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Created April 5, 2021 19:33
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A quick and dirty reimplementation of the training algorithm from Learning Neural Network Subspaces, Wortsman et al., https://arxiv.org/abs/2102.10472
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{
"cells": [
{
"cell_type": "markdown",
"id": "e85c7c11",
"metadata": {},
"source": [
"# Learning Neural Network Subspaces\n",
"\n",
"Reproducing the paper https://arxiv.org/abs/2102.10472\n",
"\n",
"$$\n",
"\\newcommand\\PaW{P\\left(\\boldsymbol \\alpha, \\left\\{ W_i \\right\\} \\right)}\n",
"\\begin{equation}\n",
"\\begin{aligned}\n",
" \\PaW &= \\sum_i \\alpha_i W_i, \\text{ } \\sum_i \\alpha_i = 1\\\\\n",
" \\theta &= \\PaW\\\\\n",
" \\mathcal{L} &= \\mathbb{E}_{x,y \\sim \\mathcal{D}} \\text{ } \\mathbb{E}_{\\boldsymbol \\alpha \\sim U} \\text{ } l(f(x, \\theta), y) \\\\\n",
" \\frac{\\partial\\mathcal{L}}{\\partial W_i}\n",
" &=\n",
" \\frac{\\partial l}{\\partial \\theta} \\frac{\\partial \\theta}{\\partial W_i}\n",
" \\\\&=\n",
" \\frac{\\partial l}{\\partial \\theta} \\frac{\\partial \\PaW}{\\partial W_i}\n",
" =\n",
" \\frac{\\partial l}{\\partial \\theta} \\alpha_i\n",
" % \\frac{\\partial P(\\textbf{\\alpha}, \\left\\{ W_i \\right\\}}{\\partial W_i}\n",
"\\end{aligned}\n",
"\\end{equation}\n",
"$$\n",
"\n",
"\n",
"### Disclaimer\n",
"\n",
"Dirty and inefficient implementation"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "2238bf61",
"metadata": {},
"outputs": [],
"source": [
"from collections import OrderedDict\n",
"from math import sqrt\n",
"from itertools import chain, product\n",
"\n",
"import numpy as np\n",
"\n",
"import torch\n",
"import torch.nn as nn\n",
"import torch.nn.functional as F\n",
"import torch.utils.data\n",
"\n",
"import torchvision\n",
"\n",
"from tqdm import tqdm\n",
"\n",
"\n",
"import matplotlib.pyplot as plt\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "4af7f32b",
"metadata": {},
"outputs": [],
"source": [
"class Net(nn.Module):\n",
" def __init__(self, input_dim, hidden_dim, output_dim):\n",
" super().__init__()\n",
" self.layer1 = nn.Linear(input_dim, hidden_dim)\n",
" self.layer2 = nn.Linear(hidden_dim, output_dim)\n",
" \n",
" def forward(self, x):\n",
" return self.layer2(F.silu(self.layer1(x)))\n",
"\n",
"\n",
"def make_net_factory(net_class, init_kwargs):\n",
" return lambda: net_class(**init_kwargs)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "38d7c85f",
"metadata": {},
"outputs": [],
"source": [
"net_factory = make_net_factory(Net, {\"input_dim\": 5, \"hidden_dim\": 7, \"output_dim\": 1})\n",
"\n",
"net1 = net_factory()\n",
"net2 = net_factory()"
]
},
{
"cell_type": "markdown",
"id": "c537cae3",
"metadata": {},
"source": [
"# Network simplex"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "eb5e2495",
"metadata": {},
"outputs": [],
"source": [
"def network_simplex(alphas, nets, alpha_strict=True):\n",
" \"\"\"Computes a weighted sum of network weights.\n",
" Alphas should be positive and sum to one.\n",
" \n",
" Args:\n",
" alphas: torch.FloatTensor, all(alphas >= 0), sum(alhpas) = 1\n",
" nets: list(torch.nn.Module) with the same arch\n",
" \"\"\"\n",
" if alphas.requires_grad:\n",
" raise ValueError(\"alphas should not require grad\")\n",
"\n",
" if alpha_strict and not torch.allclose(torch.sum(alphas), torch.tensor(1.)):\n",
" raise ValueError(alphas)\n",
"\n",
" state_dicts = [n.state_dict() for n in nets]\n",
" average_dict = OrderedDict()\n",
"\n",
" for key in state_dicts[0].keys():\n",
" average_param = sum(alphas[i] * state_dicts[i][key] for i in range(len(alphas)))\n",
" average_dict[key] = average_param\n",
"\n",
" return average_dict\n",
"\n",
"\n",
"def make_alpha_factory(n_alphas):\n",
" def factory():\n",
" alphas = torch.abs(torch.randn(n_alphas))\n",
" alphas = alphas / torch.sum(alphas)\n",
" return alphas\n",
" \n",
" return factory"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "ca4662ab",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"tensor([0.8626, 0.1374])"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"alpha_factory = make_alpha_factory(2)\n",
"alphas = alpha_factory()\n",
"alphas"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "42df11a5",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"OrderedDict([('layer1.weight',\n",
" tensor([[-0.1547, -0.3059, 0.3143, -0.1556, 0.2363],\n",
" [-0.2498, 0.0306, -0.3617, -0.0061, 0.0855],\n",
" [-0.1253, 0.1302, -0.1380, 0.0794, -0.3408],\n",
" [ 0.0374, -0.0977, -0.2570, -0.1465, -0.0879],\n",
" [ 0.1985, -0.2887, -0.3554, -0.1759, -0.2306],\n",
" [-0.1980, 0.0577, 0.3969, 0.2537, 0.2604],\n",
" [-0.0946, 0.0334, -0.2935, 0.3404, 0.1610]])),\n",
" ('layer1.bias',\n",
" tensor([-0.2981, 0.1123, 0.0991, -0.0785, 0.0121, 0.4164, -0.0101])),\n",
" ('layer2.weight',\n",
" tensor([[ 0.2781, 0.0701, -0.1546, -0.0550, 0.0528, -0.1626, -0.3547]])),\n",
" ('layer2.bias', tensor([-0.2622]))])"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"network_simplex(alphas, [net1, net2])"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "7d986dec",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"tensor([[ 0.2781, 0.0701, -0.1546, -0.0550, 0.0528, -0.1626, -0.3547]],\n",
" grad_fn=<AddBackward0>)"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Sanity check: this should be equal to the layer2 weights of the network simplex\n",
"alphas[0] * net1.layer2.weight + alphas[1] * net2.layer2.weight"
]
},
{
"cell_type": "markdown",
"id": "61feb1b9",
"metadata": {},
"source": [
"# Regularization"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "bc7698c3",
"metadata": {},
"outputs": [],
"source": [
"def cosine_reg(networks, device):\n",
" n_nets = len(networks)\n",
"\n",
" reg = torch.tensor(0.0, dtype=torch.float32, device=device)\n",
"\n",
" for i in range(n_nets):\n",
" for j in range(i+1, n_nets):\n",
" n1 = networks[i]\n",
" n2 = networks[j]\n",
"\n",
" n_params = 0\n",
" for (name1, param1), (name2, param2) in zip(n1.named_parameters(), n2.named_parameters()):\n",
" assert name1 == name2, (name1, name2)\n",
" n_params += 1\n",
" \n",
" param1_n = param1.flatten()\n",
" param2_n = param2.flatten()\n",
" param1_n = param1_n / torch.norm(param1_n)\n",
" param2_n = param2_n / torch.norm(param2_n)\n",
" reg += F.cosine_similarity(param1_n, param2_n, dim=0) ** 2\n",
" \n",
" reg /= n_params\n",
" \n",
" reg /= ((n_nets - 1) * n_nets) / 2\n",
"\n",
" return reg\n"
]
},
{
"cell_type": "markdown",
"id": "043b126b",
"metadata": {},
"source": [
"# Dataset"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "635716ae",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Dataset MNIST\n",
" Number of datapoints: 60000\n",
" Root location: data\n",
" Split: Train\n",
" StandardTransform\n",
"Transform: Compose(\n",
" ToTensor()\n",
" Lambda()\n",
" Normalize(mean=(0.1307,), std=(0.3081,))\n",
" Lambda()\n",
" )"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"device = \"cuda\"\n",
"batch_size = 32\n",
"\n",
"transform = torchvision.transforms.Compose([\n",
" torchvision.transforms.ToTensor(),\n",
" torchvision.transforms.Lambda(lambda x: x.to(device)),\n",
" torchvision.transforms.Normalize((0.1307,), (0.3081,)),\n",
" torchvision.transforms.Lambda(lambda x: torch.flatten(x)),\n",
"])\n",
"\n",
"\n",
"mnist_train = torchvision.datasets.MNIST('data', download=True, train=True, transform=transform)\n",
"# mnist_test = torchvision.datasets.MNIST('data', download=True, train=False, transform=transform)\n",
"\n",
"dataloader = torch.utils.data.DataLoader(mnist_train, batch_size=batch_size, shuffle=True)\n",
"\n",
"mnist_train"
]
},
{
"cell_type": "markdown",
"id": "e923b439",
"metadata": {},
"source": [
"# Training"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "4ebe6814",
"metadata": {},
"outputs": [],
"source": [
"n_endpoints = 3 # number of vertices in the simples\n",
"lr = 1e-3\n",
"\n",
"net_factory = make_net_factory(Net, {\"input_dim\": 784, \"hidden_dim\": 64, \"output_dim\": 10})\n",
"alpha_factory = make_alpha_factory(n_endpoints)\n",
"\n",
"networks = [net_factory().to(device) for _ in range(n_endpoints)]\n",
"train_network = net_factory().to(device)\n",
"\n",
"reg_hist = []\n",
"loss_hist = []\n",
"acc_hist = []"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "d19b9df5",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 10/10 [09:55<00:00, 59.55s/it]\n"
]
}
],
"source": [
"for epoch in tqdm(range(10)):\n",
" for X, y in dataloader:\n",
" train_network.zero_grad()\n",
" [n.zero_grad() for n in networks]\n",
"\n",
" y = y.to(device)\n",
"\n",
" alphas = alpha_factory()\n",
" state_dict = network_simplex(alphas, networks)\n",
" train_network.load_state_dict(state_dict)\n",
" \n",
" logits = train_network(X)\n",
" loss = F.cross_entropy(logits, y)\n",
"\n",
" reg = cosine_reg(networks, device)\n",
"\n",
" loss.backward()\n",
" \n",
" # NOTE: reg computaitonal graph is disconnected from the loss graph\n",
" # because `network_simplex` does not allow backpropagation into `networks` parameters\n",
" reg.backward()\n",
"\n",
" # Updating the network, AKA optimizer.step\n",
" # NOTE: if you want to make torch.optimizer work with this setup, you need to do quite some extra work\n",
" # look into the original implementation for details: github.com/apple/learning-subspaces\n",
" with torch.no_grad():\n",
" param2grad = {n: p.grad for n, p in train_network.named_parameters()}\n",
"\n",
" for i, _net in enumerate(networks):\n",
" for _name, _param in _net.named_parameters():\n",
" # loss grad * alpha + reg grad\n",
" total_grad = param2grad[_name] * alphas[i] + _param.grad\n",
" _param.sub_(total_grad, alpha=lr)\n",
" #\n",
"\n",
" _, preds = logits.max(-1)\n",
" acc = torch.sum(preds == y) / preds.shape[0]\n",
" \n",
" loss_hist.append(loss.detach().cpu().numpy())\n",
" acc_hist.append(acc.detach().cpu().numpy())\n",
" reg_hist.append(reg.detach().cpu().numpy())\n"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "8f5080b3",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(loss_hist)\n",
"plt.title(\"loss\");"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "71a4bcd1",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(acc_hist)\n",
"plt.title(\"train acc\");"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "c5b8e7e2",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(reg_hist)\n",
"plt.title(\"$cos^2$ between networks\");"
]
},
{
"cell_type": "markdown",
"id": "bcf76b5e",
"metadata": {},
"source": [
"# Plotting network subspace"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "075d60d7",
"metadata": {},
"outputs": [],
"source": [
"def infinite_iterator(iterable):\n",
" if isinstance(iterable, torch.utils.data.DataLoader):\n",
" if not isinstance(iterable.sampler, torch.utils.data.sampler.RandomSampler):\n",
" raise RuntimeError(\"this dataloader should use random sampling\")\n",
"\n",
" while True:\n",
" for x in iterable:\n",
" yield x\n",
"\n",
"\n",
"infinite_dataloader = infinite_iterator(dataloader)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "9cd1d34c",
"metadata": {},
"outputs": [],
"source": [
"# figuring out how to plot this stuff in 2D\n",
"\n",
"# OX = networks[0] - networks[1]\n",
"# OY = (networks[0] + networks[1]) / 2. - networks[3]\n",
"\n",
"# bottom_left = [1, 0, 0] <--> [-0.5, 0]\n",
"# bottom_right = [0, 1, 0] <--> [0.5, 0]\n",
"# top = [0, 0, 1] <--> [0, sqrt(3)/2]\n",
"\n",
"# bottom_center = [0.5, 0.5, 0] <--> [0, 0]\n",
"# center_point = [0.333, 0.333, 0.333] <--> [0, sqrt(3)/4]"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "2c3d39ae",
"metadata": {},
"outputs": [],
"source": [
"def get_ksi(x):\n",
" return torch.tensor([x + 0.5, 0.0, -x + 0.5], dtype=torch.float32)\n",
"\n",
"\n",
"def get_eta(y):\n",
" return torch.tensor([-y / sqrt(3) + 0.5, 2/sqrt(3) * y, -y/sqrt(3) + 0.5])\n",
"\n",
"\n",
"def get_alpha_from_xy(x, y):\n",
" \"\"\"Convert 2D coordinates of the simplex plane into 2-simplex coordinates (alphas)\"\"\"\n",
" ksi = get_ksi(x)\n",
" eta = get_eta(y)\n",
" return ksi + eta - torch.tensor([0.5, 0, 0.5], dtype=torch.float32)\n",
"\n",
"\n",
"assert torch.all(get_alpha_from_xy(0, 0) == torch.tensor([0.5000, 0.0000, 0.5000]))\n",
"assert torch.all(get_alpha_from_xy(0.5, 0) == torch.tensor([1., 0., 0.]))\n",
"assert torch.all(get_alpha_from_xy(-0.5, 0) == torch.tensor([0., 0., 1.]))\n",
"assert torch.all(get_alpha_from_xy(0, sqrt(3)/2) == torch.tensor([0., 1., 0.]))"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "05adfcbd",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 60/60 [10:39<00:00, 10.65s/it]\n"
]
}
],
"source": [
"n_iters = 20\n",
"freq = 0.1\n",
"image_size = 3\n",
"\n",
"OX = np.arange(-image_size, image_size, freq)\n",
"OY = np.arange(-image_size, image_size, freq)\n",
"\n",
"image = np.zeros([len(OX), len(OY)], dtype=np.float32)\n",
"acc_image = np.zeros([len(OX), len(OY)], dtype=np.float32)\n",
"\n",
"\n",
"with torch.no_grad():\n",
" for i, x in tqdm(enumerate(OX), total=len(OX)):\n",
" for j, y in enumerate(OY):\n",
" alpha = get_alpha_from_xy(x, y)\n",
" alpha = alpha.to(device)\n",
" network_state = network_simplex(alpha, networks, alpha_strict=False)\n",
" train_network.load_state_dict(network_state)\n",
"\n",
" total_loss = torch.tensor(0.0, device=device, dtype=torch.float32)\n",
" n_correct = torch.tensor(0.0, device=device, dtype=torch.float32)\n",
" for _ in range(n_iters):\n",
" _data_x, _data_y = next(infinite_dataloader)\n",
" _data_y = _data_y.to(device)\n",
"\n",
" logits = train_network(_data_x)\n",
" _, preds = logits.max(-1)\n",
"\n",
" loss = F.cross_entropy(logits, _data_y)\n",
"\n",
" total_loss.add_(loss.detach())\n",
" n_correct += torch.sum(preds == _data_y)\n",
"\n",
" image[i, j] = (total_loss / n_iters).detach().cpu().numpy()\n",
" acc_image[i, j] = (n_correct / (batch_size * n_iters)).detach().cpu().numpy()"
]
},
{
"cell_type": "markdown",
"id": "a4d101af",
"metadata": {},
"source": [
"### Training loss surface"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "728b0e3c",
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(image, cmap='hot', interpolation='gaussian')\n",
"plt.colorbar()\n",
"\n",
"plt.annotate(\"W1\", [(image_size - 1) / freq, image_size / freq], color='r')\n",
"plt.annotate(\"W2\", [(image_size + 1) / freq, image_size / freq], color='r')\n",
"plt.annotate(\"W3\", [image_size / freq, (image_size + sqrt(3)/2.) / freq], color='r');"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "fdd38f4b",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.contour(image, cmap=\"hot\")\n",
"plt.colorbar();"
]
},
{
"cell_type": "markdown",
"id": "a4b400fc",
"metadata": {},
"source": [
"### Training accuracy surface"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "35fdf9d8",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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TohzJOsRV/eyCBlrvM/M7ULt00XOd82d0dT+k9XmyKzn/Mf6P1y12hTG+pdb5IPjGbnR/dm2G9nTO+fVX7H9Kd7nnO+f8axoYmlJKj0r6D3POxymlpyR9TTj2566qzM1GOTE4JK2JJLlMTYlTUW86640aTp0U9/2/e8E0pD1VXeV4onZxEOtNqiK1oBLvQ+31VNaTbiB1MoKRAb6nk/UAlNeDyOD6UbRh+a5bGRWTO1WHmkrNM4OSpIM7NblCFrQY0YxV9JMx/Js6pNNHl4zzYIyDeNBTYdi0Jsv1NY7P1DZvZJxswsiAXCdqeu4a1It5u1gk7gQluq3j8GGggecfCfr921ZdzvfpLvd8l0cQPZNzXkr6Xg0RT2m4rfI/Tym9qPz/O8v+jfZgFtbSAh9fLenggLylyo6imYF4kBqk6MJGn8M+C+tjNnei1pVzz7LeZgCO6xBYX3+TmkSwIYPydXB5PfPaAI8s9ngfH9cnSNXtJDOL9MV1HQ93DUxLnfYJ5IUOsHl6bhXdPV+2KBkaI3kq7Aa+1D5tqg0ulxKjxXKu8KH25HLiHEmWY22O4n3PejJnj1x7viRw+/zJzlw/a8u+Hj4Pgq/B0i662aMjnNtjZ9sDtE33fKeUfkDS+3PO79bAwv6LlFLW4HL+kXLsMyml/0wDKErSDzhAsMkeyDq0nqUR7l2kCkvmU/JoBiWBi1M0NbMIZl7btdDgZtLlNDujMDJSWy7FJKeJqmwUYqIqrvL9XPntke7ghrQ++qyQT7GfIBsXLfE6LbG/Fyhw0OGW9Ii3O3IMME6jorUJgLcYHqPkU+tJdRT1D8vvKJv6lqJpOM6KxN3M5RO/IyEnMNLoiprc2yU+VF3XZuO8E+cmOwQm2STjMfBMV9iAxiWtfriMwetAg4v+uCrA9RyB+7PtrkPr3fOdc/4+/P4bkv7GhmPfrsrY7mo3vmzjGP8Ta/alymboVxgU3PpUlt2LTrSuAgvHuBBPaxQ5vPIysrMpjvOUyni6R0cUbGKZUSGm9jZXDRtyTQDZHKkIz5FamtmZAxkcXdFIZaR2hFHh9jXw+Zdz9BM/Jt5/e9iXSkDBeEkXjQAX7+m0jElVYBF+k+VZuxvjt09rHvKJbq4vt+vCfQeq7ImBC85B0S31sZR+WfcIrj3FwOzQ895Y1eFYIL0B7VDSSzQ8TsmaWYwc37/t7uW8f+v5Eu6xVESlNn4dY/BRwLdF4YUamkcVgwAN0iKvnqvGei20Tk04tROIqGtFQKYoFMvhyDDYRH+rl5/LieDIkd17HBH8yUb/2RQFUL18dB3dTBNkGQk4B7yrY/yPVZXap7d6bnBXcFObLdElZpkEN+/rsUKTY2K+H4XUM3cln5fwP8v0OR6okm7PldTNGKQwWyNwbg/UPjcf8HjPZupsc4M2j8nxFO8eah/EwQRrZryDmi1uFiZV1uJpmxVxjz1RdTPdm+kq0r2LnN6A1AsIcASzZzoie0vt0gyp9tJeFJPgYf/kQOsWxX6OGtctRoy93+fp0URXu4wYnlJzOcbr0UgCCgceI4QcsLz8zvs2vnvAYdbl+cnD0J57iWes1g/3ZFWW56aiLufm8f881kZS7bTuvjOkiepJBFY3wyG+eV1iEMTD4Vm1t4Xdn+0Y2rUsJWmfDCBqTjaKHRMNvdN+DH0UqV0ufqSBi7s3HGt4+wXdU6mCpgMBzMvgeUvtykgCioGJgEoqYrZkcDDTo7LL6dsA5ql3qvUFxLyvM7JQUyYjitRSHLrAPYbpPGkUwxCGJFEdh+ACwehQUnp0yHe8kMYzaXI+7Cewufgl8iVw7Gv9UeCz8E0VYKZ2PvJTM0aqIr2Jf1Q4FloHOGK/gcXNEOXSyEr9RI3IMH1JmaeNXr/dcnZdd0f/b63vWEN33pKUr21B403bzS/bMK+W1qcrTOUWmSfneKTOWFU5tiBvADhUBbWjkn6pYerydOZyKKRzFEi1h0/xm0Yt7xa2E4B6orzz9jf1L5cR72GlGWh9/TjiejF+sjp/U1jyuXBEuz6Mlm5wtSNZ9TYPxsRzKaMvLaXJvB3E0cUkUMX93jdSJehkZj6ORJZVOFZ1AnxJjPcxCO19Md5EBYAxGQOZ5wafI79tcTlK7zq6aTz3znAcibPnd8/Nm9zfe7MdQ7ue8b2X0norQ3j3zMTxt+Lk7O0Gnrg8IhrBJfaw6H9EYYfppPW7AeKTQGIdenmx/hzd/jA05jL9nBzTCWp2E7WgRCCzRXV+k+bIJSnjNo9Hzspz5+J1mkjjybDkY7X0xnkBDXoDjlUn1vI0vM2alYHLv9lXpuEj5MFmZ76x+Xy5mYZ5hsvS1J1sbBK2kfTSbXcdepfd593jTDHf7dkO0O5ufHMqpzu2xrx9dv5Ian0Iqd69PArbHbV0ngwXUSRhjyO/tzsYeT3rSEZDxmjKQGFl3PntadXpuNCYaTkaqOvFIATrZdecFMCAG5ey8GZ+5kuxy26umXDRMxPLDOeb6IYH//Azy3aRKS+LX/23vxhcWa4wofdL/I6AYmnxMdVlDWZQS+Rjcm2wxDy6Uh9uaSD6Ub9yF5kib9eLMmx0MSPYjTrp3DV6yzBG4TipAiJWz2zxeWi7oMD1zK3OAWZDC7tBE1kLwcbmFnZPtfq7UHs/Jst3L2aeUcmW6mLW6I9MVNnSQvX2JKaLwOP97itLrb8YmVHbqALHwINBhwDiBcjqpIuKuIHZOqEBiMEMIY1URZ24jo15emSFcj+z7N+uuyiHrK7ZZNDcHllKi3krrgvVpptnonlb9dHZR6qgxVPqsRw3iT9LtSxsiryiKC98O3+uIxuF9O4CztfH8ZZbn2dkpxEchf97893zt53LeT2z1ugpc1HZWDLICC/0IJOIvZdGQcE9yv/HcBx9k4lqGCn6KFLLdhh/p0bF/HrMhb6MOt9mQdHoRvJ8SSf84ei2xdHLOpBlEiij3jYKaXjedLWF4yOYa6gjGRKTr52v22VRfs7bJCSubi4noYzq+SYW4TJJsn0ZvSTRsqbnmUjcpb5aEn+7TIW0UntZnZ6A7/mW65ppnvc8n/ny7V40fNMWWjxFVhOnJWpKnN65PowgQX9mrrbFaWPV8BlHCrm/e5jLn2Kfj/P0TrDoua1XBY3oQ/TEEJ8jdcZTtUtXNt1V4X3+3/upc9FMdfgI2LjkhYLPvLOPQY8StJg+01+pv2puTjJAnUdOpOW8jadY5PelcFEOdjtORMCyu+jjIkCRocU5jx+eam/dFwMFCpfITehLb53OaU9Vm9ostNdt5kjn233dHNt565O0A7TrGKPBMbQUQSVybq6gdOu550R/otfLoobWczENZqcapmv7OhxN7j0GtV5wgUzvVOvr4Mh4mAdDZzayMPol9I+iy+x8DXZnaoEuCjQs3y5oj93FSC59JLNYn/+h6nqMT0njC2lypw8CyefMycBINJIOTqTbfvt7actHFtJkOSR1FeINJsRuV8ldZoQirEyc4JLxMkptF7IxIOE0nBOpgDCdu4ZdZOfzDI5z1+8FM5wflYTedX3+tmNo9249gYBRNwoCsdUobkvrDIZTIZkLgcJCt/0J5+NyRmo1Kk650d2iUBIjjj3Q8rcZJUcL08fzYQ92IIJ5EqDHqGMEUFovrGZGGoMJrB+NI8ltd6C6fEaSnpGmd+qlbQYs3Vkfb32ynFuaaFj3hjZ85Fzan/clPVcryp6jK9K6+d10xOjeaSvsiyTfzWZmugjpHZORqmLAJu9FSNlF4627Y+1czgcDaGRkEWgo2m9a/hD3RXcsMp7ozrLMyIgWSEP1mcwxupEx703W80OkdvFtT9SP+pfUrkaNoM3f56qqtqlMr6696d0Uhv/H67VpXQOZbwGp/ZE0XdaBbebU5OFvj3CO+g4SjUfD+1EXy3WX0QqBLbpxEfBcjF1B4yqft+bjfFlGOI6nssl6l5CAtclI0vkdm/uq7nd920U5r29kYhSgGc/3WrM4SH281Lb+VT3hquMJLKyH2dtC9Q5g93D2SDIaA1KPYdkoplOLI4V4TK1meIoyDrCvLKFo/Ce6ha7TDHVnAIH+mC0yQtbbAOPj7MPZYrsa+M3ySgDmgO53nAgWIS+m6Rm0vMWyrphHcavm2xSbkeoSDV8CAhqrFd08N5uXh/j43ilKbUDd+fquu1O1N7JLbVc1KY9N7Lq62/TiS8/Pdgzt7mY+HDu/VF0oK50UQw60vpq9B0bC/1L/JnOFMv0/93t67/kSUqtKx/Oh/rQIx0eGxqUUpAdmqKYcLtM913X32jDnG8GIrOlQm13HOGpJcyI7jZQmrhVwGTNVAcnr847CdXOdexMSr/3dxKHFUNxzkn5dA0jcVntpo2JhM8M6Um3yeMOGTyW6kG6Sx1XnFutwvMxuWncRr66Zlzpbx4veP3U+SqZCHocaHmv/UtUnY92/PcQuZ0rp7ZJ+j6RP5JxfW7a9WNJfk/RqSb8i6ZuverVUYxwUVDyXWq070nII1ydPOR407mELtdOtkA9VX6kfOWV6A8ZM6z0pPhrBxwjbpZZt9hiFe3IEuiiE+P5R92J/fM08HTtP5mP25TwJyAYfAqiNwGEgI1MlgBHgDlQ1SF4bj74YPKEuRlc6KutCXgz4bAr5Ifm56m1AUl2Rw0/EdM5dJOMGtJmqnOrLQ4bm4w9UJdH9Uhfe1EIX28d5X9TY3NX3caxQdzeF73M90nALs1na/dtDDGiS3iHpv5H0V7DtLZL+Xs75rSmlt5T//+Rdc0q60vWjNiEB1Mhs2KM2iQ8RxCLbEI7rLavgjeS95RcslxG6q9Tj6IPQnbRSLlWhn4GPyBC5v6cQE5yos9nnCeL6ygj6804a12Uf37FeETAJgFILeqYcVOrHas9rphqc6dV7UdcyGjAWquTRVeXlYrVcHD1wL/9wGuMyHxjMbuDmES4JmRLXPrtbEtPdfAZHnwe1OZ+XFQPPJ2Zqm9arPT97iAEt5/zzKaVXh83fqPrygndK+jldB9CooHJmjuIB/t2ncOHj4mCIzIpmwJRa95Mu3YXWl6Mfld+sbwyn0VXtgY7dTy7KpVhu0ecE5+dlHoxc3kIevmanqo8+IrjzOnKZCa991M98TmZ2pgwxIMGRG48lAPlcPNp43ksNftaJKnBG9Z6j/EztHR+RLc/rrgMNrpddwCO1LwPzIWRLBCyznxXxHEnjZZ17ZurPW75EIxzvy+VtnAOjVNkDWWp4jK0Y0LzfBNmXbHvr0O7m578w7flqaC/LOX+s/P51SS+71lGcQulyLNskjcVW5wwfAY0tv6nHedqmD+HnvHjgMB8bB3gsz2l70yQZqbUs9/gT1anYvpLPy72WYBAHugGtp0kRSOmn8HopHOd7ZMmgLB7ZGKLzZBSFntVspEp5eKuYGRnbz2b04CQzxwt0AsM2OzMI+DJ5sBMro7vJyyqcylgDmGkq7c+GyKybycc4bezCVCqcV7zzjJ507FKUJ91NYnekfGlGx7zv3z6Ho5w551xebtC1lNKbJb1Zkr5wT7VVCFJlGtsv4XcJbkCPcVEz6mljCtvGWu8xUmUjzsODyds5JfciltHdjAJGDBq4JzosFvMlyPaifIzd846IeL4LpHUeUguu8brRtZ6oBS0hTVyY5dFMIYhA1WNoB6pAzDottI4S5fgU69I5dbqQ8RRi821SIMZMgDaK3YfeNkksmZe0jtdObxCit+308RZbHiOtr6H2fLLQtgDtIXY5N9jHU0qfn3P+WErp8yV9YlPC8tLRt0nS62+nvMac2HEmWj00cByXH7B3xh7aa0UO4vghuByqAgtfC07x2vlNkScXANONdB17deqNKL81hEAd3WfWg1M64/+xPFIGfkvrT1fcxCx5vkLaXnuYrW0aUaQxI9Vl+z0QdL1mKDMGLIqliVb3e1J6gzTbEPqlWjDi2jQrHxNJh/N6fzFPMXruzsenMVOrAvDUGKeRWtmT3dndlIF3HsughS+t89oB2vOzd0v6dklvLd8/fu0je66OeT/FhSgsxJBPEYOT08Q8KVo7ns0pLwKStP5cG4aVCGJkHHGqd6+KDMohr8iuHKriuZvtk5m5fqQKBkLvo/K9iSbYXaVr3VvQO9ZwzahuR1c1lhmNgGy0cB4WgWb4uJ6P47ytM56FtKAsaTK4hrNlu9LFTWMCGZuXmDxXvUNsUn7fxpusDJJjVTDxnOI8ZhqeJ3qids5wjMlupI9hUCDGuVg/qe1qB+USWTk5wTnuAO0ullL6qxoCAE+klJ6U9Kc1ANmPpZS+Q9K/lfTN1y6RLSbVHhdVUjILMoKr8o383kzMojqZCFma63CqCkYEWU/rFugjU+HAldan3DHynGt9OrboY3dUat1pMjsyV07bvE2Jo9rlU7di9JCg5nqzbSJ7iwAW2SFd2egusz5RGFpgu/U21s/5OU+ik1n9eT09Xz4SWyELG8kl51I2F4HGTc57931pzzV0Ia8to3tq8LOu52MoCc9CWbQx8iBDm6h/W/H920MKaDnnb92w63fcc2mRfcQpshdVi0CGwEKK4OBjokIb3SSpDlyqsI+p1fakFtxiRHWT2Q3sGVlfPC+6w3ebamM96H7yGrLOEQhYtj8r8VJ90PTi56gnuk78zeBMDN5E+mEA43m57aZqF3RxPRuUdb+zwJcvFiGcnrui3UVnTWkwMiYS8aic9ER5xkPI6pzuKs2r163dNTiPei60HredpRufw0GBe7KFhpeWRJdtplXELs/Dglr2gLhMwu7TTFqca4hMESwiSDif2FtU9j9evk/VLl2wlmM3jb13pPXRw3p64EWGEdXkXp1sBBgeawCI26V2JFLjW6gK8hylPj6I8auRSKBkyI5MLLIy/t8L3sSJy2zQ202VKF5NcXxYbrM/kw7P62VgsW5GZz1TC2724KXWjaTywTjHGPu5UsWn4fxeorqmzSB6Gk6fTM2nzJgO9T7GbmxmfdL6M+Cenz3ELuc2LS+kxbPS2KBwqJV4sXi2vsR8Opceo97Cwe5pz/rLXFqcDZ1kshxuVF4TmHv3WJIdupceqg6aY9UbA6n6MtLI3u1vTpNxWcI4pOHA7U3XPRbDbez1kUK43mSgC7U3exvsOFLIHO3f2K/xdeCSmagtEhx5HhHE46RA6WEePmbTFqM8ao0OvpYz6bG5mhvgycZ8GmxKnzLnV89RMf7CtM7XcwMD3nYpX6JhPdNRSXOi4RFBVjai8dIQJBl34nJEzzu3O/vvz3aAdi3LKms351JyyxWGdqr2BeiHSzwKxS3tFmOY6kwaPYtCOIBjBC9qP1ILCB40Uh0B7HkMI3HgkTVI635J9EMI1Dw/heOilmXAoEZHV5gsdBqOp/jj+o5CvtGiu2pz2Zv0yB6g0QjktrhGja4vI9bUGS2SMVAzHZiapBU6jZfSZF6rZb2KTe/u4uLN4CJLWi2XGNU1cFxnRqZ0W/UpugYpIS1PLV5msknOVWScbHou49iObQ/QUkpvkvTDGqr3oznnt4b9X6hhgf5RSfOWnPN7yoL+X5L0r0rSf5hz/sNXlXXjLxp+xC0TXDJ6NGMVt9MtxB7gHuMl4NPh/Y+P+Yb2F6s+WN491OXcTbggkLh8aX3QM05udkBQi4GCnhvY09noqhJgXB+fs9SOEOfl+hhgon7lc/GDwfbVPuKVxuipKQ5ZMsHOtgjbesGEHgVhnqQ/BqsTtfraVcZzRZul2RC19KW5rRasDlRBisAjFLsioCVinpbSwVm7TMQk2I4EnQN2q4j3lHk9z5v9eQ7yfOHywAearnn/tj2GllIaS/oRSV8n6UlJ70spvTvn/CEk+1OSfizn/BdSSl8m6T0a7hOXpF/OOX/5dcu7WQ1tovaeAgKDaseZSvWluyX6mJ8dGnDfDMX5eXBK9X6XI9XBT5fVAsUmI/CM1T5MnkKFp3i/QIXBCQIDI4qur795Hj55glncZ2XZrqPz5PlE3Sz2bo+ieF7M1/X2x0EATyo+ZhHyjMEUqaUTFLGii80RTao01wBmE7V3RLgdSaPigq6OPpgmgyTxiOsdQXkxAN/4vJ2HnHSi4Zlu1CTHko7OWo/bGhllS3eNI1VQii7vYcnPSzGeDcf5zgFeUs4RjOren23V5XyDpA/nnD8iSSmld2m4dZKAllWfI/O4pF97voXdLKDtaRAWzNHB+ylDTaU6yEqrnWjo04fz4ZHMq07vdVyeEs3xqSWx5dnh6TZxcFmc8D5qNwYT3vsppPdKzchIXJe4Nswf98gpjrUZXM06XX8GJXgOUbnmYI+6n3UyRg4NqAQhRmepd0X2SV+KLNV6V1yXYArDuvg8DaA2s7qZakAg5kcW6c5EcDOF8sMHKLKdlct33l5OX9KxkM+03Xd41jI5F8MqUaZlwNjbj1TBzrg+UyXVbnqClruUJc7twNBWo5wvl/RR/P+kpK8Mab5f0k+llP6ohlb597Hvi1JK/0TDapg/lXP++1cVdvMPeHRHc+csLk0zoU5UAaS0mJOeqjwk0DzbvYbcnlpX/KYbRGAgyNnYQ3ur6eliUcPyvk0R1WiMwbNsamNxoEuVnfVc2n0cz5v/yTDox0TdzvlFIYmjlOwzGs87ivw8Z35zXUIUrQ6Q1wW+qfJL62DN/90+RghPhPbdFkOe45FW7ytYkyh9bQ3q5XqlcswttYFvEsAxDuNcYUA7VGGRuObG4ynyM87HtXNSC8L3Z3frtCt7IqX0fvz/tnJ30L3Yt0p6R875z6WUvkrSf5dSeq2kj0n6wpzzp1JK/66kv51S+k055+c2ZXSzgLZUfbKEZ+zzQbcwwZpIrVZUvjnh52VZg+Ye4VtjPKUZ7KLmEtwLd+DVPvZCtmcU+Q247o0EmwhqFLe9jawxLmugLjZVZRJknu61ZH5xUBsc2NNZX1/sSdgf+zEB2wzKE5J9K7PLCOoMJ3L5RRSlDJRugzg6pzj+DHkbzFxOLxDCbbw+EchdhxIFnp61OD4R3hEb2edculjWrkjVIXY/YrwB05c2+W6Wos1J6zeNCOm935d4e2B2Ty7n0znn11+x/ylJr8T/ryjbaN8h6U2SlHP+hZTSVNITOedPqDxQK+f8gZTSL0v6Eknv1wa7WUC71LAOrbRAPl8XUlNcfyZJk9YDWUoau6UZJmIn5izMPJ2vBwh5PxkIe8dc64OFrsyR6iNPnXcUvKnnXahle2SWro+nZPsiB6pLKDyADcan6rupLk9qB/OBqn/j8/P1ZD68XhZ57J6eIr3PkdfIIEaA2gRkcVnHidr292xnKcB50v1kHSl6MR9em7jP6UtfeSTIIftkj2yvuXQxD8+x5EQRJohxOW5/MTA6A9oq/+L6j29JB+fr3v0CWdPZkbaln0lb1tDeJ+k1KaUv0gBk3yLp20KaX9WwUP8dKaXfqOEyfjKl9FJJz+ScFymlL5b0Gkkfuaqwm19YezIwLBKKsbR6XEvjBsENsbS0WubFAd3Tpdy5vZ3LPXx8CEqsjFMpB5q3eRp2OWZQ7H0Gpuhv2B+h3kVW6Ok2uoX+n4EDXxS6cnczurAER2lt8DVBDOpbBiEzJGk9QimtP4van/jGeJqv3wzpo1s66hxHBhknRFtky97GtnDbFlDLy3KTOpkZy5638ZKVh+HJjfojy5wPT5fJLDv0lfFyWOI0x2Gco5jdorP9+dv2AC3nfJlS+k5JP6mh+m/POX8wpfQDkt6fc363pO+R9JdSSt9VCv+D5Sk+/0dJP5DS6p6gP5xzfuaq8m5cQ1ss1z2biVQ7o5kI3c6DIfpkGt64C84oDmyDHWdVLjcQjqMYEXsFhQt2ZrINPsjQT5yNJ8i1cxyQC2zjzB61PrO6uPQkHtdzR6H1rJ1/PM+4P96Qz0FH2uxJgwu5XD7PkbpYnFwoBkVxyL99PCOxUm0Hu/7RzWQZZK09qcjXdFHWQrrudIuRN+W/xDUWrDfbDuZJepU2eCZJ0njen6/Yhdz1X4gvGs45v0fDUgxu+z78/pCkN3aO+5uS/ua9lPVAXmPHyWjlZhLMDlU1HndeaX1dmNQyrair0LUgUDmiR43HnzOtu7GuKAd7jKJJ64PSvZXCtpkJbwan+EKtS6rA4Afmx6hsT1CR2sdWS62bp1BHnqujtBR3qEcSBCIjI4i47RbIm8sz6LoxQET31+dwppZJUq8cqd4pfqB1LZOML14f+nKR5U/UnlfUBw2mo3oZ9u0a2y13OZ4QKXhBd5MGJpbY73wd1XY9YulcNdDrS7gdQNtqlPNG7YEAmtttReU94AlmduHYkafIIN4rOdPKzbM2Nz5T7fQ+jjMlOzPdV7qufnwOWRbZCMGM9Vkgnc/PwM3BSPYSAUKqg5ngHJd88MK6d58jn+i6Su2U75EyUcssoni+CMe5zWxkQNFF7z2lxPWYqT4eyOfq8s41aGp2QQ/V3nQ5LvsNJu4/vC4GFbP4Xh19/QjsvD6cyHj8WEq3S3K78pxwXb6taMcxjjPW4IKuTb49BolTYaD3QtsCtN2tT9e2kQqQRTeLkS4yAqlGL23UM9y5LFRfSOlcGsUIoCOfZCDuLBxcUaiga2O3L7INMhe7d6473bWoDQr18QAYa32xrOtk14XXKmpJPA+nJ5jFW8FYTx8bz49hOzJIg7UniR7riQw1ivEMRgj7XIZBmqB+qHqNCbAGs9shH+fhttgEZtHdnmgjoDRpfO0iWMdjS5u4eSKxldS6pzCm8Sl5e09BuG/LdzvxF6bdOKCtngnPgRlvHvd0w//ZwGRI7qAhqpQ8o0ct4zm1AzTem+IBQnZCAPXHg9SgEgfHFN8HapkO003wbbcosjQahXLWyecY3aPIzry+bxTSCemj+8V9BMDI3m6ptpXdxyC0N4ERgxZBwedhfc4s0NeSDI3ppJbhez/ZPSmRjROoAcztQCmC7rsRxXXytXJ+1HI5oc4GN5NdbC0uUuqcO4C2Cbx8WiPh/uf7te1FGG7Ubv5Fw1F85mzGNWHuGEu1j/Px4Gc6G9lQr/POVJdo2z0w8BhQIqB51iUjIkiRQdDF4kCNEUroL81SD6kdDD5HnpsHXgQTiiyxTAdZuC22A+se3TKK4pyIWKeoZVLri0zcRooSgdX7j8rvWan/i1UBban6hnupdTl9zAznZPeYk4JK2Y+pygvWUmeqT00YqbLJUciD8geBkEx1Ji3O26WTj4y09h7W1btp1c5P41LmWNJkvh7rsjqzlQGddXdm+gK1mwe0qAHZuF6JHS3OkvEWHeGbQv1FONaAab2TrIkuLgGNrjBZmgGDA8AMMIIY8yCTG+HjfYyQUsvrgUjUeQySZi1kDAdar0d066N2Q22QTIpMiyOK6Sh+k1pEmSAGJHrm6+BrS8A6L79dDgNL7iNzHGuLLqGB8FC1HaaqQRj3TV6rGOCQWmYX3e957ZJuIk01AKnB8qRWKwZkx6rlJA1BBGHfvqpUeN+Wtc1FbTdqD+bWJ6mdAeIN43QD4napBb8IZtSCLDZzpjR7iAyOzM9lxYFI95ODk4Kxz22ONGYuEUCE9GEpQGPUq+KznxW+7TZNw/HSegSVtknUodtpRmm3lW1EWkGtMpbPgc7jeF0I4nQFCc52cRmYcN02gaNU2Vq0yCB9PeLCX6aN/ZR9JJ4fdq8uaZQNxvXfNZ1tqWEx+Xh4CKovbXyewY6hPQiLyxvIDigouME9QBfhE0Vyd24P5lNVRkYAY/kxOh3BydvITlxf9joObLse1Nois4rn77r0mIvziYtG2el6Agv1SDMVH292ydX8vD3J16DnZsY1dTxvLrGJwDJHWn5HQd5t7fr6faFCue4TjLKybVyfuHyFZQcGtWrHHj2KAMv6sh2IMNTPyq5xuQZj50VWPB3Y1/5MWizr4X4OwmgZ0qt2DTf/1gb0TkO7pgFM/A7ORsykq8TZ0ZzarUtWxxvo4qLcM60PdGkd0HpA5nTS+kDmKnjvd3ovtfB2AxEjcNSYOPgIKBxIcdGo6+1B2Lu9a6EB1J9FnayxRSbLAR2vPcF4FLbTJeMkw+ADNamok25qb9d/Vq5ZDAxdqHU3fa19nJFg3jmWbD2CvrfbfeQCbdeTLj1Zp1SX5ixU35qCCWFM2qVSRryeI2l8p55+PGSM5Payx+5jz+n+bcfQrmn2zRcDmLkfTFTW4ESXL0bZpDZ6RKZFVyq6AmRRPSGX4LPJzY15crak2+u6uSdedU6R5XFwCmk92M0SY70ZqOi5gb7DYpPRBeT1iayEultkVc7H5mDEWHVQ8x5XBhx4/ajzCf9TgHI5c7WPABJ+X+XCs/5ECx8T3WJffyJJ1AJ9Lg4kLZCGk2JcGcsyJjVNxOaY1E/1kDQEDIxsp53zfT62A7RrWK7+f+8Wyi6Tikwmak9xtuMCTUepTlXBIi4fiEyEQjtB8CqL9bKg4fzpohLsyFCEPGIEki5OBDypHWh0SS/ULlieIw2B7zb+j6DCARy1I4MshXeCLMHRoBDlBkoKPH+2A/Mzm2KE2Nc7jnx18rGZ3U1UHy3LCVH4HXW5nsvsehAsGRSJFnW82IfUzl+xGK92WgUX/NnGuo2snct5HVtoFchp+u5EWtclpHb246zrDOICyZkGyu28ntXwVgoXeqTheZiPqZ0CIxjYjbI5v547GOs5Vv+R1j6eK//tJnog7If0LieCeLRe1NLHTlWfBOJyCRi9ekaWxnz5P7VB+0e3tG4GHw/iU7Xr1GIEMq7S700yXsBs1uNbpNhP3G5cK+ZF2Gxnr29zOmqbUvuack+SvBOj5y7TyPLdrvtqZQOpurcXw+Lz6bKeBgkj56RH+E+US56v+eUfn4V2o4BmfZ6Sx1R4DlRv5b3w258RPkxrhmY70fDmphPke6ThqbnuzNR0opDNDusTICiw83IQROE+upXWTcwMyHh6nTKep40DhYPF5+b9R6hLnARitNLHO9+e6y5VIEv7Qy+aXgznHVf8Mx8L+GTQUqv99UCdFvWw22oDPzRqhQQw+2sGYgZ8zNoIPAa7kerz/M7VAmdsA15nMjm3Mc+ByzzglrtrxDlsX8XNjIGqbdqOoV3P3OcsNawemhfdoOhC8P/eeikbZ70T1Y7O2draDp9gQeG7l3cED7oo85Auiu5kmBTf98NvLsngMbFsqQXXqzoz3UTXx9fEA4yvhos3tBPkI6OQtOpCkwBoI7Vg4mPcFmZZEbTiZMX+QDYXGWx02UbhmxMlASW64ZsGcnRHeyp91EejUT6I+92/MSGMNUQ2Jwo3rseo80TbtV1Q4PpG3Bj7aaycaSisM3zeu0+QVE84doY03m8EFdL2bkDudVhWmstDXG5kPXRB52F/FA/dyWOUktE3pusxyAgKBAp2fOcTz83XxnWzsHxQPnv7ki6l/WUbCZxrWGOgvXUWRvBhm/Fa3kY5FrXdDw7CsXFyIdvkxOcBT+Dque8Gn2Vnu5DnXC04Uv+MWprLGOGYRScPA/8opOWEXfJc3fccJZmel7BN2zG0u5vbciINT/U81PoqdptD/ZvE3jhTsVPQzaN6StbkjhBBLs5M7FAcbFwTRvZhjcVa2SJ8u7OygxMoCZJSy0ycZqz1ZRs+hv+P1QdCM5He9TvVoD3aDqWVuDR6rpYp1cVR44K605pUYw3uqC6ly2UFeV/HQ1XW5AnC15V6lgEkno+Bd4YP3WipjaiSOV6lS/aCN36kxRj7XJ+o7ZJ9+jsGKXy9p1p/Eoi9Bh5D97JXZ9Z9G7ZjaNe3lUwSKTOBJd625PVAkXG5c/q3Oy7XVXHQRMbQc1Gkfsdwxb3Qk4ySjIquJQcZB5S0Lrj7d1xOQuDmS4KdhoyAIHm3GZxAbZ9mWRjYacl7JfCXQvfuDCcSlx6My/F7exq6lD+qx00u2rfNc4mJr+Vt/N4rJ2NWaJbja8FJiSBD4CaQ8Zx77dvTa2N79tg7j7mqP5EBUqPjRDxTjQTHZS0HqpJEXL6ybXuYAS2l9EpJf0XDGzWzhre6/HBK6cWS/pqGF4L+iqRvzjl/+m75rdqeorBXgkfqPQvfPfbBAc+Gji7nOHxcGXV+06I71xPWpfWILBfeklXYCMoxz9j5ydCoh02RngDrcuyqE9jizL9iUpJGhWmR2YylClBTaXLWuq+rQTyV9Kgq4u5peKbWpaTZwOKoP7J8CtsEhbxcd+XZHpHluk4T1ftibVFnYjk9Vhbz3zQxsE177N4Tkc8zBr4YrSULo7t8oPo+BwNaZK7binBKD/29nJeSvifn/D+nlA4lfSCl9NOS/qCkv5dzfmtK6S2S3iLpT16VEcnTdC5Nn1H7LoFeUKCwNa9fGy2LrsCZdKkWULgIk5qU1IKE7zzoubL8dl1mas0djlqO3aAl8nBH5sDwdoV87Za5LhHMeI2oIXKpiKO9dpPIMOLMTsCaXtTyzG4nUm2gGZ6Djjql2xrA7Kh82+wLTqXRWZt3PL+oJS2XrZseo4Y+B58zty9Ul5AY9F1e1A/ZzxptUAOIuD1iP5iHfG0GAu9jv76tdk1brMsBrgf776GGp4wclWvkOrif8by3ZQ8rQ8s5f0zD+/GUcz5JKf2ShpeHfqOkrynJ3inp53QNQPNwOFXpz0vp1tkwTlZvy+lEi9he415InIUwmmhgob5CLc0dQyiXAGK9i3rKAY6X1l3kC+RHzS0K9HGA+Lw8COiSMQJKIPBA2XtMA5hcSgefqBreTHXmJ6A1Lk8BrL07w+Ing8RUhb0Z0I6GB809egdvD8E+PYGLY4p0KWlvcCFHy3ZCocvs9iazjcw1uoHCdYrp2bYELKm6r76OXobhNra77WvO+lrXnSE/Bh2cv1TXXbCebAf237HqchJra26nI0m/QcMaSjK0U9R7VtLuFtZe31JKr5b0FZL+kaSXFbCTpF/X4JJeaVnrJIdBn9vzgbkl0vQyc49HYGebhF26e/OwL4rC3kZAi5FAsgY2MJkPB08sJ94wTybqfBjZulD7vk/Xha618O1Bsrevyo5mUnp6yNB1cz6MrNn123MLFJfy9tnACAysVdQqnwKa6VKNK6q9UnkytOJuOt3+RTvBRH3L17nnxhEEeE4x4OHraNCaqA52f99NYzSbJis2a5IGIPFkF9vG5nw5EUUPhIyQUgOZv5mbm8HRaJbX6/P3aw8rQ7OllB7V8AaWP55zfi6lOhWUV051H2eeUnqzpDdL0uernRwjLrl996NLUtZrrUpkR950a0svrTuJO1CcIaO+5tmQIEU2wPwoXDMiSrYVXcZN9eV9gy7LA5kz/irNnioqz+rjTqNrygvf3DcDsDo4q9fnUGoBysZuY51skwH09i+HWSmyLLZDBAayI15vLreI1yoCFTU4IQ8L8GakdLUjU7erJ3zHSac30drI4shAI3uMx/g4R1oJ2ATF8yvyuVd72BlaSmmiAcz++5zz/1g2fzyl9Pk554+llD5f0id6x5bXwr9Nkr4spez+xjG/NlFyRnOCePuLkGaE7ZzhrS15hrNuZjbVm+k5gDyjU8iNs20MENhFdJnxxck9d0pad09j+jP87wG4uiYzrUAlX7SMk4OTQNZoXwSdx6TPu1MyeFTrjOuy89uAav9nr7O/lLN3Ke2V+no5R+82G7bJ3mgA6VNVVh11wCjgE/DibV5mPow4cv0c8+Q3dUgzP9bBbU+2STc2Ah3d4qjjulznYYbJfuGlTSdqtdv7tYf51qc0ULG/LOmXcs5/HrveLenbJb21fP/4dQt1ux+qxY/GDGZ01yjMRpoebRTyMEhEhsbO4xnZYMNGpZ4ywTERjQ1MrrfzjK4rw/JLtUtCLEP5WV4ENR9P1qKltLxoFx+7HmQGrss+dTEzNJXfT5SPwn6ysAJWZoLJo/ISH7ao8yjuqkfxXvkeQSgly1mB7nSg5wfP1KfIEsDInDmZeZmIrzPvM53jGDLpOJEQLKk98gkgTsdZ2hOigY+Xg5OatbAoiTDiGR9VNQ7HzzRcl20xNG0xnxu26zC0N0r6A5J+MaX0T8u2/4cGIPuxlNJ3SPq3kr75bhkltXgQ2flqlYCZRFw9LrV0O858dAXcIQ6QR4wujcNv77MmcY59kRHwROgKRrbH6GZPZ6ELGcGPZt2EYM5zj5HduDTCZaw0M7qa1MPI2KR1MMM6s3QZ3uZxibw66Vc2k3SnfPZqMIJg1AQcpkO+aV+aXNRzIy5Hl5NR5uh6+3r5OM+wnrSivsd+M1W9zu6nvubuc9T1uEbO1nsCSwwwRF0w5kGdZtt618O8Di3n/A+0OXbyO+6lsLEGbPGkGiceqbQjXcXbah8U6KURjuL1GJILITtjR4s6mX+7MlyT5EHBMH3suNS4yBQ4QHtA5fpzaUA0MgwGIThQOGCpkfnapJFagJIqSEG0Xwn8t9SC0KUGdH9Ua25mUkgbmZkrBmAykK3ymRa2tsnuDMdl3JEQGXxk73Q5yWrdBgeqQHE37YvASH2T2qQt6mMMLsV2croeKLEtmc7lkaE6iMbt92sPK6Bt00Zq30AWn8CyYtmeeQ9V6bu1hBMNt+Ycq+2MpPtRv4rifE/LcOeeqX16aQ99CZZRaLYRIONtTSx3gnI4q9tY3zhwmM6DbaTCwuKqfYKT3T6pBRqpsjSDkY9hV7mj1bq0lTG9K0TWd4RyjpEuAhndVvtTd4b3v9mFtHwwlbRvHVADKPpuButcZrYEFIISNa4euMQlGWyDHgBax2J+ZMj8TbDypBVdbpbBCSx+7AI/3anTvdrDHhTYlrkveuKitMD2XW3wRmoFp5KekxZnVeLal4ZntEt1xiYr6zEYqRWQHW3imjIyI54EXZ2F6sMC4zFxYPTYpBmajWvYWGcao1sGwsad3ARmUnvzo41sybNADAb4m5/orvp/g9kUeR1puFCLkuZRDVMa9TuXwfoVMHNnMZBNJO3dVruYtzC5yVmVAXjteqBkjWumloXTIrsaaZ0lSS1znodj+b1Jd4nRcArM7IfUcGM9t/Vizi0ytJTSmyT9sIZa/2jO+a1h/xdqWMt6VNK8Jef8nrLveyV9R6nR/y3n/JNXlXWjgJZUuy0XVPckjlUExx3uTI2ryecDLqT6rHYKywzXs4HIlJzObuEmrYwgxgiZNbQD9W+kth5H1zIGCIT/PRhcZnRPaJzN90Zq9a9NyyniNgJP/PAYAw3BzcdH0GS+jpQ6z5nadWt7qgAYAVIaQKqEeMnEVwt+qfFd1nQROKR1tiVteCSSWuZPuYB9IXZctz+Zc29NXZQu/H/0JOLdJbYIZnRvu4un7tG2eOtTSmks6UckfZ2kJyW9L6X07pzzh5DsT0n6sZzzX0gpfZmk90h6dfn9LZJ+k6QvkPR3U0pfkvPm17rfKKApSWlP2p+3clNcGaGZWpeS4e0yk1oX7kofTm/jzE7NJa4jsnZHf3iswfV9XPV+OrqPjKb2omELDW6ywdlpI1BFd8dpXFYcDK73yk8/UmUqBh5fhJ7LGd3BR8tJEoAUjvHvO1oHHloEs0dLZR39jMdyce6lql6g4dj9Y63eqDNVjXyulotQDwSoTVTZMy1GMN1WM9V2vQpMbqtOUExziu0uh+vm3J8MPhMNfcqk+EAtADNq6cmN7c+F4Y6UboNZbTco8AZJH845f0SSUkrv0nCXEQEta3iOtDR0wl8rv79R0rtyzueS/k1K6cMlv1/YVNiNA5omA5uaLNtJrnls+1zDo7OPVRtxiW9J45H0iNNTCKdAH/3aA9XoFj/u/FxvZFC08HdUPtb1VOvSHO//hTzc2RywIAOLa5Y4+DxwetFRaobpMbVrxgqYXZaV+aMLBAekNgDg4x5XBbYeQzM4egQZeGKwwb+pm+2pzhJxfdqmj8u/M+Q1fW74t1k7Z3CdhWir2snKE0JcGmGAoTvHyY+upPsVA0LMX6iy2zDqaTYHjDgADtRqxvZG3Aej52GJxEGyE9RzG7Y9De3lkj6K/5+U9JUhzfdL+qmU0h/VcCX+fRz7D8OxL7+qsJsHtMJo9s9bmYG3vS0KoNAdHSk87I60252SACXVjnRe0p6qduxlOJY00W6ujW5AFHOltiPF+nmWneE4ApTrG1mdzZpdzH+lm8U1ZRDw44w9XgLUpL7OFoGJelhM1zu2FzGV2psOfXFZ314dALjJIEj26MXEGH0+v71yAQwAnBQJENLQRg4gSOuCLqOnUVLgEg2DlCOoPjZOylKd3Pj7sOTlgTEPx0f2F+s20/ZczusD4xMppffj/7eVxfT3Yt8q6R055z+XUvoqSf9dSum195iHpJsGNGnlK46X0nTeMnoSK4LdVNIj/hEFVXc+gxFnz7iWR6ozmjuIj48RJ99KYsa2xIcRUC/AtaAXgc8djQMhAmoUgaV27VwMKHjQPGLdLGpJJdG+VAGDjMtm5nUHmUctS9hu1sV8+YlhZS7luKMVm1rVs1enq7S4DXVKPTAudyTkizaCbFBxm/QGLkV9MyGyLVvUUtkPuYh3hnwY+Wa786EFjoyS8bn9+TioCKpRv3u+dm+A9nTO+fVX7H9K0ivx/yvKNtp3SHqTJOWcfyGlNNWwuvs6xzb2YBhaEd/3JU3m68Eht/9CcH64yDZ2gsigbOdl32nIOK5TktYpvdM6jYmFOw6pv/dZb6MeskRZDM1LbaDB4EjB2DM2XVN39EOp+sHUx1T+P1ILZkxjcPFvqd66FPUs0t+jkvZxtcAkHGfwIVjd0aAfPK3qqkYgjsGGuIwk7mN5AcgI1Gkm7fUCDcsKUpQzIoBxQopu6xT/74ftUgs2JqUuy214qNr2jLQThMfYFxmA55BlqQM9i+dr230e2vskvSal9EUawOhbJH1bSPOrGta0viOl9Bs1nNEnNdyN9D+klP68hqDAayT946sKu3mGZiuNlSSN5y2Y0SlZkRZ3gAhoBDoCkt08z6J8nI47ofWKyLhI4xnWd35zpLVG5ltypPrcqhjF6i3jcCCCQCy1AYFx+J5KSi/W+vPHKPjTRXxUQ8+/VH1hQFwe4eMOVMHG2+x2HqlGKu+E4/fU6m/2pR0EuFPKJrgQ0AiQXBoyVtXMZiGdQfZxHGfX9o7a6xGuyfiZVpqgKzdTjaq7b8R7G8202TbC/1Jl6N7PiLcnLD8SaKZhfaXLk/pRbq577Gl2UW99vrYlDS3nfJlS+k5JP6nhTN6ec/5gSukHJL0/5/xuSd8j6S+llL5LA5z+wZxzlvTBlNKPaQggXEr6I1dFOKWbBjS8Od0Nl+etrEAWLf7uUXSOHd624o50VePSjYtgIrUgFHUKdjB3fkZknZ76jc0MjQyT7gOZWAQzA9wqytfRk9b0LF8cMqaZKkgwbS8aSlBw2mk4TqE+BrOeHsc8NrnBMXAQ9/s4U2EDVY81Rlf8sv2f68NoZtMEl9iOPeOkygcqsJ3dR9n/5uFYGtc4sRzXg2C6DdvyrU9lTdl7wrbvw+8PabjFsnfsn5X0Z69b1s0C2kJaPLseiJSq9r2vYfgZD6Yq7+2UWu2p5LcGOFILPieqTyJwJ3U4/0iVdEQwcj4RvKSWyflDPc46HaOcdF89lifImwMqIjtdl+aBiwQhDtpoZkBOe6SW2RlszHjInO4gjcIxBKVH1YKLzeB5hDy5NKTnbjr/6I56mxtiGtL5Yketznkfa3ULFSOWdC3dEQ/VSgBkcFHg5exrcCQYCvs5eUYZhPvNCOkxkClGEPM5bCMoIG0V0G7SbhTQLjU4xsQgqfUmx6Ma/JGEdVZav42F4OHZkODmcLaXTTC/o/J5MfK3TnGuKsDarYjiPjurgWyK407KPjM46yYGJhIZBhpsHnANmI3UjwiO1V41u15kO3b99jT4OREQY75Sny1FVmZg8wxBxkhBh0DkAMJV5fC4S3xTLffCXIOX74m7o3WAvyN9ZtmuAaOrOFNdWE3QicyNICRVpi2tB356EgODQtRVbO4TrpMHCx97RQB1ufbGt+Eq7m59up55eU2UrVaTjUGh2ag2+kMR19rDXPXJGFyjYx3Ei2RjAIEuq8uK4Xr+joDmejK450CAB47XEhkYYzm9mTAytpVb0QMdbycz8gAP7pWk6hoeodKRUVHTIjgQwOjrP6qWdUmV2fG4ZqpSBd5oV3VLszqmox5Idob9F8vaF3xtXR0CHAM3cXGt+xb71N3aktZjaAZQBrSYX4yYSesBLSH9tmzH0O5udM3ddryLJC+l1NObpDrDcSFqpOW0yHpiRNOznqn+SOvicHQvvD2GzHnz+UR9MKJ+Qh2OM7LBepOW0m2uS1WmEnUyZmBWNA0falsLHNsDxUu1zM5gFoEx6m9SC8QEzOhmxt9xqYa38ZvHTMP2UgYnOpK8Ef4noaTryPaM0b+otfLjfBg8mIdjojm9GZk/PC4ySE7Q23qnwPainDdqNwpoce2qx3IjOZxjEa1nzAMcEB+JTFHehRAkqHFIFVAmqi/UPVALlJ6FKfaTgjPaONX644k8s/s3X9M31+AVzTT42WQBHnA2RkknUut6URez9YT7sVoG1wsk+LcZGVnOJnbGaOg05OF8jlVHYc8lps7VY508X5uPcb4EPLNPRkRnVTPz5YjMxm11oDoP0Buwue/whSpuN4XjWB4tRtOZt9T2aXsYdHEVjjEYW7N5upPuXu1hfh7aNs03p/uhrPu+32ku5fMqNUnSeClNzof3zA6J1YKTgedM0qfK9xiZ0wX0eJupLm60xuXtXNhoF5ZivtTO5l5uQbITo5IGST/eeRY+Yw2en4HPA8KgNlUN+y9UWiuynx7LYYTTGUW3lCyHovqxKqAxP+dDMDOgRZfVrh+XaUgV1HgRCJi2CLT8TX0wdl8zVQPq01qxMzL1qItxgnL13A6RsfOGh+hyUmqwRQnDzy2LUXHX0TKF9d8IZuPOb0/g884leb6209DubklDe+5L2o8RovPWw3Of2I/LHmK0qTT4Yqn6VihGjMzmuH7HHdEzbnQnvbhxGY5jZPM6RnDz/wZhlkfaSs3GaVb1CLrQ6tuCf899I7j1RH8yPjI/R0Z6QYOe2yq1a9oii2RQwIDUq2cPpHsR3B6jiy6vt+FuAU5QfES3jbKGLQLOpvaPi2FjOgKPQZF5GtziU5ltMUhEqcRlbsvl3DG0u1tSmCCxTKI3IazSebactMcw0jQWMveBnkV503pJv+b3spMTEEfht+vDMD+PdzkUeAlqdiHJ9FgX500/fBXdXWpY9R6By4zE/3PfVSDWAxNpHUAIYrfC/49qPT+CyVVaGNOQXTFsR5CU+iwzAq6v0aPD8XuX0vRivZO5D5l58R0B1kccoPFEFwGrx/ik2m6MeRBUDURhXWbzcFH3Eeq2kQg4reWKm7+X8wVlNw5oq6VXS2lUmAqxKd6mJql2DHfISOsfU9upOOt5PPRE/APV24vYqZzeHhL1sHHIl24G9TOGca0BjtW+GeZQff2N4OvBtjqHi3Dvon/TDSN7skUXcor/qYF5/yKk7zG0RzUsATGI8IGNZnkESWp+LpOBBbq+BDhbDyQ3MVPXr5zT3vHwzlG6eVzjReGdQQOpvWvEwBF1MnZcqcoaTEdZw3KGdVouC3K/cR3iYms2LTU2M75t2M7lvLuZoXEFRAxqEndWgOY1O9aW2PEMSm5gR4diJ1VJa93OYr4f50xUlVpmFjvsEnnHKCjv9TPILVSZoMFtX1UbjMtIOLtb83N+Ky2tp4n1AMOuXoxUErxuheOmSBddywhseyE/aQCSOyXfWDZBl0/HJaCRafEcCaZSe4uTjb+dtw8vTI3Lfej+uS058ZGFsa3jgI/9xf3uFGmo09H19aTIvsq8qOH6dj/nQw8krmV8vraLct6bRWYdWVmjqccVBdQznIj6EyOG7LixEH7iccJ24X/WhTcK0130CTI/AnAM9fpkOXsbCHuazVhadwF9EAe+tHn5RGQ0BJPipq2xsR4zMpPquaqsS49FxejrXjjG+07xWyGdy6RC33NHwUD53gGpXdPFJTxsf7p1DDBEt4zAMwrbPJOzH19gG/u103swxLzZF9mndhrazQKarxNZvtcV9sCseXRXHNQEhbjd6amNME1cuBj1Ls/AnPFYFk9goRrFZL6uL5kA2VsU/0eqtzXtaRh082ULsPtOY0Zjd63XjB7oPdvkyj2q6t9GUItM8A62USii9tWLxhLAenpYD2x758h6PItzjboa8/kNWumNjxxL0+fWJ0MpPJxP9RY6amw2tqlZnVk5wYm6L5cFRVeF6y5jcMg2C2nHGrrCYTjmfmwHaNczkw4GDRmokTaAGRuPLIcdz0zpVthOEZ/gRlAyYDAK5W8vA4kLLD2jx1se6Io6D7IxGhlBHLzT52oUdgWoj3Y+ZFEe5MdaZy5R/LeRxUiVda1RQ60D5Uwte/L+GH3tMUUCGvNk/QjaMXpqMDvW+v2bBmhfn0dVXetzSU9L6Wnp0WNp/2K4to4+Sy074xKKqwY6NVQf67wshXjZB9c5Evicnu6oUC7/d1/1GjoC8f3Y7tan7dpSWILBjVLLzuItJ/H2g3hXwS21i2Vp1ECk6g5E8ZedyNuiizLW5o7fS7+yAjjfdSy9ail9ZynnP5L0KknvKI+f/p5npJdfSj/1Yekfflr6bV8g/cQ31+NXA9vrwCLg9NxAAlpPd4vfs/CbjIjHbrLIzK5ik7xns3y+6x9Kr8rSH9+XdEf6+qelVyylv1AOe4ukV5xLf/1p6bkkjcfSf/ol0n/0ypCXhncW6KJGMm10MZ3cQEIjuMzVZ1ZLDWB2rBoQ4MQ3DsfFPChbRBnCk3nM435sx9DubvTo/D8nAvcXBhSbDsGZKzKiperiWlO+qfq3I0U3khFG4Xjer0d/+EC1Y01VgxJ8XIxP9haOi9pZrJeB4Y1j6cfOpD9Wjjsuu8w43vsp6Ye+UPrNL5HOXiP9xX+r9WUTp6rvvySI+f/Ilq7qClGb4++eIO+8x1q/KyG6rvG4aK77Av9fSm98TPqxX5H++Euk5Vx6OkvPqV7PX5D0g2PpP3hUes2j0q/dkv7dD0pff7s8p5Iu8Z60fznMolO1Ajv7m7QeILL3wAg83VLndaH+wxLiRBqPo4dBt9XHcXws9IJ769NN280ytCTtlycaTOe1bSxNeBK0vj5dlr5SGn8kKbkR3dk4g1q7cCaOgDqSeYDMyZIINJ5pGXmaYt+05Pdi1Y44RRqpApUjUochjW+H4jELSeOz4dn5X52l77octn1Y0mslfXwsffpQun1b+qWZ9FtuD6uTf87T/bGqoG+X87hkfqR1N1FaF9rJljzge5FN2iYWR5C8pep+ep/XG9yrFQ3sq29L33Ui6XHpg0l67Z70saV0sj9c81/6jPRbbw1ApTvSF8ykz5P0yX8jHaXOOU6lPbjM42UrY/C0410lXsbBSBfFfy/PONHQJH4YKKPccYKm9kowc562yMi2FeXcMbRrmBtxMdyEvr8cXmk3mtc7jairsY1XMhdBpjd7nWvoMFO1GsZU68BjIzCNNHQmvxGZ+heXe3gJSKwgQZKvJ5vi+LioV8LMfiG9qGz/FQ3vvHnjWHrqkYF1PD6XXvdouSfMo8SAZsZxR+3tSx68eygwupxC2jtqhX4GDaLuFcV/2qOdsszDo961qSvGOpcyvyBJe1n61UvpvQvpq6bSU1n6hUekx0fS65bS/qQe84/PpItL6Ys/Vov1xLbnurq+d+qr89z+bCv2Ic7EZGMEH6fx/ZkztZOfJ1znP8PxXCsX18/FPidt73loD6uGVl5Y8POqQsbfyDn/6fKM8HdJeomkD0j6Aznn+KDivpGul5mAy66kdQ9udX058226RWWB/WRXk/C/baOmpda98P92JQ86dbJr6Xu8CGCTTn4+Ns6+/3tJ/0ADiP2JJD21L733VHp8Obhbq8H9GVUQk+oC100WXLduNJLTc1y+QYFenW/bVC3zo9bGGyJjWtqm6G3J66sPpPfOpPdeSt99KD01kt57IT2epDd6sdZM+tiF9AcupR/VcLlozYtkwrKR8UXbdm7fGIxim5JdSS0gRWbFyChdSG/vReR7+pmt13+fjz3kDO1c0tfmnO+klCaS/kFK6X+S9N2Sfijn/K6U0n+r4c0tf+GqjJTVehmL4aZ0T16nwybtq7ZdN4rNMCkjgLHDLFVf/mqjuxDXCrlQj7c40wrluuN6HzUHryHbZARAaim012sAs1+U9KWX0ivn0p87kx77jPSHXqLKwBy9eFbri2ePyv9mVjxZp5upsjup3s8ltav4yc7iejH/dh5Ob/BjGb3X2TGvTaAW630pvXE6ANovXkqvfZH0yiT9uSelxxbSH3rRUI/nRtLvfkb6s/vSV12sA8tC5blVM5RVzqO3dlFq82A70730ZYyr/H1zOpk7o6LuE05jMwOMmm7sw9tYh+Zz+Sy0uwJaeVmBp39DR5b0tapvb3mnpO/X3QBtKeWz1c+m/R3FNqAxsCj+7i17iLJOjDRYY/MZuLNEn9YUcab6tnMyKOskRl6+GIV1Y2eOszv1uZFa/KDg/BWS/t8aopvnkh47kY5H0gcvpL90pLpC3r38WO2dAgQUf1wQgeOOpI+Xk+LF7T24MYLOVb8f1UDe9zSArQH4Dj5kdVGrY53ZTX3Ol4OO9l89I33xvjR+RHrxVDr+VemDM+kvfal0kaXf91Hp//Ii6ZtSuUbBiVid8jX0PEocvX1xiYf7pvucGb0XX5pEjrTuqo5VX57D6OZS9RHhBMO187kPe9iXbaSUxhrcyn9H0o9I+mVJxzln98gndZc3GktDe5yEbZ6nqaNK7fX0OE9RWDNguNNEes9O4oikO5Eft+y8DFYzDQDS0ysYgCCz4tojdzzfyNxzDzbdNsMTfo2Gt8f/XtWb01+3lO6MpCc+I2lP+j88Lf3LS+nOUnrFL0t/+TdIX+/Haz+qdTCwxUjjsWokhdQhfnisrbh1DaC5/CO1zM2BAX64P9Yv/h9A83UH0tOX0rd9nlbrzF73uHTnWHriSPr/flT6+TvSpy6ld5TyflTSb9J69HJtfV2pUwQIsurmeLV6WdReDW6OiLLfSuvLOLiQmy4u+/xttROytL07Ba4nHr3g7FqAVl4d9eUppSNJf0vSl163gJTSmyW9WRreEtqb3NzWR+X/+Fa3MZlOjEjykbcGHUae3AEnajtNnJCpf7FijnQFzW9165M7dNRCpBbM1NlGRsbwvV2Kf43f+5Lesa8KEnvS3/8NJaPIjqaqkmdveUVkPD1RP6Yx4HF/BJoe8PD/cUjTs15UlUDpc7uUxlPpuX+vTfeOr9YKJH//F0m//6UaaNOTUv61yp6atUE8z2J+G3uczCKYcUKkWxotrlmKWpy3cRKV2oW37ptxuQ/rty17mBmaLed8nFL6WUlfJekopbRXWNortOGNxuW18G+TpN+cUmbg0e1/WD50M5t1gmRWFPh5o+5YdWY81jrlp/5hl/FCLUByxovUkcdLLcDGJ2ZI7TsV+YkirsdoD9zGSLO3r+Fl0nQjbRFICGYRQC43HKuQngEDAwbdWB4bff4Ios7jUVyAu7mcBOUp8jlSGwQh6LH+nrHs6h4Pb+g5Vu10+8KLZ0pdMkYymT6Ffor2bFNGr6V1gGP/4GS4DMc5QjbDb6lG1e2NuF72LqKb83ztYQ4KpJReKmlewOwRSV8n6Qcl/aykb9IQ6fx2ST9+t7zMZCkZuR33+erI2RAsWC3on2rogAdqqRspvVR1rWekxVwaeyYjULETcHnFkeq6tbHasKvd0MiuDGZexkEmF1E5Rqy8/0CbXzQ8kbQ3UgWSI/UBzQf0AEzhf7p4BI9pOCa6hXQ57c6OQ35S60beKb89IqedtKyL0xjMYr2mqi8V9hILnofr6bIBahdnw5ONn1Fti0Me6/pofQ0ZF0x6AvTiaqanK2gjI+NkZYuzuFR12mOcgp/OQk/BcgqXdGwL0B5ihvb5kt5ZdLSRpB/LOf9ESulDkt6VUvozkv6JpL98r4Wvota3NOjHh2XHiZQ+JU3OpUQRnxpEzxaSZgOYnUo6mEvjGEV0JzWgedadq0VYjydHLZ7T+pt+em4wy3K6qP05TW+BLeu7t6JnuACmcz1m1XMxr3LxYr7Om8fHNWT8nxTEZXOJhtR/d4CpM4MY0SKgErAWWgfS3jkigEDWY4YzDvXOy9bliy6mrTdBebv7A5l9DNWP1JaxwH7myTVrlDGlNgof16htwx5WhpZz/ucaYm5x+0ckveFeC3RfcLtPpQogntkKMCWu6Gd0yfTagOTtYFGNlGEQY8QoNvwtDSjop/H0aKRtX1UvM933b64totbXuwBTpNsrPZkuz2o5gTQwDrpWPpGonV0FEDbmY/bXe6Ci1AKJ1K4dc8MJ+2b4zWPuqLImPvixV0+7k5veHeB0Lo9gOcW+O3W/o4ZmWStWjLx7QSCCFYM/dDXIjty2FtWpdblpXQ7dxHFI42M3MXx6ENtmUw+zy7lN8xNrPT/fVnkruge2G9WDnRfVy60YRWJGE61cyfFEuj0v7I7HGGgouLpzMCBg95GMa4r97GieSf2+R7utBKzobrgeXpO0sr0SpSpsYa7hfZLjM2labotae59mFOoJViWv5p5JsrJH1b69KYLEVO2SDepqzutWKOc4lCNVcDnt1EVqu+EMn6natXSXYf+x6t3ezo9+oMuV9MhIeumySgpHkhIW3+qy1czIdqyvzpB1DMnHW5560VEeG5kVAUtqHwDqSdJleYnRLBw7Cnk8X9vdy3k98xNrjRUpMhjOVGxEqTZ+udtnUS74eKL2ibVFM0vsWHN8O2oZNQhqGDO1tyvFRY6srzsX627NjtGoBc7J+ZrpNeYmuWgJz1zSY8flHw9uqs88nv6J2UsU0QlmR2rdReZlBuc8LOZzO4X4O6qP4ibT4rE+JmpzLv9YrTvKi++RfKek+3hIH8Hc5T0qvWg2vNIuWZdEvpeeQLTuDloekFoNlsDm5TxXARqB0m3LPsklHO5zUXdjFN8skCzuBbiwNqX0Jkk/rKGGP5pzfmvY/0OSfnv597akz8s5H5V9Cw3LyyXpV3PO33BVWTcKaFI7vvO89C2zJzccFxcSKIrleR3nt+dS8povg8WBWlrPzhQtrvw/RT2i/hWFe56MGaPfwcn8zQDpxvKOBam4l/5nT6veymUnqzRxqcUi/M98Nrl2MQAg3f3+yljuprydF1mdAY1574X/e/vi+jAyRKMCAwC9wAgYYzKIBdZpkGDwhyyNfZPgReDrifPsu0ukcV8jQ+PkTvnCNu98XIbrt62nbWzJjS3a+49oCCY+Kel9KaV355w/tCou5+9C+j+qVuL6TM75y69b3o0DWlwKtn8u3T4vUtFttc9HlyqguB8uB2Y3KvuTZ0/q2u4Ep2ofzOdGIrDE9Ty82Z2iMIGtF91yGXSJfZzLWqgGNqKgLGl4o1MZkGkkjZa1vKmKi0Rm4UFt12+qltkwTQQiun7H4RiCijUt5iOtdx2zuQg+/FDgZ4PxnQbez7IIhrFM5hf1Np6jv50GgJsLGz5TW/0eWBGwZmEbo6HSev9yenvefGJt1MmkdVBxmSzX5Tj9tm5O3x5De4OkDxfNXSmld0n6Rkkf2pD+WyX96edb2I0Cml3zGNyZSjo8kw7ONCyijVqaw+Ru7NvS9FkcbB3tUMMboG6XzJ/V+iJaMi+7mlLLyqTWpYi3LXAmHasyTM/evD2Kx0lVY6M5XWRp+xd1pn5kpGEd2pHW9SzrTRz0kSHFQc1j/fvRUgZd1js4ptRrDTDpxjrNsSpzYvkK6Q3EDFK8RJXCHKtdvzBFeuex6RzV7rt0Q16UIEy5PqdqH1wSLUYT46xMYLLRDfSE57x8zEk4jv2PE6fU195YV7up22BW21228XJJH8X/T0r6yl7ClNKrJH2RpJ/B5mlK6f0aGvKtOee/fVVhDwTQ2D+klr3vLwdisi9pbP1CavWnaWF0dsWoRxnYVPYfqxXzSeMpzfCR3nR/Y4Qyup9mXV5q5U4VB4aPuSq83ri0e9LkoubZrEWT1pdQxAE8VQsiJc+myc18jkvaI7X3YJqdOdrYWxvG0WhAY6RS2MY6WMBnfqwfQXqm9tluZGWbHtEdQM4amau7v5RGF9V9NGuiZ2BWHdeiMQLKYxmVlyobZz+i20mQ8inH6DqNDI0aGgMD2wK069/69EQBHNvbymL652PfouFpPpwaXpVzfiql9MWSfial9Is551/elMGNu5zUUOmx0dzHJsvBJV3dWykcMFVtSDf0BN9keV4OYqE/PlmW4yq6rnHhrstjR52oPpmWgQ6CIcP9fnb9VC2INs8c3xteiLJvBmRXk0s1PHDptvU0JCL3JiE+sjV/LMIzPxtd3pg/2ZPr2AO1TcZzsE7Ic2a6eM4xzaU0vmgBy+zcQR0CVk+KiHqZVCWJJbaTYfGbHoD7i/uTZ3jXh2UqbCcz5CS6TUDzuV3Pns45v/6K/U9JeiX+f4U23FWkAdD+CDfknJ8q3x9JKf2cBn3thQFodO9JgqYasOZALT5daIhmPnJcDrIrKdVFrwtV6u6Z8kg1kjkp/3tJhUGNuhwX7t7WOqjZGJpfqOp9fvqBtH4rlM0AN1d96MOB6iqMvX2tD/IpvqdhHxkRn4yx1/n42OjDSFX3MuhIrZvZE/+jBhfrbQAmgJlpRTCOoBg1MOfPukdWGjU/fpdzTx1Qc1u63xBAuCyHackdRp0PGX7USdnnphrkEYMZXVdGW6V2Mnd0vrdsY6ztMbTtaWjvk/Sa8vzEpzSA1rfFRCmlL9XwaNNfwLYXSTrLOZ+nlJ6Q9EZJ/+VVhd0ooHnZRtTHPa7H5V610dnQx/yy9PFZIVVeFOlZbqyV/pG97szPIjJwGVh6zMsdYT+k4d0CDFJEQGMkahp+T7U+00vrQYNDFTCjuyatA5JHwkLrQEVG1AO0A7VuGStAUDGLcqiPbtsmdmYwYn3UqU/PPHX1AgyuB4Gp517zGNoUaRwEeKZ1+QwavfVgveUSXM5hc4fmjeNk6AREz95kb+5blgtHGvqwXcroxsYoKfvgNqOcWwK0nPNlSuk7Jf2khhq+Pef8wZTSD0h6f8753SXpt0h6V3lcme03SvqLKa2W2L+V0dGe3TigmbQQT6Yq68kOSrr58KhtBo/2Z2pnQOtRqss4xnNp/6QU4E4XXUfOnASz3ieuJZLaDmqAJSD6hOhKurNHveXAmdINZCTObiY1Jg/iMY6N31Gn6rllzqsHhJsYEN1dn5CNbmw8px5o0fiEXYIUNLC1c4isMW4jc8RxjESzgzHSSDAzO7oqQOR25zZqZgQHdnybV/y7LzFYRSNIFmaXS9R/Va8X4CO4c87vkfSesO37wv/f3znuvZJedy9l3SigjTUwsSgPTKX27UgX0nTeepdrtxNN6sHpRFK5DW8tGhQ1Na7ripqItzkCugjH9dwIl8dbpqypeOb2UxK85o4sb+wzJKB525EG1DPIeEU8B6vpqKOUBqmeyN4Dg71O+h6r6u2LQQm6rbGc3jaOWmp3zC/qdwTdCGDUADkRlLRs7yjIR61LWtfKFmE7GVd0R7ncI7KdUdg/D+kIlHP877JL/XiX3Gpyjo8Yfz62u/XpejYaSQelkbg4dkzmNZZ0II2X0mNOMA2fA1WGVnSv6Z2Slg1vVidVj4qdhCIedYql6q1MzpMuJAfFSOvASM3EPrVBmM8aX1kPRI40RBuPyv/Hah/BQOBz9HOG/+n+RRCMjMzurrQe1t3D78gUI+AQZPh/fIdAdGFjUILnZ+sxQILfTHWJhwHtqHyXPM2qKR3YesxJ2hwQkKqr56CT3VcvzSATdBm8G8DLRWao1wL5+rRjvUpdU+yfU/WX692r7W59uqaZos2GZRfTMzBbUn13EvqnPW0LYn6KnYaaw6mqFrbAsS7XHcnHRro9VfsgSYfuN0W4pPrEWkZQmVcDaAQBJ7Ky+ITqgP/4cPGat4RTgL9Uy9aombmnP6p2PRtd0p71XD6ClbW2c9U3rkew2gRSMc0dtaDma0Ewi+I/87gzfC6X0p6P97WZtUI73cerNLPlhmOk9u4U94uZ2onNp8Kou/edqM5PVols8d5ms8Cl2iVGvkSeNF+Atz7dpN0soFlEswYgMGh3BgNK1Cr8bTfOusW5WoZF1zQuko3ahN1DRp8Ujovhe28niLHzxzw4w3t7BL7Vc8Mi8vUijLaonUWAieyFzyTzcZF1SW15BI1YzgzfsU60GM2U2mBCZGb+xDdXTbXZrrpOYV9cVhFZNcErupEKad2WZHDLkI6gOA375mrvTuBSILK0qKfFaCqBNTLM52MP+fPQtmvoOMaEi6W0f6YKIIwmsVFJx29rIASm9T6GbI5rwTj7uhxqZD7OMx3X9LiTbNI73KFZV5blc/NixSmOP5P06Qvp4BPDi4Ob9VsW5vbUMqwIMj1QisK+mZjzZ+RTSEtXLnYPuoyMQiocR+PN5HeQdor03kcw6+lj1MXieeLcVreQMa1qu7id4uJZYrMt6lpxQexIA9MiQNqljVppBEfm4zT0SsjM2Pc8D/kYPmB0x9Bu0Iz8pWFMyiRpvhyWa7BfjDVELr2cY80FleosR7Ag0YkzcWRocdlGXENmYHU5saG59segNsK3b4PyiXqm9gmeqMo/0+Vw/9ftM2nvjmogwG7knqqmtqf1Z5gRoQloZH9HGp76+gQu0lXuoI1ML6aP3YgXiQzsNKSzdkd3Mx5L/e+01N1A5fSXyI80yPUqDHhysT5BGkxcRQILQYhRT6fn5OZJ0n2Jk54DRD1bdD5SOyn7EllrW6iysaI5rySabTG0HaBdw3xLxcUQFHB/kNa9QbfLvsrN656V3DkIbnx891T1efF0HaX18CqXgBAIfZO8j3FnsuArHEuXpcfQKK7GMnnbzT7KWGi4uXXvaa3rRRZsyFboAkZm5v08wUfxO7Ky6L6xi/gxQDPsu0p767mTPfYXAfJywz4LqJFVsi49/a5s3wegSZWlS7WdOSfg1s/Ga4ir9X0clh51A0W8JW7e2Ucw4hISl8eJkdF+N2UvqPF8bedyXsMcPZmv30GyyTyJ7nNBqgd+1NY8W7GBY6eJLkRcUHtVtIu3qPBzt040D2n9zcWdF9jmzx4ZitQHnvgR0kbX1LbpWAKjR7bziYAZy4luIIX+O2rdSLurrFuvjjznGJS4G6h1rge1UgIUxX5PmBHovFaMC6x7Oq/Ushu37VgtAT0rHwNc9BRiYCtKi73+O9L2XmO3i3Jew3yhlutgRolL2CYVYjWXxmYzJ2qDAoxQWgejQLqJofkYp6fuxtk5amc8Ni7A5UDoAR3ZZc8VaY7ZBBZSDSREm244bobjTtVqWBT4SQOQz3f9lPSq29Iff+2w6+t/Qnrl49KP/gfD/9/zs9Jje9KP/2tpuZTml9IffbX0h1+q9n7QWB/WubeP+91QdFV53FXdeU/a25emFy3LopswDt8GsxMNT25hlJRLJnqLar3Sn2xupgqWftqGZQy7jQeq6xal9sXXJyWvGPUnoO1czhu0Amh53o+ax/WvNk+iY0oxblACFGc4dgpmyEL3kTbqZv7udXyXx5B9LGsS0hKxx510vACrtD3GMQvfTkcXlK9/i8eYNd1Sy5jMmrw/aG9vfJn0Y780ANpyLD19Lj33jFbR0vd+VPrBr5He8hXSrZl052nptf+T9A2SvqDHwV0fs0AHKMgEWYex2re49wAsuq2d67R3KU2W9frHCLS/6eo9q+GNUa5uZPOcPKX15TzOx3KFAc4AxfWKh6r9eq6hSbxe7aTkaZ23N7HuggI3bBtmEGKDjdd07D/uKHx0ynLDAXQHe8EBdwTqbUzDjujfcTEjj6cbKrUMjNFW6jTeR1SPT7NdAx763tLVWlbMh+I+ty/URhrDMV/9Mum7fmbY9MFPSa99ifSxM+nTJ9LtR6Rfelr6rS+T9vOQ/vxsYGo6VzvKNtWz5yL7mwDdAzGDFieAqNttCHpE0T8yZi6UPdf62rMYZODiXQYduNiWjM2Lw62hMaLut42dlG8/pcWus/N3EEJ6wT2x9qbtZgGtRP9Sofxc7TCVtO/OUpZMjCNAccFtDJM7M3cUN3pcrsE8SdMNltY73Dkp/PLRMlG7iBpZPG/bpoWd0X1IvAE0Cve2qB1F0bynLcV9PQbXOe4LjqS9kfSrnx7Y2Fe9VHrqVPqFX5Yef0R63UsGMPvop6Xf/W7pw89K/68vlr7gReqzrngedh+dxg0VHwDJ9HG5hzppStl8RZ01MKm+ci7e3iStsxS2k98bwSUfkZFZM1uGT5QwCJruO5ZWTjREwOPTdA2kzsdjZ1vMasfQrmGm1SoiPzbvj1Qj8gQUJxjjeIOaO4jBJr4fU2pnXa4RmpRjbmFffKhdjHDS5ZyqvpylB2CbwvQUgVlHu78Hkvb9z6WqVnYVg5niYP+WWgA0KES9iqDQS49yv/o3SO/9teHz3V8iPZWk935EevyW9MaXDPm88hHpn/+H0q89I/3en5G+6ZXSy/yOwDvIf5PGFxkiwZoRXWuBd/Ap9Y/v14y/DST7YTulhjiZup0PNKx88e1O1sFO1fZZRk1pcYmG+8OZBtfWwGggO9EK3HIh1asXAJkxUv/dhpi/Cwpc03ynwH5LisZSK+hzcS1Zz1h1wiZI8f68qYZOwRmLsxlpvqm+tD5zC9tdBl1F1ycGBe5mHDQ+N672nkgt6Hhwk75J6wDnfRbMpbszNIIDmeBU63YpvfHzpfd+TPrFZ6TXTqVXZunPfXwIBvyh/01b3he8WHrtE9LfP5e+6TGtr/x3vVwXgh11gavA7Fj1dqeLdk0YgcxZzkP2vu7c1zNPOGMNQGbx3v0l6mFkblyewfzYZ9wvHY+50ABux1o9R2sxr9lMzosT70nczG6kuy8nvKZ9lhK0ra1auedS06Q6SBOpdfl6nSBGFNlZqU/ZYmTTnXwWPlHT8LaorbhDM/RKbS3OvL1OLBzL7fyk2CSbemhvGUNcytA71tsjM+sJ6kGz++qXSD/xUenF+9I4Dd/HF9IvfHrY9+Sp9JmSz6fPpX/wcel/+5jWGWX8HcvzxYiamev9KUlPl8+d4SUnbEeK6JHpnKqduHoBnRgE4oQT07IfsJ8xL4NUnMRiXmZ6/i5yRwbYjoXXP3KtpJ+EvAXty0HO63xeaPZAopx2+Q4W0u1lGcMLtSsGpBqJ9EJXz3y2Rc1rxZZ84zo7H8GMb5uOLM7pvZTDeh6flGu8OSvpKRQTWPk7usD+JjvzNbhYSvt31DKyXrTT1gsIRICYhn0z/GY+NOpqZd/rHpGenknf9ipsO5LuPCM98bj0009L3/N3pZSknKU/8Rul1z2q1m2OZfWQv+Puaqb6Hs5f1wqM+a4AP8mVIn58SKL7iV3O6P5xbWCc2LgMiJMfF8VaU2WaE5THvhI1t7hUaDHklUbAXfdNPrzB57lFhPksjQncMKC5kaXVWE1o0PxsK5slA5TUDvroGjLi5HU8XB8UhVp3RM9ydCUpzntsuTwCqjUTzpZ0Gzdpa/zt48g6Z+VC7c+07mZK/UW0vX1ME7+pl1Fbu0v+46n03O9TAzTv+Pfq/1/3aumfvxplRG1uUzS2F9ygm2lm9qykX5cuP1EjfrYorpvl8CXQbhfKEFLLyCLrjmvUfGoGT+73s+/2VfVYA5rN+13uAr/jo42oyfh/a7dHqsBswJxrK1HOz+JlaNcHtPLC0PdLeirn/HvKM8LfpeGhXR+Q9Adyzle/K8azHpcouGPNKs6obN6fa3hWmhvL05RnVHZSg4M1tn2kl9qZmJ1opnVA8z6pAo+B1ZHOJY5lpMm4sPaIIFiMivL6+AqOlsOaqY0WGVjPTfSJGRy5nMFvN+8thyAAcmm61Gp0VwFUBMWx+gwtljnWOhjbjzwePieqEyOvYYwkeg0XwWCBbxsDBTECSTmP/Uaqi2fJ4rjkxv3EeXFe4uRHhuY+sEQ6ehDGevc198eVZKGt2OcCQ/tjkn5Jw6sdJOkHJf1QzvldKaX/VtJ3SPoLV+aQ1YambfP69E33z31peCx3T7dwwghoBDYztCjiE0jcYf2bgGLRlzMw84zrltxxPVNHFmCLeh9vobEb7IG1Z5bDNVZRzLeRyV2qPt12T/Xmdlps+gg2XM6xwLbopnIZxiykYxR2Fo5TSMtlFn62mm2h6mJetO3CJFeJOwYVRwIZELoIx9EF7eliUh/82NeiXuZy/KIMGyOtUTuO8gT7rWd/g6q0tVufOAw+2+xagJZSeoWk3y3pz0r67pRSkvS1qm9veaek79ddAC1rkIjGS2k0X9e/vT515WqaaRnU3EncsHHtFgFwgnTCPo95alvsULZpSMtjWB61ubiOqWdc6MsyL5Cnyr6LC2nyTLlQj6phWfm56mocPiPtuVJ00czMpFaTcjpuV2c/3UbbrHNMz82Nut+e1sHQ+fGJtlflcaeNYNp629yHKMz7NiMz+QO17cDJJYJatLiejAu9pXaypWxxqhag2N6xrKj9Ub89VsviPJHuGNq17L+W9J+ovqztJZKOc87ueU9qeEPylYZ70wdbhtueDDp8lVxkc1KrP/VecsIOQAbljkyQs7kDU8w9VV2gSxC9rfpEj4WGzkW3gZ3aZdMiqyNQm9mxHqOldPBc6awFbKzNmF08caz2Hsdjta7mASqwSaC/ah9ZFNMYMAlIdGOjO8wy/P+zaiKv+axek+Q3YhUgj+BCIIvak7Uqvh7OwHZbLWDEfOJC29iGBDw+tCCC6lTDpXfAi5oKb2HyxEhXmjII15mdDHrzrJzi2P1xqq0A2kOtoaWUfo+kT+ScP5BS+pp7LSCl9GZJb5bat41K7bhPkf04yhg7W7TeLUfRfGwU6xnx8iCQ1vOxMMuP175GFzrWkzN+ZGfeHtdHcTv1k0cADFHAzmdSsnsamZX1NLqBcZmGtLk7kIW5MSLrom63qRzn1WNvyMMDfyRpegEt8bJOOnHRdZxEuMYsBoikCm7WsHoLbK199Prepm1xQjNTZFtJfTmitwwpas2lfsbluaTHqPduiaE9tICm4eWe35BS+l0ahvBjkn5Y0lFKaa+wtFdow9uQy2vh3yZJvyWlzHacCi5mZFjSumhuo3vgTmvAYMeNHcyFmlQ4/+hycvbs6XELtS5GT/fwvl7HdToOHJtZm4+na/OI2dFlzYN3SzzytFYoe1kquHdH7Ut/e2yJ3wwymDLcUX38D6Ojm6KtphvMl3YVcAYbe3vZx0g12bOvZ9QmOQExykmWHNeRSa0kwe387UAQo5FO42+W35vc2PdiMMDLlQjahXlGB2Sb9ll8K+fdAS3n/L2SvleSCkP7Eznn/zil9NclfZOGSOe3S/rxu+XlPrJiY9E9lPpsx0DFxvfs6k7NjsXWoPzDMqOoT2Dy2jfT+Finuer0SACKwMdjNvW+uI1qrOvkZQCXywGg8rIdcCOf54U0vmgHxm0zHK4/c8BAqgBpgHIkNIr0M62DlyOXkan5+zykIWiy6zHNVJqc1c3JVBiAZveNWqb7ByeDET4T1SdZsH+wPX15KHkwHQMBnqzI+t2HXQcyLrYVzWDqJSbu14eqL62iS7octu2PpMWydB+uBNjSso0Yc/lssftZh/YnJb0rpfRnJP0TSX/52ke6ge1W2rhAkbMYwSeKtRRceYzz4xNm6SoyasR6SevCv/Pyd2RQPtYuivf5E8+xx+cJxpzhl/ieSZpiNJLNLtQ+4drXciq17mKMkE6RASOLTk9tzLaHY8j4FjjW33tIN8V2pgkXxNdi5Pqhm5KhUSboGSe3KMD7uhpQqF9N8G2gJKOKo50Bq4XayVdaX0AdWdk5frtPuw/6nlEstPW+6VkhB2SbW3rR8MPscq4s5/xzkn6u/P6IpDfcy/ELDRPhdF4CAIxGRvfQDbivtjNGWs/1QnH29SJLdshNLqCpPSm+82d5cdmFgZL1I1ug7rZJ0KbGF90Rp4tLFejixOgc67lmmyKS0joD49INIW1vzVpkcWRl43AMo5kz9UGTacu+y4tWQ+NCWp8vF6fyIYvxutzNp4raJj2DGJhlmQZZtllk8mbQDFRweZDNa+l8jPuyJE2k5PmHILlbWHtzttBwF96BpJdYP+aA5wPwCFi+/YgzchzsBAZSdLsS1DmiAMFFi5xF40tRGOmMgi2JDt0SHufz8XnGQeVz7bndXGvUc5mjGE1X/MpbowwkZEI9wNq0CJcjm1HOI9U3S/XK5cMk+Y1I5lIDiI0/MWw7USshXKjeFB6vmdv+NFwbqc1fApMNx1NXM5Oahc8mod/sz/WIz0gjkEEbW+Uz1xCo9iQd+zldUWH7lhjaNjW0lNKbNOjuY0k/mnN+a9j/Q5J+e/n3tqTPyzkflX3fLulPlX1/Juf8zqvKulFAm0t6pnzfXkqPRFHcWpHdp6IXrK0dY9TKFl0Bd5pT1fsuCUbsfLz9iMBzijyb9SU4dqx6b91YdTkFw+8cFK4rjdE0p4va3lh14Eb9UUjL/PYlpdtaX5QbNTXrZlHrUvh/qrpAMIKSAelSdZnFo6pvqaKre6r6lnMAYQYD83lH3ZTt4UnnTOsAP1Nt+wj0zN/bOZEZKBkwIDvzJMk6GhSp9/pOBS7ZMCgREH1pKYW4/j2JIrJ+140SyH3YNhlaucPoRyR9nYblXe9LKb075/yhVXk5fxfS/1FJX1F+v1jSn5b0+lKtD5RjP72pvBsFNN8oMFW57tQ3eh3Yje3fdOt6LqhnM3ZEj7mx6ns87QJI68zJ+Xp29ZjnAl/nEYE2upW9pQBSv7fY1TRLix2TbnMEZO+nrUL9PdE+upy9iCd/e7Rdal1n4+cOjrkM+UQgPdYK0C6XfRZFZhRu2G7awcdR8ySjcd+JkWobJzP3DQMX83BdnlO9R9TGvhE9BE9wkfHN1E5SBkWWT0bqcrwG08GAktdiub0H1m7R5XyDpA8XiUoppXdJ+kZJH9qQ/ls1gJgkfb2kn845P1OO/WlJb5L0VzcVdqOAlhS0dq6v4fKE0qnysty87tmKLuqBKkjF9WrslNK6+E8m55abqR2rXIzpvLlExPWaqK5w9IBwmfFDQIpGNyjqc75WkSFGdyMGVSS1OtUefvc0qzh6pHVAY+a9ZRsELQJcFJ9KurysDMPWC6JEF97ygds6BneWqq6brxvdNLOfKPB7m4FokyYZGV483gz/WINbwuAUdcCrGBX786ZyC/A9t9ysQt6rbTnK+XJJH8X/T0r6yl7ClNKrJH2RpJ+54tiXX1XYjQLanqQXqyyyv6XqpkktIypXc3Vr1Ez1aZ5TtS+TiKDIPOLMHXWSKKRLrQjrPAgsMVjgcskgpXVdjoBEoy4SBzbdS2p1k87xZDgUzfc3AcuszBhAAj+KpwGPC2l0Ie0/Vx5r5HVt1tJ6C2UvNYzkPQ0Nx+0cdnvS4qKyEU8avE5mIWyvHgtzG03xm+3qfmOQE76jd2DZ4KTs96N6JsiLE1ePoRPMPjk80yzFl/EIefC7Y4ty7qPz8gj78n8+G4o4VvtWvPu1e/Bcn0gpvR//v62sPX0+9i2S/kbO+XkTxBsFtLGqVLxiWA4GUKOIHXeugeYbkA5V14j11qdZhCUgWFOKCxptM3zH2Z7rmRSOo4sbb8OKz2WjDud6x2BI7/x9vJecUDuJARG7ZN52udRwk7vUANoloisMLBBcyASmGt7o/uhMQys+qs3AZveTSzWi64ltBhHfz0rdNFrUDM2ae4ESAgcnQTN+59HT6qx9TbT+Hgs/A8/1ia4s++Gx9Nx82PzYuertfVLbp3g+PFezUOHBGnNpvBjmIxPJY63HsJ6v3aPL+XTO+fVX7H9K7U1CGxfhawC0PxKO/Zpw7M9dVZkbdzlXer47Unz+lLS+RoyMQ6oD252egqu1DkY0p1q/yd3G33ZfCEoRFOM6N2ld7I8zLafNyD58byk67qpOvSUm3heFYA5qLhlxBVctfdlqVgQzPnUiRppd3/1lYWoxgBABbYZvqQW2oN25zeZav9XI52LmHEHrquvjfhPXNnof9TGXFQGO7MnsznVge8frCCK8xpp6DJLny3FQyhot21POQXZ0078A32L3PkmvKY8be0oDaH1bTJRS+lJJL5L0C9j8k5L+85TSi8r/v1Nlkf8mu1FAk+o42+cTX6V+54nunV0uCnGe2RlJYkdjWuYfWQ1Z1EQ1chndVB8fAddg4OM3RdK8zXUyOHNwkaFxRp+pHbC8KZpAG+82kAbX0f9HN5WD0eX6WtA9W40gAxXBzEGAqdbBLN6NoJqGwNOL6JExSev34vKcfW6eHHx9mM9IQ587VvsASF4bX4e4JjGCna9dnBRdVqnLpIDR2NHnKBn4XCLyjbW6ZSpJmmB/Gg0gN9VAPEflexsDepu3PuWcL1NK36kBnMaS3p5z/mBK6QckvT/n/O6S9FskvSvnnHHsMyml/0wDKErSDzhAsMluFNDs0cwl3Z5L02eKrkAAi5qT1ALagfAiAg2dybw7RsGsWXgQ3C166PIPNIh9RyWPpdaffhrXi3kgnGv9ceGs/6zkv1R1mx19tevlMqj7SG0on7c3xXVU0vozvlw+mUkUtT2AyEZcf7KcvJSSwYrRTDK2O3UZxvgCr+UDg/O7AGI9bWbw1rM8kfSCQL52Np8nxXhKGKeqfSaW6WtFsI9l9QR9gpn7yqi+92f1gpVpOF9qn2SL7F8jyJ2l3DQemuslC+nFy7rKaRu2RYamnPN7JL0nbPu+8P/3bzj27ZLeft2yHghDW6oKmNPz8go7aV385oMS6QqykzFox4hW1LDcQa8yalxT1c7njsoXF5EVkWWQhbmO0bVxGbdV14wZTPY752Eg9jkazBZqBzhdGYroHMwcmDaDOgVuqdXz1lgR3cq44Lbsa8D5ovhDBdAMZlxlT6NGaJDgJLUpbY9FxeBPlCdodK97kyqDRRGUqAMbXCfS2NeXnoJd1igz9CaZheqi2yW2Oc3tAdzG0qA136d9rt7Lec9mDc228hCWal8qHJ9z5k5JrckuiDtmHBAEnLhMInZ0GwdB/Pg2GqeJSwvsznBmJ4i4HtFV9UB1GZtAlwMm9rZ4nlFfoivVc7VZr+gSmfFK7QCX1Ar8dkELWJ2qjVxKBdTKUg3qni7D7THvfKKr7X5AsOLkEYGM+fS0Mv9m/lJlw7xdKWq2MTDFfsUgEANTBOoot3DCVvgdvQy2/SZd8R5td+vTNW2k+pjB7gVjQ5GNkVFYL4suGgTUtYZFQK8BJantPASNs1K+F3WeqA5Qs7ZbSO8Z2WyLb58iyJn1TTr5eu0b68t69dzIeM5RT7N5ANkimK0YIvzXR0plPGhX+0u3aVzGC2l5UdvEtx1JWEmtYfayaB7fVuTorCcsgjdZjScBAl1Pg6Kb7HrxGNuss4/leekcF/mynegyKuQRo6HhTgC/GGg8UX1oqPNgfXpMM/aFuV6Qtz7dpN08oI1qhKZh+x681IUiI/Dsd4JjpPUZLubJD2dQMiUCp9chSVVL8gAT0trNNMiOcVJ+BBFBlO60ByADGeygdrc5eKNuc9WM3LtuNs7m1KVGUnUfiz0yG1RtSdoz2JXlH65fXM1PQDOIkwFeqL19KLq1BJiLsG+hNpAUwYnbYrCDEyA11Xmoj59s7OOttxH0ei6t1DKmeJ2jC3tW1+4+Ni9eCkGYQQ1aRJvzK/Y9D9sxtOvaWNIjw8LA8WxYASCVNqTbE10nz9zSevRqHNJH9jJR23l7kTR2fHdQz8IEQbu9kTVtcjMmWp9VOTDJ7iIzWPnjqE9vANs4yKJRq4mMYc3C6v+8aYRc1vPnTds+J08A1C/plkVXUvgd00mtWxfTxU8EyHiebBNfm8hgWSdPaL2FXr1rHoNMdrvJvpbDYlt6yM38VOqTC1g1jwkKS4fyvFZjSwRtB2jXspGG591eDL/HjBrG6CaFT3Zc3gNni+u1lthGTYidvsduosYV8+d+g4zBjBpJDFzE5QOsz6aBZODcdEN7dDV6v52PtA78vbwWKoLmc/X/Rthf1odwXS7bO5lIt7l05W7rxnqRQpfduzYEkAiSdGOjcO7znqjN278ZKWb7GKjJ4JzXOKRnHX0NuMyEjHBRNwlJVuczkxbnVZrdX5Y0ZNQa0i3VqjD3a7ugwHXNi2UYXvcAZ1SRmhOBw+DRE4qltoNP8N2LZbPlqSFZ+4oAe4D0rg+BysfGlxzbnfFyCw5wAmdP9+sNZhojdfshPc+P6938PwetdalYzoVaN/tAZbX9sj0vsiif/77qaOS17BmZVfwdGdBFZx91O7MosuQIAgvVpT6+djF6SjmA325DXxP3Lwr9ZvO3VZfm+Brbx1wMj54/mJfqegIrk0M+GwKWJOnTpeqdBuiPi/Mh21Nt717OHUO7jnEWpGtgVmOGI60L+Aaw2KGldgCSMY1VGSGF6avqF8GMwr5n/dh5pXapiXug09hd4cA3K3VZPffvOu5lBP4ICr7mHgB036V2cuhdcyw/WB3n39SUeK187Cq6id89MI9lUzuje0gXcRGOiw9c9PX1sa6360D2JQ3Ac6C68HYePlz3RyOgxaCFJwFrqZQqStvsF025acPzobvwidwr9cRpvRFxGGPlNmwXFLgXi2IpjSF5GzUTHt9zY8hsot4SB5H3xRmX4Mq1cR6IPbeO52QgGGl9eYI63wbSoI2sBQFi3QnsdptcPpnqGPunIX0csASJ6JZFpkPBnhMBr4FQB9bd582lOAQzups99ta7Dr3r5PMcaz0f10H43XPNyfI5Wca+0TNOxmR6qO9qwWxJu5i3wV/OLZN5eQINjHPnC/DxQTdqNwtoWf3OKrV0nuL+WH0AZNSMA9nRSaaNUSjnx0WSnmXdeaeq7qeNzCAu1HWdL9QubmTPpJbiARFfqMyyKLT7ONsy/CbzWnZ+07V0WgYfYg+O2qUHpNSCOycAPj2Fg9TnwzoZBOO5cODT3YvXmukZBCDb9flFzew8pHU9zlVB3vtvq+0jvibez4eD+rxdrpetOFJ+onrLlUX/Zak+rgHniaiqjCUdnKlOHvPtg89D/danrdpSVePwQGfkMeo4dM04ExrErH3YnTLVl2qnpHH2NSOIjDACDQc9XTO6NGQ2Z53y7aayDrzB/iCcnzUeRwopzEvrA8jbogDO/fOwbYlv1zGCFCcEAo2ZnvUhus4chcw7rsinQC+kI5BRF1s9agL1i2aAihqbWZ8DBq7X7VC2l5kwvwP8jky2F0DyNup0ZLzlGvoxcL1LRbVgXy0HWGpgafunWq2HjPPlNmzH0K5jfmSt1LqPS60/AVRqO4xb2R2Za7rMDNjp+IgXsiqygjigozvi+nGW7zEF5qFSdi8AwO9J2Oe6cR0TdZ7obkcg64Ec6+i8OOX33CtuG+FD13YS0kcNcBE+UYOKYEQgczqXRV1MaoX73nm6fd0HFmo1tovOMbFtI/NymT732A8iKnmCnGv1dFsvrWDynjLibOKpschTSfvuY2U8uQtt42kbuyjndY3ajT/uIKDfI5WXD1Nf8YDcV9upvDyAs/dU/YFuWymsWndXCXKsd0/DscUe6UFDtiDUfZP2Z7D3wlOL02SudgWjG07GEJmDr7vdbLtPFPIJTJFlUcuL15Vg4DQGJrqOTsM2sgB/qnadlxmt03F08dxiO2y6rrHtOPEo7NvEeIXjRp3juI/M81z6zLyeQg/LI8Pi5e/ZUoPONl5Ii2Xt/ptiS/dqOw3tusYrRQGZHV8FzPhUgjNpcad6Hau7cw5VW9Pug92E2EvY4QwKHtAelMeqbg4jbnGAb2Jra4uKQrq56mxPl4v+BG8Lek6VncXyo45EMIoBjLmqKxwBO0ZxKZ6TIQnpuASEYMV2jEEF1tv6pCerY9Vr7/37agMz8XpHZh1HssuLGqavt935KDUQ3J2/+0SPmcWADwMIJ8N2FzNGkugM8ElFcS7xZaM3O5M0WraxH+kF+Ty0G7WbBzS6Op6lJekU42yiqs+UweiwtDQsg7p9Jj3izsj1VQa3KGhzoEatSGpvXzpVCxrs3FIrVktV7CD74iw+w3F0HSdq2Rd1s8hspNrDIyi5lzPqRteakTWCHSlB1AM5WM2qGTDxpMDInVkWl89EVjvSMOG47Weqz5Beqk50lhGsZRIgo2vKNo5AT3bJNilPk12BaHzUlNs2BieYj8/fk04ExHH7yoT4eDUbh0MaDayLp6nOcY7tkDizavdju6DAvdgmty0aB9mkeqgkSPtzaezewie/RpfIzGeivjhNwPDgneFD15aDnczFNuqklyowMcrKenpwmAmwJwv59K5fz9VahG9GQWM6n4//t95kcF1R486xHnkGM0TwGgrSAxWpzlRcp3eI8/LnFupl8IplELDpgrNMXyszYQYCIkOllme2R+Qgk6UEYrDvGLtEPMVocR5w+khOvV3aMbQHx9A8xZgRna97iasOcjCwselZoOB2s6Km4k7JDjdSHWxRxzJ4+ji7PHGgS20Hj63uQcZnmrE+Qn7s2Rzczjf6IHZDyRzITHpsxefPaB3ZCPN2fmRBHvBmhWSUzD9G/mIAI4IamaonjdPwPwM9lAliVJouJ91G0pd4fsKx/vY+BpaYxudMdss8CbSIaqbR4FHw1N2tI6lfqrIzdoWe/a8JODuGdg+2etipZzxpCD3Pa39adRIPxsclHUrpYmBkY3dQD1SCE10M5+Ny7F5QmJ7it9QuFaGIvkkXczlmdVI/kjbFca6H8z5QOwDpNlpnG2t92YHvgDBIeTB6QLl8Lg2h1udzcTQwAhoBYKL+khQa3a04AcS7GAgEZGfU7ejyk9lKLYvydbDfZu2V4OM+R0Dm7WK98zcYW1LoTVA8D/ZL1XM4WLanZpuq6MHjIQrKLIjBtBi3UEizrYW10ZH5bLFrAVpK6VdU76y4zDm/vrzV+K9JerWkX5H0zVe90di2LH9G51Katy97aPx/A55By4BjF8UzOtkZXQKCWewZHuQeKHG67DGLCGBL7IvLPzjgmZdndX+EdPshPcVzsswljmXPjqzSI8cD/LZa4IwDkbpdpAYcyNaLPMhZDz5hmNeqx3xieVILeAa0GLXlZHcRjh2HT2TB3Ee9UcjDdYws/qoQIr0BTn6lU+8XXYxdZsWAyrlFxSE2AYm31CoI7HrbetrG5wJD++0556fx/1sk/b2c81tTSm8p///JqzJwkJP9JI1Kmy7LOhoCADtkFOajPuVOT5eCwjQHIdkZhWBbFCk4GDiTxx5G34H7o9satR3W2QOxtz6MxnP3ILQbH6kAr4OPjSzJQEUG6OvFb6fZxzeN9eTymJ6eZRAio3M7E3R93c9VdTpGonkdSS0YOHB9GAwyk2P7MDJMAIv17j02yvXmJFfac7qsasQFssvzWlUCWQSrnnFucrV2tz49f/tG1XfmvVPSz+kagGZLYYZMPRfGA9RPbhirdujnNPSAqVp2xhk3irUHqjchm7Fw+UDk+R6E8RFE0YUyg4y3YTk9AdERXDIxp48K8EztQPI+bhuprlvjQCJInqrqX/H6xJuuI4sxkyWYu+zIWuK59vLb5K4aGM2WeR6+zicaIqKfUstAeb3ijBknRvcXSwA+bo60FLHI2k2LPHmwPObHtirnlDQ8WUMaupy07tn38DGaMdK/o4S3DSD6XAC0LOmnUkpZ0l8sb0Z+Wc75Y2X/r0t62XULHUk1NG92RGZGcDlT20Gfk3QsXdwpeHZeNDVrRHQV6BqOS3kv1fA2J5Y9V13zZcdaqkBmoKB76x7Y027o6tK9vK3hbVIGU/bkHuujIO7t+2p7vevigEfPLTpBXXmN4mDnOfq2ssdUR2BvtT2N7mDMj6OY7NPlRJbq/KTaF44lfbJ8qB+a4fVuS2Lf4XU9UAuWC+TB8/GE5WN9Dfh8NGpsC3zTJtJ4NDyZdrFsg8jRUw0e65UgF4fLtlzFh93l/G0556dSSp8n6adTSv+SO3POuYDdmqWU3izpzdLw+uQosTQsyMaOZhfAHa24HafYfHA+LOFoBH52KjMELwg1mFmXY7kUpCNg2RbhwzJYf/Y04cQZieu5gb5IsYfSZbLZxWHaKP5TcN+kHdEIOFzTFnU/HhsX0jodI5BOH8GG7R+BwCA1Cx8zcl4/T4BkY711d1cZAwGcTCJDZ7vSpR6r+pSR+ZbrOi5t5eoyjuDvKOPGKkZi7Eu/LZdzftdUL0y7FqDlnJ8q359IKf0tSW+Q9PGU0ufnnD+WUvp8SZ/YcOzbJL1Nkn5LAb25pH27DNS/bFGEj51f7RheagiNT89K1IhAZJZl8PC6I/cAAwdnXgYXqIFxhrfRTaGbFHtiZHc8/8gkOUBodm38Oz7yh0ySbIzmwRrrz/r6nEeqwRfX3cc4DTUlPoGY5+w2ofYUlW+OaNaJbNhRb09IPoauI3U1AhHzOVV91+cpjnfaKDVE4CSrc3p/L8P/Pn9c47xc91pHap2GXjGcGzg/+CEhI23vXs6H1uVMKR1IGuWcT8rv3ynpByS9W9K3S3pr+f7x6xToPjVbarilSW37r9g7H6tDDasM0sl5u4TJZOL2UnrsTMMLJ+yGOp+ZBnflWdVbp3xXwXMloyj2kp1xlqbrRxHD/wvHsGPbrTWgLTtpqV25B3uJQezdEUyklolyQAu/owATXTVrbgb5SBnoIhOoostFdkgqQeCxu7Yp8EHWeqjq2vMc/C3kyaUWZN/HarW4saqe2ot2C3lE8O/VtxcYKeecz9vbdHnIvtYD0c42uqVMw4ft7hbW3t1eJulvpbR6S+z/kHP+Oyml90n6sZTSd0j6t5K++W4ZGfnZt6J0Ypx58bmUzLLYsUqHm5wPmzze3N/d6Ic83t/uzCrbjkphY9U3o1PzotvAqdHMzm6wb5uK+h01JB9rcZsDxt+MvsVlA1LLIMygPCrovvqcDehxuicQWAvqRTfPkaanv/VU7agpOO2mZSFx6YevHetoIBmrttdC9fE8UdfztYwBFLf/sQYwe0aVzfPDyKyPjXqbLU4UTh8BEW4m+z5JNdUAZrWJRHuf568eqX8+9lAvrM05f0TSb+5s/5Sk33Evhdk358RvouI+KNVA1JiuFKercf9dJB7ns5LHPgd41Leia8A1TWRFPbeNbiEtaib+7uk3vSkwojLZWHRLXU8f14vwjUL6TeWb4fG4ZUi7ULtgVVoPftCNZl35LDJPFmSYC/zP82W+Lpf6Y1xKEd1E+mXUvYgodHmNDJw42O/4zYmP1zKmcx1KecTz6E7GU6UR2HjaJPRj7Rjajd4pULzMVf9247oPUhpZSMNboazh+AqXQWMSQoISJ9UVcBm8zOnZ6bz63f9zjZqjkXbdNnVWuzaTsD1qeFHljTO+XT+4KE2wJPYyajaRTVik2Vdb7wjGdK8o0nDU+NlbDCrwHCJgkD6YbkQAYV1PkVc8TwL5JGyLEVoCUtQsCbxSfcLuUnUpj++2YP2Zt691LyhA9z9OQIt6k7qTczK+UA2un2pd/uwVx+Pt2Uy1nQG9bQ0tpfQmST+soao/mnN+ayfNN0v6/lL8P8s5f1vZvpD0iyXZr+acv+Gqsm4U0OxtcXZyHzxUlUfcF/NcSieqLQrRPU2kaWlhyz1SHatLqdVrJqpvZXKHswDnA92LDGLu6OzQHiAuWDguuoljtfdNEijc+R3mcp5WeFkfAhABJ0YffZEd5PDgoyupUJ+lWk3K+RLQmG8sf4R9ptxmZY+pTgTRlbeZqrudOVnYD/O1sI7IPOm6UjckiEYw3Vd5e1XJm20dmTHZuusVz/UWjjvX6p0AlCel9oVinEvdXCda74Le7yUerj4nf/+/TZdzftdU17OU0ljSj0j6OklPSnpfSundOecPIc1rJH2vpDfmnD9dVlPYPpNz/vLrlnfjDG2G/91Pb2u4XfMxaXidl7Raq6OltH+mYa1Z0JvGI+n2ee333VmFAoTZl9Suc7M7RWZ2qEFjmyKfqP9ILfuKfgK3E6ml9eiu60lkjoEBD8ClhtHBekQNyksHNgUo/Ntgz9uWqPctkMcmfSCyQ6c/Rbooyjj/ZUl3rPYVdG5Ua4E8N7p6Zk2cVLwcX+U73v4Wo8AEQp4LAZAubkGqi+UQXU9wnfO8kmM+fGSioX87Kzarm/0CxdkrdhNaKpTa+ccg6UuwLZdzixraGyR9uEhXSim9S8Oi/A8hzf9V0o/41smcc3fFxHXswbz1SW3/O1AZF1i173vfVsRhqeFlq4G9pLH0yGzYx74+kdbdJ6kdDGQDcVBEYZ4ihnCcVNlWRFSKHDyeA6zHrqKIEl1Znkd0b5bhI7V1prvIa0l9LIIs3Shp/ZpS1aYuxnOJDLP3PwNABp0YjHC9/B2PV6e+vEYR1EYaOmCMpEe3l4z+VPoMXMj9ZT02TYY1kUtVTz16x64uwc1gtgy/fTq8f9952OxkTPSCvPXp5ZI+iv+flPSVIc2XSFJK6f+n4dS+P+f8d8q+aUrp/RpeOfrWnPPfvqqwGwc0eyr2xAxmj3TAhwTB42S6LI1JJjHS8BSOuVaPahkzbERhdtnJmGyIjCMOip7ZBY3p6KZyZj9Rda8icDqfnpbE8mxkTvOwj4C9CMfM1bpQ/s2687zIunjOZkeMqgr7fH1djgGEYGa9YaH2qcMMyMTIqtuFrjGpTgRyAjRnvPghM/V5+BhGSE9aMrnP6zgZ+uFBqYfZmpMI2XsydxVNLK2SnKrtru5KHCrEWkuv27B7ALQnCuDY3lbWnt6L7Ul6jYZbKV8h6edTSq/LOR9LelVZ1P/Fkn4mpfSLOedfviqjG7Ok2k8PBNmCs2WwqJtPpfVolm08vLNw7Bkzsqy4ViQOnKgt8ZlYcYbndoolnIb90En3tDMNN4l9sqR7TMOimCO1vTH2JgYUXDeC33XCYzbqirZJSC9VMJjj4/wXqrcycULwfgs+1Bc2MS26wDFSSWbK6+x8qbFxP4HUx/uciCac9HrpXceZhmUez0p6RjpdVla06o/uS54MZtLB8eCWunpcWeNirGgYzOyqHqt1M02kY2DbTeMqb+vN6ffgcj6dc379Ffuf0nCTkO0VZRvtSUn/KOc8l/RvUkr/WgPAvQ+L+j+SUvo5SV8h6YUDaOxDU4FJSWvMhBM5/19Zbxqh+8iFlR74Xj7A9ARTduwrolYNwFF0ZpqRWhA91rD26ZOqTONxlEdRpRdt9DcjdxHxaQRA6k0cBXTBvF9hO82RV+dxrgpu1L4I8NG9jHqfXT6pBQfWy/WJEwfN6jknLJ/vVddpGdKwbs7TgYuzNpi7Muq7Lnsy3GscLwOrQU+dRN7fLucq75tV3pb2tUWX832SXpNS+iINQPYtkr4tpPnbkr5V0v8npfSEBhf0IymlF0k6yzmfl+1vlPRfXlXYjQMamf3KqPeUK+mGo8eWCH6eunor+9navK+u1/qe1T19RncvHks3JOppHKwUzu2fHKtOvQsNFNX5TVVd1Ek4nmwpMhUyQqd3GjJNn4NBltHWRcjHZmAx0DFq6LQLrbMkskCfzybAIADEUe9vt4vP+RRpXb6Bx+68Ql50yxmZlVom6eOc95naxceYbFfdMXoBYIo9ZiW18x+7nYtmnGKi6s24qLgqZRNWPx9zntuwnPNlSuk7Jf2khqq/Pef8wZTSD0h6f8753WXf70wpfUjDafzfc86fSil9taS/mFJyq72V0dGe3biGRt9/LrVgVmwiKZU1QWPT+H21g/l4/WWtY9UngEplhxe89QYfP3Z7DYI+vjdQCSb2nx1Hd33ZwT3DH6v6EWRKS+RF988WQczhMw8e9vgxts1wfATfeG706SmO+7wMIvRzLPTwnEeq98X63CIQxpFHoOuNJDKlYw2uH699BLRZyCe60S6Hk1fsSKRLBrSSnl7GvnD+RSNdnLVeMaOScR1yj9j7tNw8BxqIvE9VOMb5ON8X4sLanPN7JL0nbPs+/M6Svrt8mOa9kl53L2XdKKBxnEv9wOCKaExUH11joFho1WEvllU0tU1Vwuje4MHkwmPMnGJ3FCR8g3pPqzJAkVl50a59A57gsYZ7RT3YIkvxo3CiDkMgJZCdlfxYB4jSDfuQWsDwHQF26chwTYm5hIELcw0aBNgTlGvX3dfK187g6usStTHWsceSPTEZsMxwXV+fM9kU0cJl7uMY1tHila8NwZntAHa2cv2Cr7g4q7eIOk5i5cOYSDCL3cH531Zd3mZAO9T6vG65sOfNP197qG992rYR1Eiz/T1Refgjo47+bYCa1PT0NEeCW+r0kYu7d/lgah901UZqW5UuaAwxSRUYyG44WGPAwOmo60XE50CKH/oaY62Dga3nwnngEzClFnCiYOnrOkUZkWHyvJmv6+lzFLbzXBXyok8Wn9LhY8mm47XqPbwyutpkvryekemX653D9c3L4VHy0pCH5x1Xa4oseFlY3RiMdV/2POW1ZrxMPh3iuvTCZGg3aQ8kytkzY9bqJcO9KKa04uP78+ERRItl7YPjkdpnsHhRpWdeurcuh6zIg/FUbeePzE6qDE9qnxhrVuaBz1g7I4HMwyEzDy72Xvd819uC/BT74qjx+fk6uEwO3t4g5rIJf/sczYSONFAGM9X4yCCCUAQmfqTNoya2OdNRFfekY/RgG9qinuaye89v66ULTJkYbm/04GQ4bjFfl+PIwuwa9m5t5aQepdilBkLOyxLnMDsgu8cH3aA5KBBtoqJ9UYfi7SQejFIdeAUMxnNpTPHZepbtbOhoC0mT+bCsY1XoodolEx7kjES4wnYnR6oDmsc8g31z1Vum7LoadHwO/jZjcl4crD0w57FkkRbvrwI0qepQz+AcVPI6Ur03R1rXlaaq78w81/raAqkFs96o4CjkaHQZvt69sJ9H7YH6T811Hd1fKBnE8qmJ2ihQ8VxKujxvyaaTXCyl8bImdTVddepn9mzjzQsGsp7o77mDysBUbXfg5bpfe+gf8LgtM6CxP6v8Xuk1PWYWZ1C3pkHAA3uieoOxtGrhhricl/cXmJ2ZDfZ0F1fOoMCeSoZ2qlZbIhhGwKHL4nrSbfI5UnU2uHH69oc9j6G0XhBAqrTiBHWWhmvqa+DboTjg+WZx14ujMrrXdxNh6DZG1hqBnOdBphyZIMWkyIKjRkd21qNFgWn6NXO8tCTkJKjj8P8F0s613v95elEHo1R5UrZ53uYyjn1tD9Bc789Gu/GgAFciMDw8mUv7HmBmN5tAjdYToEPUjfR8rIHVrbQr358yC/lI7YxtIKBOFqNhZgUWUngjPAcdXTpOtRaonbeZpnU/9liu9Hcd6S4xGMJtPReL9aCoL7XuHF3HnpgjpCWwTPBhHaNeJpRLTbNXb5bdM1KWCJYXYb/Uygksq1yL2MVssfqxy0YySr2M5JlzFIrtqgOuIssy0d3WrU+7oMA1LKm9N5zLimYabjRfvR/gSK0LQmNHf07Kd2pUKfkYDPjxZMjTHWw0l5JdLwOMActAEHUaMxq7ZHaJe3XzsoWo5XB69zR7pKqHuQyzPLPWaO75BjqOMgMq3bSoN1lpNsiYednll9ZvKLTW57x8vS7Uun/UHQ1okUpwFMcoIu8V4mTQY1m2TRNfBM3A3JuoVPQKwDz9oAQ3iy+ZtL4MknMC40acz2i+DHRMrLdZomRzssnj6iKe0v3ajqFdx0YD4IxL67jRlqoPRT2U9NIzad8DTGoZAMGsMKFj1YZ/0Yna+zGLGzrWAGTu4+MzVVYU/WDqT+xhnhapvTFSygHKQR4HIQf6oeoCW4OggfMCxzIY4TJtBP0YtfN+jpaRhiUxDlQchmsmHEtz4MPnRM3RdfP3BN++nvvYTmAk7SBCRO0rsl0C0SKkY14LpPM5Uhq4as3Dss3Gl2wSDuWljoRVSOtqbyKPpciVm8nL2wtCRylxG4C2Y2jXNfBharLuKBu15NhZ4Q7EMHozo0sNw0mqoJaXUjKAkAXRJaROZUbi/daZyJYocPfYRE8j8+jwNEt3z+WyB0cGYuMoIf21tkjWSprhRyVxXVoMjLBsR2RdP9p1RkEPeOhWEth7gpTblhOW68jjrb6TKRMxWD5ZJfeXztnrYrFYetjuEmxSIb1QJC+hf3M+IlBu0sk4JLb15vQdQ7uG5Sx9Zr6+WsABx8fK9yMegNLVA3gipUelozuQtriEwZmjt6VZZYgNeDjPOGt7W0Ra5j1VfVofWQmtxyqo55hRULuJ7hZ7cxRj/DGA7eM4urukGFHXclleihE1vp6rR4GSZbGedoPJymKUOGqYritZ7QJp3OD0wUxrrGFY85TaDjcv6Z5DOQdqEaXID4tlSzi9Oy7PYFcZY1tkcjY3DQMLvlzOn104RjWjNrdN20U5r2mXGu5aoUxiMHuppMf8DzWqyG6kVmyeSumoPJOqN5DcGyg0eD9/R2DouSDsscx3roHp+Gmz9EmkFpAmYb9vzTKjIFARcHsMzdsjQDli6XN2mM3LQshICUJmoafI2/kzPUcawYQvIuZ5xGtv4LFmuYmVbbqWRBMD77LU+1PI276i6zpDHifD5GpcfORMzSNi83lL8i39nWrow87KHnsMzvMSCfuoGBjIIknl3BnlzaiARCViG7Zbh3ZNW6pOimvsbKLhUTqOcMYIWI+RuMNTUPAgiYKH3Tr2IpvTbtJSLM6795PZENyE/z0C3HuXIb3r47q6R4/UjgwyC9fVF1NqWSLdsIPy22yLQQIa9T6OKl4XjkS6cLy2jIp6oZXZotSCkgMyFomYngo5gdT15rnEcKOB8hmt2JUPTSNVljgbHgF0ovrwkOVSun1nSLdYttWZaLi3eDwfjptpwM2xBinVyyIjYEUcJ6HlJXa8hYSS894t1VceUK/r2W5h7Q1bJD/uu80UJq3rTzZGrsjtaTwu3hrjD/ONIEndhmkIGmQKUex3eTy2B4SuH7UcgtlI6wAWjb6HR6frwqd3kOlF19V3UjhiyWtL1zeuBl2oLk3hsg6uwvf156OcDGJ2b+nDkXLw3Hp+HCOpUuPCXixr8sbm9UW/13XXkvvEUqsFtD59d4vVA0pLplG2s/EBjr3u6NNnd4nPO6CRAI/1gnwE943ajQKaZ7TYT/elOk1FDckHUmyPLg1v6Ob9JFJ9B+ZC0pmUz9pZMBFg6Ea5LJu5v41LPJg2BiVWJ6jaQwnaPE+WYTZEgIkiTWRuMTpoFsg8I/uLPo7rQTrhIAHD0o5aUo+kuT1tBPOeyk4G2bv1K9bfSDJVV1t0ksRrXs4nSZrO23jJVOUJL+OBiXmZz1j1OF6eg3LckYp38Xgp+2QA08iiSMIt0ZmVGRgP1dad3Z6gFxfo9oDufmzH0O6hsBerxZ3VbDeXxs+qApDU6lWMwhVgIqYl9oDorpVZmYE/68D7zmCEcmJAgszJPfNYlVXFW7Uiq6Ci2wsWUKy3q3iB702hrqgtCWWOQxr2+nguM6SxWBPTlAmh0boCUDQW87Wu57RRafe5xnV3MWjDa8Cni9hKfcZSe2dDmAQeORuAa1GyGduvK3mMR6rBI9VjfSr+fqnKn0OtAJ+n7stvefJYdX3ZqWoXOlB9ApSrybkmqi89SXmkHUO7+XVo0zoDetZZ6dfzlnAlCwhh4Oaz9jl+Iw2uwGTZzrSa1/vvSPN9TGPuEVdFEs3vHSXzAD3EcXYfvYBVWmdmzJ89x+dLQI8WGVr8jqDZc8ujWx99LwY8eD4xPO0gA0dYvH6ROUY6wXNZdn7zvKIGOQ5pFPYTnFmnkn5/UZbvRBbndDFwhEuzYnW3VW+jK5NQjFuYlEZ2xmDyWBXUpHbeIBvbZNtkaVn9W2U/G+zm16HNBzZ2qva+ZpKjuYpHE4MBxThOfGy3QUftTxKgiQqr2yRO8Hgjon+fqC4NcKU5aOwSc8mCK94DNjMWg0d0tzsDq9G2evWPkVuuQfP+qFD3wKI3mghCBvWeGGRQJEsaafNTDp0nQdbXhua0jM5aB2REm0ELn7MnGn+49iG64M4H5Y+XHdLr63c+REcpCboZGEzmabD5TFql6knMO8fReh78/dpuYe01bZml0/n6Ax/c926rfVH5mkiP1ue4aXQQduBReGSRXRCK05HLe6BH1/U5tcsM2MMIeBTGpepGnagi6m2cD/OghhgFEoIIAcEX4SCk8bWy3mXmR/DjNGyw3Q9pDFbRRYw6nFkcwcQW/SlfQ04MBC+CNWe6kdbBLgYfePtWb7IiQC1KP1pKo7MywWlgbav+taxPT/bhk3mtRj6T0qdKHU+Hfu2Yhy+Pze4tq94Dqqi3RfcypuUx2wKinYZ2DVuqagiflPRxVa/lUK2WvTIKBB0zqWjALAKgB9ih6huzZ6pLB8iK6ANYn7mQ9KyUn2lloYnKvaNcWCe1z/D3wLU+tXaCanulEd7/RzfYg9fRQWn9tiKnM9WV1pnkUm096K7SvfbJ+ps9nRHnOKLYFpypPMIdYPBaBbrozive2UAA43VgPQ/UstAFfvN7UaOdKxDooMFU0tgMt4CttTXrYtM79ZQ85/WAyE1pEnmG/XEec5dyPr27BGJTSC/I93LeqD2QN6f76TWeoN3vTaCai0kwC4Pb/+4LYEZ3ib7BLbX3YFLQ2BSpo8g/q+s1DaBjSWOyhXj/JvUn21R1PVu8OFR/CS7Mkz2ei6V6QCNsZ2CDoGfKYBa2YeJY1SlqXptEHupdZogU8HvsiqySLJPl0lXliDeY2c10/iNtXLjlyxSJqtTGOsZSw/ojWfYpuTr0hIW0fq5B9GSJufSAmUfP82adnce2bn3auZzXtNiPKU31pKKVgR2MwubVxl6Lc0B4ULtX9Z5ksancRTv2Ih41FpdwRHDZZJtAYaz1fGLvv47RleaouhuQ+VhpfRTGcyIgU6OMwBRF9+sawS5eX9aVwHiFRQJ3ZfLosmu9z7Jam/K7wuHYmPdVaa4q6/nYZ/OtT2l44coNFZbSJyX9W0lPSHr6xgq+u+3qc7W90OojvfDq9EKpz6tyzi+9nwxSSn9Hw/lcx57OOb/pfsrbpt0ooK0KTen9d3nb8o3arj5X2wutPtILr04vtPp8rtp1mO/OdraznX1W2A7QdraznT009qAA7W0PqNxNtqvP1fZCq4/0wqvTC60+n5P2QDS0ne1sZzv7X8N2LufOdrazh8ZuFNBSSm9KKf2rlNKHU0pvucmyUYe3p5Q+kVL6F9j24pTST6eU/pfy/aIbrM8rU0o/m1L6UErpgymlP/Yg65RSmqaU/nFK6Z+V+vw/y/YvSin9o9J2fy2ldJ1VfNus1zil9E9SSj/xoOuTUvqVlNIvppT+aUrp/WXbA+tDO6t2Y4CWUhpL+hFJ/ydJXybpW1NKX3ZT5cPeISmum3mLpL+Xc36NpL9X/r8pu5T0PTnnL5P0WyX9kXJdHlSdziV9bc75N0v6cklvSin9Vkk/KOmHcs7/jqRPS/qOG6qP7Y9J+iX8/6Dr89tzzl+OpRoPsg/trNhNMrQ3SPpwzvkjOecLSe+S9I03WL4kKef88xrui6d9o6R3lt/vlPR7b7A+H8s5/8/l94mGQfvyB1WnPFi5O3F1M1mW9LWS/sZN10eSUkqvkPS7Jf1o+T89yPpssAfWh3ZW7SYB7eWSPor/nyzbXgj2spzzx8rvX9fwdoMbt5TSqyV9haR/9CDrVNy7fyrpE5J+WtIvSzrOOV+WJDfddv+1pP9E9W6glzzg+mRJP5VS+kBK6c1l2wuiD32u243fy/lCt5xzTindeOg3pfSopL8p6Y/nnJ8bSMiDqVPOeSHpy1NKR5L+lqQvvamyo6WUfo+kT+ScP5BS+poHVY9gvy3n/FRK6fMk/XRK6V9y54PqQzu7WYb2lKRX4v9XlG0vBPt4SunzJal8f+ImC08pTTSA2X+fc/4fXwh1kqSc87Gkn5X0VZKOUkqeAG+y7d4o6RtSSr+iQab4Wkk//ADro5zzU+X7ExoA/w16AbTXzm4W0N4n6TUlOrUv6VskvfsGy7/K3i3p28vvb5f04zdVcNGD/rKkX8o5//kHXaeU0ksLM1NK6RFJX6dB1/tZSd900/XJOX9vzvkVOedXa+gzP5Nz/o8fVH1SSgcppUP/lvQ7Jf0LPcA+tDNYzvnGPpJ+l6R/rUGT+U9vsmzU4a9K+piGJ6Q8qSE69hINkan/RdLflfTiG6zPb9OgyfxzSf+0fH7Xg6qTpP+dpH9S6vMvJH1f2f7Fkv6xpA9L+uuSbj2AtvsaST/xIOtTyv1n5fNB9+MH2Yd2n/rZ3Smws53t7KGx3Z0CO9vZzh4a2wHazna2s4fGdoC2s53t7KGxHaDtbGc7e2hsB2g729nOHhrbAdrOdrazh8Z2gLazne3sobEdoO1sZzt7aOz/D66kuuj+A0OLAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(acc_image, cmap='hot', interpolation='gaussian')\n",
"plt.colorbar()\n",
"\n",
"plt.annotate(\"W1\", [(image_size - 1) / freq, image_size / freq], color='r')\n",
"plt.annotate(\"W2\", [(image_size + 1) / freq, image_size / freq], color='r')\n",
"plt.annotate(\"W3\", [image_size / freq, (image_size + sqrt(3)/2.) / freq], color='r');"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7944426f",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "cat",
"language": "python",
"name": "cat"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.8"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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