSIwcOTLo30PhtGAoYwxtbW1oaWlBbm4usrKy6HvYC4F+jZyDjjabTbTOzVBYfDTcReJ4y9/M877IZDLEx8cjPj4eAIRFdfnFR3ft2gWlUimMWfR6/YDdJBrIzPO++BJMdyyNGS7t9wV9apE+Odfp66sDaDabUVJSgp6eHtG0uXCb5ueMPyZvg+fBLNPirm3h0lEl/gv3c+kYvAT+6Sy0trYKnWCVSiUE0/V6vcfrPxI7c5F4zLxgZNz31nndt28fysvLoVAoRJ3XQGaCuAum8//MZjMsFguAI++bbdu2QS6X4+STTw7Y8xNCCBk8fFkTqi+91Ty3WCzYuXMnOjo6cMwxxwh9tmALl/EcXxbUYDAgLi4O2dnZoW4S+f/kcjkSExORmJgI4J/FR1tbWwd88dFI6Yv7Wv97KPCmfHAgOS+qa7VaRYuPdnd3CzeJ+hof+yucZzj3FUwHjlynZrMZr7zyCm677bZBM1uIguekV3ydPsc7e719QDU3N6O0tBQJCQmYPHmy6AMjXDpbnvBv8L4+jBhjqK6uRm1tLcaOHYthw4YF/UM7koLnkXKcg4lzZ8FisQidhcrKSphMJmg0GiGjRKvVumTtRkrnFQj8NMLBxG63B70D5Hw9ustwCmYmiKdV6Rlj+Oijj6BSqSh4TgghEcbXNaG84WnsxJfF5MuUDGRJjHAo29Le3o6ioiKoVCpkZ2ejs7MzpO0ZjAZyvOVu8VG+XnowFx+NpDFlJB0rL9QB5KioKCQlJQnrSziOj6uqqmA0GoXxMT8eCVSplVCWbfGVp2D6oUOHcPfdd2PlypUhbqH3KHhO3HJcPM2bzAmO41BZWYn6+nqPdb+lUqkwfTEcOQbPPXHMqp8xYwa0Wu2AtC1SgueRFGAdzMcaHR2N5ORkJCcnAwBMJpOw+GhZWRlsNht0Op2QTQIM7uP1VSRmf/BC0ZF1znDylAnCD8z0en1AA/yOwfTu7m7hfUEIISQyBKpMizPn4DljDDU1NaiursaYMWNCUqYklGVbGGNoaGhARUWFUKamvr4+IsZIQ4lCoUBGRgYyMjLAGENXV5cwjgj04qORMv7gZ85HyvECR8Yc4XS8zuNjs9ksXNeOMy74YLpjspmvwqlsi6/469RoNEKlUg2q46DgOXHhawfQaDSiuLgYHMdh1qxZUKvVbvcL98xzx7It7rS0tKCkpATx8fEuWfUD0bZgdQwtFgva29uh0+kG1YfXYDbUOvmxsbFIS0tDWloaGGMwGo1CZ6Gurg4AsHPnTqETHKiMknAV7Bp84SwcMiHcZYIYDAa0tbWhurpalAnC1+gM1Oc5H6gnhBASGRyzzQMdvHIcOzkn8PBlMQdaqDLPbTYbysrK0NraiilTpgizzyIlwWiokkgk0Gg00Gg0osVHW1tbA7buUiSIpMVReaHOPO9LTEwMUlNTkZqaCuDIjAt+fHzgwAHYbDYhmB4fHw+NRuP18YTDeMtfXV1dgy4mQMFzIsJnm/N3s/q6mBsbG1FWVob09HTk5ub2+ibuz4KcA4lvk3OHMBRlWty1LRgdVYPBgKKiIqGefTCmzPkqkjo6Q5FEIoFKpYJKpcKwYcNgMpnwyy+/QKfToaWlBdXV1ZDL5aKVyv3JKAlHkRw8D8dMCOfpwo6ZIHv27IHZbBZNq9TpdP3ukBqNRgqeE0JIBHBeEyoYWZ988Pzw4cMoKSlxWxZzoDlOvR+ofk5nZyeKiooQExOD/Px80bom4VBGZrAJ5/6p4+KjgPvSfLT4qKtwja8EU7gHz50pFAooFAqkp6cLyWb8tc2XL+JnbsfFxUGj0Xg8p+E43vKV0WiEUqkMdTN8Qp80BMA/dfpsNptXZVrsdjvKy8vR1NSEiRMnCkGJ3vDBiHC9U8Z3eh2Dt6Eq0+Is0CVvGGOoq6vDnj17MHr0aKSmporqz9XU1AgBTn6hvkAuwOdJpH3pR5KsrCxkZ2eD4zhhsUd/M0rC1UAvYBNOBkNH1jkTxLHsUHl5OSwWS7+nVXZ3d0OlUgWz+YQQQkLMeU2oYH7vmc1m7Nixw2NZzIHmWOZyIMZz/MLg2dnZGDVqlNuyoJR447vB8pr5u/hoqN8vAyUSg+f8eGswckw248sXdXd3u8zc5hMbnWduh2s8zReUeU4GJV/LtHR2dqK4uBhRUVHIz8/3Omt0oDtb/eE4PZIv0xIXFxfyLI9ATkm02WwoLS1Fe3s7pk2bBp1OB4vFArVaDbVaLUyZa29vR2trK/bv34/y8nIolUpRgJPu8vtnMH1R+MN5wVC+jmFcXBwA9xklKpVKuNaCuVJ5sIRbDb6BNBiC586cyw719PQI16TztEp3AzNHVLaFEEKGLl/XhPJHT08PysvLwXEcCgoKwua7pa8yl4Fit9uxa9cuHDp0CJMmTRJKsblrz0AHgiMxUBkufFl8lC+nFAkicewxlI5ZIpEIsZjMzEwwxtDZ2SncKKqpqRHG0Hq9Hna7fdAf+2AcMw2uiAQJOL5OnzcdQMdFWrKzs5GTk+NTkMSbBTlDjQ+eV1dXo6amBrm5ucjMzAz5h1OgOoadnZ3YsWMHFAoF8vPzER0d7fZ8OAc4+QX4WltbUV1djZ6eHlGNrt6CSb6KhE5OJBwjr68BhruMEv5aq6yshMlkEkpq8NdauN584w3mTAh/2e32sD8/vZFIJFAqlVAqlaJplXzN9H379sFutwtTivlplXzmWyA7guvWrcOHH36I3bt3C5/ZDz/8MHJzc4V9TCYTbrnlFrzzzjswm80oLCzE+vXrvZoNRgghxHvBWhTUnaamJpSWliIhISHsyoENxHiuq6sLRUVFkMvlKCgoQGxsrMd9qeZ5ZOtt8dH29nZ0dXWhvb09IIuPhrNIvKEzGBN2vCWRSKDVaqHVapGVlQWO44Rg+qFDhwAAf//996Aug8pnng8mFDyPUI51+rwpMWC1WrFz5060tbWJFmnxhaea4uGmrKwMVqs1pGVanAWiY7h//37s2rXL47TH3jgvwGcymYS7/KWlpcJdfn8XhIy0L/1I4Gtnznmlcr6kRmtrK8rKymCz2YR6cPziKuF23QylTAhfDbWOrHMNf+dplfX19Vi9ejWio6NRUFAAuVwesPp9P/74I5YuXYpp06bBZrPhzjvvxMknn4xdu3YJnc2bb74Zn332GTZv3gydTocbbrgB55xzDrZt2xaQNhBCCPF9Taj+stvtqKiowIEDBzB+/HhotVohUBIugj2ea2xsxM6dOzF8+HCMHj26zz4FBc8Jz3nx0R07dkCtVkMmkw3ZUpE8Cp4PbVKpFDqdDjqdDhkZGdi6dSvGjh2Ljo4O0bXtGEwfiJK7/jAajRQ8J+GP4zjYbDavMycMBgOKi4uh0WhQUFDQ7y8ZiUQiKosSblpbW2G1WiGTyTBt2rSwKhXhT8fQbrdj9+7dOHjwYK/THn0RGxuL9PR0ITOTv8vvuCAk3zHxtV46dYCHFn87c84lNfgsYD5wCXiuBxcqkdSZczbUj93dtMp169bhm2++wbZt21BdXY0zzzwTJ5xwAo4//ngcf/zxGD9+fL9eky+//FL088aNG5GcnIy//voLs2fPRnt7O1599VW89dZbOOGEEwAAGzZsQF5eHn777TfMnDkzIMdMCCGRytc1ofzR3d2NoqIiSKVS5OfnQ6lUoqenB4yxsAqMBatsC8dx2L17Nw4cOICjjz5aSKLwpj00dvBNuFxLwcYnQKSnpwPoe/FRvV4/aGdPhtNnxECJ1Jm+fCwtISFBmLltt9uFa7uhoQG7du2CUqkUyryE440iKttCwppjnT7+A7avMi01NTWoqanB6NGjkZWV5feHcjgGzx2PMyoqCjk5OWEVOAf63zE0Go0oKiqCRCLxqT69r21zvMvvrl66SqUSdUw8vb6R9KUfKccayM6cuyxgfgqb442bUE9hi9TOHDD4y7b4SiKRYObMmZg5cyY4jkN8fDxeffVVVFdX4/PPP8cdd9wBpVKJk046CW+++aZf74X29nYAQHx8PADgr7/+gtVqxbx584R9xo4di+HDh+PXX3+l4DkhhPhhIMu08LNDMzMzMWbMGKEPwf83nAJj/PgxkOM5frwCQLhx4Et7wm1sORhEwg0H52P0d/HRcBaJY4+hnrDjCV/v3PE7QSaTISEhQagO4WlNMX58rNfrERUVFapDAHCkbAsFz0lYcu4A9hU4N5vNKCkpQU9PD6ZPnw6dTheQdoRb8NxisaC4uBg9PT2YMWMGiouLw7Iz0Z/g+aFDh1BaWoq0tDSMHTt2wL5c3NVL5zOF+RrWg7VjEijheI0FU7AGfO7qwbW3t8NgMIR0eiaVbYms9zPPbDaD4zgce+yxOO+887By5UpYLBZs374dFRUVfl0THMdh+fLlKCgowIQJEwAABw8eRHR0NPR6vWjflJQUHDx40J9DIYSQiObLmlD+sNls2LVrF5qbm91mW/Pfp3y5mHDBr/MRCHx99/T09H6NVyjznPSXL4uPxsfHh8XsVk/C6QbbQInU8RbHcX0mKnlaU8xgMKC6uhpGo1FYUywuLg46nW7Ak0f5NgwmFDyPAL7W6WtubhYWqZk8eXJA30jhFDxvbW1FcXEx4uLiMGnSJERFRYVtB8yXdjHGUFlZibq6OowfP16YqhYqUVFRohrWPT09wl1+vmPCf3BzHBc21wcJjIHszDnfuOlteiZ/1z0YHYVIzP7gRXLwvLu7GwBE9fv4WugFBQV+PfbSpUuxc+dO/Pzzz349DiGEEM8c14QCgptt3tHRgeLiYuF7wt2imAOxOGd/BGI8x3Ec9uzZg4aGBkyYMAFpaWn9bks4jt1I6Pk6Bult8dGamhrIZDJRQk44LdAYqcHzSBxz9OdmqvOaYmazWbi2+VkXzsH0YM8k7u7uRmpqalCfI9AoeD6E+Vqnj+M4VFZWor6+Hnl5ecjIyAj4h3A4BM8dy7Tk5uYiMzNTOM5waJ873gbPzWYziouLYTabMXPmzLC8m6dQKKBQKET10ltbW9HS0iIsTJuQkCB0TsJ9sQvSu1B25jzddW9tbRVmQWg0GtEsiEB0FCI5E4IxFlFlWxx1dXVBIpEEbMFQ3g033IBPP/0UP/30E4YNGyZsT01NFa5px+zzpqamQdcZJYSQUOOTjfhxQF+zdPuLMYaGhgZUVFQgOzsbo0aN8vg84Ro897dUSk9PD4qLi2G325Gfn+/XonHhmvgUziKxj+ord2VJOzo60NraKsxujY2NFZWKDGVNaQqeR45AHHdMTAxSU1OF8UJPT4+QcFZeXg6LxQKdTidc28GoFNDd3U0LhpLw4GudPqPRiOLiYnAch1mzZgWt/lCog9MWiwUlJSXo7u52W44mXOvmedMxNBgMKCoqQlxcHKZMmRJ2ddvdceyYZGVlYdu2bcjMzITVahUWu1CpVEJwM1iZwgMtkjo44XSsznfdTSaTMAviwIEDsNlsQkchPj4eGo2mX22P5M4cgIg8duCfhW8Cdb0zxrBs2TL897//xZYtWzBixAjR76dOnYqoqCh89913OPfccwEAFRUVqK+vx6xZswLSBkIIGeoc14QKdpkWPkmkra0NU6ZMEerTehKM+uKB4E+2d3NzM0pKSpCSkoK8vDy/b7gPZPA8WDdUQiESbjgEcgwilUqh1+uFZAVPs1sdx6wDmUwSTuOtgRKpM32Dsb4Un9yYlpYGxphQKYAvYWS324USRnFxcVCr1X6/9rRgKAkLHMfBYrF43QFsbGxEWVkZ0tPTkZubG9QP+lAGz/ngsl6vR35+vttFEsJ16l9vrxtjDHV1ddizZw/GjBkTkIVdQ4UPpsfFxSEnJ0eol+6YKczXS+eDm5H4pTmYhHNnLjY2FmlpaUJHwWg0Ch2F+vp6ABDVOlQqlV4dSzgfczBR8Lzb62vEG0uXLsVbb72F//3vf9BoNEIdc51OB4VCAZ1OhyuvvBL/93//h/j4eGi1WixbtgyzZs2ixUIJIcQLfLJRRUUFGGMYM2ZM0L6/29raUFxcDLVajYKCAq+zVEOdeOROf9rEcRyqqqpQV1eHcePGISMjIyBtocxzEgreLD7qnJATzP5xJM56jcRjBryree4PfhatUqkUShh1d3fDYDCgra0NdXV1YIy5BNN9PRdGo5Eyz0no8GVarFarcCeut4vYbrejvLwcTU1NmDhxorBYRjCFogPIGENtbS2qq6sxZswYDB8+vNfpkeHWQQU8dwxtNhtKS0vR3t6OadOmCbWeByvn8+KuXrrzQi78h7YvwU0ycAZLIFkikUClUkGlUmHYsGFgjKGzsxMGgwEtLS2orq6GXC4XTc/0VOuQMs8j79iBwE8/fP755wEAc+fOFW3fsGEDFi9eDAB44oknIJVKce6558JsNqOwsBDr168PWBsIIWSoclwTCjiSFR6sMi179+5FVVUVRo0ahezsbJ+eJxzHJr5mw5tMJpSUlASlrGQ4ZuaT8DFQYxBvFx/lM9MDvfjoYBlvBVKwg8jhaqAXkJZIJFCr1VCr1cjMzHRZD6C2tlaYmcGPkb2JyVDmOQkZjuNgs9m8LtPS2dmJ4uJiREVFIT8/f8AWvJBKpUIbB0JfZVqchWv2grt2dXZ2YseOHVAoFMjPzw9pnbVA6u31d7eQS2trKw4fPozq6mpERUUJgfRwr5ceKR2cwdqZk0gk0Gq10Gq1yMrKAsdxaG9vh8Fg6LPWYSRPIwzmdPdw19XVFdDBkDffRbGxsXjuuefw3HPPBeQ5CSFkqHO3JlSwAtRmsxmlpaXo7u7GtGnTROtTeCscg+e+zNRtaWlBcXExEhISglJWMlxnDYezSOmnhfK68LT4qK8JOd4arOMtf3Ac57aSwFAX6psG7tYD4BPOmpubUVVVJbq+9Xo9FAqF6Prks9kpeE4GFF+nb9++fbBYLKLFLz3t77hITU5OzoAGeQayA+hNmRZn4dhBBVyD5/v378euXbv6XGjIl8cPB760w7leut1uF4Kb4V4vPZI6+UOlMyeVSoVOAOC51mFcXJww+yfSRGrGPc9oNA66TiAhhEQST2tCyWSygCf3tLS0oKSkBHFxcV6PQ9yRyWRhNzbxJtubMYaa/8femYc5UpZr/87W3ekl6fS+7+vs07N2z4AzDtucwy7K4oIignjUIyCoCCqyeI58Kooy4hFlFDwoHkaRVUBwWIaBmemk03t637cknc6+VX1/jFUk6XRnq6pUkvpdl15Md1L1VlJd9bx33e/9jIxgZGQELS0tqKioYKUe5Nr4lAw1bSrBh+8rkuajeXl5yM3NjdgUlyzzrUhIVbMS3+ZbYrEYSqUSSqUSNTU1foazubk5DAwMIC0tDSqVCsPDw9iwYQPq6upgtVoZXYV0/PhxPPTQQzh9+jRmZ2dx7NgxXH755fTvP/vZz+Lo0aN+77nwwgvx8ssvh70PfihJAlFBkiQ8Hg88Hg8sFgusViuqqqrWfH2kTWrYgAtxOpKYlkD4uvSPKgy9Xi/6+/sxNzeHbdu2obCwkJHtU0VnIt90JRIJnYUemJc+ODjIefacwFmSVUQOlnW4vLxMr4TweDw4deoU/fBGoVAk/dLCeDsh4o3FYkFmZma8hyEgICAgEAQq2jJYTygm5ycEQWB4eBhjY2OMiMZ8NPaEcntTK39tNhv27NkDhULB2lj4umqY76TCZ8bXY1yv+ejo6CjtyI2k+WgqCsl8E5G5guvYlkgJNJz5GhwfffRRnDhxAiUlJcjIyMDbb7+NxsZGRuKjrVYrtm7dihtuuAFXXnll0NdcdNFF+O1vf0v/O9KUAkE8T1B8c/oox8R6hZXRaIRGo0FOTk5ETWqYhu0C0OVyQavVwmKxhBXTEghfl/6JRCJ4vV6cPHkSIpGI06gdrmHq818vL31ychIkSfpFvAh56eyQKk6ItLQ0+nxLS0uDzWZDfn4+DAYDZmZm4PF4Vj28SbbPhe/FHNsk4vJDAQEBgWTH12y0Vk8oppznDocDGo0GLpeLsWxvPorn65mNfFf+tre3sx6rwLV4zsd5osDaJEKtzUTz0VSZb/kiNAxNDHwNji+99BIMBgNee+01fPOb38Tvf/97fPvb30ZraysOHjyIj370o/jIRz6CvLy8iPdz+PBhHD58eN3XpKeno6SkJNpDEcTzRCNYTt964rnvkrnGxkZUV1fH9SLDZgFIPSBQKpVRL4/kq/N8ZWUFFosFVVVVaGlpSVqBis1zMzB7LjCbSyaT0UJ6Xl4eqw+YUqnASaVjpaAy+EpLS1FaWgqSJGGz2ejGKhMTEwBAN1ZJlma3qeoAoRDEcwEBAQF+EW5PKCbmJwsLC9BqtSgqKsKOHTsYiwrko3gezGxENUbV6XRoamribM5JieepWG8KJCe+zUdJkoTdbqfnEGs1H03F8z9V5x2JblbKy8vDv//7v+PGG2+EVqtFWloa/vnPf+If//gH7r77bthsNoyOjrKy7zfffBNFRUVQqVT46Ec/ivvvvz+iNA5BPE8g1srpA4I7JpxOJ7q6umC326NyYbMBGwWgbxf7WB8Q8M15TpIkdDodxsbGkJ6ejg0bNsR7SKzDxecf2AySWk5kMBjovHQqv5rKnkukJ7x8IhWLucClkyKRCFlZWcjKykJFRYXfwxu2GgfFg0RzQjCN1WpFVlZWvIchICAgkPJQPaGoHiQikWjdWiSWXHGCIDAwMICpqSls3LgRZWVl0Q47KHwVz33H5Ha7odVqsbKygt27d0fVGDVaUq3GZIJU+cz4NKePFpFIhMzMTGRmZq7bfDQtLQ1isRh2uz0h5xDRkKriOUEQvOnjFi02mw0AkJ2djezsbFxxxRW44oorAJyNwWSDiy66CFdeeSVqa2sxPDyMu+66C4cPH8aJEyfCnr8m9qeeQhAEAZfLFTSnDzhbxPiK54uLi9BqtcjPz8f27dt58wfGdNMb35iWaLvY+8KnAtXpdEKj0cDpdGLDhg0YGRmJ95BYJ17FnO9yIuDD5XJGo9FvuRz1hF/ISw+fVBTPQ4nIgQ9vfBurBDYOov4Xr6itSEh0J0SsWK1WXjykFhAQEEhlfGNaAIQUzoHV86hwsdlsUKvVAICOjg5WHqDyaW5C4btS12QyQa1WIzs7Gx0dHZzXK1TdkeoP8AWCk2xzkGDNR00mE52V/t5778XcfDRRSMWcd+DsfCvRv1OLxQKRSBT0QQ9bq3ivueYa+r83b96MLVu2oL6+Hm+++SYOHToU1jb4oagKrAkV00I5J9ZabkiJ0gRBQKfTYWJiAq2trSgvL+fVTSPa4jQYVEyLQqGIqYu9L3yJbaHyAlUqFdra2mAymVh7es6n84MvrLVczmAw0JEblKiZl5cHuVwufI5rkKrieSTXo8DGKr6Ng8bHx9HT00OvhKAaB/HlgagvqeoAobDZbCgvL4/3MAQEBARSlsCeUOHek6LJPJ+dnUVPTw/Ky8vR3NzM2v2Pj+I5Nabx8XEMDg6ivr4etbW1can3qH1y4TJ2uVzo6ekBQRC06SZRXb7J4MoORSocIzWHWF5ehlwuR2NjY8zNRxMFIfM8caHOy3h+f3V1dSgoKMDQ0JAgnicD68W0BCIWi+F2u3Hy5EkQBIH29nZeZq9S44wFJmNago2PKXE/GkiSpAtR37xAtuNk+HTj4VuhE2y5nNlshsFgwOLiInQ6HdLS0ugiOhyXcCoJyql0rBSxOiGCNQ5aXl6GwWCATqeDw+FATk4Ofb4plUpeiNbJUMzFgsViEWJbBAQEBOLAWj2hwiWSlbFerxd9fX2Yn5/Hli1b6Mb0bMFH8RwAZmZm4Ha7sWPHjqiauzEFV+K5yWRCZ2cncnJykJWVhfn5eQwODiIjI4Oux1QqFesNUgUiI1XmINR8K9gcwmAwrFpNvV7z0UQhVU07ybDSl5ozxfPvc2pqCnq9HqWlpWG/RxDPeQrlNg+3AFxeXobD4UBRURGam5t5K2DEWgBSMS1ms5mRmJZA4uk893g80Gq1MJlM2LVrF+1CpcbFN1GZDRKhwPGN3KipqYHX6w3qEk7GJ/zRkIriOdNOiLS0NBQVFdETdIfDQa+EmJmZgcfjWVUIx+MzT4ZiLhZsNpsgngsICAhwTCRmo7UI1zxjNpuh0WgglUrR0dHBieuYb+L5ysoKFhcXkZaWho6ODqSnp8d1PFyI55OTk+jv70d9fT0qKyvpeodaKWgwGDAyMgK73U6bG/Ly8qBQKFK6Loo3qTB3plhr7pGWloaSkhKUlJSE3Xw0UeZtqRrbkgxmJZvNhszMTEa3abFYMDQ0RP97dHQUarWavh7fe++9+NjHPoaSkhIMDw/jzjvvRENDAy688MKw9yGI5zwjMKcvVAFIuR9mZ2chkUh431AylgJweXkZarWajmlhI+spXg1DzWYzOjs7IZfLgx5bqojniYhEIkF+fj7dqZnKSzcYDKvy0ilhM9VIlCKMKdh2QmRkZKC0tBSlpaUgSRI2m40uhKlYodzcXFpMz8zM5OQ7SFUHCAW1BFFAQEBAgBtC9YQKl1DOc5IkMTU1hf7+flRXV6OhoYGz+x1fxHOSJDE9PY2+vj5kZWUhPz8/7sI5wK547vV60dvbi8XFRbS1tSE/P5+eowOrVwr6mhu0Wq2fMMllPRYKPoxBgFnCMSuF23zUt+cSn2OJUnXekQxmJavVyviDmlOnTuHgwYP0v2+77TYAwPXXX48jR46gq6sLR48exfLyMsrKynDBBRfgvvvui+g+JojnPILK6aMKpFANbij3g0wmw/bt29HZ2cnVUKMmmgLQN6aloaEBNTU1rN304+E8n56eRm9vL2pqatDQ0BD02FJJPE/04wwnLx0ADAYDcnJykj4vPRWd51w6IUQiEbKyspCVlYWKigo6VigehXCqFrEUgnguICAgwA3h9oQKF8o8E+w+5vF40N3dDYPBgO3bt9NCKVfwQTz3eDzo7e3F0tIStm/fjoWFBd7U62yJ51QzWJFIhI6ODmRkZIR8T6C5wWKxwGAwYGlpCcPDw5DJZLTDNy8vL+Gb/iUCqTIHiWa+tVbzUaPRiNnZWQwMDPg1H+VbLFGqzjuSwXlusVgYnzMdOHBg3fvAK6+8EvM+BPGcB1DFWrgxLSRJYnJyEgMDA6ipqUF9fT2cTie8Xi/vhapIC0CXy4Xu7m6srKywEtMSCJfOc6/Xi/7+fszNzWHbtm0oLCxc87WpIp7z+dyNhrXy0ru6urCysoKTJ08iPT3dryhJtkKa79ckNohnAxvfWKHq6up1C2Hqf0ydc8lQzEULtQIgFVeWCAgICHAJEzEtgVD3rkAxxmQyQa1WIzMzE/v27YuL0zre/ZgsFgvUajVkMhktIi8tLfFmXkKZzZh8wLC4uIiuri6UlpaipaXF75wI91zzFSarq6vh9XphMploM01vby8d85iXlwelUslpDcWX749NUuEYKZgw7lDNR6noWCqWiGo+2t3dzato0lRuGJroDw0S1XAkiOdxJtIC0O12o7u7G8vLy/TyMep91Pb4fBGJRDynYlpycnJYi2kJhCt3R6CbIZQTNFXE82SHEjbT09NRXV2N/Pz8pM9L5/s1iQ34VNSsVwj7nnPUa3JzcyGVRlcaeL3eqN+bDAgNQwUEBATYxddtHmqFbiRQ92zqPkaSJMbHx6HT6VBfX4/a2tq41TJUtnY8mJmZQU9PD6qqqtDY2Eh/TiKRKK6CfiBMzZNIksTQ0BDGxsawceNGlJWVMTC6s0gkElooB/wbOfb19cHtdvvFPGZnZ6dc/cw0qTQHYeNY+d58lE/zLS7xer0Jrw9YrVbGM8+5IHVnuTyAcptTuUWhLnhGoxEajQY5OTnYt2+fn5hM/QHxPQMpHHHat2BlO6YlEC5E6oWFBWi12qBuhniOiy+kynGKRKJ189L7+/vpQjrejSBjIZUKVwo+N7AJVghTza50Oh0cDgfd7EqlUkGpVIZ9LKlaxFIkqotCQEBAgO8E9oRiUjgHPhTPqQx1rVYLs9mMnTt30g+f40U8Yluonlrz8/PYunUr3bDcd0x8qteZmCe5XC50dXXBZrNh7969rK8kC2zkaLPZYDAYYDAYMDY2BrFYTAvpeXl5vMiXF+AvXMw9+NZ8lM/zLTbhu94XDok6ZxLE8zhA5fR5PJ6wY1pGRkYwMjKCxsZGVFdXr3q9r2OCT1lUgYQqAN1uN7RaLVZWVuJSsLJZoJIkCZ1Oh/Hx8YjdDKkinqeayBpIsLx06gk/lZfuG/GSCHnpqSieJ9IywrS0NBQVFdETY4fDQZ9zMzMz8Hg8YT/ASfXYlkQtBAUEBAT4TGBPKDZEA5FIBLFYDIPBgMHBQeTm5mLfvn28mFNxLZ5brVao1WqIxeI1V8fyIYfdl1jnSVQ8T05ODtrb20N+70zPyXz711RWVoIgCKysrMBgMGB6ehr9/f2Qy+W0kB7LKkFqf6lCqhwr1/OtSJuP5uXlhdU3IFxIkkxZ8TwZzEqJOmcSxHOOiTSmxel0oqurC3a7Hbt374ZSqQz6Omo7fCpkgrFesRWPmJZA2PoMnU4nNBoNnE5nVG4GyuGRCkJkKjwkCOcYfYuSiooKEARBN4Kcn5/H4OAg0tPTaSGdr3npqfB9BpLIxVxGRgbKyspQVlZGO6EoVwn1ACc3N5cuhDMzM+lrUjI4IaLFbreDJMmELAQFBAQE+EikPaFi3RcA9PT0oLm5GVVVVbypt7kUqufm5tDd3Y3y8nI0NzeveU/n25wzFvF8amoKfX19YcfzcFHXisVi5ObmIjc3F3V1dXC73atWCfoaGxQKBW/OVz6RSnOQeGsE4TYf9Z23xvJwkrr+pNp5T90XE92sZLVa476qKxoE8ZxDqJy+cAvAxcVFaLVa5OfnY/v27SGfMMe7oUw4BCsA4xnTEmx8TN9ojUYj1Go1VCoV2traonIK+HaST+abRDIfW6yIxWIolUoolUrU1NTA6/XShTSVXZ2Tk0MX0lw3HlqLRBaSoyWRnOfr4euEqqiooBveGo1GLC0trXKVeDyelPuuKaxWKwAI4rmAgIAAA7DRFHQtHA4Hurq6QJIkNm7ciIqKClb2Ey1ciOcEQWBgYADT09PYtGkTSkpKQo6JT8JkNOI5FU2zsLDg10eMj8hkMhQWFqKwsBAA6JWpBoMBk5OTAD5cmZqXlxeylxaQOsJyMtTj4cA3jSCc5qPUvDWaPl9srkTiM9Rx82GOHws2m41399pwEMRzDvDN6aOEpPUubgRBQKfTYWJiAq2trSgvLw/rYiiRSHjlAghGoMAf75iWQJgsUKmHAoODg2hqagoatxMuvuJ5spMKxwjEXswFy0tfq/GQSqWKW156qnyfviTDcrpgUA1vFQoFqqurV7lKVlZW4HA4YDKZeL0agg0sFgskEgmjS1IFBAQEUpFIe0LFAmVUKigoQEZGRliiI9ewLZ7b7Xao1WqQJImOjo6wmrjx0XkeyXhsNhvUajVEIhE6OjoS7t4tl8tRXl5Ox2WYzWYYDIZVK1OpOQAf4ofiQSrNQfgmngcS2HPJ6XTSK1v7+/vhcrkiaj5KfbfJON9aj2R5aGCxWJCVlRXvYUSMIJ6zDEEQ8Hg8YTsnbDYbNBoNCIJAe3t7RC42iUSSUM5zKl8uOzs7bjEtgTCVLe7xeKDVamEymbBr166YHwqwLZ5Hc9wkSWKyuwtv/eE3sC4u+G4NBbV1uOir30Amy812BD4kWOMhqvno2NgYRCIRXUSH60phAr4Xc2yQKm77QFfJe++9h6KiIni9Xno1RHZ2tp+rJJaMTj5js9mQlZWVEt+7gICAABtE2hMqFnyNShs2bEB5eTnefvttXs6j2BTPFxYWoNVqUVJSgpaWlrDdjHxznkcynsXFRXR1daG0tBQtLS0Jf9/2NTbU1NQEdfgqFAq/lanxRK/Xw2AwID8/H3l5eazvL9JriM02DKdzGhkZ1UhPrwDgBkkCLtccAALp6WUQi/n3sCXR5lvp6elrNh+dnJwESZL0/CFY89FUjW3x1RQTGZvNlpCrdZNzFssDfHP6qItZqD/u2dlZ9PT0oKysDM3NzREvx0iU2Bav14uxsTFexLQEwkSBajab0dnZCblczthDAT45z62mZTz97dvgddjXeAWJpdFhPHnrTQCArRdficrWjUjPykZeWQWwzt8CX84DtmH7ewyM26Dy0uPhSkm0Yo4JkiW2JVJIkkRubi49GXK5XHQhTGV05uTk0OecUqlM+OKPIlEdFAICAgJ8gMuYlrWMSnxdwcuGeO778GDjxo0oKyuL+5hiIRwTEEmSGB4exujoaFTHnCgEc/hSES89PT3wer0QiUTQ6/XIzs72613DNARB4KmnnsLXvvY1uN1u+udFRUVobGzEVVddhU9+8pO8cP4vLr2B0dHbAax9XotEhSgsPA8q1QHIM+oglSohFsff/Ack9txjreajBoNhzeajbD9g5SvJctxWqzUh502CeM4CgQVgKOGcylybn5/H5s2bUVxcHNV++Vr0+UI9VBgbG+NFTEsgsTrPp6en0dvbi5qaGjQ0NDB2YeNaPF8aH8VkTxeUxcWo2b4bXrcLL/zkv7Ew1B/xtjTPPwvN88+u+nnl5jYc/s87Vv2cDw8Ikg3fvPTa2to1c+d8RU2mstRSxYXtSyoeM4BVDWzS0tJQXFxM39McDgcdLTQzMwOPx7NqiWaiFoOJWgQKCAgIxJtIe0LFAtUQM5hRia8mJKaFaofDAY1GA7fbHfEqZwqmVuoyRajxuFwudHV1wWazYe/evchJoZWx6enpKC0tRWlpKUiShNVqRVdXF8xmMz744APIZDK/vHQmTF8EQeC5557DZz7zmaC/X1hYwMLCAt555x08/PDDePPNN1nJnA/3HLVadRgdvTWM7S1iYeF/sbDwvwBESEsrh0p1EPl5FyEzswlicfzicZLJrOTbfDQwJnJmZgYDAwNIS0sDSZJYWFhIqWgiKs4s0bFarYLzXCDynD6z2Qy1Wo20tDR0dHTEFKXA16KPwmQyobOzEwDQ3t6O9PT0OI9oNdEWqF6vF/39/Zibm8O2bdvohi5MwZV4bjUa8NQd/8HqPigmtWdw9Labcf2PH+Nkf3wjngXOWrlzBoNhVV56Xl4esrOzox5vMhVz4ZLI7o9YCJX1npGRgbKyMpSVla2KFpqYmAAA5Obm0pM4Nt1QTEOJ54kyXgEBAYF449sTCmDXbU7V6bOzs2s2xOSrCYlJ8XxpaQldXV0oKCjAjh07oo5SSyTnORUTmpOTg/b29pQR2YIhEomQnZ2N9PR0lJeXo7CwECaTiW482tvbi+zsbNpME2kTR+Ds593c3AybzRbW68fHx1FbW4v9+/fj+eefZ1wYDOea0tf/pSi2TMLlmsL8/O8xP/80ZLIKEIQVMlkhqqq+CqViJ0Qi7po6JvN8yzcmsq6uDh6PBzMzMxgZGWGk+WgiEWhUSkSoh3iJ+BBTEM8ZItKcPpIkMTk5iYGBAdTU1KC+vj7mmwVfiz6SJDExMYHBwUHU1NTQS2/4SDQZfoFNZ9jIkuZCPCdJkjPhnMK5sgLD9BTyys92W07Wm34gfHLrAKtz5wLz0n2Llkjz0pO5mAsGSZIp6zyPxA0RGC1ENbwyGo1YWlpatURTpVLxspEbheA8FxAQEAgfymzkm1vLVq1gsVig0WggFovXbYjJVxMSE/M738iS1tZWlJeXx/R5J4p4PjU1hb6+PtTV1aGuro6RcyyZalqJREIbZYAP4/YMBgP6+/sjNtMsLCygoaEhqrG8/fbbyM3NxcDAAEpLS6PaRiDhzLesVh0IYjHGPbnhdo8CALzeBQwO3gy5fDs2bniMs1iXVJpvSaVSKJVKyGQy7NmzJ+bmo4lEsjjPhczzFCbSnD63243u7m4sLy+jra2NsWVKfCz6fI91586dyMnJwfDwMG+fmkXarZ1qtMN20xnqfGKzUB167x3Wtr0ef/7uHSjdsBn//rVvAuCfsJxqrJeXPjc3h8HBQWRkZNAFSailcqlUzAGp2/2diuSK9rh9G14FLtGcnZ3FwMAAfd5R/+NDk2mKRF1+KCAgIMAlvj2h2I5pIUkS09PT6OvrQ1VVFRobG9e9R/HVhBSrUO10OtHV1QW73c5YZAkfY1t8PyPfSFQm59rJjm/c3npmGkpM980qJ0kSra2tMY+hubkZlZWV+Otf/xq1EO/LetcXm20cPb0fj3kfwbDbOzE3fwxlpVezsv1AUs2447vKd63mo9SKilDNRxMJvmpokZKopiNBPI8RgiDgcrnCLgCNRiM0Gg1ycnKwb98+Rif/fCv6qGVyWVlZ9LFS4+PTOH0Jt0AlSRI6nQ7j4+OcNZ1hu1A988JfWNt2KGZ7tfj1TZ9ExTnno/C8C+M2DoHVxJqXnmrieap2f6euTUwVdL6rHQD4nXfj4+Po6elBdna23xLNeK5oEhqGCggICKwPl01BPR4Pent7sbS0FHacIh9NSEBs4rnBYIBGo4FKpcL27dsZu0/y2Xlut9vR2dnJ6orgRCecv7tgZpqVlRUYDAY6d1oul9NC+tLSkl9T0FiYnJxEW1sbXn/9dezatSvq7aw1b/Z47Rge/j5Mppei3nY4TE8f4VQ8T6W5x1qGnWiaj/KhYW24JIPznCCIhDUdCeJ5lFAxLW63m37SFyqmZWRkBCMjI2hsbER1dTXjFziJRMKLos83pqW+vh61tbX0sXLhoI6FcARqp9MJjUYDp9PJadOZaCJlwoEkSej1eqzMzzC+7UiZeutVbDxwKN7D4IRELXDWy0vv7e2Fx+Pxy61OtfzvVHWe+4ohbBB43lFLi41GI3Q6HRwOx6qHOFx+B4laBAoICAhwAUEQmJubAwDk5eWxWhesrKxArVYjIyMDHR0dYQsjfDMhUUQjVJMkidHRUQwPD9NOXiY/80hX6rINNUdaXFxEV1cX4yuCSZLEbX9U48U+/dn9Abh2RzFeGzRgwewGCUAGIEMCuEjA+a+PRgLg6h2l+OaFDbyrhSOdU4rFYuTm5iI3N5fOnabqf51Oh+9///uMj/HQoUP485//jAsuuICxbS4vf4BB3U0A2F85QZIrrO/jw30J4nkwwmk+mpGRQc8f+N58NBmc5zabDSRJCpnnqQJBEPB4PGE7J3yXy+3evRtKpZKVcfHBMeF2u9HT0wOj0YgdO3bQGWoUIpGId24FX0KNzWg0Qq1WQ6VSoa2tjVOnIxvOc4/HA61WC71ez+h2Y+H0/x5F9Te/E+9hsAqflrrGSrC8dIPBAKPRiLGxMRAEAbvdDplMxvvcaiZIVec5ddxcCda+S4sB0Es0qWLY4/Gsyjtk8zux2WyC81xAQEAgAN+eUHNzc5BIJKxFaPiad6LJuObDPCoY1NwkXHHM5XJBq9XCYrGwNu9ky9ATC3Nzc9Dr9diwYQPKy8sZ2+6Kw41dP/in388IAE+dnvf7mRuAO+D08QL4w+lZ/OH0LN6+dTeUmYnjcA2FVCpFYWEhCgsLQRAE3nmHnfjPq666Crfddhu+973vRfV+37+ZyalfY3b25wyNLBwInDp9EK0tR5GVVcXqnlJNPI82piZY89Hl5WUYDIaEaD6aDM5zqplwIpqOBPE8Anxz+qgLVKiL1OLiIrRaLfLz8xldLheMeDsmTCYTNBoNMjMz142k4bN47tuY0/e7JUkS4+PjGBwcRFNTEysrB8IZG5OFqsViQWdnJzIyMrBj+3b0/46xTcfE0lBfvIcgECW+SzwrKytBEATUajXEYrFfbnWiPN2PhlQWz6mHo/FALpdDLpejrKxsVU7nxMQEACA3N5c+9zIzMxn9jiwWi5CpKiAgIOBDYEwLm/MUl8uF7u5urKysBDXvhINEIoHH42FhdLFB3VfDEceWl5ehVquhUCjQ0dHBWo3FJ+e52+2GxWKBSCRifEUwQZCrhPNo2f+T9/Hr6zZhT23k5ybfGRkZYXX7P/7xj7Fnzx4cPnw4ovf5zpsdjnmOhfOzEIQRPb2XoqnxN8jNbWNtP6kmnsfSZ8mXtVZU87X5aDI4z61WKyQSCdLT0+M9lIgRxPMwIUkSHo+HLqpCCecEQUCn02FiYoKRrubhIBaL4XK5WN1HMEiSxOTkJAYGBsJyevBZPKcuhr4XJsqdbTKZsGvXLjqDl2uYFM/n5+eh1WpRWVmJxsZGxjLqmMLrdkOSZKJqKiIWiyGVSpGXl4eKioqgT/cVCgVdkHAdtcEG4cR4JSN8ckIE5nSSJAmz2Qyj0YjFxUUMDQ355R0ysSLCarWiurqaoSMQEBAQSGyoaEvfnlBSqRR2u53xffn2k+ro6Ii6nxSfnefA+mIRZfLR6XRoaGhATU0Nq3UIX5znKysrdL55XV0do8K5ZtyAT/zmDGPbA4Ab/9CNM9/cD5kkvvUS0+cGW65zX66++mqYTKaIx069fmnpOTaGFTaDupuxa+dJiETMfveLi4vYt28fTCYTDh8+jOuvvx779+9POnNSIGzFgvK9+Sif5lvRQvWJSsTjEMTzMKDc5l6vNyxnnc1mg0ajAUEQaG9v52xJQjyc5x6PB93d3WvGtAQjEcRzqiA0m83o7OyEXC6PqSBnAibEc6rR6cTEBDZt2kTfGPgm9HW+9FfsvPSqeA+DNfj4mbOF77EGe7pPRbz09PTQeemUOzg7OzvhPqdUy3inYMoBwgYikQgKhQIKhWJV3qHvigjfYjjSa70Q2yIgICDgbzYKfJjMdG8mpvtJxXsF71r4iufBcLvd6O7uhslkws6dOzkx+fDBeT41NYW+vj7U1dXBaDQyVnuRJImPHTmBnnkbI9sL5Id/H8K3Dzexsu1IYPLhR29vL2PbWo+f/vSn+NrXvhb2632P0eWeX+eVXOCGyzWH9PQyxraoUCj8/v3ss8/i2Wefxe2334677rorqQV0LuYdfGw+mizO80SMbAEE8XxdfHP6fJ0T6zE7O4uenh6UlZWhubmZ05Oba8cE1ZCHEpbDXXrBZ/Hct6Hp9PQ0ent7UVNTg4aG+Dd6iVU8d7lc0Gg0cDgc2Lt3r99Fa3k2/s1CfZkfGoj3EAQYYr0HBenp6SgtLUVpaSlIkoTVaqWf7o+OjkIsFtNCeqJ0Q482gy/RSaRizjfvEAC9IsJoNGJ8fBw9PT3Izs72yzsMFblmtVoF8VxAQCClCdUTiknxnI1+UongPA+EmotlZmZyavKJp/Pc6/Wir68P8/Pz2L59OwoKCtDZ2cnYeH53Ypw14RwAnj4zB/XUMv544y6Ik8RsYTAYONnPd77zHVx//fURPSCirkG5ynOxtPRntoYWFgTBTCxUXl7euhFTP/7xj3HgwAF85CMfYWR/fCQeph0+NB/ls1kpXKxWKzIzM+M9jKgQxPM1oHL6NBoNqquroVAo1hVPfW/kmzdvppuYcQlXjolIY1oC4bN4Tl2M+vr6sLS0hG3btqGwsDDOozpLLOK5yWRCZ2cnlEol2tvbVwlBywuzTAyRMcqaNsZ7CAIMEe45KxKJkJ2djezsbDovfWVlBQaDgXYHy+VyWkjPzc3lpaMiVZ3nibyMMHBFhMvlovMOdTodHA4HHS+kUqmCxgslsotCQEBAIBbC7QnFlHi+tLSErq4u5OXlMdpPimlnPFNQn6fv3IkkSUxNTaG/vz+quVisUOI51ysp7XY7HdPS0dFBR64xFW3p9hJ48JWhmLcTiv4FB8790Vv42y17ocqK36pmpoimx0C0VFdX49vf/jZuvfXWkA+LfM+JvLxzgeFsABaWR7g26eklMb3/9OnTOHjwYMjXkSSJEydOCOI5y0TSfJSKJ43VaOT1enk5/40EynCUiPNlQTwPgm9Mi8lkgtvtXvfLNZvNUKvVSEtL87uRcw0XRZ9vTEtbW1tUDdL46uwAQGcxWiyWuH6XwYi2MKSWNdbX16O2tjbouXzq+WeZGCJjlLVuivcQWCcRbxjREO3ESiwWIzc3F7m5uQDgV5AMDw/DbrevKkjiXUQB/Cjm4kEyHXdaWhqKi4vph+BU3iHlLPF4PFAqlRgcHERpaSk6OjoYF8+PHz+Ohx56CKdPn8bs7CyOHTuGyy+/nP79Zz/7WRw9etTvPRdeeCFefvllxsYgICAgEIpIekLFOk8hCAJDQ0MYHx9HS0sLKioqGK2l+BrbAvgbjzweD3p6eqDX66Oei8UK9blzKZ4vLS1Bo9GgpKQEra2tfjUHU+L5nIn5TP61MDmBcx9+Dw9c0oRLt8Qmqsabiy++GEeOHOFsfw8++CDeeust/PrXv0ZxcXHY56Aq9yIYl+PjPlcozoFYHP2DkmuvvRYvvPBC2K+3WOL3kIAL+BiBul7z0b6+Prr5KOVMj6b5qNfrTYiV2OthsVgS1nAkiOc+UDEtlHNCLBavW+j5OrBrampQX18fV/GAbVE62piWQPjqPF9YWIBWqwUAbNmyhVfCORD550YQBPr6+jA3N0cva1wLwyi7XdIjRa5UhH5RAsOHJktcwVRxE1iQOBwOOuIlMC89Ly8vbk+0Uzm2JVmPWy6XQy6Xo6ysDCRJwmazwWg04siRI/jb3/4GACgqKsJrr72G5uZmtLa2xnzuWa1WbN26FTfccAOuvPLKoK+56KKL8Nvf/pb+dyJ2rRcQEEhcIu0JFYt4brfbodFo4PF4sHfvXkYbQ1Lw2dxDjY0ybKWnp2Pfvn1xu+6H08SUKUiSxPDwMEZHR7FhwwaUl5eveg0T4vkx9Qy+eYyb7G5fvvf8IJqKstFSwp2YxHR93NHRwej2QkGSJI4fP46DBw/iiiuuwCc+8QlkZmaitLSUvjZQ54PvsS6bXuN0nBRpaY1oaX4k6vebzeaIhHMAOOecc6LeXyKQCPOO9ZqPTkxM+DUfzcvLQ2ZmZsi/zUQ47lAkcp8oQTz/F1RMS2BO31qFHtWcZXl5OW5P/QNhyzERa0xLIHwTz6kmmuPj49i4cSN6enriPaSgRFIYOhwOOv+Pbw76UEjS5cjJ50dUjkDssOUMyMjI4GVeeirHtiRK5nksiEQiZGVlISsrC7/61a/g8Xjw7rvv4stf/jI++OAD7Ny5E0qlEh/96Edx6NAhHDp0CNXV1RHv5/Dhwzh8+PC6r6GKcgEBAQEuiaYnFBC9eD4/P4/u7m4UFxejtbWVtXsN353n8/PzGB8f541hC1i7iSlTuN1udHV1wWKxYM+ePasaJFLEKp5/MGaMi3AOAG4SeKVvkVPxHGDWyBOv+m96eho///nP8fOf/xwikQgZGRnIz8/HgQMHsHPnTvzjH//AY489Brlcjo0bN+IjB1ycjzErcxuamn4c0zauvvrqiN9z4MCBmPbJdxJNRI6k+Sg1fw02d02kHlNrYbFYBPE8kaHc5sEKQIlEsqohg9FohEajQU5ODvbt28dZc5ZQsOGYoJYGGgwGxh4S8Kk4dTqd0Gg0cDqdtJOlr6+Pl87gcAtDg8EAtVqNwsJCbNiwIeQFlm9CX+k5hzAwMEDfOBI912st+Pa5swUXy+rWy0unGrj45qWrVCrGMlIDSbRijilS9bilUinOOeccLC4u4rnnnkNTUxNOnDiB119/HY8//jjuvvtuTE1NsfLZvPnmmygqKoJKpcJHP/pR3H///bx4kC8gIJC8rGU2CodIxXOCINDf34+ZmRls3LgRpaWlUY05XPjqPKceVExMTPCmF5NvbAtbrKysoLOzE9nZ2ejo6Fh3PhCreP5frwxG/V4mmF52xHX/TFBUVISFhYW47Z9y9k5NTeHJJ5/Ek08+6ff7Z599Fh5PAQ5+NBuAGNyUrOmorb0LMllsmfDUyvhwGR8fT/rViIm+0ne95qPT09Po7+8P2nw0kXtMUSRyn6iUFs8Dc/qCFYC+hR5JkhgZGcHIyAgaGxtRXV3NKwGMaVGaqZiWQPjiPDcajVCr1VCpVGhra6PFNL6ML5BQhSFJkhgfH4dOp2MlC5ILssurUbNlOyQSCUZHR9HT04OcnBw6ikOhUCT8DSPViEcmnW9eOtXAhcqc881LpwoSJvPSE72Yi5ZUFc+Bs8dus9mQnZ2N9PR0HDhwAAcOHMB9990Hl8vFyudy0UUX4corr0RtbS2Gh4dx11134fDhwzhx4kTCO1IEBAT4CUEQcLlcEbnNfYlEPLdardBoNADORkJkZmZGPN5I4ZO5h8JqtUKtVoMkSWzYsIEXwjnwoXjO1udF9WsKd8VzrHO3gTlz1O9lgkkjd1nrbPHII49E5ZDmkkcfNeAjB7IhFhMgCLBet1ZUfBmZmU0xb6e+vh5nzpwJ67UrKysx7y8RIAiCNSNUPAi3+ajT6YTdbk/oFb/UnCkRSZ4zLkKonD7qRhuqM7zT6URXVxfsdjt2794NpVLJ9ZBDwpRjwreDe21tLerr6xkVvwI7xnMNJTIPDg6iqalp1UMQpprOMM164/Jt5Lpr1y66yWK4lLZswmx/NwOjjI307LPLmWpqagCcXRlgMBhgMBig1WpBEATtHs7Ly4NcLk+4BwSAkHnONVKpFIWFhfSk0zcvfXp6GgRBIDc3lz63YslLF2JbUg+bzQaSJIMWgmytTLvmmmvo/968eTO2bNmC+vp6vPnmmzh06BAr+xQQEEhNgvWEiuY+R82pQtUFMzMz6OnpQUVFBZqbmzl7MMs35/ns7Cz9OZAkySuhiJo3Mz2fIwgCvb29mJ+fD9mvKXA80dbWXi8Bd5yfmegWrJhbcaJEwY1bOJK/3+XlZbzyyisYHx9HQUEBtm7dirS0NLS2tvqdkxdddBEbQ2UUk4nA739vwPXXn3WCnz1/2XOh5+ddyMh2fve732HTpk3rvuaiiy7C73//e0b2lwgk+3xrreajg4ODmJ6exvj4eMzNR+OFxWIJ+9rON/hzF+YIkiT9hPNQBaBEIoHZbMY777yD/Px8bN++nVfFiy9MOCa46OAeT2eHx+OBVquFyWTCrl27oFKpVr0m0ZznVqsVnZ2dSEtLi3qFwCVf/zYe/4/PweuM77JBkdhffEtPT/fLtaaywRYXF6HT6ZCenk4L6ckc8ZLI8EE8DyRYXrrBYIDRaMTIyEhYmXNrITjPUw+r1QoAcXVR1NXVoaCgAENDQ4J4LiAgwBixxLQEQj1gXSuz1ePxoK+vDwsLC9i6dSuKioqiH3gUUPV/vOsW37iazZs3o7i4GCdOnODd3EQsFjNqBrHb7VCr1QAQcb+mWMTz57vnonofk3gIEpNGO2fieTjMzc3hc5/7HN555501X1NUVIRnn30WW7ZsgUgkQnl5OaanpzkcZeS89KIV116rQloa9Td+1oXOhoiens7MNayqqgpf+cpX8MgjwZuOLi8v48033+TdfItNUm3eQfU5Gh0dRXNzMzIyMui5a7TNR+OF1WqljZKJBj9VYJaItACksofMZjM2btyI8vJy3p6EQPiOjrUwm83o7OxERkYGqx3c4yVOU8dHxdCs5QiMtzN+LYIVhgsLC+jq6kJFRQWampqivomIRCJ87pHH8fIvfoQpTXjLwtigoGnjmsVvYDaY1+v1W87kG/GSn5/P+yewfL6WMA2fj9U3L72qqipo5pxcLvfLnFvvAWqyOyHWItWKWF+sVitkMllc8yWnpqag1+tZzwQWEBBIHXzd5mut0I0ESjAPtlLJbDZDrVYjLS0N+/bt46zJd7DxxVM8t9lsfgIyFVfDR2MPk2NaWlqCRqNBSUkJWltbI64nYpm76RasUb2PSeRpEuRncdtDbb2HDVSvM4vFsu42FhYWsH//ftx///24+uqreS+cA4DB4MXRJ4z4wk2BOeQECOKsgE6dSrGUtWJxbvRvDsIDDzyAO++8E1dffTVOnDiBrVu34vjx4wBARxCn0vwjVecd1P2Taj5KrUwym80wGo0RNR+NFzabTWgYyncotzkVsh/q4mKz2aDRaOBwOFBYWIiKigqORho91AUk0qKP7ZiWQOJRAE5PT6O3txc1NTVoaGhY9/iYdlIwha94TpIkhoaGMDY2hk2bNsUsmFCfh9fpjHmc0ZJVUIj82oawXy+RSJCfn0+vjnA4HPQT2K6urlURL1zkZYYLH88vtkg0MTkwc87tdtMPaai8dIVCQZ9bgTn8qVrMJVv2YCRYrVbGHR4WiwVDQ0P0v0dHR6FWq+nr2b333ouPfexjKCkpwfDwMO688040NDTgwguZWSIsICCQugT2hGJCOAc+nKd4PB7awEKSJCYnJzEwMICamhrU19fH7R7qK+7HYwyUIaasrAwtLS1+Y+CjeM5EzKVvP7ENGzagvLyc87G0VcU/irWjNhe1+eE77dnmC1/4Qkjh3Je7774b99xzD4sjYpY//3kFFguBr3w1H1Kp77UteIxLNGJ6ScmnYh3mKpRKJV5++eVVP6fO/USab8VKKq/0DXz4LBKJoFAooFAo/JqPUvGklBGMmt/Ge7W+0DCUx1A5fR6PJ+wGN1TGXFlZGYqKimA2x7eJSLhEU/R5PB709vZiaWmJtZiWQLjMFPR6vejv78fc3FzYHer57DynmjV1dXXBZrNh7969yMnJiXnb1E23ce9+zPb3xLy9SMktr8TH7n4Agz5iUaRkZGSgrKwMZWVldMSLXq/HwsICHfGSn5+PvLw85ObmChEvHBHv5c+xIpPJVuWlUw9pqBz+3Nxc+sl+qornXq+XtXxvvmOxWBh3UJw6dQoHDx6k/33bbbcBAK6//nocOXIEXV1dOHr0KJaXl1FWVoYLLrgA9913X1zd7wICAolPYE8oJu9nIpHIL7rR7Xaju7sby8vLnM1B1oM6Vq/Xy2mNSBAEBgcHMTk5uaYhho/ieaxjcrvd6OrqgsViwZ49e6BQKKLeVizi+cGm+DZhFQH45gXrG7u45Pnnn8err74a8fsSyRhEksBLL1nwwQd2fPWredizNwvrffzBxHQRANEal8esrB0oK72esfGGIhXF80QzZzFFODqfrxEMOKv3GY1GGI1Gv+ajlBFMqVRy2rfKarUKznM+EmlMi9frRV9fH+bn5+mMuYmJCV41j1mPSIs+aolkeno6qzEtgYjFYrjdbtb3Qy19FIlEEWXn8dl5brfbceLECeTk5KC9vZ3x4r5p734cf+IxRre5HtXb9+C8m/4DEp/jYOKz9414qampgdfrpRtE+rqHKRcn3yNeEp1kKm6CPaTxXSYnEokgk8kwOzuLvLy8lBEzU/WhAcCOg+LAgQPrXgtfeeUVRvcnICCQ2kTaEypaqIjJ5eVlaDQaZGVlRd2vh2moY+ZSpHY4HFCr1fB4PGhvb1/zXsJH8TyWz2plZQWdnZ3Izs5GR0dHzPOZWD4fPtSohTncnv9rHbPZbMZ1113H6VjiydKSF9/5ziIyM5dw7bVKXPkxJWSy0A5z399/6EoXAahGVeU3UVS0m9OaOFXF81Sbd5AkCZIkIxa6pVKpnxGMaj5qMBjQ19cHt9tN6yJcNB8VnOc8hMrpC7cA9M3a8xVaqSIvEQi36CNJEtPT0+jr6wsrxoRpuCgAFxYWoNVqUVpaumrpYyj46jx3Op1YWlpCQ0MD6urqWPnOxFIprn7wYfzx7ts+rAZYouO6G7Dpo+f7/Yyt81Aikfh1rKbcwwaDAVNTU3STDUpMj6RJUbSkSoGT6M7z9fB9SEPlpff19cFqtdLX2KysLPrcys3NTdpok7UawKUClIMiWc9zAQGB5IbJpqChEIvFmJycxMzMDBobG1FTU8OrayeXq2MXFxfR1dWF4uJitLa2rnsP9XXs84VozUZUlGZdXR1j85lYI2TSxIArTh+vXMaf8/+yyy6L9xDigs1G4vHHl/HUUya8/vovYHf8vxDvUGBD66+QmVkHgvDAZluByeSG0WjEwIARg4Nv00IkF/NKQTxPDXzv0bFANR8tKSkBSZKw2+2cNR8lSRJWq5WR5IR4kHSzeN+cPioLab0vO1TWXiKJ50Doos83pmX79u20mMglbIrnJElCp9NhfHwcGzduRFlZWcTb4JvznCAI9Pf3w2w2o7y8HPX19azuT1lUjC889iTe/d/foecfq3PVYiW3rAIfv/eHa/5dcvHZB7qHzWYzDAYD5ufnMTg4iIyMDFpID9UgMhr4dH6xTTKL54GIxWKkp6dDJpOhqanJLy9dp9PB4XCsm5eeyMQrI5YPJPLyQwEBgdQm0p5QseByueB2u7GwsIDdu3cjNzeXtX1FCxcitW/fonBzvpPBeU4ZDObm5hifg8Yqnt99cRO+89wgY+OJhB9c2hyX/QZ+Xk6nE6dOnYrLWPiCw0GisPA8FBRcCr3+OKamfgEvsQAgAzJpMXJyNqK4+FpkZTVCLD67WkIsToNCkQmFAqisrARBEPS8cm5ujrN5JVO9KRKFVMw8p663TJqVRCLRms1Hl5aWWGk+arPZBOc5HyAIAh6PJ2znRDhZe4kmnq9X9PnGtHR0dMSt6y5bBaDT6YRGo4HT6YwpC5xPBSq1nNPr9aKgoICzppcikQgd13wa86M6LI0OM7LNso1bcM4nb4CyqHjd/XKNb5ONmpoaeDyeoA0ihYiX6Egl8Rzwz+ALzEu32+30Mrnp6Wm/vHSmn+xzTSo6QCgE8VxAQCDRiKYnVCzo9Xp0dXVBJBKhqamJl8I5wL7zPNq5Cp/mJhSRmI3sdjvUajVIkowoSjNcYhXPP7atAs+rZ/H+BLd9zrJlwEdbijjdZzA++OADHDp0KN7D4AWFhYWQSCQoLr4YxcUXR/x+sVgMpVIJpVKJ2traoPPKnJwcuvZnwkiTanMtIDXnHdS9ic3vOrD5qNfrxcrKCqPNRxN53pQU4rlvTl+4T96MRiM0Gg1ycnKwb9++NRudSSQSutt8IhBM7A+MaYlnJ3uAncLUaDRCrVZDpVKhra0tpie6fIltoY4pPz8fGzduRE9PD6eOZZFYjCu/fT9MC3N468nHYZydxbaLLsbmQxfBbbdD98G7cFrMKN+wGU6zGYaZKaRlZiKvohpvP/U49GOjAAB5bh4u+8Z3oSiMf3EYDlKpdM2Il8nJSQDgPOIlkUm1gm69LDq5XA65XL5mXrpUKvVb5smHDNhwSeXYFovFkrAOCgEBgdSDy5gWgiAwPDyMsbExNDc3Y3Z2lpX9MAWbznPqAUJeXl7EcxW+zE18CVfQX1pagkajCSueJlpiFc+lEjGe+NxuvD9mxH/8oRNWNzfzrXfvOIeT/azHqVOnBOH8X2zevJnx83O9eSVlpPF19UZjpEm1uRaQmg1DqbkWl8ctkUgYbT5KEITgPI8ngQVgKOGcJEmMjIxgZGQEjY2NqK6uXvf1ieY8DxSm+RDTEgiT7gmSJDE+Po7BwUE0NTWF/D7DHV88YzVIksTExAQGBwfR3NyMyspK+ryOx7iURSW4+LZv+/1MJpdjw7n+hVbl5m30f3/s7gej3h/fIk3YinhJlRt+qhV04RZzgXnpvk/2p6amEi4vPZVjWxK5CBQQEEgtIu0JFQsOhwMajQYul4t2WS8uLvJOBPaFDYOP79zTt66PBIlEArfbzei4YiXUvMT3uFtbW1FRURG3sYSDRCxCe10efnr1Vtz4pJqZga1DYaY0bvUxtV+z2ZwSwrlYLKb1h7WuP5mZmTh+/DjrYwmcV1osFhgMBiwuLmJoaAgymcxvXrmWwdOXVJtrAanpPOfDMcfafNRqtQKAkHkeDyLN6XM4HNBqtbDb7di9ezeUSmXIfSSaeO7rmAhsghqvmJZAmBLPPR4PtFotTCYTdu3aRT8Ri5V4uju8Xi96enqg1+uxc+dOv2NiUzznyw2XL+NYi0gjXhQKRdBj4tsDAjZJpWMFoi9sfJ/s19fXw+1200/2ffPS+RofxIeCLl5YrVbOIrUEBAQEosG3JxTArtscABYWFqDValFUVIQdO3bQD3/5Pq9i2nnucrnQ1dUFq9Ua9twzGHyNbVlrTG63G11dXbBYLNizZw8UCgWrY2Fy7nZOYwHkUsDO8sLzcxqYmbfGwiOPPJJ0dXpOTg6amprwpS99CdnZ2bjggguwsrKCtLQ0ZGVlgSRJPPnkk/jud78Lg8GA7OxsPPTQQ7j22ms5H6uvkYaKyFheXobRaMT4+Dh6enrCcvUK4nlqwEejUqjmowCQm5uL48ePY9++fSgqOptEwFRsy/Hjx/HQQw/h9OnTmJ2dxbFjx3D55ZfTvydJEt/97nfxP//zP1heXsa+fftw5MgRNDY2RrW/hBTPo8npW1xchFarRX5+PrZv3x62g08qlYIgiIS5KFGOCcq5WF1djYaGBl79oTFRAJrNZnR2dkIul6OjoyOsp7LhEi/nuc1mQ2dnJ6RSKTo6OlZFNsTLeS6wNkLES2gS5drJFEw1sJHJZCgqKqKLDN+89KmpKXqZJxud0KMhlWNbrFYr7cAQEBAQ4BuU2YiqvdlsLEcQBAYGBjA1NYWNGzeirKzM7/d8j8Nk0nlORYQqlUp0dHREnAsbOK5EEc9XVlagVquRlZUV83FHMhYm50jvffMAtt3/JticdX3n35pY3HpoXC4X/vrXv8Z1DKHYt28fDAYDFhYWYLFY/K5jgdx00024//77abOg0+nEO++8A7FYvMqM9ulPfxqf/vSnOTmGSJBIJMjPz6f78LlcLnpe2dvbC4/H49crKSsri9YHUmmuBaRuw1A+z7XWaj46Pz+PY8eO4Xvf+x6ys7NRVFSEp59+Gueff37MK5KsViu2bt2KG264AVdeeeWq3//whz/Ez372Mxw9ehS1tbW45557cOGFF6K3tzcqY3HCieeR5vQRBIHBwUFMTk5iw4YNKCsri+jiQp2gXq+X10vmKcRiMSYmJmC1WrFt2zZeTuhjLQCnp6fR29uLmpoaNDQ0MH6ziEeBuri4iK6uLpSVlaG5uTnozSBVxPNEPsZwI16oB4DJDvVdplJBx1YGX7C8dIPBQHdCl8lkfpmJXOelp6IDhMJisaCuri7ewxAQEBDww7cnFBcxLTabDWq1GgDQ0dER1FnGZqY4EzAxPpIkMTY2hqGhobAiQsOBj+J5sHkJNUerra1FfX09Z/Uf03OkDJkU3fccxDf/0oMXuxfgJQG5BMjPTseUyRnz9n9wSWPcRTDKlMFXfve73+HSSy/F7Owsuru7IRKJsGHDBng8HszNzeHxxx/HyMgIzj33XFxzzTVobm72e38izycp0tLS/Fy9NpuNFtNHR0fpVat8SRfgklTMPOej83w9fFfsv/7667BarXjqqafwwAMP4LHHHsMXvvAF1NfX47zzzsOhQ4dw8ODBiJMkDh8+jMOHDwf9HUmSePjhh3H33XfjsssuA3D2ulJcXIy//OUvuOaaayI+Jv6rwT4QBAGXyxV2AWiz2aDRaEAQBNrb26PKJE0k8dxiscBkMiE9PR379u3j7YU02gLQ6/Wiv78fc3NzrD4Y4FKkJkkSw8PDGB0dDerQCRwXW4UzX24+fBkHE6wX8UIQBM6cORNWxEsik4riORdOiGDLPE0mE4xGIyYnJ9Hb24usrCxaSOciLz3RCjomsdvtQmyLgIAAr+A6pmV2dhY9PT0oKytDS0vLmvcDvse2xOo8d7vd0Gq1WFlZwa5du5Cbm8vYuPgmnvuOiSAI9PX1sT5HWws25m5SqQT/76ot+H9XffgzkiTx95Pd+NpL81jr25CJgWt3lGB7lQofacyHzenBbf/Xi1G9HXtqFLj7cBOy0tl3468HVUc6HI64jmMtlpeX6WtIeXk5ysvL/X5fU1ODvXv3hrWtZJmDiEQiZGVlISsrC5WVlSAIAiaTic5Ld7lcOHnyJF37q1SquD+gYQuSJFPSee71ehP6O83KysLGjRuRmZmJEydOwGQy4Z///Cdef/113HPPPdi1axeeeOIJxvY3OjqKubk5nHfeefTPlEol9uzZgxMnTiS/eA58KEyEuhD6FnHNzc1Rn2jUvvhc6AEfPunPyMhAeXk5b4VzILoCkHKziEQidHR0sBp/wVWBSuUBWq1WupFSqHHx/TwUWBvfiJeZmRls2bKFjnlJ1oiXVBTP4+GEkEgk9Hnjm5duMBgwODgIp9MJpVJJn19M56VTRWwiF3SxYLFYhIahAgICvMJ3KT+b9ySv14u+vj7Mz89j8+bNKC4uXvf1EokETmfszl22iMV5bjKZoFarkZ2dzUqkJN/Ec8rUY7fboVarQZIk2tvbVz1MXlhYgNlsRmVlJaOfSeBY2DY+eTwedHd3I92xjL/f2IyFZQvG5wwgHRbovTKkyXNwbksJSosK/OohZWYaHv/0NlbHFg6zs7O47rrrcPr0aQDA9u3bsby8HN9BBSCRSPDXv/6VkRo1GZzn60HF0VD/GxgYQG1t7ara37dXUrLMx6hrYaqJ58mwytdqtdJxQ7m5ubjssstoVzjTTbHn5uYAYFVdUlxcTP8uUhJKPKc6Ja9HpEVcOPDZJeH1etHb24uFhQVs27YNc3NzvCuuAom0MKWaDpWWlq7rZmEKLhqGUpntWVlZaG9vDysPMBViW+LZrJVr0tPTkZeX5xfxotfrMTc3h8HBQcjlcrrg4cI5zAapKp7Hu7AJlpdONW+ZnJwESZJ+ES+x5qWnahFLYbVaE7ZrvICAQPLCdg8fs9kMjUZD9+oJ56E/32NbojGqkCSJyclJDAwMoL6+HrW1tUkRKRkKsVgMq9WKd999F8XFxWhtbaVF4/n5eezfv582h1B86lOfwo9//GPGG4iyPUey2Ww4c+YMZDIZ9uzZA5FIhKKiImxurofH46ENCxOjw9D19/rlUmdnZ8e9Dr7mmmvw4osv+v2ss7MzTqMJTlVVFS677DJs376dsW3G+3PnCspc6lv722y2D8/LfzVuTBaTFvW3nmrzDr5nnocDJZ4Hg4v+GLGSeGrMOpjNZqjVaqSlpTHqTuareG6xWKBWqyGTyeiYloWFBV6O1ZdwC0CSJKHT6TA+Ph4y0oRJxGIx40++fKGy2yLNA2SzMKScowLc4fu9+0a81NbW+hXiOp0ODocjId0DqSie83EZoVwup5e9+ualLy4uYmhoyC8vPS8vL2JnmG8PklTEZrMx1jVeQEBAgO+QJImpqSn09/ejuroaDQ0NYV//+Tqnooh0fJQb2Wg0YseOHcjLy2NlXHwTzynTh9lsxsaNG+mmb6dOncL+/fvXfN+TTz6JJ598EnK5HC+99FLY0RuhYNN8E9iXSiQS+a2ekEqlKCwsRGFhIUiSpA0LBoMBY2NjfqsDo6mxYuWpp55aJZzHk+zsbDz33HM4ffo03njjDVgsFhQVFWH79u342Mc+xpgZIZXmtcEahlKNG8vLy0EQBN2HizJpUX24KJNWIgiXFKlq2kmGiEyr1crZat2SkhIAZx/mlpaW0j+fn5/Htm3botpmwonnwQRE3yf+NTU1qK+vZ/TE4mOhR8W0VFVVobGxkT5evjs6gPAKQKfTCY1GA6fTGVakCZOwVaASBIGBgQFMT09j69at9JPhcEkF5zmQGsVOqGP0LcQB+BXilHvAtxDnc0wTkFriOd8b2KyVl07FB/nmpVMFdSiXQ6oWscDZv2UuC0EBAQGBcGHjXkSJxQaDAdu3b0dBQUFE75dIJHQOOx8Ri8Vhj49aRSqXy9HR0cFqo24+RTdSue5WqxWlpaWoqKjAyZMn8ZGPfCTsbdjtdhw4cABSqRR6vT7mz46NORJJkhgdHcXw8DA2bNhA524HEyp9x0GJlhUVFX651BMTE+jt7UVOTg5dYymVSlZrJ4IgcNttt7G2/UgQiUTo7u5GZWUlAGDnzp248cYbsbCwgLS0NOTl5TF+zeJzPc4k652TwNnrh1KphFKppE1aVB+u4eFh2O12v/NSoVDwuqan5h2p8v1SJLvznGlqa2tRUlKC119/nRbLV1ZWcPLkSdxyyy1RbTPhxPNA3G43uru7sby8jLa2NuTn5zO+Dz6J54ExLYENWcRiMVwuV5xGFx7UMtK1LvRGoxFqtRoqlQptbW2cx1WwUYA5nU6o1Wp4PB50dHRE1VwuFcTzVLsJhkugc3hlZQUGgwGzs7MYGBjgbcSL4DznP76OKABwuVx0QT0wMBBWXnq4TbyTFUE8FxAQSAVMJhM0Gg3kcjn27dsXleDJpzlVMCQSSVjzqKmpKfT19aGmpgYNDQ2s3//44jz3jZ0sLS2Fy+VCXV0dZmZmotqex+OBUqlEeXk5BgYGoq5fmY4o8ng80Gq1MJlM2L17N5RKZdTjojKp6+vr4XK5aDNMT08PvF6v38o/ppuPW61W2O12RrcZDdSDlQceeAC33normpubAZz9e/N1hDJJss+ZfQklngfi24cLAN2Dy2g0QqvVgiAI+rylzks+1fiUUYlPY+KCZHGeMymeWywWDA0N0f8eHR2FWq1GXl4eqqqq8LWvfQ33338/GhsbUVtbi3vuuQdlZWW4/PLLo9ofPxSWKDEajdBoNMjJycG+fftYWwbFF5cEFdMilUrpmJZAEsV5Dqx+ekaSJMbHxzE4OIimpiZUV1fH5aLIdIG6vLyMzs5O5OXlYdOmTVE/MUwF8VwgNCKRaJV7gK8RL6konvPdeR6KtLS0oHnpvo1tfbM85XJ5UhRzsSCI5wICAskMVZ/rdDrU1dWhrq4u6vsc3+cpoRzelIlpcXExKud9LOOK9+dGrXqmYiffeecdXHnllVhZWWFk29nZ2XjnnXewY8eOiN/P5BzJarWis7OTjoFlUl9IS0tDSUkJSkpK/GL0FhYWoNPpkJ6ejvz8fLonTaxmmHivTJXL5SgsLITZbMbWrVsxOjqKP/7xj7jnnnsSulbmG5GK54FkZGSgrKyM7sNFnZdLS0sYHh6GTCajz8l4RA8Fwof+UvEgGZznFouF0TnTqVOncPDgQfrf1Eqb66+/Hk888QTuvPNOWK1W3HTTTVheXsb+/fvx8ssvR31tTDjxnMo0GxkZwcjICBobG1kXWfngkpiZmUFPT8+qmJZA+LSsby2Ciee+T/h37doFlUoVt/ExVYD5xgkxcZ6minge7BhJkoRn1grvvAPi3DTIKrMhkophHzPCdWwSsP1r+VZTNrKurE2IGwtT1yw+R7ykqnieTAVd4KoHKjPRNy89OzsbJEnC5XLFvaDmGq/XC7vdLmSeCwgI8A4m7r0ulwtarRZmsxk7d+6MuT7niyFpLdYT9317TXV0dHBaT8VTPCcIAn19fZibm/Nb9fyTn/yEEeHcl3379mFsbIzOqg0XpuZIi4uL0Gg0KC8vR3NzM6v1XGCMXrAojVjNMDKZDI2NjdDpdCwdxfrY7XZYrVZ4vV4MDw+jvLwcOp0Oi4uLEceXRkOqzD+YNO6sF+9IRQ9lZ2f7RQ9xPe9OtFW+TOH1enmzujxamO4TdeDAgXWv/SKRCN///vfx/e9/n5H9Jdyn73A4oNFoYLfbY1pGFQlSqTRugrTX60VfXx8dbB8Y0xII3x0dgL94DqzODIy3+MJEger1etHT04OlpSXGGgilgngeeOMn3QScehucvx0CfL6StRYgkoMWWP5LC/EnKpFdp4JIws8bK5vfo6/Y6dsgJh4RL7E6IRKRZC7ofBvb1tTU0AX1zMwMCILA22+/jezsbNqZEk5eeqJjtVoBgNO+HAICAgJcYDAY0NXVBYVCwVh9zgdD0nqsZUIK18TE5rjiMb9zOBzo7OwESZJob2+nY0VWVlbw9ttvs7LPmpoabNiwAadPnw67hox1jkSSJG3M27hxI8rKyqLeVrQERmn4mmHGx8chFov9zDDhxiaZTCY2hx0SvV6PkpISzM7OorCwkLO4jWSfM/vC5nwrWLwjFfHS19cHt9vt95AnOzub9e830Vf5RksyGLSsViuKi4vjPYyoSTjxXKPRIC0tDdu3b+fsyUu8Cj3fmJaOjg7I5fKQ7+F7UQp8KJASBEEvAeQqMzAcYi3AbDYb1Go1xGIxo84UNjvJ8wmSJEHYPLCdnIf33cWotkH8aRIrmIT8liak5TGbH5hIBGsQw2XESyqK56lU0FEFNUEQsFqt2L59O31++eal8yFCiC0o8VyIbREQEEgWfIXEpqYmVFVVMXbt5rvJJ3B8Xq8X/f39mJubw9atWzlxywYjHuK5Xq+HRqNBUVERWltb/R6G2+12Vuebvb292Lt3L06ePBnW62OZI/muft6zZw8UCkVU22GaQDMM1e+Iytv3df/m5uauKarl5+djYWGB49H7Mzc3B7lcjtnZWZx77rmcxR0lW825FlzOtwKjh2w2G/2QZ2xsLOqHPJGQDCJyNHi93oQ3JSV61GXCiec7duzgvEFAPATpaB0OiRDbQn1/AwMD0Ov1YTnquSSWAnVpaQkajQalpaVoaWlh9MLOpvOcV8WFywPzY92ALfZN2Y8MQvatrRCJeXR8cSRUxItIJPJrXBTrg59UFc9TraCjjjktLQ3FxcUoLi4GSZKw2+20mE5FCPk2IJLL5Ql/flitVqSnp0Mmk8V7KAICAgIx43A40NXVBYfDwYqQSM2p+Fof+M6jKDOMSCQK28TE5rgIguDkcyNJEqOjoxgeHkZraysqKipWvaawsBBlZWUYHBxkbRwajQYejycss1y0DUOtVivOnDmDjIwMXqx+XguxWIzc3Fzk5uairq4OLpeLrq96e3vh8XhWNR6lzpMvfOELdA5wPHG73aivr8fVV18tOM8ZJl7XU5FIhKysLGRlZaGystLvIc/09DT6+vqQmZnJ+IrnVJxrAcmRec50w1CuSTjxXCaTcS4Ocyme+8a0RONw4LujAzhbjFLNKOJdjAYjGvHc16WzYcMGlJeXszKuZC8EpNM25B5n9m9t5VENsq9rgSQvvk1zAuHDpDGSiBeVShXxDZuvk2M2SebYlrUIVsSKRCJkZmYiMzNzVV66b2MsarKnUql4O2ldD6vV6jdJFRAQEOALkV6XFhcXodVqUVBQgLa2NlZW+FJ1BF+zW6l51Pz8PLRaLSfZ1+FA7Z/tusrtdtMZ9+vFo4rFYlx11VV48MEHWRsLAPzzn//EoUOHQr4uGoPRwsICurq6UFFRgaamprh/x5EQaFawWq2rGjxSjUevu+46PPfcc3jzzTfjOubPfe5z+OxnP8upYS5VajO+zLcCH/K43W4YjUYYjUa/Fc9U7a9QKKIadyrOtYCz981EP27BeZ4CSCQSOJ1O1vdjsVig0WggkUiiFpX57jxfWFiAVquFWCzGxo0beSecA5EXYB6PB11dXTCbzawu90v2zHPTiWnkHPeA8Vu/CbAc6Uf6BeXI2BX/FQ58/Q4DI17cbjfduCjaiBe+FHNcQZJkyh0zEN4ywmB56cvLyzAajRgfH0dPTw+9BFmlUiVMXrrFYkloB4WAgIAAQRDQ6XSYmJhAa2srysvLWc3PpfbJV+x2O7RaLTZt2hRx40q28O0XxZZ4QvWgyszMRHt7e8gH2ldffTXr4vnc3FxYr4tkjkSSJIaHhzE6OopNmzahtLQ0liHGHZFIhOzsbGRnZ6OqqoqurwwGA0ZGRmC32/Gd73wHl1xyCR555BGMjY3FZZy33347p8IfX+dbbMBXMVkmk6GoqIg2g/queJ6cnAQAvxUT4epCgvM8cRHE8xSAi87wTDWi4avznCRJ6HQ6jI+PY+PGjRgcHOTtTS0S57nFYsGZM2fCLjRjIVljWwiCgPl/eoAlL/PCuQ/Ov09D0pADmYofDnS+C6wymcwv4sVms9FLRKnGRaEiXvj6N84W1PGmWkEXTRErkUiQn5+P/Px8APBbgtzf3w+Xy5UQeelUEcjHsQkICAiEwmazQaPRwOv1or29nfVJLXWv8Hg8vFttZLfbMTAwAIIgsH//fl49GPUVz9mAmodG0oOKC2NZVVVVWK8Ld47EleEpnvjWV42NjXA4HDAYDMjIyEBTUxMuueQSzsdUUVGRcrUxlySKccd3xbPvitT5+XkMDg4iPT3db8XzWpGIqdRfypdkeGggxLZwTDz+UNiMbWG6EQ0fnedOpxMajQZOpxN79+5FTk4OhoaGeCnyA+EXYHNzc9BqtZw1O2VLPPdtlJOXl4f8/HyoVCrOltOanxwAlrg5Z13vLUB2OLxCXMAf3wgOKuJFr9djZmYGAwMDqzLtJBJJwhRzTEFd01LpmAFmirlgeekGgwFGo9EvL50qqPmSl26z2RK6CBQQEEheQl0j5+bm0N3dTffp4cLRJhKJ4tJLKhSLi4vo6upCXl4e7HY7767rbInnBEGgv78fs7OzEfegYvszKigoQEdHR1ivpeZI69WdFosFnZ2dyMjIYN3wxCcyMjJQVlaGsrIykCSJW265BUeOHOF0DO+8807QnxMEgc7OTpw6dQo2mw0tLS3o6OhYMy4oUvhQJ3JBIs63AlekejweesXE6Ogouru7oVAo6LpfqVRysgKHzyR6bAvVYDYnJyfeQ4mahBPP4wFbRZ7VaoVarYZYLGYs+5tvznOj0Qi1Wg2VSuWXnxiPrvHhEmpsBEFgcHAQU1NTjDzwCBc2xHPfRjkNDQ0wmUwYHh6G3W6HQqGg8/LYcn2SLi8wyb5zhcLTYwDiLJ4ngxvbN+KFyrSjCp6BgQE4nU4olUpkZmamVJQJdd1I5MImGpju/u6bl15RUQGCIGCxWFa5U/iQly7EtggICPCZYLWj1+vFwMAAZmZm4hJNwqe5CkEQGBoaolfGKpVKLCwsxHtYqxCLxRCJRIx+bg6HA52dnSBJEu3t7cjMzIzo/Ww3yn7llVfCri1C1ZhUvnllZSWamppirkkTNUpTJBLhBz/4AWfiuUgkwvz8/JqrU//4xz/iL3/5C0wmEz744AO43W4AwN69e/Hiiy/GZORKxO8nWpJhniWVSlFQUICCggIAZ82XVMTL9PQ0CIJAbm4u8vLy4HK5Ev54o0GIbYk/gngeBmyI57Ozs+ju7qZv4kyJLXzpYk+SJMbHxzE4OIimpiZUV1f7jYfP4vl6BZHL5YJarYbL5UJ7ezunognThdri4iI0Gg0qKyvR0NAAt9uNoqIiNDY2+mWSUREdlCs9Ly+PMaHKNrLMyHbCxgkQdg/EcuHSxyTBIl4oodPtduPtt9+mXel5eXlIT0+P84jZQYhtYQexWBw0L526Pvnmpefl5UGpVHJWXCb68kMBAYHUguqvRBl3IhVMmYCLOMxwcDgc0Gg0cLvddGSNw+Hg7UN/JudOer0eGo0GRUVFaG1tjeqe+d577zEylmAUFBSEHdkCrN1QNdnyzZlALBbjmWeewcc//nHW9zUwMBBUOAeA4eFhvPDCC7Db7Xj33Xf9fvfee+8hLy8PMzMzMQltfPsbZgs+Xq9iJT09HaWlpSgtLQVJkrBYLDAajdDr9TAajRCJROjt7aVr/1RYSZLoznMg8edNCacgJXpsC9MxLYFw1Y19PXxjQHbt2gWVSrXqNXxynQSyVnG6vLwMtVqN3NxcPxc9VzAlnpMkiZGREYyMjNCFZODx+maSEQSBlZUV6PV6TE5Oore3Fzk5OX5CVTQXcq/dDc//TcZ8PJFifkYHxadb4l5kxHv/bEK5hjMzM9Hf348NGzbQzoH+/v6gES/JgBDbwg3B8tKpiJe+vj643W4olUramc5mXnqiOygEBARSh+npafT29sbcXylW+BDbQonHBQUF2LFjh9/KWODsfI3rOj8UTIjnJElidHQUw8PDaGlpQWVlZdTbOnHiRExjWQ+9Xo/vfOc7+MlPfhLW66l7vG894na70dXVBYvFQseGCpylqqoKr732Gp555hk89thjrOyjo6NjXZ2jv78fKysrePPNN9d8TVlZGVZWVqLav+A8Tx5EIhFycnKQk5ODqqoqjI6Owmg0Ii0tDRMTE+jt7aVNNCqVKqnmlr4kuvPc6/XC4XAk9LyJX1UBT2GqyGMjpiUQ6g8qXk+mqE7tcrkcHR0daz4F5LPzPNjYJicn0d/fj4aGBtTU1MTlBsWEeO77YCPcRjlisRi5ubnIzc1FfX09LVQZDAb09PTA6/VCpVLRrvRwz2vrOzMxHUvUTDqx8qt+KG6Kv4Ce7FDd36nzh4p4oRpDUhEv1DK8vLy8hG6+mMoZfPFcTZCWloaSkhKUlJT45aVTznSRSOTX3JbJe2+iOygEBASSH4/Hg97eXiwuLkaca80G8TTQ+DqRW1paUFFR4VdzUPMoPs5RYp07ud1uaLVarKysYPfu3THnStvt9pjevx4kSeK5557DHXfcgbKyspCvp75Dap5ksVhw5swZZGZmplS+eSQUFBTg3nvvZU08v/POO0PWxOEI4ysrK1E3dk3U+USkJLt4HgwqchY4a6Kh5pb9/f20iSYZ5pYUBEHQ8+pExWKxAEBCP8gUxPMwkEqlMYvns7Oz6OnpQUVFBaMxLYH4OibYzqILhHK0hNNAk8/iua9I7fV60dfXh4WFBbS1tdFOx3gQzmdmNBpx3XXX4Y033gAAlJeX47bbbsNnPvMZSCQSnDlzBmlpaes+2AhFoFBlsVig1+vpLGK5XO7XKXutJ6SkzhLV/hlhyQmnbhkZTatXRbBNqjshZDIZioqKUFRUtEroHBsboyOCEjHiJdGLmmjh00ODYHnpZrN5VV667zUqlnulIJ4LCAjwGbPZTPe22bdv35oRClwSr9gWl8sFjUYDu92+poHEdx7FN2KZO1HmpszMzJjmAL7s3LkTTzzxRMzbWQu73Y7p6emIxfP5+Xl0dXWhuroajY2NCS+asQVJkvjhD3/IyrZ3796NAwcOrPuacOOCvvKVr+Do0aMRjyGV5lsEQaTUeR4470hLS0NxcTGKi4vpppSUmE7NLX1NNHy4D0YKde1PZOe51WoFAMF5ziWJFtvi25Rn8+bNKC4uZnh0/rDRUCYUvlE04Tpa+CyeU2Oz2+3o7OyESCRCR0dH3C+0oZznzz77LK677jq/n01PT+P222/Hgw8+iB/+8Idoa2tDc3MzY0KX7zIqqlM2dbMaHBykXcWUKz0rK+vDv+GM+Iptzrfm4iKepxKhnBDBhM6VlZWEjXhJteKVgk/ieSC+zW1ra2vh8XhgMplgMBgwOjqK7u5u5OTk0EV1pHnpVqtVyFAVEBDgLf39/SgrK0N9fT1v7k/xiG0xGo1Qq9VQqVTYvn37mpEsIpGIt3OUaMc1MzODnp6esMxNkXDZZZfhy1/+MiPbCobBYAj74TR1TMPDw5iamsLmzZs5b4SbSIhEImg0Gvz4xz9mZftf+cpXoNFo1nX+1tXV4corr8QHH3yw7rYEg0JoUs28s97xikQiZGVlISsra9XccmZmBgMDA35Gv9zcXN5FdAWDumcm8vdstVqRnp6eEJ/3WiTuyDkk2iacVqsVGo2GFl+5asojFos5K0ptNhvUajV9jOEuh+drYQp8KFK/++67KCkpQWtrKy8uVGuJ5yRJ4ic/+QnuuuuuNd+r1+vx+c9/HkeOHEFraytrY5RKpUEbR+r1eoyOjtJZxXl5echsUYKYWWBtLCFxxNdVxJdJLNtEcpyJHvGSasUrRSJl8EmlUr+8dKfTSZ9jvnnp4Z5jNpstoR0UAgICyc2uXbt458DkMraFJEmMjY1haGgITU1NqKqqClk3cDmPioRI504EQaC/vx+zs7OsxPWkpaXh3HPPxfHjxxndri9tbW2YmJgI2SOMWskwPz8v5JuHyTe/+U1Wtnvw4EGcf/75fqtKJRKJ36rStLQ0iEQifOlLX8K3vvWtdbd33333RTWOVIoySaVjBSIz7QSbWy4vL8NgMECn08HhcEChUNDnZk5ODi/ncpRBi49jCxdqtW4in6uCeB4Gvvl34QoEc3Nz6O7uRnl5OaNO33DgqihdWFiAVqtFaWkpWlpaIjpGvornJEliamoKANDU1BRTIx2mWUs8v+GGG/C///u/YW3jlltuwS233ILXXnsN+/fvZ3qIqwh0FVM3q/HxcWDegUbkQAQR4nEJlTZGl58XK3ybxLJJrMVcokW8pKrzPJG7v6enp/vFUK211JNypgc+IBZiWwQEBPgMH4VgrmJbXC4XtFotzGZzRBnf8cxkX49I5k4OhwNqtRoEQaC9vZ0VA5dYLMadd94Jk8kEjUbD+PYpqqqq8Pbbb2Pnzp1Bf0/lmwPA9u3bBeE8TObm5ljZ7qOPPrpq/ket+KOaO+bk5NC1u06nQ2NjY9BtFRcXxzUyNVFIRfE8WtOOTCbzM/pRc0uj0YjJyUkA8Kv7uTK/hiKR51oUFosl4edMCSeexyu2BTh70ob6Q6We8nMV0xIMtpdDkiQJnU6H8fFxbNy4MawsukD4KJ5TzTSXl5cBgHdL8YOJ548++mjYwrkv5513Hq644gocPXqUsyY6vkInANhnV+DsGQEAkAgUlFn+OxcBGXu5/9tMNZgs5kJFvPT19SErKyuuES98ji9hk2Q57mBLPam89Lm5OQwODiIjIwN9fX2QSqW46KKLYLFYGHWeHz9+HA899BBOnz6N2dlZHDt2DJdffjn9e5Ik8d3vfhf/8z//g+XlZezbtw9HjhxZc+IpICAgwDe4iG1ZXl6GWq1GTk4O9u3bF1FvCz4+cADCnzvp9XpoNBoUFhZiw4YNrNVC1Lzk5MmTeOedd3Do0CFW9gMA559/PoxG46qfz83NQavVoqamBiMjIwkdB8AlVOM+JpFKpdi+ffsqk4GvCaG+vh4ul4s2wvT09MDr9eLvf/87LrzwQr957r59+/DXv/41pjGliqCciuI5U/MOuVyO8vJylJeXgyRJuu5fWFiATqdjtE9SLCTSKt+1EJznKQL1x+nxeNYVGgMjTOL1pIrNos/pdEKj0cDpdMa0LI5v4rnFYkFnZycyMjKwZ88eHD9+nHcO4UDxfHp6GrfddlvU2zt27Bhefvll9Pb2xuUhT0ZJDlyZAGwAJZaT//r/D8V0kc//M4QUyLy+ERJF4jSiTFTYLObWi3iJV6d1IbYluQiWl768vIw33ngDTz/9NL761a+itLQUL7zwAurr6xnpjWG1WrF161bccMMNuPLKK1f9/oc//CF+9rOf4ejRo6itrcU999yDCy+8EL29vXHvyyEgICAQDmw6z0mSxMTEBAYHB9HQ0ICampqI7/2J6jwnSRKjo6MYHh5GS0sL66tnfcezb98+OBwO2Gw2fOtb38I//vEP6HQ6xvZlt9vx7LPP0vdFXyPXli1bUFxcjLGxMU7nboksWFJO/ViRSCQoKyuDUqmEQqHAwYMHoVKt308qLS3Nb8WfxWKBwWDAG2+8gZmZGbhcLtTU1KCyshJisRhDQ0N45ZVX8Oqrr6Kvrw8WiwXp6enYvXs3br31VrS1tQUVNPk2j2cLkiQx4SWhIoDaeA+GI9gy7YhEIigUCigUCtTU1MDr9dKr5n37JFFzS6VSydm8Lxmc58mwWjchxfNQjRPZ2F8ol0Q8Y1oCYavo822209bWFtPTfT65Oubn56HValFZWYmmpib63OJb4Uyd9wRB4JFHHsE3vvGNmLdpt9vR0tKC2dlZzs9ZkUgE+acbYX8ssLg+G+Py4V84JaXHLqRLOgqQfbAihi0wR6IW3JHA5cQiVMSLRCLx67TORsRLqsa2JIvzPBRSqRQFBQW46667cNddd2F8fBzXXHMNVlZW8OlPfxpGoxHnnHMOzjvvPJx33nnYtm1bxOfD4cOHcfjw4aC/I0kSDz/8MO6++25cdtllAIDf/e53KC4uxl/+8hdcc801MR+jgIBAcsHHe5JEIoHT6WR8ux6PB93d3TAajdi5c2dIEW8t+DRH8WU98dztdqO7uxsmkymiiJpYx0OSpF+tl5mZiZ/+9KcAgL///e+49NJLGdvf73//e1x55ZVwu93QaDSw2Wxob2+nV39xrQ8kMkzMIYGzf8uNjY0QiUQoKyvD5ZdfHtE1RyQSIScnBzk5OaiursamTZswPz+Phx56CE888cSa7zObzXjxxRfx4osvoq2tDb/85S/R0tISdPvJzHfHFvGHpRUA6YCTgOjUMK4tyIHFS6DP6kBLZhq+VV2EQllCSn5rwpVZierV5tsnKXDVBNWLS6VSseqqTgajktVqTfg+Ucn1l8QiUqk0aCHlG9OyadMmXnT2ZrroI0kS4+PjGBwcRFNTE6qrq2O+MIjFYrjdboZGGB0kSWJwcBCTk5NBvzu+FWAikQherxc33HADnn76aca263Q6sXv3bpw4cYLzzOi0gizYK9KBqdWTKFHAf1HfRrSudNH5RcjeHXnEENPw7bxik3i5coJFvJhMJhiNRjriJTs7my52mIp4SRUROZBkcENEQ1VVFVZWVvDII4/gwIED6O/vx6uvvorXXnsNP//5zzEyMsJooTs6Ooq5uTmcd9559M+USiX27NmDEydOCOK5gIBAQsBGbMvKygrUajXkcjn27dsXUyQhn53nwT43s9mMzs5OyOVydHR0cBbHSNV3a9V6F1xwAY4ePYrrr7+ekf3ZbDb6WLOystDe3u7nOBbE8/Bh6u/P5XLhH//4B4CzjT2bm5vDfu/8/DxmZmbgdrvx3HPP4fnnn8fo6GjE3+GZM2fwrW99C7/4xS/8omST/Vy4QjOM7gAphQTwhyUz/W+dy46/Wnq9PwABAABJREFULY8DAK4ryMFdVYVIFyf+A4V4mZXS09NRWlqK0tJSkCQJq9UKg8EAvV6P4eFhSKXSVY1xmSIZ5lqC8zyFCFboUTEtAOIa0xIIk0UflQNuMpmwa9euqF0cgcQ7tsXlckGj0cDhcGDv3r1+T8FEIhFEIhHvCmeHw4GXXnqJUeGcYmhoCIcPH8ZLL73EfdNFb3g3P18xfbUr/ezP19pS+tU1yGjIjWZ0AjHAlyWtvnmLvhEver3eL+IlPz8feXl5UTsH+HK8XJMMboho8c3va21tRWtrK7761a+yci5Qzb0CY7aKi4tZa/wlICAgwDRMiuckSWJqagr9/f2ora1FfX09IwafRHGez8zMoKenBzU1NWhoaOC0BqGEnPWMA1dffTWqqqpw8ODBmPe3adMmvPfee2seqyCehwdbkUn33HMPJiYm8KMf/WjN1xAEgddffx033XQT9Ho9Y/t+/fXXcfr06VV92JKlJh9xuHDP6Dy0VhdUUjGUINAX4df4hyUz/rBkxjX5ObihNBe1Gdw8ZGMDPpiVRCIRsrOzkZ2djaqqKni9XtqoNTk5id7eXmRnZ9OrnmM1avHhmGNFEM/jRDxujoGFHp9iWgJhquhj08kQz8LUZDKhs7MTSqUS7e3tQeNn+CSeEwSBX/7yl3j88cfR09PD2n5OnTqFSy65BK+88gqnxYZsez7cs9MRvScSV3rmf7ZCli3km8cDvorJgREvNpuNXoY3OjoKiUTi1xwm3AdKyVDYREOqHjdwthAM1vuDj+e9gIBA6sHHaxFT4rnH40Fvby+WlpbQ1tZGL62PFT47z6lx+a583rp1K4qKijgfD3Vuhfqs2tvb4XA48NZbb+GTn/wkFhYWIt4X1YySyjcPRryNWZFAuUj5+PcZC//zP/+Dhx56KGhN6HA4cMkll+DkyZOs7PuFF15AVVUVXb8nyrkQir8umvD18SX633YPgZkYtve03oyn9WZIADzeUIwOZeI1cOTjvMN37kg1xmWyF5fX6014o5IQ25JCUIUeQRAYGBjA9PQ0b2JaAmGi6JuenkZvby9rToZ4FThTU1Po6+tDfX09amtr1zwuKscv3rz//vv44he/iN7eXk7299577+GVV17BRRddxMn+AEC+OR/uV6eBGFJ8grnSXSDQu3MZmb0a2lHMZWOPUCRaoRINfPgbCoVIJEJWVhaysrJQWVlJR7wYDAY/54Bvc5i1ipdUbBhKkmRSLCWMBo/HA6fTyZmLgqo35ufnUVpaSv98fn4e27Zt42QMAgICArHChHhusVigVqshk8kYadbsC9+d5w6HA2q1Gl6vN64rn6n7fri13jnnnIOJiQl6/icWi6HX6/Gzn/0MR44cwcrKStD3SaVS3HXXXbj88svXFV745jx3uVwgSdLPgHH8+HH84Ac/wMmTJyEWi1FZWYlbbrkFN9xwQ0y9xCKB7f088cQTuOGGG+h/O51OvPLKK/jUpz7F6n57enqgUqmwtLSE4eFhSCQSkCSJhYUFqFSqoE1F+Q5Jkn7COZN4AXx2aB7XqLLw/brihJqXJsJ8Ky0tDcXFxSguLg7ai4taFU3NL0Pdw5Jhla/gPE8hJBIJ7HY73nvvPQD8imkJJJai1Ov1or+/H3Nzc9i2bRsKCwsZHt1ZuBbPCYJAX18f5ubmwnKn8MF53tvbiyuvvBJLS+zcNNfi+uuvx/z8PGf7E0nFyP7KRlh+1Q/S4v2X/B39DVwEAE2ZKLyqER1u96rGHtSNKj8/H3K5nKnDCBs+FfZsw1fn+Xr4RrzU19fD7XMO9fX1we12081hAiNeUrFhKHU+872IZQOLxQIAQZ3nbFBbW4uSkhK8/vrrtFi+srKCkydP4pZbbuFkDAICAgKxEqt4TkWVVFdXo6GhgfH7D5+d5zabDe+++y4KCwuxYcOGuIop4TrPA/H9vvLz83Hvvffi3nvvpX9GEAR++tOf4v3330dZWRmuuuoq7Ny5M6T4yRfxfHh4GDfffDPef/99v5/LZLJV/b6Gh4fx9a9/HV//+tdx1VVX4Te/+U1E+9q6dSvsdjv++te/or6+nrO8+/U4deoULZ5brVZ8//vfx5EjR1jfr0ajQUVFBR2hMT4+junpaYyOjqKnpwcKhYKu3RUKBW/rdepvnCAI/K608V8/jW1uvB5PG614XzuBFzZXQcrTzyQQPjrP1yNYL66VlRUYDAbMzs5iYGAAcrmcXvGsUqlWPeRKBqOS1WpdFa2UaCSkeB6Pi53H48HQ0BAqKirQ0tLC65M3WscEleEuEonQ0dHBqrDIpXjucDjQ2dkJkiTDPi62neeUW3N5eRkSiQQqlQperxfT09NQKBTIzc3FjTfeyLlwDgB2ux1jY2OoqanhbJ8SuQzK/9yMmelpLEwuoFVaDteQCcSSHTBFdi6nf6wSGS1nH46kpaWhpKQEJSUlIEkSFosFBoMBCwsL0Ol0yMjIoF3pKpUq4Z/o8o1EFM8Dkclkfs6B9SJeXC4Xr+8NbEBdx1Pxb8dqtQIAo0sQLRYLhoaG6H+Pjo5CrVYjLy8PVVVV+NrXvob7778fjY2NqK2txT333IOysjJcfvnljI1BQEAgeeDjPTha8dzr9aKvr49ebcOmwYdvznOSJLGysoLl5WVs2LABFRUVcf9uqR5RTM+XxGIxrrnmGmzatCmiHHs+iOfz8/M4dOgQDAbDqt8FCueB/PnPf8bzzz+P8fHxkHNVhULh9+89e/YAALRaLaqrq0OO88knn2TNCf7JT34SwNka6bLLLlv1EIFNurq6sG3bNkgkEmRnZyMjIwO7du2Cw+Gga/fJyUkA8GvsyOTKlXChTJmnTp2C2WzGJZdcgscffxx/+MMfAACS6jrkP/4MQJ/75IfyOcN/+yMuD7afHsF722uRJeH/PCbRzUpisRi5ubnIzc0FcFZnpCJehoaG4HA4/B725OTkJNwDg2AIsS0pABXTsrKygpKSEmzYsCHeQwpJNI6JhYUFaLValJaWcvJwgCtXh16vh0ajQVFREVpbW8MWeNhynvf392P37t1wuVx+P5fJZJDJZPB4PPB6vRCJRKw1dAmHH/3oR3jkkUc4369ILAaZDqRvL4SsJRek0wtxlgxepwe2MwsgjS5ImhRIq8yG/S/jwJTjwzcXpyHr8lpIC4IXnCKRCDk5OcjJyUF1dTU8Hg+Wl5eh1+uh0+ngcDhoR3F+fn7UTSPDPtYEvumHSzKI576Eingxm82QSqUYGhoKGfGSLFACQ6IXdNFgs9kgl8sZ/Y5PnTrl11jttttuA3B2RdATTzyBO++8E1arFTfddBOWl5exf/9+vPzyy3GZ+AkICAhEQzTiudVqhVqthlgsZt3gwzfnucfjgVarhdlsRkFBASorK+M9JBqmzVAEQUCn02FycjLiLHeuxHPqoUEwjh49GlQ4DxeHw4Hi4mKcOXMGDQ0NQV8TKJz7snnzZszMzIQUqFpaWrB79+51he1Dhw5BqVTi2WefDW/w/2Lfvn0gCAK33norp8I5cNbJ7xtjR31PGRkZKCsrQ1lZGf0gymAwYGZmBgMDA8jMzKSFylgbO4biD3/4A774xS+u+vnDDz/84T/EEqiO/H6VSE6f3f86z0X0/8WOA8CjMwbcUVnAzAZZJBmEZF+kUikKCwvpB8J2u50W06empkAQBNLS0pCenk7PPRJxfm2z2ThbrcsWgni+DjabDRqNBiRJori4mLcxLYGIxeJV4uxakCQJnU6H8fFxbNy4kbOlFGw7z0mSxPj4OHQ6HVpaWiIuNNlwnh86dAjvvPNO0N+53e6QjgQu0Wg0cds3HQORLQOyzy7RlGZIoDjo/x2mXd9CvzaaG4hUKkVBQQEKCs4WCb6O4rGxMdpRTDnTEzErL94km3geSGDEy+DgIKxWK9xud8iIl2SBuo4n23GFg8ViQWZmJqPHfuDAgXXvPSKRCN///vfx/e9/n7F9CggICHBJpOL53Nwcuru7UVFRgaamJtZFk0jmUWxjNpvR2dkJuVyOqqoq2O32eA/JDyYFa5fLBY1GA4fDgb1790bsUOSD85ypZphtbW1BRfBw5s7Hjx/Hv/3bv637GpFIhCNHjmBoaAjXXHMN/bmlpaXhqaeewquvvoqpqSlYrVa0tbXhzJkzYY1bp9MBAMbHx3Hs2LGw3sMkvg8c1joXRCIRlEollEolamtr4Xa7gzZ2pOZ/TNTudrsdarUaN998M8bGxkK+vvDl9yAKQ8An//V/TInoT86bBPGcB8jlcsjlcvphj9lsxuDgIOx2O06ePIn09HS/vPRE0SgsFouQeR4PuJikz8/PQ6vVoqysDM3NzRgcHIyrEzgSwnVMOJ1OaDQaOJ1O7N27l9MnQWxmins8HnR3d2N5eRm7du2il8REAtPi/n/+53+uKZzzkYGBARgMBuTl5cV7KOvC5LUgMIvMZDJBr9djfHzcLysvPz8fOTk5Ud+0413Yc0myi+eBiMViZGVloampaVXEy8jICKRSqd8yUT5kU8YK1cAmlb5nimQoAgUEBAS4hpqnhKoRqNW/09PT2Lx5M4qLizkdX7yZnZ1Fd3c3ampq0NDQgLGxMToujC8wNV9aWVlBZ2cncnJy0N7eHlVTSz70q2Jy3nT48GG89dZbfj9bXFwM+b7u7u6Q4rnvPkwm06qfn3POObSQ7PF4cPjw4bC2RxmS+vv74XQ6w3oPk2zZssXv3+HUpjKZDEVFRSgqKgpau8tkMr/aPRKhcmVlBR/72McieqiiePBnYQnnvpAARCQZc5wLvx7NrU0iNAxlCpFIBIVCgaysLOTn56OqqgrLy8u02a+npwc5OTn0+alUKnn72dhsNiG2JdnwLdQ2bdqEkpISAGcLKb64EEIRTlaf0WiEWq2GSqVCW1sbZx2+KdgqTK1WKzo7O5GWlob29na/DueRwJR7wev14sknn8Rjjz0W87a4xG6349ixY/j85z/P6X75IsD5OoqBsw+aqEKqq6sLJElCpVLRrgQhMiE4qSae+2bwhYp46e3tRXZ2tl+xk4gRL8nQwCZaqOy+VDrHBQQEEgs+Xp+oe53X611z/uG7+rejo4PT1b/xzjz3nYv6Rpdw2S8qXJgQrKkGsHV1dairq4v6nOWD8/zqq6/GH//4R0a2FWwVcDimCyYeMmVmZqKtrY3+94033ohf//rXId+3uLiIkpKSuJhDbrzxRr9zJ5pzIbB293q9dO0eaKaiGo+uVQOTJIldu3ZhdnY2/AHIZMjYvS+qcTPB7szEcDAneuZ5NFDzLYlEgvz8fOTnn+3vRmkURqMRPT098Hg8vF31nAymI0E894Eq1AiCQHt7u9+XG2tneC5ZT5im4kwGBwfR1NSE6urquPxBsVEALiwsoKuri5FlnUyMb3l5GVdeeSXefffdmLYTL9544w3OxXOAn87s9PR0lJaWorS0lF4+pdfr6Q7ZVFZefn5+2CIoX25kbJJq4jlJkmt+94ERLy6Xi14mmsgRL8m+dHI9bDZbwsS5CQgIpC58EBV9oQTztcRzqg9TSUkJWlpaOH+wHE/nucPhgFqthtfrXfXQgC+OeF9iibkkCAKDg4OYmpqKON+c6bFEylr12Uc/+lFkZmbCZrMxsp833njDrw8KZepZj337whNfI/ms/vu//zss8Zwi1u8yGs455xzGt0lFeFIrCnzNVFqtFgRB+LnSfXsx/OlPf4pMOAcgzi+M2D3O5Fzh9iruv7doSMW5B7XSN5BAjcJqtdJiuu+qZyrmJVpjaaxQqzqEzPM4wIagQMW0UA0zA0/ORBPPg42VajhjMpmwa9eusG7AbMGkeE6SJIaGhjA2NoZNmzahtLQ05m3G6qSw2+1obW2F0WiMeSzxIh43pUQQC6nlUwqFYlVWnq8ISrnSmc5ETjRS6dgjKebS0tJQXFyM4uLihI54WauYSwUsFkvCLz8UEBAQ4BqqLgicq1DNIicmJjjtwxRIvJznBoMBarUaBQUF2Lhx46p7K1fOc7fbjZWVFZAkie7ubjz44IN4//33kZaWhnPPPRe1tbU4efIkXC4XVCoVtm7dCrvdjpqaGvzbv/0bmpqaQtZ+LpcLarUaLpdrlWEtWuL9kIgkSbS2tjImnAPAZZddhlOnTqGpqYn+2alTp7Bz586gr7/11ltRW1vL2P4pZDIZPvvZz+KJJ55Y93WUyBwPY0FgZA4bBp5gZiqDwYD5+XkMDg5CLpfTdfszzzwT8fZJW2SxTGseX5QRLluy4iOsRgJJkikV20IRzkpfkUiE7OxsZGdno6qqym/V89TUFPr6+pCVlcVZc9xArFar4DxPdHyfem/cuHFN4VUqlSaMeB6s6PNtONPR0RF3IYapAtDlcqGrqws2m43R3PZY3AsPPPAA7rvvPkbGEU+uuOKKeA8hIQiWlafX66HX6zE8PIy0tDTala5SqXjl/mKbVHOeR7uMMNKIl9zcXN4Ujake25LoRaCAgIAA14hEolVGH4fDAY1GA7fbjfb29rg+mOTaMEWSJMbGxjA0NITm5mZUVlYGrSXYFs+9Xi9ee+01/PrXv8bf/va3Vb93OBx4/vnnV/38jTfeoP/7W9/6FoCzDe+6urpQWVm56vUmkwmdnZ1QKpWMRodyKZ4H288DDzwQsdM4HHbu3InR0VE6pqGpqQmzs7OrNIt33nkHGzZsCHv1a6Sf1cMPPxxSPKf0hfn5+Yi2zQQzMzOc7s/XTFVTUwOPx0ObqQYHB6P6DNK2Bn8ostb+1/llxPsGgFMWB/bkyEO/MI5Q522qzT2iMSsFrnr2NfwNDAzA6XRCqVTS88ucnBxW5+1U3GUik9LiOdX5OFhMSyCJ5jz3La6mp6fR29tLN5zhg5jFRAEY2FyGyU7D0Y7vL3/5S1II51lZWbj00kvjsu9EFpd9RdCqqip4vV66qcfw8DDsdjt90zCbzazfpOJNqjkDmDreYBEvlCu9t7cXHo/Hr8t6PFc3pOLSSYpkaHwjICCQ/MTbkRsMX1PS0tISNBoNioqKwhb/2ITLeBTfVcG7d++GUqlc87Vsi+cvvPACbrnlFuj1+pi3Zbfb0djYiLfeegu7du2if85Uvnkw4n2e//CHP2Rt283NzVhaWqL/nZWVhZWVFdb2FwyxWAyDwbBmU1Tf5qZdXV1cDYvm5ptvxuTkJO688076Z1zWxlKpFIWFhSgsLAQAXHzxxUFz69cj/ZKrwn5tKINSNAYmo4f/Whd1DUy1uQcTZqVAw5/dbqfnl+Pj4xCJRPTcUqVS+cUQxYrb7YbL5RJiWxKVSPP0Ekk8p5znXq8X/f39mJubw7Zt2+iLOR+gnN3ROlOpBwJsFF9A9AXYJz/5SUbHEQ8kEgnkcjkGBwfR2trK6b6TTUj2berR2NgIh8OBubk5mM1mqNVqv5tUfn5+3FeEMI3gPGeGtLQ0lJSUoKSkxC/PjlrdIJPJ/PLsuDyPUlk8F5znAgICAtEhFovh8Xig0+kwNjaG1tZWVFRUxHtYALiLR6FqwYyMjLBWBbM5LqvVittvv50R4dyXc845B0NDQygrK6OboLI1J42neO5yuVjf/rFjxxhdFRzNZyWVSrG8vIz77rsPv/jFL2gD4q9+9StGYlNj5f7778e2bdtwwQUXxP2B4Wc/+1k88MADkb3JZmZk3/SxRxjfsiWT/7Et1DUwleaXAPMxmSKRCJmZmcjMzERFRQUIgqBjiKiebhkZGX5ieiyrhCwWCwAkvOkoIcXzWP5YqJiWycnJiPKxE0k8l0gk8Hg8OHnyJEQiETo6Ohh9csQElNgS6YWAIAj09/djdnaW1QcC0RSoOp0uYc6R9SgqKoLb7YbD4YjL/uNd7LBJRkYGiouLMTIygv3792NlZcUvhyw7O5vOSlcqlQkvSqaieM72dxaYZ+f1eumIl4mJCfT29iInJ4cudtg+j7xeb9xdgvFCyDwXEBAQiA6RSISBgQEQBMFo7CITcDHnm52dRXd3N6qrq9HY2BhWrcSWeG6z2bBjxw5MTk4yvm0A2Lx5M15++WU6koeth85cPfQIxqlTp1jfx7333suLSE2xWIzvfve7+O53v7vma3ybnHLNZz/7WbzzzjtIT0+P6xwkmr5n1l//HBnnnBf264PNs/zm0REe/5/mDfhaVXFE7+EawXnODmKxGEqlEkqlErW1tXQMkdFopFfPKxQK2qilUCgiGo/VejbPP9FNRwkpnkeLb0xLR0dHRF9eIonnJpMJLpeLdtXz8eISjXju24G+vb2d1WYk0bgXvvzlL7M0Gm6x2+0oKyvj3HUOpNZTZLFYjNzcXOTm5qKurs4vmqOnpwder5e+QeXn5/PuAVg4pJp4Ho+YGolEQgvlAFadR2xHvKS683yt5csCAgICAsExGAyw2+1QKpXYs2cPY5nXTMGmCEsQBO3A3rp1K4qKiuI6Lq/Xi6qqKtoVyAZ2ux1PPPEEHnnkEVa/63g6z//85z+zvo+RkRHW98EUjY2NaG1tRV9fH+f7tlgseP/997F//37O9+1Ld3d3xO/xTk3AMzcLaUn4Lv61zvloav3fLFgSQjwXiUQpNb8EmHeehyIwhsjhcNDzy+npaRAE4Te/lMvl634nVqsVcrk84Q1X/KpWWISKaSkuLkZra2vEXxzl5uYzJElCp9PRmUUbNmyI95DWhBJbvF5vWFnlBoMBGo0G+fn5QTvQszG+SAvUeBQIbCCRSHD77bcjIyMj3kNJWoLdXAKjOSwWCwwGAxYWFqDT6ZCRkUG70nNzc3k32QxGMq8iCAZbsS2REG7EC7UEL9aIl1QWz202W8I7KAQEBJKfeN+XKEiSxOjoKIaHhyGXy1FeXs7LWoaKv2SaQBNQpPcPpsXz2dlZ7Nixg1XhnOLpp5/GkSNHWN1HPMXznp4eTvYzPT2N8vLymLfD9jVBLBbj5ZdfRnV1Nav7WYs//vGP2Lt3L2+ufZGwfNsXUPCH1Y15IyHa405PgI8r1fppUcR7vpWRkYGysjKUlZX56RSLi4sYGhoKOb+koi4T8W/SF/5VLGEQyYdOEAR0Oh0mJiawceNGlJWVRbVPynnOVyel0+mERqOB0+nE9u3bcerUKd6OFfjwOwxVBJIkiYmJCQwODq7bgZ5poilQGxsbsbCwwNKIuOPhhx/GZZddFrf9J7vgGs7xiUQi5OTkICcnB9XV1fB4PFheXoZer4dOp4PD4UBubi7tSufrzYjP1yA2iHdhE8h6ES/j4+Po6emJOeIllWNbrFYrr6IGBAQEBPiKy+WCVquFxWLB7t27MTQ0FLeIjVCw0TDUYDBArVajoKAgahMQk+K5zWbDueeeC4PBwMj2QmG321mvF7gSzz0eD/r7++HxeGhTy/z8POv7BYDt27cnzFxTpVLh7bffjosD/LXXXsOhQ4fwm9/8hvN9U+zduze6N7rZzc9fj5/Xhb8SJl7wwajENSRJsh7bEgmBOoXX68Xy8vKq+aVCoYBOp8OhQ4dY7xP1ve99D/fee6/fz5qbm9Hf38/ofhJSPA8Xu90OjUZDP+GPJZuUutlzvWQiHIxGI9RqNVQqFdra2mi3BJ+FK5FIFLII9Hq96O7uhsFgwM6dO6FSqTgdX6QF2Le+9S1cfPHFLI2IO84555y47Zuv52u8kUqlKCgoQEFBAYCzkx5q6dTY2Bgd3UEV8eGs5uCCVHMH8P14Q0W8eL1e+qFMuBEvfHtgwCVCw1ABAQGB0CwvL0OtVkOhUKCjowMymYzXcZhisRgkSTJyfyNJEmNjYxgaGorZBMSUeE6SJDZs2IC5ubmYtxUJo6OjaGhoYG37XIjndrsdZ86cgUQigUKhoHvNTE9Ps7pfCofDAb1ej/z8/Ji3xcWDhi1btuDFF1/Ev/3bv7G+r0AWFhZw8cUX4+abb8ZDDz3E+f6jbYAsyo1d74hWA9qj4r8hJBXnHdR1n28aJIVEIkF+fj59XaLmlz09PfjKV74Cs9mMDRs2QCqVQqvVYvPmzaxoPhs3bsRrr71G/5uNlW0JK56HukHGGtMSCPV+PrnsSJLE+Pg4BgcH0dTUhOrqar8TkU9PqIKxXhFos9nQ2dkJqVSKjo4OpKdz2/05mgL1vPPOw2c+8xn87ne/Y2lU3GA2m4UcXxYhnU6IHE6QBAFRlH+fgd2xTSYT9Ho9/bRXoVDQYnpOTk7crgPJvoogkERzQ0QS8bLWQxk+PlDmCsF5LiAgkAjE675EzVN0Oh0aGxv95il8Fs99DVOx1E8ejwdarRYmkwm7du1Cbm5uTONiStT/1Kc+xblwDgDvv/9+QovnBoMBnZ2dKC0tRUNDAwiCQENDA5xOJ1wu7tzCf//733Httddytr9Y2b9/P8bGxtDW1sbZSgdfHnvsMUilUvzgBz/gfN9yuRx2uz2i95A2K0ujWRsRgMGd9ZzvNxpSWTxPlOP2nV8ODw9DrVbj8ccfx4svvoiOjg5kZ2fjvPPOw/nnn4/zzz8/6mSQQKRSKUpKShjZ1pr7YHXrcYCpmJZAfMVzPhBYkPm6siPNE48Xay2LXFxchEajQXl5OZqbmxm5UNhsNrz11lv4xz/+AafTiXPOOQfnnXcelEpl0NdHW4D96le/wo033oh77rkHnZ2dIEkSOTk5WFpa4rSwigUmsvRiIZkEV6/bDa/BAKtWC+tvfwtMTgIkUCUSYfq//xv4V+dpZGVBcsnFyN69G1KVCrKCAkiKisIS18ViMVQqFX0NcDqdtJu4q6sLJElCpVLRrnQus+z5vPqFDfjuPF+PaCNevF5vzLnpiYrVamW1cbWAgIBAouJ2u9Hd3Q2TyRR09WgiiOderzdq55rFYkFnZycyMjLQ0dHByH2Sqi9iEY+ee+45/N///V/MY4kGo9HI6vbZbPQ6MTGBgYEBNDc30zUSta9nnnmG07kLH/sEhCIvLw99fX34yEc+wniMQjj84he/wPbt23H++edzupL93nvvxZ133hnRe4hFZmJ5wp2DSQD0J4hwDiT2XCta+O48Xw+xWIy2tjZ0dXVhamoKL7/8Mk6cOIFXX30Vjz76KG644QY8+uijuPnmm2Pel06nQ1lZGTIyMtDe3o4f/OAHqKqqYuAoPiTxrr7rQMW0eDyemGNaAhGJRLwp9MxmMzo7OyGXy4MWZGKxGCKRiLdZghSBYyRJEsPDwxgdHWX0wYfT6cSdd96JX//61/TPfvnLXyI7OxvDw8NBBXSxWAy32x3V/nbv3o1XXnkFFosFZ86cQVZWFrZs2QK3242Ojg5GiwamC8WtW7fGtShLBqGVJEm4l5ex+LVbQfb2Bn3Nqluf1Qrv03+E6ek/0j8SH74IxbfdBkmETqX09HSUlpaitLQUJEnCbDZDr9djdnYWAwMDyMzMpAXQ3NxcVm/EqSaeJ5rzfD0CI16cTieMRuOqiBen0wmZTJZy3zXl1Bec5wICAgL+mEwmqNVqZGVlrSkcSyQSeDyeOIwuNNS9LNo53+zsLLq7u1FdXY3GxkbG7o2+4nk0DAwM4I477mBkLNFARQ+yBRvOc4Ig0NfXh7m5OezYsWPVytwnn3wSX/rSlxjdZyguvfTSmLcRj3pNLpfjxIkTuPXWW3H06FHOzVLf/OY3MTs7i4svvhhVVVWcGAy/+MUvRiyew+uBe7AXsqYNMe+f+ozpb1vk9y8AwFtb4tPUNVpS0XlOpUkk8jyLirpMS0vDRz7yEXzkIx/B/fffD6PRyMi1YM+ePXjiiSfQ3NyM2dlZ3HvvvTjnnHPQ3d3N6FwtYcXzwBvk4uIiurq6GItpCQYfxPPp6Wn09vaipqYGDQ0Na/4RsdUpnkl8hV+3242uri5YrVbs3buX0ZP8l7/8pZ9wTmGxWFBcXIxXX311Vc53rAXY/Pw8urq6/L4nmUwGtVqNP/7xj7j++utDbkMqlaKxsRGXXXYZvvWtbyE9PR1vvPEGKioqUF9fD7vdjvT09FVit9frxY9//GP83//9H0wmE8bHx8MqtMViMX77299GfcypjmN2Fktf+SowPs7I9oiXXsbsSy8DdXWQX/zvyLv2WogifLAhEomgUCigUChQW1sLt9tNC6D9/f1wu93Izc2lXenhZFxHQqoJqslc0KWnpweNeBkfH8fU1BQWFhZCRrwkG0LmuYCAQCLA1X2YJElMTk5iYGAAdXV1qKurW3PfEokETqeTk3FFCmWYilSkJggCAwMDmJ6extatW1FUxGzzvVjEc4Ig8JWvfAXjDNWo0bBx40ZWt8+0eO5yuaBWq2nzk1wu9/u9yWTiXDgHwFiUaTxW+kokEvzsZz/DHXfcge9973t44YUXYLPZONn30tISnnrqKfT392P79u3Yu3cvtmzZwvp+Dx06hNdffz2i9xhv+RQKnn8bYjkzqxtJACJaOCfP/gBAjcgD99ICHByvTI6FZDIqhUsyzC/XmjMxtRLk8OHD9H9v2bIFe/bsQXV1Nf70pz/h85//PCP7ABJYPKdgK6YlGPEUz71eL/r7+zE3N4dt27ahsLBw3dez0SmeaagxUk76rKwstLe3Myq6eL1efOMb31j3Neeffz7Ky8txyy23YOvWrdixY0fUjm6SJDE0NISxsTFs3rw5aO7S1VdfjX//93/Hvffei6NHj8Jut0OlUqG5uRmZmZk4//zzcemllwZdZpKRkUFnWK8l2kgkEtxxxx1B3SWnT5/Gn/70Jzz++OOwWCz0z+VyOX7605+ivj6+y7a4aPbDJARBYOHIEXieOMreTkZGYP/ZI5h+5OfIe/p/kVlXF/WmZDIZioqKUFRUBJIk6cajvhnXlJCel5cX8yqEVBPPU2UpoW/Ei8FgQEFBATIzM0NGvCQbNptNcJ4LCAgI4GycZE9PDwwGA9ra2kI2NOSDIWk9IjUhORwOv9XPbDxYpeqpSOcns7OzOHToEEZGRhgfU7iUlpaitbWV1X0wuerabDbjzJkzUCgUaGtrC1oPxyP+5i9/+Qvn+2SDyspKPP744/jzn/+M//zP/4TFYuFk/jc4OAi9Xg+r1YqRkRGkpaWhpaWF1X0+9dRTUeUwL128H5INW5D7nR9CnJcPUazGUBIfOs9FQK4I+FVeelxWJsdCMgjJkcL3PobhYLPZGE0FCUVubi6ampowNDTE6HYTWjynChW32814TEsw4lXo2Ww2qNVqiESioE++g8H3ohQ4W5jq9XpMTU2htrYW9fX1jAtt4RY209PTuPvuu+l/FxQU4Ktf/SoaGhrCzrT1eDzo6uqCxWIJ6Z7Pzs7GQw89FHH371jF5R07dmDHjh34r//6L7z55pv4xz/+gbKyMlxxxRWcZsAlCzNf/CLQqY74fVGd5SQJw9XXIO2fb0LKQM6ySCRCVlYWsrKyUFlZCa/Xi+XlZRgMBoyOjgZtPBrp32eqieep6IagMmEDI16o3H0q4kWlUiEvLw8qlYrxFQ7xwOVyweVycVoICggICPARs9kMtVqN9PR0dHR0hOWM5fs8JRITksFggEajQX5+PjZu3Mia6CQSiSI291gsFtTW1rIynkjYtm0b62IcUwacubk5aLXadeemJEliaWkp5n1Fwu23346PfvSjnO6Tba666ioMDAzgF7/4hZ+piy0IgsDi4iL9EOLo0aP45S9/icsuu4y1fWZmZmJwcBBNTU0Rv9fb2wX9NRdB2tiCvF/+IeoxWP/wG0gX57Dh9m+jVp6B/1dfhOx/mRXXWpmsVCppQ1VWVhZv6vZUFM8JguDtw4xwsVgsnM6ZLBYLhoeH8elPf5rR7SaseL64uAi1Ws1qTEsg8Sj0FhYWoNVqUVpaipaWlrAvFnyPbSEIAg6HA1NTU2E56aPlqaeeiup9S0tL+M53voMjR47gvffeQ3Fx8bqvpxoDyeVyxt3zvjBVGIpEIhw8eBAHDx4EcLYIdDgcvLgZJYrz3DE4GJVwHitLDzyIkgfuZ3y7EokE+fn5tFvM4XDQrvTJyUmIRCK/WI5wJsepJp6nivPcl2BFbGDuvsVigdFoxOLiIoaGhiCTyeiHMiqVKiEjXqz/avYriOcCAgJ8h837cLhxkoFIpVJez1PCmUeRJImxsTEMDQ2hubkZlZWVrNc8kYrnbOeMh4vvknq2iHWO5Lt6eMuWLSHnfhdddBEefPDBqPcXCRKJBFdccQWmpqaQn58flpFuPfhUm3/729/G4cOHcd999+HkyZOciOgUVqsVn/70p3Huuefiz3/+M2vRJSUlJbjjjjsiNs1ReIYGIn6Ps0+Lle/dAXLpwwakTz38w6DXhLVWJhsMBoyMjNB1Ox+iGVNxrpUMznOr1RpyRVosfP3rX8cll1yC6upqzMzM4Lvf/S4kEgmuvfZaRveTsOL5ysoKWlpaUF5eztk+uWxuQ5IkdDodxsfHo4qj4XNsi9PphFqthsfjQV1dHWvCOYCYv6/Z2VnU1dVhfn5+TZFkYWEBXV1dqKysRFNTE6sFCRuxJlTxPzg4CLlcTguoubm5nF+o+VTMhWL5D9E7AGLB8/e/AyyI54FkZGSgrKwMZWVldLySXq/H9PQ0+vr6kJ2dTQug68VyJNJ3GgskSaZkQRfKDSESiZCTk4OcnBxUVVWtWuHQ3d1Nr3DIy8uDQqFIiM+QmtwJmecCAgKpiNfrRW9vLxYWFqIywfDd5BNqHuXxeNDd3Y3l5WXs2rULuRE2d4+WSMTzJ554gt3BRMDVV1/N+j6ijdwEzn6fWq0WKysrYffe2rx5M4qLizE/Px/VPiPhRz/6EZRKJRYWFqDT6SCXy+kanM8RG+HS1taGY8eOobOzE9/4xjfw3nvvcbr/48eP48Ybb8TNN9+MG264AfPz85DJZPjFL36Ba665hpF93HPPPTh+/DhOnjwZ+ZtJEs5eDdI3bA36a/Nzf0J60wZIy6vg1JyC+d5vAMTq62tdXR2qq6uh1WrX3FXgymSCIOi63TeakXKlc123p+Iq32RwnlutVlYNR1NTU7j22muh1+tRWFiI/fv347333mNcZ0xY8byhoYHzoosr57nT6YRGo4HT6Yy6eSZfi1Kj0Qi1Wo28vDxIJBLWn1xu2rQp4iYdgXi9XuzevRtvvPGGnwuBJEmMjIxgZGQEmzZtQmlpaazDDQnT4jlBEOjp6cHS0hK2bdsGl8sFg8GA3t5ev6gFJlwO4ZIoznPPmc747dvlgjQtjbP9icViKJVKKJVK1NXVweVywWg0Qq/Xr4rloBqPAqnlPKcmbKlyvBSRuiECVzj4RrxotVoQBOF3Lsnlcl5+pjabDZmZmQkh9AsICAgwicVigVqthlQqxb59+6Jya/I9tmW9eRS12pSKqUnjuB4LRyAmSRJf/OIXORhRaJqamqBUKlnfT7RzJJvNhs7OTshkMrS3t0f0ffb09KCwsJDVuct//Md/4IYbbgAAVFdXw+Px0DU4FbHhO18LN26Uj/Ot7du346WXXsJVV10V8/w9Up577jk899xz9L/dbjduuukm/Md//AeWlpYYqUWff/55bN68GXNzcxG/1/SVz0H5/x5D+vZd/j//zc/hfOo3sIe5nfHxcezcuROnTp0K6/VisXjNaEaqbvd1pbOtF6RibEsyOM/Z7hP19NNPs7ZtXxJWPI/HZJqLQo8Sl1Uq1ZoNSsKBb85zkiQxOTmJgYEBNDY2orq6Gmq1mvUxHjhwAD/96U9j3s7IyAhuu+02PPnkkxCJRH4OhT179kChUDAw2tDE4qoIxOl0orOzEyRJYu/evZBIJCBJEsXFxSBJElarFXq93s/lEE9XOu/gwGmyFnOfuwEVTz0Zt/2npaWhuLh41bmyuLgInU6HjIwM5OXlwe128+o6xCbUJCTV/i5iLWKDRbwYDAY64iUtLY0uyPkU8WKxWHiVASkgICCwFkxep2ZnZ9Hd3Y2qqio0NjZGff3ne2zLWvMoKg871uOPlnDnAQsLCyFfwxWPPfYYJ/uJRjw3GAzo7OyMOB6VIi0tDSaTCdXV1TAajRG9NxQPPPAAPvOZz6x68CCVSlFYWEiL9jabDXq9HktLSxgaGkJGRgbtClapVAnnWJVIJGhoaOBcPF8LqrceE2749PR0DA4OoqioCA6HI+L3m75+MyAWQ5xfCNJqAWmzRjWOwcFBrKysRKVfBNbtZrMZBoMB8/Pz9Cp238aj0WpZa5GK4nmyOM+TYbVuworn8YDNQo8kSYyPj9MNJaqrq2MqdvnkPPd6vejp6YFer8fOnTvpxpRMCsFrsXHjRsa29de//hXHjh3DRRddhDNnziA9PT1ih0KkkCSJmZkZGI1GZGVlwev1MuIUMJlM6OzshEqlwqZNmyAWi+F2u+nfi0QiZGdnIzs7e5XLoa+vj3Y5UGI6U0+ZE0WI8losQDxF4cFBuOfmIIuiezvTBDtXlpeXodfr4XA40NfXh5mZGbqQz87OTpjvORJS1XnOZBHrG/FSXV3N64iXZCkCBQQEBMKBIAj09/djZmYGW7duRVFRUUzb49M8JRiB4yMIAgMDA5ieng4rD5vNcYUzd7LZbByMJjTbt2/Hrl27Qr+QASIVzycmJjAwMICWlhZUVlbGtO/R0VFGo3ump6fDcmn6RmxUVVX51eCDg4NwuVx040fKlZ4IdSrfrg29vb2Mbu+f//wn9uzZE92bCQLEYuwGrubmZjzzzDPYv39/1NsQiURQKBRQKBSoqamh9QKDwYDBwUE4nU6/xqNMzAFTMSIzGZznXDcMZQtBPI8AtpznlIvZZDJh165dtLgcC3xxnttsNqjVaojFYrS3t/st7eRCPB8cHGRsWx6PB3fddRedh9fU1MTqhWx0dBQXXnghJiYm6J8pFAp873vfwxe/+MWo9025hurr61FbWxtWsRnocgjmSmcqe4+PywgDsanV8R4CzK+/jrxPfjLq999777145JFHIJPJ8Oqrr2LTpk2MjEsqlaKgoAAFBQVYXl6m8/IMBgPGxsYgkUjocyXeTWeYJJWd52y5Ifgc8UKJ54kwCRUQEBCIJfaPquVFIhE6OjrCjoVYD77HtvjOoxwOBzQaDe1AjeeD03DnTlxESYZDTU0NXnrpJRw4cMBPDHa73TCbzVAoFIw5U8M9xwmCQF9fH+bn5/1MXZHuyxexWIyMjIyo3MS+ZGRkYHBwMOp4A98anCRJ2O126PV66PV6jIyMIC0tDfn5+fB4PLyeb9XV1cV7CKtgMoqytbUVL730Ei6++OK4XQetViuuu+46dHZ2MtbI0VcvAODXeNR3Dkj9LxoDouA8T0xsNltSmI4SVjyPV2yLrzuXCcxmMzo7OyGXyxnNzeNDUbq0tASNRrPmUjguXCeRNloNxdjYGH7+858jPz8fLS0tIEkSTqcTMpmMsYva5OQk/vu//xu//vWvV/1uZWUFt912G/Lz8yNuvkM1oZ2YmIjJNbSeK903e48SRyOZZCWCEEWSJEw/eyTew4BT2x31e32X6blcLnoyHE0G33qQJElHuFRUVIAgCJhMJuj1el40nWESqoFNIpzDTEGSJKdF7HoRLzqdDunp6ZxFvAjOcwEBgVRgfn4eWq0WZWVlUcVarIVUKgVBELztjULNUQwGAzQaDfLz87Fjxw7GIwgiJVxzVEZGBr70pS/h0Ucf5WBUa3Ps2DEcO3Zszd+LxWJcdNFF+NnPfoaKioqY9hWOeO5yudDZ2QmPx4P29nZG85n7+vpQW1sb9fs/8YlPBJ37RYtIJEJmZiYyMzNRWVlJr+bT6/UwGAxwu93o7OykDS18MgRs3rw53kNYxd69e6Nr9rkG+/btg9FoxKc+9Sm/rHUuWVlZwbFjx3DjjTeysn3q/POdAxoMBkxOTqK3txfZ2dn0HFCpVIZ1f0nFhqGJ7jynjJdsZp5zRcKK5/FAIpHE/ETZl+npafT29qKmpgYNDQ2MXgjiuRzSt5Hmhg0bUF5eHvR1XDjPm5ubGW+y2d3djU984hOor6+HQqGA0WhEeno6tm3bhk9/+tPYu3dvWKKKx+PBwMAA3nzzTfT09KCvrw9jY2OYnZ0N+d477rgDl1xySdjCtMfjQVdXFywWC/bu3cvosplgrnRfQYvK3kuWjvCk3Q5MT8d7GJA2NET1vrWaNtlsNnz84x/HM888E8uw/AicFIvFYqhUKtrlE+gkJknS78FLNE3I4kUqFnPU9TseBV2oiBfqwQxbES9U5rmAgIBAMkIQBAYHBzE1NYVNmzahhOGYOOp67PV64y5IB0MsFsNgMGBkZARNTU2oqqrixT0+krnTj370I0xOTuJvf/sby6OKHoIg8OKLL+LFF19EY2MjOjs7oz4fQn02KysrOHPmDHJzc1l5EJKfnw+9Xo/LL78cb731VkTvvfnmm/HQQw8xOp5AfFfzUVnt1JhHR0chk8n8VobG8++yq6srbvtei76+Prz77rvo6OhgdLtPPvkk7rnnHkZ6tAFnv+eCggLMh9mba2xsjJH9hsJ3DlhfXw+Xy0XPAXt6euD1ev1Wk66lcRAEkTSrlsMlGZznyWI64l+1wmOYcnN7vV709/djbm4O27Zto5e2MEm8Ylvcbje0Wi3MZnPIRppcCPwSiQSf+cxncPToUUa3S5IkhoaG6H+LRCLodDq8/vrruOqqq/DVr37Vz31gsVgwPj4OkUgEm82Gd999Fy+88AJOnjwZ1QOZhYUFlJWV4Wc/+xkuvfTSdXP2bDYbndG+d+9eVjPafV3pVPYelX02MDAAl8sVsiM8n5cRAgDEYsDlivcokBFlnv96n+8rr7wS7XAi3hcQvOmMXq/H7OwsBgYG6Ca1VNMZPhcOqZjBR91j+PC9RBrxEmvsgNVqTYrsPgEBgdQgEiOJ3W6HRqOB1+tlLaaEEub4KJ5TtavT6cSuXbsYzbKOlUjEc5FIhGeeeQZLS0s4fPgwtFoty6OLDZ1OB4VCgb6+PlRXV0f8/vXOcarRa11dHerq6lh7ECKTyfDCCy+AJEl87GMfw2uvvbbu68vLy6FWq5Gens7KeNZDKpWioqICFRUV8Hq99MrQkZER9PT0QKlU0vM1rvsVvfjii5ztKxI+9alPYWhoiPF6/7777sOLL74InU4X9Taqqqrw8Y9/HF/+8pfpWvi//uu/8OCDD656LfW3IpFIovpbY4K0tDSUlJSgpKRkzdWkvo1vqftEqsa28O0+GSnJMm9K2G8hXrEtsYq9gbmBTC4X80UsFsPFscBnsVhw5swZZGZmhtVIk6sxfu9732NcPA+EJEmQJImVlRW8+eabyMvLw1133QWxWIw33ngDR44cgU6ng16vB0EQcDqdsFgsMe3T4XDgpptuwiOPPIIXX3wx6EMYvV4PtVqNsrIyNDc3c36zibQjPB9cPaGwvv1OvIcAABCns/cQhCkiEZR9m87U1tbC4/HQ4icVB5Sbm+sXB8Sn8yUVnefU/ZCPRSzbES82my0pikABAQEBXxYXF9HV1YXi4mK0tray9nCUijmLd8RkIBaLBZ2dnSAIAiUlJbwSzoHoVu0WFBTggw8+AEmS+PGPf4xvf/vbLI0udgiCwLZt2zA4OBiWuYwgCMzMzGBgYAANDQ2rxHPK7DQ2NsZoo9dQ9Z5IJMKzzz6LxcXFoOMqLy9HX18fI2NhAt8s6sbGRtjtdhgMBjpmket+RUz0VWCDpaUlVFRU4IknnsAFF1zA6LZPnz6NK664Aq+//nrE7y0oKMDp06dXPYT55je/iVtvvRXnnnuu3/lGzc+Kiopw5ZVXxjz2WAm2mpQy3w0PD8Nut0OhUCA/Px8ul4s1/YyveL1eVs2PbONyueDxeITYllQjVvF8YWEBWq12zQxwJuHaeU490Y8kgiaSAtDpdOLhhx/G+Pg4brnlloiy0LhqmkMQBLxeL+x2O/r6+jAyMgKdToevf/3rmJmZgcfjgcfjYXy/Wq0WH//4x/Hmm2/6/ZzJLvJMEE5H+OzsbHi9XthsNk6b/0WCiaFldbHimphAVltbvIexLrGsIpBKpSgqKkJRURH94IUq5IeHhyGTyfwevMR7CV+qOs8TIec9koiX/Px85OTkhPwuk2X5oYCAgABw9no+NDSE8fHxdSMXmUIkEsU1YjIY1FyGimhxOp3xHtIqYom8FIlEuP3223H77bdjYGAA119/Pbq7u1mZm8SC3W7HoUOHQkZ37Nu3D6dPn171c5vNBrFYDI/HA61Wi5WVFezdu5dx4Sac2qewsBAmkwk6nQ7vv/8+ioqKcPDgwbi7SEONXS6Xo7y8HOXl5X79isbGxtDb2wuFQuFXMzFdB95222149dVXGd0mU1gsFlx11VU4evQorrjiCka3fezYMfzjH//A5ZdfHtH7rrvuujVXL6Snp+ONN97ATTfdhJdffhkejwcymQz19fX4xS9+wVizUCahomcKCgoAgH6YYzAYYDQasby8DJvNRj/wicfKDS5J9NgWyjCaDKYjQTyPgGjFc6pR4/j4ODZu3Mh4E8tgcFWQ+mYiRtqEMtwC8POf/zyeeuop+t+/+c1vAAC//e1vce2110Y+aBYhSRJSqRROpxNvvvkmjhw5grGxMdYfZLz33nv44IMPsGvXLr8u8jt27EBeXh6r+46WwI7wNpsN09PTMJvNOHnyJL1cKz8/HyqVihc3DdLjAZaW4j0MAIAoylUb6/3dXXbZZbEMaRVMNQLzffDi2/TIV/xku5APRaouI+TD32WkBEa8OBwOuiDv6uoCQRD0Q5m1Il4sFktSFIECAgKpwXr3RIfDga6uLjidTlZExrWQSqW8EM995zKUO3lkZAR2+/9n77zj26jv///StGzLliXvvUfiDMeJHdtAUkoKBMreo4WUXUZZZc/yg7BKA3xpWaW0UFYLLXuEGSgJASx5770tS16SrH2/P9K7SrYka9xJJ+mej0cg0bj7nHS6e3/en9f79V4K9dBWQEe/KIIgEBsbi/vuuw/l5eXIzs7Gww8/jPvvv9+rRPrJJ5+MO++8E2azGVdccQVUKlVA43FFd3c3JBIJHnjgAVx//fUAgPHxcXzxxReYmZnB3//+d7fJ9bi4OGi1WjQ2NkIsFntVDc00paWlKC0tDekY/MXRq7qkpISKmTQaDYaHh8Hn851U6XR81ocddlhQeqMFwk033YQTTjiB9oWQn/70p3jiiSdwzTXXePX6Xbt24YQTTvD4mri4OLz88suYm5tDc3Mz4uPjUVVVFTYxvONijkqlQnx8PAQCAcbGxtDR0YH4+HinxqPhclzeEu4NQ8nkOVsrSnyBS577gEAg8Hl13mQyoampKegBaTCU5+Sxmc1mvzwRvbkpvvDCC06Jc0d27dqFX//617jgggsgk8kQFxeHo48+Gps2bXJ6ncFg8GlcgcDn8xETE4PExES8++67GB4eDtqN//jjj8cPP/yAiYkJv7vI05Xs9BUyOZqZmYmpqSk0NDRgdnbWSZXOCssOgeDQHxaodCSHHebX++bm5lz2IpDL5XjppZcCHZYTTJ1P7pKfGo0GIyMj4PF4lBohWIqEaLVtCedgjkQikSArKwtZWVmUxYtGo8H09LST76LdbkdaWhqSk5Oh1+t9Wiz2hXvuuQf33nuv02Pl5eXo7OxkZH8cHBzRi0ajQVNTE5KTk1FdXR1URSxdvaQCwWQyQaVSwWKxOM1l2KaKJwk0oWiz2dDe3g61Wu0ksLn11ltx1VVX4c0338Rnn32Gqakp2O12bNy4EUcffTTy8/NRUlKy4vz44IMP0NLSgv7+flxzzTWwWCwBHd9ybrvtNjz88MN455138OCDD2J8fBxGo3HV++Hvf/97nH766SGxrAwX/K0OdYyZ7HY7FhYWqET6clV6YmKi37Hx4OAg8vLy/HpvMJiensbY2BgjnuEXXnghYmJicOWVV3rMPSUkJOCOO+7wuulnUlIStm3b5tNYCIKASqXCzMwM1q1bF7SKfk/jiY+PR1ZWFoqKimCxWChVekdHBywWy4oeR+E+P7PZbGG9IEBW60bCtThsk+fh4Hk+OzsLlUoFuVwecQHp3NwcVCoVkpKS/D621RL8VqsVv/71rz1uY2lpCU8//TT17927d2P9+vW466678LOf/QzAoRXcYBEfH4+MjAyqVDCYqpWFhQWsWbMGxx57LO6///6w9QMjG5g4qtKXlpag0Wgoyw6xWBwSVTqPx4P48MNh9sOPjlYEAkgCKKleWFjAU089RZ0nX331FXJycmgc4CGCtRizPJAnG4+SigSpVEoF8jKZjJGbd7TatkTaMTtavBQUFDj5Lj733HN44YUXsGbNGqrCwWq1MnJvr6ysdGo0FuoSbw4OjsiCIAj09/ejv78fFRUVyMnJCfrcKtQJanKeplAosHnzZqfrbLDtL70lkOT50tISpRJvaGiARCJxej4hIQEXXnghTj31VMoSYTUVMdl4cNeuXSguLsYpp5wCvV7v1/jcMTc3hwsvvBBJSUkoKytDa2vrqu955JFHcOedd9I6Do6V8Pl8JCUlISkpCcXFxVSzdo1Gg9HRUQCg4u/k5GSfVOlJSUmYm5tDbm4uFhcXmTqEgPDFMvI///kPnnzySezcuRMXXHDBqq8/55xzcMYZZ+DHH3/EpZdeioGBAafnL7jgAjz55JOYnp5m7Nrd09ODyy67DB0dHbDb7RCLxTj//PPxu9/9LmR2mcvnWyKRCOnp6UhPTwdBENDr9StsPslzkA02n/4Q7vMtMnke7osYQBgnzwHfOsfTgbflhQRBYGhoCN3d3SgvL6e884IJkwHpyMgIOjs7UVJSgoKCAr+PzVUAqNFo8MQTT+Cvf/0rJicnfd6m0WjE999/v2r5EhOkpqbi+OOPx7HHHos//elPIVGi2mw2fPLJJ+jr68NDDz2EhoaGsGrO4Orz4vF4iIuLQ1xcHGXZQSazenp6YDQaKVV6cnIy4yvMinvvwWSok+epqSDsdvACuJFeeeWVuPLKK2kc1EpCUcnA5/Mhk8kgk8mcFAkajQZtbW2w2WwrFAl0EI3K83C1bfEFx4W8xx57DFdeeSU++OAD/P3vf8fLL7+MV199FUcddRSOPvpoHH300SgqKqJlv0KhEBkZGbRsi4ODg8MRs9mM5uZmGAwGbN261WU1WjAIlfKcnKf19PSgrKzM5Twt1Il9d/g7Lq1WC5VKhbS0NKxdu9ZjIoZs3u7teMi5XFlZGWMxQX9/P0444QTw+XwYjcZVX19QUMDIOCIFpuJVx2btjmKW0dFRdHR0OPWXSUxMXDUhyOfzMTY2hrq6OrS3tzMyZn/JyMjwyop3cnISZWVl1L8/+OADXH311Xj00Udx6aWXenyvWq3GAw88sCJxDgD79u3D3//+dxQUFDBiS2QymXDeeedhaGgIYrEYAoEAJpMJL7zwAhQKBX7729/Svk9v8JRI5vF4kEqlkEqlyMvLc9vjiKxkD6QyIpiE+3wrkvpEhXXyPNh4E+SRiuP5+XnU1NRALpcHaXTOMKGYsNls6OjowPT0NKqrqwNuMOEYcBkMBrzzzju45JJLaC/5oxuJRAKBQEAppPl8PrZu3Yo///nPSE1Nxd69e8Hj8ajXBBuLxYLOzk5ceOGFOOaYY/CrX/3K5xItNrO8iYjBYKBU6f39/ZQqnfQspluxKYyJQfytt0K/ezet2/UFUVlpQInzYBLqoMSVIkGj0UCtVqOnpwcSiYQK5JOSkvw+X8JdFeAPkWLb4gvFxcW4+uqr8f777+P6669HVVUVPvnkE7z++uu45pprkJeXB6VSGfCiZU9PD7KysiCRSFBfX4/du3ezunyZg4OD3ZD3YlJtnZSUhPr6+pCq8ELheW61WtHa2orZ2Vls2bLF7TyNzcpzX+ZJBEFgeHiYEnTl5ubSGpc5zuUyMjKwY8cOvPXWW7Rt3xFyTpWamor+/n6Pr12t2SgH8ywXs5jNZkrM0tLSAoIgKCFLcnKyR4vFDz/8kBF7lEBwrHz3hGPi3JEbb7wRJ510EtLT01c8RxAEHn/8cdx1111utzswMIArrriC+veGDRtw/vnn44QTTqCl4fMnn3yCoaEhp7yH3W7H0tIS7rvvPjzwwAMoLy/HnXfeiQ0bNiA3NzfgfXqDL2IldzafWq0WIyMjAOBk87m8GocthPt8S6fTRYR9DsAlz33C8cLh6gReXFyEUqlEbGwsGhoaQtqchG7FxNLSEpRKJXg8nstSP3/g8/mYm5vD7t278eijj9Je5scUdrsdIpEIcXFxiImJgdFohFAoxMLCAlJTUymltEKhwPj4eMjGOTs7i9deew1vvvkmUlJSsGHDBhx77LH4+c9/HrQbnD/4uuCwXJU+NzcHjUaD3t5exlTpSaecDP0/3gB6+wLels/w+Ui85JLg79cPQuWh7w5HRUJ+fj6sViulSCCrGGQyGbX4IpVKvR4/Z9sSXej1eiQmJmLz5s3YvHkzbr31Vuh0Ohw8eDDgxPnWrVvx4osvory8HBMTE7j33ntxxBFHoLW1NawqiTg4ONgDQRAYGBhAb2+vW7V1sAm2ulun00GlUkEsFqOhocFjso7NynNvk/o2mw1tbW3QaDQeFwoCYXkV+P/93/8xljyfnp6GVCqlFpbdKdBDfV6HC8EWeInFYmRkZCAjIwMEQVCq9PHxcXR2dnq0WJTL5XjjjTdw5plnBnXM7vjss89QU1Oz6uvee+89j8+vW7cO+/btg0gkwtzcHNLT03Hw4EFcdtllMJvNPo2pubkZN910E2666SbU1tbipZdeQnp6ut9x+tDQECUGBA7FvY6/ObJ/wjnnnEM9VlhYiB9++IHRRdlA5h7LexwtLCxAq9ViYmICXV1diI2NpeaASUlJrFF7h7vy3GAwQCqVhnoYtBDWyfNg27aQJ62r1Z+xsTG0t7ejoKAAJSUlIb9x06mY0Gg0UKlUyMjIwJo1a2hLlhiNRrz44ot4++23adlesDCbzbBarbBYLEhOTkZ2djasViuef/553HvvvaioqIBCofC6eQfTWCwWTExMYGJiAp988gn+8pe/4MYbb8Ts7Czuv/9+LC0tobKyErt370ZVVVVIxxro72b5CrPBYKBUDv39/RCJRE5e6f6qjHk8HnJefRWjZ50NrKJ+oRWRCNJrr4WkvDx4+/QTgiBYlzxfjlAodKpiIL31tVotBgcHIRAInBQJnhZEo9W2JRqT5wRBwGAwrChBlEqltPTY2LlzJ/X3DRs2YOvWrcjPz8cbb7yBiy66KODtc3BwRB8jIyMYGhpCTU0NkpKSQj0cAMG1bZmcnERLSwvy8vJQWlq66r2Lzcpzbz4zR9FTfX09Y4rK5cl8hUKB9evXo6Wlhdb9yOVySCQSKsFVVFSEwcFBGAwGp9etX78e33//Pa375qAfHo9H2QMVFhY6WSy2trbCbrc7qdIlEgmOOeYY/OIXv8BLL70UsnEffvjheP/9972O9//0pz95fN5kMmHr1q10DM2JgwcPovy/c8W6ujq8/fbbPvdCKy4uBkEQsFqtXtslDQwMUHPwjz/+GPX19b4PfhXomnvweDyqMoI8B0lb2K6uLpjNZidBVSg9uyNBec7ZtkQhjslzckWNtDKZmppCVVUVUlNTQzlECjoUE6RKpa+vD2vWrKG9oWBHRwc++eQTWrcZLHg8HqxWK+Li4lBfXw+hUIiBgQF0dXVh/fr1+OlPf4ovvvgi6As8q0EQBJqbm/HLX/7S6fEDBw7gyCOPxJVXXondIbQjoRtSlZ6Tk+OkSu/r68PS0hJ1U0xOTvbrppjz+msY/e1NwJdfMnMAJHl5SDjrTEh37IBAoWB2XzQTTgnl2NhY5OTkICcnB3a7HfPz89BqtRgeHkZ7e/sKnzzHQCYalefh3v09EHQ6XdBU4GSTtN7e3qDsj4ODI/LIzc1FSkpKSKtilxMM2xa73Y7u7m6Mjo5iw4YNLi0SXBHOynNS9JSenr6qv3mgkPMcR7HEZ599hrS0NFr3w+fzsWXLFsTGxmJ4eBhyuRylpaXYtm0bYmJikJ2dDb1eD6VSSet+OYLDcotFnU4HjUaDyclJdHd3UxXd9913X0iS59nZ2XjppZewZcsWn9532GGH4euvv6Z9PHweH1JxHCx2K5YsRpSlFGJL9jrECmLQMt2FpokumGyHlOsHDhxAeno6Ojo6fLJzOeqoo1BUVLSqRZI7jjnmGNTW1uK9996jdfGOqfmWSCRCWloa0tLSKJEMafHS398PoVBILeYoFIqgWp6Fu/Jcr9dzyvNohMfjgc/nw2q1AjikalWpVJSVia8rekwSqGLC0bu9trYWMpmMxtEdYmpqCktLS7RvNxgQBAGxWAyRSASpVAqCIGCxWDA+Pg61Wo3JyUnMzc2xKnHuDU899RQuvvhiFBcXh2wMTH1my1XppMpYo9FgYGDAb1V6ziMPw9DSCu2vfkX/oGNiIH/q/xC/cSP922YY8nsMp+S5I3w+H3K5HHK5HMXFxTCZTFQQRXo1ko1Hk5OTo1KFHY3HTBLM5jc6nQ59fX34xS9+EZT9cXBwRB58Pp9ViXOAeeW5yWSCSqWCxWJBfX29T9dsNivP3Y3LsRFqRUVFUCwayRjAMXmemJiIoaEhWj2qNRoNHnvsMfz+97/H8ccfD51Oh+rqaqeEDNsES2yGzbE5j8dDQkICEhISUFBQQCmCNRoN2tvb8eCDD+KWW27xaltyuRyzs7M+7T8xMRGHH344jjvuOBx//PEB9Xi77bbb8OCDD/r9fpK8hEzc+dMrUZW1Bna7HbOGBeTKMxEjEMFG2CHgCyDkH0qu2gk7BjQjuOhft+OwvM341ZbTIBGK8f51f8WuP10PUbJ3iWyxWIxXX30VV155JX744Qe/xn3w4EGkpaXh3nvvxbXXXkvLeReMSl8ej4f4+HjEx8cjNzcXdrudsvkcGhpy2XiUqfmQJ8vocIFrGBrFkIHe9PQ0WlpakJmZiYqKCtad0OQ4/bFN0Ol0UCqVkEgkjHq3h2viHDh04TabzVTQplarYTKZ8NJLL0Gn06GlpSVsPNyX88gjj3jdBIVughnMOaqMHbtx+6NKj1u/Dpa778biffcBdE22amuR/eQTYdMYdDnhnjxfTkxMDDIzM5GZmUl5NWq1WkoVIxQKIRKJoNFoWOWTxyThHsz5C6lIYUpFceONN+KEE05Afn4+xsfHcffdd0MgEDj5SnJwcHCEO46CJLohG6MqFAps3rzZZ5u+cFOeB8Pf3BVkjLc8HvBW4e8rN9xwA2655RbcdtttK+anfD6fS55HIMsVwVVVVfjggw+wb98+t+9JSkrCP//5TyQnJyM3NxelpaUek+hJSUl45JFHcOyxx9IuGLz99ttx//33+/3+rVnr8dJZj0Is+N/5np6QQv19+ZWNz+OjOCUfn130Vwj4/5uLnC7LwOIznZCeXwxxnneVkwUFBXjvvffQ2dmJ7du3e2Xd4oq7774bL774Ir766quAbcNCMffg8/mUjRCAFYIqR5shhUJBq6CWvN6H87yS8zxnCaFIyvD5fAwODmJ6ehqVlZXIysoK+hi8wZUSwBsmJyfR2tpKeQIy+RmztaOxt9hsNszPz6OtrQ2zs7NYXFyEXq+HTCbD3NxcqIfnN2NjY6EeQtBxVKWXlpY6eV+TqnTHUi1XkzDZz49HXH0dFv78AoytrSAMBvB4PPBSUiCurYW1rRXWpmZgbg4eQ/u0NCTecAMSf3okY8cbDCItee6Io1djQUEBrFYrOjs7odPpKJ+8pKQk6pyJlA7jy4lW2xaTyQSr1cqYbcvo6CjOOeccaDQapKam4vDDD8eBAwdYYwvHwcERfrDxHiQUCmEymWjdpqP6OpDGqKTynG29W1wlz0l/cz6fz6i/ubvxAK6rRisqKtDZ2Un7Ph988EHcfvvtKx7n8XisrBZgK+G40MDj8SCVSvHee+/h9ddfx+WXX75ikesnP/kJ9uzZA8N/52FisRhDQ0N47733cOWVV65Iop944onYvXs3Y5UaN998My644AJs2rTJZ2EdDzw8ddK9Tolzj693qL5wTJxTWG1Yeqsfoms2gMf37rrG4/GwZs0avPjiizj77LO9HvtyBgYGkJeXh9raWuzdu9fv6yobbDLdCaqmpqbQ3d0NiUTi1HjU3x5rAKjzO9THHAjBtLpkmrBOngcbk8lENbSoq6tj9UngqbmpKwiCQHd3N4aHh7F+/XpkZGQwPUTGVAnBpK+vD7OzsxCLxZiZmYFIJIJQKFzRwCacOP7440O6fzYEc8u9r0mv9P7+frS1tUEmk1GJUalUSgUAouRkJN/0W4/b1kxMoLu9HeuNRhhUKghkMiQcfTREDC9WBZtITp4vRygUIjY2FkKhEOXl5S4b1ZLni1wuD6pPHpNEq/KcnPwwpaJ47bXXGNkuBwcHB5ug27bFarWitbUVs7OzAauvyXkU27xmlyfPSX/zjIwMrFmzJiSKTAAuk9Z//OMfaWmi7YqEhAT09/c7idg425bo4qyzzsLpp5+OhYUF6HQ6WK1WSKVSSgA1OzsLoVAIq9UKhUKBnTt3oq2tDd9//z2USiUSEhKwYcMGlJeXM95EOSMjAxMTE/jggw9wxRVXeG0lUyTPRUr86tcxx7kW+Xe3vwU9AfucGQJFjFdjIDnuuONw6aWX4tlnn/Xpfcs5ePAgZDIZrrvuOtx7770+vZeNFiauBFVk49Genh4YjUanxqOOeQNvIK+tbDpmX9Hr9UHJLQYDLnnuJWT5H5/PR1lZGasT58D/fmCOzU3dYTab0dTUBKPRiPr6+qCVVWRmZiI+Pj5s7U2AQ4G6VquFUCiE0Wj0u5yJTVxyySUh2zcbE62OpVqkKp1MjA4NDTmp1t2p0h3hxcQAcXGQHnUUpCFeqGCSaEqeA/9LJC/3yXO0BBoYGEBbWxsSExOpZHpCQkLYfkZ2uz1iFgJ8Qa/Xg8fjIS4uLtRD4eDg4Ahb6LRG0el0UKlUEIvFaGhoQEyMb4khV2MD2Js8JwgCg4OD6O3txZo1a5CTkxOS8XhK1DU0NCA9PR1TU1OM7LuoqAgajQYSiQTvPfYARlpUAICeV57DlhNOx9bTzmJkv5FAuMadyxEIBFR/Ikfy8vLQ1tZGNbPt7u6G2WyGTCZDcXExamtrQ1IVetxxx+GDDz7Atm3bYLFYVn391XXnA/Dv+3L3HhsAnWoasp/6rrRfu3atz+9xxx/+8Ae8+OKLeOKJJ3DiiSd6dYzkdYbNiWShUIjU1FSqWtSx8ejg4CAEAoGTxctq9sikEDacf7MGg4HzPGcDwTiJyPK/7u5ulJeXY2JigvF90gH5I1utfG1+fh5KpRIymQz19fUBlZX4SmlpKX7+85/j9ddfD9o+mcBqtTLm2RhslEplyCcJbFeNxMbGIjs7G9nZ2U6qdMfEKJlMd7e6HM43QG9h+/dIN+7KCJc3qjUajdTiy8jICHg8HuRyObX4EuiEP5jYbLawt9/yB7LxTTT8jjk4OCIDNl6vhEIhLclz0nKS9DamI7HiWMHLpkVicsGhubkZWq0WNTU1jKtmPcHj8TzON7u7u2n3kAaAqpx0nFGzEX++7PwV3zdht+P7t9/A9++9iTPufhAT3Z2w2+0o2LgJYkks4mQy8F1ZWnBEFHw+HxKJBIWFhSAIglKkk1WhYrGYir3lcnnQciCVlZXo7e3FUUcdhd7eXrev+9PP78XOim20759nt8O2fxpzChtkG/N9ujccffTRkEql0Ol0tIxldnYWF154IS6//HLs3r171deT1xk23s/cERcXh7i4OKqafX5+HlqtFiMjI2hvb4dUKqXOQ5lMtuJ6xrYFXH/Q6/Wc53k0YLVa0dLSgvn5edTU1EAul2NmZoaVDWRcsVo55OjoKDo6OlBcXIzCwsKgX4jEYjFOPfXUsE+eRwpKpRKFhYUhHUM43QyBlQ1EjEYjFZgtV6WTdh3RklSORuW5N8GNRCJBVlYWsrKyYLfbsbi4CI1Gg7GxMXR0dEAqlVLnVFJSEqvVFWwrnQwWOp2OS55zcHBwBEigti12ux3d3d0YHR3FunXraC0LXy0pHCrMZjNMJhOMRiMtCns68PQ5xcTEYP/+/aivr6dlXzFCIc6t2YC1OV581zYb/nHX/6wUv33lL9TfK7b9FD/ddTn4YZ6U4nCP43yLrBaMi4tzqgrVaDTo7e11stZITk5mPMaTy+VobGxEZmbmigp8IV+AV07/A2rz1lNjpxuenQf7OxosLAohO8L7qpWcnBzceeeduPnmm2kbi81mw1NPPQWRSIR7773X4/GGu4UJn8+nKiWKi4thNpspVXpbWxtsNhvkcjk1D4yLi4uIuRaXPI8CFhcXoVQqERsbi4aGBqqkgm5/PiZx15Hdbrejo6MDk5OTqK6uphSRwYbP5yMmJgZ/+ctfsGvXrpCMgeN/PP7443jsscfC/gIdSiQSiZMqfX5+foUqPTY2lpVNqOiGPL5IPkZH/Alu+Hw+ZDIZZDIZioqKqJ4aGo0G7e3tsNlsSEpKohQJbLMJiYSAzh9I5TkHBwdHOME2T+hAbFtMJhOamppgNptRV1fHyMScbXO+mZkZtLW1gcfjoaamhjX3Xz6f7/G82rRpE84880y88cYbAe1nbWYazqurgpgGhXDnvs+hGR3FmXc/EDVx6nLYdC1gCnff7fKqUMdeRQMDA069iryx5PSXjz/+GIcffrjTY7s2nkolzpnGum8K5nUKiOXezy+uuOIKZGZm4pe//CWtY3n88cdRVVWFU0891e1rwsG2xRfEYjEyMjKQkZEBgiCg0+mg1WqhVqvR09ODmJgYxMfHgyAIWK3WoDpE0EkkzZvC8xv4L0zd7MbGxtDe3o6CggKUlJQ47YdtgZQnXI3VaDRCqVSCIAg0NDQgNjY2RKP734Vv27ZtWLNmDTo6OkI2Fg7gxRdfxE9+8hOPNy2mcfRODPdg1nF1uaSkhFKlT05Owmg04j//+Y9TYMamsmA6iIag3BE6zlmRSIT09HSkp6eDIAjo9XpoNBoqiJJIJJQaIZglpu6I9uR5uF+jODg4OEKJv7YtZB8qhUKB6upqxu6F7kRIwcbR37ywsBADAwOsuvd68zn96U9/wr///W+YzWa/9rElLwtn1m6k9b6r7u/G16/8FUecewF3P49AfJmHOFpr2Gw2SvzU39+PtrY2yGQyas7ma8NHT5ANS7u6ugAAEmEMrqg/D0BwKnd5NmDpywmITyn26X0nn3wyjjnmGHz88ce0jYUgCOzZs8djHsJut0esMIvH4yEhIQEJCQnIz8+HzWbD7OwsxsbGYLFY8PXXX1PWsAqFImx6ZhEEAYPBwCnPIxGbzYaOjg5MTU2hqqqKMvp3JJyS58sVHRqNBk1NTUhLS8OaNWtY4Z9EKi8vu+wyXH/99awIUqOZCy+8ECeeeGLIk3KRCKlKl0gk6OnpQXl5OTQaDQYHB9He3h4xTSRJImEBxBfoTiTzeDxIpVJIpVKnIEqr1a4oMfWnezsd2Gw2VtxHgk0kKSg4ODg4QoWvcyqCIDA8PIzu7m6UlpYiP983v16mx8cEVqsVra2tmJ2dRW1tLUQiEfr6+kI6puV4U9EQHx+Pt956CyeeeKJPcz2JSIgjSwvxkzUljHzXzR+/i4GmH/HLh56Iqpg1mo7VVxwbOpaWlmJpaYlSpZOWnHSKn7777jusXbsW4+PjqMlcB0WcLKjfj75/Ef50Jbjqqquwd+9eWnM37e3tHp8nk+fRgEAgQEpKCmw2GywWCyorKymLl+HhYfB4PKfGo2yw8HKHTqdDQkJCqIdBC1yG7L8YDAaoVCrweDyPimw2BFLeIhAIVnRkr6ioQG6u792VmYIc43nnnYfR0VE8+uijoR5S1PPwww/jtttuC+kYIjnxSh7bclU6GZgNDw+Dz+dT5YThqkqP5O/QFe4ahtIFGUSlpKQAANX4yN/u7XQQrcpz0vOcg4ODI5wIZ9sWq9WKtrY2aLVabNmyBXK5nOHRBWYrQwcGgwFKpRJCoZDyNzcajSAIglUxlrcK/R07duDgwYO48sor8d133636+rqiPJy4cQ1EQveL9HR8BouT4/j2rddw2GnnBLwtDvZA128kNjbWpSUnXeInPp+P22+/HXfffTeuOzw4NraO9wGR3gK7wQJ+nG9zze3bt+PII4/EZ599Rtu4VqtMicZ5B9lTa/l5uLCwAK1WS/XMio+Pd2o8yiZxE+d5zhLoChqmp6fR0tKCzMxMVFRUePxRCgQCmEwmWvbLNHw+H2azGU1NTZibmwt5R3ZXkAFXUlISbrjhBlRXV+Oaa67BzMxMqIcWtbzyyishS56zZSIQbJY3kSQ7cQ8NDaG9vR0JCQlUMj1cVOlsmtgFg2CrIWJjY5GTk7Oie/vw8LDTOaNQKJCYmMhIsBmNQSwQWUEgBwcHR6gQCoVe9YDR6/VQKpUQiURBbZJJCnxCwczMDJqamlbMTcn/e9ukPBj40lh13bp1+PLLL/HJJ5/gpJNOcvu6I4rzccKmtZ7jKhpjLuXb/0R6YTFKqmtp2yZH6KE7Lndlyblc/OSoSvdWyJKfn4/09HSUpuTTOl53OC6kCsCHft84Eo71fd8333wzrcnz1WBaqMRGbDbbimPm8/lISkpCUlKSU88srVaLjo4OWCyWFY1HQzUnJ21II0V0FNbJ80AhCAI9PT0YGhpCZWUlsrKyVn1POCnPAaC3txfx8fGor69nZTmHY8All8tx6qmn4tRTT8Wbb76J8847L8Sji06sVmuohxDxeLqBLe/EbTKZoNFooNFoMDIyQpVpkcl0NqvSoy15HqqAzlX3dlKV3tLSAoIgnIIounpdRKtti8FgiJggkIODgyNUkPcPm83m1i5wamoKLS0tyM3NRWlpaVDvs6FQnhMEgYGBAfT19WHt2rXIzs5eMSaAXcnz1RqGuqK8vBzvvvsuEhMTsX37dqfnxAL+6olzAHRHmB/teRhX/e2fXr8+3GNcNlWhhCvLxU8LCwtUIn25Kj0xMdHtObN161bI5XJY7KGZgy+1zfqVPK+rq6N1HOnp6R6fj0bRjjfXelc9s8hFnb6+PqcGuHK5PKi5A6PRCLvdztm2hDtkl3aTyYS6ujqvv9BwSZ5PT09jfn4ecrkcW7ZsYe2Fxp2q47TTTsPmzZuxfft2TE1NhWBk0cuOHTtCPQQuoHMgJiZm1cCMjar0aFOes+l4xWIxMjMzkZmZCYIgsLi4CK1Wi8nJSXR3dyM2NpZSxSQlJfk9AY/GIBY4ZNvCKc85ODjCDbbco0g8Jc/tdjt6enowMjKCdevWISMjIyTjC6bynPQ3n5ubQ21tLWSylU7EjslztuBLY1W73Y62tjbMzMxQ9jsLCwvYvn07lEolAOD82qoQnasEzEYjxBKJ9+9gUezH4Uyw55KOamBS/EQmMEdHRwHASfzkqEqPiYnBqaeein17v8fJlT8L+nk1t6hBmp/vvfTSS/Hss8/SMo49e/Z4fD4a5x2ulOeecOyZlZeXB5vNhrm5OWi1WgwMDKCtrW1FdTKT55perweAiJk3RWXynOzSLpfLfe7S7m9n+GBBEAR6e3sxODgImUyG1NRUVl9kPAVcBQUF6Onpwcsvv4wbb7wRBoMhyKOLTs4666yQ7TsaAtBAgjlXgRmpMF6uSg+W77U7mAj8rHYr9g7vxZOtT2LePI9YfixuqLoBOwt20roff2BrQMfj8ZCYmIjExEQUFBTAarVidnYWGo0GXV1dMJvNSEpKos4bX0r72HrMTKPX610mNTg4ODg4vIfH44HH462YV5ECJ7PZjLq6upBNuoOpPDcYDGhsbIRYLEZDQ4Pb+I28P7Mpee6tl77JZIJSqYTdbkd9fT0k/01Si8Vi7N+/H2azGenp6SjP8qw+ZZLx7nYUbKj26rXhnDgP13H7SiiPMyYmhhKy2O12LC4uUon0jo4OJCQkOKnSjz76aJy4eydOqtwBHnhBPb/2zTWhDEf59d5HH30UKpUKBw8eDGgMIpEIxx9/vMfXRFPDUJJAq4wEAgG1YAOAshoicwfAIfcHMncg8WHx0Bt0Oh14PB5tVc+hJqyT577+eAiCwNDQELq7u1FeXo68vDyft8Fm5bnZbEZzczMMBgPq6uowODjI2rGSrKZW0Gq1yM3NxXfffYe9e/fitttug9FoDOIIo4vExEQUFxfTtj2z2QytVoukpCTaL8Yc7lXpIyMjPpULMgEdQd+EfgJv9r+JH6Z/AA88jMyPwID/LaIZ7Abc13gffq/8PfaevDekAVW4+PAJhUKkpqYiNTUVBEHAYDBQQVR/f79PpX1sKhsPJgaDYUUpPQcHBweHb/B4vBXzqkAETnQTLOW5Wq1Gc3MzsrKyUF5e7jGW4PF4Pim9g4E345mfn4dSqYRcLse6detcxg5isRhN336Nd3bfHbIK1C9eeBq79tCjouUILWyqYubz+ZDJZJDJZCgqKqLmxxqNhrJXVCgUSC7IwHdDTajLD171hdFigjo1sH5+n376Kex2O5555hlMTEwAAEZHR9He3o7h4WHYbDaYzWa3eamCggI0Nzevup9oFO34qjxfDUerIYIgqMajExMT6Orqoq06mcRgMEAqlUbMokdYJ88B71e7rVYrWlpaMD8/j5qaGr+7tLM1eb6wsAClUomEhATU19dDJBKFvEu8N7gLuBwV9Bs2bDjURKO0FFVVVfh//+//4fPPPw/BaCOfu+++G5mZmQFtw2q14qWXXsJvfvObFc/97W9/w8knn7zqNtgU8DABEzeQ1coFSVU6mRhlWpXua/K8R9uDy7+6HEvEks/7MhAGXPf1ddizbY/P76WLcFRD8Hg8xMfHIz4+Hrm5ubDZbJifn4dGo6FK+xwXYBxtgcgmb9EWxAKHlOdxcXGhHgYHBweHT7DxHkXOqwiCwPDwMLq7u1FaWor8/PyQj5fpeRRBEOjv70d/f7/XvbfIcbEpeb5aw9CJiQm0traiuLgYhYWFHr/XfX99ntpmKOYC+rnZoO8zVET6XAtg5zUPOLRQlJGRgYyMDMpeUaPR4Nxzz8VVt/0O31z6KmLFwRGdTem0mFoI3CKXz+fjiiuu8Pia6elpvPjii/jiiy9gsVhwzDHH4JprrvG6L180Js/tdjtjc3Yej0ct6hQWFsJisWB2dhZarZaqTpbJZFQyPT4+3ufflE6n8+t9bCXsk+fesLi4CKVSidjYWI+lcN7AxuT52NgY2tvbUVRUhKKiIurkDGWXeG9xFQBaLBY0NzdDr9ev8KNvaGjANddcgy+//JL1xxZu/OEPf8BZZ50V0MWNIAhs2rQJQ0NDLp//5S9/icLCQrz11lsuFe6RcmFlA96UC5JlXEyo0r1Nns8Z53DN19egd7E3oP0dnDmIhrcacGXllTi37Nygn0uRENAJBAJqgQVwXdrnWMkAIOyP2R/0en3EePdxcHBwhBKBQEBVzmq1WsoHmw0wOY9yFHW58zd3B9uS5+4ahhIEge7uboyMjKCqqgqpqamrbsswr6X+7imBzliMx6LPlSMwwmVxwNFecdeuXbjuuutw0ktX4MNdz0PAZ766c3RhAm9+9E889ofHGI/p09LScNNNN+Gmm27y6/3hbJXkL3Qrzz0hEomQlpaGtLQ0l9XJQqHQyR7Wm8ajer0e8fHxQRh9cIj45DmZWC4oKEBJSUnAPzg2Jc/tdjs6OzsxMTHhMijh8/kwm80hGp13LA8AdTodtdBBKuiXs7CwwKqgMdzZs2cPzj77bCQkJMBisQS0rVNPPdVt4pxkYGAAmzZtwhFHHIH33nsv6m6CoQjmXJULajQar5rY+Is3Ac6ieREXfHYB1CZ1wPsjeartKTzV9hS+PPFLiIXB83yPRBW2Y2mf4wLM2NgYOjo6AACDg4NITk5GUlJSxB2/O7jkOQcHBwc98Hg8tLe3UwInbxWIwYAp5bler4dSqVzV39zTuNg0D3I1HqvViqamJkoI5e090/zf5nIkZBxJ/Pc/wZgy9Hz3LUq3NjC/Iw7GCbc5ZldX16H/awfwlx/fwkVbTmf0GOyEHe91fo75xQW8/fbbOOWUUxjbFx1EglDJV0Jlkbm8Otlut1ONR4eGhlw2HnX13ZDVuuH2W3RH2CfP3a1K22w2dHR0YGpqyuvVbm9gS/LcaDRCpVJRTVdclZCHm/J8enoazc3NyM3NRVlZmcsfmclkwnXXXRfsYUYcb7zxBjZs2ICCggLqMavV6vfq5tTUFF577TV89tlnXr/n66+/RnZ2NsbGxqjvmgqSw0QtEK6IxWJKlU76ndGtSvcmef7vgX/Tmjh35Gfv/AxfnfoVI9t2RTjatvjC8gWYhYUF/PDDD7BYLGhvb4fNZkNSUhIVREWyrYnBYIgoFQUHB0d0wLZ71NTUFPR6PVJTU7Fp0ybWJUUEAkHAopLlqNVqNDU1IScnB2VlZX4dM9uS58vn4nq9Ho2NjR6FUD7vg/oP83z+5z+umjwnrWrCte8L264FHIf48ssvqb8/9u0LqM3ZgPUZrnMigUKAwH+GfsTevm8BAN9//z2XPGchwVSee4LP5ztVJ5P2sFqtFi0tLbDb7dTzcrmcmgcGQ3D01FNP4ZFHHsHk5CQ2btyIJ598ErW1tYzsK+yT564wGAxQqVTg8XhoaGigtbsrmZAOZdmIVquFSqVCSkoKKisr3d642ZLo9wSfz4fVakVvby8GBgawbt06t57bBEFg+/bt0Gg0QR5l5HHmmWcC+F/51NatW7F27VoQBAGz2Qw+n0/98YRer8eHH36It956C++9957P49DpdJDJZJibm2PFjSFYsClodfQ7W97Eprm5+X9NbP6bFPVWFbbaNbJ7rht/avsTXYexAgssaHirAWcWnolrN13L2H5IIlF57gmBQAA+n09dN/R6PbRaLdRqNXp6ehATE0OdM3K5PKRN3+iEPFZOec7BwcHhH3a7HT09PRgeHoZUKkV6ejor7590Ks/99Tdnelx04JjMn5mZQVNTE7Kzs/1eHAg1FuMSCLsdPDdjJwiC+mOxWKgmruT/OdhBOAqxHnjgAervevMSfvHPG3HfUdfihDU/pW3uSBAEZgyzeO7gG3ij7UPMLs0DAO0LhUwQbXMtgL0LBo72sKRvv1arxdTUFD744AM89thjaGhoQGpqKqOCqtdffx3XX389nn76aWzduhV79uzBMcccg66uLqSlpdG+v8iYzTowPT2NlpYWZGZmoqKigvaTjUxU22y2oCcDCILA0NAQenp6UF5ejtzcXI8XUrYpE9wxMTEBu92+wt98Obt374ZKpQrewKKA6elp3HjjjQAOXQTb2tqgUChAEASsVisAeAwK33nnHVx//fXQLyuz9JUzzzwT//znP6l/h2PAEyksb2JDqtJJqw6pVOqkSnd3jfWUPJ/QT+Dizy9m8jAo3hh4A3KJHBesuYDR/US68nw5joorHo8HqVQKqVSKvLw82Gw2quFMb28vjEYjZDIZtQgT7l3XdTqdx3sVBwcHB4drTCYTmpqaYDKZUF9fj+7ublYlgh2hq4KX9DdfWFjA1q1bqZ4h/sK2+R2pwh4cHERPTw/Wrl2L7Oxsn7cTDrE/QRBUg1uBQACCIGC3253OYW8FSKEmHD7vQAm3WHN+ft7p33PGRVz9/n145uDf8d4Ff6Ye97ciGADu/vRJvNn+EXRmg9Pz5eXlfow4uLA1kcwkNpuN9RUujr79BQUFKC4uRkJCAvbu3Yu33noL09PTOPLII3HMMcfgmGOOwcaNG2n7Hh977DFccskl2LVrFwDg6aefxvvvv48XXngBt9xyCy37cCTsk+eONg89PT0YGhoKeEXfE+TJa7Vag5o8t1qtaGtr86mZjqPynCAIvDahxr2DGpgBbIoT4faCdNzVN4kW06EkaXWcCM+uzUeqOPDyOm/Q6/VQq9UQCoVuPf/6+/tx4MABHDx4EE8//XRQxhXOODb6i42NhdlshsFg8GpiYjKZUFJSgpmZGcTExFDB4fKg0G6341e/+pVfSnN3fPLJJ7BarVFxQwynYNWTKr2lpYVSpZNJUUdVuqfjvPf7e2GFNRiHAAB4tuNZnF9xPgQ85oKPaAvoPJURCgQCpKSkICUlBQCwtLREnTdDQ0NOjUkVCgVjXeSZwmAwcMpzDg4ODh+ZnZ2FSqWCXC5HdXU1hEIhq6tk6VB4k72cJBIJ6uvrabnfsTF5PjU1BbPZjJqaGiQlJfm1nf4fD9I7sABwpTon50RkvEfa0ZAV6TabjXqe/H5I8RGnSg8+4TTfWo1WdT8e/uo5/Hb7JT67Fzl+Dr//+gW82vIuzLaVKvPjjjsuwFEyT7QJlYDQeZ4Hgkwmw9lnn42zzz4bu3fvRltbG4499lh8/PHHeOCBBxAbG4ujjz4ad9xxR0CLNmazGT/++CNuvfVW6jE+n48dO3Zg//79dBzKCsI+eQ44qxhWUy8HCnkTDGagZzAY0NjYCJFI5FMznUOWKDb8Z06Hc9tHnJ77wWDBKe2jTo81GizY8kMvACCRB/w6Jxm/zFQgnoFFAtLzLy4uDklJSS6Dyba2NvzlL3/B119/jaamJtrHEG64m2Ace+yx+Ne//oW2tjY8+OCDmJqawtDQEPh8PhYWFnzez8MPP4y7776bCvLIoPA3v/kN/vKXvwR8HO7gElLsZ7kqnWwgOT4+js7OTidVursAp1XTimZtc1DHTYDA9NI0MuNcW0IFvP3/BqbRNDHyZbEgNjYW2dnZyM7Oht1ux/z8PLRaLYaHh9He3o6EhARqAcZTNQMbIG1bOM9zDg6OcCNUSQeCIDA8PIzu7m6UlpYiPz+fGgubk+eBKs8dezmVlpbSdm9jU/LcZDJBrT7Uu6ahoQESicTvbbV8sZeuYQWMzWqFwGH+65gcJ3MBJOT3Sia4SNEROX8ivys22Luo1Wq8/vrrmJ6eRlVVFaqrq0MyjmARSYnW5xv/gR7tIC7efAY256yHSLB6foacnyxZjbj+nQfwYf/XLl+3bt06xoSndBJtQiWAPZ7n/qLT6ZCZmYkrrrgCV1xxBSwWC/bv349PPvkkoPsFcMgmzGazIT093enx9PR0dHZ2BrRtd4R98lyr1aKxsdFJxcA0QqEwaIEeGXhlZ2ejvLzcpx/PFzojbiUSgWWJc29YIIAHRzR4cESDzbFivLWp2OdtuIIgCAwMDKCvrw+VlZVYXFyk7EEcsdls+PDDD9Ha2solzgHExcXhtddew/bt2/HFF1/g6KOPXnEulJeXo6SkBJOTk4iNjUVsbCwEAsGKErDVePjhh5Geno7LL78cwKGgsLS0FOPj47QdjyscF1AiSS2wnFD2S6ATxxKtwsJCWCwWaDQaqnEIWWY2Pj7upEq/6+BdIRlvnIA5vzXHiVG04K8Sgs/nQy6XQy6Xo7i4eEU1g2PDGYVCQWvPEjpYWlqC3W7nbFs4ODg4vGC1ylk2J8/9VZ4TBIG+vr5VezkFMi42JM/n5+cpcVdycnLAiZDYRPbcV3WzGshSDyVkHNXkyxPnrnC0bFmuSndl70L+nUnsdjsuu+wy/OMf/3A6d2677Tbs3buXirfCOUm3nHCcS4rFYpjNZpfPmW0W7O37Fv8ZVkIiFKMhZxPu/dlvkByXtKJpL0nrZA9u3fsoWqd6QMD15yEWi3H33Xejq6uL9X2KojF5Ho7Kc0f0er3TfV8kEmHbtm3Ytm1bCEflP+z8ZfjA/Pw8ioqKkJeXF7TERTACPcfAyx8bmi81c7hVbQQdrcl/XDLj1MYevFVdGtB2rFYrWltbMTc3h9raWshkMvT09LgMAGdmZjAyMuLUdTqaSUxMdEq6urpBikQi7Nq1C1arFfv27cPExASsVivEYjGWlpZ82t8NN9yAffv24ZVXXkF/fz/jiXPg0M07mpKPkYZIJHJSpff392Nqagrj4+Po6upCfHw85HI5Jpcmgz82ngiyGBlj249G5TldSghX1QxarRaTk5Po7u5GbGwspUpPSkoKeQBJ9nfgqmQ4ODg4PKPX66FUKiESiVBfX+8yuSoQCFjbqM4f5bnVakVzczMWFxdp8Td3BRuS5+Pj42hra0NJSQlMJhMt42k4/Tz0/GcfDaMLnFhpItUUlJzze5M4X85qqnRv+kv5CrmoYTabUVFRAYvFgp07d2JqamrFa8fHx1FZWel2W9u3b8c777zDzc+CxOOPP44rrrjC42sMliUYLEt4r+dLfNT3NbITM7AxoxxX1p6LIsWhfNicSYc///APvKT69wpvc0cyMjLQ0tICnU4HjUbj1KeIrCSOj49nzfdP9hqIJsJ9wcBgMCAnJ4eRbaekpEAgEKy4tk1NTSEjI4ORfYZ98ryoqMilcplJmE6eWywWNDc3Q6/X+2xD89qEFvcMTMG3VOnq/Gi0Iv/bDrRsKUGiH57opPWMWCx28jd3FwAKhUKYTKaAxx0piEQilJSUeEyeA0B+fj7uvPNOtLe3Y2BgAEajETMzM7j33nt9bur59ttvAwBOO+20wAbvBQKBAB9//DGOOeYYxvfFwTw8Hg8SiQRxcXGoqqqCxWKBVqvFhHoiJOO5ev3VjG7f0dsyWmAimFvecMZqtWJ2dhYajQZdXV0wm81UQK9QKEIS0Ov1eggEgoAVdhwcHBzBJpjXy6mpKbS0tCAnJwdlZWUee2QYjcagjcsXfFWeM+Fv7m5coUqeEwSB7u5ujIyMoKqqCqmpqeju7qZlLp6QnIKiLfXo/4EZr1pvEcbGQSSRUL2fAFC+5YGyXJXu+IeOpqNffPEF7rnnHiiVyoDHCgBfffUV0tLScM8990AqleL4449HSkpKWFTRhsMYl3Puuefiz3/+M3744QevXm+12zA0N4ahuTG80/k5EsTxkAhjsGjWw2j1nEf59a9/jXvuuQcxMTGIiYlBcnIygEM5G7IidGBgACKRiBKxKBSKkKrSo9HzPNxtW5i0uhSLxdi8eTM+++wznHzyyQAOnSOfffYZrrrqKkb2GfbJ81DAZPJ8cXERSqUS8fHxqK+vp5qReMMpqj40GlyX+tDF+h96MVhf4dOFa2ZmBk1NTcjKylphPeMuAKSj/M8dUqkU1dXV1Pbtdjva29sxNTXF2tLR+Ph4FBUVOTWAdUdMTAw2bdqETZs2UY/V1NTgnHPOweSkb6rfkZERTEwwn/C02Wx46qmnkJubCyA8S+18IRpu/I5Bq0gkQnp6OtLS0oDu4I4jXhiPEwtPZHQfnG0LMwiFQqSmpiI1NRUEQVABvVarRX9/v1NAL5fLfbpf+oter0dcXFxYB7IcHBzRi7vyfrqw2+3o6enB8PAw1q9fv6r6i822Lb4oz8nFgtzcXJSVlTEaD4Qqeb5c3EVWYPH5fNrOqeOuuRE/fPBvHHjtJVq25w/n3PeoW39zOnFl70Im0v1Rpbe0tOCkk06ifZwmk4lqyHf11SvFKHv27MGuXbuiKgZmCh6Ph88//xyPP/447rzzTp/eGx8fj6ycHCwuLsI+o3P5mszMTNx8883YsWMH8vLyXL4mLi4OcXFxyMnJgc1mw/z8PDQaDfr7+9HW1gaZTEbF3lKpNKjfe7irsH2FvBaEs9per9czWq17/fXX44ILLsCWLVtQW1uLPXv2QK/XY9euXYzsj0ue+wFTgR5ZAldYWIji4mKfLkYH5hYZT5yTHHegEx/UrZ5AJwgCg4OD6O3txZo1a1yWbHgKTOvr6/H000/TMmaSX/ziF8jLy8PS0hKKioqwbds2lJWVYXx8HE1NTThw4ADa2towODgIo9GImJgYtLW10ToGb3EMRjds2OCkevA2SCVLDrds2YKuri78+9//xu7du71uotDf34/169fj22+/9e8gfODgwYN48cUXsX37dsb3FUoifWHAkeXXCB6Ph7SYNEybpoM2hpMKToJYwIz6i4RcKIimiUOwlRA8Hg/x8fGIj49Hbm6uU0A/MDCAtrY2JCQkUMqYxMRERr4PnU7HWbZwcHBwuMBkMqGpqQkmkwn19fVeXSvZnjxfbWwEQaC3txeDg4OM+Ju7IhTJc71ej8bGRsTGxq4Qd/F4PFrHs+W4k0OSPE/KycXZv3sEAI/xxPlyXNm7+KpKP/bYY4My1uVce+21uPbaa3HHHXfgpptuCskY3BGucflvfvMbXHPNNbjyyivxyiuvePx9xcbG4rnnnsOJJ7oWCpELQf4ITAQCAdWDqLS0FEtLS5QqfWhoiHqejL2ZFrFEY/IcCO/KZqaT52eddRbUajXuuusuTE5OoqqqCh999NGKJqJ0EfbJ81BcFAUCAa1WMXa7HV1dXRgbG6NK4Hzltr7g2SG0E0DB/k7ckiPHFXmuFSU2mw2tra3QarWoqalBUlKSy9d5CgCPO+44iEQir7wQzz//fLz88sseX3PuuefiueeeA7Dy4puVlYWsrCzs3LkTCwsLsNvtmJ2dhVqtxq5du9DX17fqGOiEDIqsVitiY2Nx/vnnA/jf+e5NkEr69JHJWqFQiNNPPx2nn346gENKgdtvv93jNhoaGnDJJZcEJXluNBrx7LPP4ptvvsHMzAzOO+88xkpeOZjHXbnkVRuuwl3fB69pqFwiX/1FARKNZYShDmAdA3rg0PWDVKWPjBxqkk0+79iwNlCYLD/k4ODgCFfm5uagUqmQlJSE6upqr0v72Zw8Xy1JHYjNJpPjopuZmRmoVCq3qno6leckMdIEmHSLtG7THcK4OFz+9Es+NwZlEndNR0lR1HJVek9PDxYXg/N5ueP//b//h7GxMTz++OMhHQdJuIuVeDwe/vjHP+KPf/wjAKCvrw+XX345mpubER8fjwcffBBnnHEGvvnmG2zcuNHtdgQCAW3K5djYWGRnZyM7Oxt2u50SsQwODqK9vR2JiYlU3J2QkED7b4ggiLBOJPsKeZ0Pd+U50/Omq666ijGbluWEffI8FNAZ6JlMJqhUKlitVjQ0NCAuLs7nbRhsdvSZgh94Pjg6i/XxEhyenOT0+NLSEpRKJfh8PhoaGjwmLTwFgAkJCdi9ezduvPFGt+8vLCzEu+++i4KCAlRVVbl97YYNG5wSxZ4uvGRzn7m5OQwPDyM2Ntbta5mCDN5EIhHOPvtsHHXUUQDgtfLcsfTPXQBI+qr19/e73Y5IJMJPf/pTXH755bRXAbijvb0dv/nNb9Dd3Y1bbrmFKgmLpptlJOAueb4+eX1Qx1EuK2d8H6FOJIcCth2zRCKhFkEJgsDCwgI0Gg3Gx8fR2dmJ+Ph4ShmTlJTk99gNBgPi4uKibrGEg4ODwxUEQWBkZARdXV0oKSlBQUGBT9dHtifP3Y1Np9OhsbERcXFxPtts0jGuYCTPHSuIKysrkZWVFbTxHHbuhfj82Sdp3aY7zrjrQSd1d6gT58tx13SUnOvZbDbce++9oRwixV/+8hdcfvnlWLNmTaiHAiB8leeuKC4uxt69e1c8Hipvdz6fD7lcDrlcjpKSEkrEotFoMDw8DD6f76RKp0MQx7a5B9OQ16RwPY9Jy81gLSwHg+g5+2iErkBvdnYW3377LSQSCerq6vxKnD81MIE133UFPBZ/uaTbWfGu0Wjw7bffQiaToba2dlW132oB11VXXYV//OMfK9T469evxz/+8Q90dHSgpKQEQqEQV111FTo7O/HTn/6UCnySk5Nx1lln4c9//jOKi4u9Pq75+Xn09fWhu7sbra2tXr+PDhISElBQUIDDDjsMzz//PJ566ikqYCKtITwlz0l1Ammr4O6Cm5aWhu+++87t50I2GE1JScHNN9/ss/daoJAe6HK5HLW1tbjrrrvw4YcfYnZ2NqjjYIJwvQn6grtgLj0uHSnilKCNY+/IykCTbqJNCQEcCujYqoTg8XiQyWQoKirCli1bcMQRR6CgoAAWiwXt7e3Yt28fmpqaMDIyAoPB4JM6ibNt4eDgCGfojD9sNhtaWlrQ19eHzZs3o7Cw0Oftszl5LhAIKKWvI1NTU9i/fz8yMjKwefPmoCbOyXExnTwnv9vBwUHU1NS4TZwDzPjorzlsO2QZ7vdJJ0npGU5JKrbH6Hw+HyKRCGKxmPrz/vvvh3pYFG+++WaohwAg/JXn3sKWxqikiGX9+vU44ogjsH79ekgkEgwPD+Obb77BDz/8gP7+fszPz/v93URbpS/ZXyqcj5lp25ZgE/bK81DZtgQS6DmqNMrKypCXl+fXcZzZ3I/vdJ47KTON4b/XPoIgMDw8jO7ublRUVFCNH1fDG7XCCSecgBNOOAHAIVW71Wp126CioKAAH3zwAaampqDVapGYmIjs7GyfjmliYgKtra1IT0/HwsKCT+9dDYlEgtLSUmi1WoyNjTk9JxaLcdZZZ+H//u//PC46eApSfS05jIuLQ3NzMwBgcnISQ0ND2Lx584py27S0tKBYt7iju7sb3d3d2LNnD/XY3//+dxx77LEQCARhlbjkgjng2SOfxakfnxqUcbRoWxjfR7QFc0BwGobSBdmwNj09HQRBQK/XQ6vVYmZmBr29vYiJiaGUMXK53KPdQKQFgRwcHBz+oNfroVQqIRKJUF9fD4lE4td22Jw8J2NLm80GoVDo5G/uTTNUJsfFZPLcaDRCqVQCgFffLRPj4fF4OP+hJ/D6Xb/FzNAArdt2JLeqGjabLWwrXNk45t7e3lAPgSIaYnO2JM8d4fP5SEpKQlJSEoqLi2EymShV+ujoKABQqvTk5GSvVenRqDwP9+ONtHlT2CfPQ0EggZ7NZkNbWxs0Gg22bNkCudw/P94JoznkiXMSq9WKjo4OzMzM+HxMvgZc3lqokIkSXyAIAj09PRgeHkZVVRUIgsDXX3/t0zaefvppbNu2jfqOk5OTsXbtWuTn57ts7gIcuqjMzc1BoVB4dXyukuekMiaQksOMjAy3EwGywzabOO+88/DnP/8ZJ510kted6DmCh6dgLiM+A+vl69Eyy3xiO1WYyniwFY3Kc3+bD4UaHo8HqVQKqVSKvLw82Gw2zM7OQqvVoq+vD0tLS5DJZFRQv3yhlvM85+DgiHamp6fR3NyM7OxslJeXB3T/Y3Py3NEmI1T+5q5gMnk+Pz+PxsZGJCcno7Ky0qtFcqbGw+PxcPZ9j+LH9/+NA/98BQTd5wlfgKMuvop1Ni3+IJFIYDQaQz0MAMC6detCPQQAnFiJTcTExCAzMxOZmZmw2+1YXFykEukdHR1ISEig4u7ExES395RoS56Hk1DJFaRgKZLmTVzy3A8EAoFXTSyXYzAYoFQqIRAIAlJpAMBdA8FrELoaTx5Uoo5n9euYQtEx3hVWqxXNzc3Q6XSoq6uDVCrFzMwMzGazT9t55ZVXcOGFF6KoqMjr98THx/t0UVmePF/eGJSJksOuri6YzWZGSjMD4eGHH8b27dshl8u96kTPETxWC+ae3PYkfvL2Txgfx1beVuzbtw9yuZxSONDdxyDagjkgco5ZIBAgJSUFKSmHrISWlpYodczQ0BD4fD5MJhP6+/tx/PHHByUIfOqpp/DII49gcnISGzduxJNPPona2lpG98nBwREdBBIfkiKToaEhrFu3DpmZmQGPh83Jc/Iet7CwgPb2dsTHxwfd39zduJiYO42Pj6Otrc1n73qm5wabjz8Zm48/mfr37PQU/n7TVYCbz0AglmD7+btA8HjY9/e/wGZcWj5i5Gyows8uvQYxEdLD5N1338XPfvazUA8DAHDSSSeFeggUkfDdrka4CXj4fD5kMhllr2g2m6m4u6WlBQRBQKFQUMl0x2r8cDvWQAl35TlpjRlJnudhnzwPxUVRKBT6HOip1Wo0NzcjMzMTFRUVAf8QRo3WgN5PGwSBdlEsfrNlrV/HxIbkucFgQGNjI2JiYlBXV0eVDvF4PNx444244IILvN7WDz/8wNQwKRyDVDJxznRn+LS0NEgkEo/Nk0JBf38/pqamqJVs8rNw1YmeTar0aAnmPB2nWCDG8z95Hpd9eRlsYOacOrPwTJxTdQ70ej00Gg2mp6fR09OD2NhYp+aRga7qR6NtC5s9zwMhNjYW2dnZyM7Oht1ux/z8PD799FM888wzuOmmm5CXl4fk5GR8/fXXqKuroz2J8vrrr+P666/H008/ja1bt2LPnj045phj0NXVhbS0NFr3xcHBweEtZrMZTU1NMBqNqK+vp60Mm/TvZqN6khSjKJVKFBQUoKSkhBVjpHvuRBAEuru7MTIygqqqqhV9poI9ntWQp6Xjqhf/Af2sFj0/focf/v0PGBcXIBCKkFXTgMqjjkVJaSkAoHL7UdT7llfphoO/ubc0NDSwRuA0ODiI0v9+/hzM4iicC1fEYjFV/U4QBKVKHx8fR2dnJ6RSKZVIJy2WooVwV56T/fM425YoxxeVBEEQ6O/vR39/P9auXeuz/7Y7MsUCtC9fSA82BAHweFiXkeZ3UjLUyXONRgOVSoWsrKwVpad8Ph/p6ek+jTEY/odkcBSsxDkAVFVVYcOGDfj8889ZlTwXCARU8spRae7o/U4m1UlCrUpnQ2AbDLyZCK9VrMVXp3yFdwbewRNNT8BIBF5yKoAAtWm1uHL9lSiSHaoAIW068vPzYbVaMTs7C41Gg87OTlgsloBV6dGmhAAiR3nuCT6fD7lcjjPOOANnnHEGRkdHccstt6C3txennXYaTCYTjjrqKBxzzDE45phjUFBQEPA+H3vsMVxyySXYtWsXgENWYO+//z5eeOEF3HLLLQFvn4ODg8NX5ubmoFKpIJPJUF9f77EvhK+QiQHSV5wtkCp7giBQUlKCwsLCUA+Jgs65k8ViQVNTE5aWllBfX+9XZVWokrbxcgWqduxE1Y6d1GMtLS2Ai9iTIAhqTgBEVuKc5IknnsDVV18d6mHgtNNOw0MPPYQrrrgipOOIhvlWJCTPHeHxeEhMTERiYiIKCwthsVgoVXprayssFgsGBgawtLSE5OTkgFwcwoFwV57r9XoIBAKPvfzCjfD9NhwI9gXD2+S5xWKBUqnE6Ogotm7dSlviHADyY0N5EhJU4hwAfpnhn287ENrk+fDwMBobG1FWVoY1a9asuDiRwaBOp/NaXfi73/2OiaE6wePxYLPZgpY4Bw6d8w899BAqKioY3Y+v1NfXu7TI4fP5EAqFTp3ohUIh+Hw+pUo3m82wWCzU58hBL96qyPg8Pk4uOhnv/Pwd5EnzAtqnIkaBl3a8hN8f/nsqcb4coVCI1NRUVFRUoKGhgerToFarceDAARw4cADd3d3QaDReLxRFo/I8GpLny8nJyUFsbCzOOOMMTE5O4osvvkBNTQ1eeeUVlJaWYmhoKKDtm81m/Pjjj9ixYwf1GJ/Px44dO7B///5Ah8/BwcHh072KIAgMDw/j+++/R35+PqqqqmhPcDsmz9mCxWLBjz/+iMnJSYhEIr/7UzEFXXMnvV6PAwcOgMfjoa6uzm9LslALoRxx1xfKMdaPBI9zV+Tn54d6CBQ333wzOjs7Qz2MiPyeHYm05PlyRCIR0tPTsXbtWhx++OEQCoWQSqWYnJzE/v378d1336GnpwdarZY11yA6Cfe5Fml1Gc7HsBz2LPGHEd4kzxcXF6FUKhEXF4f6+nqvuwh7S3VCHF6YnFv9hbRfS/8bkPz3In1Tthxysf9l66GwAbHb7ejo6MDU1JTHBqdkMMjn87G4uIhPP/0Ud9xxB1QqlcvXr1u3jnGfNzIhaTKZKLVrsG6YJSUlePPNN3H00UdjYGAgKPtcjYceemhVpTB5wXZs/ER6xIdKlR6pQY4jvpZgS0VSvPjTF3HsO8fCDM+9BsR8MZ7f/jy+nvgaX058iRhBDHbm7cTRuUcjXuRb/wDH5pHuVOlkuWBcXJzL7YR7cOMPkWrbshqOgWB1dTWqq6tx6623YnFxMWBPv5mZGdhsthXNrtPT01kxCeXg4IgebDYb2traMDMzg82bN0OhUDCyHzKOZUvynJy/kf7m+/fvZ83YSOhIVqvVajQ1NSE3NxdlZWUBxaU8Ho81iavln00wq3RDiUajwZ/+9KdQD8OJ2tpaLCwshGz/nPI8siCPMTs7G1KpFBaLhZqztbe3w2azOc3Z6O5vFQrCfa6l0+kiyrIF4JLnfrFa8nxiYgKtra2M+uNtk0uRI+Jj1BLEYIUg/puMP3Q8x8UJcWV+YDYljjYbwUg+mc1mKJVKWK2HGpx6urAuD8B27NiB2tpa9PT04LDDDnN67eOPP45f/vKXjDYRIpO9SUlJaG5uhlQqRUpKClJTU5GYmMj4jdNoNGLv3r2suAiuXbsWH374IdXkzxeW27s4BtaOJZ1kkE2HV3pvby+qq6upf59zzjl45JFHkJiYGNB22Yw/ViYSoQQfn/Qxjnz7SLeviePH4dOTPwUAlMhLsGvtroDG6QipSk9NTQVBEDAYDNBoNJiZmUFvby8kEgll7+Lolc7ZtkQPer3e5TUwkprhcHBwRDd6vR4qlQoCgQANDQ2Ml8azpWno5OQkWlpanOZvbFJVkwQyJoIgMDg4iN7eXlRWViIrK4uW8bAlURmKvlBs4JNPPsGHH34Y6mGsINTJs0j+zoHoSp4DznMPkUiEtLQ0pKWlgSAIl/2tyEQ6Hf2tQkG4z7VIwVEkERHJ82B7rQkEAqoZoSN2ux3d3d0YHR3Fxo0bGW3uJRMK8Or6QhzR2MfYPpxwsGkBgHQAf6oKvBlIMJPni4uLaGxsRGJiIjZv3rxq6amr84p8r9EYuDezLzgGgJWVlSgvL4dGo4FarUZjYyN4PB6VSFcoFIwk8Q8ePIhHHnkkZKrz1NRUdHZ20jqJc6dKJ5Pqjt6I/jQddZccf/XVV/Hqq69icHCQMTVXqPG3+VeMIAYvH/Uyzv/sfJfPf3zix4EOzSt4PB7i4+MRHx/vpErXarXo6uqC2WxGUlISkpOTYTaboyZwJQn3gM5f3CXP6SAlJQUCgQBTU1NOj09NTQWlnwYHB0fks9q9anp6Gs3NzcjOzl7RC4gpQp08d2yYuXz+FuqxucLf5DlZTaDRaFBbWwuZTBbS8TABOXdzFMREeuIcAO68885QD8El7733Hs4+++yQ7JstCzpMEk3Jc/J37epYHSuJPfW3Wq2SmG2Eu/Jcr9cjLi4uos7PiEieBxtXgZTJZEJTUxPMZrPfDVd8JU9CrxWMa4hDTi3LTvqXN9LTOMcxec4kU1NTaG5uRmFhIYqLi73zYmZJMOhKOSEWi5GZmYnMzEzY7XbMz89jZmYGfX19aGlpQVJSEpVMp+uitWfPnpDatdx6662Mq58cVenkb5z87F3Zu5B/X05NTQ26urpW3d8VV1yB119/nY6hsw5/k+cAUCQrwhtHv4Enmp/AgalDfpwnF5yMqzZcBQE/NEGEJ1X67OwsBAIBuru7oVAoIJfLwzrY8YZwD+j8xWAwMHZ/F4vF2Lx5Mz777DOcfPLJAA7dGz/77DNcddVVjOyTg4ODA/hfg8yhoSGsW7cOmZmZQdt3KBPUZrMZTU1NMBqNqKurW7E4ypa5gCP+jMloNEKpVAI41C+Izng6VA1D3eEYs0dD4hw4VPXORkZHR2GxWPwSIHGsjqPIK9IhrzHenEPeVBKTiXQ2z9nsdjtrx+YNTAqOQgWXPPeD5UHe3NwclEol5HI5qqurWdUtPjBcJ84VAMri6Qm6mE6eEwSB/v5+9Pf3Y/369T6p98gbUSBJwEDxpuSQz+dDLpdDLpejtLQUS0tLmJmZgVqtRl9fH2JiYqhEulwu9ytwmZmZwX/+8x86Dskv1q5di/POO4/x/Tz++OO47bbbnB574IEHqO71jqp0svpkuSrdFysWNpZY0kWgv5scaQ4ebniYxhHRx3JVen9/P+bm5ij1mqMqXaFQRNyqOxCdynOyLJRJi5brr78eF1xwAbZs2YLa2lrs2bMHer0eu3bRZ0/EwcHB4YhjArm+vj7ok91QJc/JitSEhATU19e7nL+xVXnuy5jIeWpKSgrWrl1LezKGLQsMZNypVqshFouRlpYWcZYBrmDTwsVyPvvsM1xzzTUh6S8Vyvl7sCCPMdKPE/hfrsjX88ZVJfHc3Bw0Gg01Z5PJZJQtJ5vmbOE+1+JsW1hKsE9woVBIlYKNjY2hs7MTpaWlyM/PD/pYYgEsMbFh0t/cxfF8V1NC227IpCMTQZfNZkNLSwvm5uawdetWn/2lHRP7wV71IwiCKk/ytTFobGwscnNzkZubC5vNBq1WC7Vajba2NlitViQnJyMlJQUpKSmIiYnxapudnZ1Bt6ohSU1Nxeeff874ZM7dxf22227DbbfdhnvuuQcXXnghpFIphoaGIJfLkZiYiIWFBcTFxUEgEGDLli2MjjGciIag1ZHY2FiUl5dTCgetVguNRoO+vj6IxWIqKGOzwsEXwj2g8xemVRRnnXUW1Go17rrrLkxOTqKqqgofffTRiiaiHBwcHP6w/L48NzcHlUoFmUzmNoHMNKFIUJP9qVarSPU1UR0MfElWj42Nob29ndF5KhsahpJio5ycHMTExGBmZgYDAwMQi8VITU1FSkpKxMRf4URLSwsmJyeRn5/vlQCJwzeiaa7li/LcE0KhkMqDEASBpaUlaDQaaDQa9Pf3U3M2spI4lKJYm80W1qLcUPc8YILw/TZCCHnjbW1txczMDKqrq5GcnBySsRwmi8On8wZ6N7rM39yRT9bnQUyznzYTioWlpSUolUoIBALU19d7nSRePi4g+Cv6jl59AAJaURYIBE5lSzqdDmq1GmNjY+jo6IBUKqWCSk9NRwUCAWJiYlx6/TMJj8fDpZdeyngzviuuuGLV19xzzz245557nB6TSCTg8Xiw2WywWCysVn+EgmgK6MjrhaPCgVzAIr3Se3p6YDKZWKtw8BbyGhWNk1CDwcB4IHjVVVdxNi0cHByMQhAERkZG0NXVhZKSEhQUFITsXhTM5Lmv/akEAkHIE8PL8WbeRBAEurq6MDo6ik2bNiElJYXR8ZCin1CcQ45VujExMU4CotnZWajVanR0dMBsNjsJiJi2ggwWPB4Pxx13HD744INQD2UFZrMZY2NjKCwsdBKlOf5hUpUebvG1r0RT8pwJixoej4e4uDjExcVR1wxSld7b2wuj0eg0Z4uPjw/q5x3ucy0mrS5DBZc89wOz2Qzg0GpKMLrQe+K4VNkqyXMff+BuEue3ZMlxRQEzDcvoTp7Pzs5CqVQiLS0Na9eu9fsGTF4cgxk0kwEgXaurjvB4PCQkJCAhIQFFRUUwm82YmZnBzMwMhoeHwefzqYAyOTnZaaVz3bp1KCkpQVNTE23j8Ybs7GyvEtuB8re//c2v9wWqxv/lL38Z0PvZTLQFdJ4WnsjfFQDKd2+5wiGcVOn+lk6GO3a7PSJLEDk4OKILsnHkzMwMNm/eHPLG5cFKni+3p/HmWs5W5bmnZLXFYkFTUxOWlpaC0ofLUWwU7LjPU2NQx/iLtF1Tq9WYmJhAZ2cnpFIp9bxMJgvbmHV0dBS/+tWv8OWXX8JgoFlQFyBisRg5OTlOjzkmx0klOjn3pVOVHg2CpmibawHMzj0EAgE1JwPgVEk8MDAAkUhEeaUrFArGVeE2my2s51qc5zlLCeZFY2ZmhkogbtiwIeSr1kcrElAmUaPb6EkRTGD1JLprf3MAOEkmweX5zJWM05k8Hx0dRUdHB8rKypCXlxfQuRGsZqYk3vib04lYLEZWVhaysrJgt9sxNzfn1HRULpdTQWVCQgJuv/12XHXVVZienna7zfz8fPz1r3/Fli1bwOPx8OGHH+L000/3e4wvv/wy5HK53+9nO3v27IlY+4toCugcleer4U7h0NPTA6PRSHmls1mVHq3Jc4PBAIIgGK+E4eDg4GAKk8mEAwcOQCAQhFwARBKM5PnCwgKUSiUSExN9sqdhq/IccK1K1Ol0aGxsRHx8fNBseBx7RAWL5VW6q82beDwepFIppFIpCgsLYTabqQaCSqUSPB6P6g+lUCggornKmgkIgkBvby9GR0dRV1eH6elpXH755Xj55ZdDPTSKhYUFHDhwAAUFBS6fJ89l8jwmlejk9xuoKp2NMTSdRNNcKxTzZXLOlpOTA5vNhvn5eUr81NbWBplMRiXTpVIp7d9FuCvPdTodo1VPoSAikufBgCAIDAwMoK+vD2vWrEFnZycrVjQThAK8vr4Qd/eO4Z3ZlavNAgCrhqMe/M3/WJyB49KSGL0w05E8t9vt6Orqwvj4OG02OsEMBulKnFttdhwYmAV4QHZiDL7p1yIzUYIdazyXpfL5fCgUCigUCpSVlWFpaQlqtRozMzPo6elBbGwsSkpK8PLLL+Oll17C+++/j7m5OfD5fKSmpqKhoQE33ngjNmzY4LTdHTt24Oyzz8Ybb7zh83e8b98+bN682efPIByoqKjAN998syLwD0YDnWARbQGdP8GNK4WDRqOBVqulVOmO3eDZ4ntHnrPhHND5g16vB4CIU1FwcHBED6QSNDc3lzXxBtPJ8/HxcbS1taGoqAhFRUU+xSZsVZ4DK2MPtVqNpqYm5ObmoqysLGgxWLB7RNFRpSsWi5GZmYnMzEzY7XbMz887CYiSkpIoW0s2VpuR1SMLCwuora2lxvjMM8/gzTffxNISIx3R/OKiiy5CTU0NiouLV32tO1W6Y4UB+TrS1tTd98+GPA3TRNNcyxehEhMIBAIqV1JaWoqlpSVKlT40NEQ9T6rS6ViAiwTlubuFs3CFHTNxlmO1WtHS0oL5+XnU1tZCJpOhp6eHNcGUQiTEk2vy8SSATzXz+Fi7iDVxEpyXqcDE8DBOHNdj3p3y3IVNiwzAS2tzsDEpOOq6QJPny8sT4+LiWDO21XBsDOpP4txOEJheMOL2t9uxf3DBwyvbAAB37SzB2TW56JpaRMeEDhtzE1GYvDIojI2NRV5eHvLy8mCz2Sh1hs1mw5lnnonLL7+cUstWVFSgtrbW5ecuEonw+OOPY+vWrXjssccwMjKy6jEVFhbi008/RUYGMzZBrnj88cfxm9/8hvH9XHTRRbjvvvsgk8kCDgp9ZXx8HPX19ZidnQUAFBUV4YMPPkBWVhYt219ONAV0dKkhVvPdI1XpCoUi6L57jthstoB6MYQrBoMBQqHQrx4aHBwcHGyAz+ejoKCAVYklppLnjv7mVVVVSE1N9Wtswe73sxrLK2MdBV6VlZWMxXWrjSdYYiN/50zu4PP5kMvlkMvlVFJsZmYGarUavb29iImJcWo6GupkltlshkqlAgDU1tZCLBZTz9lsNpx22mmsUp8Dh6r1Jycnfarcc6dKJ+dPjh7Y7uxdIj1O5eZaoSM2NhbZ2dnIzs6mFuA0Gg0GBwfR3t6OxMREKpmekJDg1/cU7spzzvM8CtHpdFAqlZBIJGhoaKBuUKHoDO8NO5Jl2JEso/7N5/Pxe7EJfxIn4UedyfnF/02c54sEmLTYkC4W4J3KPMhjg1vCGUiCmunyRB6Px1gw6EvJ4ejsEh7/vA/vt6kBABIBYPTj9Pvdh7343Ye9Kx7//No6ZCTGunyPQCBAWloa0tLSQBAEFhYW0N7eDoIgUFxcjNjYWExMTLhtOiqVSnHppZfioosuwkUXXYR//OMfK/Zx0kknYffu3cjPz/f9oGjg4osvZjR5fuedd2L79u3YtGkTVSJNR1DoLV9++SVOPPFEp8f6+/tRUVGBjz76CA0NDf4emluiKaBjQg3hyXevv78fIpHIySs9mKp0tgWwwUKn04V00YKDg4MjEhEIBLBYLLRuk0wwms3mgHy/2a48t9lsaG1thVarpQRewSZYPaKCZW8ZGxvr1HSUFBC1tbXBarU6NR0N9mK6Xq+n7IcqKyudEmt2ux3HHXccvvnmm6COyVsyMjJw9tln4/nnn/fru/OkSndl78KmBUKm8NRzKdJg87E6LsCVlJTAaDRSczayr5yjKt1xwcsTkaA8j7Rq3YhInjP1Q5qcnERLSwvy8/NRWlq6ogkJ24IpVwgEAsjsVry6rgD75w3425ga+xf0AAHsSJLijpJspMeE1tfN3+R5MMoTmVKe+1JyOKxdwrH/d8DpMX8S55746Z4DaL3zJ+Cv8hlarVb09PSAx+Ph8MMPB5/P97rpqEAgwIsvvojLLrsMf//732GxWHDyySdj586d9B6Mn0xMTOC0007Dt99+S9s28/Ly8Je//AUikQgbNmzwWMLla1BI/t0blifOHTn22GOhUqlQVFTk1ba8JZqS58EI6Jb77s3NzUGr1aKvrw9LS0tB7QYf7koIfyGT5xwcHBwc9CEQCAJuwO7I/Pw8lEolZDIZqqurA1pcZqPnOVn5tbS0BKVSCT6fj4aGhpBVRZHjYfJz8tQYlEmWC4h0Oh3UajXGxsbQ0dGBhIQEyivdX3Wpt8zOzqKpqQnZ2dkoKSlZsa+zzz6btYlzktdeew0ffvghxsfHA9rOagIkk8lEPUZWS4ZzEtId0TbXCpfvUCKROPWVW1hYoBLpy1XproSHJOE+3+KS51GC3W5HT08PRkZGsGHDBqSnr2yWycYyPleQiokYPh+bhQR4mmFclZCADRs2sMY/19cENUEQGBwcRG9vL+PliUwkz31VTtz4Zgut+3fHr/7WiBcvcO8xbjAYoFQqER8fj02bNlEXc2+ajqamplK2LvX19aivrw/KMflCYmIi9u7di9HRUTz//PN45JFHAt4m6ZVYWVnp0w1/taDQl070zc3Nq+5v165d+OKLL2gNSqIpoAu2D5+jKp0sMdZoNEHrBh/uSgh/MRgMERcEcnBwRB9MVlX6A52CpED8zV3BRuU5cOg7VCqVSEtL8znGZGo8TJxTpL0l+R0EM3G+HB6Ph4SEBCQkJKCoqAhms9mlgIhsOkpn7DUxMYH29naUl5cjJydnxfMajQbvv/8+bftjkvn5eXR1daG8vJy2bToKi4xGI1pbW5GQkIC4uLiAm46ymWiaa4VT8twRPp+PpKQkJCUlobi4GCaTiVKlj46OAgA1Z0tOTl5hwxSOx0zC2bZEAWazGU1NTTAajairq3M7UQ4n5bndbqdU9AUFBS5Xq0OJLwlqskGKRqMJSnki3cGgo+Lc2wCwdUJP2/49cXBoAVMLS0h3Yd9Cqh0yMzPdqvyXNx01GAxUUEk2HSWDyqSkJNbeDHJycrBt2zbs2bMn4DJis9mMdevW0TJ5c1SlO/5ZLSg85ZRTVt2+UqlES0sLNm7cGNA4HWHTxJxpQh3QxcbGIicnx2M3eDpV6aE+3lCh1+sRFxfHqvsnBwcHR7hDx5zKbrejq6sLY2Njfvubuxsb25TnY2NjsNvtyMvLQ3l5OSvuSUyKjch4km29VsRi8QoBkVqtRk9PD5aWlqBQKKhqXH/7cREEgf7+fgwPD6Oqqoqy8ltOZWVlIIcSdHbs2OFVHyxfMRgMaGxsRGJiItatWwfA2SbVVwES24mm5HmoG4bSRUxMjFOz4sXFRSqRTlazkMl0m80WtspzgiCg1+t96nMQDkRE8pyui4Zjmd9q/tlCoTAskudkWV9LS4tbFX2o8VbVYTQaoVQqARxSL5Pe0UxCZzDoT8lhsBOQR+45ZA9zTLkCfzjrUCKVVDuUlZUhNzfX623FxcVRTUetViu0Wi3UajVaWlpgs9mQnJyM1NRUJCcns64B37Zt2xAfH4+5ubmAtnP77bfTHtS4sndxFxQODw9DrVZ7td2ZmRlaxxkpQY43sMmHz1M3+MHBQQiFwoBV6eFeRugvOp2OU55zcHBw0EygyXOTyYSmpiaYzWY0NDT4nah0BZuU52QD1LGxMYhEIqSnp7Mm9qDbtoWJxqBM4iggKi8vh16vp5qOdnd3Iy4ujkqkeysgstvtaG9vx+zsLGpqatzGHzabDYuLi3QfEqNotVratzk/Pw+VSoWMjIwVQi/HSl5fBEhsJ5qS52yaa9EFn8+HTCaDTCajqlnIOVtLSwvsdjt6e3tZmy9ZDc62JYIhV3uKi4tRWFi46o8zHJTnFosFfX19sNlsOOyww1h78nqToJ6fn0djYyOSk5NXNEhhEjqU5740BnXEbLXjhD8eWPV1TPBxlxZ3/LsNu9ZLMDw8jI0bNyIlJcXv7QmFQifPwMXFRajVaoyMjKC9vT2onoHejnfHjh345z//GdB2PHmN04E7exfynNu0aZPX2yopKaF1bNGkPGfzQsHybvBzc3OUvQupSieT6VKp1KvfXriXEfqLXq+PuPJDDg4OjlATyJyKFD4lJSUF7G/ubmxsUJ5bLBaoVCqYTCbU1dXhxx9/ZMW4SOhs0BisxqBMEh8fj/j4eOTn58NqtVJNR8mEmGPTUVfNAy0WC5qammC1WlFbW+sxafaHP/yByUNhBFIVThczMzNobm5GcXEx8vPz3b7OXX8p0h4o3FTpbJ5/0E00VL2KxWJkZGQgIyMDNpsNX331FeLj4zE+Po7Ozk5IpVJqziaTyVj/eXDJ8wiEXNWdmppCdXW123Ko5bA9ea7T6dDY2AixWAyBQMDqE3e15PnExARaW1tRUlKCgoKCoAZRgSrPfWkM6sjX3dO47LU2v/dLB281T+OYZKFHtYM/8Hg8JCYmIjExkfL+0mg0UKvVGBoagkAgQGpqKlJSUhjxa/aWc889N6Dk+XHHHUfjaLzDMSj86quvvH5fRkaGx2DTHzg1BPtwVEYBcFKlk7890t5FLpe7bXAbDQGsK7jkOQcHRyTAtvuVv3OqsbExtLe3ey188gc2KM/JOV18fDzq6uogFAoZsUkJBLqU56FqDMokQqEQ6enpSE9PB0EQWFhYoHzSyeaB5LxHKpVSldZxcXFOPabccffddwfpSOjj1VdfpW1b4+Pj6OjoQGVlJTIyMrx+32oCpHBQpUfbXIttnz+TkLmjgoICCIVCWCwWas7W2toKu91OzemSk5OD4sjgC3a7nfM8Zyv+XjSWlpagUqlAEAQaGhoQG7vS69kdbE6eT09Po7m5GXl5ecjMzMSBA6FRL3uLuwCQIAj09PRQPm90+Rf6QiDBoL8lh7s/7MJL3wfWhZwuttTUIJbhi3FMTAzjnoH+8LOf/czv96pUKpSWltI4Gt/xJXn/8MMP0x6UcAEd+3GlStdqtZQqPTExkUqmO6rSw/V4AyUSFRQcHBwcocbXOZXdbkdnZycmJiawadOmgCojvRlbKJPUjnO60tJS6j7MtuR5oMpzNjUGZRIej0fZNBQXF8NoNFL9oQYGBiAQCGC1WpGcnIx169atmji/7LLLgjRy30hPT8fU1JTL5+6++24UFRUFvA+CIDA4OIjBwUFs2rSJEob4iztVuuOCDvk60n8/1LFwJM61BJ//P0iUT1P/NlVdAuuRd0SVyh6A07UQAGXVRS7C6XQ6aDQaTE5OUtZQZCKdDb3l9PpDPfs4z/MIQaPRoKmpCWlpaVizZo3PNiACgQAmk4mh0fkHQRDo6+vDwMAA1q9fj4yMDCwtLVGrqGy9uLoKAK1WK5qbm6HT6Tw2bg3G2PwJBv0tOWyfWGBN4hwAJEH21mLCM9BXPvvsM5x55pkwGo0+ve+KK67Ao48+Svt4/MHXsdfV1VGlinQFhWy+5tBNJAR0jr+9kpISGI1GaDQaJ1U6GZSZzeao9DznlOccHBwc9ONL8txkMkGlUsFqtaK+vp5xUUWolOcEQWBgYAB9fX1Yt24dMjMzV4yLbcnzQMRGbG4MyiQSiYRq+E72mEpMTIROp8NXX33lJCByJfJ77bXXfNpXbm4uenp6vH5PYmIiFhYWvH49AJxwwgl47bXXMDw8jKeeegpPP/00rFYrdu7ciVdffdVtVaMvEASBzs5OTE9PY8uWLbQn6Nyp0h17TQGht3eJmLnWmBKxb+0C3zyD5UcjUT0HQvUc8iUZSI3NgXB6PXixCtgyN8JesA3gR2Y602azuT2veDweEhISkJCQgIKCAlgsFszOzkKj0aC9vR02mw1yuZyat/kiEKYLMnkeafOmiDnbvPWmJlcpe3t7UVFR4VMDREfIlWG2QCabFxcXUVdXR91EHFdQ2ZrsWB5wkZ2yY2JiUFdX59ILLlj4ozz3t+TQbLXj9Od+9GeYjBHqG3KgnoH+7M8fkpOTcdtttwW8f7rwNYAjV7HpDgpDff4Ei3CxbfEFiUTipEqfn5+nmo7q9XqIRCIMDg765JUe7uj1+pBUQHFwcHDQCduu194mzx39zTdv3hwUW79QKM9tNhtaW1sxOzuL2tpayGSyFa9hW/Lc3x5RkeBvHigEQWBoaAj9/f3YsGEDUlNTQRAEJSCamppCV1cX4uPjqf5QMpkMPB4PYrHYq3yEQCBAdnY2ysvLodPpMDEx4dXYFAoFbrrpJtxxxx1eH89f//pXAEBeXh4eeughPPTQQ16/1xtsNhtaWlpgMBhQW1sblMSgJ1V6KO1dwj55bjYg7sn14MOzIJUHINY4iVjjJDD7g9Nz1rhs2CqOg239ObCnlDE42ODiS5WvSCRy6i2n1+uh0WgwPT2Nnp4exMbGOqnSg5ETJOeK4dbkdDUiJnnuDVarFa2trZibm0NNTQ2SkpL83habbFv0ej0aGxshkUhQX1/vlER0XDFlc/KcvPFrNBqoVCpkZWWhvLw85GpOX5TngZYcftLuurwteBCAw3rvvcfT20AyUNx5BpJNRxMTE6lEuq9NRw0GQ0BJsXfffTfgckE68WUhQSKROE1A6QoKIzGh7I5IUJ57gs/nQy6XQy6Xo6SkBF1dXdDpdFhcXFyhSlcoFLSoitiIXq9HYWFhqIfBwcHBEVGQCWpPiaDR0VF0dHQEvf8RqTwPVpLKaDSisbERfD4f9fX1bhMPdCbPLRYLurq6IBAIUFpa6teihD/j4RLn/7MgUqvV2LJlCxITEwEcWoyQSqWQSqWUspQUEKlUKgBASkoKnnrqKezatWvV/RQWFkIikeDss8/Gn//8Z6Snp3s1vpycHFx++eW4/PLLUV5eDo1G4/H1l19+OaPJMovFAqVSCR6Ph5qampDEm6up0oPZdDTck+exz21bNXG+GkLDGISNzwGNz8G09lxYdj5M0+hCi7+5O8drByk+JFXpnZ2dsFgsTqp0pqq3yGrdcD4/XRE1yXO9Xg+lUgmxWOwxGPEWtiTP1Wo1mpqakJOTg7KyshUXZ/LfNpuNtQkNMuAaHh5GV1cX1qxZg5ycnFAPC4D3wSAdJYdf9XgOSJjHebxnbPavKiMYLPcMNJlMlGfg4OAghEIhlUhPTk52e/Ox2WxUoOovZ5xxBjZu3BjQNkLJm2++6fRvuoLCcA/ofCHaPMD5fD4SExNRWlrqpEofGhpCe3s7EhISKK90Xxey2EwkNr7h4ODgCDVkvGGz2VYkboPpb+5pbMGIaWZnZ6FUKpGWloa1a9d6jCv8tZMxGo2YnZ1FUlISYmNj8fjjj8NgMDi9prS0FKeffrpP2/U1eR6JjUF9hawaN5lMqyqoRSIRMjIykJGRAYIgMD8/j5mZGeTm5kIkEsFisbh9b2lpKQoLC3H++efj5JNPBo/Hw2OPPYbrr7/e4/iSk5NxzTXXUOMaHBzErbfeiv/7v/9z+fpbbrkFd955pxdH7h9LS0tQKpWIj4/3yg8+WCxXpTv+YVqVHrZCJbsdktfPhMA4SetmY9pfgT21HLYtF9G63VBgs9loOVeEQiFSU1OpihaDwUAtxPX29kIikVCJdLlcTtvvSqfTReScKWKS557KxaamptDS0oLc3FyUlpbSciKGOnlOEAT6+/vR39+PyspKZGVluXwdGZCwqbRvOXw+H7Ozs9Squ1wuD/WQKLz57PxtDLqctMTIKmsJJjExMU4WE7Ozs5iZmUF3dzdMJhPkcjlV6kgGgUVFRW6b2XhLQ0MDnn/+eToOgVZ8GdMRRxzh8flAgsKwDOj8IGyDVz9xXIx1VKUDh/xoSa/04eFh8Pl8SpGenJzM2kVcb9DpdFzDUA4OjrCHbfcrd8nzYPubrzY2JhfJSWV9WVkZ8vLyVv2OvKmMJa1KR0dHsbS0hI6OjhWJclf09PTgq6++wvbt270evy/2qdHQGHQ1jEYjlEolYmJiUFNT45Pan8fjISkpCUlJSSgpKcHExAROOeUUfP3119RrxGIxrr76avzmN7+BwWBAenq6U1XqZZddhpqaGrdzgPT0dLz44ovYtm0b9Rifz8dDDz2EBx98EN3d3XjkkUfQ19eH7du34/bbb2c0vltcXERjYyPS0tJQUVHB2nPGlb0LOWdiQpUerkKl2D2VEBCLzGz7q7uh23AOIA7+/YJOmHCN4PF4lCVuXl4erFYr5ubmoNFo0N3dDbPZDJlMRgmg4uLi/D6/9Hp9RNp6Rkzy3BUEQaCnpwdDQ0NUA026CGXy3Gq1oqWlBfPz89i6deuqytlQJ/o9YTabMTo6CovFgsMOOywkDQ08sVpwSmfJ4a/q8/CX/aN+v59OwvkyRybrkpOTXTYdtdlsOPXUUwPej1gsxsMPPxwUz01fmJqawi233OL16325MfsSFJKPRQORbtuyHE9K+5iYGGRlZSErKwt2ux0LCwtUIr2joyOsVekGgyHiusZzcHBwhBoyfnacq8zNzUGpVEKhUIRUZeoY8zCB3W5HV1cXxsfHUV1djeTkZK/H5WlMWq0WzzzzjN/j+vbbb31KnnujPHeMGYHoagzqyMLCAlQqFVJSUlBRURFw/BgbG4uPPvoIwKFFHq1WS1XjNjU1QaFQgMfjISUlBRKJhHpfdXU1VZl/+OGHAzhk0/LBBx+guLjY7f54PB7Ky8uDJh7SarVoampCQUFBUC2bAsVdJS/5O6BDlR5uyXPeRAviXtnJeJ5B8tqpMP7yI4b3wixML9gCcKrUJwgCS0tLlACqv78fYrGYEkDJ5XKfch4GgyEkC95Mw66sD42YzWY0NzfDYDA4NdCki1AlpMlmmmKxGA0NDV55G7OtqQwJuYosFAoRHx/PusQ54Fl5TnfJYbI0BmVpceieXl0VwjSFCsnqLwoTHJuO0lk+dOWVV2LTpk20bY8u6urqsLS0xPh+PAWFc3NzsFqt4PF4MJvNQW+gE2yiTXnurRqCz+dT6ijSXkmj0UCr1WJkZAQ8Hs/JKz2UzaG9Qa/XR2QgyMHBwRFqHOdVpAq7tLQU+fn5Ib2/ukrs04XZbEZTUxNMJpPPynpPczuCIAJKnPvDaspzR7ERkx7QbEetVqOlpQVFRUWMnNsCgcDJokGn02FmZgbj4+Po7OyEVCpFamoqUlJSkJiYCB6Ph02bNkGv19M6DrqYmJhAe3s71qxZ47bKPlxw13R0+aISec3x5ncSVslzqwnxr+wMyq6E6lbAsgSI2Jdb8pZg9yvk8XiIi4tDXFwccnNzYbPZKFV6b28vjEajkyp9NT/zSK3WjZjkueOXt7CwAKVSiYSEBNTX1zNSRiQUCoOePCdXkH1tpslG5fnU1BSam5tRWFiImJgYTE7S63lFF66U50yWHP7jkhrUP/w1DJbQLnacsSU7pPunG7vdTvsCmskUWIMTJrjvvvswPT0dkn2TQeHMzAxaW1tRWloKqVTqtMhEvs7boDAccDyuaMFfNYQnVTrZ9JdMppOTOrZAdq/nlOccHBzhDpuurSQCgQAWiwVtbW2YnJz0SYXNNEyIkHQ6HRobGyGVSlFXV+dzFaMnz/P9+/fTMUQ8/PDDOOaYY7xS/q+WzI/2xqAAMDIygp6eHlRWVnrdsDMQeDweEhISkJCQgMLCQpjNZmg0GqjVaspWz7E/FNsqaQcHB9Hf34+NGzcGvdcB06ymSl9eneFOgBROyXPh/ieCuj9+98ewV54c1H3SSTCU554QCARUohw4JODVarXQaDQYGBiASCRyEkAtv36QDUMjDXZdJWlgbGwM7e3tKCoqQlFREWMXlGAmpEnPut7eXqxduxbZ2b4lNv1tKsMEjl7tpJXO+Pg4K5XxwErlOR2NQT0hEvDxw63bMaCex4lPN8JGu+sFAW9MWY5dm0b3jkNKQUEB7dsM1C+dbubn5/Hggw+GdAykQqSystLJJmt501HHoJDpTvRMQ14LwnX8/kBHg1RXqnQyKBsdHWWlKp307+Pg4ODgoBc+n4/29nbw+Xw0NDSwqhqV7jnf9PQ0mpubkZ+fj5KSEr/mEe6S1f/617/Q2dlJxzBhs9nwwQcf4OOPP8Zxxx2HdevWuX2tu0pdLnF+6DPo7u7GxMQEqqurkZSUFJJxiMViZGZmIjMzE3a7HXNzc5iZmUFfXx9aWlqo/lApKSkhTXqRn9fk5CS2bNmyqj1tJOBOlb6aACmckuei7veDur+4j66CUTcO69ZfB3W/dBFs5flqkKr0nJwc2Gw2zM/PU/YubW1tkMlkEAqF0Ov12Lp1a0iS5wUFBRgaGnJ6bPfu3T7Z2a5GxCTP7XY72tvbg9aNnQykmL5o2Ww2tLa2QqvVora2FjKZzOdtCAQCViSnbTYbWlpaMDc35+TVzlZbGcBZeR7MALAwVYaWO4/E2t99QfOWVx9zokSAtITIaV5KlhzRTXV1Ne3bDIQ//vGPPr+HzoTk8PAwent7UVVVtUIt5ikodOX5R/49HHBcCIgW6EieLycmJsZpUre4uAiNRoORkRG0t7c7eaWHSpVuMBgiUkXBwcHBEUpmZ2dhNBohl8uxefNmViUMAPrmKa4ERIGMiewzAxyaYz311FOM2G/YbDa8++67EIlEKC8vdzsex0pdskqXTnvLcISc++r1etTW1rLG+o3P50OhUEChUKCsrAwGg4HySe/p6UFsbCxSUlKQmpqKpKSkoMXkdrsdra2tWFhYQE1NDWs+r2DiTpXuSoBks9nC5ndlj5Ei2Fd2yTcPQLf5IkAYfnmNUCvPPSEQCKjrR2lpKZaWlqDVarF3717cfPPNiI2NRUVFBWJiYjA7Owu5XB60sf3ud7/DJZdcQv2b7orhiEme9/T0YG5uLmjd2B0vaEwFeUtLS5QneENDA2Ji/Pvhs0F5vrS0BKVSCYFAgPr6eqdjYXPy3LHxYSiUE0mxAswtBfe7e+rsDWFzI/aG9vZ22reZkJCAuro6zM7OQiaTseLm9qc//cnn92zbti3g/RIEgb6+PoyOjmLz5s2rLvCtFhTS3YmeaaJReW6z2RhNbvD5fMhkMshkMhQVFVGlxstV6aQyPRiqdJvNBoPBwCnPOTg4wh42xXgjIyPo7OyERCJBTk4O6xLnAD3Kc3cCIn9xnDvp9Xo88QTzlghvvfUWrr32WpdVAY7jcefhHG2YTCaoVCoIBALU1tYyYiNLF3FxccjLy0NeXh6sVivVdLSlpQU2mw3JycmUVzpTMZfFYkFTUxNsNhtqa2tZUXHIBtwJkCwWCxYWFiCVSsOiv5St9DiIplRB36/o2z2wbLs56PsNFLYpzz0RGxuL7OxsXHjhhTj77LPx6aef4tlnn0VTUxNSU1OxdetW7Ny5Ezt37sSmTZsYPUcTEhICWphejYhJnhcXF6OwsDBoJxm5H6aSCBqNBiqVCpmZmQF34g618nx2dhZKpRJpaWlYu3btimNhQ3LfHaSyI1QlhwZzcL83ER/YnJcU1H0yDd3lkcXFxXj00UchlUrR1NQEgiCcPANDFexptVqf33P//fcHtE+CINDR0QGNRoOamhq/VLnLg0LHP3R0omcaTnnOPI6lxgRBUF7pZFO5YKjSSTUf53nOwcHBEThkxfDU1BSqq6vR39/PWiFNoCIfTwKiQMdEEAReeOGFgLfnLc888wyuvfbaFY8vFxtFo7DAEZ1OB6VSCblc7nLuy2aEQiHS0tKQlpYGgiCwuLgItVpNVQImJiZS856EhARaYi6j0QilUgmJRIJNmzaFTdIw2DjOl0hxWEFBAVX5wWYBEhGXGpL98uf6Q7LfQGGz8twTEokEP//5z/Hxxx+jtrYWV199NT766CN89NFHeOSRRyCRSPDDDz8gNzeXkf0/+OCDuO+++5CXl4dzzz0X1113Ha39HCImeS4SiZzK15iGPJmtViutyTKCIDA0NISenh5UVFTQcmKFsmEomdwoKytDXl6eyxssW5XnpCXPwsIC5ufnQ2IVkJ0kwYBmKWj7u/rIwqDtK1isWbMGUqkUOp0u4G0999xzOPvss6nfP5nIU6vVGBoaojy/yKBSKpUG7ZxZ3tjWEwKBAA8//LBH/8rVIC2l9Ho9ampqIJFI/N4WyfJEOrkfNqvS7XY77b0P2E6wk+eO8Hg8l6p0rVaLpqYmAKAU6XQuZhkMBgDglOccHBwRAY/H8yluoBMyUUYQBOVvPjQ0xGohjb9jW01AFMiY7HY7xsfHaYlvvWVpacmlZSmZvIt2f3PgkACuubkZeXl5jPZfCwY8Hg+JiYlITEyk+tOQ9i6Dg4MQCoVOAiJ/kt7kQoNCocCaNWtCHtczSXZ2Nubm5gAc+s10d3cjMzPTp22YzWY0NjZCLBZj48aNTpW8bBYgiX7wvUKaDixlJ4Rkv4Fit9tZ18TXF8g+UTk5Obj44otx8cUXw2Kx4LvvvvO5f6O3XHPNNaiuroZCocC3336LW2+9FRMTE3jsscdo20f4fiPLCPaNicfj0Z6UttlsaGtrg0ajwZYtW2jzBwpFctput6Orqwvj4+Oorq5e4YHsyHKfPDZAlhwmJyejt7cXn3/+OVWylpqaCoVCEZRV8YdOWYszn/+R8f0AgIAHXFifF5R9BRMej4fPPvsM9fX1Ln8Hp5xyCv71r395ta2MjAynwMMxkVdSUgKj0UgFlWQnajKoZPqcWe13np6ejrVr1+LII4/EOeecg6ysLL/3ZbVaoVKpYLfbsWXLFkbU9su9z9kaFBIEEdGBviuYtm3xBW9U6WQyPTEx0e/vSq/XQywWs7rsmoODg4PtzM7OQqVSITk5GZWVldS9JJRCn9Xwt4LXGwGRv/D5fMzMzGDv3r20bdNb3n33XZx44olOj/F4PBiNRio+COeEcSCMjY2hs7MTa9asCSjOZisxMTHIzs5GdnY27HY7ZmdnMTMzg+7ubphMJqrpaGpqqldNf8nrQSQsNHhienoahYXOAjW73Y6SkhI8//zzOOecc7zaDmnpm5iYiMrKSqeY1pW9CzlnYoMAiWcxBG1fJAQAe8XPg75fOrDZbGFtXeSqT5RIJMLhhx/u03ZuueUWPPTQQx5f09HRgYqKClx//fXUYxs2bIBYLMZll12G3bt301LxBURQ8jwUCIVC2gI9sqSPx+Ohvr6eFhUnSbADUovFApVKBZPJ5JUHPdtsWwiCgMViQVVVFfr7nUt9EhMTcf/99yMnJwdpaWlUgEDXD3I567IScV5NJv7+/YQP7yLgTWNQR4pTY/HPS2ogjNAk4Lp16zA5OYk//OEP+Nvf/gaxWIw33ngDFRUV6OjogMlkwgcffOBxGzweb0XgsxzSs5PsRE0GlV1dXTCZTFAoFFQy3Zug0hfS09MxMeH+PFl+LvuLo+IhmKWV7jz/yKZUoQoKSeV5NBFK5bknXKnStVotNBoNWlpaQBAElUhXKBQ+Xbd1Oh3i4+Oj7rvm4ODgoAOCIDAyMoKuri6XyWS2J899GZvdbkdnZycmJiZWFRD5i1qtxo8/Bkdcs5y2tjaUl5ejvLycisESExMxNjaGr7/+mopzU1JSombBmez/MzIygk2bNkGhUIR6SIzD5/OpKr/y8nLo9XrMzMxArVaju7sbcXFxlE+6q/5QU1NTaGtrQ1lZGXJyckJ0FMxz/vnnexRpXXzxxV4lz3U6HRobG5GamoqKigqP8ai7/lJkQj0UAiRj/Q2I/+Q6RvexYp9bg7s/Ogknz3NX6HQ6Wqp1b7jhBlx44YUeX1NUVOTy8a1bt8JqtWJwcNBts2tf4ZLnAUBXoKfVaqFSqWgv6SMJZnKavLDHx8ejrq7Oq3ITNtm2kAm5iooKjI+Pr3h+YWEBV199NQDg0ksvRVVVFSQSCbKyspCeng6RSIT09HRam9bevrMClx1RiBv/2Ybvh+exukbfu+RORVoc3rp8a6DDCxvi4+Nxxx134I477gDwP/W0yWTCSy+9RCW+Z2dnV7yXx+PhuOOOWzV57ohAIKAmDwRBUEHl1NQUurq6EB8fTz0fSNPRmZkZ5Ofne3zNRRdd5Ne2l7O0tIQff/wRMplsheIhmLApKIxG5Tlbk+fLEYvFyMjIQEZGBuXbqdFoKGVYfHy8k1e6p2Mik+ccHBwckUAwbVtsNhs6OjowPT2NzZs3u0wssjl57ss8xWw2o6mpyWsBkb989dVXjGzXW9566y0UFBTgzDPPhN1upypzSX/swcFBtLW1ISkpiXqOqc8i1JCV4wsLC6itrY3aWCE+Ph7x8fHIz8+HxWKBVquFWq122R9qamoKPT09WL9+PVJTQ+OFHQy8PRemp6eRlpbm9vn5+XkolUrk5ub6pdB3J0ByrOglX0daUdId5xPrzwCYSJ4vv485fDa2tafQv78gES5zLXfo9Xpa+kSR9w9/UKlU4PP5Hn9bvsIlzwMg0EDPUYVRXl6O3NxcRlRtwWoYSt4gc3NzUVZW5vWxODa9CaWqj7yRaLVal4nz5Tz77LMrHpNIJMjNzcVxxx2H6upqpKSkoKqqKuCmlSnSGLx4YTX17309M7j81Ra/t/f+lbUoTI7O4A4ATCYTlEolRCIRtmzZQiljRkdHodVqceGFF+Lzzz8HcGiCeeyxx7r8vr2Fx+NBKpVCKpWioKAAFosFGo0GMzMzlE9zcnKyX0qd1RLnxx9/PB5//HG/x06yuLiIxsZGpKeno7y8nFUK3FAGhdGmPCc/33BTQzj6dhYWFrpUpcvlciqZvlyVTpYfRtN3zcHBwREopL85ANTX17utuhMIBLBYLMEcmtd4O98j46SEhASvBUT+YLPZYDKZGNm2LwwODmJiYgLp6elUTOVoZbi0tAS1Wo2ZmRn09PQgLi6OqtgNRDTCJsjFEoIgUFtbG9Y2C3RCisnS09NX9IdqbW0Fj8dDdnY2JBJJyOf/TPDWW2/hF7/4hdev95Q812g0aGpqQklJCfLyArdXdSdAcrR6AZip5DWvOw/i1r/Tsq1DakIXC8AEAfB4h55RuFYkhwPh2jCUxGAwBHXBdP/+/fjuu+9w5JFHIiEhAfv378d1112H888/nzYrbCCCkuehuOgGkjwnuyR7UmHQBZ/Ph9lsZmz7BEFgcHAQvb29qKys9NnjzbH5Yii+R7LkkEyyffvtt35vy2g0oqenh0pW8ng8lJSU4LrrrsPZZ59Nm73LttIUtN91JF470I/ffTLk9FyCmIdFs2s1UW2eDPedWIFcRWSqP7xBr9ejsbERcrncZaWHQqHAO++8g97eXgwMDKC4uNhtOZC/iEQiJ0Xs/Pw8ZmZmVjQdTU1N9Ziw80bR8NJLLwX8u5qbm4NSqUR+fj4KCwtZHeQGOygMd2WArzguRIQz7lTp4+PjVGWITCbDwMAAjjzySOj1+qCryQoKCjA05Hx93717N2655ZagjoODg4PDH8jK2tTUVKxdu9bjoqtAIIDRaAzi6LzHG+X59PQ0mpubkZ+fj5KSEkbjJDbdfz/99FO3ScLY2Fjk5eUhLy8PVqsVGo2GEloBcFIih6O9i16vh1KpREJCAtatWxd2ooJgQVrqJSQkwGg0wmw2IycnBwsLCzh48CDEYnHQ+kN5Q19fH4444gjMz88DACoqKvDtt996PYf3J1Zcu3aty8enpqbQ2tqKtWvX+txY1Fs8CZBcVfKSf/cHW+UpQOurAOgQdXqonCII6E/7Jw37CB3hbNtCVtzToTz3lpiYGLz22mu45557YDKZUFhYiOuuu87JB50OIiZ5Hgr8TZ47dpn3pMKgCyaV545NTmtrayGTyXzehuMFO9gBoWPSHDi0SrZaUwJft9/T04Pbb78dJpMJVVVVVFJUKpUGFFzrdDpkW8bwxqmpKK9YA4sdiBUdSgba7HY8980QlKMLOK4yDSdtZOaGG27Mzc1BpVIhOzt71clNSUkJSkpKGB8Tj8dDUlISkpKSnJqOqtVq9Pf3uw0qX375Za+2r9VqAwq41Go1WlpaUFpaitzcXL+3EyqYDgqjzbYlUpLnjixXpZPlxkqlEpdeeiksFgsqKythtVoxNjbGWJd4V/zud7/DJZdcQv07mIEoBwdH5MJkcpcgCAwPD6O7u9vrylo227Z4GhtBEOjv70d/fz/Wr1+PjIwMxsfDJgGDXq/36nVCodBJiTw/P0/Fua2trZDL5ZQ/djjYu8zOzqKpqcmr+QTHIavM5uZmmM1mbN26lUpEO/aH6uzshNlshkKhoM4FOnvAecMzzzyzItnW2dkJhUKBkZERj2LH008/HR9++KFf+3UVU4+OjqK7uxsbNmwImrXNagKkQPtL2bK3wvSTexDz5T2gJ4HuHl683AurW/YS7spzvV5Pi+e5t1RXV+PAgQOM74dLngeAP4Geuy7zTMJUQLq8FNPfG5zjBTqYODYcBICrrroKf/3rXxnZ1+zsLN5++20cf/zxUKvVGBgYgFgspoIDhULh0wVyZmYGLS0tTt3JHTUbAj4fl2/z3p87GpienkZrayvrk8Dumo46BpUpKSm47LLLvNpeIKVK4+Pj6OjowLp165Cenu73dtgCE0FhtNm2kPeScA7oVoMsNz722GMxMDCA/fv349lnn8W+ffuQn5+PyspK7Ny5Ezt37kRDQwOjirmEhISgJGM4ODg46MBms6G9vR1qtRpbtmzxOgZhc/LcXe8om82GlpYWzM3NYevWrUhMTAzamI444gh8/fXXQdufOwoKCnx+j6NopLS0FAaDwWWjSdLehW0x1sTEBNrb21FeXh7RjS7pYrlVpqOdkWN/KMemoxMTE1RvGsemo0yeC9deey2ee+45t8/n5ua6XSy6+uqr/U6cu9rmwMAABgcHsWnTJlotJ3xluQDJ8Y9f/aV4PFg2/wrWkh2IfX47+GDOqouQ+eaEwDbCWXkOICQVu8EgYpLn4WDbMjIygs7OTpSWliI/Pz9oY2aiIef8/DwaGxtpWQRwvCgHC0f1KZ/Px759+xhLnJN8+eWXlPqcTIqq1Wq0t7fDarUiOTmZChA8eeaNjIygu7ub0RKuSGN4eBi9vb1Yt24drU0jmMZdUDk5Oen1Nvxd1BoaGkJfXx+qqqqQnJzs1zbYDh1BYTQqz8mFhWhAIBDg8MMPx8GDByEUCvHMM89g7969+PDDD3HWWWfBYDBg79692LqVmebLDz74IO677z7k5eXh3HPPxXXXXceYjy4HBwdHICwtLUGpVILH46GhocGn+IPNyXOBQLDC/pI8VoFAgPr6etpsGb1l/fr1rEie/+QnPwl4G3FxcZS9i2NPIJVKBQBUxW5ycnJI738EQWBgYABDQ0PYuHEjUlJSQjaWcIG0tklKSnJplemIq/5QMzMzK84FJqx+vE3yuaqSJwgCL7zwgl/7XZ44JyvWJyYmsGXLFlZVG7qq5CXnTL4KkAhZHkzHP47Y93/NyFiXLAQQE7zFTCYIZ+W5zWaD0WgMqvI8WETUDCyYneMB7wM9u92Ojo4OTE5Oorq6OuiJKLoD0omJCbS2tqKkpAQFBQUBJ1HIBn7BSp47XuDJi/tJJ50UlH2fdtppVLBNBgAVFRXQ6XRQq9UYGRlBe3s7EhMTKdUF6XlNEAS6u7sxMTGBzZs3B9yENBogg5Dx8XFUV1eH9We2PKj0hrGxMZ/3QxAEent7MTY2hs2bN/tlxRSO+BsURpvyPNo83kl0Oh2kUikUCgXOOussnHXWWbDb7VCpVCgvL2dkn9dccw2qq6uhUCjw7bff4tZbb8XExAQee+wxRvbHwcHB4S+kv3laWtqqSTJXsDl5vlx5Pjs7C6VSifT0dKxZsyYk90Q+n4+4uDgYDIag75vkF7/4Be22Go49gex2O2Xv0tfXh5aWFqr6MjU1lXHbU0fIubxGo2FdUpOtzM/PQ6lU+m1tIxKJkJmZiczMTOpcmJmZwcDAAFpbW5GUlESdC3FxcX7H4r6oY3/88UfU1NQ4PfbHP/7R533ec889+O1vf+v0GHmOabVabNmyhbWqXaPRiN7eXqjVarz99tt47bXXsLi4iIaGBvztb3+DXC73SoBkKzsO5vZjIB74mNbxWe1AyiM6TN1K62aDTjgrz3U6HYDItJqMqOR5sBEIBFRCxR0mkwkqlQpWqxX19fUh8XFzV27oK2Qicnh4GFVVVbT6bzGhjl+OY2NQUi1K3mgtFubKhhzp6emB1Wp1Uk7weDwkJCQgISEBRUVFMJlMVHf6/v5+xMTEIDk5GYuLizCbzaitrQ0LP8BQY7fb0dbWhvn5edTU1LA2CPGXY489Fh999JHb56+88krMzc1BKBR6bDrqiN1uR2dnJzQaTUR+Zt7iyt7FnSrdarVGVTI5WpPnrsoP+Xw+qqurfdrOLbfcsmpfjY6ODlRUVDj5bm7YsAFisRiXXXYZdu/eHXSVIwcHR2RB16IvQRAYGhpCT0+P1/7mrmBz8tyxdxRZRVxeXo68vLyQjYnP5yM1NXVFU+lgcMkllwTFSoLP50Mul0Mul6OsrAwGgwFqtRrT09Po7u6mLD1SU1ORmJjImJDBYrGgubkZFosFtbW1QffhDkfIfkklJSW0/E4cz4XS0lIsLS1RqvS+vj7ExMRQiXS5XO51nHrEEUf4NI7p6ekVj+3fv9+nbczOzq6oMLfZbGhtbYVer0dNTQ2rzjG73Y5///vfbhsDk3z77bdUr7Cqqip8/vnnAOBBgCSE+eRnYR37AcKmv4M3PwjhZCO8/hXzeCDsBDQGO0bmbeDxgOs/NuPLYTsWFhb8PVzWEM7Kc7KiglOeczjhqozPEdLaRKFQhLQLNx0NQ8lGHzqdDnV1dbT/GJhOni9vDBpK24HJyUmPHnkxMTFOntdTU1Po7u6mknQ9PT1e2btEMxaLBU1NTbDZbKitrY3Iz+nNN990m9w+8sgjcfXVV1NBpaO/vlwud3ktYnPgFmo8NR2dnZ0Fn8+H2Wz2u4FOOGGz2cJWCREIBoOBFu/xG264ARdeeKHH1xQVFbl8fOvWrbBarRgcHGRM7c7BwcHhLTabDW1tbZQaN5CEKpuT53w+H1arFe3t7VT1p6fGgcEak1wux8zMjNdNO+mgrKwsZB7McXFxyM/PR35+PmXvolar0djYCD6f72TvQlecQtrzxMbGrvDr5nAN2eiysrKSsX5JsbGxyM3NRW5uLmw2G7RaLdRqNdra2igrVLLC253YgCAINDY2+rTfTZs2rXhs+/bt+Ne//uXV+139Vq1WKzVnrampYbSPjq888MADuP/++31+n0qlQnZ2NmZmZijREZmLWaFKz66BPfeQ9aHJOI+4p7aAjyWX2yX9JeyyYhh//n8gZDkYGp7GGWecgaKiIrzd8q+IqAYmP6twnW8ZDAbExMRE5PUy8o4oiHgK9MbGxtDe3k6btUkgBKo8NxgMaGxsRExMDOrr6xm5qDOZPF/eGNRVUqu0tBQ9PT2M7N8RmUzmU1LSYDCgt7cXqampqKiogF6vh1qtxvDwMNrb2yGTyahg0Vt1caRDNrKVSCTYtGlT2N54vEGv1+P+++/HAw88QD22sLBAHbNjUDkzM4OOjg6YzWanoFIikcBqtUKlUsFut7MucGMb5PWDx+NRiw0bN26kFin9aqATRnDK88AgVXL+oFKpwOfzw6pvAwcHR2RCJhX5fD7q6+sDXnBnc/KcIAgsLCzAbDaHrIp4OeRC/a9//Wu8+OKLUKvVQdkvW5SEy+1d5ubmoFar0dPTg5aWFsjlcup+6++5OT8/D5VKhfT0dJSXl3NzrFUgCAL9/f0YHh4OaqNLgUBAfdcEQVBWqGNjY+jo6IBUKqUERI4VCqS1hC9kZa1sQnnRRRfh2muv9fi+3/3ud7jhhhtWPG42m6FUKiEUClFdXc2aZKPdbg/YcmNpaQnffPMNDj/8cLcCpBXCRpEUuuu6EP/H9RCY5p22Z+Anwvqb1hVzkPJyOZqbmwMaK9tw/EzCEZ1OF7F5KXb8QmmCDZ7ndrsdXV1dGB8fx6ZNm1jRTCQQ5blGo4FKpUJWVhbKy8sZ+xEzlTx3VJx7Upt/9tlnQSm/PPfcc70+J8iSt8LCQmoBJjExEYmJiSguLobRaKS605P2Lo7q4nC94AbC4uIilEol5SUfDZ/B7bffjttvv93t88uDSnIBhuxkHxcXB4vFAolEgs2bN7MmcGMzNpsNLS0tMBqNqKmpoSobVg0K/9vfIZzPy2hOngczabB//3589913OPLII5GQkID9+/fjuuuuw/nnnx8y1R8HB0fkEMiklpwbpKen++Vv7gq2Js8XFxfR29sLAKirq2NNjOT4mV988cUwGo14/PHHGbfAXL9+PaPb9wc+nw+FQgGFQoHy8nIqzp2cnERXVxekUiklNPLW3mV6eprq7xVKe55wgbR9nJmZQU1NTcgWWZZboZrNZsreZXh4mKpQSElJ8bmn00svveTycT6fj3379mHbtm0unz948CAqKytXPG40GvHjjz8iISEB69atY1VsvXXrVlq284tf/AIDAwPUv13ZYpJzJjJnAwALl6kgWBxDzL7/BwglWKy7Gd829+DICEzGuoL8HMJVAEgmzyMRdkQAYYpQKHQK9MxmM1QqFauUCYD/Aenw8DC6urqwZs0ajzYjdECXL7sjjkms1WxakpOT8eWXX9LSNd4da9eudfKw9cTw8DB6e3uxdu1at1YBEonEyd6FLFlrbW2F3W5HcnIylUyPBiWxVqtFU1MT8vPzUVhYGNrVToMGvLlhID4VhIzZ344vODYdLSwsxMLCAhobGyEQCGAwGPDNN98w1sk+UrDZbFCpVLDZbNi8ebPTZ+RtUBjO9i7RattCNgwNFjExMXjttddwzz33wGQyobCwENddd53X9xAODg4OunH0N6+oqEBubi5t2yaFPgRBsEatNjU1hebmZqSlpWFhYYE1iXMATkpO4NCc4JRTTsGbb77J2D5jYmIYs+Ggk/j4eMTHx6OgoAAWi4USGpH2LqSgRKFQrIhnyHO8v78f69at4yq9vMBms6G5uRlGo5F1nvBisRhZWVnIysqiKhRIS0tfmu1edtllOPXUU90+v3nzZiwuLuKVV17Bvn37cOSRR+Kcc85x+3q9Xo/GxkYkJydjzZo1rLnmAcD4+Dja29tp2ZYrj3hHPNliWqVZsB53qBmr2WgMqeVusCFzYuE2RyQhBUeR+H2xJwoIQxyT0mQSSiaTsarsBvBd1U12e56amgrYw9Bb+Hw+rVUDjqpPby+2NTU1GB4exqmnnooffviBtrEAh0r1v/rqq1UXVAiCQFdXFyYnJ1FdXY2kpCSvtr9cXbywsICZmRkMDQ2hra0NMpmMej4SVwInJibQ3t6ONWvWuCypCwiDBry2t8E3zYI/NwC+uhOEWQ97UiFs68+CoOllCEe/A0HYYU+uBF/TDPJWRwCwJ1fAfM4/gbhkescVIKRKPyMjA+Xl5SAIwm0n+5SUlIgtv/IFi8VClal7c533FBSGq71LtCrPDQZDUJPn1dXVOHDgQND2x8HBweEJsi+KVqtlZG5AJjFtNlvI51AEQaCvrw8DAwNYv349RCIRWltbQzqm5SxPngNgVCEtFovxq1/9irHtM4VIJEJmZiYyMzOpPjUzMzPo6uqCyWSCQqFw6iPV1dWF6elpbN682WdlcjRCCgf5fD62bNnCatGNY4UC2YDWG66//nrcd999Xm3//PPPx/nnn+/xdfPz81AqlcjJyUFxcTHr5lYdHR20bcuXnIMnAZJWq4VQKIya/lK+5K/YiMFgYI2ImG7Yk+GlgWCfYGTyfHx8HG1tbSgqKkJRURHrTnRynN6oOUjvLavVivr6esTGxgZljHTZthAEQSWoyO368n0kJyfjq6++glqtxo4dO9Df3x/QuHg8HuLi4nDjjTeuehGxWq1oaWnB0tISamtr/b7o8Hg8yGQyyGQyyt5FrVZTK+0SiYQqX0xKSgrrGw9BEBgcHMTAwAA2btxIr02STo2YZ7aCb3PdtEQwPwjR0BfUv3kA+BpnzzUeAIGmE+LntsN8TQvgx7XBZrNhfn4eCQkJtAWls7OzUKlUTip9Ho/nVSd7T01HIxmz2Uz1ftiwYYPPx7+aKt11J3r2/TajNXlOl+c5BwcHBxvwJTY2GAxUgowOf3NXsCV5Tsbi8/Pz2Lp1KxITEzE3N8e4HYqvkHGb47gkEgntFqZbtmxBSUkJcnNzWTe/9RU+n4/k5GQkJyejrKxshY2hQCAAj8dDZWUlEhMTQz1c1rO0tITGxkYkJCSgsrIy7OYF3s6z6az4I6uki4qKkJ+fT9t26YS0oqSD3/72t36/lxQVDQ8PY2hoiJp7hbMAyVtsNltYH0+wq3WDSUQlz4MNn8/H0tIS2tvbUVVV5XcTMKZxVCd4urEtLi6isbERiYmJQfc+psO2xZvGoN5CKsXvvPNOvPDCCz6/Pz4+HhKJBEKhEIcddtiqag2j0QiVSgWRSER7w0aJROLUkZzsTt/S0gK73U4lRMPN3oVU6ZMVErQGulYjJH/cDB4stGxOYNKAN/Y9iJxar99jt9vxxBNP4IknnsDCwgIUCgUuuugiXHfddQEFNuR3X1ZW5tGOyVUne7LpqMVigUKhcGo6GskYjUY0NjZCKpXS5ku4XJXu+IfNQWE02raQvQICbZ7EwcHBEW6Q/uYZGRlYs2YNo72PeDxeSH3PyWSgUChEQ0MDFWux1Y/d1dzp0ksvxTPPPEPL9i+++GIoFApatsU2HG0MMzMz0djYCOBQQrWlpQVCoZASGrmyd4l2FhYWqOrVsrKysF1YWe23vW7dOvzwww+QyWTU+eCvHQXpo19RUUF/lTSNbNy4kbZtPfLIIwEl0AcGBjA4OOhUCeJohRluAiRvWS1nx3YiWXDEJc/9xGw2o6enBzabDYcffjirTxBHpaO7HyLp61dYWBiSEqJAlefeNgb1haSkJHz//fc+vUcmk+EnP/kJlpaWIBKJcNRRR+HMM8/0uLq9sLAAlUpF+Z4xebEXCARIS0tDWloaZe+iVqsxODiItrY2JCUlUeWLbD6nyYaNBoMBtbW19FVIEASEn94FkfJ5erbngODrx2E95+9ev3779u1UMA8AY2Nj2L17NyYnJ/GHP/zBrzGMj4+jo6MD69atg1j8/9k77/C2yrv93/LeliVbHvGMHTvelmwnBEIJKwQCBQoUymiBMloKpT8oFN7SRVtKF7SUkhdKoVBe4GUGAi0zCYQVEkvytuMRj3hp2JasPc75/ZH3OZUc2dY4ko6k87mu9Cq2dM4j+ejoee7n+73vJPz0pz9FV1cXzj//fFx//fUrXnuekuw1Gg2mp6cxMDDgVxhTpGA2m9HR0YGcnBzU1dUF5bV5snfh6qQwVivPTSYTp++JPDw8PGxCOvuGh4dDkn0EhFeknp+fZzYJlgfOs9UdyzaexiUSifDDH/4QL7/8MsbHxwEcLwjKzMzE6OioV8fNy8vD1772tZiwLSEWhq5rMGLvolarMTAwAJvN5pYjlZycHO5hhxWtVutWPR3Jc/6DBw+ira3N4+8yMjLw4IMP4uSTT2Y6ccfGxvzaWJmamsLg4GBE+OhnZWXhT3/6E37wgx8EfCyj0ejX84h11rFjx9DW1uZWvLJSJy9ZO3G5AMlbIr3yPJrXTFElnofq5k0qtFNTUyEQCDh/cZAPn9PpPKGymKZpjI6OYnR0FI2NjSuGUwabQCamvgSD+sJHH32E7u5urx9fWFiIa6+9FnfddRdTrbLWWEgVcDgmIK72LlVVVYxNh1qtxtDQEFJTUxnBNDs7mzM3ceKvJxAIWK/ST3j3v5DY9Q/Wjud27Mm9cFgNQPLqbUwajQannXYaxsbGTvid3W7HE088gTvuuMOnoK6jR4/iRz/6Ed5//33YbLYTfv/+++/j9ttvx5/+9CfceOONqx7LNcm+oqICNpuN6WaQy+UQCARuk8pI6mZYjtFoREdHByQSCWpqakLy+eT6pDBWxXMSfsPDw8MTDaz2febqb97e3u51/k6ghEs8n5ycxMDAAGpqajz6hpM1CpfCTIGV106JiYm48sorPT6HoigYjUa8/fbbmJubQ2FhIXbs2MH5tWwwIGuwiooKlJeXM39bV3uXmpoapmBkamoK/f39yMzMZNZH0RqKtxKkCKeurg6FhYXhHk7A1NbWoqurC9u2bcP8/Dzz8y1btuDHP/4xTj/9dADAunXrsG7dOo+++Tk5OczGiqdiLmIv2tLSEjGdHDfeeCMoigpLSD1N0zhy5AhmZ2fR1ta25tx7pXwp10IkgBsFSN4S6ZXnvG0LD8Ps7CzzRVtYWIgDBw5wbjK1HHKjWD7BItW7i4uLjK9fuPBXPPcnGNRbLrnkEq8fe/rpp+MXv/gFpFKpVzdkmqYxMTGBkZER1NfXcyK93tWmw+FwQKvVQqPRoLOzEzRNM4KoWCwOmyBqMpmgUCgY+wxWv1ishqAJ58Bx//PUP2+A7eQfwrn1To+PsVgsqK6uhtVqXfVYV111FT7++OM1z6nVanHBBRegs7PTqzH+4Ac/QGZmJq644gqvHg8c98ZzDWMioaMjIyPo7u5mQkfz8vKQlpbG6XulK2STtKioCFVVVWEbt7eTQnL/C/akMNIndP7gcDhgsViidiLIw8PDQyDzLGJdEsoq21CL5xRFYWBgADMzM2htbV1R2PKmgzcc+Lp2IvOG5ORkXHLJJZwXkILJ5OQkhoaGUFdXt2rhmKeCEZIjNTY2hsTERLeCkWh9T0knytjYGFpaWiAWi8M9JNaorKzE5OQkgONFSmS+52nev9w332QyQa1WY25uDoODg0hPT2csLbOysjA6OoqpqSm0trZGnI/+zTffjJtvvhmHDh3CQw89BJqmUVNTA6fTyRQtPvroo6yek6ZpDAwMQKPRoL293ef8N28LkFzXS1z8zEZ6oRJv28IDmqYxNDSEiYkJNDc3QyKRMAIX1yZTnlg+ITWbzVAoFIiPj3fz9QsX/kwAAwkGXYs33ngDZrPnoMjl1NbW4rXXXvP6PaQoivNp7gkJCcjPz0d+fj5omoZOp4NarcbRo0fR09ODnJwcN0E0FOh0OqalNhj+enFz3ncZBELSZ3+A3W6D4/R7T/jdAw88sKZwDgAdHR2w2+2rbmLQNI3zzjsPPT09Po3v5ptvxoUXXuiXFU5cXJzH0FG1Ws2EjpLqjJycHM5ODHQ6HeRyOcrLy1FRURHu4TCsNSkMRXVFuMPcwoHBYAAA3vOch4cnqlgeLkkKJgoLC0+wLgkFoRTPSRej3W7Hli1bVp3Lunbwcmm958vaKVhdusFgZmYGS0tLWL9+PevzDbKen56ehkwm87mrIikpialCdjqdjL0LyQMSi8XM+ijca2u2WJ4xFc1zocTERK8LxIj7QHp6OsrLy2G3290KzxwOBwQCASorK9mzFw0D7e3teOGFFzz+7vTTT/ep2HA1KIpCX18fFhcX0dbWxsp7tlIBkmvxJXlcKAqQvCXSbVuMRiPWrVsX7mEEhahaAQdrImC329HZ2QmTyYSTTjqJqT5zTYbn0mTKE64TrIWFBSgUCkgkEtTV1XHiw0nSk71heTAoudmxxZdffokbbrjB68fPzs7i888/x2mnnbbmYx0OB7q6umCxWFb06h4bG0N3dzcMBgMoioLZbMbGjRshlUrDsosnEAggFAohFAoZQVStVjP2LmlpaYwgKhQKg/I51Gg06OrqQmVlZXDSyW0mJL74dfaPuwKJhx6Bo+4iIL/W7ed//OMfvT6GXC7H5s2bV/z9wYMHfRbOgePX6HvvvYcLL7zQ5+cux1PoqFqtRm9vLxwOB7PI4JKHJPE9raqq8ti+7QvHRW0L4uKSIRD85z57fMJmRFxcCuLi/O/iWG1SuNzeha1JYaRXQ/iDyWQCAL7ynIeHJyoJh7+5J0IlnpPOsqysLMhksjUFWtcNay7hrXjOdeF8bm4Ob731Fn77299iamrqhN+feeaZeOqpp5CbmxvQeYgdkcFgwKZNmwIu/omPj2fmsCQPSK1W49ixY+jv70dWVhZj75Kens65990blr9nkSwCB5vExEQUFBRAIpGgq6sLS0tLyMvLw8zMDIaHh91CRyP1eljOOeecs+rvf/Ob33h1HIqimOusvb09KGvClQqQXLOmAG7Yu0RCYe5q8J7nMYzBYIBcLkd6ejq2bNnithvpKp5zHTIhJV/o1dXVKC0t5cyNmysTQIPBgOuvv54RS7xBp9Ph9ddfX1M8N5vNUCqVSE5OZry6aZqGUqnEkSNHMDY2hl27dkGtVq94jLS0NFx99dX47W9/u2ZFg1wux3e/+10MDQ0hKSkJO3bswP3334+ioiKYzWakp6f79aWQmpqK0tJSlJaWMvYuarWasQZxtXdho2JkamoKAwMDqK+vD5onf/J/b0IcHEE59kqkPnMGLNd/DDp3AwD4/CVDQiQ9YbfbsWfPHr/HduWVV2J+fp7VyYun0FG1Ws14SGZkZDCbMOEKHSWbNDU1NX7vmGs0+zE0fA8A70Jy4uLEqKvbhcyM2rUfvOpxQjMpjPQJnT8YjUakpKTE3Ovm4eGJfhwOB3p6erC4uIhNmzaFtRsyFOL53Nwcurq6UFFRgcrKSq/mGmTzmWvrvbXWTsHu0mWDXbt24Yc//OGqj/nwww9RVlaGt99+G9u2bfPrPFarFUqlEnFxcWhvb2e9KtzV3mX9+vWwWq2Mvcvo6CiSkpKYOTCXOy9dsdvtUCqVoGk6KO9ZNOJwOJiq882bNzPvmcViYTpxXa8H0okbqfNLgUCAw4cPewxdbWxsxG233bbmMZxOJ7q6umC1WtHW1hay68yXAqRQ27tEQ+V5tHao8OL5KpAJVllZGTZs2HDChEMgEIQ1Gd4XBAIBxsbGsLCwAJlMxjmvMk+e7MsJlnA+ODiIzz77DHq9HkqlEkePHvXp+TRN49ChQ7DZbCve8InlSF5eHtMKu7CwgO985zs4cOAAdDqdV+cymUx44okn8MQTT+Djjz9Ga2vrCY8xGo0488wz3cJOrVYrXn75Zbz66quorq5GQUEBCgoKcN555+Giiy7CwsICgONf+jk5ObBarUhMTFyzwmAlexfid01CVPLy8nyuViBhthMTE5BKpcELWTFpEWfRBufYa5D8Pxdg9ltf+CXUbtq0yePPrVYrFAoFYzXhLyKRCIuLi0Hxt1++yLDZbEyS/cTEBOLi4phqHrY2YdZibm4OPT09fm/SUJQVB7/cDmB+zce6P0+Lnp7jXQ9Nje8hPf0/AUyB5GkEa1IY6RM6fzAYDFFTJcTDw8NDMJvNOHz4MBITE7Fly5awd4DFx8evWhgQCDRNY2RkBEePHkVTU5PPWUO+dMiGitXEc092blz7Dnv88cfXFM5d2blzJ372s5/h7rvv9uk8BoMBCoUCQqEQ9fX1fs1hjEYjxsbGIBKJvArKTE5ORnFxMYqLi1fsvCTiKRdFaWLvmpaWhsbGxogVd0OJzWZj8iJaW1vd1i4pKSknXA8ajQb9/f2w2WxunbgpKSmsjMdut+PnP/85nnjiCdhsNlRWVuKhhx5ipevCldraWhgMBjz00EN4/PHHUV5ejldeecUrj3en0wmlUgmn04nW1tawZaq5FiC5bjqS9RP5XgpVVXqkFyqRdVM0ElXiOVuTApqmMTw8jLGxMTQ2Nq4qpESCeG6322G1WkFR1Jq+fuEiPj4edrt9xd8HKxj0zTffxEMPPYRjx45hcXHRa59zV2iahtlsht1u9zgBUqlU6Onpwfr161FWVsaM/dRTT/VZqHflK1/5Cr744gs0NjYyP3vppZdw3XXXrfgcEo40MDAAAHjxxRd9OqdMJsM//vEPVFZWnvC75fYuJpOJ2WU/cuQIY++Sl5eH7OzsVf+GFEWhv78f8/PzaG9vD6pdQpxmKGjHXguBRYeyEt+F87y8PI8TDJPJBLlcjpSUFLz11lsBj08oFGJsbAx5eXkBH2s1kpKSUFRUhKKiIlAUhcXFRbfQUeKxn5ubG5Qv4+npaQwMDKCpqcnv19rV9V34KpyfcIzu7R5/Xl72UxQWXub3cV0nhWQh7e+kMBZtW6J5EsjDwxObkM5HsViMmpoaTtzXgyVQOxwOdHd3Q6/X46STTvKrIo6L672VxPPl9pZc+Nsu57PPPsMdd9zh8/N+8Ytf4MEHH8Rzzz2H7du3r1lcMT8/j87OTpSUlHjdaeCK0+nEz372Mzz88MMn/C4pKQmNjY34n//5H5SUlKx4jOWdl0tLS1Cr1ZiYmEBfXx/n7DyWlpagUCiQm5sbluyDSMRisTBOBY2Njau+Z8uvB6PRCLVajZmZGQwMDCAjI4O5HnztxH3++edx4403evzd4OAgdu7cCQAoKCjAwYMHA7ZCIggEAtx555248847vX6Ow+GAQqGAQCDwaJ81MTGBV199Ffv374fJZMJpp52Ge++9N+ii8nKbS1cNKlRV6ZFeqGQymfjK81iBeFIvLS15NcHi4mTKFWI7QwIruCicA6tPAIPRckhRFH7729/iV7/6VcDHAoDS0tIT3luapjE+Po7R0VE0NDQgOzsb//znP/GXv/wFfX19rJx3x44dOHjwIF555RU8+eSTAYnx3iCXy9HU1MT89ze/+U2cffbZaGxsRFVVldvfJi0tjbF3cQ1RUSqVAFa2dyGfQavVivb2dtZ24FeCEgbBQ90biGe/H08dGxs74WfEwzM/Px+/+93vMDs7G9j4/o/y8nJ8+eWXqK+vZ+V4axEXFweRSASRSMQk2ZOq9KGhIaSmpjJCOhutr5OTkxgaGkJzc7PfHTl6vRJmy6GAxrEaY+P3w2KZRkXF7QEfi7xf/k4KI70awh+Id1+4F7Q8PDw8bCEQCNDe3s6p+3kw1lQmkwkKhYKprve3yteXcM5Q4WlMXPc3B46P8eyzz/b7+VarFZdddhmam5tx2223ob6+HtXV1eju7obFYkFdXR3EYjGmp6fR39+P2tpaFBUVrXpMu92O73znO9i9ezcsFotX47DZbOjo6MDGjRsBAHq9fs3Pk0AgQFZWFrKyslBZWXmCnUdycjIjrAqFwpALaGSzoaysDBUVFZy8friG0WiEXC6HSCRCXV2dT++ZQCBARkYGMjIyUFFRAZvNxqyXiX5D1ssikWjFymyappGVleX1PWp2dpbJEGPbptMb7HY75HI5EhMT0dzcfMLnpre3FzfffDMUCgXzs88++4zxUL/yyitx7733Yv369UEfq6dOXrJmClZVeqSvtYxGI2c1x0DhxXMXSFtXSkqK1xMsLovnxIe6pKQEOp2O01+AK00A2W45pGkan3/+Oa666iqoVKqAjkUQCAT43ve+5zY2UuE9MzOD6elpPPPMM3jnnXcCttJYzuLiImpqalg9pi88++yzePbZZwEcb0k7//zzcccdd6Curg46nQ6ZmZlITk5mQlQKCgpAUdQJ9i4ikQi5ubnIzs5Gf38/EhMT0d7eHhK7DmQVgoZ/Irbf/J9wbncCdh/XYkbjiV7aCwsLUCqVKC8vh8lkwgcffMDGKBk2bdqEzz//3G3jJFS4bsI4HA6m1ZGN0NGxsTEcPXoUMpkMQqHQr/FZLJMYHrnfr+f6wuzckygruyWggFFP+DopjPRqCH8wGo185TkPD0/UkZSUxKk1DNu2LfPz81AoFCgsLAy4gpaL673llfqRIJwDYCWQHgA6Oztxww03ePzdunXrcPnll+P73//+mh2FdrsdGzduDLjoJCsry+McfTWW23kQ4bS7uxsURbnZuwTb0mJ2dha9vb3YuHGj37k/sYZer4dcLse6detOKCLzh6SkJBQWFqKwsJBZL7t24gqFQuZ6cJ2XnnPOOX5v7rnaohoMhqDfN8imU2pqKpqamk64L9M0jUcffdRNOF/O888/z/xj637iDSvlS5G1E1tV6U6nM2wWNoFCuin4yvMoR6VSoaurCyUlJaiurvb6xsHFyRRN0xgbG8Pw8DDq6+tRVFQEuVzOuXG6slw8d50Asukr9eabb+KGG27wKRB0LWiaxve+9z188sknkEgksNvt6O7uhtFoxNNPP43333+fddGci1gsFrzyyit45ZVX3H5eUFCA7u5uZgcyLi4OOTk5yMnJYSqLSbva4OAgEhISIBaLYTAY1rR3YQs6MRsCu3e+84GdiPkfAMCvPvauuoXw+uuvn/AztVqN7u5uVFdXo7i4GC+++KLXHvq+sGXLFp8XBWyTkJAAiUQCiUTCtL5qNBomdDQzM5MR0ldrdSTep8eOHUNra6tXvnwrMTX9DKzW0Fj/6HRfICfn1KAdf61Joc1mg91uB0VRcDgcIQ/QCRcGgyGo1lE8PDw8PGtbOPrCxMQEBgcHsXHjxlUtNbyFy5XnpEs3GPaWbLO0tIQPP/ww6OeZmprCQw89hIceegjV1dXYvn07Lr30UrS3t5/w2J/85CesdWvu3r0bF110kV/PjY+Pd5vj6vV6qNVqjI+Po7e3F9nZ2UxVOtsb+uPj4xgZGUFzczNrVh7RDilcqqioQHl5OevHd10vb9iwAWazmelSGB4eZroUcnNz8emnn7JyTjLXJbZI5DqbmprC9PQ0cnJyMDY2BovFgpaWFhQXF/t0fIvFgo6ODmRlZa2YP/Dmm28yhXlrcdttt2Hz5s1+ZVWxwWr5Uq4FoOSe7K2mFQ2V59FadBRV4rk/EwUSSkisNbwJAXElmOE2/uB0OtHb2wutVotNmzYhOzsbADcnfa64jo/tygmHw4GXXnoJf/rTn9DX18d4ALLJ1NQUduzYgQMHDqCzsxMpKSmYmprCe++9F3bBMdzMzs6ioKAAer3e4+/T0tKQnZ2No0ePoqSkBNnZ2dBoNFAoFExwJGlXC1YluiApBQi2eL5MOD+iceKXB3xbJJ5++ulu/028uuvr65nwq8nJyaDdk3p6etDQ0BCUY/uKa+urL6GjNE3jyJEjmJubQ1tbW0CiqNE0ApXqf9l6SWtitbHTLeMtrpNCu92Onp4epKSkMK2h/k4KIw1i28LDw8PDEzzi4+O9tsxYCZKZMzc3h9bWVtbC5rlYLEW6wTx9H3OVa6+9NuTnPHLkCI4cOYJHH30U69evx7Zt23Duuedi27ZtSEtLw2uvvcbaua666iosLCwEHAIqEAiQnZ2N7OxsVFVVwWKxQK1WM127KSkpzPooEHsXmqYxNDSE6elptLa2MrrBSixYFjC8OIz0xHQUpBcgPTEdyfHhDRoOB6RwqaamJmRV+qmpqSgpKUFJSYlbl0Jvby/r57r66quZ/19eXo6EhATo9XosLi66bdI1NTXhX//6l1dVxmazGR0dHcjJyXGzt6EoCh9//DF27drlc16XVqvFgQMHcNll/udCscVKBUiuXb2Ad/Yukd7lazKZorboKKrEc+D4BemtOEoCZHQ6HTZv3uxX9SGXJlMWi4VpcdmyZYubVzSXxukJ1+oJNoRzk8mEoaEhPPLII3j99ddhtVpZHvGJDA4O4m9/+xt27NiB6upq/PWvf4154ZzgdDqxZ88eXHDBBSf8bm5uDr29vdiwYQNTHUTa1Uhw5NDQECwWC3JycpiqCza90O3N30TSZ79n7Xiecb8v/XS/bwvEP/zhD24tXMRypKWlxW1x+MQTTwQ2zFV47bXXOCOeL2el0NHh4WG30FGdTgedToe2traA/NgcDiMGBn7A3gvwgtTU8pCej+B0OtHV1QWaptHa2oqEhISAJoWRRjRXUPDw8MQuXBNZA12r2Gw2KBQKOBwObNmyBampqayNjYtFSAKBgPkeBrgZDOoKTdN45513wjoGUjD31FNP4aSTTsJPfvITmM1mVs+Rk5ODo0ePQiKRsHbMlJQURjglFoZEwKUoyi1Hylu7B4qi0NvbC51Oh02bNq06J16yLeG2fbehX99/wu9KM0rx3NnPITmBeyI6RVF4+eWX8eqrr0Kj0UAmk+Haa68NaC3jqXAp1CzvUggmY2NjjC2mzWZjfk5RFORyOSorK9Hb24vx8XHMzMygtLQUTU1Nbt8vRqMRHR0dkEgkqKmpYX5nMBiwZcsWjI6O+j2+QDdcg8VqVeme7F3I/yePj9TKc7vdDqvVytu2RBsmkwlyuRxJSUk4+eST/d4h5ooordPpIJfLIRaLUV9ff8IHjlQncBUyASQVs94K5w6HAx999BHee+89HDlyBL29vZibmwtbN8DHH3+M22+/HQKBgHOT7HDz0EMPnSCeT0xMYHh4GA0NDSdMMpcHR5I08rm5OQwODiI9PZ0R0n1NI1+Os/1G0AcfhcDJ7gR6JWga2D3o/fXx9NNP4+tf//r/Pfc/VSJSqRRyuRzvvfceFhcXYbfbMT09Haxh48UXX8RPf/rToB2fLTyFjqrVaoyNjcFmsyE1NRWTk5N+VezY7QYc7tgGIPgbcieeWxvyczocDibkVyqVMhX8gUwKIw2j0Ri1FRQ8PDw8XCGQNRXxHhYKhcwmL1fGFgxomkZ8fDympqbgdDohkUhYCVEPJuPj4+EeghtffPEFdu7cGZRjV1RUYHJykrXOB1eWWxgSX+yjR4+ip6eH8cXOy8tbURC32+3o6uqCw+HApk2bPOogSpUSf1L+Cf26EwVzVyYME9i+ezve+upbSE1IRUIcd+Sln//853j66adht9uRkJCA4eFhfPDBB3jyySfR1tbm9XGINdLk5CRGRkZOKFwKJwKBABdffLFHa0+2WK0I0Wg0YvPmzUhNTYXZbIbVaoVOp2NEfYlEgksuuQSbN2/G4cOH8cc//hHvvPMO5ufnWRlbS0sLK8cJJmtVpUdTvhSxKo7WdRN37m4hRK1Wo6urC0VFRaipqQno4kxISAj7ZGpmZgY9PT2oqqpCeXm5RxFxeagMl6BpGnFxcVhaWsLQ0BDy8vKQk5Oz6nMWFhbw/e9/n9VWOzY4ePAgDh48iMXFxTVb32IN1w0dVwHY27DG9PR0pKeno7y8HHa7nfF9k8vlbvYuYrHY993a5ExYr34DSa9/G3H6SR9fme98MGqHzYvbRk1NDeRyOfPfpB15fn4eOTk52LhxI5aWloI4UnfUanXIzsUmycnJTBtte3s7DAaDW8WOSCRifANX20ilKBsOd2wJ4cjdGTv6J2RnbUJiojAk53M4HFAoFBAIBJBKpSt+rnydFEZaVTrvec7Dw8MTfPwVqGdnZ9Hd3Y3169dj/fr1Qamo51LlOdmsrqiogFAoZKwbnE5nSAMmfeXnP/95uIcQUqqqqlgTCFdCIBBAKBRCKBSiqqoKZrMZarWa6dpNS0tj1kfZ2dmIi4tjOtWTk5P/001IUxhaHMLw4jBS41Px2vBrOKQ95PU4LLQFZ71xFtLj03Fr8624aP1FiBOwN8+7//778dBDDzGZCGKxGK+//jpaW1tXfI5CocBf//pXt8rkxMRE2Gw2PPzww3juuefWvFcYDAa88soreOedd6DValFcXAypVIq7774bc3NzuPjii/Hggw8G1MnKBs899xzy8vJYzXTzBZVKhfr6ekxPT7tVp5Pf7dq1C7t27QrKubnaEb0aywuQXP+Rym2yfoq0fCniuhCtHbsCOti9HiGGhJl5gqZpHD16FCMjI6irq2PFo6q/vx8CgQAbN24M+Fi+QgTIiYkJNDc3r5omfuTIEdhsNs7dYMgE0NW7iwh0ZNdcLBbDbDbjo48+Qm9vLx588MGQ2LD4S15eHmw2W1BCGyOZd955B6eeeiooikJPTw/0ej2kUmnAN1di0UG8AK1WK0QiETNZ9MnexWFBykOVECAICySXW23u7w2YN699662trcXhw4cBHLfO6O7uhtlsRm1tbcg89lwpKirC0FBowjHZwul0QqlUwul0QiqVui0mSegoWWgsLS0hMzOTWXhmZma6TayPTb2AyckHwvEyGGpq/gJRzragn8fhcEAulyM+Ph4tLS1+tw8unxS6TjkCSaIPJd/73vewbt06/OY3vwn3UHh4eHhYgyzUucLc3BxGRkZw8skne/V4mqYxPDyMsbExNDU1BdVCobu7G6mpqaiqqgraObzB9fvUtUvXNWBSrVbDaDS6WR2yaWHjDxaLBWKxOKxjCAfhtO90OBzQarXMHBcAsrOzodPpmE71uLg47J/cjx998SNWz31L/S34Vt23Aj7OWWedhc8//3zF33/jG9/Ak08+6fF3bW1t6O8/sWpeIBCguLgYBw8eXLXQzW6345577sHLL78Mg8Hg1iG/nN///ve45ZZb1ng1wWd8fBx1dXUhP69AIEBZWRnGxsZCet4jR46EZT0cLIiltNVqRWNjI+Lj45l1U6QUIA0ODuIrX/kKDAYDp8fpLzFTee5wONDT04PFxUW3IM1AYTMZ3hccDge6urpgMBhw0kknrVkVx8XKc9c2//j4eOTn5yM/Px80TTNi6KFDh/DDH/4QExMT4R6u10RqdW4wEQgE2Lp1K+x2Ozo7O+F0OldsE/SVlSw6ZmdnMTg4iIyMDEYMXdPeJSEFVH4T4ueUAY9rJX6x3+qVcA4A27dvB3B8AkesM9ra2vDQQw8Fa3ircuutt4blvP5C3jeBQACZTHZCG7dr6GhlZSWsViuz0BgbG0N8fDxz7YhEIszNPRemV/IfaCr43zd2ux0KhQIJCQlobm4OyHfPk72Lq5AeCVXpvG0LDw8PT/DxpfKciAx6vR4nnXRS0P1Vw21/6frdScbjOp9dHjBJKpDVajWOHDnCzIXz8vJOKAwIBc89F/75U6yRkJDgtrY+duwYBgcHkZCQgLm5OdhsNphTzPhRH7vCOQA83vs4Lqu+DGkJ/ldkf/WrX11VOAeAF154ARdffPEJ9jsff/yxR+EcOP5ZMhgMa1o7feUrX0FXV5dXY73rrruwc+dOlJWVefX4YBGu86empmJmZiak5xwbG1u1cDTSoCgK3d3dsNlsaG1tRWJi4gkFSJ5sMbm2ZjIYDEhPT+dcpgpbxIR4bjKZGCFgy5YtTOgBG7CRDO8rxK89OTkZW7Zs8aotj4tefSsFgwoEAmRmZuLHP/4xnnnmmTCOkocNkpOToVKpYLVaoVAokJKSsqoFRCAIBAI3exebzcaIoRMTE4iLi2MWDyKRyOMY7Nt/g/h/nsv62JwJ6Tj3aTU+OOrd5zA5ORm33norrFYr5HI5UlJS0NTUhPj4eNx///2sj88brr/++rCc1x9sNhtznyTv21okJyefEDqqVqsxNDQEs9mM9Izw30PT0mqCeny73Q65XI7ExMSAhfPleLJ3iYRJodFojNrgGx4eHh6u4O1axTW3asuWLawUYngztnAVIZE1E6lA9OZ7MTU1FaWlpSgtLXWzOhwfH0dCQgLy8vJC6pN+++23B/0cPCtD5rI1NTUoKSmByWTCnHoOV3x5RVDO54QTbx19C1/f8HW/j/Hhhx969bivf/3rePfdd3HKKacwGWrf+c53Vn1OZmbmqp3PP/3pT70Wzgl1dXVh7TQgVFVVYXh4mNVjSiQSUBTFdDAsJzc3N2TiebSJ5sDxLumuri7YbDbIZDJG21spX4p48HOxAMloNEatZQsQA+K5VquFUqlEYWEhNm7cyPoFFWpRmrweX/3aueLVRz7snloOXR9z2WWX4b333gvTKHn85dRTT8Uf//hHVFRUICkpidnVX1pagkKhQG5ublA+hyuRlJSEwsJCFBYWgqIoLCwsQKPRYHBwkLF3IZXFxN6FLmyBffP/Q+LBh1kbBy2Ih+37PXjuJgcKCgq8es6DDz4IoVCIQ4cOQSgUoq6uLqxfiAkJCREjIFqtVnR0dCAjIwMNDQ1+vW+uHQ01NTUwGo0YH8snO1QAAO1ZSURBVP82dPr7GQeecGyqW6wTSE0tDcqxiXCelJSE5ubmoF9vkTIpjPaJIA8PDw8X8GZNFex13UrExcWFpdN4rTWTNyQmJrrNhefn56FWq9Hb2wuHw8HYHAbLJz3UFalcYffu3eEeAgBgcnISQ0NDaGhogEQiAQCkpaXhiWNPBPW8f1T+EanxqTi3/FyfQ0R97eI+55xzAByfL8bHx69or0JYy37pj3/8o0/nJ6Snp+Odd97BySefHJQiMW/461//yrwfgVJcXIz77rsPKSkpjP/27373O4yMjAA4/j42NTXhwIEDSElJCeo9cs+ePTjjjDOCdvxw4XQ60dnZCYfD4SacL2elfCnyHcGVAiSyZuIrzyMEV++38fFxDA0Noba2FsXFxUE5XyjF84mJCQwODvr1erhQeb5WyyFw/AZy0003RaRwvtYGRXx8POLj408I0ogEcnJyUFxcjMrKSqSmpqKpqQn79u3D4cOHERcXh/Lyctx00034xje+ccKNen5+Hp2dnSgrK0NFRUXYbqZxcXEQi8UQi8Worq6G0WiEWq3GzMwMBgYG3Ftav3IXHA0XI/nvXwEbXzv2pquBxFRkJh5vZxIKhatO7OLi4nDZZZfh0KFDKCgoQHV1ddi/hLwV/cON2WxGR0cH6xsO6enpqK29FF9++TgozDE/D7WQvrBwADnCrawfl1Tqkw6HUE+4uDwpNJlMvG0LDw9P1BHuecVy1lqrkHXQxo0bUVJSEsKRhafTeLUuXX+Ji4tDbm4uU8xCcl/GxsbQ29sbFJ/0Dz74gJXjRBJ33XUXzj777LCOgaZpjIyM4NixY5DJZBAKhczvzA4z9k7vDfoYftXxK7w+8jqeOPMJnwR0fwv+XAsvVmO1DLhAP+c7duxAY2Mjnn32WVRXVwd0LH/YunUrXnvtNVx55ZU+v5bx8XHk5ua6/czpdDLFZxqNBr/73e+YbDHy2EceeQQvvvgilpaWWHsdhAcffBC33XYb68flAq7C+fJcrrVYqQDJtaOXPE4gEISsACnaC46iTjwHjl+Ivb290Gq1aG9vd/uyYJtQiNIURaG/vx9zc3Noa2tDTk6Oz8fgglefNy2H3/72t/Hyyy+HcmgBkZKSgptuuonx0KdpGmq1GiKRCAkJCaBpGnNzc0hOTkZWVpbbLrTdbscrr7zCemuVr9TU1OCyyy5DW1sbKioqUFZW5tXN+/vf/z7UajV0Oh2Kioo8Jo3PzMygr68PtbW1KCoqCsbw/UIgECAjIwMZGRmoqKiAzWY7oaU1NzcXed+SY93uixGvGz/hGP8X3wE6PhV0SiaotEIkqpUnPM6ZWwfn2b9yO7dOp0N+fj4MBsMJj09ISEB3dzeUSiXKy8tRXl5+woJpaGgIGzZsCPBd8I1gpaSzidFoREdHByQSCWpqalgXBgQCATZteh9fHjodFKX9v5+5P4amgyukO53sT0xtNhs6OjqQlpaGxsbGsLf8AdyaFBL/Ph4eHh6e4EGsUWiadvv+ZmMdFCih7uBdKRiUTZbnviz3SU9PT2eE9DUzg1YhUroWAyUxMRE/+clPcP3114flGnWFfGbm5+fR3t5+whzm3fF3QzaW3sVePN7zOL7X9D2vnxPM8F8AK1ZIm0wmdHR0BHz87u5ubN26FePj42EJ6z3nnHOg1WoxPT295nqxsbERX3zxxYq/j4+PZ4RymqZhNBqh0WgwNzeHwcFBpKen4+yzz0ZdXR1SUlJwxRVX+CTaJyUleSwsvPzyy/H3v/+dc5u8bLG84nwtD/7VWKkAyTVrCghNJ6/BYIjqgqOoE8/NZjNTDbtlyxbGiiFYeNMaFAg2mw0KhQIOhwNbtmzx+wbMBa++1SaADocDP/jBDyJKOE9MTMQPf/hDt5uPQCBw+8IXCAQoLCz0+PykpCRceeWVmJ+fx2OPPRbyv49IJMJTTz2Fs846y+8vJjKpXg5N0xgbG8PRo0fR0tICsVgc6HCDSlJSkpvX9cLCAtRqNQaODKO78n5ssPWi/OhzSLQvwZnfBPv5jwKZJ1ZiOwDEyZ9BgvIZ0ClC2M/6NSCp9XjOubk59Pf34/rrr8f4+Dg2bNiAxx9/HCKRCD09Paiurl6xwyQcGxFcb5VbWlqCXC5HUVERqqqqgjbZEggEWFd0DSaP/WmF3//n/7NdlS4QJCEjY+VqGX/gonC+nHBOCslCIVYW/zw8PDzhgtzjnU4nIyRYrVYolUo4nc6A1kFsjC0URUjEtoycK1jCuSdW8kmXy+VMgDrJDPLlO7a5uTmIo+YO7e3tuPPOO8M9DDgcDnR1dcFqtaK9vd2jFmKym0I6pteGX/NJPAeOdz0vLCywPpb4+HiP3t1kHbHSut1XjEYjcnNz8e6772LrVvY7Rr3Bm/XiunXrvD6ea/FZeXk57HY7BgcHMTs7i/T0dMTFxeGjjz6CWCzGK6+8gnvuuWfFY7322mus2ctEGmwK555YrQDJUycv+f9swFeeRxhTU1PIysoKmT9wMCdT5CaelZWF1tbWgHekwlF57lpxvtoE8J577sHTTz8d4tEFxu23387KNSYSiXD22Wfj3XdDVwUAHG/NCsZnhKZpDA4OMhVCWVlZrJ8jmLjauxCva7V6Az7PPQV6vR6ZmZnIU5uQhyVkZGSccE1Tsm/BJvuWV+eqra11S5KfmppCT0+Pmy+hJ3z1Aox2dDod5HI5ysvLUVFREfTz5eXtxJzqddhsJ3YkuMK2kJ6eVguxiL02YDa84cOBr5PCQF+XyWTy2FnDw8PDE8lwraJvuXiu1+shl8shFArR2NgYNg9hIDSV58u7dElXVThY7pNOikr6+/tht9t98kn/zW9+E6JRh5cbbrgh3ENgiu4SEhLQ1ta24t/mlKJT8OfuP4dsXAanAQ7K4ZN1y2effYbaWs8FSIGQlJR0gri3sLCAjz76CMPDw3A6nfjrX/+K733PN7F/Jc455xwMDg4GzUJ4Nby5Z73zzjtIT0+HwWDw+X5z7NgxqNVqtLe3IysrCzqdjrGBqq2txf79+5GZmYn+/n4899xzqKysxIMPPhgx641gEGzhfDlrFSCxnS9lMpl48TySqKqqCqlIHCzxfG5uDl1dXaioqEBlZWXAk6dwVJ5723I4ODgYEZYQwPEbUFVVFS699FJWb3bt7e147733mAlzsPnRj34UlC8up9OJ7u5umEwmbNq0KWwVQmyxmr3L2NgYEhMTmQVETk5OQAs710p9kUjk8TE0TePVV18N+QT9mmuuCen5fGF+fh5KpRJVVVUoLQ1OkOZykpML0FD/BIaG78fS0qdePceTvYunn69GdfXvkJTETsI8Ec4zMzNRX18fsRPZUEwK+cpzHh4enuBD7tFOpxOzs7Po7u7G+vXrsX79+rAL/cGuPGcjGDRYLC8qIT7p4+Pj6O3thVAoRF5eHiQSicd5///+7/+GYdShpaioCJdddllYx2AymSCXy5Gdnb3mvG5dxjrEIx5OhEYzEUCAOIFvc69gzenNZrNbNb5arcaLL76Ixx57DGq1GjabjfXP+lNPPYWf/vSnrB7TG3x5HRkZGUhNTYVarV7z/uPqp9/W1sbMkYVCIYRCITZs2ACz2cz4pGdlZeH//b//h9zcXMzPzwe8Zo5UnE4nlEolKIoKiXDuieUFSK7/2ChAMhqNvG1LJBHqyUZCQgKrN1iapjE6OorR0VE0NTWx5vkVysBQb4JBXbn55ptDMq5Aqaurw9e+9rWgiExxcXHYvn271wJ6SUkJMjMzYbfbcdNNN+H666+H2WzGxx9/jPvuuw8TExNISUnx6Kn9ta99Dffddx/rr8Fms0GpVEIgEKC9vd2n0ItIwdXehQSouFbiiEQiphInOTnZq2PSNI2hoSHMzMygtbV11Ur97373u/jnP//J1svxmm99y7tK+lCj0WjQ1dWFmpoan9oO2SA5uQgN9f8NheJyWKx9Pj/f16r0dUXfQXIyO3Y9FosFHR0dzAKLS4v0QGF7Umiz2WCz2XjxnIeHJyoRCAQhK9zwhri4OIyOjmJ2dhbNzc2rduGFkmBWngcjGDRYrOaTPjQ05NEnPZj2plzhs88+C2sRgk6ng0KhQFFRETZs2LDmNZQQl4D72u7DLw7/IiTjy0AGtBotRCKRT6JpYmLiiv7kgfDEE0/g/vvvh16vh0KhwOOPP47Jycmg3QvZ8FH3B4vF4tO9y2w2IyMjA/v370d7e7vHx9A0jSNHjmB2dhZtbW0rCqWpqakoKSlBSUkJnE4n5ufnodFo3NbMxEs92DbLXMBVOJdKpWERzpfjqZOXrJn8LUDiPc8jjFBPONgUpUnV7uLiIk466SRWF+uhsm3xNhjUlUOHDgV7WAFTUVGBSy+91KvH+rsQ2bx5M2pqavC3v/0NZrN51cdOTk4iLi4OcrmcCQJJSUnBhRdeiAsvvNDtsXNzc/j8889B0zSam5uxfv16n8e2FiaTCQqFgrF/iIXd5OUBKgaDAWq1GseOHUN/fz+ysrKYqnRP9i7A8S+qvr4+LC4uor29fVVriNdffz0swjlw3OJny5YtYTn3SszNzaGnpwf19fUoKDjRfz5UFBffgOGROwI6xtqho6koLWWnfZQI50KhEHV1dZxepAcKG5NCo9EIAFE9EeTh4eHhAg6HAzRNQ61WY/PmzZzatAxWEVIogkGDyXKfdK1W6+aTnpubi4SEhKgW0O+66y6P+U+hQq1Wo7u7G5WVlSgrK/P6eUmCpCCOyp2S1BIMDg7CarW6FRqtJZp2dnairq6O9fFQFIWqqioUFhYyOV3B3EQMh2ULcLwAxJ9Nv23btiE/Px+jo6NuP6dpGgMDA9BoNGuuW11xzUwga2aNRoPp6WkMDAwgIyODuSYCCSfmKlwUzpezUicvWTt5W4BEvP6jFe795SKM+Ph45qIKZMfZbDZDoVAgPj4eJ598MpKS2P1CWynBnk243HIYKMsF6bXwV0AXCoW4+eab8cgjj6z5ZUdRFFpaWvDkk0/iG9/4xoqPy8/Px0UXXeTzWLxFp9NBqVSioKAA1dXVUfV39xaBQIDMzExkZmZi/fr1sFqtjL3L0aNHkZSUxEwacnJymM2srq4uWCwWtLe3r1qpPjAwgJtuuimEr8idcC4KPDE9PY3+/n40NTWFfWxi8ekYHRWBoudZO6Z7VboADvt/oa+vjwnq8ndzymKx4PDhw8jJyYl64Xw5/k4KiXgezf59PDw8POGGWE4Axzs9uSScA+wXIYUzGDRYJCYmoqCgAAUFBW4+6aeddho+/PDDcA8vaIRzfj41NYWBgQG/CkmslDVIozqRq5quwiklp/xfjpQaMzMzbqJpXl4eMjMzT/gMlJWV4fbbb8ef/8y+P7ter4der2f9uJ74/ve/H5LzLCeQ++jc3BwGBwdRU1MDwL3gq62tzW9rVtc1M7FEJZtuExMTiIuLY4rTxGIxJ4VmX4gE4dwTK+VLke+ulQqQeM9znlVxDbfxVzxfWFiAQqGARCIJWtCp68UfjKpgf1sOudQquhq+fPmQDYrl74G3r5UE3vb09Hj1+BtuuAHnnHPOij7ZwcTfaodoJzk5GevWrcO6devcWtV6e3vhcDiQk5MDk8m0YqDPp59+iu9+97sYGRkJ0ytwp7W1NdxDYJicnMTQ0BBaWlogFovDPRzExSWgtvbP6O0Lhi98PKqqHkB83Gao1WqmaicnJ4ep0PB28mo2m9HR0QGRSITa2tqIX6QHymqTQlfbMb1ej9TU1Ij1hOfh4eFZDS7Ytmi1WiiVShQVFTFj4hpsZkdxKRg0WLj6pL/xxhvYvHkzent7T3jc17/+dfzyl7/E7t27cd999wXFoiPYhKOqnqZpHD16FOPj45BKpX6tAbOTs4MwshORiqTYVrxt1Ryp8fFxJCQkMHNb10KRBx54ABdffDG2bdsWkvGyzW9/+1tGgA41gc5dTzrpJCwsLICiKPT09MBgMKxZ8OUrSUlJbuHEi4uL0Gg0GBkZQXd3N3JychgxPdJE2UgVzpfjbQGSQCDA/Px8xP2dfCEy/4KrEA7bFuD4h8Mfj2di8VBdXY3S0tKgjd/1YmdbPA+k5TDUIaahItCFyI4dO7wWz4HjLYN///vfAzqnrwRS7RBLuLaqbdy4EfPz8+jp6QFFUUzHCfl9amoqLrroIuzduzfcw2ZITk6GUCgM9zAA/CdUVSaTcWZMAJCV1YKy0h9jfOLXrB63cv2DkOTtAACIxWLQNA2TyQS1Ws1UhKSlpTGLjezsbI8TZbPZjMOHDyM3NxcbN26MukV6oKw2KXzmmWdgtVpht9tZXSzw8PDwxDo0TWNiYgJHjhxBbW0tiouL8cUXX3DS4oOtyvNI8jdnC4FAgC+//BKDg4O477774HA4cMcddyAtLQ3z8/Po7+/HaaedhgMHDuCqq67iTOGItyiVypAF1gPH5yjEOsM1rNFX1mezb+O5nOLkYvzh1D8gIe5Eyck1R8q1U2FgYAA2mw1isZiZ37a3t0Mul0MmkwV9zGwRFxeHvXv3rugdHgoefvjhgJ5PwlO7urpgtVrR1tbGujuCK3FxcRCJRBCJRKiurobJZGJCR4eGhpCamspYogqFQk4XtjidTigUCgCATCaLKkvblQqQJiYm8MUXX4RtsygURJ14HmpIi4KvEz2KojA4OIjp6WnIZLKgV1CSC9xfkd8TbLQcRsKNJBw35tTUVKSmpq7pfU74/PPPgzyi/0BCbScmJvyudohVzGYz+vv7IRaLUVdX51Z1MTo6itdee41TwjkAbNy4MdxDcEt1XytUNVwUFV0BYc7J6O+7ETb7dIBHS0V93d+RldXo9lOBQID09HSkp6ejvLwcdrsd8/PzUKvV6OzsBE3Tbq2OSUlJMJlM6OjoQF5eHmpqamJioR4o5Lts165deP755/Hhhx/ywjkPDw8PixALAJVKhba2NuTk5ABgt8KbTdgYVywK567U1NTg5ZdfBnB8PdrT04OUlBSUlpZCr9dDo9HgL3/5C3JycvDAAw9gz549YR6xd4SympTko5lMJmzatCmgoMXc1OD7Eu86axcyktbOjHHtVKipqWE8saemptDf34/MzEzk5eXhpZdewte//vWgj5sN7r333rAK5wDw5ptvBvT89PR0KJVKOJ1OtLa2sqYheUtaWhqTqeBwOJhO7u7ublAU5eafH0xR31dchXOpVBoRepe/EJ1sdnYWF154Ia688ko88sgjYR5V8ODFcxbwNUTGbrdDqVTCarViy5YtXoctBAKZpPEth74jFotD/toEAgHEYjGOHTvm1eMXFxeDO6D/g6Io9Pf3Y35+Hu3t7XyIng8sLS1BLpejsLAQGzZsgEAgQEpKCoqLi1FcXAyn04nLL7883MM8gQcffDCs5/c21Z0LpKWWorX1Xea/aZqGUnkJLNYht8fl5X0LS/rPlv08HtUb/g6RSOb1/SYxMRH5+fnIz88HTdPQ6/VM+2tvby8yMjJgNpuRm5sbs3kE/kDTNP7+97/jl7/8Jd5++21s3bo13EPi4eHhCQrh+F6wWq2MILNlyxY3+7H4+HjOVp4HknEV6cGgbGKz2aBUKiEQCLB582ZG9CKWDSqVCt/73vdwzTXX4IorruDkZooroRJIXd+39vb2gIXMpPgktOe245DmEEsjdEcoEEKSJvH5eZ48sdVqNTQaDVJTU5Gens7k0XCZu+++O9xD8NuXnPDUU0+BpmnIZLKwW44kJCRAIpFAIpGApmksLS1BrVZjcnISfX19yMrKYgqIPPnnh4pYEs4Js7OzOO+883Daaafhb3/7W1S/5qgTz8PxQfFFPDcYDJDL5UhPT8dJJ50U0hsRW0nxbAeDNjc3o7OzM+BxBQviwRhKaJr2yfcvFH6VDoeDadtqb28PqNoh1pifn0dnZycqKipQXl7u8THx8fFedxqEknAlxAPHr+v+/n5otVqfUt25gkAggFT6Gux2I/T6zxEXn4GsrBbExx3/7NhsKthsaiQlSZCUFFjwqUAgQHZ2NrKzs1FVVcVcc4mJiVCpVFhcXGQmlYGEjkY7NE3jn//8J3784x9jz549vHDOw8PDwyJ6vR5yuRxCoRCNjY0nfBextVZhG1dbL1/E82gMBg0Eg8EApVKJ7Oxs1NXVuf39XS0bSPXxF198gbPOOitkwY6+8vTTT4ckuN5sNkMulyMjIwMNDQ2szeF+uumnuPBfF4IC+xsUl9RcwspxkpKS3HKknn32WVxyCTvHDibhFpuB457ln376qV/PPfnkk1FUVITm5mbOrRkEAgGysrKQlZWFyspKWK1Wxt5lbGwMCQkJbp24oRq/w+GAQqFAXFwcWlpaOPe+BQOVSoWdO3di06ZNePLJJ6P+NYf/Ux0FeDvRI631paWlTOVpKGHDry8YLYd79uxBdXU1LBbLio9JSkrCaaedhq1bt2J0dBQjIyPQ6/UoKytDQ0MDpqen0d3djeHhYdYnWLm5uSEPVKIoCmq12uvHB1vItlqtUCgUSExMRHt7OycmBJGCSqVCT08PampqsG7dunAPx2c6Ozuxfn3wfRGXQ1EUent7odfrI36zJjExHWLxWSf8/Lho7ntVzloYjUZ0d3ejuLgYVVVVjJekRqNhQkdFIhEzsQy0MiVaoGkaL7zwAn74wx9i9+7dERtOxcPDw8NFZmZm0NPTg8rKSlRUVHhcQ3DZtgU4XlXo7Rx4eQB1NHfpegPZ1C8pKUFlZeWq7wWpPq6vr8c777yDU089lXObKl988QUaGxvXfmCA6PV6KBQK5Ofns26/J0mX4PHTH8ddB+7ComORteMmIAHnVZzH2vEI8fHx2LFjB9577z1s376d9eNHG5dffjn++Mc/+vy8d955B5mZmWhqauK0rzghOTmZ2WBxXfMcOXIEVquVCR0l+WLBIBaFc41GgwsuuAANDQ34xz/+ERP6UFS+wlALnWuJ5zRNY2xsDMPDw6ivrw9LJTMQ+IQ0WC2HYrEY09PTuOOOO/Dyyy/DYrEgJycHZ5xxBtra2nDyySdDJBKhqKho1Ra1yclJdHd34+DBg9i7dy/kcrnXY0hPT4dIJILFYgFFUUhISIBMJsOPf/xjDA4OYmJigo2X6jVqtdqnv9VVV10VtLEYjUbI5XLk5OSgrq4uIr5EucLU1BQGBwfR0NAAiWRtkVQsFkOr1YZgZN4zNzcX8nMST0ez2Yz29nZO+dhxHYPBgI6ODqxbt45ZnMbHxzNCOU3TMBqN0Gg0TOhoeno6M6nMzs6O2cX9q6++ittvvx0vv/wyzjrrxM0OHh4enmgjFPd7mqYxNDSEiYkJNDc3rzof4qptC3mfvJ2buxYbkXysWGZ6ehr9/f3YuHGjz4Ukzc3N+Oc//4krr7wySKPznsLCQvT19YVsXqrVatHV1YWKigqUlZUF5fPalNuEN7/6Jl4eehl/6f4LK8f882l/RnFG8DpXTznlFNxzzz1ht5ZciVB0I3hDbW2tV49bv349rrnmGtx0003o6+tjOhwi8b613D+frHnUajWOHDmCtLQ0xic9OzubldcYi8L5wsICLrzwQqxfvx7/8z//E3I//HAhoEOpMocIm80WUvH84MGDKC4u9jgZcDqd6O3thVarhUwmQ3Z2dsjGtZwDBw5g48aNPt/Ql7ccRkrlhMViQWdnJx577DEoFAoIBALk5eXBaDRCrVbD4XCgtLQUN9xwA66++uoVb54PPfQQM5EP1XX10Ucf4aOPPvLqsdnZ2RgcHPQ7bX01FhcXoVQqsW7dOlRVVUXE350LkA2zsbExNDc3ex2q+sknn+Ccc84J8uh844UXXsBXv/rVkJ3P6XQyXqhSqTRmvozZwJNwvhZ2ux1arZZpdwSOb+IQsT1W3v833ngDN9xwA55//nlceOGF4R4ODw8PT0hwOp1BFauJ5Z/BYIBMJlszt+TIkSOw2WxoaGgI2pj85f3338eWLVvWfA2xHgzqCk3TGB0dxcTEBJqamiAWi/0+1r333hvWILq77roLP//5z0N2vpmZGfT19aG2tjZkhXcHZw/ink/ugYk2+X2M3ORcvP3Vt1kclWdmZmZQVVUV0DFSU1NhtVqZ9T1b63yDwcCZz316evqajzEajTCbzejo6GCK5bgyfjax2+2Yn59nPPRpmnazd/FnUywWhXOdTocLLrgAEokEr7/+OpKTk8M9pJARlZXnoSYhIcFj5bnFYmECA7Zs2RJ22wF/Ks8jORg0JSUFDQ0NuPHGG5GVlYX6+nq3tkuTyYS0tLQ1b3KurzdUXQ3d3d1ePU4mk+GFF14IinA+NzeH3t5ebNiwASUlJawfP1ohFVYzMzNoa2vz6W+zadMmJCcnw2q1BnGEvlFQUBCyc5EwZYFAwIlwmkhiaWkJHR0dTDu0tyQmJqKgoAAFBQWgaRo6nY7xDOzt7UV2djZTlZ6enh4x939fePvtt3HDDTfgmWee4YVzHh4eHpYwmUyQy+VITk7GSSed5JUwwVXbFuB4ReNaY+OF8/9AURT6+vqwsLCA9vb2gAPff/3rX4dFPE9PT8fk5GTIBCKapjE+Po7R0VG0tLQEtOHgK5sLNuPDSz7E9NI0LnnXP1/x+zffz/KoPFNYWBjwMaxWK7Zt24ZPP/0UDoeDFWugQ4cOcepzL5PJVu3Gb2pqYrrM8/LyWLcG4hKJiYnIz89Hfn4+aJqGXq+HWq3G+Pi4X2ueWBTOl5aWcPHFFyMnJwevvfZaTAnnABB5vRheEOoPvCfbFp1Oh88//xzp6enYtGlT2IVzwHfPc08th5F0M52fn8eXX36JgoKCE0KJ4uPjkZmZ6dVNLtR+zw6HA/Pz82s+rrOzEwcOHAhKoOPExAR6e3vR0NDAC+c+QHy6VSoV2tvbfd7USEpKwh/+8AfWx1VSUoLf//73+OSTT3Deeef59DkuKytjfTyesNls6OjoQHx8PKRSKS+c+wARzktLS30SzpcjEAggFApRVVWFLVu2YOvWrSgsLMTi4iIOHjyITz75BP39/VCr1ZzzHvWX999/H9dddx2efPJJXHrppeEeDg8PD09ICda8XqvV4vPPP4dYLEZra6vXFX1cDQwFVh8b8TfnhfPj2O12dHR0wGg0YtOmTQEL58Dxdewbb7zBwui859FHH4VKpQqpcD44OIjx8XG0tbWFVDgnxAniUJxVjH+d+69VH5cWl3bCz77f8H205rcGa2gn8NlnnwX0fIqiUF9fj48++gjPPPNMwB72Tz/9NOrq6gI6BtscOHBg1d/v2bMHhw8fRkFBQVQL58sRCATIzs5GVVUVTjrpJGbNo9PpvFrzOBwOyOVyxMfHx4xwbjQacemllyIlJQW7d+/mhL4Zanh1ggWWT6ZIIE5VVRXKy8s5cxPypZoj0isnpqamMDAw4Je33nLOOussDA4OsjSytXnllVfWfExJSQni4uKwtLSEjIwM1v4+pGp6enoaMpkMQqGQlePGAk6nE11dXbBYLGhvb/d7on3ttdeCoij88Ic/hN1u9/n5pDsiLS0N27Ztw0033YRTTz0VVqsVarUat956KyorK/H2229jdHR01WOJRCLk5+f79Tp8wWq1oqOjA+np6WhsbIxIj71wodfrIZfLUVZWhoqKClaPnZKSguLiYhQXF8PpdDIBPAMDA7DZbBCJRIxvYCROoPbv34+rrroKjz32GK644opwD4eHh4cn4iFVs0NDQ6itrfW5wIOrnufAypXny4NBI3HdxCYmkwkKhYKZ07EpKp111lnIz88PSR7P1Vdfjeuuuy7o5yE4nU709PTAYDBg06ZNYQ9zF2eIse/Cffjex9/D4MIgaNAozSjF7U23Y6N4I0QpIixYFvDl7JfITsqGNF+K5PjQVqE2Nzfjiy++wEknneTX8wUCATIyMhAfH4/s7Gzs3LnT6+7v5Rw7dgw5OTl+PTfY6PV6ZGVlnfDzjz76CD09PSgpKcH69etj+r7ly5onISEBcrkcCQkJaG5ujgnh3Gw24+tf/zpomsaePXu8sgOKRqLS89xut4e05a+vrw/x8fGorq52C8ThSlgEQS6XQywWr1lJGqxg0FBA0zSGh4dx7Ngxn7ymV2NmZgZffPEFBgYGgi7q0TSNXbt2Md7DK/GnP/0JmzZtgkajQXJyMvLy8pCXlwehUOj3GCmKQk9PD/R6PaRSaczeFP2B2I0AQEtLCys+0VarFWeffTY6OjpWfMzf/vY3vwKUzGYzNBoNVCoV3nzzTY/V7ikpKRgZGQn6Bgrx2BMKhXwgrY/o9Xp0dHSgoqIC5eXlITuva+ioWq2GTqdDenq6WwAP1783PvnkE1xyySV4+OGH8e1vf5vz4+Xh4eEJBhRF+bVRv9Kx+vr6oFar0dLS4peQND09jcnJSWzevJmVMbHJJ598gurqarfA0+X2lrE+hyFZSYWFhaiurg7Kd6vT6fQoBLLJN7/5TTz22GMhmxvY7XZ0dnaCoii0tLSELJA00qFpGkePHsX4+DikUimEQiGOHDmCK6+8Ev39/Ws+Pzk5Gbt370ZbWxu++93v4o033vDrfnjo0CHOVZx7Qq1WQ6FQoKCgACUlJVAqlSFfQ0Qay9c8i4uLiIuLQ3JyMurq6pCTkxP1awiLxYIrrrgCer0e7777blgzHMNNVIrnbHlWecvg4CDsdjusViuMRqNXgTjhQKlUIisra0UbkkgNBiWQcFY2xd/JyUns3r0br7zyCjIzM3HqqaeyMNKVoSgK//3f/72qeL5t2zY8/vjjzM4oCb5Qq9WgKAq5ubmQSCQQi8VeW1+QSRsJaeQnbd5Dsg1SUlLQ1NTE6u4zTdMoKiqCXq8/4XdnnHEG9uzZE/A5HA4HtFot9u/fjz//+c+gKArXXHMNLrnkEojF4qAGRhqNRnR0dEAikcRUqyAb6HQ6yOVyrF+/PmTWOitBQkfVajW0Wi0AuAXwcC109IsvvsDFF1+MBx54ALfccgt/3fHw8MQsNE3DZrMFfByr1QqFQgGKoiCTyfzuRpqbm8PIyAhOPvnkgMfENp9//jkqKiqYLJhI79Jlm9nZWfT19YUkK0mhUGDr1q2sH7e5uRn33nsvGhsbGd/jYGOxWCCXy5Gamsr6OiKaoWkaR/r6oNu7D+UZGcjcWIOU9nYIEhLgMBox9MIL+PCxxyC12uAE8JpOh5d0i9C5FFieffbZePXVV7Fr1y78+te/9rjeWos9e/bgjDPOYPGVBZ/5+XkolUo+18xHiB0VTdNIT0+HVquFQCDg9JonUKxWK66++mrMzc3h/fff52x3RajgxXMW6O/vx9TUFLKzs1mrOg0G3d3dSE1N9ZhMvbzlMNKEc6vVis7OTgBgbceepmm8/PLL+PLLL/Hss8/CYrHg7rvvDurfd2xsDM8999yKnRPV1dX485//jFNPPfWEvw8J+yNCuslkYlqM8vLyVlzI8JM2/yEBKyKRCLW1tUGrOHryySdx1113wWazIScnB//4xz9w1llnsX4e12tIo9HAaDQiJyeHCU9JSzvR39BflpaWIJfLUVRUhKqqqoi634SbxcVFKBQKVFZWorS0NNzDccPTNZSdnc1UpYc7dLSjowMXXHABfv7zn+P222/nrzseHp6Yhg3xXKfTQaFQICcnBw0NDQHNIzUaDfr6+vCVr3wloDEFg4MHD6K4uBjr1q1zqziPtDUT29A0jbGxMRw9epQRnUPBjTfeiOeffz6gYyQlJeG1117D1q1bkZiYyFgcqtVqzM/PIyUlxa27l+2/s8FggFwuR25uLjZu3BjznQveQlEURi6/AokjI3D7i8THA8s0IBoA/k/uogA8rFbjJasFX7/iCjz44IPo7OzEhRdeCJPJ5PM4Tj31VOzZs4ez2o8nNBoNurq6sHHjRhQVFYV7OBGD3W6HQqFAYmIio5dQFAWdTgeNRsOseYRCodu6OZK/G+x2O775zW9ibGwMe/fuDUsGA9fgxfMA0Wq16OjoQEpKCrZu3crpL73e3l4kJCSgpqbG7eeegkEjCYPBAIVCwdg+sCH+TkxM4PPPP8err76K/v5+xhu6qKgI1157bVDCDJeWlvDiiy9iZmZmxccMDAyguLjYqxuxyWSCSqVibBUyMjIgkUiQl5fH+KQvLS1BoVDwkzY/0Ov1UCgUKCwsxIYNGyL6y3ElzGYzs4hYWFhAWloaI4IGsoggC+3S0lJUVFRE5XsXLIhwXlVVFRHVIsQiSKPRYH5+HklJScw1lJOTE9LNus7OTuzcuRP33HMP7rrrLv664+HhiXkCFc9JzlNlZSUr3+cLCwtQKpU4/fTTAzpOMDh8+DAkEgmKi4sj1t6SbSiKwsDAADQaDaRSKTIzM0N6/uHhYUilUp/tWhMTE/H555+jtrZ2xceQzkxSDACAEdLFYnHA8xdyrZeWlsa837QvOJ1OjG47HYlGI3x5x1wFL0FcHNK/+U2onQ5c8sADGPdDOAeA119/HXFxcRAKhcy1wWahEduoVCp0d3ejvr6e6aDhWRu73Q65XI6kpCQ0NzevqJeQNQ9ZNycnJzNCek5OTkTpLA6HA9/+9rfR19eHffv2udmVxTK8eB4AExMTGBwchEQigd1uR1tbW9DPGQgDAwOgadptohDpLYdarRZdXV2sTjwmJiawe/dujI6O4tlnn4XVanX7vUAgwMaNG3Haaaf5fSMxGo0YHx9HWVkZzGYzvvzySwwNDUGn0636vKWlJb9uvDabjbmZa7VaJCYmIisrCxqNBuXl5fykzUfm5+fR2dkZUz5xnhYRZELgi0UQWSxwsWqa6ywsLEChUERsmyWxmSJius1mg1gsZtodgxk62tPTg/POOw+333477rvvPv5+x8PDwwP/xXMSMD8xMYGmpibWFtZ6vR6HDh3CmWeeycrx2EQulyMnJ4cJQY31inO73Y6uri7YbDZIpdKwBYdTFIVf//rXePDBB9d87JVXXonHH3/c57UUqTBVq9VQqVSwWq0QiUSQSCTIzc1FcrJvQZlzc3Po7e1FdXW1z6G6sYzdbkffn/+M7Odf8Ek4XwnapSL9u5OT+MTsvYgeHx8PvV7PFBqRIhG2Co3YZmZmBn19fWhsbOSFUB/wVjhfjqu1rkajgcPhcFvz+HrPCCVOpxPf+c530NHRgf379/MbLS5EpXjudDqDmtROURT6+/sxNzcHqVQKs9nM2XAbV44cOQKbzYaGhgYAkS+cHzt2DIODg6itrWW17eiVV17Bk08+iQMHDqz52Pvuu2/Fmyhp5VyOzWbzaoLnCaPR6NfzXHE6nRgZGcH4+DgjeBIRlCRI86yMSqVCT08PampqsG7dunAPJyx4sgjKyclhqi5SU1M9Po+0Csbye+cvxJ8wWhZaNE3DYDAwQjrpjiGTSjZDR/v7+3Heeefhpptuwv333x9x33U8PDw8wWR5kchaOBwOdHZ2BiXnyWg04pNPPsE555zD2jHZgKZpdHZ2wmKxoKysjJXK40jGbDZDqVQiOTkZTU1NnFk76HQ6vPXWW/jyyy8xOTmJ1NRU7NixA1dccQVr1hokQJDMgfV6PbKyspg58Fr2dBMTExgeHg6pxU00YJqfx9Ef3YP0jg5WhXNXto8MY8rLAkyDwXDC35mtQiO2mZqawuDgIJqbm3nrDR/wVzhfDlnzkOtCr9cjMzOTWfNkZWVxZm3idDpx66234rPPPsP+/fv59foyePHcR2w2GxQKBRwOB2QyGVJTUzkdbuPKyMgIjEYjGhsb3TzOI004J9Uu09PTaG5uZjW4wGaz4fvf/z7++c9/evX4pqYmXHTRRSf8nKIo/O53v8O6deuwfft2iMViOJ1OKJVKfPDBB353Rlx77bX461//6tdzAXdfwubmZohEIuj1esbexVuf9Fjl2LFjOHLkCBoaGvhdexdMJpNbmxqpusjLy2NE0Lm5OfT09PCtgn5AhPNo3nSw2WzQarWMmM5WAM/Q0BB27NiBa665Bg8++GBEtUzy8PDwhAKbzeZRSPIEyXpJTU1Fc3Mz616/FosF+/fvx/bt2zlzvyZrJr1ej+npaajVatjtdrfCk0jyPA4UYltIwt658ncKF976pNM0jeHhYUxNTUEqlSI7OzvMI48MKKMRx354F6iDBwEgaMI5ADhpGtdMTKDTaln1+V1dXaisrFzzHP4UGrEN2ayRSqUxH/boCyQcNDk5OSDh3BPEEUCj0UCr1SIuLo75PhGJRGHbZKEoCv/v//0/fPDBB9i/fz/KysrCMg4uw4vnPkAC7rKzs9HQ0MBc2BqNBv39/Tj11FNZPyebjI2NYWFhAU1NTREbDOp0OtHT04OlpSVIpVLWU9AtFgtqa2uhUqm8fk55eTnOP/98CIVCAMftAfbs2RM06yB/q89pmsbAwABUKhWkUimysrJOeIzJZGJaEkklaF5eHiQSCeOTHouQTYexsTG0tLTwk49VsNvtbiIoAKSnp0Ov1/PCuR9otVp0dnbGVLDPagE8voSOjo6O4txzz8Ull1yChx56KOYX+Dw8PDye8FY812g06OzsxLp161BdXR2Ue6rdbseHH36Is846ixPVzJ66dEkVoUqlgkqlgtFojJnCE9J9uX79epSVlcXsumAlnE4nU3msVqsBgJm7zM3NBW39Gq3QNI3J73wH1KHDAFgSzo8feNXHPKXR4I/z2hV/789a3JtCI7Y5evQoxsbGIJPJ+M0aHyDCeUpKCpqamoK6fqAoCouLi8y1YTabmU2W3NzckHnoUxSFH/3oR9izZw/27du35uZQrBKV4jlFUbDb7awec25uDl1dXaioqEBlZaXbDW5hYQGdnZ3Ytm0bq+dkm4mJCczNzaGlpQUAIk5IsFqtUCqViIuLQ3NzM5KSklg/h9Fo9LuiOCEhAU6n0+vqHX/R6XQ+LyicTie6u7thMpkglUq92u325JNOvuQjLfTCF2w2GyYmJlBUVIS0tDTQNI0jR45gdnYWMpks5GFIkQxFURgaGsLk5CSSkpJgs9kgEomY3fVQVV1EKkQ4r62tRWFhYbiHEzaWh456E8AzPj6OHTt2YOfOnXj00Uej9n7Fw8PDEyhriec0TWN8fBxDQ0Ooq6sLagcURVF47733sG3btrCL0KRDd60u3eWFJ8TCQyKRRJVISipY6+vrkZ+fH+7hcB6aprG4uIi5uTlMTU2BoiiIRCLk5+cjLy+P057HXEFz8CAM370FADvCOeCdeA4AvRYzfqdS47DF7PZzNixUPRUaEbGUDXsXmqYxMjKCY8eOobW1lV+7+kAohXNPLN9kSU1NdfPQD8Z4KIrCT37yE7z00kvYt28fqqurWT9HtMCL52tA0zRGR0cxOjqKpqYmj5MFLofbEGiahkajgVwuR2ZmJiQSSURN6gwGAxQKBXJyclBXVxe0G9nc3BzWr18flGOvRkVFBY4ePerVY321brHZbFAqlRAIBGhpafGrtdQ19EKtVoOiqKjzSXc6nSgoKIBpWeL622+/jYSEBMhkMk4nqHMRYhEklUohFAphNBqZCcHi4iLS09OZayhYVReRCvGHj3XhfDmuoaNqtRoOhwMikQgdHR0444wzUFFRgenpaWzfvh1nnnmmX8FgPDw8PLGE3W5nOlKXQ1EUent7odFomO/yYPPuu+9i69atYVuj0DTNVJwDvnXp2mw2Rkifn59nhA+JRMIpX1tfoGkag4ODTAEWX8HqPVarFQqFAklJSaisrGTWUr76pMciWq0Wk7/4BXI++ZTV43ornhM+NRhw0/QUAGB6epr16981jFaj0bhZqObm5vpcaORa9NXa2spqJkW0E27hfDkOh8MtdJSiKLfQUTYKSWmaxi9/+Uv84x//wN69e1FXV8fCyKMXXjxfBVKtu7i4uOqundFoxKeffort27cHfM5gQNM0Y2Njt9uh0WigUqmg1WqZliEuT+o0Gg26u7tRWlqK9evXB3WMjzzyCO69996gHd8T9fX12Lt3L+655x48/fTTXj3H211vk8kEhUKBjIwMNDQ0sBJuRNM09Ho9sziIBp90uVy+qu0SqXbl8Q6y6Tg5OQmZTObRIojci8g/rvi9cQG1Wo3u7m7U1dXxNjerQFrnp6en8a1vfQu9vb2oqKgATdOoqanBG2+8EVM+tDw8PDz+sJJ4ToQ/mqYhlUpDNr/74IMPsHnz5rBUSxLRnCyPAxFPXMMD1Wo14uPjmTVXpHRwOhwOdHd3w2w2e925ynMckg/gqfDLarW6dfcmJye7+aRHwrURTEhOUtV//Rhg2U3AV/EcAJ7QajF71pl46qmnWB2LJ0gny/JCo7y8vDW1GmLRqtFo0Nrayhd9+QARzlNTU9HY2Mi5zyDRX8i6eWlpCVlZWcza2R97XZqm8dvf/ha7du3C3r170djYGKTRRw9RKZ7TNA2bzRbQMcxmMxQKBeLj4yGVSlfd2eFiuA3wn8qJlVoOyaROpVJBo9FwclI3OTmJI0eOoK6uLujVlxRFYePGjZiamgrqeVzJysrC1NQU8157W2XjjXWLTqeDUqlEQUEBqqurg7bpsPxLPtJ80j/++GPce++9UCqVqz6OjTa9WMCfigfi90Z21i0Wi1uoTiRuyPiLSqVCd3c3Ghoa+LZoH+nt7cXtt9/ObA4nJSXh3HPPxfnnn4+zzz6br5bj4eHh8YAn8Vyn00GhUEAkEqG+vp6V4gtv2bdvX1jyZciayel0rmrT4g8URWFhYYEpPHE6ncjNzYVEImHFpiEYWCwWKJVKJCQkBCUcNppZXFyEUqlEcXHxCXavy1nJJz0vL4+z10YwOXbsGI4cOYIquQL0888H5Ry+yl92mob+b0+gtb09KONZ8byrFBqJxWK3+zJFUejr62OKPvmNLu+x2WxMEDYXhXNPkA04EjqakJDgVoS21nc2TdP405/+hD/+8Y/44IMPIJPJQjTyyIYXzz2wsLDApIh7YxFCwm3OPPNMzkwsXEVzYO2WQzKpI+E3FEUxwlU4vriJADczM4OWlpaQtInOzc2hsrIy6J7lhNLSUnR1dbldMwaDwSvB7B//+Acuu+yyFX9PKlcrKytDmpQcaT7pDocDt9xyC55//vk1/+4Gg4HzGwHhhqZp9Pf3Q6vVBlTxYDQamUUECa4lEwKudsiwARHOGxsb/c5eiFW0Wi127tyJDRs24MUXX4RAIMDnn3+Ot99+G2+99RYGBwfx97//Hd/85jfDPVQeHh4eTrFcPJ+enkZvby+qqqpQXl4e8u/cjz/+GHV1dcjNzQ3ZOT0FgwbzXK4dnGaz2a2DkwudjktLS1AqlRCJRKitreXc/J3LkFDVDRs2oKSkxKfn0jTNWHioVCpYLBbOXRvBgqZpjI2NYWxsDM319VjacW5wznP8ZL49SSBA6ScHEBfGSm5PhUYkR0osFmN4eBgGgwGtra1RfZ2wjc1mQ0dHB9LS0iJGOF+O6+asRqOB1Wp1Cx1dvpFC0zT++te/4je/+Q3effddbNq0KUwjjzx48XwZx44dQ39/P2pqalBSUuLV5IlL4TZA4C2HK31xSyQS5OXlBSWo0xVil2M0GiGVSkPWcnTs2DE0NjYG3LWwGunp6ZBKpbj77rtxxhlneLy+vKk+v+mmm/Dwww97/N2xY8cwODiI+vr6sFo+OJ1OZkNmuU+6WCzmxEbT5OQkbrzxRhw4cGDNx3Z2dqKqqioEo4pMiC+qXq9Ha2sra/dCUnVBNmTi4uLcQnVCWQ0XTEiLKi+c+87CwgIuuOACFBcX45VXXvH4HTU2NobU1FS+mp+Hh4dnGQ6Hg1k3HDlyBJOTk2hubkZeXl5YxvPpp59iw4YNIfsu9DYYNFiQggGVSgW9Xo/s7GymgzMctgtarRZdXV0oKytDRUVF1BYsBANSNd3Q0MDK9bu8mCQzM9MtjDZa/jY0TWNoaAgzMzOQyWRInprCzJVXBe1cvkDe49LDhyDgkLDqem0sLi4iLi4OJSUlyM/Pj+pCIzaJBuF8OTRNM64AGo0Gi4uLMJvNePfdd3HBBRdg27ZteOaZZ/Czn/0M//73v3HyySeHe8gRRVT2Aflzs6AoCoODg5ienoZMJoNYLPb6uWSiRYJlwslqNi3eIhAIIBQKIRQKUVVVxdycycZCdnY2EzjKdkuQa4vgpk2bQiqwSiQS1NbWorOz06/nC4VClJWVobq6GrW1tdi6dSu2bNmCuLg40DTt9d/i7bffxs6dO1d9zBVXXHHCz4jP9MTEBKRSKUQikV+vgy3i4+OZQAvXKpujR4+ip6cHOTk5zIZMuDadkpOTvRZff/3rX3vtSR9rUBSFrq4umM1mtLW1sVrxkJiYiMLCQhQWFrpVXRw5cgRWq9UtVIcLm5f+MDs7i76+PjQ1NYVNrIhUdDodLr74YuTn5+Oll15acXO3vLw8tAPj4eHhiSDsdju6urpgNBpx0kknhTVkLj4+nslqCibLg0HDIZwDx4tm0tPTUV5eDqvVygjpw8PDjN+xRCJBZmZm0MdHCnBCYZcZTdA0jZGREUxOTkIqlbJmOeR6bZAwWrKWihafdIqi0N/fj/n5ebS3tyMtLQ02DhRYuZGQwCnhHDh+baSkpECr1SIzMxPr1q3DwsIC5HI5U2jkrYVHLEKE8/T0dDQ0NETs52c5AoHA7b5ht9shl8sxOzuLa6+9FhRFgaZp3HHHHaitrQ33cCOOqKw8B477AHmL3W6HUqmE1WqFTCbza5f/ww8/RHt7u8dgvFARipZDi8XCTOoWFhZY9bdeWlqCQqGAWCwOW4vga6+9hhtuuMGn6ycjIwP19fW48cYbceaZZzJfUoG8F2tVny/333adeEilUs4na3PJJ/1nP/sZHnvsMZhMpjUfy/uen4jT6YRSqYTD4YBMJgvZhhdN0zAajUxVOrF3IZPFUCwy2WBmZgb9/f1oamoKaYt6NLC0tISLL74YaWlp2LNnD+/vyMPDw+MHOp0Ohw4dQmpqKie8rQ8dOoSCggKfLS98YXmX7lr2luHA4XBAo9Ew2VTEClEikbAultI0jeHhYUxNTaG5uTnkfvORTDjWYE6nE/Pz88y1EW67VX8h3eYkkJYUwVBOJybbg2Ml4W/leZm8IxjD8RuHwwGFQgGBQICWlhbmb04sPMj6KFoKjdgkWoXz1aBpGv/85z/xhz/8AZs3b0Zvby96enpw8skn4/zzz8f555+P2tpazn0Pco2oFc9tNptXN0eDwQC5XI709HQ0Nzf7/WWzf//+sE42wtFyaLfbGQFUo9EwO+BkUufLGIhHd0VFRVj8FQkOhwNvvvkmHnjgAfT396/5+FNOOQU7duzAVVddxaodgMPhWDHc7s0338SZZ57p9tiuri5YrVa3iUekQGw5SMhfqH3SlUol7rnnHq+sW3jx3B2y8bh84hYOiN8++edrcEo44IVz/zEajbjkkksgEAjw9ttvc37DkIeHh4erDA4OwmKxoKamhhMLZ7lcDpFIFLSOoWAGgwYLiqIYsVStVoOmabfA0UDmOE6nk7Hdk0qlXtlH8hzH6XSiq6sLFoslbGswV7tVtVoNk8nk5pPO1XWhw+GAUqkERVGQSqVum3bjZ5wJLC4G5by+ep5zUTwn1cSJiYlobm5e8fNPCo2IVkOsf8j6KFIKjdgkFoVzAHjppZdw66234pVXXsGOHTsAHLev/de//oW33noLH3zwAb744gs0NzeHeaTcJqbFc7Vajc7OTpSWlmLDhg0B3TwOHDiA2trakAsgy1sOw1U54SkpnAjpawlXExMTGB4eRl1dXVg9ul0h1hB33HEH9u7d6/Ex//jHP7Bz586g+RHSNI27774bjz32GIDjtgP79u1z89CzWq1QKBTMl2ekVBqsBFkckOvI6XRCLBYziwO2q6GIN+H69evR0NCw6j0jPj4eer2e1fNHMiSZPCkpadWJWzjwFJzCtcCl6elpDAwMoLm52SebMB7AbDbjsssug9VqxTvvvIPMzMxwD4mHh4cnYiGe51yhs7MTGRkZqKysZP3YoQwGDRaesqnIXDk3N9enbCqbzQalUgkAaGlpCXquVTRhs9mgUCgQHx/PiY4Nwko+6Xl5eSHv7l2J1dYQtvEJzFx8cVDP74uALhAIkNDWinVPPBHUMXkLEX9TU1PR1NTkk/hLCo1IjlRCQgJTkc7VQiM2sdlsOHz4MDIyMmJKOH/99ddx00034cUXX8QFF1zg8TFmsxkpKSmcuD9wmZgUz0ma8/DwMOrr61FUVBTw+T777DNUVlaGNIws0GDQYOHqS6xSqWC325kdztzcXGZyQdM0BgcHMTs7i5aWFgiFwvAOfAXMZjOuv/56fPDBB4iPj8eZZ56JXbt2hdWiBzg+OZLL5cjJyUFdXR1n/v5s4eqTrlarYTQameTovLy8gCwaXBPdW1pamI6R1apt3n//fT5U4/+wWq3Mrj3XA1Zcqy7UajX0en3Yqy6mpqYwODiIlpaWsGcTRBoWiwXf+MY3sLi4iPfee2/FDh0eHh4eHu9wOp0h8Rj3lp6eHiQlJaG6uprV44Y7GDQYuM5xVCoVlpaWIBQKmUyh1ebKRqMRCoUCWVlZqK+vj3rhjE1MJhPkcjmysrI4LcK5iqUajQZJSUnMtREun3Sz2Qy5XI7MzEyP7532V7+G4bXXgj6ONQV0gQDkDlHy5UHEcaBAzWKxQC6XsyL+uhYaqdVq2Gw2iMViRq/hQqERmxDhPDMzE/X19Zz9zLLNW2+9heuuuw7//Oc/8bWvfS3cw4l4olY8t9vtoCjqhJ+T1jStVguZTMbawvvgwYMoKSlhRYj3hkhpOaRpGktLS8ykzmg0QiQSQSwWMzfqlpaWsKTJRzKLi4tQKpUoLi5GZWUlZ//+bLKST7qvAihN0zhy5AhmZ2chk8ncqlbvuOMOPP744yc8p6ysDL29vTHxPq+F2WxGR0cHhEJhRG7ahLvqgnQ78MK579hsNlx99dWYnp7GBx98wL9/PDw8PCxAURTsdnu4h8FAbBPZCjPjSpduKPA2m2p+fh6dnZ0oKSmJmXUEW+h0OigUChQWFqK6ujpi3jvik07WUhRFuRW3haJ7mdjl5uXlYePGjR7fO82vfw3jq8EXz32h9OAXEIS5s4Csv0jRHJvXHU3TMBgMzPqIFBpxrWPBX0jRV6wJ5++88w6uueYaPPXUU7j88svDPZyoIKbEc4vFAoVCAQCs+5IdPnwYEokEpaWlrB1zJSK55dBkMmF6ehoTExNwOp3IysqCRCKBRCLhPfa8ZG5uDr29vdiwYUNQw5S4DPFJJ5UU3vqkUxSFvr4+LC4urhgOrNVq0dLSgvn5eaSkpOC5557Djh07IupzFixIt0Nubu6Kk95IItRVF5OTkxgaGoJUKuXDuHzEbrfj2muvxcjICPbu3ct7xPPw8PCwBNfE8yNHjsBms6GhoSHgY7kWGxHRPNLnLt7iminkmk0VHx+PsbEx1NbWYt26deEeZkSh0WjQ1dWFyspKlJWVhXs4fkO6e4mHfih80smmw1qFX/bZWUyft5P18wdC1sMPIee008J2frL+ysvLC0k2hdVqZTKkXPPISKFRJInPrsJ5Q0NDzNz/9+7diyuuuAK7du3C1VdfHTOvO9jEjHiu0+kgl8shFouD0pqmUCggFApRUVHB6nGXE+kth3q9HkqlEmKxGOvXr2d80rVaLdLS0phWsqysrIh7baGA+MM3NDS4eZ/HMiv5pC+3CXI6nejs7ITNZoNUKo26drRgs7S0BLlcjqKiIlRVVUXd5zPYVReTk5MYHh6GVCrlrEUVV3E4HLjxxhvR3d2N/fv38/c+Hh4eHhbhmng+MjICg8EQcHCZa7GRQCCIKMGHbUg21ejoKJaWlpCQkMAUL8WC1zEbTE9Po7+/H/X19ZzJ6GIL0t2rUqmg0+lW7FjwF61Wi87OTlRVVXlVaDh+5lnAwkJA52Sbko/2Iy4MGTsGgwEdHR1hW385nU63HCm73e62zuZyTgIRzok1VbStXVfi448/xmWXXYY///nPuO6662LmdYeCqBXPXcNvpqen0dvbi6qqKpSXlwflAurq6kJaWhqqqqpYPzYQHS2HKpUKPT09WL9+PcrKytzG73A43CqJ4+PjGSF9tUriWIGmaQwNDWF6eprT/vDhZiWfdJFIhLm5OSQkJHAq1CdSINUipaWlqKioiLh7jz94qrog7a2+Vl1MTExgZGSEF879wOl04rvf/S4OHTqE/fv3o7CwMNxD4uHh4YkqaJqGzWYL9zAYxsbGMD8/D5lM5vcxIrlLNxiQzsuFhQW0tLTA4XBApVIx2VSugaP8HNkd15yk5ubmqLeMW25v6G1370rMzc2hp6cHtbW1Xtvb0jSNiZNPAaxWf15CUEi9/HJIfnR3SM+p1+shl8tRUlKC9evXh/0+RgqNyDp7aWkJWVlZzPWRnp4e9jESYlU4//zzz3HxxRfjt7/9Lb7zne/EzOsOFVEtnjscDgwNDWFiYgLNzc3Iy8sL2vl6e3uRkJCAmpoa1o+9PBg00oRzmqYZ8ai+vn7NUFVSSUxaySiKYm7Kubm5MVcdQVEUenp6oNfrIZVKeXsbHzCbzZiensbY2BgoikJGRgazKROOoMhIZGFhAUqlktn0ikVWqrogYvpqVRfj4+MYHR1lNWMjVqAoCrfddhsOHDiAffv2xaxNFQ8PD08w4Zp4Pjk5idnZWbS3t/v1fF44d8dut6OzsxMOh+OEzksihpE1l8FgQE5ODjNXDoZ9RyRB0zQGBgagUqlOyEmKBVbzSReLxWtutJCcn8bGRp91GKdOh2OnnxHI8FlFIJGg9J1/h+x8i4uLUCgUqKioQHl5ecjO6wtWq5VZG2m1WiQnJzPXRziLH61WKw4fPozs7OyYEs4PHTqECy+8EPfffz9uu+22mHndoSRqxXOz2QyFQgGj0QiZTIaMjIygnm9gYAAURaGuro7V40b6BJCiKAwODkKlUqGlpcVn8Yimaeh0OqaVzGKxuFVHcLlViA3IhNfpdEIqlUb962Ub4hEnEolQVVXFTAA1Gg0TFCmRSPjuhhUg3o7V1dUoLi4O93A4wWpVF7m5uW7trWNjYzh69CgvnPsBRVG488478e6772L//v2cXTjw8PDwRDpcE89JNtJJJ53k0/OioUuXbUwmExQKBdLT09HY2LhmAZLZbGaE9MXFRWRmZjJCerDX0lzD6XSiu7sbJpMJUqkUqamp4R5SWFmpu3eljRYyB25pafE752dc1srG0FkhUSZD0ZN/C8m55ufnoVQqIyrfzHWjRaPRMDaqubm5IdVsYlU4VygUOP/88/HjH/8Yd955Z8y87lATteJ5T08PFhcX0dLSEpL2s6GhIVgsFjQ2NrJ2zEgXzh0OB7q6umCxWFiZdNA0DaPRyEzqlpaWIBQKmS/taJvUWCwWyOVypKamoqmpKeYq7gOFtLqtW7fuBI84b33SYxmVSoXu7m7U1dXxVhmrQOxdSHtrUlIS8vLy4HQ6oVKp0NraiqysrHAPM6KgKAr33nsvdu/ejX379gXNDo2Hh4eH5zhWDtkjzM3NYXh4GKeccorXzyHBoCTvihfOj1euKpVKFBYWorq62uf3w2azMfNkrVaLlJQUZs2VnZ0d1e+v3W6HQqGAQCAImZYQaRCfdLLRQnzSc3NzMTs7i9nZWUil0oDmwLM/+xmse95icdT+U7R/HxJDMJ8nhUs1NTURG+hL0zSWlpaY68NgMCA7O5u5PoJl72KxWNDR0QGhUIi6urqovke50t3djfPOOw933nkn7r333ph53eEgasVzm80Gp9MZsmrSo0ePQqfToaWlhZXjRXowqNlshlKpRHJyMhobG4My6bBYLIyQvrCwwHq4SThZWlqCQqFAbm4uNm7cyFdF+8j8/Dw6Ozu9shohX/DkWiKVFMQqKNo2ZbxhZmYG/f39fDCtj5Cqi9HRUej1esTFxTHti7HQKcMGFEXhZz/7GV544QXs27cvKFZoPDw8PDzucEk812g06Ovrw1e+8hWvHr/c3pKfMx/fgCB5X94ENK6F0+lkCgXUajXi4uIYId3XHBiuQ7rX09PT0dDQwBcveYHdbodGo2HWUjRNo6CgAEVFRQF199I0jYkzzgR0OpZH7BvJp5+Ogj/+IejnIYVL0RZKa7FYmPvH/Pw8kpOTmXW2UChk5f4Rq8J5X18fzj33XNxyyy34+c9/HjOvO1xErXjudDrhcDhCdr6JiQmo1Wq0tgbWXhQNLYc6nQ5KpRJ5eXkhE37tdjszodNoNEhOTmYmdUKhMKLeQyL8lpWVxUw4I5v4E0zjitlsZq6lhYUFpKenx5RPOvEnbG5uhlgsDvdwIo6RkRFMTk4yQWfknsTlUB2uQNM0fv3rX+Pvf/879u7di/r6+nAPiYeHhycmsNls4MqSkGStnH766Ws+NtK7dNmGpmkma8Ufn2lvoCgKi4uLTOCo0+l0KxRISEhg/ZyhYmlpCXK5HBKJBBs3boz568kXnE4nenp6YDAYUFFRwdiustHdu/Dfj0P/xBNBGPUaJCYi7+9PIq2hIeinmpmZQV9fHxobG6O6cMnpdEKr1TJiOkVRAV8fsSqcDw4O4txzz8V1112HBx54IGZedziJWvGcoijY7faQnW9qagpTU1PYtGmT38cgLYdOp5MRzSPtQ6BSqdDT08NU/IZj/OSmrFKpoNFoIBAIGMFKLBZzujqCfHH6K/zGOoEE03iCVFIs90mPxkob4D/+hFKpFEKhMNzDiShomsbIyAimpqbQ2tp6gjeop6oLLoTqcAWapvH73/8ejz76KPbu3YumpqZwD4mHh4cnZuCSeK7X6/Hll1/irLPOWvVxvHDuDkVRGBgYgFqtDtguw1tcuzdVKhVMJhNEIhFTdOIaTsp1SPFSeXk5ysvLY/568gWHw8FkdLW0tDCdliv5pPvT3UvTNJb27sXCXXcH62UwZH77eoi+972gn4cwNTWFwcHBmCtccr0+NBoNDAYDhEIhsz5KT09f8xgWiwWHDx9GTk5OTAnnIyMj2LFjBy6//HL84Q9/iPl1ZKjgxXOWmJ2dxdGjR7Flyxa/nu86ARQIBBH3AXCtdOCS1YNrdYRarYbdbkdubi4kEolXKeGhgqZpRriMtS9ONqBpGkePHsX4+HhAwTSrQVEUFhYWmGvJ4XC4Vdpw5VryB5qmMTo6ylRM8x7dvrGWcL4croTqcAWapvHII4/g97//Pd5///2AO7h4eHh4eHyDS+K50WjEJ598gnPOOcfj70mXbiTbW7INyZmyWq2QSqUnhDeGCqPRCLVaDZVKBb1ej6ysLEgkEkgkEqSlpYVlTN7AFy/5j81mg0KhQEJCApqbm1ftPFje3UssV33p7p267z44/vVvNl+CG7m7HkP65s1BO/5yJiYmMDw8DKlUGpT1ayRhsViY62N+fh6pqanMOtuTvQsRzkUiEWpra2Pme2BsbAznnnsuLrjgAjzyyCMRpxtGMrx4zhJqtRqDg4PYunWrz8+N9MqJcFQ6+IMnb2suVEfQNI2BgQGoVCrIZDJkZmaGZRyRCk3TGBwcxNzcXMjeP9cgFJVKFdE+6TRN48iRI5idnfVK+OVxh6ZpDA8PY3p6Gm1tbV5VSSx/fjhCdbgCTdPYtWsXfvWrX+Hdd9/F5hAuWD7++GP8/ve/R0dHB2ZmZvD666/joosuYn5/7bXX4plnnnF7zjnnnIN33nknZGPk4eHhCQV2u50J2ww3FosF+/fvx/bt208QBfhg0BOxWCxQKBRITk5GU1MTZ2xTrFYrM0+en59HWloaI6RzyQZxbGwMo6OjaGpqQm5ubriHE1FYLBbI5XJkZGSgoaHBJxFvpe5eiUSyakcmTdOYaG1j6yX8B7EYxXveRHwIN56OHj2KsbExyGQyZGdnh+y8kYDD4XArNKIoiilaE4vFcDqdMSmcT01NYfv27di+fTt27drFC+chhhfPWWJ+fh5dXV3Ytm2bT8+LdOHcbrejq6sLNpstrJUO/mAymRghXafTMdUR3rYJsYHT6UR3dzdMJhOkUmlEia5cgKIo9Pb2QqfTobW1NWzvnyefdCKkZ2VlcfZzTdM0+vv7odVq0drayumqIC5C0zSGhoaYjQc27huk6kKj0QQtVIcr0DSNv//97/jJT36Cf/3rXzjllFNCev5///vf+PTTT9Ha2oqvfe1rHsXzubk5PP3008zPkpOTY74yiIeHJ/rgknhut9vx4Ycf4swzz3Tr6uODQU9Er9dDoVCENGfKHxwOBxMoqdFokJiYyAil4ZrbuBaPcLn4i6sYjUbI5XKIxeKAxUuKohih1JvuXqdWi2NfvRAwmwN6DQmbNqHgL48gPsTdw64dv62trXzh3BrQNA2dTsdsthiNRggEAmRmZqK+vj5kuk24mZmZwY4dO7B161Y8+eSTfJhxGIha8ZymadhstpCdT6fT4fDhwzjzzDO9enw0BIOSNPKUlBROVTr4w0rVEcEUP202G5RKJQQCAVpaWiLa9iMcOJ1OdHZ2Mhs3XPFVdK2k0Gq1iI+P56RPOtl40Ov1aG1tjaiNLy5AFl1zc3Noa2sLysYDyW9wrboINFSHK9A0jWeffRZ333039uzZ4/PGM9sIBAKP4vni4iJ2794dtnHx8PDwhAIuiecUReG9997Dtm3bmLlJpBcbBQO1Wo3u7u6w5kz5g6tQqlKpQFEUM0/Ozc0NiSBEURR6enqg1+shk8n44hEf0ev1kMvlWLduHaqqqli99jx1iq/U3WsfG4Px8GHo9u0DPv/C8wEzM4GUFCAjA3GpqaCXlpBy0kkQf+8WxIdhw4QU3szMzPAdv35gNptx6NAhpKamIi4uDgsLC0hLS3Ozd4mUe6EvzM3N4bzzzoNMJsOzzz7LC+dhghfPWcJgMOCzzz7D9u3b13xsNLQc6nQ6KJVK5Ofno7q6mjOCIBssr45ISEhg2gzZqo4wmUxQKBRMmxt/A/QNu90OhUKBuLg4tLS0cHbjhvikkwUCV3zSKYpCV1cXzGYzZDIZZzYeIgViFaRWq0NWse8pdInYu4SyW4YNaJrGCy+8gB/84Ad44403vN50DiYriee7d+9GUlIScnJycMYZZ+BXv/oVn0nBw8MTdTgcDqaghwu8++672Lp1K9LT090qziNxzRQMiE9yfX098vPzwz0cvyEVpWSebLFYmCKBvLy8oGTA2O12JtxSKpXGXM5MoJBg1YqKCpSXlwf9fL5091JmM2iLBXEcFVCJVatGo+E7fv3AbDajo6MDYrEYGzduhEAggMPhcCs0AuBm78JVjcAXNBoNzjvvPNTV1eH5558P2Wvi7S1PhBfPWYL4851zzjmr3qyjoeVwbm4Ovb29qKqqQklJCSe/nNiCVEeQ3W9SHUECR/0RvcnGQ0FBAaqrq6P6/QsGxF8vPT09ojYePHlbC4VCpsMhVJYzpGLfbrdDJpNFdPVyOHCd+La1tYXVKoh0OJBQHTJZ5Lq9yyuvvIJbbrkFL7/8Ms4999xwDweAZ/H8xRdfRFpaGioqKjAyMoL/+q//QkZGBj7//POIue/w8PDweAPXxPMPPvgAmzZtQkZGBh8M6gLpepuZmUFLSwuEQmG4h8QqBoOBEdKXlpYgFAqZdRcb8y3iD0+6pvnvct9QqVTo6elBTU0N1q1bF/LzR0p3rydomkZfXx8WFhbCajUaqZjNZhw+fBi5ubmMcL4c1804tVoNk8kUsZlkhPn5eZx//vkoLy/HSy+9FNLNPt7e8kSiVjwHjltxhAriz3fWWWetuBsU6S2HNE1jbGwMR48eRWNjI/Ly8sI9pJBCbsgqlQoqlQpWqxVisRgSiQS5uble3cxIi2VlZSXKyspCMOrowtVfj8vejt4QDp90u93uZhUUDbvxoYR4xM/Pz3Nq4rtSqA75x6UNkjfeeAM33HADXnjhBXz1q18N93AYPInnyxkdHUVlZSU++OADTlTL8/Dw8LAF18Tzffv2oampifGh5ivO/5OTZDQaIZVKo75qlWTAqFQqLCwsICMjgxHSMzIyfL4eDAYDFAoFEzAYyWuIcDA9PY2BgQE0NDRAIpGEezhu3b1qtRp2u50T3b2eIDZBBoMBMpmMt8r0ESKc5+XloaamxuvPvslkYjZbyFqbXCPZ2dmc/07R6XS44IILkJ+fj9deey2sneK8veVxolo5EQgECNXeANm5djqdHgWpSBfOKYpiggXb2tpiMlRFIBBAKBRCKBRiw4YNMBqNUKlUmJiYQF9f35pVxMeOHcPg4CDq6+tRUFAQhlcQ2eh0OigUiqD464WD1NRUlJaWorS01K2SQi6XB6WSwmazQS6XIykpCc3NzXy1jY+4Voy0tbVxauLrai3lGqozNjaG3t5epnIrNzc3rPYub7/9Nm644QY8++yznBLOvWX9+vXIzc3F8PAwL57z8PDwBAmaphEfHw+NRoPU1FTeWg7HC8IUCgUSEhKwadMmTgmDwSIlJQUlJSUoKSlh5skqlQrj4+NISkpyCxxda02wsLAApVKJ0tJSrF+/PuLXEKFmfHwco6OjaGlpgUgkCvdwABzv3heLxRCLxaipqWG6e8fHx93mvmx1LfiL0+lEV1cXrFYr2traeJsgH/FXOAeAtLQ0t7W2VquFRqOBUqkEAGZtxEV7l6WlJVx88cUQiUR49dVXOfs9uH//fkgkkpixt4zqynObzRYy8Rw47s936qmnulUCkGDQSG45tNvt6Orqgt1uR0tLC6dEI66wvIo4IyODEbPS0tJw9OhRTExMoKWlJapbWYKFVqtFZ2dnTFTse6qkcO1w8GfBZLVa0dHRgfT0dDQ2NvLVNj5ChPPFxcWIC1cl9yaNRsOEIbtWXYTqWnj//fdx5ZVX4sknn8Q3vvGNkJzTF7ypPD927BhKS0uxe/fuiBT/eXh4eFbC6XTC4XCEexjMmmlqagqTk5MwGAwQiURMcQpXBYRgQiqmc3JyUFdXF/NzOKfT6WapCYARSUUi0QnFIcRutLq6GsXFxeEYcsRC0zSGh4cxNTUFmUwWMcVz4eju9YTT6YRSqWT89WNh04tNAhHOV4OiKDd7F7PZDJFIxIjp4e4sNhqN+NrXvoaEhAS89dZbnMi14u0tj8OL5yzywQcfYPPmzcjMzAQQHcGgJpMJSqUSqampaGxs5NyuHBex2WxMdYRWq2X+5hs3bkRhYWHEXQPhZm5uDj09PaitrUVRUVG4hxNSVvJJ96WSgoSrCIVCftHlBzRNo7e3FzqdLuKE8+WsFKpDqi6CNanfv38/vv71r+Oxxx7DNddcw5l7oMFgwPDwMABAKpXioYcewumnnw6RSASRSIRf/OIXuOSSS1BQUICRkRHcfffdWFpaQnd3d0wKODw8PNELF8RzT126ZrOZsUvU6XTIzs5milPCLXCEAq1Wi66uLr5iegVomsbi4iIjpNtsNreCk5mZGQwPD3PGaiSSIFaFWq0WMpmMEwKeP5CKYzL3jY+PR25uLlMtGyyRz+FwQKFQ8FaZfmIymdDR0cG6cO4Jo9HIdIAvLi6GbbMFOL5uv/TSS+FwOPCvf/2L0RXDDW9veRxePGeRffv2QSqVQigURkUw6OLiIpRKJQoLC/lgSz9wOBzo7OyEyWRCVlYWFhYWIBAI3KojIvG6CCWTk5MYGhqKSY99T/haSUE84lcLV+FZGYqi0Nvbi6WlJbS2tkaVYLpaqE5ubi5rXqoHDhzApZdeiocffhjf/va3OXUN7t+/H6effvoJP//Wt76FXbt24aKLLoJCocDi4iKKioqwfft2/PKXv0R+fn4YRsvDw8MTPMItnpNio9W6dK1WKyOkL+/yzMjICMOog8vU1BQGBgZQV1eHwsLCcA+H89A0DYPBwAjpS0tLEAgEKCkpQVlZWUQXP4SaaPXoXqm7l8x92bJUsdvtkMvlSExM5K0y/YAI5xKJJOQaFLGIIv/i4uKYjl2xWBzUv6XFYsEVV1wBvV6Pd999F9nZ2UE7l694I54Dx7uAfvWrX+Hmm28OzcBCTFSL53a7nan6DgUff/wx6urqIBaLI9rfHABmZ2fR19eHDRs2oKSkJNzDiTiINyH50kxISABFUW7VESTYhFRH8DvS/4GmaRw9ehTj4+PMhhSPO6tVUohEIkY4LywsxIYNGyLyPhROXBcO0Sace2J5qE5aWhqzMeNvqM4XX3yBiy++GA888ABuueUW/hrk4eHh4SgURcFut4f8vMTekoSVetula7fbmTBJrVaL1NRURkjPzMyM6O8bYpVx7NgxNDc3c8ZjOlKgKAp9fX2Yn59HYWEhdDodFhcXkZmZydj/pKenR/Q1EkxI8ZfD4YBUKo1aj+7lmy2u3b15eXl+F5HYbDZ0dHQgNTUVTU1NfKGcj4RTOF8O0W7IWttisUAkEjFiOpubSlarFVdffTXm5ubw/vvvc87ml7e3PA4vnrPIp59+iqqqKojFYtA0HZE2LUS0HBsb46t9/YSIlqt5ExI7DlJBYzKZYt7TkUDTNAYHBzE3NweZTMaZdiUus7ySgnTd5OXloba2NmonvsGCCOdGoxGtra0x9/6tZO9Cqi682eg7fPgwvvrVr+IXv/gFvv/970fcdyEPDw9PLBEO8Xx5l66/6ybynUVEsMTEREZI9yZMkks4nU709vZCr9dDKpVGrFVGuHA4HOjq6oLNZoNUKmXWU8stNVNSUpg1l78FAtGIzWaDUqlEfHw8U/wVK1gsFmYdRTKCSLe4t9YdFosFcrkcGRkZaGho4IVzHzGZTDh8+DDy8/PDLpx7wmg0MteITqdDRkYG07UQiL2L3W7HN7/5TYyPj+PDDz/kTOAmb295Irx4ziJffPEFCgoKUFRUFJEV56479VKplBct/YBY3RQXF6OystLra4DcjFUqFfR6PbKystwCR2MFYpOh1+shk8liws+Sbebn56FUKiEUCmGz2VirpIgVKIpCd3c3TCZTTArnyyF+oqQq3dXeJS8vz+NnVKlUYufOnfiv//ov/PCHP4y470IeHh6eWCPU4jnJhXI6nayumSiKchPSI8kukQiXANDS0hLz8w9f8dT16wmn0+l2jcTFxUXMNRJMiPCbnp6OhoaGmLYaWd7dS66RvLw8j6G0wH8ypkjxHD/39Q0inBcUFEREx7TNZmOuEa1Wy3SAr3aNeMLhcOD666/HwMAA9u7dy6lsBt7e8kSiWjx3OBxMG2AwIRPA0dFRjI6OIi0tDRKJBPn5+cjIyOD8hx84/iVBWrRaWlqixtsslJA090CtbqxWKyOkz8/PM77W0dCKuhpOpxOdnZ2w2WyQyWT8osEPNBoNurq6UF1djeLiYgD/qaQgHqHhDEHhOhRFoaurCxaLhb8GV8BkMjGLCWLvsnv3bmzfvh3btm3DwMAAzjvvPPzgBz/Aj3/8Y/764uHh4YkAaJqGzWYL2blCYW/papeoUqngdDqZ+XSwvWt9xWg0QqFQICsrC/X19ZwaWyRA3j+hULhi168neEvN45CuaZFIhNra2pjdQPCEp2tkuU86ef9CEW4ZjRiNRnR0dESMcL4c0gFOCo2sVitEIhGz3l6pCtvpdOLmm2+GQqHAvn37UFBQEOKR8/gKL54HyPKWQ4qimLYwjUaDpKQkpoKYq21hJpMJCoUC6enpaGxs5CdsfjAxMRGUNHeHw+F2PSUmJjITf6FQGDWTG1JtExcXxyeS+4lKpUJ3d/eqwVL+VFLEChRFobOzE1arFa2trUhMTAz3kDiP3W7H+Pg47r77bnz66aeIj49Hamoqtm7diqeeeorvXuLh4eGJEEIlnnsTDBoMaJqGXq+HSqXC3NwcrFarm0gazu/8hYUFdHZ2Yt26daiqquLkWpHL6HQ6KBSKgN8/V0tNtVoNo9EYE5aaer0eCoWCz0jyAuKTToqSDAYDMjIyYDKZkJ+fz1ec+0GkC+fLoWmacRTQaDTQ6XTIzMxEbm4urFYrNm7ciLi4ODidTtx222349NNPsX//fqxbty7cQ+fxAl48D4C1Wg6Xt4XFx8e7efBxQfgkE7aioqKouGGFGpqmMTQ0hOnpaUil0qCmIlMUhfn5eeZ6ommamfhzrYLGF/g2wcCZmZlBX18fGhsbvd68CVXifCTgdDoZj0yZTMYL537Q29uLb3/720hPT8fCwgKOHj2K008/HRdccAEuuOAClJaWhnuIPDw8PDwrEGzx3N9g0GCNxWg0Ym5uDiqVyk0klUgkIZ3/kPlbTU0N0zHI4z1qtRrd3d2oqqpifZ5hMpmYNZdOp2MsNUngaDSwsLAApVKJiooKlJeXh3s4EYdarUZXVxeSk5NhsVgYn3TeS987iHBeWFgYtRuHJG9hbm6OCds87bTTQNM0Ojo68NFHH6GsrCy8g+TxmqgWz51OJxwOR1CO7WvLIRGq5ubmGOHTtXUwHEI6mbBVV1cHZDMSq5BQwXCE+tA0DZ1Ox7SiWq1WiMViZlIXKeIfaXMTi8Wora2Nyi/NYHPs2DEcOXIEzc3NfgeMBCtxPhIgdkEOhwNSqTRiPjtcYnR0FDt27MCll16Khx56CHFxcRgaGsKePXuwZ88efPLJJ/jDH/6A22+/PdxD5eHh4eFZAavVGpTjshUMGiyISEpyh7Kzs5Gfn79irgcb0DSNo0ePYnx8HE1NTZwJiIskyPy3vr4+6B67xFKT+BsTi9ZItkAkGw+uVo883rO4uAiFQsFsPJDgYnKd8N29q2M0GnH48GEUFRVFrXC+HLPZjH/961948skncejQIQgEAmzfvh0XXHABdu7cGdVe4dECL577QaAthySAjUzUHA6HW+tgsG+uNE1jdHQUExMTaGxsRG5ublDPF40Qj3in0wmpVBrWKl1SQUOuJ4PBwAT6SSQSzvrXkzZLX8NVef7D2NgYjh49ipaWFuTk5LB2XE+J85G+SPCE0+mEUqmE0+mETCbj7YL8YHx8HDt27MDOnTvx6KOPetwIXlhYgMPhQF5eXhhGyMPDw8PjDcEQz0Plb84Wy3NiMjMzmYp0topkKIpCX18fFhYW0NLSwluc+YjrOpbt+a83EJGUWGqSzvK8vDzk5ORworN8Laanp9Hf34+GhgZesPOD+fl5KJXKFXPOiE86WUu5FrnFWnevJ2JROAeOXxf33XcfXn75Zezduxc2m40pNDp06BDa2tpw22234aqrrgr3UHlWgBfPfSAYLYeuHnwqlQoWiyWoHnyuEzapVIqMjAxWjx8LEJuR1NRUNDU1cW4n2Ww2MxP/xcVFZGRkuE38ufAFpdVq0dnZGZQ2y1iALBwmJychk8mQlZUVtHNFq086Ec4pioJUKuWFcz+YmprCOeecgzPPPBOPP/54RCwYeXh4eHg8Y7PZwOayMNKE8+W4ttvPz88jNTWVmU9nZmb69XpI8Y3D4UBLSwtnC1y4CkVRGBgYgEajgUwmC/s6lnSWk3U8RVHMHFksFnNybklyugLpWI1lNBoNurq6UFNT45VPtatPulqtxtLSErKzs5nrJFosgLyFCOfr1q2LqeI5mqZx//3345lnnsG+fftQW1vr9vu5uTn861//glgsxle/+tUwjZJnLaJaPKcoCna7nZVjLW85DIZI4KmCmE0PPpvNhs7OTlAUhZaWlqgNPgkmS0tLUCgUyM3NZQIfuAyZ+KtUKmi1WqSkpDAV6eHyYpudnUVvb++qwZY8K0N89mdmZtDa2hrShYM3ifORgNPphEKhAE3TvHDuJ7Ozs9ixYwe2bNmCp556KmI3UXh4eHh4jsOmeB6uYNBg4XA4mPm0RqNBYmIiJBIJ8vPzvZ5Pm81mKBQKzhbfcB2ST2OxWCCVSjm38eBaEKdWq2E2m90CR8M9R6ZpGiMjIzh27FjQc7qiFZVKhe7ubtTX16OgoMCvY1gsFuZeQrp7Y8UnPZaF89/+9rfYtWsX9u7di8bGxnAPicdPePHcC9YKBg0Wyz34hEIhI6T7OmEwGo1QKBTIzMzkQxn9RKvVoqurC2VlZaioqIi4G/7yAFtSQSyRSCASiUKyETA5OYmhoSE0NTXxdkF+QNM0+vv7odVq0draGlYvck+J89nZ2cwigas+6Q6HAwqFAgKBAFKplL8X+oFKpcJ5552HlpYWPPvss/zmAw8PD08UwIZ4zqVg0GDhdDoxPz/PzKcFAgGzPlvJtoNYFRYUFKCmpibq3pNgY7PZoFQqERcXh+bm5ojIpyEFcWq1mvHSJ9dJsLz0V4KmaQwMDECtVnOiYj8SIVlxjY2NkEgkrBzT1Sddo9FAIBAgNzeX6VyIpjWKwWBAR0dHTArnDz/8MB566CF8+OGHkEql4R4STwDw4vkacKXlMBAPvvn5eXR2dqK4uDimfKXYhHxh1tbWoqioKNzDCRjXCmKVSgWn0+nmxca2GObqTyiVSiEUClk9fixAURR6e3uh1+vR2trKuYobTz7pZHOGKz7pRDiPi4tDS0tLVE1KQ4VWq8XOnTtRXV2NF154ISIWsDw8PDw8a2O320FRlN/PJ8VG5BjRKJwvx9N8msx9iPg1NzeH3t5e3qrQT0wmE1MAVl9fH5Fzt+Vz5PT0dGYdn5GREdTPCUVR6OnpwdLSEmQyWciF+2hgamoKg4ODQS3+WsknnVSlh7tzIRCIcF5cXIz169dH/fcCgaZpPProo3jwwQfx7rvvYtOmTeEeEk+ARLV4TtM0bDab38/nasuhzWZjhHStVrvqFzAJBKmpqeGTtP2ApmkmlDFaveFImyG5pkwmk1ubYaD2PjRNY3BwECqViq928BOKotDV1QWz2QyZTMZ5yyXS3swln3S73Q6FQoGEhAQ0NzdH5OIr3CwsLOCCCy5ASUkJXn755YieyPPw8PDwuBOIeO5abCQQCDhvaxgMaJqGTqdjhHSbzYbU1FQYjUbU19fzVoV+oNfrmYr96upqzqzFA8Fut7vNkYkFUF5eHoRCIaufHafTic7OTthsNshkMn7e5gfEI76lpQUikSgk5yRWvmRtvrS0hKysLOY6iSSfdFfhvLKyMtzDCRk0TeOJJ57Az3/+c/z73//GySefHO4h8bAAL56v8LxIaTkkX8DEgy85ORn5+fnIy8uDWq3GsWPH0NTUFJWib7AhLW5E9M3MzAz3kEKC65c1aTMkVTS+WnHw1Q6BQya+drsdMpks4ip9XSspyGKStCSGyifdbrdDLpcjMTGRF879RKfT4atf/Spyc3Oxe/duzm/g8PDw8PD4hr/iOVe6dLmE0+lET08PszazWCxMh2ekV5GGCq1Wi87OTqxfvx5lZWVReV0RCyBSbUzTtFvgaCDzVVI0QroteYs93yEFdOHumrZarW6dCyTDjGy4cPWzEcvC+T/+8Q/ce++9eOutt/CVr3wl3EPiYQlePPfwHNdgUC4L58shntZzc3OYm5sDTdMoKCjAunXrkJOTEzGvgws4nU50d3fDZDJBKpXGrOhLvqxJqEl6ejojpGdmZq56TTkcDnR1dfHVDgFAbEYAREWw5WqJ8/5szngDEc6TkpLQ3Nwck9VwgbK0tISLL74YaWlp2LNnT8zeD3l4eHiiGYfDwRQOeQsvnJ8Imf9arVa0tLQw1eeuhSmB5FjFAqRzuq6uLmYq9pd3LlitVqbYJC8vz6fiGavVCrlcjtTUVDQ2NvJFIz5C7EYnJychk8mQlZUV7iExLPdJB8DahgubGAwGHD58GCUlJTEnnP/P//wP7rzzTrz55ps4/fTTwz0kHhbhxfNlj4/0CSAJVKFpGmVlZcxuNk3TzCQtVOGQkQp5DwUCAVpaWiKu0jdY2O12JnB0rTZDm83mZpER6aJvOCDvYTRXS6/kk85W4rzdbkdHRwdSUlLQ1NTE3/f8wGg04pJLLkFcXBzefvvtiGoV5eHh4eHxHl/Ec9Kly0V7y3BisVigUCiQlJSEpqYmj2sIi8XCCKSLi4s+5VhFO8Quc2xsLKY7p4ltB7lODAYDcnJymGKT1TZcTCYT5HI5hEIh6urq+Lmvj9A0jaGhIczMzKC1tZXTdqMURUGn0zEbc1arlbFezc3NDVuXaCwL5y+//DJuvfVWvPrqqzjnnHPCPSQelolq8Rw4vvPqDdEgnBuNRigUCmRlZbkFqtA07RZm43A4kJuby9xYo1GU8xcSSpORkYGGhgb+vVkBiqKYXe/lbYZpaWno6upCeno6Ghsb+UmbH5CKkbS0tJh5D10rKdRqdcA+6Tabza3qJhbeQ7Yxm8247LLLYLPZ8O9//ztmrKt4eHh4YhFvxfNYDAb1Br1eD6VSidzcXGzcuNGreYcvOVbRDslImpubiym7TG8wm83M/HhhYQEZGRluGy7kOllaWoJcLo8qj/hQQixbNRoNWltbg9IRGyxcfdLVajX0ej2ysrKYtZTrdRJMlpaW0NHRgdLSUqxfvz7o5+MSr7/+Om666Sb87//+L84///xwD4cnCES9eG6z2bDWS+RqMKgvzM/Po7Ozk9nhW+k1kHBIIqRbLBY3IT2Wq6x1Oh2USiU/4fARsjmjVqsxOzsLq9WKlJQUVFZW+txmyHN8gtzR0RHTFSOB+qTbbDZ0dHTE1OYD21gsFnzjG9/A4uIi3nvvPWRnZ4d7SDw8PDw8QcTpdMLhcKz6mOX2lvz363HUajW6u7tRUVGB8vJyv9YQJGyddHgmJSUxAikb3XhchnjEGwwGPiNpDWw2m1vgaHJyMiQSCVJTUzE0NBTQNRjL0DSNvr4+LCwsoLW1NeKvwXD4pMeycP7WW2/huuuuw3PPPYeLL7443MPhCRIxLZ5HUjDoakxNTWFgYAAbN27EunXrvH4e2aGcm5uDSqWC0WiESCRiAkdjyaOaTHorKytRVlYW7uFEJDqdDnK5HPn5+UhOToZarfapzZDnePeIXC5nqpYi8X7ENqv5pHtKnCfCeXp6OhoaGviFvR/YbDZcffXVmJmZwfvvvw+RSBTuIfHw8PDwBJm1xPNo6NINBpOTkxgaGkJdXR0KCgpYOSbJsVKpVEw3HhHSc3JyompuY7fbGcvRlpaWmFp/Bgq5TiYnJzE/P4/4+HgUFBQw/tfRdJ0EE4qi3DZvom29Sq4TspYCwBRPsuWTToTzsrIyVFRUBHy8SOKdd97BNddcg6eeegqXX355uIfDE0RiVjyPhpZDmqYxPDyMY8eOobm5OWCBw2QyMRXpsRRmc+zYMQwODqK+vp61SW+sodVq0dnZiaqqKpSWljI/J22Gy30dQ9k+FimQRPLCwkJs2LCBf29WYDWf9JSUFMjlcmRmZqK+vp5fNPiB3W7Htddei9HRUXz44YfIzc0N95B4eHh4eELAauK5a8V5JK6ZggFN0zhy5AhmZmbQ0tICoVAYlPNQFIWFhQVmjUasEkmOVSRbTJrNZigUCqZTMJJfS7iYmZlBX18f6uvrkZSUxKy77Ha7W9cm3wnsGafTie7ublgsFshksqjfvHHtGFer1bBYLBCJRMxayh+f9FgWzvfu3YsrrrgC//3f/42rrrqK/26McqJePLfb7YxATnCtnBAIBBEpsDidTvT29kKv10MqlbIeMLM8zCYrK4sR0iPJ/2s1SJL2xMQEWlpakJOTE+4hRSSzs7Po7e1FXV0dCgsLV3wcaTMkvo4pKSmMkB7t7ahrodPpoFAoUFpaioqKiph+L3xhuU+60+lESkoKqqurOZU4Hyk4HA7ccMMN6O3txb59+yCRSMI9JB4eHh6eEOFJPOeDQT3jajMilUpDtjaiaRo6nY5ZoxFbO2K/mZCQEJJxsMHS0hIUCoVPHvE87kxMTGB4eBjNzc1u4ao0TWNpaYkR0kl3uWuxCc/xz7FSqYTT6YRUKo3JDQYSTOuvT3osC+cff/wxLrvsMvz5z3/Gddddx383xgAxJ55HQ8uh1WpFZ2cnAISkvc1mszGTtPn5eSbMJj8/P2KrhymKQn9/P+bn5yGVSjmdpM1lSKtqU1OTTxWqTqeT8etzbUcl4ZCxNIFeWFiAUqnE+vXrecsgP7FYLDh8+DBSU1ORnp4OjUYDq9UKsVjMTACjvZIkUJxOJ7773e/i0KFD2L9//6obYTw8PDw80QdFUbDb7cx/R0OXbjCwWq1QKpWIi4tDS0tL2AQ3YmtH7DfNZjNEIhEzn+byvIdkdRHBjb+ufIMUgE1OTnrV9WAymRghXafTMQIpCRyNRRwOBxQKBQBAKpVG1MZTsLBarcz6XKvVIjk52c0nffn6XK/XQy6Xo7y8HOXl5eEZdJj47LPP8LWvfQ2/+93vcPPNN/P3sBghpsTzaBDODQYDFAoFEyYY6spKu93uFmZDqoclEgmysrIi4j11OBzo6uqC1WqFVCrld9/9wLVqXyqVBtSqStpRyaTO6XS6+bBF82SG2N1UV1ejuLg43MOJSIhwnpOTg7q6OggEAibPgVRSrOWTHutQFIXbbrsNBw4cwL59+1BSUhLuIfHw8PDwhBhX8ZwPBvUMWYeROQeX3hcy71GpVFhaWkJOTg4jpHNprUM6Vn3N6uI5Dk3TGBwchEqlgkwm87kAzGazMWuu+fl5pKamMkJ6pKzlA8Vut0MulyMxMRHNzc18p6oHVvJJJ376JpMpZoXzQ4cO4cILL8Qvf/lL3HrrrTHxmeE5TkyI52TyF+kth1qtFl1dXUyCcbhfA6keJkJ6QkICI6QHK8U5UKxWKxQKBfNlGc3CbLCgaRoDAwNQq9V+TdrWOrZer2cmdaSKhkzquFxF4ysqlQrd3d1r2t3wrIzZbEZHRwdEIhFqa2tXvOdYLBbmXrXcJz3WLYMoisKdd96J9957D/v27Yu5CTAPDw8Pz3GIeE7WTE6nM2LXTMGAa+uw1VieOcQV+83x8XGMjIz43LHKcxyKotDb2wudTofW1lakpqYGdDxif0jW8vHx8cyaK9qCaQk2mw0dHR1ITU1FU1NTVL5GtiF2Ua7rcwDIy8vDxo0b/fJJj1QUCgXOP/983Hfffbjjjjs4/T3Awz4xIZ67Vp9HasshCbWsra1FUVFRuIdzAhRFYX5+nql4EAgEbmE2XPhiMhqNkMvlnKwWiRRIGvnS0hJkMlnAk7a1WO7Dlp2dzVTRRLL3Pgn3aWxs5H2l/cRsNuPw4cOMV6a393VXn3SNRgOBQMB0OkR68JavUBSFe++9F7t378b+/ftRWVkZsnN//PHH+P3vf4+Ojg7MzMzg9ddfx0UXXcT8nqZp/OxnP8Pf/vY3LC4u4pRTTsGuXbuwYcOGkI2Rh4eHJ5agaRpWqzXiu3SDwdTUFAYGBji7DluNlew3JRIJMjIyQvI3pmkaQ0NDmJ6ehlQqRXZ2dtDPGW04nU63zmm2BUvXYFqSI/T/27vv+KjKfH/gnxA66ZWAQEKAABLSKKIgohESUs4E1xVZhVXW67qrXgvXi+5VcHddBF2uit29LqzlKmQmhV4TkaJoGiWEFjrJpJdJMsnMnOf3h3fOj0TAkHamfN6vl3/skE2+hJPMcz7neb5fRzsJbDQakZubCzc3N0yYMIFZQAfU1dUpJ37NZjNqa2vh7u7eqg2Qo75vHDlyBHPnzsWSJUuwdOlSh/170vU5dHguhMCbb76Je+65B6NHj7bLUOTqxUZERIRdDLWUZRk1NTXKQs1isSi/UNUa4lddXY2CggLccsstCA0N5S+7DjCbzSgoKIDZbEZUVFSP7wI3Go3K0bGrF//+/v5wd3e3m3/TS5cu4eTJkz8b7kPt19jYiJycHPj7+yMsLKzD//bW31XW68qZ+qTLsoxXXnkFX331FbKzszFmzJge/fpbt27F/v37ERMTg3nz5v0sPF+5ciVWrFiBdevWISQkBC+//DKOHDmCwsJCmzp+TkTkKHbs2IGamhrMmjULAwcOtJt1VXcSQuDMmTO4ePEiIiIi4OPjo3ZJndK2/Wa/fv0QGBjYrS07rt4tHR0dbdebX9RiMpmQn58PAD3SZ996EtgapNtTP/3rsZ5WvbrNI92c2tpa5ObmtprTZW0D1N4+6faqsLAQ8fHx+OMf/4hly5b12PXDzUa2xaHD89raWjz00EPYuXMnQkNDIUkSUlJSMG7cOLv4QbZOcq+vr0dUVJRd9um9+s1Xr9ejublZeYrt7+/fI0+x9Xo9jh07htGjR7OXbwe1tLQgLy8PvXv3tol2N9bFv3X3cJ8+fZRrypbfqM+fP4/i4mJERkbaxYMwW2QNzgMCAjBmzJguW7xY+6RbjyQ6cp90IQT++te/4tNPP0VWVhbGjx+vaj0uLi6tFoNCCAwZMgTPP/88lixZAuCn9/PAwECsXbsW8+fPV7FaIiLH9OGHH+L1119HVVUV4uLioNFocO+99zrU+9/NsFgsOHbsGOrq6hAZGdmlbQptgbWnsTUgdXV1bdV+syvW0iaTCYcPH1Zt440jaG5uRm5uLvr374+JEyeqsgnN3k8CW0+fd3bTjTO7VnDelsViUToRVFRUQJZl5T7Knk8vnDhxAvHx8Xj00Ufx2muv9ej1w81GtsWhw3OrmpoabNy4ETqdDtu3b8ctt9yiBOm22uvq6knuERERDrHYsE6Ft+5Ib2hogK+vb7c+xb5w4QJOnz6N8PBw+Pv7d/nndwZNTU3KEbfw8HCb+3mxvlFbQ08ArVoG2cKJE+uA1YsXLyI6OhoeHh5ql2SXGhoakJOTg8DAwC4Nzq/F2ifdetLBOhzZ3vukCyGwatUqvPfee9izZw8mTpyodkk/C8+Li4sRGhqKvLw8REZGKh83c+ZMREZG4u2331anUCIiByfLMn744QdotVqkpaXhypUrmD17NjQaDeLi4uDu7q52iT2ipaUFBQUFEEIgMjLSIe7DbsTaskOv16O8vBxCiFanhjuy9jcajcjLy0O/fv0wceJEuw3O1GTdLe3l5WUzLUebm5tbDRwdNGiQcq3Y4klgg8GAnJwcBAUFYfTo0TZXnz1oT3De1tV90svLy9HY2KjMMbO1IcY3cvr0acTHx2P+/Pl44403VP0Z5GYj9TlFeH61+vp6bNmyBVqtFlu3boWfnx8kSYJGo8GkSZNs4k2pvr4e+fn5Dt+buzunwrO3XtcwGAzKk/qb6SutFiGE0jKovLwcLS0tygMaPz+/bj/meL2aTp06hZKSEsTExDjczqWeYg3OBw8e3OOL3+v1SbfupLCFBzTtIYTA22+/jTfffBM7d+5ETEyM2iUB+Pli8MCBA7jjjjtw5cqVVsN0f/3rX8PFxQVff/21SpUSETkPWZZRUFCA1NRU6HQ6nDt3DrGxsZAkCXPnzrXrB8k30tDQgLy8PLi7u2PChAl28x7fVa5eS5eVlcFkMsHPzw+BgYHt3j1qMBiQl5enDHR31HvZ7lRfX4/c3FwMHjy42zeMdJTJZGo1cLRPnz5KkG4LJ4Hr6uqQm5uLYcOG2fyQX1tlDc5DQ0MxfPjwDn8e6+ne8vLyVn3S/f39e2z2ws06d+4c4uLikJycjHfeeUf165mbjdTndOH51RobG7Ft2zZotVps3rwZHh4eSE5OhiRJuO2221RZLFVUVODIkSN2Mcm9KxmNRmWR1tmp8NahlnV1dXbb7sYW1NTUID8/324XHFefdCgvL4fBYOjSBzTtreH48eOorKxETEyMXRxttEXWXSNDhgzBqFGjVL0W7bVPuhAC77//Pv72t79h27ZtmDp1qtolKRieExHZNiEEjh07pgTpJ06cwKxZsyBJEhITE+Hj42N368Rrsc5IGjJkCHep4qd/9/r6euUerampqdWp4WttSqmpqUFeXh6GDRvGOVMdZP0ejhgxAiEhIXbxPZRlWWnZYT29cPXA0Z7OVazfw5CQEAQHB/fo13YUXRWct9XS0tKq/Wrfvn1trv3qpUuXMGfOHMyePRsffPCBTdTE+yX1OXV4fjWj0YidO3dCq9UiMzMT/fr1Q1JSElJSUnDHHXf0yFGzixcv4uTJkxg/fnyrHwBn03YqvJubmxKk/9IEZ5PJhIKCAlgsFvbW64SKigocPnwYo0aN6tI3SzU1NTUpC7qamhq4u7srb9TdsRtclmUUFhYqA5IGDBjQ5V/DGViD86FDh9rcTdjVfdKtfSCtD/5sqU+6EAL/+Mc/8Morr2DLli2444471C6pFe6kICKyH0IInDx5ElqtFjqdDgUFBZgxYwY0Gg2SkpIQEBBgU+/V7VVSUoLjx49jzJgxuOWWW9QuxyYZDAaUl5dDr9e32pQSEBCAfv36oaysDEePHuWcqU6w3oPZ8/fQ2rLDej9v3WhiPQnc3ffnVVVVyM/Pt+vvodqsDx+6Ojhv6+r2q+Xl5ZBlWTnd6+fnp0q7p5KSEsTFxWHGjBn45JNPbOb0EcNz9TE8v4aWlhZkZWUhNTUVGRkZAICEhASkpKTgzjvv7PJf+NZFaElJCSIjI+Hl5dWln9+etZ0Kb+07HBgY+LO+akajEbm5uRgwYIBqA1UcQUlJCQoLCx36IY51Mrj1AY31ugoICICHh0enb/pkWcaRI0fQ2NiI6Oho9OvXr4sqdy719fXIyclRdi/ZOmsfyKv7pFuPr6p1vF0IgX/961944YUXsHHjRtx11109XsMvuV4PvyVLluD5558H8NPR24CAAPbwIyKyIdaZLtYe6T/++COmTZsGSZKQnJyMIUOG2HyQLoTA2bNncf78eYSHh8PPz0/tkuyCdVNKWVkZamtr0b9/fxiNRoSFhTGw7KDS0lIcO3bMoe7BrBtNrBuY6uvr4eXlpWw06erNRdaHD2FhYRg6dGiXfm5nYQ3OR40a1aM/y0II1NXVKdeKGn3S9Xo94uPjMWnSJKxbt86m8iRuNlIfw/NfYDabsXfvXqSmpiI9PR1GoxEJCQnQaDSYNWtWp3+ILRYLjhw5goaGBkRFRbGtww1YLBYlSC8vL0efPn2UwNPV1RX5+fnw8/PD2LFjbeJojT2yDlidOHGi09w8XN3Pury8HK6urkrg6e3tfdPXksViQUFBAUwmE08/dII1OLe2sLI3bfukA2g1cb4nFmNCCHz55Zd49tlnkZGRgXvuuafbv2Z7GQwGnD59GgAQFRWF1atXY9asWfDx8cHw4cOxcuVKvP76662mxx8+fJjT44mIbJQQAhcvXoROp4NOp8OBAwcwefJkSJIESZIwfPhwmwvSZVlW2utFRUU5zUDUrmTdBHb58mUMGjQI9fX1N3VqmH5y8eJFnDp1yuHvwaytWsvLy1FdXa1cK13R+9p68mH8+PEYPHhwF1btPNQKzq+lsbFR2exWW1sLNzc35R69O/qkV1RUYO7cuRg/fjy+/PJLmxtyzM1G6mN4fhMsFgv279+v7K6ora1FfHw8NBoNYmNjbzr4NhqNyM/PR+/evREREaHKMEN7JcuyMqBEr9fDYrHAw8MDoaGh8PHxYXh+k6w7hy5evOjUA1ZlWUZ1dbWyqLNYLK369f3Sm6jZbEZeXh6AnwJBW3vTtRfWAT/WXo/2TpZl5fiqtU+6j4+Pcny1u04mbNiwAX/84x+xYcMGxMfHd8vX6Kjs7GzMmjXrZ68vWrQIa9euhRACy5Ytw8cff4yamhpMnz4d77//PsaMGaNCtUREdDOEECgpKUFaWhq0Wi2+/fZbREREKEG6LbRhM5lMOHz4MEwmEyIjI/lgtgOsLQqrq6sRFRUFNze3654a7qrTnY7m6pMPUVFRTnUC3WQyKZuXKioq0K9fv1a9r2/mWrGenA4PD0dAQEA3Vu24bCk4b+vqPumVlZXKcFp/f/8ObXZrq6qqComJiQgJCcHXX39tM5vfuNnItjA87yBZlnHo0CGkpqYiLS0Ner0ec+bMgSRJiIuL+8UeyvX19cjLy4Ovry+nkHdCSUkJjh07hhEjRsBisaCsrAwWi0V5KqnGgBJ7I4RAUVERysvLER0d3S39v+1R26NjTU1NSuB5rcGQLS0tyMvLQ58+fRAREcHrroPq6uqQk5PjsAN+rtcn3fo7q6v6pKenp+Oxxx7D//7v/yI5OblLPicREdHNEkKgoqJCCdKzsrIwbtw4SJIEjUaDsLCwHg9Um5qakJeXhwEDBiA8PJybHTrAbDbj8OHDaG5uRlRU1DWDmqtPDVdUVKB3796tTnc6e5Bu3bVfWlqK6Ohopz75YLFYWp0EdnFxUcJRHx+fG95XXb58GSdOnHD4XfvdyZaD87Zu1Cfd19f3pjek1tTUICkpCYMHD4ZOp7OpdqvcbGRbGJ53AVmWkZeXp0ygv3jxImJjYyFJEubOnfuzp+xpaWlwdXVFeHg4goODnX7h0BFCCJw7dw5nz55FREQEfH19ldevHlDS0tKi7BxWa+iELZNlGUePHkV9fT2HWv6Cq/v11dXVwdPTU9lJ06tXL+Tm5mLgwIEIDw/nw7AOsk51HzlyJEaMGKF2OT3ien3SO7LrxmrTpk145JFH8K9//Qv33XdfN1RNRER084QQqK6uRkZGBrRaLXbt2oXQ0FAkJycjJSUF48eP7/Y1VG1tLfLz8xEYGIgxY8ZwzdYBzc3NyoaRiRMntiuskmUZVVVVyj0aAGUd7Yynhq279mtqahAdHc3WrVeRZRk1NTVKyw6TydRqiOTV15u15WhkZCR8fHxUrNp+VVdXIy8vzy6HJVs3u1nvpRoaGpRBxu3pk15XVweNRgMPDw9kZmZytzbdEMPzLiaEwNGjR7FhwwakpaXh5MmTuPvuuyFJEhITE/HRRx/hzTffxMcff8xQo4OsO6XLyspu+JReCAGDwQC9Xo+ysjJl53BgYGCPTPq2dWazGQUFBTCbzezNfZOMRmOrwBMABg0ahPHjx/NIagc5Y3DelnXXjXWHFnDzfdK3b9+Ohx9+GP/4xz/Y646IiGxabW0tNm7cCJ1Oh23btmHo0KGQJAkpKSmIiIjo8kDV2hM5NDTUJnuw24OGhgbk5eXB09MTt956a4f+jYQQqKmpUYJ0s9ncarOTo5/etFgsOHz4MIxGI6Kjo21qp6utsd7PW6+VhoYGZYhkc3Oz0nLUmdrddCV7Ds6vxdonvby8HDU1NUqfdH9/f7i7u7f6nW8wGDBv3jz07dsXmzZt4gMs+kUMz7uRNeS17kg/efIkXF1d8cQTT+CJJ56Av78/F203yTpgtbGxEVFRUTe1U9q6c7isrAz19fXKU8mAgACnW7RYW4xY++1zR37HNDQ0ICcnB4MGDULv3r1RWVmJvn37KkdSO7pz2NlYjwpab2bp/99YWnfdWPukWxeA1/qdlZWVhQceeADvv/8+Hn74YV57RERkN+rr67FlyxbodDps2bIFfn5+SE5OhkajweTJkzsVpAshcOHCBZw5cwYTJkxgT+QOqq2tRV5eHoYMGYLRo0d3yTrj6jaJZWVlMBqN8PX1VXaOOtpMMJPJhPz8fABAZGSkw/39ultTUxP0ej0uXrwIo9GIQYMGISgoqEtbHzoLRwvO22ppaVE2JVVWVmLnzp0oLS1FcnIyZs6ciYceegiyLGPLli1sW0vtwvC8BxgMBjz44IMoLCzEfffdh2+++Qa5ubm4/fbbIUkSkpOTERQUxKDjF7S0tCA/Px8uLi6dXmw0NTUpi7Ta2lp4eHggMDAQAQEBDt+6pKmpCbm5uXB3d8eECROc7phkVzEYDMjJyUFQUJByA2HtwWZt7wJACdJ/qV+fs7Iu3EaPHm3zPfbUcq0+6cBPYfl9992HyMhI7N+/H7/61a/w1ltv4dFHH+X7CRER2a3GxkZs374dWq0WmzZtgru7O5KTkyFJEqZNm3ZT6ylZlnHixAmUlZUhMjISnp6e3Vi54yovL8eRI0cQGhrarScEr95lbDAYWs0bsvfNTi0tLcjNzUXfvn05H6mDhBA4deoUSkpKMHHiRDQ2NqKsrExpfcjhtO3j6MF5W7IsY+fOnfjiiy+QnZ2NxsZGDBw4EKtWrcK8efN4coHaheF5N7t06RKSkpLg4+MDrVYLLy8vZfeDVquFTqfD999/jylTpiiLwmHDhvGXfRuNjY3Iy8uDm5sbJkyY0KWLDWvPYesbr5ubm/LG62hPIQ0GA3Jzc+Hv74+xY8fyOusg686bYcOGYeTIkdf8PrY9kmoymZSdNG379TkrZ1u4dZXm5mbk5ORg2bJl+PHHH+Hn5wej0YhFixZh1apVPElCREQOw2g0YteuXdBqtcjMzETfvn2RmJiIlJQU3HHHHTdcT5nNZhw5cgRNTU03fWKV/r/Lly+jqKgIt956KwYPHtxjX7ftZqer5w3Z27+ldfOSh4dHh9vdODvrqf6KigpER0e32mluNptbDRzt1auXcq14e3vz+32Vqqoq5OfnIywsDEOHDlW7nB7V3NyMBQsWoLy8HHfddRd27NiBoqIizJw5U9nUylPQdD0Mz7tRRUUFIiIiEB8fjw8++OCaizshBK5cuQKdTgedTod9+/YhKioKkiRBkiSEhIQ4fcBpDSqDgoIwZsyYbv1+mEwmJUivrKzEgAEDlDfetn2y7E1NTQ3y8/NvGPjSL6uurkZ+fv5N9ea+Vr++mxlm4oiceeHWlfbu3Yv/+I//wMCBA1FcXAwASExMRHJyMmbPns0jrERE5DBMJhOysrKQmpqKjIwMyLKMhIQEpKSkYObMma3m9xQXF+OLL77A3Llz2z3UkloTQuDs2bM4f/48IiIiVB3I2NzcrKyjq6ur7Wqzk3XzUkBAAMLCwngP1gFCCBQWFqK6uhoxMTE3fHgiyzKqq6uVe3qLxaL01Pf19XXqTSbOfP9lMpmwcOFCnD9/Hrt374avry8A4OzZs8jMzERGRgYOHjwIvV4PDw8PlaslW8TwvJvt3r0bd999d7veJIUQ0Ov1SE9Ph06nQ3Z2Nm699VYlSO/u4NgW9dQRwWuxPsHW6/WoqKhAnz59EBAQgMDAQHh6etrVv0VFRQUOHz7M1hidVFlZiYKCgk7vlL5W2yBrexdnCDut38exY8diyJAhapdjt/Lz85GQkICXXnoJS5YsgSzLOHjwIDIyMpCRkYGLFy9i7dq1eOCBB9QulYiIqEuZzWZ8++23SE1NRXp6OhobG5GQkABJkuDu7o6HHnoI06dPx2effcb2GB0gy7KyyzcqKgru7u5ql6Swp81O7TmtSjcmyzKOHj0Kg8GA6Ojom9p0ZO2pb71eGhsb4evre8MZQo7KmYNzs9mMRx99FEVFRcjKyoK/v/81P85gMNj8wzhSD8NzGyWEQFVVlRKk79q1C6NHj1Ym0I8bN87h33wvXbqEEydOYMKECQgMDFS1lra9rF1cXOzmKFhJSQkKCwt7/KiloykrK8ORI0cwfvx4BAUFddnnbWlpadU2aMCAAUqQ7oj9+hicd42jR48iPj4ezz33HF566aWfXSdCCJw4cQJeXl78uSciIodmsVhw4MABaLVafPnll6ipqcGdd96JRx99FLNnz8bAgQPVLtGuWCwWHDlyBI2NjTcdVvY0i8WCiooK5R7NutkpICAAXl5eqq6jrWveUaNGsRVEB1mvRaPRiOjo6FanSzrCOkOorKwMdXV18PT0VO67HPn3hDU4d8b7L4vFgscffxx5eXnIysrifRF1GMNzOyCEQG1tLTIzM6HT6bBjxw4MGzYMkiRBo9Fg4sSJNh3e3iwhBM6cOYOLFy8iMjIS3t7eapfUivUomHXnsBDCZodCXrhwAadPn0ZERIRyNIlunvUBRHh4OAICArrt61hPO5SVlaGiogKurq7KtWXrD2naw3oCYty4cV36AMLZHD9+HPHx8fj973+PV1991eEesBAREXXEBx98gCVLluA///M/UV9fj7S0NJSWlmL27NmQJAlxcXE2tYPaFrW0tCA/Px8uLi6IjIy0q3Y3siwr62jrZqer79F6ch2t1+tx9OjRLt9040wsFgvy8/NhsVgQFRXV5ddi27lngwYNUq4XWzvB0BnOHpw/9dRT2L9/P7Kzs51uxz11LYbndqi+vh6bN2+GVqvF1q1bERAQgOTkZKSkpCAmJsauAzZZlnH8+HFUVVUhKirK5o/NWB9slJWVQa/Xw2QyKT3V/Pz8VOupZn0AcenSJURFRcHT01OVOhzBpUuXcPLkyR5/AHH1Q5ry8nK779dXXl6Ow4cP8wREJ508eRLx8fFYtGgR/va3v9n173siIqKuIMsyXnjhBaxduxbp6emYPn268np+fj5SU1Oh0+lw/vx5xMbGQpIkzJ071+7aMHY361BLNzc3TJgwwaY2BN0sWZZRU1OjbHayWCxKMOrr69utfzfrvUN4ePh120PQjZnNZuTl5QEAoqKiuv2+x2w2KycYrO1ardeLl5eX3a63nfnEryzLeOaZZ7Bnzx5kZWX1eAtgcjwMz+1cQ0MDtm3bBq1Wi82bN8PT0xPJycnQaDSYOnWqXS16zGYzDh8+jObmZkRFRdn0EcFrEUKgvr5eWaQ1NTXB19dXGQrZUzs3hBA4fvy4Monc1h9A2LLz58+juLhY9RMQ1n591mvLaDTCx8dHubY6e4Sxu1mDc1towWTPiouLERcXh/vvvx9///vf7XYhT0RE1JWWLl0KnU6HzZs3Y/To0df8GCEEjh49itTUVKSlpeHEiROYNWsWNBoNEhIS4OPj49RBel1dHfLy8hAYGOhwQy2vXkfr9Xo0Nze32uzUVfdoQgicO3cO586dU/3ewZ6ZTCbk5uaiT58+iIiI6PE8Q5blVu1ahRCtNjDZS77i7MH5Cy+8gE2bNiE7OxsjR45UuyRyAAzPHUhTUxN27twJnU6HzMxM9O/fH0lJSUhJScHtt99u0ztVm5ubkZeXp7xJ2nKt7dXQ0KAs0gwGA7y9vZUefN01nESWZRw5cgQNDQ0236PQlgkhUFxcjIsXL9rkzn3rtVVWVob6+np4enoq19aNps+rwdorvrtb3ji68+fPIy4uDomJiVizZg2DcyIiov9z6dIlDBgwoN0nBK1zQbRaLXQ6HY4cOYIZM2ZAo9EgKSkJ/v7+DhUe/5LKykocPnwYISEhGDFihEP/3YUQaGhogF6vR1lZGRoaGpQNKQEBAR3ekCKEwKlTp1BSUoLo6Gi2B+qglpYW5Obmon///jbRmtZ6ytza3sVoNCqb4/z8/Gx2A5M1OHfGVpmyLOO//uu/sGHDBmRnZ1/3gSrRzWJ47qBaWlqwZ88eaLVapKenw8XFBYmJiUhJScGMGTNs6he9wWBAXl4evL29MX78eNXfJLtDU1OTEnbW1tZ2S9hpNptRUFAAs9mMqKgom/o3tidXL35jYmJsfue+0WhUFnTV1dVwc3NTjhm6ubmpegNk7ffI4LxzLl++jDlz5iA2NhYffvihQ/6OJCIiUoN1w4Q1SM/JycG0adOg0WiQnJyMoKAghw6TrXN9xo0b53S7UwGgsbFRuUezDpAMDAyEv79/u+/Rrm47GhMT49CDJ7uT0Whs1TbI1ta71gcv1vuu+vp6eHl5KSeBbWUDkzMH50II/PnPf8a6deuQnZ2NsWPHql0SORCG507AbDbjm2++QWpqKtLT09Hc3IzExERIkoS7776723ZBt0d1dTXy8/MxbNgwhIaGOvTi1Kq5uVlZpFnDzsDAQAQEBGDQoEEd+pzWp/R9+/bFxIkTHWLnvhqEECgqKlJa3nT030MtJpOpVb++fv36terX15M/X3q9HseOHWO/x04qLS3FnDlzcMcdd+B//ud/7OaoKBERkb0RQuDChQvQ6XTQ6XQ4ePAgpkyZAkmSIEkShg0b5jD3KkIIpT1hT8/1sVVtN6S4u7srm52ud09gsVhw5MgRNDY28tRvJzQ1NSEnJ0fZTGcPP2e2uIHJ2YPz119/HR9++CGysrIwYcIEtUsiB8Pw3MlYLBbs379f6fdXX1+P+Ph4SJKE2NjYHn1Sbg3XRo8ejWHDhvXY17UlJpMJ5eXl0Ov1qKqqwoABAxAQEIDAwMB2v+lah/u4u7vb5FN6eyHLMgoLC1FTU4OYmBib2T3QURaLpVW/PgDKgs7Hx6dbQ9jS0lIUFhYyOO+ksrIyxMfHIzo6GuvWreNDMSIioh4ihMCVK1eQlpYGrVaLffv2ITIyUgnSR44caRcB37VY29bo9XpERUXBw8ND7ZJsTktLCyoqKn52jxYQEAB3d3e4uLjAbDYjPz8fsiwjKiqqx+ZbOZrGxkbk5OTAz88PY8eOtcufK1vYwFRRUYHDhw87bXD+3//93/jv//5v7N69G5GRkWqXRA6I4bkTk2UZ33//vRKkl5eXY/bs2dBoNJgzZ063tqu4cOECTp8+zXDtKm2nfPft21dZpHl6el7zTddgMCA3NxcBAQEON9ynJ1l7xVt3jah5GqM7yLKM2tpa5cSDyWSCn58f/P39u3RQEvDT8d/jx49j4sSJ8PPz67LP62wqKiqQkJCAsLAw/O///i9vyIiIiFQihEBZWRnS09Oh1WqRnZ2N8ePHQ5IkaDQajBkzxm7W4BaLBUePHoXBYEBUVBRbjLRD23u0Pn36wM/PD5WVlRgwYAAiIyN5MrCDDAYDcnJyEBQUhNGjR9vNz9GNqLGByRqcjx8/HoMHD+7yz2/LhBB499138frrr2PHjh2YPHmy2iWRg2J4TgB+Ctdyc3ORmpoKnU6HS5cuITY2FhqNBvHx8fDw8OiSNzNrP+krV67Y5CBGW2F909Xr9SgvL0evXr2UHeleXl7o1asXampqkJeXh+HDh9v17he1WSwWFBQUwGQyOUWveCEEDAaDEqRbByX5+/vD39+/U8dNr1y5gqKiIh7/7aTq6mokJiZi+PDh2LBhg8Nfk0RERPZCCIGqqipkZGRAp9Nh165dCA0NhSRJSElJwbhx42z2FKjJZEJ+fj6EEIiMjOT6ogMsFgtKS0tx4sQJyLKMPn36KJudvL29bfbf3hbV1dUhNzcXw4YNc9h7WSEEampqlCC9paWl1cDRrtgc4+zB+ccff4xXX30VW7duxbRp09QuiRwYw3P6GVmWcfToUSVIP336NO6++25IkoSEhAR4e3t36M3N+nnr6uoQHR3NnQ7tJMsyqqurlbBTCAF3d3fU1NRg1KhRGDFihNol2i2z2Yy8vDwAQFRUlFO2xWhsbFT69dXW1sLDw0PZHXEzPd8vX76MEydOIDIyEj4+Pt1YsWOrra1FcnIy/P39kZaW5nCnIIiIiBxJTU0NNm7cCJ1Oh+3bt+OWW25RdqRHRETYTJhqHcY4YMAATJw4kTulO6ihoUFpMRIWFtbqZKfFYlHW0L6+vvwe34B1E1hISAiCg4PVLqdHXL2Bqby8HAaDAd7e3srA0Y5sYCovL8eRI0dw6623IjAwsBuqtl1CCKxduxYvvvgiNm3ahDvvvFPtksjBMTynG7IOULQG6ceOHcPMmTOh0WiQmJgIPz+/dgXpJpMJBQUFsFgsTrG7t7sIIXDmzBmcPXsWffr0gSzL8PPzQ2BgIHx9fZ0y/O0ok8mE3Nxc9OnTBxEREVzg4qf+jtYg/er+jv7+/jc8fXLp0iWcPHmSwXkn1dfXQ6PRwM3NDZmZmXbfd5+IiMiZ1NfXY8uWLdBqtdi6dSv8/PyUIH3SpEmqBenWNo/WntK2Eujbm9raWuTl5eGWW25BaGhoq3WxEKJVkN7c3Aw/Pz9lHc17tP+vqqoK+fn5Tj33DPhpbpn1vqumpkYZUOvv749Bgwb9Ysbi7MH5559/jiVLliAzMxOzZs1SuyRyAgzPqd2EEDh9+jS0Wi10Oh3y8vJwxx13QJIkJCcnY/Dgwdf8Jd/Q0ICCggLudOgC1l7xERER8PHxQX19vbJIa2pqUo6B+fv7s0fyDTQ3NyM3NxcDBw5EeHg4byKuwWw2o7KyUunv6OrqqlxbVx9LtQbnUVFR8Pb2Vrlq+9XQ0ID77rsPvXr1wubNm29q1z8RERHZlsbGRmzbtg1arRabN2+Gh4cHkpOTIUkSbrvtth67H6qqqkJBQQHbPHaSNfANDQ39xVO/12qRePU9mjNvIrO2GAkLC8PQoUPVLsdmWAfUlpWVobKyEv3791eul2vNPnP24Hz9+vV46qmnoNVqMWfOHLVLIifB8Jw6RAiB8+fPK0H6oUOHMHXqVGVReMstt8DFxQXff/89Hn30Ubz//vuYMWMGQ8oOsu44v3Tp0nV7xV+9SDMYDPDx8VHedNn64f9rampCbm4uPDw8cOutt/KabIe2rYNkWYa/vz969eqF0tJSREdHw8vLS+0y7VZTUxPuv/9+tLS0YOvWrXB3d1e7JCIiIuoiRqMRO3fuhFarRWZmJvr164ekpCSkpKTgjjvu6LZdyXq9HkePHkVYWBhuueWWbvkazsD6fRw3bhyGDBly0///xsZGZQ1dV1cHLy8vpU96Z2YN2ZuysjIcOXIE48ePR1BQkNrl2CyLxaJsYLLOPrt64GhlZSUOHz6MCRMmOF1wDgA6nQ6PP/44vv76ayQmJqpdDjkRhufUaUIIXL58GTqdDjqdDvv370dUVBRiYmLwr3/9C4sXL8bf/vY3hpQdJITA8ePHUVlZiejo6HbtSG1qakJZWRn0ej3q6urg6emJwMBA+Pv7O3UriMbGRuTk5MDX1xfjxo3j7psOEEKgrq4Op0+fRlVVFVxcXODn56cMHHXm3TQdYTQa8eCDD6K2thbbt2/nEGUiIiIH1tLSgqysLKSmpiIjIwMAkJCQgJSUFNx5551dto6ynlYNDw+Hv79/l3xOZ2Sd6TNhwgQEBAR0+vMZjUaUl5dDr9e3atVxs7OG7E1paSmOHTuG8PDwLvk+OgtZln82cFSWZQwfPhyhoaFO1w5o06ZNeOSRR/D5558jJSVF7XLIyTA8py4lhIBer8eLL76Izz77DKNGjcKAAQOg0WggSRJGjx7NwPImWCwWHD16FA0NDYiOju7Q7gTrIq2srAzV1dVOs0hry2AwICcnB0FBQbwOO+n8+fMoLi5GdHQ0XF1dleurvr5e2U3j7A9q2qOlpQUPPfQQSkpKsGvXLra9ISIiciJmsxl79+5Famoq0tPTYTQakZCQAI1Gg1mzZnVo3S+EwKlTp3DlypXrnlal9jl37hzOnj2rtMvsalfPGqqsrMSgQYOUezQ3NzeHuVexPoCYOHEi/Pz81C7Hbun1ehw5cgT+/v5obGxEQ0ODU50037ZtGx5++GH885//xK9//Wu1yyEnxPCcupQQAitXrsTf/vY3bNiwATExMcjIyIBWq8Xu3bsxZswYZXAOd/7emNlsRn5+PmRZRmRkZJfsRLH2U9Pr9Q69SGurrq4Oubm5GDZsGPs9dpL1RiI6OvpnN2RtH9S4ubkpxwwd+frqCJPJhEWLFuHs2bPYs2cPfH191S6JiIiIVGKxWLB//35otVqkpaWhtrYW8fHxkCQJ9957LwYOHPiLn0OWZRw7dgy1tbWIiopyqk0yXck65+vy5cuIjo6Gh4dHt39Ns9ms9LyuqKhA3759lXu0a/W8thcXL17EqVOnEBkZ2S0PIJyFteXN1Tv3GxoaUF5ejvLyctTW1sLDw6PVwFFHsmfPHsyfPx8fffQRFixYoOrPw/Lly/Hqq6+2ei0sLAxFRUUqVUQ9heE5dRmLxYKnnnoK6enp2LJlCyIjI5U/s04gz8zMhFarxY4dOzBixAglSOfQxtZaWlqQm5uLvn37YuLEid1yJMtRF2ltVVdXIz8/HyEhIQgODla7HLt29uxZnD9/vl03EiaTqdX11a9fP2VB5+Xl5TDXV0eYzWb87ne/w7Fjx5CVlaXq8VUuAImIiGyLLMs4dOgQUlNTkZaWBr1ejzlz5kCSJMTFxcHNze1n/5+amhqcOnUKFosFUVFRDr8Ltbt0pF1mV7NYLKiqqlL6pPfq1Uu5R/P29rabe2brhpuoqCjORuqEawXnbTU3NytBemVlJQYOHKjcd3l4eNj1fdfevXtx//3345133sFvf/tb1f8uy5cvR2pqKnbt2qW81rt3b56qcAIMz6nL5Ofn45FHHkF6evovTiGvq6vD5s2bodVqsW3bNgQGBiI5ORkpKSmIjo62m0VBd2hqakJOTg48PT17bKBl28Ekrq6uyiLNy8vLbv89KisrUVBQgDFjxnBQUicVFxfjwoULiImJuemBltbry7qoc3FxUXqk+/j4wNXVtZuqtj0WiwVPPPEEfvzxR2RnZ2Pw4MGq1sMFIBERke2SZRl5eXlITU2FTqfDxYsXERsbC0mSMHfuXHh4eODChQtITk6GRqPByy+/7HR9kLuKLMs4cuRIp9pldkdN1dXVSpAuhGg1PNIW19BCCBQXF+PixYs9tnPfUbUnOG/LukGuvLwcFRUVyn29v7+/XT18AYADBw5g3rx5eOONN/Bv//ZvqgfnwE/3Tunp6cjPz1e7FOphDM+7WHBwMM6fP9/qtRUrVmDp0qUqVdSzZFm+6V/IDQ0N2Lp1K7RaLbZs2QIvLy9lAThlyhSbXBR0l/r6euTm5iIwMBBhYWGqvEFYF2l6vR7l5eWtFmm+vr5284bLie5d58yZM7h48WKHgvO2rINvrO1dTCaTMnDUz88Pffr06aKqbY/1dM6+ffuQnZ1tEw90uAAkIiKyD0IIHD16FBs2bEBaWhpOnjyJO+64A8eOHUNUVBS+/PJLmwh87ZHZbEZBQQHMZjOioqK6bHBrV7Ke5LYG6S0tLfDz80NAQAD8/Pxs4qGJted+SUkJYmJirnlKgtpHr9fj6NGjmDhxYoeH/sqyjKqqKuW+S5ZlZQOTn5+fTecshw4dgkajwV/+8hc8+eSTNhGcAz/dO73xxhvw9PRE//79MW3aNKxYsQLDhw9XuzTqZgzPu1hwcDAWL16Mxx57THnN3d3d4fpOdZempibs2LEDOp0OGzduxIABA5CUlASNRoPbb7/dJhYF3aWmpgZ5eXkYMWIEQkJCbOINQgihTPguKyuD2WxutUiz1TfckpISFBYWcqJ7J129c2TSpEldvgAWQqC+vl5Z0Dny4BtZlvHcc89h586dyMrKspkWQlwAEhER2R8hBL766iv87ne/w7Bhw3DmzBnMnDkTGo0GiYmJ8Pf3t4l7CXvQ0tKCvLw89O7dGxEREXZxvymEgMFgUO7RGhsbW62h1Qj/hRAoKipCRUWFai1vHIVer8exY8cQHh7e4eC8LSEE6urqlGvGaDSqfs1cT25uLpKSkvBf//VfeO6552zqd9nWrVthMBgQFhaGkpISvPrqq7h8+TKOHj3a6U1mZNsYnnex4OBgPPPMM3jmmWfULsXutbS0YNeuXdDpdMjIyICLi4sSpN95550OtUO1vLwcR44cwejRozFs2DC1y7mma73hXh2k28q/x6VLl3Dy5ElOdO8kIQTOnDmDy5cv99jOkcbGRqV1kCMNvpFlGUuXLkVmZiaysrIQGhqqdkkKLgCJiIjsT2ZmJhYsWICVK1fiD3/4A86cOQOtVgudTofc3FzcfvvtkCQJycnJCAoKsqnwyZYYjUbk5uZi0KBBdj2Dq6GhQblHq6+vh7e3t7KG7onTCEIIFBYWorq6GjExMRgwYEC3f01H1R3B+bW0vWY8PT2Vtq1q/vsdPnwYCQkJWLJkCZYuXWrzv7tqamowYsQIrF69GosXL1a7HOpGDM+7WHBwMIxGI0wmE4YPH44FCxbg2WeftYsn2LbMZDJh79692LBhAzIyMtDS0oLExERIkoRZs2bZ9Q7VK1eu4Pjx45gwYQICAwPVLqddhBCt3nANBoPy5DogIEC1J9fnz59HcXExIiMj4e3trUoNjkAIgdOnT+PKlSuYNGmSKsG1owy+kWUZr7zyCr766itkZ2djzJgxapd0Q1wAEhER2baPP/4Yzz33HD777DOkpKS0+jMhBC5cuKAE6d9//z2mTJmC5ORkSJKEYcOG2c0aqrs1NDQgNzcXvr6+GDdunMN8X4xGo3KPVlNTo2xGCQgIwMCBA7v868myjKNHj8JgMNhMr3h71VPBeVtGo1E5CVxdXY1BgwYp14ybm1uP/WwUFhYiPj4eTz75JF555RW7+ZmcPHkyYmNjsWLFCrVLoW7E8LyLrV69GtHR0fDx8cGBAwfw4osv4pFHHsHq1avVLs1hWCwW7Nu3D6mpqUhPT0d9fT3mzp0LSZIQGxtrV0+6z58/jzNnziAiIgK+vr5ql9Nh1h3DZWVlqKurg5eXl/KG21O7Hc6ePYsLFy4gKioKnp6e3f41HZW1V2FpaSliYmJsYse32WxWBtpePfjG1gfaCiHw17/+FZ9++imysrIwfvx4tUtqFy4AiYiIbJPFYsH8+fPx7//+75g+ffoNP1YIgStXrkCn00Gr1WL//v2IjIyERqOBJEk20yZSDXV1dcjNzcXQoUMxatQoh/0+tLS0KKFoZWVll4eisizj8OHDaGpqQkxMjE21/rA3paWlStvRngzO2zKZTK0Gjvbp06fVfVd3/aycOHEC8fHxePTRR/Haa6/Zzc+kwWDA8OHDsXz5cjz99NNql0PdiOF5OyxduhQrV6684cccP34cY8eO/dnrn376KR5//HEYDAa73h1tq2RZxnfffacE6eXl5ZgzZw40Gg3mzJljE8HftVh39l6+fNnhwt62T67d3d0RGBjYbbsdOJim6wghcPLkSej1ekyaNKlb/r0663qDb6wDbW2lD78QAqtWrcL777+PPXv2IDw8XO2S2oULQCIisnXBwcE4f/58q9dWrFiBpUuXqlSR7RNCQK/XIz09HVqtFt988w3Gjx+vBOljxoyxm7Cqs6qqqlBQUICQkBCbmUHTE6yhqHUzSr9+/ZR7tI6c6rRYLCgoKIDJZEJ0dLTNtPC0R9bg3Nbajlosllb3XQCUgaNded91+vRpxMfH48EHH8SqVatsdmMUACxZsgRJSUkYMWIErly5gmXLliE/Px+FhYWqPvSg7sfwvB2sbQNuZOTIkdd80nrs2DFMmDABRUVFCAsL664SCT+Fajk5OUhNTUVaWhouX76M2NhYaDQaxMfHw8PDQ+0SAfxUZ1FRESorKx1+mEp373bgYJquI4TAiRMnUF5ejpiYGJsMztsSQqC2tla5xoxGI3x9fZU+/GrtfhFC4O2338abb76JXbt2ITo6WpU62oMLQCIisjfBwcFYvHgxHnvsMeU1d3d3rgPbSQiBqqoqpKenQ6fTYdeuXRg9ejQkSUJKSopDtTBpq6ysDEePHkVYWBiGDh2qdjmqsVgsyqnO8vLymz7VaTabkZeXBwCIiopii9pOsNXgvC0hBGpqapT7rubmZvj5+Slhekcfnpw7dw5xcXGQJAlvv/22TQfnADB//nzs3bsXlZWV8Pf3x/Tp0/Haa6/Z1Ewr6h4Mz7vZF198gYULF6KiooI9mHuQ9QiZtd/fmTNncM8990CSJCQkJHTrkaMbsVgsOHr0KBoaGpyuJ1xX73aQZRmFhYWoqanhYJpOuvohxKRJk+zye2ntw29d0NXX1yvtg/z9/Xvs7ySEwPvvv4+//e1v2L59O6ZMmdIjX7ejuAAkIiJ7ExwcjGeeeQbPPPOM2qXYPetGhMzMTOh0OuzYsQPDhg2DJEnQaDSYOHGizYdZ7WWdMxUeHo6AgAC1y7EZsiyjurpaacEphGh1qrPtv7/JZEJeXh569+6NiIgImzn1aY9KSkpw/Phxmw/O2xJCwGAwKPddBoMB3t7eynXT3ozj0qVLmDNnDubMmYP333/fYX7XkGNieN6FDh48iO+//x6zZs2Cu7s7Dh48iGeffRbx8fFYt26d2uU5LSEEjh8/jtTUVOh0OhQWFuKuu+6CJElITEyEn59fjwTpZrMZ+fn5kGUZUVFRTn207Ua7Hby9vX/x30OWZRw5cgQNDQ2IiYlhS6ROsP58VFVVOdRDCOuwpPLyclRXV8PNzU25xgYNGtQtP/NCCPzjH//AK6+8gq1bt+L222/v8q9BRETk7IKDg2E0GmEymTB8+HAsWLAAzz77LHe/doH6+nps3rwZWq0WW7duRUBAAJKTk5GSkoKYmBi7DbfOnz+P4uJiREREwMfHR+1ybJb1YYper0dZWRlMJhP8/PwQGBgIX19fyLKM3Nxc9O/f36EerKjBGpzb++wzAGhqalKC9JqaGri7uytB+vXuu0pKSjBnzhzceeed+OSTT/gQhmwew/MulJubiz/84Q8oKipCc3MzQkJC8PDDD+O5555juGcjrL3GrUF6fn4+pk+fDkmSkJycjMDAwG4J1Zqbm5GXl4e+ffvyCX0b1h7W1qBTCKGEnD4+Pj9blF3dXy8qKoqDaTrBUYPztkwmE8rLy5XBN/369VOuMU9Pzy75mRdCYN26dVi6dCk2btyImTNndkHlRERE1Nbq1asRHR0NHx8fHDhwAC+++CIeeeQRrF69Wu3SHEpDQwO2bdsGrVaLzZs3w9PTE8nJydBoNJg6dapd3M8IIXDmzBlcunTJ4eZMdTchBOrr65Ud6Y2NjejVqxcGDRqEyMhI5hud4EjBeVstLS3KafPKykr0798f7u7u0Ov1uPvuu+Hq6gq9Xo/4+HhMnjwZa9eutYvfJUQMz8lpCSFw7tw5aLVapKWl4dChQ7jtttuQnJwMSZIwdOjQLgnVmpqakJOTA09PT9x66618Qn8D1l5q1kWa2WxudWxQCMH+el1ECNGq7Y2ztBCynnqwhukuLi7KNXathzXtIYTAl19+ieeeew4ZGRm4++67u6FyIiIix7V06VKsXLnyhh9z/PhxjB079mevf/rpp3j88cdhMBgY6HWTpqYm7Ny5E1qtFhs3bkT//v2RlJSElJQU3H777Ta5JrduEnGGOVPdrampCT/88AP69u0LFxcX1NfXw9vbW9mMwp+79nPk4Lwt633Xvn378Ic//AG9e/fGjBkzcPr0aYwbNw5fffWVTf7uILoWhudE+GlxdenSJeh0Ouh0Ohw4cADR0dHKBPoRI0Z0KEivr69Hbm4uAgMDERYW5rDDd7qDEAJ1dXVKkG40GtGrVy/0798f0dHRXKR1ghACx44dQ21trVMF523Jsqw8rCkvL1eOploHjrZ3Mbdhwwb88Y9/RGpqKuLi4rq5aiIiIsdTXl6OysrKG37MyJEjr3ni8NixY5gwYQKKiooQFhbWXSXS/2lpacGePXuQmpqKjIwMuLi4IDExESkpKZgxY4ZNnAqVZRlHjx5FfX09oqOjHfZ0ZU9obGxETk4O/Pz8MHbsWLi4uChtOvR6PWpra+Hh4aEE6QMHDlS7ZJt15coVFBUVOUVw3lZLSwvS09Px7rvv4vjx43B1dUV8fDxSUlIQHx/PUyFk8xieE7UhhEBpaSnS0tKg0+nwzTffIDw8XAnSR40a1a4QvLq6Gvn5+RgxYgRCQkIYnHeC0WjEjz/+CBcXF/Tq1QsNDQ3w9fVVhkHawiLdXsiyjGPHjqG+vp794q9y9dHU8vJyNDQ0wMfHR7nGrvd9Sk9Px2OPPYavvvoKSUlJPVw1ERERffHFF1i4cCEqKirg7e2tdjlOxWw245tvvkFqairS09PR3NyMxMRESJKEu+++W5V1ptlsxuHDh9nisQsYDAbk5OQgKCgIo0ePvub9bHNzs9LvuqqqqkfmDNkja3AeGRnplH33a2pqkJSUhKCgIKSmpqKwsBDp6elIT09HUVER7r77bixZsgSxsbFql0p0TQzPiW5ACIHKykpkZGQgNTUVe/bsQVhYGCRJgiRJGDdu3DUXBOfOnUNxcTHGjBmDW265RYXKHYfRaEROTg48PDyUtjeNjY3KjvS6ujp4eXkpizRn3UXdHtZdOAaDgcH5L7BeY+Xl5cqOGoPBAH9/f4SHhwMANm3ahEceeQSfffYZ5s2bp3LFREREju/gwYP4/vvvMWvWLLi7u+PgwYN49tlnER8fj3Xr1qldnlOzWCzYv38/UlNTkZaWhvr6esTHx0OSJMTGxvbIjmSTyYS8vDz06tULkZGRbAnRCXV1dcjNzcWwYcMwcuTIdoXgJpNJ6XddUVGB/v37K/doHh4eThukO3twXldXB41GA09PT2RkZPzsfv306dPIyMhAVFQU21+SzWJ4TtRO1n7cmZmZ0Gq12LlzJ4KDg5UJ9BMmTECvXr3w3nvvYdWqVdi7dy9GjBihdtl2zXpM0NfX97oPKoxGoxKk19TU8NjgdViD84aGBsTExHAXzk2w7qh566238Mknn+CWW27BpEmTsGnTJvzzn//E/Pnz1S6RiIjIKeTm5uIPf/gDioqK0NzcjJCQEDz88MN47rnnuCnAhsiyjO+//14J0svLyzF79mxoNBrMmTMHbm5uXf41jUYjcnNzMXDgQISHh3MIYSfU1tYiNzcXISEhCA4O7tDnsPa7tm5GcXV1Ve7RvL29nSZId/bg3GAwYN68eejbty82bdrE+3OyWwzPiTqorq4OmzZtglarxbZt2xAUFISxY8diz549+J//+R9IkqR2iXbNekxw8ODBGDNmTLsWWC0tLUr/vaqqKgwaNAgBAQEIDAx06mODsizjyJEjaGxsZHDeSdXV1XjnnXewfv166PV6+Pn5QaPRQKPRYMaMGejTp4/aJRIRERHZDFmWkZubi9TUVOh0Oly6dAmxsbHQaDSIj4/vkh3JDQ0NyM3NhY+PD8aNG9ehAfD0k6qqKuTn52PUqFEYPnx4l3xOWZZRVVWlBOlCCCVI9/Hxcdh/r8uXL+PEiRNOG5w3NjbiV7/6FWRZxpYtW7rloRlRT2F4TtQF6uvrsXDhQmzduhW33HILzGazMoF+8uTJ3PlwkzpyTLAtHhv8iSzLOHz4MIxGI6Kjoxmcd9K3336LX/3qV3jrrbfwm9/8Bt988w3S0tKQkZGB5uZmJCUlYcWKFRgyZIjapRIRERHZFOtJSGuQfvr0adx9992QJAkJCQkd2pFcX1+P3NzcG/blpvapqKjA4cOHERYWhqFDh3bL17Ce5raeHDaZTPD390dAQAD8/Pwc5r7Z2YNzo9GIBx54AA0NDdi2bRs8PDzULomoUxieE3WS2WzG73//e+zcuRM7d+7EsGHDsH37duh0OmzcuBEDBw5EcnIyNBoNpk2bxt57v6CmpgZ5eXmdOibYlsViaRWk9+7dWwnSvby8HHaRLcsyCgoK0NzcjJiYGO6K7qSDBw8iJSUFK1euxO9///tW1431eHJ6ejpefvll7qwgIiIiugEhBIqKipQg/dixY5g5cyYkSUJSUhL8/Px+cY1eXV2N/Px8BAcHIyQkpIcqd0xlZWU4evQoxo0bh6CgoB75mkII1NfXo6ysDHq9HkajEb6+vggICIC/v7/d3rtYg/OoqCinHGLc3NyM3/zmNygvL8fOnTvh5eWldklEncbwnKgTjEYjHnzwQZw8eRI7duz42RN6o9GI3bt3Q6fTISMjA66urkhKSmKLh+uorKxEQUFBtw5avfrYYFlZGVxcXODv74/AwEB4e3s7zLFBi8WCw4cPo6WlBdHR0bzWOunHH39EcnIy/vznP+Opp55y2AcuRERERD1NCIHTp09Dq9VCp9MhLy8Pd9xxByRJQnJyMgYPHvyztdeBAwfQ1NSEsLCwbrtvcBalpaU4duwYwsPDERAQoFodBoNBuUczGAzw8fFRgnR7mWlw6dIlnDx50mmD85aWFixcuBAXL17Erl274Ovrq3ZJRF2C4TlRJxw6dAj/+Z//Ca1W+4vHsUwmE7755hukpqYiPT0dJpMJSUlJkCQJd911l90sCLpLWVkZjhw5gvHjx/fYbgdZllsdG7RYLMqxQV9fX7s9NmixWFBQUACz2YyoqCgG552Un5+PhIQE/OlPf8Lzzz/P4JyIiIiomwghcP78eSVIP3ToEKZOnYrk5GRIkoRbbrkFH374If7rv/4LGzduxO233652yXbNukt64sSJ8PPzU7scRVNTk3KPVltbC09PT+Xk8IABA9Qu75qcPTg3m8149NFHceLECezZswf+/v5ql0TUZRie001577338MYbb6C0tBQRERFYs2YNpkyZonZZqhJC3HSYZjabsW/fPiVINxgMmDt3LjQaDe655x6bXRB0l5KSEhQWFqq620EIgbq6OuXYYHNzM/z8/BAYGAg/Pz+7abdjsViQn58Pi8WC6Ohou6nbVh09ehTx8fF4/vnn8eKLLzI4JyIiIuohQghcvnwZOp0OOp0O+/fvx9ixY3HmzBm88cYb+O1vf8u1WSdcvHgRp06dsvm+3M3NzSgvL0dZWRmqqqrg5uamBOm20iqRwbkZjz/+OAoKCrBnzx4MHjxY7ZKIuhTDc2q3r7/+GgsXLsSHH36IqVOn4q233sKGDRtw4sQJVY932TuLxYLvvvsOWq0WaWlpqKysxJw5c6DRaDB79mwMGjRI7RK7lXWhYUu7HYQQrY4NNjQ0tOq/Z6tDN63BuSzLiIqKYnDeScePH0d8fDyeeOIJLF++nDdnRERERCqRZRlLlizBxx9/jEmTJuHAgQO49dZbodFoIEkSh4XepHPnzuHs2bOIioqyq57UJpNJCdIrKysxYMAAJUh3d3dX5Rq4dOkSTp06ZXffy65isVjw5JNP4uDBg8jOzsaQIUPULomoyzE8p3abOnUqJk+ejHfffRfATwuYYcOG4amnnsLSpUtVrs4xyLKMH3/8UQnSL1++jHvvvRcajQZxcXEON6X6/PnzKC4uRmRkpE0/oW9oaFCC9Pr6enh7eytBev/+/dUuD8BPi5a8vDwIIRicd4GTJ08iPj4eixYtwooVK3gzRkRERKQSWZbx1FNPISMjAzt37sTYsWNRWVmJjIwMaLVa7N69G2PGjIEkSdBoNBg3bhzXbtchhEBxcTEuXryI6Ohou76/tFgsqKioQFlZGSoqKtC7d28lSPfy8uqRa+DixYs4ffq00wbnsizjmWeewZ49e5CdnY3hw4erXRJRt2B4Tu3S0tKCgQMHIjU1FRqNRnl90aJFqKmpQUZGhnrFOShZlnH48GFlAn1xcTFiY2MhSRISEhLg6elpt4tCIQTOnj2LCxcuICoqCp6enmqX1G5Go1EJ0mtqauDh4aEs0gYOHKhKTWazGXl5eXBxcUFUVJTd9mq3FcXFxYiLi8Ovf/1rvPnmmw4zRJaIiIjI3rS0tGDRokXIzc3Fjh07MGLEiFZ/LoRAbW0tMjMzodVqlY9JTk5GSkoKwsPDuZb7P0IInDp1CiUlJYiJibGZliddQZZlVFVVKfdpLi4uyiwrHx+fbrkGGJzLeOGFF7B582ZkZWVh5MiRapdE1G0YnlO7XLlyBUOHDsWBAwcwbdo05fUXXngB33zzDb7//nsVq3N8QggUFhYqQfrx48cxa9YsSJKExMRE+Pr62k2QLoTA6dOnceXKFURHR8Pd3V3tkjqspaVFWaCp1X/PGpz36tULkZGRDM476fz584iLi0NSUhLeeecd3mwRERERqai+vh7//u//jtdff71drULr6uqwefNmaLVabNu2DYGBgUqQHh0d7bRrOyEETpw4gfLyckRHRzt0a1BZllFTU6Pcp1ksFvj5+SEgIAB+fn5dcr/E4FzGn/70J2i1WmRlZWH06NFql0TUrRieU7swPLcd1h0D1iC9oKAAM2bMgCRJSEpKQmBgoM0G6UIIFBUVoaKiwuEWbSaTqdWxwZ7ov2c2m5Gbm4vevXsjIiKCwXknXb58GbNnz8bs2bPxwQcfOO3NFREREannvffewxtvvIHS0lJERERgzZo1mDJlitpl2aWGhgZs3boVWq0WW7ZsgZeXF5KTk6HRaDBlyhSnWTtbN2JVV1cjJiYGAwYMULukHiOEQF1dnRKkG43GVkF6nz59bvpzOntwLoTAq6++is8++wxZWVkYO3as2iURdTuG59QubNtim6ztT6w90n/44QfcdtttkCQJkiRhyJAhNhOky7KMwsJC1NTUOPyi7er+e+Xl5ejTp0+X998zmUzIy8tjcN5FSktLMWfOHEyfPh3/+Mc/+P0kIiKiHvf1119j4cKF+PDDDzF16lS89dZb2LBhA06cONGuXdd0fU1NTdixYwd0Oh02btyIAQMGICkpCRqNBrfffrvDzguSZRlHjx6FwWBAdHS0zcxrUoMQotUsK4PBAB8fH+U+rW/fvr/4OS5cuIAzZ84gOjrarlqPdhUhBF5//XV89NFH2LNnDyZMmKB2SUQ9guE5tdvUqVMxZcoUrFmzBsBPb8TDhw/Hk08+yYGhNkAIgUuXLkGn00Gn02H//v2YNGmSMjhn+PDhqgXpsizjyJEjaGhoQExMDPr166dKHWqQZRmVlZVKkO7i4qIs0Ly9vTu0u9lkMiE3Nxd9+/bFxIkTGfR2UllZGeLj4xEdHY1169Y57M0TERER2bapU6di8uTJePfddwH8tI4cNmwYnnrqKd5vdaGWlhbs2rULOp0OGRkZcHFxUYL0O++8s0O7kW2RdYZWU1MTYmJi2hUOO5PGxkYlSK+rq4Onp6dyn3atjV4MzgVWr16Nt956C7t370ZkZKTaJRH1GIbn1G5ff/01Fi1ahI8++ghTpkzBW2+9hfXr16OoqAiBgYFql0dXEUKgtLQUaWlp0Gq12Lt3LyZOnAiNRgNJkhAaGtpjQbrFYkFBQQFaWloQHR3t1Iu2a/Xfsw6y8fX1bVcIbjKZkJOTg379+iEiIoKtRTqpoqICCQkJGDt2LL788kuHuVkiIiIi+8KTvuowmUzYu3cvNmzYgIyMDLS0tCAxMRGSJGHWrFl2u+nHeg9mMpkQHR3NNe4vMBqNKC8vR1lZGaqrq+Hm5obAwEAEBARg0KBBDM6FwJo1a7Bq1Sps374dkydPVrskoh7F8Jxuyrvvvqv04IuMjMQ777yDqVOnql0W3YAQAhUVFUhPT1cGeoSFhSlB+tixY7stSDebzcjPz4cQApGRkVy0XUUIgdraWiVIb2lpadV/71q7n1taWpCbm4v+/ftj4sSJDM47qbq6GomJiRgxYgTWr1/v1A92iIiISF2cMaU+i8WCffv2ITU1Fenp6aivr0d8fDw0Gg1iY2Ptpu2k2WxGXl4eACAqKoqnKm9SS0uL0oKzsrISvXv3hslkwvjx4xEUFGQzbVF7ihACH330Ef785z9j69atrX4/ETkLhudETkQIgerqamRmZkKr1WLnzp0YOXKkMoH+1ltv7bJA1tpapHfv3oiMjGRrkRsQQsBgMKCsrAx6vR5NTU3w8fFBYGAg/Pz80LdvX7S0tCAnJwcDBw5EeHg4g/NOqq2tVQbs6nQ6u91VRERERI6B4bltkWUZ3333nRKkl5eXY86cOdBoNJgzZw4GDRqkdonXZJ2L5OrqynuwLnD27FkUFxfDy8sLtbW1yiyrwMBAeHp6OnyQLoTAP//5T7z00kvYvHkzZsyYoXZJRKpgeE7kxGpra7Fp0ybodDps27YNQUFBkCQJKSkpiIyM7HBA29zcjNzcXAwYMIA7pDvg6kE29fX18PT0RFNTE9zd3dmqpQvU19dDo9HA3d0dmZmZTj04iYiIiGwD27bYLlmWkZOTg9TUVKSlpeHy5cuIjY2FRqNBfHw8PDw81C4RwP8/pdqvXz/OReoC58+fR3FxMWJiYuDh4QGLxYKqqqpWs6z8/f0RGBjY4VlWtkwIgc8//xxLlixBZmYmZs2apXZJAID33ntP6YYQERGBNWvWYMqUKWqXRQ6O4TkRAQAMBgO2bNkCnU6HLVu2wMfHB8nJydBoNJg8eXK7F19GoxE5OTnw8PDo0p3szqq2tlZpfWM2m39xkA3dWENDA+677z64urpi06ZNNrtriIiIiJzP1KlTMWXKFKxZswbAT6Ht8OHD8eSTT3JgqI2wDuHUarXQ6XQ4c+YM7rnnHkiShISEBHh5eamyG7m5uRk5OTlwc3PDhAkTeA/WSefOncPZs2eV4LytrphlZcuEEFi/fj2eeuop6HQ6zJ49W+2SAPw0h2/hwoX48MMPMXXqVLz11lvYsGEDTpw4gYCAALXLIwfG8JyIfqaxsRE7duyAVqtVAkZrkD5t2rTrLgYaGxuRk5MDX19fjBs3zuGPsXU36yLYw8MD48ePh8lkUgbZVFVVwc3NTQnS3dzc1C7X5jU1NeFXv/oVTCYTtm7dCnd3d7VLIiIiIlJ8/fXXWLRoET766CNMmTIFb731FtavX4+ioiIEBgaqXR61IYTA8ePHkZqaCp1Oh8LCQtx1112QJAmJiYnw8/PrkfuhpqYm5OTkwMvLC7feeivvwTrp3LlzOHfuHKKjo9t1qkAIgbq6OqUFZ3Nzc6tZVvY490un0+Hxxx/H+vXrkZCQoHY5iqlTp2Ly5Ml49913Afz0EGPYsGF46qmn+ICRuhXDcyK6IaPRiN27d0Or1SIzMxO9e/dGUlISNBoNpk+friwGcnJy8O///u9Ys2YNIiMjuWjrJOsOfk9Pz2sugq8O0isrKzFgwAAlSHd3d+f3vw2j0Yj58+ejrq4O27dvh6enp9olEREREf3Mu+++q7QkiIyMxDvvvIOpU6eqXRb9AiEETp8+rQTp+fn5mD59OiRJQnJyMgIDA7tlfW7dvOTn54exY8fyHqCTbjY4b+vqWVZlZWVoaGiAj4+Pcp/Wt2/fbqi6a23cuBGPPvoovvjii1YtpNTG1lakJobnRNRuJpMJ2dnZyuAci8WCpKQkTJgwAX/+85+xYMECvPHGGzwm2ElGoxE//vgjvL29MX78+F9cBJvNZlRWVkKv16OiosLpBtn8kubmZjz00EPQ6/XYuXMnvL291S4JAPv1ERERETkiIQTOnTsHrVaLtLQ0HDp0CFOnToUkSZAkCUOHDu2S9bnBYEBOTg6CgoIwevRop1/zd9bZs2dx/vx5xMTEdNkJ1cbGRiVIr6urg5eXlxKk2+Lcpa1bt2LhwoVYu3Yt7r//frXLaYVDlUlNDM+JqEPMZjP27duHd955B5mZmbj11lsxYcIESJKE2NhYm1wM2APrsUsfH58Otb651iAb6wLNEQfZ/BKTyYSFCxfi3Llz2LNnD3x9fdUuCQD79RERERE5AyEELl26BJ1OB51OhwMHDiA6OhoajQaSJGHEiBEdCr3r6uqQm5uLYcOGYeTIkQzOO6k7gvO2jEajcnK4uroa7u7uyn2aLcxh2r17Nx588EF89NFHWLBggc1dUwzPSU0Mz4mow3bt2oWUlBSsWrUK4eHhyu6KqqoqxMXFQaPR4N5777WJxYA9sAbnvr6+XXLsUpZlVFdXK7sdhBDKIBsfHx+7H2TzS8xmMxYvXozjx49jz549NhVKs18fERERkXMRQqC0tBRpaWnQ6XT45ptvEB4ergTpo0aNatf6v7a2Frm5uQgJCUFwcHD3F+7geiI4b6ulpaVVC86BAwcqJ4fd3Nx6PLjeu3cv7r//fqxZswaLFi2yueAcYNsWUhfDcyLqkMzMTCxYsAAffvghHnroIeV1WZbxww8/KEH6lStXMHv2bEiShPj4eA5pvI6mpib8+OOP8Pf3R1hYWJcvWIQQqK2tVQbZmEwm+Pn5ITAwEL6+vujdu3eXfj21WSwW/P73v0dubi6ysrIwePBgtUtScOFHRERE5NyEEKisrERGRgZSU1OxZ88ehIWFKa1drncC9eLFizh16hRGjRqF4cOHq1C5YykuLsaFCxd6NDhvy2w2o6KiAmVlZaioqEDfvn2VHek90YJz//79uO+++/Dmm2/iscces8ng3Grq1KmYMmUK1qxZA+Cn7GH48OF48sknuQGJuhXDcyK6aadOnUJUVBQ+++wzpKSkXPfjZFlGQUGBMjjn3LlziI2NRXJyMhISEtiP+/9YB/10V3DelhAC9fX1yo70pqYm+Pr6IiAgAP7+/nY5Ef5qFosFTz/9NPbt24fs7GwMHTpU7ZJa4ZFDIiIiIrISQqCmpgaZmZnQarXYuXMngoODkZycjJSUFEyYMAG9evWCVqvF008/jW3btiE8PFztsu2eLQTnbV3dgrOsrAy9evXq1hachw4dgiRJeO211/DHP/7R5u/Nv/76ayxatAgfffQRpkyZgrfeegvr169HUVERAgMD1S6PHBjDc6LrWL58OV599dVWr4WFhaGoqEilimxLcXExRo4c2e6PF0Lg2LFjSE1NRVpaGoqKijBr1ixIkoTExET4+PjY/Jt1d2hoaEBOTg4CAwMxZswYVb4HDQ0Nyo50g8EAb29vBAYGwt/fH/369evxejpDlmU899xz2LVrF7KysjBixAi1S/oZhudEREREdD11dXXYtGkTtFottm3bhqCgIEyePBlpaWlYsWIFHn/8cbVLtHu2GJy31bYFpyzLSgtOX1/fTrfgzM3NRVJSEl5++WU8++yzdnMv/u677+KNN95AaWkpIiMj8c4772Dq1Klql0UOjuE50XUsX74cqamp2LVrl/Ja79694efnp2JVjkEIgZMnT0Kr1UKn06GgoAAzZsyARqNBUlISAgIC7ObNuzOswfngwYMxevRom/g7NzU1KQu02tpaeHp6KrsdBgwYoHZ5NyTLMpYuXYrMzExkZ2ff1MOdnsS2LURERETUHgaDAS+//DLWrFmD0NBQNDc3IykpCRqNBlOmTHH4GUbd4cyZM7h48SImTZoENzc3tctpl6tbcJaVlaGlpQV+fn4ICAiAn5/fTbfgPHz4MObOnYsXXngB//mf/2kT96FEtozhOdF1LF++HOnp6cjPz1e7FIcmhEBxcbHSI/3HH3/EtGnTIEkSkpOTMWTIEId8M29oaMCPP/6IIUOGtHs4UE9rbm5WFmjV1dVwc3NDYGCgzUyEv5osy3j55Zexfv16ZGVlYcyYMWqXdEPs10dEREREv2Tt2rV48sknkZqaipkzZ2L79u3Q6XTYuHEjBg4ciOTkZEiShNtvv93hZhh1hzNnzuDSpUuIiYmxm+C8LSEEDAaDcp/W0NDQqgVn3759b/j/LywsRHx8PJ566im8/PLLNnkfSmRrGJ4TXcfy5cvxxhtvwNPTE/3798e0adOwYsUKDmbpRkIIXLx4ETqdDjqdDgcOHMDkyZOVwTnDhw93iDd3g8GAnJwcDB06FKGhoXbxdzKZTK0mwg8YMEDVifBXE0LgL3/5C9auXYusrCyMGzdOtVrai/36iIiIiOhG3n//feVU5V133dXqz4xGI3bv3g2dToeMjAy4uroqO9JnzJhh9zOMuoMjBOfXYm3BWVZWhvr6enh5eSknh/v379/qY0+cOIH4+HgsXrwYf/3rX+3iPpTIFjA8J7qOrVu3wmAwICwsDCUlJXj11Vdx+fJlHD161Gb7ojkSIQRKSkqQlpYGrVaLb7/9FhEREUqQbi+hc1sGgwE//vgjhg0bhpEjR9rl30HtifBXE0Jg5cqV+OCDD7Bnzx67Gp7Efn1EREREdC1lZWWYMmUKvvrqK9x22203/FiTyYRvvvkGqampSE9Ph8lkQlJSEiRJwl133WV3M4y6mvWksyMG520ZjcZWJ4fffvttREVF4YEHHkD//v0RHx+PBx98EKtWrery4aNEjozhOVE71dTUYMSIEVi9ejUWL16sdjlORQiBiooKJUi37i6WJAkajQZhYWF2EULX19cjJycHw4cPt9l+3Der7UR4V1dXJUj38vLq1kWZEAJvvfUW/v73v2P37t2Iiorqtq9FRERERF1r+fLlePXVV1u9FhYWhqKiIpUqsi0tLS2/2IKjLbPZjH379ilBusFgwNy5c6HRaHDPPffY/AyjriaEwJkzZ3D58mWHD87bMhqN+Oijj7Bp0yYcOnQIHh4eGDVqFD766CNERETYxf0zka1geE50EyZPnozY2FisWLFC7VKclhAC1dXVyMjIgE6nw86dOxEaGork5GSkpKRg/PjxNvkU3RqcjxgxAiEhIWqX0y3aToQXQrSaCN+V/y5CCLz33ntYsWIFtm/fjilTpnTZ5yYiIiKi7rd8+XKkpqZi165dymu9e/eGn5+filU5DovFgu+++06ZLVVZWYk5c+ZAo9Fg9uzZNjfDqKs5c3B+tYsXLyIxMRGjRo2Cm5sbtm7disGDB2PevHmYN28epkyZYpP3z0S2hOE5UTsZDAYMHz4cy5cvx9NPP612OfR/amtrsXHjRuh0Omzbtg1Dhw6FRqOBRqNBRESETSwE6urqkJub69DBeVvWifB6vR5lZWUwmUxKkO7n5wdXV9dOfe5PPvkEy5Ytw9atW3H77bd3YeVERERE1BOWL1+O9PR05Ofnq12Kw5NlGT/++CO0Wi10Oh2uXLmCe++9F5IkIT4+Hh4eHmqX2KWuDs4nTZrk8A8KrqekpARz5szBzJkz8fHHH8PV1RVNTU3YuXMndDodMjMzMWLECOTl5aldKpFNY3hOdB1LlixBUlISRowYgStXrmDZsmXIz89HYWEh/P391S6PrqG+vh5btmyBTqfDli1b4Ofnh+TkZGg0GkyePFmVIL22tha5ubkICQlBcHBwj399WyCEQH19vbIjvampqdVE+JsZaCSEwLp167B06VJs2rQJd955ZzdWTkRERETdZfny5XjjjTfg6emJ/v37Y9q0aVixYgWGDx+udmkOTZZlFBQUKEF6cXExYmNjkZycjISEBHh5edl1Sw8hBE6fPo0rV644dXCu1+sRHx+PyZMnY+3atdfcvGQymXD69GmMGzdOhQqJ7AfDc6LrmD9/Pvbu3YvKykr4+/tj+vTpeO211xAaGqp2adQOjY2N2L59O7RaLTZt2gR3d3ckJydDkiRMmzatUzuf28sanI8cORIjRozo9q9nLwwGgxKkGwwG+Pj4KH3Sb9TXUQiBL7/8Es899xwyMjJw991392DVRERERNSVtm7dCoPBgLCwMJSUlODVV1/F5cuXcfToUbi7u6tdnlMQQqCwsBCpqanQ6XQ4fvw47rrrLmg0GiQmJsLX19eugnQG5z8pLy9HQkICJkyYgM8//xy9e/dWuyQiu8bwnIgcntFoxK5du6DVapGZmYm+ffsiMTERKSkpuOOOO25q53N71dTUIC8vD6Ghodw9cwNNTU0oKyuDXq9HXV0dPD09ERgYiICAAPTv31/5OCEENmzYgCeffBKpqamIi4tTsWoiIiIi6mo1NTUYMWIEVq9ejcWLF6tdjtMRQuDUqVNKkF5QUIDp06dDo9EgKSkJgYGBNh2kW4PzkpISxMTEOG1wXlVVhblz52LUqFH4+uuvu+Vel8jZMDwnIqdiMpmQlZWF1NRUZGRkQJZlJCQkICUlBTNnzrzpifbXYg3OR40ahWHDhnVB1c7BaDSivLwcZWVlKC4uxuuvv464uDg88MADKC4uxr/927/hq6++QmJiotqlEhEREVE3mDx5MmJjY7FixQq1S3FqQgicPXtWGTb6ww8/4LbbboMkSZAkCUOGDLGpIJ3B+U9qamqQlJSEIUOGQKvVdsm9LRExPCciJ2Y2m/Htt98iNTUV6enpaGxsREJCAiRJwj333NNq53N7VVdXIy8vD2PGjMEtt9zSDVU7h6qqKnz++efYuHEjDh06hH79+iEhIQEvvfQSJk6caFOLdSIiIiLqPIPBgOHDh2P58uV4+umn1S6H/o8QApcuXYJOp4NOp8P+/fsxadIkJUgfMWKEqmtz64750tJSpw7O6+rqIEkSvL29kZ6e3qF7WSK6NobnREQALBYLDhw4oOyuqKmpQVxcHDQaDe69914MHDjwFz9HVVUV8vPzERYWhqFDh/ZA1Y5v+/bt+N3vfoeHHnoIJSUl2LJlCwYPHox58+Zh3rx5mDJliiqDYImIiIioc5YsWYKkpCSMGDECV65cwbJly5Cfn4/CwkL4+/urXR5dgxACpaWlSEtLg1arxd69ezFx4kQlSB81alSPBulXB+eTJk1q1z2bIzIYDJg3bx769euHTZs2YcCAAWqXRORQGJ4TEbUhyzIOHTqkBOmlpaWYPXs2JElCXFzcNQcY5eXlobq6GmPHjsWQIUNUqNrx7NmzB/Pnz8eHH36I3/zmN3BxcUFTUxN27NgBnU6HzMxMJCQk4PPPP1e7VCIiIiK6SfPnz8fevXtRWVkJf39/TJ8+Ha+99hpCQ0PVLo3aQQiBiooKpKenQ6vVYs+ePRg7diwkSYJGo8HYsWO7NUgXQuDkyZPQ6/VOHZw3NjbivvvuAwBs3rwZbm5uKldE5HgYnhMR3YAsy8jPz1cG55w/fx6xsbGQJAlz586Fp6cn0tPT8bvf/Q4bNmzA3XffrXbJDmHv3r24//778fbbb+ORRx655sLbZDKhoqICQUFBKlRIRERERETAT0F2dXU1MjMzodVqsXPnToSEhECSJKSkpODWW2/t0tOi1uC8rKwMMTExThucNzU14YEHHkBjYyO2bdsGDw8PtUsickgMz4mI2kkIgaNHjyI1NRVpaWk4ceIEbrvtNhw6dAivvPIKnn76afbi7gIHDx5ESkoKVq5cid///vf8nhIRERER2ZHa2lps2rQJOp0O27ZtQ1BQkBKkR0ZGdipIZ3D+k+bmZixYsACVlZXYsWMHvLy81C6JyGExPCci6gAhBD7++GM8/fTTGD9+PI4dO4YZM2ZAo9EgKSkJ/v7+DH074IcffoAkSfjzn/+Mp556it9DIiIiIiI7ZjAYsGXLFuh0OmzZsgU+Pj5ITk6GRqPB5MmT4erq2u7PxeD8Jy0tLVi4cCEuXryI3bt3w8fHR+2SiBwaw3Miog7YtGkT5s+fj3/+85/41a9+heLiYmi1Wuh0OuTk5GDatGnQaDRITk5GUFAQQ+B2yMvLQ2JiIv70pz/h+eef5/eMiIiIiMiBNDY2YseOHdBqtdi0aRMGDRqE5ORkSJKEadOmoXfv3tf9/wohcOLECZSXl2PSpElOOxTTZDJh8eLFOHHiBPbs2cPhukQ9gOE5EdFNysjIwG9+8xv861//wrx581r9mRACFy5cgE6ng06nw8GDBzFlyhRlAv2wYcMYCl/DkSNHMHfuXDz//PN48cUX+T0iIiIiInJgRqMRu3fvhlarRUZGBvr06YPExESkpKRg+vTp6NOnj/Kxsixj1apVmDp1Km677TanDc7NZjMef/xxFBQUICsrC4GBgWqXROQUum5iAxHZpb179yIpKQlDhgyBi4sL0tPTW/25EAKvvPIKgoKCMGDAAMTGxuLUqVPqFGsDZFnG6tWr8cUXX/wsOAcAFxcXjBgxAs8++yz27t2L8+fPY8GCBdi2bRvCw8Nx1113YfXq1Thz5gz47PInhYWFSEpKwlNPPcXgnIiIiIjICfTv3x8JCQn49NNPUVpais8++wyurq549NFHERoaiieeeAI7duyA0WjE4sWL8dFHH2HEiBFOG5xbLBY89dRTyMnJwa5duxicE/Ug7jwncnJbt27F/v37ERMTg3nz5iEtLQ0ajUb585UrV2LFihVYt24dQkJC8PLLL+PIkSMoLCxE//791StcRbIs3/SQGyEEysrKkJ6eDq1Wi+zsbIwfPx6SJEGj0WDMmDFOGRqfPHkS8fHx+O1vf4u//e1vTvk9ICIiIiKin5jNZuzbtw8bNmxAWloaTCYTAGDZsmVYsGCBU96DyrKMZ555BllZWcjKysLw4cPVLonIqTA8JyKFi4tLq/BcCIEhQ4bg+eefx5IlSwD8NDk9MDAQa9euxfz581Ws1n4JIVBVVYWMjAzodDrs2rULoaGhygT6cePGdWoCvb04c+YM4uPj8cADD+CNN95wir8zERERERH9MlmW8cc//hEZGRlISEjAzp07UVVVhbi4OGg0Gtx7770YNGiQ2mV2O1mW8cILL2DLli3IyspCSEiI2iUROR0mFUR0XWfPnkVpaSliY2OV1zw9PTF16lQcPHhQxcrsm4uLC3x9ffHoo49i06ZNKC0txdKlS3H8+HHMnDkT0dHRWLZsGfLz8yHLstrldotz584hMTERGo2GwTkRERERESmswfn27dvx3Xff4ZNPPkFxcTF27tyJ4OBgLFu2DMHBwfjNb36D9evXo76+Xu2Su4Usy/jTn/6EzMxM7Nq1i8E5kUqYVhDRdZWWlgLAz/qpBQYGKn9Gnefl5YWHH34YaWlp0Ov1+Mtf/oLz589jzpw5CA8Px0svvYRDhw45TJB++fJlJCQkIC4uDu+88w6DcyIiIiIiAvBTYPyHP/wBO3bsQHZ2ttKipFevXpg6dSpWrVqFEydOYN++fRg/fjxWrlyJ4OBgPPDAA/jiiy9QU1PjELOlhBD485//jPXr12PXrl0YNWqU2iUROS0mFkRENsTd3R0PPPAA1q9fD71ej7///e8oLy+HRqPB+PHj8cILL2D//v2wWCxql9ohJSUlmDt3LmbNmoX333+fwTkRERERObS9e/ciKSkJQ4YMgYuLC9LT01v9uRACr7zyCoKCgjBgwADExsbi1KlT6hRrA2RZhpub2w17e/fq1QtRUVF47bXXUFhYiB9++AExMTFYs2YNQkJCMG/ePKxbtw6VlZV2GaQLIbBixQqsXbsWu3btwtixY9UuicipMbUgousaPHgwAECv17d6Xa/XK39G3WfgwIGYN28evvjiC5SWluK9996DwWDAAw88gDFjxuCZZ57BN998A7PZrHap7VJWVobExERMmTIFn3zyCVxdXdUuiYiIiIioWzU0NCAiIgLvvffeNf981apVeOedd/Dhhx/i+++/x6BBgzBnzhwYjcYertQ29O7dG2+++Wa7h2K6uLhgwoQJWL58OQoKCnD48GHMnDkT//M//4ORI0ciKSkJ//jHP6DX6+0iSBdCYPXq1fjggw+wc+dO3HrrrWqXdF3BwcFwcXFp9d/rr7+udllEXY4DQ4lIcb2BoUuWLMHzzz8PAKirq0NAQAAHhqqopaUFWVlZSE1NRUZGBgAgISEBKSkpuPPOO9G3b1+VK/y5iooKJCQkYNy4cfjyyy/Ru3dvtUsiIiIiIupR17vfev7557FkyRIAQG1tLQIDA3m/1UlCCBQXF0Or1SItLQ0//PADbr/9dkiShOTkZOUkgC0RQmDNmjVYtWoVduzYgUmTJqld0g0FBwdj8eLFeOyxx5TX3N3dnWKQKzkX7jwncnIGgwH5+fnIz88H8NOQ0Pz8fFy4cAEuLi545pln8Ne//hWZmZk4cuQIFi5ciCFDhigLPup5ffv2xZw5c/DJJ5/gypUr+OqrrzBgwAD8/ve/x8iRI/H4449j69atNrNbpbq6GpIkITQ0FJ9//jmDcyIiIiIi/HTvVVpaitjYWOU1T09PTJ06FQcPHlSxMvvn4uKC0NBQvPDCCzhw4ACKi4sxb948ZGRkYNy4cYiNjcXbb7+N8+fP28SOdCEEPvroI7z++uvYsmWLzQfnVu7u7hg8eLDyH4NzckTceU7k5LKzszFr1qyfvb5o0SKsXbsWQggsW7YMH3/8MWpqajB9+nS8//77GDNmjArV0o1YLBbs379f2V1RW1uL+Ph4aDQaxMbGYuDAgT1eU21tLZKSkhAYGAidTod+/fr1eA1ERERERLag7c7zAwcO4I477sCVK1cQFBSkfNyvf/1ruLi44Ouvv1apUsclhEBJSQnS0tKg1Wrx7bffIiIiApIkKRt+enpHuhAC//znP/HSSy9h8+bNmDFjRo9+/Y4KDg6G0WiEyWTC8OHDsWDBAjz77LPcLEUOh+E5EZEDkmUZhw4dQmpqKtLS0qDX6zFnzhxIkoS4uDi4ubl1ew319fWQJAkeHh7IzMxE//79u/1rEhERERHZKobntkUIgYqKCiVIz8rKwrhx4yBJEjQaDcLCwro9SBdC4LPPPsN//Md/YOPGjbjrrru69et1pdWrVyM6Oho+Pj44cOAAXnzxRTzyyCNYvXq12qURdSmG50REDk6WZeTl5SE1NRU6nQ4XL15EbGwsJEnC3Llz4eHh0eWLwoaGBsybNw+9e/fG5s2bVdn1TkRERERkS9qG58XFxQgNDUVeXh4iIyOVj5s5cyYiIyPx9ttvq1OoExJCoLq6GhkZGdBqtdi1axdGjhwJSZKQkpKC8ePHo1evru18LITA119/jaeffhppaWm49957u/Tzd8TSpUuxcuXKG37M8ePHMXbs2J+9/umnn+Lxxx+HwWDgiWNyKAzPiYiciBACR48exYYNG5CWloaTJ0/i7rvvhiRJSExMhLe3d6eD9KamJvzqV7+C2WzG1q1be2SXOxERERGRrbvewNAlS5bg+eefBwDU1dUhICCAA0NVVltbi40bN0Kn02Hbtm0YOnQoNBoNJElCZGRklwTpOp0Ojz/+ONavX4+EhIQuqLrzysvLUVlZecOPGTlyJPr27fuz148dO4YJEyagqKgIYWFh3VUiUY9jeE5E5KSEECgqKlJauxw9ehR33nknNBoNEhMT4e/vf9NButFoxPz581FfX49t27bB09Ozm6rvnODgYJw/f77VaytWrMDSpUtVqoiIiIiIHJHBYMDp06cBAFFRUVi9ejVmzZoFHx8fDB8+HCtXrsTrr7+OdevWISQkBC+//DIOHz6MwsJCtj20EfX19diyZQt0Oh22bNkCPz8/JCcnQ6PRYPLkyR0K0jdu3IhHH30UX3zxhfIwxd598cUXWLhwISoqKuDt7a12OURdhuE5ERFBCIEzZ85Aq9VCp9MhNzcXt99+OyRJQnJyMoKCgn4xSG9ubsZDDz0EvV6PnTt32vSCKTg4GIsXL8Zjjz2mvObu7s7p8ERERETUpbKzszFr1qyfvb5o0SKsXbsWQggsW7YMH3/8MWpqajB9+nS8//77GDNmjArV0i9pbGzE9u3bodVqsWnTJri7uyMpKQkajQbTpk2Dq6vrL36OrVu3YuHChVi7di3uv//+Hqi66x08eBDff/89Zs2aBXd3dxw8eBDPPvss4uPjsW7dOrXLI+pSDM+JiKgVIQQuXLigBOnff/89pkyZguTkZEiShGHDhv0sSDeZTFi4cCHOnz+P3bt3w9fXV6Xq2yc4OBjPPPMMnnnmGbVLISIiIiIiO2Q0GrFr1y5otVpkZmaib9++SExMREpKCu644w706dPnZ/+f3bt348EHH8THH3+MBQsWqFB118jNzcUf/vAHFBUVobm5GSEhIXj44Yfx3HPPsd85ORyG50REdF1CCFy5cgU6nQ46nQ779u1DVFQUJEmCJEkICQmBxWLB4sWLcfz4cWRlZcHf31/tsn9RcHAwjEYjTCYThg8fjgULFuDZZ59F79691S6NiIiIiIjsjMlkQlZWFlJTU5GRkQFZlpGQkICUlBTMnDkTffv2xd69e3H//ffj3XffxcKFCzs9a4qIegbDcyIiahchBPR6PdLT06HT6ZCdnY1x48bBxcUFjY2N2Lt3LwYPHqx2me2yevVqREdHw8fHBwcOHMCLL76IRx55BKtXr1a7NCIiIiIismNmsxnffvstUlNTkZ6ejsbGRkyePBn79+/Hf//3f+Oxxx5jcE5kRxieExHRTRNCoKqqCl9++SVef/11fPPNNxg1apSqNS1duhQrV6684cccP34cY8eO/dnrn376KR5//HEYDAYeMyQiIiIioi5hsVhw4MABLFu2DEOGDMFnn33G4JzIzjA8JyIih1BeXo7KysobfszIkSPRt2/fn71+7NgxTJgwAUVFRQgLC+uuEomIiIiIiIjIjrC5KxEROQR/f/8O91vPz89Hr169EBAQ0MVVEREREREREZG96qV2AUREatm7dy+SkpIwZMgQuLi4ID09vdWf//a3v4WLi0ur/+Li4tQplrrMwYMH8dZbb6GgoADFxcX44osv8Oyzz+Khhx6Ct7e32uURERERERERkY3gznMicloNDQ2IiIjAo48+innz5l3zY+Li4vDPf/5T+d/sh23/+vXrh6+++grLly9Hc3MzQkJC8Oyzz+K5555TuzQiIiIiIiIisiEMz4nIacXHxyM+Pv6GH9OvXz8MHjy4hyqinhAdHY3vvvtO7TKIiIiIiIiIyMaxbQsR0Q1kZ2cjICAAYWFheOKJJ35xICURERERERERETkG7jwnIrqOuLg4zJs3DyEhIThz5gxeeuklxMfH4+DBg3B1dVW7PCIiIiIiIiIi6kbceU5EdB3z589HcnIywsPDodFosGnTJvzwww/Izs5WuzQiIiIiIiKbtnfvXiQlJWHIkCFwcXFBenp6qz//7W9/CxcXl1b/xcXFqVMsEdF1MDwnImqnkSNHws/PD6dPn1a7FCIiIiIiIpvW0NCAiIgIvPfee9f9mLi4OJSUlCj//e///m8PVkhE9MvYtoWIqJ0uXbqEyspKBAUFqV0KERERERGRTYuPj0d8fPwNP6Zfv34YPHhwD1VERHTzuPOciJyWwWBAfn4+8vPzAQBnz55Ffn4+Lly4AIPBgP/4j//Ad999h3PnzmH37t2QJAmjRo3CnDlz1C2ciIiIiIjIAWRnZyMgIABhYWF44oknUFlZqXZJREStuAghhNpFEBGpITs7G7NmzfrZ64sWLcIHH3wAjUaDvLw81NTUYMiQIZg9ezb+8pe/IDAwUIVqiYiIiIiI7JOLiwvS0tKg0WiU17766isMHDgQISEhOHPmDF566SW4ubnh4MGDcHV1Va9YIqKrMDwnIiIiIiIiIqJuc63wvK3i4mKEhoZi165duOeee3quOCKiG2DbFiIiIiIiIiIiUtXIkSPh5+eH06dPq10KEZGC4TkREREREREREanq0qVLqKysRFBQkNqlEBEpeqtdABERERERERERORaDwdBqF/nZs2eRn58PHx8f+Pj44NVXX8V9992HwYMH48yZM3jhhRcwatQozJkzR8WqiYhaY89zIiIiIiIiIiLqUtnZ2Zg1a9bPXl+0aBE++OADaDQa5OXloaamBkOGDMHs2bPxl7/8BYGBgSpUS0R0bQzPiYiIiIiIiIiIiIjaYM9zIiIiIiIiIiIiIqI2GJ4TEREREREREREREbXB8JyIiIiIiIiIiIiIqA2G50REREREREREREREbTA8JyIiIiIiIiIiIiJqg+E5EREREREREREREVEbDM+JiIiIiIiIiIiIiNpgeE5ERERERERERERE1AbDcyIiIiIiIiIiIiKiNhieExERERERERERERG1wfCciIiIiIiIiIiIiKgNhudERERERERERERERG0wPCciIiIiIiIiIiIiaoPhORERERERERERERFRGwzPiYiIiIiIiIiIiIjaYHhORERERERERERERNQGw3MiIiIiIiIiIiIiojYYnhMRERERERERERERtcHwnIiIiIiIiIiIiIioDYbnRERERERERERERERtMDwnIiIiIiIiIiIiImqD4TkRERERERERERERURsMz4mIiIiIiIiIiIiI2mB4TkRERERERERERETUBsNzIiIiIiIiIiIiIqI2GJ4TEREREREREREREbXB8JyIiIiIiIiIiIiIqA2G50REREREREREREREbTA8JyIiIiIiIiIiIiJqg+E5EREREREREREREVEb/w+PdbuaO74lWQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 2000x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cmap = plt.get_cmap('tab10', len(unique_texts))\n",
    "\n",
    "fig = plt.figure(figsize=(20, 8))  \n",
    "label_dict = {t: i for i, t in enumerate(unique_texts)}\n",
    "colors = []\n",
    "for captions in dataloader_texts:\n",
    "    colors += [cmap(label_dict[caption]) for caption in captions]\n",
    "\n",
    "# First plot\n",
    "ax1 = fig.add_subplot(121, projection='3d')  \n",
    "ax1.scatter(embeddings_images[:, 0], embeddings_images[:, 1], embeddings_images[:, 2], color=\"black\", label='Image Embeddings')\n",
    "ax1.scatter(embeddings_texts[:, 0], embeddings_texts[:, 1], embeddings_texts[:, 2], color=colors, label='Text Embeddings')\n",
    "ax1.legend()\n",
    "ax1.set_title('Image and Text Embeddings Norm without Contrastive Learning')\n",
    "\n",
    "# Second plot\n",
    "ax2 = fig.add_subplot(122, projection='3d') \n",
    "ax2.scatter(embeddings_images_trained[:, 0], embeddings_images_trained[:, 1], embeddings_images_trained[:, 2], color=\"black\", label='Image Embeddings')\n",
    "ax2.scatter(embeddings_texts_trained[:, 0], embeddings_texts_trained[:, 1], embeddings_texts_trained[:, 2], color=colors, label='Text Embeddings')\n",
    "ax2.legend()\n",
    "ax2.set_title('Fine Tuned Image and Text Embeddings Norm')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 297,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(training_losses)\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Training Loss')\n",
    "plt.title('Training Loss per Epoch for Contrastive Learning')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 298,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Test Set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 299,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = pd.read_csv(\"Kather_test.csv\", index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 300,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7180\n"
     ]
    }
   ],
   "source": [
    "image_filenames = []\n",
    "for dirpath, _, filenames in os.walk(\"CRC-VAL-HE-7K\"):\n",
    "    for filename in (f for f in filenames if f.endswith('.tif')):\n",
    "        # base_name = filename.split('.')[0]\n",
    "        image_filenames.append(filename)\n",
    "print(len(image_filenames))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 301,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7180\n"
     ]
    }
   ],
   "source": [
    "matched_df = df2.set_index('filename').reindex(image_filenames).reset_index()\n",
    "texts2 = matched_df['caption']\n",
    "print(len(texts2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 302,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded 7180 images.\n"
     ]
    }
   ],
   "source": [
    "tif_files2 = []\n",
    "for dirpath, _, filenames in os.walk(\"CRC-VAL-HE-7K\"):\n",
    "    for filename in [f for f in filenames if f.endswith('.tif')]:\n",
    "        tif_files2.append(os.path.join(dirpath, filename))\n",
    "\n",
    "# Use Image.open() to load images and store them as PIL Images in a list\n",
    "image_list2 = []\n",
    "for tif_file in tif_files2:\n",
    "    with Image.open(tif_file).convert('RGB') as img:\n",
    "        image_list2.append(img.copy())\n",
    "\n",
    "# Print the number of loaded images\n",
    "print(f\"Loaded {len(image_list2)} images.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 303,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7180\n"
     ]
    }
   ],
   "source": [
    "processed_images2 = []\n",
    "for img in image_list2:\n",
    "    processed_img = preprocess(img)\n",
    "    processed_images2.append(processed_img)\n",
    "print(len(processed_images2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 304,
   "metadata": {},
   "outputs": [],
   "source": [
    "# End Test Set "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calculate_f1_score(self, outputs, labels, average='weighted'):\n",
    "    outputs = outputs.cpu().numpy()\n",
    "    labels = labels.cpu().numpy()\n",
    "    predicted_labels = np.argmax(outputs, axis=1)\n",
    "    # axis = 1 returns the index of the maximum value along each row\n",
    "    f1 = f1_score(labels, predicted_labels, average=average)\n",
    "    return f1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 306,
   "metadata": {},
   "outputs": [],
   "source": [
    "class LinearClassifier(nn.Module):\n",
    "    def __init__(self, input_size, num_classes):\n",
    "        super(LinearClassifier, self).__init__()\n",
    "        self.fc = nn.Linear(input_size, num_classes)\n",
    "        # input: (batch_size, input_size)\n",
    "        # output: (batch_Size, num_classes)\n",
    "        \n",
    "    def forward(self, x):\n",
    "        x = x.to(self.fc.weight.dtype)\n",
    "        # ensuring that the input x has the same data type\n",
    "        out = self.fc(x)\n",
    "        return out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 307,
   "metadata": {},
   "outputs": [],
   "source": [
    "input_size = 512\n",
    "num_classes = len(unique_texts)\n",
    "linear_classifier = LinearClassifier(input_size, num_classes)\n",
    "linear_classifier = linear_classifier.to(device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 308,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['cancer-associated stroma', 'mucus', 'debris', 'smooth muscle', 'lymphocytes', 'adipose tissue', 'normal colon mucosa', 'background', 'colorectal adenocarcinoma epithelium']\n",
      "smooth muscle\n"
     ]
    }
   ],
   "source": [
    "descriptions = {\n",
    "    'An H&E image patch of cancer-associated stroma.', \n",
    "    'An H&E image patch of lymphocytes.', \n",
    "    'An H&E image patch of mucus.', \n",
    "    'An H&E image patch of smooth muscle.', \n",
    "    'An H&E image patch of background.', \n",
    "    'An H&E image patch of normal colon mucosa.', \n",
    "    'An H&E image patch of debris.', \n",
    "    'An H&E image patch of colorectal adenocarcinoma epithelium.', \n",
    "    'An H&E image patch of adipose tissue.'\n",
    "}\n",
    "\n",
    "labels = [' '.join(desc.split()[5:]).rstrip('.') for desc in descriptions]\n",
    "\n",
    "print(labels)\n",
    "print(labels[3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 309,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 1, 2, 3, 4, 5, 6, 7, 8]\n"
     ]
    }
   ],
   "source": [
    "label_to_int = {label: idx for idx, label in enumerate(labels)}\n",
    "int_labels = [label_to_int[label] for label in labels]\n",
    "print(int_labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 310,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100000\n",
      "['adipose tissue', 'adipose tissue', 'adipose tissue', 'adipose tissue', 'adipose tissue', 'adipose tissue', 'adipose tissue', 'adipose tissue', 'adipose tissue', 'adipose tissue']\n"
     ]
    }
   ],
   "source": [
    "texts_labels = [' '.join(desc.split()[5:]).rstrip('.') for desc in texts]\n",
    "print(len(texts_labels))\n",
    "print(texts_labels[0:10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 311,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100000\n",
      "[5 5 5 5 5 5 5 5 5 5]\n"
     ]
    }
   ],
   "source": [
    "texts_labels_int = [label_to_int[label] for label in texts_labels]\n",
    "texts_labels_int = np.array(texts_labels_int)\n",
    "print(len(texts_labels_int))\n",
    "print(texts_labels_int[0:10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 312,
   "metadata": {},
   "outputs": [],
   "source": [
    "class LinearClassifierDataset(Dataset):\n",
    "    def __init__(self, image_embeddings, labels):\n",
    "        self.image_embeddings = image_embeddings\n",
    "        self.labels = labels\n",
    "        assert len(self.image_embeddings) == len(self.labels), \"Mismatched Lengths!\"\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.image_embeddings)\n",
    "\n",
    "    def __getitem__(self, idx):\n",
    "        return self.image_embeddings[idx], self.labels[idx]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 313,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1000\n",
      "30000\n"
     ]
    }
   ],
   "source": [
    "epochs = 30\n",
    "batch_size = 100\n",
    "train_dataset_linear_classifier = LinearClassifierDataset(image_embeddings_initial, texts_labels_int)\n",
    "train_dataloader_linear_classifier = DataLoader(train_dataset_linear_classifier, batch_size = batch_size, shuffle = True)\n",
    "num_batches_per_epoch = len(train_dataloader_linear_classifier)\n",
    "print(num_batches_per_epoch)\n",
    "total_steps = len(train_dataloader_linear_classifier) * epochs\n",
    "print(total_steps)\n",
    "optimizer = optim.Adam(linear_classifier.parameters(), lr=0.0001)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 314,
   "metadata": {},
   "outputs": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train_loss_this_epoch is: 1380.9139196276665\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
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    {
     "name": "stdout",
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     "text": [
      "train_loss_this_epoch is: 794.5935995578766\n"
     ]
    },
    {
     "name": "stderr",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train_loss_this_epoch is: 595.1386281549931\n"
     ]
    },
    {
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    },
    {
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     "text": [
      "train_loss_this_epoch is: 489.07670614123344\n"
     ]
    },
    {
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    {
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      "train_loss_this_epoch is: 421.9143507182598\n"
     ]
    },
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      "train_loss_this_epoch is: 375.507651925087\n"
     ]
    },
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      "train_loss_this_epoch is: 341.6844856888056\n"
     ]
    },
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      "train_loss_this_epoch is: 315.885734975338\n"
     ]
    },
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      "train_loss_this_epoch is: 295.66358114778996\n"
     ]
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      "train_loss_this_epoch is: 279.2547284066677\n"
     ]
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      "train_loss_this_epoch is: 265.7034510821104\n"
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      "train_loss_this_epoch is: 254.32971148192883\n"
     ]
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      "train_loss_this_epoch is: 236.06659381091595\n"
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      "train_loss_this_epoch is: 228.58264046907425\n"
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      "train_loss_this_epoch is: 221.9393739029765\n"
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      "train_loss_this_epoch is: 175.46486833691597\n"
     ]
    },
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     "text": [
      "train_loss_this_epoch is: 173.1502898260951\n"
     ]
    },
    {
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      "train_loss_this_epoch is: 170.87515764683485\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "training_losses_linear_classifier = []\n",
    "criterion = nn.CrossEntropyLoss()\n",
    "\n",
    "for epoch in range(epochs):\n",
    "    train_loss_this_epoch = 0\n",
    "    for i, batch in enumerate(tqdm.tqdm(train_dataloader_linear_classifier, desc=f\"{epoch}/{epochs}\", position=0)):\n",
    "        optimizer.zero_grad()\n",
    "\n",
    "        images_embeddings, labels = batch\n",
    "        images_embeddings = images_embeddings.to(device)\n",
    "        labels = labels.to(device)\n",
    "        \n",
    "        outputs = linear_classifier(images_embeddings)\n",
    "        total_loss = criterion(outputs, labels)  \n",
    "        \n",
    "        total_loss.backward()\n",
    "        train_loss_this_epoch += total_loss.detach().cpu().item()  \n",
    "        \n",
    "        optimizer.step()\n",
    "        \n",
    "    print(f\"train_loss_this_epoch is: {train_loss_this_epoch}\")\n",
    "    training_losses_linear_classifier.append(train_loss_this_epoch)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 315,
   "metadata": {},
   "outputs": [],
   "source": [
    "input_size = 512\n",
    "num_classes = len(unique_texts)\n",
    "linear_classifier_two = LinearClassifier(input_size, num_classes)\n",
    "linear_classifier_two = linear_classifier_two.to(device)\n",
    "optimizer_two = optim.Adam(linear_classifier_two.parameters(), lr=0.0001)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 316,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_dataset_linear_classifier_new = LinearClassifierDataset(image_embeddings_trained, texts_labels_int)\n",
    "train_dataloader_linear_classifier_new = DataLoader(train_dataset_linear_classifier_new, batch_size=batch_size, shuffle = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 317,
   "metadata": {},
   "outputs": [
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     "output_type": "stream",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train_loss_this_epoch is: 420.2966992966831\n"
     ]
    },
    {
     "name": "stderr",
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    },
    {
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     "text": [
      "train_loss_this_epoch is: 23.37032890599221\n"
     ]
    },
    {
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    },
    {
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      "train_loss_this_epoch is: 8.24476455617696\n"
     ]
    },
    {
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    {
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      "train_loss_this_epoch is: 3.941247187787667\n"
     ]
    },
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      "train_loss_this_epoch is: 2.134099655668251\n"
     ]
    },
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      "train_loss_this_epoch is: 1.2352483692811802\n"
     ]
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     ]
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     ]
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      "train_loss_this_epoch is: 0.07746438608955941\n"
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      "train_loss_this_epoch is: 0.0722652068025127\n"
     ]
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train_loss_this_epoch is: 0.06308419453398528\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "19/30: 100%|██████████| 1000/1000 [00:01<00:00, 560.11it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train_loss_this_epoch is: 0.06189876159930918\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "20/30: 100%|██████████| 1000/1000 [00:01<00:00, 568.94it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train_loss_this_epoch is: 0.060214570878429186\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "21/30: 100%|██████████| 1000/1000 [00:01<00:00, 566.64it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train_loss_this_epoch is: 0.05963805841423664\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "22/30: 100%|██████████| 1000/1000 [00:01<00:00, 567.17it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train_loss_this_epoch is: 0.06116961793185283\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "23/30: 100%|██████████| 1000/1000 [00:01<00:00, 564.51it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train_loss_this_epoch is: 0.05914391401324792\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "24/30: 100%|██████████| 1000/1000 [00:01<00:00, 567.53it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train_loss_this_epoch is: 0.05428305338276118\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "25/30: 100%|██████████| 1000/1000 [00:01<00:00, 564.27it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train_loss_this_epoch is: 0.05818266973253117\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "26/30: 100%|██████████| 1000/1000 [00:01<00:00, 567.20it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train_loss_this_epoch is: 0.054015637328575394\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "27/30: 100%|██████████| 1000/1000 [00:01<00:00, 533.44it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train_loss_this_epoch is: 0.05668079354381916\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "28/30: 100%|██████████| 1000/1000 [00:01<00:00, 556.43it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train_loss_this_epoch is: 0.057236745615554696\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "29/30: 100%|██████████| 1000/1000 [00:01<00:00, 560.77it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train_loss_this_epoch is: 0.05189840936901646\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "training_losses_linear_classifier_new = []\n",
    "\n",
    "for epoch in range(epochs):\n",
    "    train_loss_this_epoch = 0\n",
    "    for i, batch in enumerate(tqdm.tqdm(train_dataloader_linear_classifier_new, desc=f\"{epoch}/{epochs}\", position=0)):\n",
    "        optimizer_two.zero_grad()\n",
    "\n",
    "        images_embeddings, labels = batch\n",
    "        images_embeddings = images_embeddings.to(device)\n",
    "        labels = labels.to(device)\n",
    "        \n",
    "        outputs = linear_classifier_two(images_embeddings)\n",
    "        total_loss = criterion(outputs, labels)  \n",
    "        \n",
    "        total_loss.backward()\n",
    "        train_loss_this_epoch += total_loss.detach().cpu().item()  \n",
    "        \n",
    "        optimizer_two.step()\n",
    "        \n",
    "    print(f\"train_loss_this_epoch is: {train_loss_this_epoch}\")\n",
    "    training_losses_linear_classifier_new.append(train_loss_this_epoch)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 318,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(training_losses_linear_classifier, label='Initial Embeddings')\n",
    "plt.plot(training_losses_linear_classifier_new, label='Trained Embeddings')\n",
    "\n",
    "plt.legend()\n",
    "\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Training Loss')\n",
    "plt.title('Training Loss per Epoch for the Linear Classifier')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 319,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calculate_percentage(arr, threshold1, threshold2):\n",
    "    count = sum(1 for num in arr if threshold1 < num < threshold2)\n",
    "    percentage = (count / len(arr)) * 100\n",
    "    return f\"{int(percentage)}%\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 320,
   "metadata": {},
   "outputs": [],
   "source": [
    "def retrieval(text_norm, img_norm):\n",
    "    score = text_norm.dot(img_norm.T)\n",
    "    score_tensor = torch.tensor(score, dtype=torch.float32)\n",
    "    score_softmaxed = torch.nn.functional.softmax(score_tensor, dim=-1).numpy() # apply on the last dimension/row-wise\n",
    "    best = score_softmaxed.argsort()[-100:][::-1]\n",
    "    return best "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 321,
   "metadata": {},
   "outputs": [],
   "source": [
    "text_image = []\n",
    "best1 = retrieval(text_embeddings_trained_norm[0], image_embeddings_trained_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 322,
   "metadata": {},
   "outputs": [],
   "source": [
    "initial_text_image = []\n",
    "initial1 = retrieval(text_embeddings_initial_norm[0], image_embeddings_initial_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 323,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%\n"
     ]
    }
   ],
   "source": [
    "percentage1 = calculate_percentage(best1, 0, 10407)\n",
    "print(percentage1)\n",
    "text_image.append(percentage1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 324,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0%\n"
     ]
    }
   ],
   "source": [
    "initial_percentage1 = calculate_percentage(initial1, 0, 10407)\n",
    "print(initial_percentage1)\n",
    "initial_text_image.append(initial_percentage1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 325,
   "metadata": {},
   "outputs": [],
   "source": [
    "best2 = retrieval(text_embeddings_trained_norm[10408], image_embeddings_trained_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 326,
   "metadata": {},
   "outputs": [],
   "source": [
    "initial2 = retrieval(text_embeddings_initial_norm[10408], image_embeddings_initial_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 327,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%\n"
     ]
    }
   ],
   "source": [
    "percentage2 = calculate_percentage(best2, 10407, 20973)\n",
    "print(percentage2)\n",
    "text_image.append(percentage2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 328,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0%\n"
     ]
    }
   ],
   "source": [
    "initial_percentage2 = calculate_percentage(initial2, 0, 10407)\n",
    "print(initial_percentage2)\n",
    "initial_text_image.append(initial_percentage2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 329,
   "metadata": {},
   "outputs": [],
   "source": [
    "best3 = retrieval(text_embeddings_trained_norm[20974], image_embeddings_trained_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 330,
   "metadata": {},
   "outputs": [],
   "source": [
    "initial3 = retrieval(text_embeddings_initial_norm[20974], image_embeddings_initial_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 331,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%\n"
     ]
    }
   ],
   "source": [
    "percentage3 = calculate_percentage(best3, 20973, 32485)\n",
    "print(percentage3)\n",
    "text_image.append(percentage3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 332,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0%\n"
     ]
    }
   ],
   "source": [
    "initial_percentage3 = calculate_percentage(initial3, 0, 10407)\n",
    "print(initial_percentage3)\n",
    "initial_text_image.append(initial_percentage3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 333,
   "metadata": {},
   "outputs": [],
   "source": [
    "best4 = retrieval(text_embeddings_trained_norm[32486], image_embeddings_trained_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 334,
   "metadata": {},
   "outputs": [],
   "source": [
    "initial4 = retrieval(text_embeddings_initial_norm[32486], image_embeddings_initial_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 335,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%\n"
     ]
    }
   ],
   "source": [
    "percentage4 = calculate_percentage(best4, 32485, 44042)\n",
    "print(percentage4)\n",
    "text_image.append(percentage4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 336,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0%\n"
     ]
    }
   ],
   "source": [
    "initial_percentage4 = calculate_percentage(initial4, 0, 10407)\n",
    "print(initial_percentage4)\n",
    "initial_text_image.append(initial_percentage4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 337,
   "metadata": {},
   "outputs": [],
   "source": [
    "best5 = retrieval(text_embeddings_trained_norm[44043], image_embeddings_trained_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 338,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%\n"
     ]
    }
   ],
   "source": [
    "percentage5 = calculate_percentage(best5, 44042, 52938)\n",
    "print(percentage5)\n",
    "text_image.append(percentage5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 339,
   "metadata": {},
   "outputs": [],
   "source": [
    "best6 = retrieval(text_embeddings_trained_norm[52939], image_embeddings_trained_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 340,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%\n"
     ]
    }
   ],
   "source": [
    "percentage6 = calculate_percentage(best6, 52938, 66474)\n",
    "print(percentage6)\n",
    "text_image.append(percentage6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 341,
   "metadata": {},
   "outputs": [],
   "source": [
    "best7 = retrieval(text_embeddings_trained_norm[66475], image_embeddings_trained_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 342,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%\n"
     ]
    }
   ],
   "source": [
    "percentage7 = calculate_percentage(best7, 66474, 75237)\n",
    "print(percentage7)\n",
    "text_image.append(percentage7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 343,
   "metadata": {},
   "outputs": [],
   "source": [
    "best8 = retrieval(text_embeddings_trained_norm[75238], image_embeddings_trained_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 344,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%\n"
     ]
    }
   ],
   "source": [
    "percentage8 = calculate_percentage(best8, 75237, 85683)\n",
    "print(percentage8)\n",
    "text_image.append(percentage8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 345,
   "metadata": {},
   "outputs": [],
   "source": [
    "best9 = retrieval(text_embeddings_trained_norm[85684], image_embeddings_trained_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 346,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%\n"
     ]
    }
   ],
   "source": [
    "percentage9 = calculate_percentage(best9, 85683, 100000)\n",
    "print(percentage9)\n",
    "text_image.append(percentage9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 347,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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z82/btg0ymQzjx49Xu+/jYUC+dB1pup3s27cPxsbG6N27t3JeAwMDBAUFqSzvyZMniIyMREBAgMr5W5UrV0aTJk3w559/qtXwv//9L8s6t2/fjrS0NHTs2FGlTnt7e7i6uiq3r5zYV3Xq1AlFihRR/l2/fn0AqvuO7HB3d1cuCwCKFSuG8uXLqyxXF6/jhIQEvHnzBnZ2dpleNGBoaAi5XA7gw7mjr169QkpKCqpXr44LFy5o1a9Pn8/69eur9UnT9y0g4/1bdqXvs9+8eaNs+/g19ObNG7x48QL169fH27dvcf369SyXqem6K1y4MBISEnDgwIFMl6XL/XZO4cUTOezWrVuIjY2Fra1thvc/e/ZM5e9hw4Zh48aNOHPmDKZNm6bRGxTw4YU1ZMgQzJkzB+vWrUP9+vXxzTffoFu3bsodqbYePHgAV1dXGBio5v/0K3wfPHiQreV+HAyA/9vROzo6Ztj++vVrZdvDhw8xbtw47N69W6UdgPJNMr2usmXLqj122bJlVV7Imj4/3t7e8Pf3x8SJEzF37lw0aNAAbdq0wbfffguFQpFln52dndXabt26hUuXLqFYsWKffeysGBkZoWTJkllOp8222KlTJ+zcuRMnT55EnTp1cOfOHZw/f15tKIHjx49j/PjxOHnypNqbdGxsbLa3vY89ePAADg4OKqEfyHw7zGhdZ2bbtm3o1KkTAgMDAXx4AxgyZAiOHDmCGzdufHbeO3fuwMHBIcuT2790HWm6nTx48ADFixdHoUKFVO7/9HWQvr7Kly+vtqwKFSpg//79ygsk0mmyTm/dugUhBFxdXTO8P/3Ch5zYV326T0kPeZ/uI750uenL/ni5ungdly1bFt27d8eIESPQpUsXbNmyBYaGhmrThYWFYfbs2bh+/brKB0xttnkTExO1WjPqkzbvW9o8flbi4+MBQOX1fvXqVfz88884dOgQ4uLiVKbX9AOkJuvuxx9/xObNm9G8eXOUKFECTZs2RceOHdGsWTPlNLrab+ckBrsclpaWBltbW6xbty7D+z/dOO7evYtbt24BAC5fvqzVY82ePRsBAQHYtWsX/vrrLwwYMADBwcE4deqURm/8uSWjHdbn2tOPGqWmpqJJkyZ49eoVRowYATc3N5iZmeG///5DQEBAtoZB0PT5kclk2Lp1K06dOoU9e/Zg//79CAwMxOzZs3Hq1KksB/3M6AqxtLQ0NGnSBMOHD89wnnLlymnUB4VCoRa+M6LNtujn54dChQph8+bNqFOnDjZv3gwDAwN06NBBOc2dO3fQuHFjuLm5Yc6cOXB0dIRcLseff/6JuXPn6m2oFW2uNi5RogSOHTuGW7duITo6Gq6urrC3t4eDg4PG6/9zdLGOdLWdfAlN1mlaWhpkMhn27t2b4Wv549eIrvdVWe07skuT5erq+Rk+fDhevnyJmTNnonfv3li1apXKkd/ffvsNAQEBaNOmDYYNGwZbW1sYGhoiODgYd+7c+eI+fUzb9y1dXuF/5coVAP/3gSQmJgbe3t6wtLTEpEmT4OLiAhMTE1y4cAEjRozQ6DWk6bqztbVFZGQk9u/fj71792Lv3r0ICQlB9+7dERYWBiBvvB6zwmCXw1xcXHDw4EHUrVs3y40/LS0NAQEBsLS0xKBBgzBt2jS0b98e7dq1U06T1UjvHh4e8PDwwM8//4wTJ06gbt26WLZsGaZMmZLpPJkt08nJCZcuXUJaWppKcEg/9O3k5PTZWnTt8uXLuHnzJsLCwtC9e3dl+6eHzdPrun37ttoyPm3T5vkBgFq1aqFWrVqYOnUq1q9fj65du2Ljxo3o1auX1v1xcXFBfHw8fHx8Pjudrkb316avZmZmaNWqFbZs2YI5c+Zg06ZNqF+/PhwcHJTT7NmzB0lJSdi9e7fKkY1Pv6b5Uk5OTjh48CDevHmj8ilel9uhq6ur8kjTtWvX8OTJkyzHk3NxccH+/fvx6tWrTI/aabOOMnueNd1OnJyccPjwYbx9+1blqN2n23z6+sroiOT169dhY2OjcrROUy4uLhBCwNnZWaM3t+zsq3RNF68tTZ8fTcyYMQOvXr3Cr7/+iiJFimD27NnK+7Zu3YoyZcpg+/btKnV/eiqArvqkzX5Rl9auXQuZTIYmTZoAACIiIvDy5Uts374dX3/9tXK6e/fuqc2bWd81XXcAIJfL4efnBz8/P6SlpeHHH3/E8uXLMXbsWJQtWzbX99vZwXPscljHjh2RmpqKyZMnq92XkpKCmJgY5d9z5szBiRMnsGLFCkyePBl16tRB37598eLFC+U06Tvcj+cDgLi4OKSkpKi0eXh4wMDAAElJSZ+t0czMLMPD2S1atEB0dLTKeEIpKSlYuHAhzM3N4e3t/dnl6lr6J82PPy0LITB//nyV6RwcHFCpUiWsWbNGeVgf+DA+1KdHQTV9fl6/fq326T99gOis1m9mOnbsiJMnT2Y4EG5MTIzy+Ux/k/70Oc/O42m6LQIfvo59/Pgxfv31V0RFRaFTp04q92f0fMTGxiIkJOSL6vxUixYtkJqaikWLFqm0z507FzKZDM2bN9fZY6WlpWH48OEoVKhQlueV+fv7QwihHIT0Y+nrRJt1ZGZmluFzrOl24uvri+TkZKxcuVKlP4sXL1aZp3jx4vD09ERYWJjK4125cgV//fUXWrRo8ZleZ65du3YwNDTExIkT1V4rQgi8fPkSwJftq3Qts/2pNjR9fjS1fPlytG/fHnPmzFEJuRltS6dPn8bJkydV5tfF/kLbfYWuTJ8+HX/99Rc6deqk/KCVUb/fv3+PJUuWqM2f2XuZpusufRtNZ2BggMqVKwP4v/18bu+3s4NH7HKYt7c3fvjhBwQHByMyMhJNmzaFsbExbt26hS1btmD+/Plo3749/vnnH4wdOxYBAQHKQVFDQ0Ph6emp/N4f+PBJqnDhwli2bBksLCxgZmaGmjVrIioqCv369UOHDh1Qrlw5pKSkYO3atTA0NIS/v/9na/Ty8sKmTZswZMgQ1KhRA+bm5vDz80OfPn2wfPlyBAQE4Pz58yhdujS2bt2K48ePY968eWrnPOU0Nzc3uLi44KeffsJ///0HS0tLbNu2LcPzaKZNm4bWrVujbt26+P777/H69WssWrQIlSpVUgl7mj4/YWFhWLJkCdq2bQsXFxe8efMGK1euhKWlZbbfCIcNG4bdu3ejVatWCAgIgJeXFxISEnD58mVs3boV9+/fh42NDUxNTeHu7o5NmzahXLlysLa2RqVKlbT+uTZN+5quRYsWsLCwwE8//ZThdtS0aVPlp9sffvgB8fHxWLlyJWxtbfHkyZNsrZOM+Pn5oWHDhhgzZgzu37+PKlWq4K+//sKuXbswaNAguLi4ZHvZAwcORGJiIjw9PZGcnIz169fjzJkzCAsLy/D8qo81bNgQ3333HRYsWIBbt26hWbNmSEtLw99//42GDRuiX79+Wq0jLy8vLF26FFOmTEHZsmVha2uLRo0aabydtGnTBl999RWGDh2K27dvw83NDbt371b+HNXHRxBmzZqF5s2bo3bt2ujZsyfevXuHhQsXwsrKChMmTMjWunRxccGUKVMwatQo3L9/H23atIGFhQXu3buHHTt2oE+fPvjpp59w6NChbO+rdM3T0xOGhoaYMWMGYmNjoVAo0KhRo0zPLcuIps+PpgwMDLBu3TrExsZi7NixsLa2xo8//ohWrVph+/btaNu2LVq2bIl79+5h2bJlcHd3V9mn6WJ/oe2+QlspKSn47bffAACJiYl48OABdu/ejUuXLqFhw4ZYsWKFcto6deqgSJEi6NGjBwYMGACZTIa1a9dm+DV7Zu9lmq67Xr164dWrV2jUqBFKliyJBw8eYOHChfD09FSe05vb++1sydVrcAuAjMaxE0KIFStWCC8vL2FqaiosLCyEh4eHGD58uHj8+LFISUkRNWrUECVLllQboHP+/PkCgNi0aZOybdeuXcrBV/H/hzG4e/euCAwMFC4uLsLExERYW1uLhg0bqg14nJH4+Hjx7bffisKFC6sNB/L06VPx/fffCxsbGyGXy4WHh4faUCuZ+dwAxR/7eJDRj6UPyPzxsAjXrl0TPj4+wtzcXNjY2IjevXuLqKioDIeA2bhxo3BzcxMKhUJUqlRJ7N69W/j7+ws3Nze1Wj/3/AghxIULF0SXLl1EqVKllIN1tmrVSpw7dy7L9ZA+gGdG3rx5I0aNGiXKli0r5HK5sLGxEXXq1BG//PKLylhRJ06cEF5eXkIul6tcQv+5oQMyGsdOk75+rGvXrgKA8PHxyfAxdu/eLSpXrqwcsHnGjBli9erVasPUfMlwJ0J8WE+DBw8WDg4OwtjYWLi6un52gGJNhYSEiCpVqggzMzNhYWEhGjdunOGgpZlJSUkRs2bNEm5ubkIul4tixYqJ5s2bi/Pnzyun0XQdRUdHi5YtWwoLCwuBTwYo1nQ7ef78ufj222+VAxQHBASI48ePCwBi48aNKrUfPHhQ1K1bV5iamgpLS0vh5+eX6QDFGY2rltkAxdu2bRP16tUTZmZmwszMTLi5uYmgoCDlgLNfsq/63ADFn4KGQ02sXLlSlClTRhgaGqoMfZLZ6zajbVnT5ycjmW3z8fHxolatWsLAwECsW7dOpKWliWnTpgknJyehUChE1apVxe+//57h61zb/UVmz6Um+4rP7d8ykj7kSvqtUKFConTp0sLf319s3bo1w0Gdjx8/LmrVqiVMTU2Fg4ODGD58uNi/f7/aUDWZvZdpuu62bt0qmjZtKmxtbYVcLhelSpUSP/zwg3jy5IlKPV+6385pMiG+8OxSonzE09MTxYoV++zl7ERSsnPnTrRt2xbHjh1D3bp19V0OEeUwnmNHkpScnKx2bktERASioqLy7A9jE32pT8feS01NxcKFC2FpaYlq1arpqSoiyk08x44k6b///oOPjw+6desGBwcHXL9+HcuWLYO9vb1Gg60S5Uf9+/fHu3fvULt2bSQlJWH79u04ceIEpk2blutXNxKRfvCrWJKk2NhY9OnTB8ePH8fz589hZmaGxo0bY/r06V90sj1RXrZ+/XrMnj0bt2/fRmJiIsqWLYu+ffuiX79++i6NiHIJgx0RERGRRPAcOyIiIiKJYLAjIiIikghePIEPo7M/fvwYFhYWev0ZECIiIqJPCSHw5s0bODg4ZPnb4Ax2AB4/fgxHR0d9l0FERESUqUePHqFkyZKfnYbBDlD+NNajR49gaWmp52qIiIiI/k9cXBwcHR01+ynPXPl9izwuNjZWABCxsbH6LiVDJ06cEAYGBqJFixYq7ek/p5N+Mzc3F+7u7uLHH38UN2/eVJk2JCREWFlZ5WLVqj79GRlra2vh6+sroqKi1Kbt06ePMDAwEJs3b85wWbdu3RIBAQGiRIkSQi6Xi9KlS4vOnTuLs2fPKqcBIHbs2KH8+/3796Jz587CwcFBXL58Wef9y8jHfTYyMhK2trbCx8dHrFq1SuVnc5ycnFTWTfotODhYCKH+PBsbGwsXFxcxefJktZ/U0pcePXqI1q1bCyGESExMFO7u7qJ3795q0w0bNkyULl1axMXFiZCQEAEgw59427x5s9rP2+lD+nP4ww8/qN33448/CgCiR48eQogPPw01cOBAtekyeu3FxsaK0aNHi/LlywuFQiHs7OxE48aNxbZt2/TynOZEPxMSEsTIkSNFmTJlhEKhEDY2NuLrr78WO3fuzKFefJDel/TXT7odO3ao/GxWSkqKmDNnjqhUqZJQKBSicOHColmzZuLYsWNq/Up/7clkMmFvby86duwoHjx4oDKdt7d3ho8rhBAtWrTI1Z+UEkKIZ8+eif/973/C0dFRyOVyYWdnJ5o2bSqmTJmS4f7m49vhw4c17nduy6r28ePHK3+O8vXr12rzOzk5iblz56ot7+TJkyrTJSYmCmtra7WfLdMXbXIKL57IB1atWoX+/fvj6NGjePz4sdr9Bw8exJMnTxAVFYVp06bhn3/+QZUqVRAeHq6HajPXrFkzPHnyBE+ePEF4eDiMjIzQqlUrlWnevn2LjRs3Yvjw4Vi9erXaMs6dOwcvLy/cvHkTy5cvx7Vr17Bjxw64ublh6NChGT7u27dv8c033+Ds2bM4duxY7vwI8/+X3uf79+9j7969aNiwIQYOHIhWrVqp/DLGpEmTlOsm/da/f3+VZaU/z7du3cLEiRMxderUDNeRvikUCqxZswahoaHYv3+/sv3UqVOYO3cuQkNDlZ86zczM8OzZM5w8eVJlGatWrUKpUqVyte7MODo6YuPGjSq/6pCYmIj169dnq8aYmBjUqVMHa9aswahRo3DhwgUcPXoUnTp1wvDhwxEbG6vL8jWm637+73//w/bt27Fw4UJcv34d+/btQ/v27fHy5Utdlp0hExMTzJgxA69fv87wfiEEOnfujEmTJmHgwIH4559/EBERAUdHRzRo0AA7d+5Umd7S0hJPnjzBf//9h23btuHGjRvo0KGD2nIdHR0RGhqq0vbff/8hPDwcxYsX11X3NOLv74+LFy8iLCwMN2/exO7du9GgQQN4eHio7Gc6duyosm9+8uQJ6tSpA0Dzfuemj+ucN2+essb0208//aT1Mh0dHRESEqLStmPHDpibm+uq7FzFr2LzuPj4eGzatAnnzp1DdHQ0QkNDMXr0aJVpihYtCnt7ewBAmTJl4Ofnh8aNG6Nnz564c+cODA0N9VG6GoVCoazT3t4eI0eORP369fH8+XMUK1YMALBlyxa4u7tj5MiRcHBwwKNHj5TnPwohEBAQAFdXV/z9998qJ5B6enpi4MCBao8ZExODli1bIj4+HseOHVM+fm75uM8lSpRAtWrVUKtWLTRu3BihoaHo1asXgA+nA2RV28fPs5OTE0JCQnDhwgX07NkzZzuRDV5eXhgzZgx69uyJK1euwMTEBN9//z369+8Pb29v5XRGRkb49ttvsXr1atSuXRsA8O+//yIiIgKDBw/Ghg0b9NUFpWrVquHOnTvYvn07unbtCgDYvn07SpUqBWdnZ62XN3r0aNy/fx83b96Eg4ODsr1cuXLo0qULTExMdFa7NnTdz927d2P+/Plo0aIFAKB06dLw8vLSac2Z8fHxwe3btxEcHIyZM2eq3b9582Zs3boVu3fvhp+fn7J9xYoVePnyJXr16oUmTZrAzMwMACCTyZSvveLFi6Nnz54YMGAA4uLiVE7fadWqFTZv3ozjx48rf5c3LCwMTZs2xcOHD3OyyypiYmLw999/IyIiQvl6c3JywldffaU2rampKZKSkjLc/2ja79z0cZ1WVlYqNWZXjx49sGDBAsybN0/5Cy2rV69Gjx49MHny5C9atj7wiF0et3nzZri5uaF8+fLo1q0bVq9eDZHFmNIGBgYYOHAgHjx4gPPnz+dSpdqJj4/Hb7/9hrJly6Jo0aLK9lWrVqFbt26wsrJC8+bNVT79RkZG4urVqxg6dGiGVwUVLlxY5e/o6GjlTu3IkSO5Huoy06hRI1SpUgXbt2/P9jLOnTuH8+fPo2bNmjqsTLfGjBkDe3t7DBgwAD///DNkMhmmTZumNl1gYCA2b96Mt2/fAgBCQ0PRrFkz2NnZ5XbJmQoMDFT5RL969Wp8//33Wi8nLS0NGzduRNeuXVVCXTpzc3MYGenv87au+gl8eAP+888/8ebNG12VpzFDQ0NMmzYNCxcuxL///qt2//r161GuXDmVUJdu6NChePnyJQ4cOJDhsp89e4YdO3bA0NBQ7UOzXC5H165dVdZhaGgoAgMDv7BH2jE3N4e5uTl27tyJpKQknSzzc/3O77y8vFC6dGls27YNAPDw4UMcPXoU3333nZ4ryx4GuzwuPegAH77Wi42NxZEjR7Kcz83NDQBw//79nCxPK7///rtyh2NhYYHdu3dj06ZNypB269YtnDp1Cp06dQIAdOvWDSEhIcoge+vWLQD/17esDBw4EO/fv8eBAwfUQp++ubm5qTw3I0aMUK6b9Nvff/+tMk+dOnVgbm4OuVyOGjVqoGPHjujevXsuV645IyMjrFmzBlu2bMHChQuxZs2aDI9GVa1aFWXKlMHWrVshhNDLG2FWunXrhmPHjuHBgwd48OABjh8/rnxdauPFixd4/fq1xttwbtNVP4EPR79OnDiBokWLokaNGhg8eDCOHz+u44oz17ZtW3h6emL8+PFq9928eRMVKlTIcL709ps3byrbYmNjYW5uDjMzM9jZ2eHw4cMICgpSHtH7WPoHlYSEBBw9ehSxsbFqp5zkNCMjI4SGhiIsLAyFCxdG3bp1MXr0aFy6dEmr5WjT7/wuMDBQeWpLaGgoWrRoofwmKb9hsMvDbty4gTNnzqBLly4APrxYO3XqhFWrVmU5b3oYykvj8jVs2BCRkZGIjIzEmTNn4Ovri+bNm+PBgwcAPhwd8PX1hY2NDQCgRYsWiI2NxaFDhwAgyyOVn2rVqpXyXLy8Rgih8twMGzZMuW7Sb9WrV1eZZ9OmTYiMjERUVBQ2b96MXbt2YeTIkbldulbc3d3h7++PJk2aqPXnY+lHio4cOYKEhATl13d5RbFixdCyZUuEhoYiJCQELVu2VG6n2tB2G85tuuonAHz99de4e/cuwsPD0b59e1y9ehX169fP1a+2ZsyYgbCwMPzzzz9q92nzXFhYWCAyMhLnzp3D7NmzUa1aNUydOjXDaatUqQJXV1ds3boVq1evxnfffaeXo7D+/v54/Pgxdu/ejWbNmiEiIgLVqlVTOwfwc7Tpd37XrVs3nDx5Enfv3s2THy61wXPs8rBVq1YhJSVF5SsbIQQUCgUWLVr02XnTd2TZOTcmp5iZmaFs2bLKv3/99VdYWVlh5cqVmDhxIsLCwhAdHa2yE0xNTcXq1avRuHFjlCtXDgBw/fp1VK1aNcvH++677/DNN98gMDAQQggMGTJE953Kpn/++UflubGxsVFZNxlxdHRUTlOhQgXcuXMHY8eOxYQJE/R2XpYmjIyMsnxj69q1K4YPH44JEybo7Y0wK4GBgejXrx8AYPHixWr3W1paZnjhQ0xMDKysrAB8CE6FCxfG9evXc7bYL6CLfqYzNjZG/fr1Ub9+fYwYMQJTpkzBpEmTMGLECMjl8pzpwEe+/vpr+Pr6YtSoUQgICFC2lytXLsOwB/zfvjN9fwN8OL3l09de3759sXbt2gyXERgYiMWLF+PatWs4c+aMjnqjPRMTEzRp0gRNmjTB2LFj0atXL4wfP15lXXyOtv3OK9LP/4uNjVX7tiaj7RT4cA5zq1at0LNnTyQmJqJ58+Z6OY1AF3jELo9KSUnBmjVrMHv2bJWjOFFRUXBwcPjsSeVpaWlYsGABnJ2dNQpA+iKTyWBgYIB3794pz8W5ePGiSn83bNiA7du3IyYmBp6ennB3d8fs2bORlpamtryYmBi1th49eiA0NBTDhw/HL7/8kgu9ytqhQ4dw+fJl+Pv7f9FyDA0NkZKSgvfv3+uoMv2xtrbGN998gyNHjuTZT8rNmjXD+/fvkZycDF9fX7X7y5cvjwsXLqi1X7hwQRkSDAwM0LlzZ6xbty7DK9zj4+NVrpbWB130MzPu7u5ISUlBYmKizurNyvTp07Fnzx6VK687d+6MW7duYc+ePWrTz549G0WLFkWTJk0yXebIkSOxadOmDNcDAHz77be4fPkyKlWqBHd39y/vhI64u7sjISEh2/Nn1e+8wtXVFQYGBmrnmN+9exexsbGZbqeBgYGIiIhA9+7d8/V5hHnvYzEB+HA+2uvXr9GzZ0+1Txf+/v5YtWoVmjVrBgB4+fIloqOj8fbtW1y5cgXz5s3DmTNn8Mcff+SpjTMpKQnR0dEAgNevX2PRokWIj4+Hn58f5s2bh5YtW6JKlSoq87i7u2Pw4MFYt24dgoKCEBISAh8fH9SvXx9jxoyBm5sb4uPjsWfPHvz1118Znn/43XffwcDAAD169IAQAsOGDcuV/gL/1+fU1FQ8ffoU+/btQ3BwMFq1aqVyftybN2+U6yZdoUKFVK48S3+eU1JScPnyZcyfPx8NGzbMM4Nqx8bGIjIyUqXt4wtjshIaGoolS5ZoNU9uMjQ0VB7Nyeh11bdvXyxatAgDBgxAr169oFAo8Mcff2DDhg0qAWLq1KmIiIhAzZo1MXXqVFSvXh3Gxsb4+++/ERwcjLNnz+r1nFBd9bNBgwbo0qULqlevjqJFi+LatWsYPXp0rm+zHh4e6Nq1KxYsWKBs69y5M7Zs2YIePXpg1qxZaNy4MeLi4rB48WLs3r0bW7Zs+ex5ZI6Ojmjbti3GjRuH33//Xe3+IkWK4MmTJzA2Ns6RPmXl5cuX6NChAwIDA1G5cmVYWFjg3LlzmDlzJlq3bp3t5WbV77zCwsICvXr1wtChQ2FkZAQPDw88evQII0aMQK1atZTDuXyqWbNmeP78eZ7Zp2Zbzgyll7/kxQGKW7VqpTYgcbrTp08LACIqKkplYMZChQqJChUqiB9//FHcunVLZZ68NkCxhYWFqFGjhti6dauIjo4WRkZGmQ5I3LdvX1G1alXl3zdu3BDdu3cXDg4OQi6XCycnJ9GlSxdx4cIF5TT4ZIBiIYRYv369MDQ0FNOnT8+RPn7q0wGKixUrJnx8fMTq1as1GqA4fbDYTwcoNjQ0FCVLlhS9e/cWz549y5W+ZOXT5zf91rNnT5XBiz+W1TY5d+7cPDFAcUa1p2vdurVy4F4hhDhz5oxo0qSJKFasmLCyshI1a9ZU2w6FECImJkaMHDlSuLq6KgeP9fHxETt27NDbAMW67ue0adNE7dq1hbW1tTAxMRFlypQRAwYMEC9evMiZTvx/GfXl3r17Qi6XqwxQnJycLGbNmiUqVqwo5HK5sLS0FL6+vhkOUJzRdnry5EkBQJw+fVoIkfnAzemqVKmSawMUJyYmipEjR4pq1aoJKysrUahQIVG+fHnx888/i7dv36pMq+3r89N+69Pn9iHv3r0T48ePF25ubsLU1FQ4OzuLPn36iOfPn6tMl9F7RbrXr1/nywGKZULk8bN5c0FcXBysrKwQGxub/5M6ERERSYo2OYXn2BERERFJhF6D3dGjR+Hn5wcHBwfIZDK1n3ERQmDcuHEoXrw4TE1N4ePjoxzLLN2rV6/QtWtXWFpaonDhwujZsyfi4+NzsRd6lpoKREQAGzZ8+Dc1Vd8V6R77KB0FoZ/sozQUhD4CBaOfBaGPH8vp74U/588//xRjxowR27dvz/B77unTpwsrKyuxc+dOERUVJb755hvh7Ows3r17p5ymWbNmokqVKuLUqVPi77//FmXLlhVdunTRqo68eI6dRrZtE6JkSSGA/7uVLPmhXSrYR+koCP1kH6WhIPRRiILRT4n0UZuckmcunvg02KWlpQl7e3sxa9YsZVtMTIxQKBRiw4YNQgghrl27JgCIs2fPKqfZu3evkMlk4r///tP4sfNlsNu2TQiZTHVjBT60yWT5bqPNEPsojT4KUTD6yT6yj/lJQeinhPqYLy+ekMlk2LFjB9q0aQPgw3gzLi4uuHjxIjw9PZXTeXt7w9PTE/Pnz8fq1asxdOhQvH79Wnl/SkoKTExMsGXLFrRt21ajx853F0+kpgKlSwMZ/AYiAEAmA0qUAK5eBfLQcCdaSU0F3N2B//7L+H72Mf8oCP1kH9nH/KQg9FOTPpYsCdy7ly/6qE1OybPj2KWP6fXpD4Hb2dkp74uOjoatra3K/UZGRrC2tlYbE+xjSUlJKj+MHBcXp6uyc8fff2ce6oAPn0n+/RfIYHRtyWAfpaMg9JN9lIaC0EegYPRTCODRow/vpw0a6LsancqzwS4nBQcHY+LEibn+uNtvPNHJckqev4avdLIkIiKiguvM+Wv4t3j5L15Ou/LFdVCNbuTZYGdvbw8AePr0KYoX/78V9vTpU+VXs/b29nj27JnKfCkpKXj16pVy/oyMGjVK5XdD4+Li4OjoqMPqc1ZiMbusJwJwbMVveFm91hc/Xutyma/LT+26mfmRUm0UPXcK9fp0y3I69lFz2vQRyJ/9LAh9BLi9fqog9BEoGP3M7T5q+n6an+TZYOfs7Ax7e3uEh4crg1xcXBxOnz6Nvn37AgBq166NmJgYnD9/Hl5eXgA+/A5nWloaatasmemyFQoFFApFjvchp7yoXhNv7YvD9Gk0ZBmcIilkMryzK45ndb11c+7AZ35a51OphQp9+eMBeFbXm33UYx+BfNrPgtBHgNvrJwpCH4GC0c/c7uOL6plnhfxKr+PYxcfHK3/sHQDu3buHyMhIPHz4EDKZDIMGDcKUKVOwe/duXL58Gd27d4eDg4PyAosKFSqgWbNm6N27N86cOYPjx4+jX79+6Ny5MxwcHPTXsZxmaIhLoycD+LBxfiz970ujJ+WLE0IzxT4CkEAfgYLRT/YRAPuYbxSEfhaEPmZCr8Hu3LlzqFq1KqpWrQoAGDJkCKpWrYpx48YBAIYPH47+/fujT58+qFGjBuLj47Fv3z6YmJgol7Fu3Tq4ubmhcePGaNGiBerVq4cVK1bopT+56XHTFjg9fyXe2ake4n5nVxyn56/E46Yt9FSZ7rCP0ugjUDD6yT6yj/lJQehnQehjRvLMcCf6lFvDnejq4gkVqamwOXcaJs+fIrGY3YfDyjr+BKLNSaHsYzblsT4C+bOfBaGPALfXTxWEPgIFo58FoY/ZIYnhTkhDhoZ4UbOOvqvIWeyjdBSEfrKP0lAQ+ggUjH4WhD5+RK9fxRIRERGR7jDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRROTpYJeamoqxY8fC2dkZpqamcHFxweTJkyGEUE4jhMC4ceNQvHhxmJqawsfHB7du3dJj1URERET6kaeD3YwZM7B06VIsWrQI//zzD2bMmIGZM2di4cKFymlmzpyJBQsWYNmyZTh9+jTMzMzg6+uLxMREPVZORERElPuM9F3A55w4cQKtW7dGy5YtAQClS5fGhg0bcObMGQAfjtbNmzcPP//8M1q3bg0AWLNmDezs7LBz50507txZb7UTERER5bY8fcSuTp06CA8Px82bNwEAUVFROHbsGJo3bw4AuHfvHqKjo+Hj46Ocx8rKCjVr1sTJkyf1UjMRERGRvuTpI3YjR45EXFwc3NzcYGhoiNTUVEydOhVdu3YFAERHRwMA7OzsVOazs7NT3peRpKQkJCUlKf+Oi4vLgeqJiIiIcleePmK3efNmrFu3DuvXr8eFCxcQFhaGX375BWFhYV+03ODgYFhZWSlvjo6OOqqYiIiISH/ydLAbNmwYRo4cic6dO8PDwwPfffcdBg8ejODgYACAvb09AODp06cq8z19+lR5X0ZGjRqF2NhY5e3Ro0c51wkiIiKiXJKng93bt29hYKBaoqGhIdLS0gAAzs7OsLe3R3h4uPL+uLg4nD59GrVr1850uQqFApaWlio3IiIiovwuT59j5+fnh6lTp6JUqVKoWLEiLl68iDlz5iAwMBAAIJPJMGjQIEyZMgWurq5wdnbG2LFj4eDggDZt2ui3eCIiIqJclqeD3cKFCzF27Fj8+OOPePbsGRwcHPDDDz9g3LhxymmGDx+OhIQE9OnTBzExMahXrx727dsHExMTPVZORERElPvydLCzsLDAvHnzMG/evEynkclkmDRpEiZNmpR7hRERERHlQXn6HDsiIiIi0hyDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSUSeD3b//fcfunXrhqJFi8LU1BQeHh44d+6c8n4hBMaNG4fixYvD1NQUPj4+uHXrlh4rJiIiItKPPB3sXr9+jbp168LY2Bh79+7FtWvXMHv2bBQpUkQ5zcyZM7FgwQIsW7YMp0+fhpmZGXx9fZGYmKjHyomIiIhyn5G2M5QuXRqBgYEICAhAqVKlcqImpRkzZsDR0REhISHKNmdnZ+X/hRCYN28efv75Z7Ru3RoAsGbNGtjZ2WHnzp3o3LlzjtZHRERElJdofcRu0KBB2L59O8qUKYMmTZpg48aNSEpKyonasHv3blSvXh0dOnSAra0tqlatipUrVyrvv3fvHqKjo+Hj46Nss7KyQs2aNXHy5MlMl5uUlIS4uDiVGxEREVF+l61gFxkZiTNnzqBChQro378/ihcvjn79+uHChQs6Le7u3btYunQpXF1dsX//fvTt2xcDBgxAWFgYACA6OhoAYGdnpzKfnZ2d8r6MBAcHw8rKSnlzdHTUad1ERERE+pDtc+yqVauGBQsW4PHjxxg/fjx+/fVX1KhRA56enli9ejWEEF9cXFpaGqpVq4Zp06ahatWq6NOnD3r37o1ly5Z90XJHjRqF2NhY5e3Ro0dfXCsRERGRvmU72CUnJ2Pz5s345ptvMHToUFSvXh2//vor/P39MXr0aHTt2vWLiytevDjc3d1V2ipUqICHDx8CAOzt7QEAT58+VZnm6dOnyvsyolAoYGlpqXIjIiIiyu+0vnjiwoULCAkJwYYNG2BgYIDu3btj7ty5cHNzU07Ttm1b1KhR44uLq1u3Lm7cuKHSdvPmTTg5OQH4cCGFvb09wsPD4enpCQCIi4vD6dOn0bdv3y9+fCIiIqL8ROtgV6NGDTRp0gRLly5FmzZtYGxsrDaNs7OzTq5IHTx4MOrUqYNp06ahY8eOOHPmDFasWIEVK1YAAGQyGQYNGoQpU6bA1dUVzs7OGDt2LBwcHNCmTZsvfnwiIiKi/ETrYHf37l3lEbPMmJmZqQxRkl01atTAjh07MGrUKEyaNAnOzs6YN2+eyte8w4cPR0JCAvr06YOYmBjUq1cP+/btg4mJyRc/PhEREVF+onWwe/bsGaKjo1GzZk2V9tOnT8PQ0BDVq1fXWXEA0KpVK7Rq1SrT+2UyGSZNmoRJkybp9HGJiIiI8hutL54ICgrK8CrS//77D0FBQTopioiIiIi0p3Wwu3btGqpVq6bWXrVqVVy7dk0nRRERERGR9rQOdgqFQm14EQB48uQJjIy0/maXiIiIiHRE62DXtGlT5QC/6WJiYjB69Gg0adJEp8URERERkea0PsT2yy+/4Ouvv4aTkxOqVq0KAIiMjISdnR3Wrl2r8wKJiIiISDNaB7sSJUrg0qVLWLduHaKiomBqaorvv/8eXbp0yXBMOyIiIiLKHdk6Kc7MzAx9+vTRdS1ERERE9AWyfbXDtWvX8PDhQ7x//16l/ZtvvvniooiIiIhIe9n65Ym2bdvi8uXLkMlkEEIA+DBQMACkpqbqtkIiIiIi0ojWV8UOHDgQzs7OePbsGQoVKoSrV6/i6NGjqF69OiIiInKgRCIiIiLShNZH7E6ePIlDhw7BxsYGBgYGMDAwQL169RAcHIwBAwbg4sWLOVEnEREREWVB6yN2qampsLCwAADY2Njg8ePHAAAnJyfcuHFDt9URERERkca0PmJXqVIlREVFwdnZGTVr1sTMmTMhl8uxYsUKlClTJidqJCIiIiINaB3sfv75ZyQkJAAAJk2ahFatWqF+/fooWrQoNm3apPMCiYiIiEgzWgc7X19f5f/Lli2L69ev49WrVyhSpIjyylgiIiIiyn1anWOXnJwMIyMjXLlyRaXd2tqaoY6IiIhIz7QKdsbGxihVqhTHqiMiIiLKg7S+KnbMmDEYPXo0Xr16lRP1EBEREVE2aX2O3aJFi3D79m04ODjAyckJZmZmKvdfuHBBZ8URERERkea0DnZt2rTJgTKIiIiI6EtpHezGjx+fE3UQERER0RfS+hw7IiIiIsqbtD5iZ2Bg8NmhTXjFLBEREZF+aB3sduzYofJ3cnIyLl68iLCwMEycOFFnhRERERGRdrQOdq1bt1Zra9++PSpWrIhNmzahZ8+eOimMiIiIiLSjs3PsatWqhfDwcF0tjoiIiIi0pJNg9+7dOyxYsAAlSpTQxeKIiIiIKBu0/iq2SJEiKhdPCCHw5s0bFCpUCL/99ptOiyMiIiIizWkd7ObOnasS7AwMDFCsWDHUrFkTRYoU0WlxRERERKQ5rYNdQEBADpRBRERERF9K63PsQkJCsGXLFrX2LVu2ICwsTCdFEREREZH2tA52wcHBsLGxUWu3tbXFtGnTdFIUEREREWlP62D38OFDODs7q7U7OTnh4cOHOimKiIiIiLSndbCztbXFpUuX1NqjoqJQtGhRnRRFRERERNrTOth16dIFAwYMwOHDh5GamorU1FQcOnQIAwcOROfOnXOiRiIiIiLSgNZXxU6ePBn3799H48aNYWT0Yfa0tDR0796d59gRERER6ZHWwU4ul2PTpk2YMmUKIiMjYWpqCg8PDzg5OeVEfURERESkIa2DXTpXV1e4urrqshYiIiIi+gJan2Pn7++PGTNmqLXPnDkTHTp00ElRRERERKQ9rYPd0aNH0aJFC7X25s2b4+jRozopioiIiIi0p3Wwi4+Ph1wuV2s3NjZGXFycTooiIiIiIu1pHew8PDywadMmtfaNGzfC3d1dJ0URERERkfa0vnhi7NixaNeuHe7cuYNGjRoBAMLDw7F+/Xps3bpV5wUSERERkWa0DnZ+fn7YuXMnpk2bhq1bt8LU1BRVqlTBoUOHYG1tnRM1EhEREZEGsjXcScuWLdGyZUsAQFxcHDZs2ICffvoJ58+fR2pqqk4LJCIiIiLNaH2OXbqjR4+iR48ecHBwwOzZs9GoUSOcOnVKl7URERERkRa0OmIXHR2N0NBQrFq1CnFxcejYsSOSkpKwc+dOXjhBREREpGcaH7Hz8/ND+fLlcenSJcybNw+PHz/GwoULc7I2IiIiItKCxkfs9u7diwEDBqBv3778KTEiIiKiPEjjI3bHjh3Dmzdv4OXlhZo1a2LRokV48eJFTtZGRERERFrQONjVqlULK1euxJMnT/DDDz9g48aNcHBwQFpaGg4cOIA3b97kZJ1ERERElAWtr4o1MzNDYGAgjh07hsuXL2Po0KGYPn06bG1t8c033+REjURERESkgWwPdwIA5cuXx8yZM/Hvv/9iw4YNuqqJiIiIiLLhi4JdOkNDQ7Rp0wa7d+/WxeKIiIiIKBt0EuyIiIiISP8Y7IiIiIgkgsGOiIiISCIY7IiIiIgkgsGOiIiISCIY7IiIiIgkgsGOiIiISCIY7IiIiIgkIl8Fu+nTp0Mmk2HQoEHKtsTERAQFBaFo0aIwNzeHv78/nj59qr8iiYiIiPQk3wS7s2fPYvny5ahcubJK++DBg7Fnzx5s2bIFR44cwePHj9GuXTs9VUlERESkP/ki2MXHx6Nr165YuXIlihQpomyPjY3FqlWrMGfOHDRq1AheXl4ICQnBiRMncOrUKT1WTERERJT78kWwCwoKQsuWLeHj46PSfv78eSQnJ6u0u7m5oVSpUjh58mSmy0tKSkJcXJzKjYiIiCi/M9J3AVnZuHEjLly4gLNnz6rdFx0dDblcjsKFC6u029nZITo6OtNlBgcHY+LEiboulYiIiEiv8vQRu0ePHmHgwIFYt24dTExMdLbcUaNGITY2Vnl79OiRzpZNREREpC95OtidP38ez549Q7Vq1WBkZAQjIyMcOXIECxYsgJGREezs7PD+/XvExMSozPf06VPY29tnulyFQgFLS0uVGxEREVF+l6e/im3cuDEuX76s0vb999/Dzc0NI0aMgKOjI4yNjREeHg5/f38AwI0bN/Dw4UPUrl1bHyUTERER6U2eDnYWFhaoVKmSSpuZmRmKFi2qbO/ZsyeGDBkCa2trWFpaon///qhduzZq1aqlj5KJiIiI9CZPBztNzJ07FwYGBvD390dSUhJ8fX2xZMkSfZdFRERElOvyXbCLiIhQ+dvExASLFy/G4sWL9VMQERERUR6Rpy+eICIiIiLNMdgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSQSDHREREZFEMNgRERERSUSeDnbBwcGoUaMGLCwsYGtrizZt2uDGjRsq0yQmJiIoKAhFixaFubk5/P398fTpUz1VTERERKQ/eTrYHTlyBEFBQTh16hQOHDiA5ORkNG3aFAkJCcppBg8ejD179mDLli04cuQIHj9+jHbt2umxaiIiIiL9MNJ3AZ+zb98+lb9DQ0Nha2uL8+fP4+uvv0ZsbCxWrVqF9evXo1GjRgCAkJAQVKhQAadOnUKtWrX0UTYRERGRXuTpI3afio2NBQBYW1sDAM6fP4/k5GT4+Pgop3Fzc0OpUqVw8uRJvdRIREREpC95+ojdx9LS0jBo0CDUrVsXlSpVAgBER0dDLpejcOHCKtPa2dkhOjo602UlJSUhKSlJ+XdcXFyO1ExERESUm/LNEbugoCBcuXIFGzdu/OJlBQcHw8rKSnlzdHTUQYVERERE+pUvgl2/fv3w+++/4/DhwyhZsqSy3d7eHu/fv0dMTIzK9E+fPoW9vX2myxs1ahRiY2OVt0ePHuVU6URERES5Jk8HOyEE+vXrhx07duDQoUNwdnZWud/LywvGxsYIDw9Xtt24cQMPHz5E7dq1M12uQqGApaWlyo2IiIgov8vT59gFBQVh/fr12LVrFywsLJTnzVlZWcHU1BRWVlbo2bMnhgwZAmtra1haWqJ///6oXbs2r4glIiKiAidPB7ulS5cCABo0aKDSHhISgoCAAADA3LlzYWBgAH9/fyQlJcHX1xdLlizJ5UqJiIiI9C9PBzshRJbTmJiYYPHixVi8eHEuVERERESUd+Xpc+yIiIiISHMMdkREREQSwWBHREREJBEMdkREREQSwWBHREREJBEMdkREREQSwWBHREREJBEMdkREREQSwWBHREREJBEMdkREREQSwWBHREREJBEMdkREREQSwWBHREREJBEMdkREREQSwWBHREREJBEMdkREREQSwWBHREREJBEMdkREREQSwWBHREREJBEMdkREREQSwWBHREREJBEMdkREREQSwWBHREREJBEMdkREREQSwWBHREREJBEMdkREREQSwWBHREREJBEMdkREREQSwWBHREREJBEMdkREREQSwWBHREREJBEMdkREREQSwWBHREREJBEMdkREREQSYaTvAvKL1NRUJCcnf9EyjNK+bH59SUxM1HjagtHHFKRBhjSZASCT5WBVRERE2mGw00B8fDz+/fdfCCG+aDklklN1VFHuuncvQeNpC0of04TAW5kRYowtkGpgmIOVERERaY7BLgupqan4999/UahQIRQrVgyyLzhCE5v0XoeV5R4rhVzjaQtEHxPfIyUlGa9fvIQ8KQZPFNY8ckdERHkCg10WkpOTIYRAsWLFYGpq+kXLepdPT2k0MdE89BSUPsphAkNDIyQ9egQjkYoUGV9KRESkf/nzXVgPvuRIHUmTzCB9m/iyr+iJiIh0hcGOiIiISCIY7IiIiIgkgsFOooJ694K1qQLWpgrYWZrDq2IFzJw2FSkpKfou7bOsTRX4Y/cufZdBRESUL/GM72zafuNJrj5eQ6eiWs/TuGlTLFq+Eu+TknBg/z4MGzQQxsbGGDxsuFbLSU1NhUwmg4EBPwcQERHlZXynljCFXAE7e3s4OjkhsM8P8G7UCHt//x1JSUkYO3IEKpZxRsmiReBTvx6OHT2inG/92jUobW+Lvb/vQa2qVaBQKPDw4UMkJSVhxIgRcHR0hEKhQNmyZbFq1SrlfFeuXEGH1n5wtLFGeSdH/C/we7x88UJ5v1/TJhg5ZDDGjx6FMg72cCtdCtOnTFbeX6V8OQDAd506wtpUofz73t076NrBH+WdHOFoY43Gdesg4lC4Sl+jnzxBp7at4VDECp5u5bB140ZUKV8OSxcuUE4TGxODAX3/B1fHEihla4PWzXxx5dIl5f1RUVFo2LAhLCwsYGlpCS8vL5w7d05HzwYREVHOY7ArQExNTZGc/B7DBw/C2dOn8euatfj77Dm0btcOHb7xw53bt5TTvnv7FvNnz8b8Jctw9epV2Nraonv37tiwYQMWLFiAf/75B8uXL4e5uTkAICYmBo0aNULlKp4IP34CW3btwbNnTxHYratKDRvW/YZCZmY4cPRvTJg6DbOmTcXh8IMAgPBjxwEAi1asxD/3Hij/TohPQBPfZtjx5z5EnDqNRk2b4lv/dvj34UPlcvv2CkT0kyfYvf8AwjZsQtjqVXjx/JnKYwd07YIXz59h887dOHziJCp7eqJNi2Z4/eoVAKBr164oWbIkzp49i/Pnz2PkyJEwNjbW8bNARESUc/hVbAEghMCRw4dw6MABtOvYCevXhOHSzdso7uAAAOg/eAgOHfgL69eswdhJH46gJScn45f5C1CpcmUUMZHj5s2b2Lx5Mw4cOAAfHx8AQJkyZZSPsWjRIlStWlU5PwAsXLYCHq4uuH3rJsq6fjj6VrGSB0aM+RkA4FLWFb8uXYqjhw+jYWMf2BQrBgCwsrKCnb29cjmVKldGpcqVlX+PGT8Bf+zehb1//I7efX/EzRvXceTQIYQfO4GqXl4AgPlLl6J6pYrKeU4dP44L587h5sN/oVAoAACTp8/An3t2Y9eO7Rgc9CMePnyIYcOGwc3NDQDg6uqqi9VPRESUaxjsJGz/3j/haGON5ORkpKWloX2nzmjdti02rF2DrypXUpk2KSkJRaz/7zw+uVyOih4eyr8jIyNhaGgIb2/vDB8rKioKhw8fhqONtdp99+7e/b9g56H6uHbF7fH8+fPP9iM+Ph4zpkzGX/v24ml0NFJTUvDu3Tv8++gRAOD2zZswMjJClapVlfOUcSmLwkWKKP++cvkSEuLjUbZEcZVlv3v3Dvfv3gUADBkyBL169cLatWvh4+ODDh06wMXF5bO1ERER5SUMdhJWz9sbsxcshNxYDnsHBxgZGWH7li0wNDTEoRMnYWio+hunZmbmyv+bmJqqDMqc1a9uxMfHw8/PD6M/OmKXzs7+/8KUkZHqV5syyCDS0j677HGjRiAiPByTgmegjIsLTExNEPBtF7x/r/nPlyXEJ8DOvjj2/PWX2n1WVoUBABMmTMC3336LP/74A3v37sX48eOxceNGtG3bVuPHISIi0icGOwkzK2SGMi5lVdoqe1ZBamoqXjx7jtr16mm8LA8PD6SlpeHIkSPKr2I/Vq1aNWzbtg2lnErDyCj7m5WxsTFSU1WD3umTJ9Hlu+5o1bo1gA8h8uGDB6hb/8P9ZcuVQ0pKCi5FRsKzWjUAwN07txHz+rVyGZWreuLZ02gYGRmhlFPpTB+/XLlyKFeuHAYPHowuXbogJCSEwY6IiPINXjxRwJR1LYcOnbugb69A7Nm5Ew/u38P5s2cxd9ZM/LX3z0znK126NHr06IHAwEDs3LkT9+7dQ0REBDZv3gwACAoKwqtXr9Cr+3e4cO4c7t29g/ADfyGoT2+kpqZqXF8pJyccjTiEp9HRymDm4lIWv+/aictRUbhy6RL6BHRH2kdH+cqVd4N3o0YY3O9HnD97FpciIzE4KAimHx11bNCoMWrUrIVuHTvg0MEDePjgPk6fPIkp48fh4vnzePfuHfr164eIiAg8ePAAx48fx9mzZ1GhQoXsrGYiIiK9YLArgBatWIlOXbth7Mjh+KqyB77r2AEXz51DScdSn51v6dKlaN++PX788Ue4ubmhd+/eSEhIAAA4ODjg+PHjSEtNhb9fS9Sr7oXRw36ClZWVVuPfTZ4+AxHh4fBwdYF3rZoAgCkzZ6Jw4SJo1tAbXfzboZFPE1TxrKoy39JfV6OYrS1aNWmM7zp1RPfvA2FuYQETExMAH37rd9POXahTtx769+mDGh6V0Kv7d3j08CGK2drC0NAQL1++RPfu3VGuXDl07NgRzZs3x8SJE7VZtURERHolE0IU+F8wj4uLg5WVFWJjY2FpaalyX2JiIu7duwdnZ2dlSMiu14manxOWlxQxkWs8bV7p43///gsPVxfs+HMvvBs2ynL67PTxfVIi/n3wEP8ZWyLFIO8Pi9KufPGsJ/pIbg/CrQsFoY+Adv1kH/Mubq/qCkIfs+NzOeVTPMeOJOFoxGEkxMfDvVIlRD+JxoQxo1HKyQl16tXXd2lERES5hsGOJCE5ORmTx4/Dg3v3YG5hga9q1sKKkFAOMExERAUKgx1JQuMmTdG4SVN9l0FERKRXvHiCiIiISCIY7IiIiIgkgsFOQ7x4mNQoNwnZ56YiIiLKNQx2WUj/2S1tfr6KCoakxHdIEwKpMr6MiIgob+DFE1kwMjJCoUKF8Pz5cxgbG2s12O6n3iflz3CYiM//luvHCkQfE98jKfEdXjx/jlgDBQSDHRER5REMdlmQyWQoXrw47t27hwcPHnzRst4ma/7TWnnJK2NDjactKH1MEwKxBgrEGZvnYFVERETaYbDTgFwuh6ur6xd/HfvXvWc6qih3NXW21XjagtHH50iVGfBIHRER5TmSCXaLFy/GrFmzEB0djSpVqmDhwoX46quvdLZ8AwODL/5Jsfzws1MZ0abfBaOPknnZEBGRxEjikMOmTZswZMgQjB8/HhcuXECVKlXg6+uLZ8/y59EjIiIiouyQRLCbM2cOevfuje+//x7u7u5YtmwZChUqhNWrV+u7NCIiIqJck++D3fv373H+/Hn4+Pgo2wwMDODj44OTJ0/qsTIiIiKi3JXvTxZ68eIFUlNTYWdnp9JuZ2eH69evZzhPUlISkpKSlH/HxsYCAOLi4nKuUABv49/k6PJzSlycmcbTso95lzZ9BPJnPwtCHwFur58qCH0ECkY/C0Ifs7f8D/lEkx9LyPfBLjuCg4MxceJEtXZHR0c9VENERESUtTdv3sDKyuqz0+T7YGdjYwNDQ0M8ffpUpf3p06ewt7fPcJ5Ro0ZhyJAhyr/T0tLw6tUrFC1aFDJZ/vt5qLi4ODg6OuLRo0ewtLTUdzk5gn2UjoLQT/ZRGgpCH4GC0c/83kchBN68eQMHB4csp833wU4ul8PLywvh4eFo06YNgA9BLTw8HP369ctwHoVCAYVCodJWuHDhHK4051laWubLDVYb7KN0FIR+so/SUBD6CBSMfubnPmZ1pC5dvg92ADBkyBD06NED1atXx1dffYV58+YhISEB33//vb5LIyIiIso1kgh2nTp1wvPnzzFu3DhER0fD09MT+/btU7uggoiIiEjKJBHsAKBfv36ZfvUqdQqFAuPHj1f7ellK2EfpKAj9ZB+loSD0ESgY/SwIfUwnE5pcO0tEREREeV6+H6CYiIiIiD5gsCMiIiKSCAY7IiIiIolgsMvnFi9ejNKlS8PExAQ1a9bEmTNn9F2STh09ehR+fn5wcHCATCbDzp079V2SzgUHB6NGjRqwsLCAra0t2rRpgxs3bui7LJ1aunQpKleurBxDqnbt2ti7d6++y8pR06dPh0wmw6BBg/Rdik5NmDABMplM5ebm5qbvsnTuv//+Q7du3VC0aFGYmprCw8MD586d03dZOlO6dGm151EmkyEoKEjfpelMamoqxo4dC2dnZ5iamsLFxQWTJ0/W6Ge58jMGu3xs06ZNGDJkCMaPH48LFy6gSpUq8PX1xbNnz/Rdms4kJCSgSpUqWLx4sb5LyTFHjhxBUFAQTp06hQMHDiA5ORlNmzZFQkKCvkvTmZIlS2L69Ok4f/48zp07h0aNGqF169a4evWqvkvLEWfPnsXy5ctRuXJlfZeSIypWrIgnT54ob8eOHdN3STr1+vVr1K1bF8bGxti7dy+uXbuG2bNno0iRIvouTWfOnj2r8hweOHAAANChQwc9V6Y7M2bMwNKlS7Fo0SL8888/mDFjBmbOnImFCxfqu7ScJSjf+uqrr0RQUJDy79TUVOHg4CCCg4P1WFXOASB27Nih7zJy3LNnzwQAceTIEX2XkqOKFCkifv31V32XoXNv3rwRrq6u4sCBA8Lb21sMHDhQ3yXp1Pjx40WVKlX0XUaOGjFihKhXr56+y8hVAwcOFC4uLiItLU3fpehMy5YtRWBgoEpbu3btRNeuXfVUUe7gEbt86v379zh//jx8fHyUbQYGBvDx8cHJkyf1WBl9qdjYWACAtbW1nivJGampqdi4cSMSEhJQu3ZtfZejc0FBQWjZsqXKa1Nqbt26BQcHB5QpUwZdu3bFw4cP9V2STu3evRvVq1dHhw4dYGtri6pVq2LlypX6LivHvH//Hr/99hsCAwPz5e+lZ6ZOnToIDw/HzZs3AQBRUVE4duwYmjdvrufKcpZkBiguaF68eIHU1FS1X9ews7PD9evX9VQVfam0tDQMGjQIdevWRaVKlfRdjk5dvnwZtWvXRmJiIszNzbFjxw64u7vruyyd2rhxIy5cuICzZ8/qu5QcU7NmTYSGhqJ8+fJ48uQJJk6ciPr16+PKlSuwsLDQd3k6cffuXSxduhRDhgzB6NGjcfbsWQwYMAByuRw9evTQd3k6t3PnTsTExCAgIEDfpejUyJEjERcXBzc3NxgaGiI1NRVTp05F165d9V1ajmKwI8pDgoKCcOXKFcmdswQA5cuXR2RkJGJjY7F161b06NEDR44ckUy4e/ToEQYOHIgDBw7AxMRE3+XkmI+PdlSuXBk1a9aEk5MTNm/ejJ49e+qxMt1JS0tD9erVMW3aNABA1apVceXKFSxbtkySwW7VqlVo3rw5HBwc9F2KTm3evBnr1q3D+vXrUbFiRURGRmLQoEFwcHCQ5POYjsEun7KxsYGhoSGePn2q0v706VPY29vrqSr6Ev369cPvv/+Oo0ePomTJkvouR+fkcjnKli0LAPDy8sLZs2cxf/58LF++XM+V6cb58+fx7NkzVKtWTdmWmpqKo0ePYtGiRUhKSoKhoaEeK8wZhQsXRrly5XD79m19l6IzxYsXV/vAUaFCBWzbtk1PFeWcBw8e4ODBg9i+fbu+S9G5YcOGYeTIkejcuTMAwMPDAw8ePEBwcLCkgx3Pscun5HI5vLy8EB4ermxLS0tDeHi4JM9bkjIhBPr164cdO3bg0KFDcHZ21ndJuSItLQ1JSUn6LkNnGjdujMuXLyMyMlJ5q169Orp27YrIyEhJhjoAiI+Px507d1C8eHF9l6IzdevWVRty6ObNm3ByctJTRTknJCQEtra2aNmypb5L0bm3b9/CwEA15hgaGiItLU1PFeUOHrHLx4YMGYIePXqgevXq+OqrrzBv3jwkJCTg+++/13dpOhMfH69yJODevXuIjIyEtbU1SpUqpcfKdCcoKAjr16/Hrl27YGFhgejoaACAlZUVTE1N9VydbowaNQrNmzdHqVKl8ObNG6xfvx4RERHYv3+/vkvTGQsLC7XzIs3MzFC0aFFJnS/5008/wc/PD05OTnj8+DHGjx8PQ0NDdOnSRd+l6czgwYNRp04dTJs2DR07dsSZM2ewYsUKrFixQt+l6VRaWhpCQkLQo0cPGBlJLw74+flh6tSpKFWqFCpWrIiLFy9izpw5CAwM1HdpOUvfl+XSl1m4cKEoVaqUkMvl4quvvhKnTp3Sd0k6dfjwYQFA7dajRw99l6YzGfUPgAgJCdF3aToTGBgonJychFwuF8WKFRONGzcWf/31l77LynFSHO6kU6dOonjx4kIul4sSJUqITp06idu3b+u7LJ3bs2ePqFSpklAoFMLNzU2sWLFC3yXp3P79+wUAcePGDX2XkiPi4uLEwIEDRalSpYSJiYkoU6aMGDNmjEhKStJ3aTlKJoTEh2AmIiIiKiB4jh0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RERGRRDDYEREREUkEgx0RSUZAQADatGmj7zKIiPSGwY6I8gWZTPbZ24QJEzB//nyEhobqu1Q19+/fz7L+vFg3EeU//EkxIsoXoqOjlf/ftGkTxo0bhxs3bijbzM3NYW5uro/SspSamornz58r//7ll1+wb98+HDx4UNlmZWUFU1NTfZRHRBLCI3ZElC/Y29srb1ZWVpDJZCpt5ubmal/Fbt26FR4eHjA1NUXRokXh4+ODhIQEAEBERAS++uormJmZoXDhwqhbty4ePHgAIOOvdAcNGoQGDRoo/05LS0NwcDCcnZ1hamqKKlWqYOvWrRnWbmhoqFarkZER7O3tkZiYCAcHB1y9elVlnnnz5sHJyQlpaWmIiIiATCbDH3/8gcqVK8PExAS1atXClStXVOY5duwY6tevD1NTUzg6OmLAgAHK/gLAkiVL4OrqChMTE9jZ2aF9+/baPg1ElMcx2BGRJD158gRdunRBYGAg/vnnH0RERKBdu3YQQiAlJQVt2rSBt7c3Ll26hJMnT6JPnz6QyWQaLz84OBhr1qzBsmXLcPXqVQwePBjdunXDkSNHtKqzdOnS8PHxQUhIiEp7SEgIAgICYGDwf7vpYcOGYfbs2Th79iyKFSsGPz8/JCcnAwDu3LmDZs2awd/fH5cuXcKmTZtw7Ngx9OvXDwBw7tw5DBgwAJMmTcKNGzewb98+fP3111rVSkR5n5G+CyAiyglPnjxBSkoK2rVrBycnJwCAh4cHAODVq1eIjY1Fq1at4OLiAgCoUKGCxstOSkrCtGnTcPDgQdSuXRsAUKZMGRw7dgzLly+Ht7e3VrX26tUL//vf/zBnzhwoFApcuHABly9fxq5du1SmGz9+PJo0aQIACAsLQ8mSJbFjxw507NgRwcHB6Nq1KwYNGgQAcHV1xYIFC+Dt7Y2lS5fi4cOHMDMzQ6tWrWBhYQEnJydUrVpVqzqJKO/jETsikqQqVaqgcePG8PDwQIcOHbBy5Uq8fv0aAGBtbY2AgAD4+vrCz88P8+fPx5MnTzRe9u3bt/H27Vs0adJEeW6fubk51qxZgzt37mhda5s2bWBoaIgdO3YAAEJDQ9GwYUOULl1aZbr0EJneh/Lly+Off/4BAERFRSE0NFSlHl9fX6SlpeHevXto0qQJnJycUKZMGXz33XdYt24d3r59q3WtRJS3MdgRkSQZGhriwIED2Lt3L9zd3bFw4UKUL18e9+7dA/Dhq86TJ0+iTp062LRpE8qVK4dTp04BAAwMDPDpdWXpX3kCQHx8PADgjz/+QGRkpPJ27dq1TM+z+xy5XI7u3bsjJCQE79+/x/r16xEYGKjVMuLj4/HDDz+o1BMVFYVbt27BxcUFFhYWuHDhAjZs2IDixYtj3LhxqFKlCmJiYrSul4jyLgY7IpIsmUyGunXrYuLEibh48SLkcrnyqBgAVK1aFaNGjcKJEydQqVIlrF+/HgBQrFgxtSN4kZGRyv+7u7tDoVDg4cOHKFu2rMrN0dExW7X26tULBw8exJIlS5RfIX8qPXgCwOvXr3Hz5k3lV8jVqlXDtWvX1OopW7Ys5HI5AMDIyAg+Pj6YOXMmLl26hPv37+PQoUPZqpeI8iaeY0dEknT69GmEh4ejadOmsLW1xenTp/H8+XNUqFAB9+7dw4oVK/DNN9/AwcEBN27cwK1bt9C9e3cAQKNGjTBr1iysWbMGtWvXxm+//YYrV64oz0mzsLDATz/9hMGDByMtLQ316tVDbGwsjh8/DktLS/To0UPreitUqIBatWphxIgRCAwMzHDok0mTJqFo0aKws7PDmDFjYGNjo7x6d8SIEahVqxb69euHXr16wczMDNeuXcOBAwewaNEi/P7777h79y6+/vprFClSBH/++SfS0tJQvnz57K9kIspzGOyISJIsLS1x9OhRzJs3D3FxcXBycsLs2bPRvHlzPH36FNevX0dYWBhevnyJ4sWLIygoCD/88AMAwNfXF2PHjsXw4cORmJiIwMBAdO/eHZcvX1Yuf/LkyShWrBiCg4Nx9+5dFC5cGNWqVcPo0aOzXXPPnj1x4sSJTL+GnT59OgYOHIhbt27B09MTe/bsUR6Nq1y5Mo4cOYIxY8agfv36EELAxcUFnTp1AgAULlwY27dvx4QJE5CYmAhXV1ds2LABFStWzHa9RJT3cIBiIqI8YvLkydiyZQsuXbqk0h4REYGGDRvi9evXKFy4sH6KI6J8gefYERHpWXx8PK5cuYJFixahf//++i6HiPIxBjsiIj3r168fvLy80KBBA62vhiUi+hi/iiUiIiKSCB6xIyIiIpIIBjsiIiIiiWCwIyIiIpIIBjsiIiIiiWCwIyIiIpIIBjsiIiIiiWCwIyIiIpIIBjsiIiIiiWCwIyIiIpKI/weLhii5rsssqgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "percentages = [int(p[:-1]) for p in text_image]\n",
    "\n",
    "x = list(range(len(percentages)))\n",
    "\n",
    "bars = plt.bar(x, percentages, color='lightblue', label='Percentages')\n",
    "labels = ['ADI', 'BACK', 'DEB', 'LYM', 'MUC', 'MUS', 'NORM', 'STR', 'TUM']\n",
    "\n",
    "for bar, label in zip(bars, labels):\n",
    "    yval = bar.get_height()\n",
    "    plt.text(bar.get_x() + bar.get_width()/2, yval + 1, label, ha='center', va='bottom')\n",
    "\n",
    "plt.plot(x, percentages, color='red', marker='o', linestyle='-', linewidth=1.5, markersize=6)\n",
    "\n",
    "plt.xticks(x)\n",
    "plt.xlabel('Tissue Types')\n",
    "plt.ylabel('Accuracy')\n",
    "plt.title('Texts to Images retrieval for 9 categories in the Kather Dataset')\n",
    "plt.legend()\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 348,
   "metadata": {},
   "outputs": [],
   "source": [
    "image_image = []\n",
    "best11 = retrieval(text_embeddings_trained_norm[0], image_embeddings_trained_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 349,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%\n"
     ]
    }
   ],
   "source": [
    "percentage11 = calculate_percentage(best11, 0, 10407)\n",
    "print(percentage11)\n",
    "image_image.append(percentage11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 350,
   "metadata": {},
   "outputs": [],
   "source": [
    "best12 = retrieval(text_embeddings_trained_norm[10408], image_embeddings_trained_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 351,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%\n"
     ]
    }
   ],
   "source": [
    "percentage12 = calculate_percentage(best12, 10407, 20973)\n",
    "print(percentage12)\n",
    "image_image.append(percentage12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 352,
   "metadata": {},
   "outputs": [],
   "source": [
    "best13 = retrieval(text_embeddings_trained_norm[20974], image_embeddings_trained_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 353,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%\n"
     ]
    }
   ],
   "source": [
    "percentage13 = calculate_percentage(best13, 20973, 32485)\n",
    "print(percentage13)\n",
    "image_image.append(percentage13)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 354,
   "metadata": {},
   "outputs": [],
   "source": [
    "best14 = retrieval(text_embeddings_trained_norm[32486], image_embeddings_trained_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 355,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%\n"
     ]
    }
   ],
   "source": [
    "percentage14 = calculate_percentage(best14, 32485, 44042)\n",
    "print(percentage14)\n",
    "image_image.append(percentage14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 356,
   "metadata": {},
   "outputs": [],
   "source": [
    "best15 = retrieval(text_embeddings_trained_norm[44043], image_embeddings_trained_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 357,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%\n"
     ]
    }
   ],
   "source": [
    "percentage15 = calculate_percentage(best15, 44042, 52938)\n",
    "print(percentage15)\n",
    "image_image.append(percentage15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 358,
   "metadata": {},
   "outputs": [],
   "source": [
    "best16 = retrieval(text_embeddings_trained_norm[52939], image_embeddings_trained_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 359,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%\n"
     ]
    }
   ],
   "source": [
    "percentage16 = calculate_percentage(best16, 52938, 66474)\n",
    "print(percentage16)\n",
    "image_image.append(percentage16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 360,
   "metadata": {},
   "outputs": [],
   "source": [
    "best17 = retrieval(text_embeddings_trained_norm[66475], image_embeddings_trained_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 361,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%\n"
     ]
    }
   ],
   "source": [
    "percentage17 = calculate_percentage(best17, 66474, 75237)\n",
    "print(percentage17)\n",
    "image_image.append(percentage17)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 362,
   "metadata": {},
   "outputs": [],
   "source": [
    "best18 = retrieval(text_embeddings_trained_norm[75238], image_embeddings_trained_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 363,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%\n"
     ]
    }
   ],
   "source": [
    "percentage18 = calculate_percentage(best18, 75237, 85683)\n",
    "print(percentage18)\n",
    "image_image.append(percentage18)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 364,
   "metadata": {},
   "outputs": [],
   "source": [
    "best19 = retrieval(text_embeddings_trained_norm[85684], image_embeddings_trained_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 365,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%\n"
     ]
    }
   ],
   "source": [
    "percentage19 = calculate_percentage(best19, 85683, 100000)\n",
    "print(percentage19)\n",
    "image_image.append(percentage19)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 366,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "percentages = [int(p[:-1]) for p in image_image]\n",
    "\n",
    "x = list(range(len(percentages)))\n",
    "\n",
    "bars = plt.bar(x, percentages, color='lightblue', label='Percentages')\n",
    "labels = ['ADI', 'BACK', 'DEB', 'LYM', 'MUC', 'MUS', 'NORM', 'STR', 'TUM']\n",
    "\n",
    "for bar, label in zip(bars, labels):\n",
    "    yval = bar.get_height()\n",
    "    plt.text(bar.get_x() + bar.get_width()/2, yval + 1, label, ha='center', va='bottom')\n",
    "\n",
    "plt.plot(x, percentages, color='red', marker='o', linestyle='-', linewidth=1.5, markersize=6)\n",
    "\n",
    "plt.xticks(x)\n",
    "plt.xlabel('Tissue Types')\n",
    "plt.ylabel('Accuracy')\n",
    "plt.title('Images to Images retrieval for 9 categories in the Kather Dataset')\n",
    "plt.legend()\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "my_cool_science",
   "language": "python",
   "name": "my_cool_science"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}